From 52e5e0801a102b46eb967c28be016e5356710b6e Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 21 Mar 2024 18:44:38 +0000 Subject: [PATCH 01/64] mini changes fixed policy scripts --- scripts/fixed_policy_opt.py | 9 ++++++++- scripts/tune_fixed_policies.sh | 12 ++++++------ 2 files changed, 14 insertions(+), 7 deletions(-) diff --git a/scripts/fixed_policy_opt.py b/scripts/fixed_policy_opt.py index 893b73a..a70ef16 100644 --- a/scripts/fixed_policy_opt.py +++ b/scripts/fixed_policy_opt.py @@ -4,12 +4,17 @@ parser.add_argument("-p", "--policy", choices = ["msy", "esc", "cr"], help="Policy to be tuned", type=str) parser.add_argument("-v", "--verbose", help="Verbosity of tuning method", type=bool) parser.add_argument("-o", "--opt-algo", choices=["gp", "gbrt"], help="Optimization algo used") +parser.add_argument("-ncalls", "--n-calls", help="Number of objective function calls used by optimizing algo", type=int) args = parser.parse_args() from huggingface_hub import hf_hub_download, HfApi, login + import numpy as np + +from skopt import dump from skopt.space import Real from skopt.utils import use_named_args + from stable_baselines3.common.evaluation import evaluate_policy from stable_baselines3.common.monitor import Monitor @@ -84,11 +89,13 @@ def cr_fn(**params): # optimize -results = opt_algo(opt_fn, space, n_calls=300, verbose=args.verbose, n_jobs=-1) +results = opt_algo(opt_fn, space, n_calls=args.n_calls, verbose=args.verbose, n_jobs=-1) print( + "\n\n" f"{args.policy}-{args.opt_algo} results: " f"opt args = {[eval(f'{r:.4f}') for r in results.x]}, " f"rew={results.fun:.4f}" + "\n\n" ) # save diff --git a/scripts/tune_fixed_policies.sh b/scripts/tune_fixed_policies.sh index 1f20b4c..cf7c407 100644 --- a/scripts/tune_fixed_policies.sh +++ b/scripts/tune_fixed_policies.sh @@ -5,11 +5,11 @@ scriptdir="$(dirname "$0")" cd "$scriptdir" # gp -python fixed_policy_opt.py -p msy -v True -o gp & -python fixed_policy_opt.py -p esc -v True -o gp & -python fixed_policy_opt.py -p cr -v True -o gp & +python fixed_policy_opt.py -p msy -v True -o gp -nc 100 & +python fixed_policy_opt.py -p esc -v True -o gp -nc 100 & +python fixed_policy_opt.py -p cr -v True -o gp -nc 100 & # gbrt -python fixed_policy_opt.py -p msy -v True -o gbrt & -python fixed_policy_opt.py -p esc -v True -o gbrt & -python fixed_policy_opt.py -p cr -v True -o gbrt & \ No newline at end of file +python fixed_policy_opt.py -p msy -v True -o gbrt -nc 100 & +python fixed_policy_opt.py -p esc -v True -o gbrt -nc 100 & +python fixed_policy_opt.py -p cr -v True -o gbrt -nc 100 & \ No newline at end of file From 1bdbeabe256ed775f08017671561edff88971586 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 21 Mar 2024 18:50:01 +0000 Subject: [PATCH 02/64] refactored hf login --- scripts/fixed_policy_opt.py | 6 ++---- scripts/hf_login.py | 2 ++ scripts/tune_fixed_policies.sh | 3 +++ 3 files changed, 7 insertions(+), 4 deletions(-) create mode 100644 scripts/hf_login.py diff --git a/scripts/fixed_policy_opt.py b/scripts/fixed_policy_opt.py index a70ef16..179a074 100644 --- a/scripts/fixed_policy_opt.py +++ b/scripts/fixed_policy_opt.py @@ -20,10 +20,6 @@ from rl4fisheries import AsmEnv -# hf login -# api = HfApi() -# login() - # optimization algo if args.opt_algo == "gp": from skopt import gp_minimize @@ -103,6 +99,8 @@ def cr_fn(**params): fname = f"{args.policy}_{args.opt_algo}.pkl" dump(results, path+fname) +# hf +api = HfApi() api.upload_file( path_or_fileobj=path+fname, path_in_repo="sb3/rl4fisheries/"+fname, diff --git a/scripts/hf_login.py b/scripts/hf_login.py new file mode 100644 index 0000000..0f808ce --- /dev/null +++ b/scripts/hf_login.py @@ -0,0 +1,2 @@ +from huggingface_hub import login +login() \ No newline at end of file diff --git a/scripts/tune_fixed_policies.sh b/scripts/tune_fixed_policies.sh index cf7c407..8e90fa2 100644 --- a/scripts/tune_fixed_policies.sh +++ b/scripts/tune_fixed_policies.sh @@ -4,6 +4,9 @@ scriptdir="$(dirname "$0")" cd "$scriptdir" +# hf +python login.py + # gp python fixed_policy_opt.py -p msy -v True -o gp -nc 100 & python fixed_policy_opt.py -p esc -v True -o gp -nc 100 & From c4f47d2b1712c80e1852b8459147e473300f5ea6 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 21 Mar 2024 18:57:07 +0000 Subject: [PATCH 03/64] typo, expanding opt space --- scripts/fixed_policy_opt.py | 6 +++--- scripts/tune_fixed_policies.sh | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/scripts/fixed_policy_opt.py b/scripts/fixed_policy_opt.py index 179a074..5caa900 100644 --- a/scripts/fixed_policy_opt.py +++ b/scripts/fixed_policy_opt.py @@ -41,12 +41,12 @@ # optimizing space -msy_space = [Real(0.002, 0.25, name='mortality')] -esc_space = [Real(0.02, 0.15, name='escapement')] +msy_space = [Real(0.0002, 0.5, name='mortality')] +esc_space = [Real(0.0002, 0.25, name='escapement')] cr_space = [ Real(0.00001, 1, name='radius'), Real(0.00001, np.pi/4.00001, name='theta'), - Real(0, 0.2, name='y2') + Real(0, 0.4, name='y2') ] space = {'msy':msy_space, 'esc':esc_space, 'cr':cr_space}[args.policy] diff --git a/scripts/tune_fixed_policies.sh b/scripts/tune_fixed_policies.sh index 8e90fa2..9d0c2df 100644 --- a/scripts/tune_fixed_policies.sh +++ b/scripts/tune_fixed_policies.sh @@ -5,7 +5,7 @@ scriptdir="$(dirname "$0")" cd "$scriptdir" # hf -python login.py +python hf_login.py # gp python fixed_policy_opt.py -p msy -v True -o gp -nc 100 & From 49bd134ff0a748f0750d049bc584d0e9c5df7e61 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 21 Mar 2024 19:12:44 +0000 Subject: [PATCH 04/64] added new hyperpar files --- hyperpars/ppo-asm.yml | 12 ++++++++++++ hyperpars/tqc-asm.yml | 14 ++++++++++++++ 2 files changed, 26 insertions(+) create mode 100644 hyperpars/ppo-asm.yml create mode 100644 hyperpars/tqc-asm.yml diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml new file mode 100644 index 0000000..3541906 --- /dev/null +++ b/hyperpars/ppo-asm.yml @@ -0,0 +1,12 @@ +# stable-baselines3 configuration + +algo: "PPO" +env_id: "AsmEnv" +n_envs: 12 +tensorboard: "../../../logs" +total_timesteps: 20000000 +config: {} +use_sde: True +id: "2obs" +repo: "cboettig/rl-ecology" +save_path: "../saved_agents" \ No newline at end of file diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml new file mode 100644 index 0000000..7335609 --- /dev/null +++ b/hyperpars/tqc-asm.yml @@ -0,0 +1,14 @@ +# stable-baselines3 configuration + +algo: "TQC" +env_id: "AsmEnv" +n_envs: 12 +tensorboard: "../../../logs" +total_timesteps: 6000000 +config: {"learning_rate": 0.0001, + "learning_starts": 1000, + } +use_sde: True +id: "2obs" +repo: "cboettig/rl-ecology" +save_path: "../saved_agents" From 34187ebea5b684b6875cf30785723f0c39a18720 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 21 Mar 2024 23:51:08 +0000 Subject: [PATCH 05/64] small fixes --- src/rl4fisheries/agents/common.py | 35 ++++++++++++++++++++++++++++++- src/rl4fisheries/envs/asm_env.py | 14 +++++++------ 2 files changed, 42 insertions(+), 7 deletions(-) diff --git a/src/rl4fisheries/agents/common.py b/src/rl4fisheries/agents/common.py index b7522c0..db38982 100644 --- a/src/rl4fisheries/agents/common.py +++ b/src/rl4fisheries/agents/common.py @@ -1,10 +1,43 @@ import numpy as np +from typing import List, Text, Optional def isVecObs(obs, env): + if np.sum(np.shape(obs)) == 0: + # scalar + return False + shp = env.observation_space.shape if ( (shp != np.shape(obs)) and (np.shape(obs[0]) == shp) # quick n dirty, possibly prone to bugs tho ): + # deal with the possibility of a VecEnv observation return True - return False \ No newline at end of file + # + else: + return False + +def simulate_ep(env, agent, other_vars: Optional[List[Text]] = []): + simulation = { + 't': [], + 'obs': [], + 'act': [], + 'rew': [], + **{var_name: [] for var_name in other_vars} + } + obs, _ = env.reset() + for t in range(env.Tmax): + action, _ = agent.predict(obs) + new_obs, rew, term, trunc, info = env.step(action) + # + simulation['t'].append(t) + simulation['obs'].append(obs) + simulation['act'].append(act) + simulation['rew'].append(rew) + for var_name in other_vars: + simulation[var_name].append(getattr(env, var_name)) + # + obs = new_obs + # + return simulation + \ No newline at end of file diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index 04d905b..87e7dcb 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -72,6 +72,7 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): self.threshold = config.get("threshold", np.float32(1e-4)) self.timestep = 0 self.bound = 50 # a rescaling parameter + self.r_devs = config.get("r_devs", np.array([])) # # functions @@ -118,12 +119,13 @@ def reset(self, *, seed=None, options=None): self.state = self.init_state * np.array( np.random.uniform(0.1, 1), dtype=np.float32 ) - self.r_devs = get_r_devs( - n_year=self.n_year, - p_big=self.parameters["p_big"], - sdr=self.parameters["sdr"], - rho=self.parameters["rho"], - ) + if len(self.r_devs) == 0: + self.r_devs = get_r_devs( + n_year=self.n_year, + p_big=self.parameters["p_big"], + sdr=self.parameters["sdr"], + rho=self.parameters["rho"], + ) self.update_vuls() obs = self.observe() return obs, {} From 11be3cb7384bc80d2e7105860d2fb05ff52df98a Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 3 Apr 2024 23:45:20 +0000 Subject: [PATCH 06/64] exploring the population dynamics, especially with a higher survival rate to make it more interesting from the control perspective --- notebooks/explore-optima.ipynb | 1092 +++ notebooks/optimal-fixed-policy.ipynb | 10640 ++++--------------------- notebooks/popdyn_tests.ipynb | 343 + 3 files changed, 2829 insertions(+), 9246 deletions(-) create mode 100644 notebooks/explore-optima.ipynb create mode 100644 notebooks/popdyn_tests.ipynb diff --git a/notebooks/explore-optima.ipynb b/notebooks/explore-optima.ipynb new file mode 100644 index 0000000..0276796 --- /dev/null +++ b/notebooks/explore-optima.ipynb @@ -0,0 +1,1092 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "13d8edbb-57ef-4742-a8b7-3554a4c19a40", + "metadata": {}, + "outputs": [], + "source": [ + "from rl4fisheries import Msy, ConstEsc, CautionaryRule, AsmEnv" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "2eccdc73-4b66-4b3a-8b9f-b70f46ed4683", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b742c702-256e-401c-91ff-1e4c4de11a7a", + "metadata": {}, + "outputs": [], + "source": [ + "cr_gp = {'radius': 0.2195, 'theta': 0.4433, 'y2': 0.4106}\n", + "cr_gp_args = {}\n", + "cr_gp_args['x1'] = cr_gp['radius'] * np.sin(cr_gp['theta'])\n", + "cr_gp_args['x2'] = cr_gp['radius'] * np.cos(cr_gp['theta'])\n", + "cr_gp_args['y2'] = cr_gp['y2']\n", + "\n", + "cr_gbrt = {'radius': 0.3724, 'theta':0.4228, 'y2':0.4207}\n", + "cr_gbrt_args = {}\n", + "cr_gbrt_args['x1'] = cr_gbrt['radius'] * np.sin(cr_gbrt['theta'])\n", + "cr_gbrt_args['x2'] = cr_gbrt['radius'] * np.cos(cr_gbrt['theta'])\n", + "cr_gbrt_args['y2'] = cr_gbrt['y2']\n", + "\n", + "msy_gp_args = {'mortality': 0.0368}\n", + "msy_gbrt_args = {'mortality': 0.0261}\n", + "\n", + "esc_gp_args = {'escapement': 0.1718}\n", + "esc_gbrt_args = {'escapement': 0.1596}" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "c30b9a3d-56f1-4590-8700-7c7e3c5a9e40", + "metadata": {}, + "outputs": [], + "source": [ + "env = AsmEnv(config = {'s':0.97})" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "6217b714-31a1-4f71-b754-1b4f5b46d0c8", + "metadata": {}, + "outputs": [], + "source": [ + "from stable_baselines3.common.evaluation import evaluate_policy\n", + "from stable_baselines3.common.monitor import Monitor\n", + "\n", + "cr_gp_pol = CautionaryRule(env, **cr_gp_args)\n", + "esc_gp_pol = ConstEsc(env, **esc_gp_args)\n", + "msy_gp_pol = Msy(env, **msy_gp_args)\n", + "\n", + "cr_gbrt_pol = CautionaryRule(env, **cr_gbrt_args)\n", + "esc_gbrt_pol = ConstEsc(env, **esc_gbrt_args)\n", + "msy_gbrt_pol = Msy(env, **msy_gbrt_args)" + ] + }, + { + "cell_type": "markdown", + "id": "07b02f72-b6f1-443b-9cf6-86f3983f57d2", + "metadata": {}, + "source": [ + "# Policy plots" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "654e8451-ab1a-475b-b6c4-aaf7d2de8d14", + "metadata": {}, + "outputs": [], + "source": [ + "def get_policy_df(policy_obj, minx=-1, maxx=1, nx=100):\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'pop': (obs_list + 1)/2,\n", + " 'pol': [policy_obj.predict(obs)[0][0] for obs in obs_list]\n", + " }\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "5293ece4-f1cc-4c0b-a4e0-7dd48ca7c46e", + "metadata": {}, + "outputs": [], + "source": [ + "cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", + "cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "7c95abbe-9e73-4ae0-978b-84549099c156", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " cr_gp_df.plot(x='pop', y='pol', title='Cautionary Rule GP policy'),\n", + " cr_gbrt_df.plot(x='pop', y='pol', title='Cautionary Rule GBRT policy'),\n", + ") " + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "c9a1b7f7-512b-4b83-b3db-30a6a934a400", + "metadata": {}, + "outputs": [], + "source": [ + "esc_gbrt_df = get_policy_df(ConstEsc(env, **esc_gbrt_args))\n", + "esc_gp_df = get_policy_df(ConstEsc(env, **esc_gp_args))" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "1a6db163-ad5c-4776-81ef-bc7c26186b4b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " esc_gbrt_df.plot(x='pop', y='pol', title='Constant Escapement GP policy'),\n", + " esc_gbrt_df.plot(x='pop', y='pol', title='Constant Escapement GBRT policy')\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "694a5d2e-193a-4379-87fc-4038b087cc1e", + "metadata": {}, + "source": [ + "# Reward distributions" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "e906b630-26e8-48c8-ac70-600b072ac1dd", + "metadata": {}, + "outputs": [], + "source": [ + "cr_gp_rews = evaluate_policy(cr_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", + "cr_gbrt_rews = evaluate_policy(cr_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", + "\n", + "esc_gp_rews = evaluate_policy(esc_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", + "esc_gbrt_rews = evaluate_policy(esc_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", + "\n", + "msy_gp_rews = evaluate_policy(msy_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", + "msy_gbrt_rews = evaluate_policy(msy_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "0dc1d602-2283-4152-be8d-0594e226cb92", + "metadata": {}, + "outputs": [], + "source": [ + "rew_df = pd.DataFrame({\n", + " 'CautionaryRule_gp': cr_gp_rews,\n", + " 'CautionaryRule_gbrt': cr_gbrt_rews,\n", + " 'Escapement_gp': esc_gp_rews,\n", + " 'Escapement_gbrt': esc_gbrt_rews,\n", + " 'MSY_gp': msy_gp_rews,\n", + " 'MSY_gbrt': msy_gbrt_rews,\n", + "}).melt()" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "342e8036-3bc5-4c0d-b590-4f4f982d1425", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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variablevalueoptimization
0CautionaryRule_gp231.675426gp
1CautionaryRule_gp230.102295gp
2CautionaryRule_gp228.520022gp
3CautionaryRule_gp230.469030gp
4CautionaryRule_gp231.865324gp
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" + ], + "text/plain": [ + " variable value optimization\n", + "0 CautionaryRule_gp 231.675426 gp\n", + "1 CautionaryRule_gp 230.102295 gp\n", + "2 CautionaryRule_gp 228.520022 gp\n", + "3 CautionaryRule_gp 230.469030 gp\n", + "4 CautionaryRule_gp 231.865324 gp" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rew_df['optimization'] = rew_df.apply(lambda row: 'gp' if row.variable[-2:]=='gp' else 'gbrt', axis=1)\n", + "rew_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "88b650c5-f168-4d1d-bd4a-5ff01feb2718", + "metadata": {}, + "outputs": [], + "source": [ + "from plotnine import ggplot, aes, geom_density" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "27d3ea66-777a-4316-b34c-f9a482d1a6ff", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:779: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,)" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ggplot(rew_df[rew_df[\"optimization\"] == 'gp'], aes(x='value', fill='variable')) + geom_density(alpha=0.5)," + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "edbdf404-5570-4f48-bf6a-9ddda9103b5b", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:779: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,)" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ggplot(rew_df[rew_df[\"optimization\"] == 'gbrt'], aes(x='value', fill='variable')) + geom_density(alpha=0.5)," + ] + }, + { + "cell_type": "markdown", + "id": "ab20d63e-a945-4b85-81b4-6b68be9d932b", + "metadata": {}, + "source": [ + "# Timeseries" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "da1c6b86-95c0-47f5-b9ab-3813d37d7917", + "metadata": {}, + "outputs": [], + "source": [ + "from typing import List, Text, Optional\n", + "\n", + "def simulate_ep(env, agent, other_vars: Optional[List[Text]] = []): \n", + " simulation = {\n", + " 't': [],\n", + " 'surv_b_obs': [],\n", + " 'mean_wt_obs': [],\n", + " 'act': [],\n", + " 'rew': [],\n", + " 'total_pop': [],\n", + " 'newborns': [],\n", + " 'non_random_newb': [],\n", + " **{var_name: [] for var_name in other_vars}\n", + " }\n", + " obs, _ = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, _ = agent.predict(obs)\n", + " new_obs, rew, term, trunc, info = env.step(act)\n", + " #\n", + " simulation['t'].append(t)\n", + " simulation['surv_b_obs'].append(\n", + " env.bound * (obs[0]+1)/2\n", + " )\n", + " simulation['mean_wt_obs'].append(\n", + " (\n", + " env.parameters[\"min_wt\"]\n", + " + (env.parameters[\"max_wt\"] - env.parameters[\"min_wt\"])\n", + " * (obs[1]+1)/2\n", + " )\n", + " )\n", + " simulation['act'].append(act[0])\n", + " simulation['rew'].append(rew)\n", + " simulation['total_pop'].append(np.sum(env.state))\n", + " simulation['newborns'].append(env.state[0])\n", + " simulation['non_random_newb'].append(\n", + " env.parameters[\"bha\"] * env.ssb / (1 + env.parameters[\"bhb\"] * env.ssb)\n", + " )\n", + " for var_name in other_vars:\n", + " simulation[var_name].append(getattr(env, var_name))\n", + " #\n", + " obs = new_obs\n", + " #\n", + " return simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "0b56fc05-b2ff-4f58-8bcb-ff64e37f93a7", + "metadata": {}, + "outputs": [], + "source": [ + "from rl4fisheries.envs.asm_fns import get_r_devs\n", + "\n", + "r_devs = get_r_devs(n_year=1000)\n", + "config = {'r_devs': r_devs, 's':0.97}\n", + "\n", + "msy_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), msy_gp_pol, other_vars=['ssb']))\n", + "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), esc_gp_pol, other_vars=['ssb']))\n", + "cr_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), cr_gp_pol, other_vars=['ssb']))" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "912e8a5e-b8cf-4de0-a0fd-13713c033b2e", + "metadata": {}, + "outputs": [], + "source": [ + "trivp = Msy(env = env, mortality=0)\n", + "trivial_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), trivp, other_vars=['ssb']))" + ] + }, + { + "cell_type": "markdown", + "id": "da58583c-9d6c-4d73-a968-af50d1e30598", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "id": "7b602706-0579-4688-8d4d-27d6e7272dd7", + "metadata": {}, + "source": [ + "## MSY plots" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "5d53d2d0-51a1-4347-9c1b-9ea696278486", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,)" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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x48cxYcIELFy4EPv27cOyZcuwevVqnH/++QnvUy8GL0RERA7x+Xz47LPPcPnll2PcuHHo168ffvrTn2Lfvn3Izs4ObnfFFVfA7/eH9W0ZNWpU1Gttpk2bFmxWWrp0Kf773/+iW7duAIAzzzwTn332GQoKCjBw4EDcfffd+OUvf4k//elPpr5LamoqKisrcfvtt6Nfv374yU9+gjFjxuCxxx4ztV89fIrHZhqqqalBVlYWqqur0alTJ9HZISLylD/N3oiZK/cDAPZOu8bWtBobG1FcXIxzzjkHmZmZtqZFzoj3mxq5f7PmhYiIiFyFwQsRERG5CoMXIiIichXPBC9cmJGIiCg5eCZ4ccPCjHVNrfjt++vwxeZS0VkhInINj40rSWpW/ZaeCV7c4MWvduF/6w/hV/8sFJ0VSwUCCia8txZ/z98pOitE5CGpqSdmtW1ubhacE7JKQ0MDgOgZiI1y91SFLlNe0yg6C7ZYtrsCn244jE9xGL/9njOLchGR96WlpaFDhw44cuQI2rVrZ2pCNRJLURQ0NDSgvLwcnTt3DgamiWLwQqY1NPtFZ4GIPMjn86FHjx4oLi7Gvn37RGeHLNC5c2d0797d9H4YvDjIq622bI4mIrukp6ejb9++bDrygHbt2pmucWnD4MVB3u105tXvRUQySElJ4Qy7FIYNiBJSFAUbDlShsYXNMUQkr0U7juCq6Yuwbv8x0VmhJMPgxSINza2aNSt66yc+LDyA615chlteXWk+Yw7wbIUSURJr9Qdw2+ur8Nd521S3GftGAXaW1+HXHhtBSfJj8GKBg1XH0X/S57jjzfhzzOi9yc9aXQIAWLe/ymTOnMHYhch7Fu04giU7K/Dywt2a2za1BhzIEdFJDF4s8O/CAwBOXOxW8FmyF+dEBmWbDlajoPiomMwQkSWaDQQkp2aw+yQ5i2ecg/TWUPhcFr0oEd/s//6+FACw5k856HZqhogsEZFJRmpUT8mwZgQJkV6seXGQd0cbxfabd9fio69rpYjIu05hzQs5jMGLhHwuazhSi8kKio/iDx+udzYzRGQJI89ap6QzeCFnMXhxkO6ywF2xCzvsEiU5NhuR06QMXm644Qacdtpp+PGPfyw6K9bSeZd3WeySdM1hZK9pc7fhT7M3is4GGcBmI3KalMHLvffei3feeUd0NoRxW4ddIqu0+gOYsWg3Zq7cj5KjDaKzQzp1SGfNCzlLyuBl1KhR6Nixo+hsWC5yVI4at/V5IbJKIOQSafZz7hBZaAWSXiyz1u0/hmteWIKVeypFZ4VisDx4Wbx4Ma699lr07NkTPp8Ps2fPjtomLy8Pffr0QWZmJoYPH46CggKrsyElva0rbqt5YasRWSU0wHfZZeA5ob/FyKcW6N7WK255dSU2H6rBT19xx0znycby4KW+vh4DBw5EXl5ezPdnzZqF3NxcTJ48GWvXrsXAgQMxevRolJeXW50V13Jd8OLBgovECA2EfW67EJKYFx9gGltY8yczy3tZjRkzBmPGjFF9f/r06bjrrrswbtw4AMCMGTMwZ84cvPHGG5g4caLh9JqamtDU1BT8d01NjfFMO0R3zYvLnjm9WHCReO66CrzHyHXNIoCc5mifl+bmZhQWFiInJ+dkBlJSkJOTgxUrViS0z6lTpyIrKyv4X69evazKruXcWkPhDyh4eeFurOXKsWSBo/XNON4ce8X08JoXhzJEpvEBhpzmaPBSUVEBv9+P7OzssNezs7NRWloa/HdOTg5uuukmfPbZZzjrrLPiBjYPP/wwqqurg/+VlJTYln+nyFZof1RYgr/O24YbX1oe830WXKRXVUMzLv7LfAx8/IuY74f3edF3IdQ3tWL3kTpL8hfqYNVxfLimxNAaP15i7LJmIUDOknJw/pdffql724yMDGRkuGP9HLfe5HeUxb8xuPRrkQAbDlQDOLHo39H6ZnQ5JV11W71B/KhnFuJIbRNmj78Ug3p1tiCXJ1w1fREamv0orW7Eb7/X17L9epFbyzZyL0drXrp164bU1FSUlZWFvV5WVobu3bub2ndeXh769++PoUOHmtqPnfQvzChX1YtWwcRJ6kiv0DPl4r/Mx4YDVeHvJ3AqHak90eft882lGlsa0/B109aSXRWW7nfRjiP4/nOLUFRSZel+rWakFGIRQE5zNHhJT0/H4MGDkZ+fH3wtEAggPz8fI0aMMLXv8ePHY8uWLVi9erXZbAonV+ii3VeH5RbpFRnovrdqf/j7pvZt4sMOGvtGAXaU1eH211cJy8OMRbujjn0kI4fTrf35yL0sbzaqq6vDrl27gv8uLi5GUVERunTpgt69eyM3Nxdjx47FkCFDMGzYMDz//POor68Pjj7yMq/O80Kkl9YlEBrcGL0ObLuB2rTb2qZWe3asoeRoA6bN3QYA+Nnw3pbs0y2BI3mH5cHLmjVrcOWVVwb/nZubCwAYO3Ys3nrrLdx88804cuQIJk2ahNLSUgwaNAjz5s2L6sTrTXpn2JWLZsHEgks6Dc2t6CDjSr9aTZAhfxtuPuV5qEtto76gyUhzMA89Oc3y0m3UqFGaJ/2ECRMwYcIES9PNy8tDXl4e/P7YQzDdRLY+L1pYZSyX5bsq8LPXVuGukefgkWv6i85OmMhzJfJUDxsqbXjfZJSiKJaUNzLVvOQt2IUWfwD35fQTnZUw0j5QuJSUaxslwg19XvRPUicXrWBUpoKLgCfnbgUAvLqkWHBOokWeK1Hnjol5Xthx3DirDpksDzCNLX48/fl2PP/lzmBHbhn8c+U+9J/0OT5c4/6pPGThmeDFDeS4vI1jqxFZRXPkWgLzvLQJKMBv31+HJz/bmkjWTuYhIpOy3JitYsv3keQQ+UNW9mxqlacW/s+zNwEAHvhog+CceAeDFwlZ1Wo0Y9FufPeZhSivbTS1Hz7QuovMy0tEnkpxm40Mfo2Dx47jf+sP4ZXFexJ+6t56uAbfmZqPWavjj8TxCqsubVmKiNBzhuWWt3kmeHHFPC+6ryZrbj7T5m7Dnop6/O3LnZbsTw0LCbnI3GXKSNOO0a8R+r1X7qk0+OkT7v/XepTVNOGhf29M6PNuY1VTmyxNdjIH7vFUNTTjmc+3Y1e59TNFe5VnghdX9HnRuZ3VN58GlXVk9NKe50WOgotOkLn4NtQEabjPy8m/j9Y3x9126c6KmDeKFn9yLQXAmhc5/Gn2Jry4YBe+/9wi0VlxDXZ9lpDVN59mkwWy9gy7pnZPVpO46sXO2Zr1BtGbD1Xj519PELd32jXa+/Xw+R3vuxlaVVrCY+Smh6p1+6sAnOi3Rfp4pubFDURNUtdicmE5dth1F3lDF0DrbAmb58XgN9F7fW05VKMr/XivyW7LoRq8snh3zJqk0ONq1Q1elmPk1poXiZ83pMWaFwlZ3W5rtircTYUAyc1ILZ5dc9TF206WvhtmXf3CEgBAis+HO0d+I+w9O2okZDlubu3zksLoxTDP1Ly4osOuzu2sPo/NNhtpT4sqR8FFJ8hcDmrX4oUOlTa4b52noSw32lCKouAvn26xfB6QzXFqmU6kG+c9A0GOfEdUzjypibxmjzf7sa+yXkxmXMIzwYsrOuzqLDStbzYydxmHZvu376+LXgnY1N7JahLHLoaWmjA+86u+MzH+DVuMJTsr8PrSYsvnAXHsXJCwEJAxSFUT+Ttd+cxCXPH0Qmw8UC0kP27gmeCF1JmveTnpf+sP4boXl4W95qIyIinIsLzE3I2HMX3+Dh0Tvvki3k+c7poXw/u1/wQ/1hB/dJRdvDbDbij5cqQu8potrTkxN9cXW0pFZMcV2OdFQm7r8+KmJ5xkID50Ae55dy0AYFifLrisb7fg63aeKrr7vMTt9GJFToyz7bhonAyWddiVsAiQMU9qZLhm3YY1Lw5yeI66oGbTo41cVAqQVCrqwme61Ww1MnGq6Q2iA3G2E3Wmx8uTGWYehNw+VNpVdS8qPxODGnWeCV7c0GFXL6tPWNtrXkztnawmQatRUPT0//ZNeOjm0UZOJhualqebjeTLkirV0UYyXcyS8Uzw4ooOuzovcKv7LLT4TXbY1XrfRYVEMnDrcFHAbM2LA4nYxLZWI81mI2tIeEglDKfUqf1M7r2S7eeZ4MUNdE9SZ3G6ts+wa2rvZDmJSrzIQNzOc0nvZ+PNYipqkjq7any0ToV46RpqNtK/qWNkDKjUsOLFOAYvErJ8nheTfV60sMOuXGQq7yLzorlOlpnlAXR+1qobtpVEXUHernmRMFMq3FxbKgqDFweJqnkx3efFRYUAyfW0Ft3nxdj7dog/2Mhb0Ytms5Fl6Tp/3Fr8ASzYXo7axhZT+/lk3QH8flaR7Q958ajWvDCoUcXgxUHi+ryYvCgZu1CCIgvfyJullcGK/hl2rUvTKnYFTU7d/EQc07/n78S4N1fjttcLYr6vN0+/n7Uen6w7iFmr91uYO2vI9CAiGwYvErK+5iV5Ouwu3VmBv325E4EkXp5Vpqe1qJoVje1NddjVGQDEHSrttXleNBNO6C1T21rlo8IDAICikqqY7xs9pscazNXgmKH2wCrPlSwfz0xSl5eXh7y8PPj9ftFZUSXTTd4IO4e3Wu3nr68CAHzj9FNw7cCegnMjhkxPa1F9XiLOJSvzasX1FWsfopuyzNAebWTVJHXylAFtjH43kZdNikTXrFt4pubFHUOldZLsRHZTzUub/UcbRGdBGKmCF6M1LyZupnonepPxfLVtkjqH+rxIeEil/J3VcLSRcZ4JXrxEpmp/wF2FAMl2/hiLXpyY50WmmsI29l1j8c8FqybsYxlhjto1K8M6ZbJi8OIkvaONXHa+ylhuyViN7RSZzp/omhetJsjEWTLPi6gZdoWkat33lfFqc1MRINM16xYMXhyke7SRzfkwyo3NRjLmKRlF93mJv72pm6lNo40cOZUENRvFY6jDroQXnIw1bGpUZ9iV7WYgEQYvEpLthHVTh9028uUoOUXNsKuxvbmaF519XuJsJ+GgH1M0Z9i1KV0ZiIynDlUdx6uL96BG7xw0shX6LuCZ0UZuoH+SOrlOZNa8uIuT7eRNrX6UVjfi7K6nxM5LxL+1a14Sz4sV87wkw1BpWxZmlPB6E5mlG19ajtKaRmw6VI2//fQize3VRhvJdi+QCWteHKT3YpIuCJewYNIiY22QU5w8fW58aTmueHohlu+uiJ0XjT4v0Xk1sTyA3u3izfMi6LyxbW2jGCdD6He0bKi0B643K8vd0ppGAMCSnbGvi6i01V6X7V4gEQYvEpLthHVjwSTjk6BTnDx/Nh+qAQD8u/CgrrzYW/Pi3qHS9jUbxQgPQxPzcs2LBJnSeylykjrjPBO85OXloX///hg6dKjorKiS4WJKhK2dLG0iQ44W7TiCwn1HRWdDqKjlAWxMS3fNS7z3Yr3pwPntaLORyt9xN9TapwwXXAQZsqT3QYJBinGeCV48NUmdy05lGQsu0Zkqr2nE2DcK8KOXVzietoizR7WQNtjpxVSHXZ0fjrs8gM7XrObkJHV2PGzIWDsrR7mk72rkJHXGeSZ48RLZTljNmhdnsmGI6DyV1zYJS1vExFZq50hU7JLgfnTlQe92EnbYtYvmaKN4x8LAVSTncTOWKTuuG/01L2rNRpLdDCTC4MVB+kcbyUXGpyotogtTkenLdP5EDZXWDITtH24k49ksrtmIk9TZSfe1yJoXwxi8OMito43s7GRpF9EBl8j0RZw/at9Xa2HGqP04UvMSt9dL4hkwwa7zJVZtgt6h0oae+qUsA8RL0XkxcmFG4xi8SEi2qkLticVkKCbCyRhQOUee88fwwowSzvPiyKrSjp6vSoy/Ym1loNmIZUBMZpuNSB2DFyfpvJpY82Ke6CzJeExEiBptFHFcjK59FA9n2NWZVljNi0XNRhKe7zKMgtQ/VFrtdcluBhJh8OIg3c1GtubCeuKLiGiiyy2RyYsu70JvGlo1L5G/k+iaF1HsylPsSer0MZInCQ+pFHnSG3yoBi8W5sVrGLxISL5oW4ZiwBjR1dgin/pEnz2hX91onxer0o1HzlWlberzojFJnXXLA7ivjJCJ6mgj0RezxBi8OMit17dmvmX8Yqx5ESbsu2vkxcq86p+kzug8L+6dpM7MPC9GsiRhCSBFsaS7zwuDFMMYvDhIdG1AorQ77MpHdJ7EDpUWMtzo5J+hzUYafV6idmOq2Uhvu5E96ZvhZM1F2FBpy2perNmPlYyWt3YEEPqDFy4PYBSDFwnJFoXbObzVLuKrsZNrqHSo0G9utEOuI7UctqdgnG01LxppeXmeFxkypfdBQn1hRsluBhLxTPDijrWN9G0n27A5DpUmI+L3edH/WTPpxhOI0+lFXJ8Xe2iuKm1VwhJecDLkyGyzEWMXdZ4JXlyxtpHe4EWyE1bCckmT6CwLbTYSXvMSOtrI2MKMZg6b/qHS9qRvhqPniw1pib7eYpGh3NI9VNrWXHiTZ4IXL3HbiSxDIRFJdJ6EdtgVfAaF1bxENhtFzvMS1SfGxDwvVgyVjvGeI5PUOTnDrsrfUdsZGSotYxlgtM+LDdeN/qHS7PNiFIMXB+me50WyM9adHXZFD5UWmLjY/rphohdm1OrzYn0eItm1grMZTvZ5CU/Xqj4vyXNMjTBd8yLbzUAiDF4cpLegkK2Tljs77IpOn/O8ANo1L/E+azxd88dcWLORk2mFddiNs52R5QFkLANEZwDQfTGKmKRu6tytePjjDTamYC8GLxISffMxSsanLtHEzvPitjMolIlmI73bSXmnda7qxY4Ou3IeUvGZ0r88gPOT1P1j0R68X1CCvRX19iViIwYvpEmCMsAw0QWXG4+ZGaHHOzyYta5Pi3YmzG8WK39O/JbxZv01Q2uGXavC7CQ73XXTu6q0yMeNFn9AYOqJY/DiIN2FoGQPzpo1KxKWXKKzJLI2SvTpI6zZSOd28fq8iGs2EjNJnWX7lDBaN5ojsZPUqbwu/GqWF4MXCbnthJWv2Eq+mo9QoluN1OtdbB4qrXfa+zibiZth1579ai0P4OnrRILvpn+SOq5tZBSDFwfpfbqS7YTVflqWoJSIILwfjsh5XsQlDSD8fIia50WCmhf5zlYbJ6nTSMuqodIyEl4GwIqaF1LD4MVB+mfYlYsbCzHReU7mDrvxa160Rq45Mc9LvGYjMb+ckzUv4etQWZOO6OstFhnzpEa2B1Y3YPAiIdlOZO0bjkMZMUB0lmQ8Jk4x1efFTLp6Z9g12GzkxE/pbJ8Xtc7Vkdsltk9ZGL0G7Sh2TU9SJ9m9QCYMXhykv7+uXGesnTccu4gOHpKtw67aAJaoGXQjPmc0uImbB901L3HeSzx5cwSNNoo/2zDneTHL7CR1st0LZMLgxUH6J6mzOSMGaXaylKGUiJLEQ6WFd9gN7fMS+aZGLZ6ZeV50D5WW74S1rc9LzA67+j5rrOZFPjL0xdPf54WdXoxi8CIh6c5XzZoX8YVEJNHlllPJv7tqH257fRUamluDr4l+WjNVs2Gq5kXfh+POqSJstJGYodJWjbySIVCIJEOOdAcvBl8nSYOXTz/9FOeeey769u2L1157TXR2LKP7YpKt6sWFRJelThXmj3yyCUt2VuDNZXuDr4k+fcI67FrYLGQk3bjbxQ2uot904re0b5K6aOoTCiZOhkAhkuE+L3bM86J3qDSLfMPSRGcgUmtrK3Jzc7FgwQJkZWVh8ODBuOGGG9C1a1fRWTNPxitcB3d22JUwUzaqawqteRErbKh0VJ8XrWYjM+nq3C5eJ1WPzfMS666ov+bFSNWL/k2TiemaF0Y1qqSreSkoKMC3v/1tnHnmmTj11FMxZswYfPHFF6Kz5SjZTlcZgxMtovPswkNmitpif87OsGtDZw6HyBhsu73Piwy5Mr22kXVZ8RzLg5fFixfj2muvRc+ePeHz+TB79uyobfLy8tCnTx9kZmZi+PDhKCgoCL536NAhnHnmmcF/n3nmmTh48KDV2RRC92gjyc5Y7Q674guJSMJz5HAGQk8Z0eePmT4vTnTYlXJ5AEebjfR91vV9XmTIku6h0qY+npQsD17q6+sxcOBA5OXlxXx/1qxZyM3NxeTJk7F27VoMHDgQo0ePRnl5udVZkY7u0UaSxdta+ZahjIgkuuASO1Ra9CR1iTfLiJ5hV8absBmxb34hfV4sGjYu41Ezmic7rhv9Q6XlKvPdwPLgZcyYMXjiiSdwww03xHx/+vTpuOuuuzBu3Dj0798fM2bMQIcOHfDGG28AAHr27BlW03Lw4EH07NlTNb2mpibU1NSE/ed2skXbMhZMWkRXwzt9Dww9Z0ScP2rzvERvF/6m0bWP4ubBpnlenPgtHR1tFNbEFy/QdPk8LxLkKcXs8gCS3Qtk4mifl+bmZhQWFiInJ+dkBlJSkJOTgxUrVgAAhg0bhk2bNuHgwYOoq6vD3LlzMXr0aNV9Tp06FVlZWcH/evXqZfv3SJTuZiNbc2GcnU/LthFd8yIwfdEFXtyvrnkumQpfdG0Vr9lIFNv668aapC70b4sSFv2wEIsMedI9w67q67LdDeThaPBSUVEBv9+P7OzssNezs7NRWloKAEhLS8Ozzz6LK6+8EoMGDcL9998fd6TRww8/jOrq6uB/JSUltn4HM3SvbeSy81WGQiKS6ByJTd/5Eyg0RXN9XhJnxeRrXhttpDVJnVXJShgPSpEn/R12jb1OEg6VBoDrrrsO1113na5tMzIykJGRYXOOnCXb8DjtDruOZMMQ0X0XRKfvtLCneTNNEQ70eREe2cZgV21Q7HUZQ/u8WDNsXMbT3XCfFzvmedE9VFquMt8NHK156datG1JTU1FWVhb2ellZGbp37+5kVoSQsYZCFzd22BWdAYeFFn6iY1+rZm01nq6+nct4HTqZIzcvo2CE0QcIO85NvUFJinSTlsjP0UOWnp6OwYMHIz8/P/haIBBAfn4+RowYYWrfeXl56N+/P4YOHWo2m7aR8elEDzdm285j3dTqx8o9lWjxB9TTty95TaKf4eI2y2h+1sRQaZ3bBdR/NpX92v9rOtpspPJ31HYuHyotBd0Xo9qq0qKvZnlZHrzU1dWhqKgIRUVFAIDi4mIUFRVh//79AIDc3Fy8+uqrePvtt7F161bcc889qK+vx7hx40ylO378eGzZsgWrV682+xWECz1fZSgU3Nhh184sPfDhBvz0lZWYMmerevpJ1mE3bMp5E00RjqwqLWU4blOzUawZdsN+K/XPGslRbVMrth5290hPe5YHMJ52+AzVpMby4GXNmjW46KKLcNFFFwE4EaxcdNFFmDRpEgDg5ptvxjPPPINJkyZh0KBBKCoqwrx586I68XqR7g67IaesDIGBdmEvQSYj2Bn0/Xf9IQDAW8v3xsuBbenHEjZUWvQ8L0aGSkfcMcwFLzqbjeQ7XQXmyZo+L7WNrRjztyVYurPCgjxZQ4bfOZHlAULzzYoXdZZ32B01apRmITJhwgRMmDDB0nTz8vKQl5cHv99v6X5FCIvCxWVDNxkKiUiisyTjMZFB5HGJLCvsHyht3yKIZjh5voSNNjIQaOrx+eZSXNa3WwK5sp4MNWyJLMwoPtfu4JluQp5qNgr5m81GCRI9z4vAtEU/rTlRexL7w5ZveGJrB35Mu260sfu8hDQbxflsIt87I02eW4oM5ZLZ0Uaia1FlJs+ZlgR0Lw8gWRQuQyFglOinLqF9XsQlDcDYUOmoZiNT6ercTsLzWcY8JSKdwUsY3cGLWp8X0RezxOQ505KA3mtJvj4vWu9LkMkIoo+b08ckfGFG50u8sBEsJjqBOtLnJfEkbGNXnmLOsKuz2SgRGWmp1u7QBBl+Z91DpUOu2dB8M3ZR55ngxQ1DpfUKr3kRfwlqLswoPotRZMxTsrC6KcKKdEPJuDyAbZPUac2wG3dkmPE8ZbST55aiJ/92N8sn8hwh4ekpJXnONJPc0OclkZPSDSeyjFkUHfQl21DpUHFviDaOXLNiYUZhnOywqzNZ1/d50bONJOcClwcwTp4zjaTlxg67ovPkePKiSzkl5p/Rm9k5z4vOo240CSd+S/uajWKkZcM8L21kajYy+gXsaG5N0bnPsK4CbDjShcGLg/QWrpxV0TzR8ZTIUWKiRyhIvzCj6Mg2BrvypD3DrjXzvLSRqsOujrPJ7jMhsQ67xj+fjOQ505KA/knqjH/GTlqFgOgmmlhkOG5OCu+wKzgDJm6IToyUlvHccDRLeoO8BHLVLtVdd1vb+7yY3M5dR9NZngle2GHXPprXt/gsxpDEfV5EJKp7BIuNgbCNN2W72ba2UazRRjrb+GQM8ozQk3/7a170Lswo1whTN/BM8OKKDrs6t5Ov5sXc+yKIPm4ib5Ciq5qt6vPyQv5O1DS2GEhXZ58XCU9Y2/q8aI02sjg9mY6t0azYcdmYrnkRfTFLzDPBixvobjZSGfMvivZQaRlyGU50jsSONhIxz4vOTqBawUvI328t34tH/7tZfx50HnOjw5KdOL+dvIbC+rxY3GFXplotXTUvNmdX96WoUtvO0EUdgxcJSbeqtOgMJECG4+YkmR7Q4nYC1Wo2ivjdCvcdM5Cuzu0MnhqOjDZycqh0WM2Lte1GgUACGbKJvg67tjcc6dwqdrORTNe1bBi8OErnaCPDnxBLxjyKzlPS9XkJYabmxVy69gyVNmLlnkrc+tpK7D5SZ+hz9q1tFL/Pi/U1L/JwU82LbEvCuAGDFwfpvlB8knXesnGEiF1E50lo8qL7vFh8Q9SdruUbGvfTV1Zi2a5K3DOz0NDn7Ouwm3haiU2qKU9hYLjPiw3XTSJ9Xri2kT6eCV48NdpIdAYiuLLDruj0HS7EQ6udhc/zImqotMpnqxqaw/5teCr+BPJUVtNkLAlBJ2zcztUJfHHR110YCQIpszUvoq9lmXkmePHSaCPzH7KWKzvsCs6TyNRFP63Fr3mxcah0DC/k78Sgx+fjX2tKQtKwX4rB38C+ZqNYaYX8HXdtI+Ppte2vrqkVhfuO6roOX1m8G3e+vRotfms7zOjJvu3NRokszBh6GBi7qPJM8OIGem+o0s3zIjoDbpRkB033TSBiu8ibq9U3k+nzdwAAJv57Q0ga9v84eqeFb+Nks1FoYnYNlb7xpWX40csr8FHhAc3PPPnZNny5tRxzNhy2JS9xt7H5QtVd8xLyt4wLh8qIwYuE1Hqei2JkeKssRB83ofO8CEv5BFPLA9h02AJK7L/tYrT2y8mzRVH9R5ztDO57R9mJDsuziw7q/mxDsz+BFOWmf6j0yQ1DgxfR17LMGLw4KIH+ulIEBpo3YhkyGUF0jZXTwVPoOSO82ShunxetZiP7OfPTSFLzEmu0kc6h0ok1Gxn/jF301LCFDUu2IQ96m43Ca15CXhd9MUuMwYvNikqqcPlTC/D55tIE1zaSqDRQkWig8NnGwxgxNd/QXB56ueCw2UZ0Jz9zNS8O/HBGJ6lLIAmjfV7sCqliz7Crd0i58TxV1jXhH4t2G/6cHXT1ebE5D4l12GXNix6eCV5kHW1059ursf9oA379T/1DJ6WreTE5QqSxxY9j9c1Rr//m3bU4XN2IO94sMJG7xPJkN6eTF74wY4i4I1gkqMRzIg2jv4ETTVltwjvsnvzbH1Dwl0+3YO7Gw9Eb6vTs/B2YOndbQvn64ycb8dv31yX02Vj0zfNid58X45PUhU70J/palplnghdZRxuFtuMmcqHYdW0dqW3Ca0v2xAwqrM7DpdO+wkV/mY+jKmnVNraaSyCGZGs2CiWivAtriog3giXB/a/dfwxj3yjArnJjk7/FYrRDZCLH02jtl103Ua15XkL/nrPxMF5fWox73l174j1bchTf/9YfQqtFo45kePDTexaE1tSxw64+ngleZGV2ETS7bsK/fHs1npizFb/7ILEnnRmLdmPpzgoA2jfqyq+DlrU2NA+pEX39iw6eRIpf85JY1cuNLy3Hoh1HcOfb+h5Oiivq0dgSuwOo4XMjgejF+FBpm8ScYTf235V14XPTiGqybrWoGkpXn5eQv+3oX5JIs1F4h11Wvahh8GIz0zcxm8qPDQeqAQBLvg5A4mYhRiEwbe42/Pz1VSfe15nJFAfPNtGhg9DgSXBds6mJ5jR+uUPVjbr289byvRjztyXR+1cUw7U3CdW8SDxUOvR6Dv07LSLisiJPy3ZVYvY6/SOOAOuCFz3sn+dF53Yqs6qz2Ugdgxcnib6jJsiq4a2O9pwXXvMijpBmI9Xn+cjtwkU+WWqdS233162HazDuzQJsOlitum1xRX3Ua09/vh1NrcaaJfSctyVHG7B898kHAZmHSqulm2rT08V9s4oMbW9Zs5EEPXYTKfPsHgHlFWmiM+BlR2qb0Nhy8kLUqk7/4ycb0eWUdPTu0kHXZ2SgKPrrlpy8EIU32zi9PIBMQ6XjnuiR/1TivR0l9esv9/PXVqGyvhnLdlcayttLC42PhNFzOEc+tSD8M0aDFwvPF621cdSSiqp5sSxHxhgNLtUILwNgpObl5N/s86IPa15s9MScLbq33Vleh/cLSpC3ILxwtfs81tM2Hy8PZgqayMJy1Z5K/OD5xVi992jC+2wj+voXW/Miem2jeO9pzPOiVfPy9TnT1o+q2aIbXaLmbToc83wV+RuEP7nrX1U61YZmo0RcHaO5LxFGZ9i1JejXPcNu7EnqSB2DFxuV1+jvAFfXFHvEjd1PD2k6qorj5aG2sVV3IRfZgbJ9u9Swf9/8ykpsK63FTTNW6NthHMl2+YdWT8tc8xL5XlSzkcYvZ3TafTsVV9Tj7plrY56vsR4KiivqcdX0RTH3ZeX9KtFZbNJSjf0WdqnUMQLSKokc96P1zZiz4TCaWrVnBNY9SV1YzYvxPCUjBi82inqSibNtqz/2u1YWaot3HMGOstqw1yLzaDQP9U2t0Ftc3j1zLfwhV2Zmemqcrc0RPblfMj88mVnsT+t9PeerUw5XHVd9L1aQ9cePN2KnSmdhRxdmjBgqrSgK/AEl6kHG7edwIl1eAgEFL+TvxJKdR1Q/87NXV2L8e2sxY+Eezf3rjbVDT2vRZZdbeCZ4ETVJ3X0frAsu/hYpxUBBq7aiaiKncSBG6L6ttAa3v1GA7z+3OOx1XcFLnPfqmvTXvAAIm+sls519p5/oy19kASR6hmZTzUYa+5ap5uVgnOAl1gN3Y5wn9YCFrV9hfV5ivR/x9z0z1+Lypxag1cpMRGj1B7CzrNbR87EtKX9AUR02H2nuplJMn78Dt72uPnHmttITD4DzNpdq7k93n5ewZiOdH0pyngleRExSV17biNlFh1Tfj4wL4l23qsFLjA+VVjfiP0UHY35myc4jGPDo51HDEzcfrIm5f7M1L7WNrYYChUf/tzmYt8hmo1BXPrMQeQt2GdhzONEPL7KMlHbqOOhNx2x+ZKl4aW4N4IGPNqi+HyvIipd1K2tejIwOVJQTN+GDVcdx7wdFwdcDAcXSQGP8e2tx1XOL8e6q/bq2tyLttmM6+vnFuPCxL3A8xsKPkYHewaoG3fvvlKk93sXsPC8A8NS8bXhnxV7d+UoWngleRNCs4vbpb0M20mx01fRFuPeDIry5rDjqvTveXI2GZn/U8MTQp6r1JVXBvyM7zcamnu+ymkZ8ta1cxz5OmLPhcDBv8YKX4op6PP35dt37jST64UXoDLuhc0YISN/M2kZaB06WZqPq4y1x34+Vy3i1RvYtzBgjLR1nRWvA2oaszzeXAQBeXaLd1AIgrHk5UW3HdFd5HZpbA9gYY1i93lQ+XFMS9VrHzHaan0uk43Zo8LLlcA1eWrgbk/6z2fB+vI7Bi42saDaKpfbrzr2LdkS3y6pd9C0hwdEP85YF/zZ7M8j9V1HCn01LtfH0E93nRWjqJzlVTR/eFGGiz4tGOm0BgOggRquzZtiTdEDBpP9swhqVGaYr65osPV/ijTbaX9mAguKTo6PUfisrggczWlQe5sxo+00amltR+vVkh3pnQG+rZQv93Tu1t7LmJfYkdVpBcjLjPC82iqp5iddslEBhYaT9X23iJ7PNRomWcdtKa8JWk1Zb9yhRooMHoX1eRFdOxP3qZodKn/h/qs8Hv8BfWWuKgNCg4YstZXhnxb6Y283deDi4lpBV4gWPlz+9IHxblU1bAwGh8X9zawDtTXboj7wGW/0nmsKGTclHXVMrlk38LtINPkBVN5wMJjLj1By3MTtJneggUmYMXmxkZLRRi0phGK8AMRK8qD3JmO2wm6hbX10V9u9hU760dP+i+7w4Te1UcOowhHUSjrNd5O8SNUmdVrPR1180JQWAvj6Ytmhq0QheQg5ITZyn56dMNI3qonF5qx1tf0AROslbswWz7LaNpGpzy6srMbTPacFpKVbsrsTl/bqFba/FH7KRWpkdKpEHidA0/MlWkBnAZiMb6W02KjnagPs/XB/zvXgFiJGa8xaVkQQ+H/BBwX7sKq+N+T5gTy1C5FwOVq9nIsPsmqKEPvU71mE39G8DfV6ig5n42q6pyFrNRN362ko0NBtf1Vyr2Sj0wSJeOWBHLZmR6eXVru3WgCL0AcBIM7oaBdHn1+q9J2t7FUUJO+H0lHOhxZSeCToT+XlDa1tijRylExi82Cg18sxVOQ9/+/461X1YVvPSGntHJUePY+LHG5EzfXHM9wGxTTBHapu0N4pB9AOL0+mHBixho40E/Hrx+7yYazYK1rxYdNdftqsSz36xA68t2YNjBpouNZuNQrIXr1O8TEO/Q/kt7rBrlCXBixK/5kKB8bItNJjQNUldIjUvIWlYtMyTJzF4sVHkE5dacVByVH14XryLy0h7qpk5HEQGAte9uDShzwkPXgQW/eHzvDifvpnRRno77BrpDK/l9aXFeGLOVlxr4FwzErzEa5qNVYP0zOfb0eoPYNmuCox7syD+fDIaEl0M1Qs1L4DGVPuK/g67seireYk+/rEWDA0V2j9Ra6kARVGw50hdUvaNYfBiI71V2/GaTOJNrhRaJlY3tODHLy9X3dZMG7JTnU9jlfGHvx4VYJToS1nsUGnn09R7E4g8Lm8t34tZq/eHvB//wAWbjWwYbXTgmP4goUlj0rPQGpV4eY31W724YBc+XnsQt762Cgu2H8Ef/hW7SVmNsWaj2K+v3F2J+Vu0J2GzS7NKTbERCpS4k/8ZXUMoEFDCPqPV7wmI/fte+czCmCNF27SG1bzEz+PMVfvx3WcXYfJ/N2nmxWsYvNhI70Jn8U7QtftjD68EwgvIvIW7VIdiAurzyFjt7/k7E/6slVXooqfYdiJ10d9RTdzlAWK89tC/N+red9vgENHNLdqjjU6KF7yofY9D1ScDqdIaYwG8kcUG1WoI7/9wPSrqnFtjKJJVzUbxApQTzUZK2Pbx+JXw2ih9axvFFmvemDahteRaHXaf+PTE4r8zV+qb/M9LGLzYKLrZKLZ4F+rmQ7Fnxj2x/5N/1zbGnw/ATGFg5Bb5rMpSCXqIviFZyYm4Qi0NER12w/vZ2CfYbCT4VNFuNjqZwbh9XlRK4Iy0k8NwjV67ar95rKBS0vjXsg67cfu8KMa+vz+y5kXXaKPYv329ykK8QPiD5nsaMxLryYNXMXixkd4CNl7NS7yn2NALQ6tLi6lJnxwq4HQscK2b6ELZiT4voSmElpEiOuyGHW8zp5rGZ904SV28/jlqAXtG2smL4cCx49hZpj4aUG8+YpUzoq8TNVYMlYaiQImzm8jB4FqHIrITs5nAYcH2I3j8f1tU09ESa6mDZOOZ4EXUwozxRE9Spz4sMRGhBZ9W+61TNS9maPUR2lVep3uBtWQeKh0q8rRoaG7F8l0VMSctLKtpxD0zC7F8d4W5NE0ce63PtgUtomvptPo7pOiseVF7Ms+IWLT0bwaaY8OC2pBaOKunI7CTFTPsKohfLho9HH/+zyb83wsnO3WbHW30RozlXQDt3+nVxXtw/qR5+Gzj4bDXV+yu1MyPl3gmeBGxMKMWvc1GCe8/bDGv+NuqzbCrh3MddtWv9AXby5EzfRF+/c9CXfsS/UTpTLNRSN+GkNfjrW1059tr8LPXVuGFr8IXvaxrasUfP96IuZtK8bOICQSN58u+z7ad84nU0s3bdFh7I53irRANGOnzEvv10GajSAu2leOPn2xUDeTVrteYNS+qqYilZwI4LQu2l2P3kTr1DZTwxSe1yrmP1x7E8ZBjrjb9RKhE1jbSGhk65bOtAKKXZrnl1ZVJNerIM8GLjKyaSKtNIKBg6+GTfWBCb/ZaF56ZJxmnLod4hyvv65ttZC/9v87bhlteWRlVs5QMl7DadwwfKq3g47UHsK30xHmz/Ouns9C29NLqRgyY/DnyDSywGS83poIXjfdTfD4EAgpKjhofPnz3TOum4Tcyw268ckBPs1GkcW+txnur9uP1pbGf3NXyEeuJXtZO31b0edl0sAY/nrFC9X0FZs9VHcFLArcAM2W11cusyIzBi430jjbS69n52zHmb0uC/zbSbFRvYBbRBdvK8fDH6k92donXN2C/ylw4Ly/cjRV7KjF/S1nY66ILZSfS15PEV9vKkfuv9fjB80tUt5lrYY0EYC5w1JykLsWnWt3uJK0n3LAOu1GzVZ6kXvMSXjR/uuFw1Pwgh6tjB3BqOXNTzYslfV40mL1E9Xze7Ay7RpXXJja1hBsxeLFB203fyom0ACBvwe6wf4fuXitYr2rQvzrpuLdW4/2C/cGbhFNxQLwn1HKNmXZlq3nRXD1ZUbDxQLWudnPVfah8y9DDWFRSlfD+E2UmcNN6mk3x+fD2ir0J798poddmapw2LrWal/QYNS9XPrNQV9rxFluM3ljXLh1ndA6WRJh9wFD7dOh+E7kHmOmbpFVOegmDF4vNXncQ5/15Hv61piTuzVhRFEyduxV9Js5JOC0jNS+JLK1e1rZsvKwlXDyi+7xovD9z1X5c++JS3Pn2msTTUB0qfZJT8/uEsnWodIpPeH8mPUL7OsS7f6kFL2k6OvWUVjdi6tytcWfgDa0Bil3zIuZgzt9Shsv++hUK9x0Vkj5wop9g2OSKBg+F+pD0k38nVPNiotbpSA2DF0rQfbOKAAAPfrQhbtS9Zt8x/GPRHlNphZZvWk8RWlNSx96/7+t9G/5oQqwcDSH6/hbvmAUCCv48+8SMmEt2mhvZ0yZ8qHToCBPn54FQ++77KxuwWGVm0XjzXoRK9YnpjP3PlfuQt2CX9oZfC/s9VG5higKs2JP4CJEvt5bjH4v24PcfFEXsODTtk2IFskYuOX9AwY0vLbNkQrS73lmDA8eO4443xA2wUBAevNU2tmDORiOzCsc+eGGvJhC9mCkHazTm+/KSNNEZ8LJ4NS/WdKzSP89LIt5cthcbD1Q7UoULmGvrjSS8z0uc8OmTdQetSUOt5iXktLNiyKl6+mqddGOn+euZ6iPFvj35c7x068Waaaam+Bz/bRUgGGz+cFBPnHVaB83PODmUe+PB6rB/q517sa4vI9f21sM1WLu/ylDetKj1xZuz4TCuH3SmsfXb/AFD5aoSMWNu5Ag87c+r77dNIqON7LxmvYQ1LzZKtfnohg+VDj/hrZrEa82+Y45dTFbWEsh8+S+Ms65JosJWlQ55PXSIfGjzQkVdE777zEJUG+gLpZdaob6rPP5Eaw9/rL1MgM/nc/y3DV9JWN856mRzzNldw4OpsGYL34n83zOzMObs16JH1qql/+XW8qhO+FpueGk5vjM134Jc6aPa5yXk78RWlU68HPz7V7twzQtLNGdc9wIGLzayosNui19B7r+K4q6FAUQXAqKnT09EY5zhp0a/j+h+EVrNRpakoeMG2RKS1q2vrgx7b09FvanOr6pPnga3NyLV53OsJrBNS8jNJN6Ec6Hsaq2L1bzWq4t6TZAPPizdVYG5m0rxv/WHot4XXUMZj9HO5pE1UFoCirkQU+08NNvnxUyzUfXxFmw+VGOoaa+2qRXj3izAvwsPJJyuCGw2sli7VF+wpsKKeV4++vqE+nhtdFND6MUTeSGdqLaWt2Aywh9QkJaSYmj4pFqxdKS2CR0z05DZTn0SMCvEO/JWNY9FPmHH+kfoZF97K2MPN084fbW/DQY1RqQK6LDrD6l51FujaVeA9e3Jn0e91j7iXI588o9XW2RVIG1E6FxVIp1Y28jEyDjV8zyk2Sihmhfzv4mR2psZC3djwfYjWLD9CH40+CzTaTuFNS8WaxfSVmR3u3foSW5Xs5EMWvwBw98nVsFSVtOIoVO+xPAnHahajjstuVU1L7GFHqkvNKre481Bkii1wNGKp3yfz/mQPPRJWM8oIAA43uLH377ciS1xFla10rH6Ztz3wTos31Vh6DhbFbv86GL9Nz0zI+yspMDsnER6al7E9HmJ1Vdof2UDDhyLfoBJZCSqDBi8JGDepsP49T/XxGxXDAtebA4gQisiopuNvBW86K2ubxOrXFn59cgOqy/WfZX1UU9L8Yofy4IXlf0Y+enbmVgNU215AvtrXpwNX0J/W71B9IYD1Xjuyx24+gX1yQGt9Jc5WzC76BB+9lr40g5auY23ar1dKuvlGM5repI6Hds43eelTeR52tDcisufXoDL/rogbs2OiJq4RDF4ScDdM9fi881lePrz7VHvtQt5krXhoTZM6E0wskD3UMULWvwKUu0+mAn6ZN0BXPH0Qtz7wbqw1+MVjJY1G1mwj9aAErXkQiLpq/0dtr1GhquPt2jPsOtzvtkotOZF1meCkpAZqI10GP33Wuf7ObQzMZIhEFDw63+uwfQvostew/uKGG1kmOpoo5N/O93npU2qz4cVuyvxm3cLUVbTiCMhk9fFW3rht++Hl2PNFqwxZRcGLybsi9GHIPTCtLvpJl6fFy81G7UmVPPizB3uxa+HV366IXyK/XhdAa16uLHiK/513jYs3G7t6Cczxz5Wp9JQIkYbuWGxu9AsbjxgrOOqFYx0fU03Ebys2FOJzzeXGR7WrM5EnxfV19U6o+ljxcSSKSk+3PLqSny2sRR/nr0p7PyIVys/J2Sl6hW7K9HvT3MxY9Fu1e1FkjJ4ueGGG3Daaafhxz/+seisxFXbGN3zP7QPgf3NRiHBS0SA7KVmo13ldaioMzYvjlO3G7X2abX7d2OL37o1oyQaUWVVsLitNP5w6tQU50fIiJjoz6jQh5dxbwmY+M3AT2Km5sWKBRvbRM7zksjnY79+8m9RNS9/+XRL8O8dZbV4NqSmSu+t4aF/bwAATJu7zXR+7CBl8HLvvffinXfeEZ0NTVp9XqxeVTpSaIHlj2w28lDNS2Q7fllNo+YNzKn7m5HCtLKuCcOmfIlVxeKmRLeSesdc+9JMTfE5PjeJ22peRDCSfLu0xMqmTzccwpvL9ib02Vjs6vNipNkullaLF6XcW9kQVTOsh+znvZTBy6hRo9CxY0fR2dBUF2POhdAOkE6ONoq8mdsdOIk0/Ml8PP/lzqjXQ3vSOzVJmFrwEiv115YWoyZGbV2iwodkyvN7R3VeVhQs3F5uyb59Puc77Fq5bIVdZJ6vJVKiNS8T3lun2j/rtSXGl1oxO9pIfZ6X0I7sxq9LWYIGp+dTMsrwWbR48WJce+216NmzJ3w+H2bPnh21TV5eHvr06YPMzEwMHz4cBQUFVuRVOrHOsbCnigTvJ0d0rgwaf7RRYmm7xd/yw4OXppYALvvrguC/9Vx3Lf4ACvcdM/Wko9ahLVb6mwxOoqVFdNmiln5k4fv55lLc8aY1TRmpAvq8iD7Oeshyw9MjkT4vM1fui3ot9Bs/MWer4X2a7bCrZ1RdIuWwLMGy7OeU4bOovr4eAwcORF5eXsz3Z82ahdzcXEyePBlr167FwIEDMXr0aJSXn3zyGjRoEAYMGBD136FD8TvruYHeeSDieeaL6Gm8Y4k7SZ3Xo5cIOyOmntdz2f159ib86OXlmPKZ8YKvjWqflxg5sKyvSzCNk2T6tSObMJfuMrf4ZCBiqLIbggmnib7PGKn5SWRuoT99vbZUqMNfr3qfKEUB3lhanPjnceJ73/b6Ktz2+qrgMVBCnmcSajaSpI+V6HNKi+EZdseMGYMxY8aovj99+nTcddddGDduHABgxowZmDNnDt544w1MnDgRAFBUVJRYbmNoampCU9PJmoqaGrGzN5rpSW9UePAS/p6XRhvpEVl2Rv5708Fq3Bux+u4Hq08sufDmsr2YfO23E0pXtc9LjAv/uNXBS+hQeUv3bI7VT2yh53mKgGYjNxB9TAz1edFZRioAHvxoPXpktU8oT1qW767A6r3HEt+BAhxraAmuDF9Z34xup2ZENefuKIvfCT2SFaONrBB63ZXVNCK7U6bA3ESz9E7b3NyMwsJC5OTknEwgJQU5OTlYsWKFlUkFTZ06FVlZWcH/evXqZUs6etkxY6ma8NFG4Sd8rGHcbvHR3SMs2Ev48bglYl0fq6hV8cZ69XizfTUvIoSNNgp53ergxR8WvIj/3k541WAfDtn7J4TSG7xsOliNf605ENVEbJWSo8e1N4pDb4f17z+32NB+RTfXtAXCofkY/mS+dBPYWRq8VFRUwO/3Izs7O+z17OxslJaW6t5PTk4ObrrpJnz22Wc466yz4gY+Dz/8MKqrq4P/lZTEX8DQbmaGARoVr9nIzaxYdyjycMQa1m6nWE/C8RaeTCwNS3dnPH2VwtvympeQw3ZitJG7zvXD1cZvkkYnDpTsvhKX3trpJouvl0hmzyM9H0+s2Ujsj9m2hlxksCLbdSflwoxffvml7m0zMjKQkZFhY26MaSeq5kWu88oUK0ZpiT4csa5ztWYjRVESGi3k1Igqo6wu5MKajVzY5+VX/yy0PQ3RNxa9ye+rbNBdK2z3+W1273blLl6flwIHpllobA4gIy01qu+aTCMaAYtrXrp164bU1FSUlYUvBldWVobu3btbmVSUvLw89O/fH0OHDrU1HS1qNS929EEJPcetavOurBO/7ogFfZ6F9wGIRa3ZKOEnrdBmGwHfVy3J0O/zw7xlWLe/ylQ6ydhsZJTo092O5O1+IDN7zOwKGOMtzPgzm5q/QzW2niinRDdfabE0eElPT8fgwYORn39y1d5AIID8/HyMGGFFPwZ148ePx5YtW7B6tYDZJUOkqQQvdtxc/BY3Gz37xXYMfkJ/rZdd7JgfJ1bwGK+WbH9lA+pjzOOjV8w+Lyo1LzNX7sOVzyzEvsr6hNOTgT+gBP9r09waML34X9hoIxHLSruA+JoX69O3PyC3v9koEfGCBiealNoeskSfU1oMNxvV1dVh166T60oUFxejqKgIXbp0Qe/evZGbm4uxY8diyJAhGDZsGJ5//nnU19cHRx95ndoN0Y5zLt5oo0T83bL1QsyxK3iJLBTSU1PQ4o8OKLaX1mL084txescMrH4kJ+p9PYxc94/978RU3o98sgkz7xyuPw2jmTIgEFA0h9tHdtK94ukFyGyXimsv7GltXkISShHc52V18VEMODNLWPpqZL/RJML20MV7h8wSbYdF9poXw8HLmjVrcOWVVwb/nZubCwAYO3Ys3nrrLdx88804cuQIJk2ahNLSUgwaNAjz5s2L6sTrVU6uKRSIM9rIzRJpYYs123GotBQfQldH8gcUtEtLAWI05Sz+urOk3skCY0mkvf5Yg8H1m5TYf1uhNaAgXSt4CUn0UNVxHDh2omNqfbO1naNDC9HGloDQipd73l0LAJhw5bcE5iKaJFODWMru4MKKgM+dNU76yH5LMRy8jBo1SvPgTpgwARMmTEg4U4nIy8tDXl4e/DGepL3K6mYjWSQSALbN2aImclXqm/+xQnXUQ6f25vuxR887o/37NBgcSm1nh8a286nkaAO6Z2UaGkVn5zwvsq5wK5roG54dqcvdaGTNPib+ewOm/ehCS/eZLKRc2ygRsvR5cVK85QHczI7OzZF9kdbsO4b0tNinf1b7dsG/9S4doDX8M14nvDYNBmsswudZsfYEaA0oWLTjCEY+tQA/j1gY82Sasf+2fJ4XL53cNokcGeI4W6IXm0cbWbB7s/v4YHVJ1AK/on9Kt/BM8JKMwpqNPHTG29HyFlnzAoQHHOU1jcFApWPmyeBF7/wwkX2dIp+E9fw+xmte7OMPKMH1ZNRWwda7tpFZXjq37eLF+M7+0UYWNBtZcBVGDkH24E9pCwYvHuGl8j3F58Ps8Zdaus+YwUtIzcuwJ/Pxs1dP1DCE1vxUH2+J+lws7SJqcRL5OQwHL6HLA1j8+wcCSsIrk1s9IsLt/Tn6ZZ9qexqim40SdWqGehPtRosXMo0kQ80LAN3XWWS/RqsnvXQbzwQvsszzIoqXnk5TU3wY1KszOmZaN4dirCHskc1GBXujaxhqGnUGLxbMrGy0xsLOn7w1oGg336mkb3XnceFNIi4guuZF1gkT47Gkz0vITuoaW/H7WUVYsL1c/QMxRMUuKuf7m8v3Gsucx0k5w24ixo8fj/Hjx6OmpgZZWfINZYyUv7VMeyMDvNQvwKpmo8YWP+6eWYhR/U7XbDZSo7fmJfLpyen7rdXJBZT4Q6UX7TiC3FlFMd+zOtjwUmBuF9HHyI0/kdXNRi/k78Qn6w7ik3UHg68t3G5smYcT+4ztwzVil76RjWeCF7f515oDlu7PQ7GLZcPN/7liHxZuP4KF24/gW2dEV93Hqi35eO0BFO47Fvx3oiu8uvFJNFRrQEG8lS7GvlGg+p71axu5+1g6gcfIOCuO2FPztgf/Lq1pjHo/ken83RgIisDgxSPc2uYdi1X9dUMLk13ldVHvxxptlPuv9Zak7cTPYec8Ly2tgbCaF0VR8PrSYvTN7ogr+p0eIzMn/7RzVWmKTfQhEp1+IqzIc2gtix2jJEXZfMje/kZWYJ8XjxBdbSyb1sCJm208akOlreDErxFau2N1Tc/xFn9YU9iK3ZV4Ys5WjH2jQPMp3/JmoyTol3hfTl9Tn+f1b5zVx8yqGmMZam1fXij/fEqeCV6ScZ6XUKw1DqdniHP3Tpm2pe90zYvVGpr9YU+SB6uOB/8eMiV6/auweV4SbGpTkww3ZrM3PtHXvww3XKOszrFVNS8ynO5OzhSfKM8EL8kuGQp4q6XF69Rhmv2/R9gkcRYnd7zZH9Zs9MBHG4J/H62Pv4yB1TUvXuqMrsbsfU/09e/K4sfiPH+1zdgoIzUyHEs3NIExePEIdtiTi9kC6Gh9M5bsPBK3L5Od/ZwamlsNzfMSuiUnqTMucqIyo5LgEFlO1toiGXLFmhdyDGMXb/m/F5bgttcLwjoERrLzJz/e4jf09GXn8gBqwcu52R0tTccuO8qiO4tHMnuvEN2p2Y3FD8tMdRZMW2U7F2SR9EiGp9NITa3yLsJp9uc4VH1ipNScDYctyI1xx5v9hp6+QmuBrD4XdS4v5Wrm+7wk3/VvlqwjNGXIF2teHJTso40kON8dd/lTC0RnQZVVVdKNcQK08KHS1p4AJzrs6t8+NPVE58ZRwz4v2kRf/6LTT4QLs+yYWBNUTnhvLWbHqQl2mmeCF442Sr5LsaymyZF0vtpWhh++uBQ7y2p1f8aqn6Mp7vol9q1t9H7BfjS36q/yCE0/1jILZsjwJGo3Nzzpeo2sp5UM+YoVTM/dVIr7VGbVFsEzwUuyS8bgxSm/eGsN1h+oxq9nFur+jFW/ht6aF6vtLK/D2yv2JfRZTlJnnNkOu+J5/zdKJokuyuokBi8ekQQ168KVVUdP/63GqvttvJVjFZW/RbBz5AabjeQnY3zplg7dkdSuJSevg3jrmv3ty52YMmeLY3lRw+CFSKdGI80oFt3Md5XXYcqcLTGbTmS6YdiZF5m+p13YbERadsZY4sQu8WpenvtyB15dUhw2caUIDF4MqD7egn8XWrugIrmH1pNPIKAgb8EurNpTaWlVyKtLilFUUhX1umJjnxej7EyfNS/y8/4v5C0lRxvivh+v5qVNq+BhgFyY0YB7ZhZi+e5K0dmIojXjKcVm9Q13dtFBPP35iVVmb7zoTEv33dAc3fdFdMDiFPZ5IbLO4h1H8Mu318TdRs/pKLq20DM1L04MlZYxcAGA7aX6R8HQSW8t32vp/vZW1Af/tvp2G6ugCBsqLfjZ184RQTKONrL6eLs9dpHxN6LYZq5MrCN+JD21M3byTPCSzEOlT81gBZpsrC7MRQcnWuzMnYyT1Fl9rxb9FGvW0HO6iM4C6ZTZLjXu+7NWl+CrrdrrNIlu6vRM8ELkhF3l+mq5rO6mEWu+l9CA5vkvd2J9jH4xXiBjs5H1NWsW79Bhtw4/G9/u2Ul0NkgHreBlxqLdujoHix5OzeCFSEN6yFSzOdMX6/qM1Te3xhbtPi8/zFtmcar62TvaSMLgxeIsub3PS1qKDz8Z0kt0NkiHzHbW3PZFn7MMXog0ZCRwsYdOGng8Rmdbow5WHUd9U6vp/biRjKONLO/zYuneiNRlpMWvedFLdG0hgxciDVrVrDGF3NuGP/mloY/uilFl+8ScrbjwsS8AAOv2H8N1Ly5FQbG10/DLSsrgRb4sEemSUHkWg+iaF/b0JNLQPoGLPbTmpabRWI3J959bFPP1tpv4zf9YiWZ/ABsOVBvOlxvJuPSFjE1ZRHpY1mxkyV4Sx5oXIg2JXOxm7m1aFQ3NMg6/sZGEFS+seSHXsqrZSDQGL0QaEhnGaldtwZ0ak0t5kZTNRqIzQJQgq2peRPPGt4Azk9QR6WXXze3LrWU27VleMjYbyZgnIj3S07xx2/fGt0ByT1JH8lm3vyqhzyXriKJ4AjLWvMiXJSJdHvlkk+gsWMIzwQuRTCrqmhL63JHaxD7nZX4GCkQUgcELkUSOJBj0eJmcNS/y5YkomTB4IZIIa16iydi/RMJ4iiipMHghkkh5TaPoLEhHzrWN5MsTecOOMu11hYjBC5FU2GwUTc5mI9E50Mct+SRxVrl0pm4GLw74xumniM4CuUSs1aOTnYSxi2vqXe55dy3eL9gvOhtElmPw4oA0G1ewamr1Y/nuCtv2TySajH1e3NRh96tt5aKzQIKcdVp70VmwDdc2crmH/70RH687KDobREnFRbELJbFU0Us/24g1Ly7HwIXIeQxeyA0SWdrELRi8EBEZxNFG5AYejl28E7xwbSMicoqMnYjtlN0pQ3QWKAGpHo5ePBO8cG0jInJKsjUbZbVvJzoLlAAPxy7eCV6IiJzCZiNyAx+8G70weCEiMoqxC5FQDF6IJHRudkfRWaA4ZJx7hiiZMHghIjKIoQuRWAxeiIgMYsULkVgMXoiIDGLsQiQWgxciIoPY54VILAYvRGRaaU2j6Cw4i7ELkVAMXoiIDOI8L0RiMXghIjKIrUZEYjF4IYrj71/txLbSWtHZIMmwzwuRWAxeiOJYu7/Kkv28sniPJfshOTB2cZcnb7hAdBbIYgxeiBwwff4O0VkgCzF2cZd2qd5d4ydZSRe8lJSUYNSoUejfvz8uvPBCfPjhh6KzREQUhjUvRGKlic5ApLS0NDz//PMYNGgQSktLMXjwYFx99dU45ZRTRGeNiAgAoDB6IRJKuuClR48e6NGjBwCge/fu6NatG44ePcrghYikwdCFSCzDzUaLFy/Gtddei549e8Ln82H27NlR2+Tl5aFPnz7IzMzE8OHDUVBQkFDmCgsL4ff70atXr4Q+T0RkB9a8EIllOHipr6/HwIEDkZeXF/P9WbNmITc3F5MnT8batWsxcOBAjB49GuXl5cFtBg0ahAEDBkT9d+jQoeA2R48exe23345XXnklga9FRGQfhi5EYhluNhozZgzGjBmj+v706dNx1113Ydy4cQCAGTNmYM6cOXjjjTcwceJEAEBRUVHcNJqamnD99ddj4sSJuOSSSzS3bWpqCv67pqZG5zchIkpMgNELkVCWjjZqbm5GYWEhcnJyTiaQkoKcnBysWLFC1z4URcEdd9yB7373u7jttts0t586dSqysrKC/7GJiYjsxmYjIrEsDV4qKirg9/uRnZ0d9np2djZKS0t17WPZsmWYNWsWZs+ejUGDBmHQoEHYuHGj6vYPP/wwqqurg/+VlJSY+g5EREQkN+lGG1122WUIBAK6t8/IyEBGRoaNOSIiCseKFyKxLK156datG1JTU1FWVhb2ellZGbp3725lUlHy8vLQv39/DB061NZ0iIi4thGRWJYGL+np6Rg8eDDy8/ODrwUCAeTn52PEiBFWJhVl/Pjx2LJlC1avXm1rOkREjF2IxDLcbFRXV4ddu3YF/11cXIyioiJ06dIFvXv3Rm5uLsaOHYshQ4Zg2LBheP7551FfXx8cfURE5HYKB0sTCWU4eFmzZg2uvPLK4L9zc3MBAGPHjsVbb72Fm2++GUeOHMGkSZNQWlqKQYMGYd68eVGdeImI3Io1L0RiGQ5eRo0apTlMcMKECZgwYULCmUpEXl4e8vLy4Pf7HU2XSBSfjzdRUXjcicSSblXpRLHPCyWbFJ9PdBaSlteajf5y/QDRWSAyxDPBC1GySWHsIozXal4y03grIHfhGUvkUqx5EcdjsQuR63gmeOE8L5RsGLyIw3leiMTyTPDCPi+UbNhsJA5jl+TW94xTRWch6XkmeCFKNqx5EYexS3LjpScegxcil2IBKhCrXoiEYvBCRGRQgLELkVCeCV7YYZeInOK1eV6I3MYzwQs77BKRU9hqRCSWZ4IXIiKnMHghEovBCxGRQZznhUgsBi9ERETkKp4JXthhl4icwooXIrE8E7ywwy4ROYXNRkRieSZ4ISJyCkMXIrEYvBARGaSw5oVIKAYvREQGMXQhEovBCxGRQax4IRKLwQsRkUFsNiISyzPBC4dKE5FTGLoQieWZ4IVDpYmIiJKDZ4IXIiIiSg4MXoiIiMhVGLwQERGRqzB4ISIiIldh8EJERESuwuCFiIiIXIXBCxEREbmKZ4IXTlJHRESUHDwTvHCSOiIiouTgmeCFiIiIkgODFyIiInIVBi9ERETkKgxeiIiIyFUYvBAREZGrMHghIiIiV2HwQkRERK7C4IWIiIhchcELERERuQqDFyIiInIVzwQvXNuIiIgoOXgmeOHaRkRERMnBM8ELERERJQcGL0REROQqDF6IiIjIVRi8EBERkasweCEiIiJXYfBCRERErsLghYiIiFyFwQsRERG5CoMXIiIichUGL0REROQqDF6IiIjIVRi8EBERkasweCEiIiJXYfBCREREriJd8FJVVYUhQ4Zg0KBBGDBgAF599VXRWSIiIiKJpInOQKSOHTti8eLF6NChA+rr6zFgwADceOON6Nq1q+isERERkQSkq3lJTU1Fhw4dAABNTU1QFAWKogjOFREREcnCcPCyePFiXHvttejZsyd8Ph9mz54dtU1eXh769OmDzMxMDB8+HAUFBYbSqKqqwsCBA3HWWWfhgQceQLdu3Yxmk4iIiDzKcPBSX1+PgQMHIi8vL+b7s2bNQm5uLiZPnoy1a9di4MCBGD16NMrLy4PbtPVnifzv0KFDAIDOnTtj/fr1KC4uxnvvvYeysrIEvx4RERF5jeE+L2PGjMGYMWNU358+fTruuusujBs3DgAwY8YMzJkzB2+88QYmTpwIACgqKtKVVnZ2NgYOHIglS5bgxz/+ccxtmpqa0NTUFPx3TU2Nzm9CREREbmRpn5fm5mYUFhYiJyfnZAIpKcjJycGKFSt07aOsrAy1tbUAgOrqaixevBjnnnuu6vZTp05FVlZW8L9evXqZ+xJEREQkNUuDl4qKCvj9fmRnZ4e9np2djdLSUl372LdvH0aOHImBAwdi5MiR+O1vf4sLLrhAdfuHH34Y1dXVwf9KSkpMfQciIiKSm3RDpYcNG6a7WQkAMjIykJGRYV+GiIiISCqW1rx069YNqampUR1sy8rK0L17dyuTipKXl4f+/ftj6NChtqZDRERklZKjDaKz4EqWBi/p6ekYPHgw8vPzg68FAgHk5+djxIgRViYVZfz48diyZQtWr15tazpERERWueq5xaKz4EqGm43q6uqwa9eu4L+Li4tRVFSELl26oHfv3sjNzcXYsWMxZMgQDBs2DM8//zzq6+uDo4+IiIiIzDAcvKxZswZXXnll8N+5ubkAgLFjx+Ktt97CzTffjCNHjmDSpEkoLS3FoEGDMG/evKhOvFbLy8tDXl4e/H6/rekQOa1f9qnYUVYnOhtERNIwHLyMGjVKc7r+CRMmYMKECQlnKhHjx4/H+PHjUVNTg6ysLEfTJiIiIudIt7YRERERUTwMXoiIiMhVPBO8cKg0ERFRcvBM8MKh0kRERMnBM8ELERERJQcGL0REROQqDF6IiIjIVTwTvLDDLhERUXLwTPDCDrtERETJwTPBCxERESUHBi9ERETkKgxeiIiIyFUYvBAREZGreCZ44WgjIiKi5OCZ4IWjjYiIiJKDZ4IXIiIiSg4MXoiIiMhVGLwQERGRqzB4ISIiIldh8EJERESu4pnghUOliYiIkoNnghcOlSYiIkoOngleiIiIKDkweCEiIiJXYfBCRERErsLghYiIiFyFwQsRERG5CoMXIiIichXPBC+c54WIiCg5eCZ44TwvREREySFNdAaspigKAKCmpsbyfQeaGjS3aWqoC27XUFeLQFMDWht9uj5rVGtjii37Fa22pgbtAhnwN9Uj0OQXnR1dWhv9aKyvM/17NH59/oT+tmrnj9+XGnV8ampq0FBf65nzouW4onpcRZ7/rY0KAk3HLdtfW1mRiOYG8+edVvqtjT7U1daoblNTU4PjCZx3fkSfw1YJPT/MHN/Y+7a2TE/k2Olh5zVSXVODVH+6pftsu2+33cfj8Sl6tnKRAwcOoFevXqKzQURERAkoKSnBWWedFXcbzwUvgUAAhw4dQseOHeHz+Szdd01NDXr16oWSkhJ06tTJ0n3TSTzOzuBxdgaPs3N4rJ1h13FWFAW1tbXo2bMnUlLi92rxXLNRSkqKZsRmVqdOnXhhOIDH2Rk8zs7gcXYOj7Uz7DjOWVlZurbzTIddIiIiSg4MXoiIiMhVGLwYkJGRgcmTJyMjI0N0VjyNx9kZPM7O4HF2Do+1M2Q4zp7rsEtERETexpoXIiIichUGL0REROQqDF6IiIjIVRi8EBERkasweNEpLy8Pffr0QWZmJoYPH46CggLRWXKVqVOnYujQoejYsSPOOOMMXH/99di+fXvYNo2NjRg/fjy6du2KU089FT/60Y9QVlYWts3+/ftxzTXXoEOHDjjjjDPwwAMPoLW11cmv4irTpk2Dz+fDfffdF3yNx9kaBw8exM9//nN07doV7du3xwUXXIA1a9YE31cUBZMmTUKPHj3Qvn175OTkYOfOnWH7OHr0KG699VZ06tQJnTt3xi9/+UvU1dU5/VWk5ff78ec//xnnnHMO2rdvj29+85v4y1/+Erb2DY9zYhYvXoxrr70WPXv2hM/nw+zZs8Pet+q4btiwASNHjkRmZiZ69eqFp556ypovoJCmDz74QElPT1feeOMNZfPmzcpdd92ldO7cWSkrKxOdNdcYPXq08uabbyqbNm1SioqKlKuvvlrp3bu3UldXF9zm7rvvVnr16qXk5+cra9asUb7zne8ol1xySfD91tZWZcCAAUpOTo6ybt065bPPPlO6deumPPzwwyK+kvQKCgqUPn36KBdeeKFy7733Bl/ncTbv6NGjytlnn63ccccdyqpVq5Q9e/Yon3/+ubJr167gNtOmTVOysrKU2bNnK+vXr1euu+465ZxzzlGOHz8e3OYHP/iBMnDgQGXlypXKkiVLlG9961vKLbfcIuIrSWnKlClK165dlU8//VQpLi5WPvzwQ+XUU09V/va3vwW34XFOzGeffaY88sgjyscff6wAUD755JOw9604rtXV1Up2drZy6623Kps2bVLef/99pX379so//vEP0/ln8KLDsGHDlPHjxwf/7ff7lZ49eypTp04VmCt3Ky8vVwAoixYtUhRFUaqqqpR27dopH374YXCbrVu3KgCUFStWKIpy4mJLSUlRSktLg9u8/PLLSqdOnZSmpiZnv4Dkamtrlb59+yrz589XrrjiimDwwuNsjYceeki57LLLVN8PBAJK9+7dlaeffjr4WlVVlZKRkaG8//77iqIoypYtWxQAyurVq4PbzJ07V/H5fMrBgwfty7yLXHPNNcovfvGLsNduvPFG5dZbb1UUhcfZKpHBi1XH9aWXXlJOO+20sHLjoYceUs4991zTeWazkYbm5mYUFhYiJycn+FpKSgpycnKwYsUKgTlzt+rqagBAly5dAACFhYVoaWkJO87nnXceevfuHTzOK1aswAUXXIDs7OzgNqNHj0ZNTQ02b97sYO7lN378eFxzzTVhxxPgcbbKf//7XwwZMgQ33XQTzjjjDFx00UV49dVXg+8XFxejtLQ07DhnZWVh+PDhYce5c+fOGDJkSHCbnJwcpKSkYNWqVc59GYldcsklyM/Px44dOwAA69evx9KlSzFmzBgAPM52seq4rlixApdffjnS09OD24wePRrbt2/HsWPHTOXRcwszWq2iogJ+vz+sIAeA7OxsbNu2TVCu3C0QCOC+++7DpZdeigEDBgAASktLkZ6ejs6dO4dtm52djdLS0uA2sX6HtvfohA8++ABr167F6tWro97jcbbGnj178PLLLyM3Nxd//OMfsXr1avzud79Deno6xo4dGzxOsY5j6HE+44wzwt5PS0tDly5deJy/NnHiRNTU1OC8885Damoq/H4/pkyZgltvvRUAeJxtYtVxLS0txTnnnBO1j7b3TjvttITzyOCFHDd+/Hhs2rQJS5cuFZ0VzykpKcG9996L+fPnIzMzU3R2PCsQCGDIkCF48sknAQAXXXQRNm3ahBkzZmDs2LGCc+cd//rXv/Duu+/ivffew7e//W0UFRXhvvvuQ8+ePXmckxybjTR069YNqampUaMxysrK0L17d0G5cq8JEybg008/xYIFC3DWWWcFX+/evTuam5tRVVUVtn3oce7evXvM36HtPTrRLFReXo6LL74YaWlpSEtLw6JFi/DCCy8gLS0N2dnZPM4W6NGjB/r37x/22vnnn4/9+/cDOHmc4pUb3bt3R3l5edj7ra2tOHr0KI/z1x544AFMnDgRP/3pT3HBBRfgtttuw+9//3tMnToVAI+zXaw6rnaWJQxeNKSnp2Pw4MHIz88PvhYIBJCfn48RI0YIzJm7KIqCCRMm4JNPPsFXX30VVZU4ePBgtGvXLuw4b9++Hfv37w8e5xEjRmDjxo1hF8z8+fPRqVOnqBtJsvre976HjRs3oqioKPjfkCFDcOuttwb/5nE279JLL40a6r9jxw6cffbZAIBzzjkH3bt3DzvONTU1WLVqVdhxrqqqQmFhYXCbr776CoFAAMOHD3fgW8ivoaEBKSnht6nU1FQEAgEAPM52seq4jhgxAosXL0ZLS0twm/nz5+Pcc8811WQEgEOl9fjggw+UjIwM5a233lK2bNmi/OpXv1I6d+4cNhqD4rvnnnuUrKwsZeHChcrhw4eD/zU0NAS3ufvuu5XevXsrX331lbJmzRplxIgRyogRI4Lvtw3h/f73v68UFRUp8+bNU04//XQO4dUQOtpIUXicrVBQUKCkpaUpU6ZMUXbu3Km8++67SocOHZSZM2cGt5k2bZrSuXNn5T//+Y+yYcMG5Yc//GHMoaYXXXSRsmrVKmXp0qVK3759k34Ib6ixY8cqZ555ZnCo9Mcff6x069ZNefDBB4Pb8Dgnpra2Vlm3bp2ybt06BYAyffp0Zd26dcq+ffsURbHmuFZVVSnZ2dnKbbfdpmzatEn54IMPlA4dOnCotJP+/ve/K71791bS09OVYcOGKStXrhSdJVcBEPO/N998M7jN8ePHld/85jfKaaedpnTo0EG54YYblMOHD4ftZ+/evcqYMWOU9u3bK926dVPuv/9+paWlxeFv4y6RwQuPszX+97//KQMGDFAyMjKU8847T3nllVfC3g8EAsqf//xnJTs7W8nIyFC+973vKdu3bw/bprKyUrnllluUU089VenUqZMybtw4pba21smvIbWamhrl3nvvVXr37q1kZmYq3/jGN5RHHnkkbOgtj3NiFixYELNMHjt2rKIo1h3X9evXK5dddpmSkZGhnHnmmcq0adMsyb9PUUKmKiQiIiKSHPu8EBERkasweCEiIiJXYfBCRERErsLghYiIiFyFwQsRERG5CoMXIiIichUGL0REROQqDF6IiIjIVRi8EJFrjBo1Cvfdd5/obBCRYAxeiIiIyFW4PAARucIdd9yBt99+O+y14uJi9OnTR0yGiEgYBi9E5ArV1dUYM2YMBgwYgMcffxwAcPrppyM1NVVwzojIaWmiM0BEpEdWVhbS09PRoUMHdO/eXXR2iEgg9nkhIiIiV2HwQkRERK7C4IWIXCM9PR1+v190NohIMAYvROQaffr0wapVq7B3715UVFQgEAiIzhIRCcDghYhc4w9/+ANSU1PRv39/nH766di/f7/oLBGRABwqTURERK7CmhciIiJyFQYvRERE5CoMXoiIiMhVGLwQERGRqzB4ISIiIldh8EJERESuwuCFiIiIXIXBCxEREbkKgxciIiJyFQYvRERE5CoMXoiIiMhVGLwQERGRq/w/ipnEXu4/4xEAAAAASUVORK5CYII=", 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "msy_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", + "msy_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", + "msy_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", + "msy_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", + "msy_ep.plot(x='t', y = ['act'], title='action'),\n", + "msy_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(msy_ep.rew):.3f}')," + ] + }, + { + "cell_type": "markdown", + "id": "766da37e-aac0-4ec9-a574-670679c7be9e", + "metadata": {}, + "source": [ + "## Escapement" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "id": "45da811e-d63d-4cca-8344-624a75b45dee", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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CCCGEBAaFBSGEEEICg8KCEEIIIYFBYUFIiPT0p5BKi7CbQQipAnp7e8NuQkFQWBASEt29KRx17WKcffOysJtCCIkgM2bMwNy5czFv3jyMHDkSZ555JtatW4eZM2diyJAhGD16NC6++GLs2LEDALBo0SK0tbUhlUoBANasWQPLsnDllVfan/mFL3wBn/nMZ8rabgoLQkLipbd2Y29vCq9t7Qy7KYQMKoQQ2NvbH8o/IYqzUP7qV79CfX09nnnmGdxwww045ZRTcNRRR+G5557Do48+im3btuHCCy8EAJx44ono7OzE6tWrAQBPPvkkRo4ciaVLl9qf9+STT2LGjBlBXUojLJBFSEgk4o6uF0IwHY6QCtHdl8Kh33kslHO/cu2ZaKovfOqdPHkyfvjDHwIArrvuOhx11FH4/ve/b79/xx13YPz48diwYQPe//7344Mf/CCWLl2KY445BkuXLsV//ud/4pprrkFXVxfa29vxxhtv4OSTTw78e6nQYkFISNTFHSHBOAtCiIlp06bZP7/44otYsmQJhgwZYv+bMmUKAODvf/87AODkk0/G0qVLIYTAsmXLcP755+MDH/gAnn76aTz55JMYN24cJk+eXNY202JBSEgkYo6u70sJJPxvKkgIKYDGujheufbM0M5dDM3NzfbPXV1dOOecc/CDH/zAc5zc22PGjBm444478OKLL6Kurg5TpkzBjBkzsHTpUuzatavs1gqAwoKQ0FAtFr2pNBpBZUFIJbAsqyh3RFQ4+uij8fvf/x4TJ05EImFuv4yz+N///V9bRMyYMQM33HADdu3aha997WtlbyddIYSERDzmCIu+VDrElhBCqoE5c+Zg586duOiii7Bq1Sr8/e9/x2OPPYZLLrnEzgQZNmwYjjjiCNx99912kOZJJ52EF154ARs2bKiIxYLCgpAIQGFBCMnHuHHj8MwzzyCVSuGMM87A4Ycfjnnz5qGtrQ0xxbV68sknI5VK2cJi+PDhOPTQQzFmzBgccsghZW9n9dmCCKkR1HDN/hSDNwkhbtQ0UcnkyZPxwAMP5Py7H//4x/jxj3/sem3NmjXBNSwPtFgQEgF6abEghNQIFBaEhIRaJ4euEEJIrUBhQUhoOMqir5+uEEJIbUBhQUhIqBYLukIIIbWCL2Fxww03wLIszJs3L6DmEDI4oSuEkPJS7B4dg5UgrlPJwmLVqlX4+c9/jiOOOMJ3IwgZjKiPL4UFIeWhrq4OALB3796QW1IdyOskr1splJRu2tXVhVmzZuH222/HddddV/LJCRnMMHiTkPITj8fR1taG7du3AwCampq44Z8BIQT27t2L7du3o62tDfF46ZWASxIWc+bMwdlnn43TTjuNwoKQEhGKzaKXwZuElI0xY8YAgC0uSHba2trs61UqRQuL++67Dy+88AJWrVpV0PE9PT3o6emxf+/o6Cj2lITUPLRYEFI+LMvC2LFjMWrUKPT19YXdnMhSV1fny1IhKUpYbN68GZdddhkWL16MhoaGgv5mwYIFuOaaa0pqHCG1DF0hhFSWeDweyMRJclNU8Obzzz+P7du34+ijj0YikUAikcCTTz6Jm2++GYlEwt4ERWX+/Plob2+3/23evDmwxhNSzVBYEEJqkaIsFqeeeirWrl3reu2SSy7BlClT8I1vfMOoBJPJJJLJpL9WElKDqDEWfdwrhBBSIxQlLIYOHYqpU6e6XmtubsaIESM8rxNCCoc59oSQWoGVNwkJCVVLpKkrCCE1gu9t003buhJCiiNNiwUhpEagxYKQkFC1BHUFIaRWoLAgJCTU4E1aLAghtQKFBSERgLqCEFIrUFgQEhLu4E0qC0JIbUBhQUhIiCw/E0JINUNhQUhIqLUraLEghNQKFBaERADqCkJIrUBhQUhIuFwhVBaEkBqBwoKQkGDlTUJILUJhQUhoMMaCEFJ7UFgQEgFosSCE1AoUFoSEhBDZfiGEkOqFwoKQkFClBC0WhJBagcKCkJBg5U1CSC1CYUFIBKCsIITUChQWhIQEK28SQmoRCgtCQoKxm4SQWoTCgpCQcMVYMHqTEFIjUFgQEgEoKwghtQKFBSEhIVh5kxBSg1BYEBIWipagriCE1AoUFoSEBHc3JYTUIhQWhEQAxm4SQmoFCgtCQoKVNwkhtQiFBSEhoQZvUlYQQmoFCgtCQkK4gjcpLQghtQGFBSERIJ0OuwWEEBIMFBaEhIR723RaLAghtQGFBSEhobo/KCsIIbUChQUhIUGLBSGkFqGwICQCUFcQQmoFCgtCwoJZIYSQGoTCgpCQcG9CFmJDCCEkQCgsCAkJVt4khNQiFBaEhITg7qaEkBqEwoKQCCCYcEoIqREoLAgJCVe6KStvEkJqBAoLQkJCzQRhjAUhpFagsCAkJESWnwkhpJqhsCAkArCOBSGkVqCwICQk3Omm4bWDEEKChMKCkNBgjAUJjl/97U3c+Jf1YTeDECTCbgAhgxXWsSBBcvUfXwYAnHfU/njffkNCbg0ZzNBiQUgEoMWC+CGl+NK6+1IhtoQQCgtCQsOVFUJdQXzQl3IKoSRiHNZJuLAHEhISLlcIE06JD1RhEeeoTkKGXZCQkHDtbsrKm8QHfSmnL8UsK8SWEEJhQUgkYIwF8YNqsWBPImFDYUFISDArhARFb78jLNIsikJChsKCkJBwl/TmZEBKpz+t1kQJsSGEgMKCkNBwb0IWYkNI1aO6QlLsTCRkKCwIiQCMsSB+cLlC2JdIyFBYEBIBOBcQP6gWCwoLEjYUFoSEhDt4k5MBKR013ZSeEBI2FBaEhISrjgUnA+KDfsZYkAhBYUFIBGBWCPFDr1rHgtYvEjIUFoSEhDr+s/Im8YPqCqHFgoQNhQUhIeESFlxlEh+4gzdDbAghoLAgJDS4uykJCmaFkChBYUFIBGCMBfGDOyuEfYmEC4UFISHBypskKFh5k0QJCgtCQkId/rnKJH6gK4RECQoLQsJCZPmZkCJxuUKYYURChsKCkAjAVSbxg+pWS7EvkZChsCAkJFh5kwQFy8OTKEFhQUhIsI4FCQq1/6ToCiEhQ2FBSEiwjgUJCgYCkyhBYUFISNB8TYIiLVjHgkQHCgtCIgBjLIgf6FYjUaIoYXHbbbfhiCOOQEtLC1paWjB9+nQ88sgj5WobITWNGrzJypvED4IxFiRCFCUsDjjgANxwww14/vnn8dxzz+GUU07Bxz/+cbz88svlah8hNYt7lRleO0j1k6bFgkSIRDEHn3POOa7fr7/+etx222149tlncdhhhwXaMEJqHXfwJicDUjoukUqVSkKmKGGhkkql8Nvf/hZ79uzB9OnTsx7X09ODnp4e+/eOjo5ST0lIzcK5gPghzX1nSIQoOnhz7dq1GDJkCJLJJC699FI8+OCDOPTQQ7Mev2DBArS2ttr/xo8f76vBhNQMymRAiwXxg9p7WHmThE3RwuKQQw7BmjVrsGLFCnz5y1/G7Nmz8corr2Q9fv78+Whvb7f/bd682VeDCakV3LUHQmsGqQFcO+WyM5GQKdoVUl9fj4MPPhgAMG3aNKxatQo33XQTfv7znxuPTyaTSCaT/lpJSA3CFEESFOxLJEr4rmORTqddMRSEkBLgXEB84C7pzc5EwqUoi8X8+fMxc+ZMTJgwAZ2dnbjnnnuwdOlSPPbYY+VqHyE1i2C1RBIQqpZgVyJhU5Sw2L59Oz772c/inXfeQWtrK4444gg89thjOP3008vVPkJqFsZYkKBQC6wxeJOETVHC4pe//GW52kHIoIN+cRIU7EskSnCvEEIiAKcC4gdmhZAoQWFBSEiw8iYJCndJ7/DaQQhAYUFIaAhWSyQBoepSZoWQsKGwICQC0GJB/JBmFVcSISgsCIkAXGSSoGBWCAkbCgtCQkIf/7nSJKXCTchIlKCwICQkhJYLQl1BSiXNrBASISgsCAkJXUiw/gApFQZvkihBYUFIROB8QEqF6aYkSlBYEBIS+vhPiwUpndz7znT3pjD/gZewdP32SjaKDFIoLAgJCeoIEhTptPKzoWPdtvQN3LtyMz63cFUFW0UGKxQWhISEHrxJiwUpFdcmZAZfyD927Klkc8ggh8KCkIhA3zgplXwxFr39ae+LhJQJCgtCQoJ1LEhQ5Es37UtRWJDKQWFBSESgxYKUTJ5t03spLEgFobAgJCR0CwUtFqRUVDFhKund18++RSoHhQUhIeEtkBVOO0j1o3Ydkz7tocWCVBAKC0IiAi0WpFRUUWrKCmHwJqkkFBY1yIZtnbj+4Vewa09v2E0hOfAWyAqlGaQGECJ3gSwGb5JKkgi7ASR4zvrxU0gLYPPObvzs4mlhN4dkgVkhJChEvuBNWixIBaHFogaRK9/nN+0KtyEkJ57dTUNqB6l+XMGbdIWQkKGwqGE4mFQXrLxJSsVtsfC+z3RTUkkoLGoY+lWjDbNCSFDkK5BFSCWhsKhhaLGINp7gTU4IpETUnkPLFwkbCosapp8TVbThBEACQrgKZHnftyrYFkIoLAiJCFxpklJRuw6zi0jYUFgQEhKsY0GCIl9WCCGVhMKCkJBgHQsSFOk8dSwsxRfCfkbKDYUFISGh17HgQpOUiit4M0/MNvsZKTcUFoREBK4kSankK+mtQlcJKTcUFoSEBOtYkKBQ+5Jp23Q1L4TCgpQbCosaJBFjclk1oA/vumskKnAiij7FFMgyCw9CgoPCogZJxCksqgGPxSKC9cye3PAuDv/uY/jDmrfDbgrJQb6S3iopU6ELQgKEwqIGsVgOpyqJYh2L2XesxN7eFC67b03YTSE5yJduqmaF0GJByg2FRQ1iUVdUBVF1fZDqI19Jb8E6F6SCUFjUINQVVYIneJMDPimNfFkhqpigsCDlhsKCkJBg5U0SFOk8MRYuYUEBS8oMhUUNYtEXUpXQYkFKReTJCnEJDypYUmYoLGoQyorqQC+IFUVdQY1aHeQr6a1aLLjrMSk3FBa1CCeDqqAa9gphV6oO1J5jcnWkGLxJKgiFRQ3CyaA6qIYYC7rVqgO3K8T7fprBm6SCUFgQEhFosSClIvK5QmixIBWEwqLGieJkRTJUw14hNFhUB+kc6aZCiLzCg5AgobCoQVTzNVcn0UUvkBVFEcgqrtWB+pinNFeIPgYweJOUGwqLGoTle6sDT/BmOM3IDXVFVZCrQJY+BnCxQcoNhUWNQ11RPUTRRE1dUR3kcnXowZxR7GektkiE3QASPOpkwNVJ9RDFW8UYi+pAdaupz3xXTz8efmmL69h+7m5KygyFRQ3iirHg6iSy6DEVUVxJMsaiOlBFqdqNvvir57D8H+9px0avn5Hagq6QGkSdCli+N7p47kwEbxUtFtWBafdSIYRHVKjvE1IuKCxqHA4i0cWbbhq9exWjsqgKTDEW2bI/OCaQckNhUYPkK+9LokkUx3vKiurAVMcim1ClsCDlhsKiBnENMobyviQa6HUsomixINWB2nOkbsjWnVjHgpQbCosaRF2R0GIRXaphEzKaLKqDtCHGIptQpYAl5YbCogZx+Vu5OoksVbEJWdgNIAVhEqnZ+hNdIaTcUFjUIKbVC4k+UVxJxmKUFtWA3nVSacEYCxIaFBY1iEtYRHCyIhmqYhOysBtACsJbEyV7jAWFBSk3FBY1SJqukCpBL70cvXulFluLZAwIAWByq4ms94uLDVJuKCxqkDSDN6uCaqhjoVosmE0QXcyuEPOxtFiQckNhUYMwxqI6ifqtYl+KLqbUZcZYkLCgsKhBsu0bQKJFNVgsVDghRRdPX0qzQBYJDwqLGkP3q3IQiS6eVWbE7xXdatVDJsbC/B7HBFJuKCxqDH3Q4GQQXaohK0Qlxe22I4t+Z1I5hEXULWOk+qGwqDH0ySnqq2DiEMUBn6nL1YHJrZatPzEIl5QbCosaQx9MaPaMLvqdiWI6p9p/KFKjjO5WY4wFCQ8Kiyy8sGkXZt+xEm9s7wy7KUXhSTuL4GRFMphSBKOG2iSudKuHXDEWFIik3FBYZOH8W/+GJze8i0vuXBV2U4pCFxLc3TS6eFMEQ2pIDvqVDhRF4UMyFFPSmwKRlBsKizxs3tkddhOKwuMKocWiaohijIXLFRLB9pEMXrdadqHK+0jKDYVFjSE0CwXNnhGmCupYqMKCFovo4kkzz1XSm/eRlJlE2A0gwcLgzeoh6tum61tvsy9VD6xjQcKkKIvFggUL8KEPfQhDhw7FqFGjcN5552H9+vXlahspAbpCqgfvjpTRulesiVI9eERqmhYLEh5FCYsnn3wSc+bMwbPPPovFixejr68PZ5xxBvbs2VOu9pEi8QZvchCpFqI2b+tBfpyQoospGyzb7WLwJik3RblCHn30Udfvd955J0aNGoXnn38eJ510UqANI6XBdNPqwVMtMWIDvsdiEbH2EQeP9SsNWJb5fkXNMkZqD18xFu3t7QCA4cOHZz2mp6cHPT099u8dHR1+TknyUA21EUiGqG9CpotS9qXqIS2Ea8t7Fd5HUm5KzgpJp9OYN28ePvKRj2Dq1KlZj1uwYAFaW1vtf+PHjy/1lKQEIjZXEYWoB2/qe4NETfgQB29fYvAmCY+ShcWcOXOwbt063HfffTmPmz9/Ptrb2+1/mzdvLvWUpAD0okscRKqHqJX09losQmoIyY/BUklhQcKiJFfI3LlzsWjRIjz11FM44IADch6bTCaRTCZLahwpHsZYVA9SSMSsjLUiagO+3p5+lnGNLCbrV9a9QjgmkDJTlMVCCIG5c+fiwQcfxBNPPIFJkyaVq12kRExpZySayDsTj2W84VG7VbqwoK6IPgNdKefuplETsKT2KMpiMWfOHNxzzz34wx/+gKFDh2Lr1q0AgNbWVjQ2NpalgcQfXJ1EmIFbE7MsANnrDoQF61hUD7LvxGMW0imBdFogbZnDNyksSLkpymJx2223ob29HTNmzMDYsWPtf/fff3+52keKxJt2xkEk6jgWi2jdK28dC5osoopu/cpV0jtq/YzUHkVZLKK2oiJemG5aPchA2/jAyjJqwZHeOhYhNYTkRT73si8J4XWLSvpTHBNIeeEmZDUOx5DoIieDWEQtFiyQVX3IvpRKi6zWyqj1M1J7UFjUOHSFRBd7lRmTq8xo3StP8GbE2kccbOuX4gphSW8SFhQWNQbTTasHORnErOrICuGEFF3kY55QRKouVFsaMp5vWp5IuaGwqDFYIKv6iA88hVETgdzQrvqIKfE68nY11cfxrY99APM/9gEAtDyR8kNhUeNwMogu3oC7aN0rPQuEIjW6eGuiOHUsDhzRjC+e9D4MHbBYMHiTlBsKixqDrpDqQd4ZO3gzYlkX+gREYRFhtHiddNqxXcqiWXErmkHCpPagsKgxWHmzetCDN6M24Hv2ColY+4iDHryplvSW7pG4kjFCSDmhsKhxOIZEH7uORcQm7nKnm761ay8nuYBR+5K6Fw1AYUEqB4VFjaH76aM2WRGVgYE/5hQ1ihLlFBaPvbwVJ/xgCS67b3VgnzmY0WuiCCFs15o1IDZisWgKWFJ7UFjUGHSFVA968GbkXCFlFBa3LnkDALDopXcC+8zBjLwzCbVA1kB/kluGyPcYvEnKDYVFAUQtWj8XLOldPXiCNyN2q8pZIIs1MYJFaPEUmRgLuF6LqoAltQeFRQFU8+RMs2f0kXUsomZdKqfFopqfqSijZoXYrjbGWJAKQ2FhQB/gq2t1VXxRo7ue/Se++eDayE1stY691XVEV5J6vw/yOaiuZyr6eK1fTklvi1khpMIUtbvpYMGTZldFD2IhdSw69/VhaEOd/fu3H1oHAJg5dQxOnLxfWdtHHEyTQZTQ2xOk8KSIDRa9pHdKKZAlLRYM3iSVghYLA7W0R4K+1fWS9dtx+Hf/gh899hoAd/zIvr6IVWiqcfTgzahtS+4pkMUYi8hjW7/SwhNjkYhoITZSe1BYGNBXav1RG/FzkC8r5Oo/vAwAuGXJ3wEAe3tT9nvJBLtDGMSiurtpGS131WQFrCZiMl5HOP1JZoVIgdFPZUHKDGcSA9WcWZHPFaJ/l859/fbPckVDKoO9v0NEYyzKGbzJyS04VEGaGFAWarqpt/JmhRtIBh0UFgb04bOazLb67qbeQFT3qNK5r8/+uYcjTkWxgzerJN00SFdINYn1qKPeFjVeR75u6a6QiAlYUntQWBjwVK+s4kEwn8WiQxEWvf0UFmEQ2b1C9DoWzAqJJOqVTBiyQvTgzWpy7ZLqhMLCgD7k9VXRg5jPjaMP6B2KK4TCIhyiKizKmW6qipSoxZZUM+4CWZorxIqmZYzUHhQWBmopxsLzXbRI/y4Ki9AQ2ooyamEHuoUiSItFTInnofXCH6owk8XWUunsm5AxvoWUGwqLAqjmgS+fxWJvryIsqsgyUwsIuFeUUbdYBBljIb8zQEHrF/WuxNVNyOw33MGb1BWk3FBYmKhmiwVyTwb6d+lW0k05wFcWu6hRPJrCQm9PkM8BhUVwqLcpbmeFwFMgK8ECWaRCUFgY0CfnarJY6GNGvqyQfcqgXk2xJLVEXEkRjBKeAlmBts/5LFrKgiMu3WpKVkhM3zZdcZMQUg4oLAzoz1w1R1HrqxN9blAtFj1cOVYUTxnmiAmLlCZCg3wMVLFOi4U/1IWQO910wGIxMMrHFStRxLoaqTEoLAxUcx0LnXyT1b5+ukLCQk4ICTuoLlr9zCtKA0w3VawhFLT+cLlCLG+6qb0JWdwRFlETsX5Zsn47vv3QWuzrS+U/mJQdbkJmoJrrWHhcIXkmg31qjEUVW2aqET3GImr9TAqdeMxCKi0C3t00bfyZ+MPpS9nTTTPvR6uv+eWShasAAOOHNeFLJx8UcmsILRYFELWVZC48wZt52t7dR4tF2CQiGmMh43PqB3IYg0w3Vb+rHstBSidmslgMvBdXUnxrNYBzy+7usJtAQGFhRH/kdF9zNaE3Xd0ORAjh2tGUwqKy2HuFRDTGQgrq+kSwwkcIgT5FTDBo2B/urBBnd9NsdSwAbz2bWsFSrDIkPCgsDOhivq+KHsJ8m5DJ1TGQ+V60WISIHrwZsVVkWhMWQVnu9I+pJotgFFGtlHGlL+lZIS5XSMT6WlDEKCwiAYWFgWLdCVHCa21xv6KuWvpSaVewE1eOlcUO3hxwNUTNJdCvu0ICmoz0ftZHQRsYUjwIpaS3paSbynm3msa0YohzRosEvA0mqnhFpQee6pOBujV6T38abys+yb4q+p61RHTTTcvjCtE/h/3OHyZXSGbb9MxrqvtTCo+o9bWgoMUiGlBYGKilGAvPAKI8d1f/8WX849099u/VXK+jGpETQjyq6aZlslh4Njdjv/OFejVjrt1N3Vkh6vu15ApRxzjGWEQDCosCiJqJOheeGhxa29Xx5E8vbnG9V02xJLWAvNp1ES3prVssgnoOdCHBfucP1UqZMBTIUufahBLcWSuo7twYdUUkoLAw4Km8WUUPobft7kE81+TFegKVRQ78ToxFtK6/XNXarpCAhI/HFRKx713N2OmmaXgKZAGOK6SaxrR8uIUFlUUUoLAwUM17hejog7j6e2NdHABwwsEjAVSXZaYWkFc7qjEWnuDNgNrncYVQ0PpCvZrmrBDn/VhE+5ofXPsdsS9FAgoLA56UzQqtqP72xg585d7VeK+rx8en5BZF6neTqab7tzUC4MoxLAZbuqkuYOkK8YexjkWWGAvVVVIruDLb+mvne1UzLOltwBOnUCF1/+n/bwWAzArjpk8dVdJneESR1nbTgNJYn7FcVLNlphqxgzfj0ay8qRfICi54U4+xoKD1RYEFsgDHYlFL1klVWPSmuFdIFKDFwoCeslnpCXfTzr0l/63eUn01aFoVNycHhAUH+Iqiu0KiJuz0rJCghI83KyRa37uacTYhyx1jUVsWC1YPjhoUFgVQ6ZVkkKdTU2WF4ndVaarPGK5okq4wMngzphQ1ipC4kP0+GXAdC68rhJOBH0zbpqcUV4gazxjV1GY/qP2HwiIaUFgY8GRWVHjC9TO55MpoybZIabJdIXwowyChbmcdoZVkpQpk1dIkFwbubdMz/6ddBbIUi0UNBm+q1hcujqIBhUUB5CqQtXLjTvzH3c9ja/u+AM/nR1hk/rbOsBV3tkmrecBiQZN0ZZFXO67s3xKlAV+2pS4ebLqpHrnPkt7+cGWFKMXMpCVDjbGoxeBN9QL0sC9FAgZvGiimjsWFP18OANi9tw/3fPHDgZw/iIc+EYuhL5VyiYVsn9s0EGPBVK3KIm9HnTLyR2n1rlssgnLTsKR3+XBKdsOzCRlQm8GbavfppVstEtBiYaCUOhYvb+kI7Px+hIUdEBiXvlQ1xsL8N7RYhIO+CRkQMYuFViArKNGjx1REPWhYCIE3tndFKv5FRQ02l11JCGG3t9aDN12uEFosIgGFhYFSYiw69vUFdn5/rpDM/3W2SdRZaWb7XBljwSC6cFA3houSsChXgaxqi7G4ZckbOO3GJ/G9h18JuylG1KsnrROZ4E35mvN+LcZYqN+EFotoQGFhQH/kCtmELMgFgJ/PslfBMW9AYLZVSnOSWSFhIG+HZTmR+1EKoJX9PuiS3rqQiHok/3//ZQMAYOEzb4bbkCyYC2QhZ1ZILQkLdVyLel8aLFBYFEClV1RBDOCmVXC2OcsukEW1X1EcYWEpm0OF2CAN2R3KnW4aJTFVzViWuleIWiDLsLtpDQkLdSVIYRENKCwM6AWycj2E5dhNz9dDP/Cnqt9eujhMFouY5UwcDKKrLPJqW3AG/yhNsh6LRWCuED3Ggv3OD6Y6FpmskAyWoaR31N1PxeBON43O8zOYobAwoD9yuVwELY11gZ/fVx2Lgf/r4gaLhUFY1CdidjzGYLdYbNyxB69v66z4eS0rmhuR6ZU3A9srxLO7aXS+c1UiLV9wFjqptLpXiHNobQZvOj8z3TQaUFgY8O63kb2zNg3sEBokvgwW0mKh1EaQA7nJxVIfjym57dGq/FhJ0mmBj/73Upz+v0+hM8BA3Fy4o/kjLCxYeTPSqJYJKRyEwKApkKU+RwzejAYUFkYKj1pXXQ5BEUSMhWV5BxHTx9YnYm63SYRM8ZVEvebvdvrZXbZ4LFiRHPBlU5KJYDep47bp5cGC4/bIbJtusFhEsJ/5xVXHghaLSEBhYSDfDqEqqsshKPy5Qryr4P5crpB4zPUdBqu/W700lTITq1khsvpmlHzfusUiKFeZ/jl0hfgj67bpA5fZqvXgTWXMo/UrGlBYFECuwb6uDBYLXwWyDJkGciA3DSb1iZjbbTJIB3n1mld6bLIQzRgLueJ1tk0PxlXmjbHgZOAHuZjIZIVkXkunzZuQ2f2sRmMsaLGIBhQWBvRHLtdKTd1ASs8mKZWg5hbdYmFqXp1msRisrhCVSk3uJutSlISFbIrLohVA+zwFsgapmA0KezEBy7W7qbyqrnRTK3r9zC/quNafFoM2TixKUFgYKGavENViEZQZO4isEAvK5lF5skIsy/HxD9ZBXr02lXaFwIrmdtZyVSvTkYFgJiRpoZCrZ1osAsJSsj7SMGeFDNzKWhIW+vPKAM7wobAwoO8VkjPGQnEjBGWG82OmFIr5UxcLpu8hxcdgH+TVS145i0UGC1a0XSFxJ/MpCIuW/I6NdcEGhQ5W1KsXU9JJTZuQSbdnbaWbUlhEDQoLA0VZLBLOQxuYsAjAYgF4/famj5X+86BrFVQb6reutP/ZsqIZVCebUq9aLAKwaMk+lqzjHjVBYC8mAMh1TlqoMRa1vbupDuMswofCwoB3E7LsHVVdDQQ1QAaxmlAtFnKVaYoBkWZuezfUQTrIu1whlbJYKOeMosVCXpN4zLIDAIOwWMhJrbF+oOJrDU9ylUDNLlJjKIybkMngzlq2WFBYhA6FRQHkGuzVPh1U1Tdfc4sSyKXHWJhW4rYrJD64B3k9AKwi5xz434IaY1HZQVEIgf/5y3osemmL5z3Zb2KW4/ILQvjIgnO2K2SQitlyIPtRpkCWY8lw3q89y6Q+rAWxwNvT0+/7MwYzFBYG9BiLXA+hemxQvj1/rpDsMRamOUu6QOpCmtiiggjBYmGLQCV4ttIryWfeeA8/eeINzL1ntec92ZR4LNjgXrknTQNjLApie8e+gvqkBcsp6S2E3b9iismiNoM33b/7tVis2bwbR17zF9z4l/W+PmcwQ2FhoJgCWeqxUfMVe2MszFkhAC0WruDNEGIswsrK2dLenfU9J6vAsl1lQfTxlCYs/E4Efak0Fr20BR0VKsVeSf729x049vuP4yv3eYWfxOQKyRZjIS0WtZSSqY9rfi3Hr73Tgf60wItvtfv6nMEMhUUB5FpRqZ06Cr49J6fdG2NhEhaOK2Rwx1ioV6bCBgsA4cVYqOfT7718L+hN0qR4ciwW/vrcg6vfxtx7VuOMG5/y3bao8Yun/gEAePild/Ieq+6Smy/dtKasRAG7QuTH9fSnfH3OYIbCwkAxwZtRs1g4tRGUFEbpCsmRFVJXg77XYnBX3qzMfXRF89vbplf2+qt9e0+PeyBVXSFBWrT67RgLWSrc32eu3LgTALC1Y1/FNpCrFI0FbHJoKrSWsVhkXnNtQlaTu5sW7rou5vOisFCsVigsDBQXY+EQhS17XatgLYXUNJjoWSGDNQfcFbxZIXeEogHt61/pAX9vryMmunrdAWsuV0iQFgutjoVfQT5pZLP98649NSYs6gsQFkqsjtQQqXS2TciC3ak2CujfpM/nOCyv52AdC4OAwqIAcj6EyltRUriqK8SOsTAWyMocY4uQQRtjobgEKpZuKn+ynGj9Cl//9m5nItYj4dW9JuwYi0DSTTOf0WALC3/fWX3u9tWY+Vq1WGTbMkDNLkoowkF2YwtqjAXs92uFoAtkyevc0xed8bzaoLAwUEyBLNW6EYXAR7XyZkLL9MjtCmGMhSQMd1BcWWlWElVYdCnCQmim9ESAK115fYOKsVAtHvv6aktYNCjCojNfCqQSBKxum65uQhbFQmx+0b+K33FY/jUtFqVDYWFA75aFZoVEwWKhrl486aYDjVU3lZLlmp0Vae0MOMXgdoVUKMbClRo8MHFX2BXSrbhC9riEhXNMXHGFBJkVIs38fSmRdTVeCG5hEf4zWC7a95rdPMZCaylzjIWz2Kih51zrO377qLTsRmE8r1YoLAzog1yujqoe2ZuK1mrJk24qV4oJZxWUHAigq7NdIYPzYUqH6ApRt02vePCmcj41eFO9Hpl00wAtFrLyprIa9/O91RVqrVks1MyEbOm0psVEXzrtxMgoo3zcip7Fwu+Y47VYBPN5UYiZq1YoLAwUZ7FQXCH94T+saiCXN3gz854UEwDwwfFtAJSJLQLunDBwuUIqFbyp3Kt4XK40KzuYqX17rxK8qVpOrFiw/UO6PhqUfujnc3tr2BWiWmCyTXTuZ94RDqZNyOoitifQS2/txge+8yhuXfpGyZ+hLwT9WhpsVwiFRckULSyeeuopnHPOORg3bhwsy8JDDz1UhmaFi+ynhawi1bd6IrHad1IYHYuFu47F8OZ6jG5JYuSQekw7cBgAZ8AJIjivGlEDWyuVbiqxoKwkKzzeq/EN6uTucYXEg7Oo6HUsAH/9rs8VvFnee+fHZVMKqpjIF0yYiatyhIOpQJaTNhyN5/yqh9ahLyXww0dLr3IZeIwF0019U7Sw2LNnD4488kjccsst5WhPRMh0LFX95z4yg980pyBwTQiaMJKr0PpEDH+9/GQs+/optqCoG+RZISphrOZ0EVgp1L6trvw9rpAAg3v14M3M5wYUY9FbXotFpfuGaoHJXrDJG2MhhNNWda+QugArqAaBWm68VPSsEN8FspR001qqUFpJEsX+wcyZMzFz5sxytCVy1MVi2Ie0nROuKn8bYR6Yw8aVFTIwaEslHrcsDG2ocx0fZMnmaiSUOhZK1L4uAiuFer4+l7BwjtFXwn6RYiaZiCFmZc7lp9+5YizKnG7anxIooGZVYLgsFvlcIYDtUgOca2p0hURkAREzjak+8R9j4R7TG2IVvOE1QtHColh6enrQ09Nj/97R0VHuU/pG9qu6RAwYaHp/WriyKexjlZ+jYDpzArksz06GcjFsEkhBThzVSCjBmwP/Z+6VLMVc2evvLuktjK/HXK4Q/31cDvyyomdvf9rXZFDJGIvM96/cRNOjfJ9s383uR4plCVCFhXOsFBZRWQQFYLAIvo6F9lkNlVSSNULZgzcXLFiA1tZW+9/48ePLfUrfyI6lPqTZ3CHRLentmD2leV26QkwPcx33CrGp9DUI1WKRcq/OJGosQTxmBRq8KZ+lRMxS6qdUR7pppbMp9hVgsZCoBbIAJ5jcclksovWcG63AReLZNt1nEH3U9n+qRsouLObPn4/29nb73+bNm8t9St/YFou4ErWeTVigPJ0wiJWrPlnZrhCDsnBcIbRYVL7yZlQ2IXN+VpsRU+psBBK8aQuLWMYqCH+WkHIXyFLnvko/H71FuEIA92KoN4fFIirPeTwAYRF0uql6PZlyWhpld4Ukk0kkk8lynyZQ5AScUFwfqSwPYrk6YX9aoL4EO6EwZoW4001zu0IG54PkirGo1CZkiiiNhRZj4XxXdUBWBYdlWc5KNxBhMeAKiTsVPXt9rDLVFWo5LBZq36i88FOzQrK5QpxYnVgss1+IEI4oMcVYRMG6CrhrbJSKvreTf2FBi4VfWMfCgOxW6so+WzpckK4Qdb4vdQBzctqdVaZcncjPNOkVWdo7KkFdlSc8i4UaaBtmjEWfwRUin4F4kFkhA32sLhZTBEswMRZBb3VdTLG8cqDen/wWi4F9f7Qqqeq4ErUg7SCCN3VXiN8YC/URpLAojaItFl1dXXjjDaeYycaNG7FmzRoMHz4cEyZMCLRxYSMr2aXSIutEH6Q/Lm5Z6B/4vL50Go0lBImprUxoMRbpHK4QOcAPVtOfensrLa5MgbaVwp0V4nWFyK4SZDaBPGcmeNO/C06dJIOeCPRJq9IWC1ednDxuHjlHx2MW+lLCmBVSHzFXSBDCQhfjwbpCaqvgWqUoWlg899xz+OhHP2r/fvnllwMAZs+ejTvvvDOwhoWJq5LdgLAoZMD3q5RjMvcO2V0vhWLB8hT4MlXik0TNRFppwjB3q2cJa9fJbBYLvbhSkMGldvBm3AqklLwqdoIWxvq3rbTwK85ikUGmyUvxEGWLhWmRUyyee+Rz7GTwpn+KFhYzZsyoePW5SqPHKfSgsBiLIB/WUgcw0+6mcnCS/5tiLAa7sFAHk0pdA5PbqtLCIlsdC91tFmQ2gXR7ZLJC/K+g+yroCql0DFJBwkIZrwCnlkWvwWIRtec88ummFBYlwRgLE64BP7cPOMisEHUQ8zuAqZOVs1fIgAna8DAnE9EykVaacAL0vCIwzBWxeu/l9YiXwWIhV5SJWEzZVTeoGItgJwL961baTaZOmlnrWCjjFeCNsXALi3D6WTbKkm4aUElvYPC6hv1CYWFAdisL3o28PMeqgT6+O7TzcxADWEJbZRbiColK4ZxKI0II3pSoBbIqXdI7W1aIvTOmJQMCg8sa6ldcIYkAYjfKGmOhGdrL2Tde39aJ9m73DqaFWCwkFtwi0HnenWNsi0VEJswgLBZ6oLHf78Z0U/9QWBgw7reRzRWi/Nzr0wyrrk58Z4UYYixSmt9cJWoDTqVxi7rKukIAKMKiIqe2Ufu1KhpSiksNCNaiohbIqg/A599XzhgLT/BmeW7QC5t24fT/fQr/ducq1+tp1+q5sPEloedwGitvRsNiEUSMhb1rcyIYN49e0psUD4VFDiwLdmXA7JU3g3OFuDITShzA1Jz2uNZ2JyvE+3d1ml92sOGuY1HZ4E13PEylLRZq/1VdIe5VYBCWBYmrpHfM/2TQ5yoiFXSMhXauMk3Ity75OwDg+X/ucr3uslhkqdHhcYVovk6zKyQaz3kgrpCBJ0mmzAcZY5EvE4eYobAwoJo/43keRLUT+hl0vEFi/iwWgHeV6aQQeh/m+oDUfrXiqrxZ6U3I4NyTcGMsVFdI5n/ZrroCdvot9px18Zjiriv9c10xFgEXyNJdIeWKv1m/zbyHknq+bBuseYI3Y7mERbQsk2rlzVKTAmixiB4UFgbc6aa5o/VdMRY+Hlb9mQpicotrqXwy3ztnuqnPOvvVivqtKx5jYalZFxXOClEGTpcrRMsgisf8uyycczrWEDvdNKCS3kFPBJ7gzTL1DQvmlbu7jkWeGAs7HkYXFs7P0vLUF5HgTbVtfhdT9QEFoAc1pg9mKCwMOMGb6oBagCvEx6Cmf7r/ypvejaPsgDyDX7N+kAdvuvcKqVRJb4cgJthScFksFFHpBG9mfpftC2LFbqebxi3FBVfa56bSoqjJt1g8lsQyPR+6+0JSSh2LuBZjYdqELCqWSXUsKlVUy3uUTGQKCgZZ0pvBm6VBYWEgVy0Iz7HKz37UrZ6LXXqMRQYLXrGgV1NUqRvkrpBQCmTZp3FW7pUeyFwxFq6S3pn/9ZLefleDaUUIZNJN/RXI0vtr4DEW2u/lsljoVgZJyjXJ5d42XVLnibFQ3hsQHUJUvmaKCdV6WmrKsRw77fEuwFg3WixKg8LCgPq4JfLFWKid0Mek7BEWAZjE7WCm/kJcIdFayVQec6xBWc+oCNiwhF2+ypsxzbyuB5cW6xdXJ+Z4ANum689c4Fkh2seVy1WlWxkkarnqfBusqSW93a8rFouEsq16BJ51taWlWywy/wcVJ0ZXiH8oLHLgKjKVNd00mAkpqD0J1MlKj5LWJwuVqO0hUGnUy13plVzGuhSMRaAYhBBaVogpxiLzu110STl+W8c+fOj6v2LuPS8UvHmaem3rlDoWpa5W9SDE8texKM9Eo1oZ1GtUkMVCGzxyxlgYtlWPCqVarbzBmz6taiWk+BI3FBYmZJwC8ufZlyt4s9TgKpMrpK8QV0hAZsRqJcx0UyCcrBz9a6pZB/I9Pd1ULW2/etNu7OjqxaKX3sHqzbsLOqcqINTgzVKDhvVJpD8tAo2D0K9RuUSnaydlu6CdKKhYk/3MZ7FYmLJCgGjsZKwKp1KFjp5uGuQzNFjHQ79QWBhQa0Hky40OTFhoK6OS08GUj/G4QnJYLAZ75c0w0k2d0vFWKMJOX32rpnaRxRWi/k2HUiVyR1dPQedUhUkiFvNdIMv0d0H2YW/wZvljLPSYKEneOhaQqcF68KbzczxmBZrh4xfV0uXXFRJU8CbTTf1DYWHAeVCLW8n3p0XBJmEd/c/8dmjLsrLHWJiyQhLRGWzCINQCWaissFuyfju++eBa7Olxm3nVvSg8rhBDaXu1/HTnvv6Czt2vfG48ZvkuaiT/bkjS2U8xyMyQSgVvuiwWA8+rbh3Z15/KGdOiu60k+kJC30skTFQtUbLFws4KCUacs6S3f4re3XQwYHcsy8qbhmnaWa8hFi/6nJ7PKbFDq8Vy9CjpXK6Q+viA2h+kD5Jrr5AKD7iZOhaVc4VcsjBTNnpkc73rdXVC1gtk6anLgC4s3HtcZEPd2RRwVpmlVjiU16uhLo7uvhRSaRGoOAsqW6sY+rT0cIkQmffkIkB5x/WbbrHQhUV9PIae/nQk4qlc8QwlCkI9xsKv+HPHWAzO8dAvtFgYMPm+s030+gKidNWtfU6pwsI2r3vdOKlcrhDbYhH+YBMG4aSbOuepD6FA2Zb2fa7fe1Np+7vbJb2lsDC4LEqyWCg7mwL+yzDL61UXt+yJJdBaFtrtKJcrRO1y8hqb+qEpmFC1sALuzA/A7QoBzPcyLFQLb6mBkna6aWCVN52fGWNRGhQWBtRSy3oApOfYgGIjdBNnTwAPvXzQpOrW939QUU3xpZbWrWbUr+xnC++izjnwvwUrlOBNfWULeK1bunk9ldUVUpjFQt2ADIBvMSAFSV085nxWgJH8+pNQNtFpcAmkDM+hKeXUMbAOxFjkyAoBKmsdy0cxu7dmQ36CmhXibwwzZ0qRwqGwyIFr1V9mi4UnxsLnQwZYHlGk+81VXNHiESicU2lcO8tWbK+QzP9qSe9yx1ioK0QZOKn2BxlnoVu37M3ClL/v2FdKjEXm+8k9eGzx6zN4M2OxGHCrBDgZ6O6IcolO9Tx2FpdyraUQyyWabIuFJhj13U7rIpRaHkRqpx1jUee4oP18N/UWM920NCgsDKhBdXmFhfZ7qaZsXWEH6grxxFhkr2Ph59zVjHr1K7WPgmrtqlRWiCoA5Dnr4zFb2MiU07Rm3Yrbm5A57VOtDMUGb8rJToqBUr93n2Kx0C10QeBJAy+Tq8olLAbOoa7mG+uziya9jborRLdQOvvShP+cB1GO3S6QpYxhvmoK0WLhGwoLA+p+G46LwDygeC0WpfoJ3b+XrN6Vh0I+aGmRGURyu0K8efSDCVXYhVHquFKuENV90a+4JeQEL03tTrpp5tg6Q6E49Tp19hQXYyHnAL9iQF6v+kR5XCHe4OzyrGDVs+iuEMvKBKcC5slXaEEWuitE34ckEaHU8iBcIfIeJRPBCAtXjEUErlE1QmFhRImxyJvCpMVG+MzmkPhVymrbAXdgnskVEo9Z9uuD8WFyxVhUrKR35n81KyQtyitsVGHR3ZuZJOMxCw11mfPbrpC0bFv24E01BmBfb2ETrm0JsdwxFr0lioFeO3gzhmRd+S0W5VrBmoI3pXEobjmBqaat01ULK+B1hXgtFrmrCVeSIFwhdjG3uGUL4aCKFQa9qd1ggcLCgNqxnHTTbOV03b+X6tsrZ1aI/LxcrhDLsgZ1WW9V2FUsK2Tgf7XmCFBeYbO317Es7B0QEYl4zBOfoO9uasreUGNx9vYVZrGw+2BMi7Eosb/3mmIsyjgZlCv9UBhiLOw4l5iV02IhsYM3NVeIHmPhtyhZkAQSvKmMa0G4w4LasXowQ2FhwBnwFRN1Ft9qUPUnTPUwSkHNNEioVoj+tGe1qOOkPA6+h0kN2Kp45U24XVHlHMxUK0P3gMgwWSx0t5lp50g1uLC7SItFzGOxKO07S0tJU33C+awy1rEol2gxWczk9VUtFrnSTSW6K0S3WCQilBUSRB0LNYvPFmC+qiA7MMaiNCgscmAhf4Es2Qnlw+vX0iAJokOrVojeVNqzCtUZzFun6z7uSqbcWpYTwwCUdzBTv1a3tFgoK2IpLJx000xnaTC4GfpLEBZ67IbfFab8Do11ceezSiy2ZSKorK98uMpIa8Gb8ZgqLEzpps7ECpiyQszBm1GwTAaRgSG/RSyPACu4TXkKZPX2pzH/gbV4dN07JZ+j1qGwMOBU3iw83TTpc1IOyvIhG2TpJmzFYmFlsVhUKuUxiuhCohKDrup+icWsipRaVvvZXiXGwvbh97lTk20BEPdmb7gsFgVO5ro7zq/FQp63oS6ec/ItFb0XlCv90FggyxC8uc90nRX3J1BIVkh0FhCpPJN4IaSV6xREynG+AlkPrn4L967chEvvegF/f7cLs+9YiRsXbyj5fLUIhYUBdQWQbw8HvU69Xz+hpNS8ftWNA0CzWGReM2WFAIN7h9Og92ophGybR5Wz+qb6PaWVQbVY9GRJNzUFRqrlrfcW6grRAoidiaC0CVt+h8Z6b5xIEAQm+PNgirFIF2ixkMh+pFsovBaL6ARvBpMVkvnfsoKpvuqKsTC0SU2tvuPpjXhyw7u4+fHXIyHUogKFhYFctSA8xw7877c0cdDBmxKXxUJbheoM5uBNfW1aiTgTjwgsQ4yATjaLhR4cqAbEAU7fSKWFPRnok0IhG/DpFov8WVe52ae4QoLahErFI/jLJiycn3WLRSbGIkcdC+33+jwWCyk0omCZVCfxUl1YqnvNEcClW5ZcO1anvP16aIOzxZZaCXXX3t6Sz1lrUFgYULtR3oHPdoX428TLEyTmO93UO3Dnd4VEx0RaacKwWEh033g5r786kDsxFjEneLNfppu6+4qeYQR4S04X4g7Rt2MPyhXiirEI1F3hfS67e1O4Z8UmbO/Yl+Vvise9VbdbuMViljNhGq6xuhAC3DEWmTRyzWIRoViqIFwhahmPIKxWntR/7Tq1NNTZP2/vdPrAe10UFhIKCwNOlLFlp2blC970bbHQfi81r18vlqNG8+dzhVRixRxVKlWvwH1O90ntvlbGc6u31lXHIqEHb7qtW2rxITlx66XPC3GHqHEDQADBm7YrJFEmV4j7957+NH742Gv45oNr8R93vxDYedTTyMWJWseiIafFwt1I1fVhLIZn2Kk2LNT+6LcGUKxAl1E+9Krt+niYUITb27u67Z937qGwkFBY5MCVblpgjEXYwZtK3CkAt1jI5wqxo8UHYYxFvlVKec45gBZ0V7ngzYyvOBF3VsT7NFeIs7tpzFN8SLdYGAMLPecf+Fxt2/R+xcVSDHtti4VSICvAlFCT4Py/5f8EADz3z12Bnce0V4jtCsljsZCYrEt6fAWQP26skgSyu+nA18hYLPxnBuUrVqj207cUYfEehYUNhUUOLMscDa8i+5j0UZceG1Geic3kCjEVyAKitTlRpQlqE7hi0IM386U2B3NO54uqk3wyi8VCNaPrFgFdCBRisdD7oMnFUgz7bIuFEmMRYNltr4syVZYCasYYC9sVkjs43FPHQnOF6PiNawmSQOpYwOmrdj8OKCsE8F5zt9vKeW9nV0/J56w1KCwMqAN+XR7ztOzUclIo1QSnzyX+K296J6tclTcB1box+Hb0C2oTuFLQfePlFHamOdGdFeJeLavzku620CfY4mIsMr8nfQoLNd3UqWNRXouFSlDWJXe1x8zPakG7QoI35a1SrRQmi4WduhqBnTuDSTfN/B+zCrPs5CPfPdfFpqSjwI34BgMUFgYcBZw/7sCuY1Hnz4ytD9KBu0L608bJQqUS6Y5RpVKFkHJhu0LKKGpMg6Kp8qYpHkcvPqRuYga4y4VnPb80W9vbsTvVYUsxhXcNbH6WyQoJPsZCN4v39KddVVKDCtgz1U5Qgzf1++Nqoxa3otaxiMe8Q3xDGVxGpRKEK0T9/kHEWORbZGSzWHXu6zO+PhihsDDg2iukwHRTv9HtgcVYeAICnXbl2t0UGOQFsiqcbqreJ1sEVuD6mwbFTFZItt1Nnb6iPwtyUhgykH5XSPVNPSjUVXugyGueSgu8vq0LAPC+/ZrLsruprsP29vS7LEpBTSamGAt3Se/8osmuDaK4QowWi0SOYlsVJliLRVAFsrzur1zvS7oK3OF3MEBhYcC8CVnudNP6hL8Yi6D2CpGYaiPoq0Udv9+hmgmqQFkp57M3j6pIuqn3NVflTU+6qXOcLiykxWJIckBYFBG86RIsJboR39jehe6+FJrq45g0ckhF6ljs0cRTR0DCImcdCzV4M8fuphJ5rPxbnZxVPCuMq6R3iRYUp0psMCW9vRl6miskSzPpCnGgsDBguxOU3fKyrWDlStd/Voj7d79mytyuELOwaBwYkAotz1xLhBG8KTHdq3JhWm25Yiw0V0gsR/Cm/CwpLAoJ3jRZQpIlBj7/9dVtAIBpBw5DPBbMzpY6egyVTkd3MJOJsfKmGjuQK35ECwKW9wlwtrtXadAygMIkmG3TTdkzwQVvelwhWSwWnRQWNhQWObBQeIyF3xoQKc1fXXJJ7xzBm44rxPy3jRFayVQa714hZbZYGF4LK3hTjbGQk7LJbZbNYiELBhXSb/Q6FkDp2TBrNu8GAHz0kFEAgjGD68jrpVoBVIKyWLhjLAaCN5WS3rkCLtWYMMAdEGuyWCSjFLwZSElvRVgEUSArT7HCbBVmGWPhQGFhQA0GUgd7U4fyxliUNinIh6NRWb2VssOmHivgTjfNvJbNFdJQnzl3oTtV1hKVLpDlirHwFDMr3/U3Wizi2QtkqV1FjYVIp4V9zWSMRWHpppn/3RaL0iL55T2SJZaDKOesI++TnNh1OroDcoUoz6033bS4PTBUi0Xc8KxHyhUSQIyFWiU2EFeIbj32ZIWY/44WCwcKCwNqZoWaZ99ncK6ltYGnVIuFFC1JZQDzs3LVy0T39qddvkgTTXUDE0QEBpxKk68oTvDnc3A2ISv/dtYmsRo3BG/Kbux2hTjpyKo52I6xKMIV4rKElGixkJugyT5ejhgL22KRyGaxCGYyybW7aTxPUKJWbDdvjEWjdq/DRP3epaaIqhVKA8kKyVMsL7srhBYLCYWFCUPwJmAesGxXiM/VpuysjfXK+UoQKUJVRXAPtul8rpCBc++jxaKymTFaHYvyZoV4X0u4tk3Xdjc1BFmqIhVQskIKCt40WEK0DdAKRQowXVgEu1GY46KsM8QrBBe8mSMrJJZ7Je488+79V7KRK3W10gThCkkp41qpfUlFXz/qgke3XLcM9H9aLBwoLAyoldzyCQtJY72/VYDszI2KxaKUlZeupdXYD33HSh15bgZvlj/H37ToyVc+Pgiy1bHQ/e52kKUyQqhbp6sTwlA7eLPwOhYuS0iJgkpeJxmgaK/qy1AgS63qqBLUudw7amZ+UYOtkwVYGWyLhdJO0/2OlCtE6Uf9aYH+Evp+8FkheSwW2mAxtrURQMYVWEr7axEKCwOqaTEWs+yASt1Era4ymuv9TcqONSHmbGvsY+XlRIg7vll9x0qdxvrCfeW1hj6YlHvQVc/nrbxZznTTbFkhbh++bIKVxWLRrwoLu45F/nbrdSwAlLwrab9tsch8mL5DaxCklbFA344cCM464ioTraX85rVYaL+r7ew3BAQ48TThT4K6W6GU66m61/QKsqWg1sUA8lfeHNPaYP/MWhYZKCxy4KkFoXUwtX/JSbnUCUk15/lJO3RWWO52dfeljOZtFVosHModMe+qYzHwf2XSTb2vubIOsuxuCrj9/OpK06ljkX9QNVnNSo2NsC0WA2YV+R2CFMamqo4qQQWKumINtHTemOXN2snWRsAdV2EqiFYOAVYq+iRdyr2zLTsB7W6qB+zm2isEAIY319vnpTskA4WFAWUtCUD1faeyHAc01fsb1IQy6Ze6gsu0yd3pG5XBVmhKXEfGWAzGrBDdN1Hu1Zx6OjkR5NuXJgjy1bGQmzcJgwhV60SoK+GmIoI3TZubyXMX2+/skuID161pQETrMSB+cMIXrLJaLFRLkrwOdgCtYZM4YxsNn2vaGj1arhD376WMPWqgseMO858Vkm1jSd2gOGpoEkMHUq4pLDJQWBjQV/3OSjK7K6TRZ6qmanr2o7r1CPEm20XTr9QQyGaxKDwIr9bQh99yD7r9yogqhUVDGeow6JgmXHWl1ztgjTClJquCVwqERMwqSlTrZmZAEeVFXnPpz5YuGvk5QHB9WLXcqBaLoDc8U/WebTWyS3q7Y7iy1VEwPdem+51UCmSVktIeJLorZE8BcTo6rtLndf6tfnamX5YFni7ORw5JKgGczAwBKCyM6Kt+vdyxc5xDs19XiOJPbar3P8E7rhBn0DeZt1X8iqNqRh+syy2u1AFfWgUafcbpFEK2oFG1TkNPliqtqviQ1oJYzCrKhWb63GYZ/NlT3PeWMU8JJStEfmwhgaQFYQt1d/DmsKbMCjU4V4hisRi4jmpJb+luAryTby5tkKukN1BeEVsI8jlotsep4u+b4woJaBOygf8bsgTk62PFR6fsZ8cZ0WKRgcLCQNZVf2925drkc1JQt5OWA/UeH4FAMnhTbXu/lp6nM5hjLPSxudxZIaorQQ7+yQqYqE2ukGQibq/O5PlNqcmu8vByUo9ZRQlSU7aJ7KPFrladGIvM9bMsReQEJI4dy407KHJYUz2AAF0hys97bVeIO9tBfs89HgE2YIk0fO7Bo4Z4XmtQBFKYO5yq1hKZsuz9bvkxb9ZW+v2X91z2S/2zpJA5Zcoo/GnuCTh41FDHFdJDiwVAYWHE8atm/s+WLaGO0aqwKMW8qK7ksgmZQtDPrbZLT8/T8XPeascTvFlmcaXWKJAmbDm5lzO+w2RFTyZiSMSdiaun35yarAZvOsWbHAtbQa4QQ5G2Ui0WUpypQtlvrJOOmnqeLKOwUAWfp5bIQB+R16lLm7x0163Kxz84zvNaXdyyxWyYAZwpQwBwKffNXdI7gGdIq4LssVgMNHv/tkYcfkArANBioZHIf8jgxV711+U308nBVYjMYJOtBHA2XKllAUS326Koznlg5QCciJn1ZEOdWxxli8WoRXRBVu4Bt1+535JKuELMFgsnq6Krpx/7+lLG1GSXxWIgRiQet4raY8ZU0tu3xSLuvYaBCQvFeukSFs2ZFWpQgbbuypsCfam0q6Q3kJl827v70JVFgFmKzeLReSdi7Vvt+MRR+3uPsyw0JGLY05sKNYBTja+QK35/rpDcu8AWirwX2YJc04Znl8LCDS0WJrT0rWwreXe6qRI4VpKlIfN/zLIKEjL5PsfUdjkQ1yey1bFwvkMUctzDoFI7P6YU86197gAi2vNhCvxThQWQPR5HraUgg42LD970fm5zifVTpGtPLWIny9IHNWGqlUJbGuvs1x2LRVACRs9KSnn6iFzVd2mTl8k+OmVMCy44Znz2fYEiUNZbzQiRE7O+LX0xnxO3nD1v+lKlFdsCHCuV4woxl/RWL+2QZKZvBFWJtdqhsDDgdYWYB041yLMu7lTpLGXFqa5OmpKlr7r0QaZJCYrqt/3iuWMsgMEXZyEnkCafQbiFou9mC1RmsDe5QqQlojnp9BU5z2Xb3VRmtWRqLBTuBjS5WGR/L7a4kGyDarFoCNwVkiFmWbaYABRhUYasECCzEFBN/IATh6BfJ72MfyFEIeU07bJYSHdYCRYLxb0m+xJQ+p5HehXkrBYLy2ux0EXfYIXCwoD+kGcLzHQXOXKK2JQkLJQNhxzTcOmWDznKyIE2LZwBKVuMRTzm5OoPNmEhr1ulto63XSEuM375r3224E3AsRzsUSY1yxVj4Vhz1EDgpiIsXabPdSwWhQ/KQggnKySmWixKt/aZT5T5z7KAtibHYjF6oNpiOWIsgEwf0DeCc2IsdItF9uDNbCQjsF+IaSO7UsY8NSukPq4GuZbWB+ydpqXFwhNjQVdIPigsDNiV7OzMCvPApw4FluUvXdPJClHSTX0MjrYrRLFCSDNdfbZdyKBkhgQ1MFcJeiR4GK6QXEWQgsJkUUhqFos9Pf3KKtA5zn4O+lIua4Fq6co3oeesY1FE8KYa+KduDhZ0ALIqhFoaHGFx0MhmAOWpvAlolXIHHle5J0u2CbOYkCi7rHeI6aaqW07GWJQy7qglvdUg11IyTFSconFaVoih3H2LXSCLrhCAwsKItujP7gpRBmnL8rfaVavs+Yls11cviXjMFhKyuYkcwsIZmAdXjIUcxO1BqczCSk7McaMrpJwWC+9rjivEmbjkcarwsV0lPf2KtcByFdjKZ21Ry1Q7n1v8NVf37VH7c9ABsGrwproZ1fjhTQCCsVio44gqjFJakGBzFpdRypBpk48o7HDq2sjOR4yFLtJlTQzfFossO6WaUrFpsXBDYZEDu45Fltx4dZC2YLn25SgWNajNl7AwTBxqUCbg9ut7jh2ktSykaV8WPvJTQ6QQ0krwo8Surljhkt4eV0hPv1Jvwuuy2NPT76mJUqilwE43VUaeUtJN+5TIP5PFIqgYCzV4c3izE2Mh29zbn/a9aZx6S5qV8ui6YMjmCslXn8ZENGIsMv9bluIO8xNjMdBXm3wuDjxu0SyVN90xFizprcJ0UwNOZoW7IqJnsFKFhQU0DqwC/OZiN5bgc9axNFNze7djojPteSBpCNpHXSXIyUEG5fWlBHr70zmvlR/s4EfVYuFK5xTGqol+0UsoA97gzT29arqpc1yz4gfv0ywuTfUJ7NrbV4DFAgOfqwoWJ9200DRndQ+MOkWlBF0gSw3ePO+D+2P1pt04cfJIu4QzAHR092HEkGTJ58hWaE/35Q/NkhUi+25dltgpE5WKJcqFar1qUvpe8Z+T+T+uCbBi66JIUlqMhX6NTKnYQ1nS2wWFhQE9yDpbASDX1tfI3hELQV2dNPtyhcj2eFfCklwWi8FaJEsOzmpK4Z6eftQn6rP9iS9MWSGynwGZiUUt4xwUJouWdGM01XtdITGDK0S1WEg3REOBotq02pMrzLQovAaMTCWMWW5xlq2YXamorpD6RAwLzj/cfm9oQwKd+/qx26ewUG+JWs4/m8VCt6b1GQqF5aMpoDgEP6gujOZ6x1JT6ufEdFdIiYsj2bdl3ES23U0ZvJkdukIMZK9emb1Gv99ywupA7suca5g5mnRhkWMAymZurXWkz76xPm5PtOWMs9D950Bmcpa/lssVY6pjIS0WQ5JeV0jcEAvRnxa2RatOsVgA+fu+WrpeogZ/Fvq95WSq9+Vsz2qpCENMiERmieze62+Vqlos1EVFSpvAsqWb9vXLQNrCh3M/e3MERUpxi5VaJA1wZ4UAqkAuTTQ5iwyzSLXrZiid2L43vf1ZN4kbTFBY5ECvY6F3VFdWCOAvxkKZaPysumyLheoKqXOvfHOZTAer8rbNybHgospzYRIW7oj2MgmLHBYL1dVhKgKkZhhJ15pMXS40NsfkCokrG5kV2uf7lfulErTFTQ/kVmlrzFizOrr9CQvX1gBJp46KXktkSLYYi3TxrhBnARGexcL+fmpZ+BLaI3QBlvQnmmQ11eHNSft3NfvH9GxI64YQGXEx2KGwMKBvQpbNTOfNCvFfxyITyOR/NaEOMQ2axSKXyVQGIQ22CnLO4BxTYg3KN0A4Jb3d96LZ52orH3J1rMYIyBLyqqvD5ApJxGO2y0Ou0mVfKrSUtikrxHXuAq+5HPyTmtukoUiBkg99LFBpHXCb7e7uDeQcgPPsm4I3h2RzhcjgzSyF70zYcQhhWiyMMRalB29K61qTT6urzP4Z3uy4RdWFlqlAVjIRs4Udi2RRWBhRNx4ClEFTd4UoP/t3hTid1c9+B3rgKeBeaQK5Yyyk+W+wWSx6+wcG50TMlf1QLkwxFkDxE2yxyH52zpHj8L79mnHAsEbsNxAfIL93V0+/0Y+sHmNbLGxXSHEWC70LFmu+ln5vvSaL312GdbIJIQBoLYMrxBxjkXlPioFOrV9KkVWXpVS/CSlgwnR5qtkcpZZ1F0I4fUqm5frMDJLWy2Qibos5l7AwPBuWZTEzRIHBmzlwgjdz7xUix5wGH2ZY1RVSqL/ahDDsHKDGWCSU3TRNDNZCL3bBp5iVdWUYJHqKnKTcK0k5KI4cksRf5p2EtDCV9E7ZLjFdADQnE3hvT689mUq/fqGF1UxprIC79LyJt3btxaPrtuLTx01AU33CNk3LCpLezwnWFWJ6ZNoayxBjkXTGEH0Ck8+m7npx+m7xFotyp1XnQv1+Q5SsimI2QFRde3pWSKmiSVqA6hMxDG1IoKun33XNU4bFG5BxI+/c0zvoxk4Tg95i8ZvnNuOaP73sCrjRa+9nG6ycCp0Dx9X52EhH6ax6+p1f1Pr5+SLHB3uMRX0i5pi4fU4YuejPZrGoL6/vW3VxJOIxVzqtOtmYUuoA51mQFgtp/i3UymZKY9XPbeKL//c8rnv4VXz3jy8DyG6xCD4rxNxewAnebPcbY6H8nCsrZOSQTEzHzj29ruJS6kRYKM0+9iMKCtUaJEVaX0oUZW1Sr4NjsfBXE0N+Zl08piy0TK4Q998O1rHTxKAXFl//3UtY+MybePy17fZr+lSuVvNTJ3pnNeOO2i5lFeAE8znnk1uwF4NuRQGcuAkg+z4hzrGD8+GwXSHxmG3i3lVGYWEK3gTc1S3LgRPo5n3Pdkf0mmMsAMfP32G7QrwZJbnI9rlNWQKkJa++0wEA+M1zbwFwngvdYuEEOAZz70ybpklk8ObuvT5jLJRHXI2x0C0WskBXWgC7lHPa28cXUfdEdXuFherqaaqP2yK1mOdOtfboLqNSFnhqsTNpsQDcFtxsz+5Q7nBqM+iFheQf73bZPzsBW+5UOiHce0jogV1DfZjg1BgLtZ5BsSLFZN9oVWoz5LVYJOkKkUWy/E4YhZ5PpdzpvjJVzmRqHqJkw2QTIDIwTgYsSqFq8kUbz29IY1X/vlAXUG8Wi0VLwMLY5FqU2DEWPi0WrhiLpGNx0SewRDxmV4Z9r8srLIqpY+G3iFQQqGmblmWhrYTnTr12eunzUhZ4atn2urhlCwtVLJg20gMG76LMxKAWFqr74709Tmd2gjczv2fbZEk/boiPrXPVzhqPOe6QjiI/SxdFgFtY5FvVyAJRxZ632lFdIcNsi0X5hEW24MhCJ2i/5zWtwNW9KLK5QmQqn+0KGbBY2INqnsHcVMcCcMR7NheQmsUCKBaLhDswWQ2gC8KNKCc/s8UiGJeZ2srWRmfVq+9uCmRiYwBgR1eP/VqfbW0rJd00GlkhgHM924u4ni5XiOVeCJZksVAsxHWxmD0e5gveBKDEiQyusdPEoBYWqi9PXQHolgg1z159EGWFNj0dLN/gaiKlqHcAtnov1X9ryrEGiomxGFwWC3ULbmflVMYYi5R5cJITi1+/fTZSWSZ2wDGP9/an7ZWbJy104Bh5beS274VGxJvqWAD5aw+o1Tj7U2nHYqHFFcjBPZUWgexQmzN40+czKlFX3a2KsDdtdmUUFukSLBYRKJClT9BtJbgglS1jArVY1MUzm+s5Fgvns0w7EwODN/DdxKAWFmrgkukBU/uN/cB3O8fJQVQOqkMbSvfvprUBv6XECUbf3RTQXSGFxVgMVotFXVx1hZQ/xkK3IKkr1nKQK2ZArmIBp2/rc5U8RloMZIGqIQUK0mwWk3y1B9RYivbuPicrRBMWzfVx+xkKYoDXA7RVnMqb/ixb6rPfolxH066lIwYCOHe4XCFOfFChVKIIXD7SafeYZwv6IuqCqHvfOLublh7r1tfvvpZDDZk49iJEG0vpCnEY1MJCTec0dQbVnSDrO6gTvRy45GAw1I8rREs/dMysRQ5aBuuvKizUvTBMyAdJrzZX69g7RFbIFaKbgSWOgC2PsLAnMYPJoj4Rsy1z8rtnK2QlScQ1V0iBFgtPGqtcQWeZ6OSAL9smt7LWLRaW5aQLByGOcwdvOuLfVxlnxYrToixg9JLegNli0V/CJmT27qyK9afS6CnXpbiWTFkhLT6eoV4tXsWUFSLngFZtLB2apeT6YGRQCwu14JUqGEy+WdNK0rZYDLw3ZCDwsauneP9uSgtq8zvBmKwt+s8mhhhWrYMBp6R3ZbNC9FVPqZaqQsk2sUukqNo5sCL2ppu6Yx1k+ws1A2erY2H7/LOY5nW3ZW/KHGMBOOI4iAFej6NSkfcqLfyVcVbvSYsyzqQN2Qcy5fQ91RVSSvBmvTlurJLoY14pFiBTzI7sw3t6U0WLJv1amoI35bMp2yuRz0C5nt1qoiRhccstt2DixIloaGjAcccdh5UrVwbdroqgukLUjmNK2TT5vjt7zBaLvpQoOj88rZk9S93gSE+BBYD9hjo7L+YL3owrBaLKtWqOImZXSG8gAYAmnBgL9yNY7hiLXMGbANA68N1l4JveXeS1kejBmx3duUV11joWeWoPuITFnuwWC8CZnIOwODkLYu/1aqiL2xaeYgIOvedwAmXlWNLbn7bHEHPwptcVUswmZIl4zHYjhbXC1vdCKSW2yWTVaWmos/ttsRZfu1T8wLVxgjedNsnP1Bdpo1oy92Z7576izlmLFC0s7r//flx++eW4+uqr8cILL+DII4/EmWeeie3bt+f/44ihukJcFouB/00BkOpkK+Mt5KDanEzYne2tXd1FtUUvSytz1rcV2UlNg7q6bXohdTFaBmGcRZ/LFZK59v1pUbZB1wkAc79e7uJcul9bp00bLPUAtXFtDa7fpcVidEsDLCsjAHbuyT6YZ6tjIZ8hk5UolRaulefmnXvRmzLHWADA/m2NAIp/Bk2IPBaeIHY4tccbZASWPNd7ezJWCXXSlJPXlt3Od+srwRUCqFVew3F56plHbSWk75riUGIxJ3W1WKujfi11F18qLezg/NZGt8geNTTzbGzr6MFgp+iS3jfeeCO++MUv4pJLLgEA/OxnP8PDDz+MO+64A1deeWXgDSyUd9q7Xf62Qnhr1177547uPmzeuReWpYoHNcYi0+nXvt1u/518uGXtBwCYMLwJa99ux5rNuzz+6FxIRSzHkMmjhwAAXt7S4Wpn/s/p11ruphDT4AHDmrClfR+ee3OnbXqtdfYNrIjrYjF76/Se/jTWb+3EmNaGPH9dPDsHVj26xWL8sCYAwPbOHrz6Toc9sAWFtERkK5msm3fHD29y/S4nbYk0GTfUxTG2pSHTb/65C4eNazGff2BQ1ifqg0Zl+vuGbZ32cyjRS9u/+k6HnSViEhbjh2fa+No7xT07JqTVI1uF6dbGOrzTvg9r3tqNYc253YzZ2NqeWTzErEwmwqSRzfj7u3vw6judANzibvKooQCAv7/bhU3v7UUs5lzTYlwhQCZeZuceYOOOPa6y/5Vie6cUTpnfZcGx17YWft+27N438BnuG9TWVIede3rx+vbOosbhLQP3Ql7L4QMC5e3d3di8c++AmztzrG6xGN2SGSd2dPXY9yZMxrY2eq5LpShq1Ort7cXzzz+P+fPn26/FYjGcdtppWL58ufFvenp60NPjKLiOjo4Sm5qbj//0GbujlkJaACf+cInrNXUwmTIm80AveukdLHrpHddx6uAvhcU3fr+2pHbIQeSQ0ZmBefWm3TjhB0ty/YmZLP2psYABZNrEYVj55k5c9/CruO7hV4s/dxUjV+DDmuqxtWMf/t/PzP06KPS5oLWpDgePGoI3tndh5k3LynbebK4QVVjUJ2I4ZKDfS8ZqwkJ1rR04ohlb2vfhS79+vujzv29kM5KJGPb2pjzPoc5Da7a42qgjxdndKzbh7hWb8ralEKwsD9R+Q5N4bWsnrnponf9zDJziyAPa8Pd39xj3kzlgWCOGJDP7V5z0I/d1KqbyJuC4nwq5X+VEjnlSmG3e2V30mKdb1oY31eMf2IO596wuqU1SWBw6rgUtDQns3tvn6pdN9XFP3xvRXI94zEIqLTz3JgxWfutU24pSaYoSFjt27EAqlcLo0aNdr48ePRqvvfaa8W8WLFiAa665pvQWFkiyLmZcveSjLh5DV0+/528b6+M4dcoo+/dPHL0/fv/CW3jprXbXcUMbEjj1A871OPeD4/D0GzvsFXAxtDTW4YTJIwEA7x89BB9+33Cs3rS76M8Zkkzg5Pfv53rth//vCNyy5A18518Ozfv3531wfzzwwltlTbeMIlPGDMVB+2VWzucfvT/ueGYjyhRiASDTx077wGjP65+dfiB+8Mhr9n4iQTNySBLHvW+48b0zDhuDR9dtRXdfCp8+9kDPKnhIMoF/OWIsFr+yDW1NdfjIwSPt984/en+se7vdVb3QxLCmehx/0EjXa4l4DLOOOxD3rPxn1mt+7KTh2LRzr73CH9pQhxmH7Oc57pQpo/DLpze6Mif8UJ+I4YzDvPcJAOadNhkbd+zBuz4WNZKPf3AcAOD8ow/A0g3vYk9PP0YOSeLYic69siwLsz48Ab/625uu6zSurRFHHzisqPOd+8Fx2PTEG0VbeoMkHrPwscPHAgA+OL4NJxw8Es/9c2fRz925A9dO/f21rZ2uEt3FtOlfjsy0qS4ew7+f9D7cuvTvruv0r0cf4Pm7WMzCBdMOwIOr3y76nLWGJYqITtuyZQv2339//O1vf8P06dPt17/+9a/jySefxIoVKzx/Y7JYjB8/Hu3t7WhpMZtLCSGEEBItOjo60Nramnf+LspiMXLkSMTjcWzbts31+rZt2zBmzBjj3ySTSSSTSeN7hBBCCKktivId1NfXY9q0aXj88cft19LpNB5//HGXBYMQQgghg5OiQ84vv/xyzJ49G8cccwyOPfZY/PjHP8aePXvsLBFCCCGEDF6KFhaf/OQn8e677+I73/kOtm7dig9+8IN49NFHPQGdhBBCCBl8FBW8GQSFBn8QQgghJDoUOn8P6r1CCCGEEBIsFBaEEEIICQwKC0IIIYQEBoUFIYQQQgKDwoIQQgghgUFhQQghhJDAoLAghBBCSGBQWBBCCCEkMCgsCCGEEBIYRZf09oss9NnR0VHpUxNCCCGkROS8na9gd8WFRWdnJwBg/PjxlT41IYQQQnzS2dmJ1tbWrO9XfK+QdDqNLVu2YOjQobAsK7DP7ejowPjx47F582buQVJGeJ0rB691ZeB1rgy8zpWjXNdaCIHOzk6MGzcOsVj2SIqKWyxisRgOOOCAsn1+S0sLO20F4HWuHLzWlYHXuTLwOleOclzrXJYKCYM3CSGEEBIYFBaEEEIICYyaERbJZBJXX301kslk2E2paXidKwevdWXgda4MvM6VI+xrXfHgTUIIIYTULjVjsSCEEEJI+FBYEEIIISQwKCwIIYQQEhgUFoQQQggJjJoRFrfccgsmTpyIhoYGHHfccVi5cmXYTaoaFixYgA996EMYOnQoRo0ahfPOOw/r1693HbNv3z7MmTMHI0aMwJAhQ/Cv//qv2LZtm+uYTZs24eyzz0ZTUxNGjRqFK664Av39/ZX8KlXFDTfcAMuyMG/ePPs1XufgePvtt/GZz3wGI0aMQGNjIw4//HA899xz9vtCCHznO9/B2LFj0djYiNNOOw2vv/666zN27tyJWbNmoaWlBW1tbfj85z+Prq6uSn+VyJJKpXDVVVdh0qRJaGxsxEEHHYTvfe97rr0keJ1L46mnnsI555yDcePGwbIsPPTQQ673g7quL730Ek488UQ0NDRg/Pjx+OEPf+i/8aIGuO+++0R9fb244447xMsvvyy++MUvira2NrFt27awm1YVnHnmmWLhwoVi3bp1Ys2aNeJjH/uYmDBhgujq6rKPufTSS8X48ePF448/Lp577jnx4Q9/WBx//PH2+/39/WLq1KnitNNOE6tXrxZ//vOfxciRI8X8+fPD+EqRZ+XKlWLixIniiCOOEJdddpn9Oq9zMOzcuVMceOCB4nOf+5xYsWKF+Mc//iEee+wx8cYbb9jH3HDDDaK1tVU89NBD4sUXXxTnnnuumDRpkuju7raPOeuss8SRRx4pnn32WbFs2TJx8MEHi4suuiiMrxRJrr/+ejFixAixaNEisXHjRvHb3/5WDBkyRNx00032MbzOpfHnP/9ZfOtb3xIPPPCAACAefPBB1/tBXNf29nYxevRoMWvWLLFu3Tpx7733isbGRvHzn//cV9trQlgce+yxYs6cOfbvqVRKjBs3TixYsCDEVlUv27dvFwDEk08+KYQQYvfu3aKurk789re/tY959dVXBQCxfPlyIUTmIYjFYmLr1q32MbfddptoaWkRPT09lf0CEaezs1NMnjxZLF68WJx88sm2sOB1Do5vfOMb4oQTTsj6fjqdFmPGjBE/+tGP7Nd2794tksmkuPfee4UQQrzyyisCgFi1apV9zCOPPCIsyxJvv/12+RpfRZx99tni3/7t31yvnX/++WLWrFlCCF7noNCFRVDX9dZbbxXDhg1zjR3f+MY3xCGHHOKrvVXvCunt7cXzzz+P0047zX4tFovhtNNOw/Lly0NsWfXS3t4OABg+fDgA4Pnnn0dfX5/rGk+ZMgUTJkywr/Hy5ctx+OGHY/To0fYxZ555Jjo6OvDyyy9XsPXRZ86cOTj77LNd1xPgdQ6SP/7xjzjmmGNwwQUXYNSoUTjqqKNw++232+9v3LgRW7dudV3r1tZWHHfcca5r3dbWhmOOOcY+5rTTTkMsFsOKFSsq92UizPHHH4/HH38cGzZsAAC8+OKLePrppzFz5kwAvM7lIqjrunz5cpx00kmor6+3jznzzDOxfv167Nq1q+T2VXwTsqDZsWMHUqmUa6AFgNGjR+O1114LqVXVSzqdxrx58/CRj3wEU6dOBQBs3boV9fX1aGtrcx07evRobN261T7GdA/keyTDfffdhxdeeAGrVq3yvMfrHBz/+Mc/cNttt+Hyyy/HN7/5TaxatQpf/epXUV9fj9mzZ9vXynQt1Ws9atQo1/uJRALDhw/ntR7gyiuvREdHB6ZMmYJ4PI5UKoXrr78es2bNAgBe5zIR1HXdunUrJk2a5PkM+d6wYcNKal/VCwsSLHPmzMG6devw9NNPh92UmmPz5s247LLLsHjxYjQ0NITdnJomnU7jmGOOwfe//30AwFFHHYV169bhZz/7GWbPnh1y62qH3/zmN7j77rtxzz334LDDDsOaNWswb948jBs3jtd5EFP1rpCRI0ciHo97Iue3bduGMWPGhNSq6mTu3LlYtGgRlixZ4trafsyYMejt7cXu3btdx6vXeMyYMcZ7IN8jGVfH9u3bcfTRRyORSCCRSODJJ5/EzTffjEQigdGjR/M6B8TYsWNx6KGHul77wAc+gE2bNgFwrlWucWPMmDHYvn276/3+/n7s3LmT13qAK664AldeeSU+9alP4fDDD8fFF1+M//zP/8SCBQsA8DqXi6Cua7nGk6oXFvX19Zg2bRoef/xx+7V0Oo3HH38c06dPD7Fl1YMQAnPnzsWDDz6IJ554wmMamzZtGurq6lzXeP369di0aZN9jadPn461a9e6OvLixYvR0tLiGeAHK6eeeirWrl2LNWvW2P+OOeYYzJo1y/6Z1zkYPvKRj3hSpjds2IADDzwQADBp0iSMGTPGda07OjqwYsUK17XevXs3nn/+efuYJ554Aul0Gscdd1wFvkX02bt3L2Ix9zQSj8eRTqcB8DqXi6Cu6/Tp0/HUU0+hr6/PPmbx4sU45JBDSnaDAKiddNNkMinuvPNO8corr4h///d/F21tba7IeZKdL3/5y6K1tVUsXbpUvPPOO/a/vXv32sdceumlYsKECeKJJ54Qzz33nJg+fbqYPn26/b5MgzzjjDPEmjVrxKOPPir2228/pkHmQc0KEYLXOShWrlwpEomEuP7668Xrr78u7r77btHU1CTuuusu+5gbbrhBtLW1iT/84Q/ipZdeEh//+MeN6XpHHXWUWLFihXj66afF5MmTB30apMrs2bPF/vvvb6ebPvDAA2LkyJHi61//un0Mr3NpdHZ2itWrV4vVq1cLAOLGG28Uq1evFv/85z+FEMFc1927d4vRo0eLiy++WKxbt07cd999oqmpiemmkp/85CdiwoQJor6+Xhx77LHi2WefDbtJVQMA47+FCxfax3R3d4v/+I//EMOGDRNNTU3iE5/4hHjnnXdcn/Pmm2+KmTNnisbGRjFy5Ejxta99TfT19VX421QXurDgdQ6OP/3pT2Lq1KkimUyKKVOmiF/84heu99PptLjqqqvE6NGjRTKZFKeeeqpYv36965j33ntPXHTRRWLIkCGipaVFXHLJJaKzs7OSXyPSdHR0iMsuu0xMmDBBNDQ0iPe9733iW9/6lit9kde5NJYsWWIcl2fPni2ECO66vvjii+KEE04QyWRS7L///uKGG27w3XZum04IIYSQwKj6GAtCCCGERAcKC0IIIYQEBoUFIYQQQgKDwoIQQgghgUFhQQghhJDAoLAghBBCSGBQWBBCCCEkMCgsCCGEEBIYFBaEkECYMWMG5s2bF3YzCCEhQ2FBCCGEkMBgSW9CiG8+97nP4Ve/+pXrtY0bN2LixInhNIgQEhoUFoQQ37S3t2PmzJmYOnUqrr32WgDAfvvth3g8HnLLCCGVJhF2Awgh1U9rayvq6+vR1NSEMWPGhN0cQkiIMMaCEEIIIYFBYUEIIYSQwKCwIIQEQn19PVKpVNjNIISEDIUFISQQJk6ciBUrVuDNN9/Ejh07kE6nw24SISQEKCwIIYHwX//1X4jH4zj00EOx3377YdOmTWE3iRASAkw3JYQQQkhg0GJBCCGEkMCgsCCEEEJIYFBYEEIIISQwKCwIIYQQEhgUFoQQQggJDAoLQgghhAQGhQUhhBBCAoPCghBCCCGBQWFBCCGEkMCgsCCEEEJIYFBYEEIIISQwKCwIIYQQEhj/P6K34U0gHZTIAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "esc_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", + "esc_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", + "esc_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", + "esc_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", + "esc_ep.plot(x='t', y = ['act'], title='action'),\n", + "esc_ep.plot(x='t', y = ['rew'], title = f'reward = {sum(esc_ep.rew):.3f}')" + ] + }, + { + "cell_type": "markdown", + "id": "cd5982e9-e193-455c-9d27-bd036f8e593a", + "metadata": {}, + "source": [ + "## Cautionary Rule" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "9b18da14-869e-41d7-94aa-a1b737652d12", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cr_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", + "cr_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", + "cr_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", + "cr_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", + "cr_ep.plot(x='t', y = ['act'], title='action'),\n", + "cr_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(cr_ep.rew):.3f}')" + ] + }, + { + "cell_type": "markdown", + "id": "1088ac23-94aa-4567-8a1f-6aa15f6e4ecc", + "metadata": {}, + "source": [ + "## Trivial (no action)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "id": "0a890b9b-c1c2-405f-a506-f74aa3fc43a9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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ibgAA8DF//1++FbikpKSGZ3L5O3XqlCQpMDDwks9R+74eEQCAWiYgIEB16tTRoUOHFBgY6PWdMPiFMUanTp1Sfn6+IiIinCC8FMQNAAA+5nK51LhxY+3evVt79uyp6elc1iIiIuR2u3/VOYgbAACqQVBQkOLi4nhpqgKBgYG/6o7NWcQNAADVxM/Pj28orga86AcAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAq1RI3b7/9tpo1a6aQkBAlJSVp3bp1FY5fvHix4uPjFRISorZt22rZsmXnHfvwww/L5XLpjTfeqOJZAwCA2sjncbNo0SKNGTNGU6ZM0aZNm9SuXTulpqYqPz+/3PHffPONBg0apGHDhik7O1t9+/ZV3759tXXr1nPGfvHFF/r2228VExPj68sAAAC1hM/j5rXXXtNDDz2koUOHqnXr1pozZ47q1Kmj999/v9zxM2bM0G233aZx48apVatWev7553XjjTfqrbfe8hq3f/9+PfLII5o/f74CAwN9fRkAAKCW8GnclJSUaOPGjUpJSfnnE/r5KSUlRZmZmeUek5mZ6TVeklJTU73Gezwe3XfffRo3bpyuv/5630weAADUSgG+PPnhw4dVVlam6Ohor+3R0dHauXNnucfk5uaWOz43N9f5+0svvaSAgAA9+uijlZpHcXGxiouLnb8XFhZW9hIAAEAtU+s+LbVx40bNmDFDH3zwgVwuV6WOmTZtmsLDw51HbGysj2cJAABqik/jJioqSv7+/srLy/PanpeXJ7fbXe4xbre7wvEZGRnKz89X06ZNFRAQoICAAO3Zs0djx45Vs2bNyj3nxIkTVVBQ4Dz27dv36y8OAABclnwaN0FBQUpISFB6erqzzePxKD09XcnJyeUek5yc7DVeklasWOGMv++++/Tdd99p8+bNziMmJkbjxo3TV199Ve45g4ODFRYW5vUAAAB28ul7biRpzJgxGjx4sBITE9WpUye98cYbOnnypIYOHSpJuv/++9WkSRNNmzZNkjRq1Ch1795dr776qvr06aOFCxdqw4YNmjt3riQpMjJSkZGRXs8RGBgot9utli1b+vpyAADAZc7ncXP33Xfr0KFDmjx5snJzc9W+fXstX77cedPw3r175ef3zxtIXbp00YIFC/TUU09p0qRJiouL05IlS9SmTRtfTxUAAFjAZYwxNT2J6lZYWKjw8HAVFBTwEhUAALVEZX9+17pPSwEAAFSEuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABglWqJm7ffflvNmjVTSEiIkpKStG7dugrHL168WPHx8QoJCVHbtm21bNkyZ19paanGjx+vtm3bqm7duoqJidH999+vAwcO+PoyAABALeDzuFm0aJHGjBmjKVOmaNOmTWrXrp1SU1OVn59f7vhvvvlGgwYN0rBhw5Sdna2+ffuqb9++2rp1qyTp1KlT2rRpk55++mlt2rRJn3/+uXJycnTHHXf4+lIAAEAt4DLGGF8+QVJSkjp27Ki33npLkuTxeBQbG6tHHnlEEyZMOGf83XffrZMnT2rp0qXOts6dO6t9+/aaM2dOuc+xfv16derUSXv27FHTpk0vOKfCwkKFh4eroKBAYWFhl3hlAACgOlX257dP79yUlJRo48aNSklJ+ecT+vkpJSVFmZmZ5R6TmZnpNV6SUlNTzztekgoKCuRyuRQREVEl8wYAALVXgC9PfvjwYZWVlSk6Otpre3R0tHbu3FnuMbm5ueWOz83NLXf86dOnNX78eA0aNOi8FVdcXKzi4mLn74WFhRdzGQAAoBap1Z+WKi0t1cCBA2WM0ezZs887btq0aQoPD3cesbGx1ThLAABQnXwaN1FRUfL391deXp7X9ry8PLnd7nKPcbvdlRp/Nmz27NmjFStWVPja28SJE1VQUOA89u3bd4lXBAAALnc+jZugoCAlJCQoPT3d2ebxeJSenq7k5ORyj0lOTvYaL0krVqzwGn82bHbt2qX/+7//U2RkZIXzCA4OVlhYmNcDAADYyafvuZGkMWPGaPDgwUpMTFSnTp30xhtv6OTJkxo6dKgk6f7771eTJk00bdo0SdKoUaPUvXt3vfrqq+rTp48WLlyoDRs2aO7cuZJ+CZsBAwZo06ZNWrp0qcrKypz34zRo0EBBQUG+viQAAHAZ83nc3H333Tp06JAmT56s3NxctW/fXsuXL3feNLx37175+f3zBlKXLl20YMECPfXUU5o0aZLi4uK0ZMkStWnTRpK0f/9+/elPf5IktW/f3uu5Vq1apR49evj6kgAAwGXM599zcznie24AAKh9LovvuQEAAKhuxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKtUSN2+//baaNWumkJAQJSUlad26dRWOX7x4seLj4xUSEqK2bdtq2bJlXvuNMZo8ebIaN26s0NBQpaSkaNeuXb68BAAAUEv4PG4WLVqkMWPGaMqUKdq0aZPatWun1NRU5efnlzv+m2++0aBBgzRs2DBlZ2erb9++6tu3r7Zu3eqMefnllzVz5kzNmTNHWVlZqlu3rlJTU3X69GlfXw4AALjMuYwxxpdPkJSUpI4dO+qtt96SJHk8HsXGxuqRRx7RhAkTzhl/99136+TJk1q6dKmzrXPnzmrfvr3mzJkjY4xiYmI0duxYPf7445KkgoICRUdH64MPPtA999xzwTkVFhYqPDxcBQUFCgsLq6Ir/eWOUlFpWZWdDwCA2io00F8ul6tKz1nZn98BVfqs/6akpEQbN27UxIkTnW1+fn5KSUlRZmZmucdkZmZqzJgxXttSU1O1ZMkSSdLu3buVm5urlJQUZ394eLiSkpKUmZlZbtwUFxeruLjY+XthYeGvuazzKiotU+vJX/nk3AAA1Cbbn0tVnSCfZsZ5+fRlqcOHD6usrEzR0dFe26Ojo5Wbm1vuMbm5uRWOP/u/F3POadOmKTw83HnExsZe0vUAAIDLX80kVTWbOHGi192gwsJCnwROaKC/tj+XWuXnBQCgtgkN9K+x5/Zp3ERFRcnf3195eXle2/Py8uR2u8s9xu12Vzj+7P/m5eWpcePGXmPat29f7jmDg4MVHBx8qZdRaS6Xq8ZuwQEAgF/49GWpoKAgJSQkKD093dnm8XiUnp6u5OTkco9JTk72Gi9JK1ascMY3b95cbrfba0xhYaGysrLOe04AAHDl8PlthjFjxmjw4MFKTExUp06d9MYbb+jkyZMaOnSoJOn+++9XkyZNNG3aNEnSqFGj1L17d7366qvq06ePFi5cqA0bNmju3LmSfrk7Mnr0aL3wwguKi4tT8+bN9fTTTysmJkZ9+/b19eUAAIDLnM/j5u6779ahQ4c0efJk5ebmqn379lq+fLnzhuC9e/fKz++fN5C6dOmiBQsW6KmnntKkSZMUFxenJUuWqE2bNs6YJ554QidPntTw4cN17Ngxde3aVcuXL1dISIivLwcAAFzmfP49N5cjX33PDQAA8J3K/vzmd0sBAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwCnEDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArOKzuDl69KjS0tIUFhamiIgIDRs2TCdOnKjwmNOnT2vEiBGKjIxUvXr11L9/f+Xl5Tn7t2zZokGDBik2NlahoaFq1aqVZsyY4atLAAAAtZDP4iYtLU3btm3TihUrtHTpUn399dcaPnx4hcc89thj+vLLL7V48WKtWbNGBw4cUL9+/Zz9GzduVKNGjfTRRx9p27ZtevLJJzVx4kS99dZbvroMAABQy7iMMaaqT7pjxw61bt1a69evV2JioiRp+fLl6t27t/7xj38oJibmnGMKCgrUsGFDLViwQAMGDJAk7dy5U61atVJmZqY6d+5c7nONGDFCO3bs0MqVKys9v8LCQoWHh6ugoEBhYWGXcIUAAKC6Vfbnt0/u3GRmZioiIsIJG0lKSUmRn5+fsrKyyj1m48aNKi0tVUpKirMtPj5eTZs2VWZm5nmfq6CgQA0aNKhwPsXFxSosLPR6AAAAO/kkbnJzc9WoUSOvbQEBAWrQoIFyc3PPe0xQUJAiIiK8tkdHR5/3mG+++UaLFi264Mtd06ZNU3h4uPOIjY2t/MUAAIBa5aLiZsKECXK5XBU+du7c6au5etm6davuvPNOTZkyRbfeemuFYydOnKiCggLnsW/fvmqZIwAAqH4BFzN47NixGjJkSIVjrr32WrndbuXn53ttP3PmjI4ePSq3213ucW63WyUlJTp27JjX3Zu8vLxzjtm+fbt69uyp4cOH66mnnrrgvIODgxUcHHzBcQAAoPa7qLhp2LChGjZseMFxycnJOnbsmDZu3KiEhARJ0sqVK+XxeJSUlFTuMQkJCQoMDFR6err69+8vScrJydHevXuVnJzsjNu2bZtuueUWDR48WFOnTr2Y6QMAgCuATz4tJUm9evVSXl6e5syZo9LSUg0dOlSJiYlasGCBJGn//v3q2bOnPvzwQ3Xq1EmS9Pvf/17Lli3TBx98oLCwMD3yyCOSfnlvjfTLS1G33HKLUlNT9corrzjP5e/vX6noOotPSwEAUPtU9uf3Rd25uRjz58/XyJEj1bNnT/n5+al///6aOXOms7+0tFQ5OTk6deqUs+311193xhYXFys1NVWzZs1y9n/66ac6dOiQPvroI3300UfO9muuuUY//fSTry4FAADUIj67c3M5484NAAC1T41+zw0AAEBNIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWMVncXP06FGlpaUpLCxMERERGjZsmE6cOFHhMadPn9aIESMUGRmpevXqqX///srLyyt37JEjR3T11VfL5XLp2LFjPrgCAABQG/ksbtLS0rRt2zatWLFCS5cu1ddff63hw4dXeMxjjz2mL7/8UosXL9aaNWt04MAB9evXr9yxw4YN0w033OCLqQMAgFrMZYwxVX3SHTt2qHXr1lq/fr0SExMlScuXL1fv3r31j3/8QzExMeccU1BQoIYNG2rBggUaMGCAJGnnzp1q1aqVMjMz1blzZ2fs7NmztWjRIk2ePFk9e/bUzz//rIiIiErPr7CwUOHh4SooKFBYWNivu1gAAFAtKvvz2yd3bjIzMxUREeGEjSSlpKTIz89PWVlZ5R6zceNGlZaWKiUlxdkWHx+vpk2bKjMz09m2fft2Pffcc/rwww/l51e56RcXF6uwsNDrAQAA7OSTuMnNzVWjRo28tgUEBKhBgwbKzc097zFBQUHn3IGJjo52jikuLtagQYP0yiuvqGnTppWez7Rp0xQeHu48YmNjL+6CAABArXFRcTNhwgS5XK4KHzt37vTVXDVx4kS1atVK995770UfV1BQ4Dz27dvnoxkCAICaFnAxg8eOHashQ4ZUOObaa6+V2+1Wfn6+1/YzZ87o6NGjcrvd5R7ndrtVUlKiY8eOed29ycvLc45ZuXKlvv/+e3366aeSpLNvF4qKitKTTz6pZ599ttxzBwcHKzg4uDKXCAAAarmLipuGDRuqYcOGFxyXnJysY8eOaePGjUpISJD0S5h4PB4lJSWVe0xCQoICAwOVnp6u/v37S5JycnK0d+9eJScnS5I+++wzFRUVOcesX79eDzzwgDIyMtSiRYuLuRQAAGCpi4qbymrVqpVuu+02PfTQQ5ozZ45KS0s1cuRI3XPPPc4npfbv36+ePXvqww8/VKdOnRQeHq5hw4ZpzJgxatCggcLCwvTII48oOTnZ+aTUvwfM4cOHnee7mE9LAQAAe/kkbiRp/vz5GjlypHr27Ck/Pz/1799fM2fOdPaXlpYqJydHp06dcra9/vrrztji4mKlpqZq1qxZvpoiAACwkE++5+Zyx/fcAABQ+9To99wAAADUFOIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYhbgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AAIBViBsAAGAV4gYAAFiFuAEAAFYJqOkJ1ARjjCSpsLCwhmcCAAAq6+zP7bM/x8/nioyb48ePS5JiY2NreCYAAOBiHT9+XOHh4efd7zIXyh8LeTweHThwQFdddZVcLleVnruwsFCxsbHat2+fwsLCqvTc+CfWuXqwztWDda4+rHX18NU6G2N0/PhxxcTEyM/v/O+suSLv3Pj5+enqq6/26XOEhYXxH041YJ2rB+tcPVjn6sNaVw9frHNFd2zO4g3FAADAKsQNAACwCnFTxYKDgzVlyhQFBwfX9FSsxjpXD9a5erDO1Ye1rh41vc5X5BuKAQCAvbhzAwAArELcAAAAqxA3AADAKsQNAACwCnFThd5++201a9ZMISEhSkpK0rp162p6SrXKtGnT1LFjR1111VVq1KiR+vbtq5ycHK8xp0+f1ogRIxQZGal69eqpf//+ysvL8xqzd+9e9enTR3Xq1FGjRo00btw4nTlzpjovpVaZPn26XC6XRo8e7WxjnavG/v37de+99yoyMlKhoaFq27atNmzY4Ow3xmjy5Mlq3LixQkNDlZKSol27dnmd4+jRo0pLS1NYWJgiIiI0bNgwnThxorov5bJVVlamp59+Ws2bN1doaKhatGih559/3ut3D7HOl+brr7/W7373O8XExMjlcmnJkiVe+6tqXb/77jt169ZNISEhio2N1csvv/zrJ29QJRYuXGiCgoLM+++/b7Zt22YeeughExERYfLy8mp6arVGamqqmTdvntm6davZvHmz6d27t2natKk5ceKEM+bhhx82sbGxJj093WzYsMF07tzZdOnSxdl/5swZ06ZNG5OSkmKys7PNsmXLTFRUlJk4cWJNXNJlb926daZZs2bmhhtuMKNGjXK2s86/3tGjR80111xjhgwZYrKyssyPP/5ovvrqK/O3v/3NGTN9+nQTHh5ulixZYrZs2WLuuOMO07x5c1NUVOSMue2220y7du3Mt99+azIyMsx//Md/mEGDBtXEJV2Wpk6daiIjI83SpUvN7t27zeLFi029evXMjBkznDGs86VZtmyZefLJJ83nn39uJJkvvvjCa39VrGtBQYGJjo42aWlpZuvWrebjjz82oaGh5p133vlVcyduqkinTp3MiBEjnL+XlZWZmJgYM23atBqcVe2Wn59vJJk1a9YYY4w5duyYCQwMNIsXL3bG7Nixw0gymZmZxphf/mP08/Mzubm5zpjZs2ebsLAwU1xcXL0XcJk7fvy4iYuLMytWrDDdu3d34oZ1rhrjx483Xbt2Pe9+j8dj3G63eeWVV5xtx44dM8HBwebjjz82xhizfft2I8msX7/eGfOXv/zFuFwus3//ft9Nvhbp06ePeeCBB7y29evXz6SlpRljWOeq8u9xU1XrOmvWLFO/fn2vfzfGjx9vWrZs+avmy8tSVaCkpEQbN25USkqKs83Pz08pKSnKzMyswZnVbgUFBZKkBg0aSJI2btyo0tJSr3WOj49X06ZNnXXOzMxU27ZtFR0d7YxJTU1VYWGhtm3bVo2zv/yNGDFCffr08VpPiXWuKn/605+UmJiou+66S40aNVKHDh307rvvOvt3796t3Nxcr3UODw9XUlKS1zpHREQoMTHRGZOSkiI/Pz9lZWVV38Vcxrp06aL09HT98MMPkqQtW7Zo7dq16tWrlyTW2Veqal0zMzN18803KygoyBmTmpqqnJwc/fzzz5c8vyvyF2dWtcOHD6usrMzrH3pJio6O1s6dO2toVrWbx+PR6NGjddNNN6lNmzaSpNzcXAUFBSkiIsJrbHR0tHJzc50x5f3/cHYffrFw4UJt2rRJ69evP2cf61w1fvzxR82ePVtjxozRpEmTtH79ej366KMKCgrS4MGDnXUqbx3/dZ0bNWrktT8gIEANGjRgnf+/CRMmqLCwUPHx8fL391dZWZmmTp2qtLQ0SWKdfaSq1jU3N1fNmzc/5xxn99WvX/+S5kfc4LI0YsQIbd26VWvXrq3pqVhn3759GjVqlFasWKGQkJCano61PB6PEhMT9eKLL0qSOnTooK1bt2rOnDkaPHhwDc/OHp988onmz5+vBQsW6Prrr9fmzZs1evRoxcTEsM5XMF6WqgJRUVHy9/c/59MkeXl5crvdNTSr2mvkyJFaunSpVq1apauvvtrZ7na7VVJSomPHjnmN/9d1drvd5f7/cHYffnnZKT8/XzfeeKMCAgIUEBCgNWvWaObMmQoICFB0dDTrXAUaN26s1q1be21r1aqV9u7dK+mf61TRvxtut1v5+fle+8+cOaOjR4+yzv/fuHHjNGHCBN1zzz1q27at7rvvPj322GOaNm2aJNbZV6pqXX31bwlxUwWCgoKUkJCg9PR0Z5vH41F6erqSk5NrcGa1izFGI0eO1BdffKGVK1eec6syISFBgYGBXuuck5OjvXv3OuucnJys77//3us/qBUrVigsLOycHzRXqp49e+r777/X5s2bnUdiYqLS0tKcP7POv95NN910zlcZ/PDDD7rmmmskSc2bN5fb7fZa58LCQmVlZXmt87Fjx7Rx40ZnzMqVK+XxeJSUlFQNV3H5O3XqlPz8vH+U+fv7y+PxSGKdfaWq1jU5OVlff/21SktLnTErVqxQy5YtL/klKUl8FLyqLFy40AQHB5sPPvjAbN++3QwfPtxERER4fZoEFfv9739vwsPDzerVq83Bgwedx6lTp5wxDz/8sGnatKlZuXKl2bBhg0lOTjbJycnO/rMfUb711lvN5s2bzfLly03Dhg35iPIF/OunpYxhnavCunXrTEBAgJk6darZtWuXmT9/vqlTp4756KOPnDHTp083ERER5n/+53/Md999Z+68885yP0rboUMHk5WVZdauXWvi4uKu+I8o/6vBgwebJk2aOB8F//zzz01UVJR54oknnDGs86U5fvy4yc7ONtnZ2UaSee2110x2drbZs2ePMaZq1vXYsWMmOjra3HfffWbr1q1m4cKFpk6dOnwU/HLy5ptvmqZNm5qgoCDTqVMn8+2339b0lGoVSeU+5s2b54wpKioyf/jDH0z9+vVNnTp1zH/+53+agwcPep3np59+Mr169TKhoaEmKirKjB071pSWllbz1dQu/x43rHPV+PLLL02bNm1McHCwiY+PN3PnzvXa7/F4zNNPP22io6NNcHCw6dmzp8nJyfEac+TIETNo0CBTr149ExYWZoYOHWqOHz9enZdxWSssLDSjRo0yTZs2NSEhIebaa681Tz75pNdHi1nnS7Nq1apy/00ePHiwMabq1nXLli2ma9euJjg42DRp0sRMnz79V8/dZcy/fI0jAABALcd7bgAAgFWIGwAAYBXiBgAAWIW4AQAAViFuAACAVYgbAABgFeIGAABYhbgBAABWIW4AWKVHjx4aPXp0TU8DQA0ibgAAgFX49QsArDFkyBD98Y9/9Nq2e/duNWvWrGYmBKBGEDcArFFQUKBevXqpTZs2eu655yRJDRs2lL+/fw3PDEB1CqjpCQBAVQkPD1dQUJDq1Kkjt9td09MBUEN4zw0AALAKcQMAAKxC3ACwSlBQkMrKymp6GgBqEHEDwCrNmjVTVlaWfvrpJx0+fFgej6empwSgmhE3AKzy+OOPy9/fX61bt1bDhg21d+/emp4SgGrGR8EBAIBVuHMDAACsQtwAAACrEDcAAMAqxA0AALAKcQMAAKxC3AAAAKsQNwAAwCrEDQAAsApxAwAArELcAAAAqxA3AADAKsQNAACwyv8D3LyaoJ+Ag70AAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "trivial_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", + "trivial_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", + "trivial_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", + "trivial_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", + "trivial_ep.plot(x='t', y = ['act'], title='action'),\n", + "trivial_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(trivial_ep.rew):.3f}')" + ] + }, + { + "cell_type": "markdown", + "id": "3b22995e-d65f-4aa8-a6a0-94422fc6d346", + "metadata": {}, + "source": [ + "## Some side by side plots" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "id": "fd00e2e7-8d98-4e68-9161-4dd86376249e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,)" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "msy_ep.plot(x='t', y = ['non_random_newb'], title='MSY non-random newborns'),\n", + "esc_ep.plot(x='t', y = ['non_random_newb'], title='Esc non-random newborns'),\n", + "cr_ep.plot(x='t', y = ['non_random_newb'], title='CR non-random newborns'),\n", + "trivial_ep.plot(x='t', y = ['non_random_newb'], title='Unfished non-random newborns')," + ] + }, + { + "cell_type": "markdown", + "id": "ae919403-e1cf-4581-b457-14625e7380fa", + "metadata": {}, + "source": [ + "# r_devs" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "b1d5d2c3-d721-47ba-a535-e3a0a28f0e05", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rdev_df = pd.DataFrame({\n", + " 't': list(range(len(r_devs))),\n", + " 'r_devs': r_devs,\n", + "})\n", + "rdev_df.plot(x='t', logy=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "id": "09a2ce99-c612-49cd-9fa5-e5b4a09a1e92", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(468, 96, 390, 46)" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " len(rdev_df[rdev_df['r_devs']==0]),\n", + " len(rdev_df[(rdev_df['r_devs']>0) & (rdev_df['r_devs']<=1e-1)]),\n", + " len(rdev_df[(rdev_df['r_devs']<=1) & (rdev_df['r_devs']>1e-1)]),\n", + " len(rdev_df[rdev_df['r_devs']>1]),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "12d42c55-88b9-4e83-b397-094d84bb1fc2", + "metadata": {}, + "source": [ + "So about half of the time (n=468/1000) it doesn't actually matter what `ssb` is, since the `r_dev` is just zero.\n", + "A bout 10% of the time, it *almost* doesn't matter either, since `r_dev<0.1` in this case.\n", + "\n", + "Having a noise process that is mostly = 1 except for moments of deviation that are fewer in number might make the population dynamics not just reduce itself to the moments in which large schools happen.\n", + "\n", + "Plus, adding some danger around having too-low a population would also potentially make things more interesting.\n", + "Currently the `ssb` doesn't really matter in a large percentage of time-steps.\n", + "If we fixed the noise to make `ssb` more meaningful, the agent might be more careful about overfishing a large school too early on.\n", + "If we add to that a danger of a low population going extinct (e.g. an additive noise term) we might get an agent who will try and keep a high enough `ssb` value at all times, especially during periods that lack large schools." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "34a24d75-35d2-4d1e-82cb-a647a3a0d15b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index 5ac514b..660dc4c 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -19,77 +19,48 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 8, "id": "f15d4b8e-ef57-4bce-899b-89bb32d396f6", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Obtaining file:///home/rstudio/rl4fisheries\n", - " Installing build dependencies ... \u001b[?25ldone\n", - "\u001b[?25h Checking if build backend supports build_editable ... \u001b[?25ldone\n", - "\u001b[?25h Getting requirements to build editable ... \u001b[?25ldone\n", - "\u001b[?25h Installing backend dependencies ... \u001b[?25ldone\n", - "\u001b[?25h Preparing editable metadata (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25hRequirement already satisfied: gymnasium in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (0.28.1)\n", - "Requirement already satisfied: numpy in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (1.26.4)\n", - "Requirement already satisfied: matplotlib in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (3.8.3)\n", - "Collecting typing (from rl4fisheries==1.0.0)\n", - " Using cached typing-3.7.4.3-py3-none-any.whl\n", - "Requirement already satisfied: polars in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (0.20.11)\n", - "Requirement already satisfied: tqdm in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (4.66.2)\n", - "Requirement already satisfied: jax-jumpy>=1.0.0 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (1.0.0)\n", - "Requirement already satisfied: cloudpickle>=1.2.0 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (3.0.0)\n", - "Requirement already satisfied: typing-extensions>=4.3.0 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (4.9.0)\n", - "Requirement already satisfied: farama-notifications>=0.0.1 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (0.0.4)\n", - "Requirement already satisfied: contourpy>=1.0.1 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (1.2.0)\n", - "Requirement already satisfied: cycler>=0.10 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (0.12.1)\n", - "Requirement already satisfied: fonttools>=4.22.0 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (4.49.0)\n", - "Requirement already satisfied: kiwisolver>=1.3.1 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (1.4.5)\n", - "Requirement already satisfied: packaging>=20.0 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (23.2)\n", - "Requirement already satisfied: pillow>=8 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (10.2.0)\n", - "Requirement already satisfied: pyparsing>=2.3.1 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (3.1.1)\n", - "Requirement already satisfied: python-dateutil>=2.7 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (2.8.2)\n", - "Requirement already satisfied: six>=1.5 in /opt/venv/lib/python3.10/site-packages (from python-dateutil>=2.7->matplotlib->rl4fisheries==1.0.0) (1.16.0)\n", - "Building wheels for collected packages: rl4fisheries\n", - " Building editable for rl4fisheries (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for rl4fisheries: filename=rl4fisheries-1.0.0-0.editable-py3-none-any.whl size=2308 sha256=df1172f551bdc26310c562bf2af05b6167d549b2557a511f5e89afb29ae3da0d\n", - " Stored in directory: /tmp/pip-ephem-wheel-cache-tw68yoi8/wheels/d3/ce/fe/d5af67bb4edf309f6a59d59140b2b78d5a336b2ad4b93a1fb4\n", - "Successfully built rl4fisheries\n", - "Installing collected packages: typing, rl4fisheries\n", - "Successfully installed rl4fisheries-1.0.0 typing-3.7.4.3\n", - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], + "outputs": [], "source": [ - "%pip install -e ..\n", + "# %pip install -e ..\n", "# %pip install scikit-optimize" ] }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 6, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", "metadata": {}, "outputs": [], "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "\n", "from skopt import gp_minimize, gbrt_minimize \n", "from skopt.plots import plot_objective\n", "from skopt import dump\n", + "from skopt.space import Real\n", + "from skopt.utils import use_named_args\n", "\n", "from stable_baselines3.common.evaluation import evaluate_policy\n", "from stable_baselines3.common.monitor import Monitor\n", - "from rl4fisheries import Asm, Asm2o, Msy, ConstEsc, CautionaryRule\n", - "import numpy as np" + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.envs.asm_fns import get_r_devs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "236788a7-ed25-46bd-a9b0-f7301e96cacf", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG = {\"s\": 0.97}" ] }, { @@ -102,10 +73,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "b59deb35-b67d-4232-bce4-ae9c8c2f0fcc", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a3fdbca8d79646f0835eaa15bb8790aa", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(HTML(value='
" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(msy_gp)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(-413.97059970999993, [0.026082308394732884])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "msy_gbrt.fun, msy_gbrt.x" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "73d6974e-8d14-419d-a43d-ef0cd09659f8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(msy_gbrt)" + ] + }, + { + "cell_type": "markdown", + "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", + "metadata": {}, + "source": [ + "### Esc\n", + "\n", + "Optimal escapement is approximately `escapement = 0.133` with a (minus) reward value of about `-250`." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(-399.8290314899999, [0.17183492119923788])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "esc_gp = gp_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gp.fun, esc_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "ebff2644-b811-4bea-995c-ca3c7586c122", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(esc_gp)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(-445.35083130000004, [0.1596852959040506])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "esc_gbrt = gbrt_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gbrt.fun, esc_gbrt.x" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "d85a57bd-e338-468d-9d63-45d82fe53aef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(esc_gbrt)" + ] + }, + { + "cell_type": "markdown", + "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", + "metadata": {}, + "source": [ + "### CR" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", + "metadata": { "scrolled": true }, "outputs": [ @@ -156,7961 +427,354 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.1018\n", - "Function value obtained: -29.5673\n", - "Current minimum: -29.5673\n", + "Time taken: 14.8765\n", + "Function value obtained: -351.7318\n", + "Current minimum: -351.7318\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.1198\n", - "Function value obtained: -29.0363\n", - "Current minimum: -29.5673\n", + "Time taken: 14.7790\n", + "Function value obtained: -222.6689\n", + "Current minimum: -351.7318\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.0984\n", - "Function value obtained: -8.2585\n", - "Current minimum: -29.5673\n", + "Time taken: 14.7518\n", + "Function value obtained: -174.7706\n", + "Current minimum: -351.7318\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.0947\n", - "Function value obtained: -4.3467\n", - "Current minimum: -29.5673\n", + "Time taken: 15.0518\n", + "Function value obtained: -340.0497\n", + "Current minimum: -351.7318\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.0949\n", - "Function value obtained: -18.4655\n", - "Current minimum: -29.5673\n", + "Time taken: 14.8816\n", + "Function value obtained: -251.9900\n", + "Current minimum: -351.7318\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.0840\n", - "Function value obtained: -3.9571\n", - "Current minimum: -29.5673\n", + "Time taken: 14.7287\n", + "Function value obtained: -209.4481\n", + "Current minimum: -351.7318\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.0798\n", - "Function value obtained: -25.1142\n", - "Current minimum: -29.5673\n", + "Time taken: 14.7696\n", + "Function value obtained: -226.3372\n", + "Current minimum: -351.7318\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.0799\n", - "Function value obtained: -45.0913\n", - "Current minimum: -45.0913\n", + "Time taken: 14.6545\n", + "Function value obtained: -174.3101\n", + "Current minimum: -351.7318\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.0834\n", - "Function value obtained: -51.1744\n", - "Current minimum: -51.1744\n", + "Time taken: 14.8862\n", + "Function value obtained: -78.2966\n", + "Current minimum: -351.7318\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 2.6408\n", - "Function value obtained: -31.3025\n", - "Current minimum: -51.1744\n", + "Time taken: 18.9290\n", + "Function value obtained: -256.4544\n", + "Current minimum: -351.7318\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2831\n", - "Function value obtained: -43.3948\n", - "Current minimum: -51.1744\n", + "Time taken: 16.2500\n", + "Function value obtained: -207.3230\n", + "Current minimum: -351.7318\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2917\n", - "Function value obtained: -42.7749\n", - "Current minimum: -51.1744\n", + "Time taken: 16.2148\n", + "Function value obtained: -65.2255\n", + "Current minimum: -351.7318\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3279\n", - "Function value obtained: -43.5706\n", - "Current minimum: -51.1744\n", + "Time taken: 16.5459\n", + "Function value obtained: -167.9823\n", + "Current minimum: -351.7318\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2702\n", - "Function value obtained: -12.0224\n", - "Current minimum: -51.1744\n", + "Time taken: 16.2486\n", + "Function value obtained: -410.9384\n", + "Current minimum: -410.9384\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3008\n", - "Function value obtained: -40.9426\n", - "Current minimum: -51.1744\n", + "Time taken: 16.1813\n", + "Function value obtained: -380.7809\n", + "Current minimum: -410.9384\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2745\n", - "Function value obtained: -46.3147\n", - "Current minimum: -51.1744\n", + "Time taken: 16.1551\n", + "Function value obtained: -225.6165\n", + "Current minimum: -410.9384\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3563\n", - "Function value obtained: -40.0429\n", - "Current minimum: -51.1744\n", + "Time taken: 16.1436\n", + "Function value obtained: -289.8493\n", + "Current minimum: -410.9384\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2982\n", - "Function value obtained: -43.0713\n", - "Current minimum: -51.1744\n", + "Time taken: 15.7917\n", + "Function value obtained: -42.3463\n", + "Current minimum: -410.9384\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3049\n", - "Function value obtained: -44.8894\n", - "Current minimum: -51.1744\n", + "Time taken: 15.2254\n", + "Function value obtained: -2.2897\n", + "Current minimum: -410.9384\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3612\n", - "Function value obtained: -42.7981\n", - "Current minimum: -51.1744\n", + "Time taken: 15.3229\n", + "Function value obtained: -0.0000\n", + "Current minimum: -410.9384\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3114\n", - "Function value obtained: -48.8341\n", - "Current minimum: -51.1744\n", + "Time taken: 15.2306\n", + "Function value obtained: -231.6224\n", + "Current minimum: -410.9384\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3400\n", - "Function value obtained: -54.3074\n", - "Current minimum: -54.3074\n", + "Time taken: 15.1051\n", + "Function value obtained: -237.8984\n", + "Current minimum: -410.9384\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3257\n", - "Function value obtained: -43.1245\n", - "Current minimum: -54.3074\n", + "Time taken: 14.9081\n", + "Function value obtained: -171.7056\n", + "Current minimum: -410.9384\n", "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3539\n", - "Function value obtained: -49.7344\n", - "Current minimum: -54.3074\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4352\n", - "Function value obtained: -43.8415\n", - "Current minimum: -54.3074\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3629\n", - "Function value obtained: -41.4713\n", - "Current minimum: -54.3074\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3568\n", - "Function value obtained: -46.3356\n", - "Current minimum: -54.3074\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3868\n", - "Function value obtained: -49.9253\n", - "Current minimum: -54.3074\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3529\n", - "Function value obtained: -46.4118\n", - "Current minimum: -54.3074\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3699\n", - "Function value obtained: -47.3313\n", - "Current minimum: -54.3074\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3508\n", - "Function value obtained: -48.0017\n", - "Current minimum: -54.3074\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4703\n", - "Function value obtained: -48.9763\n", - "Current minimum: -54.3074\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3595\n", - "Function value obtained: -37.0952\n", - "Current minimum: -54.3074\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3905\n", - "Function value obtained: -46.9673\n", - "Current minimum: -54.3074\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3917\n", - "Function value obtained: -42.4579\n", - "Current minimum: -54.3074\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3958\n", - "Function value obtained: -38.2450\n", - "Current minimum: -54.3074\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4142\n", - "Function value obtained: -51.8753\n", - "Current minimum: -54.3074\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4641\n", - "Function value obtained: -37.8124\n", - "Current minimum: -54.3074\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4204\n", - "Function value obtained: -43.3219\n", - "Current minimum: -54.3074\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3954\n", - "Function value obtained: -47.8845\n", - "Current minimum: -54.3074\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4298\n", - "Function value obtained: -52.5514\n", - "Current minimum: -54.3074\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4485\n", - "Function value obtained: -40.7701\n", - "Current minimum: -54.3074\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4345\n", - "Function value obtained: -41.1451\n", - "Current minimum: -54.3074\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4141\n", - "Function value obtained: -38.6807\n", - "Current minimum: -54.3074\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4746\n", - "Function value obtained: -43.3375\n", - "Current minimum: -54.3074\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3941\n", - "Function value obtained: -45.2664\n", - "Current minimum: -54.3074\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4604\n", - "Function value obtained: -40.8030\n", - "Current minimum: -54.3074\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5163\n", - "Function value obtained: -43.6741\n", - "Current minimum: -54.3074\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4504\n", - "Function value obtained: -42.4938\n", - "Current minimum: -54.3074\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4801\n", - "Function value obtained: -48.3087\n", - "Current minimum: -54.3074\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4696\n", - "Function value obtained: -33.9598\n", - "Current minimum: -54.3074\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4530\n", - "Function value obtained: -43.7740\n", - "Current minimum: -54.3074\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5653\n", - "Function value obtained: -47.8873\n", - "Current minimum: -54.3074\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4667\n", - "Function value obtained: -38.8337\n", - "Current minimum: -54.3074\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4699\n", - "Function value obtained: -47.5473\n", - "Current minimum: -54.3074\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5007\n", - "Function value obtained: -39.2330\n", - "Current minimum: -54.3074\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4832\n", - "Function value obtained: -47.2887\n", - "Current minimum: -54.3074\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4890\n", - "Function value obtained: -47.1416\n", - "Current minimum: -54.3074\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4646\n", - "Function value obtained: -49.4100\n", - "Current minimum: -54.3074\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5008\n", - "Function value obtained: -45.6291\n", - "Current minimum: -54.3074\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4885\n", - "Function value obtained: -50.5397\n", - "Current minimum: -54.3074\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4989\n", - "Function value obtained: -42.5915\n", - "Current minimum: -54.3074\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4641\n", - "Function value obtained: -46.3676\n", - "Current minimum: -54.3074\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6358\n", - "Function value obtained: -43.0398\n", - "Current minimum: -54.3074\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4961\n", - "Function value obtained: -41.2359\n", - "Current minimum: -54.3074\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5237\n", - "Function value obtained: -41.4246\n", - "Current minimum: -54.3074\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6109\n", - "Function value obtained: -45.9230\n", - "Current minimum: -54.3074\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5661\n", - "Function value obtained: -41.8284\n", - "Current minimum: -54.3074\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5014\n", - "Function value obtained: -47.5970\n", - "Current minimum: -54.3074\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5779\n", - "Function value obtained: -46.7162\n", - "Current minimum: -54.3074\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5264\n", - "Function value obtained: -49.5663\n", - "Current minimum: -54.3074\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5174\n", - "Function value obtained: -42.0280\n", - "Current minimum: -54.3074\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5933\n", - "Function value obtained: -40.2975\n", - "Current minimum: -54.3074\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5550\n", - "Function value obtained: -42.9347\n", - "Current minimum: -54.3074\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5319\n", - "Function value obtained: -42.6333\n", - "Current minimum: -54.3074\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5485\n", - "Function value obtained: -36.4577\n", - "Current minimum: -54.3074\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5657\n", - "Function value obtained: -39.8921\n", - "Current minimum: -54.3074\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5818\n", - "Function value obtained: -45.2305\n", - "Current minimum: -54.3074\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6083\n", - "Function value obtained: -44.5000\n", - "Current minimum: -54.3074\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6562\n", - "Function value obtained: -44.6236\n", - "Current minimum: -54.3074\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5878\n", - "Function value obtained: -45.7690\n", - "Current minimum: -54.3074\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7090\n", - "Function value obtained: -37.3097\n", - "Current minimum: -54.3074\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6064\n", - "Function value obtained: -45.7503\n", - "Current minimum: -54.3074\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6031\n", - "Function value obtained: -44.0352\n", - "Current minimum: -54.3074\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6609\n", - "Function value obtained: -42.7596\n", - "Current minimum: -54.3074\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6878\n", - "Function value obtained: -42.3808\n", - "Current minimum: -54.3074\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6256\n", - "Function value obtained: -45.7836\n", - "Current minimum: -54.3074\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6204\n", - "Function value obtained: -36.7580\n", - "Current minimum: -54.3074\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6449\n", - "Function value obtained: -42.1446\n", - "Current minimum: -54.3074\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6587\n", - "Function value obtained: -49.4466\n", - "Current minimum: -54.3074\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8149\n", - "Function value obtained: -45.4638\n", - "Current minimum: -54.3074\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7727\n", - "Function value obtained: -41.9642\n", - "Current minimum: -54.3074\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7674\n", - "Function value obtained: -44.7025\n", - "Current minimum: -54.3074\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7717\n", - "Function value obtained: -37.4736\n", - "Current minimum: -54.3074\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7782\n", - "Function value obtained: -41.7831\n", - "Current minimum: -54.3074\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8471\n", - "Function value obtained: -41.7732\n", - "Current minimum: -54.3074\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7854\n", - "Function value obtained: -42.9858\n", - "Current minimum: -54.3074\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8038\n", - "Function value obtained: -39.7643\n", - "Current minimum: -54.3074\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9074\n", - "Function value obtained: -37.8795\n", - "Current minimum: -54.3074\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8590\n", - "Function value obtained: -51.2151\n", - "Current minimum: -54.3074\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8425\n", - "Function value obtained: -42.6880\n", - "Current minimum: -54.3074\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8919\n", - "Function value obtained: -39.4649\n", - "Current minimum: -54.3074\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8279\n", - "Function value obtained: -38.2470\n", - "Current minimum: -54.3074\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8630\n", - "Function value obtained: -46.4061\n", - "Current minimum: -54.3074\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8694\n", - "Function value obtained: -47.9482\n", - "Current minimum: -54.3074\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8550\n", - "Function value obtained: -43.2475\n", - "Current minimum: -54.3074\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9460\n", - "Function value obtained: -41.1355\n", - "Current minimum: -54.3074\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0082\n", - "Function value obtained: -46.3405\n", - "Current minimum: -54.3074\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0867\n", - "Function value obtained: -41.3937\n", - "Current minimum: -54.3074\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0083\n", - "Function value obtained: -40.6785\n", - "Current minimum: -54.3074\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9523\n", - "Function value obtained: -44.7224\n", - "Current minimum: -54.3074\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0685\n", - "Function value obtained: -46.2119\n", - "Current minimum: -54.3074\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9673\n", - "Function value obtained: -44.2833\n", - "Current minimum: -54.3074\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0190\n", - "Function value obtained: -48.4010\n", - "Current minimum: -54.3074\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9463\n", - "Function value obtained: -45.3038\n", - "Current minimum: -54.3074\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0688\n", - "Function value obtained: -40.6065\n", - "Current minimum: -54.3074\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1402\n", - "Function value obtained: -42.3795\n", - "Current minimum: -54.3074\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0447\n", - "Function value obtained: -62.0848\n", - "Current minimum: -62.0848\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0796\n", - "Function value obtained: -43.9325\n", - "Current minimum: -62.0848\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0397\n", - "Function value obtained: -39.7705\n", - "Current minimum: -62.0848\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0636\n", - "Function value obtained: -53.2214\n", - "Current minimum: -62.0848\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0376\n", - "Function value obtained: -48.9261\n", - "Current minimum: -62.0848\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1057\n", - "Function value obtained: -36.7139\n", - "Current minimum: -62.0848\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0601\n", - "Function value obtained: -43.8370\n", - "Current minimum: -62.0848\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2552\n", - "Function value obtained: -47.6742\n", - "Current minimum: -62.0848\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1735\n", - "Function value obtained: -39.2353\n", - "Current minimum: -62.0848\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0974\n", - "Function value obtained: -38.0873\n", - "Current minimum: -62.0848\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1062\n", - "Function value obtained: -43.8155\n", - "Current minimum: -62.0848\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0997\n", - "Function value obtained: -41.4054\n", - "Current minimum: -62.0848\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1152\n", - "Function value obtained: -48.4037\n", - "Current minimum: -62.0848\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1440\n", - "Function value obtained: -44.5616\n", - "Current minimum: -62.0848\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1757\n", - "Function value obtained: -46.6413\n", - "Current minimum: -62.0848\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1909\n", - "Function value obtained: -46.6936\n", - "Current minimum: -62.0848\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2449\n", - "Function value obtained: -47.9653\n", - "Current minimum: -62.0848\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1899\n", - "Function value obtained: -45.1756\n", - "Current minimum: -62.0848\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2704\n", - "Function value obtained: -44.0644\n", - "Current minimum: -62.0848\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2742\n", - "Function value obtained: -45.5947\n", - "Current minimum: -62.0848\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3534\n", - "Function value obtained: -47.3648\n", - "Current minimum: -62.0848\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2474\n", - "Function value obtained: -47.9739\n", - "Current minimum: -62.0848\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3191\n", - "Function value obtained: -41.7235\n", - "Current minimum: -62.0848\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3371\n", - "Function value obtained: -45.0327\n", - "Current minimum: -62.0848\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2877\n", - "Function value obtained: -44.9155\n", - "Current minimum: -62.0848\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2664\n", - "Function value obtained: -45.8658\n", - "Current minimum: -62.0848\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2699\n", - "Function value obtained: -44.1475\n", - "Current minimum: -62.0848\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3152\n", - "Function value obtained: -42.9721\n", - "Current minimum: -62.0848\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3962\n", - "Function value obtained: -44.7798\n", - "Current minimum: -62.0848\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3218\n", - "Function value obtained: -46.4581\n", - "Current minimum: -62.0848\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3397\n", - "Function value obtained: -47.4247\n", - "Current minimum: -62.0848\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3629\n", - "Function value obtained: -47.3364\n", - "Current minimum: -62.0848\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3593\n", - "Function value obtained: -45.9331\n", - "Current minimum: -62.0848\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4010\n", - "Function value obtained: -37.3971\n", - "Current minimum: -62.0848\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3866\n", - "Function value obtained: -47.4068\n", - "Current minimum: -62.0848\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4561\n", - "Function value obtained: -50.4555\n", - "Current minimum: -62.0848\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4177\n", - "Function value obtained: -38.9568\n", - "Current minimum: -62.0848\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5444\n", - "Function value obtained: -49.0524\n", - "Current minimum: -62.0848\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4851\n", - "Function value obtained: -48.7509\n", - "Current minimum: -62.0848\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4865\n", - "Function value obtained: -36.4921\n", - "Current minimum: -62.0848\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5218\n", - "Function value obtained: -46.7030\n", - "Current minimum: -62.0848\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5262\n", - "Function value obtained: -48.1893\n", - "Current minimum: -62.0848\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5817\n", - "Function value obtained: -43.6738\n", - "Current minimum: -62.0848\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5972\n", - "Function value obtained: -42.3322\n", - "Current minimum: -62.0848\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5858\n", - "Function value obtained: -42.2344\n", - "Current minimum: -62.0848\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5809\n", - "Function value obtained: -43.5521\n", - "Current minimum: -62.0848\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6159\n", - "Function value obtained: -41.2904\n", - "Current minimum: -62.0848\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6541\n", - "Function value obtained: -39.9613\n", - "Current minimum: -62.0848\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7190\n", - "Function value obtained: -44.9529\n", - "Current minimum: -62.0848\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6926\n", - "Function value obtained: -41.5135\n", - "Current minimum: -62.0848\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6609\n", - "Function value obtained: -45.5662\n", - "Current minimum: -62.0848\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7874\n", - "Function value obtained: -48.5865\n", - "Current minimum: -62.0848\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7429\n", - "Function value obtained: -48.5993\n", - "Current minimum: -62.0848\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7672\n", - "Function value obtained: -42.6785\n", - "Current minimum: -62.0848\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7453\n", - "Function value obtained: -47.5351\n", - "Current minimum: -62.0848\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7315\n", - "Function value obtained: -43.5492\n", - "Current minimum: -62.0848\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7179\n", - "Function value obtained: -43.7206\n", - "Current minimum: -62.0848\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8761\n", - "Function value obtained: -43.3261\n", - "Current minimum: -62.0848\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7670\n", - "Function value obtained: -39.7563\n", - "Current minimum: -62.0848\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7641\n", - "Function value obtained: -42.9270\n", - "Current minimum: -62.0848\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8570\n", - "Function value obtained: -42.6520\n", - "Current minimum: -62.0848\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8960\n", - "Function value obtained: -40.8912\n", - "Current minimum: -62.0848\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8666\n", - "Function value obtained: -52.1104\n", - "Current minimum: -62.0848\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9025\n", - "Function value obtained: -45.9856\n", - "Current minimum: -62.0848\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8980\n", - "Function value obtained: -44.4878\n", - "Current minimum: -62.0848\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0335\n", - "Function value obtained: -41.5425\n", - "Current minimum: -62.0848\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9454\n", - "Function value obtained: -54.9839\n", - "Current minimum: -62.0848\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9867\n", - "Function value obtained: -41.9765\n", - "Current minimum: -62.0848\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9567\n", - "Function value obtained: -50.5525\n", - "Current minimum: -62.0848\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0317\n", - "Function value obtained: -46.3131\n", - "Current minimum: -62.0848\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0139\n", - "Function value obtained: -46.3129\n", - "Current minimum: -62.0848\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0429\n", - "Function value obtained: -49.1659\n", - "Current minimum: -62.0848\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2221\n", - "Function value obtained: -33.3804\n", - "Current minimum: -62.0848\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1994\n", - "Function value obtained: -40.1401\n", - "Current minimum: -62.0848\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0935\n", - "Function value obtained: -40.8693\n", - "Current minimum: -62.0848\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2044\n", - "Function value obtained: -41.7592\n", - "Current minimum: -62.0848\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1627\n", - "Function value obtained: -46.7094\n", - "Current minimum: -62.0848\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0857\n", - "Function value obtained: -41.9930\n", - "Current minimum: -62.0848\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0290\n", - "Function value obtained: -44.4827\n", - "Current minimum: -62.0848\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1716\n", - "Function value obtained: -40.9208\n", - "Current minimum: -62.0848\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1941\n", - "Function value obtained: -42.1174\n", - "Current minimum: -62.0848\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3206\n", - "Function value obtained: -39.5979\n", - "Current minimum: -62.0848\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1543\n", - "Function value obtained: -40.5421\n", - "Current minimum: -62.0848\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2473\n", - "Function value obtained: -45.7799\n", - "Current minimum: -62.0848\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2637\n", - "Function value obtained: -34.4027\n", - "Current minimum: -62.0848\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2131\n", - "Function value obtained: -40.9786\n", - "Current minimum: -62.0848\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3027\n", - "Function value obtained: -47.0096\n", - "Current minimum: -62.0848\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2106\n", - "Function value obtained: -37.9014\n", - "Current minimum: -62.0848\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2971\n", - "Function value obtained: -43.5989\n", - "Current minimum: -62.0848\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3260\n", - "Function value obtained: -49.2067\n", - "Current minimum: -62.0848\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3123\n", - "Function value obtained: -37.5639\n", - "Current minimum: -62.0848\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3503\n", - "Function value obtained: -39.1372\n", - "Current minimum: -62.0848\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3956\n", - "Function value obtained: -44.5506\n", - "Current minimum: -62.0848\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4608\n", - "Function value obtained: -41.4432\n", - "Current minimum: -62.0848\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5018\n", - "Function value obtained: -43.1203\n", - "Current minimum: -62.0848\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5642\n", - "Function value obtained: -40.8293\n", - "Current minimum: -62.0848\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6228\n", - "Function value obtained: -50.0044\n", - "Current minimum: -62.0848\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5327\n", - "Function value obtained: -40.6575\n", - "Current minimum: -62.0848\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4775\n", - "Function value obtained: -40.6060\n", - "Current minimum: -62.0848\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5693\n", - "Function value obtained: -38.6392\n", - "Current minimum: -62.0848\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5537\n", - "Function value obtained: -51.1744\n", - "Current minimum: -62.0848\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5347\n", - "Function value obtained: -39.5364\n", - "Current minimum: -62.0848\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6819\n", - "Function value obtained: -43.7882\n", - "Current minimum: -62.0848\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8070\n", - "Function value obtained: -56.3809\n", - "Current minimum: -62.0848\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6688\n", - "Function value obtained: -46.4417\n", - "Current minimum: -62.0848\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6601\n", - "Function value obtained: -44.0623\n", - "Current minimum: -62.0848\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6670\n", - "Function value obtained: -51.3506\n", - "Current minimum: -62.0848\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6718\n", - "Function value obtained: -52.8084\n", - "Current minimum: -62.0848\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7396\n", - "Function value obtained: -45.7368\n", - "Current minimum: -62.0848\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7787\n", - "Function value obtained: -41.7063\n", - "Current minimum: -62.0848\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9293\n", - "Function value obtained: -36.9234\n", - "Current minimum: -62.0848\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9210\n", - "Function value obtained: -48.9383\n", - "Current minimum: -62.0848\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9971\n", - "Function value obtained: -41.2139\n", - "Current minimum: -62.0848\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0884\n", - "Function value obtained: -41.8616\n", - "Current minimum: -62.0848\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0999\n", - "Function value obtained: -43.5803\n", - "Current minimum: -62.0848\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0858\n", - "Function value obtained: -40.9283\n", - "Current minimum: -62.0848\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9222\n", - "Function value obtained: -45.2686\n", - "Current minimum: -62.0848\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9003\n", - "Function value obtained: -48.8593\n", - "Current minimum: -62.0848\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9526\n", - "Function value obtained: -43.9230\n", - "Current minimum: -62.0848\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9672\n", - "Function value obtained: -31.6081\n", - "Current minimum: -62.0848\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0904\n", - "Function value obtained: -47.3595\n", - "Current minimum: -62.0848\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0938\n", - "Function value obtained: -39.7590\n", - "Current minimum: -62.0848\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1222\n", - "Function value obtained: -46.0601\n", - "Current minimum: -62.0848\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2086\n", - "Function value obtained: -44.2421\n", - "Current minimum: -62.0848\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0548\n", - "Function value obtained: -39.5599\n", - "Current minimum: -62.0848\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1864\n", - "Function value obtained: -49.9932\n", - "Current minimum: -62.0848\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0080\n", - "Function value obtained: -49.5699\n", - "Current minimum: -62.0848\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0752\n", - "Function value obtained: -36.5969\n", - "Current minimum: -62.0848\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0421\n", - "Function value obtained: -40.7072\n", - "Current minimum: -62.0848\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1659\n", - "Function value obtained: -46.1310\n", - "Current minimum: -62.0848\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2168\n", - "Function value obtained: -41.6344\n", - "Current minimum: -62.0848\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2917\n", - "Function value obtained: -40.5283\n", - "Current minimum: -62.0848\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1603\n", - "Function value obtained: -44.7817\n", - "Current minimum: -62.0848\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1581\n", - "Function value obtained: -38.1412\n", - "Current minimum: -62.0848\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1273\n", - "Function value obtained: -49.5775\n", - "Current minimum: -62.0848\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3481\n", - "Function value obtained: -45.7961\n", - "Current minimum: -62.0848\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3654\n", - "Function value obtained: -42.2709\n", - "Current minimum: -62.0848\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4279\n", - "Function value obtained: -45.2843\n", - "Current minimum: -62.0848\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5854\n", - "Function value obtained: -55.6468\n", - "Current minimum: -62.0848\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2864\n", - "Function value obtained: -43.5524\n", - "Current minimum: -62.0848\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2976\n", - "Function value obtained: -42.3724\n", - "Current minimum: -62.0848\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4489\n", - "Function value obtained: -45.6108\n", - "Current minimum: -62.0848\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3004\n", - "Function value obtained: -40.8738\n", - "Current minimum: -62.0848\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5377\n", - "Function value obtained: -45.4095\n", - "Current minimum: -62.0848\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4521\n", - "Function value obtained: -33.3039\n", - "Current minimum: -62.0848\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4773\n", - "Function value obtained: -51.6857\n", - "Current minimum: -62.0848\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6067\n", - "Function value obtained: -34.6379\n", - "Current minimum: -62.0848\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5418\n", - "Function value obtained: -48.9442\n", - "Current minimum: -62.0848\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4478\n", - "Function value obtained: -44.8746\n", - "Current minimum: -62.0848\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7182\n", - "Function value obtained: -46.9764\n", - "Current minimum: -62.0848\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7048\n", - "Function value obtained: -43.8466\n", - "Current minimum: -62.0848\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5902\n", - "Function value obtained: -50.5454\n", - "Current minimum: -62.0848\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7301\n", - "Function value obtained: -42.1294\n", - "Current minimum: -62.0848\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6614\n", - "Function value obtained: -48.5922\n", - "Current minimum: -62.0848\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6776\n", - "Function value obtained: -45.0754\n", - "Current minimum: -62.0848\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8040\n", - "Function value obtained: -48.1112\n", - "Current minimum: -62.0848\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7175\n", - "Function value obtained: -41.6727\n", - "Current minimum: -62.0848\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7855\n", - "Function value obtained: -37.3404\n", - "Current minimum: -62.0848\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7674\n", - "Function value obtained: -45.3077\n", - "Current minimum: -62.0848\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9670\n", - "Function value obtained: -40.6291\n", - "Current minimum: -62.0848\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9398\n", - "Function value obtained: -48.8924\n", - "Current minimum: -62.0848\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1050\n", - "Function value obtained: -46.0012\n", - "Current minimum: -62.0848\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9125\n", - "Function value obtained: -44.5401\n", - "Current minimum: -62.0848\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1280\n", - "Function value obtained: -41.4518\n", - "Current minimum: -62.0848\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9933\n", - "Function value obtained: -46.6584\n", - "Current minimum: -62.0848\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1114\n", - "Function value obtained: -41.8416\n", - "Current minimum: -62.0848\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0579\n", - "Function value obtained: -48.5575\n", - "Current minimum: -62.0848\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0690\n", - "Function value obtained: -52.3025\n", - "Current minimum: -62.0848\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0588\n", - "Function value obtained: -44.1470\n", - "Current minimum: -62.0848\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0050\n", - "Function value obtained: -54.2064\n", - "Current minimum: -62.0848\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9521\n", - "Function value obtained: -46.1661\n", - "Current minimum: -62.0848\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0579\n", - "Function value obtained: -49.4790\n", - "Current minimum: -62.0848\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0334\n", - "Function value obtained: -54.7050\n", - "Current minimum: -62.0848\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1943\n", - "Function value obtained: -43.7255\n", - "Current minimum: -62.0848\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1193\n", - "Function value obtained: -49.2379\n", - "Current minimum: -62.0848\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4030\n", - "Function value obtained: -48.7281\n", - "Current minimum: -62.0848\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1761\n", - "Function value obtained: -45.1314\n", - "Current minimum: -62.0848\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2214\n", - "Function value obtained: -36.5071\n", - "Current minimum: -62.0848\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2238\n", - "Function value obtained: -40.1303\n", - "Current minimum: -62.0848\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5192\n", - "Function value obtained: -53.2504\n", - "Current minimum: -62.0848\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2937\n", - "Function value obtained: -43.7891\n", - "Current minimum: -62.0848\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4600\n", - "Function value obtained: -46.4439\n", - "Current minimum: -62.0848\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5191\n", - "Function value obtained: -47.2268\n", - "Current minimum: -62.0848\n", - "Iteration No: 301 started. Searching for the next optimal point.\n", - "Iteration No: 301 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4754\n", - "Function value obtained: -42.1244\n", - "Current minimum: -62.0848\n", - "Iteration No: 302 started. Searching for the next optimal point.\n", - "Iteration No: 302 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5212\n", - "Function value obtained: -51.7301\n", - "Current minimum: -62.0848\n", - "Iteration No: 303 started. Searching for the next optimal point.\n", - "Iteration No: 303 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4517\n", - "Function value obtained: -43.2842\n", - "Current minimum: -62.0848\n", - "Iteration No: 304 started. Searching for the next optimal point.\n", - "Iteration No: 304 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4308\n", - "Function value obtained: -45.6752\n", - "Current minimum: -62.0848\n", - "Iteration No: 305 started. Searching for the next optimal point.\n", - "Iteration No: 305 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4572\n", - "Function value obtained: -44.4061\n", - "Current minimum: -62.0848\n", - "Iteration No: 306 started. Searching for the next optimal point.\n", - "Iteration No: 306 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6341\n", - "Function value obtained: -48.0162\n", - "Current minimum: -62.0848\n", - "Iteration No: 307 started. Searching for the next optimal point.\n", - "Iteration No: 307 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5386\n", - "Function value obtained: -40.8854\n", - "Current minimum: -62.0848\n", - "Iteration No: 308 started. Searching for the next optimal point.\n", - "Iteration No: 308 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4845\n", - "Function value obtained: -46.4431\n", - "Current minimum: -62.0848\n", - "Iteration No: 309 started. Searching for the next optimal point.\n", - "Iteration No: 309 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6275\n", - "Function value obtained: -47.8619\n", - "Current minimum: -62.0848\n", - "Iteration No: 310 started. Searching for the next optimal point.\n", - "Iteration No: 310 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6467\n", - "Function value obtained: -43.0580\n", - "Current minimum: -62.0848\n", - "Iteration No: 311 started. Searching for the next optimal point.\n", - "Iteration No: 311 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9370\n", - "Function value obtained: -43.5322\n", - "Current minimum: -62.0848\n", - "Iteration No: 312 started. Searching for the next optimal point.\n", - "Iteration No: 312 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7230\n", - "Function value obtained: -38.7416\n", - "Current minimum: -62.0848\n", - "Iteration No: 313 started. Searching for the next optimal point.\n", - "Iteration No: 313 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6528\n", - "Function value obtained: -44.3232\n", - "Current minimum: -62.0848\n", - "Iteration No: 314 started. Searching for the next optimal point.\n", - "Iteration No: 314 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6884\n", - "Function value obtained: -40.6524\n", - "Current minimum: -62.0848\n", - "Iteration No: 315 started. Searching for the next optimal point.\n", - "Iteration No: 315 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8768\n", - "Function value obtained: -48.0421\n", - "Current minimum: -62.0848\n", - "Iteration No: 316 started. Searching for the next optimal point.\n", - "Iteration No: 316 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7872\n", - "Function value obtained: -36.6981\n", - "Current minimum: -62.0848\n", - "Iteration No: 317 started. Searching for the next optimal point.\n", - "Iteration No: 317 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0321\n", - "Function value obtained: -49.0492\n", - "Current minimum: -62.0848\n", - "Iteration No: 318 started. Searching for the next optimal point.\n", - "Iteration No: 318 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9663\n", - "Function value obtained: -46.1612\n", - "Current minimum: -62.0848\n", - "Iteration No: 319 started. Searching for the next optimal point.\n", - "Iteration No: 319 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9349\n", - "Function value obtained: -41.6581\n", - "Current minimum: -62.0848\n", - "Iteration No: 320 started. Searching for the next optimal point.\n", - "Iteration No: 320 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8507\n", - "Function value obtained: -44.1575\n", - "Current minimum: -62.0848\n", - "Iteration No: 321 started. Searching for the next optimal point.\n", - "Iteration No: 321 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9261\n", - "Function value obtained: -48.7587\n", - "Current minimum: -62.0848\n", - "Iteration No: 322 started. Searching for the next optimal point.\n", - "Iteration No: 322 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9511\n", - "Function value obtained: -36.2154\n", - "Current minimum: -62.0848\n", - "Iteration No: 323 started. Searching for the next optimal point.\n", - "Iteration No: 323 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1912\n", - "Function value obtained: -44.1617\n", - "Current minimum: -62.0848\n", - "Iteration No: 324 started. Searching for the next optimal point.\n", - "Iteration No: 324 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0710\n", - "Function value obtained: -47.4263\n", - "Current minimum: -62.0848\n", - "Iteration No: 325 started. Searching for the next optimal point.\n", - "Iteration No: 325 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1461\n", - "Function value obtained: -48.5683\n", - "Current minimum: -62.0848\n", - "Iteration No: 326 started. Searching for the next optimal point.\n", - "Iteration No: 326 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0976\n", - "Function value obtained: -43.2309\n", - "Current minimum: -62.0848\n", - "Iteration No: 327 started. Searching for the next optimal point.\n", - "Iteration No: 327 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1396\n", - "Function value obtained: -46.0352\n", - "Current minimum: -62.0848\n", - "Iteration No: 328 started. Searching for the next optimal point.\n", - "Iteration No: 328 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2984\n", - "Function value obtained: -36.5720\n", - "Current minimum: -62.0848\n", - "Iteration No: 329 started. Searching for the next optimal point.\n", - "Iteration No: 329 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2580\n", - "Function value obtained: -43.7285\n", - "Current minimum: -62.0848\n", - "Iteration No: 330 started. Searching for the next optimal point.\n", - "Iteration No: 330 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9994\n", - "Function value obtained: -38.1015\n", - "Current minimum: -62.0848\n", - "Iteration No: 331 started. Searching for the next optimal point.\n", - "Iteration No: 331 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2654\n", - "Function value obtained: -41.8246\n", - "Current minimum: -62.0848\n", - "Iteration No: 332 started. Searching for the next optimal point.\n", - "Iteration No: 332 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2093\n", - "Function value obtained: -48.2369\n", - "Current minimum: -62.0848\n", - "Iteration No: 333 started. Searching for the next optimal point.\n", - "Iteration No: 333 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3989\n", - "Function value obtained: -50.9310\n", - "Current minimum: -62.0848\n", - "Iteration No: 334 started. Searching for the next optimal point.\n", - "Iteration No: 334 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1845\n", - "Function value obtained: -37.1273\n", - "Current minimum: -62.0848\n", - "Iteration No: 335 started. Searching for the next optimal point.\n", - "Iteration No: 335 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2108\n", - "Function value obtained: -47.1764\n", - "Current minimum: -62.0848\n", - "Iteration No: 336 started. Searching for the next optimal point.\n", - "Iteration No: 336 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2602\n", - "Function value obtained: -41.9352\n", - "Current minimum: -62.0848\n", - "Iteration No: 337 started. Searching for the next optimal point.\n", - "Iteration No: 337 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4141\n", - "Function value obtained: -36.2349\n", - "Current minimum: -62.0848\n", - "Iteration No: 338 started. Searching for the next optimal point.\n", - "Iteration No: 338 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2407\n", - "Function value obtained: -50.5504\n", - "Current minimum: -62.0848\n", - "Iteration No: 339 started. Searching for the next optimal point.\n", - "Iteration No: 339 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4717\n", - "Function value obtained: -42.9737\n", - "Current minimum: -62.0848\n", - "Iteration No: 340 started. Searching for the next optimal point.\n", - "Iteration No: 340 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4073\n", - "Function value obtained: -46.0320\n", - "Current minimum: -62.0848\n", - "Iteration No: 341 started. Searching for the next optimal point.\n", - "Iteration No: 341 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6070\n", - "Function value obtained: -39.7196\n", - "Current minimum: -62.0848\n", - "Iteration No: 342 started. Searching for the next optimal point.\n", - "Iteration No: 342 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4197\n", - "Function value obtained: -34.7234\n", - "Current minimum: -62.0848\n", - "Iteration No: 343 started. Searching for the next optimal point.\n", - "Iteration No: 343 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5346\n", - "Function value obtained: -40.2098\n", - "Current minimum: -62.0848\n", - "Iteration No: 344 started. Searching for the next optimal point.\n", - "Iteration No: 344 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7361\n", - "Function value obtained: -41.3051\n", - "Current minimum: -62.0848\n", - "Iteration No: 345 started. Searching for the next optimal point.\n", - "Iteration No: 345 ended. Search finished for the next optimal point.\n", - "Time taken: 6.8730\n", - "Function value obtained: -47.5180\n", - "Current minimum: -62.0848\n", - "Iteration No: 346 started. Searching for the next optimal point.\n", - "Iteration No: 346 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7296\n", - "Function value obtained: -46.1942\n", - "Current minimum: -62.0848\n", - "Iteration No: 347 started. Searching for the next optimal point.\n", - "Iteration No: 347 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7395\n", - "Function value obtained: -43.4554\n", - "Current minimum: -62.0848\n", - "Iteration No: 348 started. Searching for the next optimal point.\n", - "Iteration No: 348 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7614\n", - "Function value obtained: -49.0854\n", - "Current minimum: -62.0848\n", - "Iteration No: 349 started. Searching for the next optimal point.\n", - "Iteration No: 349 ended. Search finished for the next optimal point.\n", - "Time taken: 6.9352\n", - "Function value obtained: -58.4105\n", - "Current minimum: -62.0848\n", - "Iteration No: 350 started. Searching for the next optimal point.\n", - "Iteration No: 350 ended. Search finished for the next optimal point.\n", - "Time taken: 6.9954\n", - "Function value obtained: -40.3890\n", - "Current minimum: -62.0848\n", - "Iteration No: 351 started. Searching for the next optimal point.\n", - "Iteration No: 351 ended. Search finished for the next optimal point.\n", - "Time taken: 6.9944\n", - "Function value obtained: -40.1277\n", - "Current minimum: -62.0848\n", - "Iteration No: 352 started. Searching for the next optimal point.\n", - "Iteration No: 352 ended. Search finished for the next optimal point.\n", - "Time taken: 6.8876\n", - "Function value obtained: -50.6249\n", - "Current minimum: -62.0848\n", - "Iteration No: 353 started. Searching for the next optimal point.\n", - "Iteration No: 353 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0892\n", - "Function value obtained: -49.8234\n", - "Current minimum: -62.0848\n", - "Iteration No: 354 started. Searching for the next optimal point.\n", - "Iteration No: 354 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0292\n", - "Function value obtained: -32.2179\n", - "Current minimum: -62.0848\n", - "Iteration No: 355 started. Searching for the next optimal point.\n", - "Iteration No: 355 ended. Search finished for the next optimal point.\n", - "Time taken: 7.1229\n", - "Function value obtained: -34.1819\n", - "Current minimum: -62.0848\n", - "Iteration No: 356 started. Searching for the next optimal point.\n", - "Iteration No: 356 ended. Search finished for the next optimal point.\n", - "Time taken: 6.8827\n", - "Function value obtained: -37.8712\n", - "Current minimum: -62.0848\n", - "Iteration No: 357 started. Searching for the next optimal point.\n", - "Iteration No: 357 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0697\n", - "Function value obtained: -43.9711\n", - "Current minimum: -62.0848\n", - "Iteration No: 358 started. Searching for the next optimal point.\n", - "Iteration No: 358 ended. Search finished for the next optimal point.\n", - "Time taken: 6.8254\n", - "Function value obtained: -40.5878\n", - "Current minimum: -62.0848\n", - "Iteration No: 359 started. Searching for the next optimal point.\n", - "Iteration No: 359 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0879\n", - "Function value obtained: -39.8327\n", - "Current minimum: -62.0848\n", - "Iteration No: 360 started. Searching for the next optimal point.\n", - "Iteration No: 360 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0953\n", - "Function value obtained: -44.7983\n", - "Current minimum: -62.0848\n", - "Iteration No: 361 started. Searching for the next optimal point.\n", - "Iteration No: 361 ended. Search finished for the next optimal point.\n", - "Time taken: 7.3701\n", - "Function value obtained: -50.2493\n", - "Current minimum: -62.0848\n", - "Iteration No: 362 started. Searching for the next optimal point.\n", - "Iteration No: 362 ended. Search finished for the next optimal point.\n", - "Time taken: 7.1847\n", - "Function value obtained: -44.6589\n", - "Current minimum: -62.0848\n", - "Iteration No: 363 started. Searching for the next optimal point.\n", - "Iteration No: 363 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3229\n", - "Function value obtained: -50.4985\n", - "Current minimum: -62.0848\n", - "Iteration No: 364 started. Searching for the next optimal point.\n", - "Iteration No: 364 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2204\n", - "Function value obtained: -43.6125\n", - "Current minimum: -62.0848\n", - "Iteration No: 365 started. Searching for the next optimal point.\n", - "Iteration No: 365 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2064\n", - "Function value obtained: -46.7746\n", - "Current minimum: -62.0848\n", - "Iteration No: 366 started. Searching for the next optimal point.\n", - "Iteration No: 366 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0830\n", - "Function value obtained: -39.0693\n", - "Current minimum: -62.0848\n", - "Iteration No: 367 started. Searching for the next optimal point.\n", - "Iteration No: 367 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2747\n", - "Function value obtained: -42.3713\n", - "Current minimum: -62.0848\n", - "Iteration No: 368 started. Searching for the next optimal point.\n", - "Iteration No: 368 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1122\n", - "Function value obtained: -42.3931\n", - "Current minimum: -62.0848\n", - "Iteration No: 369 started. Searching for the next optimal point.\n", - "Iteration No: 369 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4148\n", - "Function value obtained: -46.9974\n", - "Current minimum: -62.0848\n", - "Iteration No: 370 started. Searching for the next optimal point.\n", - "Iteration No: 370 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3314\n", - "Function value obtained: -40.9012\n", - "Current minimum: -62.0848\n", - "Iteration No: 371 started. Searching for the next optimal point.\n", - "Iteration No: 371 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4648\n", - "Function value obtained: -44.1551\n", - "Current minimum: -62.0848\n", - "Iteration No: 372 started. Searching for the next optimal point.\n", - "Iteration No: 372 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5123\n", - "Function value obtained: -49.9785\n", - "Current minimum: -62.0848\n", - "Iteration No: 373 started. Searching for the next optimal point.\n", - "Iteration No: 373 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5294\n", - "Function value obtained: -50.9312\n", - "Current minimum: -62.0848\n", - "Iteration No: 374 started. Searching for the next optimal point.\n", - "Iteration No: 374 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4718\n", - "Function value obtained: -43.5286\n", - "Current minimum: -62.0848\n", - "Iteration No: 375 started. Searching for the next optimal point.\n", - "Iteration No: 375 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7431\n", - "Function value obtained: -49.7377\n", - "Current minimum: -62.0848\n", - "Iteration No: 376 started. Searching for the next optimal point.\n", - "Iteration No: 376 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5260\n", - "Function value obtained: -41.6945\n", - "Current minimum: -62.0848\n", - "Iteration No: 377 started. Searching for the next optimal point.\n", - "Iteration No: 377 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8125\n", - "Function value obtained: -58.7762\n", - "Current minimum: -62.0848\n", - "Iteration No: 378 started. Searching for the next optimal point.\n", - "Iteration No: 378 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4712\n", - "Function value obtained: -44.4876\n", - "Current minimum: -62.0848\n", - "Iteration No: 379 started. Searching for the next optimal point.\n", - "Iteration No: 379 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8947\n", - "Function value obtained: -41.6099\n", - "Current minimum: -62.0848\n", - "Iteration No: 380 started. Searching for the next optimal point.\n", - "Iteration No: 380 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6968\n", - "Function value obtained: -43.6403\n", - "Current minimum: -62.0848\n", - "Iteration No: 381 started. Searching for the next optimal point.\n", - "Iteration No: 381 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8508\n", - "Function value obtained: -43.1346\n", - "Current minimum: -62.0848\n", - "Iteration No: 382 started. Searching for the next optimal point.\n", - "Iteration No: 382 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6416\n", - "Function value obtained: -42.9715\n", - "Current minimum: -62.0848\n", - "Iteration No: 383 started. Searching for the next optimal point.\n", - "Iteration No: 383 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8701\n", - "Function value obtained: -42.1922\n", - "Current minimum: -62.0848\n", - "Iteration No: 384 started. Searching for the next optimal point.\n", - "Iteration No: 384 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7069\n", - "Function value obtained: -37.7752\n", - "Current minimum: -62.0848\n", - "Iteration No: 385 started. Searching for the next optimal point.\n", - "Iteration No: 385 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8220\n", - "Function value obtained: -51.0735\n", - "Current minimum: -62.0848\n", - "Iteration No: 386 started. Searching for the next optimal point.\n", - "Iteration No: 386 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9062\n", - "Function value obtained: -49.4380\n", - "Current minimum: -62.0848\n", - "Iteration No: 387 started. Searching for the next optimal point.\n", - "Iteration No: 387 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8983\n", - "Function value obtained: -42.1732\n", - "Current minimum: -62.0848\n", - "Iteration No: 388 started. Searching for the next optimal point.\n", - "Iteration No: 388 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8272\n", - "Function value obtained: -41.8999\n", - "Current minimum: -62.0848\n", - "Iteration No: 389 started. Searching for the next optimal point.\n", - "Iteration No: 389 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0679\n", - "Function value obtained: -42.5240\n", - "Current minimum: -62.0848\n", - "Iteration No: 390 started. Searching for the next optimal point.\n", - "Iteration No: 390 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2189\n", - "Function value obtained: -44.7654\n", - "Current minimum: -62.0848\n", - "Iteration No: 391 started. Searching for the next optimal point.\n", - "Iteration No: 391 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3021\n", - "Function value obtained: -48.1590\n", - "Current minimum: -62.0848\n", - "Iteration No: 392 started. Searching for the next optimal point.\n", - "Iteration No: 392 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0857\n", - "Function value obtained: -38.9403\n", - "Current minimum: -62.0848\n", - "Iteration No: 393 started. Searching for the next optimal point.\n", - "Iteration No: 393 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4513\n", - "Function value obtained: -40.9373\n", - "Current minimum: -62.0848\n", - "Iteration No: 394 started. Searching for the next optimal point.\n", - "Iteration No: 394 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0098\n", - "Function value obtained: -44.3036\n", - "Current minimum: -62.0848\n", - "Iteration No: 395 started. Searching for the next optimal point.\n", - "Iteration No: 395 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1381\n", - "Function value obtained: -47.8040\n", - "Current minimum: -62.0848\n", - "Iteration No: 396 started. Searching for the next optimal point.\n", - "Iteration No: 396 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0878\n", - "Function value obtained: -39.9254\n", - "Current minimum: -62.0848\n", - "Iteration No: 397 started. Searching for the next optimal point.\n", - "Iteration No: 397 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3544\n", - "Function value obtained: -41.5138\n", - "Current minimum: -62.0848\n", - "Iteration No: 398 started. Searching for the next optimal point.\n", - "Iteration No: 398 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3346\n", - "Function value obtained: -45.0969\n", - "Current minimum: -62.0848\n", - "Iteration No: 399 started. Searching for the next optimal point.\n", - "Iteration No: 399 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3438\n", - "Function value obtained: -47.1320\n", - "Current minimum: -62.0848\n", - "Iteration No: 400 started. Searching for the next optimal point.\n", - "Iteration No: 400 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0000\n", - "Function value obtained: -51.6540\n", - "Current minimum: -62.0848\n", - "Iteration No: 401 started. Searching for the next optimal point.\n", - "Iteration No: 401 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5265\n", - "Function value obtained: -41.4070\n", - "Current minimum: -62.0848\n", - "Iteration No: 402 started. Searching for the next optimal point.\n", - "Iteration No: 402 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4849\n", - "Function value obtained: -41.8113\n", - "Current minimum: -62.0848\n", - "Iteration No: 403 started. Searching for the next optimal point.\n", - "Iteration No: 403 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4883\n", - "Function value obtained: -35.3715\n", - "Current minimum: -62.0848\n", - "Iteration No: 404 started. Searching for the next optimal point.\n", - "Iteration No: 404 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5293\n", - "Function value obtained: -44.1708\n", - "Current minimum: -62.0848\n", - "Iteration No: 405 started. Searching for the next optimal point.\n", - "Iteration No: 405 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7495\n", - "Function value obtained: -42.3582\n", - "Current minimum: -62.0848\n", - "Iteration No: 406 started. Searching for the next optimal point.\n", - "Iteration No: 406 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4702\n", - "Function value obtained: -48.9758\n", - "Current minimum: -62.0848\n", - "Iteration No: 407 started. Searching for the next optimal point.\n", - "Iteration No: 407 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6385\n", - "Function value obtained: -39.6355\n", - "Current minimum: -62.0848\n", - "Iteration No: 408 started. Searching for the next optimal point.\n", - "Iteration No: 408 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4234\n", - "Function value obtained: -45.8120\n", - "Current minimum: -62.0848\n", - "Iteration No: 409 started. Searching for the next optimal point.\n", - "Iteration No: 409 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8418\n", - "Function value obtained: -53.8279\n", - "Current minimum: -62.0848\n", - "Iteration No: 410 started. Searching for the next optimal point.\n", - "Iteration No: 410 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7073\n", - "Function value obtained: -38.6384\n", - "Current minimum: -62.0848\n", - "Iteration No: 411 started. Searching for the next optimal point.\n", - "Iteration No: 411 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9269\n", - "Function value obtained: -43.7134\n", - "Current minimum: -62.0848\n", - "Iteration No: 412 started. Searching for the next optimal point.\n", - "Iteration No: 412 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8630\n", - "Function value obtained: -43.9069\n", - "Current minimum: -62.0848\n", - "Iteration No: 413 started. Searching for the next optimal point.\n", - "Iteration No: 413 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9665\n", - "Function value obtained: -39.1919\n", - "Current minimum: -62.0848\n", - "Iteration No: 414 started. Searching for the next optimal point.\n", - "Iteration No: 414 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8831\n", - "Function value obtained: -42.0928\n", - "Current minimum: -62.0848\n", - "Iteration No: 415 started. Searching for the next optimal point.\n", - "Iteration No: 415 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8693\n", - "Function value obtained: -39.6739\n", - "Current minimum: -62.0848\n", - "Iteration No: 416 started. Searching for the next optimal point.\n", - "Iteration No: 416 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8230\n", - "Function value obtained: -44.6665\n", - "Current minimum: -62.0848\n", - "Iteration No: 417 started. Searching for the next optimal point.\n", - "Iteration No: 417 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0235\n", - "Function value obtained: -34.2864\n", - "Current minimum: -62.0848\n", - "Iteration No: 418 started. Searching for the next optimal point.\n", - "Iteration No: 418 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8918\n", - "Function value obtained: -50.9597\n", - "Current minimum: -62.0848\n", - "Iteration No: 419 started. Searching for the next optimal point.\n", - "Iteration No: 419 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3810\n", - "Function value obtained: -42.4145\n", - "Current minimum: -62.0848\n", - "Iteration No: 420 started. Searching for the next optimal point.\n", - "Iteration No: 420 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2269\n", - "Function value obtained: -43.6491\n", - "Current minimum: -62.0848\n", - "Iteration No: 421 started. Searching for the next optimal point.\n", - "Iteration No: 421 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3506\n", - "Function value obtained: -44.2672\n", - "Current minimum: -62.0848\n", - "Iteration No: 422 started. Searching for the next optimal point.\n", - "Iteration No: 422 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1861\n", - "Function value obtained: -45.7577\n", - "Current minimum: -62.0848\n", - "Iteration No: 423 started. Searching for the next optimal point.\n", - "Iteration No: 423 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4009\n", - "Function value obtained: -44.2733\n", - "Current minimum: -62.0848\n", - "Iteration No: 424 started. Searching for the next optimal point.\n", - "Iteration No: 424 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1522\n", - "Function value obtained: -41.9754\n", - "Current minimum: -62.0848\n", - "Iteration No: 425 started. Searching for the next optimal point.\n", - "Iteration No: 425 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3443\n", - "Function value obtained: -42.8176\n", - "Current minimum: -62.0848\n", - "Iteration No: 426 started. Searching for the next optimal point.\n", - "Iteration No: 426 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3663\n", - "Function value obtained: -34.4976\n", - "Current minimum: -62.0848\n", - "Iteration No: 427 started. Searching for the next optimal point.\n", - "Iteration No: 427 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5607\n", - "Function value obtained: -41.2437\n", - "Current minimum: -62.0848\n", - "Iteration No: 428 started. Searching for the next optimal point.\n", - "Iteration No: 428 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4030\n", - "Function value obtained: -40.3337\n", - "Current minimum: -62.0848\n", - "Iteration No: 429 started. Searching for the next optimal point.\n", - "Iteration No: 429 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7401\n", - "Function value obtained: -42.7095\n", - "Current minimum: -62.0848\n", - "Iteration No: 430 started. Searching for the next optimal point.\n", - "Iteration No: 430 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4478\n", - "Function value obtained: -49.0335\n", - "Current minimum: -62.0848\n", - "Iteration No: 431 started. Searching for the next optimal point.\n", - "Iteration No: 431 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6153\n", - "Function value obtained: -53.2577\n", - "Current minimum: -62.0848\n", - "Iteration No: 432 started. Searching for the next optimal point.\n", - "Iteration No: 432 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6497\n", - "Function value obtained: -47.6350\n", - "Current minimum: -62.0848\n", - "Iteration No: 433 started. Searching for the next optimal point.\n", - "Iteration No: 433 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7290\n", - "Function value obtained: -42.2877\n", - "Current minimum: -62.0848\n", - "Iteration No: 434 started. Searching for the next optimal point.\n", - "Iteration No: 434 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5694\n", - "Function value obtained: -40.2589\n", - "Current minimum: -62.0848\n", - "Iteration No: 435 started. Searching for the next optimal point.\n", - "Iteration No: 435 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7442\n", - "Function value obtained: -44.2691\n", - "Current minimum: -62.0848\n", - "Iteration No: 436 started. Searching for the next optimal point.\n", - "Iteration No: 436 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5295\n", - "Function value obtained: -44.2008\n", - "Current minimum: -62.0848\n", - "Iteration No: 437 started. Searching for the next optimal point.\n", - "Iteration No: 437 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7623\n", - "Function value obtained: -42.1854\n", - "Current minimum: -62.0848\n", - "Iteration No: 438 started. Searching for the next optimal point.\n", - "Iteration No: 438 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6952\n", - "Function value obtained: -45.9682\n", - "Current minimum: -62.0848\n", - "Iteration No: 439 started. Searching for the next optimal point.\n", - "Iteration No: 439 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8595\n", - "Function value obtained: -50.5885\n", - "Current minimum: -62.0848\n", - "Iteration No: 440 started. Searching for the next optimal point.\n", - "Iteration No: 440 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8325\n", - "Function value obtained: -41.1151\n", - "Current minimum: -62.0848\n", - "Iteration No: 441 started. Searching for the next optimal point.\n", - "Iteration No: 441 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2773\n", - "Function value obtained: -38.7506\n", - "Current minimum: -62.0848\n", - "Iteration No: 442 started. Searching for the next optimal point.\n", - "Iteration No: 442 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8389\n", - "Function value obtained: -44.8393\n", - "Current minimum: -62.0848\n", - "Iteration No: 443 started. Searching for the next optimal point.\n", - "Iteration No: 443 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2978\n", - "Function value obtained: -40.0145\n", - "Current minimum: -62.0848\n", - "Iteration No: 444 started. Searching for the next optimal point.\n", - "Iteration No: 444 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7589\n", - "Function value obtained: -43.4468\n", - "Current minimum: -62.0848\n", - "Iteration No: 445 started. Searching for the next optimal point.\n", - "Iteration No: 445 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0824\n", - "Function value obtained: -44.4086\n", - "Current minimum: -62.0848\n", - "Iteration No: 446 started. Searching for the next optimal point.\n", - "Iteration No: 446 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8075\n", - "Function value obtained: -53.1702\n", - "Current minimum: -62.0848\n", - "Iteration No: 447 started. Searching for the next optimal point.\n", - "Iteration No: 447 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1833\n", - "Function value obtained: -46.0922\n", - "Current minimum: -62.0848\n", - "Iteration No: 448 started. Searching for the next optimal point.\n", - "Iteration No: 448 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8232\n", - "Function value obtained: -37.9052\n", - "Current minimum: -62.0848\n", - "Iteration No: 449 started. Searching for the next optimal point.\n", - "Iteration No: 449 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1775\n", - "Function value obtained: -46.9470\n", - "Current minimum: -62.0848\n", - "Iteration No: 450 started. Searching for the next optimal point.\n", - "Iteration No: 450 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1647\n", - "Function value obtained: -42.3826\n", - "Current minimum: -62.0848\n", - "Iteration No: 451 started. Searching for the next optimal point.\n", - "Iteration No: 451 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4954\n", - "Function value obtained: -48.7315\n", - "Current minimum: -62.0848\n", - "Iteration No: 452 started. Searching for the next optimal point.\n", - "Iteration No: 452 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2494\n", - "Function value obtained: -41.3358\n", - "Current minimum: -62.0848\n", - "Iteration No: 453 started. Searching for the next optimal point.\n", - "Iteration No: 453 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3114\n", - "Function value obtained: -37.0468\n", - "Current minimum: -62.0848\n", - "Iteration No: 454 started. Searching for the next optimal point.\n", - "Iteration No: 454 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2661\n", - "Function value obtained: -39.7277\n", - "Current minimum: -62.0848\n", - "Iteration No: 455 started. Searching for the next optimal point.\n", - "Iteration No: 455 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6177\n", - "Function value obtained: -42.0263\n", - "Current minimum: -62.0848\n", - "Iteration No: 456 started. Searching for the next optimal point.\n", - "Iteration No: 456 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3179\n", - "Function value obtained: -43.5158\n", - "Current minimum: -62.0848\n", - "Iteration No: 457 started. Searching for the next optimal point.\n", - "Iteration No: 457 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6060\n", - "Function value obtained: -35.2703\n", - "Current minimum: -62.0848\n", - "Iteration No: 458 started. Searching for the next optimal point.\n", - "Iteration No: 458 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5465\n", - "Function value obtained: -41.1592\n", - "Current minimum: -62.0848\n", - "Iteration No: 459 started. Searching for the next optimal point.\n", - "Iteration No: 459 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8640\n", - "Function value obtained: -43.5631\n", - "Current minimum: -62.0848\n", - "Iteration No: 460 started. Searching for the next optimal point.\n", - "Iteration No: 460 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6776\n", - "Function value obtained: -44.0784\n", - "Current minimum: -62.0848\n", - "Iteration No: 461 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:449: UserWarning: The objective has been evaluated at this point before.\n", - " warnings.warn(\"The objective has been evaluated \"\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 461 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5517\n", - "Function value obtained: -47.8013\n", - "Current minimum: -62.0848\n", - "Iteration No: 462 started. Searching for the next optimal point.\n", - "Iteration No: 462 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6241\n", - "Function value obtained: -45.2473\n", - "Current minimum: -62.0848\n", - "Iteration No: 463 started. Searching for the next optimal point.\n", - "Iteration No: 463 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8598\n", - "Function value obtained: -41.5950\n", - "Current minimum: -62.0848\n", - "Iteration No: 464 started. Searching for the next optimal point.\n", - "Iteration No: 464 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4720\n", - "Function value obtained: -55.2877\n", - "Current minimum: -62.0848\n", - "Iteration No: 465 started. Searching for the next optimal point.\n", - "Iteration No: 465 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9496\n", - "Function value obtained: -37.7770\n", - "Current minimum: -62.0848\n", - "Iteration No: 466 started. Searching for the next optimal point.\n", - "Iteration No: 466 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6398\n", - "Function value obtained: -40.4458\n", - "Current minimum: -62.0848\n", - "Iteration No: 467 started. Searching for the next optimal point.\n", - "Iteration No: 467 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1696\n", - "Function value obtained: -44.4001\n", - "Current minimum: -62.0848\n", - "Iteration No: 468 started. Searching for the next optimal point.\n", - "Iteration No: 468 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8581\n", - "Function value obtained: -40.9912\n", - "Current minimum: -62.0848\n", - "Iteration No: 469 started. Searching for the next optimal point.\n", - "Iteration No: 469 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1190\n", - "Function value obtained: -43.6360\n", - "Current minimum: -62.0848\n", - "Iteration No: 470 started. Searching for the next optimal point.\n", - "Iteration No: 470 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2375\n", - "Function value obtained: -51.5146\n", - "Current minimum: -62.0848\n", - "Iteration No: 471 started. Searching for the next optimal point.\n", - "Iteration No: 471 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1895\n", - "Function value obtained: -46.2785\n", - "Current minimum: -62.0848\n", - "Iteration No: 472 started. Searching for the next optimal point.\n", - "Iteration No: 472 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0899\n", - "Function value obtained: -48.0914\n", - "Current minimum: -62.0848\n", - "Iteration No: 473 started. Searching for the next optimal point.\n", - "Iteration No: 473 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4725\n", - "Function value obtained: -47.7781\n", - "Current minimum: -62.0848\n", - "Iteration No: 474 started. Searching for the next optimal point.\n", - "Iteration No: 474 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9882\n", - "Function value obtained: -47.8958\n", - "Current minimum: -62.0848\n", - "Iteration No: 475 started. Searching for the next optimal point.\n", - "Iteration No: 475 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2896\n", - "Function value obtained: -46.6943\n", - "Current minimum: -62.0848\n", - "Iteration No: 476 started. Searching for the next optimal point.\n", - "Iteration No: 476 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1872\n", - "Function value obtained: -40.1902\n", - "Current minimum: -62.0848\n", - "Iteration No: 477 started. Searching for the next optimal point.\n", - "Iteration No: 477 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3488\n", - "Function value obtained: -47.9131\n", - "Current minimum: -62.0848\n", - "Iteration No: 478 started. Searching for the next optimal point.\n", - "Iteration No: 478 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3300\n", - "Function value obtained: -45.4172\n", - "Current minimum: -62.0848\n", - "Iteration No: 479 started. Searching for the next optimal point.\n", - "Iteration No: 479 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6102\n", - "Function value obtained: -39.3030\n", - "Current minimum: -62.0848\n", - "Iteration No: 480 started. Searching for the next optimal point.\n", - "Iteration No: 480 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4159\n", - "Function value obtained: -49.4257\n", - "Current minimum: -62.0848\n", - "Iteration No: 481 started. Searching for the next optimal point.\n", - "Iteration No: 481 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6931\n", - "Function value obtained: -43.7049\n", - "Current minimum: -62.0848\n", - "Iteration No: 482 started. Searching for the next optimal point.\n", - "Iteration No: 482 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5197\n", - "Function value obtained: -47.4038\n", - "Current minimum: -62.0848\n", - "Iteration No: 483 started. Searching for the next optimal point.\n", - "Iteration No: 483 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7771\n", - "Function value obtained: -41.7676\n", - "Current minimum: -62.0848\n", - "Iteration No: 484 started. Searching for the next optimal point.\n", - "Iteration No: 484 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5350\n", - "Function value obtained: -44.2924\n", - "Current minimum: -62.0848\n", - "Iteration No: 485 started. Searching for the next optimal point.\n", - "Iteration No: 485 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6652\n", - "Function value obtained: -40.1080\n", - "Current minimum: -62.0848\n", - "Iteration No: 486 started. Searching for the next optimal point.\n", - "Iteration No: 486 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9769\n", - "Function value obtained: -35.5416\n", - "Current minimum: -62.0848\n", - "Iteration No: 487 started. Searching for the next optimal point.\n", - "Iteration No: 487 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8828\n", - "Function value obtained: -53.9918\n", - "Current minimum: -62.0848\n", - "Iteration No: 488 started. Searching for the next optimal point.\n", - "Iteration No: 488 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8949\n", - "Function value obtained: -42.1735\n", - "Current minimum: -62.0848\n", - "Iteration No: 489 started. Searching for the next optimal point.\n", - "Iteration No: 489 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9234\n", - "Function value obtained: -45.2254\n", - "Current minimum: -62.0848\n", - "Iteration No: 490 started. Searching for the next optimal point.\n", - "Iteration No: 490 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7154\n", - "Function value obtained: -52.7972\n", - "Current minimum: -62.0848\n", - "Iteration No: 491 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:449: UserWarning: The objective has been evaluated at this point before.\n", - " warnings.warn(\"The objective has been evaluated \"\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 491 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9142\n", - "Function value obtained: -41.1283\n", - "Current minimum: -62.0848\n", - "Iteration No: 492 started. Searching for the next optimal point.\n", - "Iteration No: 492 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9688\n", - "Function value obtained: -47.3437\n", - "Current minimum: -62.0848\n", - "Iteration No: 493 started. Searching for the next optimal point.\n", - "Iteration No: 493 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2509\n", - "Function value obtained: -38.7203\n", - "Current minimum: -62.0848\n", - "Iteration No: 494 started. Searching for the next optimal point.\n", - "Iteration No: 494 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0143\n", - "Function value obtained: -42.6341\n", - "Current minimum: -62.0848\n", - "Iteration No: 495 started. Searching for the next optimal point.\n", - "Iteration No: 495 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0975\n", - "Function value obtained: -41.0785\n", - "Current minimum: -62.0848\n", - "Iteration No: 496 started. Searching for the next optimal point.\n", - "Iteration No: 496 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3136\n", - "Function value obtained: -43.9491\n", - "Current minimum: -62.0848\n", - "Iteration No: 497 started. Searching for the next optimal point.\n", - "Iteration No: 497 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2135\n", - "Function value obtained: -50.3762\n", - "Current minimum: -62.0848\n", - "Iteration No: 498 started. Searching for the next optimal point.\n", - "Iteration No: 498 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2782\n", - "Function value obtained: -45.8174\n", - "Current minimum: -62.0848\n", - "Iteration No: 499 started. Searching for the next optimal point.\n", - "Iteration No: 499 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3866\n", - "Function value obtained: -45.5974\n", - "Current minimum: -62.0848\n", - "Iteration No: 500 started. Searching for the next optimal point.\n", - "Iteration No: 500 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0844\n", - "Function value obtained: -48.9054\n", - "Current minimum: -62.0848\n", - "CPU times: user 59min 31s, sys: 1h 56min 21s, total: 2h 55min 52s\n", - "Wall time: 49min 15s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-62.08484130000001, [0.058590822346937174])" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "msy_gp = gp_minimize(msy_fun, [(0.002, 0.25)], n_calls = 100, verbose=True, n_jobs=-1)\n", - "msy_gp.fun, msy_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "01d309be-d7c2-4af1-afbc-3b91c42c1a6c", - "metadata": {}, - "outputs": [], - "source": [ - "# -> (-62.08484130000001, [0.058590822346937174])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dabc6e34-7a25-4b2d-b8b1-294b59f60ca0", - "metadata": {}, - "outputs": [], - "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"msy_gp.pkl\"\n", - "dump(msy_gp, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "4c5c2ec8-f61b-4dae-bc1b-ba70310a694b", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.0914\n", - "Function value obtained: -29.0648\n", - "Current minimum: -29.0648\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.0919\n", - "Function value obtained: -43.3516\n", - "Current minimum: -43.3516\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.0924\n", - "Function value obtained: -43.5100\n", - "Current minimum: -43.5100\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.0973\n", - "Function value obtained: -46.0853\n", - "Current minimum: -46.0853\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.0984\n", - "Function value obtained: -42.9894\n", - "Current minimum: -46.0853\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.1082\n", - "Function value obtained: -41.3878\n", - "Current minimum: -46.0853\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.1002\n", - "Function value obtained: -38.6940\n", - "Current minimum: -46.0853\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.0930\n", - "Function value obtained: -23.7426\n", - "Current minimum: -46.0853\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.0856\n", - "Function value obtained: -30.3279\n", - "Current minimum: -46.0853\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.2134\n", - "Function value obtained: -36.4970\n", - "Current minimum: -46.0853\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3040\n", - "Function value obtained: -44.5027\n", - "Current minimum: -46.0853\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1948\n", - "Function value obtained: -32.2485\n", - "Current minimum: -46.0853\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2283\n", - "Function value obtained: -41.3923\n", - "Current minimum: -46.0853\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2460\n", - "Function value obtained: -44.9274\n", - "Current minimum: -46.0853\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2421\n", - "Function value obtained: -51.5324\n", - "Current minimum: -51.5324\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2633\n", - "Function value obtained: -44.5778\n", - "Current minimum: -51.5324\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2475\n", - "Function value obtained: -32.6334\n", - "Current minimum: -51.5324\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2571\n", - "Function value obtained: -37.0061\n", - "Current minimum: -51.5324\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2576\n", - "Function value obtained: -37.8722\n", - "Current minimum: -51.5324\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2550\n", - "Function value obtained: -43.8061\n", - "Current minimum: -51.5324\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2523\n", - "Function value obtained: -48.3358\n", - "Current minimum: -51.5324\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2700\n", - "Function value obtained: -45.6882\n", - "Current minimum: -51.5324\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2545\n", - "Function value obtained: -47.6009\n", - "Current minimum: -51.5324\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2552\n", - "Function value obtained: -44.8454\n", - "Current minimum: -51.5324\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3687\n", - "Function value obtained: -57.1683\n", - "Current minimum: -57.1683\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2711\n", - "Function value obtained: -41.0737\n", - "Current minimum: -57.1683\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2394\n", - "Function value obtained: -43.9220\n", - "Current minimum: -57.1683\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2445\n", - "Function value obtained: -47.9115\n", - "Current minimum: -57.1683\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2466\n", - "Function value obtained: -42.9434\n", - "Current minimum: -57.1683\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2755\n", - "Function value obtained: -56.9780\n", - "Current minimum: -57.1683\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2595\n", - "Function value obtained: -50.2239\n", - "Current minimum: -57.1683\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2731\n", - "Function value obtained: -45.6714\n", - "Current minimum: -57.1683\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2556\n", - "Function value obtained: -48.8691\n", - "Current minimum: -57.1683\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2537\n", - "Function value obtained: -44.7308\n", - "Current minimum: -57.1683\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2691\n", - "Function value obtained: -22.9931\n", - "Current minimum: -57.1683\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2652\n", - "Function value obtained: -53.4057\n", - "Current minimum: -57.1683\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2340\n", - "Function value obtained: -43.0728\n", - "Current minimum: -57.1683\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3574\n", - "Function value obtained: -50.4005\n", - "Current minimum: -57.1683\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2359\n", - "Function value obtained: -45.5303\n", - "Current minimum: -57.1683\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2365\n", - "Function value obtained: -17.9136\n", - "Current minimum: -57.1683\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2318\n", - "Function value obtained: -53.2615\n", - "Current minimum: -57.1683\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2640\n", - "Function value obtained: -24.4683\n", - "Current minimum: -57.1683\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:449: UserWarning: The objective has been evaluated at this point before.\n", - " warnings.warn(\"The objective has been evaluated \"\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2440\n", - "Function value obtained: -39.6403\n", - "Current minimum: -57.1683\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2345\n", - "Function value obtained: -21.5861\n", - "Current minimum: -57.1683\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2316\n", - "Function value obtained: -42.6638\n", - "Current minimum: -57.1683\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2640\n", - "Function value obtained: -21.5203\n", - "Current minimum: -57.1683\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2433\n", - "Function value obtained: -41.4619\n", - "Current minimum: -57.1683\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2569\n", - "Function value obtained: -27.7758\n", - "Current minimum: -57.1683\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2313\n", - "Function value obtained: -52.7370\n", - "Current minimum: -57.1683\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2343\n", - "Function value obtained: -20.2515\n", - "Current minimum: -57.1683\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2503\n", - "Function value obtained: -43.2511\n", - "Current minimum: -57.1683\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2482\n", - "Function value obtained: -18.7646\n", - "Current minimum: -57.1683\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2523\n", - "Function value obtained: -41.3222\n", - "Current minimum: -57.1683\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3540\n", - "Function value obtained: -54.8476\n", - "Current minimum: -57.1683\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2531\n", - "Function value obtained: -36.1804\n", - "Current minimum: -57.1683\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2650\n", - "Function value obtained: -39.6648\n", - "Current minimum: -57.1683\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2715\n", - "Function value obtained: -47.8828\n", - "Current minimum: -57.1683\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2538\n", - "Function value obtained: -41.6010\n", - "Current minimum: -57.1683\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2655\n", - "Function value obtained: -38.7556\n", - "Current minimum: -57.1683\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2611\n", - "Function value obtained: -49.9988\n", - "Current minimum: -57.1683\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2785\n", - "Function value obtained: -42.6122\n", - "Current minimum: -57.1683\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2857\n", - "Function value obtained: -22.7983\n", - "Current minimum: -57.1683\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2869\n", - "Function value obtained: -38.5908\n", - "Current minimum: -57.1683\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2591\n", - "Function value obtained: -49.0260\n", - "Current minimum: -57.1683\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2604\n", - "Function value obtained: -24.3687\n", - "Current minimum: -57.1683\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2354\n", - "Function value obtained: -26.5818\n", - "Current minimum: -57.1683\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2431\n", - "Function value obtained: -44.4036\n", - "Current minimum: -57.1683\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2809\n", - "Function value obtained: -43.2633\n", - "Current minimum: -57.1683\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3522\n", - "Function value obtained: -52.3673\n", - "Current minimum: -57.1683\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2588\n", - "Function value obtained: -40.0792\n", - "Current minimum: -57.1683\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2624\n", - "Function value obtained: -52.5677\n", - "Current minimum: -57.1683\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2591\n", - "Function value obtained: -45.4142\n", - "Current minimum: -57.1683\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2823\n", - "Function value obtained: -40.1673\n", - "Current minimum: -57.1683\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2878\n", - "Function value obtained: -50.3546\n", - "Current minimum: -57.1683\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2808\n", - "Function value obtained: -35.6770\n", - "Current minimum: -57.1683\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2640\n", - "Function value obtained: -46.3193\n", - "Current minimum: -57.1683\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2550\n", - "Function value obtained: -37.6342\n", - "Current minimum: -57.1683\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2915\n", - "Function value obtained: -47.3047\n", - "Current minimum: -57.1683\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2765\n", - "Function value obtained: -50.0168\n", - "Current minimum: -57.1683\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2553\n", - "Function value obtained: -39.9186\n", - "Current minimum: -57.1683\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2754\n", - "Function value obtained: -47.1404\n", - "Current minimum: -57.1683\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2740\n", - "Function value obtained: -47.3352\n", - "Current minimum: -57.1683\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3719\n", - "Function value obtained: -49.2820\n", - "Current minimum: -57.1683\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2996\n", - "Function value obtained: -47.2134\n", - "Current minimum: -57.1683\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2643\n", - "Function value obtained: -48.1160\n", - "Current minimum: -57.1683\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3104\n", - "Function value obtained: -56.5423\n", - "Current minimum: -57.1683\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2740\n", - "Function value obtained: -42.7004\n", - "Current minimum: -57.1683\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2731\n", - "Function value obtained: -48.0647\n", - "Current minimum: -57.1683\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2614\n", - "Function value obtained: -45.5973\n", - "Current minimum: -57.1683\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2559\n", - "Function value obtained: -38.0671\n", - "Current minimum: -57.1683\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2741\n", - "Function value obtained: -47.3520\n", - "Current minimum: -57.1683\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2581\n", - "Function value obtained: -49.7922\n", - "Current minimum: -57.1683\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2482\n", - "Function value obtained: -48.8608\n", - "Current minimum: -57.1683\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2624\n", - "Function value obtained: -55.2493\n", - "Current minimum: -57.1683\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2502\n", - "Function value obtained: -36.4576\n", - "Current minimum: -57.1683\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2553\n", - "Function value obtained: -43.7821\n", - "Current minimum: -57.1683\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2584\n", - "Function value obtained: -41.2951\n", - "Current minimum: -57.1683\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2693\n", - "Function value obtained: -39.7271\n", - "Current minimum: -57.1683\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3447\n", - "Function value obtained: -50.5967\n", - "Current minimum: -57.1683\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2437\n", - "Function value obtained: -41.7235\n", - "Current minimum: -57.1683\n", - "CPU times: user 2min 4s, sys: 2.89 s, total: 2min 7s\n", - "Wall time: 2min 4s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-57.168266599999995, [0.05811506272614242])" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "msy_gbrt = gbrt_minimize(msy_fun, [(0.02, 0.15)], n_calls = 100, verbose=True, n_jobs=-1)\n", - "msy_gbrt.fun, msy_gbrt.x" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "07918bc7-cdb2-4966-b24a-ac53db2f49ec", - "metadata": {}, - "outputs": [], - "source": [ - "# -> (-57.168266599999995, [0.05811506272614242])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "05db66a7-a0f0-46e5-abd6-f57f8bb1bc59", - "metadata": {}, - "outputs": [], - "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"msy_gbrt.pkl\"\n", - "dump(msy_gbrt, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "95f89094-fd18-433b-a3fc-1e45d3e2e1ad", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(msy_gp)" - ] - }, - { - "cell_type": "markdown", - "id": "1206af08-4695-422c-95f0-25a9da2a4299", - "metadata": { - "jupyter": { - "source_hidden": true - } - }, - "source": [ - "## Const Escapement" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "05fc9be0-b0d0-4822-99ca-f0fcf2304ae4", - "metadata": {}, - "outputs": [], - "source": [ - "def esc_fun(x):\n", - " agent = ConstEsc(escapement=x[0])\n", - " mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100)\n", - " return -mean" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "2aa1a6e7-dc64-410d-9850-db17810c0f03", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.1125\n", - "Function value obtained: -3.9773\n", - "Current minimum: -3.9773\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.1054\n", - "Function value obtained: -38.1530\n", - "Current minimum: -38.1530\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.1181\n", - "Function value obtained: -21.7307\n", - "Current minimum: -38.1530\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.1157\n", - "Function value obtained: -36.2086\n", - "Current minimum: -38.1530\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.1056\n", - "Function value obtained: -24.0937\n", - "Current minimum: -38.1530\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.0928\n", - "Function value obtained: -5.1459\n", - "Current minimum: -38.1530\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.1170\n", - "Function value obtained: -21.2069\n", - "Current minimum: -38.1530\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.1333\n", - "Function value obtained: -49.0214\n", - "Current minimum: -49.0214\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.1277\n", - "Function value obtained: -37.6727\n", - "Current minimum: -49.0214\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.2919\n", - "Function value obtained: -40.8870\n", - "Current minimum: -49.0214\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3067\n", - "Function value obtained: -38.5334\n", - "Current minimum: -49.0214\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3012\n", - "Function value obtained: -47.2189\n", - "Current minimum: -49.0214\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2986\n", - "Function value obtained: -38.1800\n", - "Current minimum: -49.0214\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2706\n", - "Function value obtained: -37.5077\n", - "Current minimum: -49.0214\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3252\n", - "Function value obtained: -48.2262\n", - "Current minimum: -49.0214\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2999\n", - "Function value obtained: -47.9262\n", - "Current minimum: -49.0214\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3049\n", - "Function value obtained: -44.9649\n", - "Current minimum: -49.0214\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2984\n", - "Function value obtained: -41.4813\n", - "Current minimum: -49.0214\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2901\n", - "Function value obtained: -13.7119\n", - "Current minimum: -49.0214\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2784\n", - "Function value obtained: -45.2000\n", - "Current minimum: -49.0214\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2901\n", - "Function value obtained: -40.7887\n", - "Current minimum: -49.0214\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2931\n", - "Function value obtained: -46.4346\n", - "Current minimum: -49.0214\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3727\n", - "Function value obtained: -48.9453\n", - "Current minimum: -49.0214\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3171\n", - "Function value obtained: -46.8879\n", - "Current minimum: -49.0214\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3280\n", - "Function value obtained: -48.5425\n", - "Current minimum: -49.0214\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3255\n", - "Function value obtained: -39.8208\n", - "Current minimum: -49.0214\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3628\n", - "Function value obtained: -48.4440\n", - "Current minimum: -49.0214\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3881\n", - "Function value obtained: -50.1338\n", - "Current minimum: -50.1338\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3642\n", - "Function value obtained: -48.6810\n", - "Current minimum: -50.1338\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3503\n", - "Function value obtained: -47.2479\n", - "Current minimum: -50.1338\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3201\n", - "Function value obtained: -34.2774\n", - "Current minimum: -50.1338\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3973\n", - "Function value obtained: -43.2625\n", - "Current minimum: -50.1338\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3744\n", - "Function value obtained: -45.8149\n", - "Current minimum: -50.1338\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3712\n", - "Function value obtained: -46.1677\n", - "Current minimum: -50.1338\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3796\n", - "Function value obtained: -44.1751\n", - "Current minimum: -50.1338\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4331\n", - "Function value obtained: -35.2349\n", - "Current minimum: -50.1338\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3929\n", - "Function value obtained: -48.8561\n", - "Current minimum: -50.1338\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4125\n", - "Function value obtained: -48.1868\n", - "Current minimum: -50.1338\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4031\n", - "Function value obtained: -46.9611\n", - "Current minimum: -50.1338\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4301\n", - "Function value obtained: -43.9938\n", - "Current minimum: -50.1338\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4906\n", - "Function value obtained: -48.8963\n", - "Current minimum: -50.1338\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3660\n", - "Function value obtained: -48.5459\n", - "Current minimum: -50.1338\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3769\n", - "Function value obtained: -51.4060\n", - "Current minimum: -51.4060\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3800\n", - "Function value obtained: -45.7699\n", - "Current minimum: -51.4060\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4176\n", - "Function value obtained: -45.4640\n", - "Current minimum: -51.4060\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3695\n", - "Function value obtained: -40.8103\n", - "Current minimum: -51.4060\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4686\n", - "Function value obtained: -40.2990\n", - "Current minimum: -51.4060\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4167\n", - "Function value obtained: -42.1782\n", - "Current minimum: -51.4060\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4081\n", - "Function value obtained: -46.4875\n", - "Current minimum: -51.4060\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4414\n", - "Function value obtained: -47.9566\n", - "Current minimum: -51.4060\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3897\n", - "Function value obtained: -46.1136\n", - "Current minimum: -51.4060\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4330\n", - "Function value obtained: -51.4695\n", - "Current minimum: -51.4695\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4186\n", - "Function value obtained: -46.8573\n", - "Current minimum: -51.4695\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4602\n", - "Function value obtained: -42.9478\n", - "Current minimum: -51.4695\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4838\n", - "Function value obtained: -41.9707\n", - "Current minimum: -51.4695\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5890\n", - "Function value obtained: -45.0371\n", - "Current minimum: -51.4695\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4338\n", - "Function value obtained: -45.2809\n", - "Current minimum: -51.4695\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4864\n", - "Function value obtained: -34.8689\n", - "Current minimum: -51.4695\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4719\n", - "Function value obtained: -43.7533\n", - "Current minimum: -51.4695\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5239\n", - "Function value obtained: -45.3449\n", - "Current minimum: -51.4695\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5189\n", - "Function value obtained: -48.9998\n", - "Current minimum: -51.4695\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5099\n", - "Function value obtained: -47.1104\n", - "Current minimum: -51.4695\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4674\n", - "Function value obtained: -42.6405\n", - "Current minimum: -51.4695\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4607\n", - "Function value obtained: -38.7655\n", - "Current minimum: -51.4695\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6289\n", - "Function value obtained: -41.4829\n", - "Current minimum: -51.4695\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5078\n", - "Function value obtained: -51.7710\n", - "Current minimum: -51.7710\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4944\n", - "Function value obtained: -39.4932\n", - "Current minimum: -51.7710\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5049\n", - "Function value obtained: -36.8218\n", - "Current minimum: -51.7710\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5529\n", - "Function value obtained: -53.9134\n", - "Current minimum: -53.9134\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4845\n", - "Function value obtained: -40.5915\n", - "Current minimum: -53.9134\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4542\n", - "Function value obtained: -41.9783\n", - "Current minimum: -53.9134\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6122\n", - "Function value obtained: -38.7733\n", - "Current minimum: -53.9134\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6169\n", - "Function value obtained: -46.4973\n", - "Current minimum: -53.9134\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6208\n", - "Function value obtained: -36.6504\n", - "Current minimum: -53.9134\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5187\n", - "Function value obtained: -41.6298\n", - "Current minimum: -53.9134\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5351\n", - "Function value obtained: -45.3670\n", - "Current minimum: -53.9134\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5304\n", - "Function value obtained: -47.7983\n", - "Current minimum: -53.9134\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5182\n", - "Function value obtained: -46.1458\n", - "Current minimum: -53.9134\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6177\n", - "Function value obtained: -49.0721\n", - "Current minimum: -53.9134\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5312\n", - "Function value obtained: -42.7138\n", - "Current minimum: -53.9134\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5453\n", - "Function value obtained: -47.8174\n", - "Current minimum: -53.9134\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5279\n", - "Function value obtained: -41.1077\n", - "Current minimum: -53.9134\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5554\n", - "Function value obtained: -44.4300\n", - "Current minimum: -53.9134\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5404\n", - "Function value obtained: -36.9153\n", - "Current minimum: -53.9134\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6682\n", - "Function value obtained: -41.5900\n", - "Current minimum: -53.9134\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6140\n", - "Function value obtained: -34.9299\n", - "Current minimum: -53.9134\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5588\n", - "Function value obtained: -41.1974\n", - "Current minimum: -53.9134\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5888\n", - "Function value obtained: -45.1964\n", - "Current minimum: -53.9134\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7007\n", - "Function value obtained: -42.6928\n", - "Current minimum: -53.9134\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5980\n", - "Function value obtained: -42.7035\n", - "Current minimum: -53.9134\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6859\n", - "Function value obtained: -40.0786\n", - "Current minimum: -53.9134\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6682\n", - "Function value obtained: -36.3690\n", - "Current minimum: -53.9134\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7113\n", - "Function value obtained: -40.2670\n", - "Current minimum: -53.9134\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7315\n", - "Function value obtained: -36.9949\n", - "Current minimum: -53.9134\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6859\n", - "Function value obtained: -34.6970\n", - "Current minimum: -53.9134\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7010\n", - "Function value obtained: -42.1649\n", - "Current minimum: -53.9134\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7134\n", - "Function value obtained: -49.0917\n", - "Current minimum: -53.9134\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6951\n", - "Function value obtained: -42.9732\n", - "Current minimum: -53.9134\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8637\n", - "Function value obtained: -43.6435\n", - "Current minimum: -53.9134\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7522\n", - "Function value obtained: -39.8378\n", - "Current minimum: -53.9134\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7379\n", - "Function value obtained: -47.8749\n", - "Current minimum: -53.9134\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7905\n", - "Function value obtained: -42.2709\n", - "Current minimum: -53.9134\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7698\n", - "Function value obtained: -35.0674\n", - "Current minimum: -53.9134\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7793\n", - "Function value obtained: -50.9318\n", - "Current minimum: -53.9134\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8782\n", - "Function value obtained: -48.8531\n", - "Current minimum: -53.9134\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8932\n", - "Function value obtained: -46.8183\n", - "Current minimum: -53.9134\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8059\n", - "Function value obtained: -48.4923\n", - "Current minimum: -53.9134\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8768\n", - "Function value obtained: -42.6894\n", - "Current minimum: -53.9134\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8500\n", - "Function value obtained: -41.2160\n", - "Current minimum: -53.9134\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8618\n", - "Function value obtained: -39.1842\n", - "Current minimum: -53.9134\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8509\n", - "Function value obtained: -33.7217\n", - "Current minimum: -53.9134\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8517\n", - "Function value obtained: -41.4581\n", - "Current minimum: -53.9134\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8617\n", - "Function value obtained: -40.9622\n", - "Current minimum: -53.9134\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8974\n", - "Function value obtained: -41.7153\n", - "Current minimum: -53.9134\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9532\n", - "Function value obtained: -47.1802\n", - "Current minimum: -53.9134\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8935\n", - "Function value obtained: -45.2285\n", - "Current minimum: -53.9134\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9166\n", - "Function value obtained: -42.6737\n", - "Current minimum: -53.9134\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9321\n", - "Function value obtained: -46.8463\n", - "Current minimum: -53.9134\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9442\n", - "Function value obtained: -46.0512\n", - "Current minimum: -53.9134\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9438\n", - "Function value obtained: -54.8142\n", - "Current minimum: -54.8142\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9472\n", - "Function value obtained: -54.7148\n", - "Current minimum: -54.8142\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0384\n", - "Function value obtained: -53.9256\n", - "Current minimum: -54.8142\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9917\n", - "Function value obtained: -43.7706\n", - "Current minimum: -54.8142\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9840\n", - "Function value obtained: -38.0699\n", - "Current minimum: -54.8142\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9854\n", - "Function value obtained: -45.2017\n", - "Current minimum: -54.8142\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9863\n", - "Function value obtained: -43.6527\n", - "Current minimum: -54.8142\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0061\n", - "Function value obtained: -40.9340\n", - "Current minimum: -54.8142\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9983\n", - "Function value obtained: -38.4662\n", - "Current minimum: -54.8142\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0340\n", - "Function value obtained: -42.5364\n", - "Current minimum: -54.8142\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0660\n", - "Function value obtained: -47.6359\n", - "Current minimum: -54.8142\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0893\n", - "Function value obtained: -41.1730\n", - "Current minimum: -54.8142\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1258\n", - "Function value obtained: -38.8402\n", - "Current minimum: -54.8142\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1226\n", - "Function value obtained: -45.6224\n", - "Current minimum: -54.8142\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2257\n", - "Function value obtained: -45.5238\n", - "Current minimum: -54.8142\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1294\n", - "Function value obtained: -45.8919\n", - "Current minimum: -54.8142\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2097\n", - "Function value obtained: -42.4741\n", - "Current minimum: -54.8142\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1619\n", - "Function value obtained: -49.2020\n", - "Current minimum: -54.8142\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1966\n", - "Function value obtained: -50.5876\n", - "Current minimum: -54.8142\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1346\n", - "Function value obtained: -49.5500\n", - "Current minimum: -54.8142\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3390\n", - "Function value obtained: -43.9383\n", - "Current minimum: -54.8142\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3617\n", - "Function value obtained: -36.3815\n", - "Current minimum: -54.8142\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2532\n", - "Function value obtained: -49.7287\n", - "Current minimum: -54.8142\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3077\n", - "Function value obtained: -42.7556\n", - "Current minimum: -54.8142\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4311\n", - "Function value obtained: -39.6244\n", - "Current minimum: -54.8142\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3222\n", - "Function value obtained: -45.4188\n", - "Current minimum: -54.8142\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3613\n", - "Function value obtained: -47.1197\n", - "Current minimum: -54.8142\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3802\n", - "Function value obtained: -43.7627\n", - "Current minimum: -54.8142\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4570\n", - "Function value obtained: -43.1834\n", - "Current minimum: -54.8142\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4234\n", - "Function value obtained: -45.3453\n", - "Current minimum: -54.8142\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4394\n", - "Function value obtained: -44.8356\n", - "Current minimum: -54.8142\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4076\n", - "Function value obtained: -39.6737\n", - "Current minimum: -54.8142\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4017\n", - "Function value obtained: -48.3839\n", - "Current minimum: -54.8142\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4951\n", - "Function value obtained: -43.9973\n", - "Current minimum: -54.8142\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4469\n", - "Function value obtained: -50.8522\n", - "Current minimum: -54.8142\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5805\n", - "Function value obtained: -37.9130\n", - "Current minimum: -54.8142\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4924\n", - "Function value obtained: -45.3026\n", - "Current minimum: -54.8142\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5148\n", - "Function value obtained: -44.3300\n", - "Current minimum: -54.8142\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5219\n", - "Function value obtained: -48.9848\n", - "Current minimum: -54.8142\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5965\n", - "Function value obtained: -46.2037\n", - "Current minimum: -54.8142\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6010\n", - "Function value obtained: -43.0698\n", - "Current minimum: -54.8142\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6453\n", - "Function value obtained: -48.4222\n", - "Current minimum: -54.8142\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6056\n", - "Function value obtained: -49.4131\n", - "Current minimum: -54.8142\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7147\n", - "Function value obtained: -40.3982\n", - "Current minimum: -54.8142\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6127\n", - "Function value obtained: -42.1395\n", - "Current minimum: -54.8142\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6731\n", - "Function value obtained: -39.0541\n", - "Current minimum: -54.8142\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8352\n", - "Function value obtained: -48.5678\n", - "Current minimum: -54.8142\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7560\n", - "Function value obtained: -43.3397\n", - "Current minimum: -54.8142\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8019\n", - "Function value obtained: -47.5943\n", - "Current minimum: -54.8142\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6806\n", - "Function value obtained: -43.8352\n", - "Current minimum: -54.8142\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6020\n", - "Function value obtained: -39.0741\n", - "Current minimum: -54.8142\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8148\n", - "Function value obtained: -42.0871\n", - "Current minimum: -54.8142\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7491\n", - "Function value obtained: -52.5317\n", - "Current minimum: -54.8142\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8256\n", - "Function value obtained: -47.8101\n", - "Current minimum: -54.8142\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7506\n", - "Function value obtained: -41.0505\n", - "Current minimum: -54.8142\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8701\n", - "Function value obtained: -47.1431\n", - "Current minimum: -54.8142\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7780\n", - "Function value obtained: -44.9654\n", - "Current minimum: -54.8142\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7376\n", - "Function value obtained: -47.5688\n", - "Current minimum: -54.8142\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8238\n", - "Function value obtained: -51.5517\n", - "Current minimum: -54.8142\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8253\n", - "Function value obtained: -40.1348\n", - "Current minimum: -54.8142\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8595\n", - "Function value obtained: -50.8134\n", - "Current minimum: -54.8142\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9182\n", - "Function value obtained: -44.9363\n", - "Current minimum: -54.8142\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9655\n", - "Function value obtained: -43.5040\n", - "Current minimum: -54.8142\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9225\n", - "Function value obtained: -45.1155\n", - "Current minimum: -54.8142\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8966\n", - "Function value obtained: -44.5344\n", - "Current minimum: -54.8142\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9153\n", - "Function value obtained: -40.9757\n", - "Current minimum: -54.8142\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9482\n", - "Function value obtained: -47.6808\n", - "Current minimum: -54.8142\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9523\n", - "Function value obtained: -46.6578\n", - "Current minimum: -54.8142\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9831\n", - "Function value obtained: -44.5294\n", - "Current minimum: -54.8142\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0346\n", - "Function value obtained: -39.6323\n", - "Current minimum: -54.8142\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0679\n", - "Function value obtained: -48.7202\n", - "Current minimum: -54.8142\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0190\n", - "Function value obtained: -47.5751\n", - "Current minimum: -54.8142\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0866\n", - "Function value obtained: -48.1876\n", - "Current minimum: -54.8142\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0585\n", - "Function value obtained: -51.1669\n", - "Current minimum: -54.8142\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0450\n", - "Function value obtained: -41.7415\n", - "Current minimum: -54.8142\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1126\n", - "Function value obtained: -44.6256\n", - "Current minimum: -54.8142\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1490\n", - "Function value obtained: -44.6645\n", - "Current minimum: -54.8142\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2430\n", - "Function value obtained: -44.9590\n", - "Current minimum: -54.8142\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1601\n", - "Function value obtained: -49.6656\n", - "Current minimum: -54.8142\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1656\n", - "Function value obtained: -45.4545\n", - "Current minimum: -54.8142\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2364\n", - "Function value obtained: -38.2939\n", - "Current minimum: -54.8142\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2245\n", - "Function value obtained: -38.8849\n", - "Current minimum: -54.8142\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3089\n", - "Function value obtained: -42.7612\n", - "Current minimum: -54.8142\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2584\n", - "Function value obtained: -41.5039\n", - "Current minimum: -54.8142\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2356\n", - "Function value obtained: -48.0739\n", - "Current minimum: -54.8142\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4324\n", - "Function value obtained: -50.4017\n", - "Current minimum: -54.8142\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2589\n", - "Function value obtained: -47.6305\n", - "Current minimum: -54.8142\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3488\n", - "Function value obtained: -42.0997\n", - "Current minimum: -54.8142\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3623\n", - "Function value obtained: -49.5690\n", - "Current minimum: -54.8142\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4157\n", - "Function value obtained: -42.5549\n", - "Current minimum: -54.8142\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3793\n", - "Function value obtained: -40.0770\n", - "Current minimum: -54.8142\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5281\n", - "Function value obtained: -44.8665\n", - "Current minimum: -54.8142\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5115\n", - "Function value obtained: -41.0072\n", - "Current minimum: -54.8142\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5949\n", - "Function value obtained: -38.4857\n", - "Current minimum: -54.8142\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4584\n", - "Function value obtained: -40.0936\n", - "Current minimum: -54.8142\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5713\n", - "Function value obtained: -45.3233\n", - "Current minimum: -54.8142\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4995\n", - "Function value obtained: -44.2742\n", - "Current minimum: -54.8142\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5672\n", - "Function value obtained: -45.8370\n", - "Current minimum: -54.8142\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5891\n", - "Function value obtained: -42.3797\n", - "Current minimum: -54.8142\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6347\n", - "Function value obtained: -49.5246\n", - "Current minimum: -54.8142\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6642\n", - "Function value obtained: -47.2963\n", - "Current minimum: -54.8142\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7471\n", - "Function value obtained: -45.1107\n", - "Current minimum: -54.8142\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6473\n", - "Function value obtained: -43.7307\n", - "Current minimum: -54.8142\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6854\n", - "Function value obtained: -45.6168\n", - "Current minimum: -54.8142\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7425\n", - "Function value obtained: -51.5696\n", - "Current minimum: -54.8142\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6501\n", - "Function value obtained: -43.4567\n", - "Current minimum: -54.8142\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6933\n", - "Function value obtained: -51.3104\n", - "Current minimum: -54.8142\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9805\n", - "Function value obtained: -38.2171\n", - "Current minimum: -54.8142\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8180\n", - "Function value obtained: -48.2538\n", - "Current minimum: -54.8142\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7676\n", - "Function value obtained: -45.1358\n", - "Current minimum: -54.8142\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7566\n", - "Function value obtained: -49.2972\n", - "Current minimum: -54.8142\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8725\n", - "Function value obtained: -49.9608\n", - "Current minimum: -54.8142\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8274\n", - "Function value obtained: -46.6834\n", - "Current minimum: -54.8142\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0820\n", - "Function value obtained: -41.0620\n", - "Current minimum: -54.8142\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9297\n", - "Function value obtained: -45.1913\n", - "Current minimum: -54.8142\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1035\n", - "Function value obtained: -37.7382\n", - "Current minimum: -54.8142\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9749\n", - "Function value obtained: -38.1761\n", - "Current minimum: -54.8142\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0392\n", - "Function value obtained: -42.8216\n", - "Current minimum: -54.8142\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0305\n", - "Function value obtained: -41.6850\n", - "Current minimum: -54.8142\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1206\n", - "Function value obtained: -41.6934\n", - "Current minimum: -54.8142\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9436\n", - "Function value obtained: -39.4824\n", - "Current minimum: -54.8142\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9697\n", - "Function value obtained: -43.0018\n", - "Current minimum: -54.8142\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0289\n", - "Function value obtained: -42.1181\n", - "Current minimum: -54.8142\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1221\n", - "Function value obtained: -40.0538\n", - "Current minimum: -54.8142\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1256\n", - "Function value obtained: -43.0974\n", - "Current minimum: -54.8142\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1509\n", - "Function value obtained: -44.3181\n", - "Current minimum: -54.8142\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1153\n", - "Function value obtained: -39.8813\n", - "Current minimum: -54.8142\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2911\n", - "Function value obtained: -40.9968\n", - "Current minimum: -54.8142\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3436\n", - "Function value obtained: -42.7245\n", - "Current minimum: -54.8142\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3806\n", - "Function value obtained: -52.2548\n", - "Current minimum: -54.8142\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2776\n", - "Function value obtained: -33.3104\n", - "Current minimum: -54.8142\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4269\n", - "Function value obtained: -45.5528\n", - "Current minimum: -54.8142\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2036\n", - "Function value obtained: -42.4463\n", - "Current minimum: -54.8142\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2384\n", - "Function value obtained: -52.9500\n", - "Current minimum: -54.8142\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4487\n", - "Function value obtained: -42.8671\n", - "Current minimum: -54.8142\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3958\n", - "Function value obtained: -52.0466\n", - "Current minimum: -54.8142\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3174\n", - "Function value obtained: -51.6431\n", - "Current minimum: -54.8142\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4634\n", - "Function value obtained: -44.8405\n", - "Current minimum: -54.8142\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4287\n", - "Function value obtained: -41.3459\n", - "Current minimum: -54.8142\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5052\n", - "Function value obtained: -45.8234\n", - "Current minimum: -54.8142\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4365\n", - "Function value obtained: -40.4291\n", - "Current minimum: -54.8142\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5197\n", - "Function value obtained: -48.7839\n", - "Current minimum: -54.8142\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5040\n", - "Function value obtained: -41.4991\n", - "Current minimum: -54.8142\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7230\n", - "Function value obtained: -44.4831\n", - "Current minimum: -54.8142\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5047\n", - "Function value obtained: -44.6608\n", - "Current minimum: -54.8142\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7857\n", - "Function value obtained: -43.1532\n", - "Current minimum: -54.8142\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7688\n", - "Function value obtained: -47.4666\n", - "Current minimum: -54.8142\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7745\n", - "Function value obtained: -46.9994\n", - "Current minimum: -54.8142\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6671\n", - "Function value obtained: -43.7697\n", - "Current minimum: -54.8142\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7708\n", - "Function value obtained: -50.5434\n", - "Current minimum: -54.8142\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9154\n", - "Function value obtained: -48.9392\n", - "Current minimum: -54.8142\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9119\n", - "Function value obtained: -42.9476\n", - "Current minimum: -54.8142\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9929\n", - "Function value obtained: -45.8722\n", - "Current minimum: -54.8142\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8037\n", - "Function value obtained: -35.4552\n", - "Current minimum: -54.8142\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7387\n", - "Function value obtained: -39.5697\n", - "Current minimum: -54.8142\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8960\n", - "Function value obtained: -45.5709\n", - "Current minimum: -54.8142\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9747\n", - "Function value obtained: -31.4910\n", - "Current minimum: -54.8142\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0449\n", - "Function value obtained: -47.8176\n", - "Current minimum: -54.8142\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0147\n", - "Function value obtained: -46.0285\n", - "Current minimum: -54.8142\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0399\n", - "Function value obtained: -42.1471\n", - "Current minimum: -54.8142\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0086\n", - "Function value obtained: -39.9595\n", - "Current minimum: -54.8142\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9489\n", - "Function value obtained: -48.2704\n", - "Current minimum: -54.8142\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0237\n", - "Function value obtained: -46.2333\n", - "Current minimum: -54.8142\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9686\n", - "Function value obtained: -47.6559\n", - "Current minimum: -54.8142\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0558\n", - "Function value obtained: -48.0066\n", - "Current minimum: -54.8142\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1058\n", - "Function value obtained: -44.3809\n", - "Current minimum: -54.8142\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0046\n", - "Function value obtained: -45.4358\n", - "Current minimum: -54.8142\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1247\n", - "Function value obtained: -51.2635\n", - "Current minimum: -54.8142\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0342\n", - "Function value obtained: -31.1800\n", - "Current minimum: -54.8142\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2430\n", - "Function value obtained: -44.1933\n", - "Current minimum: -54.8142\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2635\n", - "Function value obtained: -40.1671\n", - "Current minimum: -54.8142\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3124\n", - "Function value obtained: -46.1171\n", - "Current minimum: -54.8142\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3674\n", - "Function value obtained: -39.2365\n", - "Current minimum: -54.8142\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3650\n", - "Function value obtained: -46.3525\n", - "Current minimum: -54.8142\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3412\n", - "Function value obtained: -51.8622\n", - "Current minimum: -54.8142\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3217\n", - "Function value obtained: -37.9971\n", - "Current minimum: -54.8142\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2299\n", - "Function value obtained: -49.3668\n", - "Current minimum: -54.8142\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5783\n", - "Function value obtained: -46.8952\n", - "Current minimum: -54.8142\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2065\n", - "Function value obtained: -40.0369\n", - "Current minimum: -54.8142\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4981\n", - "Function value obtained: -50.8907\n", - "Current minimum: -54.8142\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4386\n", - "Function value obtained: -44.3409\n", - "Current minimum: -54.8142\n", - "Iteration No: 301 started. Searching for the next optimal point.\n", - "Iteration No: 301 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5197\n", - "Function value obtained: -48.0973\n", - "Current minimum: -54.8142\n", - "Iteration No: 302 started. Searching for the next optimal point.\n", - "Iteration No: 302 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4516\n", - "Function value obtained: -53.6443\n", - "Current minimum: -54.8142\n", - "Iteration No: 303 started. Searching for the next optimal point.\n", - "Iteration No: 303 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4906\n", - "Function value obtained: -50.0191\n", - "Current minimum: -54.8142\n", - "Iteration No: 304 started. Searching for the next optimal point.\n", - "Iteration No: 304 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5496\n", - "Function value obtained: -34.6470\n", - "Current minimum: -54.8142\n", - "Iteration No: 305 started. Searching for the next optimal point.\n", - "Iteration No: 305 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6774\n", - "Function value obtained: -46.8803\n", - "Current minimum: -54.8142\n", - "Iteration No: 306 started. Searching for the next optimal point.\n", - "Iteration No: 306 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5386\n", - "Function value obtained: -53.5865\n", - "Current minimum: -54.8142\n", - "Iteration No: 307 started. Searching for the next optimal point.\n", - "Iteration No: 307 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5070\n", - "Function value obtained: -42.7079\n", - "Current minimum: -54.8142\n", - "Iteration No: 308 started. Searching for the next optimal point.\n", - "Iteration No: 308 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4955\n", - "Function value obtained: -42.2617\n", - "Current minimum: -54.8142\n", - "Iteration No: 309 started. Searching for the next optimal point.\n", - "Iteration No: 309 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6636\n", - "Function value obtained: -39.6691\n", - "Current minimum: -54.8142\n", - "Iteration No: 310 started. Searching for the next optimal point.\n", - "Iteration No: 310 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4506\n", - "Function value obtained: -46.1496\n", - "Current minimum: -54.8142\n", - "Iteration No: 311 started. Searching for the next optimal point.\n", - "Iteration No: 311 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6604\n", - "Function value obtained: -42.6656\n", - "Current minimum: -54.8142\n", - "Iteration No: 312 started. Searching for the next optimal point.\n", - "Iteration No: 312 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6312\n", - "Function value obtained: -44.2297\n", - "Current minimum: -54.8142\n", - "Iteration No: 313 started. Searching for the next optimal point.\n", - "Iteration No: 313 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7975\n", - "Function value obtained: -43.1222\n", - "Current minimum: -54.8142\n", - "Iteration No: 314 started. Searching for the next optimal point.\n", - "Iteration No: 314 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7419\n", - "Function value obtained: -49.6837\n", - "Current minimum: -54.8142\n", - "Iteration No: 315 started. Searching for the next optimal point.\n", - "Iteration No: 315 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9556\n", - "Function value obtained: -37.1794\n", - "Current minimum: -54.8142\n", - "Iteration No: 316 started. Searching for the next optimal point.\n", - "Iteration No: 316 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9108\n", - "Function value obtained: -47.0650\n", - "Current minimum: -54.8142\n", - "Iteration No: 317 started. Searching for the next optimal point.\n", - "Iteration No: 317 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9643\n", - "Function value obtained: -45.8842\n", - "Current minimum: -54.8142\n", - "Iteration No: 318 started. Searching for the next optimal point.\n", - "Iteration No: 318 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8749\n", - "Function value obtained: -39.5284\n", - "Current minimum: -54.8142\n", - "Iteration No: 319 started. Searching for the next optimal point.\n", - "Iteration No: 319 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8583\n", - "Function value obtained: -36.8792\n", - "Current minimum: -54.8142\n", - "Iteration No: 320 started. Searching for the next optimal point.\n", - "Iteration No: 320 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9012\n", - "Function value obtained: -41.0123\n", - "Current minimum: -54.8142\n", - "Iteration No: 321 started. Searching for the next optimal point.\n", - "Iteration No: 321 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0313\n", - "Function value obtained: -46.8805\n", - "Current minimum: -54.8142\n", - "Iteration No: 322 started. Searching for the next optimal point.\n", - "Iteration No: 322 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8262\n", - "Function value obtained: -44.5771\n", - "Current minimum: -54.8142\n", - "Iteration No: 323 started. Searching for the next optimal point.\n", - "Iteration No: 323 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0161\n", - "Function value obtained: -42.1853\n", - "Current minimum: -54.8142\n", - "Iteration No: 324 started. Searching for the next optimal point.\n", - "Iteration No: 324 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9599\n", - "Function value obtained: -45.0800\n", - "Current minimum: -54.8142\n", - "Iteration No: 325 started. Searching for the next optimal point.\n", - "Iteration No: 325 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0087\n", - "Function value obtained: -52.5638\n", - "Current minimum: -54.8142\n", - "Iteration No: 326 started. Searching for the next optimal point.\n", - "Iteration No: 326 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0586\n", - "Function value obtained: -46.8452\n", - "Current minimum: -54.8142\n", - "Iteration No: 327 started. Searching for the next optimal point.\n", - "Iteration No: 327 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1613\n", - "Function value obtained: -44.7433\n", - "Current minimum: -54.8142\n", - "Iteration No: 328 started. Searching for the next optimal point.\n", - "Iteration No: 328 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1543\n", - "Function value obtained: -40.3102\n", - "Current minimum: -54.8142\n", - "Iteration No: 329 started. Searching for the next optimal point.\n", - "Iteration No: 329 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1630\n", - "Function value obtained: -40.8956\n", - "Current minimum: -54.8142\n", - "Iteration No: 330 started. Searching for the next optimal point.\n", - "Iteration No: 330 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1818\n", - "Function value obtained: -42.8250\n", - "Current minimum: -54.8142\n", - "Iteration No: 331 started. Searching for the next optimal point.\n", - "Iteration No: 331 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2297\n", - "Function value obtained: -44.6906\n", - "Current minimum: -54.8142\n", - "Iteration No: 332 started. Searching for the next optimal point.\n", - "Iteration No: 332 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1704\n", - "Function value obtained: -37.5448\n", - "Current minimum: -54.8142\n", - "Iteration No: 333 started. Searching for the next optimal point.\n", - "Iteration No: 333 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3709\n", - "Function value obtained: -40.6308\n", - "Current minimum: -54.8142\n", - "Iteration No: 334 started. Searching for the next optimal point.\n", - "Iteration No: 334 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1840\n", - "Function value obtained: -49.1842\n", - "Current minimum: -54.8142\n", - "Iteration No: 335 started. Searching for the next optimal point.\n", - "Iteration No: 335 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4340\n", - "Function value obtained: -44.5902\n", - "Current minimum: -54.8142\n", - "Iteration No: 336 started. Searching for the next optimal point.\n", - "Iteration No: 336 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3482\n", - "Function value obtained: -41.9952\n", - "Current minimum: -54.8142\n", - "Iteration No: 337 started. Searching for the next optimal point.\n", - "Iteration No: 337 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5129\n", - "Function value obtained: -48.1524\n", - "Current minimum: -54.8142\n", - "Iteration No: 338 started. Searching for the next optimal point.\n", - "Iteration No: 338 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5450\n", - "Function value obtained: -45.5895\n", - "Current minimum: -54.8142\n", - "Iteration No: 339 started. Searching for the next optimal point.\n", - "Iteration No: 339 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5089\n", - "Function value obtained: -38.6012\n", - "Current minimum: -54.8142\n", - "Iteration No: 340 started. Searching for the next optimal point.\n", - "Iteration No: 340 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5202\n", - "Function value obtained: -48.6424\n", - "Current minimum: -54.8142\n", - "Iteration No: 341 started. Searching for the next optimal point.\n", - "Iteration No: 341 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7708\n", - "Function value obtained: -38.8402\n", - "Current minimum: -54.8142\n", - "Iteration No: 342 started. Searching for the next optimal point.\n", - "Iteration No: 342 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3637\n", - "Function value obtained: -44.2923\n", - "Current minimum: -54.8142\n", - "Iteration No: 343 started. Searching for the next optimal point.\n", - "Iteration No: 343 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7194\n", - "Function value obtained: -40.4334\n", - "Current minimum: -54.8142\n", - "Iteration No: 344 started. Searching for the next optimal point.\n", - "Iteration No: 344 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5820\n", - "Function value obtained: -50.8317\n", - "Current minimum: -54.8142\n", - "Iteration No: 345 started. Searching for the next optimal point.\n", - "Iteration No: 345 ended. Search finished for the next optimal point.\n", - "Time taken: 6.8275\n", - "Function value obtained: -47.9338\n", - "Current minimum: -54.8142\n", - "Iteration No: 346 started. Searching for the next optimal point.\n", - "Iteration No: 346 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7070\n", - "Function value obtained: -37.6213\n", - "Current minimum: -54.8142\n", - "Iteration No: 347 started. Searching for the next optimal point.\n", - "Iteration No: 347 ended. Search finished for the next optimal point.\n", - "Time taken: 6.8542\n", - "Function value obtained: -38.3767\n", - "Current minimum: -54.8142\n", - "Iteration No: 348 started. Searching for the next optimal point.\n", - "Iteration No: 348 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6985\n", - "Function value obtained: -47.6310\n", - "Current minimum: -54.8142\n", - "Iteration No: 349 started. Searching for the next optimal point.\n", - "Iteration No: 349 ended. Search finished for the next optimal point.\n", - "Time taken: 6.7671\n", - "Function value obtained: -48.9210\n", - "Current minimum: -54.8142\n", - "Iteration No: 350 started. Searching for the next optimal point.\n", - "Iteration No: 350 ended. Search finished for the next optimal point.\n", - "Time taken: 6.9268\n", - "Function value obtained: -48.9808\n", - "Current minimum: -54.8142\n", - "Iteration No: 351 started. Searching for the next optimal point.\n", - "Iteration No: 351 ended. Search finished for the next optimal point.\n", - "Time taken: 6.8813\n", - "Function value obtained: -44.4929\n", - "Current minimum: -54.8142\n", - "Iteration No: 352 started. Searching for the next optimal point.\n", - "Iteration No: 352 ended. Search finished for the next optimal point.\n", - "Time taken: 6.9323\n", - "Function value obtained: -44.9247\n", - "Current minimum: -54.8142\n", - "Iteration No: 353 started. Searching for the next optimal point.\n", - "Iteration No: 353 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0415\n", - "Function value obtained: -45.4293\n", - "Current minimum: -54.8142\n", - "Iteration No: 354 started. Searching for the next optimal point.\n", - "Iteration No: 354 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0119\n", - "Function value obtained: -42.2939\n", - "Current minimum: -54.8142\n", - "Iteration No: 355 started. Searching for the next optimal point.\n", - "Iteration No: 355 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0748\n", - "Function value obtained: -44.3765\n", - "Current minimum: -54.8142\n", - "Iteration No: 356 started. Searching for the next optimal point.\n", - "Iteration No: 356 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0728\n", - "Function value obtained: -44.2397\n", - "Current minimum: -54.8142\n", - "Iteration No: 357 started. Searching for the next optimal point.\n", - "Iteration No: 357 ended. Search finished for the next optimal point.\n", - "Time taken: 7.1915\n", - "Function value obtained: -45.4580\n", - "Current minimum: -54.8142\n", - "Iteration No: 358 started. Searching for the next optimal point.\n", - "Iteration No: 358 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0153\n", - "Function value obtained: -38.9172\n", - "Current minimum: -54.8142\n", - "Iteration No: 359 started. Searching for the next optimal point.\n", - "Iteration No: 359 ended. Search finished for the next optimal point.\n", - "Time taken: 7.2205\n", - "Function value obtained: -38.4401\n", - "Current minimum: -54.8142\n", - "Iteration No: 360 started. Searching for the next optimal point.\n", - "Iteration No: 360 ended. Search finished for the next optimal point.\n", - "Time taken: 7.1132\n", - "Function value obtained: -45.0333\n", - "Current minimum: -54.8142\n", - "Iteration No: 361 started. Searching for the next optimal point.\n", - "Iteration No: 361 ended. Search finished for the next optimal point.\n", - "Time taken: 7.1512\n", - "Function value obtained: -38.7016\n", - "Current minimum: -54.8142\n", - "Iteration No: 362 started. Searching for the next optimal point.\n", - "Iteration No: 362 ended. Search finished for the next optimal point.\n", - "Time taken: 7.0556\n", - "Function value obtained: -40.6249\n", - "Current minimum: -54.8142\n", - "Iteration No: 363 started. Searching for the next optimal point.\n", - "Iteration No: 363 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2602\n", - "Function value obtained: -45.5220\n", - "Current minimum: -54.8142\n", - "Iteration No: 364 started. Searching for the next optimal point.\n", - "Iteration No: 364 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3498\n", - "Function value obtained: -40.8088\n", - "Current minimum: -54.8142\n", - "Iteration No: 365 started. Searching for the next optimal point.\n", - "Iteration No: 365 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3622\n", - "Function value obtained: -42.9483\n", - "Current minimum: -54.8142\n", - "Iteration No: 366 started. Searching for the next optimal point.\n", - "Iteration No: 366 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3827\n", - "Function value obtained: -50.1280\n", - "Current minimum: -54.8142\n", - "Iteration No: 367 started. Searching for the next optimal point.\n", - "Iteration No: 367 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3364\n", - "Function value obtained: -43.5729\n", - "Current minimum: -54.8142\n", - "Iteration No: 368 started. Searching for the next optimal point.\n", - "Iteration No: 368 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2566\n", - "Function value obtained: -44.2424\n", - "Current minimum: -54.8142\n", - "Iteration No: 369 started. Searching for the next optimal point.\n", - "Iteration No: 369 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3578\n", - "Function value obtained: -45.2440\n", - "Current minimum: -54.8142\n", - "Iteration No: 370 started. Searching for the next optimal point.\n", - "Iteration No: 370 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3100\n", - "Function value obtained: -50.2698\n", - "Current minimum: -54.8142\n", - "Iteration No: 371 started. Searching for the next optimal point.\n", - "Iteration No: 371 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4404\n", - "Function value obtained: -44.4152\n", - "Current minimum: -54.8142\n", - "Iteration No: 372 started. Searching for the next optimal point.\n", - "Iteration No: 372 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4706\n", - "Function value obtained: -37.8531\n", - "Current minimum: -54.8142\n", - "Iteration No: 373 started. Searching for the next optimal point.\n", - "Iteration No: 373 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5975\n", - "Function value obtained: -49.9398\n", - "Current minimum: -54.8142\n", - "Iteration No: 374 started. Searching for the next optimal point.\n", - "Iteration No: 374 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6179\n", - "Function value obtained: -38.2719\n", - "Current minimum: -54.8142\n", - "Iteration No: 375 started. Searching for the next optimal point.\n", - "Iteration No: 375 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6107\n", - "Function value obtained: -45.8924\n", - "Current minimum: -54.8142\n", - "Iteration No: 376 started. Searching for the next optimal point.\n", - "Iteration No: 376 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5313\n", - "Function value obtained: -42.6041\n", - "Current minimum: -54.8142\n", - "Iteration No: 377 started. Searching for the next optimal point.\n", - "Iteration No: 377 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7210\n", - "Function value obtained: -47.5247\n", - "Current minimum: -54.8142\n", - "Iteration No: 378 started. Searching for the next optimal point.\n", - "Iteration No: 378 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4609\n", - "Function value obtained: -49.0257\n", - "Current minimum: -54.8142\n", - "Iteration No: 379 started. Searching for the next optimal point.\n", - "Iteration No: 379 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7125\n", - "Function value obtained: -44.4585\n", - "Current minimum: -54.8142\n", - "Iteration No: 380 started. Searching for the next optimal point.\n", - "Iteration No: 380 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5593\n", - "Function value obtained: -51.3283\n", - "Current minimum: -54.8142\n", - "Iteration No: 381 started. Searching for the next optimal point.\n", - "Iteration No: 381 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9296\n", - "Function value obtained: -49.2633\n", - "Current minimum: -54.8142\n", - "Iteration No: 382 started. Searching for the next optimal point.\n", - "Iteration No: 382 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7146\n", - "Function value obtained: -36.6545\n", - "Current minimum: -54.8142\n", - "Iteration No: 383 started. Searching for the next optimal point.\n", - "Iteration No: 383 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8367\n", - "Function value obtained: -41.3761\n", - "Current minimum: -54.8142\n", - "Iteration No: 384 started. Searching for the next optimal point.\n", - "Iteration No: 384 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6929\n", - "Function value obtained: -46.4049\n", - "Current minimum: -54.8142\n", - "Iteration No: 385 started. Searching for the next optimal point.\n", - "Iteration No: 385 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9726\n", - "Function value obtained: -39.5598\n", - "Current minimum: -54.8142\n", - "Iteration No: 386 started. Searching for the next optimal point.\n", - "Iteration No: 386 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9029\n", - "Function value obtained: -47.7325\n", - "Current minimum: -54.8142\n", - "Iteration No: 387 started. Searching for the next optimal point.\n", - "Iteration No: 387 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9536\n", - "Function value obtained: -41.1368\n", - "Current minimum: -54.8142\n", - "Iteration No: 388 started. Searching for the next optimal point.\n", - "Iteration No: 388 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0236\n", - "Function value obtained: -37.9952\n", - "Current minimum: -54.8142\n", - "Iteration No: 389 started. Searching for the next optimal point.\n", - "Iteration No: 389 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1064\n", - "Function value obtained: -45.8384\n", - "Current minimum: -54.8142\n", - "Iteration No: 390 started. Searching for the next optimal point.\n", - "Iteration No: 390 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8734\n", - "Function value obtained: -44.0954\n", - "Current minimum: -54.8142\n", - "Iteration No: 391 started. Searching for the next optimal point.\n", - "Iteration No: 391 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2190\n", - "Function value obtained: -44.7056\n", - "Current minimum: -54.8142\n", - "Iteration No: 392 started. Searching for the next optimal point.\n", - "Iteration No: 392 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0359\n", - "Function value obtained: -43.5856\n", - "Current minimum: -54.8142\n", - "Iteration No: 393 started. Searching for the next optimal point.\n", - "Iteration No: 393 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2162\n", - "Function value obtained: -43.9222\n", - "Current minimum: -54.8142\n", - "Iteration No: 394 started. Searching for the next optimal point.\n", - "Iteration No: 394 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2656\n", - "Function value obtained: -40.0651\n", - "Current minimum: -54.8142\n", - "Iteration No: 395 started. Searching for the next optimal point.\n", - "Iteration No: 395 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2325\n", - "Function value obtained: -44.9682\n", - "Current minimum: -54.8142\n", - "Iteration No: 396 started. Searching for the next optimal point.\n", - "Iteration No: 396 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2081\n", - "Function value obtained: -37.6295\n", - "Current minimum: -54.8142\n", - "Iteration No: 397 started. Searching for the next optimal point.\n", - "Iteration No: 397 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2516\n", - "Function value obtained: -42.3947\n", - "Current minimum: -54.8142\n", - "Iteration No: 398 started. Searching for the next optimal point.\n", - "Iteration No: 398 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1226\n", - "Function value obtained: -38.0732\n", - "Current minimum: -54.8142\n", - "Iteration No: 399 started. Searching for the next optimal point.\n", - "Iteration No: 399 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3038\n", - "Function value obtained: -43.5889\n", - "Current minimum: -54.8142\n", - "Iteration No: 400 started. Searching for the next optimal point.\n", - "Iteration No: 400 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5978\n", - "Function value obtained: -45.2339\n", - "Current minimum: -54.8142\n", - "Iteration No: 401 started. Searching for the next optimal point.\n", - "Iteration No: 401 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4443\n", - "Function value obtained: -45.5773\n", - "Current minimum: -54.8142\n", - "Iteration No: 402 started. Searching for the next optimal point.\n", - "Iteration No: 402 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4014\n", - "Function value obtained: -42.7523\n", - "Current minimum: -54.8142\n", - "Iteration No: 403 started. Searching for the next optimal point.\n", - "Iteration No: 403 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5128\n", - "Function value obtained: -45.7714\n", - "Current minimum: -54.8142\n", - "Iteration No: 404 started. Searching for the next optimal point.\n", - "Iteration No: 404 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6183\n", - "Function value obtained: -39.7821\n", - "Current minimum: -54.8142\n", - "Iteration No: 405 started. Searching for the next optimal point.\n", - "Iteration No: 405 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6371\n", - "Function value obtained: -39.6881\n", - "Current minimum: -54.8142\n", - "Iteration No: 406 started. Searching for the next optimal point.\n", - "Iteration No: 406 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4482\n", - "Function value obtained: -40.2658\n", - "Current minimum: -54.8142\n", - "Iteration No: 407 started. Searching for the next optimal point.\n", - "Iteration No: 407 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6523\n", - "Function value obtained: -44.1331\n", - "Current minimum: -54.8142\n", - "Iteration No: 408 started. Searching for the next optimal point.\n", - "Iteration No: 408 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4497\n", - "Function value obtained: -42.5939\n", - "Current minimum: -54.8142\n", - "Iteration No: 409 started. Searching for the next optimal point.\n", - "Iteration No: 409 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5884\n", - "Function value obtained: -35.9444\n", - "Current minimum: -54.8142\n", - "Iteration No: 410 started. Searching for the next optimal point.\n", - "Iteration No: 410 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5812\n", - "Function value obtained: -52.5727\n", - "Current minimum: -54.8142\n", - "Iteration No: 411 started. Searching for the next optimal point.\n", - "Iteration No: 411 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8143\n", - "Function value obtained: -40.9425\n", - "Current minimum: -54.8142\n", - "Iteration No: 412 started. Searching for the next optimal point.\n", - "Iteration No: 412 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7912\n", - "Function value obtained: -46.9195\n", - "Current minimum: -54.8142\n", - "Iteration No: 413 started. Searching for the next optimal point.\n", - "Iteration No: 413 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7528\n", - "Function value obtained: -44.5903\n", - "Current minimum: -54.8142\n", - "Iteration No: 414 started. Searching for the next optimal point.\n", - "Iteration No: 414 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6612\n", - "Function value obtained: -46.4306\n", - "Current minimum: -54.8142\n", - "Iteration No: 415 started. Searching for the next optimal point.\n", - "Iteration No: 415 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9762\n", - "Function value obtained: -37.4071\n", - "Current minimum: -54.8142\n", - "Iteration No: 416 started. Searching for the next optimal point.\n", - "Iteration No: 416 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6872\n", - "Function value obtained: -41.9396\n", - "Current minimum: -54.8142\n", - "Iteration No: 417 started. Searching for the next optimal point.\n", - "Iteration No: 417 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9720\n", - "Function value obtained: -49.4248\n", - "Current minimum: -54.8142\n", - "Iteration No: 418 started. Searching for the next optimal point.\n", - "Iteration No: 418 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9645\n", - "Function value obtained: -42.0397\n", - "Current minimum: -54.8142\n", - "Iteration No: 419 started. Searching for the next optimal point.\n", - "Iteration No: 419 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1529\n", - "Function value obtained: -51.9245\n", - "Current minimum: -54.8142\n", - "Iteration No: 420 started. Searching for the next optimal point.\n", - "Iteration No: 420 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1240\n", - "Function value obtained: -43.5731\n", - "Current minimum: -54.8142\n", - "Iteration No: 421 started. Searching for the next optimal point.\n", - "Iteration No: 421 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2124\n", - "Function value obtained: -46.6483\n", - "Current minimum: -54.8142\n", - "Iteration No: 422 started. Searching for the next optimal point.\n", - "Iteration No: 422 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0673\n", - "Function value obtained: -44.6988\n", - "Current minimum: -54.8142\n", - "Iteration No: 423 started. Searching for the next optimal point.\n", - "Iteration No: 423 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2977\n", - "Function value obtained: -51.9855\n", - "Current minimum: -54.8142\n", - "Iteration No: 424 started. Searching for the next optimal point.\n", - "Iteration No: 424 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0586\n", - "Function value obtained: -43.5582\n", - "Current minimum: -54.8142\n", - "Iteration No: 425 started. Searching for the next optimal point.\n", - "Iteration No: 425 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1936\n", - "Function value obtained: -34.9101\n", - "Current minimum: -54.8142\n", - "Iteration No: 426 started. Searching for the next optimal point.\n", - "Iteration No: 426 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2466\n", - "Function value obtained: -48.8877\n", - "Current minimum: -54.8142\n", - "Iteration No: 427 started. Searching for the next optimal point.\n", - "Iteration No: 427 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4075\n", - "Function value obtained: -46.2974\n", - "Current minimum: -54.8142\n", - "Iteration No: 428 started. Searching for the next optimal point.\n", - "Iteration No: 428 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3891\n", - "Function value obtained: -47.8045\n", - "Current minimum: -54.8142\n", - "Iteration No: 429 started. Searching for the next optimal point.\n", - "Iteration No: 429 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6014\n", - "Function value obtained: -49.4246\n", - "Current minimum: -54.8142\n", - "Iteration No: 430 started. Searching for the next optimal point.\n", - "Iteration No: 430 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3677\n", - "Function value obtained: -44.6394\n", - "Current minimum: -54.8142\n", - "Iteration No: 431 started. Searching for the next optimal point.\n", - "Iteration No: 431 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4430\n", - "Function value obtained: -42.9909\n", - "Current minimum: -54.8142\n", - "Iteration No: 432 started. Searching for the next optimal point.\n", - "Iteration No: 432 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4249\n", - "Function value obtained: -42.8327\n", - "Current minimum: -54.8142\n", - "Iteration No: 433 started. Searching for the next optimal point.\n", - "Iteration No: 433 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5058\n", - "Function value obtained: -41.7165\n", - "Current minimum: -54.8142\n", - "Iteration No: 434 started. Searching for the next optimal point.\n", - "Iteration No: 434 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4504\n", - "Function value obtained: -39.2035\n", - "Current minimum: -54.8142\n", - "Iteration No: 435 started. Searching for the next optimal point.\n", - "Iteration No: 435 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9266\n", - "Function value obtained: -50.8822\n", - "Current minimum: -54.8142\n", - "Iteration No: 436 started. Searching for the next optimal point.\n", - "Iteration No: 436 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6064\n", - "Function value obtained: -42.7771\n", - "Current minimum: -54.8142\n", - "Iteration No: 437 started. Searching for the next optimal point.\n", - "Iteration No: 437 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8898\n", - "Function value obtained: -49.8474\n", - "Current minimum: -54.8142\n", - "Iteration No: 438 started. Searching for the next optimal point.\n", - "Iteration No: 438 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7952\n", - "Function value obtained: -45.5650\n", - "Current minimum: -54.8142\n", - "Iteration No: 439 started. Searching for the next optimal point.\n", - "Iteration No: 439 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9197\n", - "Function value obtained: -40.8095\n", - "Current minimum: -54.8142\n", - "Iteration No: 440 started. Searching for the next optimal point.\n", - "Iteration No: 440 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7131\n", - "Function value obtained: -37.9934\n", - "Current minimum: -54.8142\n", - "Iteration No: 441 started. Searching for the next optimal point.\n", - "Iteration No: 441 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9708\n", - "Function value obtained: -44.5009\n", - "Current minimum: -54.8142\n", - "Iteration No: 442 started. Searching for the next optimal point.\n", - "Iteration No: 442 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7290\n", - "Function value obtained: -43.7900\n", - "Current minimum: -54.8142\n", - "Iteration No: 443 started. Searching for the next optimal point.\n", - "Iteration No: 443 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1736\n", - "Function value obtained: -44.1217\n", - "Current minimum: -54.8142\n", - "Iteration No: 444 started. Searching for the next optimal point.\n", - "Iteration No: 444 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9684\n", - "Function value obtained: -46.0429\n", - "Current minimum: -54.8142\n", - "Iteration No: 445 started. Searching for the next optimal point.\n", - "Iteration No: 445 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2352\n", - "Function value obtained: -45.9755\n", - "Current minimum: -54.8142\n", - "Iteration No: 446 started. Searching for the next optimal point.\n", - "Iteration No: 446 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0744\n", - "Function value obtained: -50.3901\n", - "Current minimum: -54.8142\n", - "Iteration No: 447 started. Searching for the next optimal point.\n", - "Iteration No: 447 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3425\n", - "Function value obtained: -43.2267\n", - "Current minimum: -54.8142\n", - "Iteration No: 448 started. Searching for the next optimal point.\n", - "Iteration No: 448 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1198\n", - "Function value obtained: -41.6579\n", - "Current minimum: -54.8142\n", - "Iteration No: 449 started. Searching for the next optimal point.\n", - "Iteration No: 449 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4314\n", - "Function value obtained: -42.4303\n", - "Current minimum: -54.8142\n", - "Iteration No: 450 started. Searching for the next optimal point.\n", - "Iteration No: 450 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3013\n", - "Function value obtained: -50.2876\n", - "Current minimum: -54.8142\n", - "Iteration No: 451 started. Searching for the next optimal point.\n", - "Iteration No: 451 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5443\n", - "Function value obtained: -40.8997\n", - "Current minimum: -54.8142\n", - "Iteration No: 452 started. Searching for the next optimal point.\n", - "Iteration No: 452 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2848\n", - "Function value obtained: -47.0574\n", - "Current minimum: -54.8142\n", - "Iteration No: 453 started. Searching for the next optimal point.\n", - "Iteration No: 453 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5715\n", - "Function value obtained: -52.1453\n", - "Current minimum: -54.8142\n", - "Iteration No: 454 started. Searching for the next optimal point.\n", - "Iteration No: 454 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3892\n", - "Function value obtained: -43.9850\n", - "Current minimum: -54.8142\n", - "Iteration No: 455 started. Searching for the next optimal point.\n", - "Iteration No: 455 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5149\n", - "Function value obtained: -53.7725\n", - "Current minimum: -54.8142\n", - "Iteration No: 456 started. Searching for the next optimal point.\n", - "Iteration No: 456 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4122\n", - "Function value obtained: -39.4991\n", - "Current minimum: -54.8142\n", - "Iteration No: 457 started. Searching for the next optimal point.\n", - "Iteration No: 457 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5833\n", - "Function value obtained: -44.6653\n", - "Current minimum: -54.8142\n", - "Iteration No: 458 started. Searching for the next optimal point.\n", - "Iteration No: 458 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5064\n", - "Function value obtained: -44.0893\n", - "Current minimum: -54.8142\n", - "Iteration No: 459 started. Searching for the next optimal point.\n", - "Iteration No: 459 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6270\n", - "Function value obtained: -39.9797\n", - "Current minimum: -54.8142\n", - "Iteration No: 460 started. Searching for the next optimal point.\n", - "Iteration No: 460 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3433\n", - "Function value obtained: -37.2180\n", - "Current minimum: -54.8142\n", - "Iteration No: 461 started. Searching for the next optimal point.\n", - "Iteration No: 461 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9003\n", - "Function value obtained: -39.9061\n", - "Current minimum: -54.8142\n", - "Iteration No: 462 started. Searching for the next optimal point.\n", - "Iteration No: 462 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5193\n", - "Function value obtained: -42.4833\n", - "Current minimum: -54.8142\n", - "Iteration No: 463 started. Searching for the next optimal point.\n", - "Iteration No: 463 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0016\n", - "Function value obtained: -46.5803\n", - "Current minimum: -54.8142\n", - "Iteration No: 464 started. Searching for the next optimal point.\n", - "Iteration No: 464 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8799\n", - "Function value obtained: -49.6144\n", - "Current minimum: -54.8142\n", - "Iteration No: 465 started. Searching for the next optimal point.\n", - "Iteration No: 465 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7350\n", - "Function value obtained: -47.8330\n", - "Current minimum: -54.8142\n", - "Iteration No: 466 started. Searching for the next optimal point.\n", - "Iteration No: 466 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6594\n", - "Function value obtained: -43.4489\n", - "Current minimum: -54.8142\n", - "Iteration No: 467 started. Searching for the next optimal point.\n", - "Iteration No: 467 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9256\n", - "Function value obtained: -43.6954\n", - "Current minimum: -54.8142\n", - "Iteration No: 468 started. Searching for the next optimal point.\n", - "Iteration No: 468 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7486\n", - "Function value obtained: -41.3505\n", - "Current minimum: -54.8142\n", - "Iteration No: 469 started. Searching for the next optimal point.\n", - "Iteration No: 469 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1642\n", - "Function value obtained: -44.9156\n", - "Current minimum: -54.8142\n", - "Iteration No: 470 started. Searching for the next optimal point.\n", - "Iteration No: 470 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0119\n", - "Function value obtained: -45.2036\n", - "Current minimum: -54.8142\n", - "Iteration No: 471 started. Searching for the next optimal point.\n", - "Iteration No: 471 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6584\n", - "Function value obtained: -44.8179\n", - "Current minimum: -54.8142\n", - "Iteration No: 472 started. Searching for the next optimal point.\n", - "Iteration No: 472 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0609\n", - "Function value obtained: -40.3063\n", - "Current minimum: -54.8142\n", - "Iteration No: 473 started. Searching for the next optimal point.\n", - "Iteration No: 473 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2703\n", - "Function value obtained: -48.7876\n", - "Current minimum: -54.8142\n", - "Iteration No: 474 started. Searching for the next optimal point.\n", - "Iteration No: 474 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2570\n", - "Function value obtained: -44.8089\n", - "Current minimum: -54.8142\n", - "Iteration No: 475 started. Searching for the next optimal point.\n", - "Iteration No: 475 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4676\n", - "Function value obtained: -41.8878\n", - "Current minimum: -54.8142\n", - "Iteration No: 476 started. Searching for the next optimal point.\n", - "Iteration No: 476 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3026\n", - "Function value obtained: -45.2469\n", - "Current minimum: -54.8142\n", - "Iteration No: 477 started. Searching for the next optimal point.\n", - "Iteration No: 477 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6276\n", - "Function value obtained: -43.7942\n", - "Current minimum: -54.8142\n", - "Iteration No: 478 started. Searching for the next optimal point.\n", - "Iteration No: 478 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3302\n", - "Function value obtained: -34.5440\n", - "Current minimum: -54.8142\n", - "Iteration No: 479 started. Searching for the next optimal point.\n", - "Iteration No: 479 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3783\n", - "Function value obtained: -37.7189\n", - "Current minimum: -54.8142\n", - "Iteration No: 480 started. Searching for the next optimal point.\n", - "Iteration No: 480 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1832\n", - "Function value obtained: -48.2896\n", - "Current minimum: -54.8142\n", - "Iteration No: 481 started. Searching for the next optimal point.\n", - "Iteration No: 481 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3376\n", - "Function value obtained: -48.5426\n", - "Current minimum: -54.8142\n", - "Iteration No: 482 started. Searching for the next optimal point.\n", - "Iteration No: 482 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2552\n", - "Function value obtained: -42.9052\n", - "Current minimum: -54.8142\n", - "Iteration No: 483 started. Searching for the next optimal point.\n", - "Iteration No: 483 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5786\n", - "Function value obtained: -45.0311\n", - "Current minimum: -54.8142\n", - "Iteration No: 484 started. Searching for the next optimal point.\n", - "Iteration No: 484 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2541\n", - "Function value obtained: -50.5432\n", - "Current minimum: -54.8142\n", - "Iteration No: 485 started. Searching for the next optimal point.\n", - "Iteration No: 485 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8294\n", - "Function value obtained: -46.3362\n", - "Current minimum: -54.8142\n", - "Iteration No: 486 started. Searching for the next optimal point.\n", - "Iteration No: 486 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3593\n", - "Function value obtained: -46.4070\n", - "Current minimum: -54.8142\n", - "Iteration No: 487 started. Searching for the next optimal point.\n", - "Iteration No: 487 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8560\n", - "Function value obtained: -43.0009\n", - "Current minimum: -54.8142\n", - "Iteration No: 488 started. Searching for the next optimal point.\n", - "Iteration No: 488 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6731\n", - "Function value obtained: -51.1493\n", - "Current minimum: -54.8142\n", - "Iteration No: 489 started. Searching for the next optimal point.\n", - "Iteration No: 489 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1563\n", - "Function value obtained: -45.9934\n", - "Current minimum: -54.8142\n", - "Iteration No: 490 started. Searching for the next optimal point.\n", - "Iteration No: 490 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9372\n", - "Function value obtained: -45.2431\n", - "Current minimum: -54.8142\n", - "Iteration No: 491 started. Searching for the next optimal point.\n", - "Iteration No: 491 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1646\n", - "Function value obtained: -44.7251\n", - "Current minimum: -54.8142\n", - "Iteration No: 492 started. Searching for the next optimal point.\n", - "Iteration No: 492 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9100\n", - "Function value obtained: -37.3032\n", - "Current minimum: -54.8142\n", - "Iteration No: 493 started. Searching for the next optimal point.\n", - "Iteration No: 493 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4204\n", - "Function value obtained: -42.5588\n", - "Current minimum: -54.8142\n", - "Iteration No: 494 started. Searching for the next optimal point.\n", - "Iteration No: 494 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8247\n", - "Function value obtained: -44.9860\n", - "Current minimum: -54.8142\n", - "Iteration No: 495 started. Searching for the next optimal point.\n", - "Iteration No: 495 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3726\n", - "Function value obtained: -48.5197\n", - "Current minimum: -54.8142\n", - "Iteration No: 496 started. Searching for the next optimal point.\n", - "Iteration No: 496 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9851\n", - "Function value obtained: -40.6493\n", - "Current minimum: -54.8142\n", - "Iteration No: 497 started. Searching for the next optimal point.\n", - "Iteration No: 497 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3255\n", - "Function value obtained: -40.3135\n", - "Current minimum: -54.8142\n", - "Iteration No: 498 started. Searching for the next optimal point.\n", - "Iteration No: 498 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0419\n", - "Function value obtained: -47.9408\n", - "Current minimum: -54.8142\n", - "Iteration No: 499 started. Searching for the next optimal point.\n", - "Iteration No: 499 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2077\n", - "Function value obtained: -49.7427\n", - "Current minimum: -54.8142\n", - "Iteration No: 500 started. Searching for the next optimal point.\n", - "Iteration No: 500 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0262\n", - "Function value obtained: -39.0553\n", - "Current minimum: -54.8142\n", - "CPU times: user 59min 16s, sys: 1h 54min 56s, total: 2h 54min 12s\n", - "Wall time: 49min 9s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-54.8142164, [0.05693229984265447])" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gp = gp_minimize(esc_fun, [(0.002, 0.25)], n_calls = 500, verbose=True, n_jobs=-1)\n", - "esc_gp.fun, esc_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9824bdb6-bacd-497d-bbfc-4ba711629e6a", - "metadata": {}, - "outputs": [], - "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"esc_gp.pkl\"\n", - "dump(esc_gp, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "a75dd9f6-f430-4458-a035-8188c6b255d5", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.0969\n", - "Function value obtained: -43.7686\n", - "Current minimum: -43.7686\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.0963\n", - "Function value obtained: -46.2158\n", - "Current minimum: -46.2158\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.0913\n", - "Function value obtained: -41.6384\n", - "Current minimum: -46.2158\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.0988\n", - "Function value obtained: -38.1748\n", - "Current minimum: -46.2158\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.0932\n", - "Function value obtained: -30.8152\n", - "Current minimum: -46.2158\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.1048\n", - "Function value obtained: -43.2001\n", - "Current minimum: -46.2158\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.0920\n", - "Function value obtained: -29.7055\n", - "Current minimum: -46.2158\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.0981\n", - "Function value obtained: -14.9470\n", - "Current minimum: -46.2158\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.1012\n", - "Function value obtained: -54.5527\n", - "Current minimum: -54.5527\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.2341\n", - "Function value obtained: -41.3130\n", - "Current minimum: -54.5527\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2185\n", - "Function value obtained: -17.4824\n", - "Current minimum: -54.5527\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2318\n", - "Function value obtained: -44.7506\n", - "Current minimum: -54.5527\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2486\n", - "Function value obtained: -47.3967\n", - "Current minimum: -54.5527\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2937\n", - "Function value obtained: -46.2593\n", - "Current minimum: -54.5527\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2439\n", - "Function value obtained: -45.1334\n", - "Current minimum: -54.5527\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2511\n", - "Function value obtained: -52.2848\n", - "Current minimum: -54.5527\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3534\n", - "Function value obtained: -44.2641\n", - "Current minimum: -54.5527\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2656\n", - "Function value obtained: -47.5177\n", - "Current minimum: -54.5527\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2651\n", - "Function value obtained: -39.1811\n", - "Current minimum: -54.5527\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2596\n", - "Function value obtained: -50.4119\n", - "Current minimum: -54.5527\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3033\n", - "Function value obtained: -49.8502\n", - "Current minimum: -54.5527\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2621\n", - "Function value obtained: -34.2876\n", - "Current minimum: -54.5527\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2721\n", - "Function value obtained: -44.8170\n", - "Current minimum: -54.5527\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2651\n", - "Function value obtained: -48.7124\n", - "Current minimum: -54.5527\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2534\n", - "Function value obtained: -43.4613\n", - "Current minimum: -54.5527\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2841\n", - "Function value obtained: -50.1634\n", - "Current minimum: -54.5527\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2204\n", - "Function value obtained: -46.1456\n", - "Current minimum: -54.5527\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2576\n", - "Function value obtained: -49.5123\n", - "Current minimum: -54.5527\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2417\n", - "Function value obtained: -43.8749\n", - "Current minimum: -54.5527\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2863\n", - "Function value obtained: -15.1505\n", - "Current minimum: -54.5527\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2939\n", - "Function value obtained: -39.1945\n", - "Current minimum: -54.5527\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2847\n", - "Function value obtained: -36.3834\n", - "Current minimum: -54.5527\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3902\n", - "Function value obtained: -50.5774\n", - "Current minimum: -54.5527\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2558\n", - "Function value obtained: -42.4625\n", - "Current minimum: -54.5527\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2752\n", - "Function value obtained: -45.6111\n", - "Current minimum: -54.5527\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2798\n", - "Function value obtained: -47.6531\n", - "Current minimum: -54.5527\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2791\n", - "Function value obtained: -49.3194\n", - "Current minimum: -54.5527\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2731\n", - "Function value obtained: -47.0923\n", - "Current minimum: -54.5527\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2289\n", - "Function value obtained: -51.0620\n", - "Current minimum: -54.5527\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2396\n", - "Function value obtained: -47.8308\n", - "Current minimum: -54.5527\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2582\n", - "Function value obtained: -41.7492\n", - "Current minimum: -54.5527\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2331\n", - "Function value obtained: -53.9972\n", - "Current minimum: -54.5527\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2387\n", - "Function value obtained: -45.0765\n", - "Current minimum: -54.5527\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2367\n", - "Function value obtained: -47.4842\n", - "Current minimum: -54.5527\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2368\n", - "Function value obtained: -50.0188\n", - "Current minimum: -54.5527\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2737\n", - "Function value obtained: -43.4538\n", - "Current minimum: -54.5527\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3142\n", - "Function value obtained: -37.4971\n", - "Current minimum: -54.5527\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2614\n", - "Function value obtained: -40.8763\n", - "Current minimum: -54.5527\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3600\n", - "Function value obtained: -47.7224\n", - "Current minimum: -54.5527\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2630\n", - "Function value obtained: -44.4086\n", - "Current minimum: -54.5527\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3092\n", - "Function value obtained: -38.5995\n", - "Current minimum: -54.5527\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2515\n", - "Function value obtained: -41.3947\n", - "Current minimum: -54.5527\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3004\n", - "Function value obtained: -47.2882\n", - "Current minimum: -54.5527\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2521\n", - "Function value obtained: -40.9196\n", - "Current minimum: -54.5527\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2991\n", - "Function value obtained: -46.1899\n", - "Current minimum: -54.5527\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2798\n", - "Function value obtained: -38.6466\n", - "Current minimum: -54.5527\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2674\n", - "Function value obtained: -48.2493\n", - "Current minimum: -54.5527\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2556\n", - "Function value obtained: -44.4888\n", - "Current minimum: -54.5527\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2703\n", - "Function value obtained: -40.4858\n", - "Current minimum: -54.5527\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2723\n", - "Function value obtained: -47.4693\n", - "Current minimum: -54.5527\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2615\n", - "Function value obtained: -42.7108\n", - "Current minimum: -54.5527\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2647\n", - "Function value obtained: -46.9946\n", - "Current minimum: -54.5527\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2688\n", - "Function value obtained: -47.0595\n", - "Current minimum: -54.5527\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2651\n", - "Function value obtained: -51.9457\n", - "Current minimum: -54.5527\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2980\n", - "Function value obtained: -45.4865\n", - "Current minimum: -54.5527\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3872\n", - "Function value obtained: -48.6415\n", - "Current minimum: -54.5527\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2750\n", - "Function value obtained: -41.4827\n", - "Current minimum: -54.5527\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2810\n", - "Function value obtained: -37.4362\n", - "Current minimum: -54.5527\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2635\n", - "Function value obtained: -48.8275\n", - "Current minimum: -54.5527\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2677\n", - "Function value obtained: -45.7886\n", - "Current minimum: -54.5527\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2796\n", - "Function value obtained: -43.8432\n", - "Current minimum: -54.5527\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2834\n", - "Function value obtained: -42.2431\n", - "Current minimum: -54.5527\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2973\n", - "Function value obtained: -45.5565\n", - "Current minimum: -54.5527\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2712\n", - "Function value obtained: -45.7411\n", - "Current minimum: -54.5527\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2646\n", - "Function value obtained: -40.4408\n", - "Current minimum: -54.5527\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2398\n", - "Function value obtained: -43.8138\n", - "Current minimum: -54.5527\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2515\n", - "Function value obtained: -44.6297\n", - "Current minimum: -54.5527\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2557\n", - "Function value obtained: -48.2106\n", - "Current minimum: -54.5527\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2734\n", - "Function value obtained: -49.9589\n", - "Current minimum: -54.5527\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2670\n", - "Function value obtained: -44.8406\n", - "Current minimum: -54.5527\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2655\n", - "Function value obtained: -43.1960\n", - "Current minimum: -54.5527\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2594\n", - "Function value obtained: -46.4007\n", - "Current minimum: -54.5527\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3572\n", - "Function value obtained: -45.8249\n", - "Current minimum: -54.5527\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2812\n", - "Function value obtained: -38.8521\n", - "Current minimum: -54.5527\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2440\n", - "Function value obtained: -46.2729\n", - "Current minimum: -54.5527\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2759\n", - "Function value obtained: -40.7351\n", - "Current minimum: -54.5527\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2846\n", - "Function value obtained: -38.0407\n", - "Current minimum: -54.5527\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3032\n", - "Function value obtained: -42.7363\n", - "Current minimum: -54.5527\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2742\n", - "Function value obtained: -43.3392\n", - "Current minimum: -54.5527\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2667\n", - "Function value obtained: -46.8565\n", - "Current minimum: -54.5527\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2623\n", - "Function value obtained: -42.6646\n", - "Current minimum: -54.5527\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2686\n", - "Function value obtained: -44.5726\n", - "Current minimum: -54.5527\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2713\n", - "Function value obtained: -42.0280\n", - "Current minimum: -54.5527\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2858\n", - "Function value obtained: -37.3644\n", - "Current minimum: -54.5527\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2923\n", - "Function value obtained: -44.7461\n", - "Current minimum: -54.5527\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2817\n", - "Function value obtained: -44.6874\n", - "Current minimum: -54.5527\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2743\n", - "Function value obtained: -41.8551\n", - "Current minimum: -54.5527\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2709\n", - "Function value obtained: -39.7368\n", - "Current minimum: -54.5527\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3960\n", - "Function value obtained: -42.4200\n", - "Current minimum: -54.5527\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2859\n", - "Function value obtained: -45.7529\n", - "Current minimum: -54.5527\n", - "CPU times: user 2min 5s, sys: 2.74 s, total: 2min 7s\n", - "Wall time: 2min 5s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-54.552704199999994, [0.05755569926168816])" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gbrt = gbrt_minimize(esc_fun, [(0.02, 0.15)], n_calls = 100, verbose=True, n_jobs=-1)\n", - "esc_gbrt.fun, esc_gbrt.x" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "33725bba-434d-4c0e-84af-e89b151676f5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(esc_gp)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "abcac3a5-8136-4104-b8e0-abda7b53783e", - "metadata": {}, - "outputs": [], - "source": [ - "dump(esc_gbrt, \"../saved_agents/esc_gbrt.pkl\")" - ] - }, - { - "cell_type": "markdown", - "id": "1c89ae1d-bbeb-49b0-b6fb-6ab0a479d148", - "metadata": {}, - "source": [ - "## Precationary Rule (piecewise linear)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "c5b6f1a3-2d7a-4698-9555-1e10f4032bed", - "metadata": {}, - "outputs": [], - "source": [ - "from skopt.space import Real\n", - "from skopt.utils import use_named_args\n", - "\n", - "space = [Real(0.00001, 1, name='radius'),\n", - " Real(0.00001, np.pi/4.00001, name='theta'),\n", - " Real(0, 0.2, name='y2')]\n", - "\n", - "@use_named_args(space)\n", - "def g(**params):\n", - "\n", - " theta = params[\"theta\"]\n", - " radius = params[\"radius\"]\n", - " x1 = np.sin(theta) * radius\n", - " x2 = np.cos(theta) * radius\n", - " \n", - " assert x1 <= x2, (\"CautionaryRule error: x1 < x2, \" + str(x1) + \", \", str(x2) )\n", - "\n", - " agent = CautionaryRule(x1 = x1, x2 = x2, y2 = params[\"y2\"])\n", - " mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100)\n", - " return -mean \n" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "cda44a0a-55ad-4953-b31e-bbb43d6a4e12", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 12.0631\n", - "Function value obtained: -11.1922\n", - "Current minimum: -11.1922\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 11.6792\n", - "Function value obtained: -7.5372\n", - "Current minimum: -11.1922\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 11.6676\n", - "Function value obtained: -43.8100\n", - "Current minimum: -43.8100\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 11.6998\n", - "Function value obtained: -14.2469\n", - "Current minimum: -43.8100\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 11.6204\n", - "Function value obtained: -8.4166\n", - "Current minimum: -43.8100\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 11.8923\n", - "Function value obtained: -8.4650\n", - "Current minimum: -43.8100\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 11.9696\n", - "Function value obtained: -44.3547\n", - "Current minimum: -44.3547\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 11.4065\n", - "Function value obtained: -40.5336\n", - "Current minimum: -44.3547\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 11.6245\n", - "Function value obtained: -6.8984\n", - "Current minimum: -44.3547\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 14.7360\n", - "Function value obtained: -53.2859\n", - "Current minimum: -53.2859\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1538\n", - "Function value obtained: -54.4276\n", - "Current minimum: -54.4276\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1046\n", - "Function value obtained: -7.2624\n", - "Current minimum: -54.4276\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2196\n", - "Function value obtained: -57.2276\n", - "Current minimum: -57.2276\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2795\n", - "Function value obtained: -53.6469\n", - "Current minimum: -57.2276\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3982\n", - "Function value obtained: -53.3176\n", - "Current minimum: -57.2276\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3147\n", - "Function value obtained: -52.0601\n", - "Current minimum: -57.2276\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4362\n", - "Function value obtained: -56.0794\n", - "Current minimum: -57.2276\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5731\n", - "Function value obtained: -51.6863\n", - "Current minimum: -57.2276\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3436\n", - "Function value obtained: -57.0873\n", - "Current minimum: -57.2276\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4931\n", - "Function value obtained: -52.0620\n", - "Current minimum: -57.2276\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6610\n", - "Function value obtained: -26.1188\n", - "Current minimum: -57.2276\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3300\n", - "Function value obtained: -53.3611\n", - "Current minimum: -57.2276\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2944\n", - "Function value obtained: -48.6626\n", - "Current minimum: -57.2276\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5814\n", - "Function value obtained: -47.9890\n", - "Current minimum: -57.2276\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4622\n", - "Function value obtained: -55.0811\n", - "Current minimum: -57.2276\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3839\n", - "Function value obtained: -57.2854\n", - "Current minimum: -57.2854\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3792\n", - "Function value obtained: -53.8160\n", - "Current minimum: -57.2854\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2599\n", - "Function value obtained: -56.0302\n", - "Current minimum: -57.2854\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5606\n", - "Function value obtained: -56.2033\n", - "Current minimum: -57.2854\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1144\n", - "Function value obtained: -55.4438\n", - "Current minimum: -57.2854\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5012\n", - "Function value obtained: -55.2050\n", - "Current minimum: -57.2854\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3371\n", - "Function value obtained: -56.6491\n", - "Current minimum: -57.2854\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2943\n", - "Function value obtained: -55.0857\n", - "Current minimum: -57.2854\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6617\n", - "Function value obtained: -57.0010\n", - "Current minimum: -57.2854\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3741\n", - "Function value obtained: -54.0185\n", - "Current minimum: -57.2854\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3744\n", - "Function value obtained: -53.1750\n", - "Current minimum: -57.2854\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8960\n", - "Function value obtained: -49.9520\n", - "Current minimum: -57.2854\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1303\n", - "Function value obtained: -51.7138\n", - "Current minimum: -57.2854\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9004\n", - "Function value obtained: -53.5052\n", - "Current minimum: -57.2854\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2150\n", - "Function value obtained: -38.9193\n", - "Current minimum: -57.2854\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0384\n", - "Function value obtained: -48.4244\n", - "Current minimum: -57.2854\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0125\n", - "Function value obtained: -57.9257\n", - "Current minimum: -57.9257\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0535\n", - "Function value obtained: -58.1373\n", - "Current minimum: -58.1373\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1772\n", - "Function value obtained: -56.5031\n", - "Current minimum: -58.1373\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0761\n", - "Function value obtained: -58.3261\n", - "Current minimum: -58.3261\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0158\n", - "Function value obtained: -57.4381\n", - "Current minimum: -58.3261\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1281\n", - "Function value obtained: -57.4230\n", - "Current minimum: -58.3261\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1244\n", - "Function value obtained: -58.0519\n", - "Current minimum: -58.3261\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1843\n", - "Function value obtained: -55.9611\n", - "Current minimum: -58.3261\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1911\n", - "Function value obtained: -57.1577\n", - "Current minimum: -58.3261\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8229\n", - "Function value obtained: -55.2999\n", - "Current minimum: -58.3261\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0927\n", - "Function value obtained: -9.6032\n", - "Current minimum: -58.3261\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1839\n", - "Function value obtained: -61.9557\n", - "Current minimum: -61.9557\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0338\n", - "Function value obtained: -60.1061\n", - "Current minimum: -61.9557\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4558\n", - "Function value obtained: -0.0000\n", - "Current minimum: -61.9557\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9799\n", - "Function value obtained: -59.4575\n", - "Current minimum: -61.9557\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4286\n", - "Function value obtained: -60.8400\n", - "Current minimum: -61.9557\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3232\n", - "Function value obtained: -61.6843\n", - "Current minimum: -61.9557\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1421\n", - "Function value obtained: -59.6827\n", - "Current minimum: -61.9557\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3285\n", - "Function value obtained: -58.2762\n", - "Current minimum: -61.9557\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6430\n", - "Function value obtained: -45.3887\n", - "Current minimum: -61.9557\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5029\n", - "Function value obtained: -51.1138\n", - "Current minimum: -61.9557\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6738\n", - "Function value obtained: -0.0000\n", - "Current minimum: -61.9557\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1612\n", - "Function value obtained: -58.4828\n", - "Current minimum: -61.9557\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6307\n", - "Function value obtained: -57.9205\n", - "Current minimum: -61.9557\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6696\n", - "Function value obtained: -57.3052\n", - "Current minimum: -61.9557\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7142\n", - "Function value obtained: -51.2662\n", - "Current minimum: -61.9557\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3029\n", - "Function value obtained: -58.2466\n", - "Current minimum: -61.9557\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1258\n", - "Function value obtained: -59.2143\n", - "Current minimum: -61.9557\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4963\n", - "Function value obtained: -57.6410\n", - "Current minimum: -61.9557\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4819\n", - "Function value obtained: -59.1981\n", - "Current minimum: -61.9557\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5206\n", - "Function value obtained: -0.0000\n", - "Current minimum: -61.9557\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7407\n", - "Function value obtained: -53.8872\n", - "Current minimum: -61.9557\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3749\n", - "Function value obtained: -56.9306\n", - "Current minimum: -61.9557\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9345\n", - "Function value obtained: -0.0000\n", - "Current minimum: -61.9557\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5919\n", - "Function value obtained: -59.3682\n", - "Current minimum: -61.9557\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7772\n", - "Function value obtained: -46.0459\n", - "Current minimum: -61.9557\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7131\n", - "Function value obtained: -59.6059\n", - "Current minimum: -61.9557\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8468\n", - "Function value obtained: -14.5497\n", - "Current minimum: -61.9557\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2665\n", - "Function value obtained: -56.0167\n", - "Current minimum: -61.9557\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2200\n", - "Function value obtained: -58.0368\n", - "Current minimum: -61.9557\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7493\n", - "Function value obtained: -58.2075\n", - "Current minimum: -61.9557\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7839\n", - "Function value obtained: -41.8693\n", - "Current minimum: -61.9557\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8004\n", - "Function value obtained: -49.5409\n", - "Current minimum: -61.9557\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7939\n", - "Function value obtained: -44.5040\n", - "Current minimum: -61.9557\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9103\n", - "Function value obtained: -57.4908\n", - "Current minimum: -61.9557\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6059\n", - "Function value obtained: -40.2197\n", - "Current minimum: -61.9557\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0102\n", - "Function value obtained: -19.3440\n", - "Current minimum: -61.9557\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1362\n", - "Function value obtained: -58.3537\n", - "Current minimum: -61.9557\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4704\n", - "Function value obtained: -61.0784\n", - "Current minimum: -61.9557\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5108\n", - "Function value obtained: -58.4893\n", - "Current minimum: -61.9557\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7022\n", - "Function value obtained: -56.7703\n", - "Current minimum: -61.9557\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8107\n", - "Function value obtained: -55.5277\n", - "Current minimum: -61.9557\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8380\n", - "Function value obtained: -58.1493\n", - "Current minimum: -61.9557\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6272\n", - "Function value obtained: -57.9444\n", - "Current minimum: -61.9557\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9787\n", - "Function value obtained: -34.9039\n", - "Current minimum: -61.9557\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9475\n", - "Function value obtained: -38.9125\n", - "Current minimum: -61.9557\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3446\n", - "Function value obtained: -56.3033\n", - "Current minimum: -61.9557\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4475\n", - "Function value obtained: -62.9005\n", - "Current minimum: -62.9005\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8014\n", - "Function value obtained: -0.0000\n", - "Current minimum: -62.9005\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4487\n", - "Function value obtained: -61.0737\n", - "Current minimum: -62.9005\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8758\n", - "Function value obtained: -56.7252\n", - "Current minimum: -62.9005\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2497\n", - "Function value obtained: -61.8095\n", - "Current minimum: -62.9005\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3870\n", - "Function value obtained: -61.0059\n", - "Current minimum: -62.9005\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9763\n", - "Function value obtained: -41.9057\n", - "Current minimum: -62.9005\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5753\n", - "Function value obtained: -61.0006\n", - "Current minimum: -62.9005\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1875\n", - "Function value obtained: -43.8200\n", - "Current minimum: -62.9005\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0394\n", - "Function value obtained: -42.7477\n", - "Current minimum: -62.9005\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1592\n", - "Function value obtained: -53.2285\n", - "Current minimum: -62.9005\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2860\n", - "Function value obtained: -53.4172\n", - "Current minimum: -62.9005\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6838\n", - "Function value obtained: -61.4022\n", - "Current minimum: -62.9005\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6009\n", - "Function value obtained: -59.7981\n", - "Current minimum: -62.9005\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7378\n", - "Function value obtained: -61.2546\n", - "Current minimum: -62.9005\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5202\n", - "Function value obtained: -10.6417\n", - "Current minimum: -62.9005\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0806\n", - "Function value obtained: -45.6646\n", - "Current minimum: -62.9005\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7339\n", - "Function value obtained: -61.6434\n", - "Current minimum: -62.9005\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3953\n", - "Function value obtained: -59.6843\n", - "Current minimum: -62.9005\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1120\n", - "Function value obtained: -44.3616\n", - "Current minimum: -62.9005\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3739\n", - "Function value obtained: -59.0726\n", - "Current minimum: -62.9005\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5929\n", - "Function value obtained: -55.0735\n", - "Current minimum: -62.9005\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2012\n", - "Function value obtained: -0.0000\n", - "Current minimum: -62.9005\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3457\n", - "Function value obtained: -47.5516\n", - "Current minimum: -62.9005\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2877\n", - "Function value obtained: -40.2875\n", - "Current minimum: -62.9005\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3080\n", - "Function value obtained: -52.4638\n", - "Current minimum: -62.9005\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8499\n", - "Function value obtained: -61.7379\n", - "Current minimum: -62.9005\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8898\n", - "Function value obtained: -59.3523\n", - "Current minimum: -62.9005\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5504\n", - "Function value obtained: -28.2328\n", - "Current minimum: -62.9005\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1396\n", - "Function value obtained: -59.3144\n", - "Current minimum: -62.9005\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8254\n", - "Function value obtained: -58.9704\n", - "Current minimum: -62.9005\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1681\n", - "Function value obtained: -57.4315\n", - "Current minimum: -62.9005\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4393\n", - "Function value obtained: -59.5577\n", - "Current minimum: -62.9005\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4760\n", - "Function value obtained: -56.6495\n", - "Current minimum: -62.9005\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3716\n", - "Function value obtained: -58.5484\n", - "Current minimum: -62.9005\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5279\n", - "Function value obtained: -55.9982\n", - "Current minimum: -62.9005\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7564\n", - "Function value obtained: -60.9014\n", - "Current minimum: -62.9005\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8224\n", - "Function value obtained: -62.2740\n", - "Current minimum: -62.9005\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0427\n", - "Function value obtained: -61.3275\n", - "Current minimum: -62.9005\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0619\n", - "Function value obtained: -62.7974\n", - "Current minimum: -62.9005\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0003\n", - "Function value obtained: -60.1912\n", - "Current minimum: -62.9005\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0238\n", - "Function value obtained: -58.9332\n", - "Current minimum: -62.9005\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3479\n", - "Function value obtained: -55.8342\n", - "Current minimum: -62.9005\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8661\n", - "Function value obtained: -25.3106\n", - "Current minimum: -62.9005\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7387\n", - "Function value obtained: -60.1885\n", - "Current minimum: -62.9005\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9695\n", - "Function value obtained: -0.0954\n", - "Current minimum: -62.9005\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0013\n", - "Function value obtained: -61.3056\n", - "Current minimum: -62.9005\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1523\n", - "Function value obtained: -60.0945\n", - "Current minimum: -62.9005\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0945\n", - "Function value obtained: -57.7263\n", - "Current minimum: -62.9005\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9058\n", - "Function value obtained: -60.9772\n", - "Current minimum: -62.9005\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0407\n", - "Function value obtained: -58.2923\n", - "Current minimum: -62.9005\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1575\n", - "Function value obtained: -60.9939\n", - "Current minimum: -62.9005\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8773\n", - "Function value obtained: -61.1306\n", - "Current minimum: -62.9005\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0987\n", - "Function value obtained: -60.3466\n", - "Current minimum: -62.9005\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3747\n", - "Function value obtained: -60.3609\n", - "Current minimum: -62.9005\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4891\n", - "Function value obtained: -61.0574\n", - "Current minimum: -62.9005\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2338\n", - "Function value obtained: -59.6392\n", - "Current minimum: -62.9005\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3860\n", - "Function value obtained: -60.8483\n", - "Current minimum: -62.9005\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3044\n", - "Function value obtained: -62.2942\n", - "Current minimum: -62.9005\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3848\n", - "Function value obtained: -64.0604\n", - "Current minimum: -64.0604\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3825\n", - "Function value obtained: -59.2104\n", - "Current minimum: -64.0604\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2389\n", - "Function value obtained: -59.3688\n", - "Current minimum: -64.0604\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2310\n", - "Function value obtained: -57.6666\n", - "Current minimum: -64.0604\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1349\n", - "Function value obtained: -59.7396\n", - "Current minimum: -64.0604\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1635\n", - "Function value obtained: -60.7662\n", - "Current minimum: -64.0604\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4525\n", - "Function value obtained: -59.8801\n", - "Current minimum: -64.0604\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0836\n", - "Function value obtained: -60.0744\n", - "Current minimum: -64.0604\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4466\n", - "Function value obtained: -60.2734\n", - "Current minimum: -64.0604\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6210\n", - "Function value obtained: -60.4521\n", - "Current minimum: -64.0604\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6434\n", - "Function value obtained: -61.3086\n", - "Current minimum: -64.0604\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3082\n", - "Function value obtained: -62.7924\n", - "Current minimum: -64.0604\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4333\n", - "Function value obtained: -60.2422\n", - "Current minimum: -64.0604\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5779\n", - "Function value obtained: -61.4014\n", - "Current minimum: -64.0604\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3421\n", - "Function value obtained: -60.5569\n", - "Current minimum: -64.0604\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6447\n", - "Function value obtained: -61.2388\n", - "Current minimum: -64.0604\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6991\n", - "Function value obtained: -57.9800\n", - "Current minimum: -64.0604\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1815\n", - "Function value obtained: -58.1343\n", - "Current minimum: -64.0604\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4433\n", - "Function value obtained: -55.6754\n", - "Current minimum: -64.0604\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4770\n", - "Function value obtained: -61.8096\n", - "Current minimum: -64.0604\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5596\n", - "Function value obtained: -61.4017\n", - "Current minimum: -64.0604\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6467\n", - "Function value obtained: -62.6805\n", - "Current minimum: -64.0604\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7692\n", - "Function value obtained: -62.1729\n", - "Current minimum: -64.0604\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5635\n", - "Function value obtained: -62.3867\n", - "Current minimum: -64.0604\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7412\n", - "Function value obtained: -59.2715\n", - "Current minimum: -64.0604\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6402\n", - "Function value obtained: -62.3255\n", - "Current minimum: -64.0604\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6232\n", - "Function value obtained: -57.7878\n", - "Current minimum: -64.0604\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4434\n", - "Function value obtained: -60.0756\n", - "Current minimum: -64.0604\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6968\n", - "Function value obtained: -62.7134\n", - "Current minimum: -64.0604\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7622\n", - "Function value obtained: -60.4191\n", - "Current minimum: -64.0604\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4076\n", - "Function value obtained: -59.9884\n", - "Current minimum: -64.0604\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8618\n", - "Function value obtained: -58.0531\n", - "Current minimum: -64.0604\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0275\n", - "Function value obtained: -60.1829\n", - "Current minimum: -64.0604\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9700\n", - "Function value obtained: -56.9907\n", - "Current minimum: -64.0604\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9410\n", - "Function value obtained: -59.3060\n", - "Current minimum: -64.0604\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0554\n", - "Function value obtained: -60.5084\n", - "Current minimum: -64.0604\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6792\n", - "Function value obtained: -59.3228\n", - "Current minimum: -64.0604\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9370\n", - "Function value obtained: -61.6902\n", - "Current minimum: -64.0604\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3246\n", - "Function value obtained: -59.4745\n", - "Current minimum: -64.0604\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1163\n", - "Function value obtained: -59.3413\n", - "Current minimum: -64.0604\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2552\n", - "Function value obtained: -62.9237\n", - "Current minimum: -64.0604\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0436\n", - "Function value obtained: -60.1312\n", - "Current minimum: -64.0604\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9885\n", - "Function value obtained: -60.2704\n", - "Current minimum: -64.0604\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8081\n", - "Function value obtained: -63.1430\n", - "Current minimum: -64.0604\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6214\n", - "Function value obtained: -60.6471\n", - "Current minimum: -64.0604\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1959\n", - "Function value obtained: -59.2585\n", - "Current minimum: -64.0604\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1290\n", - "Function value obtained: -61.1949\n", - "Current minimum: -64.0604\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9415\n", - "Function value obtained: -59.6614\n", - "Current minimum: -64.0604\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4367\n", - "Function value obtained: -60.3861\n", - "Current minimum: -64.0604\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2015\n", - "Function value obtained: -58.7163\n", - "Current minimum: -64.0604\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8368\n", - "Function value obtained: -60.6531\n", - "Current minimum: -64.0604\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0847\n", - "Function value obtained: -61.3507\n", - "Current minimum: -64.0604\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9799\n", - "Function value obtained: -62.0210\n", - "Current minimum: -64.0604\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0691\n", - "Function value obtained: -59.2022\n", - "Current minimum: -64.0604\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0307\n", - "Function value obtained: -59.5146\n", - "Current minimum: -64.0604\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1590\n", - "Function value obtained: -63.3082\n", - "Current minimum: -64.0604\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1441\n", - "Function value obtained: -62.3790\n", - "Current minimum: -64.0604\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5168\n", - "Function value obtained: -61.5604\n", - "Current minimum: -64.0604\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3991\n", - "Function value obtained: -58.8421\n", - "Current minimum: -64.0604\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5549\n", - "Function value obtained: -60.0340\n", - "Current minimum: -64.0604\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3332\n", - "Function value obtained: -60.2647\n", - "Current minimum: -64.0604\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3307\n", - "Function value obtained: -62.6641\n", - "Current minimum: -64.0604\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7140\n", - "Function value obtained: -57.3861\n", - "Current minimum: -64.0604\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5874\n", - "Function value obtained: -60.4384\n", - "Current minimum: -64.0604\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3385\n", - "Function value obtained: -60.9000\n", - "Current minimum: -64.0604\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6188\n", - "Function value obtained: -61.4048\n", - "Current minimum: -64.0604\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4471\n", - "Function value obtained: -60.4370\n", - "Current minimum: -64.0604\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4378\n", - "Function value obtained: -61.7069\n", - "Current minimum: -64.0604\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4979\n", - "Function value obtained: -59.2262\n", - "Current minimum: -64.0604\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6535\n", - "Function value obtained: -58.9766\n", - "Current minimum: -64.0604\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4131\n", - "Function value obtained: -62.6909\n", - "Current minimum: -64.0604\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4884\n", - "Function value obtained: -60.0673\n", - "Current minimum: -64.0604\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7637\n", - "Function value obtained: -60.6865\n", - "Current minimum: -64.0604\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8135\n", - "Function value obtained: -61.3215\n", - "Current minimum: -64.0604\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8739\n", - "Function value obtained: -61.6915\n", - "Current minimum: -64.0604\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0358\n", - "Function value obtained: -61.9783\n", - "Current minimum: -64.0604\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7576\n", - "Function value obtained: -60.8730\n", - "Current minimum: -64.0604\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1331\n", - "Function value obtained: -61.0792\n", - "Current minimum: -64.0604\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0708\n", - "Function value obtained: -59.3794\n", - "Current minimum: -64.0604\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2525\n", - "Function value obtained: -61.2349\n", - "Current minimum: -64.0604\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1007\n", - "Function value obtained: -61.3212\n", - "Current minimum: -64.0604\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9909\n", - "Function value obtained: -61.0800\n", - "Current minimum: -64.0604\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7854\n", - "Function value obtained: -62.4729\n", - "Current minimum: -64.0604\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0710\n", - "Function value obtained: -63.5244\n", - "Current minimum: -64.0604\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7547\n", - "Function value obtained: -63.3006\n", - "Current minimum: -64.0604\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0466\n", - "Function value obtained: -61.5016\n", - "Current minimum: -64.0604\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0494\n", - "Function value obtained: -61.8958\n", - "Current minimum: -64.0604\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3558\n", - "Function value obtained: -57.9491\n", - "Current minimum: -64.0604\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1206\n", - "Function value obtained: -58.2870\n", - "Current minimum: -64.0604\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1222\n", - "Function value obtained: -57.8903\n", - "Current minimum: -64.0604\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5961\n", - "Function value obtained: -61.4123\n", - "Current minimum: -64.0604\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3622\n", - "Function value obtained: -61.4696\n", - "Current minimum: -64.0604\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1979\n", - "Function value obtained: -58.7551\n", - "Current minimum: -64.0604\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1817\n", - "Function value obtained: -62.6879\n", - "Current minimum: -64.0604\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4637\n", - "Function value obtained: -62.1014\n", - "Current minimum: -64.0604\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8681\n", - "Function value obtained: -60.3592\n", - "Current minimum: -64.0604\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6765\n", - "Function value obtained: -59.8495\n", - "Current minimum: -64.0604\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1218\n", - "Function value obtained: -60.2259\n", - "Current minimum: -64.0604\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3014\n", - "Function value obtained: -60.6231\n", - "Current minimum: -64.0604\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8055\n", - "Function value obtained: -59.2733\n", - "Current minimum: -64.0604\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7514\n", - "Function value obtained: -63.3695\n", - "Current minimum: -64.0604\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7671\n", - "Function value obtained: -61.1099\n", - "Current minimum: -64.0604\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2785\n", - "Function value obtained: -61.4664\n", - "Current minimum: -64.0604\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7401\n", - "Function value obtained: -59.3596\n", - "Current minimum: -64.0604\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6561\n", - "Function value obtained: -60.3452\n", - "Current minimum: -64.0604\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7207\n", - "Function value obtained: -61.2755\n", - "Current minimum: -64.0604\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5358\n", - "Function value obtained: -59.8420\n", - "Current minimum: -64.0604\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7251\n", - "Function value obtained: -62.3853\n", - "Current minimum: -64.0604\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7367\n", - "Function value obtained: -59.5302\n", - "Current minimum: -64.0604\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7366\n", - "Function value obtained: -60.5180\n", - "Current minimum: -64.0604\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7718\n", - "Function value obtained: -61.8308\n", - "Current minimum: -64.0604\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1862\n", - "Function value obtained: -59.0548\n", - "Current minimum: -64.0604\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0374\n", - "Function value obtained: -62.2117\n", - "Current minimum: -64.0604\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7479\n", - "Function value obtained: -61.1200\n", - "Current minimum: -64.0604\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7602\n", - "Function value obtained: -60.7124\n", - "Current minimum: -64.0604\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8492\n", - "Function value obtained: -58.5015\n", - "Current minimum: -64.0604\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6836\n", - "Function value obtained: -61.7954\n", - "Current minimum: -64.0604\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8256\n", - "Function value obtained: -60.1689\n", - "Current minimum: -64.0604\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8844\n", - "Function value obtained: -59.4217\n", - "Current minimum: -64.0604\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9233\n", - "Function value obtained: -63.3592\n", - "Current minimum: -64.0604\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7114\n", - "Function value obtained: -59.3125\n", - "Current minimum: -64.0604\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0292\n", - "Function value obtained: -56.7142\n", - "Current minimum: -64.0604\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1970\n", - "Function value obtained: -60.8999\n", - "Current minimum: -64.0604\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2766\n", - "Function value obtained: -60.3053\n", - "Current minimum: -64.0604\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3173\n", - "Function value obtained: -59.4216\n", - "Current minimum: -64.0604\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3962\n", - "Function value obtained: -59.0886\n", - "Current minimum: -64.0604\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2433\n", - "Function value obtained: -61.0841\n", - "Current minimum: -64.0604\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4059\n", - "Function value obtained: -61.1839\n", - "Current minimum: -64.0604\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3177\n", - "Function value obtained: -61.2305\n", - "Current minimum: -64.0604\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4609\n", - "Function value obtained: -57.4124\n", - "Current minimum: -64.0604\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6741\n", - "Function value obtained: -61.0302\n", - "Current minimum: -64.0604\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 16.7129\n", - "Function value obtained: -60.1829\n", - "Current minimum: -64.0604\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4054\n", - "Function value obtained: -60.2548\n", - "Current minimum: -64.0604\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5753\n", - "Function value obtained: -63.8931\n", - "Current minimum: -64.0604\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5736\n", - "Function value obtained: -60.1983\n", - "Current minimum: -64.0604\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6126\n", - "Function value obtained: -58.2870\n", - "Current minimum: -64.0604\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6290\n", - "Function value obtained: -61.3748\n", - "Current minimum: -64.0604\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3719\n", - "Function value obtained: -58.6881\n", - "Current minimum: -64.0604\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3235\n", - "Function value obtained: -62.1723\n", - "Current minimum: -64.0604\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4572\n", - "Function value obtained: -60.2343\n", - "Current minimum: -64.0604\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 16.7519\n", - "Function value obtained: -60.1997\n", - "Current minimum: -64.0604\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 17.0712\n", - "Function value obtained: -62.1605\n", - "Current minimum: -64.0604\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8534\n", - "Function value obtained: -57.8923\n", - "Current minimum: -64.0604\n", - "CPU times: user 1h 16min 57s, sys: 1h 8min 46s, total: 2h 25min 43s\n", - "Wall time: 1h 8min 13s\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9550\n", + "Function value obtained: -306.1268\n", + "Current minimum: -410.9384\n", + "Iteration No: 25 started. Searching for the next optimal point.\n", + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1523\n", + "Function value obtained: -228.2250\n", + "Current minimum: -410.9384\n", + "Iteration No: 26 started. Searching for the next optimal point.\n", + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9595\n", + "Function value obtained: -204.5615\n", + "Current minimum: -410.9384\n", + "Iteration No: 27 started. Searching for the next optimal point.\n", + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0190\n", + "Function value obtained: -68.6305\n", + "Current minimum: -410.9384\n", + "Iteration No: 28 started. Searching for the next optimal point.\n", + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0223\n", + "Function value obtained: -243.1624\n", + "Current minimum: -410.9384\n", + "Iteration No: 29 started. Searching for the next optimal point.\n", + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9260\n", + "Function value obtained: -1.8602\n", + "Current minimum: -410.9384\n", + "Iteration No: 30 started. Searching for the next optimal point.\n", + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9621\n", + "Function value obtained: -0.0000\n", + "Current minimum: -410.9384\n", + "Iteration No: 31 started. Searching for the next optimal point.\n", + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0314\n", + "Function value obtained: -378.3103\n", + "Current minimum: -410.9384\n", + "Iteration No: 32 started. Searching for the next optimal point.\n", + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9896\n", + "Function value obtained: -278.9007\n", + "Current minimum: -410.9384\n", + "Iteration No: 33 started. Searching for the next optimal point.\n", + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4333\n", + "Function value obtained: -226.2895\n", + "Current minimum: -410.9384\n", + "Iteration No: 34 started. Searching for the next optimal point.\n", + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4029\n", + "Function value obtained: -2.9886\n", + "Current minimum: -410.9384\n", + "Iteration No: 35 started. Searching for the next optimal point.\n", + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1865\n", + "Function value obtained: -274.4211\n", + "Current minimum: -410.9384\n", + "Iteration No: 36 started. Searching for the next optimal point.\n", + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 15.3276\n", + "Function value obtained: -112.1505\n", + "Current minimum: -410.9384\n", + "Iteration No: 37 started. Searching for the next optimal point.\n", + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4141\n", + "Function value obtained: -113.2420\n", + "Current minimum: -410.9384\n", + "Iteration No: 38 started. Searching for the next optimal point.\n", + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0401\n", + "Function value obtained: -2.1604\n", + "Current minimum: -410.9384\n", + "Iteration No: 39 started. Searching for the next optimal point.\n", + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1852\n", + "Function value obtained: -127.1841\n", + "Current minimum: -410.9384\n", + "Iteration No: 40 started. Searching for the next optimal point.\n", + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8967\n", + "Function value obtained: -236.8568\n", + "Current minimum: -410.9384\n", + "Iteration No: 41 started. Searching for the next optimal point.\n", + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1567\n", + "Function value obtained: -0.0000\n", + "Current minimum: -410.9384\n", + "Iteration No: 42 started. Searching for the next optimal point.\n", + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1260\n", + "Function value obtained: -335.5016\n", + "Current minimum: -410.9384\n", + "Iteration No: 43 started. Searching for the next optimal point.\n", + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0298\n", + "Function value obtained: -353.8426\n", + "Current minimum: -410.9384\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1143\n", + "Function value obtained: -351.4422\n", + "Current minimum: -410.9384\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0066\n", + "Function value obtained: -248.2000\n", + "Current minimum: -410.9384\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1112\n", + "Function value obtained: -265.7142\n", + "Current minimum: -410.9384\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [1.0, 1e-05, 1.0] before, using random point [0.3803735619256906, 0.501488617712397, 0.11082626422314903]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0832\n", + "Function value obtained: -306.8230\n", + "Current minimum: -410.9384\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1915\n", + "Function value obtained: -192.0073\n", + "Current minimum: -410.9384\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [1.0, 1e-05, 1.0] before, using random point [0.7877568546929663, 0.7095084957907133, 0.24825060528452686]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1035\n", + "Function value obtained: -102.9234\n", + "Current minimum: -410.9384\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [1.0, 1e-05, 1.0] before, using random point [0.5156288173888501, 0.18829691640463697, 0.8405282125608928]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0984\n", + "Function value obtained: -354.1497\n", + "Current minimum: -410.9384\n", + "CPU times: user 14min 7s, sys: 11min 53s, total: 26min 1s\n", + "Wall time: 12min 45s\n" ] }, { "data": { "text/plain": [ - "(-64.06042883, [0.041136645707627796, 0.7853961999069485, 0.12010362758045579])" + "(-410.93840314,\n", + " [0.21946183895274754, 0.44335860308748737, 0.41059228240857215])" ] }, - "execution_count": 11, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "g_gp = gp_minimize(g, space, n_calls = 300, verbose=True, n_jobs=-1)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f7bf06c4-8931-4970-955b-1c2799082bf4", - "metadata": {}, - "outputs": [], - "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"cr_gp.pkl\"\n", - "dump(g_gbrt, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" + "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "cr_gp.fun, cr_gp.x" ] }, { "cell_type": "code", - "execution_count": null, - "id": "c2b92ed3-d6f7-437e-be4f-796eac28a430", + "execution_count": 14, + "id": "faa3ef2e-e477-401d-b663-3e10e15d2023", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "# -> (-64.06042883, [0.041136645707627796, 0.7853961999069485, 0.12010362758045579])" + "plot_objective(cr_gp)" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "07b3c0ff-7772-4b7b-926f-bf18cc3cd425", + "execution_count": 17, + "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -8120,1519 +784,1075 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 11.6798\n", - "Function value obtained: -17.7134\n", - "Current minimum: -17.7134\n", + "Time taken: 15.4285\n", + "Function value obtained: -145.5092\n", + "Current minimum: -145.5092\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 11.6132\n", - "Function value obtained: -35.0209\n", - "Current minimum: -35.0209\n", + "Time taken: 15.4036\n", + "Function value obtained: -376.5553\n", + "Current minimum: -376.5553\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 11.4436\n", - "Function value obtained: -4.6572\n", - "Current minimum: -35.0209\n", + "Time taken: 15.1200\n", + "Function value obtained: -61.3406\n", + "Current minimum: -376.5553\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 11.6489\n", - "Function value obtained: -11.3697\n", - "Current minimum: -35.0209\n", + "Time taken: 15.1149\n", + "Function value obtained: -103.9941\n", + "Current minimum: -376.5553\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 11.9656\n", - "Function value obtained: -24.4783\n", - "Current minimum: -35.0209\n", + "Time taken: 14.9661\n", + "Function value obtained: -82.7326\n", + "Current minimum: -376.5553\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 11.5108\n", - "Function value obtained: -3.6088\n", - "Current minimum: -35.0209\n", + "Time taken: 14.9986\n", + "Function value obtained: -238.8941\n", + "Current minimum: -376.5553\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 11.3614\n", - "Function value obtained: -12.0866\n", - "Current minimum: -35.0209\n", + "Time taken: 14.9116\n", + "Function value obtained: -232.8373\n", + "Current minimum: -376.5553\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 11.5792\n", - "Function value obtained: -7.3679\n", - "Current minimum: -35.0209\n", + "Time taken: 14.8015\n", + "Function value obtained: -243.3373\n", + "Current minimum: -376.5553\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 11.7985\n", - "Function value obtained: -47.2876\n", - "Current minimum: -47.2876\n", + "Time taken: 14.8692\n", + "Function value obtained: -75.9417\n", + "Current minimum: -376.5553\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 11.9403\n", - "Function value obtained: -18.1785\n", - "Current minimum: -47.2876\n", + "Time taken: 18.6768\n", + "Function value obtained: -226.2103\n", + "Current minimum: -376.5553\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1223\n", - "Function value obtained: -52.7711\n", - "Current minimum: -52.7711\n", + "Time taken: 16.3257\n", + "Function value obtained: -254.7679\n", + "Current minimum: -376.5553\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0074\n", - "Function value obtained: -45.7910\n", - "Current minimum: -52.7711\n", + "Time taken: 16.1989\n", + "Function value obtained: -155.9018\n", + "Current minimum: -376.5553\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0501\n", - "Function value obtained: -54.5965\n", - "Current minimum: -54.5965\n", + "Time taken: 16.5391\n", + "Function value obtained: -202.6269\n", + "Current minimum: -376.5553\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0025\n", - "Function value obtained: -55.8562\n", - "Current minimum: -55.8562\n", + "Time taken: 16.6226\n", + "Function value obtained: -338.3643\n", + "Current minimum: -376.5553\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1321\n", - "Function value obtained: -57.0049\n", - "Current minimum: -57.0049\n", + "Time taken: 16.0937\n", + "Function value obtained: -320.7793\n", + "Current minimum: -376.5553\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0953\n", - "Function value obtained: -48.6053\n", - "Current minimum: -57.0049\n", + "Time taken: 16.9577\n", + "Function value obtained: -264.4446\n", + "Current minimum: -376.5553\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8464\n", - "Function value obtained: -15.7491\n", - "Current minimum: -57.0049\n", + "Time taken: 16.2780\n", + "Function value obtained: -270.6296\n", + "Current minimum: -376.5553\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1156\n", - "Function value obtained: -58.3403\n", - "Current minimum: -58.3403\n", + "Time taken: 16.2300\n", + "Function value obtained: -438.8857\n", + "Current minimum: -438.8857\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8599\n", - "Function value obtained: -61.2241\n", - "Current minimum: -61.2241\n", + "Time taken: 15.0529\n", + "Function value obtained: -356.9705\n", + "Current minimum: -438.8857\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0904\n", - "Function value obtained: -58.4696\n", - "Current minimum: -61.2241\n", + "Time taken: 15.9364\n", + "Function value obtained: -325.3113\n", + "Current minimum: -438.8857\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4114\n", - "Function value obtained: -54.6674\n", - "Current minimum: -61.2241\n", + "Time taken: 14.8991\n", + "Function value obtained: -309.6122\n", + "Current minimum: -438.8857\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2642\n", - "Function value obtained: -57.9765\n", - "Current minimum: -61.2241\n", + "Time taken: 14.8804\n", + "Function value obtained: -293.3637\n", + "Current minimum: -438.8857\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4049\n", - "Function value obtained: -60.4507\n", - "Current minimum: -61.2241\n", + "Time taken: 15.0928\n", + "Function value obtained: -255.8187\n", + "Current minimum: -438.8857\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3021\n", - "Function value obtained: -59.0770\n", - "Current minimum: -61.2241\n", + "Time taken: 14.9054\n", + "Function value obtained: -87.3464\n", + "Current minimum: -438.8857\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3457\n", - "Function value obtained: -58.7794\n", - "Current minimum: -61.2241\n", + "Time taken: 15.1169\n", + "Function value obtained: -156.4470\n", + "Current minimum: -438.8857\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4422\n", - "Function value obtained: -53.8311\n", - "Current minimum: -61.2241\n", + "Time taken: 15.0417\n", + "Function value obtained: -202.2864\n", + "Current minimum: -438.8857\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9687\n", - "Function value obtained: -59.6819\n", - "Current minimum: -61.2241\n", + "Time taken: 15.2709\n", + "Function value obtained: -205.7233\n", + "Current minimum: -438.8857\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0262\n", - "Function value obtained: -56.7366\n", - "Current minimum: -61.2241\n", + "Time taken: 15.3404\n", + "Function value obtained: -385.5189\n", + "Current minimum: -438.8857\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9646\n", - "Function value obtained: -60.7872\n", - "Current minimum: -61.2241\n", + "Time taken: 15.1236\n", + "Function value obtained: -323.0134\n", + "Current minimum: -438.8857\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7902\n", - "Function value obtained: -59.9935\n", - "Current minimum: -61.2241\n", + "Time taken: 15.1110\n", + "Function value obtained: -0.0000\n", + "Current minimum: -438.8857\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8926\n", - "Function value obtained: -59.4059\n", - "Current minimum: -61.2241\n", + "Time taken: 15.9513\n", + "Function value obtained: -330.9457\n", + "Current minimum: -438.8857\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2833\n", - "Function value obtained: -56.6924\n", - "Current minimum: -61.2241\n", + "Time taken: 15.6098\n", + "Function value obtained: -321.6410\n", + "Current minimum: -438.8857\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8233\n", - "Function value obtained: -57.3394\n", - "Current minimum: -61.2241\n", + "Time taken: 16.0473\n", + "Function value obtained: -416.8465\n", + "Current minimum: -438.8857\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6947\n", - "Function value obtained: -58.3537\n", - "Current minimum: -61.2241\n", + "Time taken: 15.0474\n", + "Function value obtained: -213.8130\n", + "Current minimum: -438.8857\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0941\n", - "Function value obtained: -29.8357\n", - "Current minimum: -61.2241\n", + "Time taken: 15.0529\n", + "Function value obtained: -215.6033\n", + "Current minimum: -438.8857\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8063\n", - "Function value obtained: -56.4859\n", - "Current minimum: -61.2241\n", + "Time taken: 15.2426\n", + "Function value obtained: -283.9917\n", + "Current minimum: -438.8857\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5943\n", - "Function value obtained: -59.6260\n", - "Current minimum: -61.2241\n", + "Time taken: 15.0787\n", + "Function value obtained: -409.1817\n", + "Current minimum: -438.8857\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7488\n", - "Function value obtained: -56.2995\n", - "Current minimum: -61.2241\n", + "Time taken: 15.2355\n", + "Function value obtained: -271.4230\n", + "Current minimum: -438.8857\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6401\n", - "Function value obtained: -57.2068\n", - "Current minimum: -61.2241\n", + "Time taken: 15.2466\n", + "Function value obtained: -384.4810\n", + "Current minimum: -438.8857\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8762\n", - "Function value obtained: -60.4108\n", - "Current minimum: -61.2241\n", + "Time taken: 15.5393\n", + "Function value obtained: -347.7256\n", + "Current minimum: -438.8857\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9816\n", - "Function value obtained: -36.1305\n", - "Current minimum: -61.2241\n", + "Time taken: 15.3565\n", + "Function value obtained: -364.3562\n", + "Current minimum: -438.8857\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7513\n", - "Function value obtained: -58.2616\n", - "Current minimum: -61.2241\n", + "Time taken: 15.6342\n", + "Function value obtained: -286.7312\n", + "Current minimum: -438.8857\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2219\n", - "Function value obtained: -11.1168\n", - "Current minimum: -61.2241\n", + "Time taken: 15.1193\n", + "Function value obtained: -227.2325\n", + "Current minimum: -438.8857\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6561\n", - "Function value obtained: -8.8193\n", - "Current minimum: -61.2241\n", + "Time taken: 15.5973\n", + "Function value obtained: -170.8995\n", + "Current minimum: -438.8857\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7967\n", - "Function value obtained: -57.2464\n", - "Current minimum: -61.2241\n", + "Time taken: 15.9054\n", + "Function value obtained: -189.1649\n", + "Current minimum: -438.8857\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8169\n", - "Function value obtained: -58.0635\n", - "Current minimum: -61.2241\n", + "Time taken: 15.3176\n", + "Function value obtained: -0.0000\n", + "Current minimum: -438.8857\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9140\n", - "Function value obtained: -34.6101\n", - "Current minimum: -61.2241\n", + "Time taken: 15.2464\n", + "Function value obtained: -216.1407\n", + "Current minimum: -438.8857\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7391\n", - "Function value obtained: -58.6780\n", - "Current minimum: -61.2241\n", + "Time taken: 16.0330\n", + "Function value obtained: -0.0000\n", + "Current minimum: -438.8857\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0784\n", - "Function value obtained: -1.1756\n", - "Current minimum: -61.2241\n", + "Time taken: 15.2751\n", + "Function value obtained: -8.5129\n", + "Current minimum: -438.8857\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4384\n", - "Function value obtained: -53.3736\n", - "Current minimum: -61.2241\n", + "Time taken: 15.2582\n", + "Function value obtained: -185.1771\n", + "Current minimum: -438.8857\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9011\n", - "Function value obtained: -59.1350\n", - "Current minimum: -61.2241\n", + "Time taken: 15.1405\n", + "Function value obtained: -189.8003\n", + "Current minimum: -438.8857\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9555\n", - "Function value obtained: -5.7642\n", - "Current minimum: -61.2241\n", + "Time taken: 15.3087\n", + "Function value obtained: -244.8359\n", + "Current minimum: -438.8857\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9570\n", - "Function value obtained: -63.2641\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7031\n", + "Function value obtained: -173.0455\n", + "Current minimum: -438.8857\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6990\n", - "Function value obtained: -59.0446\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8906\n", + "Function value obtained: -218.5830\n", + "Current minimum: -438.8857\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0384\n", - "Function value obtained: -54.2800\n", - "Current minimum: -63.2641\n", + "Time taken: 15.5129\n", + "Function value obtained: -73.5653\n", + "Current minimum: -438.8857\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0668\n", - "Function value obtained: -48.0005\n", - "Current minimum: -63.2641\n", + "Time taken: 15.9228\n", + "Function value obtained: -180.4744\n", + "Current minimum: -438.8857\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6050\n", - "Function value obtained: -46.1320\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7201\n", + "Function value obtained: -376.6617\n", + "Current minimum: -438.8857\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7099\n", - "Function value obtained: -42.8036\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7538\n", + "Function value obtained: -190.3690\n", + "Current minimum: -438.8857\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1557\n", - "Function value obtained: -60.5838\n", - "Current minimum: -63.2641\n", + "Time taken: 15.5452\n", + "Function value obtained: -274.7172\n", + "Current minimum: -438.8857\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1032\n", - "Function value obtained: -58.7568\n", - "Current minimum: -63.2641\n", + "Time taken: 15.1527\n", + "Function value obtained: -0.0000\n", + "Current minimum: -438.8857\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1654\n", - "Function value obtained: -37.6594\n", - "Current minimum: -63.2641\n", + "Time taken: 15.3026\n", + "Function value obtained: -298.3506\n", + "Current minimum: -438.8857\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1306\n", - "Function value obtained: -1.4300\n", - "Current minimum: -63.2641\n", + "Time taken: 15.2288\n", + "Function value obtained: -177.4097\n", + "Current minimum: -438.8857\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3577\n", - "Function value obtained: -54.5438\n", - "Current minimum: -63.2641\n", + "Time taken: 15.1948\n", + "Function value obtained: -273.6563\n", + "Current minimum: -438.8857\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8911\n", - "Function value obtained: -52.8896\n", - "Current minimum: -63.2641\n", + "Time taken: 15.5529\n", + "Function value obtained: -2.0565\n", + "Current minimum: -438.8857\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0966\n", - "Function value obtained: -49.3550\n", - "Current minimum: -63.2641\n", + "Time taken: 15.5062\n", + "Function value obtained: -166.2979\n", + "Current minimum: -438.8857\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0590\n", - "Function value obtained: -17.1363\n", - "Current minimum: -63.2641\n", + "Time taken: 15.4895\n", + "Function value obtained: -305.1273\n", + "Current minimum: -438.8857\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0767\n", - "Function value obtained: -58.9848\n", - "Current minimum: -63.2641\n", + "Time taken: 15.2092\n", + "Function value obtained: -217.1084\n", + "Current minimum: -438.8857\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0086\n", - "Function value obtained: -60.0785\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7433\n", + "Function value obtained: -270.1481\n", + "Current minimum: -438.8857\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1776\n", - "Function value obtained: -60.5850\n", - "Current minimum: -63.2641\n", + "Time taken: 15.2462\n", + "Function value obtained: -400.0950\n", + "Current minimum: -438.8857\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9081\n", - "Function value obtained: -56.5372\n", - "Current minimum: -63.2641\n", + "Time taken: 16.1135\n", + "Function value obtained: -199.2659\n", + "Current minimum: -438.8857\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9204\n", - "Function value obtained: -60.1805\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8707\n", + "Function value obtained: -310.8458\n", + "Current minimum: -438.8857\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9645\n", - "Function value obtained: -44.2104\n", - "Current minimum: -63.2641\n", + "Time taken: 15.3051\n", + "Function value obtained: -190.2455\n", + "Current minimum: -438.8857\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8429\n", - "Function value obtained: -61.1250\n", - "Current minimum: -63.2641\n", + "Time taken: 15.3690\n", + "Function value obtained: -238.7819\n", + "Current minimum: -438.8857\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7514\n", - "Function value obtained: -61.4826\n", - "Current minimum: -63.2641\n", + "Time taken: 15.2562\n", + "Function value obtained: -167.9023\n", + "Current minimum: -438.8857\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8626\n", - "Function value obtained: -59.5923\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7955\n", + "Function value obtained: -259.0012\n", + "Current minimum: -438.8857\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6434\n", - "Function value obtained: -16.3552\n", - "Current minimum: -63.2641\n", + "Time taken: 15.4389\n", + "Function value obtained: -261.2114\n", + "Current minimum: -438.8857\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7324\n", - "Function value obtained: -61.2381\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7072\n", + "Function value obtained: -252.6956\n", + "Current minimum: -438.8857\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0148\n", - "Function value obtained: -0.3426\n", - "Current minimum: -63.2641\n", + "Time taken: 15.3383\n", + "Function value obtained: -353.6387\n", + "Current minimum: -438.8857\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9483\n", - "Function value obtained: -60.3125\n", - "Current minimum: -63.2641\n", + "Time taken: 15.2957\n", + "Function value obtained: -327.7674\n", + "Current minimum: -438.8857\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8928\n", - "Function value obtained: -59.3450\n", - "Current minimum: -63.2641\n", + "Time taken: 15.3852\n", + "Function value obtained: -283.0269\n", + "Current minimum: -438.8857\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0769\n", - "Function value obtained: -58.1947\n", - "Current minimum: -63.2641\n", + "Time taken: 15.4744\n", + "Function value obtained: -297.2389\n", + "Current minimum: -438.8857\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9443\n", - "Function value obtained: -58.9000\n", - "Current minimum: -63.2641\n", + "Time taken: 15.3693\n", + "Function value obtained: -376.0855\n", + "Current minimum: -438.8857\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0979\n", - "Function value obtained: -61.7360\n", - "Current minimum: -63.2641\n", + "Time taken: 15.5661\n", + "Function value obtained: -193.4612\n", + "Current minimum: -438.8857\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9792\n", - "Function value obtained: -60.8098\n", - "Current minimum: -63.2641\n", + "Time taken: 15.4443\n", + "Function value obtained: -276.4440\n", + "Current minimum: -438.8857\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0095\n", - "Function value obtained: -1.2217\n", - "Current minimum: -63.2641\n", + "Time taken: 15.5257\n", + "Function value obtained: -387.9956\n", + "Current minimum: -438.8857\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9382\n", - "Function value obtained: -37.2280\n", - "Current minimum: -63.2641\n", + "Time taken: 15.4041\n", + "Function value obtained: -375.4694\n", + "Current minimum: -438.8857\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2376\n", - "Function value obtained: -52.7982\n", - "Current minimum: -63.2641\n", + "Time taken: 15.3485\n", + "Function value obtained: -435.6686\n", + "Current minimum: -438.8857\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0687\n", - "Function value obtained: -59.2149\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7586\n", + "Function value obtained: -354.5828\n", + "Current minimum: -438.8857\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8869\n", - "Function value obtained: -59.8836\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7085\n", + "Function value obtained: -219.5666\n", + "Current minimum: -438.8857\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0468\n", - "Function value obtained: -61.4606\n", - "Current minimum: -63.2641\n", + "Time taken: 15.6027\n", + "Function value obtained: -319.3203\n", + "Current minimum: -438.8857\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2475\n", - "Function value obtained: -58.3867\n", - "Current minimum: -63.2641\n", + "Time taken: 15.4429\n", + "Function value obtained: -163.7757\n", + "Current minimum: -438.8857\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8465\n", - "Function value obtained: -61.6604\n", - "Current minimum: -63.2641\n", + "Time taken: 16.0105\n", + "Function value obtained: -422.3829\n", + "Current minimum: -438.8857\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9396\n", - "Function value obtained: -60.2289\n", - "Current minimum: -63.2641\n", + "Time taken: 16.1356\n", + "Function value obtained: -226.5309\n", + "Current minimum: -438.8857\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8531\n", - "Function value obtained: -60.3995\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8464\n", + "Function value obtained: -454.6902\n", + "Current minimum: -454.6902\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9468\n", - "Function value obtained: -10.1870\n", - "Current minimum: -63.2641\n", + "Time taken: 15.5784\n", + "Function value obtained: -170.0078\n", + "Current minimum: -454.6902\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0244\n", - "Function value obtained: -61.7787\n", - "Current minimum: -63.2641\n", + "Time taken: 15.4668\n", + "Function value obtained: -223.6554\n", + "Current minimum: -454.6902\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9392\n", - "Function value obtained: -60.8102\n", - "Current minimum: -63.2641\n", + "Time taken: 15.6039\n", + "Function value obtained: -340.4397\n", + "Current minimum: -454.6902\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2316\n", - "Function value obtained: -59.9519\n", - "Current minimum: -63.2641\n", + "Time taken: 15.6884\n", + "Function value obtained: -278.3628\n", + "Current minimum: -454.6902\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2296\n", - "Function value obtained: -33.3384\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8655\n", + "Function value obtained: -283.0379\n", + "Current minimum: -454.6902\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1631\n", - "Function value obtained: -58.1543\n", - "Current minimum: -63.2641\n", + "Time taken: 15.6039\n", + "Function value obtained: -281.5878\n", + "Current minimum: -454.6902\n", "Iteration No: 101 started. Searching for the next optimal point.\n", "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9242\n", - "Function value obtained: -61.1208\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8485\n", + "Function value obtained: -170.6390\n", + "Current minimum: -454.6902\n", "Iteration No: 102 started. Searching for the next optimal point.\n", "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1032\n", - "Function value obtained: -57.1361\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8758\n", + "Function value obtained: -202.1503\n", + "Current minimum: -454.6902\n", "Iteration No: 103 started. Searching for the next optimal point.\n", "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1405\n", - "Function value obtained: -60.0831\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8478\n", + "Function value obtained: -294.7809\n", + "Current minimum: -454.6902\n", "Iteration No: 104 started. Searching for the next optimal point.\n", "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0604\n", - "Function value obtained: -56.6697\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7031\n", + "Function value obtained: -244.5716\n", + "Current minimum: -454.6902\n", "Iteration No: 105 started. Searching for the next optimal point.\n", "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9573\n", - "Function value obtained: -59.1310\n", - "Current minimum: -63.2641\n", + "Time taken: 16.0215\n", + "Function value obtained: -276.1295\n", + "Current minimum: -454.6902\n", "Iteration No: 106 started. Searching for the next optimal point.\n", "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2556\n", - "Function value obtained: -61.2202\n", - "Current minimum: -63.2641\n", + "Time taken: 15.9697\n", + "Function value obtained: -150.1348\n", + "Current minimum: -454.6902\n", "Iteration No: 107 started. Searching for the next optimal point.\n", "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1781\n", - "Function value obtained: -62.4387\n", - "Current minimum: -63.2641\n", + "Time taken: 16.1898\n", + "Function value obtained: -213.3973\n", + "Current minimum: -454.6902\n", "Iteration No: 108 started. Searching for the next optimal point.\n", "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9306\n", - "Function value obtained: -62.4808\n", - "Current minimum: -63.2641\n", + "Time taken: 16.0638\n", + "Function value obtained: -236.5961\n", + "Current minimum: -454.6902\n", "Iteration No: 109 started. Searching for the next optimal point.\n", "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0237\n", - "Function value obtained: -59.0782\n", - "Current minimum: -63.2641\n", + "Time taken: 15.9647\n", + "Function value obtained: -377.7661\n", + "Current minimum: -454.6902\n", "Iteration No: 110 started. Searching for the next optimal point.\n", "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0927\n", - "Function value obtained: -63.1178\n", - "Current minimum: -63.2641\n", + "Time taken: 16.2499\n", + "Function value obtained: -185.7516\n", + "Current minimum: -454.6902\n", "Iteration No: 111 started. Searching for the next optimal point.\n", "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2045\n", - "Function value obtained: -56.3383\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7978\n", + "Function value obtained: -311.9500\n", + "Current minimum: -454.6902\n", "Iteration No: 112 started. Searching for the next optimal point.\n", "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0539\n", - "Function value obtained: -58.0230\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7998\n", + "Function value obtained: -267.6341\n", + "Current minimum: -454.6902\n", "Iteration No: 113 started. Searching for the next optimal point.\n", "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9242\n", - "Function value obtained: -59.0969\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8251\n", + "Function value obtained: -288.9180\n", + "Current minimum: -454.6902\n", "Iteration No: 114 started. Searching for the next optimal point.\n", "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0840\n", - "Function value obtained: -55.8618\n", - "Current minimum: -63.2641\n", + "Time taken: 15.9563\n", + "Function value obtained: -297.4210\n", + "Current minimum: -454.6902\n", "Iteration No: 115 started. Searching for the next optimal point.\n", "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0085\n", - "Function value obtained: -3.7506\n", - "Current minimum: -63.2641\n", + "Time taken: 15.9263\n", + "Function value obtained: -269.9024\n", + "Current minimum: -454.6902\n", "Iteration No: 116 started. Searching for the next optimal point.\n", "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7568\n", - "Function value obtained: -58.8149\n", - "Current minimum: -63.2641\n", + "Time taken: 15.7647\n", + "Function value obtained: -332.9702\n", + "Current minimum: -454.6902\n", "Iteration No: 117 started. Searching for the next optimal point.\n", "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1419\n", - "Function value obtained: -59.5134\n", - "Current minimum: -63.2641\n", + "Time taken: 15.8393\n", + "Function value obtained: -287.5196\n", + "Current minimum: -454.6902\n", "Iteration No: 118 started. Searching for the next optimal point.\n", "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5886\n", - "Function value obtained: -14.0546\n", - "Current minimum: -63.2641\n", + "Time taken: 16.4803\n", + "Function value obtained: -365.5712\n", + "Current minimum: -454.6902\n", "Iteration No: 119 started. Searching for the next optimal point.\n", "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9430\n", - "Function value obtained: -63.5483\n", - "Current minimum: -63.5483\n", + "Time taken: 15.8271\n", + "Function value obtained: -289.8397\n", + "Current minimum: -454.6902\n", "Iteration No: 120 started. Searching for the next optimal point.\n", "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9123\n", - "Function value obtained: -57.5134\n", - "Current minimum: -63.5483\n", + "Time taken: 15.8000\n", + "Function value obtained: -428.0189\n", + "Current minimum: -454.6902\n", "Iteration No: 121 started. Searching for the next optimal point.\n", "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1774\n", - "Function value obtained: -56.2683\n", - "Current minimum: -63.5483\n", + "Time taken: 15.8749\n", + "Function value obtained: -325.3286\n", + "Current minimum: -454.6902\n", "Iteration No: 122 started. Searching for the next optimal point.\n", "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9709\n", - "Function value obtained: -62.7771\n", - "Current minimum: -63.5483\n", + "Time taken: 16.0965\n", + "Function value obtained: -262.0612\n", + "Current minimum: -454.6902\n", "Iteration No: 123 started. Searching for the next optimal point.\n", "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0477\n", - "Function value obtained: -59.3440\n", - "Current minimum: -63.5483\n", + "Time taken: 16.0577\n", + "Function value obtained: -261.3653\n", + "Current minimum: -454.6902\n", "Iteration No: 124 started. Searching for the next optimal point.\n", "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0835\n", - "Function value obtained: -57.2872\n", - "Current minimum: -63.5483\n", + "Time taken: 16.0354\n", + "Function value obtained: -247.9604\n", + "Current minimum: -454.6902\n", "Iteration No: 125 started. Searching for the next optimal point.\n", "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9397\n", - "Function value obtained: -59.0568\n", - "Current minimum: -63.5483\n", + "Time taken: 16.1425\n", + "Function value obtained: -294.8476\n", + "Current minimum: -454.6902\n", "Iteration No: 126 started. Searching for the next optimal point.\n", "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0965\n", - "Function value obtained: -53.5808\n", - "Current minimum: -63.5483\n", + "Time taken: 16.2390\n", + "Function value obtained: -364.9957\n", + "Current minimum: -454.6902\n", "Iteration No: 127 started. Searching for the next optimal point.\n", "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5572\n", - "Function value obtained: -29.7521\n", - "Current minimum: -63.5483\n", + "Time taken: 16.4888\n", + "Function value obtained: -344.0682\n", + "Current minimum: -454.6902\n", "Iteration No: 128 started. Searching for the next optimal point.\n", "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8641\n", - "Function value obtained: -60.5877\n", - "Current minimum: -63.5483\n", + "Time taken: 16.3073\n", + "Function value obtained: -390.7574\n", + "Current minimum: -454.6902\n", "Iteration No: 129 started. Searching for the next optimal point.\n", "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8012\n", - "Function value obtained: -2.0022\n", - "Current minimum: -63.5483\n", + "Time taken: 16.5701\n", + "Function value obtained: -196.1202\n", + "Current minimum: -454.6902\n", "Iteration No: 130 started. Searching for the next optimal point.\n", "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8347\n", - "Function value obtained: -59.8018\n", - "Current minimum: -63.5483\n", + "Time taken: 16.3848\n", + "Function value obtained: -341.5758\n", + "Current minimum: -454.6902\n", "Iteration No: 131 started. Searching for the next optimal point.\n", "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7619\n", - "Function value obtained: -57.8593\n", - "Current minimum: -63.5483\n", + "Time taken: 16.4364\n", + "Function value obtained: -393.6795\n", + "Current minimum: -454.6902\n", "Iteration No: 132 started. Searching for the next optimal point.\n", "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7387\n", - "Function value obtained: -17.2792\n", - "Current minimum: -63.5483\n", + "Time taken: 16.2929\n", + "Function value obtained: -269.6585\n", + "Current minimum: -454.6902\n", "Iteration No: 133 started. Searching for the next optimal point.\n", "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8196\n", - "Function value obtained: -59.2184\n", - "Current minimum: -63.5483\n", + "Time taken: 16.1430\n", + "Function value obtained: -385.4108\n", + "Current minimum: -454.6902\n", "Iteration No: 134 started. Searching for the next optimal point.\n", "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0700\n", - "Function value obtained: -40.3140\n", - "Current minimum: -63.5483\n", + "Time taken: 16.5185\n", + "Function value obtained: -408.1678\n", + "Current minimum: -454.6902\n", "Iteration No: 135 started. Searching for the next optimal point.\n", "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0434\n", - "Function value obtained: -59.4266\n", - "Current minimum: -63.5483\n", + "Time taken: 16.2813\n", + "Function value obtained: -328.6534\n", + "Current minimum: -454.6902\n", "Iteration No: 136 started. Searching for the next optimal point.\n", "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9794\n", - "Function value obtained: -57.9248\n", - "Current minimum: -63.5483\n", + "Time taken: 16.1611\n", + "Function value obtained: -348.8009\n", + "Current minimum: -454.6902\n", "Iteration No: 137 started. Searching for the next optimal point.\n", "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0414\n", - "Function value obtained: -60.8990\n", - "Current minimum: -63.5483\n", + "Time taken: 16.0663\n", + "Function value obtained: -390.7550\n", + "Current minimum: -454.6902\n", "Iteration No: 138 started. Searching for the next optimal point.\n", "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1688\n", - "Function value obtained: -59.4997\n", - "Current minimum: -63.5483\n", + "Time taken: 16.6901\n", + "Function value obtained: -231.0736\n", + "Current minimum: -454.6902\n", "Iteration No: 139 started. Searching for the next optimal point.\n", "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9458\n", - "Function value obtained: -60.7678\n", - "Current minimum: -63.5483\n", + "Time taken: 16.5807\n", + "Function value obtained: -356.8110\n", + "Current minimum: -454.6902\n", "Iteration No: 140 started. Searching for the next optimal point.\n", "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7562\n", - "Function value obtained: -13.9338\n", - "Current minimum: -63.5483\n", + "Time taken: 16.4868\n", + "Function value obtained: -195.4664\n", + "Current minimum: -454.6902\n", "Iteration No: 141 started. Searching for the next optimal point.\n", "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6614\n", - "Function value obtained: -61.7282\n", - "Current minimum: -63.5483\n", + "Time taken: 16.2288\n", + "Function value obtained: -273.3829\n", + "Current minimum: -454.6902\n", "Iteration No: 142 started. Searching for the next optimal point.\n", "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2516\n", - "Function value obtained: -59.9228\n", - "Current minimum: -63.5483\n", + "Time taken: 16.3722\n", + "Function value obtained: -231.4419\n", + "Current minimum: -454.6902\n", "Iteration No: 143 started. Searching for the next optimal point.\n", "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8742\n", - "Function value obtained: -61.0842\n", - "Current minimum: -63.5483\n", + "Time taken: 16.6915\n", + "Function value obtained: -343.5587\n", + "Current minimum: -454.6902\n", "Iteration No: 144 started. Searching for the next optimal point.\n", "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5508\n", - "Function value obtained: -64.2008\n", - "Current minimum: -64.2008\n", + "Time taken: 16.6498\n", + "Function value obtained: -318.5991\n", + "Current minimum: -454.6902\n", "Iteration No: 145 started. Searching for the next optimal point.\n", "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7071\n", - "Function value obtained: -36.1020\n", - "Current minimum: -64.2008\n", + "Time taken: 16.2139\n", + "Function value obtained: -265.6124\n", + "Current minimum: -454.6902\n", "Iteration No: 146 started. Searching for the next optimal point.\n", "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7122\n", - "Function value obtained: -10.8799\n", - "Current minimum: -64.2008\n", + "Time taken: 16.2855\n", + "Function value obtained: -284.7378\n", + "Current minimum: -454.6902\n", "Iteration No: 147 started. Searching for the next optimal point.\n", "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0097\n", - "Function value obtained: -58.2251\n", - "Current minimum: -64.2008\n", + "Time taken: 16.2652\n", + "Function value obtained: -282.3433\n", + "Current minimum: -454.6902\n", "Iteration No: 148 started. Searching for the next optimal point.\n", "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9632\n", - "Function value obtained: -58.9409\n", - "Current minimum: -64.2008\n", + "Time taken: 16.6722\n", + "Function value obtained: -250.6419\n", + "Current minimum: -454.6902\n", "Iteration No: 149 started. Searching for the next optimal point.\n", "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7202\n", - "Function value obtained: -57.3054\n", - "Current minimum: -64.2008\n", + "Time taken: 16.6253\n", + "Function value obtained: -254.4936\n", + "Current minimum: -454.6902\n", "Iteration No: 150 started. Searching for the next optimal point.\n", "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8710\n", - "Function value obtained: -57.7709\n", - "Current minimum: -64.2008\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8168\n", - "Function value obtained: -29.2006\n", - "Current minimum: -64.2008\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8796\n", - "Function value obtained: -59.0252\n", - "Current minimum: -64.2008\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9389\n", - "Function value obtained: -58.4027\n", - "Current minimum: -64.2008\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3315\n", - "Function value obtained: -56.9751\n", - "Current minimum: -64.2008\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0141\n", - "Function value obtained: -60.5391\n", - "Current minimum: -64.2008\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6762\n", - "Function value obtained: -17.1925\n", - "Current minimum: -64.2008\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5896\n", - "Function value obtained: -59.5120\n", - "Current minimum: -64.2008\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7429\n", - "Function value obtained: -58.2255\n", - "Current minimum: -64.2008\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8302\n", - "Function value obtained: -61.6330\n", - "Current minimum: -64.2008\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8606\n", - "Function value obtained: -59.2048\n", - "Current minimum: -64.2008\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6274\n", - "Function value obtained: -58.0595\n", - "Current minimum: -64.2008\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8166\n", - "Function value obtained: -59.6479\n", - "Current minimum: -64.2008\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9969\n", - "Function value obtained: -57.8566\n", - "Current minimum: -64.2008\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8045\n", - "Function value obtained: -1.8752\n", - "Current minimum: -64.2008\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7694\n", - "Function value obtained: -59.0620\n", - "Current minimum: -64.2008\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9555\n", - "Function value obtained: -54.0182\n", - "Current minimum: -64.2008\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1104\n", - "Function value obtained: -0.6622\n", - "Current minimum: -64.2008\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9222\n", - "Function value obtained: -59.8118\n", - "Current minimum: -64.2008\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9494\n", - "Function value obtained: -60.8177\n", - "Current minimum: -64.2008\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9698\n", - "Function value obtained: -58.0343\n", - "Current minimum: -64.2008\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0410\n", - "Function value obtained: -61.2714\n", - "Current minimum: -64.2008\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8312\n", - "Function value obtained: -57.4406\n", - "Current minimum: -64.2008\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0001\n", - "Function value obtained: -57.4561\n", - "Current minimum: -64.2008\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4823\n", - "Function value obtained: -57.1348\n", - "Current minimum: -64.2008\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8245\n", - "Function value obtained: -60.3032\n", - "Current minimum: -64.2008\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8974\n", - "Function value obtained: -59.6993\n", - "Current minimum: -64.2008\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1304\n", - "Function value obtained: -61.5890\n", - "Current minimum: -64.2008\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9479\n", - "Function value obtained: -60.0620\n", - "Current minimum: -64.2008\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9545\n", - "Function value obtained: -59.5877\n", - "Current minimum: -64.2008\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9353\n", - "Function value obtained: -60.5431\n", - "Current minimum: -64.2008\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8780\n", - "Function value obtained: -61.6031\n", - "Current minimum: -64.2008\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9784\n", - "Function value obtained: -58.4893\n", - "Current minimum: -64.2008\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0741\n", - "Function value obtained: -60.3522\n", - "Current minimum: -64.2008\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5137\n", - "Function value obtained: -20.9169\n", - "Current minimum: -64.2008\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0209\n", - "Function value obtained: -61.2214\n", - "Current minimum: -64.2008\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9224\n", - "Function value obtained: -1.2471\n", - "Current minimum: -64.2008\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0420\n", - "Function value obtained: -57.4958\n", - "Current minimum: -64.2008\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8017\n", - "Function value obtained: -57.4673\n", - "Current minimum: -64.2008\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2522\n", - "Function value obtained: -56.8791\n", - "Current minimum: -64.2008\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0881\n", - "Function value obtained: -58.7399\n", - "Current minimum: -64.2008\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1866\n", - "Function value obtained: -58.8845\n", - "Current minimum: -64.2008\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2188\n", - "Function value obtained: -62.1379\n", - "Current minimum: -64.2008\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0670\n", - "Function value obtained: -55.4986\n", - "Current minimum: -64.2008\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1111\n", - "Function value obtained: -60.3700\n", - "Current minimum: -64.2008\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9044\n", - "Function value obtained: -59.8612\n", - "Current minimum: -64.2008\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6142\n", - "Function value obtained: -58.0485\n", - "Current minimum: -64.2008\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8016\n", - "Function value obtained: -59.1313\n", - "Current minimum: -64.2008\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9322\n", - "Function value obtained: -56.5354\n", - "Current minimum: -64.2008\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7632\n", - "Function value obtained: -54.4825\n", - "Current minimum: -64.2008\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8385\n", - "Function value obtained: -61.3839\n", - "Current minimum: -64.2008\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7961\n", - "Function value obtained: -60.7659\n", - "Current minimum: -64.2008\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8849\n", - "Function value obtained: -56.7409\n", - "Current minimum: -64.2008\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7678\n", - "Function value obtained: -61.5901\n", - "Current minimum: -64.2008\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5719\n", - "Function value obtained: -60.9054\n", - "Current minimum: -64.2008\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8776\n", - "Function value obtained: -61.2900\n", - "Current minimum: -64.2008\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1118\n", - "Function value obtained: -38.1511\n", - "Current minimum: -64.2008\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0551\n", - "Function value obtained: -61.4971\n", - "Current minimum: -64.2008\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6061\n", - "Function value obtained: -15.1437\n", - "Current minimum: -64.2008\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0596\n", - "Function value obtained: -28.1336\n", - "Current minimum: -64.2008\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1850\n", - "Function value obtained: -62.1882\n", - "Current minimum: -64.2008\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1008\n", - "Function value obtained: -0.2824\n", - "Current minimum: -64.2008\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7517\n", - "Function value obtained: -62.6524\n", - "Current minimum: -64.2008\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9294\n", - "Function value obtained: -61.4682\n", - "Current minimum: -64.2008\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7377\n", - "Function value obtained: -60.8087\n", - "Current minimum: -64.2008\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0554\n", - "Function value obtained: -57.9712\n", - "Current minimum: -64.2008\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1786\n", - "Function value obtained: -58.5466\n", - "Current minimum: -64.2008\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1126\n", - "Function value obtained: -60.9830\n", - "Current minimum: -64.2008\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8351\n", - "Function value obtained: -57.9373\n", - "Current minimum: -64.2008\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0871\n", - "Function value obtained: -59.9948\n", - "Current minimum: -64.2008\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0927\n", - "Function value obtained: -62.4448\n", - "Current minimum: -64.2008\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0312\n", - "Function value obtained: -57.0187\n", - "Current minimum: -64.2008\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5584\n", - "Function value obtained: -58.2656\n", - "Current minimum: -64.2008\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7703\n", - "Function value obtained: -56.9978\n", - "Current minimum: -64.2008\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1509\n", - "Function value obtained: -26.9557\n", - "Current minimum: -64.2008\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0236\n", - "Function value obtained: -56.4458\n", - "Current minimum: -64.2008\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8945\n", - "Function value obtained: -61.4464\n", - "Current minimum: -64.2008\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0286\n", - "Function value obtained: -57.8685\n", - "Current minimum: -64.2008\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0008\n", - "Function value obtained: -61.2237\n", - "Current minimum: -64.2008\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6668\n", - "Function value obtained: -63.5224\n", - "Current minimum: -64.2008\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7087\n", - "Function value obtained: -59.1868\n", - "Current minimum: -64.2008\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7601\n", - "Function value obtained: -61.0303\n", - "Current minimum: -64.2008\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8731\n", - "Function value obtained: -60.8470\n", - "Current minimum: -64.2008\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6529\n", - "Function value obtained: -58.5784\n", - "Current minimum: -64.2008\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9062\n", - "Function value obtained: -53.2886\n", - "Current minimum: -64.2008\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8628\n", - "Function value obtained: -58.1561\n", - "Current minimum: -64.2008\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5912\n", - "Function value obtained: -55.6552\n", - "Current minimum: -64.2008\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5698\n", - "Function value obtained: -59.9314\n", - "Current minimum: -64.2008\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7148\n", - "Function value obtained: -64.4987\n", - "Current minimum: -64.4987\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6921\n", - "Function value obtained: -59.4893\n", - "Current minimum: -64.4987\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0173\n", - "Function value obtained: -59.9125\n", - "Current minimum: -64.4987\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8361\n", - "Function value obtained: -58.5445\n", - "Current minimum: -64.4987\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6402\n", - "Function value obtained: -0.9727\n", - "Current minimum: -64.4987\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8184\n", - "Function value obtained: -61.4708\n", - "Current minimum: -64.4987\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7615\n", - "Function value obtained: -60.1181\n", - "Current minimum: -64.4987\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9373\n", - "Function value obtained: -59.8558\n", - "Current minimum: -64.4987\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5992\n", - "Function value obtained: -56.7192\n", - "Current minimum: -64.4987\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6040\n", - "Function value obtained: -13.5032\n", - "Current minimum: -64.4987\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8829\n", - "Function value obtained: -60.1221\n", - "Current minimum: -64.4987\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6852\n", - "Function value obtained: -59.2030\n", - "Current minimum: -64.4987\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8238\n", - "Function value obtained: -58.0980\n", - "Current minimum: -64.4987\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7425\n", - "Function value obtained: -59.4840\n", - "Current minimum: -64.4987\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7022\n", - "Function value obtained: -61.0340\n", - "Current minimum: -64.4987\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6093\n", - "Function value obtained: -60.6382\n", - "Current minimum: -64.4987\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5705\n", - "Function value obtained: -57.8769\n", - "Current minimum: -64.4987\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7033\n", - "Function value obtained: -17.1385\n", - "Current minimum: -64.4987\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1098\n", - "Function value obtained: -60.2005\n", - "Current minimum: -64.4987\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1275\n", - "Function value obtained: -60.1307\n", - "Current minimum: -64.4987\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9815\n", - "Function value obtained: -60.1234\n", - "Current minimum: -64.4987\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7756\n", - "Function value obtained: -62.3185\n", - "Current minimum: -64.4987\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7827\n", - "Function value obtained: -59.0053\n", - "Current minimum: -64.4987\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7853\n", - "Function value obtained: -62.5778\n", - "Current minimum: -64.4987\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8215\n", - "Function value obtained: -58.9497\n", - "Current minimum: -64.4987\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6667\n", - "Function value obtained: -58.1683\n", - "Current minimum: -64.4987\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6950\n", - "Function value obtained: -59.1692\n", - "Current minimum: -64.4987\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7617\n", - "Function value obtained: -62.0380\n", - "Current minimum: -64.4987\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5667\n", - "Function value obtained: -61.0297\n", - "Current minimum: -64.4987\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6791\n", - "Function value obtained: -61.0521\n", - "Current minimum: -64.4987\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9077\n", - "Function value obtained: -59.2455\n", - "Current minimum: -64.4987\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6756\n", - "Function value obtained: -60.9676\n", - "Current minimum: -64.4987\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7853\n", - "Function value obtained: -58.1950\n", - "Current minimum: -64.4987\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7149\n", - "Function value obtained: -60.5536\n", - "Current minimum: -64.4987\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8186\n", - "Function value obtained: -57.6726\n", - "Current minimum: -64.4987\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0593\n", - "Function value obtained: -61.1180\n", - "Current minimum: -64.4987\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9124\n", - "Function value obtained: -60.0623\n", - "Current minimum: -64.4987\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7973\n", - "Function value obtained: -59.1106\n", - "Current minimum: -64.4987\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9494\n", - "Function value obtained: -59.3443\n", - "Current minimum: -64.4987\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9723\n", - "Function value obtained: -60.1159\n", - "Current minimum: -64.4987\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8114\n", - "Function value obtained: -16.3106\n", - "Current minimum: -64.4987\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2002\n", - "Function value obtained: -20.0562\n", - "Current minimum: -64.4987\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0475\n", - "Function value obtained: -61.8692\n", - "Current minimum: -64.4987\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9324\n", - "Function value obtained: -63.4091\n", - "Current minimum: -64.4987\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2368\n", - "Function value obtained: -55.3698\n", - "Current minimum: -64.4987\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9327\n", - "Function value obtained: -60.1140\n", - "Current minimum: -64.4987\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9030\n", - "Function value obtained: -57.4596\n", - "Current minimum: -64.4987\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0439\n", - "Function value obtained: -48.5878\n", - "Current minimum: -64.4987\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9241\n", - "Function value obtained: -28.7198\n", - "Current minimum: -64.4987\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9393\n", - "Function value obtained: -36.1231\n", - "Current minimum: -64.4987\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1274\n", - "Function value obtained: -33.9212\n", - "Current minimum: -64.4987\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9444\n", - "Function value obtained: -45.5313\n", - "Current minimum: -64.4987\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8929\n", - "Function value obtained: -32.9250\n", - "Current minimum: -64.4987\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1958\n", - "Function value obtained: -30.9456\n", - "Current minimum: -64.4987\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0201\n", - "Function value obtained: -30.1308\n", - "Current minimum: -64.4987\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9163\n", - "Function value obtained: -30.5858\n", - "Current minimum: -64.4987\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0399\n", - "Function value obtained: -28.2928\n", - "Current minimum: -64.4987\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0871\n", - "Function value obtained: -33.0234\n", - "Current minimum: -64.4987\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8832\n", - "Function value obtained: -46.2135\n", - "Current minimum: -64.4987\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0338\n", - "Function value obtained: -40.0399\n", - "Current minimum: -64.4987\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6943\n", - "Function value obtained: -36.3213\n", - "Current minimum: -64.4987\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1700\n", - "Function value obtained: -32.2373\n", - "Current minimum: -64.4987\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4859\n", - "Function value obtained: -6.7307\n", - "Current minimum: -64.4987\n", - "CPU times: user 59min 39s, sys: 6.3 s, total: 59min 45s\n", - "Wall time: 59min 35s\n" + "Time taken: 16.5687\n", + "Function value obtained: -209.1275\n", + "Current minimum: -454.6902\n", + "CPU times: user 48min 46s, sys: 1h 5min 38s, total: 1h 54min 25s\n", + "Wall time: 39min 22s\n" ] }, { "data": { "text/plain": [ - "(-64.49868469, [0.06184391109700299, 0.3296309210963565, 0.12990125226898555])" + "(-454.69024843, [0.37243753649830236, 0.42278680991848616, 0.4207223170684818])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "cr_gbrt = gp_minimize(cr_obj, cr_space, n_calls = 150, verbose=True, n_jobs=-1)\n", + "cr_gbrt.fun, cr_gbrt.x" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "dffeed5a-f975-4a6b-b91c-1d91e6c45140", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" ] }, - "execution_count": 12, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], + "source": [ + "plot_objective(cr_gbrt)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c3a775a4-4f27-419d-8cfb-3d4ec7d19fae", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3a7567f-e007-4931-9982-7c4de99c2e0a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "01d309be-d7c2-4af1-afbc-3b91c42c1a6c", + "metadata": {}, + "outputs": [], + "source": [ + "# -> (-62.08484130000001, [0.058590822346937174])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dabc6e34-7a25-4b2d-b8b1-294b59f60ca0", + "metadata": {}, + "outputs": [], + "source": [ + "path = \"../saved_agents/\"\n", + "fname = \"msy_gp.pkl\"\n", + "dump(msy_gp, path+fname)\n", + "\n", + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c5c2ec8-f61b-4dae-bc1b-ba70310a694b", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "%%time\n", + "msy_gbrt = gbrt_minimize(msy_fun, [(0.02, 0.15)], n_calls = 100, verbose=True, n_jobs=-1)\n", + "msy_gbrt.fun, msy_gbrt.x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07918bc7-cdb2-4966-b24a-ac53db2f49ec", + "metadata": {}, + "outputs": [], + "source": [ + "# -> (-57.168266599999995, [0.05811506272614242])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "05db66a7-a0f0-46e5-abd6-f57f8bb1bc59", + "metadata": {}, + "outputs": [], + "source": [ + "path = \"../saved_agents/\"\n", + "fname = \"msy_gbrt.pkl\"\n", + "dump(msy_gbrt, path+fname)\n", + "\n", + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "95f89094-fd18-433b-a3fc-1e45d3e2e1ad", + "metadata": {}, + "outputs": [], + "source": [ + "plot_objective(msy_gp)" + ] + }, + { + "cell_type": "markdown", + "id": "1206af08-4695-422c-95f0-25a9da2a4299", + "metadata": {}, + "source": [ + "## Const Escapement" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "05fc9be0-b0d0-4822-99ca-f0fcf2304ae4", + "metadata": {}, + "outputs": [], + "source": [ + "def esc_fun(x):\n", + " agent = ConstEsc(escapement=x[0])\n", + " mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100)\n", + " return -mean" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2aa1a6e7-dc64-410d-9850-db17810c0f03", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "esc_gp = gp_minimize(esc_fun, [(0.002, 0.25)], n_calls = 500, verbose=True, n_jobs=-1)\n", + "esc_gp.fun, esc_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9824bdb6-bacd-497d-bbfc-4ba711629e6a", + "metadata": {}, + "outputs": [], + "source": [ + "path = \"../saved_agents/\"\n", + "fname = \"esc_gp.pkl\"\n", + "dump(esc_gp, path+fname)\n", + "\n", + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a75dd9f6-f430-4458-a035-8188c6b255d5", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "esc_gbrt = gbrt_minimize(esc_fun, [(0.02, 0.15)], n_calls = 100, verbose=True, n_jobs=-1)\n", + "esc_gbrt.fun, esc_gbrt.x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "33725bba-434d-4c0e-84af-e89b151676f5", + "metadata": {}, + "outputs": [], + "source": [ + "plot_objective(esc_gp)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "abcac3a5-8136-4104-b8e0-abda7b53783e", + "metadata": {}, + "outputs": [], + "source": [ + "dump(esc_gbrt, \"../saved_agents/esc_gbrt.pkl\")" + ] + }, + { + "cell_type": "markdown", + "id": "1c89ae1d-bbeb-49b0-b6fb-6ab0a479d148", + "metadata": {}, + "source": [ + "## Precationary Rule (piecewise linear)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5b6f1a3-2d7a-4698-9555-1e10f4032bed", + "metadata": {}, + "outputs": [], + "source": [ + "from skopt.space import Real\n", + "from skopt.utils import use_named_args\n", + "\n", + "space = [Real(0.00001, 1, name='radius'),\n", + " Real(0.00001, np.pi/4.00001, name='theta'),\n", + " Real(0, 0.2, name='y2')]\n", + "\n", + "@use_named_args(space)\n", + "def g(**params):\n", + "\n", + " theta = params[\"theta\"]\n", + " radius = params[\"radius\"]\n", + " x1 = np.sin(theta) * radius\n", + " x2 = np.cos(theta) * radius\n", + " \n", + " assert x1 <= x2, (\"CautionaryRule error: x1 < x2, \" + str(x1) + \", \", str(x2) )\n", + "\n", + " agent = CautionaryRule(x1 = x1, x2 = x2, y2 = params[\"y2\"])\n", + " mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100)\n", + " return -mean \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cda44a0a-55ad-4953-b31e-bbb43d6a4e12", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "%%time\n", + "g_gp = gp_minimize(g, space, n_calls = 300, verbose=True, n_jobs=-1)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f7bf06c4-8931-4970-955b-1c2799082bf4", + "metadata": {}, + "outputs": [], + "source": [ + "path = \"../saved_agents/\"\n", + "fname = \"cr_gp.pkl\"\n", + "dump(g_gbrt, path+fname)\n", + "\n", + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c2b92ed3-d6f7-437e-be4f-796eac28a430", + "metadata": {}, + "outputs": [], + "source": [ + "# -> (-64.06042883, [0.041136645707627796, 0.7853961999069485, 0.12010362758045579])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07b3c0ff-7772-4b7b-926f-bf18cc3cd425", + "metadata": { + "scrolled": true + }, + "outputs": [], "source": [ "%%time\n", "g_gbrt = gbrt_minimize(g, space, n_calls = 300, verbose=True, n_jobs=-1)\n" @@ -9669,45 +1889,20 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "7f0be87a-0380-4ec3-98c1-c5c5879ec3f0", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(-64.06042883,\n", - " [0.041136645707627796, 0.7853961999069485, 0.12010362758045579],\n", - " -64.49868469,\n", - " [0.06184391109700299, 0.3296309210963565, 0.12990125226898555])" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "g_gp.fun, g_gp.x, g_gbrt.fun, g_gbrt.x" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "3735cd70-433a-406a-936b-a598fe700d0a", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(61.346940599999996, 14.639097133690518)" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "res = g_gp\n", "\n", @@ -9723,36 +1918,10 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "1e979533-468b-42a8-baba-3c6497924374", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[, ,\n", - " ],\n", - " [,\n", - " , ],\n", - " [, ,\n", - " ]], dtype=object)" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plot_objective(g_gp)" ] @@ -9775,7 +1944,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "d9427392-bac3-48fe-8332-0e4b01daa318", "metadata": {}, "outputs": [], @@ -9787,7 +1956,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "141e553d-92ad-4361-ab3e-cefe21b2421c", "metadata": {}, "outputs": [], @@ -9808,7 +1977,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "1f4c489c-e309-4ed3-beec-b9373a4aa630", "metadata": {}, "outputs": [], @@ -9818,7 +1987,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "f0a07389-1557-4eb9-a1e1-cc9be6435567", "metadata": {}, "outputs": [], @@ -9841,18 +2010,10 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "c15e31d5-d40e-495b-9c94-a2bc35efe403", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/stable_baselines3/common/evaluation.py:67: UserWarning: Evaluation environment is not wrapped with a ``Monitor`` wrapper. This may result in reporting modified episode lengths and rewards, if other wrappers happen to modify these. Consider wrapping environment first with ``Monitor`` wrapper.\n" - ] - } - ], + "outputs": [], "source": [ "msy_rews = evaluate_policy(\n", " model=msy_agent, \n", @@ -9864,7 +2025,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": null, "id": "e73e79a1-dfda-45d9-a4fe-dfb7cf0ec534", "metadata": {}, "outputs": [], @@ -9879,7 +2040,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "id": "6be205db-7b24-4205-a970-2a177b3e2814", "metadata": { "scrolled": true @@ -9896,7 +2057,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": null, "id": "4288e3c5-7dfa-4cb0-87f0-a2a838196d28", "metadata": {}, "outputs": [], @@ -9911,7 +2072,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "id": "a8e51a06-96b7-43c1-908b-8e0572c6d4f8", "metadata": {}, "outputs": [], @@ -9926,23 +2087,10 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": null, "id": "d1f82a1e-7f08-4234-9844-97b0983c8570", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "metadata": { - "image/png": { - "height": 480, - "width": 640 - } - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from plotnine import ggplot, aes, geom_density\n", "(\n", diff --git a/notebooks/popdyn_tests.ipynb b/notebooks/popdyn_tests.ipynb new file mode 100644 index 0000000..93eb285 --- /dev/null +++ b/notebooks/popdyn_tests.ipynb @@ -0,0 +1,343 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 36, + "id": "3638cfd4-177b-4b24-b6a4-8d61d74faf80", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "from typing import List, Text, Optional\n", + "\n", + "from rl4fisheries import Msy, ConstEsc, CautionaryRule, AsmEnv\n", + "from rl4fisheries.envs.asm_fns import get_r_devs" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "id": "1f80110e-9da0-4625-9e48-b6503e56adc4", + "metadata": {}, + "outputs": [], + "source": [ + "r_devs = get_r_devs(n_year=1000)\n", + "config = {\"s\": 0.97, \"r_devs\": r_devs}\n", + "env = AsmEnv(config = config)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "id": "eb58ebf3-882d-4944-9e19-2332f3133a18", + "metadata": {}, + "outputs": [], + "source": [ + "def simulate_ep(env, agent, other_vars: Optional[List[Text]] = []): \n", + " simulation = {\n", + " 't': [],\n", + " 'surv_b_obs': [],\n", + " 'mean_wt_obs': [],\n", + " 'act': [],\n", + " 'rew': [],\n", + " 'total_pop': [],\n", + " 'newborns': [],\n", + " 'non_random_newb': [],\n", + " **{var_name: [] for var_name in other_vars}\n", + " }\n", + " obs, _ = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, _ = agent.predict(obs)\n", + " new_obs, rew, term, trunc, info = env.step(act)\n", + " #\n", + " simulation['t'].append(t)\n", + " simulation['surv_b_obs'].append(\n", + " env.bound * (obs[0]+1)/2\n", + " )\n", + " simulation['mean_wt_obs'].append(\n", + " (\n", + " env.parameters[\"min_wt\"]\n", + " + (env.parameters[\"max_wt\"] - env.parameters[\"min_wt\"])\n", + " * (obs[1]+1)/2\n", + " )\n", + " )\n", + " simulation['act'].append(act[0])\n", + " simulation['rew'].append(rew)\n", + " simulation['total_pop'].append(np.sum(env.state))\n", + " simulation['newborns'].append(env.state[0])\n", + " simulation['non_random_newb'].append(\n", + " env.parameters[\"bha\"] * env.ssb / (1 + env.parameters[\"bhb\"] * env.ssb)\n", + " )\n", + " for var_name in other_vars:\n", + " simulation[var_name].append(getattr(env, var_name))\n", + " #\n", + " obs = new_obs\n", + " #\n", + " return simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "id": "a634dbf5-00af-44d8-b2d9-5ede8969e3e7", + "metadata": {}, + "outputs": [], + "source": [ + "trivp = Msy(env = env, mortality=0)\n", + "trivial_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), trivp, other_vars=['ssb']))" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "trivial_ep.plot(x='t', y = ['total_pop'], title='total population')\n", + "trivial_ep.plot(x='t', y = ['non_random_newb'], title='Unfished non-random newborns')\n", + "trivial_ep.plot(x='t', y = ['ssb'], title='Unfished ssb')\n", + "trivial_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "id": "26c2cf63-f70a-41aa-8ef1-e3f5b69fe5b2", + "metadata": {}, + "outputs": [], + "source": [ + "mid = Msy(env = env, mortality=0.05)\n", + "mid_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), mid, other_vars=['ssb']))" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "id": "62d7175e-1b05-4353-bd63-21971fb71d6a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mid_ep.plot(x='t', y = ['total_pop'], title='total population')\n", + "mid_ep.plot(x='t', y = ['non_random_newb'], title='Fished non-random newborns')\n", + "mid_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", + "mid_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" + ] + }, + { + "cell_type": "markdown", + "id": "977fb177-37ea-470e-a83a-400d9a9dcf43", + "metadata": {}, + "source": [ + "## Escapement" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "id": "3e9aba5e-466a-4feb-8bc5-8bf34da520a3", + "metadata": {}, + "outputs": [], + "source": [ + "escp = ConstEsc(env, escapement = 0.0138)\n", + "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), escp, other_vars=['ssb']))" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "ff08dfd1-c97c-407a-aec7-968d36ca6beb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "esc_ep.plot(x='t', y = ['total_pop'], title='total population')\n", + "esc_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns')\n", + "esc_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", + "esc_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cdc4b65b-8235-4008-accd-e31594e6e640", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 2ed9f7ea4b7c8501def155a715882156a7069900 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 4 Apr 2024 00:15:31 +0000 Subject: [PATCH 07/64] updated train script/sb3 train util --- hyperpars/ppo-asm.yml | 24 ++++++++++++++++-------- hyperpars/tqc-asm.yml | 26 +++++++++++++++++--------- scripts/train.py | 23 ++++++++++++++++------- src/rl4fisheries/utils/__init__.py | 2 +- src/rl4fisheries/utils/sb3.py | 5 +++-- 5 files changed, 53 insertions(+), 27 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 3541906..ae9e7c1 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,12 +1,20 @@ -# stable-baselines3 configuration - +# algo algo: "PPO" +total_timesteps: 20000000 +algo_config: + tensorboard_log: "../../logs" + policy: 'MlpPolicy' + use_sde: True + +# env env_id: "AsmEnv" +config: {'s': 0.97} n_envs: 12 -tensorboard: "../../../logs" -total_timesteps: 20000000 -config: {} -use_sde: True -id: "2obs" + +# io repo: "cboettig/rl-ecology" -save_path: "../saved_agents" \ No newline at end of file +save_path: "../saved_agents" + +# misc +id: "2obs" +additional_imports: [] \ No newline at end of file diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index 7335609..281ffe2 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -1,14 +1,22 @@ -# stable-baselines3 configuration - +# algo algo: "TQC" +total_timesteps: 20000000 +algo_config: + tensorboard_log: "../../logs" + policy: 'MlpPolicy' + learning_rate: 0.0001 + learning_starts: 1000 + use_sde: True + +# env env_id: "AsmEnv" +config: {'s': 0.97} n_envs: 12 -tensorboard: "../../../logs" -total_timesteps: 6000000 -config: {"learning_rate": 0.0001, - "learning_starts": 1000, - } -use_sde: True -id: "2obs" + +# io repo: "cboettig/rl-ecology" save_path: "../saved_agents" + +# misc +id: "2obs" +additional_imports: [] diff --git a/scripts/train.py b/scripts/train.py index 8d65928..9b40f1e 100644 --- a/scripts/train.py +++ b/scripts/train.py @@ -1,16 +1,25 @@ #!/opt/venv/bin/python + +# script args import argparse parser = argparse.ArgumentParser() parser.add_argument("-f", "--file", help="Path config file", type=str) parser.add_argument("-pb", "--progress_bar", help="Use progress bar for training", type=bool) -parser.add_argument("-rppo", "--recurrent-ppo", help="Hyperpar structure for recurrent ppo.", type=bool, default=False) args = parser.parse_args() +# imports import rl4fisheries +from rl4fisheries.utils import sb3_train + +import os + +# transform to absolute file path +abs_filepath = os.path.abspath(args.file) + +# change directory to script's directory (since io uses relative paths) +abspath = os.path.abspath(__file__) +dname = os.path.dirname(abspath) +os.chdir(dname) -if args.recurrent_ppo: - from rl4fisheries.utils import sb3_train_v2 - sb3_train_v2(args.file, progress_bar = args.progress_bar) -else: - from rl4fisheries.utils import sb3_train - sb3_train(args.file, progress_bar = args.progress_bar) \ No newline at end of file +# train +sb3_train(abs_filepath, progress_bar = args.progress_bar) diff --git a/src/rl4fisheries/utils/__init__.py b/src/rl4fisheries/utils/__init__.py index 3588868..30b32da 100644 --- a/src/rl4fisheries/utils/__init__.py +++ b/src/rl4fisheries/utils/__init__.py @@ -1 +1 @@ -from rl4fisheries.utils.sb3 import sb3_train, sb3_train_v2 \ No newline at end of file +from rl4fisheries.utils.sb3 import sb3_train \ No newline at end of file diff --git a/src/rl4fisheries/utils/sb3.py b/src/rl4fisheries/utils/sb3.py index 0a3a9d5..d07ef31 100644 --- a/src/rl4fisheries/utils/sb3.py +++ b/src/rl4fisheries/utils/sb3.py @@ -37,7 +37,8 @@ def algorithm(algo): } return algos[algo] -def sb3_train(config_file, **kwargs): +def sb3_train_old(config_file, **kwargs): + # deprecated with open(config_file, "r") as stream: options = yaml.safe_load(stream) options = {**options, **kwargs} @@ -73,7 +74,7 @@ def sb3_train(config_file, **kwargs): return save_id, options -def sb3_train_v2(config_file, **kwargs): +def sb3_train(config_file, **kwargs): with open(config_file, "r") as stream: options = yaml.safe_load(stream) options = {**options, **kwargs} From aa38bac7066b5305bec612cb00072dc52b2d132a Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 4 Apr 2024 00:18:12 +0000 Subject: [PATCH 08/64] added parallel rl train script --- scripts/train_rl_algos.sh | 13 +++++++++++++ 1 file changed, 13 insertions(+) create mode 100644 scripts/train_rl_algos.sh diff --git a/scripts/train_rl_algos.sh b/scripts/train_rl_algos.sh new file mode 100644 index 0000000..26ea56f --- /dev/null +++ b/scripts/train_rl_algos.sh @@ -0,0 +1,13 @@ +#!/bin/bash + +# move to script directory for normalized relative paths. +scriptdir="$(dirname "$0")" +cd "$scriptdir" + +# hf +python hf_login.py + +# train +python train.py -f ../hyperpars/ppo-asm.yml & +python train.py -f ../hyperpars/tqc-asm.yml & +python train.py -f ../hyperpars/rppo-asm.yml & \ No newline at end of file From daf878ee998f4a653d81763b336a8eb9f7a34c9e Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 4 Apr 2024 00:19:46 +0000 Subject: [PATCH 09/64] updated rppo yaml --- hyperpars/rppo-asm2o.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/hyperpars/rppo-asm2o.yml b/hyperpars/rppo-asm2o.yml index 4588d84..caa9f73 100644 --- a/hyperpars/rppo-asm2o.yml +++ b/hyperpars/rppo-asm2o.yml @@ -7,7 +7,7 @@ total_timesteps: 20000000 additional_imports: ["torch"] # env overall -env_id: "Asm2o-v0" +env_id: "AsmEnv" config: {} n_envs: 4 From 05098098fca9b458b34d8b716f46f5fe6e06156c Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 4 Apr 2024 00:20:03 +0000 Subject: [PATCH 10/64] updated yaml name --- hyperpars/{rppo-asm2o.yml => rppo-asm.yml} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename hyperpars/{rppo-asm2o.yml => rppo-asm.yml} (100%) diff --git a/hyperpars/rppo-asm2o.yml b/hyperpars/rppo-asm.yml similarity index 100% rename from hyperpars/rppo-asm2o.yml rename to hyperpars/rppo-asm.yml From 235b1be9b6a506a8d63315762d6032db7f12e597 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 4 Apr 2024 00:23:51 +0000 Subject: [PATCH 11/64] updated relative paths --- hyperpars/ppo-asm.yml | 2 +- hyperpars/tqc-asm.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index ae9e7c1..f1ac4fe 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -2,7 +2,7 @@ algo: "PPO" total_timesteps: 20000000 algo_config: - tensorboard_log: "../../logs" + tensorboard_log: "../../../logs" policy: 'MlpPolicy' use_sde: True diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index 281ffe2..7a22406 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -2,7 +2,7 @@ algo: "TQC" total_timesteps: 20000000 algo_config: - tensorboard_log: "../../logs" + tensorboard_log: "../../../logs" policy: 'MlpPolicy' learning_rate: 0.0001 learning_starts: 1000 From 7bc68e02b472ff6f2efafe357c7d623677ce20d4 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 4 Apr 2024 00:27:27 +0000 Subject: [PATCH 12/64] added installation to train bash script --- scripts/train_rl_algos.sh | 3 +++ 1 file changed, 3 insertions(+) diff --git a/scripts/train_rl_algos.sh b/scripts/train_rl_algos.sh index 26ea56f..85e9c37 100644 --- a/scripts/train_rl_algos.sh +++ b/scripts/train_rl_algos.sh @@ -4,6 +4,9 @@ scriptdir="$(dirname "$0")" cd "$scriptdir" +# just for good measure, install +pip install -e .. + # hf python hf_login.py From 29b7e8b0a01ef236a94003fc924bdb31417361ec Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 5 Apr 2024 21:37:10 +0000 Subject: [PATCH 13/64] wacky behavior in evaluate_policy: now use in-house eval_pol for optimization --- hyperpars/ppo-asm.yml | 2 +- notebooks/explore-optima.ipynb | 726 ++++- notebooks/optimal-fixed-policy.ipynb | 4000 ++++++++++++++++---------- 3 files changed, 3084 insertions(+), 1644 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index f1ac4fe..3a5399a 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,6 +1,6 @@ # algo algo: "PPO" -total_timesteps: 20000000 +total_timesteps: 1000000 algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' diff --git a/notebooks/explore-optima.ipynb b/notebooks/explore-optima.ipynb index 0276796..32b2a01 100644 --- a/notebooks/explore-optima.ipynb +++ b/notebooks/explore-optima.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 3, "id": "b742c702-256e-401c-91ff-1e4c4de11a7a", "metadata": {}, "outputs": [], @@ -49,7 +49,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 4, "id": "c30b9a3d-56f1-4590-8700-7c7e3c5a9e40", "metadata": {}, "outputs": [], @@ -59,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 5, "id": "6217b714-31a1-4f71-b754-1b4f5b46d0c8", "metadata": {}, "outputs": [], @@ -86,7 +86,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 53, "id": "654e8451-ab1a-475b-b6c4-aaf7d2de8d14", "metadata": {}, "outputs": [], @@ -214,6 +214,89 @@ ")" ] }, + { + "cell_type": "markdown", + "id": "81cea6d4-8609-490d-9d45-47b4f86b8bb9", + "metadata": {}, + "source": [ + "## PPO policy" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "bf66383b-022d-4734-91a9-f315ca04d029", + "metadata": {}, + "outputs": [], + "source": [ + "from stable_baselines3 import PPO\n", + "ppoAgent = PPO.load(\"../saved_agents/PPO-AsmEnv-2obs-1M.zip\")\n", + "ppoAgent_2 = PPO.load(\"../saved_agents/PPO-AsmEnv-2obs-1M-v2.zip\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "65e9ae66-ef84-4504-9e1d-1ad244bf38c6", + "metadata": {}, + "outputs": [], + "source": [ + "def GaussianProcessPolicy(policy_df, length_scale=10, noise_level=0.1):\n", + " \"\"\"\n", + " policy_df.columns = [X, Y, Z, act_x, act_y]\n", + " -> action (act_x, act_y) taken at point (X, Y, Z)\n", + " \"\"\"\n", + " predictors = policy_df[[\"X\", \"Y\", \"Z\"]].to_numpy()\n", + " targets = policy_df[[\"act_x\", \"act_y\"]].to_numpy()\n", + " kernel = (\n", + " 1.0 * RBF(length_scale = length_scale) \n", + " + WhiteKernel(noise_level=noise_level)\n", + " )\n", + " print(\"Fitting Gaussian Process...\")\n", + " gpp = (\n", + " GaussianProcessRegressor(kernel=kernel, random_state=0)\n", + " .fit(predictors, targets)\n", + " )\n", + " print(\"Done fitting Gaussian Process...\")\n", + " return gpp" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "cc6bb9d1-af5b-457c-9299-2777f782cd21", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Error: Unexpected observation shape () for Box environment, please use (2,) or (n_env, 2) for the observation shape.", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[54], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m ppo_df \u001b[38;5;241m=\u001b[39m \u001b[43mget_policy_df\u001b[49m\u001b[43m(\u001b[49m\u001b[43mppoAgent\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m ppo_2_df \u001b[38;5;241m=\u001b[39m get_policy_df(ppoAgent_2)\n", + "Cell \u001b[0;32mIn[53], line 7\u001b[0m, in \u001b[0;36mget_policy_df\u001b[0;34m(policy_obj, minx, maxx, nx)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_policy_df\u001b[39m(policy_obj, minx\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, maxx\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, nx\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m100\u001b[39m):\n\u001b[1;32m 2\u001b[0m obs_list \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(minx, maxx, nx)\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pd\u001b[38;5;241m.\u001b[39mDataFrame(\n\u001b[1;32m 4\u001b[0m {\n\u001b[1;32m 5\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mobs\u001b[39m\u001b[38;5;124m'\u001b[39m: obs_list,\n\u001b[1;32m 6\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpop\u001b[39m\u001b[38;5;124m'\u001b[39m: (obs_list \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m)\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpol\u001b[39m\u001b[38;5;124m'\u001b[39m: [policy_obj\u001b[38;5;241m.\u001b[39mpredict(obs)[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m obs \u001b[38;5;129;01min\u001b[39;00m obs_list]\n\u001b[1;32m 8\u001b[0m }\n\u001b[1;32m 9\u001b[0m )\n", + "Cell \u001b[0;32mIn[53], line 7\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_policy_df\u001b[39m(policy_obj, minx\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, maxx\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, nx\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m100\u001b[39m):\n\u001b[1;32m 2\u001b[0m obs_list \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(minx, maxx, nx)\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pd\u001b[38;5;241m.\u001b[39mDataFrame(\n\u001b[1;32m 4\u001b[0m {\n\u001b[1;32m 5\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mobs\u001b[39m\u001b[38;5;124m'\u001b[39m: obs_list,\n\u001b[1;32m 6\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpop\u001b[39m\u001b[38;5;124m'\u001b[39m: (obs_list \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m)\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpol\u001b[39m\u001b[38;5;124m'\u001b[39m: [\u001b[43mpolicy_obj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobs\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m obs \u001b[38;5;129;01min\u001b[39;00m obs_list]\n\u001b[1;32m 8\u001b[0m }\n\u001b[1;32m 9\u001b[0m )\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/stable_baselines3/common/base_class.py:553\u001b[0m, in \u001b[0;36mBaseAlgorithm.predict\u001b[0;34m(self, observation, state, episode_start, deterministic)\u001b[0m\n\u001b[1;32m 533\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpredict\u001b[39m(\n\u001b[1;32m 534\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 535\u001b[0m observation: Union[np\u001b[38;5;241m.\u001b[39mndarray, Dict[\u001b[38;5;28mstr\u001b[39m, np\u001b[38;5;241m.\u001b[39mndarray]],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 538\u001b[0m deterministic: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m 539\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[np\u001b[38;5;241m.\u001b[39mndarray, Optional[Tuple[np\u001b[38;5;241m.\u001b[39mndarray, \u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m]]]:\n\u001b[1;32m 540\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 541\u001b[0m \u001b[38;5;124;03m Get the policy action from an observation (and optional hidden state).\u001b[39;00m\n\u001b[1;32m 542\u001b[0m \u001b[38;5;124;03m Includes sugar-coating to handle different observations (e.g. normalizing images).\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 551\u001b[0m \u001b[38;5;124;03m (used in recurrent policies)\u001b[39;00m\n\u001b[1;32m 552\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 553\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpolicy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobservation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepisode_start\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdeterministic\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/stable_baselines3/common/policies.py:363\u001b[0m, in \u001b[0;36mBasePolicy.predict\u001b[0;34m(self, observation, state, episode_start, deterministic)\u001b[0m\n\u001b[1;32m 354\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(observation, \u001b[38;5;28mtuple\u001b[39m) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(observation) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(observation[\u001b[38;5;241m1\u001b[39m], \u001b[38;5;28mdict\u001b[39m):\n\u001b[1;32m 355\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 356\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mYou have passed a tuple to the predict() function instead of a Numpy array or a Dict. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 357\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mYou are probably mixing Gym API with SB3 VecEnv API: `obs, info = env.reset()` (Gym) \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 360\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mand documentation for more information: https://stable-baselines3.readthedocs.io/en/master/guide/vec_envs.html#vecenv-api-vs-gym-api\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 361\u001b[0m )\n\u001b[0;32m--> 363\u001b[0m obs_tensor, vectorized_env \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mobs_to_tensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobservation\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 365\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m th\u001b[38;5;241m.\u001b[39mno_grad():\n\u001b[1;32m 366\u001b[0m actions \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_predict(obs_tensor, deterministic\u001b[38;5;241m=\u001b[39mdeterministic)\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/stable_baselines3/common/policies.py:270\u001b[0m, in \u001b[0;36mBaseModel.obs_to_tensor\u001b[0;34m(self, observation)\u001b[0m\n\u001b[1;32m 266\u001b[0m observation \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(observation)\n\u001b[1;32m 268\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(observation, \u001b[38;5;28mdict\u001b[39m):\n\u001b[1;32m 269\u001b[0m \u001b[38;5;66;03m# Dict obs need to be handled separately\u001b[39;00m\n\u001b[0;32m--> 270\u001b[0m vectorized_env \u001b[38;5;241m=\u001b[39m \u001b[43mis_vectorized_observation\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobservation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mobservation_space\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 271\u001b[0m \u001b[38;5;66;03m# Add batch dimension if needed\u001b[39;00m\n\u001b[1;32m 272\u001b[0m observation \u001b[38;5;241m=\u001b[39m observation\u001b[38;5;241m.\u001b[39mreshape((\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mobservation_space\u001b[38;5;241m.\u001b[39mshape)) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/stable_baselines3/common/utils.py:399\u001b[0m, in \u001b[0;36mis_vectorized_observation\u001b[0;34m(observation, observation_space)\u001b[0m\n\u001b[1;32m 397\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m space_type, is_vec_obs_func \u001b[38;5;129;01min\u001b[39;00m is_vec_obs_func_dict\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m 398\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(observation_space, space_type):\n\u001b[0;32m--> 399\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mis_vec_obs_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobservation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mobservation_space\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore[operator]\u001b[39;00m\n\u001b[1;32m 400\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 401\u001b[0m \u001b[38;5;66;03m# for-else happens if no break is called\u001b[39;00m\n\u001b[1;32m 402\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError: Cannot determine if the observation is vectorized with the space type \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mobservation_space\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/stable_baselines3/common/utils.py:266\u001b[0m, in \u001b[0;36mis_vectorized_box_observation\u001b[0;34m(observation, observation_space)\u001b[0m\n\u001b[1;32m 264\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 265\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 266\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 267\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError: Unexpected observation shape \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mobservation\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 268\u001b[0m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBox environment, please use \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mobservation_space\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 269\u001b[0m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mor (n_env, \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m) for the observation shape.\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mmap\u001b[39m(\u001b[38;5;28mstr\u001b[39m, observation_space\u001b[38;5;241m.\u001b[39mshape)))\n\u001b[1;32m 270\u001b[0m )\n", + "\u001b[0;31mValueError\u001b[0m: Error: Unexpected observation shape () for Box environment, please use (2,) or (n_env, 2) for the observation shape." + ] + } + ], + "source": [ + "ppo_df = get_policy_df(ppoAgent)\n", + "ppo_2_df = get_policy_df(ppoAgent_2)" + ] + }, { "cell_type": "markdown", "id": "694a5d2e-193a-4379-87fc-4038b087cc1e", @@ -224,24 +307,40 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 73, "id": "e906b630-26e8-48c8-ac70-600b072ac1dd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "done with CR.\n", + "done with Esc\n", + "done with MSY\n" + ] + } + ], "source": [ - "cr_gp_rews = evaluate_policy(cr_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", - "cr_gbrt_rews = evaluate_policy(cr_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", + "cr_gp_rews = evaluate_policy(cr_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]\n", + "cr_gbrt_rews = evaluate_policy(cr_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]\n", + "print(\"done with CR.\")\n", + "\n", + "esc_gp_rews = evaluate_policy(esc_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]\n", + "esc_gbrt_rews = evaluate_policy(esc_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]\n", + "print(\"done with Esc\")\n", "\n", - "esc_gp_rews = evaluate_policy(esc_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", - "esc_gbrt_rews = evaluate_policy(esc_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", + "msy_gp_rews = evaluate_policy(msy_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]\n", + "msy_gbrt_rews = evaluate_policy(msy_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]\n", + "print(\"done with MSY\")\n", "\n", - "msy_gp_rews = evaluate_policy(msy_gp_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]\n", - "msy_gbrt_rews = evaluate_policy(msy_gbrt_pol, Monitor(env), return_episode_rewards=True, n_eval_episodes=100)[0]" + "ppo_rews = evaluate_policy(ppoAgent, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]\n", + "ppo_rews_2 = evaluate_policy(ppoAgent_2, Monitor(env), return_episode_rewards=True, n_eval_episodes=300)[0]" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 65, "id": "0dc1d602-2283-4152-be8d-0594e226cb92", "metadata": {}, "outputs": [], @@ -253,12 +352,14 @@ " 'Escapement_gbrt': esc_gbrt_rews,\n", " 'MSY_gp': msy_gp_rews,\n", " 'MSY_gbrt': msy_gbrt_rews,\n", + " 'PPO': ppo_rews,\n", + " '2_PPO': ppo_rews_2,\n", "}).melt()" ] }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 66, "id": "342e8036-3bc5-4c0d-b590-4f4f982d1425", "metadata": {}, "outputs": [ @@ -292,31 +393,31 @@ " \n", " 0\n", " CautionaryRule_gp\n", - " 231.675426\n", + " 304.364097\n", " gp\n", " \n", " \n", " 1\n", " CautionaryRule_gp\n", - " 230.102295\n", + " 306.663687\n", " gp\n", " \n", " \n", " 2\n", " CautionaryRule_gp\n", - " 228.520022\n", + " 302.857712\n", " gp\n", " \n", " \n", " 3\n", " CautionaryRule_gp\n", - " 230.469030\n", + " 301.917373\n", " gp\n", " \n", " \n", " 4\n", " CautionaryRule_gp\n", - " 231.865324\n", + " 301.645522\n", " gp\n", " \n", " \n", @@ -325,26 +426,27 @@ ], "text/plain": [ " variable value optimization\n", - "0 CautionaryRule_gp 231.675426 gp\n", - "1 CautionaryRule_gp 230.102295 gp\n", - "2 CautionaryRule_gp 228.520022 gp\n", - "3 CautionaryRule_gp 230.469030 gp\n", - "4 CautionaryRule_gp 231.865324 gp" + "0 CautionaryRule_gp 304.364097 gp\n", + "1 CautionaryRule_gp 306.663687 gp\n", + "2 CautionaryRule_gp 302.857712 gp\n", + "3 CautionaryRule_gp 301.917373 gp\n", + "4 CautionaryRule_gp 301.645522 gp" ] }, - "execution_count": 45, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "rew_df['optimization'] = rew_df.apply(lambda row: 'gp' if row.variable[-2:]=='gp' else 'gbrt', axis=1)\n", + "name_transforms = {'gp': 'gp', 'rt':'gbrt', 'PO':'ppo'}\n", + "rew_df['optimization'] = rew_df.apply(lambda row: name_transforms[row.variable[-2:]], axis=1)\n", "rew_df.head()" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 67, "id": "88b650c5-f168-4d1d-bd4a-5ff01feb2718", "metadata": {}, "outputs": [], @@ -354,7 +456,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 68, "id": "27d3ea66-777a-4316-b34c-f9a482d1a6ff", "metadata": {}, "outputs": [ @@ -367,7 +469,7 @@ }, { "data": { - "image/png": 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" }, "metadata": { "image/png": { @@ -383,18 +485,18 @@ "(
,)" ] }, - "execution_count": 48, + "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ggplot(rew_df[rew_df[\"optimization\"] == 'gp'], aes(x='value', fill='variable')) + geom_density(alpha=0.5)," + "ggplot(rew_df[(rew_df[\"optimization\"] == 'gp') | (rew_df[\"optimization\"] == 'ppo')], aes(x='value', fill='variable')) + geom_density(alpha=0.5)," ] }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 69, "id": "edbdf404-5570-4f48-bf6a-9ddda9103b5b", "metadata": {}, "outputs": [ @@ -407,7 +509,47 @@ }, { "data": { - "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,)" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ggplot(rew_df[(rew_df[\"optimization\"] == 'gbrt') | (rew_df[\"optimization\"] == 'ppo')], aes(x='value', fill='variable')) + geom_density(alpha=0.5)," + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "id": "a8510e8d-74a9-4c17-b223-da7c181cdeef", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:779: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" }, "metadata": { "image/png": { @@ -423,13 +565,68 @@ "(
,)" ] }, - "execution_count": 49, + "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ggplot(rew_df[rew_df[\"optimization\"] == 'gbrt'], aes(x='value', fill='variable')) + geom_density(alpha=0.5)," + "ggplot(\n", + " rew_df[\n", + " (rew_df[\"variable\"] == \"2_PPO\")\n", + " | (rew_df[\"variable\"] == \"CautionaryRule_gbrt\") \n", + " | (rew_df[\"variable\"] == \"PPO\")\n", + " ], \n", + " aes(x='value', fill='variable')\n", + ") + geom_density(alpha=0.5)," + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "4be8c14d-9259-441e-a1a7-04fd7e6b1f3d", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:779: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,)" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from plotnine import geom_jitter, geom_point\n", + "ggplot(\n", + " rew_df[\n", + " (rew_df[\"variable\"] == \"2_PPO\")\n", + " | (rew_df[\"variable\"] == \"CautionaryRule_gbrt\") \n", + " | (rew_df[\"variable\"] == \"PPO\")\n", + " ], \n", + " aes(x='variable', y='value', color='variable')\n", + ") + geom_point(alpha=0.7) + geom_jitter()," ] }, { @@ -442,7 +639,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 28, "id": "da1c6b86-95c0-47f5-b9ab-3813d37d7917", "metadata": {}, "outputs": [], @@ -494,7 +691,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 31, "id": "0b56fc05-b2ff-4f58-8bcb-ff64e37f93a7", "metadata": {}, "outputs": [], @@ -504,14 +701,16 @@ "r_devs = get_r_devs(n_year=1000)\n", "config = {'r_devs': r_devs, 's':0.97}\n", "\n", - "msy_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), msy_gp_pol, other_vars=['ssb']))\n", - "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), esc_gp_pol, other_vars=['ssb']))\n", - "cr_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), cr_gp_pol, other_vars=['ssb']))" + "msy_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), msy_gbrt_pol, other_vars=['ssb']))\n", + "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), esc_gbrt_pol, other_vars=['ssb']))\n", + "cr_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), cr_gbrt_pol, other_vars=['ssb']))\n", + "ppo_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), ppoAgent, other_vars=['ssb']))\n", + "ppo_2_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), ppoAgent_2, other_vars=['ssb']))" ] }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 32, "id": "912e8a5e-b8cf-4de0-a0fd-13713c033b2e", "metadata": {}, "outputs": [], @@ -520,6 +719,16 @@ "trivial_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), trivp, other_vars=['ssb']))" ] }, + { + "cell_type": "code", + "execution_count": 39, + "id": "e626a82e-eeb9-4186-b97f-145f8a87186d", + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, { "cell_type": "markdown", "id": "da58583c-9d6c-4d73-a968-af50d1e30598", @@ -536,23 +745,13 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 42, "id": "5d53d2d0-51a1-4347-9c1b-9ea696278486", "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "(,)" - ] - }, - "execution_count": 58, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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x48cxYcIELFy4EPv27cOyZcuwevVqnH/++QnvUy8GL0RERA7x+Xz47LPPcPnll2PcuHHo168ffvrTn2Lfvn3Izs4ObnfFFVfA7/eH9W0ZNWpU1Gttpk2bFmxWWrp0Kf773/+iW7duAIAzzzwTn332GQoKCjBw4EDcfffd+OUvf4k//elPpr5LamoqKisrcfvtt6Nfv374yU9+gjFjxuCxxx4ztV89fIrHZhqqqalBVlYWqqur0alTJ9HZISLylD/N3oiZK/cDAPZOu8bWtBobG1FcXIxzzjkHmZmZtqZFzoj3mxq5f7PmhYiIiFyFwQsRERG5CoMXIiIichXPBC9cmJGIiCg5eCZ4ccPCjHVNrfjt++vwxeZS0VkhInINj40rSWpW/ZaeCV7c4MWvduF/6w/hV/8sFJ0VSwUCCia8txZ/z98pOitE5CGpqSdmtW1ubhacE7JKQ0MDgOgZiI1y91SFLlNe0yg6C7ZYtrsCn244jE9xGL/9njOLchGR96WlpaFDhw44cuQI2rVrZ2pCNRJLURQ0NDSgvLwcnTt3DgamiWLwQqY1NPtFZ4GIPMjn86FHjx4oLi7Gvn37RGeHLNC5c2d0797d9H4YvDjIq622bI4mIrukp6ejb9++bDrygHbt2pmucWnD4MVB3u105tXvRUQySElJ4Qy7FIYNiBJSFAUbDlShsYXNMUQkr0U7juCq6Yuwbv8x0VmhJMPgxSINza2aNSt66yc+LDyA615chlteXWk+Yw7wbIUSURJr9Qdw2+ur8Nd521S3GftGAXaW1+HXHhtBSfJj8GKBg1XH0X/S57jjzfhzzOi9yc9aXQIAWLe/ymTOnMHYhch7Fu04giU7K/Dywt2a2za1BhzIEdFJDF4s8O/CAwBOXOxW8FmyF+dEBmWbDlajoPiomMwQkSWaDQQkp2aw+yQ5i2ecg/TWUPhcFr0oEd/s//6+FACw5k856HZqhogsEZFJRmpUT8mwZgQJkV6seXGQd0cbxfabd9fio69rpYjIu05hzQs5jMGLhHwuazhSi8kKio/iDx+udzYzRGQJI89ap6QzeCFnMXhxkO6ywF2xCzvsEiU5NhuR06QMXm644Qacdtpp+PGPfyw6K9bSeZd3WeySdM1hZK9pc7fhT7M3is4GGcBmI3KalMHLvffei3feeUd0NoRxW4ddIqu0+gOYsWg3Zq7cj5KjDaKzQzp1SGfNCzlLyuBl1KhR6Nixo+hsWC5yVI4at/V5IbJKIOQSafZz7hBZaAWSXiyz1u0/hmteWIKVeypFZ4VisDx4Wbx4Ma699lr07NkTPp8Ps2fPjtomLy8Pffr0QWZmJoYPH46CggKrsyElva0rbqt5YasRWSU0wHfZZeA5ob/FyKcW6N7WK255dSU2H6rBT19xx0znycby4KW+vh4DBw5EXl5ezPdnzZqF3NxcTJ48GWvXrsXAgQMxevRolJeXW50V13Jd8OLBgovECA2EfW67EJKYFx9gGltY8yczy3tZjRkzBmPGjFF9f/r06bjrrrswbtw4AMCMGTMwZ84cvPHGG5g4caLh9JqamtDU1BT8d01NjfFMO0R3zYvLnjm9WHCReO66CrzHyHXNIoCc5mifl+bmZhQWFiInJ+dkBlJSkJOTgxUrViS0z6lTpyIrKyv4X69evazKruXcWkPhDyh4eeFurOXKsWSBo/XNON4ce8X08JoXhzJEpvEBhpzmaPBSUVEBv9+P7OzssNezs7NRWloa/HdOTg5uuukmfPbZZzjrrLPiBjYPP/wwqqurg/+VlJTYln+nyFZof1RYgr/O24YbX1oe830WXKRXVUMzLv7LfAx8/IuY74f3edF3IdQ3tWL3kTpL8hfqYNVxfLimxNAaP15i7LJmIUDOknJw/pdffql724yMDGRkuGP9HLfe5HeUxb8xuPRrkQAbDlQDOLHo39H6ZnQ5JV11W71B/KhnFuJIbRNmj78Ug3p1tiCXJ1w1fREamv0orW7Eb7/X17L9epFbyzZyL0drXrp164bU1FSUlZWFvV5WVobu3bub2ndeXh769++PoUOHmtqPnfQvzChX1YtWwcRJ6kiv0DPl4r/Mx4YDVeHvJ3AqHak90eft882lGlsa0/B109aSXRWW7nfRjiP4/nOLUFRSZel+rWakFGIRQE5zNHhJT0/H4MGDkZ+fH3wtEAggPz8fI0aMMLXv8ePHY8uWLVi9erXZbAonV+ii3VeH5RbpFRnovrdqf/j7pvZt4sMOGvtGAXaU1eH211cJy8OMRbujjn0kI4fTrf35yL0sbzaqq6vDrl27gv8uLi5GUVERunTpgt69eyM3Nxdjx47FkCFDMGzYMDz//POor68Pjj7yMq/O80Kkl9YlEBrcGL0ObLuB2rTb2qZWe3asoeRoA6bN3QYA+Nnw3pbs0y2BI3mH5cHLmjVrcOWVVwb/nZubCwAYO3Ys3nrrLdx88804cuQIJk2ahNLSUgwaNAjz5s2L6sTrTXpn2JWLZsHEgks6Dc2t6CDjSr9aTZAhfxtuPuV5qEtto76gyUhzMA89Oc3y0m3UqFGaJ/2ECRMwYcIES9PNy8tDXl4e/P7YQzDdRLY+L1pYZSyX5bsq8LPXVuGukefgkWv6i85OmMhzJfJUDxsqbXjfZJSiKJaUNzLVvOQt2IUWfwD35fQTnZUw0j5QuJSUaxslwg19XvRPUicXrWBUpoKLgCfnbgUAvLqkWHBOokWeK1Hnjol5Xthx3DirDpksDzCNLX48/fl2PP/lzmBHbhn8c+U+9J/0OT5c4/6pPGThmeDFDeS4vI1jqxFZRXPkWgLzvLQJKMBv31+HJz/bmkjWTuYhIpOy3JitYsv3keQQ+UNW9mxqlacW/s+zNwEAHvhog+CceAeDFwlZ1Wo0Y9FufPeZhSivbTS1Hz7QuovMy0tEnkpxm40Mfo2Dx47jf+sP4ZXFexJ+6t56uAbfmZqPWavjj8TxCqsubVmKiNBzhuWWt3kmeHHFPC+6ryZrbj7T5m7Dnop6/O3LnZbsTw0LCbnI3GXKSNOO0a8R+r1X7qk0+OkT7v/XepTVNOGhf29M6PNuY1VTmyxNdjIH7vFUNTTjmc+3Y1e59TNFe5VnghdX9HnRuZ3VN58GlXVk9NKe50WOgotOkLn4NtQEabjPy8m/j9Y3x9126c6KmDeKFn9yLQXAmhc5/Gn2Jry4YBe+/9wi0VlxDXZ9lpDVN59mkwWy9gy7pnZPVpO46sXO2Zr1BtGbD1Xj519PELd32jXa+/Xw+R3vuxlaVVrCY+Smh6p1+6sAnOi3Rfp4pubFDURNUtdicmE5dth1F3lDF0DrbAmb58XgN9F7fW05VKMr/XivyW7LoRq8snh3zJqk0ONq1Q1elmPk1poXiZ83pMWaFwlZ3W5rtircTYUAyc1ILZ5dc9TF206WvhtmXf3CEgBAis+HO0d+I+w9O2okZDlubu3zksLoxTDP1Ly4osOuzu2sPo/NNhtpT4sqR8FFJ8hcDmrX4oUOlTa4b52noSw32lCKouAvn26xfB6QzXFqmU6kG+c9A0GOfEdUzjypibxmjzf7sa+yXkxmXMIzwYsrOuzqLDStbzYydxmHZvu376+LXgnY1N7JahLHLoaWmjA+86u+MzH+DVuMJTsr8PrSYsvnAXHsXJCwEJAxSFUT+Ttd+cxCXPH0Qmw8UC0kP27gmeCF1JmveTnpf+sP4boXl4W95qIyIinIsLzE3I2HMX3+Dh0Tvvki3k+c7poXw/u1/wQ/1hB/dJRdvDbDbij5cqQu8potrTkxN9cXW0pFZMcV2OdFQm7r8+KmJ5xkID50Ae55dy0AYFifLrisb7fg63aeKrr7vMTt9GJFToyz7bhonAyWddiVsAiQMU9qZLhm3YY1Lw5yeI66oGbTo41cVAqQVCrqwme61Ww1MnGq6Q2iA3G2E3Wmx8uTGWYehNw+VNpVdS8qPxODGnWeCV7c0GFXL6tPWNtrXkztnawmQatRUPT0//ZNeOjm0UZOJhualqebjeTLkirV0UYyXcyS8Uzw4ooOuzovcKv7LLT4TXbY1XrfRYVEMnDrcFHAbM2LA4nYxLZWI81mI2tIeEglDKfUqf1M7r2S7eeZ4MUNdE9SZ3G6ts+wa2rvZDmJSrzIQNzOc0nvZ+PNYipqkjq7any0ToV46RpqNtK/qWNkDKjUsOLFOAYvErJ8nheTfV60sMOuXGQq7yLzorlOlpnlAXR+1qobtpVEXUHernmRMFMq3FxbKgqDFweJqnkx3efFRYUAyfW0Ft3nxdj7dog/2Mhb0Ytms5Fl6Tp/3Fr8ASzYXo7axhZT+/lk3QH8flaR7Q958ajWvDCoUcXgxUHi+ryYvCgZu1CCIgvfyJullcGK/hl2rUvTKnYFTU7d/EQc07/n78S4N1fjttcLYr6vN0+/n7Uen6w7iFmr91uYO2vI9CAiGwYvErK+5iV5Ouwu3VmBv325E4EkXp5Vpqe1qJoVje1NddjVGQDEHSrttXleNBNO6C1T21rlo8IDAICikqqY7xs9pscazNXgmKH2wCrPlSwfz0xSl5eXh7y8PPj9ftFZUSXTTd4IO4e3Wu3nr68CAHzj9FNw7cCegnMjhkxPa1F9XiLOJSvzasX1FWsfopuyzNAebWTVJHXylAFtjH43kZdNikTXrFt4pubFHUOldZLsRHZTzUub/UcbRGdBGKmCF6M1LyZupnonepPxfLVtkjqH+rxIeEil/J3VcLSRcZ4JXrxEpmp/wF2FAMl2/hiLXpyY50WmmsI29l1j8c8FqybsYxlhjto1K8M6ZbJi8OIkvaONXHa+ylhuyViN7RSZzp/omhetJsjEWTLPi6gZdoWkat33lfFqc1MRINM16xYMXhyke7SRzfkwyo3NRjLmKRlF93mJv72pm6lNo40cOZUENRvFY6jDroQXnIw1bGpUZ9iV7WYgEQYvEpLthHVTh9028uUoOUXNsKuxvbmaF519XuJsJ+GgH1M0Z9i1KV0ZiIynDlUdx6uL96BG7xw0shX6LuCZ0UZuoH+SOrlOZNa8uIuT7eRNrX6UVjfi7K6nxM5LxL+1a14Sz4sV87wkw1BpWxZmlPB6E5mlG19ajtKaRmw6VI2//fQize3VRhvJdi+QCWteHKT3YpIuCJewYNIiY22QU5w8fW58aTmueHohlu+uiJ0XjT4v0Xk1sTyA3u3izfMi6LyxbW2jGCdD6He0bKi0B643K8vd0ppGAMCSnbGvi6i01V6X7V4gEQYvEpLthHVjwSTjk6BTnDx/Nh+qAQD8u/CgrrzYW/Pi3qHS9jUbxQgPQxPzcs2LBJnSeylykjrjPBO85OXloX///hg6dKjorKiS4WJKhK2dLG0iQ44W7TiCwn1HRWdDqKjlAWxMS3fNS7z3Yr3pwPntaLORyt9xN9TapwwXXAQZsqT3QYJBinGeCV48NUmdy05lGQsu0Zkqr2nE2DcK8KOXVzietoizR7WQNtjpxVSHXZ0fjrs8gM7XrObkJHV2PGzIWDsrR7mk72rkJHXGeSZ48RLZTljNmhdnsmGI6DyV1zYJS1vExFZq50hU7JLgfnTlQe92EnbYtYvmaKN4x8LAVSTncTOWKTuuG/01L2rNRpLdDCTC4MVB+kcbyUXGpyotogtTkenLdP5EDZXWDITtH24k49ksrtmIk9TZSfe1yJoXwxi8OMito43s7GRpF9EBl8j0RZw/at9Xa2HGqP04UvMSt9dL4hkwwa7zJVZtgt6h0oae+qUsA8RL0XkxcmFG4xi8SEi2qkLticVkKCbCyRhQOUee88fwwowSzvPiyKrSjp6vSoy/Ym1loNmIZUBMZpuNSB2DFyfpvJpY82Ke6CzJeExEiBptFHFcjK59FA9n2NWZVljNi0XNRhKe7zKMgtQ/VFrtdcluBhJh8OIg3c1GtubCeuKLiGiiyy2RyYsu70JvGlo1L5G/k+iaF1HsylPsSer0MZInCQ+pFHnSG3yoBi8W5sVrGLxISL5oW4ZiwBjR1dgin/pEnz2hX91onxer0o1HzlWlberzojFJnXXLA7ivjJCJ6mgj0RezxBi8OMit17dmvmX8Yqx5ESbsu2vkxcq86p+kzug8L+6dpM7MPC9GsiRhCSBFsaS7zwuDFMMYvDhIdG1AorQ77MpHdJ7EDpUWMtzo5J+hzUYafV6idmOq2Uhvu5E96ZvhZM1F2FBpy2perNmPlYyWt3YEEPqDFy4PYBSDFwnJFoXbObzVLuKrsZNrqHSo0G9utEOuI7UctqdgnG01LxppeXmeFxkypfdBQn1hRsluBhLxTPDijrWN9G0n27A5DpUmI+L3edH/WTPpxhOI0+lFXJ8Xe2iuKm1VwhJecDLkyGyzEWMXdZ4JXlyxtpHe4EWyE1bCckmT6CwLbTYSXvMSOtrI2MKMZg6b/qHS9qRvhqPniw1pib7eYpGh3NI9VNrWXHiTZ4IXL3HbiSxDIRFJdJ6EdtgVfAaF1bxENhtFzvMS1SfGxDwvVgyVjvGeI5PUOTnDrsrfUdsZGSotYxlgtM+LDdeN/qHS7PNiFIMXB+me50WyM9adHXZFD5UWmLjY/rphohdm1OrzYn0eItm1grMZTvZ5CU/Xqj4vyXNMjTBd8yLbzUAiDF4cpLegkK2Tljs77IpOn/O8ANo1L/E+azxd88dcWLORk2mFddiNs52R5QFkLANEZwDQfTGKmKRu6tytePjjDTamYC8GLxISffMxSsanLtHEzvPitjMolIlmI73bSXmnda7qxY4Ou3IeUvGZ0r88gPOT1P1j0R68X1CCvRX19iViIwYvpEmCMsAw0QWXG4+ZGaHHOzyYta5Pi3YmzG8WK39O/JbxZv01Q2uGXavC7CQ73XXTu6q0yMeNFn9AYOqJY/DiIN2FoGQPzpo1KxKWXKKzJLI2SvTpI6zZSOd28fq8iGs2EjNJnWX7lDBaN5ojsZPUqbwu/GqWF4MXCbnthJWv2Eq+mo9QoluN1OtdbB4qrXfa+zibiZth1579ai0P4OnrRILvpn+SOq5tZBSDFwfpfbqS7YTVflqWoJSIILwfjsh5XsQlDSD8fIia50WCmhf5zlYbJ6nTSMuqodIyEl4GwIqaF1LD4MVB+mfYlYsbCzHReU7mDrvxa160Rq45Mc9LvGYjMb+ckzUv4etQWZOO6OstFhnzpEa2B1Y3YPAiIdlOZO0bjkMZMUB0lmQ8Jk4x1efFTLp6Z9g12GzkxE/pbJ8Xtc7Vkdsltk9ZGL0G7Sh2TU9SJ9m9QCYMXhykv7+uXGesnTccu4gOHpKtw67aAJaoGXQjPmc0uImbB901L3HeSzx5cwSNNoo/2zDneTHL7CR1st0LZMLgxUH6J6mzOSMGaXaylKGUiJLEQ6WFd9gN7fMS+aZGLZ6ZeV50D5WW74S1rc9LzA67+j5rrOZFPjL0xdPf54WdXoxi8CIh6c5XzZoX8YVEJNHlllPJv7tqH257fRUamluDr4l+WjNVs2Gq5kXfh+POqSJstJGYodJWjbySIVCIJEOOdAcvBl8nSYOXTz/9FOeeey769u2L1157TXR2LKP7YpKt6sWFRJelThXmj3yyCUt2VuDNZXuDr4k+fcI67FrYLGQk3bjbxQ2uot904re0b5K6aOoTCiZOhkAhkuE+L3bM86J3qDSLfMPSRGcgUmtrK3Jzc7FgwQJkZWVh8ODBuOGGG9C1a1fRWTNPxitcB3d22JUwUzaqawqteRErbKh0VJ8XrWYjM+nq3C5eJ1WPzfMS666ov+bFSNWL/k2TiemaF0Y1qqSreSkoKMC3v/1tnHnmmTj11FMxZswYfPHFF6Kz5SjZTlcZgxMtovPswkNmitpif87OsGtDZw6HyBhsu73Piwy5Mr22kXVZ8RzLg5fFixfj2muvRc+ePeHz+TB79uyobfLy8tCnTx9kZmZi+PDhKCgoCL536NAhnHnmmcF/n3nmmTh48KDV2RRC92gjyc5Y7Q674guJSMJz5HAGQk8Z0eePmT4vTnTYlXJ5AEebjfR91vV9XmTIku6h0qY+npQsD17q6+sxcOBA5OXlxXx/1qxZyM3NxeTJk7F27VoMHDgQo0ePRnl5udVZkY7u0UaSxdta+ZahjIgkuuASO1Ra9CR1iTfLiJ5hV8absBmxb34hfV4sGjYu41Ezmic7rhv9Q6XlKvPdwPLgZcyYMXjiiSdwww03xHx/+vTpuOuuuzBu3Dj0798fM2bMQIcOHfDGG28AAHr27BlW03Lw4EH07NlTNb2mpibU1NSE/ed2skXbMhZMWkRXwzt9Dww9Z0ScP2rzvERvF/6m0bWP4ubBpnlenPgtHR1tFNbEFy/QdPk8LxLkKcXs8gCS3Qtk4mifl+bmZhQWFiInJ+dkBlJSkJOTgxUrVgAAhg0bhk2bNuHgwYOoq6vD3LlzMXr0aNV9Tp06FVlZWcH/evXqZfv3SJTuZiNbc2GcnU/LthFd8yIwfdEFXtyvrnkumQpfdG0Vr9lIFNv668aapC70b4sSFv2wEIsMedI9w67q67LdDeThaPBSUVEBv9+P7OzssNezs7NRWloKAEhLS8Ozzz6LK6+8EoMGDcL9998fd6TRww8/jOrq6uB/JSUltn4HM3SvbeSy81WGQiKS6ByJTd/5Eyg0RXN9XhJnxeRrXhttpDVJnVXJShgPSpEn/R12jb1OEg6VBoDrrrsO1113na5tMzIykJGRYXOOnCXb8DjtDruOZMMQ0X0XRKfvtLCneTNNEQ70eREe2cZgV21Q7HUZQ/u8WDNsXMbT3XCfFzvmedE9VFquMt8NHK156datG1JTU1FWVhb2ellZGbp37+5kVoSQsYZCFzd22BWdAYeFFn6iY1+rZm01nq6+nct4HTqZIzcvo2CE0QcIO85NvUFJinSTlsjP0UOWnp6OwYMHIz8/P/haIBBAfn4+RowYYWrfeXl56N+/P4YOHWo2m7aR8elEDzdm285j3dTqx8o9lWjxB9TTty95TaKf4eI2y2h+1sRQaZ3bBdR/NpX92v9rOtpspPJ31HYuHyotBd0Xo9qq0qKvZnlZHrzU1dWhqKgIRUVFAIDi4mIUFRVh//79AIDc3Fy8+uqrePvtt7F161bcc889qK+vx7hx40ylO378eGzZsgWrV682+xWECz1fZSgU3Nhh184sPfDhBvz0lZWYMmerevpJ1mE3bMp5E00RjqwqLWU4blOzUawZdsN+K/XPGslRbVMrth5290hPe5YHMJ52+AzVpMby4GXNmjW46KKLcNFFFwE4EaxcdNFFmDRpEgDg5ptvxjPPPINJkyZh0KBBKCoqwrx586I68XqR7g67IaesDIGBdmEvQSYj2Bn0/Xf9IQDAW8v3xsuBbenHEjZUWvQ8L0aGSkfcMcwFLzqbjeQ7XQXmyZo+L7WNrRjztyVYurPCgjxZQ4bfOZHlAULzzYoXdZZ32B01apRmITJhwgRMmDDB0nTz8vKQl5cHv99v6X5FCIvCxWVDNxkKiUiisyTjMZFB5HGJLCvsHyht3yKIZjh5voSNNjIQaOrx+eZSXNa3WwK5sp4MNWyJLMwoPtfu4JluQp5qNgr5m81GCRI9z4vAtEU/rTlRexL7w5ZveGJrB35Mu260sfu8hDQbxflsIt87I02eW4oM5ZLZ0Uaia1FlJs+ZlgR0Lw8gWRQuQyFglOinLqF9XsQlDcDYUOmoZiNT6ercTsLzWcY8JSKdwUsY3cGLWp8X0RezxOQ505KA3mtJvj4vWu9LkMkIoo+b08ckfGFG50u8sBEsJjqBOtLnJfEkbGNXnmLOsKuz2SgRGWmp1u7QBBl+Z91DpUOu2dB8M3ZR55ngxQ1DpfUKr3kRfwlqLswoPotRZMxTsrC6KcKKdEPJuDyAbZPUac2wG3dkmPE8ZbST55aiJ/92N8sn8hwh4ekpJXnONJPc0OclkZPSDSeyjFkUHfQl21DpUHFviDaOXLNiYUZhnOywqzNZ1/d50bONJOcClwcwTp4zjaTlxg67ovPkePKiSzkl5p/Rm9k5z4vOo240CSd+S/uajWKkZcM8L21kajYy+gXsaG5N0bnPsK4CbDjShcGLg/QWrpxV0TzR8ZTIUWKiRyhIvzCj6Mg2BrvypD3DrjXzvLSRqsOujrPJ7jMhsQ67xj+fjOQ505KA/knqjH/GTlqFgOgmmlhkOG5OCu+wKzgDJm6IToyUlvHccDRLeoO8BHLVLtVdd1vb+7yY3M5dR9NZngle2GHXPprXt/gsxpDEfV5EJKp7BIuNgbCNN2W72ba2UazRRjrb+GQM8ozQk3/7a170Lswo1whTN/BM8OKKDrs6t5Ov5sXc+yKIPm4ib5Ciq5qt6vPyQv5O1DS2GEhXZ58XCU9Y2/q8aI02sjg9mY6t0azYcdmYrnkRfTFLzDPBixvobjZSGfMvivZQaRlyGU50jsSONhIxz4vOTqBawUvI328t34tH/7tZfx50HnOjw5KdOL+dvIbC+rxY3GFXplotXTUvNmdX96WoUtvO0EUdgxcJSbeqtOgMJECG4+YkmR7Q4nYC1Wo2ivjdCvcdM5Cuzu0MnhqOjDZycqh0WM2Lte1GgUACGbKJvg67tjcc6dwqdrORTNe1bBi8OErnaCPDnxBLxjyKzlPS9XkJYabmxVy69gyVNmLlnkrc+tpK7D5SZ+hz9q1tFL/Pi/U1L/JwU82LbEvCuAGDFwfpvlB8knXesnGEiF1E50lo8qL7vFh8Q9SdruUbGvfTV1Zi2a5K3DOz0NDn7Ouwm3haiU2qKU9hYLjPiw3XTSJ9Xri2kT6eCV48NdpIdAYiuLLDruj0HS7EQ6udhc/zImqotMpnqxqaw/5teCr+BPJUVtNkLAlBJ2zcztUJfHHR110YCQIpszUvoq9lmXkmePHSaCPzH7KWKzvsCs6TyNRFP63Fr3mxcah0DC/k78Sgx+fjX2tKQtKwX4rB38C+ZqNYaYX8HXdtI+Ppte2vrqkVhfuO6roOX1m8G3e+vRotfms7zOjJvu3NRokszBh6GBi7qPJM8OIGem+o0s3zIjoDbpRkB033TSBiu8ibq9U3k+nzdwAAJv57Q0ga9v84eqeFb+Nks1FoYnYNlb7xpWX40csr8FHhAc3PPPnZNny5tRxzNhy2JS9xt7H5QtVd8xLyt4wLh8qIwYuE1Hqei2JkeKssRB83ofO8CEv5BFPLA9h02AJK7L/tYrT2y8mzRVH9R5ztDO57R9mJDsuziw7q/mxDsz+BFOWmf6j0yQ1DgxfR17LMGLw4KIH+ulIEBpo3YhkyGUF0jZXTwVPoOSO82ShunxetZiP7OfPTSFLzEmu0kc6h0ok1Gxn/jF301LCFDUu2IQ96m43Ca15CXhd9MUuMwYvNikqqcPlTC/D55tIE1zaSqDRQkWig8NnGwxgxNd/QXB56ueCw2UZ0Jz9zNS8O/HBGJ6lLIAmjfV7sCqliz7Crd0i58TxV1jXhH4t2G/6cHXT1ebE5D4l12GXNix6eCV5kHW1059ursf9oA379T/1DJ6WreTE5QqSxxY9j9c1Rr//m3bU4XN2IO94sMJG7xPJkN6eTF74wY4i4I1gkqMRzIg2jv4ETTVltwjvsnvzbH1Dwl0+3YO7Gw9Eb6vTs/B2YOndbQvn64ycb8dv31yX02Vj0zfNid58X45PUhU70J/palplnghdZRxuFtuMmcqHYdW0dqW3Ca0v2xAwqrM7DpdO+wkV/mY+jKmnVNraaSyCGZGs2CiWivAtriog3giXB/a/dfwxj3yjArnJjk7/FYrRDZCLH02jtl103Ua15XkL/nrPxMF5fWox73l174j1bchTf/9YfQqtFo45kePDTexaE1tSxw64+ngleZGV2ETS7bsK/fHs1npizFb/7ILEnnRmLdmPpzgoA2jfqyq+DlrU2NA+pEX39iw6eRIpf85JY1cuNLy3Hoh1HcOfb+h5Oiivq0dgSuwOo4XMjgejF+FBpm8ScYTf235V14XPTiGqybrWoGkpXn5eQv+3oX5JIs1F4h11Wvahh8GIz0zcxm8qPDQeqAQBLvg5A4mYhRiEwbe42/Pz1VSfe15nJFAfPNtGhg9DgSXBds6mJ5jR+uUPVjbr289byvRjztyXR+1cUw7U3CdW8SDxUOvR6Dv07LSLisiJPy3ZVYvY6/SOOAOuCFz3sn+dF53Yqs6qz2Ugdgxcnib6jJsiq4a2O9pwXXvMijpBmI9Xn+cjtwkU+WWqdS233162HazDuzQJsOlitum1xRX3Ua09/vh1NrcaaJfSctyVHG7B898kHAZmHSqulm2rT08V9s4oMbW9Zs5EEPXYTKfPsHgHlFWmiM+BlR2qb0Nhy8kLUqk7/4ycb0eWUdPTu0kHXZ2SgKPrrlpy8EIU32zi9PIBMQ6XjnuiR/1TivR0l9esv9/PXVqGyvhnLdlcayttLC42PhNFzOEc+tSD8M0aDFwvPF621cdSSiqp5sSxHxhgNLtUILwNgpObl5N/s86IPa15s9MScLbq33Vleh/cLSpC3ILxwtfs81tM2Hy8PZgqayMJy1Z5K/OD5xVi992jC+2wj+voXW/Miem2jeO9pzPOiVfPy9TnT1o+q2aIbXaLmbToc83wV+RuEP7nrX1U61YZmo0RcHaO5LxFGZ9i1JejXPcNu7EnqSB2DFxuV1+jvAFfXFHvEjd1PD2k6qorj5aG2sVV3IRfZgbJ9u9Swf9/8ykpsK63FTTNW6NthHMl2+YdWT8tc8xL5XlSzkcYvZ3TafTsVV9Tj7plrY56vsR4KiivqcdX0RTH3ZeX9KtFZbNJSjf0WdqnUMQLSKokc96P1zZiz4TCaWrVnBNY9SV1YzYvxPCUjBi82inqSibNtqz/2u1YWaot3HMGOstqw1yLzaDQP9U2t0Ftc3j1zLfwhV2Zmemqcrc0RPblfMj88mVnsT+t9PeerUw5XHVd9L1aQ9cePN2KnSmdhRxdmjBgqrSgK/AEl6kHG7edwIl1eAgEFL+TvxJKdR1Q/87NXV2L8e2sxY+Eezf3rjbVDT2vRZZdbeCZ4ETVJ3X0frAsu/hYpxUBBq7aiaiKncSBG6L6ttAa3v1GA7z+3OOx1XcFLnPfqmvTXvAAIm+sls519p5/oy19kASR6hmZTzUYa+5ap5uVgnOAl1gN3Y5wn9YCFrV9hfV5ivR/x9z0z1+Lypxag1cpMRGj1B7CzrNbR87EtKX9AUR02H2nuplJMn78Dt72uPnHmttITD4DzNpdq7k93n5ewZiOdH0pyngleRExSV17biNlFh1Tfj4wL4l23qsFLjA+VVjfiP0UHY35myc4jGPDo51HDEzcfrIm5f7M1L7WNrYYChUf/tzmYt8hmo1BXPrMQeQt2GdhzONEPL7KMlHbqOOhNx2x+ZKl4aW4N4IGPNqi+HyvIipd1K2tejIwOVJQTN+GDVcdx7wdFwdcDAcXSQGP8e2tx1XOL8e6q/bq2tyLttmM6+vnFuPCxL3A8xsKPkYHewaoG3fvvlKk93sXsPC8A8NS8bXhnxV7d+UoWngleRNCs4vbpb0M20mx01fRFuPeDIry5rDjqvTveXI2GZn/U8MTQp6r1JVXBvyM7zcamnu+ymkZ8ta1cxz5OmLPhcDBv8YKX4op6PP35dt37jST64UXoDLuhc0YISN/M2kZaB06WZqPq4y1x34+Vy3i1RvYtzBgjLR1nRWvA2oaszzeXAQBeXaLd1AIgrHk5UW3HdFd5HZpbA9gYY1i93lQ+XFMS9VrHzHaan0uk43Zo8LLlcA1eWrgbk/6z2fB+vI7Bi42saDaKpfbrzr2LdkS3y6pd9C0hwdEP85YF/zZ7M8j9V1HCn01LtfH0E93nRWjqJzlVTR/eFGGiz4tGOm0BgOggRquzZtiTdEDBpP9swhqVGaYr65osPV/ijTbaX9mAguKTo6PUfisrggczWlQe5sxo+00amltR+vVkh3pnQG+rZQv93Tu1t7LmJfYkdVpBcjLjPC82iqp5iddslEBhYaT9X23iJ7PNRomWcdtKa8JWk1Zb9yhRooMHoX1eRFdOxP3qZodKn/h/qs8Hv8BfWWuKgNCg4YstZXhnxb6Y283deDi4lpBV4gWPlz+9IHxblU1bAwGh8X9zawDtTXboj7wGW/0nmsKGTclHXVMrlk38LtINPkBVN5wMJjLj1By3MTtJneggUmYMXmxkZLRRi0phGK8AMRK8qD3JmO2wm6hbX10V9u9hU760dP+i+7w4Te1UcOowhHUSjrNd5O8SNUmdVrPR1180JQWAvj6Ytmhq0QheQg5ITZyn56dMNI3qonF5qx1tf0AROslbswWz7LaNpGpzy6srMbTPacFpKVbsrsTl/bqFba/FH7KRWpkdKpEHidA0/MlWkBnAZiMb6W02KjnagPs/XB/zvXgFiJGa8xaVkQQ+H/BBwX7sKq+N+T5gTy1C5FwOVq9nIsPsmqKEPvU71mE39G8DfV6ig5n42q6pyFrNRN362ko0NBtf1Vyr2Sj0wSJeOWBHLZmR6eXVru3WgCL0AcBIM7oaBdHn1+q9J2t7FUUJO+H0lHOhxZSeCToT+XlDa1tijRylExi82Cg18sxVOQ9/+/461X1YVvPSGntHJUePY+LHG5EzfXHM9wGxTTBHapu0N4pB9AOL0+mHBixho40E/Hrx+7yYazYK1rxYdNdftqsSz36xA68t2YNjBpouNZuNQrIXr1O8TEO/Q/kt7rBrlCXBixK/5kKB8bItNJjQNUldIjUvIWlYtMyTJzF4sVHkE5dacVByVH14XryLy0h7qpk5HEQGAte9uDShzwkPXgQW/eHzvDifvpnRRno77BrpDK/l9aXFeGLOVlxr4FwzErzEa5qNVYP0zOfb0eoPYNmuCox7syD+fDIaEl0M1Qs1L4DGVPuK/g67seireYk+/rEWDA0V2j9Ra6kARVGw50hdUvaNYfBiI71V2/GaTOJNrhRaJlY3tODHLy9X3dZMG7JTnU9jlfGHvx4VYJToS1nsUGnn09R7E4g8Lm8t34tZq/eHvB//wAWbjWwYbXTgmP4goUlj0rPQGpV4eY31W724YBc+XnsQt762Cgu2H8Ef/hW7SVmNsWaj2K+v3F2J+Vu0J2GzS7NKTbERCpS4k/8ZXUMoEFDCPqPV7wmI/fte+czCmCNF27SG1bzEz+PMVfvx3WcXYfJ/N2nmxWsYvNhI70Jn8U7QtftjD68EwgvIvIW7VIdiAurzyFjt7/k7E/6slVXooqfYdiJ10d9RTdzlAWK89tC/N+red9vgENHNLdqjjU6KF7yofY9D1ScDqdIaYwG8kcUG1WoI7/9wPSrqnFtjKJJVzUbxApQTzUZK2Pbx+JXw2ih9axvFFmvemDahteRaHXaf+PTE4r8zV+qb/M9LGLzYKLrZKLZ4F+rmQ7Fnxj2x/5N/1zbGnw/ATGFg5Bb5rMpSCXqIviFZyYm4Qi0NER12w/vZ2CfYbCT4VNFuNjqZwbh9XlRK4Iy0k8NwjV67ar95rKBS0vjXsg67cfu8KMa+vz+y5kXXaKPYv329ykK8QPiD5nsaMxLryYNXMXixkd4CNl7NS7yn2NALQ6tLi6lJnxwq4HQscK2b6ELZiT4voSmElpEiOuyGHW8zp5rGZ904SV28/jlqAXtG2smL4cCx49hZpj4aUG8+YpUzoq8TNVYMlYaiQImzm8jB4FqHIrITs5nAYcH2I3j8f1tU09ESa6mDZOOZ4EXUwozxRE9Spz4sMRGhBZ9W+61TNS9maPUR2lVep3uBtWQeKh0q8rRoaG7F8l0VMSctLKtpxD0zC7F8d4W5NE0ce63PtgUtomvptPo7pOiseVF7Ms+IWLT0bwaaY8OC2pBaOKunI7CTFTPsKohfLho9HH/+zyb83wsnO3WbHW30RozlXQDt3+nVxXtw/qR5+Gzj4bDXV+yu1MyPl3gmeBGxMKMWvc1GCe8/bDGv+NuqzbCrh3MddtWv9AXby5EzfRF+/c9CXfsS/UTpTLNRSN+GkNfjrW1059tr8LPXVuGFr8IXvaxrasUfP96IuZtK8bOICQSN58u+z7ad84nU0s3bdFh7I53irRANGOnzEvv10GajSAu2leOPn2xUDeTVrteYNS+qqYilZwI4LQu2l2P3kTr1DZTwxSe1yrmP1x7E8ZBjrjb9RKhE1jbSGhk65bOtAKKXZrnl1ZVJNerIM8GLjKyaSKtNIKBg6+GTfWBCb/ZaF56ZJxmnLod4hyvv65ttZC/9v87bhlteWRlVs5QMl7DadwwfKq3g47UHsK30xHmz/Ouns9C29NLqRgyY/DnyDSywGS83poIXjfdTfD4EAgpKjhofPnz3TOum4Tcyw268ckBPs1GkcW+txnur9uP1pbGf3NXyEeuJXtZO31b0edl0sAY/nrFC9X0FZs9VHcFLArcAM2W11cusyIzBi430jjbS69n52zHmb0uC/zbSbFRvYBbRBdvK8fDH6k92donXN2C/ylw4Ly/cjRV7KjF/S1nY66ILZSfS15PEV9vKkfuv9fjB80tUt5lrYY0EYC5w1JykLsWnWt3uJK0n3LAOu1GzVZ6kXvMSXjR/uuFw1Pwgh6tjB3BqOXNTzYslfV40mL1E9Xze7Ay7RpXXJja1hBsxeLFB203fyom0ACBvwe6wf4fuXitYr2rQvzrpuLdW4/2C/cGbhFNxQLwn1HKNmXZlq3nRXD1ZUbDxQLWudnPVfah8y9DDWFRSlfD+E2UmcNN6mk3x+fD2ir0J798poddmapw2LrWal/QYNS9XPrNQV9rxFluM3ljXLh1ndA6WRJh9wFD7dOh+E7kHmOmbpFVOegmDF4vNXncQ5/15Hv61piTuzVhRFEyduxV9Js5JOC0jNS+JLK1e1rZsvKwlXDyi+7xovD9z1X5c++JS3Pn2msTTUB0qfZJT8/uEsnWodIpPeH8mPUL7OsS7f6kFL2k6OvWUVjdi6tytcWfgDa0Bil3zIuZgzt9Shsv++hUK9x0Vkj5wop9g2OSKBg+F+pD0k38nVPNiotbpSA2DF0rQfbOKAAAPfrQhbtS9Zt8x/GPRHlNphZZvWk8RWlNSx96/7+t9G/5oQqwcDSH6/hbvmAUCCv48+8SMmEt2mhvZ0yZ8qHToCBPn54FQ++77KxuwWGVm0XjzXoRK9YnpjP3PlfuQt2CX9oZfC/s9VG5higKs2JP4CJEvt5bjH4v24PcfFEXsODTtk2IFskYuOX9AwY0vLbNkQrS73lmDA8eO4443xA2wUBAevNU2tmDORiOzCsc+eGGvJhC9mCkHazTm+/KSNNEZ8LJ4NS/WdKzSP89LIt5cthcbD1Q7UoULmGvrjSS8z0uc8OmTdQetSUOt5iXktLNiyKl6+mqddGOn+euZ6iPFvj35c7x068Waaaam+Bz/bRUgGGz+cFBPnHVaB83PODmUe+PB6rB/q517sa4vI9f21sM1WLu/ylDetKj1xZuz4TCuH3SmsfXb/AFD5aoSMWNu5Ag87c+r77dNIqON7LxmvYQ1LzZKtfnohg+VDj/hrZrEa82+Y45dTFbWEsh8+S+Ms65JosJWlQ55PXSIfGjzQkVdE777zEJUG+gLpZdaob6rPP5Eaw9/rL1MgM/nc/y3DV9JWN856mRzzNldw4OpsGYL34n83zOzMObs16JH1qql/+XW8qhO+FpueGk5vjM134Jc6aPa5yXk78RWlU68HPz7V7twzQtLNGdc9wIGLzayosNui19B7r+K4q6FAUQXAqKnT09EY5zhp0a/j+h+EVrNRpakoeMG2RKS1q2vrgx7b09FvanOr6pPnga3NyLV53OsJrBNS8jNJN6Ec6Hsaq2L1bzWq4t6TZAPPizdVYG5m0rxv/WHot4XXUMZj9HO5pE1UFoCirkQU+08NNvnxUyzUfXxFmw+VGOoaa+2qRXj3izAvwsPJJyuCGw2sli7VF+wpsKKeV4++vqE+nhtdFND6MUTeSGdqLaWt2Aywh9QkJaSYmj4pFqxdKS2CR0z05DZTn0SMCvEO/JWNY9FPmHH+kfoZF97K2MPN084fbW/DQY1RqQK6LDrD6l51FujaVeA9e3Jn0e91j7iXI588o9XW2RVIG1E6FxVIp1Y28jEyDjV8zyk2Sihmhfzv4mR2psZC3djwfYjWLD9CH40+CzTaTuFNS8WaxfSVmR3u3foSW5Xs5EMWvwBw98nVsFSVtOIoVO+xPAnHahajjstuVU1L7GFHqkvNKre481Bkii1wNGKp3yfz/mQPPRJWM8oIAA43uLH377ciS1xFla10rH6Ztz3wTos31Vh6DhbFbv86GL9Nz0zI+yspMDsnER6al7E9HmJ1Vdof2UDDhyLfoBJZCSqDBi8JGDepsP49T/XxGxXDAtebA4gQisiopuNvBW86K2ubxOrXFn59cgOqy/WfZX1UU9L8Yofy4IXlf0Y+enbmVgNU215AvtrXpwNX0J/W71B9IYD1Xjuyx24+gX1yQGt9Jc5WzC76BB+9lr40g5auY23ar1dKuvlGM5repI6Hds43eelTeR52tDcisufXoDL/rogbs2OiJq4RDF4ScDdM9fi881lePrz7VHvtQt5krXhoTZM6E0wskD3UMULWvwKUu0+mAn6ZN0BXPH0Qtz7wbqw1+MVjJY1G1mwj9aAErXkQiLpq/0dtr1GhquPt2jPsOtzvtkotOZF1meCkpAZqI10GP33Wuf7ObQzMZIhEFDw63+uwfQvostew/uKGG1kmOpoo5N/O93npU2qz4cVuyvxm3cLUVbTiCMhk9fFW3rht++Hl2PNFqwxZRcGLybsi9GHIPTCtLvpJl6fFy81G7UmVPPizB3uxa+HV366IXyK/XhdAa16uLHiK/513jYs3G7t6Cczxz5Wp9JQIkYbuWGxu9AsbjxgrOOqFYx0fU03Ebys2FOJzzeXGR7WrM5EnxfV19U6o+ljxcSSKSk+3PLqSny2sRR/nr0p7PyIVys/J2Sl6hW7K9HvT3MxY9Fu1e1FkjJ4ueGGG3Daaafhxz/+seisxFXbGN3zP7QPgf3NRiHBS0SA7KVmo13ldaioMzYvjlO3G7X2abX7d2OL37o1oyQaUWVVsLitNP5w6tQU50fIiJjoz6jQh5dxbwmY+M3AT2Km5sWKBRvbRM7zksjnY79+8m9RNS9/+XRL8O8dZbV4NqSmSu+t4aF/bwAATJu7zXR+7CBl8HLvvffinXfeEZ0NTVp9XqxeVTpSaIHlj2w28lDNS2Q7fllNo+YNzKn7m5HCtLKuCcOmfIlVxeKmRLeSesdc+9JMTfE5PjeJ22peRDCSfLu0xMqmTzccwpvL9ib02Vjs6vNipNkullaLF6XcW9kQVTOsh+znvZTBy6hRo9CxY0fR2dBUF2POhdAOkE6ONoq8mdsdOIk0/Ml8PP/lzqjXQ3vSOzVJmFrwEiv115YWoyZGbV2iwodkyvN7R3VeVhQs3F5uyb59Puc77Fq5bIVdZJ6vJVKiNS8T3lun2j/rtSXGl1oxO9pIfZ6X0I7sxq9LWYIGp+dTMsrwWbR48WJce+216NmzJ3w+H2bPnh21TV5eHvr06YPMzEwMHz4cBQUFVuRVOrHOsbCnigTvJ0d0rgwaf7RRYmm7xd/yw4OXppYALvvrguC/9Vx3Lf4ACvcdM/Wko9ahLVb6mwxOoqVFdNmiln5k4fv55lLc8aY1TRmpAvq8iD7Oeshyw9MjkT4vM1fui3ot9Bs/MWer4X2a7bCrZ1RdIuWwLMGy7OeU4bOovr4eAwcORF5eXsz3Z82ahdzcXEyePBlr167FwIEDMXr0aJSXn3zyGjRoEAYMGBD136FD8TvruYHeeSDieeaL6Gm8Y4k7SZ3Xo5cIOyOmntdz2f159ib86OXlmPKZ8YKvjWqflxg5sKyvSzCNk2T6tSObMJfuMrf4ZCBiqLIbggmnib7PGKn5SWRuoT99vbZUqMNfr3qfKEUB3lhanPjnceJ73/b6Ktz2+qrgMVBCnmcSajaSpI+V6HNKi+EZdseMGYMxY8aovj99+nTcddddGDduHABgxowZmDNnDt544w1MnDgRAFBUVJRYbmNoampCU9PJmoqaGrGzN5rpSW9UePAS/p6XRhvpEVl2Rv5708Fq3Bux+u4Hq08sufDmsr2YfO23E0pXtc9LjAv/uNXBS+hQeUv3bI7VT2yh53mKgGYjNxB9TAz1edFZRioAHvxoPXpktU8oT1qW767A6r3HEt+BAhxraAmuDF9Z34xup2ZENefuKIvfCT2SFaONrBB63ZXVNCK7U6bA3ESz9E7b3NyMwsJC5OTknEwgJQU5OTlYsWKFlUkFTZ06FVlZWcH/evXqZUs6etkxY6ma8NFG4Sd8rGHcbvHR3SMs2Ev48bglYl0fq6hV8cZ69XizfTUvIoSNNgp53ergxR8WvIj/3k541WAfDtn7J4TSG7xsOliNf605ENVEbJWSo8e1N4pDb4f17z+32NB+RTfXtAXCofkY/mS+dBPYWRq8VFRUwO/3Izs7O+z17OxslJaW6t5PTk4ObrrpJnz22Wc466yz4gY+Dz/8MKqrq4P/lZTEX8DQbmaGARoVr9nIzaxYdyjycMQa1m6nWE/C8RaeTCwNS3dnPH2VwtvympeQw3ZitJG7zvXD1cZvkkYnDpTsvhKX3trpJouvl0hmzyM9H0+s2Ujsj9m2hlxksCLbdSflwoxffvml7m0zMjKQkZFhY26MaSeq5kWu88oUK0ZpiT4csa5ztWYjRVESGi3k1Igqo6wu5MKajVzY5+VX/yy0PQ3RNxa9ye+rbNBdK2z3+W1273blLl6flwIHpllobA4gIy01qu+aTCMaAYtrXrp164bU1FSUlYUvBldWVobu3btbmVSUvLw89O/fH0OHDrU1HS1qNS929EEJPcetavOurBO/7ogFfZ6F9wGIRa3ZKOEnrdBmGwHfVy3J0O/zw7xlWLe/ylQ6ydhsZJTo092O5O1+IDN7zOwKGOMtzPgzm5q/QzW2niinRDdfabE0eElPT8fgwYORn39y1d5AIID8/HyMGGFFPwZ148ePx5YtW7B6tYDZJUOkqQQvdtxc/BY3Gz37xXYMfkJ/rZdd7JgfJ1bwGK+WbH9lA+pjzOOjV8w+Lyo1LzNX7sOVzyzEvsr6hNOTgT+gBP9r09waML34X9hoIxHLSruA+JoX69O3PyC3v9koEfGCBiealNoeskSfU1oMNxvV1dVh166T60oUFxejqKgIXbp0Qe/evZGbm4uxY8diyJAhGDZsGJ5//nnU19cHRx95ndoN0Y5zLt5oo0T83bL1QsyxK3iJLBTSU1PQ4o8OKLaX1mL084txescMrH4kJ+p9PYxc94/978RU3o98sgkz7xyuPw2jmTIgEFA0h9tHdtK94ukFyGyXimsv7GltXkISShHc52V18VEMODNLWPpqZL/RJML20MV7h8wSbYdF9poXw8HLmjVrcOWVVwb/nZubCwAYO3Ys3nrrLdx88804cuQIJk2ahNLSUgwaNAjz5s2L6sTrVU6uKRSIM9rIzRJpYYs123GotBQfQldH8gcUtEtLAWI05Sz+urOk3skCY0mkvf5Yg8H1m5TYf1uhNaAgXSt4CUn0UNVxHDh2omNqfbO1naNDC9HGloDQipd73l0LAJhw5bcE5iKaJFODWMru4MKKgM+dNU76yH5LMRy8jBo1SvPgTpgwARMmTEg4U4nIy8tDXl4e/DGepL3K6mYjWSQSALbN2aImclXqm/+xQnXUQ6f25vuxR887o/37NBgcSm1nh8a286nkaAO6Z2UaGkVn5zwvsq5wK5roG54dqcvdaGTNPib+ewOm/ehCS/eZLKRc2ygRsvR5cVK85QHczI7OzZF9kdbsO4b0tNinf1b7dsG/9S4doDX8M14nvDYNBmsswudZsfYEaA0oWLTjCEY+tQA/j1gY82Sasf+2fJ4XL53cNokcGeI4W6IXm0cbWbB7s/v4YHVJ1AK/on9Kt/BM8JKMwpqNPHTG29HyFlnzAoQHHOU1jcFApWPmyeBF7/wwkX2dIp+E9fw+xmte7OMPKMH1ZNRWwda7tpFZXjq37eLF+M7+0UYWNBtZcBVGDkH24E9pCwYvHuGl8j3F58Ps8Zdaus+YwUtIzcuwJ/Pxs1dP1DCE1vxUH2+J+lws7SJqcRL5OQwHL6HLA1j8+wcCSsIrk1s9IsLt/Tn6ZZ9qexqim40SdWqGehPtRosXMo0kQ80LAN3XWWS/RqsnvXQbzwQvsszzIoqXnk5TU3wY1KszOmZaN4dirCHskc1GBXujaxhqGnUGLxbMrGy0xsLOn7w1oGg336mkb3XnceFNIi4guuZF1gkT47Gkz0vITuoaW/H7WUVYsL1c/QMxRMUuKuf7m8v3Gsucx0k5w24ixo8fj/Hjx6OmpgZZWfINZYyUv7VMeyMDvNQvwKpmo8YWP+6eWYhR/U7XbDZSo7fmJfLpyen7rdXJBZT4Q6UX7TiC3FlFMd+zOtjwUmBuF9HHyI0/kdXNRi/k78Qn6w7ik3UHg68t3G5smYcT+4ztwzVil76RjWeCF7f515oDlu7PQ7GLZcPN/7liHxZuP4KF24/gW2dEV93Hqi35eO0BFO47Fvx3oiu8uvFJNFRrQEG8lS7GvlGg+p71axu5+1g6gcfIOCuO2FPztgf/Lq1pjHo/ken83RgIisDgxSPc2uYdi1X9dUMLk13ldVHvxxptlPuv9Zak7cTPYec8Ly2tgbCaF0VR8PrSYvTN7ogr+p0eIzMn/7RzVWmKTfQhEp1+IqzIc2gtix2jJEXZfMje/kZWYJ8XjxBdbSyb1sCJm208akOlreDErxFau2N1Tc/xFn9YU9iK3ZV4Ys5WjH2jQPMp3/JmoyTol3hfTl9Tn+f1b5zVx8yqGmMZam1fXij/fEqeCV6ScZ6XUKw1DqdniHP3Tpm2pe90zYvVGpr9YU+SB6uOB/8eMiV6/auweV4SbGpTkww3ZrM3PtHXvww3XKOszrFVNS8ynO5OzhSfKM8EL8kuGQp4q6XF69Rhmv2/R9gkcRYnd7zZH9Zs9MBHG4J/H62Pv4yB1TUvXuqMrsbsfU/09e/K4sfiPH+1zdgoIzUyHEs3NIExePEIdtiTi9kC6Gh9M5bsPBK3L5Od/ZwamlsNzfMSuiUnqTMucqIyo5LgEFlO1toiGXLFmhdyDGMXb/m/F5bgttcLwjoERrLzJz/e4jf09GXn8gBqwcu52R0tTccuO8qiO4tHMnuvEN2p2Y3FD8tMdRZMW2U7F2SR9EiGp9NITa3yLsJp9uc4VH1ipNScDYctyI1xx5v9hp6+QmuBrD4XdS4v5Wrm+7wk3/VvlqwjNGXIF2teHJTso40kON8dd/lTC0RnQZVVVdKNcQK08KHS1p4AJzrs6t8+NPVE58ZRwz4v2kRf/6LTT4QLs+yYWBNUTnhvLWbHqQl2mmeCF442Sr5LsaymyZF0vtpWhh++uBQ7y2p1f8aqn6Mp7vol9q1t9H7BfjS36q/yCE0/1jILZsjwJGo3Nzzpeo2sp5UM+YoVTM/dVIr7VGbVFsEzwUuyS8bgxSm/eGsN1h+oxq9nFur+jFW/ht6aF6vtLK/D2yv2JfRZTlJnnNkOu+J5/zdKJokuyuokBi8ekQQ168KVVUdP/63GqvttvJVjFZW/RbBz5AabjeQnY3zplg7dkdSuJSevg3jrmv3ty52YMmeLY3lRw+CFSKdGI80oFt3Md5XXYcqcLTGbTmS6YdiZF5m+p13YbERadsZY4sQu8WpenvtyB15dUhw2caUIDF4MqD7egn8XWrugIrmH1pNPIKAgb8EurNpTaWlVyKtLilFUUhX1umJjnxej7EyfNS/y8/4v5C0lRxvivh+v5qVNq+BhgFyY0YB7ZhZi+e5K0dmIojXjKcVm9Q13dtFBPP35iVVmb7zoTEv33dAc3fdFdMDiFPZ5IbLO4h1H8Mu318TdRs/pKLq20DM1L04MlZYxcAGA7aX6R8HQSW8t32vp/vZW1Af/tvp2G6ugCBsqLfjZ184RQTKONrL6eLs9dpHxN6LYZq5MrCN+JD21M3byTPCSzEOlT81gBZpsrC7MRQcnWuzMnYyT1Fl9rxb9FGvW0HO6iM4C6ZTZLjXu+7NWl+CrrdrrNIlu6vRM8ELkhF3l+mq5rO6mEWu+l9CA5vkvd2J9jH4xXiBjs5H1NWsW79Bhtw4/G9/u2Ul0NkgHreBlxqLdujoHix5OzeCFSEN6yFSzOdMX6/qM1Te3xhbtPi8/zFtmcar62TvaSMLgxeIsub3PS1qKDz8Z0kt0NkiHzHbW3PZFn7MMXog0ZCRwsYdOGng8Rmdbow5WHUd9U6vp/biRjKONLO/zYuneiNRlpMWvedFLdG0hgxciDVrVrDGF3NuGP/mloY/uilFl+8ScrbjwsS8AAOv2H8N1Ly5FQbG10/DLSsrgRb4sEemSUHkWg+iaF/b0JNLQPoGLPbTmpabRWI3J959bFPP1tpv4zf9YiWZ/ABsOVBvOlxvJuPSFjE1ZRHpY1mxkyV4Sx5oXIg2JXOxm7m1aFQ3NMg6/sZGEFS+seSHXsqrZSDQGL0QaEhnGaldtwZ0ak0t5kZTNRqIzQJQgq2peRPPGt4Azk9QR6WXXze3LrWU27VleMjYbyZgnIj3S07xx2/fGt0ByT1JH8lm3vyqhzyXriKJ4AjLWvMiXJSJdHvlkk+gsWMIzwQuRTCrqmhL63JHaxD7nZX4GCkQUgcELkUSOJBj0eJmcNS/y5YkomTB4IZIIa16iydi/RMJ4iiipMHghkkh5TaPoLEhHzrWN5MsTecOOMu11hYjBC5FU2GwUTc5mI9E50Mct+SRxVrl0pm4GLw74xumniM4CuUSs1aOTnYSxi2vqXe55dy3eL9gvOhtElmPw4oA0G1ewamr1Y/nuCtv2TySajH1e3NRh96tt5aKzQIKcdVp70VmwDdc2crmH/70RH687KDobREnFRbELJbFU0Us/24g1Ly7HwIXIeQxeyA0SWdrELRi8EBEZxNFG5AYejl28E7xwbSMicoqMnYjtlN0pQ3QWKAGpHo5ePBO8cG0jInJKsjUbZbVvJzoLlAAPxy7eCV6IiJzCZiNyAx+8G70weCEiMoqxC5FQDF6IJHRudkfRWaA4ZJx7hiiZMHghIjKIoQuRWAxeiIgMYsULkVgMXoiIDGLsQiQWgxciIoPY54VILAYvRGRaaU2j6Cw4i7ELkVAMXoiIDOI8L0RiMXghIjKIrUZEYjF4IYrj71/txLbSWtHZIMmwzwuRWAxeiOJYu7/Kkv28sniPJfshOTB2cZcnb7hAdBbIYgxeiBwwff4O0VkgCzF2cZd2qd5d4ydZSRe8lJSUYNSoUejfvz8uvPBCfPjhh6KzREQUhjUvRGKlic5ApLS0NDz//PMYNGgQSktLMXjwYFx99dU45ZRTRGeNiAgAoDB6IRJKuuClR48e6NGjBwCge/fu6NatG44ePcrghYikwdCFSCzDzUaLFy/Gtddei549e8Ln82H27NlR2+Tl5aFPnz7IzMzE8OHDUVBQkFDmCgsL4ff70atXr4Q+T0RkB9a8EIllOHipr6/HwIEDkZeXF/P9WbNmITc3F5MnT8batWsxcOBAjB49GuXl5cFtBg0ahAEDBkT9d+jQoeA2R48exe23345XXnklga9FRGQfhi5EYhluNhozZgzGjBmj+v706dNx1113Ydy4cQCAGTNmYM6cOXjjjTcwceJEAEBRUVHcNJqamnD99ddj4sSJuOSSSzS3bWpqCv67pqZG5zchIkpMgNELkVCWjjZqbm5GYWEhcnJyTiaQkoKcnBysWLFC1z4URcEdd9yB7373u7jttts0t586dSqysrKC/7GJiYjsxmYjIrEsDV4qKirg9/uRnZ0d9np2djZKS0t17WPZsmWYNWsWZs+ejUGDBmHQoEHYuHGj6vYPP/wwqqurg/+VlJSY+g5EREQkN+lGG1122WUIBAK6t8/IyEBGRoaNOSIiCseKFyKxLK156datG1JTU1FWVhb2ellZGbp3725lUlHy8vLQv39/DB061NZ0iIi4thGRWJYGL+np6Rg8eDDy8/ODrwUCAeTn52PEiBFWJhVl/Pjx2LJlC1avXm1rOkREjF2IxDLcbFRXV4ddu3YF/11cXIyioiJ06dIFvXv3Rm5uLsaOHYshQ4Zg2LBheP7551FfXx8cfURE5HYKB0sTCWU4eFmzZg2uvPLK4L9zc3MBAGPHjsVbb72Fm2++GUeOHMGkSZNQWlqKQYMGYd68eVGdeImI3Io1L0RiGQ5eRo0apTlMcMKECZgwYULCmUpEXl4e8vLy4Pf7HU2XSBSfjzdRUXjcicSSblXpRLHPCyWbFJ9PdBaSlteajf5y/QDRWSAyxDPBC1GySWHsIozXal4y03grIHfhGUvkUqx5EcdjsQuR63gmeOE8L5RsGLyIw3leiMTyTPDCPi+UbNhsJA5jl+TW94xTRWch6XkmeCFKNqx5EYexS3LjpScegxcil2IBKhCrXoiEYvBCRGRQgLELkVCeCV7YYZeInOK1eV6I3MYzwQs77BKRU9hqRCSWZ4IXIiKnMHghEovBCxGRQZznhUgsBi9ERETkKp4JXthhl4icwooXIrE8E7ywwy4ROYXNRkRieSZ4ISJyCkMXIrEYvBARGaSw5oVIKAYvREQGMXQhEovBCxGRQax4IRKLwQsRkUFsNiISyzPBC4dKE5FTGLoQieWZ4IVDpYmIiJKDZ4IXIiIiSg4MXoiIiMhVGLwQERGRqzB4ISIiIldh8EJERESuwuCFiIiIXIXBCxEREbmKZ4IXTlJHRESUHDwTvHCSOiIiouTgmeCFiIiIkgODFyIiInIVBi9ERETkKgxeiIiIyFUYvBAREZGrMHghIiIiV2HwQkRERK7C4IWIiIhchcELERERuQqDFyIiInIVzwQvXNuIiIgoOXgmeOHaRkRERMnBM8ELERERJQcGL0REROQqDF6IiIjIVRi8EBERkasweCEiIiJXYfBCRERErsLghYiIiFyFwQsRERG5CoMXIiIichUGL0REROQqDF6IiIjIVRi8EBERkasweCEiIiJXYfBCREREriJd8FJVVYUhQ4Zg0KBBGDBgAF599VXRWSIiIiKJpInOQKSOHTti8eLF6NChA+rr6zFgwADceOON6Nq1q+isERERkQSkq3lJTU1Fhw4dAABNTU1QFAWKogjOFREREcnCcPCyePFiXHvttejZsyd8Ph9mz54dtU1eXh769OmDzMxMDB8+HAUFBYbSqKqqwsCBA3HWWWfhgQceQLdu3Yxmk4iIiDzKcPBSX1+PgQMHIi8vL+b7s2bNQm5uLiZPnoy1a9di4MCBGD16NMrLy4PbtPVnifzv0KFDAIDOnTtj/fr1KC4uxnvvvYeysrIEvx4RERF5jeE+L2PGjMGYMWNU358+fTruuusujBs3DgAwY8YMzJkzB2+88QYmTpwIACgqKtKVVnZ2NgYOHIglS5bgxz/+ccxtmpqa0NTUFPx3TU2Nzm9CREREbmRpn5fm5mYUFhYiJyfnZAIpKcjJycGKFSt07aOsrAy1tbUAgOrqaixevBjnnnuu6vZTp05FVlZW8L9evXqZ+xJEREQkNUuDl4qKCvj9fmRnZ4e9np2djdLSUl372LdvH0aOHImBAwdi5MiR+O1vf4sLLrhAdfuHH34Y1dXVwf9KSkpMfQciIiKSm3RDpYcNG6a7WQkAMjIykJGRYV+GiIiISCqW1rx069YNqampUR1sy8rK0L17dyuTipKXl4f+/ftj6NChtqZDRERklZKjDaKz4EqWBi/p6ekYPHgw8vPzg68FAgHk5+djxIgRViYVZfz48diyZQtWr15tazpERERWueq5xaKz4EqGm43q6uqwa9eu4L+Li4tRVFSELl26oHfv3sjNzcXYsWMxZMgQDBs2DM8//zzq6+uDo4+IiIiIzDAcvKxZswZXXnll8N+5ubkAgLFjx+Ktt97CzTffjCNHjmDSpEkoLS3FoEGDMG/evKhOvFbLy8tDXl4e/H6/rekQOa1f9qnYUVYnOhtERNIwHLyMGjVKc7r+CRMmYMKECQlnKhHjx4/H+PHjUVNTg6ysLEfTJiIiIudIt7YRERERUTwMXoiIiMhVPBO8cKg0ERFRcvBM8MKh0kRERMnBM8ELERERJQcGL0REROQqDF6IiIjIVTwTvLDDLhERUXLwTPDCDrtERETJwTPBCxERESUHBi9ERETkKgxeiIiIyFUYvBAREZGreCZ44WgjIiKi5OCZ4IWjjYiIiJKDZ4IXIiIiSg4MXoiIiMhVGLwQERGRqzB4ISIiIldh8EJERESu4pnghUOliYiIkoNnghcOlSYiIkoOngleiIiIKDkweCEiIiJXYfBCRERErsLghYiIiFyFwQsRERG5CoMXIiIichXPBC+c54WIiCg5eCZ44TwvREREySFNdAaspigKAKCmpsbyfQeaGjS3aWqoC27XUFeLQFMDWht9uj5rVGtjii37Fa22pgbtAhnwN9Uj0OQXnR1dWhv9aKyvM/17NH59/oT+tmrnj9+XGnV8ampq0FBf65nzouW4onpcRZ7/rY0KAk3HLdtfW1mRiOYG8+edVvqtjT7U1daoblNTU4PjCZx3fkSfw1YJPT/MHN/Y+7a2TE/k2Olh5zVSXVODVH+6pftsu2+33cfj8Sl6tnKRAwcOoFevXqKzQURERAkoKSnBWWedFXcbzwUvgUAAhw4dQseOHeHz+Szdd01NDXr16oWSkhJ06tTJ0n3TSTzOzuBxdgaPs3N4rJ1h13FWFAW1tbXo2bMnUlLi92rxXLNRSkqKZsRmVqdOnXhhOIDH2Rk8zs7gcXYOj7Uz7DjOWVlZurbzTIddIiIiSg4MXoiIiMhVGLwYkJGRgcmTJyMjI0N0VjyNx9kZPM7O4HF2Do+1M2Q4zp7rsEtERETexpoXIiIichUGL0REROQqDF6IiIjIVRi8EBERkasweNEpLy8Pffr0QWZmJoYPH46CggLRWXKVqVOnYujQoejYsSPOOOMMXH/99di+fXvYNo2NjRg/fjy6du2KU089FT/60Y9QVlYWts3+/ftxzTXXoEOHDjjjjDPwwAMPoLW11cmv4irTpk2Dz+fDfffdF3yNx9kaBw8exM9//nN07doV7du3xwUXXIA1a9YE31cUBZMmTUKPHj3Qvn175OTkYOfOnWH7OHr0KG699VZ06tQJnTt3xi9/+UvU1dU5/VWk5ff78ec//xnnnHMO2rdvj29+85v4y1/+Erb2DY9zYhYvXoxrr70WPXv2hM/nw+zZs8Pet+q4btiwASNHjkRmZiZ69eqFp556ypovoJCmDz74QElPT1feeOMNZfPmzcpdd92ldO7cWSkrKxOdNdcYPXq08uabbyqbNm1SioqKlKuvvlrp3bu3UldXF9zm7rvvVnr16qXk5+cra9asUb7zne8ol1xySfD91tZWZcCAAUpOTo6ybt065bPPPlO6deumPPzwwyK+kvQKCgqUPn36KBdeeKFy7733Bl/ncTbv6NGjytlnn63ccccdyqpVq5Q9e/Yon3/+ubJr167gNtOmTVOysrKU2bNnK+vXr1euu+465ZxzzlGOHz8e3OYHP/iBMnDgQGXlypXKkiVLlG9961vKLbfcIuIrSWnKlClK165dlU8//VQpLi5WPvzwQ+XUU09V/va3vwW34XFOzGeffaY88sgjyscff6wAUD755JOw9604rtXV1Up2drZy6623Kps2bVLef/99pX379so//vEP0/ln8KLDsGHDlPHjxwf/7ff7lZ49eypTp04VmCt3Ky8vVwAoixYtUhRFUaqqqpR27dopH374YXCbrVu3KgCUFStWKIpy4mJLSUlRSktLg9u8/PLLSqdOnZSmpiZnv4Dkamtrlb59+yrz589XrrjiimDwwuNsjYceeki57LLLVN8PBAJK9+7dlaeffjr4WlVVlZKRkaG8//77iqIoypYtWxQAyurVq4PbzJ07V/H5fMrBgwfty7yLXHPNNcovfvGLsNduvPFG5dZbb1UUhcfZKpHBi1XH9aWXXlJOO+20sHLjoYceUs4991zTeWazkYbm5mYUFhYiJycn+FpKSgpycnKwYsUKgTlzt+rqagBAly5dAACFhYVoaWkJO87nnXceevfuHTzOK1aswAUXXIDs7OzgNqNHj0ZNTQ02b97sYO7lN378eFxzzTVhxxPgcbbKf//7XwwZMgQ33XQTzjjjDFx00UV49dVXg+8XFxejtLQ07DhnZWVh+PDhYce5c+fOGDJkSHCbnJwcpKSkYNWqVc59GYldcsklyM/Px44dOwAA69evx9KlSzFmzBgAPM52seq4rlixApdffjnS09OD24wePRrbt2/HsWPHTOXRcwszWq2iogJ+vz+sIAeA7OxsbNu2TVCu3C0QCOC+++7DpZdeigEDBgAASktLkZ6ejs6dO4dtm52djdLS0uA2sX6HtvfohA8++ABr167F6tWro97jcbbGnj178PLLLyM3Nxd//OMfsXr1avzud79Deno6xo4dGzxOsY5j6HE+44wzwt5PS0tDly5deJy/NnHiRNTU1OC8885Damoq/H4/pkyZgltvvRUAeJxtYtVxLS0txTnnnBO1j7b3TjvttITzyOCFHDd+/Hhs2rQJS5cuFZ0VzykpKcG9996L+fPnIzMzU3R2PCsQCGDIkCF48sknAQAXXXQRNm3ahBkzZmDs2LGCc+cd//rXv/Duu+/ivffew7e//W0UFRXhvvvuQ8+ePXmckxybjTR069YNqampUaMxysrK0L17d0G5cq8JEybg008/xYIFC3DWWWcFX+/evTuam5tRVVUVtn3oce7evXvM36HtPTrRLFReXo6LL74YaWlpSEtLw6JFi/DCCy8gLS0N2dnZPM4W6NGjB/r37x/22vnnn4/9+/cDOHmc4pUb3bt3R3l5edj7ra2tOHr0KI/z1x544AFMnDgRP/3pT3HBBRfgtttuw+9//3tMnToVAI+zXaw6rnaWJQxeNKSnp2Pw4MHIz88PvhYIBJCfn48RI0YIzJm7KIqCCRMm4JNPPsFXX30VVZU4ePBgtGvXLuw4b9++Hfv37w8e5xEjRmDjxo1hF8z8+fPRqVOnqBtJsvre976HjRs3oqioKPjfkCFDcOuttwb/5nE279JLL40a6r9jxw6cffbZAIBzzjkH3bt3DzvONTU1WLVqVdhxrqqqQmFhYXCbr776CoFAAMOHD3fgW8ivoaEBKSnht6nU1FQEAgEAPM52seq4jhgxAosXL0ZLS0twm/nz5+Pcc8811WQEgEOl9fjggw+UjIwM5a233lK2bNmi/OpXv1I6d+4cNhqD4rvnnnuUrKwsZeHChcrhw4eD/zU0NAS3ufvuu5XevXsrX331lbJmzRplxIgRyogRI4Lvtw3h/f73v68UFRUp8+bNU04//XQO4dUQOtpIUXicrVBQUKCkpaUpU6ZMUXbu3Km8++67SocOHZSZM2cGt5k2bZrSuXNn5T//+Y+yYcMG5Yc//GHMoaYXXXSRsmrVKmXp0qVK3759k34Ib6ixY8cqZ555ZnCo9Mcff6x069ZNefDBB4Pb8Dgnpra2Vlm3bp2ybt06BYAyffp0Zd26dcq+ffsURbHmuFZVVSnZ2dnKbbfdpmzatEn54IMPlA4dOnCotJP+/ve/K71791bS09OVYcOGKStXrhSdJVcBEPO/N998M7jN8ePHld/85jfKaaedpnTo0EG54YYblMOHD4ftZ+/evcqYMWOU9u3bK926dVPuv/9+paWlxeFv4y6RwQuPszX+97//KQMGDFAyMjKU8847T3nllVfC3g8EAsqf//xnJTs7W8nIyFC+973vKdu3bw/bprKyUrnllluUU089VenUqZMybtw4pba21smvIbWamhrl3nvvVXr37q1kZmYq3/jGN5RHHnkkbOgtj3NiFixYELNMHjt2rKIo1h3X9evXK5dddpmSkZGhnHnmmcq0adMsyb9PUUKmKiQiIiKSHPu8EBERkasweCEiIiJXYfBCRERErsLghYiIiFyFwQsRERG5CoMXIiIichUGL0REROQqDF6IiIjIVRi8EJFrjBo1Cvfdd5/obBCRYAxeiIiIyFW4PAARucIdd9yBt99+O+y14uJi9OnTR0yGiEgYBi9E5ArV1dUYM2YMBgwYgMcffxwAcPrppyM1NVVwzojIaWmiM0BEpEdWVhbS09PRoUMHdO/eXXR2iEgg9nkhIiIiV2HwQkRERK7C4IWIXCM9PR1+v190NohIMAYvROQaffr0wapVq7B3715UVFQgEAiIzhIRCcDghYhc4w9/+ANSU1PRv39/nH766di/f7/oLBGRABwqTURERK7CmhciIiJyFQYvRERE5CoMXoiIiMhVGLwQERGRqzB4ISIiIldh8EJERESuwuCFiIiIXIXBCxEREbkKgxciIiJyFQYvRERE5CoMXoiIiMhVGLwQERGRq/w/ipnEXu4/4xEAAAAASUVORK5CYII=", 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", 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", 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", 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", 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", 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", 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", 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", + "image/png": 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", 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G4uJizJkzBxs3bsSZZ56J7OxslJWV4YorrkB9fT0A4MMPP0R+fj4cDgcAoKqqCpIk4Y477lAe87rrrsPPfvazhB43gxEiIgrogY82o8Vqx6sr9yX7UJJOlmW02+xJ+RNtZurFF1+EyWTC119/jYceeginnHIKJkyYgNWrV2Px4sWoqanBRRddBACYPn06WlpasG7dOgDAl19+ieLiYixdulR5vC+//BKzZs3S6qkMiE3PiIgooLpWq/L3po4u5GUYk3g0ydXR5cCoez5Oys/+4f45yDRF/nE9bNgw/PnPfwYA/OlPf8KECRPw4IMPKl9/7rnnUFlZiW3btmH48OEYP348li5dismTJ2Pp0qW4/fbbcd9996G1tRVNTU3YsWMHZs6cqfnvpcbMCBERBaRTtY/YVdeavAOhqEyaNEn5+/r16/HFF18gOztb+TNy5EgAwM6dOwEAM2fOxNKlSyHLMpYtW4bzzjsPxxxzDJYvX44vv/wSFRUVGDZsWEKPmZkRIiIKqMPmUP5+pDU9CiETJcOoxw/3z0naz45GVlaW8vfW1lacc845ePjhh/3uJ2bJzJo1C8899xzWr18Po9GIkSNHYtasWVi6dCkaGhoSnhUBGIwQEVEQnV2eYKSxI/ZW3z2BJElRLZWkiokTJ+Ltt9/GwIEDYTAEPn5RN/K3v/1NCTxmzZqFhx56CA0NDfjVr36V8OPkMg0REQXUoQ5G2nt3ZiRd3XzzzTh69CguvfRSfPfdd9i5cyc+/vhjzJ07V9lBU1BQgLFjx+KVV15RClVnzJiBtWvXYtu2bd2SGWEwQkREAXV2OZW/N/XyzEi6qqiowNdffw2Hw4HTTz8dY8aMwW233Yb8/HzodJ4QYObMmXA4HEowUlhYiFGjRqG8vBwjRoxI+HGmX86JiIi6hXdmhMFIOlBvyRWGDRuGd955J+T3PfbYY3jssce8bquqqtLuwMJgZoSIiPw4nDJsdk9mpLfXjFBiMRghIiI/6uJVgMs0lFgMRoiIyE+HTzDSYbMn6UioN2AwQkREfnwzI+02R5B7EsWPwQgREfnxDUY6emEwwmnFkdHieWIwQkREftTbeoHelRkxGl0zeNrb25N8JOlBPE/ieYsFt/YSEZEfp8/VbnsvqhnR6/XIz89HbW0tACAzMxOSJIX5rt5HlmW0t7ejtrYW+fn50Ouja1uvxmCEiIj82J2uYMSk18HmcPoVtPZ05eXlAKAEJBRcfn6+8nzFisEIERH5cbqDkWyLAUfbbOhyuPqOmAy9Y3VfkiT06dMHpaWl6OrituZgjEZjXBkRgcEIERH5EZmRbLMrGAFcRay9JRgR9Hq9Jh+2FFrvelUREVFERGbEYtTBoHPVS7R39Z66EepeDEaIiMiPw13AqtfpkGFyZQZ6044a6l4MRoiIyI9YptHrgEx3MNIbe41Q92AwQkREfpxOT2Yk0+QqL2RmhBKFwQgREflRMiOSJzPSm3qNUPdiMEJERH48mRGJyzSUcNzaS0REfuyqYMRkYAErJRYzI0RE5McpqzIjRncw0su6sFL3YTBCRER+HF4FrO5gxMqaEUoMBiNERORHXcDKPiOUaAxGiIjIT8ACVi7TUIIwGCEiIj/qAtYMpc8Il2koMRiMEBGRH3UBa4ZRbO11JvOQqAdjMEJERH7UBawWo+ujwmrnMg0lBoMRIiLy41AVsFrcmZHOLmZGKDEYjBARkR8RjOh0EswGZkYosaIORr766iucc845qKiogCRJeO+998J+z9KlSzFx4kSYzWYMHToUL7zwQgyHSkRE3UUUsBp0kpIZsTIzQgkSdTDS1taGcePG4Yknnojo/rt378bZZ5+Nk08+GVVVVbjttttw3XXX4eOPP476YImIqHuot/aKzEgnMyOUIFHPpjnzzDNx5plnRnz/hQsXYtCgQXjkkUcAAMcccwyWL1+Ov/3tb5gzZ060P56IiLqBQ7WbhpkRSrSE14ysWLECs2fP9rptzpw5WLFiRaJ/NBERxchTwCopu2mYGaFESfjU3urqapSVlXndVlZWhubmZnR0dCAjI8Pve6xWK6xWq/Lv5ubmRB8mERGpeBewit00DEYoMVJyN82CBQuQl5en/KmsrEz2IRER9SoOrwJWsZuGyzSUGAkPRsrLy1FTU+N1W01NDXJzcwNmRQBg/vz5aGpqUv7s378/0YdJREQqzIxQd0r4Ms3UqVOxaNEir9s+/fRTTJ06Nej3mM1mmM3mRB8aEREFIQpYDToJZlEz0uWELMuQJCmZh0Y9UNSZkdbWVlRVVaGqqgqAa+tuVVUV9u3bB8CV1bjyyiuV+99www3YtWsXfvvb32LLli148skn8Z///Ae33367Nr8BERFpzruAVa/cbnNwqYa0F3Uwsnr1akyYMAETJkwAAMybNw8TJkzAPffcAwA4fPiwEpgAwKBBg/DRRx/h008/xbhx4/DII4/gX//6F7f1EhGlMK/ZNAZPMMKW8JQIUS/TzJo1C7I7fRdIoO6qs2bNwrp166L9UURElCSeYAQw6iVIEiDLoiW8MbkHRz1OSu6mISKi5FIXsEqSpGRH2PiMEoHBCBER+VFv7QWgKmLljhrSHoMRIiLyI3bT6Nw7Z5TMCHuNUAIwGCEiIj++mRELMyOUQAxGiIjIj0M1tReAqvEZMyOkPQYjRETkR13ACkDVEp6ZEdIegxEiIvLjX8DKzAglDoMRIiLy41vAajawZoQSh8EIERH5UTIjerFMw900lDgMRoiIyI9SMyJ5ByPMjFAiMBghIiI//rtpRAErMyOkPQYjRETkh31GqDsxGCEiIj/+BazuZRpu7aUEYDBCRER+nH4FrO5lGm7tpQRgMEJERH7svgWsymwaZkZIewxGiIjIj18Bq1IzwswIaY/BCBER+fENRjx9RpgZIe0xGCEiIj+igFXvs0zDzAglAoMRIiLy41vAaubWXkogBiNEROTHt4DVbGA7eEocBiNERORHyYzoXB8TbHpGicRghIiI/CiZEfenBDMjlEgMRoiIyI9T9t1Nw8wIJQ6DESIi8uM/m4a7aShxGIwQEZEf/wJWMbWXmRHSHoMRIiLy41/A6q4ZYWaEEoDBCBER+fEvYHX9xeZwKoEKkVYYjBARkR//Ala98jXuqCGtMRghIiI/dt9BeQbPxwXrRkhrDEaIiMiLLMtwJ0aU2TQGvU7ZWcMdNaQ1BiNEROTFoaoJEQWsAHfUUOIwGCEiIi92VTCiikXYa4QShsEIERF5EcWrgKdmBGBmhBKHwQgREXlRZ0bUwQgzI5QoDEaIiMiLuo+IKGAFABMzI5QgDEaIiMiLg5kR6mYMRoiIyEuXwzMkT5JYM0KJx2CEiIi8iGBD3egMYGaEEofBCBERebG5272bfIIRZkYoURiMEBGRFzF7xmzQe93OzAglCoMRIiLyYmVmhLoZgxEiIvLCmhHqbgxGiIjIi7JMY2RmhLoHgxEiIvKiFLDqA2dGrMyMkMYYjBARkZdgBazMjFCiMBghIiIvwbb2smaEEoXBCBEReQlWwCpqSJgZIa0xGCEiIi9BMyMGZkYoMRiMEBGRl6A1I8yMUILEFIw88cQTGDhwICwWC6ZMmYJVq1aFvP9jjz2GESNGICMjA5WVlbj99tvR2dkZ0wETEVFiBW8Hz8wIJUbUwcgbb7yBefPm4d5778XatWsxbtw4zJkzB7W1tQHv/+qrr+KOO+7Avffei82bN+PZZ5/FG2+8gTvvvDPugyciIu2xZoS6W9TByKOPPorrr78ec+fOxahRo7Bw4UJkZmbiueeeC3j/b775BieeeCIuu+wyDBw4EKeffjouvfTSsNkUIiJKjqaOLgBAttngdTtrRihRogpGbDYb1qxZg9mzZ3seQKfD7NmzsWLFioDfM23aNKxZs0YJPnbt2oVFixbhrLPOiuOwiYgoUQ40dAAA+hVkeN3OzAgliiH8XTzq6+vhcDhQVlbmdXtZWRm2bNkS8Hsuu+wy1NfX46STToIsy7Db7bjhhhtCLtNYrVZYrVbl383NzdEcJhERxcETjGR63c7MCCVKwnfTLF26FA8++CCefPJJrF27Fu+88w4++ugj/PGPfwz6PQsWLEBeXp7yp7KyMtGHSUREAGRZxoGGdgAhMiNdzIyQtqLKjBQXF0Ov16Ompsbr9pqaGpSXlwf8nrvvvhtXXHEFrrvuOgDAmDFj0NbWhp///Oe46667oNP5x0Pz58/HvHnzlH83NzczICEi6gYdXQ4l81GSY/b6mtKB1c7MCGkrqsyIyWTCpEmTsGTJEuU2p9OJJUuWYOrUqQG/p7293S/g0OtdL2hZlgN+j9lsRm5urtcfIiJKvMZ2V/GqUS8h0xR4No3N7gx6/iaKRVSZEQCYN28errrqKkyePBnHH388HnvsMbS1tWHu3LkAgCuvvBJ9+/bFggULAADnnHMOHn30UUyYMAFTpkzBjh07cPfdd+Occ85RghIiIkoNYidNXoYRkiR5fU1kRgBXYzT1v4niEXUwcvHFF6Ourg733HMPqqurMX78eCxevFgpat23b59XJuT3v/89JEnC73//exw8eBAlJSU455xz8MADD2j3WxARkSZEZiQvw+j3NXXfEWsXgxHSjiSnQa6tubkZeXl5aGpq4pINEVECLd54GDe8vBaTBhTg7Run+X19yJ2L4HDKWHnnqSjLtSThCCmdRPr5zdk0RESkEMs0+QEyI4AnO2Ll9l7SEIMRIiJStHTaAQA5lsCr+J4dNdzeS9phMEJERAqbw5XxMOoDfzwwM0KJwGCEiIgUXXZXGaHREPjjgZkRSgQGI0REpOhyZ0ZMzIxQN2IwQkREii6nK8gw6KSAXzeLzAhbwpOGGIwQEZEi3DKNkhlhS3jSEIMRIiJS2N2ZEWOQzIiFmRFKAAYjFJO6Fit+9q+VWLBoM5zOlO+bR0QR6op0Nw0zI6QhBiMUk6931GP5jnr886td2HCwKdmHQ0Qa6XJEuJuGmRHSEIMRiklju035+54jbUk8EiLSksiMBC1gZWaEEoDBCMWkqcOu/P1AQ0cSj4SItGR3Z0ZMQTMjrtuZGSEtMRihmIj5FQCw/2h7Eo+EiLRkUzIjwWpGXMs0zIyQlhiMUEzUwUhdizWJR0JEWvIUsAbbTcPMCGmPwQjFRB2MNKjqR4govYllmuC7aZgZIe0xGKGYNKuCkcb2rhD3JKJ0Em5QnsiMWJkZIQ0xGKGYtHd5CliZGSHqOexhlmmYGaFEYDBCMREtowHXkg0bnxH1DF1hlmlYM0KJwGCEYiKK3ADAKQMtnfYQ9yaidBG+AyszI6Q9BiMUEzHZU+BSDVHPoDQ9424a6kYMRigm6mUagMEIUU8RbpnGLNrB2xmMkHYYjFBMxNWT6NLIHTVEPUO4AtYMdzDSYWMwQtphMEIxEdv/SnPMAJgZIeop7O5idH2Q2TSeQXmsGSHtMBihmHT5BSPMjBD1BE45dDCSwam9lAAMRigmYl25NMcCwHuKLxGlL7FLXyeFWaZhMEIaYjBCUXM4ZTjcZ6ziHBMA7/bwRJS+xHs7WDAidtN0dDkgy+wvRNpgMEJRU/cYKcxyLdOwzwhRzyCWaYKs0sBicmVGZNlTO0YULwYjFDWvYCTTCIDBCFFPIZId4WpGAKDTxmCEtMFghKIm6kUAoCDLtUzT0sllGqKeINwyjVGvUwIV1o2QVhiMUNREZkSvk5CX4cqMtFqZGSHqCZRlmmDrNOCOGtIegxGKms3uaYqUYzEA4DINUU8RrmYE8PQaYWaEtMJghKKmHqSVYxE1I1ymIeoJxNZefZBlGoDzaUh7DEYoaqJmxKTXIdvsyoy0Wu3c5kfUA4iaESlEMMJeI6Q1BiMUNe/MiMF9m8yR4kRpTn1BEWw3DQBkmFgzQtpiMEJRE70FjAYJWSYDxAUU60aI0pvIigBhakYMnE9D2mIwQlHrsnsyIzqdhGyTKGJl3QhROlPFIiF304jGZ5zcS1phMEJRE8sxZvfVUbbFUzdCROnLKaszI6FqRjwt4Ym0wGCEouYJRlwvH27vJeoZ1MFI6N00rBkhbTEYoahZ7a4TkNjeJ3bUcJmGKL2pa0ZCxCJsekaaYzBCURNFa2KZxtNrhJkRonSmrhkJtZuGTc9IawxGKGoiM8JlGqKexemMrGbEs0zD3TSkDQYjFDWryIy4T0jqxmdElL68C1iD349Nz0hrDEYoap2iZsSdGclyByNtDEaI0ppDFt1Xw3RgNbnbwXNrL2mEwQhFzZMZ8S5gZWaEKL3JEcylAVTLNHYGI6QNBiMUNb8+I8yMEPUIYjdNqHoRQFXAyswIaYTBCEVNbOcz+yzTtFp5YiJKZ6JmRBfmk4E1I6Q1BiMUNZEZEVdHWWbXf5kZIUpvTvfmmEgzI9xNQ1phMEJR893aqyzT2BiMEKUzkRkJVzPCpmekNQYjFDXfdvDKMg37jBClNfVumlDEbhou05BWYgpGnnjiCQwcOBAWiwVTpkzBqlWrQt6/sbERN998M/r06QOz2Yzhw4dj0aJFMR0wJZ8IOjJM7DNC1JPIIjMSqskIPMXrzIyQVgzRfsMbb7yBefPmYeHChZgyZQoee+wxzJkzB1u3bkVpaanf/W02G0477TSUlpbirbfeQt++fbF3717k5+drcfyUBAca2gEAffMzAXA3DVFP4YiwZkRciHA3DWkl6mDk0UcfxfXXX4+5c+cCABYuXIiPPvoIzz33HO644w6/+z/33HM4evQovvnmGxiNrhkmAwcOjO+oKWlkWcaBhg4AQP9CVzCiND2zOeB0ytCFuaoiotTk2U0Tac0IC1hJG1Et09hsNqxZswazZ8/2PIBOh9mzZ2PFihUBv+eDDz7A1KlTcfPNN6OsrAyjR4/Ggw8+CIeDEXU6qmuxwmp3QicBffItADyZEQBoZ9qWKG15+oyEvp/YTWNzOL0m/RLFKqrMSH19PRwOB8rKyrxuLysrw5YtWwJ+z65du/D555/j8ssvx6JFi7Bjxw7cdNNN6Orqwr333hvwe6xWK6xWq/Lv5ubmaA6TEuhImw0AUJhlglHvimUtRh10kmviZ5vV7hWcEFH6iLQDq8iMAK66kSy+5ylOCd9N43Q6UVpaiqeffhqTJk3CxRdfjLvuugsLFy4M+j0LFixAXl6e8qeysjLRh0kREpN5cyxG5TZJkpSTESf3EqUvz26acAWsno8O7qghLUQVjBQXF0Ov16Ompsbr9pqaGpSXlwf8nj59+mD48OHQ6z2R9DHHHIPq6mrYbLaA3zN//nw0NTUpf/bv3x/NYVICtXR2AQByLN5XQjksYiVKe84Id9PodJISkLCIlbQQVTBiMpkwadIkLFmyRLnN6XRiyZIlmDp1asDvOfHEE7Fjxw44nZ5Cp23btqFPnz4wmUwBv8dsNiM3N9frD6UGsX3XNxjh5F6i9OeMsGYEADJNbAlP2ol6mWbevHl45pln8OKLL2Lz5s248cYb0dbWpuyuufLKKzF//nzl/jfeeCOOHj2KW2+9Fdu2bcNHH32EBx98EDfffLN2vwV1m2b3MoxvXUgWe40QpT1RixrJjrhMk+s9387MCGkg6qqjiy++GHV1dbjnnntQXV2N8ePHY/HixUpR6759+6BTTVmqrKzExx9/jNtvvx1jx45F3759ceutt+J3v/uddr8FdRvPMo3R63a2hCdKf5FO7QU8mZF2vudJAzGVQN9yyy245ZZbAn5t6dKlfrdNnToV3377bSw/ilKMp4DVNzPiOjFxci9R+pIjnE0DqJZpmBkhDXA2DUVFtILPCbJMw5oRovQV6WwawNOFtY3BCGmAwQhFxSaG5Kn6DACe4ITD8ojSl6gZCbebBvDUjHRwmYY0wGCEotLlHl5h1HufrFjASpT+nFHUjGQoNSPMjFD8GIxQVGxKMOL90uEyDVH6i3Q2DQBkMRghDTEYoajYHa6TlW8wwt00ROkv0tk0gHqZhsEIxY/BCEUl/DINT0xE6UrpM8JlGupmDEYoKsGWabLdW3u5TEOUvpzRbO01ss8IaYfBCEVFLNMYWDNC1OM4Y9jay8wIaYHBCEVFLNOYfJZpsjm1lyjtiZqRSLb2igsQBiOkBQYjFJWuoMs0LGAlSneRTu0F1IPy+J6n+DEYoah0cZmGqMdSlmEjCEYyjFymIe0wGKGohNtN0+WQYbXz5ESUjqJZpuHWXtISgxGKit19sjL5ZkZMnvbwbdzeS5SWHFEs03hm0zAbSvFjMEJREbNpfJdpDHodLEbXbVyqIUpPIjNi0IX/aODUXtISgxGKSrBlGgDINhsBcD4NUboSNSMR7aYxcTcNaYfBCEUl2DIN4Gl8xmCEKD15MiORL9N0dDkgu5d3iGLFYISi0hVkmQbg5F6idCcuNiIZlCeWaWQZ6OxyJvS4qOdjMEJRsYVYpuH2XqL05nC6Lzai2NoLsCU8xY/BCEUl9DINgxGidPPJpmqM+P3/8O66A3Bfa0RUM6LTSUrROutGKF4MRihiDqfsWVMOuUzDExNRuvj5S2tgtTtx+xvro8qMACxiJe0wGKGIiZ00QLDdNMyMEKUT9XsaAJrds6X0EWztBdTD8viep/gwGKGIeQcjwXfTMBghSg9H22xe/95d3wYACPD2Doi9RkgrDEYoYuqKebMh+DJNC4MRorRQ12L1+rcnGIk0M8JlGtIGgxGKmJg5YzboIElcpiFKd7UtnV7/3ne0HUDkNSOZYlheF4MRig+DEYqY1d1jJFBWBODWXqJ0U99iC3h7JLtpACDLvTTbzvc8xYnBCEWs0331Y1H1F1Bj0zOi9BLsvRppZoTLNKQVBiMUMSUzYgz8sslRMiM8MRGlgw73BYbv7jh9gN1ygSjLNNxNQ3FiMEIRUzIjhtCZES7TEKUHq/s9XVmQ6XW7PkBNWCDKe56ZEYoTgxGKWLjMSBYH5RGlFZEZ6VfoE4xEuEzD7fykFQYjFDFrmMxINmtGiNKKCEb6F2Z43R5xB1a+50kjDEYoYuEzI55iNqeTI8WJUp3oHdQnLwPq+EMfYdczLs2SVhiMUMTC1YyIzAgAtLGgjSjlicxIlkmPomyzcnukmZFsFq2TRhiMUMTCZUbMBp2y1syTE1Hqs6q26xergpFoC1jZdZnixWCEIiYyI+YgmRFJklg3QpRGRGYkw6RHSY4qGImy6RmXaSheDEYoIpsONeHBRVsAAJYgmRGALeGJ0omoGTEb9CjOMim3GyLsM8L3O2mFwQhF5J21B5W/nzi0OOj9eKVElD7EtN0Mkx6FqmAk8swIM6GkDQYjFJE1exsAAKeMLMXZY/oEvR/XkInSR6ddFKXrUJityoxEXcBqhyxzBx3FjsEIReRgYwcAYN5pwwNO7BWYtiVKHzZ3UbrJoEORKjOii7KA1Sl7lnyIYsFghMKSZRkNba7pnkWqq6dAskwMRojShcPdD8ig06Ewy1PAagwymdtXplEPEbdwqYbiwWCEwmrusMPuPmmp15UDybaINWRu7SXtVTd14tx/LMd5T37NgFcD4n1t0Es4tiIXZoMOw0qzMXVwUUTfr9NJvAAhTRjC34V6uyNtVgCuJZhg23oFLtNQIv13/SF8f6AJAPDF1lr8aGxFko8ovdkdrqUVg05CRX4Gvvv9bGSZDBEXsAKuovVWq52ZEYoLMyMUVkO7a4kmXFYE4LA8Sqx1+xuUv3+9oz6JR9IziMyICD5yLcaoAhGALeFJGwxGKKzG9i4AQEGmMex9s82u+zAYoUTYXtOq/H2b6u8UG1EzYoxwFk0gSjaUIyAoDgxGKKwOVcvocHLcNSMtnV0JPSbqnRo7PK+rXXUMRuJld3hnRmIhakZYJ0bxYDBCYVndW/aiC0Z4lUTaa1IFIw3tXcouL4qN3empGYlVNi9ASAMMRigsZUBeBNv9ci2uZZpmnphIY51dDk9fDPeywuGmzmQeUlpzOmW4V2lgiGOZRrzneQFC8WAwQmFZ3V0azRFkRnIzmBmhxBBZEb1OwpDSbABATTODkViJ4lUgvmUa8Z5v7uAFCMWOwYjGvt11BLMf/RJ/+GBTsg9FM55hWuFfLjkiM8ITE2lMFFLnWgzok2cBAFQzGImZQxWMxLNMw2woaYHBiMZe+nYvdtS24oVv9qCuxZrsw9GEyIyEmtYrqFO2nFVBWhKZkbwMI8py3cEIl2liJupFgMin9AbCOjHSQkzByBNPPIGBAwfCYrFgypQpWLVqVUTf9/rrr0OSJPzkJz+J5cemhS2Hm5W/r9p9NIlHoh1PzUjkBax2p6zswiHSQrt762iWWZUZYTASM7GTBnC1g49VbgazoRS/qF+Bb7zxBubNm4d7770Xa9euxbhx4zBnzhzU1taG/L49e/bg17/+NaZPnx7zwaa6LocTu+rblH9vqW4Oce/0YY1imSbTpFfWn3mlRFrqcnh6YpTncpkmXqJmRJLirBlRlmn4fqfYRR2MPProo7j++usxd+5cjBo1CgsXLkRmZiaee+65oN/jcDhw+eWX47777sPgwYPjOuBU1tjeBfXKhDow8fXtriO45oXvsDvEfVKFGDMeSWZEkiQlO8IrJdJSl8Ozk6bMnRlhAWvstNjWC7CAlbQRVTBis9mwZs0azJ492/MAOh1mz56NFStWBP2++++/H6Wlpbj22mtjP9I00Nju3fNgV13gQEOWZVz34mp8vqUWN768pjsOLS5KZiSCmhHAs1TDKyXSknrcvciMcGtv7LRoeAawgJW0EdWgvPr6ejgcDpSVlXndXlZWhi1btgT8nuXLl+PZZ59FVVVVxD/HarXCavUUfzY3p8dyR0O795vxYEN7wPvVtliVdulbqlvQ2eWIqKFYsigFrBGOFXednDrYBIk0ZXNnRox6CWW5rnH3TR1dKf/+SVVKK/g46kUAV0Ex4JruTRSrhO6maWlpwRVXXIFnnnkGxcXFEX/fggULkJeXp/yprKxM4FFqRwyUG+bugdDcaQ84POpQY4fXv7dWtyT+4OKgFLBGeMJnZoQSoUsJRnTIyzDC6N4BcoRdWGMilmn0ceykATyZkQ5VUzqiaEUVjBQXF0Ov16Ompsbr9pqaGpSXl/vdf+fOndizZw/OOeccGAwGGAwG/Pvf/8YHH3wAg8GAnTt3Bvw58+fPR1NTk/Jn//790Rxm0ohlmn4FGchxD48KlEb2XedO9WCks0vUjESTGWF7aNKWeplGkiQUZbmyI/U9ZAt9dxMFrPHWjIh28ADf8xS7qIIRk8mESZMmYcmSJcptTqcTS5YswdSpU/3uP3LkSGzYsAFVVVXKn3PPPRcnn3wyqqqqgmY8zGYzcnNzvf6kA9GUKT/ThPIQWw99b9sfZDknVVhVHwKR8DQ+Y2aEtKMuYAWA4hwTAKC+lcFILETNSDzbegFXzYmY3MsddBSrqGpGAGDevHm46qqrMHnyZBx//PF47LHH0NbWhrlz5wIArrzySvTt2xcLFiyAxWLB6NGjvb4/Pz8fAPxu7wlEp9IMkx7leRZsr23F4aYOv/vV+lzJHWjwv08qcTijO2kp1fW8SqIgmju7kGnURzUTRb21FwCKs92ZEQYjMRGZkXgLWAFXV9xWq53veYpZ1MHIxRdfjLq6Otxzzz2orq7G+PHjsXjxYqWodd++fdDFGWmnK2WGi0GHirwMAIEzI+021/0GFWdhd30b9h9N7cyII8p0bn6G64q1sZ0nJvL39Fc78eCiLTh7TB88cfnEiL/PN0PnCUZYMxILh9jaG2fNCOBqfHaoqZPZUIpZ1MEIANxyyy245ZZbAn5t6dKlIb/3hRdeiOVHpgX1mraomzgcoA9ChzsYGVaajd31bWmTGYm00C0/0/W7N3XwQ4L8Pf3VbgDARxsO489WO7LMkZ2G1AWsgCcY6SljF7qbZ5lGi8wIt/dSfHpnCiNB1G3TQ7WrFm3Sh5W5J4+2dCpZlVQUbaGbCEYa2nhiIm9tVjuOtHmCh7X7GiL+3i73+8tocL0Oi7NZMxIPe5TLr6Gw8RnFi8GIhtTLNKJDZKDdNCIYqcjPQIZRD1kGDqZwdkSkc/VSpMGIe5mGJ6Ze7aUVe/DvFXu8btt3tN2rS/HO2taIH0/0GTG7MyMlOfHVjGyvacEpf12K11bti+n70522NSPMjFB8GIxoyGb3zHApy3EFI3Ut/sGI2CqbadKjb4GrtuRgY+oGI9GetArEMk07l2l6qyWba3D3+5twz/ubsK3Gs3Xd98o51MgEX77LNCVx1oz87bNt2FXfhvnvbOiVW1LFRYZRg5oRzwgI1oxQbBiMaMiqCkZK3R0ij7TZYHd4NwISNSMZRr3SSTKVU81KAWukNSPuAlbfjrTUeyzfUa/8ffHGauXvvo3wopnNZLO7d9OIAtY4MyObD3uCpKr9jTE9Rjrr0qgdPKCa3NsLgzrSBoMRDakLWAszTTDoJMiy/5WbWKaxGPVpUYSnFLBGuLacn+XpyCiyQNS7qIOMTYealL+LzIioP4pmtozNt8+I+73T2N6lZE2icVTVufX7A00h7tkzeS4yNKgZURodMjNCsWEwoiF1AatOJyknS9+OqyIYyTDqlVRzOgQjkRaw5pgNytVWE+tGeiV1MKLuMCyunEeU5wAADjd2QFYXkYTgKWB1nbbyM4zK6+xIlEs1TqfsdRWvXkrqLUQAp8luGhawUpwYjGhIXcAKQFmC8W1y1imWaUx6VRFe6tZXiJoRXYQFrJIkKcOz2Gukd1IHB/uOtitZQ1FTMLzMFYy02RxoCTC/KZAunwJWnU5CUVZsO2paOu1ehbR7jqR2r59EcLCAlVIIgxEN2XyaMpW4i1hrW0JkRnLSKDMSRaGb2N7byCLWXkm9POeUPVvcRaasLNeiBKyBtr8HokztNXheh8oyZ5TBiG/Gbt+RyGtXegpxkWHUYpmGk3spTgxGNKRepgGgFLHWNnufKNOtZkQU4EZzBZXvPjmxiLX3sTucygedyFyI+UutVtfrIcdiUHrxRFo3IoJ99YenUsQa5fun0d2QL9e9C6ShvavXLSnatSxgZWaE4sRgRENKMGJ0Pa2lOWKZpjPo/eLtldAdoq0ZAYAC0WuEmZFex6oaIz+k1NXYT4w8ULKHep0nGIlwW7vvoDxA3fgsuteZWD6syM9QLgj29bKlGqUdvAbBiGdrL4MRig2DEQ2pT7QAUCqWaVSZEYdTVtaqjTpPMHK03RbTjoDu4JCjv4IqcF8RH2Uw0uuol2iGuoMRMfJAbCc1GXQod89vijgz4vAuYAUQcwF4u821nJBlNmBgUSYAYE8vW6qxa7mbxp0JbbM5/FoZEEWCwYiGRAGrKUQBqzrgMOglFGSaoJMAWfbeaphKYil0S4flJ0qMTlVQPqDQ9UEvlmnUw+4qlGWaCDMj7j4j3pmR2DKL4jgsRh36u4ORfSk+sFJrWs6mEZkRAGiNsCCZSI3BiIZ8C8JKAxSwig92wDUTQq+TUJTiH9yxtI2ONX1O6c/qzoyYjTr0K3B90IvMiE3VRbUsV7w/InvdK31GDOqakdh201gDLBf5bsHv6bRsB2/U65BpctXKsYiVYsFgREMOn4Kw0lzPtl0RhIirEcCzO6Ukxh0B3cGpWlaKZqBWSYyFhZT+Ors8hdz9xLgDsUyjyoyUBCnwDiZgAWucmRGzQa8ERb0tGNGyHTzgKWJt5LRuigGDEQ35TrctyjJBklzZEDGp1O5ULdO475fK23vtqkxOLMs0qVyYS4nRaRe7xXQod2cd6lqtcDhlry6qwQq8g/HMpvHf2httBk5kb0wGnSqD2bteq1q2gwc8dWLcQUexYDCiId9CT4Nep5wsxdWfOjUqSWIUeup+cHsvKzEYofCsXaIeQ4+iLFdNlMMp40ir1bMjxiApQUCg+U2BKFN7Df6ZkYb2yB4j0GMF24Lf03l2yWnzMVDoHgPRkKK1b5TaGIxoKFChZ6lP1iNQC2aRGUnFk6FDjjUz4rlKStVdQpQYnapOxOqAvKbZqtpx5gpU9EHmNwXSFWCZpjArtgJwETCZjeralc6IW9P3BL6Z3HiJ7fypWohPqY3BiEZkWQ4ZjIhUdKCeHanca8ThiC0YKcg0xTw3hNKbVdXUD4CyVFPT3Kmq+5Cg00lKvVQkSzViWUEdjOh1EgrdywPR1Fx5los886G6HHKvWmJQmhlqVDNSqCzT8P1O0WMwohHVagb0kjoYESdikRnx39vv2XmSesGIusZFH+FsGiC+uSGU3jq7PNtmAc97oLq5029HTKRLJLIsB9xNA8RWN6LOjJgMOuW12puKWJXdfxot0zAzQvFgMKIRrw9t1ZWGcrJ1X/nZA1Swp3IBq0MZkucKMKIR69wQSm+i347FPRZB6bejyowowYj7tV8TJjPSpcrQ+c5SiWXnls3hLmDVizlSgSds92TiXKRVASszIxQPBiMaUcUiXkswpbneXVgDzYMoiXFHQHewx1HkFuvcEEpvnaqsAwCU53qyg74t3UsCdCkORF13ZNIHy4xE/jqz+hxjWW5kx9GTxDLmIRQxHJOZEYoFgxGNqDMjOilQzYj3bhr1h7u4Kmvq6FKuKlOFkhmJ4ZXCxme9k2gH78mMqJZpfDIjgboUB2JTzbvxX6aJfjnQd6hlWW5024x7AnuAJeN4KJmRtt5Td0PaYTCikWBbYJVgxJ3+tQfolZCXYVT+nWrFnvFs/yvh9t5eyTMI0nt6dY2qZsS3S3Fd2GUa1/fpJP9lhVhqRvyXi7xru3qDhO2m4TINxYDBiEYcQZqDiWWaulYrZFkO2IJZkqSUneUST8to9hrpnURmRPQDUe+mUQ/KA/wzh8H4BjFqMS3T2L2PsSy3N9aMaNv0zJMZsfWqLdKkDQYjUXjp2714acWegF9TF3pKkn89iNg2aA+wPRFI3Q/ueNaVxdyQVAuwKLE6VU3PAKDMnXVQb5v13U0TLgjwzWSoFcdQAO7bQK00yjk5PYHW7eBFZsTulDksj6JmCH8XAoCPN1Xj7vc2AgD65GVg9qgyr68HK/Q0GXQozDLhaJsNtS2d6HKfAAw+J4BU3VETT8V9qgZYlFhWVTt4wFXYaDLovOs+fJZpxPymYK8zT41HoMxI9LVJnvk5Prt6elFmxNMOXptr0gyTHhlGPTq6HGho60KOe1YNUSSYGYnQ0q21yt/fXnvA7+uhCj1LVR1WHUFOAKnaayRQI7dIeZq5cQ25N/HNjEiSpCyDCCIYKc72zG8KtQuj3ea60s40+V8/iezj0Tar13JpKO02h9fjiSLbuhYrnBE+RrrTejcN4FmqYd0IRYvBSIR+ONyi/H35jnq/E1aoQk91DwOlz4guNTMj76w9gP+uP6Ss+QbqehmpWOeGUHrr9KnHADxLNQCQYdQrPWsMeh2KssLvZGm1uh4zy+wfjBS6B1I65ch7XHiCG1fAJF6rdqfca/pkKNlcjZZpAKCA82koRgxGIrSztlX5e0unHfsb2r2+blfVjPhSTwUNdgJIhQZhq/ccxbz/rMcvXluHd9YeBBB4UmqkCjJjmxtC6c23HTzgyTwArnS+WiRFrO3uGoRss97vawa9DoWZ0dUn+WZGvLuwplZ2MlGUdvAaZkbYhZVixWAkAp1dDqUga2BRJgBg06Fmr/s45eB79kWKuq7F6tnb75NB8XSRTN6b+H8bq5W/P/3VLgDqYCT6l4prbkhkuyWo5xD1HaJmBPAJRow+wUiu9/b3QMT7L9AyDaAaNhlpMGL1zox4P0bvqBtR2sFr1GcE8AQjvSW7RNphMBIBEeUb9RImDigAAOyqa/W6T6DOqoJ6WJ4ytTcFMyPVTZ6T8NaaFmyvaYkrGAFUU4tTrBaGEseztVedGfHUjPhmRkSH1uqmEJkRdyYjO8AyDeC9zHm0zYZLn/4W1724Gh02/yaCsiyjvUtkRvyzN72lC2s89WDBiJqRI8yMUJQYjERABCOFWSYMKMwCAOw94r1MIzIjgYbJlaraYQcrGkuFmpEWn+143+4+qqoZie2EVRbBVS/1LL6D8gDvzEimTzBSkZ8BADjU2BH0MVsDZDLU1FmNjzdVY8WuI/hscw3eClBsbrU7IdpgZKqCG98J2z2dWKbRsoA1Fc5jlJ4YjETgiBKMmDGw2LVMs/do4JqRsJmRIIWu4j6tVjvakrRHv6XT1QdiZHkOAKBqX2PcmZGy3N7X2bK38x2UB3gHIxZjkGCkKXgwIt4TgQpYAXUnVyt2qOq7/rfhcNDHAryXjHrba9VTv6bdx0Bv3CJN2mAwEoGjba6TU1GWCf0L3cHIkTav+zhC9ONQp3/tQZZpcixGZLmv+qqT9EZu7XSdpKcOKQIAbK1p9gw2C9DfIRKerBBPTr2FZ1Be4GUa/8yI6zVyMERmRCzTZAUoYAW8i2DVwcg6VUDt+1gWo86nW3Jvy4xov7W3VLVFmigaDEYiID6kcywGDChyLdPUNFuVtXEAEOe7QG9skbq02p3K7JlAmYYy0Ta7KUnBiPuKcXxlPgBgV12b0qgq3pqR3nK1Sf7t4AHvzIhvL5C+qmWaYG3Ed9W7gv+8jMCNtNTLA+oi1o4uh1dwAvjvpBF623yaeBoaBpNubfW3VDfj/720Gv9dfyjZh9LrMRiJgLqJU0GmETkW10lsn2qpJtQb22LUI9f9PQfcW4IDdZIsV003TYYWd9B1bEUuDDoJ7TYHDjS4rlZjvXpSskK95GqTVFN7VZkR9fLKHp+sYnmeBZLkep8F2hL6/YFGLNteBwA4bVR5wJ9ZqgpGxDKMeMluq/H0CHI6ZfzqzSoA/oFNaW7vqndwOOOrBwtE3fo/1SaQB3Lb61X4eFMNfv3mejS1c9pwMjEYiUCH6uQqSRIGFImlGk8wEq4yXaQv97s/3AMteyQzGHGq5knkZ3qWo7ZUu07kxhiXaTwFrL3jBE+Bt/aqSfB+j5gNeqWL6qFG/9f+O2sPQpaBs8f0waDirICPWaKaji1exxP7u3a+ba32BCP/21iNjQdd2/JP9xnpoA6ce8OgN63bwQPu1v/uLGqqB3XNnV3Y6g5UrXYnvlB12abux2AkAp4rPdfTVVng+qA+0BBFMOI+WYbKjCRzmabV5inqyzYbMLgkG4DnRG6Ks4C1rjXyVt2UvmRZVs2R8a7vePemaRjTNw8Pnz/W7/tEEWuguhGR2Zg5oiTozxXBfpvNoWRXxDZ8dWbkq211yt9vOWWo12P4DrXs6RLRDl6SJFXH6dQORn441Ax1zPn1jvrkHQwxGImE76yNfgWuE6dYwgDCv7F9K/UDZUb65CUvMyLqYkx6HSxGPYaUuK5AxVJUrKncoixXF1aHU8aRttQ+OVH8rKpheL6ZkQn9C/DfX5ykFEir9Q2xvXdbjavmY0RZTtCfm202+BXGKpkRVTBy2P3e+vMFY/0GuYmhlkD61DzEIxHt4AF1k8fUfg59X2sbDjYl6UgIYDASkU6frYqVhcEzI7owmRHB96oRSO7WQpHaznbXtgwu8U6Hx1rAatDrlIZuXKrp+axd6mAk8M6XQMSOGt8PCLvDqQyP7Ou+CAimxOc9NnFAPgBg/9EOZRbNYffjV+QFfqxIWtP3FKLOTcvMCJA+hcDitXbS0GIAwPbaVq9NCYn00oo9OOnhz7FY1fW6t2MwEgHfZRqRGdl/NPLMiO+JMlTNSDKuykSPEdHhUizTCPG0jC7j9t5eQwTuep0U1WsmWK+RVlVPkNwwI+nVAb/FqENpjgUFma7v2VXnKpoVXYbL8yz+D4DetRU92ATxeKXLjpqD7vqkiQMKUJBphMMpey3pJYrN7sTd72/CgYYO/Oat9Rwi6sZgJAJWv2Ua/8yIZ1Be6AJWIVANhjhB1rZEXl9hszuxbHudcuUXqxbV9mUAGOIXjMR+9eQ5OaX2lRLFL9C23kh4aka8P8CaO1yvywyjPmyvG3XAL4Jq8TreWdcKq92hdBn2vTgQSntRB1F7AmpGAM+5LtWzSyLjVppjxrEVeQD8Z44lwr6jnt1kLZ12rD/QmPCfmQ4YjESgwyczIta3mzvtaOpwZRQ8g/KC1Iz4LtME2GlQnG2GXie56isinOXy+/c24IpnV+GCp1b4NXeKhghGxEm8MMuE/EzPlWg8mZHedLXZ23l20kS+RAN43lMHG7wzI83ujF1uRuDOq2rqXiZZPsHIrro2tFs9KfisIG3l0+WqXgvKMo3mNSPp8X4XW8BzLAaMqsgFAGw+nPhgZEet99b2ZdtZOAswGImIb9+ELLNBGTcuTp6im2GwzIjvenegzIheJykV/ZEUsbZa7XhrjWv2xg+Hm/Hu2oNhvyfUYwHwKuobrNpGGU8w4hmEltonJ4qf8l6JMjMigpH6Vu9mgs3uYD9YszM1kbEEPAPbhpS6XsM761qV4XgmvS5oC3RR75CI+qYOm0O5Gk8F9iCjKeKVLtklZcSAyYBhpa6g1bdBXiL47hhbzmAEAIORiARq4qTUjbiXasRVRrAP7fJci9e232ApZ7G993AEH9zba1qgXs15c83+sN8TTKvPMg3gXTcSazt4IPS2TepZArWCj0R+plGZE6MOWpXMSJh6EcDzngQ8U7AHF4tlmjZ0uJcyM4O0lAdUmRGNd4LYHU5c8vQKTHvoc6zafVTTx46F0ykr21q1XqYRy82hBh+mglbVvKMh3RiMiPq86cNchbPrDzR2W+FsKmMwEgHfrb2Aum7E9YazhZlua9DrlK27QODdNK7H9d82HIwothLbcNfsbYi5i6BvAavrcT3BSDwnrL4MRnqNWGtGJEkKuKNG1IzkRpAZqVRlRoqzRWbE9RreXd+KVvcyTWaIQKkkQZmRZdvrsf5AE2x2J/726TZNHzsWXU7Pkq5e42UacZ5r7rR7FSCnmjb36yHbbFDOdbUtViUAThRx4TeqIheFWSZ0OWT80A3LQ6mOwUgERFtj9QnWEzS4MyPKALzgT6n6yi3YyVqcUPf7TAUORAQsU4cUYUhJFpwysHL3kbDfF0iLNVBmxLNME+2Hi5r4vQ82dsDJxmc9mqiv8u35EYlAGbQ2kc2I4PHUr1fxQVNZkAGjXkJnl1O56s0MMvkXUHUM1rgLq/qK+7s9R5XgP1nUBfJGjZdpcixGZfxFKmdHPJOg9cjLMCpFzTsTnB0R9Xm5FiPG9uu+wtlUx2AkAl1K1sPzdFUWereEFzUjoTqVqte0gy17VBaKbcPhgxHRabIwy4xx7uF2mw/HtjVNKWC1BM6MTB1SHNPjAq60rU5y7fypZ+OzHk3s6soK8YEfjKfxmWeJJJqCWPV9RM2IQa/DQPdwy43uplahAhvxgdTlkAPOyYnVXtUOCrtTVlrSJ4s4pwHaDsoT+rrPdamaDZVlWQl0RTZ4aIlnSS+RlJ5OZoPyM3fVJX55KNUxGIlAoIFS4oNaXPHYHOEbCEWSGREzYfZFEIw0tLuDkUwjRvVxVYNvqY7tJOepGfGkw4eUZOH66YPw69OHY0R58O6X4Rj1OqXC3ne3BPUsIiMRS2YkUBdWsa0+0pqlV6+fgnPHVeDmkz2t3kXGRHTYzAgR2JgNeqXeJJK6rUip51gBnsAoWdSZEa1rRgCgb35qv987u5xKvZ3IlIli50TXjbSoghGxjLgrwQFQOogpGHniiScwcOBAWCwWTJkyBatWrQp632eeeQbTp09HQUEBCgoKMHv27JD3T0Viy6z6CmKo+0W0v6EdnV0OJTMSaqCcCDSA4Fd6yjJNQ3vYNHFDmyvVW5Blwsjy+LamKbtpVFe0kiThrrNH4ZZThsX0mGrR1MJQ+lIyI6boMyOBlmlsjuhqUKYNKcbfL53g1UdEXDiIYCRc1sZ3CVYLIssy2T0vZ+OhxAcj3+46EjTDKgrudVLwrtHxCNXePxWoa1lEDdFQVU+aRFLq8ywGZcfirnpmRqIORt544w3MmzcP9957L9auXYtx48Zhzpw5qK0NPPFw6dKluPTSS/HFF19gxYoVqKysxOmnn46DB2PfhtrdPJkRz9NVnG1CXoYRsgzsrm9TAhZjiDf2aaPKcN6Evrj0+P5KJsNXRX6GMk69Lsw2QJEZKcg0YWQfV+Zi79F2ZS00GoEKWLUkTk4MRnq2dpsreMiIo2YkUGYkWMF3JEQwYnMv+YQ7tr4JCJzFh5+Yy5PoOShvrt6PS57+FnMe+ypgV1Fx8aT1tl4h0P/LVKLuqi2CMZGlSHTNiHrnotixeKCho9fvqIn6lfjoo4/i+uuvx9y5czFq1CgsXLgQmZmZeO655wLe/5VXXsFNN92E8ePHY+TIkfjXv/4Fp9OJJUuWxH3w3SVQZkSSJGUXy47aVqU6PVQ/jhyLEY9ePB4LzhsT9GrEZNApczPU7eYDUZZpskwozjajJMcMWfYeDBapQAWsWhpU3H1b5yh5RDAST83IwcYOJSsoakbi2VouPmSEYA3PhERk8cQFwgmDXcHI7vq2mC4aIvXvFXsBuP5//OPzHX5fDzdlPF6pvp1fLKura/xEtnvv0XYlcE0E9Xb14mwTci0GyDKw50jvXqqJ6h1us9mwZs0azJ492/MAOh1mz56NFStWRPQY7e3t6OrqQmFhYXRHmkTB5s4MVe1NV6404mgOJkSaJm716Zp6TJ/Yl2oCFbBqaXiZ67naXpv42Q+UPOIDNpaakbI8MyTJFYCIZQ3xoRDPbi7foY/5maaQ9/fdtq8F8f4aUJSJ4mzXRUOi5qDYHU6vC5JPfqj2C3wSNbFXENmlQ42JaXR4qLEDGw7Enl0SF5gmVcatPNeCLJMeDqeMvTEGBqF2C8qyjA6bA0daXa/tomwTJElSsiO9vW4kqnd4fX09HA4HysrKvG4vKytDdXVk0wd/97vfoaKiwiug8WW1WtHc3Oz1J5m6nIEDDSUYqWv1vLg1eHMrRaxHQgcjvjsNjnEv1cQSjCipQ3P4fg6xGOYe/769ppXbe3swJTMSQ82I2aBXOhCLD7FA2+qjlWsxetWQhOvmqnXNiM3uVN6rOWaj8j7dUp2YYGTPEdeVfYZRj/6FmejscuLTH2q87mOPoOA+HiLLVd3cqfkguB21LZj96Jc45x/L8dH3h2N6jC672P3ok+2Oo/nZvP9UYfjv/4eXVuzx+1qHzYE5j32FY+5ZrASCRVnuxnzuYLm376jp1t00Dz30EF5//XW8++67sFgCT80EgAULFiAvL0/5U1lZ2Y1H6S9cZmRnbauyVU6LzIjYNrw/xMnQ4ZSVF7VIYYs6lB+i3LPebrMr/SEKshITjAwsyoRJr0NHlyNlU7cUPyUzEqLLaSi+6X2rBpkRwNMYEAgfjFSqlmm06DWizkpkmfUY6d6ZtjVBwchh9+Tj/oWZOHdcBQDg080+wYiyTJOYj4CSbDOMetecrRqN28K/8M0eJehd+OXOmB5DLNP4bjgY7r5o2hzl/5vvDzTinbUHYXfK+ONHm/2aTy7fUY9tNZ5gI9diUM7bQ7ppS3Gqi+qVWFxcDL1ej5oa7xd2TU0NysvLQ37vX//6Vzz00EP45JNPMHbs2JD3nT9/PpqampQ/+/fH3uY8XrIsBw9GSlwv3F31bbC6P8zjmeEiiF4jobb3qtc0zT7ByJbqlqiyD/UtrrShxahLWAGrQa9TrgC6Y0w3JYf4kIhlmQZQp/fdnY01qBkBvHvmqAdABtKvIBOS5Co6rW+NrddIh82BV1fuw576NqV41WJ0zcQZEefOt3DE8M68TCNmjigBAHyzo97rnBCoXYGWdDoJffICDz+M13e7G5S/bzjYhNoYBvKJ15Xv+Xq0e2DepigLjFfu8rT4t9mdWLrNe0PHip3ezSibOz0B6hBmRgBEGYyYTCZMmjTJq/hUFKNOnTo16Pf9+c9/xh//+EcsXrwYkydPDvtzzGYzcnNzvf4ki91rP77309W3IANmgw42uxO73WuMWry5xTJNqAJWkb4GPMHIoOIsmAw6tNsc2BtBnxKhrtX1Zi7JMUMKMuhPC8pSDYtYeyzPskqMwUjQzEjsu2kAn2AkI3TNiMW9vAHEXuP0u7e/x53vbsB5T32j9BjJdi+BiszIluoWTbu8Ck2q4YLjK/ORbTagob3Lq8tnoKJ8rQVq7x8vm92pbL0V/WC+2Bp4J2coyu5H32Ckb2wdUdcfaPT699KtdV7/FtkqYZY7SATgVTOSiNdDuoj6cmPevHl45pln8OKLL2Lz5s248cYb0dbWhrlz5wIArrzySsyfP1+5/8MPP4y7774bzz33HAYOHIjq6mpUV1ejtTU9PpDsqk6FvsVeep2n+Ehc5WixBit6jRxu6lDeNL7ESVqvk5SlIYNep5zoornqqnNnRsR6faIMdy9rMTPScymZjBgzhBU+Q9a0KGAFgGlDi5S/R7JjLJ4pri2dXVi0wVXLcLTNhr98stXr5w4tzYZeJ6Gpows1CZgOrA5GjHqdsoNn2Q7PB6RYVo434xRK33ztu7DuO9oOu1NGlkmPn53QHwDw5ba6MN/lL1iN3zF9ciFJrlqXaKYOi+GOV08bqByTurGcmNb82MXj8ZcLxuIP5xyrfG1AUSZ0kmtHY6pPOk6kqF+JF198Mf7617/innvuwfjx41FVVYXFixcrRa379u3D4cOeoqKnnnoKNpsNF1xwAfr06aP8+etf/6rdb5FAdvVAqQCBhqgbEcP0QjU9i1RJjhlmgw5OOfhVhaf/gvfPOyaGFLDoZ1Kc4GBEZEYYjPRc8W7F9e1PITIt8X5ojizPxRUnDMAJgwuVXWehDC31FFxHa/XeBq+M6vr9jQCAIneLeotRj0HuZlebY+yYHIo6GAE802GXbfOMqo83aIyE0oVVw2DkiPtcVZprwYlDXb/Xqt1Ho84oBMuMZJkNyv+baIbXHXW3WZh9TBkyjHocbbN5LbuI5b4+eRZcOLkSA4vVc7/0Sp1gb64bialA4JZbbsEtt9wS8GtLly71+veePXti+REpQ50ZCVQPMrTEu4eBFkOnJElCZWEmdtS2Yv/RDgwoyvK7T7BdBqJSP5oiVtHwLFxhX7xETcu26lbY7M6EXpVRcij9G+IMRg4qu2m0WaYBgD/+ZHTE941nK/pu9wfK6aPKsHZfg/JBJOblAK6lmh21rdha3YKTR5RG/TNCafYJRk5yByNr9jagw+ZAhkmvdLZN5HuwXxRDPyPV6P7d8jNdQ+ZMBh3qW23YVd/mtRQXji3AvDFhRFkOdtW1YXtNC2YOL/H7eiAN7q3opblmjO6bi+/2NOD7A03KBZjIeBTnBL7gG1ychb1H2rGrvlVpjNfb8NMgDPUVTqAVmKE+DZWMBm3WYEVFf7Ai1mAn6VEVrjXPaDIjrQnuMSJUFmYg12KAzeFkv5EeKt5lFVEzUt9qRYfNoVkBa7SGuTMjsSzTiB4Vg0uyMX2Y58OsSJV5FNmZLQkoYvXNjAwuzkJFngU2h1OZ6m2zB/8w1spQd0Cn5a6hRlXXabNBjwnuAaGrdh8N8V3+uuzBM9nRLtE5nLISJBVkmjC2n+uYvnfXkXR2OZQi5uKsIMGI2FFT23szIwxGwrArnVWlgMWdvsGIVu2V+4fZ3qsEI0bvnyfawh9q6lTeuOGop0gmkiRJSoFYsgeFUWLEGzzkZ7q6UgKuTsKiRXa8NSPREkPT6lttUU/vFcXjA4oyMWO4Z9q1ehfPiLLE9Rrx3dEkSZISFC3f7lqqCdSBVGtim2xti1XJHMSr0b1lNt8daE1x18NEHYyE6As1tCy6QLSpowtilUhkbADge/c5Tvz/AIJf8ImsTm+eUcNgJAyxTBOs6nxgcaZXxkSrK43KMNN7lbV0n5+XazEqW4MjXfPsrmAEgCoYSW4jO0oM8SEXa/AgSRKOdWf3NhxsQnuXaC8f/zJNNDJNBqX5WbTZkQb3B2ZxthkzVJmRUlWKXlw07Kxr1bz1uFJPphrGKZZqlu9wBSOhMgNayTZ7nsNYRlQEIp5b0UV3yiBXJ++Vu44E/Z5AgtWMAJ6l9+21rRHVoohgNcdigFGvwxj3Oe6HQ83ocjiV4ZEmgy7o54in8RkzIxSEWKYJVgtiNui9pvFqtW9faUkdbpnG6H9coog10roRsUwTyzyRaIlgxHcrHPUMnsLI2IOH0X09vR7areIqP/GvTV/DlexFdIFzS4eYPWJAUbYZ/77mePxkfAXOcTcgA1zLUTlmA7ocsuZXw4HqyU4cWgxJcmViaps7uyUzAkDzBm9NHa4PfpFlmtA/H3qdhENNncqOlkiEqhkZXJIFneTKeETSZ6bDp+vwwKIs5JgNsNqd2F7Tqnw9VO8dEYyIKfC9EYORMEQrY32IIEMUKQHadGAF1Ms04XbT+L/Ao10KaU3wkDy1Se4R6psONStXDNRzaFHjIa4s1+1rVD40Y2kvH69Yxys0K1NZXR+YM4aX4LFLJnjtVpMkScmObNI4Sxioa21hlgnHuht6Ld9Rr5rNkrg+I4A6oNMmGGmzeg9izDQZlCWvqv0NQb/PV6jMiMXo2d0SSW1bp90zARhwNXwbI5ZqDjQq3a0zjcGDkZJsM3LcA/P2hhkD0lMxGAlDGSgVohZksGqblkhLxksstRxtsykFaWqhZnaIk3mkY8rbunGZpm9+BiryLHA4ZVTta0z4z6PuE2hEQSxEMK1O7cfaXj4eo/p40u3RELvTwgX3Y/rmA4j8fRqpYMXtJw311I10x9ZeABhRru12fpE1sKgywuP75wNwBa+R8gTNgYOxaIpYPcfkeb7Fa/iHw81KzYglRGbEe2Be76wbYTAShjKNN0QzM/WWMnVgEo8ci1FZY94Z4MUZamaHeCPsUrWiDqXF2n3LNAAwaaBrnfe7PZFfyVDqU9c+xBOM9M3PQHmuZ3aVyaBL6K6PYEZVeMYrRDrszWp3KO/N3DBb5cf0cz2+9sGI+0LFZwn3hMGu913V/kblGBP9vCrBiEbdZjvFcFBVoCV21Kxz93OJRKjMCODpMxNZMOJfo6POqkWyTAMAQ9yfHbHs4OoJGIyEIXbThBq1fd7Evvh/MwfjxWuO17SdunoQn69Q/RdKcsyoyLNAliObsRDpm0Urxw10LdWs3htdBTx5tFntuOGlNTj3H8vx3Z7UeB69gpE4PuQkScJx7sJEAMjqptelrwGFmcg06WG1O7GrPrLCwhbVzJFwmUaRGfnhULOmk22DNUQco7pIEbtbEr1lenBxNox6CS1We8jxFpEKlIWY4M6MbDjQFPHzaAsbjLiLWCNoeqcck+q5FFm1zYdb0OZejs40hn49iOV+rYp90w2DkTDsQYbkqRn0Osw/85iIG+RESrwhdgTIjNhCFLACnuxIJFddNg0bS0Vi8gDXB826fY1eLZMpci98sweLN1Xj+wNNuOXVtSlR9GZ1eI4h3kLu41XBSDKKVwHX2r+os6iK8KpbNBzLMRvCzn0ZXJyFLJMeHV0OTTtvBrtQKco2K+32xe+T6MyIyaBTsiMbD8WfAbIG2Oo9uDgbORYDOrocEX+Qd4XpszIsxLnXl3jvZaiC5sElWTDpdWi12pVpvRlhgmqRiYum82tPwmAkjHBbexMpdGYk8NZeQex1jyYYSdQET18jynOQYzag1WqPeqcCufxvo2fkQk2zFUs2Rz8sTGvq4tV4M4THD/QEI93dY0Rtorvgeu3eyJYURX1AJEueOp2EY/t6Ch21ErKezH1eWLOvIeh9tBZtDVsoItBSZ0Z0OgnjxVJNhHUj4cYMDHGfe+tarGH7NQVaOjLqdRhe7noM8doJl3kWHap317f1yuJ+BiNheJqedf9TJfa7B1pD9PQSCHxcY5QugOFPANY4W3hHS6+TMMF9kl/NupGoNXd6JrD+ZLxru+iSzTXJPCQAqgybBu+VYapmgpHUPSWKyOKtjjAYCVavEcxYjZsAyrIcctu/CAxE+UZ3nNe0bHQYqIAV8NSNRJrBEnUevo8jZJsNEfdrsgY5JtFiQSxHh8uMlOSYUZJjhiwnphleqmMwEoZYpklmZmTfUf+95+FmdoiTzu76toC7cQRZllXb/Lrv5XCcOxhJlXqHdOIaNQ6U5ZpxyfGuyaVfbK1N+pJXvHNp1HQ6CdecOAgAcNHkyrgfL1ZiK/qO2taIuoiKi4RIa2bG+HTrjFeXQ1YCjVDb/oXueM+PrhDZn8hrOoLxBBHev5tnR01kQaOyHTfE0vSxEe6mClTHAniWXcQxR7I9XWRHot1O3hMwGAlD2U2ThMxISY5r77lTBvYc8V5TDpWKBVx9BUSvkg0hsiN2p+rkFUejqmhNGujJjGhRZd+biNknAwqzMHlAAXItBjS0d0XVZyERgn1QxOqec0Zh031z8Os5IzR5vFgUZpkwxN2QamUELcdFljHSzIi6W6cWRazivACE3vYvdEdmZFRFLvIzjWjq6IroOQzFt6eHML7SdT7ZWRf64kuwBqjz8CXqhTaFDUYCv+59p0OrxwEEI74n2u3kPQGDkTC0TD1HS5IkTxGrz1JNJNNMRd1IqG6n6h0QWg35i8T4ynwYdBKqmzs1HTHeG4imSAOKMmHQ6zDdXTj95da6bjuGls4uXLjwG5z992XKiVPsygqXjo5Gd203D2XaEFcr9RU768PeN9r+HV7dOqPc0vnVtjrc9e4G7Fbt9LGq3s+BgpGibLPXPK3uyIwY9TqccWw5AODD7w/F9VieWUXer7HCLBMGFLkuvtZHsFQTbpkGAI4VnYDDFN52BMmM+AYjkUxF781FrAxGwlD2o3fjB7Wa6C7om7YLVzMCAOPcdSOh1lG12o4ZrUyTQSneWxPhejy5iHHk5e6dEbPcwcjSbd0XjDzz1S58t6cBmw4149dvrocsy+joctV2ZGiUGUkVJw51DWP7Zmf4+SeRXCSo6XSe4ZGhMpi+9h1px9wXvsMrK/fhqudWKecpawRFxOpdf2IoYaKJVviLNlTHvPNLlmVVTw//c9X4IHUjSzbXYNqCJfj1m+uVn+3Zjhv8/5PYnruzri3kMQerY8nLMCpTqAHPPJ1QRDZm82Ftt3unAwYjYXRXp8JgxAe2b6owkoFkYinkuz1H4QxSTyAeRyd1/1LUZNaNxKS503tE/MwRrg+X7w80ob7V2i3H8Jlq984Ph5uxZm8DOmyu15KWmZFUcMLgIkiSa3BabXPo+SextMMfE8XON+G9qoNKjdC+o+3473pXxiGSKccnDfVMEj5OtWspkU4YXIQ+eRY0dXThsxiLrdVZn0BLgaKIVV1sLMsy7np3Iw41deKtNQfwyCdbAaiXe4K/VstyzSjKMsHhlEPO1hGZkUBBuMh0AJ5Jw6EMcmfKOrucypbg3oLBSBhaFuXFQkTKvlNurUHSlWpj+uYhy6RHY3sXNgfZQqvFLJFYHTeQO2piIXpZiA6fpTkW5XXyVTdkR1qtdiWNfLI7EHp15T5lO2JPy4zkZ5qUWgsx9TaYcFtGAxGPHU0Rq1iKKHF3af7Xst0AoAwWDNVwbdrQIkwbUoTzJvRFRb424yvC0esknDexLwDgnbUHY3oMr2AkwHlvymBXBmv1nqNKpuhwUyeqVQHkiyv2oqHNFjLDIkiSpAQToXqkiEGj2QHa/6uXaiKpGfGda9ObMBhxa+roUmZKqNm6qW1yMMeU50InAfWtVq+rMmsEQYRRr1M6Wa4IkmIO14kwkSa5t01urWmJqOiMXJqUqbCek9vJI0oBoFv6jVQ3uWp8cswG3HzyUADApz/UKAPiuquTb3c60Z1NCBeMeBoIRv5+ErVdmw81R7yEITKlD503Bka9hB8ON2NrtarbZ4j/B2aDHq9efwIevXh8xMeohR+PdwUjy3fUx9RHQ3yPQScF7Ik0oiwHBZlGtNscyge5qLUbUpKFYytyYbM78daaA0F3wPgS/2++3x8iGAkx22vGME8WKpJlGtfPzAcArI9i2a4nYDAC13jrkx7+HFMXfI41Pi3Kk50ZyTDpldk36rXQcLtphGlDXFcLQYORGE6eWinJMWNgUSZkGVgb4ZY88kyFzc3wnPxmjyoDACzdWuu1oyIRqptcS0FleRZM7F+AkhwzWqx2fL7FlX7vaZkRwLO08dW2eq86K1+RXCT46l+YifJcC2wOZ0RLlk6njDr3ctzovnmY5Q5EP1h/UPnAToXCX1/DSrPRryADNrsTy7eHLwb2pQz0tBgC1sPodBJOGOx9vhND54aWZuNnJwwAALyycm9ENSMAMMG9S2ddiJ1qoQaNTh5YiN+eMQJXTR2g7MoKZxwzI73XKyv3oqXTjlarHXe8vcFrq2lXEj+sBZHd+HaX50QValCe2tTBrpPoqt1HAxZEJbsmZrJ7zXoNl2oi1hwgMzK2bx5Kc8xoszmCBp5aqXFn6MpzLdDpJJzuDoS+3uH6uT2tZgQAJg90BV31rVa8s/ZA0PvFMlpBkiRMd19BL4vgQ7qxo0upFynMMuFcd3HoR98fRqu1e+dMRUOSJMw+xvVa+XxL9Bk8MfcnVL+OqeLia5frtXi03fVeKckx48fjK5BjNmDPkXbUt7p6xoR7rYr+JdtrW5VaLb/jCjP1/KZZQ3Hfj0dH3JV4rLv2ZWt1S0qMeeguDEbgvad7e22r14d+MpcxBJHd+Ea1tdAaYFJkIKMqcpFrMaDFasfGAHvXPbuFkhSMsIg1ar4FrIDrqlBkRz79IbHdWGtaXMFImXuy7mnunyv0xMyI2aDH/5sxGADwjy92KO8bX7FmGsX27EhqfkSRcn6mEUa9DiePLIVJr8OeI+343p09jaTBVjKcMtKVxfl8S23Qovpg2tyBVk6A2gxhqlI30gCr3aEE7vkZJmSaDErdihBqay8AFGeb0b/Qlb0NtlQTqmYkFhV5FhRnm2B3ypp15k0HvT4YcTplpfWu+GB8bdU+5evJzhwAUFKPW6pbcMR9IuqMcJlGr5OUwq5AV8zJ/v1EZqRqf2PI9De52B1OpfjO90pMBAWfba6J+kQfjSb31WaBuyDvhMFFXgFIT8yMAMDlUwagONuMAw0d+HhTdcD7RLp86uvEIZ73eG1L6B07IhgpynLVIGSbDcr24/eqXMWhmSm4TAMAUwYXItOkR22LNWwzMcBVH/Xaqn3YUduKVqvrdRdqCWpoaTaKs82w2p2o2teozJURgfvl7qUaIdwyDeCZCqzu7lrb3Il5b1Thb59uQ4P7Z4Sb0hwpSZKUXU6JznKmkl4fjOxvaEer1Q6TQYc7zz4GAPDxpmqlmNWW5MwB4IrOR7onX4qsTah1Sl/iakGkLtW6ey6NryElWSjINMJqd4ZszkYuobY3ThtShCyTHjXNVk2GkgXT5lOXYDHqlQ9DoOcGIxkmPS6c3A+Aa0kkkFh3pxVlmzHa3WTr6zBFskfcSwxF2WbltjnupmJi+SHbnJr/D8wGvbIktWRL6Axel8OJi/+5AvPf2YCz/74Mq3a7goFQ5zxJknDCYPcH+a4jSrF3njtwHu4uchUi2eEi+peo69rufHcj3ll3EI8v2Y4ud5durYIRAJjmrlH6OoJGez1Frw9GxBLNyPIcTKjMx5CSLFjtTize6LrySXbmQBBdIJfvcKVxRcoykkI1sY763e6jftmHZG7tBVwnj5Pdqdv31oXf8ud0yvjH59tx7/sbe2XnVnUw4vv/zGzQKz1HYu3lEAnPa8/zgXfWmD7K30Wjvp7oR2Ndv+fnW2oDDvCzxnG+OGmo6//dsm2hP4DEz1XXDJ09tg+yVEFgZoou0wDAqSNdGbxwO7++3XVEyVpb7U4897Vr+3K4D/2pqqL9xg7/Jc0nLp+IgkwjHr1oXER1HGJY4nd7GtDlcMLucHotmQtaLdMAnkzZ2r2NvWaCL4MRd7+EUX1yIUkSfjrBtab4fpWriVAyhsgFIj5kPv2hFnaHU3V1Gv4KaERZDgqzTOjocvhVaKdCsHX+RNfV5n/XHwpbsPXKqn346yfb8OKKvbjsmW+VDFFvIZYBjHop4PDG07qhbkQ85+pA+KwxfTCmbx5OGFyo7O7oiUb1ycWgYtcFS6BJyfEE96Iz6udba4PWpABAu82/SDXHYsRPVfUQqVjAKpw8shSS5GryVt0UfElK1M/MHF7iFWiFC0bEhdu6fY3K46sbjk0bUox195yO89znnXCOrchFQaYRrVY71u9vxPbaVrTbHMgxG/CzE1yDKs+b0DeqouVwBhVnoX9hJmwOZ9AlwZ6GwYg7MyKa04i98F/vrEdNc2dKfFgDrqWWXIsB9a1WLN9Rrwy3yzFH1khHpC59W1p3RDAwKtGmDi5CRZ4FzZ32sFf0b63x7GTYe6Qdf/l4a6IPL6UohctBTnwnjyiFXidhS3UL9h9tT8gxKIGw6urbYtTjv784Ca//fGpSJlx3F0mScLY7CxRoqUa8n2IJBo4bWICiLBMa27tC1gp0BGkud+XUgcrfJ3dTZ9VYlOSYlaWPUO/3XXWumTunjSrDjbOGKLfnZ4U+5w0synRtIXY4cdgdjBRmxd72XqeTlGWTZdvrccidkR1YnIX7zh2NV6+bgocvGBvz4wciSZJykfbGd/s1fexU1euDEVFEJTrtVRZmYvKAAsgy8EHVoaT3GRFMBp2yLU4U2Oqk8NXgwtQgRaydIVoZdxedTlKu6t5eE3zbZIfNoXSe/OuF4wC4On+GK/jrScJt6c7PNCmdbT9JUHakNYolwp7oR+NcwcjSbXV+2z3blWGB0T83Br0OZ4x21X4Eq0nx/hne79nhZTn4ywVj8dB5Y7zmz6SiSDJ4+xtcwXT/wkxcc9Ig9C/MRK7FgEuO6x/ysSVJwgyf31/McYrVdFXTOzEbqjjbBL07UEnEbssLJveDJLnqBPf6TG3viXp1MFLb7GoVrJNc6VfhJ+6lmnfXHYTN7kpBJDsYAaCkFT/e5HoDZ5kDN/8JZKo7dblmX4PXUogyaTXJ2zHFVcBX2+uDBhcH3CenHIsB50/si4n982FzOPHiN3u66zCTLpLdGqeNcn2gffpDYtK77WKZJoWXAhJpRFkORpTlwGZ34l2f1uYdAZZQoiGyLh//UB10qSbQMo1w4eRKXHJ86A/rVCB606zYeSRg7Y0sy9h/1JWBqCzMRKbJgEW3TsdXvz0Zg4rDNw+bMcwTjGSZ9MixhM8gh3KSu+i2an+jMiVZtOJPlL75GZju/j3eXB38Iq2nSP4nbBKJdrtDS7O9rvLOHtNHabG84WAjgOT2GRGmDSlSxmQD0VVvDynJQkmOGTa702tKrjL+OskfLINLsjGxfz4cThnvrws8ZnzfUc+VkiRJ+PkMV+r2lZX7lA+Bnk5kRkK1sRYn+u/2NOBom03zYwhUM9KbSJKEy921Ai99u9erSWK7mFwc4/vp+EGFKM52LdUEmxLcGcdSUKoYUpKNQcVZsDmcWLrVv5C1udOunJv6uLMa2WZDxC3VZwz3tGF3yPFvc+9XkIkhJVlwOGVlqbg4O7HBCABcPLkSAPDG6v09vgFa8j9hk0gUc4pZAEJBlklZEqlpdqXkUiEzotNJ+NkUzz75aD4MJElSUrcfbfCkgEXPimRnRgDg/Emu7Mjbaw94neAFUQNRWeAKyE4bVYb+hZlobO/C2yG6YvYk4oQU6vVYWZiJMX3z4HDK+KAqtqFkobTZ/HfT9DY/ndAXmSY9dtS2YuVuT8M+JWsR4/vJoNcp23SDdXqNZykoVUiShDPdS1IfVPlffIhmZWaDLuz8mEAyTQZcNdV1rjz1mLIw947M6e7/L0fcAX53BCOnjSpD3/wM1LVY8fzXexL+85Ip+Z+wSSQyI2IWgNpF7ohU6Jsf35qjVi46znNckYykVvuJuzh30YbDSmFuKtSMCD8aWwGTQYct1S0BGyKJ1s7FOa6rI71OwjUnDgQAPLd8d0IbfaWKSDvvni9qcGKckBqM0ykrPXiyIyie7qlyLEal2P3lb/cqt3uWaWIPFERNxEffH8bhJv/t6+0psrQaL/H8Ld1apzTSE0QtTm6U5zi1P5x7LN68YSoe/OmY2A9SRQSJQv/CzCD31I7JoMO804YDAP751c4evc23VwcjTqcMg07yy4wAwPRhxSjO9qQER5bn+t0nGfIyjLjnR6MwsjwHC86L7k02dUgRSnPMaGzvwv82urIjHUGK4ZIhL8OoFLYFynQEmsly4eRK5FgM2FXfhi8CpHt7mkhnEp07vi+MegkbDjZhq7tXgxZarHaImC+ShlE9mdjWuXhjtVLnFKy4NBpj+uVhyqBC2J0ynlu+2+/rHV09YzryiPIcjCzPgc3hxOJN3gW7zR2il0rsQZ3oZJoXR0CjNrZvHspzPRelgyIcfBevn0zoiwFFrgxwT95Z06uDkZevm4KN983B6L7+mRGDXod/XjEZJr0OkwYUpNT6+DUnDcLi22ZgWJTNpfQ6CZe7l3meWbYLsix7akZS5CrrAnch6wdVh/wK+JoDNDDKMhtwmbtg75llu7rpKJMn0nbjhVkmnOzu9/HSt3s0+/mivXaGUZ8yr5lkObYiDxP758PulPEf94dEvAWswg0zPfVQvnU/WgQ8qeLc8a4hf74fslpkRrSm03kaNAKe5eJE0+sk/Nw9F+lfy3aH7EGTznp1MAK4PoSD9UWYNKAAX/xmFl6Ye1w3H1XiXDF1AMwGHTYebMaKnUc8fUZS5INl+rBilOSYcaTNhqVbvYeGNQUIRgDgqmkDYdBJ+HbXUWXrb09ljWIq7DUnDQIA/Gf1gbi2P/93/SHc+PIaPP3VTmUuSkEvz4oIYiz901/twp76NqUVQLzByKwRJRjdNxftNgf+vWKP19faU3gyb7QumNQPJr0Oa/c1YrVqWGagLGgqmH/WSPx4fAXmnTa8W+sIz5/YD8XZZhxs7MDzX/tny3qCXh+MhNM3PyPubWGppDDLpMzX+MN/N3mudE2p8VIw6HX4iftq6T+rA18t+QYjFfkZyhXWE1/s6Iaj9Djc1IGt1S0BC24TweoOHs0R9JeZMqjQtf3Z7sSzy2I7gX21rQ6/eG0d/rexGg8u2oIbXl4LAMiLcFdDT3fOuAqMq8xHc6cdN7y8Rrk93qyFerfYy9/u9dpJIWp2Uu2DOhalORacP8lVO/LXT7Yq76Nm9yRcrZZYtJJrMeLxSybgl6cO69afazHq8dszRgAA/vbp9h45CiM1PoGoW9166nAUZ5uxraYV3+1xbfONZHpld7nYXaT72eYar2Y/IjMSKHV748wh0EmuRl+rVLsbEmnxxsOY/vAXmPPYV7jh5TXKEkoidYqtvRH8/5IkCTefPBQA8OKKPTGdwMRV2LEVudDrJKXhEzMjLka9Dv+4dAIsRp0yRyXLpNekY/OZo8vRJ8+C+lYb/rves+NEfFCn0hJGPG6aNRRmgw7f7jqq7PRrcl8k5WakzvJ4sl04qR+OH1iIji4H7n1/U7IPR3MMRnqhkhwzHr1onNdtld1QGR6poaU5mDG8BLIM/PMrTx1IsGUaABhWloOL3bsQ7v9wU8J31tgdTvzhgx9gd/+cjzfV4LbXq2BP8Hqu0nAswm21p4wsxfGDCtHZ5cQDH/0Q1c9yOGWl18WjF43HXWcdo3ytIj8jqsfqySoLM72KyWePKou4GWEoRr0OV00bCAB4dvluyLIMu8OpGpTXMz6oKwszlXbvD3y0Ge02O+rcy4El2amxizEVSJKEB346GgadhM821+CTHjazhsFILzVjeImyD78wy+TVgTYV3OQ+Ob22ah/W7WuA0ykro9OD7e//1enDkWM2YOPBZryV4L4ja/Y2oLq5EwWZRjx3tavQ+X8bq/Hzl9YktAFbW5RbRyVJwh/OORZ6nYRFG6rxvw3B24z7OtjQAavdCZNBh6Gl2bh62kCcPbYPKvIsuMWdcSGXn07oh7dvnIarpw3E/DOPCf8NEbr0uP7IMOqxpboFH2047NWttCctH98wcwj6FWTgcFMnnvxip5KBS3SX03QzrCxHKWa9890N2FXXGvL+LZ1dcKRJywMGI73Y7380CnecORL/uHQCdCk23OyEwUU4b0JfyDIw/50NqG2xwu6UIUnw2nKtVpxtxi9OdX1I/uXjrQHbTGtFTHuePLAQp4wswxOXT4TZoMPnW2px+xtVCcvMtNuib8U+qiIX1013FbPe+noVlm2vC/MdLttrXcsOg4uzoNdJ0OkkPHHZRHwz/1QMjKAld28zaUAB/nDusXHPQVHLyzQqHz5/+OAHpUV6hlGfEo0YtWIx6vH7s0cBcBUDi4wcgxF/vzhlGI7pk4v6Vht+9q+VypgMNVmW8bu3vseYP3yCKQ9+hvv+uwk1zak9w6vnvJopaka9DjfMHKJMpEw1d519DAoyjdhS3YIHF20GABRlmWAIsR5/9bRBGFiUiboWa0KLWbccdn1QH1Pu2l592qgy/Pua42HS67B4UzV+//7GhCzZtImdFFFuNf/VaSNw5uhy2BxO3PTKWuwMc0UFAIfcE0+7o7kTBXfTyUMwpCQL9a1W3Pyqq4C4J9ZSzDm2DDOGl8DmcCrbl0sZjPjJMOnx0rXHY3BJFg41deJn/1rpt1tuxc4jeMO9AaC+1Ybnv96DmX/5IuQAxmRjMEIpqyjbjLvcV0sfuAv4SnJCX3WaDDrle575ahe+2VGfkGMTE0XVjY+mDC7Cwxe4agdeXbkPP3nya2WollZiyYwAruflsUvGY/KAArR02nHdi6v9ul76OupeFisKkomi7mE26PHnC8bBoJOU+UyptstEC5Ik4bGLx2OwO+uWZdIzAxdEcbYZr1w3Bf0KMrDnSDuu+NcqNKj60fxvo6ue5LyJffH81cdh0oACdHY5cft/qrBmb/cU+EeLwQiltPMn9lUmmQLA4Ai6Hs4+phTnjquA3Snjun+vxhdbtO/MGqx+5acT+mHhzyYh1+KqXbnk6RXYo2FAIjIjsTThMxv0WHjFJPTNz8Du+jbc8trakNmbo22udfvCLAYjyTZpQAH+cdkEpSfSbI3mraSawiwTXv/5Cbhp1hC8dN2UHhl0aaVPXgZeuW4KSnPM2FrTgsv/tRLV7mzmlmrXMvLM4SU4eWQp/vP/puK0UWWw2Z249sXV2FGrXVdmrTAYoZQmSRL+euE4nD+xHyb0z8fv5oyM6Hv+fMFYTB9WjHabA9f9ezVeXblP0+MSzb8CFdOeMbocn82bieFl2ahptuLSZ77FpkNNmvxcJTMS45C64mwznr5yEjKMeizbXo8H3MtfgYhZQIVZTJWngjNG98G7N03DnWeN7PY+F92pNNeC354xEhP7FyT7UFLegKIsvHLdFBRlmfDD4Wac/9Q3ONDQjm01rmXYoaXZAFxdXB+/ZDzGVeajsb0LVzy7KuV6lTAYoZSXYdLjkYvG4d2bTkT/osjqFyxGPZ67+jhcMKkfHE4Zd767AX9evEWTwlK7w4mj7aF39pTmWvDKdSdgSEkWDjd14qdPfqPJVrxod9MEcmxFHv52sWtr9/Nf78HrqwIHap7MCK9OU8XYfvn4+Ywhvb4VP3kMK8vBuzediEHFWTjY2IHpf/4CTR1dMOgkDCnJVu6XaTLg+auPU85JP/vXSlSlUMdqBiPUYxn1OvzlgrG41X0V+eTSnbj9P1VxNydraO+CLAOSFHoJoyTHjLdumIaTR5TAZnfixlfW4q010W057rA58I/Pt+NX/1mPd9cdUNaF420FfsboPrh9tmsa6J3vbgiYORJLUcyMEKW2/kWZeO36EzCgKBOiGfS4yny/oLUwy4SXrp2CijwLdte34adPfo3fv7dB6eGUTAxGqEeTJAm3nzYcf75gLAw6Ce9XHcIlT3+LtfsagrZwtzuc+OyHGiz8cifu/+8P+Mfn271GuYt12eJsc9C5RkJBlgnPXDlZydD8+s31eDbAJNZAZFnGja+swV8/2Ya31x7A7W+sxxF3MKLFDpdfnjoUlxxXCafsCkgeXLTZK1A75E7j9tFwqyoRJUZ5ngWvXn8CBrmLfn80tk/A+1XkZ+CDX5yktE54+dt9OPWRL/F+1cFuG2sRiCQn86dHqLm5GXl5eWhqakJubmo156L0sWx7HW56eS1a3P1HxlfmY/6ZIzFlcJFyH1mWccur65S21ILJoMP10wfhxllD8dW2Otz0ylpM7J+Pd246MaKf7XTKeHDRZvzLHYjMGlGCa04chJOGFgft8bJmbwPOf+obGPWuacvvVx1EQ3sXpg8rxkvXTonlKfAjyzL+9tl2/H3JdgDAiLIcPHLROAwoysSYP3wCANh43xxkp9DUaiIKzu5worbFGlGX5G921uP3723ErjpXkf2fzx+Li9zjOLQS6ec3gxHqVQ42duCRj7di0cbD6Oxy7SQ5dWQpfnfmSAwvy1ECAJ0E/GhsBUpzzKja34jVe10zfEpyzMixGLCrrg0/Hl+Bxy+ZEPHPlmUZC7/chUc+2aq0ke9XkIGLJ1fiouMqUZbrnYF45JOt+L/Pdyg/p81qxxdba3H8wEKU5mqbrVi8sRp3vbsBR9ps0OskTB1chOU76pGXYcT6e0/X9GcRUeqw2h14+std+PD7w3j/lhM1r0diMEIUQm1LJx7/bDte/24/HE4ZOsm1XXJbTQv2HGn3CjRkWcanP9TggUWbsfeIp9vhL08Zinmnj4j6Z++qa8WL3+zBO+sOosU99Eyvk3DyiFJcenwlZg4vgUGvwxXPrsSy7fX4009GK6PqE+lIqxX3vL/JKys0vjIf790cWfaHiNKX3eEM2VAyVpF+fsf0k5944gkMHDgQFosFU6ZMwapVq0Le/80338TIkSNhsVgwZswYLFq0KJYfS6SZ0hwLHvjpGHx6+wycObocTtk18XePO9g4f2I/5b6SJOH0Y8vxye0zcNdZxyDHYkB5riXmdObgkmzc9+PRWHXnbDxy4TgcN7AADqeMzzbX4NoXV+Okh7/Agv9txrLtroZt4yvz4/59I1GUbcYTl0/Ev66cjBOHFqFPngXzzwy/lZqI0l8iApFoRJ0ZeeONN3DllVdi4cKFmDJlCh577DG8+eab2Lp1K0pLS/3u/80332DGjBlYsGABfvSjH+HVV1/Fww8/jLVr12L06NER/UxmRijRtla34N11B7Fsex0mDSjAfeceG3TyameXq8hTy3TmjtoWvL5qP95eewANqs6oZblmrLjj1JSbHUREFImELdNMmTIFxx13HP7xj38AAJxOJyorK/GLX/wCd9xxh9/9L774YrS1teHDDz9UbjvhhBMwfvx4LFy4UNNfhijdWe0OfLypBq+v2oe9R9px2+xhuHCytgVlRETdJdLP76hK5G02G9asWYP58+crt+l0OsyePRsrVqwI+D0rVqzAvHnzvG6bM2cO3nvvvWh+NFGvYDboce64Cpw7riLZh0JE1G2iCkbq6+vhcDhQVuY9F6GsrAxbtmwJ+D3V1dUB719dHbwbpdVqhdVqVf7d3NwczWESERFRGknJpmcLFixAXl6e8qeykmlqIiKiniqqYKS4uBh6vR41NTVet9fU1KC8vDzg95SXl0d1fwCYP38+mpqalD/79++P5jCJiIgojUQVjJhMJkyaNAlLlixRbnM6nViyZAmmTp0a8HumTp3qdX8A+PTTT4PeHwDMZjNyc3O9/hAREVHPFHWP53nz5uGqq67C5MmTcfzxx+Oxxx5DW1sb5s6dCwC48sor0bdvXyxYsAAAcOutt2LmzJl45JFHcPbZZ+P111/H6tWr8fTTT2v7mxAREVFaijoYufjii1FXV4d77rkH1dXVGD9+PBYvXqwUqe7btw86nSfhMm3aNLz66qv4/e9/jzvvvBPDhg3De++9F3GPESIiIurZ2A6eiIiIEiKh7eCJiIiItMJghIiIiJKKwQgRERElFYMRIiIiSioGI0RERJRUDEaIiIgoqRiMEBERUVJF3fQsGUQrFE7vJSIiSh/icztcS7O0CEZaWloAgNN7iYiI0lBLSwvy8vKCfj0tOrA6nU4cOnQIOTk5kCRJs8dtbm5GZWUl9u/fz86uCcbnunvwee4efJ67B5/n7pOo51qWZbS0tKCiosJrVIyvtMiM6HQ69OvXL2GPz8nA3YfPdffg89w9+Dx3Dz7P3ScRz3WojIjAAlYiIiJKKgYjRERElFS9Ohgxm8249957YTabk30oPR6f6+7B57l78HnuHnyeu0+yn+u0KGAlIiKinqtXZ0aIiIgo+RiMEBERUVIxGCEiIqKkYjBCRERESdWrg5EnnngCAwcOhMViwZQpU7Bq1apkH1LaWLBgAY477jjk5OSgtLQUP/nJT7B161av+3R2duLmm29GUVERsrOzcf7556OmpsbrPvv27cPZZ5+NzMxMlJaW4je/+Q3sdnt3/ipp5aGHHoIkSbjtttuU2/g8a+fgwYP42c9+hqKiImRkZGDMmDFYvXq18nVZlnHPPfegT58+yMjIwOzZs7F9+3avxzh69Cguv/xy5ObmIj8/H9deey1aW1u7+1dJWQ6HA3fffTcGDRqEjIwMDBkyBH/84x+9ZpfweY7NV199hXPOOQcVFRWQJAnvvfee19e1el6///57TJ8+HRaLBZWVlfjzn/8c/8HLvdTrr78um0wm+bnnnpM3bdokX3/99XJ+fr5cU1OT7ENLC3PmzJGff/55eePGjXJVVZV81llnyf3795dbW1uV+9xwww1yZWWlvGTJEnn16tXyCSecIE+bNk35ut1ul0ePHi3Pnj1bXrdunbxo0SK5uLhYnj9/fjJ+pZS3atUqeeDAgfLYsWPlW2+9Vbmdz7M2jh49Kg8YMEC++uqr5ZUrV8q7du2SP/74Y3nHjh3KfR566CE5Ly9Pfu+99+T169fL5557rjxo0CC5o6NDuc8ZZ5whjxs3Tv7222/lZcuWyUOHDpUvvfTSZPxKKemBBx6Qi4qK5A8//FDevXu3/Oabb8rZ2dny448/rtyHz3NsFi1aJN91113yO++8IwOQ3333Xa+va/G8NjU1yWVlZfLll18ub9y4UX7ttdfkjIwM+Z///Gdcx95rg5Hjjz9evvnmm5V/OxwOuaKiQl6wYEESjyp91dbWygDkL7/8UpZlWW5sbJSNRqP85ptvKvfZvHmzDEBesWKFLMuuN45Op5Orq6uV+zz11FNybm6ubLVau/cXSHEtLS3ysGHD5E8//VSeOXOmEozwedbO7373O/mkk04K+nWn0ymXl5fLf/nLX5TbGhsbZbPZLL/22muyLMvyDz/8IAOQv/vuO+U+//vf/2RJkuSDBw8m7uDTyNlnny1fc801Xredd9558uWXXy7LMp9nrfgGI1o9r08++aRcUFDgde743e9+J48YMSKu4+2VyzQ2mw1r1qzB7Nmzldt0Oh1mz56NFStWJPHI0ldTUxMAoLCwEACwZs0adHV1eT3HI0eORP/+/ZXneMWKFRgzZgzKysqU+8yZMwfNzc3YtGlTNx596rv55ptx9tlnez2fAJ9nLX3wwQeYPHkyLrzwQpSWlmLChAl45plnlK/v3r0b1dXVXs91Xl4epkyZ4vVc5+fnY/Lkycp9Zs+eDZ1Oh5UrV3bfL5PCpk2bhiVLlmDbtm0AgPXr12P58uU488wzAfB5ThStntcVK1ZgxowZMJlMyn3mzJmDrVu3oqGhIebjS4tBeVqrr6+Hw+HwOjkDQFlZGbZs2ZKko0pfTqcTt912G0488USMHj0aAFBdXQ2TyYT8/Hyv+5aVlaG6ulq5T6D/B+Jr5PL6669j7dq1+O677/y+xudZO7t27cJTTz2FefPm4c4778R3332HX/7ylzCZTLjqqquU5yrQc6l+rktLS72+bjAYUFhYyOfa7Y477kBzczNGjhwJvV4Ph8OBBx54AJdffjkA8HlOEK2e1+rqagwaNMjvMcTXCgoKYjq+XhmMkLZuvvlmbNy4EcuXL0/2ofQ4+/fvx6233opPP/0UFosl2YfTozmdTkyePBkPPvggAGDChAnYuHEjFi5ciKuuuirJR9dz/Oc//8Err7yCV199Fcceeyyqqqpw2223oaKigs9zL9Yrl2mKi4uh1+v9dhzU1NSgvLw8SUeVnm655RZ8+OGH+OKLL9CvXz/l9vLycthsNjQ2NnrdX/0cl5eXB/x/IL5GrmWY2tpaTJw4EQaDAQaDAV9++SX+/ve/w2AwoKysjM+zRvr06YNRo0Z53XbMMcdg3759ADzPVajzRnl5OWpra72+brfbcfToUT7Xbr/5zW9wxx134JJLLsGYMWNwxRVX4Pbbb8eCBQsA8HlOFK2e10SdT3plMGIymTBp0iQsWbJEuc3pdGLJkiWYOnVqEo8sfciyjFtuuQXvvvsuPv/8c7+03aRJk2A0Gr2e461bt2Lfvn3Kczx16lRs2LDB68X/6aefIjc31+9Dobc69dRTsWHDBlRVVSl/Jk+ejMsvv1z5O59nbZx44ol+29O3bduGAQMGAAAGDRqE8vJyr+e6ubkZK1eu9HquGxsbsWbNGuU+n3/+OZxOJ6ZMmdINv0Xqa29vh07n/dGj1+vhdDoB8HlOFK2e16lTp+Krr75CV1eXcp9PP/0UI0aMiHmJBkDv3tprNpvlF154Qf7hhx/kn//853J+fr7XjgMK7sYbb5Tz8vLkpUuXyocPH1b+tLe3K/e54YYb5P79+8uff/65vHr1annq1Kny1KlTla+LLaenn366XFVVJS9evFguKSnhltMw1LtpZJnPs1ZWrVolGwwG+YEHHpC3b98uv/LKK3JmZqb88ssvK/d56KGH5Pz8fPn999+Xv//+e/nHP/5xwK2REyZMkFeuXCkvX75cHjZsWK/fcqp21VVXyX379lW29r7zzjtycXGx/Nvf/la5D5/n2LS0tMjr1q2T161bJwOQH330UXndunXy3r17ZVnW5nltbGyUy8rK5CuuuELeuHGj/Prrr8uZmZnc2huP//u//5P79+8vm0wm+fjjj5e//fbbZB9S2gAQ8M/zzz+v3Kejo0O+6aab5IKCAjkzM1P+6U9/Kh8+fNjrcfbs2SOfeeaZckZGhlxcXCz/6le/kru6urr5t0kvvsEIn2ft/Pe//5VHjx4tm81meeTIkfLTTz/t9XWn0ynffffdcllZmWw2m+VTTz1V3rp1q9d9jhw5Il966aVydna2nJubK8+dO1duaWnpzl8jpTU3N8u33nqr3L9/f9lisciDBw+W77rrLq+tonyeY/PFF18EPC9fddVVsixr97yuX79ePumkk2Sz2Sz37dtXfuihh+I+dkmWVW3viIiIiLpZr6wZISIiotTBYISIiIiSisEIERERJRWDESIiIkoqBiNERESUVAxGiIiIKKkYjBAREVFSMRghIiKipGIwQkRJM2vWLNx2223JPgwiSjIGI0RERJRUbAdPRElx9dVX48UXX/S6bffu3Rg4cGByDoiIkobBCBElRVNTE84880yMHj0a999/PwCgpKQEer0+yUdGRN3NkOwDIKLeKS8vDyaTCZmZmSgvL0/24RBRErFmhIiIiJKKwQgRERElFYMRIkoak8kEh8OR7MMgoiRjMEJESTNw4ECsXLkSe/bsQX19PZxOZ7IPiYiSgMEIESXNr3/9a+j1eowaNQolJSXYt29fsg+JiJKAW3uJiIgoqZgZISIioqRiMEJERERJxWCEiIiIkorBCBERESUVgxEiIiJKKgYjRERElFQMRoiIiCipGIwQERFRUjEYISIioqRiMEJERERJxWCEiIiIkorBCBERESXV/wfUfUKSgOxjsAAAAABJRU5ErkJggg==", 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", 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" ] @@ -612,12 +811,14 @@ } ], "source": [ + "plt.close()\n", "msy_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", "msy_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", "msy_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", "msy_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", "msy_ep.plot(x='t', y = ['act'], title='action'),\n", - "msy_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(msy_ep.rew):.3f}')," + "msy_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(msy_ep.rew):.3f}'),\n", + "plt.show()" ] }, { @@ -630,23 +831,23 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 44, "id": "45da811e-d63d-4cca-8344-624a75b45dee", "metadata": {}, "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "" + "
" ] }, - "execution_count": 59, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" }, { "data": { - "image/png": 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", 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pwaxZs0K+12KxYPDgwXA6nfjnP/+Jb3/725GNmCAIgiCIAYXqMM3SpUtx/fXXY/r06ZgxYwaeeeYZdHd3Y/HixQCARYsWYfDgwVixYgUAYNOmTTh58iSmTJmCkydP4uGHH4bb7ca9994b2zMhCIIgCCIlUW2MXHXVVThz5gweeugh1NfXY8qUKVizZg0XtdbW1vqk7/T19eGBBx7AkSNHkJWVhW9+85t45ZVXkJeXF7OTIAiCIAgidVFdZ0QLOjo6kJubi/b2dtKPEARBEESKoHT9pt40BEEQBEFoChkjBEEQBEFoChkjBEEQBEFoChkjBEEQBEFoChkjBEEQBEFoChkjBEEQBEFoChkjBEEQBEFoChkjBKEhKVDmhyDSArdbhN3p1noYaQsZIwShEWt21WPcQx/guhc3kVFCEBpyqLELs5/8CJc8ux49dqfWw0lLyBghCA0QRRFP/mcveh0ufHawCdvr2iL+rD6HC29uPYH2XkfsBkgQacQLnx5BfUcf9jd04i+f12o9nLSEjBGC0IC6ll4ca+7h3/97x+mIP2v1f49i6d934LvPbYDbTR4WglDLJwfO8P+/ue2khiNJX8gYIVKG9h4Hfr32AHadbNd6KFGzra7V5/t3vzoFV4SGxAe76gEABxu78N7OyI0aInlp6OjDsaZurYcxILE73ajv6OPf7z3dgVNtvRqOKD0hY4RIGf659QR+U3MQ33p2Pdp7Ujsk8fmRFgDAollDkWMxoLHThi+Ptaj+HFEUfTwsq/97NGZjJJKHr//vOsz/33U402nTeigDjrYeOwBAJwCTK3IBAJ8dPBPqLQmhs8+RVloyMkY04FhTN5b+fTs+3tcY9Wf12l1Y/KfNuPGlLwa8ZkC+W1l3IPprFy9EUYTTFVqVv+FwEwBg/uhinDd6EABg81H1xkh7r8Pn776ttg0naVc3oOixO9FtdwEAPj/SrPFoBh7N3R5jJN9qwnzpWfz0QJOWQ8JnB89g8iMf4on392o6jkRCxogGPPruHry59SQWv/RF1DudP352BB/vP4OafY14cf3A3hU3dXmv1aYIFu5EcPhMF2at+Ajjln+A/wQJmZxo7cHx5h7odQJmVBdiamUeAGDHiTbVv6+uxWN4FGebcXZVPgDgk/3a7+qI2NHcZef/P9TYpeFIBiYtkjFSkGnCvFHFAID1h5rCbijiyWPv7oVbBF747Ciau2LrDRNFEc/WHMQPX/kSa3YlT1iXjJEE097rwMf7vbv6D3bXR/xZfQ4XXt54jH//YRSflQo0ySblvac7NBxJcFa8vw/1HX2wO934+bt7AupAPtzdAMDjEs4yGzBZMka217WpdsvWtnhCNEMKrJheVQAA2HmyLfITGOC09dhx5aqNuHLVRrzy+XFNFxylsMUSAL6KwGBNVho7+7Dy40PYVtsa/uA40iwzRqZU5iE3w4j2XkdEm4NY0etw8f9vjLE37NODTfjV2gP4YHcDbnl1K97ZcSqmnx8pZIwkmK21rZCvN9tq2yL+rDW76tHUZYdRLwAA9jd0oss2cHPk5Z6Rfac7IxZ8xpMvj3s9Nqfa+7DTT2y7o64Nv/6/AwCAy6cOBgCML8+BQSegqcuuOsRyrNkjahxSYMXEwZ54t//vJLz8eu0BbD7Wgs3HWvDg27vw/KdHtB5SWJq7vff9jhPt3GB9bXMtfr32APpkC1cq8ci/9+CXH+zHNS9sUnUOPXYnXv+iNmZeIhbmzLMaodcJmDuyCACwTkMPo9xI3nQktl7gTw/4ntcLSfIMkDGSYA5LD5DF6Ln0gTJD6tv7cM8bO/Dzd/eE3Lmx2hTXz6pCea4FogjsPDFwFyL5DrHX4cLx5uTKLmjptqNNEtaeJ7l7/3vIN/b8yL93o7PPiRlVBfje9EoAgMWox5iybADq/35HpQyL6qJMbozsr++EzZmaC1Q0fHWiLaDnQBRFfLC7HhsPN+OfW33TNlevPwpHkntH5GGalm47avY24sJnPsV9b+7Eb2oOYkWK6gpYiLrX4fJJrQ3HPf/4Cj/9505c96I6IyYYDqnqqsmgBwCfUI1WOGUbrVh7w5gn6sFvjYMgeDYvySCMJmMkwfRKQrTZwz3W98HGTp+Kfy3ddlz5/Ea8seUEXlx/FH/eeDzoZzEXfXVxJnf1a+lajDfsAbWaPJPG3tOdCfvdvXYXlvx1K977KniM9WiTx9AcnJfBJzS5C7qhow9ba9sgCMCz10yFxajnPxtf5jEk9qgMPx2TGSMV+RnIzTDC4RJxoD69tAV9Dhe+/4fPcenv/os9p3yv4T+3nsQPX9mCq1/4HF02J6qLMnHw8YtQlGVGc7cdXySp/ojR2efr7bzpz19iX7333v/HlhMp6R2RhySVZpK19zj4M3i6vU+VERMM5mE16Dwe5pnVnnDn7pMdml1XuTGy53RHzDYXoijioLQhnjOiCKNLPJugSDL5Yg0ZIwmGxQKHFFgxKNsMtwifyXPVJ4e5kQEAf/+yLuhnMc/A0IJMTGHGSBSVPJMdtoOdIHkAEqkb+ceWOrz71Wnc/tetQQuLsd1Faa4FU4fkAfCE4dik+5Xk9Rhdko2SHIvPe8eV5wBAv4U0HHLPiCAI3Duy+9TA9ZAF4kynDT2Sof+XTb4G/N82+1bUvOP8kTDqdZg9vBAA8MUxbTUL4bAH8dzcs3A0SnMs6La7Yq4rSAR2l/c5Uvo3qGvt8fk+FiEMp58xMqTAiqIsE+wut+LnaM2uely/erPq5zcYcm+dwyViX4w2Xs3ddnT2OSEIwNBCK86WdGabyRhJfURRxCsbj+G2v2zBkTPhd6N9Ds9NlmHSY1JFHgD4lAJnVv9T350EvU7AvvrOgDoCl1vkmRRDC638s74awGEatoOZqIExIten7AoyQXX0enawuRlGjCvLgVEvoLnbjhOtnr8TGy8zPOSMl17brWIya+91cPFdVVGmz+eo9bCE4stjLUmfUnpGpif6aF8jNwBtThcPfb38gxl490dzcJmk1ZkuZR/JdT7JCAsjXDi+FNkWAwDgmplDcPvXRuDrYz2pqDV7GzQbX6Q4ZE3pdp1s517jUNj8GtnF4r5koXCDpL0TBAFTh3jujS3HlRlJT63Zh08OnMF3V22ISW0Qp2SoDSv2PNexCtUcOePZvAzOy4DFqMfZkhfoCzJGUp8X1x/Fg//ajfd31uOWV7eELcfNPCMZRj3fPTNj5GRbL0629UKvE/DNiWXcA/D54f4P3Km2Xthdbpj0OpTnZWBiRS4EwfMZyRD/iwdODY2RbtlEuTHA3wPwCuFyLAZYjHqMK/MYBtukvy/bNbHX5Ywpy4EgAPUdfYpT+ViIpjjbjCyzZ5EaF4FREwqHy43vrtqI7//h86ROK22S3fOn2/twXCoEd6C+C3aXG3lWI+aNLOLPFABMG+pZcLbVtiWlGJrBPCOluRa8eetsPPrt8XjoW+MAAAskY2TNroaU0wnJPT5Ot9ivKnEg2DnmWY0AgL31HVEXQGTzil7yjADee2Pr8baw72/o6MMR6Vnssbti4mlzuj3XZro0ju11sdlkslBytbR5YZ+/93SnImMwnpAxEgVHznThsfe84rEDDV347+HQoiebZIxYjDpeX4Jl1LDY9fjyHGSZDZg1zONGDuSCZe75IYVW6HUCsswGDC/OAjCw0v/ksAVjwmDPgnuqvS/sRNTe48DNf/4y6rRnVqURCF7jpKNPMkYyPBPlFP739UxOzFsRyBjJMhtQVeiZIJRqYVg4r6rQyl9jnpG9pztissDKRcNvJ3HPDnnaNwBsOup5Zg6d8VzLUSXZEATB55gxpZ7nrMvmxP76xOmP1MIWbaNewMiSbCyaVcX1RnNGFKM0x4KmLhsu/u163PCnzXjh0yMQRRGn2nrx8Du78fKGY0lZyZOFIspzPSHLLQoWceYZqcjPwLCiTIiiJ0MxGtjCb9B5l0NmjGypbQ177Zr8Ng8fRVnMUhRFOCTPyFmSh0bpnN7cZcN9//wqaMkIZjQNk4yRslwLBmWb4XKLQT2+iYKMkSh4e7snP3tUSRaunjEEAPBumIZncs/IpMo87s1o7OzjO+4ZUhzvnGGefwO5IllKJ7NwAWCSVMp4R4xCNf/YcqJf/F0rRFHki2u+1YTBeRkAPDujULz+ZS3W7mnA/7yyJSrLv1Vm9HxxtCXgQs88I7mSMcJcvdvr2tDe6+DGw9gAxgjgNVKUxqlPt3vCP+XStQCA6qIsWIw69Nhjk20kn2iTOVTT0u27IDCDkXlzRgzK6vcevU7g3sktSRyqsTuZMdJ/ujYZdHjk2+OhEzznum7/GTz+/l5c/vsNuPL5jXhpwzEsf2c3XvsiuPZMK9h5zZLE/F8qCInYpDC32aDnz1f0xoivZgTweF+NegFnOm08zBoMFnpnrNsfnTEin1qYUXToTJeisg1rdtfjtS/q8MNXtgT0HLMwDVs3BEHgm6btUZSZiAVkjESIyy3yneLtXxuBSyaXAfDcDHa/uKacXu4Z0SPLbMCYUs8C9M72U7zJ2dfGeFyvZ1cVwKATcKK1F3UtvsIt/5sKACZz3UhblGcH1LX04O43duD+t3YlRQqtXF1u0On4gh4uVNNr9/4tPomihLzcM9JpcwYUqnXwMI2vZ2T3qQ5skNIEhxVlIj/TFPB3jFOp9zjV5mnuVZbrNUb0OoHfU7EI1cjTSnecaNPclRsM9lwxo4MJG1kIlGUN+DN9qMfgV7IQagXzIJgMgafrheNL8cfrp2POiCI+H2yva/NZRJ//5HC/Hb7bLaKxsw9awc5rliQk3lrbGjbMzcI0ZoMOZw3N4++LBpfkhTDIjD2LUY9x5Z7NXTjdCPN2D8o2QycA++o7o2q0JxevluZaVJVtaJNtml7677F+P98nbd5Gyp4HZtQpCZPFEzJGIuT/9jagtqUHORYDLhhXgpnVhSjONqO91xEyVNMnM0YA4IqzPGK6x97by9MOWXgm02zg3g4Wqnlnxylc+MyneGnDMQCBPSNfyQojRYrczRfrojuRIPdE6PUCxkl1OcKpzFtlRsSaXZGHavz7/gTyEnDNSIZHvzG00Ip8qxF2pxt/kv5eMyVvVyDU6j3YhDc4L3BmTkyMEZnHweESo5744wXfZQ8rhF4n4GRbL/bVd+CLo57xskJW/nARaxJn1ITyjDC+PqYEr940E/+5Yy4WjC3BuSMK8cDFY/Hf+74Oq0mPY809Ph5TURRx+1+3YsbjNbj11S2aaGbYeU2uyEWmSY/OPicONIZ+nlmYxmzQ8RDG9tq2qCrpBvKMAMA0hSLWPslA8mTRed4TTcE0+cbLqNfJkhPawr5X7j35YE+9j2HT3uvgSQ/jZSJ68oykOGyBvmzqYFhNBo/odEIpgNChml6WTSMZI9fMHIIhBd6Y/w/OrYJO9lCcIxkmnx9pxpbjLbj77zt8agwwnQjgcf8b9QJauu0+6cGRcPiM1xuSDH1gfD0jAveM7D4dercgz7Ko2dsYsciP7bxZOijTJMhhItdMSUwqCAKv/8Ka4M2sLgz6O8ZL53TkTJdP7ZlgnJLCNHLPCABMkHZ0sUjzbvbTYiRrqIYtbPlWIxep3vPGV7C73BhVkuVjtMuZUpnHjRcW9ko2mH7AHMQzIsdi1OOP10/HX246BzfNHYbBeRn4uuRpfV/WK2njkWb8RzLO/7OrHv/RoEcJ08JYjN6QS7iaL15jRI9RJdnIsRjQbXdFFZpmmhG9vzEyVFkYqM/hNZC+NtpTX+jjKEI1csPKoBNU1ZDqktWkaetx+DyvTPBekmNGntXrnZ1UkQud4NHgNXRo5ykjYyRCWFx/okydf/GkcgDAh3vqgy56Nj/PiNVkwGv/cw5unFONJy6fiP93zlCf488d4dnRvbXtJK57cbOPAn1YUSZ/YNhnMis3WMaHUuShmc+PNGsugAv2gO493Rly4ZZnWXTanNgQ4XVh4Yn50mSz6WhLv90Y/9savMXMplZ6/z6C4DUuAzEox+OSdYvK2gSclsI0cs0IAN4wb1tda8iQoRJY6ImFCKK9r+KFzekNZZxTzXr0eJ7RRbOq+olXGZlmA8aWscJPyekdUeIZCcXFEz0h5Pe+Os3DIP/22zAx0WsiYUaWyaDjhcY+DuNRYM+Y2ajzlG6Xigt+EtXi7xkHa6vBYGGgvac70B1CryH3drOuv/891BTxxschq7+i1wmYXOlZY748Fl5M668rkRugTIxenG32OSbTbMAoKWyzXcM6VWSMRIAoijyuP77ca4xMH5qP0hwLOvuc+CxIC2ouYDV5L315XgYe/NY4XDNzSL9Jc9awQkyqyIUoetLGzq7Kx+5HFuK5a8/Cnxaf3c+aZyGeSBddBkuNBDwCW5a9oxVyz4heJ6A8LwNluRa43GLI2ioshsoyTiKtx8B2P9OGFiDPakRnn7Of+1ZeQ4bB4uEAcOnkcpTm+oZU/GF5/5vD7BD7HC5eY6TcL0wzYlAW8q1G9DncUSvkO6Sd1sLxHq/ftro2tHbbQ71FE+wyY2TuyGL+emGmifcACgYr/BTtMxMv7GE0I+H42phByDYbcLKtlxe32i9pB37+7fEwG3TYcaI9oT2NXG6vIN2o1+FCyau8/mATz0oLBDM6mcE/fxTzREQfFtHrfK9vWW4G3xyE8jL2yUS148tzMCjb7EnxPRqZccs8NUa9AEEQcNaQfFiMOjR22rC/IXQYi1XrvXiSxwD9cHcDN0C9DQHN/d73xHcm4uO75+Mb40oiGnMsIGMkAk609qKzzwmjXvBR6euk+iAA8O5XgTshMivaLNs9h0KnE/Dy4hm476IxeOyyCfjzD2Yi02zARRPLMLSwv+uZKdM3RuHNEEWR1yph7m3/5kqJxiWrBcAMtrMUxHTZTuEi6e8S6c6eGZHZFgO+Lu1+1u5pCHgM6zsEADOqC3DjnGqcNSQP9188NuzvYQtjuCJEp9s9XhGrSc+zdxiCIPAOvtGWOmfXb2xZNsaW5cDlFmNSgjvW2FzeBeHcEYU4f8wg5FmN+O3VU3nYLBjzZLtrrT2AgYjWM2Ix6nHBeM8i87GUdnpM2mycNTQfF0gL0Hs7ExeqkWsZTAYdRpZkY8SgLNhd7pAbBh6mkZ6x8yRP5c6T7RGHGLxGUX/v2VmS5/nzEM9Rn+y5FwSBe08jDdUwTw3baFqMeu5RDTcPd9k8htz5YwYhw6hHc7edl39nGWcFVmO/9501JJ9XcdYKMkYigMXuRpVk99utMIt07Z6GgH0N5K5JpeRnmnDLecPx/84Z6rPrDsTUIXkwG3Q402nDYQUVYQPRbXfx3RjbEccqXThS2OQlF5nJS64Ho1sK4Zw/ZhAEwaOFaYxg0mJhmgyjHt+QJvYP9zT4LF7+4mTGg98ahzdvOxeDskN7RQCP8QJ44tShQiys4eKQAmvACWSGQqMmHCwGnW0xchFoMupGWMqnyeBZEF5YNB1bHriAhzlDMWtYIcwGHU619/GJO5kIl02jBNa48TPJ88Bc9lWFmfiaZFwrqfMRK+ThZmYEXCR5R97fGVxoLs+mAYBB2d7WCx/uiczrya6vv5cZ8AqfQxkBTMDKnnt2PT+OsN4I89QYZZ6aeZK3L9xGgG0e8jNNXJy9UUqoaOn2GCqBPCPJABkjEfCJ5BIMFP8/a0geBudloNvuCqiodkS5ywmHxaiX3YSRLRotkmjRYtTx7A+te974N7MCvFkjh0Io8FmstywvgyvI1fbxEEXRJyV73qhimA061Lb0+LhNgxkjahhRrCzEwlL0gtUs8ZZ5Dh9nDgWb3LLNBu61ScaMGh7KkJ4rnU4IuLgEwmLUcyMwGTUxPAQVYOeuFDZX7avvwMEGj8GVbzUi02zAFGkx33myPWEdjOWl4NmiyzY+/z3UFDQ7Rl5nhMHeF2lhw0BzC+O8UR7DYseJ4OFJNibmEZ0tGcBHmroVV1OW41+eHvB6gL442hpSI8c3D2aDLPnBsyFhnpHCrMClBbSGjBGVuN0i1knWKbOA5QiCgPOlEs2BdqXyaorxgokm90TYXKlFSoctzDTz2iVHmrr7pbcmkkAlm0cO8oiualt6AnqhbE4X90RlmQy8poRakZa8H0aGSQ+ryYA50oQjNzj7+KQUuTGi0wmYxsYZwuOzV8qoGlMauH7G+PIcGHQC2nsdPKQTCZ2SMZJlNnBj7siZ7qQrPW6XxhOp94Blc+xKoG5CKbHwjJTkWDA4LwNu0SOwB8A9ddWFmcjNMMLmdMesIVs45PMgyx4cV5aDHIsBPXZX0Fo7/p4RAFgw1uOp3HS0JaIuu44AdUYYpbkWjCnNhigG1xRxz4hkIOVmGHl4e1cE6fWBxjOsKBOD8zJgd7lDeoLZ5iHL4jVGNh31hOxbuGaEjJEBwb76TpzptMFq0uPs6vyAx4TKC3f47eDiwShpgToQRuwUDGZB52caUZBp4qnHSoruxAu+e5Fdt6IsE/KsRrhFbxE4OT0278SUadbzzCe1C458grMYfHc/LGThcot8gs2IwhgBPBV9AYQMs7Fib8E8I0a9jjfPiyb00CWJCbMsBpTlWpBjMcDpFnG4UftCeHLssvoTkTBBMrQiWTzijS1G3lSWecfq7QzK8bjrdbLstEQVvnI4veJVhk4n0zoFCRlxz4hMlzW8OBMlOWbYnW7Fje3kuIKk9jKYpzlYaq0twCZkQoRzDSATsMrG42nelwcg9GaKCVizzAZMHJwLi1GH1h4HDjV2cQFrvpWMkQEBc49PHJwbVIQ6uYLdiL79QVxukZf6jVeYBvBWmzxQ3xmRi75Vii2ym5b1gklkYzp/AmlGBEHASElAfDBAqIbtEswGHQx6HSZKf5fdp9T1bWEhGqNe4MYQy1r6Qkrx9TFYjNH9bVntmEAGFuAxjljNgDFlgT0jAPi1iabBnXxyEwQBYyTjZ39Dci3a8tTeSGCLx8GGzoh21/EkVhsYZoywTDl5iudE/own2jPie05s4Q8mvJbXGWEIgoDZknB/Q5jeYIFwhhCwAgjYXV1OXwDhOruekRgjwTw1zEsdbFNod7r59ck2G2GSFYbbfKyFh5koTDNACNXrgjGsOAuZJj16HS6fhcBfQR4vqosyYdAJ6LQ5I3LRc52A1K58bKn2xkiwuO4IKVTD4uBymHiVZVMML/b2bVGTqszEq/Kdz5jSbORmGNFtd2HnyXY/70l0npHhg0J7Rk609sAteuLCxVnBxWgjuDES+QLDzt0qCafHliqrfJto7FEaI2W5FhRkmuB0i0nXNI8v3FHOGfKaRIAndMNgdSYORuhNVUuwvxerk7QvSM+pQGEawJtCHy4lPhDe7JXA15cZAbtOtgfcxATSirHCg5Gk1gfSjADejUcwj7e8Fkqm2TMWpvPadKRFltpLxsiAgC1i8sqn/uh1Aq8/Im965qsgj9+lNxl0GFbscdFHMrEyYyTT5FnE2W54r4aTNNeM+D2gw6XzPNIUwBhh5yE9mHqdoLoZHeDb3JCh0wk4S3Kb7jrVgT7Z5KpTKJwMBvvbNXba0Bmg5gIzMMvyLCFT8UbEwDPCzt0q3QujJcM00hBgvLC7ogvTCILAi5+Fq+WQaFhII1rPyJjSbG5UAl7Pmef/3oUuEenNwbw9bF6ta+0NKKb1T+1lsMX/QEOX6vGHErACnufIatKjx+4KuEGQV2BlsDmzrqVXUTVlJeNhHu9jzd0BvXds3s4w6rlXhVWM/nhfI/dyFpIxMjBolOpvlIUpXjWypP9C4KMgj6OAFfA+1MciaHLnXcQlz4g0SR9q7Iy6omekeB9Q31uWCcWONfUvf98taUaYUQVEtpgGE6bKm/Vx70kMPF45FiN3oQcK1XBjxK8MvD/MGIlkggY8CwYzApkhxorHHY+y3UCsCZRloRa2IB9OsvTeaIueMQx6HUbLBM+soSLgMYB1gqfIXWOn+gwQtQQT8g/KNsNq0sPlFvs1BwWC/52HFWdCEDz9V5pVFuVzuPuHgOXoZe0n9gXYkDEBq1k2PxRkmviir3Yz4Agy1xVnm5EvaeQCfSYPqVq8891ZQ/ORYzFwIbpRL/BGnskGGSMqYalaRdmhc7VHBHC1O2Rlh+NdXGawVCL8ZJj214Ho9gvTDM7LQLbZAIdLjLh2SbQE0owA4CLNY83d/RbcblkmCIOJQw8ECOsEI5hLeUwAYyRcHRilDJPOK1A4qZ4bI6EN4uHFWXyCbupSXzW1Vx56kioGV0pi5hMtvZo0VwtGLBbs4THwJMWDWJYDkFenZRsmwGNoV0lFFBPh9XIEeaYEQeDjCHTv25z99Rme7/WoyPfMeWqNSa84PoSXsTj4vREspZ9d30Ah5FA4gxhqgiDwcFqgv5E8DZ9h1Otwnizrc1hRVtSe23hBxohKWOOwcK6u4QFuXkcQ0VY8GCw9mCcjaGXd6ecZEQSBZ+hoNVG7AqT2AkBlvhWC4CmV77/gdvmdBxBZbNy/hgWDdQ7eX9/p7dgbo10HX/Rb++8OmySD2L/HhD8Wox6V+Z7PieTv1icZWDrBe+7leRkw6gXYXW7Ua9hUyx9vLY7Iny3m9TkRgQEfT2LlGQGAxbOrcNv84ai567x+81Cki2ckBBOwAl5vZ2BjJLgHjM+5KjdMTDPi74nw+exBnjEFMnS8Jer9ricLfanUbIVKNWaerUDhd1Z9Ve4ZAcAr7AK+BmiyQcaICvocLr5QF4YQDgJez8jx5h5uhIR6AGMN94xEYIz4h2kA7049WIZHvHEG2b2YDDoMkhblU37n6q8ZAbwP4/EgtUkCEcwzUlWYCZPBI4hlGpRsv4kgUtguL9DCyPrt+JeBD8TIKESscq0M8+TpdQIqJAPneAQhwHhhD6IlUANrOOh/H2mJKIoxrU2Un2nCvReOCah544Z6FIJnpYQqca/MGOn/Pua9UJt27gwTpgFC66+ChXFHReoZCTEe9jcKpGuSZ77JuWBsCRetsh5AyQgZIypgRWM8cbfQi05ZrgWZJj2cbpGn0mniGYkoTONZhLJki3i4DI944wqheA9meHXb+2tGirM8cVcxSNw1EMGMEYNex0VlTMWfo8BAUAJb8AMaI5IXJk9BvYBoRKzepo6+kyyrOxMopq8FblmNl2g8I+WSBqfT5gzZrC2RuNwiWPTRrI9NCDAYI3kIIP7PeKi2GPLQqz+2EL29eJhNrWckiNdVzohiz7U52tTdLzzp34mdMTJESCXkeHg4P7hn5EBAz0hgYyTDpMfbt52L9348B9+SOssnI2SMqIBNULkZxrCaD0EQUF3MxJWeh8qrio9/zK4iz7NgNHfbuZ5BKf7ZNIDXBaqVMRKoEBBjsLRw+xtegTw8giDwnZfSxdTuCpxOCHgroHJjJFZhGsmYrAsQpmEhoTwFhs8IXoclAmMkQEozAAxlItbm5DBG7DFKmc8w6fkOMlm8Iz4ZeIZ4i96Z9zMRxkhw45F7RgJ4YYNl0wAynZ7Ke90ZIizCGJyfAbNBB7vL3W/eCFRnBPDODSdae1UZt6GMo1FS6OdUe1+/z+wKIGBlDCm0+nSYT0bIGFFBoMUtFKyrLrPwY1UvQAk5GQZuIasN1fTY+5+nd6Lq5i2pE0moB7Q8zyPk7OcZCbJTYF6HQAt9IELpEZjKvtNP9BstFZL34VRbf6Fou1SuPzdA901/AgmplRIopRnwekaSJaMmVsYI4L2XksUYYRsYIL5VmwFw4WhrjwPtPfH1DHnDNP2fZ2aMnGrv6xdKDRWmYRumk23q0mnDpfYCnnmHGeG1/saIM3CYJs9qQqlUyyWQJyMYwQSsgOeZZ5/pr3sLJGBNJcgYUQGLyck9BqEYWuC7g0xkmEYQhIh1I4FioJUFVhh0AnodLpzWQLgYSvFeEeQ8u6Rwk9XsO0lUFkhehxZl1yVUdU//CqixCtOU5lhg0AlwuMR+rdHbVHhGhhV5JuiGDhufrJTSFyRMwxatZNGMsHRPIPoFm4VqTrYlhzjXJnnlBCF0GCEWZJoNKJFKxB+N8982lCg332rkeij/UI236Fn/ME1Bpqc9BKDOa8c1GmE81swI72eMMM9IgDGx+SFQSnAwgqX2Mlgygf9nBkrtTSUienJXrlyJqqoqWCwWzJw5E5s3bw55/DPPPIPRo0cjIyMDlZWV+MlPfoK+vuR42NXg1VIo+2PzSbsl8cYIELlupDeA29Go1/GdQSLcuP6EUrwHO0+2O/L/e1XmB89UCUSo6p7j/HrDxMozotcJXFAp14243SI6JGNEiWck12rkmV/HVFSdBYBee+AdHw/TNPUkpEBWOOQLW7Qp88kmYuXaCn3056YENmepvVfUEmouFATBqxuRjcPlFvn1CFbcjj3bavRMSrJpAG+Gm/yzRVEMGqYBvLVcglWUDTye0MYRa1j5VZ1v4UavZiQ564iEQ/Wq+Prrr2Pp0qVYvnw5tm7dismTJ2PhwoVobGwMePxf//pX3HfffVi+fDn27t2LF198Ea+//jp+9rOfRT34RNNtU2d5Din0zTrwxkkTk+ft9Yyoc6f3BXHPc92IBum9oRTmgyV9TH/PSGBPljdMo9IzEmDizLOafOp9sGseC7wZNd6/X6fNyfsbKcmmAbwVXdWGanqDCPMqCzzp1J02Jxd1awnPpImBkT84yYyRWKQsqyFUJkssCXdePHtPNg55p+hgWVPc66liA6ZEwAoE9ow4XN5+Y4G8NWMiaJ8QSsAKAFODNDUMpRlJBVTf4U8//TRuvvlmLF68GOPGjcOqVatgtVqxevXqgMdv2LAB5557Lq655hpUVVXhG9/4Bq6++uqw3pRkxL/+RjjYLuOkVNrYHqBTZTyJ1DMSqAsl4FWrR9MFNlKUaEbaex0+oYhgGh82YZ1oVbazD9f3ZIysqmWonkVq8e7yvH8/FsvPMOoVVxutjjAtO1gnXItRjzIpbp0MupFo+9LIST7PSOzOTQmhMlliSbjzCuShURKOi8wzoix1OpAxEs5AGiOrRaTUixiuIuxUqfndwcYuHxFrWmlG7HY7tmzZggULFng/QKfDggULsHHjxoDvmT17NrZs2cKNjyNHjuD999/HN7/5zSiGrQ1eQaSyRWBQthlmgw5Ot4hTbb0JrTMCRFZrxCVLk/Q3RsYEiVUmglCakWyLkadayxeRYGG1stwMCIJHG6OkMmm4olOsAZlO8Go0YkFFgIwankmjIETDGCZ5tNTudu3SRBvovP29floSrHlaJHAxdJIUPgtVjyMesMJvx+KcKWUPs/tnmYhHfTwj3kU6WOZLRYhigcFQ7Rlp9m5imL5OEALff8OKsmDUe5qWKi2mFy67pzjbjMqCDIgisEPWSbgziGA/VVB1hzc1NcHlcqGkpMTn9ZKSEtTX1wd8zzXXXINHH30Uc+bMgdFoxPDhwzF//vyQYRqbzYaOjg6fr2SgO4jbPxg6mQL7eHMPr2gZbYt5pUTiGZGr1/3DNONk5c8TnVHjCBPXDZTey7r2+gtYTQYd39kryagJt/P+4XnDce+Fo/G/35scs3LwQOAqrG29UiaNCqGs1+WtzqNlCxH+8O5clU36O+raMOXRD/GNX38S8xoesfSMMAO+vqOP75i1JJbVV5XA69vE2eMVzsiq5iXh+3sh/DdJcnhKvEJxOuDd6IQz+Ni16bQ5+aagz+E1hANpekwGHQ9vK93EORVk90yt9GyAttW28de6+gJXYE0V4n6Hr1u3Dk888QR+//vfY+vWrXjzzTfx3nvv4ec//3nQ96xYsQK5ubn8q7KyMt7DVESg8uLhGFLgzTxgDZViuWCFokI2sQbqgBkIuTHib+lXF3krjvoryuONK4zrki0iJ3w8I8F3Ct4dVPhJK5wmwajX4bb5I/CdsyrCfpYavII57xjVVF9lcM/Imf79e0IRapEfqjKj5vlPD6Otx4EDDV146b/HFI9BCbE0RoqyzDDqBbhFoCEBDePCESoFNh6we6652+7Tkj7WhA3TFHnG0dTl7VwdKq2XwZ8ZhSFYURQVe0YyTHpe7ZnNf0oMJPkmTgnhBKwAeMfwrbVe3Uiwomepgqqnt6ioCHq9Hg0NDT6vNzQ0oLQ0cJnZBx98ENdddx1uuukmTJw4EZdffjmeeOIJrFixAm534AVy2bJlaG9v5191dXVqhhk3gpX9DYXc7ent7JoYY6QoywyTXge36G2uFg4mWjQZdP0aKhn0Oh6q2aPwwYoV4SYMrgORGUm8a28gY4TvoKL3jMQLdk6n23v5GCIJ0wwpsEKvE9Btd6nqyBpqVz5URfdeURSx/mAT//79nacVj0EJofqVqEWnE3g35GTQjXgX7cTMGbkZ3pBnPHv0hBPzZ1uMKMryZIGxNF1vx94QxcmkTUmP3aVIXC2v4RPKE8HwrzXC14QQfx9Wi2jPKYXGiAJPDdONbKtt40YXE7DGKqMv0aiaXU0mE6ZNm4aamhr+mtvtRk1NDWbNmhXwPT09PdD5udb1UlnjYJar2WxGTk6Oz1cyEKxjZCh8wjTsxk2QZ0SnE4IWBAsGG6N/iIbBrPyvTrQH/Hm8cLmCa0aA/uIyu9PNF9OsAGE1Nem9iXaVM4qzzLAYPcYkWxiZMaLGM2Iy6Lj7Wk1GTaiMB3ZfH20K722p7+hDR593l72vvhNnYuh1CFUHJhKSqfCZ92+QuE6rgVJYY40SLYx/916uDQqxGbQY9bxWipKMGqfcGFGgy6n0qx0VKq2XMU5Kxd2rML03WIdyOWPLcmA26NDe6+Al6ln7i7TwjADA0qVL8cILL+Dll1/G3r17ceutt6K7uxuLFy8GACxatAjLli3jx19yySV47rnn8Nprr+Ho0aNYu3YtHnzwQVxyySXcKEkVIvGMyN3ZvSGK48QLtbqRcA/XWZJYc8vxlhiMTjnhCgFV+lVVlVdg9NeMAHI9hvIwTaLSKxmCIPDzYkZWJMYI4A3VqMmoCbXIDyvKgk7whI3OdIU2LFivk5GDsnjjPrnwLlpi0ZdGjrfwmfbGSKJrEwH9n6V4oKQatX+tESVhGkBdRo1TpWek0q9nlJI1gXlGjjf3KCo8qKQ8vcmgw8TBnvLu22rbuD4OSF3NiOpRX3XVVThz5gweeugh1NfXY8qUKVizZg0XtdbW1vp4Qh544AEIgoAHHngAJ0+eRHFxMS655BI8/vjjsTuLBBGJal/u1uuVbpgMU+ImFrUZNeFioGdXFQAAdtS1o8/hUmWYRQPTjAQL07Dsjlppx8IeepNBF3AiVxOm8S7KiTeehxRYcbCxiy8MLLVXbQ+cYUWZ+AjqjJFQHqEMkx5VRZk4cqYb+053YlC2pd8xDOZhGFJgRUGmCQcbu7C9rg0LxpUEfY8aYh1GS6b0XkeYrJN4oLZCcSTIi7kFg9c8afbzjIQzRgqs+PJ4qyJjinlcAWXGiH/tHy5gDTEPFmSaUJJjRkOHDfvrOzBtaEHI3xGqD5ecqUPy8OXxVmytbcWs4YUAPNczFuFKLYjoDl+yZAmOHz8Om82GTZs2YebMmfxn69atw0svvcS/NxgMWL58OQ4dOoTe3l7U1tZi5cqVyMvLi3bsCSdY/Y1QDM7LgEEnwOZ08/h6Qj0jef2zTELBq24GGWNVoRVFWWbYXW7sPJm4UE04hTmbJDr6nGjvcYStlss8IycD9H7xR6swDeAdZz/PiArNCCBPlYwgTBOmvkq46pJMr1SSa8FkqWDTjhNtiscRjlim9gJeY+R0EpSEV1qqPJYEyuKKNSxtPJRnxL8ho1czEnr+rFDhDXbIdItKyu37e1TZRsUS5t7juhEFxc+YZ0Qf5m8+Rcqo2XWy3SteTVGvCEC9aVTRF8GkZ9DreKhkv5TalahsGkAWplG4y+MdaoOEaQRBwIxqz0Ow4VBzDEaoDFeYB9RqMnDBW11rjyzzKfC1lvd+aewMvejYY7zYqYFPfi2Ra0YAb/2TIypqjYQLT3lLXYeeYNn1Lcm2YAozRuraYlZKPtaekTKVOqt4whemOPelkVOpskJxJHg9I8HPy7/wWaiOvXIGB2ijEAyXTBivpNy+3NBxu+Wl4EPP6eNUiFi5gDVMeXpWFn5ffSdaJbFuqupFADJGVBGJZwTw6kZOSzvEUC69WKM2TKNEWDZnRDEAYP2hM1GOTjlKHlC58I53Hg5SE0be+yWcO1qrbBrAWzeBeUZYjQ61DflY1+W6lh6fqpGhCFaBlaG01HVDh0dTUpJjxsgSj9ako8+pKrNHyThj9fdhz8xphRlo8cQVRisVD+SZafHqPaSksizTjDR329HR51DsAVOzAVMiFpVTmmOBXifA7nLjTJdN8QZ1rIr0XoeC1F7AE/bMNOlhc7rx5XFPim++1IcqFSFjRAV9EWTTAN7uvYxgmSrxoEL2YCopVGZXEMudO7IIALC1ti3mBayC4QyjGQHgI/YMVgre5/gCZboRLcM0TAvDNSMRekaKs83INOnhFpVnSYQ7b+YZOdTYFbKOTZMkcC3ONsNs0PMd78GG2LQVCGc0qYX1GmrvdcS11oYSlBTAijWBinvFGiWbniyzAcVSXY9jTd2KU7grZAUQwxlTLpXX16DX8WyrupYexUkNzBjZX98ZNiysRMAKeLIl2ef+95AndT5fZfg2mSBjRAVKY5b+sNgnI1EVWAGgNNcCneB5+Ju6w+9ElewyKwusqC7KhMstYuPhxIRqlEwaQ2QFj7pC1BhhVOQpy6iJZSM2tTADq63HgY4+R8TGiCAIPKPmsEIRa7h7oSI/A5kmPewud8gurx1+Yx5Z4hnHgYbYtBWIZZ0RwFPjgtVqON2ubaiGFcAKpx+IJRajnhsB8RKxKm2NUS1L7+Xzb5j5kxmTvQ4XWntCG1Pc2FPxbMvnDSWpvYBHjGsx6tDrcIUtFKhUwAp404Y3SPNwgZU8I2lBxJ4R6YFiJNIzYtTrUJKjvN+GUpf3PMk78tnBxIRqlIi6mKejtqWXh2lC9RHydvgM4xnRMEyTaTagUHK9Hm/qQadUr0NtNg3g7d6rNKPGqxkJfA11OgGjFRTBYzVGWGhp5CDPew42xsYYiYfnqpwXPtM2VKOFZwSQlVWPk4jVoTAdWy5i9YZpQs+fcmMqnAiXeyFUXF95Jp5NoWZErxMwusRz3+8NE9Z0KPSMAF4tCoPCNGlCpJ6RKj/PSGGWOWZjUoIa3YjSSWLuSI9u5DNZZc14okYzcqJFJmAN0UeoQmHhMy2NEcBbun7PaW/2klrPCABe4+OgQo+ETcEi742FB/5MURS5N4cZUMwzojRMI4oifv7uHlz0m8/wVYAsnHjUgUmWwmdaaEaA+Bc+cyjsYC6vNdKnoAIrQ2lGjZLwrz/yjBpWaMyqoF/ZKMkYORSm67ma0BHzjDAKyBgZ+Iii6BUrqfSMVPppRpjVnijUFD5TuvCeM7wQBp2A4809CencqqR/hLwgEfMgKNOMhAnTaKgZAbzhJ5ZKnWHURzQWpvHYq7BhlxItRjhhXo/dxSdXZkCxSflAg7K26gcauvDi+qPYe7oDj/x7T7+f20J0F46UMlZrRGMRq3aekfgWPlMiYAV8a4308IU//GZQ6QbMGUEdF15rpE0ulA8/Jm/37NDGiFIBK+B5luRzYnGCN7qxhIwRhdhdbrB5U61nxGLU+4R2WApqolDjGVFazTLLbODVWD9NgHfEpaDeQlmuJ13X7nLjiFT2PFhqL+BNHTzV3utTsdUfm0YVWBnMZb7zpGfBj8QrAgBjytjOrFNR40S7gkWe7cyChWmYwNmoF/gzUF2UyTNqlJSF/+RAI///luOt/fosKa3MqYby3OTwjCitORFr4l34zMYFrKHPS57e22Xz3EtKGpUOzleW3qu0SZ6cCl7htVeRNo1Rzbtnh9OMKPeGWYx6jJCMHMDrdUxFyBhRCNslApFNenI3XqIr5KnxjPBJwhD+4TxvlBSqORB/3YiSegsepbvnXFnYINQkUZhlRnG2GaIYulaG1mEa5hnZLXlGIjVGBudlINtsgMMlKupRo8QjNKY0G4IAnOm0BTQs5CEaVsfBYpRl1IRxWQPecvKM9Yd8jd94/H144TONBawuFWLGWFKRIM9IOI8E04y09jj4ZkpJI7gKhbVGeEhEhbHHDLVTbb1cnK2kvgdLrw/XPdvpUmaoMUYMkhsj2Yrek4yQMaIQp6xscCSlme84fyQA4Oyq/JiNSSmRaUbCG0wsxXfD4WZFO+1oUFoIyL9hXn4YdXm4WhmiKGoepmFhPnYNcjIiK2wkCAL3joSrDQIo02JYTQZuWAQK1XT0ejxO/gYUT1lWoElgJf5Z+3b/vjbxMEbKkkzAqk+0ZkQW8lRSEkAtSsM0mWYD/7vvkjyDShZ+nt4bNkyjrs4IAAzKtsCoF+B0izgihVwC9b/yZ0ihFYLgSZlu6greUViNgBUAfjCnGmNKs3HD7CoqepYOsIdHrxMiqoZ4/ewq/PPW2Vh5zVmxHlpY1JRHVjOxjy/PRb7ViC6bE9tj2PgsEErdqWzXwghnjIwLo3lwukVveE6jxo7+qeHRaI68upHwxZeU1u8IdQ3ZzjHbzxipUOhGB4DjLR639qWTywH0LyUf69RewGvAn2oLX6sinjgj2LnHgrI8b0mAcI0QI0FJbxoGE7EyL5u6ME2YbJoIjD29TuD3BwtjKRmT2aDn9/2REJ5JNam9ADBtaD7W3DkPD186XtHxyQoZIwqxR2BB+zNtaD4G5QRvKBYvmMtZSREjNcaIXidgzsjEhGqUaEaA/mLhcEWAwgkw5eE5rTwj5bkZPungbNcXCRF5RsJWl2Qpi/2voTdM4ztZK81kcrlFXqn1ooll/PfIq8jGwzNSkusx+GxON1q6g+9i440W5eABj/fXW6E49qEaXvRMwd+s2q80QrYSY4TNeX3OkIUZ+cKv0tjzfwZDZe3JYW0ZjobQjSgtejbQSK+zjQI1lnyyYTUZeMpXOO+IN0yj7OFkoZp4i1gdCiflSr9JIlyqm1yAGagyYjIYIzqdgOGDvBMy211FgrefjALPiEJXeigRK1sI/MM0FQpLdrf22LlnanJFLgoyTXC4RJ9UYqWiazWYDd5aFVqWhddKMwL4VjSOJfLQpxIjYGiR7zOtpBlcptnANyKh5rxIjT3/ZzCUUF4Ozw4KZYxEIKodCKTeyqoRXHCl0YIULUp1I2p3mcwY+epEW1xLZyuttzDE3zMSxhgZXpwFi1GHHrsrYMqdPcrwXKyYUJ7L/+9vcKmBaWQaOmwhd/xut6jYAGfepcNnunlFSgbTjPj30qmQaRJCwcaYZzXCoNdhwmDPdZA3HIt1114Gy6jRsmGeVpoRIH4ZNU6Z0a/EgPT3jCgJiQDKhPsuhVo0f/w9sEq1GqzwYKgqyGoFrAOF1FxZNcCR4jcIN0bCuMVtKneZZbkZGJRthltUttuOFKX1FvwnibwwmSd6ncA1D6yOh5x4FNSKhG9N8uglss0GnDOsMOLPyTQbuAZlX4iqqXaXco9QaY4FeVYjXG6xX0En/4JnDLazrO/o8/E++dMsCf2Yh4uFhOQF4GLdm4bBM2q0NEZc2mhGgPjVGnGouLcAr2aEEe6ZZni79wYfvyNCL4S/ZyRPYRl2Vo07VOjLoVGhO61Jr7ONAkcExXGSCaWdLNXEchmslfVuBe2xI4W5q8PVW/DXiCiJu06UdttMrS8nHgW1ImHOyCI8f900vPOjOchQUGApFPKiY8FQY4wIghC0RXqwME1hpgkWow6iGDp9lnlGWEn8cQEqvtrilHrNM2o0DNNoVfQMiF8VVrnxqWQ+9RdwK60yqiSjRqkWrf9ne42RDKO+nyYqGJUyYW0wYTR5RoiQKM2LT1aUhmmUloOXM14KIewOsJjHCqU9JARBwJXTKwAAN82pVvTZE7gx0t8zEq+FLhIWji/lMedoGMUa1YWo8eGjlVFwL7BQjb9uhGfT+E3WgiAoCtW09Ph6Rpgxsu90B0857VPYH0QtyVAS3hVBufJYwcI0SjKe1CA3dJUYWf6l1lm9mnAomfMcEfSmAXxDpUXZJsVjYt62brsLbUGa+JGAlQiJQ2HFwGRFaeGzSDITuGfkdP/FPFaoqUr42GUT8ezVU/GTC0Yp+mzW7C1Qz4hkCdPEEuYZCdWjRn7eSibaYOm9nX2BNSOAPL03+M67S3p/thTmqS7KhMmgQ7fdxYWVStu4q6Vclt6rFQ4tPSPSgnu6vTemdYTkWiSli/g9C0cDAG5UuMEAvJ6dUAJcV4SanCJZ2XU1md8Wo57XTQkW/nIwbw0JWIlAsElhoHtGIom/M8/IgYYu7mKMNWoqJZoMOlwyuVyx0G24VE65uduOVj9RZ7z0CFrCuuYeaOgK6ipWa5TKPSPyz+y0BfaMAPKYfvB70r/3h0Gv4yJcZvj0KmzjrhZvNomGnhFeDj7x919xthlmgw5uMbYGmSOCDc9t84fjX7efi7u/MVrxe1iD0uNNIUIifF5Xt/DrdAKmSe0wLhhXouq94WrsRFIVdiAwcGbYOOP1jKTmJWMPQFOXvV/Gg5xIwlEV+RmwmvSwO904FqemeZF011RKptnAMyf8y6RrXX01Hgwr9vSGae91BO0No/a8RwzKglEvoLPP6WPwMs9IoNoQSsI0vPuy7P1jS71eGLdb5IZTRow9I6xKbFOXjY8j0XgrDyd+YfKE0mKfUaMmrVc+lsmVear0UpUF3oqnwTLHnK7I55XVN5yNv/9wFn72zbGq3heqxo4oirLQ0cCZc5SQXmcbBZFoKZKJ3Awj312G8o5EopHQ6QQe6gjWSj5alGpGImW41N/BP1SjdV+aeKCkN4za8JTJoMMIyeMiF7F2+oVZ5CgJ0/QEaETG7rWDjV38fgViH6bJzTByrQorSZ9otNSMADIRawwzauwJ2thZjHqUSUUmg22SXFGEwXIzjJhRXaD6PEJ5RuS1jlJVEhApA2eGjTO8AmuK3iCCICjSjURaQIq5zvcrbE+vFjWakUgYEc4YSVEjNBjsfINl1ERilHorsXo+UxRFdPYFD9MoKQnfLYVp5G3jWXZFXWuPj5cv1sYI4K1bczxOHr9waFUOnhGPwmeJTAZgacHHmoLoMzQQi4byCMprsJCAlQhIqqf2Asp0I5Gk9gLqKntGQrzjqEw34t/eeyCGaQB5em8Yz4iK8/YXsdqcbv7cBDZGPJNyqFoj3QHCNLwZYnMP+qTUa6M+PkXpmO7gmEaeEafGLntv4bNYGiOec0qEDovV9QhmTLo0EIt6s5T6X1OHykyjgcTAmmHjiDPFU3sBZRk1kYajmOt8X7w8I1HEdpVQFWTSSqbU3lgyUkrv9dfIMCLxkI3zS+9lNUYEIXDvjqKs8LVGuu1SmEb2fmbEdPQ5US/VAImHVwQIv5jFm2jCCLFgCA/TxFAzkkD9XThjUgvPE7t/61r6N2GMtjt8KpNeZxsF3pbXqWutDs4LXwQo0uwRFqY50drLXfOxJN7Fn7jrv6XXJ247UMM04Xpk2Bzqi70xg7SutQe9dhfXi2SZDdAF+LsJgiCrDBzEGOGeEa+xkWHypkcelDw78TJGqqS+KP4es0TBhNuBrl8iGFLguU9qY2iMeVtrxP+ceJgmyPi18Dyx+jW9Dlc/YS1L6wWANHOMkDGiFPtACNMo0YxE6AnIs5pQKonFQlX2jBTvDiY+178s1wKjXoDd5UZ9h7fi5kAUsALeSfpMpy2g8RhJeKowy4yCTBNE0eNx4TVGAohXGeEyanrs/QWsgHfHzu61WKf1Mnj4LkQvkXiitWeEGemtPQ60BynSpRZ7IjUjhV6jO1B6rxZN6cwGPUpyPMa0/33vkqUaK63BMlAYWDNsHGHWfCqnW6mpSBjJRBHPjJp4T8oGvY4vjHKXPJs4zYb47Ly1Isdi5IWbAon7IvWQjZSEsQcbO0OKVxnhMmqYZ8Tql9LJjRFJcBzrtF7GMMkYaeqyxWwxVoNLWkC18oxkmg28e/HxltgYZInMTGT3SWefM2DF00jLwUdLMCNca42QlqTfGUdIqldgBXybkwUqTiZv7R2JJ2BMWXwyakRRlFVKjN/192ZOeBfGgeoZAYBhknfkSKBuxRGGp5gW5UBDlyytN5QxEtozwowR/66oFdLfar8kmI5XmCbLbOC72MMBrlO8YY+pXsNdcqxFvIl8pjJMepRJNYSOBgjVRFoOPlqCGeGOFM/ajIaBN8PGCWeKV2AFgOIsM0x6HVxu0ScUwVDTHC0QobrfRoNPulscJw1esTGAMTKQKrAyQulGIjVKWXXXgw1d3DMSqr16qPRet1tEj6Rd8e9PwgzHhg5P0bZQBk+0sFDN4RC9fOKFW4Mwgj9cxBsj3Uyi+3wNLQyenu2Kc8mAYPBicn7GyEBYZyIl/c44QhKxM483Op2AMkk8FWjyV9sczZ+plZ7yyLtPtYes8qoWV4Jy74cEyJwYqKm9AFBdHMIYiXD3yjwjnjBN8IJnjFBhml6Hi/f9kAtYAa8xwvDvChxLgqV9JwIephlInhGXVxeRCJhuJFA40qlRHxieTOA3D3vlAKm7zkTKwJth4wSbFFLZGAF8azT445CllUVijFQWZKAoywSHS8TuU7HzjmjpGeFZJQNwpxLKM2KLNEwjeUZqW3pwpiu81yJUrRFW8EwQ+mtCEmuMeK5T2ntGYpRR4+1NkxgdFht/oIwaJ+/9k2BjJD+wfi/elaaTmYE3w8YJrVXtsaIqxIPJFgODTohIMCcIAs4a4vGObDneGsUofZHrW+I5KTN3bm2Lt7GWtyPswHtUmGbk6Jn+mQaRekaKskzIsxohisD22jYAoT0jRVkm3oyN1Qxh8FLwJkO/zIJB2WafsQXqChwrWKuAYDVZ4ol3E5TwX83xzhmx8owkVn9XXRTcs8OzVzQK05xs9a01wjw1aotODgTS74wjhFmsWqnaY8XQALt/RiyEZdOrPMbIxsPNEX+GP4nyjFTkexprddmcaJby/1mFz3gJJLVkSKG3kVhTl1+34gjDU4IgYJTkHdl0tAUAUCj1dwl2fLBQTVeAGiMMnc77PiAxYZrjzT0+FTITAVsstQzTxLphoCPBtXtCeXYcGnmeWGZjt93lk+Vjd5JmhAiDW0wDz0gMhGXnjRoEANhwuBm99tjoRuR6nXjm3ssbazFjjWlfzAPQGDEb9HxB9w/VRGOYjpB0I4xBUjZKMIJl1PQEqL4qh/VNAeJrjJTmWGA16eF0izHt0aKEZAjTyBsGxiJUo5WAta3HgbYeX6ObpfYmOkvSYtSjKMtzTeWhGu4ZIWOECEY8W9gnElZR8nhzT8xc83JGlWRhcF4GbE43NhxuinygMhJZmGiIn/Keh2kGqNu0ushjOBxtCtwg0BzBpDhqkK8xwupUBCOYZ4Q3yQvgGQE89xojlPclWnQ6getrEq0bcSaBZwQI7VFVS1+CM9SsJm96tn+ohunk9BrU9WDeEbkR7q3BktrrTCQMzBk2DvDdeYpXxQsUimBE2rFXjiAI+NqYYgDA/+1tjHygMpwJVJh7e9T4ekYGYpgGAKoLA5c7j8YwHSk14WMMyraEPD6YZ4SXgg/iGRlXnsP/P6O6UPU41cDTexNciZV7ZDVenEJ5VNXSw43M+KVj+xMsVKOlFpDd93LPCAvTpFvHXoCMEcVwYyTFLVaLUY/yXI9F7v9gxqoY0QXjSgEA/7e3gbuZo0ELzwhzx7Nd3EA1Rtgk7Z9dFU1K80g/z0hJ2DBN4FojXMAaZNG6YFwppg3Nx01zqnkYIV54y8In1jOSLJsg7hkJkB6rFq8wOXHPFE9Pbgpc10MLYy9Qew5HgsW9yQQZIwpxJsmkEAuGBnkwY1WmedawQmSbDTjTacP2E21RfRYg79eQuF4WbAdo456RgfmoBHO/e4u9qV8w/MMyobJpAK8x4q/H8ApYAxsjWWYD/nnrbDzwrXGqx6iW4YOkMI1GxojWwvnYekZYIbsEGiNBGubFuxt4KLxhGu99T5oRIiwDoegZI5jLMlaeEZNBh3mjPaGazw5ErxvhtQAS4Rnxq8My0MM08ntBriGyRXEvCIKA5Zd4DIS7LhileAz1HX0+omfmzk/kDjoY8jBNoIZr8YI5FrXeBMVSM8K1QEHCb/EgmDGlZcXTQL3CHFKYZiDWNQpH+p1xhAyUOiNA8IqK0SxA/syoKgAAbK2Nvt5IIqskskm3uduOzj6HTMCq/YIYDyoLMiAInhRDuYYoWv3Q4nOrsf6nX8NtXxsR9th8qxE5UmE0eTO2bnvgUvBaUF2UCUEA2nsd/bRW8SRZNkFVQQzGSOjlnZgT90yx5/qInzGpZcXTioL+xoidetMQ4UiWSSEWBPOMxDJeyYqfbattjVo3kkjNSLbFyDMzjjf3yOqMDMxHxWwIrCGy8ZTmyM+7It+q6G8mCN5slWMyIa23SZ72hqDF6E2DTmRGjdZdexl5MoMx2vRmZmRmJNDIHF6cBZ1kTJ7ptPHXtWyEyTwjbT0OHpJMdNpzMpF+Zxwh3gUx9S9ZVZCKhPYYlmkeU5YNi1GHjj5n1HH2RGpGAF8R60AP0wCBuxVz4W6CPEJVvDS9dwzdktAxkVkXodAio8adJFo1QRCC6i7UokX4zWLU8/Hvb/B2FbdFoY2KlmyL18BjIlYWkqYwDREU9wAK0wwt8DyU7b0OtMbQNS/HqNdh4uBcANF38WW7hURdeuaSPtrUzcM00XgIkp1AxmksPCOqxlAY3DMSTMCaaIYVJb4svNczkrBfGZRoetS43CKapV5FPRqF30ZLKef7673GiJaeEUCe3ut59ihMQ4TFmSSq9liQYdKjLNdT+0FeX8L7YMbmHFm9iWgnb1aYKFGNtZinQD5pJYNuIV4MKWDpvd57IdEeoUBN+7qTSMAKeDNqEpXeK4oi71qstWcEiLx7r83pwvdWbcC0x/4Pq9cfRY+NCVgT+3cdXRrcGElUATZ//NN7KUxDhGUgCViBwJN/rFJ7GawR25Eo3dreXhYJajkueQqYR0evE5JmQYwHgRYZm1ZhGplBpNUOOhjMM+JfIC5euGRaq2TQqkXqGfm/PY3YKjVNfPz9vVwzEs8S/oFgnpEDPmEaqSu3VsYIS+9t8w3TkDFCBGUgCVgBYFgxM0a8u7xYZtMAset2Gk0BrkhgngJmqOVY+neNHUj4F3oD5J6RxFzzammhO9PpbcbmFbAmhzHCBKyn2/piUswvHC5Z1kcyeGSrIkzv/Xi/txIzm0fNBh3yrIk1RkaVMmOki//9tPaMVATxjGhlHGlJRGe8cuVKVFVVwWKxYObMmdi8eXPQY+fPnw9BEPp9XXzxxREPWgsGmjHi7UkSKEwTmwdhhCT4O9bU47PLU0ui47ps0mXEsz19MsB2vC3ddnT0eTqI8pTmBIVpcq3eZmxMNxKuN02iKc21QBA8xnEi0nvdsgbByRCmYffJqbZe7lFQAvNEMA0ZwK5lYs+pqjATJoMOvQ4X6lp9NRraaUZ8qw/bNUw11hrVf4HXX38dS5cuxfLly7F161ZMnjwZCxcuRGNj4D4kb775Jk6fPs2/du3aBb1ej+9973tRDz6RDJRGeYxAIZRYxyvL8zJgMuhgd7n7NUFTQyy6CauhINPksxvPCVNBNNXJMhtQlOWpmlorNVBkKc2J3DF6w0WSMSJl0ySLZ8So16FYuk717X1x/31yz0gyzDtFWSZkmvRwi/1L9wfD7Ra5MXLb/OH89TwNDHy9TuCtCvae7oTbLXr1aBqFRQbn+fanIc2ICp5++mncfPPNWLx4McaNG4dVq1bBarVi9erVAY8vKChAaWkp/1q7di2sVmvKGSPSPTtgLNZqWZqev8syVrsEvU7gC4x/i3o18HEl6AEVBIEXSQKAnIzkWAzjyVCZIWB3ublw0pzAlOYqv1oj3RoJHUNRJsX4T7UrW4yjQe5N1LprL8CeC3W6kaZuG/ocbugEYMG4Ej7vTKnMi9cwQzK2zNNccV99B9/kAIm9z+UwAeuZThv6HC5vai+FaUJjt9uxZcsWLFiwwPsBOh0WLFiAjRs3KvqMF198Ed///veRmZkZ9BibzYaOjg6fL61xSZ6RZIjdxoKK/AwY9QL6HG6c7vDs8tjDGUnb+GBUBunIqgYt0u/kzd4GumcE8C33zbRDQGKLvVUXemuNOF1uPo5gXXu1oCzHk4V2ui3+xog7yQSsQPC+VsFo7PCk8xZlmWHU6/DKjTPw/HXTsOybY+M2xlCMkXQje093+NznWnlG8q1GZEiG0On2PpkXODn+3olE1V+gqakJLpcLJSUlPq+XlJSgvr4+7Ps3b96MXbt24aabbgp53IoVK5Cbm8u/Kisr1QwzLjCLdaB4Rgx6HU9hPSqFatiiH0sXYaX0O+qiCNNoIepiackAUJgV346wyQCrPXO8uZuLVwUhsZO0vKhWt6zkeLLUGQGAsjzJGElwmCZZph0uuFRojLFwVolkxFXkW7FwfKlmRQTHSZ6Rvac7fXQvWi3+giD4iFgdfJ0hz0hcefHFFzFx4kTMmDEj5HHLli1De3s7/6qrq0vQCIPjFgeWgBWQi1g92S5cWR7D3TAXaLXEwDOSwIVR7kYeV5Yb/MABAktnPt7cA5vDm2GQSJGhvCQ8q9Jp1AtJ5bJmpfMTYYwwz4hOQNJkc1VwT6eyzUVDJzNGzGGOTAwsTFPb0oPWbo9Y25Tg+9yfwfne7r3pUPE5GKqe8qKiIuj1ejQ0NPi83tDQgNLS0pDv7e7uxmuvvYYbb7wx7O8xm83Iycnx+dIaZ5KUZY4lLL2X1U3w9mGJ3YMQC8+IFor3mdUFfLd07ojChP1erZCXhNdqQmSekeZuO1/sk8krAsg9IwnQjCThBihQp9lQsD4wxdnJYYzkZ5pQKnlpvjrRBkC7tF6G/JqyZy/DlDwGeKJQdcYmkwnTpk1DTU0Nf83tdqOmpgazZs0K+d433ngDNpsN/+///b/IRqoxvOjZAIrl+Rc+i0eHWuYZqYuiuVYsy9QrxaDXoWbpfLx9+7lctDeQkXdlZWmridZqyLN6dp/q0GQM4SiTPCOn2hIQpuGekeSZc1inWaUasLYej/chz5o8oc6xZZ4Q7Pa6NgBJYIzIwjSso3EGeUbCs3TpUrzwwgt4+eWXsXfvXtx6663o7u7G4sWLAQCLFi3CsmXL+r3vxRdfxGWXXYbCwtTcZboGUKM8Rn9jJPb9SJhnpFXWmVItXMuS4EljSKFVM9V/osmzGpEtNe3aIxkC7PtEUi2Fi3ZIC4UWYwgFa6PQ0NEXVe0cJbA6I8noGWlT+Dx39ErGSBLV6mGhmh2SZ0TrpnQVMpF/bxqHaVQ/6VdddRXOnDmDhx56CPX19ZgyZQrWrFnDRa21tbXQ+S3Y+/fvx/r16/Hhhx/GZtQa4BqAYRr/ipLcGImhZyTHYkRuhhHtvQ6caO3BmFL1IbdYl6kn+iMIAqoKM7HzZDt2nfKUwdeivkdVYSa+ONaKbbWtAJDwKp3hGJRthk7whG2bu2wYJLn84wEP0yTRnJMte55Ptvbyfi/BaJOMkUSXfg/FGMkY2XXSY3Rr3RVaLgpmG0EyRhSyZMkSLFmyJODP1q1b1++10aNHQxTjXz45njgHWAVWACjNsUCvE2B3udHUZZNV3Yztol9ZkIH2kw7UtfRGZIxo3VkzXRhSaMXOk+3YfVI7zwjTjRyWMrxYVdZkwaDXoSTHgtPtfTjV3hdfYyRJm3NW5GfwzUU4Y6SdeUaSyKgcV+Y7Zq29NnxT2N7Lw5QUpiGC4h6AmhGDXsfFXCfaeuMiYAW8tUYi1Y1okU2TjrACdfulipnZGtRXYaFDRjJpDRilUqimPs4i1mTN4FOT3tvW49EfJVNLharCTB+diNZem+IsM8wGHdwi0CgJfjOSqNBfoqDZXSHOJBSTxYJyKTvgVFsvT+mMtTHCRawRZtQ40rgqYSJhXWkZmnhG/MTC+Um0o2Yw3Ui803uTUcAKeEuYKxGxtvd6dCV5GcljVBr0Oh+PjtbGiCAIXMTKIM8IERSeTZNku5Ro4Wllrb1x69TKRKyRVmGNdTdhIjDjyn1DaFp4RqqKrJCvvfnJ6BnJ8Twz8e5P4xXNx/XXqKZCVhcjHF02T5gm2YTIY2Xh4mTw2jARKyMdNSNJdpsnLwOtay9jcH7/HPdYpvYC0Ydpeh2e3VUiS5OnI8OLs3wqUWqxgFhNBh/vSHleRoijtYF5Ruo74muMuJNQwAr4pqKGwiOK92wkki3sMLYseTwjAFDp5xlJx7ku/c44QgaqMcIm+1NtvehzxidMUymrTRCJkLmzz2OMpEOPGC0xGXQYOcg7SVfka2MIjCrxhotYGmYyUZroME2SzTn+be+D0Scrt55sYYcxsvsqGUTS5BkhY0QxTinpf6CGaY439/DJL9ZWOXvQumxOXgRJCV02Jzr6HNwY0SJskG7IF/8Rg7JCHBk/LplcDsCjFxlaYA1zdOLhnpE4GyPJK2D1/E2au+28SFcgeuzJa4xMqshFaY4FQwutuHhSmdbD8TH8TXpdTPuDpQrJFchLUkRRBKtvlGwTQ7QwY+TwmS7+WqytcotRj+JsM8502lDX2oN8BTuRbbWtuOaFTcgw6dEiVQRNtrjzQOQb40vwz60nAHjCNlrwrUnlyDQbUJhpSjqvACDPpumDKIpx62vCOtwnW5gmN8OIbLMBnTYnTrb1YMSgwOm9zFAxG3RJ93e0mgz45N75MOh0STGny40Rdn+lGzS7K8CVhK28YwWL/7JT1MWpU2tFfgbOdNpworUXkyrywh7/9raT6HW4eEVCgIyRRLBwfCmevnIysswGTV3FXxs9SLPfHY5B2Z7Fwu5yo6XbjsKs+PRdYd7YZFvIAc+8sa++E3WtvcGNEenZtSaZXoQRy+KO0SIP0xSlQZfwQKSfLygCnAPYGLGaDD7pkzkZxrhMfmpFrJuOtvR7jcI0ieE7Z1XgG+NDN75MZ0wGHS9OFU/dCCsHn4yhYbZ4hhKxMs+INcn6CyUjcgPkWHPkfbxSGTJGFOAWB64xAvhmLMRLWc5ErEpqjYiiyPvlyMlOsg6uRPqSCN0IKwefbHVGAGUiVqYZScfMELUIgoDLpw4GANx63nCNR6MNdJcoYCB7RgBvJ1IgjsYI94yErzXS1GWHzemG/xycjO5qIj0pTUB6rzuJM/iUVGFlKfnkGVHGU9+dhD//YAYWzR6q9VA0gYwRBbhcXmPEMIC69jJYFVYgnp4RyRhR4BlhE1xpjgULx3saMM6sLojLuAgiEhLiGUnS1F7AK3wPVfis1y7VGEmyTJpkxajXYd6o4qTSsiQSMlkV4JKFaZJwXogaeZgmXtUIK2Vtst1uMeQEy3p+lOVa8NAl4zGhPBeLZlXFZVwEEQmJqDXi7dobt18RMfK298HosXs8I8lW8IxITgbeNj8OyAuexSuNT0vkKZzx8oyU5VmgEzxN75q6bCGPben21CIpyDRjcF4GfnT+SOQmYY8SIn3xVmGNX7O8VAjTnOm08crN/iR7Ng2RXJAxogBnEk8KsUDek4R1bo01Rr2Oa1PChWpapU6fydgkjSAAb3+aRHhGklHAmmc1ciPjVBDdCMumoTANoQQyRhTAdyhJOCnEgvJcC8aUZqMoy4QrzqqI2+/h3XvDiFhbpSJnSoqjEYQWlPkVPosHydyCQhCEsCJWlk1DYRpCCaQZUYBzgHbsZQiCgDdvmw2HU4xrOKSywIpNR1vC1hpplUrG55FnhEhSmGakx+5CR58zLuHNZC0Hz6jIt+JAQ1dQ3UgfhWkIFZBnRAEuqfqQPhmVZDHCajLEXZfB03vDhGnaeJiGPCNEcmIx6rmxHK+MGlYOPhnDNED4jJoeCtMQKiBjRAHJ2iMi1VDa7bOtV/KMJEFrb4IIRmlOfGuNJLOAFZDVGgnyPHvDNOSAJ8JDxogCWI+IZJ0UUgWltUa6bZ6UwCzqRUMkMV7dSHwyapJZwAp4+1qFC9NkUAVWQgF0lyjANcA1I4mClYQ/1dYHJ3M3BaDbTpUbieSnNDe+GTVeAWtcPj5qeH+aoAJWeo4J5STpbZ5cJHMlxFSiJNsCk14Hl1sMOYH32Dw7qkwzxZqJ5CXeVViTX8DqMcbqO/pgd/bfXLA6I5RNQyiBjBEFkGckNuh0AnfthgrVMM9IJu2oiCQm3lVY+SYoScM0hZkmWIw6iCJwOkCoiuqMEGogY0QBA73oWSIJJ2J1uUX0OTy7LEoJJJKZeHtGkrnOCOApCcAyagKJWJmAlZ5jQglkjCgg2VXtqQTvaRGk1giLMwNAppk8I0TywoyRU229cSl8xsM0SeoZAUL3qKEwDaEGMkYU4PWM0OWKFiZirQuTDqjXCTAb6HoTyQtbiDttTrRJhfpiCa8zksSbIJ5RE0DE2ksVWAkV0GyvANKMxA5e+CyIZ4Sl9VpN+gHZlJAYOFiMepTkmAEAx8NUFY6E1PCMBC98xsM0RvJwEuEhY0QBlE0TO8LVGmETGIlXiVRgaEEmAKA2DsZIKsw73iqsvp4RURR5mMZiomWGCA/dJQoY6L1pEkmltJNq6LDB5uzfepx7Riitl0gBmHFd29wd889O9jojgKzWiJ8xwkToANUZIZSRxLd58pDsqvZUoiDTxFP9QinwyTNCpAJDCz2L8fHm9A7T1Hf08XkS8IpXAUrtJZRBxogCXCkwKaQKgiCEFLF6q6/SBEYkP9wYSdMwTVGWGQadAJdbRGOnN8WZZcWZDDraxBGKIGNEAaxrr2EAd+1NJKFErCxMQ2m9RCpQXeTRjBw50xXzz06FTZBeJ6Akh6U4e42RXqoxQqiEjBEF8K69ZOHHhFAi1m4bTWJE6jBiUBYEAWjqsqOpyxbTz06V+kZMxHpKlt7La4xQiIZQCBkjCmCekWTeoaQSoaqw9lApeCKFsJoMGCIZ1wfqO2P62alQZwQAyvJYWXzv89xDNUYIlZAxogAqBx9bmGckUBXWbubepWwaIkUYXZINANgXY2MkFQSsAFCe5+3GzWCeEfJwEkohY0QBqeIuTRUq8oMLWHskzUgWaUaIFGFMqccY2R9zz0jyC1gBoFxWFp9BTfIItZAxogDyjMQW5hlp6bajy+b0+Rn3jFCYhkgRxpTlAAD21nfE9HNTQcAKyDwjAcM09BwTyiBjRAFUDj625FiMyLMaAfQvI91Dqb1EijG+3GOM7KvvhMPlDnO0clyu5C96BgBluR5j5HSgMA15RgiFJPltnhykirs0lRjCK1f6GiOUTUOkGkMKrMi2GGB3unGoMXYpvtwzkuQNOsslAWtztx19khHSK20qSMBKKCW57/IkgcrBxx5eRttPxNpLYRoixRAEAeOkUM2uk+0x+1x3CpSDB4DcDCPfPJxu93hHKJuGUEuS3+bJgbccPF2uWME8I/6Fz3ocFKYhUo8Jg3MBALtPxU43wjwjuiTXjAiCgDJJxHpaErFSnRFCLbS6KiAVGlalGkOCeEZoR0WkIhMGx94zkko9sZiI9SQzRqgCK6ESWl4V4BWw0uWKFcGMEZrEiFRkQrnHM7LndAcPr0QLrzOSCsYIE7FKYZpe2lQQKqHVVQGU2ht7WH+aE629PpN3D2lGiBRkWHEWLEYdeuwuHG3ujslncuF8kodpAHnhM49npIfCNIRKyBhRQCrtUFKFsjwL9DoBNqcbZ2Q9PcgzQqQiep2AsTEWsaZSTyxWEp7CNESkRGSMrFy5ElVVVbBYLJg5cyY2b94c8vi2tjbcfvvtKCsrg9lsxqhRo/D+++9HNGAtcLrIGIk1Rr2OpwSyUI3D5YZdmoFpEiNSDVZvZE+MRKypUg4e6B927eGpveThJJSh2hh5/fXXsXTpUixfvhxbt27F5MmTsXDhQjQ2NgY83m6344ILLsCxY8fwj3/8A/v378cLL7yAwYMHRz34RMEa5VFqb2zxrzXCQjQAxZqJ1IP1qDkYo1ojqVTfaGih51k+2doLp8vNKytnU1sHQiGq75Snn34aN998MxYvXgwAWLVqFd577z2sXr0a9913X7/jV69ejZaWFmzYsAFGo6fqZlVVVXSjTjCpkmKXagwpsOK/aOa7Keba1esEmCh1iUgxhg/KAoCYFT7zhodj8nFxpSTbApNBB7vTjVNtfejqk3pMWcgYIZSh6ja32+3YsmULFixY4P0AnQ4LFizAxo0bA77nnXfewaxZs3D77bejpKQEEyZMwBNPPAGXyxXweACw2Wzo6Ojw+dISKgcfHyr9ao3IS8ELZPgRKcYIyRipa+3hlUijIZUErDqdgKHS83ysuRudkjGSTcYIoRBVxkhTUxNcLhdKSkp8Xi8pKUF9fX3A9xw5cgT/+Mc/4HK58P777+PBBx/Er371Kzz22GNBf8+KFSuQm5vLvyorK9UMM+ZwzYg++SeFVKJ/nJlEb0TqUpxlRo7FAFEEjjZFn1GTSnVGAG+o5nhLDzqp+zahkrg7AN1uNwYNGoQ//OEPmDZtGq666ircf//9WLVqVdD3LFu2DO3t7fyrrq4u3sMMSap0z0w1mDFynIVpHJTWS6QugiBw70gsQjWpJGAFgCEFmQCAQw2dsDs9Ortsi1HLIREphKpZv6ioCHq9Hg0NDT6vNzQ0oLS0NOB7ysrKYDQaodd7d7tjx45FfX097HY7TCZTv/eYzWaYzWY1Q4srqbZDSRWGFnomrzOdNnTbnN7qq1SbgEhRhhdnYWttG46ciZ1nJBUErABQVeTZXOySZRORZ4RQiirPiMlkwrRp01BTU8Nfc7vdqKmpwaxZswK+59xzz8WhQ4fgdntbax84cABlZWUBDZFkhBrlxYfcDCMKMj33wLHmbvTYqC8NkdqwUIV/ZeFIkKLDKeQZ8Zz77lOeOiuZJj1t4AjFqA7TLF26FC+88AJefvll7N27F7feeiu6u7t5ds2iRYuwbNkyfvytt96KlpYW3HHHHThw4ADee+89PPHEE7j99ttjdxZxxk2ekbhRJU3eR5u6qS8NkfIMkbx9tS2x8Ix4NnCpMu8wT2efg0I0hHpU+9CuuuoqnDlzBg899BDq6+sxZcoUrFmzhotaa2troZP1cKmsrMQHH3yAn/zkJ5g0aRIGDx6MO+64Az/96U9jdxZxxklde+NGVVEmtta24VhTN3KtHi9JJmlGiBSF66CaY+AZSaEKrABQkZ8BvU7g4aWSnOQJtRPJT0Sz/pIlS7BkyZKAP1u3bl2/12bNmoXPP/88kl+VFFBqb/yolnZTR5t6MLrUY+xRmIZIVVh6a2OnDb12V1RevlTzyBr1OlQXZXLxbmmuReMREakEbfUVkGpCslSiqshjjBxrpjANkfrkWY28tkZda3TekVQstsiq0AJAaQ4ZI4RyyBhRAHlG4kc1M0aauqm5FpHyCILgrbcRZagm1TwjADCpIpf/vzQ3Q8OREKkGGSMKcKaYkCyVYJ6R5m47Trf3AaA6I0Rq49WNRCdidaVQOXjGgnHegpgXjCsJcSRB+EKzvgLcKSYkSyWyzAYUZZnR1GXD9ro2AEC+lVT4ROrCin9Fm96bSuXgGcOLs/C7a6bCatLzAnAEoQQyRhRAnpH4Ul1kRVOXjU/eedbUqD9DEIFI5zANAHxrUrnWQyBSkBRyAGoHr8CaQjuUVKJKyqhh5JJnhEhhhvo1gIyUVBSwEkSkkDGiAB67pUZ5cYHpRhj55BkhUpghkmekrrWHb2QiIdXqjBBENJAxogDWtZeyaeJDtZ8xkpdBnhEidSnLzYBRL8DhEnG6vTfiz+GN8mjeIdIAMkYUQGGa+OIfpiHPCJHK6HUCKvKlHjVR6EackmuEwjREOkDGiAJctEOJK6zbJ+C5xqQZIVIdnt4bhW6ERXho3iHSATJGFMCLnpFmJC7I64pQ1UZiIFAVg4wa8sgS6QQZIwpgmhFyl8aPV26cgbJcC5Z9c4zWQyGIqGHde6MpfEbCeSKdoDojCmBCMgN17Y0bc0cWY+Oy87UeBkHEhKEx6N7rJs8IkUbQ6qoAZ4oWHyIIQhuYDqq2pQeiGFl6L68zQrM0kQbQba4AFxkjBEGooCLfCkEAumxOtHTbVb9fFEUwG4Y8I0Q6QMaIAsgYIQhCDRajnouxj0UQqpEXS6N5h0gHyBhRAM+moUmBIAiFsB41tS3qRawuWWhHR/MOkQaQMaIAapRHEIRahhawjBr1nhHWKRygMA2RHpAxogA39YggCEIlrEdNJFVY5Z4RmneIdICMEQUwzwiFaQiCUAprc3AsglojLpcsTEOeESINIGMkDKIo8rLMFLslCEIpXs0IeUYIIhxkjIRBrmonzwhBEEphYZqmLjs6+xyq3iufd2jaIdIBMkbC4KQUO4IgIiDHYsSgbDMA4FBjl6r3sqrPOgEQKExDpAFkjISB8v0JgoiUkSVZAICDKo0Rqm1EpBtkjISBYrcEQUTKyEHZAICDDZ2q3seMERKvEukCGSNhkKvaqVEeQRBqiNQz4m3OScYIkR7Q6hoGJwnJCIKIkFElzDMSWZiGMviIdIGMkTCwHYpeJ5CQjCAIVYwo9nhGTrb1osvmVPw++bxDEOkAGSNhcJKQjCCICMnPNKEoS31GjYtVfaYNEJEmkDESBqYZoUmBIIhIGCXpRg6oELFSmIZIN8gYCYOLhGQEQUTBmNIcAMCeUx2K38NTe2kTRKQJZIyEwcU69uppUiAIQj0TKzzGyK6T7Yrf4yLNCJFmkDESBiftUAiCiIIJ5bkAgD2nO3yKKIbCG6aJ27AIIqmgWz0MVAmRIIhoGFacBYtRhx67C0eblHXw5dk0tAki0gQyRsJAxghBENGg1wkYV+YJ1ew+pSxUQwJWIt0gYyQMlNpLEES0TBzsCdXsPKHMGHFTeJhIM8gYCQObFCibhiCISBkvGSNfKRSxkoCVSDfIGAmDk9ylBEFEydTKPADAVyfa4GAVzUJAjfKIdIOMkTC4yDNCEESUDC/OQm6GEX0Ot6J6I7xRHpUUINIEMkbC4BWw0qUiCCIydDoB04bmAwC+PN4a9njmPCHPCJEu0AobBq8xovFACIJIabgxcqwl7LGUxUekG7TEhsFJnhGCIGLAOcMKAQCfH2nmwvhgUDl4It2gFTYMTGxmotgtQRBRMKkiF5kmPVp7HNhbH1o3wrJpaA9EpAt0q4eBGSMGmhUIgogCo16HGdUFAIANh5pDHuumMA2RZtAKGwanyzMpGA10qQiCiI5zRxQBADYcbgp5HKX2EulGRCvsypUrUVVVBYvFgpkzZ2Lz5s1Bj33ppZcgCILPl8ViiXjAiYZ5Roy0QyEIIkpmDffoRjYfbQlZb4SKnhHphmpj5PXXX8fSpUuxfPlybN26FZMnT8bChQvR2NgY9D05OTk4ffo0/zp+/HhUg04kDmmHYqR0GoIgomRsaQ7yrUZ021346kRb0OOoHDyRbqheYZ9++mncfPPNWLx4McaNG4dVq1bBarVi9erVQd8jCAJKS0v5V0lJSVSDTiQOp6QZIQErQRBRotMJ3DsSSjfiFbDSvEOkB6qMEbvdji1btmDBggXeD9DpsGDBAmzcuDHo+7q6ujB06FBUVlbi29/+Nnbv3h3y99hsNnR0dPh8aYXTzbJpyDNCEET0zBrOdCPBjRHyjBDphqoVtqmpCS6Xq59no6SkBPX19QHfM3r0aKxevRr/+te/8Oqrr8LtdmP27Nk4ceJE0N+zYsUK5Obm8q/Kyko1w4wpDheVZSYIInacK3lGttS2os/hCngMFT0j0o24b/dnzZqFRYsWYcqUKTjvvPPw5ptvori4GM8//3zQ9yxbtgzt7e38q66uLt7DDAoXsJJnhCCIGFBdlInSHAvsTje2BCkNL+2BKExDpA2qVtiioiLo9Xo0NDT4vN7Q0IDS0lJFn2E0GjF16lQcOnQo6DFmsxk5OTk+X1pBxghBELFEEATMHiHpRoKk+LqpQSeRZqhaYU0mE6ZNm4aamhr+mtvtRk1NDWbNmqXoM1wuF3bu3ImysjJ1I9UIXmeEwjQEQcSI2WF0I1zASpoRIk0wqH3D0qVLcf3112P69OmYMWMGnnnmGXR3d2Px4sUAgEWLFmHw4MFYsWIFAODRRx/FOeecgxEjRqCtrQ2//OUvcfz4cdx0002xPZM4YWcVWMkzQhBEjGBN8/ac6oDT5e43v1CDTiLdUG2MXHXVVThz5gweeugh1NfXY8qUKVizZg0XtdbW1kInK53e2tqKm2++GfX19cjPz8e0adOwYcMGjBs3LnZnEUe8nhGaFQiCiA1DC6zIMhvQZXPi8JlujC7N9vk5CViJdEO1MQIAS5YswZIlSwL+bN26dT7f//rXv8avf/3rSH5NUsBSe6kCK0EQsUKnEzC2LBtfHGvF7lPtQY0RCtMQ6QJt98Ngd1JvGoIgYs/48lwAwO5T/esouakcPJFm0AobBuYZIVU7QRCxZHy5J0tw96n2fj8jzwiRbpAxEgaW2msizwhBEDGEeUb2nOqAKHlCGNQoj0g3aIUNA6/AqqNLRRBE7BhZkgWTXoeOPidOtPb6/MxNAlYizaAVNgzeomc0KRAEETuMeh1GlWYB6B+qkaYdCtMQaQMZI2Gg1F6CIOLF+DJPqGbXSV8Rq1fAmvAhEYQm0K0eBruTysETBBEfxg8OLGJ1UddeIs2gFTYMPQ4nAMBq0ms8EoIgBhrejBpfz4iTa0ZoiibSA7rTw9Bj97T4ziBjhCCIGDO2LAeCADR22tDUZeOvUxYfkW7QnR6GXskYIc8IQRCxxmoyoDLfCgA41NjFXyfhPJFukDEShh4yRgiCiCMjBnkyag4GNEZoiibSA7rT/Xhz6wnc+do21Lf3AfB6RjJMEbXxIQiCCAkzRg7LjBHehoKMESJNoBVWxuEzXbjrjR0QRaC5244/3XA27NIOxWokzwhBELGHGSPyMA1v0ElhGiJNILNbxn8PNYFVZf7sYBP21Xfyn5GAlSCIeOAN03jnGxKwEukG3ekytte1+Xz/jy0nAAA6ATDTpEAQRBxgxkhDhw0dfQ4AgIPCNESaQXe6jKNN3QCAuSOLAAD/3OoxRqwmAwQqPkQQRBzIsRhRkmMG4A3VsPAwdQsn0gUyRmScbvOIVm+YXQWdAHT2eQqeUYiGIIh44q8b4ZoR8sgSaQLd6RJOlxuNnR5jZOLgXMyoLuA/Y7sWgiCIeDCiWMqoOeMxRliYxkRhGiJNoDtdoqHTBrfocYsWZZnxzYll/GfDirI0HBlBEAOdYZIxcuSMJ1RMdUaIdIPudIlmqRRzUZYZOp2AC8eX8p9V5GdoNSyCINKA4X6eETtVYCXSDDJGJNp6PCr2PKsRADAox4JfXzUZUyrz8N1pFVoOjSCIAc6w4kwAQG1zDxwuN5wuyqYh0gsqeibR2mMH4DVGAODyqRW4fCoZIgRBxJfSHAusJj167C7UtvRQmIZIO+hOl2jvlTwjGSaNR0IQRLqh0wmoLvJ4Rw43dlGYhkg7yBiRYGGa/ExjmCMJgiBiD9ONHGnqJs8IkXbQnS7BwjS55BkhCEIDmG7kcGMX14xQOXgiXaA7XYKFaXIzyDNCEETiYZ6RQ2e64HR7jBGqwEqkC2SMSHTbPNVWs8xUbZUgiMTDPCP7ZQ06qQIrkS7QnS7RbXMBALIslGBEEETiYcUVe+wu/prFQJsjIj0gY0SiS/KMZJrIGCEIIvFkmPQYnOctsJhh1JNmhEgb6E6X8IZpyBghCEIbWKgGALLJS0ukEWSMSDBjJJOMEYIgNIKJWAEyRoj0gowRiS4yRgiC0JjhMs9IDmX2EWkEGSMARFFEtyQaozANQRBaMczHM0LGCJE+kDECwOZ0wyXl9WdSai9BEBohD9NkGGl6JtIHutvhm0pnpWwagiA0oiTHzP9fnG0OcSRBDCxo5QVgc3qMEZNeBz1VPCQIQiMEQcBr/3MONh5uxjUzh2g9HIJIGGSMALA5PE2pzJTTTxCExpwzrBDnDCvUehgEkVBo9YVHMwIAZorREgRBEETCodUXQJ/DE6YxU+llgiAIgkg4ZIxA5hmhMA1BEARBJBxafSETsJIxQhAEQRAJh1ZfyASsRgrTEARBEESiIWMEFKYhCIIgCC2h1RfeMA0ZIwRBEASReGj1hdwzQmEagiAIgkg0ERkjK1euRFVVFSwWC2bOnInNmzcret9rr70GQRBw2WWXRfJr44aNpfZSnRGCIAiCSDiqV9/XX38dS5cuxfLly7F161ZMnjwZCxcuRGNjY8j3HTt2DHfffTfmzp0b8WDjBWlGCIIgCEI7VK++Tz/9NG6++WYsXrwY48aNw6pVq2C1WrF69eqg73G5XLj22mvxyCOPYNiwYVENOB4wY8RC2TQEQRAEkXBUGSN2ux1btmzBggULvB+g02HBggXYuHFj0Pc9+uijGDRoEG688cbIRxpHSMBKEARBENqhqlFeU1MTXC4XSkpKfF4vKSnBvn37Ar5n/fr1ePHFF7F9+3bFv8dms8Fms/HvOzo61AxTNd5GeeQZIQiCIIhEE1dXQGdnJ6677jq88MILKCoqUvy+FStWIDc3l39VVlbGcZRAH3lGCIIgCEIzVHlGioqKoNfr0dDQ4PN6Q0MDSktL+x1/+PBhHDt2DJdccgl/ze32eCEMBgP279+P4cOH93vfsmXLsHTpUv59R0dHXA0SbwVWMkYIgiAIItGoMkZMJhOmTZuGmpoanp7rdrtRU1ODJUuW9Dt+zJgx2Llzp89rDzzwADo7O/Gb3/wmqIFhNpthNpvVDC0qqM4IQRAEQWiHKmMEAJYuXYrrr78e06dPx4wZM/DMM8+gu7sbixcvBgAsWrQIgwcPxooVK2CxWDBhwgSf9+fl5QFAv9e1hASsBEEQBKEdqo2Rq666CmfOnMFDDz2E+vp6TJkyBWvWrOGi1traWuh0qbWoU50RgiAIgtAOQRRFUetBhKOjowO5ublob29HTk5OzD//6j98jo1HmvHbq6fi0snlMf98giAIgkhHlK7f5AoAhWkIgiAIQkto9QWFaQiCIAhCS2j1BWXTEARBEISWkDECb5jGQnVGCIIgCCLh0OoLKgdPEARBEFpCxghkYRryjBAEQRBEwqHVF5RNQxAEQRBakvarryiK6KMwDUEQBEFoRtobI3aXm/+fwjQEQRAEkXjSfvVlehGAwjQEQRAEoQVpv/qyTBoAMOnT/nIQBEEQRMJJ+9VXLl4VBEHj0RAEQRBE+kHGCJWCJwiCIAhNSfsVmBc8M1ImDUEQBEFoARkjVGOEIAiCIDQl7VdgCtMQBEEQhLak/QrMjBELhWkIgiAIQhPIGHFQmIYgCIIgtCTtV2BvmIY8IwRBEAShBWlvjPQxzwiVgicIgiAITUj7FZgErARBEAShLWm/AlOYhiAIgiC0hYwRqjNCEARBEJqS9iuwtwJr2l8KgiAIgtCEtF+BKUxDEARBENpCxgiFaQiCIAhCU9J+BSbPCEEQBEFoCxkjpBkhCIIgCE1J+xWYhWksFKYhCIIgCE1I+xWYh2moUR5BEARBaAIZI1SBlSAIgiA0Je1XYG/XXvKMEARBEIQWpL0x0keeEYIgCILQlLRfgW3UtZcgCIIgNCXtV2A71RkhCIIgCE1Je2OEBKwEQRAEoS1pvwLzcvAUpiEIgiAITUj7FZhXYKUwDUEQBEFoAhkjFKYhCIIgCE1J6xXY7RZhd5ExQhAEQRBaktYrMDNEAMBC5eAJgiAIQhPS2hhhehGAPCMEQRAEoRVpvQKzTBq9ToBBn9aXgiAIgiA0I61XYBKvEgRBEIT2pPUqzGuMkDFCEARBEJoR0Sq8cuVKVFVVwWKxYObMmdi8eXPQY998801Mnz4deXl5yMzMxJQpU/DKK69EPOBY0kc1RgiCIAhCc1QbI6+//jqWLl2K5cuXY+vWrZg8eTIWLlyIxsbGgMcXFBTg/vvvx8aNG/HVV19h8eLFWLx4MT744IOoBx8tVH2VIAiCILRH9Sr89NNP4+abb8bixYsxbtw4rFq1ClarFatXrw54/Pz583H55Zdj7NixGD58OO644w5MmjQJ69evj3rw0eKtvkrGCEEQBEFohUHNwXa7HVu2bMGyZcv4azqdDgsWLMDGjRvDvl8URXz00UfYv38/fvGLX6gfbYyxUcdegiA0QBRFOJ1OuFwurYdCEFGh1+thMBggCEJUn6PKGGlqaoLL5UJJSYnP6yUlJdi3b1/Q97W3t2Pw4MGw2WzQ6/X4/e9/jwsuuCDo8TabDTabjX/f0dGhZpiKIQErQRCJxm634/Tp0+jp6dF6KAQRE6xWK8rKymAymSL+DFXGSKRkZ2dj+/bt6OrqQk1NDZYuXYphw4Zh/vz5AY9fsWIFHnnkkbiPi3tGSDNCEEQCcLvdOHr0KPR6PcrLy2EymaLeURKEVoiiCLvdjjNnzuDo0aMYOXIkdLrI1lNVxkhRURH0ej0aGhp8Xm9oaEBpaWnQ9+l0OowYMQIAMGXKFOzduxcrVqwIaowsW7YMS5cu5d93dHSgsrJSzVAVQR17CYJIJHa7HW63G5WVlbBarVoPhyCiJiMjA0ajEcePH4fdbofFYonoc1SZMCaTCdOmTUNNTQ1/ze12o6amBrNmzVL8OW632ycM44/ZbEZOTo7PVzygMA1BEFoQ6e6RIJKRWNzPqsM0S5cuxfXXX4/p06djxowZeOaZZ9Dd3Y3FixcDABYtWoTBgwdjxYoVADwhl+nTp2P48OGw2Wx4//338corr+C5556LevDRwsI01CSPIAiCILRDtTFy1VVX4cyZM3jooYdQX1+PKVOmYM2aNVzUWltb62MldXd347bbbsOJEyeQkZGBMWPG4NVXX8VVV10Vu7OIECoHTxAEQQTihhtuQFtbG95++22th5Iwjh07hurqamzbtg1TpkxJ6O+OSMC6ZMkSLFmyJODP1q1b5/P9Y489hsceeyySXxN3bA4K0xAEQRCE1qT1KuzNpqEwDUEQRCpht9u1HgIRQ9LaGOkjzwhBEIQi5s+fjx//+Me49957UVBQgNLSUjz88MP857W1tfj2t7+NrKws5OTk4Morr/TJvHz44Yd5b7Kqqirk5ubi+9//Pjo7OxX//iVLluDOO+9EUVERFi5cCMBTFXzixInIzMxEZWUlbrvtNnR1dfH3vfTSS8jLy8MHH3yAsWPHIisrCxdeeCFOnz7Nj3G5XFi6dCny8vJQWFiIe++9F6Io+vx+m82GH//4xxg0aBAsFgvmzJmDL774gv983bp1EAQBH3zwAaZOnYqMjAx8/etfR2NjI/7zn/9g7NixyMnJwTXXXKO4xky4aw4AbW1tuOmmm1BcXIycnBx8/etfx44dOwB4anzp9Xp8+eWXADzJIwUFBTjnnHP4+1999dV+2ar79u3D7NmzYbFYMGHCBHzyySeKxhsNab0Kk2aEIAitEUURPXanJl/+C244Xn75ZWRmZmLTpk146qmn8Oijj2Lt2rVwu9349re/jZaWFnzyySdYu3Ytjhw50k8bePjwYbz99tt499138e677+KTTz7Bk08+qer3m0wm/Pe//8WqVasAeDI5fvvb32L37t14+eWX8dFHH+Hee+/1eV9PTw/+93//F6+88go+/fRT1NbW4u677+Y//9WvfoWXXnoJq1evxvr169HS0oK33nrL5zPuvfde/POf/8TLL7+MrVu3YsSIEVi4cCFaWlp8jnv44Yfxu9/9Dhs2bEBdXR2uvPJKPPPMM/jrX/+K9957Dx9++CGeffZZVecc6Jozvve973GDZ8uWLTjrrLNw/vnno6WlBbm5uZgyZQqXT+zcuROCIGDbtm3cYPvkk09w3nnn+fzOe+65B3fddRe2bduGWbNm4ZJLLkFzc7PiMUdCQoqeJStUDp4gCK3pdbgw7iFtGofueXQhrCbly8CkSZOwfPlyAMDIkSPxu9/9jpd62LlzJ44ePcp32X/+858xfvx4fPHFFzj77LMBeHbmL730ErKzswEA1113HWpqavD4448r+v0jR47EU0895fPanXfeyf9fVVWFxx57DLfccgt+//vf89cdDgdWrVqF4cOHA/DoHh999FH+82eeeQbLli3Dd77zHQDAqlWrfJq5dnd347nnnsNLL72Eiy66CADwwgsvYO3atXjxxRdxzz338GMfe+wxnHvuuQCAG2+8EcuWLcPhw4cxbNgwAMB3v/tdfPzxx/jpT3+q6JyDXfMLLrgA69evx+bNm9HY2Aiz2QwA+N///V+8/fbb+Mc//oH/+Z//wfz587Fu3TrcfffdWLduHS644ALs27cP69evx4UXXoh169b1M96WLFmCK664AgDw3HPPYc2aNXjxxRf7HRdL0tolQF17CYIglDNp0iSf78vKytDY2Ii9e/eisrLSx90/btw45OXlYe/evfy1qqoqbojI36+UadOm9Xvt//7v/3D++edj8ODByM7OxnXXXYfm5mafUIjVauWGiP/vbW9vx+nTpzFz5kz+c4PBgOnTp/PvDx8+DIfDwY0MADAajZgxY4bP+QG+16ikpARWq5UbIuw1Necc7JoDwI4dO9DV1YXCwkJkZWXxr6NHj+Lw4cMAgPPOOw/r16+Hy+XCJ598gvnz53MD5dSpUzh06FC/AqTyumHsWvifZ6xJb88Ide0lCEJjMox67Hl0oWa/Ww1Go9Hne0EQ4Ha7E/b+zMxMn++PHTuGb33rW7j11lvx+OOPo6CgAOvXr8eNN94Iu93Oq9wG+r1qQ1RKkf8uQRDies26urpQVlbWL4sVAPLy8gAA8+bNQ2dnJ7Zu3YpPP/0UTzzxBEpLS/Hkk09i8uTJKC8vx8iRIxWPJ16k9SpMYRqCILRGEARYTQZNvmLVF2fs2LGoq6tDXV0df23Pnj1oa2vDuHHjYvI7ArFlyxa43W786le/wjnnnINRo0bh1KlTqj4jNzcXZWVl2LRpE3/N6XRiy5Yt/Pvhw4dzrQrD4XDgiy++iOv5heOss85CfX09DAYDRowY4fNVVFQEwGOUTJo0Cb/73e9gNBoxZswYzJs3D9u2bcO7777bTy8CAJ9//jn/P7sWY8eOjeu5pLkxQtk0BEEQ0bJgwQJMnDgR1157LbZu3YrNmzdj0aJFOO+883zCHbFmxIgRcDgcePbZZ3HkyBG88sorXNiqhjvuuANPPvkk3n77bezbtw+33XYb2tra+M8zMzNx66234p577sGaNWuwZ88e3Hzzzejp6cGNN94YwzNSx4IFCzBr1ixcdtll+PDDD3Hs2DFs2LAB999/P8+gATxZOX/5y1+44VFQUICxY8fi9ddfD2iMrFy5Em+99Rb27duH22+/Ha2trfjBD34Q13NJ61VYrxNgMuhIM0IQBBEFgiDgX//6F/Lz8zFv3jwsWLAAw4YNw+uvvx7X3zt58mQ8/fTT+MUvfoEJEybgL3/5C29Fooa77roL1113Ha6//nrMmjUL2dnZuPzyy32OefLJJ3HFFVfguuuuw1lnnYVDhw7hgw8+QH5+fqxORzWCIOD999/HvHnzsHjxYowaNQrf//73cfz4cV4VHfDoRlwul482ZP78+f1eYzz55JM8jLN+/Xq888473NMSt3MR4xU4iyEdHR3Izc1Fe3t73JrmEQRBxJu+vj4cPXoU1dXVEXc3JYhkI9R9rXT9JpcAQRAEQRCaQsYIQRAEoSm1tbU+qan+X7W1tVoPMeak4zmHIq1TewmCIAjtKS8vx/bt20P+fKCRjuccCjJGCIIgCE1hqanpRDqecygoTEMQBEEQhKaQMUIQBJFgUiCJkSAUE4v7mYwRgiCIBMFKeyttIU8QqQC7n/1L16uBNCMEQRAJQq/XIy8vjzc6s1qtMSvJThCJRhRF9PT0oLGxEXl5edDrI2+tQsYIQRBEAiktLQUAVZ1bCSKZycvL4/d1pJAxQhAEkUAEQUBZWRkGDRoEh8Oh9XAIIiqMRmNUHhEGGSMEQRAaoNfrYzKJE8RAgASsBEEQBEFoChkjBEEQBEFoChkjBEEQBEFoSkpoRlhBlY6ODo1HQhAEQRCEUti6Ha4wWkoYI52dnQCAyspKjUdCEARBEIRaOjs7kZubG/TngpgCdYndbjdOnTqF7OzsmBYI6ujoQGVlJerq6pCTkxOzzyX6Q9c6MdB1Tgx0nRMDXefEEa9rLYoiOjs7UV5eDp0uuDIkJTwjOp0OFRUVcfv8nJwcutETBF3rxEDXOTHQdU4MdJ0TRzyudSiPCIMErARBEARBaAoZIwRBEARBaEpaGyNmsxnLly+H2WzWeigDHrrWiYGuc2Kg65wY6DonDq2vdUoIWAmCIAiCGLiktWeEIAiCIAjtIWOEIAiCIAhNIWOEIAiCIAhNIWOEIAiCIAhNSWtjZOXKlaiqqoLFYsHMmTOxefNmrYeUMqxYsQJnn302srOzMWjQIFx22WXYv3+/zzF9fX24/fbbUVhYiKysLFxxxRVoaGjwOaa2thYXX3wxrFYrBg0ahHvuuQdOpzORp5JSPPnkkxAEAXfeeSd/ja5z7Dh58iT+3//7fygsLERGRgYmTpyIL7/8kv9cFEU89NBDKCsrQ0ZGBhYsWICDBw/6fEZLSwuuvfZa5OTkIC8vDzfeeCO6uroSfSpJi8vlwoMPPojq6mpkZGRg+PDh+PnPf+7Tu4Suc2R8+umnuOSSS1BeXg5BEPD222/7/DxW1/Wrr77C3LlzYbFYUFlZiaeeeir6wYtpymuvvSaaTCZx9erV4u7du8Wbb75ZzMvLExsaGrQeWkqwcOFC8U9/+pO4a9cucfv27eI3v/lNcciQIWJXVxc/5pZbbhErKyvFmpoa8csvvxTPOecccfbs2fznTqdTnDBhgrhgwQJx27Zt4vvvvy8WFRWJy5Yt0+KUkp7NmzeLVVVV4qRJk8Q77riDv07XOTa0tLSIQ4cOFW+44QZx06ZN4pEjR8QPPvhAPHToED/mySefFHNzc8W3335b3LFjh3jppZeK1dXVYm9vLz/mwgsvFCdPnix+/vnn4meffSaOGDFCvPrqq7U4paTk8ccfFwsLC8V3331XPHr0qPjGG2+IWVlZ4m9+8xt+DF3nyHj//ffF+++/X3zzzTdFAOJbb73l8/NYXNf29naxpKREvPbaa8Vdu3aJf/vb38SMjAzx+eefj2rsaWuMzJgxQ7z99tv59y6XSywvLxdXrFih4ahSl8bGRhGA+Mknn4iiKIptbW2i0WgU33jjDX7M3r17RQDixo0bRVH0PDg6nU6sr6/nxzz33HNiTk6OaLPZEnsCSU5nZ6c4cuRIce3ateJ5553HjRG6zrHjpz/9qThnzpygP3e73WJpaan4y1/+kr/W1tYmms1m8W9/+5soiqK4Z88eEYD4xRdf8GP+85//iIIgiCdPnozf4FOIiy++WPzBD37g89p3vvMd8dprrxVFka5zrPA3RmJ1XX//+9+L+fn5PnPHT3/6U3H06NFRjTctwzR2ux1btmzBggUL+Gs6nQ4LFizAxo0bNRxZ6tLe3g4AKCgoAABs2bIFDofD5xqPGTMGQ4YM4dd448aNmDhxIkpKSvgxCxcuREdHB3bv3p3A0Sc/t99+Oy6++GKf6wnQdY4l77zzDqZPn47vfe97GDRoEKZOnYoXXniB//zo0aOor6/3uda5ubmYOXOmz7XOy8vD9OnT+TELFiyATqfDpk2bEncySczs2bNRU1ODAwcOAAB27NiB9evX46KLLgJA1zlexOq6bty4EfPmzYPJZOLHLFy4EPv370dra2vE40uJRnmxpqmpCS6Xy2dyBoCSkhLs27dPo1GlLm63G3feeSfOPfdcTJgwAQBQX18Pk8mEvLw8n2NLSkpQX1/Pjwn0N2A/Izy89tpr2Lp1K7744ot+P6PrHDuOHDmC5557DkuXLsXPfvYzfPHFF/jxj38Mk8mE66+/nl+rQNdSfq0HDRrk83ODwYCCggK61hL33XcfOjo6MGbMGOj1erhcLjz++OO49tprAYCuc5yI1XWtr69HdXV1v89gP8vPz49ofGlpjBCx5fbbb8euXbuwfv16rYcy4Kirq8Mdd9yBtWvXwmKxaD2cAY3b7cb06dPxxBNPAACmTp2KXbt2YdWqVbj++us1Ht3A4e9//zv+8pe/4K9//SvGjx+P7du3484770R5eTld5zQmLcM0RUVF0Ov1/TIOGhoaUFpaqtGoUpMlS5bg3Xffxccff4yKigr+emlpKex2O9ra2nyOl1/j0tLSgH8D9jPCE4ZpbGzEWWedBYPBAIPBgE8++QS//e1vYTAYUFJSQtc5RpSVlWHcuHE+r40dOxa1tbUAvNcq1LxRWlqKxsZGn587nU60tLTQtZa45557cN999+H73/8+Jk6ciOuuuw4/+clPsGLFCgB0neNFrK5rvOaTtDRGTCYTpk2bhpqaGv6a2+1GTU0NZs2apeHIUgdRFLFkyRK89dZb+Oijj/q57aZNmwaj0ehzjffv34/a2lp+jWfNmoWdO3f63Pxr165FTk5Ov0UhXTn//POxc+dObN++nX9Nnz4d1157Lf8/XefYcO655/ZLTz9w4ACGDh0KAKiurkZpaanPte7o6MCmTZt8rnVbWxu2bNnCj/noo4/gdrsxc+bMBJxF8tPT0wOdznfp0ev1cLvdAOg6x4tYXddZs2bh008/hcPh4MesXbsWo0ePjjhEAyC9U3vNZrP40ksviXv27BH/53/+R8zLy/PJOCCCc+utt4q5ubniunXrxNOnT/Ovnp4efswtt9wiDhkyRPzoo4/EL7/8Upw1a5Y4a9Ys/nOWcvqNb3xD3L59u7hmzRqxuLiYUk7DIM+mEUW6zrFi8+bNosFgEB9//HHx4MGD4l/+8hfRarWKr776Kj/mySefFPPy8sR//etf4ldffSV++9vfDpgaOXXqVHHTpk3i+vXrxZEjR6Z9yqmc66+/Xhw8eDBP7X3zzTfFoqIi8d577+XH0HWOjM7OTnHbtm3itm3bRADi008/LW7btk08fvy4KIqxua5tbW1iSUmJeN1114m7du0SX3vtNdFqtVJqbzQ8++yz4pAhQ0STySTOmDFD/Pzzz7UeUsoAIODXn/70J35Mb2+veNttt4n5+fmi1WoVL7/8cvH06dM+n3Ps2DHxoosuEjMyMsSioiLxrrvuEh0OR4LPJrXwN0boOseOf//73+KECRNEs9ksjhkzRvzDH/7g83O32y0++OCDYklJiWg2m8Xzzz9f3L9/v88xzc3N4tVXXy1mZWWJOTk54uLFi8XOzs5EnkZS09HRId5xxx3ikCFDRIvFIg4bNky8//77fVJF6TpHxscffxxwXr7++utFUYzddd2xY4c4Z84c0Ww2i4MHDxaffPLJqMcuiKKs7B1BEARBEESCSUvNCEEQBEEQyQMZIwRBEARBaAoZIwRBEARBaAoZIwRBEARBaAoZIwRBEARBaAoZIwRBEARBaAoZIwRBEARBaAoZIwRBEARBaAoZIwRBaMb8+fNx5513aj0MgiA0howRgiAIgiA0hcrBEwShCTfccANefvlln9eOHj2KqqoqbQZEEIRmkDFCEIQmtLe346KLLsKECRPw6KOPAgCKi4uh1+s1HhlBEInGoPUACIJIT3Jzc2EymWC1WlFaWqr1cAiC0BDSjBAEQRAEoSlkjBAEQRAEoSlkjBAEoRkmkwkul0vrYRAEoTFkjBAEoRlVVVXYtGkTjh07hqamJrjdbq2HRBCEBpAxQhCEZtx9993Q6/UYN24ciouLUVtbq/WQCILQAErtJQiCIAhCU8gzQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEppAxQhAEQRCEpvx/YVbIGsVzJJYAAAAASUVORK5CYII=", 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", 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", 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", 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", 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fjurqavz+97+HJEkYPXo0du/ejVtuuQV33HGH4d8AQDAYxJ133qn+Pnz4cCxatAjPPvssvvrVrzr6LNXV1XjwwQchSRJGjRqF1atX48EHH8S3v/1tbNq0CS+++CI++OADnHjiiQCAJ598EtXV1Xj++edx0UUXAVBqsPz+97/HlClTACgGzZgxY7B06VIcf/zxjsaVCrY8Hy+++CKOPfZYXHTRRRgwYACOPvpo/OlPf1Lf37JlC2prazF9+nT1teLiYkyZMgWLFi0y3Gd7ezsaGxt1/wiiLyNBy6NvauvK4kgIghBZv349ampqdPUupk6disOHD2Pnzp2Wfzt37lxMnjwZ5eXlKCgowB//+Eds377d8VhOOOEE3ThqamqwadMmdHd3Y/369QiFQqpRAQBlZWUYNWoU1q9fr74WCoVw3HHHqb+PHj0aJSUlum0ygS3Px+bNm/Hoo49izpw5uO2227Bs2TJcd911iEQiuPLKK1FbWwsAqKio0P1dRUWF+p7Ifffdp7MGCYLQOEzGB9FLyQ0Hse6uGVk5bjZ4+umncdNNN+E3v/kNampqUFhYiF/96ldYsmRJVsaTbWwZH7FYDMceeyx+/vOfAwCOPvporFmzBo899hiuvPJKRwO49dZbMWfOHPX3xsZGVFdXO9oXQfQGZGgxafJ8EL0VSZJSDn9kk0gkoislPmbMGPz73/+GLMuq1+GDDz5AYWEhBg8ebPg3bJsTTzwR3//+99XXPv/887TGJhouixcvxsiRIxEMBjFmzBh0dXVhyZIlatjlwIED2LBhA8aOHav+TVdXF5YvX66GWDZs2ID6+nqMGTMmrbElw1bYZeDAgbpBA8oXwdxGLL5VV1en26aurk4X++KJRqMoKirS/SMIQqGprTP5RgRBZIxhw4ZhyZIl2Lp1K/bv34/vf//72LFjB6699lp8+umneOGFF/DTn/4Uc+bMQSAQMPybWCyGkSNHYvny5XjttdewceNG/OQnP8GyZcvSGtv27dsxZ84cbNiwAf/85z/xu9/9Dtdffz0AYOTIkTj//PPx7W9/G++//z5WrVqFyy+/HIMGDVI1mQAQDodx7bXXYsmSJVixYgVmzZqFE044IaN6D8Cm8TF16lRs2LBB99rGjRsxdOhQAIqAprKyEgsWLFDfb2xsxJIlS1BTU+PCcAmiD8CJ8cnzQRDZ5aabbkIwGMTYsWNRXl6Ozs5OvPzyy1i6dCkmTZqE7373u7jqqqvw4x//2PRvtm/fju985zu48MILcfHFF2PKlCk4cOCAzgvihCuuuAKtra04/vjjMXv2bFx//fW4+uqr1ffnzZuHyZMn49xzz0VNTQ1kWcbLL7+s60abl5eHW265BV/72tcwdepUFBQU4JlnnklrXCkh22Dp0qVyKBSS7733XnnTpk3yk08+Kefl5cn/+Mc/1G3uv/9+uaSkRH7hhRfkTz75RD7//PPl4cOHy62trSkdo6GhQQYgNzQ02BkaQfQa6hpa5aG3vCQPveUl+U/vfp7t4RBE2rS2tsrr1q1LeR4gknPqqafK119/fVr7mDdvnlxcXGzrb6y+Szvzt62A23HHHYfnnnsOt956K+666y4MHz4cDz30EC677DJ1m5tvvhnNzc24+uqrUV9fj5NOOgmvvvoqcnJyXDabCKL309qRXttqgiAIP2Jb7XPuuefi3HPPNX1fkiTcdddduOuuu9IaGEH0VfgSSM1kfBBEn2P79u0J+kqedevWeTiazOB/qTFB9GFaO0jzQRB9jaqqKqxcudLy/XfeeSft48yaNQuzZs1Kez9OIOODIHwGX/2ZPB8E0fcIhUIYMWJEtoeRUairLUH4GNJ8EATRGyHjgyB8TDOFXYheRCxGjRJ7OrJLnbYp7EIQPoOvcNpCng+iFxCJRBAIBLB7926Ul5cjEonoepIQPQNZlrFv3z5IkqSrFeIEMj4Iwse0kOeD6AUEAgEMHz4ce/bswe7du7M9HCINJEnC4MGDEQym1yOHjA+C8Bm8V7OlnTwfRO8gEolgyJAh6OrqSuh7QvQcwuFw2oYHQMYHQfgaCrsQvQnmrk/XZU/0fEhwShA+Q19kjMIuBEH0Psj4IAgf09rR7Zq6nCAIwi+Q8UEQPqYrJqOjm9ITCYLoXZDxQRA+Q/R0UKExgiB6G2R8EITPoRLrRCZp66TQHuE9ZHwQhM8Q5wFqLkdkip2HWjD6J6/ihmdWZnsoRB+DjA+C8DnNVOuDyBD/WLwdAPDCSir8RXgLGR8E4XOo1geRKQJU4ZzIEmR8EITPoRLrRKYIUH8VIkuQ8UEQPocEp0SmCJDrg8gSZHwQhM8gwSnhFWR7ENmCjA+C8DkkOCUyBYVdiGxBxgdB+AwZQpGxTjI+iMxAng8iW5DxQRA+p7mdwi5EZpDI80FkCTI+CMJniJoPSrUlMgWFXYhsQcYHQfgcSrUlMkWQZgAiS9ClRxA+hzwfRKbgPR/U34XwEjI+CMJniFMAGR9EpuA1HzGyPQgPIeODIHwOhV2IdPjboq342YtrDT0bfLZLVyzm4aiIvk4o2wMgCEKPOEmQ54NIhzteWAsAOGt8JaYcUaZ7jw+7dHXLiNKMQHgEeT4Iwud0dpM/nEiffYfbE17jy6t3UdyF8BAyPgjCZ4hTQDe5wwkXaDXwoPGJtt1kfBAeQsYHQfgcmhQIN2hLUim3q5uMXMI7yPggCJ9DxgfhBkZl+mOcvojCLoSXkPFBED5DTEropvoLhAu0diR6NmKcwUFGLuElZHwQhM/pJsEp4QItnYkp27y90UlhF8JDyPggCN+hNzbI80G4QZuB4JQPu5Dng/ASMj4IwufQpEC4gVG9GN6uJc0H4SVkfBCEzyHjg3CDpIJTCu8RHkLGB0H4DDHKQitSwg2M6nx067JdSPNBeAcZHwThc2JkfBAuYOT5oLALkS3I+CAInyFOATQpEG5gGHaJUdiFyA5kfBCEz4lRtgvhEL5JoVHYhbdrSVtEeAkZHwThM0jzQbgFfy0ZlVfnDdtO0nwQHkLGB0H4FNbtXJZJ90E4g79qjFNtuTofFHYhPISMD4LwKUFJ6zlKhcYIJ+jCLgaej27q7UJkCTI+CMJnyPH1ajDAGR80MRAO4K+aZJoPSrUlvISMD4LwKSEyPog0SZZKS+XViWxBxgdB+Aw2H+g8HxR2IRwgC4nbonZIZ5yQ5oPwEDI+CMKnhILa7UmCU8IJos0q6j50dT4o7EJ4iC3j42c/+xkkSdL9Gz16tPp+W1sbZs+ejbKyMhQUFGDmzJmoq6tzfdAE0Zsx8nyQGJBwAzHjJZYkLEMQmcK252PcuHHYs2eP+u/9999X37vxxhvx3//+F/Pnz8fChQuxe/duXHjhha4OmCD6ChIAZn+Q54NwgligrqWjy/R90nwQXhKy/QehECorKxNeb2howOOPP46nnnoK06ZNAwDMmzcPY8aMweLFi3HCCSekP1qC6GOEAgF0dMdoVUo4Qgy7JHo+uCJjpPkgPMS252PTpk2oqqrCEUccgcsuuwzbt28HAKxYsQKdnZ2YPn26uu3o0aMxZMgQLFq0yHR/7e3taGxs1P0jiL4MLxIMxO9QWpUSThCvGmvPB2k+CO+wZXxMmTIFTzzxBF599VU8+uij2LJlC04++WQ0NTWhtrYWkUgEJSUlur+pqKhAbW2t6T7vu+8+FBcXq/+qq6sdfRCC6G1IklZojIwPwglyQtiFNB+EP7AVdjnrrLPUnydOnIgpU6Zg6NChePbZZ5Gbm+toALfeeivmzJmj/t7Y2EgGCNGn4ecLJjqlVFvCCYmeD73xwRsnlGpLeElaqbYlJSU46qij8Nlnn6GyshIdHR2or6/XbVNXV2eoEWFEo1EUFRXp/hEEAUiQNOODVqWEAxI1H0LYhYu0kOeD8JK0jI/Dhw/j888/x8CBAzF58mSEw2EsWLBAfX/Dhg3Yvn07ampq0h4oQfRFgnHRBxkfhCOSCE67SfNBZAlbYZebbroJ5513HoYOHYrdu3fjpz/9KYLBIC699FIUFxfjqquuwpw5c9CvXz8UFRXh2muvRU1NDWW6EIQDJAkIkuCUSAOxwmlLu3m2C4VdCC+xZXzs3LkTl156KQ4cOIDy8nKcdNJJWLx4McrLywEADz74IAKBAGbOnIn29nbMmDEDjzzySEYGThB9gRB5Pog0SJZqm6z3C0FkClvGx9NPP235fk5ODubOnYu5c+emNSiC6MvwEwJLtaWJgXCCWGRMDK1QkTEiW1BvF4LwKRI0z4c4iRBEKohXjWjE8r92dpPmg/AOMj4IwmfoiozFy6tTPJ5wgmizit4N8nwQ2YKMD4LwKZKkpdqS54Nwgig4TfB86Lra0jVGeAcZHwThM3SaD8m/xkeb0J6d8CE2PB9dFHYhPISMD4LwMQGflld/e8NejP7Jq3hs4efZHgphgXjVJBof2s/k+SC8hIwPgvAxLOziN8fHzf/6BABw/yufZnkkhBXidSMaGFRencgWZHwQhM/gpwAmOPWb5yM/Esz2EIgUEDUfiam22s/k+SC8hIwPgvApkgQEfCo4zY/aKhFEZIlkno8YlVcnsgQZHwThM3hXuF8Fp2R89AwSi4yZ/95JYRfCQ8j4IAifIklAUDU+sjwYgQIyPnoEyTUf2s9UZIzwEjI+CMJn8NND3PbwnecjjzQfPZKYVaqt3yxcoldDxgdB+BQJkm9TbfMj5PnoCdjRfJDng/ASMj4Iwsf4NdWW13y0d1GxMb+SmO1i1dvFZxcZ0ash44MgfAZvaEg+TbXlwy7N7WR8+BU7dT7I80F4CRkfBOFTJAm+7e3C6o8AQEcXTVp+JbHCaUz4ncqrE9mBjA+C8B3+T7XlR0NhF/8iC9eNWMWUwi5EtiDjgyB8igTe+MjuWET4OY08H/5FvGxEI5bCLkS2IMk6QfgYv5ZX54WM7WR8+JYEz0f8Orr1P59gV32bTgNCxgfhJWR8EITP4OcLLdvFX8YHbwuR8eFfxMuGGbH/XLojYVtqLEd4CYVdCMKnSJJ/63zIOuODNB9+RbxqrAyMDvJ8EB5CxgdB+AxdV9uATzUf3ChJ8+FfzDwfRlCFU8JLyPggCJ+iCE6Vn/2W7QIKu/QIxCJjXRada7tjckL5dYLIFGR8EITP0Gk+ekCqLXk+/IsdzwcAdFoYJwThJmR8EIRfkRTdB+DDsItM2S49gQTjI4kRS7U+CK8g44MgfEwwfof6WXBKng//ktDbJYlxQVVOCa8g44MgfAbvVWDZLv5OtaVsF7+SrLeLCGW8EF5BxgdB+BQJWraL3+YEynbpGRhpPqwMWar1QXgFGR8E4TN0qbY+zXaRKdulR5CY7ZIs7OKv64zovZDxQRA+RZIk32a78JDnw78Yez7Mt6ewC+EVZHwQhM/gJwfJp8aHPtuFNB9+RbxqumOiL0SPVR0QgnATMj4IwqfwXW39tiClOh89A2Yksh5B3bK15qOzy19GLtF7IeODIHwMS7X1X7YL1fnoCbBviRkfySqYUpExwivI+OhDdHbHcOEjH+DHz6/O9lAIC3jHeE9oLEeeD//CvqcQ7/mw2L6TvkvCI8j46EMs3XIQH22vxz8Wb09p+x0HW/Dh5/szPCrCDEnyc2M5DfJ8+Bl92EWWjfVDkZAyFVBzOcIryPjoQ0RD2tedikjwmqc+wtf+tATbDjRncliECPf8p1RbIh1EzwcAGEVWovH4HmW7EF5BxkcfIj8aUn9uaO1Muv3+wx0AgLrG9oyNiTBHgp9TbSnbpSfAHBnBgPaoN+rvEg3HPR9U54PwCDI++hCStvhBYwrGBxM5dtJqyFP4x79/U221n0nz4V/YPcx7Poz6u0Ting+61wmvIOOjD8G7W1PxfLBVE00u2UGSuBRJn30FFHbpGYjZLoBxLY9oOAiAjA/CO8j46EPwOvdUjA+2PcWBswebM/ycakvGqX9RNR9BzvNhJDhVPR/+us6I3gsZH30I/plDng//wn9PWmM5f00K+mwX0nz4FbaA0IVdDK4lTfNB9zrhDWR89CH41WpDC2k+egIByaeptrzmg64P/6IKTrmwi4F3g2XC0b1OeAUZH30IveejK+n25PnIDnx4zK/ZLvwY2zvp+vAr7FuSIKkhPEPPR4hpPvx1nRG9FzI++hA6z4eNbBda2WYHSZLUDCW/GR8gz0ePgF02OvGyRZEx8nwQXkHGRx+Cf+Q0tpHmw6/wc0OwJ2g+yPPhW1It1R+lCqeEx5Dx0YeQbXo+YuT5yCp8V1u/OT502S50ffgWzfMhqYaskeaDeT5ooUF4BRkffYiYTvORSthF+Z/abGcP32a7cMPpjlm3aSeyBzMSJVjrhzTPBxkfhDeQ8dGH4J85diqcdnRTKqWX8FODb3u7CL+Tu96fsG8lENAMWaPvigSnhNeQ8dGHsCs4Zc8oeiBlB0niU2399R2Ing6/eWaIOCzsAonTDxlUOCXBKeExaRkf999/PyRJwg033KC+1tbWhtmzZ6OsrAwFBQWYOXMm6urq0h0n4QL2i4zFPR8UB/YUfmIP+rXOh/A7TVr+hAlOeUPW6KuibBfCaxwbH8uWLcMf/vAHTJw4Uff6jTfeiP/+97+YP38+Fi5ciN27d+PCCy9Me6BE+vCTWktHd9IHDducendkB0lCj0i1Bagbql9RBacA4hXUjXu7xMMu9D0SXuHI+Dh8+DAuu+wy/OlPf0Jpaan6ekNDAx5//HE88MADmDZtGiZPnox58+bhww8/xOLFi10bNOEMcfWczPvBVk20Gsoe/k211Y+nk4SKvkS1WSVJ9aIZXUtqtgvd64RHODI+Zs+ejXPOOQfTp0/Xvb5ixQp0dnbqXh89ejSGDBmCRYsWGe6rvb0djY2Nun9EZhAnDDPjo7ahDc8s265qPSjs4i16walPU22FS8JvxhGhoFU4tRachuON52L0PRIeEbL7B08//TQ++ugjLFu2LOG92tpaRCIRlJSU6F6vqKhAbW2t4f7uu+8+3HnnnXaHQTggVc/Heb9/H/ua2tXfyfORHSRI/k21FQxZN931Bw63ozQvon52wjks1MpXODUyMIIWhglBZAJbno8dO3bg+uuvx5NPPomcnBxXBnDrrbeioaFB/bdjxw5X9kskImYomKXb8oYHQJ4Pz+G72vpU8yEOxy0DdcW2Q5h8z5uY/dRHruyvr8N7PljYxcjAYF1v/XadEb0XW8bHihUrsHfvXhxzzDEIhUIIhUJYuHAhfvvb3yIUCqGiogIdHR2or6/X/V1dXR0qKysN9xmNRlFUVKT7R2SGxAkjtQcNxYGzgyT5ubGcHrdWzH/5YAsA4JU1xp5Swh5swRGQrL1owUC8yBgJTgmPsBV2OeOMM7B69Wrda9/4xjcwevRo3HLLLaiurkY4HMaCBQswc+ZMAMCGDRuwfft21NTUuDdqwhGiq9wo398I8nx4C/89SX5Ntc1Qtkth1HYkmLBA11jOQnAa8ml4j+i92LrTCwsLMX78eN1r+fn5KCsrU1+/6qqrMGfOHPTr1w9FRUW49tprUVNTgxNOOMG9UWeRh97ciIbWTvz0vHHZHoptRFsjVc8HaT6yg5Ie6ddJQdB8uJTtUphDxoebaGEXa8+HlRiVIDKB63f6gw8+iEAggJkzZ6K9vR0zZszAI4884vZhssZDb24CAFw2ZQhGDCjM8mjsIbruU50wKOySPZjmw2+9U5yG8JJREA1zx5BVzw/hDJkTfWh1PsjzQWSftI2Pd955R/d7Tk4O5s6di7lz56a7a9/BTwD7mjowYkAWB+OAxKqUKWo+KOziKfzErq5WfWZ8iIasW5NWAef5aO+KISccdGW/fRW1wik4/ZBFtgsZH4RXUG8XG+gas7UlL0/uN8TVc6pxeurtkiUkSevt4jP7L0Fw6pJ3LJczNlJpAUBYw2s+rEIr5PkgvIaMD4f0xAdjgkiQBKe+hP+efJvtIoZdXJq0eLFtT7zH/Aav+dAEp4n3s2aY0L1OeAMZHzbgH6+ptKT3G+L8kKrngzQf2UGCj+t8CL+75fngr9GWjm5X9tmX4YuMkeeD8BMkLbcBH7bomcaHQ8EpeT48RVdePeDXVFvxWnLJ88Htt62TjA+3MEq1DUjA9WcchZEVBZrmw2dGLtF7IePDBjrPR1tX1sbhFKeCU0q1zQ58G3S/99xwq84H/zlbyfhImxhXZEyK+7mZ8SFJEq6fPhIA8P6m/QCoyBjhHRR2cUhPjEdbCU6fXrodV/9tueFqkzwf2YOlR/ot7OLUi5Z8v9rP7WR8pM3K7fXqz2LYhU9ipmwXwmvI82EDXbZLjzQ+9L/zE8aP/qNUrv3boq0Jf9cVkxGLydToyyN4I5HVufCbOzxTFU55o4Y8H+nz10XbAADvbdqP00eVA9C8S3wJFTI+CK8hz4cNeCV+T0y1TVytJj5odh1qNfxbEp16jyI49WmqrcPMqWTEdJoPn33oHo5V51rqakt4DRkfNuAfuD0x7JKY7ZL4cDfTspDx4R381+TbVFtBQeRWLRj+GiXBqbsEBMGpxAVeKNuF8BoyPhzSE40PUfNhNGE0mXh0Okn34TmSJKmucd8ZHykYsk6gsEvmSMhoobALkUXI+HBIY2sPzHZJwVVu9rnI8+EduiJj6qSQpcGYwIYYiSti3Uu11X6msIu7WDWWCwUp7EJ4CxkfNuAfjK2d3b5r9pUM0VVuJBI007J0dvWsz9ob4DUfvrvW4sMJuzxp8am2FHZxFxbCY/e9ZPCeUfVTgsgEZHykQU9zC4vzg1HYpbG1U51QeDq6e9Zn7S2wVFu/Zbuw8Eg4FPd8ZKDCKRkf7hIM6PVDlO1CZBMyPmwgeg7qW3qW7iOxE2nihFHf2olQIPGy6CDPh4ckptr6rcgYGw27VtwSnHZThdOMMPOYwaoXjYVb9YJT5Xsk44PwCjI+bCAuPnua6DSVZmAtHd2q8p2HNB/ew5fE9tucwMJAkaC7K2ZZJzilay5dBpfmAgAuP2GI5kUzSrUlzQfhMWR82EC8LXue8SFqPowf7syVzkNVTr2D/5oCvk21VWDXSmdG6nyQ5yNdjMTLquaDD7tIFHYhvIWMjzToccaH8DsvOGVZC4DWSZWH+rt4jwQJAZ+WV2fDCbNsF6rz4WskSdLqfDDNB/c+FRkjvIaMDxuInoOeZnyIugE+7FKaH1Z/bjIoNEaeD+/QdbX1a4XT+P/M+HBrxUyeD3eROUPDSlTKh1r9pi8ieidkfNggIezS4wSn+t95wWmQ88G2GxgapPnIAlJihoJfEDUfbnnGqM6Hu7DTyXdIVhvLcfd8kMtwI+8H4QVkfNhAfP4faunIzkAcoq1W2YSR+kOGPB/Zgc0Pfku1zVjYhZv4eloqu5+RIGmGrEFXW97zQboPwgvI+EiDHmd8sNoMwcTaDMkeN6T58A6dSFAtMuavQmMs7ZxVxnRLcEqptu5iKDg1MC4CEu/5oHudyDxkfNhB9Hw096ywS8JqlXsIJZvXyPPhPXyFU8Bf6bbiteReqq32Mxkf6cOMRD7son5XnOujN3o+OrpiuOIvSzH37c+yPRTCADI+bCAWGetpno+Y4Pngwy7iZxMhzYd38N9FgBcC+snzER9KxPVsF97zQddcuug9H8r/3QZhl2AvND7eXF+Hdzfuw69e25DtoRAGkPFhg56u+WDPlGiIrVa5sAt5PnyHslrVfvfTpKA2lmN1PjLQ1ZY8H+nDC07FWh684FSSpF5XYp03qPwUsiQUyPhIg0M9LNuFrajVZmA6z4c15PnwDqM4vfh6tmEP85Drqbbaz10xmbRGLqHUjNGXVxcJSuaakJ5IcS5XPqC953Uh7+2Q8WED8ZY81NzRoyxq1VVuUJUy2cegrrbeI0HSaT78lPGiaT6Y4NT98uoAeT/ShZ1OY8+Hftve5vmIcpWa63uYPq8vQMaHDRLKk8dkHO5BFrVamyFkFKdPpvmgSSAb8BOErzQfYHU+XO5qK+yG0m3TJVE/ZKT5ADTRaW8xPvhP0dNC5H0BMj5swF/MOWHl1PWkzrYxdbVqvxOpW11LieTwZ5ov/uanypPMDgoZhPDSQfTutJPoNC10no8kxkVvay7HX0pkfPgPMj4cUpoXAQAcbO4ZF/W8D7bggTc2AuBTbUlw6mf49EjAZ6m28f+NrqV0EL07FHZJD1VwCilB0yEJcZfe5vngzfietEjsK5DxYQP+uciMj55iUd/533Xqz8xV3m1DcGpUcp3IDHx4z7+ptkLYJQN1PgAKu7iFJCUPu2jl13vHvU6eD39DxocN+II9TEnd05rLAWaCU+vJg7IOvIctTJn94auwS/x/LdXW/TofANX6SBddYzlWqt9EcNrbPB96zUfPe073dsj4sANXGDBsKNrsGRgVhkqaakuej6yhNZfL8kA4VM1HwGXBKXk+XEWnH0pR89FrjA/uY9ST58N3kPHhAEmSEA64283TS1TDKSarK6OkqbY98HP2Flhs3l+ptvGaMSF3JyzSfLgLLzhVwy7qORY1H+7WbMk2vDeXPB/+g4wPG/C3pJox0gNv1LBB++xkYRfyfHiPFJ8cmFDQl2GXYGIIL639umx8NLR09qhaPG4jc4aGKjjttq7z0WuyXbifyfPhP8j4sIG6igCfYtjzJmU2YQCpr3Kowql3iHOlqvnwySTa1tmNXYdaAWg6AddSbWPuGR+LNx/ApLtex+3Pr0l3WD0eI8GpiFiErKfD3y61DW3ZGwhhCBkfNuAFp+qKrwdOyhGu8h8bP2k+/IcqOPWZ5uPiPyxSV8d8CM8NxN2kIzj97YJNAICnlmxPZ0g9Gj7AkpBqK2zb2yqc8mzZ30zPMJ9BxocDJEiq56MnFt8Kc54PdcVKmg/fIHYYTmiFnmVW7WxQfw67XOFUDJGkIzgtyQsn36i3Y9AniHnQErJdepvglPvwXTEZWw80Z3E0hAgZHzbgn4uhHuz5CAUl9cHDYvVJPR898HP2FsRJwwvW7m7ANU99hG1JHthu1/lgu2HeuXTCLnxjsb6K6vmQuMZyJvdyb9N8iA81Fiok/AEZHzZQr2XJOF21pyBBQjigHz9bcbKy8SLksswe2XCHX/KHxXjpkz2YNW+Z5XZhl+8DZmDlRYIA0vN8FOdG1J/7quhUX+dDLDKmd31o7/eOe138xvc1tWdlHIQxZHzYgL+RmdDOLZW/lwS4Pg+q8RF/LyccNPybnhhe6qmI82Q2ij+xFuRb9lt7Ptx21bPd5Mavw3S6KfOej75eL0Tp7aL83G0Sdultng/xPtrbRKJTP0HGhwMkSRPa9cRW8zK4bB0Wdol/jJyQsfFBng/vYfU9ApJ/J4VMpdqydujpdFPmvXh9tc4D39tF1A4ldLXtxZoPgDwffoOMDxvwlnQ4oJ+8exJNbZ1cQzD9DZobMTE+SPPhGQmejyxMCuKq2Aw2Nll2Z3xsH9FQ+p4P/jw2tfVR44MrMpbMsxHsdUXG9L/vJePDV5Dx4QAl26XnCk7rWzq1sJGaaqtfcQLASSP648fnjAFAno9swOb/bNRfKIyGUtpOlznlgiEeE7RH6dxf/Nlqbu+bYRd+9c8Ep5pBYtzV1o8eNieIn+JwPJRI+AMyPmzAryLUCqc9QAshiu0aWjsThIJq2IXTfDzw1UmYMa4SQM80snoq4hUVzIKXrTAntUwRw7TtNGDzXjR+HabjceOv++ZeNvEcau7Aks0Hkgpp+beDSdxZfkvpThfx3LR09E0D1K+Q8eEACVqJ8p5Q4VR8PtW3dCZMaJrgVLskJElSJxfyfHgPmyvUVFsPv4LCHHPPRz4XmmNjA9xZMYuaj7Q8H9xwWjp6l/Hx5bnv4+I/LsZra2tT2p4Pu5jR2z0fvc0A7emQ8WED3oXZozwfwu+HWjq48vD6ImNRTnAakLR6C10x2Ve9RfoS2fF8mBsfJXlaCmsL90B3wxCPCddhOkYvXxflcC8Lu+w4qNSs+NeKnZbb6ep8CJ6PhGyXoP96CKWF8DH6esaT3yDjwwZ8rFSrcGr8cGzr7PaNV0R0P/YviGp1PlhjufidypdeVzwf2hOKRKfeIH5foSwUGePDLuI1zq+go+GAqyma7DNGw+kb97Fe7Plg7DucpGEae2ZBEwczEiqc9jrPR/yZFl8o9lXdj18h48MGfJ8ENnkbGR9d3TGc+eC7OPVX7/huFTF5aCkevPgLCcYTm9d4Y4P3fABkfHiNKjh1uXlbKuRzgtOmNv3EzQyE00aV45ghpe4aH/F9sJTvtDQf3NK3t048Bw5bZ3Dw50AMu/T6ImPxj54XVa6l3mqA9lRsGR+PPvooJk6ciKKiIhQVFaGmpgavvPKK+n5bWxtmz56NsrIyFBQUYObMmairq3N90FlHAsIh8wfuoZZObD/Ygl31rdiX5OHgBfwI/3LlcRjeP1/N1hGLjIUCnOeDq4QKAJ2k+/AEM8Gpl0JAfpHc2KpPU2UP9evPGKl4x5KU7baDJjh1V/PRW+P9B5J4PniRfCiJ5qO3FhnLjyiGdGtnt+8Wg30ZW8bH4MGDcf/992PFihVYvnw5pk2bhvPPPx9r164FANx4443473//i/nz52PhwoXYvXs3LrzwwowMPBvw7vCQheeDX2Hsqs9+PwGdtz4+NLM6JXz2ghRQ0vOYN4Q8H97CUiFV48PDsAt/pEaTGhlsfCEX+7uoqbZuaD648TT30lVvMh0DX2QswfNh0liut0zQ7FMUxL14sgy0dfVOD1hPJLVk/jjnnXee7vd7770Xjz76KBYvXozBgwfj8ccfx1NPPYVp06YBAObNm4cxY8Zg8eLFOOGEE9wbdZbQhV0sBKe8kbKnvg0Y4sHgLOBdr2IGhar5iI9ZH3aR4q8F0Nnd3SOrufZIhNOcDc8Hb+c0tnYJ7+krZIZcDAu56vngfu6tno9UUTwf+rWm6AfpbZ4PRg6XndXS0Y28iK1pj8gQjjUf3d3dePrpp9Hc3IyamhqsWLECnZ2dmD59urrN6NGjMWTIECxatMh0P+3t7WhsbNT98yu84NQq1Za/dXfVt3gwstRhD5yEOh/x13lRGvsp4kKpa8I+mubD+8qTvLhV9HxoGRTK/2Kp/nSQBc9HeoJT3vPRu65dswaQIrrGcklTbXtbhVPlcwQkrVdQSy/V/vREbBsfq1evRkFBAaLRKL773e/iueeew9ixY1FbW4tIJIKSkhLd9hUVFaitNc9Fv++++1BcXKz+q66utv0hvEaSwFU4NfJ8aD/vrs9+MyMjb72Z4JRfHTHPR0St9dE7Hko9jWxkIfBHqm8x1nwwwWJI6JCcDmK2S3qpttrPvc3zUZYfVX9uswi98N+IqPkQK5wy46QnlA9IBd5TzYy1dgq7+AbbxseoUaOwcuVKLFmyBN/73vdw5ZVXYt26dY4HcOutt6KhoUH9t2PHDsf7yjx8nQ/zVFs+zLHzUPY1HzxqnD5gHKfnH1Ds2aQWGiPNhyeIDbGyUnmSO5SYUcHGlwnPh1bnw4VrjrO6e9uKl6/DYtUwTeZm4MRsFz2hHlQ4MRV4TzXz3raTaN432A5+RSIRjBgxAgAwefJkLFu2DA8//DAuvvhidHR0oL6+Xuf9qKurQ2Vlpen+otEootGo6ft+QlvxwbQxm7Kh9uNunwlOtbCL9qDhNSphXZ0P5X91IqAb11PUyT0bmg/uIhYztkRPmpupwEzsqDaWS2Mi1Hk+XBScyrKMV9bUYuzAIgzrn+/afp2y73A7qvvlWW6j9KOyDruItX96PlrIKeKGMUu4Stp1PmKxGNrb2zF58mSEw2EsWLBAfW/Dhg3Yvn07ampq0j2ML+CrBVqVHedv3d0NPjA+LASnnd2yYbdeQC84VbalG9cLzCZ3TzUf3FctrqxFzYebk1ZCYzmXKpy6GXZ5Z8M+fP/Jj3Dar99xbZ92kXWeqSSFxmBSXl34tbd5OPk04wi1ifAdtjwft956K8466ywMGTIETU1NeOqpp/DOO+/gtddeQ3FxMa666irMmTMH/fr1Q1FREa699lrU1NT0ikwXHgl8HN7A+OAeDPUtnWjv6taVLc8mLE7PHjTihKZLtY3/HyHPR5bQp9p6q/ngPB+i8SFqPoLujY/tgjU4TEd/oMt2cVFwur42+6J43rAyKzTGezSVZ5Z1tkuvC7vE/5cgIRJ//lLYxT/YMj727t2LK664Anv27EFxcTEmTpyI1157DV/84hcBAA8++CACgQBmzpyJ9vZ2zJgxA4888khGBp4NdB6CoLnITozZ72tqx+BSa7doJjEUnDLPRyymF6UFEwWnVOfDW8SvSy2vnqVU2/0Jk1s8iyB+qYRcLTLGwi7aKlyW5QRxpJ19Ae56PvpzYs9YTFZb1XsJfyUkfj/xbUw8aAzxnIbFfk89HF7vQgso/2HL+Hj88cct38/JycHcuXMxd+7ctAblV3ihndWELN70e7NtfHA/ayJBzXjSaT74VNv4j3TjZgd2/gPZznYxqXCqeT7ca7LI9s17Cju7ZURCDiZ4bjgtHd2uGQql+VpjvfrWTvTjfvcK/p7dbxJ20d/3UtIKp70u7MJpPqIUdvEd1NvFEZKl50NsAGalRk/Gt/66DBf/YVFaq16xURkgCE6514O6bJd4qq0L4j/COdloLMdfM42tnbrrT9R8uKlJEVNtAefXnXi+WlzqaspP4mZeh0zDf7IDzSbGhxB2SZ7t4l7KtB/gNR9q6jbVKvINZHzYwCjsYphqa+D5cEJndwxvrt+LJVsOYtPew472AZh4Plh5+JhecMqHXRgR5uWhVYMnZDKbxMkYYjLQxIUtxAqnYVdTbfVFxoB0jA/97y0uhV74sOr+NBYWaQ7C1hiMeruIkayIi9+jH9BpPsjz4TvI+LCBrkkTJ7Iz8izw7Gt0VmiMX0keaHbnISeKBLtjsu5hGjFIx6M0teygVThl35V351+8ohu4QmMx7j4A3C0yxi6xUFACmyudThjibXk4A4XG9pt4HTKN3vNhovngfjbq7SLCvseOXuP50MLkFDr2H2R82ICPIfLdXsVYvPjQc9rZlncbH2o2bu6VCpaC0+6Y3vMRSLwkrNKKCfcRBcvZaCwnhizqW7VJVuaVfLDO/LKLVhJbSluDkBB2cSnjRbbpdcgE+mwXs7AL94ukhFF1YVUh8NLbsl0YvPFB2S7+gYwPB0gSEOYEcKJbWJw89jY6e0Dxno+DLWmssPgiYwaCUx6jQkSRXiZE6ymomgopC4JT4VB8iXVR8+Fuqq2yj2BAu+6cCllFj6RbGS/WmUDewI/hYEuHSY+pxPMWNKhgzIj0sno+vDCafTYyPvwDGR82MPMQiA9HtzQf/ELyUBruXV2Rsfj/YZPVathA88Gqnva1rrZb9jfjXyt2Zr3FeJCFyLzUfAi/6yZu9aGu4G5vl/i+uZLYTifDhM/gUpXTVNJcMw1/T8sycKgl0TMqGy06LEIvbmYt+QE+O5HCLv6DjA8HSJB0KamJng89TrNdeNfqngbnDer0D6HE9Ej+/bxIYjE0zfPRt5Tip//6Hdw0fxWeXuZtvyHReA1lIewieg34kIXm+dDrh9h98NInu/Hl37+PHQftd3SOGYVdHE4YYtil2aX+LqmkuWYa8VJoaLUeh6gfMsLNHj1+gD9HbujWGts6s74Q6U2Q8WEDXnDK582LKz7xwX2gud3RRctPNtsPNtv+eyO01Sqfaqsd57hh/fClcZX4zqlHqK9pK9C+eeO9ub4uK8dlMXkWdvG0t4uYKcKlqYrZLmKq7TVPfYxPdjbgB8+ucnzcABfadK750P/uWtiF+9kPYRcAaGi1/mxaQ8nEVHqGGnbpZR5OSZLUujFODdk9Da2Y+LPX8bU/L3ZzaH0a243lCG4CD0roismmno/ccBCtnd3o7JbR0NqpK06UCrzBsnW//VWkOB4efbaO9npAkvDY1yfrtu3raWpm5aszhfh9BQPGpfAzOwblWKGAco23ciELUfNh1ttl8377BrOR58NpfxdxgnarxLofBKcijW1Jwi7x/4NcuDihzgdX9bg3YOj5cHgt/e+TPQCAxZsPpj0uQoE8HzYQBVxmtT7YRR8JBVCcGwbgLOOF93zsbmh1rELXFRsyqnCa5O/7ulI8W671BEFnFup85MbDcLqwCyfksxqfk/RwZmDxzcD8JjjlzcP9zR1JU+0zATtmYVRZPza2GhgfBne2leaDabt6TZGx+P8S0u/MXV6oldT3chHQmyHjwwZa2EXfnC1R5a89QNlF62SFxF/ksgwcdCg61WXcsbFzglMj44Snr3e19dy1LkxmWWksFz9UfkSZ3Fp1mg/t+gbMU22dzMla2MUFwalw/FaXKpzy++3oiukKsHkFuxSK4osbQ+PDQHBqle3CPFi95T7X1flIM2OPL6GfilG9/3A7HnpzI3bXZ7+ruV8h48MG4rOUr5Wh247LBigvUIwPJ54P0fvpNGvGCJ3gNMm2fV0pni2PT7LJPZOw8Ed+1MLzIXjR3NAEaam2WtjF6fnXQjjK761uhV2E352m0qc3BmUUzLPa2JZE8yF4qYBE40MTDveOlT3v+dC8t86uAb4mSirf95xnV+GhNzfha38ijYgZZHw4QI11mzx0+XTB/nHPh5OMF7d6xBitQM1KYht5PiJBYyOL8AarPkKZgh0pP+7W570GCdkuQgXWkryw4+PGuNVqOM3rLmbhvUkH8X7avM956wMrGgy8GeIYmPFhtK3e46n8b5Xt0us8nAZp246r5XJnM5WF5OLPDwAAth5wrtXr7ZDxYQMxths2qQjIV0JNx/MhplY6Nj4ENzmg7xeiF6ZZlFfvY56PwaW56s9utmRPRoKHLRvGX3wQLPVaN3GLdT6EFXP/An3LeTuwzZWwS3oNDdl1nxf33rgWdhG+oXT6Lpnxzoa9mHTn6/jlq5+ajEGhIEcxrFoMapgYaVFCFhVOzZ5nPRX+OZxukTH+VKbyHGbXHGEOGR82SFD5m8QReW1IeTqeD+HB7bRMuzhZAFxhqJhsWAGVp7e12k6VwhxtBb/dQc2KdGGTg1k2SSZhD27mNWjRZbvojVkxG6dfnhYfP2SjMi8/WQYkKW2PW4JuxSXjQ+TzDHg+7nppHQDgkXc+N3xf+2zMODSqcJqILtslIeyiNZvMJiu2HcJPnl+DJoMMHjsYdrV1oWZMKs9yds0R5pDxYYNElb+xO5y/6MsKlAexWf8FK0TPx16HDepENzmgX+UYVUDl6aueD34yrE2jyJv94+p/z4bng80/eVFmfHQnvKcZR/oQHu/at2Mw83NeQEq/pxCbMNgqtC0DglMAqHN4X1oxgMuuMBkFACA3PskZfbZkFU7Fez3dMJdbzHz0Q/x98Tb89MW1ae2Hf6qlKzjlv/KUPB8GxRoJPWR8OEDzfJio/Dl3H7sInTz4xJQux56PODrPh0mFU7HwEND7ej44oTYDE0xSEgSdHna1jV8UueFEdzWfRcCPjxnh/Cpx+dZDKR+Tv94lXWM5p6m2yv95YZc1H8LvdRkQnA4ozLF8n52q3HBqzxe1YJ2V5iPuFZFlf6STvrdpf1p/zy8C015Acadjb1PyZwEz2glzyPiwhaj5YBe0ueeDVdZzEmsUkxtcFZzyqbZJ/j7sQmningh/3jKxujU/rv4biWSjzkf8f6PJjc8iAPhsHFn3PgC8uGp3ysfkjRY+28W54DRDmo/4fiuKFO8EuzZW72zAM8u2u1L3g/d8GH1+dgxVk2P02Qw8H2whoXsxDrvPzY7pNU6fdwyd5iNN48Nu2KWANB9JIfPMBnwKLZA8BVKCpBa3cWR8CA8xpyssS8FpTNbX+TD4+2gfrXDKh6O8ND4Y2nXmfSyeHSonkliWWhasj4SwEDdMO+EqfaVdrqx/miJBt7NdGJVFOahrbEdTWxdaOrpw3u/fB6AIbs8YU5HWvvlqyPua2lFVkqt7XzUOLYwPo3CqLtVW2J4PyXR2x5AT7tkTqH4R6J7gNJWSB3mc5kOWZUOPcl+HPB82ELUTZkWQjC96B2GX+I7YcXbVtzoyAEStCmBe4dRQcNpHe7vIDidRtwllIwsh/uFzQuZufVX7JPR24Y3mvU1tKXsC+L/jBafO4/QpeAec7Dc+zMKcsLpvfmGwake9K8dhGBm+agVa1TNl5B3RfhYLIxrBv5fNKqe81ycdL5JmI0uIBNPr7WJX85HPaT4yJXTu6ZDx4QDR8yFOyry7Lxp/OLQbPBySwbJdqopzUBANoTsmO2owp46OMyzM0uqsNB99z/OhkYm4firHBTJb50OWZXyysz7BuBBX1mzFaFWqn90H/CjbOlOvABoT9p1ulhVzSBrVKkkH3pNYUaRoM3gDwa0eMgyja499D/kWYlqjqyVsUWQsGJDUgmzZDLsM4lLcrWqdJIXTJqnZLmmG8ABFfH04yTXNwu0A0JSkAFxfhYwPGyRmISTLdklPZc1WkoGAhCPK8wEAn+113t3WKNW2U2gsZ0RfTbXlJ9qshF2EIl6ZaPj11NLt+PLvP8B1//xY93riyrpb9zqQaISzImNiuDDVCqD6bBdJ87g57LKqaj6MapWkAf/x2Cqdvz6Mam7YP4bee5Twfvz/3BRDSmIIj3+Nxw/ptjncxJ1OirvmqU5/ASU+I5NlHvL3QLopw70VMj5sIGvxCwDmWSD8dcos7nYn2S6s1LQk4cjyAgDOagoYuS6NUm3NwpLpfIaeDH/WDjR3OC7NbPu4KRq5bvCPxdsBAK+vq9O9zh6ezPhQPR/cNgFmHHEdkoHE8afakyixzkeavV3i/+dx3hu7Rc8M98stLpjngzewmtvTv06ShvzUTJ64cWhwbRp5qXhRqRGqED2LCw0+EOxGfR0J6Vc4Ff1IG2qbLLfmL7Nkpe/7KmR82CBB5W+SF8+nIqYlOI3/STAg4Yj+iudj8z4HYRdOg8LgK5waFSHjifbRbBfRb52u+t4u7PvIZOXJYWV5hq+za4YZnl0xWTFUjcIuQkMy0dhN1XXOp3fyglPnq1Xm+dDEf0aTtO39xv+XAAzpp5y/9bWN6vtuVMNNFvJTjUMLr45ey6WvycK/xhNOs5mfG/ATd1qeD24/Ee4Z5kRHItqsy7cdSrK99geHyfgwhIwPB4jiLfPeLvpUW7sXvdbnQsKRAxTPx/o9jVZ/Yj1uzrzgO/KKQlqRaEgTtWWjfXi2ED+pV6EX8biZzHYZWpav/sxPmuxIfMZDe5c+LdtMcCqOMlXjg79vlDof7lQ4zeXEfy0uhF74xcUJR5QBAD787ID6frMrYRftZ+uwi7lXx7inU5KwS8D4meYp3KF3pGV8aKuqCOfxcbKIEs/llv3Wi0DekCbNhzFkfNhAvADNV6RMcCqpK0fA/kWvhl0CwLFDSwEoK6xDKbqx1dEYeD5CXIG0ZPZEOp+hJyMaWrUNHns+xGJ2GTj3hTmaV2BPg9b+WxbCLoCi+5D11geARMEpM5oL40LPZMZHc3sX/vPRTtTHS7EHBOM+XZFgMCAhJ34Nu6H74E/BF4aUANAXoXPFwEmS5q0WUOMMK9GrY9Sv2qqrLZCdmjIi/LideHq1/ShI0Nc3ceKFFs/lniTZb6T5SA4ZHzbgs1gA8xWpUaotYP+iZyuZoCRhQFEOhvTLgywDG+us441mGApOu+WEzyWSzmfoybBvtdIgo8FL3GxZb8Xueu3zsWs4GJB0Tbl0tSME40gLuyivl+THO64m6e/ywBsbMefZVZg1bxkAqBkXZqnsqcI3qUu1EmhKcGHKgmgIZVxNDgBoTCdDgx2C+6oNs11gZBya1BvSZblZP/JDPhCX84/TdbsbHet0jIT/gLMwHhtCabxjc7Jngd74IM+HEWR82EHwIJhVYGSXXSDNi57PdgG0Cz9ZmpeI0QqIT7ljqxwzwWkkGFDfc5Iy3FNhz4/KYm+ND9HjoqV0u3/uzfrX6NLF40aA6Plgl4uozdAe1MqknMzz8eZ6Rey6q17xvCQLa6YKv/Jlk7SbNRfYOIcIuplDLS4YH9zPDa2dCR4bnXEYP/8Jn81Ay6VLtTVYbmSlpowAf002tXdhm8PQC//9Bzgj2lmtJGVvA4uVNOCDSQTofNjFTnPFvgQZHw5QG2qZ3Kh8UowkaQ8H254PLtsF0Npn2zY+uBUAI8QXFIppYSIjJEnSTUB9BTYBD4wbH173dxEn90x0teWNCd6VzFcxjQoZL+r4WLE9wQhnD+ri3LjnI4nxMb6qWPe76vlIOz2SGe9apVZ3wi56T6FYfTSt2hTqQUQ3f6v+7fj/kiQhJ2QcUjLScvH3vdHtHvHIy2aFeORNDj29Yg8iNxpkluaH1f1YpZDzt6rXQvWeAhkfNhBvCrOVmZiSq2a82Jy4mU3DPB8F8Ri6XTeemKUDJJZSTthAIJ0eNT0V9jWy1c6e+iyFXThBp9uCX35vOs1H/P+ApG8RoCsEFv9ffKizTYpymKfO+rqv7qf3HLit+eDDLm54PkQNVb5BB9N0vyfxr8V0W3VihSY6TSgUZ+j5SBZ2yVxNmVRhEzc7r5+nofsADK5TB9cTfy2xxYiV7oMPFe1PsyFob4WMDxuIDx3TVNv4/+yidzpxaxe88ntB1FnYRYUXnBoYHxa2R1pl4ns6VSXxh01ja5It3UUtMsZNGG6vSM08HzFucmNizYSwixB+7FArnCr/M2PZbtEtZnw41Xx8WtuIrfubdWNVjQ9XBaeSbt88qVZ1NT2G8DWLEx3/LDLTsxiGW/lUW4PjMi1YNgWn7MONiGf4bXZQ24jbTYKHLp0WFYBW1Zb3hMqyjB/OX4UH39gIQEsWANLvRt5bocZyNhBvZrOy1+JF77TWB6/WB7TMBLt540arsGBAgiQpY2U3o1Xvo6hBa/XeDjttzK1e19COWExWPVGZPi5Dp8+JxRBxcc3AX9O61TV3DevSxbm/ZWE6zfOhTH5s0cfChMnKjYv3VUA1auxrXRpaO/Glh94DAEwZ3i++P8myAZtdxEVIbiTxMbq3sU31/DhBrBIrhvy0BY6kpkOLn804y41LtbUMu2SzyJjC0LJ8rNrZgJ2HnBn9YnjMafgb0M5lQJI0ATp3v+w81Ir5K3YCAK6oGaoLu+xvIs2HEeT5cIAmiDPzfOgveqcVQlXBKdN8RB1qPti4udeUOgr6m9FM8wFoJY/7kuCUUVEUhSQp7tqDHorHxKwqwHmpcTP4OW63YdhF9HwkZruIOgG2jer5SHK9isYWM+6crFT5TJMD8ZR03jvgivEh3N9Gng+nE6Z2DD0Jmg/OK5pj0VxOGSdf3yc1wWl2i4wpn21wvMfL7gaHxofw4Iuk4b3Vai4hadhl0eYDurCLl8+MngQZHzZIKHttVvxJWHE47e/CjA/m+WArSduaDwPBKWDPI8MMKDcqRPYU2AM+HAygvEDp4ZGN7rb8hOF2CiR/5Ta1damGLf+wNfN8MMRYOtuGGR/JKn6KnjlV8+Ggm3KQ80rtiWfP6DwfrhQZU/7XPB+Jj1GWuZPuMVgdjwTNB/vBwrDit2Ek03xksolhqrDPzhrM7alvc5Ruy3uHgDTDLuq+jJsJ8p6qz/Ye1mW7dHTF+pRQP1XI+LCB6EFgD8eEbBd1u3jYxWFnWzHbJV/1fNhV0+tV3wwxg8Uy7NIHPR/895iKyMy94+oftHzGlOv1FxIKqbUJL0ummo+AEEvvjslxUazyfqphF3FeSSfbhZ8E2HEDFroIJ4j3t1HYJX3Phz7Tane9ieaD/34S0nH1HhpAqHBqcL+nW1XWDTShdw4CcY+jE9GmaCSqnW2dhI75sItB9ht/De861JoQNnMlA6qXQcaHDRJSt+I3qngxJ1z0jjUfyv/MDZ2jGgvOHgzis0YUwpLgVA//PaoPHIcuYEdwX0g0zbRTM8zc+3yzQd11YiQ45YrQdXK9M1IVnIoeRbHOhx2DyzjJRNNFuFF9FMJzwCjssj/d9EpBbySKGxmSxGW7iBVODTUfXNjF4IbPZCn/VIlxHkemr3DiSUrQfKSRPcV7ArVngfF3spOMj5Qg48MBmlFhnMUiXnhOJ25N86H8nuNw9WaW9SemSJr1duGP3acEp9xMq6bbeuH5MPi+3KhRkMqxWDoxL7DL4TRLugqnbGxC6WpRcNrZLVuOW7xf2LZOtFLivpTPAHcFp/H/rYyP+jQnG3YM5vk42Nyh3vdioTc7hlUkSdgl4rAsQCaQIKmhF0fGhxj+TuMe4q96vuIxMzp4W21nfYsu7AKQ8WEEGR82EB9rar8Ik1irlu2SXqoti2OrxofN/YjjYbAHkRp2sdiH01olPRkjz4cXxgeDFwRmzPgw6VnB14jQN0fkxicIr4G450NItQXsdXplD2onBq/Rgj0gSVrreRezXRh5BnU+GtKscsomtdK8iPqcYRoDXcaRJKnHN9Oz8NdRKIngNNcHiwzN8NU8P7vT0NCo4e90jA9uTCzrsCsmq+eJ93zsqW9L0Cmlez30Rsj4iNPY1pn8AufirIC5J0KMtbqV7ZLjcD9GxYZ042I3o6Xmow+m2sb/12s+Mh92sRZ1umv8iRNpbbyWCR9ijPKaD25bdrnwvTM6umJg9anCwYA6bqtOr0beCkB/zaVatMtoX3xowh3BKbu/9c8BnvrW9DIc+EwN0evGn4uABORHjMNbRmGXSBLNh1nBMi+JcQ8s5mWwqiaaDNHz4eQZxoddcoRmi8r72rZdMTlhkUKej0TI+Igz7dcLceL9b1lOLnwcHLAwPuL/i5qPdLNdHIddTASn9jwf2V8ReY3O81GUGOfNNEaThtuCX3atstUcEzbyhhfvgTBKtQWMhYoSeN2H+TVrZlc4aWholBWhhI7cD7uwG8bI81GfrudDPYSUcO3pDUAtk0cU9ho1jORbyxsRdbH7r1P4z17oMMMPSMyicifbRSlRwK73VtX40B+LCWTZ+Mn4SISMjzjsYnn7031Jt2U3s2l+PRcvB/iQRXrZLqzWhlPBqWheiJ4PK82HU+9Nz0Yz2vjVp9slzlNBXbW5nWrLhI3q52vVvc53Zk7wfHDXCx8W4ktRs4nZKuxi5vngV5gpGx9Gu9Klo7p3/tQ6H0bGR2tnWtcJf/4Hxivs7ha+GzYI5vkwaz7Hf09sEWFGJhrw2YWvYVKY47yqs6nmw8k9xPUJArRrk51zs2u4X35qzRX7ImR8CFiFXsTrK1lZ42TC1GQkZLuoxoJLgtNg6vvrk4JTLsxWUazU+WjviqW9qk31uDyZ1nwcOSAfALB5XzOa27sM3cztnTHTa4nPTOEf+mxibLbo72I2RYcCkiq2TtXoNRac8nU+0m9vLk7qRoJTpbaD8++K91oMLBY9H3rvU17U2MCzCt/x4+fJTVKwzAv488s8B41t9u85URrt1HMMaM9iNb1aMNLM7ouSFDs790XI+BBIyfgQNBjJGjo5zXbh+2sox3P2YDCK/QK8sj2F8up9squtAks37V+gPEi8Ep3q3OUZSrVlH3JQSS4GleSiKybjo+2HdG5m9bvv6oaYbq6Oz8DzoZsYLSZ9Mw+BWNo9FUyzXTIQdjHyfAQDkuqST0f3oRc7i5oPbTsJWtjHLLTFf1V8KMvodk9ngnYL/r5z2kwTMCgGl8ZnE5uF5gnaGDPjo19eap2d+yJkfAhYlfIVHzp8HJl/gIpGilOxJp/uCOirjNpx6RrFfpVxOanz0Zc8H/rzphUXyqzo1KghWOY8HwqSJGFcVREAYAvXlE0Ua4r3gDg+vgqqBCmlWh/sWMP75ye8Z9fbZ3Rb8LoIVwWnBqm23TEZxbmKkeqGh0yChKr4dbfjYEv8+Nz7koQ8U8FpotI8mkTz0avCLmIZ/CRGmvW+EB+T3ovS2qHcj2Zhl1IKu5hCjeUExEqCVrALMCYrtQwiIeXCFB/QrMKp3YlDvQmFOKMsK+7tZPFbbT/x8Zh6PliFUwvNR18UnMb/Z6eFlVj3qlGUZDBpuF5enTOwWFqjUlMhUbfR0tGdEHJg5EUSDfFAAJzmw/yBzx7cM48ZhGAggMlDS9X3lOuuM2VvXzLPh5vhBHERwijJC2P/4XYcSqOnB2/gjB9UDADYWNeEw+1d4Psa6rNdTITv3Gv6sEvicXNcNNKcoul2JBTmKONpchJ2MfF8ODGsYoIdpxky+nYEIqUUdjGFPB8C1mEXMdtFO318dUFxOzZx2L3o+ZsQ0ASngLOHqJjXL3ozrDwfTvUmPRlZOP9shZmNVWHGi4xJSugFUAzwGPfg5lfWZl40dXLnDRRInOYjuecjEJDwvdOOxPHxbrQAL4pO7ZyzDDE+pbSloztDXW2VsxAUuhyX5MZd7Wl4PnjDoaIoB4NKchGTgbW7GoSwC5/tYpZqayw4Nbrf1e8xi/c5r5lz2slb2Y+CVgY//bCLmSHD7hfxWiDBqTlkfAh0xWTTJkbiSiISDKgXI99XQdwuz2Rlkgy+sA2gpDOy47mRdSJ2eUylt0s2hWhek2hsulii2/K4ia9lSvPBP6CZ52PnoRadR4RfWYuhQAYfguQ1H6wfkVV/l5jJPgH73ZTZvliGCKAU1soNuxh2MTHAGCXxOH86VU7F0C0LSe041CpkHAH5UbPPZh6+AwCj3nE5fki15a4HFnZp7uhOqBqa6o5EgyGd+5ddo6J+hN0vVSU5OgOEPB/mkPERJ8RdMPubrQvasJWEJEmG7lxt0mIrZmcPvphw80iS5Cjd1izskjiZppBq25c8H/H/NSPS23i4YYXTDKXaSpI2wW3e18x5PvQra8EZpKILzcRfC3CC0xYrz4fFZJ5QCC/p59HCRU99ewpuOvMonDyyXG8cpdm3RBYvDAE3NB/iORnEVfoU9V7JMoqMwncA0GlwTt1swOcUXqrCV8m16/0wEwY7MawSxP/CvtglFQ5o/WgAoF8+CU7NsGV83HfffTjuuONQWFiIAQMG4IILLsCGDRt027S1tWH27NkoKytDQUEBZs6cibq6OlcHnQl4a3WXSUdKoxVpjoGbUtR5mblFkyGKnJTj2W9tn8xVzoyPVLJd+lJXW3ATMABX0zXtkinNDf9QPaI8HwFJeVCyh6W4sjbqlAroJy0+XKVOjCkUGbPyfKQ6GfLhohOP7I9rpo1EMCDpMlLSPYeiO1+kODf9CUdcMKg9Tg616mqZKGExY8PKqLIx7/kw6lzrNKPOTXiPYyQUUJ89TTa7eZulRDtZPIgGp1g3hh8zMxQBzfOhpF73nYVbKtgyPhYuXIjZs2dj8eLFeOONN9DZ2YkzzzwTzc3N6jY33ngj/vvf/2L+/PlYuHAhdu/ejQsvvND1gbsNb1eYNzFKfPCyTrOtRmEXIS3LrsVt9KDnay6kvh82Hv3D0o4rui8LThleZwLwX5fT0vp2jpUTDqK6X57+dehX1mZeNH5VqRUZQ0pFxszSdwHN8yG6yv+1Yidu+dcn6BImUL7AmW58nCg03e/PaBHCL16Kcp3XpmCIdSXUMuNNbboLU4KW7QLoPxufycTgPbxGXjQ3tTFOERddTqucillj6Xg+xDGZaT4CkoTBpZrxUZgTVq8N8n7osZXt8uqrr+p+f+KJJzBgwACsWLECp5xyChoaGvD444/jqaeewrRp0wAA8+bNw5gxY7B48WKccMIJ7o3cbbjr1Ex0avTgzTEQMcnCgyNZHr7pkAyMBiNPi1NUxXanclNbC06z/1DyGtH4SydVz8lxeTJl+Ih9Sob0y8O2Ay3q+3zYRafngDi5x3Uhnd06j1EqqbYxE+MYAIriMX8x2+Gm+asAABOri3HZlKHavoRO0IxgQEIkFEBHVyx948OgXUE0FFCvCzbmxrQmG/0xWIfg5nZ9Z+GABITDivZMlhXvKtPZGHk++HNspB/yw30uZo4U5oSx/3CH7XRbd7Nd9M+CPMELyof7BnHGRzAgoSgnhEMtijexggvJ9HXS0nw0NDQAAPr1U9TpK1asQGdnJ6ZPn65uM3r0aAwZMgSLFi0y3Ed7ezsaGxt1/7IBf0ObhV0Y/INXdQtzN7K6L/WidyY4FTUfgLNiX2YRbtHzYRV2yU8hdt/bMPNgeeU+5b+PXIei5WSIn3Fwqd7zwady8sdP9HxoHkCd5yOaeoVTo8uPeRHMVr3r9+ifF1biVbdEp8nCGSzs0uggQ8PsGJpwtyuhzockaeGtlnbe82HuUQKMjQ92jjq6YvYFni4hGg2a58Nm2CX+v5jt4sjzIYxJNNL4cB8fdgkG3AnD9UYcGx+xWAw33HADpk6divHjxwMAamtrEYlEUFJSotu2oqICtbW1hvu57777UFxcrP6rrq52OqS04G9os7CL0a1opA4XHxyilZzymOL/B4w8H7bCLsYPIbEGg1kMW9k2eey+tyF6sLzKdjEil11nrns+lP/ZN8+7jJXXJeSEtawuFj6x1Hxwf5sv1EMwgjdWRFi2Q5OJ0SvW5TELu4hjdAMzIWdRbvqeD3Gyy+fCV7psl/j/TrxyRiFUPjyVLXG5+NxzWuVUPId54fRT5dWwi/pM1xcZU8Iuebrti11Ive6NODY+Zs+ejTVr1uDpp59OawC33norGhoa1H87duxIa39O4V19O5MJTnUrUqaFsNB8MK9Bp73KpKKrDzAv6W6FOB51X0J8NxXPR3N7V1Yaq2UDceXoVLtj+7gGp9fNCp26Y0H/hE7QfEjK6jovPikx13eCfojzzBil2lq6zC3CLoXxvzebyMUQqToJGDzZ3A6b8cY6Xz+jKMd6zKmgXXssdKsZ/0adhY2MPLFOjYiR8cEbUdlKtxUXS+l0tgX4DBXNgLf7DGPhPLNS7fx1x4ddApKkGqPk+dDjyPi45ppr8NJLL+Htt9/G4MGD1dcrKyvR0dGB+vp63fZ1dXWorKw03Fc0GkVRUZHuXzZIRXBqlDVipMaXhdUXe3DIsk3BppHGJI3Vm+jZyONWOcr75rBJpCsmu57u6VfE51MmdBdrdjXg/Lkf4MPP9xu8q30juSadS9MlmeeDkRfVh33MPB+tnXpRqln1TR4rzwd7cJtNPOK9apk549L3Z+RJjBh5PtIQnIrXXoEavhI8HwbGibgPs0WFkXg5EJAcF0V0C9HjWBC1vgZM9yMKTrkK0bZbXag/GQtO+TGzRoCAct0zz0c6dV96I7aMD1mWcc011+C5557DW2+9heHDh+venzx5MsLhMBYsWKC+tmHDBmzfvh01NTXujDhD8Dd7U1uXpYvMyBgwmhSMej/YWXUZhl0MNCZJ92Ni5IutwK3Kq/OGSotF/L43kaj5SGEVb5Ob5q/Cqh31+NqfliQclydjgtP4/+wzVouaj7hFwFbW6mc30XzwqbYBSTLtuKobg5lrDkja1VSckDSvS+K+3PJcGU3qUSPNR6tzL6F476ve0w7jOiVGod1kxdDMROtaJdDsLDK0z678n0zzsX5PI77++BKs2lFvuCOj57D9zEP9mMQ6H+xcB+JZY189djCOH94PoyoLSfNhgq1sl9mzZ+Opp57CCy+8gMLCQlXHUVxcjNzcXBQXF+Oqq67CnDlz0K9fPxQVFeHaa69FTU2NvzNdOAKSIh7acagFxXnFuves63zEErZjlnswvppo74qhpaNLLbmbjJjYUABOUy6NNR9GrcDNCAUD6mc43N6lNkzq1QjhgHTdv0ZYeZF0glMXK3TyiNdq/4KI+j0rryuohlebmeaDq4LKXW/66qiyoVGQiubDSrzZ3tWthj26TbJdlDG6o/kQV8GAseajozuG9q5YQu+XlI6RoPnQHtXMu8F/xjwDXUQyz0enUYlTKOepHp1Zq0shCu1ZGMvM6L/xmZX4tLYJ723aj633n6O+rtm0yo5CwQAiwQA6upWMp9I0xpSQahvTH+uX/zdJ/VtW8Ta97Kfehy3Px6OPPoqGhgacdtppGDhwoPrvmWeeUbd58MEHce6552LmzJk45ZRTUFlZif/85z+uD9xN+NXJkHjMe/vBlsTt4v/rsl0MNBhGKnMn6bbWglMb+zFQ5wOJno9kFESTu9B7E+LKsTjXOO0zHURPA5BE8+H6hKC/ViVJ0hnHot6FaQoSNR98nQ/ltYAkqVqhrphs6uo2uq8YRSarXr7y5cbaw+rPao+NjIZd4uM1CbvkR4KqYeB0whGvvZxwQN1ns4HuhrVuT6eZHSPbnW1FrUpBEqPfrJKscZ0k47oxScekjkgIu6gVTs2NXvJ8GGM77GL0b9asWeo2OTk5mDt3Lg4ePIjm5mb85z//MdV7+AX+YT8sXmL6872HDbZLNCqMHmhGk4eT/i7GglP7xb7EFYA4JqjvW++HuX7dDDv4GbOUv7bOmGF1SCdU99M0FmJGCP91ZK7OR+Kx2MNSeZ25/dnqM3HVDejTkPmHfp5Bmm7iGFLwfLTqzw2fBvrupn0G+zLIdnEr7GIQztA1bHNDZChce3w6bZOB96ks3nH5wOFE48Mqi82IaIa8bKkiXg9qxpOJ8cHfQ/r9xH/QLQLZPWzzswljEhcDVineZHwYQ71doI+xjx2oCF7X15rXGzFyh/MVR42KJoktmFMal8EF7aTOB0O8Ldhkqr6f5BmVz3U37QuIqx1+te1W6IU9WAFjbxsjY9kuBqt43vhgD1s+1VPZXvB8cGnI/PUfDEjqatNM92EVHjCL9/PZaZ/WNnGvm+/LrXTlZJoPgCs05tBLZuQNEvUz/PH7x42P/ZzxkSzsYkam0rpTRSyuqKXaGp9L3nuo90DH94PE57DTDuNiqXZmUFsZvWR8GEPGB/Rhl7FVceNjT5PZ5jqMjAojd1++g8nDytNiK3xjonkLBwPqxAAkXyHlp1Awqjchnv9QMKCu8N2K3/KT6PZ4ZVFRpQ9wk3+Hu6nOYkonoDc+IKz0zOp8aNeldh+IegWza9ZKJMo8CO1dMV06O3/eth1oTng9o0XG4v8bNf5j8KJTR8cwuPfFtGX++GUFSqjsANcUM5ng1Iz8FKrSZhLRYZFMa1XEXa87OAPesCK1w1o94j0pGsUxcdAG4yPjQw8ZHzD2fGw90JywUhPFeQC/IjSv8wE4qzFgFC5xYkXLRr71OPzKO2nYJYU+Hb0Jo+dJURIXsOODANhYpzd4+e+DfU9KCW33jL9kng92rWsN4hJX3YBxx19mACSr9WHx3Db1NvFhl637DYwPwzof6ReZAmBozYv1UdLt72JkXqphF4OMo/7M+DD0fOjPbCRo/dgvMgl1eYXoRWDXfirhXr41gJHx5bzPFnRj4o1ipbAeaT7sQsYH9M+SsoIoBhRGIct6dy5gLCQ1fLAazPV5Duo0GGk+SuMtmu2067Z6uPOhl2QrpFT6dPQmjGLGTks9m8Gv4P+1Yqf+uBw54YDaFMxNwavRKl5nfDDBaYLexzjswmdQaJky1iFHq3h5MCAZVrjks00b27pQ19gWfz0Fz4dL2S78Ia45fQTOnTgQj10+GYA2gTudcIwMBybeZRlH/ERXls/CLprnwwze22mE29e4XcTQWbLx6AxRzgtmZFhr14C9Z1jCmKIh9eemti7SfDiAjA/oXWqSBIyqLARgLDoV4Yv/iPvLhOajJN6i2Y6q3WwFBIieD2vzoy+WWAf0E7NWd8IdA4w3NLYeaNEZsfxxJUlKqvpP5/j8V1+k03zEV3rCajghbdsgc0r0fJiF66y62irHFlzc3GQzoFCZdFmNB5byaCw4jeulMtDbJT8awu+/dgy+NL4yPub00iuNFgxad2GLsMvhDvV8mgXnkmW5uX2N28UsxHHYpLqyLnRpoJsy0nzYDR2LXpQAZxQ3tnWmpPnoiHtJCAUyPqCfACQAR8QzXjZz7lxxO0aBQQ660cOJFelqsXHxGYnnSuPGhx3PB8PQ8xG14/noO2EXoxLWAF93wi3Ph/73rfubTSeNTNQZMXJNFxl4w4rUKo0dCdsDiuAy4bnLNB9JPGbJhJFizLyb+24mVZcAANbuVgTiVimPokjQKUaLi8QxpzeBGxlkeaLmw8Dz0dEdU8MyZkbdKSPLlTEKgnN17CadhL1CXXQF9GGXzm7jdO2YYMBr+0n8/IVJaoaYD0o/JkAfgjVqAsooiIYQjP8deT80yPgQkCRJTbfdsl/v+TB2hRoYH+q+tL9VXc+2LG6DsIuDfH4jASNDzHixIpUOpb0F0SBlJCv3bRexffgWzuAVH2SF0QxMCkk8H+x1tUR03OgVxyZJUkLROrNMmcQhmK8ajY7Nn7PRcS/lZ/uUe9Wb8urJt9EEp+55PgqE0Bf/Xm4kqJ5npvsweg4BwE+/PA43f2kUXrzmJMNjZ93zISze8sJB9TMYGf28J2w7H3aBfj+Ac8PKKATONxC08rhJkkShFwPI+EDiRDM8bnxs3a934Rk/EAzCLur+OCvZQYEq9YLmrO2SXMXz0dLRnXrXSYuVJau+JwzXkGSTSG+Cn194YzPT8fCtgreNJzOeDwV9aCkxFFcsGF1GmVG6LBnub5mBbtaZNtlkzq7R+rjBHeMWvyMr9CFS6/Lq7mqWrKKUafd3MVjo5IlhF2EAZQV63YeRQB5QnlnfP22EusgyHXuWJkpRW8eHOA4bXPtiU9CueA0eo7L9RQ7vISP9VxFX+t/K4wYkGtAEGR8AEjUfR/QvAKCIl4z6KCQTnBopn500FzLyWBTmhNT9pnohG00wDOauVd63Ro3d9wHBqS7swr3utgHAHlpMTLplf7PpbJwR48PAXawLuwieD/F1HnGbgPC3ZtkTViJRIDHUyIddjqpQ7tUt+5vRHZPV9zKZdWB1PzHSFpwaidvjxr9RkTFAr/tIh2RFvTKNkfeq0EB0zOCvh66YjN31ivjYKKRY6FCLw46gGxOng7LS1QGUbmsEGR/QP+sDkoSqkhyEgxLau2LYE1fRK9slTgrMIlfikUKHQwPjw16KrDYmdXwBybbo1Cqmri+lbW1+iIK33oze86H97HY8nH03R5THQ32c21j8Ntj3znQXrhzf4DVd2CX+f4LxYfB3idvovSYNJuNOpvnQrvfEsMvQfvmIBJVeNLsOtVpmHZSoIcs0jY8k4wU4zYfDdFW1V4hun4LuRjh+WfxePtjMzrO1kNeMZM38Mo1RiMPKIBIfy9sONuteN9J82DWsjMMunODUItUWoIwXI8j4QGLcPRQMqD1etuyzjiEWcClX7MIyWhmVOBCKmlVr1NzQ6V/IbLUEJPd8FLv08O4J6ENxiW5bt2ogsGuPedu2WAhO2eSS7sqWx2jFxhsf7Bo0C6nw6EJ4SPSamD14rXQa/H61sIt2hsJBSQ2TfravSV0gBA1mAdYMsb6lw3AhkSqpFO8qFgwFp8fgb37VCGtmuhv9CEqFRYlFeR9LXK9lYxODqLVluFN8fr+3ab/ud93961CzZZgVxnlRjKpa85DxkQgZHzBe5Q43Ep0aXGDBgKRehKoxYODKduT5MLGmNTd0ip4PC8GpLuyS5CnF0hr3ct6g3orunBmIMd16iLCjDI97PupbOtXJQ3yQ9UtY2bp3fP5IlUU5KMkLo7wwqnr2xMwIQ/1QbsRwG2Y8mBofSSZzJrJmIUu+rkNAkjBukFIY8N2N+1XDxGh8bD+d3XJ66eIpeD7Ue7Q5zTof3Gv94jV+2PcvHr+fEHbRJA/2zI9s1/kwMkatwtbsejjhiH4AgDfX1Sn7Mdh3ul6dgIGRnprmQzkuGR8aZHzAeJWrGR9GeeN6SgVPhJHHItkD2GpcYmy5JNeeB8IqHqn3fFg/pCqKcgAA+w63u1rim0eWZWzdb6y18RLdNcGdFnF1mf5xlAPlhYOojJ9fUejMYMbHATeNDwNDORiQsPS26Xjv5tNVD0IoGNBVGzXUfIiej/j1VJREbJd81ag/5/ylEQhIOGv8QADAuxv3WYZdcsNBtQz6oTTOYSqTOrtOmtq70GGjCWTiMbTXmOeDZeskaD5U41QUnNqDfV9tnTFHY08HM62VleHN/uToIaUAgG0HW9DRFTP0VrD97LfpPTQMu3BeUKvrDkg/+6k3QsYHoDORNc8Hc4Mf5jYznhBFDYbW24XPUtFcx6lOrGZ5+rY1H/H/jW6LMk7zYeUhAbTmVZ3dcsZCL/9cugOn/fod/Pr1DRnZvxOMHoLuGR/K/4GAxBm8xhkv/dXOpcmrWKZ8/Pj/4rURCQXU1FSGUdl1s/eBRMGpedjFWpuQaNzrQysTBhUDUCYdVgfCaAUqSVLCvpyQiuFdlBvWhOEOQi9GCw9m0DBE44ddH9vEQls2rQ99SXtvJ0u90a8NXPTq8DDPR1VxDvIiQXTH5HixsUSDYWCx0gF3/+H21LMF+XGZeD6siowBmlcwVW91X4CMDwjZLvH/h/VXNB/6ojXxbRLCIPqYtFHMkl2oMRk4nGK2iNmKkHkrDtq03g1d0ZzxkeyBHAkF1Mm3LkOhl0cXfgYAeOSdzzOy/1Qxewiy83WoudMV7w8fr2apj7vqWw23zUTYxSiUaIZR/Q+eRM2HslE/VatgPO5kq0ZeqwFok00wvn1FUVSddFiTuWSZM+kYj6l4FIIBrbbDIUehl0SDrJ9ofAh/UXNkGSQJ+Hh7PfY0tDq+PoO66p3e6j74EevLx5t/b1o/H82A37zvsOHzujQvrHYg3tuYuhFvFALXaT5i1hdF/0Jl/PtcXDj0dMj4gPFEwwSA2w+2oJPljWtb6f6+VFDjGz2ccsJBtadCg80UWXEVV2bT/W71EApzTaZSeSCruo+mzNxExw3rp/6crZgzYGyQAtoE0NEdc6XMPB/fPsKk7oJ6bO57dyvsZZTSaQaLWwOpZbuw67Y8fs00d3QbZkpZeeYAzWvYEH/Ii9UkJUnCyAHK/bpky0Hl2CbB9xIHRfrMxpvMo1CahrFo9Awpyg3pKxILX9rA4lyMrlT0L6t3NiQ9r1ZoIQVv78GYLuzCeT7i2jSjZx6b94OShCPLlevgzfV1huFmSZIwsFgJb+42MfKNx5U4JrboPNjcYZiKyzOgMB6yztBzsydCxgcEwWn8f341JfYLEK+vclWI2a7bn/hwYK63VHUfRnFGwH7s3yh+bATfFMyMAXFdQqY8H7xrefM+4/CDF5hpPnIjmhGZjm6AweuDWLqt0XEBzePV0eWO4QPY0wXoG84ZZLskCE6VbfKjIbXCr9HDV3VZmzyNmJYkJsfFfXEZAp/R8qW47oOFrMyEf/1UL0o6YRfl/6QaqfiEY+bJsjxG/H/+NEuShKPiFV3F9xis4uuG2qaktSesYM+0PQ32x54OstHDGFrX3lqD8fB1YoaVKR7rZ5fv1JVJ4GEdiMX2Gbp9xmS8vrZWNVCMvCjsWbivqZ3z3hnvrzzDi7aeCBkfEERO3GqKTQaseqLZYlO0pGUTo8F2iiynB+CxHftP8WGZChXxmyhTFjx/jj9LobFfptA/A43PvxsGGO/OHTmg0HLbvEhILWHulu7DKJZtRr8kBen4sIuZgW7kdk42mUdDQdV4OdTSqRaVCnIHmTy0VPc35mm7LoRdUvQWsQJom+qarDc0OoaBbkzZJ2d8GPwda4q5ce/hlFKCzTgi7kH43OMFAO9x5B977HNv3tec0JyN94Qdy3lOV++sV1/nGTNQ8Q6t39NoOo63Pt2Lq/++Aife/5Y6MnFMvEdP6zRs5vlQtq1v6bSlNenNkPEB81LazIX34ecH4tsZ38xVJYqIabdglYvXod3c/6SejxQ1H8kelqVCrN6KAUXuTbxG8G5Xq4dDpjFrLAfw37cLxgc38Q4qzdW1OzeajN3OeLEzQbFVpdkf6AWpesotDDarplzq33NGr9H2TKOlHt9U8+GG4DR+jCTbsdLvG50YH+wH4SCs/hBgfL601hDNKaUEm8FCgJ/v83YBYKa1GlispH93xeSERYkadglIOHlkf1T3U+5PFgYX76MxA5Xvxer5smZ3AzcmWSv6xo2pgPPo1cava7NzXZwbRiQe4rabadNbIeMD5h4NZkU/vWw7mtu7DF1vADcZiS46YX926/ubrUpZyuvepjZbqXBmzyD+gZYMlg5a68LEawQ/6X+0/VBGjpHSOCzeGxT/vncdSt8lzWd6BANazNoM5n52y/OUSrVOxnBOk5LM8yEmdI2IazJW72yASCrhAXbN1za2qeI+PuxSXhBVy48D5u5vFtZzw3hLds6GlSnna4eD68Ss8FpVSY52fINvQTU+DpgXq0uFofH97DyYvbAL/+kkTs+x7YA+DM6uh4AkQZIkfHVyte59M8/Hp3uaTLVTQzlDe29Tu2kmoFj7yMzzIUmSzoAmyPgAYO4ZuPS4ahTnhtHWGcMn3ENTvOnZZLT/cAfaOrtNW25X2Jy4zYqMVRRFkRsOIiYDOw4Z14TQ7SfJU8iswZQRlfFUtdqMeT60n9ftacxavQ8zzQegTQArd6RvHIkZTbxb3Qj2AP50j/3VtBGaKDG59cFfJ0aGAp+iKcIM+RXbEs9ZsgJNAGdwN7ZpYRfuDyRJUgu1KfsycX+7qFlKds4GlWqLErsCYTOxKHvWAMbGD1tINLV1acXIHAReBpU416vYoTsm686NPuwiGl76RR5D9ISJITjx0x9ZXoBIMICm9i7sNDEMg5wAaVPdYVNjkAlJa1Xjw3B3AID+fahIYyqQ8QFwmgg9oWAAU0eUAQD+tmir6UqiJC+sxuL3NLSZriaZO1AUsJphpLBW9iupE8HCDfuS7idZXP/Ws8agvDCK2acfmXRfmr4l82GXts5YSsZVRtCtwPTn7ZSR5QCA19fVpZ32KmY0MQ8BYPx1TRhcDABYvas+reOqx7fh+ajiJr4Wg6wVSZIQDhrviAkhtx4w/z6tJkmmNaptaDN0gQOapwEwLq8OKLUggPSElMnqkjDYvdLS0W07zGN2DP47MLJncsJB9TMy8a2TsMugEsWIqW1s01WUdZOOrhjO+M07uOIvS9XXYhZGv+pxFIyPbsETdvSQUjXEYbSfcDCg3mdrdxuHXvhFz8a6JtNWF8ybURdPNrC6hgdY6J76ImR8wLpi4eUnDAUAvLGuTg1xiJtJkqSuhnfXt5quJqtLlRs61QlVs7YT3zt6SAkAJSSUdD/qeIypLM7B0tvOwA9njE66r6oSZ0V6UkV8zm2sy47oVOx0zDPliDJUFedAlo1X8nYQdT3JPB/MZbzJNTFu6poP3rNhpndh2g4Rdu3vP9xuKhi0WjUOjnsRth5o0YqMCV+MLixksq+B8etXMWKcTaqpprDmhIPq5ORUOyF+DjaBAcCBZuNJbFiSYnWpUF4YRSggoTsmZ0zftfVAM7YeaMF7m/ZrfbEsPETMk7TtgP5ziV6J3EgQX6guUd83MgiSiU55g2uThXiXfb/74waFWcYWv22djfoivRkyPmAtIKs5ogyFOSF0xWT1AWL0YGOT8s5DLRaej7jxkaLnw2qF9Z1TjgCgZIQkMwJSWamlmo5XmhdWY+vbLVaxztE/fJyI9dzG6MxE456ub/9tecJkagsho2kk5/kQG2YBmhBwR7yEdLrY8XykQnlRjuHrfI0K0dUtpzCbj2Zx+trGhJUug/d8mIVdKgqjCEhKWvl+hytQOxlCU4Yr4aa3N+x1dAxx4gxxK3qz1PhhXKEtZZj2v9xgQMJAbkGVCVixL0DLCOI/kfgdjq9SroGVO+p1RoqR8XrccC30YvTxx1YlMT64/W+qa9LuUzHsUqQ3tq3ONfPcpPr87+2Q8QHrbBBJklSX8afxC9XIkmZpkut2N5pmqTDjY//hjpTa0lt5ZIb0y0NhNISYnCjAMsON+UWSJIxQVfzueyWYS50ZOE7SFN3ATHXPYCW9AeCVNXscH0e8Vqo58a9RPLq8UBFWpqr3SYYdzYcyvlzL9weVGBsfkiRp9RX2idkKmmDQDHYP7jzUqq6Sxc15TYqZFyUUDKhxeqfZSnYyhE4e2R+AMmE6OobBQUJWLiIAI+K6oHTvz6pi4zCHW/COp+VxD6LM2dPiZx9XVYxoKIBDLZ268F23wfUzdmAxrFAzXmqTh1027T1smpHFarkwrL6aI8v1RmFfh4wPJFfbs9z5T2vNJ8JJ1crF/traOrSzxk/C7opzw2rGi5nQicfMiGFjHRGvI7DOJG7JcDtie9QA9nBz3zBgn5md83VZSrflz5nR+f/hjFHqzyu31zs/jnDt8av5zw1CK7ywcosLNRhiVm4/A5761gn4QnUJbj97jOH7oyqKTP+WrTbFOHsqYYySvIiqoWDXhOj54MMu3RZOIbai3+NwUrWjHWUVRzdYPDvsHmNkktAcu3fMGtClyiBV4Jl5fdf85TsAmFcWBpT2DqOEhaCyH+V/3vgYPVA7R0bncmzck7bjYKthJWXe89HQ2ok9JoaqKNa3MqBZ7ZTN+5oz1pizJ0HGB6wneQAYFX+AtLCqkgYbnjyyHLnhIGob2/B6vKWz0WqSrRy3Hkg+cZgprBlHVyuuxeXbDqa0HyfuVyOYLmHT3kwYH8r/LDtiY91hx+7xdLCq8wEoHooHvjoJALA+jcwTq1W/mYHKwgvpxPQZdjufVvfLw/Ozp+Lb8bCfyEnxlb4RzFu0ZleD7nW+uZ4VLE7PjBdR81GaF8Zpo8oRDWlCcSPYit6550MhldtpZEUBJEnxdtq5jq3u2XsuGAcAOPWocsO/HTOwSOcdcXrbM0+V3ZBRqvD32Ob9zWjp6NIZCkb3xKiKxIWgUeo1H4IzEvjzxqzRolLUA6ll+4UxHVmeuvExtCwPAUnpdEyiUzI+ACSPe4+p1K80jDbrlx/BBUdXAdAuZsNYY/wBmkoNi2TFl1hKWXKXbupu4lQYWeGOW9cI9kAqL4iqrvbFmw+4fpyk4+B+NjPaVNFabaPjlYyRiv43F01CMCDhVxdNNPwbpvvYvD/9828V2nPC5KGl+M1Fk/D3q45PeG/8IOV88QWcAPOKwCLselgX/3sj4fcT3zge6+76Es4YU2G6HyYOd1qnJdXy6oBSlZalv2604f2wWhBNHtoPH/xoGh657BjDv+2XH1GF8oBz42PmMYMhScDSLQczUteHn99lWUlpjSUx+kdx5eO1/SQ+J3lDZIOJh9ZKdGqW4SOOqSQvousMbkU0FMTgUhZ6zF7rCL9AxgeH2cNkzMCihB4LZtvp9mew2ZThyopsyWZrbwWPmTXN3Ngb6w6jy8LP7LaokD0Atuxvdr35G/8gqTlSOVeswqyXpGJLHFlegHBQQlNbVxpx8USx3MzJg7H2zhk4/wuDDP+CiS8/TiPcox49xYnfDjMnD8bJIxNX5ew+qmtsx94mbTIz694swj43K/ltlk5r9jqDub+de+5SS7VlGK3WUzuC+TEGleQi36KuynmTqtSfnbZVGFKWp459teCtcgNRUP3R9kNJjX4Wxnp1ba0quDbrinz5CUMAALNPH2F4fKtKp93qPvWvG53JI1KoLyNum83WEX6BjA8kn5zzo6GkHUcBYDwnQozvMWGbKUco4YTVuxqSTtzJPB9D++UhLxJER1cspTCOG71dAKV75rCyPHTHZHzwmbuGAb8Sn3qk4sJflA3jI4UJJhIKYERcaGxWLyAZZrVccsJBg60VWAbFp7VNShltF3DLMLUiLxJSi6St3aWdr1R7pYgeyGQPejPU/icONUt2Q1WT4mmf/1ttQ5hsw7tixLgqbSHEG3p2Yc801ifFTWLCeun9TfuTPotHcdfA3xdvi+/HOPvp7vPHY9nt003DU0yUaqSZY/scV6V/phuFBlkHdMBacAoAE+Pnc+mW1BefvRUyPpCaep3PbjDbbnxVsVpsDDC+gQaX5qG6Xy66YzL+9O5m63ElWX0HAhInzDR/kGZC2vTFsYpb+8kl21zdL98d8vgj+iEgKR4Wr7trmhWeEzkmXm/FqYGUasEqnrKCqPpAfeLDrY6Oqx0fto+fDka6DzYJJTMmhvfPR4RLz3RqfLB05rrGdtQ7aDBn95xddOxgAEpNmFQbAqZqkJnBG6/p1JVg35cXng8+hdbsY5cXRtXS50u3HNDtxygMV15oXHcG0DwfG+qaEsIsTHA6YkCB2k/JbFx8YcBkuqUTRygLqiVbvF9Q+Q0yPpCaIJP3aphtFgkF1OJfgPkN9N1TlUqiTJhqRmopiMoK57+rdptuk0odBbtccrzi0lyy+SA6rVILbMJ/5qKcsPr5VtlMVUyXVLUQU9WHibOVTKohB5GZk5UJ7eM0+99ohrc31gdbkYu6D2UM1oSCAbVTLJA8vGJGYU5YzeSwm4UC8IZBascfUJijZuKsSdFDZte7YsTXpij3qNnKPxW0irrOdU1msN31y48gFJBwoLkDO+PhS6tz+4uZihZqTdx7lspz0oihZfnIDQfR1hlLEG8zYyQclHD2hErtDYNjjOW8TMmGMGFQsRp6zIaQ3k+Q8YHUUv0mcRXzrDh+uNbS2exCnB4Xw22sa7Ks95HKCouJTt9cX2daDCid1tpmDC/LR2E0hI7uGJ5c7J73Q1YfJMrvE+MPv08MGpJlklQf/mx8m+qaHBX9Ytee3Xn0C4NLACiZNulUmvXa8zFe9XzwqZKpTx585UqHtgcATbyaqjHA42QOHm+S6WN6jPj/6Xwv95w/Ho9dPhn3XDDe8T7GDixCMCBh/+F27HW5IRr73nPDQTU1lqWtW323bLLfVd+Kg80duq62dghynmNR98GHcr4Qzyo0Gxev9Wtpt74X86MhNRNn+db0Fg49HTI+wKV8WVy747nYn5Xy+/hhnPFhssOKohwMLM5BTLZ+GGkTk/nAZh4zCBVFUciyuXcgExNMICBhYry2yT3/W592jxOG2LdDW3l5bHyk6PYeVJKL4lyl1fdfPthi/zgOwi6AkrJdmhdGR3csrSZzXpcbECcOfgypnIOfnjdO/TmVWjlmMDHzbxdscrwCtfOdTWCZPqkaHy64KwMBCV8aX6krXGeXnHBQTSdNdeypwhtYEwaVAABWxbUlVp64opyw5kna1ZBSeX4zzDJe+MJlY4VEAhE+LGOWWcNzSjwdfZ6D54VIthpvugEZH0jN85HLteteZSG+OnqIZiVb6RQmxVeuVvtKJRNBkiScPmoAgOQTtNuu9Tu/rKyoumKya6JQcRU8Mf5Q+mRng6eFeVJNp5QkCVfUKGmNv3/rMxxOoXKt0XHsuowlScKEFK6hpMe3GUJIF37iWBsPvSQTVvOEgwE15j/cRjdmkYuOrUZuOIiG1k4899EuW3+rPS9SP2fM8/HR9kMpNWpzw/PhFmzhxXur3IC/1yeJHs4kn3s8p0Vh59PJNTzWJOOF93yM5EJ9ydKzUymd/vX482LVznrLLMVk/OX9LZh45+tY7bFX2C3I+ID9IlxtneYXDG+kWGVAsDDOqh0Wno8UxzU+iSgsU1P2iAEFuDSu/TCK4TtBrHsxqrIQOeEAGlo7baUqpot6zlK4JG6cfhQGleTicHuX7WqnRv1bUoWFIOyW7uZxQ1tgF6b7YG5nu5P5H74+GdefMRK//D/jOiipUJwbVrVX97683tYk4MSTeMyQUhTnhlHX2I53N6beidoHtgfGsZCRS/c4gw+xTowb0kx7kcyLwfq8rNnVoJ4rsehcKjBP3OpdDTovAu/5CHP9dPaZhJ7uuWA8ggFJ55kz44j+BSiIhtDWGcNnaZRav+uldTjc3oWr/rrM8T6yCRkfAFLN23/yW1MQCQVSjqFaTSzM0rdataa6IuQzCIy8A05d+6nAPscLH+9yqcut3oUaCQVwYjzl9q1PM1Np0XAUNupfBAKSKjS264Vw6vkAtM7GaZV3j//v5QqbeeqeWbYDsizbvj5HVxbhxi8epdbrcMoxQ0vUn+1cW040VDnhIP4vLhJ+comNTtQ+cH2wiX6ty2EXvj7HyIoCXdfkZIboBM4gcio4VfZTgsKcEPYf7sAKTrzNbFGmI7n7gvEYXJqL78QNVpHLTxiKtXfOwJfGVxq+zxMISKoB7oaWzW0tjleQ8YHUVxlTR/THujtn6KoHGvHv79Vg7MAiPHTx0abbjI9P2jsPtZqm36Wi+QAU70AoIOFQS6dlsatMPMe+/IUqlOaFsbuhzZUbySj7Y9poZbLy1vhg40htexZG+8Sm8WEn5CDCRKeb9zfjkFPNTYrhJTc5d9JAAEBtYxtufGZlWgZYOpw0QisFb+vadeisuvAYpWjch5/vT+5pyUDxN6cw78DuhraUU4VTIRbTrv1wMIBvn6yV7E92KTBvzI6DmnbIqp29GZFQQM0G4mtvsPuSGR9fP2Eo3r9lmi6tVsSqNo+IWasBO5TmhdWf0wnfZAsyPmBvlcG3tDZj8tB+ePn6k1VRmxFFOWG12t0nJhdgLEWjKCccVPutWF3MmZhg8iIhtQ+LG+mwRquY00YpD4ePtx9CS4c9TUW6pHrOnGblpGpgGlGaH1GL3727Kbkr3/j4mfOKmRENBVFzhHJvPL9yNw7EJw+vF/mSJKlezBXbUs88cOotGlNZhKKcEFo6upMWpfOT5qOQ0+m8sqbWtf2KlUnPmah5Dbq6rS284tywWra+PZ5l5tR4NQpfMh1JpgxiN4T0rAwBYD6H+BkyPpC9+Kq6WjbTfbCJOIVvyaoYUKZ1mqxqn5ueDz7mO7g0DwMKo4jJziuJ2sWu52N8PH9/T0ObrYqS6ZY3P2OM4hX6w0LrgnXmx0dax3fKbQZdcdNJnXUKq9OydOtB7DyUXCwI8N+ZvQEHApKaip+swqXXKdDJYCGjp5clDxmliiwsNI7kwmgdKazkJwgVpZ0aCkx/x3stu1XBqaNdJoXp9NbvaXTFa7F8a8+rmErGB7Kz+gP41XK94ftmpbeNGG+x8s7055sYv3ndSIcVH0gMtjp5ZbV7Ky/LcdiM6+dHQxgRf3jaUZ+n23H4W3FX9fraRtuZNkD2VtgTBhdj1R1nCq96P9MO75+PSYOL0R2T8fCbm1L6m3TOmWp8JJksvC7+lowLjlZCRuv3NKG1ww1tV6K4XJKkhP5YVojtLJwaCuOqihCQlMJfrIyCGnbJ0I3B6iS1dcYcL6i6uVXlR9vqXRqZd5DxgcTaEl4xUU2VNBGK2jAaeO+DmPvtledjy/5m00JnqWKmgWBZNfNX7HC1oqoZTowC/vtMlXQ0H4BSM2ZQSS5k2b7eBHCnnoRTivPCutVrNjwfAPD9eOOx+St24n+fJO+/ks79dHy8seQb6+rSLjDoJVXFOSgvjKI7JruY2Za40OArRCeDL+gIOH9+50VCatiaCcbVsEuGLspAQMJJ8XofC9ZbV7o2g3/Or9h+yNNSBG5AxgcyUwE0FcZVFSEUrx64x6BwmR2jaGxVEfIiSt0CsdBNuqvrZJTmR9RmZy9alHlPBbOxnnJUOfrlR9DU1mUrPu94HPH/7ZyxSdXWniyr46QTW2ZeoSv/stT2Ayjb2gJWoVcZQ3YGcSw3ht+8viHp9ulkooyrKkJ+PB3/F69+an6MDN+zdpEkCUczbYQL3ZQBzvjgZqETLXRyIscMKVG77gLp3UOiYDzTng9AeaYBwLKtzgwH3vOxr6kdn6eRtpsNyPhA9lYZvFDUSKxpZwIMBwPqSsBMFJbJjzdjnCIW+zDNYmNm1QqDAUl9MC1LsyNkQ0snznr4PTxgMdGkUvVWZKL6AEu9IFqqomLr4ypGT2e3bLvHTLbrSRzDTfzZ8nyUFUTVFvR7GtqwKWnbA+eLlXAwgIuPU7x4VrqP7PmjzPkCS+12qc+SUZbT2eMHYtaJw3B3CuUMJEnSifrTMRSY7mNZvPYME7xmyvMBaF6eRZsP4LI/L7H992KxuukPvGt53foNMj44shFfZRfgMoM6/2b6BzO+Eo/L/u8TvffBC2fcCfHshRVb02s0JyrgeY6JV4/9zRsbHXUjZSzctA/r9zTit299hrZO4/i1k4f/mIGFiAQDONjcgW0HUhMv2hEVm/HlL1SpP9tt1Z3tehK856MzSYZDJnn44i+gLD+C1s5ufPHBd/Gdv68w3TZdb9H3TlNqRWyoa0JDa6fxMTJYm8cpbhS149FCjtqHDAQk/OzL4/D1JOUMGKn00kqFk+MhkBXbDqGhpVP1KoQyaHyMHFCoZhF9+PkB2527mfHBd3r+7j9WpFRB1w+Q8YHsxlfZpL14c6LHwO64Th6puPE+36ev++DFg2x0ZSGKc8No7ujG9U9/7Hg/YmM5HtaQDwDe3bTf8TGKcrRiRmbNnZy4vaOhIMbHe3ikagTYERWbMbA4F3efr1RWXGZX9Z7lehJVxTkYVVGI/gVRDC7NzdIolEnvRK7ux/uf7TetZok0vUWsLbwsJ+9K7BfBKaB49gKS0pfH7kRphFFmm12OG9Yv+UYpUN0vD0eU56M7JmP5toO68uqZIhiQ8OoNJ6Mw/jyyKxplRsZNZx6lvvbepv14ZtkO18aYScj4QPY0HwAw5Qjl5llf25iwmrebpdIvP6LWDvl4h/ZQ88KFGwhImDpCMaReXl2Ll1cnF+4ZYdVifkhZHq6M90UwMtZShY+ILNt6EOt2N2JzQrzUmcHGqnc+vzK1fiFuZSIdF18BvrdpP5rajFfTxseHK8d3iiRJePn6k/HezafbKtKUCaYKeoMPP7c2cNPxFjGPj5l+KV0hciYoiIbU0OJ7G50b/4x0KpMyygujuLJmKM4cW5G28cq0P8u2HkK3ahhl9guIhoK4MO6xfujNjbYyidj5G19VjKe+PUV9feFG74oxpgMZH8iuuGtAYQ6OLM+HLCeulp2siifHQxO6Fb1Hn+/eCyaoP9/+3GrTkIYVsSQr8dPi1U7/vWInGlpSn2R5eLfk6+vqcPZv38O03yxER5cWLnKqhbhw8mBIkuJGTaXJFBMVp/uQO2pAoTpRTfjZ6ymfez9kVQQDkq4nUrZglXQZZl4kNwzGY4cqxuIzy3YYdtXNthbHDFYNdGEK/WmSYeXltMOd54/HH684Nu3nG2vj8MqaPZ54PhhM97Rp72Hc+MzKlP+Oz8g58cj++Pf3agAoz/6ekPli2/h49913cd5556GqqgqSJOH555/XvS/LMu644w4MHDgQubm5mD59OjZtSi1/Pltk+2tioRdRLOjk5mRuyEfe+TxhAsr0bVSaH8GGe76EwpwQDrV04vh737RdQCdZqe3TjirHEeX5aO+KJa2VYEYXZ3zw3Sz5LBWnWohBJblq2e7H39+SdHu3VriBgIR+eVpr7/nLU3O9+q2eRDYZUJSD/3z/RLXWxLItSUJyaRyLaRX2NrXjm08kNgZTr1CffS2nxqsNv7dpX9raAisvZzb44tgKREMBbDvQomYMZlJwyjh99AD0L1Du3Xc37Uv5mcnOHzOQxg8qRiQUwIHmDmyON+jzM7aNj+bmZkyaNAlz5841fP+Xv/wlfvvb3+Kxxx7DkiVLkJ+fjxkzZqCtLfWqj16TbXHXFBPdhxOPDCtFDmipfLKH5lU0FMR100YCABrbuvC3Rdts/b2cRIApSZJqrC3d4iz0Ytbwjzf+0plgWI+KJz7ciq0pPgTccO/eP1Pr8vpMqsaHH9MqssgxQ0rx96uOB6AIQo2EzW4sKkcMKMCcLyqx+k92NmBvo/756LSKaqaZNLgEhdEQGtu6EtrQ28Ussy1b5EdDOHaY4oX4bK8Shs1kqi2jKCeMpbdNT7n0PkMsAR8NBVVRcLoZgV5g2/g466yzcM899+ArX/lKwnuyLOOhhx7Cj3/8Y5x//vmYOHEi/va3v2H37t0JHhI/ke249wnxVdC6PY26UIJWAyL1fQ0oylE7JjLXqNeu9atOGo5BJUr89b5X1tsSp6WyGjp+WGolqs0wW7Hxxl86rvWpI/qrn//KeUt14RyRZGEmO3xxbAVW/Hg6AGDNrka14ZYVfnXvZ5P+BVFVO2UkSJbhzg113Rkj1Xt1sej1hCuHcJ1gQFLDBOmGXqwy27IF6znEyFR5dZFAQFK91qmKxrsNQkPHq/vIfC2kdHH11G7ZsgW1tbWYPn26+lpxcTGmTJmCRYsWGf5Ne3s7Ghsbdf+8RnsAZ+cmGFCUgxEDCiDLwD3/W6e+7tQl/+S3pkCSgM37mrG3sY3ze3jz+QIBCS9eMxXlhVF0dsuYv3xnyn+bigiNuazX7G40jJcng920xw/vh7J8LVSxYtshNU1YW93aP2fBgIS/X3U88iNBbDvQYpnR4LbeqKwgipHxzpupCM+ynWrrV9hD/K+LtibEz9002Nhkt0isj+Njo/CciUpX4qeWbE+opmwHu6UEvKDmyP66370cG3uu3fO/9SmJxo0KobF9vLNhL9q73CmDnylcNT5qa5XiVhUVFbrXKyoq1PdE7rvvPhQXF6v/qqur3RxSimRfWc4ahM1fsVMVKjqdmEryImrHw+N/vgAfxRX1Xn6+soIorj9DCb+8/1nqyvhU0u+qSnIxMd6P4yUHFVWZ8ZETDuI/3z8Rb9x4Ckrywmjp6Fb706TrLTqivACnxwWMf1u8zdTbkomshnMnKnU/Ugl5pdvYrrdy8XHVCAclvLdpP97ZoF/hu+mVUPVeYshVPYb/vpkvT6pCfiSIXfWtWJEkVdgKP2b0TBxcrFagBbwRnDLOGj9Q/TmVPkNdBp6PmiPLUFEUxYHmjoTr1m9kPdvl1ltvRUNDg/pvxw7vc5T94HpmOgFAS/FLxyU/bbSm/Zi/Yqfj/aQDE15+vP0QWjpSq7yXaqz7nAnKjfqeg3of3eqKARhalo+RFYXqSpeFXtxIv77wGFb0bQ/uf2W94TZaaM29b+drU4YgIAEfb6/H9hSLnflp9ekHjh5Sim9MHQ4AeGiBfiJw01N63PB+CEjA5v3NqON0H9nWoVmREw7i7Pj9l2ozPiPcyvRyk3AwoKatA94aH0PK8lRP2F8+2JI0m88oIyccDOCcCcri4/W1znrGeIWrxkdlpVJiu65O/6Hr6urU90Si0SiKiop0/7zGD6uM/gVRXDdNaXD12to6tHd1J838sOLaaSPxtSlD3ByibYaW5WFQSS46u2UbRbdSE6GxVuhLthy0nVGjxUq1y18T/SrjdEMnM210BW6Pt47/26JthumvmdDjlBdG1fjxO0lCL35ItfUrV59yBAKS0vpAr1tyzzAozg1jXFUxAFFzpODXr+W6M0ZCkhSvZiop5Ub4TXDK4PvLeG0YPXr5MQgGJMRk4PH3N1tuqy6ihFn8zHFK5GHBp3W2n41e4qrxMXz4cFRWVmLBggXqa42NjViyZAlqamrcPJSr+MHzAUCtsPjWp3vxtT8tSWv1kxMO4q4vj1Pj/073kw6SpBUeS7XnS6qhprEDi1CSF8bh9i5c8sfFtvLaNeNDe42tOJZtOaiLlaa7uv3WycMxsDgH7V0xkyq2mXkAs6ZVyTxD2Syw53f6F0QxIV5U64PPOMPA5efFCfFCgx8aHcOnX0x1vzzVW+i0K2s6i6tMwu4dwPuxleRF8N1TFS/4gk+tFw5itgvj2KGlKM0Lo76l03E5Ai+wbXwcPnwYK1euxMqVKwEoItOVK1di+/btkCQJN9xwA+655x68+OKLWL16Na644gpUVVXhggsucHno7uEXFyffTnrFtkPYHe9063QCDAUD+P7pR6q/Z0NQyzwU76cYHkl1NRQISJgxVvGmLd92CI+883nKYzJSiY+uVEp8t3Z246Nt9a49/CVJUtOfn/84seqpJgVx97thvSoWf37AstcOpdpac1LceP6A0y25nYlyUrwtwtsb9qqudNn3vg+omianWS9GvV38wOjKIvzorNGYNLhYrUDtJd+YOhySBKzd3aim/BphVggtFAzgjHgriq/9aQku/sMiXxYds218LF++HEcffTSOPvpoAMCcOXNw9NFH44477gAA3Hzzzbj22mtx9dVX47jjjsPhw4fx6quvIicnx92Ru4hfit1EQ0HcFe/RwZPOsE4ZqVnxLQ4qjqYLqxq4bk9qmSnqaigFV8DPvjwOlx6vCJR//foGbEmxpoZR2CUQkNSJ5okPt7jqEZg2WnkQPL9yN9bEBa0Mdhy3PR/jqopRkhdGU3uXYcdk7fgKfqsn4RdOGqHcP899vAsPvbkRnd0x12twnHBEP+RHgtjb1I65b38GwP+eD0Crdrp480GH1YyV//0WdgGA7556JF645iT0L4h6fuz+BVFMinvcpj+wEP9eYZwt2C0bez4AYNaJw9Sfl2w5iN8u+Mx3Boht4+O0006DLMsJ/5544gkAygR+1113oba2Fm1tbXjzzTdx1FFHWe80y/jJ9XxFzTC1+BAjnQdQWUEUXxyrTH6ncwXIvKK8MKpWjHwsBe+EnThwbiSI+y6ciBOPLIMsw1TUaXaMoHAMJqJ7bW0d1sUL/bhhkE4fM0At/vPKGn3PGya6c9vwDQYkTI0bft98Yplpto1fvH5+ZcrwfmrPkIfe3ISRt7+Ct1kWgUvnLBoKqk0hf/PGRhxq7vBNKNiK0ZWFGFCoeAvNGjRa4UZvl97KvV8Zr/780xfXGha7Y88OI1Hs+EHFarNJAHjwzY14ZY1xxmm2yHq2iy/w2SrjzHEVurGke3P+8euTseqnZ6rqfa+5/gxFSPvn97fg2SSVN514oWaMU8Ivr62tS8n70cX1ROA5c1ylaiS8sNJ+Cq8ZkiThyhOHAgDe+tTYRZ2J1d/MyUq2TWNbl2nND/8797NLICBhfFwQKuLmObvqZO3efHeTdo1k2xtrhSRJqj7i8seX4LW19ia3ZNWM+zLjqorx5pxTAQCH27tw/yufJmyjCU6Nr5Gv1wzDw5d8Qf3dKOybTehrh/9cz6Mri3DN6SPU393QHRTnhtMclXNOHz1AzZ2/+V+fWFbwc5Je/LUpQ9SKom+sS/4AZF6AkMFN+42pwwAAi+LiULee/aeMLIckKb1kahu0lMqYyy58nmmjK3BZPOPppU9Mugz7JOToZ35w5lEIi24ylzluWD9891RFn3X90yuxq17JrvH7t3IqJ878zt9X2Ppbv4S7/cqIAQWq8fD0sh0JqdhG2jWR878wCN87Tbmulm61nxmYScj4gD/jq7yXoqvbX7E6u0RDQTx8ydHq7/9cst10WycK+HAwgKtPURTib6xLrry36lj55UlVGFVRqP7u1jVRVhBVvSq/fUurjZDpa++8SUrO/zsbjBuB+bHQk98YWVGITfeejTyh867bk6ZRWNTv3wur5cP4/VubcOVfllpW9WVQ2CU5Z08YiEhImaan/HyBKh7nb+Vk/Wd+8MWjUJyrZL98bKH/8hoyPuBt47VU6ZcfwXdPPRKnHFWOUZWFyf/A50wfW4Fnrj4BgJJCZmaBOy25PD2ua1mx7RAOJBG2dpmkqAHKhHLWBK0mjZseielxBfo/l25XvR+ZnvyPHVqKopwQDjZ34N8fJQrXKOySOv/+3om6jLRNe5tc3f9xw/rh+6cdqXvNL95YM0rzI/jbN49Xf//16xuxcOM+3PXSOou/UvCz4NQvhIMBfOcUrQDlCT9fgIaWTt1CIpk4PxQMqBl3tz+3Oq2S+G5Cxgfc76/hFj86azT+9s3jEfaqu1GGmTy0FP3yI2ho7cSLJmXRYw49AYNKcjGuqggxOXl+PJvwjcIuAHDmWM34cKLiN+MbU4ehKCcEWQbeiNdGyESFU55QMKAKaX/56oYE74cfvX5+ZczAIjz3/alq07kThT4g6RIISLj5S6PxbU7/0RO+l1OOKtdlVwBKdd3Xk2hA/NjbxY9cf8ZIjI4vQA80d+DP72/WdeZOpQora7mwse6wrnt3Nukds1qa0OrPG0LBAM6NN6X6+cufWoYBnDyQWFbPzf/6BE9ZhHa6TQSnjDEDNU/TIQOVuVPyIiF8P67lYQ9mL7JNbj9nDMJBCfsPt2P5VrF7Kl39dnnu+1Px7++diFNGumt8MNhE0ZM4a7xmsLMaM39817pCJ4X8UiMUDOC3l2ph61fX1KreWyB52AVQno0srGdXGJwpyPgApRt6yc1fGo2CaAj7D7cbllxXXbEOrkxm2ADA3S+tw6tranG4PbGnjCrUMvnCJUnCfRdOwMDiHNzypdH2B2IBy8x5b9N+3Pfyek+qPBbmhFXtx8V/XKw7J+T5sE9xbhiTh5ZmzFM6qboEX5syBF+oLsHIioLkf+ADphxRhj9fcSxev/EU/GLmRABK8T+xrg1PzINrv7dwVEUhXr3hZADApr2H8S5X2C3VZ+VlU5SMu1fX1Poi9ELGB9yvWEiYUxANqaukl1cnZmCkU8BpxIBCvDB7KgCgtbMb3/3HCvz85cTaH6rxYZHBcOnxQ7Do1jPwLa7hnxsM75+vCk//8O5m1bOS6bj3V44epP78v0+0kFdPqCfRF/n5Vybg+dlTEQ0Fk2/sE6aPrcBRFYWoKslVjd2/Ldpqur1fe7v4ldGVRWr22gsrtbTZVDwfAHDSyP7IjwRR29iGlTvrMzFEW5DxAWjphvQI9oRz4h6Kf63YiX1NenGopoFwtu9J1SU4/wua2/rppdsTdBtdSTwfmeaxyyerP2eqvLrIySPLcWY8LHXLv1cneIT8pnciejZsknxlTa2uVxKPX3u7+BkWknuN61ibaufdnHAQ0+Ki92/9dbnp9+IVZHyAq3BK94AnnHpUOcYPKkJrZ7fOggfc6fdw7bQRat2PmKw06jM6hpftsnkqi3Nw85dG6V7zYii3nzNG/fnOF9cC4D1NBOEexw3rh4qiKJraurBwg3FhPeb6J8M3dY4f3g8DCrWS75Jk7/xdcpzSjuJgcwf+vmib6+OzAxkfINez10iShIsmKzeBmPUSi6Xvih0xoBAf/GiaWlznOaGyXyrFeTLNeYKo0IsH8NCyfBw3rBQA8L/Ve9DS0UUhRyIjBAOSukr/ywdbDDUGlGprn2BAUj3HANcYMkVOPLIMkzJQxdkJZHyA7+xJd4FXnDtxIIIBCZ/sbMDvFmxSDQI3XbFM5/DWp3vx+T6tO2QywakXVPfLw+ShpervXj2An/1ODYb0y0NLRzdeX1vHGd507RPu8n+TByMgKY3nXl6TqO+iImPO+N5pRzp+XkiShHmzjkNBNIQhZXlZDb2Q8QFKtc0GZQVRnB8Xpf3mjY14bKHSdM7NB9JRFYWYNnoAumOyzsWYLNXWK2YeM1j92SthoSRJuPAYxSi74ZmVqI2XbKbnP+E2YwYW4ZvxSs3zlxsUuCPBqSMGFKaXhdcvP4LlP56OuV87JquCZjI+QDdBtvjmSVoxpV+9phTAclpkzIwrapT0sic+3Ir7XlmP7pisNmQyKzLmFZccV407vzwOPz5nDCqLczw77oVHD06+EUG4wGUnKPffe5v2Yf2eRt171NvFOVeeOAxnjq1Q+wHZJSec/SwqMj5AN0G2GFdVhOvOGKn+/t6mfa4XHjp5ZDkqi5SJ/Q8LN+N/q/f4QvMBKJ6XK08c5no6bzKGlOWp6b4MuvSJTDC8fz6mjR6AmAx8Y94yXeYZhV2ckxMO4o9XHIsfneVuHSIvIeMDAAu80C3gLZIkYc4Xj1JLM8+atwztXUrPF7ceSMGAhF/830T19+v++TFWxpsr9eWH3iOXHYOSPK3TMWk+iExxx7ljAQC1jW0Y/ZNXsTjeMZoEp30bMj5AVR6zzeVx1yyPm9/FqUeV48MfTVMfctsOtAAAQhluk+5nqkpy8eLsk9TfcyPZd8MSvZNh/fPxk7gBAgAPv6l0dVbD3WR99EnI+AAvOKWbIBuMGFCAX180Sf09FJBQkhtx9RhVJbm6YwB92/MBKOGXebOOw8/OG4vh/fOzPRyiF3PVScPV8uCLNh/As8t2UG+XPk4o2wPwAzKlu2Sd/5s8GOMHFSE/EkIoKGVkJX7hMYMRDQUx+6mPAEAN8fRlTh89INtDIPoIoyuLcNb4SryyphY3//sT9fW+vgjoq5DnA1yF0yyPo68zurII1f3yMLA4N2PH+BLXfTMnTJc/QXiJkbjabqEsondAT1+Q5qMvEQxI+N91J+E7pxxBKacE4TGTh5bivZtPx2+4EOiG2kaLvyB6KxR2AWk++hrjqooxrqo428MgiD5Jdb88VPfLw56GVvz69Y246NjqbA+JyAJ9yvjo6IrhYHNHQkEnmYRPBEEQnnLNtJH4+gnDUMylfBN9hz4Tdvlo+yGc8cA7uPafH6nGhggZHwRBEN5Bhkffpc8YH1XFudjb2I5lWw/hf6v1TY6ouRZBEARBeEefMT4qi3PwnVMUpfUdL6xFQ0un+p6a7UK2B0EQBEFknD5jfADAtWeMxMgBBTjY3IHrn/lY7TNAqV4EQRAE4R19yvgIBwO44zylzO87G/bhiw8uxIHD7VyqLbk+CIIgCCLT9KlsF0DpcjrrxGF44sOt2HGwFRc88gFaOxQPCJkeBEEQBJF5+pTng/GzL4/DC7OnIiABOw62Yv/hDgDA4fauLI+MIAiCIHo/fdL4AIBJ1SW4omaY7rU99a3ZGQxBEARB9CH6XNiF55YvjUZzexdaO7vxaW0Trj4lse8AQRAEQRDu0qeNj9xIEL8S2qwTBEEQBJFZ+mzYhSAIgiCI7EDGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnkLGB0EQBEEQnhLK9gBEZFkGADQ2NmZ5JARBEARBpAqbt9k8boXvjI+mpiYAQHV1dZZHQhAEQRCEXZqamlBcXGy5jSSnYqJ4SCwWw+7du1FYWAhJklzdd2NjI6qrq7Fjxw4UFRW5um9Cg86zN9B59g46195A59kbMnWeZVlGU1MTqqqqEAhYqzp85/kIBAIYPHhwRo9RVFREF7YH0Hn2BjrP3kHn2hvoPHtDJs5zMo8HgwSnBEEQBEF4ChkfBEEQBEF4Sp8yPqLRKH76058iGo1meyi9GjrP3kDn2TvoXHsDnWdv8MN59p3glCAIgiCI3k2f8nwQBEEQBJF9yPggCIIgCMJTyPggCIIgCMJTyPggCIIgCMJT+ozxMXfuXAwbNgw5OTmYMmUKli5dmu0h9Sjuu+8+HHfccSgsLMSAAQNwwQUXYMOGDbpt2traMHv2bJSVlaGgoAAzZ85EXV2dbpvt27fjnHPOQV5eHgYMGIAf/vCH6Orq8vKj9Cjuv/9+SJKEG264QX2NzrN77Nq1C5dffjnKysqQm5uLCRMmYPny5er7sizjjjvuwMCBA5Gbm4vp06dj06ZNun0cPHgQl112GYqKilBSUoKrrroKhw8f9vqj+Jbu7m785Cc/wfDhw5Gbm4sjjzwSd999t67/B51n+7z77rs477zzUFVVBUmS8Pzzz+ved+ucfvLJJzj55JORk5OD6upq/PKXv3TnA8h9gKefflqORCLyX/7yF3nt2rXyt7/9bbmkpESuq6vL9tB6DDNmzJDnzZsnr1mzRl65cqV89tlny0OGDJEPHz6sbvPd735Xrq6ulhcsWCAvX75cPuGEE+QTTzxRfb+rq0seP368PH36dPnjjz+WX375Zbl///7yrbfemo2P5HuWLl0qDxs2TJ44caJ8/fXXq6/TeXaHgwcPykOHDpVnzZolL1myRN68ebP82muvyZ999pm6zf333y8XFxfLzz//vLxq1Sr5y1/+sjx8+HC5tbVV3eZLX/qSPGnSJHnx4sXye++9J48YMUK+9NJLs/GRfMm9994rl5WVyS+99JK8ZcsWef78+XJBQYH88MMPq9vQebbPyy+/LN9+++3yf/7zHxmA/Nxzz+ned+OcNjQ0yBUVFfJll10mr1mzRv7nP/8p5+bmyn/4wx/SHn+fMD6OP/54efbs2erv3d3dclVVlXzfffdlcVQ9m71798oA5IULF8qyLMv19fVyOByW58+fr26zfv16GYC8aNEiWZaVmyUQCMi1tbXqNo8++qhcVFQkt7e3e/sBfE5TU5M8cuRI+Y033pBPPfVU1fig8+wet9xyi3zSSSeZvh+LxeTKykr5V7/6lfpafX29HI1G5X/+85+yLMvyunXrZADysmXL1G1eeeUVWZIkedeuXZkbfA/inHPOkb/5zW/qXrvwwgvlyy67TJZlOs9uIBofbp3TRx55RC4tLdU9N2655RZ51KhRaY+514ddOjo6sGLFCkyfPl19LRAIYPr06Vi0aFEWR9azaWhoAAD069cPALBixQp0dnbqzvPo0aMxZMgQ9TwvWrQIEyZMQEVFhbrNjBkz0NjYiLVr13o4ev8ze/ZsnHPOObrzCdB5dpMXX3wRxx57LC666CIMGDAARx99NP70pz+p72/ZsgW1tbW6c11cXIwpU6boznVJSQmOPfZYdZvp06cjEAhgyZIl3n0YH3PiiSdiwYIF2LhxIwBg1apVeP/993HWWWcBoPOcCdw6p4sWLcIpp5yCSCSibjNjxgxs2LABhw4dSmuMvmss5zb79+9Hd3e37kEMABUVFfj000+zNKqeTSwWww033ICpU6di/PjxAIDa2lpEIhGUlJTotq2oqEBtba26jdH3wN4jFJ5++ml89NFHWLZsWcJ7dJ7dY/PmzXj00UcxZ84c3HbbbVi2bBmuu+46RCIRXHnlleq5MjqX/LkeMGCA7v1QKIR+/frRuY7zox/9CI2NjRg9ejSCwSC6u7tx77334rLLLgMAOs8ZwK1zWltbi+HDhyfsg71XWlrqeIy93vgg3Gf27NlYs2YN3n///WwPpdexY8cOXH/99XjjjTeQk5OT7eH0amKxGI499lj8/Oc/BwAcffTRWLNmDR577DFceeWVWR5d7+HZZ5/Fk08+iaeeegrjxo3DypUrccMNN6CqqorOcx+m14dd+vfvj2AwmJANUFdXh8rKyiyNqudyzTXX4KWXXsLbb7+NwYMHq69XVlaio6MD9fX1uu3581xZWWn4PbD3CCWssnfvXhxzzDEIhUIIhUJYuHAhfvvb3yIUCqGiooLOs0sMHDgQY8eO1b02ZswYbN++HYB2rqyeHZWVldi7d6/u/a6uLhw8eJDOdZwf/vCH+NGPfoRLLrkEEyZMwNe//nXceOONuO+++wDQec4Ebp3TTD5Ler3xEYlEMHnyZCxYsEB9LRaLYcGCBaipqcniyHoWsizjmmuuwXPPPYe33norwRU3efJkhMNh3XnesGEDtm/frp7nmpoarF69WnfBv/HGGygqKkqYBPoqZ5xxBlavXo2VK1eq/4499lhcdtll6s90nt1h6tSpCeniGzduxNChQwEAw4cPR2Vlpe5cNzY2YsmSJbpzXV9fjxUrVqjbvPXWW4jFYpgyZYoHn8L/tLS0IBDQTzXBYBCxWAwAnedM4NY5rampwbvvvovOzk51mzfeeAOjRo1KK+QCoO+k2kajUfmJJ56Q161bJ1999dVySUmJLhuAsOZ73/ueXFxcLL/zzjvynj171H8tLS3qNt/97nflIUOGyG+99Za8fPlyuaamRq6pqVHfZymgZ555prxy5Ur51VdflcvLyykFNAl8toss03l2i6VLl8qhUEi+99575U2bNslPPvmknJeXJ//jH/9Qt7n//vvlkpIS+YUXXpA/+eQT+fzzzzdMVzz66KPlJUuWyO+//748cuTIPp0CKnLllVfKgwYNUlNt//Of/8j9+/eXb775ZnUbOs/2aWpqkj/++GP5448/lgHIDzzwgPzxxx/L27Ztk2XZnXNaX18vV1RUyF//+tflNWvWyE8//bScl5dHqbZ2+N3vficPGTJEjkQi8vHHHy8vXrw420PqUQAw/Ddv3jx1m9bWVvn73/++XFpaKufl5clf+cpX5D179uj2s3XrVvmss86Sc3Nz5f79+8s/+MEP5M7OTo8/Tc9CND7oPLvHf//7X3n8+PFyNBqVR48eLf/xj3/UvR+LxeSf/OQnckVFhRyNRuUzzjhD3rBhg26bAwcOyJdeeqlcUFAgFxUVyd/4xjfkpqYmLz+Gr2lsbJSvv/56eciQIXJOTo58xBFHyLfffrsufZPOs33efvttw2fylVdeKcuye+d01apV8kknnSRHo1F50KBB8v333+/K+CVZ5srMEQRBEARBZJher/kgCIIgCMJfkPFBEARBEISnkPFBEARBEISnkPFBEARBEISnkPFBEARBEISnkPFBEARBEISnkPFBEARBEISnkPFBEARBEISnkPFBEIRnnHbaabjhhhuyPQyCILIMGR8EQRAEQXgKlVcnCMITZs2ahb/+9a+617Zs2YJhw4ZlZ0AEQWQNMj4IgvCEhoYGnHXWWRg/fjzuuusuAEB5eTmCwWCWR0YQhNeEsj0AgiD6BsXFxYhEIsjLy0NlZWW2h0MQRBYhzQdBEARBEJ5CxgdBEARBEJ5CxgdBEJ4RiUTQ3d2d7WEQBJFlyPggCMIzhg0bhiVLlmDr1q3Yv38/YrFYtodEEEQWIOODIAjPuOmmmxAMBjF27FiUl5dj+/bt2R4SQRBZgFJtCYIgCILwFPJ8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKWR8EARBEAThKf8PA8sHyb+qGnoAAAAASUVORK5CYII=", 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", 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", + "image/png": 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", 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", + "image/png": 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", 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", 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", 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", 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" ] @@ -706,12 +947,14 @@ } ], "source": [ + "plt.close()\n", "esc_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", "esc_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", "esc_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", "esc_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", "esc_ep.plot(x='t', y = ['act'], title='action'),\n", - "esc_ep.plot(x='t', y = ['rew'], title = f'reward = {sum(esc_ep.rew):.3f}')" + "esc_ep.plot(x='t', y = ['rew'], title = f'reward = {sum(esc_ep.rew):.3f}')\n", + "plt.show()" ] }, { @@ -724,23 +967,13 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 45, "id": "9b18da14-869e-41d7-94aa-a1b737652d12", "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 60, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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HqjrdiEuf/ML3t+7gRXB5zKo6E4it2Vdmc0m0C9qHsu1UQULFuSt2lSJnVwme+PEgpCYnxb5QesgRdwgh+qFDnfMiuublsf9uxX83HvZrmpKVlDUvN910E7p06YJbbrnF7qLoJjLYl+xBm0zaXFRhdxHiXlCzkS2lsMbpRg9OnentGOo6NHnBerz5bSEWrDkY24IZoG5SNXrzlyX+EX2OJar2h+gRo/+78TAA+CXqytosLGXw8sADD2DhwoV2F8MgWX4yJLugnBdJqrnJma6cvRyX/2kZyqrrIy53rKI5Xy2/qBx/WbpLypuTm34Koh9CVa1GMekNdLJW3PAfIkkZvIwbNw4dO3a0uxi247ge7uamC7RTyZZHZMaJM7Uu6wtOarph3pi9Bn//aj9eWr7X4pLpJ1VXadPEnmPq79UYg+DllMCxy0QSHrysXLkS119/Pfr06YOEhAQsXrw4aJns7Gz0798fbdu2xahRo7Bu3TrRxbBNLJqNTjd68Nj7W/DplmPiNhaHth2pwD0L87C3JDZDxgceT2murSY5OQBwcNGF2VNSbXcRgvh1lbaxHED436ldNaXqzcZiotEmScd6ER681NTUYMiQIcjOzg75/qJFi5CVlYWZM2di48aNGDJkCCZMmIDSUndk+QsNXsK8PmfZHizKK0Lm2xvFbSwO3fzKN/hiRwnu/Ke54Nnw8OURzpVv9pU5ZgZkJzd32X1jNCtnZwlueHk19qgCcOcejdCMfx9r94TW097KAFlPwq6iKHgpZ6/uh15Zf9/CextNnDgREydODPv+nDlzMGXKFEyePBkAMG/ePHz66aeYP38+pk2bpnt79fX1qK9vbeOtrKzUX2iBRI7zEu6k/2DjEWHbiGcNZwYULDY5Zk0CjF4mw3/q/15fi9/98EKDJSKtnFxrBAC/eqN5XJqZH233vaa/C77IEokh5+3Sn9Yyit696nuMnq7SeYdO4fllewAA112mfUJHWY9FTHNeGhoasGHDBmRkZLQWIDERGRkZyM3NNbTOWbNmIS0tzfdf3759RRXXkFAXjgff3YR7/71BWARbWdcoZD0khtYbYLRZpAPPjoW5h4wXKoacHgC4gfoQ6H2AkvHoqX8bRq+bVlcYaC2X6J+Hf7OR9i95Ikoit5btySSmwUtZWRk8Hg/S09P9Xk9PT0dxcevEaBkZGbj11luxZMkSnHPOOREDm+nTp6OiosL3X1FRkWXl1yLwONfUN2Fx/lEs3V6MoxX6nvCZsOsMRo9StGtCaZWxiw1p5+RfmPrm2bdLe9Xrzr92qAMwWW+e2mterDsWjbqalg12OZf0AEg5SN2XX36pednU1FSkpqZaWBp9Ao+zV1H/CI2PSqYoCvaVVmNA97NMlI6sYDznRc6Lgl5Ovk06udKosq51tOazu7Tz/dsVZ5WIEXbNryLy+iXIedHTVdrwdcrYxywX0+Cle/fuSEpKQklJid/rJSUl6NWrl6l1Z2dnIzs7Gx6PvWMWRKqy1Vu9rl560foiTPtgK34wKN318yc5TYKJrBc3cNI3D77hODd6Uec7tG3TWomuNyiWMYBzwjml9TosPOdF3VVaR7OR4RpiSQ9GTJuNUlJSMGzYMOTk5Phe83q9yMnJwejRo02tOzMzEzt27MD69fLMgtno8WLxJjHJta+uOgCgdYZSkojLnmjiiYw3bhlsOVyOn2SvwbqCk7Zs3z/nxfw6rKC95sW6k0xPwq7hkYoljV6E17xUV1dj3759vr8LCgqQn5+Prl27ol+/fsjKysKkSZMwfPhwjBw5EnPnzkVNTY2v95HjqY7zqysP4LnPWyet03vqJPhn4bX+U85zKW6JeqIRdVxLKk+j21kpSE6KzbOJk+7/DFa0ueO1taiqb8LP/pGLg7O190wRxS/nxXBfPndeKP16G8Wi5sXg56wmPHjJy8vD+PHjfX9nZWUBACZNmoQFCxbgtttuw/HjxzFjxgwUFxdj6NChWLp0aVASr1OpD/TXe8xNJ64+2ZQw/w5UdLIWfTq3c8TEWm6h9YYYNB2ABWXZVHgKN/39Gww/twvev+8KC7bgbIEBoht/JfpT64L3QpVq9nM7yPSAFq7mQYacFz0Ju1aMR2Un4cHLuHHjolYzTZ06FVOnThW6XWlyXiJ8d70nj1/Fi4Yz6NMtx5D59kb8YFA6XrtruL6NkWFGexNYUR27aH1zb7u8Q6eEr9uN3FgT47YaB2mbjbTmvFjZVTomCbtynk9Szm1khCw5L+rDHHiumOky51fzEuZXybwYe7jxBhgvnN6lOBRF0XdOynj+aq1pdgLR55h6f+ireTH6kGXoY5ZzTfAiC6vmNvJqWbGsZxmFxMNljterYMZH2/DuukLD65Dxxm2WG84rEbWS8iTsWlcGXV2lDW5D1vOJwYtgfjUvAWeL7mYj1ekm6wlEZhLhAnJgHHqQzVycK2obsTD3oKHRP7/eexwLcw9h2gdbDW/fhbGL7poKGQM4ESPsWs226QFU+0NXwq7RmhdJ675cE7xkZ2dj0KBBGDFihK3l8J8N1f9k0d/bSL1e1b8NlIus47bqWL3MfI/7392EGR9tx68X5un+LKfJCE3Wm71RRr+N1Tdd22aV9vs3a14cT5acl1iQ9WSKV1ovClZ1jXaylh55mwrLdX9WxPgZbpyXyQ2nlYhxXqymuebFwnNMz75x2wi7rgleZBGp2chM/aHbnqZcxX33P13suv/H+W4PT2fCroxE1JpIk/Ni4Xb1fEWZekWKwOBFNKEJu6qcF3GrJcFE5byQPiJu0E6/yYsgY48r//ulvb+TsPduu5JeDE5a6bZxXhi8CKa+IQUl7Oo8i9VLa+ltJOk55nqicl54/PQRcdN1Y/CiOyiWcB/4Dw1hWzEismtuIyNlMFMOWR+yXBO8yJOw2/rvoIRdU4PUmSgUWcptbclOwUGkQ3PKtWLNvjLc9+YGlFadDnpPpq7S4X7fds1tZDgfyGU1LzGdVdpKmZmZyMzMRGVlJdLS0mwrh1UHWstqeS23h9b9HnQNk/Si4BRCmo1c+KvR3VXaklJEd8frawE0XzPn3Tks7HJ2/0zCXdNtazUyUAbATM6LoY9ZzjU1L7KI3Gykj95xXiQ9x1xP65NVcDOR/wtOvY3a1/Sif8NB+9ypOz0CWW824RyrqAt6TUSzkSxdpYVPD+BfCM2fc1sNMYMXwcxeOPzGifE72WQ9hWIrv6gcP8leg/UHT9pdFB+3jZ/gFGJqXtxH1hyFcEKV1gm/De01LxY2G+n4nN9Evzp2MHsbke62T/+TTWxZnOr2V3Oxuagct87LtbsoPqKeaHiI9RFxS3DlOC8K4KSwLPS1TdWjxuAvQ5qu0hYeCn29jYyN2C7rdYnBi2CRDrSWczjcSaVpbqM4cLpR+0RkspP1icYpEl0YeIigf3oA+fajMwaps2mEXdUO0XNf8OsAYnB7MnFN8CJlbyMDF4Vwg9zJefpQM6NzhpAZbDYKQ9KbTTihggAR30DUXgi7Hrt6G6n/rafmxe9zepqNtG8jllwTvMgzPYAqZyXgHS3nsP9JpTNhV9KTzO0kfHCNC0L2O4+dlLvAGTUv2kjT28hozYuOZWPJNcGLLET+0PzHeZH1FCLNcxsF/s1DaioAETJInek1yEd/s5ElxdAs1O9AEZLzIuYHFm732JXzYnzGbYM5L5Jepxi8CBau2QfQdrE1OxI1xZ6wLohxeJBN5a0ImR7AfeGLotgfkJglU81L+GuyTTkvBrfrX/Oio9lI0gsTgxfBIkbCmpqNwiwu5/lDMFEDYPdVWRAzNSBm7rEiEnYdfo8PSVEUR51aIWteBJTf6l3guN5GBj8n67nE4EWw0Bkrej6vHueFEzM6gdsGf4olmyteXMlp55XTytvCrnFe1BvWNbeR0TnYDH3KegxeJKZ3YkayBwepM85UrQ1nlQ5Jb7ORjLvAL+fF6Ai7lo/zYs8Iu/5l0L6s8ZoXOS9UrgleXNNVOsx5om16ADlPMrcz/kTD42XmzikmYVfGW7c5TjurQt0cxdwvrd0TmpuNRG83zL+jlsNozoukJ5RrghdZukqbbTZSM3qykZwCL9LBcx1Zv03ZmMt5af231u8ZuJg7a170HXPZk5btvvaZ/glJMqu03rnyfMtKeu9xTfAiC7M3C/+am9Cvk1wM57zE4JjKft6Yuq7z9+FaInobSTM9gJVl0JXzov6cjm1I+tti8GIhIxdmv4RddaQsokBkCZkfXGNx3tg1Vov6s1pzwmQ+VnaRcZfI9LQf7pzRWkbxs0qLyAdisxEFEHqg/TKsBK6XpBCLQyp9s5GZwEfA9BmyN5kYoShyBiThROsqbfTYijrzzeQhAhbkvBj8YhxhlyJSTGa9cGJG59FaexA8wi6PqZmxWkTMuu6km7xWMtVaaBFtbiNZfyeau0pbGCDr2Tfq35qiY35bWe89DF4EC5ezovnzqn+z4sUZNB/nKAfRiou07OeNqYTdRHWzKhN2W+g+jSTcB+rfguGaF1m6Soverl8ZtH/OcAcQSS8iDF4ko/5B+A1SJ2n0S3KP8yL9aSNokDoRVeluIfshDyT9ORqG9poXwds1GNixtxFFFHZ4fwP01rw49SLgdFqrhQMvArG4KMh64WlhqrORgN5GrhznRe5DronR2gW/dVi8I7TnvFjZbKR9WfY2kpQ0g9SZvFmE+7SsJxDpmFU6cFwX1ryYzAfQ32wUD/TuC7sDuFCl9T9vbR7nxex0udbNDqCvq7T6c3p6G2leMrZcE7xIM0id2ZwXk58nG2g8TtEGpZP1ImElYb2N2Gzko3dfyLkPzP8arP49yfBgwJoXEsb0cfZrdpLyqkIBjObrxiKPKRYXHkHjzOnm13vChu3LTM6AJLRo0wPYPUhduOuw5pwXMcUIueFYJDPLWqvJ4EU0gcGHky5A8Uxzzkvg9ABWFCZwm5JeeFqYaTYyWg0eUADD248Hsdg9IZuNorwfS+F+Q5pzXiwcpM5ohKbnuuC1+wCEweBFML8Rck2OsKv7s5KeZG4nqKe0JWQ/J0Ql7Bq9wLoxdNE9t5HB96wk4ry1OnDXPMKulQm7sfigpBcRBi+CmT3OInsrUWxoDVKDzo1YJOxavwlThE0tIPsXjSGR95qYjEAcorx+3YElPba21byIaFKzaNlYYvBiIbOD1DF6cQbtT1aRm42suEjLPj6QqWYjAbOuu7HVSOQRt63mRf3vWNyhLWRp8GLwS+rKeZFkPwZi8CKY2ePsN0gdoxdXCe4qHYtxXmJAUN6Kmc1yeoBWzXMbaf9mkQ6fbTkvApJSrSbDOC9Gm0v1BD2yPgAxeBFMZPDhxqdCN9LcbBTlbyvE5LpjYiOimo0M9zZy4Y9M5DgvTn6AsryrtG2zSqv+HYOeWHKGLgxehDNd8yKkFCQjOwapk/2EMnNz9E/Y1fZFA5dy7q05PMtmtrdIyK7SqiMl6YO/beXynx7AaG8j7djbKE74ndAmB6kjZ4j76QEE5a2Y+Sx/N60cFruELm+M8zqsZGntnuGaFzYbUQCTsYv043JQMFHTA1hx7CW97viIuqxr77Ya8Lcbq14Esmv/yHTahvsNac95EUvEGDiyXxe0YPAimhvOCtLFcM4Lu0qLeyrV+EWDm41cGL0EDoYY5USLmLAbg/0TqniKgDu0NOO8WFnx4pJRuo1wTfAiz8SMrQxdmE2cKJKeY66nfZyX2B8hWat8RTP8Ld0YuwT+beIUsK/mRZ3XISfbal5EjPOiK2FXziPgmuBFlokZzZLzNKFIZH56l/18EnVz1JqwG7R9MZuXiqLo26+Ra16sF+rmKGSEXYtPfq2rF5/zYj6w09dV2uBGLOaa4EUWZkfIlfVEofCMjrDrlipfUZMrmsGpjVoFJ4ZHE6GrtE07SEh3YCElibB+CS7W7CpNwpid24icR/v4upFvKpaMsBuTHk3GxTjlJS6IDJJjUvMSMufFfHdgq2mueRG9XRE9sXQsa7RW02oMXgQzPbeRpD9U2UgVGGqeVTry3/FIWG8jw81GMp1IYgQFxaGWsSthQyMhNS8W/8Dsm1VafxmC1qGrq7SxbViNwYtgdjYbyVCNGSsy3XKMliUmgarkzUaimiXYbNRKy76QKXZx7mXLrroX8xy7y1UYvAhm9qRww0kVC04c1t2OmhfZzydxNS8Gt++800gT9dcK2SyjXjbi3Eb2V70YT0q1lhyzShtsNtKT8yJpdMngRTC/uY3cemWUgEx7Nt7nNjJ1mgvLeWGzUQslYG+E7s1j/xglkfhPDyDnzdO2nBch3cjZbESCyfpDlY1McaH2EXYDBw8LeF9McQLWKXePpljXvMTFz0tDDZ9MDR4h5zYScZys7iptU82LkTKY+ZysPxkGL4Kxq3RsyPTErH1uo+iviCb7+SQs58Xw9oVsXioKol97tF6nbOsqLaDZyGqaa68EX6tE9DbSM9kiexvFIxdeGKUh0b7VXJQo1wArvlIsLjumJlcUVAbZm0FiScu+0Dqkg10TMyrRFtC0Xot7G2lcTsqaFzYbUSCzPxhZTxTZyHQP0p7zErnZyAqyN0OKGqRO65Nk4O5wY16alsRwGZo8IpH9vAUk6SptdB1sNqJA/tWx7rswykKme47W4xyLHJdo25SNuONoNGHXfYITw43nlMQiuIuWk2N4IDarc160TswovNlIncxsdB1WLRw7DF4EM99VWs4TRTZSBYaGZ5VWIr5P2kl6fbWFpnFe1M1GkaYHEFEgHWXxvaaE/rdUpMh6NhjY6Wk2MrQF6zF4Ecy/q7SRzwssjIvJVfOiDWtegjFhVzwFit9+dWKzkVpMaheMrF/jclbuwpj0NpL0GiJl8PLJJ5/goosuwsCBA/H666/bXRxdzNe8kBYSXFN9pM55icEZJcEwL8YHqRO0fZlFTYiNIBY1nKGPnfnzVtSZHy7/xq6mt1jXSsnaGpBsdwECNTU1ISsrCytWrEBaWhqGDRuGm266Cd26dbO7aNqY7CpN2siUaGk458Uls0qb2YSow2i0O6dM55EoWs4zrTXE9iXsqv5tTxGikuGmHot8ID3dqmNJupqXdevW4Tvf+Q7OPvtsdOjQARMnTsQXX3xhd7E0Ux9nY81Gkp4pkpHpliP1CLsx2IYZwmaVZs2LLn7XqQjLydBV2vgQ+GLO/nABrl3zQ/mPPmx+HVGXlfQiIjx4WblyJa6//nr06dMHCQkJWLx4cdAy2dnZ6N+/P9q2bYtRo0Zh3bp1vveOHj2Ks88+2/f32WefjSNHjoguprT0nidxG+w48a4TLenFgkMZi/PDXLORqJwXozUvQjYvFS2J4DL1NgpFpsta2GYjjZ+3cm4jo7Ui+rpKS3QwVIQHLzU1NRgyZAiys7NDvr9o0SJkZWVh5syZ2LhxI4YMGYIJEyagtLRUdFFs4Vcda+DCrPdH64isfAvIdM9hzYtxdte8uFFwr7YQy0i0w0J3lVbVLhhdr8HPaV6/5hF2LSyD4d5GVi0cO8KDl4kTJ+Lpp5/GTTfdFPL9OXPmYMqUKZg8eTIGDRqEefPmoX379pg/fz4AoE+fPn41LUeOHEGfPn3Cbq++vh6VlZV+/9lJ0uPsOjLlKhjNeYkFie5RIdl/HO3evnhBxzxKb6NIxyA2h8eZXaW117xYl7BrePRhHTtV0t0f25yXhoYGbNiwARkZGa0FSExERkYGcnNzAQAjR47Etm3bcOTIEVRXV+Ozzz7DhAkTwq5z1qxZSEtL8/3Xt29fy79HJP4XBUNrsHBpsoLmmpegiRlZ9yLqsm48YVdQASSi5WncriYPrUSctZb/vGzKeTFQBFOfk6mWTi2mwUtZWRk8Hg/S09P9Xk9PT0dxcTEAIDk5Gc8//zzGjx+PoUOH4uGHH47Y02j69OmoqKjw/VdUVGTpd4hG65whYT8v6DyR9YQTxYk3HVuajSQ/DexuNnLgaRRVcGpV5N5GkdjVVVoRUb1gMc1NNlZOD2A4mdmaZWNJuq7SAHDDDTfghhtu0LRsamoqUlNTLS6RdmYPtLGE3eBfh1cBktx4ZT5Dpq+meVbpoC6sAX9bcJGOxXXHTLW4sHFeIr0X4UboxCA4Gk05LxrXJcP+MX5NFXP2h1uL9t5GFk4PYHwtmpdkV2kA3bt3R1JSEkpKSvxeLykpQa9evWJZFMv4n9AxeGrx+7e6C52kZ5wg9udKtNI8wm7Q39YfI9lPA2Ej7Mr+RW1kqreR0JKEFq0osh5ZGUYpjskIu5IegZgGLykpKRg2bBhycnJ8r3m9XuTk5GD06NGm1p2dnY1BgwZhxIgRZotpK2HNRmJWIy15QhfjFyfeb2NV8xJp+zKdSWLondsoUuDn5K7Sbp0eQESDmr6cF4MbsZjwZqPq6mrs27fP93dBQQHy8/PRtWtX9OvXD1lZWZg0aRKGDx+OkSNHYu7cuaipqcHkyZNNbTczMxOZmZmorKxEWlqa2a8hhKGcF70Ju+oEYdXPRNYTThSJKl50zG0UkLArvijB25Q8jBWX8xL+e0baAzKdR+Ioft8r9Ai76qXDi0nNS6jyCRmITYxw29ecN2Rh9BKLnBdZCQ9e8vLyMH78eN/fWVlZAIBJkyZhwYIFuO2223D8+HHMmDEDxcXFGDp0KJYuXRqUxOtUZquvdY/z4jceQuu/jfa+cA557jqGn06j5MCIIPtpIGyQOs3f0397bgxeFCV6cKJ5f8Vg/0Qrn90BeLjta9+F1u1EwzUverpKS3oRER68jBs3LuqXnTp1KqZOnSp0u9nZ2cjOzobH4xG6Xr3U39zIKSvpeSIdmW46xmeVZs6LqOu64YRdiYJgUaIlhgPaazbs2juOaDayKefF77oRg1opWS8h0s1tZFRmZiZ27NiB9evX21oO8+O8GN+eltfdIpYX1ewV+7Aw96Dp9djxBGn3U2s0ds8q7cLYRds4LxprNmKR8xKtN5Td17Lw27en2UhErZS+iRnlvIZI2VXayczeLETdbGS/aZkVq5qXopO1eO7z3QCAO793bsiLufZB6iL/bQVJrzs+iTHobST5LhBO0zgvGtdlX82L+e7A4q6lZlnYbGS45kVPs5GxbVjNNTUvsgiXQGvk86LK4UYiq/sj3T8rTzf6/h1+vAON47xE+dup9CQsewN2orCE3YjbDf+eCyteoCAgmAtVs6EODiLtn5jUHhsPrmJBttptIbVSOj4n07FQY/AiWKwPdLiTV9aqPlFiVfPi9ar+HWafGq95sb73kUynwX1vbsT3n/8Kpxtb89JEHUfj0wOYL4CiKFh/8CTKaxtMr8sK0RNiw7MtJ8gBPWo0115ZOc6L0WYjPctKdA1Rc03wIss4LzHPeQmTeCfp+SZMrC6pHtVO9YSpetE+SJ31wUq0bdpp6fZiHDxRi9z9J3yvCbs5RviaEXM6BGx6ydZi3DovFxlzVgpYm3mKEv3c0jrxYWyuYaFek+e8Dbc37RroT+ux07oODUsb24jFXBO8yJKwq2ZnbyNZo2VRYjV4ljpgCbdPmfMS2gcbD+PfURKdY9FsZPX2P9/ePC9bWXW9+ZUJoECJeoOTKziITNpxXmxI2N12pAK//3CrqgzG6KmplPVewoRd4WKbsBv2xJL0hJNRpB+nusraE2ZBmbvb2nkaZP1nMwDgmkvS0adzO0u3FfkYWrpp+WhJ2FX8lwgnJg8JIXNyrN+sVmZzXkReH+6av85QGQKpP9bQ5MWcZXtw9YU9Qi8r0bFQc03Niyz8m42sT9gNtzhzXsRQ17yYz3mJ/TGRYYCp6vqmsO8Jm9vIYJgmb9hpnILwzcnqZSK938KuuY38yme4O7C1574dOS8nawLzqszvm5eX78W8r/fj5699G3LZ9zYU4X+bjxrajpVcE7xIk/Ni69Zb2V2O8tqGiDcts0ReECKtS13bEthTRm9Zol1LrbjYxuI8MHMsRB1GozPfyjTBpyhaziPbhrbXSERehyhhR9jVug9FFiaoDAY/p/r3B5uORFzWqwC/fWdT2Jw/u7gmeJEl58X09AAmtqeEeT3WauqbMPSPyzB45ueWbcNIVeyfl+5C9op90RdU8e9tZK4sdhyRUKfBovWFWHvgRPAbUZysaUDGnK9178NIYjK3kc01C7GmIHryvuaaF9u6Sov9tXy8+SiWbjtm6LNmL6VWBsiGi6b64PEqbblaMtTiqrkmeJGF2cMr6gSx8zTbf7y6tRwWnfB6rweHT9Xila/247nPd6PJ443+gTO09DbSege057cfvNHH/rsVt70auoo4kr+v2Id9pdW+QftEEDZIndEPujB6CextFH1ixvB7T9Tx0Utkj5qK2kbc/84m3PvmRr9u+prXE2X9ZiiKghW7SnHoRI2m5RMDDke462vOzhL8J68o7LVOfcxTkrSFAbLVUjJhVzCzXaV117z4bTt6z5hYqG9q/cF4FSDJgnNe7yobPf6Jt1pPfPWPP9yFwmhX6Vgwch4UnqjForxCTL5yALp3SPW93mRBtbGwUyNSwm6U/A+3CfyKob+ztn0SeHz2H69G2zZJOFtgAnb0nBfVv88UVs+NtF41393pRg/atknSV8Aw1OfVsYo6tE9JRlq7NkHLRSpqflE5Ji9obi04OPu6qNtMSEjwO2Ch9l2jx4tfvZEHoLn5/p6rzg8uu+qDyVZcoGOANS+CqW9wgc0J+0qrUVHbGPiRgM9HXmek5e1uNtpxtBJvfHPQ7+nGqnZSvU8BSarlvREqXrxeBfe/swkvL98LIDjoMcOOG6eWTQaeKzf+fQ2yV+zHw2d6C1lJXFdpowm7zrxwRxPtXNP8s1QdoPLaBlzz/Ne4cvZy4wXTKmRtkYLbXv0Wd7y+Vltez5lzQl2z0KCj1jVCUfxeL6uux+hZyzHkqS9CLhfpHDt8qs73by21QoFrClW2JtU162j56ZDrUX+ujcaaF9mw5iWGfvrKN0hOTMC+Z6/V9bllO0rCvne8qh6fbT2GxflHUHii1ve62ftkQVkNjpyqw5iB3TV/5toXVzX//9JevtfC9dDZU1KFWUt24qEfXIjLzumsu3x6bzmJqt9nYBCiXlfugRP4+Exm/dTvD0Sjx78WKWRZotyB311XiBW7SzGge4eIy1kR20S7xjd5vPjxS6txbrf2+MedwwG09mjYcOgUvF4FiYF11UKJWXekgDRSbahkNeFCaEvYVf07wnLq3aO+0YoUvTdU81/FlaexruAkAKCqvgmd2gbXcoSiPn/VDyOayxdhkLonP96OBd8cjPj5SOdYj46tNZt7SqqiXgubm/FUnQhC7Dz1a41hm41aMXixWXZ2NrKzs+Hx6G/TFEl9UoQ6aaNXvQe/Hyl4yZjzdei1mLwTjv/rVwCA/00dg0vPSdP12U2F5b5/hwtefvH6WpRW1WPV3jLdwRwA3fe8ZFX0Eqk2KPDpp0l1Vwzb2yjKtqd90DyoVMe2+pNkzWpoivykmV9Ujl3FVdhVXIU5y/Zg3EWtYz1U1zdhyFNfYMpV5+H+awZaUr6YzG2k/nfAgi6MXc5838jNQlqb0mI9Snjo95upf35aihXqezVG+T1ELECIl6MFLkDksqrf05Q4q+GLq6+54a516gC3DZuN7CVLbyOzj8+hfnDtUvS30YrKr9h2tEL3Z7TUVpSe+aEazaMwVfOiY5vqJzWz47xUnbau63g4z32+K+L76lqjF3P24ua/f+P3flV9E+Ys22NJ2QB9x/HNbw8hZ2foQF59MS6rrsfKPcc11UC4sebl0y3HkF8U+XerNWHXvlml1X80/0/98BCppi2ScDURRhjpbm60V1yL4ITd4GXU+6bl+rr/eLXfQ2W4nCIncU3Niyz8al5Mfr5FOwMJZnZ2yVc/7cuY86KnTOr2Y7NzG9lBnXAbitEWIfUxNpM3ovUwbj9agT8s3gYgdGKj+shc/9JqHKs4jRduG4KbLj8n4g3DrTkvO49V+v4dfYTd8GLRw0Rrnp/64aFJQ/QSar2Gcl50vh5xXUr4c17LwKKB52uoYxuq5uWa5/1r6NWbajLQlCYD19S8yMKKRFkj2fF29slv0NBDxyy9l1T1RVjP6MNGc14qTzfi/Q2HUXk6coK21aJ9U6NdYaf9d4uhzwXSGjwUV4ROPGyhPqTHziy7eJN8o4LaIVqzUaSTxLaaF9W/65s8+MvSXX4Tehp9KDKU8xI2Y1fb59XXh0gf8SoKDpbVRLxmhqp5eX3VAfxVNXxBYM5L6PXpCwRlxJoXwaLlvADNSZKNHiVkc1Co88xY8KL7I8Kon8pPN3rx9tpCjB3YHX27the2DTMPhPqajdTBi/aal/vf2YSvdh/HD7ana96WkWP27rpCfL69GNl3fBftU4J/ztGCR6PBS7RRObXSuvloxyzU92xJPI6YkOrOihc/+rPsWtk2q7TqxQXfHMT+4/7joGhpbg61xEOL8vHhb65A5/YppsrX/LrGZiON23n+iz3YW1qNzPHn45EJF4deV8ABURTg6U93AgB+Nrwv+nVr79choaHJGzJgY80LBfHv2RD6tP3BCysx5I9foK4hOLk41EW4XRtnHSb1deWl5Xvx+w+3hk0sNspMdX/gjTBS1bj6IqkOXvKLyjH9gy04UV0f8ur01e7jACInW4sw7YOtWLH7OP615mDI96PWvNh8amkNnqIGLyFe8wUvghJSX191AO/lFWn/gAto+Z1tP1qBZz7dgYo6cbWM6kNWeLI26H2jNS8FZTWYtSR8Hljz73priDmEgml+2NCY87K3tHlwz+wV+8OvKuBwqGtNWmq81Zto9HhR3xTiPuO3DmcGL6x5EUxLNF5Q1vwUseNYJYad2yXg88FE1bzUN3lwvKoe53TxrwHZf7wa9yzMw9TvX4CbLj9H97YieWtt4Zlte5F38CT+sHgbrr4o9OylsaKn2Ug9SJ36gnlj9hoAQEVdI9q1sf9nFC4ZONpXtWsEVR+tNS9Rvkiot0/VRr8BaS3AwbIa3xPurcP7avqM2rGKOqS1axOydsxq0WrfIr1fXd+EhiYvUpLDR7nXvbgaAFBZ14Q/33KZgQJGLlNKUiIaPYG9ADXUvIT5XkWngoOhFi2/69qGJvzt9svPrCfM+qOWoJk6ADQbJgSerQ2qWpOWXkPq61uDx+s3aKivHH41L85sNnLWI30EskzMqBbtsqg1ETfJQFblNXO+Qn5Rud9rf/pkB8b+ZQW+DKgNmPbfLdh/vAYPLbJ2ULJb5uViV3EV/vH1AdPrMnPP1fOkob44hLqI7SutlrrpwaqcFz8xmJgxes1L8Pu1LTWbAmpeTtRom/8llMITtRg9aznG/HmF4XWYYabZaMexSt+wCdHsKqnSWqSA7UcuYZsQgZPHRJ6Gluup3xQnYZbRnvSs/zPhBI65tFl1jU8+M16L+qfS2KSEHC5B8ct5cWbNi2uCF1m6Sus5OVNDNAdtPRzcxdHICd/oUXDnP9f6vfbmt4VQFODXC/P8Xq8N0XzlZuHGawklXM2LWsRxHGwObKLnvIjYiPGPau3NEq22zOocr/pG4zfLr/aUAoCmpggrRNs3eQdPRXz/SLm2wenaCBzMUF3m1BDBi9GcFwBIVpVzzb4yPPr+ZlQFJNb71ZaE2YFGcl7MDmERaQ+37H/19a1eS80LgxcCAn4wUX7LgT+KvSVVeGbJzqDl9DRzqFXXh25K6HqWf7Kancm9Rm/uZrpw6hnm3xMm58W/LOE/L/tcOiKLd6K6HuWammpaaa95ifx+pN9IpAHZQm3/s63Bsw+HugFopX7yjdZryg5Hyut8I9eaYaSGGIjeGypUk1VgkqnXq2D+6gJsPaJ6+AtzSiSpEr3ueH0t/pN3GC8t958pXcvlxZaalwgFa7km+jUbNUXOeVEUxbLhLKzG4EU0dcJulEtz4AV5U0AzTwv1uXV+j7MMFqxVz47+Y3/YeeomG7zgmXnGM/pjNRpE2ilSkRVFwQ9fWGl+IwnNiYHXzPkaQ/+4LOhiGak3g9YYVE9tWSC9CbstuS1qRmYjbqHu7fG9WTnYV2qsecU4JWTnADV1N2SjrBpmPtR6A3/D7284jD9+sgM/feWboGUDhSrmsYCgUkv3ZiM5L2Zp+b34NRt5vCFrDVsenJ1a6wIweBGu5YmhvsmDeV+HzxoHgLfWHgLQfGH8cNPhsNXK6qcQo083sjL6fcw0xxhtLg87zovEA51FCrhOm2gKCVRb70H5mUlHA5shrn1xVdgne801LwabjRqavLghe3Xr9gLnNtJYAjM1L4Gjun6+3doeaIEUBZg0f13EZURcVozOTqw+dDX1TWjyeP2OZ0qIaCPwputX4+Jbr4KCshrc8NJqv9eTQ3SxC9yG3zcxmfQisuYlcs9IL/76+W58e6A1EG1o8kYcmM+ptS4AexsJ13Jy/jv3UNRlF+Yewu+vvQR/XrorbFdXwPrRctXNVzf/fQ2euelSU+vQI9SFRItIwcunW48Bb23ESz+/POSkgkZnhw71Q69v8uJ4tfFkTqvFrLJItZvzi8px5QX+E3puLAydV6G1+S/aE2K4IO2b/WUoOtmasxHUbKTxfhuq6l0rkUPSG6EAWHcwcrOQiMk3jdaitjhRXY9hT3+JgT074KfDWns9hsp5CfwthhtoLes/+Th4wr93UagHpsCmKfUiYSdmDPlqsEg5Lx9sDB4vKdJ+jLSHr39pNcqq/R+Aw9e8tL7vVKx5Eazl1Aw3FXkgr6Jg6bbiyOuMYXPFxsJy3P2v1qe06R9s9W3/nXWFYT9nNMAyXPMS5Yn5063Hwl6wjfZUCHWDPHSiFst3lRpaHwB8ssXaUWBFzXGlR6hmotmfhR5bQ+vRj9ZsFO4nImp4e1M5LzbfICo1jL8ioteZ0QeRluvL6n1lAJrHO/GredEQvIQbiC3U2DOhgoOUgFojLeeN9nFe1Mm/rS/vKq7EohDjBkW6JkYqVmDgAkTKeWkuiJNrXhi8CKY30EhMSIh64TDT3q9FYJEDfwR7Spq7DT4bIheghdEhptUXkqKTtX5dFCPRcq0N91Rh9F7S8hVrG8JPsKj3+E99exOKQgzCJYrsaTpag4toF9lwNS/RagO03rLD9TZSFAUfb44cgNo9gqmW2Yo3h8m300NEs1Hra5ETdoNqXsL8qEOdFlpqXvxqS8IcPs0TM6o/o/r3sTAPuJHOWb1BZrRxXoxMlyALBi82S0iIXvtg9ekV+HQeeCMINU5AIKMRvLq6euxfVuCa579GRW30J0UtP+GkMD90swm797+TH3YZI8GCVV1o95VWxaTexcwzu+aE3Sg7Ntz70S72WoOncM1GK3ZHr3Wzu2peyzmwdHsxDp2oib7gGaESmM02G6mpH9hCHcPAh6XGEL9pBaF/66GCrOBmo9C1JYHr10LrrNItIta8aNxmi7A1L2eK4dR5jQAXBS+yDFJn5GYRLXixPucl8t9aGM1aD3VxOXRSw0VUw00n3I0p8EanN2n0y53hEy6N7AWremlkzFmJMg1P3WaZOT1FDVIX7m2jtQFq/1pTgL9+sSfke7uK/XsObTlcHrSM7cFLwL7ZcawSv1qQF7RcSw2rFhc/sRTbj/onySZpaDY63egJuoGHut6oryeh3tda8xIqqG253qrXkZLkP2CoR1GwYlcpKuoaw+e8WHRdTo5wPdDbDNoQJuelZb/YXStohmuCFycOUtci2gOLnTNEa+Ux+CMIVatTUx89OVLLTzjcfjVa86LlOCiKoruZLyVZ2wVp1d7j+MPirbq67R4o0/40HWs19U14b8NhTctGS7IOV/MS+GDQciNqOZZa7gVP/W9H2PcCN3vDy2tQWuXfHNDQFLnsS7cV490I+WSirSs4ieJK8+PNvJiz1+/v/248jOwV+8Is3Txq7cVPLMXv3os+I7n6NxQqeAh8WAr1m1aUMM1GZw66+ncUWPOy4dApTF6wHncFDPRphDo/r67Bg0fe2xw0yrlf+QzmvISiKJEHIWVX6Tj3rzUFpj4fvebF4pwXAesw2oPnkt4dg15rySl5Z10hnl2yM2TQoOVHHG6/Gu9tFH0ZBfqPl9aal3vf3Ig3vy3UNb1CW0GTeh4trwsbvBmt25j1mX8OlXr9NfVN+MGcr/Hkx9sBRM/7ClvzEhi8KMCHmw5jxDM5yC8qN93NPdRNMzCHKVrNy71vbsC0D7ai8IQ1uU+xTNp+7vPdYd97bWXzefvfjdED1mg3VY9XwbGKOl+NS7jcjVDHp6WGqE4VvLRJSgh5fm8+XCGge3Prv19esQ/vbTgcNMq5msicF8D/ewYyM82C3Ri8mLC7uAqvrzoQ8clMi6gJu5Y3G5nfgMis9ZaRgad/sBWvrjyADYdOBS2j5SccrorVaC2RlqBEUfQfL709rvZpTGoGjE3qGcoVs5fjDQ3d//X4Zp//wGj/XF3gexp+Z10h9pZWY8E3BwFEv5mFO4dD7duHFm1GWXU97ntzg4FS+9Ny3mttNjIzf1IkslTc6imH+gEj1OdW7yvD6FnLfUFAqNwNBUrI32xLU2JgDeazIUY3b16POeozUMtIxiJrXgBEHKCQCbtxasLclSFH49QrWru81RcfEas3Wv0Y6mOB1ZyVp4MTeLW0/a7aezzk60ZrXrQ0B4W7YEaitx27Nsy0D6EY7b5qpb1nRpgNHNX06U934u9fNQ/sqB47p7y2IeqAj+GOTXCzUSuPVzE995SWY601eFmx+7gl+TGy3J701ADtL21t7gy1i98+M1v9V7ubf+PhukqHOi1azgl18OJVFLy2KnQNup6fc6ipJdSdEtQ9OcMlgce25kX7l1MUBRsOnQqaB8ou8l3Z4lC4XjEtLB+WXsDqjdZmhPrx1Gi4OWv5Cc/9cm/Ibs1er2KotknL79zrtT7YDDdnVWjW37rWFpzESwH5D5E8u2QXvtpdGvKiuuFQ85PpSdVF/uH/bI46GrBXaX5y/sPirX6vh2o2Uot2Hq3eWxbxfS0X/waNv40Xc/bi+TCJwW6g3vfRzhd1UryWoEdPwm6yL3hRT7oadROa3PfWxqDX1AGH+noUbp4rkb2NgMjBix4fbz6Kn77yDW7+e/QpGGKBI+xKINzolre/+i32PD3REQm7Rrvchbq4aJnlWusDSF2DB+1T/E9zj6L4XUi1rqu8LnqX5gaPV2iX0VBC7Z/6Jg++2VcWNCBarPLxXl+tL+/rla8i16ScUHUf19Id+XSTB6+uDM4FilarFe3Y3xulaSnS/p3zxW5sKirXlWA97+v96N4hBb8ee57mz0Qjy/VDXYrnl4kN0kIm7CJybyO1yA+Ixvefoih+PdDUv93Dp0LP1h2pttRITeFpDddTLZacqVXaW6q92dpKDF4kEKnmZdXe44ZvQIoCVGvouSMkYVfgZIc1EQaBa2Em0dLjNZbC+PiH23DHqHMjLtPo8SIhwdoKzVC1Sf9aczDkFBOy3Li02nakEl9sL/YLXrQIV/MXeJYEHnmzI/BGuum9uDx8z5tInv50p9DgxSqfby9BgY7ebEZPRS2fC5vfFmqclxDBS32EAFNvuWvqm7Bq73GMHdgDS7cV47MwI6iHCwIi57yIbTbSo0OqXOGCXKWJQ8t2lISNwIEzN1oT95+yEPPuHCmvQ35ROYb27QxAzA3O+Dgvwa9paTYKvCu9+a32ZFKPwWYjLRo9XrSxOM9ES81UC2eFLs3Dud/z7w1oo3N8Frt6fDpheHURp/rC3IPo0j4l6PXxf/1KezkMno2hPpWUmODb94qihD5flNDXzlA13ZECTb2l/u07m7B8VykyLkmPmB+ytyT07OKRciCNVOqKCl46tm0jZD2iMOfFZlPf3hRxzAWvIj7npep0E27MXuMbit/OmpdQQUS4odjV1L/hQydq8IfF2zRvM7CsIndvY5P+hF29NAV3Zzis4sVHby8IzftcZ85LNFYFLz+au9LUZJCizfhoO377ziZzKxG4q9S1E6cbvWGbWiLlvFilZa6zL3eWRDwvQ81FBETLeTFQ8yKo2ahjW7nqOhi8SE5RrKsl2HZmGnkRqxc5wq4W6trTUxqmE1ALGmFX4LWsweO1PHjRVfPi1OhFJ63fM2gpk8feqv27q7gKq/ZEThbWyo7JOUMxXIoQH1Qftqr6RoSKXRREHudF8+ZNHGMj18WIs0obyXkR1WykCl5kuK4weJFcc9KZNetuGRra7MVNURQ8+v5mQ5/VcqMvrQxu+jKX8+L/t9CaF4/X+nF5LFrWyYzuc9OD1Fl4EQ81IaEREtxnAES+4S1YUxB21vpQ1yf1ZIObCsuxJmDMoNZtBr+mt+bFzO4z8nCWlJiAJo8XS7YeCxqt2c6cF3WzUY2g2hwzGLwYFKvI06solj05ibrw5h44oWteFDUtv+1pH2zFG2cGK2thprYk8Hu3/FVQVoPMt4O7OurR6PHqPjf0VuvquvZKcuOymtbarsBjY7bWzcppi9qniBlgUJrgJcJ7T/5vB749EH0At1D+379D9whTwjS56x0U0sz+MxK8JCcmYv6aAvzmrY2Y8MJKNDR5sf1oBRRFsbWrdKoqmK4+rWe4Bmu4JniJ9cSMscrTa855sWbdrQlv5tajZS6icLTedGaeGSa+hZmbTuCAZi03tA83Ho46nkg0jR6v7qAwY87XuuZD0vP0Jcl9y3Jad1/gYmZbDPXOY6VHO0HBi1ZTFuZh57FKIetavbcM97+zCadUvcas7G0UTqjfotU5L37bN1jzkrOzOW/mVG0jfvXGelz34mp8tft4yOaxaOoaxETY6r1WXW//QHWuCV5iPTFjrGpeFMW6BNAmk8FLS86MGYZzXkzcdgLboVv+0tKtPJqGJsVQsBk4Pkskeq69MrRNx4LlAzlatN1IvVH0zDa+NkKthZ4S3vnPdTqWDu8X/1yLjzcfxTOqIfeN7inDnwvX20hkklsUInJeVp0ZKHHJ1mMGE3bF15LYPFE6ABcFL7EWq5qXcDOjiuAxeQb++KXVqKlvwoebtM0MHIrR7ya25sX8Ols0erwoq9I/R42e/aDn4hsfoYv2GpCgEXbNNhsZPIFr6pswf3UBLn3yC3MFOCNnV/iB/H73nvZ8tFBDK+iVtSjf9+/Ck+YnmxQegMcudjFUMxeuWWtAj7Ns7SotG7n6PjlItCeu4srwY7fo3Y5VT88tvVHNrP+x/27Bkq2hB2HSVAYbxsmwMsly9b6ykCO9RqMnr6m2wYMlW4/h2kt7R19vnEQvxpuNTA5SZ/D8/b/XvsXmw9pqLhVFMT2YXix9sOmI79/qYftjXQsoamtmatcM1byEGeeloclrKNp2wFBEhrDmxQJHyutM3dDVHnl/S9gJw8wSMR36J1uCJyLTVQaDFwZZL+ZGAhdAf5DxmxBzqIRiV3NKrBn9nuZrXox9TmvgcqyiDiOfzcEcwcPpx0rLzXvNvjLD1wrjzUYGPxigocn4ddJYzkvo23JDk9dQzYtbMXgxKNLFcu2B0N32jLCyZsKX82LZFqJzUk5Gl/ZtLDseVu0F5+xd7Y6WB9dqah7nJbC3kcmyWJmwW3iiFs8t3Y3jVfV4UcfElzJpGY7hjtfXGl6H3ZcIMzN9G5nzrXuH4JGMgebghbFLKwYvBtn1gyo6KaY5CmidD8bOi4PxhN1msQx+kpMSDU9AGY1l38OF0csVs5djY+Epv9eMNhuZZWXN1q8X5qGkKvzo205g1e9FC1FHRu9oz2pG4p5wc901eLwxTTaWHYMXg+yqjheZfNXSZGPnCJyGBxdLaB6XZdSzOZivc0ZjM5wWY8gyumqgtQXGxvRo8f4G/yRxw79HkzcDI8H3c5/v1rzswTLzCa92qqwz39PF7jPYXLORuOCtockrdDRwp2PCrkFuSIISNc6LGUar3b/afRxr9n2NRo+CjzcfFVyq8CwLXhy2Xru9vbYQPxiU7vtb82kU2NvIZDmsfoipjNCV2gmKK0/j0AntM0+HZHAfi6rNNPMAYHTalFDqm7zS5vrZgTUvRrngpiDyh2WUmYu/mepcoyy7WTlrtVKY/K/WMZ00d5UWvEes7i1XrWMSTlFeXi42v+btMMP+xwOROVHMefHH4MWgbwvEJeXaxSNBwq6V3Zat4LTmHSclRJthJKgsrarH30wmwlo+j1XA+rcdqcDhU9Y2Jf31C7E9m8x2R3fyGSy65oU5L63YbKSDoih4fPE29O7UFs87tOuiWpMECbsSVP7oYlXNi8MqdKSjOWFX8A6JZe7b4VO1+PFLqwEAB2dfF7PtmmX2fmt0Fz/96c7oC1lMZM1cg4c5L2oMXnTYfrQSb691TxVo6wB4NibsOix6cVqQEScVLzq6Spvf1tHyOjz4bj5+OaZ/TAdZ3Gtw8lO7mR2bRNakcy1E1iw3NHl0TyrpZgxedKhvctcwy2+tPYSP8o/gVK34pMCeHVNRqmGYfMc1G1lW8+Ks/SCbWNaAzPhoG9YdPIl1B09i1ICuMduuU5ltNnIykadlQ5MXZ6Xylt2COS9xrNGjWBK4AEDn9m00Ldc8d5P1N56H/5MvZD1Oq3mJF9rHeTG/p9W/Gcac0dnVbOQ2eiZvjQcMXsh2sah5X7H7uJD1OC3nJV5oPS6i97PTag7tYLbeJd528bGK06gJMRN0fSMTdtWkDF5uuukmdOnSBbfccovdRaEYsGNyRqOsKqqT2/VlYNegkXadux6vgtoGhzRjS3bD/dMnO3D9S6ttq8m4oGeHiO9/uvUYth2pDHqdCbv+pAxeHnjgASxcuNDuYhAFsSzIYOxiitaBTJ00PUAkN7/yDcb+ZYUt29bLdM2LkFK0qjrdhK1HKrB0m5jJc/Xq1amtoc95vAprXlSkDF7GjRuHjh072l0MoiDMeZGTXc1GdgUvm4vKbdmuEWZvuFblxDXZMMglYK4iiqFLK93By8qVK3H99dejT58+SEhIwOLFi4OWyc7ORv/+/dG2bVuMGjUK69atE1FWIttxGH852dXyyBxK0stMMMfpAVrpDl5qamowZMgQZGdnh3x/0aJFyMrKwsyZM7Fx40YMGTIEEyZMQGlpqW+ZoUOHYvDgwUH/HT0auzlqrPTkx9vtLgJZxLKEXda9mKL96VzsfnbaOEV2sHNmaRmZqnnR8dn+3dob35AD6O40PnHiREycODHs+3PmzMGUKVMwefJkAMC8efPw6aefYv78+Zg2bRoAID8/31hpQ6ivr0d9fet4IpWVwYlOsVZ5OvbzkbjJvuPVOFXTYHcxQpJpMLnc/c6fokIU9jaSl9k5yNy2i83UvOgZo25A97Nw8ISzZyWPRGjOS0NDAzZs2ICMjIzWDSQmIiMjA7m5uSI35TNr1iykpaX5/uvbt68l26HY2VRYjsv/tMzuYoQk05P2z1/71u4iSMOuwyLT+SCrJpNta26rlTTT8KNnwD+3J/cKDV7Kysrg8XiQnp7u93p6ejqKi7VndmdkZODWW2/FkiVLcM4550QMfKZPn46Kigrff0VFRYbLTxSNVU+Bf166y5oVxwnNNS82bTeeNTIxyI+ZvJVEHXdst+fHSDnW8Jdffql52dTUVKSmplpYGqJWVj0FfpTvjnwvu2hvNhJ7/NxcLS9KI2un/JjrbaT9wy6PXcTWvHTv3h1JSUkoKSnxe72kpAS9evUSuakg2dnZGDRoEEaMGGHpduLR05/uQFl19HmK4gGvw3JiTqi8zDYbuY2ZuRX1BCRun8NRaPCSkpKCYcOGIScnx/ea1+tFTk4ORo8eLXJTQTIzM7Fjxw6sX7/e0u3Eo7UFJzHtv1vsLoYUOIGinOxqNqLozCbsuo2ZiSr1NAW5PedFd7NRdXU19u3b5/u7oKAA+fn56Nq1K/r164esrCxMmjQJw4cPx8iRIzF37lzU1NT4eh+RM4UarjrWxv/1K7uLwJoXSWmNKRl7xh5zXvzpyVsJpCcccXnsoj94ycvLw/jx431/Z2VlAQAmTZqEBQsW4LbbbsPx48cxY8YMFBcXY+jQoVi6dGlQEi85S5IEdZAFZTV2FwF8dpcTE2flZddItrIyU/Oi5zLMhN0A48aNi1p1PnXqVEydOtVwoYzIzs5GdnY2PB6HTFbmMGaeFtyENS9yiodmo/c3Hra7CIaw5sWfuUHq2GzUwjW3JOa8WCuZ0QsANjvISmtQ6eScpU+3HLO7CIawt5E/MzUiTNhtJWVXaZKP238IWrF5Qk5ODkrcjsfGn6neRnq6Skd4b2NhOZKTEjCwp3MnQGbwQprIkPMiAwYvcuIw/eQUZq6kei7DkZqN3llXiHfWFeL/RvUzURp7uaYtwOpxXl75aj9++oo1Uxw4gdvbT7XiPTK6U7UN+PUbeTHdptZxXnj8yG7mZpXWs2z0hd9eW2i4LHZzTc1LZmYmMjMzUVlZibS0NLuL4zrJSQxeAN78tFjwzcGYb5M1YuQYJi6legIft1eWu6bmhayVxJoXAO6bJM4tNI/zwuNHNotdzYvhzTgCgxfSJNHiMH713jJL1y8KO07ISfvcRhYXhCgKU7NKs6u0D4MX0sTqmpdf/HOtpesXhT0n5NTEqNJyndu3sbsIrmCq5kXPsgxenIETM1qLvY2a8R4pp7IqbROHMvYku5mJKZjz0so1wQsHqbMWg5dmrHmRU1V9k6blTjdxBG6yV6wGqXN5xYt7gpd4d1G6tYMNMXhpxtDF2TYVlttdBAphUO9OdhchZkxND6BjWea8EIHBSwsv242IhIun64uZr6qn4wSDFyKwq3QLhi5E4sVR7GJqVukOqdqHZnP7JZvBC2lidVdpp+BgaETiub1njJq5uY30LOvufeqa4IW9jazFmpczGLsQ6bKnpCrqMvH0bBSrQM3t+9Q1wQt7G1kridMDAGBXaSK9Siqjd2N3e36Gmoiv2qltMq66sEfEZdxeW+6a4IWsxZqXZhxenki8uApeBDTn3HT52WjXJvLt2+17lMELaRJPvQEiYc0LkXhxFLsIa86Jln7n9jwiBi+kSTw9GUXChF0i8eLp+hKrr+r2500GL6RJstt/CVoxdiESLjGO7kSxCtTcHhDG0SlDZrg9+Usr1rwQief2G62aqOacaFcit+9S1wQv7CptrSTXnCnmMHYhEs/t+Rlqsfqqbt+nrrklsau0tdjbqBlrXojEi6eK3Vh9V7fvU9cEL2StpHhqlI6AoQuReHHVbBSjTsxu36e8I5EmbDZqprDmhUg4t9cSqMXqu7p9l/KWRJowYbcZYxci8dyen+EnVr2NXH7NZvBCmrCrdDMOUkckXjxdXmI3SJ2Y7ciKwQtpwoTdZkzYJRLPjvyMusammG8TYM6LKAxeSBO3V0FqxdCFSDw7brTvrCuK+TYB5ryIwuCFNGHNSzMm7BKJF0+XF3HfNfK1iDUvDsFB6qyVlOTuH0IohSdqg15j7EIknttvtGqxSk52+y51TfDCQeqsFU8XlxZXPbci6DXmvBCJF0+t0rGbmNHdO9U1wQtZy8qfwZxleyxcu1iMXYjEc/uNVi1W39Xtu5TBC9lu3tf77S6CZqx5IRIvnsZ5idU3dXtAyOCFSAfGLkTixVOzkaigItq1yO37lMGLQf27tbe7CGQDhZ2liYRzey2BWsy+qsv3KYMXIh04wi6RePE076uoJrK7rugf8X3WvBCRD5uNiMRjzot+V1/YA2umfT/s+26vzWLwQqQDE3aJxHN7LYGayO96dud2MdmOjBi8EOnA0IVIPLfXEqjFbJA6l08QwOCFSAdOD0AkXjwFLzGrEXH5LmXwQqQDYxci8eIodonZl3X7LmXwQqQDc16IxIunmpf4+abWck3wwokZKRbYVZpIPLcnl6rFUZxmKdcEL5yYkWKBOS9E4sVTV2kSwzXBC1EsMHYhEo+xC+nF4IVIB04PQCRePOW8kBgMXoh0YM4LkXjxlPNCYjB4IdKBzUZE4sVDzcvAnh2w7KGr7C6GazB4IdKBXaWJxIuHhN2hfTtjYHpHu4vhGgxeiIjIVmw2Ir0YvBARka3iodmIxGLwQkREtmLNC+nF4IWIiGwVDzkvJBaDFyIishWbjUgvBi9ERGQrNhuRXgxeiIjIVqx5Ib0YvBARka0Yu5Be0gUvRUVFGDduHAYNGoTLLrsM7733nt1FIiIiC7HmhfRKtrsAgZKTkzF37lwMHToUxcXFGDZsGK699lqcddZZdheNiIgswJwX0ku64KV3797o3bs3AKBXr17o3r07Tp48yeDFZusPnkJVfZPdxSAiF0pk9EI66W42WrlyJa6//nr06dMHCQkJWLx4cdAy2dnZ6N+/P9q2bYtRo0Zh3bp1hgq3YcMGeDwe9O3b19DnSZwvd5bYXQQicimO80J66Q5eampqMGTIEGRnZ4d8f9GiRcjKysLMmTOxceNGDBkyBBMmTEBpaalvmaFDh2Lw4MFB/x09etS3zMmTJ3HXXXfh1VdfNfC1iIjIKVjxQnrpbjaaOHEiJk6cGPb9OXPmYMqUKZg8eTIAYN68efj0008xf/58TJs2DQCQn58fcRv19fW48cYbMW3aNFxxxRVRl62vr/f9XVlZqfGbEBGRDJiwS3oJ7W3U0NCADRs2ICMjo3UDiYnIyMhAbm6upnUoioK7774b3//+93HnnXdGXX7WrFlIS0vz/ccmJiIiZ2HNC+klNHgpKyuDx+NBenq63+vp6ekoLi7WtI41a9Zg0aJFWLx4MYYOHYqhQ4di69atYZefPn06KioqfP8VFRWZ+g5ERBRbzHkhvaTrbTRmzBh4vV7Ny6empiI1NdXCEhFZr9tZKThR02B3MYhs0bZNkt1FIIcRWvPSvXt3JCUloaTEv2dKSUkJevXqJXJTRK6S1r6N3UUgss2F6R3sLgI5jNDgJSUlBcOGDUNOTo7vNa/Xi5ycHIwePVrkpoJkZ2dj0KBBGDFihKXbISIisXp0YO056aO72ai6uhr79u3z/V1QUID8/Hx07doV/fr1Q1ZWFiZNmoThw4dj5MiRmDt3Lmpqany9j6ySmZmJzMxMVFZWIi0tzdJtERGRGAN7dmDOC+mmO3jJy8vD+PHjfX9nZWUBACZNmoQFCxbgtttuw/HjxzFjxgwUFxdj6NChWLp0aVASLxER0S/HDLC7CORAuoOXcePGQVGUiMtMnToVU6dONVwoI7Kzs5GdnQ2PxxPT7RIREVFsSTertFGZmZnYsWMH1q9fb3dRiIiIyEKuCV6IiIgoPjB4ISIiIkdh8EJERESO4prgheO8EBERxQfXBC9M2CUiIooPrgleiIiIKD4weCEiIiJHcU3wwpwXIiKi+OCa4IU5L0RERPHBNcELERERxQcGL0REROQoDF6IiIjIURi8EBERkaO4JnhhbyMiIqL44Jrghb2NiIiI4oNrghciIiKKDwxeiIiIyFEYvBAREZGjMHghIiIiR2HwQkRERI7imuCFXaWJiIjig2uCF3aVJiIiig+uCV6IiIgoPjB4ISIiIkdh8EJERESOwuCFiIiIHIXBCxERETkKgxciIiJyFAYvRERE5CiuCV44SB0REVF8cE3wwkHqiIiI4oNrghciIiKKDwxeiIiIyFEYvBAREZGjMHghIiIiR2HwQkRERI7C4IWIiIgchcELEREROQqDFyIiInIUBi9ERETkKAxeiIiIyFEYvBAREZGjuCZ44cSMRERE8cE1wQsnZiQiIooPrgleiIiIKD4weCEiIiJHYfBCREREjsLghYiIiByFwQsRERE5CoMXIiIichQGL0REROQoDF6IiIjIURi8EBERkaMweCEiIiJHSba7AHZQFAVNTU3weDyaP9M20YOzOyb5/u7ZPhGNDUkRPhFbPdoloLqjXOWpsbg8XgU4VefFaY9i6XaIiEgucRe8NDQ04NixY6itrdX1ue90bMST43v6/k5OTECTt6Po4hnWJikBjZ6z7C6GT3N5Oli8FQVVpz14Ja8ce082WrwtIiKSRVwFL16vFwUFBUhKSkKfPn2QkpKChIQETZ89UVOP1Kp6398pSYlo8HitKqpuKclJaGjSXpNktZiUR1HQtbYS9w0Hfp9TxhoYIqI4EVfBS0NDA7xeL/r27Yv27dvr+mybRiAhufXmmJiciIQEeYKXpDZJSIA8wUusypPcvhM6tq1El3aJOFYtz/cnIiLrSJewW15ejuHDh2Po0KEYPHgwXnvtNeHbSEyU7muTUQkJABKQqK0CjYiIXEC6mpeOHTti5cqVaN++PWpqajB48GDcfPPN6Natm91FIyIiIglIVwWRlJTka9Kpr6+HoihQFOYyxNKRokIM6dsFu7ZvtbsoREREQXQHLytXrsT111+PPn36ICEhAYsXLw5aJjs7G/3790fbtm0xatQorFu3Ttc2ysvLMWTIEJxzzjl45JFH0L17d73FJCIiIpfSHbzU1NRgyJAhyM7ODvn+okWLkJWVhZkzZ2Ljxo0YMmQIJkyYgNLSUt8yLfksgf8dPXoUANC5c2ds3rwZBQUFePvtt1FSUmLw65FMGhsa7C4CERG5gO7gZeLEiXj66adx0003hXx/zpw5mDJlCiZPnoxBgwZh3rx5aN++PebPn+9bJj8/H9u2bQv6r0+fPn7rSk9Px5AhQ7Bq1aqw5amvr0dlZaXff270q1t/jNkzHsMLz8zA2MED8P3vXoRX5sz2vV9ZUY4nH7kf44ZcgCsu6Ydf33YDdu9obvapqqzA5ed2w/bNmwA0dxkfO3gAfnHDD3yf/+SDRfjhyO/4bbNg3x7cdeMPMeKCXrj5mtHIy13j935e7hr834+vwfDz03HNsIsxd9aTaGpq8ivzs394BH95cjquvux83PuLn2J97moM6dsFa1d/jZ9fOx6jBvbBXTf+EAf37/V9bveOrfjVz67H6Iv74opL+uH2a8f5yk5ERCQ056WhoQEbNmxARkZG6wYSE5GRkYHc3FxN6ygpKUFVVRUAoKKiAitXrsRFF10UdvlZs2YhLS3N91/fvn11lVlRFNQ2NEX9r67Bg9ON4v4zksfzv/ffQbv2Z+HN/32Jh37/FP4x9y/IXbkCAPDAlEk4WXYc2QvfwztLVuCSwUNwz+03ouLUKXTslIaLvnMp8nJXAwD27tqOhIQE7Nq+BbU11QCADd9+g2Hfu9Jvey88MwN33TMViz77GkOGjcT9v/w5yk+dBACUHDuKzEk/w+Ahl+O9z1fh8Weex+J338RrL/41oMzvok2bNnjjw6V4YtYc3+sv/eVpPPzE03j70+VISkrGzN9N9b03/bf3IL13H7z9SQ7eWbICv/zNg0huI11uORER2UToHaGsrAwejwfp6el+r6enp2PXrl2a1nHo0CHcc889vkTd3/72t7j00kvDLj99+nRkZWX5/q6srNQVwNQ1ejBoxuealxflP//ve2jbRt/w+QMv/g7ufegxAMC5A87HOwtew9o1XyO1bVts2bQBKzbtQUpqKgDg4Sf+hBWff4plSz7CLXfcjeHfG4P1367GpHt/i7zcNfje2HE4uH8vNq37FleOz0Be7mrcfd/9ftu7/e4pyLj2BgDA488+jzVffYkP3/03Jt/3AP6z8J/o1edsTH/6OSQkJGDABRfieMkxzJ31FP7fg48CaP5u/Qach4ce/6NvncdLm5sAf/voHzB8dHOw9MvMBzF10m2oP30aqW3bovjoEdx97/0YcMGFvu9KRETUQrrH2ZEjRyI/P1/z8qmpqUg9c8N2uwsv8W/W6dEzHSfLyrBnxzbU1lTjqsv8b/L1p+tQdKgAADD8e1dg8aJ/w+PxIO/bNRh91Xh075mO9d+uxsBLvoPCgwcwfPQYv88P+e4I37+Tk5Mx6LLLcWDvHgDAgX17cNl3R/iNUDx0xCjU1lSj5NgRDOjfHwAw6NKhIb/LQNV36d6zFwDg5Inj6H12X9w55Td46tH78ckHizBqzNX44XU3om//ATr2FBERuZnQ4KV79+5ISkoKSrAtKSlBr169RG4qSHZ2NrKzs3VNtggA7dokYccfJ0Rd7nhVPUoqT/v+Tk1ORH2T8RF2U5P1t9glt2nj93dCQgIUrxe1tTXokd4Lry/6X9BnOqalAQC+O+pK1FRXY+fWzdi49hvc/9gT6N4jHfP/PhcXXTIYPdJ7W1LD0S7MSMbJya3fpSUA8nqbm9Luy5qGiTfeglU5X2D1ii/xypzZ+PPL/8Q1E38svHxEROQ8QnNeUlJSMGzYMOTk5Phe83q9yMnJwejRo0VuKkhmZiZ27NiB9evX6/pcQkIC2qckR/2vXUoS2rYR95/WOZW0uGTwEJSVliApORn9Bpzn91+Xrs2D+3VKS8PAS76Dd994Dclt2mDABRdi2KgrsGv7FqzM+RzDv3dF0Hq3bMrz/bupqQk7t+bjvIHNTTnnXXAhtmxc75e7k79+Lc7q0BHpvc82/Z36n3cB7pzyG/zj7Q9wzY9+jI/+85bpdRIRkTvoDl6qq6uRn5/va9opKChAfn4+CgsLAQBZWVl47bXX8MYbb2Dnzp247777UFNTg8mTJwstOLX63thxGDp8JB769R345uvlOFJUiPy8tXjpz3/y66Uz4ntjsOTD9zBsVHOgktalC8674EJ8/r8Pg5J1AWDRG68j57NPULBvD579w+9QWVGBG2/7BQDgZ3f9CsVHj2DWE4+iYN8erPh8CV6ZMxt3TvmNqekXTtfV4dk/PIL1uatx9HAhNq3/Fts3b8KAM0ETERGR7majvLw8jB8/3vd3S7LspEmTsGDBAtx22204fvw4ZsyYgeLiYgwdOhRLly4NSuIlcRISEvDqW+/jr888hRkPT8Wpk2Xo3qMnvjvqCnTr0cO33LDvXYk3//mKX27L8NFjsHvHNowIyHcBgAemzcT8v8/F7h1b0bf/efjb/Ld9NTnpvfsg+43/YM4zM3DrhLFI69wFN97+C0y5/3emvktSUhIqTp3EHx68FyfKjqNzl264ZuKP8Zus6abWS0RE7qE7eBk3blzUbr5Tp07F1KlTIy4jmtGcF6f453ufBL0295+tTSkdOnTEtD/+GdP++Oew6/j+j67D5qJTfq89+uQsPPrkLL/Xzu7bz7fcxBtvCbu+4aOvxNuf5IR9P1SZR4weE1SGi79zqd9rf87+Z9h1EhERSTe3kVFGc16IiIjIWVwTvBAREVF8YPBCREREjuKa4CU7OxuDBg3CiBEjoi9MREREjuWa4IU5L0RERPHBNcGLHkYmRSS5eXlIiYjiRlwFL23ODK9fW1trc0lIFMXTBI/Xi5oG41M1EBGRs0g3MaOVkpKS0LlzZ5SWlgIA2rdvr3mY/saGeihNDb6/vUoiFI88N0wPkqA0yTPGTUzKoyioqzyFLcWnUdXAqhcionjhmuBF6yB1LRNEtgQwWlWdbkRFXZPv7+TEBDRJ1FbRJikBjZ54K4+CU7VNeHdbFeT55kREZDXXBC+ZmZnIzMxEZWUl0s7MpBxKQkICevfujZ49e6KxsVHz+t9ZV4jXVx3w/X1253Y4Ul5nqswiDeh2FgpO1NhdDJ/+3drj4Alrm+c8XqCs1oMmRi5ERHHFNcGLXklJSUhKStK8/GlvEo5UtdbqtEnx+v1ttw7tFanKc5Zk5SEiIveIq4RdIiIicj4GL0REROQoDF6IiIjIUVyT89LS26ipqblHUGVlpdD119VUwVvfmoDadFqBt16ehN2m04l+5bNb0+kEKcpTVVmJNt5Uv7LUVlehsrLS77XKykqcrq0OKrP6NU+bpqDzQJSm04j5/grcB9JKMD4IYVWV+O/YWJcScZ1VlZWorEx2xr7VwZOYDG99U/QFdWr+PbYPu7/svpY01oXevt5rQX1tNSorK1F75nOepER4dQy30XTai9M1zdejlnUB4a8btdVir1U1qvVVVVWgsr34nhIt30nLQLIJisuGmz18+DD69u1rdzGIiIjIgKKiIpxzzjkRl3Fd8OL1enH06FF07NhR8wB0WlVWVqJv374oKipCp06dhK6bWnE/xwb3c2xwP8cO93VsWLWfFUVBVVUV+vTpg8TEyFktrmk2apGYmBg1YjOrU6dO/GHEAPdzbHA/xwb3c+xwX8eGFfs50jhtakzYJSIiIkdh8EJERESOwuBFh9TUVMycOROpqal2F8XVuJ9jg/s5NrifY4f7OjZk2M+uS9glIiIid2PNCxERETkKgxciIiJyFAYvRERE5CgMXoiIiMhRGLxolJ2djf79+6Nt27YYNWoU1q1bZ3eRHGXWrFkYMWIEOnbsiJ49e+LGG2/E7t27/ZY5ffo0MjMz0a1bN3To0AE//elPUVJS4rdMYWEhrrvuOrRv3x49e/bEI4884pvPioLNnj0bCQkJePDBB32vcT+LceTIEfziF79At27d0K5dO1x66aXIy8vzva8oCmbMmIHevXujXbt2yMjIwN69e/3WcfLkSdxxxx3o1KkTOnfujF/96leorq6O9VeRlsfjwRNPPIEBAwagXbt2OP/88/GnP/3Jb+4b7mdjVq5cieuvvx59+vRBQkICFi9e7Pe+qP26ZcsWjB07Fm3btkXfvn3xl7/8RcwXUCiqd999V0lJSVHmz5+vbN++XZkyZYrSuXNnpaSkxO6iOcaECROUf/3rX8q2bduU/Px85dprr1X69eunVFdX+5a59957lb59+yo5OTlKXl6e8r3vfU+54oorfO83NTUpgwcPVjIyMpRNmzYpS5YsUbp3765Mnz7djq8kvXXr1in9+/dXLrvsMuWBBx7wvc79bN7JkyeVc889V7n77ruVtWvXKgcOHFA+//xzZd++fb5lZs+eraSlpSmLFy9WNm/erNxwww3KgAEDlLq6Ot8yP/rRj5QhQ4Yo3377rbJq1SrlggsuUH7+85/b8ZWk9MwzzyjdunVTPvnkE6WgoEB57733lA4dOih/+9vffMtwPxuzZMkS5fHHH1c++OADBYDy4Ycf+r0vYr9WVFQo6enpyh133KFs27ZNeeedd5R27dop//jHP0yXn8GLBiNHjlQyMzN9f3s8HqVPnz7KrFmzbCyVs5WWlioAlK+//lpRFEUpLy9X2rRpo7z33nu+ZXbu3KkAUHJzcxVFaf6xJSYmKsXFxb5lXnnlFaVTp05KfX19bL+A5KqqqpSBAwcqy5YtU66++mpf8ML9LMZjjz2mjBkzJuz7Xq9X6dWrl/Lcc8/5XisvL1dSU1OVd955R1EURdmxY4cCQFm/fr1vmc8++0xJSEhQjhw5Yl3hHeS6665TfvnLX/q9dvPNNyt33HGHoijcz6IEBi+i9uvf//53pUuXLn7Xjccee0y56KKLTJeZzUZRNDQ0YMOGDcjIyPC9lpiYiIyMDOTm5tpYMmerqKgAAHTt2hUAsGHDBjQ2Nvrt54svvhj9+vXz7efc3FxceumlSE9P9y0zYcIEVFZWYvv27TEsvfwyMzNx3XXX+e1PgPtZlI8//hjDhw/Hrbfeip49e+Lyyy/Ha6+95nu/oKAAxcXFfvs5LS0No0aN8tvPnTt3xvDhw33LZGRkIDExEWvXro3dl5HYFVdcgZycHOzZswcAsHnzZqxevRoTJ04EwP1sFVH7NTc3F1dddRVSUlJ8y0yYMAG7d+/GqVOnTJXRdRMzilZWVgaPx+N3IQeA9PR07Nq1y6ZSOZvX68WDDz6IK6+8EoMHDwYAFBcXIyUlBZ07d/ZbNj09HcXFxb5lQh2Hlveo2bvvvouNGzdi/fr1Qe9xP4tx4MABvPLKK8jKysLvf/97rF+/Hvfffz9SUlIwadIk334KtR/V+7lnz55+7ycnJ6Nr167cz2dMmzYNlZWVuPjii5GUlASPx4NnnnkGd9xxBwBwP1tE1H4tLi7GgAEDgtbR8l6XLl0Ml5HBC8VcZmYmtm3bhtWrV9tdFNcpKirCAw88gGXLlqFt27Z2F8e1vF4vhg8fjmeffRYAcPnll2Pbtm2YN28eJk2aZHPp3OM///kP3nrrLbz99tv4zne+g/z8fDz44IPo06cP93OcY7NRFN27d0dSUlJQb4ySkhL06tXLplI519SpU/HJJ59gxYoVOOecc3yv9+rVCw0NDSgvL/dbXr2fe/XqFfI4tLxHzc1CpaWl+O53v4vk5GQkJyfj66+/xosvvojk5GSkp6dzPwvQu3dvDBo0yO+1Sy65BIWFhQBa91Ok60avXr1QWlrq935TUxNOnjzJ/XzGI488gmnTpuH222/HpZdeijvvvBMPPfQQZs2aBYD72Sqi9quV1xIGL1GkpKRg2LBhyMnJ8b3m9XqRk5OD0aNH21gyZ1EUBVOnTsWHH36I5cuXB1UlDhs2DG3atPHbz7t370ZhYaFvP48ePRpbt271+8EsW7YMnTp1CrqRxKtrrrkGW7duRX5+vu+/4cOH44477vD9m/vZvCuvvDKoq/+ePXtw7rnnAgAGDBiAXr16+e3nyspKrF271m8/l5eXY8OGDb5lli9fDq/Xi1GjRsXgW8ivtrYWiYn+t6mkpCR4vV4A3M9WEbVfR48ejZUrV6KxsdG3zLJly3DRRReZajICwK7SWrz77rtKamqqsmDBAmXHjh3KPffco3Tu3NmvNwZFdt999ylpaWnKV199pRw7dsz3X21trW+Ze++9V+nXr5+yfPlyJS8vTxk9erQyevRo3/stXXh/+MMfKvn5+crSpUuVHj16sAtvFOreRorC/SzCunXrlOTkZOWZZ55R9u7dq7z11ltK+/btlTfffNO3zOzZs5XOnTsrH330kbJlyxblJz/5Sciuppdffrmydu1aZfXq1crAgQPjvguv2qRJk5Szzz7b11X6gw8+ULp37648+uijvmW4n42pqqpSNm3apGzatEkBoMyZM0fZtGmTcujQIUVRxOzX8vJyJT09XbnzzjuVbdu2Ke+++67Svn17dpWOpZdeeknp16+fkpKSoowcOVL59ttv7S6SowAI+d+//vUv3zJ1dXXKb37zG6VLly5K+/btlZtuukk5duyY33oOHjyoTJw4UWnXrp3SvXt35eGHH1YaGxtj/G2cJTB44X4W43//+58yePBgJTU1Vbn44ouVV1991e99r9erPPHEE0p6erqSmpqqXHPNNcru3bv9ljlx4oTy85//XOnQoYPSqVMnZfLkyUpVVVUsv4bUKisrlQceeEDp16+f0rZtW+W8885THn/8cb+ut9zPxqxYsSLkNXnSpEmKoojbr5s3b1bGjBmjpKamKmeffbYye/ZsIeVPUBTVUIVEREREkmPOCxERETkKgxciIiJyFAYvRERE5CgMXoiIiMhRGLwQERGRozB4ISIiIkdh8EJERESOwuCFiIiIHIXBCxE5xrhx4/Dggw/aXQwishmDFyIiInIUTg9ARI5w991344033vB7raCgAP3797enQERkGwYvROQIFRUVmDhxIgYPHow//vGPAIAePXogKSnJ5pIRUawl210AIiIt0tLSkJKSgvbt26NXr152F4eIbMScFyIiInIUBi9ERETkKAxeiMgxUlJS4PF47C4GEdmMwQsROUb//v2xdu1aHDx4EGVlZfB6vXYXiYhswOCFiBzjd7/7HZKSkjBo0CD06NEDhYWFdheJiGzArtJERETkKKx5ISIiIkdh8EJERESOwuCFiIiIHIXBCxERETkKgxciIiJyFAYvRERE5CgMXoiIiMhRGLwQERGRozB4ISIiIkdh8EJERESOwuCFiIiIHIXBCxERETnK/wd2M6VOKhUeoQAAAABJRU5ErkJggg==", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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", 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" ] @@ -800,41 +1033,33 @@ } ], "source": [ + "plt.close()\n", "cr_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", "cr_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", "cr_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", "cr_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", "cr_ep.plot(x='t', y = ['act'], title='action'),\n", - "cr_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(cr_ep.rew):.3f}')" + "cr_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(cr_ep.rew):.3f}')\n", + "plt.show()" ] }, { "cell_type": "markdown", - "id": "1088ac23-94aa-4567-8a1f-6aa15f6e4ecc", + "id": "30981dfd-4bde-4bea-a034-f0d0686cd1e0", "metadata": {}, "source": [ - "## Trivial (no action)" + "## PPO 2" ] }, { "cell_type": "code", - "execution_count": 62, - "id": "0a890b9b-c1c2-405f-a506-f74aa3fc43a9", + "execution_count": 46, + "id": "d2a906e8-c7fa-45e4-9cdc-6b65537896e6", "metadata": {}, "outputs": [ { "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 62, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", 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", 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", 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", 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", 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", 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", 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", + "image/png": 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", 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", 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oLAghhNQ0UlSMGzcOzc3NLM7ogBACfX192Lp1KwBg4sSJRX8WhQUhhJCaJZlMmqJi9OjR1W5OoGlqagIAbN26FePGjSvaLcLgTUIIITWLjKlobm6uckvCgeynUmJRKCwIIYTUPHR/eMOPfqKwIIQQQohvUFgQQgghxDcoLAghhBDiGxQWhPiEEAJ7B5PVbgYhpEYZHBysdhM8QWFBiE8suPslvOe7D2L15p5qN4UQUgPMnj0bF110EebPn48xY8Zgzpw5WLVqFc444wy0tLRg/Pjx+OxnP4vt27cDAO677z50dHQgmUwvcFasWAHDMHDZZZeZn/kf//EfOO+888rabgoLQnzijmXrAQDXL36ryi0hhORCCIG+weGqfAkhCmrrzTffjHg8jieffBJXXXUVTjnlFMycORPPPfccHnzwQWzZsgX/+q//CgA48cQT0dPTgxdeeAEAsHjxYowZMwaLFi0yP2/x4sWYPXu2X13pCAtkEUIIqSv2DiVx8Hcfqsr/fuWHc9Ac9z71Tp8+HT/5yU8AAJdffjlmzpyJK6+80vz7jTfeiM7OTrz++us48MADceSRR2LRokU45phjsGjRInzta1/DD37wA+zZswddXV148803cfLJJ/t+Xiq0WBBCCCEB5eijjzZ/XrlyJR577DG0tLSYXzNmzAAAvPVW2lJ68sknY9GiRRBCYMmSJfjEJz6B97znPXjiiSewePFiTJo0CdOnTy9rm2mxIIQQUlc0NUTxyg/nVO1/F8KIESPMn/fs2YO5c+fixz/+cdZxcm+P2bNn48Ybb8TKlSvR0NCAGTNmYPbs2Vi0aBF27dpVdmsFQGFBiO+wvh8hwcYwjILcEUHhqKOOwl133YUpU6YgFnNuv4yz+NnPfmaKiNmzZ+Oqq67Crl278PWvf73s7aQrhBCfKSw0ixBCvDFv3jzs3LkT55xzDpYtW4a33noLDz30EC644AIzE2TkyJE4/PDDceutt5pBmieddBKef/55vP766xWxWFBYEEIIISFg0qRJePLJJ5FMJnHaaafhsMMOw/z589HR0YFIxJrOTz75ZCSTSVNYjBo1CgcffDAmTJiAgw46qOztDJ8tiJCAQ1cIIcQP1DRRyfTp03H33XfnfN8111yDa665xvbaihUr/GtYHkqyWFx11VUwDAPz58/3qTmEEEIICTNFC4tly5bh17/+NQ4//HA/20MIIYSQEFOUsNizZw/OPfdc/Pa3v8XIkSP9bhMhhBBCQkpRwmLevHk488wzceqpp+Y9dmBgAN3d3bYvQgghhNQmBQdv3nHHHXj++eexbNkyT8cvXLgQP/jBDwpuGCGhhdGbhASOQvfoqFf86KeCLBbr16/HxRdfjFtvvRWNjY2e3rNgwQJ0dXWZX+vXry+qoYQQQkihNDQ0AAD6+vqq3JJwIPtJ9lsxFGSxWL58ObZu3YqjjjrKfC2ZTOLxxx/HL37xCwwMDCAatZcrTSQSSCQSRTeQEEIIKZZoNIqOjg5s3boVANDc3AzDoFlRRwiBvr4+bN26FR0dHVlzeSEUJCw++MEP4qWXXrK9dsEFF2DGjBm49NJLS2oIIYQQUg4mTJgAAKa4IO50dHSY/VUsBQmL1tZWHHroobbXRowYgdGjR2e9Tkg9kUrRf0tIUDEMAxMnTsS4ceMwNDRU7eYEloaGBl8MBKy8SYgPDFNYEBJ4otEoLesVoGRh4VRylJB6I0lhQQghALgJGSG+kGQqGyGEAKCwIMQXkkkKC0IIASgsCPGF4VSq2k0ghJBAQGFBiA+oMRbMECGE1DMUFoT4gJoVwgwRQkg9Q2FBiA/YLBYM5CSE1DEUFoT4gCoshhnISQipYygsCPGBYVosCCEEAIUFIb6QZIwFIYQAoLAgxBdUYcEqnISQeobCghAfoLAghJA0FBaE+IBaIIuuEEJIPUNhQYgPqFqCFgtCSD1DYUGILzArhBBCAAoLQnxBNVLQYEEIqWcoLAjxAdVIIWixIITUMRQWhPiA6v5gjAUhpJ6hsCDEBwRdIYQQAoDCghBfUN0fdIUQQuoZCgtCfECVEnSFEELqGQoLQnxAjbFguikhpJ6hsCDEB+xZIdVrByGEVBsKC0J8gBYLQghJQ2FBiA/YYiwoLAghdQyFBSE+oGaCKPuREUJI3UFhQYgPsPImIYSkobAgxAe4VwghhKShsCDEB1QrBWMsCCH1DIUFIT6QoiuEEEIAUFgQ4hNqumkVm0EIIVWGwoIQH1DFBEt6E0LqGQoLQnzAvrsphQUhpH6hsCDEB1K23U2r2BBCCKkyFBaE+ICqJWixIITUMxQWhPiALd2UMRaEkDqGwoIQH+DupoQQkobCghAf4O6mhBCShsKCEB9QtQQrbxJC6hkKC0J8QM8KYfVNQki9QmFBiA/oMoK6ghBSr1BYEOIDuoWCcRaEkHqFwoIQH9B1BOMsCCH1CoUFIT6gl66griCE1CsUFoT4gABdIYQQAlBYEOILusWCxTcJIfUKhQUhfqBZKFjWmxBSr1BYEOID2emmFBaEkPqEwoIQH0il9BiLKjWEEEKqDIUFIT6g6wi6Qggh9QqFBSE+kJ1uSmFBCKlPKCwI8YHsyptVagghhFQZCgtCfEA3ULCOBSGkXqGwIMQH9AJZjLEghNQrFBaE+ABLehNCSBoKC0J8gK4QQghJQ2FBiA/oQoK7mxJC6hUKC0LKANNNCSH1CoUFIT7AypuEEJKGwoIQH9B1BGMsCCH1CoUFIT6QFWNBkwUhpE6hsCDEB3QDBQ0WhJB6hcKCEB/ILulNZUEIqU8oLAjxgewYi6o0gxBCqg6FBSE+wBgLQghJQ2FBiA9kx1hQWBBC6hMKC0J8QDdQ0GBBCKlXKCwI8QHubkoIIWkoLAjxAbpCCCEkDYUFIT6QnW5apYYQQkiVobAgxAeyYyyoLAgh9UlBwuK6667D4Ycfjra2NrS1tWHWrFl44IEHytU2QkKDriO4bTohpF4pSFjsu+++uOqqq7B8+XI899xzOOWUU/Cxj30ML7/8crnaR0go0C0UpcRYJFMCV/9jNZ56c3upzSKEkIpTkLCYO3cuPvzhD2P69Ok48MADccUVV6ClpQVPP/10udpHSChJpYp/763PvIOfP/omPvO7Z/xrECGEVIhYsW9MJpP405/+hN7eXsyaNcv1uIGBAQwMDJi/d3d3F/svCQksusWilBiLJ2mpIISEmIKDN1966SW0tLQgkUjgwgsvxD333IODDz7Y9fiFCxeivb3d/Ors7CypwYQEEV1HlCIs1u3cW2JrCCGkehQsLA466CCsWLECzzzzDL785S/j/PPPxyuvvOJ6/IIFC9DV1WV+rV+/vqQGExJEsi0WxX/Wlu7+EltDCCHVo2BXSDwexwEHHAAAOProo7Fs2TJce+21+PWvf+14fCKRQCKRKK2VhASc7N1NmRVCCKlPSq5jkUqlbDEUhNQjehZIKSW9I4ZRanMIIaRqFGSxWLBgAc444wxMnjwZPT09uO2227Bo0SI89NBD5WofIaEgu6R38Z8Voa4ghISYgoTF1q1b8bnPfQ6bNm1Ce3s7Dj/8cDz00EP40Ic+VK72ERIK/AzepMWCEBJmChIWN9xwQ7naQTJcv/gt3PvCu7jtC+/DqBHxajeHeMTP4M0oTRaEkBDDvUICxlUPvIbXNvfgd0vernZTSAFkBW+WEmPBp5IQEmI4hAWUUoL/SOXxs0BWlK4QQkiIobAIKA1RXppQkRVjUfxHMcaCEBJmOHsFlHiMlyZM6BaKUnY3jTDGghASYjh7BZRYlJNLmNBlRCm7m9IVQggJMxQWAUIN+IvTFRIqdNdHKcGbqq4oRaAQQkg14OwVIAaGrb22GWMRLnQB4Fe6KYN4CSFhg7NXgNg7lDR/piskXPhZIEsVFsMUFoSQkEFhESD6FWFBC3i4EPAv3dRQfCHczIwQEjYoLAKEarGgCTxcpFLa76W4QhRjFe8DQkjYoLAIEKrFgibwcOGnxUKtY0FhQQgJGxQWAUIVFqVkFZDKkxVjUVJJbwoLQkh4obAIEGpWCC0W4SJrrxCfLl8phbYIIaQaUFgElKTutCeBRs7/0tjgV9AlbwNCSNigsAgSylxEi0XYSF+vWGZr0pJcWbb7gMqCEBIuKCwChDoVMcYiXJgWi8wTVZqusN5MXUEICRsUFgGFFotwIa+W3OfDL1cIYywIIWGDwiJAqHMIswHChSzpLatmlmSx4H1ACAkxFBYBhRaLcCGvViyzx4tvFgveB4SQkEFhESBU3zonlHCRMrNCMhaLEq6f+k7eB4SQsEFhEVA4oYQLyxWS/r00V4gSvMkYC0JIyKCwCBDClmbICSWMmOmmPgkC3geEkLBBYRFQWCArXGSnm9IVQgipTygsAoR9QqlaM0gRyPgYP9JN1bfSFUIICRsUFgGFFotwYVksSk83VaHFghASNigsAoQatEfferiQly4WYVYIIaS+obAIKJxQwoV0hUT8rrzJ+4AQEjIoLAIEV6rhxbRYRH1whSiihCW9CSFhg8IioFBYhAs/9wqxCcwk7wNCSLigsAgSrGMRXjKXK+pDjIUKLRaEkLBBYREgWNI7vKTKtAmZXwKFEEIqBYVFQKGwCBfyavkevEmLBSEkZFBYBAhulx1eZKqwFbxZSowFLVdeEUJg6Vs7sGFXX7WbQgLGcDKFB1dtxraegWo3pe6gsAgowyyQFSp0i0UpgoAC0ztL396Bc377NE748WPY2t1f7eaQAHHz0ndw4S3L8dFfPFHtptQdFBYBghNKeMkqkMXKmxVhx55B8+d3d++tYktI0Hho1WYAwKYuCs5KQ2ERUOhbDxfyasUy+6bTYlEZVJcT+4qQYEBhESDUYXGY9QvChYyxiJTuClGhwMxNimXwCQkcFBYBhauvcGEWyIr4WyCL6aa5UUORKMYJCQYUFgFCsJRzaJGXq8EXVwjN+16xWywY8ExIEKCwCCicUMKFTBGVrhC/zPI07+dG1d+0WBAVAd4P1YLCIkAwxiK8ZG1C5pMg8KvQVq3CGAtCggeFRUChxSJcyPlNxliU4sqyZ4WU0qraJ0m3ESGBg8IiQNgmFK5UQ0XKzApJP1K0WFQGtZsZY0FIMKCwCChcfYWTqA8xFqpvmC6x3KiBruwrQoIBhUWgUAdJrr7ChB5jwToWlUG1DNFiQVT46FQPCosAwYqL4UXPCimpjgW3TfeM3RXCviIkCFBYBBSuVMOFFbzpQx0L5WdOlrlhSW/iBcHxtKJQWAQI9dbnIBkuzL1CfC7pzeDN3Kj9M8QYC+ICBXplobAIKHwQwoVcEZkxFiW5QrgK90rK5j5kjAVxZogxaxWFwiJAqHOREPSvhwndYuHXHEdhkZtasVjQVO8/ao8ODbN/KwmFRYBhnEWIkFkhPsdYUFjkphYCngeHUzjz50/g4jteqHZTagpVdA7SYlFRKCwChF7bPqwDZT1iWix8cIWotwHFZW7s6abh7Ktla3filU3d+MuKjdVuSk2huj/oCqksFBYBJqwDZT0itMqbvgVv8h7ISdJWICuck4e6sqZLxD9U9weLp1UWCosAoY8pST4MocHPrBCmm3onVQOuEJUwx4kEjaTNFZKsYkvqDwqLAEMzeHiQq85oxOfdTWtgsiwnokaCNyUDw5wAy0FIjVmhhcIiQOjDIksUh4eskt5+pZtSXObEXiAr/M/LwHD4zyEo2EUn+7WSUFgEmFow7dYLprDIxFiUtgmZBe+B3NRCSe9BRUxQWPgHn6PqQWERIPTALQYchQ+/XSEcEHOTsgVvhrOvVGExSGHhHzUgOsMKhUWAYTnn8GBlhfjhCrF+prDITS2kmw7YLBaMsfALWiyqB4VFgAnrQFmP6HUsSqmcqtYzobjMjd0VEs7Vvs0VMhTOcwgiqgU4rPdGWKGwCBBZ6aYUFqFBXruGqPVI+RF4yXsgNzZXSEj7SrVSMMbCP2ixqB4UFgEmrD7jekRaGWSMBVD8YCboG/aMzW0U0ueFrpDywOeoelBYBAi9pDfN4OHBygqxhIUf14/3QG5SNWDuHqArpCyo4ykXaZWFwiLAUGWHB3ml/LZY0ISbm2QNBG/askJYb8E37M9R7fdrkEraU1gEiOwYi+DcKCQ3eh0LwB9RQGGRG1vwZkhXpXSFlId6coVct+gtHPr9h7Dq3a5qNwUAhUWgCetAWZ9k0k2jpVssVCgsclMLkf+qmOinK6Qs1Ppz9OMHX0P/UAr/fe+qajcFAIVFoMiyWNC/HhrkuBUxFGFR5PWzl/QuqVk1j72kdzg7Sy03HSRzdi1RL4u0/qFgWLwoLAJMWAfKekSKAcNQq2+W/rnchCw3aveEdROyWjiHICJqQHQWSlAqt1JYBIjsTcjq42GoBeSVMmAJi2JN89w23Tu1YLGoBXdOEKnH5ygodVAoLAJMWPPy6xE5NxgGEDVKs1ioHhRaLHKj9k9Yd7AUtFiUBXvwZjjvjUIJpbBYuHAh3vve96K1tRXjxo3DWWedhdWrV5erbXWHvgkZYyzCg+UKMUyLhS+VN3kP5ETVXeG1WFg/h/Ucgkg91rEISlZRQcJi8eLFmDdvHp5++mk8/PDDGBoawmmnnYbe3t5yta+u4SATHlRXiCxlUXQdC4TfvF8pasEVYt+hNRgrzlqgHgVbUCwWsUIOfvDBB22///73v8e4ceOwfPlynHTSSb42rB5hjEWIMV0hBmKZ/UL8qJpZLwNisdjcCCE1d6tXeIjX2zfqMcYiKMGbBQkLna6udDGOUaNGuR4zMDCAgYEB8/fu7u5S/mVdwQJZ4cFuscgEbxZpfq3HlVax2CwWITV322IBaLHwjXqrvBkkig7eTKVSmD9/Pt7//vfj0EMPdT1u4cKFaG9vN786OzuL/Ze1T1blzeo0gxSOPd00/VqxFgv1XdwrJDeq8Arral+NrWLwpp+Ev9x7WClaWMybNw+rVq3CHXfckfO4BQsWoKury/xav359sf+y7qDKDg+WxcIws0L8sDZwQMxNTQRvKj/XS/ZCJaDlr3oU5Qq56KKLcN999+Hxxx/Hvvvum/PYRCKBRCJRVOPqDX13U04q4cGWbhotLSuE6abeETUQ+FiPhZwqgS12hZagilKQsBBC4D//8z9xzz33YNGiRZg6dWq52lWXZG9CxochLKiisHSLhVrSm/dALuzbpoezr1h5s/zQ+ltZCnKFzJs3D7fccgtuu+02tLa2YvPmzdi8eTP27t1brvaFnp7+IfzxufXY2tNf8HspLMJDSrFYRCL+uULCGpBYKWy7m4b0ebG5QkJqdQkiogZEZ1gpSFhcd9116OrqwuzZszFx4kTz68477yxX+0LPzU+txbf+/CKOveKRrAJYOvpfKSxChJJualXe9CErhBaLnNRCDQj1HMIagBpE1J7kWFpZCnaFkMJYu6PP/DmZErZttfNBlR0epCtE3SvEl8qbvAdyok7KKZEWc9JiFBqYbloWRA1Ys8IK9wopMzFlkMvnP2WMRXiR1y6ilPQudjBjuql3dNd5GC08rLRaHkQN1DgJKxQWZUZdPRVaFY2DTHgw001t26YX6wqhb9gruvAK454Qqjhi8KZ/1GPlzaBAYVFmVKvsYB4zJ9NNw4tZIAtW5U0/hKEQdEHmQu+aMNaBsG2WFcL2BxabK6R++jUIKeoUFmXGnkpWqMWifh6GsGNeZtVi4UPlTYCWq1zUgsWC26aXh3q1WARhzxwKizKjqsd8rpDsGItytIiUA7NAFkqPsdAJY9xApcgSFiGcQGwps3zofaNeYyyCIE4pLMqMbS8DWixqHsMovUAWg3i9o4+h4TR5M6amHNSTxSKq+NyDIE4pLMqMutocyGex0H6v9YehVlBXRmq6adGuEO19FBY5qDFXSBjbH1TqdXdTWizqgFRJFovq3yAkP+oAZhiGUnnTn8+vozGxYGpBjNvLkvNil4Mw3hdeEUKUZBkvBxQWZUYVj3mVJFeqoUS9Sgas2iVFp5tqv3OycScrKyQAg2qh2Et685n3C1u2TQ33qz7MBOFcKSzKTCHBmzoUFuFAXXEahpVuyuDN8qO7m4JgBi4UW+YYRaRv1Mu26fq55StrUAkoLMpMISaqWjDr1iM2VwgMRDNPVdGCQHsb5xp3aqKOhaiPlXWlsQdvhu++8Ep2ZlT1z5XCoswUFLzJbIBQoppcjYgPlTe132mxcEfvmTBaLFTC3v5AUacWi6Hh6p8rhUWZYfBm7WO3WADRSPqx8uv61VMOfqHoGTRhjLFQV5z1lL1QbkSdpPHq5xYEdxqFRZlRV5t5XSEM3gw96W3T0z8XX8dCuw9osfBMGCcQppuWh3qJsdAto0G4hygsykyyhODNIPjKSH50i0WkxG3TWdLbO9kxFuHrK1tJbz7zvlEvBbL0cYbppnVAqhCLhfY7J5RwYIux8KHypg7vA3eyNu4LwKBaKCkGb5YFe1Bs+O4Lr+gWCwqLOkCdFPIFb+Z6LwkuelZILFrqtun232m5ckfv4jAGP+ora+5m6w/1a7Go/rlSWJQZdU7Id8Frwaxbi9z9/AbM+dnjWLu91/HvtgJZ5ahjwfvAFXO7+kxcSyhFGLPBykK9xFjoVq4gWGcoLMpMIa4QnVp+GMLEJX9cidVbevC9v77s+Hd9hVn6tunC9jlBWIEEFdkzDZniIWF0JdTCDq1Bp5b7VL9/WCCrDlDNVHm3Tc98j/m87Tbxh72DScfX3SwWpe5u2pBxqQRhBRJYMn0VzwiLIPiXCyW7Fkf4ziHo1PIiTT+3IIhrCosyU0wdi1J99KQ8yOuik115s7SsEElDph4GBaY7phiPhleMZ1ksAjAxhJ1aqG/ilay9QgLgDqSwKDM2i4XHOhYxTiiBRAoGHXUQixiWxanYwlameT8W3lV4pZB9b7lCwtdXuv5kymnp1HMV48EACFMKizKjjnNe61iYK946ehjCgJy8dFy3TS/RYmG6xAIwUASVlOYKCaMY11vM6106We6lEN4X3gmedSZW7QbUOkW5QuooxiKVEuZEHHRibhYL5WcDVh2Lol1ZZoyFnCyrP1AEjefW7oSAFegaj4U3eJMVd/2nnvo0y+JFYVH7FBK8KamXGIuuvUM4/ZrHMfugcVj4icOq3RxHVPXvHmNhL5Aljyt2laRPlswKsdM7MIxPXr8UADCuNQHACnQNoxshiBND2HEqNiiEgGGEYxFTCNnBv9UfL+gKKTN2i4W3OhZWjEVtDzD3PL8Bm7r6cfuz66rdFFd6lUwQeV107Fkhhm/+fstyVdv3QaFs6uo3f5ZxS2FON82qHlrjC4pK4OSFrFWrRVb9owA8AxQWZaag4M3MACNXvLX6IEjC4ALpGxw2f3a7GvqDbaWJlppuSouFE7v6Bs2f5TMS5uBNXTfSYlE6ulgDalew6ecahPuHwqLMFLMJWbROYizcLABBon/IumYDQ251LOzVH+V5FVuoxir6xOBNJ3b2ZgsLs45FCJ8ZBm/6Tz1bLILgDgz+yB5yCgnetFwh9RFjocYsBPVc1RoDrnu9ZA6RZ+OXIGDwpjO7FGEhxXdDLLzFxLJqLgT0WQg7QVjJV4Kh4erfPxQWZaao4M06qWPRoAiLvS7WgGojbMIid+VNGRhWqiDQazPQFWJnh4PFoiHM6aZZPvL6mADLiZPFolafoyBuWkhhUWbUMcLrtul1E2NhhEFYWD+7WSyEZrGIRaUrpMQ6Fizp7Yh6HbJjLML3zDB4szIEYcItB4yxqENStuBNbwNGvcRYqJOA2z4c1Ua9AgNDLsJCi7EodY8P+T/DXPSpnDi5zeIhdhtlb/0evnMIGupkK5/LILgIykF2unL1z5PCoszYgzdzT571FmOhTgJhsFj0O1w/IYQ5YElXiOnK8i0rhBONilNFU7OORQAG1ULJ3tcifOcQNNQubYiWFkwdNoJg4WSBrDJTSB0LSb3EWAyGwmKRO/j2czc+iyVvbAeQHbxZanR2jFkhjjgJ7jCnm2ZlhdT4c18J1B5MRCMYHE6F0prlBVos6pBUAcGb9VbHYkjpj76ACgt1LHK6flJUAFbMiF+WBiuFsjYHxGLRdwMFlA3bQvjMmDE6GWXqdH6kMFQrkFnBtlZdIYyxqD9Us63XCx6tk4qL6vn1B9UVAneLk27CNutY+GRpoMXCGafHKB5mi4XMAqoTS2UlUHuw3lwhFBZ1QL4Vr0pWjIXInrxqCXWiDkOMhX79+rVgTj8sFur1DrN5v5w4WixCLML0gmjJGl9QVAL1FrE2qKvNfs1ON63+M0BhUWYKKektUStS1rI7RJ2ovdb4qCb69VPLfQPZWSHF+Dqdgs7CaN4vJ07PRJjrWEihFAtxymzgsD1H4Q3s9YJ+VkEYSyksykxKExZeLBBRpXBUGAdKr6gr+iA8DE7oMTLq9dPjQiJZWSGlnVOpaau1inNWSHjTTbMtlbX7zFcK1YVZ69lVQazcSmFRZtRrLoQ3C0RM2ZyrlgcZ9QEYCOhDn8vMqLtvIqbFonhLg5NvmCtYO451LEK8xbyeXhyEiSHsqM9tIlbjwkL7PQgLEQqLMuJkncjlDpHHRyP1YbEIgyskl5nRzWJhmV5LTTelK8SJ3DEWwbyPciFMV0h9ZINVArUHwyw6vaA/DqVW/PUDCosy4livPkfKk7lyUWMsAnCTlAt14nXbh6Pa6OJQbbNbjEUpvnJbmlyIJ8ty4tQdYV7tZ1VareFnvhqE2U3mDb3AWvXPk8LCJ7bvGchaaTgNDwPJ/BNoJGJYZWhr9mGwD6BhtFjoRb0MHywWTq6QWl1pFYuTxSLMq9IULRa+41THIqhjjN8EweVDYaHxzo5ePPba1oLe89rmbhxz+T9x/o3P2l53coXkGvjqzb8ehuBN/RoOJnO5QtLf/Vo9x2p+pVUcjlkhPgXMVgN5i0Uz5+AUnEoKo54EOitvhoCTf7oIF/x+GZ5+e4fn9/zpuQ0AgCfe3G573enyeplADcMyiwZ1wvWDwVAIC/vvajv1ol5WVoi18ix0vxdb/n2IazOUE8eskFh4V/uWKyS85xA07M9RbQv0rODNAJwnhYULy9/Z5fnYCW2N5s/qRJKy+cvzRybbaxj4EwAYZNQB1G1L8mqjP7TqakCf38zgzZj1WBXqylLT5GI1niZXLLn2Cgmj69AK3qx9K2WlUHcclmNpUBcvpUKLRcApdjfRsa0J8+ftewbMn51SnjxZLKD4BWt4UslV1TIo5LJY6L5+s0CWEnxbyiQR5oDEcuKcFRLeSVmvY8HKmz6Q6VMDqkAP373hBSlMpSs2CAsRCguFnoHh/Ac5YFjZodjY1e94jBeh4FTUJagTrh+o5xtUAaVPYoNK8K0+3+t7hQCFP+ROVqswxg2Uk1x7hYRx8pAtppD0D9mDhmHUfGl8/f6hsAgYXX1D5s96KmEuVJN+nyJOirZYGOEeKL0STouF4grRHCV6jAVQ2vWr9aCzYsmVFRIE/3KhZGWFMHizZIRisYjXuFtZnmuQ0pUpLBR29Q0qPw/lONKOW6yAOgAmGqIAck+gThvn1OrDANhX/IGtYwHdYqFeX/uxUlikV0ml71Bb+/n3xZFzr5AADKqFYrlCMlkhITyHoOEUqxSEwlHlpCFmWbyqvXklhYXC7r2WmNitiIx8qAJCnSDVS1tIWVkDRl24QtQeCmrwph69OaS20yXGArAmiVwF0Rz/naMrpLYHxEJxsljEQrwqlZNAPCbFKK93qZgWC6P2dwmWIkpaLIDqWzkpLBQGlPTB3gHvK2j1flUnyEKLtNhzrzORzDX6MAAhcYVov3uxWADKROeDxSKMmQ7lxMliEQ9xfEKWxSKE5xA0zBgLGDXvCpEnK1OugepbOSksFNQHWt9gKuf7VIvFkCIslGMSBWR5GEZ9VItT+yeoAkpfHauDk25uVAwWRfs7nQJ4abGwkysrJBkAM3ChyNbGorRY+IVQgixq3RVi1UFRLBYFWkr9hsJCQX2g9eJHuVDTVPtVV4gyVyZi+WMs1CV8kCJ8y4U6AQRVQOlzlD2Gxv43R4tFCdfP+ozaHBCLxWkxFldqhwRVpLohhZJMUy427Z1kY6AOXCHSYqEKC1osgoPNYjFYiCvEzWKhBG8WsJeBgdrf6hewWyyCGmORXSArfx0LQImxKCHdtNYrBhaLU9ZEY4MiLAJ6L7lhukJosfANe4xFbbtC7FbOYJwrhYVCsa4Q1+BNhyyPwRzZD/YYizpwhYQhxkKvY5GjnarFIh4rzufvdA/QFWLHKQZBWgSB4N5LbsiJwXLnhKv9QUYNhK9Vy586RMUiwRgzKCwUkkW6Qjylm3qwWFgqW8kKqdGHAdBiLAI6GRRisVAKbpq1LPxxhQSzb6qFU4xFxAhvwLMcPhposfANp6yQWn+O1DT3ap8rhYXCcLGuEOEsLOzBm5kYC48XvB7qWNhiLAJ6nrksFm57hQDFlxG2ZRKFONOhnDhZLNLR/yG18mVOJ8qsEN8w9wpB7Qt0KwMmOEX1KCwUVBNk/3DKc3R5yhZj4ewKkalAudNNs4M3QzdIFslAARaiSpJVeVN5YLNKeis/x30oxx1TdrsMW6ZDOXGcd0OcSWXVIeDupn6hWn9rvYqxHBuCZJ2hsFBQV4bJlPB8I7rWsVB22ItHvVss0sfXtsoGtBiLgJ5nrk3I9Kqchh8WC+XnmOJbqdVBsRicsibUFO2gBgK7IU8nFqXFwi+cV/Hhui+8Yp5rgJ4BCgsF/YH2GsDp6grJvBwxDMu1UWBJ76BOuH6gTsxDSRHINLusAlk5XSHWzzLGotCMDqeskGI+p5ZxygoJ847A1rbpjLHwC3sdixpfpJmnapixfNXeIoHCQkEXFl4DOFMuQZ9OG+F4sljUSUnvbDdD8M61kAJZTlkhfgRvpj+Hk43ESYBGjPDGWMizadBiLN7Z0Ysdewaq1Kpwo1osat4VolrGA+IOpLBQ0FcKXgM41RWUbeIp8II7pRrWrMpGOIRFLldIzgJZZlZIgYOZGpejWiwC2DfVwtFiYQBxL0XoAkh2HYsUXt7YhZN/uggX/H5ZFVsWXoTDc1SrY6nTLtp0hQSIYl0h6gpKnUiEYqKy0kdZ0luixyioxcWCg7vFImeBLB9Keoc5hbKcuGaFhPCZUa1e8p5JpYBfPfYWAODFDV0M3C0Kuagzat8VksHmDqSwCA5Fx1go71N94SlRoMXCwb9eq+Y7IJwWiwGbK8T+N1VYxH1aJck05WCKrurgNM8aBpAoQLwHBXXIkVaulBC2FWc/r33R2DMlanMsNZ8Hw7DGCwqL4JAVY1GUK8TBYlFgGlCYA9EKIVdgZFDIKpDlsnst4M9eIepHGoZR0OZ19YJb1kRQVmuFoN5DUcMSFooXDLv3DgIA/m/pWtz34saKti+s2OPbanyvkMx3dSuIaj8Dsar+94CRFWNRhCvE6eb1aqattzoWhZTLrha6u2PQFkNjxx5jUXpxK3WgoMXCwj3GInzPjHom0YzFIins57C7bwiDwyl89y8vAwDOOHSieSxxxlrEW66QWq1iLBws48wKqSJ/WLoWn/7NUvT0DwHIrtFfTLqpuppSLRaFuDbqYeMcwGnn0OAVycodvOkeYxH3UBDN8f9pvwdloAgS+bJCBkL0zKRsMRbpe0ZorpDdfUPY2Tto/s5MkfyoFouaD97MfE8vRIIRwFzXwuI7f3kZT7+9Ezc8sQaAvdAVUEBWiPK+IVtlxvTPah2L3NumWz/WRUlv7fdqPwxO6G10qlMiUS0WxT7gqhXHMBAYn2mQyFvHIkR9pZ5KxHCOsejaO4jde4fM3zd19VesfWHFXpywxl0h5gLWYIGsILErsxrQLRbF1LFQgzedqr95ywoJb05+IYTBFaK3UbUcZKebWj8nGkq3NBiG4cvn1BqOWSG2QTWcfWUGb6bs59DTP4ydeyyLxeZuCot8WI+tYW6nUO3JtnxYz0NoC2Q9/vjjmDt3LiZNmgTDMHDvvfeWoVmVRfrBi42xUFdQw7bgTcse50VJOtWxqFW/IOBgDQjgikJeQunTViP0ddFhOFgsCo3o1/skKMFYQcIxKwThtFiorpComhWi3DfJlLC5QrZSWORFdUM3Zp7F4ZSoWasFEKzgzYKFRW9vL4444gj88pe/LEd7KoZwiIvISjcd9HZxbHUsXCwWjWYQnrtYMYNwAE8lwMNOrviFoCBNqk0N0iWhVFbVjrVZLHxaOQTFtBkknOo6qCbvIN5HbqinEnVJNx1KCexQhEXPwHDF2hdW1N1NGzPPLlCbz5EqooJSIKvgrJAzzjgDZ5xxRjnaUlHUji+3xSISMcyb26t7pRDXSVjJFb8QFOSlbWyIYs/AsM0CoQcR2i0WxT3g+pzJOhbZOCXa2FJzA3gfueGUFZISdkE6nExh76AlJnopLPLiNNkC6edxRKJKjSoT1gI2OEXiyp5uOjAwgIEBK4q5u7u73P/SE+rDKS0VcqJIxCIYGE55FgHJvJU3LdXc76VAlmFlFdRy8KY+i1b7YXBCNrEpnn5gbXvBaMeqFgt5vQsVBGrQGRAcn2mQ0Cu2SsJY+8WWFRKRlTftFotkSmBIGWN6B3gveMWAgUgkHbM2mPQ+pocJdd4ISrB32YM3Fy5ciPb2dvOrs7Oz3P/SE32DanBUOuJaWixaG2OZY7ytDNTBwTF40zDQ2JA9MblhwLC2WQ/gZOsXsn/MstUBPFfZRssV4p5uGnGwWPQXKQjkJwXFtBkk3IJmw+QKSaYEbn3mHaze3GO+5hZjMZQUNpcoLRb5ybL8FTD+hg3V7SPPs9rPQNmFxYIFC9DV1WV+rV+/vtz/0hN7lIdTujyk5WFEIi0svAbeqRaLpEO6qc1iMZR0rf1vC96sA4uF7AYrNTN4D728hvL6DQ6nTMtWznTTIi0W+mI8KCuQQKH1kXRBBcUM7IW7lm/At+9ZhbOvX2q+ZhXIElmuENVN2+txwUNUy1/tPkdOW0FU28JZdldIIpFAIhE8p5aq+oeGZYxF+qZryQgL73uFWD/bgjeV/GIZmZwS6RWIdHU4EdZAtEKRSjsRi2DPQEAfeiXGQjIwnEJTPJotEH0M3tQny0D2TZXQXSGy282+CoEYX7lhd9Zrsoz30LCwWWWGUsK2wKArJD/qKh5AQRbjsGFZxtU09xq3WAQV1RohfbLy2W0xLRYe61i4Bm+mv6sXHHA3jztt9Rsmf3GhWBaL4IooPSsEsMRCdoyFpSwsC5U/6abVXoEECd0VIrs9TBYLw2FdEc3EWOgu2GQqZRtX6ArJj7qoAxTXZA0HQasu9GoLi4ItFnv27MGbb75p/r5mzRqsWLECo0aNwuTJk31tXDlxiouQBbJkjIX3ypvqZwkIIWAYht33FYvAMNI3fP9QEm2NDa6fF9ac/EIRmjUgiCJKtrEhaiAaMZBMCXNwyo6xsH4uVhCoAb+AsgKp4QGxULLqh0BOHuGOS5IFsvQA7+GksMVu9Xocl+oZXaA3OqSL1wrqXiFBickq2GLx3HPPYebMmZg5cyYA4JJLLsHMmTPx3e9+1/fGlRN1UrBcIenvhbpC9AlmWPPBG4Y9Hc5tklBNvHbXSTgHynzIsw2yiLI0o2HWIpGWrOwgwtLTTc3/pvmGgyi6qkVWhFIYLRbINlnI+0cv4jSUFLZsM1os8qNOtkDxFsQwEaSN+Aq2WMyePds1+DBMqKcwZLpC7MGb3mMsNGGRFGiIWv9DDhiNDVH0D+VPeTIMoDFuab69Q0nTNVJLyPso4ZBxERTU9M/Ghih6B5NmO7NCLJzSTQvehMz+ofE8YrQeyQ6aTX+Ph9h9aBhAxhOSJViTqZTNYuE1W63SCCHwuRufRUoI/OHfjkOkijuwqnEHQG27FC0rpxGY86zbbdNtFouUXViYMRZFuELk5zUhmh1AFIsCGHJVzXp0b8RIDzL9g7ldJ2EnKOY7JyxxqPppMzEWXtJNCwwWUwcJ9XOqPVAEBceqm1pfVXu15gU9xsIAEHUKvIAM3rTOe09ALRZ7Boax5I3tAIB3dvZh6pgRVWuL/hwVW1cmDNg2XAvIM1B7y2CP2KKuh+2ui+Z4YRYLfayTgVZ6AJEZmZxnkjBgwDAMM2DQazvCRjiCN9MYyK6emiMpxDcrTC2nyRWD4z4hoXSFaL8bhq1yq8pwMmVzj/QPpQK554W6YNrWU+2t3XVXSGl1ZYKM+kwEZbyoY2GhVsvMmLYhXSGFTehZMRZJ5+C+Qst6N8Vr2y8o+zvIwZtQA6M0seClQNbgcKog16ES0pH1OSS7z4HsdNNA3kd5iBj24F+VYS3GAgD6ArjYUMe1d3f3VbElDkHQscLG3jBhs3QHZLyoW2EhHIRFSrNY9A+lsvaDcPws7XczeDPzu/SdJjwGEOmBe7VqsZBd21Sg4KokKdPq5OAK0Y6NKE9TqRsfZWWF1OBKqxicnkaz5keIar/o1gkDhk2YqgxrdSyAYAZwquPUu7v2VrEl9qrHgGWxqEVXiMSWIBC2bdNrBZsrJLMakKuh5nhhk0K2xUJzhUg/Xx6/u76ylRYLr2mvYUOer2khCuB5WjvOKmXZXSwWTpuQAYUNZvo9YFXSq90BsRC8WCyqPagWg2FYlTd1hlOprA0Sg1gkS31+u/YOVbElOSwWVbw3+oeSWLfDf0uO5a61F8iqZpJFHQsLB1eIXEErwsKLtSAritv8bLeUJxdhkfkuH4Ygr+T9QJ6vtBAFMdrdVtXO3Gk0af9jBnVeiEUM8/dCJjo1RRkooTR4jeI4Vmb6qinEKYXplHTnvw0lRVZMRdAtFtUOMBWasghCPZiF97+Kk376GP66cqOvn2urY5EpkCVE9m7dlaRuhYU6QMmiVvICxSLW9rOe3BDaaGfulqqpZn3Fm49aD96UE/OIjJDrC6TFIv3dtpGcm8VCCclLH198IBWzQrwjXQhN5n00HLqU+JyukGQqK8YiiPuFqONUT3+w2tcYAIvFzUvfAQB89fYXfP1cJ4sFUF0rZ90KC31SGEpaFQQiakaGh8lOF4bys53qWADKildDqMtjAI217grJfG8usIR6JVEfWv36ue2yKSk25dTpM8IYkFgOHF0h0mIRt4rKBb2/dA0RyekKsSpvygVPEF0hanp+1S0Wme96rFIYrVl5URY/caXeUTVjjepWWOjj01AyZe1GahTmhtCLGiXNypt2k0Wjx8hkyxVSgNUkhMj+aQ60xUIxM2r1NvQpTg/IKyX1S0+hpCskjWO6aea7up9L/2C4+iudbur8t+GkMOO22pvS9WyC6Da0uUKqbLHISvUPQBpmrEwFw9T5JxIx0BBN/59qWjlZICvDUDIFWdzOMAwrcNJLjIV2rya1rBDdFeL2mbpAqbcYiyBaZlRtqMfI5Eo3BYrL6NAnzqDkpQeFXFkhDdEIGqIGhpICfUPDaEdwi8rpJb0NZN8/kuFUyowD62hqwLaegapbBJxQrQHVbl/27qbVH0sbG6Jmv8j9pPxAD1R99r9ORaIhYhPalaZuLRa6GdvuCrFuRC+TnT7YyQnHsoDYXSFe001rPysk/d2MsRhKBs43Lu+KiC2VKyX/aENfkFgWqgKyQrQBkTEWdnJlhQCFPbfVJKvyppFLWAgzEM+0WATQFVJKjMXqzT247K4XsXG3T2mqehC0D27JUlEzxcqxkZw815Ej4miOx3wTLsVAi0WGoaSVnpOOsfDuhtAnQ1O0mDEW6e+JfFkh2pjZWOPBm3ISlTEWyUzp4niseg+EjlDMTnktFpHSLRYSc7tnLX2smoNFEMhVeRNIW/l6+ocD6VZTcaq86VbSO10gKy1OpbCotkXAif4is0KEEJhzzeMA0tsp/PdHDi65LdZjq8W3VdHypz67XXuHzK0jSsV6JIIzNtStxUIXA7YYC6hVL70Eb7rEWGR+t25ubwFE+sNQkwFHUEuoK+m9AZsQrMyewkp6A8i7m60T+mdKN5EQtXsfFISjsLB6vrmA5zZIGAZguIzGQ0pWSHtzcGMshrX9TLxaH9XV+8YufywWetq2VSCrevfFoLLA6Paxzod+rkGgboWFoytECfgpJCtEf370rBDz5s6T8qQ/hrWebir7R/rGAaBvKFgDprrBj+4KyVUgCyhtleQUkBjEyaTSeHWFBN1ioRMxclfelFgWi+CdX1K5NsmU8CyEh5Tnw2k7+WLQ49USRbgl/UYdB/wsIKa7T4NAHQuLHBYLozA3hJvFwm2vkHyq2YyxCEDAUSUwYJ1r0CYENTBKRnUPa3VKJNnppoWfkz5tRiNWbEfQ+qYaOAdvWj83FxB0XU0K2d1ULY4ldzkOosjULRQ9A94mT7VcuV8TbrEbQJYLIUT5hAUtFsEhq1pmyrJY2OpYeEo31T5b3ytE+svzbA+eFWNR88GbSnpvwM81YhiIZnLEk6bJN3dWiCxVXsgkoKcoA+GZLCuBs8XC6qxCXJhBIle6qVocq7Ux7RoLYuVN/dp4TTlVa47s6hv0pS3ZGXnVHV/0Md9fi0XwqFthkR1wac8KkYO5lwdYH+uSpivEmjgBIJYx9w8nc98Kuhm8VicUNQal0K3qK4V6DeWK0s1i0Zywp3eNSMhJoIjgTfVzzZLnweqbauAleBMIX185ZYXIYkfqir4t4woJYoEs/XnwGsCpjoe7+/yyWNjH3uYqL1x0YeFnjIW5A3OAnCF1Kyz0XUuTKWFzhbQ0ep8UXIM3NROVHCiG9cIXJs51LII22fqF2j9BnRDU3U2lKySZknvL2K9Xa6O9boJMoy2k/LKT5FRLVdc7uu8csIuwpgDXRFHRC4MayK68KeOO1BiLtsbg7qtTrMVCFU67fbZYSLFmivMqpbTrmWG+CosMdIUEAKcy3KpfriWRniS85GO7Bm/CriRjclvnfBYLs45F9XOvy4k6SVgrimANmNa1NcyBX14+/R6Sg75EWiwKS73L/DeHTIegT5aVwNliobhCQlKt1qm4mh6j05BxnarBjVK8BjHdVF+s9Xhso+oK6R1MmguzUrBKB6R/l9bEZEpUpdy7nhlWDlcIhUUAyLYyWK9FDMP0Ze7xEIDk9FmAuldI+rvlCvEYYxGSYj/FYrNYBLSst5oVIq+fabHQjpWrIskIuUoqYhKoBfN+OcjnCglyFVcVffJM726qWyykhTM7xiKI90KWK8SzxaI4S0fOtihVlAGgWc2uqoIbqawxFkpKfFCoW2GRFRehBG8agCIsvFssLFO53RUiRz7TFZJ5kHoHhjHvtudx6Z9fzBTokofb61gEffVVLClTeBmB3S9EFYfSYiGvn25SHeESY1FYamD2zEmLhYWjK0QZT8PyzCS1e0eegmq1cHKdthRhBasUWa4Qj20c0hZa3f2lT7opzWIRi0bM/uyrwr2hu7/9FRbZAd/Vpm4rb+oDVErZNj1iGNYD7MkVkn5fLGqYW7DLzwSs6y2Fh3yQFr++DX9/cRMA4GNHTsr63BE1H7SnZIUENLXWDAKD4S4cM4zQLRYJ7wHAOs7Bm8GbTCqNk5XclhUSEuuOLkrlYiIaMZDKCFcZYyFX9NGIYYrVvsFk4Cqx6s+DZ2Ghreb92HJdXbRImuJRDO5NVcXdqofVdfu4SRuzQgKEU7qpGqgnhYUXP6F8X0Mkk45oxlhYnwdYMRZDmbtsR68VqPTWtj1ZYkcGkFZ7p8ByoZrwmgIqotRrKAcpKyskj8WiCEHgZOpvUvZSqXecAu+c6lgETaDqOLlC0t+tk2mI2ofnqGEJi2RKBG5jOv2cvAqEIe19flgs1EWipJpWUX2sKEvlTd8+sXTqWFhocRHCOSvEk8UiM/1Eo9aKdlfvoK0uBpDtCtllExa95s/yWZDiZjCZqslNqNRJO+iuEANqjIWzsNino9n2ezHBm3KMVTME6AqxyLVtOmDVfgm6dScrKyRzEqorRBcWkYg9ViBotSyyXSEeC2SV0WJhi1Wq4hij37flCd4MjrSoW2GRlcmRErYUpdaE9+hreRPHMhaLK+9/FTN/9DAWv74NgOIKidpdIWoxmM1d/VltUjepqUWrhVBcRSMCOiFYwZsGotIipblCvj/3YDy94IPmwCVpSRRuhZGfbWgm3EI/pxbY1TuIz9/0LB5ctcl8LV9WSLMZYxGs1byOU1YIYK++KV0hkqhhIBIxlBo7wbof5Dholh0vIt0UAHp8jbEIhkDPslj4cI46wZEVdSwsnOpYCAeLRZ+H9Cc9eHNL9wAA4PZn15mfB1grEOkzVYvBqDee9BlHI4Y54fqh4oOGarEIqttHzVxxi7EY19aICe2NWe+VKW6FWSwy1i/bZBlMN1G5uev5DVi0ehsuvOV5czLIF7zZFNC0ZZ0sV0jmeySHK0SvyVBIfZRKIMfPtqbCLHV6+qc/FouMsFC6sJr9Jt3jUnT1D/lnhdaLgQWB+hUWOepYRAzD5i/P94DIC6sXuJFIodCgpZvuVFwhauVPlSDnrZeKWiNC7oFQDiVfCurupmZWiJluao8812kxK2963+lRT1EGglvjo9yoYvu1zd2Z17KPU0VYWII39awQKRrUySEe010h6T+2FCFYK4G8XvJZ9hxjoaWb+mGx0N3QQHXdrarokk3q3uvv9QuQrqhnYZGrjkV6Ayn5YOd7gOX7dNOlJCt4M/MgqQ+QOmCqg4tcyQdtwvUDVWm3msIiWIOlrY6FZrFIKcLICTmQpYT3HU6tOB+6QlRT/6aufgDOwZvq5CHTxINu4dMtpvIWikTcLRZS2Mqy3uWo3lgK0vDQVuBiKNsV4p/FIiiF5lR3eWtmwVGuDdeCQN0KC32ASgdvyt/SF6jVY8qpfJurxcJ0hWRiLDIrXtUEqFpMVApJew0bpisE1oQQtMESpsXCGvSHTVdIbouFmn7qdZBNOppww1GbwW/UCWbj7r0A8u9uKk3NfgbHlQM3V0jUgyskqOcoNHO/18WQXjDQj8WFlW5qvdZURZeiFJIRQxGGPi0WnW3d1aVuhUWWKyQlsiaKFo/VN+VNow8EEtMVkpkthMikiykBZupAo85ThRTqCh2K0pYPW9BWmmZAbyS7jkUqz0rBHmjn7byCliZXTVSL3uYcFgtV0KuTWpZVIEC4BW/a00214M3M8CLP0a8Nu/xCntOY1jgAYOceb/t+6FsclD94swp1LBTXjN/CkOmmAcJp4zDdL2fWsvDLYqH4TIeSKZvFQghn5RkW024xOFks/BhU/ETNXIlmBW/mtlgASsCYxwh+M93U5gqpz+BNdUUn45GcrHrq5CEFqhDe96qoBm51LHKlm0YDbrGQpzS2JR3I3DuY9FRPpByuEKdnMwgxFhFDiSfzS1jIHwKkLOpYWNh/1+tYAN7L55pZIS4WCznwxZS7fCiZwuCw3RUiscVYBLiEb6moMRZmwNfAcKBWmilF/cT0dNPMn/TtrlVkoJ3XSHR57k5Fn+oteFOdYIa1PldRJ4/GhigaMxuRdQVsRa+i70OoZoJJsutYBF1YWAGKsmaPWgTQDVnHYtSItKXDH4tF+rs9xkJmhVQvxsIwFKuaz9ePe4UEAN2kqtexAFS/v7eskIa8MRZWdw8nhU1YJFPCcdRsLTDCOkxYc7a16ZsQwUqjU6uDRrUYi5QHG+SIAmNknEoRm+6UOrNYqPe8W1EywB7wCAR34lXJLumd/q5e93jMfl56jEXQ4pHMVOmIYYqEHXsG8r5PPk8dzf6NdfpeIUB1BXpStVg0yYB8f9qhpsQHhboVFvoANZwSWa+NbE4/HGohK+fPSn93c4VIohFra2TdYqH+a1V5Wu6YYA0ifqA+EI0NUXOVE6TMkFxZIU4pbTqFptE6+YbNYm0B6pdKoD4fZopvHlcIEA5hke0KSZ+DGrTrlhUiJ+DdATs/uR9GxDAwuiUjLDxYLOQ93+FjnJXbXiFAdUt6RyL+35/mGOXLp/lDHQsL/XclxiLzAI9uSQAAduQJQpI3Tcw13dR63dovRGBAzwpxeG8tB2/qZyyVfJBElOPuppkRNJXfYFHwIGINQNkplHuHkln+6FpG3RHSbeM3IDvGpaMpPamFSlhkvufOCkl/D6pwUkWx17ETsPqio9k/V0iuIOhqZFc5xVj45aqjxSJA5A7eTH8fY6ru3OY8K3jTLcbC+lm6S4aG7RaLpLBX/pS0BrQipR/oD4RZy8LnwjGloO5u6h686f5Em5OAx0HEKU1OZicBtXkfuKFOvrL2i6MrROt/GcC5e6+3rIRqkJUVEpHfvdexCJ6wSH+PGMDoAlwh0k0gLTG9Hqod522LY6ySVbCu0qjWHHmeQbt+flK3wkIfn5KKK0S6IkxzXh7VnTfGQvlZZobo5ji356glUQcxFlpMS6AsFpnvuVwhuVYK7QUOIk6ukIZoxKwoWYv3gRvDykORa6KpCVeIDN5UYyw0C6geY+GUbnrL0+/g7uc3+NpWr9gsFiO8u0LkcyTPCyhdQDu5QtqKyLB7bPVWvLBuV0ltSbfHivloz1hm/BK+Qpu3gkAdCwsteFOowZvp76NGpM152/OobisrJL8rRA4cujlOuLhCpHsgyINksegpYYWWAq4EanymXDGmRHpFpGcROWFOAl6FRcreJxI/K7CmUgJ/XbkRG3b1lfxZ5USdfC33k1Pwpv33UAgL7TTk9c6VFSL/pgZvquPYuh19+O97V+GSP66sSkaM+jwU4wpJxKJIxGScVWntdwreLLQw1Ztbe3DBTcvw8V89ZbMuF9ceZNpjYGSzuzAsBrpCAkRWumlKfTAyFguPqtuMsXBxhajXW5o69fxuW4Es5Q4ZVYDyDxtqxgWgZOEEymJhPbXq9U0KYV4zt+sOFBNjkf6uZzr4Wc/k2kfewFdvfwGX3vViyZ9VTpwsFl6CN6WpOWhZEyrZJb0zwZuqpUrfK8SQwZvpMWEwmUK/UmTvpXe7zJ9fWF/6KrtQ1CB2OXbmW5QB1rWNRvzLgnMKrC70GXrqrR3mzy9v7MpxZH5Ua46MAfK7wBmFRQDQVz5q8Ka8QGMyqntX72DO2gpmHfhCLBYOrhCnQXN0xmqyqy93G8KI6mYAgm2xiBhAVLm+yZQwfcMu5UsAlBC8aejCwr/N6G58cg0A4Mk3d3gqYFQt1FLPuetY1IIrJI06hrjVsRgRj5rWC9WcLjdqA4CXN3aj0qgxR7L6phdhoe7o2+aTO9RprxA5vvQNeguCXr25x/x55frdPrVHzerxtlhc+tYOLLj7RdcFl7IkLamNflLHwsL++7Bim5QDlbQWDKeE+0VV1EC+ypvqMU6uEPN45fWRI9I3YTJHG8KKWtUSqPx+If1DSTy/blfOnUdtu5sqF3I4ZVksvARvej0nt2qefg24gJXCDACvbKr8BOQV1WIxnCN4U3/u5MDtxQxfLbJLesvv7jEW8ldDMafv6rXuB1VIyRLolUSdPMe1pqtvbu3xbrEwDAOtpruiNAGddHiOWgsMglZF/IZde0tqj+oKkfdn/1DKk7A/57dP4/Zn1+MyFwsjXSEBQp9M1NQ2eX3isYg5oG93GaTUj2nw5ApJf9ctFsmUc4xFIhY1N0OrNXeIeb56VkiFLBY/f+QNfOJXT+FXi97KcZQ1WKoTWDIpTAtSrvolha6e5UJK33/ET1eIWpflnR29JX9eubDHWHhPNx3b6i02qpq41bFQ7yW9kq/6N7no2amMCepEuKmrtImwGFShPa5NxlgMZG0ypuPkQtmZJxMvH06ukFg0YqacelmkqeKjVGFhLhgiaWFvWpwKcIfc/9Jm58/mJmTBwalAlkS9Ga0gJOcbXf2UaJ5t0wHLFdKnVX9zK+kNAKNasgeRWkCPsah0HQspKH760GrXY5KKeFBLsieFsFXTc6PQ1DKnoDPAKpJVat/sHUza/PJrtgc3gNMeYyHbnD2I6iJsXEZYeFktV4ukNv441bFQC+oB9vvMir2yzrHPYZv5SmIXCAlEjPRreWPUlGfMis0obawzg6C1Ga6tgJR2da+ZDbtLe05UF6dhGGYxsHzFF73ATcgCRLYrRLFYKL0ia1lscxEWqiCIuaxc1QEhYrpC7CpeCOedGwFlEAmwabcUsupYVMhiIfeUANzTGYeVQS8SMcy2DqdSpnXBi8WibzDpKbJcLYus0uKTxUIfyNZuD5fFwukyRTVhMTZjhu/pHw5sDIn+qMsxQp0Io4ZhGzvUe0LGXqmLDbUUfjWEherGi0YM03K0tTu3wFMF+iiPKf75cNt5WAp9LxO6Wu9iS55zyNsepY6F2o58Fgs9FsRpjtBj1YJAHQsLd4uFen3GtaUHKbcbyy4sXFwhDhYLfZJRVzD6/THawewZdpxiSvyMI/CC6rp618XUKVc+UjSqtSysbCD3J1qKJcCb1cKtTLjpCikxeFO/h4LqChFK1g2QJyska1UaQzyTUbEtoFaLLCHrkG4aixq27CAni4WbK2Rn72DFRZU+mcs4iy3duUWOmmI9JiOY8hUlzN8WZ8ufk6XHDb0/Swme19sjM3u68gRw7tKeV8fnn3UsgoNeZdMpeBMAJmSExVaXh8MWYxFzvrDqBZcDh65E3Up6A+ogEsxBshhse6OYBbIqlya4dzBpe0jf2r7H8bhhxW8MKGW9k8K0cumpoSrRiLXBmhdhoQayqfiVhqe/f8323pzBq9VCn3jl8+nUVr2vDMMIvDvEtaS3opIihuYKUX5xqoWgukKAygdw6sHM49u8XQPVSieLEpYaH+NWFbcQ6+8ebRO8UrKM9GwvyxWS+zN3apaV7Tn6khaLAGDt75HuAjV4U70Z5cPhprrVcS7ulnfokBUyqAsL5Vd9oBxlqvgaslgoP+tZIZVIN+0ZsD/Qb29zXrnr+8BIi1PaYgHba24UEsDpGmPhkzVH3nf7jx0BIO128juf3g+GdWGh7c+i4tT/0gy/rafyLgEvZGeFyPvLei0WsWciqX9LZCqxqpZPPRW50u4QPaNprEeLRdJc5BmY0J5+z8bdpbXdqfImYJUQ8GL91a0DpVhRdGtOu0dXyIDmMneKPTFdIUW3zn/qWFikvzcoK1CJei+Oz1gsNrsJC2WKdHOFOPlJdVdISgjnJH345woRyn4k1cbmCsl0T3uBlfFKQe//t7e5WCyS9pgHc78QxVSfb1fbQlJOhYtYKaYcsRPyvNsaG8z4oWr44/OhCwvTFeLwkDh1/zhTWITEYuHgCkkHbzrHWDREsy2fMsZCLoYqnRmiF3fzbLFQnqPOkc0A0q5JP1wPWYHwHsfSQWUvpzEtpQeU6guGkR7LeusL0N0OsSFCEy1BoI6FhW6xyC0s3AKQ1Hvf3RViIQeKgcxNK/3zObNCfBAWXXuHcMr/LsYxl/8zEKWc7RYLu4r3mt9dCtnCIrfFQk708n5RC2TlcoUAhWWGOBX2SX9G+h4oNYpcnnc8GrF84AFc1Se1mte5001zWSyCKSzcLBa6kFBPTd8/BrBPPNIVMm1sC4DKC0bd3C/vr3xWo6QSYzGxvRHRiIHBZKqk+zKfxSKf2FH7dVJHE4DSAkr19khXyO7e3GOCPk45jSFMNw0Q5sZhDspfjYkY35bbnKcOEG51LGKR7FWH/H9ygEgJ9xvEj0jpF9btwprtvdjRO4hFq7cV/Tl+IezKAgDQEo+Zir7ccRb6SuDtPDEWusViWK1j4dEV4rTa0HHa3RRQd4ssUVgk05NPPBaxVpR5TNXVQHVNApbQcA7ezO5/K3AwmMLCq8VC/10ixw05jgghzHt6v9FpN1fVLBaZZkqrUb5rkFIEeiwaQefI9ET+1tbiA4vdCs3tm/ns9TtzL67ULEE5B5QS96HWsQC8V9/0JCyCpyvqV1jIcUu6L9QHXb0Z5eDbO5h09G+rF9WtpLdtcNCyQqSwUc1+5cgKUQO51FK11UIVUXJQjUSMgjftKpah4fT/H5EpmLOle8CxXLbu7lCzQpLaYOGGFWOR343hVhtD1lPp2jvkqRyxG6bFIhZRRHPwJt+s4M0CXSFylbmxCoWivOCW3hzJ4QqxV+WUwkLYvgPA5FFpd0Klgzet7A7pCpHVN/NkhWhWwYMntQEAVpWwP4dbaXzZN+t39eV0C0uRlq4imruWkaf2aEHZ0gKZN8bCk8UCZluDQv0KC61ewJBLVkhzPGYGzjlZLdSbU6/tL1Er6MlJSB3gZXvc7nPVFVJsjIQaI/L6lgAICzUrRHndS6CjEAJrt/fa8swLRa7cx7QmTB/qGgd3iC4s1OBbc1fbPMqirYDgTX1lI+loajAnUD0FrRBsrpA81rhq4hZj4TQfO7lC5Mq01IqJ5UI/Dyt4UxMWarqparGI2S2fqoVHTp6lBkAWSpYrpM1yR+Xa9t50hWTO79B92gHYN1UrvC3p77pLcVJHEyJG2t3qVpsIsGKrGiIR032yvYTnTk4vUVNYeAvezI6xcF/cMt00AMjbXE7sNleIdn326ZDms+xBypZu6mKxUF+XE9PAcMYkrbpCXKSnLIYzmEwVvQmVOnm8uztYg6368JvCIscD94tH38Ts/1mEC36/rOj/OTBsuaL2H5P2Sb/lEMApJzgpHpzShfO5QszdDD1sOqSv+iSRiGFmB5USRDZgs1jkzniqJvpENJSyTP46Tq4Q+cyWGgRYLtxcITHNuqmemjq8mDEWmevpaLGo8HXVAxRHj4gr1TfdJ3E1KwQADssIi1UlCQtnV0g8FsHE9vzuEMtVbWCMDxYL3TXjdUwY8mCxkNBiEQDkhY5HnYSF/QrJ1Lw1DlUKvRTIUl0h8uGRA4G0ZuRyhTTFo2jKpJcV6w5RJ6PNXf05VxCVwNViYUZLuz9Aj63eCgB4ds1ORzHgBXXlLq+vU2aIFbGOzPfsrJ58rpDRBcTIuAWdAVZ0eilpb/K+i8ciZo2WILpCsisOpq+F013r5ApRgwBzrUyrhVtJb1UkxaKaKyRHjIXaX52j0hNnpYtkmbWBpNswGjFdeLmqbwphf8YOnZQWFu/s6Cs6Q8yt0Bxg9c+6nMLCGp/H+FBmPKuORbO3OhZZFoscwZsB0hX1KyzkAC4tFnKicBqkpo5xFxbq8OAWY6G6SPSJyYyxECJndG8h2xA7oQ4wwylR9Wh5tywYL64QteT3fSs3FfX/1QlWRtG/5XB9reDN9DWMOQiLfOmmhWQouK20gMIEihvOMRbBtViofTucck6XdrIYxaKWcApCFpSOfh7OrpCIPUskR4yFNN3HMnFKciFSyTgLpx1FrZRT93bohbVGjoibz8w7Re5lk+s5MuMsHCzQEjW4fnQBtS/c25P+Lhetcs+SweGUab12QneZO46L5mcX3TzfqVthIW/mhBQWZrBO9tWZmjGV57JYRAxvFgs5OAwk5Q0TzXyOdbzTDWKlbhUnCPTdVKvtDlGH1YjNFZKpUpkjg0Ltg7+9uLGouBP1gbUsFu7X17JYZKf55dqEDADGZgYmLytnt6AzAIorpHhRaGaFRCOmD3y7hx0oK40UdI0x+34uTpfaLX8/yHEWbq6QiO4KUYaUuNIXbhaLWDS9ydXEjvR4Ucnn3ClV2tw+PYfFwklEysn/nZ3FZYa4pW0DVtaMW+0aQImxiPpTDVQXOi3KFu65atPIcUqOIU7ZcsFz9NWxsJDBTk1xewW7gi0WihJ1W7k2qK4QbcUbz1gskjmCNwHrxiq2RHG/poo3VltYuJys9D26WSz6h5K2v725dQ9e3thd8P9XJ9j9x0rhuCfLH28VyCreYqFGledzQelFhlTMlFMfgjcTsYhtB0q9dHC1kf3UmFl5A+ln1msdCwDYN1NsKWjCQgjhEIQqg4OtV/SsENXyqafJ6+nr0gr3RgUDtWX8aNQmLPKnnDqJaSkscrkrcrYlhyvkoPGtAIDVW9yFxaAi1OT+JT39wzmtC7nQXTPRiGFmpO3JJSwy7ZAWHOcCWe4iqlrUrbCw0g3TylEOuE6RtVJYvLt7b5bPUt1zxG0zKjUrxEo3TX+OHAjsm3Jlf06pBX/kVtnSPFx1YaH87OQKcYuxkJNqQ9TARw6fCAC4+am1Bf9/1WLRObIJDVED/UMpbNLcAnoqnC4M1b+5MWpEHIacwPNtIZ3DhCtjLHb65AqJRgwz46jQ+2o4mcLFd7yAj/3iibKsioc1i2L6fwo4VVR0q6QfVIuFc2ZL+rueFRK1CQs1K0RzhaTkCjv9upfJ02+c9ucY5yHl1EkEyDH39SJT493qWADAQRPSffPW1j2uqdvDilBra4qZY3ux7hCnbdy97P8jg62lQOvaO5S1+OG26QFCuiKaE2nVKC+g0xwxsrnBnPDWartBqia3qJc6FuZKwz4QpAtkuVNqiWLpCpFm/6oLC1vwpkNWiIuw2JspWzwiEcMF758KAPjLio0FmykHZYxFNIJY1IqzeFWzfugFsuQAM6DkueervBmLRkxrQ77r55YVAli1LEpzhdhXtmYqXYFiZeWGLvxlxUas3NCFPyx9p+j2uJFMWQJIdu9QMmU+I+qE62ax2McUFsGKsXCyWlkFsuzxWOqpqRYLPejcdIVkOuvAzORZydRyK47Aes3LZnBOrpAjOjsAACvW7y6uLXKbcpeMoRHxKAaTKdfdfYeUdFPDMEqOb3KqT+Nl/x/TFZLpx5QA9gzahYh5NwVIWdStsJBpPM3SFSJ3qnQYpAzDsNwhmh/ezBCFu8XClm6qF8iKZRfochonS7VYSBOenEDXV3sV5xJT0p6n/LW0vCRiERw1uQNH7NuOwWQKf3puQ0H/Xg+KcivKY26bLjch0ywW+awVkjEe4yzc8u8Bb4N0Pga08y72vlqn+L7vKzLOJRfqHi2yrQPDKcdVcb4Yi3erfa9r6OW8AdVEbr2mV960u0J0YeFssXh9c0/F9gdymjzH59kdGsiOYwKAI/ftAACs3dFXVN0Wt71CgLTYmJ7pn9dcLCIyvVnWCxldYnyTk1VGxll057BYyOvb2thgWu/cUvFZxyIAyAuW5QpxuTb7Z4TF21qchbrCdPO166sQwBIycUV05BoAxpY4qcgJWZoB3ZR6pbBV3lRel5vzuJkcpUBqbIjCMAzMPWISAODFDbsL+v+6sJApbqvedbZYyAFBj7HIZ62QeJ3Ac7lCzEC4EvZQUNNsASWwtMD76p0dlhVgw669Ra8s3VAtRbKtaWGR/nvENgE7f4bc0GrD7mDVsshlsbClm2oxFvbgTft9aJnu069PHTMCsYiBnoHhigVwOhV3K8RiYatn09xgjrnF3Fu5YiwAu/BywsqySZ9MqRYLJ9eMdIXkqk2kjlNu+5xYcX5FNa0s1K2wkBN7syYs3G5EtwBO9aK6ZYWoFgtzE7Ihe4wFoKxWHT6j9BiL9P+bkREW63furWotC5srxLbCsYo2OQmtAcViAQAHjHMvbpULK903IywyRXle1iwWso+koCjWYuFdWMD2f1S8VjLMhS6oZIxFoZub6XELf1pemMUoH1aQadTMnBocLswVMqG9EREj/b5S3Ed+o9ewAKzVpu28IoYthd0WY+FS0lvGc8VjERyYmTxLKTRVCOa962Sx6HHPPHJ6HwDMnDwSAPDs2p0FtyVXjAVgLbBcLRZJuwAfU6Ib0ilLpRBXSCIWcXXtcROyAOHmCnGbJ6a6FMmSFzWXxSJms1hk/r9mugTc9w8ArNXq9j0DBa++hpIpcwU4dcwINETThYMqvUmRii14U/lZDkT9QylHE6HMbklkJptpY61U4EImWzlwJDRXyKauftvg4bZXiMwqyZcRIrE2xcptbXAy9UtGK0GgxRbJkq4QmW0xssh9aGRp4TMzAbS3PbMOS97wb3M7KYQbGyK2lHB1wyqJmyukIapUWQyQO8Tp+ZWnoP6luSGKxpiVFWOLsYjprpBU1jFHdKbF8soNlRIWTummCbQkYkimBN5y20HYIcYCAE6YPhoA8Pjrhd9XudK2AUtYuMWgqOm7QOkZWU4WlDZTWOTPColHI6YF7rK7XrI9rwzeDBAyeE8Gb5rmOJfj3SwWasCSa1aIww6FehBd+rPc/YKjW+KIRgwMp0TB7hA1k2VEIoZOmSO+o3pBbbYsGOV8GxuiZgCn0yQsLRaNDel+m5hZlQ4lRUEld2WfJDKf05KImaZXNX3VbXfTXOnJTnjdVdEyC2f/LRaNYGJGeOX7HDf2KhM2UPwGd3sG0sJiziETcM6xnQCAm5/yHsQphMCmrr3oHRjG9//6clZmT7/i8kooRezkbeNUG8aJIAZwOrtC0ufQp5jFWxtjtnTbmEOMxXAqvcuuTJ9XrRpHZOIUVvrspnJD3f5cEokYOHSftGh3c1e6bbx34vSxANLPY6Huv1yxSoDiEt7Zh77B7IldX/iZgdNFWoydXJxWVoi7xUIG3TfGo2bF0L1DSVy/+K2sY+kKCQAy3VPGWEjcfOZTMkVVdvYO2nKJzRxiuK9eYw6uEEk8Zv2ea8XdEI1gv4wgeHNrYWZ/GV9hGOkVujwXPcOlktjTTe19IlNinXzDusUiFo2YboZC9kboy0ywzQ3W9T8k4w5RB2J9s7osV4hHZaHuqpiLfL7hAzLm7TeKTCOULrimEi0WcpXV2hjDJ49OC4vl7+z0HCh48R0rMGvhozjkew/h90+txff++rItKE0N0lWr48pPt+/66f5/5DPjtlquBs6ukDR7BqxFQCwaMQUgYI/HUgXEYDKFwWG7yw6wMite2tBVkRgTKdZlbSDJ4RmB86KL5STlIEiAtPtBipKlb+0oqC25YpXkZ48eEYcQzuOpHrNiujKLdYVoG60BQGsiv8Vir/K8yvR6wF6fxJqDgqMs6lZYSEXarD0EbgP6iETMnPBUq4Va0MjTtunanR53cIW43SAynuDNrYWlkJmr81g6dUoKi+paLNz/dsD49Hm+tin7PHWLBWAJkULKF/cPykHQ+pz37T8KAPDwK1vM1+QAY7lC7JU3o/k2CsnQqZQRzjX5Ck3I6EzP3ANvFCguJXs1YVFsjIUMOGtrjOGwfdqRiEWwq2/I8wT+2Gtbs1576q3t5s+WRSlqCYtk0tFVlCuAdsbE9MT06qbCi6iVC+ciX+nv+o69iQZnV4hqyegfSioWC+uY6eNa0NgQQc/AcFbQud8MDqesMbXBvliTm4q96BLrkcxxz8v3vlXg/Z5rrxCJtFo4CR7dtSTHmE1Flkh3SsU1YyxyBG+qz+sB41ox+6C0FUe6jAFumx4ohrTgTUmua+PkDlEtFu7ppsq26drVV82bcjBtiOUWFoVOKr0ZU19LRiFPGZOe5NaWebDJhblxjsOpHjLJ3XRqiSRrYC1mz4s+U1hY1//kA6Xptcu8rnJA0IM3B0yLhbf/t09HEwwjPVDkqhmRyx0GWMKi2PoEpiVAExaFFt2Sq6yWRAPisQiOzKyOn/MQaLe7b9AcTM85thPHTk0LOjX6X7azMRY1xbfdFWJ9Xq7J4+AACotcrpBezSzvFmPRELUsOXsGhpUS1NYxsWjEnJjL7Q5RtwzQLRby3nhlY1fW1gIAHONmJOY+PgVanJzcMjqz9k/HcDiJXD0YdkJ7ZowpWlhkxJMt3TR/gSzLCpRuxwkHjAFgjV8qAdIV9Sks0j5Je4yFJFdZ1OmZlbSakqiaZt1Wr04xFhJ1IJC1G1oTDY6fY1ksChMWe/rtwmK/AFgszI1zHP70vswD/+hrW7Mi2geG7UGXgJItUcDkqK/cAStXPSWA3syDK1eCbummXrNC4jErPiJXmWIZOO82Wcr8+0LvAUmWxSKT3tszMGyrJpqPPYorBADeOyUtDpat3ZX3vfK+G9eawMJPHI5PzNwHgD22xUorjtjrWMDBYpHjEkhhsWHX3pwb21USR2GR+a6nHqqWuQZNxcrnuW8waStBrXJUJrPin69uQTnpGxrOtNGwpcUC6fiifTqaMJQUeO6dbOGZynHPy4J+hWZ95RIrktMPnQAgvVuyvsga0lwhUlj0DAznTA91w8mC4iUrxIyxyDyvciGsCgsRQJNFXQoLdQMpPcYi17U5er/0Q7pceTjUSGj3kt45XCHKQ9itDdY6xQoLc3WZ+dwpozMWix29FSueo2M9C9l9NrOzA0d2dmBgOIVPXPeULQXUFBaKIBhl1r7w7v+UD6zqCmtsiJjXUD7sctBzK5DltY4FYLlDcgUS5vMNy3tgU1d/UVtKWy6g9Hm3NzWY/8urO6R/yJrI5L16zJT0s7HMg8VCZiPJwEqZ6rtKsRRZMRZRm7BwmoRyxbm0Nzdgn470/3ktIFYLpwJZpsUiS1hY92dcs2TKe9fNYgEAHz8qLdoefmVLWXc07h3IFuoSwzAwa1p6sfCUQ6yEmXnlMBaoWV+FxInki1UC0iL9lBnjkBLAdYvswZCmsIhYwd3Suvfm1vSeQj958DV89oZncPuz6/Ju4uccvGnFWDz22lb8bsnbWVtG6AsBec33Dln3CdNNA4JaHz47xsL9fcdkVmWrNnabkcRqHQsv6ab6ja5uUCZXVC0uwmL6uFZEjHTKUyFmf2l2lpYQmYI3MJzCLpcqbk786bn1+Ngvn/Rk7s5HrhQpwzDwm88djRkTWjE4nMI9z79r/k2NF5GYcQK93s/FyWJhGIbtYQcsi4Uc9OQ1HtJiL7wgXWluufOAEmPhMiC2NzVgYmb1VEwAZ79iCQDSwihfUTIdKWgihiXMZc2BdTv7XCsDSnZmrpO0EE0f34KGqIHdfUNmwK6abmpzhWQ+Q+33fJsvvWdi2srzSkCERa4CWd+fewgA4KunHADAfp/rdXKkxaJ3YNgxKwQAZkxow5GdHRhOCdz/0iZ/TsABS6g7j13H5xIWDoW1JPuObEY8GsHAcKqgQl/56lhI5n1gGgDg7hc22KqDynRqWQkYAI7YNy2AX1i3C397cSN+tegtLHljOxbc/RI+89tnclr8nFJx5YaLG3fvxYW3LMflf38VP37wNdv79IBYOV/1DmRbLIJjryhSWPzyl7/ElClT0NjYiOOOOw7PPvus3+0qK+oNoPsDcyncfTqaMKm9EcmUwIp1uwHo26a7CQt1dWX/WzRq7QcgB5y2RmdXSFM8aq5YXyogN32PZrGIx6y9K7wKlJ7+IXzzzy9i5frdWTe/V3b1DuKZt9MDS64YCyBd9+HsY9LZBmq2h16HASgus0EKQ/36qylg6i6UWVkhycJcIYBlls4lzPKlyQGWO6TQOIvhpBVg11RC/8ktsMe0JEyLTXuTZRl4dXPuCVxaRkaNSPd1IhbF9HGZyT/jDlErrKpZIU4rv3yTR9DiLJxLeqe/H3/AGLzywzm45LSDANjvc90aMUIRFnKiUWMyJKfMGAcAeH5dfjdVscjnSV+oSaTF4qUNu7MsbbkClqMRw4wJK8QdkmvbdJWj9xuFIzo7MJQU+IcStC3rVchxErCe3+fX7catT68DkN4YsDkexbNrd+KOZetytCf93V7uPC2s+waT5rh205NrbddJCrYmzRWixqoE0BNSuLC48847cckll+B73/senn/+eRxxxBGYM2cOtm7NDoAJKlaOcrY/MN8K9GjNl2ypxRwFstTdTTVZHtN2MATcXSGAZTZ+qYBqerLmgExvAqyAR68pmqqJe9naXQXVjJB86Q/L8anfPI0HXtqkVBl172+ncsByJTEinh0bUUhmgzS166bbVqV+v7qyjGnbpsvslEJcIbOmjYZhpPvvf/+x2vEYt5x+lYMysT6rNcuHEAIPrtrsmjXUrwhqdcKSFh+vVQWlGFUj0wGryNgrebaxlwJmpDJoS1+6jD/pV7J/ZKDuYDJljqIRm1jPZ7GQwqJyG3Llwslqrj4H6qrflm6quUKksNgzkMS7u9P9Nikj7lRmTu4AALyQWQyVgz6XVFPJxPYmTBndjJQAlr9jFzhWoKVbJlThcUVeXCGS0w4eDwB48k0rK0k+C7LiJmBZ5f62ciOeXbsT0YiB+/7zRHwjIwLvUiyrWe1xCCYdNSJuywqUnH/Ds0ilBIQQWZZV2b99qivEw1haadxnMBeuvvpqfOELX8AFF1wAALj++uvx97//HTfeeCMuu+wy3xvolU1d3ktUy5ShhmjE9KFJpE/PjfdOGYm/rdyIv7+0Ef9y9D7mIJu2WLgEbzpsQmb+Holkbn6r7SMS7pflsH3acffz72LR69tw9jH75myrZOPudBtVF8v4tgRe2QQsW7PTzDQA0juF3vDEGsw+aCwu+dCB5uv/fNUuHP/43AbMPWIiCkGW5r1+8Vv47tyDAeRW2VJYbOraa8YlSHO2DKQFrIlxU1c/1u/s86TcZQCWvsKSwmLdjj6sH22ZXuWllcJQvt/NSuVE56hm/MtR++LPyzfgD0+/g389pjOrrdK6lOtjZanmh1/Zgv84car5+t9f3ISFD7yGiAH8/oJjzclaIl1Fsp6JZNrYFjy7ZieWv7PLjCPKxeqMpUSuuCTvmdiGh1/ZgufX7cJpu8a7vl9uCiZjYwCrzsdrm3uwYVefWStGjbFQixOpA3K+oFMpeFZv6cG6HX2OJvdK4lTx1u2ezWWxaMkEnr+7ay/e2poOPpSF2FSO6OyAYaRF24r1uzGmJZ51TKnIEu96zJrejrU7+vDM2/YxR8aHuNZuyRy7+PVtZsBlPuSK3svjKQuJvbKp2xxnZOr6aKWvjuhsRyxTpBAAPnDQOExob8RHjpiIH973Clau342XNnRh5Ihsi7N0R+sVY8e1Jcy+O/Pwifj7i5vQMzCM5et2YUxLwhRIjQ6uENlWGZcTJItFQcJicHAQy5cvx4IFC8zXIpEITj31VCxdutTxPQMDAxgYsAaE7u7ymCM/9osnC65I2RCNZPkk5SDkxskHjoVhAK9v2YMTfvyY+bphGLY00Xg0YkVq53KFGPYboqkhmjWAqEhz3Mr1u23/3wstimCZNrYFj63ehl8tegu/0gKXAODu59/F3Q4KfN+RTdiway9+/OBrRbtEVm7owr9cl75fcgoLs8rk3qxznTHBuk4HjGtBR3MDdvcN4cSfFNYnjVkWi/Sg8L2/vmx73axjkblfZJyElxWRysJPHIa7nt+Qt625LCEy//7d3dn9AqRXa5+70d09KeuZSI7sbMftzwL/t/Qd/F8BW6BnWSwysQz3vbgJ972Y35+vWiyksPjz8g34s7LviFrS+3dPrDFf33dkk3kNpHB2o3NkM0bEo+gdTOKknxZ2f1QKV2GhuDb0hYucxH/2z9fN12SAsEpbYwMOGNuCN7buwVm/fNKH1rrjZrEA0i6pv6zYiOsXv+VYOdLN8iTTVZe8sb3gMc/L4zljotyYsS/r81WLRWtjA95/wBgszpQY/9ys/QCk3bYHjm/B61v2YO4vniioPXI8BYCvzJ6G9Tv78OKGLpx9vX0+lfeBFBY7ewez2hogXVGYK2T79u1IJpMYP96+Ghk/fjw2b97s+J6FCxeivb3d/Ors7Cy+tTlIZAagQr4+duQkxKIRfOTwiUjEIhjXmsCZh+Vehe83egS+cOL+5oCXiKWr433kiIlojscw/9Tp+PqHDsQlpx2I5ngUh0xqM1eYQLpM7bjWBBKxCCa2N+L4A8bgrCP3MT9LRnG7cfi+7fjSSftjRDxa0LmOaUmYvlYAuHD2NBw0vtXxWACOr8+Y0Irbv/A+zJjg/L58X+a1Ul77aGZ3Uicmj2rGrP1HZ33OSQeONSciIB0z8p+nTC+4T963/6gs0/GHD5uA1saY7bjTDh5vmiJnHzQWo0fEkYhF0NQQNffK8EpDNIILT55mu3/0r3GtCTNf3YlDJrVjziHj0aa1MxGL4KDxrRjZ3JDzvD8+036PnTJjPKaOGVFQ340aEcecQ+yrx1nTxuDA8S2e3r/vyCYzoA8ATjpwLPYd2WQ7Zp+OJrxv/9H44HvGYVSmzxOxCFoTMcw5ZAIuP+tQTB7VbJYUdyMSMXDe+/bL2eeV/mpsiODU94zDPh1N6GhuwAdnOFt4jtt/FPYd2YTD923HtHF2C9ScQyagQ7nW75nYZk7COl/94HRz3CnXV2sihg8f5m5RmHPIBExqb3R871GTO9DpYG0B0s/c3CMmFdyezlFNOGa/UTnvDSAtHj582ISs9x/R2WGzjALADz56CE6cPgbzPjANJ2Xq3gDAf595MCa6nFuu5/qbcw7C/mNH4KIPHIBDJrXj0++djJaE/bn+yOETTavdviObcezUUVmfPbY1gROmu48ZlcYQBeQbbty4Efvssw+eeuopzJo1y3z9W9/6FhYvXoxnnnkm6z1OFovOzk50dXWhrS23dYAQQgghwaC7uxvt7e155++CXCFjxoxBNBrFli32YitbtmzBhAnOSjWRSCCRSDj+jRBCCCG1RUGukHg8jqOPPhqPPPKI+VoqlcIjjzxis2AQQgghpD4pOCvkkksuwfnnn49jjjkGxx57LK655hr09vaaWSKEEEIIqV8KFhaf+tSnsG3bNnz3u9/F5s2bceSRR+LBBx/MCugkhBBCSP1RUPCmH3gN/iCEEEJIcPA6f9flXiGEEEIIKQ8UFoQQQgjxDQoLQgghhPgGhQUhhBBCfIPCghBCCCG+QWFBCCGEEN+gsCCEEEKIb1BYEEIIIcQ3KCwIIYQQ4hsFl/QuFVnos7u7u9L/mhBCCCFFIuftfAW7Ky4senp6AACdnZ2V/teEEEIIKZGenh60t7e7/r3ie4WkUils3LgRra2tMAzDt8/t7u5GZ2cn1q9fzz1Iygj7uXKwrysD+7kysJ8rR7n6WgiBnp4eTJo0CZGIeyRFxS0WkUgE++67b9k+v62tjTdtBWA/Vw72dWVgP1cG9nPlKEdf57JUSBi8SQghhBDfoLAghBBCiG/UjLBIJBL43ve+h0QiUe2m1DTs58rBvq4M7OfKwH6uHNXu64oHbxJCCCGkdqkZiwUhhBBCqg+FBSGEEEJ8g8KCEEIIIb5BYUEIIYQQ36gZYfHLX/4SU6ZMQWNjI4477jg8++yz1W5SaFi4cCHe+973orW1FePGjcNZZ52F1atX247p7+/HvHnzMHr0aLS0tOBf/uVfsGXLFtsx69atw5lnnonm5maMGzcO3/zmNzE8PFzJUwkVV111FQzDwPz5883X2M/+8e677+K8887D6NGj0dTUhMMOOwzPPfec+XchBL773e9i4sSJaGpqwqmnnoo33njD9hk7d+7Eueeei7a2NnR0dODf//3fsWfPnkqfSmBJJpP4zne+g6lTp6KpqQnTpk3Dj370I9teEuzn4nj88ccxd+5cTJo0CYZh4N5777X93a9+ffHFF3HiiSeisbERnZ2d+MlPflJ640UNcMcdd4h4PC5uvPFG8fLLL4svfOELoqOjQ2zZsqXaTQsFc+bMETfddJNYtWqVWLFihfjwhz8sJk+eLPbs2WMec+GFF4rOzk7xyCOPiOeee068733vE8cff7z59+HhYXHooYeKU089Vbzwwgvi/vvvF2PGjBELFiyoxikFnmeffVZMmTJFHH744eLiiy82X2c/+8POnTvFfvvtJz7/+c+LZ555Rrz99tvioYceEm+++aZ5zFVXXSXa29vFvffeK1auXCk++tGPiqlTp4q9e/eax5x++uniiCOOEE8//bRYsmSJOOCAA8Q555xTjVMKJFdccYUYPXq0uO+++8SaNWvEn/70J9HS0iKuvfZa8xj2c3Hcf//94tvf/ra4++67BQBxzz332P7uR792dXWJ8ePHi3PPPVesWrVK3H777aKpqUn8+te/LqntNSEsjj32WDFv3jzz92QyKSZNmiQWLlxYxVaFl61btwoAYvHixUIIIXbv3i0aGhrEn/70J/OYV199VQAQS5cuFUKkH4JIJCI2b95sHnPdddeJtrY2MTAwUNkTCDg9PT1i+vTp4uGHHxYnn3yyKSzYz/5x6aWXihNOOMH176lUSkyYMEH89Kc/NV/bvXu3SCQS4vbbbxdCCPHKK68IAGLZsmXmMQ888IAwDEO8++675Wt8iDjzzDPFv/3bv9le+8QnPiHOPfdcIQT72S90YeFXv/7qV78SI0eOtI0dl156qTjooINKam/oXSGDg4NYvnw5Tj31VPO1SCSCU089FUuXLq1iy8JLV1cXAGDUqFEAgOXLl2NoaMjWxzNmzMDkyZPNPl66dCkOO+wwjB8/3jxmzpw56O7uxssvv1zB1gefefPm4cwzz7T1J8B+9pO//vWvOOaYY3D22Wdj3LhxmDlzJn7729+af1+zZg02b95s6+v29nYcd9xxtr7u6OjAMcccYx5z6qmnIhKJ4JlnnqncyQSY448/Ho888ghef/11AMDKlSvxxBNP4IwzzgDAfi4XfvXr0qVLcdJJJyEej5vHzJkzB6tXr8auXbuKbl/FNyHzm+3btyOZTNoGWgAYP348XnvttSq1KrykUinMnz8f73//+3HooYcCADZv3ox4PI6Ojg7bsePHj8fmzZvNY5yugfwbSXPHHXfg+eefx7Jly7L+xn72j7fffhvXXXcdLrnkEvzXf/0Xli1bhq9+9auIx+M4//zzzb5y6ku1r8eNG2f7eywWw6hRo9jXGS677DJ0d3djxowZiEajSCaTuOKKK3DuuecCAPu5TPjVr5s3b8bUqVOzPkP+beTIkUW1L/TCgvjLvHnzsGrVKjzxxBPVbkrNsX79elx88cV4+OGH0djYWO3m1DSpVArHHHMMrrzySgDAzJkzsWrVKlx//fU4//zzq9y62uGPf/wjbr31Vtx222045JBDsGLFCsyfPx+TJk1iP9cxoXeFjBkzBtFoNCtyfsuWLZgwYUKVWhVOLrroItx333147LHHbFvbT5gwAYODg9i9e7fteLWPJ0yY4HgN5N9I2tWxdetWHHXUUYjFYojFYli8eDF+/vOfIxaLYfz48exnn5g4cSIOPvhg22vvec97sG7dOgBWX+UaNyZMmICtW7fa/j48PIydO3eyrzN885vfxGWXXYZPf/rTOOyww/DZz34WX/va17Bw4UIA7Ody4Ve/lms8Cb2wiMfjOProo/HII4+Yr6VSKTzyyCOYNWtWFVsWHoQQuOiii3DPPffg0UcfzTKNHX300WhoaLD18erVq7Fu3Tqzj2fNmoWXXnrJdiM//PDDaGtryxrg65UPfvCDeOmll7BixQrz65hjjsG5555r/sx+9of3v//9WSnTr7/+Ovbbbz8AwNSpUzFhwgRbX3d3d+OZZ56x9fXu3buxfPly85hHH30UqVQKxx13XAXOIvj09fUhErFPI9FoFKlUCgD7uVz41a+zZs3C448/jqGhIfOYhx9+GAcddFDRbhAAtZNumkgkxO9//3vxyiuviC9+8Yuio6PDFjlP3Pnyl78s2tvbxaJFi8SmTZvMr76+PvOYCy+8UEyePFk8+uij4rnnnhOzZs0Ss2bNMv8u0yBPO+00sWLFCvHggw+KsWPHMg0yD2pWiBDsZ7949tlnRSwWE1dccYV44403xK233iqam5vFLbfcYh5z1VVXiY6ODvGXv/xFvPjii+JjH/uYY7rezJkzxTPPPCOeeOIJMX369LpPg1Q5//zzxT777GOmm959991izJgx4lvf+pZ5DPu5OHp6esQLL7wgXnjhBQFAXH311eKFF14Q77zzjhDCn37dvXu3GD9+vPjsZz8rVq1aJe644w7R3NzMdFPJ//t//09MnjxZxONxceyxx4qnn3662k0KDQAcv2666SbzmL1794qvfOUrYuTIkaK5uVl8/OMfF5s2bbJ9ztq1a8UZZ5whmpqaxJgxY8TXv/51MTQ0VOGzCRe6sGA/+8ff/vY3ceihh4pEIiFmzJghfvOb39j+nkqlxHe+8x0xfvx4kUgkxAc/+EGxevVq2zE7duwQ55xzjmhpaRFtbW3iggsuED09PZU8jUDT3d0tLr74YjF58mTR2Ngo9t9/f/Htb3/blr7Ifi6Oxx57zHFcPv/884UQ/vXrypUrxQknnCASiYTYZ599xFVXXVVy27ltOiGEEEJ8I/QxFoQQQggJDhQWhBBCCPENCgtCCCGE+AaFBSGEEEJ8g8KCEEIIIb5BYUEIIYQQ36CwIIQQQohvUFgQQgghxDcoLAghvjB79mzMnz+/2s0ghFQZCgtCCCGE+AZLehNCSubzn/88br75Zttra9aswZQpU6rTIEJI1aCwIISUTFdXF8444wwceuih+OEPfwgAGDt2LKLRaJVbRgipNLFqN4AQEn7a29sRj8fR3NyMCRMmVLs5hJAqwhgLQgghhPgGhQUhhBBCfIPCghDiC/F4HMlkstrNIIRUGQoLQogvTJkyBc888wzWrl2L7du3I5VKVbtJhJAqQGFBCPGFb3zjG4hGozj44IMxduxYrFu3rtpNIoRUAaabEkIIIcQ3aLEghBBCiG9QWBBCCCHENygsCCGEEOIbFBaEEEII8Q0KC0IIIYT4BoUFIYQQQnyDwoIQQgghvkFhQQghhBDfoLAghBBCiG9QWBBCCCHENygsCCGEEOIbFBaEEEII8Y3/D/9+uICSCwG0AAAAAElFTkSuQmCC", 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" ] @@ -894,41 +1119,43 @@ } ], "source": [ - "trivial_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", - "trivial_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", - "trivial_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", - "trivial_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", - "trivial_ep.plot(x='t', y = ['act'], title='action'),\n", - "trivial_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(trivial_ep.rew):.3f}')" + "plt.close()\n", + "ppo_2_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", + "ppo_2_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", + "ppo_2_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", + "ppo_2_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", + "ppo_2_ep.plot(x='t', y = ['act'], title='action'),\n", + "ppo_2_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(cr_ep.rew):.3f}')\n", + "plt.show()" ] }, { "cell_type": "markdown", - "id": "3b22995e-d65f-4aa8-a6a0-94422fc6d346", + "id": "1088ac23-94aa-4567-8a1f-6aa15f6e4ecc", "metadata": {}, "source": [ - "## Some side by side plots" + "## Trivial (no action)" ] }, { "cell_type": "code", - "execution_count": 63, - "id": "fd00e2e7-8d98-4e68-9161-4dd86376249e", + "execution_count": 49, + "id": "0a890b9b-c1c2-405f-a506-f74aa3fc43a9", "metadata": {}, "outputs": [ { "data": { + "image/png": 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P7dwWX2w8jJyluyIuf/Ur3+LpBVvxYcF+AEBFXRNWFZVLOdzW/9yQ8SbuwXnrVS8ruvhmBi+5W0tw8bNLsOuI/E+xT7a7ABSZfKcsGfX+yn2+f0t4zXC94F0efI7VNsrbxx/MPx+hQ1oy7n1vLQBgRL8uUT+3vbgKAHDlS8tw4FgdXrxpEK694FTzCqqDiHMjHk4v0d1Gd71VAOBEHp/M2PIiMQlvOFzHyrvOHSVV+NMnJ2ajDd60jHfArufCc+xIVYOquqM1b+PzDfIlK8t0Jhgti+hDzL9VyoouwDpJA3oGLxJzYb0qla+2lGDoU4uxbOcRS7Z3pCpwJlq3dBs5+Th1ctkjccPMzf6BvN7iyXIvYOb+1TpUuqq+SfNnYj3t3i4MXihuTXy7AEdrGnHbm6sMrUf39OVRKteZi3egos4ZyaOSXCPoB7JctI1QIvxb/1rsI3ruGb05L8dqGnHetEW4/IVvNG1P1uCFOS8Si5So1uTx4rkvtuGiM7riJ2dnWFwqCpYAddVkSDdRlGVnLt6JvUf5tGazyZgMapRbWvTcwsxDrFlDzsvKoqMAgH3l2uqVJhPnkjFCypaXa6+9Fp07d8b1119vd1FsFemgf3nJLryxvAh3zimwtkBkqdV7yu0ugipOvvy7MHbRTMZd4B/o680FM7sFSm25zNy/2gILfSWRNRdPyuDl/vvvx9tvv213MWwX6VD7z5oDlpaDotN79x6rJUbPxGN1jR489NF65G4t0VWmeCPjhdsozQ/8lHAn+LceSXrtVF0u0a17eruN9D+dW05SBi9jxoxBhw4d7C6GtIITP8le+qsm8dXCP/O+x0drDviGPFJ07uw2Mu54bSPeXF5kX13jgKHSdl3U/QM7LUOlnZ74HEx48JKXl4errroKPXv2REJCAubPnx+yTE5ODvr27Yu0tDSMGDECq1YZS5h0LRdWrG5kRsKuXsUV7npAH2mnKIrhJNH75xbiL59twYQ59tTNkl4vA6juNjIz50VTy4vu8EXn58wlPHipqanBoEGDkJOTE/b9efPmITs7G48//jjWrl2LQYMGYezYsSgtLRVdFMdj6OIMei8UclYJ7hZ8veE5Ft43O1qmD7BrevjAnBfj6zCD2tWbO8Ou+S0vsj5NQvhoo3HjxmHcuHER358xYwYmTpyICRMmAABmzZqFzz//HLNnz8bkyZM1b6+hoQENDSeaNisr5X0Wg1aRDnqOJpCMyloh+HeTNRFOKyc3EDq57JFoznmRMIQLyHmxub6LdJ6qznkRPVTa799NGiILmVqIRbA056WxsRFr1qxBZmbmiQIkJiIzMxP5+fm61jl9+nSkp6f7/uvdu7eo4trO/6Dfd7QWN87Kx5JtkRMxvV4FBXvKA555QuYT1RgrayXhJqEVuHwXbqPsvtiLIObxAObuB7XrNzNA9mjJedEdvMh5PFkavJSVlcHj8SAjI3BukoyMDBQXn5iiOjMzEzfccAMWLFiAU089NWpgM2XKFFRUVPj+279/v2nlt9MfP1qPVXvKceecgogn9vur9uH6Wfm45fUV1hYuzrntjsbNQrqN3Be7uOK4CpikTtLvo77lRfR2/RJ2teS8uKx7W8pJ6hYvXqx62dTUVKSmpppYGvv4V6xlNSe6xiIdTB/9MIR6w4EKE0tFwdxWKVjN61WQmGhPFOHC2AWAtqBMxgDO/wKt9zyRJegxc0SbplYRl91kWdry0q1bNyQlJaGkJLDro6SkBD169DC07pycHAwYMADDhg0ztB6Z+B9rqg4gWY8yl1NbNwUHObI2x1pp6fZSDHpiERZuOqzr85sOVnCEVRA3zPMigvmT1KlbTvyDGbWXwUg5ZO2GtDR4SUlJwZAhQ5Cbm+t7zev1Ijc3FyNHjjS07qysLGzZsgWrV682Wkxp+FcqAXcivOhJxaV1v2pGLn4T/rUaVQ3NuOfdtZo/u/tINX7x8nJcOD039sIRuPHC7YbaQcQMu2az66IesG80fE53C5Ccu198t1F1dTV27drl+7uoqAiFhYXo0qUL+vTpg+zsbIwfPx5Dhw7F8OHDMXPmTNTU1PhGH1F4qo4fN9bEDqC2UohV2claScdiV7E3HjTePSrjSBujnHIcbS+uwucbDuHuS09H+9TIlyLd3UayXHVNPMSsaHmJm6HSBQUFuOyyy3x/Z2dnAwDGjx+POXPm4KabbsKRI0cwdepUFBcXY/DgwVi4cGFIEi8FVqzsNnIf/lz2c2O8r/WwsiuAGzszDwBQXtuIp645L+A9EfO8mM2ubiPoHEauv+FFzh9AePAyZsyYmJH/pEmTMGnSJKHbzcnJQU5ODjwej9D12sq/2yjggCWZuK0vWSu7AoBEARt2YeziuApiY5gBBiLODVFBT6T1qJ+kzrxnG2lreRHzDDZZSPlsIz1cmfPi928n3InELZdl8TuFG1tNRHBaUByutIHnhpzfR4anSmvLeTF/G1ZyTfDidrzQycttDzxzChHdHa58MKOi8UJl8y4Idx7INM9L5JnOjX1er8C4Tss8Lzq3Z/cPEAGDF4n5V6yyHkCk/wIY8rgAEYWJIy6MO4TQnvMiH5nqu4jdRnY9HkDnaCPdLcT6PmY61wQvrp/nRcXysh5kotU3yZXXpPYiGlzZSVQ/O5KISwIDIPuF6+ZSIvxb03rNPr/UBi/SjDbSm/MiZ0XlmuDFlTkvAfO82FcOmcxfdxBnP7YQ76/cZ3dRfNz1oHnt7BqtIqLLx43BixvqCifk+Nk3z4u+Ob8SA64n6j8n6/53TfDiRgHBi2sudcY8MK8QAPCnTzbaWxA/bpv8ySn07Pbg88iV87xoPLDszvuJdXHUW/eZ/mBG1S0v5j1VWu8kdVoCEgYvZIisBxCJyxlw32XUXNxf4bXUFU7fO/JXeKoTds0sg5Zuo4CbYQ3b0LCslRi8SMz/rlDWWQ5J3ORP/Im10XNHG9zS4spuI7//O0HY0UYCuo2EzfMScf0qh0qLHm2k9/EAAevQ0m0k57HkmuDFlQm7AQe9nAcQAXrvrSStEyxlpGLX89HQbiMXctiBFXaeF/9/6w1e9H1M+PrNTdjVN8MuW14k4saEXX9qjlGH1VmuoXq0UYy/45GRej1RQO1ld76HGVqOK/XfS8Y9IFNdFmn/2DZU2n+2dZ1jpZnzQpaR9PghuG/yJysZCR6ETFJneA3y0XpY2R2/hTsPAh+HojNhV9D5FbHbSGW5hO/fgG4jvS0v7DYiE2mdpM7uSoi0kbNKsJahQ5bHe0ROrwucMFRahhNY71OlNbW8qF/UUgxeLFBR24RjNY2aP6d5kjpZjzKX052w65J+JEN5KxbnvJizErkoiuL4ukBE+aXJeTFxu3qHSmvanqTHkvCnSlMgj1fBoCcXAQC2/eVnSGuTpPqznKTOGXTPXCm4HE7UUqHq2xN8qnR4rng8gAPODtV1sjRPldb3OVl/C9e0vMg62qjObyr7suoG3evxMnqRlu66yYLfVNb+6lZGqnUR1wRXJuwqzuo2kn2odMT1q815kaAMgJGcFy0lso5rghdZRxsZuXgE3NFLegCR3I8HkLXiaWWs24gtL+FI/pOHiHUhtfvO3/CDGYU/VVrfaKMEvaON1C9qKdcEL06g5i7PP9jROy6frCXz3bvsx42RACSwW1XfN5X4p9NN676Q+fg1xuTHA6hcTnjOi86vpXueF0nvgBi8mEzrz+5/nGidEdHuOxTSJuQp06ZsQ+5jQlTCruRfU2p2hy5mdRuJEukYVT/Drnl7WO/5zQczUlRl1Q34/btrfX8bOYQlPX4I4h4PYAYrjhtDeStGPus/lYDu7dt96RZP1ouNFoHzvOhch6D9YLjbSEwxTmxXRxkAIzPsynlAMXgx0VOfbcHyXWW+v9Vc5PwPE442cgZhQ6VNIPtxY2iSOnYbReSkrxXul3PCUGm1TH08gIZldee8yLIjgzB4MdGhinrNnwmshP0fzCjpEUT6h0pbEbxIU4WHJ6rVhg8uPUHzby5hpBPYuiDnj2vb4wH8Nqy35UXLISLp7ndP8GL3UOmGZg8OHKsNeC34kFVzEEdsedFfNDKZ/m4j88la8fgYmuDOv9tIb8uLhFdug6T/zYOEfTyA/wVa93p1flDt+tWWTPhoIx1lgIGh0qqXtJZrghe7h0r/8pVvMeq5pViz95iwdfKh0s6gtm4KrqRj/R0PjEw0p6dbNR52sRu+ohO+g105L3rKABjpNpLz13BN8GK3bcVVAID56w76Xguul1XlvERKDnPE6UzR2PELSlrv+Bhp+EgUMUmd8VVIR/ODGW3eC7FyXvRPUifJUGlTH8yonv6h0hoWthCDFwupOYb9g5TABzOaUCASQnXXQ/DQaP6mBi+b2s8PPTcUTqP1Rsf2fRCzuHKeKKqHSovOeYG+yE7r1BthtycRBi+CBQQfOg7aiPO8aPwsWUd1t5ENlYCsFU8rUaON1Ca0By9m+4XbBO6oB/QlpYZfgzlsa3nRUQaALS8UQ9QfWuNBrKdyJhuobXgJmZTOgnleLJnoxUAAYmSzfv/mPC+BRF0wrQjuzBoqLUqk89SuMlr93CeJfooADF4EizRaCDBWUcp0MlMg9Qm7Mf4WUhrz1xm6Ef1bMZbz4t9txBOklebHA0R5T8STu/VQIvxb0zpMPyRUdhuJHm0UkPOi70vywYwUIqDbR8dBa/TzZD21XR/BdYA1Q6UlrXl8BI02ErAOCmXF7gk/VDr8v2Vi1zwvespg5HOydj0zeBEu8g+tboZdYzkzZD1RQ6XNYEm1IyhvRfNndQ79DFyH+4g8rOwK7kScG2ZfdO3KebG6VUrWCSBdE7zYPUldq8CEW4NHrRtrVhfSOdiIk9TB6LONTvxb98XOhU0vIn9yK26gwua8+P9b0oxdGc4tvbmQmgI7Gb5oGK4JXuyepK5VtN9Z1VBpA8eJpMeY66mt4EN+H0uiF/M3YeTyJiqngi0vJyiKtqAj6k9gRcJumN8uMK9DTmoDANGzOCsCdg4Tdimq0DklND4eQGxxyCTq6yYlyl/mBJ+yP7laWMKuDduXleZ5XqLUNHbtHhHHragjX+qnSgtYR8xlJY1eGLwIZvSk84+q3fjclXgWOtrIJUOlDbC928iFnJbzErbOdFPCrpnzvOjtNtIySZ2kPwCDF8EMdxtpXJ7sJ/VoIwu2YSwAsXa0UfBybjzHtP7m0X4CGQYN6B4OLOjgj7R/VHcbiSnGie1ynhcADF6EC5znxeDk5/bXG6SC3nlerCDrXZNoehMXXdm6KfA3t6TlJXrDi+1XT8PdRiY+3Ciek/4ZvAgWteXFwIMZVW1b/0fJAsF3albMuCv7MSGsXteZf+DC0EUo23JeBBy4ssxPIstTpfV+TtbZ3Rm8CBY4T0sgVU2wIodakyX0XoBd83gAA0QFL7q7jVx4ioUmgus/CKxomQrf8mJt64KZnD7DrqwYvIhm8JgIfKq0ts+6sB52BNXzvIQk7IovS8g2Ja+kRAXosgdpVlIUbXVH9JwXe1id12Hu+kU/VVpPGYLW4fxpXhi8iBaY8xL0psnBiKTHmOupnucl+G+XZOwamiVXWMuLzpwXF4b8sbonQ8kXvTihLlM/z4vJBdFB01BpSX8NBi+CBQx11vV5cWVxM5kqBPUtL9b/uLIn9ImapE73FOYSHUeiiHzgp33PNvLvNtLbNWIu2+Z5CWiVsmKotK5NmI7Bi2QCjhMXVqyiyLRr9JYl9FlHxssSug3x6xRJWL6u3tFGgrYvEzU5L2r3l12jsUR0jZhNhmJZMkmdzm2YjcGLYEaHSge23LixahVDqiGuaud5EXhHrJYVTb6GfgpR3UY6v6ZMh5EoavaFf0tV1JwXSyapU/uixvWaHPWoDwAFb9c/mZmjjZxPxgczGuXGilUUmXaN6nleNOciGCdpveNj9+/oxhsEBUrAtwp3CKi+8AopkXYiRhuZ3m2kcjnRx5iI0UZa9o6sdYhrghdpHszo929dOS9Gti3rUWYCmQI73aONJH/ukBVEtaDF0aGvSqxuF9UXXpuGSge+L+ePK8fjAaz9nExcE7zIwuiJ5oaDygoy3TFzhl39RP2K+mfYFVQAmagIkv13l80PlY5ZPt1HsOmHvl3dRlpLEH0dMZeVtA5h8CJY1KHSqj4v54EiHYkuOrqfbWRBDoyk9Y6P1ZPUmbV9mSiIfXrIPsxX9uMW0DLaSHS3kbU5L7L+FgxeRDM6XEjSA0U2Ml1z1Le8BOW8iC+KLYzl64rqNuI8L63UjGILaHmJugvsmmE30h8a1mvyGaZ67abuQr3DyDXkvOjagvkYvAjGlhNrOPGOOVbLSzxiy4t4bhg0IGKeF1EiBcZ2zfOipwxGPidrPcXgxUT6uo1IDZnumFX/ziE/rgUJu5IfUFYn7Mq+P0RQEyT75whFO5esyXlR95rm9Zr8W9s1V47Vj07gUOk4YfR3lvQ4kY5Md8zqHw8QvTnfjK9k911rLHZPUudGanaFDCNlohFxgRYlUvChfqi0eax4MKOsZxaDF8HUZvFH/Ly0h4pcJIpdVBcmVoIuE3b1Uz/0N/hvqY4kIRQoAd8r7GgeleuyooUz/DFqbVJq9PUY7DZy+CR1slYiDF4EM/JUaFJPpouO3l4jK1oL5Kx2ThAWvOjsNpLnKBJHzdPL1R57iZbsIJOGSptM9YgtE8ug95lemnJe9G3CdAxeBGO3kTVkuujon6TOfLJ3pwgbbaT3qdIyHUgmiZVTEv3xAPY/28jOdYjYgKk5L1Z0G0lahTB4ESygUtBRMUt6nMhHoouOqJwXM8h+PFnd8hKyfTGbdxyj3dsimTXDrunPNlK5nJlPldY9jFxTy4uctQiDF8GMt7zIeaDIxu4K15/elhcrWLFNI3eWds+w60ah87zEmkglMikSdu0pQkyqDzkzHw9gwef0dk2ZjcGLcMx5sYJUOS9qg5fgvy3pR5K05mll87ONZDqORFGTCB4wVDrKPrDrqdIi7vbNPvLtapEIaHixoFVK1vsCBi+CWZ3zEq8tNTJdc1R3D9oww67sh4fdP6Pd2zeDqoRdleuyaz4lmYZKRyLF4wH0rkPTsnL+AFIGL5999hnOOuss9O/fH2+88YbdxdHNkruWCCe524MamS46un9n5rwIG82iv+VFzPZlouZio36CNaOliS1cWUSE+aZPUqdyOcc/VVrSSiTZ7gIEa25uRnZ2NpYuXYr09HQMGTIE1157Lbp27Wp30VQxnLArbG4Cd1bMrZzY3G/FvC4h25S04mkl6nfUn/PivOMolpBdYajlxXxhu40kOnAjlUR1ACiuKC3bjfBv/WsRtaS1pGt5WbVqFc4991z06tUL7du3x7hx47Bo0SK7i6Wa0ZNOaxNdxBPLUCnkJ9MlR/VTpUOa883/lWRt8m0lbIZdQetxg9DYJfo8KtHIcJOg/zSRZLSRidGL/pwXLcvKeXYJD17y8vJw1VVXoWfPnkhISMD8+fNDlsnJyUHfvn2RlpaGESNGYNWqVb73Dh06hF69evn+7tWrFw4ePCi6mKYJ+JltanKN9rpbSFCnahbrqdJmBBqWjDYy8llh3UZqv2jgck48jrQKn/PilzcRZd9Z0vISrnwOGG2kesSWiXvRkpwXSX8A4cFLTU0NBg0ahJycnLDvz5s3D9nZ2Xj88cexdu1aDBo0CGPHjkVpaanoothClknqZB3eJo48Vx39M+yKLkmYbUp+HIibpC7KezZfnK2m6jdXGxzYNVRaqscDRHhd7Qy7Jj4ewIp5XmS9lggPXsaNG4ennnoK1157bdj3Z8yYgYkTJ2LChAkYMGAAZs2ahXbt2mH27NkAgJ49ewa0tBw8eBA9e/aMuL2GhgZUVlYG/GenwJwXY583srzs3QVGyXTHrH+GXXYbibo4qq+MAzco03EkjhLwvcIPlVa3JmtaXvR3a1kh0jkkw8Mtdc+wq2WotKR1iKU5L42NjVizZg0yMzNPFCAxEZmZmcjPzwcADB8+HJs2bcLBgwdRXV2NL774AmPHjo24zunTpyM9Pd33X+/evU3/HtH4HxR6+ou1dvdEvCuQ83gTRqZrDlte9LPiqdKBbwV1G0l1JImhJrdKbcuGFDkvuqfAF7R9w3WsiY8H0NvyonN7MrE0eCkrK4PH40FGRkbA6xkZGSguLgYAJCcn44UXXsBll12GwYMH4w9/+EPUkUZTpkxBRUWF77/9+/eb+h1IDhLUqT7qE3YlrQVsZPVTpc3avkzUzH2o9vk49o02Cv9vTet16VDpgNFGku4bK0g3VBoArr76alx99dWqlk1NTUVqaqrJJdLHmm4jJey/3T5dukx3zKKmeTHjJ5P9MBCW8xLle5q9C7xeBV9tLcH5p6bjlPS2Jm8tNgVK7OcFqVyXJcFd2IRieUTsmrdpqHRAGXS3SmnoNpK0ErG05aVbt25ISkpCSUlJwOslJSXo0aOHlUUxjfUz7JpTDtlZece8Zu8xbD5UYbgsaubfEE2m/urSqnrsKq0OeC1RUA0UvdsoSsuCgOPoP2sP4HfvrMGo55YaX5kAqmbY9Z+lNVq3kW0z7PrflOlch6BjP3LCrjrCW14EtEpp2TXy1CCBLA1eUlJSMGTIEOTm5vpe83q9yM3NxciRIw2tOycnBwMGDMCwYcOMFtMQ/xNG30Er6IQTshYqr2nEr179Dle+tDzKUjqfKm1Fwq5EB8Lwp3OROeMbFFfU+16zYrRRNCK2v2xnGQDAI8mwjNAYOXpCbLRS2/dsI79/234QG0zYFRgAHq9txBvLdp8og871aPmcrK34woOX6upqFBYWorCwEABQVFSEwsJC7Nu3DwCQnZ2N119/HW+99Ra2bt2Ke++9FzU1NZgwYYKh7WZlZWHLli1YvXq10a9giCy/s/0nvLmsuh88XFHn+7c3wsVJ92gjS1pexPF4Fby5vAibDga2Qmm9wG09fGJEoKiLY7QKNuo+kKf30TyxupBkrCoElMn876Wy20jgMfbAvELsLqs5UQILcl6kPD5gQs5LQUEBLrvsMt/f2dnZAIDx48djzpw5uOmmm3DkyBFMnToVxcXFGDx4MBYuXBiSxOtU/j+0rpwXQQeKJDeBprFqFIT/7+FRFCSG+VV1jzbSXSr1RAaxHxXsx18+2wIA2PPslTGXr6pvQrNHQeeTUoSVISKdX9ONsYuixP7d1d5NW3GexRoNZTejXfMi9+DX248El0LXejTlvOjagvmEBy9jxoyJeeJMmjQJkyZNErrdnJwc5OTkwOPxCF2vVoHdRjqGSmtdPmI2meZNx61oP5N/V0CkCl9/y0twN5J4Ite5rbhK0/LnTWt5rMeWJ8eiXUr4qkbUxTHa95T1ztEsStClKdZonmh7z67gzurhwFHXYzDnxUzx3PIi3bON9HJLt5HmhN0I8zXIdOdiBqsSdj1+O9XrjVAW3Tkv8eHAsbqI74mb50Xf52SYx0Q4NQm7Md5vJUXOi81nivFJ6pz9eABZayrXBC+y8P+Z9Q2VNjdD3i2suuZ4VbS8qGVLzouObewqrcLUTzehpLI+9sIGiZvnJVrOi3wtC2ZSEPtGRvVoI0uez6buNe3rNfcEsyOoCv499D+YUQn491dbSnDwePibDFmvJVLO80LqBeTYxJgS3Eo7S6qQmpyEPl3bmbJ+q4Zw+ucOeSKcxXLfvGs/Eq58aTkamr3YVlyFD38XexSgkd9C1K6LluNl98XZamouaGqPChnmU7L74mk450XgLkxMSAhsDRbQbTS/8CAenLce/bqdFHbZuBltFPcMNr1o7zYK/1mjB9wXGw/jrwu36Yrsj9c24qcv5uGS55caKkM0eiqEzYcqsKtUW96Gf86LEqnbSHXOi/WVQLhNflp4EOv2HYv4mYbmli+6ek85pv13M1YVlUffhoFQWVjOi859a/+lWTwFkbuTw70WtWXKkm6j6Am7dl87jaYVxgoA6xo9uie8099tdOKTbywrAgAU+Y1i8vfJuoNYsPGwzi2ZxzXBi5TzvOioGo2cqGr7sdW49721+MfX32PxVu1P+957tNavHObUPFr3bEVdE658aTkyZ+SFDHmOti7/IDBiy4vanJcYu8KMfRVujffPLcS1//jO9/e81fuQu7UkZDlFAeZ8twc3/jM/5L31+48LKV+ixY8HCN7Fbsx5aRlt5Pd3+KUClo8keO+UVtbjeG2jgdKpY3fA4i9yy8uJNypqm1DfFH6wSLRDrLSyHkOf+gq/fatAVVkSg1YWqc54OXcnfvdOAfaX14Z93/9jkYKWVk0eBb9/b6008xi1ck23UVZWFrKyslBZWYn09HTbymE4YVdrKlVQ36Xe9URSVt2g+TONnhNNFF4FSDLh+qD1onPU73s0exWkqLxqqhltpDaSsuPUr2lojvp+UVkNHvnPRgDAeb3ScePQU1Wt95c53/r+baxrweaHG7lQ8K4Id4FT/VRpv/Osqr4Jw59pmWBUzVB5tWImFBtcr6IouPWNlUhNTsTsO4YJD1grapsw6MlF6JiWjA3TQh8iHG1reTvLUNPoQe62Uni8CpJi1Usqit7Q7MELX+0AAPTr1h6Tx50dsoz/Pg8OiCJpOY7kCfZdE7zIIqDXyOJMfSXSGxYpr2lEUVkNGppOBC/RTsjiinpkdEzVVZlo/YR/GbR0qTX7DTGKOEmdynXZcTc5fcG2qO+X15wI6jYerMDGoAnozGZJwm6EvDBApqpYrFiHmp4Zdv1bVE0X4aZM0yp++GYllQ347vujAICqhmZ0TGujaz2RrD9wHABQWR/+RiEgF1FRAuq7np3SfP8uKqvGGd07RN1WSLdRmKL5j4qMdPPi/7E2Ku8uZWuldE23kSyMNv07eZK6S59fil+9+h0W+3VBRAoU3li2GxdOz8WLi3fq25jG88j/7iJW82d9k8e3TJMndnKc6qdK2xBR7i2P3iRsd4UkLGE3Qj4SEGO/y1UfCxEyf1DYlg193UZmCLd5kWdKst/Fuak5yoESSZSE3e+PVGPN3sj5Y0DgORa8r5P83tsXoYvHX0i3UZjC+XdvN0eotPyPkTZJzgwDnFnqMOTJeTnBkhNfAb7ZcQQ3v5aPff65JjZcKKt+uPP4cnOx77VIwctTn28FALyUqy94MdLyEil3BWhpGj9n6kJc+dIyAECzX/ASOefFXpFahADgotO7Rf2s2iZjs4hredG5fdt/PfEUqMmv8l8+WsKuXQ9m9Pu33+szvtqBv6u84WldRxu/p3/634yoLkvE1xVc/sI3+HuMOsx/D0bberQA3LeukKHSYdbjn6f3w0oVRQkIZAJbXpwZBrim28g1OS8aP/9O/h78bdEO4eUworE5sNvIDFor1WT/bqMoZVpVVA5FOTGbrKpuoxhF2VFSha2HK2NfUKK/HdZfPtuCTwsP4ov7L8HJHVJD1xljo6ISZvUS9mDGKN8z2myt1sxjouDFxTsxsGdHXHFuDws26PvfD9sPVyZ1q7Lk8AhbvtDo5Wh1g+9mZ+Il/SLO2hwswe/a3OTR0fISgeo6NqjbKNJeVdOdHZqwG6Zcfl+xNWC58Z/5WL3nRAuR/+fUdhvJxpkhl8SsznkJF7gEl8NqwQm7ZtC6axP9rtKRmlLD8Q/EIj4eIMY6rngxD/fPLUTuttARPUa9ubwIZdWNeHN5Udj3Y31TIS0vBlahdvPNHi9u+mc+Hpu/Kez7MufrLt5aipdyd+Lud9ZYsj01kwsGtLZE6zaybah06Pv1zdrqlXCna6OO4CVSYKw+APTrNoqyXF2TB0u3lUYctdSyrqAyxOo2+qGlyT9wCS6J3V3HejF4MZGuodJhDsa9R6PnLYQTrXUhWE1DM15ZshO7Sqs1byecgAu+aS0v2pb3v0hrKVNzwGijSGVRV5hNBytjLyRYrArWKd1G331/FCuLyvHOir1h34/2PaMmpKrbvCEHj53ozq1tjD76S4SCvcfwwar9vr9jdSFH3z+x99COkirMWLQdVfVNaosYU/hEVP/uEH31ip6Wl8jdRuoEJuxGXm7yfzZiwpzVePjfG1StK9L6/G+ymr1eNIf5zv6fE9kaZSUGL6KZkLD7ypJdhtYZy3MLt+Fvi3Ygc8Y3Qtbnf3dz8HgdbvpnPhZuEjvJkZHuhmg5L8H8T/xIFabM9y0xW15srgHUBn6NMRIt/e+O31i2G5c+vxSHK+pC3gvdvqrNA2gZHVdeo32OE/88iwFTv4w4DbtZjMwvtK+8FsdifOcrXszDS0t24bmF0Ue2Rd6+uvf9l1MTvIRbItZxtL24Cn/7MjAQUzPPSzSBOS+RP1P3Q4vLf9cfiryuoAN2ZVE5creWYOGm8HmGjc2Kb9JJf/6lkG3+FrUYvAhmtNso3GGU1iZJ+3o0HI+xsuWNbPuut1ZjZVE57nl3LYCWYEbE3aeRBgMtJ6v/hceOGXKNip3z4ozRRrG6+vzfferzrdh7tNaXFB59++pKUFnfhAun5+LHf/lK1fL+grsq5q87qHkdRhg5aosr63GByu+8UWDLon+Zj9c14dY3VmDu6n2+15rVZLeGcfUr32JHSeRZtsfOzMMrS3fhmQWxjx3RLS9qhMtRu+utAtzz7hqUVtWHbKPR4w0bsAW2vDivXgNcFLxIM9rIcMJu6ArapmgPXh6dvxGHVN7hmXlNLqk8MY/IC4u24+Jnl+DS5782b4MqaKn3/JtU/VtsPll3AGOeX4qdJVVhr8Ber4JtxZWauqjM+B3k7zZSt/1YyYzh3i79IfcjareIyq//vYEuVdmb5UUddm10Zn+H275/PfiPpbvw7a6j+MfX3/teU9XyEuGYmfpp+LwpfxsOnJjvKOKWbLjmRztfKutaWov8901jsydCy0tg15ITuSZ4ycrKwpYtW7B69WpbyxHweABB14W2Olpelu0swz3vBiYIbjhwHM8t3BZz1tVI1kZ5Ho4aL//Q/XWkSvusvcGMJJlpOVkDcl78PvbgvPXYc7QWf/hofdi792cXbsPPZi7D84u26y6nCLHyHex+6JraXzHWxSrc91TTxaP2MAp3AVDL7uAlVuvbp4WHwuZFaBVzdlidahtDE1ibDbQWqCmnf1AfMWFXZfQSkLBrQstLq+Qf+oD9z+kmj4KG5tD9F9AFx5YXAoIPTj0Ju6H0tLwACJktNev9tXj16+/xyH8CE8L8txncH796z4mH8k1U+fwNKxipJoMv2NECoSZP9NFG9U2esBfA1/J2AwBe9btbtEO0ytLrVXDFi3nCtvXoJxvxl8+2aPqM2uBBT8vLsdqmiO9pZSx4sffioGbrH6813pWld76QcMGB/0spyaHr1ZvzAgBJfolec1ftw8//vgzFFYEjtAK6eiKtX+1oI6ExXeSVtU7GF9Bt1OyNmfPSxJYXAsyZ56WdzuAl2P7ylsAk+Amh/pXHxc8uwb++LfL9/fHag76+1FjJbnrovVkzlvOiftnmgBl2HZiwG+V4NHJBDlZR14T3Vu7Dm8uLNCWkimp5Cffb+Fpeon5UXQkaogxfjcWM80YLNXVSsYrh1bEk65wvJGy3kd+r4YKicDlQR6sbAo+DCN/bf86nyR9vxJbDlXj+y8AWUjUtu6pzXgI+Y+wCEa2+bN1PgS0vkXJejI/cshuDF8GMJuyGOyX0JOxG07frSVHffzoo0bGkwng3TyTJOoe7WJaw61Ux2kjS6GXhpsOWzLQc/PU3B7X4XfFiHrYXh0+SVNv9Z95kh+qWM7PbaNPBCqzYfVT3+kUQ0eOTLGAlO0uqUFbdoLnlZevhSgx5ajF+88bKmNsI120U/BsFLBFxtFHMTf2wMm3dRtGOyWjvtXZ1Bea8eMN2G50oj2J7y6BeDF4cQPS1MbgyCD6hrMyD0NtPbmSotKbv57doxHleJG17uefdtdY+TO8HO8Mkt/4vwvBPtXtOT7eR771o09+Hea06zAP2ogUvBX5dq+HECl5+8fJy3PzaClWTy+mjYHaESQxbiZioTO+NSOtvt/doDX76Yh6GPrU44BdLCdvyErhPP1jVMhKpwG/kZKTfPSnMdw2uEwO7jYzmvPh/JlC4OiVaEKgmwd5/nQ3N3oAH5frKoUTevlMweBHMvzlOT3VgZCpvUaw8oPXerRmpa7XMsOsvYreRnLELADHJ0VqFS6Z8ZWmEuYrUzrCro9tIjXC/3diZoXlAke5e1+47hkN++RLh8jfUJpeqHR2olaIAT8bIRRIx6iwpRreRoihYuq00JL+kVeH+437LnnhdTcuLlnM6XDmDt5GoorVET86L//HR0OzBLa+vCC1flDox2h6ubmjGbW+uxNxVJ4aUN3ki5bwovvedyjXBiyxDpY2K1f9rzjaNr1/vTLp6+8mNVLV6uyDCfccdJdWYu3p/mKXlIKrLcevhSlNa5NReNGMdX9GKFjDbrM6vEO7uFQBW7g5sdbn6lW9DRu6onZL+jWVFqBQ4S20rNd0Czy3cZngeo1hDpRdsLMaEOasx8tncmOvyr5PCt7wEBS8RZpGta/TgnfzAWZnD3TAFb0PNUak+5yX84wG+2xW+qzBaC1a0FrLX8r7Hsp1leMOvla3RE77bqPWndmq+C+Ci4EWaodJ+x4KuSerCHEv+x9eZGe21r1THNrXS25rhn/n/et5uzFA7tDjKzv1842E8Nn9TxMo4ZLSRui2qmplXtons0tqIOcXH/X0Z3g66CLRaWVSO/eX6uqfMTNgFgM2HKqLO/Kq2yy9St1HwdjcerMD6A8cDXlN7d/v5xsO47h/f4Xit9ll8o1GbQL1id/TuL38bD1SEHOtr9h2LOhtv3o4jANTVN5pbXiIEaH/9cltIMm64lo2o3UYGhxtpnaQuastLlMPVP0hv1RRptNEP5TAy5NxurgleZBEwz4ugXAizc1BErF1vBO9/nj69YCteWrILRWWxn+UUa8++s2JvxHlp9Ja19WeI1rwvWexi2SR0v3h5uebPKIqCrcXqZmWNVcdGOkdKg7rNgneH+oTd8N1Gao4lLQmRu0qrMeq5paqXVyO4VWLtvmO4Nue7kOWqNcz/dNUrywOmpAdaRjP+9MXIjxjxrxtjBfn++zXcU4+DL7pNYX4HBScCJn9qWl6q6pvx14XbsKOkKkrOizpqkn9jlc+3Lo2nc2PEbqMWTh0mDTB4Ec6MGXbNbtkT0Vqgd5bGujBDUEVNLhZucitAfxdXa4V6a5QRDVrXHG2qchFkbhV+Z8XegIdVRjsOY/1mkd4OvhAEb0LNteBodQM2HwofZKkLXrSdG1qCCDWCS7jhQIWupysHm18YOjdMWXXkc9d/37+waEfUdfu35KpreQn/fcIdUq2tvf6/S/A2thVX4R9ff4+xM/MM57z4P9G+vtmD57/chlVFkVu5orW8aL0ZafIoYYf5t55r7DYiH/9DIdpxFnnWxrALGylSTHa2vHRulxLyWuuzjz7bcAj/+Dp8oqeaUzjcqALAeMKumpYhta54MQ9l1eqSahdtKcYDc9dpfDaUvJXTnG/3BPwdbb/G6rKL1PISazSbmlE2Q55ajK+2lIR9L1rAdeBYLdbuO6ZrnpcPC8TlUcnSGuhfjIgJ3D/wD1bD/YbBN0vhWrcUJfxx0xrQ1vtd1MMFSK3riNxrpG7H+gccj36yETlLv8eN/8yPuHzUlhdVWwwU6SYOcHbCbrLdBXAbNQf0799bgz1ltfh00sUhEzDFynmRld6AoEfHtJDXWh9fMOn9dQCAi07vhsG9OwUso+aiE2kZLU+V9qem+67l99dWxRw4Vodu7VNjLvfgvPUAgF6d2+KhsWcHvFfb2IwvNxeHtGTJcuFS4ycvfINZvxmCnw3sAaDlbjopMQEJCQkqcl7Cv653+K5a0Y6l1u6f9LZtNK/34X9vwIBTOmJgr3TdZXMy//0abhcHHw+eCC2/4c7ZJF/wcuIzyYkJ+M+aA5rKGO6Xr6hrivp7L95aGnO90UZt6ekGDte63YotL+QT0PIS9N7mgxU4UtWABRuLseVwZcDDv4CWKPj22aFdEqbPuyJg9bpH8IT5bjUNgSdbeY2+4b6RbmCCuyBUT1Gv4iZFz14I16cfzZ4wc7e8nb8Xv3tnDT4tDJxPRcaq6S+fbUFZdQN2h2lpeWfFHgDAsZpGjHgmFw/MKwSg4tlGEVtegpYTvEfU3LhW1OkbQdQ6s7VRVkxUqIaWaqwuSmsB0FJX5u04gqM/tFqGu3lSoIQ9Z5PCtLwAwB8+Wh92W1q6jS5+dknA343N3oitaJHq9agBt46ml2j70qkT1AFsebHUr4NyJVKDmiq/2FQc9mAyPedFwDr0tryEu3NV0y2iqtsoQvQSfCFUW6mqG22kPYco3FDQaGo15ETINvoJAHaX1eBPH2+MusyHBftxtKYRnxYewt9vviB2y0uE95NitLwYzWc288aibRsx1bMsh4CWIGrOd3tOfC7Mx/6z9iC+2lKCHh3TsOJPl4ft/lCU8L9PuG6j6MeX+nIH5yu9lvd9xO7Q47Xhg1qROS+A2JaXorIa9OrUNmI3m5XsL4Hb+B0Lsbo2/IOXirqmkDsB3yrNznkRsH69SbDhPlbdEPs5MmrO4Uj736sour6zms94FUVzsKn1gXY1Me5K/Uly3QoRqzXiqF/SdlFZDf6euzPq8loSdmsbm5H//VE0e7yGRwTqPe7VOClVzBw90hwDOgsSLuhpzUFqfSZTpCG/0bqN/EfhRLsx0VpVFJXV4MF5hdhZUoVlO8siLhc8Eq6V6JyX6C0v6nNecreW4LK/fY3b3oz9CAYruKblJScnBzk5OfB49D9ATQQtx3nrtXXhpsO45921EfMe9MYWaj9nZ8tLuMpfXctL7NM4csuLvn2q5jxv+iFPQwutE/VpSdiV5a5bK/8k5rveij13k1dR8M2OI2gKSo4N/i0UAL99qwDffX8UD2aeGTMI/mZ76FBbf3rzp9RITRb7TDPRvtxcgndXhJ/7Jxy9e0rNLg7fbRT+nA0XHIj8GW+YlY+y6gYs2VaK/t0jz8t14Fj4uZGsbHnRYt4Pk3GujDJSykquaXmRZ5I69WfB3W+vAQBM+2/L1N2RRp0YaZoOlx9hhkgJc7GoyXkJS8U5HOlJwM1er66KtErF7KdNHkVzU6zW58qo2j8/kLHbKJoVu8vxUcH+gOHye1SM7mr0eDF+9ir89u2CgNfDXai++75lZtP3Vu6NeRhlvb826vtmtrxoOSyeWRB5Ij4Rx8Ck99fimzBzpvx5/ibV64hWjtveXKlpVJbaG4Rw2wzXlRg8kV3AOlSXqkVrPV5R1xT1pm73kfDHtch5XoDQ3B69OqTJ1dbhmuBFFmqHSgMtff81Dc0xT0TR9eO24io8/umJGWj11m2fbzjs+7funJcwn6tRkdOh5hy+6bUVYed/0NttNDlGngbQ0vJidrygZv+0clbo0nI8PPTvDQHPuVGjqTn8N02MMc+LUUZaXqobmvHIvzcILI15PttwOOoFXo1oe2rZzjI8FGFfhPtc8DQIYS/4ihKh2yhKQcJt38BvHO3Gc3dZ6ANMgVgz7NrX8tJRx6g5MzF4EUzrcZ6YkIBYoznNGC3wVv5e352U3vX735XqnWY6/NDw2OsKPoc/2xD+qcXhcivMnNqgsdlr+ugwLcGL46KXH0RKZowk4kMzg/4OPtaNJ+zq+9yqonIMfPxLzIsxn0uzx4s3lu3G5kMVUZeLRpbGN93lCPM5/wu816uoTs5v+ay2y56R3RetXjxWE/4Yj/psIx1liDVySy22vLic1scDJCREnkzNt06TKp/WC4SI9esdKq3mznXt3uMhLSj++/bAsVrfnDBqmNnU3+QxP3jRcidl+jB7Sei9O9ZzJ+tP77EUbZIyf++s2IunPt+KK1/S/vgFO3224RBumPVdwBOkRR6J/sFKbZMnbPCiIHzdpvdJ9nroqReTEhOw+0g1Ln52Cd5ZsRd1jR58t6sMXq8S80Y3nLoIDxXVqkPaiZYXGeaHYfAimNYHMyYkhDZtBzPrYtva1WPk+tZatrfy9xj6fDSvLN0V0mTtv2+jTUkeTnDAJHLvNnm0jzbSSssF1/4qxhqq93nQckYvY2ZW4hP+tRoFe44ZXo/allWR+VGT3l+H1XuOYdp/Nxtef7jy++/3qvqmiC110UYbqd6+gd2ip1sxOSkBUz/djIPH6/DY/E24ftZ3+PUbK7FoS7Gu0XF1mmbkjsy/5UX0Iyz0YPAigZgtLyZtV2+Srb/qxmZsPFCBj9eGPudEDbUtA//M2x3wt5Eb5uD8HJGVdkvOi7khg5a6N04aXlQfRyFLGYxezBxtdPB4HbYcVvfgymjUFvHud9bgu12Rh/aq9a9vi3z/9k+8FjnaqN7vQZmPfrIp7H6K+HgAjaP7jNDb8uI/hLn1uVqLNpdoOvdbicp58Z+PSs3gBbMxeBEsoOVF5WdiJ+ya2/JiRGVdk2+uBT30Vv5G5ucIbu1p/UtRFOwvNzY6q9HjNb1JVVvLS3xEL3p3udF5XvQcvlqCWxEXCS1lDJ5IU48n/rfF9+/WpxZ/s+NIQIK/FuGK7/+dlmyLPOV+uONCa8uLEXoeWBupW+v07u113bWJynnxp2XEo1kYvEjA6tFGrTy+biP9G6iqb1Y1lDUSvY0/RlpeIgUXn6w7iGl+Fa8eTc1e07uN2PISSnXLi+AdoidQ/VuMJyr7q6y3v3neiNb9M372Ksu3rShK2G7pWC3dIesxUAY99Vuk60Fjs1dXy0u9oJwX2TB4Ecy/clR7jsQKXszqhvAFLwbW8dzCbXh6wVbdn7cjoTR4m61/Bj9rSo8mj/Zh2Gv3HtP0mfomL5ZGudv0Fyexi+q8sOCljI42MrPbCEDI3Cd66oLWbgc7iHh2juihylonejPSva6v5SX8ZbnR49XVTtjo4CdHR8PgRTA9p1mkk+nTwpY8ErPqR4+AhN2vY8xAGove4MXIKJFI3WUimpNbRhtp+8z/fbBOcyU/YY7KyRjjJHrR321kcLsWjrpobPbiZzOX4YG56kfWAcBsvxwUq4nIqzMywjrsz6PxR480h5AaelrmIuXktLS8WNflJTsGL4IFjjZSd6BFumh+sGo/th6uND3nxc68CL03BbKewo06h0precaIFvGT86K22yjwb8MtLxYGL99+X4btJVWYXxh+TiMZ7Siptm2WZ1GbNdJyoef4iPSYmMZmr+Hj1U0YvAgWOM+LiuWV6H2wB47VmZ7zYif983MILoggZdUNuO8DbXfGgHkNJLLmvBw8Xid0fWqPo5BuI6MPZrRy/0r6W8bS+hBFvew+ho3cWOgZFBHpiGxsNv4gUTdxTfCSk5ODAQMGYNiwYbaWQ+uJNuq5pVi1J/KDrvROZa9G6+yPdlYOenMGquqb0djsxdHqBsvu7DqmJccM+KYv2IaCvdrn5jDrO8h6vTtwTH/w8qtXv8Px2sC5feyKw+NlEkAj1uwzNleNkW4jEYwELyJvEBuaPdLetNlBrvl+DcjKykJWVhYqKyuRnp5ud3FaqDjQIj2MsZWimNfw39ofbWf1q/fkXrP3GM788xcAgF6d2oosUkSpbZJiJuDpnbzJrN/AjRfXNXuPIWfpLvxqyKm+1/SONnJSt5FVFhtsKQkWz60FIqajaNXoYbeRP9e0vMhCdFWmKIFJgUUGhiUHa231sPP6JmLborsgojFrXzltvXZbuv0Iav3mr9A7SZ3hhF3b8jkUISN5wgl+MrdRhi+4emfmleDgF5nQzYTdQK5peZFF4CR1xg80rxLYJC6ywjpxV2Bnwq79FYwWpl2snLUbbLertBp3+11kdQ9qMfpsI5sukHe9VRB1cjaZGB3E5+RTQ2TLSwMTdgOw5UW4EwdrrYBnSngjPNZdBI+OOUlEc1q3hnmxi7P2gwz8n2ml+jgKHm2kY7v7y2tx1cvL8d/1h2wLvp0SuAD2zGLsRmx5CcTgRbDWE21XaTXezt9reH1mXtzfWbEXg5/8SvODDUVyWvBiVnkdthukozaGEBEk/nn+Jmw8WIH7Plinv8Unjth1vX3qc/2TZ8qooZkHmz92GwnWWjW+v3KfkPU9/flWlFZFT+rVq6HZa/sJ4bBeI/OGNJu03nhhZQuif1K22TPsuoHhlBeeHQDY8hKMLS+Cia5EzQpczHZmRntVyzkt50UxKdazu/vO6fRMUlda1YDDFcaSvZ3WcmgLgxdc7uIWHG0UiMGLYDzPtLNiivVDgkYkmXUXyOPGGNXdRkHLfVhwwNh2HRZ824HX20Cj+3eL+v4by4uwsih07i+2vARi8CIY7xK0s+Lu9RcvLxeyHrOuVTxujLGr+4bdRrEZvd66bRfrfS6bV1EYCPph8EK2c9LNq3kz4TpoJ0hI/eMBxO5nlz6wVyijp4zoM+OFRdtx82v5pj1PLBYjAYiRB9K6DRN2BWPugruZFmjxsDFE7agf0acnu41iizUrtdVKKhtQUtmAhZuLbdm+kXlvGLucwJYXwViVuVu8PYPIKexKnGXCbmzNBifWNOuca2q257cz0npidMI/N2HwIhrrMleT6enPSx00UZnZ1M/zIhZzXmJrZN9aAEMtL8x68WHwIpgbq7KJbxdgf3mtZdvzeO2f+TcS0yap03HkTJiz2oSSOJPqnBd2G1nOeMuLoIJIw0DLi4Yr9kWnd9W9HSdgzotgsl50jSiurMf9c9dZtr2P1x1EfbMn9oI24AMU5WRX982eo9YF9ZX1TZZtSyTZcl7sZlXLS1qbJP0bcgApW16uvfZadO7cGddff73dRdHMrdegQ8frLd3ego32JNPFYl7LCxmh/ubeuXv6/rmFdhdBl0aDuSVuG4lnKOlWw2fdnh8jZfBy//334+2337a7GLq49Q46ye1ngkpm/b4rdx81Z8Vxwq5uI4qNLS+BjEw0p+Wzbh9WLWXwMmbMGHTo0MHuYpAfBi8tzLr4ZX+43pwVxwmO+pGXXfOpyMpITKHlo26vsTUHL3l5ebjqqqvQs2dPJCQkYP78+SHL5OTkoG/fvkhLS8OIESOwatUqEWV1BLc1cbaSIXhZuMn+riReJOWkep4Xc4tBYTQZTNh1G6uGSrv9UQKag5eamhoMGjQIOTk5Yd+fN28esrOz8fjjj2Pt2rUYNGgQxo4di9LSE8M6Bw8ejIEDB4b8d+jQIf3fRBJuvbZJELvgnnfX2F0EXvwkpf7BjPwFrdbMlpcAVs2wq2VkkhNpHm00btw4jBs3LuL7M2bMwMSJEzFhwgQAwKxZs/D5559j9uzZmDx5MgCgsLBQX2nDaGhoQEPDiScvV1ZWClu3Hm6tGpPdfiaoxJYXOfFnkVczh5MHMNIiouWjzHnRoLGxEWvWrEFmZuaJDSQmIjMzE/n5+SI35TN9+nSkp6f7/uvdu7cp21HNpedpogxNLxLgRVJOqlteTC4HUSxWDZV2e40tNHgpKyuDx+NBRkZGwOsZGRkoLlafr5CZmYkbbrgBCxYswKmnnho18JkyZQoqKip8/+3fv193+UVwb86L3SWQA7sd5KS+28jkghDFwJwXMaScpG7x4sWql01NTUVqaqqJpdHGrZVjkstPBLVc+vM6HnNCySkMjTbiPC8+Qu+nu3XrhqSkJJSUlAS8XlJSgh49eojcVIicnBwMGDAAw4YNM3U7sbi1DpVhtJEMmPMiJ9XzvJhcDqJYjDyfSEtrSrRlp3+xDb969TtHP3dKaPCSkpKCIUOGIDc31/ea1+tFbm4uRo4cKXJTIbKysrBlyxasXs3nvZiBwUsLzrcVmwIFa/aWW7pNBpXkFIZyXgRN9FJe04g1e4/hy832Tz+hl+Zuo+rqauzatcv3d1FREQoLC9GlSxf06dMH2dnZGD9+PIYOHYrhw4dj5syZqKmp8Y0+cju35kS4vf9ULbfmNIn0aeEhzFy809Jtqp7nxaXnJzmHsW4jMS0vrSpqnfm8LEBH8FJQUIDLLrvM93d2djYAYPz48ZgzZw5uuukmHDlyBFOnTkVxcTEGDx6MhQsXhiTxupVbq0a2vLTgtS+2orIay7fJlhdyCkNDpTVtJ/Yyc1fbO8DFCM3By5gxY2LevUyaNAmTJk3SXSg9cnJykJOTA4/H3qcRKwpQ3+TB7G+LbC2HaGYHLx6HzAXBa6Sc+LuYL71tG1TUOfdOXRZGWl5E5by4gWsGwNqZ8xIczMkwjb1oZgcv1/7jW1PXLwrv8OXEodLmM/NaeP6p6eatXDJGhkprm6RO92YcwTXBi10amj0YOzMv4DU3XuDMHiq94UCFqesXxX2/rDuoHTXBnCU5uX02WH9GvimfKn2ClPO8OMV/1x/Cu/l7saOk2u6imI4z7LZwY2DqBqWVDbEXImnFU/VipDtHW7eR7s04gmuCFztyXu77YJ1l27JbstvPBJUYu8iprkndec/fT05uz8/wZ+SrnpSapHpZt+9T13Qbxfs8L53btTF1/Wx5acGhts7Gn09O8VS9WDXayO271DXBS7zr3iHN1PXz8QAtHDIoikgay3aWxVzG7fkZdnD7PmXwQqqw26gFW16cLX/3UbuLQGHEU/UiojtnUO9OGHtu9LnT2G1EBHYbtWLLC5F4br/Q+hPxVQerGFru9irbNcGLLA9mdCt2G7XgUFsi8eIpeLEqqHD7LnVN8BLvCbtmY8tLC/YaEYnn9gutP6sCNbcHhK4JXqwWb7kPzHlpEWc/O5El3H6hDWBZy4u79ymDF53i7SLGBzO24CR1ROLFU/ViXcuLJZuxDYMXneLtEhZXd0ZRMHghEi+e6hdR3zRWVeT2Xeqa4MXqhN14u4glueZIMSa+fnUia7i9i8Mfc17EcM0lyeqE3TiLXZCU6JpDxZB4y3UisoLbuzj8WRVTuD0g5BVJJ7a8xKc4+9mJLOH2VgJ/VgUVbg8IeUnSKd4uYpznpQUnqSMSL54adoXlvMTcjrvr7Dg6ZMSKt8nK2G3Ugt1GROK5vYvDH0cbicErkk7xdgfObqMW8fa7E1khvrqNrNmO2ycW5SVJp3i7A3f7iaBWvP3uRFaIp9pFVFXKodIuYf1QaUs2Iw3mvLSIs5+dyBLxdG8krossem3EnBeHsH6odHxdxhi7tIi3UWZEVrCj22jDgeOWbxOwsNvI5XW2a4IXq209XGV3EcgGjF2IxLMjYbdg7zHLtwlY1yLi9jwiBi863fL6CruLQDZgywuReG5vJfBn1Xd1eezC4IWIiOzl9lYCf5xhVwwGL2S7pdtL7S5CWE0eb8hrbHkhEi+eppESFajFqorc3pqVbHcBnMTrVTD+X6twaue2UZdbsfuoRSVyh9+9s8buIoR15UvLcNlZ3QNe84bGM0RkkNtbCezg9tYsBi8arD9wHMt2lsVc7sOCAxaUhsy2o6Q6JHhhuwuReG5vJfAnKqhonxb98u3y2IXdRlqwy4B4DBCJ5/ZWAn+iArU//fwcDOrdKeL7bm/Nck3wYvUkdRSnGLsQCRdPwYuooCKjYxo+zbo44vtub81yTfBi9SR1FJ/Y8kIkXhzFLpYFFW4PCF0TvBBZgaELkXhuv9AGsOi7un2PMngh0oAtL0Tiub2Lw59VX9XtASGDFyINGLsQief2C60/y76qy3cpgxciDeLtgZxEVnD7yBg7uH2PMngh0sDL2IVIuHjqNiIxGLwQacCWFyLx4qnbiMRg8EKkAVteiMRjywtpxeCFSAPGLkTixUPOS6d2bTDv7gvtLoZrMHgh0oDdRkTixUO30U/PycCIH3W1uxiuweCFSAPGLkTisduItGLwQqQBJ6kjEi+R0Qtp5JrghQ9mJCswYZdIvDjoNSLBXBO88MGMZAWFKbtEwsVDzguJ5ZrghcgK7DUiEo+9RqQVgxciIrIVW15IKwYvRERkq3iY54XEYvBCRES2YrcRacXghVQpqWxAVUOz3cUgIhditxFpxeBFpfKaRuwoqba7GLZ5c3mR3UUgIpdiywtplWx3AZxi3ur9eG7hNruLQUTkOsx5Ia3Y8kJERLZitxFpxeCFiIhsxW4j0orBCxER2YotL6QVgxciIrIVYxfSisELERHZqmentnYXgRyGwQsREdnqjO7t7S4COQyDFyIislWbJF6KSBvpjpj9+/djzJgxGDBgAM4//3x89NFHdheJiIhMMnnc2XYXgRxIuknqkpOTMXPmTAwePBjFxcUYMmQIfv7zn+Okk06yu2hERCRYets2dheBHEi6lpdTTjkFgwcPBgD06NED3bp1Q3l5ub2FIjLZqZ2ZsEhEpJbm4CUvLw9XXXUVevbsiYSEBMyfPz9kmZycHPTt2xdpaWkYMWIEVq1apatwa9asgcfjQe/evXV9nsgpUpKlu48gIpKW5hqzpqYGgwYNQk5OTtj3582bh+zsbDz++ONYu3YtBg0ahLFjx6K0tNS3zODBgzFw4MCQ/w4dOuRbpry8HLfffjtee+01HV+LiIiI3Epzzsu4ceMwbty4iO/PmDEDEydOxIQJEwAAs2bNwueff47Zs2dj8uTJAIDCwsKo22hoaMA111yDyZMn46KLLoq5bENDg+/vyspKld+EiIiInEhoW3VjYyPWrFmDzMzMExtITERmZiby8/NVrUNRFNxxxx34yU9+gttuuy3m8tOnT0d6errvP3YxERERuZvQ4KWsrAwejwcZGRkBr2dkZKC4uFjVOr799lvMmzcP8+fPx+DBgzF48GBs3Lgx4vJTpkxBRUWF77/9+/cb+g5EREQkN+mGSo8aNQper1f18qmpqUhNTTWxRERERCQToS0v3bp1Q1JSEkpKSgJeLykpQY8ePURuKkROTg4GDBiAYcOGmbodIiIispfQ4CUlJQVDhgxBbm6u7zWv14vc3FyMHDlS5KZCZGVlYcuWLVi9erWp2yEiIiJ7ae42qq6uxq5du3x/FxUVobCwEF26dEGfPn2QnZ2N8ePHY+jQoRg+fDhmzpyJmpoa3+gjIiIiIiM0By8FBQW47LLLfH9nZ2cDAMaPH485c+bgpptuwpEjRzB16lQUFxdj8ODBWLhwYUgSLxEREZEemoOXMWPGQFGUqMtMmjQJkyZN0l0oPXJycpCTkwOPx2PpdomIiMharpmTnDkvRERE8cE1wQsRERHFBwYvRERE5CiuCV44zwsREVF8cE3wYnXOS/tU6SYnJiIiiguuCV6s1q19it1FICIiiksMXoiIiMhRGLwQERGRo7gmeGHCLhERUXxwTfDCSeqIiIjig2uCFyIiIooPDF6IiIjIURi8EBERkaMweCEiIiJHcU3wwtFGRERE8cE1wQtHGxEREcUH1wQvREREFB8YvBAREZGjMHghIiIiR2HwQkRERI7C4IWIiIgcxTXBC4dKExERxQfXBC8cKk1ERBQfXBO8EBERUXxg8EJERESOwuCFiIiIHIXBCxERETkKgxciIiJyFAYvRERE5CgMXoiIiMhRXBO8cJI6IiKi+OCa4IWT1BEREcUH1wQvREREFB8YvBAREZGjMHghIiIiR2HwQkRERI7C4IWIiIgchcELEREROQqDFyIiInIUBi9ERETkKAxeiIiIyFEYvBAREZGjuCZ44bONiIiI4oNrghc+24iIiCg+uCZ4ISIiovjA4IWIiIgchcELEREROQqDFyIiInIUBi9ERETkKMl2F8AOiqKgubkZHo9H9WfSEj3o1SHJ93f3doloakyK8glrndw2AdUd5CpPjcnl8SrAsTov6j2KqdshIiK5xF3w0tjYiMOHD6O2tlbT587t0IRpl3X3/Z2cmIBmbwfRxdOtTVICmjwn2V0Mn5bytDd5Kwqq6j14teA4dpY3mbwtIiKSRVwFL16vF0VFRUhKSkLPnj2RkpKChIQEVZ89WtOA1KoG398pSYlo9HjNKqpmKclJaGxW35JkNkvKoyjoUluJe4cCf8otYwsMEVGciKvgpbGxEV6vF71790a7du00fbZNE5CQfOLimJiciIQEeYKXpDZJSIA8wYtV5Ulu1xEd0irRuW0iDlfL8/2JiMg8cZmwm5gYl1/bnRISACQgUV0DGhERuQCv4kREROQoDF4oxMH9+zCod2ds27zR7qIQERGFYPBCREREjsLghSzT1NhodxGIiMgFpAtejh8/jqFDh2Lw4MEYOHAgXn/9dbuLJIW7bvgFnp36CF58eipGD+yHn/z4LLw641nf+5UVxzHtofswZtAZuOicPvjtTVdj+5aWbp+qygpccFpXbF6/DkDLkPHRA/vhN1f/1Pf5zz6ehyuGnxuwzaJdO3D7NVdg2Bk9cN3lI1GQ/23A+wX53+LXv7gcQ0/PwOVDzsbM6dPQ3NwcUOZn/vwQ/jptCi49/3Tc85tfYXX+cgzq3Rkrl3+DW35+GUb074nbr7kCe77f6fvc9i0bcdeNV2Hk2b1x0Tl9cPPPx/jKTkREJF3w0qFDB+Tl5aGwsBArV67EM888g6NHj5q2PUVRUNvYHPO/ukYP6pvE/aco2uck+d+/P0Dbdifh3f8txoN/egL/nPlX5OctBQDcP3E8ysuOIOftj/DBgqU4Z+Ag3H3zNag4dgwdOqbjrHPPQ0H+cgDAzm2bkZCQgG2bN6C2phoAsGbFdxhy4cUB23vx6am4/e5JmPfFNxg0ZDjuu/MWHD9WDgAoOXwIWeNvxMBBF+CjL5fh0adfwPy57+L1l/4WVOa5aNOmDd76ZCEemz7D9/rLf30Kf3jsKbz/+RIkJSXj8T9O8r035f/uRsYpPfH+Z7n4YMFS3Pn7B5DcJq5G9RMRURTSXRGSkpJ8c7A0NDRAURRdF3q16po8GDD1S9PWH8mHv7sQaW20TZ/f/+xzcc+DjwAATut3Oj6Y8zpWfvsNUtPSsGHdGixdtwMpqakAgD889hcs/fJzfLXgU1x/6x0YeuEorF6xHOPv+T8U5H+LC0ePwZ7vd2LdqhW4+LJMFOQvxx333hewvZvvmIjMn18NAHj0mRfw7deL8cncdzDh3vvx4dtvokfPXpjy1PNISEhAvzPOxJGSw5g5/Qn87oGHAbR8tz79foQHH33St84jpSUAgP97+M8YOrIlWLoz6wFMGn8TGurrkZqWhuJDB3HHPfeh3xln+r4rERFRK80tL3l5ebjqqqvQs2dPJCQkYP78+SHL5OTkoG/fvkhLS8OIESOwatUqTds4fvw4Bg0ahFNPPRUPPfQQunXrprWYrnTmOYHdOid3z0B5WRl2bNmE2ppqXHL+6bjwrFN9/x3cvxf79xYBAIZeeBEKV6+Ax+NBwYpvMXTkKAwd2RLQlBYfxr49uzF05KiA9Q/68TDfv5OTkzHg/Auwe+cOAMDuXTtw/o+HBcxQPHjYCNTWVKPk8EHfawPOGxz2u/T3+y7duvcAAJQfPQIAuG3i7/HEw/fh7luuwZs5L2L/niKtu4qIiFxMc8tLTU0NBg0ahDvvvBPXXXddyPvz5s1DdnY2Zs2ahREjRmDmzJkYO3Ystm/fju7dW54NNHjw4IDciFaLFi1Cz5490alTJ6xfvx4lJSW47rrrcP311yMjI0PH14utbZskbHlybMzljlQ1oKSy3vd3anIiGpr1z7Cbmqy9xy65TZuAvxMSEqB4vaitrcHJGT3wxrz/hXymQ3o6AODHIy5GTXU1tm5cj7Urv8N9jzyGbidnYPY/ZuKscwbi5IxTTGnhaBthJuPk5BPfpTUA8npbWtjuzZ6Mcddcj2W5i7B86WK8OuNZPPfKm7h83C+El4+IiJxHc/Aybtw4jBs3LuL7M2bMwMSJEzFhwgQAwKxZs/D5559j9uzZmDx5MgCgsLBQ1bYyMjIwaNAgLFu2DNdff33YZRoaGtDQcOKZQ5WVlSq/SYuEhAS0S4m9G9qmNAd086QmJ6p+LpLZzhk4CGWlJUhKTkav3n3CLtMxPR39zzkXc996Hclt2qDfGWeiS9eT8XDWncjL/RJDL7wo5DMb1hX48mCam5uxdWMhbr5jIgDgR2ecicVf/A+Kovj2Q+HqlTipfQdknNLL8Hfq+6Mz0PdHZ+C2ib/HI1l34dMP32PwQkREAAQn7DY2NmLNmjXIzMw8sYHERGRmZiI/P1/VOkpKSlBVVQUAqKioQF5eHs4666yIy0+fPh3p6em+/3r37m3sSzjQhaPHYPDQ4Xjwt7fiu2+W4OD+fSgsWImXn/tLwCidYReOwoJPPsKQES2BSnrnzvjRGWfiy/99EpKsCwDz3noDuV98hqJdO/DMn/+IyooKXHPTbwAAN95+F4oPHcT0xx5G0a4dWPrlArw641ncNvH3hh6/UF9Xh2f+/BBW5y/HoQP7sG71Cmxevw79+p+pe51EROQuQhN2y8rK4PF4Qrp4MjIysG3bNlXr2Lt3L+6++25fou7//d//4bzzzou4/JQpU5Cdne37u7KyMu4CmISEBLz23r/xt6efwNQ/TMKx8jJ0O7k7fjziInQ9+WTfckMuvBjvvvlqQG7L0JGjsH3LJgwLyncBgPsnP47Z/5iJ7Vs2onffH+Hvs99H5y5dAQAZp/REzlsfYsbTU3HD2NFI79QZ19z8G0y874+GvktSUhIqjpXjzw/cg6NlR9Cpc1dcPu4X+H32FEPrJSIi95ButNHw4cNVdysBQGpqKlJ/GGHjZm9+9FnIazPffM/37/btO2Dyk89h8pPPRVzHT352JdbvPxbw2sPTpuPhadMDXuvVu49vuXHXhO+uA4ChIy/G+5/lairzsJGjQspw9rnnBbz2XM6bEddJREQktNuoW7duSEpKQklJScDrJSUl6NGjh8hNERERUZwSGrykpKRgyJAhyM09cTfu9XqRm5uLkSNHitxUiJycHAwYMADDhg2LvTARERE5luZuo+rqauzatcv3d1FREQoLC9GlSxf06dMH2dnZGD9+PIYOHYrhw4dj5syZqKmp8Y0+MktWVhaysrJQWVmJ9B+GBxMREZH7aA5eCgoKcNlll/n+bk2WHT9+PObMmYObbroJR44cwdSpU1FcXIzBgwdj4cKFps3TQkRERPFFc/AyZsyYmNP1T5o0CZMmTYq6jGg5OTnIycmBx+OxdLtERERkLekezKhXVlYWtmzZgtWrV8dc1sxnJZE9vPxJiYjihmuCFzXa/DC9fm1trc0lIVEUTzM8Xi9qGvU/qoGIiJxFunlezJSUlIROnTqhtLQUANCuXTvVU/w3NTZAaW70/e1VEqF45LlgepAEpVmeLjNLyqMoqKs8hg3F9ahqZNMLEVG8cE3wojbnpXW+mdYARq2q+iZU1J14mGRyYgKaJeqraJOUgCZPvJVHwbHaZszdVAV5vjkREZnNNcGL2qHSCQkJOOWUU9C9e3c0NTWpXv8Hq/bhjWW7fX/36tQWB4/XGSqzSP26noSiozV2F8Onb9d22HPU3O45jxcoq/WgmZELEVFccU3wolVSUhKSkpJiL/iDem8SDladaNVpk+IN+Ntu7dspUpXnJMnKQ0RE7hFXCbtERETkfAxeiIiIyFFcE7zw2UZERETxwTU5L60JuxUVFejUqRMqKyuFrr+upgrehhMJqM31CrwN8iTsNtcnBpTPbs31CVKUp6qyEm28qQFlqa2uQmVlZcBrlZWVqK+tDimz/2ueNs0hx4EozfWwfH8F7wNpJeifhLCqSvx3bKpLibrOqspKVFYmO2PfauBJTIa3oTn2ghq1nI/tIu4vu+uSprrw29daFzTUVqOyshK1P3zOk5QIr4bpNprrvaivaamPWtcFRK43aqvF1lU1fuurqqpAZTvxIyVav5OaiWQTFJdNN3vgwAH07t3b7mIQERGRDvv378epp54adRnXBS9erxeHDh1Chw4dVE9Ap1ZlZSV69+6N/fv3o2PHjkLXTSdwP1uD+9ka3M/W4b62hln7WVEUVFVVoWfPnkhMjJ7V4ppuo1aJiYkxIzajOnbsyBPDAtzP1uB+tgb3s3W4r61hxn6ONk+bP9ck7BIREVF8YPBCREREjsLgRYPU1FQ8/vjjSE1Ntbsorsb9bA3uZ2twP1uH+9oaMuxn1yXsEhERkbux5YWIiIgchcELEREROQqDFyIiInIUBi9ERETkKAxeVMrJyUHfvn2RlpaGESNGYNWqVXYXyVGmT5+OYcOGoUOHDujevTuuueYabN++PWCZ+vp6ZGVloWvXrmjfvj1+9atfoaSkJGCZffv24corr0S7du3QvXt3PPTQQ2huFv+8Fbd49tlnkZCQgAceeMD3GvezGAcPHsRvfvMbdO3aFW3btsV5552HgoIC3/uKomDq1Kk45ZRT0LZtW2RmZmLnzp0B6ygvL8ett96Kjh07olOnTrjrrrtQXV1t9VeRlsfjwWOPPYZ+/fqhbdu2OP300/GXv/wl4Nk33M/65OXl4aqrrkLPnj2RkJCA+fPnB7wvar9u2LABo0ePRlpaGnr37o2//vWvYr6AQjHNnTtXSUlJUWbPnq1s3rxZmThxotKpUyelpKTE7qI5xtixY5V//etfyqZNm5TCwkLl5z//udKnTx+lurrat8w999yj9O7dW8nNzVUKCgqUCy+8ULnooot87zc3NysDBw5UMjMzlXXr1ikLFixQunXrpkyZMsWOryS9VatWKX379lXOP/985f777/e9zv1sXHl5uXLaaacpd9xxh7Jy5Upl9+7dypdffqns2rXLt8yzzz6rpKenK/Pnz1fWr1+vXH311Uq/fv2Uuro63zI/+9nPlEGDBikrVqxQli1bppxxxhnKLbfcYsdXktLTTz+tdO3aVfnss8+UoqIi5aOPPlLat2+v/P3vf/ctw/2sz4IFC5RHH31U+fjjjxUAyieffBLwvoj9WlFRoWRkZCi33nqrsmnTJuWDDz5Q2rZtq/zzn/80XH4GLyoMHz5cycrK8v3t8XiUnj17KtOnT7exVM5WWlqqAFC++eYbRVEU5fjx40qbNm2Ujz76yLfM1q1bFQBKfn6+oigtJ1tiYqJSXFzsW+bVV19VOnbsqDQ0NFj7BSRXVVWl9O/fX/nqq6+USy+91Be8cD+L8cgjjyijRo2K+L7X61V69OihPP/8877Xjh8/rqSmpioffPCBoiiKsmXLFgWAsnr1at8yX3zxhZKQkKAcPHjQvMI7yJVXXqnceeedAa9dd911yq233qooCvezKMHBi6j9+o9//EPp3LlzQL3xyCOPKGeddZbhMrPbKIbGxkasWbMGmZmZvtcSExORmZmJ/Px8G0vmbBUVFQCALl26AADWrFmDpqamgP189tlno0+fPr79nJ+fj/POOw8ZGRm+ZcaOHYvKykps3rzZwtLLLysrC1deeWXA/gS4n0X573//i6FDh+KGG25A9+7dccEFF+D111/3vV9UVITi4uKA/Zyeno4RI0YE7OdOnTph6NChvmUyMzORmJiIlStXWvdlJHbRRRchNzcXO3bsAACsX78ey5cvx7hx4wBwP5tF1H7Nz8/HJZdcgpSUFN8yY8eOxfbt23Hs2DFDZXTdgxlFKysrg8fjCajIASAjIwPbtm2zqVTO5vV68cADD+Diiy/GwIEDAQDFxcVISUlBp06dApbNyMhAcXGxb5lwv0Pre9Ri7ty5WLt2LVavXh3yHvezGLt378arr76K7Oxs/OlPf8Lq1atx3333ISUlBePHj/ftp3D70X8/d+/ePeD95ORkdOnShfv5B5MnT0ZlZSXOPvtsJCUlwePx4Omnn8att94KANzPJhG1X4uLi9GvX7+QdbS+17lzZ91lZPBClsvKysKmTZuwfPlyu4viOvv378f999+Pr776CmlpaXYXx7W8Xi+GDh2KZ555BgBwwQUXYNOmTZg1axbGjx9vc+nc48MPP8R7772H999/H+eeey4KCwvxwAMPoGfPntzPcY7dRjF069YNSUlJIaMxSkpK0KNHD5tK5VyTJk3CZ599hqVLl+LUU0/1vd6jRw80Njbi+PHjAcv77+cePXqE/R1a36OWbqHS0lL8+Mc/RnJyMpKTk/HNN9/gpZdeQnJyMjIyMrifBTjllFMwYMCAgNfOOecc7Nu3D8CJ/RSt3ujRowdKS0sD3m9ubkZ5eTn38w8eeughTJ48GTfffDPOO+883HbbbXjwwQcxffp0ANzPZhG1X82sSxi8xJCSkoIhQ4YgNzfX95rX60Vubi5GjhxpY8mcRVEUTJo0CZ988gmWLFkS0pQ4ZMgQtGnTJmA/b9++Hfv27fPt55EjR2Ljxo0BJ8xXX32Fjh07hlxI4tXll1+OjRs3orCw0Pff0KFDceutt/r+zf1s3MUXXxwy1H/Hjh047bTTAAD9+vVDjx49AvZzZWUlVq5cGbCfjx8/jjVr1viWWbJkCbxeL0aMGGHBt5BfbW0tEhMDL1NJSUnwer0AuJ/NImq/jhw5Enl5eWhqavIt89VXX+Gss84y1GUEgEOl1Zg7d66SmpqqzJkzR9myZYty9913K506dQoYjUHR3XvvvUp6erry9ddfK4cPH/b9V1tb61vmnnvuUfr06aMsWbJEKSgoUEaOHKmMHDnS937rEN4rrrhCKSwsVBYuXKicfPLJHMIbg/9oI0XhfhZh1apVSnJysvL0008rO3fuVN577z2lXbt2yrvvvutb5tlnn1U6deqkfPrpp8qGDRuUX/7yl2GHml5wwQXKypUrleXLlyv9+/eP+yG8/saPH6/06tXLN1T6448/Vrp166Y8/PDDvmW4n/WpqqpS1q1bp6xbt04BoMyYMUNZt26dsnfvXkVRxOzX48ePKxkZGcptt92mbNq0SZk7d67Srl07DpW20ssvv6z06dNHSUlJUYYPH66sWLHC7iI5CoCw//3rX//yLVNXV6f8/ve/Vzp37qy0a9dOufbaa5XDhw8HrGfPnj3KuHHjlLZt2yrdunVT/vCHPyhNTU0WfxtnCQ5euJ/F+N///qcMHDhQSU1NVc4++2zltddeC3jf6/Uqjz32mJKRkaGkpqYql19+ubJ9+/aAZY4eParccsstSvv27ZWOHTsqEyZMUKqqqqz8GlKrrKxU7r//fqVPnz5KWlqa8qMf/Uh59NFHA4becj/rs3Tp0rB18vjx4xVFEbdf169fr4waNUpJTU1VevXqpTz77LNCyp+gKH5TFRIRERFJjjkvRERE5CgMXoiIiMhRGLwQERGRozB4ISIiIkdh8EJERESOwuCFiIiIHIXBCxERETkKgxciIiJyFAYvROQYY8aMwQMPPGB3MYjIZgxeiIiIyFH4eAAicoQ77rgDb731VsBrRUVF6Nu3rz0FIiLbMHghIkeoqKjAuHHjMHDgQDz55JMAgJNPPhlJSUk2l4yIrJZsdwGIiNRIT09HSkoK2rVrhx49ethdHCKyEXNeiIiIyFEYvBAREZGjMHghIsdISUmBx+OxuxhEZDMGL0TkGH379sXKlSuxZ88elJWVwev12l0kIrIBgxcicow//vGPSEpKwoABA3DyySdj3759dheJiGzAodJERETkKGx5ISIiIkdh8EJERESOwuCFiIiIHIXBCxERETkKgxciIiJyFAYvRERE5CgMXoiIiMhRGLwQERGRozB4ISIiIkdh8EJERESOwuCFiIiIHIXBCxERETnK/wPyX8p3Nnv/3wAAAABJRU5ErkJggg==", "text/plain": [ - "(,)" + "
" ] }, - "execution_count": 63, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" }, { "data": { - "image/png": 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", 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", 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", 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", 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", 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", 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hPv/8c0yfPh3PPfecsv3MmTPx7rvvQpIkZdhGq9Vi2rRpWLFiBebMmeO1uV9+fj4WLFiAW2+9FUajES+88AIAeAyJdOd7Rs3PH/V+DEYobO6//37k5OTgueeew6OPPgqr1Yrc3Fw88sgjuPfee9sV4Kntd7/7Hd59910sW7YM9fX1yMrKwq233ooHHnggqMe77777MGzYMPz1r39VvuCzs7Nx1lln4Re/+IWy3W9/+1vYbDb86U9/wt13343Ro0fj008/xR/+8AdVXpds1KhR+O6777B48WIsWbIEdrsdU6ZMwTvvvKPMCAm1uXPn4rXXXsPSpUtx++23Izc3F3/84x9RUFAQdDAyZswYrFixAosWLcKDDz6IrKwsPPLIIyguLm73mH//+98xaNAgvPnmm/j444+RlpaGxYsXK43xeorLLrsMGRkZWLp0Kf70pz+hpaUFmZmZmDlzJq655hqPbeVsyIgRI5CYmOhx+4oVK5T725o9ezamTp2KRx55BIWFhRg5ciTefPNNjBkzRtmmO98zan/+qHeTRFcqw4iIiIi6iDUjREREFFYMRoiIiCisGIwQERFRWDEYISIiorBiMEJERERhxWCEiIiIwqpX9Bmx2+04efIkoqOj/V5ngoiIiMJLCIG6ujpkZGR02juqVwQjJ0+eVH1NBCIiIuoeRUVFyMrK6vD+XhGMyK2Bi4qKVF0bgYiIiEKntrYW2dnZPlv894pgRB6aiYmJYTBCRETUy/gqsWABKxEREYUVgxEiIiIKKwYjREREFFYMRoiIiCisGIwQERFRWDEYISIiorBiMEJERERhxWCEiIiIworBCBEREYUVgxEiIiIKKwYjREREFFYMRoiIiCisGIwQEVGnmlttaGixhns3qA/rFav2EhFReHy05Tju/3gXLDY7rpqag/vPzYNW0/kKrESBYmaEiIi8OlrRgPs+3ImmVhtsdoHXvz+KZSv3h3u3qA9iMEJERF69svYwLDY7Zg5NwrKLxwIAXlx9GNuKqsO7Y9TnMBghIqJ2Wqw2fLajGABw05whuHBCFi4Ynwm7AB77bA+EEGHeQ+pLGIwQEVE73x+qQF2zFSnRRkzJTQAA3HfOCJj0Gmw+dgpf7SoJ8x5SX8JghIiI2vl8hyPYOCc/DRpnwWpqjAnXzxwEAFi28gCzI6QaBiNEROTBYrVj5R5nMDI63eO+62cNQqRBi4Nl9Vh9oDwcu0d9EIMRIiLysPnYKdQ2W5EYacBpOQke98WY9Lh08gAAwN+/OxKO3aM+iMEIBa3FasP7Gwvx7o/H0GhhQySivmLtQUfGY9awZK89Ra6ZngOtRsL3hyqxv6Suu3eP+iAGIxS0Oz7Yhvs+2on7P96FX720gQEJUR+xZr8cjCR5vT8r3oz5eSkAgH9uLOy2/aK+i8EIBWXD4Up8sdMxphyh12L3yVo8/OnuMO8VEXVVWV0z9hTXAgBmDk3ucLvLpgwE4OjQ2txq65Z9o76LwQgF5dlvDgIA/u/0AXjjmtMgScC/Nh1nMySiXu67AxUAgNGZsUiKMna43cwhSciKj0Bts1XpR0IULAYjFLDCykasP1wJSQJunDMEpw9KxAXjMwEAf17BVtFEvZmrXsT7EI1Mo5Hwa2chK4dqqKsYjFDA/rO5CAAwY0gSMuMiAAB3zB8GjQSsO1SBA6UsaCPqjex2gXUHHZmRWZ0M0ch+NTELGskx+6agoiHUu0d9GIMRCojNLvCfzccBAL+cmKXcnp1gxpkjUwEA/9hQEI5dI6Iu2lNci8oGCyINWowfEO9z+5QYE6YPcWRQPtl2MtS7R30YgxEKyPrDFThZ04wYkw4LRqV53HfV1BwAwEdbTqC2uTUMe0dEwWq12ZW+ITOGJsGg8+/0sHCcY4j2k20n2JGVgsZghALyr02OrMjC8Zkw6bUe900dnIjByZFotNjw5U4WtBHw2Y6TWPb1fhw/1RjuXaFO7CupxaynvsVyZ3bjqmk5fv/ugvw0mPQaHKlowM4TNSHaQ+rrGIyQ36obLVix2zGd9+JJ2e3ulyQJF05wDN18tOVEt+4b9TwfbTmOW97bir99cwgXvLAeZbXN4d4l6sADH+9CcU0z4sx6PPjzkZg2uPPiVXdRRh3m5zmGaJdv5VANBYfBCPnt0+0nYbHakZceg1EZMV63WTg+E5IE/Hi0ilfD/ZgQAi+sPqz8XF7XgqVf7QvjHlFHiqoasenYKeg0Er68bSZ+MyM34MeQh2r+u+MkbHYO1VDgGIyQ3/7tHKK5ZFIWJKl9i2gAyIyLwNRBiQBY0NafFVQ24lBZPQxaDd69bgoAR7Zs53FHGn/XiRp8u78MrTZ7OHeTAHx/yDF7ZvyAOKTHRgT1GLOGJSPOrEd5XQt+PFqp5u5RP8FghPxSXteCnSdqIEnAL5xXQR2Rr5LYCKn/+uGI44Q0bkAcpg9JUvrQLFu5H298fxQ/f3YdrnnjJ1zx2o+wWAMPSOx2gfoWLj+gBrnOY1KbBfECYdBpcKZzqObr3aWq7Bf1LwxGyC/y1c6ItBgkRBo63fasUanQaSTsLa7F4fL67ti9fmvXiRos/mgn3vuxsEfNZDhY6vi7j82KBQDcNm8otBoJ3+4vxyP/3aNs98ORqoCngh8qq8OMP36DsY98jWUrD6i2z/3VwTLH32p4anSXHkeeXbdid0mPei9S78BghPzy45EqAMDpg3xfPcWZDUrvgS+YHQmZmqZWXPn6RvxzYyF+//FOvLbuaLh3SVHkrBcakBgJAMhJisRt84Yq999yxhAsvXA0AOCZVQcDmgr+4Ce7cbKmGTa7wN9WHVSadFFwDjmDkSEpUV16nBlDk2A2aFFc04wdxzmrhgLDYIT8Iqfdp+Qm+rX9uWPSAQCfc4pvyHy+oxhVDRbl52UrD6CkpmfMWCmqcgYjCWbltlvnDcV/b5mBL2+bibsWDMevJmVjSEoU6pqt+MjZSM+fx11/uBIaCZg3wrFq7EOf7oKdRZNBabXZlfeQ3E05WCa9FmcMd/xN5Fl3RP5iMEI+VdS3KKncKbn+jSsvGJkGvVbCvpI65cqL1LV6fxkA4M4zh2HCgDg0Wmx4YfWhMO+VYyZNoTMYyY73PMGNzopFXrpjJpZWI+HKqY6VX9/+4ZhfqX153ZRJOQn466XjEG3S4XB5A1btK1PzJfQbpxodgYhGAmIi9F1+vLNGOepGGIxQoBiMkE8bjzqGaEakRSPeR72ILNasxwx5qIbZkZDYfdKxzPuUQYm486zhABwznmoaw9v9tqrBgkaLDZIEZMZ3frV94YQsROi1OFzegO1+pPZ3ycWWA+MRY9Ljcucy9q+tO9L1He+HTjU43itxZgO0Gu8z5AIxd0QKDFoNDpc34FAZ16gi/zEYIZ/kIZrTB/k3RCM7d0wGAMdwAqmrtrkVJ6qbADgKD6cNTsSItGg0tdqwfFt4G87JWZH0GBOMOm2n20YZdcqaRp/4sd/yzI/RmY7C2CunDoQkOQphCyvZ1yZQ8hBNvLnrWREAiDbpMW2I43vi6z2cVUP+YzBC7fxn83FMXbIK//f3H1FZ3xJQ8aq7M0emQq+VsL+0Dge5kq+qjpQ7VkhNjTEi1qx3dr91TJ9dGeaTgByMZLnVi3Tm/HGOoPW/24s7bZhlsdqxv8TxPsp3BiMZcRFKBk5eTZr8Jw/T+JohF4h5zim+q/eVq/aY1PcxGCEPxTVN+P3HO1Fc04x1hypw6Ss/YL8zkJjsZ/GqLDZCryxDzp4j6ip2ZkXciw7PHOmYWvnDkcqwLlTorXi1M7OGJSPerEdFfQs2HO64YdaB0jq02gRiI/TIchv+kVeP/nT7SU4pDVClkhlRLxg5Y7jjM7+58FTYhwyp92AwQh4+31EMi9WOCL0WkQatUrg6KsN3fxFvzhntmFUT7qv1vqbYOWsm3S0YyU2KxJCUKFjtAqv3h++qtKjKESj5G4zotRqlR8X/9nb8PpHrRfIzYzw6AM/PS4VRp0FBZSP2FjMDF4hTDepnRrLizRiWGgWbXWDNQWZHyD8MRsjDmgOOL4+7FwzH0ovGKLdfHcAqnu7mjkiBJAF7imtx0nk1T11X4lx0Lj3G5HG7vGDZ/8IY/CkzaRL8nyoqp/b/t7e0w+zGTiUYifW4PdKowxzn1TiLpQNTFYJgBIAyxXc1ZzmRnxiMkEIIoczQmDgwHueNzcCrV07CK1dMVFLhgUqINGDCgHgAwDf8YlKN3E8kLdYzGJGLQcO57kthgMM0ADB9SCIMOg2On2pSsnFtKZmRjNh29/3MmYH7YmdxQEM1QgisP1SBbUXVfv9OXxKKmhEAOMPZA2b1gXIunEd+YTBCitLaFlQ1WKDVSBie5mgNfebIVJw1Kq3DhfH8MS/P8cXEYEQ98kmk7Vj/uOw4JEUZUNdsVQqPu1OrzY7iGkcGLDuAYMRs0GH6YEdNkrehmlabHXudxaujM9sHI/PyUmHQaXCkokGpcfLHX1cewGV//xELn/8ef/+u/00PrgpBzQjguJiJNulQ1WDBjuPVqj429U0MRkhxpMJxRTogwQyTvvMpmYGYN8Jxtf79oQo0WWyqPW5/pgQjkZ5TMrUaSTnendVfhMrJ6ibYBWDSa5AcZQzod+c6h2q+9RK0Hiitg8VqR7RR5zXjEmXUYfYw51CNn8XSpxoseGmNKwB5asX+fjeUGKrMiF6rUYrXvf09idpiMEKK41WBX9H6Y1hqFDLjItBitSvLlVPXuDeramuuMxMl1/90J1fnVXPA2bQ5zmBiS2E1apo8Z2FsOXYKgGMVYE0Hzbl+NtpRBPu5n0M1X+4qgcVmx6iMGEzOTYDFasd7PxYGtM+9nfw+8reZYSDkOp5vw1hMTb0HgxFSyIubtW3h3VWSJGG+8wTJtt3qqO5gmAYApg1OhFYj4WhFgzLNtrsEUy8iy04wY3ByJGx20W7xuy2F1QCg1B95My8vVen+uaWwGofK6jqtm/n+sOM5FoxKwxWnOzq5frz1RL9a50YpYFV5mAYAZjuDkZ0nalBe16L641PfwmCEFCdOOTIjWfHqZkYAVwr+m30dz5Yg/1isdjQ4h7u8dc6MNukxYUAcANdaLqFQWNmIi1/egAtf+F5p/V3UxezaHHkWxn7PoHWzMzMycWDHwUiMSa+cAC96cT3mL1uLnz3zHSrq258I7XaBH5w9TaYNTsSZI1MRbdLhRHUTNhZ0f61NODRZbGhqdb6PItXpwOouJdqE/EzHOkRrw5Clo96FwQgpyp1f2qkxgY31+2NKbgLMBi1Ka1uw60St6o/fn1Q3Oa5mJclxAvZmpnO8/rsDoRsWu3/5Tmw8WoUthdX43dub0WqzK5mY4IMRx36vOVCuBK3ldS0orGqEJDmGaTrzwLl5Hg3RDpbV47HP9rTb7kBZHSobLDAbtBiTFQeTXouznE3jVoWh1iYcqpzZNYNWgyijLiTPMWeYa1YNUWcYjJBCTqUmR6sfjJj0Wswc6mjbzVk1XdPY4riaNeu1HdZPzHLWX3x/uALWEEzxLa5pwnduQymHyxvwybaTOFzuKILOTQouGJmcm4AIvRZldS3YU+wIWrcUOrIiw1KiOwy+ZAMTI7Hm7jOw7cEz8d9bZgBwdGaV28jLvj/kyIpMykmAQef4GpzXz4YS5YZn8ZH6Ls2W64wcXH53kFN8qXMMRkgRymAEcDVC+nZ///iyD5VG5xBNhKHjq9nRmbGIM+tR12zF9hBMrdxyrFp5nvvOGQEAePabg0qPkOFpMUE9rlGnxTTnFF+5i6xcvDqhkyEad1qNhDizAaOzYnH2qDQIAby5vsBjm/XOQmp5OjEAzBiaBJ1GwpHyBhRUNAS1/71JqKb1uhuXHYcYkw7Vja39tpcL+YfBCAFw9HGQ07aBTsn0l9wIafvxalR6Gccn/zS1WgEAZkPH06+1GgnTnQvIrQnBUI0c4IzJisXlUwYg2qTDscpG2OwC0SYdMto0YwuEMlTjDEb8qRfpyJVTHYWpn20/iWZnfUSrza6sRC0fI8Ax5DU517EYZH/I3oVqWq87nVaDmcPkv2fPPKb1LVY88fke/HnFfjS0WMO9O/0WgxEC4PhiEsJRhxCqK6XUGBNGZcRACIR17ZTeTs6MdBaMAMAs57BYKIoHtzuvcsdmxyHapFdmowDAzKFJXUr7y0WsmwtPoaK+BTucnVcn+KgX8eb0QYnIio9AXYsVK3aXAAB+KqhCg8WGOLMeI9M9MzhzR4R2WnRNYytarD2j146SGQlhMAK4pmz31Cm+j/53N1797iie+/YQ7vlwR7h3p99iMBJmrTZ7j5hKWNvkuCKINuo6rENQg/xl/00PvUrqDeRgxFdjuhnOItYdx6tVXcXXZhfKOjFjs+IAANdMz0WcWQ+DVoOrp+V26fGzE8wY5Jzi+8raI7BY7Yg365GbFBnwY2k0Ei4cnwkAWL71BADgoy2O/549Kq3de33aYEcAt6mgSvV2+n9deQBjH/0a05d+g53Ha1R97GCcCuG0XnehmuIrhOjyzLwmiw2fbDup/Pz5jmLsPhn+v01/xGAkjDYfq8L4R1di+h+/CfsHQD5ZxUSoP8XPnTxUs/ZAedjWTunt5OEGX5mRzLgI5CSaYRfAT0fVm656uLwejRYbzAYthqREAXDUGf1v0Wx8f99cZaijK+RZGK+sdXRInTgwPuhsy0JnMLL2YAWOVTbgS+diehd5WW9pRFo04sx6NFhsylo4ath1ogZ/++YgAKCi3oLbP9ga8oLOmsZWXPfWJsz982qvq2ZXNXZPZiQUU3yrGy248MX1GPPI1/jP5uNBP84PRyvRYrUjMy4C543NAAC8tu6oKvtIgWEwEkaP/ncP6lusKK5pxp3/2h7WanO542VsiIORsVlxSIh0rJ0iFyZSYPwdpgGAqc4CzfXOnhpqkAsR8zNjoXXLLCRFGVUrfj5jRLLHz3Kr92AMSo7C2Ow42OwCv3xpAxosNgxKjsQkLzUoGo2EKc5gasMRdY6Z3S7w6H/3QAjH64iN0ONweUO7Xipq+9s3B/G/vaU4UtGAm9/bgsJKzwZ4roZnof3MA+pP8X1x9WFsLaxGXbMV9324I+iC4z3OhUEn5cTj2hmOjN5n24tVzSSSfwIORtauXYvzzjsPGRkZkCQJy5cv9/k7q1evxoQJE2A0GjFkyBC8+eabQexq31JU1YjtbqnafSV1WBfGVum1zmDE19TJrtJqJOXEwqGa4Pgzm0Y21TnssEHFYERe+GxsVvsF69QybXASchId04NNeg0WjErr0uPJQzXyMMGtc4d2mGk5fZAjgPuhiwsN2u0Cj/x3N/Ie/AobC6pg0mvw5IWjcfEkR0bm7R+OdenxfT33R1tcGQOL1Y7HPvfst6IEIyEqWHen5hRfIQQ+dg65AYDVLpSsU6D2OqePj0iLwdisWAxJiYLFZsfK3f2j10xPEnAw0tDQgLFjx+L555/3a/ujR4/i3HPPxRlnnIFt27bh9ttvx3XXXYcVK1YEvLN9idw7YfyAOKXi/8MupBu7qrbZUTMSExGa5kfu5KEaLqAVnCaLczaNH4sZTnWeWPcU1yo1Al21vchZL5Idp8rjeaPVSPj7VafhoglZeP6yCUiJCX52DgBcPCkbI5wrUU/JTVBS8t7IwUhX60aWbzuBN74vQIvVjgi9Fk8sHI3MuAhcPsXxeV97oFy1v0lb+0rqcKqxFWaDFl/eNhMaCVi5pxQH3VY0ltelCXXNCKDuFN/D5fUoq2uBUafBv2+YCgD4ZNtJr512fSmodGRUhqREQZIknDfG8b74746Tnf0ahUDAwcg555yDxx9/HBdccIFf27/00kvIzc3FX/7yF+Tl5eGWW27BL3/5S/z1r38NeGf7kh3HXQWAF01wXCmt2F0S1NSyFqsNN7+3BZOf+J9SpBeo7sqMAMDsocnQaiQcKK3H8VPdu3ZKX+DKjPgORpKjjRjqrOv4QYVhh5rGVuVqclwIgxHAcYL4y8VjMc+5lEBXRBi0WH7zdHxx60y8d/3pHsNLbQ1PjUa8WY9Gi03JAgVDvnq/dkYutj54plKjkpMUiRFp0bCL0E0h3nmiGoDjYicvPQZnjnQcw9e/d9VDVHWw8nMoqDnFd7dzaGV0ZixOy0lQhuA+3RZ4AFFW6whg0p1T0X8+Nh0AsO5ghZI5CpXV+8tw17+3K7O8+ruQ14xs2LAB8+fP97htwYIF2LBhQ4e/09LSgtraWo9/fY08xjk0NQpjsmKRneBY1TaYsf33Nxbh8x3FKKtrwV3/3q50wQxEbTfVjABArFmPic4Fz5gdCZy8nog/wQgApYlYV2ogappacfO7WzDusa9htQsMS40KyRpGoWTSazEyI6bTQASQ60a6NlRjtdmx0Vk0fOlp2e1mPp3lDA68FZaq4Yj8/ZLiyAZdM91RD/HptpNotFghhHDNpglxAatMnuLb1bqRggrHBYw8u+qiCY4huI8DvBCz2YWSTUlx1joNTo5CXnoMrHaBNQdC991UVNWI6/+xCf/ZfBw3vLNZea/0ZyEPRkpKSpCa6nllk5qaitraWjQ1NXn9nSVLliA2Nlb5l52dHerd7HYnqh2vPTMuApIkKd1Jgylq+3S764rAahd4ec3hgB+ju2bTyOaM6Nm9B3qyJourHbw/5LqRrhSx/nXlAXy+sxjyTMqrpuUE/Vi9gVz4G2ytTUFlozI8Mzg5qt39ZzrXwVl7sFyZHaWmo+WOYEQ+YU/JTcDARDMaLDas2F2CuhYrrM7ajVB2YHUn14rtOF4T1JCK7JhzaCXH+drOHZ0OjeSYOhxIprWyvgV2AWgkINGtbkZetuKHw6ELEP6xoQCtNsfxFwJ4ZW3g39l9TY+cTbN48WLU1NQo/4qKisK9S6orrmkGAGTEORb1kgu8Vu8vD2jufJPFpjSgeubScQAcVwiBftjlPiMxptDXjACufiPfH6roMU2geotAhmkA4PRBCZAk4FBZPcpqmwN+Prtd4HPndNjzx2Xg+csm4LLJAwJ+nN5EDkY2HasK6v0pr4UzPC3aa9+e/MwYpMea0GixqTZrx52cGZGDEUmScOF4xzDR8q0nlayI2aD12a9GLSkxJqXJ3LqDwRfrH630fG2JUUZMynHMgPpfAJmmUucQTVKU0SNbJtdZBft3Ka1t7rRIt77Fivd/cpzTHjg3D4BjPaS2s536m5AHI2lpaSgt9XyDlJaWIiYmBhEREV5/x2g0IiYmxuNfb/P+xkKc//z3+OCnwnb31bdYlam08ljl1EFJMOg0OFHdhENl/g+zHCyrg9UukBhpwC/GZmBMVixabQKf7ygOaH+7OzMyPDUaSVFGtFjtSkEk+cc1tde/wDHObFBOAsF8wR6tbEB5XQtMeg2e+uUYnDsmPWQLq/UUQ1OikBRlQHNrcO/PolOeQwltSZJrVtn3XTgxe2OzCyV74P78PxvtyMZsOFKJoipHZra7siIyuQFaV/qNyEPcAxNdw4TysNf/9vqfWS51BuapbYqjJ+XEQ6uRUFjVqGSw/bXs6/2Y8uQq/OyZ71Dd6L3m5MPNx1HXbEVuUiR+Mz0X04ckQgjgi12BfWf3NSEPRqZOnYpVq1Z53LZy5UpMnTo11E8dNkVVjXhg+S5sL6rGvR/uxI9tTgDFzjd4tEmHaGfBaIRBq1Txrw3gy+mo84M5ONlRDX7+OMf46SfbAhs/7a4+IzJJcvVzaHt8qHPy2jQRBv8/vtO6MOwgz8AYlhoNo657rqLDTZIkTBkU/DGTP+PpnazRI6+Lo/aU/hOnmtBqEzDoNErmFXAUBGcnRMBiteM/m4t87l8oyAHY2oPlQXWermlsxalGx3dVTqIr0JIzy5uOVcFi9W8GVFmdZ72ILNqkR36mY9r6DwH87cvrWvD8asdwy/7SOjy1Yn+7bZpbbXj1O0cjv2um50CjkXC2c9p6qOqHeouAg5H6+nps27YN27ZtA+CYurtt2zYUFjoyAIsXL8aVV16pbH/DDTfgyJEjuOeee7Bv3z688MIL+Ne//oU77rhDnVfQA329p1QZjwWA57495HH/SecQTWacZ2ZIPjkH0gzsiHNseFCy44N53ph0SBKwpbAaZXX+p+SV2TTdFIwAwJRBzmCExVsBkWtGIvT+D6lN7UIR64FSR6ZO7rbaX7jS9YEHC/JnPD3Oe/YXcAWI+0rqVG2TLg9j5CSaPYYfJEnCXGdt2nLnzJOMTvYvFCYMiEeUUYeKegv2FAc+MUF+bSnRRkQaXe//wclRSIx0ZLLkmUS+yJkRb9PGgxmq+WZfqcfwzH82HVcu8mSvrD2C46eakBpjxC+ds6vmO7M6W5xrMfVXAQcjmzZtwvjx4zF+/HgAwKJFizB+/Hg8+OCDAIDi4mIlMAGA3NxcfP7551i5ciXGjh2Lv/zlL/j73/+OBQsWqPQSeh75Sv//TneMq687VIGTbuk++f/bfhFMcM4w2RxAMCKnEbMTHClL93HZQK7olD4j3TC1VyZngjYfO8XW8AEIpAOr7LScBGg1Eo5VNgY8nbqwyrH9oCDWhunN5ABuS2F1wEWmJXIw0kl/lMQoo/JZXX9YveyI/PcakND+7zW3zTTp9LjuzYwYdBolCAtmMcK2xasySZKUZQj8nQHVUWYEcP3tA5kOv7WwGgBww+zBGJbqaJ62Ypdr2m5JTTOed16Y3n/uSGWYNT02AnnpjgVE1WxO2NsEHIzMmTNHWaDI/Z/cVfXNN9/E6tWr2/3O1q1b0dLSgsOHD+Pqq69WYdd7rkPOqbVnj0rHlNwECOE57ayjFO7YbEd77ZLaZo/gpTPePlAz5PRvAMM9dc6akehuKmAFHOPyCZEGNLXalL4r5FuTn2vTuIs26THG2TE10C+8jsbW+7pBSZFIiTbCYrUrTQr9pUwZjem8u+kM58yN74McqhFCYNXeUmwqcJ2Ai5RgpP3U6ym5CYhwK1jN6ubMCOB6zcH0vZGHpXMT2wdacjDi7zTZsk7e15MGxkOnkXD8VJPfdSO7nOuLjcuOVYbL3Wc6vvvjMbRY7Zg4MB7njUn3+N2uFs32BT1yNk1vZrHaccxZFT04JRIXOufAf+UWIZ+o9pxJIzMbdMqVkr/ZkTIvqUZ5LPr7QxV+zcyxWO3KNLNIP4si1SBJEibnyEM1/fdDGKhAZ9PIgv3Ck4ORtG6uLwg3SZJcV8gBBnBywyxfBaLy0Gwg2VB3b64vwLVvbcIvX9qgdHCWswcDEtoHGia9VslMAK4MQHc6Lcf1mq0BZkTl4tW2mRHAFYxsKqjy63E7y4xEGnXIc34Xb/UzED1+qknZt3NHO4KNH45UKhd6cnHtFacPbFcAHuz7rC9hMKKyk9VNsNkFIvRapMWYMHdEKiTnHPjimiZlGwDI8JIinTAgDkAAwYiXD9RpOQkwaDU4WdOsXEl0ptHi6voa6Amuq5S6kS6uA9KfuGpGAvtbTXNbpyaQ6ePykENaP8uMAK4ALpDmZ00WG1qcRZS+VsQd7xyaPVzeEHBreCEE3vi+QPn5qRX70Gqzo9A5U2ZAovemdLfNH4r0WBNmDk3y2gMl1IanRiPGpEOjxaZ0U/XXUeeFXo6X1zYiLQYxJh0aLDa/6lF8ZfzGO7+L5eGXzjRarKh2FtZmxEUgJykSuUmRsNoF1h+uRHWjBftKHPs0bUj7AHByrmP6/ZGKBmW/+hsGIyqTg4PUGCMkSUJytBHjnW2zVzkjYzkoyYhtf+UywbmSqD/ReKvNrlyBua+WGmHQYsJAx3P60+hKvtLWayUYdN37lpjsVrQbzlWLewshhNswTWBZrIkD42HQalBc04wCP3saNLfalHqilOj+F4zIdU1bi04pQaAvcpt1g1aDSB/BfUKkQSk+D3QoqKCyEYVVjZAkIMqoQ2ltC77aVeI2TOO9xmdMVhw2LJ6Ht6+dEpYp2hqNpGRHfioI7CKko5oRwLGekfy4vi5u3LuvpnYwlCbX8PnzdznpzHZHG3VK3d0s53DUmgPl2Hi0CkIAg5MjvX6OYiP0GJXhyMSosWxDb8RgRGXyDBb3N5zcXXXD4UrY7UKptPdWyT7RGYzsPlnr88uvrtmV0YhrMwtGbmftz4e9McgrbTUMT41GpEGLuhYrDpbV+f6Ffs5isytBW6BZrAiDVrna87duRJ4NoNVI3bKIYk8zMNGM9FgTWm3C72ylnOGIj9T7dbKfNDDwwnUA2Oe8+s/PiMV1Mx3t3v+26iDqnetbZcV3fz2Iv04LsL4DcHRMrfYyrdedvzP0Ouq+6k7+rOw+Ueuz8Z2c7XYvCHbvqSJn1uTp4t6c7vzO7q+zCxmMqExeeCnZLdo+3a0yu6KhBRarHZLkfQw+My4CKdFGWO3C5yJd9c5gJEKvhU7r+aec4vZh95WSl4Me96ly3UWn1Sip6k0FwY2b9yfuAWogBayyKW7j6v6Qv/zjIvw7sfY1kiQFPMX3VKN/9SKyicEGI84uryPSonHJadnQSMBBZ8PEgYnmbuusGgw5I/pTge/vJ9mOE44C0UFJkR0G4pPdLsI662MiZ7Dbdl91NyDBjIRIAyw2u8/hJCXb7XaBefqgRBi0Ghw/1YR/bixUbuuInBXf5sewUF/EYERl3mo4xmTFwqTXoLLBgu8OVCj367XtD78kScqX0xYfb8raTmbAjB/gqAYvrmlWCqs60mCRm2iF58sr2C/j/sh9SM3b+8eXic409iZ/r/KdJ9ZYc/dN+e5pTg+wYVxdgNPk5ff/9uPVAU1xV7q8JkciPTYCM4YmK/fJwxU91aiMGBi0GpxqbFWmInempqkVXzi7SsuzwrzJz4iB2aBFTVOrEph54+ox0vFsJ0mSlBo+X3Uj3iYlmA06nJbr+NvKQ6un53b8d5EzMftKaj3q+PoLBiMqk1O0iW6Fa0adVvnCkaf4pnupF5H5e3KWv/S8BSMRBq3SRdBXKrQpiL4VamIw4j/5Sy3Yq97xA+IgSY5eFP40xXPPjPRXcmZkx/EaNLT4PknIwySRRv/+RoOSohAboUdzqx17AijolAuL5dqzG2YNglYjQauRcNGELL8fJxyMOi3ynDUS25xra3XkhyOVmL70G/zbOVuoba8Ud45MaxyAzoeoldo+H3VQ4/2sGznptvCpO7njLOAIorw1WJOlx0YgLcYEu0C/bHXAYERlHbVVl8cD5dbPbd+07iYMdH0AOkthyl96UR1cgU3J9a9ITGmiFUBHTzUFeoLsz7oaOMaY9Bie6lhWfrMfw2I1TYENOfRF2QlmZMVHwGoXfmWU5OFTf4c9NRopqIBcmeXkHO6dNiQJX9w6E1/eNjMsU3YDJRf2+wpGlny5T/mumzciBefkp3W6/aSBvoci/cmMAK5sha+hk5Md9I765cRsJDlrUq6dkdvpY3g8n49j0hcxGFFZTQdt1U9v8+XQWWttOYVZ1WBRepZ4I89f72ilXTlV6yszIqcEzX5eyaktOsATZH8W6CJ53kzKcdbo+HHikzMj3bVmUU91egDr1MjZk0AaCCrBiJ8zaoQQysrf7ifA4WnRGOb8LPV04/wIRsrrWpRVyTf+fh5eu/o0n8OT3t7fq/eX4cxla7Dog21ostiUQM5XIz85u3yiukmZuehN21XYZQmRBnxx2wysunO20gitM67pxP3ve5DBiMo6yozIdSMyuaGON0adFqOd46KdXSl1NkwDuD6URyoaOl37Ipj24mqT97U3DtUUVjbimjc24r4PdwTcNjxQcuDYlZlPypWjH8c6mBNrX+TqN+I7GKl3/o0CaSCoLAVR0Hk2VNZgsSlDdslemnb1BmOdwcjuk7UdLm4nn5RHpEV3OsThbvyAeGgkRxOy4pomNFqsuO39bThYVo+Ptp7AX/93QLnI89al1l2MSa+sfLzzhPehEyGE0qXVW8Y7Jdrkdz8XeVhoa2F1QL2A+gIGIyrrKBgx6rQeRWVyH5COKIVTRZ0FI47niuogHRxnNmBYquND0NnVR2MQC6+pLZATJAC0WG1YsbtEucIJp3s+3I5v95fj/Z+K8Mev9oX0udSo71Gmj5+o8Tl9vL7F+XxhmGnVk8iZzZ0napQhg44EOkwDOLIEylIQfryn5do0g04Tlin5ashJNCPOrIfFalcagrV1wLlidGcXb21FGXUY6axH2VRwCmsPlHssWPfW+gJsd85U9BWMAK7syK4OgpHKBosyQ7KrSybkZziWBCmra1GyLf0FgxGVdRSMAMATC0djcm4CnrxgtM8GUmOy4gAAu050XNBWp1y1dpxCH+t8nO2dBCNN8jBNGDMjrv4qNX5lF258Zwt+9/ZmnPfcurDWmVTUt3h053z3h8KQrrwpXw13ZeZTVnwEUmMc08e3+5g+3qhc5ffOE55aMuMiMCDBDJtd+KzBkrNJHV0keBNh0CpNr/zJDsrDZ/Hm3jvlWpIk5fupo4sleUbM0NTAOsW6142s3ONoNvmb6bnIz4xBi9WuXIB11KXW3ehMx9+lo2Ck2DmTJjnK2OWmkREGLUakOYbZOvvO7osYjKjIarMrV03egpEBiWb863dTcdmUAT4fS/5i2ltc2+E6C76GaQBXKrSzk44yTBOmmhHAcYJMiTai1SZ8VpLvOVmLb/Y5vmDK61rwwreHu2MXvZJ7owxPjcbY7DhYbHZ88FNRyJ5PjQZ1kiQp4/W+etk0qFCj0lec7myo5Wv9EDmbFBXg0JbS8dOPYCTQXiY91VgfdSNyYag/GQx38rDvj0er8M2+UgDAmSNTcf3MQco22QkRSO6g4Zk7OTPS0TDNiQ5WYQ+Wr2PSVzEYUVGj2xV9VxuI5SRGItKgRYvVjiMdrC8jByOdXYHJJ53tRdUdNgGS9ztcs2kAz/4qm451fuUpL7cuNytavu1Eh2POobbf2XhqTFYsrjh9IADg35uKQjbeq9Y0bDnz5ivwC+Yqv6/yd1n5+hZH1iLQ74BAZtT0lWDE14waV9+mwIY/5MzIvpI6nGpsRWyEHqflxONno9Mx0JkNOW9Mhl9ZpVEZjmDk+Kkmr+sHdTStN1j+FPb2RQxGVCSfKDQSYOxiuk6jkZQPQUfpwXplNk3HwzTD06Jh1GlQ22xFQaX3oKaxJfzDNIDbl7GPGTVbnR/SO+YPRVKUEdWNrfjuYHmod88ruWFTTlIkzslPg1GnQUFlo18LdQXDtWJv14KDsQEGI+HMmvUU8oyanSdqlIaD3jTImZEAj5k8k2Jvca3PoUplmCayd89ykrMAR8obUNPoeUyFEEpHa28r63YmLdaEbLdVi+eNSIFOq4Feq8HHN03HhzdOw6Izh/n1WLEReiWA2XWy/efF1X1VnbWb5GBk54mafrVeF4MRFblPu1RjHHeUMlbp/cTmzzCNXqtR0owdDdX0hGEawHN6Y2eZhaPljqAqLz0G5411LNX95a6S0O+gF/KiZFnxEYg06jDHuR7FFzuLQ/J8ja3qBI7ybK3CqsZOV4uV3xuBzAzpq9JjI5CTaIZddN7DwpVNCixQyIyLQFKUAVa7wG4vJz13tZ3UpvUmCZEGZQhmx4lqj/vqW6xKjZSvfiDeXDDe1fjtcmfWUn7OiQPj2y2h0RlXEWv772J5Zo5amZHByVGIMjpWNZYLePsDBiMqalA5w5DvzIx09MWkDNP4GJtWisQ6aNzjWgU2vMHIqIxYGHUaVDe24nC59yyOEELJ8OQkRWLeCEc3xu8PVYRlKtxxZ0vubOcX6oJRjoZMaw6EJlPTrNKihrERrimLOzrIvAGu93Q41i3qifzpN1IXYAdWmXstz7aizoMRpctrHwgSldfc5vtJHqKJMuqCqlm6+YzBWHzOCLxx9WnKhU6wRncyo0YeRh/k5/RdX7QaSXm+/lTEymBERWqf1OXMyJ6TtV7rPer9mE0DAOPkrn4dpOR7wtRewDFNUU7bdlTEV1FvQaPFBo0EZMebMSknHgadBsU1zR3W1oSKEAIV9Y6sglwIJ9cV7DlZ22kqP1iuYZquv8fkNT52dPKF19ADZlr1JK66EX8yI4F/nvytF6jvQ0FiR6852CEamVGnxe9mD8YZI1K6snsAXMFI2yJWq82OY5VyMOJ9JeFgjOuHnVgZjKhIrfF82ZDkKBh1GtS1WL0uJtXZQnnuxjkzI3s7aC6kdkanK9zHS72Rp83Gmw0w6DQw6bXKEuzfH/JvVVW11LdYYXHOdEqMchQSpsc6poDaRWgauDWqGPDKRazbO6kbaWwJ34rOPZGcGdl9ssajd4XMbhfK90AwwYhrJkXn752+VFjsmvFX45HdlKfs94SmbvLsxsKqRo/alp0natBqE4gx6ZQ1gtTQH4tYGYyoqLFF3Z4MOq0GI5zNftoWTtntwpUZ8fGFlJ0QgdgIPSw2u9cxSDmjE2haORTkD723QjHA1ewpwW0hwulDkgAA6w52bzAit4eO0Gs90sjymkA/dnL1HCw1FzVUMiMd1BIJIZTMSH/vMyJLjTFhUFIk7AL4ycsyCw1uq60GE8DJAWJRVRMqO+lXU9+HgsRRGTHQaSRU1Ld4NHyTu0b723k1lOLMBqUg1n3Y/L/bHbVh0wYnQaNRr9+LHIwcKK3za3HGvoDBiIrUTKHL5JPz7jareTZYrJAvInwN00iS1GGaEeg5wzSAq1Cso/4qlZ0EIxuOVHY4fTkUvO0LAEzOldcE8m/J+UAo7eBVyL6NyoiBRnKMzXvrZNvcaod8OPvCSU8tU+S6ES9TfOULBJ1GCmpGXWyEHoOd6f7OegMpmZE+0KbfpNdiRHr7Rl+uab3hz4wAbnUjzmDkk20n8Pr3RwEAv5qk7irJqTEmpMc6VvDtaDZlX8NgREVqptBlcjDSdmlx9y899zVvOiKf5L1N5VTzarurcp39VZpb7V6LWKu8BACjMmIcw1mdTF8OhSpnvYg8RCObkutact5Xu/VANbU6AjQ1WoCbDTplUTVvJz73q/ze2nI8FDrrN+IeJAQ7o26sH0Ws8t8m0OnDPZW3Tqxl8sq6PSQYkVst7DxRC5td4PHP9wJwrMY7Ly9V9efz1Z22r2EwoqKmIBbI8mVkuvfMiPtMGn++9OSUfNso2z0V3xOCEV/9VbxlI/RajbIWRUe1JqHQUev/7IQIpMeaYLUL1VffVLt1f2dDNe61RGqmoHu7052Zrz3Ftahu9JwWrQyfdOE7wFcjMMBt/Zs+MJsG8N51VMmMBDGtNxTkC7rdJ2rwU0EVyutaEBuhx71njwjJ8/W3IlYGIyqSmx2pOUwzIs2RSq+ob1GuFADXInn+rqYqpxj3ldSixeq6Wm+x2pXhnp6yGJo8i8hbYFHV4PiCSmwzNOJag6f7gpG6DprOSZKkDNX84KWuoCvUHgrsrBNrQx+qS1BTSowJg5MjIQSwsc3ft96Prsi+jHXrmtzRdPW+NJsGcCtcP16jDM8G2301VPKdFzxHKhqUJR/OHJna5fVoOuLPumJ9CYMRFYWiX0eEQavMX9/t1tVTaXjmZ2OlrHhHEWurTeBASb1ye6PbMEJPScXLgZO3/irehmncf2dnm8ZJoVTfyYyGUNWNNKo8pObeibXtiY+L5HXs9A7qRupVqOUYkRYDg06DmqZWFFS2n0UH9K3ZNICr0VdTqw2Hyh3fTz1tmCYxyqj05vl46wkAwLmj00P2fGOyYqGRgJM1zR4Xon0VgxEVNSopdHW/ILzVjfjTfdWdJElKSt494yDvs1GnUdZ6CTclHeqlv0qls04joc0CV65hqNpua6HsWjW5/d9AnlGztbDaIxPVFUKIDrMxwRqWFgW9VkJNUyuOn2ryuK++JTTv576go34jajSJM+g0ylW4tym+drtQFjDsK5mRto2+mlttqHV+x/WUzAjg+rsDjs/9tCGJnWzdNZFGV01XfxiqYTCiIrkng9q1F2oEI4D76pPVym2NPfBLbVBSJEx6DRottnaNzOTMSNthmkHJUTAbtGhqteFweT26Q2cdcAcnRyEx0oAWq93n+i/+am61o9XmCLQC+bt3xqjTKl94beuSXO8NZkbakouU9xbXevQbcWXLunbMxnbQlRTwXJCzr2RGAM/CXXlar0GnQUxEz3mNv5romjVzyaRsGHWh/Wz0pyJWBiMqUjuFLhuZ3n7YwlUz4v8VsrfpvWosSa82nVbjVrjreSKXVyttO0yj1UiuNXi66YNbrwSE7f8G7nUjbesKgiX/zTWSuoWLrunjnseareA7lhxtRI5z8TT3E0VnQ3eBUJpeea3lcTyHRoJfM+l6i3HZrs+v3PAsJdqoyjpfahk/IB5/vWQsbp03FHf4udBeV8hFrJ1N8+4r+s47uQdwTe1V98tbnilSUNmonJDqOxki6IgcjOwvqVOGDhp70Ewad/le1oKw2wVOObsftg1GAGBMJ71UQkEJCDs48cjByI8qBSNyx90oo07V2S3uw2LuuEhe58YPcHT+dZ8xpVYANz7b8dh7T9a2G+arcyuS7Ukn6q6SMyP7S+uUjtM9pV7E3QXjs7DozGHdEqQrNV1FNd3aQykcGIyoSO1pl7KESAPSYx3jpvtKHB1U64Ko2s+Kj0Cc2VHEut/5OD2px4i7/Iz2gUVNU6tSDxJvbh+MjFamqXZPMOKrWFFO5W8uqPLawC1Q8hh6jMortSpdb9sEcfU9aJmAnmi886p1q9tQilqZkeyECCREGmCx2bG32LNrcl8rXpWlxZiQEm2EzS7wzT7HQpM9qV4kHIalRiFCr0Vdi7Xbhp/DhcGIikIxtVempNKdJ4zaIIZpvHVibbCEJpvTVe6LBMqzPOQeI9EmndfpdPI01T3FtWhV4eTvS4OPGqHhadGIMenQYLG1yzoEQ142PpC/uT/y0mMgOTuxyulxwG02TR876alFzl5sLTylXLWqNeVWkiSMzfI+7NhXh88kSVKyI1/udLRZT4vt38GITqtRvrP7et0IgxEVudZ4Uf9LYmSGZyq9PogCVqD9UtiB9ivpLkNToqHXSqhttiqzPDoqXpXlJJoRbdLBYrUrmZ9QavYxLKfVSDgtR726kdog/+a+mA06DHJOWXQPmlx9RpgZ8WZEejRMeg1qm61KobWcsVRjtlN+B1Pc+1qPEXdyrYzVGdzJU2n7s/7S/IzBiIqUdUNCUAwqF3TucfYaCWY2DeAKRuShjPpOZoSEk0GnwfA0xywPOXCSG555qxcBOp6+HCpyMNJZEeGUQerVjZQ6149JDcHCYe7dJWUNnNrbKb1WgzGZcQBcdSNy9kqNGSCuTsTt16UC+t4wDeAa+pIxGOk/K/gyGFFRqKb2Aq5hmgOldbBY7ahrCS6jIZ90DpQ6ilj9Xfk3HOS6EXlhKlcr+I6L2kY7Tw7dUTciZ8I6Cz4nO+tGfiqo6nIB2vFTjqK+zDj1liqXeVuQ0VXAysxIR5S6EeeJolbFzIj8NzlY5vjMy5RW8H0wYzVxYLzHz/K08/5MDkb2ldQpF7x9EYMRlQghlNk0oUifZsVHIMakQ6tN4GBZndLbINAvvbZFrHWdTE8Nt7YnSGVhug4yIwCUcfbu6MTapGRGOj4pjMqIgdmgRU1TKw6UdW3o6ES1Y7gqK179YKRt4Ae4rsD74nCAWuRgZMuxtpmRrn+ePLoml7reO/V9uE2/UafF1dNyAAAzhyb1+5oRAMiIi0BajAk2u8DObirODwcGIyqx2OzKTI9QFLBKkqRM8d1zshanGjqe4urrcdyHajpr3BVuozI909RVzh4j8Z28ZnlGzb7iOmUYJRSEEGh2rqDbWTCi12o8pud15fnkWRXZCeagH6cj8nurqKoJNc7p0321UFJN8vTeA6V1qG+xKoXlMSp8niRJ8trwsKEHZzPVcP+5eXj+sglYdvG4cO9Kj6EEvV6a4PUVDEZUIg/RAIA5RA3E5DHkLYXVyvBKoMEI4FnEWt/i6l3R0+S1WSTQVwEr4BjCSIg0wGr3vJpUW4tb2txX4yllynEXsjU/HKnCieommA1anJYT7/sXAhRnNigZl93FzplWIRx27CtSY0zIjIuAXThmvcifS7WmX3trSNeXC1gBRwB/7ph0JPfAHiPhMsEZ9G5ReRXwnoTBiErkIRqDTgOdNjSHVS7OXHvAMQdfq5GCGpt2z4wE0zytu0QYtBjsXCRw18maDhfJc+d+Ndm28E9N7lmXzjIjgFvn2y6kWF9bdwQAsHB8ZsgKSttehQdbl9TfyLMd1h4oV1bAVuuYKUWsXjIjfTUYofbce9p0tJJzb8dgRCWhanjmTu6jIdcOxJv1QXXilK/UD5TWoazWMUNFrYXX1JbvNlTjWiSv82yQ8jteVv1Vi1wvotNI0PsIPuUgcm+xZyGiv6w2u7Ig22WTBwT8+/5S6kaUad89t56oJxnvLDBcuacUgCPLqNaaJfnOfjt7i10LQPbl2TTkXX5mLPRaCRX1Le0WtOwrGIyoRFmXJoRrvOQkmj3Gor11IfVHZlwE4s16WO0CB8scXf16akrUPU3tzzAN4Dqp7g7h9F65XsSfadwDEhx/N4vNHtTQ0aHyetS3WBFt1ClTvEPBvS28Y4Xgnps160nkuhG510i6ikWXuUmODpyNFhsKKj17mTAz0n+Y9Fql11RfHaphMKISZXw9hF8Qjj4accrPA4IsZJQk16Jysp64BgTgSlNvL6pRuoOm+eizoVxNltSFrBOr3Ebf5EcmzP3vFkz/k4IKx5TeQcmRqq5J05Yc+B0ur0dVg0W5EmdmpHP5mTEwuGXH1JwBotVIGJHuuapyg0orA1PvImfgtvbRIlYGIyppau2edTymOBdfA6B8SQVDHjoAHKt/Jkb1zGBEnuVRUtsMuwD0WglJPvY1O96MaKOjE+uhstCs59DkR8Mzd/ltms0Fosi5aNiAxNA2gEqJMSE52gi7cPRFAeQVgnnS64xRp8XYbNfnyVewHKi2S0E09OGpvdSxCQP7dhErg5EA2ewC/9hQgE+2nfAoJJKHaULRfdXdWaPSlP+X18YIxmi3zEhilBHaEF5xd0VshN4jA5QWa/KZHdBoXNOg2y7+ppYWPxqeuVOKQ4sDL6qVVzAdkKB+f5G25P3ccLgSgCMr0pdWhg2V6UOSlP8fkhKl6mPnt1kKQu4xFKvygonUs8mZkT0na0PatiBcGIwE6L2NhXjwk9247f1teG9joXJ7YzddrQxPi8Z7103Bi5dPwLy8lKAfZ5xbIOMr0xBu7lmcjFj/Tsju9Q+h4E/DM3fySX5fcW3AK/j6OzylBnk/5YJZ1ov455LTsmE2aGHQanDe2AxVH3uUEozUQAjBYKSfyoqPQHK0EVa76JblLrobg5EAfbzluPL/f//uqJIdqevGZb2nDUnCOaPTu3TFmhZrwvnjHF+a/2/uELV2LSTcrzonDPQvGyTXjYQqM+JPwzN3OYmRMBu0aLHacdRZ6OgvpXC3G4JG+cS331lo21NnWfU06bER+PSW6fjopmnIULld/7C0KOg0Ek41tqKwqlEJhBmM9C+SJLnVjfS9oRoGIwFosdo8elccrWhoV1TWm8Zxn/rlGHxx60z8bHR6uHelU+fkpyHDWRS4wG2YqjNyanuP25RINQWaGdFoJOSlt1//xR/KlOYgGtwFSs6MyFJjenbWrCcZkhLdrjBcDUadVhn6kYfPABYW90dK3cix6vDuSAgwGAnAkfIGWGx2xEbocbbzpPj5zmIA6NHNwzpi1GmV2oqeLM5swIo7ZuGr22cqi0b5Mig5Cia9xmNKpJqalZoR/z9CbVde9pe8QGCSj/4qapCLf2Vpfg6LUWjJQc73Si2PrsfWeVHoyJmRLYWn+lzzMwYjATjhbDaTnRCBc0Y7gpFv95UBcGvRzOXWQyLapMeINP8DJ61GUk7+oRiqaQ6wgBXw3trbF4vVrtQIdLZasVrcMziAuj0zKHiuwuIKABw+66/GZMVBp5FQVteiNL/sKxiMBOBkjeOPnxEbgVlDkyFJjmWdS2ublWW9e+KCc/1VKItYmwMcpgHgsdChv1c1ciAiSd1XIzB+YJzy/wxGega5lqeiXl4sksFIfxRhcGWz+9qieQxGAiBnRjLjIxAfacCYTNdaMWxE1PPIdSOhWHY70JoRABiWGg2tsxCxuKbZr9+pc64CG2XovrT8z/JdNURnjAh+xhapJ69NTyF/Z5VR36MsmnesbxWxMhgJQHm9Yx2XVOcUyxlDHbM8fjhSpcym6U0FrH3dKHlGzcka2FUuYm2yBDabRt52qLMQcY+f2ZpwtGQfmx2Hl6+YiP/eMqPHT/vuL6JNeuQkuvrtZMYzGOmv5CLWzQxG+q/qRsdVarzZkSKVI9Qdx6uVYRoGIz3HsNRoGHUa1DVbVS9ibbYG1+RuZIAzasK1WN2CUWnKgorUM4xym6mTqfL0Yeo9JjqDkT3FtWh0LprYFzAYCUB1o2O8NjbCMatBXm/kUHm90iUzqRuKDMk/eq1GGV9Vu0lQsyWwdvAypW6k2L/9kYdpYiIY5PZ3892aHI71c1YZ9T0ZsSakxZhgs4uglpfoqRiMBKDaWUwY58yMJEcbkRkXASFcs2l66uq3/dVYZ8C4vUjlYETOjAS4bsvIjN6RGaGe55z8dJw1MhW/mz0Ip+Uk+P4F6pMkSVKyI31pqIaXWwFwDdO4+j2MzY71mGKV2A29IMh/8ho8O09Uq/q4yqq9AQ7TjEp37M/xU02oaWr1OUOm1pkZ6U39ayg0THotXrlyUrh3g3qA8QPi8PnO4j7ViZWZET/Z7UIZppEzI4DryhtwdMjUa3lIexJ5NdVdJwJfE6YzgbaDl8Wa9cp4vz9FrOEoYCWins09M9JXmp/xzOmnxlYb5AkZ7lez7mO33dGumwKTmxSFSIMWTa02HC5Xr4i1KYimZ7JAVvBtYDM9ImpjVEYsDDoNTjW24kiAa131VAxG/NToPCloJMCocx228QPilP/3t1U5dR+tRlKan20/Xq3a47qangX+ERoZQCfWxtbgalOIqO8y6DQY65zt5qvfyJNf7MWYh1fgnv9sV73FgZoYjPipwVkjEGnQeayWa9Rp8bdfj8eMIUm466zh4do96sSYLPWbnwXTDl4md9P0Z5hGrk0xMxghIjf+9BvZeLQKr6w9gtpmK/616Tje3VjYXbsXMAYjfpLT5WYvHVZ/MTYD71w3BWlsnd0jyVOwd6iYGQmmA6tMzowcKqtHi3NWTkfkPgIRHKYhIjeTBjpmVG3qJBj5wrmQq+zlNYd7bHaEwYif5JMPx+57Hzkzsre4DharOkWswRawAo4+AXFmPax2gf0ldZ1u2yhnRoJ4HiLqu+Qi1kNl9crkirZ+OOJY5fnpS8Yh0qDF8VNN2BXAQp3dicGIn+TMCMfue58BCWbERuhhsdlxoLTzk7+/mrpQyyFJkpKt2V5U3fnzcJiGiLxIiDRgUFIkAGCLlym+Fqsdh8rqAQCn5SZg1rBkAMD/9pR2304GgMGInxotzIz0VpIkKTNY/Cka9cVuF0qGxaQL7iM0zpmt2eojGJHfdwyCiagtOTuyqaB9MHKkoh5Wu0C0UYeMWBPOHJkKAFi5t6xb99FfDEb81FnNCPV88owafzufdqbZrc4j2CBhnHMW1jZfmZFWOTPCIJiIPE3KcQYjXupGCisdS5TkJkdCkiQlM7K3uBY1zgaePQmDET81Ml3eq8mZkV0qrFEjD50AgEkX3PtBbpZ3pLwBNU0dfzHIBax83xFRWxOdRazbi6rR2qapY0ltMwAg3TmxIinKiFx5WKeo53VuZTDiJ1cwwivU3kieTru3uA62LlaTNzuHaAw6DTQaycfW3iVGGTEgwbEkfGezfDhMQ0QdGZQUiTizHi1We7usb3GNIxhJi3HN8pRXmt/sZVgn3BiM+KkrHTcp/HKTImF2dmI9WlHfpcdS1qUJsl5EJnfv3VZY7fO5mBkhorY0GgkTB8h1I1Ue95XIwUhshHKba1jHc9uegMGIn+R+EMYunoAoPLQaCSPT5aGartWNyAFCpLFrWTK5Y29HdSMWqx1WZxbHrGdGjojam5jjvfmZHIyku/W/kr9zdp+o7XH9Rnhm9VOLs6+EMYj239QzqFU30mBRZ5q3/MWw/Xi118Wu3GtTOExDRN64Nz9z/x6Ra0bcm3EOSYmCQadBXYsVRacau3dHfeCZ1U8tzjoBY5AFixR+o4KYUfPOD8dw+pOr8KcV+5TbmlSa5j0qIwY6jYSKeguOn2pqd39jqyPo0WkkGJiRIyIvxmTFQq+VUF7XonyPCCFQXOP4f/fMiF6rwYi0aABdzxCrLahvuOeffx45OTkwmUyYMmUKNm7c2On2Tz/9NIYPH46IiAhkZ2fjjjvuQHNzc1A7HC4cpun98p1FrLtO1vi17HZRVSMe/GQXSmqb8fy3h7F6v2N+vlpFpSa9FnnOoSNvQzUsXiUiX0x6rVKgL9eC1DS1Kl2iU2M8lylRs+eSmgI+s37wwQdYtGgRHnroIWzZsgVjx47FggULUFbmvZHKe++9h/vuuw8PPfQQ9u7di9deew0ffPABfv/733d557uTKzPCYKS3GpoaBYNWg7pmK4qq2mci2vpwy3G4D6u+96NjkakGFafbdlY3wuJVIvLHpDbNz+SZNPFmfbslK0YpF2W9PDOybNkyXH/99bjmmmswcuRIvPTSSzCbzXj99de9br9+/XpMnz4dl112GXJycnDWWWfh17/+tc9sSk/jqhnhiaG30ms1GO5MUfpzVfD9oQoAwJVTBwIA1h4sR4vVptowDeBWN+ItGGHDMyLyw6Q2RaylznqRtlkRwC0zcsK/DHF3CSgYsVgs2Lx5M+bPn+96AI0G8+fPx4YNG7z+zrRp07B582Yl+Dhy5Ai++OIL/OxnP+vweVpaWlBbW+vxL9w4TNM35Gc6i1h9BCNWmx3bjzu2uXpaDpKiDGhutWNbYbWqwyfy9N6dJ2raNS1SnocBMBF1Yrxzeu+B0jo0Wqwoq20B4D0YyUuPgVYjobLBglLndj1BQGfWiooK2Gw2pKametyempqKkpISr79z2WWX4dFHH8WMGTOg1+sxePBgzJkzp9NhmiVLliA2Nlb5l52dHchuhgQLWPsGOUW500fx1rGqRlisdkTotchJjMTUwUkAgPWHK1XtijooKRLRJh1arPZ2K/g2sfsqEfkhNcaE1Bgj7MJRoF+iZEaM7bY16bUYnOzoxKpGR2q1hPwyf/Xq1XjyySfxwgsvYMuWLfjoo4/w+eef47HHHuvwdxYvXoyamhrlX1FRUah30ycLa0b6hNHOGTU7O5hOKzvgDAyGpkZBo5EwbXAiAMeS3Gp249VoJGWopu2ieSxgJSJ/ua8ELg/TpHnJjACexfw9RUBn1qSkJGi1WpSWei5BXFpairS0NK+/84c//AFXXHEFrrvuOowePRoXXHABnnzySSxZsgR2u93r7xiNRsTExHj8CzclM8I+I71aXnoMDFoNTjW2orCq43n2x5z3yWs5yG2Ud5+sRX2zI2MRqVKQ0FHdCNdDIiJ/jXWuBL7jeI0SjKR0FIw4L8p8LdTZnQI6sxoMBkycOBGrVq1SbrPb7Vi1ahWmTp3q9XcaGxuh0Xg+jVbr+HLtScUzvrhqRnhi6M0MOg1GZnQ8nVZ2wjlfPzPO0Up5cHIkjDoN6lusyu/FmfWq7JO8aF7bNWqauB4SEflpjNv3iFwL0lFm5LQcR6O0zQWnurxWl1oCvsxftGgRXn31Vbz11lvYu3cvbrzxRjQ0NOCaa64BAFx55ZVYvHixsv15552HF198Ee+//z6OHj2KlStX4g9/+APOO+88JSjpDZTZNBym6fWUYZFO1oQ5Ue0MRuIdwYhOq1F6guwvdQzhxEcaVNkfOTg6Ut6gBL0Ah2mIyH9jnJmRgspGHHB+R3krYAWAvPRoRBq0qGuxtqtVC5eAL7kuueQSlJeX48EHH0RJSQnGjRuHr776SilqLSws9MiEPPDAA5AkCQ888ABOnDiB5ORknHfeeXjiiSfUexXdgMM0fcf4AXF4c72jDXtHTjqDkYw41yJT+ZkxHtmUBLM6wUh6rAnRJh3qmq04XNagBCdyB1YzZ9MQkQ9xZgMGJppxrLJROV+lxrYvYAUcF1cTBsbju4MV+KmgSvnOCaeg8r+33HILbrnlFq/3rV692vMJdDo89NBDeOihh4J5qh5DvmI1aBmM9HbysMjuk7WwWO1eW61XNlgAAMlRrg+zXPQlUyszIkkS8tJisLGgCvtKapUvBjY9I6JAjMmKw7FKR71bhF6LxEjvwQgATM5JwHcHK7CxoApXTcvppj3sGM+sfrLaHONqegYjvd7ARDPizXpYrHbsLW4/xVcIgVPOYCQxyhVwjGobjKiUGQGAEemOZmz73FKm8jCNicEIEflBLmIFHMO/Wo3U4ban5TrqRn46WtUj6jd5ZvWT1TnzR6ft+I9LvYMkSUqzMW9FrLVNVlidRV0JbtmPoalRHtvFR6pTwAoAI9Ic2RD3YETJjHCYhoj8cNZI16xWuUV8R8Zlx0GvlVBW19LpzMLuwmDED0IItDozIzoND1lfMNZtTn5blQ2OSvQoo85j9pRJr4XJWTOk1UiqzqxSMiNumRpXczXOpiEi3wYkmnHP2cNx8aQs3Dx3SKfbmvRape/SxqNV3bF7neKZ1Q/uM590naS9qPcYNyAOgPfMSJVziCbBS03IP34zBQMSzHj5/yaquj/DUh3BSFldCyrrHcEQZ9MQUaBumjMET/1yLGJMvjO38hTfLZ3MLOwuDEb84L5mCIdp+oZxzszIkYoG1DS1etxX2UkwMjk3AWvvOQPzR6a2u68roow6DEgwA4Ay1c61UB6DESJSn7ymzdbCU2HeEwYjfnFvCsNhmr4hPtKgNDRrW8QqZ0YSVZot468RaZ5FrMyMEFEoTRgYB8DRO6muubXzjUOMZ1Y/yDNpAGZG+hJ5Cu2ek96DEW+ZkVCSgxE5OGpskdvOs2aEiNSXEm1CVnwEhAC2F4V3nRoGI36wuq2hw5qRvmOks6Pqng4yIwlR3RuMDHfOqDlQVg8AqHOugRNtYjBCRKEhr7u1+Vh4h2oYjPhBnuap1UiQJAYjfcUoH5mR7h6mGe7MjBwsrYPVZke9czZNFIMRIgqRCc5i/i1hrhthMOIHuYCVWZG+RR6mOVhWB4vVlf1yFbB23L0wFHISzTDoNGi02LCvpA5yHyJ/quKJiIIxzpkZ2XWiJqzNzxiM+EEuYGUw0rdkxkUgxqRDq03gYJmr2dgpJRjp3iBAp9VgSLKjsZqcMtVrJS7OSEQhMyItGlqNhMoGC4prmsO2H/yW84PS8Iyt4PsUSZK8FrGeanQEI2q2e/eXPFSzyRmMRJv0HBokopAx6bUYmuK4CNp1InxFrByM9gMzI33XqIxY/HCkyqOIVc6MhCMYkZufbS5wdERk8SoRhdrSi8YgLkKv9DoKB37T+UGpGeG03j5HnlGz25kZaW61ocHZ30OtVXkDIU/vPelMlzIYIaJQG+dcqyucOO7gB1dmhIerr5GHafaerIUQAtWNjsY/Wo2EmDAEAsOcwYgsHNkZIqLuxrOrH7hib981JCUKBq0GdS1WHD/V5FYvEp5ajYxYE6KNriAoPdbU7ftARNTdGIz4wbViL4ORvkav1WBYmqN4a/fJmrDWiwCOolr37EiGs2U9EVFfxmDEDxym6duUTqwna1ElZ0bCUC8iG5MVq/x/RiyDESLq+3h29QMLWPs297bwrsxI+BqNzR6WrPy/vJAVEVFfxlJ9P3Bqb982KtORidhzshajM+MAdP8iee5mDU3G3QuGY2R6DIakRPv+BSKiXo7BiB/Y9Kxvc59Oe7TCsUhdOGexaDQSbj5jSNien4iou/Hs6gdmRvq2aJMeAxMdzX5WHygHACRGde+6NERE/RmDET9wam/fJ6/gK/cZyYpn4SgRUXdhMOIHq42zafo6uYhVFs62yERE/Q3Prn5QMiMcpumzJg5M8Pg5m8EIEVG3YTDiB1cBK4ORvsp9Cm16rAlRRtZ2ExF1FwYjfmDTs77PqNPiqV+OQZRRh9//LC/cu0NE1K/w8s8PbHrWP1w8KRu/mpgVljVpiIj6M17q+0HOjGhZM9LnMRAhIup+DEb8YHUGI3oO0xAREamOZ1c/WFnASkREFDIMRvzAqb1EREShw2DED1ybhoiIKHR4dvWDjZkRIiKikGEw4gc2PSMiIgodBiN+cE3t5eEiIiJSG8+ufpALWPUcpiEiIlIdgxE/WFnASkREFDI8u/rBqqxNw8wIERGR2hiM+IFr0xAREYUOgxE/2JgZISIiChkGI35g0zMiIqLQ4dnVD3LTM67aS0REpD4GI35QVu1lzQgREZHqGIz4QZnay6ZnREREquPZ1Q9ctZeIiCh0GIz4QekzwgJWIiIi1fHs6gfXMA0zI0RERGpjMOIHNj0jIiIKHQYjfnCt2stghIiISG0MRvzgmtrLw0VERKQ2nl39YGXTMyIiopBhMOIHuYBVzz4jREREquPZ1Q+uqb3MjBAREamNwYgfrDY2PSMiIgoVBiN+sHLVXiIiopDh2dUPyjANMyNERESqYzDiB2VtGtaMEBERqY7BiB+sbHpGREQUMgxGfLDZBYQjFuHUXiIiohDg2dUHeYgG4DANERFRKDAY8UGeSQMAOmZGiIiIVMezqw8ewQgzI0RERKpjMOKDxzANC1iJiIhUx2DEB/eZNJLEYISIiEhtDEZ84LReIiKi0GIw4oO8Lo2ewQgREVFIMBjxwbViLw8VERFRKPAM64OySB4zI0RERCHBYMQHrktDREQUWkEFI88//zxycnJgMpkwZcoUbNy4sdPtq6urcfPNNyM9PR1GoxHDhg3DF198EdQOdzdXZoRxGxERUSjoAv2FDz74AIsWLcJLL72EKVOm4Omnn8aCBQuwf/9+pKSktNveYrHgzDPPREpKCv7zn/8gMzMTx44dQ1xcnBr7H3LMjBAREYVWwMHIsmXLcP311+Oaa64BALz00kv4/PPP8frrr+O+++5rt/3rr7+OqqoqrF+/Hnq9HgCQk5PTtb3uRnJmhFN7iYiIQiOgsQeLxYLNmzdj/vz5rgfQaDB//nxs2LDB6+98+umnmDp1Km6++WakpqYiPz8fTz75JGw2W9f2vJvIs2m4Yi8REVFoBJQZqaiogM1mQ2pqqsftqamp2Ldvn9ffOXLkCL755htcfvnl+OKLL3Do0CHcdNNNaG1txUMPPeT1d1paWtDS0qL8XFtbG8huqso1tZeZESIiolAI+eW+3W5HSkoKXnnlFUycOBGXXHIJ7r//frz00ksd/s6SJUsQGxur/MvOzg71bnZIbnrGqb1EREShEVAwkpSUBK1Wi9LSUo/bS0tLkZaW5vV30tPTMWzYMGi1WuW2vLw8lJSUwGKxeP2dxYsXo6amRvlXVFQUyG6qik3PiIiIQiugM6zBYMDEiROxatUq5Ta73Y5Vq1Zh6tSpXn9n+vTpOHToEOxuq98eOHAA6enpMBgMXn/HaDQiJibG41+4sICViIgotAK+3F+0aBFeffVVvPXWW9i7dy9uvPFGNDQ0KLNrrrzySixevFjZ/sYbb0RVVRVuu+02HDhwAJ9//jmefPJJ3Hzzzeq9ihCSp/bqWTNCREQUEgFP7b3kkktQXl6OBx98ECUlJRg3bhy++uorpai1sLAQGreZJ9nZ2VixYgXuuOMOjBkzBpmZmbjttttw7733qvcqQsiVGeEwDRERUShIQggR7p3wpba2FrGxsaipqen2IZsPfirEvR/uxLwRKXjt6tO69bmJiIh6M3/P37zc90EuYGXNCBERUWgwGPFBHqbRczYNERFRSPAM6wObnhEREYUWgxEf5KZnHKYhIiIKDQYjPnBtGiIiotDiGdYHZWovh2mIiIhCgsGID0rTMw7TEBERhQSDER9cU3t5qIiIiEKBZ1gf5AJWtoMnIiIKDQYjPnBqLxERUWgxGPGBa9MQERGFFs+wPrim9jIzQkREFAoMRnxQmp5xmIaIiCgkGIz4wKZnREREocUzrA9ctZeIiCi0GIz4wKm9REREocVgxAfX1F4eKiIiolDgGdYHrtpLREQUWgxGfFAKWDlMQ0REFBIMRnxg0zMiIqLQ4hnWh1bnMI2BmREiIqKQYDDiQ6sym4aHioiIKBR4hvWhxerMjOh4qIiIiEKBZ1gfmBkhIiIKLZ5hfbDYmBkhIiIKJZ5hfWi1OmbTGJgZISIiCgmeYX1gZoSIiCi0eIb1odXKmhEiIqJQ4hnWhxZmRoiIiEKKZ9hOCCHcZtOw6RkREVEoMBjphNUuIBz1qzBqteHdGSIioj6KwUgn5KwIAOh1zIwQERGFAoORTlisrmCEU3uJiIhCg2fYTsjTeiUJ0GqYGSEiIgoFBiOdkDMjBq0GksRghIiIKBQYjHSi1cbuq0RERKHGs2wnLFyxl4iIKOR4lu0EV+wlIiIKPZ5lO9HQYgUAmA3sMUJERBQqDEY60WBxBCORRl2Y94SIiKjv4lnWTYvVhrv+vQP7imvx9KXjUN9iAwBEGpkZISIiChVmRtws33oC/91+EgfL6nHnv7ajrrkVABDFzAgREVHIMBhxs2J3qfL/+0rqsGZ/OQAGI0RERKHEYMTNnpO1AIABCWYAwNd7HMEJa0aIiIhCh8GIU01jK0pqmwEAt8wd4nEfMyNEREShw2DEqaCyAQCQGmPEz8ekezQ6YzBCREQUOgxGnOSsSFpsBMwGHaYPTlTui4nQh2u3iIiI+jwGI06lcjASYwQAzM1LVe4bkxUbln0iIiLqDxiMOJXUOIKR9NgIAMCZzmAkQq9FfiaDESIiolBhMYRTWV0LACA52pEZSYs14cvbZsKk13JtGiIiohBiMOJU2+RocBZndtWH5KXHhGt3iIiI+g1e8jvVOrutxphYrEpERNSdGIw41TY5FsXjzBkiIqLuxWDEyZUZ4cgVERFRd2Iw4iTXjDAzQkRE1L0YjACw2wXqWpzDNKwZISIi6lYMRgDUtVghhOP/ozlMQ0RE1K0YjMA1RGPUaWDSa8O8N0RERP0LgxG4Fa+yXoSIiKjbMRiB27ReDtEQERF1OwYjYGaEiIgonBiMwG1aL2fSEBERdTsGIwBqm9l9lYiIKFwYjMCVGeG0XiIiou7HYARAo8WRGYk2MhghIiLqbgxGADRabADAHiNERERhwGAEQFOrIxgxGxiMEBERdTcGIwCanJmRCAYjRERE3Y7BCFyZkQgO0xAREXU7BiNw1YwwM0JERNT9ggpGnn/+eeTk5MBkMmHKlCnYuHGjX7/3/vvvQ5IkLFy4MJinDZlm1owQERGFTcDByAcffIBFixbhoYcewpYtWzB27FgsWLAAZWVlnf5eQUEB7rrrLsycOTPonQ0VzqYhIiIKn4CDkWXLluH666/HNddcg5EjR+Kll16C2WzG66+/3uHv2Gw2XH755XjkkUcwaNCgLu1wKMgFrGYD+4wQERF1t4CCEYvFgs2bN2P+/PmuB9BoMH/+fGzYsKHD33v00UeRkpKCa6+9Nvg9DSEWsBIREYVPQKmAiooK2Gw2pKametyempqKffv2ef2ddevW4bXXXsO2bdv8fp6Wlha0tLQoP9fW1gaymwFzZUYYjBAREXW3kM6mqaurwxVXXIFXX30VSUlJfv/ekiVLEBsbq/zLzs4O2T7a7ULJjLBmhIiIqPsFlBlJSkqCVqtFaWmpx+2lpaVIS0trt/3hw4dRUFCA8847T7nNbrc7nlinw/79+zF48OB2v7d48WIsWrRI+bm2tjZkAUmL1a78PzMjRERE3S+gYMRgMGDixIlYtWqVMj3Xbrdj1apVuOWWW9ptP2LECOzcudPjtgceeAB1dXV45plnOgwwjEYjjEZjILsWNHmRPICZESIionAIePrIokWLcNVVV2HSpEmYPHkynn76aTQ0NOCaa64BAFx55ZXIzMzEkiVLYDKZkJ+f7/H7cXFxANDu9nCRh2iMOg20GinMe0NERNT/BByMXHLJJSgvL8eDDz6IkpISjBs3Dl999ZVS1FpYWAiNpvc0duW6NEREROElCSFEuHfCl9raWsTGxqKmpgYxMTGqPvaO49X4xXPfIyPWhPWL56n62ERERP2Zv+fv3pPCCBGl+yozI0RERGHR74ORJq5LQ0REFFYMRizsvkpERBRODEaUAlauS0NERBQO/T4YaVTWpen3h4KIiCgs+v0ZuJkr9hIREYVVvw9GlNk0rBkhIiIKi34fjHA2DRERUXgxGHGuTcPZNEREROHBYKSV7eCJiIjCqd8HI43sM0JERBRW/T4YaWbNCBERUVj1+2Ckkav2EhERhVW/D0aUmhEO0xAREYUFgxFmRoiIiMKKwQhrRoiIiMKq3wcj7MBKREQUXv0+GOHaNEREROHVr4MRIYTbqr3MjBAREYVDvw5GWm0CNrsAwAJWIiKicOnXwYhcvAowM0JERBQu/TsYcdaL6DQSDLp+fSiIiIjCpl9XbbLhGRGFgxACVqsVNpvN98ZEPZhWq4VOp4MkSV16nH4djDRarABYL0JE3cdisaC4uBiNjY3h3hUiVZjNZqSnp8NgMAT9GP06GJEXyWMwQkTdwW634+jRo9BqtcjIyIDBYOjyFSVRuAghYLFYUF5ejqNHj2Lo0KHQaIIreejXwYiySB6HaYioG1gsFtjtdmRnZ8NsNod7d4i6LCIiAnq9HseOHYPFYoHJZArqcfp11SbXpSGicAj26pGoJ1Lj/dyvPxFcl4aIiCj8+ncwwmEaIiLy4uqrr8bChQvDvRvdqqCgAJIkYdu2bd3+3P06GFFqRrguDRERUdj062DE1WekXx8GIqJex2KxhHsXSEX9+izMYRoiIv/MmTMHt956K+655x4kJCQgLS0NDz/8sHJ/YWEhzj//fERFRSEmJgYXX3wxSktLlfsffvhhjBs3Dm+//TZycnIQGxuLSy+9FHV1dX4//y233ILbb78dSUlJWLBgAQBg2bJlGD16NCIjI5GdnY2bbroJ9fX1yu+9+eabiIuLw4oVK5CXl4eoqCicffbZKC4uVrax2WxYtGgR4uLikJiYiHvuuQdCCI/nb2lpwa233oqUlBSYTCbMmDEDP/30k3L/6tWrIUkSVqxYgfHjxyMiIgJz585FWVkZvvzyS+Tl5SEmJgaXXXaZ3z1mfB1zAKiursZ1112H5ORkxMTEYO7cudi+fTsAoKamBlqtFps2bQLgmFqekJCA008/Xfn9d955B9nZ2R6PuW/fPkybNg0mkwn5+flYs2aNX/vbFf07GGnlMA0RhZcQAo0Wa1j+tT3h+vLWW28hMjISP/74I5566ik8+uijWLlyJex2O84//3xUVVVhzZo1WLlyJY4cOYJLLrnE4/cPHz6M5cuX47PPPsNnn32GNWvWYOnSpQE9v8FgwPfff4+XXnoJgGMmx9/+9jfs3r0bb731Fr755hvcc889Hr/X2NiIP//5z3j77bexdu1aFBYW4q677lLu/8tf/oI333wTr7/+OtatW4eqqip8/PHHHo9xzz334MMPP8Rbb72FLVu2YMiQIViwYAGqqqo8tnv44Yfx3HPPYf369SgqKsLFF1+Mp59+Gu+99x4+//xzfP3113j22WcDes3ejrnsV7/6lRLwbN68GRMmTMC8efNQVVWF2NhYjBs3DqtXrwYA7Ny5E5IkYevWrUrAtmbNGsyePdvjOe+++27ceeed2Lp1K6ZOnYrzzjsPlZWVfu9zMPr1WZh9Rogo3JpabRj54IqwPPeeRxfAHMDF2JgxY/DQQw8BAIYOHYrnnnsOq1atAuA40R09elS5yv7HP/6BUaNG4aeffsJpp50GwHFl/uabbyI6OhoAcMUVV2DVqlV44okn/Hr+oUOH4qmnnvK47fbbb1f+PycnB48//jhuuOEGvPDCC8rtra2teOmllzB48GAAwC233IJHH31Uuf/pp5/G4sWLceGFFwIAXnrpJaxY4fqbNDQ04MUXX8Sbb76Jc845BwDw6quvYuXKlXjttddw9913K9s+/vjjmD59OgDg2muvxeLFi3H48GEMGjQIAPDLX/4S3377Le69916/XnNHx/zMM8/EunXrsHHjRpSVlcFoNAIA/vznP2P58uX4z3/+g9/+9reYM2cOVq9ejbvuugurV6/GmWeeiX379mHdunU4++yzsXr16nbB2y233IKLLroIAPDiiy/iq6++wmuvvdZuOzX168xIM6f2EhH5bcyYMR4/p6eno6ysDHv37kV2drZHun/kyJGIi4vD3r17ldtycnKUQMT99/01ceLEdrf973//w7x585CZmYno6GhcccUVqKys9BgKMZvNSiDS9nlrampQXFyMKVOmKPfrdDpMmjRJ+fnw4cNobW1VggwA0Ov1mDx5ssfrAzyPUWpqKsxmsxKIyLcF8po7OuYAsH37dtTX1yMxMRFRUVHKv6NHj+Lw4cMAgNmzZ2PdunWw2WxYs2YN5syZowQoJ0+exKFDhzBnzhyP55g6dWq7Y9H2daqtn2dGHGvTmBiMEFGYROi12PPogrA9dyD0er3Hz5IkwW63d9vvR0ZGevxcUFCAn//857jxxhvxxBNPICEhAevWrcO1114Li8WidLn19ryBDlH5y/25JEkK6TGrr69Henq6MgzjLi4uDgAwa9Ys1NXVYcuWLVi7di2efPJJpKWlYenSpRg7diwyMjIwdOhQv/cnVPp1ZqSp1fEHNXOYhojCRJIkmA26sPxTa12cvLw8FBUVoaioSLltz549qK6uxsiRI1V5Dm82b94Mu92Ov/zlLzj99NMxbNgwnDx5MqDHiI2NRXp6On788UflNqvVis2bNys/Dx48WKlVkbW2tuKnn34K6evzZcKECSgpKYFOp8OQIUM8/iUlJQFwBCVjxozBc889B71ejxEjRmDWrFnYunUrPvvss3b1IgDwww8/KP8vH4u8vLyQvpb+HYxw1V4ioi6bP38+Ro8ejcsvvxxbtmzBxo0bceWVV2L27Nkewx1qGzJkCFpbW/Hss8/iyJEjePvtt5XC1kDcdtttWLp0KZYvX459+/bhpptuQnV1tXJ/ZGQkbrzxRtx999346quvsGfPHlx//fVobGzEtddeq+IrCsz8+fMxdepULFy4EF9//TUKCgqwfv163H///coMGsAxK+fdd99VAo+EhATk5eXhgw8+8BqMPP/88/j444+xb98+3HzzzTh16hR+85vfhPS19OtgRCNJMGg1DEaIiLpAkiR88skniI+Px6xZszB//nwMGjQIH3zwQUifd+zYsVi2bBn++Mc/Ij8/H++++y6WLFkS8OPceeeduOKKK3DVVVdh6tSpiI6OxgUXXOCxzdKlS3HRRRfhiiuuwIQJE3Do0CGsWLEC8fHxar2cgEmShC+++AKzZs3CNddcg2HDhuHSSy/FsWPHkJqaqmw3e/Zs2Gw2j9qQOXPmtLtNtnTpUmUYZ926dfj000+VTEvIXosI1cCZimpraxEbG4uamhrExMSo/vhCCC7jTUQh19zcjKNHjyI3Nzfo1U2JeprO3tf+nr/7dWZExkCEiIgofBiMEBFRWBUWFnpMTW37r7CwMNy7qLr++Jo706+n9hIRUfhlZGR0ulJsRkZG9+1MN+mPr7kzDEaIiCis5Kmp/Ul/fM2d4TANERERhRWDESKibtYLJjES+U2N9zODESKibiK39vZ3CXmi3kB+P7dtXR8I1owQEXUTrVaLuLg4ZaEzs9nM1gLUawkh0NjYiLKyMsTFxUGrDb6BKIMRIqJulJaWBgABrdxK1JPFxcUp7+tgMRghIupGkiQhPT0dKSkpaG1tDffuEHWJXq/vUkZExmCEiCgMtFqtKl/iRH0BC1iJiIgorBiMEBERUVgxGCEiIqKw6hU1I3JDldra2jDvCREREflLPm/7aozWK4KRuro6AEB2dnaY94SIiIgCVVdXh9jY2A7vl0Qv6Etst9tx8uRJREdHq9ogqLa2FtnZ2SgqKkJMTIxqj0vt8Vh3Dx7n7sHj3D14nLtPqI61EAJ1dXXIyMiARtNxZUivyIxoNBpkZWWF7PFjYmL4Ru8mPNbdg8e5e/A4dw8e5+4TimPdWUZExgJWIiIiCisGI0RERBRW/ToYMRqNeOihh2A0GsO9K30ej3X34HHuHjzO3YPHufuE+1j3igJWIiIi6rv6dWaEiIiIwo/BCBEREYUVgxEiIiIKKwYjREREFFb9Ohh5/vnnkZOTA5PJhClTpmDjxo3h3qVeY8mSJTjttNMQHR2NlJQULFy4EPv37/fYprm5GTfffDMSExMRFRWFiy66CKWlpR7bFBYW4txzz4XZbEZKSgruvvtuWK3W7nwpvcrSpUshSRJuv/125TYeZ/WcOHEC//d//4fExERERERg9OjR2LRpk3K/EAIPPvgg0tPTERERgfnz5+PgwYMej1FVVYXLL78cMTExiIuLw7XXXov6+vrufik9ls1mwx/+8Afk5uYiIiICgwcPxmOPPeaxdgmPc3DWrl2L8847DxkZGZAkCcuXL/e4X63jumPHDsycORMmkwnZ2dl46qmnur7zop96//33hcFgEK+//rrYvXu3uP7660VcXJwoLS0N9671CgsWLBBvvPGG2LVrl9i2bZv42c9+JgYMGCDq6+uVbW644QaRnZ0tVq1aJTZt2iROP/10MW3aNOV+q9Uq8vPzxfz588XWrVvFF198IZKSksTixYvD8ZJ6vI0bN4qcnBwxZswYcdtttym38ziro6qqSgwcOFBcffXV4scffxRHjhwRK1asEIcOHVK2Wbp0qYiNjRXLly8X27dvF7/4xS9Ebm6uaGpqUrY5++yzxdixY8UPP/wgvvvuOzFkyBDx61//OhwvqUd64oknRGJiovjss8/E0aNHxb///W8RFRUlnnnmGWUbHufgfPHFF+L+++8XH330kQAgPv74Y4/71TiuNTU1IjU1VVx++eVi165d4p///KeIiIgQL7/8cpf2vd8GI5MnTxY333yz8rPNZhMZGRliyZIlYdyr3qusrEwAEGvWrBFCCFFdXS30er3497//rWyzd+9eAUBs2LBBCOH44Gg0GlFSUqJs8+KLL4qYmBjR0tLSvS+gh6urqxNDhw4VK1euFLNnz1aCER5n9dx7771ixowZHd5vt9tFWlqa+NOf/qTcVl1dLYxGo/jnP/8phBBiz549AoD46aeflG2+/PJLIUmSOHHiROh2vhc599xzxW9+8xuP2y688EJx+eWXCyF4nNXSNhhR67i+8MILIj4+3uO749577xXDhw/v0v72y2Eai8WCzZs3Y/78+cptGo0G8+fPx4YNG8K4Z71XTU0NACAhIQEAsHnzZrS2tnoc4xEjRmDAgAHKMd6wYQNGjx6N1NRUZZsFCxagtrYWu3fv7sa97/luvvlmnHvuuR7HE+BxVtOnn36KSZMm4Ve/+hVSUlIwfvx4vPrqq8r9R48eRUlJicexjo2NxZQpUzyOdVxcHCZNmqRsM3/+fGg0Gvz444/d92J6sGnTpmHVqlU4cOAAAGD79u1Yt24dzjnnHAA8zqGi1nHdsGEDZs2aBYPBoGyzYMEC7N+/H6dOnQp6/3rFQnlqq6iogM1m8/hyBoDU1FTs27cvTHvVe9ntdtx+++2YPn068vPzAQAlJSUwGAyIi4vz2DY1NRUlJSXKNt7+BvJ95PD+++9jy5Yt+Omnn9rdx+OsniNHjuDFF1/EokWL8Pvf/x4//fQTbr31VhgMBlx11VXKsfJ2LN2PdUpKisf9Op0OCQkJPNZO9913H2prazFixAhotVrYbDY88cQTuPzyywGAxzlE1DquJSUlyM3NbfcY8n3x8fFB7V+/DEZIXTfffDN27dqFdevWhXtX+pyioiLcdtttWLlyJUwmU7h3p0+z2+2YNGkSnnzySQDA+PHjsWvXLrz00ku46qqrwrx3fce//vUvvPvuu3jvvfcwatQobNu2DbfffjsyMjJ4nPuxfjlMk5SUBK1W227GQWlpKdLS0sK0V73TLbfcgs8++wzffvstsrKylNvT0tJgsVhQXV3tsb37MU5LS/P6N5DvI8cwTFlZGSZMmACdTgedToc1a9bgb3/7G3Q6HVJTU3mcVZKeno6RI0d63JaXl4fCwkIArmPV2fdGWloaysrKPO63Wq2oqqrisXa6++67cd999+HSSy/F6NGjccUVV+COO+7AkiVLAPA4h4paxzVU3yf9MhgxGAyYOHEiVq1apdxmt9uxatUqTJ06NYx71nsIIXDLLbfg448/xjfffNMubTdx4kTo9XqPY7x//34UFhYqx3jq1KnYuXOnx5t/5cqViImJaXdS6K/mzZuHnTt3Ytu2bcq/SZMm4fLLL1f+n8dZHdOnT283Pf3AgQMYOHAgACA3NxdpaWkex7q2thY//vijx7Gurq7G5s2blW2++eYb2O12TJkypRteRc/X2NgIjcbz1KPVamG32wHwOIeKWsd16tSpWLt2LVpbW5VtVq5cieHDhwc9RAOgf0/tNRqN4s033xR79uwRv/3tb0VcXJzHjAPq2I033ihiY2PF6tWrRXFxsfKvsbFR2eaGG24QAwYMEN98843YtGmTmDp1qpg6dapyvzzl9KyzzhLbtm0TX331lUhOTuaUUx/cZ9MIweOslo0bNwqdTieeeOIJcfDgQfHuu+8Ks9ks3nnnHWWbpUuXiri4OPHJJ5+IHTt2iPPPP9/r1Mjx48eLH3/8Uaxbt04MHTq03085dXfVVVeJzMxMZWrvRx99JJKSksQ999yjbMPjHJy6ujqxdetWsXXrVgFALFu2TGzdulUcO3ZMCKHOca2urhapqaniiiuuELt27RLvv/++MJvNnNrbFc8++6wYMGCAMBgMYvLkyeKHH34I9y71GgC8/nvjjTeUbZqamsRNN90k4uPjhdlsFhdccIEoLi72eJyCggJxzjnniIiICJGUlCTuvPNO0dra2s2vpndpG4zwOKvnv//9r8jPzxdGo1GMGDFCvPLKKx732+128Yc//EGkpqYKo9Eo5s2bJ/bv3++xTWVlpfj1r38toqKiRExMjLjmmmtEXV1dd76MHq22tlbcdtttYsCAAcJkMolBgwaJ+++/32OqKI9zcL799luv38tXXXWVEEK947p9+3YxY8YMYTQaRWZmpli6dGmX910Swq3tHREREVE365c1I0RERNRzMBghIiKisGIwQkRERGHFYISIiIjCisEIERERhRWDESIiIgorBiNEREQUVgxGiIiIKKwYjBBR2MyZMwe33357uHeDiMKMwQgRERGFFdvBE1FYXH311Xjrrbc8bjt69ChycnLCs0NEFDYMRogoLGpqanDOOecgPz8fjz76KAAgOTkZWq02zHtGRN1NF+4dIKL+KTY2FgaDAWazGWlpaeHeHSIKI9aMEBERUVgxGCEiIqKwYjBCRGFjMBhgs9nCvRtEFGYMRogobHJycvDjjz+ioKAAFRUVsNvt4d4lIgoDBiNEFDZ33XUXtFotRo4cieTkZBQWFoZ7l4goDDi1l4iIiMKKmREiIiIKKwYjREREFFYMRoiIiCisGIwQERFRWDEYISIiorBiMEJERERhxWCEiIiIworBCBEREYUVgxEiIiIKKwYjREREFFYMRoiIiCisGIwQERFRWP1/j7EbGo2Nwr0AAAAASUVORK5CYII=", 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4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA60QscKqrq5WTkyO32y2v16uZM2fqxIkT5zxm//79mjx5snw+n9xut372s5+pqqoqbMwnn3yim266ST169JDb7daoUaO0YcOGSF0GAADogCIWODk5Odq5c6fWrVunNWvWaOPGjZo9e/ZZx588eVLXXXedHA6HioqKtHnzZjU0NGjixIkKBoOhcTfccIOamppUVFSkbdu2afDgwbrhhhtUWVkZqUsBAAAdjMMYY1r7pLt379bAgQO1detWDR8+XJJUWFioCRMm6LPPPlNaWtppx6xdu1bjx4/XV199JbfbLUmqra1VUlKS1q5dq+zsbB07dkw+n08bN27UNddcI0k6fvy43G631q1bp+zs7POaXyAQkMfjUW1tbei5AABA+9aS398ReQWnuLhYXq83FDeSlJ2dLafTqZKSkjMeU19fL4fDIZfLFdoWHx8vp9OpTZs2SZK6d++ufv366cUXX9TJkyfV1NSk5557TsnJyRo2bFgkLgUAAHRAEQmcyspKJScnh22LjY1Vt27dzvpW0lVXXaXOnTvrgQceUF1dnU6ePKn77rtPzc3N+vzzzyVJDodD7777rj766CN17dpV8fHx+tWvfqXCwkIlJSWddT719fUKBAJhDwAAYK8WBc78+fPlcDjO+dizZ88PmojP59PKlSv15ptvqkuXLvJ4PKqpqdEVV1whp/ObaRpjdPfddys5OVnvvfeetmzZokmTJmnixImhCDqTxYsXy+PxhB7p6ek/aI4AAKBjaNE9OF988YW+/PLLc47p06ePXnrpJeXl5emrr74KbW9qalJ8fLxWrlypyZMnn/Mcx44dU2xsrLxer/x+v/Ly8jRv3jytX79e1113Xdh9OpJ0ySWXaObMmZo/f/4Zz1dfX6/6+vrQz4FAQOnp6dyDAwBAB9KSe3BiW3Jin88nn8/3veNGjBihmpoabdu2LXRvTFFRkYLBoLKysr73+B49eoSOOXr0qG688UZJUl1dnSSFXtH5ltPpDPuk1V9yuVxh9/YAAAC7ReQenAEDBmjcuHGaNWuWtmzZos2bN2vOnDmaNm1a6BNUhw8fVv/+/bVly5bQcQUFBXr//fe1f/9+vfTSS5o6darmzp2rfv36SfomnJKSkjR9+nRt375dn3zyiebNm6fy8nJdf/31kbgUAADQAbXoFZyWWLFihebMmaMxY8bI6XRqypQpWrJkSWh/Y2OjysrKQq/KSFJZWZkWLFig6upqZWRkaOHChZo7d25of48ePVRYWKiFCxfqr/7qr9TY2KhLL71Ub7zxhgYPHhypSwEAAB1MRL4Hp73je3AAAOh4ov49OAAAANFE4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsE9HAWbRokUaOHKnExER5vd7zOsYYo/z8fKWmpiohIUHZ2dnau3dv2Jjq6mrl5OTI7XbL6/Vq5syZOnHiRASuAAAAdEQRDZyGhgZNnTpVd95553kf88QTT2jJkiVaunSpSkpK1LlzZ40dO1anTp0KjcnJydHOnTu1bt06rVmzRhs3btTs2bMjcQkAAKADchhjTKSfZNmyZcrNzVVNTc05xxljlJaWpry8PN13332SpNraWqWkpGjZsmWaNm2adu/erYEDB2rr1q0aPny4JKmwsFATJkzQZ599prS0tO+dTyAQkMfjUW1trdxu94++vu/O/+vG5lY7HwAAHVlCpxg5HI5WO19Lfn/HttqztoLy8nJVVlYqOzs7tM3j8SgrK0vFxcWaNm2aiouL5fV6Q3EjSdnZ2XI6nSopKdHkyZNPO299fb3q6+tDPwcCgYjM/+vGZg3Mfyci5wYAoKPZ9ehYJcZFJzXa1U3GlZWVkqSUlJSw7SkpKaF9lZWVSk5ODtsfGxurbt26hcb8pcWLF8vj8YQe6enpEZg9AABoL1qcVfPnz9e//Mu/nHPM7t271b9//x88qda2YMEC3XvvvaGfA4FARCInoVOMdj06ttXPCwBAR5TQKSZqz93iwMnLy9OMGTPOOaZPnz4/aDJ+v1+SVFVVpdTU1ND2qqoqDRkyJDTm6NGjYcc1NTWpuro6dPxfcrlccrlcP2hOLeFwOKL2UhwAAPg/Lf5t7PP55PP5IjEXZWZmyu/3a/369aGgCQQCKikpCX0Sa8SIEaqpqdG2bds0bNgwSVJRUZGCwaCysrIiMi8AANCxRPQenIqKCpWWlqqiokLNzc0qLS1VaWlp2HfW9O/fX6tWrZL0zSsgubm5euyxx7R69Wp9/PHHuvXWW5WWlqZJkyZJkgYMGKBx48Zp1qxZ2rJlizZv3qw5c+Zo2rRp5/UJKgAAYL+Ivp+Sn5+v5cuXh34eOnSoJGnDhg0aPXq0JKmsrEy1tbWhMffff79Onjyp2bNnq6amRqNGjVJhYaHi4+NDY1asWKE5c+ZozJgxcjqdmjJlipYsWRLJSwEAAB1Im3wPTnsTqe/BAQAAkdOS39/t6mPiAAAArYHAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGCdiAbOokWLNHLkSCUmJsrr9Z7XMcYY5efnKzU1VQkJCcrOztbevXtD+w8ePKiZM2cqMzNTCQkJ6tu3rx566CE1NDRE6CoAAEBHE9HAaWho0NSpU3XnnXee9zFPPPGElixZoqVLl6qkpESdO3fW2LFjderUKUnSnj17FAwG9dxzz2nnzp16+umntXTpUv3iF7+I1GUAAIAOxmGMMZF+kmXLlik3N1c1NTXnHGeMUVpamvLy8nTfffdJkmpra5WSkqJly5Zp2rRpZzzuySef1LPPPqsDBw6c13wCgYA8Ho9qa2vldrtbdC0AACA6WvL7u13dg1NeXq7KykplZ2eHtnk8HmVlZam4uPisx9XW1qpbt25n3V9fX69AIBD2AAAA9mpXgVNZWSlJSklJCduekpIS2veX9u3bp2eeeUb/8A//cNbzLl68WB6PJ/RIT09vvUkDAIB2p8WBM3/+fDkcjnM+9uzZE4m5nubw4cMaN26cpk6dqlmzZp113IIFC1RbWxt6HDp0qE3mBwAAoiO2pQfk5eVpxowZ5xzTp0+fHzQZv98vSaqqqlJqampoe1VVlYYMGRI29siRI7r22ms1cuRIPf/88+c8r8vlksvl+kFzAgAAHU+LA8fn88nn80ViLsrMzJTf79f69etDQRMIBFRSUhL2SazDhw/r2muv1bBhw1RQUCCns1290wYAAKIsomVQUVGh0tJSVVRUqLm5WaWlpSotLdWJEydCY/r3769Vq1ZJkhwOh3Jzc/XYY49p9erV+vjjj3XrrbcqLS1NkyZNkvRN3IwePVq9evXSU089pS+++EKVlZVnvUcHAABceFr8Ck5L5Ofna/ny5aGfhw4dKknasGGDRo8eLUkqKytTbW1taMz999+vkydPavbs2aqpqdGoUaNUWFio+Ph4SdK6deu0b98+7du3Tz179gx7vjb4xDsAAOgA2uR7cNobvgcHAICOp8N+Dw4AAEBrIHAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFiHwAEAANYhcAAAgHUIHAAAYB0CBwAAWCeigbNo0SKNHDlSiYmJ8nq953WMMUb5+flKTU1VQkKCsrOztXfv3jOOra+v15AhQ+RwOFRaWtp6EwcAAB1aRAOnoaFBU6dO1Z133nnexzzxxBNasmSJli5dqpKSEnXu3Fljx47VqVOnTht7//33Ky0trTWnDAAALBDRwHnkkUc0d+5cXXbZZec13hijf/u3f9Mvf/lL3XTTTbr88sv14osv6siRI3r99dfDxr799ttau3atnnrqqQjMHAAAdGTt6h6c8vJyVVZWKjs7O7TN4/EoKytLxcXFoW1VVVWaNWuWfvvb3yoxMfF7z1tfX69AIBD2AAAA9mpXgVNZWSlJSklJCduekpIS2meM0YwZM3THHXdo+PDh53XexYsXy+PxhB7p6emtO3EAANCutDhw5s+fL4fDcc7Hnj17IjFXSdIzzzyj48ePa8GCBed9zIIFC1RbWxt6HDp0KGLzAwAA0Rfb0gPy8vI0Y8aMc47p06fPD5qM3++X9M1bUKmpqaHtVVVVGjJkiCSpqKhIxcXFcrlcYccOHz5cOTk5Wr58+Wnndblcp40HAAD2anHg+Hw++Xy+SMxFmZmZ8vv9Wr9+fShoAoGASkpKQp/EWrJkiR577LHQMUeOHNHYsWP1u9/9TllZWRGZFwAA6FhaHDgtUVFRoerqalVUVKi5uTn0XTUXX3yxunTpIknq37+/Fi9erMmTJ8vhcCg3N1ePPfaYLrnkEmVmZurBBx9UWlqaJk2aJEnq1atX2HN8e56+ffuqZ8+ekbwcAADQQUQ0cPLz88PeMho6dKgkacOGDRo9erQkqaysTLW1taEx999/v06ePKnZs2erpqZGo0aNUmFhoeLj4yM5VQAAYBGHMcZEexJtLRAIyOPxqLa2Vm63O9rTAQAA56Elv7/b1cfEAQAAWgOBAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgAAMA6BA4AALAOgQMAAKxD4AAAAOsQOAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrxEZ7AtFgjJEkBQKBKM8EAACcr29/b3/7e/xcLsjAOX78uCQpPT09yjMBAAAtdfz4cXk8nnOOcZjzySDLBINBHTlyRF27dpXD4WjVcwcCAaWnp+vQoUNyu92tem78H9a5bbDObYe1bhusc9uI1DobY3T8+HGlpaXJ6Tz3XTYX5Cs4TqdTPXv2jOhzuN1u/uNpA6xz22Cd2w5r3TZY57YRiXX+vlduvsVNxgAAwDoEDgAAsA6B08pcLpceeughuVyuaE/Faqxz22Cd2w5r3TZY57bRHtb5grzJGAAA2I1XcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwWtF//Md/KCMjQ/Hx8crKytKWLVuiPaUOZfHixbryyivVtWtXJScna9KkSSorKwsbc+rUKd19993q3r27unTpoilTpqiqqipsTEVFha6//nolJiYqOTlZ8+bNU1NTU1teSofy+OOPy+FwKDc3N7SNdW4dhw8f1t///d+re/fuSkhI0GWXXaYPPvggtN8Yo/z8fKWmpiohIUHZ2dnau3dv2Dmqq6uVk5Mjt9str9ermTNn6sSJE219Ke1ac3OzHnzwQWVmZiohIUF9+/bVP/3TP4X9vSLWuuU2btyoiRMnKi0tTQ6HQ6+//nrY/tZa0z//+c+65pprFB8fr/T0dD3xxBOtcwEGreKVV14xcXFx5je/+Y3ZuXOnmTVrlvF6vaaqqiraU+swxo4dawoKCsyOHTtMaWmpmTBhgunVq5c5ceJEaMwdd9xh0tPTzfr1680HH3xgrrrqKjNy5MjQ/qamJjNo0CCTnZ1tPvroI/PWW2+ZHj16mAULFkTjktq9LVu2mIyMDHP55Zebe+65J7Sddf7xqqurTe/evc2MGTNMSUmJOXDggHnnnXfMvn37QmMef/xx4/F4zOuvv262b99ubrzxRpOZmWm+/vrr0Jhx48aZwYMHm/fff9+899575uKLLzY333xzNC6p3Vq0aJHp3r27WbNmjSkvLzcrV640Xbp0Mb/+9a9DY1jrlnvrrbfMwoULzWuvvWYkmVWrVoXtb401ra2tNSkpKSYnJ8fs2LHDvPzyyyYhIcE899xzP3r+BE4r+clPfmLuvvvu0M/Nzc0mLS3NLF68OIqz6tiOHj1qJJk//vGPxhhjampqTKdOnczKlStDY3bv3m0kmeLiYmPMN/9BOp1OU1lZGRrz7LPPGrfbberr69v2Atq548ePm0suucSsW7fO/PSnPw0FDuvcOh544AEzatSos+4PBoPG7/ebJ598MrStpqbGuFwu8/LLLxtjjNm1a5eRZLZu3Roa8/bbbxuHw2EOHz4cucl3MNdff725/fbbw7b99V//tcnJyTHGsNat4S8Dp7XW9D//8z9NUlJS2L8bDzzwgOnXr9+PnjNvUbWChoYGbdu2TdnZ2aFtTqdT2dnZKi4ujuLMOrba2lpJUrdu3SRJ27ZtU2NjY9g69+/fX7169Qqtc3FxsS677DKlpKSExowdO1aBQEA7d+5sw9m3f3fffbeuv/76sPWUWOfWsnr1ag0fPlxTp05VcnKyhg4dqhdeeCG0v7y8XJWVlWHr7PF4lJWVFbbOXq9Xw4cPD43Jzs6W0+lUSUlJ211MOzdy5EitX79en3zyiSRp+/bt2rRpk8aPHy+JtY6E1lrT4uJi/b//9/8UFxcXGjN27FiVlZXpq6+++lFzvCD/2GZrO3bsmJqbm8P+sZeklJQU7dmzJ0qz6tiCwaByc3N19dVXa9CgQZKkyspKxcXFyev1ho1NSUlRZWVlaMyZ/n/4dh++8corr+jDDz/U1q1bT9vHOreOAwcO6Nlnn9W9996rX/ziF9q6dat+/vOfKy4uTtOnTw+t05nW8bvrnJycHLY/NjZW3bp1Y52/Y/78+QoEAurfv79iYmLU3NysRYsWKScnR5JY6whorTWtrKxUZmbmaef4dl9SUtIPniOBg3bp7rvv1o4dO7Rp06ZoT8U6hw4d0j333KN169YpPj4+2tOxVjAY1PDhw/XP//zPkqShQ4dqx44dWrp0qaZPnx7l2dnlf/7nf7RixQr993//ty699FKVlpYqNzdXaWlprPUFjLeoWkGPHj0UExNz2qdMqqqq5Pf7ozSrjmvOnDlas2aNNmzYoJ49e4a2+/1+NTQ0qKamJmz8d9fZ7/ef8f+Hb/fhm7egjh49qiuuuEKxsbGKjY3VH//4Ry1ZskSxsbFKSUlhnVtBamqqBg4cGLZtwIABqqiokPR/63Sufzf8fr+OHj0atr+pqUnV1dWs83fMmzdP8+fP17Rp03TZZZfplltu0dy5c7V48WJJrHUktNaaRvLfEgKnFcTFxWnYsGFav359aFswGNT69es1YsSIKM6sYzHGaM6cOVq1apWKiopOe9ly2LBh6tSpU9g6l5WVqaKiIrTOI0aM0Mcffxz2H9W6devkdrtP+2VzoRozZow+/vhjlZaWhh7Dhw9XTk5O6H+zzj/e1VdffdrXHHzyySfq3bu3JCkzM1N+vz9snQOBgEpKSsLWuaamRtu2bQuNKSoqUjAYVFZWVhtcRcdQV1cnpzP811lMTIyCwaAk1joSWmtNR4wYoY0bN6qxsTE0Zt26derXr9+PentKEh8Tby2vvPKKcblcZtmyZWbXrl1m9uzZxuv1hn3KBOd25513Go/HY/7whz+Yzz//PPSoq6sLjbnjjjtMr169TFFRkfnggw/MiBEjzIgRI0L7v/348nXXXWdKS0tNYWGh8fl8fHz5e3z3U1TGsM6tYcuWLSY2NtYsWrTI7N2716xYscIkJiaal156KTTm8ccfN16v17zxxhvmz3/+s7npppvO+DHboUOHmpKSErNp0yZzySWXXNAfXT6T6dOnm4suuij0MfHXXnvN9OjRw9x///2hMax1yx0/ftx89NFH5qOPPjKSzK9+9Svz0UcfmU8//dQY0zprWlNTY1JSUswtt9xiduzYYV555RWTmJjIx8Tbm2eeecb06tXLxMXFmZ/85Cfm/fffj/aUOhRJZ3wUFBSExnz99dfmrrvuMklJSSYxMdFMnjzZfP7552HnOXjwoBk/frxJSEgwPXr0MHl5eaaxsbGNr6Zj+cvAYZ1bx5tvvmkGDRpkXC6X6d+/v3n++efD9geDQfPggw+alJQU43K5zJgxY0xZWVnYmC+//NLcfPPNpkuXLsbtdpvbbrvNHD9+vC0vo90LBALmnnvuMb169TLx8fGmT58+ZuHChWEfPWatW27Dhg1n/Dd5+vTpxpjWW9Pt27ebUaNGGZfLZS666CLz+OOPt8r8HcZ856seAQAALMA9OAAAwDoEDgAAsA6BAwAArEPgAAAA6xA4AADAOgQOAACwDoEDAACsQ+AAAADrEDgArDJ69Gjl5uZGexoAoozAAQAA1uFPNQCwxowZM7R8+fKwbeXl5crIyIjOhABEDYEDwBq1tbUaP368Bg0apEcffVSS5PP5FBMTE+WZAWhrsdGeAAC0Fo/Ho7i4OCUmJsrv90d7OgCiiHtwAACAdQgcAABgHQIHgFXi4uLU3Nwc7WkAiDICB4BVMjIyVFJSooMHD+rYsWMKBoPRnhKAKCBwAFjlvvvuU0xMjAYOHCifz6eKiopoTwlAFPAxcQAAYB1ewQEAANYhcAAAgHUIHAAAYB0CBwAAWIfAAQAA1iFwAACAdQgcAABgHQIHAABYh8ABAADWIXAAAIB1CBwAAGAdAgcAAFjn/wNnaA0TXn52rgAAAABJRU5ErkJggg==", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.close()\n", + "trivial_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True),\n", + "trivial_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns'),\n", + "trivial_ep.plot(x='t', y = ['surv_b_obs'], title='survey biomass'),\n", + "trivial_ep.plot(x='t', y = ['total_pop'], title='total biomass'),\n", + "trivial_ep.plot(x='t', y = ['act'], title='action'),\n", + "trivial_ep.plot(x='t', y = ['rew'], title=f'reward = {sum(trivial_ep.rew):.3f}')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "3b22995e-d65f-4aa8-a6a0-94422fc6d346", + "metadata": {}, + "source": [ + "## Some side by side plots" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "fd00e2e7-8d98-4e68-9161-4dd86376249e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,)" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -984,7 +1257,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 50, "id": "b1d5d2c3-d721-47ba-a535-e3a0a28f0e05", "metadata": {}, "outputs": [ @@ -994,19 +1267,9 @@ "" ] }, - "execution_count": 64, + "execution_count": 50, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ @@ -1019,17 +1282,17 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 51, "id": "09a2ce99-c612-49cd-9fa5-e5b4a09a1e92", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(468, 96, 390, 46)" + "(478, 91, 380, 51)" ] }, - "execution_count": 65, + "execution_count": 51, "metadata": {}, "output_type": "execute_result" } @@ -1059,10 +1322,191 @@ "If we add to that a danger of a low population going extinct (e.g. an additive noise term) we might get an agent who will try and keep a high enough `ssb` value at all times, especially during periods that lack large schools." ] }, + { + "cell_type": "markdown", + "id": "1f1994d7-fdde-438f-a47f-3c4f56d7cc11", + "metadata": {}, + "source": [ + "# What is this reward tail cutoff thing?\n", + "\n", + "To recap, these are some of the reward distribution functions we got out of different policies." + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "bc6321a9-02de-4805-a649-fe20a4285912", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:779: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,)" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ggplot(\n", + " rew_df[\n", + " (rew_df[\"variable\"] == \"2_PPO\")\n", + " | (rew_df[\"variable\"] == \"CautionaryRule_gbrt\") \n", + " | (rew_df[\"variable\"] == \"PPO\")\n", + " ], \n", + " aes(x='variable', y='value', color='variable')\n", + ") + geom_point(alpha=0.7) + geom_jitter()," + ] + }, + { + "cell_type": "markdown", + "id": "86817d63-8d34-4299-9b93-4f559379ffbb", + "metadata": {}, + "source": [ + "Why do they cut off so abruptly near the upper end? In this section I try to explore that." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a378860e-d0e6-4987-8510-03934f15d7ed", + "metadata": {}, + "outputs": [], + "source": [ + "ppoBoundary_ish = 317.5\n", + "crBoundary_ish = 316" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "0cbdf248-c670-45bc-bfd9-b8c8c7ff5c04", + "metadata": {}, + "outputs": [], + "source": [ + "import ray\n", + "from rl4fisheries.envs.asm_fns import get_r_devs\n", + "\n", + "@ray.remote(num_cpus=0, num_gpus=0.05)\n", + "def generate_rew_cuda(policy, env_cls, config):\n", + " ep_rew = 0\n", + " env = env_cls(config=config)\n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, info = policy.predict(obs)\n", + " obs, rew, term, trunc, info = env.step(act)\n", + " ep_rew += rew\n", + " return rew\n", + "\n", + "def best_from_batch(policy, env_cls, batch_size=20):\n", + " tmax = env_cls().Tmax\n", + " configs = [{'s': 0.97, 'r_devs': get_r_devs(tmax)} for _ in range(batch_size)]\n", + " parallel = [generate_rew_cuda.remote(policy, env_cls, config) for config in configs]\n", + " # return parallel\n", + " rews = ray.get(parallel)\n", + "\n", + " idx = np.argmax(rews)\n", + " print(max(rews), end=\" \")\n", + " return configs[idx], rews[idx]\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "35a17749-7149-4112-9c4e-79dbc3a76bbe", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "cfg, rew = best_from_batch(ppoAgent, AsmEnv)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 145, + "id": "e9161931-89d2-4860-bad8-5c30b9ac0113", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "([0.459517,\n", + " 0.462409,\n", + " 0.452862,\n", + " 0.460016,\n", + " 0.455386,\n", + " 0.456048,\n", + " 0.460467,\n", + " 0.458816,\n", + " 0.457718,\n", + " 0.461759],\n", + " [1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000])" + ] + }, + "execution_count": 145, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluate_policy(cr_gbrt_pol, env=Monitor(AsmEnv({'s':0.97})), return_episode_rewards=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "id": "5c307631-f9e6-4bdd-b528-149b490d9e24", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[(True, ),\n", + " (True, )]" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "@ray.remote(num_gpus=1)\n", + "def f(arg):\n", + " arg.predict([0,0])\n", + " return torch.cuda.is_available(), arg\n", + "\n", + "ray.get([f.remote(ppoAgent) for _ in range(2)])" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "34a24d75-35d2-4d1e-82cb-a647a3a0d15b", + "id": "b0a7b44b-aa45-4030-be1b-b76e735f2686", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index 660dc4c..71df943 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -32,17 +32,18 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 29, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", + "import ray\n", "\n", "from skopt import gp_minimize, gbrt_minimize \n", - "from skopt.plots import plot_objective\n", "from skopt import dump\n", + "from skopt.plots import plot_objective, plot_convergence\n", "from skopt.space import Real\n", "from skopt.utils import use_named_args\n", "\n", @@ -55,7 +56,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "id": "236788a7-ed25-46bd-a9b0-f7301e96cacf", "metadata": {}, "outputs": [], @@ -73,14 +74,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "b59deb35-b67d-4232-bce4-ae9c8c2f0fcc", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a3fdbca8d79646f0835eaa15bb8790aa", + "model_id": "1f4f8db48f7d45479af91d26c45e3d8c", "version_major": 2, "version_minor": 0 }, @@ -101,18 +102,66 @@ }, { "cell_type": "markdown", - "id": "0f5bdc89-cfb7-4c22-9304-65c1d65f2beb", + "id": "5a7848b7-4b40-4950-a4a5-63e55fadd240", "metadata": {}, "source": [ "# Policy Optimization\n", "---\n", "\n", + "## Policy evaluation fn" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "38838cb2-44df-404b-9cd8-4ecfc9347dd9", + "metadata": {}, + "outputs": [], + "source": [ + "@ray.remote\n", + "def generate_rew(policy, env_cls, config):\n", + " ep_rew = 0\n", + " env = env_cls(config=config)\n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, info = policy.predict(obs)\n", + " obs, rew, term, trunc, info = env.step(act)\n", + " ep_rew += rew\n", + " return ep_rew\n", + "\n", + "\n", + "def rew_batch(policy, env_cls, config, batch_size):\n", + " tmax = env_cls().Tmax\n", + " parallel = [generate_rew.remote(policy, env_cls, config) for _ in range(batch_size)]\n", + " rews = ray.get(parallel)\n", + " \n", + " return rews\n", + "\n", + "def eval_pol(policy, env_cls, config, n_batches=4, batch_size=40, pb=False):\n", + " batch_iter = range(n_batches)\n", + " if pb:\n", + " from tqdm import tqdm\n", + " batch_iter = tqdm(iter)\n", + " #\n", + " rews = []\n", + " for i in batch_iter:\n", + " rews.append(\n", + " rew_batch(policy=policy, env_cls=env_cls, config=config, batch_size=batch_size)\n", + " )\n", + " return np.array(rews).flatten()" + ] + }, + { + "cell_type": "markdown", + "id": "0f5bdc89-cfb7-4c22-9304-65c1d65f2beb", + "metadata": {}, + "source": [ "## Objective fns" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 25, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], @@ -129,15 +178,23 @@ "def msy_obj(**x):\n", " eval_env = AsmEnv(config=CONFIG)\n", " agent = Msy(env=eval_env, mortality = x['mortality'])\n", - " mean, sd = evaluate_policy(agent, Monitor(eval_env), n_eval_episodes=100)\n", - " return -mean\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=4, batch_size=40\n", + " )\n", + " return -np.mean(rews)\n", "\n", "@use_named_args(esc_space)\n", "def esc_obj(**x):\n", " eval_env = AsmEnv(config=CONFIG)\n", " agent = ConstEsc(env=eval_env, escapement = x['escapement'])\n", - " mean, sd = evaluate_policy(agent, Monitor(eval_env), n_eval_episodes=100)\n", - " return -mean\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=4, batch_size=40\n", + " )\n", + " return -np.mean(rews)\n", "\n", "@use_named_args(cr_space)\n", "def cr_obj(**x):\n", @@ -147,9 +204,15 @@ " x2 = np.cos(theta) * radius\n", " #\n", " eval_env = AsmEnv(config=CONFIG)\n", + " eval_env.reset()\n", " agent = CautionaryRule(env=eval_env, x1 = x1, x2 = x2, y2 = x[\"y2\"])\n", - " mean, sd = evaluate_policy(agent, Monitor(eval_env), n_eval_episodes=100)\n", - " return -mean \n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, \n", + " config=CONFIG, \n", + " n_batches=4, batch_size=40\n", + " )\n", + " return -np.mean(rews) \n", "\n" ] }, @@ -166,260 +229,16 @@ "id": "a7208d50-0547-4691-8a78-a47b20d73371", "metadata": {}, "source": [ - "### MSY\n", - "\n", - "Minimum at spproximately `mortality = 0.036`, with a (minus) reward value of `-344`." + "### MSY" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 26, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { "scrolled": true }, - "outputs": [ - { - "data": { - "text/plain": [ - "(-344.81508420000006, [0.03679360865276369])" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 50, verbose=True, n_jobs=-1)\n", - "msy_gp.fun, msy_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "6563ba01-9664-4dbc-9594-c4439d22023a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(msy_gbrt)" - ] - }, - { - "cell_type": "markdown", - "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", - "metadata": {}, - "source": [ - "### Esc\n", - "\n", - "Optimal escapement is approximately `escapement = 0.133` with a (minus) reward value of about `-250`." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(-399.8290314899999, [0.17183492119923788])" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gp = gp_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", - "esc_gp.fun, esc_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "ebff2644-b811-4bea-995c-ca3c7586c122", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(esc_gp)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(-445.35083130000004, [0.1596852959040506])" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gbrt = gbrt_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", - "esc_gbrt.fun, esc_gbrt.x" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "d85a57bd-e338-468d-9d63-45d82fe53aef", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(esc_gbrt)" - ] - }, - { - "cell_type": "markdown", - "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", - "metadata": {}, - "source": [ - "### CR" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", - "metadata": { - "scrolled": true - }, "outputs": [ { "name": "stdout", @@ -427,322 +246,279 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 14.8765\n", - "Function value obtained: -351.7318\n", - "Current minimum: -351.7318\n", + "Time taken: 1.0331\n", + "Function value obtained: -5.2814\n", + "Current minimum: -5.2814\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 14.7790\n", - "Function value obtained: -222.6689\n", - "Current minimum: -351.7318\n", + "Time taken: 0.9389\n", + "Function value obtained: -5.5732\n", + "Current minimum: -5.5732\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 14.7518\n", - "Function value obtained: -174.7706\n", - "Current minimum: -351.7318\n", + "Time taken: 0.9743\n", + "Function value obtained: -4.0990\n", + "Current minimum: -5.5732\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 15.0518\n", - "Function value obtained: -340.0497\n", - "Current minimum: -351.7318\n", + "Time taken: 0.9839\n", + "Function value obtained: -23.4898\n", + "Current minimum: -23.4898\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 14.8816\n", - "Function value obtained: -251.9900\n", - "Current minimum: -351.7318\n", + "Time taken: 0.9085\n", + "Function value obtained: -6.0686\n", + "Current minimum: -23.4898\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 14.7287\n", - "Function value obtained: -209.4481\n", - "Current minimum: -351.7318\n", + "Time taken: 0.8752\n", + "Function value obtained: -235.2743\n", + "Current minimum: -235.2743\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 14.7696\n", - "Function value obtained: -226.3372\n", - "Current minimum: -351.7318\n", + "Time taken: 0.9102\n", + "Function value obtained: -72.9662\n", + "Current minimum: -235.2743\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 14.6545\n", - "Function value obtained: -174.3101\n", - "Current minimum: -351.7318\n", + "Time taken: 0.9273\n", + "Function value obtained: -4.1430\n", + "Current minimum: -235.2743\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 14.8862\n", - "Function value obtained: -78.2966\n", - "Current minimum: -351.7318\n", + "Time taken: 0.9578\n", + "Function value obtained: -102.7956\n", + "Current minimum: -235.2743\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 18.9290\n", - "Function value obtained: -256.4544\n", - "Current minimum: -351.7318\n", + "Time taken: 5.1846\n", + "Function value obtained: -3.8220\n", + "Current minimum: -235.2743\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2500\n", - "Function value obtained: -207.3230\n", - "Current minimum: -351.7318\n", + "Time taken: 2.6037\n", + "Function value obtained: -221.5640\n", + "Current minimum: -235.2743\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2148\n", - "Function value obtained: -65.2255\n", - "Current minimum: -351.7318\n", + "Time taken: 2.4502\n", + "Function value obtained: -241.0760\n", + "Current minimum: -241.0760\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5459\n", - "Function value obtained: -167.9823\n", - "Current minimum: -351.7318\n", + "Time taken: 2.5486\n", + "Function value obtained: -242.0662\n", + "Current minimum: -242.0662\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2486\n", - "Function value obtained: -410.9384\n", - "Current minimum: -410.9384\n", + "Time taken: 2.4723\n", + "Function value obtained: -241.7904\n", + "Current minimum: -242.0662\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1813\n", - "Function value obtained: -380.7809\n", - "Current minimum: -410.9384\n", + "Time taken: 2.4760\n", + "Function value obtained: -242.3443\n", + "Current minimum: -242.3443\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1551\n", - "Function value obtained: -225.6165\n", - "Current minimum: -410.9384\n", + "Time taken: 2.4076\n", + "Function value obtained: -234.9429\n", + "Current minimum: -242.3443\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1436\n", - "Function value obtained: -289.8493\n", - "Current minimum: -410.9384\n", + "Time taken: 2.4601\n", + "Function value obtained: -242.2561\n", + "Current minimum: -242.3443\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7917\n", - "Function value obtained: -42.3463\n", - "Current minimum: -410.9384\n", + "Time taken: 2.0870\n", + "Function value obtained: -246.7795\n", + "Current minimum: -246.7795\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2254\n", - "Function value obtained: -2.2897\n", - "Current minimum: -410.9384\n", + "Time taken: 1.0813\n", + "Function value obtained: -3.5915\n", + "Current minimum: -246.7795\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3229\n", - "Function value obtained: -0.0000\n", - "Current minimum: -410.9384\n", + "Time taken: 1.0608\n", + "Function value obtained: -245.7409\n", + "Current minimum: -246.7795\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2306\n", - "Function value obtained: -231.6224\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1608\n", + "Function value obtained: -242.4195\n", + "Current minimum: -246.7795\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1051\n", - "Function value obtained: -237.8984\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2913\n", + "Function value obtained: -249.4727\n", + "Current minimum: -249.4727\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9081\n", - "Function value obtained: -171.7056\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1837\n", + "Function value obtained: -255.9701\n", + "Current minimum: -255.9701\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9550\n", - "Function value obtained: -306.1268\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1286\n", + "Function value obtained: -239.7620\n", + "Current minimum: -255.9701\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1523\n", - "Function value obtained: -228.2250\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1826\n", + "Function value obtained: -241.4610\n", + "Current minimum: -255.9701\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9595\n", - "Function value obtained: -204.5615\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1768\n", + "Function value obtained: -3.0542\n", + "Current minimum: -255.9701\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0190\n", - "Function value obtained: -68.6305\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1074\n", + "Function value obtained: -240.5148\n", + "Current minimum: -255.9701\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0223\n", - "Function value obtained: -243.1624\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1506\n", + "Function value obtained: -175.6737\n", + "Current minimum: -255.9701\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9260\n", - "Function value obtained: -1.8602\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2762\n", + "Function value obtained: -242.4093\n", + "Current minimum: -255.9701\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9621\n", - "Function value obtained: -0.0000\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2277\n", + "Function value obtained: -239.8314\n", + "Current minimum: -255.9701\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0314\n", - "Function value obtained: -378.3103\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1895\n", + "Function value obtained: -12.8741\n", + "Current minimum: -255.9701\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9896\n", - "Function value obtained: -278.9007\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1584\n", + "Function value obtained: -246.0282\n", + "Current minimum: -255.9701\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4333\n", - "Function value obtained: -226.2895\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2231\n", + "Function value obtained: -252.3802\n", + "Current minimum: -255.9701\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4029\n", - "Function value obtained: -2.9886\n", - "Current minimum: -410.9384\n", + "Time taken: 1.1898\n", + "Function value obtained: -244.2205\n", + "Current minimum: -255.9701\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1865\n", - "Function value obtained: -274.4211\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2412\n", + "Function value obtained: -245.0308\n", + "Current minimum: -255.9701\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3276\n", - "Function value obtained: -112.1505\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2361\n", + "Function value obtained: -240.3855\n", + "Current minimum: -255.9701\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4141\n", - "Function value obtained: -113.2420\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2539\n", + "Function value obtained: -248.9827\n", + "Current minimum: -255.9701\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0401\n", - "Function value obtained: -2.1604\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2386\n", + "Function value obtained: -243.1192\n", + "Current minimum: -255.9701\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1852\n", - "Function value obtained: -127.1841\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2474\n", + "Function value obtained: -241.5725\n", + "Current minimum: -255.9701\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8967\n", - "Function value obtained: -236.8568\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2848\n", + "Function value obtained: -247.1950\n", + "Current minimum: -255.9701\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1567\n", - "Function value obtained: -0.0000\n", - "Current minimum: -410.9384\n", + "Time taken: 1.3895\n", + "Function value obtained: -247.4009\n", + "Current minimum: -255.9701\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1260\n", - "Function value obtained: -335.5016\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2803\n", + "Function value obtained: -250.5159\n", + "Current minimum: -255.9701\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0298\n", - "Function value obtained: -353.8426\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2237\n", + "Function value obtained: -251.7577\n", + "Current minimum: -255.9701\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1143\n", - "Function value obtained: -351.4422\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2773\n", + "Function value obtained: -242.7973\n", + "Current minimum: -255.9701\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0066\n", - "Function value obtained: -248.2000\n", - "Current minimum: -410.9384\n", + "Time taken: 1.2824\n", + "Function value obtained: -250.8797\n", + "Current minimum: -255.9701\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1112\n", - "Function value obtained: -265.7142\n", - "Current minimum: -410.9384\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [1.0, 1e-05, 1.0] before, using random point [0.3803735619256906, 0.501488617712397, 0.11082626422314903]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.2094\n", + "Function value obtained: -252.1934\n", + "Current minimum: -255.9701\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0832\n", - "Function value obtained: -306.8230\n", - "Current minimum: -410.9384\n", + "Time taken: 1.3456\n", + "Function value obtained: -241.3902\n", + "Current minimum: -255.9701\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1915\n", - "Function value obtained: -192.0073\n", - "Current minimum: -410.9384\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [1.0, 1e-05, 1.0] before, using random point [0.7877568546929663, 0.7095084957907133, 0.24825060528452686]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.3082\n", + "Function value obtained: -239.3630\n", + "Current minimum: -255.9701\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1035\n", - "Function value obtained: -102.9234\n", - "Current minimum: -410.9384\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [1.0, 1e-05, 1.0] before, using random point [0.5156288173888501, 0.18829691640463697, 0.8405282125608928]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.3090\n", + "Function value obtained: -248.1995\n", + "Current minimum: -255.9701\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0984\n", - "Function value obtained: -354.1497\n", - "Current minimum: -410.9384\n", - "CPU times: user 14min 7s, sys: 11min 53s, total: 26min 1s\n", - "Wall time: 12min 45s\n" + "Time taken: 1.3575\n", + "Function value obtained: -243.1287\n", + "Current minimum: -255.9701\n", + "CPU times: user 1min 52s, sys: 11min 32s, total: 13min 24s\n", + "Wall time: 1min 12s\n" ] }, { "data": { "text/plain": [ - "(-410.93840314,\n", - " [0.21946183895274754, 0.44335860308748737, 0.41059228240857215])" + "(-255.9700683041442, [0.02342418282318141])" ] }, - "execution_count": 13, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 50, verbose=True, n_jobs=-1)\n", - "cr_gp.fun, cr_gp.x" + "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "msy_gp.fun, msy_gp.x" ] }, { "cell_type": "code", - "execution_count": 14, - "id": "faa3ef2e-e477-401d-b663-3e10e15d2023", + "execution_count": 31, + "id": "6563ba01-9664-4dbc-9594-c4439d22023a", "metadata": {}, "outputs": [ { @@ -751,15 +527,15 @@ "" ] }, - "execution_count": 14, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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79u2orq7GzJkzLVTK9oldnhVmC1QaLS7fqULGrQqk36rAb7nlKK9WGz7n8xhEB7ljWKgnhoV5om+AK/gOdCTSEkydOhWlpaVYs2YNZDIZ+vfvj+PHjzdysrUnNBoNUlJScOPGDbz44ouQSCS4c+cOpFIpXFxczLJJxd0CJVV1yMivRI6sCrX1Wqjq2WZoXb0WFdVqlFWrUaZUo1ShatQPlor5eCLSG6N7+eLxcE9IxAIbvUXnY8GCBR2mGX7r1i2MHTsW+fn5UKlUGD16NCQSCTZv3gyVSoWPP/7YLLtU3E2QXVSFXSk3kHGrAoWVtSY/18VZiOhu7hgYxF4DurlBQGtnSgu8/vrrGDRoELKysuDh4WGInzx5MubMmWO2XeuL290dmDaNDdsZhBB8+Vs+1n9/BWoNWwvzGCDcR4K+XV0hFQsg5PMg5LNDQh7OQnRxFsLDRQgviQgBbo523f+lWIbTp0/j7NmzEAqFRvHBwcEoLCw02671xd29O/Dll1bPtiXktfVYcfAifvyTPSz+iUhvzB7eHX27usFFRBs4FMuh0+mg1WobxRcUFLRpJZz124x1dcD162zYTrheosT4D07jxz9lEDgwWD2+Jz6fMQhDe3hSYVMszpgxY7B9+3bDPcMwUCqVSEhIwLhx48y2a/ZmDWZvmJeRAQwcCKSnA9HR5mTNKRqtDpN3ncWlQjkCuzjiwxei0S/QzdbFotyHvW/OWFBQgLi4OBBCcO3aNQwaNAjXrl2Dp6cnTp06BW9vb7PsdvpqKTE1D5cK5ZCK+Tg4byi8pWJbF4nSyejatSuysrLw9ddfIysrC0qlErNmzcK0adPg6Ohott1OLe78shpsTboKAFg9vhcVNsVm8Pl8TJs2DdOmTePMZqcdpyGEYNX/LqGuXoehPTwwZRDdm4tiGzZu3NjkWvMvvvgCmzdvNttupxX3wYxCnLl+FyI+D/+aHEWHsCg2Y/fu3YiMjGwU37t3b7MnsAC2aJZHR7OrEmzIXaUK67+/AgBYNDocwZ7ONi0PpXMjk8ng18Q6Cy8vLxQVFZltt1PW3Lt/vQF5bT16+0sxe1h3WxeH0skJDAxEampqo/jU1FT4+/ubbdf6NffVq0B8PLBnDxARYfXsVRotDmaws34WxYbTxRsUmzNnzhwsXLgQ9fX1eOKJJwAAycnJWLZsGZYsWWK2XeuLu7oaOHeODW3AySslKK9Ww0cqwsgIL5uUgUK5nzfeeANlZWV45ZVXoFazKwnFYjGWL19utBdca+l0Q2H7f88HAEwZGEhrbUq7gGEYbN68GW+++Says7Ph6OiIsLCwNu981KnEfbu8Bmeu3wUAPDeIHoVEaV+4uLjgkUce4cxepxL3N+kFIAQYFuqJbh5Oti4OhQIAqK6uxqZNm5CcnIySkhLodMb7Aty8edMsu9YXd3Aw8J//sKEV0eoIvvnjNgBg6iO01qa0H2bPno1ff/0V06dPh5+fH2dzLqwv7i5dgJdesnq2p/4qRZG8Dm5OAozp3X6326F0Pn788Uf88MMPeOyxxzi1a32PUmkpsHMnG1oRvSPtmQFdIeI7WDVvCuVhuLu7o0uXLpzbtb64b98GFixgQytRoqhDcjZ7CNzzg2mTnNK+WL9+PdasWYOamhpO7XYKh9rRrCJodATR3dwQ7kPPeKa0L7Zu3YobN27Ax8cHwcHBEAiMN9LMyMgwy26nEHfKVbbWHt/X/Kl8FIql0B+ewDV2L+4atQa/3SwHADojjdIuSUhIsIhd6/e5JRJgzBg2tAK/3SyHWqtDV3dHhNDVX5R2SmVlJT777DOsXLkS5eVsZZSRkdHBdj8NCwNOnLBadr/+xXrlR4R70TXblHbJxYsXERsbC1dXV+Tl5WHOnDno0qULDh06hPz8fOzdu9csu9avubVaoKqKDa3A/eKmUNojixcvRnx8PK5duwax+N5WX+PGjcOpU6fMtmt9cWdlAa6ubGhhbpVVI/duNfg8BkNDPS2eH4ViDr///jvmzp3bKD4gIAAymcxsu3a9LOpUQ609MMid7j9OabeIRCJUVVU1iv/rr7/g5WV+i9OuxW1oklMvOaUdM3HiRLz11luor2fPbGcYBvn5+Vi+fDmeffZZs+3arbhVGi3O3igDQPvblPbN1q1boVQq4e3tjdraWowYMQKhoaGQSCTYsGGD2Xbttq2anleBGrUWXhIRevnZ3ykVFPvB1dUVSUlJOHPmDC5evAilUono6GjExsa2yW6bxV2r1qJV0omKAkpKADe3tmb9UPRN8sfD6BAYpWMwbNgwDBs2jDN7bRZ3qbIOPq1xRAsEQBucBKZC+9uU9swHH3xgctrXXnvNrDzaLm6FqnUP3LgBLFoEbNsG9OjR1uybRCavQ45MAYYBhtMhMEo7ZNu2bUb3paWlqKmpgVtDi7ayshJOTk7w9vY2W9xtdqjdVahb94BcDhw9yoYW4tQ1ttbu19UN7s7CFlJTKNYnNzfXcG3YsAH9+/dHdnY2ysvLUV5ejuzsbERHR2P9+vVm59FmcZcq288523r+yGPn5sb08LBxSSiUlnnzzTexY8cORNy3j39ERAS2bduG1atXm2237eJubc1tBTLyKwEAA7u527YgFIoJFBUVQaPRNIrXarUoLi422y4H4m5ln9vCVNaocb1ECQCIDqLiprR/nnzyScydO9doU4b09HS8/PLLbRoO46BZ3kpxBwQAW7eyoQXIvF0JAAjxdEYX2t+mdAC++OIL+Pr6YtCgQRCJRBCJRBg8eDB8fHzw2WefmW23zd7ystaK28cHWLy4rdk2S8atCgDAANokp3QQvLy8cOzYMfz111/IyckBAERGRiI8PLxNdq0/FFZRAZw8CcTGAu7cCzC9QdwDaZOc0sEIDw9vs6Dvp83irqiph1qjg5BvYgs/Nxd47jkgPZ1zcWu0OmQ1NMujg9w4tU2hWAqtVos9e/Y0e+LIzz//bJZdTuaW31Wq4O/myIWpNnG1WIFqtRYSER9h3nSXU0rH4PXXX8eePXswfvx49OnTp32dOFKiaB/i1g+B9e/mBgcenU9O6Rjs378fBw4cwLhx4zi1y8mSz5Kq9jGRRe9Mi6bONEoHQigUIjQ0lHO73Ii7NU41R0dgwAA25JiM/AZxU2capQOxZMkSvP/++yCEcGrX+uLu2RPIyGBDDrmrVOFWWQ0YBugf6MapbYr9smHDBgwdOhROTk6GRRsPkp+fj/HjxxsWcrzxxhuNZpSlpKQgOjoaIpEIoaGh2LNnj8llOHPmDPbt24cePXpgwoQJeOaZZ4wuc+Gkz12qsH2zXN8kD/N2gaujoIXUFAqLWq3GlClTEBMTg88//7zR51qtFuPHj4evry/Onj2LoqIi/P3vf4dAIMC//vUvAOwikPHjx2PevHnYt28fkpOTMXv2bPj5+SEuLq7FMri5uWHy5MmcvxuImcjlcgKABC48QGbtOW/6gxkZhAiFbMgh/zp2hQQt/56sOJjFqV2K7dF/1+RyucXySExMJK6uro3ijx07Rng8HpHJZIa4jz76iEilUqJSqQghhCxbtoz07t3b6LmpU6eSuLg4i5XXFExulqtUKlRVVRldelrVLCcEUKvZkEMyb1UCoDPT7JkHv38qleXXNaSlpSEqKgo+PvfOdI+Li0NVVRUuX75sSPPgHPC4uDikpaWZnI9Go8HJkyexe/duKBQKAMCdO3egVCrNLrvJ4t64cSNcXV0NV2DgvaNwS6psu3hErdEhq6ASAJ2ZZs8EBgYafQc3btxo8TxlMpmRsAEY7vV7ijeXpqqqCrW1tS3mcevWLURFRWHSpEmYP38+ShvOrt+8eTOWLl1qdtlNFvfKlSshl8sN1+37zte+q1RBp+O2Jm4N2UVVUGl0cHMS0PPA7Jjbt28bfQdXrlzZZLoVK1aAYZiHXvo53O2B119/HYMGDUJFRQUc7xtFmjx5MpKTk822a7JDTb9a5UEYBtDoCMpr1PB0afy5NchsGAIbEOhGN0O0Y6RSKaTSlrfjXLJkCeLj4x+aJiQkxKQ8fX19cf78eaM4/RprX19fQ/jguuvi4mJIpVIjsTbH6dOncfbsWQiFxqsYg4ODbXsQYBcnASo0bNPcJHH37An8+Sdg4j/XFC4Vsv3/vl3dOLNJ6bh4eXm16aSO+4mJicGGDRtQUlICb29vAEBSUhKkUil69eplSHPs2DGj55KSkhATE2NSHjqdDtomzs4rKCiApA2n4bZ5nNtTwh5cVmLqcJijI9C7N6eTWC7fYfdj6xPgyplNSucgPz8fFy5cQH5+PrRaLS5cuIALFy4YHFljxoxBr169MH36dGRlZeHEiRNYvXo15s+fb2jJzps3Dzdv3sSyZcuQk5ODXbt24cCBA1i0aJFJZRgzZgy2b99uuGcYBkqlEgkJCW2bkmqum10/PPH8h8kkaPn35Ovf8017MC+PkFmz2JADatUaErLyBxK0/Htyp7KGE5uU9oUlh8JmzJhBADS6fvnlF0OavLw88tRTTxFHR0fi6elJlixZQurr643s/PLLL6R///5EKBSSkJAQkpiYaHIZbt++TXr16kV69uxJ+Hw+efTRR4mHhweJiIggxcXFZr8bQ4h5Y1JVVVVwdXXFq3vO4Eh2Jd6Ii8D8USbMj83IAAYOZJd8Rkebk7URF25X4umdqfB0EeL3f8bSPrcdov+uyeVyk/rcHRGNRoP9+/cbnTgybdo0k/rszdHmPre+n22rxSN/FrJN8t7+rlTYlA4Ln8/HSy+9xK3NthrwkrAevlZNZOEQvbj7BNjnLzqlc3D16lXs2LED2dnZAICePXtiwYIFiIyMNNtmmx1qXgaHmo3ErXem+VNnGqVjcvDgQfTp0wfp6eno168f+vXrh4yMDERFReHgwYNm2+WgWa6vuU1slvv4ACtWsGEbUWt0uCpjp+pRTzmlo7Js2TKsXLkSb731llF8QkICli1bZvYZ3dzV3FUq09ajBgQAGzdysrXxX8UK1GsJXB0F6Opu+51gKBRz0K80e5CXXnoJRUVFZtvlQNysQ02l0aGqrvGpCY1QKICUFDZsI/fGt6XUmUbpsIwcORKnT59uFH/mzBkMHz7cbLttbpaLBQ6QiPlQ1GlQqqhreS31tWvAqFGcDIX92TAzjfa3KR2ZiRMnYvny5UhPT8ejjz4KADh37hy++eYbrFu3DkeOHDFKayqcbNbgLRFBUadBSZUKoVbcdfSSfhiM9rcpHZhXXnkFALBr1y7s2rWryc8AduZaU9NUm4OTbZa8beAx12h1yC7S19x0GIzScdHpdCZdrRE2wJW4pWy/25qHAt4orYZKo4Oz0AHBHnSZJ8U+qKvjbjIYRzV3wyw1U4bDBALWUy5o2z5n989M49E9yikdGK1Wi/Xr1yMgIAAuLi64efMmAPbc7qb2dTMV6zfLo6KAggI2bAN/0pVgFDthw4YN2LNnD7Zs2WK0prtPnz5tOuWT02a5NbdbotNOKfbC3r178cknn2DatGlwcHAwxPfr169NO8ZwIm6v1jTLL10CunZlQzPR6Qgu32lwptGam9LBKSwsbPLEEZ1Oh/r6erPtciJuXynbLC82peaurwcKC9nQTHLLqlGj1kIs4NE90ygdnl69ejU5ieXbb7/FgAEDzLbLyTi3rysrbqVKA0VdPSRiyx4KoG+S9/STgu/Aye8ThWIz1qxZgxkzZqCwsBA6nQ6HDh3C1atXsXfvXnz//fdm2+VEGU5CvmFmmkxu+XXdVxrGt3vT8W2KHTBp0iQcPXoUJ0+ehLOzM9asWYPs7GwcPXoUo0ePNtsuJzU3APi5iiGvrUeRvA5hPpadpXbljl7ctL9NsQ+GDx+OpKQkTm1y1qbVN82L5C1swh4WBvzyCxuaASHEIO5efrTmplCag9OaGwCKWmqWSyTAyJFm51OiUKGsWg0eA0T4Wm8eO4XCJe7u7iavZCwvLzcrDw7Fza6nbrHPXVgIfPghsGCBWWu69bV2Dy8XiAUOLaSmUNon929lXFZWhrfffhtxcXGGvc7T0tJw4sQJvPnmm2bnwZm4fU2tuYuLgU2bgClTzBN3gzOtF3WmUTowM2bMMPz97LPP4q233sKCBQsMca+99ho+/PBDnDx50uT9zx+Esz63vlluaW857W9T7I0TJ05g7NixjeLHjh2LkydPmm2Xc3G36FBrI/eGwainnGIfeHh44PDhw43iDx8+DA8PD7PtctgsZ/vcVXUaVKs0cBZxZtqAUqVB7t1qAEBPP+pMo9gH69atw+zZs5GSkoIhQ4YAAH777TccP34cn376qdl2Oau5XUR8SBoELXvYAQUeHsCsWWzYSnIaam1fqRgeNjpRlELhmvj4eKSmpkIqleLQoUM4dOgQpFIpzpw50+JppQ+D0+rV11UMRYkSRZV16OHl0nSioCDAzGVs1JlGsVeGDBmCffv2cWqT04nZJk1kqa0FLl9mw1ZCnWkUiulwKm5/U8a6s7OBPn3YsJXQmptCMR3L1NwWOBRQo9Uhp+F0EVpzUygtw6m4LTnWffNuNdQaHVxEfHTr4sS5fQrF3rBQn5t7cetPF+npJ6EbIlIoJsCpt/ze/PKHOMsYBhAK2bAVUGcaxZ545plnTE576NAhs/LgfCgMACpq6lFXr216YceAAYCq9RspUmcaxZ5wdbX8DEtOxS0V8+EkdECNWosieR26c7S/mfEabjrtlNLxSUxMtHgenPa5GYZpeaw7O5s9ALAVQ2GyqjpU1NTDgccgzKeZyTEUCsUIzieA+7mKcbO0unmPeW0tkJnZqkkslxtO8wzzpmu4KfbJt99+iwMHDiA/Px9qtdros4yMDLNscr51qN6pxqXH/GLDbqe0v02xRz744APMnDkTPj4+yMzMxODBg+Hh4YGbN2/iqaeeMtuuBcTN/Vj3xYJKAEC/rm6c2aRQ2gu7du3CJ598gh07dkAoFGLZsmVISkrCa6+9BrlcbrZdzsXN9Vg3IQQXC9gX7NuVOtMo9kd+fj6GDh0KAHB0dIRCwc7EnD59Or766iuz7Vqu5q5qpk/dvTtw4AAbmkBBRS3Kq9UQODDoSce4KXaIr6+vYRPEbt264dy5cwCA3NxcEELMtst9zS1tYfGIuzu7f5q7u0n29LV2pK+UOtModskTTzyBI0eOAABmzpyJRYsWYfTo0Zg6dSomT55stl2LeMsB4K5SDZVGCxH/AUEWFwP79gHTpgE+Pi3a0/e3aZOcYq988skn0Ol0AID58+fDw8MDZ8+excSJEzF37lyz7XIubjcnAUR8HlQaHYrlKnTzeGCRR2EhsGQJu3e5CeLOos40ip3D4/HA491rRD///PN4/vnn22yXc3EzDAM/VzHyympQJK9tLO5WoNURXNI70wJpzU2xHy5evIg+ffqAx+Ph4sWLD03bt29fs/LgfhdDsGPdeWU1D99LzQRulipRrdbCUeCA0Oa2baJQOiD9+/eHTCaDt7c3+vfvD4ZhmnSeMQwDrVZrVh4WEjc3w2FZDbV2nwB6VC/FvsjNzYWXl5fhb0tgEcX4Pmwii6srMGECG7YAnbxCsSR5eXmYNWsWunfvDkdHR/To0QMJCQmNpn9evHgRw4cPh1gsRmBgILZs2dLI1jfffIPIyEiIxWJERUXh2LFjD807KCjIcFbYrVu3EBAQgKCgIKMrICAAt27dMvv9LCLuhx5Q0KMHcOQIG7ZAlqG/7cZl8SgUAEBOTg50Oh12796Ny5cvY9u2bfj444+xatUqQ5qqqiqMGTMGQUFBSE9PxzvvvIO1a9fik08+MaQ5e/YsXnjhBcyaNQuZmZl4+umn8fTTT+PPP/80qRyjRo1q8rA/uVyOUaNGmf+CxEzkcjkBQORyeaPPfrosI0HLvycTdpxu/KBaTUhJCRs+BFW9loStOkaCln9P8u4qzS0mxQ542HeNa7Zs2UK6d+9uuN+1axdxd3cnKpXKELd8+XISERFhuH/uuefI+PHjjewMGTKEzJ0716Q8GYYhJSUljeKvXr1KJBJJa1/BgMl9bpVKBdV9myxUVVU1mzawCzuRJfduNQghxkeVXroEDBwIpKezSz+b4apMAbVWBzcnAd0zjQKg8XdOJBJBJOL2cAq5XI4uXboY7tPS0vD4449DKBQa4uLi4rB582ZUVFTA3d0daWlpWLx4sZGduLg4fPfddw/NS78bC8MwiI+PN3oXrVaLixcvGqalmoPJzfKNGzfC1dXVcAUGBjabNsTTBXweA0WdBnfMdKpdaOhvRwW4mnyOMcW+CQwMNPoObty4kVP7169fx44dO4wmjshkMvg8MB9Dfy+TyR6aRv95c+jfgxACiURi9G6+vr74xz/+gS+//NLs9zG55l65cqXRr1NVVVWzAhfyeQj1dkGOTIGcoioEuDm2umAXb1cCoM40yj1u374NqfTe+oLmau0VK1Zg8+bND7WVnZ2NyMhIw31hYSHGjh2LKVOmYM6cOdwUuAUSExMNw187duyAiwu3w70mi7u1TaBIXwkrbpkCT/ZseSbag9CVYJQHkUqlRuJujiVLlrR4xlZISIjh7zt37mDUqFEYOnSokaMMYBd1FBcXG8Xp7319fR+aRv/5wyCEYN++fVi1ahXCwsJaTN8aLDLODQARvlIAdwwHCbSGGrUG10rY5/pTTzmllXh5eRnGkFuisLAQo0aNwsCBA5GYmGg0DRQAYmJi8M9//hP19fUQCAQAgKSkJERERMC9YfFTTEwMkpOTsXDhQsNzSUlJiImJaTF/Ho+HsLAwlJWVcS5ui80MiWw4Yld/MqeBfv0AuZwNm+HPwiroCHuap7dUbKkiUjo5hYWFGDlyJLp164Z3330XpaWlkMlkRn3lF198EUKhELNmzcLly5fx9ddf4/333zfqor7++us4fvw4tm7dipycHKxduxZ//PEHFixYYFI5Nm3ahDfeeMPkoTOTMdfN3tLwRFFlLQla/j0JWfkDqVVrWmX7vZ+ukqDl35OXv/zD3OJR7AhLDYUlJiYSAE1e95OVlUWGDRtGRCIRCQgIIJs2bWpk68CBAyQ8PJwIhULSu3dv8sMPP5hcDjc3NyIUCgmPxyNisZi4u7sbXeZisWa5j1QEV0cB5LX1uF6iRJ+Ahr7ztWvAggXAhx8CzTRDUv4qBQCMDPe2VPEoFMTHx5t0/nXfvn1x+vTph6aZMmUKpkyZYlY5tm/fbtZzLWExcTMMg0hfCX7LLcdVmeKeuBUK4Kef2LAJypQqw7TTERGm9ZsolI7MjBkzLGLXYuIGgJ5+UvyWW44cWfMTXh7k1LVSEMI+60P725RORl1dXaO57aaMEDSFRZdaRfg2ONVa4TFPuco2yUfRWpvSSaiursaCBQvg7e0NZ2dnuLu7G13mYlFxR7ZS3FodwSl9fzuC9rcpnYNly5bh559/xkcffQSRSITPPvsM69atg7+/P/bu3Wu2XYs2y8N9JGAYoFShwl2lCp4uIiAwkHWmNTG7LaugEhU19ZCI+Yju5mbJolEo7YajR49i7969GDlyJGbOnInhw4cjNDQUQUFB2LdvH6ZNm2aWXYvW3M4ivmHRx1V97e3lBcyfz4YPoG+SDw/zpJszUDoN5eXlhhlzUqnUsPxz2LBhOHXqlNl2La6gRk3z8nLgyy/Z8AF+vVoCgDbJKZ2LkJAQw24skZGROHDgAAC2RndzczPbrhXEzXr6DDPV8vKA6dPZ8D7uKlWGzRlGhlNnGqXzMHPmTGRlZQFgF73s3LkTYrEYixYtwhtvvGG2XYv2uQHTnWp6R1ovPymdckrpVCxatMjwd2xsLHJycpCeno7Q0FCzdz4FrCHuhiOA/ipWQKsjaO7MEMMQWCSttSmdA51Oh3feeQdHjhyBWq3Gk08+iYSEBMMeam3F4s3ybl2c4ChwgEqjQ15ZdZNptDqCU9foEBilc7FhwwasWrUKLi4uCAgIwPvvv4/58+dzZt/i4nbgMQj3YReh5xQpAGdn4NFH2bCB87nlqKyph1TMxwC6xJPSSdi7dy927dqFEydO4LvvvsPRo0exb98+w9FCbcUq400Gp5qsCoiIANLS2BDsYvV3f7oKABgX5UeHwCidhvz8fIwbN85wHxsbC4ZhcOfOHU7sW0fcDWu7sx9c2w3gh0tFSL9VAUeBAxbGhlujOBRKu0Cj0UAsNnYeCwQC1NfXc2Lf4g41AOjbsA/azzkl+P3gSTzyt9FAejrqovph0485AIC5I0IMhxlQKJ0BQkijXU/r6uowb948ON/XbT106JBZ9q0i7uhubnhuUFcc+KMAm4/n4NuG+MTUPBRU1MJXKsY/Hg95qA0Kxd5oaqnnSy+9xJl9q4ibYRi8/XQUCipqIZddBwDcKFVg51nWQ75sbASchFYpCoXSbkhMTLSofat5r4R8Hj6aNhCB7uw2x4sPZEGp0qBvV1c83T/AWsWgUDoNVnVNuzoJkDChNwBAo2X3a149vhd4PHroAIXCNVYfd/IbOhB/pvyBu4E98MLgQAzu3qXlhygUSquxfkdXLEafEQNx7nFCjwmiUCyI9WeM5OYCL70E5oFVYRQKhVusL+6KCmDfPjakUCgWg871pFDsFCpuCsVOMduhRhqOHn3wQPQWUSrvha19ltIp0X/H9N85immYLW5Fw4khzZ3R3SIjRpibNaWTolAo4OpKj3Q2FYaY+XOo0+lw584dSCQSOqRFsSiEECgUCvj7+zc6YpfSPGaLm0KhtG/ozyCFYqdQcVModgoVN4Vip1BxUyh2ChU3hWKnUHFTKHYKFTeFYqf8P9LCNFzLUAS/AAAAAElFTkSuQmCC", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -767,13 +543,44 @@ } ], "source": [ - "plot_objective(cr_gp)" + "plot_objective(msy_gp)" ] }, { "cell_type": "code", - "execution_count": 17, - "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", + "execution_count": 32, + "id": "a10c7628-c47a-4622-8f45-440bcca00901", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_convergence(msy_gp)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", "metadata": { "scrolled": true }, @@ -784,779 +591,279 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 15.4285\n", - "Function value obtained: -145.5092\n", - "Current minimum: -145.5092\n", + "Time taken: 0.9771\n", + "Function value obtained: -26.3370\n", + "Current minimum: -26.3370\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 15.4036\n", - "Function value obtained: -376.5553\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9244\n", + "Function value obtained: -91.3720\n", + "Current minimum: -91.3720\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 15.1200\n", - "Function value obtained: -61.3406\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9164\n", + "Function value obtained: -4.1192\n", + "Current minimum: -91.3720\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 15.1149\n", - "Function value obtained: -103.9941\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9492\n", + "Function value obtained: -144.8091\n", + "Current minimum: -144.8091\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 14.9661\n", - "Function value obtained: -82.7326\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9418\n", + "Function value obtained: -5.0079\n", + "Current minimum: -144.8091\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 14.9986\n", - "Function value obtained: -238.8941\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9620\n", + "Function value obtained: -239.1690\n", + "Current minimum: -239.1690\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 14.9116\n", - "Function value obtained: -232.8373\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9639\n", + "Function value obtained: -3.4427\n", + "Current minimum: -239.1690\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 14.8015\n", - "Function value obtained: -243.3373\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9970\n", + "Function value obtained: -5.2620\n", + "Current minimum: -239.1690\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 14.8692\n", - "Function value obtained: -75.9417\n", - "Current minimum: -376.5553\n", + "Time taken: 0.9451\n", + "Function value obtained: -4.6567\n", + "Current minimum: -239.1690\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 18.6768\n", - "Function value obtained: -226.2103\n", - "Current minimum: -376.5553\n", + "Time taken: 1.1872\n", + "Function value obtained: -3.4642\n", + "Current minimum: -239.1690\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3257\n", - "Function value obtained: -254.7679\n", - "Current minimum: -376.5553\n", + "Time taken: 1.1129\n", + "Function value obtained: -189.9888\n", + "Current minimum: -239.1690\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1989\n", - "Function value obtained: -155.9018\n", - "Current minimum: -376.5553\n", + "Time taken: 1.2358\n", + "Function value obtained: -249.3925\n", + "Current minimum: -249.3925\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5391\n", - "Function value obtained: -202.6269\n", - "Current minimum: -376.5553\n", + "Time taken: 1.2038\n", + "Function value obtained: -246.7732\n", + "Current minimum: -249.3925\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6226\n", - "Function value obtained: -338.3643\n", - "Current minimum: -376.5553\n", + "Time taken: 1.1527\n", + "Function value obtained: -244.8790\n", + "Current minimum: -249.3925\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0937\n", - "Function value obtained: -320.7793\n", - "Current minimum: -376.5553\n", + "Time taken: 1.1352\n", + "Function value obtained: -246.6691\n", + "Current minimum: -249.3925\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 16.9577\n", - "Function value obtained: -264.4446\n", - "Current minimum: -376.5553\n", + "Time taken: 1.1069\n", + "Function value obtained: -251.1293\n", + "Current minimum: -251.1293\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2780\n", - "Function value obtained: -270.6296\n", - "Current minimum: -376.5553\n", + "Time taken: 1.0869\n", + "Function value obtained: -239.0236\n", + "Current minimum: -251.1293\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2300\n", - "Function value obtained: -438.8857\n", - "Current minimum: -438.8857\n", + "Time taken: 1.0756\n", + "Function value obtained: -255.6125\n", + "Current minimum: -255.6125\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0529\n", - "Function value obtained: -356.9705\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1644\n", + "Function value obtained: -245.1025\n", + "Current minimum: -255.6125\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9364\n", - "Function value obtained: -325.3113\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1044\n", + "Function value obtained: -243.8743\n", + "Current minimum: -255.6125\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8991\n", - "Function value obtained: -309.6122\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1368\n", + "Function value obtained: -245.2926\n", + "Current minimum: -255.6125\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8804\n", - "Function value obtained: -293.3637\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1712\n", + "Function value obtained: -168.8751\n", + "Current minimum: -255.6125\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0928\n", - "Function value obtained: -255.8187\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1538\n", + "Function value obtained: -246.9532\n", + "Current minimum: -255.6125\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9054\n", - "Function value obtained: -87.3464\n", - "Current minimum: -438.8857\n", + "Time taken: 1.2467\n", + "Function value obtained: -244.0198\n", + "Current minimum: -255.6125\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1169\n", - "Function value obtained: -156.4470\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1267\n", + "Function value obtained: -247.0916\n", + "Current minimum: -255.6125\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0417\n", - "Function value obtained: -202.2864\n", - "Current minimum: -438.8857\n", + "Time taken: 1.2093\n", + "Function value obtained: -239.9214\n", + "Current minimum: -255.6125\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2709\n", - "Function value obtained: -205.7233\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1178\n", + "Function value obtained: -244.0956\n", + "Current minimum: -255.6125\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3404\n", - "Function value obtained: -385.5189\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1884\n", + "Function value obtained: -247.1154\n", + "Current minimum: -255.6125\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1236\n", - "Function value obtained: -323.0134\n", - "Current minimum: -438.8857\n", + "Time taken: 1.2091\n", + "Function value obtained: -248.9217\n", + "Current minimum: -255.6125\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1110\n", - "Function value obtained: -0.0000\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1379\n", + "Function value obtained: -241.1653\n", + "Current minimum: -255.6125\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9513\n", - "Function value obtained: -330.9457\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1090\n", + "Function value obtained: -28.3147\n", + "Current minimum: -255.6125\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6098\n", - "Function value obtained: -321.6410\n", - "Current minimum: -438.8857\n", + "Time taken: 1.0924\n", + "Function value obtained: -79.6383\n", + "Current minimum: -255.6125\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0473\n", - "Function value obtained: -416.8465\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1303\n", + "Function value obtained: -30.9982\n", + "Current minimum: -255.6125\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0474\n", - "Function value obtained: -213.8130\n", - "Current minimum: -438.8857\n", + "Time taken: 1.2369\n", + "Function value obtained: -240.4885\n", + "Current minimum: -255.6125\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0529\n", - "Function value obtained: -215.6033\n", - "Current minimum: -438.8857\n", + "Time taken: 1.2260\n", + "Function value obtained: -247.4966\n", + "Current minimum: -255.6125\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2426\n", - "Function value obtained: -283.9917\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1080\n", + "Function value obtained: -242.3285\n", + "Current minimum: -255.6125\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0787\n", - "Function value obtained: -409.1817\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1507\n", + "Function value obtained: -26.6754\n", + "Current minimum: -255.6125\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2355\n", - "Function value obtained: -271.4230\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1205\n", + "Function value obtained: -248.9659\n", + "Current minimum: -255.6125\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2466\n", - "Function value obtained: -384.4810\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1671\n", + "Function value obtained: -245.3836\n", + "Current minimum: -255.6125\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5393\n", - "Function value obtained: -347.7256\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1508\n", + "Function value obtained: -245.2714\n", + "Current minimum: -255.6125\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3565\n", - "Function value obtained: -364.3562\n", - "Current minimum: -438.8857\n", + "Time taken: 1.2429\n", + "Function value obtained: -250.2411\n", + "Current minimum: -255.6125\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6342\n", - "Function value obtained: -286.7312\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1812\n", + "Function value obtained: -246.8306\n", + "Current minimum: -255.6125\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1193\n", - "Function value obtained: -227.2325\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1512\n", + "Function value obtained: -249.8087\n", + "Current minimum: -255.6125\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5973\n", - "Function value obtained: -170.8995\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1647\n", + "Function value obtained: -251.4381\n", + "Current minimum: -255.6125\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9054\n", - "Function value obtained: -189.1649\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1128\n", + "Function value obtained: -241.3467\n", + "Current minimum: -255.6125\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3176\n", - "Function value obtained: -0.0000\n", - "Current minimum: -438.8857\n", + "Time taken: 1.3361\n", + "Function value obtained: -248.4483\n", + "Current minimum: -255.6125\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2464\n", - "Function value obtained: -216.1407\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1575\n", + "Function value obtained: -255.1910\n", + "Current minimum: -255.6125\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0330\n", - "Function value obtained: -0.0000\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1234\n", + "Function value obtained: -242.8394\n", + "Current minimum: -255.6125\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2751\n", - "Function value obtained: -8.5129\n", - "Current minimum: -438.8857\n", + "Time taken: 1.1373\n", + "Function value obtained: -246.2295\n", + "Current minimum: -255.6125\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2582\n", - "Function value obtained: -185.1771\n", - "Current minimum: -438.8857\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1405\n", - "Function value obtained: -189.8003\n", - "Current minimum: -438.8857\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3087\n", - "Function value obtained: -244.8359\n", - "Current minimum: -438.8857\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7031\n", - "Function value obtained: -173.0455\n", - "Current minimum: -438.8857\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8906\n", - "Function value obtained: -218.5830\n", - "Current minimum: -438.8857\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5129\n", - "Function value obtained: -73.5653\n", - "Current minimum: -438.8857\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9228\n", - "Function value obtained: -180.4744\n", - "Current minimum: -438.8857\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7201\n", - "Function value obtained: -376.6617\n", - "Current minimum: -438.8857\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7538\n", - "Function value obtained: -190.3690\n", - "Current minimum: -438.8857\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5452\n", - "Function value obtained: -274.7172\n", - "Current minimum: -438.8857\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1527\n", - "Function value obtained: -0.0000\n", - "Current minimum: -438.8857\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3026\n", - "Function value obtained: -298.3506\n", - "Current minimum: -438.8857\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2288\n", - "Function value obtained: -177.4097\n", - "Current minimum: -438.8857\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1948\n", - "Function value obtained: -273.6563\n", - "Current minimum: -438.8857\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5529\n", - "Function value obtained: -2.0565\n", - "Current minimum: -438.8857\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5062\n", - "Function value obtained: -166.2979\n", - "Current minimum: -438.8857\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4895\n", - "Function value obtained: -305.1273\n", - "Current minimum: -438.8857\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2092\n", - "Function value obtained: -217.1084\n", - "Current minimum: -438.8857\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7433\n", - "Function value obtained: -270.1481\n", - "Current minimum: -438.8857\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2462\n", - "Function value obtained: -400.0950\n", - "Current minimum: -438.8857\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1135\n", - "Function value obtained: -199.2659\n", - "Current minimum: -438.8857\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8707\n", - "Function value obtained: -310.8458\n", - "Current minimum: -438.8857\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3051\n", - "Function value obtained: -190.2455\n", - "Current minimum: -438.8857\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3690\n", - "Function value obtained: -238.7819\n", - "Current minimum: -438.8857\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2562\n", - "Function value obtained: -167.9023\n", - "Current minimum: -438.8857\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7955\n", - "Function value obtained: -259.0012\n", - "Current minimum: -438.8857\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4389\n", - "Function value obtained: -261.2114\n", - "Current minimum: -438.8857\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7072\n", - "Function value obtained: -252.6956\n", - "Current minimum: -438.8857\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3383\n", - "Function value obtained: -353.6387\n", - "Current minimum: -438.8857\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2957\n", - "Function value obtained: -327.7674\n", - "Current minimum: -438.8857\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3852\n", - "Function value obtained: -283.0269\n", - "Current minimum: -438.8857\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4744\n", - "Function value obtained: -297.2389\n", - "Current minimum: -438.8857\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3693\n", - "Function value obtained: -376.0855\n", - "Current minimum: -438.8857\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5661\n", - "Function value obtained: -193.4612\n", - "Current minimum: -438.8857\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4443\n", - "Function value obtained: -276.4440\n", - "Current minimum: -438.8857\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5257\n", - "Function value obtained: -387.9956\n", - "Current minimum: -438.8857\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4041\n", - "Function value obtained: -375.4694\n", - "Current minimum: -438.8857\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3485\n", - "Function value obtained: -435.6686\n", - "Current minimum: -438.8857\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7586\n", - "Function value obtained: -354.5828\n", - "Current minimum: -438.8857\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7085\n", - "Function value obtained: -219.5666\n", - "Current minimum: -438.8857\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6027\n", - "Function value obtained: -319.3203\n", - "Current minimum: -438.8857\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4429\n", - "Function value obtained: -163.7757\n", - "Current minimum: -438.8857\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0105\n", - "Function value obtained: -422.3829\n", - "Current minimum: -438.8857\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1356\n", - "Function value obtained: -226.5309\n", - "Current minimum: -438.8857\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8464\n", - "Function value obtained: -454.6902\n", - "Current minimum: -454.6902\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5784\n", - "Function value obtained: -170.0078\n", - "Current minimum: -454.6902\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4668\n", - "Function value obtained: -223.6554\n", - "Current minimum: -454.6902\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6039\n", - "Function value obtained: -340.4397\n", - "Current minimum: -454.6902\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6884\n", - "Function value obtained: -278.3628\n", - "Current minimum: -454.6902\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8655\n", - "Function value obtained: -283.0379\n", - "Current minimum: -454.6902\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6039\n", - "Function value obtained: -281.5878\n", - "Current minimum: -454.6902\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8485\n", - "Function value obtained: -170.6390\n", - "Current minimum: -454.6902\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8758\n", - "Function value obtained: -202.1503\n", - "Current minimum: -454.6902\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8478\n", - "Function value obtained: -294.7809\n", - "Current minimum: -454.6902\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7031\n", - "Function value obtained: -244.5716\n", - "Current minimum: -454.6902\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0215\n", - "Function value obtained: -276.1295\n", - "Current minimum: -454.6902\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9697\n", - "Function value obtained: -150.1348\n", - "Current minimum: -454.6902\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1898\n", - "Function value obtained: -213.3973\n", - "Current minimum: -454.6902\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0638\n", - "Function value obtained: -236.5961\n", - "Current minimum: -454.6902\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9647\n", - "Function value obtained: -377.7661\n", - "Current minimum: -454.6902\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2499\n", - "Function value obtained: -185.7516\n", - "Current minimum: -454.6902\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7978\n", - "Function value obtained: -311.9500\n", - "Current minimum: -454.6902\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7998\n", - "Function value obtained: -267.6341\n", - "Current minimum: -454.6902\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8251\n", - "Function value obtained: -288.9180\n", - "Current minimum: -454.6902\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9563\n", - "Function value obtained: -297.4210\n", - "Current minimum: -454.6902\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9263\n", - "Function value obtained: -269.9024\n", - "Current minimum: -454.6902\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7647\n", - "Function value obtained: -332.9702\n", - "Current minimum: -454.6902\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8393\n", - "Function value obtained: -287.5196\n", - "Current minimum: -454.6902\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4803\n", - "Function value obtained: -365.5712\n", - "Current minimum: -454.6902\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8271\n", - "Function value obtained: -289.8397\n", - "Current minimum: -454.6902\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8000\n", - "Function value obtained: -428.0189\n", - "Current minimum: -454.6902\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8749\n", - "Function value obtained: -325.3286\n", - "Current minimum: -454.6902\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0965\n", - "Function value obtained: -262.0612\n", - "Current minimum: -454.6902\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0577\n", - "Function value obtained: -261.3653\n", - "Current minimum: -454.6902\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0354\n", - "Function value obtained: -247.9604\n", - "Current minimum: -454.6902\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1425\n", - "Function value obtained: -294.8476\n", - "Current minimum: -454.6902\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2390\n", - "Function value obtained: -364.9957\n", - "Current minimum: -454.6902\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4888\n", - "Function value obtained: -344.0682\n", - "Current minimum: -454.6902\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3073\n", - "Function value obtained: -390.7574\n", - "Current minimum: -454.6902\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5701\n", - "Function value obtained: -196.1202\n", - "Current minimum: -454.6902\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3848\n", - "Function value obtained: -341.5758\n", - "Current minimum: -454.6902\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4364\n", - "Function value obtained: -393.6795\n", - "Current minimum: -454.6902\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2929\n", - "Function value obtained: -269.6585\n", - "Current minimum: -454.6902\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1430\n", - "Function value obtained: -385.4108\n", - "Current minimum: -454.6902\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5185\n", - "Function value obtained: -408.1678\n", - "Current minimum: -454.6902\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2813\n", - "Function value obtained: -328.6534\n", - "Current minimum: -454.6902\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1611\n", - "Function value obtained: -348.8009\n", - "Current minimum: -454.6902\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0663\n", - "Function value obtained: -390.7550\n", - "Current minimum: -454.6902\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6901\n", - "Function value obtained: -231.0736\n", - "Current minimum: -454.6902\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5807\n", - "Function value obtained: -356.8110\n", - "Current minimum: -454.6902\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4868\n", - "Function value obtained: -195.4664\n", - "Current minimum: -454.6902\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2288\n", - "Function value obtained: -273.3829\n", - "Current minimum: -454.6902\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3722\n", - "Function value obtained: -231.4419\n", - "Current minimum: -454.6902\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6915\n", - "Function value obtained: -343.5587\n", - "Current minimum: -454.6902\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6498\n", - "Function value obtained: -318.5991\n", - "Current minimum: -454.6902\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2139\n", - "Function value obtained: -265.6124\n", - "Current minimum: -454.6902\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2855\n", - "Function value obtained: -284.7378\n", - "Current minimum: -454.6902\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2652\n", - "Function value obtained: -282.3433\n", - "Current minimum: -454.6902\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6722\n", - "Function value obtained: -250.6419\n", - "Current minimum: -454.6902\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6253\n", - "Function value obtained: -254.4936\n", - "Current minimum: -454.6902\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5687\n", - "Function value obtained: -209.1275\n", - "Current minimum: -454.6902\n", - "CPU times: user 48min 46s, sys: 1h 5min 38s, total: 1h 54min 25s\n", - "Wall time: 39min 22s\n" + "Time taken: 1.1679\n", + "Function value obtained: -248.5894\n", + "Current minimum: -255.6125\n", + "CPU times: user 17 s, sys: 4.8 s, total: 21.8 s\n", + "Wall time: 56.1 s\n" ] }, { "data": { "text/plain": [ - "(-454.69024843, [0.37243753649830236, 0.42278680991848616, 0.4207223170684818])" + "(-255.61248660708233, [0.02511500817922824])" ] }, - "execution_count": 17, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gbrt = gp_minimize(cr_obj, cr_space, n_calls = 150, verbose=True, n_jobs=-1)\n", - "cr_gbrt.fun, cr_gbrt.x" + "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "msy_gbrt.fun, msy_gbrt.x" ] }, { "cell_type": "code", - "execution_count": 18, - "id": "dffeed5a-f975-4a6b-b91c-1d91e6c45140", + "execution_count": 34, + "id": "73d6974e-8d14-419d-a43d-ef0cd09659f8", "metadata": {}, "outputs": [ { @@ -1565,15 +872,15 @@ "" ] }, - "execution_count": 18, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" + "
" ] }, "metadata": {}, @@ -1581,528 +888,2217 @@ } ], "source": [ - "plot_objective(cr_gbrt)" + "plot_objective(msy_gbrt)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "c3a775a4-4f27-419d-8cfb-3d4ec7d19fae", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e3a7567f-e007-4931-9982-7c4de99c2e0a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "01d309be-d7c2-4af1-afbc-3b91c42c1a6c", + "execution_count": 35, + "id": "5f305f10-8363-46eb-bb96-484f17f04f21", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "# -> (-62.08484130000001, [0.058590822346937174])" + "plot_convergence(msy_gbrt)" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "dabc6e34-7a25-4b2d-b8b1-294b59f60ca0", + "cell_type": "markdown", + "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", "metadata": {}, - "outputs": [], "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"msy_gp.pkl\"\n", - "dump(msy_gp, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" + "### Esc" ] }, { "cell_type": "code", - "execution_count": null, - "id": "4c5c2ec8-f61b-4dae-bc1b-ba70310a694b", + "execution_count": 36, + "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", "metadata": { "scrolled": true }, - "outputs": [], - "source": [ - "%%time\n", - "msy_gbrt = gbrt_minimize(msy_fun, [(0.02, 0.15)], n_calls = 100, verbose=True, n_jobs=-1)\n", - "msy_gbrt.fun, msy_gbrt.x" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "07918bc7-cdb2-4966-b24a-ac53db2f49ec", - "metadata": {}, - "outputs": [], - "source": [ - "# -> (-57.168266599999995, [0.05811506272614242])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "05db66a7-a0f0-46e5-abd6-f57f8bb1bc59", - "metadata": {}, - "outputs": [], - "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"msy_gbrt.pkl\"\n", - "dump(msy_gbrt, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "95f89094-fd18-433b-a3fc-1e45d3e2e1ad", - "metadata": {}, - "outputs": [], - "source": [ - "plot_objective(msy_gp)" - ] - }, - { - "cell_type": "markdown", - "id": "1206af08-4695-422c-95f0-25a9da2a4299", - "metadata": {}, - "source": [ - "## Const Escapement" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "05fc9be0-b0d0-4822-99ca-f0fcf2304ae4", - "metadata": {}, - "outputs": [], - "source": [ - "def esc_fun(x):\n", - " agent = ConstEsc(escapement=x[0])\n", - " mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100)\n", - " return -mean" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2aa1a6e7-dc64-410d-9850-db17810c0f03", - "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 1.0844\n", + "Function value obtained: -26.2461\n", + "Current minimum: -26.2461\n", + "Iteration No: 2 started. Evaluating function at random point.\n", + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 0.8625\n", + "Function value obtained: -287.0738\n", + "Current minimum: -287.0738\n", + "Iteration No: 3 started. Evaluating function at random point.\n", + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 0.9552\n", + "Function value obtained: -257.8897\n", + "Current minimum: -287.0738\n", + "Iteration No: 4 started. Evaluating function at random point.\n", + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 0.9146\n", + "Function value obtained: -275.3590\n", + "Current minimum: -287.0738\n", + "Iteration No: 5 started. Evaluating function at random point.\n", + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 0.8751\n", + "Function value obtained: -147.8621\n", + "Current minimum: -287.0738\n", + "Iteration No: 6 started. Evaluating function at random point.\n", + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 0.8221\n", + "Function value obtained: -117.3944\n", + "Current minimum: -287.0738\n", + "Iteration No: 7 started. Evaluating function at random point.\n", + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 0.8502\n", + "Function value obtained: -208.3737\n", + "Current minimum: -287.0738\n", + "Iteration No: 8 started. Evaluating function at random point.\n", + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 0.8278\n", + "Function value obtained: -23.8751\n", + "Current minimum: -287.0738\n", + "Iteration No: 9 started. Evaluating function at random point.\n", + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 0.8681\n", + "Function value obtained: -171.0908\n", + "Current minimum: -287.0738\n", + "Iteration No: 10 started. Evaluating function at random point.\n", + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 1.0946\n", + "Function value obtained: -123.2161\n", + "Current minimum: -287.0738\n", + "Iteration No: 11 started. Searching for the next optimal point.\n", + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0900\n", + "Function value obtained: -273.5842\n", + "Current minimum: -287.0738\n", + "Iteration No: 12 started. Searching for the next optimal point.\n", + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1399\n", + "Function value obtained: -290.1932\n", + "Current minimum: -290.1932\n", + "Iteration No: 13 started. Searching for the next optimal point.\n", + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1050\n", + "Function value obtained: -272.2383\n", + "Current minimum: -290.1932\n", + "Iteration No: 14 started. Searching for the next optimal point.\n", + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1772\n", + "Function value obtained: -287.2174\n", + "Current minimum: -290.1932\n", + "Iteration No: 15 started. Searching for the next optimal point.\n", + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0851\n", + "Function value obtained: -275.4792\n", + "Current minimum: -290.1932\n", + "Iteration No: 16 started. Searching for the next optimal point.\n", + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1296\n", + "Function value obtained: -291.3676\n", + "Current minimum: -291.3676\n", + "Iteration No: 17 started. Searching for the next optimal point.\n", + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0728\n", + "Function value obtained: -299.6824\n", + "Current minimum: -299.6824\n", + "Iteration No: 18 started. Searching for the next optimal point.\n", + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0646\n", + "Function value obtained: -277.7666\n", + "Current minimum: -299.6824\n", + "Iteration No: 19 started. Searching for the next optimal point.\n", + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9859\n", + "Function value obtained: -280.4648\n", + "Current minimum: -299.6824\n", + "Iteration No: 20 started. Searching for the next optimal point.\n", + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0740\n", + "Function value obtained: -285.2623\n", + "Current minimum: -299.6824\n", + "Iteration No: 21 started. Searching for the next optimal point.\n", + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1533\n", + "Function value obtained: -283.2448\n", + "Current minimum: -299.6824\n", + "Iteration No: 22 started. Searching for the next optimal point.\n", + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9934\n", + "Function value obtained: -285.1611\n", + "Current minimum: -299.6824\n", + "Iteration No: 23 started. Searching for the next optimal point.\n", + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0790\n", + "Function value obtained: -280.3531\n", + "Current minimum: -299.6824\n", + "Iteration No: 24 started. Searching for the next optimal point.\n", + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1106\n", + "Function value obtained: -285.3636\n", + "Current minimum: -299.6824\n", + "Iteration No: 25 started. Searching for the next optimal point.\n", + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0145\n", + "Function value obtained: -283.7417\n", + "Current minimum: -299.6824\n", + "Iteration No: 26 started. Searching for the next optimal point.\n", + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1208\n", + "Function value obtained: -284.4480\n", + "Current minimum: -299.6824\n", + "Iteration No: 27 started. Searching for the next optimal point.\n", + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0133\n", + "Function value obtained: -287.7597\n", + "Current minimum: -299.6824\n", + "Iteration No: 28 started. Searching for the next optimal point.\n", + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1579\n", + "Function value obtained: -277.8224\n", + "Current minimum: -299.6824\n", + "Iteration No: 29 started. Searching for the next optimal point.\n", + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1744\n", + "Function value obtained: -281.4562\n", + "Current minimum: -299.6824\n", + "Iteration No: 30 started. Searching for the next optimal point.\n", + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1383\n", + "Function value obtained: -284.2537\n", + "Current minimum: -299.6824\n", + "Iteration No: 31 started. Searching for the next optimal point.\n", + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0973\n", + "Function value obtained: -285.4861\n", + "Current minimum: -299.6824\n", + "Iteration No: 32 started. Searching for the next optimal point.\n", + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1838\n", + "Function value obtained: -281.1279\n", + "Current minimum: -299.6824\n", + "Iteration No: 33 started. Searching for the next optimal point.\n", + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0223\n", + "Function value obtained: -275.3974\n", + "Current minimum: -299.6824\n", + "Iteration No: 34 started. Searching for the next optimal point.\n", + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1810\n", + "Function value obtained: -283.2870\n", + "Current minimum: -299.6824\n", + "Iteration No: 35 started. Searching for the next optimal point.\n", + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1356\n", + "Function value obtained: -291.6721\n", + "Current minimum: -299.6824\n", + "Iteration No: 36 started. Searching for the next optimal point.\n", + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1261\n", + "Function value obtained: -285.1709\n", + "Current minimum: -299.6824\n", + "Iteration No: 37 started. Searching for the next optimal point.\n", + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1326\n", + "Function value obtained: -278.2225\n", + "Current minimum: -299.6824\n", + "Iteration No: 38 started. Searching for the next optimal point.\n", + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1895\n", + "Function value obtained: -291.0208\n", + "Current minimum: -299.6824\n", + "Iteration No: 39 started. Searching for the next optimal point.\n", + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3190\n", + "Function value obtained: -281.5575\n", + "Current minimum: -299.6824\n", + "Iteration No: 40 started. Searching for the next optimal point.\n", + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2062\n", + "Function value obtained: -281.0431\n", + "Current minimum: -299.6824\n", + "Iteration No: 41 started. Searching for the next optimal point.\n", + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2715\n", + "Function value obtained: -290.5128\n", + "Current minimum: -299.6824\n", + "Iteration No: 42 started. Searching for the next optimal point.\n", + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2446\n", + "Function value obtained: -283.3796\n", + "Current minimum: -299.6824\n", + "Iteration No: 43 started. Searching for the next optimal point.\n", + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2764\n", + "Function value obtained: -288.0767\n", + "Current minimum: -299.6824\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2241\n", + "Function value obtained: -284.4223\n", + "Current minimum: -299.6824\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2803\n", + "Function value obtained: -278.7137\n", + "Current minimum: -299.6824\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3172\n", + "Function value obtained: -287.6410\n", + "Current minimum: -299.6824\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2718\n", + "Function value obtained: -278.5836\n", + "Current minimum: -299.6824\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2220\n", + "Function value obtained: -280.4583\n", + "Current minimum: -299.6824\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2973\n", + "Function value obtained: -287.5747\n", + "Current minimum: -299.6824\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1781\n", + "Function value obtained: -290.1275\n", + "Current minimum: -299.6824\n", + "CPU times: user 1min 44s, sys: 10min 30s, total: 12min 15s\n", + "Wall time: 55.2 s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-299.6823555974254, [0.16787857585865285])" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "%%time\n", - "esc_gp = gp_minimize(esc_fun, [(0.002, 0.25)], n_calls = 500, verbose=True, n_jobs=-1)\n", + "esc_gp = gp_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", "esc_gp.fun, esc_gp.x" ] }, { "cell_type": "code", - "execution_count": null, - "id": "9824bdb6-bacd-497d-bbfc-4ba711629e6a", - "metadata": {}, - "outputs": [], - "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"esc_gp.pkl\"\n", - "dump(esc_gp, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a75dd9f6-f430-4458-a035-8188c6b255d5", - "metadata": {}, - "outputs": [], - "source": [ - "%%time\n", - "esc_gbrt = gbrt_minimize(esc_fun, [(0.02, 0.15)], n_calls = 100, verbose=True, n_jobs=-1)\n", - "esc_gbrt.fun, esc_gbrt.x" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "33725bba-434d-4c0e-84af-e89b151676f5", + "execution_count": 37, + "id": "ebff2644-b811-4bea-995c-ca3c7586c122", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plot_objective(esc_gp)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "abcac3a5-8136-4104-b8e0-abda7b53783e", - "metadata": {}, - "outputs": [], - "source": [ - "dump(esc_gbrt, \"../saved_agents/esc_gbrt.pkl\")" - ] - }, - { - "cell_type": "markdown", - "id": "1c89ae1d-bbeb-49b0-b6fb-6ab0a479d148", - "metadata": {}, - "source": [ - "## Precationary Rule (piecewise linear)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c5b6f1a3-2d7a-4698-9555-1e10f4032bed", + "execution_count": 38, + "id": "23e3b71f-dcb0-41df-a74d-37043f57cbe1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "from skopt.space import Real\n", - "from skopt.utils import use_named_args\n", - "\n", - "space = [Real(0.00001, 1, name='radius'),\n", - " Real(0.00001, np.pi/4.00001, name='theta'),\n", - " Real(0, 0.2, name='y2')]\n", - "\n", - "@use_named_args(space)\n", - "def g(**params):\n", - "\n", - " theta = params[\"theta\"]\n", - " radius = params[\"radius\"]\n", - " x1 = np.sin(theta) * radius\n", - " x2 = np.cos(theta) * radius\n", - " \n", - " assert x1 <= x2, (\"CautionaryRule error: x1 < x2, \" + str(x1) + \", \", str(x2) )\n", - "\n", - " agent = CautionaryRule(x1 = x1, x2 = x2, y2 = params[\"y2\"])\n", - " mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100)\n", - " return -mean \n" + "plot_convergence(esc_gp)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "cda44a0a-55ad-4953-b31e-bbb43d6a4e12", + "execution_count": 58, + "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", "metadata": { "scrolled": true }, - "outputs": [], - "source": [ - "%%time\n", - "g_gp = gp_minimize(g, space, n_calls = 300, verbose=True, n_jobs=-1)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f7bf06c4-8931-4970-955b-1c2799082bf4", - "metadata": {}, - "outputs": [], - "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"cr_gp.pkl\"\n", - "dump(g_gbrt, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c2b92ed3-d6f7-437e-be4f-796eac28a430", - "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 0.9597\n", + "Function value obtained: -48.4151\n", + "Current minimum: -48.4151\n", + "Iteration No: 2 started. Evaluating function at random point.\n", + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 0.8968\n", + "Function value obtained: -240.4979\n", + "Current minimum: -240.4979\n", + "Iteration No: 3 started. Evaluating function at random point.\n", + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 0.9159\n", + "Function value obtained: -28.7273\n", + "Current minimum: -240.4979\n", + "Iteration No: 4 started. Evaluating function at random point.\n", + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 0.8697\n", + "Function value obtained: -163.8213\n", + "Current minimum: -240.4979\n", + "Iteration No: 5 started. Evaluating function at random point.\n", + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 0.8175\n", + "Function value obtained: -188.8821\n", + "Current minimum: -240.4979\n", + "Iteration No: 6 started. Evaluating function at random point.\n", + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 0.8082\n", + "Function value obtained: -267.1244\n", + "Current minimum: -267.1244\n", + "Iteration No: 7 started. Evaluating function at random point.\n", + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 0.8877\n", + "Function value obtained: -25.4796\n", + "Current minimum: -267.1244\n", + "Iteration No: 8 started. Evaluating function at random point.\n", + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 0.8593\n", + "Function value obtained: -277.7872\n", + "Current minimum: -277.7872\n", + "Iteration No: 9 started. Evaluating function at random point.\n", + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 0.8390\n", + "Function value obtained: -75.4651\n", + "Current minimum: -277.7872\n", + "Iteration No: 10 started. Evaluating function at random point.\n", + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 0.9403\n", + "Function value obtained: -103.9634\n", + "Current minimum: -277.7872\n", + "Iteration No: 11 started. Searching for the next optimal point.\n", + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9237\n", + "Function value obtained: -277.5634\n", + "Current minimum: -277.7872\n", + "Iteration No: 12 started. Searching for the next optimal point.\n", + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0463\n", + "Function value obtained: -274.7053\n", + "Current minimum: -277.7872\n", + "Iteration No: 13 started. Searching for the next optimal point.\n", + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0051\n", + "Function value obtained: -279.8106\n", + "Current minimum: -279.8106\n", + "Iteration No: 14 started. Searching for the next optimal point.\n", + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2822\n", + "Function value obtained: -292.9942\n", + "Current minimum: -292.9942\n", + "Iteration No: 15 started. Searching for the next optimal point.\n", + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0648\n", + "Function value obtained: -283.4486\n", + "Current minimum: -292.9942\n", + "Iteration No: 16 started. Searching for the next optimal point.\n", + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9720\n", + "Function value obtained: -280.7494\n", + "Current minimum: -292.9942\n", + "Iteration No: 17 started. Searching for the next optimal point.\n", + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9772\n", + "Function value obtained: -281.5005\n", + "Current minimum: -292.9942\n", + "Iteration No: 18 started. Searching for the next optimal point.\n", + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0893\n", + "Function value obtained: -279.1016\n", + "Current minimum: -292.9942\n", + "Iteration No: 19 started. Searching for the next optimal point.\n", + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0611\n", + "Function value obtained: -276.8813\n", + "Current minimum: -292.9942\n", + "Iteration No: 20 started. Searching for the next optimal point.\n", + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1266\n", + "Function value obtained: -289.1597\n", + "Current minimum: -292.9942\n", + "Iteration No: 21 started. Searching for the next optimal point.\n", + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0954\n", + "Function value obtained: -282.1525\n", + "Current minimum: -292.9942\n", + "Iteration No: 22 started. Searching for the next optimal point.\n", + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1350\n", + "Function value obtained: -274.5432\n", + "Current minimum: -292.9942\n", + "Iteration No: 23 started. Searching for the next optimal point.\n", + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1059\n", + "Function value obtained: -283.8849\n", + "Current minimum: -292.9942\n", + "Iteration No: 24 started. Searching for the next optimal point.\n", + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0729\n", + "Function value obtained: -281.4180\n", + "Current minimum: -292.9942\n", + "Iteration No: 25 started. Searching for the next optimal point.\n", + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1352\n", + "Function value obtained: -280.5095\n", + "Current minimum: -292.9942\n", + "Iteration No: 26 started. Searching for the next optimal point.\n", + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0043\n", + "Function value obtained: -280.1594\n", + "Current minimum: -292.9942\n", + "Iteration No: 27 started. Searching for the next optimal point.\n", + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0292\n", + "Function value obtained: -286.0372\n", + "Current minimum: -292.9942\n", + "Iteration No: 28 started. Searching for the next optimal point.\n", + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0649\n", + "Function value obtained: -281.2779\n", + "Current minimum: -292.9942\n", + "Iteration No: 29 started. Searching for the next optimal point.\n", + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1362\n", + "Function value obtained: -274.9848\n", + "Current minimum: -292.9942\n", + "Iteration No: 30 started. Searching for the next optimal point.\n", + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9673\n", + "Function value obtained: -283.4041\n", + "Current minimum: -292.9942\n", + "Iteration No: 31 started. Searching for the next optimal point.\n", + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0601\n", + "Function value obtained: -268.8392\n", + "Current minimum: -292.9942\n", + "Iteration No: 32 started. Searching for the next optimal point.\n", + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0646\n", + "Function value obtained: -285.1852\n", + "Current minimum: -292.9942\n", + "Iteration No: 33 started. Searching for the next optimal point.\n", + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0657\n", + "Function value obtained: -280.3916\n", + "Current minimum: -292.9942\n", + "Iteration No: 34 started. Searching for the next optimal point.\n", + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0999\n", + "Function value obtained: -285.1286\n", + "Current minimum: -292.9942\n", + "Iteration No: 35 started. Searching for the next optimal point.\n", + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1333\n", + "Function value obtained: -279.3222\n", + "Current minimum: -292.9942\n", + "Iteration No: 36 started. Searching for the next optimal point.\n", + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1070\n", + "Function value obtained: -282.5652\n", + "Current minimum: -292.9942\n", + "Iteration No: 37 started. Searching for the next optimal point.\n", + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0807\n", + "Function value obtained: -283.9872\n", + "Current minimum: -292.9942\n", + "Iteration No: 38 started. Searching for the next optimal point.\n", + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1115\n", + "Function value obtained: -282.8966\n", + "Current minimum: -292.9942\n", + "Iteration No: 39 started. Searching for the next optimal point.\n", + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1009\n", + "Function value obtained: -280.1954\n", + "Current minimum: -292.9942\n", + "Iteration No: 40 started. Searching for the next optimal point.\n", + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1071\n", + "Function value obtained: -289.4851\n", + "Current minimum: -292.9942\n", + "Iteration No: 41 started. Searching for the next optimal point.\n", + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1248\n", + "Function value obtained: -280.7557\n", + "Current minimum: -292.9942\n", + "Iteration No: 42 started. Searching for the next optimal point.\n", + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0596\n", + "Function value obtained: -285.0433\n", + "Current minimum: -292.9942\n", + "Iteration No: 43 started. Searching for the next optimal point.\n", + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9994\n", + "Function value obtained: -277.5333\n", + "Current minimum: -292.9942\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1541\n", + "Function value obtained: -280.4080\n", + "Current minimum: -292.9942\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0767\n", + "Function value obtained: -252.8654\n", + "Current minimum: -292.9942\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1111\n", + "Function value obtained: -243.0593\n", + "Current minimum: -292.9942\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0752\n", + "Function value obtained: -277.6296\n", + "Current minimum: -292.9942\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0205\n", + "Function value obtained: -266.3835\n", + "Current minimum: -292.9942\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0828\n", + "Function value obtained: -284.8118\n", + "Current minimum: -292.9942\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1228\n", + "Function value obtained: -282.9191\n", + "Current minimum: -292.9942\n", + "CPU times: user 18 s, sys: 4.17 s, total: 22.2 s\n", + "Wall time: 51.9 s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-292.9941660091451, [0.11305329406169397])" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# -> (-64.06042883, [0.041136645707627796, 0.7853961999069485, 0.12010362758045579])" + "%%time\n", + "esc_gbrt = gbrt_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gbrt.fun, esc_gbrt.x" ] }, { "cell_type": "code", - "execution_count": null, - "id": "07b3c0ff-7772-4b7b-926f-bf18cc3cd425", - "metadata": { - "scrolled": true - }, - "outputs": [], + "execution_count": 59, + "id": "d85a57bd-e338-468d-9d63-45d82fe53aef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "%%time\n", - "g_gbrt = gbrt_minimize(g, space, n_calls = 300, verbose=True, n_jobs=-1)\n" + "plot_objective(esc_gbrt)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "f95cb6e7-9d2c-4f70-a648-e27cea582bd6", + "execution_count": 60, + "id": "2e4f4fe1-236c-4f3f-ba31-49d56fdc610d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "# -> (-64.49868469, [0.06184391109700299, 0.3296309210963565, 0.12990125226898555])" + "plot_convergence(esc_gbrt)" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "6e9df680-a093-4d4b-9bed-5e5a8aa8b59d", + "cell_type": "markdown", + "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", "metadata": {}, - "outputs": [], "source": [ - "path = \"../saved_agents/\"\n", - "fname = \"cr_gbrt.pkl\"\n", - "dump(g_gbrt, path+fname)\n", - "\n", - "api.upload_file(\n", - " path_or_fileobj=path+fname,\n", - " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", - " repo_id=\"boettiger-lab/rl4eco\",\n", - " repo_type=\"model\",\n", - ")" + "### CR" ] }, { "cell_type": "code", - "execution_count": null, - "id": "7f0be87a-0380-4ec3-98c1-c5c5879ec3f0", - "metadata": {}, - "outputs": [], + "execution_count": 43, + "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 0.9688\n", + "Function value obtained: -177.7430\n", + "Current minimum: -177.7430\n", + "Iteration No: 2 started. Evaluating function at random point.\n", + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 0.9021\n", + "Function value obtained: -236.8874\n", + "Current minimum: -236.8874\n", + "Iteration No: 3 started. Evaluating function at random point.\n", + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 0.8375\n", + "Function value obtained: -220.4030\n", + "Current minimum: -236.8874\n", + "Iteration No: 4 started. Evaluating function at random point.\n", + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 0.8323\n", + "Function value obtained: -191.7080\n", + "Current minimum: -236.8874\n", + "Iteration No: 5 started. Evaluating function at random point.\n", + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 0.7831\n", + "Function value obtained: -232.0564\n", + "Current minimum: -236.8874\n", + "Iteration No: 6 started. Evaluating function at random point.\n", + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 0.7658\n", + "Function value obtained: -277.0722\n", + "Current minimum: -277.0722\n", + "Iteration No: 7 started. Evaluating function at random point.\n", + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 0.8433\n", + "Function value obtained: -285.9566\n", + "Current minimum: -285.9566\n", + "Iteration No: 8 started. Evaluating function at random point.\n", + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 0.8087\n", + "Function value obtained: -267.4499\n", + "Current minimum: -285.9566\n", + "Iteration No: 9 started. Evaluating function at random point.\n", + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 0.8111\n", + "Function value obtained: -299.6419\n", + "Current minimum: -299.6419\n", + "Iteration No: 10 started. Evaluating function at random point.\n", + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 1.0602\n", + "Function value obtained: -294.7403\n", + "Current minimum: -299.6419\n", + "Iteration No: 11 started. Searching for the next optimal point.\n", + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2801\n", + "Function value obtained: -2.0025\n", + "Current minimum: -299.6419\n", + "Iteration No: 12 started. Searching for the next optimal point.\n", + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2088\n", + "Function value obtained: -290.3686\n", + "Current minimum: -299.6419\n", + "Iteration No: 13 started. Searching for the next optimal point.\n", + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1222\n", + "Function value obtained: -289.1794\n", + "Current minimum: -299.6419\n", + "Iteration No: 14 started. Searching for the next optimal point.\n", + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1470\n", + "Function value obtained: -0.0000\n", + "Current minimum: -299.6419\n", + "Iteration No: 15 started. Searching for the next optimal point.\n", + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2602\n", + "Function value obtained: -0.0000\n", + "Current minimum: -299.6419\n", + "Iteration No: 16 started. Searching for the next optimal point.\n", + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2552\n", + "Function value obtained: -296.1389\n", + "Current minimum: -299.6419\n", + "Iteration No: 17 started. Searching for the next optimal point.\n", + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2958\n", + "Function value obtained: -299.3016\n", + "Current minimum: -299.6419\n", + "Iteration No: 18 started. Searching for the next optimal point.\n", + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1075\n", + "Function value obtained: -295.2190\n", + "Current minimum: -299.6419\n", + "Iteration No: 19 started. Searching for the next optimal point.\n", + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2466\n", + "Function value obtained: -286.7931\n", + "Current minimum: -299.6419\n", + "Iteration No: 20 started. Searching for the next optimal point.\n", + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1416\n", + "Function value obtained: -294.4900\n", + "Current minimum: -299.6419\n", + "Iteration No: 21 started. Searching for the next optimal point.\n", + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2500\n", + "Function value obtained: -293.6535\n", + "Current minimum: -299.6419\n", + "Iteration No: 22 started. Searching for the next optimal point.\n", + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2807\n", + "Function value obtained: -298.7796\n", + "Current minimum: -299.6419\n", + "Iteration No: 23 started. Searching for the next optimal point.\n", + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2438\n", + "Function value obtained: -0.0000\n", + "Current minimum: -299.6419\n", + "Iteration No: 24 started. Searching for the next optimal point.\n", + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1796\n", + "Function value obtained: -285.3215\n", + "Current minimum: -299.6419\n", + "Iteration No: 25 started. Searching for the next optimal point.\n", + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1962\n", + "Function value obtained: -297.3151\n", + "Current minimum: -299.6419\n", + "Iteration No: 26 started. Searching for the next optimal point.\n", + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2090\n", + "Function value obtained: -274.2131\n", + "Current minimum: -299.6419\n", + "Iteration No: 27 started. Searching for the next optimal point.\n", + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1861\n", + "Function value obtained: -288.9430\n", + "Current minimum: -299.6419\n", + "Iteration No: 28 started. Searching for the next optimal point.\n", + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4074\n", + "Function value obtained: -295.3861\n", + "Current minimum: -299.6419\n", + "Iteration No: 29 started. Searching for the next optimal point.\n", + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1041\n", + "Function value obtained: -294.5380\n", + "Current minimum: -299.6419\n", + "Iteration No: 30 started. Searching for the next optimal point.\n", + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2119\n", + "Function value obtained: -298.0625\n", + "Current minimum: -299.6419\n", + "Iteration No: 31 started. Searching for the next optimal point.\n", + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2237\n", + "Function value obtained: -299.2880\n", + "Current minimum: -299.6419\n", + "Iteration No: 32 started. Searching for the next optimal point.\n", + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2877\n", + "Function value obtained: -298.9851\n", + "Current minimum: -299.6419\n", + "Iteration No: 33 started. Searching for the next optimal point.\n", + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2722\n", + "Function value obtained: -287.3789\n", + "Current minimum: -299.6419\n", + "Iteration No: 34 started. Searching for the next optimal point.\n", + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2941\n", + "Function value obtained: -290.9719\n", + "Current minimum: -299.6419\n", + "Iteration No: 35 started. Searching for the next optimal point.\n", + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3283\n", + "Function value obtained: -293.7134\n", + "Current minimum: -299.6419\n", + "Iteration No: 36 started. Searching for the next optimal point.\n", + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2048\n", + "Function value obtained: -285.8287\n", + "Current minimum: -299.6419\n", + "Iteration No: 37 started. Searching for the next optimal point.\n", + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3702\n", + "Function value obtained: -294.2641\n", + "Current minimum: -299.6419\n", + "Iteration No: 38 started. Searching for the next optimal point.\n", + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3412\n", + "Function value obtained: -207.8937\n", + "Current minimum: -299.6419\n", + "Iteration No: 39 started. Searching for the next optimal point.\n", + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3885\n", + "Function value obtained: -282.4190\n", + "Current minimum: -299.6419\n", + "Iteration No: 40 started. Searching for the next optimal point.\n", + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3269\n", + "Function value obtained: -275.7333\n", + "Current minimum: -299.6419\n", + "Iteration No: 41 started. Searching for the next optimal point.\n", + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4073\n", + "Function value obtained: -298.2017\n", + "Current minimum: -299.6419\n", + "Iteration No: 42 started. Searching for the next optimal point.\n", + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3829\n", + "Function value obtained: -294.5551\n", + "Current minimum: -299.6419\n", + "Iteration No: 43 started. Searching for the next optimal point.\n", + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4270\n", + "Function value obtained: -294.8593\n", + "Current minimum: -299.6419\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3759\n", + "Function value obtained: -289.8119\n", + "Current minimum: -299.6419\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4846\n", + "Function value obtained: -284.6668\n", + "Current minimum: -299.6419\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3418\n", + "Function value obtained: -295.8836\n", + "Current minimum: -299.6419\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3991\n", + "Function value obtained: -258.0139\n", + "Current minimum: -299.6419\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4414\n", + "Function value obtained: -295.4342\n", + "Current minimum: -299.6419\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5540\n", + "Function value obtained: -295.7363\n", + "Current minimum: -299.6419\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4234\n", + "Function value obtained: -214.8187\n", + "Current minimum: -299.6419\n", + "Iteration No: 51 started. Searching for the next optimal point.\n", + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3538\n", + "Function value obtained: -293.3212\n", + "Current minimum: -299.6419\n", + "Iteration No: 52 started. Searching for the next optimal point.\n", + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3868\n", + "Function value obtained: -226.8610\n", + "Current minimum: -299.6419\n", + "Iteration No: 53 started. Searching for the next optimal point.\n", + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4428\n", + "Function value obtained: -290.3791\n", + "Current minimum: -299.6419\n", + "Iteration No: 54 started. Searching for the next optimal point.\n", + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4112\n", + "Function value obtained: -297.0097\n", + "Current minimum: -299.6419\n", + "Iteration No: 55 started. Searching for the next optimal point.\n", + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4513\n", + "Function value obtained: -280.0968\n", + "Current minimum: -299.6419\n", + "Iteration No: 56 started. Searching for the next optimal point.\n", + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5152\n", + "Function value obtained: -292.7703\n", + "Current minimum: -299.6419\n", + "Iteration No: 57 started. Searching for the next optimal point.\n", + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3899\n", + "Function value obtained: -295.7863\n", + "Current minimum: -299.6419\n", + "Iteration No: 58 started. Searching for the next optimal point.\n", + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4704\n", + "Function value obtained: -294.8457\n", + "Current minimum: -299.6419\n", + "Iteration No: 59 started. Searching for the next optimal point.\n", + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5006\n", + "Function value obtained: -281.6922\n", + "Current minimum: -299.6419\n", + "Iteration No: 60 started. Searching for the next optimal point.\n", + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3983\n", + "Function value obtained: -178.4917\n", + "Current minimum: -299.6419\n", + "Iteration No: 61 started. Searching for the next optimal point.\n", + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4636\n", + "Function value obtained: -302.6849\n", + "Current minimum: -302.6849\n", + "Iteration No: 62 started. Searching for the next optimal point.\n", + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4780\n", + "Function value obtained: -311.0656\n", + "Current minimum: -311.0656\n", + "Iteration No: 63 started. Searching for the next optimal point.\n", + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4972\n", + "Function value obtained: -303.8878\n", + "Current minimum: -311.0656\n", + "Iteration No: 64 started. Searching for the next optimal point.\n", + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6057\n", + "Function value obtained: -2.1697\n", + "Current minimum: -311.0656\n", + "Iteration No: 65 started. Searching for the next optimal point.\n", + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5193\n", + "Function value obtained: -303.1321\n", + "Current minimum: -311.0656\n", + "Iteration No: 66 started. Searching for the next optimal point.\n", + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5252\n", + "Function value obtained: -295.1447\n", + "Current minimum: -311.0656\n", + "Iteration No: 67 started. Searching for the next optimal point.\n", + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7154\n", + "Function value obtained: -303.2232\n", + "Current minimum: -311.0656\n", + "Iteration No: 68 started. Searching for the next optimal point.\n", + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5050\n", + "Function value obtained: -303.0628\n", + "Current minimum: -311.0656\n", + "Iteration No: 69 started. Searching for the next optimal point.\n", + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6620\n", + "Function value obtained: -298.0582\n", + "Current minimum: -311.0656\n", + "Iteration No: 70 started. Searching for the next optimal point.\n", + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5761\n", + "Function value obtained: -307.8417\n", + "Current minimum: -311.0656\n", + "Iteration No: 71 started. Searching for the next optimal point.\n", + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6041\n", + "Function value obtained: -298.3403\n", + "Current minimum: -311.0656\n", + "Iteration No: 72 started. Searching for the next optimal point.\n", + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7091\n", + "Function value obtained: -301.8719\n", + "Current minimum: -311.0656\n", + "Iteration No: 73 started. Searching for the next optimal point.\n", + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5736\n", + "Function value obtained: -125.0059\n", + "Current minimum: -311.0656\n", + "Iteration No: 74 started. Searching for the next optimal point.\n", + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6025\n", + "Function value obtained: -287.2530\n", + "Current minimum: -311.0656\n", + "Iteration No: 75 started. Searching for the next optimal point.\n", + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6006\n", + "Function value obtained: -287.6337\n", + "Current minimum: -311.0656\n", + "Iteration No: 76 started. Searching for the next optimal point.\n", + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5020\n", + "Function value obtained: -0.0000\n", + "Current minimum: -311.0656\n", + "Iteration No: 77 started. Searching for the next optimal point.\n", + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5976\n", + "Function value obtained: -307.7633\n", + "Current minimum: -311.0656\n", + "Iteration No: 78 started. Searching for the next optimal point.\n", + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5648\n", + "Function value obtained: -298.2648\n", + "Current minimum: -311.0656\n", + "Iteration No: 79 started. Searching for the next optimal point.\n", + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6787\n", + "Function value obtained: -302.3059\n", + "Current minimum: -311.0656\n", + "Iteration No: 80 started. Searching for the next optimal point.\n", + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6299\n", + "Function value obtained: -286.9437\n", + "Current minimum: -311.0656\n", + "Iteration No: 81 started. Searching for the next optimal point.\n", + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6426\n", + "Function value obtained: -221.7871\n", + "Current minimum: -311.0656\n", + "Iteration No: 82 started. Searching for the next optimal point.\n", + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5901\n", + "Function value obtained: -295.1352\n", + "Current minimum: -311.0656\n", + "Iteration No: 83 started. Searching for the next optimal point.\n", + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6654\n", + "Function value obtained: -272.5847\n", + "Current minimum: -311.0656\n", + "Iteration No: 84 started. Searching for the next optimal point.\n", + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7248\n", + "Function value obtained: -285.7321\n", + "Current minimum: -311.0656\n", + "Iteration No: 85 started. Searching for the next optimal point.\n", + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6756\n", + "Function value obtained: -281.1855\n", + "Current minimum: -311.0656\n", + "Iteration No: 86 started. Searching for the next optimal point.\n", + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7014\n", + "Function value obtained: -298.2237\n", + "Current minimum: -311.0656\n", + "Iteration No: 87 started. Searching for the next optimal point.\n", + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6424\n", + "Function value obtained: -301.8678\n", + "Current minimum: -311.0656\n", + "Iteration No: 88 started. Searching for the next optimal point.\n", + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7478\n", + "Function value obtained: -306.2168\n", + "Current minimum: -311.0656\n", + "Iteration No: 89 started. Searching for the next optimal point.\n", + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7986\n", + "Function value obtained: -304.4900\n", + "Current minimum: -311.0656\n", + "Iteration No: 90 started. Searching for the next optimal point.\n", + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7096\n", + "Function value obtained: -303.1646\n", + "Current minimum: -311.0656\n", + "Iteration No: 91 started. Searching for the next optimal point.\n", + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8139\n", + "Function value obtained: -292.6286\n", + "Current minimum: -311.0656\n", + "Iteration No: 92 started. Searching for the next optimal point.\n", + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8023\n", + "Function value obtained: -293.7803\n", + "Current minimum: -311.0656\n", + "Iteration No: 93 started. Searching for the next optimal point.\n", + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9644\n", + "Function value obtained: -0.0000\n", + "Current minimum: -311.0656\n", + "Iteration No: 94 started. Searching for the next optimal point.\n", + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8525\n", + "Function value obtained: -307.6464\n", + "Current minimum: -311.0656\n", + "Iteration No: 95 started. Searching for the next optimal point.\n", + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0535\n", + "Function value obtained: -297.1392\n", + "Current minimum: -311.0656\n", + "Iteration No: 96 started. Searching for the next optimal point.\n", + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9497\n", + "Function value obtained: -295.7007\n", + "Current minimum: -311.0656\n", + "Iteration No: 97 started. Searching for the next optimal point.\n", + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9379\n", + "Function value obtained: -300.8349\n", + "Current minimum: -311.0656\n", + "Iteration No: 98 started. Searching for the next optimal point.\n", + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9077\n", + "Function value obtained: -303.4907\n", + "Current minimum: -311.0656\n", + "Iteration No: 99 started. Searching for the next optimal point.\n", + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9800\n", + "Function value obtained: -304.5316\n", + "Current minimum: -311.0656\n", + "Iteration No: 100 started. Searching for the next optimal point.\n", + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9321\n", + "Function value obtained: -297.2611\n", + "Current minimum: -311.0656\n", + "CPU times: user 6min 24s, sys: 37min 45s, total: 44min 10s\n", + "Wall time: 2min 22s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-311.0656367052435,\n", + " [0.8260241432235854, 0.12728057019636857, 0.6172786457423112])" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 100, verbose=True, n_jobs=-1)\n", + "cr_gp.fun, cr_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "faa3ef2e-e477-401d-b663-3e10e15d2023", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_convergence(cr_gp)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 1.0046\n", + "Function value obtained: -290.4467\n", + "Current minimum: -290.4467\n", + "Iteration No: 2 started. Evaluating function at random point.\n", + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 0.9040\n", + "Function value obtained: -287.7544\n", + "Current minimum: -290.4467\n", + "Iteration No: 3 started. Evaluating function at random point.\n", + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 0.8965\n", + "Function value obtained: -249.5194\n", + "Current minimum: -290.4467\n", + "Iteration No: 4 started. Evaluating function at random point.\n", + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 0.9173\n", + "Function value obtained: -270.6394\n", + "Current minimum: -290.4467\n", + "Iteration No: 5 started. Evaluating function at random point.\n", + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 0.8864\n", + "Function value obtained: -65.5867\n", + "Current minimum: -290.4467\n", + "Iteration No: 6 started. Evaluating function at random point.\n", + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 0.9363\n", + "Function value obtained: -271.5450\n", + "Current minimum: -290.4467\n", + "Iteration No: 7 started. Evaluating function at random point.\n", + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 0.7902\n", + "Function value obtained: -222.5058\n", + "Current minimum: -290.4467\n", + "Iteration No: 8 started. Evaluating function at random point.\n", + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 0.8681\n", + "Function value obtained: -295.9096\n", + "Current minimum: -295.9096\n", + "Iteration No: 9 started. Evaluating function at random point.\n", + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 0.9238\n", + "Function value obtained: -216.7773\n", + "Current minimum: -295.9096\n", + "Iteration No: 10 started. Evaluating function at random point.\n", + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 1.2149\n", + "Function value obtained: -266.4456\n", + "Current minimum: -295.9096\n", + "Iteration No: 11 started. Searching for the next optimal point.\n", + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2302\n", + "Function value obtained: -290.8275\n", + "Current minimum: -295.9096\n", + "Iteration No: 12 started. Searching for the next optimal point.\n", + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1770\n", + "Function value obtained: -0.0000\n", + "Current minimum: -295.9096\n", + "Iteration No: 13 started. Searching for the next optimal point.\n", + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2050\n", + "Function value obtained: -304.2257\n", + "Current minimum: -304.2257\n", + "Iteration No: 14 started. Searching for the next optimal point.\n", + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1736\n", + "Function value obtained: -298.4433\n", + "Current minimum: -304.2257\n", + "Iteration No: 15 started. Searching for the next optimal point.\n", + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2257\n", + "Function value obtained: -194.3862\n", + "Current minimum: -304.2257\n", + "Iteration No: 16 started. Searching for the next optimal point.\n", + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1873\n", + "Function value obtained: -297.8070\n", + "Current minimum: -304.2257\n", + "Iteration No: 17 started. Searching for the next optimal point.\n", + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2018\n", + "Function value obtained: -291.6737\n", + "Current minimum: -304.2257\n", + "Iteration No: 18 started. Searching for the next optimal point.\n", + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2290\n", + "Function value obtained: -198.6580\n", + "Current minimum: -304.2257\n", + "Iteration No: 19 started. Searching for the next optimal point.\n", + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2352\n", + "Function value obtained: -295.1444\n", + "Current minimum: -304.2257\n", + "Iteration No: 20 started. Searching for the next optimal point.\n", + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1875\n", + "Function value obtained: -295.9261\n", + "Current minimum: -304.2257\n", + "Iteration No: 21 started. Searching for the next optimal point.\n", + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1330\n", + "Function value obtained: -289.4736\n", + "Current minimum: -304.2257\n", + "Iteration No: 22 started. Searching for the next optimal point.\n", + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3153\n", + "Function value obtained: -260.2356\n", + "Current minimum: -304.2257\n", + "Iteration No: 23 started. Searching for the next optimal point.\n", + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1901\n", + "Function value obtained: -288.9316\n", + "Current minimum: -304.2257\n", + "Iteration No: 24 started. Searching for the next optimal point.\n", + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1431\n", + "Function value obtained: -296.7682\n", + "Current minimum: -304.2257\n", + "Iteration No: 25 started. Searching for the next optimal point.\n", + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1726\n", + "Function value obtained: -287.2288\n", + "Current minimum: -304.2257\n", + "Iteration No: 26 started. Searching for the next optimal point.\n", + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2014\n", + "Function value obtained: -275.8044\n", + "Current minimum: -304.2257\n", + "Iteration No: 27 started. Searching for the next optimal point.\n", + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2636\n", + "Function value obtained: -267.4262\n", + "Current minimum: -304.2257\n", + "Iteration No: 28 started. Searching for the next optimal point.\n", + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0494\n", + "Function value obtained: -0.0000\n", + "Current minimum: -304.2257\n", + "Iteration No: 29 started. Searching for the next optimal point.\n", + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1206\n", + "Function value obtained: -301.4241\n", + "Current minimum: -304.2257\n", + "Iteration No: 30 started. Searching for the next optimal point.\n", + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1381\n", + "Function value obtained: -267.7554\n", + "Current minimum: -304.2257\n", + "Iteration No: 31 started. Searching for the next optimal point.\n", + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1519\n", + "Function value obtained: -292.7353\n", + "Current minimum: -304.2257\n", + "Iteration No: 32 started. Searching for the next optimal point.\n", + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2797\n", + "Function value obtained: -297.3140\n", + "Current minimum: -304.2257\n", + "Iteration No: 33 started. Searching for the next optimal point.\n", + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2027\n", + "Function value obtained: -287.8151\n", + "Current minimum: -304.2257\n", + "Iteration No: 34 started. Searching for the next optimal point.\n", + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1803\n", + "Function value obtained: -0.0000\n", + "Current minimum: -304.2257\n", + "Iteration No: 35 started. Searching for the next optimal point.\n", + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1506\n", + "Function value obtained: -301.6094\n", + "Current minimum: -304.2257\n", + "Iteration No: 36 started. Searching for the next optimal point.\n", + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3169\n", + "Function value obtained: -209.3356\n", + "Current minimum: -304.2257\n", + "Iteration No: 37 started. Searching for the next optimal point.\n", + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3316\n", + "Function value obtained: -295.5580\n", + "Current minimum: -304.2257\n", + "Iteration No: 38 started. Searching for the next optimal point.\n", + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3323\n", + "Function value obtained: -285.1147\n", + "Current minimum: -304.2257\n", + "Iteration No: 39 started. Searching for the next optimal point.\n", + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3400\n", + "Function value obtained: -303.0626\n", + "Current minimum: -304.2257\n", + "Iteration No: 40 started. Searching for the next optimal point.\n", + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3514\n", + "Function value obtained: -305.2943\n", + "Current minimum: -305.2943\n", + "Iteration No: 41 started. Searching for the next optimal point.\n", + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2372\n", + "Function value obtained: -203.5269\n", + "Current minimum: -305.2943\n", + "Iteration No: 42 started. Searching for the next optimal point.\n", + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4567\n", + "Function value obtained: -303.0688\n", + "Current minimum: -305.2943\n", + "Iteration No: 43 started. Searching for the next optimal point.\n", + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3484\n", + "Function value obtained: -301.9493\n", + "Current minimum: -305.2943\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4485\n", + "Function value obtained: -296.1355\n", + "Current minimum: -305.2943\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5512\n", + "Function value obtained: -293.9905\n", + "Current minimum: -305.2943\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3773\n", + "Function value obtained: -303.7250\n", + "Current minimum: -305.2943\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3116\n", + "Function value obtained: -282.0631\n", + "Current minimum: -305.2943\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4090\n", + "Function value obtained: -293.7529\n", + "Current minimum: -305.2943\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5175\n", + "Function value obtained: -298.3346\n", + "Current minimum: -305.2943\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4520\n", + "Function value obtained: -289.3039\n", + "Current minimum: -305.2943\n", + "Iteration No: 51 started. Searching for the next optimal point.\n", + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4870\n", + "Function value obtained: -306.4716\n", + "Current minimum: -306.4716\n", + "Iteration No: 52 started. Searching for the next optimal point.\n", + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5303\n", + "Function value obtained: -291.8902\n", + "Current minimum: -306.4716\n", + "Iteration No: 53 started. Searching for the next optimal point.\n", + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4603\n", + "Function value obtained: -291.8776\n", + "Current minimum: -306.4716\n", + "Iteration No: 54 started. Searching for the next optimal point.\n", + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3981\n", + "Function value obtained: -300.2908\n", + "Current minimum: -306.4716\n", + "Iteration No: 55 started. Searching for the next optimal point.\n", + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5068\n", + "Function value obtained: -295.8518\n", + "Current minimum: -306.4716\n", + "Iteration No: 56 started. Searching for the next optimal point.\n", + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3083\n", + "Function value obtained: -286.2281\n", + "Current minimum: -306.4716\n", + "Iteration No: 57 started. Searching for the next optimal point.\n", + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5260\n", + "Function value obtained: -306.9200\n", + "Current minimum: -306.9200\n", + "Iteration No: 58 started. Searching for the next optimal point.\n", + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5102\n", + "Function value obtained: -308.5368\n", + "Current minimum: -308.5368\n", + "Iteration No: 59 started. Searching for the next optimal point.\n", + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4828\n", + "Function value obtained: -303.5964\n", + "Current minimum: -308.5368\n", + "Iteration No: 60 started. Searching for the next optimal point.\n", + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5236\n", + "Function value obtained: -2.1453\n", + "Current minimum: -308.5368\n", + "Iteration No: 61 started. Searching for the next optimal point.\n", + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4958\n", + "Function value obtained: -291.4858\n", + "Current minimum: -308.5368\n", + "Iteration No: 62 started. Searching for the next optimal point.\n", + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5144\n", + "Function value obtained: -283.4553\n", + "Current minimum: -308.5368\n", + "Iteration No: 63 started. Searching for the next optimal point.\n", + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5721\n", + "Function value obtained: -273.3013\n", + "Current minimum: -308.5368\n", + "Iteration No: 64 started. Searching for the next optimal point.\n", + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5130\n", + "Function value obtained: -294.4617\n", + "Current minimum: -308.5368\n", + "Iteration No: 65 started. Searching for the next optimal point.\n", + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4355\n", + "Function value obtained: -299.3130\n", + "Current minimum: -308.5368\n", + "Iteration No: 66 started. Searching for the next optimal point.\n", + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6231\n", + "Function value obtained: -294.1639\n", + "Current minimum: -308.5368\n", + "Iteration No: 67 started. Searching for the next optimal point.\n", + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5358\n", + "Function value obtained: -278.8293\n", + "Current minimum: -308.5368\n", + "Iteration No: 68 started. Searching for the next optimal point.\n", + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5408\n", + "Function value obtained: -303.0506\n", + "Current minimum: -308.5368\n", + "Iteration No: 69 started. Searching for the next optimal point.\n", + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5449\n", + "Function value obtained: -63.6140\n", + "Current minimum: -308.5368\n", + "Iteration No: 70 started. Searching for the next optimal point.\n", + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7312\n", + "Function value obtained: -285.4334\n", + "Current minimum: -308.5368\n", + "Iteration No: 71 started. Searching for the next optimal point.\n", + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5485\n", + "Function value obtained: -287.7139\n", + "Current minimum: -308.5368\n", + "Iteration No: 72 started. Searching for the next optimal point.\n", + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5449\n", + "Function value obtained: -277.4130\n", + "Current minimum: -308.5368\n", + "Iteration No: 73 started. Searching for the next optimal point.\n", + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6182\n", + "Function value obtained: -277.4510\n", + "Current minimum: -308.5368\n", + "Iteration No: 74 started. Searching for the next optimal point.\n", + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7583\n", + "Function value obtained: -198.3445\n", + "Current minimum: -308.5368\n", + "Iteration No: 75 started. Searching for the next optimal point.\n", + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6535\n", + "Function value obtained: -284.8034\n", + "Current minimum: -308.5368\n", + "Iteration No: 76 started. Searching for the next optimal point.\n", + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6444\n", + "Function value obtained: -157.9246\n", + "Current minimum: -308.5368\n", + "Iteration No: 77 started. Searching for the next optimal point.\n", + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6303\n", + "Function value obtained: -287.9055\n", + "Current minimum: -308.5368\n", + "Iteration No: 78 started. Searching for the next optimal point.\n", + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6791\n", + "Function value obtained: -299.9861\n", + "Current minimum: -308.5368\n", + "Iteration No: 79 started. Searching for the next optimal point.\n", + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6413\n", + "Function value obtained: -260.2050\n", + "Current minimum: -308.5368\n", + "Iteration No: 80 started. Searching for the next optimal point.\n", + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7575\n", + "Function value obtained: -242.1260\n", + "Current minimum: -308.5368\n", + "Iteration No: 81 started. Searching for the next optimal point.\n", + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7188\n", + "Function value obtained: -303.5188\n", + "Current minimum: -308.5368\n", + "Iteration No: 82 started. Searching for the next optimal point.\n", + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7791\n", + "Function value obtained: -297.5755\n", + "Current minimum: -308.5368\n", + "Iteration No: 83 started. Searching for the next optimal point.\n", + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7636\n", + "Function value obtained: -297.3914\n", + "Current minimum: -308.5368\n", + "Iteration No: 84 started. Searching for the next optimal point.\n", + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7330\n", + "Function value obtained: -293.5340\n", + "Current minimum: -308.5368\n", + "Iteration No: 85 started. Searching for the next optimal point.\n", + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6580\n", + "Function value obtained: -306.8974\n", + "Current minimum: -308.5368\n", + "Iteration No: 86 started. Searching for the next optimal point.\n", + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7665\n", + "Function value obtained: -301.9013\n", + "Current minimum: -308.5368\n", + "Iteration No: 87 started. Searching for the next optimal point.\n", + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6774\n", + "Function value obtained: -279.4106\n", + "Current minimum: -308.5368\n", + "Iteration No: 88 started. Searching for the next optimal point.\n", + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7285\n", + "Function value obtained: -289.2226\n", + "Current minimum: -308.5368\n", + "Iteration No: 89 started. Searching for the next optimal point.\n", + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6588\n", + "Function value obtained: -277.8815\n", + "Current minimum: -308.5368\n", + "Iteration No: 90 started. Searching for the next optimal point.\n", + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7752\n", + "Function value obtained: -253.0651\n", + "Current minimum: -308.5368\n", + "Iteration No: 91 started. Searching for the next optimal point.\n", + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8283\n", + "Function value obtained: -258.8707\n", + "Current minimum: -308.5368\n", + "Iteration No: 92 started. Searching for the next optimal point.\n", + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8296\n", + "Function value obtained: -304.0923\n", + "Current minimum: -308.5368\n", + "Iteration No: 93 started. Searching for the next optimal point.\n", + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8217\n", + "Function value obtained: -286.9844\n", + "Current minimum: -308.5368\n", + "Iteration No: 94 started. Searching for the next optimal point.\n", + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9184\n", + "Function value obtained: -291.0580\n", + "Current minimum: -308.5368\n", + "Iteration No: 95 started. Searching for the next optimal point.\n", + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9376\n", + "Function value obtained: -300.1590\n", + "Current minimum: -308.5368\n", + "Iteration No: 96 started. Searching for the next optimal point.\n", + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9354\n", + "Function value obtained: -270.6343\n", + "Current minimum: -308.5368\n", + "Iteration No: 97 started. Searching for the next optimal point.\n", + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8628\n", + "Function value obtained: -288.8999\n", + "Current minimum: -308.5368\n", + "Iteration No: 98 started. Searching for the next optimal point.\n", + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9223\n", + "Function value obtained: -292.9728\n", + "Current minimum: -308.5368\n", + "Iteration No: 99 started. Searching for the next optimal point.\n", + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9157\n", + "Function value obtained: -284.6444\n", + "Current minimum: -308.5368\n", + "Iteration No: 100 started. Searching for the next optimal point.\n", + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8037\n", + "Function value obtained: -268.8821\n", + "Current minimum: -308.5368\n", + "CPU times: user 6min 27s, sys: 38min 11s, total: 44min 39s\n", + "Wall time: 2min 22s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-308.53680147877856,\n", + " [0.23674914103361688, 0.4274663412150027, 0.10944474970918672])" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "g_gp.fun, g_gp.x, g_gbrt.fun, g_gbrt.x" + "%%time\n", + "cr_gbrt = gp_minimize(cr_obj, cr_space, n_calls = 100, verbose=True, n_jobs=-1)\n", + "cr_gbrt.fun, cr_gbrt.x" ] }, { "cell_type": "code", - "execution_count": null, - "id": "3735cd70-433a-406a-936b-a598fe700d0a", + "execution_count": 47, + "id": "dffeed5a-f975-4a6b-b91c-1d91e6c45140", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "res = g_gp\n", - "\n", - "radius = res.x[0]\n", - "theta = res.x[1]\n", - "y2 = res.x[2]\n", - "x1 = np.sin(theta) * radius\n", - "x2 = np.cos(theta) * radius\n", - "\n", - "agent = CautionaryRule(x1, x2, y2)\n", - "evaluate_policy(agent, Monitor(env), n_eval_episodes=100)\n" + "plot_objective(cr_gbrt)" ] }, { "cell_type": "code", - "execution_count": null, - "id": "1e979533-468b-42a8-baba-3c6497924374", + "execution_count": 48, + "id": "6f027ba6-05ac-49d5-90c9-07ec37927510", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "plot_objective(g_gp)" + "plot_convergence(cr_gbrt)" ] }, { "cell_type": "markdown", - "id": "ad2a9d3e-5131-404b-a48a-6dab2c20e87f", + "id": "91246eab-af4e-45ad-b681-f5b20d6e95a2", "metadata": {}, "source": [ - "# Reward statistics" + "# Saving results" ] }, { "cell_type": "markdown", - "id": "230d8821-9f17-41ea-88af-189e33f2f0d7", - "metadata": {}, - "source": [ - "## RL agents" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d9427392-bac3-48fe-8332-0e4b01daa318", + "id": "34a2d6bc-8fd9-4ffc-92e5-18f7e949a0bc", "metadata": {}, - "outputs": [], "source": [ - "revision = \"d21aac2cf7acd04485ae97c4194954cdba038ce2\"\n", - "ppo_1obs = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/PPO-Asm-v0-1.zip\", revision=revision)\n", - "ppo_2obs = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/PPO-Asm2o-v0-1.zip\", revision=revision)" + "### MSY" ] }, { "cell_type": "code", - "execution_count": null, - "id": "141e553d-92ad-4361-ab3e-cefe21b2421c", + "execution_count": 51, + "id": "dabc6e34-7a25-4b2d-b8b1-294b59f60ca0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "CommitInfo(commit_url='https://huggingface.co/boettiger-lab/rl4eco/commit/93a77a99bc7c9d63f939b187be8953839673c1f4', commit_message='Upload sb3/rl4fisheries/msy_gbrt.pkl with huggingface_hub', commit_description='', oid='93a77a99bc7c9d63f939b187be8953839673c1f4', pr_url=None, pr_revision=None, pr_num=None)" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "from rl4fisheries.utils.sb3 import load_sb3_agent\n", + "path = \"../saved_agents/\"\n", + "fname = \"msy_gp.pkl\"\n", + "dump(msy_gp, path+fname)\n", + "\n", + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")\n", + "\n", + "path = \"../saved_agents/\"\n", + "fname = \"msy_gbrt.pkl\"\n", + "dump(msy_gbrt, path+fname)\n", "\n", - "ppo_agent = load_sb3_agent(algo = \"PPO\", env = Asm(), weights = ppo_1obs)\n", - "ppo2o_agent = load_sb3_agent(algo = \"PPO\", env = Asm2o(), weights = ppo_2obs)" + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")" ] }, { "cell_type": "markdown", - "id": "1ba152f6-31c0-4dff-98fc-792ee2c20f3d", - "metadata": {}, - "source": [ - "## Fixed policy agents" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1f4c489c-e309-4ed3-beec-b9373a4aa630", + "id": "fe6f30de-f118-4cba-815a-f742a88a831a", "metadata": {}, - "outputs": [], "source": [ - "msy_agent = Msy(mortality = 0.05811506272614242)" + "### Esc" ] }, { "cell_type": "code", - "execution_count": null, - "id": "f0a07389-1557-4eb9-a1e1-cc9be6435567", + "execution_count": 52, + "id": "eda35133-a2de-4dc4-adfc-7e00cf245cb8", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "CommitInfo(commit_url='https://huggingface.co/boettiger-lab/rl4eco/commit/6d5916a6c8a127c0fad05c60939599a5433977f3', commit_message='Upload sb3/rl4fisheries/esc_gbrt.pkl with huggingface_hub', commit_description='', oid='6d5916a6c8a127c0fad05c60939599a5433977f3', pr_url=None, pr_revision=None, pr_num=None)" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "radius, theta, y2 = [0.041136645707627796, 0.7853961999069485, 0.12010362758045579] \n", + "path = \"../saved_agents/\"\n", + "fname = \"esc_gp.pkl\"\n", + "dump(esc_gp, path+fname)\n", + "\n", + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")\n", "\n", - "x1 = radius * np.sin(theta)\n", - "x2 = radius * np.cos(theta)\n", + "path = \"../saved_agents/\"\n", + "fname = \"esc_gbrt.pkl\"\n", + "dump(msy_gbrt, path+fname)\n", "\n", - "cr_agent = CautionaryRule(x1=x1, x2=x2, y2=y2)" + "api.upload_file(\n", + " path_or_fileobj=path+fname,\n", + " path_in_repo=\"sb3/rl4fisheries/\"+fname,\n", + " repo_id=\"boettiger-lab/rl4eco\",\n", + " repo_type=\"model\",\n", + ")" ] }, { "cell_type": "markdown", - "id": "219bdbd1-3010-48e5-965f-908855dd712b", + "id": "6a368847-01aa-4d15-88a6-ef79f2bc7a7a", "metadata": {}, "source": [ - "## Generate reward data" + "### CR" ] }, { "cell_type": "code", - "execution_count": null, - "id": "c15e31d5-d40e-495b-9c94-a2bc35efe403", + "execution_count": 53, + "id": "65d4a502-7bcd-4949-8dc7-294bfd11dfec", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5b58f469a6104327bd24aa4551c89f1c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "cr_gp.pkl: 0%| | 0.00/5.96M [00:00 Date: Mon, 8 Apr 2024 20:45:52 +0000 Subject: [PATCH 14/64] found r_dev bug on reset, fixed it! Plus, playing around with parameter values, recruitment function shape and noise process --- hyperpars/ppo-asm.yml | 2 +- hyperpars/rppo-asm.yml | 6 +- hyperpars/tqc-asm.yml | 4 +- notebooks/optimal-fixed-policy.ipynb | 2999 ++++++++++++++------------ notebooks/popdyn_tests.ipynb | 279 ++- src/rl4fisheries/envs/asm_env.py | 12 +- src/rl4fisheries/envs/asm_fns.py | 7 +- 7 files changed, 1892 insertions(+), 1417 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 3a5399a..89bf92f 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -8,7 +8,7 @@ algo_config: # env env_id: "AsmEnv" -config: {'s': 0.97} +config: {'s': 0.94, 'p_big':0.05} n_envs: 12 # io diff --git a/hyperpars/rppo-asm.yml b/hyperpars/rppo-asm.yml index caa9f73..cbf4bdc 100644 --- a/hyperpars/rppo-asm.yml +++ b/hyperpars/rppo-asm.yml @@ -2,13 +2,13 @@ # algo overall algo: "RPPO" -total_timesteps: 20000000 +total_timesteps: 5000000 additional_imports: ["torch"] # env overall env_id: "AsmEnv" -config: {} +config: {'s': 0.94, 'p_big':0.05} n_envs: 4 # io @@ -91,7 +91,7 @@ save_path: "../saved_agents" # INVERTED PENDULUM id: "inv_pend" algo_config: - tensorboard_log: "../../logs" + tensorboard_log: "../../../logs" policy: 'MlpLstmPolicy' n_steps: 2048 batch_size: 64 diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index 7a22406..ff85617 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -1,6 +1,6 @@ # algo algo: "TQC" -total_timesteps: 20000000 +total_timesteps: 5000000 algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' @@ -10,7 +10,7 @@ algo_config: # env env_id: "AsmEnv" -config: {'s': 0.97} +config: {'s': 0.94, 'p_big':0.05} n_envs: 12 # io diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index 71df943..ccc3738 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 1, "id": "f15d4b8e-ef57-4bce-899b-89bb32d396f6", "metadata": { "scrolled": true @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 1, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", "metadata": {}, "outputs": [], @@ -56,12 +56,46 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 11, "id": "236788a7-ed25-46bd-a9b0-f7301e96cacf", "metadata": {}, "outputs": [], "source": [ - "CONFIG = {\"s\": 0.97}" + "CONFIG = {\"s\": 0.86, \"p_big\": 0.1}" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "e8df2b0b-bf26-46e3-9ddb-331870bc4719", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(2.2530262102712397, 2.703631452325488)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "env = AsmEnv(config=CONFIG)\n", + "env.parameters['bhb'], env.parameters['bha']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d94545dc-fe80-4a1d-8b16-77d3ad8f3493", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "esc_gp = gp_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gp.fun, esc_gp.x" ] }, { @@ -74,14 +108,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "b59deb35-b67d-4232-bce4-ae9c8c2f0fcc", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1f4f8db48f7d45479af91d26c45e3d8c", + "model_id": "5389c5ee0ffb45af9a7f40d41c71c9a6", "version_major": 2, "version_minor": 0 }, @@ -113,7 +147,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 4, "id": "38838cb2-44df-404b-9cd8-4ecfc9347dd9", "metadata": {}, "outputs": [], @@ -161,7 +195,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 5, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], @@ -234,9 +268,13 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 85, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -246,265 +284,265 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.0331\n", - "Function value obtained: -5.2814\n", - "Current minimum: -5.2814\n", + "Time taken: 0.9026\n", + "Function value obtained: -10.5153\n", + "Current minimum: -10.5153\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.9389\n", - "Function value obtained: -5.5732\n", - "Current minimum: -5.5732\n", + "Time taken: 0.8077\n", + "Function value obtained: -420.3512\n", + "Current minimum: -420.3512\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.9743\n", - "Function value obtained: -4.0990\n", - "Current minimum: -5.5732\n", + "Time taken: 0.7918\n", + "Function value obtained: -16.8727\n", + "Current minimum: -420.3512\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.9839\n", - "Function value obtained: -23.4898\n", - "Current minimum: -23.4898\n", + "Time taken: 0.8600\n", + "Function value obtained: -419.8449\n", + "Current minimum: -420.3512\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.9085\n", - "Function value obtained: -6.0686\n", - "Current minimum: -23.4898\n", + "Time taken: 0.9068\n", + "Function value obtained: -22.9095\n", + "Current minimum: -420.3512\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8752\n", - "Function value obtained: -235.2743\n", - "Current minimum: -235.2743\n", + "Time taken: 0.7952\n", + "Function value obtained: -238.6421\n", + "Current minimum: -420.3512\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.9102\n", - "Function value obtained: -72.9662\n", - "Current minimum: -235.2743\n", + "Time taken: 0.8001\n", + "Function value obtained: -116.9043\n", + "Current minimum: -420.3512\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.9273\n", - "Function value obtained: -4.1430\n", - "Current minimum: -235.2743\n", + "Time taken: 0.8405\n", + "Function value obtained: -31.0751\n", + "Current minimum: -420.3512\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.9578\n", - "Function value obtained: -102.7956\n", - "Current minimum: -235.2743\n", + "Time taken: 0.7906\n", + "Function value obtained: -57.5424\n", + "Current minimum: -420.3512\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 5.1846\n", - "Function value obtained: -3.8220\n", - "Current minimum: -235.2743\n", + "Time taken: 5.4712\n", + "Function value obtained: -204.3319\n", + "Current minimum: -420.3512\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6037\n", - "Function value obtained: -221.5640\n", - "Current minimum: -235.2743\n", + "Time taken: 2.2698\n", + "Function value obtained: -420.2488\n", + "Current minimum: -420.3512\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4502\n", - "Function value obtained: -241.0760\n", - "Current minimum: -241.0760\n", + "Time taken: 2.3171\n", + "Function value obtained: -412.5722\n", + "Current minimum: -420.3512\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5486\n", - "Function value obtained: -242.0662\n", - "Current minimum: -242.0662\n", + "Time taken: 2.2952\n", + "Function value obtained: -426.1817\n", + "Current minimum: -426.1817\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4723\n", - "Function value obtained: -241.7904\n", - "Current minimum: -242.0662\n", + "Time taken: 2.3829\n", + "Function value obtained: -21.7216\n", + "Current minimum: -426.1817\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4760\n", - "Function value obtained: -242.3443\n", - "Current minimum: -242.3443\n", + "Time taken: 2.3202\n", + "Function value obtained: -420.7467\n", + "Current minimum: -426.1817\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4076\n", - "Function value obtained: -234.9429\n", - "Current minimum: -242.3443\n", + "Time taken: 2.3807\n", + "Function value obtained: -423.5646\n", + "Current minimum: -426.1817\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4601\n", - "Function value obtained: -242.2561\n", - "Current minimum: -242.3443\n", + "Time taken: 2.3794\n", + "Function value obtained: -423.5132\n", + "Current minimum: -426.1817\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0870\n", - "Function value obtained: -246.7795\n", - "Current minimum: -246.7795\n", + "Time taken: 2.0279\n", + "Function value obtained: -404.1033\n", + "Current minimum: -426.1817\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0813\n", - "Function value obtained: -3.5915\n", - "Current minimum: -246.7795\n", + "Time taken: 1.4973\n", + "Function value obtained: -423.7958\n", + "Current minimum: -426.1817\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0608\n", - "Function value obtained: -245.7409\n", - "Current minimum: -246.7795\n", + "Time taken: 1.0718\n", + "Function value obtained: -429.7038\n", + "Current minimum: -429.7038\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1608\n", - "Function value obtained: -242.4195\n", - "Current minimum: -246.7795\n", + "Time taken: 1.0845\n", + "Function value obtained: -416.9777\n", + "Current minimum: -429.7038\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2913\n", - "Function value obtained: -249.4727\n", - "Current minimum: -249.4727\n", + "Time taken: 1.0639\n", + "Function value obtained: -418.7107\n", + "Current minimum: -429.7038\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1837\n", - "Function value obtained: -255.9701\n", - "Current minimum: -255.9701\n", + "Time taken: 1.0806\n", + "Function value obtained: -423.0774\n", + "Current minimum: -429.7038\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1286\n", - "Function value obtained: -239.7620\n", - "Current minimum: -255.9701\n", + "Time taken: 1.0506\n", + "Function value obtained: -411.4311\n", + "Current minimum: -429.7038\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1826\n", - "Function value obtained: -241.4610\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1297\n", + "Function value obtained: -430.1984\n", + "Current minimum: -430.1984\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1768\n", - "Function value obtained: -3.0542\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1152\n", + "Function value obtained: -426.8712\n", + "Current minimum: -430.1984\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1074\n", - "Function value obtained: -240.5148\n", - "Current minimum: -255.9701\n", + "Time taken: 1.0828\n", + "Function value obtained: -422.6701\n", + "Current minimum: -430.1984\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1506\n", - "Function value obtained: -175.6737\n", - "Current minimum: -255.9701\n", + "Time taken: 1.0951\n", + "Function value obtained: -434.4590\n", + "Current minimum: -434.4590\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2762\n", - "Function value obtained: -242.4093\n", - "Current minimum: -255.9701\n", + "Time taken: 0.9898\n", + "Function value obtained: -380.1998\n", + "Current minimum: -434.4590\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2277\n", - "Function value obtained: -239.8314\n", - "Current minimum: -255.9701\n", + "Time taken: 1.0739\n", + "Function value obtained: -418.1824\n", + "Current minimum: -434.4590\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1895\n", - "Function value obtained: -12.8741\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1644\n", + "Function value obtained: -417.3401\n", + "Current minimum: -434.4590\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1584\n", - "Function value obtained: -246.0282\n", - "Current minimum: -255.9701\n", + "Time taken: 1.3077\n", + "Function value obtained: -408.3845\n", + "Current minimum: -434.4590\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2231\n", - "Function value obtained: -252.3802\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1248\n", + "Function value obtained: -425.7940\n", + "Current minimum: -434.4590\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1898\n", - "Function value obtained: -244.2205\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1439\n", + "Function value obtained: -435.2489\n", + "Current minimum: -435.2489\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2412\n", - "Function value obtained: -245.0308\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1030\n", + "Function value obtained: -425.5306\n", + "Current minimum: -435.2489\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2361\n", - "Function value obtained: -240.3855\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1023\n", + "Function value obtained: -412.2225\n", + "Current minimum: -435.2489\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2539\n", - "Function value obtained: -248.9827\n", - "Current minimum: -255.9701\n", + "Time taken: 1.0874\n", + "Function value obtained: -419.7807\n", + "Current minimum: -435.2489\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2386\n", - "Function value obtained: -243.1192\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1151\n", + "Function value obtained: -424.9055\n", + "Current minimum: -435.2489\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2474\n", - "Function value obtained: -241.5725\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1586\n", + "Function value obtained: -424.1673\n", + "Current minimum: -435.2489\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2848\n", - "Function value obtained: -247.1950\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1460\n", + "Function value obtained: -8.2247\n", + "Current minimum: -435.2489\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3895\n", - "Function value obtained: -247.4009\n", - "Current minimum: -255.9701\n", + "Time taken: 1.2315\n", + "Function value obtained: -415.1648\n", + "Current minimum: -435.2489\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2803\n", - "Function value obtained: -250.5159\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1781\n", + "Function value obtained: -405.1189\n", + "Current minimum: -435.2489\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2237\n", - "Function value obtained: -251.7577\n", - "Current minimum: -255.9701\n", + "Time taken: 1.2721\n", + "Function value obtained: -418.6292\n", + "Current minimum: -435.2489\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2773\n", - "Function value obtained: -242.7973\n", - "Current minimum: -255.9701\n", + "Time taken: 1.2206\n", + "Function value obtained: -424.6042\n", + "Current minimum: -435.2489\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2824\n", - "Function value obtained: -250.8797\n", - "Current minimum: -255.9701\n", + "Time taken: 1.2746\n", + "Function value obtained: -432.5434\n", + "Current minimum: -435.2489\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2094\n", - "Function value obtained: -252.1934\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1960\n", + "Function value obtained: -430.1637\n", + "Current minimum: -435.2489\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3456\n", - "Function value obtained: -241.3902\n", - "Current minimum: -255.9701\n", + "Time taken: 1.1901\n", + "Function value obtained: -431.3944\n", + "Current minimum: -435.2489\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3082\n", - "Function value obtained: -239.3630\n", - "Current minimum: -255.9701\n", + "Time taken: 1.2000\n", + "Function value obtained: -426.7682\n", + "Current minimum: -435.2489\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3090\n", - "Function value obtained: -248.1995\n", - "Current minimum: -255.9701\n", + "Time taken: 1.0900\n", + "Function value obtained: -424.9954\n", + "Current minimum: -435.2489\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3575\n", - "Function value obtained: -243.1287\n", - "Current minimum: -255.9701\n", - "CPU times: user 1min 52s, sys: 11min 32s, total: 13min 24s\n", - "Wall time: 1min 12s\n" + "Time taken: 1.2593\n", + "Function value obtained: -428.2801\n", + "Current minimum: -435.2489\n", + "CPU times: user 1min 47s, sys: 11min 4s, total: 12min 51s\n", + "Wall time: 1min 8s\n" ] }, { "data": { "text/plain": [ - "(-255.9700683041442, [0.02342418282318141])" + "(-435.2489318270209, [0.06034835458305745])" ] }, - "execution_count": 26, + "execution_count": 85, "metadata": {}, "output_type": "execute_result" } @@ -517,9 +555,15 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 86, "id": "6563ba01-9664-4dbc-9594-c4439d22023a", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -527,13 +571,13 @@ "" ] }, - "execution_count": 31, + "execution_count": 86, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -548,9 +592,15 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 87, "id": "a10c7628-c47a-4622-8f45-440bcca00901", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -558,13 +608,13 @@ "" ] }, - "execution_count": 32, + "execution_count": 87, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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"text/plain": [ "
" ] @@ -579,9 +629,13 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 88, "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -591,265 +645,265 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.9771\n", - "Function value obtained: -26.3370\n", - "Current minimum: -26.3370\n", + "Time taken: 0.8035\n", + "Function value obtained: -221.2843\n", + "Current minimum: -221.2843\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.9244\n", - "Function value obtained: -91.3720\n", - "Current minimum: -91.3720\n", + "Time taken: 0.8925\n", + "Function value obtained: -10.2133\n", + "Current minimum: -221.2843\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.9164\n", - "Function value obtained: -4.1192\n", - "Current minimum: -91.3720\n", + "Time taken: 0.8206\n", + "Function value obtained: -415.1535\n", + "Current minimum: -415.1535\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.9492\n", - "Function value obtained: -144.8091\n", - "Current minimum: -144.8091\n", + "Time taken: 0.7985\n", + "Function value obtained: -8.6206\n", + "Current minimum: -415.1535\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.9418\n", - "Function value obtained: -5.0079\n", - "Current minimum: -144.8091\n", + "Time taken: 0.7964\n", + "Function value obtained: -8.1362\n", + "Current minimum: -415.1535\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.9620\n", - "Function value obtained: -239.1690\n", - "Current minimum: -239.1690\n", + "Time taken: 0.7841\n", + "Function value obtained: -9.7457\n", + "Current minimum: -415.1535\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.9639\n", - "Function value obtained: -3.4427\n", - "Current minimum: -239.1690\n", + "Time taken: 0.8345\n", + "Function value obtained: -163.5276\n", + "Current minimum: -415.1535\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.9970\n", - "Function value obtained: -5.2620\n", - "Current minimum: -239.1690\n", + "Time taken: 0.7647\n", + "Function value obtained: -255.7494\n", + "Current minimum: -415.1535\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.9451\n", - "Function value obtained: -4.6567\n", - "Current minimum: -239.1690\n", + "Time taken: 0.7774\n", + "Function value obtained: -368.6215\n", + "Current minimum: -415.1535\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.1872\n", - "Function value obtained: -3.4642\n", - "Current minimum: -239.1690\n", + "Time taken: 1.0549\n", + "Function value obtained: -14.2423\n", + "Current minimum: -415.1535\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1129\n", - "Function value obtained: -189.9888\n", - "Current minimum: -239.1690\n", + "Time taken: 0.9360\n", + "Function value obtained: -424.3514\n", + "Current minimum: -424.3514\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2358\n", - "Function value obtained: -249.3925\n", - "Current minimum: -249.3925\n", + "Time taken: 0.9955\n", + "Function value obtained: -423.4653\n", + "Current minimum: -424.3514\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2038\n", - "Function value obtained: -246.7732\n", - "Current minimum: -249.3925\n", + "Time taken: 1.0607\n", + "Function value obtained: -416.7628\n", + "Current minimum: -424.3514\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1527\n", - "Function value obtained: -244.8790\n", - "Current minimum: -249.3925\n", + "Time taken: 1.0108\n", + "Function value obtained: -422.3483\n", + "Current minimum: -424.3514\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1352\n", - "Function value obtained: -246.6691\n", - "Current minimum: -249.3925\n", + "Time taken: 0.9800\n", + "Function value obtained: -419.6802\n", + "Current minimum: -424.3514\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1069\n", - "Function value obtained: -251.1293\n", - "Current minimum: -251.1293\n", + "Time taken: 1.0304\n", + "Function value obtained: -424.7456\n", + "Current minimum: -424.7456\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0869\n", - "Function value obtained: -239.0236\n", - "Current minimum: -251.1293\n", + "Time taken: 1.1265\n", + "Function value obtained: -421.1680\n", + "Current minimum: -424.7456\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0756\n", - "Function value obtained: -255.6125\n", - "Current minimum: -255.6125\n", + "Time taken: 0.9452\n", + "Function value obtained: -435.0719\n", + "Current minimum: -435.0719\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1644\n", - "Function value obtained: -245.1025\n", - "Current minimum: -255.6125\n", + "Time taken: 1.3339\n", + "Function value obtained: -417.6995\n", + "Current minimum: -435.0719\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1044\n", - "Function value obtained: -243.8743\n", - "Current minimum: -255.6125\n", + "Time taken: 0.9722\n", + "Function value obtained: -423.1987\n", + "Current minimum: -435.0719\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1368\n", - "Function value obtained: -245.2926\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0860\n", + "Function value obtained: -421.4179\n", + "Current minimum: -435.0719\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1712\n", - "Function value obtained: -168.8751\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0215\n", + "Function value obtained: -412.4332\n", + "Current minimum: -435.0719\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1538\n", - "Function value obtained: -246.9532\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0904\n", + "Function value obtained: -423.9834\n", + "Current minimum: -435.0719\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2467\n", - "Function value obtained: -244.0198\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0610\n", + "Function value obtained: -415.0636\n", + "Current minimum: -435.0719\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1267\n", - "Function value obtained: -247.0916\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0096\n", + "Function value obtained: -416.8264\n", + "Current minimum: -435.0719\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2093\n", - "Function value obtained: -239.9214\n", - "Current minimum: -255.6125\n", + "Time taken: 0.9887\n", + "Function value obtained: -409.5035\n", + "Current minimum: -435.0719\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1178\n", - "Function value obtained: -244.0956\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0241\n", + "Function value obtained: -265.4770\n", + "Current minimum: -435.0719\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1884\n", - "Function value obtained: -247.1154\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0953\n", + "Function value obtained: -197.1016\n", + "Current minimum: -435.0719\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2091\n", - "Function value obtained: -248.9217\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0468\n", + "Function value obtained: -384.7105\n", + "Current minimum: -435.0719\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1379\n", - "Function value obtained: -241.1653\n", - "Current minimum: -255.6125\n", + "Time taken: 0.9983\n", + "Function value obtained: -426.8065\n", + "Current minimum: -435.0719\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1090\n", - "Function value obtained: -28.3147\n", - "Current minimum: -255.6125\n", + "Time taken: 1.1073\n", + "Function value obtained: -418.9250\n", + "Current minimum: -435.0719\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0924\n", - "Function value obtained: -79.6383\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0422\n", + "Function value obtained: -425.7556\n", + "Current minimum: -435.0719\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1303\n", - "Function value obtained: -30.9982\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0887\n", + "Function value obtained: -71.5326\n", + "Current minimum: -435.0719\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2369\n", - "Function value obtained: -240.4885\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0324\n", + "Function value obtained: -61.4797\n", + "Current minimum: -435.0719\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2260\n", - "Function value obtained: -247.4966\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0843\n", + "Function value obtained: -407.8623\n", + "Current minimum: -435.0719\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1080\n", - "Function value obtained: -242.3285\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0719\n", + "Function value obtained: -424.6370\n", + "Current minimum: -435.0719\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1507\n", - "Function value obtained: -26.6754\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0527\n", + "Function value obtained: -420.0040\n", + "Current minimum: -435.0719\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1205\n", - "Function value obtained: -248.9659\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0574\n", + "Function value obtained: -422.4029\n", + "Current minimum: -435.0719\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1671\n", - "Function value obtained: -245.3836\n", - "Current minimum: -255.6125\n", + "Time taken: 1.1347\n", + "Function value obtained: -413.4915\n", + "Current minimum: -435.0719\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1508\n", - "Function value obtained: -245.2714\n", - "Current minimum: -255.6125\n", + "Time taken: 1.2443\n", + "Function value obtained: -409.1322\n", + "Current minimum: -435.0719\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2429\n", - "Function value obtained: -250.2411\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0059\n", + "Function value obtained: -416.9569\n", + "Current minimum: -435.0719\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1812\n", - "Function value obtained: -246.8306\n", - "Current minimum: -255.6125\n", + "Time taken: 0.9965\n", + "Function value obtained: -422.5781\n", + "Current minimum: -435.0719\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1512\n", - "Function value obtained: -249.8087\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0657\n", + "Function value obtained: -418.6904\n", + "Current minimum: -435.0719\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1647\n", - "Function value obtained: -251.4381\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0396\n", + "Function value obtained: -52.1393\n", + "Current minimum: -435.0719\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1128\n", - "Function value obtained: -241.3467\n", - "Current minimum: -255.6125\n", + "Time taken: 1.1144\n", + "Function value obtained: -416.3284\n", + "Current minimum: -435.0719\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3361\n", - "Function value obtained: -248.4483\n", - "Current minimum: -255.6125\n", + "Time taken: 1.1051\n", + "Function value obtained: -415.8117\n", + "Current minimum: -435.0719\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1575\n", - "Function value obtained: -255.1910\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0517\n", + "Function value obtained: -419.7361\n", + "Current minimum: -435.0719\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1234\n", - "Function value obtained: -242.8394\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0421\n", + "Function value obtained: -415.4998\n", + "Current minimum: -435.0719\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1373\n", - "Function value obtained: -246.2295\n", - "Current minimum: -255.6125\n", + "Time taken: 1.0357\n", + "Function value obtained: -426.0757\n", + "Current minimum: -435.0719\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1679\n", - "Function value obtained: -248.5894\n", - "Current minimum: -255.6125\n", - "CPU times: user 17 s, sys: 4.8 s, total: 21.8 s\n", - "Wall time: 56.1 s\n" + "Time taken: 1.0421\n", + "Function value obtained: -426.8498\n", + "Current minimum: -435.0719\n", + "CPU times: user 18.3 s, sys: 4.25 s, total: 22.5 s\n", + "Wall time: 50.6 s\n" ] }, { "data": { "text/plain": [ - "(-255.61248660708233, [0.02511500817922824])" + "(-435.07193758413604, [0.0473505166744664])" ] }, - "execution_count": 33, + "execution_count": 88, "metadata": {}, "output_type": "execute_result" } @@ -862,9 +916,15 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 89, "id": "73d6974e-8d14-419d-a43d-ef0cd09659f8", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -872,13 +932,13 @@ "" ] }, - "execution_count": 34, + "execution_count": 89, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -893,9 +953,15 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 90, "id": "5f305f10-8363-46eb-bb96-484f17f04f21", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -903,13 +969,13 @@ "" ] }, - "execution_count": 35, + "execution_count": 90, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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q3PnMAsccPXFGm7b/bGVpAABUWISkMuDEr+fK5LUAAKjICEllQFRklTJ5LQAAKjJCUhmQ1LS2YqKqFjgm5oqqhY6pERWupKa1rSwNAIAKi5BUBgQHB2nogJsKHDN04E2Fjhky4EaatgEAsAh/o5YRKW0b6cURPfKtFtWICteLI3oopW0j15iIqmGXHQMAAKzBFgBlSErbRupwXcMCd9NOadtIOTlGY6Z+KknqeXNLDRvUhRUkAAAsRkgqY4KDg3RNYp0Cx4SG/vbHFhMVTkACAMAH+Ns1ADnsv4WkjMysUqwEAIDyi5AUgByO30KSMyu7FCsBAKD8IiQFIIc92PV9JitJAAD4BCEpALmFJCcrSQAA+AIhKQDl7UlyEpIAAPAJQlIAytuTlOHkdhsAAL5ASApA9CQBAOB7hKQAlPd2Gz1JAAD4BiEpAOVdSaInCQAA3yAkBaDg4CAFBdkkSZn0JAEA4BOEpABks9lcq0n0JAEA4BuEpABl//++pAxutwEA4BOEpACVu5Lk5HYbAAA+QUgKULmfcOPTbQAA+AYhKUC5epJYSQIAwCcISQEqd9ftzExWkgAA8AVCUoBy9SRlZcsYU8rVAABQ/hCSAhS7bgMA4FuEpABlz/v8NvqSAACwHCEpQIXmWUni0SQAAFiPkBSgHI48K0nsug0AgOUISQGKniQAAHyLkBSg8vYkZdCTBACA5QhJAcpBTxIAAD5FSApQ9CQBAOBbhKQA5QjJuwUAK0kAAFiNkBSgch9LIrFPEgAAvkBIClB8ug0AAN8iJAUoepIAAPAtQlKAcoSwkgQAgC8RkgJU3pUkJz1JAABYjpAUoPL2JGWwkgQAgOUISQHKrSeJlSQAACxHSApQ9rw9SZmsJAEAYLWACkn79u3TwIEDVa9ePVWqVEkNGjTQc889p8zMTLcxNpst39fatWvdrrVgwQI1adJEYWFhatGihT777DN//zolQk8SAAC+FVL4kLJjx44dysnJ0WuvvaaGDRtq69atGjRokM6dO6e//e1vbmO//PJLNW/e3PVzVFSU6/vVq1erT58+mjBhgm6//Xa9//776tWrlzZs2KDExES//T4lEco+SQAA+FRAhaTu3bure/furp/r16+vnTt36tVXX80XkqKiohQXF+fxOtOnT1f37t01YsQISdL48eOVmpqqmTNnatasWb77BSxkt9OTBACALwVUSPLk9OnTuuKKK/Id79Gjhy5evKhGjRpp5MiR6tGjh+vcmjVrNGzYMLfx3bp106JFiy77PhkZGcrIyHD9nJ6eLklyOp1yOp1FqjV3XFHHFyTIZlzfX7xY9BoqGivnHIVjvv2L+fYv5tu/fDXfxbleQIek3bt365VXXnFbRapataqmTp2q9u3bKygoSAsXLlSvXr20aNEiV1A6fPiwYmNj3a4VGxurw4cPX/a9JkyYoHHjxuU7vmTJElWuXLlYdaemphZrvCfp5377Qz7w088B11Plb1bMOYqO+fYv5tu/mG//snq+z58/X+SxZSIkjRo1SpMmTSpwzPbt29WkSRPXz7/88ou6d++u3r17a9CgQa7j0dHRbqtE1113nQ4ePKgpU6a4rSYV1+jRo92um56ervj4eHXt2lURERFFuobT6VRqaqpuvvlm2e12r2uRpFPp5/XawtclSVHRMbr11ltLdL3yyso5R+GYb/9ivv2L+fYvX8137p2goigTIWn48OHq379/gWPq16/v+v7gwYO68cYb1a5dO82ePbvQ67dp08YticbFxenIkSNuY44cOXLZHiZJCg0NVWhoaL7jdru92H943rzm9ypXCnN978zK4V/YQlgx5yg65tu/mG//Yr79y+r5Ls61ykRIiomJUUxMTJHG/vLLL7rxxhvVunVrvfXWWwoKKnwXg7S0NNWsWdP1c3JyspYuXaqhQ4e6jqWmpio5ObnYtZeWvDtuO/l0GwAAlisTIamofvnlF3Xq1EkJCQn629/+pmPHjrnO5a4CzZ07Vw6HQ1dffbUk6aOPPtKcOXP0xhtvuMYOGTJEKSkpmjp1qm677TbNmzdP33//fZFWpcqKkJAg2WySMVIGn24DAMByARWSUlNTtXv3bu3evVu1a9d2O2fMb5/2Gj9+vPbv36+QkBA1adJE8+fP19133+06365dO73//vv685//rD/96U+66qqrtGjRooDZI0mSbDabHPYQZWRmseM2AAA+EFAhqX///oX2LvXr10/9+vUr9Fq9e/dW7969LaqsdNjtwZdCEitJAABYLqAeSwJ3ubtu05MEAID1CEkBLPf5bawkAQBgPUJSAMv9hBs9SQAAWI+QFMByn9/GShIAANYjJAUw10qSM9vt030AAKDkCEkBLLcnSZKcWdxyAwDASoSkAOYI+W0HB/qSAACwFiEpgOVdSaIvCQAAaxGSAlje57dlslcSAACWIiQFMFaSAADwHUJSALPTkwQAgM8QkgJYqNun21hJAgDASoSkAObWk8RKEgAAliIkBTCHnZ4kAAB8hZAUwOx5VpIyWEkCAMBShKQA5qAnCQAAnyEkBTB6kgAA8B1CUgCjJwkAAN8hJAUw95UkQhIAAFYiJAUwtx23s7jdBgCAlQhJAYyeJAAAfIeQFMDoSQIAwHcISQEs70qS08lKEgAAViIkBTC3niRWkgAAsBQhKYA52HEbAACfISQFMDs9SQAA+AwhKYDRkwQAgO8QkgJYKD1JAAD4DCEpgLFPEgAAvkNICmD0JAEA4DuEpABmD8kbklhJAgDASoSkAGaz2eRwXLrlxkoSAADWIiQFOMf/rybRkwQAgLUISQEud9dtVpIAALAWISnA5X7CjX2SAACwFiEpwOWGpAxWkgAAsBQhKcDlbgPAp9sAALAWISnA5fYkOZ1ZMsaUcjUAAJQfhKQAF/r/t9uMkbKyckq5GgAAyg9CUoBzezQJfUkAAFiGkBTgeDQJAAC+QUgKcA47jyYBAMAXCEkBLvexJBK7bgMAYCVCUoBzcLsNAACfICQFOBq3AQDwDUJSgKMnCQAA3yAkBTh6kgAA8A1CUoBjCwAAAHyDkBTg8vYkObndBgCAZbwOSRcuXND58+ddP+/fv18vv/yylixZYklhKJpQVpIAAPAJr0NSz5499c4770iSTp06pTZt2mjq1Knq2bOnXn31VcsKRMHoSQIAwDe8DkkbNmxQx44dJUkffvihYmNjtX//fr3zzjuaMWOGZQWiYPaQ31aSMlhJAgDAMl6HpPPnzys8PFyStGTJEv3hD39QUFCQ2rZtq/3791tWIAqWdyWJniQAAKzjdUhq2LChFi1apJ9++klffPGFunbtKkk6evSoIiIiLCsQBWMzSQAAfMPrkDR27Fg9/fTTqlu3rtq0aaPk5GRJl1aVrr76assKRMFCHXkatzMJSQAAWCWk8CGe3X333erQoYMOHTqkpKQk1/HOnTvrzjvvtKQ4FC5vTxI7bgMAYB2vQ5IkxcXFKS4uzu3Y9ddfX6KCUDxun24jJAEAYJlihaRhw4YVeey0adOKXQyKj54kAAB8o1ghaePGjUUaZ7PZvCoGxedgM0kAAHyiWCFp+fLlvqoDXnILSWwmCQCAZXh2W4BjnyQAAHyDnqQAl7cniR23AQCwDj1JAc5OTxIAAD5BT1KAy9uTxO02AACsQ09SgLPZbK6gxD5JAABYp0SbSUrSDz/8oAMHDigzM9PteI8ePUp6aRSRwx6iTGc2jyUBAMBCXoek//znP7rzzju1ZcsW2Ww2GWMk/daPlJ3Nqoa/2F0rSYQkAACs4vXttiFDhqhevXo6evSoKleurG3btumrr77StddeqxUrVlhYorsePXqoTp06CgsLU82aNdW3b18dPHjQbczmzZvVsWNHhYWFKT4+XpMnT853nQULFqhJkyYKCwtTixYt9Nlnn/msZl/jdhsAANbzOiStWbNGL7zwgqKjoxUUFKSgoCB16NBBEyZM0ODBg62s0c2NN96oDz74QDt37tTChQu1Z88e3X333a7z6enp6tq1qxISErR+/XpNmTJFzz//vGbPnu0as3r1avXp00cDBw7Uxo0b1atXL/Xq1Utbt271Wd2+lLtXEiEJAADreH27LTs7W+Hh4ZKk6OhoHTx4UI0bN1ZCQoJ27txpWYG/99RTT7m+T0hI0KhRo9SrVy85nU7Z7Xa99957yszM1Jw5c+RwONS8eXOlpaVp2rRpevjhhyVJ06dPV/fu3TVixAhJ0vjx45WamqqZM2dq1qxZPqvdVxwh/7+SRE8SAACW8XolKTExUZs2bZIktWnTRpMnT9Y333yjF154QfXr17eswIKcPHlS7733ntq1aye73S7p0grXDTfcIIfD4RrXrVs37dy5U7/++qtrTJcuXdyu1a1bN61Zs8YvdVvtt5WkLFdvGAAAKBmvV5L+/Oc/69y5c5KkF154Qbfffrs6duyoqKgozZ8/37ICPXnmmWc0c+ZMnT9/Xm3bttXixYtd5w4fPqx69eq5jY+NjXWdi4yM1OHDh13H8o45fPjwZd8zIyNDGRkZrp/T09MlSU6nU06ns0h1544r6viisodcyrrGSBcvZigkJLiQV1QcvppzeMZ8+xfz7V/Mt3/5ar6Lcz2vQ1K3bt1c3zds2FA7duzQyZMnFRkZWewdt0eNGqVJkyYVOGb79u1q0qSJJGnEiBEaOHCg9u/fr3HjxumBBx7Q4sWLfbrT94QJEzRu3Lh8x5csWaLKlSsX61qpqalWlSVJOn36lOv7xf/6txx2tr/6PavnHAVjvv2L+fYv5tu/rJ7v8+fPF3ms1yFpwoQJio2N1YABA1zHrrjiCs2ZM0fHjh3TM888U+RrDR8+XP379y9wTN5beNHR0YqOjlajRo3UtGlTxcfHa+3atUpOTlZcXJyOHDni9trcn+Pi4lz/62lM7nlPRo8e7fbsuvT0dMXHx6tr166KiIgo0u/pdDqVmpqqm2++2XV70Apfb/1E+w/tlSR1uvEmVY8oXmgrz3w15/CM+fYv5tu/mG//8tV8594JKgqvQ9Jrr72m999/P9/x5s2b69577y1WSIqJiVFMTIxXdeTk5EiS61ZYcnKynn32WVcjt3QphTZu3FiRkZGuMUuXLtXQoUNd10lNTVVycvJl3yc0NFShoaH5jtvt9mL/4XnzmoKEhv52LaMg/uX1wOo5R8GYb/9ivv2L+fYvq+e7ONfy+r7M4cOHVbNmzXzHY2JidOjQIW8vW6B169Zp5syZSktL0/79+7Vs2TL16dNHDRo0cAWc//qv/5LD4dDAgQO1bds2zZ8/X9OnT3dbBRoyZIg+//xzTZ06VTt27NDzzz+v77//Xk888YRP6va1UPtvWZdPuAEAYA2vQ1J8fLy++eabfMe/+eYb1apVq0RFXU7lypX10UcfqXPnzmrcuLEGDhyoli1bauXKla5VnmrVqmnJkiXau3evWrdureHDh2vs2LGuj/9LUrt27fT+++9r9uzZSkpK0ocffqhFixYpMTHRJ3X7msPxW6M2u24DAGANr2+3DRo0SEOHDpXT6dRNN90kSVq6dKlGjhyp4cOHW1ZgXi1atNCyZcsKHdeyZUutWrWqwDG9e/dW7969rSqtVNnzfJotM5MNJQEAsILXIWnEiBE6ceKE/vu//9v1cNuwsDA988wzGj16tGUFonC5+yRJUmYWIQkAACt4HZJsNpsmTZqkMWPGaPv27apUqZKuuuoqj83N8C0HPUkAAFjO65CUq2rVqrruuuusqAVeyn3ArURPEgAAVmHXwXLALSTRkwQAgCUISeUAPUkAAFiPkFQO0JMEAID1CEnlgJ2eJAAALEdIKgfoSQIAwHpef7rtu+++06hRo3Ts2DE1bNhQrVq1cn3VqVPHyhpRiNA8PUlOepIAALCE1ytJffv2VXBwsB5++GHVq1dPK1eu1IMPPqi6desqKirKyhpRCHqSAACwntcrST/99JP+9a9/qUGDBm7H9+/fr7S0tJLWhWLI25OUQU8SAACW8DokJScn65dffskXkhISEpSQkFDiwlB0eVeSnE5utwEAYAWvb7c99dRTeuGFF3Ty5Ekr64EXHI68n24jJAEAYAWvV5LuuOMO2Ww2NWrUSD179lRycrKuvvpqtWjRQg6Hw8oaUYhQepIAALCc1yFp9+7d2rRpk+vrr3/9q/bt2ye73a7GjRtr8+bNVtaJArBPEgAA1vM6JNWvX1/169fXnXfe6TqWnp6uTZs2EZD8zO3TbdxuAwDAEl6HJE8iIiLUsWNHdezY0crLohDuPUmsJAEAYAV23C4HHCHsuA0AgNUISeWA3e12GytJAABYgZBUDgQF2WT//9Uk9kkCAMAaXoUkp9Opzp07a9euXVbXAy/l9iWxkgQAgDW8Ckl2u51PsJUxuStJGfQkAQBgCa9vt91///168803rawFJeBwXOpLcmYRkgAAsILXWwBkZWVpzpw5+vLLL9W6dWtVqVLF7fy0adNKXByKLnevJHbcBgDAGl6HpK1bt+qaa66RJP34449u52w2W8mqQrGF2ulJAgDASl6HpOXLl1tZB0rI7gpJ3G4DAMAKJdoCYNWqVbr//vvVrl07/fLLL5Kkd999V19//bUlxaHocnuScnKMsrJzSrkaAAACn9chaeHCherWrZsqVaqkDRs2KCMjQ5J0+vRp/fWvf7WsQBSN2/Pb6EsCAKDEvA5Jf/nLXzRr1iy9/vrrstvtruPt27fXhg0bLCkOReew8/w2AACs5HVI2rlzp2644YZ8x6tVq6ZTp06VpCZ4wT0k0ZcEAEBJeR2S4uLitHv37nzHv/76a9WvX79ERaH4cnuSJB5NAgCAFbwOSYMGDdKQIUO0bt062Ww2HTx4UO+9956efvppPfbYY1bWiCLI25OUQU8SAAAl5vUWAKNGjVJOTo46d+6s8+fP64YbblBoaKiefvppPfnkk1bWiCKw05MEAIClvA5JNptNzz77rEaMGKHdu3fr7NmzatasmapWrWplfSiivD1J3G4DAKDkvA5JBw4cUHx8vBwOh5o1a5bvXJ06dUpcHIrObQsAQhIAACXmdU9SvXr1dOzYsXzHT5w4oXr16pWoKBRfqIN9kgAAsJLXIckY4/EZbWfPnlVYWFiJikLx0ZMEAIC1in27bdiwYZIu9SSNGTNGlStXdp3Lzs7WunXr1KpVK8sKRNFwuw0AAGsVOyRt3LhR0qWVpC1btsjhcLjOORwOJSUl6emnn7auQhQJO24DAGCtYoWkzZs368svv1RwcLAefPBBzZgxQ+Hh4b6qDcXgcOtJYiUJAICSKlZP0tVXX62TJ09KklauXKnMzEyfFIXiYyUJAABrFSskVa9eXf/5z38kSfv27VNOTo5PikLx0ZMEAIC1inW77a677lJKSopq1qwpm82ma6+9VsHBwR7H5oYp+AcrSQAAWKtYIWn27Nn6wx/+oN27d2vw4MEaNGgQPUllhNsWAPQkAQBQYsX+dFv37t0lSevXr9eQIUMISWWEW+M2K0kAAJSY148leeuttyRJP/zwgw4cOJCvibtHjx4lqwzFEpqnJ4lntwEAUHJeh6S9e/eqV69e2rJli2w2m4wxkuTahTs7m7+o/YmeJAAArOX1Y0kGDx6sevXq6ejRo6pcubK2bdumr776Stdee61WrFhhYYkoirw9SRn0JAEAUGJeryStWbNGy5YtU3R0tIKCghQUFKQOHTpowoQJGjx4sGtnbvhH3p4kZxYhCQCAkvJ6JSk7O9vVtB0dHa2DBw9KkhISErRz505rqkORue2TlMntNgAASsrrlaTExERt2rRJ9erVU5s2bTR58mQ5HA7Nnj1b9evXt7JGFEEoPUkAAFjK65D05z//WefOnZMkvfDCC7r99tvVsWNHRUVFaf78+ZYViKKxs+M2AACW8jokdevWzfV9w4YNtWPHDp08eVKRkZGuT7jBf4KCbAoJCVJWVg4hCQAAC3jdk+TJFVdcQUAqRbl9SfQkAQBQcpaGJJSu3L2S6EkCAKDkCEnliGslidttAACUGCGpHMldSeKxJAAAlBwhqRzJ3VCS220AAJSc159ukySn06nDhw/r/PnziomJ0RVXXGFVXfBC7qNJaNwGAKDkir2SdObMGb366qtKSUlRRESE6tatq6ZNmyomJkYJCQkaNGiQvvvuO1/UikLk9iRl5xhlZeeUcjUAAAS2YoWkadOmqW7dunrrrbfUpUsXLVq0SGlpafrxxx+1Zs0aPffcc8rKylLXrl3VvXt37dq1y1d1wwNHnl23ndxyAwCgRIp1u+27777TV199pebNm3s8f/3112vAgAGaNWuW3nrrLa1atUpXXXWVJYWicKEO9123K4WVYjEAAAS4YoWkf/zjH67vz5w543rA7e+Fhobq0UcfLVllKDZ7SJ7nt9GXBABAiXj96baOHTvq8OHDVtaCEnI4eH4bAABW8TokXX311WrTpo127NjhdjwtLU233npriQtD8eXtSWIbAAAASsbrkPTWW2+pf//+6tChg77++mv9+OOP+uMf/6jWrVsrODi48AvAcqwkAQBgnRLtkzRu3DiFhobq5ptvVnZ2tjp37qw1a9bo+uuvt6o+FIODniQAACzj9UrSkSNHNGTIEP3lL39Rs2bNZLfb1b9/fwJSKcq7ksSjSQAAKBmvQ1K9evX01VdfacGCBVq/fr0WLlyohx9+WFOmTLGyvnx69OihOnXqKCwsTDVr1lTfvn118OBB1/l9+/bJZrPl+1q7dq3bdRYsWKAmTZooLCxMLVq00GeffebTuv0hb09SBj1JAACUiNchac6cOdq4caNuu+02SVL37t21fPlyvfTSS3r88cctK/D3brzxRn3wwQfauXOnFi5cqD179ujuu+/ON+7LL7/UoUOHXF+tW7d2nVu9erX69OmjgQMHauPGjerVq5d69eqlrVu3+qxuf7C7NW6zkgQAQEl43ZN077335jt2zTXXaPXq1brllltKVFRBnnrqKdf3CQkJGjVqlHr16iWn0ym73e46FxUVpbi4OI/XmD59urp3764RI0ZIksaPH6/U1FTNnDlTs2bN8lntvpb7WBKJniQAAEqqWCHpwIEDqlOnToFj6tatq9WrV0uSfvnlF1155ZXeV1eIkydP6r333lO7du3cApJ06bbcxYsX1ahRI40cOVI9evRwnVuzZo2GDRvmNr5bt25atGjRZd8rIyNDGRkZrp/T09MlXXrIr9PpLFK9ueOKOr64goNtru8vXsz02fsEEl/POdwx3/7FfPsX8+1fvprv4lyvWCHpuuuuU69evfTQQw/puuuu8zjm9OnT+vDDDzV9+nQ9/PDDGjx4cHHeokieeeYZzZw5U+fPn1fbtm21ePFi17mqVatq6tSpat++vYKCgrRw4UL16tVLixYtcgWlw4cPKzY21u2asbGxBW6OOWHCBI0bNy7f8SVLlqhy5crFqj81NbVY44tqx5501/cbNqYp5/w+n7xPIPLVnMMz5tu/mG//Yr79y+r5Pn/+fJHH2owxpqiDT548qRdffFFvvvmmwsLC1Lp1a9WqVUthYWH69ddf9cMPP2jbtm265pprNGbMmCJvKjlq1ChNmjSpwDHbt29XkyZNJEnHjx/XyZMntX//fo0bN07VqlXT4sWLZbPZPL72gQce0N69e7Vq1SpJksPh0Ny5c9WnTx/XmP/5n//RuHHjdOTIEY/X8LSSFB8fr+PHjysiIqJIv6fT6VRqaqpuvvnmfCtfVli2eqfGz/hckvT4Azfo7luvtvw9Ao2v5xzumG//Yr79i/n2L1/Nd3p6uqKjo3X69OlC//4u1krSxIkT9eKLL+ovf/mLPvvsM61atUr79+/XhQsXFB0drfvuu0/dunVTYmJisQoePny4+vfvX+CY+vXru76Pjo5WdHS0GjVqpKZNmyo+Pl5r165VcnKyx9e2adPGLYnGxcXlC0NHjhy5bA+TdOl5dKGhofmO2+32Yv/hefOaoqgU9lt92TmGf4nz8NWcwzPm27+Yb/9ivv3L6vkuzrWKFZJefvllPf3006pRo4Y+/fRT/c///E+xbzV5EhMTo5iYGK9em5OTI0luqzy/l5aWppo1a7p+Tk5O1tKlSzV06FDXsdTU1MuGrEDBjtsAAFinWCGpVq1a2rhxo7p166Z3331XU6ZMsSQkFdW6dev03XffqUOHDoqMjNSePXs0ZswYNWjQwBVw5s6dK4fDoauvvnSr6aOPPtKcOXP0xhtvuK4zZMgQpaSkaOrUqbrttts0b948ff/995o9e7bffhdfcHt2G59uAwCgRIq1T9Lw4cN1xx13qGPHjpKk//3f/9W3336rCxcu+KS436tcubI++ugjde7cWY0bN9bAgQPVsmVLrVy50u1W2Pjx49W6dWu1adNG//znPzV//nw9+OCDrvPt2rXT+++/r9mzZyspKUkffvihFi1aVOzbhGWN2xYArCQBAFAixVpJevLJJ5WSkqJPP/1U33zzjf7+979rxIgRstlsatiwoZKSktSqVSslJSX5ZK+kFi1aaNmyZQWO6devn/r161fotXr37q3evXtbVVqZ4LaSxI7bAACUSLE3k2zZsqVatmypt99+W2vWrFGVKlW0efNmpaWlKS0tTf/85z/14osv6syZM76oFwWgJwkAAOt4veP2rl27XN+3adNGbdq0cf1cjF0FYCF7CD1JAABYxetntxXkcvsVwbdCWUkCAMAyXq8kSdLSpUu1dOlSHT161PVR/Fxz5swpUWEovrw9SU56kgAAKBGvQ9K4ceP0wgsv6Nprr1XNmjVZPSoD6EkCAMA6XoekWbNm6e2331bfvn2trAclQE8SAADW8bonKTMzU+3atbOyFpRQcHCQgoMv/ZFmZrGSBABASXgdkh566CG9//77VtYCC+T2JbGSBABAyXh9u+3ixYuaPXu2vvzyS7Vs2TLfA+OmTZtW4uJQfKGOEF246KQnCQCAEvI6JG3evFmtWrWSJG3dutXtHE3cpSe3L4mVJAAASsbrkLR8+XIr64BFcj/h5qQnCQCAEvHJZpIoPbk9SRmsJAEAUCLFWkkaNmyYxo8frypVqmjYsGEFjqUnqXTkriTRkwQAQMkUKyRt3LhRTqfT9f3l0JNUehz/35OUnZ2j7Owc15YAAACgeIoVkvL2IdGTVDbl3XXbmZVNSAIAwEslenbbxYsXtXnz5nzPbrPZbLrjjjtKXByKL+/z2zIzsxQWai9gNAAAuByvQ9Lnn3+uvn376sSJE/nO2Ww2ZWfTE1Ma7Hae3wYAgBW8vhfz5JNP6o9//KMOHTqknJwcty8CUunJu5LEJ9wAAPCe1yHpyJEjGjZsmGJjY62sByX0+54kAADgHa9D0t13360VK1ZYWAqs8PueJAAA4B2ve5Jmzpyp3r17a9WqVWrRokW+Z7cNHjy4xMWh+Bz0JAEAYAmvQ9I//vEPLVmyRGFhYVqxYoXb3kg2m42QVErcVpKcrCQBAOAtr0PSs88+q3HjxmnUqFEKCmIvnrIib08SK0kAAHjP63STmZmpe+65h4BUxtCTBACANbxOOP369dP8+fOtrAUWoCcJAABreH27LTs7W5MnT9YXX3yhli1b5mvc5gG3pSPvSpKTniQAALzmdUjasmWLrr76aknS1q1b3c7xgNvSk3clKYOVJAAAvOZ1SOIBt2WTnZ4kAAAsQdd1OeP+6TZCEgAA3iIklTPuPUncbgMAwFuEpHImlE+3AQBgCUJSOUNPEgAA1iAklTNuPUlZrCQBAOAtQlI5w47bAABYg5BUzrDjNgAA1iAklTOsJAEAYA1CUjmTtyfJSU8SAABeIySVM3lXkjJYSQIAwGuEpHLGTk8SAACWICSVMyHBQQoOuvSAYR5LAgCA9whJ5VBuXxKPJQEAwHuEpHIodxsAPt0GAID3CEnlUO6jSehJAgDAe4SkcsjhCkmsJAEA4C1CUjnkut3GShIAAF4jJJVDuY3brCQBAOA9QlI5lHu7LSsrRzk5ppSrAQAgMBGSyqG8u247WU0CAMArhKRyyJFn1+0M+pIAAPAKIakcyvuQW/qSAADwDiGpHLKH/Ha7jQ0lAQDwDiGpHAp15O1J4nYbAADeICSVQ3l7ktgrCQAA7xCSyiF7nk+3ZdCTBACAVwhJ5ZDbShI9SQAAeIWQVA456EkCAKDECEnlED1JAACUHCGpHMq74zb7JAEA4B1CUjnEShIAACVHSCqH8vYk0bgNAIB3CEnlECtJAACUHCGpHKInCQCAkiMklUN5V5LYAgAAAO8Qksohh+O3kJRBTxIAAF4hJJVDdm63AQBQYoSkcsi9J4nbbQAAeIOQVA7RkwQAQMkRksqhUEfeLQC43QYAgDcCNiRlZGSoVatWstlsSktLczu3efNmdezYUWFhYYqPj9fkyZPzvX7BggVq0qSJwsLC1KJFC3322Wd+qtz33HqSaNwGAMArARuSRo4cqVq1auU7np6erq5duyohIUHr16/XlClT9Pzzz2v27NmuMatXr1afPn00cOBAbdy4Ub169VKvXr20detWf/4KPkNPEgAAJReQIenf//63lixZor/97W/5zr333nvKzMzUnDlz1Lx5c917770aPHiwpk2b5hozffp0de/eXSNGjFDTpk01fvx4XXPNNZo5c6Y/fw2fYcdtAABKLqTwIWXLkSNHNGjQIC1atEiVK1fOd37NmjW64YYb5HA4XMe6deumSZMm6ddff1VkZKTWrFmjYcOGub2uW7duWrRo0WXfNyMjQxkZGa6f09PTJUlOp1NOp7NIteeOK+p4bwXZjOv7jIyi11ce+WvOcQnz7V/Mt38x3/7lq/kuzvUCKiQZY9S/f389+uijuvbaa7Vv3758Yw4fPqx69eq5HYuNjXWdi4yM1OHDh13H8o45fPjwZd97woQJGjduXL7jS5Ys8RjWCpKamlqs8d6w2SRjpGPHT5Srfitv+WPO8Rvm27+Yb/9ivv3L6vk+f/58kceWiZA0atQoTZo0qcAx27dv15IlS3TmzBmNHj3aT5X9ZvTo0W6rT+np6YqPj1fXrl0VERFRpGs4nU6lpqbq5ptvlt1u91WpkqRX5v9dFzOyVLlKVd16660+fa+yzJ9zDubb35hv/2K+/ctX8517J6goykRIGj58uPr371/gmPr162vZsmVas2aNQkND3c5de+21uu+++zR37lzFxcXpyJEjbudzf46Li3P9r6cxuec9CQ0Nzfe+kmS324v9h+fNa4rLYQ/RxYwsZTpz+JdZ/plz/Ib59i/m27+Yb/+yer6Lc60yEZJiYmIUExNT6LgZM2boL3/5i+vngwcPqlu3bpo/f77atGkjSUpOTtazzz4rp9PpmojU1FQ1btxYkZGRrjFLly7V0KFDXddKTU1VcnKyhb9V6cp9fhv7JAEA4J0yEZKKqk6dOm4/V61aVZLUoEED1a5dW5L0X//1Xxo3bpwGDhyoZ555Rlu3btX06dP10ksvuV43ZMgQpaSkaOrUqbrttts0b948ff/9927bBAQ6e8ilbQDYJwkAAO8E5BYABalWrZqWLFmivXv3qnXr1ho+fLjGjh2rhx9+2DWmXbt2ev/99zV79mwlJSXpww8/1KJFi5SYmFiKlVsr1HEpJDmz2AIAAABvBNRK0u/VrVtXxph8x1u2bKlVq1YV+NrevXurd+/eviqt1OXulZSZSUgCAMAb5W4lCZfkPprEmZWtnJz8QRIAABSMkFRO5d1120nzNgAAxUZIKqccjjzPb6MvCQCAYiMklVNuz2+jLwkAgGIjJJVTDnuelSRutwEAUGyEpHLKvSeJlSQAAIqLkFRO5e64LUkZrCQBAFBshKRyyu12Gz1JAAAUGyGpnLLTkwQAQIkQksqpUHqSAAAoEUJSOZW3J4mVJAAAio+QVE7ZQ3673ZaRSUgCAKC4AvoBt7i8kJDf8u+uvUfVqW0jBQe7Z+Ls7Bxt2v6zTvx6TlGRVZTUtHa+MUUdV9bG5I5L2/aztu89o1rbftY1LRI8jgMAwBNCUjm0cu2PenPeN66f//fjb/XFVz9o6ICblNK2kWvMy3OW6diJs65xMVFV3cYUdVxZG+Np3OJVCz2OAwDgcvi/1eXMyrU/6tkpn+jMuQy348dOnNWzUz7RyrU/usbkDRq/H5P3WgWNK2tjilo3AACFYSWpHMnOztHLc5YVOOa5aZ9KNluBY55/abGuqldDP+49WuJr+XNMUeuePme5OlzXkFtvAIAC8bdEObJp+8/5Vk9+LyvbKCsrp8Axzqwc/bDrcKHjinItf44pat1HT5zRpu0/FzgGAABCUjly4tdzpV1CwGCuAACFISSVI1GRVSy71hP9Oll2LX8qat1WzhUAoHwiJJUjSU1rKyaqaoFjYq6oWuiYGlHh+sMtrSy5lj/HFLXuGlHhSmpau8AxAAAQksqR4OAgDR1wU4Fjhg68qdAxQwbcKIc9xJJr+XNMUeseMuBGmrYBAIXib4pyJqVtI704oke+1ZQaUeF6cUQPpbRtVKQxVl7Ln2MKqjtXWKi9oCkEAEASWwCUSyltG6nDdQ0L3JW6KGOsvJY/x+Qdt2HLfi1d8Y0qV6ulDxZvkCT9bXaq3nmpvyqFOayZcABAuURIKqeCg4N0TWKdEo+x8lr+HJM7rlXz2jq4P1y33NJBu/Ye08ZtP+nQ0XS9OX91wDanAwD8g9ttqBBsNptGPtpVDvulB/9+sHi9duw5XMpVAQDKMkISKoz4WpHq3ztZkpSTYzT51SXKyi5440kAQMXF7TZUKP/V8zot/XqH9hw4rh/3HtW8f36nZo1qFtjflJ2dU2gPlFVjijMOAOBbhCRUKCEhwRr5WDc9+qf3ZIw0671Vbudjoqpq6ICbXJ+UW7n2R708Z5nb4158NaY446wMZQAAzwhJqHCaN6qptlfX05oNe/OdO3birJ6d8oleHNFDkvTslE/8MialbSOtXPtjkcdZFcoAAJdHSEKFk52do137jhU4ZtKrSwq9jlVjJs9KVVa20dTXUwscN33OcuXkGI2Z+mm+c96EMgBAwQhJqHA2bf9Zx0+eLXBM+tmLhV7HqjGnz1zQc9PyB5/fO3rijMYWMu75lxbLZrMVOGb6nOXqcF1Dbr0BQCH4ryQqnBO/nivtErxmTMHnnVk5ynRmFzjm6Ikz2rT9ZwurAoDyiZCECicqskppl5BPu9b1/fp+gRwUAcBfCEmocJKa1r7sc91yxVxR1W9jakSF6y8FPGsuV/WISgWeL46yGBQBoKwhJKHCCQ4O0tABNxU4ZujAm/w2ZsiAG+WwhxQ6bvigLpaFsqSmtQscAwAgJKGCSmnbSC96WL2pERXu+vSXP8cUpaYb2zW2LJTRtA0AhePTbaiwUto2UofrGha44aI/xxRlXG6Q+v0eSDWiwjVkwI2uwOVpTK7wKmHWTCAAlHOEJFRowcFBuiaxTpkZU5Rx3oSyPfuO6n8XfSdJmvH2cr05uS+rSQBQCEISEICKG8o6t2+i77Yc0M49R7R73zF9tnyr7ujS0h+lAkDA4v9KAhVAUJBNg/vf6Pr59X98rfMXMkuxIgAo+whJQAWR1Ky2OrW9SpJ08tR5vfvRulKuCADKNkISUIE81jdF9pBgSdL8T7/XoaOnS7kiACi7CElABXJlXHX1vv0aSVKmM1uz/verUq4IAMouGreBCqbfXW312bKtOpV+QUu/2amWTa5URHily25LkJ2dU+jWBbnj0rb9rO17z6jWtp91TYsEr67lzzFlsSbmu+yNYb7L5nz7AyEJqGCqVA7VQ3066G+vpUqSXnpzmetcTFRVDR1wk2u/pZVrf8y339Lvx3gat3jVQq+u5c8xZbEm5rvsjWG+S79uT/PtLzZjCnuuODxJT09XtWrVdPr0aUVERBTpNU6nU5999pluvfVW2e12H1cIiTm/nGWrd2rs1E8ve/7FET0kSc9O+aTAMSltG2nl2h8LHVeUa/lzDHVTN3UHbt0lDUrF+fubkOQlQlJgYM7zy87O0d2Pzfa4G3euypUcstmkc+cvv01Alcqh6tPjWv3jk+8KHFeUa/lzDHVTN3UHbt01osK14NVBJbr1RkjyA0JSYGDO89uw9YAGP/dBaZcBAF6ZMe6PRXp6weUU5+9vPt0GVDAnfj1X2iUAgNf8+d8wQhJQwURFVrHsWrfemGjZtfyJuv2Luv2rvNdt5X/DCkNIAiqYpKa1FRNVtcAxMVdULXRMjahwPf1IF0uu5c8x1E3d1B24ddeICldS09oFjrESIQmoYIKDgzR0wE0Fjhk68KZCxwwZcKMc9hBLruXPMdRN3dQduHUPGXCjX/dLonHbSzRuBwbm/PI87VlSIypcQwbcWOC+Jr8fY+W1/DmmLNZE3WVvTFmsibpLhk+3+QEhKTAw5wWzeofcDVv2a+mKb9S5U3t2JPZD3cw3812R59tbhCQ/ICQFBubcv5hv/2K+/Yv59i9fzTdbAAAAAJQQIQkAAMADQhIAAIAHhCQAAAAPCEkAAAAeEJIAAAA8ICQBAAB4QEgCAADwgJAEAADgQUhpFxCocjcqT09PL/JrnE6nzp8/r/T0dHZr9RPm3L+Yb/9ivv2L+fYvX8137t/bRXngCCHJS2fOnJEkxcfHl3IlAACguM6cOaNq1aoVOIZnt3kpJydHBw8eVHh4uGw2W5Fek56ervj4eP30009Fft4bSoY59y/m27+Yb/9ivv3LV/NtjNGZM2dUq1YtBQUV3HXESpKXgoKCVLt2ba9eGxERwb9gfsac+xfz7V/Mt38x3/7li/kubAUpF43bAAAAHhCSAAAAPCAk+VFoaKiee+45hYaGlnYpFQZz7l/Mt38x3/7FfPtXWZhvGrcBAAA8YCUJAADAA0ISAACAB4QkAAAADwhJAAAAHhCS/Ojvf/+76tatq7CwMLVp00bffvttaZdULnz11Ve64447VKtWLdlsNi1atMjtvDFGY8eOVc2aNVWpUiV16dJFu3btKp1iy4EJEybouuuuU3h4uGrUqKFevXpp586dbmMuXryoxx9/XFFRUapataruuusuHTlypJQqDmyvvvqqWrZs6dpQLzk5Wf/+979d55lr35o4caJsNpuGDh3qOsacW+f555+XzWZz+2rSpInrfGnPNSHJT+bPn69hw4bpueee04YNG5SUlKRu3brp6NGjpV1awDt37pySkpL097//3eP5yZMna8aMGZo1a5bWrVunKlWqqFu3brp48aKfKy0fVq5cqccff1xr165VamqqnE6nunbtqnPnzrnGPPXUU/r000+1YMECrVy5UgcPHtQf/vCHUqw6cNWuXVsTJ07U+vXr9f333+umm25Sz549tW3bNknMtS999913eu2119SyZUu348y5tZo3b65Dhw65vr7++mvXuVKfawO/uP76683jjz/u+jk7O9vUqlXLTJgwoRSrKn8kmY8//tj1c05OjomLizNTpkxxHTt16pQJDQ01//jHP0qhwvLn6NGjRpJZuXKlMebS/NrtdrNgwQLXmO3btxtJZs2aNaVVZrkSGRlp3njjDebah86cOWOuuuoqk5qaalJSUsyQIUOMMfzzbbXnnnvOJCUleTxXFuaalSQ/yMzM1Pr169WlSxfXsaCgIHXp0kVr1qwpxcrKv7179+rw4cNuc1+tWjW1adOGubfI6dOnJUlXXHGFJGn9+vVyOp1uc96kSRPVqVOHOS+h7OxszZs3T+fOnVNycjJz7UOPP/64brvtNre5lfjn2xd27dqlWrVqqX79+rrvvvt04MABSWVjrnnArR8cP35c2dnZio2NdTseGxurHTt2lFJVFcPhw4clyePc556D93JycjR06FC1b99eiYmJki7NucPhUPXq1d3GMufe27Jli5KTk3Xx4kVVrVpVH3/8sZo1a6a0tDTm2gfmzZunDRs26Lvvvst3jn++rdWmTRu9/fbbaty4sQ4dOqRx48apY8eO2rp1a5mYa0ISAK89/vjj2rp1q1sPAazXuHFjpaWl6fTp0/rwww/Vr18/rVy5srTLKpd++uknDRkyRKmpqQoLCyvtcsq9W265xfV9y5Yt1aZNGyUkJOiDDz5QpUqVSrGyS7jd5gfR0dEKDg7O15F/5MgRxcXFlVJVFUPu/DL31nviiSe0ePFiLV++XLVr13Ydj4uLU2Zmpk6dOuU2njn3nsPhUMOGDdW6dWtNmDBBSUlJmj59OnPtA+vXr9fRo0d1zTXXKCQkRCEhIVq5cqVmzJihkJAQxcbGMuc+VL16dTVq1Ei7d+8uE/98E5L8wOFwqHXr1lq6dKnrWE5OjpYuXark5ORSrKz8q1evnuLi4tzmPj09XevWrWPuvWSM0RNPPKGPP/5Yy5YtU7169dzOt27dWna73W3Od+7cqQMHDjDnFsnJyVFGRgZz7QOdO3fWli1blJaW5vq69tprdd9997m+Z8595+zZs9qzZ49q1qxZNv759kt7OMy8efNMaGioefvtt80PP/xgHn74YVO9enVz+PDh0i4t4J05c8Zs3LjRbNy40Ugy06ZNMxs3bjT79+83xhgzceJEU716dfPPf/7TbN682fTs2dPUq1fPXLhwoZQrD0yPPfaYqVatmlmxYoU5dOiQ6+v8+fOuMY8++qipU6eOWbZsmfn+++9NcnKySU5OLsWqA9eoUaPMypUrzd69e83mzZvNqFGjjM1mM0uWLDHGMNf+kPfTbcYw51YaPny4WbFihdm7d6/55ptvTJcuXUx0dLQ5evSoMab055qQ5EevvPKKqVOnjnE4HOb66683a9euLe2SyoXly5cbSfm++vXrZ4y5tA3AmDFjTGxsrAkNDTWdO3c2O3fuLN2iA5inuZZk3nrrLdeYCxcumP/+7/82kZGRpnLlyubOO+80hw4dKr2iA9iAAQNMQkKCcTgcJiYmxnTu3NkVkIxhrv3h9yGJObfOPffcY2rWrGkcDoe58sorzT333GN2797tOl/ac20zxhj/rFkBAAAEDnqSAAAAPCAkAQAAeEBIAgAA8ICQBAAA4AEhCQAAwANCEgAAgAeEJAAAAA8ISQAAAB4QkgAEjE6dOmno0KGlXYaLMUYPP/ywrrjiCtlsNqWlpfnkffL+3mVtDoDyjJAEoMj69+8vm82miRMnuh1ftGiRbDZbKVVVej7//HO9/fbbWrx4sQ4dOqTExMTSLgmAhQhJAIolLCxMkyZN0q+//lrapVgmMzPTq9flPq28Xbt2iouLU0hIiMWVAShNhCQAxdKlSxfFxcVpwoQJlx1Tt25dvfzyy27HWrVqpeeff971c6dOnfTkk09q6NChioyMVGxsrF5//XWdO3dODz74oMLDw9WwYUP9+9//drtOVlaWnnjiCVWrVk3R0dEaM2aM8j6CMicnRxMmTFC9evVUqVIlJSUl6cMPP3S7RqdOnfTEE09o6NChio6OVrdu3Tz+HhkZGRo8eLBq1KihsLAwdejQQd99952kS6tqTz75pA4cOCCbzaa6det6vEZOTo4mT56shg0bKjQ0VHXq1NGLL77oOv/555+rQ4cOql69uqKionT77bdrz549l53b3/vwww/VokULVapUSVFRUerSpYvOnTt32fF79uyRzWbT4sWL1blzZ1WuXFmNGzfWunXrivyeQEVBSAJQLMHBwfrrX/+qV155RT///HOJrjV37lxFR0fr22+/1ZNPPqnHHntMvXv3Vrt27bRhwwZ17dpVffv21fnz591eExISom+//VbTp0/XtGnT9MYbb7jOT5gwQe+8845mzZqlbdu26amnntL999+vlStX5ntvh8Ohb775RrNmzfJY38iRI7Vw4ULNnTtXGzZsUMOGDdWtWzedPHlS06dP1wsvvKDatWvr0KFDrvD0e6NHj9bEiRM1ZswY/fDDD3r//fcVGxvrOn/u3DkNGzZM33//vZYuXaqgoCDdeeedysnJKXT+Dh06pD59+mjAgAHavn27VqxYoT/84Q8q6LnlmzZtks1m07Rp0zRmzBht2rRJderU0ahRowp9P6DCMQBQRP369TM9e/Y0xhjTtm1bM2DAAGOMMR9//LHJ+5+ThIQE89JLL7m9NikpyTz33HOun1NSUkyHDh1cP2dlZZkqVaqYvn37uo4dOnTISDJr1qxxvaZp06YmJyfHNeaZZ54xTZs2NcYYc/HiRVO5cmWzevVqt/ceOHCg6dOnj9t7X3311QX+rmfPnjV2u9289957rmOZmZmmVq1aZvLkycYYY1566SWTkJBw2Wukp6eb0NBQ8/rrrxf4XnkdO3bMSDJbtmxxq3fIkCH5vl+/fr2RZPbt21fk648dO9ZERkaao0ePuo7NmDHDNG/evMjXACoKVpIAeGXSpEmaO3eutm/f7vU1WrZs6fo+ODhYUVFRatGihetY7orL0aNHXcfatm3r1iSenJysXbt2KTs7W7t379b58+d18803q2rVqq6vd955J98trNatWxdY2549e+R0OtW+fXvXMbvdruuvv77Iv/P27duVkZGhzp07X3bMrl271KdPH9WvX18RERGu23YHDhwo9PpJSUnq3LmzWrRood69e+v1118vtFds06ZN6tmzp2JiYlzH9u7dq4YNGxbpdwIqEkISAK/ccMMN6tatm0aPHp3vXFBQUL5bPk6nM984u93u9rPNZnM7lhuGinLrSZLOnj0rSfrXv/6ltLQ019cPP/yQry+pSpUqRbpmSVSqVKnQMXfccYdOnjyp119/XevWrXP1BhWlmTw4OFipqan697//rWbNmumVV15R48aNtXfv3su+ZtOmTUpOTnY7lpaWplatWhX6fkBFQ0gC4LWJEyfq008/1Zo1a9yOx8TE6NChQ66f09PTC/yLuzh+32C8du1aXXXVVQoODlazZs0UGhqqAwcOqGHDhm5f8fHxxXqfBg0auHqWcjmdTn333Xdq1qxZka5x1VVXqVKlSlq6dKnH8ydOnNDOnTv15z//WZ07d1bTpk2L/alBm82m9u3ba9y4cdq4caMcDoc+/vhjj2NPnz6tffv26eqrr3Y7TkgCPOPzqgC81qJFC913332aMWOG2/GbbrpJb7/9tu644w5Vr15dY8eOVXBwsCXveeDAAQ0bNkyPPPKINmzYoFdeeUVTp06VJIWHh+vpp5/WU089pZycHHXo0EGnT5/WN998o4iICPXr16/I71OlShU99thjGjFihK644grVqVNHkydP1vnz5zVw4MAiXSMsLEzPPPOMRo4cKYfDofbt2+vYsWPatm2bBg4cqMjISEVFRWn27NmqWbOmDhw4UKwG6nXr1mnp0qXq2rWratSooXXr1unYsWNq2rSpx/GbN29WSEiI2y3N/fv369dffyUkAR4QkgCUyAsvvKD58+e7HRs9erT27t2r22+/XdWqVdP48eMtW0l64IEHdOHCBV1//fUKDg7WkCFD9PDDD7vOjx8/XjExMZowYYL+85//qHr16rrmmmv0pz/9qdjvNXHiROXk5Khv3746c+aMrr32Wn3xxReKjIws8jXGjBmjkJAQjR07VgcPHlTNmjX16KOPSrp0W3LevHkaPHiwEhMT1bhxY82YMUOdOnUq0rUjIiL01Vdf6eWXX1Z6eroSEhI0depU3XLLLR7Hb9q0SY0bN1ZYWJjr2MaNG1W9evXLbmEAVGQ28/vGAQAAANCTBAAA4AkhCQAAwANCEgAAgAeEJAAAAA8ISQAAAB4QkgAAADwgJAEAAHhASAIAAPCAkAQAAOABIQkAAMADQhIAAIAHhCQAAAAP/g8XOzzLsFjQOgAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -932,7 +998,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 12, "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", "metadata": { "scrolled": true @@ -944,267 +1010,396 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.0844\n", - "Function value obtained: -26.2461\n", - "Current minimum: -26.2461\n", + "Time taken: 0.9448\n", + "Function value obtained: -61.2205\n", + "Current minimum: -61.2205\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8625\n", - "Function value obtained: -287.0738\n", - "Current minimum: -287.0738\n", + "Time taken: 0.7981\n", + "Function value obtained: -1.3165\n", + "Current minimum: -61.2205\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.9552\n", - "Function value obtained: -257.8897\n", - "Current minimum: -287.0738\n", + "Time taken: 0.7924\n", + "Function value obtained: -0.0000\n", + "Current minimum: -61.2205\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.9146\n", - "Function value obtained: -275.3590\n", - "Current minimum: -287.0738\n", + "Time taken: 0.8847\n", + "Function value obtained: -0.0043\n", + "Current minimum: -61.2205\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8751\n", - "Function value obtained: -147.8621\n", - "Current minimum: -287.0738\n", + "Time taken: 0.8267\n", + "Function value obtained: -116.8023\n", + "Current minimum: -116.8023\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8221\n", - "Function value obtained: -117.3944\n", - "Current minimum: -287.0738\n", + "Time taken: 0.8190\n", + "Function value obtained: -0.0000\n", + "Current minimum: -116.8023\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8502\n", - "Function value obtained: -208.3737\n", - "Current minimum: -287.0738\n", + "Time taken: 0.8277\n", + "Function value obtained: -0.0000\n", + "Current minimum: -116.8023\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8278\n", - "Function value obtained: -23.8751\n", - "Current minimum: -287.0738\n", + "Time taken: 0.8259\n", + "Function value obtained: -0.0000\n", + "Current minimum: -116.8023\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8681\n", - "Function value obtained: -171.0908\n", - "Current minimum: -287.0738\n", + "Time taken: 0.8282\n", + "Function value obtained: -0.0000\n", + "Current minimum: -116.8023\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.0946\n", - "Function value obtained: -123.2161\n", - "Current minimum: -287.0738\n", + "Time taken: 4.7821\n", + "Function value obtained: -0.0000\n", + "Current minimum: -116.8023\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0900\n", - "Function value obtained: -273.5842\n", - "Current minimum: -287.0738\n", + "Time taken: 2.4264\n", + "Function value obtained: -118.2319\n", + "Current minimum: -118.2319\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1399\n", - "Function value obtained: -290.1932\n", - "Current minimum: -290.1932\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", + "Time taken: 2.3306\n", + "Function value obtained: -276.4398\n", + "Current minimum: -276.4398\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.38927630582277944]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1050\n", - "Function value obtained: -272.2383\n", - "Current minimum: -290.1932\n", + "Time taken: 2.3965\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1772\n", - "Function value obtained: -287.2174\n", - "Current minimum: -290.1932\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", + "Time taken: 2.3848\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.18417481589713974]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0851\n", - "Function value obtained: -275.4792\n", - "Current minimum: -290.1932\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", + "Time taken: 2.3431\n", + "Function value obtained: -9.8336\n", + "Current minimum: -276.4398\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.6163259384209202]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1296\n", - "Function value obtained: -291.3676\n", - "Current minimum: -291.3676\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", + "Time taken: 2.3639\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.7620265074972382]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0728\n", - "Function value obtained: -299.6824\n", - "Current minimum: -299.6824\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", + "Time taken: 2.4569\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.7176335045210767]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0646\n", - "Function value obtained: -277.7666\n", - "Current minimum: -299.6824\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", + "Time taken: 1.9941\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.47975524824311866]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9859\n", - "Function value obtained: -280.4648\n", - "Current minimum: -299.6824\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", + "Time taken: 1.1352\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.6610471994826488]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0740\n", - "Function value obtained: -285.2623\n", - "Current minimum: -299.6824\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", + "Time taken: 1.1225\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.5849803799180963]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1533\n", - "Function value obtained: -283.2448\n", - "Current minimum: -299.6824\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", + "Time taken: 1.2836\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.39568235674564767]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9934\n", - "Function value obtained: -285.1611\n", - "Current minimum: -299.6824\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", + "Time taken: 1.1409\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.5068234394773203]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0790\n", - "Function value obtained: -280.3531\n", - "Current minimum: -299.6824\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", + "Time taken: 1.1433\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.5599477470534967]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1106\n", - "Function value obtained: -285.3636\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1053\n", + "Function value obtained: -0.0000\n", + "Current minimum: -276.4398\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0145\n", - "Function value obtained: -283.7417\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1822\n", + "Function value obtained: -119.5722\n", + "Current minimum: -276.4398\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1208\n", - "Function value obtained: -284.4480\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1073\n", + "Function value obtained: -124.9303\n", + "Current minimum: -276.4398\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0133\n", - "Function value obtained: -287.7597\n", - "Current minimum: -299.6824\n", + "Time taken: 1.2083\n", + "Function value obtained: -129.5423\n", + "Current minimum: -276.4398\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1579\n", - "Function value obtained: -277.8224\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1394\n", + "Function value obtained: -133.6385\n", + "Current minimum: -276.4398\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1744\n", - "Function value obtained: -281.4562\n", - "Current minimum: -299.6824\n", + "Time taken: 1.0907\n", + "Function value obtained: -135.4072\n", + "Current minimum: -276.4398\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1383\n", - "Function value obtained: -284.2537\n", - "Current minimum: -299.6824\n", + "Time taken: 1.2051\n", + "Function value obtained: -132.3138\n", + "Current minimum: -276.4398\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0973\n", - "Function value obtained: -285.4861\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1947\n", + "Function value obtained: -287.7266\n", + "Current minimum: -287.7266\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1838\n", - "Function value obtained: -281.1279\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1099\n", + "Function value obtained: -300.7117\n", + "Current minimum: -300.7117\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0223\n", - "Function value obtained: -275.3974\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1438\n", + "Function value obtained: -312.6263\n", + "Current minimum: -312.6263\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1810\n", - "Function value obtained: -283.2870\n", - "Current minimum: -299.6824\n", + "Time taken: 1.2755\n", + "Function value obtained: -317.7043\n", + "Current minimum: -317.7043\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1356\n", - "Function value obtained: -291.6721\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1432\n", + "Function value obtained: -322.8711\n", + "Current minimum: -322.8711\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1261\n", - "Function value obtained: -285.1709\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1544\n", + "Function value obtained: -329.9536\n", + "Current minimum: -329.9536\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1326\n", - "Function value obtained: -278.2225\n", - "Current minimum: -299.6824\n", + "Time taken: 1.2283\n", + "Function value obtained: -119.6188\n", + "Current minimum: -329.9536\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1895\n", - "Function value obtained: -291.0208\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1304\n", + "Function value obtained: -128.0405\n", + "Current minimum: -329.9536\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3190\n", - "Function value obtained: -281.5575\n", - "Current minimum: -299.6824\n", + "Time taken: 1.2385\n", + "Function value obtained: -120.1647\n", + "Current minimum: -329.9536\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2062\n", - "Function value obtained: -281.0431\n", - "Current minimum: -299.6824\n", + "Time taken: 1.0728\n", + "Function value obtained: -0.0000\n", + "Current minimum: -329.9536\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2715\n", - "Function value obtained: -290.5128\n", - "Current minimum: -299.6824\n", + "Time taken: 1.1438\n", + "Function value obtained: -139.1815\n", + "Current minimum: -329.9536\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2446\n", - "Function value obtained: -283.3796\n", - "Current minimum: -299.6824\n", + "Time taken: 1.2534\n", + "Function value obtained: -80.8014\n", + "Current minimum: -329.9536\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2764\n", - "Function value obtained: -288.0767\n", - "Current minimum: -299.6824\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2241\n", - "Function value obtained: -284.4223\n", - "Current minimum: -299.6824\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2803\n", - "Function value obtained: -278.7137\n", - "Current minimum: -299.6824\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3172\n", - "Function value obtained: -287.6410\n", - "Current minimum: -299.6824\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2718\n", - "Function value obtained: -278.5836\n", - "Current minimum: -299.6824\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2220\n", - "Function value obtained: -280.4583\n", - "Current minimum: -299.6824\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2973\n", - "Function value obtained: -287.5747\n", - "Current minimum: -299.6824\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1781\n", - "Function value obtained: -290.1275\n", - "Current minimum: -299.6824\n", - "CPU times: user 1min 44s, sys: 10min 30s, total: 12min 15s\n", - "Wall time: 55.2 s\n" + "Time taken: 1.2480\n", + "Function value obtained: -118.6952\n", + "Current minimum: -329.9536\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" ] }, { - "data": { - "text/plain": [ - "(-299.6823555974254, [0.16787857585865285])" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m:1\u001b[0m\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/skopt/optimizer/gp.py:281\u001b[0m, in \u001b[0;36mgp_minimize\u001b[0;34m(func, dimensions, base_estimator, n_calls, n_random_starts, n_initial_points, initial_point_generator, acq_func, acq_optimizer, x0, y0, random_state, verbose, callback, n_points, n_restarts_optimizer, xi, kappa, noise, n_jobs, model_queue_size, space_constraint)\u001b[0m\n\u001b[1;32m 273\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m base_estimator 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284\u001b[0m \u001b[43m \u001b[49m\u001b[43mbase_estimator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_estimator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 285\u001b[0m \u001b[43m \u001b[49m\u001b[43macq_func\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43macq_func\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 286\u001b[0m \u001b[43m \u001b[49m\u001b[43mxi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mxi\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 287\u001b[0m \u001b[43m \u001b[49m\u001b[43mkappa\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkappa\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 288\u001b[0m \u001b[43m \u001b[49m\u001b[43macq_optimizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43macq_optimizer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 289\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_calls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_calls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 290\u001b[0m \u001b[43m 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\u001b[49m\u001b[43mx0\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mx0\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 296\u001b[0m \u001b[43m \u001b[49m\u001b[43my0\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43my0\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 297\u001b[0m \u001b[43m \u001b[49m\u001b[43mrandom_state\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrng\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 298\u001b[0m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 299\u001b[0m \u001b[43m \u001b[49m\u001b[43mspace_constraint\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mspace_constraint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 300\u001b[0m \u001b[43m \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 301\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 302\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_queue_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmodel_queue_size\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 303\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/skopt/optimizer/base.py:332\u001b[0m, in \u001b[0;36mbase_minimize\u001b[0;34m(func, dimensions, base_estimator, n_calls, n_random_starts, n_initial_points, initial_point_generator, acq_func, acq_optimizer, x0, y0, random_state, verbose, callback, n_points, n_restarts_optimizer, xi, kappa, n_jobs, model_queue_size, space_constraint)\u001b[0m\n\u001b[1;32m 330\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(n_calls):\n\u001b[1;32m 331\u001b[0m next_x \u001b[38;5;241m=\u001b[39m optimizer\u001b[38;5;241m.\u001b[39mask()\n\u001b[0;32m--> 332\u001b[0m next_y \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnext_x\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 333\u001b[0m result \u001b[38;5;241m=\u001b[39m optimizer\u001b[38;5;241m.\u001b[39mtell(next_x, next_y)\n\u001b[1;32m 334\u001b[0m result\u001b[38;5;241m.\u001b[39mspecs \u001b[38;5;241m=\u001b[39m specs\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/skopt/utils.py:779\u001b[0m, in \u001b[0;36muse_named_args..decorator..wrapper\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 776\u001b[0m arg_dict \u001b[38;5;241m=\u001b[39m {dim\u001b[38;5;241m.\u001b[39mname: value \u001b[38;5;28;01mfor\u001b[39;00m dim, value \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(dimensions, x)}\n\u001b[1;32m 778\u001b[0m \u001b[38;5;66;03m# Call the wrapped objective function with the named arguments.\u001b[39;00m\n\u001b[0;32m--> 779\u001b[0m objective_value \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43marg_dict\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 781\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m objective_value\n", + "Cell \u001b[0;32mIn[5], line 24\u001b[0m, in \u001b[0;36mesc_obj\u001b[0;34m(**x)\u001b[0m\n\u001b[1;32m 22\u001b[0m eval_env \u001b[38;5;241m=\u001b[39m AsmEnv(config\u001b[38;5;241m=\u001b[39mCONFIG)\n\u001b[1;32m 23\u001b[0m agent \u001b[38;5;241m=\u001b[39m ConstEsc(env\u001b[38;5;241m=\u001b[39meval_env, escapement \u001b[38;5;241m=\u001b[39m x[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mescapement\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[0;32m---> 24\u001b[0m rews \u001b[38;5;241m=\u001b[39m \u001b[43meval_pol\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 25\u001b[0m \u001b[43m \u001b[49m\u001b[43mpolicy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43magent\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 26\u001b[0m \u001b[43m \u001b[49m\u001b[43menv_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mAsmEnv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mCONFIG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 27\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_batches\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m40\u001b[39;49m\n\u001b[1;32m 28\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 29\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39mmean(rews)\n", + "Cell \u001b[0;32mIn[4], line 29\u001b[0m, in \u001b[0;36meval_pol\u001b[0;34m(policy, env_cls, config, n_batches, batch_size, pb)\u001b[0m\n\u001b[1;32m 26\u001b[0m rews \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 27\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m batch_iter:\n\u001b[1;32m 28\u001b[0m rews\u001b[38;5;241m.\u001b[39mappend(\n\u001b[0;32m---> 29\u001b[0m \u001b[43mrew_batch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpolicy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpolicy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43menv_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43menv_cls\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbatch_size\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 30\u001b[0m )\n\u001b[1;32m 31\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray(rews)\u001b[38;5;241m.\u001b[39mflatten()\n", + "Cell \u001b[0;32mIn[4], line 16\u001b[0m, in \u001b[0;36mrew_batch\u001b[0;34m(policy, env_cls, config, batch_size)\u001b[0m\n\u001b[1;32m 14\u001b[0m tmax \u001b[38;5;241m=\u001b[39m env_cls()\u001b[38;5;241m.\u001b[39mTmax\n\u001b[1;32m 15\u001b[0m parallel \u001b[38;5;241m=\u001b[39m [generate_rew\u001b[38;5;241m.\u001b[39mremote(policy, env_cls, config) \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(batch_size)]\n\u001b[0;32m---> 16\u001b[0m rews \u001b[38;5;241m=\u001b[39m \u001b[43mray\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparallel\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m rews\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/auto_init_hook.py:21\u001b[0m, in \u001b[0;36mwrap_auto_init..auto_init_wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(fn)\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mauto_init_wrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 20\u001b[0m auto_init_ray()\n\u001b[0;32m---> 21\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/client_mode_hook.py:103\u001b[0m, in \u001b[0;36mclient_mode_hook..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 101\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m func\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minit\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m is_client_mode_enabled_by_default:\n\u001b[1;32m 102\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(ray, func\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m)(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 103\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/worker.py:2667\u001b[0m, in \u001b[0;36mget\u001b[0;34m(object_refs, timeout)\u001b[0m\n\u001b[1;32m 2661\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 2662\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid type of object refs, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(object_refs)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, is given. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2663\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mobject_refs\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m must either be an ObjectRef or a list of ObjectRefs. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2664\u001b[0m )\n\u001b[1;32m 2666\u001b[0m \u001b[38;5;66;03m# TODO(ujvl): Consider how to allow user to retrieve the ready objects.\u001b[39;00m\n\u001b[0;32m-> 2667\u001b[0m values, debugger_breakpoint \u001b[38;5;241m=\u001b[39m \u001b[43mworker\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_objects\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobject_refs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2668\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, value \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(values):\n\u001b[1;32m 2669\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(value, RayError):\n", + "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/worker.py:843\u001b[0m, in \u001b[0;36mWorker.get_objects\u001b[0;34m(self, object_refs, timeout)\u001b[0m\n\u001b[1;32m 837\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 838\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAttempting to call `get` on the value \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mobject_ref\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 839\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwhich is not an ray.ObjectRef.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 840\u001b[0m )\n\u001b[1;32m 842\u001b[0m timeout_ms \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(timeout \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m1000\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m timeout \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[0;32m--> 843\u001b[0m data_metadata_pairs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcore_worker\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_objects\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 844\u001b[0m \u001b[43m \u001b[49m\u001b[43mobject_refs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 845\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcurrent_task_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 846\u001b[0m \u001b[43m \u001b[49m\u001b[43mtimeout_ms\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 847\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 848\u001b[0m debugger_breakpoint \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 849\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m data, metadata \u001b[38;5;129;01min\u001b[39;00m data_metadata_pairs:\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] } ], "source": [ @@ -1215,7 +1410,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 6, "id": "ebff2644-b811-4bea-995c-ca3c7586c122", "metadata": {}, "outputs": [ @@ -1225,13 +1420,13 @@ "" ] }, - "execution_count": 37, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -1246,9 +1441,15 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 93, "id": "23e3b71f-dcb0-41df-a74d-37043f57cbe1", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -1256,13 +1457,13 @@ "" ] }, - "execution_count": 38, + "execution_count": 93, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -1277,9 +1478,13 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 94, "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -1289,265 +1494,265 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.9597\n", - "Function value obtained: -48.4151\n", - "Current minimum: -48.4151\n", + "Time taken: 0.7164\n", + "Function value obtained: -26.8844\n", + "Current minimum: -26.8844\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8968\n", - "Function value obtained: -240.4979\n", - "Current minimum: -240.4979\n", + "Time taken: 0.7265\n", + "Function value obtained: -222.6033\n", + "Current minimum: -222.6033\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.9159\n", - "Function value obtained: -28.7273\n", - "Current minimum: -240.4979\n", + "Time taken: 0.7946\n", + "Function value obtained: -80.9190\n", + "Current minimum: -222.6033\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8697\n", - "Function value obtained: -163.8213\n", - "Current minimum: -240.4979\n", + "Time taken: 0.7275\n", + "Function value obtained: -22.7700\n", + "Current minimum: -222.6033\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8175\n", - "Function value obtained: -188.8821\n", - "Current minimum: -240.4979\n", + "Time taken: 0.7880\n", + "Function value obtained: -15.2744\n", + "Current minimum: -222.6033\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8082\n", - "Function value obtained: -267.1244\n", - "Current minimum: -267.1244\n", + "Time taken: 0.8445\n", + "Function value obtained: -3.0041\n", + "Current minimum: -222.6033\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8877\n", - "Function value obtained: -25.4796\n", - "Current minimum: -267.1244\n", + "Time taken: 0.8175\n", + "Function value obtained: -233.2936\n", + "Current minimum: -233.2936\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8593\n", - "Function value obtained: -277.7872\n", - "Current minimum: -277.7872\n", + "Time taken: 0.8094\n", + "Function value obtained: -38.3504\n", + "Current minimum: -233.2936\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8390\n", - "Function value obtained: -75.4651\n", - "Current minimum: -277.7872\n", + "Time taken: 0.7705\n", + "Function value obtained: -83.3108\n", + "Current minimum: -233.2936\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 0.9403\n", - "Function value obtained: -103.9634\n", - "Current minimum: -277.7872\n", + "Time taken: 0.9808\n", + "Function value obtained: -37.9396\n", + "Current minimum: -233.2936\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9237\n", - "Function value obtained: -277.5634\n", - "Current minimum: -277.7872\n", + "Time taken: 1.0739\n", + "Function value obtained: -278.4030\n", + "Current minimum: -278.4030\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0463\n", - "Function value obtained: -274.7053\n", - "Current minimum: -277.7872\n", + "Time taken: 0.9643\n", + "Function value obtained: -460.3324\n", + "Current minimum: -460.3324\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0051\n", - "Function value obtained: -279.8106\n", - "Current minimum: -279.8106\n", + "Time taken: 0.9603\n", + "Function value obtained: -490.2741\n", + "Current minimum: -490.2741\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2822\n", - "Function value obtained: -292.9942\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9234\n", + "Function value obtained: -485.4477\n", + "Current minimum: -490.2741\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0648\n", - "Function value obtained: -283.4486\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9955\n", + "Function value obtained: -450.4965\n", + "Current minimum: -490.2741\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9720\n", - "Function value obtained: -280.7494\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0095\n", + "Function value obtained: -493.7419\n", + "Current minimum: -493.7419\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9772\n", - "Function value obtained: -281.5005\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0223\n", + "Function value obtained: -498.2012\n", + "Current minimum: -498.2012\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0893\n", - "Function value obtained: -279.1016\n", - "Current minimum: -292.9942\n", + "Time taken: 1.1705\n", + "Function value obtained: -466.6017\n", + "Current minimum: -498.2012\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0611\n", - "Function value obtained: -276.8813\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9742\n", + "Function value obtained: -477.9343\n", + "Current minimum: -498.2012\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1266\n", - "Function value obtained: -289.1597\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0431\n", + "Function value obtained: -484.4293\n", + "Current minimum: -498.2012\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0954\n", - "Function value obtained: -282.1525\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0719\n", + "Function value obtained: -480.3876\n", + "Current minimum: -498.2012\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1350\n", - "Function value obtained: -274.5432\n", - "Current minimum: -292.9942\n", + "Time taken: 1.1128\n", + "Function value obtained: -483.0817\n", + "Current minimum: -498.2012\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1059\n", - "Function value obtained: -283.8849\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0581\n", + "Function value obtained: -483.6774\n", + "Current minimum: -498.2012\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0729\n", - "Function value obtained: -281.4180\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0420\n", + "Function value obtained: -483.3315\n", + "Current minimum: -498.2012\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1352\n", - "Function value obtained: -280.5095\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0541\n", + "Function value obtained: -485.7821\n", + "Current minimum: -498.2012\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0043\n", - "Function value obtained: -280.1594\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0474\n", + "Function value obtained: -483.0713\n", + "Current minimum: -498.2012\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0292\n", - "Function value obtained: -286.0372\n", - "Current minimum: -292.9942\n", + "Time taken: 1.1090\n", + "Function value obtained: -487.6074\n", + "Current minimum: -498.2012\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0649\n", - "Function value obtained: -281.2779\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0390\n", + "Function value obtained: -490.3229\n", + "Current minimum: -498.2012\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1362\n", - "Function value obtained: -274.9848\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0100\n", + "Function value obtained: -491.0666\n", + "Current minimum: -498.2012\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9673\n", - "Function value obtained: -283.4041\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9422\n", + "Function value obtained: -485.1380\n", + "Current minimum: -498.2012\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0601\n", - "Function value obtained: -268.8392\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0197\n", + "Function value obtained: -492.1412\n", + "Current minimum: -498.2012\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0646\n", - "Function value obtained: -285.1852\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0195\n", + "Function value obtained: -485.7869\n", + "Current minimum: -498.2012\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0657\n", - "Function value obtained: -280.3916\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0170\n", + "Function value obtained: -492.3588\n", + "Current minimum: -498.2012\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0999\n", - "Function value obtained: -285.1286\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0175\n", + "Function value obtained: -478.8948\n", + "Current minimum: -498.2012\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1333\n", - "Function value obtained: -279.3222\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9582\n", + "Function value obtained: -488.4867\n", + "Current minimum: -498.2012\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1070\n", - "Function value obtained: -282.5652\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0812\n", + "Function value obtained: -487.9997\n", + "Current minimum: -498.2012\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0807\n", - "Function value obtained: -283.9872\n", - "Current minimum: -292.9942\n", + "Time taken: 1.1216\n", + "Function value obtained: -483.7180\n", + "Current minimum: -498.2012\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1115\n", - "Function value obtained: -282.8966\n", - "Current minimum: -292.9942\n", + "Time taken: 1.1025\n", + "Function value obtained: -493.1157\n", + "Current minimum: -498.2012\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1009\n", - "Function value obtained: -280.1954\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0879\n", + "Function value obtained: -484.7133\n", + "Current minimum: -498.2012\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1071\n", - "Function value obtained: -289.4851\n", - "Current minimum: -292.9942\n", + "Time taken: 1.3282\n", + "Function value obtained: -486.6326\n", + "Current minimum: -498.2012\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1248\n", - "Function value obtained: -280.7557\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0917\n", + "Function value obtained: -483.5718\n", + "Current minimum: -498.2012\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0596\n", - "Function value obtained: -285.0433\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0574\n", + "Function value obtained: -482.9294\n", + "Current minimum: -498.2012\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9994\n", - "Function value obtained: -277.5333\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9581\n", + "Function value obtained: -478.3334\n", + "Current minimum: -498.2012\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1541\n", - "Function value obtained: -280.4080\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9518\n", + "Function value obtained: -484.7935\n", + "Current minimum: -498.2012\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0767\n", - "Function value obtained: -252.8654\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0271\n", + "Function value obtained: -482.6666\n", + "Current minimum: -498.2012\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1111\n", - "Function value obtained: -243.0593\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0760\n", + "Function value obtained: -486.2643\n", + "Current minimum: -498.2012\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0752\n", - "Function value obtained: -277.6296\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0205\n", + "Function value obtained: -482.6045\n", + "Current minimum: -498.2012\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0205\n", - "Function value obtained: -266.3835\n", - "Current minimum: -292.9942\n", + "Time taken: 0.9537\n", + "Function value obtained: -487.0841\n", + "Current minimum: -498.2012\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0828\n", - "Function value obtained: -284.8118\n", - "Current minimum: -292.9942\n", + "Time taken: 1.0468\n", + "Function value obtained: -482.9095\n", + "Current minimum: -498.2012\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1228\n", - "Function value obtained: -282.9191\n", - "Current minimum: -292.9942\n", - "CPU times: user 18 s, sys: 4.17 s, total: 22.2 s\n", - "Wall time: 51.9 s\n" + "Time taken: 1.0051\n", + "Function value obtained: -493.3676\n", + "Current minimum: -498.2012\n", + "CPU times: user 18 s, sys: 4.32 s, total: 22.3 s\n", + "Wall time: 49.6 s\n" ] }, { "data": { "text/plain": [ - "(-292.9941660091451, [0.11305329406169397])" + "(-498.2012416556625, [0.09553591362425362])" ] }, - "execution_count": 58, + "execution_count": 94, "metadata": {}, "output_type": "execute_result" } @@ -1560,9 +1765,14 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 95, "id": "d85a57bd-e338-468d-9d63-45d82fe53aef", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + } + }, "outputs": [ { "data": { @@ -1570,13 +1780,13 @@ "" ] }, - "execution_count": 59, + "execution_count": 95, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -1591,9 +1801,15 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 96, "id": "2e4f4fe1-236c-4f3f-ba31-49d56fdc610d", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -1601,13 +1817,13 @@ "" ] }, - "execution_count": 60, + "execution_count": 96, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -1630,9 +1846,13 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 97, "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -1642,516 +1862,516 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.9688\n", - "Function value obtained: -177.7430\n", - "Current minimum: -177.7430\n", + "Time taken: 0.8137\n", + "Function value obtained: -112.5777\n", + "Current minimum: -112.5777\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.9021\n", - "Function value obtained: -236.8874\n", - "Current minimum: -236.8874\n", + "Time taken: 0.7754\n", + "Function value obtained: -494.5841\n", + "Current minimum: -494.5841\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.8375\n", - "Function value obtained: -220.4030\n", - "Current minimum: -236.8874\n", + "Time taken: 0.7743\n", + "Function value obtained: -105.5923\n", + "Current minimum: -494.5841\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8323\n", - "Function value obtained: -191.7080\n", - "Current minimum: -236.8874\n", + "Time taken: 0.8433\n", + "Function value obtained: -490.8444\n", + "Current minimum: -494.5841\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.7831\n", - "Function value obtained: -232.0564\n", - "Current minimum: -236.8874\n", + "Time taken: 0.8100\n", + "Function value obtained: -26.2553\n", + "Current minimum: -494.5841\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.7658\n", - "Function value obtained: -277.0722\n", - "Current minimum: -277.0722\n", + "Time taken: 0.8124\n", + "Function value obtained: -49.0520\n", + "Current minimum: -494.5841\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8433\n", - "Function value obtained: -285.9566\n", - "Current minimum: -285.9566\n", + "Time taken: 0.8422\n", + "Function value obtained: -471.6829\n", + "Current minimum: -494.5841\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8087\n", - "Function value obtained: -267.4499\n", - "Current minimum: -285.9566\n", + "Time taken: 0.8121\n", + "Function value obtained: -500.5413\n", + "Current minimum: -500.5413\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8111\n", - "Function value obtained: -299.6419\n", - "Current minimum: -299.6419\n", + "Time taken: 0.8180\n", + "Function value obtained: -34.5078\n", + "Current minimum: -500.5413\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.0602\n", - "Function value obtained: -294.7403\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0414\n", + "Function value obtained: -70.7846\n", + "Current minimum: -500.5413\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2801\n", - "Function value obtained: -2.0025\n", - "Current minimum: -299.6419\n", + "Time taken: 0.9993\n", + "Function value obtained: -2.1498\n", + "Current minimum: -500.5413\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2088\n", - "Function value obtained: -290.3686\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1331\n", + "Function value obtained: -376.4437\n", + "Current minimum: -500.5413\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1222\n", - "Function value obtained: -289.1794\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0099\n", + "Function value obtained: -0.0000\n", + "Current minimum: -500.5413\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1470\n", - "Function value obtained: -0.0000\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0186\n", + "Function value obtained: -506.2584\n", + "Current minimum: -506.2584\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2602\n", - "Function value obtained: -0.0000\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1363\n", + "Function value obtained: -490.7306\n", + "Current minimum: -506.2584\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2552\n", - "Function value obtained: -296.1389\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0444\n", + "Function value obtained: -0.0000\n", + "Current minimum: -506.2584\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2958\n", - "Function value obtained: -299.3016\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0615\n", + "Function value obtained: -494.1847\n", + "Current minimum: -506.2584\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1075\n", - "Function value obtained: -295.2190\n", - "Current minimum: -299.6419\n", + "Time taken: 0.9965\n", + "Function value obtained: -379.5701\n", + "Current minimum: -506.2584\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2466\n", - "Function value obtained: -286.7931\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1032\n", + "Function value obtained: -500.5689\n", + "Current minimum: -506.2584\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1416\n", - "Function value obtained: -294.4900\n", - "Current minimum: -299.6419\n", + "Time taken: 0.9070\n", + "Function value obtained: -505.7714\n", + "Current minimum: -506.2584\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2500\n", - "Function value obtained: -293.6535\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0314\n", + "Function value obtained: -480.1877\n", + "Current minimum: -506.2584\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2807\n", - "Function value obtained: -298.7796\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1043\n", + "Function value obtained: -494.8285\n", + "Current minimum: -506.2584\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2438\n", - "Function value obtained: -0.0000\n", - "Current minimum: -299.6419\n", + "Time taken: 0.9981\n", + "Function value obtained: -502.9280\n", + "Current minimum: -506.2584\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1796\n", - "Function value obtained: -285.3215\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0053\n", + "Function value obtained: -498.3964\n", + "Current minimum: -506.2584\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1962\n", - "Function value obtained: -297.3151\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1590\n", + "Function value obtained: -504.6819\n", + "Current minimum: -506.2584\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2090\n", - "Function value obtained: -274.2131\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1096\n", + "Function value obtained: -507.3854\n", + "Current minimum: -507.3854\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1861\n", - "Function value obtained: -288.9430\n", - "Current minimum: -299.6419\n", + "Time taken: 1.3070\n", + "Function value obtained: -496.4364\n", + "Current minimum: -507.3854\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4074\n", - "Function value obtained: -295.3861\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1095\n", + "Function value obtained: -509.8005\n", + "Current minimum: -509.8005\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1041\n", - "Function value obtained: -294.5380\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0825\n", + "Function value obtained: -499.6756\n", + "Current minimum: -509.8005\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2119\n", - "Function value obtained: -298.0625\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2373\n", + "Function value obtained: -438.7227\n", + "Current minimum: -509.8005\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2237\n", - "Function value obtained: -299.2880\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0852\n", + "Function value obtained: -493.1978\n", + "Current minimum: -509.8005\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2877\n", - "Function value obtained: -298.9851\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1011\n", + "Function value obtained: -481.2166\n", + "Current minimum: -509.8005\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2722\n", - "Function value obtained: -287.3789\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0862\n", + "Function value obtained: -487.4244\n", + "Current minimum: -509.8005\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2941\n", - "Function value obtained: -290.9719\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0467\n", + "Function value obtained: -500.3367\n", + "Current minimum: -509.8005\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3283\n", - "Function value obtained: -293.7134\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1106\n", + "Function value obtained: -433.0037\n", + "Current minimum: -509.8005\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2048\n", - "Function value obtained: -285.8287\n", - "Current minimum: -299.6419\n", + "Time taken: 1.0931\n", + "Function value obtained: -487.6623\n", + "Current minimum: -509.8005\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3702\n", - "Function value obtained: -294.2641\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1745\n", + "Function value obtained: -494.4660\n", + "Current minimum: -509.8005\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3412\n", - "Function value obtained: -207.8937\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2472\n", + "Function value obtained: -491.5872\n", + "Current minimum: -509.8005\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3885\n", - "Function value obtained: -282.4190\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1841\n", + "Function value obtained: -483.2152\n", + "Current minimum: -509.8005\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3269\n", - "Function value obtained: -275.7333\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2541\n", + "Function value obtained: -507.4246\n", + "Current minimum: -509.8005\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4073\n", - "Function value obtained: -298.2017\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2425\n", + "Function value obtained: -513.3998\n", + "Current minimum: -513.3998\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3829\n", - "Function value obtained: -294.5551\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2428\n", + "Function value obtained: -496.3897\n", + "Current minimum: -513.3998\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4270\n", - "Function value obtained: -294.8593\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2923\n", + "Function value obtained: -498.7091\n", + "Current minimum: -513.3998\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3759\n", - "Function value obtained: -289.8119\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2726\n", + "Function value obtained: -486.7539\n", + "Current minimum: -513.3998\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4846\n", - "Function value obtained: -284.6668\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2129\n", + "Function value obtained: -487.7921\n", + "Current minimum: -513.3998\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3418\n", - "Function value obtained: -295.8836\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1948\n", + "Function value obtained: -508.5968\n", + "Current minimum: -513.3998\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3991\n", - "Function value obtained: -258.0139\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2143\n", + "Function value obtained: -0.0000\n", + "Current minimum: -513.3998\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4414\n", - "Function value obtained: -295.4342\n", - "Current minimum: -299.6419\n", + "Time taken: 1.3151\n", + "Function value obtained: -492.3543\n", + "Current minimum: -513.3998\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5540\n", - "Function value obtained: -295.7363\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2298\n", + "Function value obtained: -479.0166\n", + "Current minimum: -513.3998\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4234\n", - "Function value obtained: -214.8187\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2691\n", + "Function value obtained: -476.7967\n", + "Current minimum: -513.3998\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3538\n", - "Function value obtained: -293.3212\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2773\n", + "Function value obtained: -490.0617\n", + "Current minimum: -513.3998\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3868\n", - "Function value obtained: -226.8610\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2703\n", + "Function value obtained: -493.9555\n", + "Current minimum: -513.3998\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4428\n", - "Function value obtained: -290.3791\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2973\n", + "Function value obtained: -487.7396\n", + "Current minimum: -513.3998\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4112\n", - "Function value obtained: -297.0097\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2287\n", + "Function value obtained: -493.3764\n", + "Current minimum: -513.3998\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4513\n", - "Function value obtained: -280.0968\n", - "Current minimum: -299.6419\n", + "Time taken: 1.2962\n", + "Function value obtained: -495.2301\n", + "Current minimum: -513.3998\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5152\n", - "Function value obtained: -292.7703\n", - "Current minimum: -299.6419\n", + "Time taken: 1.1916\n", + "Function value obtained: -494.6566\n", + "Current minimum: -513.3998\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3899\n", - "Function value obtained: -295.7863\n", - "Current minimum: -299.6419\n", + "Time taken: 1.3476\n", + "Function value obtained: -494.5629\n", + "Current minimum: -513.3998\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4704\n", - "Function value obtained: -294.8457\n", - "Current minimum: -299.6419\n", + "Time taken: 1.3886\n", + "Function value obtained: -476.8271\n", + "Current minimum: -513.3998\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5006\n", - "Function value obtained: -281.6922\n", - "Current minimum: -299.6419\n", + "Time taken: 1.3089\n", + "Function value obtained: -454.1770\n", + "Current minimum: -513.3998\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3983\n", - "Function value obtained: -178.4917\n", - "Current minimum: -299.6419\n", + "Time taken: 1.3821\n", + "Function value obtained: -479.4262\n", + "Current minimum: -513.3998\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4636\n", - "Function value obtained: -302.6849\n", - "Current minimum: -302.6849\n", + "Time taken: 1.3460\n", + "Function value obtained: -488.0920\n", + "Current minimum: -513.3998\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4780\n", - "Function value obtained: -311.0656\n", - "Current minimum: -311.0656\n", + "Time taken: 1.3315\n", + "Function value obtained: -495.5999\n", + "Current minimum: -513.3998\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4972\n", - "Function value obtained: -303.8878\n", - "Current minimum: -311.0656\n", + "Time taken: 1.3999\n", + "Function value obtained: -497.0044\n", + "Current minimum: -513.3998\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6057\n", - "Function value obtained: -2.1697\n", - "Current minimum: -311.0656\n", + "Time taken: 1.3116\n", + "Function value obtained: -497.7739\n", + "Current minimum: -513.3998\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5193\n", - "Function value obtained: -303.1321\n", - "Current minimum: -311.0656\n", + "Time taken: 1.3412\n", + "Function value obtained: -495.4617\n", + "Current minimum: -513.3998\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5252\n", - "Function value obtained: -295.1447\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6248\n", + "Function value obtained: -481.8066\n", + "Current minimum: -513.3998\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7154\n", - "Function value obtained: -303.2232\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4060\n", + "Function value obtained: -476.4783\n", + "Current minimum: -513.3998\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5050\n", - "Function value obtained: -303.0628\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4152\n", + "Function value obtained: -484.6194\n", + "Current minimum: -513.3998\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6620\n", - "Function value obtained: -298.0582\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4634\n", + "Function value obtained: -496.8883\n", + "Current minimum: -513.3998\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5761\n", - "Function value obtained: -307.8417\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4412\n", + "Function value obtained: -493.4366\n", + "Current minimum: -513.3998\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6041\n", - "Function value obtained: -298.3403\n", - "Current minimum: -311.0656\n", + "Time taken: 1.5024\n", + "Function value obtained: -43.6975\n", + "Current minimum: -513.3998\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7091\n", - "Function value obtained: -301.8719\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4950\n", + "Function value obtained: -487.2044\n", + "Current minimum: -513.3998\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5736\n", - "Function value obtained: -125.0059\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4426\n", + "Function value obtained: -504.0297\n", + "Current minimum: -513.3998\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6025\n", - "Function value obtained: -287.2530\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6614\n", + "Function value obtained: -508.1937\n", + "Current minimum: -513.3998\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6006\n", - "Function value obtained: -287.6337\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6196\n", + "Function value obtained: -498.8906\n", + "Current minimum: -513.3998\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5020\n", - "Function value obtained: -0.0000\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4713\n", + "Function value obtained: -502.7833\n", + "Current minimum: -513.3998\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5976\n", - "Function value obtained: -307.7633\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4901\n", + "Function value obtained: -457.3923\n", + "Current minimum: -513.3998\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5648\n", - "Function value obtained: -298.2648\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4277\n", + "Function value obtained: -495.4230\n", + "Current minimum: -513.3998\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6787\n", - "Function value obtained: -302.3059\n", - "Current minimum: -311.0656\n", + "Time taken: 1.3866\n", + "Function value obtained: -484.4664\n", + "Current minimum: -513.3998\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6299\n", - "Function value obtained: -286.9437\n", - "Current minimum: -311.0656\n", + "Time taken: 1.4482\n", + "Function value obtained: -450.4714\n", + "Current minimum: -513.3998\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6426\n", - "Function value obtained: -221.7871\n", - "Current minimum: -311.0656\n", + "Time taken: 1.5498\n", + "Function value obtained: -447.0368\n", + "Current minimum: -513.3998\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5901\n", - "Function value obtained: -295.1352\n", - "Current minimum: -311.0656\n", + "Time taken: 1.5107\n", + "Function value obtained: -503.6635\n", + "Current minimum: -513.3998\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6654\n", - "Function value obtained: -272.5847\n", - "Current minimum: -311.0656\n", + "Time taken: 1.5648\n", + "Function value obtained: -480.9978\n", + "Current minimum: -513.3998\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7248\n", - "Function value obtained: -285.7321\n", - "Current minimum: -311.0656\n", + "Time taken: 1.5428\n", + "Function value obtained: -508.8501\n", + "Current minimum: -513.3998\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6756\n", - "Function value obtained: -281.1855\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6999\n", + "Function value obtained: -506.6400\n", + "Current minimum: -513.3998\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7014\n", - "Function value obtained: -298.2237\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6390\n", + "Function value obtained: -511.4363\n", + "Current minimum: -513.3998\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6424\n", - "Function value obtained: -301.8678\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6624\n", + "Function value obtained: -497.5874\n", + "Current minimum: -513.3998\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7478\n", - "Function value obtained: -306.2168\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6502\n", + "Function value obtained: -506.5583\n", + "Current minimum: -513.3998\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7986\n", - "Function value obtained: -304.4900\n", - "Current minimum: -311.0656\n", + "Time taken: 1.6838\n", + "Function value obtained: -513.0943\n", + "Current minimum: -513.3998\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7096\n", - "Function value obtained: -303.1646\n", - "Current minimum: -311.0656\n", + "Time taken: 1.8091\n", + "Function value obtained: -494.3544\n", + "Current minimum: -513.3998\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8139\n", - "Function value obtained: -292.6286\n", - "Current minimum: -311.0656\n", + "Time taken: 1.8969\n", + "Function value obtained: -494.5385\n", + "Current minimum: -513.3998\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8023\n", - "Function value obtained: -293.7803\n", - "Current minimum: -311.0656\n", + "Time taken: 1.9822\n", + "Function value obtained: -495.4969\n", + "Current minimum: -513.3998\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9644\n", - "Function value obtained: -0.0000\n", - "Current minimum: -311.0656\n", + "Time taken: 1.7196\n", + "Function value obtained: -501.8062\n", + "Current minimum: -513.3998\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8525\n", - "Function value obtained: -307.6464\n", - "Current minimum: -311.0656\n", + "Time taken: 1.7021\n", + "Function value obtained: -335.6426\n", + "Current minimum: -513.3998\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0535\n", - "Function value obtained: -297.1392\n", - "Current minimum: -311.0656\n", + "Time taken: 1.7080\n", + "Function value obtained: -488.1054\n", + "Current minimum: -513.3998\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9497\n", - "Function value obtained: -295.7007\n", - "Current minimum: -311.0656\n", + "Time taken: 1.8927\n", + "Function value obtained: -489.9963\n", + "Current minimum: -513.3998\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9379\n", - "Function value obtained: -300.8349\n", - "Current minimum: -311.0656\n", + "Time taken: 1.7363\n", + "Function value obtained: -488.8647\n", + "Current minimum: -513.3998\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9077\n", - "Function value obtained: -303.4907\n", - "Current minimum: -311.0656\n", + "Time taken: 1.8983\n", + "Function value obtained: -511.9136\n", + "Current minimum: -513.3998\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9800\n", - "Function value obtained: -304.5316\n", - "Current minimum: -311.0656\n", + "Time taken: 1.8238\n", + "Function value obtained: -503.3750\n", + "Current minimum: -513.3998\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9321\n", - "Function value obtained: -297.2611\n", - "Current minimum: -311.0656\n", - "CPU times: user 6min 24s, sys: 37min 45s, total: 44min 10s\n", - "Wall time: 2min 22s\n" + "Time taken: 1.8622\n", + "Function value obtained: -502.9744\n", + "Current minimum: -513.3998\n", + "CPU times: user 5min 51s, sys: 34min 47s, total: 40min 38s\n", + "Wall time: 2min 10s\n" ] }, { "data": { "text/plain": [ - "(-311.0656367052435,\n", - " [0.8260241432235854, 0.12728057019636857, 0.6172786457423112])" + "(-513.3997923114888,\n", + " [0.3467172508239331, 0.12349136947209918, 0.4543957127238083])" ] }, - "execution_count": 43, + "execution_count": 97, "metadata": {}, "output_type": "execute_result" } @@ -2164,9 +2384,15 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 98, "id": "faa3ef2e-e477-401d-b663-3e10e15d2023", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -2174,13 +2400,13 @@ "" ] }, - "execution_count": 44, + "execution_count": 98, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -2195,9 +2421,15 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 99, "id": "44a0bbe7-8c66-44aa-a01f-8dc8c3e17f61", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -2205,13 +2437,13 @@ "" ] }, - "execution_count": 45, + "execution_count": 99, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -2226,7 +2458,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 100, "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", "metadata": { "scrolled": true @@ -2238,516 +2470,516 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.0046\n", - "Function value obtained: -290.4467\n", - "Current minimum: -290.4467\n", + "Time taken: 0.8759\n", + "Function value obtained: -233.1128\n", + "Current minimum: -233.1128\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.9040\n", - "Function value obtained: -287.7544\n", - "Current minimum: -290.4467\n", + "Time taken: 0.8044\n", + "Function value obtained: -307.0875\n", + "Current minimum: -307.0875\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.8965\n", - "Function value obtained: -249.5194\n", - "Current minimum: -290.4467\n", + "Time taken: 0.7951\n", + "Function value obtained: -412.8523\n", + "Current minimum: -412.8523\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.9173\n", - "Function value obtained: -270.6394\n", - "Current minimum: -290.4467\n", + "Time taken: 0.8084\n", + "Function value obtained: -338.3821\n", + "Current minimum: -412.8523\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8864\n", - "Function value obtained: -65.5867\n", - "Current minimum: -290.4467\n", + "Time taken: 0.8783\n", + "Function value obtained: -424.7119\n", + "Current minimum: -424.7119\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.9363\n", - "Function value obtained: -271.5450\n", - "Current minimum: -290.4467\n", + "Time taken: 0.7928\n", + "Function value obtained: -203.1513\n", + "Current minimum: -424.7119\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.7902\n", - "Function value obtained: -222.5058\n", - "Current minimum: -290.4467\n", + "Time taken: 0.9477\n", + "Function value obtained: -56.8296\n", + "Current minimum: -424.7119\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8681\n", - "Function value obtained: -295.9096\n", - "Current minimum: -295.9096\n", + "Time taken: 0.7769\n", + "Function value obtained: -503.4267\n", + "Current minimum: -503.4267\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.9238\n", - "Function value obtained: -216.7773\n", - "Current minimum: -295.9096\n", + "Time taken: 0.7798\n", + "Function value obtained: -231.2070\n", + "Current minimum: -503.4267\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.2149\n", - "Function value obtained: -266.4456\n", - "Current minimum: -295.9096\n", + "Time taken: 0.9929\n", + "Function value obtained: -484.0746\n", + "Current minimum: -503.4267\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2302\n", - "Function value obtained: -290.8275\n", - "Current minimum: -295.9096\n", + "Time taken: 1.0217\n", + "Function value obtained: -417.6312\n", + "Current minimum: -503.4267\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1770\n", - "Function value obtained: -0.0000\n", - "Current minimum: -295.9096\n", + "Time taken: 1.0202\n", + "Function value obtained: -500.1832\n", + "Current minimum: -503.4267\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2050\n", - "Function value obtained: -304.2257\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0544\n", + "Function value obtained: -0.0000\n", + "Current minimum: -503.4267\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1736\n", - "Function value obtained: -298.4433\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0568\n", + "Function value obtained: -504.8582\n", + "Current minimum: -504.8582\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2257\n", - "Function value obtained: -194.3862\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0988\n", + "Function value obtained: -504.6257\n", + "Current minimum: -504.8582\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1873\n", - "Function value obtained: -297.8070\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0208\n", + "Function value obtained: -395.6925\n", + "Current minimum: -504.8582\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2018\n", - "Function value obtained: -291.6737\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0912\n", + "Function value obtained: -346.6311\n", + "Current minimum: -504.8582\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2290\n", - "Function value obtained: -198.6580\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1218\n", + "Function value obtained: -477.6310\n", + "Current minimum: -504.8582\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2352\n", - "Function value obtained: -295.1444\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0633\n", + "Function value obtained: -500.3590\n", + "Current minimum: -504.8582\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1875\n", - "Function value obtained: -295.9261\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0645\n", + "Function value obtained: -513.5516\n", + "Current minimum: -513.5516\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1330\n", - "Function value obtained: -289.4736\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0958\n", + "Function value obtained: -495.1691\n", + "Current minimum: -513.5516\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3153\n", - "Function value obtained: -260.2356\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1352\n", + "Function value obtained: -504.2848\n", + "Current minimum: -513.5516\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1901\n", - "Function value obtained: -288.9316\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1211\n", + "Function value obtained: -459.4911\n", + "Current minimum: -513.5516\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1431\n", - "Function value obtained: -296.7682\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1139\n", + "Function value obtained: -390.4078\n", + "Current minimum: -513.5516\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1726\n", - "Function value obtained: -287.2288\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1085\n", + "Function value obtained: -505.9347\n", + "Current minimum: -513.5516\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2014\n", - "Function value obtained: -275.8044\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1294\n", + "Function value obtained: -509.0020\n", + "Current minimum: -513.5516\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2636\n", - "Function value obtained: -267.4262\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1306\n", + "Function value obtained: -496.0927\n", + "Current minimum: -513.5516\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0494\n", - "Function value obtained: -0.0000\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1705\n", + "Function value obtained: -499.4885\n", + "Current minimum: -513.5516\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1206\n", - "Function value obtained: -301.4241\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0458\n", + "Function value obtained: -510.9051\n", + "Current minimum: -513.5516\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1381\n", - "Function value obtained: -267.7554\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0913\n", + "Function value obtained: -490.8750\n", + "Current minimum: -513.5516\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1519\n", - "Function value obtained: -292.7353\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1187\n", + "Function value obtained: -499.1893\n", + "Current minimum: -513.5516\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2797\n", - "Function value obtained: -297.3140\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0444\n", + "Function value obtained: -487.7983\n", + "Current minimum: -513.5516\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2027\n", - "Function value obtained: -287.8151\n", - "Current minimum: -304.2257\n", + "Time taken: 1.0989\n", + "Function value obtained: -488.6591\n", + "Current minimum: -513.5516\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1803\n", - "Function value obtained: -0.0000\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1467\n", + "Function value obtained: -516.4465\n", + "Current minimum: -516.4465\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1506\n", - "Function value obtained: -301.6094\n", - "Current minimum: -304.2257\n", + "Time taken: 1.2149\n", + "Function value obtained: -507.6791\n", + "Current minimum: -516.4465\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3169\n", - "Function value obtained: -209.3356\n", - "Current minimum: -304.2257\n", + "Time taken: 1.2537\n", + "Function value obtained: -499.6489\n", + "Current minimum: -516.4465\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3316\n", - "Function value obtained: -295.5580\n", - "Current minimum: -304.2257\n", + "Time taken: 1.2248\n", + "Function value obtained: -495.9194\n", + "Current minimum: -516.4465\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3323\n", - "Function value obtained: -285.1147\n", - "Current minimum: -304.2257\n", + "Time taken: 1.1706\n", + "Function value obtained: -495.4624\n", + "Current minimum: -516.4465\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3400\n", - "Function value obtained: -303.0626\n", - "Current minimum: -304.2257\n", + "Time taken: 1.2321\n", + "Function value obtained: -492.3438\n", + "Current minimum: -516.4465\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3514\n", - "Function value obtained: -305.2943\n", - "Current minimum: -305.2943\n", + "Time taken: 1.2600\n", + "Function value obtained: -476.3084\n", + "Current minimum: -516.4465\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2372\n", - "Function value obtained: -203.5269\n", - "Current minimum: -305.2943\n", + "Time taken: 1.3298\n", + "Function value obtained: -504.0439\n", + "Current minimum: -516.4465\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4567\n", - "Function value obtained: -303.0688\n", - "Current minimum: -305.2943\n", + "Time taken: 1.2792\n", + "Function value obtained: -475.7052\n", + "Current minimum: -516.4465\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3484\n", - "Function value obtained: -301.9493\n", - "Current minimum: -305.2943\n", + "Time taken: 1.2487\n", + "Function value obtained: -4.5003\n", + "Current minimum: -516.4465\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4485\n", - "Function value obtained: -296.1355\n", - "Current minimum: -305.2943\n", + "Time taken: 1.3283\n", + "Function value obtained: -512.0985\n", + "Current minimum: -516.4465\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5512\n", - "Function value obtained: -293.9905\n", - "Current minimum: -305.2943\n", + "Time taken: 1.4956\n", + "Function value obtained: -513.6646\n", + "Current minimum: -516.4465\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3773\n", - "Function value obtained: -303.7250\n", - "Current minimum: -305.2943\n", + "Time taken: 1.3218\n", + "Function value obtained: -502.0291\n", + "Current minimum: -516.4465\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3116\n", - "Function value obtained: -282.0631\n", - "Current minimum: -305.2943\n", + "Time taken: 1.2947\n", + "Function value obtained: -502.3735\n", + "Current minimum: -516.4465\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4090\n", - "Function value obtained: -293.7529\n", - "Current minimum: -305.2943\n", + "Time taken: 1.3929\n", + "Function value obtained: -501.0830\n", + "Current minimum: -516.4465\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5175\n", - "Function value obtained: -298.3346\n", - "Current minimum: -305.2943\n", + "Time taken: 1.2471\n", + "Function value obtained: -498.8909\n", + "Current minimum: -516.4465\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4520\n", - "Function value obtained: -289.3039\n", - "Current minimum: -305.2943\n", + "Time taken: 1.3721\n", + "Function value obtained: -455.5715\n", + "Current minimum: -516.4465\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4870\n", - "Function value obtained: -306.4716\n", - "Current minimum: -306.4716\n", + "Time taken: 1.3055\n", + "Function value obtained: -509.1090\n", + "Current minimum: -516.4465\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5303\n", - "Function value obtained: -291.8902\n", - "Current minimum: -306.4716\n", + "Time taken: 1.2473\n", + "Function value obtained: -504.7172\n", + "Current minimum: -516.4465\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4603\n", - "Function value obtained: -291.8776\n", - "Current minimum: -306.4716\n", + "Time taken: 1.3238\n", + "Function value obtained: -496.4901\n", + "Current minimum: -516.4465\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3981\n", - "Function value obtained: -300.2908\n", - "Current minimum: -306.4716\n", + "Time taken: 1.2955\n", + "Function value obtained: -498.1164\n", + "Current minimum: -516.4465\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5068\n", - "Function value obtained: -295.8518\n", - "Current minimum: -306.4716\n", + "Time taken: 1.3724\n", + "Function value obtained: -487.1825\n", + "Current minimum: -516.4465\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3083\n", - "Function value obtained: -286.2281\n", - "Current minimum: -306.4716\n", + "Time taken: 1.3903\n", + "Function value obtained: -443.5640\n", + "Current minimum: -516.4465\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5260\n", - "Function value obtained: -306.9200\n", - "Current minimum: -306.9200\n", + "Time taken: 1.3909\n", + "Function value obtained: -504.0442\n", + "Current minimum: -516.4465\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5102\n", - "Function value obtained: -308.5368\n", - "Current minimum: -308.5368\n", + "Time taken: 1.3259\n", + "Function value obtained: -11.6978\n", + "Current minimum: -516.4465\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4828\n", - "Function value obtained: -303.5964\n", - "Current minimum: -308.5368\n", + "Time taken: 1.2722\n", + "Function value obtained: -2.0871\n", + "Current minimum: -516.4465\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5236\n", - "Function value obtained: -2.1453\n", - "Current minimum: -308.5368\n", + "Time taken: 1.3765\n", + "Function value obtained: -502.7847\n", + "Current minimum: -516.4465\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4958\n", - "Function value obtained: -291.4858\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4298\n", + "Function value obtained: -476.2454\n", + "Current minimum: -516.4465\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5144\n", - "Function value obtained: -283.4553\n", - "Current minimum: -308.5368\n", + "Time taken: 1.3521\n", + "Function value obtained: -499.4191\n", + "Current minimum: -516.4465\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5721\n", - "Function value obtained: -273.3013\n", - "Current minimum: -308.5368\n", + "Time taken: 1.3929\n", + "Function value obtained: -509.7841\n", + "Current minimum: -516.4465\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5130\n", - "Function value obtained: -294.4617\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4950\n", + "Function value obtained: -507.6909\n", + "Current minimum: -516.4465\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4355\n", - "Function value obtained: -299.3130\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5223\n", + "Function value obtained: -504.1375\n", + "Current minimum: -516.4465\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6231\n", - "Function value obtained: -294.1639\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5151\n", + "Function value obtained: -501.4337\n", + "Current minimum: -516.4465\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5358\n", - "Function value obtained: -278.8293\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4234\n", + "Function value obtained: -509.0546\n", + "Current minimum: -516.4465\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5408\n", - "Function value obtained: -303.0506\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4756\n", + "Function value obtained: -470.3480\n", + "Current minimum: -516.4465\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5449\n", - "Function value obtained: -63.6140\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4302\n", + "Function value obtained: -512.9682\n", + "Current minimum: -516.4465\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7312\n", - "Function value obtained: -285.4334\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5046\n", + "Function value obtained: -508.2239\n", + "Current minimum: -516.4465\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5485\n", - "Function value obtained: -287.7139\n", - "Current minimum: -308.5368\n", + "Time taken: 1.3520\n", + "Function value obtained: -496.6860\n", + "Current minimum: -516.4465\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5449\n", - "Function value obtained: -277.4130\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5156\n", + "Function value obtained: -497.0283\n", + "Current minimum: -516.4465\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6182\n", - "Function value obtained: -277.4510\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4678\n", + "Function value obtained: -485.8158\n", + "Current minimum: -516.4465\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7583\n", - "Function value obtained: -198.3445\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4658\n", + "Function value obtained: -492.1256\n", + "Current minimum: -516.4465\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6535\n", - "Function value obtained: -284.8034\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4276\n", + "Function value obtained: -492.6602\n", + "Current minimum: -516.4465\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6444\n", - "Function value obtained: -157.9246\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5533\n", + "Function value obtained: -487.4258\n", + "Current minimum: -516.4465\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6303\n", - "Function value obtained: -287.9055\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4635\n", + "Function value obtained: -480.4005\n", + "Current minimum: -516.4465\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6791\n", - "Function value obtained: -299.9861\n", - "Current minimum: -308.5368\n", + "Time taken: 1.6314\n", + "Function value obtained: -483.6275\n", + "Current minimum: -516.4465\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6413\n", - "Function value obtained: -260.2050\n", - "Current minimum: -308.5368\n", + "Time taken: 1.6047\n", + "Function value obtained: -499.5568\n", + "Current minimum: -516.4465\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7575\n", - "Function value obtained: -242.1260\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4426\n", + "Function value obtained: -475.6688\n", + "Current minimum: -516.4465\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7188\n", - "Function value obtained: -303.5188\n", - "Current minimum: -308.5368\n", + "Time taken: 1.7155\n", + "Function value obtained: -497.6063\n", + "Current minimum: -516.4465\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7791\n", - "Function value obtained: -297.5755\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5705\n", + "Function value obtained: -509.9816\n", + "Current minimum: -516.4465\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7636\n", - "Function value obtained: -297.3914\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5857\n", + "Function value obtained: -481.8413\n", + "Current minimum: -516.4465\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7330\n", - "Function value obtained: -293.5340\n", - "Current minimum: -308.5368\n", + "Time taken: 1.4546\n", + "Function value obtained: -502.4067\n", + "Current minimum: -516.4465\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6580\n", - "Function value obtained: -306.8974\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5303\n", + "Function value obtained: -475.5580\n", + "Current minimum: -516.4465\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7665\n", - "Function value obtained: -301.9013\n", - "Current minimum: -308.5368\n", + "Time taken: 1.5645\n", + "Function value obtained: -482.2570\n", + "Current minimum: -516.4465\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6774\n", - "Function value obtained: -279.4106\n", - "Current minimum: -308.5368\n", + "Time taken: 1.6686\n", + "Function value obtained: -487.1464\n", + "Current minimum: -516.4465\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7285\n", - "Function value obtained: -289.2226\n", - "Current minimum: -308.5368\n", + "Time taken: 1.7093\n", + "Function value obtained: -498.6504\n", + "Current minimum: -516.4465\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6588\n", - "Function value obtained: -277.8815\n", - "Current minimum: -308.5368\n", + "Time taken: 1.6878\n", + "Function value obtained: -500.6579\n", + "Current minimum: -516.4465\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7752\n", - "Function value obtained: -253.0651\n", - "Current minimum: -308.5368\n", + "Time taken: 1.7178\n", + "Function value obtained: -503.6822\n", + "Current minimum: -516.4465\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8283\n", - "Function value obtained: -258.8707\n", - "Current minimum: -308.5368\n", + "Time taken: 1.7264\n", + "Function value obtained: -492.6878\n", + "Current minimum: -516.4465\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8296\n", - "Function value obtained: -304.0923\n", - "Current minimum: -308.5368\n", + "Time taken: 1.7623\n", + "Function value obtained: -473.5731\n", + "Current minimum: -516.4465\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8217\n", - "Function value obtained: -286.9844\n", - "Current minimum: -308.5368\n", + "Time taken: 1.8100\n", + "Function value obtained: -506.3473\n", + "Current minimum: -516.4465\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9184\n", - "Function value obtained: -291.0580\n", - "Current minimum: -308.5368\n", + "Time taken: 1.6605\n", + "Function value obtained: -240.6829\n", + "Current minimum: -516.4465\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9376\n", - "Function value obtained: -300.1590\n", - "Current minimum: -308.5368\n", + "Time taken: 1.8061\n", + "Function value obtained: -489.8163\n", + "Current minimum: -516.4465\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9354\n", - "Function value obtained: -270.6343\n", - "Current minimum: -308.5368\n", + "Time taken: 1.7793\n", + "Function value obtained: -455.7926\n", + "Current minimum: -516.4465\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8628\n", - "Function value obtained: -288.8999\n", - "Current minimum: -308.5368\n", + "Time taken: 1.6722\n", + "Function value obtained: -486.7914\n", + "Current minimum: -516.4465\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9223\n", - "Function value obtained: -292.9728\n", - "Current minimum: -308.5368\n", + "Time taken: 1.7796\n", + "Function value obtained: -434.7148\n", + "Current minimum: -516.4465\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9157\n", - "Function value obtained: -284.6444\n", - "Current minimum: -308.5368\n", + "Time taken: 1.8419\n", + "Function value obtained: -496.4754\n", + "Current minimum: -516.4465\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8037\n", - "Function value obtained: -268.8821\n", - "Current minimum: -308.5368\n", - "CPU times: user 6min 27s, sys: 38min 11s, total: 44min 39s\n", - "Wall time: 2min 22s\n" + "Time taken: 1.9441\n", + "Function value obtained: -514.5396\n", + "Current minimum: -516.4465\n", + "CPU times: user 6min 16s, sys: 36min 44s, total: 43min 1s\n", + "Wall time: 2min 12s\n" ] }, { "data": { "text/plain": [ - "(-308.53680147877856,\n", - " [0.23674914103361688, 0.4274663412150027, 0.10944474970918672])" + "(-516.4464921212091,\n", + " [0.4235963298591771, 0.10683989693940918, 0.5989144263953697])" ] }, - "execution_count": 46, + "execution_count": 100, "metadata": {}, "output_type": "execute_result" } @@ -2760,9 +2992,11 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 101, "id": "dffeed5a-f975-4a6b-b91c-1d91e6c45140", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -2770,13 +3004,13 @@ "" ] }, - "execution_count": 47, + "execution_count": 101, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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p3igha8DVp3lsh0CISmzevBklJSWws7PDy5cv8frrr8PDwwPm5uZYs2YN2+ERQkizRqssG3D1aR6m9XfXzMVMTIDu3UW3hKiYpaUlzp07h0uXLuHOnTsoKSmBr68vAgMD2Q6NEEKaPUrIGnAtWTSPTF+Po/6LdewI0PY1RM369euHfv36sR0GIYSQaighq4cZVx/F5VV4kFmErq01WI+MEBXZtm2b3Od+/vnnaoyEEEJIfSghq4efqzX+fVaGq0/zNJOQ3boF9O4NXL0qGrokOmPNmjU4efIk4uPjYWRkhIKCglrnpKamYsaMGfj7779hZmaG4OBgrF27FgYGr/6ZRkdHY968ebh//z5cXFywdOlShISE1Hndb775Rup+bm4uysrKYGVlBUBUub9Fixaws7OjhIwQQlhEk/rr0bNtSwBAjKYm9jMMUFEhuiU6paKiAu+88w5mzJgh83GBQICRI0eioqICV65cwf79+xEREYHQ0FDJOcnJyRg5ciQGDhyI+Ph4zJkzB9OmTcOZM2fqvG5ycrLka82aNfDx8UFCQgLy8/ORn5+PhIQE+Pr6YtWqVSp/zYQQQuTHYRj69K+pqKgIlpaWiElIxXsRd2DONcCt0CEw0Fdz/hoXB/j5AbGxgK+veq9FahH/3gsLC2FhYaGWa0RERGDOnDm1eshOnz6NN954A5mZmbC3twcAhIeHY+HChcjNzYWRkREWLlyIkydP4t69e5LnvffeeygoKEBkZGSD127Xrh2OHj2K7jV6X2NjYzFu3DgkU0FiQghhDfWQAeDz+SgqKpL6AoAODhawMDZAMb8K9zOpHllzUfO9wOfz1X7NmJgYdO3aVZKMAUBQUBCKiopw//59yTk1V0QGBQUhJiZGrmtkZWWhqqqq1nGBQIDs7OxGRE8IIaSxKCEDsHbtWlhaWkq+XFxcAAD6ehz0cm8FALjyhOqRNRcuLi5S74e1a9eq/Zo8Hk8qGQMguS/e1qiuc4qKivDy5csGrzF48GB8/PHHiKu2kjc2NhYzZsyg0heEEMIySsgALF68GIWFhZKvtLQ0yWN92okTsufqD6RjR+DePdEtYU1aWprU+2Hx4sUyz1u0aBE4HE69Xw8fPtRw9HXbt28fHBwc4O/vDy6XCy6Xi549e8Le3h579uxhOzxCCGnWaJUlIPlwkqWvhw0A4EZKPvhVAnAN9NUXiIkJ0Lmz+toncrGwsJBrDtn8+fPrXeEIAO7u8hUVdnBwwPXr16WOiYcRHRwcJLc1hxazs7NhYWEBEzmKCdva2uLUqVN49OiRJFH08vJC+/bt5YqREEKI+lBC1gBPOzPYmHHxvISPuGcFCPivx0wtnj0DVq0Cli0DXF3Vdx2iEra2tirblDsgIABr1qxBTk4O7OzsAADnzp2DhYUFOnXqJDnn1KlTUs87d+4cAgICFLpW+/btKQkjhJAmhhKyBnA4HPRp1wrHb2ci5slz9SZkeXnA3r3Ap59SQqZjUlNTkZ+fj9TUVAgEAsTHxwMAPDw8YGZmhqFDh6JTp06YNGkSNmzYAB6Ph6VLl2LmzJmS3ttPPvkE3333HRYsWIAPP/wQFy5cwJEjR3Dy5Em5YhAIBIiIiEBUVBRycnIgFAqlHr9w4YJKXzMhhBD5UUImh74eooTs8pM8zGM7GKKVQkNDsX//fsl9cemJv//+GwMGDIC+vj5OnDiBGTNmICAgAKampggODsbKlSslz2nbti1OnjyJuXPnYuvWrWjdujX27NmDoKAguWKYPXs2IiIiMHLkSHTp0gUcjga2AyOEECIXqkMmQ816VGn5Zei/4W8Y6HEQHzYUZlw15bFUh4xVmqhDxiYbGxscOHAAI0aMYDsUQgghNdAqSzm4tGyBNi1boErI4Hoylb8g2snIyAgeHh5sh0EIIUQGSsjkJC5/cTlJjQmZvT2waJHolhAVmz9/PrZu3QrqFCeEkKaH5pDJqY+HDQ7dSMPlJDXWI3N2BjRQhJQ0T5cuXcLff/+N06dPo3PnzjA0NJR6/NixYyxFRgghhBIyOYl7yB7yivG8hA8bM9l1yxqluFg0f8zPDzA3V337pFmzsrLCW2+9xXYYhBBCZKCETE42Zlx4OZjjIa8YV5/m4Y1uTqq/yOPHwMCBNKmfqMUPP/zAdgiEEELqQHPIFNCnnahq/6XHGthGiRA1qKqqwvnz57Fz504UFxcDADIzM1FSUsJyZIQQ0rxRD5kC+re3wb7Lyfj38XMwDEN1nIhWefbsGYYNG4bU1FTw+XwMGTIE5ubmWL9+Pfh8PsLDw9kOkRBCmi3qIVNAr7YtYaSvh4yCl3j6vJTtcAhRyOzZs+Hv748XL15I7X351ltvISoqisXICCGEUA+ZAloYGcDfzRpXnuTh30e5aGdrptoLGBqKVlrWWP1GiCr8+++/uHLlCoyMjKSOu7m5ISMjg6WoCCGEANRDprDX2os2k/5HHfPIunYF0tNFt4SomFAohEAgqHU8PT0d5rSqlxBCWEUJmYL6e4om9sc8yQO/qvaHGyFN1dChQ7FlyxbJfQ6Hg5KSEoSFhdF2SoQQwjJKyBTU0cECNmZcvKwUIO5ZgWobv3sXaN1adEuIim3evBmXL19Gp06dUF5ejgkTJkiGK9evX892eIQQ0qzRHDIF6elx0N/TBr/fysA/j3MR8F/BWJWorAQyMkS3hKhY69atcfv2bRw6dAh37txBSUkJpk6diokTJ0pN8ieEEKJ5lJApQZyQ/fs4FwuHebEdDiFyMzAwwAcffMB2GIQQQmqghEwJ/f6bR3Yvowh5JXy0Usc2SoSoQWJiIr799lskJCQAADp27IhZs2bBy4v+sCCEEDbRHDIl2Jkbo6OjBQDgkjo3GydEhX777Td06dIFsbGx8Pb2hre3N+Li4tC1a1f89ttvbIdHCCHNGvWQKem19jZIyCrCxUe5eNPHWTWNenoCf/8tuiVExRYsWIDFixdj5cqVUsfDwsKwYMECjB07lqXICCGEUA+Zkl73/K8e2aNcCIWMaho1NwcGDBDdEqJiWVlZmDx5cq3jH3zwAbKysliIiBBCiBglZEryd2sJM64BnpdU4E5GoWoazcgAFi8W3RKiYgMGDMC///5b6/ilS5fQv39/FiIihBAiRkOWSjIy0MNr7W1w6i4PFxKy4eNi1fhGs7OBdeuAd94RbaFEiAqNHj0aCxcuRGxsLHr37g0AuHr1Kn799VesWLECx48flzqXEEKI5nAYhlHReJvuKCoqgqWlJQoLC2FhYVHneb/eTMOXR++gi7MFTnymgh6GuDjAzw+IjQV8fRvfHlGIvL93baWnJ1+HOIfDkbnFEiGEEPWhHrJGGNDBDhyOqPxFdlE57C2M2Q6JkDoJhUK2QyCEEFIHmkPWCLbmXHRrbQUA+PthDrvBEKKA8vJytkMghBBSDSVkjTTYyw4AEKWKhKxVK2DqVNEtISomEAiwatUqODs7w8zMDE+fPgUALFu2DHv37mU5OkIIad4oIWukQf8lZJeTnqO8spHzblxdgT17RLeEqNiaNWsQERGBDRs2wMjISHK8S5cu2LNnD4uREUIIoYSskTo7WcDegouyCgGuJec3rrGXL4H790W3hKjYgQMHsGvXLkycOBH6+vqS497e3nj48CGLkRFCCKGErJE4HI6kl+xCQnbjGktIALp0Ed0SomIZGRnw8PCodVwoFKKyspKFiAghhIhRQqYCAzu8mkdGVURIU9WpUyeZhWGPHj2K7t27sxARIYQQMSp7oQL9PG3ANdBD+ouXeJBVhM5OlmyHREgtoaGhCA4ORkZGBoRCIY4dO4bExEQcOHAAJ06cYDs8Qghp1qiHTAVaGBng9faivS3P3OOxHA0hsr355pv466+/cP78eZiamiI0NBQJCQn466+/MGTIELbDI4SQZo16yFRkWBcHnH2QjdP3eJg3tINyjXA4gJGR6JYQNejfvz/OnTvHdhiEEEJqoIRMRQZ3tIehPgePc0qQlFMCDzszxRvp3h3g81UfHCGEEEKaNErIVMTSxBB92tng4qNcnLnPg4dd7dVshGiatbU1OHL2uObnN7JsCyGEEKVRQqZCw7o44OKjXETe42HmQCUSsoQEYOJE4OBBoGNH1QdImp0tW7ZIvs/Ly8Pq1asRFBSEgIAAAEBMTAzOnDmDZcuWsRQhIYQQAOAwVKehlqKiIlhaWqKwsBAWFhZyP+95CR8915yHkAH+XTAQLi1bKHbhuDjAzw+IjQV8fRWMmjSWsr93bTF27FgMHDgQs2bNkjr+3Xff4fz58/jjjz/YCYwQQgitslQlGzMueri1BACcuU+rLUnTcubMGQwbNqzW8WHDhuH8+fMsREQIIUSMEjIVG97FAQAQSeUvSBPTqlUr/Pnnn7WO//nnn2hFG9oTQgiraA6ZigV1ccDyvx4gNvUFsovKYW9hzHZIRAaBkEFqfhkeZxcjo+AlMgteIiXzOdthqdWKFSswbdo0REdHo1evXgCAa9euITIyErt372Y5OkIIad4oIVMxR0sT+LlaI/bZC/x1OxPT+rvL/+S2bYEjR0S3RKVyispxPSUf15PzEZ9WgEfZxSivFEqdI+SXsRSdZoSEhKBjx47Ytm0bjh07BgDo2LEjLl26JEnQCCGEsIMm9cvQ2MndP159hmV/3ENnJwuc/Ly/GiIkDREIGcSnvcC5Bzk4n5CNpJySWucYG+rB084cbVq2gJOVMawMqjBrmLfOTuonhBDSdFEPmRq80dURK47fx/3MIjzKLkZ7e3P5npidLSp5MXEiYG+v3iB11IPMIhyLS8eftzORW/yqyC6HA3R0sEDPti3h52qNzk4WcG1lCn29VzW6ioqKMEtWo4QQQoiaUUKmBtamRhjQwQ7nE7Lx+60MLBzmJd8TMzKA+fOBAQMoIVNAWUUV/riViR+vPkNCVpHkuLmxAQZ2sENgJ3u87mkLyxaGLEZJCCGE1I0SMjV529cZ5xOy8eetDHw5tAP09Gh/SlXLKnyJiMspOHQjDYUvKwEARvp6GNzRDmN9W+O19rYwMqCFxIQQQpo+SsjUZJCXHcyNDZBZWI5ryfkIaEdlBVQlLb8M30c/wdHYNFQKRFMg27RsgckBrhjn1xpWLYxYjpAQQghRDHUfqImxoT5GdnUEAPx+K53laHQDr7Aci367g4GbovHL9VRUChj0bNsSeyb74+8vBmBaf/cmmYylpKRg6tSpaNu2LUxMTNCuXTuEhYWhoqJC6rw7d+6gf//+MDY2houLCzZs2FCrrV9//RVeXl4wNjZG165dcerUKU29DEIIIWpEPWRqNKa7Mw7dSMPpuzysfLMLjA3163+CpSUwapTolkgUvqzEzotPsO9ysqRURX9PG3w2yBM927ZkObqGPXz4EEKhEDt37oSHhwfu3buH6dOno7S0FJs2bQIgWlAwdOhQBAYGIjw8HHfv3sWHH34IKysrfPTRRwCAK1eu4P3338fatWvxxhtv4Oeff8aYMWMQFxeHLl26yLz222+/LXec4lIYhBBCNI/KXsigqj0NhUIG/Tf8jYyCl9j2fneM9nZSYZS6TyBkcOhGKjadScSLMtEcsR5u1lg03At+rqpPxDS5l+XGjRuxY8cOPH36FACwY8cOLFmyBDweD0ZGol6+RYsW4Y8//sDDhw8BAOPHj0dpaSlOnDghaad3797w8fFBeHi4zOtMmTJF7ph++OEHZV8OIYSQRqIeMjXS0+NgrK8ztl1IwsGrzxpOyCorgYICwMoKMGzeKwJvpOQj7M/7ePDfqklPOzMsHOaFwR3twOFo/wKJwsJCtGz5KqmMiYnBa6+9JknGACAoKAjr16/HixcvYG1tjZiYGMybN0+qnaCgoHo3BackixBCtAMlZAD4fD74/Fc1q4qKiuo5WzHv92qD7dFPcC05v+GaZHfvAn5+QGws4Ourshi0SX5pBb46lYCjsaJ5dxbGBpg/tAMm9moDA33NTHms+fvncrngcrkqaz8pKQnffvutZLgSAHg8HtrW2KHB/r/SJzweD9bW1uDxeJJj1c/h8WjfVEII0XY0qR/A2rVrYWlpKflycXFRWduOliYI7GgHAPjp6jOVtatrGIbBkZtpGLw5Gkdj08HhAO/3dMHfXwxAcB83jSVjAODi4iL1fli7dq3M8xYtWgQOh1Pvl3i4USwjIwPDhg3DO++8g+nTp2vi5Ug5evQo3n33XfTu3Ru+vr5SX4QQQthDPWQAFi9eLDUUVFRUpNKkbFJvN5y5n41jcRlYMMwLZlz6sVf3LK8Ui367i5ineQAALwdzfPV2V/i2sWYlnrS0NKk5ZHX1js2fPx8hISH1tuXu/mov08zMTAwcOBB9+vTBrl27pM5zcHBAdna21DHxfQcHh3rPET/ekG3btmHJkiUICQnBn3/+iSlTpuDJkye4ceMGZs6cKVcbhBBC1IMyA6h+SKqmPu1awd3GFE+fl+KPWxn4oLer2q6lTQRCBj9cTsams4korxTC2FAPcwLbY2q/tjDUYI9YTRYWFnJN6re1tYWtra1cbWZkZGDgwIHw8/PDDz/8AD096dcXEBCAJUuWoLKyEob/zR88d+4cOnToAGtra8k5UVFRmDNnjuR5586dQ0BAgFwxfP/999i1axfef/99REREYMGCBXB3d0doaCjy8/PlaoMQQoh60JClBujpcTDxvyTsp6vPQAtbgSe5JXgn/ApWn0xAeaUQAe6tcGbOa/jk9XasJmPqkJGRgQEDBqBNmzbYtGkTcnNzwePxpOZ+TZgwAUZGRpg6dSru37+Pw4cPY+vWrVI9t7Nnz0ZkZCQ2b96Mhw8fYvny5bh58yZmzZJvB87U1FT06dMHAGBiYoLi4mIAwKRJk/DLL7+o8BUTQghRFPWQacg439bYeOYhHvKKcfPZC/Rwk1G2wdsbKCwETE01H6CGCIQM9l0S9Yrxq4Qw5xrgfyM74r0eLjqxelKWc+fOISkpCUlJSWjdurXUY+Lk3NLSEmfPnsXMmTPh5+cHGxsbhIaGSmqQAUCfPn3w888/Y+nSpfjf//4HT09P/PHHH3XWIKvJwcEB+fn5cHV1RZs2bXD16lV4e3sjOTmZ/kgghBCWUR0yGdRVj2rRb3dw6EYahnV2QPgkP5W1qy2Sn5fii19vI/bZCwCi4q7rx3aDk5UJy5GJaLIOGRumTZsGFxcXhIWFYfv27fjyyy/Rt29f3Lx5E2+//Tb27t3LdoiEENJsUUImg7o+mB9lF2PoN/8AAM7MeQ0dHGqUwHj8GJg1C/juO8DTU2XXZZtQyOBATArWRT5EeaUQZlwDLB3ZEeObWK+YridkQqEQQqEQBgaijvFDhw7hypUr8PT0xMcffyxVA40QQohmUUImgzo/mGf8FIvT93gY5e2Eb9/vLv1gXJzO1SFLf1GGBUfv4MoT0QrKPu1aYcO4bmht3YLlyGrT9YSMEEJI00VzyDRs1iAPnL7Hw4k7mZg92BMedmZsh6QWDMPg15vpWHniAUr4VTAx1MfiEV74oJcr9PSaTq+Yrrtz5w66dOkCPT093Llzp95zu3XrpqGoCCGE1EQJmYZ1drLEkE72OPcgG9//nYSvx/uwHZLK5RSVY9Gxu7jwMAcA4OdqjU3veKOtje4uVmiqfHx8wOPxYGdnBx8fH3A4HJkT+DkcDgQCAQsREkIIASghY8Xngzxx7kE2/ojPwOeDPeGmI4kKwzA4fjsToX/eR+HLShjp62H+0PaY1t8d+tQrxork5GRJrbTk5GSWoyGEEFIXSshY0LW1JQZ2sMXfibn49kISNr/rLXrAxUU0oV+FuwRoSl4JH0v/uIfT90S1tbo4W2DzOz61Fy4QjXJ1fVWE+NmzZ+jTp49kUr9YVVUVrly5InUuIYQQzaJJ/TJoYnL3rdQXeOv7K+BwgD8+7QtvFyu1XEcTTt7JwrI/7yG/tAIGehx8NsgTnw7UvgKvuj6pX19fH1lZWbCzs5M6npeXBzs7OxqyJIQQFmnXJ6YO6d7GGm91dwbDAMv+vAeBkAHy84GffhLdaoG8Ej5mHozDzJ/jkF9aAS8Hc/wxsy9mB3pqXTLWHDAMI7PMSF5eHkx1uBgxIYRoAxqyZNHiEV44/yAbd9IL8cv1VHxglAdMmiQqe9FSRiX/JoJhGPx1JwvLj99HfmkF9PU4mDmgHWYN8oSRASViTc3bb78NQDRxPyQkRGrfVoFAgDt37ki2VCKEEMIOSshYZGdujHlD22PFXw+w8Uwi3hhsASu2g2oAr7AcS/+4h/MJ2QAALwdzbHrHG12cLVmOjNTF0lL0u2EYBubm5jAxebUzgpGREXr37o3p06ezFR4hhBBQQsa6Sb1dceRmOhKyirD/Sgpmsx1QHYRCBj9fT8X6yIcoLq+CoT4HswZ6YsaAdtQr1sT98MMPklIX3377LczMdLP2HSGEaDP6JGWZgb4eVo/pDAA4+yCb5Whke5xdjHd3xmDpH/dQXF4FbxcrnPisP2YH0hCltmAYBgcPHkRWVhbboRBCCJGBesiaAD/XlpjWry0u/JmOeGcvtOQDbdgOCkBZRRW+u5CE3f8+RaWAQQsjfXwZ1AGTA9yorpiW0dPTg6enJ/Ly8uCpQ/ukEkKIrqCErIlYONwLd9ILMabVJrS/WozffatgymXn18MwDM4+yMbKvx4go+AlAGCwlx1WjukCZyuTBp5Nmqp169bhyy+/xI4dO9ClSxe2wyGEEFIN1SGTga16VDnF5Xhj2yXkFPMxytsJ297zkVmmQJ0eZRdj9ckE/PMoFwDgbGWCsFGdMKSTvcZj0TRdr0NmbW2NsrIyVFVVwcjISGpyPwDka0m5FUII0UXUQ9aE2D1+gOtLh+DNKVvx123AuoUhlo/qrJHNuPNK+Nhy/jF+vp4KgZCBoT4H0/u7Y9YgD7QworeJLtiyZQvbIRBCCKkDfdI2QTMHeuDjBwwOxDxD4ctKbHrHW22FVovKK7Hnn6fYeykZpRWiSu1Bne2xeHhHndljk4gEBwezHQIhhJA6UELWBA3t7ICt3Rww73A8/ozPRHF5Fb6b0F2lPVUFZRX46eoz7P43GYUvKwEAnZ0ssGRkR/RpZ6Oy65Cmqby8HBUVFVLHdHGYlhBCtAUlZE3UaG8nmHMN8MlPsbjwMAdDv/kHK9/sjEFe9o1q91leKfZdSsaRm+l4WSnqEfOwM8P8Ie0xrIuDzs8Ta85KS0uxcOFCHDlyBHl5ebUep70sCSGEPZSQNWEDvezw07RemP3LLaS/eIkPI24iqLM9vhjaAZ725nK3U1hWiVP3svD7rQxcT341cbujowU+fs0do7ydqIxFM7BgwQL8/fff2LFjByZNmoTt27cjIyMDO3fuxLp169gOjxBCmjVaZSkDa6vtysuB9HSgdWvA2FhyuJRfhW1Rj7H3UjKqhKJfVwd7c4zs5oiAdq3gYGEMOwsujPT1UPiyEs9LKpCaX4rryS9wIyUfd9ILUCkQPY/DAV7ztMVHr7mjT7tW1CNWja6vsmzTpg0OHDiAAQMGwMLCAnFxcfDw8MCPP/6IX375BadOnWI7REIIabYoIZOhqX4wP+QVYdOZR7j4KEeSYFVnoMeRJGw1dbA3x1u+zhjt7QQnqiUmU1P9vauKmZkZHjx4gDZt2qB169Y4duwYevbsieTkZHTt2hUlJSVsh0gIIc0WDVk2JcnJwLJlwKpVQNu2tR72crDAnmB/FJZV4swDHk7fzUJSbgmyi/ioqBJKkjFzYwPYWxjDt40Veri1RM+2LeHailZMNnfu7u5ITk5GmzZt4OXlhSNHjqBnz57466+/YGVlxXZ4hBDSrFEPmQys9ZTExQF+fkBsLODrK/fTGIbBi7JK8KsEaGlqBK6BvhqD1F263kP2zTffQF9fH59//jnOnz+PUaNGgWEYVFZW4uuvv8bs2U11a3tCCNF91EOmAzgcDlqaGrEdBmni5s6dK/k+MDAQDx8+RGxsLDw8PNCtWzcWIyOEEEIJGSE6TigUYuPGjTh+/DgqKiowePBghIWFwdXVFa6urmyHRwghBJSQySQexS0qKtLshcWTqktKAE1fm0h+37o2ir9mzRosX74cgYGBMDExwdatW5GTk4N9+/axHRohhJD/0BwyGdLT0+Hi4sJ2GIQlaWlpaN26NdthqIynpye++OILfPzxxwCA8+fPY+TIkXj58iX09NSzJRchhBDFUEImg1AoRGZmJszNzalOVzPCMAyKi4vh5OSkU4kKl8tFUlKS1B8ZxsbGSEpK0qnEkxBCtBkNWcqgp6dHH1TNlKWlJdshqFxVVRWMqxUaBgBDQ0NUVlayFBEhhJCaKCEjRMcxDIOQkBBwuVzJsfLycnzyyScwNX1Vn+7YsWNshEcIIQSUkBGi84KDg2sd++CDD1iIRLbo6GgMHDgQL168oAK1hJBmixIyQnTcDz/8wHYIUgYMGAAfHx9s2bJFpe1yOBz8/vvvGDNmjErbJYQQTdCdmcuEEEIIIVqKEjJCiMaEhITg4sWL2Lp1KzgcDjgcDlJSUgAAsbGx8Pf3R4sWLdCnTx8kJiZKPffPP/+Er68vjI2N4e7ujhUrVqCqqgoA4ObmBgB46623wOFwJPefPHmCN998E/b29jAzM0OPHj1w/vx5Tb1cQgiRGyVkhBCN2bp1KwICAjB9+nRkZWUhKytLUo5jyZIl2Lx5M27evAkDAwN8+OGHkuf9+++/mDx5MmbPno0HDx5g586diIiIwJo1awAAN27cACAans3KypLcLykpwYgRIxAVFYVbt25h2LBhGDVqFFJTUzX8ygkhpH5Uh4wQolE155CJJ/WfP38egwcPBgCcOnVKUrzW2NgYgYGBGDx4MBYvXixp56effsKCBQuQmZkJQP45ZF26dMEnn3yCWbNmqeX1EUKIMmhSPyGkSai+wbmjoyMAICcnB23atMHt27dx+fJlSY8YAAgEApSXl6OsrAwtWrSQ2WZJSQmWL1+OkydPIisrC1VVVXj58iX1kBFCmhxKyAghTYKhoaHke/EOGUKhEIAosVqxYgXefvvtWs+rWfS2ui+++ALnzp3Dpk2b4OHhARMTE4wbNw4VFRUqjp4QQhqHEjJCiEYZGRlBIBAo9BxfX18kJibCw8OjznMMDQ1rtXv58mWEhITgrbfeAiBK7MSLCAghpCmhhIwQolFubm64du0aUlJSYGZmJukFq09oaCjeeOMNtGnTBuPGjYOenh5u376Ne/fuYfXq1ZJ2o6Ki0LdvX3C5XFhbW8PT0xPHjh3DqFGjwOFwsGzZMrmuRwghmkarLAkhGvXFF19AX18fnTp1gq2trVzzuYKCgnDixAmcPXsWPXr0QO/evfHNN9/A1dVVcs7mzZtx7tw5uLi4oHv37gCAr7/+GtbW1ujTpw9GjRqFoKAg+Pr6qu21EUKIsmiVJSGEEEIIy6iHjBBCCCGEZZSQEUIIIYSwjBIyQgghhBCWUUJGCCGEEMIySsgIIYQQQlhGCRkhzcT27dvh5uYGY2Nj9OrVC9evX6/z3Pv372Ps2LFwc3MDh8OR7DtZ3fLly8HhcKS+DA0N5Wr/2LFj8Pf3h5WVFUxNTeHj44Mff/xR6hyGYRAaGgpHR0eYmJigQ4cOaN26tVztV3fo0CFwOJxae1yGhITUit/ExETu9gsKCjBz5kw4OjqCy+Wiffv2OHXqlNQ51X/mbm5ucHJykqv9AQMG1IqNw+Fg5MiR9cY/bNgwuX4mhJCmhxIyQpqBw4cPY968eQgLC0NcXBy8vb0RFBSEnJwcmeeXlZXB3d0d69atg4ODQ53tdu7cGVlZWQgPD4eRkRE2b94sV/stW7bEkiVLEBMTgzt37mDKlCmYMmUKzpw5Izlnw4YN2LZtG8LDw7FixQokJSWBz+cjJiamwfbFUlJS8MUXX6B///4yHx82bJhU/Bs3bpQr/oqKCgwZMgQpKSk4evQoEhMTsXv3bjg7O0vOqf4zX7NmDdLS0lBQUIBz58412P6xY8eQlZUl+bp37x709fXxzjvvyIxf/PXLL7/U+/MghDRhDCFE5/Xs2ZOZOXOm5L5AIGCcnJyYtWvXNvhcV1dX5ptvvql1PCwsjPH29m50+2Ldu3dnli5dyjAMwwiFQsbBwYHZuHGjpP3p06czXC6X+eWXX+Rqv6qqiunTpw+zZ88eJjg4mHnzzTelHq9+TNH4d+zYwbi7uzMVFRV1Xr96mz179mQ+/fRTSZuK/ny++eYbxtzcnCkpKZEZPyFE+1EPGSE6rqKiArGxsQgMDJQc09PTQ2BgIGJiYhrV9uPHj+Ho6Ijr16/jzp07kqr7irTPMAyioqKQmJiI1157DQCQnJwMHo+HwMBASfwjRoxAr169EBMTI1f7K1euhJ2dHaZOnVrnOdHR0bC1tcX169eRlJSEvLw8ueI/fvw4AgICMHPmTNjb26NLly746quvJHtpVv+Zi78fMmSIpE1Ff/579+7Fe++9B1NT01rx29nZoUOHDpgxY4YkfkKI9qGEjBAd9/z5cwgEAtjb20sdt7e3B4/HU7rdXr16ISIiQjL368WLF+jfvz+Ki4vlar+wsBBmZmYwMjLCyJEj8e2332LIkCEAIHmevb29VPzV26yv/UuXLmHv3r3YvXt3ndcfNmwYDhw4gEOHDgEAHj58iOHDh0uSqvraf/r0KY4ePQqBQIBTp05h2bJl2Lx5s2RfzeoxKxN/ddevX8e9e/cwbdo0mfFHRUVh/fr1uHjxolT8hBDtQpuLE0KUMnz4cABAZmYmANFeku+88w6OHDlSb6+UmLm5OeLj41FSUoKoqCjMmzcP7u7uGDBgQKPiKi4uxqRJk7B7927Y2NjUed57770nFf+mTZvwzjvvIDo6GoMHD673GkKhEHZ2dti1axf09fXh5+eHjIwMbNy4EWFhYY2Kv6a9e/eia9eu6Nmzp8z4AaBr167o1q0b2rVrJ1f8hJCmhxIyQnScjY0N9PX1kZ2dLXU8Ozu73gn7irZfVlaG9u3bIykpSa729fT04OHhAQDw8fFBQkIC1q5diwEDBkiel52djU6dOkniz87Oho+PT73tP3nyBCkpKRg1apTkmFAoBAAYGBggMTER7dq1qxW/gYEBbGxskJSUhMGDB9cbv6OjIwwNDaGvry851rFjR/B4PFRUVEj9zP38/KTir/7aGvr5l5aW4tChQ1i5cmW95wGAu7u7VPyEEO1CQ5aE6DgjIyP4+fkhKipKckwoFCIqKgoBAQEqaz8yMhJPnjyBo6OjUu0LhULw+XwAQNu2beHg4ICoqChJ+6dPn8a1a9cQEBBQb/teXl64e/cu4uPjJV+jR4/GwIEDER8fDxcXF5nx//nnn8jLy5Mr/r59+yIpKUmS6AHAo0eP4OjoCCMjI6mfufj78+fPS9qU9+fz66+/gs/n44MPPmjw55eeni6JnxCihdheVUAIUb9Dhw4xXC6XiYiIYB48eMB89NFHjJWVFcPj8RiGYZhJkyYxixYtkpzP5/OZW7duMbdu3WIcHR2ZL774grl16xbz+PFjyTnz589noqOjmeTkZGbFihWMnp4eY2Zmxly6dKnB9r/66ivm7NmzzJMnT5gHDx4wmzZtYgwMDJjdu3dLzlm3bh1jZWXF/Pnnn8yGDRsYPT09xsbGhrl161aD7ddUc0VicXEx88UXXzAxMTFMcnIys2TJEobD4TD29vZMfHx8g+2npqYy5ubmzKxZs5jExETmxIkTjJ2dHbN69WqZP/PNmzcz+vr6TIsWLZh//vlH7vj79evHjB8/vtbxmvGfP3+e8fX1ZTw9PZny8vI6fw6EkKaLhiwJaQbGjx+P3NxchIaGgsfjwcfHB5GRkZKJ/qmpqdDTe9VhnpmZie7du0vub9q0CZs2bcLrr7+O6OhoAKIemffffx95eXmwtbWFj48PeDweBg0a1GD7paWl+PTTT5Geng4TExN4eXnhp59+wvjx4yXnLFiwAKWlpfjoo49QUFAADw8PlJSUoFevXg223xB9fX3cuXMH+/fvR0FBAZycnBAQEIBnz56hZ8+eDbbv4uKCM2fOYO7cuejWrRucnZ0xe/ZsLFy4sM6feevWrcHn8xEYGChX/ImJibh06RLOnj0rV/xDhw7FqlWrwOVy5f45EEKaDg7DMAzbQRBCCCGENGc0h4wQQgghhGWUkBFCCCGEsIwSMkIIIYQQllFCRgghhBDCMkrICCGEEEJYRgkZIYQQQgjLKCEjhBBCCGEZJWSEEJn4fD6WL18u2c6I2tet9gkhTQsVhiWEyFRUVARLS0sUFhbCwsKC2tex9puyqqoqREdH48mTJ5gwYQLMzc2RmZkJCwsLmJmZsR0eIWpBWycRQghpMp49e4Zhw4YhNTUVfD4fQ4YMgbm5OdavXw8+n4/w8HC2QyRELWjIkhBCSJMxe/Zs+Pv748WLFzAxMZEcf+uttxAVFcViZISoF/WQySAUCpGZmQlzc3NwOBy2wyEawjAMiouL4eTkpNBG1WxR9/u0qKhI6pbaZ799bXuPKuPff//FlStXYGRkJHXczc0NGRkZLEVFiPpRQiZDZmYmXFxc2A6DsCQtLQ2tW7dmO4wGaep9qu5rUPuKt68t71FlCIVCCASCWsfT09Nhbm7OQkSEaEaTSMi2b9+OjRs3gsfjwdvbG99++y169uwp89wBAwbg4sWLtY6PGDECJ0+eBACEhIRg//79Uo8HBQUhMjJSrnjE/+jdFoZCj2uMylZVtc7htnwp87lurfIbbL+TBU+uOMTijzzBP9vuSe67v+aAp/+8auO1z7vA5912tZ73oMgBz/68i8c7r0iOeX7cB65vdpV5nZS8lgrF9fz3eBQcOy25b/X2cJi/HlDn+YZ5qnm7cZ+rpJlaBBXleLRnpdb8py+OMy0trdlN+m6uioqK4OLiojXvUWUMHToUW7Zswa5duwAAHA4HJSUlCAsLw4gRI1iOjhD1YT0hO3z4MObNm4fw8HD06tULW7ZsQVBQEBITE2FnZ1fr/GPHjqGiokJyPy8vD97e3njnnXekzhs2bBh++OEHyX0ulyt3TOLhHz2uMfSMjaFnUjsh028he3GqgWn91+lqmQnAUO5YAKDnlA4w4Ooj43YenL1bIf2WdEaS/bAAXLPabXY3y4P++37QNzJAwb0sWHVxhOtY7zqHtzxMS5H8vJXccVkEDQDH0BD8JyngtnOD+aC+9Q6dCVoDhs8b/5ar/K9jwDi30U3JpC3D1OI4LSwsKCEDgNxc4MgR4N13AVtbtqNRK215jypj8+bNCAoKQqdOnVBeXo4JEybg8ePHsLGxwS+//MJ2eISoDesJ2ddff43p06djypQpAIDw8HCcPHkS+/btw6JFi2qd37KldC/OoUOH0KJFi1oJGZfLhYODg/oCV4IoGVMch8OB30RP+E30lBx7dP7VXApn77qTqG5WWeCM8wHG+Sh17fqY2JSDM7gfMLif3M+ptKlSSVIGAOW26kvKiBZKSwNmzQICAnQ+IdNlrVu3xu3bt3H48GHcvn0bJSUlmDp1KiZOnCg1yZ8QXcNqQlZRUYHY2FgsXrxYckxPTw+BgYGIiYmRq429e/fivffeg6mpqdTx6Oho2NnZwdraGoMGDcLq1avRqpXsxIXP50sVX6w+ibbSpnbvWF3a2uTJfW5j+E7wAABJj5n4viq0tclTqJdMGapOygBKzAjRJQYGBpg4cSImTpzIdiiEaAyry3SeP38OgUAAe3t7qeP29vbg8RqeZ3X9+nXcu3cP06ZNkzo+bNgwHDhwAFFRUVi/fj0uXryI4cOHy5woCgBr166FpaWl5KuhSbrGrWTPH6uPsr1jsoh7zEZv6A2/iZ4NDl8oem1FEktlfhaAYomuPMqpQ4QQnbB27Vrs27ev1vF9+/Zh/fr1LEREiGZo9brpvXv3omvXrrUWALz33nsYPXo0unbtijFjxuDEiRO4ceMGoqOjZbazePFiFBYWSr7S0tI0EL38GIZB7MHHOP7lVcQefAxlNldQZUJYk7JJmaqV21JiRoi227lzJ7y8vGod79y5MxWFJTqN1YTMxsYG+vr6yM7OljqenZ3d4Pyv0tJSHDp0CFOnTm3wOu7u7rCxsUFSUpLMx7lcrmRitLITpOvrVWpsMhT3cxIubLyNxHPpuLDxNuJ+lv06VEkTw6+q7iUTo8SsmTI3B4YOFd0SrcXj8eDo6FjruK2tLbKysliIiBDNYDUhMzIygp+fn1T1ZaFQiKioKAQE1F0+AQB+/fVX8Pl8fPDBBw1eJz09HXl5eTL/kWuDjHjp5CjjtnLJUlPsJVNXUga8SswoOWsmPD2BM2dEt0Rrubi44PLly7WOX758GU5OTixERIhmsL7Kct68eQgODoa/vz969uyJLVu2oLS0VLLqcvLkyXB2dsbatWulnrd3716MGTOm1kT9kpISrFixAmPHjoWDgwOePHmCBQsWwMPDA0FBQRp7XY3Vw+yp5PvcXkDiuVeP1beqsiFdLTNxt1C+/9QUneBv3OolyvMUXwWlykn+damelNECAB0lEAClpYCpKaCvz3Y0REnTp0/HnDlzUFlZiUGDBgEAoqKisGDBAsyfP5/l6AhRH9YTsvHjxyM3NxehoaHg8Xjw8fFBZGSkZKJ/ampqrS1CEhMTcenSJZw9e7ZWe/r6+rhz5w7279+PgoICODk5YejQoVi1apVCtcgAoODqZZTnpYHr8arGlqI9QYr2SlVPxMSGB4uyicS4EnTwNcPwYD3cLFWoWaVpYtUloJmkTKyuHjPDdI1cnqjL7duAnx8QGwv4+rIdDVHSl19+iby8PHz66aeSmpPGxsZYuHCh1Ip8QnQNh1FmhriOKyoqgqWlpdQx6/GjYTG4n8yETFXzx2QlY/W5UeKu0PnVydtLBkDhhEyZXjIxTSVlsgjLy/F05f9QWFioFYVWxe9TbYlX7eLidD4ha06/85KSEiQkJMDExASenp4K/0FNiLbR6lWWmsR/kqLwc9SZjCn7HGUoOsG/Masu1TmnjBCiPczMzNCjRw906dKFkjHSLLA+ZKktuO3c1NZ2YxKrHmZPleopU2QumTKUnU8GaHb4khDStJSWlmLdunWIiopCTk4OhEKh1ONPn2rmD1FCNI0+9eph9fZwVKRmSPZpVAdV9HJpIinT1FwyMUrKCGmepk2bhosXL2LSpElwdHTU6X07CamOPvHqYf56APRMjJV6rjzDlaocclQ2KVOEplZdiomHLykxI3Lp2hXIyQGsrNiOhDTC6dOncfLkSfTtq54/gglpqmgOmQIUndCvacokeOqsTQaopoo/zSsjcjE0FG0qbmjIdiSkEaytrdGyZUu2wyBE4yghY4m6JuSre6K/MgkoJWVEI548AUaPFt0SrbVq1SqEhoairKyM7VAI0SgaC9JBig5fKjrBX5n5ZI0dvgTUO4TJMAwKrtauDk60SGEh8NdfwPLlbEdCGmHz5s148uQJ7O3t4ebmBsMaPZ5xcXEsRUaIelFCpgYNDQNqqlyFItS96hJQTVIGqGfCf+GVf5F/9qRK2ySEKG7MmDFsh0AIKygh01HqnuSv7KpLVSZlgOp6y8qfJaukHUJI44SFhbEdAiGsoDlkGqbJ3jFFr6XoBH9lFzSoYk6ZWKVNlUrmlxm7tlVBNIQQVSgoKMCePXuwePFi5OfnAxANVWZkZLAcGSHqQz1kjdCUVlhqG1X1lIk1tsfMsk9/CCsradhSmzk7A5s3i26J1rpz5w4CAwNhaWmJlJQUTJ8+HS1btsSxY8eQmpqKAwcOsB0iIWpBPWQ6rqn2kgGq7SkTU7bHjMPhwKo31T3Savb2wLx5oluitebNm4eQkBA8fvwYxsav6kCOGDEC//zzD4uREaJelJBpEFuT+ZtbUgaobiiTaJEXL4BffxXdEq1148YNfPzxx7WOOzs7g8fjsRARIZrBekK2fft2uLm5wdjYGL169cL169frPb+goAAzZ86Eo6MjuFwu2rdvj1OnTjWqTVVSd6HVpqopJmXAq8SMkrNmIDkZePdd0S3RWlwuF0VFRbWOP3r0CLa2tixERIhmsJqQHT58GPPmzUNYWBji4uLg7e2NoKAg5OTkyDy/oqICQ4YMQUpKCo4ePYrExETs3r0bztXmjCjaZnOh7l4yoOkmZWLVkzNK0AhpmkaPHo2VK1eisrISgGg6QWpqKhYuXIixY8eyHB0h6sNqQvb1119j+vTpmDJlCjp16oTw8HC0aNEC+/btk3n+vn37kJ+fjz/++AN9+/aFm5sbXn/9dXh7eyvdJqmbpnv7NJGUVVczQatsRUkaIWzbvHkzSkpKYGdnh5cvX+L111+Hh4cHzM3NsWbNGrbDI0RtWEvIKioqEBsbi8DAwFfB6OkhMDAQMTExMp9z/PhxBAQEYObMmbC3t0eXLl3w1VdfQSAQKN0mAPD5fBQVFUl91dTYZMHf9AlOReTg68+e4lREDhiGqfNchmHkPlcRmpjD1tiVp5pOygghTYulpSXOnTuHv/76C9u2bcOsWbNw6tQpXLx4EaampmyHR4jasFb24vnz5xAIBLCvsSLK3t4eDx8+lPmcp0+f4sKFC5g4cSJOnTqFpKQkfPrpp6isrERYWJhSbQLA2rVrsWLFisa/qHqc3p+LiNXpAICrpwsAACNC7Bp9rropU8Ff2aKxYuKkTJVlMUgzYGICdO8uuiVar1+/fujXrx/bYRCiMVpVh0woFMLOzg67du2Cvr4+/Pz8kJGRgY0bNzaquvPixYsxb948yf2ioiK4uLioImSJh7ElUvcT40rqTLJqnpt3+zn6Ggtwudyx0XGou4K/WGOTMkD1tcqIjuvYEaB9DrXStm3b5D73888/V2MkhLCHtYTMxsYG+vr6yM7OljqenZ0NBwcHmc9xdHSEoaEh9PX1Jcc6duwIHo+HiooKpdoERKt6uFxuI15Nw7z8zCS9XQDQwddM5nkMw0AokB6i9PczAgD0Nc4CgEYnZurefFyMkjJCtMuaNWtw8uRJxMfHw8jICAUFBbXOSU1NxYwZM/D333/DzMwMwcHBWLt2LQwMXn2cREdHY968ebh//z5cXFywdOlShISE1Hndb775Rup+bm4uysrKYGVlBUC0ur5Fixaws7OjhIzoLNbmkBkZGcHPzw9RUVGSY0KhEFFRUQgICJD5nL59+yIpKQlCoVBy7NGjR3B0dISRkZFSbWrK8GBbhCxtjYARVghZ2hrDg2Uv3z69PxfXzxZK7g8bxsXUqS2kzhEnZpqk7AR/VexmYNzqJc0tIw27dQvgckW3RCkVFRV45513MGPGDJmPCwQCjBw5EhUVFbhy5Qr279+PiIgIhIaGSs5JTk7GyJEjMXDgQMTHx2POnDmYNm0azpw5U+d1k5OTJV9r1qyBj48PEhISkJ+fj/z8fCQkJMDX1xerVq1S+WsmpKlgdZXlvHnzsHv3buzfvx8JCQmYMWMGSktLMWXKFADA5MmTsXjxYsn5M2bMQH5+PmbPno1Hjx7h5MmT+OqrrzBz5ky521Sn+pIWDoeDESF2mLvNHSNC7MDhcGSeV3O40tCQI/PcxiZlykzwZzMpA2jCP2kAwwAVFaJbopQVK1Zg7ty56Nq1q8zHz549iwcPHuCnn36Cj48Phg8fjlWrVmH79u2oqKgAAISHh6Nt27bYvHkzOnbsiFmzZmHcuHG1esHqsmzZMnz77bfo0KGD5FiHDh3wzTffYOnSpY1/kYQ0UazOIRs/fjxyc3MRGhoKHo8HHx8fREZGSiblp6amQk/vVc7o4uKCM2fOYO7cuejWrRucnZ0xe/ZsLFy4UO422aBI8jO8lxBXT7+6Lx6ulKWvcZZK5pVpgiqGL4HmPeGfz+eDz+dL7staDUyah5q/e01MuwCAmJgYdO3aVer/06CgIMyYMQP3799H9+7dERMTI7XSXXzOnDlz5LpGVlYWqqpql6ARCAS1pqMQoktYn9Q/a9YszJo1S+Zj0dHRtY4FBATg6tWrSrfZlPU1zkKf/4Ynb8ZWwN/PqNZwpSopM8Ff2flkgOqSMqB5JmaaWA1MtEPNRUdhYWFYvny52q/L4/FkrmIXP1bfOUVFRXj58iVMGlgFO3jwYHz88cfYs2cPfH19AQCxsbGYMWNGrUSPEF3C+tZJRBqHw8G0aaYI32GNadNM6xzaFNOmoUtAdcOXYs1pftnixYtRWFgo+UpLS2M7JMKStLQ0qfdC9akdNS1atAgcDqfer/rKAmnavn374ODgAH9/f0nPX8+ePWFvb489e/awHR4hasN6DxlpPDaGLptKT5lYc+gx09SwlNbq2BG4dw9wV39ZF7ZZWFjAwsJCrnPnz59f7wpHAHCX82fm4OBQa29g8TCieCW7g4ODzJXuFhYWDfaOAYCtrS1OnTqFR48eSRJFLy8vtG/fXq4YCdFWlJA1EY3t6WpMUqbK2mQMw+DZb7dRcDcTVl2d4DrWW2YvnzqSMqB5JGakDiYmQOfObEfR5Nja2qpsU+6AgACsWbMGOTk5sLMT1VE8d+4cLCws0KlTJ8k5p06dknreuXPnFF7p3r59e0rCSLNCCRlRmqxesme/3cbDb/8BAPCikwAAbuN8ZD5fXUkZIL0ik5KzZuLZM2DVKmDZMsDVle1otFJqairy8/ORmpoKgUCA+Ph4AICHhwfMzMwwdOhQdOrUCZMmTcKGDRvA4/GwdOlSzJw5U9J7+8knn+C7777DggUL8OGHH+LChQs4cuQITp48KVcMAoEAERERiIqKQk5OjlSZIwC4cOGCSl8zIU0FzSFrwhiGwZ49pfj4kxfYs6e0wT0tG9PLpuw+lzXnkxXcrXH/Xv0xtbXJU/m8sprE88yay1yzZisvD9i7V3RLlBIaGoru3bsjLCwMJSUl6N69O7p3746bN28CAPT19XHixAno6+sjICAAH3zwASZPnoyVK1dK2mjbti1OnjyJc+fOwdvbG5s3b8aePXsQFBQkVwyzZ8/G7NmzIRAI0KVLF3h7e0t9EaKrqIdMTuV5Jhr/QN+7twxhy0XL20+cKAcATJsme3NdhmGwd28ZTl97Ci8/MwwPtm1wQUBNyg5dVu8ps+rqJOkZAwCrLvINo6qzt6y6mr9D6j0j5JWIiAhERETUe46rq2utIcmaBgwYgFtKFug9dOgQjhw5ghEjRij1fEK0FSVkLGEYBqf35+JhbAm8/MzQ52OmVgJ142aF1P2bsRV1JmTVkzc2NiQXJ2WuY0V/wRbcy4JVF0fJfXloKimrrnqCJigr1+i1CSG1GRkZwcPDg+0wCNE4GrJkyen9uYhYnY6rpwsQsTode/eW1Tqnh790Udj6isTWTN4S40rqOLN+yg5dAqKkjMPhwG2cD3yWD4fbOB+Fe+k0MYRJCGm65s+fj61btzY4RYMQXUM9ZCp0t9BJ7hpdNbdIuvlfQnX9Bh8CAWBgwIG/nyGWLzdHbGxlg0Vie/gbSYY1gbo3L5eHskOXDMOg4sRFPLhRWu8KS3mw0VtGtJy9PbBokeiWaK1Lly7h77//xunTp9G5c2cYGhpKPX7s2DGWIiNEvSghY4mXn5lkaBEAKqsYyZCj2IkT5Rg2jIs9u60bTGym1qjw7zVRNcvcFRH3cxIubLwNoOEVlvKgpIwoxNkZWLuW7ShII1lZWeGtt95iOwxCNI4SMpYMDxYlTIlxJejga4bcW7kyz4uM5GPv3rI6546JiSv8vzqP16hiscr0kmXESw81FtzLAhqRkAGvKvtTYkYaVFwMxMYCfn6AuTnb0RAl/fDDD2yHQAgrlErI0tPTcfz4caSmpqKiQnru0tdff62SwHQdh8PBiBA7ycT7BIMinDzJl3lu9cn84tWUN25WoIe/aBhT2WHB6mouMhgebKtwUubs0wqJ59Il9zv5q24fTkrMSIMePwYGDhQlZf/tgUi0U1VVFaKjo/HkyRNMmDAB5ubmyMzMhIWFBczMlJ+OQUhTpnBCFhUVhdGjR8Pd3R0PHz5Ely5dkJKSAoZhJBvBEsVNndoCMVf5iIysnZRVVjL4+JMX6OFvBIZhsHxFMYCGS2EoUr1fvMgAUH6Vpu8E0cqojNt5cPZuBd8JHuBwlN9iSRYaxiREtz179gzDhg1Damoq+Hw+hgwZAnNzc6xfvx58Ph/h4eFsh0iIWii8ynLx4sX44osvcPfuXRgbG+O3335DWloaXn/9dbzzzjtKBbF9+3a4ubnB2NgYvXr1qrVXWl0OHToEDoeDMWPGSB0PCQmptXnusGHDlIpNFeTpZeJwODAwqN3T5eCgh8hIPk6cKEfY8iIc+VW6jtbN2Ipaz1FGzUUG4lWaiqy65HA48JvoidEbesNvoqek564xm5HLQisxCdFds2fPhr+/P168eCG19+Vbb72FqKgoFiMjRL0UTsgSEhIwefJkAICBgQFevnwJMzMzrFy5EuvXr1c4gMOHD2PevHkICwtDXFwcvL29ERQUhJycnHqfl5KSgi+++AL9+/eX+fiwYcOQlZUl+frll18Ujq0hje2pYRgGpyJy8PVnT7FnTyn8/Q1h2cBzao5O+vka1lvNX97q/V5+0sMA1VdpNqYUhpiqkzKAEjNCdNG///6LpUuXwshIusyPm5sbMjIyWIqKEPVTeMjS1NRUMm/M0dERT548Qef/NvR9/vy5wgF8/fXXmD59OqZMmQIACA8Px8mTJ7Fv3z4sWrRI5nMEAgEmTpyIFStW4N9//0VBQUGtc7hcLhwcHBSOpzrDPAMIWr+6r+pq/dLDhMDyMHPss+JgbMGrpKplSw54vFfPcXHRxzvjTBAbJyqFwYCRu5p/fWouMhDfF1PFBuSy9r5UBZpfRgAAhoailZY1yiQQ7SIUCiEQCGodT09Phzkt1iA6TOEest69e+PSpUsAgBEjRmD+/PlYs2YNPvzwQ/Tu3VuhtioqKhAbG4vAwMBXAenpITAwEDExMXU+b+XKlbCzs8PUqVPrPCc6Ohp2dnbo0KEDZsyYgbx69rfj8/koKiqS+tKEmsOEaf/w8XYBA7dqx/KeC2Fu/qpbLDKSDw6Hg/Ad1pg2zRQ3b1ZKtSFrCFOeXjLxIoO529wxIsROJQsFZFFHT5kY9Zg1c127AunpoluitYYOHYotW7ZI7nM4HJSUlCAsLIy2UyI6TeGE7Ouvv0avXr0AACtWrMDgwYNx+PBhuLm5Ye/evQq19fz5cwgEAtjXKORob28PXvVuoWouXbqEvXv3Yvfu3XW2O2zYMBw4cABRUVFYv349Ll68iOHDh8v8qwsA1q5dC0tLS8mXi4uLQq+jOnl6gMRDlVkp0hP4e2eI4htb7Vh2DoPiYulhyOpJlyLV/BtLFUOXgCgpo8SMECLL5s2bcfnyZXTq1Anl5eWYMGGCZLhSmWkxhGgLhYcs3d1fDVuZmppqdMVLcXExJk2ahN27d8PGxqbO89577z3J9127dkW3bt3Qrl07REdHY/DgwbXOX7x4MebNmye5X1RU1KikrCHVhyoBoKW9ISxaGqB7kmg4dCyAzfU8v3rSVbMgbF3V/BVZcVkfVQxdiqlrCFOselJGw5nNwN27wPDhwOnT1EumxVq3bo3bt2/j0KFDuHPnDkpKSjB16lRMnDhRapI/IbpGqYTsxo0baNVK+gOuoKAAvr6+ePpU/l4UGxsb6OvrIzs7W+p4dna2zPlfT548QUpKCkaNGiU5JhQKAYgWGCQmJqJdu3YyY7axsUFSUpLMhIzL5YLL5codtzJulLhLepge3izGpwD6iB/MrgQnuxLd/7vbC8BBANX7xa4AuNhJH+++a4qpU1tI6pFV32pJU7QpKROj5KwZqKwEMjJEt0SrGRgY4IMPPmA7DEI0SuGELCUlRebQH5/PV3gFjJGREfz8/BAVFSUpXSEUChEVFYVZs2bVOt/Lywt3796VOrZ06VIUFxdj69atdfZqpaenIy8vD46Oje8hUgUvf3PsjCyEE4BFAPRrPK4HYMJ/3wsAfGcK2M8zw5mPzCRzu/bsKZW51RKg3KR+RWljUiZGyRkhTVtiYiK+/fZbJCQkAAA6duyIWbNmwcvLi+XICFEfuROy48ePS74/c+YMLC1fFWgQCASIioqCm5ubwgHMmzcPwcHB8Pf3R8+ePbFlyxaUlpZKVl1OnjwZzs7OWLt2LYyNjdGlSxep51tZWQGA5HhJSQlWrFiBsWPHwsHBAU+ePMGCBQvg4eGBoKAgheMzfG6ASpuqOh9Pft5K4flK4hWMJ+NKcD2mGN+/EMBZxnnpACYBSLTQwyf60tP9btyUXX+selX/mlQ1bCmm6qQMkG8OnipV/91VlfKRpNGrE0Jq+u233/Dee+/B398fAQEBAICrV6+ia9euOHToEMaOHdtAC4RoJ7kTMnEPFofDQXBwsNRjhoaGcHNzw+bN9c18km38+PHIzc1FaGgoeDwefHx8EBkZKZnon5qaCj09+dce6Ovr486dO9i/fz8KCgrg5OSEoUOHYtWqVSoZlpSn9MXdQqd6J61X3zbp5A/ZGLomA/dlnDcUQAIAZAklvWHiZKuHv5GkR6w6dU7ql0WVSRmg+d4yQrRJlUDIdghqt2DBAixevBgrV66UOh4WFoYFCxZQQkZ0FoepWUm0AW3btsWNGzfqnVSv7YqKimBpaQn30K+gZ2xcq4esZkImq4esroSs5kpFhmHw8vNkBP+3XVF1HwPYVe3+qFHGCN9hLXmeaE9LPqqqAEMDDvzl3NtSlb1kYqpMygDN95QBoh6y8yN2orCwEBYWFhq/vqLE71NtiVftdHxz8bKKKny891/89Okgnf6dt2jRAnfu3IGHh4fU8cePH8Pb2xtlZWUsRUaIeik8hyw5OVnyfXl5OYyNjVUaUHPD4XAwrEg0J6+onTEWvhTgs8xKdIJotWX1hKx67xeHw8G0aaYamS/GBraGMIkWMzcHBgxgOwq1yC3mY+r+G4h/onjxbW0zYMAA/Pvvv7USskuXLtW5MwshukDhhEwoFGLNmjUIDw9HdnY2Hj16BHd3dyxbtgxubm71FmvVVcrMIxMzelEF22vFeDq+FeKXuuB1IwZvvfEQC5/yMUkArFtgissJgnpLWihK1XPJANUPXYrRECaRW0YG8N13wKxZoor9OiIppwQhP1xH+ouXsDIxQBrbAanZ6NGjsXDhQsTGxkqKjV+9ehW//vorVqxYITWfefTo0WyFSYjKKTxkuXLlSuzfvx8rV67E9OnTce/ePbi7u+Pw4cPYsmVLvRX2tYV4KKjl0JGwfn0QqmylV5XKmkOm7LCl09kCcAQMMoZbS53T1zgLxideAvoclA9XfS+kOoYtAdUPXVan7sSMhiy1XFycaLgyNhbw9WU7GpWIfZaPqftvoqCsEq6tWuDbcV7wdnfS6d+5vHOGORxOncW+CdFGClfqP3DgAHbt2oWJEydCX/9VwQZvb288fPhQpcGxLf/sSRRe+ReGz6U7EsvzVFecMHOIZa1kDBAlTOVvmKB8mOyFCAzD1NpUXNYxTVNVNX9Z1Fndn5Cm5sx9HibsvoaCskp4u1jh2Iw+cGulm1MUqhMKhXJ9UTJGdI3CQ5YZGRm1xvYB0T+iSh0syFiemgL0fU19F2hoz8g6Ht+7t6zWpuIA5N5oXB3DlmLqGr4EaG4ZaR5+vPoMYX/eg5ABBnvZ4bsJvjAx0kdREb/hJ+sQmqdMmhOFe8g6deqEf//9t9bxo0ePonv37jKeod2M27jJdZ6sAqOykgaGYRC+U4CvP3uKUxE59fZi1Zcw1axDdjO2Quax+oj31JQnFkX1MHtKvWWEKIhhGGw6k4hlf4iSsfd7umDnJD+YGNUsH627BAIBVq1aBWdnZ5iZmUl2f1m2bJnC+yUTok0U7iELDQ1FcHAwMjIyIBQKcezYMSQmJuLAgQM4ceKEOmJkTcuhI2HZR7WreuJ+TsKFjbcBAFf/K3UxIsSuzvMvlzuir3FWreM165CJV2DKOlaXhwefIGJ1kdyxKIN6y4jGtGoFTJ0qutVCVQIh/vf7XRy5Kdrndm5ge3w+2KPBMja6Zs2aNdi/fz82bNiA6dOnS4536dIFW7ZsaZYLx0jzoHBC9uabb+Kvv/7CypUrYWpqitDQUPj6+uKvv/7CkCFD1BEja6x695X8Z1izYr88BWJlyYiXnvyfGFfSYBIkKymrb1PxhjYaF6vZoyZPLMpQZ1IGUGJG/uPqCuzZw3YUSimrqMKsn2/hwsMc6HGAr97qivd6tmE7LFaI5ykPHjwYn3zyieS4Ls5TJqQ6hRMyAOjfvz/OnTun6lh0Us2q/c4+rZB4Ll1yv4OvmdT5DMPg9P5cPIwtgZefGYYH28r8C7muOmSK1Car2ctWMxZVUndSBlBi1uy9fAk8fQq4uwMmqlt4o24vSiswJeIG4tMKwDXQw3cTfDGkkz3bYbGmuc1TJkRMqYQMACoqKpCTkwOhUHorjzZtmudfdYB89ch8J4j+o8m4nQdn71YYHiw9je/0/lxErBYlbNWHEesaumwMcQ9a5HU9dPA1k+yxqS6aSMoASsyarYQErSt7kVHwEpP3XsOT3FJYmhhiX4g//Fxbsh0Wq8TzlF1dXaWO6+o8ZULEFE7IHj9+jA8//BBXrlyROs4wTLOrC6PMsCWHw4HfRE/4TfT87770xPeHsSVS96sPI6o6KRP3snX8QD2rLWXRVFIGUGJGmrZEXjGC910Hr6gcjpbGOPBhT3ja696WT4pqTvOUCalO4YQsJCQEBgYGOHHiBBwdHXV6win3OVDZ+tX9mvPI5NXQZuPVefmZSXrGAOlhRIZhsCRcH8/jn6OHnPtWNkWaTMoA6RWZlJyRpuB6cj6m7b+BovIqeNqZ4cDUnnC01J5hVnVqTvOUCalO4YQsPj4esbGx8PLyUkc8Wk/RbZRulLhLlYcQDxsmxpXUGkasPpzZUJ2xpk7TSZkYJWeEbWfu8/DZL7dQUSWEv6s19gT7w6pF/Suimxuap0yaI6XqkD1/rtoNbrdv3w43NzcYGxujV69euH79ep3nHjt2DP7+/rCysoKpqSl8fHzw448/Sp3DMAxCQ0Ph6OgIExMTBAYG4vHjxyqNWVH1ffhXT0w4HA5GhNhh7jZ3jAixk+oBqzmcGXld4V+fTKqemyYvddYpk0dXy0ypL6LlOBzAyKjhYsss+vlaKmb8FIuKKiECO9rjp2m9KBkjhACQMyErKiqSfK1fvx4LFixAdHQ08vLypB4rKipSOIDDhw9j3rx5CAsLQ1xcHLy9vREUFIScnByZ57ds2RJLlixBTEwM7ty5gylTpmDKlCk4c+aM5JwNGzZg27ZtCA8Px7Vr12BqaoqgoCCUl5fLbFMR8myjJKtIrCp4+Umvguzga6a2avuawnZSVl0nCx7bISjlSU4x2yE0Dd27A3y+6LaJYRgGW84/wv9+vwshA7zXwwXhH/jC2LD5FHytj7W1NVq2bCnXFyG6Sq7NxfX09KR6asQT+KtTdlJ/r1690KNHD3z33XcAREubXVxc8Nlnn2HRokVyteHr64uRI0di1apVYBgGTk5OmD9/Pr744gsAQGFhIezt7REREYH33nuvwfbEmzZ3/PQr6HONUV5j8WHNeWSN3WxcrKHkRFwSo/pwpvj3UL2Xi2EY7N1bhhs3K+Sea6auxE7eMh5sDF/WxC+pxLZ+f2rNxs3i9+lrq0/g5BdBMOMqvWiaqJFAyGDZn/fw87VUAMCsgR6YP7S9UvM/dXVD+f3790u+z8vLw+rVqxEUFISAgAAAQExMDM6cOYNly5Zh7ty5bIVJiFrJ9T/433//Lfk+JSUFLi4uUhuLA6JEKjU1VaGLV1RUIDY2FosXL5Yc09PTQ2BgIGJiYhp8PsMwuHDhAhITE7F+/XoAQHJyMng8HgIDAyXnWVpaolevXoiJiZGZkPH5fPD5r/aIU7SnT97VlopM7pdFPJwpq3irOKHqa5wlc59Ltuaa1VXGoya25pTpguTnZVh49A6+m9BdKxd5qExCAjBxInDwINCxI9vRAADKKwWYfegWztzPBocDrBzdGZMC3NgOq8kJDg6WfD927FisXLkSs2bNkhz7/PPP8d133+H8+fOUkBGdJVdC9vrrr0u+HzRoELKysmBnJ/2hmpeXh8DAQKl/WA15/vw5BAIB7O2liyDa29vXW5G5sLAQzs7O4PP50NfXx/fffy9ZfcPj8SRt1GxT/FhNa9euxYoVK+SOWx6KTu4Hak/wV8blckecvibdxs3YinoTMnUOe9ZXxqMmSsqUY6jPwcm7Weh+yQrT+jfjn9/Ll8CtW6LbJqCgrALT9t/EzWcvYKSvh63v+WB4V+2eYqAJZ86ckfyBXd2wYcPkHjUhRBspPCtc1nAlAJSUlMDY2FglQTXE3Nwc8fHxuHHjBtasWYN58+YhOjpa6fYWL16MwsJCyVdaWprU48a50ufXnEemiIZW9imTkNTcJLyDr3TyVd+eluqegyZr3lt9mtKcMm3xZVAHAMDa0w9x5YlqF9wQ5WQUvMS48BjcfPYC5sYGODC1JyVjcmrVqhX+/PPPWsf//PNPtNLSfUoJkYfcmcW8efMAiIbNli1bhhYtXu2TKBAIcO3aNfj4+Ch0cRsbG+jr6yM7O1vqeHZ2NhwcHOp8np6enmRrDR8fHyQkJGDt2rUYMGCA5HnZ2dlwdHz1H2B2dnad8XG5XHC5XIVir0nWsKUyvWTKqDksGLzEGSFLW0vmmnlNtMXlcnaGsuor41EX6ilTzPs92+BRvgDHbmVg5sE4HJ/VDy4t69/HlKjPg8wiTIm4juwiPhwtjRExpSc6OFDBV3mtWLEC06ZNQ3R0NHr16gUAuHbtGiIjI7F7926WoyNEfeTuIbt16xZu3boFhmFw9+5dyf1bt27h4cOH8Pb2RkREhEIXNzIygp+fH6KioiTHhEIhoqKiJJM55SEUCiVzwNq2bQsHBwepNouKinDt2jWF2lQnVfeS1RwWfHSrtM7SGepQs4eu+jqR+sp41Id6yuTH4XDw1dtd4d3aEi/KKjH9wE2U8hUvYEwa79/HuXh3Zwyyi/hob2+G32b0oWRMQSEhIbh8+TIsLCxw7NgxHDt2DBYWFrh06RJCQkLYDo8QtZG7h0w8sX/KlCnYunWrylb4zJs3D8HBwfD390fPnj2xZcsWlJaWYsqUKQCAyZMnw9nZGWvXrgUgmu/l7++Pdu3agc/n49SpU/jxxx+xY8cOAKIPpzlz5mD16tXw9PRE27ZtsWzZMjg5OWHMmDFKx2mcC6nVlvJW7a+rl6yhCf6KzCerr7q/Jsg7cV9R4tevid4yhmEQf+SJ2q+jLsaG+tg5yR+jvruEh7xizD9yG99P9IWeXjOa5N+2LXDkiOiWBb/eTMPiY3dRJWTQ270ldk7yh6WJISuxaLtevXrh4MGDbIdBiEYpPBnqhx9+UGkA48ePR25uLkJDQ8Hj8eDj44PIyEjJpPzU1FTo6b3qyCstLcWnn36K9PR0mJiYwMvLCz/99BPGjx8vOWfBggUoLS3FRx99hIKCAvTr1w+RkZFqn+OmzN6W9ZE3KZNnWFDe8hOKnC8+5/ge6SHn+ibuK0MTQ5hxPyfhn2331HoNdXOwNEb4B354f9dVRN7nYfO5RHwZ1Ix21LC2Bt55R+OXZRgGW6MeY8t5UfHpMT5OWD+uG7gGVGOMECI/ueqQNTc165CJ1axHBihfk0xMnjIYqhi+OxWRI+nFAoCQpa3rTZrkOb/mOWI9h1pi/nZ3lQ+VqjMpO/7lVSSeE70WbanxVFdNqqOx6fji19sAgA1ju+HdHi5shahZ2dmikhcTJwI1VlmrC79KgMW/3cWxWxkAgBkD2uHLoR3U1jOpq3XICCFKrLJszmqutpRFk5X7FSGr/ERjz695jtj1s4U4vV+OH5aC1DmvzMlbdyqAj/Nrjc8HiRa9/O/3u7ic1ExWXmZkAPPni241oKCsApP3XsexWxnQ1+Ng7dtdsXCYV/MaJiaEqAwlZPVokae6zsO6kjJ5NrhWRc+QPOUnqk/OFwqYBs+v2WZ10cfyoI7OV7UlZTr2GTp3SHu86eOEKiGDT36KRSKPtldSpae5JXjr+yu4lpwPM64Bfgjpgfd7tmE7LEKIFqO9VhpJ1uR+ReeSyVPBv7FFY+WZZ1Z9cj4gGnrUN+DUeX71NgVVDK6fLZQ8lvLgJU7vz1XpXDIxWXPKGIZB3M9JyIjPg7NPK/hO8FBoyDQzPl/VYbKKw+Fg/dhuyCx4iRspLzB53zUc/aQPlcNQgStJzzHjYBwKX1bC2coEe0P84eVAw4eEkMahhExBNVdbKqKxdckak5TVt+2SWM0hSHEyJj4+bLINIg88l5roL26TYRgsGP0QzxJeJaKqntxfXc2kLO7nJFzYKJo3JZ4L5jfRU+72nH1aSZ6nK4wN9bF7sj/eCY/B45wSTN53Hb9+EgAbs8bV3GvODl57hrA/76NKyMC3jRV2TvKHrblu/DxTUlKwatUqXLhwATweD05OTvjggw+wZMkSGBm9Ki59584dzJw5Ezdu3ICtrS0+++wzLFiwQKqtX3/9FcuWLUNKSgo8PT2xfv16jBgxos5rv/3223LHeezYMcVfHCFagIYsG9DiecPDbrIq98uaS1YfeYYuAfVObK85BCmoYhCxOh1XTxcgYnU6vp6VLHW/+jwxDoeDgWOlh2XVXX6jenKaES+d6GbcVizx9Z3ggdc+76KSuJoSqxZGODC1J5ytTJD8vBRTfriBEl2tUWZpCYwaJbpVsYoqIZb8fhdLfr+HKiGDMT5O+Hl6b51JxgDg4cOHEAqF2LlzJ+7fv49vvvkG4eHh+N///ic5p6ioCEOHDoWrqytiY2OxceNGLF++HLt27ZKcc+XKFbz//vuYOnUqbt26hTFjxmDMmDG4d6/uVcyWlpZyfxGiq2iVpQzilUx+49dA38gYZTbSQ1/yrLYEZK+4BBq/6hJQz1wqcRkL8bBmws1iXIt8NQzZysEQebxKyf2AEVaYu81d8txTETmIPpYPDgd4/a2WGilKC4iS1NiDjyU9ZAAw6EtvhXrIAIBfUolt/f7UmhVsiqy4e5pbgnHhMcgvrUBPt5b4YUoPmHKpg1weucV8fHowFjdSXoDDAb4Y2gGfDmjHykbuml5luXHjRuzYsQNPn4r+v9mxYweWLFkCHo8n6TVbtGgR/vjjD8n+w+PHj0dpaSlOnDghaad3797w8fFBeHi42mMmRFtRD5kS5FltCSjeSwaw21NWs6p+R3/pCuPtuknPP6reA3Z6fy72r8nAs4SXSHnwEhwOR2MfWD3MnsJ3ggcGfemNDkNbY9CX3vCd4KGRa2sSn89HUVGR1Je83G3NsH9KT5hzDXA9JR8fRtxAWYWO9ZRVVgK5uaJbFbmV+gKjv7uEGykvYM41wN5gf8wcqNj8RHWo+T4Q71SiaoWFhWjZ8tUK5JiYGLz22mtSQ5hBQUFITEzEixcvJOcEBgZKtRMUFISYmBi1xEiIrqA/keXQ4jlTq5esJnkr9wOq2+OysRP9G1JzIYB4DpmshQGyymSoa/6YLD3Nk8GZ6Klwr5g2Wbt2LVasWKH087u2tsSBqT0xae91XEvOx9SIm9gX0gMmRjpSwPTuXcDPD4iNBXx9G9UUwzD46eozrDzxAJUCBu42ptgd7I92tprdBaMuLi7SteXCwsKwfPlylV4jKSkJ3377LTZt2iQ5xuPx0LbGTgjiIt48Hg/W1tbg8XiSY9XP4fF4cl/76NGjOHLkCFJTU1FRUSH1WFxcnKIvhRCtQD1kSmpsL1l9tcnk7SUD1DunrGaPmZ6eXp37UsqafyZrb0t10vX9LxcvXozCwkLJV1pamsJtdG9jjf0f9oSpkT5inubhwwgdnlOmpLKKKsw/chvL/ryPSgGDYZ0d8Oesvk0mGQOAtLQ0qffC4sWL6zx30aJFkh7rur7Ew41iGRkZGDZsGN555x1Mnz5d3S9HyrZt2zBlyhTY29vj1q1b6NmzJ1q1aoWnT59i+PDhGo2FEE2iHjI5qbqXrCHylMIQEydlbCYk1XvTqipflcC4eroADMNgRIidQls3KUuT+19qGpfLBZfb+Enkfq7WODC1JybvvY6Yp3mYsPsqfgjpgVa0+hIPeUWY9fMtJOWUQF+Pg4XDOmB6f9XvOtFYFhYWcs8hmz9/foObcru7v/r3kpmZiYEDB6JPnz5Sk/UBwMHBAdnZ0lulie87ODjUe4748YZ8//332LVrF95//31ERERgwYIFcHd3R2hoKPLzdas8DSHVUQ9ZI6izlwxQrKcMYDcJqd6blpsuPcRw8fd8SY0zWSs01UHXe8say8+1JX75qDdamhrhTnoh3t0Zg8wC1e3Dqm0YhsHBa8/w5neXkZRTAnsLLg5O64WPXmNn8r4q2drawsvLq94v8ZywjIwMDBgwAH5+fvjhhx+k9hEGgICAAPzzzz+orDZP79y5c+jQoQOsra0l50RFRUk979y5cwgICJAr3tTUVPTp0wcAYGJiguJiUVHjSZMm4ZdfflHuh0CIFqCETMVklcCojy4lZWK1BigZxbduUoUeZk8pMatHt9ZWOPJxABwtjfEktxRjd1zBg0z5FwroirwSPj7+MRZLfr8HfpUQAzvY4tTn/dHbnf0tzzRJnIy1adMGmzZtQm5uLng8ntTcrwkTJsDIyAhTp07F/fv3cfjwYWzduhXz5s2TnDN79mxERkZi8+bNePjwIZYvX46bN29i1qxZcsXh4OAg6Qlr06YNrl69CgBITk7W2PQHQtjAekK2fft2uLm5wdjYGL169cL169frPPf+/fsYO3Ys3NzcwOFwsGXLllrnLF++vNb8CC8vL5XEKk9Nsroos+JSTFuSMnHpC9T4T/P1t1vKtXWTulBSVjcPOzMcndEH7ramyCosx7jwKzh7X/7J102KtzdQWCi6lVNUQjaCtvyDsw+yYajPwZIRHbE3uHkO3547dw5JSUmIiopC69at4ejoKPkSs7S0xNmzZ5GcnAw/Pz/Mnz8foaGh+OijjyTn9OnTBz///DN27doFb29vHD16FH/88Qe6dJGvzt+gQYNw/PhxAMCUKVMwd+5cDBkyBOPHj8dbb72l2hdNSBPCah2yw4cPY/LkyQgPD0evXr2wZcsW/Prrr0hMTISdXe0Vejdu3MCRI0fg5+eHuXPnYuHChZgzZ47UOcuXL8fRo0dx/vx5yTEDAwPY2NjIHZe41k+/QctR4Sxd+kHWPDJ565IBytUmA+SvT1aTJpORUxE5UlsvuXU0wYCxrSTzy6rXOFPXHLKG1Jes6nIdsoYUllXi059jcTkpDxwOsCDIC5+83vTmTqlKYVkl1px6gCM3Re/XDvbm+Hq8Nzo7Ne3Co5quQ8YGoVAIoVAIAwPRaMOhQ4dw5coVeHp64uOPP5YquUGILmE1IevVqxd69OiB7777DoDoH6KLiws+++wzLFq0qN7nurm5Yc6cOTITsj/++APx8fFKx1VfQgbUTspUkZAB2p+Uff3ZU1w9XSC5X71wbFMlTtAYhsH1HxLxz7Z7WvNhp+oP50qBECv+uo+frqYCAII622PDWG9YtjBsdNsa8fgxMGsW8N13gGfd5U9O381C6PH7yC3mg8MBpvVri/lDO8DYsOmX/2gOCRkhzRVrqywrKioQGxsrtVxbT08PgYGBjS4g+PjxYzg5OcHY2BgBAQFYu3Yt2rRp09iQ6yRrf8u6VlzWt/F4Q/XJFFl5WZ2mVmF6+ZlJJWTi0hfqXFXZWOKfyamIHPyzTbf2slSUob4eVo/pig725lh54gHO3M/GvYx/8d2E7ujexprt8BpWXAycPSu6lSEtvwwrTzzAuQeiFYDutqZYP7Yberi1lHk+0Zw7d+6gS5cu0NPTw507d+o9t1u3bhqKihDNYi0he/78OQQCgcwCgjVr4iiiV69eiIiIQIcOHZCVlYUVK1agf//+uHfvHszNa/d2AaIK6NUrXVevgN4iuxJl9sr1EKiyDIaYskkZoJlCsgzD4OKxfBTlV0mVvgCg0UKxiqq56KA5mxTgBm8XK8z6+RZS88vwTngMPhvkiRkD2sHIgPVppworrxRgR/QThF98An6VEAZ6HMwY0A4zB3poRa9Yc+Dj4wMejwc7Ozv4+PiAw+HInMDP4XAgEAhYiJAQ9dO5OmTVCwd269YNvXr1gqurK44cOYKpU6fKfI6iFdBl1SST1UtWl8b0kgGNT8oA1feWiffBvHgsHykJtV+bpiv3K0oooNVb1XVrbYUTn/fD4t/u4uTdLHxz/hFO38vC+rHd4O1ixXZ4chEIGfxxKwNfn3uEjP9KegS4t8Ly0Z3RwUH2H2eEHcnJybC1tZV8T0hzxNqfuzY2NtDX129UAUF5WFlZoX379khKSqrznIYqoLfIVn5vvLrKYNS36rKhUhiA4isva1L1SkxxnTFZyRig2VWVyuBoX8eP2lkYG+K7Cd2x9T0ftDQ1wkNeMd76/jKWH7+P/NKKhhtgCcMwOPcgG8O3/oP5v95GRsFLOFkaY/sEX/w8vRclY02Qq6urZErDs2fP4OzsDFdXV6kvZ2dnPHv2jOVICVEf1j6GjIyM4OfnJ1VAUCgUIioqSu4CgvIoKSnBkydPpJZu18TlciWVr+WtgC2rBIa8hWLlIW9S1pjE7EaJu8oSs7qG/Nw6mSBkaWupfS+bopobqRMRDoeDN32ccW7uaxjt7QQhA0RcScHrG//GzotPUF7ZdIaPqpyccWfRarwfmYnpB27iUXYJLIwNsGi4F6LmD8DIbo5Nch4jkTZw4ECZFfkLCwsxcOBAFiIiRDNYHbKcN28egoOD4e/vj549e2LLli0oLS3FlClTAACTJ0+Gs7Mz1q5dC0C0EODBgweS7zMyMhAfHw8zMzN4eHgAAL744guMGjUKrq6uyMzMRFhYGPT19fH++++z8yKh3AR/QP5NyBszhAmoZhiz5oR+QFT2Yv2fXlrxITg82BYVfCF+3qj8z1GXtTLjYtv73fGuvwvWnEpAQlYR1p5+iB8up+DDfm54v2cbmBuzsxozv7QCx+LSsT8mBWmMD1AMtDDSR3AfN3zyWjvtWSVKAIh6OGX9n5GXlwdTU1MWIiJEM1hNyMaPH4/c3FyEhoaCx+PBx8cHkZGRkon+qampUlt3ZGZmonv37pL7mzZtwqZNm/D6668jOjoaAJCeno73338feXl5sLW1Rb9+/XD16lXJ/ARlyZrcr8hcsqaelAGNm/Q/PNgWD64XSybyA4Cdy6t6QeI5Zurey1JZHA4HQyfYUkLWgH6eNjjxWT/8fisDm88mIquwHF+deohvo5LwXk8XjPNz0ciQYKVAiKtP8/DrzXRE3uOhQiCE5ctifJBxC20mjsO7Qd6wakH1qrTJ22+/DUD0bzEkJERq31aBQIA7d+5ItlQiRBexWoesqapeh8zAwFhyXNZqy7o2HFekNhnQuPpk1TU2KROrLzGrK7liGAabZz6VSspClrbGiBC7WkVjxcebkrJiAUK639aaGk9s16TiVwnwZ3wmdv/zFI9zXg1Zd3K0wJjuThjYwQ4edmYqS7wLX1bi2tM8nHuQjXMJ2SgoezW3s4uzBWZaFGF4yBtAbCzg66uSazY1bP/O1Uk8MrJ//368++67MDF5Nc/WyMgIbm5umD59ukJFvgnRJjq3ylKd5O0lq4uyZTDk7SUDVNNTBtQ/jCmewA+ISlqIhxgexpYgO016srd4daWsvSybWkJGFMM10Me7/i4Y59sa0Y9ycOh6Gv5OzMGDrCI8yCrCV6cewsHCGH09bNCttSU6OJjDy8Fcrp6rsooqPM4uQWJ2MRKyinAjJR/3M4ukduVqZWqEYV0c8F6PNuja2hKIi1PjqyXq9sMPP0hKXXz77bcwM2vaC4EIUTVKyNSEraFL4NUKTHUlZjWTq4u/5yPlgezYE26WQCgU1ppj1r67KU5F5DTZIUwiPz09DgZ52WOQlz1elFbgxN0snLnHw/WUfPCKyvFbXDp+i3vVO2rONUArMyO0MuOihZGoDhjDiHrc8koqkFvCR3G57D9c3G1M0d/TBsO6OKJn25bQ16P3jC5hGAYHDx7E//73P3jWs9sCIbqIErJ6cLOKIXAxljrW2F6y+qgyKQNU11sGSJfJ8PLLkUqu6hv0LsipwtezkjF/u+j54r0sGYaR6mUDmnbhWCIfa1MjTOrtikm9XVFeKcDNlBe4+jQPD3lFeMgrRvqLlyjmV6GYX4WUvLJ627Ix46KDgxk87czRvY0Veru3gr2Fcb3PIdpNT08Pnp6eyMvLo4SMNDuUkKmRor1kQNNOysRsxvbCIH4rvLz/TJJc7V+TUef5T+6WgcPhYESInSTp+voz6aFQGsLUPcaG+ujnaYN+nq/m/JTwq5BTVI680go8L+ajvEpUNoMDDgz0OWhlyoWtuRFszYwVXx1pagr07i26JVpr3bp1+PLLL7Fjxw506dKF7XAI0RhKyBrAzSwC30l68qwqeskam5QB8k/2V+UQJiBaBeU30ROA6C9YhmEQwrmGxLgSJNwsRkGOdG2qdl1b1Gqj5hBmUy8cS1TDjGsAM1szuKujLF2HDkAj98El7Js8eTLKysrg7e0NIyMjqcn9AGTWKCNEF1BCpmaKbKlUXUNJGdA0essAUYJmO643bMcBd4eeAPAqITPkcjDvu7a1niMuFCsewmzqhWMJIZqxZcsWtkMghBWUkMmhsb1kygxdAtqVlImZWHNRklMuuW/tZoHYMo9aqzVrDmES0mhxcYCfn06XvWgOgoOD2Q6BEFZQQqZiqhy6lJcySRmguiHM6rqMcsXfiXck9xkGiD34GMwEjzpXUap6o3NCiG4oLy9HRYV0KR1dq79GiBglZI0gq5esLvUNXTZmPpmYokkZoJ7EzG+iJzgcDu4dT0FOYiFyHxXiwsbbksdkUdV+mpTYEaL9SktLsXDhQhw5cgR5ebX/TxMIms7+qYSoEmubi2sbbmaR3OfK2ngcUH7z8fI8k4ZPgnwbksvSmA3KaxJP+LduI719TsZtxZJFZYg3S1dm03SGYXD2ZxXuDk8IUcqCBQtw4cIF7NixA1wuF3v27MGKFSvg5OSEAwcOsB0eIWpDCVkjtciubPgkORg+r7+zUpVJGcMwSDkaj/iwU0g5Gg+GYXC30EmliZmzj3Qcwiohjn95VTR8qaHduhRJzE7vz6V9LAlpAv766y98//33GDt2LAwMDNC/f38sXboUX331FQ4ePMh2eISoDQ1ZKkDW5P66KDrBH1DNJH+g4bIYz367jYff/gMA4EUnAQDcxvkAUN0wpu8EDwCinjFhlRCPL4jaSzwnKgZb1/BldQzDIO7nJGTE58HZpxV865mHVp/6toESq7n7ANFCnToBjx8DrVuzHQlphPz8fLi7i/7NWlhYSMpc9OvXDzNmzGAzNELUinrIVKCuXjJlhi5V1VMG1N1bVnBXOtkquJdV65zG9paJhy5Hb+gNPX3pt5m8w5dxPyfhwsbbSDyXjgsbbyPu56RGxVRfj5mXH9VB03rGxoCHh+iWaC13d3ckJycDALy8vHDkyBEAop4zKysrFiMjRL0oIVOQInPJ6sNmUmbVVTrZsuriKPO5qhrGrDl86ewt31y3jHjpxE1V89BkJWXDg20x4UvVDdkSFiQnAx98ILolWmvKlCm4fVu0EGjRokXYvn07jI2NMXfuXHz55ZcsR0eI+nAYTU3o0SJFRUWwtLTEYMtJMHBxqfV4XcOWda24rKsMRkMFY+UphyHPEKaYeAiTYRg8++02Cu5lwaqLI1zHess1FFjXMGZDQ4uSx2/nwdlb/qHH2IOPJSs0AWDQl95yDXXKq+YQZlmxACHdb6OwsFArltaL36faEq/aNYM6ZM3xd/7s2TPExsbCw8MD3bp1YzscQtSG5pApoa65ZHWVwVBmPhkgX40yeeeVAa9KY3A4HNGcsf/mjcmrrvll4qFFQPYcMfHwpaLJVPV5aOJETpVulLhTqQxCmgihUIiNGzfi+PHjqKiowODBgxEWFgZXV1e4urqyHR4hakcJWUPSs4HW9mprXhVJ2cvnxii/+jdePkyDiZcLrEb2rrMHStF9MGWpPozZ1TJT5tBi9/fb4fgXV8G7/wIOna0xelNv6OlJj5A31LNWPZFT1QT/msRJmVAoxLfzaaiLELasWbMGy5cvR2BgIExMTLB161bk5ORg3759bIdGiEZQQiaDeBS3ivmvQrSAX+sc/bRc8B3Nax03yijHS9vavWTcTKCslewEQlgu8/Crx1/Wn5AVX4xBwbFI0fcx9yGsqILVsB71PqeqtPZrUsat0law72gl6RkDAHsvK/w+5wqe/sMTxZT9Er/PuYI3vuol9dz4I0/wz7Z7AEQ9a1V8AXzebSfzOoqcq6hLJS64HPo3Yi+I5gdqyyi+OM6iItXMa9R6JSWvbnX0ZyL+XWvLe1QRBw4cwPfff4+PP/4YAHD+/HmMHDkSe/bsqfXHHCG6iOaQyZCeng4XGXPHSPOQlpaG1lpQOoHep82XtrxHFcHlcpGUlCT1njY2NkZSUpLOvVZCZKEeMhmcnJyQlpYGc3NzlQyLyVJUVAQXFxekpaWpbXKurlxDU9dhGAbFxcVwctKO1ZaaeJ+SpkXb3qOKqKqqgnGNkiWGhoaorFRN8W1CmjpKyGTQ09PT2F9kFhYWal8tpSvX0MR1LC0t1da2qmnyfUqaDm16jyqCYRiEhISAy+VKjpWXl+OTTz6Bqamp5NixY8fYCI8QtaOEjBBCCOuCg4NrHfvggw9YiIQQdlBCRgghhHU//PAD2yGo3LFjx7Bjxw7Ex8eDz+ejc+fOWL58OYKCgtgOjTRBtHSFJVwuF2FhYVLd83QN9q9DCCGq8s8//2DIkCE4deoUYmNjMXDgQIwaNQq3bt1iOzTSBNEqS0IIIUQJBw4cwNy5c5GZmSn1x+KYMWNgbm6OH3/8sdZzOnfujPHjxyM0NFSToRItQD1khBBCiBLeeecdCAQCHD9+XHIsJycHJ0+exIcffljrfKFQiOLiYrRs2VKTYRItQQkZIYQQogQTExNMmDBBav7bTz/9hDZt2mDAgAG1zt+0aRNKSkrw7rvvajBKoi0oISOEEEKUNH36dJw9exYZGRkAgIiICISEhNSqDfjzzz9jxYoVOHLkCOzs7NgIlTRxNIeMEEIIaQQ/Pz+MGzcOQ4cORc+ePZGSkiK148ChQ4fw4Ycf4tdff8XIkSNZjJQ0ZVT2ghBCCGmEadOmYcuWLcjIyEBgYKBUMvbLL7/gww8/xKFDhygZI/WiHjJCCCGkEQoLC+Hk5ISqqiocOHAA48ePByAapgwODsbWrVvx9ttvS843MTHR2R0XiPIoISOEEEIaafLkyTh58qRUCYwBAwbg4sWLtc4NDg5GRESEhiMkTR0NWRJCCCGNlJGRgYkTJ0rVI4uOjmYvIKJ1qIeMEEIIUdKLFy8QHR2NcePG4cGDB+jQoQPbIREtRT1khBBCiJK6d++OFy9eYP369ZSMkUahHjJCCCGEEJZRYVhCCCGEEJZRQkYIIYQQwjJKyAghhBBCWEYJGSGEkCZt+/btcHNzg7GxMXr16oXr16/Xee7u3bvRv39/WFtbw9raGoGBgfWer+x1qjt06BA4HA7GjBmj8msUFBRg5syZcHR0BJfLRfv27XHq1CmVXmPLli3o0KEDTExM4OLigrlz56K8vLzB10JUjCGEEEKaqEOHDjFGRkbMvn37mPv37zPTp09nrKysmOzsbJnnT5gwgdm+fTtz69YtJiEhgQkJCWEsLS2Z9PR0lV5HLDk5mXF2dmb69+/PvPnmmyq9Bp/PZ/z9/ZkRI0Ywly5dYpKTk5no6GgmPj5eZdc4ePAgw+VymYMHDzLJycnMmTNnGEdHR2bu3Ln1vhaiepSQEUIIabJ69uzJzJw5U3JfIBAwTk5OzNq1a+V6flVVFWNubs7s379f5depqqpi+vTpw+zZs4cJDg5uMCFT9Bo7duxg3N3dmYqKinrbbcw1Zs6cyQwaNEjq2Lx585i+ffvKfU2iGjRkSQghpEmqqKhAbGwsAgMDJcf09PQQGBiImJgYudooKytDZWUlWrZsqfLrrFy5EnZ2dpg6dapaXsvx48cREBCAmTNnwt7eHl26dMFXX30FgUCgsmv06dMHsbGxkmHNp0+f4tSpUxgxYkSDr4moFhWGJYQQ0iQ9f/4cAoEA9vb2Usft7e3x8OFDudpYuHAhnJycpJIUVVzn0qVL2Lt3L+Lj4+WKQ5lrPH36FBcuXMDEiRNx6tQpJCUl4dNPP0VlZSXCwsJUco0JEybg+fPn6NevHxiGQVVVFT755BP873//k+t1EdWhHjJCCCE6ad26dTh06BB+//13GBsbq6zd4uJiTJo0Cbt374aNjY3K2q1JKBTCzs4Ou3btgp+fH8aPH48lS5YgPDxcZdeIjo7GV199he+//x5xcXE4duwYTp48iVWrVqnsGkQ+1ENGCCGkSbKxsYG+vj6ys7OljmdnZ8PBwaHe527atAnr1q3D+fPn0a1bN5Ve58mTJ0hJScGoUaMkx4RCIQDAwMAAiYmJaNeuXaNfi6OjIwwNDaGvry851rFjR/B4PFRUVMDIyKjR11i2bBkmTZqEadOmAQC6du2K0tJSfPTRR1iyZAn09KjfRlPoJ00IIaRJMjIygp+fH6KioiTHhEIhoqKiEBAQUOfzNmzYgFWrViEyMhL+/v4qv46Xlxfu3r2L+Ph4ydfo0aMxcOBAxMfHw8XFRSWvpW/fvkhKSpIkewDw6NEjODo61krGlL1GWVlZraRLnAAytLOiZrG9qoAQQgipy6FDhxgul8tEREQwDx48YD766CPGysqK4fF4DMMwzKRJk5hFixZJzl+3bh1jZGTEHD16lMnKypJ8FRcXq/Q6NcmzylLRa6SmpjLm5ubMrFmzmMTERObEiROMnZ0ds3r1apVdIywsjDE3N2d++eUX5unTp8zZs2eZdu3aMe+++269r4WoHg1ZEkIIabLGjx+P3NxchIaGgsfjwcfHB5GRkZKJ66mpqVI9PDt27EBFRQXGjRsn1U5YWBiWL1+usuto4rW4uLjgzJkzmDt3Lrp16wZnZ2fMnj0bCxcuVNk1li5dCg6Hg6VLlyIjIwO2trYYNWoU1qxZ06jXShTHYRjqkySEEEIIYRPNISOEEEIIYRklZIQQQgghLKOEjBBCCCGEZZSQEUIIIYSwjBIyQgghhBCWUUJGCCGEEMIySsgIIYRoLT6fj+XLl4PP52v9dXTlGkQ5VIeMEEKI1ioqKoKlpSUKCwthYWGh1dfRlWsQ5VAPGSGEEEKIAqqqqnD+/Hns3LkTxcXFAIDMzEyUlJQo3SZtnUQIIYQQIqdnz55h2LBhSE1NBZ/Px5AhQ2Bubo7169eDz+cjPDxcqXYpIZNBKBQiMzMT5ubm4HA4bIdDNIRhGBQXF8PJyanRe9ZpAr1Pmx96j9ZWVFQkdasumriOrlxD296nipo9ezb8/f1x+/ZttGrVSnL8rbfewvTp05VulxIyGTIzM+Hi4sJ2GIQlaWlpaN26NdthNIjep80XvUdr06Xr6Mo1tOV9qqh///0XV65cgZGRkdRxNzc3ZGRkKN0uJWQymJubAwA6RnwO/RZcyfFOrXhyPb+f1eMGz4n+OQvHNj+T3H97viuWT30p89yDB8qwft2rcemFi8wwcXILuWKprw0ASrUb/dJd6j7DMNj7xSPciX4hOdZtgLXU/bfnu2LABEe5Yr1U4CnXeap0OTQaGZfTALz6/Td14jjXX/SHiZnon3LN95VY9Z8/wzC4+AsPT28Xw93bHK+/7yDVezHA5KncMdT33lTX+3bi5Ba13oPKkPVvUPwzUsV78PFvD3Dr+1jJfYfgQbAZ6adwOwXZon+rxdExKPwtEoD2vUfT0tJoAnkzUlRUBBcXF615nypKKBRCIBDUOp6ent6o10wJmQziDyf9FlyphCzxpSu62mQ1+Hzxh2N9hk1vDUOuHp7cKka77uYYPNkJ5qZPZJ778aem4BpzEHuzEn7+hgj5sIXC3f+y2gCgcLvnyzxgYlbj2P4MqeSre2BLfPKtFy78mCX1+uSJ+eKLDjAyVeilqcTrGwNx8cvzyLicpjXDf+I4TcwMJO+5V++rIggqGegZcODhayH18z+/P0OSiMSfz4chVw+Bwc6Sdq+hPQAgsEVSgzHU995U1/uWw+HARL/x/3XJ+jcojs+o0qiBZzes0yRvZFe2QunDdJh6tYbN6B5Kvbf0TIwBABbDBgAACn+L1Lr3qIWFhWIJWW4ucOQI8O67gK2tmqIj6qYt71NFDR06FFu2bMGuXbsAiF5nSUkJwsLCMGLECKXbpbIXMoiXBXc58qVUQiYmT1L2unWiUteW50OQDefLPOp8LHz2Q8RGPpfc9x9ug4+3eCl8jYsvOigVm6pUlFbgyOAftWY5uPh9+m7UJAxpnSz38xT9fTW192R970VVUcV78e5z+XqE6/OCJ/3XtvBlOdI/C9O696jC8cbFAX5+QGws4OurvgCJWuh6aY309HQEBQWBYRg8fvwY/v7+ePz4MWxsbPDPP//Azs5OqXaph4zUS54PPw9fc6kP+HbdFe+yZTsZ03YXX3SQ+48ARX9f4vdAU0jMtCUZI9JS8krRTQc/mEnz1Lp1a9y+fRuHDx/G7du3UVJSgqlTp2LixIkwMTFRul1KyJRw97ljg71kinxANkWKfPANnuwEAFJDP4qgD0DVEP8cG3rfKfv7Yjsx00QyRtQj7tkLdGvb+B5DQpoKAwMDTJw4ERMnTlRdmypriagdwzCI2FeGmzcr4a/knJyGKPOhx+FwEBjsjMBgxZ5HiZh6NPTHgLK/LzFVJ2aaeF9rmjqGK7VZThFt00N0x9q1a2Fvb48PP/xQ6vi+ffuQm5uLhQsXKtWu7hUIUSHx6iZZVPEfrqIi9pVh5fJinDpRjpXLixGxr0xlbZ8v89BoDwQlY+p18UUHtf+MVfV+ked9ran3Jr0v1YNXVK7YE8zNgaFDRbeENDE7d+6El1ftebedO3dWuigsQAmZWinzn3t9Hzw3b1ZK3Y+tcV9Zjf2wYxgG5/dnIHz2Q5zfn4H61oloIlFobq6s/AcPD9+T+XPXRFLW2PdPQ+9rGqrUftlFskv61MnTEzhzRnRLSBPD4/Hg6Fi7U8bW1hZZWQ0v+qsLJWQNqG/YQNO9ZP7+hlL3/WrcV5SqesWiDmTi8FfJiI18jsNfJSPqQKbM8ygRU4/0i89w85trSDxyX+bjmvi5i99Lyryf6npfa7rXlqhPTnGFYk8QCICiItEtIU2Mi4sLLl++XOv45cuX4eSk2Bzq6mgOmRxe8Mxh7VDMdhiS2mE1a4kpQ5UfdElx0j+bJ7eKpeYnUSKmGbl3cuA1XvZjmlxkcr7MQ6H5ZbLe12wkYqp6n9L8sdqyCxXsIbt9m8pekCZr+vTpmDNnDiorKzFo0CAAQFRUFBYsWID58+cr3S4lZI3U0IpLVX4QcjgcTJlqiilTlW9DHR90dZVR0KZEjGEYPP7tAdthNIptt/pr3yjyXmQYBlEHMpEUVwwPX/kL+4pVf581lJxVf1+fL/NAlIKf3aTpK3hZhfJKAYwN9dkOhZBG+/LLL5GXl4dPP/0UFRWi3l9jY2MsXLgQixcvVrpdSsjk1FR6yRpDXb0OssooaFMyBgCJR+5LbXOjTVxed4W9rwM6vNu5wXPlTcrEw9AAJMl29Wr+ipAnOaOhSd3HKyyHmw0L23AQomIcDgfr16/HsmXLkJCQABMTE3h6eoLLrV1IXhGUkCmgrqRMnrpkqqZoqQB1fuDVLKOgbckYAOTcyWE7BKUFhL4GI1P5t/qRJylraBhaWep4Hza2Nw9oWsOVuiqLEjKiY8zMzNCjRw+VtUcJmZYSlwoAgFMnREvKp0yV/Z8dlbNomF03O6RGyb/9kK5Txe4LmqLK3jyiPtmKlr4gpIkqLS3FunXrEBUVhZycHAiFQqnHnz59qlS7lJApSJleMnmHicR/6YfHVWFkb369vV6ySgXImltGyZh8OrzbGQJ+ldYOWyqqofdkY3df0KSavXlXfs9RqpeMqFdWoQIJWdeuQE4OYGWltngIUda0adNw8eJFTJo0CY6Ojir7v4YSsnoYZRuiyk1z15P+S190rK5eL39/Q0nPGND4EhiNpc3JGCAadvUc26nZJGQNaWw1f02q2ZuXllCKqAOZcveSaft7V1vwFFlpaWgI2NqqLxhCGuH06dM4efIk+vbtq9J2qQ5ZA7i82olOXUvS65s/Is9/+jX/0q+v8GvIhy0QutwcI98wRuhy80aVwCBEmw2e7ITWXtJ/uDy5pd0LcHSRQj1kT54Ao0eLbglpYqyt/9/euce3fP1//JX03upF9aqqRUtRLVpKDTWlxhib+0aL2Wb8xsrXbdRt5jLXuc7MbWPYmMtqaIuNuZcqeqG0SvWmRe9Nm5zfH5Fo0iTN5ZPkk/Y8H48+0nwu55x8cpLPK+/zvjSGvb094+1SQaYm2sgT5NVZsk1FVi9RqoDN2+wwYZKVTJMpjVyjKKK+WIY4HA56fCiZ8kMfPm/UoV8xKpVPev0aOHlS+EihsIxly5YhKioKZWXMlS8E6JKlUpjlmKDSRbkyRZpEXEr77URMZPbNplDqK+r6vNUXUWoIqGQho1BYzNq1a/Ho0SM4OzvD09MTJiaSxpNbt26p1S4VZEoiS5SpmpusLkdqab8dDkf5bOf6pnfjVIO+udWHxLBMwUQaCV1jSD5vDZUXJZWo4gtgYkQXZiiGzdChQ7XSrkEIsi1btuD7779HTk4O/P39sWnTJnTt2lXu8Rs2bMC2bduQmZkJBwcHDB8+HCtWrIC5ublOxquPvGRswJBFmSEnhmUamkaCwjQmRhzwCZBXXAk3Owt9D4dC0YhFixZppV3W/1Q5dOgQIiMjsWjRIty6dQv+/v4ICwtDXp7sRJ4HDhzA3LlzsWjRIiQnJ+Pnn3/GoUOHMH/+fI3HooqDPxMo4wNGCMHun0sxdcor7P65FIQQ8T5V6gkyha7qJTINSTZc5+GkAhdG25OVFNYQIYQgdm8Wtk9PQezeLInPhjZoiD/ClMXRWpjBXOlISzc3YO1a4SOFwkJevXqFnTt3Yt68eSgsLAQgXKrMyspSu03WW8jWrVuHyZMnY8KECQCA7du3Izo6Grt27cLcuXNrHX/58mX06NEDY8eOBQB4enpizJgxuHbtmsp9W+YBlc01G780TBd5ViVBrK4QvT5DsJaJxlollTqhIWNISWEVYciWvsYuxfWqwLiLjTlyynnK+5E5OwORkdodFIWiJomJiQgNDYWtrS0yMjIwefJk2Nvb4+jRo8jMzMS+ffvUapfVFjIej4f4+HiEhoaKt3G5XISGhuLKlSsyzwkODkZ8fDyuX78OQJgx99SpUxg4cKDcfiorK1FUVCTxJw9lrWS6iriSlSC2Jvqwkono3ThV/MdGao6r7/im+HCmhx5HUzeqzFNlkPe+9B3fFKPmt0Dgew4YNb8Fq5PCKqK+WPrqA842QneRHGUF2cuXwO+/Cx8pFJYRGRmJiIgIPHz4UMIVauDAgfj333/VbpfVguzFixfg8/lwdnaW2O7s7IycnByZ54wdOxZLly7FO++8AxMTE7Rq1QohISEKlyxXrFgBW1tb8Z+7u7t4n6XsbjRCGcuRaLll+OTqWkuRNQmUSo0hK1WGPkWZCLaJM+lxcDgchIxld9oCRfOUSUQO8p9v8EFouBvrHfqlEX12cjMkl8dkWfrYMh9loUrAENtxtlVRkKWnAyNHCh8pFJZx48YNfP7557W2u7m5ydUmysD6JUtVuXDhAr777jts3boVQUFBSEtLw/Tp07Fs2TIsXLhQ5jnz5s1DZA3zeFFRkcKbnbJpMDRx7lc2a78oIWz8zSoEvCkyLotQyzTW5CWTvgkysbRJCEHq4fvIS8yDk58T2oxsL1NIsPkGXBeqzlNdwqbIzJqfHQBwb2uF4GFOOrH0dXDIZtQ6Xl+WLp3e+JBl03qWlHqAmZmZzBWKBw8ewFGDChOsFmQODg4wMjJCbm6uxPbc3Fy4uMh2ZF64cCHGjRuHTz/9FADQoUMHlJaW4rPPPsM333wDLre2UdDMzAxmZmZyx2GZA5TV4TetagqMupCVtV9WrUpRglhZ+6QRWcrYIsxEyBJJqoq01MP3cXO90E9QVCTcZ5Rvnf0YEnXNU32ijL+WPEst0/NR+rPj7GlhML5jsqgPosxF1SVLCoXFDBkyBEuXLsXhw4cBCO/DmZmZmDNnDj766CO122X1kqWpqSkCAgIQFxcn3iYQCBAXF4fu3bvLPKesrKyW6DIyMgIAlaOsXtz9T+45snzJVKEuwaFK1n5FkZayCLVMY8UypiJqLnFK/8kiL1Ey6jb/zXO2LZXWVxT5a4nmm7x5quxcVDZqUvqzU1dQAtNzg0Zb1sbJRhRlSQUZxfBZu3YtSkpK4OTkhPLycvTu3RteXl6wtrbG8uXL1W6X1RYyQOg8Fx4ejsDAQHTt2hUbNmxAaWmpOOpy/PjxcHNzw4oVKwAAgwcPxrp169CpUyfxkuXChQsxePBgsTBTlpwr0eAam8DRv5faVjJ1ly1rZh4fGFSpsFalupGWbLWY1YWsG2hVEJD5VrejW5DhW8QMCXmRmTXFlqJ5qsySurJRk+pm7Wczhm4lE1nIcosqwBcQGHHrWM62sAA6dRI+Uigsw9bWFjExMbh06RISExNRUlKCzp07SwQgqgPrBdmoUaOQn5+PqKgo5OTkoGPHjjh9+rTY0T8zM1PCIrZgwQJwOBwsWLAAWVlZcHR0xODBg9VWraXZGXD078XIa1EFVbL2y4q0VGYJU4ShCrOa1MebsCEh6/pLW77qmqd1iTJZVjhZmfnVydrPdFJjpn3JAKEo45dV4hmjreoGh0Zm4HKAagFBQUklnGzqSNLdti2gZvkZCkVXvPPOO3jnnXcYa4/1ggwApk2bhmnTpsncd+HCBYnnxsbGWLRoEWOZdK1cPeXuU6XGpSyYykkWGGgitjgAipc3FaGuMGODQzctnaNf5F1/Qgj27CrDzZtV4FdLLjGqOk8NLT+aNkSZoWJsxIWjtRlyiyqRU1RRtyCjUFjGDz/8oPSxX331lVp9GIQg0xcu3QfBwa+nSucwuWypLMpGWipLTcuGMuLMkBNw1gfaNckBYKrvYcik5jIlAIQNMIOxMUeteaptK6g2Sn9RUfYWF1sL5BZVIvt1Bfya1XHw7dtAt27A1avCpUsK5Q3Lly9HdHQ0EhISYGpqilevXtU6JjMzE1OmTMH58+fRqFEjhIeHY8WKFTA2fit5Lly4gMjISNy/fx/u7u5YsGABIiIi5Pa7fv16ief5+fkoKyuDnZ0dAGHmfktLSzg5OaktyFjt1K9vHDr0kLD0aCMnmbIoEkaiSMvN2+wwYZIVo9YpZQIAaAJO/cJ06SSmiC3zqrVMaWzMUXueGmp+NOrkL8RVlUhLQgAeT/hIodSAx+NhxIgRmDJlisz9fD4fgwYNAo/Hw+XLl7F3717s2bMHUVFR4mPS09MxaNAg9OnTBwkJCZgxYwY+/fRTnDlzRm6/6enp4r/ly5ejY8eOSE5ORmFhIQoLC5GcnIzOnTtj2bJlar82Ksj0jCGUFwIUCzNVo9ooDQdrP0nrkKJlSkP2YawLKsoAlzfJYZUun0ShyGDJkiX4+uuv0aFDB5n7z549i6SkJPz666/o2LEj3nvvPSxbtgxbtmwBj8cDICzB2KJFC6xduxZt27bFtGnTMHz48FpWMHksXLgQmzZtQps2b+/fbdq0wfr167FgwQK1XxtdsqTIpKbvT+Cb5SUOhyPTz0x6Kendca6I3ZvFiiShFOZQ1VeQEAJCCJr5WIHDASJGcmUuU7JJiGlj2bIhUVlZicrKSvHzmskzXd8IsuevlCwwTjF4pJOn6iKX4pUrV9ChQweJCj9hYWGYMmUK7t+/j06dOuHKlSu1IiLDwsIwY8YMpfrIzs5GdXV1re18Pr9W3lRVoIJMRzDhRxZb5qWz/GF1pdKoGREn7dAduzdLwqfswfXXmLK5LRVlWuJFdDzIF55av76q+grG7XuOwysyxM8fVLVAXHnD9S1sCP5kK1aswJIlS2Tuc7cXivGnL8t0OSSKHpGuJLJo0SIsXrxYq33m5OTILLco2qfomKKiIpSXl8OijnQrffv2xeeff46dO3eic+fOAID4+HhMmTJFo9QXdMmyHqFqglhF1FW0HJCd0JMQgstHJZO03o4tRNy+52qPhaKYnL3nkHr4vtb7UdVXkCnfQmUTwmqKqJ/kxceRcuieVvqp70uX8+bNw+vXr8V/T58+Fe9zb/xGkBUqYSFr2xa4d0/4SDFYnj59KjEf5s2bJ/O4uXPngsPhKPxLSUnR8ejls2vXLri4uCAwMFBs9evatSucnZ2xc+dOtdulFjIWwFT6C3UTxMpC2VQa0rmj4vY9x9OU0lrHycsZpU+kl6Z4pTwAV/UzGA3JT8yDzyjVzlF13qmadoKpNBW6iuKVqIH5ph/p8ltMIBJl9dFapmhJqvkbC9mLkkqU8aphaarg9mNhAbRvr40hUnSIjY0NbGxs6jxu5syZCiMcAaBly5ZK9eni4oLr169LbBMtI4pKLrq4uMgsyWhjY1OndQwAHB0dcerUKTx48EAsFH18fNC6dWulxigPKsgMDEXLlpomiK2Juqk0pK0iItjk6F8ffYQc/Zy03oeqaSeYSlOhbEJYTZHuRx2RqwoNYQmzJraWJrA2N0ZxRTWevSxHa2cF3wlPngDLlgELFwIeHrobJEUvODo6alSUuybdu3fH8uXLkZeXBycn4fdiTEwMbGxs0K5dO/Exp06dkjgvJiZGbklGebRu3VpjEVYTKshUoK7SSfqGqQSxgGpFy2sibRVxb2uF4GFOrMmcXx/FWKcvA9BmpPatCaom32UqWa+uEsJK96MLkdvQRFlze0vcf16EzIIyxYKsoAD4+Wfgyy+pIKNIkJmZicLCQmRmZoLP5yMhIQEA4OXlhUaNGqF///5o164dxo0bh9WrVyMnJwcLFizA1KlTxdbbL774Aps3b8bs2bMxceJEnDt3DocPH0Z0dLRSY+Dz+dizZw/i4uKQl5cHgUAgsf/cuXNqvTYqyOoRTCeIVZaay5ayrCJsceavj2IMALw/aseaa6wNdFUWS7of48G6WTJrSKLMvbFQkFHHfoq6REVFYe/eveLnnd4kDj5//jxCQkJgZGSEv/76C1OmTEH37t1hZWWF8PBwLF26VHxOixYtEB0dja+//hobN25Es2bNsHPnToSFhSk1hunTp2PPnj0YNGgQfH19Gfv+pYKsHqGuVUtdaqbGsPbLEosvNpYwqkuMEULw8EiSjkbTMBA5yV/+Mx8cAMEfOqkl0HU1p2r380BnIr6hiLLmTVRw7KdQZLBnzx7s2bNH4TEeHh61liSlCQkJwe3bt9Uaw8GDB3H48GEMHDhQrfPlQQWZksharlSljmV9jK6SKIvzl9AZmo0lk5S5qaYevo/bW+N1MJqGg3TaC5HDPBvnCBuoz87+ItwbCx2mMwuphYxiuJiamsLLi/n8iTTtBcNI17Gsz0gHERhyyaS8xLy6D6KohKwAD0ObI0xEP6tKffzxJqLZm0jLZ3UtWTo7A3PnCh8pFJYxc+ZMbNy4kfHUONRCxgL08aXPBNJBBGyKpBSh7JKTk58TMuPStTyahoW0kzzAzjlSF/rI3l9frWWi1BeZhWUghMhfvnZzA1as0OHIKBTluXTpEs6fP4+///4b7du3h4mJZADd0aNH1WrXICxkW7ZsgaenJ8zNzREUFFQrx4g0r169wtSpU+Hq6gozMzO0bt26zvVkRSi7XNmQrGOAMIggarE1Br1vjqjF2nO21gVtRrZHpy8D9D0MnaLtHwJ9xzfFyHmecG9rBfe2Vhg1v4XBzhF9/Wiqb9YyNzvhkmUZj4/CUp78A4uLgQsXhI8UCsuws7PDsGHD0Lt3bzg4OMDW1lbiT11YbyE7dOgQIiMjsX37dgQFBWHDhg0ICwtDamqqOMdITXg8Hvr16wcnJyf88ccfcHNzw5MnT2BnZ6dW/5r6jgHMfqnqqnSSMkgHEcSWGW6kH4fDgfdH7agfGYNwOBz0i2iGfhHN9D0URtBXncv6ZC0zNzGCi405cooqkFlYhiaN5NQ1fPgQ6NMHiI8H3pSmoVDYwu7du7XSLustZOvWrcPkyZMxYcIEtGvXDtu3b4elpSV27dol8/hdu3ahsLAQx44dQ48ePeDp6YnevXvD399fq+NU1zpmqMuVsmCTWKQopj7NO12iz+vWwSEb7Zrk6K1/pnC3F1rJnr6kkZYUw6W6uhqxsbH48ccfUfzGkvv8+XOUlJSo3SarBRmPx0N8fLxEsU4ul4vQ0FBcuXJF5jknTpxA9+7dMXXqVDg7O8PX1xffffcd+Hy+3H4qKytRVFQk8QcAZTLyQlLrmGIMYYyGirx5qipUjGkGvX6aIS4yTiMtKQbKkydP0KFDB3zwwQeYOnUq8vPzAQCrVq3CrFmz1G6X1YLsxYsX4PP5Mquyi6q2S/P48WP88ccf4PP5OHXqFBYuXIi1a9fi22+/ldvPihUrJNZ/pSvUi5AnxuRZx+oSY/X1i51Noqw+XWNl56ki6tP10Cf0OqrP2yLjVJBRDJPp06cjMDAQL1++lKh9OWzYMMTFxandLqsFmToIBAI4OTlhx44dCAgIwKhRo/DNN99g+/btcs+ZN2+eREX6p0+fKt2frhz52SRylMHQxmsIaDJPASoimIZeT/UQW8gUpb4wMRFGWpqoX/6NQtEWFy9exIIFC2Bqaiqx3dPTE1lZWWq3y2qnfgcHBxgZGcmsyi6q2i6Nq6srTExMYGRkJN7Wtm1b5OTkgMfj1bqAAGBmZiaucSUPppcqVfkyN1RxU7OkEkVzlJmnsqDCQXuIrm19LculDWqmvpBLhw7As2c6GhGFohoCgUCmG9SzZ89gba1+ah9WW8hMTU0REBAgYQIUCASIi4uTW5W9R48eSEtLkyj2+eDBA7i6usoUY8qgz6XKusQYIQS7fy7F1CmvsPvnUsYT1WkKG8RkQxYkDeW1i8o0bZ+egti9WTr/HDSU68wEIqf+568qUM0X1HE0hcI++vfvjw0bNoifczgclJSUYNGiRRqVU2K1hQwAIiMjER4ejsDAQHTt2hUbNmxAaWkpJkyYAAAYP3483NzcsOJNEsEpU6Zg8+bNmD59Ov7v//4PDx8+xHfffYevvvpKrf5VFWN1oY4Yq1kzMvBN0XBRQsWa5YtESVonTLJSa2zaQvQ69Gkt01fKAn2iT5GgqRBXda7E7XsuLs0kSkar6xJNmlrLCCFIPXwfeYl5cPJzQpuR7etl0Xhna3OYGnHB4wuQ/bpCvIQpwd27wHvvAX//LbSWUSgsYu3atQgLC0O7du1QUVGBsWPH4uHDh3BwcMBvv/2mdrusF2SjRo1Cfn4+oqKikJOTg44dO+L06dNiR//MzExwuW8Nfe7u7jhz5gy+/vpr+Pn5wc3NDdOnT8ecOXMYG5MiMcZUVGXNG5oi0SVdvij+ZpXOiourir6XMBuKKNOHEGPaEiqrPUVzR7pM06PbxXorcK/uPEs9fB83118DAHHVCJ9RvoyOjQ1wuRw0a2yBxy9K8bSwTLYgq6oCsrKEjxQKy2jWrBnu3LmDgwcPIjExESUlJZg0aRI+/vhjCSd/VWG9IAOAadOmYdq0aTL3Xbhwoda27t274+rVqxr3y3OuAhdGdR/4Bm1FVSoSXdLliwIC1XeCVWSJY+p8Ksq0C9NijBCCuH3PkXarGF6dhdUYRO+ptGjSdP7URc3+pOeQdJkmfZdoUmeeSddTzU/Mg88oJkfFHtztLfH4RSkyC8sQrO/BUChqYGxsjE8++YTZNhltDcCdO3dw8uRJ2NvbY+TIkXBwcBDvKyoqwowZM+QmdTUE9OE3pkh0RUwU/rqMv1mFgDc3QXXRdPlT2fOpKGMebVnFpJcC25i+kDsndLl8Li3ORCWZHt0uRqtO7CjjpeoSpnQ9VUc/GYkQ6wlvk8PS1BcUwyQ1NRWbNm1CcnIyAGHw4LRp0+Dj46N2m4w69Z89exZdu3bFwYMHsWrVKvj4+OD8+fPi/eXl5di7dy+TXeoUfTnxS9eMrCm6ROWLNm+zw4RJVhpZJGRZ4nR5vi7p3Ti13jhiv2P3UGttSy8FKnpP9fX+h1qmoZ/VI4SGu+HzDT4IDXdjle+VsvOszcj2CPw6CB59WyDw6yC0GdleyyPTH29zkdFs/RTD48iRI/D19UV8fDz8/f3h7++PW7duoUOHDjhy5Ija7TIqyBYvXoxZs2bh3r17yMjIwOzZszFkyBCcPn2ayW70gi6d+KVhUnQpIlBquVPV5U9VzmdD9CVAo+PqYlC3Sonnit5TTeePpoRaprFmXkmjzDzjcDjwGeWLnsvfhc8oX1aJSqYRpb54Ii/1hbc3cP688JFCYRmzZ8/GvHnzcOXKFaxbtw7r1q3D5cuXMX/+fMyePVvtdhldsrx//z5++eUXAMIvl9mzZ6NZs2YYPnw4Dh48iC5dujDZnc5Q14nf0HKNabL8SQiBgBA4u3BRXkbQrbsJwidYSOyX9i/S99KliN6NU0EIwbZ9FXUfzEIuHMjGgMnNtOKvRaTmRPgEC+z+uVSmn1jEREsQAhz5oxwFLwT4/VAZCAEmTGLWl0zZsbNhbtWkPi6Vq4ung3Ap+3F+CQghteeHtTUQEqL7gVEoSpCdnY3x48fX2v7JJ5/g+++/V7tdRgWZmZkZXr16JbFt7Nix4HK5GDVqFNauXctkd3pHGxGV+kRkiRMFDIhynCnjpL1nVxm+XfK2qOrZMzzs3V0u9iFie3qOuH3PcXtret0HspCja5/AxIzLSJoH6bkoPSd2/1xa632MmGgpFtv8aoKk+9UAgNxcYNmSYnA4+nmv2SrMKEBLRysYcTkorqhGTlEFXG2lItOysoDNm4Fp04QZ+ykUFhESEoKLFy/Cy0vyu+XSpUvo2bOn2u0yKsg6duyI8+fPIyAgQGL76NGjQQhBeLie4tA1QNt+Y2wRY7JQRURJ+w8BktGg8iJF2WIlk/aVMjSYSPOgzFyU7Sf2dp7IQt+pWNgyxwBqJRNhZmyElg5WeJhXgpSc4tqCLDcXWLkSGDGCCjIK6xgyZAjmzJmD+Ph4dOvWDQBw9epV/P7771iyZAlOnDghcayyMCrIpkyZgn///VfmvjFjxoAQgp9++onJLrWKnXMJAHaWqtF2igFAtRxn0pGggKQPEZPpObSBdNoEQ0OTNA+q/CiQ9T7KEuM10fS9ZmKus0mUUYS0drHGw7wSPMgpRp829TeilFL/+PLLLwEAW7duxdatW2XuA4QrDLJKLMmDUUE2bNgwDBs2DOHh4Zg0aRJ69eolsX/s2LEYO3Ysk13qBTYsVepiCVAVEVXTfwgE+GiEuYQPmiL/NDbcLPuOb4qqSgGOrn2i13Gow4czPdRO86DqHJT9PpZJzJP+YaZ49lQAcICPhltolIoFYG6us2GeAdRKJqKNszWikY3UXMO2TlMaHjVLMzKJVhLDvn79GqGhofDw8MCECRMQHh4OtwZidtbVUqUuMvSr4uTP4XAw8VMrTJj01p+IwykTWzOkfZHYBofDQchYV4MUZCFjXdWyjva1eIjdP6tmeZL1PsqaJ0xaaw2pGgVFeVo7C626D6ggoxgwFRUVMDc3Z6QtrRQXP3bsGLKysjBlyhQcOnQInp6eeO+99/D777+jysBLYahrHWO6+LEuUgxIp9sAUGchc5E149RfFVi6uBh7dimX+JHNvnT1kVDLNLXfK2k4HA4iJlqKly/37CpjtLi3vtNpSKPvQub1BR8XoSB7mFsCvkDqGjZpAkyaJHykUFgGn8/HsmXL4ObmhkaNGuHx48cAgIULF+Lnn39Wu12tlU5ydHREZGQkIiMjcevWLezevRvjx49Ho0aN8Mknn+DLL7+Edz3LMaPIOlY747m1RkuMTGboB5Tz01Fm6YhaM9hNTeHL5HulzSV0Tee65Ny+g2aj/TSy4LGhkHl9wN3eEuYmXFRUCfCkoBQtHRu93enhAezcqb/BUSgKWL58Ofbu3YvVq1dj8uTJ4u2+vr7YsGEDJk1S74tUKxaymmRnZyMmJgYxMTEwMjLCwIEDcffuXbRr1w7r16/XdveMoonvmCoZz5WB6WSxylhLlMnELm3N6BxgUqdVjaIbZJXkqokmlidVsvSL0qkoOyc0nevScztu33OVzpdGViFziuoYcTnwdpKzbFleDty/L3ykUFjGvn37sGPHDnz88ccwMnpb79rf3x8pKSlqt6sVC1lVVRVOnDiB3bt34+zZs/Dz88OMGTMwduxY2NjYAAD+/PNPTJw4EV9//bU2hsA6pKP49L3sIo0y1hJlnPylrRmEECxdLMxPVpflhC1O1/UReSW5AGasrKoEgOg6J5303NY0RYimhcypQ/9b2rhY427Wa6TmlGCAb40dyclAQAAQHw907qy38VEossjKyqqVgwwQOvtr4palFUHm6uoKgUCAMWPG4Pr16+jYsWOtY/r06QM7OzttdK8X6nLmF0XBlSRmM7LEyDTqiC1Zr0Ha6XvqlFcS++kSpu6pqyQXE++HKuJO18va0nNbkxQhAFhZyNxQaUMd+ykGSLt27XDx4kV4eHhIbP/jjz/QqVMntdvViiBbv349RowYoTDywM7ODunpymVG37JlC77//nvk5OTA398fmzZtQteuXes87+DBgxgzZgw++OADHDt2TNnhawUOh4PQcDeEWurfBC/LX0wdsaUMbM8/Vp8ghCBu33Ok3SqGV2ehUOhn9UgnfasyN3Q9J0Rz+dQ1M0YElPizbHh5rllH6zeO/Sk5RXoeCYWiPFFRUQgPD0dWVhYEAgGOHj2K1NRU7Nu3D3/99Zfa7WpFkI0bN46xtg4dOoTIyEhs374dQUFB2LBhA8LCwpCamgonJ/nJBDMyMjBr1iyNyhjUV+QtGTFhLZEWe6J6lkwFH2gLQgguHGAmv5y+kOVs3m+KcJ8uEgkr2w/TASl1IRKL7mP0vxxOlyslEVnIMgrKUFHFh7mJUR1nUCj654MPPsDJkyexdOlSWFlZISoqCp07d8bJkyfRr18/tdvVWpQlU6xbtw6TJ0/GhAkTAADbt29HdHQ0du3ahblz58o8h8/n4+OPP8aSJUtw8eLFWvU11YGpZLBsQFtLRoQQTPnsFc6crgQgLfY0b1+bxO17bpA5yGoi7WxekpgNwA5A3X5bTAk2ZfzD9JGTjvomshNnGzPYWpjgdXkVHueXol1ToY8xOBzA1FT4SKGwkJ49eyImJobRNrUeZakJPB4P8fHxCA0NFW/jcrkIDQ3FlStX5J63dOlSODk5KR16WllZiaKiIom/+oy28jrt2VUmFmMiVIkmlb5p6jLfU9ot9r/n8ubphQPZEAgEEFRLZo+u+b7WFQXJVE4yVaItKRQOhyPbj6xTJ6CyUvhIoTQQWG0he/HiBfh8PpydnSW2Ozs7yw0tvXTpEn7++WckJCQo3c+KFSuwZMkSTYaqV1S1bjC1ZCTd740bvFrH3LzBw66dpYiYaIG9u8tVssDoMt+ToJr96TjkzdOja58g/U4xbscWireFDTCTeF+l/bYepVWhW5dcNLbjomUrY6SnS9Zb++Owau+VvH7Y4DPIFuuYpsuVhBA8PJLE0GjYQ2uXRrieUYiUHOrYT2EvjRs3Vvp7sLCwsO6DZMBqQaYqxcXFGDduHH766Sc4ODgofd68efMQGRkpfl5UVAR3d3fGx6etbPSqphFgaslIut+wAbULsefmCrBsSTGuX+PJXMoUIeumKSvfk7YcqTlG7F8aUTRPU669ljjW2Jgj8eVRU4Q/SqtCSopQgOXm8MX/1yQpqRpJSdUqp6XQtX9YQyL18H3c3hqv72EwjkwLWXIy8PHHwP79QNu2ehoZhfKWDRs2iP8vKCjAt99+i7CwMHTv3h0AcOXKFZw5cwYLFy5Uuw9WCzIHBwcYGRkhNzdXYntubi5cXFxqHf/o0SNkZGRg8ODB4m2iIqDGxsZITU1Fq1atap1nZmYGM7PaYkLfKGv50ld2fOl+jY2Btu2MkZxUXevYxDuqj1HTfE+q4B1gg1tnCrTWPhMomqdmlkYoL34rrKQtUzVFePeueTLbaNfeGC1aGCP9sVCMiVBlPrGtZqky1jFZ0anaCHjQlLxE2e+bodPGReg3llrTQlZeDty+TRPDUlhDePhba8BHH32EpUuXYtq0aeJtX331FTZv3ozY2Fi186uy2ofM1NQUAQEBiIuLE28TCASIi4sTq9Ka+Pj44O7du0hISBD/DRkyBH369EFCQoJGVq+7L1zVPlddlPXr0Vetv9r9mmL4CAuZx/r5yx+jvJtm3/FNMWp+CwS+54BR81toNd9T3/FN8eFMj7oPZCn9Jrhi1PwWGPS+OaIWW8u0TIky5BOBjAYADB9hgc3b7DB8pOR7yIZlR20iWhqPP/0Ch75L1ziTv7Zw8pMfVW7IiCxkWa/K8bqM+hxS2M+ZM2cwYMCAWtsHDBiA2NhYtdtltYUMACIjIxEeHo7AwEB07doVGzZsQGlpqTjqcvz48XBzc8OKFStgbm4OX19fifNFyWelt7MNWdYwZS1f+lomktXvrp0lEsc4u3Dx2edWYh8y6TEqsmDoMt8Th8NByFhXg4y0/HCmB/pFNBNeLxl57kRz64/D5RKWL2trwM3NCC29jBEYaCp+T+rLsqO8uSVtEZMO6NDG0jgT6S7ajGwPfmV1vVu2tLU0QUtHKzzOL8X1jEL0a+dc90kUih5p0qQJjh8/jpkzZ0psP378OJo0aaJ2u6wXZKNGjUJ+fj6ioqKQk5ODjh074vTp02JH/8zMTHC5rDb0KYUsPzBlHaT1tUwkq98jf0hGWTax52Lip0L/I+lj2eJsbeiEjHVVuMRWc27VpFdvc2zeZldrO9uWHZlGOlikU6i9xH5tLo1rAofDgfdH7eqdIAOAbi2b4HF+Ka4+LqCCjMJ6lixZgk8//RQXLlxAUFAQAODatWs4ffo0fvrpJ7XbZb0gA4Bp06ZJrNXW5MKFCwrP3bNnD/MDYhCR9WLHj6US2+NvVmHTVlvx/4ZiqaglC+ToBCrGdIe0pVVEfVmKlGVdjiv3lnu8dLAI15iDUfNb0FJIeqRbyyY4cC0TVx+/8eNs0QI4fFj4SKGwjIiICLRt2xY//PADjh49CgBo27YtLl26JBZo6mAQgqw+I896ERBoYpCWio9GWCBpydvX89Hw2j5lVIzpFmlLa7t2xhg+0sIgBL4yyLIuu4+Rf7x0sIhXZxtaCknPdGsptFImZRfhVRkPdo0bAyNG6HlUFIp8goKCsH//fkbbpIJMz0hbL1xduZj8uZXB3iwnTLIEhyPfqkfFmHaJLfOqlV5Flk8YG6MI1UX6M3Tqmhk+VyDIaHFw9uFkbY5WjlZ4lF+K6+mF6O/AEaa8+PhjwJkuYVIaBlSQ6Rlp68Wnnwn9raZ9+Vpmqgtd1SRUF0VWPSrG9IMhWlpVQfozJO0DJu3ETwjBo9slOktxQetXKke3lk3wKL8UVx8Xon9lBTBzJhASQgUZpcFABZmekbZeEEKwdLEwUlFWUk5Vk8CyBUMQY5deeQO4qu9hUFSk5meokZ9rLYuXrIoPNf/XVvUHimp0b9UE+69l4srjAsCN/d9pFArTGH54og7RRi4ykfVi8zY7TJhkhfh4yaSq0rUADbFWIJvF2D8v24j/KIaJ6DM0dG0gQsPdalm8pJ34a/LoNi3XwxaCWgjTBaTkFKG4nP3faxQK01BBxjLqSvIqvb+6mmi16LamsFWMURHWcPDqLD+NhbZTXDAxxwghSDl0D/9+c65e1rIU4WhtBi+nRiAEuPv8dd0nUBocGRkZmDRpElq0aAELCwu0atUKixYtAo8nWUc5MTERPXv2hLm5Odzd3bF69epabf3+++/w8fGBubk5OnTogFOnTunqZciFLlkq4EV0PMofZcOqrTschnTRia9WXUk5IyZa4trVt3Uhz5yuxJ5dZQaxbMkWqBCrfygS/tJO/IQQPE4o0btDPyEEqYfvIy8xD05+Tmgzsr3M75jUw/dxc/01AEBmXLquh6lTurdsgrS8Etwo5CN48GDA1lbfQ6KwiJSUFAgEAvz444/w8vLCvXv3MHnyZJSWlmLNmjUAhDV++/fvj9DQUGzfvh13797FxIkTYWdnh88++wwAcPnyZYwZMwYrVqzA+++/jwMHDmDo0KG4deuW3CTyH374odLjFKXCUBUqyBSQs/ccAOD1pWQAgOMHXbXeZ10O2BwOB0bGkl/auqpdqSpss45RIdYw0WXFh5rUNd9kCS2fUbVvBvW1hqUsurVsgl+uPsHf5VaYfuKEvodDYRkDBgyQKFnUsmVLpKamYtu2bWJBtn//fvB4POzatQumpqZo3749EhISsG7dOrEg27hxIwYMGID//e9/AIBly5YhJiYGmzdvxvbt22X2bauDHwdUkClJacoznQgyZVA2gz/lLVSM1V/YJvwB5eabtNDKT8yDz6jaxzn5OdV7y5iIoDf5yNKyXuJVRhbs3JwAE/r9RpHP69evYW//ttrGlStX0KtXL5iamoq3hYWFYdWqVXj58iUaN26MK1euIDIyUqKdsLAwHDt2TG4/u3fvZnzs0lBBpiRWPs30PQQxspY12Z4OQ59QMUaRhXQ6DKZSYCg736SFlqOc4uFtRrYHIBRs9m3sWV06qbKyEpWVb8unFRUVKTi6Ng6NzNDG2RrGd27DrsVQID4e6NyZ4VFSdIX0+29mZgYzMzPG2k9LS8OmTZvE1jEAyMnJQQupCg+iUos5OTlo3LgxcnJyxNtqHpOTk8PY2NSBCjIFuIS/i/LHObDyaQaHIV30PRwxspY1d/9cyqp0GGyxWlAxVr/RZJ7JSoehyxQYNYWW4xsfMllwOBz4jPKFzyiAV8pjtSBbsWIFlixZolEbQzo2xak7txkaEUWa7Nfl+C+tAJfTXuDOs1eoqBKgii8AX0Dg0cQSAR6N0bl5Y3Rv1QR2lqZ1N6gAd3d3ieeLFi3C4sWLax03d+5crFq1SmFbycnJ8PHxET/PysrCgAEDMGLECEyePFmjcarDH3/8gcOHDyMzM7NWUMGtW7fUapMKMgU4DAqAkSVzal6byEqHwUa/Ml1CxRhFEdLpMB7dLtbYz0yVOVdTaNUX5s2bJ7EUVFRUVOumXBcjAprhzC9CS+WTglJ4MDrChklJZTVOJDzHoRuZuPNMfgRrQSkPtzJfAUiHqTEXQ/ybYnx3D/g1s1Or36dPn8LGxkb8XJ51bObMmYiIiFDYVsuWLcX/P3/+HH369EFwcDB27NghcZyLiwtyc3Mltomeu7i4KDxGtL8ufvjhB3zzzTeIiIjA8ePHMWHCBDx69Ag3btzA1KlTlWpDFlSQ1RPY5lcWapnGqJVM1eWlhiTGLhzIxoDJzYTO61Jlkyjyka5pqWkKjIY05+TBxJKUk405unoKfYLO3M/FZ/2YGFnDQyAguJpegD9vZSH6bjbKeHwAAJcDdGhmhx6tmqBrC3vYWZrCxEj4XZqSXYz4zJe4nl6ItLwS/BH/DH/EP0OAR2PMGeCDri3sFXVZCxsbGwlBJg9HR0c4Ojoq1WZWVhb69OmDgIAA7N69G1yuZPau7t2745tvvkFVVRVM3vgfxsTEoE2bNmjcuLH4mLi4OMyYMUN8XkxMDLp3767UGLZu3YodO3ZgzJgx2LNnD2bPno2WLVsiKioKhYWFSrUhCyrIVKCDQ7a+hyCXutJlGDr6Xl5iM0fXPoGJGZdeDxVhsqYlFWPMEuYrtFTEJedifBUf5iZGeh4R+xEICDIKSnHveRESMl/h73vZyH799kd6S0crjOnSHMM6u8GhkWzR3L6pLT4KaAZCCG4/fYV9lzMQfTcb8U9eYuSPVxDW3hlzBvigpWMjXb0sCbKyshASEgIPDw+sWbMG+fn54n0i69bYsWOxZMkSTJo0CXPmzMG9e/ewceNGrF+/Xnzs9OnT0bt3b6xduxaDBg3CwYMHcfPmzVrWNnlkZmYiODgYAGBhYYHiYqG1fdy4cejWrRs2b96s1uszCEG2ZcsWfP/998jJyYG/vz82bdqErl1lRzz+9NNP2LdvH+7duwcACAgIwHfffSf3+PoCm+oVEkKw++dS7D50GxwAwR86aewwrcryUkO8OabdKtKZIKsvAST6SodBqZvOg0PQb9EJPCojOH0vB0M7NcwfG2W8ahy5lYWEzFfIKChF+otSvCrjwdSYCzNjI5gYccAXEPAFBBXVAvCqBRLnW5sb430/Vwzr1AxdPBsr/TnlcDjo3FzoSzZ/YFtsiHuIg9czceZ+LuKS8/B575b4v3e9dS6UY2JikJaWhrS0NDRrJhloJ0qQbmtri7Nnz2Lq1KkICAiAg4MDoqKixCkvACA4OBgHDhzAggULMH/+fHh7e+PYsWNyc5BJ4+LigsLCQnh4eKB58+a4evUq/P39kZ6erlGidtYLskOHDiEyMhLbt29HUFAQNmzYgLCwMKSmpsLJqXZU0oULFzBmzBgEBwfD3Nwcq1atQv/+/XH//n24ubHrQy3rxgbA4G92e3aVYdmSEvFzkWVLE8Gg7PJSQxRjACCo1l21Bm3XU2VK8GkrilKahjrntImRiTHef8cH62Mf4LfrmQ1OkJVUVmPflQz8fDEdBaW8WvsrqgSoqBLU2m5mzEVbVxv4utngHS8HhLRx0lg0OdmY47thHRAR7InvTiXjQmo+tpx/hOjEbHz3YQcEt3LQqH1ViIiIqNPXDAD8/Pxw8eJFhceMGDECI0aMUGsc7777Lk6cOIFOnTphwoQJ+Prrr/HHH3/g5s2bKiWQlYb1gmzdunWYPHkyJkyYAADYvn07oqOjsWvXLsydO7fW8fv375d4vnPnThw5cgRxcXEYP368TsasLLJubABYFS2pDtIBBgBw+c88jW6MTC4v1UeMTITXUxfWK20HkDAl+HSxzE3FmJZ4+BBfrPgSx71G4BqAR/klaKWnZTJdcz4lD18fTsCrMuHnzN3eAh91bgYvp0Zo4WAFh0Zm4FULUFktjI405nLA5XJgasSFq605jI20UxGxtbM19kzoitP3crDoxD1kFJRh7E/XMDKwGb4Z2A62lg0nX9yOHTsgEAgF8dSpU9GkSRNcvnwZQ4YMweeff652u6wWZDweD/Hx8Zg3b554G5fLRWhoKK5cuaJUG2VlZaiqqpJIHCeNprlz1EXWjU3azsHGaMm6LHt8Gdaap8mleJpcKr4x9h3fVCXrhTLLS/X95qhonrbqJHScnbfdEoe+E0YPyRIz4vfuBg98PsA1Arp0MVXJOqvtABKmBJ82oij1TVKBclFgBk9xMczOxaJ3z/F4XAGsj3mAzWPrdz4yQgh+vpSO704lQ0CAlg5WmNrHCx90bKo1kaUOA3xdEOzVBN+fTsWv157g8M1nOJeSj6UftMd7vi4Gt6KjDlwuVyKYYPTo0Rg9erTG7bJakL148QJ8Pl9mAreUlBSl2pgzZw6aNm2K0NBQuccwkTtHHeTd2NgULSmLuix7ANA/zBTJmcKxE0LwLKVMvO/R7WIAzFov6rsYA+TP0w9neogthtIiRFrM1HzvRPwd/VbkKWOZ0nYACVOCj+koSml0PefuvnAFUFnncfWJsUHNse9iKf5KzMbADtkY2MFV30PSCrxqARaduIffrj8FAIzu4o6lH/jC1Jg9QqwmNuYmWDbUFx90bIo5RxLxKL8UX+6/hb4+Tlj4fjvYa5a+jJUkJibC19cXXC4XiYmJCo/18/NTqw9WCzJNWblyJQ4ePIgLFy7A3Nxc7nFM5M5RB0U3NjZHSypj2TMx4SLqWCcAQOzeLLH4AoQ3RiatFw1BjAHy52nIWFfxr1JpESItZmQtJwOqWWe1HUDClOCrT8vcQjHW8PB2tsaXIS7YdC4NC47dQ9cW9nIjBA2VKr4AUw/cQkxSLrgc4JtB7TCxh6dBWJoCPe1xanpPbDn/CNsupCEuJQ8XH77AJ52VS2FhSHTs2BE5OTlwcnJCx44dweFwZDrwczgc8Pl8tfpgtSBzcHCAkZGRWgnc1qxZg5UrVyI2NrZOtapp7pzejVPVOk/ejY0t0ZLyUMay18jv7Q1E9o3xOSPWi4YixgDl5qn0tW42uimAR+L90u+dCDZZZ5kSfNqMotTlvGuoYkzE/73rjZikXKTkFGPBn/ew7ZPOBiFWlIEvIIg8fAcxSbkwNeZi+yed8a6Pc90nsggzYyNE9muNIf6uWHIyCRcfvsDOS/Wv9mp6ero4V1p6unZeH6sFmampKQICAhAXF4ehQ4cCAAQCAeLi4jBt2jS5561evRrLly/HmTNnEBgYqKPRKo+2Ha+13b5iyx4Pzyus8DBe6N8k8g2TvjEyYb1oSGJMWWRd65oJepuNJohCIuJv8lBdDRgZAYE1fMgAiPfduCGM7mLr/JSVeFhXkZW6osGKMXd3YPNmwN0dpsZcrB3pjw82/4fT93Pw+81nGNlF+ysY2kYgIJh3NBEn7zyHiREHP34SgD4+suuZGgJeTtbYN7ErYpPzsOiPG3iq7wExjIfH25oRT548QXBwMIyNJSVUdXU1Ll++LHGsKrBakAFAZGQkwsPDERgYiK5du2LDhg0oLS0VR12OHz8ebm5uWLFiBQBg1apViIqKwoEDB+Dp6SkuFtqoUSM0asSOKB1FUWTc1wIIbDXzG9B2WgJFlr1UngNuv1mevHWmAIBs3zBNrBdUiKkPh8OB+xh/uI8RPpfO7C+aJ6L5I/IvY3L+aHN+XtnxFIfWZQIw/ATCDVaMAYCjI1CjBE37prb4qq831sU8wOwjiXj2sgwzQluDyzVMsU0IwdK/knD45jNwOcDG0Z0MWoyJ4HA46NfOGf5Te8B5kb5Hoz369OmD7OzsWqm3Xr9+jT59+qi9ZMlOj8EajBo1CmvWrEFUVBQ6duyIhIQEnD59Wuzon5mZiezstxn0t23bBh6Ph+HDh8PV1VX8V7MavL6R5YMlovHSYunDGW1fW8SWeSGmtBUuH82T2C504GcOKsaYJbbMS/wnQtvzh4n25ZXlGnpI0r1Bev4RQhC7Nwvbp6cgdm+WWkkc6RzUAYWFwK+/Ch/fMLWPFyb2aAEA+OFcGibtvYHX5dr/btMG62IeYM/lDADA6uH+9S5Yob5XViCEyLS8FxQUwMpK/R+XrLeQAcC0adPkLlFeuHBB4nlGRob2ByTFPy/bqORHJs8Hy/hJNawPl+P1dCtUN1f/rdFlXcuaN8a4fc/xNKVUYj9TkW30Jqh9RO+ltV8W8NdbHwmhP2A5Y/1oMj8V1Ue1flqBIVmV8ASQ8Wab9PwzlBJcDdo6BgAZGcC4cUB8PPAmZZERl4Oowe3QoZkN5h65i/Op+Qj5/jyGdnLDqC7u8HGpu2YiG9j+zyNsOie0TC/7oD2GBzSr4wwKWxAlfeVwOIiIiJDw6eXz+UhMTBSXVFIHgxBk9Q15PliWp4Q3qTOfvkLmKAu1fWu0nZZA3k1ROnLSva0VrQ+oAy698oZplanawSXSyPLviy1TPA9VKWqu6vxUtki95xmhwFr6bmN8k82DKGy05q/Z+pibrKExrFMzeDtZY+qBW3hSUIbd/2Vg938Z8HGxRkd3O/i62aKDmy3auFizzlLzy5UMrPxbmLJpzgAfjOvuqd8BUVTC1tYWgPA7xdraGhYWFuJ9pqam6NatGyZPnqx2+1SQqcDdF64aFRiPLfNCqGWaXB+s0r1lsAfQLrkany4uhkAgAJfLVdn5WRtpCZS5KUqnXAge5qSWoNRXBBu/zLBzPElfN02if1X171NWNIlwHwOxH1ucBsa3mk78vyUKxZZ/fBGevhb6cEiX7dI0N5ku5maDt44pga+bLeIie+Piwxc4fPMpYpOFUZgpOcXADaE7OZcDeDpYoZ2rDQI9GqN7Kwd4OzXSi98ZIQSbzqVhXcwDAMC0Pl6YEtJK5+OgaMbu3bvFbg6bNm1i3C+dCjKGUHbZMrbMC6EWD2G9twxm8UL/h8ePqlFYIECv58JSDEEA9gMwW12KigqgNYDLf1VgDyGY8KluAhNUvcECmkVO6kqENaSbnbxrypQlTW8QgrYHsuF8qxg56WWwvF8KDgDR7c33NR/7ITaQocnu57A25iB5rGu9yk3W0DE24qKPjxP6+DihoKQSNzIKcTfrNe5mFeF+1msUlPLwOL8Uj/OFiWUBwN7KFL28HRDW3gW92zjC0lT7t8AqvgAL/ryHQzeFQvHLkFaY2b+11vulaAdCCPbv3y8uSs4kVJCpiCIrmdKirNwboZ88hFFuCWy2lMJPyq+YC2AsAFQAfAArAfwIwGlHGcDhaKU+oToCTBpVLCtUgOkPRdfeIMQah4OUUa6wyuOh+1/5eEdqt/jzA+HnZ48ZB2SkC8DhgAOwOrqXztc3WFkB3boJH5WgSSMzDPB1xQBf4fUjhCC/uBJJ2UW4l/Ua19ILcTPjJQpLeTiW8BzHEp7DzJiLnt6OGODrgn5tnbVSizGvqAKz/kjEvw/yweUASz7wxbhu6qVEoLADLpcLb29vFBQUUEGmS17lNkKTFrWjeBgRZTxvhM5Jw6qbPEy7WgVZbsXPAIwDcOHN8+xsgThdgKZpApgQYKpCb2jaIanABUblQudSTZbUAcOxqhFjDm5+7YkTRdWYdCBH8ecnowIdZ6QgI7EEleV8tOlqgymb20rUoqsL6s+oY9q0AZSsVywLDocDJxtzONmYI6SNE6ZBWJ4o4ekrxCTl4Mz9XGQWliE2ORexybkw5nLQrWUT9G7tiN5tHOHt1EijH71VfAH2Xs7AhtiHKKmshrkJF5vGdEa/doaV9JUim5UrV+J///sftm3bBl9fX8ba5RB14r7rOUVFRbC1tUWzTUvAtTBHYxfZqRsU3fyUvYHF7s3C3e/ScV/GvnYAkmVsH/S+OTZvs1OqfaD+ii+AWQHGL6vEvZHf4/Xr17CxYX/Elmie+h7+H4ws6640oalYqwt9iDY+n4/dPW7g6svqWvvkfX4AoFOoPb7c0q7O9tmWkd9Q5yjbxksIQUpOMc7cz8HpezlC37MauNiYI8CzMTq526FTczu0cbFBI7O67RdPC8sQk5SL365n4mFeCQDA390O3w3zRfumtlp5LWyEre87UzRu3BhlZWWorq6GqamphHM/ABTWSNeiCtRCpgQvc4SOv9LCTPQFKutGJ/oir+sm1Xd8U4TeKgJOF9Ta1xOybyiy0gToQ3SJMETx1RBRdP2YEGvKzgOmhBshBMuG3sH7MsQYIP/zAwAp117LzSWkD2sYndtS3LoFBAQI01507sx48xwOB21dbdDW1QYzQlsj/UUpzqXk4Z8H+bj2uAA5RRWITsxGdOLbz4WzjRlaOjSCq605bCxMYGthAi6Hg5dlPBSU8vAwt1hC2NlbmWLOgDYYEeBusAlsKbLZsGGDVtqlgkwFXuZYy7SWaSLMOBwO3isSRoQ9a2KCrwuqsATCX/cfAdghdXynUHs0G922zjQE2oAKL3byKrcRuBbmEtvkWXXlUdc1Z9K6pso8UiTe4vY9R9aDMnz05nkSgEUA1jcxQbOCKnxsxcXfzS0g4BNkPSiTOLe8mI+4fc8RGu6m9+VIOt/1TwsHK0x6pwUmvdMCFVV83HryErefvsLtzFe48+wV8osrkVsk/FMElwN08bRHv3bOGB7QDHaWpjp6BRRdEh6unVw5VJApwDTXBNWektvkWcsA5YQZIHmTMXtZBdfrr5Ey0hmX57XAsaBriOYRbAQQAaAxACsfS7i0sBRHhWm7Nl9DFV6vctlRWosJRPNUHmwWbDVRNBevXMuCPYAQCH+4zABg1qoxonYOxrj1V9Ez+iG8Q3xwblu8zPOvXgNMhqg+1wkhSD18H3mJeXDyc0Kbke3V/kyy7TNAEWaZD/ZyQLCXg3jb6/IqPM4vweP8UuSXVOJ1eRWKyqvAFxDYW5nC3soULrbmCG7lAHsrKsIaEhUVFeDxeBLb1F2mpYKsDsxyhMuDlS6Szv01b3jyljKBusVZwIUMbF7aB5YfCd9Q5xYWyEotw2cAzgLoDeBJM3N8vsFHw1cifwzahA03nLrEyVsq6j6EhZjmmsDIXPY8lYcy10QV0abs+8ykcHPyc0LnuHSMAXAEgF2rxhj4y1BUcbnYNb8n7gU1Q6uD93BOzvmOfurVDkw9fB83118DAGTGCfOc+YxSzbGXDZ8LivLYWpigU/PG6NS8sb6HQmEBpaWlmDNnDg4fPoyCgtruRurWsqSCTElEwgyQL84UWc0A2Tej+N4eAIcDvBQ+d3mPh6zU6wCAP94cE2ii2q9vXS/B6PPmorzYahjUnKfyYEq0qWplA5SbK8qKtjYj2yOVEOTfzUegDEvV9b4tkJJfAtx9W1/VvbcHuMZcOL45Xh3yEiXrteYn5sFnVN3nURFGodQPZs+ejfPnz2Pbtm0YN24ctmzZgqysLPz4449YuXKl2u1SQaYAyzzAyBQoc5Hcro7VDKj9hdzBIVsoxmrgM8oXebdz8fSfJzU2eunVz0VfNxIqtpRD3jyVR12iTZ+CDVDN2uYzugN8Rss/ps0oX4DDQX5inliEabrk7+TnJLaMAfItbVSAaUC7dsDDh0AzWueRwj5OnjyJffv2ISQkBBMmTEDPnj3h5eUFDw8P7N+/Hx9//LFa7VJBpgSWOW//r3nTk76x1byRSd+slBFogNA/pdq7NeyeF4PDAVoO9Fb7l3xdUKFVv6g5TxVRl3Bjysqm7PusbeGGvk1h1xeoAnCvxuqCKsunNf3GHDs4ounkfihNyYKVTzPw3u2Cuy9oFB2jmJsDXvqLHKdQFFFYWIiWLVsCEPqLidJcvPPOO5gyZYra7VJBpgCr53wYm/BR4va2QK30TU9dgQbIvhG9OHED2TtjxM+ze9uiuoD95V2oyNIfonkKQGKuykMZ4aYr0QYw78+mLKr8IMk/fh3Pf3rrN9Z0cn94zvmQ8TFR3pCeDixcCCxbBrRooe/RUCgStGzZEunp6WjevDl8fHxw+PBhdO3aFSdPnoSdnZ3a7VJBpgSNsiQd9OQJNHlLmyIULXGKeHVb8ld7acozOH7QVZXhSkAIwYsTN1Ca/BRWbd3hMKSL0ks2hiKylBEHysCvUM8Rk01Iz1V51CXcdCHalBVsgP5Em4jS5KeSzzX8XKrKyxxrEEJQdPqmzvrUKy9fAvv3A5GRVJBRWMeECRNw584d9O7dG3PnzsXgwYOxefNmVFVVYd26dWq3SwWZAqyySmFsJLzBlbq/LVUkT6DJuokpsqCJqHljMvXyRNnNu+LnHLdWGgmjothLeHXwLADg9aVklBWbwSZUuvqf7mFKRFEk5ykgOVfloYxw07ZoY9LKBqj2A0JV8WbV1h2vL71NM2vlox3fJkWvoTjuP7w+clor/VIoFOX5+uuvxf+HhoYiJSUF8fHx8PLygp+fn9rtUkGmJFZPSyWeKyPQgNo3LUIIXiReRNHLdJg3bwG77j0lbkwO7UNgPNAIFZkZMG/uCbv2PcGD7EzkysBLy5B6/gTQUJDVdSMlhODVlYuoyHz7GmVZ5ZQ9jqKYzLybaOHSQ3ztpOeqNIQQZOZdw6uSTFg284Jrq3dkXncmrG11iTZFgo0QgrKjV+qcH6qINhGq/sgx6vou7IrNwEt7AlMvDxh17YGXOcKxSIs7bVmWpT/LFApFtwgEAnz//fc4ceIEeDwe+vbti0WLFsHDwwMeHpoXjaeCTAai8p789CfgcN4m+SOeb31OzDJq56wqdROKNPOM2m2WNhXetF7c/Q85V6IBACX37sD4ZRUcOvQQH1fmBNh07gqbzsLlEEFlJYxltKcs5o2bowx3azx3h3GGZktzfCg+/9W1/1AY8/Y1CqqqYBfUQ+3jdIWgUvieGkp5V9E407JiwSl8jebmtWsz1pyzIjLzbiItK1b45GUSjArL0NwpUGFforktC1nzXeLcpvIFm1mm/PNe3P0PL67UPT/q+nzwnFUXbLJo1CMQ6CG8TqSiEqJZUpAu/QNFO/nsTDzcgDfWc0Obo0VFRaqdWFLy9lHVcyl6R/R+G8o8VZbly5dj8eLFCA0NhYWFBTZu3Ii8vDzs2rWLkfZpcXEZPHv2DO7u7voeBkVPPH36FM0MINyeztOGC52jFEPAUOapsnh7e2PWrFn4/PPPAQCxsbEYNGgQysvLweVyNW6fCjIZCAQCPH/+HNbW1lpbQisqKoK7uzuePn2qdpmFhtKHrvohhKC4uBhNmzZl5MOlbbQ9T7V9zWn7qrdP5yjFEDC0eaosZmZmSEtLk/iRYW5ujrS0NEaEJ12ylAGXy9WZqrexsdGqkKlPfeiiH1tbW621zTS6mqfavua0fdXap3OUYggY0jxVlurqapibm0tsMzExQVUVM24RVJBRKBQKhUKh1AEhBBERETAzMxNvq6iowBdffAErq7d+tkePHlWrfSrIKBQKhUKhUOogPDy81rZPPvmEsfapINMTZmZmWLRokYTSpn3ovx/KW7R9zWn7+m2fQqGoxu7du7XaPnXqp1AoFAqFQtEz9Sf8gUKhUCgUCsVAoYKMQqFQKBQKRc9QQUahUCgUCoWiZ6ggo1AoFAqFQtEzVJBRKJQGh0Ag0PcQNMLQx0+hUGpDBVkDoLKyUvy/toJq8/Ly8OjRI620LUJ67PSmpD8M9do/efIEWVlZBlvOxdDHT6FQ5EM/1XokNzcX8fHxiImJQVlZmVb6SEpKwkcffYS4uDgAAIfDYVyUJSYmomfPnjhz5gzy8/MZbVvEw4cPMXv2bHz55ZdYvXo1ANCbkh54+PAhHj9+rJVrn5aWhvXr12P27Nn4+++/kZuby2j7CQkJCAgIwMWLFxltV1cY+vgpFIpi6B1NT9y9exd9+vTBpEmTEBYWhhEjRuDevXuM9kEIwerVq3Hp0iVs2LBBK6Ls4cOHePfdd/Hee+9h/PjxcHR0lNjPhCXl7t27CA4OxpMnT5CamoqDBw9i+/bt4v00lZ5uuHPnDnx9fXHmzBnG27537x66du2Ko0eP4t9//8WwYcPw9ddf4++//2ak/Tt37iA4OBgREREYPXq0xD6m5s+DBw8QFRWFiIgI7Nu3D3fv3mWkXUA346dQKPqFCjI98PDhQ4SFheGjjz7Cn3/+ieTkZCQmJuLnn39mtB8OhwMrKyv4+PjAxMQEK1euRExMjHgfE/z444/o378/NmzYACsrKxw8eBCbNm3CL7/8AkBoxdJElL148QKffPIJJk6ciMOHD+Po0aNwcXFBeXm5+BgOh2OwS2iGQkJCArp3746vvvoKU6ZMYbTt8vJyzJs3D5988gkuXLiAq1ev4tixYygoKMDq1avx559/atR+amoqgoKCMGfOHKxZswZ8Ph///fcf/vzzT9y9e5eRuZOUlISgoCDcuHEDubm5mD17NmbMmIE9e/Zo3LYuxk+hUPQPLZ2kY8rLy7F27VoMHDgQCxcuhJGREYyMjLBgwQJs2rQJlZWVMDU1ZUwwvfPOO2jevDn69OmDqKgorFmzBo6Ojjh79ixGjx6N5s2ba9T+kydP0LNnTwBAcHAwTExM8Pz5cwDAli1bcPnyZXC5XBBC1HpNmZmZ4PF4+OyzzwAAtra2cHFxwaVLl3Dz5k3Y2tpi69atYuFHlzGZ5+HDh+jSpQuioqKwcOFCVFdXIy4uDpmZmWjdujXatm0LJycntds3NTVFVlYWunXrBiMjIwDAgAEDYGdnhxUrVmDHjh1o2rQpgoKCVG67srISS5cuhZWVFQYNGgQAGDZsGB4/fozc3Fy8fPkSkZGRmDJlClq0aKHW+KuqqrBy5UoMHz4cO3bsAIfDwY0bN7Bjxw58//334uLD6lBRUaH18VMoFHZA7146hs/ng8fj4Z133oGpqan4BuTi4oLCwkLweDxG+7O2tsaJEyfQtWtX/O9//4OVlRXef/99zJ07V1wjT5Mlj+rqaiQkJGD79u2wsbHBn3/+iWvXrmH//v0oKirC0KFDAahvkbOyskJZWRl+/fVXVFdXY9myZfjll1/g7e0NJycnnDt3TiwIqRhjnqqqKuzcuRPGxsYICAgAAAwZMgQzZ87E4sWLMWDAAMyaNQtXr15Vq32BQICKigq4urrixYsXAISfEQDo1q0bZs2ahczMTBw7dgyA6nPVzMwMn332Gfr27YtZs2bB29sbAoEAu3fvxoMHD7B792789NNPYouuOp8FY2NjZGRkwMzMTDzPu3TpglmzZiEkJAQ7d+7EiRMnVG4XAMzNzTFp0iStjp9CobAEQtE5z58/F/9fXV1NCCHk6tWrxNfXlwgEAvG+5ORkjftKTU0lQUFB4uehoaHE0tKSdOvWjVy8eFHtdvl8PiGEkL1795LQ0FDSr18/EhUVJXHMwYMHSbt27cjjx4/V7uf169dk9uzZxM3NjfTr148YGxuTI0eOiPefO3eOuLi4kAsXLqjdB0Uxd+/eJdOnTyetW7cmzZs3J0OGDCGJiYmEz+eTU6dOEV9fX/L5558TQojE/FWFzZs3E1NTU3LmzBlCyNv5RQghW7duJdbW1iQvL0/p9ioqKiSeX7x4kQwYMIAMGDCAPHr0SGLfypUriZ2dHSkoKFBr7Hw+n0ydOpWMHDmSFBYWSuxLTEwk/fv3J+Hh4YQQ5a/Pw4cPyapVq3QyfgqFwg6oINMjNW86ly9fJs2bNyclJSWEEELmz59P+vfvT169eqVxH7169SKZmZlk3LhxpGnTpmTr1q1k6NChpEuXLuSff/7RqP0nT56Q3r17Ew6HQ8aNGyex759//iFt2rQhGRkZGvVRVFREHj9+TP755x/i6+tL8vPzxftu3rxJvLy8SHx8vEZ9UGpTc34mJSWRzz77jLz33nskKSlJ4rhdu3YRExMTkpmZqVS7T548IQcOHCBbtmwh169fF2+fNGkSsba2JpcuXZI4/uzZs6RDhw5KC4779++TQYMGkdjYWIntN2/eJCdPniRVVVUSr2/btm3Ez8+P8Hg8pdonhJDc3FySlpYmfn748GFiYWFBduzYUUt0/f7778TY2FjpHyZ37twh9vb2xMPDo9ZcZ2r8FAqFfVAfMj1Sc4mNx+OhuLgYxsbGWLRoEVavXo0rV67A1tZW7fYJIaiurgYhBN27dweXy0V0dDQ6duwIDw8P7Nu3D56enhq137x5c+zYsQOjR49GdHQ0VqxYgXnz5qGyshJxcXFo0qQJbGxs1O4DEC67WltbQyAQwMzMDMnJyeJlyuPHj6NRo0Zwc3PTqA/KW0pKSmBubg5jY2OxX17btm0xa9YsPHv2DF5eXgAg3mdrawtvb2+l3ue7d+9i0KBB8PLywq1bt9C5c2esXbsWnTp1wsqVK1FeXo7+/ftj27Zt6NWrF9zd3XHmzBlwuVyllqRJjchi0fJh3759AQABAQESfoaix+TkZHh5eaG6uhrGxsZ1Lq8nJiZixIgRmD59Oj766CM4OztjxIgRSExMxP/93//B0tISw4cPF7sEeHt7o02bNnWOHRBGU3bv3h0jR47E8ePHcfDgQUybNo3R8VMoFJaiXz1Yv+Hz+eIlyZrbZHHlyhXSpUsXMmvWLGJmZkZu3rzJWB+//vorCQoKqtWmyBqnSR+ix9TUVDJ8+HDi7u5OXF1dSa9evYi9vT25ffs2Y68jNzeXBAYGkn79+pGRI0eSiRMnksaNGyvdB6VukpKSSFhYGDlw4IDY4lLzfZC15DZz5kzSv39/UlxcrLDtlJQU4uLiQr755htSVlZGMjMzib29Pfntt98k2p85cyaxt7cnzZs3J4GBgaRJkybk1q1bSr+GL7/8kgQFBZFhw4aR0NBQcvbsWZnHZWZmkgULFhBbW1ty7949pdp+8OABadKkCZk+fbrM1ztjxgzC5XLJsmXLyPXr18nr16/J//73P+Lt7S1h7ZLF7du3iYWFBZk7d674dQQHB5OsrCzGxk+hUNgLFWRa4v79++Tjjz8mffv2JV988QX566+/xPukhQchhPz333+Ew+EQe3t7pZfflO2Dx+ORly9fip+r4uejTB+iG/aLFy9IQkICWbFiBdm/f7/Eko6mfYjGnJSURL744gsyYMAA8vnnn9daPqOoT3p6OvHx8SEmJiYkODiYHDlyRKYoE5GWlkbmz59P7OzsyN27dxW2XVpaSj799FPy2WefkaqqKvH7OXz4cLJ8+XKyZMkScvDgQfHxly5dIr///jvZv38/SU9PV+l1HDhwgKxcuZJcu3aNhIWFkf79+5Pbt2+TVatWkSdPnhBCCElISCAhISGkRYsWKgn6mTNnkjFjxhBChHPyt99+Iz/88APZu3ev+JjVq1eTdu3aEXt7e+Lv709cXFzqFJSPHz8mtra2YjFGCCFHjhwhNjY25Ny5c4QQyfdA3fFTKBT2QgWZFkhJSSG2trZk9OjRZO7cucTf358EBgaSGTNmiI+prKyUOCc9PZ106dKF3L9/n7E+pB2b5VnnmHwdqqJKH6Lxl5WVEUII9ZlhkKqqKvL999+TIUOGkFu3bpF+/fqRgIAACVFWU8jfv3+f9OvXj7Rp00YpQVBeXk5OnDhBEhISxNuWLl1KOBwOGTt2LAkODiYdOnQg06dP1/i1nDx5kgQHBxNCCImNjSXDhg0jbm5uhMPhkJycHPFxp0+fruUgXxfDhw8nGzduJIQQ0q1bN9KzZ0/SqlUr0qpVK9KlSxfxHE1KSiLnz58nZ86cIc+ePauz3fT0dAlRJ2Lw4MGkV69etT7L6o6fQqGwFyrIGEYgEJD58+eTkSNHircVFRWRb7/9lnTs2JFMnjxZ4vjjx4+T7OxsQkhtAcVkH6pEqLG1j2PHjpHc3FyJ8ynMIBAISHx8PDl8+DAhRCh2a4oykSiuec3//fdfscVJGWqK9zt37hBLS0ty/PhxQohQbM+ZM4cEBgZKvMfqoK3IYkIIGTp0KJkwYQLZtm0b6d+/P3nx4gV58eIFuXr1Kmnbti0ZOHCgym3K+qEkus67d+8mrVq1Ijdu3JB7LIVCqR/QxE0Mw+Fw8Pz5c+Tk5Ii3WVtb46uvvsInn3yC27dvY+XKlQCA6OhoTJ06FZs2bQKfz4epqanW+ti4caNKGb3Z2Me0adPwww8/iPugzsvMweFw4O/vjxEjRgAATExMcPz4cdjb2+O7775DdHQ0qqurweFwxDnBevbsqVJi4Zrz28/PD2lpaRgyZIjYUb1Vq1YoKysTO8Ori5eXF8zMzPD06VOMHz8eSUlJWLNmDVxcXBAZGYl///1X5TZFc27YsGF4+vQpjh49im7duqFJkyZo0qQJgoKCsGjRImRkZCA9PV2ltmUFK4jm9pgxY0AIwbZt2+QeS6FQ6gf0080g5E1Sxs6dO4PP5yM1NVW8z9raGhMnTkSnTp1w8uRJ8Hg8DBo0CBMnTsSkSZNgZGSklMBQt4+JEycq/WVeX/qgqIYoSTEgTM5qYWGBY8eOiUXZn3/+iSlTpmDq1Kniagya4OLiAuCtyLh79y58fX01EmREKrL4woULiI6OxpQpUzB58mS0bNlSrchi0RhDQkJQVVWF2NjYWsLL1dUVfD6fsfnJ5/NhZmaG2bNn49KlS4iPj2ekXQqFwlL0aJ2rt6SlpREHBwcyceJEcSSWaAkiMzOTcDgccvLkSdqHjvqgqIco31V5eTkJCwsjpqamxMrKqs6gE1WiiwkROvzPnz+fODo6KhUtqIvIYlmI5mVqairp1KkTsbe3J9999x0hROhuEBUVRYKDg2slh1Vn/DVJSkoipqamYt81CoVSP6GCTEucO3eOmJmZkalTp0qEu2dnZxN/f39y+fJl2ocO+6C8RRVBIDruiy++IPb29nUKJlWji48fP07Cw8OJu7u7UqktdBFZrM00L6peHxErV66kqS0olHoOFWRa5MSJE8TMzIx8+OGH5ODBgyQpKYnMnTuXuLq6kqdPn9I+dNwHRT1BsGnTJsLhcOoUTOpE5WZkZJB169YplSJFF5HF2kzzos71USTSKBRK/YIKMi0THx9PevfuTTw8PEirVq1I69atVUpySftgto+GjLppTPLy8uoUG5pEFysjmnQR9avNNC+6GD+FQjFsqCDTAa9fvybp6ekkMTGxzmzdtA/t99EQ0YUgiIiIIL169ZLYVlRURNasWUMCAwPJihUrCCGE/PXXX6RZs2Zk/vz5hM/nK72cqGr733zzjdIWMjZeH1XGT6FQDB8arqYDbGxs4OnpiQ4dOsDBwYH2oec+GiLaTGNCNIgu5nK5dUYXq9u+KhG5bLw+NKKYQmlg6FkQUigULSOyQP3www+kR48eJCUlRWJ/YWEhmTx5MgkODhYvyUVFRamcBV7bEbPaar++XB8KhWLYUEFGoTQQdCEItB0xq83268P1oVAohouxvi10FApFN7Rq1QqHDx/Ge++9BwsLCyxevFi8LGxiYgI/Pz80adJEoz769OmD33//HSNGjEB2djZGjhwJPz8/7Nu3D3l5eXB3d2dt+/Xh+lAoFMOFQ8gbBwcKhdIgOHnyJEaMGIFBgwZJCIK9e/fi+vXraNasmcZ93Lp1C5GRkcjIyICxsTGMjIxw8OBBdOrUiYFXoN3268P1oVAohgcVZBRKA0QXgqCoqAiFhYUoLi6Gq6sr40Ea2my/PlwfCoViWFBBRqE0UKggUAy9PhQKRZdQQUahUCgUCoWiZ2iSGwqFQqFQKBQ9QwUZRcyePXtgZ2cnfr548WJ07NhRb+OhUCgUCqWhQAUZRS6zZs1CXFycvodBoVAoFEq9h+Yhq4fweDyYmppq3E6jRo3QqFEjBkZEoVAoFApFEdRCVg8ICQnBtGnTMGPGDDg4OCAsLAzr1q1Dhw4dYGVlBXd3d3z55ZcoKSmROG/Pnj1o3rw5LC0tMWzYMBQUFEjsl16yDAkJwYwZMySOGTp0KCIiIsTPt27dCm9vb5ibm8PZ2RnDhw9n+uVSKBQKhVLvoIKsnrB3716Ympriv//+w/bt28HlcvHDDz/g/v372Lt3L86dO4fZs2eLj7927RomTZqEadOmISEhAX369MG3336r0Rhu3ryJr776CkuXLkVqaipOnz6NXr16afrSKBQKhUKp99Aly3qCt7c3Vq9eLX7epk0b8f+enp749ttv8cUXX2Dr1q0AgI0bN2LAgAFikda6dWtcvnwZp0+fVnsMmZmZsLKywvvvvw9ra2t4eHjQzOMUCoVCoSgBtZDVEwICAiSex8bGom/fvnBzc4O1tTXGjRuHgoIClJWVAQCSk5MRFBQkcU737t01GkO/fv3g4eGBli1bYty4cdi/f7+4PwpFHhcuXACHw8GrV6/0PRQKhULRG1SQ1ROsrKzE/2dkZOD999+Hn58fjhw5gvj4eGzZsgWA0OFfXbhcLqTzCFdVVYn/t7a2xq1bt/Dbb7/B1dUVUVFR8Pf3pzdaigSyfBGZgMPh4NixY4y3S6FQKLqACrJ6SHx8PAQCAdauXYtu3bqhdevWeP78ucQxbdu2xbVr1yS2Xb16VWG7jo6OyM7OFj/n8/m4d++exDHGxsYIDQ3F6tWrkZiYiIyMDJw7d07DV0ShUCgUSv2GCrJ6iJeXF6qqqrBp0yY8fvwYv/zyC7Zv3y5xzFdffYXTp09jzZo1ePjwITZv3lyn/9i7776L6OhoREdHIyUlBVOmTJGwfv3111/44YcfkJCQgCdPnmDfvn0QCAQS/myUhk1ERAT++ecfbNy4ERwOBxwOBxkZGQCEPyQCAwNhaWmJ4OBgpKamSpx7/PhxdO7cGebm5mjZsiWWLFmC6upqAEI/SQAYNmwYOByO+PmjR4/wwQcfwNnZGY0aNUKXLl0QGxurq5dLoVAoSkMFWT3E398f69atw6pVq+Dr64v9+/djxYoVEsd069YNP/30EzZu3Ah/f3+cPXsWCxYsUNjuxIkTER4ejvHjx6N3795o2bIl+vTpI95vZ2eHo0eP4t1330Xbtm2xfft2/Pbbb2jfvr1WXifF8Ni4cSO6d++OyZMnIzs7G9nZ2XB3dwcAfPPNN1i7di1u3rwJY2NjTJw4UXzexYsXMX78eEyfPh1JSUn48ccfsWfPHixfvhwAcOPGDQDA7t27kZ2dLX5eUlKCgQMHIi4uDrdv38aAAQMwePBgZGZm6viVUygUimJocXEKhaJTQkJC0LFjR2zYsAGA0Km/T58+4kAUADh16hQGDRqE8vJymJubIzQ0FH379sW8efPE7fz666+YPXu2eDmew+Hgzz//xNChQxX27+vriy+++ALTpk3TyuujUCgUdaBpLygUCivw8/MT/+/q6goAyMvLQ/PmzXHnzh38999/YosYIPRhrKioQFlZGSwtLWW2WVJSgsWLFyM6OhrZ2dmorq5GeXk5tZBRKBTWQQUZhUJhBSYmJuL/ORwOAEAgEAAQCqslS5bgww8/rHWeubm53DZnzZqFmJgYrFmzBl5eXrCwsMDw4cM1ijamUCgUbUAFGYVC0Smmpqbg8/kqndO5c2ekpqbCy8tL7jEmJia12v3vv/8QERGBYcOGARAKO1EQAYVCobAJKsgoFIpO8fT0xLVr15CRkYFGjRqJrWCKiIqKwvvvv4/mzZtj+PDh4HK5uHPnDu7duycu+eXp6Ym4uDj06NEDZmZmaNy4Mby9vXH06FEMHjwYHA4HCxcuVKo/CoVC0TU0ypJCoeiUWbNmwcjICO3atYOjo6NS/lxhYWH466+/cPbsWXTp0gXdunXD+vXr4eHhIT5m7dq1iImJgbu7u7hk17p169C4cWMEBwdj8ODBCAsLQ+fOnbX22igUCkVdaJQlhUKhUCgUip6hFjIKhUKhUCgUPUMFGYVCoVAoFIqeoYKMQqFQKBQKRc9QQUahUCgUCoWiZ6ggo1AoFAqFQtEzVJBRKBQKhUKh6BkqyCgUCoVCoVD0DBVkFAqFQqFQKHqGCjIKhUKhUCgUPUMFGYVCoVAoFIqeoYKMQqFQKBQKRc9QQUahUCgUCoWiZ/4f260d4x5fIusAAAAASUVORK5CYII=", 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", 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" ] @@ -2791,9 +3025,11 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 102, "id": "6f027ba6-05ac-49d5-90c9-07ec37927510", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -2801,13 +3037,13 @@ "" ] }, - "execution_count": 48, + "execution_count": 102, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -2820,6 +3056,121 @@ "plot_convergence(cr_gbrt)" ] }, + { + "cell_type": "markdown", + "id": "2c5e685e-7117-4b21-a7a5-3c975fe3acf8", + "metadata": { + "jupyter": { + "source_hidden": true + } + }, + "source": [ + "# Plot policies" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "id": "6a61d3fa-97a9-4274-945c-be2742d1e956", + "metadata": {}, + "outputs": [], + "source": [ + "def get_policy_df(policy_obj, minx=-1, maxx=1, nx=100):\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'pop': (obs_list + 1)/2,\n", + " 'pol': [policy_obj.predict(np.float32([obs]))[0][0] for obs in obs_list]\n", + " }\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "id": "b86effb9-d8ad-4b50-8174-ea76dcd60c32", + "metadata": {}, + "outputs": [], + "source": [ + "cr_gp_preargs = {'radius': cr_gp.x[0], 'theta': cr_gp.x[1], 'y2': cr_gp.x[2]}\n", + "cr_gp_args = {}\n", + "cr_gp_args['x1'] = cr_gp_preargs['radius'] * np.sin(cr_gp_preargs['theta'])\n", + "cr_gp_args['x2'] = cr_gp_preargs['radius'] * np.cos(cr_gp_preargs['theta'])\n", + "cr_gp_args['y2'] = cr_gp_preargs['y2']\n", + "\n", + "cr_gbrt_preargs = {'radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", + "cr_gbrt_args = {}\n", + "cr_gbrt_args['x1'] = cr_gbrt_preargs['radius'] * np.sin(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['x2'] = cr_gbrt_preargs['radius'] * np.cos(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", + "\n", + "msy_gp_args = {'mortality': msy_gp.x[0]}\n", + "msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", + "\n", + "esc_gp_args = {'escapement': esc_gp.x[0]}\n", + "esc_gbrt_args = {'escapement': esc_gbrt.x[0]}\n", + "\n", + "#\n", + "\n", + "env = AsmEnv(config=CONFIG)\n", + "\n", + "cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", + "cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))\n", + "\n", + "esc_gbrt_df = get_policy_df(ConstEsc(env, **esc_gbrt_args))\n", + "esc_gp_df = get_policy_df(ConstEsc(env, **esc_gp_args))\n", + "\n", + "msy_gbrt_df = get_policy_df(Msy(env, **msy_gbrt_args))\n", + "msy_gp_df = get_policy_df(Msy(env, **msy_gp_args))" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "id": "88d5b45d-eeed-4321-9e9d-1a58ba63e84c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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ZwMBAc+WVV5qXXnrJFBYWOvdbtmyZ6d+/v/H39zedO3c2zzzzjPnHP/5R5ZJTY4wpKyszv/rVr0y7du1MixYtzOjRo83+/fvPu1TaGGNee+01ExMTY7y9vatcblrdpcEnTpwwd999t2nXrp3x8/Mzl1122XmXI1deKv3//t//O+9z6geXyx49etT85Cc/MSEhISY4ONhMnDjRpKenn7df5aXSJ0+erPEcHj9+3Hh7e5sePXrUuM8PVV6uu3HjxvOeKysrM127djVdu3Y1paWlxhhj/vWvf5mYmBjj5+dnBg4caD755JNaXSptTPm5mzVrlomOjja+vr4mIiLCjBw50syfP79WtZaWlpoFCxaY6667zrRp08b4+PiYdu3amZEjR5pXX331vMuLJZlZs2bV+lx834gRI0zfvn3Npk2bzLBhw4y/v7/p1KmTefnll8/btza/E5X1XOhS6UrLli0zw4cPNwEBASYoKMjExsaaxYsXn/d6KSkpRpK54YYb6vUZgbqyGeOCMU4AzVpWVpYiIyP12GOP6dFHH7W6HI8WHx+vrKysWjeTW2H79u0aOHCg3nrrLd15551Wl4NmgJ4XAA1u4cKFKisr44usmXjttdfUqlUr3XLLLVaXgmaCnhcADWbNmjXavXu3/vjHP+rmm2+u1X2G4LmWL1+u3bt3a/78+Zo9e3aD3ZwTuBimjQA0mPj4eH399de68sor9a9//ate9zJCVe48bdS5c2edOHFCo0eP1j//+c86N4oD9UV4AQAAHoWeFwAA4FEILwAAwKM0uYZdh8Oh9PR0BQYGcmMwAAA8hDFG+fn5ioqKuugNS5tceElPT1d0dLTVZQAAgHpIS0tThw4dLrhPkwsvld3uaWlpCgoKsrgaAABQG3l5eYqOjq7VVWtNLrxUThUFBQURXgAA8DC1afmgYRcAAHgUwgsAAPAohBcAAOBRmlzPS22VlZWppKTE6jLchq+vr7y9va0uAwCAi2p24cUYo4yMDOXk5FhditsJCQlRREQE6+MAANxaswsvlcElLCxMLVq04Ita5YGuoKBAmZmZkqTIyEiLKwIAoGbNKryUlZU5g0vbtm2tLsetBAQESJIyMzMVFhbGFBIAwG01q4bdyh6XFi1aWFyJe6o8L/QCAQDcWbMKL5WYKqoe5wUA4AmaZXgBAACei/DSTCxcuFAhISFWlwEAwCUjvAAAAI/SrK42AjxVcalDJ88UyRhjdSkAIB8vL0UE+1v3/pa9M+okPj5e/fr1kyT985//lK+vr372s5/pySeflM1m0+nTpzVnzhwtX75cRUVFGjFihF588UV1797d4spRV8YYrdqZoW1Hc3Qg86wOnDyjI9kFKnMQXAC4h5jQllrzULxl79/sw4sxRudKyix57wBf7zpd4fPmm29q2rRpSklJ0aZNmzRjxgx17NhR06dP19SpU7Vv3z4tW7ZMQUFB+tWvfqWxY8dq9+7d8vX1deGnQENbvfuEfpa05bztvt42eXFFGAA34OdtbddJsw8v50rK1OexTyx5791PjlYLv9r/EURHR+uFF16QzWZTz549tWPHDr3wwguKj4/XsmXLtG7dOg0fPlySlJSUpOjoaH3wwQeaOHGiqz4CXOCfGw5Lkq7q1k6j+4ara2grdQ1rpbBAO5ezA4AILx5l6NChVb68hg0bpueff167d++Wj4+P4uLinM+1bdtWPXv21J49e6woFfV0+NRZ/Xdflmw26elbLlN0GxZUBIAfavbhJcDXW7ufHG3ZewPftyjliCTpmu6hBBcAqEGzDy82m61OUzdWSk5OrvLzhg0b1L17d/Xp00elpaVKTk52ThudOnVKqamp6tOnjxWloh6KSsu0dNNRSVJCXEeLqwEA98U6Lx7kyJEjevDBB5WamqrFixfrpZde0pw5c9S9e3eNHz9e06dP11dffaXt27frjjvuUPv27TV+/Hiry0YtfbLrhE6dLVZ4kF0je4VZXQ4AuC3PGHKAJGnKlCk6d+6cYmNj5e3trTlz5mjGjBmSpAULFmjOnDm66aabVFxcrGuuuUYrV67kSiMPsii5vFF38pCO8rG4kx8A3BnhxYP4+vpq3rx5+tvf/nbec61bt9Zbb71V47FTp07V1KlTXVgdLsX+zDPacDBbXjZpcmy01eUAgFvjP+8AN7C4olH3ul7higwOsLgaAHBvhBfAYoUlZVq6ubxRN5FGXQC4KKaNPMSXX35pdQlwkZU7jiv3XInahwTomh6hVpcDAG6PkRfAYknJ5VNGCXEd5e3FCroAcDHNMrxwZ97qcV4a396MPG0+fFo+XjZNHNTB6nIAwCM0q/BSedlwQUGBxZW4p8rzwuXVjWdRxajLDX3DFRZk3e3lAcCTNKueF29vb4WEhCgzM1OS1KJFC250p/IRl4KCAmVmZiokJETe3ty2oDEUFJfq/S3HJEkJsZ0srgYAPEezCi+SFBERIUnOAIP/CQkJcZ4fuN7y7enKLypV57YtNLxrW6vLAQCP0ezCi81mU2RkpMLCwlRSUmJ1OW7D19eXEZdGVjlldHtsR3nRqAsAtdbswkslb29vvqxhmZ3HcrX9aK78vL10K426AFAnzaphF3AXlZdHj+kXobat7BZXAwCehfACNLL8whJ9uK28UZcVdQGg7ggvQCP7cFu6CorL1C2slWK7tLG6HADwOIQXoBEZY/63om5sRy7VB4B6ILwAjWhbWo72HM+T3cdLE66gURcA6oPwAjSiylGXH/WPVHALVjIGgPogvACNJLegRCu+SZck3TGUFXUBoL4IL0Aj+ffWoyoscahXRKAujw6xuhwA8FiEF6ARfL9RN3FoJxp1AeASEF6ARrDxu9Pan3lGLfy8dfPAKKvLAQCPRngBGkFS8mFJ0viBUQr0p1EXAC4F4QVwseyzxfp4R4YkKSGWRl0AuFSEF8DFlm5OU3GZQ/07BOuyDsFWlwMAHo/wAriQw2G0OCVNUvmKugCAS0d4AVxo/cFTOpR1VoF2H40bQKMuADQEwgvgQosqLo+++fL2amn3sbgaAGgaCC+Ai2TmF+qTXRWNunFMGQFAQyG8AC7y7qajKnUYXdExRL0jg6wuBwCaDJeGl+zsbCUmJiooKEghISGaNm2azpw5c8H977//fvXs2VMBAQHq2LGjfv7znys3N9eVZQINrrxRt2JF3TgujwaAhuTS8JKYmKhdu3Zp9erVWrFihdauXasZM2bUuH96errS09P13HPPaefOnVq4cKFWrVqladOmubJMoMGt3XdSR0+fU3CAr37UP9LqcgCgSbEZY4wrXnjPnj3q06ePNm7cqMGDB0uSVq1apbFjx+ro0aOKiqrdlRfvvvuu7rjjDp09e1Y+PhdveMzLy1NwcLByc3MVFMRQPawx/a1NWr37hO65soseG9fH6nIAwO3V5fvbZSMv69evV0hIiDO4SNKoUaPk5eWl5OTkWr9O5YeoKbgUFRUpLy+vygOw0vHcc/p8zwlJNOoCgCu4LLxkZGQoLCysyjYfHx+1adNGGRkZtXqNrKws/f73v7/gVNPTTz+t4OBg5yM6OvqS6gYu1dsb0+QwUlyXNuoW1srqcgCgyalzeJk7d65sNtsFH3v37r3kwvLy8vSjH/1Iffr00RNPPFHjfo888ohyc3Odj7S0tEt+b6C+SsscWlKxom7iUBp1AcAV6rxq1kMPPaSpU6decJ+YmBhFREQoMzOzyvbS0lJlZ2crIiLigsfn5+drzJgxCgwM1Pvvvy9f35rvwmu322W322tdP+BKX6SeVEZeodq09NPovuFWlwMATVKdw0toaKhCQ0Mvut+wYcOUk5OjzZs3a9CgQZKkNWvWyOFwKC4ursbj8vLyNHr0aNntdi1btkz+/v51LRGwTFLyYUnSxMEdZPfxtrgaAGiaXNbz0rt3b40ZM0bTp09XSkqK1q1bp9mzZ2vy5MnOK42OHTumXr16KSUlRVJ5cLnhhht09uxZvfHGG8rLy1NGRoYyMjJUVlbmqlKBBpGWXaD/fHtSknT7EBp1AcBVXHqzlaSkJM2ePVsjR46Ul5eXJkyYoBdffNH5fElJiVJTU1VQUCBJ2rJli/NKpG7dulV5rUOHDqlz586uLBe4JEs2HpEx0tXd26lzu5ZWlwMATZZLw0ubNm20aNGiGp/v3Lmzvr/MTHx8vFy07AzgUiVlDr298agkKSGWURcAcCXubQQ0gNW7TyjrTJFCA+0a1YdGXQBwJcIL0AAWJZffx2jS4Gj5evPXCgBciX9lgUv0XdZZfbU/SzabNDmWRRIBwNUIL8Alqrx7dHyPUHVo3cLiagCg6SO8AJegqLRM72yqWFE3jhV1AaAxEF6AS7BqZ4ZOF5QoKthf1/YKu/gBAIBLRngBLkFSZaPukI7y9rJZXA0ANA+EF6Ce9p3IV8qhbHl72TRpCI26ANBYCC9APS2qaNQd2StMEcHcgwsAGgvhBaiHwpIyvbe5fEXdxKE06gJAYyK8APWw4pvjyissVYfWAbq6WzurywGAZoXwAtRDUvJhSVJCXEd50agLAI2K8ALU0e70PG09kiMfL5smDqJRFwAaG+EFqKNFKeWjLqP7RSg00G5xNQDQ/BBegDo4W1SqD7amS5ISYztaXA0ANE+EF6AOlm1P15miUsW0a6lhXdtaXQ4ANEuEF6AOFlWsqHt7bEfZbDTqAoAVCC9ALX1zNEc7juXKz8dLEwZ1sLocAGi2CC9ALVWOuvzoski1aelncTUA0HwRXoBayCss0Yfbyht1E+Jo1AUAKxFegFr4YOsxnSspU4/wVhrcqbXV5QBAs0Z4AS7CGOOcMkqgURcALEd4AS5iy5HT2puRL39fL/3kChp1AcBqhBfgIpIqRl3G9Y9ScICvxdUAAAgvwAXkFBRrxTfHJUmJQztZXA0AQCK8ABf03pZjKi51qE9kkAZ0CLa6HACACC9AjYwxSkouvwlj4lAadQHAXRBegBokH8rWwZNn1dLPW+MHtre6HABABcILUIPKRt3xl7dXK7uPxdUAACoRXoBqZJ0p0qqd5Y26CbGsqAsA7oTwAlRj6eajKikzGhAdon7tadQFAHdCeAF+wOEwWpxSPmWUyKgLALgdwgvwA+sOZOnwqQIF2n1004BIq8sBAPwA4QX4gaQN5aMut1zRXi38aNQFAHdDeAG+50ReoVbvOSFJSohjRV0AcEeEF+B73tmYpjKH0eBOrdUzItDqcgAA1SC8ABXKHEZLNqZJKl9RFwDgnggvQIX/fJupYznnFNLCVzf2o1EXANwV4QWosKhiRd1br+ggf19vi6sBANSE8AJISs85pzV7MyVJt8cxZQQA7ozwAkhasjFNDiMNi2mrrqGtrC4HAHABhBc0e6VlDr29sXzKKIFRFwBwe4QXNHuf783UibwitW3pp9F9I6wuBwBwEYQXNHtJFY26tw2Jlp8PfyUAwN3xLzWatSOnCvTffSclSbcPYcoIADwB4QXN2uKNR2SMdE2PUHVs28LqcgAAtUB4QbNVXOrQu5vKV9RNiGXUBQA8BeEFzdanuzOUdaZY4UF2jewdZnU5AIBaIryg2UraUN6oO2lwtHy9+asAAJ6Cf7HRLB04eUbrD56Sl02axJQRAHgUwguapcUVl0df2zNM7UMCLK4GAFAXhBc0O4UlZVq65agkKXEooy4A4GkIL2h2Pt55XDkFJWofEqARPWjUBQBPQ3hBs7OoYspo8pBoeXvZLK4GAFBXhBc0K9+eyNfG707L28um24ZEW10OAKAeCC9oVipHXUb1DlN4kL/F1QAA6oPwgmbjXHGZ3qto1L1jaCeLqwEA1BfhBc3G8m/SlV9Yqo5tWujKru2sLgcAUE+EFzQbSRVTRglxHeVFoy4AeCzCC5qFncdytT0tR77eNt06qIPV5QAALgHhBc3CopTyUZcx/SLVrpXd4moAAJeC8IIm70xRqT7cekySlMB9jADA4xFe0OR9uO2YzhaXKSa0pYbGtLG6HADAJXJpeMnOzlZiYqKCgoIUEhKiadOm6cyZM7U61hijG2+8UTabTR988IEry0QTZoxR0oaKRt3YjrLZaNQFAE/n0vCSmJioXbt2afXq1VqxYoXWrl2rGTNm1OrYefPm8UWDS7b9aK52H8+Tn48XjboA0ET4uOqF9+zZo1WrVmnjxo0aPHiwJOmll17S2LFj9dxzzykqKqrGY7dt26bnn39emzZtUmRkpKtKRDOQtOGwJOmmyyIV0sLP4moAAA3BZSMv69evV0hIiDO4SNKoUaPk5eWl5OTkGo8rKChQQkKCXnnlFUVERFz0fYqKipSXl1flAUhS7rkSLf8mXVL52i4AgKbBZeElIyNDYWFhVbb5+PioTZs2ysjIqPG4Bx54QMOHD9f48eNr9T5PP/20goODnY/oaG62h3LvbzmqwhKHeoYHalCn1laXAwBoIHUOL3PnzpXNZrvgY+/evfUqZtmyZVqzZo3mzZtX62MeeeQR5ebmOh9paWn1em80LcYY59ouiUNp1AWApqTOPS8PPfSQpk6desF9YmJiFBERoczMzCrbS0tLlZ2dXeN00Jo1a3TgwAGFhIRU2T5hwgRdffXV+vLLL887xm63y25n0TFUtenwaX174owCfL118+XtrS4HANCA6hxeQkNDFRoaetH9hg0bppycHG3evFmDBg2SVB5OHA6H4uLiqj1m7ty5uvfee6tsu+yyy/TCCy9o3LhxdS0VzdiiivsY/XhAlIL8fS2uBgDQkFx2tVHv3r01ZswYTZ8+Xa+++qpKSko0e/ZsTZ482Xml0bFjxzRy5Ei99dZbio2NVURERLWjMh07dlSXLl1cVSqamNNni/XRjuOSyqeMAABNi0vXeUlKSlKvXr00cuRIjR07VldddZXmz5/vfL6kpESpqakqKChwZRloZt7bclTFpQ71ax+k/h1CrC4HANDAXDbyIklt2rTRokWLany+c+fOMsZc8DUu9jzwfcYYJVVMGSXGdbK4GgCAK3BvIzQp6w+c0qGss2pl99GPB9S8ECIAwHMRXtCkJFVcHn3z5VFqaXfpwCIAwCKEFzQZJ/OL9MnO8gUQE2KZMgKAporwgibj3c1pKnUYDYwOUZ+oIKvLAQC4COEFTYLDYbS4ckVd7mMEAE0a4QVNwn/3Zykt+5yC/H10U38adQGgKSO8oElI2nBYknTLFR0U4OdtcTUAAFcivMDjZeQW6vO95ffRYsoIAJo+wgs83tsb01TmMIrt3EbdwwOtLgcA4GKEF3i00jKHlmysaNTlPkYA0CwQXuDRvkw9qeO5hWrT0k9j+p1/U08AQNNDeIFHW1RxefStgzrI7kOjLgA0B4QXeKyjpwv0RWp5o+7tsUwZAUBzQXiBx1qSkiZjpCu7tVWXdi2tLgcA0EgIL/BIJWUOvb0pTZKUGMd9jACgOSG8wCN9tvuETuYXqV0ru0b1Dre6HABAIyK8wCNVNupOGtJBfj78GgNAc8K/+vA432Wd1X/3ZclmkyYPoVEXAJobwgs8zuKKRelG9AhVdJsWFlcDAGhshBd4lKLSMr276agkKYHLowGgWSK8wKN8suuEss8WKyLIX9f1CrO6HACABQgv8ChJGw5LkiYNiZaPN7++ANAc8a8/PMb+zDNKPpQtL5s0OTba6nIAABYhvMBjLEoub9Qd2TtckcEBFlcDALAK4QUeobCkTO9tqWjUjaNRFwCaM8ILPMJH3xxX7rkSdWgdoGu6h1pdDgDAQoQXeITKFXVvj+0oby+bxdUAAKxEeIHb23M8T5sPn5aPl00TB3ewuhwAgMUIL3B7lY26N/QNV1igv8XVAACsRniBWztbVKr3tx6TJCXGdbK4GgCAOyC8wK0t356uM0Wl6ty2hYbFtLW6HACAGyC8wK1VNuomxHWUF426AAARXuDGdhzN1TdHc+Xn7aVbB7GiLgCgHOEFbmtRSvl9jG68LEJtWvpZXA0AwF0QXuCW8gtL9OG2dElSQiwr6gIA/ofwArf0wbZ0FRSXqVtYK8V2aWN1OQAAN0J4gdsxxihpQ/mUUWJcR9lsNOoCAP6H8AK3szUtR3sz8mX38dItl7OiLgCgKsIL3E7ShvLLo8cNiFJwC1+LqwEAuBvCC9xKbkGJVnxT0agbR6MuAOB8hBe4lfe2HFVRqUO9I4N0eXSI1eUAANwQ4QVuwxijpOTyRt0EGnUBADUgvMBtpBzK1oGTZ9XCz1s3D4yyuhwAgJsivMBtJCWXN+qOHxilQH8adQEA1SO8wC2cOlOkVTszJEkJsZ0srgYA4M4IL3ALSzcfVXGZQ/07BOuyDsFWlwMAcGOEF1jO4TBanFI+ZZTI5dEAgIsgvMByXx84pe9OFSjQ7qNxA2jUBQBcGOEFlluUUn559M2Xt1cLPx+LqwEAuDvCCyyVmV+oT3edkCQlDmXKCABwcYQXWOrdTUdV6jAa1Km1ekUEWV0OAMADEF5gmTKH0aKKtV0SYhl1AQDUDuEFllm776SO5ZxTcICvftQ/0upyAAAegvACyyRtKB91mXBFB/n7eltcDQDAUxBeYIn0nHNas7e8UTeBtV0AAHVAeIEl3t6YJoeR4rq0UbewVlaXAwDwIIQXNLrSMoeWbKxYUXco9zECANQN4QWNbs3eTJ3IK1Kbln4a3Tfc6nIAAB6G8IJGl1RxefTEQR1k96FRFwBQN4QXNKq07AKt3XdSknQ7a7sAAOqB8IJGtTjliIyRrurWTp3btbS6HACAByK8oNEUlzr0zqajkqRELo8GANQT4QWNZvXuE8o6U6TQQLtG9aFRFwBQPy4LL9nZ2UpMTFRQUJBCQkI0bdo0nTlz5qLHrV+/Xtddd51atmypoKAgXXPNNTp37pyrykQjWpRyWJI0aXC0fL3JzQCA+nHZN0hiYqJ27dql1atXa8WKFVq7dq1mzJhxwWPWr1+vMWPG6IYbblBKSoo2btyo2bNny8uLLzpPdyjrrNbtPyWbTZocG211OQAAD2YzxpiGftE9e/aoT58+2rhxowYPHixJWrVqlcaOHaujR48qKiqq2uOGDh2q66+/Xr///e/r/d55eXkKDg5Wbm6ugoKC6v06aFhPrdyj+WsP6tqeoVpwd6zV5QAA3Exdvr9dMqSxfv16hYSEOIOLJI0aNUpeXl5KTk6u9pjMzEwlJycrLCxMw4cPV3h4uEaMGKGvvvrqgu9VVFSkvLy8Kg+4l8KSMr27KU2SlBjHiroAgEvjkvCSkZGhsLCwKtt8fHzUpk0bZWRkVHvMwYMHJUlPPPGEpk+frlWrVumKK67QyJEjtW/fvhrf6+mnn1ZwcLDzER3NlIS7+WRXhk4XlCgy2F/xPUOtLgcA4OHqFF7mzp0rm812wcfevXvrVYjD4ZAkzZw5U3fffbcuv/xyvfDCC+rZs6f+8Y9/1HjcI488otzcXOcjLS2tXu8P10naUL6i7uQhHeVDoy4A4BL51GXnhx56SFOnTr3gPjExMYqIiFBmZmaV7aWlpcrOzlZERES1x0VGRkqS+vTpU2V77969deTIkRrfz263y26316J6WOHbE/lK+S5b3l42TRrCqBgA4NLVKbyEhoYqNPTiw/7Dhg1TTk6ONm/erEGDBkmS1qxZI4fDobi4uGqP6dy5s6KiopSamlpl+7fffqsbb7yxLmXCjSyquI/RyF5higj2t7gaAEBT4JIx/N69e2vMmDGaPn26UlJStG7dOs2ePVuTJ092Xml07Ngx9erVSykpKZIkm82mhx9+WC+++KKWLl2q/fv369FHH9XevXs1bdo0V5QJFztXXKb3tpSvqJvAiroAgAZSp5GXukhKStLs2bM1cuRIeXl5acKECXrxxRedz5eUlCg1NVUFBQXObb/4xS9UWFioBx54QNnZ2RowYIBWr16trl27uqpMuNCKb9KVX1iqDq0DdE13GnUBAA3DJeu8WIl1XtzHza+s07a0HD08uqdmXdvN6nIAAG7M8nVegF3pudqWliMfL5tuG0yjLgCg4RBe4BKVjbqj+0YoNJCrwQAADYfwggZ3pqhUH2w9JklKpFEXANDACC9ocMu2petscZli2rXUsK5trS4HANDEEF7QoIwxSko+LEm6PbajbDabxRUBAJoawgsa1DdHc7UrPU9+Pl6aMKiD1eUAAJogwgsaVGWj7th+EWrT0s/iagAATRHhBQ0mr7BEy7anS5ISh3ayuBoAQFNFeEGDeX/LMZ0rKVP3sFYa3Km11eUAAJoowgsahDHGOWWUGEejLgDAdQgvaBCbD59W6ol8+ft66SdX0KgLAHAdwgsaROWoy7j+UQoO8LW4GgBAU0Z4wSU7fbZYK3Ycl0SjLgDA9QgvuGTvbTmq4lKH+kQGaUCHYKvLAQA0cYQXXJIqjbpDadQFALge4QWXZP3BUzqYdVYt/bw1fmB7q8sBADQDhBdckspRl/GXt1cru4/F1QAAmgPCC+ot60yRPtmVIUlKiO1ocTUAgOaC8IJ6e3fTUZWUGQ2IDlG/9jTqAgAaB+EF9eJwGC1O+d+KugAANBbCC+rlq/1ZOpJdoEB/H43rH2V1OQCAZoTwgnpJSj4sSZpwRQcF+HlbXA0AoDkhvKDOTuQV6rM9mZKkBKaMAACNjPCCOnt7Y5rKHEZDOrdWj/BAq8sBADQzhBfUSZnDaImzUZf7GAEAGh/hBXXyZWqm0nMLFdLCV2P6RVhdDgCgGSK8oE4qV9SdOKiD/H1p1AUAND7CC2rtWM45fZFa3qh7OyvqAgAsQnhBrb2dckQOIw2LaauY0FZWlwMAaKYIL6iVkjKHlmxMkyQlDmXUBQBgHcILauXzPZnKzC9Su1Z+uqEPjboAAOsQXlArlSvq3jooWn4+/NoAAKzDtxAu6sipAv13X5YkKYFGXQCAxQgvuKhFFYvSXdMjVB3btrC4GgBAc0d4wQUVlzr07qbyRl1GXQAA7oDwggv6ZFeGTp0tVniQXSN7h1ldDgAAhBdcWGWj7qTB0fL15tcFAGA9vo1Qo/2ZZ7ThYLa8bNIkpowAAG6C8IIaLa5o1L22Z5jahwRYXA0AAOUIL6hWYUmZ3ttyVBIr6gIA3AvhBdVaueO4cgpK1D4kQCN60KgLAHAfhBdUa1Fy+ZTR5CHR8vayWVwNAAD/Q3jBeVIz8rXp8Gl5e9l025Boq8sBAKAKwgvOs6ji8ujre4crPMjf4moAAKiK8IIqCopL9e8txyTRqAsAcE+EF1SxYvtx5ReVqmObFrqyazurywEA4DyEF1RRuaJuQlxHedGoCwBwQ4QXOO08lqvtR3Pl623TrYM6WF0OAADVIrzAKani8ugx/SLVrpXd4moAAKge4QWSpPzCEn24rbxRN4H7GAEA3BjhBZKkD7elq6C4TDGhLTU0po3V5QAAUCPCC2SMcU4ZJcR2lM1Goy4AwH0RXqBtaTnaczxPfj5eNOoCANwe4QXOUZebLotUSAs/i6sBAODCCC/NXG5BiVZ8ky6JFXUBAJ6B8NLM/XvrURWWONQzPFBXdGxtdTkAAFwU4aUZM8ZoUcWUUeJQGnUBAJ6B8NKMbfzutPZlnlGAr7duvry91eUAAFArhJdmbFHFfYx+PCBKQf6+FlcDAEDtEF6aqeyzxVq5I0MSjboAAM9CeGmm3tt8VMVlDvVrH6T+HUKsLgcAgFojvDRDDofRopSKRt24ThZXAwBA3RBemqH1B0/pUNZZtbL76McDoqwuBwCAOnFZeMnOzlZiYqKCgoIUEhKiadOm6cyZMxc8JiMjQ3feeaciIiLUsmVLXXHFFXrvvfdcVWKzVXl59M2XR6ml3cfiagAAqBuXhZfExETt2rVLq1ev1ooVK7R27VrNmDHjgsdMmTJFqampWrZsmXbs2KFbbrlFt912m7Zu3eqqMpudk/lF+mRXeaNuQixTRgAAz+OS8LJnzx6tWrVKr7/+uuLi4nTVVVfppZde0pIlS5Senl7jcV9//bXuv/9+xcbGKiYmRr/97W8VEhKizZs3u6LMZumdTWkqdRgNjA5Rn6ggq8sBAKDOXBJe1q9fr5CQEA0ePNi5bdSoUfLy8lJycnKNxw0fPlxvv/22srOz5XA4tGTJEhUWFio+Pr7GY4qKipSXl1flgeo5HEaLnY26XB4NAPBMLgkvGRkZCgsLq7LNx8dHbdq0UUZGRo3HvfPOOyopKVHbtm1lt9s1c+ZMvf/+++rWrVuNxzz99NMKDg52PqKjoxvsczQ1a/ed1NHT5xTk76Ob+tOoCwDwTHUKL3PnzpXNZrvgY+/evfUu5tFHH1VOTo4+++wzbdq0SQ8++KBuu+027dixo8ZjHnnkEeXm5jofaWlp9X7/pi6polH3lis6KMDP2+JqAAConzpdavLQQw9p6tSpF9wnJiZGERERyszMrLK9tLRU2dnZioiIqPa4AwcO6OWXX9bOnTvVt29fSdKAAQP03//+V6+88opeffXVao+z2+2y2+11+RjN0vHcc1qzt/zPhCkjAIAnq1N4CQ0NVWho6EX3GzZsmHJycrR582YNGjRIkrRmzRo5HA7FxcVVe0xBQYEkycur6mCQt7e3HA5HXcpENd7emKYyh1Fs5zbqHh5odTkAANSbS3peevfurTFjxmj69OlKSUnRunXrNHv2bE2ePFlRUeW9FseOHVOvXr2UkpIiSerVq5e6deummTNnKiUlRQcOHNDzzz+v1atX6+abb3ZFmc1GaZlDb28sn07jPkYAAE/nsnVekpKS1KtXL40cOVJjx47VVVddpfnz5zufLykpUWpqqnPExdfXVytXrlRoaKjGjRun/v3766233tKbb76psWPHuqrMZuGL1JM6nluoNi39NKZf9dN2AAB4Cpctr9qmTRstWrSoxuc7d+4sY0yVbd27d2dFXRdYlHxYknTroA6y+9CoCwDwbNzbqIlLyy7Ql9+elCTdHsuUEQDA8xFemri3N6bJGOnKbm3VpV1Lq8sBAOCSEV6asJIyh5ZUNOpyHyMAQFNBeGnCVu8+oawzRWrXyq4b+oZbXQ4AAA2C8NKELapYUXfSkA7y9eaPGgDQNPCN1kR9l3VWX+3Pks0mTR5Coy4AoOkgvDRRlXePHtEjVNFtWlhcDQAADYfw0gQVlZbp3c1HJUkJXB4NAGhiCC9N0KqdGco+W6yIIH9d1yvM6nIAAGhQhJcmKMnZqBstHxp1AQBNDN9sTcz+zHylHMqWl02aHBttdTkAADQ4wksTUznqMrJ3uCKDAyyuBgCAhkd4aUIKS8r0XmWjbhyNugCAponw0oSs+Oa48gpL1T4kQNd0D7W6HAAAXILw0oQsSj4sqXzUxdvLZnE1AAC4BuGlididnqctR3Lk42XTxMEdrC4HAACXIbw0EYtSykddbugbrrBAf4urAQDAdQgvTcDZolJ9sDVdkpQY18niagAAcC3CSxOwbHu6zhSVqnPbFhoW09bqcgAAcCnCSxOwqGJtl4S4jvKiURcA0MQRXjzcN0dztONYrvy8vXTrIFbUBQA0fYQXD1c56nLjZRFq09LP4moAAHA9wosHyyss0Yfbyht1E2JZURcA0DwQXjzYh1uP6VxJmbqFtVJslzZWlwMAQKMgvHgoY4zzJowJsR1ls9GoCwBoHggvHmrLkRztzciX3cdLE65gRV0AQPNBePFQSRX3MRo3IErBLXwtrgYAgMZDePFAOQXF+uib45LK13YBAKA5Ibx4oPe2HFNRqUO9I4N0eXSI1eUAANCoCC8eprxRt3zKKCGORl0AQPNDePEwyYeydfDkWbXw89bNA6OsLgcAgEZHePEwlZdHjx8YpUB/GnUBAM0P4cWDZJ0p0qqdFY26sZ0srgYAAGsQXjzI0s1HVVJm1L9DsC7rEGx1OQAAWILw4iEcDqPFKeVTRolcHg0AaMYILx5i3YEsHT5VoEC7j8YNoFEXANB8EV48xKKKRt2bL2+vFn4+FlcDAIB1CC8eIDOvUJ/uPiFJShzKlBEAoHkjvHiAdzalqcxhNKhTa/WKCLK6HAAALEV4cXNlDqPFKWmSaNQFAEAivLi9td+e1LGccwoO8NXYyyKtLgcAAMsRXtxc5X2Mbh3UQf6+3hZXAwCA9Qgvbiw955zW7M2UJN0ey5QRAAAS4cWtLdmYJoeRhsa0UbewVlaXAwCAWyC8uKnSMofe3li+tktCHPcxAgCgEuHFTX2+N1Mn8orUtqWfRvcNt7ocAADcBuHFTSVVrKh76+AOsvvQqAsAQCXCixs6cqpA/913UpKUQKMuAABVEF7c0OKNR2SMdHX3durUtqXV5QAA4FYIL26muNShdzexoi4AADUhvLiZT3dnKOtMscIC7RrZm0ZdAAB+iPDiZhZVNOpOGhItX2/+eAAA+CG+Hd3IgZNn9PWBU/KySZNp1AUAoFqEFzeyuGLUJb5nmNqHBFhcDQAA7onw4iYKS8q0dMtRSTTqAgBwIYQXN/HxzuPKKShRVLC/4nuGWV0OAABui/DiJiobdSfHdpS3l83iagAAcF+EFzeQmpGvjd+dlreXTZOGRFtdDgAAbo3w4gZeWrNPknR973CFB/lbXA0AAO6N8GKxXem5WvHNcUnSz0d2t7gaAADcH+HFYs9/+q0kadyAKPWJCrK4GgAA3B/hxUKbvsvWmr2Z8vay6cHre1hdDgAAHoHwYhFjjJ79JFWSdNvgDurSjrtHAwBQGy4LL3/84x81fPhwtWjRQiEhIbU6xhijxx57TJGRkQoICNCoUaO0b98+V5VoqbX7spRyKFt+Pl66/zp6XQAAqC2XhZfi4mJNnDhRP/vZz2p9zLPPPqsXX3xRr776qpKTk9WyZUuNHj1ahYWFrirTEsYY/b9P9kqS7hzaSVHcCgAAgFrzcdUL/+53v5MkLVy4sFb7G2M0b948/fa3v9X48eMlSW+99ZbCw8P1wQcfaPLkya4qtVZKyhw6kdcwIerrA6e081ieWvp56774rg3ymgAANBcuCy91dejQIWVkZGjUqFHObcHBwYqLi9P69etrDC9FRUUqKipy/pyXl+eS+tKyC3Td8/9p0NecdlUXtW1lb9DXBACgqXOb8JKRkSFJCg8Pr7I9PDzc+Vx1nn76aecojyvZbDbZfRpulq1raCvde01Mg70eAADNRZ3Cy9y5c/XMM89ccJ89e/aoV69el1RUXTzyyCN68MEHnT/n5eUpOrrhl9jv0q6lUv9wY4O/LgAAqJs6hZeHHnpIU6dOveA+MTH1G02IiIiQJJ04cUKRkZHO7SdOnNDAgQNrPM5ut8tuZ+oFAIDmok7hJTQ0VKGhoS4ppEuXLoqIiNDnn3/uDCt5eXlKTk6u0xVLAACgaXPZpdJHjhzRtm3bdOTIEZWVlWnbtm3atm2bzpw549ynV69eev/99yWV95T84he/0B/+8ActW7ZMO3bs0JQpUxQVFaWbb77ZVWUCAAAP47KG3ccee0xvvvmm8+fLL79ckvTFF18oPj5ekpSamqrc3FznPr/85S919uxZzZgxQzk5Obrqqqu0atUq+ftzp2UAAFDOZowxVhfRkPLy8hQcHKzc3FwFBXGjQwAAPEFdvr+5txEAAPAohBcAAOBRCC8AAMCjEF4AAIBHIbwAAACPQngBAAAehfACAAA8CuEFAAB4FMILAADwKC67PYBVKhcMzsvLs7gSAABQW5Xf27VZ+L/JhZf8/HxJUnR0tMWVAACAusrPz1dwcPAF92ly9zZyOBxKT09XYGCgbDZbg752Xl6eoqOjlZaWxn2TXIjz3Dg4z42D89x4ONeNw1Xn2Rij/Px8RUVFycvrwl0tTW7kxcvLSx06dHDpewQFBfEXoxFwnhsH57lxcJ4bD+e6cbjiPF9sxKUSDbsAAMCjEF4AAIBHIbzUgd1u1+OPPy673W51KU0a57lxcJ4bB+e58XCuG4c7nOcm17ALAACaNkZeAACARyG8AAAAj0J4AQAAHoXwAgAAPArh5QdeeeUVde7cWf7+/oqLi1NKSsoF93/33XfVq1cv+fv767LLLtPKlSsbqVLPVpfz/Nprr+nqq69W69at1bp1a40aNeqify4oV9ff50pLliyRzWbTzTff7NoCm4i6nuecnBzNmjVLkZGRstvt6tGjB/921EJdz/O8efPUs2dPBQQEKDo6Wg888IAKCwsbqVrPtHbtWo0bN05RUVGy2Wz64IMPLnrMl19+qSuuuEJ2u13dunXTwoULXV6nDJyWLFli/Pz8zD/+8Q+za9cuM336dBMSEmJOnDhR7f7r1q0z3t7e5tlnnzW7d+82v/3tb42vr6/ZsWNHI1fuWep6nhMSEswrr7xitm7davbs2WOmTp1qgoODzdGjRxu5cs9S1/Nc6dChQ6Z9+/bm6quvNuPHj2+cYj1YXc9zUVGRGTx4sBk7dqz56quvzKFDh8yXX35ptm3b1siVe5a6nuekpCRjt9tNUlKSOXTokPnkk09MZGSkeeCBBxq5cs+ycuVK85vf/Mb8+9//NpLM+++/f8H9Dx48aFq0aGEefPBBs3v3bvPSSy8Zb29vs2rVKpfWSXj5ntjYWDNr1iznz2VlZSYqKso8/fTT1e5/2223mR/96EdVtsXFxZmZM2e6tE5PV9fz/EOlpaUmMDDQvPnmm64qsUmoz3kuLS01w4cPN6+//rq56667CC+1UNfz/Le//c3ExMSY4uLixiqxSajreZ41a5a57rrrqmx78MEHzZVXXunSOpuS2oSXX/7yl6Zv375Vtk2aNMmMHj3ahZUZw7RRheLiYm3evFmjRo1ybvPy8tKoUaO0fv36ao9Zv359lf0lafTo0TXuj/qd5x8qKChQSUmJ2rRp46oyPV59z/OTTz6psLAwTZs2rTHK9Hj1Oc/Lli3TsGHDNGvWLIWHh6tfv3566qmnVFZW1lhle5z6nOfhw4dr8+bNzqmlgwcPauXKlRo7dmyj1NxcWPU92ORuzFhfWVlZKisrU3h4eJXt4eHh2rt3b7XHZGRkVLt/RkaGy+r0dPU5zz/0q1/9SlFRUef9hcH/1Oc8f/XVV3rjjTe0bdu2RqiwaajPeT548KDWrFmjxMRErVy5Uvv379d9992nkpISPf74441Rtsepz3lOSEhQVlaWrrrqKhljVFpaqp/+9Kf69a9/3RglNxs1fQ/m5eXp3LlzCggIcMn7MvICj/KnP/1JS5Ys0fvvvy9/f3+ry2ky8vPzdeedd+q1115Tu3btrC6nSXM4HAoLC9P8+fM1aNAgTZo0Sb/5zW/06quvWl1ak/Lll1/qqaee0l//+ldt2bJF//73v/XRRx/p97//vdWloQEw8lKhXbt28vb21okTJ6psP3HihCIiIqo9JiIiok77o37nudJzzz2nP/3pT/rss8/Uv39/V5bp8ep6ng8cOKDvvvtO48aNc25zOBySJB8fH6Wmpqpr166uLdoD1ef3OTIyUr6+vvL29nZu6927tzIyMlRcXCw/Pz+X1uyJ6nOeH330Ud1555269957JUmXXXaZzp49qxkzZug3v/mNvLz4b/eGUNP3YFBQkMtGXSRGXpz8/Pw0aNAgff75585tDodDn3/+uYYNG1btMcOGDauyvyStXr26xv1Rv/MsSc8++6x+//vfa9WqVRo8eHBjlOrR6nqee/XqpR07dmjbtm3Ox49//GNde+212rZtm6KjoxuzfI9Rn9/nK6+8Uvv373eGQ0n69ttvFRkZSXCpQX3Oc0FBwXkBpTIwGm7p12As+x50aTuwh1myZImx2+1m4cKFZvfu3WbGjBkmJCTEZGRkGGOMufPOO83cuXOd+69bt874+PiY5557zuzZs8c8/vjjXCpdC3U9z3/605+Mn5+fWbp0qTl+/LjzkZ+fb9VH8Ah1Pc8/xNVGtVPX83zkyBETGBhoZs+ebVJTU82KFStMWFiY+cMf/mDVR/AIdT3Pjz/+uAkMDDSLFy82Bw8eNJ9++qnp2rWrue2226z6CB4hPz/fbN261WzdutVIMn/+85/N1q1bzeHDh40xxsydO9fceeedzv0rL5V++OGHzZ49e8wrr7zCpdJWeOmll0zHjh2Nn5+fiY2NNRs2bHA+N2LECHPXXXdV2f+dd94xPXr0MH5+fqZv377mo48+auSKPVNdznOnTp2MpPMejz/+eOMX7mHq+vv8fYSX2qvref76669NXFycsdvtJiYmxvzxj380paWljVy156nLeS4pKTFPPPGE6dq1q/H39zfR0dHmvvvuM6dPn278wj3IF198Ue2/t5Xn9q677jIjRow475iBAwcaPz8/ExMTYxYsWODyOm3GMH4GAAA8Bz0vAADAoxBeAACARyG8AAAAj0J4AQAAHoXwAgAAPArhBQAAeBTCCwAA8CiEFwAA4FEILwAAwKMQXgAAgEchvACwVHx8vGbPnq3Zs2crODhY7dq106OPPuq88+/p06c1ZcoUtW7dWi1atNCNN96offv2OY9fuHChQkJC9MEHH6h79+7y9/fX6NGjlZaWZtVHAuBihBcAlnvzzTfl4+OjlJQU/eUvf9Gf//xnvf7665KkqVOnatOmTVq2bJnWr18vY4zGjh2rkpIS5/EFBQX64x//qLfeekvr1q1TTk6OJk+ebNXHAeBi3JgRgKXi4+OVmZmpXbt2yWazSZLmzp2rZcuW6cMPP1SPHj20bt06DR8+XJJ06tQpRUdH680339TEiRO1cOFC3X333dqwYYPi4uIkSXv37lXv3r2VnJys2NhYyz4bANdg5AWA5YYOHeoMLpI0bNgw7du3T7t375aPj48zlEhS27Zt1bNnT+3Zs8e5zcfHR0OGDHH+3KtXL4WEhFTZB0DTQXgBAAAehfACwHLJyclVft6wYYO6d++uPn36qLS0tMrzp06dUmpqqvr06ePcVlpaqk2bNjl/Tk1NVU5Ojnr37u364gE0OsILAMsdOXJEDz74oFJTU7V48WK99NJLmjNnjrp3767x48dr+vTp+uqrr7R9+3bdcccdat++vcaPH+883tfXV/fff7+Sk5O1efNmTZ06VUOHDqXfBWiifKwuAACmTJmic+fOKTY2Vt7e3pozZ45mzJghSVqwYIHmzJmjm266ScXFxbrmmmu0cuVK+fr6Oo9v0aKFfvWrXykhIUHHjh3T1VdfrTfeeMOqjwPAxbjaCICl4uPjNXDgQM2bN69exy9cuFC/+MUvlJOT06B1AXBfTBsBAACPQngBAAAehWkjAADgURh5AQAAHoXwAgAAPArhBQAAeBTCCwAA8CiEFwAA4FEILwAAwKMQXgAAgEchvAAAAI9CeAEAAB7l/wMi2JlXr/ho/gAAAABJRU5ErkJggg==", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " cr_gp_df.plot(x='pop', y='pol', title='Cautionary Rule GP policy'),\n", + " esc_gp_df.plot(x='pop', y='pol', title='Const. Escapement GP policy'),\n", + " # msy_gbrt_df.plot(x='pop', y='pol', title='MSY GP policy'),\n", + ") " + ] + }, { "cell_type": "markdown", "id": "91246eab-af4e-45ad-b681-f5b20d6e95a2", @@ -3013,17 +3364,17 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 28, "id": "f9c0a041-1921-40fd-beaa-1dacabf46574", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[0.23674914103361688, 0.4274663412150027, 0.10944474970918672]" + "[0.05315057491054871, 0.5001404675569652, 0.3328873132349565]" ] }, - "execution_count": 56, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -3034,7 +3385,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 108, "id": "5163a6f7-e13d-473e-8180-6d686a969004", "metadata": {}, "outputs": [], @@ -3066,13 +3417,13 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 109, "id": "56a537f8-545d-4ef9-9671-d0906464400c", "metadata": {}, "outputs": [ { "data": { - "image/png": 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RERHlMQaAREREREREREREeYwBIBERERERERERUR5jAEhERERERERERJTHGAASERERERERERHlMQaAREREREREREREeYwBIBERERERERERUR5jAEhERERERERERJTHGAASUdaTjgPpOJlu4zIpJaRtZ7oNIiIiIiIiIle0TDdARNQUaRowNm+EsWYlqk8eB6SEVtYN2uRp0KfNhFJYmN5+pIR1YB+M1cth7tkNmCYQCEIfOx76zDnQ+vRLaz9EREREREREbgkppcx0E9R+lZWVmW6BqMM4NdWIPP1rOKdPNXm/CIUQfuARaAMHp6Uf6TiIv/IijHWrm60JLLoZgQVXp6UfIspdJSUlUFUVtm2jqqoq0+0QEbUZ38+oMygrK8t0C0QdhiMAKW/YZ04juXoFrH2fQiYTEOEC6OMmQp9WDqWoS6bbI5ekaSDy28fhnDndfE0shsjTT6Dwe38PtVv3lPeUeOf1FsM/AEi8+wZEOAz/tPKU90NERERERETkBQNAynlSSiTefwvJTz5seHtdHRJn3kHikw8R+tI90MdPylCH3kgpYZ88AafiLKAoUHv3TUvIlS2MTRtaDP8uS8SRXPwhQnfdk9J+nJpqJFcsdVWbeP8t6JOmQmh8ayUiIiIiIqLswW+plPOSH73fKPxrwDIR+9OzEP4AfKNGp6+xNjC2bUFy8QewT55ocLs2bAQC1yyCNmhIhjpLn+SaFa5rjS0bEbjpNijBUMr6MdatAVxuQCLr6mDu3A59/MSU9UNERERERETkFXcBppzm1NYi8fF7rRdKifgbL2fVTrKfl/jkA8T++Eyj8A8ArP17EXniv2Fs35KBztJHOg6cJp5/syzL3WjBdrBOHPVUb584lqJOiIiIiIiIiNqGASDlNGP9atejs5zKClgH96e4o7Yx9+xG4r23Wi5yHMReeA52ZUV6msqENgS0MplMQSP1OB73SXLs1PRBRERERERE1EYMACmnWYcPeas/dCBFnbRPctkn7gotC8aq5altJpMU729J0jJT0MhnlNJSj/XcKYyIiIiIiIiyCwNAym1ewx/bSk0f7eBUV8Hav9d1vbFxHaT0OCotV7Rh9Jw0jBQ08hl96gz3xZoPvgmTU9cMERERERERURswAKScJE0T5t5PIT0GRkqXkhR11HZOdZWnehmPAame9poxwvshKc5CtT79oI0Y5apWnzETSiic2oaIiIiIiIiIPOIuwJRTZDKJxMfvw1i3GjIW9XawpsGXjbuzar42HJOnv7ptmAKsepyi2xahr9yH6JO/gn2q+Q1KtFGjEfzCLSnvhYiIiIiIiMirPE0RKB/JRAKRpx6DfexIm47XJ0+DEi7o2KY6gNqjB0QwCBmPu6vv2w8iTwNAoShQ+vSDc/K4uwM0H9RefVLbFAAlFEbBt76PxNKPYaxbBVlX99l9Zd3gnzkHevkcCFVNeS9EREREREREXuVnikB5KfbqX9oc/qmDhiB40+0d21AHET4d+uTpSK5Y4qpeL5+T4o4yS580FQmXAaA2dBiE35/iji4SgQCC192AwMLrYJ86AZlIQIQLoPbqDdGGkYtERERERERE6cIAkHKCU10Fc8tGz8eJUAj69JkIXH09hE9PQWcdwz9/IYxtmyFra1qsU/v2hz7x4iYT0jTh1FQDQkApLsmb0Wde1kR0oh6ngXcAoWnQ+g9M++MSERERERERtRUDQMoJxuaNgIedb9VhIxCYs+DiCLEsDv4uUYq6oOAb30H0mSfgXDjfZI06YBDC9z8Mp+oCkssWw9i8AfjbDrgiGII+dTr8s+dDKc6+jU688BL0OsePwj5fCbW0LIUdEaXXpV2+hWjDpjiUE/J2J3ciIiIiyloMACknONUXPNUL3Q/fqNEp6iY11B49Ufh3P4GxdROMdavhVFYAioDaux/0GTPhG3UlrP17EX3uacA0Ghwr47GLoeCGdQg/+C1o/Qdk6Fm0j7QsyLpaT8c4VRcYAFLOM6WFLeY2rEyuwTH7BBw46KaUYro+FTP0qShQuLt0LrOkhS3m9ouvb81x2NJBd60bpmgTUa5PQ6GSfevTEhEREVF+YQBIOUGo3v6p5uomGULX4Z86A/6pMxrdZ585jehzvwVMs9njZSyK6DNPoPBHP4ZSVJTKVlOjDWvp5eprTXRJrVOLJ6LP4Lh9ssHtZ50KvJF4B58kl+KR8AMYqOVmsN/Z1TkRPBl9BkfthmubnrHO4i3rPXySXIZvhO/HEG1QhjokIiIios6AK9dTTlAHevtipHmszwXJpR+3GP5dIqMRJFcvT0NHHU8oCkRxV/cHKArUnr1T1xBRipnSwq+bCP/qi8goHo8+jQq7Mo2dUUewpNVk+FdfTMbwROQZnLHPpbEzIiIiIupsGABSTvCNHgtR6HJEm88H36RpqW0ozWQiAWPrZtf1xrrVkI6Two5SyLbc1zoO5OemQxPlko3GZpxoIfy7JC7j+CD5SRo6oo60xdzeYvh3SQIJfJD4OA0dEREREVFnxQCQcoLQNARvvNVVbeCaL0AJhVLcUXo5FyoBq/XRf5fIulrIRDyFHaWGtG3vawBWcNQM5a6VxhrXtZuMLYg5ufd73ZmtTLp/fbeY2xBx0r+zORERERF1DgwAKWfoE6cgeNtdLa4T57/6evjnXZXGrtKFu4ES5RtHOjhmn3Bdb8LCaedMCjuijiSlxFH7mOt6CzZO2qdS2BERERERdWZcPZ9yir98NrQRo2CsWQlzx1bIWBQIBOEbdSX85bOh9uyV6RZTQiktA3w+V2sAAoAo6gIRzL1RkEJVoXTvAefcWXcHKAqUbj1S2xRRisi//ccLW9op6oZSwYa3pRi81hMRERERucUAkHKOWlqG4A23IHjDLZluJW2E3w99wmQY691NJ9OnlUOI3Bw1qE8rR+Kt11zV+q4cB6WwMMUdEaWGKlSUiGJUyWrXx5QqHjbJoYwSQqBMKUWF437zljK+vkRERESUIpwCTJQj/POuAnx6q3WioBD+8tlp6Cg1/FPLIYpLWi9UNfgXXJP6hohSaLo+xXXtcG0oSlUGRLnEy+s7RB2E7mq3FHZDRERERJ0ZA0CiHKF274nw/Q8BevMhoAgXIPzgt6C43TE5C4lgEAUPfguiS3HzRZqG8FcfgNa3X9r6IkqFWf4ZCCDgqnahf36Ku6GOVq5PQ0gEXdUuDMxLbTNERERE1KkJKaW3BYgoK1VWup9iRLnNrqxAcuVSGBvXAYkEgIvBnz5tBvwz50JpKTjLIU6kDslVy2GsXXV5Z2Ch++GbOBn+2fOh9uiZ4Q6JOsY+8wCejP4OBoxma24N3IirAnPT2BV1lAPWITwZeQYJJJutuSmwCNcEFqSxKyKi9ispKYGqqrBtG1VVVZluhyglysrKMt0CUYdhAJgnGAB2PtKyIGtrAUVAFBZBqGqmW0oJ6TgoEoAiBERBIaojkUy3RNThTtmn8X7iE2w1t8OptxHEUHUwrg7Mx2jfqAx2R+11xj6L9xIfY6u5HTY+28hlsDoQCwPzMdY3OoPdERG1DQNA6gwYAFI+YQCYJxgAUj7jB0zqLOqcOpy0T8OBg25KGbqp/NCZT+qcCGpDdZBCokwtRSDiz3RLRERtxs9n1BkwAKR8wl2AiYiIskShUoiRCne2zleFSgH6B/t99oUZ/MJMREREROnBAJAoy9iVFbAO7IM0DCiFhfCNuhIi4G6TgHwjpYR97ChqtmyAcCS07j3g9OwNoWkQQmS6PSIiIiIiIqKcwACQKEvYZ04j/tarsPZ+2vAOvx/61BkIXn8TRAs7AOcbY+d2xF9/CbK6iREyQkDt0w/6jFnQJ06G8HWenwsRERERERGRV1wDME9wDcDcZp04hsiTvwIS8WZr1IGDUfDwtztFCJhYvgSJN19xVav06ImChx6FUlyS4q6IiNonKZOIhuOQQqJUKQHqMt0RtabCrkStrIMOHb3UHtAEr50TXcI1AKkz4BqAlE/4KYYow6RlIfrsb1sM/wDAPnII8bdfR+i2L6aps8ywTp1wHf4BgHP2DCK/fRyF3/17CD8X1Cei7HPevoAPk4uxwdgMo8YAAAgIjNJGYKF/Hob7hma4Q6pPSomN5hYsTa7AUfv45dsLRSHK9am4yj8PISWYwQ6JiIiIvFMy3QBRZ2fu2Nr0NNcmGBvWwonHUtxRZsXffNXzMc7ZMzA2rktBN0RE7XPMOoF/i/wCq4y1MGBcvl1CYre1B7+K/gbLkqsy2CHVJ6XEi/FX8FzshQbhHwDUyTp8kPwE/xn5FWqc2gx1SERERNQ2DACJMszYvMF9sWnA3Lk9dc1kAfvggTYdl1y7soM7ISJqn6gTwxPRpxGTzV+4kZB4Kf4aPjX3pbEzas7i5DKsMta2WHPWOYenor+HI500dUVERETUfgwAiTJM1taktD6XOEYSaOMXKuf0KUjL7OCOiIjabo2xHnUy4qr2o+TiFHdDrbGkhY+Ty1zVHrWPY5/VtgtWRERERJnAAJAo07zuYJvXO96K9h1uczQGEWWPNcZ617X7rAOotM+nsBtqzS5zD+qk+51ZVnt4fYmIiIgyjQEgUYZpQ4Z5qvcN9VafSxRdB7S27U0kCguBTrBDMhHlBiklKpxKT8d4raeOdc6p8FRf4bGeiIiIKJMYABJlmH/6TEC4G/mmDhgEtXffFHeUWdoVY9p0nD5lBoTLnyMRUToIj6OaFX4syyiFrxcRERHlMX5yIcowpaQrAldf33qh5kPw5ttT31CGBW+6DVA8vjX5A/CXz05NQ0REbSCEQD+1j6djapxabiyRQf1UbxfY+np8fYmIiIgyiQEgURbwX309/Fdf3+xIQBEKI/zgN6H1H5jexjJALS5B+IFH3IeAPh3h+x6CUlyS2saIiDyaqU/3VP+H+J/xs7p/xwnrZIo6opYM1Qaju9LNdf0sj68vERERUSYJKaXMdBPUfpWVXDcoH9jnK2GsWQnrwF7IpAFRWAh94mToE6ZA+P2Zbi+trDOnEX/rVdj79gBNvU2pKnxjxyOw4FqovXqnv0EiolaY0sRPan6GGGKejgsigB8Wfhu91J4p6oyas8XYhmdif2y1boJvLL4evjcNHRFlr5KSEqiqCtu2UVVVlel2iFKirKws0y0QdRgGgHmCAWD+kJYJ+8RxyHgcoqAAap9+EF6nxOYR69wZ6EcPQzgOlK5lF79GCwG1V28o4YJMt0dE1KwD1iH8IvLrNh07RB2EHxQ+2sEdkRvLk6vwUvx1SDT9EXm0NhJfD98LXXDjKercGABSZ8AAkPJJ27bbJKIOJxNxJBZ/BGPdasho5PLtStdS6OVz4J89D0JVM9hhetlnTiPx8Xswt28FnM/WxFIHD0VgwTUM/4go6y1Prm7zsQftwzhpn0YftVcHdkRuzPHPxBBtEJYlV2GTsRVJJCEgMFQbjDl6Ocb5xkARnffCHBEREeUmjgDMExwBmNucaASRJ38J5/SpZmu0EVcgfP9DEJovjZ1lhnlgH6K/exIwjGZrAjfdjsCc+WnsiojIm7+r/ikSSLT5+JsDX8DVAb7PZZKUEkkk4YMPqug8F+GI3OAIQOoMOAKQ8glHABJlgdjzv28x/AMAa+9uxN9+HaFb7kxTV5nh1FQj+uxTLYZ/AJB48xWoPXvCN3xUmjojonySlElsMrZinbERVU41fELDYG0QZuvl6K952w22KVLKdoV/AJCQ7Tue2k8IgQACmW6DiIiIqN0YABJlmHX8KKz9e13VGmtXI3D19Xk9/TW5ZiWQcPelN7nkYwaAROTZUesYfhN9FrWy9rMbJXDWqMAaYz2m+ibh7tCd0ETbPyYJIVAgwojIaJvPUSDCbT6WiIiIiKg+LmBClGHGhnXuiy0T5tZNqWsmCxgb1rqutfbvhVN1IYXdEFG+OWOfw2ORpxqGf5+z3tyEF2IvtfuxxvnGtPlYAYFx+pXt7oGIiIiICGAASJRxzgVv6zc65/N3vUdpWZA11Z6OcS6cT00zRJSX3kq8i7iLqbnrzU04bB1t12P1Unu0+dgxvtHoqnRt1+MTEREREV3CAJAo0xSPv4ZKHi9CriiAEN6O6UQ7IxNR+1Q7Ndhu7nJdv6Idu/gCwC5zT5uOK1VKcFfwtnY9NhERERFRfVwDkCjDtH4DYO3e6bpe7Tcghd1kllAUqH36wj5x3N0BPh/UHr1S2xQR5Y1D1hFISNf1B6xD7Xq8thw/WhuJu0NfRBelqF2PTUTUERJxiTOnbdgO0LWrgpKuFy9cJxISB/YnAHnxtny+Pk1ElC8YABJlmD51BhIfvQc4Tqu1orAIvivHpqGrzNFnzEb8pRfc1U6YDBEMprgjIsoXJsyU1tcnpYQFy9MxdwfvRLl/Wpsfk4ioo5yvtLH4wyQ2bzRgGp/dPnCwikBA4NABC4ZRc/n2ocM1zFvox8grfBnoloiI3OAUYKIMU7oUwz9ngavawPU3QuT5lFd94hQovfu0WieCQfgXXJOGjogoXxSLLt7qFW/19Qkh0EV4G8U3QOvf5scjIuooJ45Z+O9/j2Dd6obhHwAcOWRjz24LxuduP7DPwtO/jmLJR62vsUpERJnBAJAoCwQW3QR9xqzmC4RA4MZb4Z86I31NZYjw+VDw4Leg9u7bfE24AOEHH4Va1i2NnRFRrhuqDfYUAk71TWrX403R3R/fR+mN3krPdj0eEVF7xWIOnnkiiljM/XIJ9b3zRgI7t7d99DQREaUOpwATZQGhKAjd/iXoEyYjuXo5zE93A8kERCgM37gJ8JfPgdqrd6bbTBulqAsKvvsjmFs3I7lmxcU1AR0Hvu49oU6eCn3qDCjhgky3SUQ5RhUq5vln4/XE263WhkQQ0/TJ7Xq82f4ZWJpcDtPFVOD5gdkQXjdBIiLqYBvWGKira1v4d8mSDxO4ciynAhMRZRsGgERZRBs8FNrgoQAA6TgQXncIziNC80GfPA365GkoLi6GqqpwHAdVVVWZbo2IctgC/xwcs09gs7m12RoffHgw9DWElFC7HqurUoL7Ql/BM7E/wkHz67zO1ssxzde+sJGIqCOsX2u0XtSKo0dsnDlto2ev/F62hogo13TedIEoy3Xm8O/zhBAcGUNEHUIRCu4L3Y2bA4tQ1MQafSO0YfhhwaMY7hvaIY83Th+D7xY8giHqoEb3dRUl+GLwVnwxeCvf44goK1RWtL4pnRvnO+g8RETUcTgCkIiIiDoVRSi4OrAAC/xzscfahyqnBppQMVgdiO5qx68tOlQbjB8UPopT9mlU+i9ACokytRS94j2gCF7sIaLsoSiA3QHn4VsbEVH2YQBIREREnZIqVIz2jUrb4/VWe2F04RVQVRW2baMqwSUNiCi79O2n4vDB9kWAQgB9+nL6LxFRtuG1GSIiIiIiIsKMWf52n+OKMRq6FPNrJhFRtuE7MxEREREREWHsBB/69Gv76D3NB1x9faADOyIioo7CAJCIiIiIiIigaQJf/2a4TVN4dR2476Ew+vbjKlNERNmI785EREREREQEACgqUvDtHxVgy0YDq1cYOHHM/tvtApOm6QgXCGzbbOL40Yu3dylWMWmqhvLZfhSXcHwJEVG2ElJKmekmqP0qKysz3QJRypSUlHy2aH4VF80notzF9zMiyjW2LSEdQPOJBrd36VIMKRWoquT7GeWtsrKyTLdA1GE4ApCIspoTqUP8zCkokFDKul9cXCaHyUQc1onjgGVBKS6B0qMnhBCtH0hERESUAaoqgCZmBCuKgKoqsO327RpMRETpwQCQiLKSfeY04h+9C2vbFtTWu1307Y/QdTfAN/KKjPXWFk51FRIfvQdj80bANC7frvbpC//cq+CbMJlBIBEREREREaUEpwDnCU4BpnxiHtiH6G8fB1q4ouy/+joEr70hjV21nX3mNCK/+RVkXW2zNfrseQjedDtDQKI8xynARJQv+H5GnQGnAFM+4SqtRJRVnJrqVsM/AEh+9D4SG9emqau2k6aB6DNPthj+AYCxYimMdavS0xQRERERERF1KgwAiSirxD96r9Xw75LEK39JcTftZ27dDKfqvKva5JKPIR0nxR0RERERERFRZ8M1AIkoq5gb13koNmHs2g599NjUNdROyQ3uRyk65ythHz4IbciwFHZEnYGUEnusfVhhrMEh6zBMaaFEKcY0fRKm61NRqBRkusVOxZEOdlq7sTK5BsdqT8CGg+5aGaaoEzFNn4ygCGa6RSIiIiLKcwwAiShrSMsCLMvTMcbqlVkdADrnva3PaZ+vZABI7WJIA7+P/gk7rF0Nbj/jnMUbiXfxYWIxHgx/DSN8/HeWDjEnhqeiz+KAfajB7UeN4ziK4/ggsRiPhB/AAK1fhjokIiIios6AU4CJKGtIx93U3/qcaF0KOuk4QlG91ave6onqk1Li2dgLjcK/+uJI4Mno73DcOpnGzjonW9r4TfT3jcK/+upkHR6P/hYVNjfzIiIiIqLUYQBIRFlD+HTPxyiFXVLQScdR+w/wVt+vf4o6oc7ggH0I282drdaZMPFW4r00dNS5bTN34KB9uNW6mIzh/eTHaeiIiIiIiDorBoBElDWEEBBdij0d4xs/0fPjOLEorGNHYR0/ChmPez7eC33GLNe12pBhULv3TGE3lO9WJNe4rv3U2otK290GNQAQc+I4YZ/CKfs0DGm0pb1OZ4Xh/vXYbGxFzImlsBsiIiIi6sy4BiARZZXADbcg/qdn3RX7fNDHuQ8ArZMnkFzyEcwdWz/baVjT4Bs/CYH5V0Pt0fHhmzZkGLSRo2HtaX5KJgBAVRG47oYOf3zqXA5bR1zXSkgcsY+hTC1tse64dRKfJJdii7kdNi7+3gTgx1R9Eq7yz0Op2rU9LectKSUOW0dd15uwcMI+heHK0BR2RURERESdFUcAElFW0cdNhFLW3VVt8PYvQWjurmMYO7ch8sv/gLl102fhHwBYFsyN61D33/8Oc9+nbWm5RUIIhO+5H9rwkc0X+XwIf/Xr0AYN6fDHp87lUkDXUfWbjW34j8gvsdHc0qA2gSSWG6vxb5Gfewq5Ohuvr4cFb5sgERERERG5xRGARJRVZCwKGY+6qlW7tjxy6RL79EnEnv89YLfw5dowEH3uaRT+8P+DWlrm6rxuiUAA4Qe/BXPXDhhrVsA6dBCwLYiiLtAnT4V/xmwoxSUd+pjtJS0T5vatMPd+ChgGREEh9PEToQ4eCiFEptujZnRVSlBru98Yp6vS/L+7Y9YJPBd7ocUQKybjeDL6DH5S+HcoUoo89ZrvhBAoFl1QJatdH9NV4WhKIiIiIkoNBoBElFWMtasgo+4CwMSSj1AwuPXpcolliwHLxciaZBLGymUI3ny7q8f3QigK9DHjoI8ZB+Di9MBsDdKMHdsQf/nPkNFIw9vXrIDSuw/C99zPtQqz1DR9Mo7Ej7mqLVNKMUQd1Oz9HyeXuBrBFpUxrEiuwReC17rus7PoqfZAlVXtqjaAAHqq7kY/ExERERF5xSnARJRVjPXuF8239uyGU1PdYo1MJi9O+3X7+BvXQtrepu21RdaGf9s2I/aHpxuFf5c4p04i8vgvYFdWpLkzcmOKPhFFotBV7QL/HCii6Y8BESeKreYO14+72lgHKaXr+s7ivHPBdW0CCVzwUE9ERERE5AUDQCLKGtK24VxwvysppIRTWdliiVN1wd3ov0unjMfhVFW57yGPyEQCsZdeAFoJcmQ0gvirf0lTV+RFQATwjfADCIpgi3Uz9emYrZc3e/955zwcOK4ft0bWIomk6/rOQEqJSsfD+xmAszaDdSIiIiJKDQaARJQ92jAqTqKVUUeK97e52J+fg7RMz8flOmPzBiCRcFVr7dsD+9zZFHdEbTFA64e/L/guJvrGQ4Xa4L4eSjd8KXgHvhS8vcVRqKINHw8EsnNUayZ5/ZnwZ0hEREREqcI1AIkoe7RpWmzLAaDStStEMAgZj7s+o330MJKrVyAwZ0Eb+sld5m73Uz4v1u+E2r1Hirqh9uiudsMD4XtQ69ThqH0cljRRohRjgNrf1fTzbmoZfNBgutyVtkwphQ69vW3nFSEE+qi9cMw+4a4eAr1Urq1JRERERKnBEYBElD08TNW9zG55mqLQfNAnT/d8WmP1CkjH/RTIfOAlJAUAmfBWT+lXpBRijO8KTNDHYaA2wPXak0ERwCR9guvHmaVPz9p1LTNppu7+vWesbzS6cCdlIiIiIkoRBoBElDWkqrZe9DlOrPUdg/1zF0CEwt7OW1kBp5NNcRWhkMd6bz9Tyi1X++fDD3+rdSWiGOUegq7OZIo+ET2U1nf21aDhWv/CNHRERERERJ0VA0AiyhqiDbvvinBBqzVKcQlC937d87k72wg335jx7ouFgG/0mJT1QpnXQ+2Ob4TvRwCBZmtKRDEeLXgYIaXlTUc6K13oeLTgQXRTypqt8cGHr4fvRX+tbxo7IyIiIqLOhmsAElH20DRA1QDb/VRgNexuFJo2eOjFDUE8TOsVQW8j4nKdPn4SEm+/DuliVKU2ajTU0uZDDcoPw31D8eOiH2F5chXWGhsQkRf/bXQVJZjln4GZ+nSElc71e+JVV6Ur/qHw+1iTXI8VxmpUOBd3Lg8pIUzVJmGufya6qfxdIiIiIqLUYgBI1AlYx4/CWL8WzoVKQFGg9RsAfeoMKMUlmW6tASEEfGPHw9yy0V1911IoPXu7q1UU+EaPhbljq6t6pXsPKJ1sgwuh6wh9+V5Ef/+bFoNS0aUYodvuSmNnlEldlRLcErwBNwUWISbjUCAQFEGu+edBUASwIDAH8/2zoRf5IVWJMEKoqa7JdGs5z5EOFMEJLUREREStYQBIlMecSB1if3oW1v69DW63Pt2FxMfvwz97HgJfuAVCyZ4vT/6Zc1wHgP6Zczz17p8113UA6J85p1MGHL5RoxF+6FHEX/4znPOVje7XhgxD6EtfzbrwmFJPEQoKBNd9bAtTWthsbsXK5BocqzkBGza6aWWYqk3CTH06ipTCTLeYU/ZbB7E8uQq7zD0wYCAkghjvG4s5ejn6an0y3R4RERFRVhJSSpnpJqj9Kisbf1Gnzk0m4qh7/OdwTp9qsU6fVo7QnXenqavWSSlR95//CufM6ZYL/X4U/fj/QHE5BfiS+JuvILl8SYs12sgrEL7/GxBt2JQkX0jHgbX3U1j79kAaSYiCAujjJkHtzS/XRF7UOnV4IvoMjtsnmrxfg4ZJvnHoq/XFON+V6KowXG+OIx38Nf4aVhprmq25ObAIVwcWpLEros6rpKQEqqrCtm1UVVVluh2ilCgr4zIdlD8YAOYJBoD0efF330Ry8YeuasOPfBe+ocNT3JE75t5PEf3t465q/Vdfj+C1X/B0fiklkos/RGLxh0Ay2fBORYE+dQaCt9wBofk8nZeI6PMsaeE/I481G/59noDAWN9ofDF4G7ooRSnuLve8Hn8bHyeXtlr35eAdmOnnztREqcYAkDoDBoCUTzgFmCgPScuEsW6163pj9YqsCQCTq5e7rjXWrUJg4XWeRuoJIRC46lr4Z86FsWUj7JPHAceB0q079EnToBTxSzcRdYzN5jbX4R8ASEhsM3fihH0SPyj4NoqVLinsLrdUOzVYnHT39+HtxPuYqk+GT/BjLhEREdEl/GRElIfsE8choxHX9ebe3Snsxj0pJaw9n7qvr62FffoktL79PT+WCATgnzHL83FERG4tTri/oFHfeacKf4r9FY8WPNTBHeWutcYGOHC3i3udjGC7uROT9PGpbYqIiIgoh2TPyv9E1GFkIuHtgGQSsoVdX9PGsgDb8nSI5+dKRJQGUkqcdFpeg7Uln1p7cdY+14Ed5bZj1nFP9Udtb/VERERE+Y4BIFEeEgUF3upD4ezYCVjTAL/f0yFK2NtzJSJKF4n2LbO82dzWQZ3kPtvl6L9LHJkFF7WIiIiIsginABPlIbV3XyilZXDOu9scxjduQoo7ckcIAX3sBBgb1rqqV7r3gNKzV4q78sapuoDk2lWwDu4HTAOiqBj6xMnwjRkPofEtl4jcq3PqMt1C1uimlHqqL1O91RMRERHlO34bJcpDQlGgz5yDxJuvuigW8JfPTn1TLukz57oOAP0z50AIkeKO3JFSIvHhu0h+/D5Qf3P1kydgfboTorgE4fsehta3X/sexzRgnz4NmCZEcTHUUu5MRpSNhBBQocKG3eZz+IW3EdH5bLo+BUuNla5qNWiY7MuOC1tERERE2YIBIFGe8s+cC2v/Xlif7mqxLnDDLVB79UlTV61Te/eB0qMnnLNnWi7UdWjjJqanKRcSH7xzMfxrhqyuQuTJX6LwOz+C2qOn5/M7dXVILvkQxoa1kPH45dvVAYPgn7MAepaM4iSiz4zUhmGXtacdx2fH7uzZoK/WB6O0EfjU2ttqbbk+FQVKOA1dEREREeWOLFj0i4hSQagqwl97CP7Z8wHN1/j+oiKE7roHgblXZaC75lm7d7Ye/gGAYcBYtjj1DblgV1Yg+ckHrRcm4oi/9Vqbzl/33/+O5PIlDcI/ALCPHkbsj88g/tZrkLJ9640RUcea75/T5mN7KN0xXBvagd3kvvtCX0FftXeLNVdoI3Fr8KY0dURERESUOzgCkHKSTCRgbN8C53wFIBRofftDGzUaQlUz3VpWEZqG4M23w3/1dTC3br7481JUqP36wzd6bFb+vBLL3Yd6yTUrELh2EUQTAWc6GWtWNpz22wJr727Y5ytdT92VloXoM09CVle1WJdc9gmU7j3gn1bu6rxElHojtGGY6puE9eYmT8dpUPHl0O1Zs8RBtggrIXy/4Fv4OLEUq4x1qJOfrZFYppRitl6Oef5ZUEX2/W0jIiIiyjQGgJRTpG1fXGdt5TIgmbh8exKA6FKM4HU3QJ8yPXMNZiklFM6qdf6aI6WEffig+wMSCdinTkHrPyB1TblgHWh9StplUsI6sM91AGju3A6n4qyr2uTiD6FPmZ4dOzoTeRRxoojIKALCjy6iKC/CLyEEJusTsdHcAsflLrYCAvcEv4Sh2pAUd5ebAiKAG4LX4brAQpywTyIuEygQYfRRe0MRfO8jIiIiag4DQMoZ0nEQ+/NzMLdubvr+mmrE/vI8nGgEgXkL09wddQjbcj2S7vIhFyozHgBKw/B2gJF0X7p+teta53wlrEMH4BvKdcMoN0gpsd3chWXGCuyzPgv/eyu9MMdfjun6FGgidz+q1Dq1+F30j67DPwCQkFhqrMAkfXxehKCpogkNA7XMvvcTdVbnztpYs9LAqRNx2DZQWqZi3ESBkVdoUBS+b6VCba2D9asN7NtjIpkECgsFxk3UMX6SDz4ff+ZE5E7ufqqmTsdYv6bZ8K++xNuvQxs2Alqf9u22ShnQltEbltXxfXgkCouAinPe6l1yKis89eJUVgAMACkHSCnx1/irWGGsaXTfKec0Xoy/gs3mVnwj/EDO7oa7yliLBBKtF37OEfsYDtqHMVQbnIKuiIjaxrYlXn8pjjUrG174PHII2LQe6NVbwX0Ph1Faxmn4HWn5kgTeeT0B+3Obyu/ZbeHdNwTufTCMQUP4tZ6IWse5EpQTpJRIrljqut5YtTxlvVAKtWG0iygpTUEj3ujjJ7kv9gfgG3Wl+3qv03k5/ZdyxEfJJU2Gf/Xtsw7i+dhf0tRRx1uT3NDmY9cZGzuwEyKi9pFS4qUXYo3Cv/pOn3LwxH9HUFvrftQztWz5kgTefKVx+HdJXZ3EU49FcPxo5i+IE1H24zdFygnO2TNwzp52XW9s3cQdUXOREJ5DQKFm/m1MnzgFIhRyVeufNgPC7340k9rX20hWlSNfKQcY0sBHySWuareY23HadrEzeJaRUuKCbHnznpacdy50YDdERO1z6KCNjevMVuuqqyQ+fMf7yGdqrK7OwTtvtP6zNE3gtZfiaeiIiHJd5r85E7kgoxFvBxgGYLX+IYWyTBvWAMyKKcCBAEL3Pgi0shuxOnAwAtfd6Onc+vRZrmvV/gOh9enr6fxEmbDV3IG4dP9lZbWxLoXdZCcNnEJHRNljzXL36xdv3mAgEeeF+PbasMaA7fJj7rEjNk4cz/xnYiLKbgwAKTf4A97qFQVQuRZGzlE1QPX2pdfLaLpU8g0djoJvfQ/qgEFN3KlDnzkHBQ9/G0LXPZ1XGzIM2ohRrRcKgcB1N3g6d0dyLlyAdewI7NOnIJubp0L0N15H9J223e2EnU+4wQURZZN9e92HS4YBHDvCMKq99nv4mbelnog6HyYklBPUXr0hiooga2td1WvDR0FwLbScI4SANnwUrE93uqsvLITaq0+Ku3JP6z8Qhd/5EayTJ2Ad3A+ZTEAUFsE/biJEMNimcwohEP7qA4j+/rewDu5rukhVEbrrHviGj2xH995JKWFu34Lk8iWwjx6+fLso6gL/9Jnwz5kPEWjb86Z81zl2LBQQkPA+CkaBgnJ9Wgo6IqJUSSYl9n1qoq5Owu8XGDJMQ3FJ/nwWNQxv72VJj/XUmJH09jP0Wk9EnQ8DQMoJQlWhT5uJ5Efvuar3z5yT4o6aJg0D1r49cCK1ELof2pBhULoUZ6SXXOUvn+06ANSnzYTQsuttTJom7ONHYW5aD/vkcQBA8oN3oE+ZBn/5HCjFJZ7PKQJBhB9+9GLYtnoF7COHACkhQiH4Jk2Fv3wO1G7dO/qptEhKifjrLzW54Y6srUHiw3dhbNuCgke+A8XDrsfUOfRWe3qs75WiTlJHCIHeSi+cdE55Pnahfx6KlS4p6IqIOpppSLz/TgLrVieRqLeygaIAo8f4cMOtgbzYFbewSEHVefebexQW5k/4mSmFRQoA97MqLtYTETUvu745E7UgMPcqmLu2wzl1ssU63/hJ0EZekaauLpKmeTHwWLsKMh777A5FgW/0WARuuAVqaVlae8pVSt9+gKICTusfeLRBg9PQkXtObS0iTz/e6N+orKtFcvFHSK5ajvC9D8LnZkrv5whVhT5hMvQJkyEd5+J6iZoPog07J3eE5Iqlre627Zw9jeizT6Hg2z/KWJ+Uncb5xiAkQojJWOvFAGbm6Gi4Wf7p+Ev8VU/HzNNn4YbAdSnqiIg6kmFc3IH1yKHGn1kcB9ixzcShgxa++b0C9OyV2yHghIk+LP7I3TqAXUsF+g/M7eebDcZP8mHndndrmqsqMGZcy2tRExHxMgHlDBEIoOAb34E2dHgzBQL69JkIffnetIYN0jQQ+e3jSC75qGH4BwCOA3PHVkR++R+wz7jfxbgzM9ascBX+AUDik49S3I170rIQfeaJlgPqZBLRZ5+CdfJEux5LKAqET89YqCZtG8kl7n729tEjsA40M3WZOi1d+HCtf4Gr2sm+CeihpneEa0eZqk9CmVLqqna0Ngp/X/Bd3BG6BYrgxzOiXPDWa/Emw7/6ohGJZ5+KwrZze3rmlR7Cpb79NSgKL/y115XjfCgucfdzHD/JxxGARNSqTjcCsLq6Gm+//TY2bNiAc+fOwTRNlJSUYNCgQZg2bRquuuqqJo9bs2YN3nvvPRw8eBDJZBJlZWWYMmUK7rzzThQVtTy9raamBi+//DLWr1+P8+fPw+/3Y8iQIVi0aBGmT5+eiqeZt5RwAcLf+A7s40dhrF8Dp6ICUATUfv2hT5uZkVF28XfegH3oQIs1MhpB9NmnUPj3P4XwuMlFZ5NcvtR1rX1oP5ya6qyYZm1u23x5ym/LhSaSH78H7WsPpb6pFLE+3QVZ5249TgAw1q+Gb9iIFHZEuWiBfy6qZS2WJJsfSTpKG4G7Q3emsauO5Rd+PBp+CI9Ff4PzTlWTNRpUfC10Nybo49LcHRG1RyzqYMNaw1VtZYWDT3dZuHJs7o7Q2rPb/QYTp05akFJy9H87aZrAvQ+G8ZtfRZBMNF/Xq4+CW+7gmstE1LpOFQCuW7cOv/jFLxCNRgEAuq5DVVWcPXsWZ8+exZEjR5oMAJ988km8++67AABFUeD3+3Hq1Cm88cYbWLZsGf7lX/4F/fr1a/Ixjx07hp/85CeoqakBAASDQUSjUWzduhVbt27FjTfeiIceyt0gIBOEEND6D4TWf2CmW4ETj8FYt8ZdbWUFzE93Qr+SX/KaI20bDRbQccE+eSIrAsDk2lWua81dO+DU1kApys01vuwKbzuyOufOpagTymVCCNwevAmjtOFYllyJ3dbeyxtm9Ff7Yo4+E1P0iVBFZi+amNLCVnM7tpk7EHGiCIkgRvtGYbI+AX7R+i7k3dQy/EPBD/Bh8hOsSq5FAhen0ClQMFobiRsD16O3lntrHBJ1dju2mbDczc4EAGxab+R0ALh5g7uwEwAqz0kcP2aj/4DMfdWUUuLYERtHj1iwLaBrqYIrrvTBp+dWKNl/gIZHf1CIN16O4+D+hiGsqgETJ+u46bYAgiGO/iOi1nWaAHDr1q34t3/7N1iWhfnz5+P2229H//79AQCRSAR79+7Fnj17Gh33wQcf4N1334UQAl/5yldw8803w+/34/Dhw/iv//ovHD16FP/8z/+Mxx57DD5fwz/qpmnin//5n1FTU4MBAwbghz/8IQYNGoRkMok33ngDf/rTn/DWW29h0KBBWLhwYVp+DtSxzB3bANP9ByJz43oGgC2Q0vv0GOv4MfiuuDIF3Xhjn3Ax+u8Sx4F96mTOBoDwOj2RIwCoBVf4RuIK30jEZQIxJwa/8KNACWe6LQDAPvMAno39CbWyrsHt261deD3xDu4O3okJ+tgWz2FLG+8lPsIyY2WDHYEdONhh7UYsHsfXw19FkcLNcohySXWV+w0xAKC22lt9tqn22H9ttQMMSFEzrdi3x8Tbrydw6kTD6dmhkMCseX4svM6fU1OUe/dR8c3vFeDMaRv791hIJiUKiwRGj/GhgJutEJEHneIdIx6P45e//CUsy8Jtt92GH/zgB5fDPwAoKCjApEmT8JWvfKXBcaZp4oUXXgAALFq0CF/84hfh91+82j9o0CD8j//xP+D3+3H69Gl89FHj9bA++OADnDlzBn6/H//zf/5PDBo0CADg9/vxxS9+Eddffz0A4Pnnn4dluR9WT5nhVFfBOnkcdmXFxU0YAMiaam/n8Fjf6dht+D3QsmRKtfT4wd7J3S8Cap++Ka2nzikoAihVu2ZN+HfQOoxfR59uFP5dEpdx/C72R2wzdjR7DiklXoy/gqXGigbhX4PHsQ/jl5EnEXO8jX4moszyOpJMy7GRZ5/n83nr32t9R9m22cDTv442Cv8AIBaT+PDdBJ7/fQyOk3trMvbspWL2fD8WXhfAtHI/wz8i8qxTvGt88sknqKysRGlpaaOQryXbt29HVVUVhBC47bbbGt3fvXt3zJkzBwCwdOnSRvdfum3OnDno1q1bo/tvv/12CCFw4cIF7NjR/BcIyhwpJYwtG1H3y/9A7T//D0R+/m+o+7//G3X//jMkli8BFI+/Qr7cnfqRDsKnez5G7dk7BZ14p5Q2/h1vsb6J94RcoQ0ZBqXMff/6jFkp7Iao40kp8ULsJVho+aKEhMSf4y/DlE3PA9xvHcQaY32rj3fGOYcPk5+0qddUizkxnLcvIC5bWICKqBMaPMTbRKrBQ7LkgmUb9evvvn9FAfoNSP/zra5y8Oc/xFq9xrp9i4mVy9ztaExElE86RQB4KYgrLy9vNE23Jdu3bwcA9OvXr8kADwAmTJgAANi7dy8Sic8+HMfjcezfvx8AMHHixCaP7datG/r2vTgyZtu2ba77ovSQjoP4X55H7E/Pwj52pMF9TmUFEm++AmPrJk/n1AYP7cAO849QFIjiEvcHKErWbC6hT5vhulYdNARqtx4p7Ca1hKIgcN0Nrmp9V46D1rd/64VEWWSfdQBnHXdrV0ZkFFvM7U3et8JY7foxVxvrmw0S082RDjYYm/FfdY/hH2r/J/5X3b/i72t+isciT2G7uatNyzUQ5ZsBg1T07usu5FIUYPrM1tcMzWahkPsRfT4fEAimfwTgmpVJuJ1UtXKpkZOjAImI2iPvA0DDMHDo0CEAwJAhQ3DixAn853/+J+69917cdttt+PrXv45f/OIXOHbsWKNjjx+/uKbXgAHNL2Bx6T4pJU6cOHH59hMnTlz+gOzm+EuPRdkj8dF7MDaua7HGOX0KCLjcdUsI+KfP7IDO8pt/9lzXterAwRC691GDqaBPmQ5R6G4Nr8CCa1LcTerp4ychePMdLa7vpw0fidCX701jV0Qd41Nrr7d6s+n65m5vSkzGcMw+0XphilnSwtOxP+C52As4ZB9pcN8eax+eiv4eL8ZfgeN12QOiPCOEwM23B6G6yACvutaPLsW5/bXr6BH3y7Qkk8Dxo42n4Kba1k3uL6JcOO/g2JH090hElEl5vwnIuXPnLq+vd+rUKTzxxBNIJpPQdR26rqOiogKLFy/GihUr8IMf/ACzZn02Ve3ChQsAgK5duzZ7/vr3VVVVNTrW7fH1j23K888/f3k9wqZ8+ctfxt13393iOcg9J5FAzYol7ooTcUBVAbvlDxFdFt2EroMGd0B3+a1K88HtRDM9GERJiYcRg6lUUoKCH/wDzvzX/4UTiTRb1vWue9ClPE+mxN50K5LjxqP2k48Q3bAG0ri4IY5/2AgUzV+I8JTpEF6nyRNlAWkD8DA7zPY5jd6LpJRIVHubYqaFfSgJZfY97ZnKP2C7ubPFmlXGWvQM9cBtJTelqSui7DR5KqD/MIynHjuHeLzp0WRfuLkLbr2zBCLHN8SK1NV4qnfsEEpK0ruma12txx6d9PdIRJRJeR8ARup9EX/55ZfRpUsX/OM//iMmTpwIRVFw6NAhPPbYYzhw4AB+8YtfYPDgwejd++KaYpem9F7a+KMp9e+LxWKX/3f96cBujo/HW178OxqN4ty55qcjxWIxqG4uQZIr0c0bIBPu1zsKjR2PxJ7dcJp5HYsX3YTS2+9iGOJCdNVy17Xx3Tsh62qheZk2nEKhwUPR73/9K6reeRN1a1ZAJj/78h8cPQYl19+I0JXN7xhq19YicXA/HNOAVtIVgSHDsv7fTGjwUIQGD4X8+jfgxGMQPh1KlozKJGqrLpq3HXmLtaIm/wYHRAAJD2vnlfiKM/q3vMKsxJI6d+/B79R8gBu6Xoeg4nIUPFGemjCpEP/xqxBWLq/DulV1qK214fcrGD0miAVXd0HP3vnxN9EfEDBN91Nmg0Et7e9nfr+AYXjpUeX3JyLqVPI+AKy/To3jOPj+979/ed0+ABg8eDB++tOf4pFHHkEikcCbb76JRx55JBOttigcDqN79+7N3h8KhWC3MgKN3Eue9DYNSxoG+v7fXyCyegUi61fDrqmB4vcjeMWVKJx/NfReveFI2eoowc5OWhbMc2c9HCCROHUSQZdTb9NB6VqK0q/ej5I7vgTj9EnAtqGVlkHrWgoATf6emhXnUPX6y4huXIf6i9do3Xugy9XXoXDewqwPAgEAgSAkmn6ORLlkSmgSXq1603X91NDkJv/d+4SGhIclpsLI7N/yxTXLmt2t+PMSMoGVNWuwoMj9sg1E+SoQBBZeW4iF1xY2ui9f/iaOvCKIjeuirmp1v8CAwb60P/eRVwSxwUOPAwelv0fKPQyJKZ/kfQAYDH52Zbpfv34Nwr9Lunbtijlz5uDDDz9ssBlHIBAAACSTzU/hqX9fKBRqdOylmvr3NXV8/T6bcs899+Cee+5p9v7KyspWpxGTe4kWXvOmmJaNWtMEpkxHaMr0BvdFAUT52rgi2/AhLBKNIpGtP9+S0s/+dzM92qdOIvLkLyFjjT+wWufO4vyfnkPtnk8Ruuue3AgBifJAIcIYrg3BPutgq7U9lO7oHe+JqkTD33EpJSKOuy+il+yrOgDVl7nf80PRI57qD9QdwgS7+VHNRJQ/Jk8DWlka+7IJk3xIJmvg8eN0u02eLrDBS49GLZJGanui3FdWVpbpFog6TN5/m6y//t6lHXebcum+ioqKRsfWX8/v8+rfV3/9n/qP6+b4rFnHjAAAau8+Ka2npglVhShrfqRrI4oCpXv27KYrE3Ek165C/I1XEH/zFSTXr2kwDbhRvWkg8rsnmwz/6jM3rUdy+eKObpeIWnBP6C4Uiy4t1gRFEA+E74Eimv44JZBra3552xHT7WhBIsp9Q4ZpmDjF12pdl2KBaxYFWq1LhcFDVUyamt09EhFlUt4HgEVFRZ7CtfoL9Pbr1w8Amtwh+JJL9wkhGgSMffv2vXwuN8dfeizKDr4rx0GEC1zX69PKU9hN56J6+X0NhaB4eJ1SRToO4u+/jZqf/RTxl/+M5IolSC5fgvhf/4San/0UiU8+aLAcwSXm1s2Q1e5GLyaXL2nTCEkiapuuSlf8sPDbuEIb2eT9Q9RB+GHBo+ij9m7yfiEEeinuL1AICPRUPVwASYGeHvoFgF5q9lyAIaLUEkLgi18JYVp582sadu+p4JvfK8jYjseueuyh4JHvZq5HIqJMyvspwAAwfvx4LFmyBCdONL+u26X76q+zN3bsWLz22ms4duwYKisrmxz+u2XLFgDAiBEjGkz7DQaDGDZsGPbt24fNmzejvLxxQFRZWYnjx48DAMaNG9e2J0cpIXw+BBZeh/gbL7daq0+ZDrWsWxq66hzsM6dd18pIBPb5SqilmRuaL6VE7K9/gtncvJhEHIn33oJTV4vgzXc0uMhgbFzv/nFqa2Dt3wvfyCva2zIRudRVKcG3Ch7EObsC28ydiMoogiKI0b5R6NtM8FffDP80vBx/3dVjjdJGoEQpbl/D7TRDn4oPk4tdjezT4cNkvfGyKkSUvzRN4M67Q5g934+1K5M4eRywbKCsm4bxEwVGjtagqpkd+ayqDXs8esSGbUmUlCqYMt2PUVnQIxFRpnSKAHDBggVYsmQJjh8/js2bN2PixIkN7r9w4QKWL7+4693kyZMv3z527FiUlJSgqqoKr732Gh566KEGx1VUVFw+bt68eY0ed968edi3bx+WL1+Ou+66C926NQyJXn31VUgp0bVrV4wZM6Yjnip1IH3WXDh1NUgu/qjZGm30WARvvyuNXeU3aVmQdbWejnGqLmQ0ADS3bW4+/KvHWLkMvhFXwDdq9OXbnKrznh7LueCtnog6Rne1G65W53s+bpo+GZ8klqJKVrdYp0DBtYGr2thdxylTSzHVNwnrzI2t1s73z0FQZN8OwLa0scfah3N2BYRQ0E/tg8HqwAYXX4iofXr2UnHLnSGUlJRAVVXYtp11a5Ff6pGIiD7TKQLAcePGYdKkSdi0aRP++7//G9/97ncxYcIEKIqCw4cP47HHHkMikUBhYSFuvvnmy8f5fD7cfffdePzxx/H222+jpKQEN954I/x+Pw4fPoyf//znSCQS6NWrF66++upGj3vttdfizTffxJkzZ/Czn/0MP/jBDzBo0CAkk0m89dZbeOeddwBc3OBD0zrFS5FThBAILroZ2vBRMFYtg7lrB+A4AAB18FD4y+fAN3Z8VmzMIG0b5q7tsA4fBEwTSnEJfBMmZzQYa5O2/CwzvDNXcuUy97WrljcIAKF6/L3n+wR1Uo50sMfah/XGJlQ7NfAJH4ZqgzFDn4oipfGum9kiKAJ4tOAh/LzucUQRa7bunuBdGKINSmNnzftS6HbURSPYbe1ptmaqbxK+ELg2jV21TkqJ5cYqfJRYgmpZ0+C+XkoP3Bi8HmN9V2aoOyIiIqLME7KphanyUCQSwU9/+lMcOnQIAKDrOjRNQyx28QN5QUEBfvzjH+PKKxt/OHzyySfx7rvvAri4Dbjf7798XHFxMf7lX/6l2TX8jh07hp/85Ceoqbn4YTQUCiGRSMD5W5B0ww034OGHH27386usrGz3Oahl0jQhE3EI3Q/h92e6ncuMrZsRf/NlyNrPjZwTAr4rxyJ451egNLMLdbaRUqLmH74LeHhbKvj2j6ANzMwXZ6e2FrX/58fuDxACXf75Py7/+4m9+EcYbrfUA1D49z+F2qOn1zaJcto5uwK/jT6L087ZRvepUHF94Gpc678qa0d4rU9uwh/if26xZqJvPO4PfSVrnoMtbawzNmK5sQon7FOXbx+iDsJc/0xM8I3Lml6Bi387Xom/gaXGyhbrvhS8A7P809v8OIY0UOFUwpESpUoJQkpu/G0lSpVsHgFI1FG4CzDlk04znKSgoAD/7//9P7zzzjtYvnw5Tp48Ccuy0KdPH0yaNAm33norSktLmzz2kUcewbhx4/Duu+/i0KFDl0f9TZ06FXfccQe6dGl+l8D+/fvjV7/6FV555RWsX78elZWVCIfDGDx4ML7whS9g+vS2fxCl9BI+H4Sv9Z3F0im5fg3if/1T03dKCXPHNtiVlSj81vchgtk3VasRy/IU/gGAtMwUNdM8JxqBsW4NkmtWeDtQSsh47HIAqJfPdh0AakOGMfyjdok5MWw2t+O8cwEaVAzU+mOUNqLZHWyzwQXnAv4r8hgisumdsm3YeDvxPmxp4wvBiyPSpJQ465xDVMYQFAH0VHpk7DlWWJX4Y/zFVus2m1sxODkA8wKz09BV61Shotw/DTP0qaiRtUjIJMIiiMIsHW25xdzWavgHAH+Jv4LB2gD0Vnt5Ov95+wI+Ti7FemMTkri4s7sCBeN9Y7HQPw/9tb6tnIGIiIgo8zrNCMB8xxGAnY9TU43af/3/AbbVaq0+ay5Ct9yZ+qbaSUqJmn/6PuBht9uC7/8jtL7p20XbOnII0d/9BjLWdCDRmi4/+38Nwtjon56FuaWV9bY0DQXf/B60AdkxRZByiyktvBF/B6uMtTDRMDAvVUpwS+AGTNCzcyOqn9c9joP24VbrBAR+XPB32Gfvx/Lkapx1zl2+r1Tpitl6Oeb6Z8En0nvd85noH7DF3O6qNowQ/m+X/51VI+tyxX/W/QqH7aOuamfq0/Hl0B2uz33EOopfR59BTDY9hVuFiq+GvsQNUahT4ghA6gw4ApDySfZe9ieiFiXXrnIV/gGAsWEtZCKR4o7aTwgBUeBhhIkQUNI4Ks6uOIfI00+0OfxTBw5uNBIzdNdX4Bs3sZkjAPgDCN/3MMM/ahNb2ngq+nssNVY0Cv8A4LxThWdif8TqpPup6OnyqbHXVfgHABIST0afwUvx1xuEfwBw3rmA1xNv47HIb5CUyVS02qwd5m7XtVHEcMQ+lsJusospTWw2tuK9xId4L/ERtpu7YEv3F38uOW9fcB3+AcBGYwsc6biqrXPq8EQL4R9wcRTqH2J/xhGr87x2RERElJs6zRRgonxj7tzmvjiZhLl/L/Qx2TnK5xIppbddgKWErDgH9O6TuqbqSXzyAZCIt/l4f3nj6X1C8yF0z/2wZsyCsXoFrEMHIE0TSpdi6JOmQJ9aDqUwO6fdUfZbnFyGT629rda9GH8Fw7Qh6KZmz1XuN5Pveao/Ly+0eP9B+zBeiL2E+8P3tKct16SUsODuIs0lB61DGKQNSFFH2UFKiU+SS/Fxcmmjqd3FogsWBa5BuX+a6/PVSG87xyeRRBIGggi0WrvSWINoC+HfJQ4cfJxcgge1r3nqhYiIiCidGAAS5SgZ9TYKra2j1tLKsi7vtOyWXXUBahoCQCcWg7l1U5uP10aPhW/8pCbvE0LAN3Q4fEOHt/n8RJ9nSxvLkqtc1TpwsNJYg1uDN6a4K3dqnFoct090+Hk3mVtxg31dVgWd9V2w83sKnZQSf42/hhXG6ibvr5Y1eCH+EmplHa4LLHR1Th3e1+Z1c4yUEquT612fc7u5C3VOBIVKged+iIiIiNKBU4CJcpQIeNvUw2t9JkjF+1uSjEZS0EljzulTFwNKr4SAPq0c4a/eD9GG50fUVkfsY6iWNa7rNxseRhWn2Cn7dMrOvcbYkLJz19eWJZbP2RUp6CR7bDV3NBv+1fd24n0ctNxN/+6p9kChcB+6DVEHQRVqq3UmLFTJatfndeCg0jnvup6IiIgo3TgCkChH+a64EslzZ9wVaz5ow7J/dJlowxdmpaRrCjppTDre16byL7gG+vSZULs2vcM4USpFHG/heESmJ0x3QyJ1+5NVOOkJ2RyPo5kBwMnzfdmWJt3vnL4suQpDtNbXPtWEhhn6NHyY/MTVeWf7y13VtWUrFm7fQkRERNmMASBRjtJnzEJy2SeAiy+M+sTJUELhNHTVPkLTIMIFnkb1qWXdUtjRZxSPIZ4o6YrgoptS1A1R6/zCn9L6VOqupO73WqRp8oOqtj7K7PMK1fydPlrt1Lje1AUAtpk7YErL1c7NC/1zscXchgqnssW6EdowTPS5WwvXJ3zooXTDWZeBsQ8auivdXdVSfrNMiV07TJw+dfHCYY+eKq4c54PPlz8RseNI7Ntj4dyZKjiOQNdSBcNGOAiGONOBiCibMQAkylFqaRkCX7gZibdfb7FOKS1D4PrcCaL0GbOQ/Ph9V7Xa0OFpGwGolpZBGzIM1sH9rur9U2akuKPc5lRXIbl21cWfp2lCFBVBnzgFvivHQWj809QRBmkDEIAfCbjb+XaUNiLFHblXppZiuDYU+6wDHX7ufmp6Ng1qi1G+7HkNvHCkg7POOSRkEgUijDKlFEI0DDu8jki1YSMu4/CJ1jdBCikhfLfgEfwm+nucsE82WTNGG437wndDEe4Dipn6DLyaeNNV7UR9PEJK9i+1QakjpcSqZQY+/iCBSF3Di7OhsMD8q/2Yd5W/0e9Grtmx1cBbryVw4XzDUc4+HZgx049FNwegabn9HImI8hW/ZRHlsMC8hRA+H+LvvgkkG3/JVwcNQfie+3NqF1n/jFlIrljS5PNpVDv/6jR0VO/x5i10FwAGgtCnz0x9QzlISonkx+8j8dF7jTZ8sXbvhCjpivB9D0Hr0y9DHeYPv/Bjmj4Fy4yVrurn+LPr3+y1/quw3zrY6nTgEIJw4LgKOjWomK5P7qgWWySEgAIFDtxPBS5Tc2u5AEOaWJZciZXGapx3PtvApI/SC3P9szBdn3I5cNOF7vn8fg/HlCjF+IeC7+FTay9WG+twzq6EAgV9td6Yrc/AALW/5+Blhn8KlhkrGjy3pujQcbV/gadzU/55980ElnzU9PtQLCrxzusJVF1wcOudwZwNAdetTuKlF+JN3mcawPIlSZw7a+P+b4Shqrn5HImI8hkDQKIc5585F/qkaTA2b4B1+ABgWhDFxdAnToXWf0Cm2/NMFBZB7dUH9pFDLdcVFEDtl97n5xs1GoEbbml51KXfj4L7H4ZSVJS2vnJJ4sN3kfzovWbvl1UXEH3ylyj4zo+gdu+Zxs7y0/WBq7Hb2tPq1MjZejkGadn1fjHCNwx3BW/DX+KvNhsCFiCMbxd+A3vMvXg98U6r55zvn4NCJX0XRK5QR2KnvdtVrR9+9Ff7prijjhOXcfw68jQO20cb3XfSOY0X4i9hj7UPXwvdDVWoKFNKUaaUut4oY5A6wPO0dEUoGO0bhdG+UZ6Oa05QBPGt8MP4dfSpZkPAAPx4KHwfeqqc/tuZ7dtjNhv+1bd6uYHhIzRcOc57IJ5plRU2Xnmx6fCvvj27LSxbnMSCqwNp6IqIiLxgAEiUB0QgAH/5bPjLZ2e6lXazPt3ZavgHADISQXLpRwguujkNXX0mMG8h1B69kFj8IezDBz+7Q1XhGzMegYXXQe3ZK6095Qr7fKWr6d0yHkf8zVdR8OC30tBVfitQwvhewTfxdPQPONJEUKNAwQL/HNwUWNSux7GljZ3mbuyx9iEpDRQphZjoG4/+WvsCrVn+Geil9sQniaXYYe2+HAQGEcA0fQquCsxFiVKMPkovRGQUHyeXNnuucn0abgxc365+vJrhn4KdMXcB4ChteJtGyWXKH6MvNhn+1bfZ3IbSRFfcHPwCFKFglj7dVVALZM+I1B5qN/xjwQ+xyliLlcYanHcuAAAKRBjT9SmY45+JrkpJhrukTFu51N1SCwCwcpmRkwHgmpXG5wfuN2v18iTmXeWHonAUIBFRNmEASERZJbna/S6Rxro1CFyzCELzpbCjxnyjRsM3ajTsinNwzlcCigK1dx8oBbkz1ToTjDUrXW1aAwDW3k9hV1akbZOXfFasdMGPCr6Ng/ZhrDU24LxzASpUDFIHoNw/DSVKcbvOv8v8FH+OvYxqWdPg9o+TSzFYHYh7Q19udmqrlBIWbGhQm50SN0QbhCEFg1DnRFDlVEMRCror3aCLz37vhRC4JXgDrvRdgeXJVdhu7oQFGwoUXKmNwmz/TIzUhqV92l2F3fLIy/oiMprCTjrWKfs0tlu7XNUuS67ENYEFCIog5vhnYrO5DcfsEy0eM0ob4XqzjnQIKUFcHZiPhf55SCABR0oERcDTeoKUv5JJiU93Wa7rD+yzEKlzUFCYW/9+tm02XNdWV0kcPWxj0BB+1SQiyiZ8VyairCGlhLV/r/v6aAT2qVMZm+qsdusOtRunfbnl5bWFlLAO7mcA2EGEEBiqDcZQbXCHnne7uRO/jT7X7BTdQ/YR/DzyOH5U+J0Go6RO2qewLLkKm41tSCABFSpGasMw21+O0dqoJoO6QqUAhUrLu+Reeo6OdGDAgA49oyHNWnOD69oD9iFU2udzYh3ANcZ617UGTGwytmKWfwZ0oePR8MP4fex57LH2NVk/0TcO94Tugiq876KcakIIBBEEOKiJ6olFpdtrW5dFIhK5ds0wEvH2JCMR9+ufEhFRejAAJKLsYVuNNoZojTTcT7uhzJKG+9EDACBdbARDmZOUSfwx+mKrm3TUyFr8NfYqHin4OgBgSWI5Xk281eA4GzZ2WXuwy9qDib7xuDf0JWii7R9RFKEggMyuPyWlxFmnwtMxFU5lTgSA52xvz6v+zyGshPBo+CEctY9hlbEOZ+1zEBDoo/bGTP909FG5hALlFn8b3moCgdxLkf1+Act0HwL6/bn3HImI8h0DQCLKGkLzQQSDkPHWF5m+RCnkZhvZyolGYKxfC+vQfsAwIeMxT8fn0u7VndEGYzPiSLiq3WXtQaV9Hofto3gl8WaLtZvNrQjE/bg7dGdHtJlRrYWjjeq9DiPKEAFvoyqVzw2ZE0JgoDYAA7Ns4xmitgiFFPTtr+LEMdtVffeeCroU5144NmKUhs0bTFe1/gAwYBC/ZhIRZZvcWnyCiPKeb/wk17VK7z5QuvdIYTfUFlJKJJZ9gtqf/RSJd16H9ekuWAf3QUbq3J/EH4Bv1JWpa5Labbu503WthMR2cxfejL/rqn61sc7zKLNsI4SA8DhX1PEYGGZKP7WPp/q+HuuJck35bPebepTP9qd9PdKOUD7b/a7ck6fqHAFIRJSFGAASUVbRy+e4r502Myc/ROe75JKPkXjrNcByvyj65+lTp0MEMjuFk1oWld5GdB61j6FKVruuX22s89hRdpFSeh4BmJDuRlRm2gz/VNfhZoEIY7xvTIo7IsqsSVN1DB/Z+oi3QUNUTC/PvR2AAWDgYA0zXASdpWUKrlnEv99ERNmIASARZRVZU+2+tq42dY1Qm9gXziPxXstTPFujDhiE4PU3dVBHlCohEfJUH5fup/YDwDH7uKf6fBDNkZ2AuyolmK3PcFV7XeBq+ET7dmqPOjEcso7gkHUEdU6kXeciSgVVFbjv4TDGT2z+3/rosRq+/kgBNF/uXri89c4g5l7lR3PXXvsNUPHN7xUgXMCvmERE2YiLMxBRVkmuXu661li3GoGF10FofCvLFsbaVfC8HeIlPh/0ydMRvOEWCD03R0h0JmN8V+BTy/3OzmWKt80tnBxZD68jlXr8GWXS7cGbEZVxbDK3NFtznX8h5uoz2/wYJ+3T+CixGFvM7bBxcX01BQrG+kbjav8CDND6tfncRB1N1wXueSCMhdfbWLcqidOnLk7q79FTwfRyP3r3zb6drb1SFIEbbw1i9jw/1q5K4tQJAdsGyrppGDsRGDxE5cwMIqIsxm/NRJQ1pJSw9u5xX19XC/vMKWh9+7fp8ZxoBOa2LXCqqyA0DeqgIdCGDINQeOW6ray9uz3V+8ZPhNqzN0RRF/iuHAcl5G1UGWXOFH0S3oy/h4SLjUCu0EZigNYfMFa7Pn9bd8Otcqqx1diOWhmBX+gYoQ3DQLV/2r+UCiFQIoo9TXvuoXZLXUMdTBUq7gvdjcnWeCxLrsJeaz8kJDSoGOsbg7n+mRiiDWrz+Xebe/Db6HMw0XDTAQcOtpo7sMPcja+F7sZEfVx7nwpRh+rZS8XNd+T337LiEgXX3RBESUkJVFWFbduoqqrKdFtERNQKBoBElBZSSsC2Wx6tZ1sX/+vlvAnva2ZJw0D8zVdgbFzXaJ06pVt3BG+6Hb5Roz2flwCZTHqq1wYOhn/WvNQ0QykVFAF8JfRF/C72xxbXuisShfhi8FYUKgV4Ca+7CgwBYIY+1VM/ESeKv8ZfxVZzBxw4l29/G++jn9oHdwVvS/uus9P1yXgv+bGr2p6iB7qpZSnuqGMJITDGNxpjfKNhSxtJaSAg/FBE+y6iVNiVeLqJ8K8+Gzb+EHsB3dVu6Kv2btfjEREREXUGHOZCRCkjpYT56S5EnnkSNf/0A9T80/dR/dO/R+ylF2CfOtn4AFUD/N4WjlbCBd56Mg1Efvv4xamqTWxS4VScQ/R3T8LYusnTeeki4fH18FpP2WWCPhYPhe9DkShq8v4Baj/8oOBRlKml8As/5vlnuTrvEHUQBqsDXfcRcaL4ReRxbDa3NQj/Ljlun8R/R57AAeug63N2DPejDtsbmmWaKlSElGCHPI+lyZUwWgj/LrFgY3FiWbsfj4iIiKgz4AhAIkoJaduIvfgHmFs+F6Ql4jDWrYaxfg0CN96GwJz5l+8SQkAbOhzWru2uHkMUFkHp2ctTX4mP3od9uJUQQErEXnwe2uChUIq6eDp/Z+cbNwH20cPuinUdvpEcaZnrxvpGY3TRSGwzd2CPtR9JaaBQFGCyPh4DPjf1dlHgGpxzKrHZ3Nrs+XopPfD18L2epuy+En8DZ5xzLdaYsPBM9Hn876IfQ2/nphRurTfdX0g45ZxGpX2+zVOf84UtbawzNrqu32xuwxflrQgI7jpKRERE1BIGgESUEvHX/to4/KtPSiTefAVKOAx9Ur2pfo7t+jGkh1oAkKZ5ceSfG5Z5cZORq6/39BidnT55OhIfvAskW5/mqU+eBhEMpqErSjVVqJioj8dEfXyLdYpQcF/obgw3hmJZcgVOO2cv31coClCuT8PCwDwEhft/F7VOLTa1ECjWVyfrsMXchmn6ZNfnd8uRDnZZe7AquQbH7ZNw4KBOetux9qxd0ekDwDoZcT1NHAAsWKh2atBTZQBIRERE1BIGgETU4ezKCtdBW/y9t+CbMBlCUS5uArLf/a6iiEbhnD0D1eUoQOvAPshY1PXpjW2bGQB6pIRCCN99L6LPPQ04jadiXqL26YfgopvT2BllC0UomOWfjpn6NJxxzqLOicAv/Oij9oImvH8s2WbubHLab3M2G1s7PACMOFH8NvosDtouR78244JzoYM6yl1KG1anEVzRhijtaqodHD0cg+MIlJYqKOwiuQNwjrlwwcGpEzakI1HWTUWvPrm/UzURtYwBIJFHMpmEsXUT7BPHAMeBUloGfdJUKF2KM91a1nA9yg6ArK6CtWcXfFeMubgBSBPr8rXEPl/pOgCUkTpP55YRb6N36CLf6LEIP/Qo4q/9Fc65sw3vVBT4JkxG6JY7IQIcsdOZCSHQS+2JXu38vhHxOMouIt1fBHDDkhaejD6DI/axdp8roPB3okCEUSy6oFrWuKoPiSC6KiUp7oqILjl9ysaH7ySwa4cJx6m9fHuv3grmLQxg4hQfg8Asd+yohQ/fTWDvbguy3h5e/QaoWHCNH2PG6ZlrjohSigEgkUtSSiRXLEHiw3eBz+08m3j/beiTpyF4650QPv7RtE8e91RvHT8G3xVjINuweLyM1LZedInHwEn4/R67oUt8w0ZA+/ufwjq4H9bB/YBpQunSBb5xE7muInUoP7z9XvtFx/5ebzA2d0j4B4BBFi6OEJ3pn453Eh+4qp+uT4WvDSNHici7gwcs/O6JCJLJxvedPuXgz3+I4fQpP264hct7ZKvdO0z84Zlok9fbjx+18dxvY1h0k4MF1/CCFFE+4icmIpcSH7yD5MfvN32n48BYvwbOhfMIP/hNCC09C8xnK2l7W5vv0lRRUf8ypEtKifv1srTBQwFNcz3KUBs+ynM/9BkhBHxDh8M3dHimW6E8Nso3HB6WjMMorWP/Pa401nTYucqUzr3+3yWz9XKsTq5Dlaxusa5AhDHfPzs9TRF1ctGIg2efijYZ/tW39OMkevdRMXEKL4hnmwsXHPzxd02Hf/W9+2YCvfqoGDW6c3+fIcpHXDSFyAXr2NHmw7/6dQf2IbliWRo6ym5qWTdP9crf6oWmAR43hVC793D/OOEC+MZNdF3vL+cXSyIAqLAr8Xr8bfxz7b/jJzX/B/9a+594N/Ehqh130zRTqZfaE8O0Ia5qNWiYoU/rsMe2pIWjtrcRzy05a7e8k3FnUaCE8WjBwygRxc3WFIpCPBp+CCVK8zWpVufUocKuRMyJZawHonRZt8ZAPObuQu2SjxOQbbioS6m1enkSpumudtknrSS9RJSTOAKQyIXkKvehnrF6BfxzF0AonTdf16fOgLHe5agYfwD62AmX/6/SpRhOPO7uWM0H4XE6aXDRTRc3A6mpbrmt+VdD7dXb07lzgbQsQAgIlQs9U+uklPg4uRRvJt6FxGdf5mpkLU4lTuPDxGJ8OXRHSnbV9eLO4C34r7rHW9099vbgTShQwh32uDY8jnZuhQVva6Dms55qd/x/hT/CGmM9Vhlrcc6pAACUKl1Rrk/DTH16h76WbtnSxlpjA1YaF3d7vmSENgxz/TMxRhvN9c8oL21cZ7iuPX3SwamTNvr05VfNbCGl9PQaHthnoeqCg5Kunff7DFE+4rsykQvmzu2ua52q87BPnYTWt18KO8pu6oBBUAcPhX3oQKu1/llzLq+1J6WEU1np/oEsE86ZU1B793V9iNKlGAXf+j6iz/0WzqmTTRQo8F91LQLXLHLfR5ZzohEYa1fBWLcazoXzAACle0/o02fCP3U6RIBr9VDTlhkr8UbinWbvt2Dhj7EX4Ycf4/Uxaeysod5qL3yv4BE8HXsO552qRvf74MNtwRsx21/eoY+rQ0dIBBGTLi9atCKTo9myUUgJ4qrAXFwVmAtTWgAkfCIzU9IMaWBVch3eTryPJBqPjNlr7cdeaz9m6TPwxeCtUNqwpi1RNqs673639Uv1fdx/PKMUs0wgUudtVCYDQKL8wwCQqBXStoGkhwWmAMhYx+4ymWuEEAh/9euI/OaXcM6cbrbON24iAtd84bMbLOviJxQPnFgMXseyqaVlKPz+P8I6sA/GpvVwqi5A+HzQBg6GPq08rzapsE4cR/TpXzfaAdk5dwaJN1+BsXIpwg99C2o391OpqXOIyzjejL/rqvbl+OsY47sCqsjcyNJ+Wl/8z8J/wk5zNzaZW1Hr1MEvdIzQhmO6PhkhJdThjymEwFTfJCw1Vrb7XDp09BDdO6Cr/NQRG31ccKpw1q6AwMWp412UIlfHVTs1eDzyFE47Z1utXWmsQbHSBdcFFrazW6LsompwPX30Yj1HwmYTpQ1/njUmBUR5h7/WRK0QqgroOmC4HzbPEVWAUliIwkd/iMTSj2GsW90ggFJ69IR/1jzo08obTpXWtIufMG330+CExzUDLx+nKPANHwnf8JFtOj4XONVViP72cchopPmaC+cReepxFP7gn6CEOj4gody13tgEA+6+7VXLGuw0P8U4/coUd9UyVagYp4/BuDSORpzjn4mVxhpY7ZwObMDAY7Gn8FD4awgK/g3pSAesg3g/8Qn2WPsu36ZAwRjfFbjWvxD9teaHKZnSxK8jT7sK/y75KLEEvZWegBAoEcXoq/bmtGDKeQMGadi7293nM0UB+vbjUiPZRFUF+g1Qcfyou79Vfj/QoxdfQ6J8wwCQyAXfFWNgbt3kqlZ0KYbKOQ8ALoZzwetvRODq62GfOgmZTEApKITSs1eTX4aEEFB69oJz0uWi+j4daq8+Hdx1/kgs+6TF8O8SWXUBxtpVCCy4Og1dUa44YB3yVH/QPoRxyGwAmAnd1W64N/RlPBt7AQ68TZH7vH3WATwZ+R2+U/ANaC5HvNnSxm5rD87Y5yAA9FZ7Y6Q2jFNQ/2ZNcj1eiL/UYA1LAHDgYJu5E7vMPfh6+KsY4xvd5PEbjS045TQ/kr0pSSTxVOzZy/+/l9ITV/nnYpo+mUEg5awZs/yuA8Cx430oLOJ7ULpVVtg4dsSGbQNdSxUMGqJCUT57z5kxS8fxo+6WrJg0VYffz/cronzDAJDIBf/MOa4DQP+MWdxg4XOEpkHrP8BdsZfp1rYFmUhAcORaI9I0YWxY57reWLMS/vkL+eWULru45lrq6vPJRH08ipRCvJP4EPutg+0610H7MNYbm1Dub3m34ogdxSuJN7DD3IXE59akK1W6YlHgmoxvzpJpR6yjTYZ/9Vmw8Lvo8/hx4Y/QTS1rdP9Kw+WGVi047ZzB8/G/4Jh9HHcGb+X7LOWkK67UMHS4hgP7Wn6v9/uBaxYF0tQVAcDxoxbeeyuBfXsavjalZQrmXuXHjFk6hBCYOFnH6uUGThxveRRgQaHAgmv4GhLlI16aIXJBGzQE/tnzW61TBwyEf+6CNHSUn6TjwKmscH+A48A5621kRmfhnK8EEu43JnCqzkPGYynsiHKN1w0pipX8WTuzLYZqQ/C9gm/ip4X/gPtCX8FXg19q87lWGKubvS8pk3gx9gp+XPe/scHc3Cj8A4DzzgX8MfYiPkh80uYe8sEnyWUthn+XmDCxLNl4HUcpZYOdfttrubG6QwJFokxQFIGZc3S0ll8PG6mhWw9+xUyXfZ+aePwXkUbhHwCcr3Tw6l/iePUvcUgpofkEHvxWGP0HNj9QoUuxwMPfLkBxCV9DonzEEYBELgVuug0iGERi8UdNblThGzsBoS/eDeHTM9BdnpDedicDADjuj5FSwj58EMk1K2Ad3A9pmFC6dIE+YfLFzT8K3S0InxOcNkxFbMsxlLem6pNaDKLqExCYok9McUe5oafaHT3V7pBS4o/xF9t0juP2ScRlvNFagEmZxK8iT+GIfdTVed5KvIeh2mAM0Qa1qY9cFnNi2GbudF2/ztiIW4M3NtjIRv7tPx3pk+QyzNSnc4o25Zy6WgcvPh9r9aPazm0WNqw1MHWGPz2NdWJ1tQ6eeyba6v55a1Ya6NtfxbRyPwoKFTz6gwLs3G5i7cqLowGlI1HWTcXUch0Tp+gIBDhKmShfMQAkckkIgcA1i6DPmgtj43rYx48CjgOltAz6lOlQu3H3xvYSqgpR0hWy6oLrY5TSUld10rIQ++ufYG7e0OB2JxFH4v23kVjyEcJfuR++K/JjDTNRUgKoKmC7W+xZBEMQoXCKu6JcMlDtj0HqABx2ETZN8I1DV6UkDV3lDtmWCxr1GNJsFAC+GX/Pdfh3ybLkyk4ZAF6Q1Z7WZIwjgZiMoVAUXr5NEQq6KWU453gYmd6KSuc8DtqHMUwb0mHnJEqHdasN16u0LPskiSnTdU53TzEvr8nyxUlMnXHxNVFVgXETdIybwEELRJ0NLz8SeaSEwgjMmY/wV+5D+KsPILjoJoZ/HUifNNV1rTpkGJRid6FD/JUXG4V/DSSTiD73NKzD7Vu/K1sowRB8Y8a7rtenTGu4IzN1ekIIPBD+KkpbCfb6qn3wpeDtaeoqd7QnANSgIiQarm0alwmsMdZ7PtdWcwcM6W4353yituEjrorG0+Jm6O7/JrlVaZ/v8HMSpdqm9Ybr2rNnHJxsZZ25TIvHJY4csnDogIXqqtycAbFpg7fX5MSx7H5NiCj1OAKQiLKKUlDYetHfCL+7BYqtkydgbFjbeqFtIf7OGyj89g9d95DN/PMWwty+pfWpvboOfebc9DRFOaVEKcaPCr6LNxPvYqOxBRY+W2MoAD+m61PwheB1CAouFv557Rn5Mt43Fr7P7QK8y/wUBtx/2bvEgYOojEIXxW3uJxeVKWUIiSBi0t1aqGVKaaMRlwBQrk/D4uQy1MnWd1R3y+0Oz0TZpMpjSFZd5aBv/xQ10w6VFTYWf5jElo0GzHrXRoaP1DD/aj+GjfBlrjmPqi94fE2qHfRzuScfEeUnfgIhoqxibNnoutY6uO/iLsCBlsMHY80K1+e0jxyCfeok1N59XB+TrbS+/RD68r2I/fkPzYeAPh/CX3sQamnj3S+JAKBIKcQ9obtwS+AG7LMOICETCIsQRvqGwy+4xlNz2hMAzvPPanRbrVPX5vP50fmmefmEhun6FCxOLndVP1uf0eRrFlZCeCT8AB6PPo2Y7JiNkgao/TrkPETp5NMELNP9yGbNl33Tf48esfD041HE442fx749FvbtsXDLnUHMmpsbf9s0n4Dp5TXRsu81IaL0YgBIRK7Y587C2LwBTnUVhM8HbdAQ+MaOh9A67kqpdBzYx464PyCZhH3mFLSBg1sss456OCcA6+jhvAgAAUCfMBlK11Ikl3wEc9eOzzZaUTX4xo5HYME1UHv1zmyTlBMKlDAm6uMy3UbOEEJAQHjeROLWwI0YqDUeoqGLtoV4fdU+CCmh1gvz0AL/XGwwtqBOthyedlPKUO6f3uz9A7T++IeC7+Gj5BKsMzY2GAnr1QhtGLqr3dp8PFGm9BugNrnTbHP69suuZUWiEQe/e7Lp8K++11+Ko3t3BcNHZf9IwEGDVeze6e41UTWg/4Dmd/8los6BASARtciJ1CH2l+dhfbqrwe3GmpUQb7yC4E23eVq3r+UHczzvBCwtFx983NS0pz7LaQMGQbvvYTh1tXAqKwAhoHTrDiVckOnWKEWklNhvHcQGczNqnBr4hA9DtSGY5puMkNJ4miOlxgC1H47Yx1zXfzX4JUzzT27yvhHa0Db1MEcvb9Nx+aBY6YJvFzyEJyLPoFrWNFnTXemGb4UfbHUae5laii+H7sDNgUX4XfR57LH3ee5Hg4YbA9d5Po4oGzitLSfyOZUVEh5WdUm5tasMRCPuPmMu+TiZEwFg+Ry/6wBw3AQfwgXZFcoSUfoxACSiZjmxGCJP/Decs2eavF9GI4j9+Q+QhgH/jMZT1rwSmgZRWARZV+v6GKWkq4uaEjgVZzv0nLlIKSyCUliU6TYoxSrt83g69gecsE82uH2buRNvxt/FzcEvNDnFlDreIv81+HXsaVe15b5pzYZ/ANBNLcMobQQ+tfa6fvyh6mBM1Se5rs9HfdTe+EnR32FtcgNWGesu7+jbR+2Nmfp0TNUnehpdGVJC+FbBg3gn8QGWJVcigaSr43To+Hr4q02O7iTKBYcPegsAP3gngW98J3suNG5Y634N1f17LZyvtFFa9tmIuWjEweYNJk6furiRRveeCiZP1VFQmLlQbcQoDaOu1PBpKyFgKCRwzSKu1UtEDACJqAWJ995sNvyrL/76S/CNGu16R96WaMNGtLxbbz2ia6mrtev0ydNg7dvj7pwFhdBGjnJVS5Rtqpxq/DzyOGpk0yG6CRMvx1+HJS0sDMxLb3Od0CjfCJQppah0Wt71VYWCawILWj3fbcEb8V91RxFHotXa0doo3Bf+CjecABAUQcwPzMH8wJzLuzO3Z41GRSi4MXg9rg7MxxZjO845lVAg0EfpDVWoWG2sxUHrMCxYKFaKMU2fhHJ9OroovABD6WcYEls3GVi/xsD5CgdCAfr1VzF9lh8jRmlQFHe/C7bHDWRPncyeHWcdR+J8pbcA83ylg9IyFY4j8f5bCSxfmoT1uQ3V33srgfLZftxwSwCqmv719YQQuOf+MF54Lopd25sOAYu6CDzwSBhl3Tj9l4gYAFIesisrYB8/CjgOlNIyqAMGteuDfmcl43EYG9e7K7ZtJNeuQvC6G9r/uInWv9heZhiQjgOhtHz11Td2PJT33oZT1fKXcADwz5rboesaEqXTa/G3mw3/6nsz8S4m6mPRVcnP0a7Z4qB9uNXwDwBsOFhlrMPNwUUt1vVSe+K7BY/gqeizqJLVTdb0U/vgi4HbMFDrz799TWjLz0RKiQP2IWw2tqJORuCHHyN9wzHeNxYz/I2XwBinX9kRrRK125nTNp55IoKqCw2nvu7aYWHXDgtDhmu478EQgqGOH8UmveVtKSXExf96WWVGUS7+7v/1TzFsXGc2WWNbwIolSdRUO7jn/pDrMLUj+f0C9z0UxqEDNtasSOLoEQu2BXQtUzB5mo4Jk3X4/fxbQEQXMQCkvGEdPYzE+2/D2t9wepTSvQf886+GPnkavwx5YO7fA5jup0uYO7e1OwCUUsLa726kHgDISB3s06eg9enbYp3QfAg/8DAiT/4KMhppts43biL8C65x/fhE2aTGqcVWc7urWgcOVibX4qZWAidqn+XJ1a5r1xjrsChwDXytjNjrp/XF/yr6J2wzd2KDsRk1shY6fBiuDUW5fxpKlOJ2dk31nbHP4vfRP+Gkc6rB7evMjXhVvIkvBe9g4EdZqbrKwW9+FUFdbfOp18F9Fn7/VBTf+E5BqyPYFOXiUs1ulXXPnvXmhBDo00/F8aPuRiWqKtCrt4qd281mw7/6tm8xsXWsiYlTMrPjuhACQ4ZpGDKMX+2JqGV8l6C8YO7egehzz1y8FPc5zrmziP/leThnTiN4460Z6C43yVjMW3083v4HtSzAbP2DVsPHdden2qsPCr77d0h88A7MbVsa/FsRJV3hnzUX/tnzWx1NSJSt9lr74cD9t7Pd1h7chM4bAJrSxGZzGzYZW1Dj1MEvdAzXhmKmf3qHhWi7TfcXNCIyimP2cQzRBrVaqwkNk/TxmKSPb0d31JpzdgV+HnkcUdn035k6GcHTsefwAO7BBO6QTVnmkw8TLYZ/lxw6YGP7FhMTJrccXoULAA9LNGPOfL/74jSYMUvH8aPuPquO/duGGauWub8QvnJZMmMBIBGRWwwAKec51VWI/vH3TYZ/9SWXfQK1X3/o4zv3guhuiWDIW32gA3YW1TRA1Vp9LRs8btD946qlZQjf/TU4N90G++hhSMOA0qUY6sDBDP4o58Wlh+nzABLS3eYF+eiQdQRPR/+A2s9Nlz5kH8GHycVYFLgG1/qvateocSklEi7W6qsv4fE1pNT6S/zVZsO/SyQkXoi9hCt8I+EX2RV4UOeVTEpsXu8+vFqzMtlqABiLeutBKB7m26bBhMk6VixJ4vSpli+U6Tpw1bUBJOISB/a5/zx67IiN2loHRUX8PElE2YvvUJTzkmtWuJ6qmly2OMXd5A9t2AjA534tPN+VY9r9mEIIKF09rEmmalB79fH8OEpBIXyjx0KfMBna4KEM/ygvFIiwp/qw8Bby54sT1kk8FnmqUfh3iQMHbyfexwfJT1yfMymTOGWfxmn7DJJ/C1aFENDgbdH1ILJ7l0ZHOthnHsDy5CqsSK7GAevQ5U018s0Z+yz2Wvtd1caRwAZjc4o7InLv9EkbSQ/XeI4cslv9Xfa6Ccjpk1m0CCAAn0/gwW8VoFfv5j/zBYLAA4+E0bOXiljc+3tbPJaf74dElD84ApBynuuNKgDYx4/CPncGaveeKewoPyihEPSJU2Csc7eGlbFtC5xz56BPK4c2fGSbQzUZaX6NvkZsC86F81DLurXpsYjyyRW+EdDhgwF30+gn+MamuKPs9HL8DRho/aLRO4kPME2f3OJ04NP2GXySXIZNxhaYuDhSRIeOKfpELPTPgwNvXwaz+avjBmMz3kt8hHNORYPbeyrdsShwDSbm2XTkneZuT/U7zN2Y5Z+Rom6IvDFNb+8mjnPxv2oHbhTbkefqKF2KFXz37wqxaYOBNSsMnDxh/+12gSnTdZTP9qOoy8XPr8Gg9xHggQDXGiei7MYAkHKadBzImmpPxzhVVTkfAErThH3iGGQiAREugNq3X0pGsQUW3QTr4H44lRWt1srKCpiVFTB3bIXabwDC938DSlGRp8eTluV6Tb9LnOoqBoBEAIIiiGn6ZKww1rRaq8OH6Xrj3Uvz3Wn7DA7Yh1zVSkisSq7FDcHrmrx/l/kpno7+AebnAlcDBlYZa7HJ2OJpTUYAqJN1nuo7Up0TQURGEBABFIsuDaY/f5D4BG8l3mvyuDPOOfwu9jyqnBpcFZibrnZTLuZxOnZcdsA6uEQdpKSrt8+ERUWi1U1AAkEg4eGf+bCR2fk106cLTJ/px/SZfti2hHQAzdf4uQeDAoOHqjh0wN3Qx779VXQpbv9n8XhcYuM6A5vWGaiqcqBpwMDBGmbM0jFkmMYNDYmoXbLznZnIJSml523JhOZ+Wmu2kfE4Eos/hLFuNWS9xViUrqXQy+fAP3sehItLrtIy4VRXXzy2uLjZn4kSLkDBt36A2J+fa7S7ckvs40cR+c2vUPidH3pbG1BRACEAD1PKhIdpykT57qbgF3DIOtpox9L6BAS+GvoSChRvU4bdOmGfworkahy0DsGEhWLRBdP0yZikj8/4Gmn7rAOe6vda+3EDGgeAZ+yzTYZ/9SXgfY3FOulhBHQHkFJiu7kLS40V2G8dvHx7T6U7ZvtnolyfhsPWkWbDv/peS7yFQdoADNYGprDj9PE6RT7USafUU3Yq66Zi4GAVRw65C68mT2t984pJU3SsWu5uyZ1wGBgwMPu/ZqqqQEsrNcyc48ehA+4uTM+c0/6/b4cPWnj2t1FEIw0/B2/bbGLbZhNjxvlw99dC8OkMAYmobbL/nZmoGdK2EX/xD57CP/h0qH28rxnX6LGlhH3oIIxtmyAjEQhdhzZiFHxjxkNoqfm1ciJ1iDzxSzhnTze+78J5JN5+DdaBvQjf91CzgZ59vhLJ5YsvTptO/m10QyAAfdJU+OcsgFpa1ugYpagIBd/4DuxTJ2FsWg/r0AHYx4+23u/Z00iuXIbAwqZHzzRFKAqUbt3hnDvr7gBVhdqzt+vzE+W7oAjgewXfxF/ir2CzuQ3yc5NKy5RS3Bm8BaN9ozr8sW1p46/x17DKWNvg9vO4gIPxw3g78T4eDt+HgdqADn9stwzpflH8luo/SS5rMfxrqy7wNmq6PaSU+Gv8NawwGi/zcMY5h5fir2GzsdVTaLs0uSJvAsCxvtF4LfGW6/rxvvavg0vUkeYu8OPIodbDK58PmD679d/zq671uw4AZ87V82Kk2pjxPkyY5MOWTS2/31851odJU9t3QfrMaRtPPxG5/PG8KTu2mXjhuRjufTCUFz9fIko/BoCUsxJvvw5zyyZPx+gTJ7d7t1r73FnE/vR72CdPNLjd2LgOorAQodu/DN+VHb+2Vuz53zcZ/tVn7dmN+NtvIHTLHY3vO7gfkd//Bkh87pNFIgFj1XIYm9aj4P5HoA0Z2uS51d59EOx9K+p+/m+ue06uXQX/gms8TU+WXlaZlhJQ+AGIqL6QEsT94Xtwi3MDNhlbUO3Uwid8GKYNwUhtGBSRmk1v/hJ/FauNdc3eXyvr8Fjkt/hR4bfRS83MMgxFireAral6QxrYaGzpqJYaqHaqU3LepnycXNpk+FffQfuwp3NuNXfAkAZ00fpoomzXTS3DaG0UdlmftlobFqG8WwORct+Y8TquusbGJx82PxpZ1YB77g+jq4spwyeOu7/gXnEum1c0dU9RBL50bwiFRQmsWp5stBGKogDTZuq4+fYglHZ+Hn3vrXiL4d8lO7aZOLjfwtDhnAFDRN5x60vKSU5tLZKrl3s6RhQUehqN1hS7sgKRx3/eKPy7RNbVIfrcb2Fs69gvh9axo7AO7HNVa6xdBafe9GDg4si/JsO/+hIJRH7/JOwL55stkYk47JPHXfUBALK6Cs751tcPvFzvOJDnK13Xw3FgHTnivj5LSMOAE49Behm9SuRRiVKMhYH5uCN0M24OLsIVvhEpC/+OWydaDP8uSSCBN+LvpKQHN8Zoo+GD+y9Nk/UJjW674FSnZPQfAMSQnnXkDGnio+SSDj+vAweRNE9jTqUvhW5HsejSYo0CBV8L3Q1d8Ms4ZZ/rbwriy/eG0KNn4/f+YSM0fPO7BRg91t2/3TUr3C9rsH2riUhdfnzGUVWBm24P4qc/K8KimwOYOMX3/2fvvMOrqtL9/127npoeaui9BwKBhNBBQSkqVhRQ7Do6o+PcuXfq/U27c2e8M86MZexdQRFBAQVFOqH33nuAQOqp++y91++PmJiQU/Y+OSd1fZ6H5yFnv3ut9+zT1v6ut2DIMBGTp1rwy98lYOZdNghC3cS/kmIdB/ephu3zN5iLZmcwGIxKWAQgo0mibN+CWttwYSBWKxyP/ghcckqd5vUuWgDqjnBzQyk8n34EsVcfEIulTvNVomzbHNmoEjWAwK4dkEeOrnrIv35NePGvEp8Pyvo1sM6YGfQwVczf9Jo6RzcR/fc97ndeheORH0Ho1MX0ufUJVRQo2zbDv3kD9IKK+mzEaoM4NBvyyDGskQmjSWOk8UglB9TDKNKLkMLV7fs4GmycFSMMNkpJIE4MFgfVejyeMcdmG09Ey57APniouYZLRjEjsDZ2krkkPOt8Eu+55wdtHpPGpeIe6+3oJfZoAO8YDGNkZUsYMkzE2TMarhXq4DigfQce6a3Mtek1Wk8QADQVOH9OQ+++zSfWxJnAIW+MjKJrFcJmcgoHWY7NL8KZ06qZ8tc4fdK4WMhgMBjVYQIgo0miXQpd4D4YQt8B4NvWrfafduUS1KOHjRn7vFB2bYeck1enOSvRi0xExV1nT1W1QjA1iH/bZlhunhG0liGx2QBBAFTjCw8znYCpFsVusd8P12svwfnUT8G3aWv+/HpALyuF6/WXqoS/SqjXA2X9Gij5G2G/74G4pI4zGPVB9QYSkaCgOKGeRopU/wIgANxinYqz2nmc0UJHM0uQ8JB9btCorhQuGRZY4EPsxTourvLiD1zSDNZZNUkbrhUcxBGXsRuKFC4FP3E+gfPaRexU9qCclsNCZPQWeqKPEL+oWgYjlhBC0KmzgE6dox9DVc2l9aqB5pEGDABXCzWs/c6PnVsV+L8PhBRFYPBQCWMmyGjdxpyYej2aST3PxDKcwWAwasBWLYymiZltMsBQZ9xIBA4eMGd/YG+d56yCM+l/NXu9tATwmUgr83mhl5UGPUQEAeLA2ilxoRB69ALnNC4A6tGmxPp98C5bEt25cYaqKtxvvlJL/KuBGoD7/begnjldb34xGLEkQM1FB5u1jyUykfG04zGMknKCRqt157viGceTIZtZiETEcGloXHyzkrrVqDUKiZPQmCfnNtvC9Bl8O0y3TsG9tjsx0zoD/cQ+TPxjtCiSDNQJrIt9Y+XEcRUv/G858tf/IP4BQCAAbM1X8ML/luPQgbr9piUlm7y2Ju0ZDAajEvbtwWiS8K3NFZDnWtW94Dz1mkuXokZSbg0idDDXNZPvWLcum+FuDuW8sYDBGzx51DhT83J1uHFUDx8IW7+woQjs3RWyZmQNNBW+b76Kv0MMRhxI4sLXSTNjr1AFRwLHsFvZh+PqCWjUfGmASMhExl22mfhjwq9xn+0uTLfchNutt+CXzufwE+cT6CCEjxgfL4+Oi1jXSegQ8zGD0c5kExY7sUe06chnIFcaHq1LDAajkZM5xHh6f3IKQfuMum++NzTFRTreftUVtopOIAC894Ybly9F/1vVuSuP1DTjt+VDhzf9RksMBqNhYCnAjCaJNGwEfCuXAwYjxqirDJTSOkUmEHvkG6Aa9tbY3RxKw3Pg+/YrQ8+XJCRC7Dug6m8uMQnEagX1GosCJFYbSGLom3OhYydYp98G75LPwo4jj78BYt/+huasQqxD7ShKoZ0+CT4lFdTvh7JrOwIH9oF6PSA2G8T+gyBlZoFI9bto8m/eaNhWPXIQenFRnWtVMhj1zTBpCE57zxqyTSBO9BJq10zz6F587f8G+co2eKm3hn2enINJ8jiIMW60YONsGCENM31eKp+Cx+0P4t/uN+Ghwb9bncSJVC4ZpzVj18UCOeh1iQcDxP5wEDtc1B3ZGMDDtjlY4luOU9qZoMe7811DpkwzGIzmgWSi3p0goFlEA29Y6zeURBMIAOu+8+OOWbao5uE4gtHjZHz+aeTJbHaCodnsu5bBYEQHiwBkNEm4xCRIw0catvevWQXfl4vqNKfYd4DhyDcAEAdk1mm+6nCJSZBHjzdka71peo2UZyIIkIaNMDyXlD0iYsq0PGocbLPngWvVuravyamw3jELlinTDM9ZhdkiKNdBAwEo+/eg7A+/gnfhx1AP7Yd2+iTUg/vh/eRDlP3h1wgcMpfKXVe0iwai/yqhFNrFC/FzhsGIE9lSFuzE2I3PaHkkeFLzO6Zcd+HvrhfxnX9dDfEPAMpoOZb7VuIl1+tQaOPpfNhV6IxfOJ/DDfJ4OKpFyCWSBEyRJ+EXzmdxr+1Ow+ONlUfV2w2zSARMtkw0ZDtEzER3sRuecTyJJ+wPI1McgNZcK7ThWmGwOBBP2R/Fjx2Pw8GZ2yRjMBhNiz07jae5Fl6hKLwc++jt+kTTKLblG//N2blNgd8ffd3D3NESsnPCb1LLMvDAI3ZYbewWnsFgRAeLAGQ0WawzZkIvK4VqsNaef91qiIOGRN0tlk9Lh9C7L1QDAhKx2SFlZkU1TygsN00H9fug5G8IMSmBZdptkIbWTsGS88ZB2bY5YhQgsdoqUnwNIA0aAnHgYGgnT0AruABQCq5Vawg9eoFw0S1MCF+3ryS9pBj+hR+HrBFJPW64334V9gcfh9irT53mMu6UybqGJutbMhiNASux4mH7XLzsehMKQt8wDRT7Y5JcuzTAu56PUKCHb0xxXDuJT72LTYlq8SaJS8R0602YapkMN/WAgMBGrFW14agOCBCgIvLmRgbfLt7u1mCMlIcSvRTf+teEtOkt9MR9319vjnDoK/ZCX7FXPXnIYDAaE1dMprheuaIjvXXTTQN2uyk8HuNrskAAKCnWo24IQgjBHbOsaJ/BY91qP65d1asdA/oOEDB5qhVt2zXda8pgMBoeJgAymixEEGC7936U/e4XCFucoxruD96G2KsPhN59Ifbpb7o5iG3m3Sj/5/OgIZpkAAA4DrZ75sQ81ZRwHGwz74Y0eCj8m9YjcPgA4PeD2OwQBw2GnDs6ZBdcLiUF9nmPwf3Wv0OKgMRqg/3Bx0ylnxJCIHTrDqFb96ieU63xeL5ilROFCEacCfBv3hD5XF2HZ+HHSPiv/45aqDQDn94a2oXQ3Uavh0tvFUdvGIz40V3ohmcdT2KxbxkOq0drHHMQO8bIebhBHl8r+u+ceqGWfSi2KNsx1TIZiZzx5kL1AUc4OIN0v92obDYk/gHAKv9aZEr11wmcEIJbrFPRW+iJNf4NOKAeAkXF92dHPgOjpZEYJg2p9XoxGIyWidkA5aaeAByN/3V9zoQQjBwjI2eUhNMnNRQX6RAEoFMXgTX+YDAYMYEJgIwmjX7xvGHxDwBocRGUzRuhbN4IkpQM252zIPY0HgnGJSXD8aNn4Zn/PrSTx2sfT0mF9fZ7IPbsbXhMswhdu0PoWiG4malrKHTpBuez/wX/hjVQtm6uampCbDZIw0ZAzhtbp9pz6rkzUI8eBlX84BwJEAdmgktMMjUGpTTqCDihWw8Edu8wNk9xEdRDByD2GxDZuI5I2Tnwfm5MAOQ7dzXd4KapQDUNgQN7Edi3G9TtBrFYIfTpBylzCIjIilk3FzKE9viR4xFc0QpxQj0FFSqSuET0FnpBJMGXHFuU7YbH16Fjm7ITEy1jY+RxfDHz3E5pZ3BZu4LWfP1uAvQWe6K32BN+6oebemCBDBsXXR0rBoPRfGnbnsfpk8ajANu0a9qCld1B4EwgKC8zti61WIDkGHU+5jiCrt3ZbTqDwYg97JuF0aQx2tgi6LklxXC/8Qrs8x6D2Luv4fP4lFQ4n/gJ1AvnEdizE9RVDsgyxB69IfTuayqqTC8tgX/zRgR2bYdeWgoiihC694SUOwpCtx4Rxb3K49Tvh7J7B7SzpwFNA5eaBilrOLiUmoIel5wC67TbYLlpBmh5WcUYzgTTkZDVUc+dgXfRJ9DO1SwO7/1yEcSBmbDeeic4e+3ImGDQgPH6MtUR+w8CTEZcBo4cqh8BMCsbvtXfgJYUR7S1jL8h7v40BOqpE3B/+E6taxDYuwu+Lz+H9c5ZkPoPaiDvGPGgFZ+OVny6IdtrepGpsc3aNxSU0qieW30LgJXIRIZM5AaZm8FgNH6G58o4fdJjyLZXHwEpqU07epjjCIbnSvj2a78h+6xsCaLU1OMeGQxGc4cJgIwmjdnOvLXQdXjmv4+EX/4OxGQHWqF9BoT2GVFPrezbA89H71QUDfkeGlAQ2LsLgb27IA7Ogu2u2SBC6I8ppRT+9WvgW7msViSkb+VyiIOHwjbzbhC55k0d4XmQpOSofa9EPXUCrtdeAgJBan7pOgK7d0K7eAGOJ58xJgJGsW4S+g2AbfY8eD5+19R5VDG2oKsrxGKB46En4Hr1X1WiazCsM2aa75rcBFDPnIbrtRdrvM+rQz1ueN59A2TuwxD711/6I6PxIJhMMTVr35Dw4A2nAFfaM4xBKcVR9Ti2BXaiWC+BCBHdhS4YIWWzhiQMRhzIzBKxZhWHywXhaxtzHDBxsqWevIovI0fL2LxRgas8fBSgxQqMHs82UBgMRuOnacdmM1o8fEZHEGfdakFRVzkCe3fFyCNjqCeOwfP+myFFEQAI7NoBz8KPw47j/+Yr+L74LHgaNKUI7NwG1+svgQYT6OoIVQNwv/9mcPGvGvqVy/AuXmhoTCKYE2EBQL7hZujFRdAKr5g6j3M4Tc8VLXybtnD+5D8gjxpXsUqshBAIvfvB/tjTFceaGZRSeBZ+FPZ9/r0hPJ9+FHUEKKNp04nvaMq+M98pTp7EFkIIOpt4bgIEZPDt4+hR8+Gqdg3/63oB/3K/is3KNhxRj2G/ehCLfcvwq7Lf4xvf6oqSEgwGI2aIIsHDTziQ3jr07SMvAPfeb0OXbs0jxsSZwOHhJ+xwOEPvUFutBA8+5kBqGtvAYTAYjZ/m8e3MaLFQjzsmkVyBA/sgZWXHwCNjeJcuNtQdNrB9C7TR48C3qx1pqJ4/B9/K5RHH0E6fhH/NKlgmTYnG1dC+7d0NWhY6oq2G7Z6d0KfdCi4hMaY+AICybTMCG9earh0oZg6JuS/h4BKTYJ0xE5abpkG7cgXQVHBJKeASGlczg1iinToBveCiIVvqdiGwd1e9fg4ZjYMR0jAs9X1tKFLOSZwYJDadSNk8OQfHPScN2Q4S+8POau9FpFgvwQuul1FCgzfjUqFiiW8ZVKiYYplUz94xGM2bpGQOP/6ZE1s2+pG/QcHVwoq1rCwTDBkmIm+sHHUX3MZK+w4CfvpfTmxa78eWjQrKvq8JaHcQZOdIGDlaZg06GAxGk4EJgIwmjbJpPeCvuwBY2RCjPlDPn6tVLy8c/vwNsM28u9bjyqZ1psaQx99Qp1p/teY32HADQEU68L49kEeODm+mmI9UDGxYY/ocvnNXCBnmoo6ihaoB6GVlIBwHkpAIIkp1Sh1vSgQOHzBtzwTAloeDs+NGywQs862IaDvDchOEEM1EGiNOYjwVVQZLHzPCF97lIcW/6iz3rcRQcTDS+bR68IrBaDlYLARjJlgwerwMSUwEpRysNqC8vKShXYsbzgQON95sxaQpFnjcFf3S7XYCjmM1/xgMRtOi6ayiGYzroLoO/+aNMRmLWOsv6kI7c8qUvRrCPrB/j+ExaFkptHNnIHTuamrusGO6XKbsdVd5ZJsoBECzEGcCbPfMifs8WuFl+NetgbJza5VITRxOSMNzII8c26wj/yqhJjp0R2PPaD5MlifCT/341r8m6HECgtss0zBCHla/jtWRjcoWw7Z71H24g94CkZgvhdBSKNfLsTNg7LePgmK9sgm3WadHPV+xXoJDgSPwUC/sxIZ+Yh8kcPVXPoLBaMwQQuBw8uB5HppmvDtwU4bjSNh0YAaDwWjsMAGQ0WShbhdoWeQoACPUZ/MBanaRpAa3N9sBuS4dk4NxfWORWNvHA6F3X1hvuwt8Smpc5wkcOgD3e2/Uqn1HXeXwr1oJZWs+HA8/GTS1uzlBDHZ/jtae0XwghOAW61RkiZlYp2zC/sAh+KgXdmJHpjgAeXIu2jRQd9y6cDBw2LCtm3pwVjuPbkKXOHrUtDmiHocG47+hBwNHcJs1st31FOslWOT9AnsC+6Hjh3IdvJdHB749OvEdYSUWdOAz0F/sA74JNaZhMBgMBoPRcmECIKPpYqCGniE4HsrObaCKH9LgYXEXqriUFJP2wcUqYrGaSl0m1ijugsIg9OwD9dgRw/Zizz4Rbbg4Xnuh/yA47n84buNXohVcDCr+VYeWl8P1+stwPvcLY92RmyjSwEz4v/nKhP3gOHrDaAp0EDJwr3BnQ7sREyil8MFciQofZVGw4fDR+F/Pa1oR/u56KWiasQYNp7WzOK2drXoskSRgqmUycmRWvoDBYDAYDEbjhlUsZTRZiMNZs6NqtOga1MMH4V04H6W//xWUfbvrPmYYxN59TUU6ScOGB31c6DfA8BjEmQC+Q2w7Z0rZIwCDXXv5Lt3At4vc3ZLj4veVRMT62e/wrf4mctdbALS8DEqMUtgbK3zb9hC69TBky6WmQejdN84eMRo7RXoxvvR+hb+Xv4T/LX8Br7rexk5lDzTa9NLLCCGwwdxvlIM03w2BWGCmpiIAODhz15NSirc9HxqqMVhJKS3Dh95P8K1vtam5GPVDWamOy5c0lJfFaNOYUYWmURReCaDgogKvl11fBoPBaAqwCEBGk4XwPKRhw6GsXxO7QX1eeN57E2Tuw3FLCyaCCHnUWPi+XhrRlktLh9h/UNBjcu5oBLYbqy8ljRgZ0wYgAMDZHbBOvw3eRQvCG8oybLcai+ghQvy+krgkc5GX0aB7PQjs2WXY3r95Y0VzFtJ868lY77wXrhf/BloepmO0LMM2ex5IHAVgRv2iUAXblV3YqGzGBa0AAEVrrjVy5eEYLmXBQiw17CmlWOZbgRX+Vagor17BOZzHPvUAUrlkPGx/ABl8u3p+JnXDyTng0Y2VXyAgyOCa1vOrb3qLPWGBBT4Yi+wbLJr7HT+jncVpzXiTruos9i1DL6EnOgiRN7sY8UXXKXZsVbBxnYLzZ3/YPOjUhcfI0TIys8SYNW8ovKxh80YFZ06rUFUgJZXD0GwJvfsJzbZBhNulY+liL3ZuC0DTfhDLMzpwuPUuKzp1btg6pn4/xc5tCk4cVaEoFAmJHAYPk9C1G9+s11sMBoNhBCYAMpo0ct5YKFs2AZGaR/A8hEFDoB7YG7lrMKXwLPwYzh49oR0/CvXkCdBAAFxSMqTBWeCS6y4kyeNvgHa5AIFdoTvpEmcC7PMeDSncCR07QR5/A/zfrQw7F9+hEyzjJtXJ31DIuaMAQuD94rOgUW8kKRn2OQ8Ziv4DoqiPaAJpaPBIyliiXy0ENNWwPS0uqnjvNoL6iPGCT02D46mfwvvpR0FTxvmMjrDeMavFdEZuCVzVruEV9xu4rBfWePyCfhGfej/HKt8aPOF4CG341lXHvvR9jZX+VSHHvKYX45+uV/BTx9NozafHzfdYU6SXGLaloLioF6ADxz4LoZCJjBx5GFb710e0FSEiVzKXlrtNMb6BE4y1ygbcJ9xVpzEYdUMNULz/lhsH9tX+LT5zSsOZUx4c2i/i7jk28Hz0YpCmUXzxmRcb19Vcf54/q2HvrgBat+XwwCN2pKU3r/qQlwpU/P3PLgRbrp0/p+Nfz7sxcbKEyVPrr7ledbbm+/HFZ15c31Ns80YF7TN4zH7Q1uxeEwaDwTADEwAZTRo+NQ32uQ/D/c7rQCCECMgLsM1+AEQQoe7cZmhc6ipH+R9+Xatxhu+rLyAOGgzrzLvB1aFzMOE42O6ZC6VTF/jXr4F+7eoPBwUR0pChsNxwE7ik5LDjWKZMA7FY4fv2q6AiqDhwMGx3zgKRpKh9jYSckwdx0GAo2zZDPXoEVPGDczghZmZB7D8w5pGH0SD07ge+dZv4T0Qjm7RE+JRUOB59CtqlAgT27wF1uwGLBWKffhA6dm5o9xgxxEu9eNH9Gq7q10LaFNFivOh6DT93/gROzonLWmFY8a8SD/VisXcpHnU8EEuX4walFAFELgdQnRPqKXQQmAAYjqmWyTipnsYZ7VxIGwKC2ba74DTZsbeMholUNsBOZQ/utd7JoowakMULvUHFv+rs2hFAQpIP026NvozMogVebNkUevP5coGOV/7hwtPPOZGY1Dyi2/1+PaT4V51vv1aQmsZj2Ij63dzM3+DHZ/NDR1xfOK/hpb+78NRzTqSkNI/XhMFgMMzCBEBGk0fs1QfOH/8MvtXfILBnJ6B+v/DjeYgDMiGPmwihfYeKKDUTBO2aSykCu3dCPX4MjseeAt8m+nQtwnGQ88ZCyh0N7exp6OVlIKIEvmMncDZjdY4IIbCMnwQ5Jw/Kzq1Qz54BdB1cahqkocPBp9VPpAxns8MyZgIwZkIdBzK/IONS02oKqNcfb9MWtntm18Ur476kpQO8YDgKkCQlA3EUZxsbfJu24Nu0bWg3GHFkgz8/rPhXSQktxWr/eky33oQNSr7h8ferB1GkFyGFi39Kf0PgZU1AIiITGU85HsUnns+xPbCrRpdeAEjjUnG7dQb6i+ZrioqoW+qiAgUBqJDqOA4jOkqK9bCiXHU2rvVj/CQZdof5dcfpk6qheUpLKFYu9+GOWQ0TDRdrPpvvjSj+VfL5J956FQDLy3QsXhi53EJ5WUXk5v0Pm6snymAwGM0FJgAymgV8m7aw3zMH+i23V6RhUoBLS6shpNFIqb8moK5ylP/tz7Df/wjEvv3rNBbhOAidu9ZtDKsV8sgxkEfWaZiGx0T6bCWWGTOhnTgGZWt+TdHWYoE0bERFJGUdojXNwNlsEAcNRsBgpKk8YiSLFGHEjSK9GKV6GSQiojXXCgKJ708+pdSUmLdJ2YKbLTfiSOCY8TlAcVQ9gRFS4xcAo/lsUxZGbAgLsWCO/R7M0G/GTmU3imkpRAjoLnRFL6EHOBJddE9PoTu2BkKX5ogEBw4CGj7qvaWybbMCavAjpKrAzm0BjBpnXqTatN74enLnNgVTb7HAamv6EWd7dhmPaFaUCqG0c9f6udXcskkxvIQ8sDeAkmIdSclN/zVhMBgMszABkNGs4Kw2cCG63RJHjLsr6jrc774Ox5PPQugY2w67LRZeAAiB4RU8AC45FdK0AbDcOBXqiWOgXg+I1Qaha3eQBqitZxk7EYG9uwE1/EKZOJ2QRjR1xZbR2KCUYk9gP1b71+GEdqrqcSdxIlfKxgR5DGxcfARxF3Xjml5s0r4ICoxF7FTip+bsGwpdZ10x400il4BxltExG2+IlIlFvi/hoZ6ozu8t9IxafGxueDw6Tp/QoCgUDidBl25CnWruGeHyJXN1hC8VRFd3+Nhh45uVgQBw+pSGPv2a/vvC7B7t5o3+ehMADx0wLk5SChw5FMDw3OZbf5nBYDBC0fR/jRgMg4gDh8R+UE2Db+Xy2I/bkjEh/gEA/X5FSiQJYp9+kIYMg9inX4OIfwDAt2sP+5x5gBA6BYw4nLA/9AQ4h7n6VAxGOCil+Nz3Jd7wvFtD/AOAclqOFf5VeN71LxSbaExhBg3mb6Y1aEgg5j4HZu0bimgiAC2wYLuyC1/5vsEK3yocDByBTpmQWF9IRMQd1luiPn+0nBs7Z5oopSU6Fnzgwe9+WYa3XnXjg7c9+Pc/3fjTb8vw3UofNC1+Ua5mP3HRBuArirnnoPhbZmSvz2f8easBil3bFXw234P577vx1ZdeXDEh6Hq95q6xWXsGg1G/jB07FoSQesmUuv/++6vmOn36dJ3GOn36dNVY999/f0z8izUsApDRYhDaZ4Dv2h3ayeMxHVc9chB6URG4lJopabrbBe30SVBFAXE4KyLSrmuIQXW9YktVEFkqKAAapJNwJLSTJyBmdIyDN9Ej9h0A57M/h3/daig7tlU1qCE2O6ThuZDzxoBLTGpYJxnNjg1KPr7zrwtrc0UvxKvut/Efjh/HPFLJQeyQIBmO6OPBI4lLxBApEye9pw2dY4UFfcVedfCy/iCEQIYEv4kIxyX+ZbWE1DQuFdMsU5AlZcbYQ0YwhklDoFIVC7yLoMJ4yFOWmIl+Qp84etb4uVqo4ZV/uFBaUltcKS2hWP6FD6dOqLj/EbuhaEBNo9i/J4Ct+QquXdVBOKBDRx45eTI6d+VrrZvatOOBHcbXEW3aRpeu7Uzg4C80Lsw7E1pmvEW79sau785tCr5Y5IWrvOb7ZtUKP3r3FXD3bBsczvDX0G43t4Y2a89gMBjNBSYAMloUtrtnw/Xi30DLSmM3KKVQL56D9L0AqJcUw/v1UgR27/ihIQkAkpAIeeRoSGMmQDt6GP5N66EePQToOiDLkAYOhjRyDISMDrHzrYlBo0iZ00tLYu9IDOBbtYHt9ntgnTETemkpQAi4pORG0RWZ0fzQqY6Vvu8M2Z7XLuCgejiqJgnhEIiAYdIQbFQ2G7LPFAfASqwYLmVhmW8FvDRyAfcceThk0nTStjL49rWiMcMRLIryqn4Nb3s+gIu6MEbOi6V7jBDkyNnoL/ZBvrIN+wMH4aJulOvl8KJ2kxYCglxpOO603tqiN/J0neLtV91Bxb/qHDqg4uulPtw8I3wH3quFGt76txtXLtdcFxRe1rFzWwB9+gu47wE7ZPmHaz50uIQVy3wwspQQRWBIdnTNWjKzRHz7tbE6gEnJBJ27No/f/cREoNTE8nncpMjf1Vs2+fHpR6G/+w8fVPHyCy786FkHbPbQIuCATBGnThiLGOQFoE8/1qiHwWC0TJgAyGhR8CmpcP7op3B/+iG0Y0diN/D3q02t8Apcr7wAWlZWy4SWlcL31Zfwb1xb+7jfD2XbZijbNsMy9RZYxk6MnW9NCCKY/0ri6qnTcbQQUaq3bsyMlsth9RiKaYlh+03K1pgLgAAwTh6FLco2qBHSgTlwGC+PAQBYiRXzbLPxqvutsBFX3fgumGqZHFN/402xZrwmYiQWepegu9AN7XnWSbs+cHJO3GAZjxss4wFUpNif0c4hX9mKQv0qOHDowLdHrjQc6XxaA3vb8Bw+oOLyJWObePnr/Zg42VJDvKtOeZmOf//ThZLi0GLiof0q3n3djYeesIPjKsZJTOKQO0rChrWRo25Hj5Nhi7Ixx4iRMtZ866++xxuSkWPkKv+aOu078ijdZ0xk4zhAEMI/79ISHYs+ibzxc+WyjuVf+HD7PaHr1w77Xvz1G2iknjlEjBhRyGAwGpY1a9Y0tAvNFvbtx2hxcCkpcD76FPgYNu7g09JBdR3ut18NKv5VJ9Jx39LFULYZi6BpbnCCULFqNIHYq2WnXDEYAHBFv2LOXiuMix9t+NaYa5sFPkwnVAKCWdY70En4Idq5j9gTTzseQye+dgQ0Bw42YkORXoy/u17CN77vUK674uJ/LKGUogglsRsPFOv8G2M2HsMchBDw4JDBt8MgsT/GyaMw1TKZiX/fs32r8VR3nw/Yvyd0qu6qlb6w4l8lRw+r2HfdONNus2LQkPDRXcNGSLhxqsWYs0FISuZw92xbxBqC/QYIGB1Fl+HGyvGjxmvy6Tpw9nR4ezOde3dsVeD1hBaYrTZjr0l6Kw7TbwsffcpgMBjNGRYByGixyGMnwvPem3Ueh2/fAVzb9lAP7oN+5XIMPAO8Xy+FOGRYC00XNbdTziUkxMkPBqPpQEzu55HvP2cBquKSdhkBBJDEJSCFS4lwZmQGS4OQxCXha9+3OKgeBsUPN/K9hZ64QR6PnmL3Wud1FTrjZ84f44x6DscCJ3BYO4Ij6nHo0OGhHnjgQbFWgnPaeXzl+wb32e7GEGlQnf1tSuxQduNu68wWnWraEBwJHMMXvuU4o52r8XgiScAEeSzGyaNa/GtSXGSuhEcoe0Wh2L7FuJiYv17BoMFS1d88T3Dv/TYMyAxg0zo/Th7/QYTq0UvAyNES+g2se93lzCwJVivBl597camg5nOxWIDcUTJunGqJe+fj+kQxlvVcxYF9Cjp1CX2ruX+v8XqNgQBw5LCKzCFSSJsBgyTMe4xg0SdeFF+r/f7q21/AnffaYHew+BcGg9FyYQIgo8UiDsiEmJWNwI6tdRpHHn8DCCFQttdtnOrQ0hKohw5A7D8wZmM2BSilgG6uk6iyexfkodlx8ojBaBp04Nubsm/DtcZi71LkK1vhpp6qx7vxXTBeHo1B0oA6+dNF6ITHHQ+iWC9BgXYZAEUrLh1pfGrEczsJHXBcPYHD6rGQNgoCeNvzAWQioZ/YcqKAffAhABUSWP2qaKCU4qJ+CaV6KSQiIoNvDwsJHwm2U9mDdzwfQkdtQaGUlmGR7wtc0i/jHuvtLVoENLtfyYe4Aym4oMEXOSu0ipPHVVBKa1x7jiPIHCIhc4gEr0eH1wdYrQRWa2xfn159RfTsI+D0SQ1nTqlQVSAllUO/gWLI9ObGjt9PsXuHgrOnNWgaRXIKh6xsCWnp5jeki4KIcNXxuM2Jxl5P5KjQPv1E/NdvBRw5pOL4URWKQpGYyCEzS4zqOTAYTQlN09ChQwcUFBTA4XDg8uXLsNlCp84DgKIoaNeuHa5du4aUlBQUFBRAkiqEdp/PhxUrVmDVqlXYvn07jh07hpKSElgsFrRp0wYjRozAnDlzMGnSpLBz/Pd//zf+3//7fwCA1atXY+zYsVizZg3efPNNbNy4EZcuXYLX6606BlR0AV67di2A7+8Pg1BeXo5ly5Zh9erV2LlzJ06cOIHy8nLY7Xa0a9cOI0eOxMMPP4zsbPP3iYsWLcKbb76JPXv2oLCwEGlpacjNzcXjjz+O8ePHmx4vFLt378bbb7+NNWvW4Ny5c3C73UhNTcXgwYMxc+ZMzJkzB0IUJbLCwQRARouFEALbXffBl5AI//rVMFTM5TqkESMhDRoMANCLi2Lqn3r+bIsTAHWviVX/96jnTpsWAHW3C8qWfCjbt0AvKQIRBPCdukLOHQWhVx8Qk2nIDEZD04XvhLZcGxTolwzZn9ROYZe6p9bjJ7RTOOE5hYnaWMyw3FxnQSOZS0Iyl2TqHJfuxlLf1xHtKCg+9S5GH6FXzDsaN1Y4cBDCpFczgkMpxRZlO1b71+GCXlD1uAwZ2VIWJlsmIpGrHU1+TSvCe56Pg4p/1dmkbEEXvhNy5Ja7GdW5a4UQZtg+RGSYokQWeaqj6xX/QgmQVhsHa/j73zpBCEGXbgK6dGv6t1Qb1/nx1ZfeWgLst1/7MSDT/KZDUnL472WrjRhK9a6yNyjgchxBn34ia/TBaHHwPI97770Xzz//PFwuFxYtWoT77rsv7DnLly/HtWvXAAB33XVXlfgHAH379sWpU7UbmblcLhw/fhzHjx/HBx98gBkzZuCDDz6Aw+Ew5OfTTz+Nf/3rXyaeWW0URUGrVq3g89Uu/FlaWorS0lIcOnQIb7zxBh599FG8+OKLhoQ0VVVx9913Y8GCBTUev3jxIhYuXIiFCxfiiSeewIsvvlinNbLf78cTTzyBt99+u5bAWVBQgIKCAixfvhx/+9vf8MUXX6Br165Rz3U9Tf/XisGoA4TjYL15BuSxE6Bs2wLfssVAiF2GYFgm3PjDHzFW50HNd8Rt6hDR/GKNs5hb2QeOH4Xn3ddBq4mNVFGgHtoP9dB+CL37wj77QRC5+dTtYTR/CCGYZp2M19zvRLSVIaOUhq9F+q1/DVpx6ciVh8fIQ+NsUbYhEKYZSHWu6tdwRD2GPmKvOHtlnnhEg/UUurcYsTNWUEox3/tZ0O7UfvixXtmEfYEDeNrxGFrxNRs2bVDywzamqc5q/3qMkIa12CjAESMlrPnWWI5o23ZcyM64SUnm3t92B2lWabYNxXcrfVj+RfAOGpQCe3cFQIipJTL6Dgi/pus3QETBBWPvGUEEevZmt60MRiTmzp2L559/HgDw/vvvRxQA33vvvar/z5kzp8Yxj8eDpKQkjB8/HoMHD0anTp1gs9lQVlaGvXv3YsGCBSgoKMCSJUswb948fPLJJxH9+8tf/oKvvvoK6enpmDt3LgYOrAh22bVrFxJMlHXSdR0+nw+tW7fGhAkTMGjQILRr1w5WqxXFxcXYvn07PvnkExQXF+PVV19FQkIC/vKXv0Qc9+c//zkWLVqEtm3bYt68eejXrx+8Xi9WrVqF+fPnQ9d1vPzyy7BYLPi///s/w/5WR1VVTJ48uarRSbt27XD33Xdj4MCBsNlsOH/+PBYtWoQNGzbgwIEDGD16NHbt2oX09Ng0lWTfpAwGAM7ugGXsBGiXLiKwfYuhc/jOXcEl/1AvS+jUBdrpk7HzKa1VzMZqKnCiCLMrTHFIlmFb7eJ5uN/8NxAIXV9IPXwQ7vffgn3eoywSkNGkGCj2x93W27HA+1mNunvVacu1RoFurFbpSv93GCENq3fB6bhae7c5vP3JRikAxoPR8siGdqHJsUbZEFT8q04JLcUr7jfxS+dzEMgPS+Ntyk7D81zUC3BRL0B7vl3UvjZl0tJ55I2VsGFN+Pp9HAdMvdUaUihNb80joyOP82eNRRNmDQtdE45hjEsFGr76MnL7XDPiH88DXbqGv80cMVLGdyv90A3sdw8ZKsFmZ2syBiMS/fv3x+DBg7Fr1y6sWrUKBQUFaNu2bVDboqIiLFu2DADQs2dPjBgxosbxt99+GxMnToQYIkDjj3/8I+69914sXrwYn376KTZs2IC8vLyw/n311VfIycnBsmXLkJycXPX47NmzzTxNiKKI5cuX48YbbwQX5H7toYcewh//+EdMmzYN+fn5+Nvf/oYnn3wSnTqFbwK6aNEi5OTkYPny5UhKSqp6fN68eXj44Ydx8803w+Px4O9//ztmzpyJ3NxcU34DwK9//esq8e/hhx/GP//5T1gsNcuRPPPMM/jnP/+JH//4x7hw4QKeeeYZfPDBB6bnCgb7JmUwqiHnjTFuO2psjb+lnPBfeKaQZEgDB8duvCYESYlcI+wHYw5C6+A/asHwfr00rPhXiXr4ANTjR4z7wWA0EvLkEfhP5zPIlYZDwg83xl35zphjuwdJJtJxr+rXcEw9EQcvwxOA8cLw0djXF7qRu1oTDBIHYIDQN6ZjNnc0qmGVb40h20L9KvYG9lf9TSmNGCl7PSV6qSn75sb026zIyQstyAkicO/9NvTqEz4ybMx4YxH4vADkjmYCYF3ZtM5vStwzAscjYoffpGQOM26P3JE3NY3DTdOj79rMYLQ0KiP5NE0LKxp98sknUJSK+6JgAtyUKVNCin8AYLPZ8O6778JutwMA3n333Yi+2e12fPrppzXEv2jgeR5TpkwJKv5VkpqaWhXhGOlaVOJwOLBw4cIa4l8lY8eOxf/8z/8AqFgjVEZamuHKlSt44YUXAAATJ07Ea6+9Vkv8q+Tpp5/GrFmzAADz58/HhQsXTM8XDCYAMhjVEDI6wjL9toh2Uu4oiNcJdHxaOqTrRMGo/ejctcWmoNIgtRxCG+uG7fXiIqiHDhgeWtm04YdpNA2B/XvhXbYE3i8+g3/9Gujl5cb9ZDDqkfZ8O8yy3YHnE/+AvyT8Hn9P/DOedf4I2VIWCvWrpsYyax8LkrhEU/aJxJx9fRHLVNBsMQv32+5tseml0XJEPYYSalyU26xsq/o/IQSiyUQZibRsMYrjCGbebcPTzzmQlS0iIZHAYgXSW3GYNEXGf/02AYPCdHGtJDNLRN7Y8HYcB9x9n401dogBB/bFfhMloACnT0VOnx85Wsad91phtQX/buveU8CTzzjgcLJbVgbDKLNmzaqqd/f++++HtKsUxwghpiPwKklISMCAARWN4zZvDh9tDwC33XYb2rc317iuLnTv3h1t2rQBYMy/++67D+3ahY7kf+SRR5CYWLHuXLp0adAahOFYsGBB1Tk/+9nPItrPnTsXQIWAuWrVKlNzhYKlADMY12EZPR6cMwG+r5dCv1bz5pc4nZDHTYI8alzQGzHrtNsAVYOSv75OPlCfJ7JRM4TqOuB2mToncPgApMzIacDquTOm8lfUMxVpiMqu7fAuXQxaWlLjuHfp55CGDod1xu0gUsu+6WM0TjjCwUZqRldwJvf9zNrHgmHikBpCTDg4cMiSMuPrUJSE6lpnFAECBor9MMUyCW35NjHyqmVxVb9myr7wOvseQjccUA8bOleGbLobd3OlY2cBHTtHf4tBCMGMmVa0as1j9Tc+FBfV/Cx17Mxj8lQLevZmTR5igccd4/C/7/F6jY2bnSMjM0vC7h0KTp3QEAhUdO4dki2ifQa7VWUwzNKqVStMnjwZS5cuxb59+7B7925kZmbWsDl+/Djy8/MBAKNHjw6ZGltcXIwPP/wQX3/9Nfbv349r167B7XYHXeOcP38+om+jRo0y/4TCcPHiRbz//vtYtWoVDh48iOLiYng8we+jjfg3ceLEsMctFgvy8vKwbNkyBAIB7N69u1bqdDjWrVtX9f/Lly9j8eLFYe2rR/0dPHjQ8DzhYN+qDEYQpMFDIQ4aAvX4UWgXzgOUgmvVCmLvfiBhmn0QjoNt5l2Qho2AsmkdAseOAIoCCAJoufFUIr20ZaYRUSVyeu71GL5WmvHuhBX2Kvz5G+D9bH7I8ZQtm6AVXoHj4SejamDCYNQ3GXx7XNELTdnXNz2F7sjg2+G8djGibZaYaTpisL6IJlqvM98Rbfk2yBQHtKjuxvGCM9kxmb/OfpSca1gAzJaGwEJYmmKsIIRgeK6E4bkiThzTcLVQB88DGR15JgrFGKuNIFAaexHQaNdeAJAkguwcGdk5MXeDwWiRzJkzB0uXLgVQEel3vQBYPR32+uYflSxZsgQPPvhgVZfgSJSVRb7XzcjIMDSWEV599VU8++yzIQW/6zHiX48ePUzZXLwYea1andOnT1f9P9R1D0VRUZEp+1CwX1AGIwSE4yD27A2xZ2/T5wodO0Ho+EMotbJzGzwfRa6LUDV3MxCTdI8byrbNUE+eANQAuMQkSFnDwXftFvLGOJpIOs5gzcDqDVuMQJyJ8H4euZuVdvI4/Ku/geWGm0yNz2A0BHnSCOwM7DZk24HPaJCIJkIIHrLNxd9dL4WtwdaBb487bZFLNjQUhBCkIgXXYHzB9pj9QTg4exy9all04jvUyb6f0AcDhH7Yp4YvH5FEEjHZMsm0f4zaFF7RsGm9gp3bFLhdFDwPdOshIHeUhL4DRHAcS4OPNf0GiMjfYH4DNhx2B0GnLuw2k8FoKKZPn47k5GQUFxfj448/xl//+lfw/A+bXJWpwTabDXfccUet8/Pz83H77bdDVStS+QcOHIiJEyeie/fuSE5OhizLVfdzv/rVr3DgwAFDtY+t1sh1P43w6aef4rHHHqv6OycnB2PGjEGXLl2QmJgIuVoprUceeQSFhYXQDASDVNYzNGpTbrIkVElJiSn76ihRBMoEg30zMxj1gNC5m6nutkKXbnH2KH5QSuFf+x18Xy8F1Jp1ZZSt+eAzOsA25yHwQYQ7/3crTc8nGBRo+U5dwKW3hl5orAMq53RCv1xgyNafvwHy+BvCRocyGI2BHkI39BZ64rB6NKwdAcE0y+QGqzmXxqfiOefTWOxdit2BfdDww6LNAhnDpWGYZp3c6COuJlsn4kNv5I0EAOgr9GLiX4zpILRHJ74DzmjnDNnnyTXDjwgheMB+H973fIxdgb1Bz2nFpeMx+zwkcgl19rels2Orgk8+9NQI2Nc04OhhFUcPq+jTT8DsB+2QJCYCxpLcUXLMBcDhuRJEkb1ODEZDIcsy7rzzTrz66qu4dOkSVq5ciSlTpgAANm7ciJMnTwIAbrnlFjidzlrn/+Y3v6kS/1566SU88cQTIef64x//GIdnEJ5f/OIXACqagXz++eeYNm1aSNuHH37Y8Lhut9uUTbBrFw6Hw1H1/7KyMtPnxwKWW8Jg1ANcSgqE3v0M20s5sa2PUJ/4V62Ab+nntcS/SrTz5+B6+QXo19XUU8+erhANTUKLjDUpIIRAHjvBmK3DCe2q8TRJWl4G9fRJw/YMRkNBCMGD9tnozncNacOBw73WO9FXNB/9HEuSuSQ8YL8Pv0/4JebaZuEu62140DYHf0j8Ne6w3dLoxT8AGCYNQTsucv0+ESJus06vB49aHtMtNxmqZTlIHIDOfMdaj0tExIP2OfiZ42mMkIahLdcarbl09BV640HbbPzS+Rxa8enxcL1FcfhgAPPf94St1nHogIqP32uZNZLjSdv2FTUVI9Eug0OCgYoLhAB9+jf9TBYGo6lTPcW0suHH9f8PloYaCASwZs0aAEBWVlZY8Q+omdZaH5w6dQrHjx8HUCFghhP/ysrKTKXOVo5r1CZcw5BgVE+BPnfO2OZkrGECIINRT1hvngHIkRdY0rAREDoGL8Ta2NGuFsK3YllEO1pSDO/yL2o85t+wNqo5dZfxpiFSdg7E3AjiKiGwTL8N1GRINzXZvITBaCisxIqnHI9iju0edOU7Vz1ugQWjpBz8l/NZjJCHNZyD15HAJWCYNASj5FwMlgY2CeGvEoEIeMrxKDK40AtEC2Q86XgYbfjW9ehZy6GX2AP322ZBCJP00k/og7m2e8JGvHYSOuI+2134ZcLP8OuEn+MJx0MYLA0CT1gX2rpCKcXyL3yGkiT27Q7g7JnI3WUZ5phwo4wZM60hl6n9B4rIGyOjzEDZZUqBtav8sXWQwWCYJjc3t6pe3ZIlS1BeXg6/349PPqnITGjbtm3QphdXr16tiv7r3r172Dm2bduGq1eNBWPEikuXLlX9P5J/K1asMJSaXMk333wT9rjf78eGDRsAAJIk1aqtGIkxY8ZU/f+rr74ydW6sYPlqDEY9wbdpC8cjT8L9zmshxSUpOwfWmXfXs2exQ8lfbzjNObB7J/Rpt4JzOEF1HYG9u6OaUzfRXIUQAs5qC29EKbzz3wdM/FgAALE0HVGivqCUgnoqwuSJ1QbCsT2nxgJPeGRLWciWsqBSFSpUyJAbLOW3OePknHjO+TR2BfZivX8TzmjnoEFDKz4dw8WhyJWy4eTqPwWkJTFEykQnviPWK5uwTdmJMloOAQJ6CF2RJ+eiv9CHNVxpQM6d0XDxvPFGXfnrFXTsxG5hYgkhBKPGyRiWI2H3dgWnT2nQNIqUFA5Dh0tIb83j3/80vtF5YG8ApSU6EpPY54rBaEhmz56N3/zmN/B6vfj000+RmJhYVYfu3nvvrVEXsJLqNe4iRcT99re/jam/RjDqn6Io+MMf/mBq7A8//BC/+c1v0LZt26DH33jjjarrN3XqVFhM3v/dfffd+NWvfgW/34+//e1vmDt3LtLS0kyNUVfYryeDUY8Inbog4T//G8qubVC2b4VeWgIiiBC6doOUMwpChrmC5Y2NwCET7ck1Ferxo5AyswDFHzJlOBLUYOcnANAuX4J/1YrIhibFP8iWijqPDACA7iqHsmkD/Fs2gn6f6k3sDkjZOZBHjgaXlNywDjJqIBAhbHQUo+4IRMAwaQiGSUOQlJQEnueh6zqKi4sb2rUWQyqfglusU3GLdSp0qjPBrxFx7qxx8Q8Azp9lEYDxwmIhGJEnY0Re7WNmrjulwIXzGhMAGwCvR8f2LQEcPhiAz0thdxAMHCxh0BCR1WVsgcyePRu//e1vQSnFe++9h8TEH/L4Q3WhTUhIQM+ePXH06FHs2LEDCxcuxO23317DRtM0PPfccw0Sxda7d284HA64XC588cUXyM/PR05OzRq+Xq8Xc+fOxd69wev3hqK8vBx33nknli1bhoSEmrV9161bh5///OcAKjZNnnvuOdO+Z2Rk4Omnn8Zf//pXXLx4ETfeeCM+/fRTdO0aujTPnj178PLLL+PVV181PV8w2IqfwahniCxDHpEHOdjqqolD/T5z9r7v7UXJVJOUGphYy/jz15sf3wDS0GyQat2mWjLaxQtwvfESaFnNyEzqdsG/+hsomzfAPu+xJt3ohsGIFkopyvWKKBobYtMJjwEoNAAP9UCCBBsX+boy8a9xYXbPTTNpz4gNZq+72deVUXe2b1GwaIEH1zcLPbhfxdLFBPc9YEP3nqw+Y0uic+fOGD16NNauXYt169ZVRfxlZmZiwIABIc/7yU9+UlX7784778Rdd92FMWPGIDk5GcePH8eHH36IQ4cOoX///pBlGTt27KiX5wNUpN4+8cQT+Mtf/oJAIIAxY8bg/vvvR3Z2Nux2Ow4ePIh3330X586dw4QJE3DkyBGcP3/e0NgzZ87EZ599hj59+uDBBx9E37594fV6sWrVKsyfP7+qk/AzzzxTS3Q0yp/+9Cfs2bMHK1euxM6dO9G7d29Mnz4do0aNQtu2baHrOq5evYr9+/dj9erVOHr0KHieZwIgg8FofHB2B7TrmnuEg9grOiERnofQszfUI4eimNR4/aWoxo80fVo6LDfcFPNxmyK6qxyu114EdYWun0i9Xrje/Decz/wcfGr9hrwzGA2Fl3qxwZ+PDUo+rpVWRP1ZiIxh4hCMlUehNd+qgT1smpxQT2GNfz32BPZDR4Xa0IHPwGgpF9lSFqvP10RITTMnyKaZtG9MUEpBKcBxxnYv3S4d27YoOHVChRoAkpI5ZGVL6NKNr/eSDWlpHAouGlf10tKb3uuk6xSHDqjYmu/Hlcs6OAK0a89jRJ6Mrt3r/5qbYcdWBfPfD50V4yqneONlNx59yoEu3ZgE0JKYM2cO1q5dC0ppVW2/UNF/lTz22GPYvn073nrrLVBKMX/+fMyfP7+GzYABA7BkyRI88MADcfM9FL///e+xd+9efP311wgEAnj99dfx+uuv17AZM2YMFixYgKysLMPj/vnPf4YkSfj444/x+9//PqjN448/jr/+9a9R+y4IApYuXYr/+q//wj/+8Q8EAgF89tln+Oyzz0KeU715SF1hn34GgxEzxIGZ0C4a22EBAPXUcQgdOoJLSoacOzoqgY4GjKcOm41QjATXth0cDz8Jzu6IbNzM0QouwP3+W2HFvyp8XvjXfgfbbXfG3zEGo4G5ql3Di+7XcFW/VuNxH/VjvZKPfGUbHrDdh0FS/wbysGnyte9bLPV9Xevxc9p5fOj9BNsCO/CofR5kwqKzGzu9+ghISCQoKzWWBZCdI8XZo9ji91Ps2Kpg80YFBRcqokfSW3HIzpWQnSPBZqstlFFKsWaVHyuW+qBel3m7ZZOCjI4cRo6x4MCeAM6dVaFrQGo6h2EjJGRmSZDl2AtV3XoIKLioRDYE4HAStGnbtAT40hIdb/3bjQvX1aO8fEnHrh0B9OwtYPaDdlitjU8E9PspPv8kckkcVQUWzvfguV84G7WYyYgtd9xxB5566il4vi+bJAgCZs2aFfYcQgjefPNN3HzzzXjttdewfft2lJWVITU1Fb169cIdd9yBBx980HQNvFghSRKWLVuGd955B++++y727NkDr9eL9PR0DBgwAPfccw/uu+8+cCbrjwuCgI8++ggzZ87EW2+9hd27d+Pq1atITU1FTk4OnnjiCUyYMKHO/ouiiOeffx5PPfUU3nrrLaxevRrHjh1DUVEROI5DamoqevbsieHDh+PGG2/E6NGj6zxnJYTSaHLuGI2N+u6+w2h66MVF0IuKAJ4D36ZdXJpW6GVlKPvTb83V87NYYL//EQjdesD9/ltQ9+4yNad1xu2QR401ZFv2t/+BfvGCqfHDYX/8xxC79YjZeE0V9cQxuN54GTAhxkK2IPG3fwKRmtaNHINhBj/148/lf0ehHv43WgCPZxxPopPQsZ48a9rk+7fiQ+8nEe0GCP3wqKP+IxMY5lm32ocvPou8Sde6DYdn/8sJnm8a4sW1qxpef8mNq4XBI+cSEggeesKBdhk1xbJvvvJhxbLoNi2TkgkefMyBtu1jK8C987oL+/cYqwPIC8D/+3MiLJam8Tp5PTr++X8uFF4OH+HYpRuPx552NLr3X/4GPz6b7zVs//hPHOjWncUBGaW+mzQwGPGk6cVmMxgMUwSOHITr1X+h7I+/geuVF+B68W8o/d0v4Fn4MbSia5EHMAGXkADbXfdW1PMzis8H99uvQi+8DNvds81PmpAY2eZ7pIGDzY8fBj4tPabjNUV0twvud14zJ/4BgN8HPcbvPwajsbFN2RlR/AMAFRpW+FbVg0dNH53qWO5bach2n3oAZ9RzcfaIEQtGjZUxYmT4DaHkFIJ5j9kbnfgSCq+X4rUXQ4t/AFBWRvHaSy6UlvxgU3hZw8rl0WcslBRTvPqiC8VFsS3Cd+Sg8SYgmgqcPdV0mrWsW+2PKP4BwKkTGnZuMxYFWZ8cPWzuWh89FF3jPQaD0fRhAiCD0QBQSqFeOI/AwX0IHDsC6jW+a2cG35pv4X79ZajHjtQ8oChQNm+E64W/QD0f25sjafBQ2O9/BFxKqvGT/H74vvsGJEgr+kjwDqdx34bnAmJsih8LvfqCS0yKyVhNGWVLfvTvXxaAzmjmbFQ2G7bdpx5EiV4aR2+aB4fUIyimJYbtzbwGjIaDEIKZd1txzxxbrWg4ixUYNU7G0z9zIjWt6aSVbt7ox7WrkUUlVznF2u/8VX9v2qDU+efRVU6xakVsy56Y3ecrKjbX3TkarlzWsGGNH6tW+LBlkx+ucvOip6ZRbNloXNTbtL7xCYCK39wbxqw9g8FoPrDYXwajDlBKoZ0+Cf/mjdAvXQQowLVuA2l4LoRuPWrV16CUQtm2Gf6130G/XPDDAVGENGQYLJOmgEtKjolvgYP74Fu6OLz/Hjfcb74C53/8CpzVFpN5AUDsNwBCn34o++NvQb8veB+JwO4doDNmmp5LDxhfiHHOBNjungPPB2/VTXwiBPK4idGf34xQtkd5cy2I4JJTYusMg9GIoJTiglYQ2bDSHhSXtMtI4oxHNdcHOtVxRD2GrcoOFOnFEIiArnxn5MrDkcwl1bs/Zq4pAFzULsXJE0asIYQgK1vCkGEirlzWUVaqQxQJ2mXwkKSmEfVXCaUUmzcYX59sy1cwZZoFokhw+GBsorN2blMw9RYrLA1Us+7YIRUjcuMz9uVLGhZ/6sWxIzUj3xYJXgzOkjB9piVobcVgFF7RUVZmfE147owGRaExf0/qOsXhAyqOHg7A76+oozhoiIiMDpFv1x1Oc744nCwGiMFoqTABkMGIEt3rgef9t6AePVzjce3ieQR2bQfftTvscx+qahBBKYX3s/lQNm+sPVggAGXLJgQO7oPj0afBt2lbZ/98331jyI6Wl0HZtgWW0ePqPGcNdN2w+AcAUFWoF4w3EKmapvAK0LuvYXtp0GAQ+XF4l3wGvfByzYOCUNGN+PgxQPEHH4AQWG+9E2L3nqZ9bY7oxUVRnSdlDolLHUoGoynT2GIyrmrX8Lr7HVzQa4puR9RjWOFfhUnyONxsuREcqb+bSWr6KjW2q8qIBCEErdvwaN2m6UT7XY/XSw1F/11v36YtD583Nu9ZRQEuXtDQtYFqvZWUxDYFuZIL51W88g8XfEGSDzQV2L5FwfmzKp54xmFIBAwo5q93IMYC4NHDAXz6sRfF12pes9Xf+NGlG4975tiQkhr68zBoiIQdW40Lx4OGxCYbhsFgND2YAMhgRAFVA3C/+W9op0+GtNFOHof7tZfgePIZEEmCsnFtcPGv+rjl5XC/9W84/+NXIEL0P87alUthfbseZeum2AuAND4Lv1pE0dlX7N0XQq8+UI8fhXbqJKgaAJeUDHHQYHB2B7TLl+D7biUCu3dWrCa/R+jZG/K4SRB79IrlM2ja8IL5vCBBhDym7h20GIzGDCEErUg6LtHLkY2/pzXfeOqKluileMH1Mkpo8LRkHTpW+FdBhYpbrdPqza82XGtT9q25VnHyhMEIjR5F9mvlOQ4HQbmJiLRwqIGGE8AtlthvDGgaxXtveIKKf9W5VKDj8wVe3PuAPeKYCYnm/BRFxDSq8tCBAN5+1Q09xLL51AkNL/6fCz96zomUlOC+9u4rIC2dC1tvspI+/QSkpTddcZ3BYNQNJgAyGFGgbN1sSGDTLpyDP3895FHj4FtjrMC7XnQNgb27IQ0ZFrV/+tVCc/aXClD2x9+C79ARUk4ehO49a6Uvm4WIEkhSMmiJwShAQqJqqkGiTCMlhEDs0SuomMe3bgP7PXOgz5gJ/VIBqK6DT01jKatBEDp1gXrkoIkTBNhnzwPftl38nGIwIuClPpToJeDAI5VLhkDisxzqKXbDJcWYAJhKkpHCxaYERCz40vtVSPGvOqv8a5EtZaE9Xz+f6f5iHyQQJ8pouSH7kfKIOHvEqMTnpdi5XcGFcxooBdJacRiaLZkWWJoDNjuB1UrgNRjNx3FAUkrFumvAYAkFF2NTvy8phGBUHwwZFnuR6dD+gOHIyj27Aph6q47EpPDXIDGJQ7eeAk4cNdZIY/BQKWaNaBSF4uP3PCHFv0rKyigWLfDgoccdQY9zHMGcB+145R+usO+51DQOd9wbu5I/DAaj6cEEQAbDJJRS+PPXG7ZXNq0H16atcSEMgLI1v04CIDjziy69+Br04msI7N0FoVcf2Gc/WOcUTTk7B76Vyw3ZCn0HgDPR0beKOgqV4eBsdnBdu8dt/OaAnJtnWAAkKalwPPAoE/8YDcZZ9TxW+ddid2AvNFSE29iJDTlSNsbLo5HAJcR0vmITTT3c1AOFBiCRhk/Nculu7AjsNmy/zr8J99huj59D1eAJjxssE7DQuziibU+hO7rwneLvVAuHUorvVlY0YlCuK3v39Zc+DBsh4ZY7rBDFplXHry5wHEHWcBEb1hirAzggU6xKVx2eI+G7FT6odWyi26ETj1atYyfCEWKufHJScuwFwF07jGcc6Dqwd3cAo8bKEW1Hj5MNCYCEAHljIo9nlN07FHjcxi7q4QMqrhZqIaP32mXwePJZBxYt8ODk8ZohqIQA/QeKuPUuKxISWp4gz2AwfoB9AzAYJqEeN/SCi4bt9WtXoZ0z12lXL7pm1q0a8G3bVWwnR4l65BDc774OGmlLMgJSTh6IzcBOI8fBMm4iaBSrXVpeFoVnjFgh9OkPwUhKtGyB46EnmPjHaDC2KjvwvOuf2BHYVSX+ARXC27f+Nfhz+Qu4aLLBRCSOqccN2/rgxznNfB3UeHBCPQUVxr+PD6tH4+hNbcZIIzFOHh3WpgOfgQdtc+oczc6IzJeLfPjqy9riH1AhwmzZpOCd19zQtJZVjzFvjAzRgJ7PccCY8T+ISolJHO6811bn/c0xE2InVAHme6edPB77UjDlZebGLC81Zt9vgIjxkyJfr1vusMBmJygt0aHrdX8/799jroTK/r3h7du05fHET5z46S+cmHqLBRMny5hxuxW//F0C5j5sZ+Ifg8FgEYAMhmmCrXAjYXbVxP+wu6cXF8G/ZRO0C+cAnYJLT4ecnQO+XUbI07nEJIh9ByCwf495X79HPXYEgX17IA0aHPUYnDMB9gcfh/uNl0G9IQq2cBxsd90HoXNX6KEab4SDbxp1TKjfD2XXdijb8qFfvQrwHPiMjpBzRkHo1QekDoJtQ0I4Dva5D8H9zutQjwcXAYjdAfu8x8C3Mle7i8GIFSfUU/jAswA6Qt8MltEyvOx6A79MeA5WYq3znJRS+GDuO81HY5P2V1f8Jv320yi+u+sAIQQzrdPRQ+iGtf4NOKIeqzqWxqVilJSDUXIuJCLVq18tkeNHA1i3OvLrf+SQivwNSlX0FKUUBRd1uMp1yBaC9u15CM0sQjAtncfsB+1470031BC6DSHAHbNs6Ni55i3ZkGESJJlgyUIPiotorXOA8EvLsRNlZA5p2Pd/LASy6zHbeEOSjdtPmW5BajqHVSv8KLquGUd6aw7p6Ry+/tKPzz+p+J62OwiG50rIGyNHnebu8Zi7Rl6D9m3b8WjbrmmsjxkMRv3CBEAGIwJU0xA4tL+iWYSmgjidFdu1RqPjCIHYvQf8K4zPyXfoBKpp8H7xGZRN62uu8o4Ayoa1EHr3g+3eueCswSPs5ElTEDhy0HyDhmoo+evrJAACFTXiHD/5OfxrvoWyY+sPAirHQew3EPLYiRA6da54SDK/W823DS2ENha0ggtwvfnvWmng6sH9UA/uh9CtJ2z3PxTytWzsBA4fghoiKpakpsHxwCPg27DIP0bDscK3Kqz4V0kJLcVmZTvGyaPqPCchBDJkU2KakzjrPG8scJDgdaZiZR8rBor9MFDsh3K9HGXUBRkSUrjkeu1K3NLZuM74pujGdX7k5InYvCGADev8KLz8w2eyUkwZN8kCawwbLDQ0ffuLeOqnDqxa4cf+PYGqpSMhQK++AsZPsoTs0tt/oIi+/RNw+KCK0ydUBFQgKYkgM0tCSbGOr5f6cOxIzUjdVq05jJtkwdDhsS8lYDYFuF0cBKjuvQQcPmg8Orl7T+O3uoQQDM+VMWyEhONHVRRe1kG4CiFz+Re+Gu9XAHC7KlLft2xS8PCTdmR0MH9bbfa9HovmI2dOqdi03o+jh1QoCoXDyWHQEBEj8uSQTUYYDEbzgQmADEYYlD074f1iEWhpSdRjCL36QOjSDXyXbtBOnTB0jpSTB8+CDxDYuS2kjXr4ANyvvgjHEz8BkWrv8grtM2C//xG433sD8EcXnaGeOgFKaZ1TqPjUNNhm3g3r1FuhXb0C6Dq4lFRw9po3jVGlHPONe7GiFxfB9eqLoK7QBevVE0fhfutVOB57GqSJRDRWouzYCs/H74U8Tq9dheuNV+B86qfgEpPqzzEG43uK9RIcUo8Ytt/k3xwTARAAeJj7PNtI49gE6CF0g4PY4aJuQ/ZZ0qA4exQeJ+eEE41DPG1J6DrFwX3GNxkLL+t44xUPjh2uLeBUiikH9gXw2NMOOJ2N+7fdDO0zBMx5UEB5mY7LlyoapKS34pGUHPk5chxB3/4i+vavKeglJnF49CkHrhZqOHdGg65XNHjo1IWPW9o7xwGaie7GkiX2fgwbLuHrpb6QEZXVaZfBo1MX82sqjiPo2VtEz95A4RUNL/xvOcIlqLhdFK+/5MZPf+E0nWLbd4CIQweMC5r9BkQv7Oo6xeefepG/vqZo7/fr+G6lH2u/8+POWTZkZbPIaQajOdN8fl0ZjBjj37IJnvffqpP4BwDyqLEAAOtN0w2lq4r9B4H6vGHFv0q082fhX7869Fi9+iDhZ7+CPOFGkIQoittrmvn05TAQWYbQvgOEDp1qiX8AAN3EyrKSulbJjjO+VSvCin+VaKdOILB3Vz14FDt0twuehR9HtKMlxfB+uagePGIwanNZuwIK499jl/QroDH43qOUwosQpQ9CUKhfrfO8sUAkAvKkHGO2EJAjDY+zR4zGiOI3JwgBCCr+VedygY7333TH5DPY2HAmcOjeU0SPXqIh8c8Iaek8Bg+VkJUtoXNXIa41L82+1ooS+9fQ7uAw7ZbIJRoEAbjtTmudr8faVX5De+huF8WmdeY324cMkwxHAfboJdSpqcvSxb5a4l91NBWY/77HlKjPYDCaHiwCkMEIgl5UBO+iBXUeR544GWKvvgAAoUs32Gc/CPeHb4dMyxX69odt1ly433/T8Bz+1d9CGjUOXJAoQADgkpJhnTIN1inToF48D9ff/mx4bJKQUK+16YhgfmeTio13p5L6vFB2RBZyK/Hnb4A0eGgcPYotytZ8wynmgb27oZeVRtfpuYVBKcUx9QROaWegUhUpXDIypQExqUvXEiEwdwNIQfGz0l/DwdkxUOyPUVIO0vk00/Oe086bEh4BmPQ0vtxomYgT2ikcU0NHrhMQ3Ge7G0kc+1y3RCTZXEUUo5w8ruHMKQ2du7LblMaE2RTgQBwEQAAYOUYGpcCXi73QgujJdgfB7Hm2Or9/FIVi5zbjKe5bNym44SYLOM74N7ksE9x5nxXvveEJe23tDoKZd0e/Bii6pmG9gVqdlde1T//4ismM2FNeHjnYoDHhdLKo/YaC/bIyGEHwb95gfKszyIqIJKfAMnEy5OG5NR4X+w9Ews9/A//mjVB2bK2ILhQlCF27Qc4dDaFXHwAVXXiNQn1euN94CY5HI6ePCu0ywGd0hHb+rKGxpaz6jerQoojmUw8dgPR9DcHGhlZwEQgYXzxqp0/GJOW6vggc2GfcWNcROHwQcraxqKKWyoHAISzyfoHLemGNxz/1LkaePALTLTdBIOyn2wxt+NYgIKbEOB988Ok+fOdfizX+9bjNOh1j5TzD56/xr8dn3i9M+UlA0IZvPI1yRCLgcftDWOz9EvnKVgSu6wrcmkvHbdbp6Cf2aSAPGQ0NxxH06S/gwN7YR+JvzVeYANjIMBuUWVgY+y7AleSNlTFoiIgtmxQcPRyA31chkmVmicjMkkw3CwlG0TXdVN+/sjIKj5vC4TQ394BBEu5/mGDhxx6Ul9e+yO0yeNz3gA1p6dFH/23eqBh+/Qov6zhxTEX3nrGvI8lgMBoe9svKYAQhsG+3cWNKYZk8DZBEgFLwrdqE7erKJSXDOnkqrJOnBh/O7ze9na6dPAHf8iWwTrstoq08Zjw8H74TeVBBhJwTmzpYRqFuY/WmqqNfuRQHT2IDNSto6nrFvyZSB5B6PHG1b2lsU3biPc/HQYUqBQq+86/DJe0yHrXPA0+axnukMZDIJWCA2A97A/ujOl+HjoXexbBAxgh5WET7ncpuLPQuMT1PRy6j0UXSSUTEnbbbcLNlMnYF9qJYL4ZIRHThO6Gn0L3JbFYw4sfI0XJcBMBrV+MnHjHqhyuXoijrYgJnAoeJky2YONkSl/HrMwu930ARvfomYP+eAI4eVuHzVQiJg7MkdO5a97qOZ06Zey3OnNKYAMhgNFOYAMhgBIG6XabsueRkSFnZsZlckgBRNN29179pAywTp4BYw6cIiJlZkM+dgX9d6NqB4DjY7r0fXEqKKR/qCrGYX8QRZxS1DesJLinZlD1JSGxSTUCIzVzDArP2LYlivQQfehZEjFI7qB7Bt/41uNEyoZ48ax7cKE/AwcAhqIj+hnSxbymypMEQw0Rg6lTHl76voxr/sn4lWtfijp2zIU8e0dBuMBohPXoJyMmTkL8hfKhUcgpBcZFxRaUeq48w4oTN3rQ3CFJSOVPLcbuD1Ok5C0JFh+fMrNiXttE0c2qmqja/GpwMBqMC9vPKaNZQNQC9pBi6qzxoQWnq80G7Wgi9tKTGcSKbq7NBLLGrzUUIgTgg0/yJAQXKnh2GxrdMuw3WO2aBS0uvdZzv2h2Ox56GNKD+uzqGqmMYDqFHrzh4Ehv49FbgTaQnS0ObViF9sd9A48YcB7F3v/g508TZ6N9sWJxa598IjcY3sqK50UnogHn22RDrsO/pom7sDuwNa3NMPRF1Iw8f/LikNt6IZgYjGIQQ3HqnFRNulCEE+XgRAgwZJmLqrebWSR06Np3NsJaC2f3J/gObdgSZLBMMHmp8XTo8VzJV/68+SU4xd8tv1p7BYDQdWAQgo1miXjgPZf1qKLt3AmrF1h2Xlg4pJw/yiDxoF8/Dv241Agf2VqXbVj8u9OkHZdM6Y5NJEoSu3WPqv5w3xlAX4OvRr10zZEcIgTw8F9KwEdBOnYR2rRCE58FndATfuo3peWOG2RZzADhZjoMjsUMeMwGe9ww0dRElyDnGa4w1BqTsEfCtXGZoe1wcOBhcNJ2oWwg7ArsN25bSMpxQT6GnGNvvnebOQLE//tP5LNb4N2CrsgN+mO/YeEo9jWHSkJDHz2sX6+IiNihbcLswo05jMBj1DccRTJlmxehxMrZvUXDhvAaqA2mtOAwbISEllYemUSQlE5QUR44sIgQYPrLxNvhqqfQfJGLPTmPhcJIE9OzdtAVAABgzQcauHUrEcs42G8HI0Y13PTp0uIRd242/dgMz2eePwWiuMAGQ0ezwb82Hd+HHtero6VcL4fvyc/jXfAsapFNS5XFlx1ZYb7ndsAAoZWVHTLs1i9CxMyw33FwhrpjBZM4M4TgI3bpD6NZIhIQocn6I2LgXmNLAwdAm3AD/qpWhjXgB9tkPgEuu35TrusLZHbDdMQuej94Na0eSU2CdHrk+ZUumXDdXdqCcmrNnVNCab4W7bLfhdusMlFMX5ns+w371oOHzI0VpUtStbplHZ3UyGU0Xu4PDmAnBS3nwfIVI+PF7kd/jOXkSUtNYBGBjY8ZMC/buChiqjTfhRkuzqBHaug2PuQ/Z8e4b7pAioNVGMO8xOxKTGm/UXI9eAtpl8Lh4PvJGe06eDIu16b92DAYjOI33m4rBiILA0UPwfvpR2CYawcS/6ugXL8C3dAnkiZMjzselpsESoplHXbHcMAVC776mzhE6dIqLL/UF4ThwbdoZP4HnwbduGz+HYoR1ynTY7pkDLoivQs/ecDzxY3Bt2sG/aT18330D/5ZN0MvKGsBT80hDhsE2+0EQpzPocaFbDzh/9Cy4hMbV3KCxIRNzu+1m7Rk14QmPJC4RrfjaZRDCkcwlhT3eim9VB6+A9nzj/z5jMKIlK1vCjJlWhNOFsrJFzLg9tpuqjNiQkMhj7iP2sK8fAAwcLGLCjfFpzNEQ9O4r4pmfOzFipITqlWosVmDUOBnP/Kez0Xes5jiC+x+xIzkl/IvXu5+AKdObz2vHYDBq07i/rRgMk/hWfhWTtl3a2dOQJ06G5aYZ8K1cXpVGXB2+c1fYZ88DZ3fUeb5Q2GbejbI//saQLUlMgtCnGdRYM7NjzPExj76MF1JWNsQhw6CdPQP9WiHA8eAzOgAcB++ShVAP7q/x3vVyHMRBQ2CdPhNcCHEtFNq1q9BOnwQNBMAlJ0Po3iuuzUWkQYMh9huAwP49UI8fBVUUcAmJkIYMBd8uI27zNid6Cz2xJbDdkK0EEV35LnH2qGUwXMrCd/61hmwJCLLFrLA2/YTeSCQJKKXRCfijLLlRncdgNBVGjZPRvaeAjev82LMrAK+HQhCBXn0E5I6S0bO30Cwix5or/QeI+PF/OLDwYy/On60ZTeZwABMmWzBqbPMTkFq15nH7PTbMmGlFSYkOQoCkJA6C2HTeqykpHJ5+zokVy3zYuU2BUi2iMTGpIoV5zAQZPN90nhODwTAPocE6IzCaHFevRld0vDmhXSpA+fN/jNl4Yv+BsN//CHS3C8r2LRWCiqqCS0qBNHQ4+I6d6mWR6l3yGfzrw3Ts/R7bPXNi14m4ASn5j6fDRnBej+O5X0Jo0zSjZrSrhXC99HfQ8tBiAZeWDseTz4Az0O1Yu3ge3mVLoB45VONxkpAAOW8c5LETQFhrxUbJafUsnnf905BtrjQcs2x3xNmjlsOLrtdwWD0a0W6wOBAP2udEtFvjX4+F3iWm/ejMd8RzzqdNn8dgNGU0jYLjwES/JkhpiY7iIgs0jSA9nYcz0c1exyaC10tx5pQKv5/C4eTQuQvPhL8wpKWlNbQLESmPkOHW2HCaDG5gxA4WAchoNmiX6lZ8/XrUgorxOLsDljETgDETohpH93qgFxWBcARcajqIyU63lmm3gvp9ULbmBzcgBNbpM+tF/NPdLihbNyOwZyd0VzmIbIHYszek3Dzw6a3rPr6imBL/AEA7cbRJCoCUUnjefzOs+AdU1Kb0LPgQjoceD2unnjwO1xsvo8aWbuVcZWXwLV8C7eI52Gbdz0TARkhnoSNGS7lYp2wKa2cjNoyWRtaTVy2DubZZ+IfrZVzSr4S06cBnGBZdx0h5uKpdwxplg2EfJIh43P6QYXsAUKmKA4HDKNSvggeHDkIGuvFd2A04o0nBRIemS2ISh85d7OB5HpqmobiY1TBtKlitBL37Nu4a2gwGIz4wAZDRfIh1MKvffIfI6qgXzsG/5lsE9u7+obutLEMakg157ATwqcZ2kwjHwXrHLIhDhkHZtB6BIwcBvx/E7oA4aDDk3NHg60EAC+zfC/dH79QQmCgA/+UC+DesqUiZvuGmer/5pHrTDGLWTp6AduG8IVv18AFohZdDiqy61wP3O68HFf+qE9i9E/72HWEZN9G0v4z4c7v1FghExGr/OlAEf197qAd/cb2AIeIgzLTOgJMLX4KgTC9HvrIVuwJ74dJdsBIL+oq9kSflIJ1v/Dva9YGTc+BZx4+wzLcSW5Rt8FXrDmwjVuRI2bjJcgNkYqzDIyEEM60z0E3ogjX+DTihnQprz4PHLxzPwc7ZDI2vUx2r/GvxnX9trWYwbbjWmGG9CQPE+i0HQSlFAAEIEMCRpr3BUKyXoFgvAQ8ebfnWkFi9TQYjKLpOUVysguo6mkowj6ZRlJdR6BRISCAQBCZAMxiMlgVLAW4msBRgQLt4AeV/+5/YDWi1Ien3f4nqVGXPzorOqFrwblvEaoX9wcchdO4a1fhU14NGcVFdh3r4YEUTiSuXABDwbdtBGjESQveeUUd+BY4ehvuNlyNG51kmT4XFQPOUcJQ89yNT9pZZ98MyZCiAyud/AOqpk6BqAFxSMqTBQxtlAwrPwo+hbN5o2N5yw02w3HBT0GP+9WvgXbLQ0DgkMQkJv/h/YWsC6h4PlO1boB49BOr3g3M4IA4cDHFAJojA9o3izTWtCCv932GzshVamK6y6VwannU8CScX/M5rh7IbH3jmIwC11jECgqmWybhBHs8ixqrhp34cV0/CQ72wExu6C90gkbpFSbzpeg+71L1hbRKRiP+X8F8QuPCfL0opPvJ+inxla0gbAoJZ1juQI8c/KvyCVoB1/o3YoeyCD34QEPQUumOUlIt+Qm8c0o5gf+AQfNQHO7EjUxyAnkL3kO85P/Vjh7Ibh9Qj8FE/HMSOIdIg9BP6xF1YPBg4glX+NTiiHqt6zAILhktDMckyDklc4/sdYTAaAq9Hx6b1CvI3+FFSXHEbKYoEg4aIGD1ORruMxtfBuaxUx4a1fmzZpMDtqvDZYqloTDNqnIy09MbnM6PxwFKAYw9LAW442J1cM4GPY4H/pgLfoSP4jp2gnT0TmwF9XnCEmBbN1HNnw4p/AEC9XrjfehVJ//FrcIlR3FQEeb310lKUv/kKtHM1n79eeBmBvbsqurE+8IjppiWUUviWfGYoNde3cjmsOXlRC266Yj7qkly9Ap7n4d+7C57FC6EXF9X0adkSyFnZsM+8C0RuPIWpqcsV2aiGfXnIz7mya5vxcUpLoJ86AalXn6DHfVs2wb1oQY1oQg1AYN8ecIlJcNz/MMQohWuGMdK4VJz0nAor/gFAoX4VH3s/w+MJD9Y6tk85gHc8H4aMJKSg+NL3FSROwkTr2Fi43SywwYaBQv+YjXfIfySi+AcApSjF294P8FiQ17I6m3xbwop/QMVr+7F3IbrL3dCmjl2Jw7HWtwEL3ItqvMcoKI6ox3BEPQYRIgKo2UBrvbIJbfnWeMAxGx2E9jWO7fDvwofuT+Gl3hqPbwvsRDqXhoecc9BR6BCX57LC+y0We5bVetwHH9YqG7ArsAc/Tngc7YSmV26iueHz6igrrWgckpTMgePYBkZ9cu2qhn//04WrhTV/nwIBiu1bFOzcpuCeOQ4MHW4sYro+OH9Oxav/KoervObvoc8HbFynYNsWBfMedaJXHxbty2Awmj9MAGwmJCcnN7QLjQLptjtR8MJfYzMYpUhOSjLdPfXSx++FFf+qhve4gV3bkHxr3Yv5614Pzv/1RWgXQ6eUqieOwfPWv9H+P38LzkQdQu+RQyi6XGDQER1kz04kT7/N8PjV0dxuFJs8R9RU8Af2wvX2ayF98m/bDFy7irRZc+HatB7+c2cASiG2bYeEMeNh6daj3qOg/A47aveWDo3VmRDyc15SWmpqbmtAQUKQscrWrYZ7/vshz9NLS1D+yj/R/he/hYWJgHFjr2c/CoouG7LdFzgAvyOANuIPQo9OdSw8sySk+FedL7zLMaX1JDj4+HUzb8l8eOoTw7Z7AvuRmJgILsSmE6UUa88ZixrWoWML3Yb7k+8zPH8kyjUX1pStw9ryDbgUuAKV1o4src714l8lBdpl/L38Jfx3+1+gk1wh6G0q34w3rr0XcqxC/SpeKHsZ/53xy6pzYsVW13YsvlZb/KtOGS3HK+438XzHP8HCNR5hoyVx7IgXK5aXYOc2d9V+ZGqagHETEzD+hkTYbLHfCKeU4tABL7ZvdcNVpsFq4zBoiA2ZQ+wtUnhUFB3/+/tztcS/6ug68PF7LnTslIhefaz16F1wykpVvP7SuVriX3UUP/D2qy789k8d0K49EwEZDEbzJq4C4LZt27BixQocPHgQRUVFCAQCWLVqVQ2bq1evQlEUWCwWpKSkxNOdZk1xsVnZpJnSqStst94Jz+JP61wTkEtKRklZ+AYN16O73XBt32LYvmT1tyBjJtRZfPJ88xWUMOJfJf6TJ3B5xXJY8sYYH3v3TlO+lB/YBzJqnKlzKtHV8DeUwfB5vCh7+/WIdv6Tx3HhD7+uee7xoyhfvwZCj15wzn3IdHRkXaCdugKbwzd8qI7WoVPIzzk1KVJ7FAXadWPpXg+KP3g74rlU8ePSW68h8Zmfm5qTYZzVrnWGbSkoVheuxWTrD3Ud9yuHcEUtNHR+gAbw9eVvMKGZRwFSSlFOXQjQAJyco97qul3TiiIbVeOryyuRaxke9FiBeglnlXOGx1pflo8Zws2m5g/FscAJvFr+Ftw0NkX+vboXL198DT9PfAZ++PFa8TuRz6E+vFrwJn6W+OOY+FDJwpLFhuyuqtew8vK3GGXJjen8jMisW+3F55/Ufu9du6pi4fwirFtdgsd/nICk5NiJgBfOq/jgLRcuFdTc0F37XRmSUzjcM8eBHr1aVhOFLZt8uHQx8talrgOffXIFjz+dUA9ehWfFMg/KSiNvyvv9FEs+u4y7Z7PNMEZtWKBNw3LixAn84x//wLfffotz586BUooOHTogOzsb99xzDyZPrig/tWbNGowbV3EPSinF5s2b8fzzz2Pjxo24cuUKnnrqKbzwwgsN+EwaB3ERAI8fP4558+Zh48YfdqoppUFFjv/5n//BCy+8gPT0dFy4cIGlskaJZiDirKUgjRwNrl17+Nd9h8CBfVWpqyQhEYTna6WIhkIcNsL0dVULL5vqYkvLSqF53CCW6HdJqa7Dt2m9YXvvxrUQc/IM25tNy9UVJer3ox6hiUUw1EsXAc28cFhjjGNHUPbKP+F44icgcvDoDqppoG43wHMgNjsIIdAuX4I/fwO0U8dBAyq4pCRIWdkQBw4GEcPfGAiDhoB88Rmo1xvWDgC4lFRwPXuHvK58l27Qi65FfqIAQAi4jp1rjeXfkh+xiUgl6tnT8J8+CaFDJ2NzMkxRqpnbeChRS2u8nkeV46bOPxo4gbHSKFPnNBUUGsAmZQs2+DdVdfnlwCFTHIixch66Cp3jNrdusqM5AGz17MBwcWjQY8Vqiamx3NQNRVXAk7qtqwq0S3ip/HX4UbfGWNdzRjuHk8ppnNPOw0d9hs45qZ7Gaf/ZWunD0XJBu4izmrFmTACw0bcZuWJwgZYRHw7sDQQV/6pz5bKO114qw0/+wxmTrsIFFzS89Pdy+EK8LYuLdLz6rzI89IS9RYmAG9dGXq9UcvRQAFcuK0hNa7j7Okop8jcY+24BgB3b/Jh2qwUWa8uL7mQwqqOrKjyrv4Fv+xZQnw/EYoFl6HDYxk0CV8+1wF9//XU8+eSTCAQqNh8sFgusViuOHDmCw4cPY8mSJSgpKal13oIFC3DfffdBVVUkJiYyjakaMX8Fd+7cifHjx6O8vBxG+os8/vjj+Pvf/47CwkKsXLkSU6ZMibVLjBaI0KUbhC7doHs9oKWlgCCAS0mFeuQQ3G++EnkA2QJ5xEjzE0dTpLyOhc314iLQEuMRoPqlAugeNzib3ZA9l2hu14tLSjJlXx3zt8uAbiDy0QjahXPwb1wHy/hJNR8vvAL/+jVQdmwF/BULSZKUAi4xEdqZmt099SuXoB49DPLVl7A/8AiE9qFT1YgkwXrLHfB8HDrtDQDAcbDOvCtsLUo5dxQCO8LXBatE6NMPXHLtaOvA0UOGzq9EPXqYCYBxQjYZnXa9vWoqubwiCrApUqaX4Zx2ASrVkMqnoD3XtsZGo0t34yX36zh3ncCjQ8fOwG7sDOzGbZbpGG8ZHRf/oumxVkhDR26ajVrkwYND3RtnLPOtiLn4V8newAFc1AyWmPieA+qhmAmAVzRjkbJV9jpruFafUEqx8itjAk7BBR379wYwaHDdonsppVjwoSek+FeJpgEfv+fBL3+XEBPRsSlw8YK5VdqlAr1BBUCvl6K0xPj3sBoArl3T0D6DVchitFy8mzeibP77tcpZub9YBPeyJUi4ezas0dwjR8HixYvxyCOPAABuuukm/OEPf8DgwYMBVDQ9WbNmDT766KOg5z700EOYMWMGnn/+eXTu3BmqquL8+djcMzZ1YtpSzev14pZbbkFZWRl4nscvfvELHDlyBJ98EroGTvfu3ZGZmQkA+Oabb2LpDoMBzmoD36Yt+LR0EI6D2KcfLDffEv4kUYL9/ofBJSaZno9PSwciRH7V8C81DTBRjy8oUUTNIWD8hl8cNBgwsdsjDYm+8yQJxPe5RELJ3wBaLWoncGAfyv/vf6BsWlcl/gEALSmqJf5Vh5YUw/3vf0ErDF/HTcrKhvXOewEhxHvGYoFtzoMQe/UNOw7fsTPELAPX3WKB9aYZwX32m7vBp37ju+oMc/QUutfJPomYa8LT1LqbFmiX8Kb7Pfyq7A94xf0mXve8gz+X/w3/63oB25VdACrqIL7ufqeW+Hc9i3xfYJeyJy5+RiMAWhA6Grw93w42YjxaPFy3XaOU6mXYGzhQpzHC4aVew9F/lfhp7MRIswIph5Yh9DQWLpzXcOGc8YyCLRujWENcx9kzGs6fNTZnWSnF/r1NcwMlGswmdxQXsewkBqMp4d28EWUfvhP6w65pKPvwHXg3G6tHXBcCgQB+/OOKkh8zZszAl19+WSX+ARVdhKdNm4aPP/446PmDBg3CJ598gs6dOwMABEGo+n9LJ6YC4Ouvv47z58+DEIIFCxbgD3/4A3r06AExgiAyatQoUEqxffv2WLrDYATFMm4i7A88Cv76JgYcB3HgYDif+inEHr2iGptYLJAGB0/fCoY0YmSdb9BIQgJgZgxeADEY/QcAnN0ByYi4BIBr1QZCiO6yhrDazJ8TRZpdyKGKr0G/VhERop4/C/d7b1ZsCUcB9XrgW/ZF+Pk8blC3C1xCtTo5ggAuNQ2Wqbcg8Ze/h9R/UMS5CCGw3TErrAhIHE44Hn4SfJvgXSw5hzPiPNePx4gPw6QhsMBYo4FWXDp6CT1qPJYlDTYlbAyXskz515AcV0/i+fJ/YVdgL/TrYobPaxfwjudDfOH9CkfUYzihhRbpq7PMtzIqsS4S0aSbtBNahzwmEREjpGGGxxol171W3VntfK3rHEvsxAYHZ/z3qPKcWNGeb2fKPoOPTeQhwxiXC8xGnNVdcDpoUtA70IIEQLNcuxq/7w4jWK0ECYnG18eCCKSmsjRBRstEV9WKyD8DlM1/P6q67Wb47rvvcPbsWRBC8Le//S1kg7RQ/PSnPzV9TkshpjHOS5YsASEEU6ZMwa233mr4vD59KgSD48fN1S1iMKJF7DcAYr8B0K5chn61EOA58G0zagoxUSKPmwhlz64aEWPBIEnJkIbXPYSaszsg9OoL9bCxKA1xUOT6dNdjnT4T2qWCsFFvxOmE/f6Hw6aqRoKjDbtYBADqr4gg8H+7os61BQMH90EvKQaXVDuNWr1wHu43Xwa9vtGMqkK/dhXKpvUQ+w0AbzUW8UMEAfZ75kAdOQZK/nqop06Aqiq4pGRIWdmQhgwLWd8QqHhfBPbuMvbECIE0INOYLcM0FmLB7dZb8IF3QVg7Dhzuts6stYmQxCUiS8zEtkDkBj4d+Ax045tGR2eX7sZr7ncipqOu9K/CEfWo4XEv6ZdxUjuNbkKXurpYZ64Xc6/nBnkC9gYO4KoevubnQKEf+gt12Iz5Ho3GN4JnoNgfbfU22B3YZ8iegGCQOCBm86fxqegj9MIh9Ygh+zwpJ2ZzM2JPHfdTAVSkjcbTviUhig0bMUsIwfBcCd98ZSxqOHOI1Cjr/104r2LzBgXnz2nQNSA1ncPwHAk9egstshs1Iz54Vn9jPMxX0+BZ/Q0ck+JXui0/Px8A0Lt3b3Ttan6dmpPDfq9DEVMB8MCBCgHi5pvNdZ2r7P4brIAjgxFP+FatwbcKHXER1ZjpreGY9yhcb7+KUEVkSFIyHI88Cc4Wm0gGefRYYwIgIZBNdACuOk2W4Xj0KfhWLK1oFuGrVgia4yAOyITl5hngU1JNj10dWsd6iLGAczqhl5UhcNDYDWlYdB3qqROQBg8FpRTamVNQjx+FXl4GZfsWIEzarV50Da7XXoLzmZ8brtcIAELHThA6mq/NJ/YfBJKUbKiepNh/UNA6gozYMUIeBh06PvV+jgBqC9E2YsVc2yz0FIOnC99puw2XXFfCpsAmkUQ8aJtd5yjk+iJf2QKPwS60F0zWlbuoFTQKAbC6gkEpxRntHPYG9sNNPbARGwaIffGU/VG87nkH57WLQYfoyHVAKS3DL8t+Bx48OgsdMUrKjSolOJWL3+e8M98JHYUMtKNtkEgSUEojN7/pJ/RGOp8WUz9ustyAY67jUBH+xqcz3xEDxX4xnZsRnjbtzK0J2rSte/SW1WbuM2Izad+U4XhAN7En0KZtw6/pckfJ2LRegdsVXqgVRWDsRGOR9/VFQKmoR7l7R80o0wvnNezdFUD7DjweeMSOpOSGv86Mpo9v+xbT9vEUAC9friij1KlTdPXG09PTY+lOsyKmAmBxccWNY6tWrUydF4/UGwajIRG69UDCc7+Ef+M6KFvzQd0uAABJToGckwdpxEhTok4kxJ59YLnxZvhWLAtrZ50xE0LHzlHNQSQJ1mm3wXLDzQgcPQzqKgeRZQjde4JLiFENsTiHk0eC79INXGISAseOxCy1mCoK1NMn4f38E2gXzBWfpcVFUPI3wDLhxujmprSiRqQggERIRyQ8D/vsB+F69Z9h60pyaemw3nZXVP4wzJErD8dAsT/yla04EDgEH/ywExsGi4MwTBoMmYS+WbESC37seAxLvV9js7INvmpRcwJ4DBYHYYb15nqt/6dTHcfUEzirnYMGHWlcKgaK/Qw3t9isGC8TogYRTZsClauhAu0SPvAswBntXI3j3/i/Qwe+Pe613oUyWoZ8ZSsKtWvgCIcUkowT2kmc1WueszuwD7sD+9BP6IN59vvCvm+uJ4Nvh3ZcW1zUzQmqkbARK+6z3QkAEIiAB+z34SXXa0HF7kqSSRLutt0eUz8AoIvQCfPss/G2+4OQ83fgM/CofV7EjsoleilOqKegUAWJXAJ6Ct0hENZQIFraZwjo0InHuTPGVKcReXWsqQyg/0ARq1YYrzPZf1DL6QLcpSuPE8eMvRY8DwzMrPvrUVecCRweetyON15xhxQBRQmY86A9JgJyrNB1ig/eduPAvtDfiRfOafj3P114+jkHbHYmAjLqBo3U+aiO9vUN6/obmpiuShITE3Ht2jWUXZ/SFoHKjiypqXWLHmIwGhNcUjKsN8+AZco0UK8H4DgQizVu0TaWSVPApaTC9+3X0Auv1PSlTVtYbrw5JmmbRJYhDYhcly4qGvjLOproyEjobhe8//5n1OKmP38D5PE3mHrfaJcK4N+4Fsqu7RVRqISA79wVcu4oiIOGhEzTFjp1huPJZ+BdtADamdM1DxICcUAmrLfeCc7J6v/VFw7OjkmWcZhkGWf6XAux4HbbLZhqnYzDgWNwUTcsREYvoTucXP2+hnuUfVjiW44res2uqzZixVh5FCbLE1FCS7HBvxkHAofgpV7YOTsGif2RKw1HAufENb0obv615WMbCR4tAuFxUSvA310vw0u9QW3OaRfwD9cr+InjcTxknwsAKNSu4q+uf8AT4hygonvum+738Zh9HjiD0daEEEy0jMV7nuBFtoPhJA70EXrhpHoaV2ntVOUOfAbm2O5Gm2rXvLvQFT92PI6PPQtxIYjY2FfohVm2O+MmWA8U++OXzp9hvbIJW5TtcFE3AKAjn4FRUi6GSkMghhHyCrWrWOJbhr2BAzVqJjqJA6PlXNwgT4goHrZELhVo2LVNQWkphSgB3XoI6D9QhCD88Ht3w00WvPmKO+JY7Tvw6Nu/7mJch04COnXmceZ0ZKErKZnEZM6mwqAhomEBMDmFQGjgFOBKOnQS8Ox/OrFutR/b8hV4PBVCoCQBQ4ZJGD1eRqvWjevzeXBfIKz4V8nVQh2rv/Xj5hnGG0QxGMEgFktc7c3Spk0bAMCZM2fiOk9LJKYCYOfOnXHt2jXs2LEDDzzwgOHzVq1aBQDo2zd8p0sGoylCOA7E7qiXuaSsbIiDh0I7dQLa5UsVwk/bduA7dWkaaX5mW8wZQMrJA0lKhv+rL8Pb5Y6COLCiuxSf3qoiFa+O0cnE7oB/zao6RTbSkmJQt8tw0w3/lk3wfja/ZgQjpdBOnYDn1AkIW/Nhv/+RkPUAhfYd4HzqOajnz0E9egjU7wPncEIckFmjliFVAwDhIkYWMhoeC7EgU4pd3TSzbPJvwUfeT4Me81AvlvtWYq+yHxf1Auj44TNXpBXjnHYeK3zfYpbtTgjg4xLZ15pLj1sdRAICCuPfIwlw4j3P/JDiXyU++PCu5yP8wvkcCCH4wrs8rPhXyUH1MA6qh9FfNL7eGiYOwWHxKLYGdhiyv0m+EaMsOdCpjsPqMRwMHIKX+mDnbMgUB6IL3yno71FnoRP+0/ksTmqncShwBD7qh4OzY7A4CK35+KfypPGpuNU6DbdYpkKBAh68oei9C9pF/NP1b7iDpKeXUxeW+VbitHoWD9vvZ9GA31NWpmPB+x4cOVTz85y/XoEzgeCWO6wYNLgieqxPPxG33WXF5594Q/4kt27LYd6jdvB8bNY5d95nw4t/c8HrCf3ZFQTgnrmxm7MpcPyo8TVaSQmF10thbSQ19RKTOEy71YqbpltQUqyDUiAxkYMoNQ7/rmfTeuMdrbdsUnDDTZYGr7nIaNpYhg6H+4tFpuzjSWUNv8OHD+PkyZNR1QFkBCemK5EJEyZg+/btWLBgAf70pz8hwUBDhd27d2PFihUVu8wTJ8bSHQajRUI4DkK3HhC6hS8m3yiJg5jEt8+APCIPnDMBvpXLa9W4I3YH5HETIY+ZUHVTyiUlQ+jVB+rhg3Wbu3MXqAdiUUvQmIAQOLAP3k8/CmujHjsC94dvw/7Ao2FFYSGjA4SMDjXdKC2Bf9N6KNs2g5aVAgD49h0g5eRByhoGIkaf7kN1vSL1WJLq1EiG0bi4rBVivveziHbn9eD17AAgABXveT5GO65N0OiwYPDg0Y5rg3P6hYi2ky2T4rJBQog58Q+oEIzOa5F9BoAC/TKOqSeQxCVhl7rX8Bzr/fmmBEBCCMw8jQ3KJuTJI8ARDn3FXugr9jI1VzehS4PWYySEQDbYhVulKl5zvx1U/KvOAfUwlvtWYrr1pli42KRxlet4+e8uXC0MXmajvIzi/Tc9UOcAWdkVvym5o2RkdOSxYY0fe3YFqvpzpaZxyMmTkDNKhizH7jPcug2PJ59x4OP3PLhwrrbolZbO4a77bOjSrWUJusePGt+AUQPA2dMqevVpXBGSPE+Qmta4Ny51nZq61h43RcFFDR07taz3IyO22MZNgnvZEmPBGDwP27hJcfVn/Pjx6NixI86ePYtnn30WixYtYl19Y0RMvykefvhh/N///R+Kioowd+5cfPrppxCE0FOcPHkSt99+OyilsNvtmDdvXizdYTAYTYyYR5NxHMQ+/QEAcnYOpKxsqEcOQrtYcYPNpbeC2G8AiFB7gWqZcCNcRw9HXQtQ6N0PNEwtPcNYLCD2yPUiKaXwfh0+yrES9eB+aGdPQ+hk/CY7cPQw3O++Uau7tXbhHLwLP4Z/0zo4HnrCVD1ISinUY0egbFqHwMH9FdeaFyD2GwB55BgI3YI3uGA0Hdb7N9ZIiYwWCopivdSwfaY4ADOtM/Ci67Ww9eumWaZgmDSkzv7Fiu/860zZ7wrsNZ0afVI7bcqeUordJgTGC3oBruiFaM2bqwfdFNkd2IdreuTGSQCwXsnHZMtEwzUvmytffu4NKf5V59OPPejZR4DTWXHD17GTgFlzBdx+D4WrXIcgEjidJG7ZDW3a8vjJfzhw5pSGvbsD8Lh1WKwEffqKLbb7qt9vbkNDUVpWjfdLBRq2bPRXdOvVKwTq7BwJ3XoIpt6numZ+6amYfG0YjOvhBAEJd89G2YfvRLRNuHs2uDAaTywQBAEvvPACbrvtNixZsgTTp0/HH/7wB2RmZgIAXC4XvvrqK3z00Uf4/PPP4+pLcyOmr1zXrl3x3HPP4c9//jO++OILZGZm4ic/+QnKy8urbA4ePIizZ8/iq6++wltvvQW32w1CCH7729+yGoAMRktHi216n9h/ELjEpKq/Cc9D7DsAYt/I6ZBCl26w3XUfPAs+CL0S4/laO2XEaoOUOwqWG26C6x9/rYv7AABp6HBDwqh25hT0gtBRVNfjz99gWADULl6A++3XgEBoQVO/eAHuN16B4+mfBhVUr4fqOryLFkDZvPG6yVQE9u5CYO8uyGPGwzL11qaRvs4Iyo7A7piN5YEHbbnWKNAvh7WzwIIplklI4Jz4qfNHWOffhA1KfpVQRkAwQOiLsfKokF2UY4EWRUmDq3rtmnnhKNPLcUQ9ZuoclQYiG1VDgQIF5s4ppy60RvMXALcqxtKiAcBLvdgfOIghUmb8HGrkuMp17N5p7L2kBoBt+QrG31CzzpQkEaSk1k8EFyEEnbsK6Ny1cUVWuV06LpzToOlASiqH1m3q53oIvLllmr2FdEhWAxQL53uxz95sagABAABJREFUfUvNNdKZUxp2bgugc1cecx6yIyHBWPQSLwBWK4HXa6J8hMGxGYxwWEeMBACUzX8/eCQgzyPh7tlVdvHm1ltvxUsvvYSnn34ay5Ytw7Jly2C1WmG1WlFcXAxKKRIT66+ZXXMh5r9of/zjH3Hu3Dl8+OGHOHToEB599FEAqLqBGzDghxvvyu6/8+bNw3PPPRdrVxiMRg/VdeiXC0A9XhC7HVyr1i06/ZEaLExvBJKUDOuMmXUaQ8rKBteqNfxrv0Ng3+6qH0Nis0EalgN59DhQjxvqqZOgqgouMQli334/pMKGqLNnGFGEnDfWkKl24Vxkoyjtfd9+HVb8qxrz4nkE9uyClJUdecwVS2uLf9fhX/sdiN0Jy/j4phkw4oNOdZRTV0zH7CZ0g12z47h2MuhxO7HhUfu8qgYTMpExyTIOE+QxKKElUKiKBOKEjYt/wfRohGsvItfxq44PPmgwJzQmc8mRjaohQgQHzlQkp8VgCm1Tp1gviat9c+PIIdWUgLR/b6CWANiSuXJZwzdf+bB3V6DGvXmHTjzGTZQxcHB8o0vNlkXW6h783ejRdYoP3/Vg3+7QwvbpkxXdep961gGrLfI6lxCCwUNFw3UA22fwSG/dcu8dGLHFOmIk5KHD4Vn9DXzbt4D6fCAWCyxDh8M24cZ6T8N94oknMH78eLzwwgtYtWoVzp8/D1VV0bt3b4wYMQKzZs2qV3+aAzEXAAkheP/995GXl4ff/e53KCgInXqTnp6O//7v/8bjjz8eazcYjEYNDQTg37AWyqb10It/iPjg0tIhjxwNKXd0i2yuEKu9Yr5LN9jvvb9G9F+0CB06QbjvAVCvF3pJMcBz4FLSQCpD3xOTwLdtH/RcsVcfaKdORDmxCPuch8CnGSx+b7BO4A/2xlbmenkZAvv3GB7Wn78hogCou8rhX/OdofF8q1ZAzh0V925jjNjDEQ4SRNPRY+GheNrxGPYFDmK9sgln1LPQoCGFS8EIaRhypGzYOVtQX1JISgz9aBykcak4AnMRgNlSlil7jnDoLfTAQfWIIftEkoC2fBtTczRVwnUGDkZLbwLicZv7nTJr35w5fVLFGy+74PPVPnbujIb33vRg0hQNN94cv80N1WRQs8/X/F+/Q/vVsOJfJVcu6VjzrR9Tpht7fUbkScjfoBgSXfPGyixTghFTOEGAY9IUOCZNaWhXAAC9e/fGv//974h2Y8eOrQowY4QmbiuRRx99FA888ABWrlyJdevW4fTp0ygpKYHD4UBGRgbGjBmDKVOmwGarvVBnMJoz1O+H642XgwpD+tVCeJd8hsDhQ7Df/zCI2DDFk7VLBQgc3Afq8YDY7BD7DwDfqh5u6KJYwIi5o0B0HVRRwDkTIA4eWqt5RUxcs1rBW80trKXsXPi++cpcd2OOgzgwE5bxN4Bvl2H8tHRz6XZcmjF7reCCqWI02vmzEW2U7VuM5xH5fVB2b4c8Is+wD4zGQy+hJ/apB2I2XhKXCI5wGCT1xyCpf8zGjQfxviFL5ZLRle+Mjdhs+BwCgpGS+c59o+RcwwJgnjwCPGkZG1jdhK44q503Zd+SsZpMCTVr31zxuHW8/Zo7qPhXnW++8qNNWx6DhsQnEtDsq8G3gDqJm9b7Ddtu3qRg0hQLhAjdejWN4pvlfkPiX3aOhKHDG1ejFQaD0biJ61akJEmYOnUqpk6dGs9pGIwmhefTjyJGhalHDsK7ZCFst99T43GqKNDOnQVV/CBOJ/h2GTFNGdYKL8O7cD7UEzUjSnzLl0Do0QvW2+8Bn5oWs/muh0ZRM0to1RZy3ug4eFN3uIQEWKfeCu+SheENLRZYb70TfEoquPRW4BxO03MJPXqBJCaBlpYYspeH5xgbOA6RhebTlY3fYDManvPqBaxX8nFcPRGxO6oZCAiGioNjNl5TRgCPe613oQ3fGryXN5wGnCVmwsn98P1SpBdjg38z9gcOwku9sHM2DBL7I1cagUQuocquv9AXQ8RM7IxQ0zGDb4fx8hgAFWVedOjNWgzMk0ZgtcHGLV34Tsjg28XZo8ZNrz5CsNK5Iek3gAkbALA1X4HbZey3ePW3/rgJgGaXA5Q27xxgXac4dsR4TrvbVdGtt0OEbr3ffOXDvj2RowqdCQS33WVh0X8MBsMULTsXgdFsod+LEI2tnp52tRCB3caKhitb82G54WZwCQnQ3S74V62Asm0zqPeHGlFcWjrkvDEVKcN1fK7alUtwvfh3UI876HH12BG4/vV/cPzoWeNpqSaJ5jkQp3mxrD6RR40FCIF36eKKqubXwaWmwTbnIQjtjUf7BYPwPCzjJ8H7+acRbbl27SH07mdoXM7ka20osjBO6cqMhkWjGhZ6F2O9kh+X8QeK/ZHGt5xmYclIQjFKaj2eRBIxx3ZPVQOTIeIgbAvsjDgeBw4zrDdX/b3Gvx6LvF/WqO1XrJXgvHYRK3yrcJd1JnLkinR+Qgjm2O6G1WvBRiV4xGEvoQfmWmfhQOAQ1iv5OKGegg4dDmJHtpSF0dLIZvf6teZbYayUhzXKhrB2AgTcap1WT141XpwJHAYOFrFre2RxgxeA7NyW3TG5km2bjdWCA4DzZzUUXNTQtl3shXezet7Vq837t1uLoltvpE7Kfj/FhrXGogrLyyiOHdHQp1/jutdhMBiNGyYAMpoN1O+Hsn0L/Fs2VnRDpRRceisIPfuAet3Qr1ypeKxVK0jZuRC696z3XTNlm/FULeg6lB1bIQ0ZCtcr/4B+tbC2ydVCeBcvhHriOGz3PRB13UBKKTwfvhNS/Kuyc5XD8/G7cD4Vn6Y90fjPpTT+G0o5bwzEwVlQtm2BevxIVbqyNHgohD79YlbvUcodDe1qIZT1a0LacGnpcMx7zLDYyqelg+/aHdrJ48Z8yI4cWRivdGVGw7LQuyRu4l9brg1mWe+Iy9jxhICAIrp6NL9O+A8c1o5ij7IfHuqFlVgwUOyPAWLfGlF1t1in4rh6EsW0JOx4t1qnIZlLAgBs8G/GQu+SkLYqNHzo/QQykaq61gpEwD222zFRHotNyhac0y5Ah450Lg25UjZa863wuvvdWl2JXdSN7/zrsM6/CXNs92CINCiq69FYuc06HTp0rFM2BT1ugQXz7LPRVehcv441UqbdZsXpUxqKr4VXTm6708o6m35PUYRrVcv+qh4XAdAsxUXNuxaXIAAWCyKmZlfHGeE9fXBfAD4TvaC2bVbQpx+LlGUwGMZhAiCjWaBduwr36y/VEsn0witQCq/UtL1wDoFdO8B37gr73IfAORNQXwQT8cKhFV6G+53XI54X2LcbvpXLYJ0yPSq/tFMnDKdZamdOQz17BkLHTlHNFY5oUoCpYrz+SkPC2R2wjJ0AjJ0QtzkIIbBOnwmhc1f4162GdubUD8fsDkjDcyCPnQjOZjc1rmXcJLgNCIDE4YSUPSKinTR0OPzffm1sco4z1FWY0bBc1AqwPoQAcj1WWODgHCjUrxqyz5GycatlWr107o0lhBDYYYML4TdWgtGaawWJkzCQ64+BYvhah4lcAp5xPom33B/gtHam1nELZNxinYo8uUKc91M/FnuXGvJjoXcJBokDagiO6XxajUhCoGIT6RX3G7XEv+qoUPGO50M4iL0qerE5wBEOd9puQ440HOuVTTiqHodCA0jknBgqDsaIEI1pWioJCRye/IkDH73rxsnjtX/zbTaCGbdbkZXNov8q4XkgYKKXEtfw2h8AQJabd2oqIQSZWRI2bzQWodmuPYdWEbr1mhZ7TdozGAxGTAXArl3rVtyYEIITJ6LsmMlosVCvF+7XXoR+zdjNZCXa6ZNwvfovOH/00/rrMGqyIDJ1lUM7V/uGLhj+jetgGX8jiCybdkvZEzl9rDqBPTvjIwBGcY5eUhxzP5oyhBBIg4ZAGjQE2rWroGWlgCSBb90GRIhul1js0w+W6TPh++Kz0PPabLA/+JghcZFPS4c4OAuBXZHT4aXsHHAJ9SfSN1XOqGexQdmMC9pF6KBozbVCrpSNnkL3eol0Xu83HvnnhQ/P2X+Mg+phfBYmCs0KK55wPIQuQuy/a+oLL0yEhlQjT4ospFcnhUvGTx0/wmntLLYpO1BCyyBCRHehC4ZJQ2AhP/zGbVd2wWfQrzJajj2B/RGj9o6pJww1CdGhY6nvazwr/sjQ/E2JDkJ7zBKaXpRqQ5CUzOGJnzhx/pyKndsCKCvRIUoE3XoIGDRYhCg1b+HILB06CYZrzXEc0L5DfBRAwplLA44kdjUHRo6WsWWT8W69mgYc2Kfg0kUNlAKt2/DoP0iE+H1jELMJITFKIGEwGC2ImAqAp0+fBiEkYvvlypuR6+1YEVNGNPi3bDQt/lWiXyqAf8MaWCZOjrFXweHbdzAkelRCXS7jg/t8COzbDWmo+Q6P1G1iHgC6SXujkCgKRlPVeAHmYOcG9u9BYPdO6K5yEFmG0KM3pOwRpqPkGiN8ahoQo6YtltHjwLdpC/+ab6EePfzDAVGCNGQo5PE3mGoQY7t9FlylpWFTi4XefWG95fa6uN3s8VM/3nV/hL3Xddo9r13AjsAudOU74yH7XCRw8a2VeVw9acr+hHoS4+RRaM+1xSr/WhxUD1elylqJFTnSMEyQx9ZoRNEUMdqcozopJBkj5GGmzyOEoIvQKaJgav61OhVRANxgIvX7pHYaF7QCtOfbmvKD0fipbIqwa7uCslIKSSbo3kNA1nAJVmvtNX5GBwEZHVgyUiRG5EmGBcD+g8S4pU63acOh4KLxdVqP3s0/NbVtex4zbrdi8afh83aHDBOg+Cn+8OsyuMpr3v/a7ATjJskYO0FGx87mPg+dTNozGAxGTL81OnbsGFHE0zQNRUVF8HgqOgMSQtCuXTsIAvsCY5iHUgolP3zx7Uj48zdAHjcpZnXYwiENGwHf10sBI6KVbD4qUYtSCCUm54omytAIRnZQa50ToW5hKNQzp+F+741aXXPVI4fgW7EU1mm3Qc4dFdXYzRWxZ2+IPXtDLymGXnQN4PmKyEKL+dRMIstwPPIk/BvWQclfX0PE59JbQx45GlJOXr18LpsqGtXwmvudsGmXJ7XT+JfrVfzU+aMaUWCxRoU5IT6Ainy2nmJ39BS7o0wvR7FeDJ4IaM2lQyRN/8ZR+//snWV0HFe2tp/CJkmWDDIzMzPbiR2H7cQO2g7DJBOazB3KMNy5d76ZOzPhCRrCnDhOYjsxMzMzg2xZau6uqu+HIkWyoKsaRK5nrawVq3edc5qqq96z937jaGmgovJI2v24hNSVOxe+9smMP6JZc+o+Gj1mC4C1jDOnNGa86uP0qZIC0bbNEeZ+HuC6SS4GD/vh2kHXDXbtiLJ1UwSvV8flEujURaFHLwVZsRMCitOth0LrthIH91d8TnE44MoJqTvPXznBwczXzDWoa99Jumx6OA4b6SAtTeCrL4LkXGJ84nYLDB/tIBw2+PTDsjOv/T6DLz8NcuG8zo03O2nYWOT0SXNC66Bhdqm8jY2NNZKeAWiWTZs28fe//5233nqL9u3b8/HHH5OZmZnM5dhcBhiBQNzZf0VjXMxFP3cWqWGjJK2qfERPGo6RYwl9+03MWHXgYMIrl1saP16xRO7QmfBqc/27AJSOneOaJxaxsofLPMabb/mY6PFjeP/zLITK6R8YiRD4+D0QBByDh1kev7YjZmYhZmYlPI4gKzhHjcUxYjT66VMYwQCCy43YsJGdEW6C9ZFNFYp/hZzUT7EotIyrnFekbC2ZYh3TPf0AMoXMEv/OENNTnqVY2YhxuJoPUwfRUEqt6c2lr33MeLFOzBjdYvZ2cedhm5rPubMaz//Ti89b9m94OAwfvRtA12DoSAdHD0eZ/Ya/lFiyYW2Ezz8WmHKHmy7dav4mQLKQJIG7H/Dw+ss+Dh0oWwR0uQTuetCTUvMPK2PXr395iH+F9Oqr0qO3wt7dUY4d0dB1qN9ApFsPhUMHo7z8bOzN6hVLwrTvKHPtjS5ef8kXc1N80FCV7Ib2JqmNjY01quzs3KtXL2bNmsU//vEPFi1axKRJk+K6+be5zImjZLTMYSrRSMI5/hrUGKKS0n8wkbWrIWKusXAhUvP4emUp3Xog1Mk0FStm1UPu1DWueWIh6NYzZoQ4SnUDH79XvvhXPO6zj1JW7mzzA4IoIjVugty6LVKjxrb4Z5IlIfOi/bLQSjTD+vfLLAOUvqZj0wQPXZSOKVtLdUEQBASsfZb7y31StJofGKCaf68A+iux19RAstZqoL5Y/d3bbczz2UeBcsW/4nz+cYDduyK89G9vKfGvEG++wZv/8bFjq7VM1dqO2yMy4TonrdpIFP+JdDgKhKCf/Sadtu1SW001/yvz18rr10TQ9cvrvk4UBTp2Vhg73smVE5z07qeiqALLFpl/3ZYtLnD1vW2aG6mCt7PfQIWJU2qWMZaNjU31oMq3Z5544gkGDRrE4sWLmTFjRlUvx6aGIbjcCK7E3fUq0wlYEEVck27B8+CPUbr3/KGDryyj9OpD2iNPYpzPwQj4LY0r1m+A3D6+m2pBknDffFtB9+gKJxFxTbkdIY7MFjOIcZSSSs1aWIqPHj9Wwh234uAI4bWrLK/JxibVhI1wmY6v5ZFrXLSUoWeVvmovMgRz59Hh6pBaUeJrBqsCYEhM/WZUC7kZ7SRzpm3d5a6mxL1BqvmehfXFerSTEzONs6k+5JzT2LXdXAsATYP3Zvlj7r/pOrz/tp9o5PISkMrDMAy++DjAi/8qyAAsni8RCsGq5WEWLgilPJFiyybzomw4DPv2xN+jubYQChns2Gb+ddi/J0p+vk6f/io/+00GY8Y5yKorICsFvQJ79lF4+Ik0brnTjSTZm6U2NjbWqRaN9yZPnsyqVauYMWMGd911V1Uvx6YGIYgiar+BhJYujHsMqU27pJQzWkEQBJT2HVHad8TQdYhEQFEQRBHt1Emi+/dYHtN5zQ0JCXNK56547rof/7uzy+yrJ3jScN8+DSVOkdEMcV28WuxHGN2z02L8LhiV3NJJQ9fRTh7H8OYjqA6kZs0RlJrZx8XQdaK7dxJasRTtyCEMTUPMqovafyBq/0GISRDobUoTNqxnx4QMaxnFsTgcPcq2yA4CRhCP6GaS61re9X9cocNsN7lzSkuRqxOGYRQZm5gl2e9RedzluYP/8z5Pjn6+3JhGYkPucE8xNV4vpQdzxXmmROYrHaMRhSrff7ZJErt3Ri317827aC7Ym2+wZVOEPv1r5m9jMvluXojF31Wsmi7+NoTbLTB2fAp7vVrU8zasDdG+o3xZZ/UH/Ibl/tY+r0F6OtStK3L19S6uvt7O9LOxsUke1UIAbN68OQA7duyo4pXY1ETUYSMJrVpuuVy2EMfwUcldkEUEUSwhYkV2brM8huvm21C790p4LUqX7mQ880fCm9YT2b4VI+BHdLtRuvVE6dkHQUlt1o4RtS5q6CdPQCvz2SSGidLfROIrHEvXCa9cSmjZYvSzZ4r+LrjcqAMG4Rg7Pm734ejRw0R37sAIBRA86SjdeyI1SG0vMSMYxDfz1ZKuwIB+8jjBzz8m9O08PHc/gGzh/bExh0twoiATsWC+kawee8e1E7zt/4DD2tFSj7WQmuPEwV5tfwnxK11IY4RjCOMcY5GEy6NnkSAIpAvp5Bl5po+pYzKLMlEyxTr8JO3HfBb8kvXhTSVMXFQUBqj9uN45AbdoTsBXBJmHPPfyrPclco2L5caNcYxgiGrdqd6m+hIKpi7rbMc2WwAM+HUWfFP+pkpxvv0myNARDpxlOC5XBetWRzl6JJ+x45yX7fuoxuGZd2BfhEaNL4/fSRsbm8qnWgiAFy5cACAvz/xFso1NIVK9+nim3YtvxqtgUUBSh41C6dYzRSuLDyNozmGtELFZcxyDhiZnbsNAO34U/cxpxLQ0hOyGKN16ILVoVTk7uHHcR1g1PhHTrIkgYnpyRBND0/C/9SaRLRtLPxbwE1r8HZHtW0l7+HFEk/0YoaCkOfDhO2hHS5aDBud+htypK+7Jt1kazyyGrpcp/pWI8XnxvvoC6Y89jZSdepOdywlJkOit9GRNZL2p+HZSG7LEzITnPRo9zr+8L5ab5XdEO0q6kM5jnge5YFwkYkSoI2bQUe6AIshEjCjbI9u5oF9AQaGN3JpGKTa9qEr6qb34LrTEVGxDMZumUpMUr+gHMsR0prpvZaLzOnZH9xIwArgFN52VDnG5EDeUGvDT9MeZF/yO1eF1JT4jraQWjHGMoLfS87LOBqqNeNJS934GA3YJ8Pq1EdP72+EwbFgXZsjwOFSnFHH6pM7bM/ycO6sz7urUZSdWV9xukeYtJY4eNt+D9+P3guTnGYy/xs78s7GxST7VQgD84IMPAGjYsGEVr8SmpqJ07kr6Yz8h+O08Ils3FTSQKXpQLZUdKGTUwTn6StRhI6vdzYhVU4tkiTvR48cIvDcb7cSxEn8PLZyP1LQ57lvvRGrcNClzlYegKCAIWKmXkJo2tzSH0r0ngc8/KvkZqSi+Z3Ka8gfnzS1T/CuOfu4svjdfIe2xp019LqNHDuN9+d/lGppEd20n/9m/k/7oU0kvc4/u2l6h+FdEMEhw3lw8d96T1PltYKRjmGkBcJRjeMLz6YbOm/7ZFZb4AuQb+cwJfsOT6Y8U/U0zNL4KzmNxaDleo2SLgQ5yW25wXktL2dp3uSbQQW5nWgBsLDaskt+jNNFDX7VXUsaqI2Yw2X0j17smcFw7ScSIkClm0lBqkJTxbaofXbopSHIALQXt3tye6nN9pusGAb+BrAg4HJW3rkMHrL2wx46kzuwpEebNDdKsuUSX7pdH/9fiDBmu8t5ha5v7878K0aixRM8+l2fmpI110pOUsGBT+6lSAdDr9fKLX/yCBQsWIAgCI0eOrMrl2NRwpCbN8Ey9Bz0/H/3MKQzDQGqQjZCeQXT/XrTjR8EAKTsbuVNXy5ljlYXStQfBOZ+aFsHUJGQwRo8fxfvCvyBU9o29dvwo+c//k/QfPYHUJHUioCAIBUYkmvkLWDGrrqU5xDqZKD16E9kUWzgRMuqgJKG02giFCC1fbCpWO3qY6P69KO06VDympuGf/XpMN2Mj9wL+D94h7f4fmV6vGUIrlpmOjWzZhJ6fV6lmO5cDLeXmTHJez8fBzyuMG6UOp6fSLeH5dkX3clo/ayp2v3aQo9HjNJebohkar/lmsiW6vczYPdH9/NP7Ag957qGj0j7hdVYntkXM9xw9HD2Kbui1oj+eQ3DQRm5V1cuwqQTS0kV691VZtzp2mprqgLCFrho9elW9WHTmlMbSxSE2rA0XXSI1aiwyeLiDAYMKXF5TxarlIbZstFbZomnVN2ty8cLQZSkA9umvsnFdhD27rIm5CxeEbAHQxsYm6SRVALznHnMZHuFwmOPHj7NmzRqCwYJfU0mSePrpp5O5HJvLFDE9vVTZZqHhRk1Aqt8AuVNXoiZ6AQqeNJRefROazzAM/G/PKFf8KyIYwPfuTNKf/HnKslQMXbck/gFE9+1B7dHL0jGuiZPRThxDP3O6/CBFxTPtXgQ58dNkZNtmCJrr4QMQXrsqpgAY3bkd/XyOqfGiu3egnT2N1CB5WdamnZQBdB3t6BHELomLUDYlGeMcQYaYzpfBb0oZMNQRMrjSOZqR6rCkfGc3RbZYit8Y2UJzuSkLQovKFf8KiRDhNf9Mfpf+S9xi7Sl72hDeZDr2Arkc1Y7RUrbmbG5jU9VcP8nJ0cNRTp8qP7NeFOHOuz0sWhDkwL7Yv/NZ9UQ6d6tasWjT+jDvzPSXuiw5dVLnk/cDrF4e4v5H0kjPSL5ov2JpiI/fs5Y1BlC/QfXc3IYCh9vcCzqZWTV/k8MKkiRw1wMe3p/tZ9MG84LusSMaJ09oNMgW2bE1wonjBQ7Q2Q0luvdSUFMoPtvY2NRekioAvvnmm5ZuMgodP51OJ6+88grdu3dP5nJsbGos7ptuIf/ZYxgXc8sPkiTcd0xP2Jgjum8P+ulTpmL1E8fRDu5HbtMuoTnLHT8Ow43I4YOWBUDRk0baI08S+OR9Ils2lSoHllq0wjVpCnKz5NyI6zmxnTGtxodjlBNfSmTLJqSx4y0dUxGGxXovw6Kwa2Oefmpv+ig92RvdzzHtOAYG2VI2XeVOSTXc8OpeS/E+w4dmaCwOmcsW9RsBVkfWMToJ5crVAcMw8GPtBj7f4mtsE5sj0WMsDa9gR2QXISNEmphGb6UHw9TB1JOsZZDblI3bI/KjJ9L48N0A2zZHShUwNGgoMmmKi/YdFbIbijz3Dy/e/PIz1RQV7pjuRpKqTuDYvy/K2zP8FXYLOXFc57WXfPz4J2lJXas3X+fzj6yLf4IA/QZW74yxy1EABFBVgTvv8bB1S66lcvkVS0Js2xwh/5Lvy6cfCIwc62DMOAeiaAuBNjY25kl6CbBhoXdXmzZtmDBhAo8//jjt2qVGULCxsYIRDBBet4bI1k3ofh+Cw4nSuSvqgCFJM4Mwg5iZRfqjT+F/bzbRfXtKP16/Aa6bb4uZJWaGyNbNluNTJQASx0WM7vPFDiprKk8anjvvQb+YW/B+5+cjOBzIHTolTfj7YTKLF7sm4g1vvqUhDW9yhQUxq65p4bgw3iZ1iIJIR6V9SktonYK1Bu5OwcHu6D7yDPOf1YXBJfRWepAp1rG6vGpHPFmXl/ZHtIkf3dD5JDiHhZf0YAzqIeaHFvJdaAm3um5isGNAFa2wduFJE5l+n4fz53U2bwiTd9FAVaFdB5l2HeSi70P9BhKPPpXGe7P9HNxfemOocRORybe7adGqatuUz5sbNNUq+NgRje1bIvTonTzhbc2qMNE4eir26a+QVbd6i2sJ7lnXeBQZSwLgymVll9YHAgZfzwlyPkdn8u2uatfP3MbGpvqS1F/XgwfNlYQ5HA4yMzNxOi8/Nyib6ktk+1Z878yES1x4tUMHCM7/CteNN+MYNKzS1iNm1SXtocfQTp4gvHkDhjcfweFE7tgJuV1HBKuiUjkYfms3nLrFeGtYv4ARYpUux0Csk4lj2KiExoiF1LylpXjZRLzgsHj+TPL5Vu03iOCXn5qKFRs3RWraLKnz21Q+XZROpk1HALrInTivX7A0x3njAr/J+zM9lW7c5LqhRguBVjZEC3HH4b5rUzZfBr8pJf4VR0PjrcD7uAQXvVS7AiVZ1K0rMvqKin9v6jeQeOTJdE4c09iyKYzPZ+ByCnTsqtCmrVTlYsbZ0xr795hXaVYtDydVANy9w7r616adxKRb3ElbQypwuQWyG1XfEuXKoHlLmb27k+eYs2ZlmPYdZXr3q96ZnzapJz/fWmJAVWObllQdSRUAW7a0dpNrY1NdiOzZiW/GK+U7w0ajBD58F0QJx4DBlbo2qXETXI2bpGx8wWXthlNIoXAfz0W/1fVXBXL7joj16psuBVYHDY09ZqcuBY7XJlE6djYdawZ1wCBC383DCPhjxjpHja3yGzqbxOmldCddSCffREZfIzGbDnI71kc2WZ5HR2djZAuHokd4Mv0R6orJdbCuLARBQEJEw5zjOICrFvU/rEpy9YvMDy00FftJ8At6KF1rhflKTaNJM4kmzarfZ/7ECWstK44fS26Li1DQ2uZBh04y9zzoQVaq9+9s/0EqSjVfY6oZPExNqgAIsGxxyBYAbWxsTGNf7dhc9hi6TuCj98oX/4oR+OwjjDj61FVnlM7WjBmULqnLlIinn6HUNDnlukYoRHjDWoLfzSO4+Fuihw/FlcFTFoIo4rz6BlOx6qChSA2yY8f16mta/JSaNENq2dpUrFlETxqeux4Ah6PCOMeIMSh9+id1bpuqQRZk7nBPRoxx6aAgc7t7CoIg0FZujRBHZi/ABSOXGb634zq2kLARZk14PZ8F5vJ5YC7rwhuJGNZcNRNBxdpNWT3BLpVPBivDq9FNCq85+nl2RneneEU2NQnDvGZfEJ9k411PurVzZvdeSrUX/zKzBEZfUfH1wuVA1x4KrdsmNwvy8EGN3AsWP7Q2NjaXLVXbYMPGphoQ3bPLvElDKEh4w1ocgyuvFLg42tnTRDauR7+YC6qK3KY9SpduCFL8FxNypy6ms9PEBtnI5bgpG9EIkW1b0E4cBwyk7EYo3XshxBCIiiMIAkjWGqQoPXubji0LQ9MIfvMloRVLS5V/S02a4bxuYlIcpNWevTECtxL4+P1yxWalT39cE6eYGk9wOHDddBv+2a9XHKgouG6+LSUZeHLbdqQ/+hOC33xJZPuWEndBYsPGOEeNRek30M7+q0V0U7pwv+cu3vK/V2a/ukyhDnd57qCN3AqALDGT7kpXtkRiu5qXxX7tIIejR2kpN7d0nGEYzAt9x4LQIgJGye+1R3AzzjGWMY4RKf1sGoZBAGstCs5q56gr1cyMx+rEwehhy/FdleRmSdvUXLIbWrumym6Y3HyKnr0V02XAklQgKlVn6jcQufdhT0rckmsakiRw9wMeXn/Zx6EDZWeOOp0QtNjdxuu9PM1VbGxsrGMLgDaXPWWZbMSKr2wBUM/Px//+W0R3lryJDi9dhFAnE9fEyajdesY1tiCKuG+5E+9/nqPCrtOygvuWO0v1HjQMg/CyxQQXfI3hu8Ro4tMPcY4ai2PMOFM9C/Vg0Fp3ZMA4fw7S0iwdU3SspuF785VSr2sh2olj+F55HvfUe1G7x/f6FscxaBhym/aEViwlsml9gZGHqqJ06IQ6ZARy+46WBAm1Vx/AwP/hu6XESwChTiaeqfcgt0hdewapcRM8d92PfjEX7egRDC2KmFUPoU4dIqtX4n3hnxAOIaSlo/Tsg9q7L4Jil6rUZLorXfhjxjNsjGxha2Q7ASOIR/DQS+lGD6VbKefhG5xXsze6v5QQZ5b1kY2WBEDDMHgv8DHLwivLfNxn+Pkk+AUXjTwmua6La02p4rR+ho6kzsjlciGKtZLMKMktybOp2TRpJtGshcSxI+Y+RwOHJPc3rVdflS8/C+Lzxk4t7NlHIaOShDVFhUjZnhRl0riJyKgrnPTorVz2pb/FcXtEHn48jW1bIqxcGubwoSi6Bll1RfoPUundT+Evv7XWz83hsF9fGxsbc8QlAM6cOTPZ6yhi2rRpKRvbxqYsjLCFqxnACFduCbDu8+J94Z/oZ0+XvZ6LufhnvAq3T0ft3S+uOeQ27Ui7/1F8787EuHC+1ONiVj3ct09DbtWm1GPBrz4n9N38sgcOBgh+PQf9wvmYWWjhrZsIvG+93M/q+1ec0OJvyxX/itB1/G+/ifyL3yFmJG5IIGU3xH3jzXDjzRi6nrCZi9qrL0rnboQ3riWycweEggieNJQevVG69UgoO9QKYp1MxDqZAASXfEfwy89AK3nzFN29k+Dcz/FMvRe5re38XpNRBIUBal8GqH1jxjaUsvmx50Fe9r3ORSPP8lwXdWvHbIlsK1f8K853ocV4dS/1xLo0lLLpqXRDEao2k0YULu8G+cnCat/IeqJdem1TkivGO3jzldg9buvVF+nVJ7kCoKoK3Hm3m9de9FW4L5vdUOSGmyqvh2KXbgqbN5hroaAo8OhP0m1hqhwkSaBnb5We5ZjHtG4rlemSXRb16ovUq29n/9nY2JgjLgHwrrvuSknZjCAItgBoU+mIGRkW4yvXlTI459Nyxb8iDAP/+28VmE2kxeeqJLdtR8bPf0t053Yi27dgBAIIbjdK1x7InbuWKVRF9u0pX/wrRnj1CuT2nb7PWCvj8a2b8M98La5GOkKcLlKGphFatthccCRCePUKnFdOiGuu8kiWk7PgcOAYNKxSXarLI7hkIcHPPy73ccObj/fV50l7+HHkFq0qb2E2VUoLuRm/zfgFG8Kb+CL4lSUhUBWs3VwvCi8zHVvc1dgjuBnrGMUVjlFJMYQQBAEBAQPz57VssX7C89rAILUfq8JrTcUqyPRWEs/wtqlddOupcu1EnTmflF+LmZklcN/DHhQ1+fdE7TsqPPjjND5+z8/JEyXbhggCdOupcPOtLjxplSf8DB/lMC0ADhis2uJfAgwZ7uDg/tgCNBQYi4ii/Vrb2NiYI+4S4GQ1x7exqWqUXn0Jfj3HfHycWXbxoPu8hDeuMxcciRBeuwrn6Cvjnk+QJJRuPVC69TAVH1q6yPTYoeWLyxQAjUiYwAfvxN1FWzdh3lIW0YP7MfIumo4Pb1yfdAGwtqHn5xdk/sUiEiHwyQekP/7T1C/KptqgCgqDHP1RBYXX/bNNH9dBLp0tqhs6ESKoqCU2JPN1L3uj++Nan8/w83lwLuf0HG5z3ZyUjU4RAc2CALj+e4HUb/hxCW66K10Yog4gXYxvo6MmYRgGB7RDLA+t4qh2HAOdbLEBgx0D6Cp3tiTKtpXa0FJqzmHtaMzYQeoA0kRPIku3qaWMGuukaTOJxd+F2L0jWnSZ4vYIDByiMmKMg/T01AlwrdvKPPWLdA4d0Ni7O0ooZJCeUZA5llW38jO+WrWRGTxcZeXSiisv6tUXGXe1M+XriUQMDu6L4vMZOF0CrdvKOJ21Qwjr2Udh4zqZHdsqbk/QopXE0BG2uYqNjY154hIA33jjjWSvw8amypDqN0Du0o3ojthN6sXGTZHbVl5/puiuHRX35buEyNbNCQmAVjAiYaI7tpqO1w7uR7+YW1QmWkh40wYMf2kzAbOEN6xDvaap5eOMfGtlhUa+ebHwciW8dqXpHo7a0cNEjx5Gbp66/oQ21ZMeSjcyhHTyjNg9jtIED72Ugg0JwzDYGd3NktBydkR3o6OjoNBL6c5IxzBayS3wlWFMYpUV4dV0kNvRT03QYMgw0Ew60RayPLKqxL8PaYf5KjifW1yTGOwYABSURK8Jr+O0fhYRkaZSE/orfXCLlVcKmGxCRog3fLPZFt1Z4u+n9DNsiW6nmdSEBz33kCVmmhpPEATu80znn94XyNFLt7UopIPcrtr1gbSpXrTvqNC+o0J+vs7FCzqSLNCggVhprruCUCBstW5bPdq2T5zsIhwyWL+m7EzAuvUEHnrMk9LMxHDYYMHXQVYtD+P3/bDB4nBCvwEq469x4vbU7JJYURSYeq+HD9/xl/tad+oqc8d0d0oyUG1sbGovcf2aTJ8+PdnrsLGpUtyT78D7wv+hnz1TboyQlo5n2j2V6mhqVRhLREiziuH3W87aM3w+uEQAjO7akdA69OOxMzzKQlAt9uxR7R3WWET37rYWv2+PLQBehsiCzBTXJF7zz4xZHjvZNRFFkNEMjbf9H7A6UjIjOkKEtZENrI1s4GrnOAarA5KyxsWhZQkLgMn6rYgS5a3A+wiIHNIOsyK8Gv0SYfGzwByudI5mvOOKpJQvVxaGYXBMO8Fb/vc5ph8vN+6YdoJ/e1/i6bTH8IhuU2NniZk8nfZjPg58wYbIZrRixiAZQjrDHYO5wjEGRagewopN9SY9XUxptl9N4cC+KFs2lV8GfD7HYOnCMNdNcqbkejkYNHjlOS+HD5XujxcKwvIlYfbsjvKjx9NqvOuwogjcNs3D2HEaq1aEOXlcQzcKej8OHKLSrLl97rKxsbGOfeawsQHE9HTSHn2KwGcfEdm8oaR5gSAgd+6K64abkepVbn8mwWkto8NqfCIIjjjKOxylRTQjWH5/HTOIrvies9SqDciy6QxLuV2HuOa5nLBuqBO/gYtNzaaX2p3p3M7b/vcJU/pmUkHhVvdN9FV7AfBJYE4p8e9S5gbn4cFDY7EhJ/UYfVNjcFA7zAU913TGWVlohjUn2li8E/ighIhVnDARvgzOI1/3Mtk1sVI3quJBN3RWhNewKLSUUybfq7P6Ob4NLeJ619Wm4k9pp/k8MJet0R0lhGaP4GGUY3jSej3a2KQawzDweQ0iEfCkCahVlPHlzdeZ8Yo/phPwkoUhmjaX6DsgueYoAB+/5y9T/CvO2dM6s9/08/BjaUmf3yyhkIE3X0dRBNIzhITOydmNJK6fVHMzvG1sbKoXtgBoY/M9oicNz+3T0a+bSGTHNgyfD8HpRO7UBaluPdPjaOdzCK9cRnjjOoz8fARVRW7fEXXIcOS27S1dBMgdO4Mogsk+d0qX7qbHThTB6URq1Qbt0AFT8WKDhohlvI5CWmIXaHL3+LJ0RE8aSs8+RNavMRXvGDIirnkuJ8T0jHLkifLjbS5f+qm96SR3YHV4LVsi2/Ebftzf970r3pftgp7LYpPGHl+F5jHeMZaPgp8nvL48PT8hAXBHxFpGbCzKE/+KsyS8gh5KNzop1XfDQjd0ZvrfYV1ko+VjV4RXc7VzHHKMrL1D0cM8532FIKU3mHyGj8+DczmmHecu9x22CGhTbYlEDNasCLNiaYjTpwquA0WxwABkxGgHrdpU7m3cmpVhAgFzlR+Lvg3Sp7+S1M2I3As6m9abMyHZvyfKsSNRmrWo3Nfo8MEoSxeG2LIpUnTpXq++yODhKoOHOWxjFBsbmyrHFgBtbC5BTM/AMXBIXMeGN6zF/95bJfqgGYEokS0biWzZiNKnP+5b7kSQJHNryaiD0qMXkU0bYgdLEurAwXGtO14cQ4bjNykAOoYML/NCUO3Ry7QIVxZqj15xH+uacB3Rvbsw8iruB6gOGorcslXc81wuKL37Etm22VywKCF36ZbaBdlUe9JED2OdoxjrHFVuzMrwGtNOul7Dh1tw005qwz7N3LmpPBxCYmX/p/XyW0qkkiWh5dVaAPwm9G1c4h8UvL+ntNM0k8vv+xoyQrzse7NM8a84GyKbaRZqyjjnmLjWYmOTSvw+nVde8HH0cEnhX9dhy8YIWzZGuHaik1FjU2+2Uci61eaz9k8e1zlxTKNpEstUN64Lm90PBwrWW5kC4LJFIT77KFCqO07OuQI36fVrwtz/SBoZNbw02cbGpmZjn4FsbJJEZNcO/O/MrNAEIbJhLYGP37M0ruu6SQiZWbHjbri5lMGGVXS/n+CSheT/629c/NOvyfvfP+H/5H20UyfLjFd69UXuHFvEkVq1QR08tMzH5M7dEOMsrZY6dkYU4z+NiZlZpD38OGKDhuXGqMNG4po4Je45LieUbj1NfVYB0DW8f/8Lgc8+Qj9ffpN+G5sj0WOW4k/oJ3k47V56KfFnRNcVssgWE2z5EJ9BecJsi+4kapg3j6pMwkaEhaGliY1RRsl4cdaGN5JvwmAGYFFoWdJLtW1sEsUwDGa86i8l/l3KnE+CbFpfea00zudYO6ldOJ/ck6DV8ZI9f0Vs2xLh0w9Li3/FOXlc542Xfei6tf7ZNjY2NskkZQLgihUrePDBB+nZsyf16tVDURQkSarwP1m2ExJtaiaGYRD48lNTphjh1SvQTp8yPbZYJ5P0Hz2JVF4GmtOFa8odOIYMNz1mWUR27yDvL78l+PlHaEcPY+ReQD9zivDyJeT/vz8TmPMpxiVbr4Io4pl2L0rf8hvvy117kHbfjxBkpczHBVHEfefdZfYHjIWQUcfyMZciNWhI+tO/xH3X/SjdeiA1bY7UsjWOEWNI/9lvcN842XTG5uWOIEl47rofnOYyEoxAgNDSheT947+JHtiX4tXZ1FQMi0qajoFDcHCfZzq/TP8Jo9ThdJI70ERsZHqMYY7BCZeGNpObJHR8vOjohIzq2V9z6/el3olQR6i4dcCacMW9IouTZ+SxK7onofXY2CSbfXui7N9rTsT/Zm4Qw6IhW7xYnUaSk1vuKlscL9nzl4dhGMz7MmAq9uhhjZ3bq+cGjY2NzeVB0hU3v9/PPffcwwcffABQaT9KNjZViXboAPrJE6bjQyuX4b7xZtPxYt26pD36E7QjhwlvWINx8SKoKnLb9qi9+iLEIZ4VJ3pwP77X/1Nh9mJo0QIQRVxXX1/i74Ki4LltGtoV4wmvWoF2ssDJUcxuiGPAEKQm5ZdqFSI3b0naj54g8ME7aMeOmF/3xnUYN9yUsPmJIEmo3XqiduuZ0DjJwoiEwQCU5PbPqQzkZi1If+QpAp99SHSfyRvrYADv6y+R/uTPK91ox6b600BsAOwyHV88c6+J1Jib3TcABb3nXva9zvZoxWM1l5oy0lF2xrIV2kltEh4jHgQEHELym+8ng3N6TkLHt5FaUU+qW2HMBT3X0pi5+sUEVmRjk3xWrzAv4J89rbN7Z5ROXcreZE0mVspvAaKR5GbgtWwtwULz8a1aV87m7dEjGieOm3+uq5aH6Nr9h/fLMAz2742yc3uUUNDA7RHo0VuxXX5tbL5n7969/OMf/+Dbb7/l2LFjSJJE27ZtmThxIk888QR16pRMCDEMg9mzZzNjxgw2b95Mbm4uGRkZNGjQgH79+nHDDTcwefLkMufatGkTzz77LIsXL+bEiROoqkqzZs0YMWIEd955J0OGxNcmrDqR9DPLHXfcweeff45hGHg8Hrp3786qVasQBIEuXbrgcrk4dOgQ586dA0AQBPr27YvH40n2UmxsKo3okUOW4jWL8VDwXZFbtkpJL7rA5x9XKP4VElo4H3XQ0DJNUaQGDXFdNzHuNchNm5P22NNc/K/HzB8UjaKdOoncKvEbbcMwwDAQEigpTgTd7yO8ajnh1SvQcwrOj2LdeqgDh6AOGoroqTo3O6tIjZuQ9tBjaKdPEfjkfXNCYDBIaOkiS8K4zeXBYEd/FoXNlY0qKPRVepX5mCiI3OuZzlv+91lfTg+6hmI2k52TEu7/ByCJVZM53FXuFNMko6oQEyw8Ge2InemuCAomW0YCVNvXyuby5eQJa2Xpr77go0FDkcFDVQYMduB0pWbj0GpOx84dUbr3SvxcWkjXHgrpGQL5ebEXoijQb1DlbIScsvh+nTr5g1h4+FCU99/yc/pkSQHxu3khWrWRuOVONw2y7SoUm8olqkeZ71/I6uA6gkYQp+BkoLMfV7pHI4uV+5v52muv8fDDDxOJFLT/cLvdhEIhNm/ezObNm5kxYwbz58+nbdu2RcdMnz6dWbNmFf07IyMDn8/H+fPn2b17N4sWLSpTAPzd737HH/7wh6IENo/HgyAIbN++ne3bt7NixQo2bdqU2idcCST1TnfBggV89tlnANx4442cOHGCFStWFD3+5z//mTVr1nDmzBlWr17NVVddhWEYhEIh3nzzTRYutLCtY2NTndAs9hAyIbZVFtFjR9COHjYXbBiEVy1P3WKsbi8D2oULcU9nhMOEVi0j///+ysX/eoyLP3ucvL/+nuDC+eh+X9zjWkU7eZz8//cXgnM/LxL/APTzOQS/+oL8//cXtBPW+qBVB8T6DSytO7xuFUbUnMNfbSdoBDmuneC4dpKQEarq5VQpTaUmdJU7m4od7hiMW3SX+7gqKNztuYNfpT/NSGUodYUsJH64uTqtn+Efvmf5l/dFDkXNZyNfStgI83nwq7iPvxS3YD7LeUQSshdTRQupWdzHjnYMp5fSI2ZcW7m1pXGbibGz1CtCN3R2RHbxmm8mf83/P/6W/y/e9X/EsejxhMa1uYyJo3jq7Gmdzz8O8n//k0/OueT3tTRbklycNSsiPP9/+ZYFzfKQZYFrbzR3LrzyaidudzVtdf+9uHBwf5SX/uUtJf4VcuiAxnP/8HL2jN2n1KbyWB5YxaNnn+Zj3+cc106Qo5/nuHaCj32f8+jZp1keWFVpa5k7dy73338/iqLwxz/+kZMnT+Lz+fD7/Sxfvpx+/fpx8OBBJk2ahP79PeTSpUuZNWsWoijy97//ndzcXC5evEggEOD06dO89957TJgwodRc//rXv/j973+PYRhMmzaN3bt34/V6uXDhAjk5Obz99tsMHly5ZpupIqlnxpkzZwLQuHFj3n77bdLT08uN7d+/P3PnzuXxxx9n69at3HjjjYTD1bNnjY1NLMQyMuKSGZ9Kovv3WotPYa+2eFoGFBfMLB13/jz5//wfAh++i3b8WMEFmWGgnztL8MvPyP/bn4haKEeOFz0/D+9/nsfIK78MzcjPw/vK8+gx3IqrG0Z+HobfQr+vYBA9Nzdl66kJnNROMcv/Lr+4+Dv+O/8f/Hf+3/nFxd/xtv8DTmtnq3p5VcZ09+20lJpXGNND6cYNzmtMjddQzCYfH+eNC2iUvrnaG93PP70vsDNivT9cyAjxnPc/zA99Z/nY4mIkFGTM9VV68fO0p+gkx3b2HaIOpLPc0fR8mqGRp+eRp+ejG6lvmN9ebku22MDSMVlCJlNcE5nkvN5US4QecldL4x/V499cuaDn8jfvv3jB9yobI1s4ph3nsHaUZeGV/NX7f7zhm03YsDc1bKzRsHH8GV8553Reed5HMJi8Fkw55zTeeNkb17EH92s8/498jh9LzsZ33wEqk25xUVGxxhVXORh9RfIyD2Nh9f1q2FhC0wzeetNHJMbpwec1+ODtxPqm2tiYZXlgFW/mvVXmdRGAhsabeW9VigioaRo//vGPi8p5n3nmGRo1KujlLMsyQ4YM4ZtvvqFx48Zs2bKFTz/9FICVK1cCcOWVV/LUU08VlQcLgkB2djZTpkzhlVdeKTHX+fPn+dWvfgXAj3/8Y2bMmEGHDj9cc9WtW5fbbruNF198MdVPu1JIqgBYWOp7yy234CyjCXxZN/d///vf6dSpE1u2bOH1119P5nJsbCoNpWt3BFf5WSeXovavRjsIUYsXZbGuVhJBt77LKTisl3gYwWCBoHbmdPkx+fn4XnkB/UJqHWpDyxZj5McW9oz8fELL7Czp2sz2yE7+N/9frA6vI8IP38swEVaEV/O/+f9kd8SaYF9bcIsuHk97mOucE8gUSvZ6aSRmc4trEve5pyEJ5m7EFoaWsCGyqcKYKFFe883Eq1vLBv4g8CkHtEOWjinkAffd3Om+hUnO67nDNYU/ZTzD3Z47qStl8YDnbgaq/RAoLYLJyIxzjOFW102mRLLz+gU+CXzBL/J+zy/z/sAv837PM3l/ZE7ga/J0cw668SAKIjc4rzYV21Jqzo889/H7jF8ywjHUdD/Uc4a1c/am8BZL8YX4dD//9r7EUa38TL/1kU284ZtdKeKqTe1h4JDESlfPndVZtyp5SRWLvwsRDMZ/fDAIs17zJ839dshwBz/7TTqjrnBQr76I0wWZWQKDh6v85JfpXHWtq1L7J7doKdG4qflb6kFDHezYFiH3grnX48A+jRPH7SxAm9QS1aPMynvXVOysvHeJ6qmtZlu8eDEHDhwo6vVXFnXr1i3K5ps3bx5QUO4LcPbs2aKswFh88MEH+Hw+0tLS+POf/5yE1VdvklrEfepUgbNpjx4lSzQKT8KhUOkyJlEUufPOO3nmmWd4//33eeihh5K5JBubSkFQVBzDRxGcNzdmrNioMXKnLpWwKnOIdTItxQuZ1uKtIDrMuceWOCa7oeVjwmtXop8tX/wrxPB5CS5agHviFMtzmMHQdcJrVsQO/J7w6pU4x19r2ZXY0DT0i7mg64gZdRDUyumLI6RnILjcGAGTu9cOp+XPY23hlHaGV30ziVC+wB4ixCu+N/lF+k9iGiHURlRBZbxzLFc4RnFSO0WQIB7BQyOxoaWbPd3QWRRaZio2SJBV4TVc4RxtKj5Pz2NteIPptVyKgc4gtX+Zj6mCwlT3rVzjHM/q8FpOa2cREGgmNWGg2p800Vwv5X3R/bzkfYMgJe/o84x8vg4tYHl4NY947qOZnFhpbHn0VLtzm3Ez7wU+Ri/H4bm30oNp7ttR4ujP57Mo2PridCWeH/qOs3rsDPSt0e1si+6gh9ItrnlsLj/ad5Rp1Ubi0IH4RZ+Vy0IMG5V4FlwkYrB+TeJi4rmzOrt2ROnSLTlmJfXqS1x7o8t0SXAqEQSBcROczHg19rmkWXOJzl1l3ptt7byzdVOYJk2r/rna1F7m+xeWm/l3KRoa8/0LmZB2ZcrWU9hG7tixY0WZf2Xh9RZkJx85UlC1NXbsWFRVZcOGDYwcOZL777+fMWPG0KxZ+S1ICrMGhw8fXmEFa20hqQJg8PvtoULltRCPx4PP5+NCOb262rVrB8Du3buTuRwbm0rFccVVaKdPEdlc/s2fkJmF5+4Hq8xooiyUbj1AVcFkCb7aZ0DK1mLE0QNQiKNsOLTS3M0/QHjdGlzX3JgS0czIu4iRbz7bxvB50S/mlmnCUha6N5/QssWEVy//YR5ZRunVF+eI0UhN4u/HZQZBklD7DyK0xFwppNpvAIKSeifD6sh3ocUVin+FBAmxKLyMm1zXx4wtjmEYHNaOsDy8mlPaaQQEGkuNGKYOormc2s9BspEEKSFxal/0ABeMXNPxa8MbTAuA6yObTV9Al8UR7RjdqHiDqK6YxQTnuLjGP6udK1P8K06+kc/zvlf5ZfpTpIupuRAe6hhEW7kNS0MrWB/ZiNfwoSDTUW7PcMcQusid4s7gcQnWNpLKis/XvWyIbOK8fgEZmdZyS7rInRCFgt/uiBFhRXiN6TmWhFbYAmAKCAYNtm+JkHtBR5KhdRuZFq2kSs3+SgWiKDD9fg+vPOe15C5bnNOndKJRA1lO7LXIPa8TSiD7rzib1oeTJgBWN7r3Urn+Jp3PPyr/xWrYWOTuBz1IkoDfZ+3a1Wq8jY1VVgfXWY5PpQB48uRJoCCB7PTp2Ekb/u9bDrVv356XXnqJRx99lGXLlrFsWcE9X7NmzRg3bhx33303w4YNK3Fs4fgtW7ZM5lOotiRVAMzMzCQnJ6foDSikXr16+Hw+9u0ru3dYoTCYk5OTzOXY2FQqgijivuMuwq3bEFq6qGRvOocDtc8AnFdOQLxEIK9qBKcLx8ChhJbGLi8V69YrEAxThGHVTAXQz1k7bxihUIWlv6UIBdHOnkFumnyRJB7B06xRinb6FN7/PIdxMbfkA9EokXWriWxch/u2aai9+lpfgwUcw0cRXrsSIxCIEejEMWJMStdSXQkbYUtZY6vCa7nReY3pcle/HuAN/2x2Rktush3QDrE8vIoeclemeW7DaVE4qalcNKz10sw1yu/PeSkX9PhNiQBOaCcTOj4W34YWVyj+FZJv5LM0vJKr4xQazdBIymay+0YmcyO6oSMgJEW46aJ04pPgHNPxXZUfDGbCRoSPAp+xOryWaHEhNwR1hSwmuq6jt9qD49pJ/BYyB/dE92EYRo0XpqoL0ajB13OCrFwWKiVONWkmcd1EJ+071myhKT1d5JGn0lmxNMSqZWFyzlm/Xqhulec+b+0WsUaMdtK8hcyShSG2b4kUXa7VrScyaJjKkOEOnM6Cc4DLolNzqpydbWwKCRrWlH6r8VbRvr8nHD9+PF9//bWlY++++26uueYa3n//fRYuXMjy5cs5duwYr7/+Oq+//joPP/wwL7zwQiqWXSNIqgDYvn17cnJyOHy4pKNot27dOHz4MAsWLCjzuMWLFwOlMwdtbGoagijiGDYKdcgItGNHMPLywOFAbt4CwVl9U/edV1+PduJYhYYggtuN5+4HLJefWiGemyMhw1qGihFHn8F4ehOaQczIsJR9iaIi1qkTM8wIBvC+8nxp8a84mob/7RmIWXWRW1pzzbSCmFUXzz0P4X3tJQiWIwI6nHjufgCpXv2UraM6c0HPNZX9V0jACJBveEv1wiuLsBHhBd8rHNLKN7TZEt3Oy743eNTzgGlRsSajYk0YUCzEywleVsVbjmqGsBFmTXi96fjloVVc5biiKOstlSRzjsZSIzrIbdkT3R8z1oGDAWrBJkjEiPKi71X2lnPceeMCr/lncocxhXqitRJ8HZ0oGkpyL7trJNGIwdbNEQ7ujxKNQmZdkb79FerVN3fu0TSDN/7jY/eOsvtPnTim8crzPqbd66Zbz8ppd5EqHA6B0Vc4GTnGwbFjGs/+zYvZoofMLAFFTVw0yswScTigjC5OllEdtV/Eat1WpnVbmWDAID9fR1EEMuoIiGLJ5965m8LG9eZ/97t0r9mCtk31x+omcKo3jRs2LGjxVFjaa5Xs7GweffRRHn30UQA2b97M3//+d2bNmsWLL77Itddey9VXF/QkLiwxvlTDqq0k9aquX79+GIbBxo0bS/z9qquuAmDLli28/PLLJR77+OOPee+99xAEgX79+iVzOTY2VYYgisgtWqF064HSvmO1Fv8ABEXBc9+PcIwZh+C+xMxEEFC69STtsZ8iNU5NT6iiqWQZZGs3SHKLVtbmcDgRPGkWDhAQs1LTb02QFdS+5kuq1T79EJTYNzThtasxck1kIuk6wW+/MT1/vMit25L+1M9xDB8Nxb8LTifqsJGkP/VzlHaxHU5rL6m7KVoeWlmh+FfI3uh+VoetlX/UVFrLLREtXP60l9uajm0jt4pjRT9QV8hK6PiKyNHPE8Z8L6+LRh5+I0bmbjVliusm3ELs391b3Tfh+j5ufui7csW/4rwb+MiyqYdbcMXVz7C2sX5NmD/+Oo+33vSzYmmYNSvDzPsyyF9/n8+MV334/bFf14XzQ+WKf4XoOrw1w09eXjVLgYsTURRo0UKmS3fzn6EBQ5LjgquoAn0GJEdI7djp8vkOOF0CDbIlMrPEUuIfQI9eCunp5n77mzWXaNGy9m/O2VQtA53WdBir8VYZMmQIALt27WL//ti/zbHo2bMnM2fOpHv37gAsWrSo6LHBgwvMOZcuXUq+hdZMNZWkCoBjx44F4LvvvitK2wS44447qFevoGfVj370IwYMGMDtt9/OgAEDmDx5cpE78AMPPJDM5djY2FhAUBRcV19Pxq//hOeuB3DddCvu26eT8as/4LnrfqT6DSpnIVZ7wFnMSBREEbX/IPPL6dodMS11DWEdw0ebe86yYrpENrR6uen5ozu3FxiEpBipbj1cN9xEnd/9hfRf/I70n/+WOr/7b9w3Tr5sM/8KqStm4cL8Tmq6kE6GEPszaRgGS8MrTY+7JGzekKYmkyFm0Evpbjp+mMO8a3sXuVNCIl47uU3cx8bCwHr5XTzHVAcaSdk8mfYIjcSyTaLcgpu73XfSX+0DQNSIsjRk7ruiobErupdmUhPT6+mn9DYdW1tZsTTEOzP9ZZaBGgZs3RThpX/7CAbK/8xFowbLl5hLRYuEYc2K5DnhVgdGX+HETAtpt1tg8NDkZT+OHOPAkaCe6HRB7/5Vn5Gp6wZ7d0dYtCDId/ODbN0cJhqt/POcrAhMudMd8/10OGDyHZXramxzeXKlezQS5u6pJCSudJvrjRwvY8aMoWXLlhiGwZNPPlmho28kEikyAwnHqKpyOguut4ub09588814PB68Xi+/+tWvkrD66k1SBcDx48fTqlUrVFUtUe6bmZnJq6++iiRJGIbB+vXree+991i/fn2R+HfPPfdw4403JnM5NjY2cSAoKkq3HjgGD0Pt0x8xM3UZKZdiaBrE6hV3CfrZM5bncQwZUVB6GwtBwDHqCsvjW0HKbohn6j0gVyACyjKeqXcjNSzfBasQwzDQT58yvwDDQLPSEzFBBFlBqlcfqX4DhIqe82WEIsgMLMf5tSyGqgNNlUxeMHI5o581Pe4x7Tg+PXUlqNWJ65wTcAvumHEtpGZkC+Y3P0RB5CbX9QhxZnXmG964jjNDXTHLUglqmuDBY+I1qq40lhrxy/Sf8IjnAQarA+gmd6Gv0ps7XFP4U8av6av2KordHz1IvmF+139TdAuj1OGmYkVERjiGWl1+rSLnnManH8T+bT9xTOObueX3lTqwL0p+nnmxZuP62iUAtmojM+WOikUjl0vgnoc8pGck7xavfgOJux4w5zJeHpOmuHFUcQnwpg1h/veP+bz8rI85nwaZ+1mQGa/4+fOv81j0bbDonrSy6NxV4e4HPWRklP261G8g8vDjaTRtdvlkTtpUHbIoMzXjVlOxUzNuRRZT+7lUFIUXXngBURT54osvGD9+PKtWrSoSAnVdZ8eOHfz1r3+lQ4cObNq0CYBHHnmE2267jc8++4zz588XjZeTk8Ovf/1r1q5dC8CECROKHqtbty5/+tOfAHj22We566672Lv3h7ZY58+f5/XXX+fee+9N6XOuLJL6zjkcDg4cOFDmYzfccAOLFy/mN7/5DYsXLyYaLUjf79ChA0888QQPPfRQMpdiY2NjUy5i3bp4pt+P783/QKScHiyCgOvm25BbpS4jpxClS3fSH3ua4ML5RLZshMIMaklC6dELx6grU2JCYlN9GOMcwZrIupgll+lCGiMcQ0yNGTKsN20KEcJD5Yg+hTdbVZHZ0ECqz489D/Ky7/UKTT6OaMf4df6fGO4YYtp4pafanTu5hbf9H1h2BI5ScWljIjgFJ33V3qwKrzUVP8Sk0FydEQWRzkoHOisVtxjwGj5L43p1HwPVfuzXDrIyhhvwLa5JNJLKzkS8XFi1PGzWv4q1K0Ncda2zTLHIivgXT3xNoN9AlfoNRBZ9W2A0UahZKSr06acy+koH9Rskv1y0fUeloFuFxZfU4YBJt7jpU8XZf8sWhfj0w7J/X/PzDeZ8EiTnrM6kWyo3265zV4Vf/iGDbZsj7NweIRg08HhEevZWaN9JLrN82MYmVQx1FVRIzcp7t8zrFwmJqRm3FsWlmquvvprZs2dz7733smDBAhYsWIDD4SAtLY28vDwixe7hCr+3kUiEd999l3fffReA9PR0BEEgL+8HA7hHHnmkqEVdIU888QRnzpzhv//7v5kxYwYzZswgLS0NWZbJzc0FCsqIawOVuqUwePBg5s+fTzQa5dy5c3g8HtLTU1daZ2NjU7MQJAkxu6F5l15RRGwQ342V0rEz6T9+muB33xDZsqmEu67csQuO0VdUal86qUlTPHfchT5xMvrZgqwtsX59RCv9Cin4ARQbNUY/ecLsAUjZl/fNaXWgrpjFjzz38YLvtXLdRdOFdH7kuY8M0ZxhVrqJMuHiiIgpz/gKGEFWh9eyPLSaU/ppBAQaiw0Z4hjEILUfDiE5favM0Fxuym8yfs6G8Ca+CH5VrjtwlCgLQ0vI1XO5231nkSimGzqHtCPk6fmogkorqQVusaCf3EC1Hx3kdvw670+W1pQlZib0nGIx1jGS9eFNMU1n3ILrsspac1r83DkFB4IgcJvrZrLFBnwbWlRKRGwoZnO982p6qt2SudQaybYt5s0OgkHYvydapumBavH0kGjZanWlVRuZu9rIePN1zufoiCLUz5aKHGarC117yNw21VPlDrbHj0X57KPYGagrl4Vp006md7/KFStlWaBXX5Vefau+RNrGZqhrEAMd/ZjvX8jq4DqCRhCn4GSgsx/j3WMRzfQhSCK33XYbI0aM4LnnnuPrr7/mwIED5ObmUqdOHTp06MCQIUOYNGkSQ4cWXLP8+te/pnfv3nz33Xfs2rWLkydPEggEaNq0KQMHDuS+++4rkf1XnL/85S/ceOONPPfccyxZsoRTp06hKArdu3dnxIgRTJ06tTKfesoQjCTmO0ejUWSLDfxtksO5c+eqegk2NkkhuPhbgl98YipW6dEbz7TE07F1bz7aqZNgGEj1G6TM9KOyCC1bTODTD0zFyl17kHa33X+1upCrX2RpaAUrwmuKShLrCBkMdQxiuDqYdNGaqPes92V2R8t39y5OT6Ub93vu4rR2lhPaScCgkdSQxlLs0nMznNRO8YL3VS4YuWU+Xk+syyOe+8mWKqnf6Pdsj+zkRd9rpmLvdN/CAKUvi0LLWBxeSo7+g9mOikI/tQ9XO8eRKRY4NP/64p/Kfb5l8Y+Mv6CKqb0J3B7Zyau+meWKgC7BxcOeexM2NKlJBIwgv7r4B9MmKYPVAdzhnlL074gRZXtkJ+f0cwiItJCb0U5qY/ft+p7f/vximb3/yuPWqW76DSz9PfDm6/zx13loJhNlBwxWmXJHzS1jr248/Wiupfhbp7roN7DqVdj33/KzZqW573aLVhKPPW0np9iUpH796t+ruqaZV9hJYFVHUtW6xo0bc+uttzJ16lQGDDDvbGljY2NTiGPAEEJLF8V2sZVkHGPGJWVOMS0dsV3t+SFS+w0ktPg79As5FQdKEs6xyXkNbZJDpliH61wTuMY5Hr8RQEDALcRfkjTKMdy0ANhGas2/vC+WckJtLbXkKucVdFU6x7UGgHw9n+e9r1RYbpujn+c573/4WfqTeMTKu2lfEjJvmrMouIxt4R1sim4t9ViYCCvCq9kR2cXjaQ/TQKpPXTGLC1quqbElJFMlxonSVenMz9Kf4NvQYtaFNxYJgU6cDFT7McYxgnpSwSaIYRjsje5nT3QfYSLUETLoo/ZMeaZiZeMSnAxU+5o2zRmhlsyOVASZXqp5Y5nLDZdLsCQAusrJGEtLLyiN3LDWXEbhkOF2RlUyEQSwkjYSClZ9CbauG5Z6QR45pJFzTqNefdt118bGpnaS1BzOnJwcXnjhBQYPHkznzp357//+b44ePZrMKWxsbGo5gstF2n0/QqiTWX6QrOCZeg9ys+aVtq6ahOB04rn/RwgVGbhIMu477kJu0arS1mVjHlEQSRM9eER3QllE3ZUujHGMiBnXQ+7Kp8E5pcQ/gIPaYV70vWZJKLuUhaFlFYp/hZw3LrC0Et2Iw0aEHdHdpuOP6cfLFP+Kk2tc5GXf6+iGzmHN/DWQhsZR7Zjp+ERoJDXkDvcU/lrndzyT/lOeSf8v/lLnt0x231gk/u2O7OVP+X/j376X+Dq0gO9Ci/kk+AW/zfsLr/tm469lhjFXO8dTX6wXM26MYyTN5aaVsKLaQ5du5g2fVBXati8/P2HCdS7SyzFNKM6Q4SrNWthVSVWJJ63qM2DDoQJHaCvUxt6RNjY2NoUkVQCsW7cuhmFgGAZ79uzhmWeeoXXr1owZM4YZM2bg81lrsmxjY3N5IjVqTPqTP8Nx5QQoniKuqqiDhpL+1M9QuvWougXWAKTshqQ/+TOc465ByKjzwwOKgjpwCOlP/gy1R+9KX5eWc47Ivj1ED+7HCFpzfLaJj4nO67jZdUOFPQG3RLdjxOju/kHgUw5ED1meXzM0VoZXm45fFlqJbph0DEiQgBGI+bzj4ZR+hm2RHZZNPXK0GJnPScYhOGgkNaSRlI0q/CDSbI3s4HnfK5zWS7us6+hsiGzin94X8eu15zucLqbxRNqPaCW1KPNxEZGrHFcw0XltJa+s5jN4uIrZfYy+A9UKe8Zl1S1wRm3QsPxbmBGjHdw42WV1mTYxsNpT0e1Ofa8wXTfIz9fJz9PR9dLnclnB9GevELWK3YptbGxsUklSt8ZOnjzJ3LlzmTlzJl9++SXhcBjDMFi8eDGLFy/m0UcfZeLEiUydOpUrrrjC7o1ic9mj515Av5iLoCiI2Q0RZPO75LUdw+9HP58D/mJZJuEw+vkc9IsXkbKT05esNiN60nCOm4DjivEYeRcxdB0xPQNBqfzPWWT7FoKLvkU7WCzDTFVR+/THOWY8Yt2a3XexOiMIAqMcwxmmDmZ+cCHzQt8SicNt1sDgu9Biy73hLui55Bte0/G5xkXyjHwyhTqxgxPEJThTNvaq8DrLx5zQTtCXXslfjAUCRoAZvrfRqViEPaGf5NPgHG53T66klaWeTLEOP0n7MQe0Q6wOryNHP4+MTGu5JUPUAaYNeGxK0iBb4urrnXz5WbDiuIYiE66N/Z3Mbijx9C/T2bk9yrrVYXLP68hKgTnGoKFqSlxwbaBjF4XNG8yVXysKNG+VugzMvIs6y5eEWLMiTH5+gfDnSRMYOFhl6EgHdTILxEdZFmjdVuLAPnOO7OkZAg0b1Wz3cxsbG5uKSOqZWVEUbrjhBm644QYuXLjAe++9x6xZs1i5sqCnis/n46233uKtt96icePG3HnnnUydOpWuXbsmcxk2NtWeyI6thBYvJLp/T9HfBLcHdcBgHKPGIqbVnn508RA9sA/vqy9AuHTdRnTPLqJ7duGaOAXH0NiljTYgiGLF5cApJjjvK4Lzviz9QDhMeNVyIls3k/bgo0hNmlX+4i4jcvQLfBtaFJf4V8iWyHb8eqDI7dYMWgwhqSxiiU/lcV4/z7LQKrZGtuMzAngEF92VrgxzDKKuWFpkVgWVDnI79kT3xTVfReTo5y0f46sGGXWrw+sJUrFQU8ja8HpucF5TqT0bU40gCLSVW9NWbl3VS6lVjL7SiaoKzP0iQKiMj1f7jjK3T3fj9pgTXyRJoFsPhW497I3TymLIcIdpAbDvALXcXo6JcvRwlFdf9JXqK+nzGnw3P8Sq5WHufdhDy9YFt7lDRjg4sM9cy4JBQ1UkyU5QsbGxqb2kbGsmKyuLhx56iIceeoj9+/cza9YsZs+ezYEDBwA4ceIEf/vb3/jb3/5Gr169mD59OrfddhsNGlSu+5+NTWUT+OZLQvO/KvV3w+8jtGgBkc0b8Tz0Y6R61d9xqhBD14nu3UX00EHQNcSseig9eyO6rN8U6nl5eF97sUzxrziBT95HzG6I0r5jvMu2qQTCmzeULf4Vw/B58b72Ehk/fQbBmbqMrMud+aHvCBJKaAwdnYvGRdyYFwAzxQxkZNPlsCpKheXK5bE4tJyPAp+VEA/zjDxOhk6zILSIm1w3MNIxtNRxI9ShKREAZaxnISX6/iSDjeHNpmMjRNke3ckAtW8KV2RTWxg60kHfgSob14U5dCBKJAJZWSJ9B6o0aVq1WXuhkMHGtWF2bo8QCBh40kR69FLo3ktBlm1BCKB5SxGnC8x07+jUNTW3mBdz9TLFv+L4/QavvujjqZ+nk1W34H3s1EVm146Kf4MaNhIZMca+BrGxsandVEqOc9u2bfnd737Hvn37WLZsGQ888ACZmZlF/QI3btzIk08+SfPmdkN/m9pNeP2aMsW/4ugXcvC99iJGNP4sncokvHUT+f/zB3yvvEBo/leEvp1H4MN3yPvDMwQ++wgjam63uJDQkm8hZO4mODj383iWbFNJGIZB6Nt55mIv5hLesDbFK7p8CRgB1oc3JmUs2eLeoUNw0EfpaTq+v9oXRbA2x8rQGj4IfFJu5qCOzgeBT1gVKv0Z66l0o58Sux9mS8naNUpruaWleCjoQ1fVeA1r/Zq9ut3f2cY8TqfA4GEObpvmYdq9Hq6b5Kpy8W/zhjB/fOYiH74bYPvWKAf2aWzdFOGtN/385Td57N9bM67HUs3mDVFT4h/AyqUWnTdMsmxxyJSjdMBvsHRhwbWkKApMu89Dj97lZ4u2aCXx4GNpKctatLGxsakuVHqTgyFDhvDSSy9x6tQpPvzwQ66//npkWcYwDCIRa0KBjU1NwjAMggu+MRWrnzlNZJv5LIyqIrRmJf4Zr6LnnCv9YCRMaOlCfG+8gqGZ670CEFpl3mlUO3oYPTf5TfONUAg94MfQK8eIoLainTiOdsK8q2l4TeW5v15unNbOJlT6W0iGkE5d0Xo5+RjHCEQTlxwyEqMcwyyNHTYifBKcYyr24+AXhI2S1xqCIDDVfSuj1OFlrlFAYKDSj8c8D9NUbGx6XUPVQaZjC0kTPJaPSTZOwVqnf6vxNpc3fr/Oku+C/PN/8/njMxf5nz/k8dG7fk4cN3+dkEy2bAwz+w1/ucJWXp7BK897OXTAFgFXrzCfobx7Z5TzOcl9TzXNYM1K88Li2lVhotECsVBVBabd6+GJn6UxaKhK85YSzZpL9O6r8OCPPfz4J2lkZNi9/2xsbGo/qevOGoNIJEJeXh4XL15EsyAO2NjUVLRDB9DPnjYdH169ArVX9S2r0nLOEfjwnZhx0d07CC3+FueYcTFjjWgUguZ6TxWNf+QQahL62xmhEOE1KwitXIZ+puB9Etwe1P4DUYeORKpbL+E5Ljf0c2ctxWvnyhCSbZJCvD31LmWoOghJsJ6t00xuyjT3bcz0v1PuWiQk7nLfSWPJmsHPhsgm/Ia5/k5+w8+a8DqGOQaXnFuQuNl9A1c6R7MqvJbj2gkMDBqK2QxWB1BPKugfeKPrOl70vRrz9RyqDqKR1NDS8wCoJ1b9eaaL3InD2lFTsQICnZT2cc1zXr/AuvBGLugXkJBpI7ekh9IN2WL2p03NYffOCLNe910ithmcPRNm5bIww0apXD/JhShWnIXl9+mcPaNjGFC/gUhaenzCTSRs8OE7AYwYCWXRKHzwtp+nf5V+WRsYHj9q7X7t1AmduvWSl92Zn2eYyv4rJBAwyL2glzCFadZc5ubb7HOMjY3N5UulngENw2DevHnMnDmTzz77jEAgUPR3ALe79jSRtrG5FO3smZTGVzbhFUvBZIZcaPkSHCPHIkgVXwgasa7Cy0DPy7N8TKkxLpzH+5/nSwm0ht9HaPF3hFYswzP9PpROXRKe67JCsnZTJoj27nuqaCDWQ0DAwPp3rJB6Yl1GWszOK04/tTd1xSzmBb9le3RX0VoEBLrLXRjnHEsruYXlcfdHD1qK/zQwh05yB+pLpcW2OmIG451jyz22s9KBu9y3M9P/brk9DQcofZnimhiXUGCYEGoNw+CAdoiV4TWc0c4iItJcbhq36HgpQx2D+Cb0rSnRuJvcpUxzlYoIGEHe83/E+simEp/HReGlZAjpTHRdR3+1j+V121RvDh2I8sbLPirqbrJsURhRELj+prJ7jJ48obFwfpDNGyNo348jitC1h8KYKx00b2nttmbThjB+v7lz4ulTOvv3RmnX4fI1HbGarxGOxP97Y2NjY2OTGipFANyyZQszZ87knXfe4dSpU8APN/qCIDBy5EimTZvG5MmTK2M5NjZVgtWbQUGo3mJIeIv5fmLGxVy0I4eQW7etODAOAShR0ciIhPG+8kLF2ZmRML43XyH9sZ/YTrUWkJs0B0EgZnrF90jNrYs/NuZIF9PpLndhS3R7XMdniw142HMvaWJiJapt5FY8lHYvF/RczmgFGaINpWwyxTpxjxk1rJXmBQnxnO8//Cz9SVyC9YbvfdRetJZbsTy0inWRjVzU83AIKh3k9oxwDKat1AZBEOLa0Ijlppuve3nNN5N92oESf9+nHWBhaCkDlL7c5p5suYdicTLFOtzovJaPgxX3WE0TPNzkut7S2CEjxHPel8vNMMwz8pnhf5ugEWS4Y4ilsW2qN198EqhQ/CtkycIQg4erNMguuWG4e0eEN1/xcWm3IF2HrZsi7Nga4fbpbnr2UU2vafdOa+eOPTsvbwHQ6iktEk6uAJieIZg2IQFwOKBOZvW+lraxsbGpbFImAJ4+fZrZs2cza9Ystm7dCpTM7mnfvj1Tp05l6tSptGxpvVG2jU1NQ2pqrYG81LR6C02GN99SvG4iXjCslykKGfELBwDh9WvRz5yKHRiNEFzwDZ5p9yY03+WEWLcucscuRHeZE53UwfFnl9nE5grnaLZ5d8bM7BIRceBAEAQaiw0Z4hhIH6UnipC8G98sMZMsMTMpY2XGMc45PYcVodWMdY6Ma84sMZNrXVdxreuqcmMEQcCBSgjzPasqek2CRpBnvS9zQj9ZbsyayHpC/hD3uqchJrCJNMY5AkmQ+DQwhwil+zM3Ehtyn2d6mVmUFfF1cIGp8uIPAp/SWe5oeXyb6smJYxqHD5pPH1u5LMz1k37IAsw5pzHj1dLiX3E0Dd6e4adBtkSTZubKTkNBawJVMHR5Z7RZFQCTXSwtSQL9B6osXWTunNpngIqiFKzCMAz2742yYmmYvbujhMMG6ekCvfqqDBmuJrVU2cbGxqY6k1QBMBgM8vHHHzNr1iy+/fbbot5+hcJfVlYWU6ZMYdq0aQwePLiioWxsah1Sk6ZILVuhHT5kKr66iyGCw4lhwbhHcJhoFC9ZPyUJqvnd/rIIr1pmOjaybTN6fh5iekZCc15OOMdfjXffbmKlfkit2qB07lZJq7o8aSO34g73FN7yv1+uCOjCyUNp99JWbp3wfCEjxO7oPvy6H5fgooPSFpdQdmlfIgxQ+zA/9J3l45aFVzLGMSKlPb00rNXMuYzyX59vg4srFP8K2RzZxtbIDnqqiX2fRjqG0l/pzarwOvZG9xMmTB0hg/5qHzrK7S0LjGEjwvLwalOxOjrLwiu50XVtPEu3qWYc2G8t0+7gJfHLFoUIm9B8NA0WfRvg9unm3LQ9adY+w/H2Grxc8fqSL5gOG+VgzaowoRjtolUVRowuuO7UNIP33/Kzfk3Ja9bcCwaLFoRYuijELXe46dM/sevJmkA4bLBpfZhN6yPk5+moqkC7jjKDhjrIqmt/vm1sLgeSKgA2bNgQr9cL/CD6ybLMVVddxbRp07j++utRE7xZt7GpyTjHX4PvlRdibqPKbdsjt+9YSauKD7lDJyIb1poLdjiRW5gQFOIomYunbPiH6Qy0E8fNH6DraKdO2gKgBeTmLfFMvx/frNco7w5Oatkaz90PxOwRaZM4A9V+ZIsNWBBayJbI9qIebCoK/dQ+XOkYTQOpfkJzBIwgXwa+ZlV4LUF+cI1UURmg9uVa51UJlxIXp7HUiC5yR3ZEd1s67qx+jhAhnFgvAzaDYRhELQqA66ObGCuXzkrUDM20eAawNLwiYQEQwC26GeMcwRhGJDzWvugB02YtUCBk2gJg7SBisRdctFi8phmsW21+s3HD2ijhkI8RYxy0aVfxbU7PPgrrVpvP0O3Z+/It/40HUUy+AFivvsTdD3h44z++ckVAVYW77vcUlZF/8n6glPhXHC0K78z043ILdO5ae9/jg/ujzHzVR35+yffl8CGN7+aFGHe1kyuuclzWRjc2NpcDSRUA8/N/KPHr3bs306ZN4/bbb6dBgwbJnMbGpsaidOiM+9ap+N+bXa6BhtSyNe7p91d7QwTH0BGmBUC17wAEp4mb7DgEwIR7JVqdM44y5csdpXNXMv7r14RWLiO8dhVG3kUQBKSWrXEMGY7Ss48t/gEntVMc1Y6jo5MtNqC11DIlF+Kt5ZbcL99Fvp5Pjn4eAZGGUgOccfTDuxS/7udf3pc4rp8o9ViYMMvCK9kT3ccTaT8iQ0xPeL5Cprpv5W/5/+a8ccHScbqhJ79O7Xvi6QF4SvuhF6lu6BzUDnNRzyNPzyPPMG94tDu6F83Q4nJsThU+w5fSeJvqS6bFPmzF+7b5fAaBgLXv0rYtEbZtiTDmSgcTrneWex7t2FmmfgORc2dj/6637yjTsFH1+T7VBAw9NSfXdh0UnvxZOou/DbF+Tbhob1FRoW9/lRFjHGQ3LHivzpzSWLU8tshrGDDn0wCdusi1UgA7djTKf573EinnpTAM+ObLIIIAV1yVmk0xm9SSnp68ayqb2k1SBcDGjRtzxx13MH36dLp27ZrMoW1sag1q3wFIzVoQWr6Y8Ia1ECzYwpSat0QdPAy1T38EuVINuuNCbtkadcjwAjfgChDr1cc5boKpMQVJQsiqi3HhvOl1iPXjz1YSBAGxfnbFBiCXINVP3GXTKkYkghHwI6gqgjP5JZSVgZiZhWvCdbgmXIehaSAI1V7kriz2RPYxJ/g1B7RDJf7eSGzIeOfYlDmipovppCdRhAN4K/BBmeJfcc7oZ5nhf5vp7tvwGQXlwXWEjIRuutLFdB71PMgfvH81fUya4LEseubr+WyN7CDf8OIUHHSSO9JQKnuTM57nkyZ40A2dxaFlLAovJUe3JmgWYmAQJYpE9REsrBquxGPQYlM96dJdweksutyJSd8BP1QLiQloMd/ND5GWLjBiTNmfJVEUmHqvmxf/6a1wbXUyBW65s2KDHpvSuNNSJ6TVbyBx061urpvk4nxOgYCbVVfE4Sg550oT4l8hp0/qHNyvxcwcrYl89mGgXPGvOPPmBuk3UCUzy74+s7GprST1DHf06FFE+4bOxiYmUsNGuCfdguvGyRAKgSwjKDWv7MB142QERSW05LsyM+mk5i3xTL8PMc28yOAYNJTgV1+YipU7d0Osk2l67LJQBw4mOOdTc/N16IRYt25C81khenA/oaWLiGzbXJQxKjVvWZA116d/jc2aq6nrTgXrwhuZ6X+nzJ58p/TTzPC/zRntLNe4xic0T9gIsy68kU2RrXgNLy7BRRe5I4PUATGdZ81yVjvHlsg2U7G7o3v5Zd4fiv7dTGrCCHUoA9V+FWathYwQYSOCW3CVisuW69NL6c6myFZTaxik9jfdx86n+/ko8BnrI5tK9fXrJHfgZteNNJKyS/xdEAQEwEruUjepM2/632JDZLOFo0qjoqBSvVqutJXb4MBBqFhZeEV0lbukeEU2lYXDITBomINFC2K/91l1Bbr3+uF6yJMmkJklkHshvnLS+V+HGDzMgaKWLUY1bSbzyFPpfPSun0MHSpfsd+oqc/OtblsQiYNkuwCXhaoKNGpc/m/GkUPW+k8eORStdQLgyeMaB/eba0eh67BqeYirrq2Zm802NjaxSeoZzhb/bGysIYgiuKrPj6x25jTRg/shEoH0DOSWrRA9HgSl7BtJQRRxXTcRx/BRhFYtRztyCCMaRaxbD0f/QUht2lnOglEHDSW46FsIxO4V5RxzpaWxy5xvwBBCi7/DyI9RXicIOMaMS3g+swQXfE3w6zml/q4dPYz/vcPIG9biuesBc+YqNtWS09oZZvnfjenK+1VoPi3k5nRX4hNEdkX28Kb/LbyXlFTuju5lTvAbprgmMtgxIK6xi7M2sqGop6BVjmkneDvwAZsiW7nfM72E47BmaKyPbGJJaAWHtMMAyMj0Vnow0jGMVnKLotgrHKPZEtke8zV14GCEY6iptXl1H//0vsApvexM4V3RPfzD+yyPpz1MU6lJiccERIwYaynOem1zwuIfQB+1V7UrY3MJTgaqfVkSXmEqfrjDNourTVx1rZMTxzT27CpfkHG7Be5+IA1Z/uGzKwgCg4Y6+HqOyfTBSwj4DTZvjNBvYPmCeOMmEo8+lc7xY1F2bY8SCBh4PAVCZP0G9oZVvJw5U/UtUzRr+h+HD0WJhI1yBeOayL691l6EfXssvmg2NjY1itq1xWFjYxMX0ePHCM75hOjespvoS81b4hg6AqV3vzKzt8TMLFxXJadZuyBJCIqCEYgRKIpJEb9EtxvPfQ/j+8/zGD5vOYsScN10K0q7DgnPZ4bQmpVlin/Fie7djf/dmXim329qTCMYILJ3D4bfh+B0IbfvgOhOnhGDjXUWh5abdoldGFoclwC4L7qfl3yvlWtGESHCW4H3EQWRgWo/y+MX54Kem9DxADuiu3g38BFT3bcCBRl///G9ye7o3hJxUaKsjWxgbWQDE53XMdZZYJzRSm4R0+lYReV+z3Tqilmm1vR+4JNyxb9C/EaAV30z+XX6fxVlFRqGEVOIvJQ14fWW4stjpGpO3CwP3dC5oOcSRSNTzMAhJGej4RrnVeyO7uW0frbCuKud42gsNUrKnIVohsZh7Sg+w4dTcNJSaoEq1LzM+5qKLAvc85CHb78JsmJpGJ/3h80CUSwoE77mBmeRcUNxhgxXWbU8FHcW4PFjGv0Gxo5r2kymaTP71ihZhOPTbJNK3foix46aN2PauinK/xzO456H0mjStHaIv+GQte+NGcdtGxubmov9K2dTq9DOnCa0cinRndsxgkEEjwelR28cA4cgZpq72bvciB7Yh/eVF6ioOYh29DD+d2chr11d4NZqxtAjTopMImKh6wS+/Ya0qfcmPKfctDnpT/wXwcXfEl63+odGRYKA0rU7jpFjkVu3TXgeMxiaRvCbL03FRrZuJnr8KHLT5uWPFwgQ+PqLgucVKlZ+JSuoffrhvPp6SyXaNsnBMAzWWhB79kT3c0HPJUvMtDTHu/6PTTnRfuD/lF5K94SEHiVJlxRrwuu52jGOelJdZvjeLiX+XconwS+oI2bQT+0NFDgd1xfrMT+4kO3RnUVZiTISvZWejHOOMS0uXdBz2WgyI++sfo7t0V1FQm08GXhBEr9jnui8luZys7iO9eo+FoeWsTy8ush0pPB1G+MYEfe4hXhEN4+nPcyb/rfYE91f6nEVhWuc4xnjKO2EHC9RI8rC0BKWhFZwwcgt+rtbcDFYHcB4xxW4xeqTiV+bkWWB8de4GDvOyZ7dUfLzdBRFoE07ucISW7dH5IFH0njlBS8XzlsXAQ099aWoNqWpn131WXT9B6ls2WjeRRog94LBy896efynadStV/NFwIw61t6HjIyqf99sbGxShy0A2tQKDMMgNP9rgvPnluhFZ3jzCc3/itB383HffCtq/0FVuMrqhxEM4pvxaoXiX3Gi+/fge+tNPPc8mLLyssDSxaZjo5s3ok/yInrSEp5XzKqL+8bJuK6+Ae3sGdA1xKy6lSKOGZpGZMdWwqtXop04Zk4A/Z7wquXIN91a5mO634f3xX+jnzxe+sFohPCalUT37yXtR08k3EvRxhpBQgQsij1WBcC90f0xM9d+WE+QNeH1DHcMsbSm4rSRW5su76wIA4OV4TV0V7qwJbrd1DFzgl/TR+lZlH3XVm5N27TWXNTzOKufQ0CgkdjQcr/DjeEtlsqa14U3FgmAejlO76kiS8jkOtcEBqh94zr+rHaOZ70vl3JSjqKxNrKB9ZFN3OGeknCmaIaYwWNpD3M0eozV4XWcN3KRkWkjt2SA0i+pYlzEiPCy7w12RfeUesxvBPg2tJjtkV08nvZQ0g1xbMpHVgS6dLOWfZndSOKpX2SwZkWIBd8EzXQJKaKsrEIb61gxcgHoavE9TgUdO8s0biJy8oS187HPa/DNl0Fum1bzKyW69lBQlAARkzpo737Vq3+sjTny8/OregmWsF2Lqw5bALSpFYQWfUtwXgVZU1oU/3uzwelE7d6r0tZV3QlvWFt+2Ws5RHduQztyCLll66Svx9A0OH/O0jH6mdOIrRMXAAsRVBW5aWJZLlbQzufge+0l9NMn4zv+ZPmOq4EP3i5b/CuGnnMO31tvkv6jJ+Ka3yY+5Dh+fhWs3UztipE5dym7o3sTEgB7Kt1JF9LIN6ydU8rilH6avLD5i9lzeg57ovvopJQs068jZlBHzIh7HYVZcGbJLxZvlGGMlEzqClkMcvRHRKSZ1IQucifTpiaXEjbCPO97pZT4Vxwdndn+98gSMumgtIt32UU0l5vFlVEYMAKsCa9nfXgTeUY+DlQ6Ku0Zpg4m+xJH5o8DX5Qp/hXnlH6a1/2zeTztYctrsalcXC6BkWOddO6q8L9/Mnd+UBTo3b/qhajaQHodgWDQ/HktLb3qe8OLosBdD3h48V9eyyXkmzdEuH6Sjiet6p9HIrjdIv0GqqxcFnuzP6OOQI/e9vfFxqY2U7PPaDY2gO7zmi6ZDHz2EUYlZ2VUZ8Ib1sZ33MplSV5J/GinyhfAqju6Nx/fi/+OW/wDynRfBtByzhHZtsXUENqBfUSPHYl/DTaWUQSZllL5pduX4hbcpVxmYxE2rDXysRp/KYogM9F1XUJjFCIgcEyrWLy+lGNa8s8FDsFaJkRlOu92VTpxtXMcVzmvoJvSJW7xD2BteAPn9JyYcQYG34S+jXueRNkZ2cNv8v7CB4FPOaAd4pyew3H9JN+FlvCH/P/hi8BXRcKrV/exMrza1Lh7o/s5HLXPgTWF7EZSCafgihgy3IHbHd934+wZjaULQ8ybG2TZ4hAXzl/e149ea/shHDtivvdeKqlXX+Kxn6YzeLi183M0Wn2eQ6JcO9FFi1YVZ8I6nHDX/R4UxS4BtrGpzdgZgDY1nvC61RA1l9du5F4gunMbStceKV5VzcC4aL7UtDjRE8eSvJICDJPvY3GiJ09SU31wQwsXoF+IfdNdEVJ2wzL/HtmwtlxxsCzC69cgN2sRO9AmaQxXh3A48J6p2EFq/xLOuGZIF61lxqYLiZdjDFD7EjJCfBD41LIBRnEaS404p5+3eFTyM+46yO35knmm4zvK7Yv+XxStiw4e3PgwV9s4LIFszUtZHl5lOnZ3dC/ntBzqS/WSNr8ZDkQP8XIFhjYA34S+RUTkGtd41kc2mup/Wciq8FpayuWfAwNGkLXh9eyJ7iNshEkX0+mn9Kaj3D4h8dUmPm65040338vB/eW/x917KVx9g/WexefOanzyfoDdO0u6oX72YYCuPRQmTnZRJ/Pye88jUWvn2Eik+vRezMgQuekWN2tXholaMLlN9nM4n6Oxfk2EnHM6sgwtWkn07KPicKRWdHM4BB78cRpffhZg7apwqc4/7TrIXH+Tq9YYn9jY2JSPLQDa1Hi0gwcsxUcPHrAFwEKUONP8U3RNp0et77Tq+Ra3pKsJRiRCeO3KhMdRB5YtAui55Zfylbkei/E2idNP7c3y8CoOaocrjMsSMrnSMcry+H2UnnwR/Mp0fF+1l+U5ymK4YwhdlU4sC61mc2QrfiOAA5ULxgU0E6KgiMhgdQBntLMc1cxvNlxa/pkM2kitaCo25rgeO0tXQWGg2r/o3/GUAHeQ27E5ui2meDpYHUBTqbHl8cvjlGauV2QhJ/XTlS4AfhT4zJSg93VoAUMcAy0LyDkVxK8MreGjwGcECZX4++rwOhqJDbnXMzXprsU2FeN0CjzwaBrLl4RYuTRMzrkfvjONm4oMHeFgwGAVUbQmrJw5rfH8/3lLuBQXYhiwbXOEY0eiPPpUeoXGJVYwDIPdO6OsWBLiwL4okQhkZIr07a8waKgjafMkSmamyLmz5jd2qqNImplVNc8hGDT48B0/mzdESuzNrloOn38c4KprXAwdqaasvzYUiICTpriZcJ2LHVsj5OXpqKpA+w4y2Y1s4c/G5nLBFgBtajxWs8YMK1t/tRy5bTvCZ05ZPk5qYK0U0SyCZP0CRHTVTPdG7dQJDL+FLuZlILfviFReL0ar4q5s93ypbGRB5iHPvbzie5N9WtkbGdliAx723BuXQUEDqT7d5C5si+6IGdtQzKaT3CFmnFnqinW53jWB610Tiv42NziPucHY2XRD1IFkiZkMUQeyLrLR1Hx1hAy6yp3jXm95CILAFPcknvW+TJSKfzsmua5L2MCiidSI/o4+vOl7izBl/7b1V/pwi2tSQvMkSmUXiB2OHuWwdtRUrIHB8tAqZKz9nojlxC8LreLdwIflHndKP82/vC/yk7Qf00Cqb2lOm8RQFIFRY52MGO3g7BmdYMDA7RGo30CMS0gxDIPZr/vKFP+Kk3vB4L3Zfh78ceL9hyNhg7fe9LNtS8nv+4UcnQVfh1j8bYjb73LTvWfVGzN07iazdKG5VhEeDzRrUf1EpT4DVOZ9ac7JJLuhmJTnEA4bvPKcl8OHyt7ACAbg0w8DBIMGV1xlPWPVKi6XQN8BVf95srGxqRqq39aMjY1FxMwsi/GZqVlIDcQxZHhcx5WXdZYoomz9QisVZiSVglk7tnKQmrXAPfWecm9y5NZtLY1nNd4mOXhEN4+lPcSPPPfRQ+5KlpBJplCHDnJbprtv5xfpP0lIVLjdPZn6YsWZWm7Bzb2eqSkvY7zKcQVD1Yqd2Hsq3bnZdQMA7eW2tJFamRr7SucYJMHc+SNoBFkaWsE/8p/jt3l/5k95/8u7/o84rpWd5ddWbs3DnnvxCGU7CMtITHZNLGWgEk8JcB0hkx5KN36b8QuucY4jW2yAAwfpQjp9lF48kfYw09y3IQvJ3b+1mr3WSCy79UCq2Be1lum/N7qflpK1lgatyij/zdfz+TDwacxjvYaPD0zE2aQGURRo2EiiZWuZBtlS3FlUB/ZpnDhuLjts7+4op04m1h/OMAzenV1a/CtOJAKzXvOzf1/Vb17nXTSfORcMWepCUmkMGqKimtS+RoxxJCUjb+H8YLniX3G+nhPkxHFrnynDMAgGDAIBI+XGUzY2NrUDOwPQpsaj9htIeNVyc8GiiNq7X2oXVIOQGjdFHTKC8Iol5o9p3hK5fceUrEeQFRBFsGDUIrepmcKVkFEnruPEevVRBw/HMWQ4QgVXsXLb9gUdnUMmdrodDtQ+/WPH2aQEURDponSii9Ip6WNniOn8JO1RPgh8yqbI1lKlpR3l9kxxTaShRYOReBAFkVtdN9FN6czi0PIS7qxtpdYMdwyhj9KzSIgUBIH7PdN51vsfTlRQgjtKHc5IdaipNeyPHuQV35t4DV+Jv58Kn2FZeCXD1SFMdt1YSgztqLTnDxm/Yn14Exsim/EaPpw46Kx0ZIg6oMwMzXhuxtJFD1DgXjzBOY4JznGWx4iHoeogDgfMZdh1ljtWevlvpJxsyIriuytdyBAyTDk5F5adX8rK8NqYmZ+F7Iju4qx2zs4CrMFsWm/NCGnT+jBXXRt/1u/RwxqbN8T+bOs6fPV5gEefSrxPayJs32JehNSicHBflLYdqld1QUYdkan3enjzFR9aBU9n4BCVgUMSz5KLRg1WmXDfLWTFkhA331b2ZlNxfF6dlcvCrFoeKnI3rpMpMGCwypDhDtIz7BwfGxubsrEFQJsaj9SyNVLLVmiHD8WMVXr1RayTmfI11SRcN94MAoSXxxYBxYaN8Nz9AEIcmS1mUXr3JbLenDuxkFUXqUHlZqIkC6l+A9OfWyj47Dqvuhaxbr2Yr394w1r8H70LoVCFcYW4rr4BwVmy7MQIBIjs3Iaen4fgcCC364hUP/k91mxST7qYzj2eqeTqF9kS2YbP8OHESWelk2Vn4UQRBIHuSle6K10JGEECRgAnznJLZ9PFdJ5Kf4RFoWUsD63igpFb9Fg7qQ2jHMPpqXQzlaVxTDvB895XCFP+zdjS8AoEBKa4J5Z6zCE4GOIYyBDHwNhPFOLKHPEbAcvHJIN+ah8WhBZxRj9bYZyIyHjn2JSv52j0GEvCK9ga2Y7P8Ft2V84U6iAJEje6rmGm/52Y8Vc4RlFHzCj19x2RXZbm3RHdzUhbAKyx5OdbE+3z8xLLuFqx1LwwdOiAxonjWpWaNFjtoLNzR6TaCYAAnbsq/OjxNOZ+EWT/npJPKjOroKw8Wf34jhzSLH2utm2JcPNtFcecOKbxygveUp+/i7kG878KsWJpmPse9tC8pX2bb2NjUxr7zGBT4xEEAc/Ue/E+/88KHVWl5i1xT7qlEldWMxBEEffEKTgGDye0cimRHVsx8r0lnJWFjDo4Bg3FMXw0Qop77jnGjjctADqvvCqla0k1jhFj8M96PXagKOIcN8GUABfeuA7/2zPMLUAQcF5zA46hI4r+ZIRCBL78jPDaVVxqEyd37Izr+puQGtrN7msimWIdRjjMZcpVBi7BiUuI3e/IKTi5ynkF4xxjOKufI2SEyRDTyRStZdF+GphTofhXyJLwcoY7Bids6hBPBqBH8CQ0Z7yogsKPPPfxnO8/nNPL/h0VEZnqvpV2cpuUrcMwDL4MfsPXoQUl/h7C3GZGIf3VPkCBK7Xf8PNR4HOMctyrRqhDudZZ9m9JEHO9woriDWvxNtULs6WhhSTq3Hr0sDVF7cihaI1yab14ofqWpLZsLfPwY2mcOaVx+JCGphnUrSfSroNs2TimIvx+a69BIEZ8fp5epvhXHJ/X4NUXfTz5s+QZ1djY2NQebAHQplYgZmaR9thPCH71BeGN60r0VxNcbtQBg3GOuxrB4ajCVVZvpEaNcU+cAhOnAAUusnpeHoKqIjbIjsugIx6MnPJF3EvRzp1L4UpSj9KjN44RowktWVh+kCDgnnIHUnZsMcIIhfB/9J6puQWPB8+Pn0YuJioawSDel59FO1q2K2109068z/0dz0OPITdtbmoeG5tkIQpi3KXKZ7SzJUqOY7E0tIIp7sSMNgRBQESM6ehbHDXJvf2sUF+qx3+lPc7S8EqWhVYWZVsqyPRVezPaMZymUpOUruG70OJS4p9V6olZ9FC6Ff17lGM4neQOLA2tZGNh+bbgoKvcmeGOIbSRW5U7llVBNq2KBFyb5NChk8KGtebLzdt3Suz7qllsIWg1vqqpW7/6i0/ZjaSUOuC63NbERKer4vjlS0KmMk99XoOli0JcN7FmGuXZ2NikDlsAtKk1iOkZuKfcgfPaiUT374VgAMHjQW7XscJeafFiGEZBlpwkp7QktqoQM7MsG6wkg+DC+aZjw8uX4Bp3NYJcM09lgiDgvG4SYv1sggvnY1w4X+JxqWlznBOuQ+nUxdR44Y3rCuzkTGD4fHDxIhQTAANffFyu+Fd0XCCA781XyPj5bytNFLaxSZT90YOW4vdaNJ0oj/KyzsqPr1rcopvxzrFc6RhNnpGPjka6kI4ipL6ML2gEmRs0f/4vC7fg4n7P3aUMYRpJDZnsvpHJ3GhpvF5Kd3ZH95qKlZDornS1NL5N9aJnH4XPPxbw+2J/E+vVF+nYObFrj7r1RM6dNb9BULde1V5rCoI1Y48WrexrhJYtJTxpQkxn6UK69Sj/XKvrBquXmy8bX7syzITrnMhyZfu229jYVGdq5l2zjU0FiG43aveeKRtfyzlHePkSwuvXYPi8IAhILVvjGDwMpVdfWxRJAMMw0A7uN39AKEj0xHGUFi1Tt6gUIwgCjiHDUQcNJbpvD/q5syAKSE2bIzVrYakHTXSPtX5VkT07kdu2A0D3eQmvX2PqOOPCeSLbtqD27G1pPhubqiIch4lEohiGYVkAvNScpKoQBZFMIT6jonhZF95oudS3EAGBbnIXbnRdS0Mpeb1K+6t9+Dz4FQETvRn7KD3JKMMMxqbmoCgCk25xMft1f4Vxogg33eJKuFS0/yCVPbvMlQHXyRTokGDGYaKIYs3LQqxqZEVg0BCVb+eZO7cNGV5+wkJ+nmGpn6Dfb5B7Qad+A/u+xMbG5gdsAdDGxgLhLRsL+qsV74RsGGiHDuA/dABp5TI89zyE6I7t4GVTBlrU2vYyoJ8+BTVYACxEEEWUDp2gQ/xOsIZJ04+y4iNbN1vq8B3ZuNYWAG1qDFbFrMoWvwq5nHvIHdKOWIrvILWjp9odByodlLbUFesmfU1Owcld7tt52fdGhaXc2WIDbnLdkPT5bSqfXn1UDB0+fMdfpo+Wyy1w2zQ3HTpby4oN+HXWrg6zdlWYnLM6kiTQrIVEWrqA14SoM2K0A0mq2kwuywKgYWeeAYwZ72T3zijHjlb84l1xlYOmzcu/NY+jrSyG+QRTGxubywRbALSxMUn0wD78s98AvfxfU+3QAfwzXsHz4I9rZVlwqomnab59dfMDQlqapXixWLyRd9HSsfrF2PF63kW0I4cxtChiZl2kFi2T4qpnY2OVLkpHPIIbn1FxZk8hA9S+KV5R2WQKmVUybyqJGlF2RHeTo+UgChKtpOa0kJqXOhdohrXUokyxDiMrwdSmq9KZRz0P8F7gI05f4pIsUOBqfZvrJtJEu/9fbaF3P5VOXRXWrQ6zc1uEQMDA7RHo3lOhdz+1XPOPkyc0dmwtiHe5BLr2UGjUWOLI4Sivv+S7ROgz2Lu7YNNNkioW1gYMVhk+uup7WGc3lDh+zPz3tEFD+zoYCsxiHvyxh/feCrBtc+nscocDrpzgZOTYit/jtHQBpxOCJveJFBXq2CYgNjY2l2ALgDY2Jgl8PadC8a+Q6P69RHfvROls9wKyiiBZPyWJtiNtEWrPPkRMlvECKD37FPuHtT6Zglr+hap2+hTBr+cQ2b6lxHdGzG6IY+RY1AGDbSHQplJRBIUR6lC+CsXuMZcupNNX7ZXwnIIgkCVkFplpmKG+VC/heasLuqHzXWgx34WWkGfkl3isudSU653X0FnpUPS3+qK1514vBRl/5dFBaccz8n+xJ7qP3dF9hI0QGWIGfZSeteo9s/kBl0tg+CgHw0fFFt7OntH48J0A+/eWzKL/6osgLVtJnD6lVSjaaFqBuBMMGCUS8bMbiYwY7WDgELVa/Gb2H6xw/ANzAmDT5hLZDe3S00JcbpG77vdw9rTGutVhzufoiBK0aCXTt78a0/wDQJYF+g1UWbbYXB/APv1UVLXqPzc2NvEyatQoFi9ezG9/+1t+9atf8fe//53Zs2dz4MABsrKymDBhAn/84x9p3LgxAPv27eMvf/kL8+fP5+zZs7Rs2ZL777+fp556CvGSxJxIJMLLL7/Mu+++y/bt2/F6vWRlZZGdnc3gwYOZPHky48aNA+CNN97gnnvuoX79+pw4cQJFKTsD/PDhw7Rp0wZd11m/fj19+vQpM66qsQVAGxsTaGdOoR3YZzo+tGqZLQDGgSCKoCglXJxjIWVVvlFJdUXu1AWxfoOCPoImYqUGPziqyu3aW5urnPjooQN4X32hzC1q/cxpAh+8jXb8GK6Jk6vFDY3N5cNVzis4oh1je3RnuTFOHDzguQuHkJxsm6GOQcwJfm0qtrXYMqn966oSwzB4y/8+qyPrynz8qHacF32vMt19e5HYOkDty9ehBab6JgoIDFT7JXPJsecUBDoq7emoWDtX2tRuzpzSeP6f3nJNHg4fMieYefMNptzhIjNLJBIp6PnXtJlUrX4nPR7z2WTl3B9f9jRoKDHh+videYeNcrBmZZhwDA1QVmDEmKrPGrWpmUSjOgvn+1m3OkgwaOB0CvQb6GT0lW5kufKzSiORCOPGjWPRokU4nU4ATpw4wWuvvcaSJUtYuXIle/fuZcKECeTm5lKnTh3C4TB79uzhpz/9KceOHeOf//xnsecXZfz48SxcuLDob5mZmeTm5nL27Fm2b9/Ozp07iwTAW265hSeeeIJz587x+eefc9NNN5W5ztdffx1d1+ndu3e1Ff8A7LxgGxsTaMeOpjTepgBD1y2JfwB6Ts4P/38xl+C8ueQ/+//I+9uf8b74L0LLl2CYdMat6QiiiHvqveCs+OJSyKqLe/LtJf4mN2+J1NxkL0VRRB04pNSf9YAf3xv/iVmfEl6xhPCalebmsrFJEpIg8YDnLiY4riRNKFmuKSDQRe7EU+mP0lpOXk/RTlKH2EHf01xulrR5q5oV4dXlin+F6OjM8r9Djlbgft5Aqk9vpYep8XvbmXc1Am++zsL5QV570ctL//byzkwfe3ZF0PWq9rtODoZh8NYMv2mH11isXxOhQyeFrt0VmjWXq5X4B7Biqfk+w4cPauTn2S1akk39BhJ33e+psGhDVmDaPR4aNrIzMG2ss2p5gKcfPcvnH/s4cVzjfI7OieMan3/s4+lHz7JqeeXfU73wwgvs2rWLOXPm4PP58Hq9fPrpp6Snp7N3715+85vfcMsttzBs2DD2799Pbm4uubm5PPTQQwD8+9//ZufOHzZ/33nnHRYuXIjL5WLGjBn4/X4uXLhAMBjk2LFjvPbaawwZ8sN9jtvt5o477gDgtddeK3ONuq7z5ptvAnDfffel6JVIDnYGoE2twNB1oju2Ed6yEcPnRXA4kTt3Re3VB8FiaWPZE1i8uKuhfekMXS9wos05B6KI1Kw5gqKg515AUFSkJs0QHCncUYynB+D3NxLBJQsJzvmkRMmpfrqgJDv49Re4b7/rssjKlJs2I/2RJ/F//F5pR2VBQO7SHfekKYh1Mksd67rxZrwv/huiFYuwzvHXIGaUNkmIrPveGdsEoUUL7FJgm0pHEiSucY1nnHMsu6K7ydUvoggK7aQ2KRGUNkY3m47dG92HYRg1/jthGAYLQ0tMxUbRWBZeyQ2uawC4zT2Z894LFRqCtJJacrv75qSs1SY1GIbBogUhvv4yiHaJt9T6NREaNxWZfp8n6e6khmFw+GBBieWF8zqSBC1bywwYrJKekfych0MHNI7HMHawwuGD5o24qoIjh80/V8OAI4eidO2RhGtwmxJ06KzwxH+ls2hBiI3rw0WXbJIMvfoojBrrpHFTW/yzsc6q5QHeejOv3Mc1jaLHBw2NP5PVKrm5uSxatIiRI0cW/e2GG27gpz/9Kb/5zW944YUX6NChA5988gmyXCBvZWRk8Pzzz7NgwQL27dvHhx9+yK9//WsAVq4sSEKYNm0a06ZNKxpTFEWaNm3KPffcU2oNDzzwAC+++CLffPMNx48fp2nTpiUenz9/PkeOHMHlcnH77beXOr46YQuANjWe6JFD+Ge/gX4+p8TfI1s2EvziE1yTb0ft3jOhOcT61sqyxHo1q4zLMAzCK5YSXLQA48L58gMdDtS+A3COHV+mgJQoghTHBYsoElq2mODnH5UbYgQC+N78D2kPPIrctvaXb0mNm5D+yJNoJ44T2b0DIxhA8KShdOuJVLd8kUNu2RrPvQ/hn/Uahr8MswRBwDn+GhxjxpV5fHjdKtNr1M+eQTt8ELlVG9PH2NgkC0WQ6a6kfkNgXXij6diT+mmO6ydpJjVJ4YpSz3HtBKf0M6bj14Y3FAmALsHJY2kPMT+4kGXhVeQX6x2YIaQzVB3Elc7RqIItKlRnFnwd4psvy88EP3lc54X/8/LYT9PJTJJJQd5FnVmv+zi4v6RItWNblHlzg4wZ52Dc1c6kCuybN5rrxWYWTaNabwJcKubG4tRJna7mknptLNKwkcQtd7q54SYX584VfObr1RNxue3iPpv4iEZ13p1VvvhXnHdn5dFvoKPSyoEHDx5cQvwr5IorruA3v/kNAE8//XSR+FeIKIqMHj2affv2sXXr1qK/Z2RkAHDq1CnTa+jVqxf9+/dn7dq1vPnmm/zqV78q8XhhZuBNN91EZmam6XGrAvssYVOjiR47ivelf5cS/wox/D78M18lvHVTXOMbkTDhtasIrVsDLvM7HY4Bg+OaryowDIPApx8Q+OT9isU/gFCI8Iql5P/rb2hnzJ80Ta8lan33W/d5CXz5aexATcP/8fvxOQ3XUKQmTVH7DUKsnw26QXTvbvSLuRUeo7TvSMav/ojrpluR27ZHzG6E1LwljjHjyPjF73FecVW5Nyd6rM9PgvE25jAMgzw9n3NaDkHDpF2gTdIxDKOU+UUsLurW3LirIxcNczcQxeOLn5dVQeUa13j+mPErnkx7hAc99/Bk2iP8MeMZrnGNt8W/as65sxrz5sY+7+TlGXz5aXJKyXxenRf+6S0l/hWiaTD/qxBzPknu+dCXn9zriay6YrUV/+JBtvsAphynS6BZc5lmzWVb/LNJiIXz/RW6kRdH0wriK4vu3buX+ffs7B96mXfr1q3MmIYNGwJw4cKFor9NmDABgM8++4zrrruODz74gLNnY/dPv//++4GCXn/Fr1tycnL47LPPALj33ntjjlPV2BmANjUWwzAIfPg2MTvhGgaBD95G6dTFUjlwaPkSgl/PwQhYO8GJ9eqj9Kq+jT8vJbJxHeHl5sq1CjHyLuJ77SXSf/orhGRe4YnWL16iu3eY7huonz6JdmDfZZEFqHvzCXzxCZFNG0ps2wdEEaVbT1zXT0LMLNtARXA4cAwehmPwMGuTWnVxlu2foGQSMSKsCK9haWgFp/TTQEFvu+5yF0Y5htNBaVfFK7y8EAQBBZkw5vua1gZxS8Hab4KCUqboIQsybeXWyVqWTSWxcmnYdDePLZsiXJenk5Fgee78r4KcOxu79cri70L07l/QXy8ZOJzJFev6D6re339BsNappX792iNm2tjUdtattrZBsm51kCsnpKVoNSUpdPm9FKlY5VismEixe8WRI0fyxz/+kd///vfMmTOHOXPmANC+fXvGjx/P/fffT48epdOXb7vtNn7yk59w4MABFi1axOjRowGYNWsW4XCYdu3alZmpWN2wtwpsaizakcOmzTYMv5/wxvWmxw4u+LogI86i+CfUycRz70PJ6TtYCRiGQWjxt3Edq+ecI7JlU3IXFAfa8WOW4iP79qRoJdUHPT8P73P/ILJ+TemaHV0nsmUj+c/+Ha2czNl4kVtauFkXBGSzpiO1GM3Q2BTeytv+D3jdN4v3/R+zJ7LPcqaqXw/wb+9LfBD4pEj8AzAw2BLdzr99LzE3OC/Zy7eJQXvZvOjqxEELqeYbgbSQm+HAfK/YDnLbFK6mYs5oZ/k6uIAP/Z/yeWBuXN89m5Ls2mle8NY02L8nsb53oZDB2tXmS3FXLEle2W6nLsnbxHI6YeDQmnHtaJZI1BYAbWxqCsGgtd8+q/HVjWeeeYZ9+/bxv//7v1xzzTVkZWWxd+9ennvuOXr16sX//M//lDomLS2N2267DSjIAiyksPz3nnvuqRFZ3LYAaFNjiezabik+umuHqTjtxDGCX8+xthinC3XYKNIf/ylSdiNrx1Yh+pnTlgW04iTbydWw2mAG0PMslsxZdBmOhaFpRI8dIbJ3N9HjxwqcjKsY/7uz0c9VnMpuXMzFP/uNmDe72tnTBWXwq5YT2b0To4L6AHWI+YxBpWv3cjMQLxd2Rnbz27y/8Kp/BivCq9kQ2cyS8Ar+7XuJ/87/Bye0k6bGMQyD1/2zOKgdrjBubnAeK0NrkrF0G5MMUvuZju2kdMAhpNBkqZJwCk4GqOaz4Ec4hqZwNWVzUc/jRe9r/CH/f5gT/JpF4WXMC33Hv30v8ef8/8e+6IFKX1NtIVTJN5GH9kcJWUhc2bU9edcAnbspZGYlfrOnqDD9fk/CmZCpxqo2fuZU8gxSbGxsUovTYkaz1fjqSMuWLfnpT3/KnDlzOHfuHMuXL+fqq6/GMAx++ctflugbWMgDDzwAwEcffcTFixdZs2YN27ZtQ5Ik7rrrrkp+BvFh11/Z1FyC1lKVjaC5XjMhK+WwnjQ8dz+A3KQZglrzdm5j9YOLhZZzLjkL+R4jFLJ+kMXfH+H7xq+JYoTDhJZ8R2jlMoxir6NYrz7q0BE4ho6Mz9QkQbTTpwrKos3EHjmEduRQmZl70SOHCc79jOglGZNCnUwcI0bjGD4a4ZKSbbl9J+TOXYnujCHOOxw4x19jao21lR2RXbzkex2dsgXjE/pJ/s/7Ak+lPUJjqeJNhQPaIXZFzWW2fhWcz0C1H6JQvW80awt5uvkegD698vrppJqrnFeyNbKDXKPiDZqeSnc6yx0raVUF5Ol5/MP7HDl62T1IT+mnec77Mg977qOjUvvbRSSbtDSR3AvmhZ+0tMRuIqsya0WSBCbf7ua1F31UtPcnijD6Sge7dkRLuAYLAnTtoTDuaidNaqFrq1j7npKNTa2l30Ann3/ssxRfmxBFkSFDhvDJJ5/QpEkTcnJyWLp0aan+g3379qV3795s3LiRt99+m02bNgFw9dVXl1uGXN2w7wBsaiyCx2Mx3lyfgsi2LeYH9XkRoEaKfwCCklj/vksFoEQxVOvZL0IdC1lkoojaM/H+jEYwgPelfxf0iLxERNVzzhH8/GN8r7+EEU1utqEZwpvMl7oDhDesLfW3yJ6deF/4ZynxDwoyB4NffIL/vdmlsh0FQcBz5z3Inct3VxXcbtLufRipcVNL66xNRIwos/zvliv+FRIwArzj/zDmeCtCq03Pfd64YFostEmcb0OLTcfu1fZzQc9N3WIqkTpiBo+nPUwjMbvcmH5Kb+5y317p5TLvBT4pV/wrJIrGG/7ZhI3KP4fXdHr0MX9d4XRCh86JXYd4LAqIVuNj0bGzwt0Pesod15MmcM9DHiZc5+KJ/0rjqZ+nM/1+N/c86OGZP2Zw1/2eGiP+Wb1Ea9XazjOxsakpjL7Sjdm8BUkqiK+phCvwD1AUpahvYKicxJTCLMCXXnqJd999F4D77rsvyatMHfaZ2abGonTvZalUV+nR21Sc4Te/+1EQX3OzNqQmzcDhxFL9TPHjk9zDTYyjBFhs0w58PvSzp2PGKj17I9bJjGNlJfG/OxvtyKEKY6K7dxL49EPcN9+W8HxWMCyWRF8ar3vz8c18DWKIl5H1awg3b4ljWMlmt4LDgeeeh4ju2UVoxVK0wwcxolHErCzUvgNRBwxCdFsT72sbmyJbyDe8pmIPaIc4Gj1Oc7l8wfSEbs2R+4R2ii5KJ0vHmMGvB1gdWceWyDb8uh+X4KKb0oXB6gA8Ys29UIwXwzA4b1yIHViM49ETZKmZqVlQJdNAqs8v0n/CtsgOVobXkKOfR0Sipdyc4epgmsuV3+/wvH6BLZFtpmK9ho8NkU0MUvuneFW1iwGDVOZ/FSRiotVe/8EOHI7EBLlWbWTSMwTy88xl9vXonfwN285dFZ75QwabNkTYvjVCIGDgdgl066nQo7eCohQ8R0EQaNJMokmzmiH4XUqPXirrTPZbdDigdVv7NtPGpqYgyyK3Ts3grTfzYsbeOjUDWa65eWQ33ngjTZs2ZcqUKQwaNIj09HQAjh8/zu9+9zvOnDmDKIqMGzeuzOPvuOMOnn76abZsKUgaaty4MVdffXWlrT9R7DOzTY1FatgIqXlLtKMV970CEDKzULqUbQ9eKtbpsmT+IbhcpmOrG4LDgdpvgGUX4EIsu8TGIo4MQCW7IfL0+/C+8M8KxVuxcRNcE29JZHVAQYltZNtmU7Hhtatwjr8GMT05ZcemsGpAc8lrHl6z0nR5fWjpQtQhw0tlggqCgNKxM0rHztbWcpmwNWKtf+nW6PYKBUCo+kbMG8Obme1/nxAld0v3aQeYG/yGW903M0DtW0Wrqznsju6jm9qlqpeRNCRBoqfanZ5q99jBlcCWyDYMC9+XTeEttgBokbR0kVunupn9ur/CnnHNW0pcdW3iJWSyLDB4mIN5c2P/bokiDB6WmooNRRXoP0it9k6+iTB2nIP1a8y5PI8c60CSqn+PML9P59hRjWgEMrNEGjcVa0QT/2jUYNvmCKtXhDlzuqCsvHFTiUFDHXTpJiOK1f852FQ/Bg0tuKd9d1YeZbX8lqQC8a8wrqbi9/t59dVXefXVVxEEgTp16hCJRPD5Cu4jBUHgr3/9K127ll3RlJ6ezq233lpk/jF9+nRkuebIajVnpTY2l6CdOY12xkTmiyjivvNu0/3Y5C7dCtxTTSCkpSc9C66ycY4dT2TbllKlrLGQO3VFamPe4dIMYjw989LSkBo1Ju2xpwl89hHRXdtLdqqWFdQ+/XBeNxHRlXgWUnjtKvPBmkZ4/Vqco8YmPK9Z5HbtCS9bZD6+bckeV2GTn30oKHfWDh9Ebl11Lp41Eb9hrh9pIYEY8Y3FRhzVjpser7HU0NL8sdga2c7r/tnlCithIsz0v4OERF+1V1Lnrs7YbrLVD69uLcPfZ9TcDP+qpGdvFcfDAp9+EODc2ZKtDiQJevdTuHGyO+Hsv0LGXOlg/94o+/dWXEUwcYqL+g1qZvZddaBBQ4lrJzr54uOKxdZmLUTGjKve/cHO52jMmxti04ZwiYKHxk1FRo110qe/UkoI9Hl1gkEDt0fE5ao6ge38eZ3XXvRy+mTJ79bF3Ci7tkdp0Uri7gc9pKfX3Awtm6pj0FAX/QY6WDjfz7rVQYJBA6dToN9AJ2PHuxGT3P6pKvj3v//N3LlzWbRoEfv27ePkyZNEo1FatWrF0KFDeeSRRxg8eHCFY9x0000l3H9rErYAaFNjCX71BZgxjdB1BAs3Yo6hI0wLgOqgoQg1SPEvCzGjDmkPPYbvtRdjOscWInfohOfOu5O+S6qbNGopjnHmNHTqilS/AWn3PoSWc47o3l0YwSCiJw25SzdEk/0fTa0xx9xrFG98oiiduyHUyTQl6AouF2qvkllZ+kVrJcSJGslcjrgFa0K0W6h4p3WoYxBrIuZ6P2YJmUk1XdAMjff8H5vKqvog8Ak9lG4oQs0+Z5olnovkhlL5PfNsEscpWBMlrMbb/ECnLgr/9WuZfXuiHNwfJRKBOv+fvf+Mj+O60kXvZ1fshEiAAAMI5pzATBDMpCKVkxWsLMuWJecw4zRzrj3n3DlzX4/HlmzZkqxgSVbOoihSYgIB5pxzjgCRO1VX1X4/QKQAAmhUNTpj/f3zB7F3d+/uBhpVT629V7aAcRPkqHe7lWSGR7/jxofv+rFxvYYrdxPJymZYdLMTJZPStzovHkyTY8fWzvfFPHfGRF2tmbRh65lTBv76dBO8TW3/bp09beKfr/hw8oSCm25zwjSBLRtDqCwP4uTxr0uihg6XMHOuiuEjpbhWDPp8Jv72p6Y2wXpLJ44ZeO4ZL576kQeyQpWAxD5JErDwWg8WXhu986dIrFy5Muzt/fv37/Ri67//+7/j3//931v929ixYzF27Fj8y7/8S8RzW758OQBg9uzZGDIktRqGdY+jcJJ2zPo6hHZbb9YRrCy3XKUk9esPdfZ8BFd9GXac2KcIjrkLLc8hmYn5PZHxk18itHMbtI3rYF6sBuccTJbBGxubl9aKIqSBg6GUzoQ8amzUG4AAAKQINgNnrQ8wxR55EHtEeWlyS3bb2sX5ShkTRbhuvRPel55DZ+t0nDff0aaBDZMlcBtbQna1kUx3NFYehS2hbTbGh9++YKDYH8OkIdivH+z0sRSm4M/e59FP7ItSZSryxB6W59EeK51eL2niXmwL7cBkpeuNeDp9LtOLddpGHNKPQIeOHCEbk+UJGCINiuvJmgwZIVhvJDFW6riBDum6UfJwfBCwvndwLPbK7E4EgWHocBlDh8f+74SsMNx+twtXL3Jg2+YQai+akCSg3wAJI0ZJYZejmibHnl061pYHceKYAcPgyO0hNC/pna7A5Ur9ipdo2LE1hONHO+/wrOvAG//w4ckfZcRhVvYEgxwvPNt++NfSmpUa8vNF7N0dwr49bStLD+zTcWCfjrLZCm663Rm3vyvlK4Jhw79LzpwysH6thrLZ9rfWIYSE5/f78dJLLwH4uiFIKqEAkKQk/fhRwOz8D+Dl8UcP23p8x6KbwZxOBL74vN1mCNKoMXB945tgavr8YWWSBKVkEpSSSW1u46YJMBbzA5xIQkWhR9cCDLvEvkUIbd9iebzUt18MZ9M+edRYuO59CL63XgXa63QlSXDecieUiVPa3jRgMEI7tlp7IlGE2G9AF2fb/YyXxyCTZaKBd77R8mBxIPqIvcOOYYzhEdc38Yz3ORw3ToYde968gPPmBezTD2BZcAXKlGm43XkzRBZZpcYBC6FjS/v0Ax0GgA1mA2rMWogQ0VPMh8rsf79yzvFFcAU+DSyFjtYnbWu1DSgS++JR1/3oIebafuxI8E46PV/pAr+ATCTfSXO66CUWYqg0CAf0zo8JFCiYKrf9e0iSW0aGgJlzrH93+H0mXnrO12b58LmzJj5+P4Dly4J4+HE3iqmjLT7/1PoqjWNHDDQ1GvBkJFcV4LbNGurrrK0KWvyRv9OFRmtWacjMFjBvYeyrhQ2DY32FtSYsALC2PIgZs5SU2NOQkFSh6zp+9rOfobq6GkVFRbj99tsTPSXb6K8ZSU0h6xUVkYxnjMGx4BoopTOhbdoA4+QxwDAh5PaAMnkaxIJCe8+f4mJS7dces/Mry1e6soIt1pRJ0xBY8inarDFqB3O6II+LfbVTe5TxEyANHQZt4zqEdm4H9/nAnA7II8dAmTK9w8YkSulMywGgPGY8hAwKK+ySmIQHXHfjL97noaPjn3k3c+Fu1x2WHtMluPB9zxOo1NahPFiJ82bnS885OMq1tfDzAB5w3RPRSUIQ1k9GACDE234XH9IPY1lgJfbo+y4vJVahYooyEQsdc5Er5HT4eJxzHNAPYVNoKxrMRtSYtTgbpivySeMU/rvpGfwk43vIFrJszd0uznnYz7c9QW7v/ST23em8Ff+/pqc73VvzG67b4BJSe6NzEp5pcrz4Ny+OHOr499TbxPHsn5rwo59nIL8gucKseKu6YG9f0+1bdcyYlVzv2cZ11r9jrewyBAArlgVRNluFEuPltjXVJhosdrsGgPPnzOaO1C4KAAnpqnfeeQc/+clPUF1dfblZyH/9139BifN5aDRQAEhSEsvKtjVesDn+8v1cbjhmzY3ovsQ+JsmAywX4rG+8LmR3HA7EgpCRAXXOPAS/XNrpWMdV18U0oDQbG6Ef2Nsc7rlckIaPbLXfoeBywzF7PhyzrTchkQYNgTy2pNMQkLlccFyzKOK5d3fD5CF4wv0YXve/jWrzYpvbi8Ui3O+6GwVivuXHVJiMOepMzFbKUM8bsDSwHKu1ik7vtym0FZP1CRgl2+/anMXsdbjOZK0D4/JgJd7yv99mD8EggijXKrE1tB3fdT+GIqlvm8c6Z1zA373/wBnzrK051PF6fORfjPvdd9u6n12MMahQ23RGDsfu+0nsKxQL8APPE/i795V2g3InHLjTdWtclqqTxNq9IxQ2/LskpAF//6sXP/t1BlVT2XDujA4guVbK1FTbq8q2wu9r3htx0tTYBgGhzq87t9HOIiZCSASamppw/PhxKIqC0aNH4+c//znuuuuuRE8rIhQAkpQkDRwMlp0DXldrabw8cXKMZ0SiRZ00FcHVKyyNFYv7Q8yzHpBEi+PqReA+P7S15R2OURdcA6Vsdkye32xsgP/j95uXIhstTl5ECfL4CXDecAsET2SVeYwxuO6+Hz5BQGhb+40lWFY23A8/npD3Pp0MlQfjN9LPsVffjz2h/QjwANyCGxPksSgW+0V8oskYQwY82Bbaafk+q4OVEQWAE5USLA0utzx+UotQZV/oQLvhX0tN3Is/e1/ArzN+CpfwdfOUKqMaf2h6Bk3cXlfXS7aEtuEW8wZkCLHd4NpKc5SWclh2bCZCWukj9sIvM36KffoBbA5tQ6PZBJUpGCENw0RlfETLz0nqqSy3Xg1WdcHEZx8HcN2NVBVqVSCQfJ3Q7W7jbNW5s/ZXsFh93G2bNTQ2cDBm7/2UZMDlpsCakGh48MEH8eCDDyZ6GlFBASBJSUwQoM6ai8BH73U+1umEMjl8K2+SPJTSWQiuWWVpj0d15rw4zKgtJghw3XYXlPETEKxYjdCeXc2XWVUV8uhxUGfMgtSvf0ye26yvQ9Mz/w2zpm3VGAwdoc0bYBw/Cs8TP4SQGVk1EZNluO59EMbMuQhWroZx/Ci4YUDIzoEyeRqU8RPjvvQ6XQlMwCh5REThWzhnjLOW9hi8ZJ9+ACY3ITB7y/37iL0sNyDpLxajWCy6/N/LgissBWSNvBFrtY2Y7/g6UH/H/0HE4R8A6DBwUD+MCcq4iB/DCs3mEunN+nbMEktjNBvSksAEjJSHU6OPbuz4UXslVeUrgph3lQMOB4UqVngyvv57EtI4dm4PoepCc1DWu4+IkWPksM1ZYqFffwl1tclfFtdQb+KNf/hwYF8EZX9fKZmoQJLoZ5UQ0hoFgCRlqWVzYJw8jtDW9quUAACyDNcDj0FwuToeQ5ILNzvtXttqbAJJg4ZAGjSkuQW9YYBJsf1K5boO7wt/aT/8a8GsroLvjVfg+daTET8XYwxScX9Ixf0jfgySOAEby04BwIABHQYU2N/v85uub+D3jU+jhndckZ3FMvGQ697LVY3VxkVLoeEla7X1lwPAauMi9uj7bc/zSoEr2l1zzrFfP4hybS2O6cehQ0eukIOpyiRMVSbByexV/pg2GlVdck4/n2wr5ghJW4bNX9FQCNi6ScP0MvoltcLtZuCcY8WyIFZ+EYTP1/rYLjOTYeF1jri+n9PLFOzYGv0AsKAwentlNzaYeOa/m3CxC8uVBQEom0MXagkhbVEASFIWEwS47n4Awd5FCJavAG+ob3W7NHQ4HNfdBKlvUQePQJJRsKLccgAYXL2i3a7F8cYYA2IY/vGQhsDyZdAqVoP7rFU96Qf2wTh7BmKv8B1kSXryMLet8SpUyBEeEmQLWfhxxlN41/8htoV2wmzR+ZaBYaw8Crc7b0aOkH3536vMalvPccGsBuccjDHsbtEspCs8LZb/BnkQL3pfwy59T6sxXsOHk/7TWBL4Ao+7H8YAqdjy40eyhNvbhapGQog9ubkCqi7YC1nOnIrNUs90pKoM777hx7oOOtc2NHC8+4YfDfUmrr4+PkurBw+VMGKUhL27w1fWiWLrHVbCcTiBsSVtw7b6OhObN2qoqTYhiEC/YgnjSmTInTQL+fBdf5fCP8aA2+92ok9fOs0nhLRF3wwkpTFBgGPuAqiz5kI/tB9mbS2YJEHsP5D2J0tRoS0bLY81Th6HUXUeYn5BDGdkHw+FENq5DcaZ04BpQuhZAGX8BDCH/QNcHgyi6blnYBw7Yvu+2taNcPa6yfb9SOorFApQKBTgnHne0vgSZWyXNrfPEjLxsPubqDPrsSu0F37ug5M5MUoe0Sr4u0SwWWnI8PXcrqzci4QTDgyXhgBorvx70fsqdul7OxzfxL14puk5/CTjeygUe1p6Dm61krmFQiF5vst0rmNbaCf2hvYjgAA8zIMSeSyGSUOoEQJJC5OmKvjsY3vfJxEU9nZbx4/p2La58yWsyz4LYsgwGQMHx/60lDGG+x5245Xnvdi/t/25qSpw38NubN6gYdvmzqsF58x3QFW//k7UNI733/Jj8wat1c9LJTR8+C7DNYscmDGr/arHhnqzSxWKxf1FLLzOgeEj5YgfgxCS3igAJGmBiSLkYSMTPQ3SRVwPWa5wu8Ssr0+aAJBzDm3NSgSWLWnzOvwfvQt15hw4rl4EJlgPP3zvvhFR+Ac0vzeke2KMYY5ahjf871oaP1uZEZXnzRayUKZO63RcL7EQAoRW1YLh9BV7Xw6d3DarG9szXZ0ChTVXbOzTD4QN/y4JIIBPA0vwiPt+S88h2Pg9v6SfnBwV67tCe/C672008MZW/16hrUOhUICH3Pehj9grQbMjJDqmlipY9lkAuo1t1vILIl/qaZocgtB9wvPdO6y/sWtWBeMSAALNlYmPfMeNvbt0rF0TxNHDOnQdyM4RMHGKgmkzFGRmCRg0RIK3yYuD+zt+HdNmKJh31ddhnh7ieOEvXhw+2P59/L7mcNDv41hwjaPN7Xt2hWyFzH2KRMya2/z8vXqL6N03Rl1OCCFpgwJAQkjyiKA9G5OTZ4+TwGcfIbh8Wfs3ahqCXy5FcNVysIxMSIOGQC2dGbZZiFlXi9DWTRHPh8l0Bbg7K1WmYr9+EFtDO8KOu8lxPYqkvnGaVbNMIQPj5NGdzu2SMuXrRk5j5JF4y289PLxSsViE6x1XX/7vcm2t5ftuD+1CvdmALMFagx0nHPDDeoVRyyYpibIjtBvPeV/qcJn1OfM8/tD0Z/zI8130EgvjPDtCoseTIeCu+1x47SWfpfGiBEycYv2Yg3OOwwd1VJZr2Lc7BE0DnC6GseNlzJilpn1YE7JRyLZrewh6iEOS4xOQCgLDqLEyRo3t+DhJURgefcKNjWs1VJYHceb0139zBg+VMGO2gtFj5VYV0auWBzsM/1pa8kkAI0fLbX4GfF57leOmyW39TBJCCAWAhJCkwQShOQQ0re+xw5xtr6Amgn74YMfhX6uBOnhtDUKb1iO0aT2UKdPhvO0bYGLbEwFt8wbrDVHaIQ0aEvF9SeoTmIAHXfciP5CHVcEKBK9oDJLFMrHIcQ2mq1MSMr+rHQuwK7QXIYQ/S+wlFGKSUnL5v7OETJTI47A5tNXW8wkQMFmegDtcN0NlX1dsHNGPWn4MEyaOGycwVhhtabzdLsBnjLMYKgy2dZ9o0ngIr/ne7HSPRT/345++d/CjjMgbDRGSDEomKdi6ScOeXZ2HNtNKFWRkWKsANE2O995su/+d38exvlLD+koN19/kwNyFyXEMk2imCfj8HJlxCgCtEkWGaWUqps5Q0FDPEQxyuN0Mbk/bnwPD4Kgst96Aq2J1EHfc07pJocNp7/U7bY4nhBAKAAkhSYPruq3wDwDMhgaIPRNfhRJcsyqi+2kb1gKCANftd7e5rbNuv+EwTwbkMeMjvj9JDyITcaPzOlzlmIet2g5cMKshgKGfWITR8giILHEVKH3F3njM/SCe977cYVBWKBTgCc+jkFnrKo3bnTfihHEybDMRBobx8hjkCNnIZtmYqIxvt3LP4Pa+c3RubVkb5xyGzSrFILfXvTnatmjb4OXWqqGOGMdwSj+NvlKfGM+KkNi672E3Xvxr+KWeo8ZIuOFW6/v4fvphoMPmFy3HuNwMU0tj0wVX0zh27wihusqEIABFxSIGD5Vw4byJyvIgThw1YBgcObkCJk9TMHKMDFFMXKDUch+9ZMMYQ1Z2+PmdOmmgvs76Rdud20O4457W/zZ8lAzG/Jav/Y4cTSs9CCH2UABICEkaPIKN5XldbQxmYnMOuo7QbmtLGdujrauAOmN22469YuRf0c6bbweLYWdikloczJGwSr9wRsrD8KvMn2B1sBLrtI1o+qoLbi+hEDPV6ZiqTGpVrXdJhpCBH3q+i9d9b7W7f1++kIe7nLdiuDy00znkCDnwm2ctzzlXyLE0jrHm1iV2angDSGwAuPOKLsid2aXvpQCQpDxFad4Tbt0aDRXlQVSd/zq479VbwIxZKqaUKpb376uvM1G+wtrv8pKPA5g4RYEkRS/8Mk2OL5YEUb4yCL+v9TeQ6gCCV+xKcPaMiT27dOQXCHj4W27kF8T/wlD/gWJSB4BW2F2+6/fxy93tL8nNFTBqjIxdOzpfPy3LwORptPyXEGIPnR0SQpIGi6C9Hk+CPQB5wN/l1oDBteVw3XpXq3+TivtDq1xt74EkCc7bvgFl/MQuzYeQeMkVcnGzcxFuclyPIIIQIEJhnVc1ZAoZ+LbnEVwwqrAltB0NZgNUpmKoNBjDpCEQmLWlelOViXg/8ImlsQVCPorFfpbGct7ZQtq2XMx+p/Bo8nN/TMcTkqwkiaFsjooZsxVUXzDhD3C4XAw98gTbXa/Xr9UsHxI0NjZX6Y2bEJ1jGdPk+OfLPmztoHvtleFfS1XnTfzlf5rwvZ9mIDsn8mYnl7QXNnakdGZsqiDjye5yXIeDtfuzddPtTpw4pqOhIfxfkFvvcra7FJl0TxkZGYmeAkkR9K1BCEkaPIKumdASWzEDAEzt+oGr3k6nX3lsCZjL1c7o9ibBoC64Bpm//H+gTu68CyshyYYxBgdzWAr/Wuop5uMaxwLc6boVNzmvxwh5mOXwDwCmKVMsB2/z1TmWwwDGGBywt7+Xm1n8fY8Ru8/vSvB8CYk2xhjyC0T0K5aQly/aDv8A4NRxG22FAZw8YW8bgnA2VGodhn9WNDRwLF1svXFROOMmyOjXv/NqwuGjJIyfmPpLWfv2E5GRYf3nZeSY9utwcnIFfPdHHvTt1/5753Ix3POAC5OnpX5oSgiJPwoACSFJg0XQ8ELIyo7+RGxisgJpcOdLDcMKtT1hYLIMx3U3Wrq749ob4bxmEYQMa91JCSHN3IIL33I/CAXhK3BmKtMxXbG3jLpEGWt5bA7LRpEY327MVxonj7E53lozFEK6E7sLAmxufdwhzjlWr+z6RdGtmzT4fF1b1QA0L+t97Ak3ho/seMFZyUQZDzzitry8OplJEsPUGdYrOUtndRzg9cgT8f2fevDkjzwonaVgzDgZE6fIuOs+J379u0xMmJz41S+EkNTUrZcA/+53v8OGDRsAAPPmzcMPfvCDDseuXbsWn332GQ4fPoxgMIi8vDxMnjwZd9xxBzIzw59w19fX45133sGGDRtw8eJFqKqKQYMG4brrrsO0aVSpQ8glTJIApxPwW19WJuT2iOGMrFNmzIJ+6EDE9xdy2t9XTJ1WBu4PILD4ww47Aqvzr4I6d0HEz01IdzdYGoQfZzyJT/yfY5e+p1UX3HwhD/PV2ZihTLNdDTRLmYG12gZLY8vU6QltygI0B4CZLBMNvKHTscOkISgUC+IwK0JSS488e/UVdsd35OwZExfOdT24C4WAE8cMDB/ZtXldOGfCOU3Ao094sGl9EF8sCeJitQnOAVEEhgyTMGO2CllJ/fDvkrkLHdi3W8epk+FT3dnzVBT3D38azhhD/4ES+g/s1qfrhJAo67bfKBUVFZfDv848++yzWLx4MQBAEASoqoozZ87gww8/xKpVq/Af//EfKCoqave+J06cwC9/+UvU19cDAJxOJ7xeL7Zt24Zt27bhhhtuwGOPPRadF0VihnMO7m0C1zQIbk9UlnyS9ilTSqGt+tLSWLG4P8S8/BjPyBp51FjIY0sQ2rE1ovsrEzuuLHLMXQB5xCgE15YjtHM7uM8H5nRAHjkGSuksSH0SWzVESDroI/bG456HUGvW4Zh+Ajp09BBy0V/sZ2tJcUtFUh8sclyDTwJLwo4bIg3CPHV2RM8RTTKT8KDrHvzZ+xx0dHwCm8EycLfz9jjOjJC2DINjz84QjhzSEQoBmdkCJkySkZef2CB98nQFFavDdwC+RJKBkknRWf7a1ND18O8SLWh/RUZ7OOf4/NMAvljSujLRMIB9e3Ts29OEWfNU3HCLI6Ll1slGVRkef8qNN/7hw+6dbVd2SDKw4GoH5l9N5xGEkMTolgGg1+vFc889B7fbjZycHJw6darDsZ9//jkWL14Mxhjuvfde3HTTTVBVFUePHsXvf/97HD9+HL/73e/w9NNPQ5Zb/wEPhUL43e9+h/r6ehQXF+NHP/oRBgwYgGAwiA8//BCvvfYaPv74YwwYMAALFlD1TjLiug5t0zoEK8phnj3d/I+MQRo5BurMOZC7uuyTtKGWzoRWsRrQO9/DRp2zMA4zsoYJAlz3PAC/ywVtfWWH1Xrt3jc7B/LYkrBjxMJecN1yJ3DLnV2dKiEkjBwhGzlKdtQe7xrHAjiZE58GlsB3RdMMAQKmKBNxp/MWyCw5DsmGyoPxpOdxvO57GxfMqja3DxT7437X3cgTk6P6mnRPO7Zq+PBdP+rrWv+tXfppAKPHyrjjnsQ1SOhbJGHocAkH9nW+F+C0GQpc7ujMU4liF93MrLZzYszWoQ2ysgSUrwy2Cf+utHp5EE4nw8Jr7e2ZmqycLgEPPe7B+XMGNq7TUHPRhCAA/YpFTJoavc/7klCIY8fWEDZv0FBXa0KSGQYOFjG9TEVBYWLDcEJI8kmOo804e+mll1BTU4PHH38cFRUVHQaAoVAIr7/+OgDguuuuw513fn3iPWDAAPz617/Gd7/7XZw9exbLli3Ddddd1+r+n3/+Oc6dOwdVVfGb3/wG+fnNlUqqquLOO+9ETU0NFi9ejFdffRVz5syBJHXLjyNp8YAfTS88C+Po4Stu4NB374C+ewfUhdfCefX1iZlgmhJ75MGx6GYEPng77DhpbAmUMePiNCtrmCTBdfvdUOddBW19JfTTJ2GeOgne1NjxfVwuuB96HExO/Q2wCSHtm63OwHRlCraEtuG8WAWTmcgXe2C0MRLZQlaip9fGYGkgfpXxU+zXD2Kvvh8BHoSHuVEij0OR1CfR0yPd3OYNGv75iq/D23ftCKGqysCTP/TA6UpMCHjvgy789U9NOHO646q8EaMkLLo5ep2/+xSJcLkYfL6uVe/l9hDabd6RmcXaBK7hjBkv4//7j46Pf1r6cmkAM2YrcCXo8+oKzjkOH9SxdVMIDQ0mVIVh8FAJJZOVqH6+7Tl9Usff/+pt87mcOWVgzUoNM2YpuOl2Z1rssUgIiY5ulzjt2bMHS5cuxZAhQ3DttdeioqKiw7E7duxAbW0tGGO49dZb29zes2dPzJo1C8uWLcPKlSvbBIArV64EAMyaNety+NfSbbfdhs8++ww1NTXYuXMnSkrCVwCR+PK+9lLb8O8KwWWfQcjOgTq1NE6zSn/c70dw5RedjtP37IR+6iSkvu0vv08kMbcHnNfeAADghoHgqi8RXLMKvKH+60GCAHn0ODiuuzFpljETQmJHYTKmKZORk5MDURRhGAZqa2sTPa0OCUzACHkYRsjDEj0VQi5raDDx9usdh3+XnD9rYvFHAdz2jcR0qnZ7BDzxwwys/CKAdRUamhq/Dmh65AmYMVvBjFkqRDF6wYwsM0wpVbDyi641Aimbo7QbGEmivWBx2+YQAhYbCushYPP6EGbOTa2lsVXnDfzj7942Qe+2LSF88oEfN93uwuRpsWnYUXXewLN/9MLv7/hzqVitweTAbXdRx3ZCSLNuFQCGQiE8/fTTYIzhiSeegCCEv8q0Y8cOAEBRUVG7AR4AlJSUYNmyZdi/fz8CgQAcjubydb/fj4MHDwIAJkyY0O598/Pz0bdvX5w8eRLbt2+nADCJ6CeOQ9+729LYwLLPoEyaCiZSmX00BDeuBa+zcFKs6wguXwrp/kdiP6kuYKIIx7yroM6eD/3wweYQUFYg9R+QFB2MCSGEkFSxoVKD3vnKWgDApg0arrvRkbAqQIeD4ZpFTiy4xoHTJw0EAhxuD0PvPmLMKrLmLVSxe0cIVRci2w9wbImMstnth3A1NfYey8oS6JZOntABpE4AeLHawDN/aGoV7rYUCABvvuqDaXJMLY3+6/r0w0DY8O+SteUappUq6FPUrU77CSEdSL066y54++23cerUKVx//fUYNGhQp+NPnjwJACguLu5wzKXbOOetlhKfOnUK/KuNMqzc/9JzkeSgre+4MvRKvK4W+v69MZxN96Kts/7eh3ZthxlmeW0yYaIIeehwKJOmQhlXQuEfIYQQYtPO7Z3vD3xJSAP22wyhYkGSGIoHSBg2QkbfIimmyzFdbgHf/p4HRcUdX5R2uds+v8vNcNX1Dtz3kKvD+dnZ/w8AmhrthZBm+Ma5SeeDd/wdhn8tvf+23/Z70Zm6WhO7d1r/Xagst9aUhhCS/rrNpYCTJ0/inXfeQW5uLu69915L96n56lJXbm5uh2Na3tZyKU9Ni8tkVu7f2TKgV1999fJ+hO25++67cc8994R9DGKdv+q8rfFKfS2yc3JiNJvugxsG6i7YeO9NE26/D46ifrGbFCGkS6pC1VjVtAYntVPg4Ogj98acjJkokHsmempxVW80YHXjGhy5cAwGN5Av52O2Zwb6Kcm3jQEhySrgb7J3B+5ETk5mbCaTpHJygH/7j1zs2xNA+cpGVJ3XIYjAgIEqZs/PQGEvGceOaDh8MADdAPLyJIwrcUJWOqsLqbM1D1kRAVgPvvoUuZCTIsfSVRdC2Le7ztJYPQTs3C7iuhuyo/b8B/Y22Qpkjx42U+a9JYTEVrcIADnneOaZZ6DrOh599FG4XNb2QQh8tXGFqnZctt3yNp/v6z1JAi02vbByf7/f3+EYoLlz8YULFzq83efzQaQlqAkjMIHe/yiIZNtqQaD3npBkFOIhvFj1D6xoKAdv8du9GdvwUf1izMwoxWP5D0IRYrM/UrIwuYm3a97HR7WLYaB1icuS+mUY5xqDpwoeh0f0JGiGhKQOl1vAxWrr491uqdseI4we68Hose1/rwweKmHw0NjuC5ffU8bJ4yGYFjPAWXOzUuaz2rPTXgC3c5sfN9wcvc7poZC9KlJN4ynz3hJCYqtbBICff/459uzZg4kTJ6KsrCzR04mI2+1Gz54dV0u4XC4YRorVzicxuVdfBI+EbwDSktirF73/USIX9ELo/FlrgwUBYn4BvfeEJBmTm/jDhWew2betwzHljZWo1xvwk4LvQWRfn5ic0E7hbOgcGIB+ShEK5YKI5hAwA9jh34UGowlOwYFRjhHIluLfcffli69jacOXHd6+3bcTvz39n/h1r5/DKcS2YyQhqW7seCdOHre2nFGSgBGjVDpGSJC+RQpUh4CKVZ1XbU6c4kJevpgyn5XXa29puc9nRvW1ZWXZCwCzc1LnvU1GFJ6SdJL2AWBNTQ1efvllKIqCxx9/3NZ9LzX0CAY77qbV8raWlYWX7ntpTEdVh5fu73SGP+i/7777cN9993V4e3V1dVJ3E0w5JROBilWWhrLMLAT7FkOj9z8qxMlTEfrkA0tj5VFj0GCaAL33hCSVjdqWsOHfJTv8u/DZ+aWYoU7DztBuLAl8geNG6z1xh0qDcZ3jKgyWBlp67iAP4mP/EqzTNiCAr/9GCxBQIo/Fzc5FyBGy7byciB3Wj2JpU8fh3yXHtZN469z7uNF5bRxmRUjqGj+R47OPYamqbNwEGbrRQIcIUSIrzfsqWlXYO4QppRLOnZVw+EDHgVlxfxG33CGn1HkME+x1WlYdpu3XZxi8wy7Rhb05PBnM0h6EADC2REip9zfZ5OXlJXoKhERN2geAr7zyCrxeL+644w5kZWW1WWprfnUEYRjG5dtUVYUgCMjNzcWRI0da7ed3pZa3tdxboeW+fzU1NR0GgJfuT/syJBexeACkocOhH9jX6VjH/KupA3AUKVNKEVy9orlbbjiiCHXuVfGZFCHEltVB6818VgcrETSDeC/4cbu3H9AP4VDTETzgugcTlfFhH8vPA/hT07M4YZxqc5sJE5tD23BIP4IfeJ5Avhj7A/rVwUrLYyuCa3GtYyFklvaHZoRcxjnHyeMGdm4PwdvE4XQyjBgtYdAQCYy1DT9ycgXccKsTH74TfuucnB4Crr85OSpqTZNj/14dGyo1VF0wIAhAnyIJ08sU9OufOr/v4yco2LjOWgKoOoABgySIIsNj33GjfGUQleVB1NZ8HVhlZTNML1Mxe54KWbFX0cY5h2miw4As1kaOkSG+5YfVorqx42VL404c01GxOohdO0IIBgBVBUaOljFjtor+A7/+WZFkhtJZKpZ+GgjzaM2cToZJU9N7qw1CiHWp81cnQpf2zXv77bfx9ttvdzhu1apVWLWqueLrD3/4AwYOHIiioiJs2rQJJ06c6PB+l25jjKFv376X/71v375gjIFzjhMnTrS6rb37FxXRJuDJhDEG130Pw/v8n2GcONbhOHXuQiilM+M3sW5AcLngeewJNP3tGfDGhvYHiRJc9zwAqV/HHbYJIYnhM304ahy3PP60eQbvBc+EHWPCxCu+f6KP2BuFYsfbYbzte7/d8K+let6A572v4F8yfthuwBBNO0O7LY/1woeTxikMlPrHbkKEJJEL5wz88x8+nDzeOkVZtTyIgkIBd93najcgmzlHhSwBn3zgR6Cd/KP/QBH3PeRGZmZnTS1ir67WxIt/8+L0ydav8cxpDRvXaRg9Tsbd97ugqtH9LjJNDr+PQ5JZ1B577gIVG9drljZsnjVXvRzOSTLD3IUOzJ6v4vRJA34fh8PJ0KdItBXgmSbHzu0hrC3XcOSQDtME3B6GiVMUlM5UkJcfv4vxmZkCxk2QsWVj5514HU5g4uTwARznHEs+CeDLz1tXFgaDwNbNIWzdHMKseSpuuMVx+e/W/KtUnDymY+/ujqsrJRn45iMuuFyJ/10ghCSHtA8Au2Ls2LF4//33ceLECVRXV7db/rt161YAwLBhw1ot+3U6nRgyZAgOHDiALVu2oLS0tM19q6urcfJk81KncePGxehVkEgJLhc83/k+tHUVCFaWw2zRGVgaNhJq2WzII0YlcIbpS+zVBxk//BcE16yAtn4tuLd5/xgmy5DHTYA6ex7EXn0SPEtCSHsC6LwiIRIGDKwKrsFdrlvbvb3ebMCm0FZLj3XaPIMD+iEMk4dEc4qtcM6hwcZ6OTSHp4R0BxfOGXj6903w+dpPk86fM/GX/2nC4095WlU+XTKtTEXJZAVbN2o4fEhHKARkZzNMmKKgX3FynN74fCae/WMTqqs6Xq+8a3sILz/nxaNPuCEIXQ/qzp01sGZlEFs3abi0S1GfviKmz1QwaYoCSY78OXLzGBiDpeYXhb3bBk6CwFAU4WcTDHK8/JwXB/a1Dru8TRyrlwdRsTqIb9znQsmk+FW63XirEyeOGWE/X0EA7r7fDYcz/Pu+enmwTfjX3hiXi2HBNc3nm6LI8OC33Fi6OIDKcg3+K36XBgwSccMtzpSqMiWExF7afyP87//9v8Pe/otf/AK7du3CvHnz8IMf/KDVbWPHjkVOTg5qa2vx/vvv47HHHmt1e1VVFVavXg0AmDNnTpvHnjNnDg4cOIDVq1fjrrvuQn5+fqvb33vvPXDOkZubizFjxth/cSTmmCxDnTkHStls8Po6cC0I5smA4HInemppT8jMhPO6m+C4ehEyuAkBHCwzC/W+8Mt+CCGJ5WSx6yy5UduM2503tWoacskWbRtMWGw3CWCDtjmmAWAk1YXnzAsYjZExmA0hyeWNV30dhn+XhELA6y/78C//ltFuOKaqDNPKVEwrU2M1zS5Z+UUwbDh0yYF9OnZsDWH8xK6FV5vWa3jrNV+b/RFPnzLwzj/9WF+p4dHvuOH2RFYN9t5bPnCLX7Fv/sOPcSXR+Vw453j1xbbhX0uGDvzzFR88GQxDhllbbttVngwB3/2hB2+97sPeXW3n1iNPwG13OTF0RPj5BIMcSz+zduHsy88DKJ2lXK7oE0WGa29wYsHVDuzZHUJ9nQlJYhgwSEKv3rQ9ESGkLaoHDkOWZdxzzz0AgE8++QTvvPPO5aYdR48exW9/+1sEAgH06tULCxcubHP/q6++GoWFhQgEAvjtb3+Lo0ePAmhu/PHOO+/g008/BdDc4EOS0j6LTWmMMQjZORB7FlL4F2dMFCHn94RS2BuC6uj8DoSQhHIyB4ZLQ2Py2AEE4eftnyjV8U72De3ieLtMK10KrqBxexWDhKSiE8d1nDhmbfO0motm2CWOyUoPcayvtP77XFlur6nElQ7sDeHNV9uGfy2dPG7gpee8ME1rjSOutHGd9c9B04AzpzpfHmvF0cNGuwHblUwTWPJxbCrQO5KRKeCRb3vw899k4JpFDpTOVDBngYrHnnDj57/J6DT8A9BcrWlx2qEQsHlD2/dVVhjGlSiYNdeB0pkqhX+EkA5R6tSJq6++GkePHsXixYvxyiuv4LXXXoOqqvD5mpfpZGdn41e/+hVkue0XvCzL+NWvfoVf/vKXOHbsGL7//e/D5XIhEAhcPjFYtGgRFixYENfXRAghhMTSbLUM+/QDMXns9qr/AECGvaoPOcaHQIJg/xqrg9FFDpL+dm+3Fwzt3BbCqDHxqeqKlvPnDHibrAdtRw8bYbu+dubzTwOWluYePWxg/14dI0bZfz+tVv9d8uXSIL75cNc/t7VrrIejx48ZOHPKQO++8Q3A8nuKWHBNZM956oTFTiJfOXlcB5CcVa+EkORHAaAF3/72tzFu3DgsXrwYR44cuVz1N2XKFNx+++3Iysrq8L79+vXDn/70J7z77rvYsGEDqqur4Xa7MXDgQFx//fWYNm1aHF8JIYQQEnujpRGYqUxHubY27Lgp8kTsDu2FF9b2vuslFMDZQUg2SBoI2CiiGSwNtD44Qi7mhI9b37ZgvDw6hrMhJDl4vfYq0Pw++9W0iabZLOblHNB1QIwgQzpz2sBxixWVALBuTTCiANCu6ip7wVZHbAdkJ/S4B4BdYbdYPILickIIuazbB4Cd7RF4yfTp0zF9+vSIniM7OxuPPPIIHnnkkYjuTwghhKQSxhjucN6CLCELXwRWIHBFMqdAwTx1Fq5zXIWPA59hWXCFpcedqbZtqHXJMGkw8oU8VJnVnT6OBAnTlCmWnrMrpstT8aW20tLYnkI+csXc2E6IkCTgdNmrcuusgUIyysyyN2fVASgRbgF49rS9gOz0qegEc52Rpeh8bukekPXIs1ctbnc8IYS01O0DQEIIIYREn8AEXONYgLnqTGzWtuGMcQ4AR6FYgIlKyeVKvnnqLGzStqKW14V9vD5CL0xTJod9vjucN+Mv3hfAEb7CaJHjaniE2O/nushxNdZq6+FD+CpABoZ7nXfijHEWm7StqDProTAFg6WBGC+PgcTocI2kj5GjZaxYZr1cd2SKLf8FgB55Ivr1Fy3vdThhkhJR4yAAtvf0s7JUOBpGj4/O59YjT8DFauupXl5+agVkE6co+PzTgOXgcvK0+HU6JoSkHzqiJIQQQkjMqExFqTq1w9szhAw86Xkcf/E+j2rzYrtjisS++I77YSgs/InPSHk4HnZ9E//w/RMa2u4zxsBwveNqzFfn2HoNkZIFGf/q+TF+2/Sf7c7nkjscN+Gz4LI2+yau0dYig3lwu/NmTFTGx3i2hMRH/4EievcRcOZ054lHVjbD6LGpFwACwKy5Kl59sfPtDRgDZsyOfE+3ngX2lrvaHX+JywX4rO3WAAAYOTo6QdWU6UrYDsAt5fYQMGhIap3eZmQy9B8g4sjhzsPisSUy8vJTZ3kzIST5pNY3JCGEEELSToGYj19k/ARbtG2o1NbjnHkBDEBfsQ9mKNMwTh7dYfOPK5UoYzFYGoh12kZsCW2H1/RCZSpGysNQpkxHvpgX2xdzhYrQurDhHwC8H/gEIbR/gtvIm/Ci71WEeAjT1I4rIAlJFYwx3HmfC3/5QxOCYQoBRRG46z5XxI0xEm3cBBlHDyuoWB1+Q8Db7nKisFfkoU6//iIKegk4f9ZaCdnU0siCuXlXOfDJB9ba1eb3FCIOGq80epyM/AIBVec7f31zFqgQhNT5efH7TLz4N6+l8K94gIg773XFYVaEkHTGOI9XITiJperqzvc8IiRV5eTkQBRFGIaB2traRE+HEEIsOaGfwv9t+kNUHkuChP8n85fIFDKi8niEJNrJ4zpee8mH6qq2wU5WNsNd97kwdHhqVv9dwjnHmlUaViwLoKG+9SlXQS8B197gjEqF49ZNGl57qfPyvJ6FAn70LxmQItifz+c18e//2mBpqerNdzhQNjt6Xc2rqww8+8cm1NV2fNo6c46CG29zRryUOl6CQY6GOhOCwPH2P/04dKDz8G/aDAU33eaErCT3a0tXeXnxvXBISCxRBSAhJGkZ584iuK4C/nNnAM4h5fcExk+ENGhI0h/gtcQ1Ddq2zQjt2Aru9YI5HJCGjYQyZRoEV+z3ISOEJMZqrSJqj6VDx1ptA652zI/aYxKSSEXFEn726wwc2Kdj57YQfF4Oh5Nh5GgJI8fIKVv51xJjDDPnqCidqWD/Xh3VFwwwgaFvkYj+A8WoHcuUTFJwsdrEkk86rtDL7SHgkW+7Iwr/AODgft3yPnWHDhgomx3R07QrL1/E936ageVLA9i0XkOgxbaqRcUiZs1VMX6inNTHhqdO6li9PIjtW0MwrK1ovuxitUnhHyEkKqgCME1QBSBJJ1wPwffOGwhtWt/u7WJxf7gfeAxCZlacZ2Zf6OB++F59Edzb1PZGWYbz5jugTu24sykhJHX9rP7X8PHwDUDs6Cf2xc8yfhC1xyOEpJf9e0JYtTzYas88t4dhaqmC2fNUuD2RN8h49o9NOHTAWnLFGPCr32YiKzv6DTk0jePMKQOhEEd2toD8KC01jqVN6zW89ZqvSx2Kf/6bDOT3TP7Xmo6oApCkE6oAJIQkFc45fK+9jNDObR2OMY4fQ9Ozf4TnqR9DcCbvfij60cPwvvAXQO/ggDkUgv/t1wFBgDp5WnwnFyWcc5gXq8H9PjCXG0Juj6S+Ak9IvHDOoxr+AYj64xFCOsY5x+FDOvbtDiEUAgp7iRg1RkZmVvJ2mR02UsawkTIa6k3U15mQZIb8nkLEVX8tnTxhvWyNc+D0KSMmAaCiMPQfmDqnsIcP6njzVV+Xuy+fPmlQAEgI6bLU+fYkhHQL+p5dYcO/S8wL5xFc8QWc190Y+0lFgHMO3ztvdBz+teD/4G0oY8aDOaK3X06scV2Htm4NgpXlMC+cv/zvYu++UGbMgjJ5GpiQvCdJhMQaYwxOOOFH9EI7F3NG7bEIIe0zTY41q4JYtjgA/xW/vu+96ceIURJuudOFnNzk/RuXmSVENag8d9aAFqZhS3u6Uu2WTr78PNDl8A+g95MQEh0UABJCkkqwstzyWG19JRxXXQsmJd8m4caRwzDPn7U2OBiEtnkD1BmzYjupLuCcQz98EPrB/eB+P/T9e2BebLv1gHHmFPxvvw5932647nsYTKSr1aT76i0W4rBxNGqPN0YeFbXH6m6O6ydRrlViT2gfAjwAD/OgRBmbkM7QJHmZJsc/X/Fi66b2L95xDuzZpeP4sUY8+SNP2ldkGQbH+2/5sa4ifCfj9ogi7TJ1sdpotRy7K3rkJW/gTAhJHRQAEkKSBucc+sF91sd7m2CcOQOpX3EMZxWZkI3XAQD6wf1JGwDqhw/B994bMM+fs3yf0M7tCHzyAZw33RbDmRGS3ILcZslMGBJElCpTo/Z43YXJTXwQ+ATLg6tb/XsNr8WXwVVYESzHXc5bMUNNzW0YSHStXhHsMPxrydvE8fJzXvzoXzMgCNHf9sIwOI4dMdDYYH615FWEyx3/AOjdN/zYsNZ++AcApknbgZw/F52yvYJCAf36p3fYTAiJDwoACSHJw9Btr3HgdtekxIvNeSXr6wgd2AvvC3+F7ZZ1AIJry6EuuBqC2xODmRGS3DjnOGNaD807c4fzFmQJmVF7vO5icWBpm/CvJRMm/ul/B07mwARlfPwmRpKOYXCsXNZxF90rnTtr4tB+HUNHRG8VgmFwrFoeRMWqIOrrvq6gk2SgZKKCaxY5YrKvXnuOHdEjDv8AwKQ1q4jWlsjzrnLQ/sqEkKigWmJCSPIQI7gmkaQHRMxj70SdeTJiNJPIcU2D79WXIgr/AAC6Dm3zxqjOiZBUYqLrJ8Au5sL9rrupQi0CDWYDlgaXWxr7vv8TmJwCi+7swD4dTU327rN5Y+QB2ZUMo7mqcPGHgVbhHwDoIWDjOg3/81+NqLpgRO05w6ks79qFyfNn6fepoLDrp9rzrlIxcYoShdkQQghVABJCkkkEV4t5NHZWjgF5XAkCn30Eqzs/KyWTYjwj+7Stm8B93i49hll1vvNBhKQhxhhEiDBg72R9plIKH/dDYTIGSwMxQR4HmSXfPqepoFLbYDmEreV12K3vpX0Wu7GaavvHIHV10TsG+fzTAPbsCn/BraGe48W/efGTX8Rm6XFLhw92be+6s2fiE1Qms9weIoaNkLB/r/33sri/iFnzVYwrofCPEBI9FAASQpJGJGEer62JwUy6TuyRB2nkGOi7d3Q6VsjLhzRsRBxmZU9ox7auP0iSVmgSEmucc3DY+04bKPbHXa5bYzSj7ueoftz2eAoAu69IFiHIUcrmg0GOytXWKu4unDOxd7eOUWNie2FAi15xY7e24BoHDu5v6vQad24PhjvucQEAsnOEtG8wQwhJDAoACSFJg0UQADKnMwYziQ7X7Xej6fxZmNVVHY5hTifcDzwKJiTfjgzc29jlxxB7943CTEhX6VzHQf0w6nkDVCgYJA1AJu0nF3N2A8Cx8ugYzaR7slt9qdscT9JLv/72T4sGDo78VOrMKQMVq4PYvzcEbxNHKGT9vpvWaTEPADMzGfy+yCsce/ftWoB19rSBdRVBnDltgHMgv6eIqaUKigeIKbUf3oBBEu6+34V/vuLrMATskSfgW0+60SOPQj9CSGxRAEgISR6SBDABsLEPk5CdE8MJdY2QkQHPkz+C/4O3Edq+te1yYFGENH6i7f0C44WpXQxXVQeU8ROjMxkSEYMbWBZcgdXBCjTwrwNdAQLGy2Nwo+M65Ik9EjjD9MUYQ66Qg4um9Srl0fLIGM6o+8kV7P196GFzPEkvvfuIKB4g4PhRa8cgoghMmWZ/eSbnHIs/CmDFssj32Kutif3+eiWTFCz5xHpTlCtFWsEW0jjefM2HbZtbJ6LHjhjYuE7DoKES7n/YBbcn+S6cdqRkkoLCXiLKVwaxZZMG/auXlp3DML1MxfSZClyu1Hk9hJDURQEgISRpMMYgDhsBY99ua3dweyD26hPbSXWR4MmAPGY8Qju2A/yK6hLDQGjtGuh7dsHz2HchFvZKzCQ7II0YCf3wgYjv75i3EMzhiOKMiB0GN/A370vYre9tc5sJE1tC23FAP4SnPN9GHzG5fvasMriBHaFdOGIcQ4jryBGyMVkpQa6Qm+ipAQCmKpOwOLDU0thioQiFYs9Ox/l5AJu0LThhnILBDeSJPTBVnoQeYnK85mQyTZmMSm29pbESJEyUS2I8I5Lsrr/JhWf/2PlyTQC4ZpEDngz7oc2ST7oW/gGRLVe2a2qpguVLAxEvBZZl+1V6psnx8gte7Nvd8Z55hw/o+NvTXjzxQw9UNXUqAXv1EXHnvS7ccqcTjQ0mRJEhI5PFfC9HQghpiQJAQkhSUadOh89iAKiMHgsmJvdyCf3EMfhefxkwO15axuvr0PT8n5H5418k1ZJmZfI0BJZ8isuXqu3ct2wO1HlXxWBWxKpPA0vbDf9aauJe/M37In6d8TNILLUOCTZr2/Cu/yM08IZW//5JYAlK5HG423UbnCyxv09jpJFYDGsB4ACpf9jbOef4MrgSnwW+QBAtwoMQ8FlgGSbK43G363aoTO3CjNPLALEYA8X+OGIc63TsNGUyPII79pMiSW3gYAn3P+rGP17wwgizInzBtSrmLLD+u8Y5x4F9OlZ9GcSBfV1rrgEA/QfE/vs6I1PAvQ+58crz4d+LjvTtZ//4bPuWUNjw75LTpwysWRnE/KtT7yKjLDPk9kjuY1dCSPqiWmNCSFIxL1ZbH9vUFMOZREfgy6WwcuTM62qhbVoXhxlZJ7g9cN5yh/U7MAaW2wNCbg/o+3bD++wfEVxfCU47icedxjWUa5WWxl40a7A9tCvGM4quyuB6vOh7tU34BzTvu7cltA1/bHoWAR758rVosPO+HtQPh22E9HFgCT4IfNo6/PsKB8em0FY80/QcNG4/sE9XjDE87P4m8oW8sOOGSoNwq/PGOM2KJLvRY2X84n9lYvZ8BS4XA1hzPyvVAYwdL+Pnv/Hgmuudlveh45zjw3f9eO4Zb1TCPwCYVhafzrCjxsh4/CkP+vW3H1gFg/b3D6wst14ZuXZNEKYZvS7MhBDSHaTW5X5CSNrT1q+1PFbfuwtmYwOEjOTcQ89sqIe+Z6fl8cF1FVBnzo3hjOxTp5YCjMH/4btAsG2YIuQXwPmNbyK0oRLa+krwmouX2x6Y1VXQDx9EYMkncD/4GKTiAfGdfDe2K7QHfu63PH6DtgkTlfGxm1AU1Zi1eNP/XqfjThqn8WlgKW5LYLBjNYQFgNPmGZwzz6OXWNjmtuP6CSwNftnpYxwxjmF5cBWucSywNc90li1k4ceep7A4sBQbtE0ItAhQM1kmZqrTsUCdCznFKmBJbGVlC7jhFhduuKXrj7V8aRBrVkbvQtiMWUpcO8QOHCzhez/JwE+erLN1v22bQlhwjfV5hjSOo4etlxrW1XJUXTBRUEjVdIQQYhUd7RBCkgY3DJhV563fwTRhVl1I2gDQuHC+beOPMMwL58FNM+k6AqtTpkMZWwJty0boB/eBB4NgGZlQxk+ENGwE/B+9C219x0EHb2xA09+eQcZTP066fQ7TVY1ZZ2t8rVkfm4nEQEVwneXuruuCG7DIcXVClsVyzuHlPlv3qTKq2w0AVwUrLD/GmuBaLFTnQmR0UnyJR3DjTtctuMl5HY7oxxDgAXgEDwaK/el9IjEVDHIsXxa9SuSppQpuvC15tgoJJxiw16hE0+xX80VSZUgIId0ZBYCEENt4MIjQnp0wG+rBZAXSoCEQC9qetJL0wRwOqKUzoZbObPXvxtkz0Nas6vwBggH4P3kfnkefiNEMSUt2q5mkFApB7Cyr9SOAA/ohjJFHxXBG7bO6PLClw/pRjFVGt/n3nSGLjZEA1PF6nDROob9UbPv5053KVIyQhyV6GqQb2bZZa6943jJJAlxuhiHDJJTOVFEch73/osXttvcd6HAySBKg21glnRFBExZCCOnOUuevCCEk4XgohMCSTxBcXwEEWh/RSoOGwHHjrZD6FEX8+EwUAVkGQtb3sGLZydv5UuxZ2LxxkMUqQKFnYdJV/3UmuLbc8lh9/14YF6sh9gi/HxfpukGiveXWA22OTyQv99obb9qrwosW00ob0SsI7WzNbHITfthLEHw2ln+nMs45AgiAgUGFGlHoSkgsnT0dQfeMr4gS8MvfZloOufw+E+fOmjAMjtw8Ebm50T2esHE4AwDI62nv+UWRYcx4GVs3WTsGLB4gIifKrzHaGhtNBHwcLjeD25PccyWEdA8UABKSJjjnME6fglldBQgMYp+iqAYtXA/B+8JfoB860O7t+uGDaHr6v+F57AlIAwdH9hymae/SL5qXlyI3OUNAITMT8qgxCO3aYWm8Om1GjGcUffrhg9YHcw7jyCEKAOOgr9QH/cViHDOOWxo/U50e4xlFj5M50citNwByssR0iRQiCPN7iD3aPg4T4IADARshoCvB3Y9jrc6sR3mwEmu1DWjgjQCAPKEHZijTMEOZBpeQ3q+fpA47gdmVJk1RLIV/1VUGli8NYssmDXqL7GzwUAlzF6gYNlKOfBItSJKt67NgzP53YNkc1XIAWDa7a1s76DrHnp0hnPkqpO1ZIGLMOBmy0rULCabJsXlDCJXlQZw8/nUAPHCwiLLZKsaMl+liBSEkYSgAJClLP3kc2roKGGfPAJxDKCiEOrUUYv+B3e4Pq7ZtC4LLl8I4c6rVv0tDh8Nx9SJIxf27/ByBJZ92GP5dFtLgffl5ZP7if4GpERyYmYbto2UeSu4Os+q8qxHau7vTTsAsJxfK5KlxmlUU2TkbQHMVKYmPW5yL8KemZ6F3sl/ebKUMBWLPOM2q60bJI3AhWGVprAIZQ6TILkhEQy5yUINay+MnyyXt/vtYeRQ2hDZbeoxsloUisa/l50w1h/Wj+Kv3722qHKvNi/gw8ClWByvwpOdbKfUzTdJXz4LItlcYMEjETbd3HmSfOKbjuT974fe1PXY6dEDHoQM6brjFgdnzu34hpKBQxKmT1isaexbYDwCL+0u47kYHFn8U/oLHtBkKxk+MLNjknKOyXMMXnwXQ2Nj6fXO6GObMVzF3oQpBsH8uoYc4XnnBiz272l7MPnLIwJFDPkyepuCOe5wRPT4hhHQV1SKTlMODQTS9+Dc0/c9/QVtfCePEMRgnjyO0aT2anvlveJ/9E0yv9eqQVBf4Ygl8r/69TfgHAPqBfWj68x8Q2m2tAq0jPBhEcJ21Tei5twna1k0RPQ+T5OZLzHbuk5kV0XPFi9SvGK77Hmpey9MBlp0Dz2NPgDlSr2rF7vsvZCX355VOBkkD8Jj7QTjQcRhfpkzHrc4bLv93vdmAI/oxHNdPIMiDHd4vkWYq08Fg7cRpsjIxodVgCxzWu3oXCX2gCu1/VrNU69XBZer0tG1sUWVU49mmF8Iuca7ldXim6Tn4ErT0m5CWSibLkG3kVC43sOAaFd960gOlk0o0n9fEC8+2H/619PH7AezdHfnFN7+fY83KILxe69saZOcw5EcYfs67yoG77nMiO6ft63d7GK67yYHbvuGM+GL/558G8P5b/jbhHwD4fRyffRzAe2/6wSMo33z/bX+74V9LG9dp+PzT6DWGIYQQO6gCkKQUbhjw/v2v0A93XImmHz4A73PPwPPED8EUJY6zi7/Qnl0ILPkk/CBDh/fVF5Hx019BzG27vMzS8+zbAwSs7ymlbdkY+XJWm/tmpcL1U2XMeIg//DmC5Sugbdl4uWqOZWZCmToDatlsCG5PgmcZGWXCZPiPHbE0lrk9kIaOiPGMSEuj5BH498xfYJ22AZtCW1FvNkBhCoZKgzFTKUU/qblS7EDoEL4MrsQefT84mk96FCiYrEzAQnUu8tpZmpooPcV8LHJcg48Dn4Udly/k4QbHtXGaVfvsNFfJEjruZt5f6oeF6jwsCy4P+xgDxf6Yp862/Jyp5ovgSkv7IdbwWlRo67HQRgBLSCy4XAJmzFax8ovOL6gMHiri0Sc8kCRrRzbr12rwNlkLqVYsC2DEKPsVc/v3hvDq333w++2FYQ31XevOO3maiolTFOzbo+PMKQOcA/kFAkaPkSHJkR/5HT6o44slnX8W6yo0DBkmYdwE6+cRNTUmNqy1tipl9Yog5ixwwOlMhaNYQkg6oQCQpBRt84aw4d8lxqmTCFauhmPOgjjMKnGCq760NjAUglZZDueimyN6Ht5Yb298g73xl++nh2wHgGZDPcSeBRE9XzyJhb3guuMeOG++o7l7siiCZWalXNOPKykTJiPw+afgFqpulellYHZKIUhUeAQ3FjjmdliNtjpYgbf9H1wO/i7RoKFCW4etoR34rvsxFEuRN/iJtqvUeVCYgo/9n0FD2xOuweJAPOi+Fx7BnYDZfa1CW2d57B59PxrMBmR2EATe6LgWLubAZ4Ev2rxmBoYJ8jjc47oDCkvP37EgD2KjZm0ZNND83i9Q53S7LUFI8rn2Bgfqak1s29xxFd7goRIe/rbbcvgHABsthk1A8/LTqgsG8ntavyhx9LCOv//VC8Pe1swAmg/ldu8MYtSYyPfpEwSGkaNljBwdve+0NSutV7avWRW0FQBuXBu0vItNSAO2btJQOrNr+xgSQohdFACSlKJVWu84qq1dA3XWvJQPWDpi1tTYasCgbVofcQAI2WYlZaSVl4L95SJmU2Nkz5UgTJbTqgkGczjgfuBRND3/Z0Dr+GREGj4SjoWJrcYibe0LHcBb/vfDjvFxH571voBfZvw04YHaJYwxzFVnYpoyCRu0zTisH4MOHTksG1OUiUkRVnLOcco4Y3m8CRNnjHMdBoCMMSx0zEOZWoqN2mYcN07C5CbyhB6YqkxKqirNWKgyL0KD9WWM1eZFBBCEE4lpAkPIJaLIcM8DLgwfGULF6taNIQoKBZTOVDF1hmIr/AOA6ip7F0wvVpuWA0DOOT58xx9R+HfJ9q16lwLAaAuFOHbvtP4dcvSwgYZ6E5lZ1s4jzp2x93mcOxt5h2hCCIkUBYAkZXC/H8apE5bHmxerYdbWpFXY0pJZW2NrPG9qBA+FIqrAkgYNsTVeHjzU9nMAzUu8bd+nsSGi5yLRIw0cDM93f4TAJ+9DP7i/1W3M5YIyfSYcC68FE9NzX7JUtiy4wtK4Rt6EddoGW3vaxYOTOTFbLcNstSzRU2mXCXsnhFdWYbbHyRy29gRMF5zbey8v34cKAEkSEASGSVMVTJqqoK7WhNdrwuFgyO0hoLGRo3J1ELU1JkSJof8AESNGyxDF8D+8gmBv0YSd6+Enjxu2Gn60J2hz2XCs+X3c7iITNDVyWN7qOMm+awyD48A+HVXnDTCBoU9fEQMGiVQVTUg3RwEgSRlci2BD+mBybmIfFTabZQCwd/TXgpiXD2nYCOj791oar0yP8GQ8ghM8sPSs8Ew1Up++8Dz+FIyq89CPHAZCGlhWDuThI8DsVpCSuLho1GC/br2KuDIJA8BkxhiDAAFGJ12YW5LosKxDPYRcCBAsh6oZzAMHo+o/knyycwRk5wgIBjneft2PTeu1NsFUVjbDDbc4MX5ix38/+/YTceyIte8XQQB69bF+Ee7wwS6U/n0lIzO5giZFtT8f1cZXSGEvATu32Rkfm4uinHNUrNawYlkA9XWtQ9iehQKuvcGBMePouIyQ7orOnEnKYC637QCLZWTEaDaJJxb2snVkIhb371IFlnPRLZaeT52zAGJ+ZHvyCYpq+zOWivtH9FwkNsT8AqhTS6GWzYEyZhyFf0nsgllta3yVWQ0zkpC+m+Kc264A1NH1k+505RJcGC+PtTx+ujIVAl0gIkkqpHE8/+cmbFjbNvwDgPo6jldf9GFdRccXsqeXWV9eO3a8jIwM678PocibBl82aEhyXdBwOBiKB1g/Ds7LF5CTa/09mzJdhdXiOkUBSiZF//iIc46P3vXjg7f9bcI/ALhwzsTLz/lQWZ7GBRKEkLDoyIikDCbLkEePszxeGjwUQkbHXRVTHVNVKBOnWB6vTp/ZpecTe/WG5/EnwTI7fk/VuQvhuO7Grj3PwMHWB7vcEPv269LzEdJdCTbXK7Gv/kess/t+CXRYFtZCdQ5EdH4C74QDs9TSOMyIkMh8uTSAo4c7r957700/Lla3P27cBBl9ijr/fVAUYP419qphs7K7/l3fIy/5tv2w03SjdKYCQbD+PuTkCpgy3VqoN2ueGpMOwDu2hVC+svPmMO+/5ceZ07QHISHdER1pkpSizpxjfWyZ9bGpyjFvoaUqR7Fff8jjJ3b5+aR+/ZH5r/8O1ze+CWnocAgFhRD79oM6ez4y/uXf4Lz+pi43XXHecKvlseq8hbSXCSER6i0W2gqcisQ+9PtmA2MM/cS+lscLENBLLIzhjJKLyU14TR80br2TaR+xN77p/EbYENABBx73PIxswerGXYTElx7iWLvG2s+9aQLrKtofK0kMj3zHjT59w/w+OICHHnejV297YdzosTKkLjbfLeiVfH8vSibJGD6y88rE4gEipkfQofeWO5wYNSb840+ZruCq62KzPUH5CmuVfZwDFauoCpCQ7ii5arMJ6YQ0YBAc1yxCYMknYceps+ZCGjUmTrNKHCE7B55vPYWmF/4CXlfb7hix/0C4H/oWWCR7BraDyQqUSVOhTJoalce7ktSnLxyLbkbgkw/Cjxs5Bo7Z82MyB0K6gwwhA+PlMdgS2m5pfJkyPcYzSj8zlGk45rfWvGqcPBqZQvpuW3HJOeM8VgbXYJO2BQE0n4AWiX0wUynFZGUiZNb6b1WAB7BO24SK4FqcNc8DALJZNtzMibPm+cvLrBXImKRMwEJ1LvLF9Gz+RdLDkcM6vE3WG2Ts2BrC9Tc5270tM1PAkz/2YOsmDWvXaDh1wgDnzRV8U6YrmDZDRVa2/Quzbo+ASVOUDsNHKzZv1FFallxVgILA8MCjbrz1ug9bN7W/znnEKAn3POiGLNsPMCWZ4YHH3Ni6KYTK1UEcP/Z1ld2goRLKZikYPU6OycW0mhrT8p6QALB1k4bbvuG0VeVICEl9FACSlONYcA1YVjYCn3/aJvRiGZlwzLsKStnsblOpIvbqjcyf/gra1k3Q1lfCvFgFMKG5Mm96GaSRo7tclRdvjjkLwLJyEPjo3bZdfhUF6uz5zV1lu8lnTEisXO1YgF2hPdAQfsOnXkIhJiolcZpV+piklGBp8EtUmRfDjhMh4BrHgjjNKnE2aJvxqu/NNnsjnjRO43X/26jU1uPb7kfgEdwAgAtGFf7sfR7VV7x/dbwOdbwOGcjAba4bUSDkI1/Mo6YfJCXYCf8AwOsNv5eoLDNMma5iynQVpsnBOTrtIGzFDbc6cfaMgeNHI1sqWtPB0uVEkxWGex90Y/7VBtZXajh72gAH0LNAwNRSBX2LunZ6LAgME6comDhFgbfJhN/P4XIzuFyxPRZvrLe356ymNfdKdLafLRNC0hQFgCQlqZOnQZk4Bfr+vTDOngHAIfQsgDxidJcaXaQqpqpQp82AOm1GoqcSNWrJRCjjSqAfPgjlYhUYmrsRa8UDweQurkshhAAA+oi98C33Q3je+/Llaqwr9RIK8ITnUSiMfu/s0riOGrOu03EGTFwwqtBH7B37SSXIvtAB/MP3Bjg6Dj+OGSfwnPclfN/zHQR4AM94/4aLZvvV7QDQiEa86/8QP8/4IYV/JGk0NZrYuE7DkUM6dB3IyhYwcYqMwUMlMMbgsLn3m8NhfXw0q7lUleHxpzxY8nEA69cGEQzYu3+sA6+uKuwl4qbbYpt+uT0C3J6YPsVlsmL/s6fDaUK6HwoAScpiggB5xCjII0YleiokRpggQB4yDNlTpkEURRiGgdrajk8GCSH2DZeH4peZP0V5sBJrtY1o5I0AgN5CL8xUp2OqMgkKo27OkXg/8BEMWKuCedf/EUoU642uUs2ngc/Dhn+XHDaOYp9+ACeN02HDv0saeRNWBFfjFucN0ZgmIRHjnGPFsiA+XxyAcUVD703rNfQpEnH/Iy4MGCRBVZurr6wYPjJxKY2iMNx4mxNXL3LgP35TD5/X+n0nTqF0KZ4KCgVkZDA0NlqrMB0wSIQk0UoaQrobCgAJIYSQbi5HyMaNzutwg+NaaNAgQGyzFxuxb4tmbX9FAKjj9Tijn0VvqVcMZ5QYp42zOGoctzy+PLgWp40zlsev1TZikeNa+pklCbXssyCWLu64TO70SQN//kMTvveTDEycoqCy3Nr+eqWz7DejiDZVZbj6egfef8taGWB+AUNWdvdbkZNIosgwdYaCL5ZYS5anlyX+54oQEn90pEQIIYQQAM2da1XQSUE0mKYJDfY20N+t70vTANB6mAcAJ41TqOP1lsf7uA81Zg0KxJ52p0biKBjk2LU9hKoLBhgD+hZJGD5Kisp+dYlWdd7Ass86D8fq6zgWf+THjbc6cWCfjuqq8Pu2zVuoonef+AVpVRcM7NoegtfL4XAwjBgloc9Xe+L1LbI+j6J+dIqZCLPnqdi+NYSq8+F/roYMkzBuAlVoEtId0bczIYQQQkgSMLi9TdxThWnzdVlZKtzmOZCe7106ME2OZZ8FUL4yiIC/5S1BZGUzXLPIgcnTUvvCQ+UaDdzij+22LSHccIsT3/m+B6++6MXRw223CRAlYOE1Dsy/Oj7vS12tiXf+6cO+Pa3XLi/5BCgeIOL2u12WKxYBYM+uEIJBDlVN/XA3EUyT48J5E34fh9PF0LNAsLS/o9Ml4NtPefDi37w4daL97SdGjZVwzwPutAjeCSH2UQBICCGEEBJlgiBAhGh5D0AAGCgVx3BGidNTzLc1vkDoiaChIQBryw0liMgWsiOYGYk10+R44x8+bNnYfqfx+jqON1/1o6mRY+7C1G3ksm9P+E7qLRk6cPigjnETFDzxAw9OHDewaZ2G2hoTksRQPEDE5GkKPBnxaaJRW2Pi6d83or6u/QTz+FEDz/y+EbCRFwX8wIljOoYMoyozO3Sdo7I8iMrVWqvq0Lx8ATNmqZg+U+l0376sbAHf+4kHB/bpWF+pofqritvefSVMn6mgX7EIxij8I6S7ogCQEEIIISQGhktDsFvfZ2msE04MlQfHeEaJMUAsRqFQgHPmeUvjZ6jT0Es/hlXaGkvjS+RxcFIX4KS0ab3WYfjX0qcfBjB4qISi4tQ8NQn67VWtBgLN4xljKO4vobh/4l73W6/5Ogz/LgnY7ADcfB/7lbzpyjQ5amtMhEJAVhaDs50OyZrG8eJfvTi4X29zW3WViQ/f9WPv7hAe+pa7046/gsAwfKQctQYyfp+JUycNhEJAdo6AXr0FChEJSVGp+VeWEEIIISTJ3e68GXsa/9PSktYFjjmxn1CCMMZwtWM+Xva93unYAqEnxsmj0U/si0ptPUIIHx4JEDBPnRWtqZIo4pxjzSrry0YrVgfxjW+m5qmJO4OhocF64OXxxKe6rzPnzhrtBk7R4KBMHn4/R8WqINauCV4OWRkDRo2RMWueioGDv/55f+9NX6efxYF9Ot5/248773W1e/vJ4zo2b9RQV8shS0D/gRImTlHgcEYW1tXWmFj2WQBbN2kItfgq7tVHwKy5DkyaKlMQSEiKSY6/PoQQQgghaSZfzMN9zrs6HVcijcXVjvlxmFHiTFYm4HrHVWHH9BBy8B33I5CYhHwxD4+4vwk5zLVqAQLud92NIqlvtKdLoqC6ysSZU9aXwG/fEoJppmbV2LgSxfJYhxMYMjw5gs4d26wvXbbr3NnuvS9nXa2JP/5XI5Z8EmhVYck5sGtHCH/+QxNWL28uraytMbF5g7XPYtN6DXW1rd/b+joTf/5DI/7nv5qwZqWGXdtD2Lo5hPff9uO3v6rHmlXWOgO3dPaMgf/5r0ZsWNs6/AOAs6dNvPmqD++/7Qe3uvklISQpJMdfH0IIIYSQNDRVnYQeQi7e8L+Dc+aFVrd5mBsL1XmY75idoNnF17WOq9BPLMLy4Grs1w9e/ncPc2O6MgXz1TnwCO7L/z5aHokfe57C0uBybAvtvNzog4FhtDQSCx1zMVDqH7X5cc4vd25WoFBlSxc1NdoLBkIhQNPiVzlmmhz7duuoXBPEiWMGDIMjt4eAyVMVTJqmwNXOMs2OTC1V8OXngTZBSbtjp6tQOlnCGS9NjbEL6c6cth7+phvD4HjhL02ouhD+/f3ovQByegg4d8a03ETGNJtDwAXXNP+iNDWa+Mv/NHXYUToYBD5424+QZn2fzZDG8fdnmzr9Ha5craGwl4jSmandxIeQ7oQCQEIIIYSQGCqS+mCmWopVwQpcMKsAAC7BhanyJJQoYxI8u/gaJY/AKHkE6sx61Jv1kJiMAiEfEmv/kLSv1AcPS99Eo9mE8+Z5cAA9hXxkCZlRm1OT6cUabS0qgutQy+sAALksB6XqVJQp01uFksQ61WEv5GIMkOPUM8Lv53jl+bb7rZ09beKj9wL4cmkQDz/uRvEAa6dKGZkC7rrPhdde8oUNcvr1F3HV9cmzNtYRwy69ZvfN/7Brewhnz1gLV5d9FkRBob3Pobrq6zf3s48DHYZ/LS3+KIAx42Xk5Yudjt22RUNtjbVEctWXQUyboVjqUkwISTwKAAkhhBBCYqTWrMMzTX9rU/3nM334MrgK5cG1eNT9AEbKwxI0w8TIFrKQLWRZHp8heJAheKI+j1P6aTzjfR6NvLHVv9fwWnwSWILVwQo84XkMfcXeUX/udFdQKCArm3XaYOKSIcMkiGLsQwTT5Hj5OS8OHeh4vzVvE8dzf27C936SgZ4FnQcmADB+ogJFYfjwXT8uVrcOZEQRKJmk4JY7nVBjGLrZNWykjOXL7C8PtcKZPDknACAU4ti5LYQTx3QYBpDTQ8DEyQqysqO/I9b6Sut7X545ZSAry9rP2CWXwja/z8SWjdaei3Ng7RoNN9ziDDuupsbE559a7/pysdrEkUM6Bg+ljs+EpAIKAAkhhBBCYkDjIfy56bk24V+rMdDwnPcl/NjzJPpKfeI4O1JvNuAZ73No5E0djmngjXi68W+4330X3MyDfCEPLiH8CTRpJooMU2eoWGoxTCidFZ9lhHt26WHDv0sCfmDZ4gDufch6BejIMTKGj5JwcL+Oo4f15q6p2QLGTZSRmZl8W68PHCyioJeA8zHYr6/WYvAbD+srg1j8UQDeptZzWvJxABMmy7jlTldUg9nz5+yVPzZ3BbZ+n959mwPDQwd1S8vOL9mzK9RhAMg5x+efBvDl50HLy5EvqbnYvfd7JCSVUABICCGEEBIDm7WtOGue73RcCCF8HvwSj0j3x2FWkdG5jh2hXdiobUUdr4MMGYOlQShTpyJXyE309CKyMlgeNvy7pAlN+LP3BQCABAkT5HFY6JiLXmJhrKeY8mbPU7Fre6jTZiBjxssYOTo+pyVry61XvO3YFsKNjSYyMqyHd4LAMGyEjGEjkr8iijGGO+524dk/NUEPEyQxBtuhEE+Shi4rvwzgk/fbD6Gb99MLobqqCY8/6YGcoL0ZBwwSsXNbyFKYJyvAxMnNP1t+n733OODvePxnHwewfGlk1aDxqNwlhERH8l2KIoQQQghJA2u0tZbHbg/tQoPZEMPZRO6UcQa/bfxP/N33Knbqu3HSOI0jxjEsDX6Jf2v4P/jY/1nKdYI0uIG12gbb99OhY0NoM/6r8X+wJ7Q/BjNLL6rK8PiTbgwe2nG4N2W6gnsfcMVtD7HjRzuv/rvEMIDTJ9N7M7v+AyU89l0PMrPaf/+dTob7HnbZftzs3MSfZp4/Z+DTDzqvQD12xMCKL6K3FLpXb3tLevv1lzBngbUK2LkLHV9VDAJut7332OVq/zOuOm9EHP4BQFE/e6+XEJI4VAFIuiXj3FmYF6sBSYTYuwhCRkaip0Q6YDbUw3fqBARwCHk9AQctvSKEJD/OOU4YpyyPN2HijHEOmVFsbhEN540q/LHpL/Bxf7u3c3B8HvwSJjhucl4X59lFrs6sRxP3Rnx/DSE8730J/5rxY+SLeVGcWfpxewQ8/pQbJ44b2FCpoeqCAUFg6NNXxLQZCvIt7rEXLbrNPE+3nhcmXMDPsXWzhrNnDIADBYUiSibLnXY0HjRYwi/+VyZ2bgth5/YQvE0cDicwYqSMkskKVJXhH/DZmkufPokPhSpXW1/OunZNEPOuUiFJXQ+ip81QsG+PtR+comIRffpK6NVbhM/LUbG64z39yuYoWHjN10Hh4GESHA4gYHHLvjHj269KXbvG+p6FVxo0VELPwsR/1oQQaygAJN2Ktn0Lgiu+gHHqxNf/KAiQx46HY+F1EAtoOU+yMM6cQmDpZwjt2YkG8+u9RcTiAXDMuwryqO7VOZMQkno47FXF2R0fD+/7P+4w/GtpWXA5pimTUCD2jMOsus5E1/es0hDCyuAa3OG6uesTSnOMMRT3l1DcP/GnHrm5Ai6ct/755yZBJVtnTJNj2WcBrPoyCO2KLOeTD/yYOUfFNTc4wlZZShJDySQFJZOUqMzp3LnE7wu3c7v1DfIaGziOHzMwaHDXf0ZHjJbRt5+IUyfCp82MAVdd19wtRRAYbrnThdHjZFSu1rBnVwiG0dxAZuQYGTNmKW0abagqw+RpCspXdh7giSIwbUb7VYYHD9jYSLDlY0rAtYuSrNsLISSsxP8VJiRO/Es+QfCLJW1vME2Etm1BaO8eeB79DqQBg+I/OdJK6MBeeF/8G9rbDMU4fhTeF/8Kx/U3wzF3QQJmRwghnWOMgQG2Ir1kW0ZbY9Zgt77X8vg12lrc5rwphjOKnmwhCwpkaIjsxPeS9dom3Oq8ASKjCphUMWmqgsUfWSuZ6t1XRK8+yR0Acs7x3pt+rKtoPwQKhYDly4KoqzNx9/0uMBafpdaCkPjvM5/X3hx83uiElqLI8PC33Xju6SacPdP+YzIG3HaXEyNGtQ71hgyTMWSYDNPk0DRAURA2uL16kROHDxmd7rN5611OZOe0/7OsRbD6V1aAbz7kRv+BFCcQkkqS+y8aIVGibd/SfvjXUjAA74t/hentfENwEjtmfR28Lz/fbvjXUuDTDxDatydOsyKEEHs4t1/Pd9Y8F5O5ROqAfthWVeL+0KEYzia6ZCZjsjKxy48TQAANvDEKMyLxMmW6AqfTWgg2Z74at8AsUnt26R2Gfy1t2RjCts1dC7ztyM5JfChu9XO+xOGI3medmSngyR9n4MbbHMjv+fUptyQBE6fI+P5PPZhW1vG+f4LA4HCwTvfGdDgYvvM9N8aWyGjvRzUjk+HeB12YWtrxc2Vk2nvdY8dL+JffZGLkmORvdEMIaY0ie9ItBFd8YWkc9/mgbVgLx9yFMZ4R6UiwshwIWrsUGVz5BeThI2M8I0IIsS+Saj4dybXZmMbt7QsVRPQ20Y+HueosbNA2I9TFKsDmWk+SKjwZAh78lhsv/KWpzXLZluYsUDFhcnSWw8bSmpXWf+8qVgcjXuLrcgM+G9tmTpiU+HBoxGgZG9Za+x5zuRj6D4juqbGqMsya68DMOSq8TRy6Drg9DLIc3e8Mp0vA/Y+4UXPRwJaNIdTVmpBkYMAgCaPHyp126S2ZqODYkc63egCat+K+65tuqCp97xGSiqgCkKQ94+yZ1nv+dULbuC6GsyGd0TattzxWP3QAZk1NDGdDCCGREQQBgs3DrGKhX4xmE5lMZq8hSSZLrYZahWJPPOL+JuQuXA/PZBkp97oJMGiIhKd+nIHR49pWTfXqLeDu+11YdHPyNx0L+DkO7rd+4eDYEQONjZEuc7UX+Jw7l/glwKWzrIedU0oVyEpsQi3GGDwZArJzhKiHfy3l9hCx4BoHbr/bhZtvd2FcidJp+AcAE6cocHbQIfhKU0tVCv8ISWFUAUjSnllzMabjSfRwXQevr7N1H7P2IoTc3NhMiBBCumCoNAj79IOWxqpQMEweEuMZ2TNCHgonHPDD2n5pE5WSGM8o+kbLI/GTjO/ji8AKbA1thw57LWJnKNMgMLqenop69RHx4GNu1NeZOHXCgGFw5PYQ0KdITPplv5f4fPbDPJ+XIyOCzFoLJmY/va7oWyRh3kIVy5eFr5Ls1VvA/Ku7bzMLh5Ph/kdceOFZL/QwBdEDBom45vru+z4Rkg4oACTpT7S5B4lIvxYJIwjNuyLbWTpn9/MlhJA4ucVxA/5P0+8tjZ2tliVd6KAyFTPUafgiuLLTsU7mxNQo7KmXCH3EXnjAfQ/uMG9GlXkRjWYT/uF/A14efr1jJsvELLU0TrMksZKVLSArOzVDXLt73AGR73PndDI0Nlo/Povmfnpdce2NDqgOhmVLAu2GW8NGSrjnfldE72U6GTJMxne+58GH7/px4ljrCyGK0rx35vU3OWNWJUkIiQ9KOkjaE/sUNQdLprUrkVK/4hjPiHSECQLEvv1gnDxu7Q6yArGwV2wnRQghEeoj9cYtjkV4P/BJ2HGDxUFY5LgmTrOy5zrH1Timn8Ah40iHYyRIeNj1TThZ8i+ZDMcluFAsuAAATwqP4c/e59HI228MlsUy8YTnMWQItPyXJI7TJaD/QBHHjlirXO1TJCIzK7IAJ9H76UWKMYb5VzswvUzBpg0aThw1oBtAbg8Bk6cq6NWHLnMu1ssAAGVwSURBVCRfUjxAwvd+koHTJ3UcPqQjpDUH5KPGyt0+ICUkXSTHNzMhMSRkZEAeOx6hbVssjVeml8V4RiQcZXoZ/BYDQGXCJDBHap9wEkLS23zHHGQL2XjX/wEargiTJEiYqU7HLY4bknYZqcJkPOF5DB/6P8VabT20KxpmFItFuM15EwZK/RMzwRgpkvriFxk/QYW2DhXBdajldQCAHkIuZijTMEOZBvdXYSEhiTRjlopjR3yWxpbOVCKuNC6dpVgOACdPj91+epFyuQXMmusA5iZ6JsmvT5GEPkUUExCSjhiPpE0dSTrV1dWJnkJSM86fQ+Mf/z8gGH4fI3HAIHi+/T0wWlaaMFwPoelPv4dx+mTYcczlhuf7P4XYIy9OMyOEkMhxznHIOIKz8nkYMFAoFmBQaAAUlvhOmVb5uR/bQ7tQbzZAhozB0kD0k/omeloxxzmHhubgQ0HkAQohsWCaHP94wYed2zvvZl3Yi+HeBz0RV719+qEfKzrZT69noYCnfpxBFWMkbeTl0bkGSR8UAKYJCgA7px89DO+LfwX3tX+VVBwwCO6HvgXB5Y7zzMiVzMYGeF94tsPuzSwjA+6Hvw2piJZrE0JSS05ODkRRhGEYqK2tTfR0CCFpQNc5Pnjbj/WVWqfbKDudDN/9kQeFveyHgEs+8eGLJeGrAAt7C3jyRxlJswdgPFVXGai5aEKUGHr1FuByJWdlN7GHAkCSTigATBMUAFpjepugbVgLbeO65m6/ogipX38o08sgjxpLlX9JhOs6Qju3Ibh2DczTJwHThJRfAHHSFCiTpkFw0dIrQkjqoQCQEBILeojjt7+uh7f9bStbKe4v4qmf2Nu/8swpA7//fxstjZ23UMV1N3WfLVr27AxhxRcBHD389V6MkgyMn6BgwTUq8vLp/CKVUQBI0gkt7ifdiuD2wDF3IRxzFyZ6KqQTTJKglEyCUjKJTpgJIYQQQsLYuT1kKfwDgOPHDJw6oaNvP+ungpXl4Zf+trR+rYaF1zkgy+lfBfjl5wF89nHbLYb0ELBpvYbdO0N47Ak3+vWn025CSOJRXTIhhBBCCCGEpLDdOzvfA7Ar43ftsNYABAC8TRzHj+q2Hj8V7doRajf8a8nv43jhWS98PjNOsyKEkI5RAEgIIYQQQgghKczvs7erk99vb7zPa2u47cdPRSuWhg//LvE2cWy02EGZEEJiiWqRCSGEEEIIIQSAz2tiy6YQqs4bYALQu4+IcRMUqGpky1nrak2cPdO8N1zPAgE98mKzH5zLZW9+se7SazeQjKbGBhPnzhrgJpDXU0Buj+i/5+fPGTh+zOh84Fc2rNUwe74j6vMghBA7KAAkhBBCCCGEdGuGwbH4wwAqyoPQr1gd+9F7fsy/yoE5C1QwZi04O35Ux7IlAezfo7fqzDtkmIT5V6voUyRh/54QvE0cDifDkOESMjMjX5w1apyMrZutL+sdPU6O+LmsiDQw7Yozpwx88XkAu7aHYLZYcTtkmIR5V6kYMix6r/lilb0lvReraQkwISTxKAAkJMlxXQdvagRECczjsXzgmS64acKorwdnAFzuRE+HEEIIIWnGNDlee8mHHVvbD9ACfuDTDwNobOS48dbOu9tu36rh9Zd8MNopEDu4X8fB/TpEEa1uFwRgbImMRTc7kZ1jPwgcPVZGZhZDQ33nlXcDBono09feaaAkA5r1PiCQlfger+7fE8JLz3kRaucjPLhfx6EDOm67y4lpZWpUnk+wWVQo0MZbhJAkQAEgIUnKOHcWwfIV0LZsAkLN+4YIOT2gTC+DOr0MzNn5AWgqM71N0CrLEVxXgfr6OgAAczggT5gMdeYciPkFiZ0gIYQQQtLCpvVah+FfS6uXBzFilBS2kuz8OQOvv9x++NfSlbebJrBtcwhHD+t44gce20uFJYnhngdceO7PXhhh+m+4XAx33OOy9dgAkJfPcOaU9WW9ffrGZqlze2pqTLz8fPvh3yWcA++84cehgzquutaBnoVdm1/vviIEAa0qDcMpKqbTbkJI4tG1CEKSkLZtCxr/+z+hra+8HP4BgFl7EYHFH6Lxf/4vjJqLCZxhbBkXzqPxv/8Tgc8/Bf8q/AMAHghAqyxH4+//X4T27EzcBAkhhBCSFjjnWLPKeoOGitXhx5avCIYN4DpTX8fxygs+cG5/D73BQ2V860kPeuS1f4rXt5+IJ3/kQc8C++FXXa29+bg9tp8iYhWrgtAsfoTbNofwf3/XiFde8CIYjHyfwsxMAaPGWl9SPL1Mifi5CCEkWigAJCTJ6MeOwPf6Swh39GhWV8H7/J/BQ+nXUYwH/Gh67hnwutqOB4VC8L7yd+inT8VvYoQQQghJOzUXTZw5Zb2Zw+4dIYRC7Zd9GQbHlo1dPzY7fdLAkcPW59TSoMESfv6bDDz6hBtlsxVMmipj9jwVT/3Yg+//1BNx5ZvdLsDLLXbI7SrT5Ni4zv57vmNrCC/8pQl6KPIQ8KprHZAt5HpFxSLGjI/tnouEEGIFBYCEJJnAsiWW1hOYF85D27o5DjOKr+CGdeC1NZ0P1EMILl8a+wkRQgghJK445zCM+HSR9XntPQ/nwAfvBNqt0Gtq5JYr0TqzZUPkDyQIDMNHyrj5Dhe+8U03brjVieIBUlz3kT58MLIA065g0P5neMmRQwbWron8fe7VR8TDj7vhCNPct6hYxCPfdkMUu9ce3oSQ5ESbERCSRMyaGuj791ger62rgDplegxnFH/augrLY0M7t8FsaoTgyYjhjAghhBASicZGE5vXazh7pjkMKigUMWmqgsystjUIhsGxc1sIleVBHDtiwDSBzEyGCVMUlM5SkZsbm7oFh9N+MLO+QsPwERLGjG9d/iVF8cyqvj61u8aaZnwC3K4216gsD2LGbAWCEFlAN2SYjJ/9OhPrKjRsXBdEbQ2HIAD9+ouYXqZi3AQZkkThHyEkOVAASEgSMc6ftTf+7JkYzSQxuGHAvHDO+h1ME2bVBQoACSGEkCRiGByLPwxgzeor98MLYcknAUwrU3Djrc7LwYjfz/HiX5tw5FDrqrGGBo6VXwSxZlUQ9z3owuhx0d9HLS9fQH6BgKrz9gK31SuCbQJAl5sht4eAmotdD+9kObVDo4Je8VlopqoMPQsFXDgX2XtedcFEzUUTefmRNwXJzBJw1XUOXHWdA6bJwRjiWm1JCCFW0RJgQpKJ7Q2f43N1NalFsEk2IYQQQmKDc443X/Vh1fL2m2GYJlC5WsOrL/pgmhymyfGPF7xtwr+W9BDwj7/7cPRwF7prdIAxhtKZqu37HT1soK62dejEGItas4dBg1O7TsPjiV8X4Oll9j+/lgKB6B1LCgKj8I8QkrQoACQkiQg9C2yNF3sWxmgmicFEEUJevo07MAh5PWM3IUIIIYTYsnNbCFs2hjodt2t787iD+3Uc2Nd5sGcYwOefxqaxxPQyBf0H2g+sGhvaVp1NK1ORl9+1UyxZASZOTe2usdFcDt2ZKdMV9CyI/D13uemUmBDSPdC3HSFJRMzLhzR4qOXxyrQZMZxNYihTSy2PlUeNgZCZGcPZEEIIIcSOitXWmypUrA7aasJw6ICOc2d1NDaY8PnMdhtxREKSGB58zG37frLSttLL6WT41pPuLgVS19/khDOCvQmTSUZW/J5LVRm+9aQHBYX23/OiYjFm+0sSQkiySe3ackLSkLrgGuiHD3a6tFXI7QFlwuQ4zSp+lKmlCJavAG9oCD9QEKDOvSo+kyKEEEJIp/x+jsMHrS/TPXncQH2dvW6xf/jPJuhfPUV+gYDSMhVTShWoatcCM0+GgOIBIo4ftTafrGyG/J7tB0e5PUT88OcZ2LpZw9o1Gs6dMcABFBSI6NNPxNZNGkLt5J6CAFx3kwNls7u2pDVadJ1j144QDuy1v/T6iyUanA4Ro8fJETfYsCM7R8APfpaBLZs0rPwiiKoL1vYEnDErOd5rQgiJB8ajdemMJFR1dXWip0CiKLhhLfxvv95hCMiyc+D51pMQbS4ZThXGmVNoeu4Z8MbG9geIIlx33w9l/MT4TowQQrooJycHoijCMAzU1tYmejqERFVNjYn//ZtOLuBdwe0GvN6uPW9hLwGPfdeDrOyuVXJt3qDhn6/4LI29+noHFl7riOh5vE0mNqzTsGNrCD4vh+pgGDFSwrQyFTlJUo22Z2cI7/zTh4aGrp0qDh8p4f5H3VDaqZaMpY/e82H18vDVpSUTZdz9gCsuASVJXXl5eYmeAiFRQwFgmqAAMP3oJ44juHo5Qju2Nu+YDYB5MqBMLYVaNgdCRnp3vjXr6xAsXwltQyW476uDcUmCPG4C1FnzIPXpm9D5EUJIJCgAJOnM7+f49U/rbd2nqFjAyeNd75rbu6+I7/3Ec7mzcCQMg+P5P3txcH/4irfCXgKe/FEGHCm+TLcju3aE8PJz3qj1WRszTsYDESyx7grOOVYtD+LLz4Pw+1q/EEUByuaouGaRg8I/0ikKAEk6oQAwTVAAmL54wA+zvh4QRQg5uWBi/LqqJQOu68gwDQgAWGYW6gOx2QCcEELigQJAku7+8scmHD5gbcloUbGI0pkK3nzVH5XnvvdBF0omda15RjDI8frLXuze0f5rKB4g4sHH3MjITI5KvWgLBjl+9+uGNqFZV33vpx70K47/7lOaxrFjawhnThvgHOhZIGD8RCXl91gk8UMBIEkntAcgIUmOOZwQHc5ETyNhmCRBzsm/fMIMCgAJIYSQpFU2S7EcAJbNVjF2vIylnwVRe7HrVYDrKrUuB4CqyvDQtzw4cVzHujUaTp8yAN683+DUUgWDh0pgLH3Do62btKiHfwCwbo2WkABQURgmpXhHZUIIiRYKAAkhhBBCCCFRMXqcjIlTZGzeEAo7bmyJjJJJzQ0iHvm2G3/9UxMau7jf3NlT9hqKhNOvWEpIYJVoe3aG/9wideqE/UYihBBCois9a9cJIYQQQgghcccYw133uTBngQqpnfxMFIGyOQruffDr5guFvUT84GcZmD5TgdqFpqy0sVHX+f2xeRPNrhd4EkII6aLud1mLEEIIISTOGswGrNU24uz5czBgIl/KwwRzLPpKfRI9tZRmchO79b3Yqu1AE/fCwRwYJQ/HBHkcZCYnenrdliAwLLrZibkLVGxar+HcWROcAwWFAiZNVdrdPy8rW8Btd7lw/U1OnD1tQNc5QhrH3/9qrSsv0Ly/G+kalys2y5vz8mO/h3UwyHHssA5/gMPtZhgwUIIkp+9ybUIIsYsCQEIIIYSQGDG5iU8CS/BlcBUMtF6euBRfYrg0FA+67oVHiG+HzHRwXD+JF32votq82Orft4S24T32Ee5x3oFxypgEzY4AgNsjYPZ8h637OBwMAwZ9fYpSPCCI40etLe2dOoP2euuq0eNk7N4Z/eW6U6bH7rPxeU0s/SyATeu0VltFezIYps1QMP8qB2SFgkBCCKHLZIQQQgghMfKO/wMsDS5vE/5dsk8/gD81/RV+Tg2O7Diln8Yfm55tE/5d4uU+PO97Bdu1nXGeGYm2BddYCxB75DV3dyVdM36CArcnumFZrz4Cho+KvO7ENDkCfg5db7s8ubHBxNO/b8KalVqbPnFNjRxfLAnir083IRik9eGEEEIBICGEEEJIDBzWj2K1VtnpuNPmGSwLrIjDjNID5xyv+99GEMHw48Dxmv9taDw2TQ1IfIwYJePm251hx2TnMDz6HTcUqvLqMllhuPt+F4QonSX2yBPw8OOey/s92nH2tIG3X/fh1z+tx69+Wo9/+UE9nvnvRmzdpME0mwO9117y4cL58BsMHjti4P23rC8lJ4SQdEVLgAkhhBBCYmB1sMLy2EptHa51LITM6NCsM8eNkzhhnLI01sd92KxtxXR1SoxnRWKpbI6K3n1FrF4exO6docvNPtwehqmlCmbNVeHJoLqGaBk+UsajT7jx9j/9qL0YWfcOl4th8nQF8xaqcHvsfzaV5UG8/5a/TWOXo4cNHD3sw8Z1EuZfo+LQAWvLlbdsDOHaG0xkZdPPCSGk+6KjTEIIIYSQGNgd2md5bBP34qRxCgOl/rGbUJrYHdpra/wefR8FgGlg4GAJAwdL8DaZqK/jEKXm6jJJim/VH+cchg6IUnPH43Q1dLiMf/03Cft269i/V8PGdSFomvX7P/KEC8X9I2vEs3O7hvfe9Icdc2Cfjuoqa3tDAs1diLdu0jBngb09KaPJMDh27QhhfYWGC+eb596rj4hpM1SMGCVFVCVJCCF2UABICCGEEBJlnHMEYG9fPz8Pf8JLmtl/X2l/xXTi9ghwe+L/vGfPGKhYFcS2LRoCfkAQgCHDJZTOVDFytJSWYaChA2dOG9i1Q7cV/gFAY31ke+5xzvHZx9Z+Z2su2nuOmprIqhmjoa7WxAvPNuHsafOKf9exd5eO4v4iHnzcjQyqZCWExBAFgIQQQgghUcYYg5u54OXW953yMOoEbIXb5vtkdzwhV6pYFcQH77RejmqawP49Ovbv0TFmvIx7H3BBktMnBAz4OZ57pgnHj1mvsmt1/0BkAeCxIwYunItNUBfvatFL/D4Tf/1TE6oudPy6jh8z8PwzXnz3Rx7ay5IQEjN0iYEQQgghJAbGy2Mtj81lOSgS+8ZwNuljvDzG1vgSG58DIVfatkXD+2+33YuupZ3bQnjnjfRqMvHmq76Iwz8AYBEuZz11MvLn7EzxADFmjx1O+SotbPh3yelTBjZU2iy1JIQQGygAJIQQQgiJgVlqKRisnQTPUkshMDoss6JQLMAwaYilsTksG2PkkTGeEUlXpsnx2UfWlqNuWh/C+XOxC6/i6cI5Azu3d7F7drjENNzdzMju15mMTIbRYyPbk7ArTJNjfUX4juUtVa4Jgkf43hFCSGfoSJMQQgghJAb6iL1xk+O6TscNl4ZijjozDjNKH/e67kAWyww7RoaMh9z3QWSJqfohqe/gfh0Xq60vR123xnrQk8w2ru96FVqklXx5Pe39vhYUWjudXXSzE6IY/6W1NRebm9ZYdeGcCZ+XAkBCSGxQAEgIIYQQEiMLHHNxj/MOZLC2XQskiJiplOJx90OQGG3LbEeukIsfZzzZYSVgH6E3fuD5DnVVJl1y6oS9ECuWy1fjqbqq63vw1ddF9hjDRkjIzLIe1F1/swPzr1I7vF0QgFvucGLiFCWi+XRVKIJCSl2P/jwIIQSgJiCEEEIIITFVqk7FFGUitod24bx0ASbjyBd7YKQ+HBlCAtqZpolcIRdPeR7HWeMctoZ2oMn0wsEcGCUPx0Cxf1p2ZSXxZXclppke+R+EKJSIONTIfv9EkWHeQgc+eKfzruh9ikQMHylj5GgF4yYoqCwPYu/uEAJ+DpdHwNjxMqaXKcjLT1wVcFYWA2PWf5YkCXC76buLEBIbFAASQgghhMSYxCRMVMYjJycHoijCMAzU1tYmelppoZdYiF5iYaKnQdJQjzx7SViP/PRYXNW3n4jtW7q2B2DJ5Mj325sxW0F1lYE1qzpeipzfU8DDj7shfNVspHdfEbff7Yr4OWPF5RYwYpSEPbuslfWNmyCnVTdpQkhySY+/UoQQQgghhBASRaPHynC6rIcxU6YnZplptE2eqkDsQpmIrABDhkX+XjDGcNPtTtz3sKtN515PBsP8q1Q89RMPsrJT41R21ryOlyi3xBgwc661sYQQEgmqACSEEEIIIYSQK8gKw6y5Kj7/tPNOwMX9RQwakh6nVp4MAXPmqfhyaWRNTa6+3tHlOTDGMH6CgvETFNRcNNBQz6EoDD0LBUhSalXIDR4q4/qbHfj0g/A/R7fd5UTfovT4GSKEJCf6hiGEEEIIIYSQdsy/WkV1lYHNGzpeEtuzUMADj7nTat/Jqxc54PdzVJbb6wg8eZqMOfO7HgC2lNtDRG6PqD5k3M1d4EBuDwFffBbA2TOtG6QUFYtYeK0DI0dHvmyaEEKsYJzb3d6WJKPq6upET4GQmKE9swgh6YK+zwhJPZxzbFynoXxlEGdPfx3euD0MU0sVzF2gwulKjeWodh06EEJluYY9u0LQQ4AsA6qDoamx9Slkdg7DNYscmDSVlrCGwznHieMGLpwzADD07iOgD1X9JbW8vLxET4GQqKEAME1QAEjSGZ0wE0LSBX2fEZK6OOc4f85EU6MJRWXo3VvsNg0bOOcwdECUmpfn+rwmzp1VEdIYigfIcDi9iZ5iUvA2mQgEOFxuAU5n9/jZSHcUAJJ0QpcbCCGEEEIIIaQTjDEU9hKBXmLng9MMYwySDPh9JirLg1i7Joi62gYAgCwzjJsgY9ZcFb37dr/3xjA4tmwMobI8iJPHjcv/PnS4hLLZKkaMltJqeTghJHVRBWCaoApAks6oYoaQjp0yzmB3aC8CPAA3c2OcPBr5Il2tTjYmN7FH34fzchU448gX8zA0NAhO5kz01AghxJKL1Qb+9rQXF6vNdm8XBOAb33RhwuT06IZsRUjjePl5L/bt0TscM2OWgpvvcFIImKKoApCkE6oAJIQQQlLQWeMc3vC9i8PG0Vb//kHgE4ySRuAbrtuQI2QnZnKklU3aVnzo/xS1vK7VvytQMEstxQ2OayGy7lc1QwhJHSGN4/m/dBz+AYBpAm/8w4esHAGDBneP08x33vCFDf8AoGK1hqxsAfOuim5zFEIIsSs9d6slhBBC0tgp/TR+3/h0m/Dvkt36Xvy+8WnUmnXxnRhpY1WwAi/5XmsT/gGABg1fBFfiBe8rMLjR9s6EEJIktm7WUHW+4/DvEtMEvlwSiMOMEq/qQvju0C2tWBaEptHCO0JIYlEASAghhKQQk5v4u+9V+BH+BKuW1+E131txmhVpzznjPN7xf9DpuB36bqzWKmM/IUIIidD6Cs3y2AP7dFysTv+LGusrrb8nfj/H9i3WwkJCCIkVCgAJIYSQFLJX348LZpWlsfv0AzhnnI/xjEhHVgcrwGGt4mNVcA1M3nl1DSGEJMK5s/YCvXNn0//7zP57kv6hKCEkuVEASAghhKSQLaHttsZvtTmeRM/W0A7LY6vNizhlnInhbAghJHLUNrId9J4QQlIMBYCEEEJICmkym2yNbzS9MZoJCYdzjkZu87PijTGaDSGEdE1BL3uNigoK0/80k94TQkiqoW8hQgghJIWozF4XQZWpMZoJCYcxBgfsvfcOm58tIYTEy7QZiuWxg4dKyMtP/87mU0utvycOBzBugvXxhBASCxQAEkIIISlkhDQ0puNJ9AyXrb/3LuZCkdg3hrMhhJDIlUxSkJff+akjY8CCa7rHhaeeBSJKJsqWxs5Z4ICqshjPiBBCwqMAkBBCCEkhE5XxcDGXpbG9hAIMkQbFeEakI7OUGZbHTlcmQ2HWTiQJISTeFIXh0SfcyOnR8emjIAB33uvE4KHd57vsjntdGDJMCjtm2gwF867qHqEoISS5Mc5pS9d0UF1dnegpEBIzOTk5EEURhmGgtrY20dMhJOG2aNvxd98/wo6RIOEpz+MYJA2I06zIlTjneM3/FtZpG8OOKxB64seeJ+ESrAW7JDHOGRdQoa3FUf04dBjIFXIwTZmEUdIIiCz9lzsSAgDeJhMVqzWsqwiiob75NFKSgLElMmbNVdG3X/gwLB0ZBsfGdRoqVwdx5vTX3Y8HDZVQNlvB6LEyGKPqv1SVl5eX6CkQEjUUAKYJCgBJOqMAkJC2Nmvb8E/fOwgg0Oa2TJaBB133Yqg8OAEzIy0FzSD+b9P/4Lx5od3bFcj4vuc7KJb6xXlmxCqDG3jH/wHKtbXt3l4g9MTj7ofQU8yP88wISRzT5OBmBrgpICOLwe+vT/SUEo5zjsYGjkCAw+1mcHtosV06oACQpBMKANMEBYAknVEASEj7AjyAjdoW7A7tQ4AH4BbcGC+PwXh5LGTW/aowkg3nHC/6XsWW0Paw43oIufiJ53vIEDxxmhmx4zXfW1irbQg7Jotl4qcZ30e2kBWnWRGSeHR8RroDCgBJOqGzA0IIISRFOZgDM9VSzFRLEz0V0o69+v5Owz8AuGjW4PPAF7jddXPsJ0VsOawf7TT8A4B63oBPA5/jXtedcZgVIYQQQoh9VJdMCCGEEBIDq4OVlseu0zYhyIMxnA2JRLmNz3CTtgU+0xfD2RBCCCGERI4CQEIIIYSQGDigH7I8NoAAThqnYzgbEon9Nj7DEHQcNY7HcDaEEEIIIZGjAJAQQgghJMo45wghZOs+VAGYfEJcszU+aHM8IYQQQki8UABICCGEEBJljDFkMHtNPbJYZoxmQyKVIWTYGp9pczwhqco0OWprdVRdCCGkmYmeDrHB22TiYrWBgJ96gRLS3VATEEIIIYSQGJiolGBFcLWlsQVCT/QRe8d4RsSuSXIJPgsuszQ2h2VjoNg/thMiJMH8PhOV5RrWrgmirrYeACDLDOMmyJg1V0XvvmKCZ0jaYxgcm9ZrqCzXcPqkAQBgDBg2QkLZHBXDR8oJniEhJB4oACSEEEIIiYFZSilWBdfAROfVMXPUMjDG4jArYscMdRq+CK5ACHqnY2erZRAYLa4h6etitYG/Pe3FxerW32mhUHO4tGWjhrvuc2HiFCVBMyTtCQY5XvqbFwf3t/4e4xzYt0fHvj06Zs1TccMtDvo7REiao6MUQgghhJAYyBfzcK/rTjCEP6GaLE/ADGVanGZF7MgWsnC/624InRwyj5VHY546K06zIiT+QhrH839pG/61ZJrAm6/6cPhQ+4E55xyc07LTeHvrNV+b8O9Kq5cHUb6C9qElJN1RBSAhhBBCSIxMVSbBzVz40P8pzprnW93mYW7MUWfiKnUeVY4lsRJlHJzMiQ8Cn+CUcabVbS7mxCxlBq51LKTPkKS1rZs1VJ3vvJrZNIEvlwQw6MnmPVD9fo6N64JYX6HhwnkTjAGFvUVMm6Fg4hQFqkoVZ7F07qyB7VusNaT6cmkQpTNVSDJ9JoSkKwoA04Qo0n4bpHugn3VCSKoZJ47BWHU0DutHcU46D86APLEHBusDIDPadykVjBJHYKQ6HMf0EziiH4UOA7lCDsYpo6EwWu5I0t/6SutdzQ/s01Fb01w1+LdnGlFX+3VwyDlw5pSB9970Y/XyIB5/KhN5+XRsFysbKgOWx3qbOHbvNDBhshrDGRFCEokCwDSRk5OT6CkQEnOiKNLPOiEkZeUiN9FTIF2Ui1xMwPhET4OQuDt3tsbW+PNnFbz9z4uor+u4arC6ysTfnm7Cv/+fIrjdFALGQnWVz9b4ulqZjrUJSWMUAKaJ2traRE+BkJjJzMyEKIowDAMNDQ2Jng4hhESMvs8IIanI0O3t3bd+bR3q64xOx1Vd0LH44/NYcLUz0qmRMEIh65WbABDwB+i88goUiJJ0QgFgmjCMzv/AEpIO6GedEJIu6PuMEGv8PhNNjRyywpCVzahTaQKIEqB33gz7soP7NMtjK1f7MWe+TJ9rDBQUCji43/r4/AJGf5sISWMUABJCCCGEEEKSzsH9IZSvCGLvbh2Xmsfm5QuYXqZg+kwVikKBUVeZJsfhgzqqq0wIAtC3n4g+fdueIho2wj8ACFjfeg61NRzeJg5PBn2e0TalVMWaVdbCWJeLYcx42peWkHRGASAhhBBCCCEkqXyxJIAln7RNkaqrTHz8fgBbNobw2Hfd8GRQ9+VIcM6xdo2GFV8EUXux9T59/fqLuPYGB4YMaxEGxTibMztvMEwi0LuPiDHjZOzc3vlS4LlXqZCpAzAhaY3+YhJCCCGEEEKSxuYNWrvhX0unTxl4+XkvOLe3Nx1pDv8+eteP9970twn/AODEMQPPPePF1k1fV4716GEvGBJsnGWqKuD2UPAUK9+434VBQ8LX/ZTNVjBnPnX/JSTdUQBICCGEEEIISQqmybF0sbX1o0cPGzh0wObaVIJtm0MoXxl+WahpAm+86kN1VfN+cD3yrHfplSRgXIn1paQTpygQRQoAY0VVGR77rhu33uVEYa/Wp/9Dh0t46HE3brrdSXswEtIN0BJgQgghhBBCSFI4fFDHxWrr60HXVWitl6qSTq1eEbQ0ztCBynINN97qxMkT1htD6DowtkTC9q2hTpf2SjIwcw5VnsWaJDGUzlQxvUxBQz1HMMjh8TC43FQPREh3QgEgIYQQQgghJCbqak2srwziwF4dgSCHJ0PAuBIZEyYrcDjaVhydO2tvM7jzZ6ljqR1V5w2cPG79Pdu8oTkAbGywt9T64kWOu+5z4c1XfR2GgKIE3PeQG/kF1qsLSdcw1txJmxDSPVEASAghhBBCCIkqzjlWfRnE4o8CrQKg82dNHD6g47OPA/jmwy4MHd66eo+iidiqq7MXsHqbOAzD/j6Lfq+JOfMdyO0h4MulAezf83UnZ8aAUWNlzL9KRVExnY4SQki80DcuIYQQQgghJKrKVwTxyQcd7+Xn93G88KwX337KgwGDJIRCHJvWayhfaW3/v0sKe1P1mB12u7wKQvP/GQPs9FvJy2/+XAYMkvDodzyoqzVRdaG58rCgUERmFi09JYSQeKMAkBBCCCGEEBI1TY0mFn/UeZBn6MD7b/vxre+68PxffDhlY5+5S6bNUCKZYrfVu68IhxMI+K2NHzBYAmMMuXkMF6usJ4Cjxrau7MzOEZCdQ6EfIYQkEn0LE0IIIYQQQqJmwzoNusXmvGdOGXj2T96Iwr9BQyQMGkL1DHYoCsOkqdZD09Ky5rFul73KQWooSwghyYcCQEIIIYQQQkjUHD5gMf37yrkz9valA4CiYhH3P+ICo6TJtnlXOZCd0/n7NmSYhDHjmyv5zp2z9xmdsNFohBBCSHxQAEgIIYQQQgiJGk2z3zTCqtweAm6+w4knfuCB20OnMpHIzBTw7e95kN+z4/dvxCgJDzzmhiA0B4Uhzd5z1Fy0H+oSQgiJLaqZJ4QQQgghhERNc4OH2FSAXXWdiklT1Zg8dneSly/ix7/IwK4dIWyo1HCx2oQgAH37iZhepmLAILFVdaXdSDcYiF0ITAghJDIUABJCCCGEEEKipmSSgu1bQjF6dFryGy2SxDB+goLxEzrfE1BggGmrCzBVZxJCSLKhb2by/2/vzgOrqO/9/7/mrNkhkISwySIgIDvIJhARBMGNqxWtIGotSvnen629t9+21moVa/uzXrVVe4v7ghYVFyyi7PsiIPsqKMgSkARi9pycZb5/0BwTs50DOTnJ5PnoH8Uzn5l5z5l2ZF7nswAAAAB1pselDrVMCe01IzEpvEAvrRWvL9GQGub3npZuj1AlAIDzxb9BAQAAANQZu93QHdPjFVfLyrFt2tl19bUxIR+3dRub2ncgWIqGy0eFPuy6Y2eb0lpxnwCgoSEABAAAAFCn2rS16z//K0GX9Kw845DDKQ0Z7tLMnydo4GCX0tJDeyUZc3UMq/5GycDBrpBWDpaksVfHRrgaAMD5MEzTZIZWC8jOzo52CUDEJCcny263y+/3KycnJ9rlAMB543mGpig7y6+DB3zylJhKSLSpZy+H4uK/D/3OZPv1wnOFOpNd/cqxE66L0ZjxofcWRN07ddKvF54rUF5u1a+PhiFNujk2rN6CQEOXkpIS7RKAOkMAaBEEgLAyXpgBWAXPM6BqhQUBrV7h0efrS1WQ//3rySU9Hcq40q1u3Z1RrA5l8vICWrXMo80bSlVUdO4+GYbUs7dDV4yJUaeLWWMS1kIACCshALQIAkBYGS/MAKyC5xlQM7/fVNbpgHw+U82a2ZSYxIxFDZHPa8rjSZBpGmqebJPPlxftkoCIIACElfATDQAAAIAGwW43lN6aBSQaOofTUGqaq9wPGtGuCABQGwJAAAAAAKhDXq+p3Tu8Ov2tX9K5RVF69HLK4Wj8i5gEAqYOHvAp69sc+f2GWqbYdXE3U7Gxjf/aAMDKCAABAAAAoA6YpqmVyzxascSjosKKMy0lJhkae3WMho90NdrVjHfvKNW/PiyptGCLyyUNG+HWhOtjLBFyAoAVEQACAAAAwAUyTVMfvles9atLq9yen2fqw3eLlZcb0ITrYuu5ugu3aYNH775VXOW20lJp1XKPvv3Wr7vuiZfdTggIAA0Ns+oCAAAAwAXavdNbbfhX3rJFHh360lsPFdWdM9l+zftn1eFfefv3+LRqWUk9VAQACBcBIAAAAABcoLUraw//gm1Xhd62IdiwtlSBQO3tJGnhxx699Vqhvjnii2xRAICwEAACAAAAwAXIzwvoq4OhB157d3lVWmrW3rCB2P5FeIHlti1ePftkgRZ9UizTbDzXCQBWRgAIAAAAABegoCC8kCsQUKVFQhqy/Pzzq3XJpx6tC2FYNAAg8lgEBAAAAAAugNt9HvvENJ6FMhx2yX+eI3oXLyzRkOEuOZ2Rv16v19T+PV6dyQ7I7jB0UQe7Lupob7SrLgNAXSIABAAAAIALkNzCptQ0m7JOhzZRXvsOdsXGNp5Qyuky5PGcXy/AokJTu7Z7NeAyVx1X9b1AwNTyxR6tWelR4Q96Y7Zpa9M1k2J1SQ9nxM4PAI0BQ4ABAAAA4AIYhqHhI0PvBhhO24bgfMO/MseP+uuoksoCAVP/fL1Iny0oqRT+SVLmiYBe+nuhtm1hKDKApo0AEAAAAAAu0NARLnXsbK+1XbfuDg24rHH1RrvQdTwCEVwIZMPaUm37wltjG9OU5s4p0tmzIS5lDAAWRAAIAAAAABfI6TR0988S1OPS6mdZ6jvAqTvviZfd3niG/0pSTMyF7Z+SUnswej4CAVNrVnhCauv3SRvXhNYWAKyIOQABAAAAoA7Exp4LAY8f9enz9aX69pRfhmGodRubhlzuVus2kQnCIi0QMCSdXy8+h1PqPygyPR5PHPMrOyv0Xn1bt5Rq4g2xEakFABo6AkAAAAAAqEPtLnKo3UXWedUqvYA5AIdd7lJ8QmQGnuXlhVdXXm7khiIDQENnnX8rAQAA+Uyftnl3ap1no77xH5VfAaXaWmqoa7CGuQYrwRYf7RKbHL/p1zbvTq31bNDR3OPym36lOVM02D5Qw1xDuCcAGjyX25DPF354dmlvh66ZFLked64wFxZ2Na61VwCgThEAAgBgEfmBAv2j8GV94z9W4fNvA1maX/KJlnlW6p74u9TZ0TE6BTZBBYFC/aPwZR3xH63w+Unvt5rvXailnpW6N/4n3BMADVqXbg7t3FbzQhvlpaTZNDLDraEjXBGd77D9RQ65XFJpiAv8dunWuBZfAYC6xCIgAABYgM/0VRn+lVdgFup/C17SaX9WPVbWdPlNf5XhX3mFZpH+XvCSvvWfrsfKACA8w0eG3tWudz+Hfv37RF2e4Y74YicxsYYGDg69tnCuAwCshgAQAAAL2OrdUWP4V6ZYJVpUsqweKsJW744aw78yJSrRZyVL66EiADg/F3d1hLSQR7Pmhib9KE6GUX+rHF81IUbNmtd+vn4DnOp6CQPgADRdBIAAAFjAWs+GkNt+4d2uwkBRBKuBFN492ebdoYJAYQSrAYDzZxiGbpkap8HDqu9Bl9rKphn3JahZ8/p9xUxqZtPPfp6gtPTqzztoiFO3TqvfYBIAGhp+AgEAoJEzTTOknmZlfPIpM3BSXW0XR7Cqps00zZB6ZJbxya8T/kxdYusawaoA4Pw5HIYmT4nTyNFubVjr0Yljkt8vpaQ41G+g1KOXM+JDfquTkmrXf/02Ufv2+LR5o0dnzwRktxm6qKNdw0a41bqtPSp1AUBDQgAIAEAjZ/77P+Hwm/4IVYMyfoX3HfsViFAlAFB3Wrex68bJcUpOTpbdbpff71dOTk60y5LdbqhXH6d69WGhDwCoCkOAAQBo5GyGTS1szcPap6WtRWSKgaRzw+XC/Y65JwAAAIgUAkAAACxgqOuykNt2sXdWqj0lgtVACu+edLZ3VCt7agSrAazL4zF19mxARUX0oq0vpmkqN9evM9leeb3h9UAHAEQHQ4ABALCAy13DtLxktYpVUmvbMTFXRL4g6HLXEC3zrFKxWVxr27Exo+uhIsA6TNPU/r0+rVvl0YF9Ppn/zqA6dLRr+Ci3+g9yymZjwYe6VlxsasNajzasLVXOmVxJkstlqN9Ap0ZewVx7ANCQGaZp8pONBWRnZ0e7BCBiGtocM0BDddD3lf5R8Io88lTb5oaYiboq5sp6rKppO+T7Wv9b8HKN9+S6mAkaHzOmHqsCGjfTNPXx+8Vas7K02jY9LnVo2k/j5XQSAtaVs2cDeuHZAmVnVd3T0m6Xbr09Tv0HVb9SMNDYpKQwYgLWQQBoEQSAsDICQCB0J/2n9GnJUm337lSg3KISne0ddVXMaPV2XhrF6pqmk/5T+qxkqbb94J50snfQVTGj1cfZK4rVAY3PiqUl+uSj2ns7Dxri1K23x9dDRdbn9Zp6+v/P1+lTNQ+zttmkGfclqHMXBprBGggAYSUEgBZBAAgrIwAEwpcfyNdxf6YCCijF1lKt7GnRLqnJyw/kKzcuX6ZhKsXWUrGFMdEuCWh0SktNzfpdnoqLQ3uF+c3DiUpJZVjqhdq80aN35tQ+nYEkdevu0D3/mRDhioD6QQAIK+GnGQAALCjRlqgetkuiXQbKSbQl6qLYi77/QaOQHzSAcO3c5g05/JOkz9eX6pobYiNYUdOwcV31w61/6Mv9Pp3J9qtlCsErADQkrAIMAAAAoFE4mekPq/2pMNujauF+j9+eZEVmAGhoCAABAAAANA5hTl7EXEd1I9xJo/jeAaDhIQAEAAAA0Ci0ah3e60urVgxDrQutWof3PbZK5zUzmgIBU0VFAXk8RLEAvsccgAAAAAAahb4DXPr4/WKV1L4IsCRpyOWuyBbURAwZ7tKxb0JbBOTibg4WXomS7Cy/1q7y6IvPv58rM721TcNGunXZUJdcLiPKFQKIJn6aAQAAANAouN2GMsaEtoJ2vwFOpdEDsE4MuMyl5OTQwqOx490RrgZV2bWjVE/+MV9rV5ZWWCjn1MmAPny3WM/+T77ycpmbEWjKCAABAAAANBpjxrs1ZHjNPfu6dHPo5ilx9VSR9dlskjOE3mM2m+Ry08usvn1z2Kc5rxTJ56u+zckTAb38j0L5fAwLBpoqAkAAAAAAjYbNZuhHP47V7XfHqXOXij380lvbdNOtsZr+f+LlJoiqMzu3eXX629p7jwUC0tJPQxyfjTqz+NMS+UNYqPnEMb92bfdGviAADRJzAAIAAABoVAzDUN/+LvXt71J+fkCFBaZiYgw1a27IMAj+6tqGtZ6Q2+7f61PO2YCSW9DXpD6cPePXgb01dP37gQ1rPeo/iLkxgaaIABAAAABAo5WYaFNiYrSrsLbMEyF0L/s305ROnvATANaTkyfCm9cvnHsJwFp4KgMAAAAAqhUIc+0Ik2nm6k0gzC+bewM0XQSAAAAAAIBqpaWFt5pyahqvmfUlNex7w8rYQFPFkxkAAAAAUK3Btay6XF6ni+1KSydkqi/pre3q0Cn077u2FbQBWBcBIAAAAACgWgMHu9Q8ObTFVa4cFxPhavBDY0L8zpNbGBpwGQEg0FQRAAIAAAAAqhUTY+inMxOUmFRzCDjpR7HqcamznqpCmZ69nbr+pppDwKRmhu7+WYLcblbJBpoqwzSZBtQKsrOzo10CEDHJycmy2+3y+/3KycmJdjkAcN54ngFozHK/C2jVMo82byxVcfG510jDkLpf6lDGlW516Ub4F02HvvRq5TKPDuz1BRf7iI0zdNlQl64Y41ZSM/r/hCslJSXaJQB1hgDQIggAYWW8MAOwCp5nAKzA6zXlKY5XwLSpebJNgUBetEtCOfl5AeXkBOSwG0ptZZPTSa+/80UACCtxRLsAAAAAAEDj4XQaSktzl/tBI9oVobzEJJsSk+jtB6AingoAAAAAAACAhREAAgAAAAAAABZGAAgAAAAAAABYGAEgAAAAAAAAYGEsAgIAAAAAFnTyhF9ff+WTz2uqebJNPXo55XJd+Iqwx77xaevmPJkBQy1a2tS+gykHK80CQINGAAgAAAAAFvLNYZ/+9WGxjnztr/B5bJyh4SNdGjcxRnZ7+IHdwQNefTK/RMeP+iUVBD+PTzA0arRbo69yy2YjCASAhogAEAAAAAAs4st9Xr0yu1A+X+VtxUWmli3yKPO4X3feEx9WCLhzW6nmvFqkQKDytsICU5/+q0SnMv368R1xhIAA0AAxByAAAAAAWEBRYUBvvFJ1+Ffevj0+LV/sCfm43+UE9PYbVYd/5W37wqv1a0pDPi4AoP4QAAIAAACABWzeWKqS4tDarl/tkc9nhtR24zqPfN7Qjrt2pUeBQGjHBQDUHwJAAAAAALCAbVtCTOkk5eebOvRlLV0Fz+O42VkBHTvqr70hAKBeEQACAAAAgAXk5dYyRvc82+dG6LgAgPrDIiAAAAARFjAD2u87qNM5WQoYAaXYW6qbebFijJhol9bkld2bb/xH5Tf9SrG1VD9Xb+4NGiWny5AU+vBblyu0xTpcTkM+b90fFwBQfwgAAQAAImhr6Q7NL/lEZwJnK3weI7dGui/XtTHjZTfsUaquadtWukPzSxYqO3Cmwufzij/i3qBR6tLNoTPZoS3CYbNJnS4O7XXw4m4O7doe2jBgp1O6qAP/vwGAhoYhwAAAABGy1rNBrxS9WSn8k6QSebTEs1yvFM1RwGS4XH1b69mgl4verBT+SeXvzZvcGzQqw0e6Qm57aW+nmjUP7XUwnOP2H+RSbByvmQDQ0PBkBgAAiIBT/tN6p/iDWtvt8O7S6tL19VARynzrP613iz+std0O727uDRqVtu0dIYV1cXGGJt4Q+jD3Lt0c6j/QWWu7pGaGxl/D8HkAaIgIAAEAACJgjWe9zBDn4lrlWUtPs3q0xrNeAYX2fXNv0NhMujlWIzKqDwGbJxu69754paaFPkzXMAzdcnucBg2p/ripaTb97L6EkHsVAgDqF3MAAgAARMBW7/aQ22YFsnXCn6n2jnaRKwhBX3h3hNw2K5Ct4/5MXcS9QSNhsxmadHOcho90a8Naj77+yi+fz1Tz5jYNGuJS775OOZzhL9LhcBi69fY4jbrSrfVrSnTsG8nvk1LT7BpwmU1duztUUiwVFgQUF2/IMFgIBAAaEgJAAACAOmaapvLNgrD2yTPzI1QNyjt3b8L7rsNtDzQEael23fCjuDo9ZkmxqQP7vDq4368z2ed6xmZne5V5wqbvcgLy+8+1a9XapuEj3Bo8zPXvlYkBANFGAAgAAFDHDMOQW2555Al5nxiDebPqw/ncG7fhjmBFQOOQczagF54rUNbpikPifV4Fw8Ay354M6MP3irX581JNnxmv+ASGBQNAtPEkBgAAiIDuzm4ht40zYtXezhDT+tIjzHtzEfcGTZzXa+qlv1cO/2pz/Khfr71YqEAgtPlQET6f11TudwEVFQZkmnzPAKpHD0AAAIAIGOUarh3eXSG1HeoaLJdR+wqbqBsjXcO1PeR7c5lcRu2rqgJWtv0Lr749dX6L4Rz+yq9DB3zq1oNnXF069o1Pa1Z6tHObVz7fuc8Yeg2gJvQABAAAiIBuji4a7BxYa7s0W6rGu8fUQ0Uo083RRUOcg2ptd+7ejK2HioCG7fP1oQ+Zr8qGdaV1VAkkaf0aj/72ZIG2bv4+/JO+H3r9/NMFKixg9XIAFREAAgAARIBhGJoSN1kjXcNlqOqeGB3tHXRfwgzF2+p2on7UzDAM3RZ3s0bVeG8u4t4A/5Z53H9B+588cWH743t7dnr1wTvFqmm07/FjDL0GUBlDgAEAACLEbth1S9yNutI9SutKNyrTOCW/AkpzpGiA+qqLvbMMg2Fa0WA37Jocd6NG//veHPUfk98MqKWthYa5B3NvgHL85HcNgmmaWrSwJKS2h7/y6+B+ny7pydBrAOcQAAIAAERYqj1Fk2KvVXJysux2u/x+v3JycqJdFvT9vQHK83hM7dhaqlOZ54ZRprexqe8Al9zuphkK2+0XFgK2SmfgWV04dtQfVm/MDetKCQABBBEAAgAAAICkQMDU8sUerVhaIs8POlp9/H6xrhgboyvHuWWzNa0gMHCB08kNGe6um0KauHCHUjP0GkB5BIAAAAAAmjzTNPXBO8XaWM2CFSUl0mcLSvRdTkA33RrbpIaI2y6gA1+79nZ1v7R+Xzt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}, "metadata": { "image/png": { diff --git a/notebooks/popdyn_tests.ipynb b/notebooks/popdyn_tests.ipynb index 93eb285..2d68ca7 100644 --- a/notebooks/popdyn_tests.ipynb +++ b/notebooks/popdyn_tests.ipynb @@ -1,8 +1,16 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "97c859d6-9c64-4981-b28f-d5c5a63c4f7d", + "metadata": {}, + "source": [ + "# Pop dyn tests" + ] + }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 6, "id": "3638cfd4-177b-4b24-b6a4-8d61d74faf80", "metadata": {}, "outputs": [], @@ -17,19 +25,19 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": 135, "id": "1f80110e-9da0-4625-9e48-b6503e56adc4", "metadata": {}, "outputs": [], "source": [ "r_devs = get_r_devs(n_year=1000)\n", - "config = {\"s\": 0.97, \"r_devs\": r_devs}\n", + "config = {\"s\": 0.90, \"r_devs\": r_devs}\n", "env = AsmEnv(config = config)" ] }, { "cell_type": "code", - "execution_count": 88, + "execution_count": 136, "id": "eb58ebf3-882d-4944-9e19-2332f3133a18", "metadata": {}, "outputs": [], @@ -38,6 +46,7 @@ " simulation = {\n", " 't': [],\n", " 'surv_b_obs': [],\n", + " 'bare_surv_b_obs': [],\n", " 'mean_wt_obs': [],\n", " 'act': [],\n", " 'rew': [],\n", @@ -55,6 +64,9 @@ " simulation['surv_b_obs'].append(\n", " env.bound * (obs[0]+1)/2\n", " )\n", + " simulation['bare_surv_b_obs'].append(\n", + " obs[0]\n", + " )\n", " simulation['mean_wt_obs'].append(\n", " (\n", " env.parameters[\"min_wt\"]\n", @@ -79,7 +91,7 @@ }, { "cell_type": "code", - "execution_count": 89, + "execution_count": 137, "id": "a634dbf5-00af-44d8-b2d9-5ede8969e3e7", "metadata": {}, "outputs": [], @@ -90,23 +102,23 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 138, "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 90, + "execution_count": 138, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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", 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", 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", 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", 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" ] @@ -147,51 +139,50 @@ ], "source": [ "trivial_ep.plot(x='t', y = ['total_pop'], title='total population')\n", - "trivial_ep.plot(x='t', y = ['non_random_newb'], title='Unfished non-random newborns')\n", - "trivial_ep.plot(x='t', y = ['ssb'], title='Unfished ssb')\n", - "trivial_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" + "# trivial_ep.plot(x='t', y = ['non_random_newb'], title='Unfished non-random newborns')\n", + "trivial_ep[trivial_ep.t < 50].plot(x='t', y = ['ssb'], title='Unfished ssb')\n", + "# trivial_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)\n", + "# trivial_ep.plot(x='t', y = ['bare_surv_b_obs'], title='surv_b_obs')" + ] + }, + { + "cell_type": "markdown", + "id": "977fb177-37ea-470e-a83a-400d9a9dcf43", + "metadata": {}, + "source": [ + "## Escapement" ] }, { "cell_type": "code", - "execution_count": 91, - "id": "26c2cf63-f70a-41aa-8ef1-e3f5b69fe5b2", + "execution_count": 118, + "id": "3e9aba5e-466a-4feb-8bc5-8bf34da520a3", "metadata": {}, "outputs": [], "source": [ - "mid = Msy(env = env, mortality=0.05)\n", - "mid_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), mid, other_vars=['ssb']))" + "escp = ConstEsc(env, escapement = 0.05)\n", + "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), escp, other_vars=['ssb']))" ] }, { "cell_type": "code", - "execution_count": 92, - "id": "62d7175e-1b05-4353-bd63-21971fb71d6a", + "execution_count": 119, + "id": "ff08dfd1-c97c-407a-aec7-968d36ca6beb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 92, + "execution_count": 119, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", + "image/png": 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BA8jn88hkaG/NME0Tk5OT2L9/P4aHh3kQFgYKLIjEoVIIQRDtwDAMLFmyBNu3b8ezzz7b7sNJJcPDwy27clJgQSQOlUKItGAYNK8mSu595hBu+NmT+N9/vB7rlw21+3CUFAoFrF27lsohCvL5fEuZCgYFFkTi1KgUQqQQ0zQDD4Yi7LzpP+4FAPz5Vx/AvX93fpuPxp1MJkPOmzFCBSYiceoUWBApQcxWkKdKdBwYn2n3IcwqNu8ewXNHJtt9GBzKWBCJYxNv1khjQaSDat1ErvUsMAEgS5mfxNh1eBKX3ngXAGDHDZe0+WgaUMaCSJwaOW8SKUDu16dzMTqo2SI5Hnz2SLsPwQF9/ETiiKWQCmUsiDYhizZrpOKMDMpYJMfodIX/Oy3GXxRYEIkj7gxpl0i0CzmQoEm70ZHJUGCRFGPTVf7vSkrOYQosiMQR203TciEQsw85qCUhcXRkKGORGGLGYqZaa+ORWFBgQSROlTIWRAqoSxkL+f9EeLKUsUiM0SkrYzFTTUdpmQILInHIeZNIA5SxiA/KWCTHmC1jkY71lAILInFszpu0mBNtQo5pSWPRGqJwMEt3lsQYnxEyFhUqhRCzFLERhCy9iXYhlz6oK6Q1RL0UZSySYfPuEdyx5QD//3SFMhbELKVOpRAiBTi6QuhcbAnq9kqed33jQdv/SbxJzFrszpu0ABHtoU4ai0gxQf40SbNvxG6dThoLYtZSkzQWaTF1IWYXzowFnYetIL595ZTc4LqdYt5+C6fAgpi1yDtFWtCJdiCfd3QetoZJ/jSJU5SG25B4k5i1UJsfkQYclt50HraELWNBpZBEKOYoY0EQACiwINIBZSwiRnr75MwkET2yEdk0ZSyI2QrNaCDSgHweUoDbGnL7LmUt4mdkqmGOtWZ+H4D0lKAosCASR94ZVqjNj2gD8o6adtitIb97MynxVOhmJprmWMO9eQDp6cahwIJIHBJvEmmAMhbRImcs0uKp0K1UanV+zg6WKLAgZjnygp6WiyEKfvzI8/jwDzdTsNQBOCy96TNrCVkMmxYhYbci6ikGSjkA6SmF5Np9AMTso5tFc+/51kMAgHOOm48LT17c5qMhvHBYenfRedgOZD8ayljEy1QzsDAMoL/YuJVXU7JJo4wFkTgOjUVKouxWEU2BuikL061Qd1K0yO9eWuZWdCvT5cb725PPIt+c+paWdYcCCyJxutXxcO/INP/3QLPmSaSXbj0P24VTY5GOm1y3Mt3MCJXEwCIl5zAFFkTiyOLNtETZrfLc0Un+77SkJAl3HCJispZvCafGgkohcTJVbry/Pfks8rmGn0UlJcEcBRZE4sj33G7ZKR6drPB/d0uw1M04tT70mbUCZSyShWksSvkM8hkqhRCzHHkB75bR6eIOrdwlupFu4PBEGXdtO+gQF8rxLE3abQ1HxoI0FrHCAoueApVCCMLpH9AlC7q4kKYlJUkAl914F97yX5vwo0eet31d3mHL/yeCQaWQZGEDx3ryWeSyVAohZjlytq5b1Pgz1BWSKEcny1o3r91HpwAAP3hot+3r1BUSLSaoFJIkVikki0IzY5GWc5gCCyJxZNFcWi4GXX7y6PP49ZP7HV8Xb3IUWMTLjoMTOOeG2/HGL96r/ZzR6art/9QVEi3y20eBRbxMNdtNG10hjYxFWuazkEEWkTjOUkg6LgYdjkyU8e5vNkywnvjYhegtWJeQWAohjUW8fObWrZgo1/DIrqPaz2EDmxhkLR8tDoOslEza7FambKWQZsYiJWspZSyIxOnkFPShiTL/9+PPj9q+R6WQ5GDDlwDnDc2NUTmwkJ5GgUVrUMYiWaaFwKLADbLScQ5TYEEkjiOwSMnFoMPIlBBY7B6xfc9WCqFFNVYMw+D/1l1M5YyFfB6mJY3cuUjvJ10DsTIttJty8WZKzmEKLIjEcU6VTMfFoIPoVTE+Y6/Zizs0uknFS1ZYuXTfa3kHLXeB0I2wNShjkSzMIKtUIEtvoovRTUk7xJsdlLE4IgQW8iwEu8YiHRd4t5IRMhZha/lyxoJuhK1B7abJImos8lQKIbqRf71tG878xG3YdXjS97FOjUXnLOhHJ61SyLR0Q7OXQtJxgXcr4jkUNoijjEW0kPNmsrCNTY/QFULiTaKr+MytW3FgbAZfvPNp38d2snhTrNPLCyeJN5NDPGfCOjw6b4S0w24Fct5MlmmF82ZautEosCAiJZ/1P6VkjUUnLUBilsKZsaDAIimqEWQs5Kd10nmYRpwGWRSoxQk3yMqRxoLoQsQb7FCP/7hwlrEo5hqn34Qkgkwz4nU77chYiLNC0nGBdytiytcvIBDkGDYdkKz1oc+sNZwaC3o/40QUb/YUsravtRsKLIiWOTA2w/+tk7FgKejBZhAykZKLQQcxfS6LBm2zQlKSkuxWRMFvueZ9/rAAFrDf7Do5c5ZGKLBIlumqJd7sbQYWk+V0bNIosCBaRjSN0omYWcZisNRwreysjIW1ejozFuIuunOCpU6kUtfPWBSEYHdSOD+dXSH0mbWCQ7NC10CssLXWHlik4z1vKbC44YYbYBgGrrvuuogOh+hExAVlSmMx4YEFy1h0UmAh/K5eXSE67wMRHjEomPEpYYhmWuKOztEVQqWQlpBzdJSxiBfRIKuvOVpgplpPhYNs6MDi/vvvxxe/+EWccsopUR4P0YGIdWudiNnKWDQCC9loKs2IdXmvrpBOCpY6EbHU5JexED8zMaPGvp7LGFo/h/CG2k2TZaw5VK+/lOMaCyAd5ZBQgcX4+DiuvPJKfOlLX8KcOXOiPiaiwxDXkymNk5rdE1jGIi3pOx1sO2UPjUUn/U6diCje9Ms01FwCX3Ye9uQbizLdCFvD2W5K10BcmKbJA4vBUh7FXAbZZoCchrUnVGBx7bXX4pJLLsEFF1zg+9iZmRmMjo7a/hDdhZh50zmp65LGoqMyFsLv6sxYWL97Gi7ubqbqEeB5PXZcMbys1NztkUFWa8jOuxMp2Dl3KzPVOg+oB0o5GIaB3nx6dBaBA4ubb74Zv//977Fx40atx2/cuBFDQ0P8z4oVKwIfJJFuzDZoLLYfnMD1338Md207GPi5rVD31FiIGQtaVONEdGuVRbQyYilENDhjH2Up31gGSbzZGuxdZqWl0Sm6BuJidLpxHhsGuL6it9gILNJQhg0UWOzatQvve9/78I1vfAOlUknrOddffz1GRkb4n127doU6UCK9BM1YsMCCeV6wlF4Q3vKfm/Ct+3bihp//IfBzW6HmsvsFZI0F3aTiRGw39VtIxVKIGFiwIJFKIdFQl67rqUotNYZN3cYf9owBAPoLOWSagRwLMNKQscgFefCDDz6I/fv344UvfCH/Wq1Ww5133onPf/7zmJmZQTabtT2nWCyiWCxGc7REKhEd9+TR1CrYQj+nlwUW/s+R2X10CgCweXeypTXxJjU+U0W9biKTMVCt2dXYU5Ua/x4RPaJ4c9wjMDVN01b7twcWjb/7ip1Xkksj7G0e7MnzFvSx6Srm9hXad1BdylVfvg8AMCacszxjkYJsaaCMxfnnn4/HHnsMDz/8MP9zxhln4Morr8TDDz/sCCqIBk/tH8fGn/0BRwS/h25CXLjFIV1usJ3NcG9jwZko11IzPMcPMa1umtZFrNrtUstpfIilEK+AQG69s5VCwALcxnk4Nl1tS6vekYmy1nWTdlgGKJcxuK9CmE0DEQ6WKRrV2NzFTaCMxcDAANavX2/7Wl9fH+bNm+f4OmFx1Zfvw+6jU3hyzxi++mdntvtwIkcMLI5MVmCaps07QIbt+ocF+++x6SrmSDubg+MzqNZMLB5ylt1yGaMtw8vkG8/YdBUDpbwysJgoV/lumIgWsRTiGViYHoFF81vieTg6VXGch3FSq5u46HO/xYHxGfzw2nOwftlQYq8dOc33M2MYGCzlMVmukc4iZgZK1voy3NM4b9OwgSXnzQRgafvfbD3Q5iOJB7EUUqubGPXRTPBZIfks+po7G7mEUqubuPzzv8P5n76Dv38irC4OONXocSL36jN9CBP+5bMG73YZmWz/zqFbsWUsPM43z4xF87Ms5DLobwaARxPe7c1Ua9g7Oo1a3cT3Hnwu0deOGvZWGwYw2NN4PyljEQ8nLx0EAPyfN76Af224WVpO+hxW0XJgcccdd+Czn/1sBIfSvXhs3hNjqlzDVV++D/+hMdY8KHLiwC+tyxb7rGHwzpBRaQF67sgkdh+dwkS5hpvv2+n4GSXBECbJkoMzY9E4buZhUcxleYZl7+h0Ysc129DOWEif16hCY2EYBk8j62iEokQ8vIPjM+4P7ADYBsMwDAyU1Nc1EQ3W5sy6hfPAIgUbGspYJMCKOb3tPgTc+8wh/GbrAXzip0862iRbRc4YHPE5sdlFkcmIdUH7zeHff20FQPsUN+i8IIoM01USFnm2mJWxYIFFBosGm4HFCAUWcWCapq0MNuYRWNSlCpWqFGIY1nmYtNZBzIAdGm9/CrsVeKAGy6MmTClkx8EJ/OkX78Gvt+yP8Oic/O6pg3jvtx7CoQ4M6PjmTFgHmVYoDXodCiwSQNQItKv9SrR8vW/74Uh/tlyJOOJzYrPFNJsxuK23uLMxTRPfedBqS1YtuGLtPMnAQh61zW5UrBQiBhaqgIhoHVlb45Vu99JYsPMwY1i7vaQzFqawHBya6LwbnAjbYGQyaClj8cHvP4pN2w/j7TfdH+nxyVz5n5vwo0eex6dv3Rrr68SBmPVlsODYb2OXBBRYJIAoDts/1p7FQ9wZbT84EenPNqXxQ8FKIWxnY10Mz49M24KVQwoxkpgKTzLdKu8UfvrYHpz7ydvxH3c+AwAo5bNYPEilkDiRyxvPH51y1dnoaCwMGG1LI4vX5cEOz1jwDBCE6zpE0P/U/mjXJz+eO+LUcKUdFjDnsoqMRTdoLDqF7z6wC1f8x71tSROJS1u70uNiSnjX4cnYfjYAHJnwPrGrde+MxZa9dm+Kw6rAQrhhHE5wQWYX9Io5PQCAXz6xD88dmcJPHt0DoOGJsIhpLEY6eweaVuSMxXSljgMu6WyVxoJlndh3MgYw1MPSyO0LLI5Mljum7VoF22BkDGvAYBjxZhJZXTHz2JvvPJsEtrHKCBkLKzhuf4A6awKLD3zvUdzzzCH88y+2JP7a4kncrvS4uIDtjDiwkPeKuhmLfDbDxZviTpL9e3nz5q2qgYoLcJKiN/ZZrpir1s30FqyMBZVC4kEMFhYMNMz3dh1W7zrlUkjdBMab3iPsmjAMo22lEDHuMU11EN0p8A2GKN4MobEQ18uo9WAMMRAt5DrvNmh5hojizfYExyo67x1tkWcOJJtmAySBVpsWDnGBjTpFL7dg+tX47BkLp8iLLVDz+hs3jYlyzTEgSty1JvmesvdxuYsgt6+Yo1JIzIg3nlXNAE/Vkiw+tief5TcQ1gasFG9OJXt9yiWcdpVKo0DMALXSbip20e04FM96Ld58O7FzpSoI4BksOB6drrTF6E1k1gUW7WjpEj/jKMxLjk6WcfVN9+GHD+/Wfo4Zo/o8qHiTnfS5jLrdlAUqg4L5i7xAiYHFgQQXYytj0aP8fm8hi0VDjYCoYfDVuanttCIGyUwYvd8liBM1McNSdoydQhlD+F6Luz3TNPHfDz6HzbtHtB4vr/9JnstRwzNAsEohQTNApmliQph18fDOo1Edng0xE9KJWaJ6XZGxaJ7Dptl+981ZF1i41WLjRNzRR3ESf/l3O3DHlgN4380P6x+DpD6P1lRKFm+6n9SmadoW+0GFDS07tELWMi4SOz/EnwG0J2Ph1kLcV8hhXl8RhtFMbaeg3tltsEXVMOBbdmKfV8ZwWh6bwo2Q7fb8gmI/7nn6EN7/3Udw6Y13aT1ezvZ1cmBhCoGatWEIVgqZqdpn7tz99KHIjk9+HcbzLtmuNGNlfa2v5bIZDDTXy1bP41aZdYFFO+pP4uIRhbBGFDfpBgjiLm+6UrftClpF3nV5BU9ipiGXyQjiTaEUItS+mWWtmNGQxXtJ9qGzt35Q6PQR6S1mkc0YmNusd3bibijtsI8/axg8Y7FvVH0O8J1dNuMwweKp+4yB+c2yW6uliCf3jvF/61yb8iM6ORDlgZoiiNNFNju7/cn9saT1WXs40OjGSYPgMQh1HljYb+HDfeloOZ11gUU7EC+MwxF84POEWQa6GRh5kYvyZsx+NLPZ9rpIxfcil7Xa0lRTJ0V1uajBkBeadog3s4aBs4+ZBwBYu7Cff58NX5rX3/iMOt30KI3wLETG4OJNt4wFr0UL7pqsHY9nPmCJcfeMTLdUvhLb/3SCStkXJQ3Cu7Cw36QVJ1Nmz17MZZDLGBifqUYqgv7hw7vxoVsew8SMfWO1dd94ZK+RBFVhHRJhLacjCWuFZCiwSICoNRZiBsRNDS8jr5VR9syz42Hjkb2iZTHbYGs3FRYgK30t9sN7ZSySL4VkDODzbz4NP373ubj+4hP493sLjeOd12fpLIhoEYM79j673ZBrQsrYLWNhGAYW9BdRyGVQq5vY00JLuHge64h35aRGp+2cRUSNBXuvx2eqtkCtXjcx5ZEtZRmLoZ48ljW7wqLsYnvfzQ/jG5t24r9/b5/LEkSvlgbYOpTN2gMLbpLl0/IfN7MmsMgJ1qdJDq2SXy+K2tdU2bpQdQMVuZYbacai+TcLLKYqNdc2sZpgbJXLWDsb2XkTaCieVf3w8o7ycIL9/3Vhtzyvv4gNy4ewZr6VsWC/z1zKWMSGqNGZ00z9upUQuMurUPe3xJtWkJjJGFg+3LiRteLzIup9dDxrnB1VnXu+2DQWgvBaLHO+9cubcPYNt2GLUDISmWgGFv2lHFY2s0hRBRaTZes4ZJPAqN2I40blvAmkxyRr1gQW4njZJIdWAfbUfRQZC/H4dWuyjsAiwto/CwQGSjkewLntICuCilTMWExX6rzuaYnzrJuB+PPEjAUTSSZVU6wLNzXGmvl9+OtXrsMVZ67AJRuWAAAWshT9GLWcRo2YNRLnI6g2DF6DxsR2UwBY3ryR7TrSQmAhBJI6QaV8XXZyKaQuaCxygvCavd8jUxX87qlDODpZwad+/qTyZ7CMRX8xx31sohJXigHKnubPPGX5EADgmYMTNt1FmpEF8CJpMcmaNYFFMWe5qyUtbBEz9xPlWssnsJgNSEXGgonpMoavul68IAzDQL+tpZQZFzV/nmFwPYlYUmCuczlBJJlUyUEs04i89/y12Pi6UzCnebzLhtmiSIFF1IjBHQssKjVTOeW0LmS/nIGF/bNkbqq65UUV4rV5UGP2h3MycOcGFgx2acjv92PPWS24T7pkLNhn2FfIYcFAQ5gbVafMbsG6m4nXV87txWAph1rdjHzUQVyI50zOEVikwyRr1gQWYldE0tGcvJNq9UOfDpOxSEBjAVgnthxYjM9U8fPNe7nRFbsgshmr80OVop4/wLQK1s+rNn+ZXNZIXCTJ3kd5pyDDAovdLex+CTW8vpwx0FPIotQcHa26rsT0vNypIE7jBCwBZysZC1trucY5Ka8NnWjWxKhLgdqgMDH2Bw/txlv+axN/7O6jU9ivyOYxUWV/KceFuUE6de5++iDO//QduPcZZ5vqTNVZLi3ls1jWbB3vlGnEYgY8IwcWPdG0TbfKrAksRPV1qyY4QZFthVttQRRLIUc1RTryMURbCmn8bRgG5rgMc3rnVx/ANV9/EP9113YA9khbFnCKNwPWBqjOWGT495OaDOlW25RZygKLDuyRTzu1uv0G5tXaK3pVOMWbVskNAI5d0NDKPP78KMJi6wDT6QqRMhZJTuqNGrkSNdQUXv9hzxiu+/bDjsc/pejEmBBKIaycGCRj8eYvbcLTBybw8f/5g+N7qrbVUj6DxYPenUVpw9ZZJwUWTHOUtDW9zKwJLMQba+KlEMeQrhYDi3LwjIW8MxqPcGfE/QAMdcbi8EQZ9zR3EF+5ewcA+46f1WInm7+X6GMxv5mREBcX0RKc2X4nZSxUE1LrXqye1weg4a8QxtaYcIddTyywcMuSAeK5aWCoVxZv2n/O6avmAACe2j8eOvgXtMk4qBVYWLoEoJHZk1tQOwX5/WSB3M7DVonhT05fjvOOXwAAeOqAM7AYY6WQYpZnLHSvbXGNKyrmf8jl4Mbjslg06O2FkjbEe5lDY9Hjfi0kyewJLISLNel5APIJPaaoBQdhKoTGQm6akPu4W0FsM2MZC/G4VB0iOcEyrreYbR6TXWORMaBcXKwhZlbgkdTIaZV4U8VQb57vuJ7a31k98mlHLIUA1i5NVQqpC/UOP/Hm3L4C1sxvBISPP69nyS0j3tx0zKHYtTMkGK6Nlzsza2FKQRL7nQ6MNa7N5XN68C9vOBXrlzYEkw8Jdt0z1Ro++fMncdPvGhnN/mLelrHQ6eQTSx1yiQCwMp0ixVyGBxadMttH7KxzF29SxiIRxF1Au0Yj55s9x+MtpjtVGov9Y9P46I8fx6+f3O95DMzAqdXgxoawU5nT6/SyUF3QYgqvr6DOWGQMg2sVDk2U+e/NnEezQrtqUlkBflPzKYUAwLpFAwCAbR1mvpN2eCmkuXrN8SqFNP+WNRb1uimIN63Hn7RkEADwRMhyiLiB8fJr4MfXfHgpl41sfWgX4nsNCIFFs4xZaG4mzjluPgDgt9sO8HX5M7/cii/c8TQvBfUXs7zMWa7VtVL7MxUrsJCHFgLOcjDQyFiwzYmOJiYN2DIWhhxYkHgzUcQPo12jkUXTmFaoCDdqlhn48A8ex02/24F3fPV+ZV1fbAkFrOxAFIjpXPbzxZ7xilwLgj2wYMHOBBtnLdw4hnry6Gt+n/1e1hCzDH+uziIeBdZNzT+wOK7pyLl1n1oBT4TDlII7seVURsymsXOzbgKTlZpNG8Q4aWkzsNjTemAxWfG/xupC9mWAe7Z0aGAhvNeAtd4dbGYb2XTZ01fNQV8hi4PjZTyxZxS1uolv3bfT9rP6ijmU8lkh6+FfphC77VTrgarE1FfMYoi7VXZGyZKJ1w3DuQ6xjPH4TNU2+iFpZk1gId7bovCSCPbajRN6MKLdtW32yFRjRO4zB8eb31NPBGQLHhNKRhlYsKMxDAOlvPNGrxJNiY5xfUV7sCN6DxiGwUeUP9dsFxO7QpjT5URC6WPR9dEPlrHYSqWQSJGDO9biq9QbCdm0ktByPl2pOfQNQOsZC/Ha1Al2rXPdCnw6VZMjB2psvWPC6nwzY1HIZXD2sQ07/LufPoix6YpjWBnTXQXpDJkWMhaq91B27AUaTrnDktV72uGdaYo1aKCU5+dzO7MWsyawEDMWSe8I5Dpqq2UI8UZtmo2dmpj6e3Kvc1FkTxmM6BjsP9vaqfDAQijXqCJncdwvz1jM2Esh7MJZOGjXWdSEC6uvqc+YTCpjIdX3vVi3qJGx2EYZi0iRy1HDChM1hnjjzmQMLuprBBaN72UUGYunD4yHav0Ur00dHZNY9lNN8u0kxPcasNYCdsPPC5uJ01Y2hLKPPz+qvHZ5YKHoCnNDzFiopqqqxJt9RSsrMtIhrqdsY6Vag7IZA2960Qpc/ZLVWmtUXMyewEK44KcTdlhjCyHLFrRaQ5UzAI20l/U1lQVunR9D44ItV+uRpcrE9tAeHlhYP1ulsVB3hVSbP89e+3b6D1g7zZ68XZ8RN7wjQeOiXdvMWOwZme5of4K0IXuJsMBUJRKWW0qtm13N+p7w+IUDRRy3sB91E/jxI88HPjbxVJ+q1Hw7PMRz3ev36ATY+8kuDfb7MApCpwYvOT0/yjch/cUcLj1lCRYNFvGClcMArCyOTvlYzFioumtUmdP+Ys4SPHZaxsJlDdr4ulPwkdeczEcstINZEVjIJ1jSFy47EaLSWMiRd8MO27qoVGWOOtdY5D0fFwZRDd6jWByrvhoLVs5gGQs0f55dBCYbaGUzVsYiytKOF0HEm0M9eSxqZlsoaxEdsvupvDMWkU2weOBbrtsCYoZhNHZ8APDt+3cFPjbHWuOziRGzJswdWGXk1AlY73Xj/WTvNSMvdIKtaJY3941O85JRXzGLz7/5hbj3+vOxZKin+bXmxkEj+yO/1/L7qAos+oo53qI5GYErchJ4ZSzSwqwILGQ18JRiAYoTUy6FRJyxmK7UUBYuCNXPZ08p5DJ85zAR0S7f0lhYi8m0rRSi6AqxaSya5QyusbDfOByBheBjwMWbCQWLckeCHxuWDQMA7tt+JKYjmn3Upc9AVX5jiAPtACHwrdYc7ZGM1562DPmsgUefGwncdipfm36ZNGsujrWjV3U0dATyey0FFgUhsGC76dHpKs/msQ2GKKaVhd1ezEjruhwkuGUsxDlSo1PpL0PVA5Rj28XsCCykE2om6SFkrNWzyHYkrb2+fH1MV2ooC2UN1UVouRUCxWy0C5go2lKJN9WlEOvUk28Moo8FYOlC2AIkBh482xGhL4cb4m5UJ2MBAOce1xCp/eCh3YlNYO12ZPdTZumtLIVIu2imsZgq1xyZMca8/iJeurZh4hR06qWcTfQTcNozFo1j64Rdswo5Y1HyKIUM9VgiQ2alLQcigJCx0NgEyZ+/I2Oh1FjkkMkIJdyESqqtwESosutmmpgVgYXjYk+6FNJ8+d6mHkCVsg2CI2NRrduCBJWGwxSi3Kh3RnbxZnPhFjMWPqUQ+XisXaY9YyFrLDIZa0czmUBXiJfjnRuXv2AZhnvz2LJvDN+UWuqIcNSk86PHK2Mh1f17hAxXXdLyiCweapgmBW1BlNcavxuiOAjNCiw6MwCVM0BepRBxsjGbXtpTcAYWlrBbQ2MhBWRyoMGMpVbP6+VfY9lSvo5otAi3G9nSPo3MisBCVTpIEnbB9RSi2ZHII3MnZ6q2LIZKw8E2y4ZhBRZR7Yxs4k2VxqJ5QTORpnjsgJUiZVmXWt2+QFmzRJylkl7BXCtuK2Sv4T9uzOkr4C9ediwA4HdPHYzluGYbcssvO+fkVHjjsc1/sOxGThRvNr+leA25/KaLsxTifaMSOym6RmNh2AM+hhhYAFY5ZHdzArAs9gSc5nleOEsh6owFGzYHWGtST8J+OK1Q64CMRc7/IZ2PM7BI9sJlr99TiCZjIbpojk1XHZoKr/HRWSPGjIUBZUqRlQDm9hX4sakyFpWq2fx5ja+ziLxfUoaLGguWIQEagUkp41ycokLcjeqWQgDgmAUNm+ggUxoJd+SMhZfGQs5KiIGvnBkTCRtYyLGt3zUmBsmFTs9YNP+W32tGQZrfwboxeMZCUQqR7f698MtYsIB0zfw+rJzbi3w2wzcmnVQKCWLS1y5mZWDRvlJINBoL9vv0FXIYm646Fr/pSqOVVNwhiG1txZhEYmK76XS1DtM0YRgGKs3jndtX4K2w4uLJMhYzzQBE9rGQa8/izUL8Hcu1Or/JxIF4GgURTrGZB/s7ZMhR2pE1FirBMEPOSog3EEt/4UQuvwU9NkbZR1cjlvU6XWMhO2/K12Iha3+nWbaAeVSoSiFRZizE4YUfu3y97XtWSTX9773KfyVtzI5SiFT3LFfriU4QrPOMhXvKNtDPk8SgKo8EOcKv8ayCsDOKSExo01g0f8da3eTdICxjIaqvRSGjq8aied1Ypkb2wCNjGDaledxqelspJMBFvbA55Eh3mBLhDXsLWXBXFHQ98vsrahjEx05X67YpujKs/NZqKcTvWhfFpezYWl0f2oXcvutXCmE380PNGR2qUkiQrhC5rd2hsfBoFffKeqUPd21QWpgVgYVCO5ioSRZbwFT6g3A/r/E3i+bZrqqQy/DFVo7W68JiXIizK0SwTWYXqUrFzPrUAWvBKfOMhPXzAOuiZ78Tj9gzBjIZgzv6xe2NX7cFFvrPWyAMU2r3cKBuQE4FsxuYaTrPe3mCqc0gS/qeSPhSiGk7Jr+MhSguZRoLv+eklbqUAspnDbuWKicHFo31i02bLuZUgYW+j4X8tskBmtdk4qRnDrUCZSxSAotURUvZJHUWzlJINF0h7GJg9rXFbMZKp7pcVBmhXz6qWq4oQBMXExZAMfGmOCr9jNVz+L95xqLmzEgAQoq4+fPE1lkAkQdKboTpCgEavx+fKtuhds1pwtp5Nv4vptwd570UpLJzpVKrey7Q3PEx4OdVk7KTvhoLlai6UzMWzb/Z+2kYBl/zAGfGwtpoNX5fOfBoPIZlmHQCC/1SiAwLYDohYyF6n6SVWRFY1PmOOcMXliRPIO5j0Tx5Z5r6g7Cw36ePzxawMhbWTVoSLglCNb4ziipjIVgjG4azJ5ylKPNZA/9+5QtxxZkr8bazV/PnF13Fm42/nRkL+wKRlLGQeEGr0ude8DkQM5SxaBUrSG58BvlshmfD5Otatu22slvqsemMkqAVCnRscsZCW7zZ+RoLsSTKEL0sHBkLDwMtRjGnn+WVMxZu4k1VYME+b9JYRMOsEm9mMwZyGQPlWj1RdztTKoUAjZtkWKGhFag0MxbNNsxCLsN/Vzkjwy46UX0edSlEtFgen6nyRZ5pLXKZDC7esAQXb1hie76csZDV+kXh+/W66Xi9pNT0Qey8ZfpLOewfm0nEyKvbkbtCAOucc9xMpHMlL2S3LGGn6kbjbrrlBXs99nw/HVM3WXqrLNJFnUXRUQrx7hoBoDTcc0PW0rm1m6puyFYpJP0ZRVk3lEZmRcaiJu4K8snvCuT0aOP1wy8eYlcIYIk389kM//3kOq24M7ICi6h8LOypOZ6+5KUQa8y5irxUypB9LGyp7mpd+L50s4i5Nt1KmxfLWIxTxqJlVKPr3cR38rnJW5tronjT+Rp2LYZ+djFoKURlkNWplt4qi3QxsJC7PrycOfljBLGtH3IpxCHe1NFYdEIpxEMblBZmRWAhpsD4rqANGotCNsPTrq3Yiju6QgTxppvewBR228WIb8SieBNwOiGy2mbeZcCGnEGRd5niTmemajkmZg318+OCTxUMk7Ho8JHYaUJ1g3DLMMi76LygsZDPWxEmQq6b6lk3bvAOMM3WcvEmUciFy5KkBdX7KQYPcpeITilELCn5dfI5xJsuQ8g6vxRCGYtUUDPFwCKZ3S1D3O1kM4ZDLxAGdoGwmxUTbxayGRRc0qnKdtOIgis5ghZ3e4DVreGWsRCdN03TtAVBjedZNfTpinMqpSjIixPxPAoK+6yoFNI67D4vZo7cbL2tsemN/1vniulp6V0UjNeCdJCxc6QUWGNh2LIpnYhqJ90jvI+OwKJgr8R7lUIA/zXTP2PR+LvzMxYk3kwFord60spru/eB6MkQ7gQ2TdPqMinYHSkLuYxrOlVsN406uJLnMVh10cbPZ10hsiqcIS4o4oIvXjiisE0MksTvJeVjEaZ/3HIPpVJIq1ilEOtrPGB3dEM1/rbKZo2/xXNftfMr5jL8/AtyrcodW9qBRcYe9HQi8joAeJdC/Jw5AXtg4XfT989YNMeNe2os0h9YyN03aWRWBBZ1IVJNWnktZu/EjoywGQvx57EBOgxbV4gcWCjaTaOz9G78zURw8u6RDSFz87YvSO6ZKtVzUcj0WF0hzecnVQqJIGMRtH2RcKISb7pnLBrwrhDegeStsTDEoWABNiFBu0LE7Fs+ocxbXMjrAGAPHpwZC/v/ZXEn0LjWWDDoF+DJA+AcY9OFzZVMJ5VCvLqZ0sKsCCxENXDSymvxZBdnW4QNbMQMiCOVKPpYVGV1vLUYR95FIc9jkDUWzSs661YKERaUsrDgixdOScj0qNoNgeTEm2ECiz4u3kz/wpV2ZEtvQHDfLLuc99y0SRBvStkMGbmkF+TYuHhT09JbLFF2qkGWvA4A9oyDb8bCJaOp+zmwtvYMzzQFMcjqJB+Lxt9BW96TZHYEFqJ4M5/M7pZhDyzEvuywGQvr5/UpUol+pZCGDXa0wZVjqiG3LrcbWrmJN7MZy1SrXBU0FBlnxmK6ImQ0JB+L2NtNWxhX3MuDLcpYtIqpyBxZM2qkG4N0borlBtnjQqYU8FoVy5S6InHRsyUpB9m4kNcBQCqFhNBYAGJg4aexaPzdx/2C7OcCDzwUgQXrZOuEUoiXNigtzIrAQkxh84FX7SiFGEbL7a62jEXRmbFw2/XEWQoxYdr+z7IyLK3oJ94EZEdEu4bC7ftJizdbKYWwYKsTUq1pp6bYsbmNvXbLWDQyY2h+zy1joe/62Hgt699BMxZiKaRj200loSxgDyZk3x4dH4vG8/RMDZmGgnXLyUEd+yhUJdmePBt2lv7AvxMMsmZFYCGK7qwbezvEm0bgXZDj5wkZi36FxsJtp1S3lYOiTbnKJ7qcuvQTbza+13iu6FMhXv9iMOSw9E5cvBm+FEKBRevUFJqdkkuJ07paJJfWWp1/0y1ODFoKEbOJ+hoLZ8DfqeJNlcZibn+B/9tRCtFoNwWEz1ZTvNnrkrGQpyaL9BZaW5eThAyyUgK7IeQy7jfeuJDbTVvNWNQ9NBb5bMbWuilSE27+0RtkNf7mBlkBxZsAeJus205SVPPz6ZaS82aaxZvWWOb074jSjqrtVz9jYZUb/Nr2ipopeH5ctmtTr9wolg945q1TMxaKQO2ExQP8337iTbeMBZ8p4usJYu/IcZsVoi6FdM71yU+z9MYVsyuwyLTBx8JeCtGvvbqhWrwYYleIc7qpUA6KqRQiize9hpDJiJ+L7GMBuDkmJt1u2vg7VCmkg1TnaUc1TKroki6Xg16xbMbXZ7dSSMDWcDFjwX0stEshVsdKp4o3Vc6bZ6yeC6Bx/YbWWGhmedl5wTQWbrNC1KWQzvGxULX1po3ZMStEaE+0fCySOYHEQMAQNBZhfSxqwsUrX6jFnGUkJWdExJRrMWKxo+y4J4utxCFkbojBjmonKdafa25186QsvUNc0Fx1ToFFy6huEHIwy5DTxnmh3KAamiUS1MxOvNatUoie82ZDYyFm5cxUq/5VqPwVBkt53P3BVyCbMRyZglK+4RXC1g+3Uohbx48MOy+4xsLFedMrYzFdaTh8hrHtT4pO0FjMisBCnC0Q9U3VD1nB3urrs1ajhhDUmbFgi628exfna0S9w5d3KiUpLS0OIXPDnqJufE28cGw7Takf3a38EzUk3kwHqpS2W+eAlZVo/B1KvKmbsRBeukezFCIGPuw8Ns3G9eoldk4jdUtkYWPpcI/y8WwSMrsm3IYyltw6fiTYBsYtY+E1RFB87XKtjlIm3IDIJCCNRUqwl0KS9bGQd9etWnqLAqRS3v7x2bpCPJw3o+6X9zPI8htCBqgzFmIcYh2z6RhClrTGIpx4s3NquGlHlbFwK1vUpXPF1tKpOM9Egoo3RWG19th0YeCeKG7uRAGnVfrXvz7Ea2lOX0H5mJ6A7aZuGgsvHxrbPKKUCzjJ0jsliDfjpDMWbgO1QpdC6tZiKA41A5rTTV0CJ1u7aVZv0dNFFm3JOz0+hEyj3XSm6pwF0niuIvBoU1dIKPFmnrpCokKlsbBS2d7Om/a2ZfY9N41F+FKIrl+OzV9GNIrrQJ1FGH8FsWQr+/IwdDNH7PVZB1aQ6ab5bIZ/PchsmHYgZq3TyqwILNg1anedTMjHQmpRbN3S2wqSDMOwpfA8Lb0Vw46is/S2R9ByvZv7WHiUQsQsisrHIq+4IfBSSAd0hfCuhYBjuAknKudNt7HpcmCfVxlkubabhhNvijqmIOJNMQPTiSZZslBWB/Hm2KoDKgs43UbWy6MAZFrd9CUFGWSlhFpbMxZyKSSqjIVdKAnIXSFqn3zbILaI3wP3Uoi7GpvB2k0rPj4WFWF8smyQFb94E7bXDQJLz5pmZ/TKpxkeWGSdgYWbeNOQs1sxWHrbjfiCzwoRW0471SQLCHZ9DJT8ZX66nwMXb7qUm9k65K6pSbZMHhZVRjdtzIrAQvSI58OsElrcZfvpyDIWLLAQ0qdelt6mUE+OOrhyBE/SCGK2k/BqNy0ofCrs4k3r+w7nzQ6Ybip28EyQzqIlvDMW8nnf+NsxV8ZlJo1IWB+LIFlBOTvXybbefl02KvqKQQILv3bTxvfdhLPs+Nwyp0Hbi9sFaSxSQnt9LKR2txYXDu6lYCgyFln3309dConWIIud6XLfObvgA4s3VRoLW9dI87kdYOmdyRhWJod0Fi2hNMjiGwZZY2G/2RVsAkk2tCrarpBsRj8raBlkNf622mE7L7CQ2851uGj9EgDAwoGi62O0NRaS82atbnLhOPs/4C7WLXZKxqL5d5rbkWdFu6lVCknex6Iu7XKLLS4ccilEbDntKeT4zt7pk+9sa4squHIYZDEhXVmy9PbSWPjsJMXAgwUZnTSEDGiUQ6YqNRJwtgjPgNnaTdUGWfJgrHzOeg47X1x9LFiArCveVJRcdTMWcpBcrnaeDifMTvq6C9Zi0WAR55+wyPUx7HPwnRUiOW8CjTWOZUpVmS4R0lhEx6wILGylkMTHpoO/NoCWBw3Jfvdiy6k4O8SZsbCOQ1z0ojDi8Ws31RpCllNlJNTiTfa7J10KaSVjATQDrglqOW0V1fhrd4Osxt+yjwVgnS9RaSzEoF88n3WuMae4NN27ZhUsFAoSeJfyWbz9nDW+jwH0nTfFmSQzlTp6m12sLPBwW4eClr7aRScYZM2OUohiAFfSQ8gcngsh+9Tllimxdt9fzLuKxlTTTeumdTG2gtxuyo6pWjdRqdW12k3FgEvUgzAs8abpWgpJynkzbGDRSyZZkWC1m1oniNvNR97diVkOnrGIuCtELIUA3uel7LMRtcdMkpghNBY6sJHmfp187L0UjQLFdd4v41jK6b1OuyGDrJRgz1hEqy/wfW0pw2DdQFuz9GZrqqix6CtmXae32qebCpmNCAIsWXlfFLIo05Wa0BWi226K5s8TxZvOdlTZpjnN000Bq/ZLgUVrWAGe9TWx3VTVzsuyaarOC98ugTDiTUVmRIUcJHMNVsrr/Cr4BiPiHL2l2dJrN826iGf9NgYdk7Go29fbNDIrAgtVijI5S+/G3/Jci7DOeqI9OSCXQnKu7WquRjyRBBaNv8WhYOykn6rUgpVCbO2mYilE0RXCdCYdIN4EaMJpVNSUGQvBOVE4p3mmTljp2LnEdqZ+GQvdHawY8IiBhdda4xR3d27Goq4I6KLAzaPE8fqKDaT42fkFFp2SsaBSSEpg9/Cs0T5L76gmccriTXEB6yvmfKebZjKNC4tdXFEsYLJoi80AAIDpslgKcT/digrxpn26qbvPRXLtpmi+bmuBBXWFtIZXxgKw72ytW514LlmlQMCj3TTgWiEGCZmMMFTM4/mmqT6XO9LSO6YbnjW4Ua/d1E1L57cx0NVytBtqN00JNdbumLGmiybWFSKdzK2Ks+RBOqJQqb+YU0bq4nHI1uJR+Hnw9idh8RZ3GZbzpr/GolqvK9vC7BmLxtfYe5BYYOHj3OdHT7MUMkGBRUuoMhb5rFVXF28MKgW9HOC6CSuDZjed9v3+JlmOrpUOFm/KrbNR4SbMdXt9t3bfat25YRFxWzvTCmUs2oxo6Z24j0XEu2uxVx4Als/p5d8relh6y7ttS9PQ+kWkWrzFxUBHY5ET2uxUUwitnZwo7kxW8KbqRghCL/exoFJIK7DAQg5UVSlzlc20I7BweR0r+A5aCtE/Lx1mbx3svCm3nUeFbiah1mophDIWkTErAgsxtS5GsknMbJCdN8Wddxhq0kJ06vJh/j3D4/eTx7eLQ79aRrF4i74COgZZtrHpigWAm2BVxemm9u+l3seiSF0hUSBfAwxVe6hKQS9qjFQ/hxG2FCJfY2HEm52oseBBXMR9Ibptv6JPhUrE7rcxCBpItotO0FjMCh8L1dh002zUMQu5eD+cqO2n5YvjnOPm4W9ffQLWzG9kLsSOD/H3k6PcKEWsqv51ceiWZentL96s1utC54vTx2JGUQpJKn0cnXgz3QtX2lEZZAFqkyyrTGchtz27rc9BW9PdtD9ez3fLvnViKUTuDosK3bZfe8bCWYaq+mwMOmVWCBlkpQRR7FUUdisz1Zpj9xI1jlJIqxoLSbxpGAbedd6x/Pvi71eu1fnvJ++2WxWRiqjU4KxFbGKmyncyxax6LDIgtuGaVrlH7AoRhpDJu9Aofxcv/Jz7/LDaTakU0go1QaQnoqrFe03KZbjtsIsBu0LkoF9nEyEH/DxITvnNTYWqTTwKRF+cquCkKVMV3n9VFpPPCnEzyOoQ500aQpYSxFKI7cabwMUrp61azViI9uQqbG1uilqztejpTV/UQXWis4zF6JR1E817ZIfErIOqFioGZDWXxbhuwjYbIGpUmZQgsAWSMhatwefluGgspgNqLNxT481OpJpVfvM8Lje9hKfGAoGfk1aszGW0P9fW8aMRpGVdRPp+G4OOyVjUncFy2pgVgYW4yxcNcpI4gdz61Fv2sXC5em1tbuIAHpe2tigzFnaNRTOwmK7wr3m1m4oaC1UNnZV0bF0h0s6w8fz4dDOyh0hQ+orUbhoFYpeXSI9CfKeqRxe0A4tgmxBX8aaWj0Xj/62uD+0kzHRTHcTPwevaUYk32RpomqZD7yYT1Gm1Xfi1SaeB2RFYSF0GSdp6y06Z8gyB0D/P4+amEo25tptGqLEQj4gt8qNTVmDh1W4qZiRUwZOYIq5LZZ2oDb/c8FuY/Ogh581IkMuBDLZLFW8+8nRTwCne1AksdMohDvGmRmDhGOvOAuiU75qVtHh9uGEImWavm76YkWAZWdZOL2ac3NahpD2OwtJ1XSFf+MIXcMopp2BwcBCDg4M4++yz8bOf/SyuY4sM+UYVtHbaCqYU1Ii79jC7Ep15FSrRGNMtOHQJEbSbygI0wIr+WcaikM14pu54u2nNVPpF2C2/7a8nLhRxppBVxkxB6OWlENJYtIJbuynPWFSdpRC7ENj+PLdrKZfN8O/p3GzYqecww/O4xmQNCJv104nizbgyFoBVWvVas9Xtps3AQtjEuQU+xQ7JWKjE8mkj0BK5fPly3HDDDXjwwQfxwAMP4BWveAUuv/xyPP7443EdXySIPhaAEJkm0K/sttgA4RYPncBCpYgO0wqni2zpDYgZi8ZN1GsAmfj9as3N0ts6Xll9L7bZxhlYqBxBg0BdIdHgpnVR+RCoBmPJ4j+vTFoQIznr/Gj8X6/dVCqF5KySYKehWgeiwpoX4v6+KEshVWfGwt0gK9g023bRdUPILrvsMlx88cVYu3Yt1q1bh49//OPo7+/HvffeG9fxRYJ8Q0hygqCb8yYQ7qYeOmMRY7upqv2pVLBrLPI571PNrxRSEGrPXN0tfL8YYaDkhlsKXpceCiwioVbzyVjYukIaf6sG2jG8Ps8gbozhukKax9AFBllxpuhVrcQyNWGtLUifmy2w8NFYUCmkdUK3m9ZqNXz3u9/FxMQEzj77bNfHzczMYGZmhv9/dHQ07EuGRr4hRGln7Yc8CyCbMZAxGgtKmF2Jzq5Z7TqH5nHE0W5q/9mAtcNgGgsv4SYgtJMKpRCVqVFZGMNuy2jkMsBMvDs9lSNoEPqKjcvNb5gS4U3VJbhWie9UXSFyu6F3xiILoKJXCnHxrNHysZDEm+UOFG/GmaL3M8kyTRMqHwv23teFj8CvCyjtGYtOMMgKXC1+7LHH0N/fj2KxiGuuuQa33HILTjrpJNfHb9y4EUNDQ/zPihUrWjrgMLiLN+M/geRSCNBatkAu66hQ7ZQczptRijdVlt7N3fnYdKMUIu8SZcRSh2xbLn6/VjeV01KT2Om1aunNdtQTM6SxaAU3ozJu6V2uOR7rNSvEa4FWOTi64egK0Wk3ldaHTp4Voio7RYWf3bbYDSzaCrD1oCpEFu7tpp2VseiqrpDjjz8eDz/8MDZt2oR3vetduOqqq/DEE0+4Pv7666/HyMgI/7Nr166WDjgMdUl0l6T6V5VhaGXx0Nk1qwKLeNtNG38rNRasFKKpsRDbTW2lEKGUwhYXVUYjzs9UFSQGobdgnXc6vgiEGnfnTad4kyGaYMnnopbGIqauEDdn3s4MLBp/x5Ox8BZWitdTRlUK0RBvdsqskE4wyApcCikUCjjuuOMAAKeffjruv/9+fO5zn8MXv/hF5eOLxSKKxWJrR9kijlJIXv+mes/Th7ByXi+WDfeEem1xXDmjmMtgDOE0Hjq7ZlUrqaNFMxtdcKVSgzvFm3oZi4qreNP6N9uR5mzTLeMXvVk3jnDPZ86bQKMc0l+cFca3keM2s8XKWKjarK3HOTIWGkLoIF0hQUohsidBIYHzOC64A28sGgvngDkRuZ1UXgNZwiKqILKd1Ovxvc9R0bKPRb1et2ko0oi8y7cMsrxPoM27R3DFl+7FOTfcHvq15R0JIHoyhG839S6FOLtC5Cg3SHDlhyqCLkpiK93AQjweWykkI2Ysas3vW8+P0knUjVYtvUv5DK/1U8tpeKx2U/s51cN2tVVnKUQUWcjP0wrSdbpCQog3ZYW/6jroFGLVWPBOPpfAQshINJw37Z1/rBTitW6WpOeklU5oNw20Zbr++utx0UUXYeXKlRgbG8M3v/lN3HHHHfjFL34R1/FFglz71K2bbt49wv89Nl3BQCkf+LVl/wigtZHlckubClVt191uOMKx6cJ63SPY8AL+XSEs4yBa9oo3cOYoWqmZPFjJCi8YZWnHjVYtvQ3DQG8+i4lyDZMzNWAgyqObPVjBtf3rPJVddoo3bRkLyVrecxcbwPNGvsZ0OpXcZoV0ongzzo0002y5lSnkro+itAaq5g/JiG6dtboZWkulw67Dk6ibJlbN6wv83E7QWAQKLPbv34+3ve1t2LNnD4aGhnDKKafgF7/4BV75ylfGdXyR4AgsNH0sxGBg8+5RnH3svOCv7ZGKLceUsVD55Ms3/0KEnTFes0IYBR+NRUEQZzLkG0c+m0GlVuOBhXhD0E0hj05X0JvPug4y8qJVS2+g4b45Ua5Ry2kLuGYsCk6NhXWzU2e/AB/xZoBSiLzgB2k35eJNYdhep2EqNhhREURjYR+bbtdYeAWR4kyScrXuWMOiYqZaw0s/9WsAwBMfu9BWItWh6zQW//Vf/xXXccSKLKqSfeTdODxZ5v/ePzYd6rXlbgygtUFDOuJNOVoHvJw3o5wV4hRvMnRLISLyjqHxmBrXWIjBlY43ydMHxnH553+Hl66djy+85XTP41HRqo8FYAk4pypUCgmLW7spCwLs8yT8NRY6VvNagYVbKcRzCJkUjHR0V0jjb7dpsa3AP1ufwMIwGtenXMLS2pDZBOK12AKLR5+zMuG7j0xh7aJgqUvVeps2Yogt04cs9rJ26967xiMTVmAxOh3uRqDqmGhlV6Ij3lTtlFyDq5gMsuQoXNfHQkSOyGUxXE4RrHndAP73T57A+EwVP9u81/NY3FB1qwSF3Ddboy6lvEVU6XKrndN6nOxjETT754Z889JpgZbr5YVOdt6EdXOPGr+ODVn/JAd1OsaCuWyGrylxdpc9suso//e+0eD6xE4ohcySwKLxt3xT9Tt5DouBhTBMK9hrO0+CYivtpho+FqrfTx41Hku7qbBTYZM8Gf4ZC+fvIy8CDsfEgC28hyetzzDM7x1FKYQFFhMzFFiEoeoRWJTYoCpxVgicuzvxPPLKVgDBhvUxWYR1c/Mvo7gZZKXdS0GF7MkRJao5MCKy/kkud+sEFoC/EVcUjAj3kn2jwTPhXWmQ1YnIXhK6ddOjwgkQNrBQlULywgjwoITxsTBN01GXi9T3QSGQc2gsct4XgVz3Bpy/ozyV0maQpREoFYUbyoHx4DsFduNopRTC3DfJJCscvMsDHhmLskJj4ZKx8PssA2kswpRCuskgSzFJNip6Cs0uM5dMX53rbuTNY+PxunN+kph8PS5c+/tClNhVhoRpY1YEFq6W3j4nj/h9ZvQU9rVVO6aWds0BZoWI09nl4CrKUoj4O/YFLIVkMobjd5IXfTmroey08fh9JgVdw/4wOwWesQj8VM5gs7NoLOT5FBfVDrmRiRkLN4OsKYWltyq7pfoZMkG8DRxdIfyc9J9u6jTI6tyukDh20qy06haQV+vqzaPlvJmejMWkkK08PF72eKSaODNDUTErAgvZ2Eh2ZXNDrKsyo6fgr934W+W82UrGIoiS3eY6J3t5RCjetGUsJPFmr4YQSgwcVAuAl+hOR/QmXtAHxkJkLFq09AaAwZ7GAjkWUrMTB5/91VZs+Mgv8eTe0XYfii9ew6R6NKeb2s4zvx0s11gEsfRu/D/YELLmczo4YwFFdigqmJmcmzaJv/dZdUZW99plwWCcgcW44GEzEcLPJk4tS1TMisBCFm/qZizEG/9IyFKI0vkvEvGm+2PkBU1MH8vtpnENIctkDFsw0ZP3b0ASAwfVgi+XQlSW316/j3gRhxHjtupjAVgZi7AZsDj47K+2YapSw4d/+Hi7D8UXr/HXYsaCBRQqMyHxPGt3KaS7DLLiS9GztWTcJWMhizcdzpuawmturBXj+z8p/A5hNhiksUgJToMsPR8L8ftjIWviKudNVTuoLlrOm5KzqDjZzxlctR6Zm6Y6ghYDC52MRcG24Du/L2csVC28XhkYUTAZRjMThXhzoJRrvn56MhaMgyGyOEnDHBRZW6GIqOuRbyh2jUW8pRCWog5nkBVef9VurJgv+huelbHwDizcxjZUa3pBj59fRhSI61AYrRV1haQEp3hT78YuLibjIXeYPLpUTOoMU0eVa4kq5ItKJXiLO2MB2FtOdXrCfTMWHqUQKwukfk9N05QyFiECiygyFj3py1gwjkwGr/cmjZeDYknIaDGRn+XoLQahQcSbAXwsHF0hQUohXSDejPGG18tFz96lELYmiF5B9brJr13ZVE2mFfHm3U8f1OryELMubhkYLzrBIGtWBBaO/nJNHwsx8AjbHqhqN22lI8O6QPwzFtzOVggs5HbTSMamu9T8gmYs/NT6cikko8hYuFmUT1fqNhFrmNKW3E4YhrSVQsTgOc0LFYNlLFQp7Vw2w88DJuBUDcgTby6+GYsA8yPCzAqRHXGLXSDejENU2N9sX3fTJDiEs6KLpjjYMCbx5s8e24M3f2kT3vZf9/k+Vsy6jIe4r5BBVkqQbwi6dVNxMQkTWQIu7aYt+VhoOMhJi6GqFGIN3IlgVohiHgpg3USB4KUQtXjT/jWbeNNnEZcXpDClCJ2OHD+YeDMtpRDRqyXNCxWDZyxcR1/bAwt2e3ZtN9VuPwzeFaKnsbAfB1sbanXTpifpBCw9S/Q/m2U/J/0yFll7VhporPOysNaNsBmLr9y9AwCwZd+Y72MnBAHq+EyYzGnjbyqFtBn5hhBGvDlRrtpc/7RfW5WKbaEModOP7ZWxYM/r8RlDHOaY5EV6uNcKLHo0/PD9SiGOcdeKFl63nZ68IIXJGERh6Z22dtOjgmlYJ0xc9cpYAFbJzSqFOINBm0GWT+9wkLZsWVit4wYr7z5FB9pOK4e4aa2igLWvl2t15WchizdzGYMfx0y1pj2ZOGzGQvTF8btPiD87TCZclYVLG7MisHDzsfDqLwfsGQvTBCZD3ISVpRDNgVmeP0/DebOsaDdl1xXLIFRqZssLmGqCJADM6S3wf/fmNTQWgomWTikkiEGWvGsMI97UMSfzw9JYpOMmLn72k+Va6nfJfqXAHunGoOr5F8+jKA2T3EquWqUQSbwJdJ6AU6VniYpewclXFQDL771h2OeF6Nrxh81YsLHuAHBowlurJJ4P42HWAYVuL23MqsBCFlX5G2TZA4kwJ4GpuBm1krGQ7clVuLnOZQzrohcn+bWateAZEemQhvuEUkgxevGm6j11+0yrdSmwCNPmpZlO9YJrLKYq/NxoJ3JQGaavPkn8jI7kmRKq6cJF4Sbg334YILAw1etMuVZ3/awd4k1B/9FpE07j3Ennsxn+fqrK0rJ4E7CXvINaegctEYvXkZeA0zRNW8BYrtUDm9ORxiIlyNGqjsaiWqtD3ryF0Vkoh5C10G6qVQpxWHo3vm5rec1l+GI73eJALJVXACBlLIKWQjQMsoLoVqpSiaSVjEUrIkfWblqtm5GUoVqlLHXRpN1qnH2OfoEF11gorhemw/D6OQxrrfD/rBwl12y2eQx2x1ARuZMikzF41qLTBJxxdyt4mWSprk1xHZS9jNzggWnAoE48Jq/uqmrdhBxjBs2EU7tpSnBc8BoTC8WgY25f4wYZJrDwOuHDLBx6pRDJeVNxURmGwdPGrU7adNNYiGn11fN6fX+On3jTUQoRdnd+WSA54GjJx6LF6abs+WkQcMqZnFCp2QTxC6xl7ZCqFVrM1mmLN3WcN13Em4D7eem18eg0jYXKMyRKvEyy+KyQrH3zBDSCQl5C89XU6HUMyoibBK9rSHUeuM0/cYMMslKClbFo/F/Hx6KsCixCuaQ50+eWu14IzQZfWN0fIyvj5ZY2BhNUtrpzdtNYXHrKEgyUcnj3Hx2HYSF74UYuoKW3+PvIglUZtmMcbGYMxmaqgfUEUWQsDMOwjiEFAk755hW2+ykpeCnE5QKQB5FZs3qsx4gdA1GWQuQFXy+wcJ5TnTzhFIjvhtfn0RlSVWyeRL2EZZClK94MmrHQc9MUz4OwG7tOGELmn5/uAuQdu1iPN01TWatiF3UuY2CoKbgLVQpRnPCtZCx0ds2yMt6tHZRNDIwqYyG/j6vm9eHRf3yV9s+xWS0rfj3vjIW3IJZ9fV5/kesrxqerGBI6V/zQGVmvw2BPHkcmK6nwspBLIWkPLKwpluo9kTNj4bxeRI+Duov2gT82VCkE/DWzGQO1uuka8KpaBzs+YxHTz+/z8LJQaSgKQkdPcPGm/ppYr5u2QMTLpZmdB9mMgf5SDlOVWuBurDj9QqJiVmQsnO2mVu3T7ebOTqxCLsNHXbeisVCaOYUSb/qXQpiegYmW3LoZepvzO1q1r/Wq+RmGoX0B+JZC5OmmtoyFd1sg27GU8ll+8wl6Y4/C0hsQBZztv4nLN6+gadmksXam6u87NRZoPl6tsZC1NzJBjORU1yZvOXXZAcuzQhrPCd811k7i7AoBwNdhlQ5IFViIGQt5rLobxRAZCznj65XZZudBIZvhpZ3gpZDWM6dxMysCC7dxxoB7ZMoCjnw2gwGPE9oP1U1XxzjH7+d53dzEyaLTFaGHW7oxlwoRaSwULX1hEFvtVGPWndNNM8L3Gs91DSyaB5nPGtykKqj7Zs2lpBQUbpKVgoyFrLFIg6DUC9+MRTMLN+VRChED2Erd+xoUW7f9unhUAbx1ravfV5UuwcpodlZgEbfGgpVCJjzEm1llKaSmLJWo4NNNA2Qs5PXTq8TJzoNCLhO6FMIzFoGelSyzI7CQWjSLGrVPsX2JpeCiKoW0MsFQJ2Mh7shEbwJnxiI6kyyg9ZqfGDioAguHpXeAYI0FirmMEdpWO/qMRfsDC3m2SsdkLHR9LBQpcDEA9uv4lR0cvVCVKf0yHqoypbU+dFhXSPPvuHbSrGVdtcFTiTdFQbfudNNSAAt3hnzNeN0n2HlQyFkZi9AaixTfvVN8aNEhn1SGYfi64rHdQi5roL/I3BKjGXGbb8Ugq/nzvG5uYsfHdKXm6lZoaTFaS8lHlZoTAwc5iACc7ahB3EyrNWuny02qQmYsWukKAYQJpynowJADsbRnLFR+BSKyxsKvBbLPx19F9LzwCyxqitfyK3t6iTc71yArnp/P200VN261eDOEj0WYjEXFfjyeGouqWAph4vlg6wANIUsJqnZLP4e1mpBy7feIlH1f26e/Oii6LY9iNMx2RfJiLIs8wxJVClRcxGUzLPlrcmDl3xViBYpDPeE0DlFYegPpGkTm0Fh0SGDh6mMhndMqgywRdrNyI5+1W0N7obo2ZRdcGdXN2JrU22mBRbzdCuxGrBrcpXzvBVsB3cAijMZCzm7odIUUcxlh/SWDrI7E86RzWSzEG1F/Kbx405pVYH2t0ILqO+iUvikhYyE/h9f4WhZvNv5uNYIu5r0zFuLX5DRgwWcx5qWQbIa3e7atFBIysImDThVvus4KcekKcTs3WTbSDdka2guleNOnRKcKyosd2xXC/hVXuynbLLlnLJRBnTDd1HdWSAgfC9n8bNxTY6EqhQTtCkl/u+msCCzUwh7vLgKxJs8Wn3Aai8bfYYeQ3f7kPjy5d5T/X3dehXjSus1X6JV6/sOiUraHQaxny5NMG1/LCI+1p7D9FnBmm5vPGG0vhYQNbOJA7opKe2DhVyvvkXacfkEvK0t5oTsN2VO86ZaxgPP42MycjiuFIN4bHu8KCSreDDArJMwQMtmS2+s+YctY5MNljDvBIGt2+ViIWYMApRAu3gxRE1eVQqwaqrc466n94/izrzzQ+PfHL0Ium9Ee/8uNgio1frG5ZixaLoU0/m71PBcdEQs5Z+07r3DVs75neYOovEmqgrjLKkUELYU0/m71gh4ohdfsRI28K241exU3VZ+dp3xjcCsd5rMGKjUTrzhhoe9r6nobqEoBLWksOqwUElV3mBt9GuLNbNa5eZyp1lFs7qG1xZsB3nvZaE+nFFIQSiFBrzkyyEoJSpMcn/SmKN4caKEUonLetHYx3ifUc0cm+b9/v/MozlwzVwgsvCMLMWhgk/dcNRYtO29Gc6L7ZSzEUohYNpG/V67VHRmNKv88M1a7Z8CMha6y3I/eiESzUSAHFq1mr+JGpf4XkX0s3PQ/t7//PGzePYJXr1/s+5q67puqUgh7rlv2QeVaKwbJnUjsGQsP8aYqY1Gu1fn54l9Cboo3A6yJleZr9+SzmKrUvC29FaWQsBmLNDeczo5SiMdJ57YLsbWbFsL7WKgUvH5CQ4YY+e44NAFAHaioEE9aKw1of1LYVJxMVE5wYjAgZyQAu3jTUQoRvqfa6bGFJy84qQb1sdB97/3o5Qtk+2/i7OYlaxPSip8fgcN11iVtvGJuLy7asETrnOU7Xz+NhaJjy6/7TCXEa0WD1U4s5824NBasFOKRsVC1+lZq2vqoMEPIas1UzZymi+94ucpfT2ZG0RUSVGPRCRmLrg8sTNNUul/61U1FsV+/MF8iKJZBj/OE99uRHBWm5LHdte6UPjEbUXUpn/RGlLGIqt3UnrHwFm/KgYfN9EjxvtrFm+G6MnTfez/6Inrfo4DdvFgWp9WyWNywRdyv3dSvFBIE3VKI183NvxRifa1TDbLibjflujGPWSFuzpt+ol8Gy+7W6qb2+89a2dk8JNNUBz+AVApp0SArzRqLrg8sxPpXThXN+mQsshmDt6S1NIRMkeqs1U3PQVhHJq0bnxxY+F0gPU277qmyEK1LGYtSRBoLtyFkQbF1hfg4b8qBRSZj8M9XmbFg4s2sEborI4qbFGAFfWkYUc4Di2awlYZgxwu/eS1uXSGtrMF+LaPWsam6QrxF4mqDrM4Ub8buvFn0yFj4CPS1Z4UIa5BuOYQFLf3FHF+D3MrmlkFWNnQphAyyUgA7oQD7BV/iPc7+FtAssJgS+qF1sSaLOoMawHtXcnhCyFg0gxodS2/APmDMqj/aH9Mb0XTTqFKgYnkjryiFeHWFAN67wwovbbWQsYgoM8OnNKYgO8CcN1l5KO1dITXhulTBLb012011aKkrxKfsqeqo6lTxpqrDJUr6PEqIqrEFokBfd1Mgblh0vSxEYTi3JnDZhIoGWT0hnTdpCFkKEEcBiBe8LPKSqQhOjf1CS1pQAafXjgTw3pWI4sIRuRTia5DlDIbk+QryXIWwRJUCFS9qpUGW8P1S3j3wUL2nVUGMOxSy3ZR9li2LN4tWK7Df/Im4sUohnZGxqLpk3xilvFpj0VIpRFO8KU83BXRKIY2/bQZZHaqxMGPPWFjTTeXrxku82ZiX1Pia33kg+pZoZyyEiaUDPmVzsRTCNRYBrzkaQpYCxIxFNuMMLNyiUrGWW8xl+Y3Oa8CMCtVJ4Cc0ZIiLPLsJ6i6U4gLrVj7xEkMFQZWVCYO93TSYeFN8jqd4U+gKmSjXHD3oXkTlY8EWlLoZrK0tDlgmh3lrpD9jYYmqVfQI7YL1uhmJmZCuxkKV0fIroyjXB00NVtqI22qarVem6Vy3vU0Q63w91zG3s1pOg5VCRM8jt5ZTNoSsaOsKCTc2ncSbbUQsXYgnvJ8K3hL7NZ4z3FT8Hp0MG1hYXzMMQ2teiHjTcWQstA2y3AMLv7SdLpFpLHwyFsw4CHC2m4rPUWUsePuwoJkBgnlZRCXeFKfPtltnwZxKOy9j4d0VAjTmPURhf6zbFaIS1fk7bzafo3Dm7bRSiFUSjQfbdSPdjFXnBRNiTldqwmRincCCZSyCiTdzwiRs31JILnwpJCpDwjjp+sBCbPvJKjUWfu2mjcfNaSp+jwidGlqvr+hIAfQWDzEVx0ow+uJN4aJyec5AC46iIpF1hQjBgtLHIusdeHip6cWLP5fN8JSl7ufpdh6FIZsxIjMnaxWHeLPDMxYlIZM1JczJacWG3W+uEEPZFeJznXtpLDquFNL8O67afyZjuHaGqDxmrNZRqxTidt6IBHXfFLPblueRegMqOm+G97GIN4CLgq4PLGziTeGT8M9YWDV5wMpYHAmYsXDb5eY1WsrEhcwxBlqz3XSyXPXNWIhZjTBEpQZfMtjD//3ckSnH90VBpyqI8VrEq1Kb4vz+IgDg0LheYGErqUWwcPYV0xFYsJ30kJCxcOvBTwMsQHQL7jIZoUYujMtuSbzpM1eI4TUrxM/HwmaQxSy9Oy1jUY9mHfCi16V8q1rjikLmoeYy4VmFlenQe/+V1gSupRDBxyIfTsRtadrSG1p0fWBRr1sXrvhBFH3MoeQTlWcsJoJmLNQeEn7GOY3vWcfGTj6VPbkKMXBySx+LI6NbyVpwAVqLMfRQbx4r5/YCAM5ZO9/xfXE3quro8LoByKWtuX2Nz/PwxIzWsdlKahFcNbzltM3um+xGzXQnQPt1H17o3CBEk6wogt5CVq8rRBX064s3nVmOjs1YxPgafYLwWURlgliyZW0bX9MJMIO6b4pZNFZmdQssZhSlkKlKLZCIuxOGkHW9pbeb4K7Hx2HNcmpslkL6wpVC3ARNOra9YsQst88FGZvO3gM5DchEqeVaHeMzVb5rDYLpkhEKy/+891w8+twIXnLsPMf3REHnvtFpx/e9bNqtIWSNx7DA4pBmoFgXMxYR/KJMiNbu0gO7ebH5JUDjXBO1CmlCx+ioEYBWAnUDeFH0aU1nKGcS+bSbqtLanWrpzS6RKK4PN3jGQiqFqDIWYubBbRCjimLAeSGieJNdR24bNXtXiKAHqtS1rzl+T0lxZNH1GQu3UoRs/Ssjl0LmhBRvqpw3AT3THXHnzaJn3fG//ASfrqLW/F1UJ2KrAk4x0I5CTDRQyuOc4+a7pvluvOI0zO0r4P2vOt7xPbGmKsN9LLKsFNIMLHRLIS4i4LD0psQki53nxVyGn5NBLYaTxE9jAUC5E2zNxyJYV4g6Y6F+rqdbZ4dlLJJog3Qbna4Ubwo6uqqiTOVGUI2F2MrO201dugdVzptAsGuOMhYpwM17oORTN5UXsPDiTXUgoCPQEjMWlVrDYlbXx2KAj+au8hkGqsW4v5jD4Ymyq9jIj7oZ7Q3Xj8tOXYrLTl2q/J5XxqIm1EEBsRSiK960/h1NYJEOkyw2YTffNOyZqdYDDWBKGj8fC8Deah1Nu6lmKcRrXoXbFOUuEm/G7bwJuM/ZUb334kbDmhXi/xolrtEJ2m6asVya/Zw3sxlkMgZK+QymK3VMlmtw5mjVkEFWClDtIgD/AVwV6UYUVrzp1orpV3sFnB0rU5Wa5WPhm7FggUXFs4fbryboh6jzM9p8NhU9dhrcSTXDNBZN8aZmYOHmhxKW3pCtZlFjWZ1n0MuvifTe0HQyFmKN3K0rKwi6XSGqlkZfHwvFxodbeqdY66IiiRkWwTIWjcdWaib/7LIaEwT9PI5kqoLuZ8BPvClkLIBw7sdkkJUC3Hb4RY+0eeN59i6CsOLNGo/i5YxFc/HQ7AoBGiOtddtNWSmkXK3zm5fqOf0tjIQHks9YeOF1A5ADRasUEkK8GcGvyeyJ2112qPDAwkDJZdFOEzrnP6+tC1bOkXSF+Cz+qtZWv3ZTlQasY8WbCdzwrK4Ql3ZTm3jTur2xjGxBI2URVLxpN8jS6wpha1WYtnPeFaL9jOTp+sDCTeyon7FoBhYhxZtur++XsTBN03GDFO25fUshxRxPSTJdSE5xUfkZuvghaizafaJ77TSq0oyJwKUQIaUeRQrSGkTWbvGmVQqJatptnFQDZywSLIV4uGiqNhCmaSo1YJY1fWeJN5NwhORdITP+7aZiFxm70ctjDVRw501tjYWz3VRHvAnYbQF0IYOsFOAm3vS39LbXcsOKN8V2VxG/Oqq4iLGF0qvDQyaTMdDfjO7Z+HXVidhqxsJEGjMWHu2mUlfIwYDizagU7zylW2lvdqAslEL8gu00wMt6HjtP8cYQRXpeW7yp6grx2ECIZUTV5OVKx5VC1NnZKHHLWKiuz0zG4Nkftr6phhvKiD4oOojluUFBNK/CGkLWOEfDmGSp5sukjVkTWMiltR4f5a9ck2elkPGZaqDap1uN16/2KgYW7LVtGQuNs8pyl2xmLFzEm0BEGos2n+ieGQupy2deU2NxZLKsZQgVlZ03w2qba7ePBdtBGb6D+dKAXsbCOg+CWDm7oe286VHWUF3ndm8UVcaicwIL0zQjs/b3wk1j4V7ybgYWzfUtr3FwgbtC6tbaYq2nLl0hrBSSD18KIY1FCnCb7MmyAH6zQtjOaLAnb5UWpvTLIW4ngX/GonFchmEFCKKNrc7Omc1/ONqcM+LZbtpVGguVeJOl/O2lkFrd1BqfHnWPflrEm2ImpxNKIXImUYU4ndKMohTCMyB6PhaqdlNVUOLmjVJoOm92ksYi6rZzN9y6QtwCThYksI1TPpB4M2ApJGONTZ9wcTMWx6YDrWUsojDqi4sUH1o0WDsW+9fFjIXK9YydFMxQKZsxMNy8UR+Z0C+H1FxKIX5taGzBL2Qz6Ck4b/46ttIsIGGlENUur2WNha0NM9SPiIyihxWvXAop5Kx5ITrlELfuorCEnRMQNbwUkuuMUkigjEVVv4vKi+ClED2NhXjjySo0Fp1UCklqg+GWsXBr62cbyLKUsfTCCkwDGmRlM7wUAlgTqUVmXLpCSGPRYdQVuwgAXAFfN32mYQonYhgvC9NlYfNz16sIkS1rAxQDC51olXWGMIGiapfH+65DdgKIC0q7+6q9vEnkUggAzAsg4NQVzerSkxIfC7ErpCclbqBe1HxmhQDyjIjW6/5FTcMqVRBjTUZ1vqe2OUYqXUYHiTeTajt3y1i4aaBEASegHl4oE9ogK2OgkMtwPd7+MWfHGTNKc4g3Q7Wbaj8lcbo+sHC7IYgnnCoyVfXLW6PT9QMLt3ZTv66QiriTVLg06qTk5Z5q1TXV7yM28sO+Uwn1IyLDS71vlUKsN2FecxCZzrwQXSt1XdKQsajVrbp4QRBvBlnkkkYrY5FzlnQi6QrRLYWofCwUQUndL2PRQaWQdmcsXAOLvD2wyAUJLEJYegPAosESAPXYAXEIGdCqeDO9kUX3BxauzpcGPwlVkansewCIGQv9Uohru6nP4lEWd5KqjIXGSSWm5QBvg6zwXSEW7T7RvfrPK8KughGkMyRq8aZ1E2+feFM892ztpmnOWGgMISspSjqRzAoJY5AlPFcuudpKIQFGracRu8Yivtdh/i9uXSGODWTefovLx+FjwfV4jectGGhsWOTAwjRN29h0QGw3DZ6xSG9YMQsCCzdLb8MwLOtWVZpSsYDNCeh9AGg4b7oEFqImgJ184yEzFvJrqh7Tasai3dkKwCdjIWksgHClEI0NjxZ+s2qSQDz3clkjFcfkh1XP9vexEHe1UZRC/DQWpmITw85J03SWPa1spv34KGPhDhve5+Zj4SbeZGiJNzV9Sxi6GYtq3eTZBq6xyAd33gS/p6Rg0XWh6wMLlRc/o8dDBS93EQDWDjdQKcSlxutn21vhbYBWinoisHjTnrEoSvVGIIKMRYpO8pKHQ6LYEsaY168fWLiJw8KShuyAKA7MZzI8zRxWb5MEOl0hJUULX1QGWV7jrVVCbXHHLAcmKqdOwFobqnVTqxU6Ddi1VvG9Tm/TIMuRsXBZ5+U1L0hXiLZBluTSvGpuLwDgmYMTtseJa70l3gxTCiHxZttRDadhsJNO9aGyG7u4gLFSyOEAXSHupZDGa7tmLKpWKaRXkbHQEREO9tgzFsW88+Pu95nG50eaTnKvjIXlMCkGio2U5UENW++oxZu9IURbUVMR2uQywsjnsJ4mSRDEeXMy4lKI6SL0bnzPVHrWiGJB+bx089gQd9m6u+Z2I8Y/iWQsXDQWzoyFfc3T6QoJWgqpSVm0tYsGAADb9o3bHmcLLLLhnTfJICsFeN0Q2IfqJd4UDVXm8EFkrZdC8qxX3WXhEB0R2UIzzkWYemfUUI+csVCUQoSMhdduzA2+oKTgJPdaEFR+JkFKIVGLN9PQFVIRzjFA8DQJGWQmQZBZIfaMRfjPzU/oDdhvrGIGwjAMV4Mt1461vPh66S1LiZgJlUJYxqJSM203al3xZj6Apbd2u6lUZl23qB8AsHXfmO0Y2ZqeMSztXhg/m7pLQJomuj+w4Cls5/e8xX4K8WYIjYWb6K/g465XlcZZA8BEM6rVTcezDAtDWQpp3kzqZjhjJLfFsR14ZyxaK4XUXNLWYWEtxOVqHSojnSSQ3xO/yYxpIIiPhbgLbOVm5yf0BtxdNAG7YZeI2++SFayo02xWJmLPWMT3Or1CoCB+vtrizVyAjIX22HR7KWT1vD7M6c1jplrHY7uP8sdZwk3rdwhTCknC4bRVuj6w8CqFeNl6q1JrYTQWbqUCPg/AVbwp+FgU7BkLXcc1nYxFTz7LT9AwAs6od/Kt4BUoqtpNQ3WFRJaxUC+QSSKasAHAQLHZetxmm3EvmKja63MoKkohrXxshmH4moe5uWg2jkfdrup1ThV9nIHTRlJ+Nrlshq9jos7CtRQibaZ0hpBZRnsBp5s2r6NMxsCZa+YCAO595jB/nGyOBYTLXKap/OxG1wcWXuJNr9kIXgZZQTIWVtrK/nW/ljLLEdGa4TDK/e71PjaWYWGoNBaGIfjbh7ihWOLUwE+NHLeMhThFMpdxfp4jU2XfMlDU4s1iLsNvdu0ScMqlkI7IWNT0MxZTEZVCbD/TdbaQdf7Ix+bWVeIVlPvNMkobSXaHsZZTsTPEbZ2XSyE6BlmiwZpOeVh1Tr74mHkAgE3brcBCnmwKIJSNPrWbpgCvmqxXLU31PLbDHZ2uareCuVkK+41GFsdZs0WGCSx1JvQB4BbkDFUpBLC6R7opYyEuCGKbn1jaYhmdSs30vbCjzlgYhiHY+bY5sGimh8W5MWntRgiisZgoBxM7e9FT8M4gVMXWXdfAwiVj4dGx1imBRZLdYb28NGy9N3WeNYhCvBlMPFtVnJNnrWkEFg/sOMyvM9kcCxCHkAWw9G7+3W7fIC+6PrDQ2RV4t5vab0R8EJmmSZbbKGHLedNtCJpznDXLWPiNTGf0FrK2LghVKQRoreU0ilkMUcECp7pp30GyGihg7woR3x+/z5NrdSK8YsKY40QJD14z9owFkN6WU7ehgiIloYsDiGYXzTMILp+VeL45SiEumTQvb5SSx9ybNJJkel7lZVF1CdJY8M4I4mMB+LutAupxAScsHsBQTx6T5Ro27x4BAIc5VuP4gq0BSU2RbZWuDyzYRkJdCvF3ahQXCdsgMk2dhdsQMt9ZIUJ0y25A5ao9de2HYRgYFgScbhmL/hZS4FHMYogKsdQjfqa2jIVwQzIMA0M9TDfjHVjUPXaXYbHSoO3SWNjPp2Iuy3dTYQ3T4qamkSGT099RfGY8sHDZCIjpcPlacPNX8SqvlVLgcxKEJFsgWWeIuBFy01iwTRNDx3kznzX4eq0j4FQFu5mMgReuHAYAPPqcPbCwl0KCzedJaopsq3R9YNGqeFPWMwTVWbiN2y76zAopCz4WTvc4/RNKLIeoNBZAaxmLqB0pW0HcCYi7w2pNnbEAhPkvU96fZ9SW3oCYBm3PzaMslUKA1oLMJAiisWBEUb6ydBsuXVweVuN+GQvV8XFXYM3OhHYTR+DtBstYiJlmtxIZC0IAddCnwjAMBBlE5uYGe/LSIQDAE8+PArDKHeL5ydaAat3UsnBPyuG0VVJwO4gXVf2LoRJ5MSouUxSZIPKIZmDhdkPys+0V2117C3Jgof+xiS2nskKa0Yp/gdv01nYgegaIC4J4DsgLC9NZqEYci8ShJWl3KURsaWZwi/eZdHpZaGks5BbDKAMLn3ZT1bXpNmvEs0zbYRmLJNPzXGMhTDh1E2/2CRmLIOtmj4f+Tkacbipy8tJBAMDjexoZC3buiOu52B2m81knNUW2VVJ8aNHgNoQMEKfYuc8KkXe4PGOhWQpxMzPRnm4qaCwYOhP6GEO9/hmLgVYyFi4aknahEsqpBpAxWEbHV2MRsY8F0H5bb36OCVk5lr0aTWvGQmdWiNxiGEE6zUuPBbhvRAB3Hwuvc4prLDrGeTPBjEXR6b7pJt7sEzQW/dLsJC9UXihuVF10PyxjsXXvOCq1Or/OxcCikMvwdUlnICFlLFKCVynEK71ZVRhkAcDcPr0bEcPVeZPNCvH1sTBsUS37mi6iIM9PvNlKu2kaukIAKFOYqp05Y4iXQvTEm7oeIjr05NPVFQK0PpQubmp19yCRkREMpoBgpUM3eJeGy2flVuMHwpVC/F4vbVgi9fhfS5WxcBdvWmvnQFE/sAjSBuoW7K6Y24OBUg7lWh1b943x61wu1QXJXCY1RbZVuj6w8Lx4PRzW3FzxgrpvuqXo/DIWZa40zjhOxCA7sBEhAJIV0oz+Fm4maWo3BdRpZ6/697CmeNOM4ffsDTEnIEpUYuD+YrrnhVhlLe9rQMzO6Zgi+eHvY+HsDODH4udj4SEs7xyDrMbfSdhMe2YsPMSbQTIWQUpRbqUQwzCwYVkja/HocyPKUoj4f71SiGBElmIni64PLKyL1/k9r12B20Ixt1dfYyEaM7lZertqLKpNV8ScsxQSZAd2+WnLAABXv2S1cmw60GK7aYoMsgCxTc/ZFaJ635h4c8QvYxFnV0i7NBYKXcBgh2gs/FquxWBcx7vAD79SiDwvQoQHu1K9Xkf/1Tk+FsmVQiwfC2e7qZd4s89lY6XC7/MWcSuFAMALVgwDAB7eeVQohdiPgx3XhMb6K/YQpmXNVaH/TnconsprF42FaZru4s0AGgtRaCMvhEE0FmxWgZdAzI3LTlmCFywfxoq5Pa6P4YFFmHbTiB0pW0WZsfBY9Jl4c0SzKyQW8Wabbh7WOdZBXSGan4Mo4AxyvbjBDbJ8fCyCdIXodKx1XMYigWXA8rFQiDc9MhZBEldByhP8s1cEsDyw2HUU5xw3H4CzFDKkubkBSGORGnTEm/JiIQYEjnbTAKUQcTCRfNLp+1gYtlkF4nN1MAwDK+f1eoor+c0kVMai8XdaSiEsYzFj6wpxT1PzdlM/H4sYAqh2ZyxUpRAr0OrwjIUg4NQ1lPPCz2JbHp1tO5a8uhSitenpMIOsJETcLAsxoRhCJn/W4rqpq4sDrGtTq92Ui6AVgUXTy2Lr/jEcHJ+x/WwGF5BrXHOmcDqkZMlV0vWBhZZ4U7p4xfKEHBAwW+9DAQZXAR4Zi5raj57bvzYfZ0vtRnxGtZKxSHJB0UGtsfAQbwbsComyhmxZerd3CFmnBBZiadE/YyGWQhLQWHh0HrmKN73KtB1WCkl0VojCCt+tVCmuS3tHprVfw+oK8X7/63XTch9W/PILB0pYNtwD0wTua84NcQQWbGaRRuDTlRmLjRs34kUvehEGBgawcOFC/PEf/zG2bNkS17FFgtcNgV28siOeGBDIGYsF/UUAwMHxGd8BNaKVtJuPBaDOWsiLvngy6s4K0WWg1Hq7aRoMsgD1ZEKvdlM2J2XMR1MQR8mn3QZZ1Zp7xiLI7i4p7IG69wlnL4VE1xXiXwpRaCyYeLOiXwrxcgVOI22ZFdJcr+oeGzjA2gyeuGQw8Gv4ZRNrwj3ALYBl5ZC9o43ARu7yGwrg5myfIuv78LYR6Hbwm9/8Btdeey3uvfde3HrrrahUKnjVq16FiYmJuI6vZbxLIWrldVW40csX/fyBxkk6U6373oiFuMJ1MBGgbjmtSGlqWykk8oxF+HHZfHFMyVle8tJYKC78QU1NgddNICztLoWI5TYG3z2lMGNR9SgtykSd4fPzlbD0Tx4+FnIpJOTk5STZtm8M/+/eZ32H0rXHx6Lx3ojnhWoD+d1rzsabz1qJG16/Qfs1dDUu1Zp3UAMAG5YP2f4vi0iHNVveAbt1elqyxCoCiTd//vOf2/7/la98BQsXLsSDDz6Il73sZZEeWFSEsfSuuAytAhrp695CFpPlGg6Nl/mOV4WYsZBf35axqNaBov254qwQwJodID83ClprN238nZaTXJWxqLqYnQFCxmK6CtM0XX+PqKebAu133iwrAq40l0K8Sosy4lycSAyyfHwlVLOF+LHwzKjbEDJ9/VfSvPL/3AmgUeK48qxVro9LclZIj9QVIu7iVe/lsQv68YnX6gcVjdfQm+EhrvFu3UfHLx6w/X9+v32xZxoLnVIIy5KnY7V1p6UrbmRkBAAwd+5c18fMzMxgdHTU9idJwuwKxAtedaOZL5RDPF9bGEAm/5xsxuAXgSpjIc9x6BH78qMOLJo7gHKt7hCY+ZE+gyxn2rniMV+ClYFqde/R6V5ty2HpVcw8SBJ5CBkgiln1fFqSxGuCqEzkpRBNS2+1xsLHx8Jr09NG501Ra/a7pw56PrY9002dGYuo9Ge6Zcqqy4BDkROkwGLBgD2wYA0BfvOKAKvdNM36CqCFwKJer+O6667DOeecg/Xr17s+buPGjRgaGuJ/VqxYEfYlQ2FlLJzfE5XXol7Ca/cBAPP7GyeCX2Dh1d8MCO6bisVDVuyLpZAgzps6iC1ZQbMWcXRLtALPWAiLuFcppLeQ5Z+zVzkkloxFm3elVUUpRMxY+KW/k8bWZeVzvtlLIUkYZHn4WLg6bzb+9tr0tNN58+kD4/zffqVCM0HxpuxjIZ4XUd1wdbtC2OduGO73i8WDJfQJGWc5sAiia0oygGuF0Ffctddei82bN+Pmm2/2fNz111+PkZER/mfXrl1hXzIUOra5gP2ityabqj+8ec2MxQGfzhC/3Twrcyg1FtJuUjzWqDMW2YzBL6SgOoskrXx1UJkReZVCDMOwLM09hrDFIt7kPhZtct706Aqpm8B4m7pV3GCfo2H4B3jJizd1nDcD+FgU2j/ddP+otXE6MOa9ibJ8LJLTWExX6qjVTV/xZhisjIX3NVDVsJg3DIPfMwD7xGnA0jXpBBa1errWWzdC3aHe/e534yc/+Ql+/etfY/ny5Z6PLRaLGBwctP1JEk/xpiCgFBcMr4FCgFAK8bnYfAOLnLv7JjsGrrEI6WOhS1j3zbSVQlQZi4qHQRZglUO8Bm91s3hTDFRL+Sy/EerUfJNE18MCkH0s4h9CVvUaQsaDXUkknnKNhaiz8etYSNKBV+yQmyxXfcWbYeCBpKZ4029duPwFSwEApywfchzjcABdU9p8g9wIJN40TRPvec97cMstt+COO+7AmjVr4jquyPC68eWarpaVmmm7Efk5XC5olkIOTeiVQnwzFopSiCNjYQssoj+p+ks57B+bCV8KScmJbrXpiV0h7hkLgAk4pzxHp8fhY2FZ+bZbYyEtdL157BudwchUBckWLr3RXcSB6C29/TJ6NY9SiNtAK7bbLShLdO0dUAdIgcVExVPcnGTGopjLcCdi8f2J1BVXM7CzstvewetfXbAOrzxpEVbN63N8j+maxmeqKFfrrqMXgPQ5HbsRKJS/9tpr8fWvfx3f/OY3MTAwgL1792Lv3r2YmpqK6/haxm/GA9vZ2DMWPhqLAZax8IniTe8dVt4jY1GWFn3blL4Aw3R0CTs6nR16WrpCVJ0+FR+ty4BGy2kcFzTrxpmq1HjwkyTsRi0vZGntDPG6ectEbek92OweKlfVAueKRzal1yWAtHRUzuf0Ce6Sfn45cTEqlAbLtbpnkJPkrBDDMGxeFro270HQnW7KBxz6BK+ZjIFTlg/za0tkoJTnmR7tmUUp2ci5EeiK+8IXvoCRkRGcd955WLJkCf/z7W9/O67jaxmv/nLAauO07XB9Mha6XSFs4XY7CdhORa69AkK7ac6ZsVCdnK3SH9IkK45uiVZQBRbspu128et4WcRRChEDxDAeIq1SVnSFAPoTX5OmFiA7Jg56iqLuLk7GVJ0nNY9zzG2Krcr5lL9eM9A3zfZlLeSbnFc5JMl2U8DuvhmHl05JsxXcT6CvQzZj8HKIXxY8bRliNwKXQjoNvzHLKpOsmocQCwjebuqasfCYF8Kmm7LHiAvboId3RlgsAWPAwCJlGguVNwQL8NzEuJaXhb94M8odWT6bQSmfwXSljrHpKhdxJYWbI2mQoUhJEkRjIV4vUYidsxkDfYUsJso1jE1XHV4EfDPikbGYqjRugmyjwUtRitR3Tz6LjNG4YU/MVLlgMUnk0uDRyQqWz1E/NuluBT4vZKbK164oRx1od4V4tLIHYdFgCUcmK9g3OoMTFrs/Lo4py3GQEiPm+PBbjFS23n7izXm83dS7FMLTZD7iTWW7qZSxWDRY4t+LJWMR0n2zxrtC0nGiq0R2lbpTpCiiUwqp8ws6ksMUXrvxvo96BDVxIWfFGLz9TaOvPkmCaCwGhBtxVO3ZXgGo1waGlTVMUxYVu2ssDMPgu/IwwwGD8NT+MWzePeL4+uhUVfq/+znKA4uE7ihixqIaQ3lA28fCY/hcEBYPNdb3fT7zTCzNYEsvFzspP7zW8etaUN2I/AQ5bLcyPlP1jGj90lZegYVs6S0GFoMxBBYDId03+QCetAQWik6LGk85u2UsNNpNY8rM6AQ1cSFnxRhBVOpJ0s6MBeD9WXkdm9ihIt6oZB2VDPsdJmIMLHYdnsQFn7kTr//C3TgiTWyWNxleAU6Ss0IAu5dFHOUBsSvEK1PvNXwuCIsGGus7myfiRtp8g9yYNYGFW0RZzDs1Fn7izcFSju8yvMohfjuskoulOOBcdOLPWITUWKSsFKISXfmJNwcFW283eCkk8sDC/7XjolJXayyGAlgMJ4muUA6ArXQQRVcI4B2AMp2UStGfEXxiJgUBp1tgx+gLeU0G4Web9wBoHP8Te+yuyHJHhGdGL+HMJZ8XMlMLlMnShW04TVOtgWNEJRxdNKQXWHSleLMT8StHeGYsXBYkwzAE9033dLHfDqvkMpwIcKZJFw1aNV1WA4+S/pA757QZtqj6//muwrPd1NvHwowpM8OEo15p5riouLwvlq23/jFNlqt485fuxfXffzS6A5QI0hUilkIGItIneJ0nrFOk6NIqKLtFAmpLdRF284yzHVk0wfqDFFiwY+UdYx4ZPavdNOIDdEGZsYjw2hTFv14Zo6qHADcIiwf1SiGdIt7s+sDC9+auEG/6aSwAseXUI2Ph1+qqyJawY2YXqjU2PYf/eOvp+PcrXxireHPcZ3y4TNpO9F7F8CC/Lp8gpZDoMxb+rx0XbMcs1/gHQ5RCvnbPs7j76UP41n27fN0KwxJkdyiWQlbPd3oHhMGrFMKcXot5t8DC6UvhpnFh9AsCxbgQM67PHpq0fY8d68LmpkYnY5FUKUTUWMRRpsxmDL7p9Ars/DauuiwearzH+8b8MhbN40vLTs6Frg8s/LpCVOLNqo/YD9DrDGHpc7edsmXmJE1XFTwNRMX4q05ejIs3LHF9vVYYaLndNB0nulK86VMHbZePBQAMFNtYCnFrN2UWwwECi6f2W3Mlth+ciODonATSWAhZiqXDPZG8vpd4k6XLxamqIqqWUz+NBbt5xlkKOSToKmTbbhbQMGGht8YiHnGzG2JXSBw+FoBeKcoqtbd2K2Wl7r0jmoMtU7KRc6PrAwv/jIVC7KexgM3rY+6bHqWQmndQ46axEGeHxOGyqYJnLAKXQhp/p6YrpLmAV+smv3F6DSEDhBuGR7bGa5hdK/Cgpg0+FhWXGSpMYxGkPCMK/545EE9gEeQG0lfI8SBTni4ZFi+/E91SyKRidIBbJi2s7ikIYjBxQNoksTWRCQu9MxaNvxPTWIg+Fj5GhGHpLzrLVzJek5ODwAKLQxMzSsNERto2cm4k3xydMNoCStVsCa+MRbMU4jWcp6oZ1DgyFoJYyM8qNiq4j0XYjEVKQlTRSGyyXMNQT8YaQuYhxgWSn24K6HloxIWbeDCM7kMMsPf61InDUguQds5kDNz9wVegZpq2enkr6Ig33QILLjYUNRZVb41FEl0houmVuJaZpslvqAsHWWCh0W7ajoyFjxFhWAJlLFp87bm9BT5eYv/YDJa5ZNkoY5ES9DMW4nRT7xsRoFcK8YsuuXhT0liIKdKkTqD+sO2mKesKyWcNfiwsYPMLFMXODLfWsrhKIYM9/gPQ4sKtFMI0FuPlqvbo9MNCYOE3sCosfjt8mTl9BYeRVSt4dfBYGgvvUohYr/fysQCS6QoRj+fA2Aw//2eqdZ6FWKylsWj83Q6Nhc6E0VCvUfQP7Lym2gYhkzGwkLWcegTmtZRt5NxI+eG1jm5XiCpj4Sne5F0h/hkLt59TdM1YRKM0DkLYWn/aDLIMw0CvZG7jP4SssYDU6qbrbIC4Aqh2tpu61fjZ+2Ga+hmsJAILr9kaSeAp3vQthThFxfz9z7n4WGjc2FpBzEoADV3SRPP4xJINy1h4BThJzgoB7F0hUXVmyOi8/1WfyclBYFqW/R4tp3HYl8dB1wcWfj4WPYVm1kChsfA6URfwjIVXu6l3NGuVYdwyFsl9PMN9jRvcVKUWaFRzGk/0kmSS5TUgCmgsUixgcLvB12LakbWzK8RtQS7mrNHpOuWQcrVuu+kc9tAdtYJfe2bcRCHeDNRuqshyRMlMtQ45Qce63NjNtJjLcM2NTikksVkhgo+FW9t0VK8xrtEVEkW2hLWcenlZUCkkJfjPCnHvItBpNz2kYZDl3m7q3RWSbMbCErvt8zFpEeHOmyk60WWTLMvHQv1+GobBdyduN9L4MhZtdN70OM8Ge/QzKXJ76ZGJeIIkdrxuWYG4sazOg2ssehWOsBWf3W5fSN2TLuJOfMXcRk2fCThZxqK/mNO0vG/83ZaMhebo8qDotPtG2ZGySCOw6BTxZtcHFroaC9s0TA3/d1a7PTJZcVXx+qmVmdWvW2AR1YwDHQzDsPzqAwQWtYR3Kjr0SJ0+OoOC/Loz4topzGm2dsa1y3ejWqvz81x1M+QCTo1MijxPIbZSSEwpb10WeHjXsHZ1Px8LVcai0KZSCPvcevJZ3vnBBJwsA9VbzGp1jCUt3rTEsDFmLDTafaMswzATRC+TLHaroYxFm/GLKFUZCx2l73BPnl9Esse+7muz1sgZSbzpNfUwThYOMJMW715qkVSWQqTPlJdCPC5+P61DXOJN9p4fnigrZ8bEhdjSrLoZcpdJjVJIUoGFXxdF3LDAYqJcc9zsyz6lEDaITLT0Lmt2hQQVVOvCgpy+Ypb/bqy+z7JQfYUcPxe8xLxtmxUidIVENROGoSOejTJjsVjD1juudShquj6w0J1uqpoV4nWiZjKGr0OhnyMcL4VIlt7lNog3ASsV5yUekkmb8ybgXgrxEv0x22K3OnJcPhZzegv83Dw0oR/QtYoYzKpuhkFKISwzxNa6I5MV7W6SILRDeyTSX8zxc0tuM/crhfQIXQzjM1X87qmD/Px0+30GY558y7QbvYWc0OVWtn2vTyiFmKa7p0PSIu5eRVeIVxdfGHQyRn46uiBY669Hp2HKuvDc6PrAwq8rRKVzYBGwWxsYw28KpG9g4VIKadcCylJxQXwI0maQBYilkMaCYPmJeGUsvOvItZhU75mMIewWEwwshA4L1fkZrBTSeM+WDjXq9LW6GYtmpFL1Lh0kAf+sHIGFdymkT9AEfPgHm3Hlf27iFtqsHCYzFPOUWfa59RayjvZ58XvFXIYH5W6fq59nT9SI76dOF1+o19AILKIyyALs4k3XtncSb6aDmo9Aqkehsaho7HABYIhZH7sMa/ITYaomqwLCAppwWx2LmAOVQlLYVy2PTvcbQgb4j42Pa2w6YJVD/CYbRonVHqlO3VulEA3xZvPaGe7N8wU/jnJIu7tCAGBJM1393BFrroZpWoFUn4sZ19ymU+/2gxP4/kO7bd+b1+8dWIg6gihhJazeQhbzB+xDFdnNtK+Qg2EYvqXCpHfSvUUri8JKFVGfF6x8lYSlN2Ctv5PlmrvWi5dCWn65WEnR7SAewmgsdDMGwx4qccCqobplPtLUFQIIgUWAG5zVbpWeU4kFi+yGZw0h8wosvFvq4iz5rJrXGJIV14wNFX6pe2bcpdMGOzlj3aDmNG+gh2MILMqamcQ4WdMcaLZD+KxGp6v8/WQZDRmWEXjuyJTje24ZC1aOAuLJWkyVVaWQZrtp2SqFAOIsIe/sbFI7adFhl703UYs3+zWmy/JNSwS/d08hyzOFbgJOKoWkBD8fC9WEUR2NBSCOl1YvonzxdkmPqoIawAps3KYexkWowCLCVGBUyK19fm19gCWUc3PA5AtnDCWfYxf0A7AP8oob7hTpFlgEqO+ztHlPIcd35oc9/F3C0i5Rs8hqFgQKk0CZ3mKglOPXtMxCl4ADcL9JZDMGv6HHEViwDU0pn3EY/k3OWMJOwLrJul0fcc3rcEOcPsoDi8jbTXWcN6O90fsJOOMqyUZN1wcWup0ZU0qNhfeH56ex8M9YuHWFtEe8uVgILNxqfDI6c1WSpkcaUR2kFOKe6m38HcdOYe2iRmDx+POjkf9sN6a5JkB9I7TmhWiIN5vXTl8ha7XPKoLtXz+5H5f/2+/w4LOHQx2zXxdFErDP6onnR/jXnj/ayEK4ZSuARikkzL0gTp0FCyyKObvGouHIaWUzAP/roxpj4O0GC3rYexO1I2uQrpCozklryillLFKNr49Fc/dTrtb5Y3VLIX4ai5mqd+aBv3bNem2gfaWQhU3x5nSlrnVDAaxSSLtsllXIxjY6Fz9vqXNL9ca4UzhzzVwAwB/2jGL/WDI6C9+MBesK8Zj4yuB+CIUsz1jILdiVWh1v/8r9eGTXUXzm1q2hjrkd/i4yL1gxBwDw9IEJHJ0sY8veMbzty/cB8M5K5LIZPhEZAP7vW16IE5cM4u8vOdHz9WINLISMKgsspit1TArttEwz09+0/PfXIEV+mK6woGc09lKIv49FZBkL1hnionMj8WZK8J0VUrB2bEzQppsx8NVYcKdA9a5QTJvOVJ3i0aTV76V8lpd3dIWESavBdZAntVY06qB+E06tUkhkh8mZ31/E+mWDAIDfbj0Y/Qso8JttMRhEvCmIAHkpRAosxDLPpmcO2wJpXdrdbgo0Mg9rFzayFrc/uR8f+8nj/HuvPnmx53OXDFkTK1++biF+9r6X4s9feoznc8KMsNeFBZelfBZ9gvPuwfEZh8Zi0Md6vh07aVbyjKsUwrI0E+Wa6/mqM7AyCLwU4pKxYKMFyMeizdR8Wg1Lwk2f1+SrerVcX41FxSdjIQQWosaDpXzbIYhcHFBnwcoM2RSVQuQ2MR13PL9UrxmzX8fL1y0AANy57UAsP1/Gb7bFQIB20ynemphzDSwe222VDqp1k5cPgsAC/qS1RzKXnLIEAPDX33kEv3vqEPJZA3f8zXm4+pw1ns/721efgIwB/N3FJ9g2NF5wG3GXrGgrsHIYWwOtzpAZh8bCEm8m247tBbvO4yqFsCwm4J6pqfCAKppzcqGPrTeVQlKCn8YikzH4QsVSg7opV780pZ8IM5sx+MUgdoawf/e41L/jxO/EluE37RSd6HIKU2e0cX/RuyukGmFbmYqXrW0EFr/ddjAWcykZP9+FYLNCrPPVLbB4+oBdmPqsIH7Upd3Om4wrz1rFd8sA8GfnrsHqZreIF+eunY9tH78Y/+tlx2q/ViIai+Y5wMohB8bKlqV3s9zQr5nRSzJz6chYRHxeFHIZaxify7rA7QwiCmr8NnYk3kwB9brJrWa9TnimdXBOw9TLWLiLN73TzY3XdvpoiDXrpFk8aLf29UPHLjtp+PCmaVYK0TfIct2RxbxwvnDVHPQXczg8Ucbm50di8S0Q0e4Kmar4CnmnhFKIm3hzpxRIbD8UvLXWCvjbe64tGCji828+DccvGsDrX7gcf3XBOu3nBt1pxhlYsKwVW4PYvJB9o9O2IWSA4GvidoNtQ+2feYbwjEUMr80CbLffuxLhdFNAMMlyK4W0QcsSBrWbS5dQFXZ+WY+IsqeQxeh0ld/cdUshQz2tiTeBhip/bKZqK4W0M7DQmbAnUkujeJPXRlkpRMPS26fdVGfibSvksxm85Nh5+OUT+/Caz/8OA6Uc/vVNp+GPTlgYy+v5lUKYj0W1bmKqUuM7VxWixoKZPckZC5ahWDbcg91Hp7AnRCmEayza6LzJeMUJi/CKExbF/jp+YwNaQWw3BYClww0NyPNHp/i1w7ICvgZybZhh0dss0/DNYwx324FSDgfGZly1RlEaZAHAoiGrO6daqzt+LpVCUgBLgQPeEaXsvqlbCmEZi9HpilLcU/YxIQKAnkIzW6IohfS2oRRitTvpuW/qZAOSRja20fEFYTuycrVuE9Iykkj1XiiI/8amq/j4T/8Q22tNcO8J9TnWk8/yxcuvHDIh+FioprWapomdhxuBxVnNDpgwLqMzKSmFJEmsGQspa7V0uHHtPz8yzU3PWPavv+hdCmnHDU92OY26KwSwMneuJdKIfXzm9xWRzRiom5YLqgiVQlJApWrd7L3Sp45pmLrtps2L3jTVJ55OYMEuDrGlKQ0ZC922x2rMO/kw9Aljnut10xL9eXyebOEE1Itn3BoLoCEKPGaBVat/5sA4LzNEDfsd2U5UxjAMwcvC+6bGjrGvkOUtlWPTVX7+H5po1OwNw2qtDTKPxvk6XZ1otcECtZEYxJssgGbrny1jMWPPWPAbrEv7cdRGUTqwjAUjH8Pmxt+/I9r1L5MxbBb/pmnaSpGUsUgBMzVr6qLXByG7b5Y1203z2Qy/IanKITqlkEGFB387AwvuwKc5L0THLjtp2GdSrtUxLkxjdDODAhrnB+vZVy0iSWQsSvksfnHdy3Df352P+f0F1E3gyb3xmGaxQFhUvsv41ZcZ4vk61JPnLblsXggrgywZLGHlvF4A4QKLSZ8sSzcyp6/xGcQx+XZaaDcFrMBi9xGrFMKuJb8R7mnIWMTx2n7XgNVxFt1rs8/hwWeP4LLP34U3f2kTz2JTxiIFiH4UXtM3WY3ROWbb/+0Z8vCysJw33RfCfkV/OC+FtCWwsMYn67hvVlPovNknvG+iUZOf6I+bZHlkLOJeOPPZDBYOlnBM0+Z7l2K2RBSw33Gg6L7799OdMKb4+ZpDJmPwXfahcRZYNISaq+b1cS8H1QTHfaPT+LOv3I/33fyQUrw6OQszFvP6GtfjkTjaTSt2cTkrhewdnQar7MqzQpKe/uuFvD7Gsbnx87epRtxuCoD7pPzTT57A5t2juOeZQ/jeg88BsKZJU8aijfBShM8NxU1joXOiqrws9o9OY3S6YhlkubT0AepuBL4zyye/gDJb4nKt7ntDAQTnzRSd6LlshgeLh4TAwu/zHPAwAYpy2JAOvO0sxM5eB79SCGDvDPFiUhL6sXOItcyxjMXq+b3895os1xzn19fu2YHbn9yPHz78PH78yPOO12Hp+dmYsTgyWQ5lKubFtFQKmd9XtAXfPU3jLEAY0ufaNdX4O9GMRVHWWMRRCvG+BmoxZGzXLRpwfO2+7Q0b/DiHIUZJVwcWukOLSo7AQt//XRZX/fDh3Thr42247Ma7cKg50Mdrp6zaFbazFFLKZ3n6kw0k8iKNGQvASuGyjEUx5521Arx36EnXkP2GEbWKFVh4lEJ4i6F3gCmfryvmNsodu5qjxVnGYuXcPl4uAZzlkF89sZ//+5eP73O8Dp9JUpxFgUUz+2Oa7kZ8YeHizWYQnskY/LwD7LNP2LVRrtYd05iB9jpvMuLw/fHLWMTRLcZ0SCIP7zoKIN5hiFGSrrtBxPgNAWPIGYsg1sEsY3FkolE6+NfbtsE0G7s0tiCzx6hQefC3sxQCWDqLQxoTKisRi5eiggUWrDtBx63Ra3S6tTNJ5pLx62dvFbbz7PfIWHhlcEREHwsAWD6nUe5gI8LZOPhVTX3FEkXQtOvwJLbsG+P/f+DZw7ZSSbla5wG/V+trt5HPZvjN7UjEgYWcsQCszwiw1gGgUTJju/JDE87jaId4Uy6JuU2WbYUBH9Gqn7NzGNYvG8KrTlqE/mIOG1+3AQDw3JFJVISZUinbxzlI+eG1hm7fOxP1TZUbj68GmNWxgLnVjc9g99EpPH3AafyzcKDk+BpDtXiPz7TPeROAbdKhH7UYxEtR0CcFFl6dOYx+D5OspBdONhDugKaI1o8Hnz2CXz1hZQFYatezFMLnVLhnLMrVOn9vepulu5XNjAXramFTW9cvHQIgzkOw9CO/+kPj2E5bOYxsxsDB8TL2jVq/u9gd066Au13Ma16POoF+ELh4U/AyObap7QHsGQvDMLje47DiOOpt9LFgxJHhZX4ubtdAJSZR9xffejoe+8ir8KYXrUAxl0HdBPYcnRaGPqb71p3uo2sRXQtgdgOfrDROniCzOhZyC9YZbG7OQ1gyZA8kvE542QCnWqvjcFMB7jUtMU6CBBa6LqVJIwcWOm6NXmnPpC2LuTV2BLvUHQcncMWX7sWff+0B/OqJfajW6lz/IJ+rIoM+bouA/YbPzvNTlg8DAH71h/345M+fRLVuYslQCSvm9thec4+QjWGBxSUblmBN0x5b7IhhXQqFbCb1i2rUuNmkt4pskAUAxy60AgvWnSAfx0FFh0o7nTcZcQScAz5W/zWNcQFhMAyD/1nGM4CT/N6U9msg3UfXImVNC2DZVY7NDNGJgNnNf//YDB+09PJ1C7R2yACwoN8a/PPNTTtx8j/+AnWzsTNmO5Wk4cOINHbLOq6W7WBAzlhoZH+Yk6qccjZNU0hBJhxYRHAzufWJfXxB+j+/2ordR6dQrZso5jLcxlnFgIaPBbvh54SZOxuWDfHOnK/cvQMA8KYXreQal0VSmWd0uoJNzzTEaeefuAjHN8VrW/ZapZHZ2GrKcLNJb5UZqd0UAM5rDsMDgJccO9/2eO6q6mHclOQyIGttYtFY9HjrjKoJGASumGNplnQ8edJAuo+uRSoajouAXYAp1rFKLnbHIixjsX90Go8+1wgs1i8bwocvOwkAcL6PJfMCITD5l19u4d4X8/oKbdMt8GFEGqlXdmGlTmNRsgtQdS5E7uEh/d6iNXxSmRkWWETRDbBDmMvx+POj+Pq9zwJo1NO9dpg6g8gmy049UCGXwYcvOwm5jIENy4bwoYtPxLV/ZA3ekjUW//PoHlTrJtYu7Mea+X04fnEzsBA0F2xh7/doj+1WmOmY6oYellrd5BsvMbBYMbcX1/7Rsbh4w2K8bJ0UWDSPQ+WpwUqiSU457klEY+GtM0qiRCpqlsop3cjJdPVVqiveFKNSUfHs1SbKWNbs/X7uyBRPL5+yfAinLB/Gmnl9WLfY2TokwvQXz0l+Be1cQIOUQqoJixp1Ybs8lm7XEW/y31vK1Ig39jhsg1WI3QAjUxUeaISBtXsWchmUq3V86bfbAQCnr3Kqz0W486ZGKUQWVP7pi1bijWesUHbisBQ7s/n+5qadAIA3nrECAKzAQshYsDHrXqWbbmVOhGUxhmhbX5LWuQ9ceILyOVzrociitWNWSJ/cFRJHKcTHyyWOdlMZ3mV1eFJ7jlW7SffRtYiug6ZoXcwETYahJ/hbMbcX2YyB8ZkqjkxWkM8afGF8yXHz+c3KjQUKHcX8/gLedvYq39eOi2CBRTw1xlZhuyu2Kw4SWMg7Mtswu4QyM2I3wOEWXRefa7Z9fuSyk/nxz+nN4z2vOM7zeX49/IDTw0LErb33uGYd/9lDk/jN1gN4bPcICtkMXn/6cgDgpZBt+8f5wr27GXizevNsYl4MGgtx6KFOZhawsmgqEWm9Dd0Kcqt0nKUQtzbbuIcTAmIpZEp73ES76eqMRUXDUhuw27aKbnR+vgeNx2WxYk4PdjR3hesWDbhOjFRRymcxv7/Ib+L/cOlJeMe5a7SfHwcLBizdhxemaaZyCBlg7a6Y1bpOkMi1JdLCydK8QHLiTaDxO4xOV3F4ojXXReYKe8bqObjp6hfh9if34y0vXuUQ58kwRbxnKaQS3HNl8WAJA8UcxmaqeOfXHgAA/OmLVvAb18q5vSjlM5iu1LHj0ASOXdCP3c2MxTKfY+5G4hBvsnWukM1oCy6tNnRFKaQNzpvZjIFiLsPLx3GIN/sLORgGmwdVdZRbkmhD546oI9PoyTeEzboavnaR7qNrEV0/CsthsOoYzKPDyc02OgA4fdWcoIeJM4Tn/NHxCzwemQxWScB7IbOVCFKmsZBLB0EyFkcmy1yUClheHUCyWpI5Tf+TVjIW9brJMw5DPXm8bN0CfOQ1J/OsgRdBukKCLOqGYeAFK4cBNHaCvYUs3nv+Wv79TMbg7oNbm+UQ5jwotkPOFuIMLHTKvQzebqoqhfAhfcmuA6L7Zhw320zG4GVp1XVQSUBjxtqz941O8/tT2jMW6T66Fqlo+lHwXuXpirK3249Xr7fGXV+yYUnQw8Slpy6BYQBvOH05b7VrJ+wGO1Wp2aauyrCdAhCPcKoV5vXbAwudRWdObwGZ5u5EXDzFjhCdLFZUzOULefiMxUS5yuc+MJGyLiyTN12pc72SjOW6GSz5edkpS/m/r3n5sY6SICuHPLl3DFv2juHJvWPIZw1ccOKiQK/TDcQTWDiFm77H4SJuBtrnCFkSruu4rk3VoEhGrR6/mHJBfxEZo1GSZZqxtAcWXVMK+dKdz8CEiYvWL+FiF13x5pBQR2N+ErKgyYtLNizByFQFQz15nHXMvMDHfukpS3H+CYtS00rXV8yhJ5/FVKWGg+MzDk9+xlTFXQDWbuSMhZd1NSObMTC3r1GWOjA+wzt+qgl7WDDm9rWesWDncyGXCRz82UfJV5Ttz+NsSmpAsfEbzliO8Zkqpio1XPPyYx3fFwWcTMdz3vELMeThYtutiIGFaZqR3EAt103961Y0A5SPI+l2bMbBiL09VHjPEIp+CJlMLpvBwoES9o5Oc5F/2rtC0nU3aIEv/fYZfOKnT+LSG+/i/fG6pZC+Qo6PemadHUEW4UzGwFtevAqXnbrU/8EupCWoYLjpDURYGrwnn010J6/DPEdgoXfjU7Wc1mrtCixaz1iMCGWQoGQzhiAgVZ8HOsPMVBiGgT87dw2u/aPjlDejE5cMAgAeee4ofvhwYyDZa1q4vjoZFljMVOs8Q9Qq3BwrQGaWucGWq3WuXWK0w3kTAK6/qNHB8i9vODW21xBL5TJJbToWSd1Q5GOREK974XIsG+7ByFQFX/5do51uuqynl8hkDL6j3d9sNdQxVOpmWD3VS8A5FUK4lxSDpbzthqW7o1a1nFbbNA8lyozFYMAbP8NvGBqbORI0sPDjhSvnoJjLYM9IY5fWW8jOyjII0NCvsFJeVOUQeQCZDsVclgc58vnQrozF1S9ZjQf//gL8SbOjKA48MxYJdcUtGbQHFtRumhAfvOgEXH9xI3q9rWkPzGZueA1aYjCdxf7mfIJSyj+4uNFpORUzFmkjkzFs5RCdUghguULuEeZY8F1JwrsElrFQ+QboMq4xxdQL2SVThi22YX++Gz2FLF4hmMu9+uTFqQxgk8AwjMh1FmEyFoBwPqQksDCM+B2Kxa5BmaRmCC2WMhZp11ik++gCcu5xDae4pw9MYGSygvHmRDods6lBnrEIXgrpRnjLqUdnyJRi1kCamGcLLPR21GvmN/Q52w9O8q+1y12UZSxamWrJs0ohz2fukukSWMTpiPnXr1yHBQNFzO0r4LoL1kX+8zuJyAOLEN1vALC4WQ6Rzwfebpqy7rAoGHCZIVSrm2ADePMxt9s7A4t0v89dI94EgOHeApYOlfD8yDS27h/DBMtYBAgs2AUz2yYoylhCLfex3WkuhQAN87Enm+2KujvqNfMb7YzbD47zr/Fe9XZpLFqwcmYp77Cf0WKXHSojrMZCh7WLBnDPB1+BuqnXLtzNcHOqiEshQTcFi10CTdadnbTGIgncukIqQkt63Oen7DhLGouEWSeoyVn9162rQYSJ255t2gwP94a3UO4GFg81jIj2HHUPLJiGhY3LThti665OOUx8zvaD1nwNrrFIeJcwN4LhU61mldh5kHQphJHLZmZ9UAEIs2MiLoUE1ZIt4tOc7edDvU2lkCRwG8ZXFgKLuEsTi2SNBQUWycL637fuG+MeDDoZC+Z7cKAp2huehW1tIsztjTkequA3rZRmLJgAFQBWNVuQ/VjdLIUcmazwRdwamZ6wxqJ5Tk5X6tw6Oyhha+mMxUPN1LdLxoIttkyjRMSD18jyMLAJzkHPC3mAHIMF30n7WCQBt7aXMxZVMbCIWbwpl0JSHmyn++hCsE4YuTweoP67WIoIh0O053UTbKLe8xqBRU9KNRYXnLQQhgG85Nh5WK1pPNZbyPFzYXtzKijbmSTdbtpXyPKUZ9jaOjdCChn8+Yk3WVvugpgFdLMdXTdcXaZDZrLczgcmYuzG7JJooChS4bOo4jfOc2Ys0h3Add1ZwIx1tu4bwzjLWGikwWVxzGzPWCxppsBHp6uuI4PT3BUCNKzWb3//efjPq84I9LxjFjSCkKf2N3QWZc2ZM1ETRTcAF+mFzFiw8+DQRNkxhGm6UuPtrKphekR0LAgwGFCHMM6bgN1eWqSiaUbYiQz4aCySKEuU8lnbBjnt73O6jy4Exy7oh2E0Utksja+VsZACi6Ge2a2x6CvmeHC1x7W+3pxs2cYR736smd/nGOnthzynol2BBdB6N8BUuTWNxZzePNcfPXNgwvY9dpMr5DKhDLgIfVjgdmAsqsAi3HnBsnlHJiu2QJNPkvYZn9CJDLr4WLCRBknpHcSE6WBMmqao6LrAoqeQxUqhnm4YehMR2WhaxmzPWADA0uZulY2slmFtkLLLZafD7aT3NQOLWvt2Y60GFmGG6okYhoG1zYFl2/aP2b7HbnIL+oupc17tNlhgEVXGYiZkJmuoJ8/NupjnD5Ds7j1puMZiSi6FJPs7m8K/097W231nAYATFw/yfy8b7tFqtVspiftOaN5cZjNsrLabgJPd7OZ0WQeNOKcC6OyMBUt5t1KuWisIoncdnsSffeV+fOaXW3jnDBP6EvHBNBaHJsq8A6MVwpZCDMPg2V3RRK7SxuA7bljGYnymanvvrd85mZu82frHnhjddxYAOOuYufzfOuOhgUYEeObqufw5s73dFACWNW8YooDz4PgMbvvDPtTqJs9YyAO/Oh1WCtk/NoMjE2We8oxjLLMfrQcWrZuYrVvUzFjsG8eNt2/D7U/ux7/e/hT+5ruPAGhoWYh4YV1r4nXXCq2cFzyTedQZWHRjxoI5b9bNxrRgBv+dE1oXzlrTuD91QtkxvcXxFnjVyYvxL7/YgolyDa89bZn28z7/5tPwtXuexR8JVsKzGZaxYIHFTLWG13/hbjx7aBLvecVxfDjWnC4LLPqLOSwb7sHuo1PYtn+cZyyKIQWQrdCyxiKkX4EIC7QefPaIbWFlm7dTllNgETf5bAZzevM4MlnBgfGZlm2sLX+T4OfFyrm9uOeZQ9jZ9PwxTdPWIdFtFHMZ5LMGKjUTY9NVXhopV9nvnExgsfF1G/D5Xz+Ft7x4VSKv1wpdGVgsG+7Bd695CbbuGws0EXHhYAl/c+HxMR5ZZ2EFFg3x5ta943j2UGMx+crvdvA639wuzO4cs6APu49OYcehibaWQuZElrEIH1ictGQQhmG5Ph6/aADzBwr43VOHsGpeL169fnHon03os2Cg2AgsxmZwQotv+VgLM2RWzmuUjXcdbmw4WFABpN9fIQyGYWCwlMehibKtMyTp8s/CwRI+dvn6RF6rVboysACAk5YO4qSlg/4PJFyRNRZP7h3l32OupgCwbI6/OLbTWDWvF7/dBuw8NMk1Ou2oH89LgcZiTl8Bpy4fxsO7jgIA3vLilXjtC5fjt1sP4Oxj5wXuuiHCMb+/iK37xiMRcLIOhzBTb5nHza5mxsJmbd2FpRCgUQ45NFHGUaEMlXQppJOgd4RwhXXT7B2dRq1uYuu+McdjFg+Wuk5jAQCr5ja8LHYcmuAai7ZkLFq09Y5CYwEA73/VOpTyGZy6Yhh/cvoK9BdzuGjDEtIiJUiULactZSyaQvedisCiGzUWgKVrOCp0hiQt3uwkuvMsICJh4UAR+ayBWt3EvtFpPtDr3X90HBcynn3svHYeYmysaqZ7nz00yVvz2hFYMNFeO0shAPDStQtw34cuwC3veklqh851O9x9s4WhdIxWhsexwGLf2DSmKzXejp0xunNWCNDwcwGAkUkrsODeHV0aTLUC5TAJVzKZRmvZrsNTeP7oFG+/fMWJC/GS4+Zh0zOH8fZzVrf3IGNi1TwrY3HG6jkA2puxGJmqoFqrIxdwEeNthREIT9NuytPtRJWxqNXNQK7EMnP7CugrZDFRruG5I1M80OzmGyy7DsWOnErCBlmdBL0jhCestezx50exv7mgrVs0gJccOx9/9cp1XZsKZ7uysekqNwJqR/2Y7ZRM056G1YVZevcU6FLvdOa3aOt999MH8X9u3Yrnjkzyr4XJWBiGgTVN2/unD4x3tZ03Y6jXWQopd3GLbavQO0J4srzpSHrrE/sAACvm9mhZpHc6PYUsFjZ3iE8faMwMKbZh2Foua9llhymH8PHYbWiVJaKllYzF/rFpvPOrD+Bzt23DFf9xL4BGBi7sebF2YaMF+an947NCxMgyFirxZqELbcxbpXvPBCIS1jTHiN/11EEA1lj62QDLWrBhZO3akYXtDDFNM7TDIpE+Fg02Agu32T1e/M+jezDRnBvzfPP581sQXTPjwW37xoSde/feYNmIh6OixoJKIa7QO0J4wrQGjONnkdX5imZgwUZCt8N5EwjvZcG6WYDWu0KI9sOyhyNTFccIbz9+u+2g42srpDEGQWDzY7buG58VN9hhhcZiZhaUgMJC7wjhiWyJfvzi2eMNskLy52jFvbIVWDvvoYCBhTh9kjIWnU9/McfPBeYhocujz40AAP70jBX8a6zzKQzMjfXpA+M8K9bNN9jhHmfGgl1fvdQl5aB7zwQiEtZKgcXJs8h0bLm0oxtuk0f//GbL6aGAoj224OcyRlfvJmcTK7g5lXowoIoDYzM4OD4DwwDedd6x/OtMJxHqOOb2opDLYKZa58PouvkcszQWVmAxWWbC6O7XnAUl8Jlw55134rLLLsPSpUthGAZ+8IMfxHBYRFrIZTN8+M0xC/pwzPw+n2d0Dyvm2AOLds1EWdAfTrTXyjwIIp2wYFfs7PDjD3sajrmr5/Vh9fw+/NdVZ+DvLzkRbz5rZejjyGYMHLugsel4Yk8jG5KbDRqLKStryAMLur4cBA4sJiYmcOqpp+Lf/u3f4jgeIoX8+5UvxJ+dswYbX7sBhtG9i4fMirn2Ughr/Uwa1g0QtM0wKtdNIj2wYDdIKYQFFicuaWQozj9xEf78pcegr8XuLpbNfGRXI7Bo9eelGRZYTFfq/LqiUog7gc+Eiy66CBdddFEcx0KklHn9RXz4spPafRiJs2SoB4VchovThnralLEI2WZIrabdh2ynrQMPLCLWR7HA4rHdjcCimw3U+os5PuH08EQZS4d7MNmc9FuiwMJB7FuZmZkZjI6O2v4QRCeQzRhYMlTi/x9uc8biQEiNBWUsuofVzfbvp5reKjr8YU/DMffEJREHFovs+qvBnu7NWBiGgXl99szhVPP66qVSiIPYV5yNGzdiaGiI/1mxYoX/kwgiJbxodUNfMtybb5s4bb6gsTBN0+fRFmzGCWksuoeTlw4BaIg3xbkVbsxUa9zg7cSIhddrJU+bbs5YAMDCpo8Ic+KdamYsqBTiJPaV8vrrr8fIyAj/s2vXrrhfkiAi40MXn4gPXnQC/u9bTm/bMbDAYrpS5yZHOpA5Vvcx1JPnbaK/33nE9/Hb9o2jWjcx1JPHUiH7FgWr5vbahIuDbeqaSgrmxLtvrGEwxsXRFFg4iD2wKBaLGBwctP0hiE5hTl8B17z8WLz4mPZNce0r5tDXXLyC6CxYxqJdxl5EPLykOVH4zm0HfB+7ual/WL9sMHLhdS6bwfpl1no+GGLuSCexYKARmLGMBesKoVKIE1pxCKIDCCPgnKGMRVfysrULAAB3btUILJ5vBhbNEkrUnNEsFQLdXwpZPNgILPY2LdGnuY8FXV8ygQOL8fFxPPzww3j44YcBANu3b8fDDz+MnTt3Rn1sBEE0CRNYTFep3bQbeclx85HNGHj6wAR2H/U2ynr8+YZY/qSYjO0uOHEh//eG5fEEL2mBtZ/vPDwJ0zT5pNNuD6jCEHjFeeCBB3DaaafhtNNOAwD89V//NU477TR8+MMfjvzgCIJoEGZkNrWbdidDPXm8YMUwAO+sRaVW562m65fFc9M/fdVcfOr1p+Cbf35W5F0naYNpW3YensT4TJWXQpiok7AIXBQ777zzAinTCYJondZKIZSx6DbOOW4+Hnz2CO7ffhhXnKl20Hz0uaOYrtQxpzePNfPic8x944tmR6cfG9r2/MgU9xEZKObQS5beDmjFIYgOIIyt93SVMhbdyklNF82t+8dcH3PbH/YDAM4+dh4ymdnjmBsXC/qLmNdXgGkCd25tTItdQNkKJRRYEEQHEMYki7WbFilj0XUwD4mn9o+jXndmkKcrNXz/97sBABdvWJLosXUrhmHwktItDz0HAFg0EG0Lb7dAKw5BdADzQ2QsuEEWZSy6jlVze1HIZjBdqWOXYiDZNzftxN7RaSweLOGCExe14Qi7E9bqu3Vfw3Ts3LXz23k4qYUCC4LoAOY3MxZBRqeTQVb3kstmcMyChm6C3eQYpmniv+7aDgB47/lr6fOPkNe8YCkKTV+Y+f0F/Oks0ZcEhQILgugA5vc3BqAdHC9ri6etrhC6zLuRdc1yyNZ9dp3F5t2j2H10Cj35LF572rJ2HFrXsmSoB199+5l464tX4eb/9WKeSSTskJyVIDoAtoCVa3WMTlcxpGGfPFOljEU3c8KSAfzoEWt6KeNnm/cAAP7ohAVk3hQDZx87D2cf2z4n3k6AtjIE0QGU8lkMFBv7AF0vC5axoHbT7uSkpm/EE0JgYZomfr55LwDgwpMXt+W4CIJWHILoEJjO4qCmgJP5WFC7aXfC3DS3H5zAZHPS5lP7x/HMwQkUshm84oSFXk8niNigwIIgOoR5fZbOQocZsvTuahYOlDC/vwjTBLbsbegsftbMVpy7dj4GyGqaaBO04hBEhxDU1pu6QroflrW4f8dhTJar+Pb9uwAAl5B3BdFGKLAgiA5h/gDLWGgGFjQ2vet51UkNj4pP/PRJnPThX2D30SnM7y/gklMosCDaB604BNEhWBkLzVIIZSy6nte9cBlOFiaXzu8v4F+vOI0+c6KtULspQXQIgUshpLHoenoLOfz43edix6EJDJTymNtXQJbmghBthgILgugQLJOsYO2m1BXS3WQyBo5Z0N/uwyAIDm1lCKJDCJKxME2TG2TREDKCIJKEVhyC6BB4YDFmaSzqdRPfe/A5/MedT2N8psq/Xq7VwZy/qd5OEESSUCmEIDoEZpA1ValhYqaKvmIOX7zzGXzy508CAH795AF8851nwTAM3moKUFcIQRDJQisOQXQIfYUsF2IeGJtBpVbHF+98mn//nmcO4Vd/2A/AMscyDKCQpcucIIjkoBWHIDoEwzCwbLgHAPDckSnc+8whHJ2sYF5fAX9+7hoAwHceaBgkTc40Aou+Qg6GQV0CBEEkBwUWBNFBrJzbCwDYeXiS2ze/6uTFeMMZKwAAv9lyACNTFYxNN/QW/UWqdhIEkSwUWBBEB7FqXh8A4NlDE/jVE/sAAK9evxjHLx7AukX9KNfquO0P+zA2UwEA9JcosCAIIlkosCCIDuKYBY3A4r9/vxv7x2bQW8jixcfMBQC84oSGvfM9Tx/iGYsBCiwIgkgYCiwIooM4dfkwAMvL4qVr53MDLBZg3Lv9EMapFEIQRJugwIIgOogTlwxiQAgWXnnSYv7vM1bPRTZjYNfhKWzZ1xijTRkLgiCShgILguggCrkM3vmyYwAAaxf24zWnLuXf6y/msGHZEADgtj809BcDxXzyB0kQxKyGtjME0WG85xXH4fIXLMWiwRIKkvnVmWvm4uFdR/H0gQkAJN4kCCJ5KGNBEB2GYRhYNa9PadX9otVzbf+f21dI6rAIgiAAUGBBEF3FGavm2P6/fE5Pm46EIIjZCgUWBNFFzOkrYO1Ca4Q2BRYEQSQNBRYE0WW8aI1VDlk+p7eNR0IQxGyElF0E0WVcedZK3PvMIZy3biEWDZbafTgEQcwyKLAgiC7j5KVDuP3957X7MAiCmKVQKYQgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMigwIIgCIIgiMhIfGy6aZoAgNHR0aRfmiAIgiCIkLD7NruPu5F4YDE2NgYAWLFiRdIvTRAEQRBEi4yNjWFoaMj1+4bpF3pETL1ex/PPP4+BgQEYhhHZzx0dHcWKFSuwa9cuDA4ORvZzCTv0PicHvdfJQO9zMtD7nBxxvdemaWJsbAxLly5FJuOupEg8Y5HJZLB8+fLYfv7g4CCdtAlA73Ny0HudDPQ+JwO9z8kRx3vtlalgkHiTIAiCIIjIoMCCIAiCIIjI6JrAolgs4h//8R9RLBbbfShdDb3PyUHvdTLQ+5wM9D4nR7vf68TFmwRBEARBdC9dk7EgCIIgCKL9UGBBEARBEERkUGBBEARBEERkUGBBEARBEERkdE1g8W//9m9YvXo1SqUSzjrrLNx3333tPqSOYePGjXjRi16EgYEBLFy4EH/8x3+MLVu22B4zPT2Na6+9FvPmzUN/fz9e//rXY9++fbbH7Ny5E5dccgl6e3uxcOFCfOADH0C1Wk3yV+kobrjhBhiGgeuuu45/jd7n6Ni9ezfe8pa3YN68eejp6cGGDRvwwAMP8O+bpokPf/jDWLJkCXp6enDBBRdg27Zttp9x+PBhXHnllRgcHMTw8DDe8Y53YHx8POlfJbXUajX8wz/8A9asWYOenh4ce+yx+Kd/+ifbLAl6n8Nx55134rLLLsPSpUthGAZ+8IMf2L4f1fv66KOP4qUvfSlKpRJWrFiBT33qU60fvNkF3HzzzWahUDC//OUvm48//rj5zne+0xweHjb37dvX7kPrCC688ELzpptuMjdv3mw+/PDD5sUXX2yuXLnSHB8f54+55pprzBUrVpi33Xab+cADD5gvfvGLzZe85CX8+9Vq1Vy/fr15wQUXmA899JD505/+1Jw/f755/fXXt+NXSj333XefuXr1avOUU04x3/e+9/Gv0/scDYcPHzZXrVplXn311eamTZvMZ555xvzFL35hPvXUU/wxN9xwgzk0NGT+4Ac/MB955BHzNa95jblmzRpzamqKP+bVr361eeqpp5r33nuv+dvf/tY87rjjzCuuuKIdv1Iq+fjHP27OmzfP/MlPfmJu377d/O53v2v29/ebn/vc5/hj6H0Ox09/+lPzQx/6kPn973/fBGDecssttu9H8b6OjIyYixYtMq+88kpz8+bN5re+9S2zp6fH/OIXv9jSsXdFYHHmmWea1157Lf9/rVYzly5dam7cuLGNR9W57N+/3wRg/uY3vzFN0zSPHj1q5vN587vf/S5/zB/+8AcTgHnPPfeYptm4CDKZjLl3717+mC984Qvm4OCgOTMzk+wvkHLGxsbMtWvXmrfeeqv58pe/nAcW9D5Hx9/+7d+a5557ruv36/W6uXjxYvOf//mf+deOHj1qFotF81vf+pZpmqb5xBNPmADM+++/nz/mZz/7mWkYhrl79+74Dr6DuOSSS8w/+7M/s33tda97nXnllVeapknvc1TIgUVU7+u///u/m3PmzLGtHX/7t39rHn/88S0db8eXQsrlMh588EFccMEF/GuZTAYXXHAB7rnnnjYeWecyMjICAJg7dy4A4MEHH0SlUrG9xyeccAJWrlzJ3+N77rkHGzZswKJFi/hjLrzwQoyOjuLxxx9P8OjTz7XXXotLLrnE9n4C9D5HyY9+9COcccYZeMMb3oCFCxfitNNOw5e+9CX+/e3bt2Pv3r2293poaAhnnXWW7b0eHh7GGWecwR9zwQUXIJPJYNOmTcn9MinmJS95CW677TZs3boVAPDII4/grrvuwkUXXQSA3ue4iOp9veeee/Cyl70MhUKBP+bCCy/Eli1bcOTIkdDHl/gQsqg5ePAgarWabaEFgEWLFuHJJ59s01F1LvV6Hddddx3OOeccrF+/HgCwd+9eFAoFDA8P2x67aNEi7N27lz9G9Rmw7xENbr75Zvz+97/H/fff7/gevc/R8cwzz+ALX/gC/vqv/xp/93d/h/vvvx/vfe97USgUcNVVV/H3SvVeiu/1woULbd/P5XKYO3cuvddNPvjBD2J0dBQnnHACstksarUaPv7xj+PKK68EAHqfYyKq93Xv3r1Ys2aN42ew782ZMyfU8XV8YEFEy7XXXovNmzfjrrvuavehdB27du3C+973Ptx6660olUrtPpyupl6v44wzzsAnPvEJAMBpp52GzZs34//+3/+Lq666qs1H1z185zvfwTe+8Q1885vfxMknn4yHH34Y1113HZYuXUrv8yym40sh8+fPRzabdSjn9+3bh8WLF7fpqDqTd7/73fjJT36CX//617bR9osXL0a5XMbRo0dtjxff48WLFys/A/Y9olHq2L9/P174whcil8shl8vhN7/5Df71X/8VuVwOixYtovc5IpYsWYKTTjrJ9rUTTzwRO3fuBGC9V17rxuLFi7F//37b96vVKg4fPkzvdZMPfOAD+OAHP4g3velN2LBhA9761rfir/7qr7Bx40YA9D7HRVTva1zrSccHFoVCAaeffjpuu+02/rV6vY7bbrsNZ599dhuPrHMwTRPvfve7ccstt+D22293pMZOP/105PN523u8ZcsW7Ny5k7/HZ599Nh577DHbiXzrrbdicHDQscDPVs4//3w89thjePjhh/mfM844A1deeSX/N73P0XDOOec4Wqa3bt2KVatWAQDWrFmDxYsX297r0dFRbNq0yfZeHz16FA8++CB/zO233456vY6zzjorgd8i/UxOTiKTsd9Gstks6vU6AHqf4yKq9/Xss8/GnXfeiUqlwh9z66234vjjjw9dBgHQPe2mxWLR/MpXvmI+8cQT5v/6X//LHB4etinnCXfe9a53mUNDQ+Ydd9xh7tmzh/+ZnJzkj7nmmmvMlStXmrfffrv5wAMPmGeffbZ59tln8++zNshXvepV5sMPP2z+/Oc/NxcsWEBtkD6IXSGmSe9zVNx3331mLpczP/7xj5vbtm0zv/GNb5i9vb3m17/+df6YG264wRweHjZ/+MMfmo8++qh5+eWXK9v1TjvtNHPTpk3mXXfdZa5du3bWt0GKXHXVVeayZct4u+n3v/99c/78+eb/9//9f/wx9D6HY2xszHzooYfMhx56yARgfuYznzEfeugh89lnnzVNM5r39ejRo+aiRYvMt771rebmzZvNm2++2ezt7aV2U8aNN95orly50iwUCuaZZ55p3nvvve0+pI4BgPLPTTfdxB8zNTVl/uVf/qU5Z84cs7e313zta19r7tmzx/ZzduzYYV500UVmT0+POX/+fPP973+/WalUEv5tOgs5sKD3OTp+/OMfm+vXrzeLxaJ5wgknmP/xH/9h+369Xjf/4R/+wVy0aJFZLBbN888/39yyZYvtMYcOHTKvuOIKs7+/3xwcHDTf/va3m2NjY0n+GqlmdHTUfN/73meuXLnSLJVK5jHHHGN+6EMfsrUv0vscjl//+tfKdfmqq64yTTO69/WRRx4xzz33XLNYLJrLli0zb7jhhpaPncamEwRBEAQRGR2vsSAIgiAIIj1QYEEQBEEQRGRQYEEQBEEQRGRQYEEQBEEQRGRQYEEQBEEQRGRQYEEQBEEQRGRQYEEQBEEQRGRQYEEQBEEQRGRQYEEQRCScd955uO6669p9GARBtBkKLAiCIAiCiAyy9CYIomWuvvpqfPWrX7V9bfv27Vi9enV7DoggiLZBgQVBEC0zMjKCiy66COvXr8fHPvYxAMCCBQuQzWbbfGQEQSRNrt0HQBBE5zM0NIRCoYDe3l4sXry43YdDEEQbIY0FQRAEQRCRQYEFQRAEQRCRQYEFQRCRUCgUUKvV2n0YBEG0GQosCIKIhNWrV2PTpk3YsWMHDh48iHq93u5DIgiiDVBgQRBEJPzN3/wNstksTjrpJCxYsAA7d+5s9yERBNEGqN2UIAiCIIjIoIwFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCRQYEFQRAEQRCR8f8DKU7F4BfHWucAAAAASUVORK5CYII=", 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "# esc_ep.plot(x='t', y = ['total_pop'], title='total population')\n", + "# esc_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns')\n", + "esc_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", + "# esc_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)\n", + "# esc_ep.plot(x='t', y = ['act'], title='actions')\n", + "esc_ep.plot(x='t', y = ['surv_b_obs'], title='surv_b_obs')" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "c5c5a541-abb1-44f2-b53a-01ae726f9cbd", + "metadata": {}, + "outputs": [ { "data": { - "image/png": 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tsurv_b_obsmean_wt_obsactrewtotal_popnewbornsnon_random_newbssb
001.2253870.622407-0.0608900.9263083.6920930.0000000.7832150.834071
110.5882200.556437-1.0000000.0000004.0951360.9199360.7915000.859990
220.6094900.556648-1.0000000.0000003.5218170.0000000.8015520.892880
330.6339580.565610-1.0000000.0000003.0287620.0000000.8120200.928948
440.6572310.580948-0.9779970.0145853.3500020.7650730.8184080.951927
\n", + "
" + ], "text/plain": [ - "
" + " t surv_b_obs mean_wt_obs act rew total_pop newborns \\\n", + "0 0 1.225387 0.622407 -0.060890 0.926308 3.692093 0.000000 \n", + "1 1 0.588220 0.556437 -1.000000 0.000000 4.095136 0.919936 \n", + "2 2 0.609490 0.556648 -1.000000 0.000000 3.521817 0.000000 \n", + "3 3 0.633958 0.565610 -1.000000 0.000000 3.028762 0.000000 \n", + "4 4 0.657231 0.580948 -0.977997 0.014585 3.350002 0.765073 \n", + "\n", + " non_random_newb ssb \n", + "0 0.783215 0.834071 \n", + "1 0.791500 0.859990 \n", + "2 0.801552 0.892880 \n", + "3 0.812020 0.928948 \n", + "4 0.818408 0.951927 " ] }, + "execution_count": 28, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "mid_ep.plot(x='t', y = ['total_pop'], title='total population')\n", - "mid_ep.plot(x='t', y = ['non_random_newb'], title='Fished non-random newborns')\n", - "mid_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", - "mid_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" - ] - }, - { - "cell_type": "markdown", - "id": "977fb177-37ea-470e-a83a-400d9a9dcf43", - "metadata": {}, - "source": [ - "## Escapement" + "esc_ep.head()" ] }, { "cell_type": "code", - "execution_count": 93, - "id": "3e9aba5e-466a-4feb-8bc5-8bf34da520a3", + "execution_count": 91, + "id": "26c2cf63-f70a-41aa-8ef1-e3f5b69fe5b2", "metadata": {}, "outputs": [], "source": [ - "escp = ConstEsc(env, escapement = 0.0138)\n", - "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), escp, other_vars=['ssb']))" + "mid = Msy(env = env, mortality=0.05)\n", + "mid_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), mid, other_vars=['ssb']))" ] }, { "cell_type": "code", - "execution_count": 94, - "id": "ff08dfd1-c97c-407a-aec7-968d36ca6beb", - "metadata": {}, + "execution_count": 92, + "id": "62d7175e-1b05-4353-bd63-21971fb71d6a", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "data": { @@ -258,13 +367,13 @@ "" ] }, - "execution_count": 94, + "execution_count": 92, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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", 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", 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", 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", 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qaqrn76qqqnYJelYlMXXA9Gy2O6bmcDgkNd2Y0bXXXouioiJERERg8ODBfpfp3r07rr76arzxxhvo1KkTrrjiCvTp0wf33nsvvvzyy3b5LgCwY8cOjB8/HsD5OaEyMzORkpICALjyyivx3//+F4IgeIKPrVu3omvXrhgwYIDifRo6dCiGDh2KP/7xj7jvvvvw7rvvMnghksGUCRXffvstSktLUVdXh9OnTwcMXAAgKioK3bp18/lH5uSdyMmRzymUpKQkjB07FnfccQe++eYb5OXlYdu2bXjmmWd8eulMmDABH374oSdQ6dmzJ6688kqsWLHCb/DidDrx2Wef4fDhw0hOTsa5c+c8ibW/+93vkJ+fj9///vc4fPgwPv/8c8ydOxepqamKZuqur69HSkoKNmzYgJMnT2Lr1q3YtWsXrrzyStnrJOrIdA1eevfujfDwcBQXF/u8XlxcjPj4eEXrdjqdGDZsGEaNGqVoPaQPxi4UisPhwOrVqzF+/HjMmDEDQ4cOxc9//nOcPHnSp/b2pptugsvl8sltmTBhQrvXWi1cuNDTrLRlyxZ88cUX6N27NwCgf//+WL16NdLT05GQkIBHHnkEv/rVr/B///d/ivYlPDwc5eXlePDBBzF06FDcc889mDx5su2avIn04hCk9muUsnKHA5999hnuuOMOz2tjxozB6NGj8frrrwM43x48aNAgpKSkYNasWYq3WVVVhdjYWFRWVlq2FmbwrFUAgH6x0dg2+xaDS6OesppGjHzhWwBA5v8loVeXKINLZB8NDQ3Izc3FpZdeiujoaKOLQyrgd0odjZT7t+qN4jU1NcjJudBLJjc3F1lZWejZsycGDRqE1NRUTJs2DSNHjsTo0aOxePFi1NbWYsaMGWoXxfLsliPiHSZzxlwiIpJL9eAlIyMDEydO9Pzdmkw7bdo0LFu2DPfeey9KS0sxZ84cFBUVITExEWvWrGmXxEv2S9j1xtCFiIjkUj14mTBhQsgRNlNSUjzZ/WpxOp1wOp1wuVyqrtdIVh7UbdvxMpworcUvrrvE85qV94eI7KmxxYUwh8NWA4J2BLb5tpKTk3Hw4EHs2rXL6KKoxso1L/e/vRP/t3I/0nPPXnjRp9lI/zIREXmrb3Ih4blvcOvfNhtdFJLINsGLHVk4dvE4fa7O7+scpE4bGubfk874XWov+3QFGprdOFZSY3RRSCLbBC9W6yrtcguobmg2uhi64qVYO+Hh50e1bWpqMrgkpJa6uvOBPydv1E5Vfce6BtuJtYfg9JKcnIzk5GRPVyuz+6lzC/YXVGH77JvRN7az32Xs9uDFuY20ExERgZiYGJSWlqJTp06KBlQjYwmCgLq6OpSUlKB79+6ewJTUV8ngxbJsE7xYzf6C8xNIfr2/CNNvuDTAUjaLXrww50VdDocDffv2RW5uLk6ePGl0cUgF3bt3Vzx4JwXH4MW6GLyYTEbehQRX29W82DgYM4PIyEgMGTKETUc20KlTJ9a46KCqocXoIqhqz6lzeG9bHmbfeiXiutl7YEPbBC926Sp915ILs2vb+VbPihdthIWFcTTWDqKosgG/em8XHhx7Ce4dNcjo4liSkTkvK/cUYGduOf780+GIUKmb9tQ3twEAymqa8MGvx6iyTrOyTcO4PbtK2yt80Wp3th8vR0lVgzYrJzKpF1cfwoHCKjz9332y1/HGumP4YEfHbWY0Mnh5bEUWPk7PxxfZhaqv+0BhJUqq7X1NtE3wYkf2Cl1890et6QE2Hi3FfW/vwHUL0lRZH5FV1DUpq2XOLavFy98cxf+t3K9SiaynyeU2ugg4W6t+M++5umaMnp+GY8XVqq/bLBi8mERG3tl2kbLNKl40seloKQDArcKxanG58e7WXBwpsu8PnqhVRxuqway0nOftv7sL0Njiwm/+lYF/2ayGzTY5L1a2/Xg57nt7h2br7tUlEkPjumqyfim0aAZzqRG1fOeDHSfx3P8OAgDyFt6m2nqJ/CmtboTDAfQ2aHZ1PhyZg5b5f1UNzfhP5ml8faAYXx8oxi+9pmuxOtvUvFhtkDpvW3JK/b6u9GZ/srwW9729Az96dZOkz607XIxbXtmAvacrFG2/LS0uls0qVvvuPV2p2rqIgmlscWHU/G8x8oVvVT2HpWDsYg5aDhtRWd+Mapv1qGplm+DFygm7gYbKV3pxOVFWK+tzDy3LwPHSWjy0zPzHUk7NS2OLCy1+bhi8mJNeKusuNNnUGHRzsVuHAGrPziMI2yZ4sbKAkbfSa4vCz9c2mr/beYvE4KWpxY1rn1+L8S+tb/ceL+ZEpDexFS+CIOC9bXk+Y4GFYufghTkvJqY8djHXzViL2EBqzUteeS1qm1yoVdhTg8jqzHV16LjEJuyuO1yCuV8cACA+J89ug/B5Y82LCQSseGFNQEhSa16C4dGmjoSXF3MQm/OSKyMNwM7THzB4McCqvWd8Xwhw9iqueTHZxUmLmiB/uStyme14EWmLJ7wZaNnbyKhkcD0weNHZtpwyJH+02+e1wDUvyral9s1409FSpK7Ikh3NaxEcsOaFSB7v32NVQzNe+PIg9rHHnf407G5U3dCCtEPFmq3fSLYJXszYVVoQBCzbmottOWWe1w4UVrVbzqwzLLetKXlwaTo+3VOAl78+Imk9G78LerTosqfmOC9splOuprEF5TWNRheDRPA+26+e9w3e2ZKLKW9sMaw8pI1deeeMLoImbJOwm5ycjOTkZFRVVSE2Ntbo4gAAdpw4i3kiBj0L3FVa2c1Uq1txQUW9pOWnLU0HAJRrMAw2a17MZfjcrwEAe+f9CN2iOxlcGmO53QJKaxpNO7uv0bF6SXUDLu4SpekIs/4cOlOFrw8U4eHx39N1u4GY9NnV9GxT82JG+efq2r3m73ca6LervNlIm6uT3PUWSgx6xHC5VWzTZfSimmPFNUYXQXf7Cyrx943HPXlYv/kgE2NeTMOGIyUGl8w/I2savz5QhNHz0/D4J9m6b3vy3zZj8bfHsPjbYwGXcbkFPPe/A1izv0jz8qgZu5m1Fl8LDF5MzKz3UjOVq9mlZs2LmfbM2jrSRbTVT17fggVfHcaHO08BANYePJ9r8M7mXCOLZUp/+y5w+HR3geJ11Ta2YOmWXMkPR8Hye1buKcC7W/PwyAeZSosXUqCadzk6hXecW3rH2VMTC3jqKq15UfbxwOuVuWItyqNuzotqq+rwOmDs4nG4yDevzaxBsZGlUjO4fXblfjz/5UH84p2dqq2zuM0kuVpS81h0Cus4vzwGLyYQsNlI5OXlYGEVJr26Cd8e9M0q1+pmLHe1WlRTq5nzQurRO4/BzEKd9kadwUYG62qeHv/bWwhA/nQoRlPzl9IpouPc0jvOnppYoAu92IvLbz7IwJHiavz6/QwVSxWYmXrlqJnzYqLdsrxgF+SKuiZTnUNaCxm8GHQszFIjdONf1mHDkRLZtahqNh1bXURYx7ml22ZPzdhVWimxP8nAE7tdWMNfvz6Mu97ahoZm8cPiq31NVWN1Dc0u/PXrw9hz6nz3vxbmvJhSoCfr9UdKkPj8Wvzps336FshAbrMGakbWvHiFt6fP1WP6u7twz9+3G1cgA6nabBTecWo8bRO8WHpWaYXnm5iaG+f648g4eQ7/yy5UtjEoCGpkfK7tCJFvbTgO5/rjmPrmNgAqd5U26T3GTl5dexQA8HF6vsEl0U+o08qwZiODtgv4v+ZlnlQ2HkmkRZtMmLArT8fZUxMLOM6LyLuplFNfjSpWvWooFqw+hCufXYOckmrPa8e8/g+onLCr2po6Ju/zVc0LsuX5ObG8XzIqaDY050WDdfaIkTaukJrXDkVUPBgRTNglKU6fq4Nbgx+C2DUGrHnx+5oKwYtOvY3+vukEWtwCFn33tO5v2y3MeTEN7+PHfN0L/P3mvI+VUc2VhjaTqnSCeAcgF3eNkvTZ9LyzKKrUr1dRIKr+VDrQ747Bi0KfZxXgxr+sxx+W75G9DqWD1En5vBo3aNnBi8wPBnuKd6marMfoRQkePf/8Pdf4BA4d8MCpdY89WnyhJvZ7vbtI/nyGwqYqNbBnnjwMXhR6c/1xAMCXbWeKDsDfiar01JXyeTWuk2ZKbGXOi3n4NBvxeuzhL2gXTBC72KGrdE7JhZGcwztQkwkxeDEFpT/ksIDNRtpUveg+SJ3X7rXdVc5tZB7ex485LxeY9bwyNGFXpfWYtieXBPylyMPgxQSUXuglNRtJWG+gZeUPUifzg0G0uFSc24gUYc6Lf6F+h8Yl7Bp342dTyQU8FPIweDEBxV2lJSyryvVK52tesP1Td3oA6z/FGcm7po8X5Av8Js57nWvGJewah6fHBfytyMPgxQYk9TaScIMO9JuSe7GV+znv/Wvf24jNRmbhU/PC25NHyJyXDjjQC2/YF/C3Ig+DF51pcZoGbjbyc9FUYXvyexupsPE2ODGjvppa3NhfUBkyCObN6QLTzm1kYPTCG/YF/K3Iw+DFBJS2/0r5uCpdpZWvQjWsedHXbz/IxE9e34KlW/Pavedb8+JfR7xOhxznxai5jdhuRBZmm+DFynMbKe8qLX4N6tS8yGw2krlxva5zzHkJLe1wCQBg6Zbcdu8Fynk5fa6uQx9bO+/6idIafHOgSPLnGLuQUrYJXjr23Ebil1XjJmLjazEp4HtqnT8pP9x5Ejf+ZX2HmoixrVCD1Fl5eoCbX9mIh/+Via05ZcpX1kGx55U8tglerEzpqRtwnBeFF6eAXaX17m3ktXtabtvOT8h68Bnn5bvv7JVvOt5EjG2FStg1ippF2Hu6UtLyvF9fwEMhD4MXnfn70SrOeQnwulYJefLHeZE7PYA+zDRysBX5TsxIwag9zsu/tudJL4OKEZTUSxgTdi9gICcPgxcTUHzy6pywK3clamyaP3Tz8q154RfVyv8cY+qO8/Ls5wckf0bNUF3qt83T4wIGcvIweLEBKc1GqswqrXgN5mSGqnwrE9PbqCPyN4S9OUbYVW9dkmteeIKQQgxeTECrihfzzSot73N6PcUzeFFIxPQAZjrE/8k8ja9l9JSRykz77EvFZiOJVzHWNlzAQE6eCKMLQFB89krqbaRoS63r0HmEXVmfko45L8r4dJU2+c2psKIeT3ySDQDIW3ibptvqCLNKs+ZFPh4KeVjzYgJajfPif3oAhRtTaR1m3DZrXpSx0sSM5+qadNuW/9PKu6u09U885jjJx0MnD4MXnfk7T7Ua58X/9AAq5LzoPT2ATj9u699CjGWl4+edJ6Z58BCi+dYOUxtJT9jlHfsCHgs5GLzIsP14Oaa8vgXZ+RWqrE9pFbuUC4Gk63SAZWV3lZb5Od2YvoDWEeiUNMtlWq+xgwAm7PpdXr1NWx7jOHmY8yLDfW/vAADc//YODOgRo3h9imteAryu1TVR72puvfInmPOijM84Lya/InufU1p/66Gbbw2a20jVhF2Jy5v79CALYM2LArVNLlXWozjnRUL0YmT7uvzeRuqWg7ThM86LYaUQx7fmRdvfRMhZpW1R8yL+G29scWHDkVL1Nm5xZv+tmJUpg5cvv/wSl19+OYYMGYJ33nnH6OKYXqBxXvwxNmHX3DUbNsibNJSVjl+Yd/Ci8bb8ziptgt+CqjkvEu7A7/qZkbyjsVItpVmZrtmopaUFqampWL9+PWJjYzFixAhMnToVvXr1MrpoqvB3omqWsOv3oqmcGS68WrDnXunHWufFhR+Nv5wUNbnd7V8zRcKumtMDSFj2eEmNatu1Kg7oqJzpal7S09Pxgx/8AP3790eXLl0wefJkfPPNN0YXS1OKE3YDvG6bQerkfUwyO3RZNZSFDp+eCbv++AQvFjpuAUl4AvM3y3ZH428SU5JG9eBl06ZNmDJlCvr16weHw4GVK1e2W8bpdGLw4MGIjo7GmDFjkJ6e7nmvsLAQ/fv39/zdv39/FBQUqF1Mc1Fc8yKh2cjA6QHMfs0ye/nMzkrHT8/7RaghC6xVY+WflONph/1VE4MXeVQPXmpra5GQkACn0+n3/RUrViA1NRVz587F7t27kZCQgEmTJqGkpETtoliGVgm7SgepC3SR0b23kV7jvPCaqoiVjp/vOC/abivU79AeCbtSNqzedq2KtbzKqR68TJ48GS+88AKmTp3q9/1FixZh5syZmDFjBoYNG4YlS5YgJiYGS5cuBQD069fPp6aloKAA/fr1C7i9xsZGVFVV+fyzGqUJW5KajRRtSdk65P5g9esqTUpY6Yna+yenec5LiPUbFrwYNLeRdc4S7fj2zGPVixy65rw0NTUhMzMTSUlJFwoQFoakpCRs374dADB69Gjs378fBQUFqKmpwVdffYVJkyYFXOeCBQsQGxvr+Tdw4EDN90MJf3GK8poXKZMbqZH0ouvH2qyD8wOYlZUOn67jvJj0uKhZrjAJlyCtg0UrEHyjF5JB1+ClrKwMLpcLcXFxPq/HxcWhqOj87K4RERF45ZVXMHHiRCQmJuLxxx8P2tNo9uzZqKys9PzLz8/XdB/MKNCFQ6sbvd6XHt2ajfTZjG1Z6fjpOs6Lv9d8ehsZNEidQc1GjF18v3PGLvKYrqs0ANx+++24/fbbRS0bFRWFqKgojUukLeUj7AaYmFFhs1Hg9cq7+vCiZW+izguTZCf6BC8ab8v/71AI+r4e1J3biM1GUvhOYmqO34TV6Frz0rt3b4SHh6O4uNjn9eLiYsTHxytat9PpxLBhwzBq1ChF6zGC4nPXGq1G8nNemLBrCVY6ft43DMHPOCzq8tPbyATHStUaJ0nXIBPsvIkwdJFH1+AlMjISI0aMQFpamuc1t9uNtLQ0jB07VtG6k5OTcfDgQezatUtpMXWn2Tgvfl9Toau07tcezm1E6vI+o7T+3v2Na+L9kj1qXiRslz8zUoHqzUY1NTXIycnx/J2bm4usrCz07NkTgwYNQmpqKqZNm4aRI0di9OjRWLx4MWprazFjxgy1i2JK/n7kSmsWAk4P4G98CTW6Ssu87Jn9msWLqjJWOn56DlIXqqbBDkGz3mNNWZ1vs5Fx5bAy1YOXjIwMTJw40fN3amoqAGDatGlYtmwZ7r33XpSWlmLOnDkoKipCYmIi1qxZ0y6JVyqn0wmn0wmXS53JEq1EUrKcCtuTfbE3+TXLSjdfM7LSTclnnBeNt+U/YdcEx8qYViP+ztA2YZfRixyqBy8TJkwI+cNMSUlBSkqKqttNTk5GcnIyqqqqEBsbq+q6taZ4nBeNBqkLRO+LD3sbWYOo88Ikdy7vU0rrrruhEudtMc4LextJwpoX5Uw3txFJF6jZKFQvB72Z/ZpliqdhC7PU0dOx2chfcGSOiRnVW5eUGzDHeWk7SB3JweDFBHQ9eVWpeZHbVVruCLtkBVYN/jQP6P2u3rurtEHjvKi4LnaVVoAXOFlsE7xYpqu0n0cUxeO8BKx58fPEp2xTqq1DCnaVtgbLHj4DYpeOXPPC35l1A30zsU3wwq7S7WmVKCh3FYYmC5PmrPrdaD9IXfCHCHvkvEioebHqiaIi32YjVr3IYZvgxcqUd5UWv6ykrtIBlpXdVdrk1ywr9ZYxJ2seP80TdjVdu3wGjVFn2uOhJybsKsfgxQS0mphRs1ml9e5tpNcgdbyqKiLq+JnwSm10wq4dbufSmo2sv7+KeQcvxpXC0mwTvFgm58UP5XMb+adZV2nZnzP3RcvcpTM/qx4/7ZuN/L0mBH1fD0zYNY7POC8mDOitwDbBi1VyXrQ4TfUe3VJ2zovMz+mXsMvLakdkyKzSId7XhYr7La2rtGqbtQXGLvLYJnixNo0GqVM4PUBg+l59vHdPyx86r6nKWDX207zcfmtedNx+AOrWvEjYrlVPFBXxECjH4MUEtGo20optexvxgqKI2ZsFAzEk58UM47wY1FWaOEidGhi8mIDyhF1ViiGa7Gueye9tJi+e6Vn1aVLroMush0Vp0OT7eSldpRVt1ha8jx0DP3lsE7xYO2FX2dkraXoACVeOQEvq/aTIhDZrsOpNyZBZpc0wSJ3Sz8vs7svpAdoee17f5LBN8GKVhF1/P1s9a16MHGHX7M0KbItXxuzfbyBGjPNiikHqFG5XbtMHf2Y8BmqwTfBiGX7OWuU5LwFqXvxcNo2cVdrsP1iTF8/0zP79BmJMV2nv7VvzwPk2fejb45GIwYvONPnZBuxt5G/7anSV1rvZyGvbGm7HqjdfUsaI710wQbuR4mYjr/9rNcq3XTGAU47Bi878/XCVTw+gb7Kc/GYjc+MFRRnr3pT0L7g5JmZUtmW3T82LlO0q2qw98BgoxuDFBHSdmFHRlpStRO7FktMDWIOY4M+MqYkcNE0en4RdSSPs8oDzCChnm+DFKr2N/N7Alea8SGk2MrDmRS79RtjVZzt2ZdXjZ0yzkbHbV327rHmRhMdAOdsELx25t5GUZiM1Qg+5NShSPhVoG2Z8cqfzrHo9NqImwGduI4OOnNLt+ta8iMeu0qx9UoNtgher8J/zolWzkUa9jeR+TsIHpV4Y1aidYVdpZcQcPzMeYda8yPy8zMkFzXgO6I2XGuUYvOhMi5oXSb2NDOwqLUWgp7NAm2aNjPGsej02pCbADAm7Sj8vs+aFN25SA4MXE9BqnBd/VOkqrcPlVswW5I4zoWSbFJhVb0pGd5W2ao2fzyB1Og+UaXU8BsoxeNGZFhcqO46xIGbocbfMJz8x2yQ5eACtRHGzkffDg6S5jXie8Bgox+DFBBR3lQ7YbOQn50XRllrXq8JKQm1DRHu62pObMYlOGatejw2peTFFs5HChF2v/3OcF2l4DJRj8KIzLQapk/bUo2xbgD4XWzHlVLscvKAoY9XDZ0TOi88mrZqwKzfnxbJnCpmJbYIXy4zzosEPV9I4L2psX+drj/fu+TyxyhwkKxBeUpWxavBnRLF9YxfrHzhJvY0surtq4jFQzjbBi1XGedFCwGYVhesN1C6rx8VWzNOwTzlU6SqtfB0dmVXb8Y0ot884L4bVvCjbsNzpATiiManBNsGLVWhxodJ5jDp9cl58GtRDL6NOV2leVZUQc/TM2KXd8JoXqzYbef1fWldp/s4sW9tmIgxedKbFKRtwkDq/zUbK6ZLz4vV/7yahQIGaOoPUKV9HR2bV42fVchtN7aEKOhKec8oxeNGZFidtoOkB/I+wq8I4Lzr88kSN1qpyzgspY9WnSWOajbz+r/vW1dkuexvJx0OgHIMXnemZsOt/+8rpXfMSeBm1u0pTR2TM9278IHVq9jaSgnMbselMDQxebEBSs5FVcl7cF/7vHZh4b1v9Qep4QVHEooeP47zo+3mLniaq4jFQjsGLzrRJ2BXf28gqPxoxF0ZOD2AuVj1+hjQb+Wxf982rs12Zn+dDAqmBwYsNSGtvFn/hMPISI6YnkdzeDmK2SdJZ9fgZ0XXX91gZ3XCl7+etep6oicdAOQYvOtPiqSNgsqpG0wPoQUwyoJju1JK2ySuKIpZN2DW43Iaddgo3LPfj1jxL1MajoBSDF53pOc6L301Z5DcjKpBQO+dFhXV0ZFLPbdMEi0bUvJjgbFNe8yIz58Us37uBeAiUs03wYpXpAbTgO3x+8F+FGS6aYgQupVcvDRGTN6q0URJB6uEzywXckEHqTJCwqxRrXuSz0jE4V9uEnJJqo4vRjm2CF6tMD6DFSRsWduHGHWjun2CvmZF3d8pAZfbJi+EwL4aT+kRtllPRkIkZvf9v0YRduceNXaWtcx0GgGv+vBZJizYhp6TG6KL4sE3wYhWaNBt5r9/n//4GqVN/+5oI+GTq8Pu6nNjlVHkd1h4sDrAdkkrM8fPt9m6OI25MV2n/NYi6lkFpV2nZvY0UbZYMkp571ugi+IgwugAdjSYXqnY3hMC3cus3G3kto7Cr9Pi/rgcAvDt9FCZe0cc0N1PLEpOmZMLmEqPLofdp987mE/giuxBXD4jVd8Pf4c/MOtdhM2PNi860nh4gVHW0IADVDc1ocbnbv+lnWaMEbv4S/PxPWcLujtzydusj6aRekM3SfGB00Kr31l9YdQh7T1figx2n/L6f/NFuUesxyddnSTx2yjF4sQHvG7dProifZctrm3DVvG/wk9e3aF4uJQSfIMV//ovbp+ZF/rYam93t1k3SSe9tpE05pDJ6hF2zWbX3DEqqG0IuJ7f2wCxBq5Gseggaml1I+Wg3Ps8qMLooDF70psU5G2j4fH8yT54DABwuCp09bmQSbMAk3YB/yC9s03e1UKzKVcaqF2QjvnffgNyEB05iE6CkVZtwd/Vm1WvNu1vz8OXeM3h0eZbRRWHwojsdB6mz8kXCHSA5IlDNEmtejGfZrtKseZFF7i5Y9cathCAIqG9yef1tYGEUOFvbaHQRPBi86EyTrtISal6sQkz3aDFTCIjR2HL+omKTQ2cY6V2lzXHEjQ5erPqblVtjFOpjgiBg0dqjWL3vjKT1NrW48bO3tuEvaw7LKpeWHv5XJq6cswb5Z+uMLoptMHjRmSYXKq9qB9+aCe2uisvTT6GsJnQUnvrvbMXbEgL+P3TOS+bJc56mskCaWtztV06SWbXmRY8cDFebCZRCDWlgBXJLHWouqc3HyvBa2jH87kNxicOt1h4sRubJc3hrw3GZJdNO65AMy3f5T5Im6Ri8mNzRYhG5KV7/D5wToq5Zn+7DL97Zqdn6fZ9M/ecHuH1qXtpHL5V1zfjZW9vws7e2oTlI76rGltA9ryg0yQm72hRDMj3KccPCdahravG/fRULUFbTiN9+kIlNR0vVW2kA8ssd/IOl1fKaJsLDzD9SZes1yyyBu5UxeNFRQ7PLkxwq1uJvj4ZcRquBv0KtSkzSbyDFVQ1oaHbB5RaQnV/RLrgQ8zTqdgeveTlQWOn5f9snX2+NLS7kltVK/m6oLYnNRia5gutRjKKqBqQdKvHapjYbff5/B/HV/iI8uDRdk/X70qbZSK6YyHDP/91GTBUuQmstn1Vr28yEg9TpRBAE3PbaZhwvrZX0ufCw0PFlmE+zkdc2JW3Jv8+zCnB7Qj915g7ycssrG9G/e2fceW1/vL4uBz8fNRALf3a1532f/QiUsBsi5yWnVNxw1k0tbiQt2ii26BSAVWtejChJqPGY2qpvciEqIsxnKhB/zlTWKyuYBHKDEK2a6WKiwlH+3eW1vtmFi6LMd3sTWPOiGlPWvEydOhU9evTAXXfdZXRRVNPY4pYcuABAhIiqUO8lPthx0jOMsxpPd48uz8IX2YWK1+NPQUU93vyufXr5rnyf93yHT/d+/cL/XSFG2BWbHNfY4g5aM0PiiDmCUrr168WQr17CQ0ZpdSOunLMG97+zQ9MiSSXnuG07XoZzdc3qFwZAdMSFmpc6r549asopqcZne07Lvra21giZ5NS3NFMGL48++ijef/99o4thCmLacb1vCH/9+gju+ft2Sds4UVqDosrAg1LtOVUhaX1S9IiJ9Pt6oB93oFqYgop6zPl8v89FpW0uy7rDxZj5fka7dTLnRR3SB6kzxyXckN5GEsZ5ae11s+OEueaWkdr0caayHve/LT9P7nhpDT7aeSrgg4b3dTBQfpFSSYs24Y8rsvH1gSJZnzfzM5IgCNh5ohzlIjpimIEpg5cJEyaga9euRhfDFMTUvASqShbTJbG8phE3v7IR1y1IC7hcqBaj6oZm5JVJr1UCgJ4XdQpQtgD/D3LRf3/7SWz0SlRsm0fz0LIMnCxvXxvT5Cd4OR6kyelIUTVqGrW5OFrRu1tzsWb/Gck3M5PELprlHwT76UqZ48mseahSv79gD0jBt3N+Q7e8shF/+mwfPtp5MuRntKp5abW/oErW5zw5Lwad/IIgIPXfWZjz+f527609WIx7/7ED419ab0DJpJMcvGzatAlTpkxBv37n8yBWrlzZbhmn04nBgwcjOjoaY8aMQXq6Hslj9hSqjRsIMkhdiM8JApArIugICxG9XPdiGia8vAE5JdITeAPVvHiXPvD0AO0/5d1TQWyNSus4L95uecV/Dkx67llMWrwJP33D3NMr6OVocTWe+99BPPLBbsvmvLSWu7KuGf/NPI1alQJT0b1fQhwItfPN1CL1+44Qkb/X1s4T5bjmz2t9hqPfIWJ2Y61qXlpFhMv7TlqDFrXO/Yq6JjQ0iw/UTp+rx6e7C/D+9pPtrnvrj5xPKK/VOPBTi+Szqba2FgkJCXA6nX7fX7FiBVJTUzF37lzs3r0bCQkJmDRpEkpKLmTaJyYmYvjw4e3+FRZqk1thZWJqXuT6W9oxUcuFKkLryb7lWJnkMvS8KECzUaBB6rz+7y/xr97rh9zsEneJkNJs9Nme8xdROflLdlRZfyF/Qfo4L+0/UVnfjCmvb8Hbm04oLJl4refRr9/fhcc/ycbT/90bdPmGZhfufHMrXlpzGPtOV2Ld4WK/ywUL+qUcq1APD0aRWmMlpyvzL/+Zjoq6Zp/h6FtHxA6mtlHbG7Dc67KaXaXLaxqR+Pxa3LBwnejPtLj9PwhakeR07MmTJ2Py5MkB31+0aBFmzpyJGTNmAACWLFmCVatWYenSpZg1axYAICsrS15p/WhsbERj44Wn7aoqedV5Wjt9Tl4vACVjF4Q6Of+WdgzjhvQOuR6xT35iaona6h5zodnI5RY8+xuot5HvmC/t1+c9BHez2JoXERfDVmJm4+5IoiIuPP+43NKOjb/T85+bT2BfQSX2FVRi5vjvKSxdYP6+81155wcz/HLvGbxxf+DPfrn3DHafqsDuUxWehPN1j9/UbrmgwUuAplB/xP6s2vY02nPqHK4Z1EPch2UIdX05VV6Hz/YUYPr1gxEb0wmdZNRW+Bu+wF9NaVvezUbe1xW1iOkF6s+FBy7lkUPGd4Nvltc2if5MoEl8rUjVnJempiZkZmYiKSnpwgbCwpCUlITt26UlkYq1YMECxMbGev4NHDhQk+0oJbcrbriCpy612vLFFkHOE6L3RcW3h5H/sgdK2G1V3+zCp7tPY+/p9mPHBFIvotr1y72FWLHrlM+TCwFRXj08xASB3l/Zq2vbj2HUoEPy9PojJRjn1a7v7xruXJ+Dfacr27+B9rlUgP+Hk2A3zEBNof6I/V09+E/f5vmpb24zNDdryhtb8Oq3RzH7s/M1WWoFEGJqSlsDnHO1TbhuQRpmfxq8Ng0A9hec/76rGprxZXbwqQnkBGKAujUvcsvQyuo9LFUNXsrKyuByuRAXF+fzelxcHIqKxGdnJyUl4e6778bq1asxYMCAoIHP7NmzUVlZ6fmXn58fcFkr0nPUyPoAbZ1iL55qltXfj7uh2eV52gi0zPrDJUj9dzZuf2OraoPOCYKAlI/24On/7hOVI9SRRHrVvIhpe/f+yj7ceQqVGnWbDWZWm2Yhf4HyX78+gikS8pr85UC0/TkEGqMo1C1E7DPBsZL2SebVDcqOb+bJc/jx4k3Ydrx9k3CoG3Brk+LO73pJycl5adXVa8wWMcFLa5PxBztOorS6ER+nh74v/OT1Laisa0bKR3tw8EzwGny51zo1c17k1v60klhRajrmG8UHwLfffit62aioKERFRWlYGmMpOcmlRvdjF6Yha86P2r0u9neqNHbJPHkOGSfP4ZGbLvPbVPTVft+nIX81L/sKLjwt++tFJIf3A4r32DFutyCrqcxOvGsGRdWatPnOWkxwBVXjKdjfjbntDe7R5VnoGh2Bm6+IkzRInZKcl0DJ/GJNW5qOmsYW3P/2TuQtvM3nPak1u0rutT27RKL6u1qkRhFBcmvtmNSap5tf2SCqGSYiXH6z0cfppzD7032yPu9TBhnXnkmLN3n+7wpy4h0sPB+8DevXTXrBdKJq8NK7d2+Eh4ejuNg3ga24uBjx8fFqbqodp9MJp9MJl8samdKtKutbgj4diW36UENFgKdgKRfP3/wrA8P6xsra/r3/OD8IV6+LIjG8/4V1tP7EOnfyPV39VXt6v6TWsfO+wZ6tu3BhM+sonkYJ1Wz04NJ0ZAdoinGuz0FJVQOiOoX7fV9LatSe+3sS9/faQ8syJAcBSm76SmPr2iC9dsQGfeW1TXC5BUVB2Pd6X+QZ5kDMQ0lrblq1xOBFbP6IkoTdYIHLwcIqpHy8G0/+6HJMvqpv0Ack7zKIfZDyrrUK1mx062ubAQCH//zjkOs0iqrNRpGRkRgxYgTS0i6MGeJ2u5GWloaxY8equal2kpOTcfDgQezatUvT7ajt1W+P4pEPAs+e2iKyx4yWxP5MvzlQjK8PFONVEfMxBTPr031+q+x7xPiOCRPqpiO2t1Eo3pUD3hfsx/+dLXu8huKqBlQprNI3m4YQiZTBJgv869dH8N72kziiYL4sucR8h6HmyvGXfxDoZv3RzlPIETHhaqj1iOI4X1v4839sx/rDJaGXbyMmSDAp5cz/KF3ZbMregaCUZqPqBm1yflrLk1NSI6npM1SS7K/e24UTpbX47Ye7UVTZgJHzv8WLqw/5Xda7qTJYLYrcsgBAVb15r1GSg5eamhpkZWV5egzl5uYiKysLp06dPzlTU1Px9ttv47333sOhQ4fw29/+FrW1tZ7eRySNkgRRtQZCCtbbyDt6T5NxcQzE3yB1bcsRav+Utve3CnRhWHOgSNaop+U1jRjzYhqunveN0qKZipTxJrRcR1sZeWcx8eUNPgMYegt2FuWU1MC5PgeJz38TNLASW/MCAH/6bB/e235hoLVQP1Ml47yEORx44pNs7DhxFjOWSX+w6xwZuGZRSm+VtQf9dycXy/s6Iy54+a7ZSKMHhE7hDuSUVCNp0UYk/ln87zjUITvjNZDfO5tP4GxtE/4RYNgA76ZKOQ+5YhJ2zTxZreQ674yMDEycONHzd2pqKgBg2rRpWLZsGe69916UlpZizpw5KCoqQmJiItasWdMuiVdtVm02CkVJ11y16myCPfnpkbMQqFo91G8vz89ounIE+5HLqT3ZX2jO7vxKNUjocq6F0+fqcKK0FuOHXuzz+v3v7ERTixvTlqa3a7IBEPSH4t1LcP7qQ3j/odF+l+vkJwdCbI2JliPshjkcPgM3StU5MvDzrZ49bb3vzY3NLjS2uHCHc1vAkbBbH/rk9LYKc/i/tnjXvoWHhWH7idY55MSv21/AV1rtf+ThThHB6xa8g+Pz12FpTa5ighe1aq+1IDl4mTBhQsgn3pSUFKSkpMgulBzJyclITk5GVVUVYmPl5VyYkRm65ga7eBrZrKXXOAXBmgzk1G5ZfXyFQMSMvxHKThGjpwZy41/Od3/+6NdjcP33L4xfFCpHQuz3ERkkSdNfLYvoXBVBwI4T5ThWUoNfXndJ+/UoStiVdw3ZfqIc2fmVIYZq0O889h5DqLqxBRuPlOJQkB5BrTUvcpqNOncK9zvKrPdxjAiTlwrt76t45IPd2PPsD9HDa8DOHjGdfMZQ+u0Hmfhqv2+PXe9mIznXYTHnvZ45l1Ix21AD81cdxKEz1Zj0A+W1TUpOHrXukcESwfQIXgLth15BQLCLv5yvJ1T+hBJ//vIg6ptdeHHqVaLLsu14Oa7qH4vYGP/zTIklZbA/Le3Jr/AJXkIR+21EdwocjfgLMMSO0SQA+Pl3yerf630RbmhTdik3ybY/iTCHQ9Z4Ht4j2ordlhpe/voI/rG5fTNJ230ItWlFwUuk/+DF1SZ4kRNUBrpmHSiswg+8evYM6nWRzxhKbQMXwPf8khOgimo2MvGktaacmNHKDhZW4e3NudiSU4b0vHOhPxBC2+CgodmFkipxE5xpNeGcN32ajQK8rtODX7AgSU4AJXdwqC/3FmLV3sCDZzU0u/DPLbn4aOcpFFaIG9H5o/RT+MU/d+LOt7bKKlPb7ZtBVIjq9rbEfoXREntCie1G7739Y34SeaXkvHiPg3T+w9oMRpaVX4GjxYEnL5XrjfU5fm+Ybrfv9xpq/qnW66acnI1A33Oz17UuItwhqzkvUE1ti9uNHSfKPX9f2ivGZwwlf7xPCznfMWteTMIsOS/HvCYnzPEzaJRUbYOD8S+tR0l1I579yTB8uOMkXrvvGsXb8OY9AVqr4Dkv1mg2UlJLE+zCIGe9cg5ZTWMLUj7aAwC46fJJ6NKmi3ZuWS1iO/tOtSDGl3vPzycmZ66m2sYWlNYEngizodmFsxKGLldL50jfm493DsOZyvp2N0exQX6wmhd/5IyO7W+sHCU5Lw6HvJ4owZTVNOIOp/JgV4oWtxsxkeGecyz/bPDgXEmuRqCpXFxe6wwPCxM9eKC3QM96LS6hXaAlJQiXE2S43OdzKnfmnsU1g7r7XcbMNS+2CV7MmPMSrE1WrLY/wpLvku/+/OVBAMAjH2TigTHt28kBeTUT/qqLg1089YjMAzcbiV+HkhhL/eBFRm2N13lQ29jiE7zsPnUOd765DX1joyWv11+iqVgJz33jE7y2rXlxrs+RvW4pSqsbfboBR0f4Bi8Oh8NzEo1d0H4SO7HnRtv1elvsZ3gAsaOwej+NL/zqMK7qH+vTdKR0Yka1a15KqtonAGfnVyAyPAwJA7uruq1WLsH3ewo1pYcW1yXvcz3c4QhZIyYIAs5UNvj8LgP99v3VYIeqefEm5zt2uQUs/vYY3lifgxu+3wuDesa0W8bMCbtsNjK5UM0ywarq9ehtpPXsrecF6G0k4QerpOYl2Gdl5bzIKEu4V3Je26ehz7+b6dq7m6VYSoKXtrVubWteMlRoNhXj4X9l4CmvIf/91bwEJfL7iApS8/J5VmG71+T2Nmr7AOGd+CsnQVyt4KV12/6OwwurDuGnzq2e69FOryYQNbjdgqTfuxbN2W3X6f3tHiuuRllNIz7ceRLVDc341/Y8XDp7Na5fuA5vrLsQxAfaBX9BgpSaFzk14G5B8Iy/szXH//dl5mYjBi8mFyryVTIGhFjBNuE93LTepOT0CAp+g2rXvIi5mbTtIu/9FbQNEpSMxaB0cjdvbb8PpTeQO9/cKqraes+pCp+/2170Qz4hiyxPsJoXf8T2Nmp7CpXVNGL6u+ko+65Jzrv8cuIQtYKX1mtRsJtq67nZOlq2WlrcgqTmLy1qDNrmH3oHpz98dRMe+VcmnvlsP2b9dx+e/fyA571XvCYgDZbz0pa04EVOs5GIhF0GL9pzOp0YNmwYRo0aZXRRVBVqnJdgT5VqNXW/sOpQwBl29RBoP5SOryBW0OBFg0S5TUdLMWzO1/j4u6eithe8phY3ml1upB0qRmV9s6JePkpqXtpqu1tKbyC7T1X45JCJ1TZWCVXzIvbUWJGRj8f/nR3y+xOE8+eMlN5GbW04UooFqw8D8L1J6pkg3lbrtoNNsCh32PyQ23YLkvZDixqDtttvexhak6VX7QucVB/o+/P3W5HSbCSn1+eps3Uhc9LMXPPCnBeTC/WDDV41rd7Th5QZdvWiW/AStLeR9PWFekh6cGk6gPNzoEy4/GJMeX0Lbk/o73m/yeXGa2nH8Pq6HCQMiMWAHu3bqsXSKnh54pNsVaru25Zv/ZESvLjqEF65JwFXD+gOAOgSFeEzGJm/7sLBiD03Tp+rx+lzp0P2dFm+Kx/bT5SjW7S4rueBnsbLa8/XvHjHA0YGL2KaJrSqCG5xuyXtuxZDOLRvNpLTVdr/6wtWH/KZzw2QVqsu5zue98WBkMuYOXixTc1LR6U0mc8KAta8SFiHVgm7cnpyiP3M4F4x+Nu3x1BW04SlW3M9rze1uPGfzNMAgOzTlYoGh1O32eiCbcfLUadBPtSMd3fhWEkNZrx7Yaj7uG6+s8pLDV6kfoVibuIny+twUGTCfqj1eZdfTgyuVm8jl6EDUkr7DWudsAu0D9TEJGgHCsDO1TVj87EyBWWTvr9iRh9ubmHCLmkk2HXZLgO5BsptkZK8qGSep2DXBTnrFfuZ7jGRfl8/32x0YR1i5noJRN2aF9/9atZwDKDy2ibkfNekFNkmF6XtDSLULaWsphF7TolPLr4oSlzui9jvOVTTsMM0NS/GPYW7TNBsFCznBWg/caw/Wl2TtRphlzkvpJmOELwEolvNS9DeRnJuJuKWC/Qk1+xy+1ycxea87C+oxNItuT5l9g5eXl17VNE8OG1pPfrynz7d7/d1AcDR4mq8tOYwqhqaQzZlvLnhOKa+uU30dmOCTFbYthxihMoNClOYsKsWpUGQkk9LneNNi/GnQtW8eI+zFIhWo4KrMcKuv6k5zNxsZJucF7MMUqe3Dt1spFvCbuAfsKzeHyLLEijhs7HF7XMxF9Ns9OXeQs8gdzGR4fj56EEAfJuN/pZ2DNtPlOPfvxkrqnxttd0trQcwDFQTIAjAT17bgiaXG4UV9aJHuhUrUmRTm9hTLtB+bDhSirO1TYoTdtWipPlJEARM/y6XS44miYGwNgm7vutse+09X1MafLBHMwUvbT9yws9AlWYOXmxT85KcnIyDBw9i1y7p075bWbDgRY/pAfQQeC/E75+y4CXIemVcNMQ2JwTq1NHkcqPZa7timo1aAxfAd/DEiDbNRukKJkZs11Va5Qvf2oPFokvSWt29+ViZ6QP8YDVUt7yyAeuPXBiAL/9snaZzYwWjpCatqcWNYwpGHJd6E9Wiq3TbdbaNiYNN3NlKq68u2AOWEmYeYdc2wUtH4O+m16GbjSTsn5JjYcQ4L0DgZqOmNjUveeXSh/Zv1Umjrq2Aus1G6w+XYOb7GaKW9T68FfXNiobX10OwG+25uma8teG45+/bXtuC3y/fE3B5LWkxR5JYUoMXtQNnwN/++55YYsb1EZ0H5RYk5dNpNRKu1BovPTF4sRB/147ymib8Zc1h/QujIzV6GylJag06wq6GcxttzSn3G5g0tbh91tGgYJwXLS9Naibszlgmvka1xmsmYZdb0GUgRyWkJsIGm5xTS0bOYyY1eNGiqG3Hb2kbFIup4XML4sbC+XLvGTy0LHCwnpVf4fO3VoElm41IFf5O0Mr65oDLmzdmliZwbyPx60hatFH29oNdGOTU6ASr9m/7tLXjRPtmnCYFXaPblUXD6jmtE3YD8Z4qAAjd28hoZp4/xpuR+TZGH6P9BZX4aOcpn9fkNEe6BUH0nFfBtJ0YU6vAUosaLLUweLGI+iYX7l4ivkdER6BXTk/QcV7kZPkHuQmIuT+o2X1Ry2uTkU/q3syf82LeG4Q3o4JRM8gta18D2n4kZ3E1L2oOT9BKq3PI6KAxGNsEL3adHqDV8l2nkC1xiH7b5Lyo0NtICT1nlRbTDKVmEp2RT9N6MXvOi1mCvFDEBOq/+VcmSqqlTxBqdv4Ck7aviTnPBEFAhIoDQ7bSqtnIyLF9QrFN8GL33kZy8hrs3ttIr70LOj2AnC6KCmtyxAQvLW4B/9qeh6PFwecG8leWkuoG7D1dEXIbVmH2nBcz5xV4E3Mj23ysDHNWhh523mr8nUL/y/adSVxczYug2fxPWjBzbZttgheSZ+PRUqOLIJuSUXOlCBZsiI1dCivq8eXeQrjcQtDPiKkJEfOk/nH6KTz7+QH86NXgs377C8xGz0/D7W9sxf4C4ybjVJPY2Z2NYuYbhDexT/dnKus1Lon+2sYb+efq8OmeAp/XxMTIbnfwiS3Nxsy1grYZpI78EHHevb4uR/tyKKRXkBJI0BF2RZbtxr+sg1sA5k9tVj2Hxp9sr94IE/66PuBywYq/40R5u8nirMj0OS8mrpr3ZmRXaSNtO16GRz7Y7fNamZ+RqMXU8KmVsKsXM+djWScEJMnscqkJtB+1Gkz8548aOS+tq9h2vDzoZ7S4j+WV1wV8T+18HrW1uAT8/mNl45qYP3gx/jiL0VGDl/vf3ilqOXE5L+pOhqq1ZhN/5wxeyLL+9Nk+XbYT7KL9940nJK0r3OFQfdwYJYLP26RjQQL4PLugXW6BVGa/VeiV86I0hrNKkGUUh4gzjTUv6mHwYnLZpyslzXjrzejmFrUYvRuhnjgr6ppEryvM4RsUNLW4UVLdgLqmFlHbUluwc8QMNS/nasUf20BMXvGiW85LoLmyxHpzg/mbmI0kJpXFLQiadJUuqKiXfZ8Ixsz5WMx5sYCpb27D0z++QtJnXv76iCWajcTMpWP0foS6iUsJOMLCHD4Bwy2LNiD/7PkEx81PTURkhL7PE3rk3yihxsXzuJ8J58xEr+Os9Inf34CJdIGYnBdBUP49+LP422NY/O0x1ddr5to229S82H2cF6neWG+Np6SjxfIna9NLqJrTtpMbBiMIwNcHijx/twYuAPBa2jHsOFEuuXxKBLs2mSF4MXObu1r0ukFYqbnCisRM2+AWBEnXC6OZOZncOkcxBLuP8yKHCWr9VWF081eoGVsD3RPe356HJz/J9ulq/dmegoAJtHVNLjy6PEtuMWUJ3g3c+BOo2cSz2qrFKjUvpJxbMH8Oljczj7DLZiMbM+9pJ41R+7Fq7xks25aLay/pIevzcz4/P1jXpB/Eq1ksVQVNHjZBrYeZn/zUIqfm5bM9p/HtoWJJnwkPc2D1PmMmdaTz3IK1hg41c8IugxeiAJI/Oj+2w648ZYlwNY0toRdSQZhD+my6wR6sWnsi7S+oxK68s5g2drD8wslk5ic/tYSq2fPnjyuyJX8mIsyB3324O/SCpBlBgKWqxM2c88LgxcaMbm5RjU12Q2sR4WGS5z0K2mz03Xs/eX0LAKBzp3D5hZPJKkPnW4HZx7vpCKxX82Le0tom50UPjS0ufLjzpNHFEM28p5001vq5GydSRiJgsGaj4qpGn/NdaQ2UHGa+eFoNc16Md6aywVK1iWZutmXwIsG7W/PwzGf7jS4GkV9iZ6uta3Khsq4ZQPC8li+yC33O96qGZmUF9OPfGaeDvt9s4oun1TB0MYdDZ6qMLoJoZn54YPAigfd8MZag4nln5FObXVq/QlmlMJlS7OBXn2SeRsLz36CuqUVSjkxlvfrBy1/WHA76vpkvnh3VWomJwmRdZn54YPAiQa8ukUYXQRI1m1uUjs5J2uskMcA8dbZOUnfoKg2Cl1CY82IuLreAZ1cGr31muGkf3g8PLkHA25tzDSyNLwYvEvS8KMroIhjGyFncO0rNi1JSB7+KCAuT1B2awQuJ6QSw93SlDiWxLjm5aUbx7m20/nCJgSVpzzpH0QR6W63mRc1mIwNrXpiwK47Upr1O4cEniWyrqkGfLt/ezNxVk0gOI69noy/tiYfHf0/08t7jvNTqNOSDWLYJXvSYHsCIrqJKqBm8hLGngulJ/YYiwsMkBS96jVfjrSOMsGsVXaM4soYajK5J7hYt/ns0c86ZbYIXTg+gLSbshvbvXfl4PU39ydG00inMATPk4+0MMp9TR5jbyCo66TxpqBbe25ZndBEMr0cOl5ADYOaEXYbSNmaXhF2jf+xiPfXfvQCAH/0gHpfHdzW4NCI4Loyia6R7/7Ej4HtmHp6czK3Z5UZpdaPn79LqRsz94oAq6/5WQf6H0YOHRkh4EG1oNu/vz/qhNAXEZiNjVGswHopWjL6QhmKlAb3IXJ7+7mGiVX2TS7V1Kxk2w+gz2i6DFTJ4IVEMrXkx+tduY2aYfDEY9jYiuT7dXWB0Efwy+nrWSeRglmbH4MXG1PyNGButm/sGa2Vmr9hgbyMidUnJeTEze+wF+aVus5F66yLzMHuzkdlrhoisRkrOi5nxlkSisNlIPindkfXG4ICoY2HOC1mAejcmIxN2zX57FQBsPFoa8H0zxwdmLhsRqU/sBK5mx+DFIuR0e1a12YhzGwX0RVYhpi1ND/i+28QRgpnLRkTqY80L6crolgcjz/dgeRl/uvUKHUviX6g5P8wwlkogZm7SIiL1MeeFdCUnN8Eut6Vg+2GFyTKXbjHPTKxE1LGxtxHpSk6XUbP3JOkojpXUGF0EIuqAhsZ1afcaa140kp+fjwkTJmDYsGG4+uqr8cknnxhdJFNwmXiOCa0xBpPu9Ll6o4tARAZz+Jmu1S45L6ab2ygiIgKLFy9GYmIiioqKMGLECNx666246KKLjC6aoWTVvGhQDiPYZT/0VFDB4IWI2rNLzYvpgpe+ffuib9++AID4+Hj07t0bZ8+e7fDBC3uFmFeagknaiIj0ZJeaF8nNRps2bcKUKVPQr18/OBwOrFy5st0yTqcTgwcPRnR0NMaMGYP09MDdSIPJzMyEy+XCwIEDZX3eTuTlvGhQEAMwd0d7j9x0mdFFICIdyB3nZWfuWZVLoozk4KW2thYJCQlwOp1+31+xYgVSU1Mxd+5c7N69GwkJCZg0aRJKSi48nSYmJmL48OHt/hUWFnqWOXv2LB588EH84x//kLFb9tORexuR9m4aejGG9+9mdDGISGN26W0kudlo8uTJmDx5csD3Fy1ahJkzZ2LGjBkAgCVLlmDVqlVYunQpZs2aBQDIysoKuo3GxkbccccdmDVrFq6//vqQyzY2Nnr+rqqqErkn6sg/V+f39Ut7X4TcslrVtsNh3ElrRk4BQdrYZbKnZVLPmxuOy/qcXXJeVA3BmpqakJmZiaSkpAsbCAtDUlIStm/fLmodgiBg+vTpuPnmm/HLX/4y5PILFixAbGys55/eTUx1TS6/r0eGqxvdtsiY/tcuzS022Q3Ts0tbOF3wq/cyjC4CaeTT3QWyPmeX37mqd9iysjK4XC7ExcX5vB4XF4eioiJR69i6dStWrFiBlStXIjExEYmJidi3b1/A5WfPno3KykrPv/z8fEX7QOYjZ2oEks4uFzUiCswuU72YrrfRjTfeCLeEMU2ioqIQFWX+UVaJzM4uFzUiCswuP3NVa1569+6N8PBwFBcX+7xeXFyM+Ph4NTfVjtPpxLBhwzBq1ChNt2Mldmlusct+mE1do8tn9F+7zDZLRPanavASGRmJESNGIC0tzfOa2+1GWloaxo4dq+am2klOTsbBgwexa9cuTbdjJWxuoWCmvrnV52/WvBCRVUhuNqqpqUFOTo7n79zcXGRlZaFnz54YNGgQUlNTMW3aNIwcORKjR4/G4sWLUVtb6+l9RCQVa160ca6u2edv5rwQkVVIDl4yMjIwceJEz9+pqakAgGnTpmHZsmW49957UVpaijlz5qCoqAiJiYlYs2ZNuyReIrFYg6QPu3ShJCL7kxy8TJgwIWQX3JSUFKSkpMgulBxOpxNOpxMul/+uy0R2d0LhuEJ2bza6PK4rjhRXG10MIlKBPYbaA3Ne7IzNRvqwe/BCRPZhm+CF7Iuxiz4YuxCRVdgmeGFXaSIioo7BNsELm41sjFUvRETkxTbBC9mX1XobzfvfAZRUNRhdDCIi22LwQqSy/QVVeGxFltHFICKyLdsEL8x5sS8r9jbaV1BpdBGIiGzLNsELc17sy4KxCxERacg2wQsRERF1DAxeyPRCjehMHZMAoMXlNroYRGQAydMDEOmNoQv5s+dUBUbN/xYXRfEyRtbjcFgzn88sbFPzwoRdoo7nXF0zTp+rN7oYRJJxQGtlbBO8MGHXvvh0QkR24+B8HIrYJngh+2LsQkR2w9BFGQYvREREOmPFizIMXoiIiHTmYN2LIgxeiIiI9MbYRREGL0RERGQptgle2FWaiIgC+VvaMaOL4IMVL8rYJnhhV2kiIgrkv7tPG10EH0zYVcY2wQsREZFVMGFXGQYvREREOmPNizIMXoiIiHTG2EUZBi9EFnOyvM7oIhCRQpweQBkGL0QWs2rfGaOLQEQKMXRRxjbBC7tKExGRZTB6UcQ2wQu7ShMRkVUwdlHGNsELERGRVTDnRRkGL0RERDpj7KIMgxciIiKdMXZRhsELERGRzthspAyDFyIiIrIUBi9EREQ6Y72LMgxeiIiIdMZWI2UYvBAREemO0YsSDF6IiIh0xpoXZRi8EBER6YyxizK2CV44txEREVkFa16UsU3wwrmNiIjIKhyse1HENsELERGRVbDmRRkGL0RERDpj7KIMgxciIiKdcXoAZRi8EBERkaUweCEiItIZK16UYfBCRESkMwYvyjB4ISIiIkth8EJERKQzjvOiDIMXIiIinbHZSBkGL0RERGQpDF6IiIh0xFoX5UwXvFRUVGDkyJFITEzE8OHD8fbbbxtdJCIiItUwdlEuwugCtNW1a1ds2rQJMTExqK2txfDhw3HnnXeiV69eRheNiIhIMY6uq5zpal7Cw8MRExMDAGhsbIQgCBAEweBSERERqYOhi3KSg5dNmzZhypQp6NevHxwOB1auXNluGafTicGDByM6OhpjxoxBenq6pG1UVFQgISEBAwYMwJNPPonevXtLLSYREZEpseJFOcnBS21tLRISEuB0Ov2+v2LFCqSmpmLu3LnYvXs3EhISMGnSJJSUlHiWac1nafuvsLAQANC9e3dkZ2cjNzcXH330EYqLi2XuHhERkblwjBflJOe8TJ48GZMnTw74/qJFizBz5kzMmDEDALBkyRKsWrUKS5cuxaxZswAAWVlZorYVFxeHhIQEbN68GXfddZffZRobG9HY2Oj5u6qqSuSeEBERGYCxi2Kq5rw0NTUhMzMTSUlJFzYQFoakpCRs375d1DqKi4tRXV0NAKisrMSmTZtw+eWXB1x+wYIFiI2N9fwbOHCgsp0gIiLSEGMX5VQNXsrKyuByuRAXF+fzelxcHIqKikSt4+TJkxg3bhwSEhIwbtw4/P73v8dVV10VcPnZs2ejsrLS8y8/P1/RPhAREZG5ma6r9OjRo0U3KwFAVFQUoqKitCsQERERmYqqNS+9e/dGeHh4uwTb4uJixMfHq7mpdpxOJ4YNG4ZRo0Zpuh0iIiIylqrBS2RkJEaMGIG0tDTPa263G2lpaRg7dqyam2onOTkZBw8exK5duzTdDhERERlLcrNRTU0NcnJyPH/n5uYiKysLPXv2xKBBg5Camopp06Zh5MiRGD16NBYvXoza2lpP7yMiIiIiJSQHLxkZGZg4caLn79TUVADAtGnTsGzZMtx7770oLS3FnDlzUFRUhMTERKxZs6ZdEq/anE4nnE4nXC6XptshIiIiY0kOXiZMmBByuP6UlBSkpKTILpQcycnJSE5ORlVVFWJjY3XdNhEREenHdHMbEREREQXD4IWIiIgsxTbBC7tKExERdQy2CV7YVZqIiKhjsE3wQkRERB0DgxciIiKyFNsEL8x5ISIi6hhsE7ww54WIiKhjsE3wQkRERB0DgxciIiKyFAYvREREZCm2CV6YsEtERNQx2CZ4YcIuERFRx2Cb4IWIiIg6BgYvREREZCkMXoiIiMhSGLwQERGRpdgmeGFvIyIioo7BNsELexsRERF1DLYJXoiIiKhjYPBCRERElsLghYiIiCyFwQsRERFZCoMXIiIishQGL0RERGQptgleOM4LERFRx2Cb4IXjvBAREXUMtgleiIiIqGNg8EJERESWwuCFiIiILIXBCxEREVkKgxciIiKyFAYvREREZCkMXoiIiMhSGLwQERGRpTB4ISIiIkuxTfDC6QGIiIg6BtsEL5wegIiIqGOwTfBCREREHQODFyIiIrIUBi9ERERkKQxeiIiIyFIYvBAREZGlMHghIiIiS2HwQkRERJbC4IWIiIgshcELERERWQqDFyIiIrIUBi9ERERkKaYNXurq6nDJJZfgiSeeMLooREREZCKmDV7mz5+P6667zuhiEBERkcmYMng5duwYDh8+jMmTJxtdFCIiIjIZycHLpk2bMGXKFPTr1w8OhwMrV65st4zT6cTgwYMRHR2NMWPGID09XdI2nnjiCSxYsEBq0YiIiKgDkBy81NbWIiEhAU6n0+/7K1asQGpqKubOnYvdu3cjISEBkyZNQklJiWeZxMREDB8+vN2/wsJCfP755xg6dCiGDh0qf6+IiIjItiKkfmDy5MlBm3MWLVqEmTNnYsaMGQCAJUuWYNWqVVi6dClmzZoFAMjKygr4+R07dmD58uX45JNPUFNTg+bmZnTr1g1z5szxu3xjYyMaGxs9f1dVVUndJSIiIrIQVXNempqakJmZiaSkpAsbCAtDUlIStm/fLmodCxYsQH5+PvLy8vDyyy9j5syZAQOX1uVjY2M9/wYOHKh4P4iIiMi8VA1eysrK4HK5EBcX5/N6XFwcioqK1NyUx+zZs1FZWen5l5+fr8l2iIiIyBwkNxvpafr06SGXiYqKQlRUlPaFISIiIlNQteald+/eCA8PR3Fxsc/rxcXFiI+PV3NT7TidTgwbNgyjRo3SdDtERERkLFWDl8jISIwYMQJpaWme19xuN9LS0jB27Fg1N9VOcnIyDh48iF27dmm6HSIiIjKW5Gajmpoa5OTkeP7Ozc1FVlYWevbsiUGDBiE1NRXTpk3DyJEjMXr0aCxevBi1tbWe3kdERERESkgOXjIyMjBx4kTP36mpqQCAadOmYdmyZbj33ntRWlqKOXPmoKioCImJiVizZk27JF61OZ1OOJ1OuFwuTbdDRERExpIcvEyYMAGCIARdJiUlBSkpKbILJUdycjKSk5NRVVWF2NhYXbdNRERE+jHl3EZEREREgTB4ISIiIkuxTfDCrtJEREQdg22CF3aVJiIi6hhsE7wQERFRx8DghYiIiCzFNsELc16IiIg6BtsEL8x5ISIi6hhsE7wQERFRx8DghYiIiCyFwQsRERFZim2CFybsEhERdQy2CV6YsEtERNQx2CZ4ISIioo6BwQsRERFZCoMXIiIishQGL0RERGQptgle2NuIiIioY7BN8MLeRkRERB2DbYIXIiIi6hgYvBAREZGlMHghIiIiS2HwQkRERJbC4IWIiIgsJcLoAqhNEAQAQFVVlerrrquphruxLuD7VVVVnmVaGsKCLitVY12N5PU110erVobmeoeq+yNt251QVVWFmuqqdmUI9Z0YxYVwuBtdRhdDtNrqajTViz/HWhrccDc2+Lxm5Dkihlq/STm/xWD0Om4tDS64Gxtlf94V3oyqqva/QTGa66NU3ccGP9+B93Fsro8w9bnocoV9933Ua7qdtud8c32U3+uoHFrcY1vX2XofD8YhiFnKQk6fPo2BAwcaXQwiIiKSIT8/HwMGDAi6jO2CF7fbjcLCQnTt2hUOh0PVdVdVVWHgwIHIz89Ht27dVF03XcDjrA8eZ/3wWOuDx1kfWh1nQRBQXV2Nfv36ISwseFaL7ZqNwsLCQkZsSnXr1o0/DB3wOOuDx1k/PNb64HHWhxbHOTY2VtRyTNglIiIiS2HwQkRERJbC4EWCqKgozJ07F1FRUUYXxdZ4nPXB46wfHmt98DjrwwzH2XYJu0RERGRvrHkhIiIiS2HwQkRERJbC4IWIiIgshcELERERWQqDF5GcTicGDx6M6OhojBkzBunp6UYXyVIWLFiAUaNGoWvXrujTpw/uuOMOHDlyxGeZhoYGJCcno1evXujSpQt+9rOfobi42GeZU6dO4bbbbkNMTAz69OmDJ598Ei0tLXruiqUsXLgQDocDjz32mOc1Hmd1FBQU4Be/+AV69eqFzp0746qrrkJGRobnfUEQMGfOHPTt2xedO3dGUlISjh075rOOs2fP4oEHHkC3bt3QvXt3/OpXv0JNTY3eu2JqLpcLzz77LC699FJ07twZl112Gf785z/7zH/DYy3dpk2bMGXKFPTr1w8OhwMrV670eV+tY7p3716MGzcO0dHRGDhwIF566SV1dkCgkJYvXy5ERkYKS5cuFQ4cOCDMnDlT6N69u1BcXGx00Sxj0qRJwrvvvivs379fyMrKEm699VZh0KBBQk1NjWeZRx55RBg4cKCQlpYmZGRkCNddd51w/fXXe95vaWkRhg8fLiQlJQl79uwRVq9eLfTu3VuYPXu2Ebtkeunp6cLgwYOFq6++Wnj00Uc9r/M4K3f27FnhkksuEaZPny7s3LlTOHHihPD1118LOTk5nmUWLlwoxMbGCitXrhSys7OF22+/Xbj00kuF+vp6zzI//vGPhYSEBGHHjh3C5s2bhe9///vCfffdZ8Qumdb8+fOFXr16CV9++aWQm5srfPLJJ0KXLl2Ev/3tb55leKylW716tfDMM88In376qQBA+Oyzz3zeV+OYVlZWCnFxccIDDzwg7N+/X/j444+Fzp07C3//+98Vl5/BiwijR48WkpOTPX+7XC6hX79+woIFCwwslbWVlJQIAISNGzcKgiAIFRUVQqdOnYRPPvnEs8yhQ4cEAML27dsFQTj/YwsLCxOKioo8y7z11ltCt27dhMbGRn13wOSqq6uFIUOGCGvXrhVuuukmT/DC46yOp59+WrjxxhsDvu92u4X4+Hjhr3/9q+e1iooKISoqSvj4448FQRCEgwcPCgCEXbt2eZb56quvBIfDIRQUFGhXeIu57bbbhIceesjntTvvvFN44IEHBEHgsVZD2+BFrWP65ptvCj169PC5bjz99NPC5ZdfrrjMbDYKoampCZmZmUhKSvK8FhYWhqSkJGzfvt3AkllbZWUlAKBnz54AgMzMTDQ3N/sc5yuuuAKDBg3yHOft27fjqquuQlxcnGeZSZMmoaqqCgcOHNCx9OaXnJyM2267zed4AjzOavniiy8wcuRI3H333ejTpw+uueYavP322573c3NzUVRU5HOcY2NjMWbMGJ/j3L17d4wcOdKzTFJSEsLCwrBz5079dsbkrr/+eqSlpeHo0aMAgOzsbGzZsgWTJ08GwGOtBbWO6fbt2zF+/HhERkZ6lpk0aRKOHDmCc+fOKSqj7SZmVFtZWRlcLpfPhRwA4uLicPjwYYNKZW1utxuPPfYYbrjhBgwfPhwAUFRUhMjISHTv3t1n2bi4OBQVFXmW8fc9tL5H5y1fvhy7d+/Grl272r3H46yOEydO4K233kJqair+9Kc/YdeuXfjDH/6AyMhITJs2zXOc/B1H7+Pcp08fn/cjIiLQs2dPHmcvs2bNQlVVFa644gqEh4fD5XJh/vz5eOCBBwCAx1oDah3ToqIiXHrppe3W0fpejx49ZJeRwQvpLjk5Gfv378eWLVuMLort5Ofn49FHH8XatWsRHR1tdHFsy+12Y+TIkXjxxRcBANdccw3279+PJUuWYNq0aQaXzl7+/e9/48MPP8RHH32EH/zgB8jKysJjjz2Gfv368Vh3YGw2CqF3794IDw9v1xujuLgY8fHxBpXKulJSUvDll19i/fr1GDBggOf1+Ph4NDU1oaKiwmd57+McHx/v93tofY/ONwuVlJTg2muvRUREBCIiIrBx40a89tpriIiIQFxcHI+zCvr27Ythw4b5vHbllVfi1KlTAC4cp2DXjfj4eJSUlPi839LSgrNnz/I4e3nyyScxa9Ys/PznP8dVV12FX/7yl/jjH/+IBQsWAOCx1oJax1TLawmDlxAiIyMxYsQIpKWleV5zu91IS0vD2LFjDSyZtQiCgJSUFHz22WdYt25du6rEESNGoFOnTj7H+ciRIzh16pTnOI8dOxb79u3z+cGsXbsW3bp1a3cj6ahuueUW7Nu3D1lZWZ5/I0eOxAMPPOD5P4+zcjfccEO7rv5Hjx7FJZdcAgC49NJLER8f73Ocq6qqsHPnTp/jXFFRgczMTM8y69atg9vtxpgxY3TYC2uoq6tDWJjvrSo8PBxutxsAj7UW1DqmY8eOxaZNm9Dc3OxZZu3atbj88ssVNRkBYFdpMZYvXy5ERUUJy5YtEw4ePCg8/PDDQvfu3X16Y1Bwv/3tb4XY2Fhhw4YNwpkzZzz/6urqPMs88sgjwqBBg4R169YJGRkZwtixY4WxY8d63m/twvujH/1IyMrKEtasWSNcfPHF7MIbgndvI0HgcVZDenq6EBERIcyfP184duyY8OGHHwoxMTHCBx984Flm4cKFQvfu3YXPP/9c2Lt3r/DTn/7Ub1fTa665Rti5c6ewZcsWYciQIR26+64/06ZNE/r37+/pKv3pp58KvXv3Fp566inPMjzW0lVXVwt79uwR9uzZIwAQFi1aJOzZs0c4efKkIAjqHNOKigohLi5O+OUvfyns379fWL58uRATE8Ou0np6/fXXhUGDBgmRkZHC6NGjhR07dhhdJEsB4Pffu+++61mmvr5e+N3vfif06NFDiImJEaZOnSqcOXPGZz15eXnC5MmThc6dOwu9e/cWHn/8caG5uVnnvbGWtsELj7M6/ve//wnDhw8XoqKihCuuuEL4xz/+4fO+2+0Wnn32WSEuLk6IiooSbrnlFuHIkSM+y5SXlwv33Xef0KVLF6Fbt27CjBkzhOrqaj13w/SqqqqERx99VBg0aJAQHR0tfO973xOeeeYZn+63PNbSrV+/3u81edq0aYIgqHdMs7OzhRtvvFGIiooS+vfvLyxcuFCV8jsEwWuYQiIiIiKTY84LERERWQqDFyIiIrIUBi9ERERkKQxeiIiIyFIYvBAREZGlMHghIiIiS2HwQkRERJbC4IWIiIgshcELEVnGhAkT8NhjjxldDCIyGIMXIiIishROD0BEljB9+nS89957Pq/l5uZi8ODBxhSIiAzD4IWILKGyshKTJ0/G8OHD8fzzzwMALr74YoSHhxtcMiLSW4TRBSAiEiM2NhaRkZGIiYlBfHy80cUhIgMx54WIiIgshcELERERWQqDFyKyjMjISLhcLqOLQUQGY/BCRJYxePBg7Ny5E3l5eSgrK4Pb7Ta6SERkAAYvRGQZTzzxBMLDwzFs2DBcfPHFOHXqlNFFIiIDsKs0ERERWQprXoiIiMhSGLwQERGRpTB4ISIiIkth8EJERESWwuCFiIiILIXBCxEREVkKgxciIiKyFAYvREREZCkMXoiIiMhSGLwQERGRpTB4ISIiIkth8EJERESW8v/q5oSKGea43QAAAABJRU5ErkJggg==", + "image/png": 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", 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" ] @@ -304,10 +413,10 @@ } ], "source": [ - "esc_ep.plot(x='t', y = ['total_pop'], title='total population')\n", - "esc_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns')\n", - "esc_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", - "esc_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" + "mid_ep.plot(x='t', y = ['total_pop'], title='total population')\n", + "mid_ep.plot(x='t', y = ['non_random_newb'], title='Fished non-random newborns')\n", + "mid_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", + "mid_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" ] }, { diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index 87e7dcb..bbc611c 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -62,6 +62,14 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): self.parameters["ages"] = range( 1, self.parameters["n_age"] + 1 ) # vector of ages for calculations + self.reproducibility_mode = config.get('reproducibility_mode', False) + if self.reproducibility_mode: + self.fixed_r_devs = get_r_devs( + n_year=self.n_year, + p_big=self.parameters["p_big"], + sdr=self.parameters["sdr"], + rho=self.parameters["rho"], + ) default_init = self.initialize_population() self.init_state = config.get("init_state", equib_init) @@ -119,7 +127,9 @@ def reset(self, *, seed=None, options=None): self.state = self.init_state * np.array( np.random.uniform(0.1, 1), dtype=np.float32 ) - if len(self.r_devs) == 0: + if self.reproducibilty_mode: + self.r_devs = self.fixed_r_devs + else: self.r_devs = get_r_devs( n_year=self.n_year, p_big=self.parameters["p_big"], diff --git a/src/rl4fisheries/envs/asm_fns.py b/src/rl4fisheries/envs/asm_fns.py index fa41187..4edfc93 100644 --- a/src/rl4fisheries/envs/asm_fns.py +++ b/src/rl4fisheries/envs/asm_fns.py @@ -32,6 +32,7 @@ def asm_pop_growth(env): new_state[0] = ( env.parameters["bha"] * env.ssb / (1 + env.parameters["bhb"] * env.ssb) + * (env.ssb if env.ssb < 1 else 1) # let's suppress spawners if ssb is smaller than 1 * env.r_devs[env.timestep] ) # @@ -90,7 +91,11 @@ def get_r_devs(n_year, p_big=0.05, sdr=0.3, rho=0): n_rand = np.random.normal(0, 1, n_year) r_big = np.random.uniform(10, 30, n_year) - r_low = (1 - p_big * r_big) / (1 - p_big) # small rec event + # r_low = (1 - p_big * r_big) / (1 - p_big) # small rec event + r_low = [ + np.random.choice([1,0], p = [0.6, 0.4]) + for _ in range(n_year) + ] r_low = np.clip(r_low, 0, None) dev_last = 0 for t in range(0, n_year, 1): From 81aefbafb5063d696fc21d0e447e443086a3440c Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Tue, 9 Apr 2024 23:09:55 +0000 Subject: [PATCH 15/64] added SystemDynamics --- notebooks/SystemDynamics.ipynb | 553 +++++ notebooks/optimal-fixed-policy.ipynb | 2845 ++++++++++++-------------- notebooks/popdyn_tests.ipynb | 573 ++++-- src/rl4fisheries/envs/asm_env.py | 10 +- src/rl4fisheries/envs/asm_fns.py | 18 +- 5 files changed, 2292 insertions(+), 1707 deletions(-) create mode 100644 notebooks/SystemDynamics.ipynb diff --git a/notebooks/SystemDynamics.ipynb b/notebooks/SystemDynamics.ipynb new file mode 100644 index 0000000..11afca8 --- /dev/null +++ b/notebooks/SystemDynamics.ipynb @@ -0,0 +1,553 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "4915b572-bc73-42a4-95d3-0f2cb400232c", + "metadata": {}, + "source": [ + "# Deep dive into the population dynamics of the system\n", + "---\n", + "\n", + "## Setup" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "33f65b87-cce6-4cbc-96aa-687798d5db53", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# %pip install -e .." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "15ea0eae-88c4-4306-803d-76f0a7b0bba6", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import ray\n", + "from typing import List, Text, Optional\n", + "\n", + "from skopt import gp_minimize, gbrt_minimize \n", + "from skopt import dump\n", + "from skopt.plots import plot_objective, plot_convergence\n", + "from skopt.space import Real\n", + "from skopt.utils import use_named_args\n", + "\n", + "from stable_baselines3.common.evaluation import evaluate_policy\n", + "from stable_baselines3.common.monitor import Monitor\n", + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.envs.asm_fns import get_r_devs" + ] + }, + { + "cell_type": "markdown", + "id": "4472d266-d374-49af-8044-4c1a9f5108e5", + "metadata": {}, + "source": [ + "## Helper functions\n", + "---\n", + "### Dynamics" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "5ad23ce3-a12c-4a26-b050-bd96d8682c7b", + "metadata": {}, + "outputs": [], + "source": [ + "def simulate_ep(env, agent, other_vars: Optional[List[Text]] = []): \n", + " simulation = {\n", + " 't': [],\n", + " 'surv_b_obs': [],\n", + " 'bare_surv_b_obs': [], \n", + " 'mean_wt_obs': [],\n", + " 'act': [],\n", + " 'rew': [],\n", + " 'total_biomass': [],\n", + " 'newborns': [],\n", + " 'non_random_newb': [],\n", + " **{var_name: [] for var_name in other_vars}\n", + " }\n", + " obs, _ = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, _ = agent.predict(obs)\n", + " new_obs, rew, term, trunc, info = env.step(act)\n", + " #\n", + " simulation['t'].append(t)\n", + " simulation['surv_b_obs'].append(\n", + " env.bound * (obs[0]+1)/2\n", + " )\n", + " simulation['bare_surv_b_obs'].append(\n", + " obs[0]\n", + " )\n", + " simulation['mean_wt_obs'].append(\n", + " (\n", + " env.parameters[\"min_wt\"]\n", + " + (env.parameters[\"max_wt\"] - env.parameters[\"min_wt\"])\n", + " * (obs[1]+1)/2\n", + " )\n", + " )\n", + " simulation['act'].append(act[0])\n", + " simulation['rew'].append(rew)\n", + " simulation['total_biomass'].append(np.sum(env.state))\n", + " simulation['newborns'].append(env.state[0])\n", + " simulation['non_random_newb'].append(\n", + " env.parameters[\"bha\"] * env.ssb / (1 + env.parameters[\"bhb\"] * env.ssb)\n", + " )\n", + " for var_name in other_vars:\n", + " simulation[var_name].append(getattr(env, var_name))\n", + " #\n", + " obs = new_obs\n", + " #\n", + " return simulation\n", + "\n", + "def expand_state(age_cls):\n", + " def wrapped(row):\n", + " return row.state[age_cls]\n", + " return wrapped\n", + "\n", + "def add_state_columns(df, env):\n", + " df_inner = df.copy()\n", + " for age_cls in range(len(env.state)):\n", + " df_inner[f'age_{age_cls:02d}_b'] = df_inner.apply(expand_state(age_cls), axis=1)\n", + " return df_inner\n", + "\n", + "def prepare_for_altair(df):\n", + " df = add_state_columns(df, env)\n", + " melted_df = df[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')\n", + " melted_df['population'] = melted_df['variable']\n", + " melted_df['biomass'] = melted_df['value']\n", + " return melted_df[['t', 'population', 'biomass']]" + ] + }, + { + "cell_type": "markdown", + "id": "692db175-77e9-492e-b762-ad9618262a99", + "metadata": {}, + "source": [ + "### Optimization\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "f3cda8d8-c3cb-4e13-9553-205b9f2a4647", + "metadata": {}, + "outputs": [], + "source": [ + "@ray.remote\n", + "def generate_rew(policy, env_cls, config):\n", + " ep_rew = 0\n", + " env = env_cls(config=config)\n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, info = policy.predict(obs)\n", + " obs, rew, term, trunc, info = env.step(act)\n", + " ep_rew += rew\n", + " return ep_rew\n", + "\n", + "\n", + "def rew_batch(policy, env_cls, config, batch_size):\n", + " tmax = env_cls().Tmax\n", + " parallel = [generate_rew.remote(policy, env_cls, config) for _ in range(batch_size)]\n", + " rews = ray.get(parallel)\n", + " \n", + " return rews\n", + "\n", + "def eval_pol(policy, env_cls, config, n_batches=4, batch_size=40, pb=False):\n", + " batch_iter = range(n_batches)\n", + " if pb:\n", + " from tqdm import tqdm\n", + " batch_iter = tqdm(iter)\n", + " #\n", + " rews = []\n", + " for i in batch_iter:\n", + " rews.append(\n", + " rew_batch(policy=policy, env_cls=env_cls, config=config, batch_size=batch_size)\n", + " )\n", + " return np.array(rews).flatten()\n", + "\n", + "msy_space = [Real(0.001, 0.25, name='mortality')]\n", + "log_esc_space = [Real(-6, -1, name='log_escapement')]\n", + "cr_space = [\n", + " Real(-5, 0, name='log_radius'),\n", + " Real(0., np.pi/4.00001, name='theta'),\n", + " Real(0, 1, name='y2'),\n", + "]\n", + "\n", + "@use_named_args(msy_space)\n", + "def msy_obj(**x):\n", + " eval_env = AsmEnv(config=CONFIG)\n", + " agent = Msy(env=eval_env, mortality = x['mortality'])\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=4, batch_size=40\n", + " )\n", + " return -np.mean(rews)\n", + "\n", + "@use_named_args(log_esc_space)\n", + "def esc_obj(**x):\n", + " eval_env = AsmEnv(config=CONFIG)\n", + " escapement = 10 ** x['log_escapement']\n", + " agent = ConstEsc(env=eval_env, escapement = escapement)\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=4, batch_size=40\n", + " )\n", + " return -np.mean(rews)\n", + "\n", + "@use_named_args(cr_space)\n", + "def cr_obj(**x):\n", + " theta = x[\"theta\"]\n", + " radius = 10 ** x[\"log_radius\"]\n", + " x1 = np.sin(theta) * radius\n", + " x2 = np.cos(theta) * radius\n", + " #\n", + " eval_env = AsmEnv(config=CONFIG)\n", + " eval_env.reset()\n", + " agent = CautionaryRule(env=eval_env, x1 = x1, x2 = x2, y2 = x[\"y2\"])\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, \n", + " config=CONFIG, \n", + " n_batches=4, batch_size=40\n", + " )\n", + " return -np.mean(rews) " + ] + }, + { + "cell_type": "markdown", + "id": "4110153c-0b94-4557-87f9-99fd2ca8b38e", + "metadata": {}, + "source": [ + "### Plot policy" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "30d5bb5d-e335-463e-bcec-816e5aee53b8", + "metadata": {}, + "outputs": [], + "source": [ + "def get_policy_df(policy_obj, minx=-1, maxx=1, nx=100):\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'pop': (obs_list + 1)/2,\n", + " 'pol': [policy_obj.predict(np.float32([obs]))[0][0] for obs in obs_list]\n", + " }\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "551c9097-df55-429d-9a0b-cb3f3d39e21b", + "metadata": {}, + "source": [ + "## Basic dynamics: total biomass vs biomass observation" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "d7a3b7ea-6f14-469b-bd7e-218b423ccd3e", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG1 = {\"noiseless\": True}\n", + "trivial_agent = Msy(env=AsmEnv(config=CONFIG1), mortality=0)\n", + "no_harvest_episode = pd.DataFrame(\n", + " simulate_ep(env=AsmEnv(config=CONFIG1), agent=trivial_agent)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "8601427e-9303-4915-be4a-b242a69460eb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "no_harvest_episode.plot(x='t', y=['total_biomass', 'surv_b_obs'])" + ] + }, + { + "cell_type": "markdown", + "id": "41957f88-4635-4582-8783-c72e38ad6f25", + "metadata": {}, + "source": [ + "In this plot we see that the biomass observation is considerably smaller than the total biomass of the system. \n", + "This is because the values of the vector `env.parameters['survey_vul']` (the relative frequencies at which different age-classes are caught by the survey) are all smaller than one:" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "1a8b271b-0bcc-47a2-b6f4-df27151fd183", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.02918574, 0.09509395, 0.17481713, 0.2555421 , 0.33069718,\n", + " 0.3973833 , 0.45477778, 0.5031675 , 0.54337645, 0.5764369 ,\n", + " 0.6034075 , 0.6252806 , 0.64294 , 0.657148 , 0.6685485 ,\n", + " 0.6776772 , 0.68497485, 0.6908012 , 0.6954482 , 0.69915164],\n", + " dtype=float32)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "AsmEnv().parameters['survey_vul']" + ] + }, + { + "cell_type": "markdown", + "id": "1cf4cd82-5f22-47c8-b567-50e5813db521", + "metadata": {}, + "source": [ + "### Let's add the stochastic 'spasms' back into the mix:" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "99ed3c1f-3fe9-4c04-8b3f-a510bcc82829", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "CONFIG2 = {\"noiseless\": False}\n", + "trivial_agent = Msy(env=AsmEnv(config=CONFIG2), mortality=0)\n", + "no_harvest_episode_noisy = pd.DataFrame(\n", + " simulate_ep(env=AsmEnv(config=CONFIG2), agent=trivial_agent)\n", + ")\n", + "no_harvest_episode_noisy.plot(x='t', y=['total_biomass', 'surv_b_obs'])" + ] + }, + { + "cell_type": "markdown", + "id": "da353522-3e54-47f3-9105-79b23edc48a1", + "metadata": {}, + "source": [ + "Similar pattern here: although the total biomass varies up to $\\sim 40$, the biomass observation never exceeds $\\sim 5$.\n", + "This means that survey observations are indicators for the total biomass but not estimates for it.\n", + "\n", + "Keeping in mind that the system's 'observation bound', `env.bound = 50`, this means that most of the action happens in a rather reduced portion of observation space. We can see this clearly when we look at 'bare observations' living in the space $[-1,+1]$: here the observations are all crammed in the subspace $[-1,-0.8]$." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "71b2643c-185d-413e-84da-a11a92c34d76", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "no_harvest_episode_noisy.plot(x='t', y=['bare_surv_b_obs'])" + ] + }, + { + "cell_type": "markdown", + "id": "10424b51-c00b-4c23-91e4-9daf13a77ee3", + "metadata": {}, + "source": [ + "### Implication for policy functions:" + ] + }, + { + "cell_type": "markdown", + "id": "a70ba801-b4e8-4581-a618-ed4a4145eb58", + "metadata": {}, + "source": [ + "When tuning / training policy functions \n", + "(either 'classic' policy functions tuned using Management Strategy Evaluation, or reinforcement learning\n", + "policies tuned using RL algorithms)\n", + "this means the following:\n", + "\n", + "Policies rarely use datapoints with suvey biomass observations greater than $-0.8$ to train. \n", + "That part of observation space, $[-0.8, +1]$ is simply one which is rarely visited at all.\n", + "This way, policy values in this region of observation space have little interpretability:\n", + "the policy function is tuned using time-series of episodes that mostly 'live' in $[-1, -0.8]$.\n", + "\n", + "Correspondingly, we get policy functions who's interesting portion is all concentrated on this\n", + "slice of observation space." + ] + }, + { + "cell_type": "markdown", + "id": "d76f102b-a0c5-453b-be45-aadb7411ec83", + "metadata": {}, + "source": [ + "### Examples\n", + "\n", + "For example, consider the optimal escapement strategy which is seemingly extreme, using an escapement biomass of $\\approx 0.01$. (Compare this tiny value to the typical biomass scale at which the unfished system fluctuates - in the order of 10-50 biomass units!)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "9fa339ed-b194-486a-8cf1-43b546855f85", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "get_policy_df(ConstEsc(env=AsmEnv(config=CONFIG2), escapement=0.01)).plot(x='pop', y='pol', title='Optimal escapement policy')" + ] + }, + { + "cell_type": "markdown", + "id": "afb7202b-52e8-4c34-8677-dfcfe5808f41", + "metadata": {}, + "source": [ + "Initially I was taken aback looking at this optimal policy: it seems like an extremist 'always fish as much as possible' policy - a boundary solution.\n", + "\n", + "This was contrasted by the optimal constant-effort strategy, with an MSY mortality of 5%. I was definitely scratching my head at that contrast." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e2a1ff56-39c5-4703-b2ef-850daff15721", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "9f766e75-f3ba-4fd5-a88a-4e31f9344d30", + "metadata": {}, + "source": [ + "## Noiseless dynamics" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b01fb69b-9ac7-4faa-a564-98f729540690", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index ccc3738..fcbed01 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "f15d4b8e-ef57-4bce-899b-89bb32d396f6", "metadata": { "scrolled": true @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", "metadata": {}, "outputs": [], @@ -56,46 +56,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 82, "id": "236788a7-ed25-46bd-a9b0-f7301e96cacf", "metadata": {}, "outputs": [], "source": [ - "CONFIG = {\"s\": 0.86, \"p_big\": 0.1}" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "e8df2b0b-bf26-46e3-9ddb-331870bc4719", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(2.2530262102712397, 2.703631452325488)" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "env = AsmEnv(config=CONFIG)\n", - "env.parameters['bhb'], env.parameters['bha']" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d94545dc-fe80-4a1d-8b16-77d3ad8f3493", - "metadata": {}, - "outputs": [], - "source": [ - "%%time\n", - "esc_gp = gp_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", - "esc_gp.fun, esc_gp.x" + "CONFIG = {\"s\": 0.86, \"noiseless\": False, \"testing_harvs\": False}" ] }, { @@ -108,14 +74,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 20, "id": "b59deb35-b67d-4232-bce4-ae9c8c2f0fcc", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5389c5ee0ffb45af9a7f40d41c71c9a6", + "model_id": "790aaca66e3641e88ff874c427254e0f", "version_major": 2, "version_minor": 0 }, @@ -147,7 +113,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 83, "id": "38838cb2-44df-404b-9cd8-4ecfc9347dd9", "metadata": {}, "outputs": [], @@ -195,16 +161,16 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 84, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], "source": [ "msy_space = [Real(0.001, 0.25, name='mortality')]\n", - "esc_space = [Real(0.001, 0.80, name='escapement')]\n", + "log_esc_space = [Real(-6, -1, name='log_escapement')]\n", "cr_space = [\n", - " Real(0.00001, 1, name='radius'),\n", - " Real(0.00001, np.pi/4.00001, name='theta'),\n", + " Real(-5, 0, name='log_radius'),\n", + " Real(0., np.pi/4.00001, name='theta'),\n", " Real(0, 1, name='y2'),\n", "]\n", "\n", @@ -219,10 +185,11 @@ " )\n", " return -np.mean(rews)\n", "\n", - "@use_named_args(esc_space)\n", + "@use_named_args(log_esc_space)\n", "def esc_obj(**x):\n", " eval_env = AsmEnv(config=CONFIG)\n", - " agent = ConstEsc(env=eval_env, escapement = x['escapement'])\n", + " escapement = 10 ** x['log_escapement']\n", + " agent = ConstEsc(env=eval_env, escapement = escapement)\n", " rews = eval_pol(\n", " policy=agent, \n", " env_cls=AsmEnv, config=CONFIG, \n", @@ -233,7 +200,7 @@ "@use_named_args(cr_space)\n", "def cr_obj(**x):\n", " theta = x[\"theta\"]\n", - " radius = x[\"radius\"]\n", + " radius = 10 ** x[\"log_radius\"]\n", " x1 = np.sin(theta) * radius\n", " x2 = np.cos(theta) * radius\n", " #\n", @@ -271,10 +238,6 @@ "execution_count": 85, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -284,262 +247,262 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.9026\n", - "Function value obtained: -10.5153\n", - "Current minimum: -10.5153\n", + "Time taken: 0.9297\n", + "Function value obtained: -34.4195\n", + "Current minimum: -34.4195\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8077\n", - "Function value obtained: -420.3512\n", - "Current minimum: -420.3512\n", + "Time taken: 0.8327\n", + "Function value obtained: -3.9477\n", + "Current minimum: -34.4195\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.7918\n", - "Function value obtained: -16.8727\n", - "Current minimum: -420.3512\n", + "Time taken: 0.8055\n", + "Function value obtained: -45.2543\n", + "Current minimum: -45.2543\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8600\n", - "Function value obtained: -419.8449\n", - "Current minimum: -420.3512\n", + "Time taken: 0.7800\n", + "Function value obtained: -6.9639\n", + "Current minimum: -45.2543\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.9068\n", - "Function value obtained: -22.9095\n", - "Current minimum: -420.3512\n", + "Time taken: 0.7849\n", + "Function value obtained: -46.6104\n", + "Current minimum: -46.6104\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.7952\n", - "Function value obtained: -238.6421\n", - "Current minimum: -420.3512\n", + "Time taken: 0.7970\n", + "Function value obtained: -8.3589\n", + "Current minimum: -46.6104\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8001\n", - "Function value obtained: -116.9043\n", - "Current minimum: -420.3512\n", + "Time taken: 0.7963\n", + "Function value obtained: -35.0244\n", + "Current minimum: -46.6104\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8405\n", - "Function value obtained: -31.0751\n", - "Current minimum: -420.3512\n", + "Time taken: 0.8935\n", + "Function value obtained: -6.8083\n", + "Current minimum: -46.6104\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.7906\n", - "Function value obtained: -57.5424\n", - "Current minimum: -420.3512\n", + "Time taken: 0.8012\n", + "Function value obtained: -6.0992\n", + "Current minimum: -46.6104\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 5.4712\n", - "Function value obtained: -204.3319\n", - "Current minimum: -420.3512\n", + "Time taken: 1.0304\n", + "Function value obtained: -6.3427\n", + "Current minimum: -46.6104\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2698\n", - "Function value obtained: -420.2488\n", - "Current minimum: -420.3512\n", + "Time taken: 1.0080\n", + "Function value obtained: -45.6181\n", + "Current minimum: -46.6104\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3171\n", - "Function value obtained: -412.5722\n", - "Current minimum: -420.3512\n", + "Time taken: 1.0777\n", + "Function value obtained: -46.3725\n", + "Current minimum: -46.6104\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2952\n", - "Function value obtained: -426.1817\n", - "Current minimum: -426.1817\n", + "Time taken: 1.0550\n", + "Function value obtained: -47.2633\n", + "Current minimum: -47.2633\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3829\n", - "Function value obtained: -21.7216\n", - "Current minimum: -426.1817\n", + "Time taken: 1.0385\n", + "Function value obtained: -44.1828\n", + "Current minimum: -47.2633\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3202\n", - "Function value obtained: -420.7467\n", - "Current minimum: -426.1817\n", + "Time taken: 1.0444\n", + "Function value obtained: -46.5199\n", + "Current minimum: -47.2633\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3807\n", - "Function value obtained: -423.5646\n", - "Current minimum: -426.1817\n", + "Time taken: 1.0745\n", + "Function value obtained: -48.1007\n", + "Current minimum: -48.1007\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3794\n", - "Function value obtained: -423.5132\n", - "Current minimum: -426.1817\n", + "Time taken: 1.1061\n", + "Function value obtained: -48.2133\n", + "Current minimum: -48.2133\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0279\n", - "Function value obtained: -404.1033\n", - "Current minimum: -426.1817\n", + "Time taken: 1.0789\n", + "Function value obtained: -47.0517\n", + "Current minimum: -48.2133\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4973\n", - "Function value obtained: -423.7958\n", - "Current minimum: -426.1817\n", + "Time taken: 1.1093\n", + "Function value obtained: -47.2809\n", + "Current minimum: -48.2133\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0718\n", - "Function value obtained: -429.7038\n", - "Current minimum: -429.7038\n", + "Time taken: 1.0385\n", + "Function value obtained: -46.6564\n", + "Current minimum: -48.2133\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0845\n", - "Function value obtained: -416.9777\n", - "Current minimum: -429.7038\n", + "Time taken: 0.9958\n", + "Function value obtained: -45.2278\n", + "Current minimum: -48.2133\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0639\n", - "Function value obtained: -418.7107\n", - "Current minimum: -429.7038\n", + "Time taken: 1.0789\n", + "Function value obtained: -45.3176\n", + "Current minimum: -48.2133\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0806\n", - "Function value obtained: -423.0774\n", - "Current minimum: -429.7038\n", + "Time taken: 1.0752\n", + "Function value obtained: -45.4752\n", + "Current minimum: -48.2133\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0506\n", - "Function value obtained: -411.4311\n", - "Current minimum: -429.7038\n", + "Time taken: 0.9604\n", + "Function value obtained: -44.8737\n", + "Current minimum: -48.2133\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1297\n", - "Function value obtained: -430.1984\n", - "Current minimum: -430.1984\n", + "Time taken: 1.0631\n", + "Function value obtained: -46.7914\n", + "Current minimum: -48.2133\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1152\n", - "Function value obtained: -426.8712\n", - "Current minimum: -430.1984\n", + "Time taken: 1.0564\n", + "Function value obtained: -46.7580\n", + "Current minimum: -48.2133\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0828\n", - "Function value obtained: -422.6701\n", - "Current minimum: -430.1984\n", + "Time taken: 1.1281\n", + "Function value obtained: -46.9997\n", + "Current minimum: -48.2133\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0951\n", - "Function value obtained: -434.4590\n", - "Current minimum: -434.4590\n", + "Time taken: 1.0858\n", + "Function value obtained: -44.5727\n", + "Current minimum: -48.2133\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9898\n", - "Function value obtained: -380.1998\n", - "Current minimum: -434.4590\n", + "Time taken: 0.9800\n", + "Function value obtained: -47.5164\n", + "Current minimum: -48.2133\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0739\n", - "Function value obtained: -418.1824\n", - "Current minimum: -434.4590\n", + "Time taken: 1.1264\n", + "Function value obtained: -47.8769\n", + "Current minimum: -48.2133\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1644\n", - "Function value obtained: -417.3401\n", - "Current minimum: -434.4590\n", + "Time taken: 1.0978\n", + "Function value obtained: -44.8638\n", + "Current minimum: -48.2133\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3077\n", - "Function value obtained: -408.3845\n", - "Current minimum: -434.4590\n", + "Time taken: 1.0241\n", + "Function value obtained: -48.4403\n", + "Current minimum: -48.4403\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1248\n", - "Function value obtained: -425.7940\n", - "Current minimum: -434.4590\n", + "Time taken: 1.0426\n", + "Function value obtained: -45.9114\n", + "Current minimum: -48.4403\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1439\n", - "Function value obtained: -435.2489\n", - "Current minimum: -435.2489\n", + "Time taken: 1.0396\n", + "Function value obtained: -45.3013\n", + "Current minimum: -48.4403\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1030\n", - "Function value obtained: -425.5306\n", - "Current minimum: -435.2489\n", + "Time taken: 1.0787\n", + "Function value obtained: -45.7534\n", + "Current minimum: -48.4403\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1023\n", - "Function value obtained: -412.2225\n", - "Current minimum: -435.2489\n", + "Time taken: 1.3994\n", + "Function value obtained: -48.3400\n", + "Current minimum: -48.4403\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0874\n", - "Function value obtained: -419.7807\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1389\n", + "Function value obtained: -45.6515\n", + "Current minimum: -48.4403\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1151\n", - "Function value obtained: -424.9055\n", - "Current minimum: -435.2489\n", + "Time taken: 1.0842\n", + "Function value obtained: -46.8415\n", + "Current minimum: -48.4403\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1586\n", - "Function value obtained: -424.1673\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1503\n", + "Function value obtained: -47.1488\n", + "Current minimum: -48.4403\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1460\n", - "Function value obtained: -8.2247\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1281\n", + "Function value obtained: -48.6317\n", + "Current minimum: -48.6317\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2315\n", - "Function value obtained: -415.1648\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1454\n", + "Function value obtained: -45.3279\n", + "Current minimum: -48.6317\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1781\n", - "Function value obtained: -405.1189\n", - "Current minimum: -435.2489\n", + "Time taken: 1.0289\n", + "Function value obtained: -49.5151\n", + "Current minimum: -49.5151\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2721\n", - "Function value obtained: -418.6292\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1277\n", + "Function value obtained: -45.9657\n", + "Current minimum: -49.5151\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2206\n", - "Function value obtained: -424.6042\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1321\n", + "Function value obtained: -48.8441\n", + "Current minimum: -49.5151\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2746\n", - "Function value obtained: -432.5434\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1791\n", + "Function value obtained: -45.1809\n", + "Current minimum: -49.5151\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1960\n", - "Function value obtained: -430.1637\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1060\n", + "Function value obtained: -47.6197\n", + "Current minimum: -49.5151\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1901\n", - "Function value obtained: -431.3944\n", - "Current minimum: -435.2489\n", + "Time taken: 1.0466\n", + "Function value obtained: -45.1608\n", + "Current minimum: -49.5151\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2000\n", - "Function value obtained: -426.7682\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1008\n", + "Function value obtained: -45.8224\n", + "Current minimum: -49.5151\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0900\n", - "Function value obtained: -424.9954\n", - "Current minimum: -435.2489\n", + "Time taken: 1.1540\n", + "Function value obtained: -46.0425\n", + "Current minimum: -49.5151\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2593\n", - "Function value obtained: -428.2801\n", - "Current minimum: -435.2489\n", - "CPU times: user 1min 47s, sys: 11min 4s, total: 12min 51s\n", - "Wall time: 1min 8s\n" + "Time taken: 1.2157\n", + "Function value obtained: -45.1788\n", + "Current minimum: -49.5151\n", + "CPU times: user 1min 32s, sys: 9min 11s, total: 10min 43s\n", + "Wall time: 52.1 s\n" ] }, { "data": { "text/plain": [ - "(-435.2489318270209, [0.06034835458305745])" + "(-49.515058565010186, [0.0560298054012827])" ] }, "execution_count": 85, @@ -558,10 +521,6 @@ "execution_count": 86, "id": "6563ba01-9664-4dbc-9594-c4439d22023a", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -577,7 +536,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -595,10 +554,6 @@ "execution_count": 87, "id": "a10c7628-c47a-4622-8f45-440bcca00901", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -614,7 +569,7 @@ }, { "data": { - "image/png": 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", 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" ] @@ -632,10 +587,6 @@ "execution_count": 88, "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -645,262 +596,262 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8035\n", - "Function value obtained: -221.2843\n", - "Current minimum: -221.2843\n", + "Time taken: 0.8201\n", + "Function value obtained: -20.8203\n", + "Current minimum: -20.8203\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8925\n", - "Function value obtained: -10.2133\n", - "Current minimum: -221.2843\n", + "Time taken: 0.8470\n", + "Function value obtained: -45.4203\n", + "Current minimum: -45.4203\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.8206\n", - "Function value obtained: -415.1535\n", - "Current minimum: -415.1535\n", + "Time taken: 0.7855\n", + "Function value obtained: -5.5793\n", + "Current minimum: -45.4203\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.7985\n", - "Function value obtained: -8.6206\n", - "Current minimum: -415.1535\n", + "Time taken: 0.8221\n", + "Function value obtained: -11.1915\n", + "Current minimum: -45.4203\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.7964\n", - "Function value obtained: -8.1362\n", - "Current minimum: -415.1535\n", + "Time taken: 0.7927\n", + "Function value obtained: -44.1016\n", + "Current minimum: -45.4203\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.7841\n", - "Function value obtained: -9.7457\n", - "Current minimum: -415.1535\n", + "Time taken: 0.8089\n", + "Function value obtained: -14.6585\n", + "Current minimum: -45.4203\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8345\n", - "Function value obtained: -163.5276\n", - "Current minimum: -415.1535\n", + "Time taken: 0.7807\n", + "Function value obtained: -21.0878\n", + "Current minimum: -45.4203\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.7647\n", - "Function value obtained: -255.7494\n", - "Current minimum: -415.1535\n", + "Time taken: 0.8078\n", + "Function value obtained: -4.1043\n", + "Current minimum: -45.4203\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.7774\n", - "Function value obtained: -368.6215\n", - "Current minimum: -415.1535\n", + "Time taken: 0.8377\n", + "Function value obtained: -32.1021\n", + "Current minimum: -45.4203\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.0549\n", - "Function value obtained: -14.2423\n", - "Current minimum: -415.1535\n", + "Time taken: 1.0039\n", + "Function value obtained: -28.6322\n", + "Current minimum: -45.4203\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9360\n", - "Function value obtained: -424.3514\n", - "Current minimum: -424.3514\n", + "Time taken: 1.1528\n", + "Function value obtained: -47.0562\n", + "Current minimum: -47.0562\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9955\n", - "Function value obtained: -423.4653\n", - "Current minimum: -424.3514\n", + "Time taken: 1.0595\n", + "Function value obtained: -47.7504\n", + "Current minimum: -47.7504\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0607\n", - "Function value obtained: -416.7628\n", - "Current minimum: -424.3514\n", + "Time taken: 1.0471\n", + "Function value obtained: -43.8821\n", + "Current minimum: -47.7504\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0108\n", - "Function value obtained: -422.3483\n", - "Current minimum: -424.3514\n", + "Time taken: 1.0353\n", + "Function value obtained: -47.3315\n", + "Current minimum: -47.7504\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9800\n", - "Function value obtained: -419.6802\n", - "Current minimum: -424.3514\n", + "Time taken: 1.1125\n", + "Function value obtained: -48.6935\n", + "Current minimum: -48.6935\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0304\n", - "Function value obtained: -424.7456\n", - "Current minimum: -424.7456\n", + "Time taken: 0.9939\n", + "Function value obtained: -48.6872\n", + "Current minimum: -48.6935\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1265\n", - "Function value obtained: -421.1680\n", - "Current minimum: -424.7456\n", + "Time taken: 1.0482\n", + "Function value obtained: -44.4783\n", + "Current minimum: -48.6935\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9452\n", - "Function value obtained: -435.0719\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0298\n", + "Function value obtained: -47.5510\n", + "Current minimum: -48.6935\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3339\n", - "Function value obtained: -417.6995\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0493\n", + "Function value obtained: -45.9067\n", + "Current minimum: -48.6935\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9722\n", - "Function value obtained: -423.1987\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0278\n", + "Function value obtained: -47.6435\n", + "Current minimum: -48.6935\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0860\n", - "Function value obtained: -421.4179\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0599\n", + "Function value obtained: -46.3318\n", + "Current minimum: -48.6935\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0215\n", - "Function value obtained: -412.4332\n", - "Current minimum: -435.0719\n", + "Time taken: 1.3514\n", + "Function value obtained: -49.5974\n", + "Current minimum: -49.5974\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0904\n", - "Function value obtained: -423.9834\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0790\n", + "Function value obtained: -47.4932\n", + "Current minimum: -49.5974\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0610\n", - "Function value obtained: -415.0636\n", - "Current minimum: -435.0719\n", + "Time taken: 1.1718\n", + "Function value obtained: -46.7006\n", + "Current minimum: -49.5974\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0096\n", - "Function value obtained: -416.8264\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0293\n", + "Function value obtained: -47.8838\n", + "Current minimum: -49.5974\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9887\n", - "Function value obtained: -409.5035\n", - "Current minimum: -435.0719\n", + "Time taken: 0.9834\n", + "Function value obtained: -46.3363\n", + "Current minimum: -49.5974\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0241\n", - "Function value obtained: -265.4770\n", - "Current minimum: -435.0719\n", + "Time taken: 1.1368\n", + "Function value obtained: -46.4499\n", + "Current minimum: -49.5974\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0953\n", - "Function value obtained: -197.1016\n", - "Current minimum: -435.0719\n", + "Time taken: 1.1134\n", + "Function value obtained: -40.1026\n", + "Current minimum: -49.5974\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0468\n", - "Function value obtained: -384.7105\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0998\n", + "Function value obtained: -28.8108\n", + "Current minimum: -49.5974\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9983\n", - "Function value obtained: -426.8065\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0352\n", + "Function value obtained: -24.5495\n", + "Current minimum: -49.5974\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1073\n", - "Function value obtained: -418.9250\n", - "Current minimum: -435.0719\n", + "Time taken: 1.2080\n", + "Function value obtained: -48.5815\n", + "Current minimum: -49.5974\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0422\n", - "Function value obtained: -425.7556\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0966\n", + "Function value obtained: -47.7910\n", + "Current minimum: -49.5974\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0887\n", - "Function value obtained: -71.5326\n", - "Current minimum: -435.0719\n", + "Time taken: 0.9493\n", + "Function value obtained: -46.6133\n", + "Current minimum: -49.5974\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0324\n", - "Function value obtained: -61.4797\n", - "Current minimum: -435.0719\n", + "Time taken: 1.1299\n", + "Function value obtained: -45.7727\n", + "Current minimum: -49.5974\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0843\n", - "Function value obtained: -407.8623\n", - "Current minimum: -435.0719\n", + "Time taken: 1.1286\n", + "Function value obtained: -13.5939\n", + "Current minimum: -49.5974\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0719\n", - "Function value obtained: -424.6370\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0683\n", + "Function value obtained: -47.3934\n", + "Current minimum: -49.5974\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0527\n", - "Function value obtained: -420.0040\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0373\n", + "Function value obtained: -46.9083\n", + "Current minimum: -49.5974\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0574\n", - "Function value obtained: -422.4029\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0734\n", + "Function value obtained: -47.3283\n", + "Current minimum: -49.5974\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1347\n", - "Function value obtained: -413.4915\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0384\n", + "Function value obtained: -46.2170\n", + "Current minimum: -49.5974\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2443\n", - "Function value obtained: -409.1322\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0122\n", + "Function value obtained: -47.3127\n", + "Current minimum: -49.5974\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0059\n", - "Function value obtained: -416.9569\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0147\n", + "Function value obtained: -45.8262\n", + "Current minimum: -49.5974\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9965\n", - "Function value obtained: -422.5781\n", - "Current minimum: -435.0719\n", + "Time taken: 1.1555\n", + "Function value obtained: -44.7477\n", + "Current minimum: -49.5974\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0657\n", - "Function value obtained: -418.6904\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0391\n", + "Function value obtained: -48.3279\n", + "Current minimum: -49.5974\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0396\n", - "Function value obtained: -52.1393\n", - "Current minimum: -435.0719\n", + "Time taken: 1.2610\n", + "Function value obtained: -45.3069\n", + "Current minimum: -49.5974\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1144\n", - "Function value obtained: -416.3284\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0652\n", + "Function value obtained: -45.7178\n", + "Current minimum: -49.5974\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1051\n", - "Function value obtained: -415.8117\n", - "Current minimum: -435.0719\n", + "Time taken: 1.3785\n", + "Function value obtained: -46.6172\n", + "Current minimum: -49.5974\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0517\n", - "Function value obtained: -419.7361\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0412\n", + "Function value obtained: -48.5573\n", + "Current minimum: -49.5974\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0421\n", - "Function value obtained: -415.4998\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0659\n", + "Function value obtained: -46.4082\n", + "Current minimum: -49.5974\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0357\n", - "Function value obtained: -426.0757\n", - "Current minimum: -435.0719\n", + "Time taken: 1.0267\n", + "Function value obtained: -43.5981\n", + "Current minimum: -49.5974\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0421\n", - "Function value obtained: -426.8498\n", - "Current minimum: -435.0719\n", - "CPU times: user 18.3 s, sys: 4.25 s, total: 22.5 s\n", - "Wall time: 50.6 s\n" + "Time taken: 1.0281\n", + "Function value obtained: -46.9634\n", + "Current minimum: -49.5974\n", + "CPU times: user 18.2 s, sys: 4.16 s, total: 22.4 s\n", + "Wall time: 51.8 s\n" ] }, { "data": { "text/plain": [ - "(-435.07193758413604, [0.0473505166744664])" + "(-49.59740600044421, [0.05475473233147571])" ] }, "execution_count": 88, @@ -919,10 +870,6 @@ "execution_count": 89, "id": "73d6974e-8d14-419d-a43d-ef0cd09659f8", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -938,7 +885,7 @@ }, { "data": { - "image/png": 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8bWZsCGNDOjeqq1RVVSE2NhYpKSkoLS2FRCKRe37//n1WcpU27gdlVXC276asGMXw8AB++EGaUiCg422lWbt2LU6cOIHr16+Dy+Xi6dOnTfLk5+djzpw5OHv2LMzNzTF9+nSsW7cORkbP/t3PnTuHjz/+GFlZWXB3d8eKFSsQERGhUBnef/99nD9/HtOmTYOzs7PKnG4o/Vbkl1fjZVWURBG6dQPefVdT2jo8z9a46XibLXV1dZgyZQoCAwOxe/fuJs/FYjHGjx8PJycnXLp0CcXFxXjvvfdgbGyM//znPwCA3NxcjB8/HrNnz0Z8fDxSUlLw/vvvw9nZGaEKeOv99ddfceLECbzyyiuqrRxhiUAgIABI3C/X2IpoP6WlhGzbJk0p5NTNYsKLPk4mfX1R20VRK7J3TSAQqE3H3r17iZWVVZP7J0+eJAYGBoTP5zP3vvnmG2JpaUlEIhEhhJAlS5YQPz8/ue+99dZbJDQ0VCHdHh4e5NatW+wL3wIKD9REIhGEQqHcBwAelGkwGkRBATBvnjSldLo17hffP5EGAkKmpaXB398fjo6OzL3Q0FAIhUJkZWUxeUJCQuS+FxoairS0NIV0rFmzBitXrkR1tWptSeFu+bp167B69eom9x+U0TVnbdHZ1rjd3d3lrmNiYrBq1Sq16uTz+XKGDYC55vP5reYRCoWoqalp89jmxo0bkZOTA0dHR3h4eMDYWP7H+tq1a6zKrvBbsWzZMnz88cfMtSwgen45jeOkLTrbmLugoEAuFnxL68BLly5t8zRVdnZ2s4c1tMGkSZPUIldh4zYxMWn2H/NJdT0ENfWw6iQvWEdC2MkcNVhaWsoZd0tERUW1OVPt5eWlkE4nJydcuXJF7l5JSQnzTJbK7j2fx9LSUiFnCzExMQqVpb2o5K3Ie1yF/u7WqhDVOhYWwJgx0pTCeGHpLGNuRbG3t4e9vb1KZAUGBmLt2rUoLS2Fg4MDACApKQmWlpbo06cPk+fkyZNy30tKSkJgYKDCep4+fYpDhw4hJycHixcvRrdu3XDt2jU4OjrC1dWVVdlVYty5mjJub2/gt9/Ur0dHeOY/rXO03OogPz8f5eXlyM/Ph1gsxvXr1wEAPXv2hLm5OcaMGYM+ffpg2rRpiIuLA5/Px4oVKzB37lymJzt79mxs27YNS5Yswb/+9S+cOXMGCQkJOHHihEJlyMzMREhICKysrJCXl4eZM2eiW7duSExMRH5+Pvbv38+ucmyn2WXLE+4LEsiXp++ocga/ZRoaCBEIpCmFTP02jfCij5Mj6Q+1XRS1os6lsOnTpxMATT5nz55l8uTl5ZGxY8cSMzMzYmdnR6Kiokh9fb2cnLNnz5IBAwYQLpdLvLy8yN69exUuw+jRo8nixYsJIYSYm5uTnJwcQgghqamphMfjsa6barrlmpoxz8gABg8Grl6VOm7o5Mha7s4y5lYH+/btw759+1rNw+PxmnS7X2TkyJFIT09nVYY///wTO3fubHLf1dWVmZFng0o2JOc9psth2oCOufUDExMTZt/I8/z9999KzR2oxLjvP64Coe6PNI4s2gj1wqLbTJgwAZ999hnq66U/1hwOB/n5+YiOjsYbb7zBWq5KjLuitgHlVXWqEEVREELIs5ab+k/TaTZu3IjKyko4ODigpqYGI0aMQM+ePWFhYYG1a9eylqv0W+FsZYqSWum429ZcucPlFMWprZegXiztLdGWW7exsrJCUlISLl68iMzMTFRWVmLQoEFNtrS2F6WNm2fbBSWFtch9XI3BPDUf/fT3B0pLAWtr9erRAWQbWAw4QFeuoZZLQ1EFw4YNw7Bhw1QmT2nj7t6tC64U1iL3caUqytM6xsaAijYn6DrPBwBU1flfiub46quvFM770UcfsdKhkpYbKEfeYw3sMc/JARYuBDZtAnr0UL++Doyghvor12U2bdokd/3o0SNUV1fDurFX+vTpU3Tp0gUODg6sjVvpCTWebVcA0l1qakcgAI4dk6adHKblNqHjbV0kNzeX+axduxYDBgxAdnY2ysvLUV5ejuzsbAwaNAhr1qxhrUNp4+5u2wWAdEKNLodpDiGNNKI3fPrpp9i6dSt8nvPF7+Pjg02bNmHFihWs5Spt3G7WXWDAAarrxCitUP/heYqUChppRG8oLi5GQ0NDk/tisbjJabP2oLRxc40M4GYjbb010jWnAHj+0Ag1bl1n9OjRmDVrlpxThqtXr2LOnDlKLYepZBOLp5103K32baiursDGjdK0k1PRyc5y6zN79uyBk5MThgwZwvhNGDp0KBwdHfHdd9+xlquSN8PTrivO//0Iueo+QOLoCDznDaYzI2R2p9GWW9ext7fHyZMn8ffff+P27dsAAF9fX/Tq1UspuSoxbo/GSbXcR2o27idPgORkICQEsLFRr64OzjPniLTl1hd69eqltEE/j2qMu7FbnvNIzRtZcnOBN9+UHvns5MYtc45Ix9y6j1gsxr59+1qMOHLmzBlWclVi3P6uVjDgADmPqpD3uIoxdor6qKBLYXrD/PnzsW/fPowfPx59+/btOBFHAMDW3ARBPexw8d5jnLhRjLmjeqpCLKUVhHQpTG84cOAAEhISMG7cOJXKVVn0uH/0cwYAHMsoUpVISit0toAE+gyXy0XPnqpvEFVm3GF9nWBkwMFtfgXulapp7G1mBgwcKE07OZ0tIIE+ExUVhS1btqh8h6fK3gzrLlwM87bDuTuPcDyzCAtCVDfrx9C7N8Ay+oI+0SCWoKpODIAuhekDFy9exNmzZ/Hrr7/Cz8+vScSRxMREVnJV+rP/j34ujcZdjPmjvelRRDVRKXq2VZG23LqPtbU1Jk+erHK5Kn0zxvg5gptogHullbhTUgFfp7ajQ7SL9HTg5ZeBy5el3fNOimy8bWZsCGNDlY2sKFpi7969apGr0jfD0tQYw3tJnSkczyhWpWgphAB1ddK0EyOg4229o6GhAcnJydi5cycqKioAAEVFRaisZD9/pfKf/df7S2fNj2cW0SOgaqKzBQDUdx48eAB/f39MnDgRc+fOxaNHjwAA69evx6JFi1jLVblxj+7tCBMjA+SVVSOrqKkvZorydLYAgOoiLy8PkZGR8PT0hJmZGXr06IGYmBjU1cl78s3MzERwcDBMTU3h7u6OuLi4JrIOHjwIX19fmJqawt/fv80gBs8zf/58DBkyBE+ePJELHDh58mSkpKSwrp/KjdvcxAiv+koDph3LpGve6oCucauG27dvQyKRYOfOncjKysKmTZuwY8cOLF++nMkjFAoxZswY8Hg8XL16FV988QVWrVqFXbt2MXkuXbqEd955B5GRkUhPT8ekSZMwadIk3Lx5U6FyXLhwAStWrACXy5W77+HhgcLCQvYVZBuHqLX4Tccziggv+jgZvfEcW/HNU11NyM2b0rQTs/vCfcKLPk7mxl/VdlE0gjpjhb1IXFwc8fT0ZK63b99ObGxsiEgkYu5FR0cTHx8f5vrNN98k48ePl5MTEBBAZs2apZBOa2trkpWVRQiRjxV24cIF4uDgwLouCrfcIpEIQqFQ7tMSg3jWAKTOG+oaJC3mazdmZoCfX6ffxNJZx9wvvn8ikeo9/wgEAnTr9sxFd1paGoYPHy7XqoaGhuLOnTt48uQJk+dFpwqhoaFIS0tTSOeYMWOwefNm5prD4aCyshIxMTFKbUlV2LjXrVsHKysr5uPu7t5iXidLU3TlGkIsIcgvV+Ex0AcPgPffl6admM465nZ3d5d7B9etW6dS+ffu3cPWrVsxa9Ys5h6fz4ejo6NcPtm1LEhfS3kUDeK3ceNGpKamok+fPqitrcXUqVOZLvn69etZ10dh4162bBkEAgHzKSgoaDEvh8NBDwdzAMC9UhUad1kZsHu3NO3EdNYAgAUFBXLv4LJly5rNt3TpUnA4nFY/MqcIMgoLCxEWFoYpU6Zg5syZmqgOg5ubGzIyMrB8+XIsXLgQAwcORGxsLNLT0+Hg4MBarsI//TL3L4rSw94cmQ8F6j/j3Ql55j+tc7XclpaWsLRse2NUVFQUIiIiWs3j5eXF/F1UVIRRo0YhKChIbqIMAJycnJo4KZRdOzk5tZpH9lwRjIyM8O677yqcXyGZKpX2HD3sNeTAoQPwqEKE/6U/VO38Qivc5kvnOzrbmFtR7O3tFQ59W1hYiFGjRmHw4MHYu3cvDAzkO7OBgYH45JNPUF9fz+z5TkpKgo+PD2waHYYEBgYiJSUFCxYsYL6XlJSEwMBAhct8584dbN26FdnZ2QCA3r17Y968efD19VVYxouo0bil3fIcdbte6gBs+O0Ofv6r5WGKurDtSgMvKkNhYSFGjhwJHo+HDRs2MJtHgGet8tSpU7F69WpERkYiOjoaN2/exJYtW+QihsyfPx8jRozAxo0bMX78eBw4cAB//fVXk15ASxw+fBhvv/02hgwZwvwgXL58Gf7+/jhw4ADrML7qM+7GMff90koQQlRziMTREVi6VJp2IFJzHgMAxvRxhK05t43cqsHJ0gwve6k58KKek5SUhHv37uHevXtwc3OTe0Yad1daWVnh9OnTmDt3LgYPHgw7OzusXLkS//73v5m8QUFB+PHHH7FixQosX74c3t7eOHLkCPr27atQOZYsWYJly5bhs88+k7sfExODJUuWsDZuDiHs9ogKhUJYWVlBIBA0Ow4SNYjR+9NTkBDgyvLRcLA0ZVXAjk7R0xoExZ6BoQEHmTFj0NWkc42DNUFb75qu06VLF2RmZjZx2HD37l30798f1dXs4vCp7UiRiZEhuneTekVVmfOGigrg3Dlp2kH4M68cANDXxZIaNoUVI0eOxIULF5rcv3jxIoKDg1nLVevb2MPeHHll1ch5VImgnnbKC7x7Fxg1Sur9dNAg5eWpgD9ypcb9kgftIlPYMWHCBERHR+Pq1at4+eWXAUjH3AcPHsTq1avxyy+/yOVVFPUat4M5Um6X6vWk2p8y4/akxk1hxwcffAAA2L59O7Zv397sM0C6f0QsFissV80tt34vh5VX1eFu45CDttwUtrzop1xVqNWNR8/GGfMcdTlM1DKy8ba3gzm6ddXMLDlFv6mtrVWZLLUat5ed1LiLBLWoEjUNUdpujI2lQQCNO8bmDVmXfCjtklOUQCwWY82aNXB1dYW5uTnu378PQBq3e/fu3azlqtW4bbpyYdvYoqkkvK+/P/DwoTTtAFzJo8ZNUZ61a9di3759iIuLkzt91rdvX6WifKrdu96znWr61TWvFDUwnmboeJuiDPv378euXbsQHh4OQ0ND5n7//v2bHHBpD+o3bofGSTVVjLtv3ADc3KSplrn24AnEEgI3GzO4WHfu8+UU5SgsLGw24ohEIkF9fT1ruRpsuVXQLa+vBwoLpamWkU2mDaWtNkVJ+vTp0+wmlkOHDmGgEi681b6lSl+75Vfo+jZFRaxcuRLTp09HYWEhJBIJEhMTcefOHezfvx/Hjx9nLVdjLff9x1UQS/TD1bGoQYz0gqcA6GQaRXkmTpyIY8eOITk5GV27dsXKlSuRnZ2NY8eO4bXXXmMtV+0tt6uNGbhGBqhrkKDwSQ2623ZRt0q1c+OhAHUNEtiZc+FFY5FTVEBwcDCSkpJUKlPtxm1owIGXXVfc5lcg51Glcsbt7Q2cPStNNUjqvcdYmpiJmjrpTiJRvXQL4BBeNxoPjdJh0cgxph4O5oxxj/Jl7xMKFhbAyJEqK5ei/C+9EAXlNU3uh/VV3I0OhfI8NjY2CjcM5eXlrHRoxrjtZc4SlZxUKywEtm0D5s2T7lTTEA+fSM/TLh3ri5E+Uvc9XblGcO+m+0MMinZ43pVxWVkZPv/8c4SGhjKeWNLS0vDbb7/h008/Za1DQ8atogMkJSVAbCwwZYpGjbvwqbTVHsyzUX3kUkqnZPr06czfb7zxBj777DPMmzePuffRRx9h27ZtSE5OxsKFC1np0Ej8V5nThsInTbu2HR2xhKD4qXQzv5sN3axCUT2//fYbwsLCmtwPCwtDcnIya7kaMW4nK6mLpdIKESQ6thxWIqxFg4TAyIADBwv9dBVF0S62trY4evRok/tHjx6Fra0ta7ka6ZbbmZuAwwEaJATl1XWwM9cdr50PG3sbLtZmMDSgM+MU1bN69Wq8//77OHfuHAICAgAAf/zxB06dOoVvv/2WtVyNtNzGhgaMG94SoRLnVW1tgchIaaohCp9KJ9Nc6f5xipqIiIhAamoqLC0tkZiYiMTERFhaWuLixYttBldoDY159HO0NMHjShFKhSL4ubAUwuMBShyBY8PDxiUwOt6mqJOAgADEx8erVKZGWm4AcGx0baxUy11TA2RlSVMNIZspd6XGTdExNGjcsm65EmFXs7OBvn2lqYaQjbndbOiaNkW30Jhxy2aaSypU5yNKEzAtNx1zU3QMjXfLS5XplmsYiYQwa/N0zK2fTJgwAd27d4epqSmcnZ0xbdo0FBUVyeXJzMxEcHAwTE1N4e7ujri4uCZyDh48CF9fX5iamsLf3x8nT57UVBVaRLe65RrmcaUIdWIJDA04cLaia9z6yKhRo5CQkIA7d+7g8OHDyMnJwT//+U/muVAoxJgxY8Dj8XD16lV88cUXWLVqlVyQv0uXLuGdd95BZGQk0tPTMWnSJEyaNAk3b97URpUYNDhbroIJNQ4H4HKlqQYoaGy1nSxNYWSosd9BigZ5fmsnj8fD0qVLMWnSJCZkb3x8POrq6rBnzx5wuVz4+fnh+vXr+PLLL5lggFu2bEFYWBgWL14MAFizZg2SkpKwbds27Nixo1m9//d//6dwGRMTE1nVTWHjFolEEImetbpCobBdihwaW+7HlSI0iCXsjGXgQECkuZafzpR3LF5850xMTGBioroNUeXl5YiPj0dQUBATizstLQ3Dhw+X80oaGhqK9evX48mTJ7CxsUFaWho+/vhjOVmhoaE4cuRIi7qsrKxUVu6WUNi4161bh9WrV7NWZNvVBIYGHIglBGVVdUxL3pGRnQZzo5NpHQJ3d3e565iYGKxatUppudHR0di2bRuqq6vx8ssvy7k24vP58PT0lMvv2BhCms/nw8bGBnw+n7n3fB4+n9+izr179ypd7rZQuPlctmwZBAIB8ykoaF+weUMDDuzNldyllp0tDQCooaWwh3QyrUNRUFAg9w4uW7as2XxLly4Fh8Np9fO8y+DFixcjPT0dp0+fhqGhId577z2wjGzdoVC45VZFF8jR0gR8YS37SbWaGiA9XWObWGQz5bRb3jGwtLRUKD53VFRUm9s2vby8mL/t7OxgZ2eHXr16oXfv3nB3d8fly5cRGBgIJycnlJSUyH1Xdu3k5MSkzeWRPVeEQ4cOISEhAfn5+airq5N7du3aNYXlPI9GZ4kcVDGppkGYbjndwKJT2Nvbw9fXt9XP82Po55EF5ZPNLwUGBuL333+X8x+elJQEHx8f2NjYMHlSUlLk5CQlJTGOF9riq6++wowZM+Do6Ij09HQMHToUtra2uH//PsaOHdvu+svQqHHLlsN0Ya2bEEI3sOg5f/zxB7Zt24br16/jwYMHOHPmDN555x306NGDMcypU6eCy+UiMjISWVlZ+Pnnn7Flyxa5CbT58+fj1KlT2LhxI27fvo1Vq1bhr7/+knO+0Brbt2/Hrl27sHXrVnC5XCxZsgRJSUn46KOPIBAIWNdPs8Yt26WmA2vdZVV1qK2XgMMBnK07/uQfpf106dIFiYmJGD16NHx8fBAZGYl+/frh/PnzzBDUysoKp0+fRm5uLgYPHoyoqCisXLmSWQYDgKCgIPz444/YtWsX+vfvj0OHDuHIkSPo27evQuXIz89HUFAQAMDMzAwVFRUAgGnTpuGnn35iXT+NrXMDz611s92C6ukJJCRIUzUjG287WJjAxMiwjdwUXcTf3x9nzpxpM1+/fv2ajQjyPFOmTMGUKVNYlcPJyQnl5eXg8Xjo3r07Ll++jP79+yM3N1epiT0Nj7mV3KVmYyP1n9Y41lEn9MAIRVO8+uqr+OWXXwAAM2bMwMKFC/Haa6/hrbfewuTJk1nL1UrLzXrMXVICxMcD4eHAC+uKqkbmpIEug1HUza5du5iJvLlz58LW1haXLl3ChAkTMGvWLNZytWLcZVV1qGuQgGvUzo5DYSEQFSX1Xa5m45a13HQyjaJuDAwMYGDwzBbefvttvP3220rL1ahx23QxhrEhB/VigkeVog5tOIW0W05RI5mZmejbty8MDAyQmZnZat5+/fqx0qFR4+ZwpB5EC5/WoERY26GN+yHdwEJRIwMGDACfz4eDgwMGDBgADofT7OQZh8OBWCxmpUOjxg1I3RwXPq3p0Gvdz69x0zE3RR3k5ubC3t6e+VsdaNy4lTrXbWUFvP66NFUjgpp6VIoaANAxN0U98Hg85u8HDx4gKCgIRkby5tjQ0IBLly7J5W0PGj+kzLhbYtNy9+gB/PKLNFUjsi65nbkJTI3pGjdFvYwaNarZYH8CgQCjRo1iLVfjxi2bMeezMe76euDRI2mqRuh4m6JJCCHNRvwsKytD167s479rrVteyqZbfuMGMHgwcPWq9OingjyqEGFz8t9MV7st8h5XAaDjbYp6kXlj4XA4iIiIkDt1KRaLkZmZyWxLZYMWjFvzJ8O+u3Af8X/kt/t7vRws1FAaCkWKzBsLIQQWFhYwM3vWmHC5XLz88suYOXMma/lanFDTnHEnZUvP2oYHdIdXY6zwtujCNcTr/dmGRqFQ2mbv3r3M8tfWrVthbq7Yu6koGjdu2ZluYW0DaurEMOOqd8Lq/qNK3H9UBWNDDpaO9YWFqbFa9VEo7YEQgvj4eCxfvhze3t4qla3xCTULEyOYNc5Al2ogQEFKdikAIMDTlho2pcNhYGAAb29vlJWVqV62yiW2AYfDYb/W3b8/IBBIUwVJbuySh/R2aJ8uCkVDxMbGYvHixSr3c67xbjkg7ZrnlVW3f9xtaAgo4ENLhqC6Hn89eAIAGN1bvQdNKBS2vPfee6iurkb//v3B5XLlJtYANLsGrghaMW7WM+Z37wLz5gHbtgEKjE/O/V0KsYTAx9EC7t3oARBKx2Tz5s1qkasd47ZoXOuuaGe3vKICOH1amipA0i1pl3w07ZJTOjDTp09Xi1zdarnbQb1YgvN/PwIAhPShXXKKblBbW9vEtbEi7pybQ0tjbmnLffR6EU7eKAYgnWj7d7AXFoX6qETHn7nlqKhtgJ05FwPcrFUik0JRB1VVVYiOjkZCQkKzs+Zsj3xqJbrdoO426NK4vl0vJqgXE9Q1SLDjfA5z1FJZkhuXwEb5OMDAQDOBAykUNixZsgRnzpzBN998AxMTE3z33XdYvXo1XFxcsH//ftZytdJyu3frgr9WhEBY82yv98KfryPtfhl2nc/B6oktuIR1d5dOpr0QM+pFCCHMEhidJad0dI4dO4b9+/dj5MiRmDFjBoKDg9GzZ0/weDzEx8cjPDyclVytGDcAdOEaoQv3mfoPX+2JtPtlOPBnAea96g17i2ZCF9nbA3Pnol4sQcIfD/C0uvnTYVWiBuSXV4NrZIBgbzt1VYFCUQnl5eVMeCNLS0tm6WvYsGGYM2cOa7laM+4XCexhiwHu1rhe8BS7L+Zi6VjfppnKy4GTJ/E/e398cvZhmzKDetiiq0mHqSKF0ixeXl7Izc1F9+7d4evri4SEBAwdOhTHjh2DtbU1a7kdJqI8h8PB3FE9AQD/vfwAguZa5bw8YNo0XL9wHQAQ4NkNbw1xb/bz7svdsWJ8H81VgKLTiEQixpfZ9evX5Z5lZmYiODgYpqamcHd3R1xcXJPvHzx4EL6+vjA1NYW/vz9OnjypsO4ZM2YgIyMDgDRC6ddffw1TU1MsXLgQixcvZl8pwhKBQEAAEIFAwFZEE8RiCQnddJ7woo+TLcl/N81w9SohAHl9xhbCiz5O8h5Xqkw3peOijnftRT766CMyduxYAoCkp6fL6XZ0dCTh4eHk5s2b5KeffiJmZmZk586dTJ7U1FRiaGhI4uLiyK1bt8iKFSuIsbExuXHjBquy5OXlkcOHD5OMjAyl6tShjJsQQo6kPyS86OOk/+rfSGVtvfzDRuMeN30zCdv8u0r1Ujou6jbukydPEl9fX5KVldXEuLdv305sbGyISCRi7kVHRxMfHx/m+s033yTjx4+XkxkQEEBmzZrVql6xWExiY2NJUFAQGTJkCImOjibV1dWqqRQhpMN0y2WM93cGz7YLnlbX46crLTtYCPNTPPYxhdISJSUlmDlzJn744Qd06dJ0i3JaWhqGDx8uF/I3NDQUd+7cwZMnT5g8ISEhct8LDQ1FWlpaq7rXrl2L5cuXw9zcHK6urtiyZQvmzp2rglpJUdi4RSIRhEKh3EcdGBkaYPYIqQPEHefvo7ru2XJZlbEJ0l19UWNsirC+1Lg7Gy++f7IY2mwhhCAiIgKzZ8/GkCFDms3D5/Ph+EJ0G9k1n89vNY/seUvs378f27dvx2+//YYjR47g2LFjiI+PZ0ILKYvCxr1u3TpYWVkxH/c21pqV4Y1BbnDvZobHlSLsu5TH3D9LbDD53Q0gPj7o5aharxWUjo+7u7vcO7hu3bpm8y1duhQcDqfVz+3bt7F161ZUVFRg2bJlGq6JlPz8fIwbN465DgkJAYfDQVFRkUrkK7xOtGzZMrmA40KhUG0GzjUywMKQXvg4IQM7z99HeAAPVmbGOHVT+ksY6ufUrLdIin5TUFAgt8/6eYeCzxMVFYWIiIhWZXl5eeHMmTNIS0trImfIkCEIDw/H999/DycnJ5SUlMg9l107OTkxaXN5ZM9boqGhAaam8rHfjY2NUa8i774KG7eJiUmL/5jqYOIAV3xzLgd3Syux+8J9fDCqJ/hnLyHvuw9xZ/g5AM2sg1P0GktLS4UOUdjb2zPRPFrjq6++wueff85cFxUVITQ0FD///DMCAgIAAIGBgfjkk09QX18PY2OpJ5+kpCT4+PjApjGUdGBgIFJSUrBgwQJGVlJSEgIDA1vVLxsWPG9XtbW1mD17tpxL48TExDbr0hwddoeHoQEHUWN6YfZ/r2H3xVy4deuCmnrpBnpvB9olpyhP9+7d5a5lDgp79OgBNzc3AMDUqVOxevVqREZGIjo6Gjdv3sSWLVuwadMm5nvz58/HiBEjsHHjRowfPx4HDhzAX3/9hV27drWqv7mjnu+++66y1XoG22l2Taw9SiQS8o+vLhBe9HHS65OTZNz0zYQA0iUxSqdBE+8aIYTk5uY2WQojhJCMjAwybNgwYmJiQlxdXUlsbGyT7yYkJJBevXoRLpdL/Pz8yIkTJ9RaVkXgENJMaEEFEAqFsLKygkAgYH3eVBHO//0I0/dcAQD48e/hxPcL2h2UgKLbaOpd0zc63Dr3iwz3tsNQj24AACsz6r2UQlGUDm/cHA4HK/7RGzZdjDFswnCpH7U+dM84hdIWHXZC7Xn6uVkjfeUYbReDQtEpOnzLLUduLvDuu9KUQqG0im4Z95MnQHy8NKVQKK2iW8ZNoVAUhho3haKnsJ5Qky2Pq+t0WLNUVj5LNamXolVk7xjLLRmdFtbGXdEY9UOdp8NaZMQIzeukaJ2KigomYD2lbVjvUJNIJCgqKoKFhQU9oUVRK4QQVFRUwMXFBQYGdCSpKKyNm0KhdGzozyCFoqdQ46ZQ9BRq3BSKnkKNm0LRU6hxUyh6CjVuCkVPocZNoegp/w9FZxQgL2k/vAAAAABJRU5ErkJggg==", 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", 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" ] @@ -956,10 +903,6 @@ "execution_count": 90, "id": "5f305f10-8363-46eb-bb96-484f17f04f21", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -975,7 +918,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -998,7 +941,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 91, "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", "metadata": { "scrolled": true @@ -1010,407 +953,278 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.9448\n", - "Function value obtained: -61.2205\n", - "Current minimum: -61.2205\n", + "Time taken: 0.8895\n", + "Function value obtained: -1.9314\n", + "Current minimum: -1.9314\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.7981\n", - "Function value obtained: -1.3165\n", - "Current minimum: -61.2205\n", + "Time taken: 0.7702\n", + "Function value obtained: -83.4853\n", + "Current minimum: -83.4853\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.7924\n", - "Function value obtained: -0.0000\n", - "Current minimum: -61.2205\n", + "Time taken: 0.8837\n", + "Function value obtained: -4.3212\n", + "Current minimum: -83.4853\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8847\n", - "Function value obtained: -0.0043\n", - "Current minimum: -61.2205\n", + "Time taken: 0.7844\n", + "Function value obtained: -1.8607\n", + "Current minimum: -83.4853\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8267\n", - "Function value obtained: -116.8023\n", - "Current minimum: -116.8023\n", + "Time taken: 0.7663\n", + "Function value obtained: -66.8640\n", + "Current minimum: -83.4853\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8190\n", - "Function value obtained: -0.0000\n", - "Current minimum: -116.8023\n", + "Time taken: 0.7465\n", + "Function value obtained: -7.5460\n", + "Current minimum: -83.4853\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8277\n", - "Function value obtained: -0.0000\n", - "Current minimum: -116.8023\n", + "Time taken: 0.7858\n", + "Function value obtained: -48.6599\n", + "Current minimum: -83.4853\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8259\n", - "Function value obtained: -0.0000\n", - "Current minimum: -116.8023\n", + "Time taken: 0.7636\n", + "Function value obtained: -1.9422\n", + "Current minimum: -83.4853\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8282\n", - "Function value obtained: -0.0000\n", - "Current minimum: -116.8023\n", + "Time taken: 0.8648\n", + "Function value obtained: -81.8343\n", + "Current minimum: -83.4853\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 4.7821\n", - "Function value obtained: -0.0000\n", - "Current minimum: -116.8023\n", + "Time taken: 0.9334\n", + "Function value obtained: -19.9633\n", + "Current minimum: -83.4853\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4264\n", - "Function value obtained: -118.2319\n", - "Current minimum: -118.2319\n", + "Time taken: 1.0032\n", + "Function value obtained: -87.3024\n", + "Current minimum: -87.3024\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3306\n", - "Function value obtained: -276.4398\n", - "Current minimum: -276.4398\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.38927630582277944]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.0474\n", + "Function value obtained: -85.5118\n", + "Current minimum: -87.3024\n", + "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3965\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", + "Time taken: 1.0281\n", + "Function value obtained: -85.6057\n", + "Current minimum: -87.3024\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3848\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.18417481589713974]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 0.8791\n", + "Function value obtained: -83.3193\n", + "Current minimum: -87.3024\n", + "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3431\n", - "Function value obtained: -9.8336\n", - "Current minimum: -276.4398\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.6163259384209202]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.0138\n", + "Function value obtained: -84.5095\n", + "Current minimum: -87.3024\n", + "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3639\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.7620265074972382]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.0012\n", + "Function value obtained: -87.0050\n", + "Current minimum: -87.3024\n", + "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4569\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.7176335045210767]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 0.9778\n", + "Function value obtained: -84.4120\n", + "Current minimum: -87.3024\n", + "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9941\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.47975524824311866]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.0535\n", + "Function value obtained: -83.0230\n", + "Current minimum: -87.3024\n", + "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1352\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.6610471994826488]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.0381\n", + "Function value obtained: -81.0072\n", + "Current minimum: -87.3024\n", + "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1225\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.5849803799180963]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 0.9801\n", + "Function value obtained: -86.3396\n", + "Current minimum: -87.3024\n", + "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2836\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.39568235674564767]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 0.9412\n", + "Function value obtained: -86.0437\n", + "Current minimum: -87.3024\n", + "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1409\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.5068234394773203]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.0107\n", + "Function value obtained: -87.1612\n", + "Current minimum: -87.3024\n", + "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1433\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.001] before, using random point [0.5599477470534967]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.0426\n", + "Function value obtained: -84.8570\n", + "Current minimum: -87.3024\n", + "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1053\n", - "Function value obtained: -0.0000\n", - "Current minimum: -276.4398\n", + "Time taken: 0.9731\n", + "Function value obtained: -86.3455\n", + "Current minimum: -87.3024\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1822\n", - "Function value obtained: -119.5722\n", - "Current minimum: -276.4398\n", + "Time taken: 1.0634\n", + "Function value obtained: -82.7459\n", + "Current minimum: -87.3024\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1073\n", - "Function value obtained: -124.9303\n", - "Current minimum: -276.4398\n", + "Time taken: 1.0838\n", + "Function value obtained: -85.1438\n", + "Current minimum: -87.3024\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2083\n", - "Function value obtained: -129.5423\n", - "Current minimum: -276.4398\n", + "Time taken: 1.0458\n", + "Function value obtained: -82.9107\n", + "Current minimum: -87.3024\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1394\n", - "Function value obtained: -133.6385\n", - "Current minimum: -276.4398\n", + "Time taken: 1.0000\n", + "Function value obtained: -83.1693\n", + "Current minimum: -87.3024\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0907\n", - "Function value obtained: -135.4072\n", - "Current minimum: -276.4398\n", + "Time taken: 1.0817\n", + "Function value obtained: -88.3016\n", + "Current minimum: -88.3016\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2051\n", - "Function value obtained: -132.3138\n", - "Current minimum: -276.4398\n", + "Time taken: 1.0293\n", + "Function value obtained: -84.2473\n", + "Current minimum: -88.3016\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1947\n", - "Function value obtained: -287.7266\n", - "Current minimum: -287.7266\n", + "Time taken: 0.9022\n", + "Function value obtained: -84.7010\n", + "Current minimum: -88.3016\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1099\n", - "Function value obtained: -300.7117\n", - "Current minimum: -300.7117\n", + "Time taken: 1.0825\n", + "Function value obtained: -84.0562\n", + "Current minimum: -88.3016\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1438\n", - "Function value obtained: -312.6263\n", - "Current minimum: -312.6263\n", + "Time taken: 1.0863\n", + "Function value obtained: -81.5943\n", + "Current minimum: -88.3016\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2755\n", - "Function value obtained: -317.7043\n", - "Current minimum: -317.7043\n", + "Time taken: 1.0594\n", + "Function value obtained: -81.7522\n", + "Current minimum: -88.3016\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1432\n", - "Function value obtained: -322.8711\n", - "Current minimum: -322.8711\n", + "Time taken: 1.0530\n", + "Function value obtained: -84.6776\n", + "Current minimum: -88.3016\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1544\n", - "Function value obtained: -329.9536\n", - "Current minimum: -329.9536\n", + "Time taken: 1.0158\n", + "Function value obtained: -84.9923\n", + "Current minimum: -88.3016\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2283\n", - "Function value obtained: -119.6188\n", - "Current minimum: -329.9536\n", + "Time taken: 1.0790\n", + "Function value obtained: -84.2549\n", + "Current minimum: -88.3016\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1304\n", - "Function value obtained: -128.0405\n", - "Current minimum: -329.9536\n", + "Time taken: 1.0874\n", + "Function value obtained: -86.2316\n", + "Current minimum: -88.3016\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2385\n", - "Function value obtained: -120.1647\n", - "Current minimum: -329.9536\n", + "Time taken: 1.0445\n", + "Function value obtained: -83.9166\n", + "Current minimum: -88.3016\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0728\n", - "Function value obtained: -0.0000\n", - "Current minimum: -329.9536\n", + "Time taken: 1.1374\n", + "Function value obtained: -85.5846\n", + "Current minimum: -88.3016\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1438\n", - "Function value obtained: -139.1815\n", - "Current minimum: -329.9536\n", + "Time taken: 1.4393\n", + "Function value obtained: -85.8292\n", + "Current minimum: -88.3016\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2534\n", - "Function value obtained: -80.8014\n", - "Current minimum: -329.9536\n", + "Time taken: 1.1425\n", + "Function value obtained: -84.7982\n", + "Current minimum: -88.3016\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2480\n", - "Function value obtained: -118.6952\n", - "Current minimum: -329.9536\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" + "Time taken: 1.0837\n", + "Function value obtained: -84.9636\n", + "Current minimum: -88.3016\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0810\n", + "Function value obtained: -80.9480\n", + "Current minimum: -88.3016\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0476\n", + "Function value obtained: -81.6247\n", + "Current minimum: -88.3016\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0960\n", + "Function value obtained: -83.5560\n", + "Current minimum: -88.3016\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1526\n", + "Function value obtained: -83.6973\n", + "Current minimum: -88.3016\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1651\n", + "Function value obtained: -85.3829\n", + "Current minimum: -88.3016\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1530\n", + "Function value obtained: -83.4624\n", + "Current minimum: -88.3016\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1107\n", + "Function value obtained: -83.4790\n", + "Current minimum: -88.3016\n", + "CPU times: user 1min 33s, sys: 9min 8s, total: 10min 41s\n", + "Wall time: 50.5 s\n" ] }, { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "File \u001b[0;32m:1\u001b[0m\n", - "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/skopt/optimizer/gp.py:281\u001b[0m, in \u001b[0;36mgp_minimize\u001b[0;34m(func, dimensions, base_estimator, n_calls, n_random_starts, n_initial_points, initial_point_generator, acq_func, acq_optimizer, x0, y0, random_state, verbose, callback, n_points, n_restarts_optimizer, xi, kappa, noise, n_jobs, model_queue_size, space_constraint)\u001b[0m\n\u001b[1;32m 273\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m base_estimator \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 274\u001b[0m base_estimator \u001b[38;5;241m=\u001b[39m cook_estimator(\n\u001b[1;32m 275\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mGP\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 276\u001b[0m space\u001b[38;5;241m=\u001b[39mspace,\n\u001b[1;32m 277\u001b[0m random_state\u001b[38;5;241m=\u001b[39mrng\u001b[38;5;241m.\u001b[39mrandint(\u001b[38;5;241m0\u001b[39m, np\u001b[38;5;241m.\u001b[39miinfo(np\u001b[38;5;241m.\u001b[39mint32)\u001b[38;5;241m.\u001b[39mmax),\n\u001b[1;32m 278\u001b[0m noise\u001b[38;5;241m=\u001b[39mnoise,\n\u001b[1;32m 279\u001b[0m )\n\u001b[0;32m--> 281\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mbase_minimize\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 282\u001b[0m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 283\u001b[0m \u001b[43m \u001b[49m\u001b[43mspace\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 284\u001b[0m \u001b[43m \u001b[49m\u001b[43mbase_estimator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_estimator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 285\u001b[0m \u001b[43m \u001b[49m\u001b[43macq_func\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43macq_func\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 286\u001b[0m \u001b[43m \u001b[49m\u001b[43mxi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mxi\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 287\u001b[0m \u001b[43m \u001b[49m\u001b[43mkappa\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkappa\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 288\u001b[0m \u001b[43m \u001b[49m\u001b[43macq_optimizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43macq_optimizer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 289\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_calls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_calls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 290\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_points\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_points\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 291\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_random_starts\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_random_starts\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 292\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_initial_points\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_initial_points\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 293\u001b[0m \u001b[43m \u001b[49m\u001b[43minitial_point_generator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minitial_point_generator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 294\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_restarts_optimizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_restarts_optimizer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 295\u001b[0m \u001b[43m \u001b[49m\u001b[43mx0\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mx0\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 296\u001b[0m \u001b[43m \u001b[49m\u001b[43my0\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43my0\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 297\u001b[0m \u001b[43m \u001b[49m\u001b[43mrandom_state\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrng\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 298\u001b[0m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 299\u001b[0m \u001b[43m \u001b[49m\u001b[43mspace_constraint\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mspace_constraint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 300\u001b[0m \u001b[43m \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 301\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mn_jobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 302\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodel_queue_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmodel_queue_size\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 303\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/skopt/optimizer/base.py:332\u001b[0m, in \u001b[0;36mbase_minimize\u001b[0;34m(func, dimensions, base_estimator, n_calls, n_random_starts, n_initial_points, initial_point_generator, acq_func, acq_optimizer, x0, y0, random_state, verbose, callback, n_points, n_restarts_optimizer, xi, kappa, n_jobs, model_queue_size, space_constraint)\u001b[0m\n\u001b[1;32m 330\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(n_calls):\n\u001b[1;32m 331\u001b[0m next_x \u001b[38;5;241m=\u001b[39m optimizer\u001b[38;5;241m.\u001b[39mask()\n\u001b[0;32m--> 332\u001b[0m next_y \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnext_x\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 333\u001b[0m result \u001b[38;5;241m=\u001b[39m optimizer\u001b[38;5;241m.\u001b[39mtell(next_x, next_y)\n\u001b[1;32m 334\u001b[0m result\u001b[38;5;241m.\u001b[39mspecs \u001b[38;5;241m=\u001b[39m specs\n", - "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/skopt/utils.py:779\u001b[0m, in \u001b[0;36muse_named_args..decorator..wrapper\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 776\u001b[0m arg_dict \u001b[38;5;241m=\u001b[39m {dim\u001b[38;5;241m.\u001b[39mname: value \u001b[38;5;28;01mfor\u001b[39;00m dim, value \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(dimensions, x)}\n\u001b[1;32m 778\u001b[0m \u001b[38;5;66;03m# Call the wrapped objective function with the named arguments.\u001b[39;00m\n\u001b[0;32m--> 779\u001b[0m objective_value \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43marg_dict\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 781\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m objective_value\n", - "Cell \u001b[0;32mIn[5], line 24\u001b[0m, in \u001b[0;36mesc_obj\u001b[0;34m(**x)\u001b[0m\n\u001b[1;32m 22\u001b[0m eval_env \u001b[38;5;241m=\u001b[39m AsmEnv(config\u001b[38;5;241m=\u001b[39mCONFIG)\n\u001b[1;32m 23\u001b[0m agent \u001b[38;5;241m=\u001b[39m ConstEsc(env\u001b[38;5;241m=\u001b[39meval_env, escapement \u001b[38;5;241m=\u001b[39m x[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mescapement\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[0;32m---> 24\u001b[0m rews \u001b[38;5;241m=\u001b[39m \u001b[43meval_pol\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 25\u001b[0m \u001b[43m \u001b[49m\u001b[43mpolicy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43magent\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 26\u001b[0m \u001b[43m \u001b[49m\u001b[43menv_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mAsmEnv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mCONFIG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m 27\u001b[0m \u001b[43m \u001b[49m\u001b[43mn_batches\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m40\u001b[39;49m\n\u001b[1;32m 28\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 29\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39mnp\u001b[38;5;241m.\u001b[39mmean(rews)\n", - "Cell \u001b[0;32mIn[4], line 29\u001b[0m, in \u001b[0;36meval_pol\u001b[0;34m(policy, env_cls, config, n_batches, batch_size, pb)\u001b[0m\n\u001b[1;32m 26\u001b[0m rews \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 27\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m batch_iter:\n\u001b[1;32m 28\u001b[0m rews\u001b[38;5;241m.\u001b[39mappend(\n\u001b[0;32m---> 29\u001b[0m \u001b[43mrew_batch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpolicy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpolicy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43menv_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43menv_cls\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbatch_size\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 30\u001b[0m )\n\u001b[1;32m 31\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray(rews)\u001b[38;5;241m.\u001b[39mflatten()\n", - "Cell \u001b[0;32mIn[4], line 16\u001b[0m, in \u001b[0;36mrew_batch\u001b[0;34m(policy, env_cls, config, batch_size)\u001b[0m\n\u001b[1;32m 14\u001b[0m tmax \u001b[38;5;241m=\u001b[39m env_cls()\u001b[38;5;241m.\u001b[39mTmax\n\u001b[1;32m 15\u001b[0m parallel \u001b[38;5;241m=\u001b[39m [generate_rew\u001b[38;5;241m.\u001b[39mremote(policy, env_cls, config) \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(batch_size)]\n\u001b[0;32m---> 16\u001b[0m rews \u001b[38;5;241m=\u001b[39m \u001b[43mray\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparallel\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m rews\n", - "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/auto_init_hook.py:21\u001b[0m, in \u001b[0;36mwrap_auto_init..auto_init_wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(fn)\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mauto_init_wrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 20\u001b[0m auto_init_ray()\n\u001b[0;32m---> 21\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/client_mode_hook.py:103\u001b[0m, in \u001b[0;36mclient_mode_hook..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 101\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m func\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minit\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m is_client_mode_enabled_by_default:\n\u001b[1;32m 102\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(ray, func\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m)(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 103\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/worker.py:2667\u001b[0m, in \u001b[0;36mget\u001b[0;34m(object_refs, timeout)\u001b[0m\n\u001b[1;32m 2661\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 2662\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid type of object refs, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(object_refs)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, is given. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2663\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mobject_refs\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m must either be an ObjectRef or a list of ObjectRefs. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2664\u001b[0m )\n\u001b[1;32m 2666\u001b[0m \u001b[38;5;66;03m# TODO(ujvl): Consider how to allow user to retrieve the ready objects.\u001b[39;00m\n\u001b[0;32m-> 2667\u001b[0m values, debugger_breakpoint \u001b[38;5;241m=\u001b[39m \u001b[43mworker\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_objects\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobject_refs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2668\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, value \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(values):\n\u001b[1;32m 2669\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(value, RayError):\n", - "File \u001b[0;32m/opt/venv/lib/python3.10/site-packages/ray/_private/worker.py:843\u001b[0m, in \u001b[0;36mWorker.get_objects\u001b[0;34m(self, object_refs, timeout)\u001b[0m\n\u001b[1;32m 837\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 838\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAttempting to call `get` on the value \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mobject_ref\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 839\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwhich is not an ray.ObjectRef.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 840\u001b[0m )\n\u001b[1;32m 842\u001b[0m timeout_ms \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(timeout \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m1000\u001b[39m) \u001b[38;5;28;01mif\u001b[39;00m timeout \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[0;32m--> 843\u001b[0m data_metadata_pairs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcore_worker\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_objects\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 844\u001b[0m \u001b[43m \u001b[49m\u001b[43mobject_refs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 845\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcurrent_task_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 846\u001b[0m \u001b[43m \u001b[49m\u001b[43mtimeout_ms\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 847\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 848\u001b[0m debugger_breakpoint \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 849\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m data, metadata \u001b[38;5;129;01min\u001b[39;00m data_metadata_pairs:\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] + "data": { + "text/plain": [ + "(-88.30164756300354, [-1.9537556537577059])" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ "%%time\n", - "esc_gp = gp_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", "esc_gp.fun, esc_gp.x" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 92, "id": "ebff2644-b811-4bea-995c-ca3c7586c122", "metadata": {}, "outputs": [ @@ -1420,13 +1234,13 @@ "" ] }, - "execution_count": 6, + "execution_count": 92, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -1444,10 +1258,6 @@ "execution_count": 93, "id": "23e3b71f-dcb0-41df-a74d-37043f57cbe1", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -1463,7 +1273,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1481,10 +1291,6 @@ "execution_count": 94, "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -1494,262 +1300,262 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.7164\n", - "Function value obtained: -26.8844\n", - "Current minimum: -26.8844\n", + "Time taken: 0.8928\n", + "Function value obtained: -1.9366\n", + "Current minimum: -1.9366\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.7265\n", - "Function value obtained: -222.6033\n", - "Current minimum: -222.6033\n", + "Time taken: 0.8940\n", + "Function value obtained: -2.1499\n", + "Current minimum: -2.1499\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.7946\n", - "Function value obtained: -80.9190\n", - "Current minimum: -222.6033\n", + "Time taken: 0.7580\n", + "Function value obtained: -2.1207\n", + "Current minimum: -2.1499\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.7275\n", - "Function value obtained: -22.7700\n", - "Current minimum: -222.6033\n", + "Time taken: 0.7685\n", + "Function value obtained: -2.9358\n", + "Current minimum: -2.9358\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.7880\n", - "Function value obtained: -15.2744\n", - "Current minimum: -222.6033\n", + "Time taken: 0.8323\n", + "Function value obtained: -7.0135\n", + "Current minimum: -7.0135\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8445\n", - "Function value obtained: -3.0041\n", - "Current minimum: -222.6033\n", + "Time taken: 0.7688\n", + "Function value obtained: -75.4833\n", + "Current minimum: -75.4833\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8175\n", - "Function value obtained: -233.2936\n", - "Current minimum: -233.2936\n", + "Time taken: 0.7837\n", + "Function value obtained: -6.7920\n", + "Current minimum: -75.4833\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8094\n", - "Function value obtained: -38.3504\n", - "Current minimum: -233.2936\n", + "Time taken: 0.8485\n", + "Function value obtained: -48.8146\n", + "Current minimum: -75.4833\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.7705\n", - "Function value obtained: -83.3108\n", - "Current minimum: -233.2936\n", + "Time taken: 0.8639\n", + "Function value obtained: -49.1108\n", + "Current minimum: -75.4833\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 0.9808\n", - "Function value obtained: -37.9396\n", - "Current minimum: -233.2936\n", + "Time taken: 0.9739\n", + "Function value obtained: -68.7822\n", + "Current minimum: -75.4833\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0739\n", - "Function value obtained: -278.4030\n", - "Current minimum: -278.4030\n", + "Time taken: 1.0094\n", + "Function value obtained: -82.2816\n", + "Current minimum: -82.2816\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9643\n", - "Function value obtained: -460.3324\n", - "Current minimum: -460.3324\n", + "Time taken: 1.0761\n", + "Function value obtained: -78.0358\n", + "Current minimum: -82.2816\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9603\n", - "Function value obtained: -490.2741\n", - "Current minimum: -490.2741\n", + "Time taken: 1.1717\n", + "Function value obtained: -82.6843\n", + "Current minimum: -82.6843\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9234\n", - "Function value obtained: -485.4477\n", - "Current minimum: -490.2741\n", + "Time taken: 1.0236\n", + "Function value obtained: -70.0158\n", + "Current minimum: -82.6843\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9955\n", - "Function value obtained: -450.4965\n", - "Current minimum: -490.2741\n", + "Time taken: 0.9966\n", + "Function value obtained: -85.8629\n", + "Current minimum: -85.8629\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0095\n", - "Function value obtained: -493.7419\n", - "Current minimum: -493.7419\n", + "Time taken: 1.0580\n", + "Function value obtained: -83.4641\n", + "Current minimum: -85.8629\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0223\n", - "Function value obtained: -498.2012\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0565\n", + "Function value obtained: -86.9627\n", + "Current minimum: -86.9627\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1705\n", - "Function value obtained: -466.6017\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9480\n", + "Function value obtained: -86.1189\n", + "Current minimum: -86.9627\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9742\n", - "Function value obtained: -477.9343\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9449\n", + "Function value obtained: -82.8694\n", + "Current minimum: -86.9627\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0431\n", - "Function value obtained: -484.4293\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9600\n", + "Function value obtained: -84.5687\n", + "Current minimum: -86.9627\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0719\n", - "Function value obtained: -480.3876\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9804\n", + "Function value obtained: -88.4548\n", + "Current minimum: -88.4548\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1128\n", - "Function value obtained: -483.0817\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0303\n", + "Function value obtained: -33.5852\n", + "Current minimum: -88.4548\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0581\n", - "Function value obtained: -483.6774\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9988\n", + "Function value obtained: -87.0987\n", + "Current minimum: -88.4548\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0420\n", - "Function value obtained: -483.3315\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0530\n", + "Function value obtained: -35.9950\n", + "Current minimum: -88.4548\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0541\n", - "Function value obtained: -485.7821\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9661\n", + "Function value obtained: -85.1322\n", + "Current minimum: -88.4548\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0474\n", - "Function value obtained: -483.0713\n", - "Current minimum: -498.2012\n", + "Time taken: 1.3338\n", + "Function value obtained: -85.4144\n", + "Current minimum: -88.4548\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1090\n", - "Function value obtained: -487.6074\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9657\n", + "Function value obtained: -85.9783\n", + "Current minimum: -88.4548\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0390\n", - "Function value obtained: -490.3229\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0462\n", + "Function value obtained: -81.8535\n", + "Current minimum: -88.4548\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0100\n", - "Function value obtained: -491.0666\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0058\n", + "Function value obtained: -85.4714\n", + "Current minimum: -88.4548\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9422\n", - "Function value obtained: -485.1380\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9512\n", + "Function value obtained: -84.0389\n", + "Current minimum: -88.4548\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0197\n", - "Function value obtained: -492.1412\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0799\n", + "Function value obtained: -84.3946\n", + "Current minimum: -88.4548\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0195\n", - "Function value obtained: -485.7869\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0637\n", + "Function value obtained: -86.6287\n", + "Current minimum: -88.4548\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0170\n", - "Function value obtained: -492.3588\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9846\n", + "Function value obtained: -88.3544\n", + "Current minimum: -88.4548\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0175\n", - "Function value obtained: -478.8948\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9553\n", + "Function value obtained: -85.9460\n", + "Current minimum: -88.4548\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9582\n", - "Function value obtained: -488.4867\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0458\n", + "Function value obtained: -81.9748\n", + "Current minimum: -88.4548\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0812\n", - "Function value obtained: -487.9997\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0769\n", + "Function value obtained: -85.6594\n", + "Current minimum: -88.4548\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1216\n", - "Function value obtained: -483.7180\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0835\n", + "Function value obtained: -84.7670\n", + "Current minimum: -88.4548\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1025\n", - "Function value obtained: -493.1157\n", - "Current minimum: -498.2012\n", + "Time taken: 1.1385\n", + "Function value obtained: -85.7179\n", + "Current minimum: -88.4548\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0879\n", - "Function value obtained: -484.7133\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0549\n", + "Function value obtained: -85.1600\n", + "Current minimum: -88.4548\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3282\n", - "Function value obtained: -486.6326\n", - "Current minimum: -498.2012\n", + "Time taken: 1.1085\n", + "Function value obtained: -87.5070\n", + "Current minimum: -88.4548\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0917\n", - "Function value obtained: -483.5718\n", - "Current minimum: -498.2012\n", + "Time taken: 1.1128\n", + "Function value obtained: -84.2948\n", + "Current minimum: -88.4548\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0574\n", - "Function value obtained: -482.9294\n", - "Current minimum: -498.2012\n", + "Time taken: 1.1448\n", + "Function value obtained: -83.3965\n", + "Current minimum: -88.4548\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9581\n", - "Function value obtained: -478.3334\n", - "Current minimum: -498.2012\n", + "Time taken: 1.1306\n", + "Function value obtained: -83.7405\n", + "Current minimum: -88.4548\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9518\n", - "Function value obtained: -484.7935\n", - "Current minimum: -498.2012\n", + "Time taken: 1.1046\n", + "Function value obtained: -83.8566\n", + "Current minimum: -88.4548\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0271\n", - "Function value obtained: -482.6666\n", - "Current minimum: -498.2012\n", + "Time taken: 1.1216\n", + "Function value obtained: -83.0424\n", + "Current minimum: -88.4548\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0760\n", - "Function value obtained: -486.2643\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0563\n", + "Function value obtained: -83.3528\n", + "Current minimum: -88.4548\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0205\n", - "Function value obtained: -482.6045\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0197\n", + "Function value obtained: -25.1002\n", + "Current minimum: -88.4548\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9537\n", - "Function value obtained: -487.0841\n", - "Current minimum: -498.2012\n", + "Time taken: 1.0718\n", + "Function value obtained: -29.6400\n", + "Current minimum: -88.4548\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0468\n", - "Function value obtained: -482.9095\n", - "Current minimum: -498.2012\n", + "Time taken: 0.9993\n", + "Function value obtained: -86.4158\n", + "Current minimum: -88.4548\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0051\n", - "Function value obtained: -493.3676\n", - "Current minimum: -498.2012\n", - "CPU times: user 18 s, sys: 4.32 s, total: 22.3 s\n", - "Wall time: 49.6 s\n" + "Time taken: 0.9361\n", + "Function value obtained: -84.7042\n", + "Current minimum: -88.4548\n", + "CPU times: user 17.7 s, sys: 4.08 s, total: 21.7 s\n", + "Wall time: 50.3 s\n" ] }, { "data": { "text/plain": [ - "(-498.2012416556625, [0.09553591362425362])" + "(-88.45482307660751, [-1.9533840854652205])" ] }, "execution_count": 94, @@ -1759,7 +1565,7 @@ ], "source": [ "%%time\n", - "esc_gbrt = gbrt_minimize(esc_obj, esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", "esc_gbrt.fun, esc_gbrt.x" ] }, @@ -1767,12 +1573,7 @@ "cell_type": "code", "execution_count": 95, "id": "d85a57bd-e338-468d-9d63-45d82fe53aef", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - } - }, + "metadata": {}, "outputs": [ { "data": { @@ -1786,7 +1587,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1804,10 +1605,6 @@ "execution_count": 96, "id": "2e4f4fe1-236c-4f3f-ba31-49d56fdc610d", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -1823,7 +1620,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -1849,10 +1646,6 @@ "execution_count": 97, "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -1862,513 +1655,513 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8137\n", - "Function value obtained: -112.5777\n", - "Current minimum: -112.5777\n", + "Time taken: 0.8277\n", + "Function value obtained: -3.3906\n", + "Current minimum: -3.3906\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.7754\n", - "Function value obtained: -494.5841\n", - "Current minimum: -494.5841\n", + "Time taken: 0.8487\n", + "Function value obtained: -47.0619\n", + "Current minimum: -47.0619\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.7743\n", - "Function value obtained: -105.5923\n", - "Current minimum: -494.5841\n", + "Time taken: 0.8061\n", + "Function value obtained: -15.8264\n", + "Current minimum: -47.0619\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8433\n", - "Function value obtained: -490.8444\n", - "Current minimum: -494.5841\n", + "Time taken: 0.7809\n", + "Function value obtained: -2.1098\n", + "Current minimum: -47.0619\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8100\n", - "Function value obtained: -26.2553\n", - "Current minimum: -494.5841\n", + "Time taken: 0.8065\n", + "Function value obtained: -3.1192\n", + "Current minimum: -47.0619\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8124\n", - "Function value obtained: -49.0520\n", - "Current minimum: -494.5841\n", + "Time taken: 0.8604\n", + "Function value obtained: -15.0873\n", + "Current minimum: -47.0619\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8422\n", - "Function value obtained: -471.6829\n", - "Current minimum: -494.5841\n", + "Time taken: 0.8625\n", + "Function value obtained: -35.7408\n", + "Current minimum: -47.0619\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8121\n", - "Function value obtained: -500.5413\n", - "Current minimum: -500.5413\n", + "Time taken: 0.7732\n", + "Function value obtained: -0.5765\n", + "Current minimum: -47.0619\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8180\n", - "Function value obtained: -34.5078\n", - "Current minimum: -500.5413\n", + "Time taken: 0.8468\n", + "Function value obtained: -14.0440\n", + "Current minimum: -47.0619\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.0414\n", - "Function value obtained: -70.7846\n", - "Current minimum: -500.5413\n", + "Time taken: 1.1358\n", + "Function value obtained: -53.9416\n", + "Current minimum: -53.9416\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9993\n", - "Function value obtained: -2.1498\n", - "Current minimum: -500.5413\n", + "Time taken: 1.1185\n", + "Function value obtained: -37.9501\n", + "Current minimum: -53.9416\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1331\n", - "Function value obtained: -376.4437\n", - "Current minimum: -500.5413\n", + "Time taken: 1.1148\n", + "Function value obtained: -55.1610\n", + "Current minimum: -55.1610\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0099\n", - "Function value obtained: -0.0000\n", - "Current minimum: -500.5413\n", + "Time taken: 1.2095\n", + "Function value obtained: -53.4027\n", + "Current minimum: -55.1610\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0186\n", - "Function value obtained: -506.2584\n", - "Current minimum: -506.2584\n", + "Time taken: 1.0414\n", + "Function value obtained: -23.3036\n", + "Current minimum: -55.1610\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1363\n", - "Function value obtained: -490.7306\n", - "Current minimum: -506.2584\n", + "Time taken: 1.0363\n", + "Function value obtained: -60.5604\n", + "Current minimum: -60.5604\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0444\n", - "Function value obtained: -0.0000\n", - "Current minimum: -506.2584\n", + "Time taken: 1.0544\n", + "Function value obtained: -64.3094\n", + "Current minimum: -64.3094\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0615\n", - "Function value obtained: -494.1847\n", - "Current minimum: -506.2584\n", + "Time taken: 0.9672\n", + "Function value obtained: -69.4757\n", + "Current minimum: -69.4757\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9965\n", - "Function value obtained: -379.5701\n", - "Current minimum: -506.2584\n", + "Time taken: 1.0518\n", + "Function value obtained: -75.2616\n", + "Current minimum: -75.2616\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1032\n", - "Function value obtained: -500.5689\n", - "Current minimum: -506.2584\n", + "Time taken: 1.0739\n", + "Function value obtained: -81.2147\n", + "Current minimum: -81.2147\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9070\n", - "Function value obtained: -505.7714\n", - "Current minimum: -506.2584\n", + "Time taken: 1.1083\n", + "Function value obtained: -81.5636\n", + "Current minimum: -81.5636\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0314\n", - "Function value obtained: -480.1877\n", - "Current minimum: -506.2584\n", + "Time taken: 1.1196\n", + "Function value obtained: -79.4084\n", + "Current minimum: -81.5636\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1043\n", - "Function value obtained: -494.8285\n", - "Current minimum: -506.2584\n", + "Time taken: 1.1764\n", + "Function value obtained: -0.0000\n", + "Current minimum: -81.5636\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9981\n", - "Function value obtained: -502.9280\n", - "Current minimum: -506.2584\n", + "Time taken: 1.0733\n", + "Function value obtained: -77.2342\n", + "Current minimum: -81.5636\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0053\n", - "Function value obtained: -498.3964\n", - "Current minimum: -506.2584\n", + "Time taken: 1.0143\n", + "Function value obtained: -79.9140\n", + "Current minimum: -81.5636\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1590\n", - "Function value obtained: -504.6819\n", - "Current minimum: -506.2584\n", + "Time taken: 1.1439\n", + "Function value obtained: -80.7929\n", + "Current minimum: -81.5636\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1096\n", - "Function value obtained: -507.3854\n", - "Current minimum: -507.3854\n", + "Time taken: 1.1345\n", + "Function value obtained: -85.4421\n", + "Current minimum: -85.4421\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3070\n", - "Function value obtained: -496.4364\n", - "Current minimum: -507.3854\n", + "Time taken: 1.1557\n", + "Function value obtained: -80.6570\n", + "Current minimum: -85.4421\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1095\n", - "Function value obtained: -509.8005\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1955\n", + "Function value obtained: -82.7055\n", + "Current minimum: -85.4421\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0825\n", - "Function value obtained: -499.6756\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1922\n", + "Function value obtained: -87.1918\n", + "Current minimum: -87.1918\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2373\n", - "Function value obtained: -438.7227\n", - "Current minimum: -509.8005\n", + "Time taken: 1.0719\n", + "Function value obtained: -85.4975\n", + "Current minimum: -87.1918\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0852\n", - "Function value obtained: -493.1978\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1543\n", + "Function value obtained: -85.1530\n", + "Current minimum: -87.1918\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1011\n", - "Function value obtained: -481.2166\n", - "Current minimum: -509.8005\n", + "Time taken: 1.2110\n", + "Function value obtained: -81.3207\n", + "Current minimum: -87.1918\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0862\n", - "Function value obtained: -487.4244\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1746\n", + "Function value obtained: -81.8238\n", + "Current minimum: -87.1918\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0467\n", - "Function value obtained: -500.3367\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1516\n", + "Function value obtained: -82.0723\n", + "Current minimum: -87.1918\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1106\n", - "Function value obtained: -433.0037\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1830\n", + "Function value obtained: -84.5704\n", + "Current minimum: -87.1918\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0931\n", - "Function value obtained: -487.6623\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1976\n", + "Function value obtained: -61.5135\n", + "Current minimum: -87.1918\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1745\n", - "Function value obtained: -494.4660\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1740\n", + "Function value obtained: -81.7941\n", + "Current minimum: -87.1918\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2472\n", - "Function value obtained: -491.5872\n", - "Current minimum: -509.8005\n", + "Time taken: 1.1302\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1918\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1841\n", - "Function value obtained: -483.2152\n", - "Current minimum: -509.8005\n", + "Time taken: 1.2333\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1918\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2541\n", - "Function value obtained: -507.4246\n", - "Current minimum: -509.8005\n", + "Time taken: 1.2138\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1918\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2425\n", - "Function value obtained: -513.3998\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2293\n", + "Function value obtained: -76.3928\n", + "Current minimum: -87.1918\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2428\n", - "Function value obtained: -496.3897\n", - "Current minimum: -513.3998\n", + "Time taken: 1.1403\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1918\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2923\n", - "Function value obtained: -498.7091\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3364\n", + "Function value obtained: -84.5465\n", + "Current minimum: -87.1918\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2726\n", - "Function value obtained: -486.7539\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3526\n", + "Function value obtained: -86.3146\n", + "Current minimum: -87.1918\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2129\n", - "Function value obtained: -487.7921\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2450\n", + "Function value obtained: -50.8457\n", + "Current minimum: -87.1918\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1948\n", - "Function value obtained: -508.5968\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2840\n", + "Function value obtained: -83.0865\n", + "Current minimum: -87.1918\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2143\n", - "Function value obtained: -0.0000\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3018\n", + "Function value obtained: -85.2767\n", + "Current minimum: -87.1918\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3151\n", - "Function value obtained: -492.3543\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2706\n", + "Function value obtained: -83.9122\n", + "Current minimum: -87.1918\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2298\n", - "Function value obtained: -479.0166\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2112\n", + "Function value obtained: -85.7570\n", + "Current minimum: -87.1918\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2691\n", - "Function value obtained: -476.7967\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4107\n", + "Function value obtained: -82.9332\n", + "Current minimum: -87.1918\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2773\n", - "Function value obtained: -490.0617\n", - "Current minimum: -513.3998\n", + "Time taken: 1.1957\n", + "Function value obtained: -75.5497\n", + "Current minimum: -87.1918\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2703\n", - "Function value obtained: -493.9555\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2399\n", + "Function value obtained: -84.9163\n", + "Current minimum: -87.1918\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2973\n", - "Function value obtained: -487.7396\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3341\n", + "Function value obtained: -85.7154\n", + "Current minimum: -87.1918\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2287\n", - "Function value obtained: -493.3764\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3625\n", + "Function value obtained: -88.0328\n", + "Current minimum: -88.0328\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2962\n", - "Function value obtained: -495.2301\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3219\n", + "Function value obtained: -86.8834\n", + "Current minimum: -88.0328\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1916\n", - "Function value obtained: -494.6566\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3578\n", + "Function value obtained: -85.5236\n", + "Current minimum: -88.0328\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3476\n", - "Function value obtained: -494.5629\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2891\n", + "Function value obtained: -88.8933\n", + "Current minimum: -88.8933\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3886\n", - "Function value obtained: -476.8271\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3102\n", + "Function value obtained: -84.2244\n", + "Current minimum: -88.8933\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3089\n", - "Function value obtained: -454.1770\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3314\n", + "Function value obtained: -82.4454\n", + "Current minimum: -88.8933\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3821\n", - "Function value obtained: -479.4262\n", - "Current minimum: -513.3998\n", + "Time taken: 1.2334\n", + "Function value obtained: -82.1581\n", + "Current minimum: -88.8933\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3460\n", - "Function value obtained: -488.0920\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3595\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.8933\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3315\n", - "Function value obtained: -495.5999\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3186\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.8933\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3999\n", - "Function value obtained: -497.0044\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4082\n", + "Function value obtained: -78.9668\n", + "Current minimum: -88.8933\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3116\n", - "Function value obtained: -497.7739\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3325\n", + "Function value obtained: -86.3067\n", + "Current minimum: -88.8933\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3412\n", - "Function value obtained: -495.4617\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3904\n", + "Function value obtained: -81.0560\n", + "Current minimum: -88.8933\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6248\n", - "Function value obtained: -481.8066\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3399\n", + "Function value obtained: -82.6791\n", + "Current minimum: -88.8933\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4060\n", - "Function value obtained: -476.4783\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3901\n", + "Function value obtained: -6.3653\n", + "Current minimum: -88.8933\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4152\n", - "Function value obtained: -484.6194\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3662\n", + "Function value obtained: -87.1675\n", + "Current minimum: -88.8933\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4634\n", - "Function value obtained: -496.8883\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4481\n", + "Function value obtained: -85.4332\n", + "Current minimum: -88.8933\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4412\n", - "Function value obtained: -493.4366\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4340\n", + "Function value obtained: -52.2253\n", + "Current minimum: -88.8933\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5024\n", - "Function value obtained: -43.6975\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3260\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.8933\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4950\n", - "Function value obtained: -487.2044\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3548\n", + "Function value obtained: -86.3187\n", + "Current minimum: -88.8933\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4426\n", - "Function value obtained: -504.0297\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4130\n", + "Function value obtained: -83.7906\n", + "Current minimum: -88.8933\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6614\n", - "Function value obtained: -508.1937\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4170\n", + "Function value obtained: -84.1353\n", + "Current minimum: -88.8933\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6196\n", - "Function value obtained: -498.8906\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4485\n", + "Function value obtained: -83.7904\n", + "Current minimum: -88.8933\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4713\n", - "Function value obtained: -502.7833\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4173\n", + "Function value obtained: -84.7642\n", + "Current minimum: -88.8933\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4901\n", - "Function value obtained: -457.3923\n", - "Current minimum: -513.3998\n", + "Time taken: 1.3184\n", + "Function value obtained: -65.5597\n", + "Current minimum: -88.8933\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4277\n", - "Function value obtained: -495.4230\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4865\n", + "Function value obtained: -89.2098\n", + "Current minimum: -89.2098\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3866\n", - "Function value obtained: -484.4664\n", - "Current minimum: -513.3998\n", + "Time taken: 1.4974\n", + "Function value obtained: -85.0183\n", + "Current minimum: -89.2098\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4482\n", - "Function value obtained: -450.4714\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5393\n", + "Function value obtained: -83.8698\n", + "Current minimum: -89.2098\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5498\n", - "Function value obtained: -447.0368\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5302\n", + "Function value obtained: -87.2745\n", + "Current minimum: -89.2098\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5107\n", - "Function value obtained: -503.6635\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5426\n", + "Function value obtained: -84.7901\n", + "Current minimum: -89.2098\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5648\n", - "Function value obtained: -480.9978\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5858\n", + "Function value obtained: -85.0201\n", + "Current minimum: -89.2098\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5428\n", - "Function value obtained: -508.8501\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5041\n", + "Function value obtained: -78.1778\n", + "Current minimum: -89.2098\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6999\n", - "Function value obtained: -506.6400\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5008\n", + "Function value obtained: -77.2769\n", + "Current minimum: -89.2098\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6390\n", - "Function value obtained: -511.4363\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5763\n", + "Function value obtained: -77.7452\n", + "Current minimum: -89.2098\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6624\n", - "Function value obtained: -497.5874\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5668\n", + "Function value obtained: -82.0783\n", + "Current minimum: -89.2098\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6502\n", - "Function value obtained: -506.5583\n", - "Current minimum: -513.3998\n", + "Time taken: 1.7369\n", + "Function value obtained: -81.9447\n", + "Current minimum: -89.2098\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6838\n", - "Function value obtained: -513.0943\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5226\n", + "Function value obtained: -74.3187\n", + "Current minimum: -89.2098\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8091\n", - "Function value obtained: -494.3544\n", - "Current minimum: -513.3998\n", + "Time taken: 1.5942\n", + "Function value obtained: -3.8355\n", + "Current minimum: -89.2098\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8969\n", - "Function value obtained: -494.5385\n", - "Current minimum: -513.3998\n", + "Time taken: 1.6684\n", + "Function value obtained: -85.2797\n", + "Current minimum: -89.2098\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9822\n", - "Function value obtained: -495.4969\n", - "Current minimum: -513.3998\n", + "Time taken: 1.6661\n", + "Function value obtained: -71.3702\n", + "Current minimum: -89.2098\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7196\n", - "Function value obtained: -501.8062\n", - "Current minimum: -513.3998\n", + "Time taken: 1.6443\n", + "Function value obtained: -0.0000\n", + "Current minimum: -89.2098\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7021\n", - "Function value obtained: -335.6426\n", - "Current minimum: -513.3998\n", + "Time taken: 1.7330\n", + "Function value obtained: -80.8421\n", + "Current minimum: -89.2098\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7080\n", - "Function value obtained: -488.1054\n", - "Current minimum: -513.3998\n", + "Time taken: 1.7009\n", + "Function value obtained: -7.7503\n", + "Current minimum: -89.2098\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8927\n", - "Function value obtained: -489.9963\n", - "Current minimum: -513.3998\n", + "Time taken: 1.6462\n", + "Function value obtained: -78.0483\n", + "Current minimum: -89.2098\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7363\n", - "Function value obtained: -488.8647\n", - "Current minimum: -513.3998\n", + "Time taken: 1.8061\n", + "Function value obtained: -81.7959\n", + "Current minimum: -89.2098\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8983\n", - "Function value obtained: -511.9136\n", - "Current minimum: -513.3998\n", + "Time taken: 1.7677\n", + "Function value obtained: -88.2391\n", + "Current minimum: -89.2098\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8238\n", - "Function value obtained: -503.3750\n", - "Current minimum: -513.3998\n", + "Time taken: 1.7579\n", + "Function value obtained: -88.6091\n", + "Current minimum: -89.2098\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8622\n", - "Function value obtained: -502.9744\n", - "Current minimum: -513.3998\n", - "CPU times: user 5min 51s, sys: 34min 47s, total: 40min 38s\n", - "Wall time: 2min 10s\n" + "Time taken: 1.7046\n", + "Function value obtained: -82.8556\n", + "Current minimum: -89.2098\n", + "CPU times: user 5min 28s, sys: 32min 33s, total: 38min 2s\n", + "Wall time: 2min 8s\n" ] }, { "data": { "text/plain": [ - "(-513.3997923114888,\n", - " [0.3467172508239331, 0.12349136947209918, 0.4543957127238083])" + "(-89.20981597465533,\n", + " [-1.7637732817759972, 0.7853961999069485, 0.29606695833461205])" ] }, "execution_count": 97, @@ -2386,13 +2179,7 @@ "cell_type": "code", "execution_count": 98, "id": "faa3ef2e-e477-401d-b663-3e10e15d2023", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, + "metadata": {}, "outputs": [ { "data": { @@ -2406,7 +2193,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -2424,10 +2211,6 @@ "execution_count": 99, "id": "44a0bbe7-8c66-44aa-a01f-8dc8c3e17f61", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -2443,7 +2226,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -2470,513 +2253,513 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8759\n", - "Function value obtained: -233.1128\n", - "Current minimum: -233.1128\n", + "Time taken: 0.8555\n", + "Function value obtained: -82.0494\n", + "Current minimum: -82.0494\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8044\n", - "Function value obtained: -307.0875\n", - "Current minimum: -307.0875\n", + "Time taken: 0.8180\n", + "Function value obtained: -27.8807\n", + "Current minimum: -82.0494\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.7951\n", - "Function value obtained: -412.8523\n", - "Current minimum: -412.8523\n", + "Time taken: 0.8761\n", + "Function value obtained: -20.9274\n", + "Current minimum: -82.0494\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8084\n", - "Function value obtained: -338.3821\n", - "Current minimum: -412.8523\n", + "Time taken: 0.8165\n", + "Function value obtained: -83.8672\n", + "Current minimum: -83.8672\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8783\n", - "Function value obtained: -424.7119\n", - "Current minimum: -424.7119\n", + "Time taken: 0.8392\n", + "Function value obtained: -58.3317\n", + "Current minimum: -83.8672\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.7928\n", - "Function value obtained: -203.1513\n", - "Current minimum: -424.7119\n", + "Time taken: 0.8122\n", + "Function value obtained: -75.1273\n", + "Current minimum: -83.8672\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.9477\n", - "Function value obtained: -56.8296\n", - "Current minimum: -424.7119\n", + "Time taken: 0.8032\n", + "Function value obtained: -29.1520\n", + "Current minimum: -83.8672\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.7769\n", - "Function value obtained: -503.4267\n", - "Current minimum: -503.4267\n", + "Time taken: 0.8224\n", + "Function value obtained: -75.0358\n", + "Current minimum: -83.8672\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.7798\n", - "Function value obtained: -231.2070\n", - "Current minimum: -503.4267\n", + "Time taken: 0.7970\n", + "Function value obtained: -0.0000\n", + "Current minimum: -83.8672\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 0.9929\n", - "Function value obtained: -484.0746\n", - "Current minimum: -503.4267\n", + "Time taken: 1.0994\n", + "Function value obtained: -2.3324\n", + "Current minimum: -83.8672\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0217\n", - "Function value obtained: -417.6312\n", - "Current minimum: -503.4267\n", + "Time taken: 1.1198\n", + "Function value obtained: -82.1685\n", + "Current minimum: -83.8672\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0202\n", - "Function value obtained: -500.1832\n", - "Current minimum: -503.4267\n", + "Time taken: 1.1385\n", + "Function value obtained: -68.2328\n", + "Current minimum: -83.8672\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0544\n", - "Function value obtained: -0.0000\n", - "Current minimum: -503.4267\n", + "Time taken: 1.0531\n", + "Function value obtained: -87.7303\n", + "Current minimum: -87.7303\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0568\n", - "Function value obtained: -504.8582\n", - "Current minimum: -504.8582\n", + "Time taken: 1.1378\n", + "Function value obtained: -80.4829\n", + "Current minimum: -87.7303\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0988\n", - "Function value obtained: -504.6257\n", - "Current minimum: -504.8582\n", + "Time taken: 1.1361\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.7303\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0208\n", - "Function value obtained: -395.6925\n", - "Current minimum: -504.8582\n", + "Time taken: 1.1869\n", + "Function value obtained: -85.6731\n", + "Current minimum: -87.7303\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0912\n", - "Function value obtained: -346.6311\n", - "Current minimum: -504.8582\n", + "Time taken: 1.1151\n", + "Function value obtained: -68.5814\n", + "Current minimum: -87.7303\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1218\n", - "Function value obtained: -477.6310\n", - "Current minimum: -504.8582\n", + "Time taken: 1.2229\n", + "Function value obtained: -84.3523\n", + "Current minimum: -87.7303\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0633\n", - "Function value obtained: -500.3590\n", - "Current minimum: -504.8582\n", + "Time taken: 1.1939\n", + "Function value obtained: -84.5253\n", + "Current minimum: -87.7303\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0645\n", - "Function value obtained: -513.5516\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1486\n", + "Function value obtained: -79.8591\n", + "Current minimum: -87.7303\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0958\n", - "Function value obtained: -495.1691\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1457\n", + "Function value obtained: -84.3700\n", + "Current minimum: -87.7303\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1352\n", - "Function value obtained: -504.2848\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1551\n", + "Function value obtained: -84.1606\n", + "Current minimum: -87.7303\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1211\n", - "Function value obtained: -459.4911\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1697\n", + "Function value obtained: -76.5916\n", + "Current minimum: -87.7303\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1139\n", - "Function value obtained: -390.4078\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1482\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.7303\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1085\n", - "Function value obtained: -505.9347\n", - "Current minimum: -513.5516\n", + "Time taken: 1.0297\n", + "Function value obtained: -62.5643\n", + "Current minimum: -87.7303\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1294\n", - "Function value obtained: -509.0020\n", - "Current minimum: -513.5516\n", + "Time taken: 1.0952\n", + "Function value obtained: -80.1087\n", + "Current minimum: -87.7303\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1306\n", - "Function value obtained: -496.0927\n", - "Current minimum: -513.5516\n", + "Time taken: 1.0540\n", + "Function value obtained: -79.2209\n", + "Current minimum: -87.7303\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1705\n", - "Function value obtained: -499.4885\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1351\n", + "Function value obtained: -76.4538\n", + "Current minimum: -87.7303\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0458\n", - "Function value obtained: -510.9051\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1745\n", + "Function value obtained: -84.9686\n", + "Current minimum: -87.7303\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0913\n", - "Function value obtained: -490.8750\n", - "Current minimum: -513.5516\n", + "Time taken: 1.0644\n", + "Function value obtained: -73.2859\n", + "Current minimum: -87.7303\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1187\n", - "Function value obtained: -499.1893\n", - "Current minimum: -513.5516\n", + "Time taken: 1.4059\n", + "Function value obtained: -83.9607\n", + "Current minimum: -87.7303\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0444\n", - "Function value obtained: -487.7983\n", - "Current minimum: -513.5516\n", + "Time taken: 1.1826\n", + "Function value obtained: -82.2966\n", + "Current minimum: -87.7303\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0989\n", - "Function value obtained: -488.6591\n", - "Current minimum: -513.5516\n", + "Time taken: 1.0995\n", + "Function value obtained: -49.7182\n", + "Current minimum: -87.7303\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1467\n", - "Function value obtained: -516.4465\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1138\n", + "Function value obtained: -87.0738\n", + "Current minimum: -87.7303\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2149\n", - "Function value obtained: -507.6791\n", - "Current minimum: -516.4465\n", + "Time taken: 1.0403\n", + "Function value obtained: -84.9800\n", + "Current minimum: -87.7303\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2537\n", - "Function value obtained: -499.6489\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1664\n", + "Function value obtained: -82.1302\n", + "Current minimum: -87.7303\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2248\n", - "Function value obtained: -495.9194\n", - "Current minimum: -516.4465\n", + "Time taken: 1.0682\n", + "Function value obtained: -2.0276\n", + "Current minimum: -87.7303\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1706\n", - "Function value obtained: -495.4624\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2282\n", + "Function value obtained: -84.5040\n", + "Current minimum: -87.7303\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2321\n", - "Function value obtained: -492.3438\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1662\n", + "Function value obtained: -78.4776\n", + "Current minimum: -87.7303\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2600\n", - "Function value obtained: -476.3084\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1560\n", + "Function value obtained: -64.3111\n", + "Current minimum: -87.7303\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3298\n", - "Function value obtained: -504.0439\n", - "Current minimum: -516.4465\n", + "Time taken: 1.0951\n", + "Function value obtained: -80.9890\n", + "Current minimum: -87.7303\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2792\n", - "Function value obtained: -475.7052\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1764\n", + "Function value obtained: -84.7831\n", + "Current minimum: -87.7303\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2487\n", - "Function value obtained: -4.5003\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2259\n", + "Function value obtained: -86.9937\n", + "Current minimum: -87.7303\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3283\n", - "Function value obtained: -512.0985\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2247\n", + "Function value obtained: -82.5205\n", + "Current minimum: -87.7303\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4956\n", - "Function value obtained: -513.6646\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1729\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.7303\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3218\n", - "Function value obtained: -502.0291\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1083\n", + "Function value obtained: -85.2571\n", + "Current minimum: -87.7303\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2947\n", - "Function value obtained: -502.3735\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2374\n", + "Function value obtained: -81.2485\n", + "Current minimum: -87.7303\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3929\n", - "Function value obtained: -501.0830\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2915\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.7303\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2471\n", - "Function value obtained: -498.8909\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2097\n", + "Function value obtained: -85.7873\n", + "Current minimum: -87.7303\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3721\n", - "Function value obtained: -455.5715\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2805\n", + "Function value obtained: -81.6781\n", + "Current minimum: -87.7303\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3055\n", - "Function value obtained: -509.1090\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2983\n", + "Function value obtained: -82.7063\n", + "Current minimum: -87.7303\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2473\n", - "Function value obtained: -504.7172\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3231\n", + "Function value obtained: -83.9367\n", + "Current minimum: -87.7303\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3238\n", - "Function value obtained: -496.4901\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3488\n", + "Function value obtained: -79.2575\n", + "Current minimum: -87.7303\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2955\n", - "Function value obtained: -498.1164\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3788\n", + "Function value obtained: -85.5246\n", + "Current minimum: -87.7303\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3724\n", - "Function value obtained: -487.1825\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2843\n", + "Function value obtained: -89.1864\n", + "Current minimum: -89.1864\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3903\n", - "Function value obtained: -443.5640\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3775\n", + "Function value obtained: -75.4612\n", + "Current minimum: -89.1864\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3909\n", - "Function value obtained: -504.0442\n", - "Current minimum: -516.4465\n", + "Time taken: 1.1820\n", + "Function value obtained: -80.8734\n", + "Current minimum: -89.1864\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3259\n", - "Function value obtained: -11.6978\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2727\n", + "Function value obtained: -87.1315\n", + "Current minimum: -89.1864\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2722\n", - "Function value obtained: -2.0871\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3786\n", + "Function value obtained: -48.6218\n", + "Current minimum: -89.1864\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3765\n", - "Function value obtained: -502.7847\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2821\n", + "Function value obtained: -84.0148\n", + "Current minimum: -89.1864\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4298\n", - "Function value obtained: -476.2454\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2556\n", + "Function value obtained: -89.5829\n", + "Current minimum: -89.5829\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3521\n", - "Function value obtained: -499.4191\n", - "Current minimum: -516.4465\n", + "Time taken: 1.2678\n", + "Function value obtained: -85.6779\n", + "Current minimum: -89.5829\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3929\n", - "Function value obtained: -509.7841\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3682\n", + "Function value obtained: -89.0580\n", + "Current minimum: -89.5829\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4950\n", - "Function value obtained: -507.6909\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3095\n", + "Function value obtained: -86.1623\n", + "Current minimum: -89.5829\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5223\n", - "Function value obtained: -504.1375\n", - "Current minimum: -516.4465\n", + "Time taken: 1.4135\n", + "Function value obtained: -83.1700\n", + "Current minimum: -89.5829\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5151\n", - "Function value obtained: -501.4337\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3607\n", + "Function value obtained: -87.2959\n", + "Current minimum: -89.5829\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4234\n", - "Function value obtained: -509.0546\n", - "Current minimum: -516.4465\n", + "Time taken: 1.4241\n", + "Function value obtained: -86.2028\n", + "Current minimum: -89.5829\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4756\n", - "Function value obtained: -470.3480\n", - "Current minimum: -516.4465\n", + "Time taken: 1.4970\n", + "Function value obtained: -89.1065\n", + "Current minimum: -89.5829\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4302\n", - "Function value obtained: -512.9682\n", - "Current minimum: -516.4465\n", + "Time taken: 1.4113\n", + "Function value obtained: -85.5268\n", + "Current minimum: -89.5829\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5046\n", - "Function value obtained: -508.2239\n", - "Current minimum: -516.4465\n", + "Time taken: 1.4445\n", + "Function value obtained: -82.6634\n", + "Current minimum: -89.5829\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3520\n", - "Function value obtained: -496.6860\n", - "Current minimum: -516.4465\n", + "Time taken: 1.3563\n", + "Function value obtained: -82.7298\n", + "Current minimum: -89.5829\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5156\n", - "Function value obtained: -497.0283\n", - "Current minimum: -516.4465\n", + "Time taken: 1.4265\n", + "Function value obtained: -86.5039\n", + "Current minimum: -89.5829\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4678\n", - "Function value obtained: -485.8158\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5006\n", + "Function value obtained: -80.6437\n", + "Current minimum: -89.5829\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4658\n", - "Function value obtained: -492.1256\n", - "Current minimum: -516.4465\n", + "Time taken: 1.4145\n", + "Function value obtained: -81.7166\n", + "Current minimum: -89.5829\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4276\n", - "Function value obtained: -492.6602\n", - "Current minimum: -516.4465\n", + "Time taken: 1.7114\n", + "Function value obtained: -80.1674\n", + "Current minimum: -89.5829\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5533\n", - "Function value obtained: -487.4258\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5242\n", + "Function value obtained: -32.1797\n", + "Current minimum: -89.5829\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4635\n", - "Function value obtained: -480.4005\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5228\n", + "Function value obtained: -2.7370\n", + "Current minimum: -89.5829\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6314\n", - "Function value obtained: -483.6275\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5110\n", + "Function value obtained: -70.8688\n", + "Current minimum: -89.5829\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6047\n", - "Function value obtained: -499.5568\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5334\n", + "Function value obtained: -76.3349\n", + "Current minimum: -89.5829\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4426\n", - "Function value obtained: -475.6688\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5702\n", + "Function value obtained: -88.7394\n", + "Current minimum: -89.5829\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7155\n", - "Function value obtained: -497.6063\n", - "Current minimum: -516.4465\n", + "Time taken: 1.6312\n", + "Function value obtained: -88.2038\n", + "Current minimum: -89.5829\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5705\n", - "Function value obtained: -509.9816\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5903\n", + "Function value obtained: -81.7246\n", + "Current minimum: -89.5829\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5857\n", - "Function value obtained: -481.8413\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5821\n", + "Function value obtained: -86.1727\n", + "Current minimum: -89.5829\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4546\n", - "Function value obtained: -502.4067\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5880\n", + "Function value obtained: -0.0000\n", + "Current minimum: -89.5829\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5303\n", - "Function value obtained: -475.5580\n", - "Current minimum: -516.4465\n", + "Time taken: 1.6344\n", + "Function value obtained: -82.8846\n", + "Current minimum: -89.5829\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5645\n", - "Function value obtained: -482.2570\n", - "Current minimum: -516.4465\n", + "Time taken: 1.6308\n", + "Function value obtained: -80.8315\n", + "Current minimum: -89.5829\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6686\n", - "Function value obtained: -487.1464\n", - "Current minimum: -516.4465\n", + "Time taken: 1.6460\n", + "Function value obtained: -84.9013\n", + "Current minimum: -89.5829\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7093\n", - "Function value obtained: -498.6504\n", - "Current minimum: -516.4465\n", + "Time taken: 1.5901\n", + "Function value obtained: -77.6854\n", + "Current minimum: -89.5829\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6878\n", - "Function value obtained: -500.6579\n", - "Current minimum: -516.4465\n", + "Time taken: 1.7287\n", + "Function value obtained: -78.7553\n", + "Current minimum: -89.5829\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7178\n", - "Function value obtained: -503.6822\n", - "Current minimum: -516.4465\n", + "Time taken: 1.6824\n", + "Function value obtained: -2.2109\n", + "Current minimum: -89.5829\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7264\n", - "Function value obtained: -492.6878\n", - "Current minimum: -516.4465\n", + "Time taken: 1.7875\n", + "Function value obtained: -88.9535\n", + "Current minimum: -89.5829\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7623\n", - "Function value obtained: -473.5731\n", - "Current minimum: -516.4465\n", + "Time taken: 1.7372\n", + "Function value obtained: -85.3073\n", + "Current minimum: -89.5829\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8100\n", - "Function value obtained: -506.3473\n", - "Current minimum: -516.4465\n", + "Time taken: 1.6662\n", + "Function value obtained: -84.7486\n", + "Current minimum: -89.5829\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6605\n", - "Function value obtained: -240.6829\n", - "Current minimum: -516.4465\n", + "Time taken: 1.6876\n", + "Function value obtained: -87.9872\n", + "Current minimum: -89.5829\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8061\n", - "Function value obtained: -489.8163\n", - "Current minimum: -516.4465\n", + "Time taken: 1.7000\n", + "Function value obtained: -87.0723\n", + "Current minimum: -89.5829\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7793\n", - "Function value obtained: -455.7926\n", - "Current minimum: -516.4465\n", + "Time taken: 1.7661\n", + "Function value obtained: -85.2508\n", + "Current minimum: -89.5829\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6722\n", - "Function value obtained: -486.7914\n", - "Current minimum: -516.4465\n", + "Time taken: 1.8248\n", + "Function value obtained: -86.0122\n", + "Current minimum: -89.5829\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7796\n", - "Function value obtained: -434.7148\n", - "Current minimum: -516.4465\n", + "Time taken: 1.8281\n", + "Function value obtained: -84.9965\n", + "Current minimum: -89.5829\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8419\n", - "Function value obtained: -496.4754\n", - "Current minimum: -516.4465\n", + "Time taken: 1.8010\n", + "Function value obtained: -90.3341\n", + "Current minimum: -90.3341\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9441\n", - "Function value obtained: -514.5396\n", - "Current minimum: -516.4465\n", - "CPU times: user 6min 16s, sys: 36min 44s, total: 43min 1s\n", - "Wall time: 2min 12s\n" + "Time taken: 1.8328\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.3341\n", + "CPU times: user 5min 42s, sys: 33min 45s, total: 39min 28s\n", + "Wall time: 2min 10s\n" ] }, { "data": { "text/plain": [ - "(-516.4464921212091,\n", - " [0.4235963298591771, 0.10683989693940918, 0.5989144263953697])" + "(-90.33409885861906,\n", + " [-1.7507018612191905, 0.7853961999069485, 0.23877043334814907])" ] }, "execution_count": 100, @@ -3010,7 +2793,7 @@ }, { "data": { - "image/png": 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RkcS2/Px88Pl82NcaAra3t8eDBw/UXqMijIyMpH62Hz58CFu6igMhhLCKesgAREREwNLSUnxzcXFhuyTCIhcXF4nPQ0REBNslqcTo0aOxatUqVFVVAQA4HA7S09OxcOFCjBs3juXqCCFEt1EgA7B48WIUFRWJbxkZGWyXRFiUkZEh8XmQNuHdxsYG+vr6yMvLk9iel5cHBweHpipVLhs2bEBpaSns7Ozw6tUrDBo0CO7u7jA3N8fatWvZLo8QQnQaDVlC+pCU1jExAXr2FN6TBllYWMDCwqLBfbhcLnx8fBATEyNecFUgECAmJgZz5sxpgirlZ2lpibNnz+LSpUtITExEaWkpvL29JebBEUIIYQcFMl3RuTNAl8ZRqbCwMEyZMgW+vr7o3bs3oqKiUFZWhqlTp7JdWoP69++P/v37s10GIYSQGiiQEaKgCRMm4Pnz51i+fDlyc3Ph5eWFU6dO1Znoz6bvv/9e5n0/++wzNVZCCCGkIRyGYRi2i9A0xcXFsLS0RFFRUaNDV83GrVtAnz7A1avCoUtShzb+3Nu1ayfx+Pnz5ygvL4eVlRUA4cr9LVq0gJ2dHZ48ecJChYQQQgCa1K87GAaorBTeE52Rmpoqvq1duxZeXl5ISkrCixcv8OLFCyQlJcHb2xurV69mu1RCCNFpFMgI0RHLli3D5s2b0alTJ/G2Tp064bvvvsPSpUtZrIwQQggFMkJ0RE5ODqqrq+ts5/P5dZbvIIQQ0rQokBGiI9544w189NFHiK9xtm1cXBw++eQTWvqCEEJYRoFMV3TuDNy9K7wnOmnXrl1wcHCAr6+veO293r17w97eHjt27GC7PEII0Wl0lqUU2ni2HWmcrvzcHz58KL7epoeHBzp27MhyRYQQQmgdMl3x9CmwejWwbBnQti3b1RAWdezYkUIYIYRoGApkuqKgANi5E5g1iwKZjuLz+di9ezdiYmLw7NkzCAQCiefPnz/PUmWEEEIokBGiI+bOnYvdu3dj5MiR6NatGzgcDtslEUII+Q8FMkJ0xIEDB3Do0CGMGDGC7VIIIYTUQmdZEqIjuFwu3N3d2S6DEEKIFBTIdIW9PbBokfCe6KT58+dj06ZNoBOrCSFE89CyF1LoyvIHRJK2/9zHjh2L//3vf2jZsiW6du0KQ0NDieePHDnCUmWEEEJoDpmuKCkB4uIAHx/A3JztaggLrKysMHbsWLbLIIQQIgUFMl3x6BEwZIgwlHl7s10NYcHPP//MdgmEEELqQXPICNEh1dXVOHfuHH766SeUlJQAALKzs1FaWspyZYQQotuoh4wQHfH06VMEBQUhPT0dPB4Pw4YNg7m5OSIjI8Hj8RAdHc12iYQQorOoh4wQHTF37lz4+vri5cuXMDExEW8fO3YsYmJiWKyMEEII9ZDpCkNDwNlZeE900sWLF3HlyhVwuVyJ7a6ursjKymKpKkIIIQAFMt3RvTuQmcl2FYRFAoEAfD6/zvbMzEyY05m3hBDCKhqyJERHDB8+HFFRUeLHHA4HpaWlCA8Pp8spEUIIyyiQ6Yo7d4DWrYX3RCdt2LABly9fRpcuXVBRUYGJEyeKhysjIyPZLo8QQnQaDVnqiqoqICtLeE90UuvWrZGQkIADBw4gMTERpaWlmD59OoKDgyUm+RNCCGl6FMgI0SEGBgb48MMP2S6DEEJILRTICNEhycnJ2Lx5M5KSkgAAnTt3xpw5c+Dh4cFyZYQQottoDhkhOuKPP/5At27dEBcXB09PT3h6eiI+Ph7du3fHH3/8wXZ5hBCi0zgMwzBsF6FpiouLYWlpiaKiIlhYWLBdjmrQxcUbpZU/9xrat2+P4OBgrFq1SmJ7eHg4fv31Vzx+/JilygghhFAPma4wNwcGD6YwpsNycnIwefLkOts//PBD5OTksFARIYQQEQpkuiIrC1i8WHhPdNLgwYNx8eLFOtsvXbqEAQMGsFARIYQQEZrUryvy8oB164Dx44WXUCI6Z/To0Vi4cCHi4uLQp08fAMDVq1dx+PBhrFy5EkePHpXYlxBCSNOhOWRSaOVcovh44fyxuDjA25vtajSSVv7ca9DTk61DnMPhSL3EEiGEEPWhHjKi0xiGQebLV7ie+gKXk9LZLketBAIB2yUQQgipBwWyBtzLKoK/FvaU6LrnJTxcTsnHxUf5uPI4HzlFFQAAAa+c5cqaTkVFBYyNjdkugxBCyH8okDXg6xNJOOrRGhwOh+1SlNeqFTB9uvBexzAMgwe5JTh3Pw9nk/KQmFkk8byBHgfdnC3Rw94Oq6PYqbEp8Pl8fP3114iOjkZeXh4ePnwINzc3LFu2DK6urpg+fTrbJRJCiM6iQNaAhMwi/Hk7C2N7tma7FOW1bQvs2MF2FU2GYRgk5ZTgWGI2jt/JwdMCyd6vLo4WGNDRBgPcbeHd1gotuAYoLi7GapbqbQpr167Fnj178M033yA0NFS8vVu3boiKiqJARgghLKJlLxoRceIBSnnVbJehvFevgHv3hPdaLKfoFbb8LwUBG//BiO8v4scLj/G0oBxGBnoI6GyHde90x/Ulb+DE3AFY/GZn9O9ggxZc9f5dkpaWhunTp6Ndu3YwMTFB+/btER4ejsrKSon9EhMTMWDAABgbG8PFxQXffPNNnbYOHz4MDw8PGBsbo3v37jhx4oTMdezduxfbtm1DcHAw9PX1xds9PT3x4MEDxd8gIYQQpVEPWQPatDRBZgkPm88/wuI3O7NdjnKSkrT2LMsqvgBn7+fht+vpuJSSD9F5w1wDPQztZIe3PB0x1MNO7cGrPg8ePIBAIMBPP/0Ed3d33L17F6GhoSgrK8P69esBCM/wHD58OAICAhAdHY07d+5g2rRpsLKywsyZMwEAV65cwQcffICIiAi89dZb2L9/P8aMGYP4+Hh069at0TqysrLg7u5eZ7tAIEBVVZVq3zQhhBC50LIXUoiWPzh64xE+/T0ZhvocnJw7EO52ZmyXpjgtXPYiu/AV9l9Lx8GbGXhewhNv792uJd71aY03uznA3NhQ5vaactmLb7/9Flu3bsWTJ08AAFu3bsWSJUuQm5sLLpcLAFi0aBH+/PNPce/VhAkTUFZWhmPHjonb6dOnD7y8vBAdHd3oMX18fDBv3jx8+OGHMDc3R0JCAtzc3LBq1SqcPXtW6qKxhBBCmgb1kAHg8Xjg8V7/Qi8uLgYADOpoh6EeL3H+wTMs/fMOfgvtox0T/JsxhmEQn/4Suy6l4dS9XPAFwr8nbM2N8J5va7zn64K2rUyVOobo5y9iZGQEIyMjpdqsraioCC1bthQ/jo2NxcCBA8VhDAACAwMRGRmJly9fwtraGrGxsQgLC5NoJzAwEH/++adMx1y+fDmmTJmCrKwsCAQCHDlyBMnJydi7d69EyCOEENL0aA4ZgIiICFhaWopvLi4u4udWju4KY0M9XH3yAr/HZbJYpW7jCxicupuDsT9ewbitsTh+Jwd8AQN/t1bYGuyNK4uG4stAD6XDGAC4uLhIfB4iIiJU8A5eS0lJwebNm/HRRx+Jt+Xm5sLe3l5iP9Hj3NzcBvcRPd+Yt99+G3///TfOnTsHU1NTLF++HElJSfj7778xbNgwZd4SIYQQJVEPGYDFixdL9DwUFxeLQ5lLyxb4PKAj1p18gK9PJOGNzvZoacqtrynNxeEAXK7wvhmprBbg/25l4qd/nuBJfhkA4dywsV7OCOnnis6Oqh9azMjIkBiyrK93bNGiRYiMjGywraSkJHh4eIgfZ2VlISgoCOPHj5c407GpDBgwAGfPnm3y4xJCCGkYBTI0PiQ1vX87/HkrCw9yS7D2eBI2vOfZhNWpSM+eQI1hWU3Hq+bj8M1MbL3wGFmFwjNDLYwNMNnfFSH9XGFjptohxJosLCxkmkM2f/58hISENLiPm5ub+Ovs7GwMGTIEffv2xbZt2yT2c3BwQF5ensQ20WMHB4cG9xE9TwghpPmiQCYDQ309rB3bHe9GX8Ef8ZkY5+2Mvu42bJellar4Ahy6mYEfzqeIV9C3NTfCzAFu+MCvDcyMNOcja2trC1tbW5n2zcrKwpAhQ+Dj44Off/65znUl/f39sWTJElRVVcHQUHgiwtmzZ9GpUydYW1uL94mJicHnn38uft3Zs2fh7+9f73Gtra1lnvf44sULmfYjhBCieprz203D+bS1RrBfG/x6NR0L/kjEqc8HalQ4aFRSEhAcDOzbB3TWvCU8+AIGf93OQtS5R0h/IVzE1d7CCJ8Mao/3e7eBsaF+Iy1orqysLAwePBht27bF+vXr8fz5c/Fzot6tiRMnYuXKlZg+fToWLlyIu3fvYtOmTfjuu+/E+86dOxeDBg3Chg0bMHLkSBw4cAA3b96s09tWU1RUlPjrgoICrFmzBoGBgeIQFxsbi9OnT2PZsmUqfteEEELkQcteSFHf8gelvGoEfvcvsgpfYaJfG3w9tjuLVcpJQ5e9YBgG/0t+hsiTyUjOKwEA2JhxMXuIOz5o4iCmrmUvdu/ejalTp0p9ruY/v8TERMyePRs3btyAjY0NPv30UyxcuFBi/8OHD2Pp0qVIS0tDhw4d8M0332DEiBEy1TFu3DgMGTIEc+bMkdj+ww8/4Ny5czKfrUkIIUT1KJBJ0dAv5isp+Zi44xoAYO+03hjYUbYhK9ZpYCBLyCjE1yeScC1VOFRmYWyAjwe3R0hfV1YWcW3KdcjYYGZmhtu3b9dZHDYlJQVeXl4oLS1lqTJCCCG07IWc+rrbYLJ/WwDAwj8SUVxBK5zLK7vwFeYdvI23t1zGtdQX4Bro4aOBbri4YChmDXZnbUV9bdeqVSv89ddfdbb/9ddfaKWDF50nhBBNQr/5FLDoTQ/88/A5nhaUY8XRe9j4nhfbJTUL5ZXV2HrhMbb9+wS8agEA4B1vZ3wxvBOcrExYrk77rVy5EjNmzMCFCxfg5+cHALh27RpOnTqF7du3s1wdIYToNhqylEKWoasbaS8w4adYCBjguwmeGNuzdRNXKaeXL4Fz54CAAOC/s/aaCsMwOJqQjYgTD5BbLDxzsne7llg2sgu6t7Zs0loaou1DloAwgH3//fdISkoCAHTu3BmfffaZOKARQghhBwUyKWT9xRx17iGizj1CC64+jn3aH262zfhal2pyL7sI4X/dw82nLwEALi1NsGREZwR2ddC4y1DpQiAjhBCimWgOmRI+HdoBfu1aorySjzn7b4FXzWe7pPrl5QEbNwrvm0BheSWW/XkXozZfws2nL2FiqI8vAzvh7LxBCOrmqHFhjBBCCGETBTIl6OtxsOn9nmhpysX9nGJ8fTyJ7ZLql5UFzJ8vvFcjgYDBwRvpGLrhH/xy9SkEDDDa0wnnvxiE2UPcm/V6YoQQQoi60KR+JTlYGmPDeE9M3X0De2KfopuzJcb7ujT+Qi10N6sIy/66i1vphQCAjvZmWDm6G/zb0xl8hBBCSEMokKnAEA87fPZGB3wf8whL/u8u3GxN4dO2JdtlNZmiV1XYeCZZ3CNmytXHvGEdMaWvKwz1qROWEEIIaQwFMhX5/I0OSM4txul7efjol3gcndNP65dyYBgGf93OxprjScgvFV64fLSnE5aM7Ax7C2OWqyOEEEKaDwpkKqKnx8HG97wwbusVPMgtwcxfbuLgTH+Yasr1Li0tgVGjhPcq8CivBMv/uofYJwUAADdbU6x+uxv60UXXNco777wj875HjhxRYyWEEEIaoiFpQTuYGhlg+2RfvL3lMu5mFWPmLzexc0ovzZjI3r49cPSo0s2U8arx/flH2HkxFdUCBkYGevjsjQ6YMaAdjAw04H0SCZYqCuCEEELUi9Yhk0LZ9ahuZxQiePtVlFXyMbyLPX4M9oYB23OpqqqAwkLAygowNJT75QzD4OTdXKw5dh/ZRcLFXQM62yF8VFe4tGyh2lpZQuuQEUIIYQvNuFYDLxcrbJ/iC66BHs7cz8OCPxIhELCce+/cAezshPdySnlWikk7r2PWvnhkF1WgtbUJdkz2xY4pvbQmjBFCCCFsoiFLNenb3gY/TvTGR7/G4Uh8FsAAke/2aFZnHRZXVGFzzCPsvpKGKj4DroEePh7UHrMGt9eMYVgit99//x2HDh1Ceno6KisrJZ6Lj49nqSpCCCHNJx00QwFd7PHdBC/o63Fw5FYWZu69iVeVGrya/3/4Aga/XU/HkG8vYPvFVFTxGbzhYYez8wYibFhHCmPN1Pfff4+pU6fC3t4et27dQu/evdGqVSs8efIEb775JtvlEUKITqNApmajPZ2wfbIPjA318L/k5wjecRWF5ZWNv5AFDMPgQvIzjPz+IhYfuYOCskq42Zri56m9sDOkF9q2MmW7RKKEH3/8Edu2bcPmzZvB5XKxYMECnD17Fp999hmKiorYLo8QQnQaBbImMNTDHvtm+MHC2ADx6YV4a/MlJGQUsl2WhDuZRfhw5zWE/HwDD3JLYGFsgGVvdcHpzwdiSCc7tssjKpCeno6+ffsCAExMTFBSUgIAmDRpEn777Tc2SyOEEJ1HgayJ+LRticMf90Wbli2Q+fIV3o2+gj1X0tBkJ7l6egJFRcL7Gu5lFyF0702M+uESLqcUgKuvhxn92+HfBUMwvX+7ZjXnjTTMwcEBL168AAC0adMGV69eBQCkpqY23eeQEEKIVDSpvwl1cjDHsc/6Y8HhRJy6l4vwo/dw8dHzplk6Ql8fqLGUQ9zTF9j27xOcvpcHANDjAG97OSNsWEc6c1JLDR06FEePHkXPnj0xdepUzJs3D7///jtu3rwp1wKyhBBCVI/WIZNC3etRMQyDny+n4esTSeLFVWcPccfMgW7qmzD/6BEEs2fj4mfh2JQOxP93AXAOBxjVwwmfvdEB7nZm6jl2M6Ht65AJBAIIBAIYGAj/Djtw4ACuXLmCDh064KOPPgKXy2W5QkII0V0UyKRoql/MD/NKsPyvu7j6RDiM5GxlgpC+rpjQ2wUWxvIv3lqflGcl+OfAGUyf+y5GTonCPQd3cPX1MKanE0IHuKGDvbnKjtWcaXsgI4QQorloyJJFHe3N8VtoH/ydmIO1x+8jq/AV1p5IQtS5hxjn0xpBXR3g69oSXAP55nFV8wVIzCrCuft5OJeUh4d5peiam4npAKxacDFniDsm920LO3O6ALi2S0xMRLdu3aCnp4fExMQG9+3Ro0cTVUUIIaQ26iGTgo2ekooqPv68lYVdl1PxMK9UvN3MyAB927dCZ0cLuNmawrWVKcyMDWCopwd9fQ6KX1Uhr7gCecUVSHlWioSMItzJKsKrqtfrnenrcTDFqADLV0xG1fUbMOzl2yTvqbnRxh4yPT095Obmws7ODnp6euBwOFIn8HM4HPD5mr9GHiGEaCvqIdMQxob6eL93G0zo5YKLj/JxNCEbF5KfIb+0Emfu5+HM/Ty52jM3NsCgjrYY1sUegzvawfLBHWAF6KxJHZOamgpbW1vx14QQQjQTBTINw+FwMLCjLQZ2tIVAwOBudhFiHxcgNb8MT/LL8LSgDK8q+eALGFQJGJhy9WFvYQwHS2O4WLdAj9aW8HKxQntbM+jpcV437OIC/PCD8J7ojLZt24q/fvr0Kfr27Sue1C9SXV2NK1euSOxLCCGkadGQpRTaOHRFGqftP3d9fX3k5OTAzk5yod+CggLY2dnRkCUhhLCIxq90xYsXwK+/Cu+JTmIYBhwOp872goICmJrSZbEIIYRNNGSpK9LSgEmTgLg4oGVLtqshTUi06CuHw0FISAiMjIzEz/H5fCQmJoovqUQIIYQdFMgI0XKWlpYAhD1k5ubmMDExET/H5XLRp08fhIaGslUeIYQQUCAjROv9/PPP4qUuNm/eDDMz3b4iAyGEaCKaQ0aIDmAYBvv27UNOTg7bpRBCCJGCApmuMDUF+vQR3hOdo6enhw4dOqCgoIDtUgghhEhBgUxXdOoExMYK74lOWrduHb788kvcvXuX7VIIIYTUQuuQSaHt61ER6bT9525tbY3y8nJUV1eDy+VKTO4HgBe0JAohhLCGJvXrivh4wMdHuOyFtzfb1egsHo8HPz8/JCQk4NatW/Dy8hI/l5iYiNmzZ+PGjRuwtbXFp59+igULFki8/vDhw1i2bBnS0tLQoUMHREZGYsSIETIdOyoqSoXvhBBCiCpRICOkCS1YsABOTk5ISEiQ2F5cXIzhw4cjICAA0dHRuHPnDqZNmwYrKyvMnDkTAHDlyhV88MEHiIiIwFtvvYX9+/djzJgxiI+PR7du3Ro99pQpU9TyngghhCiP5pAR0kROnjyJM2fOYP369XWe27dvHyorK7Fr1y507doV77//Pj777DNs3LhRvM+mTZsQFBSEL7/8Ep07d8bq1avh7e2NH374Qe5aKioqUFxcLHEjhBDCHgpkEA4j0S8nIlL7s8Dj8ZRuMy8vD6Ghofjll1/QokWLOs/HxsZi4MCB4HK54m2BgYFITk7Gy5cvxfsEBARIvC4wMBCxsbEy1VBWVoY5c+bAzs4OpqamsLa2lrgRQghhDwUyABEREbC0tBTfXFxc2C6JsMjFxUXi8xAREaFUewzDICQkBB9//DF8fX2l7pObmwt7e3uJbaLHubm5De4jer4xCxYswPnz57F161YYGRlhx44dWLlyJZycnLB371553xYhhBAVojlkABYvXoywsDDx4+LiYu0LZV26AI8eAa1bs12JxsvIyJA4y7LmtR9rWrRoESIjIxtsKykpCWfOnEFJSQkWL16s0jrl9ffff2Pv3r0YPHgwpk6digEDBsDd3R1t27bFvn37EBwczGp9hBCiyyiQQfgLt75fulrD2Bhwd2e7imbBwsJCpmUv5s+fj5CQkAb3cXNzw/nz5xEbG1vnM+br64vg4GDs2bMHDg4OyMvLk3he9NjBwUF8L20f0fONefHiBdzc3AAI36NomYv+/fvjk08+kakNQggh6kGBTFekpgLLlgGrVwPt2rFdjVawtbWFra1to/t9//33WLNmjfhxdnY2AgMDcfDgQfj5+QEA/P39sWTJElRVVcHQ0BAAcPbsWXTq1Ek8v8vf3x8xMTH4/PPPxW2dPXsW/v7+MtXr5uaG1NRUtGnTBh4eHjh06BB69+6Nv//+G1ZWVjK+a0IIIepAc8h0xcuXwL59wnvSpNq0aYNu3bqJbx07dgQAtG/fHq3/G0KeOHEiuFwupk+fjnv37uHgwYPYtGmTxFD63LlzcerUKWzYsAEPHjzAihUrcPPmTcyZM0emOqZOnSpebmPRokXYsmULjI2NMW/ePHz55ZcqfteEEELkQT1khGgAS0tLnDlzBrNnz4aPjw9sbGywfPly8RpkANC3b1/s378fS5cuxVdffYUOHTrgzz//lGkNMgCYN2+e+OuAgAA8ePAAcXFxcHd3R48ePVT+ngghhMiOLp0khVZeQodW6m+UVv7cAQgEAnz77bc4evQoKisr8cYbbyA8PLzOpZMIIYSwh3rIpBBlVK1aj6y09PW9Nr0vFRL9vLXtb5S1a9dixYoVCAgIgImJCTZt2oRnz55h165dbJdGCCHkP9RDJkVmZqb2LXtBZJaRkSGe26UNOnTogC+++AIfffQRAODcuXMYOXIkXr16BT09mkZKCCGagAKZFAKBANnZ2TA3NweHw2G7HNJEGIZBSUkJnJyctCqoGBkZISUlReKPDGNjY6SkpGhV8CSEkOaMhiyl0NPTo19UOsrS0pLtElSuuroaxsbGEtsMDQ1RVVXFUkWEEEJqo0BGiJYTXbqp5sK0FRUV+Pjjj2FqaireduTIETbKI4QQAgpkhGi9KVOm1Nn24YcfslCJdBcuXMCQIUPw8uVLWqCWEKKzKJARouV+/vlntkuQMHjwYHh5eSEqKkql7XI4HPzf//0fxowZo9J2CSGkKWjPzGVCCCGEkGaKAhkhpMmEhITgn3/+waZNm8DhcMDhcJCWlgYAiIuLg6+vL1q0aIG+ffsiOTlZ4rV//fUXvL29YWxsDDc3N6xcuRLV1dUAAFdXVwDA2LFjweFwxI8fP36Mt99+G/b29jAzM0OvXr1w7ty5pnq7hBAiMwpkhJAms2nTJvj7+yM0NBQ5OTnIyckRL8exZMkSbNiwATdv3oSBgQGmTZsmft3FixcxefJkzJ07F/fv38dPP/2E3bt3Y+3atQCAGzduABAOz+bk5Igfl5aWYsSIEYiJicGtW7cQFBSEUaNGIT09vYnfOSGENIzWISOENKnac8hEk/rPnTuHN954AwBw4sQJ8eK1xsbGCAgIwBtvvIHFixeL2/n111+xYMECZGdnA5B9Dlm3bt3w8ccfy3xRdkIIaQo0qZ8QohFqXuDc0dERAPDs2TO0adMGCQkJuHz5srhHDAD4fD4qKipQXl6OFi1aSG2ztLQUK1aswPHjx5GTk4Pq6mq8evWKesgIIRqHAhkhRCMYGhqKvxZdIUMgEAAQBquVK1finXfeqfO62ove1vTFF1/g7NmzWL9+Pdzd3WFiYoJ3330XlZWVKq6eEEKUQ4GMENKkuFwu+Hy+XK/x9vZGcnIy3N3d693H0NCwTruXL19GSEgIxo4dC0AY7EQnERBCiCahQEYIaVKurq64du0a0tLSYGZmJu4Fa8jy5cvx1ltvoU2bNnj33Xehp6eHhIQE3L17F2vWrBG3GxMTg379+sHIyAjW1tbo0KEDjhw5glGjRoHD4WDZsmUyHY8QQpoanWVJCGlSX3zxBfT19dGlSxfY2trKNJ8rMDAQx44dw5kzZ9CrVy/06dMH3333Hdq2bSveZ8OGDTh79ixcXFzQs2dPAMDGjRthbW2Nvn37YtSoUQgMDIS3t7fa3hshhCiKzrIkhBBCCGEZ9ZARQgghhLCMAhkhhBBCCMsokBFCCCGEsIwCGSGEEEIIyyiQEUIIIYSwjAIZITpiy5YtcHV1hbGxMfz8/HD9+vV697137x7GjRsHV1dXcDgc8XUna1qxYgU4HI7EzdDQUKb2jxw5Al9fX1hZWcHU1BReXl745ZdfJPZhGAbLly+Ho6MjTExM0KlTJ7Ru3Vqm9ms6cOAAOBxOnWtchoSE1KnfxMRE5vYLCwsxe/ZsODo6wsjICB07dsSJEyck9qn5PXd1dYWTk5NM7Q8ePLhObRwOByNHjmyw/qCgIJm+J4QQzUOBjBAdcPDgQYSFhSE8PBzx8fHw9PREYGAgnj17JnX/8vJyuLm5Yd26dXBwcKi33a5duyInJwfR0dHgcrnYsGGDTO23bNkSS5YsQWxsLBITEzF16lRMnToVp0+fFu/zzTff4Pvvv0d0dDRWrlyJlJQU8Hg8xMbGNtq+SFpaGr744gsMGDBA6vNBQUES9X/77bcy1V9ZWYlhw4YhLS0Nv//+O5KTk7F9+3Y4OzuL96n5PV+7di0yMjJQWFiIs2fPNtr+kSNHkJOTI77dvXsX+vr6GD9+vNT6Rbfffvutwe8HIUSDMYQQrde7d29m9uzZ4sd8Pp9xcnJiIiIiGn1t27Ztme+++67O9vDwcMbT01Pp9kV69uzJLF26lGEYhhEIBIyDgwPz7bffitsPDQ1ljIyMmN9++02m9qurq5m+ffsyO3bsYKZMmcK8/fbbEs/X3CZv/Vu3bmXc3NyYysrKeo9fs83evXszs2bNErcp7/fnu+++Y8zNzZnS0lKp9RNCmj/qISNEy1VWViIuLg4BAQHibXp6eggICEBsbKxSbT969AiOjo64fv06EhMTxavuy9M+wzCIiYlBcnIyBg4cCABITU1Fbm4uAgICxPWPGDECfn5+iI2Nlan9VatWwc7ODtOnT693nwsXLsDW1hbXr19HSkoKCgoKZKr/6NGj8Pf3x+zZs2Fvb49u3brh66+/Fl9Ls+b3XPT1sGHDxG3K+/3fuXMn3n//fZiamtap387ODp06dcInn3wirp8Q0vxQICNEy+Xn54PP58Pe3l5iu729PXJzcxVu18/PD7t37xbP/Xr58iUGDBiAkpISmdovKiqCmZkZuFwuRo4cic2bN2PYsGEAIH6dvb29RP0122yo/UuXLmHnzp3Yvn17vccPCgrC3r17ceDAAQDAgwcP8Oabb4pDVUPtP3nyBL///jv4fD5OnDiBZcuWYcOGDeLratasWZH6a7p+/Tru3r2LGTNmSK0/JiYGkZGR+OeffyTqJ4Q0L3RxcUKIQt58800AQHZ2NgDhtSTHjx+PQ4cONdgrJWJubo7bt2+jtLQUMTExCAsLg5ubGwYPHqxUXSUlJZg0aRK2b98OGxubevd7//33Jepfv349xo8fjwsXLuCNN95o8BgCgQB2dnbYtm0b9PX14ePjg6ysLHz77bcIDw9Xqv7adu7cie7du6N3795S6weA7t27o0ePHmjfvr1M9RNCNA8FMkK0nI2NDfT19ZGXlyexPS8vr8EJ+/K2X15ejo4dOyIlJUWm9vX09ODu7g4A8PLyQlJSEiIiIjB48GDx6/Ly8tClSxdx/Xl5efDy8mqw/cePHyMtLQ2jRo0SbxMIBAAAAwMDJCcno3379nXqNzAwgI2NDVJSUvDGG280WL+joyMMDQ2hr68v3ta5c2fk5uaisrJS4nvu4+MjUX/N99bY97+srAwHDhzAqlWrGtwPANzc3CTqJ4Q0LzRkSYiW43K58PHxQUxMjHibQCBATEwM/P39Vdb+qVOn8PjxYzg6OirUvkAgAI/HAwC0a9cODg4OiImJEbd/8uRJXLt2Df7+/g227+HhgTt37uD27dvi2+jRozFkyBDcvn0bLi4uUuv/66+/UFBQIFP9/fr1Q0pKijjoAcDDhw/h6OgILpcr8T0XfX3u3Dlxm7J+fw4fPgwej4cPP/yw0e9fZmamuH5CSDPE9lkFhBD1O3DgAGNkZMTs3r2buX//PjNz5kzGysqKyc3NZRiGYSZNmsQsWrRIvD+Px2Nu3brF3Lp1i3F0dGS++OIL5tatW8yjR4/E+8yfP5+5cOECk5qayqxcuZLR09NjzMzMmEuXLjXa/tdff82cOXOGefz4MXP//n1m/fr1jIGBAbN9+3bxPuvWrWOsrKyYv/76i/nmm28YPT09xsbGhrl161aj7ddW+4zEkpIS5osvvmBiY2OZ1NRUZsmSJQyHw2Hs7e2Z27dvN9p+eno6Y25uzsyZM4dJTk5mjh07xtjZ2TFr1qyR+j3fsGEDo6+vz7Ro0YL5999/Za6/f//+zIQJE+psr13/uXPnGG9vb6ZDhw5MRUVFvd8HQojmoiFLQnTAhAkT8Pz5cyxfvhy5ubnw8vLCqVOnxBP909PToaf3usM8OzsbPXv2FD9ev3491q9fj0GDBuHChQsAhD0yH3zwAQoKCmBrawsvLy/k5uZi6NChjbZfVlaGWbNmITMzEyYmJvDw8MCvv/6KCRMmiPdZsGABysrKMHPmTBQWFsLd3R2lpaXw8/NrtP3G6OvrIzExEXv27EFhYSGcnJzg7++Pp0+fonfv3o227+LigtOnT2PevHno0aMHnJ2dMXfuXCxcuLDe73nr1q3B4/EQEBAgU/3Jycm4dOkSzpw5I1P9w4cPx+rVq2FkZCTz94EQojk4DMMwbBdBCCGEEKLLaA4ZIYQQQgjLKJARQgghhLCMAhkhhBBCCMsokBFCCCGEsIwCGSGEEEIIyyiQEUIIIYSwjAIZIYQQQgjLKJARQqTi8XhYsWKF+HJG1L52tU8I0Sy0MCwhRKri4mJYWlqiqKgIFhYW1L6Wta/JqqurceHCBTx+/BgTJ06Eubk5srOzYWFhATMzM7bLI0Qt6NJJhBBCNMbTp08RFBSE9PR08Hg8DBs2DObm5oiMjASPx0N0dDTbJRKiFjRkSQghRGPMnTsXvr6+ePnyJUxMTMTbx44di5iYGBYrI0S9qIdMCoFAgOzsbJibm4PD4bBdDmkiDMOgpKQETk5Ocl2omi3q/pwWFxdL3FP77Lff3D6jirh48SKuXLkCLpcrsd3V1RVZWVksVUWI+lEgkyI7OxsuLi5sl0FYkpGRgdatW7NdRqOa6nOq7mNQ+/K331w+o4oQCATg8/l1tmdmZsLc3JyFighpGhoRyLZs2YJvv/0Wubm58PT0xObNm9G7d2+p+w4ePBj//PNPne0jRozA8ePHAQAhISHYs2ePxPOBgYE4deqUTPXU/EdvY9Yeni5j6uzDc1T+P4ZXtoZKtyEvk+dVAIDs9Fg8STkt3u7mHginNv4qOYZRTolK2mlU9jOVNZXOu49HFXEA0Gz+0xfVmZGRoXOTvnVVcXExXFxcms1nVBHDhw9HVFQUtm3bBgDgcDgoLS1FeHg4RowYwXJ1hKgP64Hs4MGDCAsLQ3R0NPz8/BAVFYXAwEAkJyfDzs6uzv5HjhxBZWWl+HFBQQE8PT0xfvx4if2CgoLw888/ix8bGRnJXJNo+MfGrD16thlfZ2iA52Sh8Deu3P51CNNXsA1lVDobAwBaOQ2Dnr4higrTYWnVBs5t+qls2IvvIjyGUbZ6hnLERD0HmXlKN9XOyBMA8KgirtkMU4vqtLCwUDyQPX8OHDoEvPceYGurwuqIOjWXz6giNmzYgMDAQHTp0gUVFRWYOHEiHj16BBsbG/z2229sl0eI2rC+7IWfnx969eqFH374AYCwu9rFxQWffvopFi1a1Ojro6KisHz5cuTk5MDU1BSAsIessLAQf/75p0I1iU43f6PzfBjovw5yPCfFeyFqBjFN1CKvSi3tqj2U1aRkMKtmKhFT9EuzWWZAJcsixMcDPj5AXBzg7a3aAonK6cpSGNXV1Th48CASEhJQWloKb29vBAcHS0zyJ0TbsNpDVllZibi4OCxevFi8TU9PDwEBAYiNjZWpjZ07d+L9998XhzGRCxcuwM7ODtbW1hg6dCjWrFmDVq1aSW2Dx+NJLL4obZKuomFM04OYiKhOVQcz0fetSYJZa3vhvQp6zAgh7DEwMEBwcDCCg4PZLoWQJsPqaTr5+fng8/mwt7eX2G5vb4/c3NxGX3/9+nXcvXsXM2bMkNgeFBSEvXv3IiYmBpGRkfjnn3/w5ptvSp0oCgARERGwtLQU32pPolUkjJXbG6otjDEMg9ykf5Hy717kJv0LVXZyqqtunpOFUj2Mcmlt//pGCGlWIiIisGvXrjrbd+3ahcjISBYqIqRpNOvzpnfu3Inu3bvXOQHg/fffx+jRo9G9e3eMGTMGx44dw40bN3DhwgWp7SxevBhFRUXiW0ZGhvg5RcOYOuU9uIj0m3/hxdMEpN/8C3kPLqr8GOoMZk2KghkhzcpPP/0EDw+POtu7du1Ki8ISrcZqILOxsYG+vj7y8iSHmPLy8uDg4NDga8vKynDgwAFMnz690eO4ubnBxsYGKSkpUp83MjIST4yuOUFa3jMp1dkrVlPp87QGH6uSOt5Tk/aWiVCvmXTm5sDw4cJ7QjRAbm4uHB0d62y3tbVFTk4OCxUR0jRYDWRcLhc+Pj4Sqy8LBALExMTA37/hJRgOHz4MHo+HDz/8sNHjZGZmoqCgQOo/clVpiiBWbsNBuQ0HZrauEttrP1bLsdUUzFhRM5zpekDr0AE4fVp4T4gGcHFxweXLl+tsv3z5MpycnFioiJCmwfqyF2FhYZgyZQp8fX3Ru3dvREVFoaysDFOnTgUATJ48Gc7OzoiIiJB43c6dOzFmzJg6E/VLS0uxcuVKjBs3Dg4ODnj8+DEWLFgAd3d3BAYGqrx+VYaUchvZTmU37z8QDqYclOekoYWjK8x7DkB5jdPgW+Sr78RZVU/+b9JJ//URhTI+DyhirwxW8PlAWRlgagros7EQCyGSQkND8fnnn6OqqgpDhw4FAMTExGDBggWYP38+y9URoj6sB7IJEybg+fPnWL58OXJzc+Hl5YVTp06JJ/qnp6fXWQcsOTkZly5dwpkzZ+q0p6+vj8TEROzZsweFhYVwcnLC8OHDsXr1arnWIpOFKsKYrCGsJg6HAxvvgQAGytSmOgJaub2hSs/I1IhgposSEmjZC6JRvvzySxQUFGDWrFniNSeNjY2xcOFCiTPyCdE2rK9DpolEa/30H7oCBgbGUvdRJowpEsJURR3hTNVLZbAVyqr5PMQkbWg2azzROmS6R1fWIQOEox1JSUkwMTFBhw4dVP4HNSGahvUesuZI0TDGZhCrXYMqg5lWDmMSQlhlZmaGXr16sV0GIU2GApkcmnMQq61mTaoKZ+oYxqRQRohuKSsrw7p16xATE4Nnz55BIBBIPP/kyROWKiNEvSiQyUiRMKaJQUwaVfaaUW8ZIUQZM2bMwD///INJkybB0dFRq6/bSUhNFMhkIG8Yay5BrDZVBzOa9N8MdO8OPHsGWFmxXQkhAICTJ0/i+PHj6NevH9ulENKkmvVK/U1BV8JYTaL1zpRuR5vWLtNWhoaAra3wnhANYG1tjZYtW7JdBiFNjgKZiqgqxGgSVb0frVjpX1s9fgyMHi28J0QDrF69GsuXL0d5eTnbpRDSpGjIsgGvbA0hy1KZqgouFbbKvd74uUrKkKCqYUxVzy0DaBhTJYqKgL//BlasYLsSQgAAGzZswOPHj2Fvbw9XV1cY1uq9jY+PZ6kyQtSLApmSlA1jyoawhtpSZUBTZTBT9bplFMwI0R5jxoxhuwRCWEGBTAmKhjFVhjBZj6OqcFZuw9HI3jKAghkh2iA8PJztEghhBc0hU4Ci88UqbJsujKnz2Kqc9K8ONMeMkOatsLAQO3bswOLFi/HixQsAwqHKrKwslisjRH0okMmpuQWx2kS1qKIeTT0TU0QUzCicNcDZGdiwQXhPtNaWLVvg6uoKY2Nj+Pn54fr162yXVK/ExER07NgRkZGRWL9+PQoLCwEAR44coWtZEq1GgUwO8gYQTQpi0qiiPk3vLROhYFYPe3sgLEx4T7TSwYMHERYWhvDwcMTHx8PT0xOBgYF49uwZ26VJFRYWhpCQEDx69AjGxq+vJTxixAj8+++/LFZGiHpRIFMTTQ5itakqmClLnb1lItRrVsvLl8Dhw8J7opU2btyI0NBQTJ06FV26dEF0dDRatGiBXbt2sV2aVDdu3MBHH31UZ7uzszNyc3NZqIiQpsF6IJO3K72wsBCzZ8+Go6MjjIyM0LFjR5w4cUKpNmUha+DQ9F6xhuhKb5lIcwtnPB4PxcXFEjelpaYC770nvCcar7JaeF3H2p8DHo8nff/KSsTFxSEgIEC8TU9PDwEBAYiNjW2SmuVlZGQk9bP98OFD2No20/9cCZEBq4FM3q70yspKDBs2DGlpafj999+RnJyM7du3w7nG/Bd1dM/LE8aaO13qLauJ52QBnqN5kx1PEREREbC0tBTfXFxc2C6JNKFXlXx8+ptwDS4XFxeJz0JERITU1+Tn54PP58O+1pC0vb29xvY2jR49GqtWrUJVlfAsbA6Hg/T0dCxcuBDjxo1juTpC1IfVQCZvV/quXbvw4sUL/Pnnn+jXrx9cXV0xaNAgeHp6KtxmY5oyjFXZVCt8UzVlg1lz6y1rDhYvXoyioiLxLSMjg+2SSBMpqajClF3XcTmlAACQkZEh8VnQpsnuGzZsQGlpKezs7PDq1SsMGjQI7u7uMDc3x9q1a9kujxC1YW0dMlFXes3/SBrrSj969Cj8/f0xe/Zs/PXXX7C1tcXEiROxcOFC6OvrK9QmIBwKqtnlL+ouL2/FkWmlfmWCi6rCVO12DPNV86OtsFVuDTNNXresuTEyMoKRkRHbZZAm9rKsElN+vo7EzCKYGQn/R7KwsICFReND7TY2NtDX10deXp7E9ry8PDg4OKilXmVZWlri7NmzuHTpEhITE1FaWgpvb2+JYVdCtBFrgayhrvQHDx5Ifc2TJ09w/vx5BAcH48SJE0hJScGsWbNQVVWF8PBwhdoEhENBK1eulPs9KBrE1NGj1dAxlA1novepaDBTRSgDKJiphYkJ0LOn8J5onGclFfhwxzU8zCtFS1MufhzfA/6Rsr+ey+XCx8cHMTEx4hXwBQIBYmJiMGfOHPUUrSL9+/dH//792S6DkCbTrFbqFwgEsLOzw7Zt26Cvrw8fHx9kZWXh22+/VWp158WLFyMsLEz8uLi4uNH5OYqEsaYIYg0dVxXBTJlQBih/6SVAvssvMQyDrPTLKCp8CkurtnBu0w8cjnZdBF4pnTsDdG1AjZRd+ArBO64hNb8M9hZG2DfDD3bG8v/7CQsLw5QpU+Dr64vevXsjKioKZWVlmDp1qhqqVsz3338v876fffaZGishhD2sBTJFutIdHR1haGgIff3XA4mdO3dGbm4uKisrFe6el3coSN4wxlYQq00Vway59ZZlpV9GSvIxAMDzvDsAgNZt6a9uotkyXpTjg+1XkfnyFZytTLA/1A9tW5kqdGbthAkT8Pz5cyxfvhy5ubnw8vLCqVOn6owksOm7776TePz8+XOUl5fDysoKgPDs+hYtWsDOzo4CGdFarE3qr9mVLiLqSvf395f6mn79+iElJQUCgUC87eHDh3B0dASXy1WoTXXTlDBWkypOBNCECf9A42djFhU+rfU4XSXH1Rq3bgFGRsJ7ohFS88vw3k+xyHz5Cm1btcChj/3RtpWpUm3OmTMHT58+BY/Hw7Vr1+Dn56eialUjNTVVfFu7di28vLyQlJSEFy9e4MWLF0hKSoK3tzdWr17NdqmEqA2rZ1mGhYVh+/bt2LNnD5KSkvDJJ59IdKVPnjxZYoL+J598ghcvXmDu3Ll4+PAhjh8/jq+//hqzZ8+WuU1lyRpE1HX2oyopW6MqzsRUlfqCmaVV21qP26jsmFqBYYDKSuE9YV3Ks1JM+CkWOUUVaG9rikMf+cPZSrfm9y1btgybN29Gp06dxNs6deqE7777DkuXLmWxMkLUi9U5ZI11paenp0NP73VmdHFxwenTpzFv3jz06NEDzs7OmDt3LhYuXChzm8qQJ4w1J8oOZWrK3DKg7lCmc5t+AIQ9Y5ZWbcSPCdE0j/JK8MH2a8gv5aGTvTn2hfrBxkz3zqrNyclBdXXd/0P5fH6d6SiEaBMOw9CfxrUVFxfD0tISnWd9DX0j4bXUtDWM1abM/DJllscAVBfKJNqU44zM6uoKXDq/AkVFRTItKcA20edUqXrj4wEfHyAuDvD2Vm2BRGbJuSWYuP0qCsoq0dnRAvtm+KGlKbfOfir5mWu4UaNGISsrCzt27ID3f5/JuLg4zJw5E87Ozjh69CjLFRKiHs3qLEu2NGUYM271Su7XVBSobkhDmd4yVUz4B1QbzGipDKLpaoaxbs4W+HW6H6xa1A1jumLXrl3is0INDYX/fqurqxEYGIgdO3awXB0h6kOBTEUUDWOKBLCG2lBVOKuyqWZlCBNQ3ZmYEm3WmF9G4ayGzp2Bu3cBNze2K9FJtcPYvul9YNlCt69OYWtrixMnTuDhw4fi9SM9PDzQsWNHlisjRL0okDVClt4xRcKYKoJYY+0qG860rbdM3DaFs9dMTICuXdmuQidRGGtYx44dKYQRnUKBrAE8m8ZPQ5U3jKkriDV2LGXCmbb1lkm0XyOc8Sv5ajuOxnr6FFi9Gli2DGjbtvH9iUo8yqMwVh8+n4/du3cjJiYGz549k1jmCADOnz/PUmWEqBcFMiXIE8aaMog1dHxFg5myvWXKhjJAPb1lOq+gANi5E5g1iwJZE0l5VooPtl+jMFaPuXPnYvfu3Rg5ciS6detGV9YgOoMCmYKaUxirSRXBjI0hTED9vWWEqNvj56X4YPtV5Jfy0MVROIGfwpikAwcO4NChQxgxYgTbpRDSpFhdGLa5aq5hrCZl6lJmQVllFpIFVLvKPyFNKS2/DBO3X8XzEh48HMyxb4Zun01ZHy6XC3d3d7bLIKTJUSBTE+NWrzQ2jIkoWyNboQygYEaal4wX5Zi4/SryinnoaG+GfTP8YC1lnTECzJ8/H5s2bQItkUl0DQ1ZykmWEKLpQaw2ZYYx2RzCBGh+mdLs7YFFi4T3RC2yC1/hg+1Xkf3f5ZD2zeiDVjq4Ar+sLl26hP/97384efIkunbtKl6LTOTIkSMsVUaIelEgk0NTh7F2NgX1Ppea30plxxExbvVK4VAGsDPhX4SCmYKcnYGICLar0FrPiiswcftVZL58BddWLbA/tA9szSmMNcTKygpjx45luwxCmhwFMhVSNow1FMAa21dVAa0595YBFMzkVlIivGySjw9gbs52NVqloJSH4B3XkFZQjtbWJtgf2gf2FsZsl6Xxfv75Z7ZLIIQVCgWyzMxMHD16FOnp6aisrJR4buPGjSopTNM01jumaBiTJ4TJ2o4qwpkyvWVsrVlWEwUzGT16BAwZQteyVLGi8ip8uPM6Hj0rhYOFMX4L7QMnK9Vd4kzbVVdX48KFC3j8+DEmTpwIc3NzZGdnw8LCAmZmZmyXR4hayP2bMyYmBqNHj4abmxsePHiAbt26IS0tDQzDiC8Eq23UccFwVQWxxtpWJpwp2lvG5gr/tVEwI02tpKIKk3++jqScYtiYGWF/qB9cWrZgu6xm4+nTpwgKCkJ6ejp4PB6GDRsGc3NzREZGgsfjITo6mu0SCVELuc+yXLx4Mb744gvcuXMHxsbG+OOPP5CRkYFBgwZh/PjxChWxZcsWuLq6wtjYGH5+frh+/bpMrztw4AA4HA7GjBkjsT0kJAQcDkfiFhQUpFBtspCnd6ydTYFaw5g6jqdo758yQVYVZ2LWJDork87MJOr0qpKP6btvIiGjENYtDLFvhh/cbKlHRx5z586Fr68vXr58CROT138Mjh07FjExMSxWRoh6yR3IkpKSMHnyZACAgYEBXr16BTMzM6xatQqRkZFyF3Dw4EGEhYUhPDwc8fHx8PT0RGBgIJ49e9bg69LS0vDFF19gwIABUp8PCgpCTk6O+Pbbb7/JXRug2qHKpgxi0o6tzPHZCmWqDmYAhTOiHrxqPmb+chPX017A3NgAv0z3QycHmpcnr4sXL2Lp0qXgciWXBXF1dUVWVhZLVRGifnIHMlNTU/G8MUdHRzx+/Fj8XH5+vtwFbNy4EaGhoZg6dSq6dOmC6OhotGjRArt27ar3NXw+H8HBwVi5ciXc3Nyk7mNkZAQHBwfxzdraWu7aGtNcwlhNygQzRdctq28hWYZhUHj5X+Tu34PCy//Wu+6QuoIZIBnOylvpYEAzNBSeaWlIq8Uro4ovwJz9t3DxUT5acPWxe2ovdHO2ZLusZkkgEIDPr3td2czMTJjTiSdEi8kdyPr06YNLly4BAEaMGIH58+dj7dq1mDZtGvr06SNXW5WVlYiLi0NAQMDrgvT0EBAQgNjY2Hpft2rVKtjZ2WH69On17nPhwgXY2dmhU6dO+OSTT1BQUH8I4fF4KC4ulrgBQFUr1cwd05QwVpMm9JYVXbmI/ON/ovRuAvKP/4miKxcbfL26QplO694dyMwU3hOF8AUM5h9KwNn7eeAa6GHHZF/4tG3JdlnN1vDhwxEVFSV+zOFwUFpaivDwcLqcEtFqcs+63rhxI0pLSwEAK1euRGlpKQ4ePIgOHTrIfYZlfn4++Hw+7GstSmlvb48HDx5Ifc2lS5ewc+dO3L59u952g4KC8M4776Bdu3Z4/PgxvvrqK7z55puIjY2Fvr5+nf0jIiKwcuVKuWqXNZRoYhgTEdWmyMR/VZyFWfE0VeK5ivQ0oN/ABl+v6kn/hCiDYRgs+b87OJqQDQM9DqI/9EZfdxu2y2rWNmzYgMDAQHTp0gUVFRWYOHEiHj16BBsbG4WnnhDSHMgdyGoOEZqamjbpGS8lJSWYNGkStm/fDhub+v/Te//998Vfd+/eHT169ED79u1x4cIFvPHGG3X2X7x4McLCwsSPi4uL4eLiUm/72hDGampnU6BwKAMUPwvTuG07lN5NeN1eG1eZ26BgpiJ37gBvvgmcPEm9ZHJiGAarjyXhwI0M6HGATe/3xFAPuuKBslq3bo2EhAQcOHAAiYmJKC0txfTp0xEcHCwxyZ8QbaNQILtx4wZatZL8BV5YWAhvb288efJE5rZsbGygr6+PvLw8ie15eXlwcHCos//jx4+RlpaGUaNGibcJBAIAwhMMkpOT0b59e6k129jYICUlRWogMzIygpGRalfPbiiMMQyDp38koPBONqy6O6HtOE9wOOzOX2Kjt6zFaH/YQNgzZtzGFZZ9pZ+g0RAKZkqqqgKysoT3RC7fnXuEXZeFvbzrxvXAyB6OLFekPQwMDPDhhx+yXQYhTUruQJaWliZ1wiWPx5P7DBgulwsfHx/ExMSIl64QCASIiYnBnDlz6uzv4eGBO3fuSGxbunQpSkpKsGnTpnp7tTIzM1FQUABHR+X/w5Sld6yxnrGnfyTgweZ/AQC5F1IAAK7veomf726ZLVdNd4qc5Nq/Icr0lskbyjgcDkzf7gtT9FV4MVkRCmakKW3/9wm+j3kEAFgxqgve862/R53ILzk5GZs3b0ZSUhIAoHPnzpgzZw48PDxYrowQ9ZH5t+DRo0fFX58+fRqWlq/PIOLz+YiJiYGrq6vcBYSFhWHKlCnw9fVF7969ERUVhbKyMkydOhUAMHnyZDg7OyMiIgLGxsbo1q2bxOutrKwAQLy9tLQUK1euxLhx4+Dg4IDHjx9jwYIFcHd3R2BgoNz1yUuWYcrCO5KBq/BuDrpPt1P4mDUDnCrCmaK9ZYoMYTIMg5Lzl8FLSUMLBzdY9h2gVG8hBTOibvuvpWPtCWFQ+DKwE0L6tWO5Iu3yxx9/4P3334evry/8/f0BAFevXkX37t1x4MABjBs3juUKCVEPmQOZqAeLw+FgypQpEs8ZGhrC1dUVGzZskLuACRMm4Pnz51i+fDlyc3Ph5eWFU6dOiSf6p6enQ09P9pNB9fX1kZiYiD179qCwsBBOTk4YPnw4Vq9erfSwZGO9Y7LOGbPq7iTuGQOALr6qW8VbleGsKXrLSs5fxsuDwrBfjkTwzQRo5TlY7mPWRsGMqMNft7Ow5E9hL/3Hg9pj1uC6UySIchYsWIDFixdj1apVEtvDw8OxYMECCmREa3GY+hZ/qke7du1w48aNBifVN3fFxcWwtLSEy6ZV0DN5fTFgVQUy0RwyJvkJnD1bwXuiu1rnkCkbzBS9/JIsoez5T7+iPC5R/LiFbw/YzvxQ6SFMaRoLZ3xeBZJ+/ApFRUWwsLBQ+fFVTfQ5Vapeuri4zM7dz8NHv8aBL2DwYZ82WP12tyaf+6mSn7mGa9GiBRITE+Hu7i6x/dGjR/D09ER5eTlLlRGiXnL/1ktNfb1UQUVFBYyNjRvYW3fIc0ZlD6sc9JhuB0DxYUp5iHrNFA1m6hzCNHJ3lQhkRu1dASh3Pcz6UK+ZFObmwODBbFeh8a6k5GPW/njwBQzGeDlh1eimD2O6YvDgwbh48WKdQHbp0qV6r8xCiDaQ+7edQCDA2rVrER0djby8PDx8+BBubm5YtmwZXF1dG1ystTlTdDHU2uSdsK9K3S2zleotU8cQpvnQfgAA3uM0GLV3FT8WUWcwE9enywEtKwv44Qdgzhzhiv2kjvj0l5ix9yYqqwUY3sUe68d7Qk+Pwpi6jB49GgsXLkRcXJx4sfGrV6/i8OHDWLlypcR85tGjR7NVJiEqJ/eQ5apVq7Bnzx6sWrUKoaGhuHv3Ltzc3HDw4EFERUU1uMJ+cyFtyLKhQCZr7xibYaw2ZYKZOocwG6KOYcyaBBUVeLJKx4Ys4+OFw5VxcYC3t2oL1AJJOcV4f9tVFL2qQn93G+wM8YWRQd3FpZuKLgxZyjpnmMPhSD3jn5DmSu5LJ+3duxfbtm1DcHCwxKr3np6e9a6u39ypondMk8IYIKxH0Zqa+lqYIvVdE5MQdUjNL8OknddR9KoK3m2ssG2yD6thTFcIBAKZbhTGiLaRO5BlZWXVGdsHhP+IqnRwcUlZwommhbGalAllygQzZVAwI+qWVfgKH+64hvxSHjo7WuDnqb3RgqveHlpSV0VFBdslENJk5A5kXbp0wcWLdS8C/fvvv6Nnz54qKYo0LWUCI1u9ZQAFM6Ie+aU8TNpxDVmFr+BmY4pfpveGpYkh22XpDD6fj9WrV8PZ2RlmZmbiq78sW7YMO3fuZLk6QtRH7j/5li9fjilTpiArKwsCgQBHjhxBcnIy9u7di2PHjqmjRlYpO3dMk3vHalLmTExFJ/sDil92qSZ1TPzXGa1aAdOnC+8JisqrMGnndTzJL4OzlQl+neEHGzPVXlaNNGzt2rXYs2cPvvnmG4SGhoq3d+vWDVFRUVp74hghcveQvf322/j7779x7tw5mJqaYvny5UhKSsLff/+NYcOGqaPGZktVYayX2ZM6N3VpjkOYItRjpoC2bYEdO4T3Oq6MV42Q3deRlFMMGzMj/DrDD05WunMx67S0NEyfPh3t2rWDiYkJ2rdvj/DwcFRWVkrsl5iYiAEDBsDY2BguLi745ptv6rR1+PBheHh4wNjYGN27d8eJEydkrkMX5ykTAijQQwYAAwYMwNmzZ1VdC6mhsdBV+/kbpW4qO7Yyy2MoszQGoPyZmAD1mMnl1SvgyRPAzQ0w0Z3wUVtFFR+he2/iVnohLE0M8euM3mhnY8p2WU3qwYMHEAgE+Omnn+Du7o67d+8iNDQUZWVlWL9+PQDhWZ7Dhw9HQEAAoqOjcefOHUybNg1WVlaYOXMmAODKlSv44IMPEBERgbfeegv79+/HmDFjEB8fX+fSd9LQPGWiqxT+jVVZWYlnz55BIBBIbG/Tpo3SRTUHjfUGKdrTpGjvV83XqSKcsTmECSgezGpeG9PIXbiuGYfDoXBWn6QknV/2ooovwJz9t3DlcQFMufrYM603PBy0c0mJhgQFBSEoKEj82M3NDcnJydi6das4kO3btw+VlZXYtWsXuFwuunbtitu3b2Pjxo3iQLZp0yYEBQXhyy+/BACsXr0aZ8+exQ8//IDo6OhG6xDNU25bq9eW5ikTbSf3b6lHjx5h2rRpuHLlisR2hmG0bl0Yo5avADTNlQhUOQwpaktVwaypQxmg+NwyiWtj/ncFAIs3+ksMZVI4IyJ8AYOwQwk4l5QHIwM97JjSC14uVmyXpTGKiorQsmVL8ePY2FgMHDgQXC5XvC0wMBCRkZF4+fIlrK2tERsbi7CwMIl2AgMD8eeff8p0TF2bp0yIiNy/mUJCQmBgYIBjx47B0dGRLh8ihby9Y+qaE6aqYKZMKAMUX0hWkd4yXkqa5OPHacAb/SW2NddwxuPxwOPxxI+Li4tZrKb5EwgYfHXkDv5OyIahPgfRH/rAv33zOLmh9s/eyMgIRkaqPfkgJSUFmzdvFveOAUBubi7atWsnsZ+9vb34OWtra+Tm5oq31dwnNzdXpuOK5imvWrVKPE/Z29ub5ikTrSf3b6Pbt28jLi4OHh4e6qinWVB08ro06pygX/MYbIUyQDW9ZYBsway+a2PWp2Y4E7zS7BMCIiIisHLlSrbL0AoMw2D18fs4eDMDehxg0/s9McSjaa4tqwouLi4Sj8PDw7FixQqp+y5atAiRkZENtpeUlCTxf3pWVhaCgoIwfvx4iTMdmwrNUya6SKF1yPLz81VaxJYtW+Dq6gpjY2P4+fnh+vXr9e575MgR+Pr6wsrKCqampvDy8sIvv/wisQ/DMFi+fDkcHR1hYmKCgIAAPHr0SKU110ee3rGmCGM1j6Xs8ZRd3V/ZICvL2ZjmQ/vBesJotPDtAesJo+tcG7M5W7x4MYqKisS3jIwM5RvlcAAuV3ivQ9afScbPl9MAAN+864kR3R3ZLUhOGRkZEp+FxYsX17vv/PnzkZSU1ODNze31H2zZ2dkYMmQI+vbti23btkm05eDggLy8PIltoscODg4N7iN6nhAinUw9ZDW7xyMjI7FgwQJ8/fXX6N69OwwNJRdMlPf6agcPHkRYWBiio6Ph5+eHqKgoBAYGIjk5GXZ2df9ibdmyJZYsWQIPDw9wuVwcO3YMU6dOhZ2dHQIDAwEA33zzDb7//nvs2bMH7dq1w7JlyxAYGIj79+/D2Lhp5oQ1RhVhjGEYnNzzHA/iSuHhY4Y3p9g2OoSs7b1lHA4HFm/0rzNMqQ3UMSyFnj2BGsOgumDL/1Kw5X+PAQCr3+6Kd31as1yR/CwsLGT+v9bW1ha2trYy7ZuVlYUhQ4bAx8cHP//8c53rSvr7+2PJkiWoqqoS/99/9uxZdOrUCdbW1uJ9YmJi8Pnnn4tfd/bsWfj7+9d7XGtra5mnv7x48UKm/QhpbmS6uLienp7EPxbRBP6aFJ3U7+fnh169euGHH34AIDy12cXFBZ9++ikWLVokUxve3t4YOXIkVq9eDYZh4OTkhPnz5+OLL74AIJyYam9vj927d+P9999vtD3RBXzdf1kM/RZ1A1xDPT2y9iApE8hEQezCHwVIS3rdaxSytDVGhMg+7KJsMGPjAuW1qWKZDBHBqwpkzF3ebC7crAsXmla1XZdSserYfQDAVyM8MHNge5Yrko86f+ZZWVkYPHgw2rZtiz179kisASbq3SoqKkKnTp0wfPhwLFy4EHfv3sW0adPw3XffSSx7MWjQIKxbtw4jR47EgQMH8PXXXze47MWePXvEXxcUFGDNmjUIDAwUh7jY2FicPn0ay5Ytw7x581T6vgnRFDL1kP3vf/8Tf52WlgYXFxeJf6yAMEilp6fLdfDKykrExcVJdLfr6ekhICAAsbGxjb6eYRicP38eycnJ4jkSqampyM3NRUBAgHg/S0tL+Pn5ITY2Vmogk2eyNNthDABO7nmO3Wsy62xPji+VK5Ap21umbE8ZoHwwqzmMqcpwpjOSkoDgYGDfPqBzZ7arUav919LFYWzuGx2aXRhTt7NnzyIlJQUpKSlo3Vqy11D0d7ulpSXOnDmD2bNnw8fHBzY2Nli+fLk4jAFA3759sX//fixduhRfffUVOnTogD///LPBNcimTJki/nrcuHFYtWoV5syZI9722Wef4YcffsC5c+cokBGtJVMgGzRokPjroUOHIicnp85wYkFBAQICAiT+YTUmPz8ffD5f6hk5Da3IXFRUBGdnZ/B4POjr6+PHH38Un30jOpNHnrN8mnKydM0wpsiQIwA8iCuVur2Tt5lC9bAVygDlhzBrUuXisjrj1Svg1i3hvRb7PS4TS/68AwCYOdANnwd0YLkizRMSEoKQkJBG9+vRo4fU6xnXNH78eIwfP16hOk6fPi31JISgoCCZR00IaY7kPstS2nAlAJSWljbZ/Cxzc3Pcvn0bpaWliImJQVhYGNzc3DB48GCF2lu8eLHEujnFxcV1zmJSNYZhsGH2E1w/UwQAuHqyUPy9bSygefiY4erJQvFj184mGDyuFd6cIts8kdqUXR5DmUVkAdX1lolQMCM1HU3IxoLfE8AwwBT/tlj8pgct16PBWrVqhb/++gvz58+X2P7XX3+hFV1zlWgxmQOZKLBwOBwsW7YMLVq0ED/H5/Nx7do1eHl5yXVwGxsb6Ovry31Gjp6envjSGl5eXkhKSkJERAQGDx4sfl1eXh4cHV+fOZWXl1dvfWqZLN2Ik3uei8OYyD//9wJp94VhQhS4pA1BioJXcnwpOnnL3rPWGG3qLQNoOJMAp+7mYN7B2xAwwAe9XRA+qiuFMQ23cuVKzJgxAxcuXICfnx8A4Nq1azh16hS2b9/OcnWEqI/My17cunULt27dAsMwuHPnjvjxrVu38ODBA3h6emL37t1yHZzL5cLHxwcxMTHibQKBADExMQ2ekVObQCAQzwFr164dHBwcJNosLi7GtWvX5GpTXrLMH6s5XClt2LH26RXJ8dKHJjkcDkaE2GHe924YEWKn0l8wqlgaQxmqWB5DGuNWr8Q3ohvO3s/DnP23wBcweMfbGWvHdIeeHoUxTRcSEoLLly/DwsICR44cwZEjR2BhYYFLly7JNKRKSHMlcw+ZaGL/1KlTsWnTJpWd4RMWFoYpU6bA19cXvXv3RlRUFMrKyjB16lQAwOTJk+Hs7IyIiAgAwvlevr6+aN++PXg8Hk6cOIFffvkFW7duBSAMK59//jnWrFmDDh06iJe9cHJywpgxY1RSsyrUHnbsPdwSnXuZYc/aLPE2ReaEqQLbPWWA6ocxa6KesxratQMOHRLea5HzD/Iwa18cqgUMRns64dt3PSmMNSN+fn7Yt28f22UQ0qTknkP2888/q7SACRMm4Pnz51i+fDlyc3Ph5eWFU6dOiSflp6enS6yFU1ZWhlmzZiEzMxMmJibw8PDAr7/+igkTJoj3WbBgAcrKyjBz5kwUFhaif//+OHXqlNJz3JTpuand8yRt2BEQBsra29igilAGKLc0BqDeYAZIhjN+eYVajqHRrK0BBSdfa6p/Hj7Hx7/Eo4rPYGR3R2x8zxP6FMYIIRpOpnXIdE1965Aps+RFU67Kr0qquEC5sqGsJnUFM0AYyFImRTSbdb1UsiZVXp5wyYvgYKDWmcnN0T8PnyN0701UVgswvIs9tgR7w1Bf7guSaCxae44Q7dV8rqxM0M84p8HnL1cod/kXactwqOIC5aoYwhRR9cR/nZeVBcyfDwwe3OwDWc0wNqyLPX6YqF1hjBCi3SiQNQONBbHa+1165aDQ+mY1F5ytfZanpgxhApI9lRTOCAD8WyuMbZnoDa4BhTFCSPNB/2OpgDqHK0Uhi2EYbN9RiuHDn2PY8OfYvr0U9Y02P9j3GLvXZOLqyULsXpOJk3uey3Ss2md+1j7LUxXDrsqehVmbus7KJM3H/x48wwwKY4SQZo56yDSQaOgw/3Y+kny5mD69BXbuLMeKFSXifVasLAGHw8GMGaZ1Xn/jZqXEY1kvqVT7zE9pZ3mq6uLkgGrnlql78j/RTGfvC8+mrOIzCOxqj80fUBhrjt555x2Z9z1y5IgaKyGEPRTINFDNocNjx4Rn/tUOWQCwYWMJDh4qx/h3jcHR4+DGjUrw+UB6uuQF3mVdPqO+Mz9rU0UoA1Q7t0yEhjPlZGkJjBolvG9mTt3NwZz9t1AtEJ5NGfW+F80Za6Ysm+HnjxBVo0CmgWoPHd6Mq0QvX644nIkUFzO4f78aK1dJX0DWwUEPLVvqwVW/CH2NqnGF13D4ES04K0tvmipDGaDa3jIR6jWTQfv2wNGjbFchtz9vZWH+4QTw/1tnbON7njCgMNZsqXo5JUKaI/ofTAO96SeQeOzrIxy2XLHCHF27GsDCQrY1lXJzBbh/vxorVpZg585ymU8OkJUql/JQ9dyymkTzzGiumRRVVcDz58L7ZuK36+mYd+g2+AIG47xb47sJXhTGCCHNHvWQaaDp04XXCb0ZVykOYxwOB6EzzBA6www7dpQhfEWxXG3ejKvEjBmm6Geco/TyGDXJ21PGMAzi96cg63YBnL1awXuiu/gMUHX2lonUDmU633t25w7g4wPExQHe3mxX06hdl1Kx6th9AMCkPm2xcnRXWoFfC/3+++84dOgQ0tPTUVkpOV0jPj6epaoIUS8KZBpINFlf2oR9QBjYGDA4fFi4yvy744RzyG7erER1NWBowEFVNYNTp3ji1/j6cMVfsxnK4ven4Py3CQCA5LPCeXI+wR0k9mmKYCZSM6BVl/GQovYjEkUwDIOoc4+wKeYRAOCjgW5Y9KYHXShcC33//fdYsmQJQkJC8Ndff2Hq1Kl4/Pgxbty4gdmzZ7NdHiFqQ4FMw/Q1ysaOHeW4cVM4b0zUO1ZTzd6ymkJnvP5aIBAgdGYhEhKq4OlpiGnTTMAwDHbsKMOhw6/AwXP4jrVX2cXJZQ1lWbcle6iyEgrqBDKRpgxmRHMJBAxW/n0Pe2KfAgDChnXEp0PdKYxpqR9//BHbtm3DBx98gN27d2PBggVwc3PD8uXL8eLFC7bLI0RtKJBpmJ07y8XDkaJJ/PX1lDVk165X4h6ynBweQmcWok8fLlasfL10xr37WeKJ/Kogy6r+zl6txD1jAODs2fiQIQUz3VXFF+DLwwn483Y2OBxg5eiumOzvynZZRI3S09PRt29fAICJiQlKSoT/Z02aNAl9+vTBDz/8wGZ5hKgNBTINU3t5C9HcL2XbOXWKV2c5DAAoSMgHoJpAJtJQb5n3RHcAwp4xZ89W4seyoGCmW0p51fjk1zhcfJQPAz0ONrznibe9nNkui6iZg4MDXrx4gbZt26JNmza4evUqPD09kZqaWu9i2IRoA9ZPTdqyZQtcXV1hbGwMPz8/XL9+vd597927h3HjxsHV1RUcDgdRUVF19lmxYgU4HI7EzcPDQ43vQHUYhkF1teR/OI8eVUEgENTzivr18uXW2fbiRd12fHwM5W5bpuPXcwYmh8OBT3AHjP6mD3yCOyg07NTdMlutZ2XqFE9PoKhIeK9Bnpfw8P62WFx8lA8TQ31sn+xLYUxHDB06FEf/W4pl6tSpmDdvHoYNG4YJEyZg7NixLFdHiPqw2kN28OBBhIWFITo6Gn5+foiKikJgYCCSk5NhZ1e316a8vBxubm4YP3485s2bV2+7Xbt2xblz58SPDQzU+zbvFDmpJCCc3PNcYiI+ADx4wEev3s/xycdmmDbNBLt2vap3fhnDMNi5Uzj/zNfXEHZ2HDx7xkg8X3sbGMUn+Uu7GHnNelS1Vll9qMdMBfT1AQsLtquQ8OR5Kab8fB0ZL16hpSkXu0J6wcvFiu2ySBPZtm2b+I/Q2bNno1WrVrhy5QpGjx6Njz76iOXqCFEfVgPZxo0bERoaiqlTpwIAoqOjcfz4cezatQuLFi2qs3+vXr3Qq1cvAJD6vIiBgQEcHBxUXm9qfivxWXkMw+DpHwkovJMNq+5O6DZNtgt4N6T2grAiubkChK8oxtboUuTmCv+jkja/rPb8s6BAI5w6/Trg5eXV7e6Pi69CKBQLZQ1djFxElnllyqoZhimcyenRI2DOHOCHH4AO0k+uaEpXnxTg41/jUFhehbatWmDP1N5wtZF/yJ40X3p6etDTez148/777+P9999nsSJCmgZrQ5aVlZWIi4tDQEDA62L09BAQEIDY2Fil2n706BGcnJzg5uaG4OBgpKenK9QOwzB4eSwW2esP4eWxWIn5C0//SMCDzf8i90IKHmz+F/H7lV8wwcOn4UscicKYyM241/PEGIbBwUPlEs8bGnKwcoUFRo0yRtcu0rN37eUw5NHYxchrUuUisg0RDWfSkKaMSkqAM2eE9yz7Iy4Tk3ZeQ2F5FbxcrPDHJ30pjOmIxMREca9YYmJigzdCtBVrPWT5+fng8/mwt7eX2G5vb48HDx4o3K6fnx92796NTp06IScnBytXrsSAAQNw9+5dmJubS30Nj8cDj/e6J6m4WNjLVHT6JvL3CYc+S2LvCZ8M6QgAKLwj+Qu/oeUbZPXmFFu0MyjGjZs8pKRUIzubj+IG1n8VhSmGYTAj9CXu36+WfN6XK17PrPZisvb2HAAcHDxUDgYMZkw3lbuHT5aLkdek7iHM2qjnrHkQCBhsOJuMLf97DAAY2d0RG97zhLGhPsuVkabi5eWF3Nxc2NnZwcvLCxwOR+oEfg6HAz6/7slJhGgDrTvL8s033xR/3aNHD/j5+aFt27Y4dOgQpk+fLvU1ERERWLlyZZ3tFQ8zJR6/Ss4AIAxkVt2dkHvhda+YLMs3NIbD4aDzh+6YMUPYU8UwDHbsLEN0dJlE71jXrgZ4b3wL8Yr+O3eW15l71rWrgfh5gUCAK7EVcDEHqkz14OVp+N9QJoO8PAFWrCgBGAAc4PChRJQyhhj8TstG1yiT9WLkNTXFEKY0FM40U0lFFeYdvI1zSc8AALOHtMf8YZ1o9X0dk5qaCltbW/HXhOgi1gKZjY0N9PX1kZeXJ7E9Ly9PpfO/rKys0LFjR6Sk1D+kuHjxYoSFhYkfFxcXw8XFBcYdW6P0xuveOpNOLuKv244TnpVWeDcHVt0c4T2x/jByo9RNoSE7DocDDjgSYSwoyAg7tltLBKXaS1wAwHvjX0/4nxH6EqdPV2IngOklAtxi6u5/+PdXuHdP1MNWjT1rG1+jTJ6LkdfW1L1lNUkLZwzD4Olfd1ipR1el5pchdO9NpDwrBddAD5HjumNsz9Zsl0VY0LZtW/HXT58+Rd++feucjFVdXY0rV65I7EuINmFtDhmXy4WPjw9iYmLE2wQCAWJiYuDv76+y45SWluLx48dwdKx/wrqRkREsLCwkbgBgGegLu6lBMO/bFXZTg2A1so/4NRwOB67vesFrxZtwfddLbauG1w5bBgbCHrGPPn6JHTvKwDBMnSUugoKMxL1jABAbW4V2AKYBcAVQWFh3KEDa8j4NzQlThV5mT5psbll9RPPNqo7/i0c/XWG1Fla4uAgn9Lu4NL6vCp2+l4vRP1xCyrNSOFgY4/BH/hTGCABgyJAhUlfkLyoqwpAhQ1ioiJCmweqQZVhYGKZMmQJfX1/07t0bUVFRKCsrE591OXnyZDg7OyMiIgKA8ESA+/fvi7/OysrC7du3YWZmBnd34QKjX3zxBUaNGoW2bdsiOzsb4eHh0NfXxwcffCB3fRwOB9Zv+cP6rcYDoqqWvqitly9XfEYlAFRXo85K/vVdjFykRQsOxhULE9c4ANu4HCxaaIrf/xC+fvx4E1y9WllnDlpjc8JUha1hzJpqX9JJZ9jaAk14fcAqvgDfnHqA7ReFw1K+ba3x44fesDM3brIaiGZjGEbqH7gFBQUwNaWTPIj2YjWQTZgwAc+fP8fy5cuRm5sLLy8vnDp1SjzRPz09XeL05+zsbPTs2VP8eP369Vi/fj0GDRqECxcuAAAyMzPxwQcfoKCgALa2tujfvz+uXr0qnp+grJpLX6jL5QpH8RmPtcNW7R6zGzd5/92/XpsMAHbsKBNv++ijFghaKeztGgdgQwmDq9cqMX68CW7erAIHHOjXmj/dpYu+THPCVInNYFb7kk4648UL4MQJYMQIoGVLtR4qq/AV5v52CzefvgQAhA5ohwVBHjDUZ319aqIB3nnnHQDCP4RDQkJgZGQkfo7P5yMxMVF8SSVCtBGHoWtR1FFcXAxLS0u4/7IY+i3q/uVeXyBrrIdMluE50WKr+bfzpS7+WvtsSQcHPYk5Zl0662MWOLBKet3b1aObAbrerYYeAAGAAxDO4Re5AuBJIBenTr8OeytXWGDGDFOFFoxVhaYOZQzD4PrPyfj3+7soKioSD1trMtHnVKl64+MBHx8gLg7w9lZtgTUcS8zGV0fuoLiiGuZGBvh2fA8EdWPns9WcqeRnrqFEIyN79uzBe++9BxMTE/FzXC4Xrq6uCA0NhY2NDVslEqJWWneWZXNXc7FVaYu/inrADh0ux7171XXWJrufxMdcACsBLAKgDwB3X4czPQAT//uaD2AdgJ8AvGkgXLOs5rAnm2qG16YIZxwOB17vtce/399V+7F0SUlFFVYcvY8/4oWfaS8XK2x63wttW9HQE5H0888/i5e62Lx5M8zMmmbKBCGagsYKGsB7YdL4TjWoYjmF2out1lz8FRAGhxkzTNGuXf1Zmg9gKYAAAFn17JP53/NL/9u/mi8MftFbrTFjxus1yeRdLFYdNGHyP5HfheRnGP7dv/gjPhN6HODToe44/LE/hTFSL4ZhsG/fPuTksP//DiFNjQKZAlLzFVtzTJaentqr9ddcSb+m2mdW1phuAUA4lPm8qwE+cZO+uOYnbhxcqPE4Pb1a4sxNTUTBrHkoKq/CF4cTEPLzDeQUVaBNyxY4MNMf84d3ovlipEF6enro0KEDCgp09CQbotNoyFLD1F5s1SPYFkBunf1qT/YXMAKsXPm6d020+Gv/eo7zURcjHHvy+uzN+/f5uH+fL3WYVNM09XCmVjM1Bfr0Ed4rSSBgcDguA5GnkvGirBIcDjC1bzt8EdgRLbj0Xw2Rzbp16/Dll19i69at6NatG9vlENJk6H9JFVN2+QtZF1sVDV2KghPDMNDj6IkD2vUbwrMvx/23/30A4RDOLesCoPP9KqwIN0dcfBWePK7GvRpLXtyMq5QIZIpceLypUDhTUqdOgJLXjgWAhIxChB+9h9sZhQAAdzszrHunO3xd1XvmJtE+kydPRnl5OTw9PcHlciUm9wOQukYZIdqAAlkjKgpMYNzqlcraU2TV/prLYNSndkADgNjjPAwGsA3A5wBeATgOYBOAkCd8mLwCorda1zlzs75hUk1X+/tKAU39njwvxYYzD3H8jvDzaWZkgM8DOmBKX1caniQKiYqKYrsEQlhBgUxBTbEeWU2yhLKapk9vgU5JVdiQUo1/bPXw6r9rXb4CMBPAGQA9z1cAn5lJXVhWG1DvmQwUXPYiLb8M0f88xuG4TPAFDDgcYKyXMxa+6QF7C1rktbnj8Xjw8/NDQkICbt26BS8vL/FziYmJmD17Nm7cuAFbW1t8+umnWLBggcTrDx8+jGXLliEtLQ0dOnRAZGQkRowYIdOxp0yZosq3QkizQYFMDRobtlT02pbyhDIOh4MB6y0xgMPBJIbBzp3l4qUyAOB3AN1HGov3rd27pm2kfb8ppMkvMbMQP/3zBCfv5kDw37kfAZ3t8EVgJ3g4aNe6WLpswYIFcHJyQkJCgsT24uJiDB8+HAEBAYiOjsadO3cwbdo0WFlZYebMmQCAK1eu4IMPPkBERATeeust7N+/H2PGjEF8fLzcc8IqKipQWSl5prm2rb9GiAgFsmZGrp4yDgfMf2Hsxs1KjH/XBOPHA3FxVVrVE6ao2iGtnOGzVIlmK+VV4++EbBy4no6EzCLx9qEedpg1uD3NE9MyJ0+exJkzZ/DHH3/g5MmTEs/t27cPlZWV2LVrF7hcLrp27Yrbt29j48aN4kC2adMmBAUF4csvvwQArF69GmfPnsUPP/yA6OjoRo9fVlaGhQsX4tChQ1LPtuTz6d8p0U4UyGRQ3zwyZYYtFe0lA+QLZTt3lktc+3LlCgtEb7VW6LiEXTweDzweT/y4uLi4gb2VU8arxoXk5zh1LxcxSXkorxT+EjTU52BUDyfMHORGPWIsqv2zNzIykrjUkKLy8vIQGhqKP//8Ey1a1P2DLTY2FgMHDgSX+3qeaWBgICIjI/Hy5UtYW1sjNjYWYWFhEq8LDAzEn3/+KVMNCxYswP/+9z9s3boVkyZNwpYtW5CVlYWffvoJ69atU+r9EaLJKJCpiSxnWyobygCgr1G2uAdM2qWWal/7svYZlPIci7ArIiICK1eurLP9RSkPyo7i8Kr5SEx7gWtPCnAt9QWup74Ar/r1VSDcbEzxfm8XjPNujVZmyv/iJ8pxcXGReBweHo4VK1Yo1SbDMAgJCcHHH38MX19fpKWl1dknNzcX7dq1k9gmuvZwbm4urK2tkZubK95Wc5/c3LrL90jz999/Y+/evRg8eDCmTp2KAQMGwN3dHW3btsW+ffsQHBys2BskRMNRIGvmlv5kgN1rXveAAZJriPXy5Yq3A/KfQUlhTHMsXrxYouehuLgYLi4uGPjtBbS2a4mODuZwsW6B1tYmcLA0hoWxIcyMDWBiqA8Bw6BawKCyWoAXZZV4XsLDs5IKpGdV4OWiXxH3exZe6T2TOF6bli3wZjcHBHZzQE8XK4mgT9iVkZEhMZeqod6xRYsWITIyssH2kpKScObMGZSUlGDx4sUqq1MRL168gJubcH6nhYWFeJmL/v3745NPPmGzNELUigKZjBQZtlR3Lxkg/VJL0q59qcgZlBTGNEtDw1LZRRXILqqQ+lzjrAA9oJUpF35uLdHbtSX829ugo70ZhTANZWFhIfPk9vnz5yMkJKTBfdzc3HD+/HnExsbW+Yz5+voiODgYe/bsgYODA/Ly8iSeFz12cHAQ30vbR/R8Y9zc3JCamoo2bdrAw8MDhw4dQu/evfH333/DyspKpjYIaY4okGkAZUKZh48Zrp4sFD9u5WmDyxV24jlmip5BSWGs+YhdPBSZpUBqfhkyXpYj48UrPCupQCmvGiUV1XhVyYeBHgf6+hwY6umhpSkXtuZGsDEzQldeAYbs2wy91Wtg06MTBTAtZGtrC1tb20b3+/7777FmzRrx4+zsbAQGBuLgwYPw8/MDAPj7+2PJkiWoqqqCoaEhAODs2bPo1KkTrK2txfvExMTg888/F7d19uxZ+Pv7y1Tv1KlTkZCQgEGDBmHRokUYNWoUfvjhB1RVVWHjxo2yvm1Cmh0Oo6kXLmRRcXExLC0t4bJpFfRMJNdUqm+R2IYm98uycr+igYxhGJzc81x8qaU3p9jW+0u1oRMBKIAB5SV8hPRMQFFRUbM4tV70OVWqXgXXISPsUMnPXEZpaWlo166dxDpkRUVF6NSpE4YPH46FCxfi7t27mDZtGr777juJZS8GDRqEdevWYeTIkThw4AC+/vprhZa9AICnT58iLi4O7u7u6NGjhyrfIiEahXrINISivWSyXmoJoNBFCFGOpaUlzpw5g9mzZ8PHxwc2NjZYvny5OIwBQN++fbF//34sXboUX331FTp06IA///yz0TAmEAjw7bff4ujRo6isrMQbb7yB8PBwtG3bFm3btlX3WyOEdRTIVESeuWQMwyB+fwqybhfA2asVvCe6AwCif+Kj/O5TePg03NMlD4ZhcGL3M1z4owDFL/mwaGmAwe+0xIgQuzrti3rbHsSVStTAMAyO/5yHv3c+B69cgK59zDB/Szvo6cl3aZza7QdNtsGpvfkSj0/ueY5/jrwAA8CutSH09Dno7Gsuvuj6id3PhM8zDOxcuNA30KtTq7T30Bgej4epPvfkej+EaDNXV1dIG0Dp0aMHLl682OBrx48fj/Hjx8t1vLVr12LFihUICAiAiYkJNm3ahGfPnmHXrl1ytUNIc0WBTArRf0KCirqTpPnl9U+cri7j1fscT79K/PXtQ4/x7/d3AQDJZzNRzROu8STadvVkISp5Agyf2Pi8j8ac2f8c+799HQZf5lVhz9osVFUyddqvuW/NGmq3ceNsEb79+Ak+3SB5+rs8tVw9WYg7V4oRd75Y6mMAeJokHB6+dqoIlTzhEgw163j6oKLBWuX5Pk71uQfmv1UemssovqhOpdYjKy19fa/Gdc2Iaoh+1s3lMyqPvXv34scff8RHH30EADh37hxGjhyJHTt2yP3HHyHNEc0hkyIzM7POOj9Ed2RkZKB169Zsl9Eo+pzqrubyGZWHkZERUlJSJD7TxsbGSElJ0br3Sog01EMmhZOTEzIyMmBubq62s85Ea0jVXk+IjsHecRiGQUlJCZycnNTSvqo1xeeUaJbm9hmVR3V1NYyNJU+iMjQ0RFVVVT2vIES7UCCTQk9Pr8n+IpNnPSFdP0ZTHMfS0lJtbataU35OieZoTp9ReYiuFFBzHbSKigp8/PHHMDV9vWzPkSNH2CiPELWjQEYIIYR1U6ZMqbPtww8/ZKESQthBgYwQQgjrfv75Z7ZLULkjR45g69atuH37Nng8Hrp27YoVK1YgMDCQ7dKIBqJTV1hiZGSE8PDwBq9BR8do+uMQQoiq/Pvvvxg2bBhOnDiBuLg4DBkyBKNGjcKtW7fYLo1oIDrLkhBCCFHA3r17MW/ePGRnZ0v8sThmzBiYm5vjl19+qfOarl27YsKECVi+fHlTlkqaAeohI4QQQhQwfvx48Pl8HD16VLzt2bNnOH78OKZNm1Znf4FAgJKSErRs2bIpyyTNBAUyQgghRAEmJiaYOHGixPy3X3/9FW3atMHgwYPr7L9+/XqUlpbivffea8IqSXNBgYwQQghRUGhoKM6cOYOsrCwAwO7duxESElJnbcD9+/dj5cqVOHToEOzsGr/2MNE9NIeMEEIIUYKPjw/effddDB8+HL1790ZaWprEFQcOHDiAadOm4fDhwxg5ciSLlRJNRsteEEIIIUqYMWMGoqKikJWVhYCAAIkw9ttvv2HatGk4cOAAhTHSIOohI4QQQpRQVFQEJycnVFdXY+/evZgwYQIA4TDllClTsGnTJrzzzjvi/U1MTLT2igtEcRTICCGEECVNnjwZx48fl1gCY/Dgwfjnn3/q7DtlyhTs3r27iSskmo6GLAkhhBAlZWVlITg4WGI9sgsXLrBXEGl2qIeMEEIIUdDLly9x4cIFvPvuu7h//z46derEdkmkmaIeMkIIIURBPXv2xMuXLxEZGUlhjCiFesgIIYQQQlhGC8MSQgghhLCMAhkhhBBCCMsokBFCCCGEsIwCGSGEEI22ZcsWuLq6wtjYGH5+frh+/Xq9+27fvh0DBgyAtbU1rK2tERAQ0OD+ih6npgMHDoDD4WDMmDEqP0ZhYSFmz54NR0dHGBkZoWPHjjhx4oRKjxEVFYVOnTrBxMQELi4umDdvHioqKhp9L0TFGEIIIURDHThwgOFyucyuXbuYe/fuMaGhoYyVlRWTl5cndf+JEycyW7ZsYW7dusUkJSUxISEhjKWlJZOZmanS44ikpqYyzs7OzIABA5i3335bpcfg8XiMr68vM2LECObSpUtMamoqc+HCBeb27dsqO8a+ffsYIyMjZt++fUxqaipz+vRpxtHRkZk3b16D74WoHgUyQgghGqt3797M7NmzxY/5fD7j5OTEREREyPT66upqxtzcnNmzZ4/Kj1NdXc307duX2bFjBzNlypRGA5m8x9i6dSvj5ubGVFZWNtiuMseYPXs2M3ToUIltYWFhTL9+/WQ+JlENGrIkhBCikSorKxEXF4eAgADxNj09PQQEBCA2NlamNsrLy1FVVYWWLVuq/DirVq2CnZ0dpk+frpb3cvToUfj7+2P27Nmwt7dHt27d8PXXX4PP56vsGH379kVcXJx4WPPJkyc4ceIERowY0eh7IqpFC8MSQgjRSPn5+eDz+bC3t5fYbm9vjwcPHsjUxsKFC+Hk5CQRUlRxnEuXLmHnzp24ffu2THUocownT57g/PnzCA4OxokTJ5CSkoJZs2ahqqoK4eHhKjnGxIkTkZ+fj/79+4NhGFRXV+Pjjz/GV199JdP7IqpDPWSEEEK00rp163DgwAH83//9H4yNjVXWbklJCSZNmoTt27fDxsZGZe3WJhAIYGdnh23btsHHxwcTJkzAkiVLEB0drbJjXLhwAV9//TV+/PFHxMfH48iRIzh+/DhWr16tsmMQ2VAPGSGEEI1kY2MDfX195OXlSWzPy8uDg4NDg69dv3491q1bh3PnzqFHjx4qPc7jx4+RlpaGUaNGibcJBAIAgIGBAZKTk9G+fXul34ujoyMMDQ2hr68v3ta5c2fk5uaisrISXC5X6WMsW7YMkyZNwowZMwAA3bt3R1lZGWbOnIklS5ZAT4/6bZoKfacJIYRoJC6XCx8fH8TExIi3CQQCxMTEwN/fv97XffPNN1i9ejVOnToFX19flR/Hw8MDd+7cwe3bt8W30aNHY8iQIbh9+zZcXFxU8l769euHlJQUcdgDgIcPH8LR0bFOGFP0GOXl5XVClygAMnRlxabF9lkFhBBCSH0OHDjAGBkZMbt372bu37/PzJw5k7GysmJyc3MZhmGYSZMmMYsWLRLvv27dOobL5TK///47k5OTI76VlJSo9Di1yXKWpbzHSE9PZ8zNzZk5c+YwycnJzLFjxxg7OztmzZo1KjtGeHg4Y25uzvz222/MkydPmDNnzjDt27dn3nvvvQbfC1E9GrIkhBCisSZMmIDnz59j+fLlyM3NhZeXF06dOiWeuJ6eni7Rw7N161ZUVlbi3XfflWgnPDwcK1asUNlxmuK9uLi44PTp05g3bx569OgBZ2dnzJ07FwsXLlTZMZYuXQoOh4OlS5ciKysLtra2GDVqFNauXavUeyXy4zAM9UkSQgghhLCJ5pARQgghhLCMAhkhhBBCCMsokBFCCCGEsIwCGSGEEEIIyyiQEUIIIYSwjAIZIYQQQgjLKJARQghptng8HlasWAEej9fsj6MtxyCKoXXICCGENFvFxcWwtLREUVERLCwsmvVxtOUYRDHUQ0YIIYQQIofq6mqcO3cOP/30E0pKSgAA2dnZKC0tVbhNunQSIYQQQoiMnj59iqCgIKSnp4PH42HYsGEwNzdHZGQkeDweoqOjFWqXApkUAoEA2dnZMDc3B4fDYbsc0kQYhkFJSQmcnJyUvmZdU6DPqe6hz2hdxcXFEvfq0hTH0ZZjNLfPqbzmzp0LX19fJCQkoFWrVuLtY8eORWhoqMLtUiCTIjs7Gy4uLmyXQViSkZGB1q1bs11Go+hzqrvoM1qXNh1HW47RXD6n8rp48SKuXLkCLpcrsd3V1RVZWVkKt0uBTApzc3Px150/6gPXsd3lbmNQq4cNPn/ptwwc2/hE/PitMDf0/6D+fyD7Ft/DnXP5Up9r7LWyHOufgo4N1sum5DxbtR8j9/vfUR4n/JnV/Plrspp19hxiiVkb3MWP+5pkyN3eL3vKsW7d6/kPixaZYdKUFjK9dt7nRThz+vVZW4FBRtj4naX48ZVXLji3Pw8H12fWee2EL1ojYKJ9o8e4WtJeplpE7r50kGm/3HzLxnfKN5apLaPnjfcCmTyXqSmY5lVLPM5Ji0Vq8kkAze8zmpGRQRPIdUhxcTFcXFyazedUXgKBAHw+v872zMxMpd4zBTIpRF3rLScGwD24o0Jd7VcqumGozYN6n39jhisMjfSReqsI7XpaYuAklwaP497LWiKQdQ+wgb6BnkyvleVYhhXcel7NnqRc4S9pfdkygVIcF0xEzjf7UR73sNkM/4nq7DnEEmHRHSSGBsxN5B8m+GS2KYyMOYiLq4KPjyGmTW8h8/fC358rEcj69OHC3Px1DS0M9DFqpiO4RnpIji+BoJqBvgEHHb3NETjFvtHjXCruAK6Z7O8l8YUTDExl21evXIawZdz4PsbPOIBRw/uYPAMgwz81s9xqwFDyv+fW7oMBAKnJJ5vdZ9TCwoICmSyePwcOHQLeew+wVf8fourWXD6n8ho+fDiioqKwbds2AML3WVpaivDwcIwYMULhdmnZCylEpwW77fkK+i2M0dkhT+G2Ggpl8mAYBv/+ktFgqJJln/qcz/dQSZ2qIgpjTYlfXoEnU75uNqeDiz6n2+N90MJcX+K5ASbpTVIDwzDYtbMcN29WoroaMDAAfH25EmHu4qs2Sh/nUnEHufZPfOEk037Zz60a3+mZbL1jxs9k6B171ng7ZrnV9T5XXVWBK6eXN7vPaHOpl3Xx8YCPDxAXB3h7s12NwrT9556ZmYnAwEAwDINHjx7B19cXjx49go2NDf7991/Y2dkp1C71kMkgKdde4VAmCjrKBjMOh4NBk9tg0OT69/n3lwz8X8QjAMDtU8L/+QdNVv6XYVNjI4xpm4uv2jRJKNu1sxwrV5SIH4evMMf0GTJ2TamJrGFMlVQVxrTV9ScvEOClfb+YiW5q3bo1EhIScPDgQSQkJKC0tBTTp09HcHAwTExMFG6XApmMlAllgDCYNRbKlOnhAoDUW0V1HjcU4DRRQ2GMYRgUnriKiuR0GHdqA6sRfbS2S1we5/bnYdRMR7V8L173gFXB17fuMObNm1US+8fFVWH6jNeP2egdk5WqesdkCWOyaqh3rDlLeV6CALaLIESFDAwMEBwcjODgYNW1qbKWdIC6Q5m8PVyiAPckvggCvgAFma8knm/XU4bJyhqksZ6xwhNXkb9bOKm5NPYeAMB6pL/a69J0B9dngmukh6AQyUnsquglq9kDdvxYBQBI9ID5+hqKtwOAj4+hxPHrwzAMTu/Jw8P4UnT0NpNpHpks2Ogdk4WyQ5XNXebLV43vREgzERERAXt7e0ybNk1i+65du/D8+XMsXLhQoXa1b4EQNUvKtVdqSO18vke987Wk9XA1RBTgEk4/w51z+ch+UAYAcPYww9jFHTBwkmynNWva/LH6VCSn13os/5mE2urhLcVXh66JYRjs3FGGTz4uxM4dZbhxo1Li+bi4qjr7N/S4Pqf35OGXtem4dvIFflmbjtN7pP+how29Y6oMYyZZqvk5N7XsQgpkMjE3B4YPF94TjfXTTz/Bw6Pu782uXbsqvCgsQIFMYcrOc5IWgmr3aDXWw9VQYBs0uU2zGs6T5ftp3KlNrce0BpdIx57ST0GUd8hQ1CN2/FgFVq4oQe0zu2v2gAFAXJxkkIiPr5bpuA/jJYOFtEDJ6kR+DWSSUdL4ThoqkwKZbDp0AE6fFt4TjZWbmwtHR8c6221tbZGTk6NwuzRkqQRVDGECryf8i3q0as4ha0i7npbioU0JHOXnozUlWcOt1Yg+AIQ9Y8adXMSPdd2EL1ojcIpqToSoPSfM0EA4Ub/mUhg11R6ytOphi4uv6v5HVVtHbzNcO/ni9eN6AiVrNLB3rDnLpiFL2fD5QFkZYGoK6Os3vj9hhYuLCy5fvox27dpJbL98+TKcnBSfNkGBTEnKhjJAMpg1diZlTaLAdv3/cpD14HUPQ68xjjLPR2suw5WA8ExT65H+AM0bkxAwseH5V/LMJaszJ8yXi+kzTCUm6tdUZ4hSxkV0RAHy4a1SdOxpVidQavoyF00+VNmMe8cAoLiiGsUVVbAwNmx8Z12WkKAVy15ou9DQUHz++eeoqqrC0KFDAQAxMTFYsGAB5s+fr3C7FMgUVPOMv5f/nfHXxVG589plOROzJtFSGAMnudTpDdsTdldiX00945KWuNAsoh4wUY8YwzD45ONCqWdYCveTDBSPbpfhTRmOw+FwEBTigKCQus/RUKWk5h7GRDJfvEIXJwpkpPn78ssvUVBQgFmzZqGyUjjP1tjYGAsXLsTixYsVbpcCWQP4OabQb1/38giA9DP+kkb6q7S3TFbS1iirPZwpbT4a271jFMaajqy9ZBwOR9wjtnNHGVatFPa8SjvDEqjbo6bs0KO6wpjMNKx3TFvCGABkvCxHFydai4w0fxwOB5GRkVi2bBmSkpJgYmKCDh06wMiokUt1NIICWSOqs0xh4FxWZ7vUM/5G+qtkCBNQfkHZxuajsR3GNA3DMCg8fZ3tMhSirnXIZFljrMNEBpOq8uodetQUzXWoUptkvChnuwRCVMrMzAy9evVSWXsUyGQgLZQZd2oj7hkTPn4deFQVygDFg1lDK/trUhjTlMVeC09cxYv955r8uKpQ3zpktcm7Lpksa4w1NPQoL0V6xxiGQc7/xaP4XhYsujrDcax3nc8PDVVqBlqLjGiLsrIyrFu3DjExMXj27BkEAoHE80+ePFGoXQpkMqodyho740+VoQyQDFHKXIZJU8KYaLhSUxZ7rd3j2dw8vFWqklBUU+35ZKLHqlh9vzZFhypz/i8eqVvPAwAK/k0GADi94yN/AdQ7pnaZL6mHrFHduwPPngFWVmxXQhowY8YM/PPPP5g0aRIcHVU3OkGBTA41Q5ksZ/ypOpSJKNprpilhrKb6hn6bWu0ez+ZGHctG1JxPJqIJYaym4ntZko/vZ0kEMuod0xzUQyYDQ0PA1pbtKkgjTp48iePHj6Nfv34qbZcWhpVTdZZ8F05W58R10ar/Da3+39jzbNOUxV6tRvRBy4nN82p7qlyHrCHqCGOKqDmR36Krs8RzFl2ca+/eOA3rHdPGMAYI55DJeiUHnfX4MTB6tPCeaCxra2u0bNlS5e1SD5kC6pvoXx919ZTVJgpdDMMg9fdEvLiTg5bdeWj3bo9Gu1QlX+NY5zWNPa8oTVnslcPhwCqwd7OdR6aMxi4gDsgWxhS5PqWyZ1U6jhWu1VR8PwsWXZzFjwHVTeQnqlFWyUdheRWsTblsl6K5ioqAv/8GVqxguxLSgNWrV2P58uXYs2cPWrRo0fgLZESBrIk0VSgDgNTfE3H3+0sAgOz/Cf/SchvvqdRrFGlTFrTYq/JkndQPSJ/Y39gFxGXtGRNdnxKAeBX+hmpSxXUqORwOnN7xqTNvTJVDldQ7pjxbMy4KqoRLX1AgI83dhg0b8PjxY9jb28PV1RWGhpLr68XHxyvULgUyBcnbSwY0XSh7cUfyWlov7ubWCU+1e7wKGnmNLG0S9sg6qb92GGMYBocPSc7tqb28hcw1SLk+pSpPNFD5mmOkyThbt0DBs0pkvHiFHq2t2C6HEKWMGTNGLe02i0C2ZcsWfPvtt8jNzYWnpyc2b96M3r1717t/VFQUtm7divT0dNjY2ODdd99FREQEjI1VOzyhqaGsZXdHcS8WALTsVreXonaPl8NAyWty1X6NLG0S9ig6qX/XznLcvy/ZcyNteQuZapDj+pSq6B1TmobNHdNmTlbGSHxWSWdaEq0QHh6ulnY1PpAdPHgQYWFhiI6Ohp+fH6KiohAYGIjk5GTY2dnV2X///v1YtGgRdu3ahb59++Lhw4cICQkBh8PBxo0bWXgHTa/duz0ACHuxWnZzED+u2StWmlEk8RqOvh66fda/zmsaa5OwT9FJ/dJ6x7p0NahzAXFZNXZ9yqZCZ1ZqntZWLQAUI4MCWcOcnYENG4T3Okjezhc2FRYW4vfff8fjx4/x5ZdfomXLloiPj4e9vT2cFfz5aXwg27hxI0JDQzF16lQAQHR0NI4fP45du3Zh0aJFdfa/cuUK+vXrh4kTJwIAXF1d8cEHH+DatWtqqU8Te8k4HA7cxnvWGVJ8cjjh/9s777Cmrv+Pvy8r7CUIigwVUByIgqLU2aJQrf6k1bZqEZRatfpVS61bHK1Frds6at1Wa9U6q8WBWhcuUMCFoCCKgAKykZGc3x8xkYQAGTcLzut5eJKbnHvOSbiQdz4T99dflXhOk47NJJ5T35wU9VNfc/HakGQdGz7cqM656grcZ7NIrDjqaJFEYY/mlvz3m5a+qAc7OyA8XN27UAuyGl/USUJCAvz9/WFhYYG0tDSMGzcO1tbWOHz4MNLT07F792655tXoshcVFRWIjY2Fv//7cgQ6Ojrw9/dHTEyMxHP8/PwQGxuLmzf5bXCePn2KU6dOYeDAgbWuU15ejsLCQpGfhgYhBCl/3hV5jGNjguYfuqLDlJ4aY/EihODNyRhkrvoLb07G0DT5atR2nZ7bly3V+yQePybeGsnOXgdjxhrVOYcgcP/Gv3nYsyQdp3epJlFFHWiku/JFFntzqZAWVnyrK22fVA9v3gAHD/JvGxnVjS/t2rXD5s2bYWxsjO3bt6t7azUIDw9HaGgokpOTRUKhBg4ciEuXLsk9r0YLspycHHC5XNjZibo+7OzskJUl+R/TyJEjsXjxYvTs2RP6+vpo3bo1+vbtizlz5tS6TmRkJCwsLIQ/jo7Kr4Wl6sbaqYcSUJ4jasnjWBnBZ1EAWg3vpJZ2RZIQVO4vjrmPnJ3/Iv/UdXVvSWOo7Tr9a8WLeoWRpJZJPj6imUHZWTzs2F63BUNS4L4mQd2VmomDFV/ov3hTRr9k1UVqKvD55/zbRoQ8xhd1cuvWLYwfP77G4w4ODrVqE2nQaEEmDxcvXsTPP/+MjRs3Ii4uDocPH8bJkyfx448/1nrO7NmzUVBQIPx5/vy5TGvKWixWHYhnSQKAY2AbNeyET20uW4mV+ykA6r5O5RFGY8OM0a6daNRCbKyo1UxcyLl3EQ3UV0aHAIr2UpsV197CEDoMUF7Fw+vicjXvkqIqxK+F8nLJv3t5jC/qhMPhSPSkPX78GLYKdFrQaEFmY2MDXV1dZGeLfnhnZ2fD3l5ylt/8+fMRHByMr7/+Gh07dkRQUBB+/vlnREZG1mgAKoDD4cDc3Fzkp6Fh3bGZyLF975YSS2E8PRiP2xFReHowXi3fZDWlcr8mUtd1Wpcwqq2hOMMwGP65qIuyspJg4oR8bNtaIvH3HxBih+C5TvAdaI3guU5qC9ynaCa1WXH1dXXQzIJ/rT3Po3FkjQVHR0eR6yEyMlLdW2KFIUOGYPHixais5H+BZRgG6enpmDlzJj777DO559XooH4DAwN4e3sjOjpaWPeDx+MhOjoakydPlnhOaWkpdHREdaauri4ANGpTuaQsSXE3pbKKv8qCplTu1yYUaZ1UvYF4ZSXB6Sj+N1hJBWIB5QbuU7Sf2bNnI7xaUHphYaFQlDlYGSEjvwwv3pTC29lKXVukqJDnz5+LfHHkcDgSx8ljfFEnK1euxLBhw9C0aVOUlZWhT58+yMrKQo8ePbBkyRK559VoQQbwg+dCQkLg4+ODbt26Yc2aNSgpKRFmXY4ePRoODg5C5T148GCsWrUKnTt3hq+vL1JSUjB//nwMHjxYKMwaG9XLXVh1sAchBLELTtdogaTq4q8e9tk1Yulo5X7ZqSvLsjbrmIDqDcQnjBcNJL59u0JEkMnTGkkjYSnDUpqA/sYGh8Op9UPX0coYN1PzaKZlXRgZAZ07828bANJ6nOQxvqgTCwsLnD17FleuXEFCQgKKi4vRpUsXkRg4edB4QfbFF1/g9evXiIiIQFZWFry8vBAVFSX0Naenp4tYxObNmweGYTBv3jxkZGTA1tYWgwcPVki1ajuSLF/V7wtEV2Mu/koIQf7pm+rehlyc25eNwd80U1gccbmix1XvkgN7GaXjcpmTzK2RKLQgbHUcrQUuS5ppWSseHoCcbXe0nfqML5pIz5490bNnT9bm03hBBgCTJ0+uVSVfvHhR5FhPTw8LFixQWiVdbURSQH/15wSCrDEXf80/dV1rG4vX1suyPuuYOHpi/w309d43Ho+6kYKstLciz7PdGkmTkKbkBUU2nJvw3eNpubLVbaQ0DuozvqibdevWST12ypQpcq2hFYKMohjilq/q8LjvEx3UUfxVkttSHYhnd2obbIgjHx8DnPznfRaUt4+BSONxcWiGJUUWXJrw3d9pOdRCVit37gDduwPXr/Ndl42Muowv6mb16tUix69fv0ZpaSksLS0B8Cv3Gxsbo2nTplSQUWqnuuWr6Fkeip687zfI6Kov0VYQ25Z56w0M2zjBcmB3tcUkGbZxQnHMfbWszQbi4khW6xggGuDv7a2PsWHG+HaiaIstZw9j2Lc0VGtrJGkghKAwKgblj5+B4+4M88Ae2hnv1oBoacMXZFmFb1FWwYWRQeOM6a0TQoCKCv4tRaNIrVYbbt++fdi4cSO2bduGNm345aOSkpIwbtw4ifXJpIUKskZAdcvX04PxwngygN8ySV1Uj20TiCErNQXzWw7sDl5FpVa6LcWzLOURY4BogL8AHx99YcYlAPT+1EYr4sYKo2KQt+ckAKDkxj0AgMXHfvwnm76tN7D/bVNC3ZYsY2lsAEtjfeSXViIttwQezRpeeSFK42D+/Pk4dOiQUIwBQJs2bbB69WoMGzYMo0aNkmteKsgaGQJrWW5iJgiXh9x38WWSymAoG/HYtrdJz9WWXckwDCwDummlIJO3l6UkBDFjt29XwsdHX9hKSWA1cxupuVax6pQ/fiZ6nJwOCASZCim216OB/dVwaWKCu6X5SMuhgoyivWRmZqKqqubfNZfLrVG6QxaoIGMBWZuLqxOBtQyA0DqVqaaaY+KxbbQIrOLIax0TUD1mrHotMoHV7HKZdliNOO7OQssYAHDcnOoYLR9lTWnpC1lxaWKMu8/zkZZL48go2stHH32E8ePHY+vWrejSpQsAIDY2FhMnTlSo9IVGV+qnKA9JNcdUTcthnugwpaewwTkbRWAbY3NyQXNxRcUYULPheH2tlOSlp3kyK/PUhnlgD1gHD4JJ946wDh4E80Ba104TcLERBPZrz5dYleLhAdy7x7+laCzbt2+Hvb09fHx8hLX3unXrBjs7O2zdulXueamFTE3U1stRVWhCzTHxrM6HWYpbXwTNyQH1x6WpCkHZi94TFZ9LPGbM21u/jtGaC8Mw/JgxNbgpKbUjCOxPpaUvJGNkBLRvr+5dUOrB1tYWp06dwuPHj/Ho0SMAQNu2beHu7q7QvFSQNSCqV+QXr8IvTkOtOSaxOXkDF2QA8CbhFQBLheepnmnZpQv/38PECfnw8eFnXdJMReVQ5mgGo+eSy4uI0MIeyFf6dpTG+9IXVJBJ5Nkz4McfgfnzAWdnde+GUg/u7u4Ki7DqUEHWgJClF6U6ao7VBxs1ycTLVzSWuDS2LFnVMy23bS2RGE8mqNyviTS3zcfL15bq3galFgQuy1dF5Sgpr4IJh34EiZCbC2zbBnz7LRVkGgyXy8XOnTsRHR2NV69egcfjiTx//vx5uealfw0KokkB/aruRamJNMbm5LNmmQotW2wiKZ6sekkMVeJp/RIJec3VsziFNSyM9GFtYoC8kgqk5ZagfXMLdW+JQpGZqVOnYufOnRg0aBA6dOjAmueACjI1oKz4MUXiwmRxdyoTRa1kjbE5eXAIO65E8ZIX3t56OPnP++e1NZ5M3dDSF6I4NzFGXkkFnuWWUkFG0Ur279+PAwcOYODAgazOSwVZA6K+uDCTonKUmHEkniuLu1OdEEKQf+o63ialq726v6awZ1cpJk4ykft9YAp4IBY6NUpeLFhohgULzUQq9wvQZLeltiJ1HJmW07KJCe6k5yOVxpFRtBQDAwO4urqyPi8te6EAmuSuBN7HhfksCkCr4Z1EPqAJIRg+/ThuR0Th6cH4GuUgNKEMhjQIsiiLY+4jZ+e/yD91Xd1bUjtLlxZj+zb56zpZLuaLgBouytsVAGgXl7ooa6ruHWgftPRFHdjZAbNm8W8pGsv333+PtWvXsl5WiVrIVIy6yl1UbruJoAevEP7gFe5JsIBpQhkMAXW5LZWVRUkIQf7pmwrPoy5ib1cg7GsTmc/TfVYF07/KUDjVpEbJi8oqSAzqbyzQ9knKQSjIaOmLmjg4AJGR6t4FpR6uXLmCCxcu4N9//0X79u2hry8aznH48GG55tUKC9mGDRvg4uICQ0ND+Pr64ubNuj848/PzMWnSJDRr1gwcDgfu7u44deqUinarmfhdeQoA+OzdsbgFTLxIq6aWwTBs4yR2zE4WZf6p61rZNklApZwhSsanyoW3Y8OMsWChGT4ZbIgFC82gK9b7WbxILEV6iu2l++5b5mim5J2on5bvSl+k5tBq/TUoKgIuXuTfUjQWS0tLBAUFoU+fPrCxsYGFhYXIj7xovIXsr7/+Qnh4ODZv3gxfX1+sWbMGAQEBSEpKQtOmNf0FFRUV6N+/P5o2bYpDhw7BwcEBz549g6Wlpeo3r0LqC8ofUsx3P30GYCUAy/Z2Up+rSSgri1Lc8qZt6OnWbzqX1KeyeGcJLAEU7SwBxhsLS14QQnD9eoXI+Q0qqF+KBuMU5eBiw49FzCkuR9HbSpgZNqDrSlGSk4F+/YDYWOBdSx6K5rFjxw6lzKvxgmzVqlUYN24cxowZAwDYvHkzTp48ie3bt2PWrFk1xm/fvh15eXm4du2a0Izo4uLC+r40LX6selD+0AtPMPB0EkydLPlPEqBjdjEAwBfAXgC6O25B/0A8OJZGuGNvhhP/8S1omhzQDygvi1K8fpm2UcWtR0ATgsTx+XA7VQ43APjnLZ7+VoI+mfz6OQ4veLj/cS5aufL/Jdy4UYHWme9r6wQEcmqU1qCB/XxoT0vZMDPUh42pAXKK+ZmWHRxopiVF+6iqqsLFixfx5MkTjBw5EmZmZnj58iXMzc1hamoq15waLcgqKioQGxuL2bNnCx/T0dGBv78/YmJiJJ5z/Phx9OjRA5MmTcKxY8dga2uLkSNHYubMmdAV98G8o7y8HOXl5cLjwsJCdl/IO5QZP1Y9KP83AC1fFeO7pNcQf8U6AEYCQHEFuMUVWJpdjFVVXNG5NKB+GRtFYmXBcmB38CoqNdptWdd1qlfPXzIBMDu1Cl8AmAXwr4tqgksHQMd7VcC9KvAYIIbwryMB+vqMxlpNtQVpy180hmxL5yYmyCnm1yKjgoyibTx79gyBgYFIT09HeXk5+vfvDzMzMyxbtgzl5eXYvHmzXPNqdAxZTk4OuFwu7MQyTuzs7JCVJTkL8OnTpzh06BC4XC5OnTqF+fPnY+XKlfjpp59qXScyMlLE/+voqH3V3a07NhPe5wL44U0Z/AFk1DL+BQB/APMAcHVELwN1BvSrC4ZhYBnQTd3bqJO6rlMfH4M6z92+rRSJD7mYB9R5XVTZ62Curz7/uqj2uMBdSQjBtq0lmDghH9u2ljSK5u0U9qEtlCjazNSpU+Hj44M3b97AyMhI+HhQUBCio6PlnlejLWTywOPx0LRpU2zZsgW6urrw9vZGRkYGfvnlFyxYsEDiObNnz0Z4eLjwuLCwsE5Rpqi7UhkxW9VrkBWnv0FhSi4uAhgAQJIjbgCAh+/uOwa2AfNxW63qa9kY65HVdp26uekgdEzd8VDVS1pcBDCxtS6OP+HWGPetqy7+ShC14lR3V4rXKguuzEZgaMMV8OrKtGzoVrKW7+LIaGC/GPr6/ExLfRpXp8lcvnwZ165dg4GB6BdhFxcXZGTU9nW3fjRakNnY2EBXVxfZ2aKuvuzsbNjbS/4QaNasGfT19UXckx4eHsjKykJFRUWNNxAAOBwOOBzJBVPZorq7UhlFWKv3pnx6MF44f69axn/ZrzV+YxihABOcr0zYFKKCemQAhLFfVg28On9t12lyMg/jvynA1m3WtZ4rXtLim7Z6gARBxlyphMARam+vg/ETTESaiovXKnt8pxiBobK/loaGtHFktGo/H1r6ohY6dgRevFD3Lij1wOPxwOXW/P/54sULmJnJnymt0S5LAwMDeHt7i5gAeTweoqOj0aOH5A/fDz74ACkpKSLNPh8/foxmzZpJFGPqQNlFWFsO84R975YA3pe5eABg+LtbABhcVA7rDvbIS8xE6qEElbieBEL05YUnuLfuClIPJcg9l8R6ZI2Y6zF1l6QQL2nh8ZAvCp6ZMFjaRQ+vbfj/Cj6rdg6jw687Vl00+/iIfnN37yxf8CqlfhpyCYxWNvzrJuVVMXV7U7SOAQMGYM2aNcJjhmFQXFyMBQsWKNROSaMFGQCEh4fj999/x65du/Dw4UNMnDgRJSUlwqzL0aNHiwT9T5w4EXl5eZg6dSoeP36MkydP4ueff8akSZNY2Q8b2ZXV470A9mO2GIZB158+xgfjfNGXAXaYceAD4BAAHwB77U3RIS4DGSyJI2mRVYjWlQShrHpk2oqxcd2WRoZhEPa1CTZusoRRKYHTUy62APAoIXg7xAjlMbb4t4UO+gGweneOp2dNt0l1YRc81wkBIVpcUbzp2/rHgO+2lAZpq/ZLW5MMaLiirHVTE+jqMCgoq8SrovL6T2gsJCYCLVrwbykay8qVK3H16lW0a9cOb9++xciRI4XuymXLlsk9r0a7LAHgiy++wOvXrxEREYGsrCx4eXkhKipKGOifnp4OnWpB6Y6Ojjh9+jS+++47eHp6wsHBAVOnTsXMmTPV9RJqUF/PSTZgGAaDXKxxZnUH5Pe3hevURDy/VwRD9+bY/2MgLn17GH3uZ+Pou/GqyKxksxuAsuqRaSvfjDeuf9A7qqLLMQLA3++OY2MrEfY1g3bXbLB8SB6GPuPipa8BfttSM/tNIOzcR2luuYvmtvl4+dpS3dug1AFHTxctbUyQ8qoYj7KKYGdOa8IBACorgYwM/i1FY2nRogXi4+Oxf/9+JCQkoLi4GGFhYRg1apRIkL+saLwgA4DJkydj8uTJEp+7ePFijcd69OiB69c1p8ehuKWneryXMjEOKkcKYwcdAGHrq6/1GFs/csO9++/3pYrMSjaFqLLqkWkjs2aZytTSqPITDv6uVnVfkEGpo6OD0f/Y8JtXNvAECWWhjFiyhhrg38bODCmvivE4qwh93G3VvR0KRSb09PTw1VdfsTsnq7MBiI+Px4kTJ2BtbY3PP/8cNjY2wucKCwsxbdo0bN++ne1lKWJ8aPMIQO0fqmETDLANPVWaWSmPEJW1HlljzL4MDjGW6TWO/doEYBjExlbC21u/RsFXVYixK4VuNR4jhCDxzyRkxb+GfSdbdBzRRmN+d8rItmzsoszdzgwnEzPxKKthvS5K4yApKQnr16/Hw4f8egUeHh6YPHky2rZtK/ecrAqyM2fOYPDgwXBzc0NRUREiIiJw8OBB9OvXDwBQVlaGXbt2aa0g07Tq/LXBF2N1wzAMvp7IwfmcABXsSHU0xuxLWRG4HcO+VvdOREn8MwlXV8YCAJ6c4ydteI6U/5+bVCihhZKyKveXOZpBP63hxFu1sefHxz3OpoKMol38/fff+PLLL+Hj4yNMMLx+/To6duyI/fv347PPPqtnBsmwGtS/cOFCTJ8+Hffu3UNaWhpmzJiBIUOGICoqis1ltAplVucX50ObR1KJMfFzGhI0+1L5KKtdUlb8a9HjhNe1jFQP0gb3y4IsAf4AUObQcLJaBYIs+VURuDyaaQkAcHMDLlzg31I0lhkzZmD27NmIiYnBqlWrsGrVKly7dg1z5szBjBkz5J6XVUF2//59jB07FgD/W/iMGTPw22+/YdiwYfjnn3/YXErlaLp1TBFhpUpRRgjB04PxuB0RhacH42tNea8+jnP5jNSp8eLZlxz3FnhzMgaZq/7Cm5Mxda6Xf/qmbC9GQ5jyv3yRMi/KhhCCqJ1ZWDclBVE7s1grW2DfSTSOyN5T/rii5rb50g+WItuSEIKC/y7hxeFdyLt5qd7XLG3GJSC7KGsoOFkbw1BfB28reUjPowViAQBmZkDfvvxbisaSmZmJ0aNH13j8q6++QmZmpoQzpIPV/wQcDgf5+fkij40cORI6Ojr44osvsHLlSjaX03hUZR2TJKgIIbi05zlS7xSgZWcL9A52rDMeRzDH+RzluoikLYorPs6m0Ewq16N49iVApHJh5p+6rtF9LOsi+lwFxn9TgN+3WtU5jhCC7dtKcft2JXx89EUKvsrC6V3Z2LOEb4m88W8eALBSrb/jiDYA+JYxe09b4bEmUHjpMvKOHAMAFD2KBwBYd+td5zmyuC4bY8FYXR0Gbk3NkJhRgKSsIrS0kT4xpcGSkQH8+isweTK/Yj9FI+nbty8uX74MV1dXkcevXLmCXr1qK8deP6wKMi8vL1y4cAHe3t4ij3/55ZcghCAkJITN5Sio3bp1ac9zHIlMBgDcjeJ/KvQZXb+r6UObR0oVZZJqkUkSZOLjDNKTAdQvyMSzLzNX/SXy/Nuk5xIzM8VdndpGQkL9afLibY8AyJSdKeBxXLHosRzV+nuaJ9cI7GcYBp4j29YaN+Zp/RIJec1lW0ha6oklK09NEzkuzUiDNeoWZLLSGEWZu917QRbYCHvo1iA7G1i6FBg+nAoyDWbIkCGYOXMmYmNj0b073whw/fp1HDx4EIsWLcLx48dFxkoLq4Js4sSJuHTpksTnRowYAUIIfv/9dzaXVAnyuCuVbR2rz82YeqegxnGfmhbWWudWliiTthaZpHHyhDMbtnESWsb4x5ILyIqP0zYkFXEVR7ztEb/+mOxruXcxFVrGAM2t1s9mPTJOSxeU3I0XHhs7uEh1nqwB/o1NlLWx5187NLCfok18++23AICNGzdi48aNEp8D+F8yJbVYqg1WBVlQUBCCgoIQEhKCsLAw9O4t+g1y5MiRGDlyJJtLNkqkiflq2dlCaBkTHMu6hjJEmbS1yCSNYxjZSmAA0heQtRzYHbyKSq10W37kL7mIqzji/SwF9cdk4XKZEwJC+PFTj+8Uw72zqXZX669OHVYy8958N0R5aho4LV1g1LsnIGXOARVltdPG3hwAkEQFGUWLUFbMrlKiSQsKCuDv7w9nZ2eMGTMGISEhcNBS86smWcdkCb7vHcy3BFWPIZNnPbZFmbS1yNgqnittAVmGYWAZ0E0rBdm69ZYi3SpqQ1BvrNb6Y1LQyygdl8ucEBhqr5am4rK6LdmykjEMA4s+vYE+779kylKbjIoyybSx4wevp+aUoLyKC46erpp3RKHIxtu3b2FoyE7pHKX0sjx69CgyMjIwceJE/PXXX3BxccHHH3+MgwcPorKBt4TQBDEG8D9A+ox2Qujqjugz2knuApvylNJQJqosI9LQqN7PUrxpOOUdUva3FCBLKQxZMi+BxpF9aWfOgbmhHrg8gievNDuTXSU0aQKEhfFvKRoLl8vFjz/+CAcHB5iamuLp06cAgPnz52Pbtm1yz6u05uK2trYIDw9HfHw8bty4AVdXV4wePRrNmzfHd999h+TkZGUtzRq6zWT7B6EMsaApgkgT9iCAirKGQU9z+f4HeFq/lGm8TCUwAJlFmSxQUSYKwzBoK3RbFqp5NxqAszOwdSv/lqKxLFmyBDt37sTy5cthYGAgfLxDhw7YunWr3PMqTZAJyMzMxNmzZ3H27Fno6upi4MCBSExMRLt27bB69WplL6+1aIoQq46m7YdCkRZlijJZC8bKI8oasjBzfxfYn5RVXM/IRkBZGXD/Pv+WUoO0tDSEhYWhZcuWMDIyQuvWrbFgwQJUVFSIjEtISECvXr1gaGgIR0dHLF++vMZcBw8eRNu2bWFoaIiOHTvi1KlTUu9j9+7d2LJlC0aNGgVd3fdu9k6dOuHRI/k/J5UiyCorK/H333/jk08+gbOzMw4ePIhp06bh5cuX2LVrF86dO4cDBw5g8eLFylheLbBptdE04UMIwX+707Hzu0TonpK+SKsyoVay9+zZVaoRvxNVIquVDNA8UUatZXwEcWQ00xLAw4dAhw78W0oNHj16BB6Ph99++w3379/H6tWrsXnzZsyZM0c4prCwEAMGDICzszNiY2Pxyy+/YOHChdiyZYtwzLVr1zBixAiEhYXhzp07GDp0KIYOHYp79+5JtY+MjIwaNcgAfrC/ImFZSvkLb9asGXg8HkaMGIGbN2/Cy8urxph+/frB0tJSGcurHLbEgaYJMQHiNc06lNgpHGxPYY+lS4vBMWTkqimmbiTVI5MWpdYlEyBDr0uBKJOlCbmswf4ldg1PlAkzLWmTcUo9BAYGIjAwUHjcqlUrJCUlYdOmTVixYgUAYO/evaioqMD27dthYGCA9u3b4+7du1i1ahW++eYbAMDatWsRGBiIH374AQDw448/4uzZs/j111+xefPmevfRrl07XL58Gc5iruVDhw6hc+fOcr8+pVjIVq9ejZcvX2LDhg0SxRgAWFpaIjU1Var5NmzYABcXFxgaGsLX1xc3b0rX4mb//v1gGAZDhw6Vcueyw4YYU5Z7khCCi7ue4ZegG/gl6AYu7k6Xy5IiXtNM7/FjtraoENRK9p7btyvqH6QAhBBs21qCiRPyWW2XpGpktpLJgbJdmJpMeXk5CgsLRX7qQ2Ahy8gvQ0Fpw076amyIXwvl5fJUk6ybgoICWFtbC49jYmLQu3dvkdiugIAAJCUl4c2bN8Ix/v7+IvMEBAQgJiZGqjUjIiIwefJkLFu2DDweD4cPH8a4ceOwZMkSREREyP1alCLIgoODWUsD/euvvxAeHo4FCxYgLi4OnTp1QkBAAF69qvtrZVpaGqZPn65QG4P6YEuMyUN1N+J/tQitS3ue4+jSFGQ8KkbGo2IcjUzGpT2yN9sWr2HWsrOFxljzqCjjUyVjhYTqAmvb1pJ6BZagyv/Jf95iz5J0nN7F3vsub3A/oELXpRKzLwH5XJiaSGRkJCwsLIQ/jo71l9uxMNaHcxN+CZY7z98oe4sUFeLo6ChyPURGRrI6f0pKCtavX4/x48cLH8vKyoKdnWhtRMFxVlZWnWMEz9fH//3f/+HEiRM4d+4cTExMEBERgYcPH+LEiRPo37+/3K9H6UH9irJq1SqMGzcOY8aMQbt27bB582YYGxtj+/bttZ7D5XIxatQoLFq0CK1atVLKvhQVAopaxQRuxLtRr3CkFqElbtmq7bH66B3siKDZbvAKbIqg2W7CmmaKijJpG43XBxVlgF41T5Y0Yqu6wFq0sAjbt9Xd3Fm8yv/jO+wGYGu8KAOULsoA7Rdls2fPRkFBgfDn+XPpvgB2ceL3YY1Lz1fi7rQAhgEMDPi3DYDnz5+LXA+zZ8+WOG7WrFlgGKbOH/Fg+YyMDAQGBmL48OEYN26cKl6OCL169cLZs2fx6tUrlJaW4sqVKxgwYIBCc2p0QEJFRQViY2NFfok6Ojrw9/ev07S4ePFiNG3aFGFhYbh8+XK965SXl4uYUuszs7MhxhRFmtZI4tX6AYBbJXuFYUFNM2lbL0mLtI3GpcHDXvYq/tUhhCD/tHSucHVR13VaWfn+w1+anpWytlESr/If2E2zXEvyxJPJVTRWhpgyQP64MkC22DJNgcPhgMPhyHxeF2crHLmTgbhnjdxC1rkzoAS3nrowNzeHubl5veO+//57hIaG1jmmunHl5cuX6NevH/z8/ESC9QHA3t4e2dmin9GCY3t7+zrHCJ5XFxotyHJycsDlciWaFmtLLb1y5Qq2bduGu3fvSr1OZGQkFi1aJNVYRcQYG0KMEIJLe57jdZqoRUNSa6TewY64cfglXia9r6eW+6IMO79LFFbvV7Q4qCLV/KVtNK4K8k9d1/gq/XVdpy+ev++XJi62BPFlt29XwseHX6FfUhulbVtLRMZUvzYkVfm/wnK5LkUC/OVFFaIMkK2qvwBtFmay4v3OQnb3eT64PAJdnYZhIaJIh62tLWxtbaUam5GRgX79+sHb2xs7duyo0aWkR48emDt3LiorK6Gvz28Pd/bsWbRp0wZWVlbCMdHR0Zg2bZrwvLNnz6JHj9o7ulhZWUn9eZmXl1f/IAlotCCTlaKiIgQHB+P333+HjY2N1OfNnj0b4eHhwuPCwkKpYh9kga2Yq+oZjwDg4GGKbkObSWyNxDAMfD9tLjL+5aMSvHxUIrSc9RntpPCe5BVl0jYalxZFrGRvk9IVWlsV1HWdVv9HIS62qqpQw2ImLrAIIVi8qFhkTHWrmqDKf3UrmqCNEpuoI+tSlaIMkM1aBjQOYdbG3gwmBrooLq/C4+wieDSr36rSIHn4EBg1Cti7F/DwUPduNI6MjAz07dsXzs7OWLFiBV6/ft9QVmDdGjlyJBYtWoSwsDDMnDkT9+7dw9q1a0Xqnk6dOhV9+vTBypUrMWjQIOzfvx+3b9+uYW2rzpo1a4T3c3Nz8dNPPyEgIEAo4mJiYnD69GnMnz9f7ten0YLMxsYGurq6UpsWnzx5grS0NAwePFj4mKAJqJ6eHpKSktC6desa50lrZpfHOsZ28Lu4q9LW2Rh9RjsJg/zFe1cSQuDQ1hRgAEKAl4+KReZi2w0pC9I2GpcFeUWZYRsnFMfcV3h9ZVLXdTpsuJHwvrjYEs/A5LsnmXfjSnH7diVSn1ZJGMO/TwjB9m2ltVrPNAmVizJAJdYygC/MuA3HmyWCrg4DLydLXE3JRVz6m8YryMrKgDt3aGHYWjh79ixSUlKQkpKCFi1aiDwniJW1sLDAmTNnMGnSJHh7e8PGxgYRERHCkhcA4Ofnh3379mHevHmYM2cO3NzccPToUXTo0KHWtUNCQoT3P/vsMyxevBiTJ08WPjZlyhT8+uuvOHfuHL777ju5Xp9GCzIDAwN4e3sjOjpaWLqCx+MhOjpa5I0Q0LZtWyQmJoo8Nm/ePBQVFWHt2rUyW73yT9+E9dBeYBhGI8QYUDMuTOCqFK8VJuDo0hTh/Y7+NiKCTJKbU17ksZKx1UBcHHlEmeXA7uBVVGq821ISs2aZijQKl2TNOvnP+09yb2++Gb96rJk4gjHi48StZ5pmJQNULMoAlVnLCCF4E3tVpnW0iS5OVriakovYZ28wype2DqLUJDQ0tN5YMwDw9PSsN358+PDhGD58uFz7OH36NJYtW1bj8cDAQMyaNUuuOQENF2QAEB4ejpCQEPj4+KBbt25Ys2YNSkpKMGbMGADA6NGj4eDggMjISBgaGtZQuILis3Up39rI23cOOgb68AuTPVNTWWUhBJav1DsF4Fbx8DQuHwDwNK5mkL84OroMgma71bCiCRDEp1V/XlMtIfUhENDSCjOGYWAZ0E0rBVl9SIr/AmrGmrVrr4dWrfRExkgaJ249i9qZhcdxxXDvYoqAEDtWrhl1ijIAKrWWAdIJsze3LuP1xZOy7UuL6OL8LtOysQf2s8DbSi7eVnJRweWhkktgoKsDK2N96OlqfGEFraBJkyY4duwYvv/+e5HHjx07hiYKNIbXeEH2xRdf4PXr14iIiEBWVha8vLwQFRUlDPRPT0+vEdTHJgbpyQCkF2SK1BWTRgwJMh6BdKFFLP70a5jb6ouMc/EyB8MwItayVl0s68yWlGRlkyXGTJEAf2WhaPalNlBfpX5xi5mgLIa4m9LRURcbNlrUuO4kJQAI2L6tFHuW8MXvjX/5gayBoexkKqlLlAGqtZYB0gmz0hfSFdLWVro48gVZWm4pcovL0cRU9mzNxgIhBM/zyvA4uwipOSVIzS3Bs9wSZBeW41XhWxS+rVmYkGEASyN92FsYwcvRAp2drODtbIVWNiZa+8VbXSxatAhff/01Ll68CF9fXwDAjRs3EBUVhd9//13ueTVekAHA5MmTJbooAeDixYt1nrtz506F1pYl0JyNumIAXwzdPJKJbkHNahVm4hawwtdiZQgYRsSaJskiVt+c6o4xY4vGIMoOHSyTunVSba7K01Hl2L6ttMY87y1qFaiqep+1OTbMWGJ9ssBQOV6AklCbKANYF2bGLVqi6FG87PvREiyM9eHa1BQpr4oRl56P/u0a9t+sRFq2BA4c4N++g8cjSM0tQcKLfMQ/L8D9lwV4mFmE4nLpqkEb6OqgkscDIcCb0kq8Ka3Ew8xC/HmTXyOujZ0Zhvu0wNDODrChIlgqQkND4eHhgXXr1uHw4cMAAA8PD1y5ckUo0ORBKwSZuvAY313qQHNFXZTiYijjUbFQoIlbqQgh9dYTS7tTgL6jnWSqH1ZbfJosaKKVDGj4okyWEqTiIqo6kuqRCSxsQPVsTX5Mmre3Hk7+836smxe7/TTZKIWhqCgD5HBhAqwLM6uuvcCrqmzYbksny3eC7E3jFGRWVngdOAQJL/Jx91YS7j7PR/zzfIkWLwNdHbSyNUHrpqZoZWMC5yYmaG5hCFszDmzNODDl6EFXh19UtYrLQ35ZJXKLK5CaU4I7z9/gzrN83H2ej6TsIvx08iGW/vsIQzo1x3f93eFobSxhc5Tq+Pr6Yu/evazOSQVZHbgEdZTKlMtGvJikIq4A8DbxOQaailZF37WtBInn6i5eK4+YktWipm00ZFE2bJj0H/riLsjqVHdHiiMplqzGeA31fCjaiFxuaxnAmjBjGAZW3h80aEHm7WyFA7dfILaRxJG9KalAYkYBEjMKkPAiH88fpqHH9Sgca98XOSZWwnGG+jpo39wCni0s0NHBAu2am6O1rSn0pYwJ09PVgY0pBzamHLSxN0PgO89PQWklTiS8xKHYF7j7PB+H72TgRMJLjPJ1xqR+rrA1oxYzVUIFmYKwFbwvED+PjqXi4YP334a6+BjUGBsnVsbAo50enFvqgssFXsNCbjHFVkV+TbWSAQ1TlM2aZSq1uxKQXIMsLq6qRjC/OJJiycRFWvKdEnwcKtv+64OtgrFsiDJATmsZIHd8GfBemPHeamdTd2nxfhfYn/AiH5VcntSCQ1t48aYU157k4nZaHm6lvUFqTonI8+2zMjD/wjZkePnC1LsjvBwt4eVoiTb2Zkp5LyyM9fFVd2d81d0ZCS/y8cvpJFxOzsHOa2n4O+4F5g70wBddtTe5S9uggkwB2MykHGT2EIO+BchEG+zeXoq42xXo4mOA0WNrfkB28THAv9U+GD/93BghYdU/kItxqpj+AdVGQxNlwSGy1QWTVBZDGiRna5aKiDT3zqayTSolmiLKAJasZYDc4qwh08rGFOaGeih8W4X7Lwvh5Wip7i0pTHJ2Ef69l4XT97Nw/2VNz0ZLGxN0dOBbvrrnGwG7gM1feQNdVNu1xLOFJfaE+eJqSg4i/32IexmFmHU4EcfuvkTkpx3hYsNuOAKlJlSQyQkbYmyg6YMajzEMg5AwEzGBJYpApNUl2gaaPsCp4nYK75FCESBJyAlEWtRNfbh35pe90HTYEmWAAtYyQCFXZkNFR4dB91ZNcOZBNs4/eqW1gqySy8Pp+1nYfe0Zbqa9b6OjwwBejpbo1rIJurW0greTNSyMq7n935UxUicfuNrg6LcfYOe1NKw4k4SYp7kIXHsJMwPbIqSHC3RoWyulQQWZHCgqxiQJMVmQRrRVX0cdwkyT3ZZAw7OSqQuBSHMfxW5xWEmw2evS0/olAFBhpoEMaG+PMw+yceZ+FsL7u6t7OzJRyeVh/810bLjwBFmF/N+rrg6DPu62CGhvB38PO60o56Gnq4Ove7XCgHb2mH0kAVdTcrHoxAOcvp+FX4Z1okH/SoIKMhlRpxgjhNRwZ0rjqqLWMoo8SNsyie1K/aqEDWsZoKAbUwAVZgAAf4+m0NVh8CirCGk5JVrhKuPxCE7dy8SK00lIyy0FANiYGmBkNyeM9HWGvYWUv1MLC2DwYP6tBuDUxBh/hPnijxvp+PnkQ1x/mofANZcwI7Atvuru3KiawH/66adSjxWUwpAVKshkQBExpqhVDAB2by/FkoX8GARBDFl9VjJtghCC1EMJyEvMhHXHZmg5zJMGk0rBnl2lmDiJ/eKOdbVMUhdsWskEsCnKAAWtZUCjjzOzNDZA91bWuJqSi9P3szC+T83+w5rE09fFmPV3otA1aWNqgKkfueHzro7g6OnKNlnr1sDx40rYpfwwDIPg7s7o7WaD6QfjcSvtDRYcv48jdzIQ+WnHRtN31EIFIpkKMiXDhhATIJ5dGXe7QmpBpg4rmaxuy9RDCbi37goA4OWFJwDAep/Lhkh9lfrlpa6WSepEWaIMUNyFCbAozIBGazULbG+v8YKsisvD75dTsfrcY1RU8WBsoIvxvVvj614tYcKR86O1shLIzwcsLQH92kvQqAPnJib465se2HvjGZZH8WukfbL+Ckb5OmFyP1c0NW/Y1+iOHTuUvkbDyilWIvJYx9gUY0DNEhiSSmLURfX9EELw3+507PwuEf/tTgch6k+nz0vMFD2+l6W0tcTjxwghyD99U2nrKZtYMbHOBj4+oh8IkmqUabO7UhICYcYGzW3zheJMYZq+BbEtQ+Gd/9iZT8Pp345fJysuPR/ZhZJr5qmTZ7kl+GzTNSyLeoSKKh56udng9LTemOrvJr8YA4DERKBpU/6tBqKjwyC4hwvOhvdBYHt7cHkEu2OeofcvFxB56iFyi8vVvUWthlrIpEBVYqy+GDFpsiulRdG+lcrAumMzoWUMkK1tlSxICubPP3VdqxuLV0rXRUUmamtKLg+EEJzelc1aE3JlWMkEsOXCFMCWxawwKgZv/jqj+Ia0AHsLQ3R2ssSd9HyceZCN4O7O6t6SkKN3MjDv6D0Ul1fB3FAPEYPb47MuDo0qvMLewhCbg71x7UkOVpxOQlx6Pn679BTbr6aifzs7DGprqe4tKp1Dhw7hwIEDSE9PR0WFmPcqLk6uOakgUwLyWsbqixGTNruyvr2dKm4nc99KaZufK4KgTVXevSxYd7CXum2VLNSWWfk2KZ31tVSJri77Fs766pXJYh07vSsbe5bw32O2m5ArAzZdmAIUFWblj5+xthdtIKC9PV+Q3c/SCEFWVsHF/GP3cCj2BQCgm4s11nzpheaWRmremfrwa22Dvyc2wYWkV1h7LhnxLwpwKjEL/9x+qu6tKZV169Zh7ty5CA0NxbFjxzBmzBg8efIEt27dwqRJk+Sel7os60FW65gibkpJMWLKQry1Un2tlgQWtbtRr3AkMhmX9jxnfU8Mw6DV8E7wWRSAVsM7sS746ipzYdhGu11vXK5qv53L6qp8HCfa/uvxneJaRmoWbLowBcjryuS4q1+UqJKA9nzBHvMkFwWltfdfVQVPXxdj6IarOBT7AjoMMPUjN+wb59uoxZgAhmHwYVs7HJvcE6em9EKonwvMDRu2rWfjxo3YsmUL1q9fDwMDA8yYMQNnz57FlClTUFBQUP8EtUAFWR30afJYpvGKxoyJx4SlPa3Crm0lrMd3DTR9gN7Bjgia7QavwKYImu1Wb6slSRa1+tCkOmT11RyzHNgd1iP9VbQb9tFX0v8/Qgi2bS3BxAn52LZV/mvRvYtoBX82Kvr3NE9WeA5pUIYoA2QXZuaBPWD1xQCl7EUTaWljgjZ2ZqjiEZx5oLx40vo4lZiJIb9eRVJ2EWxMOdj7dXd8198deg2srRMbtGtujoVD2uP89L7q3opSSU9Ph5+fHwDAyMgIRUX8bPTg4GD8+eefcs+rFVfUhg0b4OLiAkNDQ/j6+uLmzdqDr3///Xf06tULVlZWsLKygr+/f53j2YKNAP7RY40xd6E5PNrzP10fPqjCkoWF2L29VOG5xRH0rQxd3RF9RjvVa42S1aKmKTzMspOqACzDMLAM6KaCHSkHbxkTPKRFUPri5D9vsWhhEbZvK5UrkD8gxA7Bc53gO9AawXOdtKKif3WUJcoA6YUZwzAw7++rtH1oIp94NgMAbLuSCh5PtYlHFVU8LDpxH9/ujUNxeRW6tbTGqSk90aN1E+Ut2qkTUFDAv9ViDPVlLPehZdjb2yMvjx964eTkhOvXrwMAUlNTFTKgaLwg++uvvxAeHo4FCxYgLi4OnTp1QkBAAF69eiVx/MWLFzFixAhcuHABMTExcHR0xIABA5CRkaG0PbKVTSmIEXNpKWruUKbrUlpktaip2zomrRBrCMyaZapQwH1diJe+iLopXyo+wzAIDLXHlLWuCAy1Z8Udrayg/tpQpigDwF5GZgMiuIczzDh6eJRVpFIr2fO8UgzffA07rqYBAMb3boV9X/sqv7SDri5gbs6/pWgsH374IY6/qxc3ZswYfPfdd+jfvz+++OILBAUFyT2vxguyVatWYdy4cRgzZgzatWuHzZs3w9jYGNu3b5c4fu/evfj222/h5eWFtm3bYuvWreDxeIiOjlbxzuVH0fIWykBWi5q6aExCTICszcVlQbz0hbKah1P4sFoqowFgaWyA0A9cAABrziWrxEr2b2ImBq27jPgXBbAw0se2EB/MHuihGhdlcjIQEMC/pWgsW7Zswdy5cwEAkyZNwvbt2+Hh4YHFixdj06ZNcs+r0ZF3FRUViI2NxezZs4WP6ejowN/fHzExMVLNUVpaisrKSlhbW9c6pry8HOXl7+unFBYWSr1HTS9vIeu+2MikVId1rDGIMEWuU3lxG9kWwZXZeHynWKrm4WyXt6gNcesYIQSJfyYhK/417DvZouOINhr7pUEaWGnF1EAI69kSO66mvbOSZSNQSeVwit5WYtGJB8Isys5Olvh1ZBc4qDJwv6gIOHOGf0vRWHR0dKCj816gf/nll/jyyy8VnlejBVlOTg64XC7s7EQ/BOzs7PDokXTZjzNnzkTz5s3h7197wHZkZCQWLVqk0F5lQby8xeEDpfj0c2OhMGOjvEVd1FaxX9HaZKoWYo1BhFVHldepIE6MYfjlKQJDpTuvvvIWigq22tyUiX8m4erKWADAk3P89T1Hsns9slkCQxqoKONjaWyAED9nbLjwBOuikxHQnn2RfzM1D98fvIvneWXQYYCJfVtjmr879GngPuUdCQkJ6NChA3R0dJCQkFDnWE9P+Uo2abQgU5SlS5di//79uHjxIgwNa/f9z549G+Hh4cLjwsJCODrWHSOlCOIxYYLgfUC9vSllrU1WHVWKscYmxASo4jpVtPK+pPIW1cWcvPXI6osXy4p/LXqc8JpVQaZqMUYR5euerbDzahoeZBbizINsYUkMRSl8W4nlUY/wx3X+NdnCygirv/BCV5faPSqUxomXlxeysrLQtGlTeHl5gWEYiQH8DMOAy+XKtYZGCzIbGxvo6uoiOztb5PHs7GzY29f9B7lixQosXboU586dq1etcjgccDgcmfcnbzB/Fx8DYeHX6oj3phS4NmNvlYPLBXR1GXh3renilIW6+lm27GwhtIwJjqVBFWKssYqw6sh7nUqDuBATWLKS4orAqyLQ0WXQxtusXouWexdTodACasac1SfYxJE2cN++k63QMgYA9p62Up0nDVSMqR8rEwOE+Llg48UniDh2Dx0cLBRyJRJCcPp+NhYev4+sd62ZvvBxxNxPPGBuqFk9JCmaQWpqKmxtbYX3lYFGCzIDAwN4e3sjOjoaQ4cOBQBhgP7kyZNrPW/58uVYsmQJTp8+DR8fH6Xt71RxO7lEmSAm7PCBUjx88L7njXjwfnXXpoCokzUr+LOFIHOyegxZXUS/boPUQwnIS4yCdcdmaDnMk1VXAhVhykEaK1h1S5aAm1FvANRt0RLEmNUWc1afYAPky57sOKINAL5lzN7TVngsD5ogwKirsiYT+rbGuYfZeJxdjJDtN3FoQg9YGsue8HT/ZQGWnHyIa09yAQAuTYzx86cd4dfahu0ty46jI/Drr/xbikbh7Py+MPOzZ8/g5+cHPT1RCVVVVYVr166JjJUFjRZkABAeHo6QkBD4+PigW7duWLNmDUpKSjBmzBgAwOjRo+Hg4IDIyEgAwLJlyxAREYF9+/bBxcUFWVn8VGlTU1OYmsqWISZowM12uyBBjNjoscY1gvurU1u5C3FLmrTUZR0T7KvPaKd63ZQCi1jqoXjcW3cFAIQ9KFsNV6x+DhVh7CKPC5IQgkuHcyQ+V59FS1DeorYxtQk2RUtYMAwDz5Ft5XZTaoIIA6gQqwtzQ33sHNMNn268hpRXxRi3+zb2hPlKXfMqNacEGy+k4FDcCxACGOjpYFyvlvjfh26aUzfL1hZQoPUORTX069cPmZmZaNq0qcjjBQUF6NevX8N0WQLAF198gdevXyMiIgJZWVnw8vJCVFSUMNA/PT1dJNth06ZNqKiowLBhw0TmWbBgARYuXCjT2lf3v8A/q/g9uZTRgLu24H2BqzLtqeSO0fKUwahPjElLdfdkXmKmyHN597LkFmTqFmKEEOSfVn4BYWVwrcwRxnqKf6AI3JSXDufg2UPJxYglWbRkCdQXCDbTT/kC7Kqaksk0RYAJkEaIEUJQePaG8jejwTS3NMLOsV0xfHMMbqW9QeiOm5j1sQe8HC0ljieEIC79DbZceoozD7IhCPn5xLMZZga2haO1ajLYpSYvDzh1Chg4EKijMgBFvRBCJP6Py83NhYmJ/N4rjRdkADB58uRaXZQXL14UOU5LS2Nt3WcJou5CSUHu8rot60KSq1JA/0AOgscYYde2EsTdrkBnb368w53YSoklNNgQYrXFiFl3bCa0jAGAtQzp6OoSYFUZkv9YCv67hLwj51S8G3ZRNINRkpuyOj79LSWWvZAmUF/VRVwFaJvwIoSgMCoG5Y+fgePuDPPAHsLfYWFUDN78dUYFu9Rs2tqbY0uwD0J23MT1p3kYuuEqPnBtgs99HGFioAc9XQYFZZW4kpyDy8k5whgxAPiwbVNM6ucKb2crNb6COkhLA4KDgdhYKsg0kE8//RQA/4tlaGioSEwvl8tFQkKCsKWSPGiFIFMXzp7mSDz33nVTW5A7m6KMEILDB2pvlaSnx2DPjjKRshkCBPdDwkyUKsQEtBzGT5bIu5cF6w72wuPaULUIq018SaI8NU15G1ERsmYwigu4pFjJ5ipnD2P0/tSmVoEnHqh/7SaEFjBVoW3CqzYKo2KQt+ckAKDkxj0AgMXH/H/w5Y+fsbK3hkCP1k1wakovbLyYgmN3X+JqSi6upuRKHMvR08GQTs3xTe9WcLMzU/FOKQ0JCwu+BiCEwMzMDEZG7xNLDAwM0L17d4wbN07u+akgq4Oq/h8iiKMrVZA7W6Js93bRQH9xuvgY1NlK6eR1Q9h+oZgYkzZrkmEYtBreqU43pSpEmCzCqzY4LV1Qcjeehd2oD1kzGMUFnE9/S5Hn6xNiAvTatQSqBeqzmeEoCU0RX8qI9xIXXeXJ6cA7QcZxdxaKNArg2tQUqz73Qnh/d2y7korEFwWo5BFUcXnQ09VBNxcr9Ha3RVcXa82JEaNoNTt27BCWuli/fr3Mcen1QQVZHTAMA+7AAQgdLV0RWoFVShFhJi62PNrpIWi4kYhLEoDEshmA/E2/2SpdoUwBxobwqg3z3r1AKivx5p9TSltD2UiTwVgdcQGnq8cgeK6TSMB9dSFWm9ux4wj+Pyg2MhwFqFN0qTOwXlx0cdzex6yaB/YAqaikbksxWlgZY8Hg9ureBqWRQAjB3r17MWfOHLi5sesJoIJMCs7ntMWHNtKJMkA0bktWcSZeo6yFky5CwkwQ+rVoa6UH5XZIvVMAFy9zgGGQJmWpiuqwIcKUJcCUKb4kwTAMzHt+oNWCrL6SE+KICzi9dq1g+mlbdOGHSeBqkXhLIq7ElkSKZDiqWnhpehajeWAPAHzLGMfNSXiMV4ZgAJh37kMFWUPGxATo3p1/S9FIdHR04ObmhtzcXCrI1IVAvMgizADZxdnosca4eb0cZ6P4PQvPRpVj1iazGtmdfUZDNMFAyor6gOJCjG0Rpmrx1VCRVHKirmB6kyBXfPA2qU7LFlstiVQhvDRdbInwSnLnEAaAhfeHgPe7B15LHEZpqLRpA0jZp5miPpYuXYoffvgBmzZtQocOHViblwoyGZFXmAHSZzy+RiKA9xXzZWlhJAlNEWDqEl7GGdJlGnLLtbMZ9fWi1jAgslcXl8ayJW1LImULLo0RW7UIKQqF0ngYPXo0SktL0alTJxgYGIgE9wNAXl5eLWfWDRVkclJd5MgjzupC3hZG4vuSB20SX9IKLYr8iLck4rm6si6+VC62qKiiaCpxcYC3N7/sRZcu6t6NRlNeXg5fX1/Ex8fjzp078PLyEj6XkJCASZMm4datW7C1tcX//vc/zJgxQ+T8gwcPYv78+UhLS4ObmxuWLVuGgQMHSrX2mjVrWHwl76GCjAXYFmeytDDSBAGmLPFFBZdykUZYkYBmaFlqgcIHGTBv54BmQbJ/SChdcDUSgWX4itFaKy6FwjYzZsxA8+bNER8vmh1fWFiIAQMGwN/fH5s3b0ZiYiLGjh0LS0tLfPPNNwCAa9euYcSIEYiMjMQnn3yCffv2YejQoYiLi5PKBRkSEqKU10QFWR0kZdtC15j/z97DPrue0XzqEkjSijVBCyPuwLbgArggubyOXCgiwJQhvKjoUpx7b+yhV6GcpuMMw6D5p95o/qm3xOeVKrY0QGgZvqLXJ4Wiafz77784c+YM/v77b/z7778iz+3duxcVFRXYvn07DAwM0L59e9y9exerVq0SCrK1a9ciMDAQP/zwAwDgxx9/xNmzZ/Hrr79i8+bNMu3l7du3qKgQrY5gbm4u1+uigkxKxIWMtAKtOmyVlpAGRS1fbIkvTRJcphm8Op+vqqz7+caCtossKqLUR3l5OcrLy4XHhYWSO45QGgfiv38OhyNS3V4esrOzMW7cOBw9ehTGxjVbX8XExKB3794wMHjfYjAgIADLli3DmzdvYGVlhZiYGISHh4ucFxAQgKNHj0q1h5KSEsycORMHDhxAbm5Ni0mD7WWpqbAh0NjegzywIbxUKbrqE1WU96g0NktJQquhiiujV5IfL2sq+XFtITIyEosWLVL3NigagqOjaLiNPD2lq0MIQWhoKCZMmAAfHx+JrRKzsrLQsmVLkccEva+zsrJgZWWFrKws4WPVx2RlZUm1jxkzZuDChQvYtGkTgoODsWHDBmRkZOC3337D0qVL5XtxoIKsTriZJtBtLZ3SlVUciQs4ZVe012ThRUWWYmTlWECnVEmWJyUILVWJrNpEjyZT3565tTfp0Ahmz54tYnkoLCys8aFMqYN27YDkZKBFC3XvhBWeP38u4r6rzTo2a9YsLFu2rM65Hj58iDNnzqCoqAizZ89mdZ+ycuLECezevRt9+/bFmDFj0KtXL7i6usLZ2Rl79+7FqFGj5JqXCrJ6kCRk9BxKFJ5XU2t5sSm6qNDSEJTsJlSWwNJGQdXYYcMl1agxNARcXdW9C9YwNzeXKp7q+++/R2hoaJ1jWrVqhfPnzyMmJqbGNebj44NRo0Zh165dsLe3R3a2qMFDcGxvby+8lTRG8Hx95OXloVWrVgD4r1FQ5qJnz56YOHGiVHNIggoyOZBG/LAh2qRdSxYaiuAySy1jfc6qKsntqDSeHEP+P3IWYVtkqUpcmWbV3ge2IVBV2bBfX6MnNRWYPx/48UdAzO3WkLG1tYWtbf09cNetW4effvpJePzy5UsEBATgr7/+gq+vLwCgR48emDt3LiorK6Gvz6/PePbsWbRp0wZWVlbCMdHR0Zg2bZpwrrNnz6JHjx5S7bdVq1ZITU2Fk5MT2rZtiwMHDqBbt244ceIELC0tpXzVNaGCrA6MXjLQ5TAodSAyn6vO6vNsiS5lCy5liCqKKMp0DypDZDV0QUWh1MmbN8DevUB4eKMSZNLi5CTasUbQ3Lt169Zo8c7NO3LkSCxatAhhYWGYOXMm7t27h7Vr12L16tXC86ZOnYo+ffpg5cqVGDRoEPbv34/bt29jy5YtUu1jzJgxiI+PR58+fTBr1iwMHjwYv/76KyorK7Fq1Sq5Xx8VZFIgjcCRR7Sxub6ssC22qLhSH5zX/C8OisC2uFK2sDJ6XqTU+TWVInvZOzJQKI0JCwsLnDlzBpMmTYK3tzdsbGwQEREhLHkBAH5+fti3bx/mzZsnbBJ+9OhRqdsgfffdd8L7/v7+ePToEWJjY+Hq6gpPT0+5904FGUuoItOQEIK8uMsozUiFsUNLWHfpVaPRc0MVWnpPMpS/CE/DI6alQFmuQWkEFiEEL1OvouBNGiysXNC85Qc1rk8BjVVQKYpRRrG6t0ChaAwuLi4gpKYxxNPTE5cvX67z3OHDh2P48OEyrcfj8fDLL7/g+PHjqKiowEcffYQFCxbA2dkZzs7OMs0lCSrIJCD4BRuml0JXv3aBU9JMR+l7Mcl8v/6rx9eQFX8KAFCYFA/93Ao0dfcTGS+tXcIsTTqhpYidQy81U4Gz2duH1Gu8E2SS/sA1EcE+DTLeQvddyR1pcoJNsmV/N+s6QyAS0nNu40nWeQBATmYCdPKK4WTjI/N8Ql5Il4LeoGkhGmRcxeXX+NK2a5TWI5OS4uL3t1r8ngl+39pynUrLkiVLsHDhQvj7+8PIyAhr167Fq1evsH37dlbmZ0hDe8dY4MWLFzRVuxHz/PlzYTyCJkOv08YLvUYp2oC2XKfS4ubmhunTp2P8+PEAgHPnzmHQoEEoKyuDjo7iBhoqyCTA4/Hw8uVLmJmZ1epyURRBfR7xOi10DfWtQwhBUVERmjdvzsofl7JR9nWq7Peczi/7/PQapWgD2nadSguHw0FKSorIlwxDQ0OkpKSwIjypy1ICOjo6KlP10tZpoWuoZh0LCwulzc02qrpOlf2e0/llm59eoxRtQJuuU2mpqqqCoViJIX19fVRWVrIyPxVkFAqFQqFQKPUgaN1UvTDt27dvMWHCBJiYvC91dfjwYbnmp4KMQqFQKBQKpR5CQkJqPPbVV1+xNj8VZGqCw+FgwYIFSm0z0lDWUOU6lPco+z2n86t3fgqFIhs7duxQ6vw0qJ9CoVAoFApFzTSc9AcKhUKhUCgULYUKMgqFQqFQKBQ1QwUZhUKhUCgUipqhgoxCoVAoFApFzVBBRqFQGh08Xu09arUBbd8/hUKpCRVkjYDy8nLhfWUl1b569QpPnjxRytwCxPdOP5TUh7a+98+ePUNGRobWtnPR9v1TKJTaoX/VaiQ7OxuxsbE4e/YsSktLlbLGgwcP8NlnnyE6OhoAwDAM66IsISEBvXr1wunTp/H69WtW5xaQnJyMGTNm4Ntvv8Xy5csBgH4oqYHk5GQ8ffpUKe99SkoKVq9ejRkzZuDff/9FdnY2q/PfvXsX3t7euHz5Mqvzqgpt3z+FQqkb+ommJhITE9GvXz+EhYUhICAAw4cPx71791hdgxCC5cuX48qVK1izZo1SRFlycjI+/PBDfPzxxxg9ejRsbW1FnmfDkpKYmAg/Pz88e/YMSUlJ2L9/PzZv3ix8npbSUw3x8fHo0KEDTp8+zfrc9+7dQ7du3XD48GFcunQJQUFB+O677/Dvv/+yMn98fDz8/PwQGhqKL7/8UuQ5tq6fx48fIyIiAqGhodi9ezcSExNZmRdQzf4pFIp6oYJMDSQnJyMgIACfffYZjhw5gocPHyIhIQHbtm1jdR2GYWBiYoK2bdtCX18fS5cuxdmzZ4XPscFvv/2GAQMGYM2aNTAxMcH+/fuxfv167NmzBwDfiqWIKMvJycFXX32FsWPH4sCBAzh8+DDs7e1RVlYmHMMwjNa60LSFu3fvokePHpgyZQomTpzI6txlZWWYPXs2vvrqK1y8eBHXr1/H0aNHkZubi+XLl+PIkSMKzZ+UlARfX1/MnDkTK1asAJfLxdWrV3HkyBEkJiaycu08ePAAvr6+uHXrFrKzszFjxgxMmzYNO3fuVHhuVeyfQqGoH9o6ScWUlZVh5cqVGDhwIObPnw9dXV3o6upi3rx5WL9+PcrLy2FgYMCaYOrZsyecnJzQr18/REREYMWKFbC1tcWZM2fw5ZdfwsnJSaH5nz17hl69egEA/Pz8oK+vj5cvXwIANmzYgGvXrkFHRweEELleU3p6OioqKvDNN98AACwsLGBvb48rV67g9u3bsLCwwMaNG4XCj7ox2Sc5ORldu3ZFREQE5s+fj6qqKkRHRyM9PR3u7u7w8PBA06ZN5Z7fwMAAGRkZ6N69O3R1dQEAgYGBsLS0RGRkJLZs2YLmzZvD19dX5rnLy8uxePFimJiYYNCgQQCAoKAgPH36FNnZ2Xjz5g3Cw8MxceJEtGzZUq79V1ZWYunSpRg2bBi2bNkChmFw69YtbNmyBb/88ouw+bA8vH37Vun7p1AomgH99FIxXC4XFRUV6NmzJwwMDIQfQPb29sjLy0NFRQWr65mZmeH48ePo1q0bfvjhB5iYmOCTTz7BrFmzhD3yFHF5VFVV4e7du9i8eTPMzc1x5MgR3LhxA3v37kVhYSGGDh0KQH6LnImJCUpLS/HHH3+gqqoKP/74I/bs2QM3Nzc0bdoU58+fFwpCKsbYp7KyElu3boWenh68vb0BAEOGDMH333+PhQsXIjAwENOnT8f169flmp/H4+Ht27do1qwZcnJyAPD/RgCge/fumD59OtLT03H06FEAsl+rHA4H33zzDT766CNMnz4dbm5u4PF42LFjBx4/fowdO3bg999/F1p05flb0NPTQ1paGjgcjvA679q1K6ZPn46+ffti69atOH78uMzzAoChoSHCwsKUun8KhaIhEIrKefnypfB+VVUVIYSQ69evkw4dOhAejyd87uHDhwqvlZSURHx9fYXH/v7+xNjYmHTv3p1cvnxZ7nm5XC4hhJBdu3YRf39/0r9/fxIRESEyZv/+/aRdu3bk6dOncq9TUFBAZsyYQRwcHEj//v2Jnp4e+fvvv4XPnz9/ntjb25OLFy/KvQalbhITE8nUqVOJu7s7cXJyIkOGDCEJCQmEy+WSU6dOkQ4dOpDx48cTQojI9SsLv/76KzEwMCCnT58mhLy/vgghZOPGjcTMzIy8evVK6vnevn0rcnz58mUSGBhIAgMDyZMnT0SeW7p0KbG0tCS5ubly7Z3L5ZJJkyaRzz//nOTl5Yk8l5CQQAYMGEBCQkIIIdK/P8nJyWTZsmUq2T+FQtEMqCBTI9U/dK5du0acnJxIcXExIYSQOXPmkAEDBpD8/HyF1+jduzdJT08nwcHBpHnz5mTjxo1k6NChpGvXruS///5TaP5nz56RPn36EIZhSHBwsMhz//33H2nTpg1JS0tTaI3CwkLy9OlT8t9//5EOHTqQ169fC5+7ffs2cXV1JbGxsQqtQalJ9evzwYMH5JtvviEff/wxefDggci47du3E319fZKeni7VvM+ePSP79u0jGzZsIDdv3hQ+HhYWRszMzMiVK1dExp85c4Z07NhRasFx//59MmjQIHLu3DmRx2/fvk1OnDhBKisrRV7fpk2biKenJ6moqJBqfkIIyc7OJikpKcLjAwcOECMjI7Jly5YaouvgwYNET09P6i8m8fHxxNramjg7O9e41tnaP4VC0TxoDJkaqe5iq6ioQFFREfT09LBgwQIsX74cMTExsLCwkHt+QgiqqqpACEGPHj2go6ODkydPwsvLC87Ozti9ezdcXFwUmt/JyQlbtmzBl19+iZMnTyIyMhKzZ89GeXk5oqOj0aRJE5ibm8u9BsB3u5qZmYHH44HD4eDhw4dCN+WxY8dgamoKBwcHhdagvKe4uBiGhobQ09MTxuV5eHhg+vTpePHiBVxdXQFA+JyFhQXc3Nyk+j0nJiZi0KBBcHV1RVxcHLp06YKVK1eic+fOWLp0KcrKyjBgwABs2rQJvXv3hqOjI06fPg0dHR2pXNKkWmaxwH340UcfAQC8vb1F4gwFtw8fPoSrqyuqqqqgp6dXr3s9ISEBw4cPx9SpU/HZZ5/Bzs4Ow4cPR0JCAv73v//B2NgYw4YNE4YEuLm5oU2bNvXuHeBnU/bo0QOff/45jh07hv3792Py5Mms7p9CoWgo6tWDDRsulyt0SVZ/TBIxMTGka9euZPr06YTD4ZDbt2+ztsYff/xBfH19a8wpsMYpsobgNikpiQwbNow4OjqSZs2akd69exNra2ty584d1l5HdnY28fHxIf379yeff/45GTt2LLGyspJ6DUr9PHjwgAQEBJB9+/YJLS7Vfw+SXG7ff/89GTBgACkqKqpz7kePHhF7e3syd+5cUlpaStLT04m1tTX5888/Reb//vvvibW1NXFyciI+Pj6kSZMmJC4uTurX8O233xJfX18SFBRE/P39yZkzZySOS09PJ/PmzSMWFhbk3r17Us39+PFj0qRJEzJ16lSJr3fatGlER0eH/Pjjj+TmzZukoKCA/PDDD8TNzU3E2iWJO3fuECMjIzJr1izh6/Dz8yMZGRms7Z9CoWguVJApifv375NRo0aRjz76iEyYMIH8888/wufEhQchhFy9epUwDEOsra2ldr9Ju0ZFRQV58+aN8FiWOB9p1hB8YOfk5JC7d++SyMhIsnfvXhGXjqJrCPb84MEDMmHCBBIYGEjGjx9fw31GkZ/U1FTStm1boq+vT/z8/Mjff/8tUZQJSElJIXPmzCGWlpYkMTGxzrlLSkrI119/Tb755htSWVkp/H0OGzaMLFmyhCxatIjs379fOP7KlSvk4MGDZO/evSQ1NVWm17Fv3z6ydOlScuPGDRIQEEAGDBhA7ty5Q5YtW0aePXtGCCHk7t27pG/fvqRly5YyCfrvv/+ejBgxghDCvyb//PNPsm7dOrJr1y7hmOXLl5N27doRa2tr0qlTJ2Jvb1+voHz69CmxsLAQijFCCPn777+Jubk5OX/+PCFE9Hcg7/4pFIrmQgWZEnj06BGxsLAgX375JZk1axbp1KkT8fHxIdOmTROOKS8vFzknNTWVdO3aldy/f5+1NcQDm2uzzrH5OmRFljUE+y8tLSWEEBozwyKVlZXkl19+IUOGDCFxcXGkf//+xNvbW0SUVRfy9+/fJ/379ydt2rSRShCUlZWR48ePk7t37wofW7x4MWEYhowcOZL4+fmRjh07kqlTpyr8Wk6cOEH8/PwIIYScO3eOBAUFEQcHB8IwDMnKyhKOi4qKqhEgXx/Dhg0ja9euJYQQ0r17d9KrVy/SunVr0rp1a9K1a1fhNfrgwQNy4cIFcvr0afLixYt6501NTRURdQIGDx5MevfuXeNvWd79UygUzYUKMpbh8Xhkzpw55PPPPxc+VlhYSH766Sfi5eVFxo0bJzL+2LFjJDMzkxBSU0CxuYYsGWqausbRo0dJdna2yPkUduDxeCQ2NpYcOHCAEMIXu9VFmUAUV3/PL126JLQ4SUN18R4fH0+MjY3JsWPHCCF8sT1z5kzi4+Mj8juWB2VlFhNCyNChQ8mYMWPIpk2byIABA0hOTg7Jyckh169fJx4eHmTgwIEyzynpi5Lgfd6xYwdp3bo1uXXrVq1jKRRKw4AWbmIZhmHw8uVLZGVlCR8zMzPDlClT8NVXX+HOnTtYunQpAODkyZOYNGkS1q9fDy6XCwMDA6WtsXbtWpkqemviGpMnT8a6deuEa9DgZfZgGAadOnXC8OHDAQD6+vo4duwYrK2t8fPPP+PkyZOoqqoCwzDCmmC9evWSqbBw9evb09MTKSkpGDJkiDBQvXXr1igtLRUGw8uLq6srOBwOnj9/jtGjR+PBgwdYsWIF7O3tER4ejkuXLsk8p+CaCwoKwvPnz3H48GF0794dTZo0QZMmTeDr64sFCxYgLS0NqampMs0tKVlBcG2PGDEChBBs2rSp1rEUCqVhQP+6WYS8K8rYpUsXcLlcJCUlCZ8zMzPD2LFj0blzZ5w4cQIVFRUYNGgQxo4di7CwMOjq6kolMORdY+zYsVL/M28oa1BkQ1CkGOAXZzUyMsLRo0eFouzIkSOYOHEiJk2aJOzGoAj29vYA3ouMxMREdOjQQSFBRsQyiy9evIiTJ09i4sSJGDduHFq1aiVXZrFgj3379kVlZSXOnTtXQ3g1a9YMXC6XteuTy+WCw+FgxowZuHLlCmJjY1mZl0KhaChqtM41WFJSUoiNjQ0ZO3asMBNL4IJIT08nDMOQEydO0DVUtAZFPgT1rsrKykhAQAAxMDAgJiYm9SadyJJdTAg/4H/OnDnE1tZWqmxBVWQWS0JwXSYlJZHOnTsTa2tr8vPPPxNC+OEGERERxM/Pr0ZxWHn2X50HDx4QAwMDYewahUJpmFBBpiTOnz9POBwOmTRpkki6e2ZmJunUqRO5du0aXUOFa1DeI4sgEIybMGECsba2rlcwyZpdfOzYMRISEkIcHR2lKm2hisxiZZZ5kfX9EbB06VJa2oJCaeBQQaZEjh8/TjgcDvn000/J/v37yYMHD8isWbNIs2bNyPPnz+kaKl6DIp8gWL9+PWEYpl7BJE9WblpaGlm1apVUJVJUkVmszDIv8rw/dYk0CoXSsKCCTMnExsaSPn36EGdnZ9K6dWvi7u4uU5FLuga7azRm5C1j8urVq3rFhiLZxdKIJlVk/SqzzIsq9k+hULQbKshUQEFBAUlNTSUJCQn1Vuumayh/jcaIKgRBaGgo6d27t8hjhYWFZMWKFcTHx4dERkYSQgj5559/SIsWLcicOXMIl8uV2p0o6/xz586V2kKmie+PLPunUCjaD01XUwHm5uZwcXFBx44dYWNjQ9dQ8xqNEWWWMSEKZBfr6OjUm10s7/yyZORq4vtDM4oplEaGmgUhhUJRMgIL1Lp168gHH3xAHj16JPJ8Xl4eGTduHPHz8xO65CIiImSuAq/sjFllzd9Q3h8KhaLdUEFGoTQSVCEIlJ0xq8z5G8L7Q6FQtBc9dVvoKBSKamjdujUOHDiAjz/+GEZGRli4cKHQLayvrw9PT080adJEoTX69euHgwcPYvjw4cjMzMTnn38OT09P7N69G69evYKjo6PGzt8Q3h8KhaK9MIS8C3CgUCiNghMnTmD48OEYNGiQiCDYtWsXbt68iRYtWii8RlxcHMLDw5GWlgY9PT3o6upi//796Ny5MwuvQLnzN4T3h0KhaB9UkFEojRBVCILCwkLk5eWhqKgIzZo1Yz1JQ5nzN4T3h0KhaBdUkFEojRQqCOqGvj8UCkWVUEFGoVAoFAqFomZokRsKhUKhUCgUNUMFGUXIzp07YWlpKTxeuHAhvLy81LYfCoVCoVAaC1SQUWpl+vTpiI6OVvc2KBQKhUJp8NA6ZA2QiooKGBgYKDyPqakpTE1NWdgRhUKhUCiUuqAWsgZA3759MXnyZEybNg02NjYICAjAqlWr0LFjR5iYmMDR0RHffvstiouLRc7buXMnnJycYGxsjKCgIOTm5oo8L+6y7Nu3L6ZNmyYyZujQoQgNDRUeb9y4EW5ubjA0NISdnR2GDRvG9sulUCgUCqXBQQVZA2HXrl0wMDDA1atXsXnzZujo6GDdunW4f/8+du3ahfPnz2PGjBnC8Tdu3EBYWBgmT56Mu3fvol+/fvjpp58U2sPt27cxZcoULF68GElJSYiKikLv3r0VfWkUCoVCoTR4qMuygeDm5obly5cLj9u0aSO87+Ligp9++gkTJkzAxo0bAQBr165FYGCgUKS5u7vj2rVriIqKknsP6enpMDExwSeffAIzMzM4OzvTyuMUCoVCoUgBtZA1ELy9vUWOz507h48++ggODg4wMzNDcHAwcnNzUVpaCgB4+PAhfH19Rc7p0aOHQnvo378/nJ2d0apVKwQHB2Pv3r3C9SiU2rh48SIYhkF+fr66t0KhUChqgwqyBoKJiYnwflpaGj755BN4enri77//RmxsLDZs2ACAH/AvLzo6OhCvI1xZWSm8b2Zmhri4OPz5559o1qwZIiIi0KlTJ/pBSxFBUiwiGzAMg6NHj7I+L4VCoagCKsgaILGxseDxeFi5ciW6d+8Od3d3vHz5UmSMh4cHbty4IfLY9evX65zX1tYWmZmZwmMul4t79+6JjNHT04O/vz+WL1+OhIQEpKWl4fz58wq+IgqFQqFQGjZUkDVAXF1dUVlZifXr1+Pp06fYs2cPNm/eLDJmypQpiIqKwooVK5CcnIxff/213vixDz/8ECdPnsTJkyfx6NEjTJw4UcT69c8//2DdunW4e/cunj17ht27d4PH44nEs1EaN6Ghofjvv/+wdu1aMAwDhmGQlpYGgP9FwsfHB8bGxvDz80NSUpLIuceOHUOXLl1gaGiIVq1aYdGiRaiqqgLAj5MEgKCgIDAMIzx+8uQJ/u///g92dnYwNTVF165dce7cOVW9XAqFQpEaKsgaIJ06dcKqVauwbNkydOjQAXv37kVkZKTImO7du+P333/H2rVr0alTJ5w5cwbz5s2rc96xY8ciJCQEo0ePRp8+fdCqVSv069dP+LylpSUOHz6MDz/8EB4eHti8eTP+/PNPtG/fXimvk6J9rF27Fj169MC4ceOQmZmJzMxMODo6AgDmzp2LlStX4vbt29DT08PYsWOF512+fBmjR4/G1KlT8eDBA/z222/YuXMnlixZAgC4desWAGDHjh3IzMwUHhcXF2PgwIGIjo7GnTt3EBgYiMGDByM9PV3Fr5xCoVDqhjYXp1AoKqVv377w8vLCmjVrAPCD+vv16ydMRAGAU6dOYdCgQSgrK4OhoSH8/f3x0UcfYfbs2cJ5/vjjD8yYMUPojmcYBkeOHMHQoUPrXL9Dhw6YMGECJk+erJTXR6FQKPJAy15QKBSNwNPTU3i/WbNmAIBXr17ByckJ8fHxuHr1qtAiBvBjGN++fYvS0lIYGxtLnLO4uBgLFy7EyZMnkZmZiaqqKpSVlVELGYVC0TioIKNQKBqBvr6+8D7DMAAAHo8HgC+sFi1ahE8//bTGeYaGhrXOOX36dJw9exYrVqyAq6srjIyMMGzYMIWyjSkUCkUZUEFGoVBUioGBAbhcrkzndOnSBUlJSXB1da11jL6+fo15r169itDQUAQFBQHgCztBEgGFQqFoElSQUSgUleLi4oIbN24gLS0NpqamQitYXUREROCTTz6Bk5MThg0bBh0dHcTHx+PevXvCll8uLi6Ijo7GBx98AA6HAysrK7i5ueHw4cMYPHgwGIbB/PnzpVqPQqFQVA3NsqRQKCpl+vTp0NXVRbt27WBraytVPFdAQAD++ecfnDlzBl27dkX37t2xevVqODs7C8esXLkSZ8+ehaOjo7Bl16pVq2BlZQU/Pz8MHjwYAQEB6NKli9JeG4VCocgLzbKkUCgUCoVCUTPUQkahUCgUCoWiZqggo1AoFAqFQlEzVJBRKBQKhUKhqBkqyCgUCoVCoVDUDBVkFAqFQqFQKGqGCjIKhUKhUCgUNUMFGYVCoVAoFIqaoYKMQqFQKBQKRc1QQUahUCgUCoWiZqggo1AoFAqFQlEzVJBRKBQKhUKhqBkqyCgUCoVCoVDUzP8D9FY9fp1RrCoAAAAASUVORK5CYII=", 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", 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", + "image/png": 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", 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" ] @@ -3059,11 +2842,7 @@ { "cell_type": "markdown", "id": "2c5e685e-7117-4b21-a7a5-3c975fe3acf8", - "metadata": { - "jupyter": { - "source_hidden": true - } - }, + "metadata": {}, "source": [ "# Plot policies" ] @@ -3093,23 +2872,23 @@ "metadata": {}, "outputs": [], "source": [ - "cr_gp_preargs = {'radius': cr_gp.x[0], 'theta': cr_gp.x[1], 'y2': cr_gp.x[2]}\n", + "cr_gp_preargs = {'log_radius': cr_gp.x[0], 'theta': cr_gp.x[1], 'y2': cr_gp.x[2]}\n", "cr_gp_args = {}\n", - "cr_gp_args['x1'] = cr_gp_preargs['radius'] * np.sin(cr_gp_preargs['theta'])\n", - "cr_gp_args['x2'] = cr_gp_preargs['radius'] * np.cos(cr_gp_preargs['theta'])\n", + "cr_gp_args['x1'] = (10 ** cr_gp_preargs['log_radius']) * np.sin(cr_gp_preargs['theta'])\n", + "cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", "cr_gp_args['y2'] = cr_gp_preargs['y2']\n", "\n", - "cr_gbrt_preargs = {'radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", + "cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", "cr_gbrt_args = {}\n", - "cr_gbrt_args['x1'] = cr_gbrt_preargs['radius'] * np.sin(cr_gbrt_preargs['theta'])\n", - "cr_gbrt_args['x2'] = cr_gbrt_preargs['radius'] * np.cos(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", "cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", "\n", "msy_gp_args = {'mortality': msy_gp.x[0]}\n", "msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", "\n", - "esc_gp_args = {'escapement': esc_gp.x[0]}\n", - "esc_gbrt_args = {'escapement': esc_gbrt.x[0]}\n", + "esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", + "esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", "\n", "#\n", "\n", @@ -3127,7 +2906,7 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 105, "id": "88d5b45d-eeed-4321-9e9d-1a58ba63e84c", "metadata": {}, "outputs": [ @@ -3135,16 +2914,38 @@ "data": { "text/plain": [ "(,\n", - " )" + " ,\n", + " ,\n", + " )" ] }, - "execution_count": 107, + "execution_count": 105, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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", 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", 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oAQB47bXXEBkZCZlMhqioKADAoEGDAOCec6r82bZt22odevz444/Dy8sLgwcPhre3N/r16wcvLy/Ex8fj888/x/Dhw/V9Q95//33s2bMHAwYM0A+jTktLw9atW3Ho0CGoVCo88cQTWLhwISZMmIC+ffvi3Llz2Lhxo/5/7XdydXXFww8/jAkTJiAjIwPLli1D27ZtMWnSJACAVCrFv/71LwwdOhQdO3bEhAkT0LJlS6SmpmL//v1QKpXYsWNH3U76fbzwwgv47rvv8Pe//x379+9Hv379oNVqcenSJXz33Xf4+eefa+1gfS/VP8N33nkHUVFRsLW1xZNPPnnX1pnnnnsO58+fx+LFi3H06FFERUUhICAAxcXFOH/+PL799ls4OTkZ9DlqDElJSXjqqacwZMgQxMbG4t///jeee+45dO3aFUDj/w0sX74cDz/8MB566CHExMQgICAA169fx86dO2t0oI6OjsaoUaMAAIsWLWqU4yUrYarhW0TNweXLl8WkSZOEv7+/kMvlwsnJSfTr10+sWLFClJWV6dfTaDRiwYIFIiAgQNja2go/Pz8xe/Zsg3WEqBomXtvw7zuHzr777rsiLCxMqFQqYW9vL0JCQsR7770nKioq9OtUVlaKV199VXh4eAiJRGIwZLxNmzaiTZs29z2+ew0TByD2798vhBDiyy+/FP379xdubm5CoVCIoKAg8dZbb4mCggKD/d24cUNER0cLDw8PoVAoRGBgoJg8ebIoLy8XQlQNE58+fbrw8fER9vb2ol+/fiI2NrbG8VcPE//222/F7Nmzhaenp7C3txfDhw+vMXRYCCFOnTolnn76aX19bdq0EaNHjxb79u2rcaxZWVkG244bN044OjrW+jO5c2h8RUWF+PDDD0XHjh2FQqEQLi4uokePHmLBggUG5wKAmDx5co19tmnTxmDouRBCLFq0SLRs2VJIpdI6Dxk/cOCAGDVqlPDx8RG2trZCqVSKnj17innz5om0tLT7HkddVZ+zixcvilGjRgknJyfh4uIipkyZIkpLSw3WrevfQF2GiQshxPnz58Vf/vIXoVKphJ2dnWjfvr2YM2dOjRrLy8uFi4uLcHZ2rlET0b1IhDBSmycR0V0cOHAAjz76KLZu3ar/3zk1vfnz52PBggXIyspqtpd+Kisr4evriyeffLJG3y6ie2EfHCIiara2b9+OrKwsREdHm7oUMjPsg0NERM1OXFwczp49i0WLFqF79+4YMGCAqUsiM8MWHCIiana++OILvPzyy/D09Kxxs1qiumAfHCIiIrI4bMEhIiIii8OAQ0RERBbHKjsZ63Q63Lp1C05OTk0+HT4RERE1jBAChYWF8PX1hVR67zYaqww4t27dqnHjPCIiIjIPKSkpaNWq1T3XscqAUz31fEpKCpRKpYmrISIiorpQq9Xw8/PTf47fi1UGnOrLUkqlkgGHiIjIzNSlewk7GRMREZHFYcAhIiIii8OAQ0RERBbHKvvg1JVWq4VGozF1Gc2GXC6/77A8IiKi5oABpxZCCKSnpyM/P9/UpTQrUqkUAQEBkMvlpi6FiIjonhhwalEdbjw9PeHg4MDJAPHH5IhpaWlo3bo1zwkRETVrDDh30Gq1+nDj5uZm6nKaFQ8PD9y6dQuVlZWwtbU1dTlERER3xQ4Vd6juc+Pg4GDiSpqf6ktTWq3WxJUQERHdGwPOXfASTE08J0REZC4YcIiIiMjiMOCQ3rp166BSqUxdBhER0QNjwCEiIiKLw1FURERE1CiEECiu0CK/pAJyGyk8nexMVgsDjgUZOHAgOnXqBAD45ptvYGtri5dffhkLFy6ERCJBXl4epk6dih07dqC8vBwDBgzA8uXLERwcbOLKiYiouamo1CG/pAJ5JRrklVTc8b0GecUVyC/VIL/6eYkGBaUV0GgFAGBCP3/Me7KjyepnwKkDIQRKNU0/NNreVlbvkUvr16/HxIkTcfToURw/fhwxMTFo3bo1Jk2ahPHjx+PKlSv48ccfoVQqMXPmTAwbNgwXL17kvDZERBasUqtDfmlVKMkprjD4mltS9bU6vOQWVwWWovLKBr+fXCaFVica8QjqjwGnDko1WnSY+3OTv+/FhZFwkNfvR+Tn54dPP/0UEokE7du3x7lz5/Dpp59i4MCB+PHHH3H48GH07dsXALBx40b4+flh+/btePbZZ41xCEREZAQarU4fUnKKKpBTXI6coqpw8ufvc28HloJSDUQD8oZUAqgc5FA52MLFQQ4XB1uo/vS1ernK/vZyR1uo7OWws5WafGoRBhwL07t3b4Nfqj59+uDjjz/GxYsXYWNjg/DwcP1rbm5uaN++PeLj401RKhER3VbddyW7sBzZReXILqpAdlFVUMkuKkdOcdWynKJy5NxuYakviQRwtreFq6Mcrg5yqBzkcHOUw8VRDlfH6gAjh2uL218d5HCys4FUap5zoDHg1IG9rQwXF0aa5H2JiMh8lWm0yCosR2ZhObJuh5eswnJkFf3xvHpZmUZXr31LJagKK7cfbi0UcKv+/vZzFwc53FpULVPZ28JGZj2Dpxlw6kAikdT7UpGpxMXFGTz//fffERwcjA4dOqCyshJxcXH6S1Q5OTlISEhAhw4dTFEqEZHZKiqvRIa6DJnqcmQW/ulrYbnB94Vl9evHYm8rg7uTHO4tFLcff3zv1kION8eqr+4tFHC2t4XMTFtXmoJ5fGpTnSUnJ2PatGl46aWXcPLkSaxYsQIff/wxgoODMWLECEyaNAlffvklnJycMGvWLLRs2RIjRowwddlERM1CeaUWmepypKvLkKEuQ3pBVVDJuP08Q131fUlF3QeeyG2k8GihgIeTAp5OCrg7KeDR4o+vHn8KNI4Kfiw3Fp5JCxMdHY3S0lKEhYVBJpNh6tSpiImJAQCsXbsWU6dOxRNPPIGKigr0798fu3bt4ggqIrIKxeWVSCuoCi1pBaVVX2+HmPSCMqSry5BbXFHn/TkpbOChVMDLyQ6eyqrw4nn7e48WiqqvTnZQ2tmYvMOtNZII0ZB+1eZNrVbD2dkZBQUFUCqVBq+VlZUhKSkJAQEBsLMz3QRFDTFw4EB069YNy5YtM8r+zfncEJFlK6/UIr2gDKn5pbiVX4a0/FLcuh1k0vLLcKugtM6Xi+Q2Ungr7eCttIOXsx28nBTwdraDp7Lqe0+lHbyUCrPpumBJ7vX5fSf+dIiIqNkrKNUgNa8UqfmluJlXglu3g8zN/FLcyi9FVmF5nfbjpLCBj8oO3s728LkdYHycq8KM9+2vKgdbtrhYAAYcIiIyuYJSDW7mlSAltyrA3Mwrvf0oQWpeKQrrMOmcna0Uvs728FXZw1dlBx/nqq/ezvbwda4KME52vCRvLZok4KxcuRJLlixBeno6unbtihUrViAsLKzWdQcOHIj//e9/NZYPGzYMO3fuBACMHz8e69evN3g9MjISu3fvbvzizciBAwdMXQIRUa0qKnVIzS9Fcm4JknNLkJJbguScEqTkVX2vrsPlIzdHOVq62KOlqurhq7LXP/dxtoOro5wtL6Rn9ICzZcsWTJs2DatWrUJ4eDiWLVuGyMhIJCQkwNPTs8b633//PSoq/ujklZOTg65du9aYaXfIkCFYu3at/rlCoTDeQRAR0X0VlVfiRk4xknNKcD2nBMm5xbiRU4IbOSVIKyjF/Wbud3OUo5WLPVq5OqCViz38XKq+tnKpCjPs80L1YfTflk8++QSTJk3ChAkTAACrVq3Czp07sWbNGsyaNavG+q6urgbPN2/eDAcHhxoBR6FQwNvb22h1W2Hf6/viOSGikopKJGUX43p2Ca7nFN/+vhjXc0qQXXTvfjD2tjK0dnWAn6sDWrs6oLWrPfxuP2+psucQaWpURv1tqqiowIkTJzB79mz9MqlUioiICMTGxtZpH6tXr0ZUVBQcHR0Nlh84cACenp5wcXHBY489hnfffRdubm617qO8vBzl5X/84anV6ru+X/WQ6ZKSEtjb29epRmtR3bImk3GGZSJLVqnVISWvFNeyinAtqxjXsouRlF2E69klSFeX3XNbV0c52rg5wN/NEa1dHdDG7XaYcXOARwsFLyFRkzFqwMnOzoZWq4WXl5fBci8vL1y6dOm+2x89ehTnz5/H6tWrDZYPGTIETz/9NAICAnD16lW8/fbbGDp0KGJjY2v98F28eDEWLFhQp5plMhlUKhUyMzMBAA4ODvyDBKDT6ZCVlQUHBwfY2PB/WUSWoKi8EteyipCYWYSrWUW4mlmMxKwi3MgphkZ79xZbFwdb+Ls7IsDNEf7utx9uDmjj5ghne3bipeahWX9SrV69Gp07d67RITkqKkr/fefOndGlSxcEBQXhwIEDGDRoUI39zJ49G9OmTdM/V6vV8PPzu+v7Vl/6qg45VEUqlaJ169YMfERmpqBEg8uZhbicUYjEzCL9I63g7q0xChspAtwdEeTRAgHujgj0cESAe9VD5SBvwuqJGsaoAcfd3R0ymQwZGRkGyzMyMu7bf6a4uBibN2/GwoUL7/s+gYGBcHd3R2JiYq0BR6FQ1KsTskQigY+PDzw9PaHR1P+OrZZKLpdDKrWeG7URmZui8kpczijE5fRCJGRUBZrLGUX3nCPGvYUCbT2rgkxbzxYI9GiBIA9H+Drbm+1dpIkAIwccuVyOHj16YN++fRg5ciSAqksd+/btw5QpU+657datW1FeXo7nn3/+vu9z8+ZN5OTkwMfHpzHK1pPJZOxvQkTNTqVWh6TsYlxKL8SldDUS0gsRn1aI1PzSu27j62yHtl5OaOdZFWSCvVqgrYcTnB14SYksk9EvUU2bNg3jxo1Dz549ERYWhmXLlqG4uFg/qio6OhotW7bE4sWLDbZbvXo1Ro4cWaPjcFFRERYsWIBnnnkG3t7euHr1KmbMmIG2bdsiMjLS2IdDRNSkCko0uJimRnz1I12NyxlFqKjU1bq+p5MC7b2d0N7LCe28nKqCjGcLTnBHVsfoAWfMmDHIysrC3LlzkZ6ejm7dumH37t36jsfJyck1LnskJCTg0KFD2LNnT439yWQynD17FuvXr0d+fj58fX0xePBgLFq0iHPhEJHZEkIgQ12O86kFuHBLjQu3CnAxTY2bebW3yjjKZWjn7YQQbyVCvJ30ocbFkf1jiADebPO+N+siImpsQgikFZTh7M0CnEvNx/nUqkCTXVT7naxbquzRwVeJUB8lOvg4IdRHCT8XB/aRIavDm20SETUj2UXlOJOSjzM3C3DuZj7OpdYeZqQSINjTCR19lejgq0RHX2d08FVy6DVRAzDgEBE1otIKLc7fKsCp5DycSSnA6ZT8Wjv/yqQStPdyQueWzujUyhmdfJUI8VbCXs6BDUSNgQGHiKiBhBC4mVeKEzfycOJGHk6l5OFSWiEq77jpkkQCBHm0QJdWzujS0hld/FTo4KOEnS3DDJGxMOAQEdVRRaUOF24V4Pj1qkBzIjmv1jlmPJwU6O6nQrfWKnRrpUKnVs5QchQTUZNiwCEiuoui8kqcvJGHY9dzcex6Lk6n5KNMYzg821YmQUdfZzzU2gUPtVGhe2sX+DrbccZvIhNjwCEiuq2gVINjSbmIS8rB0aRcnL+lhvaOy00uDrbo6e+Knm1c0KONCzq1dOalJqJmiAGHiKxWYZkGx67nIvZqDn6/losLtwpwR55BKxd7hAW4IszfFT39XRHk4cjWGSIzwIBDRFajvFKLkzfyceRqNg4nZuPMzYIaLTSB7o4ID3RFeIAbegW4oqXK3kTVEtGDYMAhIoslhMCVzCIcvJyF365kIy4pp0YfmjZuDugT6IY+QW4ID3CDt7OdiaolosbEgENEFqWgRIPfErPwv4QsHLyShQy14Sgn9xYK9Gvrhn5B7ujb1g2tXBxMVCkRGRMDDhGZNSEELtxSY/+lTBy4nIVTyXkG/WjsbKUIC3BD/2B3PBLsgXZeLdiHhsgKMOAQkdkpqajE4cQc/HopA/svZSFdXWbwerBnCwxs74EB7TzR09+Fo5yIrBADDhGZhazCcuyLz8Deixk4lJiN8so/+tLY28rQr607Hg3xwIB2HrzsREQMOETUfCXnlGD3hTTsPp+OUyn5EH+69NRSZY+IUE88GuKJ3oFubKUhIgMMOETUrFzJKMSuc+nYfSEd8Wlqg9e6tHJGRKgXHu/ghRBvJ/alIaK7YsAhIpNLzCzET2fTsOtcGi5nFOmXy6QShAe4Ymgnb0R08IKPM+ekIaK6YcAhIpNIyS3Bj2du4cfTt5CQUahfbiuT4JFgDwzp5I2IUC+4OspNWCURmSsGHCJqMtlF5dh5Ng3/PZ2Kk8n5+uXVoWZ4Zx9EdPCCsz3vvE1ED4YBh4iMqkyjxS/xGfj+ZCr+dzlLf2sEqQToE+SGp7r6YkhHHzg7MNQQUeNhwCGiRieEwMnkfGw7kYKfzqahsKxS/1rXVs4Y0a0lnujiA08lb4tARMbBgENEjSazsAw/nEzFd8dTcDWrWL+8pcoeI7v74i/dW6GtZwsTVkhE1oIBh4geiFYncPBKFr6NS8a+S5n6S1D2tjIM7eyNZ3v4ITzAFVIph3QTUdNhwCGiBslUl+G74yn49mgKUvNL9cu7t1ZhdE8/PNHFB0527FdDRKbBgENEdSaEwLHreVgfex0/n09H5e3WGqWdDZ5+qBWeC2+Ndl5OJq6SiIgBh4jqoLRCi+2nU7H+yHVcSv9jzpqHWqvwXHgbPNHFh7dKIKJmhQGHiO4qvaAMG2KvY2NcMgpKNQAAO1spRnZrieg+/ujgqzRxhUREtWPAIaIazqcWYPWhJOw4c0t/GcrP1R7Rvf3xbM9WUDlwdmEiat4YcIgIQFX/mkOJ2fjiwFUcuZqjXx7m74qJjwQgItQLMo6EIiIzwYBDZOW0OoHd59Pxxf8ScT616u7dMqkET3TxwcSHA9Cllcq0BRIRNQADDpGV0mh12H4qFf88cBVJ2VWT8tnbyhAV5ocXHwlESxXv3E1E5osBh8jKVFTq8MOpm1i5/yqSc0sAACoHW4zr449xff15924isggMOERWQqPVYduJm/j810T9xHxujnLE9A/E873bwFHBfw6IyHLwXzQiC6fVCew4cwuf/nIZN3KqWmw8nBR4qX8gxoa3gb2c89cQkeVhwCGyUEII7LmYgU/2XEZCRtXkfO4t5Hh5YFuMDW/NifmIyKIx4BBZoBM38vD+rnicuJEHoOpWCi8NCML4vv68FEVEVkHaFG+ycuVK+Pv7w87ODuHh4Th69Ohd1123bh0kEonBw87OzmAdIQTmzp0LHx8f2NvbIyIiAleuXDH2YRA1e9ezi/HKxhN45osjOHEjD/a2Mkx+NAi/zXwMkx9ty3BDRFbD6P/abdmyBdOmTcOqVasQHh6OZcuWITIyEgkJCfD09Kx1G6VSiYSEBP1zicRwcrGPPvoIy5cvx/r16xEQEIA5c+YgMjISFy9erBGGiKxBQYkGy/Zdxr9/vwGNVkAqAZ7t4Ydpg9vBS8m/CSKyPhIhhDDmG4SHh6NXr174/PPPAQA6nQ5+fn549dVXMWvWrBrrr1u3Dq+//jry8/Nr3Z8QAr6+vpg+fTrefPNNAEBBQQG8vLywbt06REVF3bcmtVoNZ2dnFBQUQKnkvXTIfGl1AluOpWDpngTkFlcAAAa088DsYSEI8ebvNhFZlvp8fhv1ElVFRQVOnDiBiIiIP95QKkVERARiY2Pvul1RURHatGkDPz8/jBgxAhcuXNC/lpSUhPT0dIN9Ojs7Izw8/K77LC8vh1qtNngQmbtj13Px1OeH8PYP55BbXIFgzxb4ZmIY1v8tjOGGiKyeUS9RZWdnQ6vVwsvLy2C5l5cXLl26VOs27du3x5o1a9ClSxcUFBRg6dKl6Nu3Ly5cuIBWrVohPT1dv48791n92p0WL16MBQsWNMIREZledlE53t8Zj+9PpQKo6kD8xuPt8HzvNrCVNUm3OiKiZq/Z9Tjs06cP+vTpo3/et29fhIaG4ssvv8SiRYsatM/Zs2dj2rRp+udqtRp+fn4PXCtRU9LpBLYcT8EH/3cJBaUaSCRAVK/WeHNwO7i1UJi6PCKiZsWoAcfd3R0ymQwZGRkGyzMyMuDt7V2nfdja2qJ79+5ITEwEAP12GRkZ8PHxMdhnt27dat2HQqGAQsEPADJf8WlqvPPDOZxMzgcAdPRV4v2/dEZXP5VJ6yIiaq6M2p4tl8vRo0cP7Nu3T79Mp9Nh3759Bq0096LVanHu3Dl9mAkICIC3t7fBPtVqNeLi4uq8TyJzUVGpwyd7EvDkikM4mZwPR7kMc5/ogP9O7sdwQ0R0D0a/RDVt2jSMGzcOPXv2RFhYGJYtW4bi4mJMmDABABAdHY2WLVti8eLFAICFCxeid+/eaNu2LfLz87FkyRLcuHEDL774IoCqIeOvv/463n33XQQHB+uHifv6+mLkyJHGPhyiJnMmJR8ztp3Vz0I8uIMXFozoCB9n3uWbiOh+jB5wxowZg6ysLMydOxfp6eno1q0bdu/ere8knJycDKn0j4akvLw8TJo0Cenp6XBxcUGPHj1w5MgRdOjQQb/OjBkzUFxcjJiYGOTn5+Phhx/G7t27OQcOWYQyjRaf/nIZXx+8Bp2ouiHmwhGdMKyzd405oYiIqHZGnwenOeI8ONRcnU8twBtbTuNKZhEAYEQ3X8x7siNcHeUmroyIyPTq8/nd7EZREVkjrU7gq4PX8MneBGi0Au4tFFj8dGc83sHr/hsTEVENDDhEJpaSW4Lp353B0eu5AIDIjl5Y/HQXttoQET0ABhwiE9p5Ng2z/nMWheWVcJTLMO+pjni2Ryv2tSEiekAMOEQmUKbR4t2dF/Hv35MBAA+1VmHZmO5o7eZg4sqIiCwDAw5RE0vKLsbkjSdxMa3qnmivDAzCtMfbwYa3WSAiajQMOERN6KeztzBz21kUV2jh6ijHp2O6YUA7D1OXRURkcRhwiJpApVaHJT8n4MuD1wAAYQGuWB7VHd7OnLuJiMgYGHCIjCyvuAKvfnsKhxKzAQAvDQjEW4Pb85IUEZERMeAQGdGFWwV46ZsTuJlXCntbGZY82wVPdPE1dVlERBaPAYfISP7vXBre+O40yjQ6tHFzwJcv9ECIN2fOJiJqCgw4RI1MCIEvD17DB/93CQDQv50HVkR1h7ODrYkrIyKyHgw4RI1Io9XhHz+cx5bjKQCA8X398Y/hoexvQ0TUxBhwiBpJQakGL//7BI5czYFUAsx5ogMm9AswdVlERFaJAYeoEaQVlCJ69VFcySyCg1yGFX/tjkGhvFEmEZGpMOAQPaBrWUV4YfVRpOaXwkupwJrxvdDR19nUZRERWTUGHKIHcO5mAcatPYrc4goEuDtiw9/C4OfK+0kREZkaAw5RAx1JzMakDcdRXKFFp5ZKrJsQBvcWClOXRUREYMAhapC9FzMweeNJVGh16BPohq+ie8DJjsPAiYiaCwYconr6+UI6pmw6CY1WILKjFz6L6g47W5mpyyIioj9hwCGqh/87l4ZXvz2FSp3Ak1198enorpzjhoioGeK/zER1tPNsGqbcDjcjujHcEBE1Z2zBIaqDHWdu4fUtp6HVCTzdvSWWPNsVMqnE1GUREdFdMOAQ3cfeixn6cDOqRyt8+EwXhhsiomaOAYfoHo4kZmPyppP6lpuPnukCKcMNEVGzxw4ERHdxOiUfL244jopKHQZ38MJHoxhuiIjMBQMOUS0S0gsxfu1RlFRo0a+tG5b/tTs7FBMRmRH+i010h+ScErywOg75JRp081Phqxd6cp4bIiIzw4BD9Cf5JRUYv+4oMgvLEeLthHUTesFRwa5qRETmhgGH6LbySi1ivjmBa1nF8HW2w4a/hUHlIDd1WURE1AAMOEQAhBCYse0sjiblwklhg7UTwuCptDN1WURE1EAMOEQAPt17Gf89fQs2Ugn++fxDaO/tZOqSiIjoATDgkNXbejwFy39NBAC895dOeCTYw8QVERHRg2LAIat2/Hou3v7hHADglYFBGNOrtYkrIiKixsCAQ1YrQ12GlzeehEYrMKyzN94c3N7UJRERUSNhwCGrVFGpw8v/PoGswnK082qBJaO6cpZiIiIL0iQBZ+XKlfD394ednR3Cw8Nx9OjRu6779ddf45FHHoGLiwtcXFwQERFRY/3x48dDIpEYPIYMGWLswyALsmDHBZxMzofSzgZfvdCTc90QEVkYowecLVu2YNq0aZg3bx5OnjyJrl27IjIyEpmZmbWuf+DAAfz1r3/F/v37ERsbCz8/PwwePBipqakG6w0ZMgRpaWn6x7fffmvsQyELseVYMjbGJUMiAT6L6g5/d0dTl0RERI1MIoQQxnyD8PBw9OrVC59//jkAQKfTwc/PD6+++ipmzZp13+21Wi1cXFzw+eefIzo6GkBVC05+fj62b9/eoJrUajWcnZ1RUFAApVLZoH2QeTqdko/Rq2JRodVh+uPt8OqgYFOXREREdVSfz2+jtuBUVFTgxIkTiIiI+OMNpVJEREQgNja2TvsoKSmBRqOBq6urwfIDBw7A09MT7du3x8svv4ycnJy77qO8vBxqtdrgQdanoFSDyRtPokJbdXfwyY+2NXVJRERkJEYNONnZ2dBqtfDy8jJY7uXlhfT09DrtY+bMmfD19TUISUOGDMGGDRuwb98+fPjhh/jf//6HoUOHQqvV1rqPxYsXw9nZWf/w8/Nr+EGRWRJC4O0fziE1vxR+rvZYOpqdiomILFmz7ln5wQcfYPPmzThw4ADs7P6YNj8qKkr/fefOndGlSxcEBQXhwIEDGDRoUI39zJ49G9OmTdM/V6vVDDlWZsuxFOw8mwYbqQTLo7pDaWdr6pKIiMiIjNqC4+7uDplMhoyMDIPlGRkZ8Pb2vue2S5cuxQcffIA9e/agS5cu91w3MDAQ7u7uSExMrPV1hUIBpVJp8CDrkZhZiPk7LgAApg9uj+6tXUxcERERGZtRA45cLkePHj2wb98+/TKdTod9+/ahT58+d93uo48+wqJFi7B792707Nnzvu9z8+ZN5OTkwMfHp1HqJstRptFiyqZTKNPo8EiwO17qH2jqkoiIqAkYfZj4tGnT8PXXX2P9+vWIj4/Hyy+/jOLiYkyYMAEAEB0djdmzZ+vX//DDDzFnzhysWbMG/v7+SE9PR3p6OoqKigAARUVFeOutt/D777/j+vXr2LdvH0aMGIG2bdsiMjLS2IdDZub9XfG4lF4IN0c5Pma/GyIiq2H0PjhjxoxBVlYW5s6di/T0dHTr1g27d+/WdzxOTk6GVPpHzvriiy9QUVGBUaNGGexn3rx5mD9/PmQyGc6ePYv169cjPz8fvr6+GDx4MBYtWgSFQmHswyEzciAhExtibwAAPh7dFZ5OdvfZgoiILIXR58FpjjgPjuVTl2kw+JODSFeXYXxff8x/qqOpSyIiogfUbObBITKV936KR7q6DG3cHDBzSIipyyEioibGgEMW50BCJrYcT4FEAiwZ1RX2cpmpSyIioibGgEMWRV2mwezvzwEAxvf1R1iA6322ICIiS8SAQxbl/Z3xSCuoujT1VmR7U5dDREQmwoBDFuPg5SxsPvbHpSkHebOeqJuIiIyIAYcsQmmFVn9palwfXpoiIrJ2DDhkEf55IBGp+aXwdbbDjCG8NEVEZO0YcMjsJWUX48v/XQMAzH2yAy9NERERAw6ZNyEE5v73PCq0Ogxo54HIjve+iSsREVkHBhwya/93Ph2/XcmG3EaKBU91hETCe00REREDDpmx4vJKLNxxEQDw9wFB8Hd3NHFFRETUXDDgkNlavu8K0tVl8HO1xysDg0xdDhERNSMMOGSWEjMLsfpQEgBg/pMdYWfL2zEQEdEfGHDILH3wfwmo1AlEhHpiUKiXqcshIqJmhgGHzE7ctRz8Ep8BmVSCWUNDTV0OERE1Qww4ZFaEEHj//y4BAKJ6+aGtZwsTV0RERM0RAw6ZlV3n0nEmJR8OchmmRgSbuhwiImqmGHDIbFRU6vDRz1WtNzH9A+HpZGfiioiIqLliwCGzsSnuBm7klMDDSYFJjwSauhwiImrGGHDILKjLNPhs3xUAwBsR7eCo4P2miIjo7hhwyCysOnAVeSUaBHk4YnTPVqYuh4iImjkGHGr2corKsfbwdQDAzCEhsJHx15aIiO6NnxTU7H39WxJKNVp0aeWMxztwUj8iIro/Bhxq1nKLK7Ah9joA4LXHgnm3cCIiqhMGHGrW1hxKQkmFFh19lRgU6mnqcoiIyEww4FCzVVCiwboj1wEArw1i6w0REdUdAw41W2sOJ6GovBIh3k54nDfUJCKiemDAoWZJXabBmsNJAKpab6RStt4QEVHdMeBQs7T+8HUUllUi2LMFhnT0NnU5RERkZhhwqNkpKq/Evw5Vtd68ytYbIiJqAAYcanY2xd1AQakGgR6OGN7Zx9TlEBGRGWLAoWalUqvDutuzFv+9fxBkbL0hIqIGYMChZmX3hXTcKiiDews5nurma+pyiIjITDHgULOy+nbfm7HhbWBnKzNxNUREZK4YcKjZOJmch1PJ+ZDLpHi+dxtTl0NERGasSQLOypUr4e/vDzs7O4SHh+Po0aP3XH/r1q0ICQmBnZ0dOnfujF27dhm8LoTA3Llz4ePjA3t7e0RERODKlSvGPARqAtWtN09184WHk8LE1RARkTkzesDZsmULpk2bhnnz5uHkyZPo2rUrIiMjkZmZWev6R44cwV//+ldMnDgRp06dwsiRIzFy5EicP39ev85HH32E5cuXY9WqVYiLi4OjoyMiIyNRVlZm7MMhI0nNL8Xu8+kAgL/1CzBxNUREZO4kQghhzDcIDw9Hr1698PnnnwMAdDod/Pz88Oqrr2LWrFk11h8zZgyKi4vx008/6Zf17t0b3bp1w6pVqyCEgK+vL6ZPn44333wTAFBQUAAvLy+sW7cOUVFR961JrVbD2dkZBQUFUCqVjXSk9CDe3xWPrw5eQ98gN2ya1NvU5RARUTNUn89vo7bgVFRU4MSJE4iIiPjjDaVSREREIDY2ttZtYmNjDdYHgMjISP36SUlJSE9PN1jH2dkZ4eHhd91neXk51Gq1wYOaj+LySnx7NBkAMPFhtt4QEdGDM2rAyc7OhlarhZeX4Y0Svby8kJ6eXus26enp91y/+mt99rl48WI4OzvrH35+fg06HjKOrcdTUFhWiQB3Rzza3tPU5RARkQWwilFUs2fPRkFBgf6RkpJi6pLoNp1OYN2R6wCACf38eVsGIiJqFEYNOO7u7pDJZMjIyDBYnpGRAW/v2m+g6O3tfc/1q7/WZ58KhQJKpdLgQc3D79dycD2nBE4KGzzzUCtTl0NERBbCqAFHLpejR48e2Ldvn36ZTqfDvn370KdPn1q36dOnj8H6ALB37179+gEBAfD29jZYR61WIy4u7q77pObr22NVrWlPdfOFo8LGxNUQEZGlMPonyrRp0zBu3Dj07NkTYWFhWLZsGYqLizFhwgQAQHR0NFq2bInFixcDAKZOnYoBAwbg448/xvDhw7F582YcP34cX331FQBAIpHg9ddfx7vvvovg4GAEBARgzpw58PX1xciRI419ONSI8oor8PPtoeFRvVqbuBoiIrIkRg84Y8aMQVZWFubOnYv09HR069YNu3fv1ncSTk5OhlT6R0NS3759sWnTJvzjH//A22+/jeDgYGzfvh2dOnXSrzNjxgwUFxcjJiYG+fn5ePjhh7F7927Y2dkZ+3CoEf1wKhUVWh06+irRuZWzqcshIiILYvR5cJojzoNjekIIRC47iMsZRVg0oiNe6ONv6pKIiKiZazbz4BDdzamUfFzOKIKdrRRPdWtp6nKIiMjCMOCQSWw5WtW5eFhnHzjb25q4GiIisjQMONTkisorsePsLQDsXExERMbBgENNbseZWyip0CLQwxG9/F1MXQ4REVkgBhxqcptvz30T1csPEglnLiYiosbHgENNKj5NjTMp+bCRSvA0Zy4mIiIjYcChJrX1+E0AwOMdvODeQmHiaoiIyFIx4FCT0eoEfrrduZitN0REZEwMONRkjiblIrOwHEo7G/Rv527qcoiIyIIx4FCTqR4aPqSTNxQ2MhNXQ0RElowBh5qERqvD/51LAwA81ZUzFxMRkXEx4FCTOJSYjbwSDdxbyNE70NXU5RARkYVjwKEmseN01eWp4Z19YCPjrx0RERkXP2nI6Mo0Wuy5mAEAeLKrr4mrISIia8CAQ0a3/1Imisor0VJlj4da89YMRERkfAw4ZHTVo6ee6OIDqZS3ZiAiIuNjwCGjKizTYF98JgBeniIioqbDgENG9Ut8BsordQj0cERHX6WpyyEiIivBgENGteNM1dw3T3bx5Z3DiYioyTDgkNEUlGhw8HIWAF6eIiKipsWAQ0Zz4HImKnUC7bxaoK1nC1OXQ0REVoQBh4zml9udiyNCvUxcCRERWRsGHDIKjVaHAwlVAWcQAw4RETUxBhwyimNJuSgsq4R7Czm6+alMXQ4REVkZBhwyir3xVbdmeLS9J2Sc3I+IiJoYAw41OiGEfnK/iA68PEVERE2PAYcaXWJmEZJzSyC3keKRYHdTl0NERFaIAYcaXfXlqX5BbnCQ25i4GiIiskYMONToqi9PcfQUERGZCgMONarsonKcTM4DAAwK9TRxNUREZK0YcKhR7b+UCSGATi2V8HG2N3U5RERkpRhwqFH9crv/zaAQXp4iIiLTYcChRlOm0eK3K9kAgMc5PJyIiEyIAYcaTey1HJRUaOGttENHX6WpyyEiIivGgEON5lf96ClPSCScvZiIiEzHqAEnNzcXY8eOhVKphEqlwsSJE1FUVHTP9V999VW0b98e9vb2aN26NV577TUUFBQYrCeRSGo8Nm/ebMxDoTo4lFh1eWpge46eIiIi0zLqLGxjx45FWloa9u7dC41GgwkTJiAmJgabNm2qdf1bt27h1q1bWLp0KTp06IAbN27g73//O27duoVt27YZrLt27VoMGTJE/1ylUhnzUOg+buWXIim7GFIJEB7oaupyiIjIyhkt4MTHx2P37t04duwYevbsCQBYsWIFhg0bhqVLl8LX17fGNp06dcJ//vMf/fOgoCC89957eP7551FZWQkbmz/KValU8Pb2Nlb5VE+Hb7fedGmlgtLO1sTVEBGRtTPaJarY2FioVCp9uAGAiIgISKVSxMXF1Xk/BQUFUCqVBuEGACZPngx3d3eEhYVhzZo1EELcdR/l5eVQq9UGD2pcR67mAAD6tXUzcSVERERGbMFJT0+Hp6dhXwwbGxu4uroiPT29TvvIzs7GokWLEBMTY7B84cKFeOyxx+Dg4IA9e/bglVdeQVFREV577bVa97N48WIsWLCgYQdC9yWE0Lfg9AvizTWJiMj06t2CM2vWrFo7+f75cenSpQcuTK1WY/jw4ejQoQPmz59v8NqcOXPQr18/dO/eHTNnzsSMGTOwZMmSu+5r9uzZKCgo0D9SUlIeuD76Q2JmETILy6GwkeKhNi6mLoeIiKj+LTjTp0/H+PHj77lOYGAgvL29kZmZabC8srISubm59+07U1hYiCFDhsDJyQk//PADbG3v3acjPDwcixYtQnl5ORQKRY3XFQpFrcupcVS33vT0d4GdrczE1RARETUg4Hh4eMDDw+O+6/Xp0wf5+fk4ceIEevToAQD49ddfodPpEB4eftft1Go1IiMjoVAo8OOPP8LOzu6+73X69Gm4uLgwxJjI4dv9b/ry8hQRETUTRuuDExoaiiFDhmDSpElYtWoVNBoNpkyZgqioKP0IqtTUVAwaNAgbNmxAWFgY1Go1Bg8ejJKSEvz73/826BDs4eEBmUyGHTt2ICMjA71794adnR327t2L999/H2+++aaxDoXuoVKrw+/XqjsYM+AQEVHzYNR5cDZu3IgpU6Zg0KBBkEqleOaZZ7B8+XL96xqNBgkJCSgpKQEAnDx5Uj/Cqm3btgb7SkpKgr+/P2xtbbFy5Uq88cYbEEKgbdu2+OSTTzBp0iRjHgrdxflbahSWVcLJzgadWzqbuhwiIiIAgETca3y1hVKr1XB2dtYPQaeGW7k/EUt+TsDgDl74Krrn/TcgIiJqoPp8fvNeVPRAjly9PTycl6eIiKgZYcChBivTaHHseh4ATvBHRETNCwMONdiJG3moqNTB00mBII8Wpi6HiIhIjwGHGkw/e3Fbd0gkEhNXQ0RE9AcGHGqwP+a/4eUpIiJqXhhwqEEKSjU4dzMfADsYExFR88OAQw1y8kYedAJo4+YAX5W9qcshIiIywIBDDXIyuWr0VA/eXJOIiJohBhxqkBM3GHCIiKj5YsCheqvU6nAmJR8A8FBrBhwiImp+GHCo3hIyClFcoUULhQ3aeTmZuhwiIqIaGHCo3k4m5wMAurdWQSbl/DdERNT8MOBQvZ283f+mOy9PERFRM8WAQ/XGDsZERNTcMeBQvWQVliM5twQA0M1PZdpiiIiI7oIBh+qlev6bdl4t4Gxva+JqiIiIaseAQ/VSHXA4PJyIiJozBhyql+oOxg+x/w0RETVjDDhUZxWVOpy9WQCALThERNS8MeBQnV1MU6O8UgeVgy0C3R1NXQ4REdFdMeBQnennv/FTQcoJ/oiIqBljwKE6O8E7iBMRkZlgwKE6O3WDI6iIiMg8MOBQnaQVlOJWQRmkEqArJ/gjIqJmjgGH6uTkjXwAQKiPEo4KG9MWQ0REdB8MOFQnJ3h5ioiIzAgDDtXJ6ZTqCf5Upi2EiIioDhhw6L60OoH4tEIAQOeWziauhoiI6P4YcOi+rucUo1SjhZ2tFAHuLUxdDhER0X0x4NB9XbilBgCEeCsh4wR/RERkBhhw6L4u3Kq6/1RHX6WJKyEiIqobBhy6r4u3W3A6+rL/DRERmQcGHLonIYQ+4HRgCw4REZkJBhy6pwx1OXKKKyCTShDi7WTqcoiIiOqEAYfu6WJaVf+bIA9H2NnKTFwNERFR3Rg14OTm5mLs2LFQKpVQqVSYOHEiioqK7rnNwIEDIZFIDB5///vfDdZJTk7G8OHD4eDgAE9PT7z11luorKw05qFYrQupty9P+fDyFBERmQ+j3lRo7NixSEtLw969e6HRaDBhwgTExMRg06ZN99xu0qRJWLhwof65g4OD/nutVovhw4fD29sbR44cQVpaGqKjo2Fra4v333/faMdirS6wgzEREZkhowWc+Ph47N69G8eOHUPPnj0BACtWrMCwYcOwdOlS+Pr63nVbBwcHeHt71/ranj17cPHiRfzyyy/w8vJCt27dsGjRIsycORPz58+HXC43yvFYq4tp1QGHLThERGQ+jHaJKjY2FiqVSh9uACAiIgJSqRRxcXH33Hbjxo1wd3dHp06dMHv2bJSUlBjst3PnzvDy8tIvi4yMhFqtxoULF2rdX3l5OdRqtcGD7k9dpkFybtW55wgqIiIyJ0ZrwUlPT4enp6fhm9nYwNXVFenp6Xfd7rnnnkObNm3g6+uLs2fPYubMmUhISMD333+v3++fww0A/fO77Xfx4sVYsGDBgxyOVaoeHt5SZQ+VA1vGiIjIfNQ74MyaNQsffvjhPdeJj49vcEExMTH67zt37gwfHx8MGjQIV69eRVBQUIP2OXv2bEybNk3/XK1Ww8/Pr8E1WgvOf0NEROaq3gFn+vTpGD9+/D3XCQwMhLe3NzIzMw2WV1ZWIjc39679a2oTHh4OAEhMTERQUBC8vb1x9OhRg3UyMjIA4K77VSgUUCgUdX5PqvJHB2MGHCIiMi/1DjgeHh7w8PC473p9+vRBfn4+Tpw4gR49egAAfv31V+h0On1oqYvTp08DAHx8fPT7fe+995CZmam/BLZ3714olUp06NChnkdD91J9DyoOESciInNjtE7GoaGhGDJkCCZNmoSjR4/i8OHDmDJlCqKiovQjqFJTUxESEqJvkbl69SoWLVqEEydO4Pr16/jxxx8RHR2N/v37o0uXLgCAwYMHo0OHDnjhhRdw5swZ/Pzzz/jHP/6ByZMns5WmEZVXapGYWTVnUceWHCJORETmxagT/W3cuBEhISEYNGgQhg0bhocffhhfffWV/nWNRoOEhAT9KCm5XI5ffvkFgwcPRkhICKZPn45nnnkGO3bs0G8jk8nw008/QSaToU+fPnj++ecRHR1tMG8OPbgrGUWo1AmoHGzh62xn6nKIiIjqRSKEEKYuoqmp1Wo4OzujoKAASiUvv9Rmy7FkzPzPOfQNcsOmSb1NXQ4REVG9Pr95Lyqq1UV2MCYiIjPGgEO14i0aiIjInDHgUA06nUA8b9FARERmjAGHariRW4LiCi0UNlIEuDuauhwiIqJ6Y8ChGqpbb0K8nWAj468IERGZH356UQ1Xb89/09bTycSVEBERNQwDDtWQmFUdcFqYuBIiIqKGYcChGqpnMA7yYP8bIiIyTww4ZECnE7iWVQyALThERGS+GHDIwK2CUpRqtLCVSdDa1cHU5RARETUIAw4ZuHq79cbfzZEjqIiIyGzxE4wMJGaygzEREZk/Bhwy8EcHYwYcIiIyXww4ZOAqh4gTEZEFYMAhA1fZgkNERBaAAYf08oorkFNcAQAI8uQcOEREZL4YcEiv+vJUS5U9HOQ2Jq6GiIio4RhwSK+6g3EgZzAmIiIzx4BDeuxgTEREloIBh/Q4RJyIiCwFAw7pXeU9qIiIyEIw4BAAoEyjRUpeCQAGHCIiMn8MOAQAuJZVDCEAZ3tbuDnKTV0OERHRA2HAIQCGHYwlEomJqyEiInowDDgE4M8djDlEnIiIzB8DDgHgEHEiIrIsDDgEgEPEiYjIsjDgELQ6gWvZHCJORESWgwGHkJpXiopKHeQ2UrRycTB1OURERA+MAYeQmFUIAAh0d4RMyhFURERk/hhwCFczqy5PBfHyFBERWQgGHGIHYyIisjgMOMQh4kREZHEYcAjXc6ouUQW6c5I/IiKyDAw4Vq64vBLZRRUAAD9XjqAiIiLLYNSAk5ubi7Fjx0KpVEKlUmHixIkoKiq66/rXr1+HRCKp9bF161b9erW9vnnzZmMeisW6mVcKAFDa2cDZ3tbE1RARETUOG2PufOzYsUhLS8PevXuh0WgwYcIExMTEYNOmTbWu7+fnh7S0NINlX331FZYsWYKhQ4caLF+7di2GDBmif65SqRq9fmuQklsCgK03RERkWYwWcOLj47F7924cO3YMPXv2BACsWLECw4YNw9KlS+Hr61tjG5lMBm9vb4NlP/zwA0aPHo0WLQw7wKpUqhrrUv2l5FUFnNYMOEREZEGMdokqNjYWKpVKH24AICIiAlKpFHFxcXXax4kTJ3D69GlMnDixxmuTJ0+Gu7s7wsLCsGbNGggh7rqf8vJyqNVqgwdVScmtukTFFhwiIrIkRmvBSU9Ph6enp+Gb2djA1dUV6enpddrH6tWrERoair59+xosX7hwIR577DE4ODhgz549eOWVV1BUVITXXnut1v0sXrwYCxYsaNiBWLjk6ktULvYmroSIiKjx1LsFZ9asWXftCFz9uHTp0gMXVlpaik2bNtXaejNnzhz069cP3bt3x8yZMzFjxgwsWbLkrvuaPXs2CgoK9I+UlJQHrs9S3Lx9iaoVW3CIiMiC1LsFZ/r06Rg/fvw91wkMDIS3tzcyMzMNlldWViI3N7dOfWe2bduGkpISREdH33fd8PBwLFq0COXl5VAoFDVeVygUtS63dkKIPzoZ8yabRERkQeodcDw8PODh4XHf9fr06YP8/HycOHECPXr0AAD8+uuv0Ol0CA8Pv+/2q1evxlNPPVWn9zp9+jRcXFwYYuopr0SD4gotAKAVL1EREZEFMVofnNDQUAwZMgSTJk3CqlWroNFoMGXKFERFRelHUKWmpmLQoEHYsGEDwsLC9NsmJibi4MGD2LVrV4397tixAxkZGejduzfs7Oywd+9evP/++3jzzTeNdSgWq7r1xkupgJ2tzMTVEBERNR6jzoOzceNGTJkyBYMGDYJUKsUzzzyD5cuX61/XaDRISEhASUmJwXZr1qxBq1atMHjw4Br7tLW1xcqVK/HGG29ACIG2bdvik08+waRJk4x5KBYpmZeniIjIQknEvcZXWyi1Wg1nZ2cUFBRAqVSauhyT+eeBRHy0OwF/6d4Sn47pZupyiIiI7qk+n9+8F5UV08+Bw/43RERkYRhwrBiHiBMRkaViwLFiHCJORESWigHHSml1Aqn5VZeoWrsx4BARkWVhwLFS6eoyaLQCtjIJvJV2pi6HiIioUTHgWKnqy1O+KnvIpBITV0NERNS4GHCsFPvfEBGRJWPAsVIpebeHiLtyiDgREVkeBhwrdfN2C04rtuAQEZEFYsCxUtW3aWjNOXCIiMgCMeBYqZTbk/z5MeAQEZEFYsCxQmUaLTLU5QB4mwYiIrJMDDhWqHqCPwe5DK6OchNXQ0RE1PgYcKzQn4eISyScA4eIiCwPA44V0gcc9r8hIiILxYBjhTgHDhERWToGHCvEWYyJiMjSMeBYIQ4RJyIiS8eAY4VScnmJioiILBsDjpUpKNWgoFQDgJeoiIjIcjHgWJnq/jdujnI4KmxMXA0REZFxMOBYmZu3+9+0Yv8bIiKyYAw4VubCLTUAINDd0cSVEBERGQ8DjpX57Uo2AKBPkJuJKyEiIjIeBhwrkl9SgbM38wEAjwS7m7YYIiIiI2LAsSJHruZAJ4BgzxbwceYQcSIislwMOFbk4OUsAMAjwR4mroSIiMi4GHCshBBC3//mkXa8PEVERJaNAcdKXMsuRmp+KeQyKcIDXE1dDhERkVEx4FiJ325fnurp7wIHOSf4IyIiy8aAYyX0l6fY/4aIiKwAA44VqKjUIfZaDgAODyciIuvAgGMFTibnoaRCCzdHOTr4KE1dDhERkdEx4FiB365U9b95ONgdUqnExNUQEREZHwOOFWD/GyIisjZGCzjvvfce+vbtCwcHB6hUqjptI4TA3Llz4ePjA3t7e0RERODKlSsG6+Tm5mLs2LFQKpVQqVSYOHEiioqKjHAEliG3uALnUgsAAP3Z/4aIiKyE0QJORUUFnn32Wbz88st13uajjz7C8uXLsWrVKsTFxcHR0RGRkZEoKyvTrzN27FhcuHABe/fuxU8//YSDBw8iJibGGIdgEQ4nZkMIIMTbCZ5KO1OXQ0RE1CSMNiHKggULAADr1q2r0/pCCCxbtgz/+Mc/MGLECADAhg0b4OXlhe3btyMqKgrx8fHYvXs3jh07hp49ewIAVqxYgWHDhmHp0qXw9fU1yrHUVVF5JfJLKkxaw532XswAwNFTRERkXZrNjG9JSUlIT09HRESEfpmzszPCw8MRGxuLqKgoxMbGQqVS6cMNAEREREAqlSIuLg5/+ctfat13eXk5ysvL9c/VarVRjuHH07fw9g/njLLvB8X+N0REZE2aTcBJT08HAHh5eRks9/Ly0r+Wnp4OT09Pg9dtbGzg6uqqX6c2ixcv1rcoGZNMCihsml+/7Y6+SoQH8vYMRERkPeoVcGbNmoUPP/zwnuvEx8cjJCTkgYpqbLNnz8a0adP0z9VqNfz8/Br9fcb0ao0xvVo3+n6JiIiofuoVcKZPn47x48ffc53AwMAGFeLt7Q0AyMjIgI+Pj355RkYGunXrpl8nMzPTYLvKykrk5ubqt6+NQqGAQqFoUF1ERERkfuoVcDw8PODhYZy+HAEBAfD29sa+ffv0gUatViMuLk4/EqtPnz7Iz8/HiRMn0KNHDwDAr7/+Cp1Oh/DwcKPURURERObHaB1GkpOTcfr0aSQnJ0Or1eL06dM4ffq0wZw1ISEh+OGHHwAAEokEr7/+Ot599138+OOPOHfuHKKjo+Hr64uRI0cCAEJDQzFkyBBMmjQJR48exeHDhzFlyhRERUWZfAQVERERNR9G62Q8d+5crF+/Xv+8e/fuAID9+/dj4MCBAICEhAQUFBTo15kxYwaKi4sRExOD/Px8PPzww9i9ezfs7P6Yv2Xjxo2YMmUKBg0aBKlUimeeeQbLly831mEQERGRGZIIIYSpi2hqarUazs7OKCgogFLJm08SERGZg/p8fje/Mc1ERERED4gBh4iIiCwOAw4RERFZHAYcIiIisjgMOERERGRxGHCIiIjI4jDgEBERkcVhwCEiIiKLw4BDREREFsdot2pozqonb1ar1SauhIiIiOqq+nO7LjdhsMqAU1hYCADw8/MzcSVERERUX4WFhXB2dr7nOlZ5LyqdTodbt27ByckJEomkUfetVqvh5+eHlJQU3ufKiHiemwbPc9PgeW4aPM9Nx1jnWgiBwsJC+Pr6Qiq9dy8bq2zBkUqlaNWqlVHfQ6lU8g+oCfA8Nw2e56bB89w0eJ6bjjHO9f1abqqxkzERERFZHAYcIiIisjgMOI1MoVBg3rx5UCgUpi7FovE8Nw2e56bB89w0eJ6bTnM411bZyZiIiIgsG1twiIiIyOIw4BAREZHFYcAhIiIii8OAQ0RERBaHAacBVq5cCX9/f9jZ2SE8PBxHjx695/pbt25FSEgI7Ozs0LlzZ+zatauJKjVv9TnPX3/9NR555BG4uLjAxcUFERER9/25UJX6/j5X27x5MyQSCUaOHGncAi1Efc9zfn4+Jk+eDB8fHygUCrRr147/dtRBfc/zsmXL0L59e9jb28PPzw9vvPEGysrKmqha83Tw4EE8+eST8PX1hUQiwfbt2++7zYEDB/DQQw9BoVCgbdu2WLdundHrhKB62bx5s5DL5WLNmjXiwoULYtKkSUKlUomMjIxa1z98+LCQyWTio48+EhcvXhT/+Mc/hK2trTh37lwTV25e6nuen3vuObFy5Upx6tQpER8fL8aPHy+cnZ3FzZs3m7hy81Lf81wtKSlJtGzZUjzyyCNixIgRTVOsGavveS4vLxc9e/YUw4YNE4cOHRJJSUniwIED4vTp001cuXmp73neuHGjUCgUYuPGjSIpKUn8/PPPwsfHR7zxxhtNXLl52bVrl3jnnXfE999/LwCIH3744Z7rX7t2TTg4OIhp06aJixcvihUrVgiZTCZ2795t1DoZcOopLCxMTJ48Wf9cq9UKX19fsXjx4lrXHz16tBg+fLjBsvDwcPHSSy8ZtU5zV9/zfKfKykrh5OQk1q9fb6wSLUJDznNlZaXo27ev+Ne//iXGjRvHgFMH9T3PX3zxhQgMDBQVFRVNVaJFqO95njx5snjssccMlk2bNk3069fPqHVakroEnBkzZoiOHTsaLBszZoyIjIw0YmVC8BJVPVRUVODEiROIiIjQL5NKpYiIiEBsbGyt28TGxhqsDwCRkZF3XZ8adp7vVFJSAo1GA1dXV2OVafYaep4XLlwIT09PTJw4sSnKNHsNOc8//vgj+vTpg8mTJ8PLywudOnXC+++/D61W21Rlm52GnOe+ffvixIkT+stY165dw65duzBs2LAmqdlamOpz0CpvttlQ2dnZ0Gq18PLyMlju5eWFS5cu1bpNenp6reunp6cbrU5z15DzfKeZM2fC19e3xh8V/aEh5/nQoUNYvXo1Tp8+3QQVWoaGnOdr167h119/xdixY7Fr1y4kJibilVdegUajwbx585qibLPTkPP83HPPITs7Gw8//DCEEKisrMTf//53vP32201RstW42+egWq1GaWkp7O3tjfK+bMEhi/PBBx9g8+bN+OGHH2BnZ2fqcixGYWEhXnjhBXz99ddwd3c3dTkWTafTwdPTE1999RV69OiBMWPG4J133sGqVatMXZpFOXDgAN5//33885//xMmTJ/H9999j586dWLRokalLo0bAFpx6cHd3h0wmQ0ZGhsHyjIwMeHt717qNt7d3vdanhp3nakuXLsUHH3yAX375BV26dDFmmWavvuf56tWruH79Op588kn9Mp1OBwCwsbFBQkICgoKCjFu0GWrI77OPjw9sbW0hk8n0y0JDQ5Geno6KigrI5XKj1myOGnKe58yZgxdeeAEvvvgiAKBz584oLi5GTEwM3nnnHUilbANoDHf7HFQqlUZrvQHYglMvcrkcPXr0wL59+/TLdDod9u3bhz59+tS6TZ8+fQzWB4C9e/fedX1q2HkGgI8++giLFi3C7t270bNnz6Yo1azV9zyHhITg3LlzOH36tP7x1FNP4dFHH8Xp06fh5+fXlOWbjYb8Pvfr1w+JiYn6AAkAly9fho+PD8PNXTTkPJeUlNQIMdWhUvA2jY3GZJ+DRu3CbIE2b94sFAqFWLdunbh48aKIiYkRKpVKpKenCyGEeOGFF8SsWbP06x8+fFjY2NiIpUuXivj4eDFv3jwOE6+D+p7nDz74QMjlcrFt2zaRlpamfxQWFprqEMxCfc/znTiKqm7qe56Tk5OFk5OTmDJlikhISBA//fST8PT0FO+++66pDsEs1Pc8z5s3Tzg5OYlvv/1WXLt2TezZs0cEBQWJ0aNHm+oQzEJhYaE4deqUOHXqlAAgPvnkE3Hq1Clx48YNIYQQs2bNEi+88IJ+/eph4m+99ZaIj48XK1eu5DDx5mrFihWidevWQi6Xi7CwMPH777/rXxswYIAYN26cwfrfffedaNeunZDL5aJjx45i586dTVyxearPeW7Tpo0AUOMxb968pi/czNT39/nPGHDqrr7n+ciRIyI8PFwoFAoRGBgo3nvvPVFZWdnEVZuf+pxnjUYj5s+fL4KCgoSdnZ3w8/MTr7zyisjLy2v6ws3I/v37a/33tvrcjhs3TgwYMKDGNt26dRNyuVwEBgaKtWvXGr1OiRBshyMiIiLLwj44REREZHEYcIiIiMjiMOAQERGRxWHAISIiIovDgENEREQWhwGHiIiILA4DDhEREVkcBhwiIiKyOAw4REREZHEYcIiIiMjiMOAQUbM3cOBATJkyBVOmTIGzszPc3d0xZ84c/R2f8/LyEB0dDRcXFzg4OGDo0KG4cuWKfvt169ZBpVJh+/btCA4Ohp2dHSIjI5GSkmKqQyIiI2PAISKzsH79etjY2ODo0aP47LPP8Mknn+Bf//oXAGD8+PE4fvw4fvzxR8TGxkIIgWHDhkGj0ei3LykpwXvvvYcNGzbg8OHDyM/PR1RUlKkOh4iMjDfbJKJmb+DAgcjMzMSFCxcgkUgAALNmzcKPP/6I//73v2jXrh0OHz6Mvn37AgBycnLg5+eH9evX49lnn8W6deswYcIE/P777wgPDwcAXLp0CaGhoYiLi0NYWJjJjo2IjIMtOERkFnr37q0PNwDQp08fXLlyBRcvXoSNjY0+uACAm5sb2rdvj/j4eP0yGxsb9OrVS/88JCQEKpXKYB0ishwMOERERGRxGHCIyCzExcUZPP/9998RHByMDh06oLKy0uD1nJwcJCQkoEOHDvpllZWVOH78uP55QkIC8vPzERoaavziiajJMeAQkVlITk7GtGnTkJCQgG+//RYrVqzA1KlTERwcjBEjRmDSpEk4dOgQzpw5g+effx4tW7bEiBEj9Nvb2tri1VdfRVxcHE6cOIHx48ejd+/e7H9DZKFsTF0AEVFdREdHo7S0FGFhYZDJZJg6dSpiYmIAAGvXrsXUqVPxxBNPoKKiAv3798euXbtga2ur397BwQEzZ87Ec889h9TUVDzyyCNYvXq1qQ6HiIyMo6iIqNkbOHAgunXrhmXLljVo+3Xr1uH1119Hfn5+o9ZFRM0XL1ERERGRxWHAISIiIovDS1RERERkcdiCQ0RERBaHAYeIiIgsDgMOERERWRwGHCIiIrI4DDhERERkcRhwiIiIyOIw4BAREZHFYcAhIiIii8OAQ0RERBbn/wHzwmd9Gd7mVwAAAABJRU5ErkJggg==", + "image/png": 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", "text/plain": [ "
" ] @@ -3167,6 +2968,8 @@ "(\n", " cr_gp_df.plot(x='pop', y='pol', title='Cautionary Rule GP policy'),\n", " esc_gp_df.plot(x='pop', y='pol', title='Const. Escapement GP policy'),\n", + " cr_gbrt_df.plot(x='pop', y='pol', title='Cautionary Rule GBRT policy'),\n", + " esc_gbrt_df.plot(x='pop', y='pol', title='Const. Escapement GBRT policy'),\n", " # msy_gbrt_df.plot(x='pop', y='pol', title='MSY GP policy'),\n", ") " ] diff --git a/notebooks/popdyn_tests.ipynb b/notebooks/popdyn_tests.ipynb index 2d68ca7..d137250 100644 --- a/notebooks/popdyn_tests.ipynb +++ b/notebooks/popdyn_tests.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 1, "id": "3638cfd4-177b-4b24-b6a4-8d61d74faf80", "metadata": {}, "outputs": [], @@ -25,19 +25,19 @@ }, { "cell_type": "code", - "execution_count": 135, - "id": "1f80110e-9da0-4625-9e48-b6503e56adc4", + "execution_count": 15, + "id": "c1131bf0-840c-4a40-b111-f3d74351795a", "metadata": {}, "outputs": [], "source": [ - "r_devs = get_r_devs(n_year=1000)\n", - "config = {\"s\": 0.90, \"r_devs\": r_devs}\n", - "env = AsmEnv(config = config)" + "config = {'s':0.86, 'noiseless': False, 'flat_harv_vul': False}\n", + "env = AsmEnv(config=config)\n", + "_ = env.reset()" ] }, { "cell_type": "code", - "execution_count": 136, + "execution_count": 16, "id": "eb58ebf3-882d-4944-9e19-2332f3133a18", "metadata": {}, "outputs": [], @@ -46,7 +46,7 @@ " simulation = {\n", " 't': [],\n", " 'surv_b_obs': [],\n", - " 'bare_surv_b_obs': [],\n", + " 'bare_surv_b_obs': [], \n", " 'mean_wt_obs': [],\n", " 'act': [],\n", " 'rew': [],\n", @@ -91,58 +91,218 @@ }, { "cell_type": "code", - "execution_count": 137, + "execution_count": 17, + "id": "9ab73841-a5f3-4704-ab7c-0a71ca683a90", + "metadata": {}, + "outputs": [], + "source": [ + "def expand_state(age_cls):\n", + " def wrapped(row):\n", + " return row.state[age_cls]\n", + " return wrapped\n", + "\n", + "def add_state_columns(df, env):\n", + " df_inner = df.copy()\n", + " for age_cls in range(len(env.state)):\n", + " df_inner[f'age_{age_cls:02d}_b'] = df_inner.apply(expand_state(age_cls), axis=1)\n", + " return df_inner\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "704d10a7-f568-4033-a1e1-8ae08c6d7b71", + "metadata": {}, + "source": [ + "## No Harvest" + ] + }, + { + "cell_type": "code", + "execution_count": 18, "id": "a634dbf5-00af-44d8-b2d9-5ede8969e3e7", "metadata": {}, "outputs": [], "source": [ "trivp = Msy(env = env, mortality=0)\n", - "trivial_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), trivp, other_vars=['ssb']))" + "trivial_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), trivp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "6f4dc7c8-47d3-414f-bc97-d6c2290d455c", + "metadata": {}, + "outputs": [], + "source": [ + "# trivial_ep.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "d4286e3d-ab4c-4244-8008-9e836c202e9c", + "metadata": {}, + "outputs": [], + "source": [ + "trivial_ep = add_state_columns(trivial_ep, env)\n", + "melted_triv_ep = trivial_ep[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')" ] }, { "cell_type": "code", - "execution_count": 138, + "execution_count": 21, + "id": "b5a371a2-d2d4-4a9a-87c7-30121b7d07df", + "metadata": {}, + "outputs": [], + "source": [ + "def prepare_for_altair(df):\n", + " df = add_state_columns(df, env)\n", + " melted_df = df[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')\n", + " melted_df['population'] = melted_df['variable']\n", + " melted_df['biomass'] = melted_df['value']\n", + " return melted_df[['t', 'population', 'biomass']]" + ] + }, + { + "cell_type": "code", + "execution_count": 22, "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 138, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "trivial_ep.plot(x='t', y = ['total_pop', 'surv_vul_b', 'harv_vul_b'], title='populations')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "7dc378fd-0a34-4279-8b7f-ae62b6f171f5", + "metadata": {}, + "outputs": [], + "source": [ + "# %pip install altair\n", + "# %pip install vega_datasets" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "168e0fae-6b11-4fcc-9f64-c34c4ea5c3c2", + "metadata": {}, + "outputs": [ { "data": { - "image/png": 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", + "text/html": [ + "\n", + "\n", + "
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" + "alt.Chart(...)" ] }, + "execution_count": 14, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "trivial_ep.plot(x='t', y = ['total_pop'], title='total population')\n", - "# trivial_ep.plot(x='t', y = ['non_random_newb'], title='Unfished non-random newborns')\n", - "trivial_ep[trivial_ep.t < 50].plot(x='t', y = ['ssb'], title='Unfished ssb')\n", - "# trivial_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)\n", - "# trivial_ep.plot(x='t', y = ['bare_surv_b_obs'], title='surv_b_obs')" + "import altair as alt\n", + "\n", + "triv_population = prepare_for_altair(trivial_ep)\n", + "\n", + "triv_population_short = triv_population[triv_population.t < 100]\n", + "\n", + "alt.Chart(triv_population_short).mark_area().encode(\n", + " x=\"t:T\",\n", + " y=\"biomass:Q\",\n", + " color=\"population:N\"\n", + ")" ] }, { @@ -155,44 +315,34 @@ }, { "cell_type": "code", - "execution_count": 118, + "execution_count": 74, "id": "3e9aba5e-466a-4feb-8bc5-8bf34da520a3", "metadata": {}, "outputs": [], "source": [ - "escp = ConstEsc(env, escapement = 0.05)\n", - "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), escp, other_vars=['ssb']))" + "escp = ConstEsc(env, escapement = 0.008)\n", + "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), escp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" ] }, { "cell_type": "code", - "execution_count": 119, + "execution_count": 75, "id": "ff08dfd1-c97c-407a-aec7-968d36ca6beb", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 119, + "execution_count": 75, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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", 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" ] @@ -204,206 +354,276 @@ "source": [ "# esc_ep.plot(x='t', y = ['total_pop'], title='total population')\n", "# esc_ep.plot(x='t', y = ['non_random_newb'], title='non-random newborns')\n", - "esc_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", + "# esc_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", "# esc_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)\n", "# esc_ep.plot(x='t', y = ['act'], title='actions')\n", - "esc_ep.plot(x='t', y = ['surv_b_obs'], title='surv_b_obs')" + "# esc_ep.plot(x='t', y = ['surv_b_obs'], title='surv_b_obs')\n", + "esc_ep.plot(x='t', y = ['total_pop', 'surv_vul_b', 'harv_vul_b'], title='populations')" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 76, "id": "c5c5a541-abb1-44f2-b53a-01ae726f9cbd", "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
\n", - "\n", + "
\n", + "" ], "text/plain": [ - " t surv_b_obs mean_wt_obs act rew total_pop newborns \\\n", - "0 0 1.225387 0.622407 -0.060890 0.926308 3.692093 0.000000 \n", - "1 1 0.588220 0.556437 -1.000000 0.000000 4.095136 0.919936 \n", - "2 2 0.609490 0.556648 -1.000000 0.000000 3.521817 0.000000 \n", - "3 3 0.633958 0.565610 -1.000000 0.000000 3.028762 0.000000 \n", - "4 4 0.657231 0.580948 -0.977997 0.014585 3.350002 0.765073 \n", - "\n", - " non_random_newb ssb \n", - "0 0.783215 0.834071 \n", - "1 0.791500 0.859990 \n", - "2 0.801552 0.892880 \n", - "3 0.812020 0.928948 \n", - "4 0.818408 0.951927 " + "alt.Chart(...)" ] }, - "execution_count": 28, + "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "esc_ep.head()" + "esc_population = prepare_for_altair(esc_ep)\n", + "\n", + "esc_population_short = esc_population[triv_population.t < 100]\n", + "\n", + "alt.Chart(esc_population_short).mark_area().encode(\n", + " x=\"t:T\",\n", + " y=\"biomass:Q\",\n", + " color=\"population:N\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e314658b-54a6-4e57-9bb2-9aa51f0720c9", + "metadata": {}, + "source": [ + "## MSY" ] }, { "cell_type": "code", - "execution_count": 91, - "id": "26c2cf63-f70a-41aa-8ef1-e3f5b69fe5b2", + "execution_count": 77, + "id": "ade66528-f9fb-46b3-8d3e-9c0374c60e15", "metadata": {}, "outputs": [], "source": [ - "mid = Msy(env = env, mortality=0.05)\n", - "mid_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), mid, other_vars=['ssb']))" + "msyp = Msy(env = env, mortality=0.057)\n", + "msy_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), msyp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" ] }, { "cell_type": "code", - "execution_count": 92, - "id": "62d7175e-1b05-4353-bd63-21971fb71d6a", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, + "execution_count": 78, + "id": "17930d75-ae56-4746-b3fc-3e24d4a894dc", + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 92, + "execution_count": 78, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "msy_ep.plot(x='t', y = ['total_pop', 'surv_vul_b', 'harv_vul_b'], title='populations')" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "0f761edf-3096-4364-b675-b5f9547af94d", + "metadata": {}, + "outputs": [ { "data": { - "image/png": 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", + "text/html": [ + "\n", + "\n", + "
\n", + "" + ], "text/plain": [ - "
" + "alt.Chart(...)" ] }, + "execution_count": 79, "metadata": {}, - "output_type": "display_data" - }, + "output_type": "execute_result" + } + ], + "source": [ + "msy_population = prepare_for_altair(msy_ep)\n", + "\n", + "msy_population_short = msy_population[msy_population.t < 100]\n", + "\n", + "alt.Chart(msy_population_short).mark_area().encode(\n", + " x=\"t:T\",\n", + " y=\"biomass:Q\",\n", + " color=\"population:N\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "dbca68f2-67fb-4b04-a339-fe2c965066b9", + "metadata": {}, + "outputs": [ { "data": { - "image/png": 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", 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" + "" ] }, + "execution_count": 40, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -413,16 +633,17 @@ } ], "source": [ - "mid_ep.plot(x='t', y = ['total_pop'], title='total population')\n", - "mid_ep.plot(x='t', y = ['non_random_newb'], title='Fished non-random newborns')\n", - "mid_ep.plot(x='t', y = ['ssb'], title='Fished ssb')\n", - "mid_ep.plot(x='t', y = ['newborns'], title='newborns', logy=True)" + "df = pd.DataFrame({\n", + " 'age': list(range(20)),\n", + " 'harvest_vul': env.parameters['harvest_vul']\n", + "})\n", + "df.plot(x='age')" ] }, { "cell_type": "code", "execution_count": null, - "id": "cdc4b65b-8235-4008-accd-e31594e6e640", + "id": "dddb417b-c0d6-47cc-b798-e79774b32b99", "metadata": {}, "outputs": [], "source": [] diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index bbc611c..ffc99df 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -70,6 +70,8 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): sdr=self.parameters["sdr"], rho=self.parameters["rho"], ) + self.noiseless = config.get('noiseless', False) + self.flat_harv_vul = config.get('flat_harv_vul', False) default_init = self.initialize_population() self.init_state = config.get("init_state", equib_init) @@ -124,11 +126,15 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): def reset(self, *, seed=None, options=None): self.timestep = 0 self.state = self.initialize_population() + if self.flat_harv_vul: + self.parameters["harvest_vul"] = np.ones(shape=len(self.parameters["ages"])) self.state = self.init_state * np.array( np.random.uniform(0.1, 1), dtype=np.float32 ) - if self.reproducibilty_mode: - self.r_devs = self.fixed_r_devs + if self.noiseless: + self.r_devs = np.ones(shape = self.n_year) + elif self.reproducibility_mode: + self.r_devs = self.fixed_r_devs else: self.r_devs = get_r_devs( n_year=self.n_year, diff --git a/src/rl4fisheries/envs/asm_fns.py b/src/rl4fisheries/envs/asm_fns.py index 4edfc93..fabeb5d 100644 --- a/src/rl4fisheries/envs/asm_fns.py +++ b/src/rl4fisheries/envs/asm_fns.py @@ -32,7 +32,7 @@ def asm_pop_growth(env): new_state[0] = ( env.parameters["bha"] * env.ssb / (1 + env.parameters["bhb"] * env.ssb) - * (env.ssb if env.ssb < 1 else 1) # let's suppress spawners if ssb is smaller than 1 + # * (env.ssb**1.2 if env.ssb < 1 else 1) # let's suppress spawners if ssb is smaller than 1 * env.r_devs[env.timestep] ) # @@ -66,9 +66,11 @@ def harvest(env, mortality): env.wbar = 0 # # - yieldf = mortality[0] * env.harv_vul_b # fishery yield + # true_mortality = np.clip(mortality[0] * (1 + 0.05 * np.random.normal()), 0, 1) + true_mortality = mortality[0] + yieldf = true_mortality * env.harv_vul_b # fishery yield reward = yieldf ** p["upow"] # this is utility - new_state = p["s"] * env.state * (1 - p["harvest_vul"] * mortality) # remove fish + new_state = p["s"] * env.state * (1 - p["harvest_vul"] * true_mortality) # remove fish return new_state, reward def get_r_devs(n_year, p_big=0.05, sdr=0.3, rho=0): @@ -91,11 +93,11 @@ def get_r_devs(n_year, p_big=0.05, sdr=0.3, rho=0): n_rand = np.random.normal(0, 1, n_year) r_big = np.random.uniform(10, 30, n_year) - # r_low = (1 - p_big * r_big) / (1 - p_big) # small rec event - r_low = [ - np.random.choice([1,0], p = [0.6, 0.4]) - for _ in range(n_year) - ] + r_low = (1 - p_big * r_big) / (1 - p_big) # small rec event + # r_low = [ + # np.random.choice([1,0], p = [0.6, 0.4]) + # for _ in range(n_year) + # ] r_low = np.clip(r_low, 0, None) dev_last = 0 for t in range(0, n_year, 1): From 8103a8a7abc9e9649eb23f47186cb56660370cee Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 11 Apr 2024 00:13:16 +0000 Subject: [PATCH 16/64] initialize_population a bit leaner --- src/rl4fisheries/envs/asm_env.py | 54 +++++++++++++++++++++----------- 1 file changed, 36 insertions(+), 18 deletions(-) diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index ffc99df..41db2c6 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -81,7 +81,7 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): self.Tmax = self.n_year self.threshold = config.get("threshold", np.float32(1e-4)) self.timestep = 0 - self.bound = 50 # a rescaling parameter + self.bound = config.get("bound", 50) # a rescaling parameter self.r_devs = config.get("r_devs", np.array([])) # @@ -221,35 +221,53 @@ def initialize_population(self): ninit = np.float32([0] * p["n_age"]) # initial numbers survey_vul = ninit.copy() # survey vulnerability harvest_vul = ninit.copy() # harvest vulnerability - wt = ninit.copy() # weight - mat = ninit.copy() # maturity - Lo = ninit.copy() # survivorship unfished - Lf = ninit.copy() # survivorship fished + # wt = ninit.copy() # weight + # mat = ninit.copy() # maturity + # Lo = ninit.copy() # survivorship unfished + # Lf = ninit.copy() # survivorship fished mwt = ninit.copy() # mature weight # leading array calculations to get vul-at-age, wt-at-age, etc. - for a in range(0, p["n_age"], 1): - survey_vul[a] = (p["linf"] / p["lbar"]) * (1 - np.exp(-p["vbk"] * p["ages"][a])) ** (p["survey_phi"]) - # 1 / (1 + np.exp(-p["asl"] * (p["ages"][a] - p["ahv"]))) # <- this harvest_vul was previously - harvest_vul[a] = 1 / (1 + np.exp(-(p["ages"][a] - p["ahv"]) / p["asl"])) - wt[a] = pow( - (1 - np.exp(-p["vbk"] * p["ages"][a])), 3 - ) # 3 --> isometric growth - mat[a] = 1 / (1 + np.exp(-p["asl"] * (p["ages"][a] - p["ahm"]))) - if a == 0: - Lo[a] = 1 + survey_vul = [ + (p["linf"] / p["lbar"]) + * (1 - np.exp(-p["vbk"] * p["ages"][a])) ** (p["survey_phi"]) + for a in range(p["n_age"]) + ] + harvest_vul = [ + 1 / (1 + np.exp(-(p["ages"][a] - p["ahv"]) / p["asl"])) + for a in range(p["n_age"]) + ] + # + wt = [ + (1 - np.exp(-p["vbk"] * p["ages"][a])) ** 3 + for a in range(p["n_age"]) + ] + mat = [ + 1 / (1 + np.exp(-p["asl"] * (p["ages"][a] - p["ahm"]))) + for a in range(p["n_age"]) + ] + mwt = mat * np.array(wt) + # + Lo = [ + p["s"] ** a + if a<(p["n_age"]-1) + else (p["s"] ** a) / (1 - p["s"]) + for a in range(p["n_age"]) + ] + Lf = [] + for a in range(p["n_age"]) + if a==0: Lf[a] = 1 - elif a > 0 and a < (p["n_age"] - 1): - Lo[a] = Lo[a - 1] * p["s"] + elif 0 Date: Wed, 24 Apr 2024 01:01:06 +0000 Subject: [PATCH 17/64] added custom harv vul, observe_total, updated notebooks with more comparisons --- hyperpars/ppo-asm.yml | 12 +- hyperpars/tqc-asm.yml | 6 +- notebooks/SystemDynamics.ipynb | 536 +- notebooks/optimal-fixed-policy.ipynb | 11093 +++++++++++++++++++++---- src/rl4fisheries/envs/asm_env.py | 53 +- src/rl4fisheries/envs/asm_fns.py | 45 + 6 files changed, 9945 insertions(+), 1800 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 89bf92f..bc0f381 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,14 +1,20 @@ # algo algo: "PPO" -total_timesteps: 1000000 +total_timesteps: 15000000 algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' use_sde: True + # batch_size: 128 + gamma: 0.995 + gae_lambda: 0.999 # env env_id: "AsmEnv" -config: {'s': 0.94, 'p_big':0.05} +config: + observation_fn_id: 'observe_2o' + n_observs: 2 + use_custom_vul: True n_envs: 12 # io @@ -16,5 +22,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2obs" +id: "2o_flat_harv-long" additional_imports: [] \ No newline at end of file diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index ff85617..449bdc9 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -10,7 +10,9 @@ algo_config: # env env_id: "AsmEnv" -config: {'s': 0.94, 'p_big':0.05} +config: + observation_fn_id: 'observe_2o' + n_observs: 2 n_envs: 12 # io @@ -18,5 +20,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2obs" +id: "2o" additional_imports: [] diff --git a/notebooks/SystemDynamics.ipynb b/notebooks/SystemDynamics.ipynb index 11afca8..28922a0 100644 --- a/notebooks/SystemDynamics.ipynb +++ b/notebooks/SystemDynamics.ipynb @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 1, "id": "15ea0eae-88c4-4306-803d-76f0a7b0bba6", "metadata": {}, "outputs": [], @@ -60,7 +60,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 2, "id": "5ad23ce3-a12c-4a26-b050-bd96d8682c7b", "metadata": {}, "outputs": [], @@ -140,7 +140,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 3, "id": "f3cda8d8-c3cb-4e13-9553-205b9f2a4647", "metadata": {}, "outputs": [], @@ -237,7 +237,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 4, "id": "30d5bb5d-e335-463e-bcec-816e5aee53b8", "metadata": {}, "outputs": [], @@ -263,7 +263,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 5, "id": "d7a3b7ea-6f14-469b-bd7e-218b423ccd3e", "metadata": {}, "outputs": [], @@ -277,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 6, "id": "8601427e-9303-4915-be4a-b242a69460eb", "metadata": {}, "outputs": [ @@ -287,13 +287,13 @@ "" ] }, - "execution_count": 21, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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z506NGzdOv/nNb/TMM89IkrKyslRaWqolS5aoSZMm2rx5s2JiYiRJU6ZM0ebNm/X++++rRYsW2rFjh44ePVqj/qgqggUAICDcbrciIyMVHR2txMRESdJ9990nj8ejP//5z3I4HOrcubP27t2re+65R/fff/8p95Gk8PBwPfjgg/71tm3bavny5XrjjTdqHCw8Ho+efPJJORwOderUSRs3btSTTz55ymCxaNEibdy4UXl5efJ4PJKkV155RV27dtXq1at14YUXSjoeQF588UXFxsYqNTVVV1xxhXJzc/Xee+8pLCxMnTp10qOPPqqPP/7YHyx+OJ8kJSVF//u//6uxY8f6g0V+fr5uuOEGpaWlSZLOP/98f/v8/Hz17NlT6enp/v3rGsECAEJQVKNwbX5oYEDOWxtbtmxR7969K91PoU+fPjp06JC+/PJLJScnn3bfp59+Wi+++KLy8/N19OhRlZaW6oILLqhxLRdffHGlOnr37q0nnnhCFRUVJ92VcsuWLfJ4PP5QIUmpqamKi4vTli1b/MEiJSVFsbGx/jYtW7ZUeHi4wsLCKm07cWttSfrwww+VnZ2trVu3yuv1qry8XMeOHdORI0cUHR2t8ePH67bbbtMHH3ygjIwM3XDDDerevbsk6bbbbtMNN9ygdevWacCAARo6dKguueSSGvdJVTDHAgBCkMPhUHRkRL0vgbpJ15w5c3T33Xdr9OjR+uCDD7Rhwwb98pe/VGlpaUDqOZ1GjRpVWnc4HKfc5vP5JEm7du3SNddco+7du+sf//iH1q5dq6efflqS/O/tf/7nf7Rz507dfPPN2rhxo9LT0zVjxgxJ0qBBg7R7927deeed2rt3r/r376+77767Tt8jwQIAEDCRkZGqqKjwr3fp0kXLly+vNEnyk08+UWxsrFq3bn3KfU60ueSSSzRu3Dj17NlT7du31xdffFGr2lauXFlpfcWKFerQocMpn6HRpUsX7dmzR3v27PFv27x5swoLC5WamlrjGtauXSufz6cnnnhCF198sTp27Ki9e/ee1M7j8Wjs2LF66623dNddd+mFF17wvxYfH6+RI0fq1Vdf1VNPPaXnn3++xvVUBcECABAwKSkpWrlypXbt2qVvvvlG48aN0549e3THHXdo69atmjdvnn7/+99r0qRJ/ssF/72Pz+dThw4dtGbNGi1YsEDbtm3TlClTtHr16lrVlp+fr0mTJik3N1evvfaaZsyYoQkTJpyybUZGhtLS0pSZmal169Zp1apVGjFihPr16+ef31AT7du3V1lZmWbMmKGdO3fq//7v//SXv/ylUpuJEydqwYIFysvL07p16/Txxx+rS5cukqT7779f8+bN044dO/T555/r3Xff9b9WVwgWAICAufvuuxUeHq7U1FTFx8errKxM7733nlatWqUePXpo7NixGj16tH73u9+ddp/8/Hz96le/0vXXX6+bbrpJvXr10rfffqtx48bVqrYRI0bo6NGjuuiii5SVlaUJEyac9oZYDodD8+bNU9OmTdW3b19lZGTo/PPP1+uvv16rGnr06KFp06bp0UcfVbdu3TRr1ixlZ2dXalNRUaGsrCx16dJFV111lTp27Oif2BkZGanJkyere/fu6tu3r8LDwzVnzpxa1XQ2DlOdLx1b4PV65Xa7VVRUJJfLVZ+nBoCQdOzYMeXl5alt27Zq3LhxoMtBEDvT31JVP78ZsQAAANYQLAAADUp+fr5iYmJOu+Tn5we6xKBWq/tYTJ06VZMnT9aECRN4whsAICi0atVKGzZsOOPrqLkaB4vVq1frueee89+EAwCAYBAREaH27dsHuoyQVaNLIYcOHVJmZqZeeOEFNW3a1HZNAAAgSNUoWGRlZWnw4MHKyMg4a9uSkhJ5vd5KCwAACE3VvhQyZ84crVu3rso3HsnOzq70YBgAABC6qjVisWfPHk2YMEGzZs2q8nelJ0+erKKiIv/yw9udAgCA0FKtEYu1a9eqoKBAP/rRj/zbKioqtGTJEv35z39WSUnJSfdQdzqdcjqddqoFAADntGqNWPTv318bN27Uhg0b/Et6eroyMzO1YcOGUz6YBQCAYJGSklKnt0944IEHavUo92BQrRGL2NhYdevWrdK2Jk2aqHnz5idtBwAADQ933gQAhITS0tJAlwBZCBaLFy/mrpsAgBr5+9//rrS0NEVFRal58+bKyMjQ4cOHdfnll2vixImV2g4dOlSjRo3yr6ekpOjhhx/WiBEj5HK5NGbMGF1yySW65557Ku339ddfq1GjRlqyZEmVaiouLtbw4cPVpEkTnXfeeXr66aer/H7y8/M1ZMgQxcTEyOVyadiwYTpw4MBJ7Z577jl5PB5FR0dr2LBhKioq8r+2ePFiXXTRRWrSpIni4uLUp08f7d69u8o1BBojFgAQioyRSg/X/1KNB2bv27dPw4cP1y233KItW7Zo8eLFuv7661Wdh27/8Y9/VI8ePbR+/XpNmTJFmZmZmjNnTqVjvP7662rVqpUuu+yyKh3z8ccf9x/z3nvv1YQJE7Rw4cKz7ufz+TRkyBAdPHhQOTk5WrhwoXbu3KmbbrqpUrsdO3bojTfe0DvvvKP58+dr/fr1/ke8l5eXa+jQoerXr58+++wzLV++XGPGjJHD4ahynwRarZ4VAgA4R5Udkf4QgGde/HavFNmkSk337dun8vJyXX/99WrTpo0kKS0trVqn+8lPfqK77rrLvz5s2DBNnDhRS5cu9QeJ2bNna/jw4VX+cO7Tp4/uvfdeSVLHjh31ySef6Mknn9SVV155xv0WLVqkjRs3Ki8vTx6PR5L0yiuvqGvXrlq9erUuvPBCSccfTf7KK6/ovPPOkyTNmDFDgwcP1hNPPKHIyEgVFRXpmmuuUbt27SRJXbp0qUaPBB4jFgCAgOjRo4f69++vtLQ03XjjjXrhhRf03XffVesY6enpldbj4+M1YMAAzZo1S5KUl5en5cuXKzMzs8rH7N2790nrW7ZsOet+W7Zskcfj8YcKSUpNTVVcXFyl/ZOTk/2h4sTxfT6fcnNz1axZM40aNUoDBw7Utddeq+nTp2vfvn1Vrv1cwIgFAISiRtHHRw8Ccd4qCg8P18KFC7Vs2TJ98MEHmjFjhu677z6tXLlSYWFhJ10SKSsrO+kYTZqcPDqSmZmp8ePHa8aMGZo9e7bS0tKqPRISSDNnztT48eM1f/58vf766/rd736nhQsX6uKLLw50aVXCiAUAhCKH4/glifpeqjkXwOFwqE+fPnrwwQe1fv16RUZGau7cuYqPj6/0/9QrKiq0adOmKh1zyJAhOnbsmObPn6/Zs2dXa7RCklasWHHSelUuR3Tp0kV79uypdIfpzZs3q7CwUKmpqf5t+fn52rv3P6FvxYoVCgsLU6dOnfzbevbsqcmTJ2vZsmXq1q2bZs+eXa33EEiMWAAAAmLlypVatGiRBgwYoISEBK1cuVJff/21unTpoiZNmmjSpEn617/+pXbt2mnatGkqLCys0nGbNGmioUOHasqUKdqyZYuGDx9erbo++eQTPfbYYxo6dKgWLlyoN998U//617/Oul9GRobS0tKUmZmpp556SuXl5Ro3bpz69etX6ZJN48aNNXLkSP3xj3+U1+vV+PHjNWzYMCUmJiovL0/PP/+8rrvuOrVq1Uq5ubnavn27RowYUa33EEgECwBAQLhcLi1ZskRPPfWUvF6v2rRpoyeeeEKDBg1SWVmZPv30U40YMUIRERG68847dcUVV1T52JmZmbr66qvVt29fJScnV6uuu+66S2vWrNGDDz4ol8uladOmaeDAgWfdz+FwaN68ebrjjjvUt29fhYWF6aqrrtKMGTMqtWvfvr2uv/56XX311Tp48KCuueYaPfPMM5Kk6Ohobd26VS+//LK+/fZbJSUlKSsrS7/61a+q9R4CyWGq870eC7xer9xut4qKiuRyuerz1AAQko4dO6a8vDy1bdu2yg+IBE7lTH9LVf38Zo4FAACwhmABAGgQ/v3vfysmJua0y9nMmjXrtPt27dq1Ht5BcGCOBQCgQUhPT9eGDRtqvP91112nXr16nfK1Ro0a1fi4oYZgAQBoEKKiotS+ffsa7x8bG6vY2FiLFYUmLoUAQIio57n4CEE2/oYIFgAQ5E4Mwx85ciTAlSDYnfgbqs2lHS6FAECQCw8PV1xcnAoKCiQdvxdCMD0NE4FnjNGRI0dUUFCguLg4hYeH1/hYBAsACAGJiYmS5A8XQE3ExcX5/5ZqimABACHA4XAoKSlJCQkJp3xYF3A2jRo1qtVIxQkECwAIIeHh4VY+HICaYvImAACwhmABAACsIVgAAABrCBYAAMAaggUAALCGYAEAAKwhWAAAAGsIFgAAwBqCBQAAsIZgAQAArCFYAAAAawgWAADAGoIFAACwhmABAACsIVgAAABrCBYAAMAaggUAALCGYAEAAKwhWAAAAGsIFgAAwBqCBQAAsIZgAQAArCFYAAAAawgWAADAGoIFAACwhmABAACsIVgAAABrCBYAAMAaggUAALCmWsHi2WefVffu3eVyueRyudS7d2+9//77dVUbAAAIMtUKFq1bt9bUqVO1du1arVmzRj/5yU80ZMgQff7553VVHwAACCIOY4ypzQGaNWumxx9/XKNHj65Se6/XK7fbraKiIrlcrtqcGgAA1JOqfn5H1PQEFRUVevPNN3X48GH17t37tO1KSkpUUlJSqTAAABCaqj15c+PGjYqJiZHT6dTYsWM1d+5cpaamnrZ9dna23G63f/F4PLUqGAAAnLuqfSmktLRU+fn5Kioq0t///nf99a9/VU5OzmnDxalGLDweD5dCAAAIIlW9FFLrORYZGRlq166dnnvuOauFAQCAc0dVP79rfR8Ln89XaUQCAAA0XNWavDl58mQNGjRIycnJKi4u1uzZs7V48WItWLCgruoDAABBpFrBoqCgQCNGjNC+ffvkdrvVvXt3LViwQFdeeWVd1QcAAIJItYLF3/72t7qqAwAAhACeFQIAAKwhWAAAAGsIFgAAwBqCBQAAsIZgAQAArCFYAAAAawgWAADAGoIFAACwhmABAACsIVgAAABrCBYAAMAaggUAALCGYAEAAKwhWAAAAGsIFgAAwBqCBQAAsIZgAQAArCFYAAAAawgWAADAGoIFAACwhmABAACsIVgAAABrCBYAAMAaggUAALCGYAEAAKwhWAAAAGsIFgAAwBqCBQAAsIZgAQAArCFYAAAAawgWAADAGoIFAACwhmABAACsIVgAAABrCBYAAMAaggUAALCGYAEAAKwhWAAAAGsIFgAAwBqCBQAAsIZgAQAArCFYAAAAawgWAADAGoIFAACwhmABAACsIVgAAABrCBYAAMCaagWL7OxsXXjhhYqNjVVCQoKGDh2q3NzcuqoNAAAEmWoFi5ycHGVlZWnFihVauHChysrKNGDAAB0+fLiu6gMAAEHEYYwxNd3566+/VkJCgnJyctS3b99TtikpKVFJSYl/3ev1yuPxqKioSC6Xq6anBgAA9cjr9crtdp/187tWcyyKiookSc2aNTttm+zsbLndbv/i8Xhqc0oAAHAOq/GIhc/n03XXXafCwkItXbr0tO0YsQAAIPhVdcQioqYnyMrK0qZNm84YKiTJ6XTK6XTW9DQAACCI1ChY3H777Xr33Xe1ZMkStW7d2nZNAAAgSFUrWBhjdMcdd2ju3LlavHix2rZtW1d1AQCAIFStYJGVlaXZs2dr3rx5io2N1f79+yVJbrdbUVFRdVIgAAAIHtWavOlwOE65febMmRo1alSVjlHVyR8AAODcUSeTN2txywsAANAA8KwQAABgDcECAABYQ7AAAADWECwAAIA1BAsAAGANwQIAAFhDsAAAANYQLAAAgDUECwAAYA3BAgAAWEOwAAAA1hAsAACANQQLAABgDcECAABYQ7AAAADWECwAAIA1BAsAAGANwQIAAFhDsAAAANYQLAAAgDUECwAAYA3BAgAAWEOwAAAA1hAsAACANQQLAABgDcECAABYQ7AAAADWECwAAIA1BAsAAGANwQIAAFhDsAAAANYQLAAAgDURgS7AmgX3SYe/ljIelFxJ9o5bUSaVHZHKS6TyY1J56fGfFSWSzycZnyRz/KcxZ1g39mqqD8FWLwDgP87vJ0U4A3Lq0AkWG/8uHdov9b69esHCVyEVbJa+Wicd/EI6uFMq+lI6cvD4UlpcdzUDAFAX7tomxbYMyKlDJ1hERh//WXbk7G3LS6Xc96RN/5B2LpZKvFU7R0RjKdx5PAVGOKWwcEkOyREmOb7/ecr17xc5avTWAsYRZPUCAI4LC9zHe+gEi0ZNjv8sPXz6NhVl0tqXpKVPSd4v/7M9MlY670dSfGep2flSXLIU3fz7pZkU2UQKj+SDFgCAswidYHG2EYuCrdLcMdK+T4+vx7SUegyXUodIST2+H30AAAC1ETrBotH3waL0FMFixyLpjZHH50s0jpOuuE/60QipUeN6LREAgFAXOsEi8vtLIWX/dSlkZ440e5jkK5faXCr97G9SbGL91wcAQAMQOsHiVCMWX+dKb9x8PFR0uU664W9SRGRg6gMAoAEInRtk/fcci0NfS7NulI4VSZ5e0vUvECoAAKhjoRMsfvitkNIj0pz/JxXulpqmSD+fzXwKAADqQehcCjkxYvHFR9KeVdKXq45P1Mz8u9SkRUBLAwCgoQidYHFijsX+z47/jIyV/t8bUosOgasJAIAGJnQuhbTvL7laS7FJUudrpP/5UEruFeiqAABoUEJnxCKphzTp80BXAQBAgxY6IxYAACDgqh0slixZomuvvVatWrWSw+HQ22+/XQdlAQCAYFTtYHH48GH16NFDTz/9dF3UAwAAgli151gMGjRIgwYNqnL7kpISlZSU+Ne93io+ohwAAASdOp9jkZ2dLbfb7V88Hk9dnxIAAARInQeLyZMnq6ioyL/s2bOnrk8JAAACpM6/bup0OuV0Ouv6NAAA4BzA100BAIA1BAsAAGBNtS+FHDp0SDt27PCv5+XlacOGDWrWrJmSk5OtFgcAAIJLtYPFmjVrdMUVV/jXJ02aJEkaOXKkXnrpJWuFAQCA4FPtYHH55ZfLGFMXtQAAgCDHHAsAAGANwQIAAFhT749NP3EZhVt7AwAQPE58bp9tOkS9B4vi4mJJ4tbeAAAEoeLiYrnd7tO+7jD1PBPT5/Np7969io2NlcPhsHZcr9crj8ejPXv2yOVyWTsuKqOf6w99XT/o5/pBP9efuuprY4yKi4vVqlUrhYWdfiZFvY9YhIWFqXXr1nV2fJfLxR9tPaCf6w99XT/o5/pBP9efuujrM41UnMDkTQAAYA3BAgAAWBMywcLpdOr3v/89T1KtY/Rz/aGv6wf9XD/o5/oT6L6u98mbAAAgdIXMiAUAAAg8ggUAALCGYAEAAKwhWAAAAGtCJlg8/fTTSklJUePGjdWrVy+tWrUq0CUFjezsbF144YWKjY1VQkKChg4dqtzc3Eptjh07pqysLDVv3lwxMTG64YYbdODAgUpt8vPzNXjwYEVHRyshIUG//vWvVV5eXp9vJahMnTpVDodDEydO9G+jn+356quv9Itf/ELNmzdXVFSU0tLStGbNGv/rxhjdf//9SkpKUlRUlDIyMrR9+/ZKxzh48KAyMzPlcrkUFxen0aNH69ChQ/X9Vs5ZFRUVmjJlitq2bauoqCi1a9dODz/8cKVnSdDPNbNkyRJde+21atWqlRwOh95+++1Kr9vq188++0yXXXaZGjduLI/Ho8cee6z2xZsQMGfOHBMZGWlefPFF8/nnn5tbb73VxMXFmQMHDgS6tKAwcOBAM3PmTLNp0yazYcMGc/XVV5vk5GRz6NAhf5uxY8caj8djFi1aZNasWWMuvvhic8kll/hfLy8vN926dTMZGRlm/fr15r333jMtWrQwkydPDsRbOuetWrXKpKSkmO7du5sJEyb4t9PPdhw8eNC0adPGjBo1yqxcudLs3LnTLFiwwOzYscPfZurUqcbtdpu3337bfPrpp+a6664zbdu2NUePHvW3ueqqq0yPHj3MihUrzL///W/Tvn17M3z48EC8pXPSI488Ypo3b27effddk5eXZ958800TExNjpk+f7m9DP9fMe++9Z+677z7z1ltvGUlm7ty5lV630a9FRUWmZcuWJjMz02zatMm89tprJioqyjz33HO1qj0kgsVFF11ksrKy/OsVFRWmVatWJjs7O4BVBa+CggIjyeTk5BhjjCksLDSNGjUyb775pr/Nli1bjCSzfPlyY8zx/xGEhYWZ/fv3+9s8++yzxuVymZKSkvp9A+e44uJi06FDB7Nw4ULTr18/f7Cgn+255557zKWXXnra130+n0lMTDSPP/64f1thYaFxOp3mtddeM8YYs3nzZiPJrF692t/m/fffNw6Hw3z11Vd1V3wQGTx4sLnlllsqbbv++utNZmamMYZ+tuW/g4Wtfn3mmWdM06ZNK/3bcc8995hOnTrVqt6gvxRSWlqqtWvXKiMjw78tLCxMGRkZWr58eQArC15FRUWSpGbNmkmS1q5dq7Kyskp93LlzZyUnJ/v7ePny5UpLS1PLli39bQYOHCiv16vPP/+8Hqs/92VlZWnw4MGV+lOin2365z//qfT0dN14441KSEhQz5499cILL/hfz8vL0/79+yv1tdvtVq9evSr1dVxcnNLT0/1tMjIyFBYWppUrV9bfmzmHXXLJJVq0aJG2bdsmSfr000+1dOlSDRo0SBL9XFds9evy5cvVt29fRUZG+tsMHDhQubm5+u6772pcX70/hMy2b775RhUVFZX+oZWkli1bauvWrQGqKnj5fD5NnDhRffr0Ubdu3SRJ+/fvV2RkpOLi4iq1bdmypfbv3+9vc6r/Bidew3Fz5szRunXrtHr16pNeo5/t2blzp5599llNmjRJv/3tb7V69WqNHz9ekZGRGjlypL+vTtWXP+zrhISESq9HRESoWbNm9PX37r33Xnm9XnXu3Fnh4eGqqKjQI488oszMTEmin+uIrX7dv3+/2rZte9IxTrzWtGnTGtUX9MECdmVlZWnTpk1aunRpoEsJOXv27NGECRO0cOFCNW7cONDlhDSfz6f09HT94Q9/kCT17NlTmzZt0l/+8heNHDkywNWFjjfeeEOzZs3S7Nmz1bVrV23YsEETJ05Uq1at6OcGLOgvhbRo0ULh4eEnzZw/cOCAEhMTA1RVcLr99tv17rvv6uOPP670aPvExESVlpaqsLCwUvsf9nFiYuIp/xuceA3HL3UUFBToRz/6kSIiIhQREaGcnBz96U9/UkREhFq2bEk/W5KUlKTU1NRK27p06aL8/HxJ/+mrM/27kZiYqIKCgkqvl5eX6+DBg/T1937961/r3nvv1c9//nOlpaXp5ptv1p133qns7GxJ9HNdsdWvdfXvSdAHi8jISP34xz/WokWL/Nt8Pp8WLVqk3r17B7Cy4GGM0e233665c+fqo48+Omlo7Mc//rEaNWpUqY9zc3OVn5/v7+PevXtr48aNlf6QFy5cKJfLddI/8A1V//79tXHjRm3YsMG/pKenKzMz0/87/WxHnz59TvrK9LZt29SmTRtJUtu2bZWYmFipr71er1auXFmprwsLC7V27Vp/m48++kg+n0+9evWqh3dx7jty5IjCwip/jISHh8vn80min+uKrX7t3bu3lixZorKyMn+bhQsXqlOnTjW+DCIpdL5u6nQ6zUsvvWQ2b95sxowZY+Li4irNnMfp3XbbbcbtdpvFixebffv2+ZcjR47424wdO9YkJyebjz76yKxZs8b07t3b9O7d2//6ia9BDhgwwGzYsMHMnz/fxMfH8zXIs/jht0KMoZ9tWbVqlYmIiDCPPPKI2b59u5k1a5aJjo42r776qr/N1KlTTVxcnJk3b5757LPPzJAhQ075db2ePXualStXmqVLl5oOHTo0+K9B/tDIkSPNeeed5/+66VtvvWVatGhhfvOb3/jb0M81U1xcbNavX2/Wr19vJJlp06aZ9evXm927dxtj7PRrYWGhadmypbn55pvNpk2bzJw5c0x0dDRfNz1hxowZJjk52URGRpqLLrrIrFixItAlBQ1Jp1xmzpzpb3P06FEzbtw407RpUxMdHW1++tOfmn379lU6zq5du8ygQYNMVFSUadGihbnrrrtMWVlZPb+b4PLfwYJ+tuedd94x3bp1M06n03Tu3Nk8//zzlV73+XxmypQppmXLlsbpdJr+/fub3NzcSm2+/fZbM3z4cBMTE2NcLpf55S9/aYqLi+vzbZzTvF6vmTBhgklOTjaNGzc2559/vrnvvvsqfX2Rfq6Zjz/++JT/Lo8cOdIYY69fP/30U3PppZcap9NpzjvvPDN16tRa185j0wEAgDVBP8cCAACcOwgWAADAGoIFAACwhmABAACsIVgAAABrCBYAAMAaggUAALCGYAEAAKwhWAAAAGsIFgCsuPzyyzVx4sRAlwEgwAgWAADAGp4VAqDWRo0apZdffrnStry8PKWkpASmIAABQ7AAUGtFRUUaNGiQunXrpoceekiSFB8fr/Dw8ABXBqC+RQS6AADBz+12KzIyUtHR0UpMTAx0OQACiDkWAADAGoIFAACwhmABwIrIyEhVVFQEugwAAUawAGBFSkqKVq5cqV27dumbb76Rz+cLdEkAAoBgAcCKu+++W+Hh4UpNTVV8fLzy8/MDXRKAAODrpgAAwBpGLAAAgDUECwAAYA3BAgAAWEOwAAAA1hAsAACANQQLAABgDcECAABYQ7AAAADWECwAAIA1BAsAAGANwQIAAFjz/wE4qTOOEYMypQAAAABJRU5ErkJggg==", + "image/png": 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", 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" ] @@ -317,7 +317,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 7, "id": "1a8b271b-0bcc-47a2-b6f4-df27151fd183", "metadata": {}, "outputs": [ @@ -331,7 +331,7 @@ " dtype=float32)" ] }, - "execution_count": 22, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -350,7 +350,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 8, "id": "99ed3c1f-3fe9-4c04-8b3f-a510bcc82829", "metadata": {}, "outputs": [ @@ -360,13 +360,13 @@ "" ] }, - "execution_count": 29, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -397,7 +397,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 9, "id": "71b2643c-185d-413e-84da-a11a92c34d76", "metadata": {}, "outputs": [ @@ -407,13 +407,13 @@ "" ] }, - "execution_count": 26, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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AXrNmjeX3iT3mH/7wB3ncuHFyMBiU58yZI3/00UeWH+PnP/+5PG7cONnv98snnnii6toty7IMQP7Zz34mf/rTn5aDwaA8ZswY+amnnuJ/f/jhh+VPfvKTcmVlpVxdXS3Pnj1b/te//mX4fGbHpdXrt5TcMUJDV1cXampq0NnZierq6nzvzqDmf1/9EHe/kDDXTxtdh//7uj3DIEEQmTMwMIDdu3dj7NixKCsry/fuEAQA8+PS6vWbWkcSBU8oqqS9KAVGEARBOAEJIKLgCceUICUJIIIgCpmvfe1rqKqq0v352te+lpd9+sxnPmO4Tz/4wQ/S3v/kk082vP/KlStz8ArcobjrGIlBQVQYgjpAZfAEQRQw3//+93HTTTfp/i1fdopHHnnEsNu0lQqrF154QbccHwCGDh2a1b7lExJARMEjToGnCBBBEIVMc3NzyiSEfKPtV2SXXHRlzgeUAiMKnoiQAuujCBBB5AWxHxtB5BsnjkeKABEFjxgBEv9PEIT7BAIBeDweHDhwAE1NTQgEAildiAkiV8iyjHA4jMOHD8Pj8SAQCGT8WCSAiIJHFD1xGYjFZXg9dAImiFzg8XgwduxYHDx4EAcOHMj37hAEAKCiogKjRo2yNA3CCBJARMETjalbVUVicXg99ociEkQx8s9dR/DLf3yIu/7fJzCqoSIv+xAIBDBq1ChEo1HEYpSGJvKL1+uFz+fLOhJJAogoeMKatFckFkdZBlOhCaIY+dL/JmZZ3fT0W/j912ak2do9JEmC3++H3+/P2z4QhJOQCZooeLQRIO3vBDEY+PBIT753gSBKChJARMGjNT6TEZoYjMTiJPwJwklIABEFT0Rz4temxAhiMBAlAUQQjkICiCh4IlFtBIguBMTgQJxVHScBRBCOQgKIKHi0Ka8oRYCIQUKv0PiTeu8QhLOQACIKHkqBEYOV3lCU/5/kD0E4CwkgouChFBgxWAkLx34oSsKfIJyEBBBR8ETjlAIjBidi+jcci1MlGEE4CAkgouDRRnwoBUYMFrTHfihKXZgJwilIABEFT5hSYMQgRVsAMBAh8U8QTkECiCh4WAos4E0crlpPEEGUKtpoJ0WACMI5SAARBQ+L+JT5E4er1hNEEKWKVuxTBIggnIMEEFHwMNNzeSAxADVMKTBikKBN9w5EKAJEEE5BAogoeFjhS3lyAjylwIjBQqoHiAQQQTgFCSCi4GEpr7KkAKIUGDFY0HqAKAVGEM5BAogoeFjvk6CfUmDE4CKqTYGRCZogHIMEEFHwMAFU7qcqMGJwoU2BhSgCRBCOQQKIKGjicZl7gFgKTHtRIIhShcrgCcI9SAARBU1MVlIAZT7mAaIU2GBgf0c/5v/kVSz89aZ870re0Ip9agJKEM7hy/cOEIQZ4uwjXgZPKbBBwf+++iG2t3Zje2s3wtE4Ar7Bt15LHQRMxz5BOMXgO6MQRYUogCgFNrgQp5/3hqJ53JP8oY340LFPEM5BAogoaKIqAeRJuY0oXcSLfc8gFUBaDxClwAjCOUgAEQWNXgSIUmCDA7Hp32AVQKkeIDr2CcIpSAARBQ0TQJIEBJMeELoIDA5IAOkIIBL/BOEYJICIgoYJIK8kwe8lATSY6CcBRB4ggnAREkBEQcPGXng9EvxeKXEb+SAGBf1hQQANDE4BFNP43agLOkE4BwkgoqBhY798HiUCpDWGEqWJOPdqsFaBaQVQlI59gnAMEkBEQSNGgHyUAhtUkAcoVQDRsU8QzuGaAGpvb8eCBQtQXV2N2tpaLFy4ED09Pab3aW1txZe//GW0tLSgsrISU6ZMwR/+8AfVNmPGjIEkSaqfZcuWqbZ5++23cdZZZ6GsrAwjR47EPffc4/jrI3ID9wB5JAQoBTaoED1AoUFq/mUtH1j6l1JgBOEcrnWCXrBgAQ4ePIjVq1cjEong6quvxjXXXIPHH3/c8D5XXHEFOjo6sGrVKjQ2NuLxxx/HpZdeijfeeAOTJ0/m233/+9/HokWL+O9Dhgzh/+/q6sLcuXMxZ84cPPTQQ3jnnXfwla98BbW1tbjmmmvcebGEa7BRGF6Ph1Jgg4wBEkCIJwVQmc+LSCxKESCCcBBXBNC2bdvw4osvYtOmTZg2bRoA4MEHH8T555+P5cuXY/jw4br3++c//4lf/OIXOOOMMwAA3/ve9/DjH/8YmzdvVgmgIUOGoKWlRfcxVq5ciXA4jEcffRSBQAAnn3wytmzZgh/96EemAigUCiEUCvHfu7q6bL9uwnlYtMdHKbBBhzoCNDiHgLIFQFnAi+5QlDxABOEgrqTA1q1bh9raWi5+AGDOnDnweDzYsGGD4f1mzpyJp556Cu3t7YjH43jyyScxMDCAc889V7XdsmXL0NDQgMmTJ+Pee+9FNKr4A9atW4ezzz4bgUCA3zZv3jzs2LEDx44dM3zupUuXoqamhv+MHDkyg1dOOI1eCoy64ZY+siyrTNChyOC88LPjn3VBp2OfIJzDlQhQa2srmpub1U/k86G+vh6tra2G9/v973+PL3zhC2hoaIDP50NFRQWeeeYZjB8/nm/zzW9+E1OmTEF9fT3++c9/4tZbb8XBgwfxox/9iD/32LFjVY87dOhQ/re6ujrd57711luxZMkS/ntXVxeJoAJASYEpVWC0Ci59Usu/B+dnHhNSYMDgfR8Iwg1sCaBbbrkFP/zhD0232bZtW8Y7c/vtt6OjowMvvfQSGhsb8eyzz+LSSy/Fa6+9hlNOOQUAVCLl1FNPRSAQwLXXXoulS5ciGAxm/NzBYDCr+xPuwC4A6jJ4WgWXOtp5bxQBokHABOE0tgTQjTfeiKuuusp0m3HjxqGlpQVtbW2q26PRKNrb2w29O7t27cJPf/pTvPvuuzj55JMBAKeddhpee+01/OxnP8NDDz2ke7/p06cjGo1iz549mDBhAlpaWnDo0CHVNux3o+cmChfmAfJ4JPh4CowuAqWOVgAN1siHNgVGFZAE4Ry2BFBTUxOamprSbjdjxgx0dHRg8+bNmDp1KgBgzZo1iMfjmD59uu59+vr6AAAej9qW5PV6EY8bn/y2bNkCj8fDU24zZszAbbfdhkgkAr/fDwBYvXo1JkyYYJj+IgqXuKxEgAKUAhs0aD/jUGSQm6D9lAIjCKdxxQQ9adIkzJ8/H4sWLcLGjRuxdu1aLF68GJdddhmvANu/fz8mTpyIjRs3AgAmTpyI8ePH49prr8XGjRuxa9cu3HfffVi9ejUuuugiAAmD809+8hO89dZb+PDDD7Fy5UrccMMNuPzyy7m4+dKXvoRAIICFCxdi69ateOqpp3D//ferUmdE8RAVTNBKFRitgksd7WcslsG/sr0NCx5Zj33tfbnerZxDKTCCcA/XGiGuXLkSEydOxOzZs3H++edj1qxZePjhh/nfI5EIduzYwSM/fr8fL7zwApqamnDBBRfg1FNPxW9+8xs89thjOP/88wEkfDpPPvkkzjnnHJx88sm4++67ccMNN6get6amBn/729+we/duTJ06FTfeeCPuuOMO6gFUpMTETtAeSoENFqKaqG9YEEBX/3oT1u48iu8+806udyvnkAAiCPdwrRFifX29adPDMWPGQJbVq7wTTjghpfOzyJQpU7B+/fq0z33qqafitddes76zRMHCzveqKrA4RYBKHa3XRa8P0I7W7lztTt5QqsDIA0QQTkOzwIiChkWAfGSCHlSkVIHpdIIWp8WXKtoIEHmACMI5SAARBQ27EHokCX4PrYIHC1oTNEuBiVHjgUHQHVoxQVMXdIJwGhJAREHD+wB5lQiQ1h9ClB5GJmhxKnww2RywlEnxAEVJ/BOEU5AAIgoaZRSGR0iBySn+MaK00Ipc5gHq6Ivw2wbDMaAVQCT+CcI5SAARBQ0vg5fAU2BA6qgEorTQRoDY76IXqC8SK3kRlOIB0vFCEQSRGSSAiIJGjAB5kxEggCrBSh3mAZKSHznzvojVYLIM1cDUUoSGoRKEe5AAIgoa1SwwIQJEAqi0YZ97hab/jbYarC8cRSmjHYZKJmiCcA4SQERBE1N1ghYiQHQhKGkiyc+9PMAu/InftSmgvhIvhdeOwojGyf9GEE5BAogoaFSjMDyKAKJUQGnDBC4TQLG4jHhc1okAGQugUogOxbkQVE7VdOwThDOQACIKmriQApMkRQRRNUxpwy7yFX6lWX0kHk8ZitprIHJ++Y9dOOXOv+H1D464t5M5IKpJgQGUBiMIpyABRBQ0YgQIgNILiFbBJQ0TuGUB8cIvp3RCNuoGvfQv2xGLy0U/L4ylgIN+EkAE4TQkgIiCRhyGCiil8HQRKG3Yhb/cLxjfY3GENFVfvSHzNJfoGytG2PsQ8Hp4RRyNwyAIZyABRBQ04jBUQIgAURVYScNSYEGfV3Xh13qA9GaEiQS8xX2KYyZo1TBgin4ShCMU99mBKHnEYagA4PNSBGgwwEzQfq9y4Y/E5JSp8HqNAbsHlG7RQV9xn+LiwiiYAB37BOEoxX12IEoePgyVp8DIAzQYiHDzu0e58EfjKYJHLx3UPaCkxfojxV0mLw4DVkbBkAAiCCcgAUQUNCwFoI0AUQqstGERIO0QXG3KSy8CJN52TJgdVoyIVZAsEhamgagE4QgkgIiCJhZTRmEAihCiRoilTczgwm8lBSaKpIESiQB5PUoKrFRaQISjcbyyow09aYzsBOEWJICIgka5ACR+JxP04ECcASd6X6ykwMIlJIBYBNTjkeAvsRTYz17ZiatXbMKSp7bke1eIQQoJIKKgicvaCBAZQQcDovA1S4HpVYGJUaJITC7qaKGYAvOVWApsxdrdAIC/vXcoz3tCDFZIABEFTTSu9gD5qRHioCAuRIDEFJh2DEQ6DxAADKQplS9kVCboEuuCXhHwpd+IIFyEBBBR0CgeIK0JujQuAoQ+YgTIL6TAWDSH9wZK4wECjLtFFzri0FOvR0LAV1rRzwqhy3eMUtpEHiABRBQ0YiM4QIkE0UDI0iYuK2XwfiEFxoRRZTJ6oDVFJ27TRICK1AckagKPVHrHvkcYbtzRF87jnhCDFRJAREETS0mBUQRoMCCmftQpsMTnzqIH+hEgteApVgEkRkUkSfEAlUr6VxQ9fUUapSOKGxJAREEjXggBCM3gSuMiQOgTV6XAlOondvGvDCYiQOmqwABgIFKcYjmuSYGJkbBSQBQ9xd6wkihOSAARBQ0fheFlKbDSWgUT+kR1TNCRWNxiBEjjASrSi6usSYEpkbDSEEDi60g31JYg3IAEEFHQxOJqD1CprYIJfWI6JuhoTOYjMpgHyEoVWLEKoJiggBJVYKXTBT0Wl1Wvg1JgRD4gAUQUNPxCKGmqwCgCVNKI/Z+Y6A0LVWCVQS+/TUvpmKDVAkhpAVH84l8rUkkAEfmABBBR0ES1EaAS64VC6BMVhK9PVQav9gCla4QIFK8AkoWX5pEgvA/FL/5TBRClwIjcQwKIKGh4FVhy9estsVJgQp+48LkHVCmwZATIRgqsWD0z2hRYKY3C0IrU3lBxilSiuCEBRBQ0sZQqMEqBDQbUZfBiCixxe0XQ2AStva1YxbIqBeaR4C8hD5A2ckcRICIfkAAi8kpHXxgPv7oL+9r7dP+ujMJIHKpkgh4c6M3AEqvAeARIJxqiFQhhnWaJxQATQKxfoK+EIkDaz40iQEQ+IAFE5JUnN+3DD17YjrPueUW3HX5c4wFShqEW/yqYMIZHgDzqFBi7nUWA9DpBa48jPZFUDDCNz6Kf/hKKfoY0vZkGilSkEsUNCSAirxzo6Of/7+yPpPzdeBhqcV7UCGvEZOVzVzdCTO8B0kaAilUsKxEgzRiYEoh+akVpsfq0iOKGBBCRV8SVYJeOANL2AfLxFFhxXtQIa7AhuB4hBRaOxbmYMWuEqBXHepVixQAXQMmztJ8NQ40W/7Ef0lTm6UXyCMJtSAAReaVH6ADbNWBBAHkUPwhRuvAhuMIssEQKjPUBMo4ApaTAilUAaVNgJdQCgiJARCFAAojIK92iAOpPrQQx7ARdpGkNwhriENyAkAKLWJgFxqKDQV9xi+WUFFgJ9QHSeoCKNUpHFDckgIi80iNEffQiQMzv4PNoyuApBVbSxAQTtF+VAmMeoEQKLBKTuVGewSIkZmmyYsCoCqwU/G9a4aoVRASRC1wTQO3t7ViwYAGqq6tRW1uLhQsXoqenx/Q+ra2t+PKXv4yWlhZUVlZiypQp+MMf/sD//ve//x2SJOn+bNq0CQCwZ88e3b+vX7/erZdKZIEqBWbiAVKGoZZOGoAwJqZbBi+ndIIGUi+mvFdQ0ihd9BGg5DEf8BZ3REskpVllCbwmovjwpd8kMxYsWICDBw9i9erViEQiuPrqq3HNNdfg8ccfN7zPFVdcgY6ODqxatQqNjY14/PHHcemll+KNN97A5MmTMXPmTBw8eFB1n9tvvx0vv/wypk2bprr9pZdewsknn8x/b2hocPYFEo7QM2DuAWIXM6UPUOmUAhPGxFRl8ErkI6rpBA0kLp5lfm/KfcuLPgKU+De1Cqz4j33tZ0ImaCIfuBIB2rZtG1588UU88sgjmD59OmbNmoUHH3wQTz75JA4cOGB4v3/+85+4/vrrccYZZ2DcuHH43ve+h9raWmzevBkAEAgE0NLSwn8aGhrwpz/9CVdffTWk5EmC0dDQoNrW7/e78VKJLBE9QKIYYrALHvMAKaMwCuOitv7Do3h3f2e+d6PkUJfBJ1NgUcUDVBZQTl3aiynvFZQUQKECOVbsYuQBKoUUWGqzyuJ/TUTx4YoAWrduHWpra1VRmTlz5sDj8WDDhg2G95s5cyaeeuoptLe3Ix6P48knn8TAwADOPfdc3e1XrVqFo0eP4uqrr07524UXXojm5mbMmjULq1atSrvPoVAIXV1dqh/CfUTz44BJRQ+7CPoLqAy+vTeMyx5ej39/8PWCEWSlgjgChV34xWMl4PXwlJDWQMtEM4sKRYr04qq8B4nfS6kAgH1GzKhOJmgiH7gigFpbW9Hc3Ky6zefzob6+Hq2trYb3+/3vf49IJIKGhgYEg0Fce+21eOaZZzB+/Hjd7X/1q19h3rx5GDFiBL+tqqoK9913H55++mn8+c9/xqxZs3DRRRelFUFLly5FTU0N/xk5cqSNV0xkgizLqpWf3tRutuIvxDL4w90h/v8drd153JPSQ/QAsQu/OC/K5/Ug4FMiQyJRba+gAjhWMkHWpMBEM3ixo/VyUQSIyAe2BNAtt9xiaEJmP9u3b894Z26//XZ0dHTgpZdewhtvvIElS5bg0ksvxTvvvJOy7ccff4y//vWvWLhwoer2xsZGLFmyBNOnT8fpp5+OZcuW4fLLL8e9995r+ty33norOjs7+c++ffsyfh2ENbTlvP1h47EGPm0jxAJYBYueJUqDOYvY/oBFevqE48PnkQwFUEyTAisEsZwJLAXm1VZAFsCxny3az4giQEQ+sGWCvvHGG3HVVVeZbjNu3Di0tLSgra1NdXs0GkV7eztaWlp077dr1y789Kc/xbvvvsvNy6eddhpee+01/OxnP8NDDz2k2n7FihVoaGjAhRdemHa/p0+fjtWrV5tuEwwGEQwG0z4W4RzaC5NeCoxtw4QPN0EXQBVYR58igI72hvO4J6WHKIDYhV+MEPq9Hp4+MfIAlfuLO7rA3gNmbyylRohan1axfkZEcWNLADU1NaGpqSntdjNmzEBHRwc2b96MqVOnAgDWrFmDeDyO6dOn696nry8xDdzjUQelvF4v4povvCzLWLFiBa644gpL5uYtW7Zg2LBhabcjcov2pGceAfIk/2Um6PyvgsXZZb2hVAM3kTmiAGIpsN7k8SFJycgQE0Ax9XFTOn2AEv+WYiPEGP+MEpcgqgIj8oErZfCTJk3C/PnzsWjRIjz00EOIRCJYvHgxLrvsMgwfPhwAsH//fsyePRu/+c1vcMYZZ2DixIkYP348rr32WixfvhwNDQ149tlnsXr1ajz//POqx1+zZg12796Nr371qynP/dhjjyEQCGDy5MkAgD/+8Y949NFH8cgjj7jxUoks0EaAtCdBWVamfxdiBEgUQH064o3InJgq/ZOMACXfY7+mJUJYMxsr1QNUnIJB1qTAxKGwxY7S0ZtSYET+cK0P0MqVK7F48WLMnj0bHo8HF198MR544AH+90gkgh07dvDIj9/vxwsvvIBbbrkFF1xwAXp6ejB+/Hg89thjOP/881WP/atf/QozZ87ExIkTdZ/7rrvuwkcffQSfz4eJEyfiqaeewuc//3m3XiqRIdqTnjYCJM50KkQPUGefkvbqoQiQo4gRINbgoi+ZAtOKYa0gSO0DVJziNCUFVpIeIBYBIgFE5B7XBFB9fb1p08MxY8bwFQ7jhBNOUHV+NsLsca+88kpceeWV1neUyBvaapaBqDaVIQggL0uBFc4oDLGHEaXAnEUsg/f6JNVtTAgEDCIiXAD5lXEZxYhxI8TiFwt6HiBZllP6uRGEm9AsMCJvaC9c2ghQVCcC5C+geUiit4QiQM6iKoPX+ALZMRAwGHbKBEJFkZdY8xRYSiPE4hR0IloPEFAa5f1EcUECiMgb2gvTgGYgYkw40WtLgQthVS/uP3mAnEVdBaaOCmjHomg9Puy4qfAXdx8g5oNiQZFSmgXGPUABZYRJsQpVonhxLQVGEOlIKYMXypw/OtqLrn6h8Z1HnQYoBBO0eGGlFJiziCZoJnQYWg+QYRl8oLg7QadWgRVOBWS2aPsAAQkf0JB87RAxKCEBROQNZnwM+DwIR+PoTwqgQ10DOOfev/PtvB6JewMKyQRNKTD30CuDZyhjUayZoIt9Fpi2CqwQxH+2KNWdHv79pwgQkWsoBUbkDbaSrS5TezWee0s9MJdFfRL/L5w0gHjCpioWZ1ELIE0EKHk8BI08QMnfK/xKJ2htwUUxENfMAuMFAAUg/rMlJgw5DhrMdCMItyEBROQNJiCqkmbVaFxGNBbHx8f6VduJAqiQhqGKKbCQzhwzInO4AJJ0PECawbjGozASx5UsF8bxYhe2y9roZyGI/2yJ8oo+CUE/E0D0HSJyCwkgIm+wC9eQMqWbdzgWR/eAOp3kFSNABVQJE4pQBMgtVBEggyowo+GgWg8QUJwGW20KrJRM0FE+5NjDX1cxfkZEcUMCiMgb7ETOIkBAQlSIQ0YBqFIg/gLqhSJ6S8JFmmYpVFQCyKefAmO3R7SdoHUEUDGKhpQUWPJ7EJeVvxUrYpuDoJ+6QRP5gQQQkTfYiq884OUXtVA0jm6NANKLAMmyulN0PhBXrLJcGtU5hQKrAvN5JFUKFFCOAb2IiCzL/LgI+jxcPBRjdMEoBQbkdgHwm3V78Nt1exx9zKjgAaIIEJEvqAqMyBvsJO7zSAj6PIiGYwhFYykpMDECJF4EovE4vB4v8oV2xEIoGuPN+YjMEUWMR8cEzS6Yeo0QRU3slRIDUwci8aKMLsQ1jRDFVGA0JiOYg7N3Z18Ed/xpKwDgwtOOQ01F+uHTVoiRB4goAOhsTeQNcbSBGAY38wBpLwL5ROs9oRWsM2hFjNcjQQwCKX2AkiZo4XMQo4KieCrKFJjMRGDid7EdQK5eT2vXAP//gc5+ky3tEY2TB4jIPySAiLyhGCElXtIcjqZ6gMSojyoClG8BpDlhF2OUoRAR+9x4veoO4IBOJ+iovgDyicdVMQugZARIXAjkKt2qEkAdDgqgmOgBojJ4Ij+QACLyRlSTAgMSYfAeTQRI3QcoPz4IPbQCiFawziB+rEr6J7UVgl50JyYY0cUeQlqjdDHA3gfmAZIkKefNEFuFqI+jAkjHA0QCiMg1JICIvBGNixGgRAqsNxRL6dniE9JekqSYYikCVJpoRQwAVSVYqgla2V6VAkt6gAAgHCs+f4niAVJuy3UzxLauEP//4e6QyZb2UHmAfFQFRuQHEkBE3mBDK32CEbKzP5KynVjOzLYH8u/rYGkVNqySTJzOoDsEVxDBLBoU0ElvieXhxR5d0KbAAH3fk5v0CQ0+nRz4q/IA+cgDROQHEkBE3uDzgDwengLT+n8A9cBEtr14/3wgyzKPPLA+RnQCdwZVBEhSG56B1GGo4rBT8b4eSdkm39HCTNCWwQO5fz1is89eJwWQ4AEyGmpLEG5DAojIGzGdFJheBChFAPGBqPk7YYriiwmgYowyFCLMHyJJiUouQN0KgUUM9KIhYvNASVKaKBbjxVXpBK3cluvopxjV7As7N/BXTH/rtTMgiFxAAojIG1GxGyyLAPWnnmTZTCeGMhA1f6t60WvCUnTFeJEtRJi/V2V+FyJAAW/i/da7cMZSxkcURro0ExQxlzoMOFfRT1HU94aciwDFdAog6PtD5BoSQETe4BOhvcoq0IoHKNeVMHqIF6DKAIsAkQfICdjnKl74AzoRoIBOhZfYWkHctjjL4BP/qt6HHEdLBgQPUH/E3QhQMX5GRHFDAojIG5GYXgQoIYDEjsplPoMUWB49QKJRlwk0SoE5A9O1Yt8b1igTEFNgOiZobfdknUqxYkFphJjaBiJ3KTB3IkBxQQDxVCZ9f4gcQwKIyBsxoRKEeYCYCXpYTRnfTnuy9+e4FFgP0WxbQQLIUcQeMYygEAFiYlnP3yOO0AD0ewUVCzHBz8Tw5doELby3TnqAYoK4YylNigARuYYEEJE3VB4gTRm8OCFeW35bGCZolqZRIlQkgJwhrvHxAODHByAIIB1/j/a+xTxmQdZJgeU6/SumwJyNACX+9Yq9morwMyKKGxJARN6ICSt9bQqsTEh5iCdhQDBB5zMFJpbws1b+EfIAOQHTM6IJOugz8QCpZoEl/tWWzxdjBEivD5CSAsuDCdrJCJCeB4gEEJFjSAAReUNdBaYugy/TWfEz/IUQAdKbY1aEF9lCRM8EHRR8YKnT4FM7QWtTYMX42fA0kZACy3VKTxT1Yk+gbFGZoMkDROQJEkBE3uBRFK/YCDGxygz6vLjn4lNx0rBq3Dhvgup+vgIwtsYE8cYuxE5eIAYzemXwehEgMxO0T1MFVoyzwPRTYLn1AImiJBSNQZadeV4xVUl9gIh84Uu/CUG4g54HiAmLMr8Hl54+EpeePjLlfnwWWAGUwXuFWUbFGGUoRHgEyNADlHi/9ToIRzW9c4rZBB3XRLOA3DdCFNPPcTnx/opduTMlJnxOVAZP5AuKABF5I6ZKI6lL3bW/iygmaIoAlSLaKA6gSYGZeoBKpw+QXgosn40Q9X7PFHUZfPHOayOKGxJARN6I6nSDZYgeIC1KJ+j8V4GJHiBqhOgMTNiKkY+AXgrMl74KrJh7zOg3QsxfHyDAOaN/TOjXVMyVekRxQwKIyBuiETKoETxmESB/ITRCjCsncJ4CK8ET+Dsfd+K//vSubodut4hpmhkCGg+QVxsBkrk3Rds7p5hTYLJOO4Bcj4HRvm9ORWl4qtKT++7WBMEgDxCRNxQTtE4KzEIEKJ8CSPQA8RRYCQqgLz2yHt0DURzri+CBL07OyXNq01iAgQlauC0SkxHwSarUirhtMV5c2fsgiSmwHFdAar9jTqfAfB4PlcETeYMiQETeUErJPSkpMGseoPydMFV9gEr4BN6drMp7/u0DOXtOfQHkFf6vjgABiscnpumdEyiAisFM0UuB+XMo/mVZThFhTqV5lU7QQrPKIhSpRHFDAojIG6KRWCt4zDxAuS4F1kOvkVspe4ByGWzTM0F7dKJBfkEARZLiU4wqitsUozjVS4Ex31MuXo8oGquSA3+deF5ZlnmJP3WCJvIJCSAib6iMxBrBox2AKsK74eaxDF4t3ko3BZYP9EzQorgc1VABIHHcMHHAUlyiNwso8kaIeikwHgFy//WIz1GZHE3jxDEeE9Q09QEi8gl5gIi8wU6Efm9qFZipB6gAIkAqA3eJrmDzlWLUiwB9YdpIrNt1FJefOVoVLfR7JcTispICS+kEXcyjMBL/6s4Cy8GxL0aAKoLJeXcOtHoQ03eJYai0gCDyAwkgIm8oIsKTmgKzUgWWVw+QWMJfmsNQtZVfoWjM1JvlFNpmhgDQUBXEbxdOT9nW7/VgIBLn4jOuqSAr5uiC9rUAue2CLkZqKgMsApR9mjcudJP2SlJRpymJ4oZSYETeYKtYvT5AVqrA8jkMVZwFVsyl1mYwA7TR726h9fGYoTU5s4+ARYD434twFEY8z7PA2ALDIwHlfudEvjYFFixikUoUNySAiLyRqQeoMCJApV/Gq73Y9eRYAIkRICO0gkDbQ4h3GS7CiysTQJKqCix3Y2AiXIh6+PfTkQiQsOuiBygu5/c7TQw+XBNA7e3tWLBgAaqrq1FbW4uFCxeip6fH9D67du3C5z73OTQ1NaG6uhqXXnopDh06ZPtx3377bZx11lkoKyvDyJEjcc899zj++ojsMasCM/cAMV9HYXiAeLfhEjt5ay92uY4AidVPRmhHXWj7ALFeQZEiFKcsUKJqhJjDFBgTIyqjvwMeoJgmBSZ2+S617xBR2LgmgBYsWICtW7di9erVeP755/Hqq6/immuuMdy+t7cXc+fOhSRJWLNmDdauXYtwOIwLLrgAcWHJkO5xu7q6MHfuXIwePRqbN2/GvffeizvvvBMPP/ywWy+VyJCoTik5o8xvHAHy5rASxggxTVOqESDt6+kO5aYbtCiM08FNzsl9jWoFUDGboON6KbDcRT8jsdQFihMpMPF76xFSyEDpfYeIwsYVE/S2bdvw4osvYtOmTZg2bRoA4MEHH8T555+P5cuXY/jw4Sn3Wbt2Lfbs2YM333wT1dXVAIDHHnsMdXV1WLNmDebMmWPpcVeuXIlwOIxHH30UgUAAJ598MrZs2YIf/ehHpgKMyD16zQQZpikwT+4qYYwQjbpBTRSiVMhbCky2nwIzigAVmr9ElmWsfu8QJg2rxsj6CtNtdVNguYwAJYWK3+txdN4d0z/sM/J5JEgSIMul9x0iChtXIkDr1q1DbW0tFykAMGfOHHg8HmzYsEH3PqFQCJIkIRgM8tvKysrg8Xjw+uuvW37cdevW4eyzz0YgEODbzJs3Dzt27MCxY8cM9zkUCqGrq0v1Q7iLuFr3eSTVSpeV3erBy+DzOgtMSQ/wi1KJrV61q/GBHL0+WyZon74HyKPxABVKJ+jV7x3CNb/djIt+tjbttvopsNxFtHiRglfx6DkRodH6tCQaiErkCVcEUGtrK5qbm1W3+Xw+1NfXo7W1Vfc+Z555JiorK3HzzTejr68Pvb29uOmmmxCLxXDw4EHLj9va2oqhQ4eqtmG/Gz03ACxduhQ1NTX8Z+TIkfZeNGEb8UInabwAVUHj4GQhmKD10neltnrVrvYHHJoEng47JmjlwqkehsqyKv4C6zHz/NuJc9nR3nDabXVTYDkchRFVRWidS4Fpo3QASjaNTBQ2tgTQLbfcAkmSTH+2b9+e0Y40NTXh6aefxnPPPYeqqirU1NSgo6MDU6ZMgcfjfrHarbfeis7OTv6zb98+159zsCOaLAFA8EbyzrN6KJ2g87eqjwviTYwyyHJhRBqcQHuxC+VYAFnzAKkjQHHN+IhCa1Eg9lbqCZmnFOM6qcDcRoDi/Dmd7HauZ3KneWBEPrDlAbrxxhtx1VVXmW4zbtw4tLS0oK2tTXV7NBpFe3s7WlpaDO87d+5c7Nq1C0eOHIHP50NtbS1aWlowbtw4ALD0uC0tLSmVY+x3s+cOBoOq9BvhPuIKU/wdACpMTNC+Akg5iU0ctVUsuWgWmAu0F7sBByqArKDt5myGXxM50EaPAiYC6Lm3DuD7z7+HR66YhtNG1ma931boDysicv+xfkxoGWK4Lfs6SDqNEHPZCdonzrtzQARHdSJbPJVZhP2aiOLFlgBqampCU1NT2u1mzJiBjo4ObN68GVOnTgUArFmzBvF4HNOnp3Zz1dLY2Mjv09bWhgsvvNDy486YMQO33XYbIpEI/H4/AGD16tWYMGEC6urq7LxcwmW4iEiuasUGaWYXv0BBeICEi4M4lDMmwyR4VVSkeIByFQHSGYVhREATEdFGF8w6QV//xJsAgDuf24pnvvGpLPfaGmLU51DXgKkAUrwyym3a1+sm+iZoB1JgOkNelTRy6Q4UJgoPV3JLkyZNwvz587Fo0SJs3LgRa9euxeLFi3HZZZfxCrD9+/dj4sSJ2LhxI7/fihUrsH79euzatQu/+93vcMkll+CGG27AhAkTLD/ul770JQQCASxcuBBbt27FU089hfvvvx9Llixx46USWWAn1SHCJmLnM62h8gCVaBlvSgQoR9PuY7HUC6QRKY0QDcvg1elJUcyJnx8jFI2h3YJPxy59YUUApUuBsf0VFwO57IIeFdK8TnqA9FJghebVIgYHrq1VV65cicWLF2P27NnweDy4+OKL8cADD/C/RyIR7NixA319ffy2HTt24NZbb0V7ezvGjBmD2267DTfccIOtx62pqcHf/vY3XHfddZg6dSoaGxtxxx13UAl8gSHLsq2GdyKF4OsQxZsnWcUWjcslJYBSI0A5SoHpRAiMUCIHsvq+rArMID3Z0ad4cYKadGs0Fselv1yPbQe68Mp3zsVxteWZvpQUeoUUWLq2AqxcXNLxAOWiAEAZVeNsJ2g9kztVgRH5wDUBVF9fj8cff9zw72PGjEkxjC5btgzLli3L6nEB4NRTT8Vrr71mfWeJnCOmu1gEaEjQh+40q2KgMEqbozFtpMGDaDxWMGZbJ8h3FZg3g1EY2gojo/RkrxCJaesaUD3m+g/b8da+DgDA1v2djgqgPuH47howbyypFXOA8npz4QFyqxN0XCfFqaQqyQNE5A6aBUbkBdG/wy5W188eDwCYNKza9L5mxtZcIfYBApQTeCmF8IvCBK2JHGiHoYpdhkXTfF9IEXOHu0OqxzzSo/xupVzdKvG4rI4AWU2B5WkYasSlFFhU5/OlMngiH5SIXZMoNtQRoMTJ76uzxqGxKojTx9Sb3ld70csHYhWYuE+lFAFi729FwIu+cCx3HiAb3rBUE7RamHo9ErweCbG4rPpsek28OGJkRiuOsqE/Ym+2GvuK6JbB52AMDIsAiSZoJ75zun2AeBk8maCJ3EECiMgLehEgj0fCf0wZkfa+hTDfSdtwz8kLRKHAXsuQMh/6wrGc9wGyFQEy6ASd2CYhgMQeM6IZORSNIxqL8xJzUZiI0aBsEUUXkN4DpPc+8EaIOUmBCbPAXPAAiak9igAR+YBSYEReEE2c9qvA8u8XSI0A5V+UOQ17jawrd65N0JYiQJr+Mezt16swEi+uvSH1hVz8vavfnQhQn+Y5rTdCVG7zCVVtbiMe445WgelUtykRIPIAEbmDBBCRF5RKEGsrfZHC8ACpL9KluIJl6SRFABWBCVqvx4yOab5XIz7E6EyXEJkRo0H7O/qx4JH1eGWHuhmrVfrCmhRYWg9Q4l+P7jBU948zMZ3Ijm8njgGWvdMzQZfS94cofEgAEXlB2wXaDoXgtzFquBcqwQgQG0uSaw+Q18Kxob1waqvzAP3jpTesjQDpV2eJUZpfr92NtTuP4uoVmzK6UGuP13RiQjcFlssyeKFRqZNl6qzBop6wIwFE5BISQEReyLQHEKCkAQrBBO3TVBuV0kT4mFYA5bgKTKc/YQra1GNcp3Rcb1htX0oESBEjYtRHFEZiBGd/R3/6ndMQjdsTQPopsNw1QhSjnHwavAPCy7QTdAl9f4jChwQQkRe0AsIOeimNXMPSA2yMRykOc0z1ABVgBEhrgjaJmqjK4CPGEaD+sL4AOtoTFv5v3xukPV77w+bvp24KzJO7CJCYimTvszOdoBP/ip9R0GRkCUG4BQkgIi9oBYQdCiEFphVwZjOnihU2kqIymDDAFmQESPO+mzUPFAWINlInCh3xIq+a3dWtNEzMpD+QtnIrXUpRv6It8VrisrqVhBuIHblZt2wnR2HoeoBK6PtDFD4kgIi8kE0EiPsg4nJKN/FcoY1SlGIrf60HKGdl8DoXfiNSGiGy0m2v3sVV2X/thVY0QYvdjvvCMX6MtXUJDRJ77AugCO+rk9i3/rD5sWJWBSY+nluI76V4fGf7ndMzufsLIK1NWOPNvcccrY7MJySAiLygZ1a1ijjfKV9pMCMPUCmV8fIqsEBuTdB2xLE2HWoWNQlHlc9Ge6EVxYjY6yYal3nUQxRJmaXAWF8lPwArHqDEv3qvRXw8t+AdmyWlCizxvFkKIF4Gr9wW8DoXYSLc4939nfjcz/+Jzz5QGqOmSAAReSGbKrBADi8CRmgnlpeiiVMbAYrEZNfTLoB+p2AjtI0Q4zrpM722CdoIkChGtBdhlh4TTdAZpcCS+zakLPF+ajtDa9F7H0QB5HYzRHFmV1AQQNk2Q9TtBF2CKeRS5B/vHwYAtHWHHGmKmW9IABF5gfcYycIDBOTvhBmNl74AimlM0EBujNCZlMFrPUCqqInOxTVl0n3UTADFEp2kVY0U0w/t1aJEgBLvp3Y8hxYmQMRMIBvtAbjvlxEbIYqLjmyPcb3PtxS/P6VIXFgAfXCoJ4974gwkgIi8kE0KzOuRuC8iX6ZJbuLWlsGX0AqWXQArkiZoINcCKP222jJ4vfSZdl4YoFxo2WaiwVvrdeqPxFSjM4DUsRZWYMf8kKBf9dhG6KXAgNz5zcRomscjKT6dLI9xxQOk3BYgD1BRILZ/+PiY/VYQhQYJICIv2Bl4qYdeZU8u0V5oS3EWWExIU/JOwDl4fUr1kY0y+Kg2BWbeZI9dxKvLE2IkpBMBYo8xEImllKynG2SqB+sDVBHwKo9tUgpvlAp0SoikQzvuhY/DyLIaMGbWB6iEFhClyKEupRJSbBharJAAIvKC9uRql0CeGw9qm7mV8iwwn0dCmYOjENKRWRk8mwWm1wco1aDOPqfqpCGZXdSjsTh/3bVJcdQfiZl2jrZKWKiqYu+neQQoNQUGAIGkEHFbbGs/B6dEijIGhzxAxYb4PRBn5hUrJICIvJB1BCjPJ0xlUnayDJ6NwiihCBCPQHgllPlZL6DC8gBpoztmnaD1UmDV5eomj+LFvaZcqdZKSYGF7L8PrHmhz+tBeSDxfloRQNoUWK6ijUatHrKNAHFztTdVpJbS96cUEb//nSSACCIzojordTvkKg1ghHaURyl7gHweUQDlcAaVhT5A2govveNKb0wJEw/Mj8NO7OLFvVoQQNoUWLpJ7now0Rzweiy9n8wDZJQCy1UZPE/z8nEY2Ylg9j6oIkAl2EerFBErIUkAEUSGMBOxP0MBxCIvheIBKsUqFtHoHeQRLvcjQHql7EYEfGoxoNtlWM8EzQzJZeo5ZywC4fNIwgiQOD/xs885EwEUEaarlycFkNk4DL1GiOI+5M4ErR73km2UhmaBFS/9lAIjiOyJZFEFBuTfMxAT0kNAac8C83k8fPWfixSFHX+YYQpMJwIUUqXAEidyHuVJ/s4EXtCnRGkSVWCJ25uqggASHiC7HZF52lQVAbLiAdJGgHJzrBm1esj2GNDrBJ3v7zNhDTEVTBEggsgQvlLPoA8QoD/gMpcMillgwgWwzKEKICsoIib9ttpqQD2DLfeLiZ2gNT15eAoseTwF/V6U+RXjNxNGDVUBAInP364AYR4gv1eIAJkJoOTDa1OBuYqWxISIFeCc90i3CqwEFxCliHi8ZhIFLTRIABF5IdsqsFytgo3Q9gEqRQ+DYvSWhAiQ+ykw9h6y8QhmiJVJsiyneLMAfX8WE0PVfCxFMgUWYc/tUYkUdjszRov3sUpEiKiVBaxHgAz7ALk9C0zTh8gp4aXtou7kYxPuEY/LqmO+zyR9WyyQACLyQrYeIHZRc3scgBHaUR6lOQtMmAaewwiQEoWxngIDEp+JngAK6lWBafoAaavAAj61UZkJv6qgT9UfyA4sWunPugw+N9FGbbd2fgw4FAHykAAqKrTHarpRLsWAL/0mBOE8Wn+BXfTmO+USwx4pJTAfhxEV0pS5MEEf7QnhhXdb0Z6csyXOnzJCO6KB6U/dSeM6ZfAsBcYu6qo0lRClYX8v83tR7veiJxQ1NTDrwd5Pv1gGb/IYbHfz1QlaKyadEilxXaM6pcAKHW3Ex+7xX4iQACLyQtYeIF9+y+CVUR7qCFC+qtLcQPSABF3ucyTLMv7tvn+ojJUs4mCGXzh+IrG4/U7QGg8Q+/z8Xo+q+SOPSiUjQz2hqO0VMBPrPsEDZBZFknW8MkAuPUBqs7JTIl93XlsJppBLDa3goRQYQWSIVkDYJd+CQ1tuXYqjMESfFksHuSWA2nvDKVUlAQsRIK9H4imisNDFWbcPkCCWo9wErU6BsVJ1v1fx6fSHY3w+WEIApU9f6REVxZUVE7RBGXyu0q3aKK1TIlgv+hvUeLmIwkMb/S2FCBAJICIvODcLLE8pMNmd9EAhIX5GQSEa4gZHk2kvESspMEmShHSobJpeYWI5Hpd5k0HW64dd1JlPJzGuIhmlicZV1WFWojd6iH2ArDRCZO+/tgw+5xEgh0W+XpSOvSZZVgQSUViw749YeBAt8pQlCSAiL5SKB4hdaPMtyNxAjKYEXY4AHekJpdxmRQAB6rlweukVrWmYCREAqBJSYLIsq1Jgok9HTIGVW6jg0kPsA8RElFkagQVCUjtB58oE7U4jRLbbegIIKK3vUCmhnZ8HAH1FboQmAUTkBW2PEbtwY2u++gDFNGXwJTgLTC8CFHLphNeuFwHyp/cAAUqfn7BFD5BYOcgiQHE5scKN8hSYxFNdoWhMv0Fi2GYZfEznsTNIgeV6FhirdGSfR7a+O715bX6NmZ0oPNh3ozLo5d+vYk+DkQAi8kK2EaDC8QAxE3RpTYPX9tRx2wR9tCezFBigFsPKcaXzd828MACoDCp1IAPRGL/4+sU+QGGlD1DQ57XUxFCPiI4HyOz9ZLuZUgXm0FT2dKRUOjpkVGYXUtGn5RO9XCSACpJwVIiOWhjlUgyQACLyQrYeIF+eU078QuvV+CNKRADFBJEgelbcNEFrsXpsiCkhvUnyfk0KTPQtVPi9/MI7EIlpxn8IjRCF3kQZm6BVHqD0niq9fjmJ15ub6Ke2WakS5cyyCkynw7Xo5SqlKGopoUQwlTRwsVeCkQAi8kK2naD1BlzmEkMPUImcvGNCJY43ByZoccYQQ2v+NULx+Mi66RXFI5T4mxh99KjSe3F+PAV86lJ1MQXGbrebDtSrAhswEROy0TBUrzOpqHSw91Jb6Zj1MFSDFhilOE6mlBDTwxXMHxcp7nEYJIAI2xzuDmHJU1vw7v7OjB+DrcIznwWWv4iLLMuGgyJLMwLkcawLsBHZrCTF1AyfBSac2VJM0DElEgNANZhUL02V6AQtpMAsNDHUQ+wDpAjKLFJgbkeAYuoIlFPPy831eRrxQWSGXgqMIkDEoOP6J/6FP765H1/83/UZP0bWHiCdAZe5QqzS9WkqZCIxuST6mIg+GW8OZoFlcyLVT4HpmKCTF1Zt9I6XuwsRIJ/Ho44AcQ+QtR4+euil10xTYAZCIVd+s9QIkDMi2GjYbSm2kigl9CJAJICIQcf6D9sBAN0DmYc/i7kPUFQoo2arY79g2C2FFWwsJkaA1GkiN9BLgVlFNDnHdCuM1J6ZiFCODkDx40RjPDIZ8Ekqrw9Pgfk9WZigxVlg5mJCFNH5qgIzjHJmXQavn/4mAVTYiB6gikCieIBM0MSgJtOTlXaYqF3y2XlZaxAGUmdSFTvs85Gk3PQBYivJU0fUAACGVgct31dMcelFgLQ9o8SVLKBOgbHuytoI0IBOFZjtRoiq9Jq5p0qMMqZGgPLUB8gpAcRFqvr2fKa1ifRExBRYiUSAaBYYYQtZluGRlBN0W/cARtRV2H6cGF+FZ9cIMR8nS216SNwfoDTmgRmN+nDLBM1Wkl8/53iEY3GcOHSI5fuKgsCsDxD7XKIxtfjm4k5Igfm9SpoqLgM9oUSESkyBmfl39IiqPEDmjyGKbG0VWK56Thl1gs66CiyW+hkBuRvySmSG2Mmc++CoEaI+7e3tWLBgAaqrq1FbW4uFCxeip6fH9D67du3C5z73OTQ1NaG6uhqXXnopDh06xP++Z88eLFy4EGPHjkV5eTmOP/54/Nd//RfC4bBqG0mSUn7Wr8/cr0Io9IZjqtVpR1/EeGMTsvUAue1JMSOuMQgDiYsUEwulcAJnURKvw/4PI9hKsjzgxf/75HGYNKza8n3FC6eewVZrUI9oDPhidZM4DZ5FaQDwOWVBn1c1I8wO4jT4dI0Q4yYpsLwPQ81y0WFU3k8psMKGVbj6fWIfIKoC02XBggXYunUrVq9ejeeffx6vvvoqrrnmGsPte3t7MXfuXEiShDVr1mDt2rUIh8O44IILEE+ejLdv3454PI5f/vKX2Lp1K3784x/joYcewne/+92Ux3vppZdw8OBB/jN16lS3XuqgontALXgyFUDZdoLO52pRjACJu19K4zBSugA7tPo3gq0kmbfADuJw0LjOBHXxcxEbPKarAgt4PbxHEI8AOeABstJXSS6AFFiKCHboO6c3rw0ovUrKUoOd9wKUAjNn27ZtePHFF7Fp0yZMmzYNAPDggw/i/PPPx/LlyzF8+PCU+6xduxZ79uzBm2++ierqxOrvscceQ11dHdasWYM5c+Zg/vz5mD9/Pr/PuHHjsGPHDvziF7/A8uXLVY/X0NCAlpYWN17eoEZrfD7Wl9rAzgrORYDy5wFKdK9VRxrEpnnFjPbzKXP5/WYmaFZdYgelIjCua65nYpkN2tSaoMUIkBgdkqSEWVkUOmIfICemwYeTviXt90Dbh0kkd52gE//ySJlDx4DevDYg//P9CHPCgoCnKjAT1q1bh9raWi5+AGDOnDnweDzYsGGD7n1CoRAkSUIwqJgfy8rK4PF48Prrrxs+V2dnJ+rr61Nuv/DCC9Hc3IxZs2Zh1apVafc5FAqhq6tL9UOk0tWvjQBlJoCyrQJjzeDyITaMxFspNXJL9QApPhk3EFNgdhH9YLx3jhgB8in/T6TJ1NFHMboleoAAqNJgiW29KA9k5ocSxZX4uHpRNTEFpu0H6VQkJh0sSstTYKwBo2NVYJQCKya4CdpHVWCmtLa2orm5WXWbz+dDfX09Wltbde9z5plnorKyEjfffDP6+vrQ29uLm266CbFYDAcPHtS9z86dO/Hggw/i2muv5bdVVVXhvvvuw9NPP40///nPmDVrFi666KK0Imjp0qWoqanhPyNHjrT5qgcHqRGgbD1AGXaCzvHJ8omNe/HTNR8AEAzcJWzijGqMqkGhVNyNPkdMWLHoih0CvtTBjHqdoIGECBEjMQBUpmb2t4Dmb4ygzyP0Dcq0DF5pLMmeV4ss3JSSAhM6X7uJURVY9tPgyQRdjLCFQ0BshDiYTNC33HKLrsFY/Nm+fXtGO9LU1ISnn34azz33HKqqqlBTU4OOjg5MmTIFHp2L5P79+zF//nxccsklWLRoEb+9sbERS5YswfTp03H66adj2bJluPzyy3HvvfeaPv+tt96Kzs5O/rNv376MXkep0+WYByi7CJDbwzlFOvsiuPWP72D5397HzrbuFG8Eo5Q8DKkVQIkTniw7f+GNx2X+nlkdgCrC9k1MSakGbXo9/HWEVANTUyNAYY1BOkUA+T2KCTrDRoh+T2J/WBm+npBSpcCMOibnehq8432A8lPdRmSGmAJjkVq3qkJzhS0P0I033oirrrrKdJtx48ahpaUFbW1tqtuj0Sja29tNfTlz587Frl27cOTIEfh8PtTW1qKlpQXjxo1TbXfgwAGcd955mDlzJh5++OG0+z19+nSsXr3adJtgMKhKvxH6aE9OvaHMqgCy9QApESD3v4DrPjzC///h4V6MbawEoHhIGLxDbwmcwFOrwNQpm0AGQsUIUTAGM4gAseiU2ExRK6yDPg/6wolp72KlV+JvSjpVGx3SCjJx9dsftlsGr279UObzIhKL6l7wzVJgueqXwyvqkm+BU1FXvXltQGq7AqKw4N8NnyfjXliFhi0B1NTUhKamprTbzZgxAx0dHdi8eTOvvlqzZg3i8TimT5+e9v6NjY38Pm1tbbjwwgv53/bv34/zzjsPU6dOxYoVK3SjQ1q2bNmCYcOGpd2OSI/25NeTYRkkrwLLtA9QDqMte9v7+P93He7FyPpE3yPDFWwJRYC0PhkgIRSsd+lJjygAAt7MI0CiIVPvs+kLJzo6RzSRDbEpYUQrjgRB5vNI8HkzP/lHNMd80O9Fdyiq+zhMJEhS6lDYXKV/lVEYmghQst+StozdKoqwIg9QMcG/G0IVY7F7gFypAps0aRLmz5+PRYsW4aGHHkIkEsHixYtx2WWX8Qqw/fv3Y/bs2fjNb36DM844AwCwYsUKTJo0CU1NTVi3bh2+9a1v4YYbbsCECRP4fc4991yMHj0ay5cvx+HDh/lzssjSY489hkAggMmTJwMA/vjHP+LRRx/FI4884sZLHXRoDb49GY7D0HpM7OL2aAaRrn7lNX58rC+lPwqjlCbCa9MUkpQYhxGKxh1PUTATsCQpwsMO7FjoCwkpMCk1AgQwn4+2D5ASAQprTdCC8GOPkUkTuFhc5qXtfh3hpYVNW9EeY+J+5GsUBpAQQWUe+9E6wLgMXhFYxX1RLVVED5s4PqaYca0T9MqVK7F48WLMnj0bHo8HF198MR544AH+90gkgh07dqCvT1ld79ixA7feeiva29sxZswY3Hbbbbjhhhv431evXo2dO3di586dGDFihOr5RGPmXXfdhY8++gg+nw8TJ07EU089hc9//vNuvdRBBTvpVga86A3HeH8Uu0Qd8gDlIgIk9j7q6I8YV4GVUCt/rf8DABdAToe92TEV9HlSoh1WYMdCrxCNNPNnaY89UYhEU+aEKRd5Fg1iJuhYXEYkFudiyQxx4aBtwKhngo4blIqL9wslDemZvGfpiAuCzVAAZZCuBKgRYrES0UmBUQTIgPr6ejz++OOGfx8zZkxKNcmyZcuwbNkyw/tcddVVaT1IV155Ja688kpb+0pYh52c6ioD6A33O+ABysxL4nZZtkiXEOXq7Iso4sCrfwIvhTJ4PZEX9HuBgajj7zmLKGWS/gIUYSKejFMHiCrHi1bk6PUBCnjV4kjcriyg3NYfidkWQCnVZyZl8Hrahr2WeLKvUSZRs3To9SESP59QJA6UZfjYBtEtZco9eYAKkYiuCbq4z3WudYImShP2JaivDADIfCJ81p2g8xQBOtYXHhRlvHoiz61u0ExQZWKABoQUWFIAeTUNKsVtQtFYyjBU1SywFH+Qsk/smAt4PVxgDVhcAUeFi7pWAOkJSp4C0/l+BAVR5pYJVZxFJqZBnfjexYyqKPPY24tID18cZNEMtNAgAUTYIqQRQBmnwBwahhqLy9zT4RaiB6ijL5LSSI/vUwmF8HUjQC6VKWdTAg8oQoJVgen5ZsTPJhLTihyhEaIw7whQ0l2A0qNIkiTbFwBmgJYkve7axhEgsxRY4r7uHGviuBfxOHeiCSM1QixOxO9NqZigSQARtmDdQOsrFAGUSWM8o5OgVcRVsNtRILH3UYcqAqQtg2er4+IP4etF6NLNr8oUNhA009J6bQRIL6sqijfta1OlxzTRIbEzdWVQcQzYNULzEmKVp8q4mswsBcYM6ez1uIFeBAhwZggxe+hS7qNViogVkmXCAsCNxqi5ggQQYQtWoVGXjADF4nJGJ2E9k60dRD+C2ytGMc3XG47xvPdgjQA5nXYJcRN0dikwthrVO6bYY6siQCnT4NXDUAGgMqjskzinTBEv1j5rvYinYr62Z4IW9zknKTCdrtpORIBSZoHlsLcXYR/eJd3nUS0MijllSQKIsAU78dWW+/ltmfiAsm2E6BN8GG4LDu0XvDM5D02776U8DR5Ql4s7iVgFlglsv1gVmN4hJXYZNqr0GojEU2aBiVEfUQDxCJDFFIDYRZdRxt9PvQhQ4l+j70fQxD/kBOzzlyR1tZYT3ZqNor+57O5O2Ec5hj2q9hDF3AyRBBBhC7ZCLvN7UZW8OGTiA8p2FAbg3gVZi/YCxQSQYR+TEjiB6/Vp4ukPlyJAGafAkvtlJhp0TdAmw1DZZ1slCKDKgJACs9kMkc9REvsK+Y2jSEoESP/x3O7DYvT9FCNpTj92WYl0Fy5VxBSYz+vh0cBiNkKTACJsERYuViw9kEkpvNE8LTvkanaQdpXdZRABKqUyeL2LlFsrdCYwM48Aqe+nL4D0UmAe1d8SESAlzA+AT70GgIpgqiHargdIjKiZNUJUIjBGKTB3I0Ds+2mcpspCABmk98p4Wq/4vz+lSOoQYXXquRghAUTYgl38/F4PXx1nkgIz6qVjh4CwcncLcVBnZTLtwSNAXm0KTBm4WezopSjdMkFnmwLTNuTT880ETEzQqiqwlAiQYIIWxFCZzRQYf1xVWwHjCBBvQpjGA+TWsc/K8I18blmZoI1SYBQBKmi06eGyEiiFJwFE2ELsBVFVlvABZZICy7YTNJCblJNYkcKM3ywClLI6TvYxKYUqFr1eLW4Zb8Ox1PSQHbTCSe+Y0jM6643CMPMAicZPHq2wKAT4JHivTgTItAxe//HKTNJnTmAUoXUiCmjk/ysroRRyKaKdk1cKE+FJABG2EFNgQ5IXh0xSYDHuMcn8EMxF1ZWYYmhICqCOpADSdi5WPDLFfwLXrwJzNwJkpaOyHtrqMb0hnaJYVvo4qUP5iWGo2iowAw9QphEgvYiazvGSPgXmbgTIzV49RhEg8gAVNtrUcbnLIjwXuDYKgyhNwsKoAOYBEjslW8WZCJD7Jmh2gfFIQE2y95FRCszti1IuMfcAOfv69KIjdhB7QgHpTNBxwcugjgDFZfDcE/ubKHpqhMpHuyZo7cUDMI8ipasCMxNPTsB8OtoFihMRIP7Y2m7dPCJWvBfUUkYZE6NJgRWxB4gEEGELMQVWyavA7H8BnDRBuxoBEnrUMD/Isb4wgNQLdq6q0nKBXrNHtyJckawjQBoBpNc9WRAM2ou7VkABSifo0Q0VOK62HDXlfsz7RAv/u13/Q1RYOKTuU+pjyGlSYG6LbaUKUH17wMEqMG3wl7cFoAhQQaIMQ02mwErAA0QCiLBFWMcE3RfOkwcoB9PX2QWmzO/hFUGdfYkIkPaCrZhpi18A6X0+ZS4JPO0AUrtoU5F6ojogHCuyrI0A6QggYRbY379zLrySpEqt2R0GqRsBMmmEaNQskJGrTtDappIBB75zRo+tDIct/u9PKRKJqVPHdruhFyLkASJswT1AXjECZE8AxeOyUuWSjQByoC1/OtjFKREBSrzeDsM+QKXjYVBW6e73AQrriAM7iKMhAPMBoqFoTBh4mjrkkyFOWPd7PSm+IiYGLUeA9EaLWGiEqOdnAtz3yyhRMv00VTZRQF4Gr40AJR87FpdLopVEqRFNSYG52408F5AAImwhVuxUZWiCVg1azPCiB+Rm+jrvUeNX+h4xceDXXDRLqZOtXgTIrRSftvIqE8RSeLMBouFonJ/IxWPPSi8hkfJA8uRvcxq8ugrMrAzeagrM3QhQ6sR2FgGyd9HbdbgHA5GYevGj9QAJZvZS+A6VGtrqyVLwAJEAImwhpsBYX5xemx4gcc5QNimwXFaBBQXPE8NvuDou3hMCQ69Sxy3fSbYpMABpI0DqPkA66T1BQAW8HsPqK4btafB6fYDMGiGmmwXmUk8m/vzpxlXYiABt/ugYZt/3Dyz6zRv8dZk9NlDcUYVSRJaVfmj+EqoCIwFE2IJ9CYI+DyoyTIGxdACQZQosBxEX0QQtVgQBqdErdhEthT4mumXwLnmctKXnmSAamc06QYciqZ2gE39X/m+lH5HdFFREpxM0T5mapcAMBJDSNTnXozDse4D+vqMNAPDaB0ew+0gvv137OXk8SiqSBFBhIS5aAxoBRB4gYtDAKnbEFJgVE3R7bxjvHegC4HwEKBdl8LoRoJQqsNI5ebNGfLqeFaerwNjKMsNGiIA6fWJaBh9T+gD5vQYRIAv7YdcAqswCszkN3mBX3B6GGjUwYWcSdRU7xX94uIf/P127AqJwYAIeUKKY1AiRGHSIYVA7ZfDXP/EvnP/Aa1i366jKA1Tos8DCQt5bHIsAqC+gQGmVwTPPip4J2ukBnHpNAu2iSoGZjcIQmh2qozFCBMhCJEoxQdusAlPNAjMu+45brAJzaxgqe35tr6tMvnMfH+sT/t/P/6/32qgZYmESEaL25AEiBiWyLKuGRVZZHIYaj8tYu/MoAOAX/9il8hek81qY4cRk6nREBcFXoU2BudAkrlDQiwC5NYAzkuUoDEAtYPSiJuKxoudvsZsC46tfyyboVA+QWdl3uhRYriJARt2a7fjAWrsG+P8PdCj/1xO8ZlExIn9EhGNUbBEBUAqMGCSIeX+xEWI6AbS/Q1n1dQ9EDE+udsmFCVqs3klJgfk0EaAclOXnCr1p4G6ZoMPR7D1AYgpLK0wBdeQiGss+BWa7ESKrHNSJOoWjcR5xYaSbBeb+KIxko9KUie32ja9ikcT+DiUaZOrVKoHvUCkhnrNZVJg8QMSgQhQaAa+Hm4LTmaA/Oqqc9I71hvkcsGxSHkBuRk9EhP4tVSlVYBoTdPLkHYnJKp9TMcK0bi5mgTlRBi9GcPQaG4rRubQmaAv7YX8UhnEEiO2XSLoUmNvDUPU+f0AR+XbSHuL54UhPoou6JOnPOSsroXl6xUpfOIoVa3fjSE+I36aXpuatIEgAEYMB0QgnRkTEVbUebHYWALR1hxwZgwHkPgJUEVB7gFJmgQmVSMW+gtWbBu9Wp2s9U7JdxEntehEcUSzz59MRd0b318LeC+ujMHT6AJmUfadrhOj6KAyD7ygXfjaeV4wQszEyej4tQIwwFff3p5j57bqP8N/PvYf5P3mN36Z3/NpdBBQiJIAIyzCh4fVI8HqUYagA0GuyIhSHpfaFY8ow0WwFUA5GYYgrd60A0kYsxMhBsa9gzSJATp/wIg6nwHQjQIJnJmoylgKw6QGyGQESRZ7P6+HfgZQIUIE2QrQbeYrHZfQJ54aO5BgZo8WPW60WCOv84/3DAIAjPSEcTUaBeCdznVl2lAIjBgXiGAwgcUFkJ3QzH5BYBgsABzsTRkjtpGm7uG0EBcSOyHpl8OqTuNkFrdjQNUG7dHHSNljLBFGcitEcBou2hGNxvv964i7xf+spsEhMNo1+MvTSboBx1VM8TSNE10dhGPQBsvu8fZrteATIaMQHRYDyjjiGhJnW9aoYy6kKjBhMhHWqdawYocUIEAC+qsjaA5SDCJBomA36PBCvR3pm20yqZAoRvT4wTBg4PatJLzpil/I0JmYxRdab7Fvl1+nKDFgsgxeez8rwTr20G2Bczm4UgdHeL9cRILtpjz7NecFoDAaDyuDzz952xbPJClj0urVTJ2hiUCGOwWBYMUJ3aSJAR3sTq0Cth8YugVyYoIU+QJIkqbpB6zXuU5ohFu9JAdDvA6O66Dt4gVJOrpmfjsrTpMDKhAgPi0iKQsluFZgohq2sgNNHgNTHSzoB5LoJ2mAYql3vk9F5wdDbRCmwvMPSlABwgAug1OOXpsETgwpxDAZD6QZt5gFSnwTbkwIom74v4n64aoLmVWCJ5xJTLdrVvLhPxR8B0i+D5xd9RwWQ/nBZO5QLwlTvuPJ4JC6wYvHUcL7dPkCSJNlK1+j1AQKM58dxAZSmEaJ7ZfCp7xFgP0LDSuBryv2q242iv8EMyuwJ5whH4yrxeSjZw0nv+KUUGDGo0GtYV5E0QptFgFJSYEwAZbHiF/cjN1VgiS++KID0Jtm7PaQyV7AMl3ihkiRJCXuHnU+BZZMSLfeLYibVAwSojc6A+vjTDkO19Jw2VsB6fYAAwfOiOV74MFTDSIm7x5leJ3BAHXmShcGmRrB0Y0NVQPX5Gr2uMpe6jRPW0FoZWMGK3vFbJlQEWjkWChESQIRllBSYcvKqsuABYtEhtphlHqBsTK9AbkZPaEO/YjdovRReJtOyCxFWBq+9ULnR/MyJPkAVaSJAgFrkAOpGlnZTYIA9P0zYwOdUZjARPm5gQub3M2mi6AR6JnhALSKtfO8iPGrsRbUQBTISmWU5KGwgjNEuZJkA0u9jlfgMZbl4F3wkgAjL8Cow0QQdSC+A2P0aq4IAgKPJZmjZmF7F/chFCoylu8QIkHY6PKCszIvdxMlaPhlVAbmRAssmJVoWMPcAAToCSLgIV5elF1Cpj2e9KaCSQlA/tlFrAW5CTxMBAtwpAkg3CgOwdoyL5lkr77HbM84Ic7R2BR4B0m0d4Y4nMJeQACIsE9Yxq1oZiBqKqQWQUx6gXAxD1UaAxFJ4ra8BKJ15YHqNEAEh7eNg3j+iY663i8oE7dd/nHIzASR8llqhZPicdlJgmlSq8lz6EUOrHiC9+zqB0fP7hVYPVnw6YuGEnQhQsV5Qix1tBIgZovWqwPxeDz+ei9UITQKIsIxeFZiVgajM4NlYFQCgeICyT4G5Lza05r+6CuUkXl2uEwEqERN0zGAUgxvdX43SQ3YQI3PGF1djD1B1mfK5NlQGLD2nHRN0JI2pWHu8GKWgGH6vh4tTN6IlXADpfCZ2ooBhoYOw+B4bidSyEllAFCtavyZPgaU5fovVCE0CiLCMbgqMeYDCJikwTQSI4ZQJ2k2xoTX/if1k9CNApWKC1r8AF6oHaFhNGf+/YXpFE9kR/QyimG0aoj5OjbAXAdKvAjMqZ0+XAgPc9ZtFTSJQdqI0PLrn86jeY6PvvtLctDgvqMUOiwCx71MXT4HpH7/FPhCVBBBhGb1+LVYaITLhpF1ZZ5sCK8+BYVJr/tPrhCpSZlDWXGzEDC7AZQ6nwGJxmc+9ykYAjayv4P9nKVYt2s9LFHdidKKpypoAstOLR2+WEiD2jdI3QRulwFTP78ACoDcUxT6hAZ5RCjTxvNZ7Aak9QEIKzNCnVRp9tIoV9r0eWp0QQN2hKKKxuOHx63Y/KrchAURYRrcTdIClwIxPhtwErVlZZ5sCYxe0cMx8GGs2aM1/4gpIb5p10KCsudgwMkGXO1ymLHaUziYFJh5L2pltjDJNt2fx8xP9KdU6kT097PRBMRr3YSRi+Cw2k/fEyQjQ9U+8ifOW/x0bd7ernl8vBWcnDSpG94ZYMEGX+fRTgkRuYJ+XGAXtGogiwvuhuZ8SzyUkgAjLmKXAzPoAhaL6KbCsBZBwoXNLcGirwPTSXiJBg7LmYsOoDN7pnL9aAGV3PKy4+nRcNXMMLpp8nO7fRXOzVmwNEcztw2vLLT2fnfC/3jBJQGyEqN8HyCwC5JTfLBSNYc32NkTjMu5ctTXx/KYRIOuRV9EDNKTMjgm6uBcQxQo7V1cEvLzFSWd/xDgC5EJRRC5xTQC1t7djwYIFqK6uRm1tLRYuXIienh7T++zatQuf+9zn0NTUhOrqalx66aU4dOiQapsxY8ZAkiTVz7Jly1TbvP322zjrrLNQVlaGkSNH4p577nH89Q1G9FaxVvoA8RRYlTYFluUsMEGIufUF1FaBXT1zLCYNq8ZNc0/U3b4U5uMAxhEAp1d87P0FshdA501oxp0XnmzYCFFMgWm7Tns8Ev503afw1DVnot6qCdqG2OUXEMNGiNoIkLEAUZ7fmWNt28Fu/v++pJfPqAw+8bwZpMB8Hn6uAFL9WPx2g5QgkRvESl+22Ovsj+j2AQKUiDB5gDQsWLAAW7duxerVq/H888/j1VdfxTXXXGO4fW9vL+bOnQtJkrBmzRqsXbsW4XAYF1xwAeJx9Rf8+9//Pg4ePMh/rr/+ev63rq4uzJ07F6NHj8bmzZtx77334s4778TDDz/s1ksdNJiboE1SYCys6rAJWtWZ2KUvII8AJb/4NRV+/OVbZ2Hxv52gu32xh4QZ/AIsGUSAHBNAbOSG+cXeCcQIkN4g29NG1mL6uAbrjxewnwqyaoLmKTALJuhsj7WDyXlPALDvWL+quaJeCiwjE7TXg6oyGyboIk8hFyuRqDKWplolgPQjQMVugk6t43WAbdu24cUXX8SmTZswbdo0AMCDDz6I888/H8uXL8fw4cNT7rN27Vrs2bMHb775JqqrqwEAjz32GOrq6rBmzRrMmTOHbztkyBC0tLToPvfKlSsRDofx6KOPIhAI4OSTT8aWLVvwox/9yFSAFTo9oSiu+NUGTBlVh+/9+0l52YdMTNDRWJwbap1OgQGJNFh/JObaF5BHgHQumEb7AxRvSJhhOA2cvz5nLlBOVIBZRT3xPXuxZS8Fpt8HyNAEbTCMVMQpE/QxYfhlLC7j42N9plVodkSwaIIW04zpTdDF/f0pVsKxxPse8HpQmxRAHX1h7rFM7WNV3As+V84669atQ21tLRc/ADBnzhx4PB5s2LBB9z6hUAiSJCEYVC6SZWVl8Hg8eP3111XbLlu2DA0NDZg8eTLuvfdeRKPKxXfdunU4++yzEQgoYex58+Zhx44dOHbsmOE+h0IhdHV1qX4KiTXb2/CvvR145PXdaO0cyMs+6EeAzPsAiV1qh5T5VF+gbIZfMtweyGdU/mmEG52S84GhAHI8ApTsAp0DAWSWAsvm8ayIwaiBkDYsg2ezuEw8QMzs3WdSgGCFY33qqrm27pBpHyI7qTfRAyRGgIy6dRt1xiZyAzvHB31KCqyrP2LYB4gtiMyGYRcyrpx1Wltb0dzcrLrN5/Ohvr4era2tuvc588wzUVlZiZtvvhl9fX3o7e3FTTfdhFgshoMHD/LtvvnNb+LJJ5/EK6+8gmuvvRY/+MEP8J//+Z+q5x46dKjqsdnvRs8NAEuXLkVNTQ3/GTlypO3X7Sbvtyp5+g27j+ZlH7gAEiNAAXMTtDimIujzqDopOxUBAtwTHEYrdyMqivyEwIgZRCCc9wApfWLcRm2Cdu7YszMLLDUFpm9kTtcIEVDmn/WZ9OCygrZtwOHuEBdgXp3IZ7mNKI34+ao8QGkiQJQCyw9iqov1beoaiBouBNn5v8/EA1rI2DoL3HLLLSkGZO3P9u3bM9qRpqYmPP3003juuedQVVWFmpoadHR0YMqUKfAIX8IlS5bg3HPPxamnnoqvfe1ruO+++/Dggw8iFApl9LyMW2+9FZ2dnfxn3759WT2e0+w6rBjIPz7Wb7Kle4R1Zjaxk1ooql+KzgSQR0oYia2cBO3gdg7adgqsyEPCjFhMXwA5XfWhN2DXLcqE480JAcQMzHYaIWojXUYVVUZ9mET46jvLY00bATrSExIigKnb20l7iN3jLZXBCx6gYp0w7jQdfWHcuWordraZFxE5QUiI8rOqva6BiLAQVH9uVkYhFTK2PEA33ngjrrrqKtNtxo0bh5aWFrS1taluj0ajaG9vN/TuAMDcuXOxa9cuHDlyBD6fD7W1tWhpacG4ceMM7zN9+nREo1Hs2bMHEyZMQEtLS0rlGPvd7LmDwaAq/eYWoWgM/eEYgj6vqow7HR1Cnv5AR54EkM4oDDGi0xuOoaZc/QUJadJmVaoIkHM+jAFKgTkKiwAZjcJw2gRtVWBmQ7lqXIYDxx6P9qVf/eoNkwSMh3+adWJmVDgkRo8lI0Dl/oSf7khPSIgA6kWArD+vygMklMEbDTBWD9iM2zpHlio/fHEHnti4F49v3Iv3/+czrj5XWCWAEufq7oEoF+7aiKSVUUiFjC0B1NTUhKamprTbzZgxAx0dHdi8eTOmTp0KAFizZg3i8TimT5+e9v6NjY38Pm1tbbjwwgsNt92yZQs8Hg9Puc2YMQO33XYbIpEI/P7EF2716tWYMGEC6urq0j6329zw1Ba88E4rvv//TsYVM8ZYvl9HfwEIIJ1GiAGfBwGvB+FYHL2haEqfnBDPKSe+KKIAcsL3UZazFNjgNEG73freiUnwVlFVgTlw7DH/myUhYNBIziiaEjd4/0Wc8l+wJqZjGiux7WBXIgXGBZjJ89pI/fm9HjRbGDEi+rT6wlESQAA2Ji0P4Wgcx3rDqLPYpiETxM+LnfO6B6KoSabDjCJAZqOQChlXzjqTJk3C/PnzsWjRImzcuBFr167F4sWLcdlll/EKsP3792PixInYuHEjv9+KFSuwfv167Nq1C7/73e9wySWX4IYbbsCECRMAJAzOP/nJT/DWW2/hww8/xMqVK3HDDTfg8ssv5+LmS1/6EgKBABYuXIitW7fiqaeewv33348lS5a48VJtY2eAokinEKY+1JVdui9TIlFlNSdSYbIK0BqnRSNkVZm1jrtmuN2HQolQWIsYlEwKzCACUR5wtkrHqLrEDcT+QEbdou3APDhmLSAYxqME9Ec/GEXgVM/vZx6g7D6Lvkjiezs6OU7kSE9YSYHqCEW2iLHi+xA9JZIk4ZlvzMS/nzoMX5k1Vnd7r0fi70mx++icolNY/O471meyZfZEhPN1dfJc3aVqhKjvARoUESA7rFy5EosXL8bs2bPh8Xhw8cUX44EHHuB/j0Qi2LFjB/r6lA90x44duPXWW9He3o4xY8bgtttuww033MD/HgwG8eSTT+LOO+9EKBTC2LFjccMNN6jETU1NDf72t7/huuuuw9SpU9HY2Ig77rijYErggzYqKETECFBHn/6sI7fRiwABiS9BR19E1wgd1ngfxAiQ6AnIFLerwOyWaZeKCdqoEZ7TnaCNRkS4gRhNcOLYU6qwzE/+8bjM30/td6fcQMTETTw4DCUCld3Fhz33qAYmgEJ8FpSe8Lcj/MRhqAAweVQdfvol80h8RcCHgUi46L9DThCPyyqT+sfH+nHqiFrXno99H4NC5+7ugQhvYaKNnCptUIrzs3JNANXX1+Pxxx83/PuYMWNSTG7Lli1L6eosMmXKFKxfvz7tc5966ql47bXXrO9sDsmkz0UoGlOdDMS+HblErwweELtBp74mNhQ0qOMBqnYiAmSjEicTFO/G4PIAxdMIIOdmgel7Y9xANEEPCWZ/7PEqrDSftdgKQmv8NxIxigA1fl/YsW9FiJjBxOyoZATocHeIX/D0PEhsn614n0QPkFUqAl6092Zf3VYKdA1E+LBgAPjY5QgQ93n6JB4B6h6IKqNcNOcDdiyYjUIqZGgWWI7JpH29GAIFEhfXfKRYjFbrvBeQzglLGzUSB006sQp3W3DYNem6XZafK9KVwTs9C8wJU3I6aiqUY6/KgWOPC4E0q1+xwku7eBBFVFy40imzwIwf1ykTNEtfjE5GgI72hPnnoteIsSJgvfInkwhfqURRnUDbouCgyz3glIi9V4gARQ1TuFXkASLsYDT7xwx2gqsIePkJqSMPUSC9PkCAeTdosbEWAAyvKeN/cyQCZKMZXSbY7QPEJ9RHlQ7YxYhRI0Te98NhAZSLFJg4ikU022YK8+CEY3HVUFctrMePRzJeQcuy+pxgFIETUdJn2V18mFgfWZcQQOFYnJ9f9CKfivCzEQGyYXKvcPgYK2a00X63z/tilF/pAxQx7GNV7CkwEkA5JrMUWOLgK/d7lfbk/bn3AaVPgaWeELVl8C2iACp30APkegrMXh8goLiN0EYCqCKorM7jDgg8oxlDblBXoVTPmAkWq4ieIrOLtfgdkLSz1Xz6j2ElBeZEpCQcjfPPoK4iwL/Lh7sThRZ6Jmw7IjiTz7fCRnuBUueYJgKkjQg5jdiXi0WA+sIxfgwbRoAoBUZYwajxmRls26DPg9pkGP9Yb+4jQHqzwADzkHhYUwYvpsBEP1CmuO0BYuXLfotVYKLHo1hXsLIsc9+B1gPCLn5A9g34gNxGgMSmgk4cL6wFBGB+sda2gtDuk95ICysm6AoH0q1i+qw84EVdZeL72dadSLXoRT7NUt5ajM4ZZlAESEFrf3C7AEaM2IkWBfa82uNBPAaLMeJNAijHZBIBYqHxoN/LV7H5qAQzqgIza4aljRpNGVWHUfUVOH1MnSPGV6erkkRicRnMp291Xz0e9yfUu414IkudXeUB0xFOtL9XTrjue4BEnPAAAYIR2SQFYBQ5ZShVVcr7aaUM3ok+QKwE3ueREPB5+PmFHQJ6oi3dAGQRveap6agIGJ9PBhtskcF6KLW7fN7nVWC+RB8gdi472pN4Xu35QN0It/g+L9eqwAh9Mqmi0Y0A5dMDlFLJYjwPLKRZAZb5vVhz4zmmJ3Y7uJkCE9MkVqvAAPcn1LtNVBBA2gyMJEmoDPjQHYpmXX0EKMdULjpBA8B9l5yGZ7fsxzVnHe/I41UGvOjsj6SJAKkrIbXopbKMGlGq75f43mUj/tlzMjElpgkB/X1mzxuJyQhH46b+nkgGfZ6cMneXAqzD/XF15WjrDrke+dcK1iFlPvRHYnxcivZzDPo88HkkROMyekNRR3yduYQiQDlGmXZsPQXGIglBvxe1yROUdn5PLjBKVzABpHcRYGXw4knS5/WYzjiyg5tVV6IQsBPCd7s3kdvEhfYUulVADra/z6UHCAAunjoCv104XVURlg0VwfTpmvQRoFTPC58FZrJQqAwoqahM52axcws7Zus074vePleovE/mxwCvAsvABO2EwC522HE1vLYcQGKRqR2c6yRa0zpLg7H90C5UJEkqaiM0CaAck40Juszn4SeofKTAtIZmhlkfIDGk6gZuppvE4a5WO0EDymdcChEgPQHkZCVYNE8pMKeotGDYNfMAAfqVNEYmdBEm/mU58+np2u+0dsyC3j77vR6+fTqREokmG0BmkALLtsFjKcDOIUOHlPHUs5uVYCFNpe8QTURHLyJZzEZoEkA5hqXA3jvYZXnVForqRYAKxwTNvgBdA6n7lG71my3s/XTDMMmiE4D5hUhLsfcCEqu79BrhORsByp0J2g2seIBCUfNFgF4EiEXhzIR3hWhIz/D417ap0KbAjL63Vi96mXy+YqXhYIeJwMqg4v90sxJMe76u1sx21BOylUU8ELU4zzpFDItYyDKw5PdvWRJBA4IHKK8maAMxw74kXQPpy+CdhoVoe3SeO1tY91O/V0opXzaD9YdxKgWW6+qKdBEgPdNupoRznAJzmkoLPhzrKbDUMnizFJg3aVxO3Dezz0LZt2QKLCUCZL7P6S564Uw8QC4uaooN0aPFPhs37Q/aRa62Wa1eMYhSBUwCiEjDpGHVOOfEJgDAM2/ux/oP29Peh0WAyvxeboLWlke6TTQW55Uh2lUAmwDfrbNP2jJ4p6kyMWBnC+8BZNOgW+agifO+v+3AJ//7b/jnriNZP5ZV4vziC13hpwzDdK4M3o7JvJCosNAJN50JWkkpChEgCykwIHvDcEoKTOMBCvrT7XOaFFhGESBnGjyWAv2CR6ueRf9dMkKrzvEsApQigFKPR74IJQFEpCPg8+Cxr5yBS6aOAAC8+O7BtPcRI0C8EWKOU2BiOkhraBQ7hmpxOwUmfvmcjpRkenFmE+qz7ZMjyzIeXLMT3aEorv3t5qweyw4x2Vz4VQjm22yJZtAnppCwEq3QpplSHiOYmkYzGkZr9PyZGoa1+1avTYEZfC5WZ0Cx84a9TtDOzDgrBcQpAKxHU3tvyJXnEmfWKSZotSD265wTWOVXV44X5U5QnGedEuC8ic0AgM17j6XdVokAeXj1SkeOD7awYLLUnhSVL0BqNUq6k3+2iP1cnO5DoYzBsLfvdvqkmPHhkV7+/55QVGXKdhMW+TIKfDlpgi72FJgVP1RaEzRLowmC2WoDQXb8Z3qshWPq6FRKCsxgZIhZ5ScjFpf5osSOwLWSVhwssGOizO9FbXnis3Er+s8M64DyfbQSATKzQBQ6xXnWKQE+MbwGAPB+a0/atvziCZSZoDv7IhmXvmZCKKacjLT5fPYFCMfiKeX9TLy5tcIP+rz8sZ32ASmDUO1FgJyqivj4WD//vywDe472mmztHPF0ESAHJ0AXuwnaihhkwlwcnSFSruOnsRo5UQZWZnZRFHuMATomaIPPpcKC+Vs8r9kpgy93MMJY7PTxCJCP2x/civ6zc7wkzKxLiQDpCqDEdyDXtgwnKM6zTgkwsr4cVUEfwrE4PkpzYeN9gIQUWDgWz2mVET8he1PnGVUKQ1q1aTBeBm/gJXAClgbrdlgAGU1ATodZY0g7tHb2q37fc6Qvq8ezSlTwAOnBL/qOCqDi9ADpiRct7MJQU67fe0hPRFntoMzEdqbHvra7e21F+gseoO9b0qISQNQIMSPEPk1soemW0BCHXbNzfIoJWmdRxI5rSoERlpEkCSPqEs2t9h3rN92W9wHye1ER8PKTSS59QGZeHkmSeKhU+yUwmiDvJFXcB+Ts+8GqwOx6gJyKALV2qnP9rV0DWT2eVeK8C7GR/8O5RnWZisxCgV0gzKIVXWkEkFL2rTxG2GJkLFvxzyJAYqd2EaPqR0Xkm0WAhJSKjUKCYqkqenLjXjy1aW/WkfhYXDZsbihWgdW6bH/QO1drI0B6UUxmgaAIEGGLEXUVANSpDj3ECJAkSagpZ6XwuTvgeCrLIJRttDpxuwweUC4CTuegI7wKzJ4AqrSQHrCCVvC05UgApSvBrtS5YGeK1Qt9oWJFgGQSAdJ25DV+fpYCyy4CZLdKk4s2E5EippDtdH6vFnxNuUzz22Ffex9u+eM7uPkP72DVWwcyfpxYXMb597+G0/77b3jtg8MpfxerwGpcjgDppV21HqAKHQHEI0AZpmHzSXGedUoEFgHabzECFNSEqTv6c9cLqE+oRtCDG6EH9AWQW2XwgFAKX2IpMNbriQ1CzFUEiM+hMrho8T5ADpbBF2sKrCqYXoCkE0DsOyUeL1Yjp0OyjH7qLVCsCP5KC+MqMhmECigR3bhcuJVg63Yd5f9fs70t48fZdbgHOw51YyASx9NvfJzyd7EKjAsglxa+elF+bQRIbL7JUBa/hR2x04MEUB5hAujjY+beDhamZuHpWpe/CHqwni9GAkjJA6u/BG6XwQPWLkKZEMkyBZatAGJi8sShQwAArV3ulL9qSTeGodJiEzwrWI10FCpWPut0AkivkosLwzQjQoZk6QHSi+xGLbSTsFIFlkkTRCAR7WDHnhsNTp3gvYNd/P+bP0pfyWvEu/s7+f837lb3hJNlWYkABdyvAmMVgX5VCkwRPGV+j+45wcj+UAwU51mnRFAEULoIEBuFoY0A5VAAJU90eisAwLgXUC4EULVbHqAMGyE6VQbPxOT45ioAwKHOHEWAZPMy+AoHPUCs9DZX0+CdRkmBGR977IKlHSvAH0Mj4GVZVhUdmMHEU3emZfA6bSoWzhoLALj+38Yb3s+KCM5U3EqSZOl9zSdt3cp3cX9Hf8YDSncLrS5auwZU4iYci/PFSHnA/RRYOKqXAlOOWSMfVzGboPWvZkROsOoB4hGgZBopHx4gthJJlwLTRqXcLoMHBBO04ymwzFawTqXAUiNAuU6BGXUBds4DFIkXdwrMyiiWoz2JVGZjVUD379rjN2yjfDxrD5DOAmXJp0/EZz7Rgqmj6wzvV2FhAjgTt5n4u4aU+dDRFynY3jKHhGisLCfO4cc3Vdl+nKOauV4fHe3FqSNqAair4Mr9XsiJywX6IzGEojHHbQVhnd5TYp+1mIEfiwn77mQzWjtzE/NNcS67SgQWATrSEzKdZj5gGAHKnQeol6fAjCJA+h6gXJTBK8NYnU6BZRadcKoKjK2oThyaOLF29kdcmXqvJZauDN7Cxc8qSqqnOE9FVUI0TK8TeW8oyv1zjVVB08foCUcRj8uq6imrHqCM+wDpePQqgz5MG1NvOv/OigjOxuDO0tqFWgl2SLMY2dueWYuK9h71OVyMCLFFp98rwe/1YEjQB/aRuBEF4p4t4bsoihmjTvtilKhQI3ZGFOdZp0SoKffz4aitJukNpVlZHj1APAVm7gHSRqVyUQbPVsFOnyxZBMiuB6hSZ7SBXWRZ5oJuRF0FypICUnvidYN42giQc7OaWJSgWEdhiCtkvePvcHciUlAR8HLhqIWJGFlOlNNHhK7racvgsywAyDRFbaUVQjYG90JPgbHPddKwagCJqrBMYJPdmaAUe30x4cy8nx6P5KoRmn1eQYNjzqhhb8Dn4dcxrQe00CnOs06JIEkShtWUAQAOmgigAWEUBgDXO4LqwcKx7OKuhXWQPZaSAnN3FAYg+CAcPllmWgXGVvThWFw1QsQOfUJEoabcj+YhieOEnXjdhJfBG1WB8TL4GBdLmVLsnaCDPi8XD3oC6EhP4vNqGqIf/Uk8hoeLhJ5QlEdOvB4pbTrBjRSYFXgVmAUPUCafbbVLzU2dIBSN8fPaqcclOvrvPZqZADqanOs1JZluFLu99+tU3rrpA0p3LJh91d32J7lFcZ51SoiWpABq7TL2AWkjQDVJsZHTFBhryOXXX8XWJwf1HetT75Pb0+ABsQrBpSowu32AhJV+pmkwlkr0eyWU+T38ApoLAaQMQzXvAgxkP/A100q7QsIsCsM+L6P0F5BYCImtHJTy8fTvSbaTuNNNqjeiyoJA4RGFDBY/2Y74cBPxc544LOHP+yjDCBBbME4ZlRBAeimwcqE5pZvDsI2Ou/+YchwAYELSi6gHzwDk8JrkBCSA8kyLhQhQSBsBykPfhf40KTAeAerVF0BuVoEp0SdrX75n3vwYU+5ajZUbPjLdLtMIkN/rMY0KWIGJueoyPyRJQlPyAnq4JwcCKGYeASrze7gXIdtxGMWeAgPM0zVMIGgbyqU+hjJQ0uogVEDsgh419GiYEc5QpLALntmQ3nAWJmi3ens5Qa/QEmRMQyWAzFNg7PWdPDyRShNbovRrUmCAccNZJ9CORWHcfdEpuGnuifjF5VMM76tMqicBRNiApcDMPEAD2ggQzwPn7mBrT644tLNhGPXJKdLtwj7F4jJPp7gpgNjq+kiPtfdjxdo9aO8N47Zn3jUtX41k6AEClKhApgMdWQSInfAahyTe3yMFEAGSJMlSIzwrFHsKDDAvRWcCuErTUC7lMYTKQaMLkR7i9zGTY007CsMqoqAzKj7I5rN1q7u7E3Qn221UBn18AZtJZDYai/PPmrW6ONIT5oUOepW3fBi2qykw9SK3PODF4n87AeNMqtwaKhPnYBJAhC1aahKVYEYCSJbllDB1rvsAxeIynku2ez/RIAxaV6l8MdmKUPS/uCuAkuKrN5TWkxKOxrH9YDf/XWxEpiWaYRUYkH0vIFYBxi40TVXJE20uIkCsEaJZFVDQmWaImTbLKyTMohVcABl45/hjCKXwdsrHRQ9SJn1YMq3S9Hk9/HUbXYyzqfDL1tvkJiwCNCTow9DqxPfyaG/Ytt9PTB8Pry3nEX52LWBCSIwA1ST7rblx7tcrg7cKXwCTACLsMKyaeYD0BVAkJnPzWZB3gk4cbH3hWE7Kon/+yk7+f1b1oIWl5WRZOSGKJwQ3TdBMfMXl9CeGQ10Dqj4r73xsIoCyuDhbGRZphjYClFMPUJpO0ID+/KpMKPZhqID5xZoJxEqD9hH8MYJKGs1u+Xg2vhClStO+Ry+d8VVJ5WVeBeZ0c1Mn6BEiQHUVfn5+sLs4YSkuj5Q4Pw6vTSyGD3Qm/KADuh6gxLnOjaaDER4Bsv95MQGk7WtU6BTvWadESOcBElM0TEQMKfPx9IRV30umyLKMxzfuBQCc0FyFodX6Zk6f18NPiGyfQsnW6pJk30hsB7/Xw6NiR9KchMQOrgCwx6R6gw9DzeIEnumJSvQAAe4KoFVvHcB/P7eVr94sCaCgse/FDqWQAuMmaJ2LNYsAGZXA88cQvDx2TNBAdlWhvEozgz5d6fwomc4CA7Kfcu8mbFFTFfRBkiReoWm3RYUyXzHxOMOT2YADHYnH4R4gnSqwDhfO+9lEgBpYFN6iDaFQKN6zTonAPEBHekK6IdSQThTF45EUxe3yAdfeG+bibNXiWabN0ZQwaOKEKPoLzO7nBA3J504ngA5p5ml9KFRdaInyKjD7X5O6LNOUTDixCwFL81n1OcXjsqE5VSQUjeE7T7+FFWv34L9WbQUgNEI0EUBOlL3GBY9YUafATC7WLAJk5J3Te4wBYf6TFWqzqArNpk8XS8cYCqAsonsFLYAG1KK2ObkobLM5q48dG+xzHl6bXAx3JCNAyc+m3F8YZfBmUAqMyIj6ygACXg9kOTU6AShh0KBPLSIU46+7KRFWlnlcbXnaE7L2S5BphUkmNCTfj3SCkK3S2Pu3x0wAxTK/OLNQdUeGJwSWAmMXAjECJBu0pGcc6w1jxrKXMe3ul7Czrdt02zf3dnCRvW7XEciynHYaPODMiZiVwAPF2wkaMH8vWLQgXQRI7HzMIwMGLSe0MLGt7cFlBb1p8FaxmgLLrA9Q4faV0YraockIkN752wxmcmZNEIfVqFNgShWY8v7VuOj/zKZzt5ICy83AZqco3rNOiSBJktILSCcNZtRIsMFmRCBTWIRkbGNl2m215ehGVQVuwCIkR9MIQiYYzxib6Lvx8bE+w0owJQVm/2tSW5ndiYqtfNlFhgm2cCyett/RazuP4FBXCB19EfzxX/tNt/3gkCKQjvSE8fGxfh6VMUuBOVGOa2fkQyHDIzA6AkT0i5ghltKzDtuWI0BZiO1M+wAB6atRs/GUKO9p4UUUunlaM/H5MFtApimw8qQ/7LhadQpMzwNUqBEgVgWWiQjPJ8V71ikhWqqNfUB6lQCAckFMd8HPlrbkl5qFZ82o1/SC0Js07Rb8/UhzEWDh63GNVagMeBGXjXt48BVsBv6l2iwH1mpN0GV+L68IO9xjfqLdvKed/3/tziOm22qPuQ+P9CLMBtiafG5OnIjFFF0xe4C4CVnnvejlfhFzMSOmfNINHk55/izEdjYXPTcjQCyq1TVg3GcoX/Tyyr7EPjZXMw+QXRO0urfasOQ59kAyBabbCJG9LwUmgOqERriZ9KPKF8V71ikhLEWANCbFhhy57o/wSdbGnWz5PlWpjbrZhNftwlYg6VKC3bwviw9jmxJRrd1H9AUQ9wBlcQLPdAWrNUEDQCNPg5k/ptiV9oO2HtPWANpj7sPDPUrq0uR1OyGA2PNIknm0qdCpNfmstRdL48dQoqdKZMBeBMhuQUSixYZ7AigbDxB7bLPHzxdsEcVEbXPye9lms0ChTzPqgleBdfRDlmVl8atrgo6kTYXbJRsTNIv+y3JhRu2MIAFUAJjNA2NG4jJNGqkhRx4g9vgNFgSQciJIvI5cRoCaeRja/P1QTl4+jK5PCKCPhPk7ItlUgWXbq0mJACmpE6vdoEVR0xeO4aBJaJ4dcyz8/uHhXv66zS5cTqxErTxPMWBWhdWjSZcYUc87qUdSLozpqMuwCkxMQWYyqsZyGXwG33+f18OjYoWWVukJq03QrBdQW6YpsGSEh1WB9YZj6BqIol/n3M/EbjQuZ92CQks2n5dYiVtMpfDFfeYpEczmgbFBqNoIkOJ5cfdgO8ojQIG027JyUFYNEY6lT6U4hbh6MoN1y60K+jCqoQIAsNcgBcb7AGVQBVaT4aqcoTRCVFbCVkvhtV6EnW09htsqnqh6AAnTu5WogCMm6CwqkAoJM7+KEgEy9wDxUQJ9YSE1Ys0EnalfRuyHlckiJZ0PLNsWB3UF6gMSF1GAIoDseoC0w07LA14uZg929vO/i5HAMr+Hf1+cNkJnUxEIKAs0u9Vw+cS1M097ezsWLFiA6upq1NbWYuHChejpMT4RA8CuXbvwuc99Dk1NTaiursall16KQ4cO8b///e9/hyRJuj+bNm0CAOzZs0f37+vXr3frpWaNlQiQdoWmeF5yEwGykgLj5aAsBZZhm/1MOC6ZP9+fRgCpI0AJAfSRQS+gSDzzCBC7oHVm7AFKpsDK7QmggUiMr5hnjGsAoDY6a2Fm60+OrAWQTIHlSACxFGMxl8ADigeoa0A9jysel/mokHQmaFZF0yGmwPxWy+AziwCFhCaqmXxHzczfQHaNEIHsqtvcRCtqWeT7WF/EdLROyuMwoSscG+JCTs8ELUkSrwTL9NxiRCiLvk2AEAmzWQ2XT1y7Mi1YsABbt27F6tWr8fzzz+PVV1/FNddcY7h9b28v5s6dC0mSsGbNGqxduxbhcBgXXHAB4skT5cyZM3Hw4EHVz1e/+lWMHTsW06ZNUz3eSy+9pNpu6tSpbr3UrDEbh6EdhMrgVWBp/CDZwi5wYk7eCDEFJsuyrZlG2cJKSLsHojx9pEeP4AGyGgHKqAqMmaD77efqZVk2jQCZpT2ZAd3nkTBtTKLSbddh44UHe69OSwqgA50DvHLJ7EToiAcoi2GZhYT43RBTguJsrrQRoKSYiMRkvoCwngLLLNoojiEx6/lkhNKbSv94zPbzrc3wdbmNeA4BEgKUCUg7jUp5BEgQOMOEZohGBTC1moazTpFNCgxQzv92zeD5xFqM1Sbbtm3Diy++iE2bNnFh8uCDD+L888/H8uXLMXz48JT7rF27Fnv27MGbb76J6urEuIXHHnsMdXV1WLNmDebMmYNAIICWlhZ+n0gkgj/96U+4/vrrUxrtNTQ0qLYtZFgEqK07hGgsrrrgGkWAGoQIkCzLlhsN2tkWEKdZWxFAidcxEImjayBqWMLvBpVBH2or/Ojoi+BgxwCqW/T3t0dYvbERGh8f60MsLqcYcZlHwswMbARblcfiMrpDUUvvH6M/EuOl6KIHqLEqfQSoW4gcsQGLu9r0PU7RWJxHG0bVV6Ay4EVvOIY9SVO46ymwEugCDST9KkEfukNRHOsL8+OKVYD5PFLa70CZ34tyvxf9kRj2H0tEMS1XgVUon0U8LlsWM9mmPNj3/WhvOOW8BTiRAnOv63E2aLt7S5KE5uogPj7Wj0NdIYyoq7D0OHper+OESrD+iPHi94M25/2f2VSBAUBTtdoDWgy4cuZZt24damtrVVGZOXPmwOPxYMOGDbr3CYVCkCQJwaCSaikrK4PH48Hrr7+ue59Vq1bh6NGjuPrqq1P+duGFF6K5uRmzZs3CqlWr0u5zKBRCV1eX6idXNFYF4fVIiMXllL4+hhGgSmXFaHVi8svbDuGkO/6KSx9aZ2lwXzQW51/CqjSdbIFErpqNBTjcPZD1F8ouSit54zSYmAJrqS5DwOtBJCbr3kcZ5mh/dVzm9/LPzG6omlWA+TySKvxtJQXWLTRQHNOQrHIzMHmLXXaHlPlwXB0zQiciRmapC5aaG4jEbYX9RdixlckYhkJDr0GdeKG0suioFwQ5YN0DxCJAVmbhiSgVppn16WqoDMDrkSDL+v3IshmGCogRoMJOgQGZGaG1fYAAYJiQAtMrgwfEFijOCsNsqsAAwQOag3mFTuHKmae1tRXNzc2q23w+H+rr69Ha2qp7nzPPPBOVlZW4+eab0dfXh97eXtx0002IxWI4ePCg7n1+9atfYd68eRgxYgS/raqqCvfddx+efvpp/PnPf8asWbNw0UUXpRVBS5cuRU1NDf8ZOXKkzVedOV6PhKHJi9vBTvWFeMAgAlTmV8SG1V5AP37pffRHYti4px1Pb96XdvteYZBnuhA+Q2wLH8phI0RAyZ8b+YC0ngyvR8KI+sR99HxA2QyKBJQLk9328GIPIPHCaaUKjImaIWU+jEk2rzzcHeIXY71ty/1e+L0evnI9kEzFmgnXIUEf2K5lGgWy2++mkGGftSh2rRqg+WNUKl4iIP34DEbAZ30Wnki2ESCPR+JpML1Vv/L4mXqACtMErefryqQZYn9E3QcIEDxAnQMYMGiH4NYUgEgyZZnpgnUoP/eXaATolltuMTQhs5/t27dntCNNTU14+umn8dxzz6Gqqgo1NTXo6OjAlClT4NGpwvn444/x17/+FQsXLlTd3tjYiCVLlmD69Ok4/fTTsWzZMlx++eW49957TZ//1ltvRWdnJ//Zty+9QHASpvw/Pqa+eJt1amU+ICtlh539Eby7X4lqrdpyIO19upNekKDPY/lLIa4CclkGDyjhY+17yBA9Geziwo3Q7alREtEjkQlKTtzeCUHx/6gvgOzx2nuNm43xERpBP2rK/TyqoDfyQ1tqPyIZAWKYXRg9HknoBJyhALI58qGQUdoeKN9FJoDsenkYVqKuDH5RtLH6dqJPl7byUySb0QqA8p4e6y2cCFAkFufntUrhc80k+qHX72l4jZIC05sFBqT3XmVKtp7NYowA2Trz3HjjjbjqqqtMtxk3bhxaWlrQ1tamuj0ajaK9vd3UlzN37lzs2rULR44cgc/nQ21tLVpaWjBu3LiUbVesWIGGhgZceOGFafd7+vTpWL16tek2wWBQlX7LNWMbK7H5o2MpFyoWAdIa4YCED2jP0T5LJ71tB9Upvc0fHcNAJKb7uIxumytRQPEzHejsz3pFYZeRSTFj1NlZz5MxuqESwGHs1YkAZRvCT4TFO3HI5glB2wWaUV8ZgCQlfEXH+sK6lXna6MHYxkq094ax52gvPnFcje7zDEn6k7QCKN3rrq8MoKMvgqO9YZxg9cUJ9OlMuy5Wanm0T7lY91msAGMwscqw4xtrrApgZ1v6HlEi2YzBYJg1AczWA1SIAzb7hKi4mKJkke/WDFJglYHUKrBDXQM8+ms0BcDpMUjhLKvA+LHQZc+Xmk9sCaCmpiY0NTWl3W7GjBno6OjA5s2befXVmjVrEI/HMX369LT3b2xs5Pdpa2tLETmyLGPFihW44oor4PenP0ls2bIFw4YNS7tdPmGztnZrBJDZSYqtBKyc9Fgp9OyJzXjr4w4c6QnjvYNdmDKqzvA+PTZD+IByEd3X3s9NjLnq88I8L3rRHEA9l4l9OUc3GJfCMwGXiQkaEPqD6FT3maHXBRpImG3rKwI42hvG4e6QrgDq1oiaMQ36wlr9PCwCpDZvpvvcmqqC+PBwr63KFxHe7yZDD0ohobcq7w1nFwGys/BoSq6+7XwWTnj0moYYG1+zbXTJPW8uN3u1A2uCGPCqo+LMf3iww44ASj0+mocE4ZHYe5d4/7QCqMGlMUhZe4CSIrA/kmjkaKVyON+4cmWaNGkS5s+fj0WLFmHjxo1Yu3YtFi9ejMsuu4xXgO3fvx8TJ07Exo0b+f1WrFiB9evXY9euXfjd736HSy65BDfccAMmTJigevw1a9Zg9+7d+OpXv5ry3I899hieeOIJbN++Hdu3b8cPfvADPProo7j++uvdeKmOMS4pgD40iADpGRUV4136LwLzdYysr8CpI2oBAG/t6zC9Tw+PJlg/kEckozAfH+sTVsC5ucBxMXOkT7f0vHsgVdDx++hEjcJZRoCUBpf2BBDz1OhdANMZobVRu7GNidenN+5DK5ZSUmBpXnejhbJ8M+x2PC5k9Cr0lEZ31oRMQ6VWANmLAAH2ogLOpMDSR4AyGYYqPrbdFLKb9LG0puaclsl3XZn2rjyWz+vhsyEZqR4gdwZhZyuIKwI+nrZM15C2UHAt+b5y5UosXrwYs2fPhsfjwcUXX4wHHniA/z0SiWDHjh3o61NOzDt27MCtt96K9vZ2jBkzBrfddhtuuOGGlMf+1a9+hZkzZ2LixIm6z33XXXfho48+gs/nw8SJE/HUU0/h85//vPMv0kHYXKoPD/eowodmESAmgKx86ViPoZaaMtRVBLBmexve/rjT9D7dWUSAPj7Wz7/IVlMA2TKyvgKSlNjv9t5wyvgOZTClsj+jkuMw9h7tTQnbZhsSzrRDLAv512kuiEBCAG1v7TYRQGr/0BgeWUztBaQVS5lEgAB7UQcRXuVSAgJIT5j22hR4QzUXPnsRIPufhRMevSaT6qesUyrJx+4Lx9ATito6D7lFr07aClBXoFpN/7DFrfb4GFZbzhesAFCm+XwahWIIJ1NNThwPI+rK0dEXwf5j/Zg0rNqR/XIT146o+vp6PP7444Z/HzNmTMoqfdmyZVi2bFnaxzZ73CuvvBJXXnml9R0tEMY0VEKSEh4O8eJt1kvHzgWWVZcNqynj3pK3P+4wvQ+7mNoxY45MXkT3H+vHhKFDEvfP0YmrzO/FsOoyHOgcwEftfSkCiKXAxNczsr4ckpQ4sR3uCXEjHyB2ss2uKsKuAGLdvRt1BBDbPyPR262J2rG04B6dFJ/Wa1RX4ee9aID0K0ErjRnN0I4CKGb0BEifxTlgjKE1yrFX5vfYEg6ZVAaFHajSHFlnXEWZ7fenKujjvanaugZQ1VSV8X46Ra/BZzq0RjlfH+uLpPi59DBaAAyvLcfmj44BSBRgaPsrsc86HI3b7jFmhhN9uY6rLce7+7t4K4dCp/gbcJQIZX4vH0i5o1UZXWDUDRSwd4Fl3TmHVpdxYfLR0T5+0OvBU2A2BMywmjJ4PRLCsTj2JPvPWE0BOMEo7ulJ9bz06ESAgj4vrwT74JA6ShLOMoTPImB6Hb7NYP099AbQjkruq55pG0iN6rAIUHtvOKVcXbutJEmqNFhaAZRlBMjuyIdCRq9FQV/EXgqMfZ8BoKHSXkFGUwYCyIlGpccnRclHR/tSKhO5ByibFBsfr1AYPiClsk/9mQZ9Xi5MrKZ/eApMI0CHi0JYR5yWB7z8HJbpd09LPC7z5qvZpESPq00ugIskBUYCqIBg85iY+gesRoDSfwlY2/SGygBaqstQEfAiGpcNx0AAignaTije5/XwSrDtSSFXlSMPECAYoXUEgtHqbUJLQhBuF4QnoAzrzDgFlnwfugai/GRnBUUApa4iRzUkBIrR59atiepUBX08OqE1QuuN21AJoDSvu3FIZl6Ej4724uoVG/Hb9R8BUDeCK1aadFoU9Nksgx9Wrbz3ViIIes9vLwWW/bDi4bXlCPg8CMfivIM1I9sIEKC8rkLxATHRrhfVNpvpqEWWZT7ouiygfn9YJRgA1FbqR3eGCeXyTiAOxs3meGDnDxJAhG2mjU5UZL0hCKAB3i3X2ATd2R/h2+kRjyuzpWoq/PB4JF519uFh/YopQDAN2xBAgCJCGLnyAAGsrN1AACWrLrT5exYRe18rgGLZrYiGBH38RGknJHyEpcDMIkCGAihVtLLPeo8mKqaMOUntRAuoT8R6WBnNocdP1+zEKzsO89/tHl+FiLZFASCavK29PtZNGrBvnGfngiM9IdOorgi76GVa5QgkmriOSUZdP9T4zJxIqbDX5VSkI1t6TEQtEyWtnekv/qFoHMwBoo2ADhMiQEZDqI8TvJZOIAqgbIYTO71fbkMCqICYOroeAPCvvccQT64iWQRIa4QDEhcuNm7BbIXUHYqCRadZaSILXZsNylSqpuzlmCcmIyqMXKbAWFWX9mIPKD08tIJsQkvCrLddmJouDnPN9AQuSZJhewMzjjETdEVqFID1OjrY2a87zkTrAQKAsUlRuEsjdrt1PFHiGKl0Akj0AMUNGjPq8coOdY+wE5vz7+3IFn+yRQGgXKwzqXK7dFqiq/2359jrrNRQGUDA50Fcth4t4XMGsxxFMq4x8flpF1OKCTrzC6pZlVk+YKXrehEgsYtzOsQFq9beIH7vmowEEOt675QAEs4l2UTsnN4vtyEBVEBMGjYElQEvugeieC/ZuDBkUgYvSZKlNBiL/pT7vXykBhdAbcYCSM80bIWJGvd/Lqs3mADS88gY9WWZ0JJ4Lz441M0v5Cz6A2S3grUrgOJxmXt16ipShWdTVRBl/sSFTi/83TWQWkLPUnzaZpiKx0t5HjaNGkDKcFgtzKcSjcuWZ1B19kVSUmYnDS/8ahEraCNidvsAAcD/XHQKnv7aDHzx9FG2ntvjkYQuwtYEULZ9XxisglW7mMq2DxCg+KKspJVyAfMRasvgAaUU/qCF9A8zQPs8Usr7o21HoQer2HQq1SSORcmmqox5MI/2hnk6vpAhAVRA+LweTB/XAAB4fecRAFDyxAZpGCul8B3JUQViY6rjm/VPWiLcA2RTwEwZVav6PVd9gAAlBXa0N8zFAMMoAjSmoRIBrwd94RgP3YpphGxMolZSjSJitE7bCRpIiF6jNFg8Lut+ZkxgvHdALYC6dTxeV80cg8+eMgwPfnFy2n0N+Dw8CmTVi8Aicw2VAVwydQSu/7fxtvrdFDK8G3DyYm03BQYk3tPTx9RbnuguMlwYpGkFs/S6HSYaCOxsRysASlWpmVcxl/DKPp3PVOmCbyUCpD/mAlC6igMwbCbIUk1OR4CyidYBCT8h61O0R6f3WKFBAqjAmDU+0QX79Q8SAsgsAgRYm0LMIgq1QkRBSYH16jYNBNST0+3ALvoMbWMvN6kK+vgXUBsFMlqR+7weHJ9Mw+xIpsHEkHA2K9hxTfYiQGyuVpnfYzimhF0U9ml8RX2RGPcViKKC9ePY39GvmtvVo+Pxqgz68LMFU3DBacMt7W+6AbRaWMPJ45uqcO8lp+HGuRPS3KN4YKvyj5PvBe/0m6MFgN3PwmzMjh1OHp4YsfLewS5Ek6InFpe5GTyb7w9b0OzVSWnnA71BqAz2/lup+uxPMwbm+etn4d9PHYYlc0/U/ftxfHakMyIj4oBYZfBFn07vsUKDBFCBcdYJCQG0cU87BiKxtPN6WjSrTj3YgEYxojC2MdF3qLM/YjhMtYdXTdkTQJIk4YwxCT9TwOdJ6WPhNuykqRUderN3GGwV+35SALETgkdKnwoyY6xBh28juFgtN64CGmkQAWJVbh4J3BsGJFaRLKz+nrBK79ZJgdmFDaC1GnVgc+uaq/W9DcXMCM2q3Ox4cwP7Aoi12MjWA1SJyoAXA5E4P84jDplqWUrlWF8kpY1Drvj533fi+ifeRGvngOmAW/b+H+zsNxxWzOA9gAzE5yeOq8FPvzRFlZIWYf2XWrsGLJvezeATB7LoCcXgRRcUASLsMr65Ci3VZQhH49i0pz3tPC7uATIxCSoXVeVCV+b38hP2TgMfkF7nZKvc/8VPYt7JQ/HY1WfYvm+2sLEi2vRer0EbewA4cai6FD6UZQk835dkpO1IT8jSUEcmVmt1/D+MUQZDX8VRH9o8/knJKNDWA4nu39FYnJ+Es6nCEjvgWqFDJxpZKihd0BOfC0u55qrRo10xyj5/vV4zdvB4JJ5mfXd/4vhSVxVl/h0yi+jmgvcPdeOeF3fgubcO4HvPvmtqgm6pLkPA50EkJqdNTQ2kEUDpaKwKIuBNeAHt9hnTw8lopVn3+UKDBFCBIUkSPpVMg736/mGuzI168TABZGa80/MAAekrwXpsdrIVGVZTjl9+eRpmHN9g+77ZcsLQxOvSCjtLEaCkABpwaExDVdDHV0Ts4mCG0WclwivdjuhHgPROzmKaIrGtUoWSjUld8Z1YOwl39BlXuBU7x2kiMJmYoLNheK29EmSnUmCAcny9uz9xfA0kv2uSlJ2HDhBaWxgMOXaTl7cpFYtrth/ix3mFznfG65GUiss0F39lDlhm743HI2F4UvA6YYR2ci7fuAwqX/MFCaACZPrYRPpozXbly2d0kWLRAL1hngw9DxAAjG/SFwpAogy812S1U8iMbzYSQInXoydqTkwKoF2HexCOxg1n/mTCyWx1fMCCALIQIREry0T/Fo8W6ohlrRGalcAHfZ6sG+EB1k/Cx/rY6ys9AcQ8QK2dA4kIWwYm6Gxg/bf2tqd2ZdaDpdfLA9lfBk45jgmgxDHOoksVfm/Ws6pYp3a93l5uI6aM47Lyu1FzV/7dTFP0wItbshCfTvbc4QLIn/2xOpa1RThi7C8tFEgAFSCnJwUQ69tSEfAa+mjYSe9wd4hf4LV0GkQVmFDQ9ocBEl8IduzmspGhE4xvSoiZD4/0qi4EZhGg4TVlGBL0IRqXsftIr2HX6Ez4RPLisHV/V5otgc5khMQsAjSyvgI+j4T+SExV/WeWLv3EcQkB9EFbD/qTwyUBe12+9dBGPdKhRIBKLwXWPCQIv1dCNC7j42P9fLRALk3QAZ8H4WjcUhpswKEUGCAc4wc6EYvLjg66ZYUERql6N9nRmvjOHqfpidVUpV/YwfY1nQGYieNs3p8RybETThihnUyBjW5IDqVOzrUsZEgAFSBjGipUHUDNIjA1FX4eLTBaITFfSY1m1c0qn/R6ATEBIEnFN6zyuLpylPkTFwLRJ2PmAZIkiUeBtrd2CQIoe/H3iWR64B0bKTCzCInf6+GRP7G8nlV16e1zS3UZGquCiMVlvHewM+MKPy3M93K4O2Rp3AfrklyKHiCPR+IXyu2titityNGsM69H4tESK+mHfpM5g3YZ31yFqqAPveEYtrd28cWGE489MdmoVFtmnwuYv+aSZINKxlADE7/Vvl/ZeoAARWzpLWDtwiN2Dpzry/xe7g20WvyRL0gAFSCSJOGMsXX893SrdGX8g/7BxlJgKRGgZApsf0c/v+AzeoR+F9mGsHON1yPx7rQfJMWdLMtpq3KYEfr9Q92GYzMygaXA9rb3qcrQ9TD6rLToVZeZRXUkScJpIxJC7O2POzMec6KltsLP99WKR8OKwCtmxjcnjqE393YAyH0VpJ3GmwMOdYIGEt+5ycn+X5s/OsY9QE5cUCcOU6enc8VAJIau5Pfk309Vt4XQG1QMKIvKHa3dpukfJ8Qni+B/IHSwt8qx3jAufWgdpv/gJWz+6Bj3BJY7kAIDlPdBO2C60CABVKBMS47FAJC2URxb9e0xiAB19Se+xNqLal1lAA3JoYvaE2YvbxpYXNEfhtYIHY7F06YkmBF6R2s3f/1OnMDrKgM8UrI1jQ/IapUUD7ULBvYekyZtAHCKKIB4w8TsIjGSJPGqD+2wVT2YACpFEzSgdBXfuKcdgP0motky1kbfKSeiECLsnPXGnmNpy7ztcFxtOYaU+RCJyaaNW53mSE+isjbg9eD4pkr4hHYYRq0xThpWjYDXgyM9YVPPkhMG9BOa9VP9Vnj4tQ+xcU87DnWF8M0n3uRZAqei/ZOSojXd+S7fkAAqUM4YKwog85MoG0ZoFAFiHZGrdR7neAMjdKY9gAoFFt36oC2xOuoTqp6MUhLMKPzm3g7TiqpMOG1ELQD1oFs9jPxaWtjnJq6wzEzQ4j68/XGHbhPETBnLh2GaX3TD0Tjfx1L0AAHKXDkWATIaZukWRi0g9BhwMAUGANPGJKLWmz865mgKTJIkTMpDGoyNNGkaEoQkSbhp3gR4PRIWnTXW8D5lfi9OTS40mAjWwwmBaJTqt8IrQoHN/o5+/GHzxwCc86tpq04LFRJABcokYZ6WtrOyFjHsqgebBaY3WoGHKtvU93VaAOQaNv+KVT2xlFbQJCVx6ogalPk9ONobxuakUHHqhHBmsh3AP3cdMd3OagqMnWC2HujkofZ0nxmLAH14pJdPrHYiQmE1AsRWmZKUPqpZrGgHAddX5jbSdcJQJYqZDifL4AHgkyNr4fVI2N/RzyNQTpigAWVx8vbHuYsosJl1jclxL18753i8/z+fwW2fPcn0ftOSTWA37TYRQNwEnfklWC/Vb4XugQjveH/FjNEAlNfqRBUYoPQd236w23Z0KpeQACpQvB4J1513PE5orsLi88abbsvE0vbW7pSp3PG4zNMd1ToXHSVUqVbqTnpg8sFpI2sBJPw8feGo4v8xueAHfV6cdUITAOBv7x1Ku70dPpUUQP/6qEM1CVoLi9alE0AntlTB55FwrC/CZw+lMzY3VgVxXG05ZBlYu+toYlsnIkAWO7+K0a1sumsXMmMbK1XDRRuqciuAmI+trdu88aYsy46mqYDEd4Vd+F7ZkYgwOJVSYf6iN/d1OPJ4VuARIOEztHLcnjkuIYD+/v5hw4u/UxV4Rj3PzNhzpA+ynIhsXXfeeNVrcqo4YWxjJcr8HvRHYgXdEJEEUAHznXkTsXrJOWhOM0trXGMlAr7EME/teISecFSYD6VXHq3079DrKVOsKbCh1WUYWh1EXE40ZzNrYS/ypTPUU7ibHEphjG2sxLCaMoRjcaz78KjhdjxalyZCEvR5+cWO9V6x8plNHa2kKQBnInzjeN8P8xPdsRL3/wCJCj2WAgFynwKrCvowsj61Ek1LfyTGL87ZtkIQOefExAKCpQCdii5NGZU4bt870Gm6gHASMQVmh5nHN6Kuwo/D3SE8//aBlEUpAMfaBGhT/VY4kIz+Dq8tx9DqMsye2Mz/xs4p2eL1SPhkchHK5loWIiSASgCf14MTkysBbY6cXVCDPv3hmicNq4bXI+FITxiHupRxGko6pThN0IDa89JvsbHhuROa+Dw2AJg8qs5ka+tIkoQ5k4YCAF54+6DuNtGY0oBRL12phfX2eedjtQAyu6CdLnjLrD5POsY3V0GSEmF0ZhzVo5RL4EVYFBFQOrXnkglDE8eFWRqMVQF6HG5zMeekoarfnXrsEXXlaKwKIBKTc2asPdyTiKzaXQQFfB5cOXMMAOBbT27Bid/7CxY8sh5bhOiVU/6rTCJAbGrA8OT0+svOGMn/pk3hZsN5ExLC6pUdhx17TKchAVQiMJOg1nTGKsCMLnRlfi9fRYh9anpC6VNGhc4nk2HzjbuVmWrpVlySJOEHnzsFjVVBDKsp4yLDCT576jAAwF+3tuqW87KLEmBtVc5Wxa/vTKywrPi2Th+jFnTDarK/QJcHvLwhp9lFlzVBrHVAdBUy/zHlOP7/f09+5rmEpbXNDMPdyVSr3ty4bDj1uBpVjxzWHTtbJEnix/v6D429NU6SaQQISPiF/i0ZWYnGZazdeRRf+OU6oVN24vufbfqReQG3Heyy1IcLAA4mU+Zs0Oq5Jzbjy2eOxuLzxqPOQc/aecnXv+7DoyltVgoFEkAlwqnJcOO/9qqrjMwqwPh9kyF78b7FboIGgE8dn4jkrNt1FG3Jk5kVU+rI+gr8/Tvn4qUl5zgyHZlx+ph6NA8Jomsgitc+SF0VMQN0ZcBraYDkuckV1lsfd+BIT4h7vcxE64nNQ1TiipXnZ8sEzTBZPUq9BJ4xsr4Cj391Oh5fNB0j650RAHZgF0UzwzDrb+O0Gd3jkXCB0DOHVSs6AYvM6n133CAbAVTm9+LRq07Hm7d/Gi8tOQdnndCIUDSO/35uKwBFgGbbZmREXTlaqssQicl4c595hSmDeQbZLDGPR8JdF30CN82bkNW+aDmhuQpjGysRjsbxzJv7HX1spyABVCKwlf2bezsQFSYxm1WA8fsm0yIbBG+Kk52Q88UnjqtBXYUf3aEoXt6WMDU3WFzhVAV9jr92r0fC+ackIgLP66TBuFi1GCFpSUaoZDkxN67bQndnj0dSpfWG1zokgFgXbZOoQynPAdMyc3wjZh7fmH5DF2CG4fcPdRuuvHsG0qdLM+XLycoiQBHGTsBSi4kye/cjCod7MhdAjLrKAMY3V2H5JafB75Wwac8xvLWvgxcEZPtdSDTNZVVn1gQQS4GxCJBbSJKEy89MHAuP/XNPQc4FIwFUIrCVfV84hm0HlVU4W+mZmWpnjEtUKL39cSc/sRS7CRpICI5PjU9chFgeujGLk5kTXHBaQgCtfu9QipmTpyttrMrnndQCAPj9pn04mjxhNxu06WfMTfo0hteUoXmIMx4VlnYx6/tRynPAComh1WUYXlOGuGwcBeq2cF7IlNENlfj11afjx184DaManIuAjW6owMj6ckRiMja4nAaTZRlHupNl8A4Y2YdWl/Fu0o+t28P9cE5EQ5kAen2ntcgYT4HVuu9Pu2TaCFQEvPigrQf/3GVc/JEvSACVCB6PxCt8NgkNuKxEgEbUlWN4TRmicRmb9iRWER0WG/IVOikt7HPcl0XL5JF1GF5Thp5QFH/XmAOVCJB10fn5aSPgkRINFuNyQvQ1VJqfsL90xii88M2z8Jdvn+1YOTprO7DtYBcXz1oGiwm6EGD+N21KnMFSMG5EgIBEevZzk0ek39AGkiTxKNA/3refBjvY2Y//ef49rE62uDCjNxzjlVpOVfKxaMgL7xwUoqHZfxdmT2qGJAGb9hzDXpPu0wAQi8t8gPJwlyNAQEJgf35q4jj49T/3uP58diEBVEKcnmzA9cZHggCy4AESTyyr32sFoLSBb8xxHxOnmT2pWfUacl2WrMXjkbgZ+vm3D6j+ZrUEXmRYTTk3WwKJieTpRI3HI+Gk4dWOitthNeU4rrYccRnYkiyB1jKYUmD5hp0L1u7UL0E+VqQLHFZm/9K2Q7ZSKrIs4yu/fgOPvL4bi37zBp5764Dp9sz/UxnwOhYFnzKqFmMbK3kDSsCZ939YTTlmJSPd//evj023PdwdQiwuw+eRskrt2eGKGWMAAC9vO2S7Y7XbkAAqIaYlI0Abd7fz3hNGc8C0fOaURCrlxXcPIRaXlS6oeRYM2eL3enDxVGUlyvwR+YRFpV7e1qbyMlhtgqjlstOV3kX5NBizCKQowEU6B4kJuhBgBvlNe9p1I3Jt3ckS7zTp0kLjnBObUBHw4uNj/aqq1XT8a+8xVVXcbc+8g0PJSIge2RigjZAkCRcLFYLlfq9jfZIumZYoZX98w17TPkmsB9DQ6rKcNSMd31yFs05oRFwGfvnqrpw8p1VIAJUQnxxVi6qgD0d6wnjr4w4A1o21M49vRHWZD0d6Qvj7jja09yb9JHn2zDjBN84Zj1njG/Gt2SdgdIP5WJFccOqIGoyqr0B/JIZXtiuh/HQtC4w4d0ITLz2edUJ+jLeAYqY3anxGKbDcMbaxEqMbKhCJybpRIHaBd8oDlivK/F5eXv3CO62W78dK5+ef3IJTR9SgayCKL/9qA375j13YqdNE0A0BBACfm6IsxpwcEfGZT7RgWE0ZjvSEsGqLcXTrYAcrgc/t535dcprBU5v2YX/ShF0IkAAqIYI+L86ZwFJZiTw3M8am670S8HnwhdMTq4g7n9uKuJyY2ZTrWUZuUFPhx+++Oh03fPrEfO8KgMRKkKXBxFC8lXSlHj6vBz9fMAXfmTcBS/L4Gj89aSikpB/pgOYkJ8sy95WRAMoNrPHm02+kpkXaXLrA54LzP5H47rzwzkHLaTAW/Zk8qhY/uvQ0DCnz4f1DPVj6l+2Y95PX8GdNVeZhFiFz+P05rrYc45oSi7DPT3POI+X3evCVTyWGtD782oeG4upgMgLUkmMBdOa4BswY14BITMb9L72f0+c2gwRQifHp5EnvubcPIBaXBcd/esPborPHIejzYF974ksytqHScHAokR2sV8rL2w/xdIQVw7oRU0fX47rzxjsWUs+ElpoynD46EQX6k2YV2heOIZxsz0ApsNzwxeRYlzXbU70XSgSo+ATQeRObUO73Ym97HzaaDBwVYQJo4rBqjG8egr/dcDZuO38Szhhbj1hcxnf+7y3sOqx0Uz7MPZDOvz+/vuoMfGv2Cfju+ZMcfdzLzhiJ6jIfdrb14KlN+3S3OdDBegC5b4DWcuPcxOLs9298jL/vaEuzdW6gq1uJMe/kFtRV+LGvvR8vvtvKV+JWQp7NQ8pw62cm8t+1be0J5zhpeDWmjq5DJCZj5fq9AICjyeGVxWZMFbl4asLj8NA/dqmGcXYkxV3A63F09AJhjOi9uOnpt3g0OByNc0GUj0aN2VIR8OH/fTKxgFi5YW/a7QciMT6dflKyX9WwmnIsOnscnlh0JmaMa0BfOIabnn6LR05YCbxTswBFRjVU4IZPn+h4k9khZX4e5V76l2264zFYBCjXKTAAmDamHl9OVsJ9Y+W/sN5kJmKuIAFUYpQHvPhy0nV/+5/e5X2ArB7wV31qLH7zlTPwn/Mn8Lwt4Q5XJecFrVi7Gx19YR6ty8fqzCkunjICE1uGoLM/gm8+8SZC0YQh80gy4lBX6Xd09AJhzh3/fhIqAl5s2N2OT/1wDb75xJv4zbo9iMZlVAV9fB5UscFKyv/y7kHT+XNAoiFkXE60wNCmtLweCfddehqGBH14c28HfvX6hwCAjzsSAjHXqaJsufzM0Zg2ug7dA1F88X/X401NG4QDmjEYuea2z07CWSc0oi8cw9UrNmFVmmo8tyEBVIJ89ayxGFVfwVfgTUOCtlren31iE75x7viijkQUA+efMgwThg5B10AUP3npA6FDa3GddEV8Xg+WX3IaKgJevL7zCG78fWJVzYyPxxWxuCtGThg6BCu/Oh2fOK4aA5E4Vr11AP/z520AgBOHVhWtGP3EcTU4bWQtIjEZK9buNt12e7Ix7MRhQ3Rf7/Dacnzv3xPpqOV/ex8723qw+3AiYsT8OsWC3+vBL788FROGDsHh7hC+8Mv1eGKjEiXjg1Bz0ARRjzK/F/97xTScc2IT+iMxfPOJN/GzV3bmZV8AEkAlSXWZHz9fMIULmC9MG5nmHkQ+8Hok3PbZxIn31//cwyfBF3MECEhcnH755anweyU8//ZB/PdzW/HxscSK2qnhmIR1Jo+qw3OLZ+HZ6z6FK2eMRmUyBXl10jRbrHzj3OMBAL96fTdP7ejBupOzgdF6XDptJM46oRHhaBzXP/Emj5SMbXRullmuaKgK4v++PgNzTxqKcCyOW//4Du55cTs6+yLc/D66Pn/CrszvxSNXTsO3Zp+A6jIfLjxtePo7uYQkF+KAjgKgq6sLNTU16OzsRHW1cxPBc8mRnhC27O3AOROaLA3XJPLDzf/3Np56I2FabKkuw/rvzs7zHjnDqrcO4FtPvgnxDPP1c4/HzfMnGt+JcJ1jvWG0dYf4/LZiRZZlfP6hddj80THMPL4Bj33lDN3z3GUPr8P6D9ux/JLTeFdiPfZ39GPej1/lfZOG15Rh7S3/VrRRMlmW8cDLO/HjZNXVcbXl2N/Rj+Nqy7H2ln/L894l6OyPuJJpsHr9pqtiCdNYFcSck4aS+Clw/vv/nYyzkx1urzl7XJ73xjkuPG04fvgfp8InNFz7ZHJkBpE/6ioDRS9+gEQ7iXs+fyrK/V78c9dRXL1iU0q1myzLfDbixDSv+bjacjz4pcncpL/wrHFFK36AxPvzrTkn4IcXnwKvR+Jp6NNG1uR5zxTybbOgCJABpRABIoqHWFzG+4e6MbFF36dQzPxz5xHc/qd3Mby2HL+++oycdaAlBgev7GjDN373L/RHYgj6Ep3fr545BicMHYIDHf2YuWwNvB4J731/HoK+9BWInX0RHOoewAnNxeuR0vLq+4dx53Nbcaw3jCevmVESAtiMvEeA7r77bsycORMVFRWora21dB9ZlnHHHXdg2LBhKC8vx5w5c/DBBx+otmlvb8eCBQtQXV2N2tpaLFy4ED096nK/t99+G2eddRbKysowcuRI3HPPPU69LIJwBa9HwqRh1SVzwhWZOb4RL994Ln67cDqJH8JxzpvQjFWLP4Uzx9UjFI3j8Q178ekfv4rLH9mA//y/twEAk4YNsSR+gETj1BOHltZC5OwTm7DmxnOx6bY5JS9+7OCaAAqHw7jkkkvw9a9/3fJ97rnnHjzwwAN46KGHsGHDBlRWVmLevHkYGFBmtixYsABbt27F6tWr8fzzz+PVV1/FNddcw//e1dWFuXPnYvTo0di8eTPuvfde3HnnnXj44YcdfX0EQRBEYXDC0CF4YtGZeGLRmZh38lB4JOD1nUfwenIMCOuKPdihxrYaZJdZsWKFXFNTk3a7eDwut7S0yPfeey+/raOjQw4Gg/ITTzwhy7Isv/feezIAedOmTXybv/zlL7IkSfL+/ftlWZbln//853JdXZ0cCoX4NjfffLM8YcIEW/vd2dkpA5A7Oztt3Y8gCILIL3uP9sr3vLhNPvfeV+TLfrlO7ugL53uXiBxi9fpdMHJw9+7daG1txZw5c/htNTU1mD59OtatWwcAWLduHWprazFt2jS+zZw5c+DxeLBhwwa+zdlnn41AQGm3P2/ePOzYsQPHjqmbQomEQiF0dXWpfgiCIIjiY2R9Bb4zbyJeuelcPHHNmXk32xKFScEIoNbWxGTfoUPVocqhQ4fyv7W2tqK5uVn1d5/Ph/r6etU2eo8hPoceS5cuRU1NDf8ZOZJ65xAEQRBEqWJLAN1yyy2QJMn0Z/v27W7tq6vceuut6Ozs5D/79ukPkyMIgiAIovixNY3txhtvxFVXXWW6zbhxmfUxaWlpAQAcOnQIw4YN47cfOnQIn/zkJ/k2bW3qKbLRaBTt7e38/i0tLTh06JBqG/Y720aPYDCIYLD4JiMTBEEQBGEfWwKoqakJTU1NruzI2LFj0dLSgpdffpkLnq6uLmzYsIFXks2YMQMdHR3YvHkzpk6dCgBYs2YN4vE4pk+fzre57bbbEIlE4Pcn8r6rV6/GhAkTUFdX58q+EwRBEARRXLjmAdq7dy+2bNmCvXv3IhaLYcuWLdiyZYuqZ8/EiRPxzDPPAEh0rfz2t7+N//mf/8GqVavwzjvv4IorrsDw4cNx0UUXAQAmTZqE+fPnY9GiRdi4cSPWrl2LxYsX47LLLsPw4Yl5Il/60pcQCASwcOFCbN26FU899RTuv/9+LFmyxK2XShAEQRBEkWErAmSHO+64A4899hj/ffLkyQCAV155Beeeey4AYMeOHejs7OTb/Od//id6e3txzTXXoKOjA7NmzcKLL76IsjJlcu3KlSuxePFizJ49Gx6PBxdffDEeeOAB/veamhr87W9/w3XXXYepU6eisbERd9xxh6pXEEEQBEEQgxsahWEAjcIgCIIgiOIj76MwCIIgCIIgChUSQARBEARBDDpIABEEQRAEMeggAUQQBEEQxKCDBBBBEARBEIMOEkAEQRAEQQw6SAARBEEQBDHocK0RYrHD2iN1dXXleU8IgiAIgrAKu26na3NIAsiA7u5uAMDIkSPzvCcEQRAEQdilu7sbNTU1hn+nTtAGxONxHDhwAEOGDIEkSY49bldXF0aOHIl9+/ZRh2mXofc6N9D7nBvofc4N9D7nDrfea1mW0d3djeHDh8PjMXb6UATIAI/HgxEjRrj2+NXV1fTlyhH0XucGep9zA73PuYHe59zhxnttFvlhkAmaIAiCIIhBBwkggiAIgiAGHSSAckwwGMR//dd/IRgM5ntXSh56r3MDvc+5gd7n3EDvc+7I93tNJmiCIAiCIAYdFAEiCIIgCGLQQQKIIAiCIIhBBwkggiAIgiAGHSSACIIgCIIYdJAAyjE/+9nPMGbMGJSVlWH69OnYuHFjvnepqFi6dClOP/10DBkyBM3NzbjooouwY8cO1TYDAwO47rrr0NDQgKqqKlx88cU4dOiQapu9e/fis5/9LCoqKtDc3IzvfOc7iEajuXwpRcOyZcsgSRK+/e1v89voPXaO/fv34/LLL0dDQwPKy8txyimn4I033uB/l2UZd9xxB4YNG4by8nLMmTMHH3zwgeox2tvbsWDBAlRXV6O2thYLFy5ET09Prl9KwRKLxXD77bdj7NixKC8vx/HHH4+77rpLNSuK3ufMePXVV3HBBRdg+PDhkCQJzz77rOrvTr2vb7/9Ns466yyUlZVh5MiRuOeee7LfeZnIGU8++aQcCATkRx99VN66dau8aNEiuba2Vj506FC+d61omDdvnrxixQr53Xfflbds2SKff/758qhRo+Senh6+zde+9jV55MiR8ssvvyy/8cYb8plnninPnDmT/z0ajcqf+MQn5Dlz5shvvvmm/MILL8iNjY3yrbfemo+XVNBs3LhRHjNmjHzqqafK3/rWt/jt9B47Q3t7uzx69Gj5qquukjds2CB/+OGH8l//+ld5586dfJtly5bJNTU18rPPPiu/9dZb8oUXXiiPHTtW7u/v59vMnz9fPu200+T169fLr732mjx+/Hj5i1/8Yj5eUkFy9913yw0NDfLzzz8v7969W3766aflqqoq+f777+fb0PucGS+88IJ82223yX/84x9lAPIzzzyj+rsT72tnZ6c8dOhQecGCBfK7774rP/HEE3J5ebn8y1/+Mqt9JwGUQ8444wz5uuuu47/HYjF5+PDh8tKlS/O4V8VNW1ubDED+xz/+IcuyLHd0dMh+v19++umn+Tbbtm2TAcjr1q2TZTnxhfV4PHJrayvf5he/+IVcXV0th0Kh3L6AAqa7u1s+4YQT5NWrV8vnnHMOF0D0HjvHzTffLM+aNcvw7/F4XG5paZHvvfdefltHR4ccDAblJ554QpZlWX7vvfdkAPKmTZv4Nn/5y19kSZLk/fv3u7fzRcRnP/tZ+Stf+Yrqtv/4j/+QFyxYIMsyvc9OoRVATr2vP//5z+W6ujrVuePmm2+WJ0yYkNX+UgosR4TDYWzevBlz5szht3k8HsyZMwfr1q3L454VN52dnQCA+vp6AMDmzZsRiURU7/PEiRMxatQo/j6vW7cOp5xyCoYOHcq3mTdvHrq6urB169Yc7n1hc9111+Gzn/2s6r0E6D12klWrVmHatGm45JJL0NzcjMmTJ+N///d/+d93796N1tZW1XtdU1OD6dOnq97r2tpaTJs2jW8zZ84ceDwebNiwIXcvpoCZOXMmXn75Zbz//vsAgLfeeguvv/46PvOZzwCg99ktnHpf161bh7PPPhuBQIBvM2/ePOzYsQPHjh3LeP9oGGqOOHLkCGKxmOqCAABDhw7F9u3b87RXxU08Hse3v/1tfOpTn8InPvEJAEBraysCgQBqa2tV2w4dOhStra18G73Pgf2NAJ588kn861//wqZNm1L+Ru+xc3z44Yf4xS9+gSVLluC73/0uNm3ahG9+85sIBAK48sor+Xul916K73Vzc7Pq7z6fD/X19fReJ7nlllvQ1dWFiRMnwuv1IhaL4e6778aCBQsAgN5nl3DqfW1tbcXYsWNTHoP9ra6uLqP9IwFEFC3XXXcd3n33Xbz++uv53pWSYt++ffjWt76F1atXo6ysLN+7U9LE43FMmzYNP/jBDwAAkydPxrvvvouHHnoIV155ZZ73rnT4/e9/j5UrV+Lxxx/HySefjC1btuDb3/42hg8fTu/zIIZSYDmisbERXq83pVLm0KFDaGlpydNeFS+LFy/G888/j1deeQUjRozgt7e0tCAcDqOjo0O1vfg+t7S06H4O7G+Dnc2bN6OtrQ1TpkyBz+eDz+fDP/7xDzzwwAPw+XwYOnQovccOMWzYMJx00kmq2yZNmoS9e/cCUN4rs/NGS0sL2traVH+PRqNob2+n9zrJd77zHdxyyy247LLLcMopp+DLX/4ybrjhBixduhQAvc9u4dT76tb5hARQjggEApg6dSpefvllfls8HsfLL7+MGTNm5HHPigtZlrF48WI888wzWLNmTUpYdOrUqfD7/ar3eceOHdi7dy9/n2fMmIF33nlH9aVbvXo1qqurUy5Gg5HZs2fjnXfewZYtW/jPtGnTsGDBAv5/eo+d4VOf+lRKG4f3338fo0ePBgCMHTsWLS0tqve6q6sLGzZsUL3XHR0d2Lx5M99mzZo1iMfjmD59eg5eReHT19cHj0d9ufN6vYjH4wDofXYLp97XGTNm4NVXX0UkEuHbrF69GhMm/P/27hgkuTYM4/jzYnjqEGmgGAgiQbwRLi2B0BAEgVM0NoS1RLUUFC3REgROLW0tFRQ4BdHSVA0NGYEVEURD1uJSUAk1RF7v9El+xDv0heeL5/+Ds3hu5D73IBd67uPvL//8ZYxhDb6WstmsHMfR2tqaLi8vNTo6qmAwWLUpg78bHx9XIBDQwcGBisVi5Xh5eanUjI2NKRaLaW9vTycnJ0omk0omk5Xz/6xo9/X16fT0VLu7uwqHw6xo/8XHLTCJGX+X4+Nj1dXVaXFxUdfX19rc3JTrutrY2KjUZDIZBYNBbW9v6/z8XP39/Z+uEXd2diqXy+nw8FBtbW3Wr2d/lE6nFY1GK2vwW1tbCoVCmp2drdQw568plUrK5/PK5/MyxmhpaUn5fF63t7eSvmeuj4+PikQiGhoa0sXFhbLZrFzXZQ3+p1leXlYsFpPf71dXV5eOjo68bulHMcZ8eqyurlZqXl9fNTExoebmZrmuq4GBARWLxar3KRQKSqVSamhoUCgU0vT0tN7e3mp8NT/HvwMQM/4+Ozs7SiQSchxH7e3tWllZqTpfLpc1Pz+vSCQix3HU29urq6urqpqHhwcNDg6qsbFRTU1NGhkZUalUquVl/K89Pz9rcnJSsVhM9fX1am1t1dzcXNVaNXP+mv39/U8/k9PptKTvm+vZ2Zm6u7vlOI6i0agymcx/7v2X9OFRmAAAABbgHiAAAGAdAhAAALAOAQgAAFiHAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEACr9PT0mKmpKa/bAOAxAhAAALAO/wUGwBrDw8NmfX296rWbmxsTj8e9aQiAZwhAAKzx9PRkUqmUSSQSZmFhwRhjTDgcNj6fz+POANRandcNAECtBAIB4/f7jeu6pqWlxet2AHiIe4AAAIB1CEAAAMA6BCAAVvH7/eb9/d3rNgB4jAAEwCrxeNzkcjlTKBTM/f29KZfLXrcEwAMEIABWmZmZMT6fz3R0dJhwOGzu7u68bgmAB1iDBwAA1uEbIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwDgEIAABY5w8fmi3Fx2vJPgAAAABJRU5ErkJggg==", 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" ] @@ -465,7 +465,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 10, "id": "9fa339ed-b194-486a-8cf1-43b546855f85", "metadata": {}, "outputs": [ @@ -475,7 +475,7 @@ "" ] }, - "execution_count": 33, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, @@ -499,31 +499,517 @@ "id": "afb7202b-52e8-4c34-8677-dfcfe5808f41", "metadata": {}, "source": [ - "Initially I was taken aback looking at this optimal policy: it seems like an extremist 'always fish as much as possible' policy - a boundary solution.\n", + "Initially I was taken aback looking at this optimal policy: it seems like an extremist 'always fish as much as possible' policy - a boundary solution. When plotting the average episode reward vs log-escapement, however, we see that this is not a boundary solution:\n", + "\n", + "![title](escapement_rewards.png)\n", + "\n", + "Here, the *negative* reward is plotted as a function of log-escapement (sorry for the weird y-axis name!).\n", "\n", "This was contrasted by the optimal constant-effort strategy, with an MSY mortality of 5%. I was definitely scratching my head at that contrast." ] }, + { + "cell_type": "markdown", + "id": "9f766e75-f3ba-4fd5-a88a-4e31f9344d30", + "metadata": {}, + "source": [ + "## Lowered bound" + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "e2a1ff56-39c5-4703-b2ef-850daff15721", "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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vvBCVhhIEERnsRJEMHwTsGYIFIlGfbZKTTz4Z559/PoYMGYJx48Zh7Nix+H//7/+hQ4cOps8xfPhw2euCggKMHTsW77zzDs466yzs2bMHy5cvx8svv2z6nEqLfllZmakMmK1bt6K4uFiWXDFw4EDk5eVh69atkvgoKSmRhId4fr/fj4qKCpxzzjm49tprMW7cOFxwwQUoLy/HFVdcgS5duphuf6IJO+Zj7Nix4Hkeffv2DdmXlpaGuXPn4tixY2hsbMRHH32kG+9BEERiILcLAY4TXB+J+AvDPWC1WrFo0SJ8/fXXGDhwIJ5//nn069cPe/bsgcViCXG/eDyekHNkZoa6eCZPnoz//Oc/8Hg8mD9/PoYMGRK2RSWRzJs3D8uXL8cZZ5yB999/H3379sWKFSsS3SzT0NouBNEOoQqnRCrBcRxGjx6Nhx56COvXr4fD4cDHH3+MgoICHDx4UDrO5/Nh06ZNps552WWXoaWlBQsWLMD8+fMxefLksNqkvNGvWLHClOtjwIAB2L9/vyyzc8uWLaitrcXAgQOlbZWVlaiqClqmVqxYAYvFgn79+knbTj31VMyaNQs//fQTBg8ejPnz54f1HRJJqwJOCYJIPVi5QdqDSBVWrlyJxYsXY+zYsejcuTNWrlyJw4cPY8CAAcjMzMTMmTPx5ZdfolevXnj66adDMi61yMzMxIQJE3Dfffdh69atuOqqq8Jq148//ognn3wSEyZMwKJFi/Dhhx/iyy+/NHxfeXk5hgwZgsmTJ2POnDnwer2YNm0azjnnHJl7KC0tDVOmTME//vEP1NfX47bbbsMVV1yBoqIi7NmzB6+88gouvfRSdO3aFRUVFdixYweuueaasL5DIiHxQRDtEKrzQaQKOTk5WLp0KebMmYP6+nr06NEDTz31FMaPHw+Px4Off/4Z11xzDWw2G+644w6ce+65ps89efJkXHjhhTj77LNRUlISVrv+9Kc/Yc2aNXjooYeQk5ODp59+GuPGjTN8H8dx+PTTT3Hrrbfi7LPPhsViwW9+8xs8//zzsuN69+6NiRMn4sILL8SxY8dw8cUXSzGUGRkZ2LZtG9544w0cPXoUXbp0wfTp0/HHP/4xrO+QSDg+yRZ5qK+vR25uLurq6qjmB0FEEa/Pj95//RoAcEd5X9xe3ifBLSLiSUtLC/bs2YPS0lKkpaUlujlEiqL3Owrn/k0xHwTRDqGAU4IgEgmJD4Joh5D4IAh1fvjhB2RlZWn+GfHOO+9ovnfQoEFx+AapAcV8EEQ7gZUbJD4IQp3hw4djw4YNrX7/pZdeipEjR6rus9vtrT5vW4PEB0G0QyjelCDUSU9PR+/evVv9/uzsbGRnZ0exRW0TcrsQRDuBNXaQ5aP94vf7E90EIoWJVo4KWT4Ioh1CqbbtD4fDAYvFgqqqKhQUFMDhcKTUQmRE4uF5HocPHwbHcRG7kEh8EEQ7hLRH+8NisaC0tBQHDx6UVc4kiHDgOA7du3eH1WqN6DwkPgiincAzIafkdmmfOBwOlJSUwOv1wufzJbo5RApit9sjFh4AiQ+CaJeQ26X9IprMKfOCSCQUcEoQ7QR5wGni2kEQBEHigyDaIeR2IQgikZD4IIh2CIkPgiASCYkPgmiHUKkHgiASCYkPgmiHkOWDIIhEQuKDINoJFHBKEESyQOKDINoh0SqRTBAE0RpIfBBEO8RH4oMgiARC4oMg2gnyCqcJbAhBEO0eEh8E0Q6hgFOCIBIJiQ+CaCeweoNiPgiCSCQkPgiiHeIjvwtBEAmExAdBtENIexAEkUhIfBBEO4HVG+R2IQgikZD4IIh2CLldCIJIJCQ+CKKdwFo7SHsQBJFISHwQRDuEUm0JgkgkJD4Ioh1C4oMgiERC4oMg2gms3PD7E9YMgiAIEh8E0R4hywdBEImExAdBtAG2HqzHoi01usfIK5zGuEEEQRA62BLdAIIgImf8sz8AAD67ZTSGds8zPJ4sHwRBJJKwLR8HDhzA73//e+Tn5yM9PR1DhgzBmjVrpP08z+P+++9Hly5dkJ6ejvLycuzYsSOqjSYIQp1t1Q2mjvOR+CAIIoGEJT6OHz+O0aNHw2634+uvv8aWLVvw1FNPoUOHDtIxTz75JJ577jm89NJLWLlyJTIzMzFu3Di0tLREvfEEQcjRrVzK7KI6HwRBJJKw3C5PPPEEiouLMW/ePGlbaWmp9JznecyZMwf33nsvLrvsMgDAm2++icLCQnzyySf43e9+F3JOl8sFl8slva6vrw/7SxAEIeAzmcVC5dUJgkgkYVk+PvvsMwwfPhyXX345OnfujFNPPRX/+te/pP179uxBdXU1ysvLpW25ubkYOXIkli9frnrO2bNnIzc3V/orLi5u5VchCEIvloMHb+o4giCIWBOW+Ni9ezdefPFF9OnTBwsXLsTNN9+M2267DW+88QYAoLq6GgBQWFgoe19hYaG0T8msWbNQV1cn/e3fv78134MgCJgXFWYtJARBELEgLLeL3+/H8OHD8dhjjwEATj31VGzatAkvvfQSpkyZ0qoGOJ1OOJ3OVr2XIAg5fp1gDnmqLVk+CIJIHGFZPrp06YKBAwfKtg0YMACVlZUAgKKiIgBATY283kBNTY20jyCI2OEzqSnI7UIQRCIJS3yMHj0aFRUVsm3bt29Hjx49AAjBp0VFRVi8eLG0v76+HitXrkRZWVkUmksQhB5mLRo+SnchCCKBhOV2ueOOO3DGGWfgsccewxVXXIFVq1bhlVdewSuvvAIA4DgOM2bMwCOPPII+ffqgtLQU9913H7p27YoJEybEov0EQTDoB5wyz0l7EASRQMISHyNGjMDHH3+MWbNm4eGHH0ZpaSnmzJmDyZMnS8fcddddaGxsxI033oja2lqceeaZWLBgAdLS0qLeeIIg5Jg1aJDbhSCIRBJ2efWLL74YF198seZ+juPw8MMP4+GHH46oYQRBhI+u5YNnU23j0RqCIAh1aGE5gmhD6GW7yI4jywdBEAmExAdBtCFMu13I9EEQRAIh8UEQbQizAae0sBxBEImExAdBtCHMB5zGth0EQRB6kPggiDaE2Qqn5HYhCCKRkPggiDaE6bVdyO1CEEQCIfFBEG0Is6KCLB8EQSQSEh8E0YbQ0x48qM4HQRDJAYkPgmhDmF2zhdZ2IQgikZD4IIg2hG7MB2/yOIIgiBhD4oMg2hBmNQWJD4IgEgmJD4JoQ5jOdiG3C0EQCYTEB0G0IcxWOCXtQRBEIiHxQRBtCJ/f/LGUbksQRKIg8UEQbQhez/Kh2EWFxgiCSBQkPgiiDRFOICnFfRAEkShIfBBEGyIcPUHigyCIREHigyBSHNbVoruwHOT7vCQ+CIJIECQ+CCLF4VtZPIwsHwRBJAoSHwSR4rASwqdX4FSxz+sPIzWGIAgiipD4IIgUR+Z2IcsHQRApAIkPgkhxZMXDwhAUXj0zCUEQKcWWqnrsPNSQ6GaYxpboBhAEERlmYz6Ue2h9F4JoG9S3eHDhcz8AAHY9diGsFi7BLTKGLB8EkeKwWSzheFIo24Ug2gZHT7il555wyhwnEBIfBJHisAYM/Qqn8n0U80EQbQMrF7R0pIpFk8QHQbQhwrJ8UMwHQbQJLMydPFUmFSQ+CCLFYSc64Qw8qTJIEQShDxvjkSoZ9CQ+CCLFkcd8CM95nsfGX+vQ7PYFj6M6HwTRJmHdLqnSr0l8EEQbQhQY/1n7Ky755zJM/vcKzWPJ8kEQbQQmuSVVVqsm8UEQKY5aqu0Ha/YDANZV1mq+j7JdCKKN0ErXayIh8UEQKY6svHpg4LFwxnn+qTJIEQShD9uTUyWQnMQHQaQ4auXVzRQZIssHQbQ9KNWWIIi4ICuvHnihJj6UY5IvRQLTCILQh+3bqTKpIPFBECmOWsyHKctHiphnCYLQh814SxV3alji48EHHwTHcbK//v37S/tbWlowffp05OfnIysrC5MmTUJNTU3UG00QBAMrPgIDj1Ul5oNXrO6SKuZZgiDM0ybFBwAMGjQIBw8elP6WLVsm7bvjjjvw+eef48MPP8SSJUtQVVWFiRMnRrXBBEHIUVvbxUIxHwTRbmhtocFEEvaqtjabDUVFRSHb6+rq8Oqrr2L+/Pk477zzAADz5s3DgAEDsGLFCowaNUr1fC6XCy6XS3pdX18fbpMIol2j6nahbBeCaDfIsl1SpF+HbfnYsWMHunbtipNOOgmTJ09GZWUlAGDt2rXweDwoLy+Xju3fvz9KSkqwfPlyzfPNnj0bubm50l9xcXErvgZBtF9aG3BKMR8E0TZgM95SZVIRlvgYOXIkXn/9dSxYsAAvvvgi9uzZg7POOgsNDQ2orq6Gw+FAXl6e7D2FhYWorq7WPOesWbNQV1cn/e3fv79VX4Qg2ivswCM+N+N2SZVBiiAI86RKvw7L7TJ+/Hjp+dChQzFy5Ej06NEDH3zwAdLT01vVAKfTCafT2ar3EgQhxycFnIbuUw5JqWKeJQhCH3mqbWqk0EeUapuXl4e+ffti586dKCoqgtvtRm1treyYmpoa1RgRgiCig6zCqZRqa9y1qc4HQbQ9UqVbRyQ+Tpw4gV27dqFLly4YNmwY7HY7Fi9eLO2vqKhAZWUlysrKIm4oQRDq8GqptiZ6Nlk+CKLtkSqWj7DcLnfeeScuueQS9OjRA1VVVXjggQdgtVpx1VVXITc3F1OnTsXMmTPRsWNH5OTk4NZbb0VZWZlmpgtBEJEjKzCkU2SMV0ScpopvmCAIfdp8qu2vv/6Kq666CkePHkVBQQHOPPNMrFixAgUFBQCAZ555BhaLBZMmTYLL5cK4cePwwgsvxKThBEEEkFk+hEczC8uR5YMg2gapWOE0LPHx3nvv6e5PS0vD3LlzMXfu3IgaRRCEeeQ5/oL6ULV8KF6nyiBFEIQ+qWj5oLVdCCLFkQ88wqMpywfV+SCINkeqWDRJfBBEiiMvr25+YTnKdiGItoG80CCJD4Ig4oCaydVmosKpL0UGKYIg9GGDyVPFoknigyBSHFmdD39ohVNllotIqphnCYLQR20MSHZIfBBEiqO2rgO7sFxwLFKk2qbIDIkgCPOkikWTxAdBpDgyt4vK2i5aRYfI8kEQbQN5efXU6NckPgiiDeFXsXxomWFTxTxLEIQRjPXTlxqB5CQ+CKINEaxwGtwmzoSU1thUmSERBGGeVPGmkvggiBSHFRU8L1g/WLeLX9PykRozJIIg9JFnvKVGvybxQRApDq8MJOV5WZExyfKheB9ZPgiibSCvcpwa/ZrEB0GkOCH1OxSDD8V8EETbRm1l62SHxAdBpDjKocbP86ai31NlhkQQhHlSpV+T+CCIFEdZRMzr5+WrXPrUA06pzgdBtA1ScVVbEh8EkWIoxUaI5cOvFCNU54Mg2jK0qi1BEDGlqrYZIx9bjOcW75C2qcV8qA1GIYGpKRIVTxCEeUh8EAQRdeZ8sx2HGlx4etF2Zqt+gKlWuWXyuhBE24AqnBIEEVM4GK9Wqxx8tFa5JMsHQbQNKOaDIIiYwhYP00Jwu4QORiEihUwfBNEmoJgPgiBiik1FfCiHGo/Pb8oMmyqDFEEQ5iG3C0EQUcfKiI8/zFsFvyK4FAhYPhSvAVrbhSDaA6niTiXxQRApBCs+vqs4jLWVx0OyWDwKd4pWqi1ZPgiibSB3uySuHeFA4oMgUgil28Xj9ZtOtVVClg+CaBvIA05TQ32Q+CCIFEIZcOrn1dwpftlg5KU6HwTRbkiVSQWJD6Ldsq26HuOeWYqFm6sT3RTTWDml+OBDRIVXYfnQWmgqVQYpgiD0kfV3jbo+yQaJD6Ldcsv89aioacAf31qb6KaYxhpi+QgNOFWm0Ho1Ak4p5oMg2gZsT06VFHoSH0S7pcnlTXQTwkYpPtQmOVrZLkpSZZAiCMI8qTKpIPFBtFusVuOCXcmGGcuHx++XqRKq80EQbRtZUUFyuxBEcqOMn0gFlNkufl4lkNRnLrCUYj4Iom1gxtKZbJD4INotSitCKmAq5sPvN+UDTpXANIIg9JFVNE4RdyqJD6LdYrOk3s/fwiljPkIHGmW2i/baLpRqSxBtDXK7EESSk4qWD5tVze0iRwg4NfYBp4p5liAII2hVW4JIGVJRfCgtH4LbRb+8uk+jyBjFfBBE28DMQpLJBokPot2SiuJD2WZlWq2wza/rAxbPkSozJIIgzKNVVDDZIPFBtFvUlqdPdozWcQEEy4de9LsoPoTYkNQYqAiC0EYWYN4exMfjjz8OjuMwY8YMaVtLSwumT5+O/Px8ZGVlYdKkSaipqYm0nQQRdVLR8hHiOvHxUEZ9KMWGssIpK7pSZJwiCEIHeYB5agSSt1p8rF69Gi+//DKGDh0q237HHXfg888/x4cffoglS5agqqoKEydOjLihBBFtlMGbqUBoWq1aqq0y20U+GLHiw5siAxVBENrIioylyIyiVeLjxIkTmDx5Mv71r3+hQ4cO0va6ujq8+uqrePrpp3Heeedh2LBhmDdvHn766SesWLEiao0miGigDN5MBZTDirKmByCk0Kqvaitgswa7faoMVARBmCNV+nSrxMf06dNx0UUXoby8XLZ97dq18Hg8su39+/dHSUkJli9frnoul8uF+vp62R9BxINUjPlQmjk8PnXLB2SWD/kBcstHagxUBEFoo4z54Hkee440JnXwadji47333sO6deswe/bskH3V1dVwOBzIy8uTbS8sLER1tfqy5bNnz0Zubq70V1xcHG6TCKJVWFOwyJhyLBEyW9TiQNhjtMWHshQ7QRCpBzsE+P083lqxD+f+43vc/d9fEtcoA8Iafffv34/bb78d77zzDtLS0qLSgFmzZqGurk76279/f1TOSxBGpKLlQ62mh2qqrey1GHAqPFrI8kEQbQqlm/XZb3YAAD5c+2uimmRIWOJj7dq1OHToEE477TTYbDbYbDYsWbIEzz33HGw2GwoLC+F2u1FbWyt7X01NDYqKilTP6XQ6kZOTI/sjiHiQmtkuctT8u8oUWqXA4Lig8EoV/zBBJCNzv9uJi5//AQ0tnkQ3RcLr51NibAtLfJx//vnYuHEjNmzYIP0NHz4ckydPlp7b7XYsXrxYek9FRQUqKytRVlYW9cYTyQHP87jxzTW4/o01KVU3IhU6qBK19VlUYz4YfIqAUyBo/UiVdSAIIhn5+8IKbDpQj9eW7U1sQ2RFBf2wW5PfpWwL5+Ds7GwMHjxYti0zMxP5+fnS9qlTp2LmzJno2LEjcnJycOutt6KsrAyjRo2KXquJpKK+xYv/bRFquRw+4ULn7Oi45GJNSrpdFK+9inVcACHmg/1qynRaDhxsFg5uUMwHQUSDZo8voZ+vDDhNhTICYYkPMzzzzDOwWCyYNGkSXC4Xxo0bhxdeeCHaH0MkEWzGaiqZ8VPT8qFSQEwlCJVjZj5qS2wHq5xSnQ+CiJRkWiHa60sNt0vE4uP777+XvU5LS8PcuXMxd+7cSE9NpCAppD1kswOe58GlYN0Pj88f4mbx+HmwVldlhVOAYj4IIpokOnCb7dsevx/2FMjkS/4WEkkPz4j+ZM4rV8IWGUuVZvv50HiOa15bJd/mU7phFG4XLphmnOhBkyDaAom2ILKuV56XW6OTFRIfRMT4U7C0LyCP+fAkkdlUD7VF5JR4/PIKpx7pfxLcRpYPgogeie5HqRg3TuKDiBi/TlpnMsMWGUv04GEWtZoeSpQr3YZYPiBf2ZYgiMhQi6tKJKkgRkh8EBHD3r8SbX4MBzbmI9kGDy1CU23V63wYHSN+91RZAZMgkplEi3jlp4eWHkw+SHwQESMraJVEN/FGlxcLN1ejRSMNjo35SBXRpBxUPGpFxhSWDnfgNStcJMtHEv2/CCJVSbTbNpXqK4mQ+CAihr3/JboTstz27nr88a21uO+TTar71VZ+TXaUY4y220VbEHIcRzEfBBFFqB+FD4kPImKSNeZj8bZDAHTWN0hS0RQOqgGnivVeRKsOu42yXQgieiS6H4W4XVKgW5P4ICKGFR+pehNPlZmLMpVZrd3KbUqBIgScar+fIIjwSHiRsRTsxiQ+iIiRZ1akTi9gW6pmQUhGlK1UE3tev3y9F7V4FrJ8EET0MOpHdc0ezP1uJyqPNsXk85WxYKnQq0l8EBEjd7ukjuWDT8H6JKayXXzy9V7EY6jCKUHEBqNJ10OfbcbfF1bgoud/iFOLkh8SH0TEyANOU+dmJitJnGizqUmUMxw18eBV1PkI+W5cMNuFxAdBRI7RpGvlnmMAgIYWb0w+Xy/GI1kzYUh8EBHjT9JU23BIlZtwSIVTjWwXluDaLqEVTlPJUkUQyYqR2yXWq8wqxwU+SZMAWEh8EBHDp6rbhXmu1+6Fm6vx7qrK2DfIBKEVTtWyXfzy76YacEqWD4KIFkb9yBbjVWb1Pj1ZrboRr2pLEOxvO1XdLnoWmz++tRYAMLK0I04qyIp1s/RRTHHUrreyvLra4CMOhmr7eJ7HjW+tBc8D/7pmWEqu9ksQ8cTI4muL8yqzsmB6Lw844vrxpiDxQUSM3O2SPCqb4wx8oWEWGTvc4Eq4+DCztktIeXXR7cJsswdybdXES32LF4u21AAQvnPnnLTWN5gg2gFGFt/Yu10U2S7MS3cSjcks5HYhIkZW5yOJzPh2g9lGuAGnyeA79SsGGfW1XfxgpYbyu3EcJ4kPNbHIWoiT4TsTRLJjbPmIr9vF7Q3262R1hZPlg4gYvRVUE4nVwgHqy7qEYCb2IRl8p6YCTn3KVW1DU23tVtHtEvq9WTdLqgYQE0Q80RLpvx5vwrIdRxBvDc+OVR5vcvZhEh9ExCRrtovNygEec8eaiVVJhu8W4nZRK6+uiPlQznw4MG4XFfHCyyxZiRdcBJHsaE1eLnh6KZo1FraMJspJCetqIbcL0WaR1flIopuVkakz3CJjyeCCCLV8mCuvrvQJ20TxoTIrYrdQNgxBGKNlFY2H8BBQ9HnG7ZIMFls1SHwQEZO8lg+DmA/muRm/aDL4Ts0UGRNSbUOPY7c5rNp1PlKx+BpBJJJEi/SQSQkzDidrHybxQUQMn6TZLnZDy0fwuRnRlOgBBkCI30VtYFGm2gJyqw3HBYWZqkmWeW9SfGeCSHKSwSrKwvbrZC1/QOKDiBi52yV5fujWMNLbzFg1kqETiy0YP7gIgFa2S+g2t88vExV2XbcLO2tK/HcmiGQn0ZOuVCwyRuKDiBh2mXfW15hoDFNtw6zzkegBBghea1E8qK7toqhwKmxjLB/gpGwXI7cLWT4IwphET7r06hmR+CDaLGy/Sybzo1FhHzNuFz7JapiILdDLVvHzKuu7KAagYJExtfenZrl8gkgUySzSSXwQbRbZDTqJfuhWQ8tHEK12J1sNE7E9ouVCa8bjVligPH7edIVTWSAuuV0IwpBEiw9lgDmLO0nrfJD4ICLGb8KCkAjsYVg+tAaPZEs7FQcZO5PJI6YUP/u7U6RtykBSVjhxHFtkjLJdCCKexGIc0XO7JKv1ksQHETH+JC1KFU5JYzPuomQIvhQvtcMW2nUHdc2RnodYPhRVT4Pl1Y0CTpPn/0kQbYFY9CkKOCXaJala54PtsmZiPpLB7SLCig9ROAlrtgiCy+WVFzdSzn7EeBijVFtRcG2uqsPv/70SP++vjbTpBNGuiXfF0WQtr07ig4iYZA1QNK5wGnyu1W5ZXEgyuF0CjbZZOCi/noXj4BDrd3iVbhd52/UCTtViYa5+dRWW7TyCCS/8GEnzCaLdE4uMQGUFYxYqr060Wdj7djK4JkSszN1Zzc/Kq8zw9Y5RW74+3ohfg12fRYQDYLepFw9TVj2VUm3V3C4qMTzHGt0h+wiCCJ94j5HkdiHaLP4kdU2wN2ejDqjVbt6EayaeSO1hrBwiHAdty4eswiknXRu1WRH7/0zWWRNBpCoxifnQCzhNgnFLDRIfRMQkbZ0PxvKh7l4IL7AyGaw6PGv5sCktH4yoCAk49WsEnJpzu3DmY3cJgtAh3oI+WScQJD6IiEnWOh9skTEj94LbhNslGeJZxOaw6bJgtomBqHoxH4LLRky1VbsuodYeo2qxBEGYIzbZLtoTo2Qak1loRCEiJlnrfHCckeUDuvuVJINVR9QFFsZ1IiJzuyjrfCiEk27AqUyUCfutYaQtE0R7xGz9jlhkn7T58uovvvgihg4dipycHOTk5KCsrAxff/21tL+lpQXTp09Hfn4+srKyMGnSJNTU1ES90URyIa/zkfgbtBpq7TJTTCvZKpyKkokDVGI+ONhtYqqtSp0P5rXNoi0+WEQxGU7NFIJoj5i9ycc91TaJJoQsYYmP7t274/HHH8fatWuxZs0anHfeebjsssuwefNmAMAdd9yBzz//HB9++CGWLFmCqqoqTJw4MSYNJ5KHZA04ldWrMEhvU7opgqdIsoDTYLxpiOXDwmxTig+Z24UDHDY9t0vwuTigGq2TQxDtEVaUm7WMxjvgNFktH7ZwDr7kkktkrx999FG8+OKLWLFiBbp3745XX30V8+fPx3nnnQcAmDdvHgYMGIAVK1Zg1KhR0Ws1kVSYWaAtEchXrY1CwGkSWHWC4iNo5RDhEMyAUX4fr98vi+UQLR/qAaeh18VonRyCaI9YLZwkOsxOvKjCqUCrRxSfz4f33nsPjY2NKCsrw9q1a+HxeFBeXi4d079/f5SUlGD58uWa53G5XKivr5f9EalFspZXN6zjEWbAaXLU+WBrdajEfAQCTpUzIY/C8hFMtTVX/8RonRyCaI/IM+oSafnQCThtKxVON27ciKysLDidTtx00034+OOPMXDgQFRXV8PhcCAvL092fGFhIaqrqzXPN3v2bOTm5kp/xcXFYX8JIrEka8Api2HAqabbhT1H4r+bPNtFpciYRkl55axMdLuoWYT8KtlL5HYhiFDYEcFsNly8V5ltM5aPfv36YcOGDVi5ciVuvvlmTJkyBVu2bGl1A2bNmoW6ujrpb//+/a0+F5EYkjXmw8jyYSZFmD0mKVa1lep8qBUZC90mIlQ4DSIFnKqILrUB1UZuF4IIQTbGmBQVcXe7JMG4pUZYMR8A4HA40Lt3bwDAsGHDsHr1ajz77LO48sor4Xa7UVtbK7N+1NTUoKioSPN8TqcTTqcz/JYTCcXr8+NPH/6MYT06wMkUu0qmH3o4MR3miowlXliJ30mrzoey8JiIzO0CTjrOKAtInKVRqi1B6GPW5RyTcSTQZ60WLmSSFIu1ZKJBxNMZv98Pl8uFYcOGwW63Y/HixdK+iooKVFZWoqysLNKPIZKMRVtq8OmGKtz/6WaZ2yXeN2g9a4RRICy7RZkdonZMMogPsUEWTbeLukjw+v2yL2O3iNkufhV/sYrbhcQHQYQQbtB6OMe1BrX+nxTjlgphWT5mzZqF8ePHo6SkBA0NDZg/fz6+//57LFy4ELm5uZg6dSpmzpyJjh07IicnB7feeivKysoo06UN0uQOLtnOCoB4xny8snQX5nyzAx/8sQyDu+XqHqs2Kwm3zkdSuF0Cj6z1QsTCcTIrFItWwCnPC9+LjelQq+qqFUtCEO0ZuZXQbJ2PGBQZC4wMTpsVLR55O5K1vHpY4uPQoUO45pprcPDgQeTm5mLo0KFYuHAhLrjgAgDAM888A4vFgkmTJsHlcmHcuHF44YUXYtJwIrHIb1bBzhTPH/pjX20DANz7ySZ8Mn10yH6jgFJTwaRGGTNxRrzWbDVTEbUgVBGlKJSVnvfzsFmZz2COE90uFHBKEPqYFR+xcIOIQ7Da5KNNWD5effVV3f1paWmYO3cu5s6dG1GjiOSHvfH5Feqf53lZafNYY6o6qWpsg4mAU+ZWnAyWD7YJITEfCC25brdy8Pj4QMCpepqu2+dHmj2oPlSLjJHbhSBCkAv1xNf5cKiIj2TNQCRbKtEqbMzNS3ljj3/5YK3Pa4sBpwKcytou4EIHH6noGON2UqbkKgcnWfaSn9Z2IQhNmK7jSoKYDzXxkQzjlhokPohWwc66XV6fbJ9W8GasMOMOUU21ZZ5rllc3sJ7EG8ntAv3y6iLsKrfsd7FaOIh6Qjk4qaUPsudNBgsQQSQDrDXRvOUjBjEfktvFGrIvFjEm0YDEB9EqWLdLSIBT3MWHsXBQPcZEPIes5kUSzCDYImPKWY5Q50NuoRAHI9n3D7jEtFa2lUXwq1g+4v3/JYhUILFuFzHglCwfRBuHvRkl3vLRujRZ2azFRJGxZLB8iE1WS6vloOJ2YSwfSoLiQ/691GM+5DEiBEG0LtsllgvLkduFaFe4Em750FqXxbxJ1OfnVd0JcstH4sWHKJgsltCYD7VsF3Ew8vj4kPVeRPGiNzh5pCJjwW1k+SAIAZnrVqUfqcXdxzJrTs3ykQzjlhokPohWwf6cWzxKy4f8dawxo+zVBobQxdciD0qNNbzM8hFa5yNEfEgLyMkDToFg0LBuzEfA7WKmJgpBtDeMJjhq673FwnIofoya+EhWSyWJD6JVsJ1KKT6SJuaDea60zgDmxEey3XSlTBSNdVz03C7KcdCh5XZRyRJKZBVbgkgFlOOeX8NNG5Ny54FxQW0NpmTtryQ+iFbB3qCUAafJku0i88caxHxonUd+I068+VJu+Qhd20UpSIJuF7/sODDvVwbSqpWlD8eFZYbFW2uwdt+xiM9DEIlEz+3iVzN7ILZiQG0MSNa1XcJeWI4gAIXlw5tYy4dW6qdRKq0pt4tKqfFEwma7qJVXV1o+nDoBpzYVlwwgHzSDlo/oVbE9UNuMqW+sAQDsffyiiM5FEImEHUOUky6t+PSYpNoGHsUsOLaPJsOkSQ2yfBCtQs/tEu+YDzOYEUSqAoV5LgRtJrYjBy0fKgGnCI0DcTKWD2XbNbNdmOfiNTFVit4kRxpcwc9K8PUkiGgR4nbR+G3HJOaDGReUExC36uKRiYfEB9Eq9NwuyZINYRgMpnhtZlBIfPCW3touXIgrRor5YBeWU+7zartdRKGhLKEfCcrS7gTRFjArPmKTahv0x6rFgiVjPyPxQbQKv67lI/l+6K3NdlEek2hhpZftolbnQzxGLeDUadVyyYS6WMysg2MWh40KlhGpj9Ka4PbJx0Ftt0tsf/N2W2h+bzKOySQ+iFbBdjzlDztZfuhyf6yaK0gRcOrVDzgVzpNg8RF4tKhYOdSsIU7VgFPhfU67sE95bdjrJtY/8Ucx4JSNyE/09SSI1mI0MdG0fKiMMxG3JfDIQcPykYT9jMQH0SrY7tPsTgHLh4mAUzPWkUR/N9a8qgw4VVtsTi3bRdqnYfkIcUd5/WBjbaNpwk3GQZEgWoPZVNuYxnxwHBxq67skYT8j8UG0CtbykehsFy1Yq4UZ0aBegl2Oy5O4YFqfn8d3FYcBhM5wxPRZXbeL4ssELR/aMR/Se8NYIdgIv47VjCBSBaOYsUS4XYRxgdwuRBvjpSW7MP7ZH1Db5E6qImNaGK27oDbDNyKRnXjh5mrpudLKYRFdKSGptqELy0kBpwrLx2vL9uCcv3+HA7VNsnO4fL6oBpzKir8lYWYUQZghJOYjkQGnzHO19V2SZUxmoTofhGke/3obAODFJbswokdHaXtozEd8bihWC6e7vLthkTHF4KAecJo8MR91zR7pubLImPjMaZebXMWBSGi3/LuIwkS8Ng9/sQUA8MgXW2XHCVaT6Fk+WrMYF0EkGyFWUdPiIwYxHzyTBaciPpJR5JPlgwibEy1eWcdLVEaIMuBSD9Xy6orXZrJdEul2Ya0aykXkJLeLRsAp+z9RumiU3+mEyyt77fb65ZaPCAdPvWBlgkhVQmM+zB1nFjO1OijglGjTCDcj7Y4QrxuKMrhSCa+SMirbHxJwaty5E3mzTGOsGiHiA/IMFpH0wHtcCgEBBIWJy6e0XCnqtvj8Uc12Mao8SxCpgFHAejTdLk1uL879x/f4y8cbDY9VGxeTsZ+R+CDCRqiYp7M/WcRHmOZ9tTUQkinbhbV8eLy8zLwqWjOUMR/pjqBgEWNzRKEStHzofydlsGrE4sMwBZogkh9lGn4sYz6+2liNvUebMH9lpXpbZNkuam4XEh9EG8CtEj8AMDPpON1QWLeLWlqb4douitdmBoVE3iydTAqdy+tDmt3Y7ZJuZ8WH/PspYz60UMZ8RCo+omlFIYhEYeRu1pqgtSbmw2CeJQkhtUKDAIkPoo2gjAEQEd0CibB8GN5AWxtwqiwyZmAliCVWS1Bsubx+mRjRmvlYLJwkSJoVsR3hWD78UbRW6C3GRRCpinKM0QqGb02dD9NWXi7U+tnaz4w1JD6IsNFyu7DxBfGA7ZCqnxmmq0DtHMrvqaxpEk9ktVU8PrkbhhlcZIGpCMaBSCnRioBTo4HJpYj5UFpQwkVWfyWBYo4goonpheW85hd6+2ZLDV78fpesKrDRe9lxUZywJDJQXgtKtSXCxqUoOiUiugHiZflgLQHqbhU2q0K78zltFri8fnXxoXidyJsl25YWj18mMthJltNmRQOEjBWOE0RhQ4s3pBKtUyPbRUlMLR9JOCMjCDMYl1fXfq/bJ7dcanH9m2sAADecVar73qDhg5O5XtNsFjS6fWT5INoGHp++2yURpnSjbBaPjw+JCxH3692Ek6nOhzJQ06ZhipVbPjjp/9IsBZwKmLV8KGdqkV4D2fdIwhkZQbSG0JiP6GUE1tS7dN8bdLvKYz6kMTkJLYwkPoiw0TIbxjvmI9wgSOVNVrSMiBkhZgaERAacmnV9hGS8KMSH8jija6fMdolYfBikQBNEKhASDxYyvmijrApthGxJAp2+r1ztWhqTk7CfkfggwkbrZhWM+YjPDTrcbJYQ8RE4QM9iY1TFMJ7I3S7a11iZgiu6w1q03C4G38mlqOsSqbVC5sJJwhkZQZhBdQ0kZqNeaEa4v3u2j6qNr6wQYvu/2QlGIqCYDyJsXCqLlAHhWRCigeHaLQZrL0jiI+A/Vbuhh1Y4TaTbJdiYqYwPWAlbYp0DQt0uUk0Qc5aqFo8vqovBySxWSTgjIwgzqGkLj4+HwyZ0sEgKMX618SDe+Gmv9Jodm4zcLqzl0xHn8gfhQOKDCBuPT73CabyzXeQ3MbXZgBytm2yaxuquamdJZCcWv+5JBZnoX5SjeZxTEQuiFB8iZgemFq8vqoXBZAvLkeWDaEO4fX6pX+lZPozcLtPeWSd7LbN86LpdONWYj2S0fJDbhQgbteXZATa4Kf5uF3PxGuoxH04dd1EyVTgV25vlDM4ZbJbQ9W2ciuJjUsyHW17h1KxJtsUdO8tHMs7ICMIManFv7NgXzSUoXDLLh36fYWM+zLpWEwGJDyJs3F6/qskxI+B2aYnTD92oUqbZCoSiaDJTvyIZsl04Lig41KoZygNOOckdpvy/OEwOTM0eX1StFbSqLdEWYPuE2CWV1kUtwhXd8pgPbRczx8mrHJPlg0hpvq84hIuf/0F6rSw6JSKKj7hZPgwyMIzcLuL+dLu2+yG0zkcis12ER9bWoSY+zAecmhuYmkNiPqLodknCQZEgzMCOP+n20LixWAWc6sWmCf09GPMV79pL4UAxH4Qh185bLXvt8flVo620ZtixwjD9UxlwqowLUWa7qAwISeV2YWY3ImrLZysLEGkFnDpMul2a3X7Z8uCRVjhl660k46BIEOGS4bCiye1Dszv4e9Z3u4Qn4I0CTn85UBd4xsksn+JYkIwinywfRNjwfGiOOxC0fPj8fKtWbowEM3nzWh1QynYxSGETzpHAgNPAoyUMt4tatovyOKOBqcXji26RMeY5xXwQKQtr+XCE9jE16SFOFsKO+TBwuyzaUgMAqK5rVrV8kPgg2gxqFU7THUFDWrhFdFrXBv0borHbRThC6qCpYvlgtqktIiUTHxwXNAm7NSwfPv21JoRU2+DraJZXp1RbIlVhJyYZdmHsazYIOE1TrrNkEpnlQ+e9vx5vlgWcm125OhGEJT5mz56NESNGIDs7G507d8aECRNQUVEhO6alpQXTp09Hfn4+srKyMGnSJNTU1ES10UTiUc12YW56kZrmw22Deml0+euQbBcTRcaUJLbOh/Aoc7uorA+htIaIA55Wqi2g/91DYz6imO1CqbZEisKOL2kOeUYZu59dg6q1tZCM3C4ibp9fsuQC7MQq+SyMYYmPJUuWYPr06VixYgUWLVoEj8eDsWPHorGxUTrmjjvuwOeff44PP/wQS5YsQVVVFSZOnBj1hhOJxaeiPqyWoL8xHpYP+cJxrUm1FUhTCRaTjgkRMIl3uxhnu8iLjImWD6/CXMVaSNw+P1SydgGEZruEsyqnGhRwSrQ1MlQDTgPLN8jcIK1ba0VuedQRH16/zPKRzOXVwwo4XbBggez166+/js6dO2Pt2rU4++yzUVdXh1dffRXz58/HeeedBwCYN28eBgwYgBUrVmDUqFEh53S5XHC5govm1NfXt+Z7EHFGmTkBCLEIaXZrYIXYeLhdgs9VLR8IBmjyfKi4EAcH/fLqybOwnF/N7aIacCrPdmErngrvF87ABqu6PH7YrRbV79fs9oWIDZfXL/MthwOl2hJtAbZHZOjEfKTZLTgRuMWJdXkimZwpx1a2b3oUlo/gopnJ188iivmoqxMibDt27AgAWLt2LTweD8rLy6Vj+vfvj5KSEixfvlz1HLNnz0Zubq70V1xcHEmTiDihls8uS+uMt9tFp86H2BldKrMSgA3KMrZ8xON7aaHmdmFnOWrb2CJjSjiOk8V9KK0oDsaKpYzxiUSERTNtlyDC4YPV+7F0++GonIsdQ6RMP5VUW5klMtB5I+k/SiGhFPNtMuaDxe/3Y8aMGRg9ejQGDx4MAKiurobD4UBeXp7s2MLCQlRXV6ueZ9asWairq5P+9u/f39omEXFETXyIlg8gXjeVYK/Tc5kEBwahA877cQ9GPPoNdhw6AUBeZMzInZDYOh9C22TZLiqWD+U2pYVCJl6swXRb5fvY2ZwyeC6S/y+5XYhEsKOmAXf99xdc89qqqJ9bbeVosc+wYkB0bUbSf7Tcx0BozIfNKoqd5BP5ra7zMX36dGzatAnLli2LqAFOpxNOpzOicxCxxcKFZrc0a7ldbPIbfSwxu8y7crXdhz7fItufZpfHPijrZACM6yYJOrE84FTN8sHGfHBSETU1nHYLGlyCeBMHKpEMuxW18KiKskjMuOy54hEbRBAAcOSEW3rO87wsdqo1sD1CmuCoBZwynyNOHCIZH5VCQlnpWWb5FN/TVtwut9xyC7744gt899136N69u7S9qKgIbrcbtbW1suNrampQVFQUUUOJxKF2g2t0eUO2WTjzqWS1TW5sPRhZfI/f4CbG+lyFY/TrfADaGTGigPH44l/DRNkWDubrfICTiyslbLyL0ujD1i4IqfQaJcuH2XLUBBEpDkWAdaSoVThtVnHtshon6HaJouWDaYefl/d/S8DUkoz9LCzxwfM8brnlFnz88cf49ttvUVoqX9Z72LBhsNvtWLx4sbStoqIClZWVKCsri06LibijZtpvUo354CSrgZGyH/34txj/7A/Y+Gud7nF6GJnvlQGlWoLIbrVIA0RIUCpCI9YTNVv3qwxmqm6XkFRb7cBQdtE5pcAQxYfb64fXJ98bycxNbvmILHOGIMzC3pTVLLfhwgajqxXyk7LTmMlCpywHAGN3o55RRmnFULpEOVVLS/KJj7DcLtOnT8f8+fPx6aefIjs7W4rjyM3NRXp6OnJzczF16lTMnDkTHTt2RE5ODm699VaUlZWpZroQqYFQS0Ju6VDrvFYLJ5n8jH7sjYH3L95WgyHdc1vVLrNuF0l8aMw2OE6wfjR7fJrBXGl2q+R6afb4kJ1mb1WbI0FtYTnVgFNFqq2u+JCsG94QESAWThL2BwuU8XxksRpq9VdamzlDEGZhY6WaPT7kRem8HMf0I6a8Ohsg/vQVJ2PTgXqUFmTihx1HDMdHp82iKfDDsZqIkxPRYmtXmawkirBa8uKLL6Kurg5jxoxBly5dpL/3339fOuaZZ57BxRdfjEmTJuHss89GUVERPvroo6g3nIgfalU0td0u+jd6JZHMoFnFrzeTSbfrW2OEdFT1MsQyv65UKTRBbpfAo2xhOWvoTTtNlu0SXNWW3RY8NjhoKuN60hyh51bGz7SGEPGRhP5oou1hdrwwDbPQo9rCckFLJYeJp3XH/ZcMlAoxGol3tbgzET23i8j/jSzBgC45+M2QYLhDslk/wrJ8mDGPpqWlYe7cuZg7d26rG0UkF2qz6yadOh9A8EbP8zw+XPsrTu6eh35F2SHviahDMD/HJneoGDJbwZSDcXE0MWW1ye1LmP80mO0S3KYW85HhUFg+VI4RYX3Vyv5tDcSLsKItLXANopVqCwhCNRfxtyQR7Qsfo67Vxq9wYYv+qcZ8BB7Z/ioGgxsJbrUJn4hyjFIr4/7Yb4cIbeD5hFtstUgeGwyRtKjGfKjc7AX3hbxmxoJN1bjrP79g3JylqueOVuDiCRVLjBSvoZKDL4PTFijyeiDqC7TFDRW3S1mv/JDD0u3yOYXS8iE/lk2nle/jGDGpPD6ibBfF66jMQgnCAJ8s1igK4sOgvLpajJY4PhpZhtUmfCJ61lkl8rWdksvC2OpUW6L9oKbCzVo+tlY36J47WoGLquJDKjJmYNUAu8KrMuA0cAxnHLgaa6SKrcy2c/oWYN61I9C7c5a0jRUbYjwLC/t+NkVQafkQzcm18EjbMhzRd7skQ/oy0fZhf9/RnECwbhfZeVWy08xaPtQmfCLKWkOs5eOVq4eFHJ9oi60WJD4IQ8yn2nIhCxnpmQ+ByG7k7Ey90aV9HjPrKWgdw6a3ai3QFi/8KpYPADi3f2fZ6wyFpcNiESqZqpUyT5O5XeT71KqjZqUJQ0Yk/zelyElk1Vii/cBm10bH7RK0bKjFfIj7ZW4XjUmOEr3AUOX4w3anMf06Q0nCLbYakNuFMMRmCf2ZqFc4DbUOGGUxRHQTYwyOje7QbA3xVYZTaEOTJ1QwAWKKsNagoDLAJMhNoFZeXQ3W8iGmyLIign2/LOYj5EyhbpcsZ2Dp8AiugfJzki0QjmibsDEf0XS7cOCQ7gi1rvpFsaMS4B2J4FYKJ3bcUxsb0lVcQskAiQ/CEOXiaoCQuqWEvYmLnYu1fKgFLEeixtnT8bx2p8wO3DC1rCNsOqrWjIg9JlEzCDW3ixoZjGBolkSgelcXB81md2gJdTaFUEQUH2p1XswSul5Ocg2KRNuE/X1Hw/LBImanGAWcmi3CqIdSRLD9yaKiPtSsMskAiQ/CEGUgohZqqbbszFmtqmBE9SIUr5WuIHF/piQ+tCwfQKYjcIxOx1b168YR8f+gNsCw2BiTrThQaS0uxw5MIW4Xlfdli26XCAZvpchJthkZ0TZhLR/RKTIWgFO3LqitQi2OM2oxarJz64y5IW4X5rnayJDocUsLivkgjDErPiycFFDVojLjbnb7QvLXW2N+XLXnGI41ukIsKQ0uL0I9nibEBzjNY2TpdIk2X6pEzxvRrOL+Yt/OWnOUooCN4RHJcgqpepHMHENEI4kPIg74oxxwyjPiQq2WEK8yWRAthy6vH16fXzZR0GqrEjEtXoz98hu4XdQycZIBEh+EIXodwW7lJBeMhWMzS4ROyC6qpFZVsDWrxF7x8nLZa3HhuxBxEWh2NuMq8PuDee8sWYG4kBDxYVBIKNbUt3hQXdeCvoXZsswbsxjF3rCCSvlfZjN8RMSA08jcZfJP0hKFBBFNol1kjI3BEscGty8oKtTWdhHjzwBBdOemq4sPvfkezwvjq9h32e6ktlheeoID5bUgtwthiJ74yHAE9SsnS7X1Bd4bPFZtthyNDiHOJpSmTKXbRSy0o8zA4bjgMSHnYNRHImI+yp9agrHPLMX6yuPw+4MVE80iDlCywmPM+/WKjCmzXQT3VOSzKOXPycgETRDRgPX6RrsPs7FRLQFXstraLk6bFfbA6tF6otuooCdbZ0lN5MjaRjEfRKqiF/ORyXQ6C8ch0ym/QRvNNqLRIcSqfcqAUrFTpjusUtBXo9sb4vrhYMY1E51I9XA51OACACzYXK1aXl2Lpy4/GZee3BX/b5iw6jQrEln0Yz7kpdltFk4SMRFZPkCWDyL+RLvCqQhbIRkIjnNa2WniWKNWqFHEyNPNtj8Y2Ko+MiTcXawBuV0IQ/RUeIYz+BOycMGbnDibNYowj8aNXAyC1BMOmQ4bGlxeNLpCLR/ggtaTEAHDPE9k4JabWfLejOVj0rDumBQQHgAkUagkzaEd8wGF5cNq4aJi/VF+DIkPIh7IV1OOrttFrCTa7PExVl91i0Smw4baJg9O6NQmMlIfbP9TC2xlSXSWnhZk+SAM0esHmTLxwQVTMV1y9Q+oK/1wq1uqCSFRfDRoBosGfa2NLm9I6WI24DTU7SKeg8nlT8AMwuX1q67tYhblei8ikqBSi/mAPObDZrFIs6hIZo5KS5ruIEwQUcIX7ZgPRep7usIqqGWRECcCTTqiW8/VDSgsHwZZcMma7ULigzBEryMo3S7iTa5RxfKhNtswsVahDJ+KDyhLK1OFyYVj3SpqRdM0A06ZASaRnZitvNoK7WHC7eIPdbso1nYRLFuR+48p4JRIBDK3Swz6MCvkAe1YDK2JDoux24WJ+RCfaAwMiXAXm4HEB2GIX+c3y97ULBZGCAQqjhoFnIaLT0WtZEkxHxrCQVbHI7QSql7AaXAxt8SaL11eH9glusMlU7Hei0jQkqFWLj8YKQ8I9UMkt1pL6wWD8j9IAadEPJBNhKKa7SJ0KOXyC2wFVBZ2LDI6txayeiJ+fYsoBZwSKYue5SOLiSXg+eBN3B9IBzNTVdAoslvWFhUhJLpd9G5imZJlQ2X1VgRFlNaAwAZfJiJwSx7zEf772dgcFnFgUqu1wUEexW+1cMgJCL36SMSH4v9N4oOIB9HOdlEGgIe6XbQsH8GxSPvc5t0uIkqRI5KsdT5IfBCG6GkD9qbm8vplAYpKK4PWjz+cKqdqlo9sA7eLGHAqHhNaRpwzFXAqrg6biBmEy+tXTd0zS6aiTLqIOGCqLTqndLvYLBxy0oXrVN/iCTneLOLlz3Sou7oIIhbIJ0KR/+aUIlocH8TaReJESWmpZMcizbYaDIlqlVSNLB8U80GkHHoqnF2uvcXjg8XCyW4qrJVB68cfjiJXi/nQsnywZlEp5sMdmlIKsLMRrXME4x2ivS6EGeRul/Dfny6L+Qit86GG189LAyUQsHykC5YPt9ffahEmXv5sDXcZQcQCPzN26FkdwibQnbQDTuWHG6X1m0Fe5yPQDAo4JdoaenU+2OrAYvGcDCZ+wozbxWyncHl9sgFERLyJaWVNCHU8WEEUGvOhLHsswgqvaAwarcXFuF1ak+2iZfnQW3W42e2VhB0giI8sh00SP62xfvj8vHT9zbjLCCJasFbTaPzmlG4X5eKUWimw7ERI89xG2S5hpNpmaEysEg3V+SAMUd6sMxxWqYNxHId7LxqAXYcbcVpJBwBATpoNhxtcaGhRWD4Car012Q7HG90484lv0btzVsg+rWwXFjbIK0R8QJ4y3OjyITfDEmgrpO9pJko9VsizXcJXH6x7jJ0gCbU7LKqR8M0enyTsxGMtFg7ZThvqW7yob/aic7b5Njzw6SZ89nMVri7rCSBYql2wRvGtCqQlCLPILB9uL/x+HpbWKPkASotDhjK2QsMiYcbdaBQF16JSZEyr++SIpQgiiNOKBSQ+CEOUIjwnzR4UHwCuP+sk2f68DAeARtQ2eWRCo0lR+U/EzM38q00H0ej24edf60L2ZWkUGWNT3TKcbMyH/P0cB9itFjhsFri9fpxwe5GbYZcfAzaTJ/43y6bAYCm2N1y0LB+AsFhci8cVsv1Ei9zyYQsM1DnpdkF8hGn5eGP5PgDAv5buDnyucG6fn4fL69e1whBEpLAuW54XrAdZGoHYrUE5ORGtplpuF91U20BTH7hkIDpmOnD7extk+9XqfGiNR+IEoiGCOK1YQG4XwhClpUAMOgTUf/C5gbiAuma3bLahVnIdMCc+9AYJzZgPsY3gpKycJlfoGiaiwVLNgsIeKYocn5+PS848rzATB2c4rbB8aNT5AOQZSyx1zR4puwUIDt5Sxktz6wYz8XfA/k/J9ULEmpDidhFbAuSTAeX4Efw8eX+VCjHquF3EMfL00o4oykkL2c+6XcRxQsuII46P9S2hZQYSCYkPwhA1y4eI2n0wLyA+aps88MncLqGLzQHmBgF2Bq4kR4r50AsWZeNQ1M8jxoWw55FZT5iZeTxulmw7T7i8kaXaalQ4BYKiSklds0e2T/z/BTNeIrsGFo6jjBciboROeiKzBLDZdADr2pVbeJWiIENlnAk5N8Rzc7I+KC4N0azqdlEfGMTx0efnkyrolMQHYYjYaf90QV/8dM95UsYDoB7kJLosapvlbhfR56gcBJRl0dVIt+vN3I1jPtjZhlqRMeGYgIhpCbV8cBxCMnliDWsmZmumtKrCqYZ1A9C2KtU1e2BlRk5xUI3U8iHCFndLNn800fZQZspF+ptT3vSVGXOaa7uYWViOmWiw/TNL5b1GqbYZDqvUj+ubk6efkfggDBE7wtl9C9A1L11mhVC3fDgACDcvVmjUadyszFg+9Gb74szA4+Ph8rIzguBnizN/NcuHeOocyTzJtFNRpTArjhkaysFSrIeitYaDHmzKrLKuipb4UF6noOVDLDQWqfjgTAlHgogGyhpBUU23RWg2XDDVVt3tov/5THVmpn+qxYuwy0iowfazZIr7IPFBGBJU1oGAQ8btonYjzA2Y5euaPLIbWG2zW3Y+ETMzEP0qq/JMFRG12UOTWraL+L3Em6rK7ED8mvHMeFEOlrVNbllbwoGt56GccZkNunMHUpCDlo/IrgGbZaRXapogooEyTT/qbheFqNBa24WdCBmdm12sEwBsgXIG7JhpZsHJaLlKowmJD8IQpflQFnCqcnx2WnBmrGb5CF3V1HgQ0IuTslm4YJlwlWBRDhyT7RJaZCxo+Qid0SsLrMVzpu7zyT/7uCg+WnEuNqVQOePKVIiPC4cUAQBG9Oygeq5oVDkFhMEyGGeTPL5oom2iHHcid7vIx0XJJSuVFBC2K1Pjgyt/G69qyyEY5wEEM85krmETsWDZzuhYK6MJpdoShiiXbGYtH2q/+Gwmr5y90bd4hKqYrcl20bN8WAI1OJo9Ps0BRVq1VsXyISLdVBn3kFZQWawtHy0eHy54Zols2/EmoV2Rpvgqg86UAadPTBqKM3sXYNygQtX3Ry/mg9wuRPzYc6RR9jrSPqx0d4Sk2hrEfDS6fZq1RthYM7a/i2NwvZr40JmWZCdhrQ+yfBCGiDMGcSV6NuBUzdTHxgQoTZ31zZ4Qy4M5t4v2PsGtIp91APIZAeuPVatwCgRThGWWD0UFn3jFfHxfcQiHGuS1NyJxu7Ao256lSMPNTrPj/0aWID/Lqfr+4P83crcLiQ8iHri8Pny8/oBsW+SptnJypHoa8lRbrbVdAHnKLItWHIcYONqgYp3Vd7skX60PEh+EIZKCD3QEWcCpitpmVbZSNNQpMmCAyC0f2tVHmTRZBxuUKg+4FL+DOHjUNau5bgTidbN02kKzU441BiwfrXK8BFEOulkGAcQ2xagmBeZGaPkAF98YGqL9orZ45YkI44yU7o48McuvyQ2e5zXXdkmzW6RtWq4XrdodYl90ef3SYpBGRcYAptYHZbsQqYQyoMmozkcOU1FPKRpqmz2hMR8mZiBGxXFUC4Qx5ki2wmdIzIcUy6LtTggGnFpNtzkS1OqaiJaPCCpCA1Bxuzj1Y3jSFdVRo5XtYiG3C5FAIu3DUsxH4HWHDCHLz+PjpSrI7H4RM0s1aAkK9vUJg5RelpwkrHJK4oMwRGk+NKrzId44Wzx+KUNCRMiAaYXlw6CgqNFNzGa1IM2u/nMX26OWaqsUPVItkBgHSNqsoW31RlBeXQ9WfKhlL2UoxUcMsl3I8kHEErUFKaP1mxO7TJpdWKIBEK0f4v7QPiUVJNMYR5QWVxGX1y/1R1FIKDzDqiTj+i4kPghDlCbAHGZWrhYsxd7MlLU9alsd86Fv+VArVqXslLJAWQZxAFCzfIS6XeJTZExZ44Ml2mvKGLldbjqnFwDggoFCAGq0sl3YWBzKdiFiiVp3aq3l41B9C/Yfa1KxoHLoILlePCHZMCxin2vQyPTTClbtnO1kanbIA1v16v9kq2TyJRoSH4QhIdkujOVDzR1is1okdV7XJP+xtz7mQ3+/MseebZvYJXPTtcSH8PnBVFu1oFX1iPZYoedmaq320HLXsKm2asJmSllPfHbLaPzz/04FEPz/u71C9lJrsXAcsw5Q8gyKRNtDbfLS2hvx6Y8txllPfif9ZtkYLLHAYi1T40gtRivHIAaDLRMAAO/eMArlAwrx6G8HM2u1BCwfiow8NdQy+RINpdoShih9imw8gtaMVVz5VnlTqVOL+XB5DVeJNYr5CC4up2K1UMR0KBEL96h3ULmAkWYdMRYfutk9rQw4zXLaVDNUsg1iPiwWDkO75wXP47CB44RBr77FY3o12gyHVbaYFscB+VnCYH30ROiqugQRLdTEx9ET7rDPw45DFdUNAOSTATHo9DjjdlET/bk68WXC50B27rJe+SjrlQ+AXaVWnlWjZ/lIRpEftuVj6dKluOSSS9C1a1dwHIdPPvlEtp/nedx///3o0qUL0tPTUV5ejh07dkSrvUQCUP642UwMrQJhohgIER9N7pCBwMyCR0aWD6OZBBBq+fjzuH743YhinN2nQDhHYL9LZUYfjGh3SN8jluhn97TunNkabicjt4sSi4WTBEs4PuTQwZFDp0whnbc1NwKCMItadzrcCsHLnkfNcpLHrGulFwhqJAb03itNtBRuF705SS6z5EWyELb4aGxsxMknn4y5c+eq7n/yySfx3HPP4aWXXsLKlSuRmZmJcePGoaWlJeLGEolBryNo+U2V4kPMT69r9kgWCYfNAnvA6lDbpN8pjGI+1DqzMldeKT5+P6oHHp80VIpbEWf0AOtPlX9OB2lmE9tOrBYgJ9LabJfHJg4BAMwo7yPbLpqKASFI2Ax6mUFaKP+HFtby0ehKquW+ibYF+9t79nenABD6eLhuQ/Y84kSH7Y5ixkttY1BMq1kqxUmMuOSEkqDVVq+UgSLgVKfdbcLyMX78eDzyyCP47W9/G7KP53nMmTMH9957Ly677DIMHToUb775JqqqqkIsJETqEMxXD/15a818s9PkP/YO7IzAHwxgzWV8pHoYiQ+19E9l0JZSfChv4uyMvj6kYwsHd8gU2nu8MdaWD+19rXW7nNO3AJsfGocZ5X1l25WptGZQi48xQq24W8fMYHpiMq07QbQtxABum4XDpSd3hSOQTXY0zH7MrrckjhGsQFBb0duicpfNMRIDOsYMsVS6cpVwPbeLaJFRi7lLFFENON2zZw+qq6tRXl4ubcvNzcXIkSOxfPly1fe4XC7U19fL/ojkQi+aWlt8yC0f4oygjsl2sbDR4RozgGAb9Nuo1pmVMwJlzIfa91HO6HnFScTv0eDywuMzZyVoDfrl5Ft/XuU6Lq2lNQFsoasJc0izWyXBR3EfRKwQu5PdagHHcZLF7UhDeL85tluqCQdxfDje5GZ+76EdNmiJ0Ao41R5zJcuHGHemiA9RQ/w8j4+XxV0lkqiKj+rqagBAYaF8TYjCwkJpn5LZs2cjNzdX+isuLo5mk4goEIz5CN2nFXipjC9gxQer1POY1DT9NoTvdtE6RkRVfGjM6NmMGfFtx2MY96H7faNd6APQrIGihdoifEYoZ1zi7ynoeqG4DyI2KAsldgosHXAkTMHLpsCrCe88cRxq8pgKONWO+RAe1WM+5BMkMwGnGQ6r5OJOFtdLwlNtZ82ahbq6Oulv//79iW4SocCvEtAkdqjBXXNU38OufAsAHTKZThnYxoXldtFvY06aSmdWpMkqxYdqdVbFjF65qq3VEkwPNWpzJCjFB1uhNfrSQx73YYaghSgct4v8tfh/EdeQIcsHESuUN+hOouUjzN8c2y9Fq68824W1fJgIONWYwGhVRwWAjpnBjBogdIxSg+M402NtvIiq+CgqEpbirqmpkW2vqamR9ilxOp3IycmR/RHJhbLOBwAsmnkObjuvN+69aKDqewoUi5Kxlg9x9sABpt0uRpYP8TwNLV64vIJZUel2Cc/yocihZw7tGPgux2I4U1dWdBUHNUB/htNaRAuUWaJh+RDJzxRvBGT5IGKDUggELR/h/eZYAR2M+QhuY7Nd9GLl2BgMNXQ8NsG4sybzlg8AyE1Xz0BMFFEVH6WlpSgqKsLixYulbfX19Vi5ciXKysqi+VFEnGBvGOyPu1dBFmaO7ScFWCkpzEmTvRY7jNfPS1HaFot5t4tRkFTHTIdkHdh/rEn2HrMBp0DojF4ZcArIF5CKFazY+vc1w+Ul7WNg+tCqgaJ9fPgDmdLyYQmxfJD4IGJDMPgzYPnIFn5zh8OM+WCz0NSKjEnZLk0eXeuFkduFXZdKiTj5EYPetaqhKpHKBBhM9OJF2NFnJ06cwM6dO6XXe/bswYYNG9CxY0eUlJRgxowZeOSRR9CnTx+UlpbivvvuQ9euXTFhwoRotpuIE+wNI5xAR6X4yAgEFja4vKiuawmcjwumnBncyNXcLn885ySc1CkTgGBWLC3IxKYD9dh9uBG9O2eHHK90BZmzfIR2bDFDQ1xlNhaI33d4jw4oH1iIV5ftkfbFxu0SnvjISw9PgKmJx+AsNJhuSxCxQIwNt0pul9bFfKi5XVjYiUnQ2qIXcCpk/7HLVMgnfKFtCFo+RLeLeKyR5SO50m3DFh9r1qzBueeeK72eOXMmAGDKlCl4/fXXcdddd6GxsRE33ngjamtrceaZZ2LBggVIS0vTOiWRxLCdLZw1RYoU4sNi4dCtQzq2VTdgX8AyYeEQhuUjdNus8QNkr0s7ZWHTgXrsPdoovEdst0adDz1frPKmquXXjRXKDCPWLaK2nk6khOt2yQ/TbK0mHsVvIbpdyPJBxAqlEGhtzIdPR0QDwfHDzzN1QHTGGT8PnHB7ZetOsR+hNuZ2ZNwufj9v3vKR6uJjzJgxButOcHj44Yfx8MMPR9QwIjkQXRhAeOb+zjnymA8Lx6G4Ywa2VTegUjonJ1sLQQ+jmA8AKA1YQfYcCYgPRbxGhwx5UKVaxxbbLVpn1OgYh1ofPsWAEq44CJe8jPACTsOdOar9/0QRld/KWShBmEWZ7VLQypgPtWGIHUXS7Fak261o9vhwLDA5UXOdpNmtcNoscHn9qGvyyMWHxrlFxLHA5+fR0OI1tbYLEHSttsmAU6Ltcft7G6Tn4QQ6ptmt8tk6B5R0zAAA7A2IAwtnPuDUTGEc0QWz+7Bo+ZC/x8waJF1yBYvNwYD4UPO9iiImlqmhyiCyXCYbJRYxH1qL7mkhuUpMWz5C/39inRRKtSVijTJovrWCV+13rJzEiGOaWENEy1DZMVPdgsrLrM2h73ParNIaU8eYeiJGlulgDRISH0QKsLmqTnoerrW/MDvoerFwHHoVZAEAtteckLblmq7zITz27pyFopw0PDFpSMgxPRWWDzUyDap5ds1LBwBU1TYDgOqy2N07CMdUMlahaCMOQGJZermQi7L68PswSCNlWgvR8lHX7IHba1xsTU07Hqp3yc5Flg8iVoTW+QhaXMMpFugzyvkH0CNfGId2HhLGOa3u2lHD3SizfGi8WSxdcKzRbdrt0im7da6mWEHig9BF7CBA+De9wtyg+OA4QTgAwR+/hWODN92665mIg8eALjlY8ZfzceWIkpBjeuYLlpVDDS40u32qabL5ihRgJaLlo77Fi0aXV/Wm2TMwuOw7GjvxoUwNZC0TUZUe/5kK/K0A59R+gvsvHoj514809bbcdLskjMykHKvNGGvqBeuSGPMR7o2AIMyitA50yHBIv99wYo2M3C4A0L+LEOwuWvK0BISU5aXoP34Dywcgz3gxm2orivxwM3xiBYkPQhc2TiLcCXdhdvBGb+E49AmIj+D5OEl8eP28biCUXpVVkdx0u1R6uPJYk+riTOKMR4vsNLtU7vtgXbOsrSIlAZFz5IQLjRoVXiNFvAdLAafhpNr6PMDKV4Dd3+sfV1sJbPoPwPvAff8YrivrjjN6dzLVPouFY+pzGA9marqypkEQH3kZDun/Gus1c4j2iV9hSbRYgmNPOJYAVcuHoj/2LZRn2mn1106S5UP++bKAU412iBkvQlyJdkovS0F2clkYSXwQunRgLB/hLmhWlMu6XYRzsTd/jhP8lzkBwaDXKfTWlwmej0OPgDDYd7RRdXEmI8sHAHTJE9pdVduiOtNhRQ4rUKKJ0kycG47b5cdnga//DLw5Afh1rfZxu5cEnzcfB6rWh9XGcPzm6pYP4X1W2Y2AxAcRfdjFLEUkS0AYN2PVmA/Fa3EMCu7XsnwYxzppWU3YQodqRSDVKGAsH8mwuByJD0KXXgWZ0nOHLbyfS2cm3VbMbBDjPgCm1HG28SCgV6qYpVsgZuOgRrZKJzPiI1c8R7PmctWie6aqVjsrJhJCUm3DKX++8UPxLMDaedrHHdoqf733hzBayKYrGgsGnvGm3HpebwDAw5cOkrblZ4om6OSYlRFtCzXXRKdWLC5nIuRDivkQ0bLWirWQDhyXT2DMWD7YhfH8WoOUAtHy4fL6NdfkiickPghdxDLffx7XL+z3srU+RAUvpsMCaos8ad/EJJ+tQQ8TP7OmvkU1WNTI7QIEg05/Pd6sGcwlChS9lNxIkAbLwEUSA8wMaakDDlcEX+9Zon3s4W3CY34f4fHgz2G1sVMYa7KwM8bbz++DVX85H787PRi3kx9m9gxBhIPa5KVAI+bCzHlYlNaJLjlpsoma1oSpV2cxAL9Btp3N0tOyZojCpZoZ54wSAtgVpJMh7oPEB6GLT+ErDYfCHDbmQ9wmz4ABgK4BK8J+newRpRtC8zNzmU6pIljMWD56M4OC1qSiq+iaiZHbxacwE7Nr5eiaiQ+sA8ADGfkAZxXiOuoOqB97bLfwOOi3wmP1prDaKM6kDpkYyNhB22rhZFYxgGp9ELHFr+K2FX+/4UwgzLhdLBYOp/fsyOxXH7T6BWJD9hxplGWMsdYVLeEiurRr6ltMT8wAJu6DxAeR7Ig3QVsrxAdr+RD7bBcmDkTsK30CnVA5A2Ax69dkLR/SxzBvOakgU/mWEAYUCe3ZVh1sT8jsRnTNxMntYrMGu6ruZx5YIzyeNAYoCqQjVy4Hju4Cfn4f8AYGHb8fqA+Ikn6/ER6P7QZcJ0y3sXNgIGOvtRbyAVWluFsY5yKIcBHHD3YSJY4FYkqsGcyk2gLAmX2CgdtaQ2eX3DQ4bRZ4/bzsd28mHqOItXyYdEkDrYtziRUkPghdvP7QGYNZ2OBOMR1THoQqnFPMgtlRoz0ISAFjBr9YyRxZ16K60PSZvTvh5jG98NTlJ2ueo19AfOw72qSZzSJ+j1hZPvTS58QaJBLuJiGw1NMM/BoQH92GAz3OEJ7/8gHw8jnAxzcCH/9R2NZ4GPC5Ac4CFA0FsooA8MChLabbyM6+jOANLFfdpPoqJD6I6KO2zkq/IqG2DTvJMEI11VblNy2rm6MxdnIcJ7l4DzB9Wl7nQ70dhdIky6Vq1dGioJUL6sUCEh+ELuJN32YNX3ywswzxxy5aDIDgjUgsDvbrcT23i/BoVMWP7ZRqq0pyHIe7f9Mfk4Z11zxHfpZTmolXBAamELdLzGM+RLEV/OSrAjESt57fJ3ggzwPvXgn8+zzgvcnAr6uF7d1HACWjhOc7FgLuwAC7+WPBClL3q/A6uwtgtQNFg4XX1RtNt5GdfRl/H+FRa4CU4myUwoogooDSjQkAfQuzwHGCq89M3BKg5XYJ/U33LwqKD70ifJL7lhUfsoBT/ZgPt9eP44EFLs3MD8XlI7QC8uMJiQ9CF28g4rQ1MR8shwI1HVhXjNgp2cJeJzQsDWZjPsTZ+AmX13QUuBr9uwiDx+q9x4RTKANO8+Rl2KON2mD52G8HY8295Tinb0Fw44F1wJ6lwvNdi4Gmo4DVIbhcSsrkJ7UEgla3LwTqA+Ijp5vwWBgQH62xfNS54DUoDmY0OxOrxoZYdQgiCqi5bTMcNmnJhwodly+L2C/Z4otqYxYb2K5nGRQnMXLxwQacqr/PYbNIdXbEdH/ViZnrhPDlG6oBn1f6vnrxdfGCxAehSyQxHwBw1enFAIBpY4T0SnZZe7HOQ3YaUzdD4+Zjps4HAGQ5bdK6ByLh1icBgAsGdAYA7DoslmqXn0McNE64vKhvif5aCWqDJcdxoQGzu78LfXPpOYA9DcjqDAyeJGzrMw4of0B4vmtx0PKRG7AAieKjZrPpNnbNTUemwwq3z69b0h4wTpUWLR+HG1xo8fhMt4EgzKA1eRELgm036XoRJzTsGHNAZcxihYBeLaCg24WN+VA/jxLR+iFOgGRH8jzw/u+B2d2Af/QFnuoHvDAKvTKEY2NZndksJD4IXSKJ+QCAx347BL88OBYnF+cBkHemZuYmI97Mfz2u3lHNlhAG5HElrWX8kC6y18qPTXcEF86LRdCp2bom2L9SeDz7z4IVw+oAyqYH9//2ZWDKF8CVbwO9zhe27f0ROLpTeC6Jj0DNjZrN6o5tFSwWDgMCFqLNVfW6xxoFDHfIsCM9sPBfrFxZRPtFy20rLka5z6QlQFkp1Qx61tFueSqWD2a/3qeILhvRNSxr0r6fgK2fC88bDwmPR3dg6K4XAQiWj0QXGiPxQejia23MR/NxwO8Hx3Gy5aK16BsI8txyUP0mZvpmjODquSKt0U2dspzSwKRFkTTz0J7Z+P18qzq5abEl1vQ4aQwwbQVw53ag17nB/VY7UHoWYHMAnQcAWYWAtxnY8pmwP1ewTKFTH8Et46oH6vabbqf4fzPKGDBymwnBd6H+b4KIBlqiobvkhjD3mxNj4DgOkrVWi9NLhXTbS4Z21TxGuZAlYLyqrciYfoJ1doe0gB1z8M5FwmOnfsD4vwOXPg8AyN3+X6TBhQaX13Axz1hD4oPQRRQfVqM0E5YfnwOeKAVeGydkYihg63+IDO2WCwBYX3lc9ZThWD56KioMhqU9ThwCfIIPV5zVa51DHDj2argcfH4eFz2/DJe/tDxsASINlnrf19Mi1PEAhEJhaTlAegft4zkOKA4sHNd0RHjs0EN4tNqBgv7C8zBcL6WBa73nqL7bxUyqdLcOgRuBTuAxQbQGrWwrMdbom601ppZKEMchK8ehe4cM3WP/PWU4Xrl6GG49v7d8h7sJ+N99wKe3oFu6kAV4oDZY0FCe7aLdX2SxX1CMUQd/ER5H3QSMvBE45fdATndw7hMYn7UDgHlrT6wg8UHoIrpddG+CLA01wLd/A8ADv64CVr4UcojSMgEAZb3yAQBLdxxRjaEwStVk6dlJafkw2fY18wT/6MtnAS11smqsaqcYESgk9PF69SJehxtc2HqwHmv2HZfiW8xiKrX42G4APODMEeI7zCCKD5GOvYLPJdeL+WJjYqaSlgATMWO5Ei1Nuw3ORRDhIsZDK8eCgcwE492VlYbnYQOnRZeJFjlpdowdVASnzSrfsfhh4KfngPVvoeSnv8DCAU1un1R7I5ylJERXpXA88waxDxcNFR4tFqBPOQDgAocwudhnMGGINSQ+CF2Clg+TN/BN/xXqR4hsmB8SQzBaZeXUQV1zUNIxA26vHz/vrw3ZH04uu3JtBVN43cA3D0KqdbF8rlx8qNg+Lj1FMKdurqpXTadj0/J2HTZfyEh4b+Bz9b7vke3CY6c+5n1LSvEhWj4AoHCg8BiO5SMg9PYeadS17ijLxashriO06xCJDyK6aLn9CnPScMu5gmXi++2HTZ+H44DzB5gU/CwtdcC6N6SX1i2f4LQcIWZj75GAJUKqWKqPxcJJ1ZjFNgEQ6v2cqBGedzwp+IZAzNcI33oA2i7ueEHiQwHP83hn5T6s0zD/tzfCznap+Ep4PPevgC0NOLojZM2QaWN644/nnIT3bxwlbeM4DgO6iJVOQ2/UZut8AEFXgHRuM+3etwxoqQ2+3vCudGMVPjf0LV1z05DpsMLr51VnER4m/TR88WHC0nNUMJ9Ka7OYoQtTXM2ZI7hbRNigU5YD64BXxgh1RJoD/aL5OFC7H8UdM2DhgEZm5qaGmWylkwKLDu4O81oRhBF6kxex5k9FdYNhBVN2Mnbl8GL87bJB+PK2M+UHnTgsuW5D2PYV4GkSYjF6ngWAx6Q0oTDgoi3VAIJuFzNjHSs+pLFCzGSzZ8rdsCedA3BWFLgq0RVHVCd58YTEh4I1+47jrx9vwsQXfkp0U5ICqbOZCThtOiZEWQPA0CuAvoGy3Zs/lh3msFkwa/wAjDwpX7ZdTHvboZJzH4wZMG5G17w0mVgwZRTYHyjONeBSwJEF1FWijztY86LJHZr+yXEceottVgm4ZK0hu8Io4QyYjPk4EshY6dRb+xglNgcw9hEAHPBbhUtMTLc9ulOYPQFCGfb/Xg9UrQe2fQEsmCVUUX1mMDBnCJzrXmNiX4yLxOn9/8QVj/cda9ItzEQQ4aIXc1TSMQNOmwUur9+w/gV7HouFw9VlPTGoa27wgJUvA//oLbhum1UmsFs+ER4HTwQGTQAAjONWAAD+u+4AeJ5n1qQyRmb5EN8hBoznFcsHv7RcoNtpAIAyyxbsPKRvrYw1JD4U1DERwMfDWO2wrRJWzMfqVwHeJxS46tATGHCJsH37AlOfpbfGSzhuF5vVIrN+SJ3yxGFg/u+EGfwJhYlVXBOl55lA/4sBANk7P5d2y+pY8Lwwu/D70VenNLybsXzsbKXlQ3f2I1o+OvUN69w441bgrweB/hfJt2cVCgvS8f5gsbG9S4Fju4LH/Pwu8O/zAfcJADywYBZGdBRSCX//6kpsrqpr9fcpzHEi02GFz8+j8hi5XojooVYxWMRq4dCnUOjHRsXG9M4D1wng20eE54e2AD88Jd/fUgfs+lZ4PvAyYaIDDh1rN6Kb5RiONboVq9Qaj3VszIpEbUB8iJlsLKVnAwDuG3QYK2adZz4eLgaQ+FBgZ5ZC3ppgn1gy4DfjduF54PPbge8CHW/4VOGx9/nCyqqHtwHH9hh+Vt/AALDxQJ30ucGPMBGE5fMK1heel9ZnkfHNA8D2r4UZ/Bcz5O0/sFZ43m2YMDAAgok0MBBUsjOiz28HnhkEvHkp+hUImTs7DoUOWh5f8DtsO2hs0mUxzO7heeBIK9wuInaVYDmOE74/AFQKszGsDfinh08FBk0MHpvdBSgYAPg9+D/rNwAES8/U19eofpwZNxLHcZIAXbev1vRXIdovbq8fX/5y0LA8upHlzWyxMbXKwxKVK4RUdZH1bwcXcgSAigVCPFynfoG0985A8ekAgCtzBLG/+UB9WJWZxUB9ANggulFEy4dYw4clID7yala0unBktCDxoYA19xoVTmoPaJZX53lg9xKhVPfmj4C1rwPggJE3AaddIxyT3iG4uJkJ60dpp0w4bRZ4fDzeWrFPts8w5qOlHnjlHODJUuCjG6WVaYU3QQgo3fTf4LZtXwhrnABA7T6hLLnFLlhtep0L2DOAukqcn1cj/5yDvwQDxvb+gDF1nwBQD95iYz6ONrqxas8xo0vAfF+Dm/WJQ4GBjpMHlUVKj9HC49YvhFgdsVDRsCnA+fcLcSL2TOCyfwJj7gYAnHroE9gg+Lir61s0spUQ+D76A975/YUgvoWbq6PwZYi2zvyV+zB9/jpc/vJy3eOMLKfi8vbbDC0fwqOqJbg6kN46cIJQ8K/5uDDOiIhWjwEXB7cFXNMX2ITJz6aqOtU1qWQ01ABf3wN8PgNpTQelzUdEASbGfOSpWD6KRwqFCOsPBLLlEgeJDwWs+Eh0NHAyoFlk7Mc5wJuXAvOvAP5znbDtnLuA8U8AFia1TIz7EANRdXDarPj9KCH74ttth2T7DG/GPz4bTC/b+AEm2n+UdlktnDAweFsEt0LvC4Qda14THsWVYIuGADanYBXodR4A4B9DfsUpxXn41zXDhWMUIqp09zuwwI/dhxtR2yR30ynjFt5asVfv68uQbtZaX1h0ueSVCKXUo8XAywBwQOVPwMtnA36PYA3pcjLQsRSYsRGYuRnoXQ70vwTI7Axby1H875Kg4Bjz9+9DrDyGbrPje4HKlTg7sBT5usrjCa/ASCQ/S3cI9Wp2HzZI9dazWAAYGFiF1siKovs7Fhdl7HoKcMr/Cc9/fj+4X6xGLE7IAKDfeABAn6b1SEcLNh2oD8Z8KD+iuRZYdD/wYhmw8kVg7TzgjUvx5c3D0S0vHf8QV+qW3C4loW20pwcz3vYs0fye8YDEhwK3LxhYmOho4GRAtbx6Sx2w5O/yAzv1A868I/QEgc6FfT8J7zPgskD66pq9x1DXHLyh6boh/H7g5/eE54VDAADdf5mLm8/uietGlwrrMOxfJezvPgIYcb3wfMM7QqEu1uUiEoj76FC5CJ9MH40LBhYK2ysDM6wL/gakd4C1rhL/lyeYTNdX1sqa5VYstvbVxmrM+9HY/QSw5l2N0fJIK+M9jOhYCoyZJViBOCvQeRBw2QvB/el5wQh6qw0YcjkA4KQDn2FwN2EAP9boxhe/VMlO69caUAFg+/+A504DXhuLwRsehMNqwfEmDxZtqVE5mEgkfj+PX48nvjS3COte1auMa2Q5Hdo9T3p+/2faqea6NThE8VE0BBhyhfB812Kg8ahgqTy+BwAnjEEiBf2BDj1h87txlmVjQHQLu2R9X1yr5cdnBSttfm8hgPTYLgyqfAc/3nMeJpwaWCSSDThVI+B6wW4SH0kFO1vdfaRRWgq+veH382ho8TAxH8xPZctngKdREBw3fAeMewy49kv1OIL8XsIN0u8Fdn5j+LkDugj1PhrdPry1fK+0XbfI2L5lwiqtzlzgmk+AtDzg6A7c3WM77r8kULtCWmp+ONDnAiCnu2AW3fJJ0DTKzkj6jhNuvjUbhVk5APh9wayYXucCp14NAJhsXQwAIenZnsBv6dSSPIzoKdywH/p8i2FBLsCEpefQVuEx2uIDENwpfzkA3H8UmPYT0Lm/9rEnXyk8VizAnWcVSpv/t1kuHDRnjDwP/O9eIVAZgHXd6/hTH8GU/PSi7UlzkyME/rvuV5z5xHf457c7E90UAHL3x9p92uURjLLHctODawt9u/WQ5u9Os+6RuzG4XlLRUKCgr2At9HuFMUa0enQeKIgGEY4D+goTtLG29TjW6JaCXmWfsHcZsPcHoXzBxH8BN/0IjH9S2Pfjs0KwKyCMUfWBoodqMR9AUHzs/UGYuCWIdiU+DjW0GNbvUJrKP1r3ayyblLQ88NlmDHvkG1QFFkWSdTbRhTLkciF1q2w6kFWgcpYAoutl6xfCzcarLejsVgtuPFuIYfi+IpiRopstIZo2B00AMjsBp98ovF42J+i/EF0r3UcIbqHTBOGAj/8olCh3ZAmCQySjY1CMbAt835rNgLtBiHvoPBAYdi0AoH/jKnTnDmP5rqOyZokBpw6rBRNPCw4E32w1ntEbxkiI/uUuQw3P1SpsTnM5ykVDhWvhc2GM90e8e4NQu+XLjQeDPmjoiMdDW4AjFcKgOvR3AIDrm15Fmg3YVt1AcVdJxt8XCmsJPbVoe4JbIsBaF5fvPqp5nPT707njrb//AtgsHJo9Ps0qu5r98tBWADyQ2TlYbThgFcTGD4PiIxBgKqOfGPexARz8WBoodiYb6zZ+IDwOvVIoY2BPE87fsZdQn2jDO8L+hmpB8FhsQlC4Gl1PA867D7jqPY0rER/ajfj4cecRjHpsMe54f4PubMqlEB/zftwrCxxsL7y1Yp9MiEniw+sG9iwVngfK9Roy6LfC4+aPgOeHAY90Bl6/WAicAgTV/sVM4K2JwM7F0poFa/Ydx9uBwFNNt0tDdTCQ9GTh5oWRfwRs6cDBDYJfs/EoUBcondz1VOFxxA3BVDR7BnDZXMChqIwqpqKK5xetJ91OEwRMfi/gpDHgwON31m+xrvI4jjHp2eLvxmGz4P8N6y6tafPIl1vxjYFLQdfy4WkJrt1QFCPxYRaOC173X97H8J7BokajHlssPdf8/237UnjsdR7wm9mAMwfWQ5twRzfh5vb1poMgkoeh3YOz9mRYANDFrIz99caDmmO1qtvF1QB89EfgpTOBXz5Emt0qLZnwnSLmLHgejVRbcTJQNCS4bfAkwXpauRxY87qwTVlhGABKzgCcOcj11+JUbqcUbC99As8DOwJWYzETDxDGIHEF6+X/FLL9RJdLTld57B2LzQGcfacghMJZsyvKtBvxcWpJHpw2K/YdbcLXm7Qj6UXxMeGUruiU5UB1fQsuf0k/kro9IImPX1cJNR4yOgFFJ+u/SaTbacBJ5wrPxZoRe38QAlabjgGf3ASseVXwj75zOYrr1yEnsGLkvZ9sgtvrV78Ze13A+1cLq7R2Gw6UlAnbMzsFLRvL5gAH1wvPO/YKmjwz84GbfwQm/xe4Y7NU8EfGoIlC7MOBNUKVz6p1ge8zPHjMsD8AAP7PvhQW3isLlBXFm91qgd1qweI/jZG+1/VvrsESnXLOUswH+4Vb6oAP/wA81kVwe+V0Dy4Gl0iGXA4hSHU57LV7MKafIB69fl6qj8KuBipDdHn1u1CwNo28CQBwVfM74ODHVxuryfWSRLDrlCRDTA47WTze5MGynUdUj1N1+y16APjlPSFW46MbgC2fYdwgwXX40pJdcHlDCwtqptqy8R4iOV2BgZcKz92BLBrWtStic0ixcb9PWxbcLn7G4W1AQ5VgHVS+/5T/E4LoayuBrZ8FM/g69Az9nCSj3YiPDIcNYwM/rGnvrMOcb7ajWaVqpXjDyHTacOEQwWy1YX8tNh0wDpZsS+Rl2GWvpZzwnYHZbK/zwlPNl78upGr+5gnguv8JJsHD24TU2K2fCzOELqcIvv//TMXTFwfdFA9+vhmNLiGVUzZ4rHpFEENpeUK1TnZf2S3COXd/ByyfK2zreoq8TWm5gvUmo6N6m7MLhUqEgLAQ1AFRfLCBqRcBWYXoyB/HZZaf8PT/KiTrh2gStgcyhbKcNnx2S7AU85TXVsmLlzGoWgq+uEOwHvGBAXfUTQmduUjkdBWyXwBgxYt45opTpF1vLdexXNXuF9J5OUswMLlsGuDMRU79DlxiX4M9RxoNCz8R8aPRHSwb/t8kcEkrLdWfb6hSPS5ENLgagPVvCc8LBwPggU9uxuQ+HnTOduLICTdufzfUSi6+DIkdqRYXchsi3152S/B519PkaymxBMoTXGz5CVloCrQ18Bliim6P0aFxdfb0oJv5p+cFFyYgxOMlOUkwcsWPO8cG/yFzvtmBu//7S8gxbsZUfue44PF/+2JLu5qBKVMlJcvHroD46H1+eCdMzwPO+pNwwywZCfz+v4CDqcVx5h3AH74SOs2JapTveBQ3nlUKAJi/shILAwGMUp9vqQOW/kN4PvYRYXE1lg49pJgMqfN2OSW8NgNCNVBwQol4sepnoEQxAGFtlFHTAAAznZ/gUN0JPBPwhwfdLsHZYs9Omfj3NUHLyRUvL1ctPhYSI3F0V8D9wwkC7qr35QNbojnjVuFx/dvo4D+O1/8gRPS/uXyvbNE5mfgQ66WUlAnWKkDIpBl1MwDg7rRPwMGP91fvj8tXIIxpcgUnbL/8WoevNybWLSZaJy49WciS+3pTtWpl6pBYjd3fCwW/OpQCNy4R1llxn4D9v9fh8lMEy92CzdWY9dFGWf/0qcWe+bzB9ZCU4qP7cCEwtNd5Qm0cLXqMBjr1hcPXhGus/wOAYLYfO+FTY8T1glWkah2w6t/CtlgEokeZdiU+ijtm4Ie7zpVef/ZzFXYq1twQLR8OmwU5aXZ8f+cYpNktWLnnGEpnfYV3VsqLX7VFeJ6XrWWSk2ZDfpZDSBcTF4nT6ghmKRwE/O4dYdYx4npgzD1CzMWkfwuujoovcVP2DyFvkwaP1f8WAq069Qvm1CsZM0uI5xDpOTr8dhYNCcY0AEBeDyC7SH7MiOuBzAJ046txo/VLvLViH6a/sw7HA6X67YoaKeUDC/HkJCFW43CDCx+sEW6uLR4fvq84hEVbaiQRLA1yYipxr/MEAdfvN+ZXso0HpWcL7ihvM7D4YZzTtwDn9C2A18/jiQXbsCIQDCgNqK4GwXIFSK4WiVE3A85cdPPsxaWWn/Deqv2yWBoicYiWj05ZDgDArI83qhaVixcuj9BPzuiVj0Fdc9Ds8eH1n/Ya15nZvlB47DtOSBmf+C/BlVyzETc1vQKxsvF7q/fjtnfXS+JZ1f17YK3gBk3LFVJglYz8I3D1x8GFG9XgOODsuwAA0xxfoiPq0S0vXVhjaV+gZpHWhC+zU3AM9AQsqSWj1I9NItqV+AAEAfLwZcEfwcNfbMGG/bVSgShRfDitwqXp2SkTk0cGTWUPfb4F26rrcfSEC0u3Hw4pA94WcHn9Uudddve5+O7OMchw2IBd3wkHFA0JRnRHwknnCHEXFz0VXF21y1DBPQOg45J7sfkaB/ooV250NwHLA7UnzvqTdmBVVgFw8TPCrGDAJXJ3SThc8HAwOHX0baH7nVnA2EcBADPsH6GUO4gvNx7Ec4uFWhwOa2g3u2JEMW47TxioZn20ET3v+RL971uAa+etxg1vrsFH6w4ED/b7gV8CGT1aQivRcJwQMAoAG94Gt/UzzCgXrFFfb6rGc4HUzOp6IXsKa98QrFf5vUPXmEnPA0YLlpS/Od9Cjucw/vLRRslNyvO8qsuUiB2bq+rw+o97UBsQ1E9dcQpKO2WitsmDMx//FofqW3CwLvIAVJ+fxy3z1+Hxr7eZsjSLbpc0uxU3ndMLAPDs4h3o9Zev8Ow3O6TjZOXVeR7YsUjY0Ges8JjTBZj4CgAO2Zvfxi/n/oLLh3WH3crhy40HMeYf32NzVR28PkWqrdcNLA2kvPY6X3ssMsPgiUDhEGTxjZjf7b94+vKhQnC/t8U4vuucu4P1dzoPCrXAJCHtTnwAwDVlPfHNzHPgtFmwdPthTJj7Iy7954841NAis3yITD+3N84I1NB3e/2Y+MJPGPbIN7jmtVXoe+/XeODTTWhifKGpDjuwd8lNR36WkKUhuVx6helyCZeyW4Sobp8bmR9fg3+PDAZxFmSnCb7apiOCFWLwJP1znfw74N4a4Mq3W9+erM7AtBXAzcuD69YoGXoF0Os8OODBK/ankYugRa3Zo36jnMb8rrRweXxCtdHafYKbqt+Frf4aMaf49KAr6D9TcWrV+5gxpqfskKtH9RAGbDEO54zb1AfsM24HioYgh2/APOffsXzzTgy4fwEGP7AQFz+/DKf+7X8JN/m3J+7/dDMe/HwLDgQyXDplOTBrvHAzrG/x4vTHFqNs9rf49w+RlezeerAeX/xyEC8t2YV5P+41PF50uzhtFlw4pAtOZrJxnvlmO+79ZCNaPD655ePgz8CJamGZgJ7BGCz0Ph8YJ0wicpY/gb/nfIB7xgoThH1Hm3DRc8vwQKAAmWRB+eEpoX6R1aFeZDEcLFbgsucBzor+Rxdh5K/zghWV+47Tt3RmFwFTFwkptL//T3JZRTWImfiYO3cuevbsibS0NIwcORKrVq2K1UeZZ+nfhapu7kb07pSBey8aIO2qPNaE0Y9/i/cDJnA7M1vtmOnA/BtG4ef7x6JP5yyZS8Lr5/HG8n0Y/sg3eOH7nfjs56qUXw5cNK06bRa5whdNlWJwYaywWAQzaO9ywNOEHouux8+nfYV5l5dg3IB8Ia0MEKwQVlts2yLizAIKB2p3ao4TKoFmd0UfywF8k/cYBnJ7AQBFuYHy5zwvDFTfPw4s/QfStn2Ml8dlYsLQoBWpa24aZl7QF2f0ykevgkyhauGG+cLOwb8FHBlIasofElKr/R5gwd2YUTEZXwxbh8v6OPHEpCH424TBQs2Chiogq0ju0mKxOYAr3gQyCzCQ24fPHX/FKdxOnHB5sbmqHi0eP257bz0+Wvcr6po8+PKXg9KNkYg+ygJemQ4bLhhYiD+M7inb/siXW/HW8r2tjo+rES1jEKzSD3y6SXc8lSzVdmGseu3aEZjE1NR5e0UlLnl+mVSfxGIBsEOIqcBJY4R6Nixl04HzHxCeL/8npu6YjmfPDv0uDS6vsFjmsmeEDZfNjU7Nna6nAr95XHj+3SPBJSDEWkl6dOojpNDmdI28HXGA42MQRfn+++/jmmuuwUsvvYSRI0dizpw5+PDDD1FRUYHOnfXN9fX19cjNzUVdXR1yclSWC24tO78B3pbPkvm8EuziSrDocAds54uxzV+MXXxXuGHHA5cMxB9GFAIrXwLWvSnkT6d3gCuvNz4/1Ak/NXVHdulwvL3TAR/kM7fijum4YEARBnTJRp/CbBxucOGMXvnIdMbpRhkGn6w/gMe/3oZhPTvgutGlGNQ1B5XHmjD2maXokGHH+vsDZsm1bwCf3yYU0fnTtsjMi2bxeYCFfwVWvSy8ttiEFLKjO4X0sjs2q1dVTSSHtgr1ShqqwHNWbM47D0WjLkennExhoDqgsuqrLU1Y5bJoiFC3o2iI8NqeISwS9cIowfR63cKU8OXC7xdSp79/XLBQAUIcT+nZgpl7xQuCJeeCh4HRt+ufq2Yz+HevAlcrxFp95R+FnztfilW+flh/UF6szmG14OKhXTB2UBFOL+2I7DSbbBJBtA6Pz4++934tBW3arRzW3ncBctLswOEKVG9bgZ92HsaCSg5bWvJxkO8IH6w4uTgPZSflg+d5ZDltKO6YgTN65aNzjvZaRO+uqsSsjzaGbO9XmI3Lh3eHy+vHtuoGjOjZAb8ZXISr/70KFTUNeOf6kRjdu5Ng1dj2JfimY/ih2oZ3d6dhu78rKvlCeGDDFcO64ckjtwiViy95NhiUrmTzx8An06UYCn/X07A5cxQe35yLnf5uGDNsKJ7wzBZWyS49B7jm0+haG5bNEVbhBoSFI6etCBVKSUg49++YiI+RI0dixIgR+Oc/hRmq3+9HcXExbr31Vtxzzz26742Z+GipE1YC/OV9qZSzGj5YsB9F6Ny5EBkNe4US3DrwtjTw6fk47HHgQJMVLbwDzXCiBXa0wIEW3okWOOC2OJGXk4OOOTmwp2fCzTmRmZkFe1omeFsaYEuHx+qEF4JA4TgOHAdYOAs4joOFg/Ro4bjAcwssFnE7Jz23goPFYgHHCZPtN1bsQ0V1Pbp3yEBpfgaKO6Qh02FBho3Do19ugRU+2OGDDV6kW31Ihwec34OOmQ7MvriXkD8u1mMofzBy82K47P0RWPxQsEogIGR8jLpJ+z2JpKEaWHCPMIApsaULLiWLVRBRNZuFuilGlJQBf/g6JcypEq4TwKb/CCseV62X78vIB27bAKSZ6ONNx4CFfwF+flfaxFtsOGHriP0t6ajlM1GLLNTzGWhEOhrhRAvvhN9ih93pRHpaOhwOJ2BzIiczA7/W+3C0hUdmejpysrNgtViR6bShU7YTVqsN6Q4bWrw+eH0Az1lgs1ngtNlg4Tg47VY47Fa4PH7wPOCwcXBYrUI9Fo4Dh0B5Bk545DiAAyfPjpC2Bfq5WNCBeVBW8uU4pugUZ2GOC55L+dvgeeBYowsurx92mxU2qwV2Cwe7NXA8mDZzHLZV1+PXY83Iy3Qgx2kB73HB6neB97rw7++3IZ3z4q/jTgK8LTgJVcCOhcEAdAYPb0UVn49DyMNRPhdH+RwcRTaO89logQN5WZnITE9HWnoaTngsyMnMQF52JrIz0/D1lqPYe6QR5QM6Y2TPXLz/7Sp08lSjgKuFSxpTHXDDDjdscMEOL2/FbeeWovTYD8FVmBV4eQsq+UJ06NgJHWo3Cv1w5hbtNHsAqDsgjDub/itUDWWvrcUGTqwkevNPQEEMUlv3/igUSRxyeWg2X5KSUPHhdruRkZGB//znP5gwYYK0fcqUKaitrcWnn34qO97lcsHlCs5g6uvrUVxcHH3xIeL3CbNIV4Mw+B/aKqRQHtoK1GwBXIp6HnklQtZEzzOFQfDQFqHDHfxFqGpn5sbRVjjl98Alc4LBofHmcIVgwepQKtSFSPYbcdV6YMO7gmhqOiosVnfmHUL9EBG/X1hwqnqj/K+BqVfQqS/wfx8Ii76lKoe3AxVfCoF+vF+weqiVmtajeqNght76BdCoXoGSiDMWG1A8SvBn1FcJxa58icxM4oQA5k59hTVOjmwXFmFUjtPn3y8Eq5vhxCFB1Oz7EajaIKz1xPuEOkLjnwBOvyHaXyJlSaj4qKqqQrdu3fDTTz+hrKxM2n7XXXdhyZIlWLlypez4Bx98EA899FDIeWImPvTgeaEDHdstWEocmUL+t1Zcgd8vmI+bjwtixn1CSI3ytgiPnmZ43c2weptRW1+P43V1aGo8Ad7bAoe/BbynGTZfC+y8Cw7eDSfvghVBhc0BAA/w4GWLDPEAODD/tpB/YfC1eJzNYoHNAvh4Dl6egx/CH8DBZrcjKz0NvMUOD2xo5m3wwIaOmU5YLFbBD3naFP0Fxojo4moIzrbS8pJfaMUTsZ+eqBEmBC21Qh9sqQXcjeBdJ+BxNcHjdsHjakFLSzNcLhesvAc+rwsZFj8cnBfwucF7XYDfD57n4fP7wfHCc47jAwFxvNCHeB4IPAr9j2kOAI7pg8reyIVs0TrS6Hi25Lb83Vrv4TghsI/dywdesecSN4jFs3gAXs4ONydYGVy8HdmZmeiUlyPE4+R0E6xx/S8WqgWL+P1Aw0FhXGw8HPg7Ijw2HYXb1YL6E43wet3gvR7Y4YHP44bf6wbndwM+LzgO6JiZBrvNCmQVCq7W7CIhjsjdJIyvXhe8nhY0nGiEDT5kOwPLHQyfKsRmyS4zL7TpcIXwu+nQQx5oGi5et+CGd+bor2nVDglHfCQ8CGHWrFmYOXOm9Fq0fCQEjgNyuwl/ZrBYArNR7RmpeIE7BP4SjZ7NggPgCPwRCcaZbXxMe8Wgn9LvOIFYLLr/GweATlH6KBtMjqkcJwRhRisQ0+YQhA4REVEXH506dYLVakVNjbzuf01NDYqKikKOdzqdcDqTP5CGIAiCIIjoEPVQcIfDgWHDhmHxYmZFS78fixcvlrlhCIIgCIJon8TE7TJz5kxMmTIFw4cPx+mnn445c+agsbERf/jDH2LxcQRBEARBpBAxER9XXnklDh8+jPvvvx/V1dU45ZRTsGDBAhQWFhq/mSAIgiCINk1M6nxEQszqfBAEQRAEETPCuX9T+T+CIAiCIOIKiQ+CIAiCIOIKiQ+CIAiCIOIKiQ+CIAiCIOIKiQ+CIAiCIOIKiQ+CIAiCIOIKiQ+CIAiCIOIKiQ+CIAiCIOIKiQ+CIAiCIOJKTMqrR4JYcLW+vj7BLSEIgiAIwizifdtM4fSkEx8NDQ0AgOLi4gS3hCAIgiCIcGloaEBubq7uMUm3tovf70dVVRWys7PBcVxUz11fX4/i4mLs37+f1o2JIXSd4wNd5/hB1zo+0HWOD7G6zjzPo6GhAV27doXFoh/VkXSWD4vFgu7du8f0M3JycuiHHQfoOscHus7xg651fKDrHB9icZ2NLB4iFHBKEARBEERcIfFBEARBEERcaVfiw+l04oEHHoDT6Ux0U9o0dJ3jA13n+EHXOj7QdY4PyXCdky7glCAIgiCItk27snwQBEEQBJF4SHwQBEEQBBFXSHwQBEEQBBFXSHwQBEEQBBFX2o34mDt3Lnr27Im0tDSMHDkSq1atSnSTUorZs2djxIgRyM7ORufOnTFhwgRUVFTIjmlpacH06dORn5+PrKwsTJo0CTU1NbJjKisrcdFFFyEjIwOdO3fGn//8Z3i93nh+lZTi8ccfB8dxmDFjhrSNrnP0OHDgAH7/+98jPz8f6enpGDJkCNasWSPt53ke999/P7p06YL09HSUl5djx44dsnMcO3YMkydPRk5ODvLy8jB16lScOHEi3l8lafH5fLjvvvtQWlqK9PR09OrVC3/7299k63/QdQ6fpUuX4pJLLkHXrl3BcRw++eQT2f5oXdNffvkFZ511FtLS0lBcXIwnn3wyOl+Abwe89957vMPh4F977TV+8+bN/A033MDn5eXxNTU1iW5ayjBu3Dh+3rx5/KZNm/gNGzbwF154IV9SUsKfOHFCOuamm27ii4uL+cWLF/Nr1qzhR40axZ9xxhnSfq/Xyw8ePJgvLy/n169fz3/11Vd8p06d+FmzZiXiKyU9q1at4nv27MkPHTqUv/3226XtdJ2jw7Fjx/gePXrw1157Lb9y5Up+9+7d/MKFC/mdO3dKxzz++ON8bm4u/8knn/A///wzf+mll/KlpaV8c3OzdMxvfvMb/uSTT+ZXrFjB//DDD3zv3r35q666KhFfKSl59NFH+fz8fP6LL77g9+zZw3/44Yd8VlYW/+yzz0rH0HUOn6+++or/61//yn/00Uc8AP7jjz+W7Y/GNa2rq+MLCwv5yZMn85s2beLfffddPj09nX/55Zcjbn+7EB+nn346P336dOm1z+fju3btys+ePTuBrUptDh06xAPglyxZwvM8z9fW1vJ2u53/8MMPpWO2bt3KA+CXL1/O87zQWSwWC19dXS0d8+KLL/I5OTm8y+WK7xdIchoaGvg+ffrwixYt4s855xxJfNB1jh533303f+aZZ2ru9/v9fFFREf/3v/9d2lZbW8s7nU7+3Xff5Xme57ds2cID4FevXi0d8/XXX/Mcx/EHDhyIXeNTiIsuuoi/7rrrZNsmTpzIT548med5us7RQCk+onVNX3jhBb5Dhw6ycePuu+/m+/XrF3Gb27zbxe12Y+3atSgvL5e2WSwWlJeXY/ny5QlsWWpTV1cHAOjYsSMAYO3atfB4PLLr3L9/f5SUlEjXefny5RgyZAgKCwulY8aNG4f6+nps3rw5jq1PfqZPn46LLrpIdj0Bus7R5LPPPsPw4cNx+eWXo3Pnzjj11FPxr3/9S9q/Z88eVFdXy651bm4uRo4cKbvWeXl5GD58uHRMeXk5LBYLVq5cGb8vk8ScccYZWLx4MbZv3w4A+Pnnn7Fs2TKMHz8eAF3nWBCta7p8+XKcffbZcDgc0jHjxo1DRUUFjh8/HlEbk25huWhz5MgR+Hw+2UAMAIWFhdi2bVuCWpXa+P1+zJgxA6NHj8bgwYMBANXV1XA4HMjLy5MdW1hYiOrqaukYtf+DuI8QeO+997Bu3TqsXr06ZB9d5+ixe/duvPjii5g5cyb+8pe/YPXq1bjtttvgcDgwZcoU6VqpXUv2Wnfu3Fm232azoWPHjnStA9xzzz2or69H//79YbVa4fP58Oijj2Ly5MkAQNc5BkTrmlZXV6O0tDTkHOK+Dh06tLqNbV58ENFn+vTp2LRpE5YtW5boprQ59u/fj9tvvx2LFi1CWlpaopvTpvH7/Rg+fDgee+wxAMCpp56KTZs24aWXXsKUKVMS3Lq2wwcffIB33nkH8+fPx6BBg7BhwwbMmDEDXbt2pevcjmnzbpdOnTrBarWGZAPU1NSgqKgoQa1KXW655RZ88cUX+O6779C9e3dpe1FREdxuN2pra2XHs9e5qKhI9f8g7iMEt8qhQ4dw2mmnwWazwWazYcmSJXjuuedgs9lQWFhI1zlKdOnSBQMHDpRtGzBgACorKwEEr5Xe2FFUVIRDhw7J9nu9Xhw7doyudYA///nPuOeee/C73/0OQ4YMwdVXX4077rgDs2fPBkDXORZE65rGcixp8+LD4XBg2LBhWLx4sbTN7/dj8eLFKCsrS2DLUgue53HLLbfg448/xrfffhtiihs2bBjsdrvsOldUVKCyslK6zmVlZdi4caPsB79o0SLk5OSE3ATaK+effz42btyIDRs2SH/Dhw/H5MmTped0naPD6NGjQ9LFt2/fjh49egAASktLUVRUJLvW9fX1WLlypexa19bWYu3atdIx3377Lfx+P0aOHBmHb5H8NDU1wWKR32qsViv8fj8Aus6xIFrXtKysDEuXLoXH45GOWbRoEfr16xeRywVA+0m1dTqd/Ouvv85v2bKFv/HGG/m8vDxZNgChz80338zn5uby33//PX/w4EHpr6mpSTrmpptu4ktKSvhvv/2WX7NmDV9WVsaXlZVJ+8UU0LFjx/IbNmzgFyxYwBcUFFAKqAFstgvP03WOFqtWreJtNhv/6KOP8jt27ODfeecdPiMjg3/77belYx5//HE+Ly+P//TTT/lffvmFv+yyy1TTFU899VR+5cqV/LJly/g+ffq06xRQJVOmTOG7desmpdp+9NFHfKdOnfi77rpLOoauc/g0NDTw69ev59evX88D4J9++ml+/fr1/L59+3iej841ra2t5QsLC/mrr76a37RpE//ee+/xGRkZlGobDs8//zxfUlLCOxwO/vTTT+dXrFiR6CalFABU/+bNmycd09zczE+bNo3v0KEDn5GRwf/2t7/lDx48KDvP3r17+fHjx/Pp6el8p06d+D/96U+8x+OJ87dJLZTig65z9Pj888/5wYMH806nk+/fvz//yiuvyPb7/X7+vvvu4wsLC3mn08mff/75fEVFheyYo0eP8ldddRWflZXF5+Tk8H/4wx/4hoaGeH6NpKa+vp6//fbb+ZKSEj4tLY0/6aST+L/+9a+y9E26zuHz3XffqY7JU6ZM4Xk+etf0559/5s8880ze6XTy3bp14x9//PGotJ/jeabMHEEQBEEQRIxp8zEfBEEQBEEkFyQ+CIIgCIKIKyQ+CIIgCIKIKyQ+CIIgCIKIKyQ+CIIgCIKIKyQ+CIIgCIKIKyQ+CIIgCIKIKyQ+CIIgCIKIKyQ+CIIgCIKIKyQ+CIKIG2PGjMGMGTMS3QyCIBIMiQ+CIAiCIOIKre1CEERcuPbaa/HGG2/Itu3Zswc9e/ZMTIMIgkgYJD4IgogLdXV1GD9+PAYPHoyHH34YAFBQUACr1ZrglhEEEW9siW4AQRDtg9zcXDgcDmRkZKCoqCjRzSEIIoFQzAdBEARBEHGFxAdBEARBEHGFxAdBEHHD4XDA5/MluhkEQSQYEh8EQcSNnj17YuXKldi7dy+OHDkCv9+f6CYRBJEASHwQBBE37rzzTlitVgwcOBAFBQWorKxMdJMIgkgAlGpLEARBEERcIcsHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBxhcQHQRAEQRBx5f8D67Odm8Jx5vUAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "CONFIG3 = {\"noiseless\": False, \"bound\": 10}\n", + "trivial_agent = Msy(env=AsmEnv(config=CONFIG2), mortality=0)\n", + "no_harvest_episode_noisy = pd.DataFrame(\n", + " simulate_ep(env=AsmEnv(config=CONFIG2), agent=trivial_agent)\n", + ")\n", + "no_harvest_episode_noisy.plot(x='t', y=['total_biomass', 'surv_b_obs'])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "b01fb69b-9ac7-4faa-a564-98f729540690", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "no_harvest_episode_noisy.plot(x='t', y=['bare_surv_b_obs'])" + ] }, { "cell_type": "markdown", - "id": "9f766e75-f3ba-4fd5-a88a-4e31f9344d30", + "id": "05da3c77-fef4-4a21-b6c3-1884bab761fb", + "metadata": {}, + "source": [ + "Pretty much same dynamics, but now our bound used for observation space matches the scale at which observations happen. Let's optimize to find the optimal escapement---the escapement function plot should look less crammed." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "d16575ff-82ad-4350-90b7-d308246a1a96", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-10 22:25:13,894\tINFO worker.py:1752 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 5.0892\n", + "Function value obtained: -1.9766\n", + "Current minimum: -1.9766\n", + "Iteration No: 2 started. Evaluating function at random point.\n", + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 0.9183\n", + "Function value obtained: -2.4964\n", + "Current minimum: -2.4964\n", + "Iteration No: 3 started. Evaluating function at random point.\n", + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 0.8939\n", + "Function value obtained: -87.6669\n", + "Current minimum: -87.6669\n", + "Iteration No: 4 started. Evaluating function at random point.\n", + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 0.8825\n", + "Function value obtained: -12.3996\n", + "Current minimum: -87.6669\n", + "Iteration No: 5 started. Evaluating function at random point.\n", + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 0.7935\n", + "Function value obtained: -4.1797\n", + "Current minimum: -87.6669\n", + "Iteration No: 6 started. Evaluating function at random point.\n", + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 0.8511\n", + "Function value obtained: -1.9213\n", + "Current minimum: -87.6669\n", + "Iteration No: 7 started. Evaluating function at random point.\n", + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 0.8244\n", + "Function value obtained: -8.2361\n", + "Current minimum: -87.6669\n", + "Iteration No: 8 started. Evaluating function at random point.\n", + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 0.8970\n", + "Function value obtained: -1.9136\n", + "Current minimum: -87.6669\n", + "Iteration No: 9 started. Evaluating function at random point.\n", + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 0.9187\n", + "Function value obtained: -65.2409\n", + "Current minimum: -87.6669\n", + "Iteration No: 10 started. Evaluating function at random point.\n", + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 4.9578\n", + "Function value obtained: -83.8363\n", + "Current minimum: -87.6669\n", + "Iteration No: 11 started. Searching for the next optimal point.\n", + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4057\n", + "Function value obtained: -81.0312\n", + "Current minimum: -87.6669\n", + "Iteration No: 12 started. Searching for the next optimal point.\n", + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4643\n", + "Function value obtained: -86.2845\n", + "Current minimum: -87.6669\n", + "Iteration No: 13 started. Searching for the next optimal point.\n", + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5376\n", + "Function value obtained: -86.9626\n", + "Current minimum: -87.6669\n", + "Iteration No: 14 started. Searching for the next optimal point.\n", + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4763\n", + "Function value obtained: -85.3167\n", + "Current minimum: -87.6669\n", + "Iteration No: 15 started. Searching for the next optimal point.\n", + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3795\n", + "Function value obtained: -85.3954\n", + "Current minimum: -87.6669\n", + "Iteration No: 16 started. Searching for the next optimal point.\n", + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4464\n", + "Function value obtained: -86.8606\n", + "Current minimum: -87.6669\n", + "Iteration No: 17 started. Searching for the next optimal point.\n", + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3965\n", + "Function value obtained: -85.2312\n", + "Current minimum: -87.6669\n", + "Iteration No: 18 started. Searching for the next optimal point.\n", + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0767\n", + "Function value obtained: -86.8239\n", + "Current minimum: -87.6669\n", + "Iteration No: 19 started. Searching for the next optimal point.\n", + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0380\n", + "Function value obtained: -83.4708\n", + "Current minimum: -87.6669\n", + "Iteration No: 20 started. Searching for the next optimal point.\n", + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1029\n", + "Function value obtained: -85.2556\n", + "Current minimum: -87.6669\n", + "Iteration No: 21 started. Searching for the next optimal point.\n", + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2281\n", + "Function value obtained: -84.6053\n", + "Current minimum: -87.6669\n", + "Iteration No: 22 started. Searching for the next optimal point.\n", + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0660\n", + "Function value obtained: -86.8382\n", + "Current minimum: -87.6669\n", + "Iteration No: 23 started. Searching for the next optimal point.\n", + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0861\n", + "Function value obtained: -85.3114\n", + "Current minimum: -87.6669\n", + "Iteration No: 24 started. Searching for the next optimal point.\n", + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1002\n", + "Function value obtained: -84.0091\n", + "Current minimum: -87.6669\n", + "Iteration No: 25 started. Searching for the next optimal point.\n", + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0851\n", + "Function value obtained: -84.2599\n", + "Current minimum: -87.6669\n", + "Iteration No: 26 started. Searching for the next optimal point.\n", + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9678\n", + "Function value obtained: -78.3740\n", + "Current minimum: -87.6669\n", + "Iteration No: 27 started. Searching for the next optimal point.\n", + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0973\n", + "Function value obtained: -85.3701\n", + "Current minimum: -87.6669\n", + "Iteration No: 28 started. Searching for the next optimal point.\n", + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0858\n", + "Function value obtained: -84.9778\n", + "Current minimum: -87.6669\n", + "Iteration No: 29 started. Searching for the next optimal point.\n", + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 0.9512\n", + "Function value obtained: -84.4985\n", + "Current minimum: -87.6669\n", + "Iteration No: 30 started. Searching for the next optimal point.\n", + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2041\n", + "Function value obtained: -81.8451\n", + "Current minimum: -87.6669\n", + "Iteration No: 31 started. Searching for the next optimal point.\n", + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0863\n", + "Function value obtained: -85.8334\n", + "Current minimum: -87.6669\n", + "Iteration No: 32 started. Searching for the next optimal point.\n", + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1263\n", + "Function value obtained: -85.9086\n", + "Current minimum: -87.6669\n", + "Iteration No: 33 started. Searching for the next optimal point.\n", + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1764\n", + "Function value obtained: -85.9833\n", + "Current minimum: -87.6669\n", + "Iteration No: 34 started. Searching for the next optimal point.\n", + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1546\n", + "Function value obtained: -83.1661\n", + "Current minimum: -87.6669\n", + "Iteration No: 35 started. Searching for the next optimal point.\n", + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1208\n", + "Function value obtained: -84.8888\n", + "Current minimum: -87.6669\n", + "Iteration No: 36 started. Searching for the next optimal point.\n", + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1755\n", + "Function value obtained: -87.2595\n", + "Current minimum: -87.6669\n", + "Iteration No: 37 started. Searching for the next optimal point.\n", + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2202\n", + "Function value obtained: -81.2867\n", + "Current minimum: -87.6669\n", + "Iteration No: 38 started. Searching for the next optimal point.\n", + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1810\n", + "Function value obtained: -87.6799\n", + "Current minimum: -87.6799\n", + "Iteration No: 39 started. Searching for the next optimal point.\n", + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0646\n", + "Function value obtained: -85.8656\n", + "Current minimum: -87.6799\n", + "Iteration No: 40 started. Searching for the next optimal point.\n", + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1809\n", + "Function value obtained: -86.7755\n", + "Current minimum: -87.6799\n", + "Iteration No: 41 started. Searching for the next optimal point.\n", + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2532\n", + "Function value obtained: -84.5371\n", + "Current minimum: -87.6799\n", + "Iteration No: 42 started. Searching for the next optimal point.\n", + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1642\n", + "Function value obtained: -89.1145\n", + "Current minimum: -89.1145\n", + "Iteration No: 43 started. Searching for the next optimal point.\n", + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2658\n", + "Function value obtained: -84.1145\n", + "Current minimum: -89.1145\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2284\n", + "Function value obtained: -82.6845\n", + "Current minimum: -89.1145\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 1.0983\n", + "Function value obtained: -83.8531\n", + "Current minimum: -89.1145\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1574\n", + "Function value obtained: -84.2416\n", + "Current minimum: -89.1145\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2358\n", + "Function value obtained: -83.9671\n", + "Current minimum: -89.1145\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2055\n", + "Function value obtained: -87.1115\n", + "Current minimum: -89.1145\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2437\n", + "Function value obtained: -84.9626\n", + "Current minimum: -89.1145\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2165\n", + "Function value obtained: -85.3321\n", + "Current minimum: -89.1145\n", + "CPU times: user 1min 50s, sys: 11min 23s, total: 13min 13s\n", + "Wall time: 1min 12s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-89.11450923243565, [-1.2382929119922421])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "CONFIG=CONFIG3\n", + "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gp.fun, esc_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "7202f799-b847-47fb-8677-b627b45c04dd", "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "## Noiseless dynamics" + "esc = 10 ** esc_gp.x[0]\n", + "\n", + "get_policy_df(ConstEsc(env=AsmEnv(config=CONFIG3), escapement=esc)).plot(x='pop', y='pol', title='Optimal escapement policy')" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "3e34e14f-6d98-4d0a-ba1b-86553275bf9e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00867406, 0.05012764, 0.12382168, 0.2176034 , 0.3191206 ,\n", + " 0.4192168 , 0.5122158 , 0.5952108 , 0.667202 , 0.7283712 ,\n", + " 0.7795541 , 0.8218887 , 0.856597 , 0.8848603 , 0.9077545 ,\n", + " 0.92622364, 0.9410753 , 0.952988 , 0.9625244 , 0.9701466 ],\n", + " dtype=float32)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "env = AsmEnv(config=CONFIG3)\n", + "env.reset()\n", + "env.parameters[\"wt\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "4f82649d-f46e-441c-8a2b-1938c918f86c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9701466" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "env.parameters[\"max_wt\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "88b8ba0c-ae20-4d43-b559-107187144f4d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.008674059994518757, 0.9701465964317322, 0.3191205859184265)" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pop1 = np.array([1] + [0] * 19)\n", + "n1 = sum(pop1 / env.parameters[\"wt\"])\n", + "mwt1 = 1 / n1\n", + "\n", + "pop2 = np.array([0] * 19 + [1])\n", + "n2 = sum(pop2 / env.parameters[\"wt\"])\n", + "mwt2 = 1 / n2\n", + "\n", + "pop3 = np.array([0] * 4 + [1] + [0] * 15)\n", + "n3 = sum(pop3 / env.parameters[\"wt\"])\n", + "mwt3 = 1 / n3\n", + "\n", + "mwt1, mwt2, mwt3," ] }, { "cell_type": "code", "execution_count": null, - "id": "b01fb69b-9ac7-4faa-a564-98f729540690", + "id": "08f97f8d-0e9b-446d-a6c8-9721da71e1de", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index fcbed01..e995a5a 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", "metadata": {}, "outputs": [], @@ -51,17 +51,22 @@ "from stable_baselines3.common.monitor import Monitor\n", "\n", "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", - "from rl4fisheries.envs.asm_fns import get_r_devs" + "from rl4fisheries.envs.asm_fns import get_r_devs, observe_total" ] }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 2, "id": "236788a7-ed25-46bd-a9b0-f7301e96cacf", "metadata": {}, "outputs": [], "source": [ - "CONFIG = {\"s\": 0.86, \"noiseless\": False, \"testing_harvs\": False}" + "# CONFIG = {\"s\": 0.86, \"noiseless\": False, \"testing_harvs\": False}\n", + "CONFIG = {\n", + " 'observation_fn_id': 'observe_1o', \n", + " 'n_observs': 1, \n", + " 'wrong_harv_vul': False,\n", + "}" ] }, { @@ -74,14 +79,14 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 4, "id": "b59deb35-b67d-4232-bce4-ae9c8c2f0fcc", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "790aaca66e3641e88ff874c427254e0f", + "model_id": "b92ef02995e64837905f934c9b53f6dc", "version_major": 2, "version_minor": 0 }, @@ -113,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 15, "id": "38838cb2-44df-404b-9cd8-4ecfc9347dd9", "metadata": {}, "outputs": [], @@ -134,7 +139,8 @@ " tmax = env_cls().Tmax\n", " parallel = [generate_rew.remote(policy, env_cls, config) for _ in range(batch_size)]\n", " rews = ray.get(parallel)\n", - " \n", + " if ray.is_initialized():\n", + " ray.shutdown()\n", " return rews\n", "\n", "def eval_pol(policy, env_cls, config, n_batches=4, batch_size=40, pb=False):\n", @@ -161,13 +167,13 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 4, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], "source": [ "msy_space = [Real(0.001, 0.25, name='mortality')]\n", - "log_esc_space = [Real(-6, -1, name='log_escapement')]\n", + "log_esc_space = [Real(-6, 2, name='log_escapement')]\n", "cr_space = [\n", " Real(-5, 0, name='log_radius'),\n", " Real(0., np.pi/4.00001, name='theta'),\n", @@ -181,7 +187,7 @@ " rews = eval_pol(\n", " policy=agent, \n", " env_cls=AsmEnv, config=CONFIG, \n", - " n_batches=4, batch_size=40\n", + " n_batches=5, batch_size=40\n", " )\n", " return -np.mean(rews)\n", "\n", @@ -193,7 +199,7 @@ " rews = eval_pol(\n", " policy=agent, \n", " env_cls=AsmEnv, config=CONFIG, \n", - " n_batches=4, batch_size=40\n", + " n_batches=5, batch_size=40\n", " )\n", " return -np.mean(rews)\n", "\n", @@ -211,7 +217,7 @@ " policy=agent, \n", " env_cls=AsmEnv, \n", " config=CONFIG, \n", - " n_batches=4, batch_size=40\n", + " n_batches=5, batch_size=40\n", " )\n", " return -np.mean(rews) \n", "\n" @@ -235,9 +241,13 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 7, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -245,348 +255,1549 @@ "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-18 20:07:06,260\tINFO worker.py:1752 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.9297\n", - "Function value obtained: -34.4195\n", - "Current minimum: -34.4195\n", + "Time taken: 5.4834\n", + "Function value obtained: -45.4869\n", + "Current minimum: -45.4869\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8327\n", - "Function value obtained: -3.9477\n", - "Current minimum: -34.4195\n", + "Time taken: 1.2390\n", + "Function value obtained: -45.4833\n", + "Current minimum: -45.4869\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.8055\n", - "Function value obtained: -45.2543\n", - "Current minimum: -45.2543\n", + "Time taken: 1.3095\n", + "Function value obtained: -10.7505\n", + "Current minimum: -45.4869\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.7800\n", - "Function value obtained: -6.9639\n", - "Current minimum: -45.2543\n", + "Time taken: 1.2724\n", + "Function value obtained: -5.0272\n", + "Current minimum: -45.4869\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.7849\n", - "Function value obtained: -46.6104\n", - "Current minimum: -46.6104\n", + "Time taken: 1.2496\n", + "Function value obtained: -3.9916\n", + "Current minimum: -45.4869\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.7970\n", - "Function value obtained: -8.3589\n", - "Current minimum: -46.6104\n", + "Time taken: 1.2104\n", + "Function value obtained: -33.0886\n", + "Current minimum: -45.4869\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.7963\n", - "Function value obtained: -35.0244\n", - "Current minimum: -46.6104\n", + "Time taken: 1.2964\n", + "Function value obtained: -45.3213\n", + "Current minimum: -45.4869\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8935\n", - "Function value obtained: -6.8083\n", - "Current minimum: -46.6104\n", + "Time taken: 1.2228\n", + "Function value obtained: -46.4804\n", + "Current minimum: -46.4804\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8012\n", - "Function value obtained: -6.0992\n", - "Current minimum: -46.6104\n", + "Time taken: 1.2179\n", + "Function value obtained: -37.1732\n", + "Current minimum: -46.4804\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.0304\n", - "Function value obtained: -6.3427\n", - "Current minimum: -46.6104\n", + "Time taken: 5.4263\n", + "Function value obtained: -17.7539\n", + "Current minimum: -46.4804\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0080\n", - "Function value obtained: -45.6181\n", - "Current minimum: -46.6104\n", + "Time taken: 2.8543\n", + "Function value obtained: -44.8017\n", + "Current minimum: -46.4804\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0777\n", - "Function value obtained: -46.3725\n", - "Current minimum: -46.6104\n", + "Time taken: 2.8846\n", + "Function value obtained: -47.1156\n", + "Current minimum: -47.1156\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0550\n", - "Function value obtained: -47.2633\n", - "Current minimum: -47.2633\n", + "Time taken: 2.7248\n", + "Function value obtained: -2.1069\n", + "Current minimum: -47.1156\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0385\n", - "Function value obtained: -44.1828\n", - "Current minimum: -47.2633\n", + "Time taken: 2.6298\n", + "Function value obtained: -47.2816\n", + "Current minimum: -47.2816\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0444\n", - "Function value obtained: -46.5199\n", - "Current minimum: -47.2633\n", + "Time taken: 2.7281\n", + "Function value obtained: -48.4797\n", + "Current minimum: -48.4797\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0745\n", - "Function value obtained: -48.1007\n", - "Current minimum: -48.1007\n", + "Time taken: 2.6663\n", + "Function value obtained: -45.8552\n", + "Current minimum: -48.4797\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1061\n", - "Function value obtained: -48.2133\n", - "Current minimum: -48.2133\n", + "Time taken: 2.6468\n", + "Function value obtained: -44.8384\n", + "Current minimum: -48.4797\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0789\n", - "Function value obtained: -47.0517\n", - "Current minimum: -48.2133\n", + "Time taken: 2.2501\n", + "Function value obtained: -47.2674\n", + "Current minimum: -48.4797\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1093\n", - "Function value obtained: -47.2809\n", - "Current minimum: -48.2133\n", + "Time taken: 1.4988\n", + "Function value obtained: -47.9821\n", + "Current minimum: -48.4797\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0385\n", - "Function value obtained: -46.6564\n", - "Current minimum: -48.2133\n", + "Time taken: 1.4442\n", + "Function value obtained: -48.3160\n", + "Current minimum: -48.4797\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9958\n", - "Function value obtained: -45.2278\n", - "Current minimum: -48.2133\n", + "Time taken: 1.4421\n", + "Function value obtained: -48.4776\n", + "Current minimum: -48.4797\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0789\n", - "Function value obtained: -45.3176\n", - "Current minimum: -48.2133\n", + "Time taken: 1.4981\n", + "Function value obtained: -46.0047\n", + "Current minimum: -48.4797\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0752\n", - "Function value obtained: -45.4752\n", - "Current minimum: -48.2133\n", + "Time taken: 1.5107\n", + "Function value obtained: -47.0921\n", + "Current minimum: -48.4797\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9604\n", - "Function value obtained: -44.8737\n", - "Current minimum: -48.2133\n", + "Time taken: 1.4536\n", + "Function value obtained: -45.4472\n", + "Current minimum: -48.4797\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0631\n", - "Function value obtained: -46.7914\n", - "Current minimum: -48.2133\n", + "Time taken: 1.5842\n", + "Function value obtained: -44.6242\n", + "Current minimum: -48.4797\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0564\n", - "Function value obtained: -46.7580\n", - "Current minimum: -48.2133\n", + "Time taken: 1.5491\n", + "Function value obtained: -45.6832\n", + "Current minimum: -48.4797\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1281\n", - "Function value obtained: -46.9997\n", - "Current minimum: -48.2133\n", + "Time taken: 1.5361\n", + "Function value obtained: -47.7525\n", + "Current minimum: -48.4797\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0858\n", - "Function value obtained: -44.5727\n", - "Current minimum: -48.2133\n", + "Time taken: 1.5167\n", + "Function value obtained: -48.0074\n", + "Current minimum: -48.4797\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9800\n", - "Function value obtained: -47.5164\n", - "Current minimum: -48.2133\n", + "Time taken: 1.4705\n", + "Function value obtained: -45.3860\n", + "Current minimum: -48.4797\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1264\n", - "Function value obtained: -47.8769\n", - "Current minimum: -48.2133\n", + "Time taken: 1.5557\n", + "Function value obtained: -47.2246\n", + "Current minimum: -48.4797\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0978\n", - "Function value obtained: -44.8638\n", - "Current minimum: -48.2133\n", + "Time taken: 1.4705\n", + "Function value obtained: -46.7993\n", + "Current minimum: -48.4797\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0241\n", - "Function value obtained: -48.4403\n", - "Current minimum: -48.4403\n", + "Time taken: 1.4802\n", + "Function value obtained: -47.5363\n", + "Current minimum: -48.4797\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0426\n", - "Function value obtained: -45.9114\n", - "Current minimum: -48.4403\n", + "Time taken: 1.5252\n", + "Function value obtained: -44.5044\n", + "Current minimum: -48.4797\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0396\n", - "Function value obtained: -45.3013\n", - "Current minimum: -48.4403\n", + "Time taken: 1.5382\n", + "Function value obtained: -46.5751\n", + "Current minimum: -48.4797\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0787\n", - "Function value obtained: -45.7534\n", - "Current minimum: -48.4403\n", + "Time taken: 1.5391\n", + "Function value obtained: -46.4138\n", + "Current minimum: -48.4797\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3994\n", - "Function value obtained: -48.3400\n", - "Current minimum: -48.4403\n", + "Time taken: 1.5699\n", + "Function value obtained: -46.8731\n", + "Current minimum: -48.4797\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1389\n", - "Function value obtained: -45.6515\n", - "Current minimum: -48.4403\n", + "Time taken: 1.5144\n", + "Function value obtained: -44.6237\n", + "Current minimum: -48.4797\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0842\n", - "Function value obtained: -46.8415\n", - "Current minimum: -48.4403\n", + "Time taken: 1.5497\n", + "Function value obtained: -47.7694\n", + "Current minimum: -48.4797\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1503\n", - "Function value obtained: -47.1488\n", - "Current minimum: -48.4403\n", + "Time taken: 1.5183\n", + "Function value obtained: -45.6401\n", + "Current minimum: -48.4797\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1281\n", - "Function value obtained: -48.6317\n", - "Current minimum: -48.6317\n", + "Time taken: 1.5764\n", + "Function value obtained: -44.6487\n", + "Current minimum: -48.4797\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1454\n", - "Function value obtained: -45.3279\n", - "Current minimum: -48.6317\n", + "Time taken: 1.6051\n", + "Function value obtained: -48.4921\n", + "Current minimum: -48.4921\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0289\n", - "Function value obtained: -49.5151\n", - "Current minimum: -49.5151\n", + "Time taken: 1.5972\n", + "Function value obtained: -45.5842\n", + "Current minimum: -48.4921\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1277\n", - "Function value obtained: -45.9657\n", - "Current minimum: -49.5151\n", + "Time taken: 1.7220\n", + "Function value obtained: -46.4373\n", + "Current minimum: -48.4921\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1321\n", - "Function value obtained: -48.8441\n", - "Current minimum: -49.5151\n", + "Time taken: 1.5566\n", + "Function value obtained: -47.1885\n", + "Current minimum: -48.4921\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1791\n", - "Function value obtained: -45.1809\n", - "Current minimum: -49.5151\n", + "Time taken: 1.5261\n", + "Function value obtained: -45.9221\n", + "Current minimum: -48.4921\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1060\n", - "Function value obtained: -47.6197\n", - "Current minimum: -49.5151\n", + "Time taken: 1.5645\n", + "Function value obtained: -43.6403\n", + "Current minimum: -48.4921\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0466\n", - "Function value obtained: -45.1608\n", - "Current minimum: -49.5151\n", + "Time taken: 1.5970\n", + "Function value obtained: -45.2802\n", + "Current minimum: -48.4921\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1008\n", - "Function value obtained: -45.8224\n", - "Current minimum: -49.5151\n", + "Time taken: 1.6565\n", + "Function value obtained: -45.3725\n", + "Current minimum: -48.4921\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1540\n", - "Function value obtained: -46.0425\n", - "Current minimum: -49.5151\n", + "Time taken: 1.6801\n", + "Function value obtained: -47.2802\n", + "Current minimum: -48.4921\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2157\n", - "Function value obtained: -45.1788\n", - "Current minimum: -49.5151\n", - "CPU times: user 1min 32s, sys: 9min 11s, total: 10min 43s\n", - "Wall time: 52.1 s\n" + "Time taken: 1.6020\n", + "Function value obtained: -46.1278\n", + "Current minimum: -48.4921\n", + "Iteration No: 51 started. Searching for the next optimal point.\n", + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5772\n", + "Function value obtained: -45.1661\n", + "Current minimum: -48.4921\n", + "Iteration No: 52 started. Searching for the next optimal point.\n", + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6349\n", + "Function value obtained: -48.4165\n", + "Current minimum: -48.4921\n", + "Iteration No: 53 started. Searching for the next optimal point.\n", + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6452\n", + "Function value obtained: -46.2293\n", + "Current minimum: -48.4921\n", + "Iteration No: 54 started. Searching for the next optimal point.\n", + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6030\n", + "Function value obtained: -47.8491\n", + "Current minimum: -48.4921\n", + "Iteration No: 55 started. Searching for the next optimal point.\n", + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6037\n", + "Function value obtained: -47.8606\n", + "Current minimum: -48.4921\n", + "Iteration No: 56 started. Searching for the next optimal point.\n", + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6668\n", + "Function value obtained: -47.1706\n", + "Current minimum: -48.4921\n", + "Iteration No: 57 started. Searching for the next optimal point.\n", + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6347\n", + "Function value obtained: -44.8855\n", + "Current minimum: -48.4921\n", + "Iteration No: 58 started. Searching for the next optimal point.\n", + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7118\n", + "Function value obtained: -48.2741\n", + "Current minimum: -48.4921\n", + "Iteration No: 59 started. Searching for the next optimal point.\n", + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6909\n", + "Function value obtained: -46.0191\n", + "Current minimum: -48.4921\n", + "Iteration No: 60 started. Searching for the next optimal point.\n", + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6286\n", + "Function value obtained: -46.5769\n", + "Current minimum: -48.4921\n", + "Iteration No: 61 started. Searching for the next optimal point.\n", + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7985\n", + "Function value obtained: -45.2123\n", + "Current minimum: -48.4921\n", + "Iteration No: 62 started. Searching for the next optimal point.\n", + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6588\n", + "Function value obtained: -47.8129\n", + "Current minimum: -48.4921\n", + "Iteration No: 63 started. Searching for the next optimal point.\n", + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6954\n", + "Function value obtained: -47.5916\n", + "Current minimum: -48.4921\n", + "Iteration No: 64 started. Searching for the next optimal point.\n", + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7652\n", + "Function value obtained: -47.5889\n", + "Current minimum: -48.4921\n", + "Iteration No: 65 started. Searching for the next optimal point.\n", + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6750\n", + "Function value obtained: -45.0518\n", + "Current minimum: -48.4921\n", + "Iteration No: 66 started. Searching for the next optimal point.\n", + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7389\n", + "Function value obtained: -45.4444\n", + "Current minimum: -48.4921\n", + "Iteration No: 67 started. Searching for the next optimal point.\n", + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7756\n", + "Function value obtained: -45.8260\n", + "Current minimum: -48.4921\n", + "Iteration No: 68 started. Searching for the next optimal point.\n", + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7541\n", + "Function value obtained: -46.2042\n", + "Current minimum: -48.4921\n", + "Iteration No: 69 started. Searching for the next optimal point.\n", + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6736\n", + "Function value obtained: -46.1098\n", + "Current minimum: -48.4921\n", + "Iteration No: 70 started. Searching for the next optimal point.\n", + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8213\n", + "Function value obtained: -47.9813\n", + "Current minimum: -48.4921\n", + "Iteration No: 71 started. Searching for the next optimal point.\n", + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7609\n", + "Function value obtained: -47.3720\n", + "Current minimum: -48.4921\n", + "Iteration No: 72 started. Searching for the next optimal point.\n", + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7459\n", + "Function value obtained: -45.8506\n", + "Current minimum: -48.4921\n", + "Iteration No: 73 started. Searching for the next optimal point.\n", + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7373\n", + "Function value obtained: -47.3937\n", + "Current minimum: -48.4921\n", + "Iteration No: 74 started. Searching for the next optimal point.\n", + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7282\n", + "Function value obtained: -47.7427\n", + "Current minimum: -48.4921\n", + "Iteration No: 75 started. Searching for the next optimal point.\n", + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7312\n", + "Function value obtained: -46.9223\n", + "Current minimum: -48.4921\n", + "Iteration No: 76 started. Searching for the next optimal point.\n", + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9500\n", + "Function value obtained: -45.0708\n", + "Current minimum: -48.4921\n", + "Iteration No: 77 started. Searching for the next optimal point.\n", + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7779\n", + "Function value obtained: -47.4218\n", + "Current minimum: -48.4921\n", + "Iteration No: 78 started. Searching for the next optimal point.\n", + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7577\n", + "Function value obtained: -47.6362\n", + "Current minimum: -48.4921\n", + "Iteration No: 79 started. Searching for the next optimal point.\n", + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8317\n", + "Function value obtained: -46.0445\n", + "Current minimum: -48.4921\n", + "Iteration No: 80 started. Searching for the next optimal point.\n", + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8320\n", + "Function value obtained: -44.9416\n", + "Current minimum: -48.4921\n", + "Iteration No: 81 started. Searching for the next optimal point.\n", + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8045\n", + "Function value obtained: -47.1192\n", + "Current minimum: -48.4921\n", + "Iteration No: 82 started. Searching for the next optimal point.\n", + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8466\n", + "Function value obtained: -48.4313\n", + "Current minimum: -48.4921\n", + "Iteration No: 83 started. Searching for the next optimal point.\n", + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8834\n", + "Function value obtained: -47.3605\n", + "Current minimum: -48.4921\n", + "Iteration No: 84 started. Searching for the next optimal point.\n", + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8080\n", + "Function value obtained: -48.2420\n", + "Current minimum: -48.4921\n", + "Iteration No: 85 started. Searching for the next optimal point.\n", + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8395\n", + "Function value obtained: -46.2903\n", + "Current minimum: -48.4921\n", + "Iteration No: 86 started. Searching for the next optimal point.\n", + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8343\n", + "Function value obtained: -47.3175\n", + "Current minimum: -48.4921\n", + "Iteration No: 87 started. Searching for the next optimal point.\n", + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8653\n", + "Function value obtained: -45.3488\n", + "Current minimum: -48.4921\n", + "Iteration No: 88 started. Searching for the next optimal point.\n", + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9204\n", + "Function value obtained: -48.0706\n", + "Current minimum: -48.4921\n", + "Iteration No: 89 started. Searching for the next optimal point.\n", + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9728\n", + "Function value obtained: -44.7884\n", + "Current minimum: -48.4921\n", + "Iteration No: 90 started. Searching for the next optimal point.\n", + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9866\n", + "Function value obtained: -44.1032\n", + "Current minimum: -48.4921\n", + "Iteration No: 91 started. Searching for the next optimal point.\n", + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0576\n", + "Function value obtained: -47.2277\n", + "Current minimum: -48.4921\n", + "Iteration No: 92 started. Searching for the next optimal point.\n", + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0363\n", + "Function value obtained: -46.7563\n", + "Current minimum: -48.4921\n", + "Iteration No: 93 started. Searching for the next optimal point.\n", + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0899\n", + "Function value obtained: -46.3911\n", + "Current minimum: -48.4921\n", + "Iteration No: 94 started. Searching for the next optimal point.\n", + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0240\n", + "Function value obtained: -48.2728\n", + "Current minimum: -48.4921\n", + "Iteration No: 95 started. Searching for the next optimal point.\n", + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0093\n", + "Function value obtained: -48.0412\n", + "Current minimum: -48.4921\n", + "Iteration No: 96 started. Searching for the next optimal point.\n", + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0485\n", + "Function value obtained: -48.0344\n", + "Current minimum: -48.4921\n", + "Iteration No: 97 started. Searching for the next optimal point.\n", + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0404\n", + "Function value obtained: -48.5009\n", + "Current minimum: -48.5009\n", + "Iteration No: 98 started. Searching for the next optimal point.\n", + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9809\n", + "Function value obtained: -44.2641\n", + "Current minimum: -48.5009\n", + "Iteration No: 99 started. Searching for the next optimal point.\n", + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9447\n", + "Function value obtained: -49.1602\n", + "Current minimum: -49.1602\n", + "Iteration No: 100 started. Searching for the next optimal point.\n", + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0264\n", + "Function value obtained: -47.1086\n", + "Current minimum: -49.1602\n", + "Iteration No: 101 started. Searching for the next optimal point.\n", + "Iteration No: 101 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1010\n", + "Function value obtained: -48.3980\n", + "Current minimum: -49.1602\n", + "Iteration No: 102 started. Searching for the next optimal point.\n", + "Iteration No: 102 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0427\n", + "Function value obtained: -47.8815\n", + "Current minimum: -49.1602\n", + "Iteration No: 103 started. Searching for the next optimal point.\n", + "Iteration No: 103 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0931\n", + "Function value obtained: -47.5502\n", + "Current minimum: -49.1602\n", + "Iteration No: 104 started. Searching for the next optimal point.\n", + "Iteration No: 104 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2007\n", + "Function value obtained: -47.4727\n", + "Current minimum: -49.1602\n", + "Iteration No: 105 started. Searching for the next optimal point.\n", + "Iteration No: 105 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0616\n", + "Function value obtained: -47.9100\n", + "Current minimum: -49.1602\n", + "Iteration No: 106 started. Searching for the next optimal point.\n", + "Iteration No: 106 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1357\n", + "Function value obtained: -46.7392\n", + "Current minimum: -49.1602\n", + "Iteration No: 107 started. Searching for the next optimal point.\n", + "Iteration No: 107 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0894\n", + "Function value obtained: -47.8489\n", + "Current minimum: -49.1602\n", + "Iteration No: 108 started. Searching for the next optimal point.\n", + "Iteration No: 108 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0558\n", + "Function value obtained: -46.5916\n", + "Current minimum: -49.1602\n", + "Iteration No: 109 started. Searching for the next optimal point.\n", + "Iteration No: 109 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1618\n", + "Function value obtained: -48.1301\n", + "Current minimum: -49.1602\n", + "Iteration No: 110 started. Searching for the next optimal point.\n", + "Iteration No: 110 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2526\n", + "Function value obtained: -46.3323\n", + "Current minimum: -49.1602\n", + "Iteration No: 111 started. Searching for the next optimal point.\n", + "Iteration No: 111 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1880\n", + "Function value obtained: -46.9814\n", + "Current minimum: -49.1602\n", + "Iteration No: 112 started. Searching for the next optimal point.\n", + "Iteration No: 112 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1675\n", + "Function value obtained: -48.6653\n", + "Current minimum: -49.1602\n", + "Iteration No: 113 started. Searching for the next optimal point.\n", + "Iteration No: 113 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1985\n", + "Function value obtained: -46.3422\n", + "Current minimum: -49.1602\n", + "Iteration No: 114 started. Searching for the next optimal point.\n", + "Iteration No: 114 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1815\n", + "Function value obtained: -46.4887\n", + "Current minimum: -49.1602\n", + "Iteration No: 115 started. Searching for the next optimal point.\n", + "Iteration No: 115 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1457\n", + "Function value obtained: -47.0818\n", + "Current minimum: -49.1602\n", + "Iteration No: 116 started. Searching for the next optimal point.\n", + "Iteration No: 116 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1414\n", + "Function value obtained: -46.6261\n", + "Current minimum: -49.1602\n", + "Iteration No: 117 started. Searching for the next optimal point.\n", + "Iteration No: 117 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1700\n", + "Function value obtained: -47.6725\n", + "Current minimum: -49.1602\n", + "Iteration No: 118 started. Searching for the next optimal point.\n", + "Iteration No: 118 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2580\n", + "Function value obtained: -47.3460\n", + "Current minimum: -49.1602\n", + "Iteration No: 119 started. Searching for the next optimal point.\n", + "Iteration No: 119 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2411\n", + "Function value obtained: -46.7710\n", + "Current minimum: -49.1602\n", + "Iteration No: 120 started. Searching for the next optimal point.\n", + "Iteration No: 120 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2818\n", + "Function value obtained: -46.3773\n", + "Current minimum: -49.1602\n", + "Iteration No: 121 started. Searching for the next optimal point.\n", + "Iteration No: 121 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2879\n", + "Function value obtained: -46.3798\n", + "Current minimum: -49.1602\n", + "Iteration No: 122 started. Searching for the next optimal point.\n", + "Iteration No: 122 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2791\n", + "Function value obtained: -46.6607\n", + "Current minimum: -49.1602\n", + "Iteration No: 123 started. Searching for the next optimal point.\n", + "Iteration No: 123 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3396\n", + "Function value obtained: -47.6516\n", + "Current minimum: -49.1602\n", + "Iteration No: 124 started. Searching for the next optimal point.\n", + "Iteration No: 124 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2591\n", + "Function value obtained: -47.4018\n", + "Current minimum: -49.1602\n", + "Iteration No: 125 started. Searching for the next optimal point.\n", + "Iteration No: 125 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3125\n", + "Function value obtained: -46.9759\n", + "Current minimum: -49.1602\n", + "Iteration No: 126 started. Searching for the next optimal point.\n", + "Iteration No: 126 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4122\n", + "Function value obtained: -47.9909\n", + "Current minimum: -49.1602\n", + "Iteration No: 127 started. Searching for the next optimal point.\n", + "Iteration No: 127 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4453\n", + "Function value obtained: -47.1735\n", + "Current minimum: -49.1602\n", + "Iteration No: 128 started. Searching for the next optimal point.\n", + "Iteration No: 128 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3740\n", + "Function value obtained: -46.0115\n", + "Current minimum: -49.1602\n", + "Iteration No: 129 started. Searching for the next optimal point.\n", + "Iteration No: 129 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4357\n", + "Function value obtained: -43.6239\n", + "Current minimum: -49.1602\n", + "Iteration No: 130 started. Searching for the next optimal point.\n", + "Iteration No: 130 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3402\n", + "Function value obtained: -47.6954\n", + "Current minimum: -49.1602\n", + "Iteration No: 131 started. Searching for the next optimal point.\n", + "Iteration No: 131 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3421\n", + "Function value obtained: -46.7463\n", + "Current minimum: -49.1602\n", + "Iteration No: 132 started. Searching for the next optimal point.\n", + "Iteration No: 132 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3503\n", + "Function value obtained: -47.3892\n", + "Current minimum: -49.1602\n", + "Iteration No: 133 started. Searching for the next optimal point.\n", + "Iteration No: 133 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4501\n", + "Function value obtained: -47.0282\n", + "Current minimum: -49.1602\n", + "Iteration No: 134 started. Searching for the next optimal point.\n", + "Iteration No: 134 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4205\n", + "Function value obtained: -46.1954\n", + "Current minimum: -49.1602\n", + "Iteration No: 135 started. Searching for the next optimal point.\n", + "Iteration No: 135 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5106\n", + "Function value obtained: -48.0156\n", + "Current minimum: -49.1602\n", + "Iteration No: 136 started. Searching for the next optimal point.\n", + "Iteration No: 136 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5138\n", + "Function value obtained: -45.6801\n", + "Current minimum: -49.1602\n", + "Iteration No: 137 started. Searching for the next optimal point.\n", + "Iteration No: 137 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4558\n", + "Function value obtained: -47.0258\n", + "Current minimum: -49.1602\n", + "Iteration No: 138 started. Searching for the next optimal point.\n", + "Iteration No: 138 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5781\n", + "Function value obtained: -45.6934\n", + "Current minimum: -49.1602\n", + "Iteration No: 139 started. Searching for the next optimal point.\n", + "Iteration No: 139 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4864\n", + "Function value obtained: -47.4580\n", + "Current minimum: -49.1602\n", + "Iteration No: 140 started. Searching for the next optimal point.\n", + "Iteration No: 140 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5932\n", + "Function value obtained: -45.6992\n", + "Current minimum: -49.1602\n", + "Iteration No: 141 started. Searching for the next optimal point.\n", + "Iteration No: 141 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4581\n", + "Function value obtained: -45.1805\n", + "Current minimum: -49.1602\n", + "Iteration No: 142 started. Searching for the next optimal point.\n", + "Iteration No: 142 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6622\n", + "Function value obtained: -46.3799\n", + "Current minimum: -49.1602\n", + "Iteration No: 143 started. Searching for the next optimal point.\n", + "Iteration No: 143 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5337\n", + "Function value obtained: -46.6137\n", + "Current minimum: -49.1602\n", + "Iteration No: 144 started. Searching for the next optimal point.\n", + "Iteration No: 144 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5876\n", + "Function value obtained: -46.7286\n", + "Current minimum: -49.1602\n", + "Iteration No: 145 started. Searching for the next optimal point.\n", + "Iteration No: 145 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5612\n", + "Function value obtained: -46.9521\n", + "Current minimum: -49.1602\n", + "Iteration No: 146 started. Searching for the next optimal point.\n", + "Iteration No: 146 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5794\n", + "Function value obtained: -46.0575\n", + "Current minimum: -49.1602\n", + "Iteration No: 147 started. Searching for the next optimal point.\n", + "Iteration No: 147 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5318\n", + "Function value obtained: -46.8464\n", + "Current minimum: -49.1602\n", + "Iteration No: 148 started. Searching for the next optimal point.\n", + "Iteration No: 148 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5888\n", + "Function value obtained: -48.7687\n", + "Current minimum: -49.1602\n", + "Iteration No: 149 started. Searching for the next optimal point.\n", + "Iteration No: 149 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7167\n", + "Function value obtained: -47.1604\n", + "Current minimum: -49.1602\n", + "Iteration No: 150 started. Searching for the next optimal point.\n", + "Iteration No: 150 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6717\n", + "Function value obtained: -45.7514\n", + "Current minimum: -49.1602\n", + "Iteration No: 151 started. Searching for the next optimal point.\n", + "Iteration No: 151 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6518\n", + "Function value obtained: -48.3608\n", + "Current minimum: -49.1602\n", + "Iteration No: 152 started. Searching for the next optimal point.\n", + "Iteration No: 152 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5351\n", + "Function value obtained: -45.0135\n", + "Current minimum: -49.1602\n", + "Iteration No: 153 started. Searching for the next optimal point.\n", + "Iteration No: 153 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6665\n", + "Function value obtained: -48.4784\n", + "Current minimum: -49.1602\n", + "Iteration No: 154 started. Searching for the next optimal point.\n", + "Iteration No: 154 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6906\n", + "Function value obtained: -47.8889\n", + "Current minimum: -49.1602\n", + "Iteration No: 155 started. Searching for the next optimal point.\n", + "Iteration No: 155 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6694\n", + "Function value obtained: -47.0118\n", + "Current minimum: -49.1602\n", + "Iteration No: 156 started. Searching for the next optimal point.\n", + "Iteration No: 156 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7407\n", + "Function value obtained: -46.7522\n", + "Current minimum: -49.1602\n", + "Iteration No: 157 started. Searching for the next optimal point.\n", + "Iteration No: 157 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7208\n", + "Function value obtained: -48.2136\n", + "Current minimum: -49.1602\n", + "Iteration No: 158 started. Searching for the next optimal point.\n", + "Iteration No: 158 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8332\n", + "Function value obtained: -46.3153\n", + "Current minimum: -49.1602\n", + "Iteration No: 159 started. Searching for the next optimal point.\n", + "Iteration No: 159 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7492\n", + "Function value obtained: -45.8129\n", + "Current minimum: -49.1602\n", + "Iteration No: 160 started. Searching for the next optimal point.\n", + "Iteration No: 160 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9116\n", + "Function value obtained: -46.4367\n", + "Current minimum: -49.1602\n", + "Iteration No: 161 started. Searching for the next optimal point.\n", + "Iteration No: 161 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8496\n", + "Function value obtained: -45.6333\n", + "Current minimum: -49.1602\n", + "Iteration No: 162 started. Searching for the next optimal point.\n", + "Iteration No: 162 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8590\n", + "Function value obtained: -46.2112\n", + "Current minimum: -49.1602\n", + "Iteration No: 163 started. Searching for the next optimal point.\n", + "Iteration No: 163 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8651\n", + "Function value obtained: -45.0481\n", + "Current minimum: -49.1602\n", + "Iteration No: 164 started. Searching for the next optimal point.\n", + "Iteration No: 164 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8631\n", + "Function value obtained: -46.4866\n", + "Current minimum: -49.1602\n", + "Iteration No: 165 started. Searching for the next optimal point.\n", + "Iteration No: 165 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8506\n", + "Function value obtained: -46.0082\n", + "Current minimum: -49.1602\n", + "Iteration No: 166 started. Searching for the next optimal point.\n", + "Iteration No: 166 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9569\n", + "Function value obtained: -47.5285\n", + "Current minimum: -49.1602\n", + "Iteration No: 167 started. Searching for the next optimal point.\n", + "Iteration No: 167 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9269\n", + "Function value obtained: -47.8298\n", + "Current minimum: -49.1602\n", + "Iteration No: 168 started. Searching for the next optimal point.\n", + "Iteration No: 168 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9630\n", + "Function value obtained: -48.0272\n", + "Current minimum: -49.1602\n", + "Iteration No: 169 started. Searching for the next optimal point.\n", + "Iteration No: 169 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9377\n", + "Function value obtained: -48.8270\n", + "Current minimum: -49.1602\n", + "Iteration No: 170 started. Searching for the next optimal point.\n", + "Iteration No: 170 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8955\n", + "Function value obtained: -48.3741\n", + "Current minimum: -49.1602\n", + "Iteration No: 171 started. Searching for the next optimal point.\n", + "Iteration No: 171 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0323\n", + "Function value obtained: -46.7494\n", + "Current minimum: -49.1602\n", + "Iteration No: 172 started. Searching for the next optimal point.\n", + "Iteration No: 172 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9283\n", + "Function value obtained: -48.7623\n", + "Current minimum: -49.1602\n", + "Iteration No: 173 started. Searching for the next optimal point.\n", + "Iteration No: 173 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0291\n", + "Function value obtained: -48.1221\n", + "Current minimum: -49.1602\n", + "Iteration No: 174 started. Searching for the next optimal point.\n", + "Iteration No: 174 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0170\n", + "Function value obtained: -48.7643\n", + "Current minimum: -49.1602\n", + "Iteration No: 175 started. Searching for the next optimal point.\n", + "Iteration No: 175 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1282\n", + "Function value obtained: -46.4082\n", + "Current minimum: -49.1602\n", + "Iteration No: 176 started. Searching for the next optimal point.\n", + "Iteration No: 176 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9267\n", + "Function value obtained: -47.9548\n", + "Current minimum: -49.1602\n", + "Iteration No: 177 started. Searching for the next optimal point.\n", + "Iteration No: 177 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0769\n", + "Function value obtained: -47.4106\n", + "Current minimum: -49.1602\n", + "Iteration No: 178 started. Searching for the next optimal point.\n", + "Iteration No: 178 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1087\n", + "Function value obtained: -48.8447\n", + "Current minimum: -49.1602\n", + "Iteration No: 179 started. Searching for the next optimal point.\n", + "Iteration No: 179 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0330\n", + "Function value obtained: -46.6117\n", + "Current minimum: -49.1602\n", + "Iteration No: 180 started. Searching for the next optimal point.\n", + "Iteration No: 180 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2589\n", + "Function value obtained: -48.5135\n", + "Current minimum: -49.1602\n", + "Iteration No: 181 started. Searching for the next optimal point.\n", + "Iteration No: 181 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2152\n", + "Function value obtained: -45.4152\n", + "Current minimum: -49.1602\n", + "Iteration No: 182 started. Searching for the next optimal point.\n", + "Iteration No: 182 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0810\n", + "Function value obtained: -45.7898\n", + "Current minimum: -49.1602\n", + "Iteration No: 183 started. Searching for the next optimal point.\n", + "Iteration No: 183 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3461\n", + "Function value obtained: -47.2987\n", + "Current minimum: -49.1602\n", + "Iteration No: 184 started. Searching for the next optimal point.\n", + "Iteration No: 184 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1987\n", + "Function value obtained: -46.2405\n", + "Current minimum: -49.1602\n", + "Iteration No: 185 started. Searching for the next optimal point.\n", + "Iteration No: 185 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3101\n", + "Function value obtained: -46.9703\n", + "Current minimum: -49.1602\n", + "Iteration No: 186 started. Searching for the next optimal point.\n", + "Iteration No: 186 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3039\n", + "Function value obtained: -47.3671\n", + "Current minimum: -49.1602\n", + "Iteration No: 187 started. Searching for the next optimal point.\n", + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2898\n", + "Function value obtained: -49.2781\n", + "Current minimum: -49.2781\n", + "Iteration No: 188 started. Searching for the next optimal point.\n", + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2604\n", + "Function value obtained: -45.6923\n", + "Current minimum: -49.2781\n", + "Iteration No: 189 started. Searching for the next optimal point.\n", + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5017\n", + "Function value obtained: -47.5145\n", + "Current minimum: -49.2781\n", + "Iteration No: 190 started. Searching for the next optimal point.\n", + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4741\n", + "Function value obtained: -46.3412\n", + "Current minimum: -49.2781\n", + "Iteration No: 191 started. Searching for the next optimal point.\n", + "Iteration No: 191 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4891\n", + "Function value obtained: -47.0852\n", + "Current minimum: -49.2781\n", + "Iteration No: 192 started. Searching for the next optimal point.\n", + "Iteration No: 192 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4091\n", + "Function value obtained: -46.4869\n", + "Current minimum: -49.2781\n", + "Iteration No: 193 started. Searching for the next optimal point.\n", + "Iteration No: 193 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5463\n", + "Function value obtained: -47.2560\n", + "Current minimum: -49.2781\n", + "Iteration No: 194 started. Searching for the next optimal point.\n", + "Iteration No: 194 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4077\n", + "Function value obtained: -45.5755\n", + "Current minimum: -49.2781\n", + "Iteration No: 195 started. Searching for the next optimal point.\n", + "Iteration No: 195 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5328\n", + "Function value obtained: -47.5300\n", + "Current minimum: -49.2781\n", + "Iteration No: 196 started. Searching for the next optimal point.\n", + "Iteration No: 196 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4624\n", + "Function value obtained: -46.2453\n", + "Current minimum: -49.2781\n", + "Iteration No: 197 started. Searching for the next optimal point.\n", + "Iteration No: 197 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5501\n", + "Function value obtained: -45.9818\n", + "Current minimum: -49.2781\n", + "Iteration No: 198 started. Searching for the next optimal point.\n", + "Iteration No: 198 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6110\n", + "Function value obtained: -44.2845\n", + "Current minimum: -49.2781\n", + "Iteration No: 199 started. Searching for the next optimal point.\n", + "Iteration No: 199 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5313\n", + "Function value obtained: -50.3900\n", + "Current minimum: -50.3900\n", + "Iteration No: 200 started. Searching for the next optimal point.\n", + "Iteration No: 200 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5884\n", + "Function value obtained: -47.5778\n", + "Current minimum: -50.3900\n", + "Iteration No: 201 started. Searching for the next optimal point.\n", + "Iteration No: 201 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5219\n", + "Function value obtained: -45.7308\n", + "Current minimum: -50.3900\n", + "Iteration No: 202 started. Searching for the next optimal point.\n", + "Iteration No: 202 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4850\n", + "Function value obtained: -46.5011\n", + "Current minimum: -50.3900\n", + "Iteration No: 203 started. Searching for the next optimal point.\n", + "Iteration No: 203 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7918\n", + "Function value obtained: -47.2935\n", + "Current minimum: -50.3900\n", + "Iteration No: 204 started. Searching for the next optimal point.\n", + "Iteration No: 204 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7020\n", + "Function value obtained: -46.3767\n", + "Current minimum: -50.3900\n", + "Iteration No: 205 started. Searching for the next optimal point.\n", + "Iteration No: 205 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6193\n", + "Function value obtained: -47.5970\n", + "Current minimum: -50.3900\n", + "Iteration No: 206 started. Searching for the next optimal point.\n", + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6386\n", + "Function value obtained: -46.2089\n", + "Current minimum: -50.3900\n", + "Iteration No: 207 started. Searching for the next optimal point.\n", + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7037\n", + "Function value obtained: -47.2441\n", + "Current minimum: -50.3900\n", + "Iteration No: 208 started. Searching for the next optimal point.\n", + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7155\n", + "Function value obtained: -45.6728\n", + "Current minimum: -50.3900\n", + "Iteration No: 209 started. Searching for the next optimal point.\n", + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7618\n", + "Function value obtained: -47.8828\n", + "Current minimum: -50.3900\n", + "Iteration No: 210 started. Searching for the next optimal point.\n", + "Iteration No: 210 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7382\n", + "Function value obtained: -46.1474\n", + "Current minimum: -50.3900\n", + "Iteration No: 211 started. Searching for the next optimal point.\n", + "Iteration No: 211 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7545\n", + "Function value obtained: -47.6435\n", + "Current minimum: -50.3900\n", + "Iteration No: 212 started. Searching for the next optimal point.\n", + "Iteration No: 212 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9274\n", + "Function value obtained: -46.2764\n", + "Current minimum: -50.3900\n", + "Iteration No: 213 started. Searching for the next optimal point.\n", + "Iteration No: 213 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8311\n", + "Function value obtained: -47.7107\n", + "Current minimum: -50.3900\n", + "Iteration No: 214 started. Searching for the next optimal point.\n", + "Iteration No: 214 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7216\n", + "Function value obtained: -45.7783\n", + "Current minimum: -50.3900\n", + "Iteration No: 215 started. Searching for the next optimal point.\n", + "Iteration No: 215 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8901\n", + "Function value obtained: -46.7034\n", + "Current minimum: -50.3900\n", + "Iteration No: 216 started. Searching for the next optimal point.\n", + "Iteration No: 216 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7970\n", + "Function value obtained: -48.6155\n", + "Current minimum: -50.3900\n", + "Iteration No: 217 started. Searching for the next optimal point.\n", + "Iteration No: 217 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9145\n", + "Function value obtained: -45.7807\n", + "Current minimum: -50.3900\n", + "Iteration No: 218 started. Searching for the next optimal point.\n", + "Iteration No: 218 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8581\n", + "Function value obtained: -47.6175\n", + "Current minimum: -50.3900\n", + "Iteration No: 219 started. Searching for the next optimal point.\n", + "Iteration No: 219 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1427\n", + "Function value obtained: -46.7095\n", + "Current minimum: -50.3900\n", + "Iteration No: 220 started. Searching for the next optimal point.\n", + "Iteration No: 220 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9117\n", + "Function value obtained: -48.1388\n", + "Current minimum: -50.3900\n", + "Iteration No: 221 started. Searching for the next optimal point.\n", + "Iteration No: 221 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1734\n", + "Function value obtained: -46.8995\n", + "Current minimum: -50.3900\n", + "Iteration No: 222 started. Searching for the next optimal point.\n", + "Iteration No: 222 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0980\n", + "Function value obtained: -50.1261\n", + "Current minimum: -50.3900\n", + "Iteration No: 223 started. Searching for the next optimal point.\n", + "Iteration No: 223 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0633\n", + "Function value obtained: -44.6711\n", + "Current minimum: -50.3900\n", + "Iteration No: 224 started. Searching for the next optimal point.\n", + "Iteration No: 224 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9759\n", + "Function value obtained: -47.1576\n", + "Current minimum: -50.3900\n", + "Iteration No: 225 started. Searching for the next optimal point.\n", + "Iteration No: 225 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0273\n", + "Function value obtained: -47.7665\n", + "Current minimum: -50.3900\n", + "Iteration No: 226 started. Searching for the next optimal point.\n", + "Iteration No: 226 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2018\n", + "Function value obtained: -46.0928\n", + "Current minimum: -50.3900\n", + "Iteration No: 227 started. Searching for the next optimal point.\n", + "Iteration No: 227 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2215\n", + "Function value obtained: -46.2331\n", + "Current minimum: -50.3900\n", + "Iteration No: 228 started. Searching for the next optimal point.\n", + "Iteration No: 228 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1366\n", + "Function value obtained: -48.4136\n", + "Current minimum: -50.3900\n", + "Iteration No: 229 started. Searching for the next optimal point.\n", + "Iteration No: 229 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0939\n", + "Function value obtained: -45.8923\n", + "Current minimum: -50.3900\n", + "Iteration No: 230 started. Searching for the next optimal point.\n", + "Iteration No: 230 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2826\n", + "Function value obtained: -47.9723\n", + "Current minimum: -50.3900\n", + "Iteration No: 231 started. Searching for the next optimal point.\n", + "Iteration No: 231 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2689\n", + "Function value obtained: -46.6460\n", + "Current minimum: -50.3900\n", + "Iteration No: 232 started. Searching for the next optimal point.\n", + "Iteration No: 232 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0645\n", + "Function value obtained: -45.9143\n", + "Current minimum: -50.3900\n", + "Iteration No: 233 started. Searching for the next optimal point.\n", + "Iteration No: 233 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3859\n", + "Function value obtained: -46.5508\n", + "Current minimum: -50.3900\n", + "Iteration No: 234 started. Searching for the next optimal point.\n", + "Iteration No: 234 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4730\n", + "Function value obtained: -47.9804\n", + "Current minimum: -50.3900\n", + "Iteration No: 235 started. Searching for the next optimal point.\n", + "Iteration No: 235 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3902\n", + "Function value obtained: -47.0151\n", + "Current minimum: -50.3900\n", + "Iteration No: 236 started. Searching for the next optimal point.\n", + "Iteration No: 236 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2887\n", + "Function value obtained: -44.4297\n", + "Current minimum: -50.3900\n", + "Iteration No: 237 started. Searching for the next optimal point.\n", + "Iteration No: 237 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3634\n", + "Function value obtained: -46.6838\n", + "Current minimum: -50.3900\n", + "Iteration No: 238 started. Searching for the next optimal point.\n", + "Iteration No: 238 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2440\n", + "Function value obtained: -48.1649\n", + "Current minimum: -50.3900\n", + "Iteration No: 239 started. Searching for the next optimal point.\n", + "Iteration No: 239 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2938\n", + "Function value obtained: -46.2227\n", + "Current minimum: -50.3900\n", + "Iteration No: 240 started. Searching for the next optimal point.\n", + "Iteration No: 240 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4050\n", + "Function value obtained: -45.0731\n", + "Current minimum: -50.3900\n", + "Iteration No: 241 started. Searching for the next optimal point.\n", + "Iteration No: 241 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4776\n", + "Function value obtained: -45.9867\n", + "Current minimum: -50.3900\n", + "Iteration No: 242 started. Searching for the next optimal point.\n", + "Iteration No: 242 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4071\n", + "Function value obtained: -47.1149\n", + "Current minimum: -50.3900\n", + "Iteration No: 243 started. Searching for the next optimal point.\n", + "Iteration No: 243 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5018\n", + "Function value obtained: -48.3418\n", + "Current minimum: -50.3900\n", + "Iteration No: 244 started. Searching for the next optimal point.\n", + "Iteration No: 244 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3588\n", + "Function value obtained: -46.9173\n", + "Current minimum: -50.3900\n", + "Iteration No: 245 started. Searching for the next optimal point.\n", + "Iteration No: 245 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5967\n", + "Function value obtained: -47.6389\n", + "Current minimum: -50.3900\n", + "Iteration No: 246 started. Searching for the next optimal point.\n", + "Iteration No: 246 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5045\n", + "Function value obtained: -47.4420\n", + "Current minimum: -50.3900\n", + "Iteration No: 247 started. Searching for the next optimal point.\n", + "Iteration No: 247 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6585\n", + "Function value obtained: -46.9558\n", + "Current minimum: -50.3900\n", + "Iteration No: 248 started. Searching for the next optimal point.\n", + "Iteration No: 248 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5302\n", + "Function value obtained: -47.2430\n", + "Current minimum: -50.3900\n", + "Iteration No: 249 started. Searching for the next optimal point.\n", + "Iteration No: 249 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6487\n", + "Function value obtained: -46.9436\n", + "Current minimum: -50.3900\n", + "Iteration No: 250 started. Searching for the next optimal point.\n", + "Iteration No: 250 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7154\n", + "Function value obtained: -47.2870\n", + "Current minimum: -50.3900\n", + "Iteration No: 251 started. Searching for the next optimal point.\n", + "Iteration No: 251 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7374\n", + "Function value obtained: -46.1422\n", + "Current minimum: -50.3900\n", + "Iteration No: 252 started. Searching for the next optimal point.\n", + "Iteration No: 252 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5813\n", + "Function value obtained: -46.9244\n", + "Current minimum: -50.3900\n", + "Iteration No: 253 started. Searching for the next optimal point.\n", + "Iteration No: 253 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5524\n", + "Function value obtained: -47.1142\n", + "Current minimum: -50.3900\n", + "Iteration No: 254 started. Searching for the next optimal point.\n", + "Iteration No: 254 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6731\n", + "Function value obtained: -47.1417\n", + "Current minimum: -50.3900\n", + "Iteration No: 255 started. Searching for the next optimal point.\n", + "Iteration No: 255 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6971\n", + "Function value obtained: -48.0082\n", + "Current minimum: -50.3900\n", + "Iteration No: 256 started. Searching for the next optimal point.\n", + "Iteration No: 256 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6721\n", + "Function value obtained: -44.1149\n", + "Current minimum: -50.3900\n", + "Iteration No: 257 started. Searching for the next optimal point.\n", + "Iteration No: 257 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7240\n", + "Function value obtained: -48.7647\n", + "Current minimum: -50.3900\n", + "Iteration No: 258 started. Searching for the next optimal point.\n", + "Iteration No: 258 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8619\n", + "Function value obtained: -48.4711\n", + "Current minimum: -50.3900\n", + "Iteration No: 259 started. Searching for the next optimal point.\n", + "Iteration No: 259 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9958\n", + "Function value obtained: -46.1754\n", + "Current minimum: -50.3900\n", + "Iteration No: 260 started. Searching for the next optimal point.\n", + "Iteration No: 260 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7924\n", + "Function value obtained: -47.3461\n", + "Current minimum: -50.3900\n", + "Iteration No: 261 started. Searching for the next optimal point.\n", + "Iteration No: 261 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9955\n", + "Function value obtained: -47.7343\n", + "Current minimum: -50.3900\n", + "Iteration No: 262 started. Searching for the next optimal point.\n", + "Iteration No: 262 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9547\n", + "Function value obtained: -47.4042\n", + "Current minimum: -50.3900\n", + "Iteration No: 263 started. Searching for the next optimal point.\n", + "Iteration No: 263 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8644\n", + "Function value obtained: -47.5446\n", + "Current minimum: -50.3900\n", + "Iteration No: 264 started. Searching for the next optimal point.\n", + "Iteration No: 264 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9177\n", + "Function value obtained: -46.0754\n", + "Current minimum: -50.3900\n", + "Iteration No: 265 started. Searching for the next optimal point.\n", + "Iteration No: 265 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1236\n", + "Function value obtained: -46.5039\n", + "Current minimum: -50.3900\n", + "Iteration No: 266 started. Searching for the next optimal point.\n", + "Iteration No: 266 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1350\n", + "Function value obtained: -47.5166\n", + "Current minimum: -50.3900\n", + "Iteration No: 267 started. Searching for the next optimal point.\n", + "Iteration No: 267 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0588\n", + "Function value obtained: -47.5519\n", + "Current minimum: -50.3900\n", + "Iteration No: 268 started. Searching for the next optimal point.\n", + "Iteration No: 268 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9890\n", + "Function value obtained: -48.8447\n", + "Current minimum: -50.3900\n", + "Iteration No: 269 started. Searching for the next optimal point.\n", + "Iteration No: 269 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1606\n", + "Function value obtained: -47.1201\n", + "Current minimum: -50.3900\n", + "Iteration No: 270 started. Searching for the next optimal point.\n", + "Iteration No: 270 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0070\n", + "Function value obtained: -48.6648\n", + "Current minimum: -50.3900\n", + "Iteration No: 271 started. Searching for the next optimal point.\n", + "Iteration No: 271 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2681\n", + "Function value obtained: -46.2319\n", + "Current minimum: -50.3900\n", + "Iteration No: 272 started. Searching for the next optimal point.\n", + "Iteration No: 272 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0337\n", + "Function value obtained: -46.0469\n", + "Current minimum: -50.3900\n", + "Iteration No: 273 started. Searching for the next optimal point.\n", + "Iteration No: 273 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2960\n", + "Function value obtained: -47.4200\n", + "Current minimum: -50.3900\n", + "Iteration No: 274 started. Searching for the next optimal point.\n", + "Iteration No: 274 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1563\n", + "Function value obtained: -47.0962\n", + "Current minimum: -50.3900\n", + "Iteration No: 275 started. Searching for the next optimal point.\n", + "Iteration No: 275 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3941\n", + "Function value obtained: -46.4848\n", + "Current minimum: -50.3900\n", + "Iteration No: 276 started. Searching for the next optimal point.\n", + "Iteration No: 276 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1359\n", + "Function value obtained: -46.1953\n", + "Current minimum: -50.3900\n", + "Iteration No: 277 started. Searching for the next optimal point.\n", + "Iteration No: 277 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3135\n", + "Function value obtained: -44.3502\n", + "Current minimum: -50.3900\n", + "Iteration No: 278 started. Searching for the next optimal point.\n", + "Iteration No: 278 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2371\n", + "Function value obtained: -48.6788\n", + "Current minimum: -50.3900\n", + "Iteration No: 279 started. Searching for the next optimal point.\n", + "Iteration No: 279 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3045\n", + "Function value obtained: -48.1817\n", + "Current minimum: -50.3900\n", + "Iteration No: 280 started. Searching for the next optimal point.\n", + "Iteration No: 280 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3008\n", + "Function value obtained: -47.5294\n", + "Current minimum: -50.3900\n", + "Iteration No: 281 started. Searching for the next optimal point.\n", + "Iteration No: 281 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4910\n", + "Function value obtained: -46.3327\n", + "Current minimum: -50.3900\n", + "Iteration No: 282 started. Searching for the next optimal point.\n", + "Iteration No: 282 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3888\n", + "Function value obtained: -45.6673\n", + "Current minimum: -50.3900\n", + "Iteration No: 283 started. Searching for the next optimal point.\n", + "Iteration No: 283 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4214\n", + "Function value obtained: -45.5122\n", + "Current minimum: -50.3900\n", + "Iteration No: 284 started. Searching for the next optimal point.\n", + "Iteration No: 284 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4576\n", + "Function value obtained: -46.6317\n", + "Current minimum: -50.3900\n", + "Iteration No: 285 started. Searching for the next optimal point.\n", + "Iteration No: 285 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4995\n", + "Function value obtained: -48.3950\n", + "Current minimum: -50.3900\n", + "Iteration No: 286 started. Searching for the next optimal point.\n", + "Iteration No: 286 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5975\n", + "Function value obtained: -47.3764\n", + "Current minimum: -50.3900\n", + "Iteration No: 287 started. Searching for the next optimal point.\n", + "Iteration No: 287 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4760\n", + "Function value obtained: -46.1770\n", + "Current minimum: -50.3900\n", + "Iteration No: 288 started. Searching for the next optimal point.\n", + "Iteration No: 288 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4981\n", + "Function value obtained: -48.4162\n", + "Current minimum: -50.3900\n", + "Iteration No: 289 started. Searching for the next optimal point.\n", + "Iteration No: 289 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6847\n", + "Function value obtained: -46.3198\n", + "Current minimum: -50.3900\n", + "Iteration No: 290 started. Searching for the next optimal point.\n", + "Iteration No: 290 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7812\n", + "Function value obtained: -44.1499\n", + "Current minimum: -50.3900\n", + "Iteration No: 291 started. Searching for the next optimal point.\n", + "Iteration No: 291 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6644\n", + "Function value obtained: -48.3996\n", + "Current minimum: -50.3900\n", + "Iteration No: 292 started. Searching for the next optimal point.\n", + "Iteration No: 292 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4829\n", + "Function value obtained: -45.9433\n", + "Current minimum: -50.3900\n", + "Iteration No: 293 started. Searching for the next optimal point.\n", + "Iteration No: 293 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7236\n", + "Function value obtained: -45.6916\n", + "Current minimum: -50.3900\n", + "Iteration No: 294 started. Searching for the next optimal point.\n", + "Iteration No: 294 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3748\n", + "Function value obtained: -45.3838\n", + "Current minimum: -50.3900\n", + "Iteration No: 295 started. Searching for the next optimal point.\n", + "Iteration No: 295 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6545\n", + "Function value obtained: -47.8300\n", + "Current minimum: -50.3900\n", + "Iteration No: 296 started. Searching for the next optimal point.\n", + "Iteration No: 296 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8150\n", + "Function value obtained: -49.2014\n", + "Current minimum: -50.3900\n", + "Iteration No: 297 started. Searching for the next optimal point.\n", + "Iteration No: 297 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7817\n", + "Function value obtained: -45.3947\n", + "Current minimum: -50.3900\n", + "Iteration No: 298 started. Searching for the next optimal point.\n", + "Iteration No: 298 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8951\n", + "Function value obtained: -47.4768\n", + "Current minimum: -50.3900\n", + "Iteration No: 299 started. Searching for the next optimal point.\n", + "Iteration No: 299 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8960\n", + "Function value obtained: -47.9250\n", + "Current minimum: -50.3900\n", + "Iteration No: 300 started. Searching for the next optimal point.\n", + "Iteration No: 300 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8756\n", + "Function value obtained: -45.0798\n", + "Current minimum: -50.3900\n", + "CPU times: user 2h 2min 7s, sys: 1h 11min 48s, total: 3h 13min 56s\n", + "Wall time: 15min 22s\n" ] }, { "data": { "text/plain": [ - "(-49.515058565010186, [0.0560298054012827])" + "(-50.39000406549121, [0.05365088255575121])" ] }, - "execution_count": 85, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", "msy_gp.fun, msy_gp.x" ] }, { "cell_type": "code", - "execution_count": 86, - "id": "6563ba01-9664-4dbc-9594-c4439d22023a", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_convergence(msy_gp)" - ] - }, - { - "cell_type": "code", - "execution_count": 88, + "execution_count": 8, "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -596,343 +1807,1541 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8201\n", - "Function value obtained: -20.8203\n", - "Current minimum: -20.8203\n", + "Time taken: 1.3560\n", + "Function value obtained: -46.5391\n", + "Current minimum: -46.5391\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8470\n", - "Function value obtained: -45.4203\n", - "Current minimum: -45.4203\n", + "Time taken: 1.1664\n", + "Function value obtained: -4.6581\n", + "Current minimum: -46.5391\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.7855\n", - "Function value obtained: -5.5793\n", - "Current minimum: -45.4203\n", + "Time taken: 1.3000\n", + "Function value obtained: -14.8136\n", + "Current minimum: -46.5391\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8221\n", - "Function value obtained: -11.1915\n", - "Current minimum: -45.4203\n", + "Time taken: 1.2598\n", + "Function value obtained: -3.6463\n", + "Current minimum: -46.5391\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.7927\n", - "Function value obtained: -44.1016\n", - "Current minimum: -45.4203\n", + "Time taken: 1.1637\n", + "Function value obtained: -4.3602\n", + "Current minimum: -46.5391\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8089\n", - "Function value obtained: -14.6585\n", - "Current minimum: -45.4203\n", + "Time taken: 1.2462\n", + "Function value obtained: -4.0893\n", + "Current minimum: -46.5391\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.7807\n", - "Function value obtained: -21.0878\n", - "Current minimum: -45.4203\n", + "Time taken: 1.2717\n", + "Function value obtained: -10.5623\n", + "Current minimum: -46.5391\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8078\n", - "Function value obtained: -4.1043\n", - "Current minimum: -45.4203\n", + "Time taken: 1.2456\n", + "Function value obtained: -38.1398\n", + "Current minimum: -46.5391\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8377\n", - "Function value obtained: -32.1021\n", - "Current minimum: -45.4203\n", + "Time taken: 1.2314\n", + "Function value obtained: -48.0675\n", + "Current minimum: -48.0675\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.0039\n", - "Function value obtained: -28.6322\n", - "Current minimum: -45.4203\n", + "Time taken: 1.4094\n", + "Function value obtained: -6.6195\n", + "Current minimum: -48.0675\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1528\n", - "Function value obtained: -47.0562\n", - "Current minimum: -47.0562\n", + "Time taken: 1.4140\n", + "Function value obtained: -49.6017\n", + "Current minimum: -49.6017\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0595\n", - "Function value obtained: -47.7504\n", - "Current minimum: -47.7504\n", + "Time taken: 1.4435\n", + "Function value obtained: -46.6843\n", + "Current minimum: -49.6017\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0471\n", - "Function value obtained: -43.8821\n", - "Current minimum: -47.7504\n", + "Time taken: 1.4193\n", + "Function value obtained: -45.0990\n", + "Current minimum: -49.6017\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0353\n", - "Function value obtained: -47.3315\n", - "Current minimum: -47.7504\n", + "Time taken: 1.5035\n", + "Function value obtained: -46.8608\n", + "Current minimum: -49.6017\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1125\n", - "Function value obtained: -48.6935\n", - "Current minimum: -48.6935\n", + "Time taken: 1.5919\n", + "Function value obtained: -49.3540\n", + "Current minimum: -49.6017\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9939\n", - "Function value obtained: -48.6872\n", - "Current minimum: -48.6935\n", + "Time taken: 1.4357\n", + "Function value obtained: -47.5765\n", + "Current minimum: -49.6017\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0482\n", - "Function value obtained: -44.4783\n", - "Current minimum: -48.6935\n", + "Time taken: 1.4996\n", + "Function value obtained: -45.1326\n", + "Current minimum: -49.6017\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0298\n", - "Function value obtained: -47.5510\n", - "Current minimum: -48.6935\n", + "Time taken: 1.4617\n", + "Function value obtained: -46.9510\n", + "Current minimum: -49.6017\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0493\n", - "Function value obtained: -45.9067\n", - "Current minimum: -48.6935\n", + "Time taken: 1.4780\n", + "Function value obtained: -12.6043\n", + "Current minimum: -49.6017\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0278\n", - "Function value obtained: -47.6435\n", - "Current minimum: -48.6935\n", + "Time taken: 1.4956\n", + "Function value obtained: -48.6197\n", + "Current minimum: -49.6017\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0599\n", - "Function value obtained: -46.3318\n", - "Current minimum: -48.6935\n", + "Time taken: 1.4565\n", + "Function value obtained: -45.1803\n", + "Current minimum: -49.6017\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3514\n", - "Function value obtained: -49.5974\n", - "Current minimum: -49.5974\n", + "Time taken: 1.3789\n", + "Function value obtained: -48.0291\n", + "Current minimum: -49.6017\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0790\n", - "Function value obtained: -47.4932\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4518\n", + "Function value obtained: -47.8936\n", + "Current minimum: -49.6017\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1718\n", - "Function value obtained: -46.7006\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4929\n", + "Function value obtained: -46.8791\n", + "Current minimum: -49.6017\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0293\n", - "Function value obtained: -47.8838\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5805\n", + "Function value obtained: -48.7646\n", + "Current minimum: -49.6017\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9834\n", - "Function value obtained: -46.3363\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4410\n", + "Function value obtained: -45.4169\n", + "Current minimum: -49.6017\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1368\n", - "Function value obtained: -46.4499\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5256\n", + "Function value obtained: -46.7357\n", + "Current minimum: -49.6017\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1134\n", - "Function value obtained: -40.1026\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5359\n", + "Function value obtained: -46.2242\n", + "Current minimum: -49.6017\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0998\n", - "Function value obtained: -28.8108\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5400\n", + "Function value obtained: -12.6620\n", + "Current minimum: -49.6017\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0352\n", - "Function value obtained: -24.5495\n", - "Current minimum: -49.5974\n", + "Time taken: 1.6019\n", + "Function value obtained: -43.9229\n", + "Current minimum: -49.6017\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2080\n", - "Function value obtained: -48.5815\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4984\n", + "Function value obtained: -47.8351\n", + "Current minimum: -49.6017\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0966\n", - "Function value obtained: -47.7910\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5293\n", + "Function value obtained: -44.4191\n", + "Current minimum: -49.6017\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9493\n", - "Function value obtained: -46.6133\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4842\n", + "Function value obtained: -47.5384\n", + "Current minimum: -49.6017\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1299\n", - "Function value obtained: -45.7727\n", - "Current minimum: -49.5974\n", + "Time taken: 1.6029\n", + "Function value obtained: -47.4318\n", + "Current minimum: -49.6017\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1286\n", - "Function value obtained: -13.5939\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4040\n", + "Function value obtained: -44.8686\n", + "Current minimum: -49.6017\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0683\n", - "Function value obtained: -47.3934\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5284\n", + "Function value obtained: -47.4501\n", + "Current minimum: -49.6017\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0373\n", - "Function value obtained: -46.9083\n", - "Current minimum: -49.5974\n", + "Time taken: 1.3685\n", + "Function value obtained: -47.0818\n", + "Current minimum: -49.6017\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0734\n", - "Function value obtained: -47.3283\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4836\n", + "Function value obtained: -46.7556\n", + "Current minimum: -49.6017\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0384\n", - "Function value obtained: -46.2170\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5081\n", + "Function value obtained: -46.9364\n", + "Current minimum: -49.6017\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0122\n", - "Function value obtained: -47.3127\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4114\n", + "Function value obtained: -46.0513\n", + "Current minimum: -49.6017\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0147\n", - "Function value obtained: -45.8262\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4602\n", + "Function value obtained: -47.1258\n", + "Current minimum: -49.6017\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1555\n", - "Function value obtained: -44.7477\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4598\n", + "Function value obtained: -44.6687\n", + "Current minimum: -49.6017\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0391\n", - "Function value obtained: -48.3279\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4767\n", + "Function value obtained: -45.9894\n", + "Current minimum: -49.6017\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2610\n", - "Function value obtained: -45.3069\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5332\n", + "Function value obtained: -46.3990\n", + "Current minimum: -49.6017\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0652\n", - "Function value obtained: -45.7178\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5325\n", + "Function value obtained: -47.7062\n", + "Current minimum: -49.6017\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3785\n", - "Function value obtained: -46.6172\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5390\n", + "Function value obtained: -47.8023\n", + "Current minimum: -49.6017\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0412\n", - "Function value obtained: -48.5573\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4629\n", + "Function value obtained: -45.6460\n", + "Current minimum: -49.6017\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0659\n", - "Function value obtained: -46.4082\n", - "Current minimum: -49.5974\n", + "Time taken: 1.5021\n", + "Function value obtained: -44.3852\n", + "Current minimum: -49.6017\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0267\n", - "Function value obtained: -43.5981\n", - "Current minimum: -49.5974\n", + "Time taken: 1.4780\n", + "Function value obtained: -46.6708\n", + "Current minimum: -49.6017\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0281\n", - "Function value obtained: -46.9634\n", - "Current minimum: -49.5974\n", - "CPU times: user 18.2 s, sys: 4.16 s, total: 22.4 s\n", - "Wall time: 51.8 s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-49.59740600044421, [0.05475473233147571])" - ] - }, - "execution_count": 88, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 50, verbose=True, n_jobs=-1)\n", - "msy_gbrt.fun, msy_gbrt.x" - ] - }, - { - "cell_type": "code", - "execution_count": 89, - "id": "73d6974e-8d14-419d-a43d-ef0cd09659f8", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 89, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_convergence(msy_gbrt)" - ] - }, - { - "cell_type": "markdown", + "Time taken: 1.4235\n", + "Function value obtained: -45.2947\n", + "Current minimum: -49.6017\n", + "Iteration No: 51 started. Searching for the next optimal point.\n", + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4191\n", + "Function value obtained: -47.4422\n", + "Current minimum: -49.6017\n", + "Iteration No: 52 started. Searching for the next optimal point.\n", + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5193\n", + "Function value obtained: -47.2893\n", + "Current minimum: -49.6017\n", + "Iteration No: 53 started. Searching for the next optimal point.\n", + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4471\n", + "Function value obtained: -48.0579\n", + "Current minimum: -49.6017\n", + "Iteration No: 54 started. Searching for the next optimal point.\n", + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5124\n", + "Function value obtained: -46.6369\n", + "Current minimum: -49.6017\n", + "Iteration No: 55 started. Searching for the next optimal point.\n", + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5033\n", + "Function value obtained: -48.1478\n", + "Current minimum: -49.6017\n", + "Iteration No: 56 started. Searching for the next optimal point.\n", + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5597\n", + "Function value obtained: -48.1605\n", + "Current minimum: -49.6017\n", + "Iteration No: 57 started. Searching for the next optimal point.\n", + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4899\n", + "Function value obtained: -45.0397\n", + "Current minimum: -49.6017\n", + "Iteration No: 58 started. Searching for the next optimal point.\n", + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4978\n", + "Function value obtained: -46.5459\n", + "Current minimum: -49.6017\n", + "Iteration No: 59 started. Searching for the next optimal point.\n", + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4811\n", + "Function value obtained: -43.7516\n", + "Current minimum: -49.6017\n", + "Iteration No: 60 started. Searching for the next optimal point.\n", + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5171\n", + "Function value obtained: -47.2481\n", + "Current minimum: -49.6017\n", + "Iteration No: 61 started. Searching for the next optimal point.\n", + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4386\n", + "Function value obtained: -46.4790\n", + "Current minimum: -49.6017\n", + "Iteration No: 62 started. Searching for the next optimal point.\n", + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4536\n", + "Function value obtained: -47.3387\n", + "Current minimum: -49.6017\n", + "Iteration No: 63 started. Searching for the next optimal point.\n", + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6102\n", + "Function value obtained: -47.5327\n", + "Current minimum: -49.6017\n", + "Iteration No: 64 started. Searching for the next optimal point.\n", + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5174\n", + "Function value obtained: -45.3859\n", + "Current minimum: -49.6017\n", + "Iteration No: 65 started. Searching for the next optimal point.\n", + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4711\n", + "Function value obtained: -46.8727\n", + "Current minimum: -49.6017\n", + "Iteration No: 66 started. Searching for the next optimal point.\n", + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5031\n", + "Function value obtained: -48.0277\n", + "Current minimum: -49.6017\n", + "Iteration No: 67 started. Searching for the next optimal point.\n", + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5509\n", + "Function value obtained: -48.6187\n", + "Current minimum: -49.6017\n", + "Iteration No: 68 started. Searching for the next optimal point.\n", + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5195\n", + "Function value obtained: -48.3695\n", + "Current minimum: -49.6017\n", + "Iteration No: 69 started. Searching for the next optimal point.\n", + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4830\n", + "Function value obtained: -44.5009\n", + "Current minimum: -49.6017\n", + "Iteration No: 70 started. Searching for the next optimal point.\n", + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5454\n", + "Function value obtained: -45.3096\n", + "Current minimum: -49.6017\n", + "Iteration No: 71 started. Searching for the next optimal point.\n", + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4323\n", + "Function value obtained: -47.1526\n", + "Current minimum: -49.6017\n", + "Iteration No: 72 started. Searching for the next optimal point.\n", + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4273\n", + "Function value obtained: -47.3175\n", + "Current minimum: -49.6017\n", + "Iteration No: 73 started. Searching for the next optimal point.\n", + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5579\n", + "Function value obtained: -46.5905\n", + "Current minimum: -49.6017\n", + "Iteration No: 74 started. Searching for the next optimal point.\n", + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5067\n", + "Function value obtained: -46.8752\n", + "Current minimum: -49.6017\n", + "Iteration No: 75 started. Searching for the next optimal point.\n", + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5313\n", + "Function value obtained: -47.8672\n", + "Current minimum: -49.6017\n", + "Iteration No: 76 started. Searching for the next optimal point.\n", + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5224\n", + "Function value obtained: -45.6860\n", + "Current minimum: -49.6017\n", + "Iteration No: 77 started. Searching for the next optimal point.\n", + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5298\n", + "Function value obtained: -46.8637\n", + "Current minimum: -49.6017\n", + "Iteration No: 78 started. Searching for the next optimal point.\n", + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7157\n", + "Function value obtained: -47.9359\n", + "Current minimum: -49.6017\n", + "Iteration No: 79 started. Searching for the next optimal point.\n", + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4869\n", + "Function value obtained: -48.3924\n", + "Current minimum: -49.6017\n", + "Iteration No: 80 started. Searching for the next optimal point.\n", + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4701\n", + "Function value obtained: -45.2819\n", + "Current minimum: -49.6017\n", + "Iteration No: 81 started. Searching for the next optimal point.\n", + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4596\n", + "Function value obtained: -48.8099\n", + "Current minimum: -49.6017\n", + "Iteration No: 82 started. Searching for the next optimal point.\n", + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4203\n", + "Function value obtained: -44.6818\n", + "Current minimum: -49.6017\n", + "Iteration No: 83 started. Searching for the next optimal point.\n", + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3309\n", + "Function value obtained: -48.0720\n", + "Current minimum: -49.6017\n", + "Iteration No: 84 started. Searching for the next optimal point.\n", + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5261\n", + "Function value obtained: -47.3489\n", + "Current minimum: -49.6017\n", + "Iteration No: 85 started. Searching for the next optimal point.\n", + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4705\n", + "Function value obtained: -48.0898\n", + "Current minimum: -49.6017\n", + "Iteration No: 86 started. Searching for the next optimal point.\n", + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4849\n", + "Function value obtained: -45.8602\n", + "Current minimum: -49.6017\n", + "Iteration No: 87 started. Searching for the next optimal point.\n", + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6133\n", + "Function value obtained: -47.4123\n", + "Current minimum: -49.6017\n", + "Iteration No: 88 started. Searching for the next optimal point.\n", + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5090\n", + "Function value obtained: -46.1113\n", + "Current minimum: -49.6017\n", + "Iteration No: 89 started. Searching for the next optimal point.\n", + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5676\n", + "Function value obtained: -48.4236\n", + "Current minimum: -49.6017\n", + "Iteration No: 90 started. Searching for the next optimal point.\n", + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4747\n", + "Function value obtained: -47.6057\n", + "Current minimum: -49.6017\n", + "Iteration No: 91 started. Searching for the next optimal point.\n", + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4737\n", + "Function value obtained: -45.1571\n", + "Current minimum: -49.6017\n", + "Iteration No: 92 started. Searching for the next optimal point.\n", + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4616\n", + "Function value obtained: -48.5987\n", + "Current minimum: -49.6017\n", + "Iteration No: 93 started. Searching for the next optimal point.\n", + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4667\n", + "Function value obtained: -47.1953\n", + "Current minimum: -49.6017\n", + "Iteration No: 94 started. Searching for the next optimal point.\n", + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4862\n", + "Function value obtained: -46.9125\n", + "Current minimum: -49.6017\n", + "Iteration No: 95 started. Searching for the next optimal point.\n", + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4970\n", + "Function value obtained: -47.4312\n", + "Current minimum: -49.6017\n", + "Iteration No: 96 started. Searching for the next optimal point.\n", + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4997\n", + "Function value obtained: -47.1148\n", + "Current minimum: -49.6017\n", + "Iteration No: 97 started. Searching for the next optimal point.\n", + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6946\n", + "Function value obtained: -46.7082\n", + "Current minimum: -49.6017\n", + "Iteration No: 98 started. Searching for the next optimal point.\n", + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5323\n", + "Function value obtained: -47.0256\n", + "Current minimum: -49.6017\n", + "Iteration No: 99 started. Searching for the next optimal point.\n", + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4895\n", + "Function value obtained: -45.8617\n", + "Current minimum: -49.6017\n", + "Iteration No: 100 started. Searching for the next optimal point.\n", + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4927\n", + "Function value obtained: -46.0801\n", + "Current minimum: -49.6017\n", + "Iteration No: 101 started. Searching for the next optimal point.\n", + "Iteration No: 101 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5328\n", + "Function value obtained: -47.8178\n", + "Current minimum: -49.6017\n", + "Iteration No: 102 started. Searching for the next optimal point.\n", + "Iteration No: 102 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5578\n", + "Function value obtained: -45.8014\n", + "Current minimum: -49.6017\n", + "Iteration No: 103 started. Searching for the next optimal point.\n", + "Iteration No: 103 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5063\n", + "Function value obtained: -48.7166\n", + "Current minimum: -49.6017\n", + "Iteration No: 104 started. Searching for the next optimal point.\n", + "Iteration No: 104 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4746\n", + "Function value obtained: -46.6069\n", + "Current minimum: -49.6017\n", + "Iteration No: 105 started. Searching for the next optimal point.\n", + "Iteration No: 105 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5559\n", + "Function value obtained: -47.1771\n", + "Current minimum: -49.6017\n", + "Iteration No: 106 started. Searching for the next optimal point.\n", + "Iteration No: 106 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4994\n", + "Function value obtained: -47.1168\n", + "Current minimum: -49.6017\n", + "Iteration No: 107 started. Searching for the next optimal point.\n", + "Iteration No: 107 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5939\n", + "Function value obtained: -46.4010\n", + "Current minimum: -49.6017\n", + "Iteration No: 108 started. Searching for the next optimal point.\n", + "Iteration No: 108 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5162\n", + "Function value obtained: -48.2321\n", + "Current minimum: -49.6017\n", + "Iteration No: 109 started. Searching for the next optimal point.\n", + "Iteration No: 109 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4968\n", + "Function value obtained: -45.6238\n", + "Current minimum: -49.6017\n", + "Iteration No: 110 started. Searching for the next optimal point.\n", + "Iteration No: 110 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5985\n", + "Function value obtained: -47.4828\n", + "Current minimum: -49.6017\n", + "Iteration No: 111 started. Searching for the next optimal point.\n", + "Iteration No: 111 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5077\n", + "Function value obtained: -46.7207\n", + "Current minimum: -49.6017\n", + "Iteration No: 112 started. Searching for the next optimal point.\n", + "Iteration No: 112 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5293\n", + "Function value obtained: -46.3870\n", + "Current minimum: -49.6017\n", + "Iteration No: 113 started. Searching for the next optimal point.\n", + "Iteration No: 113 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4890\n", + "Function value obtained: -47.6239\n", + "Current minimum: -49.6017\n", + "Iteration No: 114 started. Searching for the next optimal point.\n", + "Iteration No: 114 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5437\n", + "Function value obtained: -46.1445\n", + "Current minimum: -49.6017\n", + "Iteration No: 115 started. Searching for the next optimal point.\n", + "Iteration No: 115 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4350\n", + "Function value obtained: -47.7099\n", + "Current minimum: -49.6017\n", + "Iteration No: 116 started. Searching for the next optimal point.\n", + "Iteration No: 116 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4450\n", + "Function value obtained: -47.2153\n", + "Current minimum: -49.6017\n", + "Iteration No: 117 started. Searching for the next optimal point.\n", + "Iteration No: 117 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5301\n", + "Function value obtained: -46.0510\n", + "Current minimum: -49.6017\n", + "Iteration No: 118 started. Searching for the next optimal point.\n", + "Iteration No: 118 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6147\n", + "Function value obtained: -46.7348\n", + "Current minimum: -49.6017\n", + "Iteration No: 119 started. Searching for the next optimal point.\n", + "Iteration No: 119 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4782\n", + "Function value obtained: -48.0223\n", + "Current minimum: -49.6017\n", + "Iteration No: 120 started. Searching for the next optimal point.\n", + "Iteration No: 120 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5107\n", + "Function value obtained: -45.9638\n", + "Current minimum: -49.6017\n", + "Iteration No: 121 started. Searching for the next optimal point.\n", + "Iteration No: 121 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5445\n", + "Function value obtained: -47.4704\n", + "Current minimum: -49.6017\n", + "Iteration No: 122 started. Searching for the next optimal point.\n", + "Iteration No: 122 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4802\n", + "Function value obtained: -46.3621\n", + "Current minimum: -49.6017\n", + "Iteration No: 123 started. Searching for the next optimal point.\n", + "Iteration No: 123 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4472\n", + "Function value obtained: -48.2987\n", + "Current minimum: -49.6017\n", + "Iteration No: 124 started. Searching for the next optimal point.\n", + "Iteration No: 124 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4813\n", + "Function value obtained: -45.8185\n", + "Current minimum: -49.6017\n", + "Iteration No: 125 started. Searching for the next optimal point.\n", + "Iteration No: 125 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5345\n", + "Function value obtained: -46.9240\n", + "Current minimum: -49.6017\n", + "Iteration No: 126 started. Searching for the next optimal point.\n", + "Iteration No: 126 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6460\n", + "Function value obtained: -45.6050\n", + "Current minimum: -49.6017\n", + "Iteration No: 127 started. Searching for the next optimal point.\n", + "Iteration No: 127 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5271\n", + "Function value obtained: -45.5833\n", + "Current minimum: -49.6017\n", + "Iteration No: 128 started. Searching for the next optimal point.\n", + "Iteration No: 128 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5524\n", + "Function value obtained: -45.4827\n", + "Current minimum: -49.6017\n", + "Iteration No: 129 started. Searching for the next optimal point.\n", + "Iteration No: 129 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5740\n", + "Function value obtained: -48.2536\n", + "Current minimum: -49.6017\n", + "Iteration No: 130 started. Searching for the next optimal point.\n", + "Iteration No: 130 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4685\n", + "Function value obtained: -46.3540\n", + "Current minimum: -49.6017\n", + "Iteration No: 131 started. Searching for the next optimal point.\n", + "Iteration No: 131 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5441\n", + "Function value obtained: -47.9790\n", + "Current minimum: -49.6017\n", + "Iteration No: 132 started. Searching for the next optimal point.\n", + "Iteration No: 132 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5442\n", + "Function value obtained: -46.5460\n", + "Current minimum: -49.6017\n", + "Iteration No: 133 started. Searching for the next optimal point.\n", + "Iteration No: 133 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4367\n", + "Function value obtained: -49.8897\n", + "Current minimum: -49.8897\n", + "Iteration No: 134 started. Searching for the next optimal point.\n", + "Iteration No: 134 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5285\n", + "Function value obtained: -48.0609\n", + "Current minimum: -49.8897\n", + "Iteration No: 135 started. Searching for the next optimal point.\n", + "Iteration No: 135 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5231\n", + "Function value obtained: -45.9417\n", + "Current minimum: -49.8897\n", + "Iteration No: 136 started. Searching for the next optimal point.\n", + "Iteration No: 136 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5069\n", + "Function value obtained: -48.1052\n", + "Current minimum: -49.8897\n", + "Iteration No: 137 started. Searching for the next optimal point.\n", + "Iteration No: 137 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4651\n", + "Function value obtained: -47.1823\n", + "Current minimum: -49.8897\n", + "Iteration No: 138 started. Searching for the next optimal point.\n", + "Iteration No: 138 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5213\n", + "Function value obtained: -46.5411\n", + "Current minimum: -49.8897\n", + "Iteration No: 139 started. Searching for the next optimal point.\n", + "Iteration No: 139 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4664\n", + "Function value obtained: -44.4394\n", + "Current minimum: -49.8897\n", + "Iteration No: 140 started. Searching for the next optimal point.\n", + "Iteration No: 140 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7325\n", + "Function value obtained: -48.4451\n", + "Current minimum: -49.8897\n", + "Iteration No: 141 started. Searching for the next optimal point.\n", + "Iteration No: 141 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5663\n", + "Function value obtained: -46.7940\n", + "Current minimum: -49.8897\n", + "Iteration No: 142 started. Searching for the next optimal point.\n", + "Iteration No: 142 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5296\n", + "Function value obtained: -47.4213\n", + "Current minimum: -49.8897\n", + "Iteration No: 143 started. Searching for the next optimal point.\n", + "Iteration No: 143 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5615\n", + "Function value obtained: -44.7370\n", + "Current minimum: -49.8897\n", + "Iteration No: 144 started. Searching for the next optimal point.\n", + "Iteration No: 144 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4711\n", + "Function value obtained: -46.5875\n", + "Current minimum: -49.8897\n", + "Iteration No: 145 started. Searching for the next optimal point.\n", + "Iteration No: 145 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4040\n", + "Function value obtained: -46.5380\n", + "Current minimum: -49.8897\n", + "Iteration No: 146 started. Searching for the next optimal point.\n", + "Iteration No: 146 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4615\n", + "Function value obtained: -47.0075\n", + "Current minimum: -49.8897\n", + "Iteration No: 147 started. Searching for the next optimal point.\n", + "Iteration No: 147 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5457\n", + "Function value obtained: -47.6239\n", + "Current minimum: -49.8897\n", + "Iteration No: 148 started. Searching for the next optimal point.\n", + "Iteration No: 148 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4523\n", + "Function value obtained: -45.9532\n", + "Current minimum: -49.8897\n", + "Iteration No: 149 started. Searching for the next optimal point.\n", + "Iteration No: 149 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5191\n", + "Function value obtained: -47.6434\n", + "Current minimum: -49.8897\n", + "Iteration No: 150 started. Searching for the next optimal point.\n", + "Iteration No: 150 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4987\n", + "Function value obtained: -45.9662\n", + "Current minimum: -49.8897\n", + "Iteration No: 151 started. Searching for the next optimal point.\n", + "Iteration No: 151 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5810\n", + "Function value obtained: -46.5016\n", + "Current minimum: -49.8897\n", + "Iteration No: 152 started. Searching for the next optimal point.\n", + "Iteration No: 152 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4548\n", + "Function value obtained: -46.2267\n", + "Current minimum: -49.8897\n", + "Iteration No: 153 started. Searching for the next optimal point.\n", + "Iteration No: 153 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4238\n", + "Function value obtained: -47.4453\n", + "Current minimum: -49.8897\n", + "Iteration No: 154 started. Searching for the next optimal point.\n", + "Iteration No: 154 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5048\n", + "Function value obtained: -47.2020\n", + "Current minimum: -49.8897\n", + "Iteration No: 155 started. Searching for the next optimal point.\n", + "Iteration No: 155 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4631\n", + "Function value obtained: -47.1068\n", + "Current minimum: -49.8897\n", + "Iteration No: 156 started. Searching for the next optimal point.\n", + "Iteration No: 156 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3817\n", + "Function value obtained: -48.2429\n", + "Current minimum: -49.8897\n", + "Iteration No: 157 started. Searching for the next optimal point.\n", + "Iteration No: 157 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4986\n", + "Function value obtained: -44.8097\n", + "Current minimum: -49.8897\n", + "Iteration No: 158 started. Searching for the next optimal point.\n", + "Iteration No: 158 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4233\n", + "Function value obtained: -46.8809\n", + "Current minimum: -49.8897\n", + "Iteration No: 159 started. Searching for the next optimal point.\n", + "Iteration No: 159 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5612\n", + "Function value obtained: -45.5597\n", + "Current minimum: -49.8897\n", + "Iteration No: 160 started. Searching for the next optimal point.\n", + "Iteration No: 160 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6052\n", + "Function value obtained: -46.4952\n", + "Current minimum: -49.8897\n", + "Iteration No: 161 started. Searching for the next optimal point.\n", + "Iteration No: 161 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5001\n", + "Function value obtained: -46.6400\n", + "Current minimum: -49.8897\n", + "Iteration No: 162 started. Searching for the next optimal point.\n", + "Iteration No: 162 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6195\n", + "Function value obtained: -46.5302\n", + "Current minimum: -49.8897\n", + "Iteration No: 163 started. Searching for the next optimal point.\n", + "Iteration No: 163 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5431\n", + "Function value obtained: -47.6782\n", + "Current minimum: -49.8897\n", + "Iteration No: 164 started. Searching for the next optimal point.\n", + "Iteration No: 164 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4370\n", + "Function value obtained: -47.6993\n", + "Current minimum: -49.8897\n", + "Iteration No: 165 started. Searching for the next optimal point.\n", + "Iteration No: 165 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5255\n", + "Function value obtained: -10.5757\n", + "Current minimum: -49.8897\n", + "Iteration No: 166 started. Searching for the next optimal point.\n", + "Iteration No: 166 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4695\n", + "Function value obtained: -48.1290\n", + "Current minimum: -49.8897\n", + "Iteration No: 167 started. Searching for the next optimal point.\n", + "Iteration No: 167 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5103\n", + "Function value obtained: -46.8644\n", + "Current minimum: -49.8897\n", + "Iteration No: 168 started. Searching for the next optimal point.\n", + "Iteration No: 168 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4537\n", + "Function value obtained: -46.8415\n", + "Current minimum: -49.8897\n", + "Iteration No: 169 started. Searching for the next optimal point.\n", + "Iteration No: 169 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4604\n", + "Function value obtained: -47.4611\n", + "Current minimum: -49.8897\n", + "Iteration No: 170 started. Searching for the next optimal point.\n", + "Iteration No: 170 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5201\n", + "Function value obtained: -45.5961\n", + "Current minimum: -49.8897\n", + "Iteration No: 171 started. Searching for the next optimal point.\n", + "Iteration No: 171 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5280\n", + "Function value obtained: -44.9130\n", + "Current minimum: -49.8897\n", + "Iteration No: 172 started. Searching for the next optimal point.\n", + "Iteration No: 172 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4738\n", + "Function value obtained: -47.5096\n", + "Current minimum: -49.8897\n", + "Iteration No: 173 started. Searching for the next optimal point.\n", + "Iteration No: 173 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5386\n", + "Function value obtained: -46.5298\n", + "Current minimum: -49.8897\n", + "Iteration No: 174 started. Searching for the next optimal point.\n", + "Iteration No: 174 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5460\n", + "Function value obtained: -48.4569\n", + "Current minimum: -49.8897\n", + "Iteration No: 175 started. Searching for the next optimal point.\n", + "Iteration No: 175 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4322\n", + "Function value obtained: -46.6290\n", + "Current minimum: -49.8897\n", + "Iteration No: 176 started. Searching for the next optimal point.\n", + "Iteration No: 176 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5870\n", + "Function value obtained: -46.9834\n", + "Current minimum: -49.8897\n", + "Iteration No: 177 started. Searching for the next optimal point.\n", + "Iteration No: 177 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5292\n", + "Function value obtained: -45.0813\n", + "Current minimum: -49.8897\n", + "Iteration No: 178 started. Searching for the next optimal point.\n", + "Iteration No: 178 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5267\n", + "Function value obtained: -49.7659\n", + "Current minimum: -49.8897\n", + "Iteration No: 179 started. Searching for the next optimal point.\n", + "Iteration No: 179 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5247\n", + "Function value obtained: -47.7063\n", + "Current minimum: -49.8897\n", + "Iteration No: 180 started. Searching for the next optimal point.\n", + "Iteration No: 180 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4800\n", + "Function value obtained: -46.8807\n", + "Current minimum: -49.8897\n", + "Iteration No: 181 started. Searching for the next optimal point.\n", + "Iteration No: 181 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5016\n", + "Function value obtained: -46.6104\n", + "Current minimum: -49.8897\n", + "Iteration No: 182 started. Searching for the next optimal point.\n", + "Iteration No: 182 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3970\n", + "Function value obtained: -45.0529\n", + "Current minimum: -49.8897\n", + "Iteration No: 183 started. Searching for the next optimal point.\n", + "Iteration No: 183 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5808\n", + "Function value obtained: -47.7305\n", + "Current minimum: -49.8897\n", + "Iteration No: 184 started. Searching for the next optimal point.\n", + "Iteration No: 184 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5231\n", + "Function value obtained: -46.8753\n", + "Current minimum: -49.8897\n", + "Iteration No: 185 started. Searching for the next optimal point.\n", + "Iteration No: 185 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4697\n", + "Function value obtained: -46.4229\n", + "Current minimum: -49.8897\n", + "Iteration No: 186 started. Searching for the next optimal point.\n", + "Iteration No: 186 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4536\n", + "Function value obtained: -46.3220\n", + "Current minimum: -49.8897\n", + "Iteration No: 187 started. Searching for the next optimal point.\n", + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4468\n", + "Function value obtained: -45.0930\n", + "Current minimum: -49.8897\n", + "Iteration No: 188 started. Searching for the next optimal point.\n", + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4897\n", + "Function value obtained: -46.2899\n", + "Current minimum: -49.8897\n", + "Iteration No: 189 started. Searching for the next optimal point.\n", + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5649\n", + "Function value obtained: -45.7537\n", + "Current minimum: -49.8897\n", + "Iteration No: 190 started. Searching for the next optimal point.\n", + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5258\n", + "Function value obtained: -47.8918\n", + "Current minimum: -49.8897\n", + "Iteration No: 191 started. Searching for the next optimal point.\n", + "Iteration No: 191 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4762\n", + "Function value obtained: -44.7468\n", + "Current minimum: -49.8897\n", + "Iteration No: 192 started. Searching for the next optimal point.\n", + "Iteration No: 192 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4744\n", + "Function value obtained: -45.6541\n", + "Current minimum: -49.8897\n", + "Iteration No: 193 started. Searching for the next optimal point.\n", + "Iteration No: 193 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4850\n", + "Function value obtained: -47.9981\n", + "Current minimum: -49.8897\n", + "Iteration No: 194 started. Searching for the next optimal point.\n", + "Iteration No: 194 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6339\n", + "Function value obtained: -48.7292\n", + "Current minimum: -49.8897\n", + "Iteration No: 195 started. Searching for the next optimal point.\n", + "Iteration No: 195 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4541\n", + "Function value obtained: -45.9848\n", + "Current minimum: -49.8897\n", + "Iteration No: 196 started. Searching for the next optimal point.\n", + "Iteration No: 196 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4691\n", + "Function value obtained: -47.4092\n", + "Current minimum: -49.8897\n", + "Iteration No: 197 started. Searching for the next optimal point.\n", + "Iteration No: 197 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4781\n", + "Function value obtained: -47.0885\n", + "Current minimum: -49.8897\n", + "Iteration No: 198 started. Searching for the next optimal point.\n", + "Iteration No: 198 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4757\n", + "Function value obtained: -46.2062\n", + "Current minimum: -49.8897\n", + "Iteration No: 199 started. Searching for the next optimal point.\n", + "Iteration No: 199 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5059\n", + "Function value obtained: -47.5081\n", + "Current minimum: -49.8897\n", + "Iteration No: 200 started. Searching for the next optimal point.\n", + "Iteration No: 200 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5575\n", + "Function value obtained: -45.9276\n", + "Current minimum: -49.8897\n", + "Iteration No: 201 started. Searching for the next optimal point.\n", + "Iteration No: 201 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5190\n", + "Function value obtained: -46.9264\n", + "Current minimum: -49.8897\n", + "Iteration No: 202 started. Searching for the next optimal point.\n", + "Iteration No: 202 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4911\n", + "Function value obtained: -46.2056\n", + "Current minimum: -49.8897\n", + "Iteration No: 203 started. Searching for the next optimal point.\n", + "Iteration No: 203 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4858\n", + "Function value obtained: -47.2440\n", + "Current minimum: -49.8897\n", + "Iteration No: 204 started. Searching for the next optimal point.\n", + "Iteration No: 204 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4779\n", + "Function value obtained: -46.6488\n", + "Current minimum: -49.8897\n", + "Iteration No: 205 started. Searching for the next optimal point.\n", + "Iteration No: 205 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5805\n", + "Function value obtained: -46.4220\n", + "Current minimum: -49.8897\n", + "Iteration No: 206 started. Searching for the next optimal point.\n", + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4339\n", + "Function value obtained: -46.7641\n", + "Current minimum: -49.8897\n", + "Iteration No: 207 started. Searching for the next optimal point.\n", + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3939\n", + "Function value obtained: -46.9997\n", + "Current minimum: -49.8897\n", + "Iteration No: 208 started. Searching for the next optimal point.\n", + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5466\n", + "Function value obtained: -48.8444\n", + "Current minimum: -49.8897\n", + "Iteration No: 209 started. Searching for the next optimal point.\n", + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4416\n", + "Function value obtained: -46.6399\n", + "Current minimum: -49.8897\n", + "Iteration No: 210 started. Searching for the next optimal point.\n", + "Iteration No: 210 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4550\n", + "Function value obtained: -45.9676\n", + "Current minimum: -49.8897\n", + "Iteration No: 211 started. Searching for the next optimal point.\n", + "Iteration No: 211 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5161\n", + "Function value obtained: -48.5639\n", + "Current minimum: -49.8897\n", + "Iteration No: 212 started. Searching for the next optimal point.\n", + "Iteration No: 212 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4859\n", + "Function value obtained: -46.1388\n", + "Current minimum: -49.8897\n", + "Iteration No: 213 started. Searching for the next optimal point.\n", + "Iteration No: 213 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5181\n", + "Function value obtained: -46.3721\n", + "Current minimum: -49.8897\n", + "Iteration No: 214 started. Searching for the next optimal point.\n", + "Iteration No: 214 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5108\n", + "Function value obtained: -46.5996\n", + "Current minimum: -49.8897\n", + "Iteration No: 215 started. Searching for the next optimal point.\n", + "Iteration No: 215 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5101\n", + "Function value obtained: -48.4447\n", + "Current minimum: -49.8897\n", + "Iteration No: 216 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.047611662929937286] before, using random point [0.018415831307791897]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 216 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4304\n", + "Function value obtained: -29.1544\n", + "Current minimum: -49.8897\n", + "Iteration No: 217 started. Searching for the next optimal point.\n", + "Iteration No: 217 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6251\n", + "Function value obtained: -47.1906\n", + "Current minimum: -49.8897\n", + "Iteration No: 218 started. Searching for the next optimal point.\n", + "Iteration No: 218 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3746\n", + "Function value obtained: -47.6795\n", + "Current minimum: -49.8897\n", + "Iteration No: 219 started. Searching for the next optimal point.\n", + "Iteration No: 219 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4408\n", + "Function value obtained: -46.9766\n", + "Current minimum: -49.8897\n", + "Iteration No: 220 started. Searching for the next optimal point.\n", + "Iteration No: 220 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4518\n", + "Function value obtained: -47.4589\n", + "Current minimum: -49.8897\n", + "Iteration No: 221 started. Searching for the next optimal point.\n", + "Iteration No: 221 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4711\n", + "Function value obtained: -46.4065\n", + "Current minimum: -49.8897\n", + "Iteration No: 222 started. Searching for the next optimal point.\n", + "Iteration No: 222 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4315\n", + "Function value obtained: -46.8208\n", + "Current minimum: -49.8897\n", + "Iteration No: 223 started. Searching for the next optimal point.\n", + "Iteration No: 223 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4927\n", + "Function value obtained: -48.4958\n", + "Current minimum: -49.8897\n", + "Iteration No: 224 started. Searching for the next optimal point.\n", + "Iteration No: 224 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4322\n", + "Function value obtained: -48.3613\n", + "Current minimum: -49.8897\n", + "Iteration No: 225 started. Searching for the next optimal point.\n", + "Iteration No: 225 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3822\n", + "Function value obtained: -47.1586\n", + "Current minimum: -49.8897\n", + "Iteration No: 226 started. Searching for the next optimal point.\n", + "Iteration No: 226 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4858\n", + "Function value obtained: -46.6550\n", + "Current minimum: -49.8897\n", + "Iteration No: 227 started. Searching for the next optimal point.\n", + "Iteration No: 227 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5341\n", + "Function value obtained: -45.6371\n", + "Current minimum: -49.8897\n", + "Iteration No: 228 started. Searching for the next optimal point.\n", + "Iteration No: 228 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6043\n", + "Function value obtained: -46.8676\n", + "Current minimum: -49.8897\n", + "Iteration No: 229 started. Searching for the next optimal point.\n", + "Iteration No: 229 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4331\n", + "Function value obtained: -45.4488\n", + "Current minimum: -49.8897\n", + "Iteration No: 230 started. Searching for the next optimal point.\n", + "Iteration No: 230 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4794\n", + "Function value obtained: -43.7159\n", + "Current minimum: -49.8897\n", + "Iteration No: 231 started. Searching for the next optimal point.\n", + "Iteration No: 231 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4488\n", + "Function value obtained: -47.7269\n", + "Current minimum: -49.8897\n", + "Iteration No: 232 started. Searching for the next optimal point.\n", + "Iteration No: 232 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3763\n", + "Function value obtained: -47.0402\n", + "Current minimum: -49.8897\n", + "Iteration No: 233 started. Searching for the next optimal point.\n", + "Iteration No: 233 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4456\n", + "Function value obtained: -46.3409\n", + "Current minimum: -49.8897\n", + "Iteration No: 234 started. Searching for the next optimal point.\n", + "Iteration No: 234 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5082\n", + "Function value obtained: -44.8427\n", + "Current minimum: -49.8897\n", + "Iteration No: 235 started. Searching for the next optimal point.\n", + "Iteration No: 235 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5316\n", + "Function value obtained: -45.9650\n", + "Current minimum: -49.8897\n", + "Iteration No: 236 started. Searching for the next optimal point.\n", + "Iteration No: 236 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3972\n", + "Function value obtained: -47.7037\n", + "Current minimum: -49.8897\n", + "Iteration No: 237 started. Searching for the next optimal point.\n", + "Iteration No: 237 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4648\n", + "Function value obtained: -47.3788\n", + "Current minimum: -49.8897\n", + "Iteration No: 238 started. Searching for the next optimal point.\n", + "Iteration No: 238 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5315\n", + "Function value obtained: -48.0615\n", + "Current minimum: -49.8897\n", + "Iteration No: 239 started. Searching for the next optimal point.\n", + "Iteration No: 239 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5314\n", + "Function value obtained: -45.4083\n", + "Current minimum: -49.8897\n", + "Iteration No: 240 started. Searching for the next optimal point.\n", + "Iteration No: 240 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4335\n", + "Function value obtained: -48.1749\n", + "Current minimum: -49.8897\n", + "Iteration No: 241 started. Searching for the next optimal point.\n", + "Iteration No: 241 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4931\n", + "Function value obtained: -44.8295\n", + "Current minimum: -49.8897\n", + "Iteration No: 242 started. Searching for the next optimal point.\n", + "Iteration No: 242 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5030\n", + "Function value obtained: -46.7296\n", + "Current minimum: -49.8897\n", + "Iteration No: 243 started. Searching for the next optimal point.\n", + "Iteration No: 243 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4114\n", + "Function value obtained: -45.8937\n", + "Current minimum: -49.8897\n", + "Iteration No: 244 started. Searching for the next optimal point.\n", + "Iteration No: 244 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5107\n", + "Function value obtained: -47.4962\n", + "Current minimum: -49.8897\n", + "Iteration No: 245 started. Searching for the next optimal point.\n", + "Iteration No: 245 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4967\n", + "Function value obtained: -46.7295\n", + "Current minimum: -49.8897\n", + "Iteration No: 246 started. Searching for the next optimal point.\n", + "Iteration No: 246 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4799\n", + "Function value obtained: -43.7786\n", + "Current minimum: -49.8897\n", + "Iteration No: 247 started. Searching for the next optimal point.\n", + "Iteration No: 247 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4795\n", + "Function value obtained: -47.1058\n", + "Current minimum: -49.8897\n", + "Iteration No: 248 started. Searching for the next optimal point.\n", + "Iteration No: 248 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4587\n", + "Function value obtained: -49.6577\n", + "Current minimum: -49.8897\n", + "Iteration No: 249 started. Searching for the next optimal point.\n", + "Iteration No: 249 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5489\n", + "Function value obtained: -49.3541\n", + "Current minimum: -49.8897\n", + "Iteration No: 250 started. Searching for the next optimal point.\n", + "Iteration No: 250 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5626\n", + "Function value obtained: -47.7101\n", + "Current minimum: -49.8897\n", + "Iteration No: 251 started. Searching for the next optimal point.\n", + "Iteration No: 251 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4293\n", + "Function value obtained: -45.9207\n", + "Current minimum: -49.8897\n", + "Iteration No: 252 started. Searching for the next optimal point.\n", + "Iteration No: 252 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3498\n", + "Function value obtained: -47.1748\n", + "Current minimum: -49.8897\n", + "Iteration No: 253 started. Searching for the next optimal point.\n", + "Iteration No: 253 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4637\n", + "Function value obtained: -48.7569\n", + "Current minimum: -49.8897\n", + "Iteration No: 254 started. Searching for the next optimal point.\n", + "Iteration No: 254 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4763\n", + "Function value obtained: -48.4897\n", + "Current minimum: -49.8897\n", + "Iteration No: 255 started. Searching for the next optimal point.\n", + "Iteration No: 255 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4182\n", + "Function value obtained: -40.4936\n", + "Current minimum: -49.8897\n", + "Iteration No: 256 started. Searching for the next optimal point.\n", + "Iteration No: 256 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5062\n", + "Function value obtained: -45.8526\n", + "Current minimum: -49.8897\n", + "Iteration No: 257 started. Searching for the next optimal point.\n", + "Iteration No: 257 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4394\n", + "Function value obtained: -47.1508\n", + "Current minimum: -49.8897\n", + "Iteration No: 258 started. Searching for the next optimal point.\n", + "Iteration No: 258 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5217\n", + "Function value obtained: -45.7852\n", + "Current minimum: -49.8897\n", + "Iteration No: 259 started. Searching for the next optimal point.\n", + "Iteration No: 259 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4756\n", + "Function value obtained: -46.8237\n", + "Current minimum: -49.8897\n", + "Iteration No: 260 started. Searching for the next optimal point.\n", + "Iteration No: 260 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4404\n", + "Function value obtained: -46.1407\n", + "Current minimum: -49.8897\n", + "Iteration No: 261 started. Searching for the next optimal point.\n", + "Iteration No: 261 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6887\n", + "Function value obtained: -48.1504\n", + "Current minimum: -49.8897\n", + "Iteration No: 262 started. Searching for the next optimal point.\n", + "Iteration No: 262 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4078\n", + "Function value obtained: -47.5959\n", + "Current minimum: -49.8897\n", + "Iteration No: 263 started. Searching for the next optimal point.\n", + "Iteration No: 263 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5040\n", + "Function value obtained: -46.7583\n", + "Current minimum: -49.8897\n", + "Iteration No: 264 started. Searching for the next optimal point.\n", + "Iteration No: 264 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4849\n", + "Function value obtained: -47.5103\n", + "Current minimum: -49.8897\n", + "Iteration No: 265 started. Searching for the next optimal point.\n", + "Iteration No: 265 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4771\n", + "Function value obtained: -47.8489\n", + "Current minimum: -49.8897\n", + "Iteration No: 266 started. Searching for the next optimal point.\n", + "Iteration No: 266 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4587\n", + "Function value obtained: -45.8764\n", + "Current minimum: -49.8897\n", + "Iteration No: 267 started. Searching for the next optimal point.\n", + "Iteration No: 267 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4583\n", + "Function value obtained: -46.5789\n", + "Current minimum: -49.8897\n", + "Iteration No: 268 started. Searching for the next optimal point.\n", + "Iteration No: 268 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4331\n", + "Function value obtained: -46.0664\n", + "Current minimum: -49.8897\n", + "Iteration No: 269 started. Searching for the next optimal point.\n", + "Iteration No: 269 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4405\n", + "Function value obtained: -47.8028\n", + "Current minimum: -49.8897\n", + "Iteration No: 270 started. Searching for the next optimal point.\n", + "Iteration No: 270 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4182\n", + "Function value obtained: -46.2383\n", + "Current minimum: -49.8897\n", + "Iteration No: 271 started. Searching for the next optimal point.\n", + "Iteration No: 271 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5164\n", + "Function value obtained: -45.5827\n", + "Current minimum: -49.8897\n", + "Iteration No: 272 started. Searching for the next optimal point.\n", + "Iteration No: 272 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4859\n", + "Function value obtained: -47.0983\n", + "Current minimum: -49.8897\n", + "Iteration No: 273 started. Searching for the next optimal point.\n", + "Iteration No: 273 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5458\n", + "Function value obtained: -48.8226\n", + "Current minimum: -49.8897\n", + "Iteration No: 274 started. Searching for the next optimal point.\n", + "Iteration No: 274 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4604\n", + "Function value obtained: -47.5462\n", + "Current minimum: -49.8897\n", + "Iteration No: 275 started. Searching for the next optimal point.\n", + "Iteration No: 275 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4289\n", + "Function value obtained: -47.3570\n", + "Current minimum: -49.8897\n", + "Iteration No: 276 started. Searching for the next optimal point.\n", + "Iteration No: 276 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3581\n", + "Function value obtained: -46.5619\n", + "Current minimum: -49.8897\n", + "Iteration No: 277 started. Searching for the next optimal point.\n", + "Iteration No: 277 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4701\n", + "Function value obtained: -45.2298\n", + "Current minimum: -49.8897\n", + "Iteration No: 278 started. Searching for the next optimal point.\n", + "Iteration No: 278 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4266\n", + "Function value obtained: -49.0624\n", + "Current minimum: -49.8897\n", + "Iteration No: 279 started. Searching for the next optimal point.\n", + "Iteration No: 279 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4952\n", + "Function value obtained: -45.3503\n", + "Current minimum: -49.8897\n", + "Iteration No: 280 started. Searching for the next optimal point.\n", + "Iteration No: 280 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4420\n", + "Function value obtained: -48.2820\n", + "Current minimum: -49.8897\n", + "Iteration No: 281 started. Searching for the next optimal point.\n", + "Iteration No: 281 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3905\n", + "Function value obtained: -46.8497\n", + "Current minimum: -49.8897\n", + "Iteration No: 282 started. Searching for the next optimal point.\n", + "Iteration No: 282 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4410\n", + "Function value obtained: -46.8442\n", + "Current minimum: -49.8897\n", + "Iteration No: 283 started. Searching for the next optimal point.\n", + "Iteration No: 283 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2640\n", + "Function value obtained: -47.1821\n", + "Current minimum: -49.8897\n", + "Iteration No: 284 started. Searching for the next optimal point.\n", + "Iteration No: 284 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4318\n", + "Function value obtained: -45.5262\n", + "Current minimum: -49.8897\n", + "Iteration No: 285 started. Searching for the next optimal point.\n", + "Iteration No: 285 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6499\n", + "Function value obtained: -49.1007\n", + "Current minimum: -49.8897\n", + "Iteration No: 286 started. Searching for the next optimal point.\n", + "Iteration No: 286 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5032\n", + "Function value obtained: -46.3078\n", + "Current minimum: -49.8897\n", + "Iteration No: 287 started. Searching for the next optimal point.\n", + "Iteration No: 287 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5046\n", + "Function value obtained: -44.4964\n", + "Current minimum: -49.8897\n", + "Iteration No: 288 started. Searching for the next optimal point.\n", + "Iteration No: 288 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4397\n", + "Function value obtained: -46.7686\n", + "Current minimum: -49.8897\n", + "Iteration No: 289 started. Searching for the next optimal point.\n", + "Iteration No: 289 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5065\n", + "Function value obtained: -46.5951\n", + "Current minimum: -49.8897\n", + "Iteration No: 290 started. Searching for the next optimal point.\n", + "Iteration No: 290 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4144\n", + "Function value obtained: -49.6134\n", + "Current minimum: -49.8897\n", + "Iteration No: 291 started. Searching for the next optimal point.\n", + "Iteration No: 291 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4564\n", + "Function value obtained: -46.9677\n", + "Current minimum: -49.8897\n", + "Iteration No: 292 started. Searching for the next optimal point.\n", + "Iteration No: 292 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4083\n", + "Function value obtained: -46.6134\n", + "Current minimum: -49.8897\n", + "Iteration No: 293 started. Searching for the next optimal point.\n", + "Iteration No: 293 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3414\n", + "Function value obtained: -47.6949\n", + "Current minimum: -49.8897\n", + "Iteration No: 294 started. Searching for the next optimal point.\n", + "Iteration No: 294 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4464\n", + "Function value obtained: -45.4689\n", + "Current minimum: -49.8897\n", + "Iteration No: 295 started. Searching for the next optimal point.\n", + "Iteration No: 295 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4637\n", + "Function value obtained: -45.1194\n", + "Current minimum: -49.8897\n", + "Iteration No: 296 started. Searching for the next optimal point.\n", + "Iteration No: 296 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5177\n", + "Function value obtained: -48.8048\n", + "Current minimum: -49.8897\n", + "Iteration No: 297 started. Searching for the next optimal point.\n", + "Iteration No: 297 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5104\n", + "Function value obtained: -46.8760\n", + "Current minimum: -49.8897\n", + "Iteration No: 298 started. Searching for the next optimal point.\n", + "Iteration No: 298 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4363\n", + "Function value obtained: -46.8663\n", + "Current minimum: -49.8897\n", + "Iteration No: 299 started. Searching for the next optimal point.\n", + "Iteration No: 299 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4296\n", + "Function value obtained: -47.4900\n", + "Current minimum: -49.8897\n", + "Iteration No: 300 started. Searching for the next optimal point.\n", + "Iteration No: 300 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5483\n", + "Function value obtained: -47.6654\n", + "Current minimum: -49.8897\n", + "CPU times: user 2min 10s, sys: 26.7 s, total: 2min 36s\n", + "Wall time: 7min 25s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-49.8897409867848, [0.05286591768013252])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", + "msy_gbrt.fun, msy_gbrt.x" + ] + }, + { + "cell_type": "markdown", "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", "metadata": {}, "source": [ @@ -941,9 +3350,13 @@ }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 9, "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -953,346 +3366,1536 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8895\n", - "Function value obtained: -1.9314\n", - "Current minimum: -1.9314\n", + "Time taken: 1.1826\n", + "Function value obtained: -7.4553\n", + "Current minimum: -7.4553\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.7702\n", - "Function value obtained: -83.4853\n", - "Current minimum: -83.4853\n", + "Time taken: 1.1341\n", + "Function value obtained: -0.0000\n", + "Current minimum: -7.4553\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.8837\n", - "Function value obtained: -4.3212\n", - "Current minimum: -83.4853\n", + "Time taken: 1.2756\n", + "Function value obtained: -4.4028\n", + "Current minimum: -7.4553\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.7844\n", - "Function value obtained: -1.8607\n", - "Current minimum: -83.4853\n", + "Time taken: 1.1568\n", + "Function value obtained: -5.8711\n", + "Current minimum: -7.4553\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.7663\n", - "Function value obtained: -66.8640\n", - "Current minimum: -83.4853\n", + "Time taken: 1.1990\n", + "Function value obtained: -0.2118\n", + "Current minimum: -7.4553\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.7465\n", - "Function value obtained: -7.5460\n", - "Current minimum: -83.4853\n", + "Time taken: 1.1679\n", + "Function value obtained: -0.0000\n", + "Current minimum: -7.4553\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.7858\n", - "Function value obtained: -48.6599\n", - "Current minimum: -83.4853\n", + "Time taken: 1.1591\n", + "Function value obtained: -2.3609\n", + "Current minimum: -7.4553\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.7636\n", - "Function value obtained: -1.9422\n", - "Current minimum: -83.4853\n", + "Time taken: 1.2370\n", + "Function value obtained: -0.0000\n", + "Current minimum: -7.4553\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8648\n", - "Function value obtained: -81.8343\n", - "Current minimum: -83.4853\n", + "Time taken: 1.1136\n", + "Function value obtained: -0.9760\n", + "Current minimum: -7.4553\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 0.9334\n", - "Function value obtained: -19.9633\n", - "Current minimum: -83.4853\n", + "Time taken: 6.0222\n", + "Function value obtained: -0.0000\n", + "Current minimum: -7.4553\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0032\n", - "Function value obtained: -87.3024\n", - "Current minimum: -87.3024\n", + "Time taken: 2.6276\n", + "Function value obtained: -9.8312\n", + "Current minimum: -9.8312\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0474\n", - "Function value obtained: -85.5118\n", - "Current minimum: -87.3024\n", + "Time taken: 2.5292\n", + "Function value obtained: -16.3186\n", + "Current minimum: -16.3186\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0281\n", - "Function value obtained: -85.6057\n", - "Current minimum: -87.3024\n", + "Time taken: 2.5773\n", + "Function value obtained: -52.3397\n", + "Current minimum: -52.3397\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 0.8791\n", - "Function value obtained: -83.3193\n", - "Current minimum: -87.3024\n", + "Time taken: 2.5389\n", + "Function value obtained: -80.4999\n", + "Current minimum: -80.4999\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0138\n", - "Function value obtained: -84.5095\n", - "Current minimum: -87.3024\n", + "Time taken: 2.5486\n", + "Function value obtained: -83.3830\n", + "Current minimum: -83.3830\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0012\n", - "Function value obtained: -87.0050\n", - "Current minimum: -87.3024\n", + "Time taken: 2.5781\n", + "Function value obtained: -85.2906\n", + "Current minimum: -85.2906\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9778\n", - "Function value obtained: -84.4120\n", - "Current minimum: -87.3024\n", + "Time taken: 2.6010\n", + "Function value obtained: -83.7895\n", + "Current minimum: -85.2906\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0535\n", - "Function value obtained: -83.0230\n", - "Current minimum: -87.3024\n", + "Time taken: 2.1588\n", + "Function value obtained: -84.0034\n", + "Current minimum: -85.2906\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0381\n", - "Function value obtained: -81.0072\n", - "Current minimum: -87.3024\n", + "Time taken: 1.8256\n", + "Function value obtained: -84.9165\n", + "Current minimum: -85.2906\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9801\n", - "Function value obtained: -86.3396\n", - "Current minimum: -87.3024\n", + "Time taken: 1.4439\n", + "Function value obtained: -85.3266\n", + "Current minimum: -85.3266\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9412\n", - "Function value obtained: -86.0437\n", - "Current minimum: -87.3024\n", + "Time taken: 1.3466\n", + "Function value obtained: -83.1760\n", + "Current minimum: -85.3266\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0107\n", - "Function value obtained: -87.1612\n", - "Current minimum: -87.3024\n", + "Time taken: 1.3850\n", + "Function value obtained: -85.6441\n", + "Current minimum: -85.6441\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0426\n", - "Function value obtained: -84.8570\n", - "Current minimum: -87.3024\n", + "Time taken: 1.6499\n", + "Function value obtained: -86.0217\n", + "Current minimum: -86.0217\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9731\n", - "Function value obtained: -86.3455\n", - "Current minimum: -87.3024\n", + "Time taken: 1.4183\n", + "Function value obtained: -81.2758\n", + "Current minimum: -86.0217\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0634\n", - "Function value obtained: -82.7459\n", - "Current minimum: -87.3024\n", + "Time taken: 1.4525\n", + "Function value obtained: -86.4711\n", + "Current minimum: -86.4711\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0838\n", - "Function value obtained: -85.1438\n", - "Current minimum: -87.3024\n", + "Time taken: 1.4082\n", + "Function value obtained: -84.7038\n", + "Current minimum: -86.4711\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0458\n", - "Function value obtained: -82.9107\n", - "Current minimum: -87.3024\n", + "Time taken: 1.4371\n", + "Function value obtained: -85.5746\n", + "Current minimum: -86.4711\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0000\n", - "Function value obtained: -83.1693\n", - "Current minimum: -87.3024\n", + "Time taken: 1.3616\n", + "Function value obtained: -83.9651\n", + "Current minimum: -86.4711\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0817\n", - "Function value obtained: -88.3016\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4229\n", + "Function value obtained: -84.9482\n", + "Current minimum: -86.4711\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0293\n", - "Function value obtained: -84.2473\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4596\n", + "Function value obtained: -87.2128\n", + "Current minimum: -87.2128\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9022\n", - "Function value obtained: -84.7010\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4209\n", + "Function value obtained: -1.9491\n", + "Current minimum: -87.2128\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0825\n", - "Function value obtained: -84.0562\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4119\n", + "Function value obtained: -82.4391\n", + "Current minimum: -87.2128\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0863\n", - "Function value obtained: -81.5943\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4297\n", + "Function value obtained: -84.4656\n", + "Current minimum: -87.2128\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0594\n", - "Function value obtained: -81.7522\n", - "Current minimum: -88.3016\n", + "Time taken: 1.3742\n", + "Function value obtained: -87.5589\n", + "Current minimum: -87.5589\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0530\n", - "Function value obtained: -84.6776\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4501\n", + "Function value obtained: -84.6758\n", + "Current minimum: -87.5589\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0158\n", - "Function value obtained: -84.9923\n", - "Current minimum: -88.3016\n", + "Time taken: 1.3994\n", + "Function value obtained: -83.8463\n", + "Current minimum: -87.5589\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0790\n", - "Function value obtained: -84.2549\n", - "Current minimum: -88.3016\n", + "Time taken: 1.3315\n", + "Function value obtained: -82.0701\n", + "Current minimum: -87.5589\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0874\n", - "Function value obtained: -86.2316\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4285\n", + "Function value obtained: -84.5005\n", + "Current minimum: -87.5589\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0445\n", - "Function value obtained: -83.9166\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4393\n", + "Function value obtained: -85.6002\n", + "Current minimum: -87.5589\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1374\n", - "Function value obtained: -85.5846\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4556\n", + "Function value obtained: -84.1980\n", + "Current minimum: -87.5589\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4393\n", - "Function value obtained: -85.8292\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4592\n", + "Function value obtained: -82.4640\n", + "Current minimum: -87.5589\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1425\n", - "Function value obtained: -84.7982\n", - "Current minimum: -88.3016\n", + "Time taken: 1.6511\n", + "Function value obtained: -87.7919\n", + "Current minimum: -87.7919\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0837\n", - "Function value obtained: -84.9636\n", - "Current minimum: -88.3016\n", + "Time taken: 1.5517\n", + "Function value obtained: -81.3267\n", + "Current minimum: -87.7919\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0810\n", - "Function value obtained: -80.9480\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4859\n", + "Function value obtained: -83.6141\n", + "Current minimum: -87.7919\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0476\n", - "Function value obtained: -81.6247\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4735\n", + "Function value obtained: -87.8643\n", + "Current minimum: -87.8643\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0960\n", - "Function value obtained: -83.5560\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4527\n", + "Function value obtained: -83.2510\n", + "Current minimum: -87.8643\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1526\n", - "Function value obtained: -83.6973\n", - "Current minimum: -88.3016\n", + "Time taken: 1.5046\n", + "Function value obtained: -86.9130\n", + "Current minimum: -87.8643\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1651\n", - "Function value obtained: -85.3829\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4827\n", + "Function value obtained: -83.3556\n", + "Current minimum: -87.8643\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1530\n", - "Function value obtained: -83.4624\n", - "Current minimum: -88.3016\n", + "Time taken: 1.4384\n", + "Function value obtained: -83.4610\n", + "Current minimum: -87.8643\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1107\n", - "Function value obtained: -83.4790\n", - "Current minimum: -88.3016\n", - "CPU times: user 1min 33s, sys: 9min 8s, total: 10min 41s\n", - "Wall time: 50.5 s\n" + "Time taken: 1.4393\n", + "Function value obtained: -85.4573\n", + "Current minimum: -87.8643\n", + "Iteration No: 51 started. Searching for the next optimal point.\n", + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4980\n", + "Function value obtained: -87.0808\n", + "Current minimum: -87.8643\n", + "Iteration No: 52 started. Searching for the next optimal point.\n", + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5822\n", + "Function value obtained: -88.7936\n", + "Current minimum: -88.7936\n", + "Iteration No: 53 started. Searching for the next optimal point.\n", + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4725\n", + "Function value obtained: -84.3028\n", + "Current minimum: -88.7936\n", + "Iteration No: 54 started. Searching for the next optimal point.\n", + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5056\n", + "Function value obtained: -85.6013\n", + "Current minimum: -88.7936\n", + "Iteration No: 55 started. Searching for the next optimal point.\n", + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5053\n", + "Function value obtained: -83.5249\n", + "Current minimum: -88.7936\n", + "Iteration No: 56 started. Searching for the next optimal point.\n", + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5376\n", + "Function value obtained: -82.9111\n", + "Current minimum: -88.7936\n", + "Iteration No: 57 started. Searching for the next optimal point.\n", + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5847\n", + "Function value obtained: -85.2942\n", + "Current minimum: -88.7936\n", + "Iteration No: 58 started. Searching for the next optimal point.\n", + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5688\n", + "Function value obtained: -86.9849\n", + "Current minimum: -88.7936\n", + "Iteration No: 59 started. Searching for the next optimal point.\n", + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5754\n", + "Function value obtained: -83.3894\n", + "Current minimum: -88.7936\n", + "Iteration No: 60 started. Searching for the next optimal point.\n", + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5956\n", + "Function value obtained: -87.2385\n", + "Current minimum: -88.7936\n", + "Iteration No: 61 started. Searching for the next optimal point.\n", + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7217\n", + "Function value obtained: -88.1977\n", + "Current minimum: -88.7936\n", + "Iteration No: 62 started. Searching for the next optimal point.\n", + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6260\n", + "Function value obtained: -85.9176\n", + "Current minimum: -88.7936\n", + "Iteration No: 63 started. Searching for the next optimal point.\n", + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5686\n", + "Function value obtained: -86.1229\n", + "Current minimum: -88.7936\n", + "Iteration No: 64 started. Searching for the next optimal point.\n", + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6506\n", + "Function value obtained: -87.0458\n", + "Current minimum: -88.7936\n", + "Iteration No: 65 started. Searching for the next optimal point.\n", + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5661\n", + "Function value obtained: -84.9915\n", + "Current minimum: -88.7936\n", + "Iteration No: 66 started. Searching for the next optimal point.\n", + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5983\n", + "Function value obtained: -82.9268\n", + "Current minimum: -88.7936\n", + "Iteration No: 67 started. Searching for the next optimal point.\n", + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5894\n", + "Function value obtained: -87.0604\n", + "Current minimum: -88.7936\n", + "Iteration No: 68 started. Searching for the next optimal point.\n", + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5748\n", + "Function value obtained: -83.9895\n", + "Current minimum: -88.7936\n", + "Iteration No: 69 started. Searching for the next optimal point.\n", + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6066\n", + "Function value obtained: -84.5049\n", + "Current minimum: -88.7936\n", + "Iteration No: 70 started. Searching for the next optimal point.\n", + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5568\n", + "Function value obtained: -85.2982\n", + "Current minimum: -88.7936\n", + "Iteration No: 71 started. Searching for the next optimal point.\n", + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6147\n", + "Function value obtained: -82.4611\n", + "Current minimum: -88.7936\n", + "Iteration No: 72 started. Searching for the next optimal point.\n", + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6405\n", + "Function value obtained: -86.2719\n", + "Current minimum: -88.7936\n", + "Iteration No: 73 started. Searching for the next optimal point.\n", + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6894\n", + "Function value obtained: -87.1919\n", + "Current minimum: -88.7936\n", + "Iteration No: 74 started. Searching for the next optimal point.\n", + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6873\n", + "Function value obtained: -86.2144\n", + "Current minimum: -88.7936\n", + "Iteration No: 75 started. Searching for the next optimal point.\n", + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7893\n", + "Function value obtained: -84.4256\n", + "Current minimum: -88.7936\n", + "Iteration No: 76 started. Searching for the next optimal point.\n", + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6642\n", + "Function value obtained: -85.9299\n", + "Current minimum: -88.7936\n", + "Iteration No: 77 started. Searching for the next optimal point.\n", + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7292\n", + "Function value obtained: -84.2092\n", + "Current minimum: -88.7936\n", + "Iteration No: 78 started. Searching for the next optimal point.\n", + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6602\n", + "Function value obtained: -83.4907\n", + "Current minimum: -88.7936\n", + "Iteration No: 79 started. Searching for the next optimal point.\n", + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7371\n", + "Function value obtained: -85.7356\n", + "Current minimum: -88.7936\n", + "Iteration No: 80 started. Searching for the next optimal point.\n", + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7526\n", + "Function value obtained: -86.5642\n", + "Current minimum: -88.7936\n", + "Iteration No: 81 started. Searching for the next optimal point.\n", + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7205\n", + "Function value obtained: -84.9649\n", + "Current minimum: -88.7936\n", + "Iteration No: 82 started. Searching for the next optimal point.\n", + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8873\n", + "Function value obtained: -84.4085\n", + "Current minimum: -88.7936\n", + "Iteration No: 83 started. Searching for the next optimal point.\n", + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7784\n", + "Function value obtained: -85.5729\n", + "Current minimum: -88.7936\n", + "Iteration No: 84 started. Searching for the next optimal point.\n", + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7582\n", + "Function value obtained: -85.6790\n", + "Current minimum: -88.7936\n", + "Iteration No: 85 started. Searching for the next optimal point.\n", + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7340\n", + "Function value obtained: -83.7601\n", + "Current minimum: -88.7936\n", + "Iteration No: 86 started. Searching for the next optimal point.\n", + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6939\n", + "Function value obtained: -83.4566\n", + "Current minimum: -88.7936\n", + "Iteration No: 87 started. Searching for the next optimal point.\n", + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9619\n", + "Function value obtained: -81.6177\n", + "Current minimum: -88.7936\n", + "Iteration No: 88 started. Searching for the next optimal point.\n", + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7582\n", + "Function value obtained: -87.3755\n", + "Current minimum: -88.7936\n", + "Iteration No: 89 started. Searching for the next optimal point.\n", + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7490\n", + "Function value obtained: -84.8986\n", + "Current minimum: -88.7936\n", + "Iteration No: 90 started. Searching for the next optimal point.\n", + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 1.7268\n", + "Function value obtained: -85.6259\n", + "Current minimum: -88.7936\n", + "Iteration No: 91 started. Searching for the next optimal point.\n", + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8012\n", + "Function value obtained: -83.1990\n", + "Current minimum: -88.7936\n", + "Iteration No: 92 started. Searching for the next optimal point.\n", + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9378\n", + "Function value obtained: -84.7424\n", + "Current minimum: -88.7936\n", + "Iteration No: 93 started. Searching for the next optimal point.\n", + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8454\n", + "Function value obtained: -84.3947\n", + "Current minimum: -88.7936\n", + "Iteration No: 94 started. Searching for the next optimal point.\n", + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8884\n", + "Function value obtained: -81.2216\n", + "Current minimum: -88.7936\n", + "Iteration No: 95 started. Searching for the next optimal point.\n", + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 1.8839\n", + "Function value obtained: -83.8132\n", + "Current minimum: -88.7936\n", + "Iteration No: 96 started. Searching for the next optimal point.\n", + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9101\n", + "Function value obtained: -83.3671\n", + "Current minimum: -88.7936\n", + "Iteration No: 97 started. Searching for the next optimal point.\n", + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9602\n", + "Function value obtained: -88.2126\n", + "Current minimum: -88.7936\n", + "Iteration No: 98 started. Searching for the next optimal point.\n", + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9470\n", + "Function value obtained: -84.5989\n", + "Current minimum: -88.7936\n", + "Iteration No: 99 started. Searching for the next optimal point.\n", + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9378\n", + "Function value obtained: -82.4315\n", + "Current minimum: -88.7936\n", + "Iteration No: 100 started. Searching for the next optimal point.\n", + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0896\n", + "Function value obtained: -85.8491\n", + "Current minimum: -88.7936\n", + "Iteration No: 101 started. Searching for the next optimal point.\n", + "Iteration No: 101 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1454\n", + "Function value obtained: -84.4998\n", + "Current minimum: -88.7936\n", + "Iteration No: 102 started. Searching for the next optimal point.\n", + "Iteration No: 102 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9997\n", + "Function value obtained: -85.8866\n", + "Current minimum: -88.7936\n", + "Iteration No: 103 started. Searching for the next optimal point.\n", + "Iteration No: 103 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0399\n", + "Function value obtained: -86.4996\n", + "Current minimum: -88.7936\n", + "Iteration No: 104 started. Searching for the next optimal point.\n", + "Iteration No: 104 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0249\n", + "Function value obtained: -84.7751\n", + "Current minimum: -88.7936\n", + "Iteration No: 105 started. Searching for the next optimal point.\n", + "Iteration No: 105 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0895\n", + "Function value obtained: -85.8201\n", + "Current minimum: -88.7936\n", + "Iteration No: 106 started. Searching for the next optimal point.\n", + "Iteration No: 106 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0012\n", + "Function value obtained: -86.1520\n", + "Current minimum: -88.7936\n", + "Iteration No: 107 started. Searching for the next optimal point.\n", + "Iteration No: 107 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0896\n", + "Function value obtained: -84.1424\n", + "Current minimum: -88.7936\n", + "Iteration No: 108 started. Searching for the next optimal point.\n", + "Iteration No: 108 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0959\n", + "Function value obtained: -83.4526\n", + "Current minimum: -88.7936\n", + "Iteration No: 109 started. Searching for the next optimal point.\n", + "Iteration No: 109 ended. Search finished for the next optimal point.\n", + "Time taken: 1.9556\n", + "Function value obtained: -84.7809\n", + "Current minimum: -88.7936\n", + "Iteration No: 110 started. Searching for the next optimal point.\n", + "Iteration No: 110 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0623\n", + "Function value obtained: -86.2088\n", + "Current minimum: -88.7936\n", + "Iteration No: 111 started. Searching for the next optimal point.\n", + "Iteration No: 111 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0576\n", + "Function value obtained: -82.8475\n", + "Current minimum: -88.7936\n", + "Iteration No: 112 started. Searching for the next optimal point.\n", + "Iteration No: 112 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0564\n", + "Function value obtained: -82.2386\n", + "Current minimum: -88.7936\n", + "Iteration No: 113 started. Searching for the next optimal point.\n", + "Iteration No: 113 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1342\n", + "Function value obtained: -82.7799\n", + "Current minimum: -88.7936\n", + "Iteration No: 114 started. Searching for the next optimal point.\n", + "Iteration No: 114 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1511\n", + "Function value obtained: -86.5301\n", + "Current minimum: -88.7936\n", + "Iteration No: 115 started. Searching for the next optimal point.\n", + "Iteration No: 115 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0862\n", + "Function value obtained: -84.3601\n", + "Current minimum: -88.7936\n", + "Iteration No: 116 started. Searching for the next optimal point.\n", + "Iteration No: 116 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0905\n", + "Function value obtained: -82.8963\n", + "Current minimum: -88.7936\n", + "Iteration No: 117 started. Searching for the next optimal point.\n", + "Iteration No: 117 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1330\n", + "Function value obtained: -82.3177\n", + "Current minimum: -88.7936\n", + "Iteration No: 118 started. Searching for the next optimal point.\n", + "Iteration No: 118 ended. Search finished for the next optimal point.\n", + "Time taken: 2.0847\n", + "Function value obtained: -83.1737\n", + "Current minimum: -88.7936\n", + "Iteration No: 119 started. Searching for the next optimal point.\n", + "Iteration No: 119 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2786\n", + "Function value obtained: -83.6992\n", + "Current minimum: -88.7936\n", + "Iteration No: 120 started. Searching for the next optimal point.\n", + "Iteration No: 120 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2530\n", + "Function value obtained: -85.0952\n", + "Current minimum: -88.7936\n", + "Iteration No: 121 started. Searching for the next optimal point.\n", + "Iteration No: 121 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3448\n", + "Function value obtained: -88.1863\n", + "Current minimum: -88.7936\n", + "Iteration No: 122 started. Searching for the next optimal point.\n", + "Iteration No: 122 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3633\n", + "Function value obtained: -86.2675\n", + "Current minimum: -88.7936\n", + "Iteration No: 123 started. Searching for the next optimal point.\n", + "Iteration No: 123 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2945\n", + "Function value obtained: -85.9106\n", + "Current minimum: -88.7936\n", + "Iteration No: 124 started. Searching for the next optimal point.\n", + "Iteration No: 124 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3613\n", + "Function value obtained: -84.3397\n", + "Current minimum: -88.7936\n", + "Iteration No: 125 started. Searching for the next optimal point.\n", + "Iteration No: 125 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2880\n", + "Function value obtained: -85.3764\n", + "Current minimum: -88.7936\n", + "Iteration No: 126 started. Searching for the next optimal point.\n", + "Iteration No: 126 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3144\n", + "Function value obtained: -86.4584\n", + "Current minimum: -88.7936\n", + "Iteration No: 127 started. Searching for the next optimal point.\n", + "Iteration No: 127 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3437\n", + "Function value obtained: -84.1038\n", + "Current minimum: -88.7936\n", + "Iteration No: 128 started. Searching for the next optimal point.\n", + "Iteration No: 128 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4015\n", + "Function value obtained: -83.6414\n", + "Current minimum: -88.7936\n", + "Iteration No: 129 started. Searching for the next optimal point.\n", + "Iteration No: 129 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4514\n", + "Function value obtained: -82.4285\n", + "Current minimum: -88.7936\n", + "Iteration No: 130 started. Searching for the next optimal point.\n", + "Iteration No: 130 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5143\n", + "Function value obtained: -83.9299\n", + "Current minimum: -88.7936\n", + "Iteration No: 131 started. Searching for the next optimal point.\n", + "Iteration No: 131 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4768\n", + "Function value obtained: -84.0752\n", + "Current minimum: -88.7936\n", + "Iteration No: 132 started. Searching for the next optimal point.\n", + "Iteration No: 132 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4899\n", + "Function value obtained: -85.5614\n", + "Current minimum: -88.7936\n", + "Iteration No: 133 started. Searching for the next optimal point.\n", + "Iteration No: 133 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4991\n", + "Function value obtained: -82.9782\n", + "Current minimum: -88.7936\n", + "Iteration No: 134 started. Searching for the next optimal point.\n", + "Iteration No: 134 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5405\n", + "Function value obtained: -82.5327\n", + "Current minimum: -88.7936\n", + "Iteration No: 135 started. Searching for the next optimal point.\n", + "Iteration No: 135 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4868\n", + "Function value obtained: -83.9966\n", + "Current minimum: -88.7936\n", + "Iteration No: 136 started. Searching for the next optimal point.\n", + "Iteration No: 136 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5473\n", + "Function value obtained: -88.9424\n", + "Current minimum: -88.9424\n", + "Iteration No: 137 started. Searching for the next optimal point.\n", + "Iteration No: 137 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5489\n", + "Function value obtained: -83.7380\n", + "Current minimum: -88.9424\n", + "Iteration No: 138 started. Searching for the next optimal point.\n", + "Iteration No: 138 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4844\n", + "Function value obtained: -84.4171\n", + "Current minimum: -88.9424\n", + "Iteration No: 139 started. Searching for the next optimal point.\n", + "Iteration No: 139 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5307\n", + "Function value obtained: -82.4263\n", + "Current minimum: -88.9424\n", + "Iteration No: 140 started. Searching for the next optimal point.\n", + "Iteration No: 140 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5930\n", + "Function value obtained: -85.9834\n", + "Current minimum: -88.9424\n", + "Iteration No: 141 started. Searching for the next optimal point.\n", + "Iteration No: 141 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5014\n", + "Function value obtained: -83.8756\n", + "Current minimum: -88.9424\n", + "Iteration No: 142 started. Searching for the next optimal point.\n", + "Iteration No: 142 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6132\n", + "Function value obtained: -82.3975\n", + "Current minimum: -88.9424\n", + "Iteration No: 143 started. Searching for the next optimal point.\n", + "Iteration No: 143 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6866\n", + "Function value obtained: -86.5412\n", + "Current minimum: -88.9424\n", + "Iteration No: 144 started. Searching for the next optimal point.\n", + "Iteration No: 144 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6383\n", + "Function value obtained: -88.2652\n", + "Current minimum: -88.9424\n", + "Iteration No: 145 started. Searching for the next optimal point.\n", + "Iteration No: 145 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5024\n", + "Function value obtained: -83.6148\n", + "Current minimum: -88.9424\n", + "Iteration No: 146 started. Searching for the next optimal point.\n", + "Iteration No: 146 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5122\n", + "Function value obtained: -84.3451\n", + "Current minimum: -88.9424\n", + "Iteration No: 147 started. Searching for the next optimal point.\n", + "Iteration No: 147 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6220\n", + "Function value obtained: -85.2411\n", + "Current minimum: -88.9424\n", + "Iteration No: 148 started. Searching for the next optimal point.\n", + "Iteration No: 148 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6338\n", + "Function value obtained: -86.6159\n", + "Current minimum: -88.9424\n", + "Iteration No: 149 started. Searching for the next optimal point.\n", + "Iteration No: 149 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6826\n", + "Function value obtained: -85.3567\n", + "Current minimum: -88.9424\n", + "Iteration No: 150 started. Searching for the next optimal point.\n", + "Iteration No: 150 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6434\n", + "Function value obtained: -86.8232\n", + "Current minimum: -88.9424\n", + "Iteration No: 151 started. Searching for the next optimal point.\n", + "Iteration No: 151 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7826\n", + "Function value obtained: -83.9509\n", + "Current minimum: -88.9424\n", + "Iteration No: 152 started. Searching for the next optimal point.\n", + "Iteration No: 152 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7286\n", + "Function value obtained: -85.4207\n", + "Current minimum: -88.9424\n", + "Iteration No: 153 started. Searching for the next optimal point.\n", + "Iteration No: 153 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8137\n", + "Function value obtained: -86.3905\n", + "Current minimum: -88.9424\n", + "Iteration No: 154 started. Searching for the next optimal point.\n", + "Iteration No: 154 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7077\n", + "Function value obtained: -84.2835\n", + "Current minimum: -88.9424\n", + "Iteration No: 155 started. Searching for the next optimal point.\n", + "Iteration No: 155 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8523\n", + "Function value obtained: -84.8326\n", + "Current minimum: -88.9424\n", + "Iteration No: 156 started. Searching for the next optimal point.\n", + "Iteration No: 156 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8403\n", + "Function value obtained: -84.5681\n", + "Current minimum: -88.9424\n", + "Iteration No: 157 started. Searching for the next optimal point.\n", + "Iteration No: 157 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8305\n", + "Function value obtained: -85.5560\n", + "Current minimum: -88.9424\n", + "Iteration No: 158 started. Searching for the next optimal point.\n", + "Iteration No: 158 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8183\n", + "Function value obtained: -82.0426\n", + "Current minimum: -88.9424\n", + "Iteration No: 159 started. Searching for the next optimal point.\n", + "Iteration No: 159 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7790\n", + "Function value obtained: -85.3996\n", + "Current minimum: -88.9424\n", + "Iteration No: 160 started. Searching for the next optimal point.\n", + "Iteration No: 160 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8958\n", + "Function value obtained: -83.6048\n", + "Current minimum: -88.9424\n", + "Iteration No: 161 started. Searching for the next optimal point.\n", + "Iteration No: 161 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9179\n", + "Function value obtained: -87.0923\n", + "Current minimum: -88.9424\n", + "Iteration No: 162 started. Searching for the next optimal point.\n", + "Iteration No: 162 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8525\n", + "Function value obtained: -83.6731\n", + "Current minimum: -88.9424\n", + "Iteration No: 163 started. Searching for the next optimal point.\n", + "Iteration No: 163 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8948\n", + "Function value obtained: -85.2705\n", + "Current minimum: -88.9424\n", + "Iteration No: 164 started. Searching for the next optimal point.\n", + "Iteration No: 164 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8606\n", + "Function value obtained: -83.5560\n", + "Current minimum: -88.9424\n", + "Iteration No: 165 started. Searching for the next optimal point.\n", + "Iteration No: 165 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0209\n", + "Function value obtained: -85.5659\n", + "Current minimum: -88.9424\n", + "Iteration No: 166 started. Searching for the next optimal point.\n", + "Iteration No: 166 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9857\n", + "Function value obtained: -84.7900\n", + "Current minimum: -88.9424\n", + "Iteration No: 167 started. Searching for the next optimal point.\n", + "Iteration No: 167 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9454\n", + "Function value obtained: -84.1219\n", + "Current minimum: -88.9424\n", + "Iteration No: 168 started. Searching for the next optimal point.\n", + "Iteration No: 168 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9525\n", + "Function value obtained: -83.1055\n", + "Current minimum: -88.9424\n", + "Iteration No: 169 started. Searching for the next optimal point.\n", + "Iteration No: 169 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0326\n", + "Function value obtained: -85.0939\n", + "Current minimum: -88.9424\n", + "Iteration No: 170 started. Searching for the next optimal point.\n", + "Iteration No: 170 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0220\n", + "Function value obtained: -83.6331\n", + "Current minimum: -88.9424\n", + "Iteration No: 171 started. Searching for the next optimal point.\n", + "Iteration No: 171 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9313\n", + "Function value obtained: -83.9011\n", + "Current minimum: -88.9424\n", + "Iteration No: 172 started. Searching for the next optimal point.\n", + "Iteration No: 172 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0664\n", + "Function value obtained: -85.1330\n", + "Current minimum: -88.9424\n", + "Iteration No: 173 started. Searching for the next optimal point.\n", + "Iteration No: 173 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0426\n", + "Function value obtained: -85.6506\n", + "Current minimum: -88.9424\n", + "Iteration No: 174 started. Searching for the next optimal point.\n", + "Iteration No: 174 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0477\n", + "Function value obtained: -85.4941\n", + "Current minimum: -88.9424\n", + "Iteration No: 175 started. Searching for the next optimal point.\n", + "Iteration No: 175 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1297\n", + "Function value obtained: -83.8772\n", + "Current minimum: -88.9424\n", + "Iteration No: 176 started. Searching for the next optimal point.\n", + "Iteration No: 176 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0690\n", + "Function value obtained: -87.7085\n", + "Current minimum: -88.9424\n", + "Iteration No: 177 started. Searching for the next optimal point.\n", + "Iteration No: 177 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1604\n", + "Function value obtained: -83.2798\n", + "Current minimum: -88.9424\n", + "Iteration No: 178 started. Searching for the next optimal point.\n", + "Iteration No: 178 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1356\n", + "Function value obtained: -83.6723\n", + "Current minimum: -88.9424\n", + "Iteration No: 179 started. Searching for the next optimal point.\n", + "Iteration No: 179 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1426\n", + "Function value obtained: -84.5765\n", + "Current minimum: -88.9424\n", + "Iteration No: 180 started. Searching for the next optimal point.\n", + "Iteration No: 180 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1975\n", + "Function value obtained: -86.8002\n", + "Current minimum: -88.9424\n", + "Iteration No: 181 started. Searching for the next optimal point.\n", + "Iteration No: 181 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2572\n", + "Function value obtained: -85.6453\n", + "Current minimum: -88.9424\n", + "Iteration No: 182 started. Searching for the next optimal point.\n", + "Iteration No: 182 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2087\n", + "Function value obtained: -83.9469\n", + "Current minimum: -88.9424\n", + "Iteration No: 183 started. Searching for the next optimal point.\n", + "Iteration No: 183 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1656\n", + "Function value obtained: -86.0028\n", + "Current minimum: -88.9424\n", + "Iteration No: 184 started. Searching for the next optimal point.\n", + "Iteration No: 184 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2144\n", + "Function value obtained: -85.4008\n", + "Current minimum: -88.9424\n", + "Iteration No: 185 started. Searching for the next optimal point.\n", + "Iteration No: 185 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3211\n", + "Function value obtained: -88.3011\n", + "Current minimum: -88.9424\n", + "Iteration No: 186 started. Searching for the next optimal point.\n", + "Iteration No: 186 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2718\n", + "Function value obtained: -83.7345\n", + "Current minimum: -88.9424\n", + "Iteration No: 187 started. Searching for the next optimal point.\n", + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4193\n", + "Function value obtained: -84.5432\n", + "Current minimum: -88.9424\n", + "Iteration No: 188 started. Searching for the next optimal point.\n", + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4525\n", + "Function value obtained: -82.9519\n", + "Current minimum: -88.9424\n", + "Iteration No: 189 started. Searching for the next optimal point.\n", + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3937\n", + "Function value obtained: -86.8457\n", + "Current minimum: -88.9424\n", + "Iteration No: 190 started. Searching for the next optimal point.\n", + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3132\n", + "Function value obtained: -83.9400\n", + "Current minimum: -88.9424\n", + "Iteration No: 191 started. Searching for the next optimal point.\n", + "Iteration No: 191 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3959\n", + "Function value obtained: -84.7115\n", + "Current minimum: -88.9424\n", + "Iteration No: 192 started. Searching for the next optimal point.\n", + "Iteration No: 192 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4165\n", + "Function value obtained: -83.8742\n", + "Current minimum: -88.9424\n", + "Iteration No: 193 started. Searching for the next optimal point.\n", + "Iteration No: 193 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4788\n", + "Function value obtained: -84.1349\n", + "Current minimum: -88.9424\n", + "Iteration No: 194 started. Searching for the next optimal point.\n", + "Iteration No: 194 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4574\n", + "Function value obtained: -85.6765\n", + "Current minimum: -88.9424\n", + "Iteration No: 195 started. Searching for the next optimal point.\n", + "Iteration No: 195 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4817\n", + "Function value obtained: -85.5814\n", + "Current minimum: -88.9424\n", + "Iteration No: 196 started. Searching for the next optimal point.\n", + "Iteration No: 196 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4379\n", + "Function value obtained: -84.1399\n", + "Current minimum: -88.9424\n", + "Iteration No: 197 started. Searching for the next optimal point.\n", + "Iteration No: 197 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5142\n", + "Function value obtained: -85.3376\n", + "Current minimum: -88.9424\n", + "Iteration No: 198 started. Searching for the next optimal point.\n", + "Iteration No: 198 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5114\n", + "Function value obtained: -84.7863\n", + "Current minimum: -88.9424\n", + "Iteration No: 199 started. Searching for the next optimal point.\n", + "Iteration No: 199 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5168\n", + "Function value obtained: -82.2336\n", + "Current minimum: -88.9424\n", + "Iteration No: 200 started. Searching for the next optimal point.\n", + "Iteration No: 200 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6195\n", + "Function value obtained: -87.5592\n", + "Current minimum: -88.9424\n", + "Iteration No: 201 started. Searching for the next optimal point.\n", + "Iteration No: 201 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6604\n", + "Function value obtained: -84.5312\n", + "Current minimum: -88.9424\n", + "Iteration No: 202 started. Searching for the next optimal point.\n", + "Iteration No: 202 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4938\n", + "Function value obtained: -83.7691\n", + "Current minimum: -88.9424\n", + "Iteration No: 203 started. Searching for the next optimal point.\n", + "Iteration No: 203 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5901\n", + "Function value obtained: -81.1916\n", + "Current minimum: -88.9424\n", + "Iteration No: 204 started. Searching for the next optimal point.\n", + "Iteration No: 204 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7502\n", + "Function value obtained: -83.9095\n", + "Current minimum: -88.9424\n", + "Iteration No: 205 started. Searching for the next optimal point.\n", + "Iteration No: 205 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7670\n", + "Function value obtained: -87.8404\n", + "Current minimum: -88.9424\n", + "Iteration No: 206 started. Searching for the next optimal point.\n", + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6893\n", + "Function value obtained: -85.6244\n", + "Current minimum: -88.9424\n", + "Iteration No: 207 started. Searching for the next optimal point.\n", + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6738\n", + "Function value obtained: -85.1493\n", + "Current minimum: -88.9424\n", + "Iteration No: 208 started. Searching for the next optimal point.\n", + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6733\n", + "Function value obtained: -88.5660\n", + "Current minimum: -88.9424\n", + "Iteration No: 209 started. Searching for the next optimal point.\n", + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7156\n", + "Function value obtained: -87.2563\n", + "Current minimum: -88.9424\n", + "Iteration No: 210 started. Searching for the next optimal point.\n", + "Iteration No: 210 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7896\n", + "Function value obtained: -85.2322\n", + "Current minimum: -88.9424\n", + "Iteration No: 211 started. Searching for the next optimal point.\n", + "Iteration No: 211 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7659\n", + "Function value obtained: -85.6738\n", + "Current minimum: -88.9424\n", + "Iteration No: 212 started. Searching for the next optimal point.\n", + "Iteration No: 212 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7728\n", + "Function value obtained: -81.9408\n", + "Current minimum: -88.9424\n", + "Iteration No: 213 started. Searching for the next optimal point.\n", + "Iteration No: 213 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7804\n", + "Function value obtained: -84.1900\n", + "Current minimum: -88.9424\n", + "Iteration No: 214 started. Searching for the next optimal point.\n", + "Iteration No: 214 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8427\n", + "Function value obtained: -83.3240\n", + "Current minimum: -88.9424\n", + "Iteration No: 215 started. Searching for the next optimal point.\n", + "Iteration No: 215 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9387\n", + "Function value obtained: -84.1631\n", + "Current minimum: -88.9424\n", + "Iteration No: 216 started. Searching for the next optimal point.\n", + "Iteration No: 216 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7826\n", + "Function value obtained: -85.6438\n", + "Current minimum: -88.9424\n", + "Iteration No: 217 started. Searching for the next optimal point.\n", + "Iteration No: 217 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8798\n", + "Function value obtained: -82.5955\n", + "Current minimum: -88.9424\n", + "Iteration No: 218 started. Searching for the next optimal point.\n", + "Iteration No: 218 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7385\n", + "Function value obtained: -83.4224\n", + "Current minimum: -88.9424\n", + "Iteration No: 219 started. Searching for the next optimal point.\n", + "Iteration No: 219 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8461\n", + "Function value obtained: -83.1485\n", + "Current minimum: -88.9424\n", + "Iteration No: 220 started. Searching for the next optimal point.\n", + "Iteration No: 220 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9106\n", + "Function value obtained: -84.5849\n", + "Current minimum: -88.9424\n", + "Iteration No: 221 started. Searching for the next optimal point.\n", + "Iteration No: 221 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8486\n", + "Function value obtained: -84.3890\n", + "Current minimum: -88.9424\n", + "Iteration No: 222 started. Searching for the next optimal point.\n", + "Iteration No: 222 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9103\n", + "Function value obtained: -85.0342\n", + "Current minimum: -88.9424\n", + "Iteration No: 223 started. Searching for the next optimal point.\n", + "Iteration No: 223 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8383\n", + "Function value obtained: -85.6265\n", + "Current minimum: -88.9424\n", + "Iteration No: 224 started. Searching for the next optimal point.\n", + "Iteration No: 224 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8497\n", + "Function value obtained: -84.4915\n", + "Current minimum: -88.9424\n", + "Iteration No: 225 started. Searching for the next optimal point.\n", + "Iteration No: 225 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8692\n", + "Function value obtained: -86.3210\n", + "Current minimum: -88.9424\n", + "Iteration No: 226 started. Searching for the next optimal point.\n", + "Iteration No: 226 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8890\n", + "Function value obtained: -86.6679\n", + "Current minimum: -88.9424\n", + "Iteration No: 227 started. Searching for the next optimal point.\n", + "Iteration No: 227 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0577\n", + "Function value obtained: -86.0960\n", + "Current minimum: -88.9424\n", + "Iteration No: 228 started. Searching for the next optimal point.\n", + "Iteration No: 228 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8758\n", + "Function value obtained: -82.2918\n", + "Current minimum: -88.9424\n", + "Iteration No: 229 started. Searching for the next optimal point.\n", + "Iteration No: 229 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9900\n", + "Function value obtained: -86.4659\n", + "Current minimum: -88.9424\n", + "Iteration No: 230 started. Searching for the next optimal point.\n", + "Iteration No: 230 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0141\n", + "Function value obtained: -88.0084\n", + "Current minimum: -88.9424\n", + "Iteration No: 231 started. Searching for the next optimal point.\n", + "Iteration No: 231 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0637\n", + "Function value obtained: -85.8032\n", + "Current minimum: -88.9424\n", + "Iteration No: 232 started. Searching for the next optimal point.\n", + "Iteration No: 232 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0320\n", + "Function value obtained: -85.6518\n", + "Current minimum: -88.9424\n", + "Iteration No: 233 started. Searching for the next optimal point.\n", + "Iteration No: 233 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1576\n", + "Function value obtained: -83.9464\n", + "Current minimum: -88.9424\n", + "Iteration No: 234 started. Searching for the next optimal point.\n", + "Iteration No: 234 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1127\n", + "Function value obtained: -84.2372\n", + "Current minimum: -88.9424\n", + "Iteration No: 235 started. Searching for the next optimal point.\n", + "Iteration No: 235 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2002\n", + "Function value obtained: -82.7422\n", + "Current minimum: -88.9424\n", + "Iteration No: 236 started. Searching for the next optimal point.\n", + "Iteration No: 236 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0266\n", + "Function value obtained: -84.0363\n", + "Current minimum: -88.9424\n", + "Iteration No: 237 started. Searching for the next optimal point.\n", + "Iteration No: 237 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1392\n", + "Function value obtained: -84.0081\n", + "Current minimum: -88.9424\n", + "Iteration No: 238 started. Searching for the next optimal point.\n", + "Iteration No: 238 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1213\n", + "Function value obtained: -84.2905\n", + "Current minimum: -88.9424\n", + "Iteration No: 239 started. Searching for the next optimal point.\n", + "Iteration No: 239 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2836\n", + "Function value obtained: -83.6245\n", + "Current minimum: -88.9424\n", + "Iteration No: 240 started. Searching for the next optimal point.\n", + "Iteration No: 240 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1579\n", + "Function value obtained: -85.9179\n", + "Current minimum: -88.9424\n", + "Iteration No: 241 started. Searching for the next optimal point.\n", + "Iteration No: 241 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4125\n", + "Function value obtained: -84.8672\n", + "Current minimum: -88.9424\n", + "Iteration No: 242 started. Searching for the next optimal point.\n", + "Iteration No: 242 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2033\n", + "Function value obtained: -87.8986\n", + "Current minimum: -88.9424\n", + "Iteration No: 243 started. Searching for the next optimal point.\n", + "Iteration No: 243 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2769\n", + "Function value obtained: -82.4511\n", + "Current minimum: -88.9424\n", + "Iteration No: 244 started. Searching for the next optimal point.\n", + "Iteration No: 244 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3056\n", + "Function value obtained: -83.2432\n", + "Current minimum: -88.9424\n", + "Iteration No: 245 started. Searching for the next optimal point.\n", + "Iteration No: 245 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3734\n", + "Function value obtained: -86.2849\n", + "Current minimum: -88.9424\n", + "Iteration No: 246 started. Searching for the next optimal point.\n", + "Iteration No: 246 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3651\n", + "Function value obtained: -84.2954\n", + "Current minimum: -88.9424\n", + "Iteration No: 247 started. Searching for the next optimal point.\n", + "Iteration No: 247 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2664\n", + "Function value obtained: -85.9061\n", + "Current minimum: -88.9424\n", + "Iteration No: 248 started. Searching for the next optimal point.\n", + "Iteration No: 248 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5226\n", + "Function value obtained: -84.1788\n", + "Current minimum: -88.9424\n", + "Iteration No: 249 started. Searching for the next optimal point.\n", + "Iteration No: 249 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6910\n", + "Function value obtained: -83.5698\n", + "Current minimum: -88.9424\n", + "Iteration No: 250 started. Searching for the next optimal point.\n", + "Iteration No: 250 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6748\n", + "Function value obtained: -86.8285\n", + "Current minimum: -88.9424\n", + "Iteration No: 251 started. Searching for the next optimal point.\n", + "Iteration No: 251 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6907\n", + "Function value obtained: -86.2896\n", + "Current minimum: -88.9424\n", + "Iteration No: 252 started. Searching for the next optimal point.\n", + "Iteration No: 252 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6244\n", + "Function value obtained: -86.5565\n", + "Current minimum: -88.9424\n", + "Iteration No: 253 started. Searching for the next optimal point.\n", + "Iteration No: 253 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7568\n", + "Function value obtained: -84.7245\n", + "Current minimum: -88.9424\n", + "Iteration No: 254 started. Searching for the next optimal point.\n", + "Iteration No: 254 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7726\n", + "Function value obtained: -83.1910\n", + "Current minimum: -88.9424\n", + "Iteration No: 255 started. Searching for the next optimal point.\n", + "Iteration No: 255 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8861\n", + "Function value obtained: -86.4182\n", + "Current minimum: -88.9424\n", + "Iteration No: 256 started. Searching for the next optimal point.\n", + "Iteration No: 256 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8083\n", + "Function value obtained: -85.5617\n", + "Current minimum: -88.9424\n", + "Iteration No: 257 started. Searching for the next optimal point.\n", + "Iteration No: 257 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7195\n", + "Function value obtained: -85.4845\n", + "Current minimum: -88.9424\n", + "Iteration No: 258 started. Searching for the next optimal point.\n", + "Iteration No: 258 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8084\n", + "Function value obtained: -82.9101\n", + "Current minimum: -88.9424\n", + "Iteration No: 259 started. Searching for the next optimal point.\n", + "Iteration No: 259 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1051\n", + "Function value obtained: -85.7685\n", + "Current minimum: -88.9424\n", + "Iteration No: 260 started. Searching for the next optimal point.\n", + "Iteration No: 260 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8924\n", + "Function value obtained: -82.1995\n", + "Current minimum: -88.9424\n", + "Iteration No: 261 started. Searching for the next optimal point.\n", + "Iteration No: 261 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0344\n", + "Function value obtained: -83.7582\n", + "Current minimum: -88.9424\n", + "Iteration No: 262 started. Searching for the next optimal point.\n", + "Iteration No: 262 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9853\n", + "Function value obtained: -83.0905\n", + "Current minimum: -88.9424\n", + "Iteration No: 263 started. Searching for the next optimal point.\n", + "Iteration No: 263 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9829\n", + "Function value obtained: -85.3908\n", + "Current minimum: -88.9424\n", + "Iteration No: 264 started. Searching for the next optimal point.\n", + "Iteration No: 264 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0274\n", + "Function value obtained: -83.6712\n", + "Current minimum: -88.9424\n", + "Iteration No: 265 started. Searching for the next optimal point.\n", + "Iteration No: 265 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1189\n", + "Function value obtained: -85.2795\n", + "Current minimum: -88.9424\n", + "Iteration No: 266 started. Searching for the next optimal point.\n", + "Iteration No: 266 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9782\n", + "Function value obtained: -87.4455\n", + "Current minimum: -88.9424\n", + "Iteration No: 267 started. Searching for the next optimal point.\n", + "Iteration No: 267 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0205\n", + "Function value obtained: -84.6936\n", + "Current minimum: -88.9424\n", + "Iteration No: 268 started. Searching for the next optimal point.\n", + "Iteration No: 268 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1304\n", + "Function value obtained: -85.3183\n", + "Current minimum: -88.9424\n", + "Iteration No: 269 started. Searching for the next optimal point.\n", + "Iteration No: 269 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1316\n", + "Function value obtained: -80.6488\n", + "Current minimum: -88.9424\n", + "Iteration No: 270 started. Searching for the next optimal point.\n", + "Iteration No: 270 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1816\n", + "Function value obtained: -84.6192\n", + "Current minimum: -88.9424\n", + "Iteration No: 271 started. Searching for the next optimal point.\n", + "Iteration No: 271 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2824\n", + "Function value obtained: -86.3812\n", + "Current minimum: -88.9424\n", + "Iteration No: 272 started. Searching for the next optimal point.\n", + "Iteration No: 272 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2275\n", + "Function value obtained: -83.9857\n", + "Current minimum: -88.9424\n", + "Iteration No: 273 started. Searching for the next optimal point.\n", + "Iteration No: 273 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1941\n", + "Function value obtained: -86.2361\n", + "Current minimum: -88.9424\n", + "Iteration No: 274 started. Searching for the next optimal point.\n", + "Iteration No: 274 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2506\n", + "Function value obtained: -85.5450\n", + "Current minimum: -88.9424\n", + "Iteration No: 275 started. Searching for the next optimal point.\n", + "Iteration No: 275 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2945\n", + "Function value obtained: -84.8205\n", + "Current minimum: -88.9424\n", + "Iteration No: 276 started. Searching for the next optimal point.\n", + "Iteration No: 276 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1573\n", + "Function value obtained: -83.0944\n", + "Current minimum: -88.9424\n", + "Iteration No: 277 started. Searching for the next optimal point.\n", + "Iteration No: 277 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2734\n", + "Function value obtained: -83.9087\n", + "Current minimum: -88.9424\n", + "Iteration No: 278 started. Searching for the next optimal point.\n", + "Iteration No: 278 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2244\n", + "Function value obtained: -84.3036\n", + "Current minimum: -88.9424\n", + "Iteration No: 279 started. Searching for the next optimal point.\n", + "Iteration No: 279 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3524\n", + "Function value obtained: -84.5203\n", + "Current minimum: -88.9424\n", + "Iteration No: 280 started. Searching for the next optimal point.\n", + "Iteration No: 280 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1440\n", + "Function value obtained: -83.2822\n", + "Current minimum: -88.9424\n", + "Iteration No: 281 started. Searching for the next optimal point.\n", + "Iteration No: 281 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4573\n", + "Function value obtained: -87.1670\n", + "Current minimum: -88.9424\n", + "Iteration No: 282 started. Searching for the next optimal point.\n", + "Iteration No: 282 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4217\n", + "Function value obtained: -81.0240\n", + "Current minimum: -88.9424\n", + "Iteration No: 283 started. Searching for the next optimal point.\n", + "Iteration No: 283 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5427\n", + "Function value obtained: -87.7591\n", + "Current minimum: -88.9424\n", + "Iteration No: 284 started. Searching for the next optimal point.\n", + "Iteration No: 284 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3975\n", + "Function value obtained: -80.9265\n", + "Current minimum: -88.9424\n", + "Iteration No: 285 started. Searching for the next optimal point.\n", + "Iteration No: 285 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5825\n", + "Function value obtained: -83.4174\n", + "Current minimum: -88.9424\n", + "Iteration No: 286 started. Searching for the next optimal point.\n", + "Iteration No: 286 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4088\n", + "Function value obtained: -87.5917\n", + "Current minimum: -88.9424\n", + "Iteration No: 287 started. Searching for the next optimal point.\n", + "Iteration No: 287 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6184\n", + "Function value obtained: -83.8790\n", + "Current minimum: -88.9424\n", + "Iteration No: 288 started. Searching for the next optimal point.\n", + "Iteration No: 288 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5515\n", + "Function value obtained: -88.2637\n", + "Current minimum: -88.9424\n", + "Iteration No: 289 started. Searching for the next optimal point.\n", + "Iteration No: 289 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6982\n", + "Function value obtained: -83.4047\n", + "Current minimum: -88.9424\n", + "Iteration No: 290 started. Searching for the next optimal point.\n", + "Iteration No: 290 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7383\n", + "Function value obtained: -84.9295\n", + "Current minimum: -88.9424\n", + "Iteration No: 291 started. Searching for the next optimal point.\n", + "Iteration No: 291 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7732\n", + "Function value obtained: -87.1347\n", + "Current minimum: -88.9424\n", + "Iteration No: 292 started. Searching for the next optimal point.\n", + "Iteration No: 292 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7829\n", + "Function value obtained: -86.7605\n", + "Current minimum: -88.9424\n", + "Iteration No: 293 started. Searching for the next optimal point.\n", + "Iteration No: 293 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6685\n", + "Function value obtained: -87.0208\n", + "Current minimum: -88.9424\n", + "Iteration No: 294 started. Searching for the next optimal point.\n", + "Iteration No: 294 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7354\n", + "Function value obtained: -81.1226\n", + "Current minimum: -88.9424\n", + "Iteration No: 295 started. Searching for the next optimal point.\n", + "Iteration No: 295 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8814\n", + "Function value obtained: -87.2329\n", + "Current minimum: -88.9424\n", + "Iteration No: 296 started. Searching for the next optimal point.\n", + "Iteration No: 296 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7860\n", + "Function value obtained: -84.2515\n", + "Current minimum: -88.9424\n", + "Iteration No: 297 started. Searching for the next optimal point.\n", + "Iteration No: 297 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9065\n", + "Function value obtained: -87.4453\n", + "Current minimum: -88.9424\n", + "Iteration No: 298 started. Searching for the next optimal point.\n", + "Iteration No: 298 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8620\n", + "Function value obtained: -87.0349\n", + "Current minimum: -88.9424\n", + "Iteration No: 299 started. Searching for the next optimal point.\n", + "Iteration No: 299 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9848\n", + "Function value obtained: -87.0860\n", + "Current minimum: -88.9424\n", + "Iteration No: 300 started. Searching for the next optimal point.\n", + "Iteration No: 300 ended. Search finished for the next optimal point.\n", + "Time taken: 6.0444\n", + "Function value obtained: -86.2412\n", + "Current minimum: -88.9424\n", + "CPU times: user 2h 1min 35s, sys: 1h 11min 36s, total: 3h 13min 11s\n", + "Wall time: 15min 6s\n" ] }, { "data": { "text/plain": [ - "(-88.30164756300354, [-1.9537556537577059])" + "(-88.94242714465256, [-1.985554010378551])" ] }, - "execution_count": 91, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 300, verbose=True, n_jobs=-1)\n", "esc_gp.fun, esc_gp.x" ] }, { "cell_type": "code", - "execution_count": 92, - "id": "ebff2644-b811-4bea-995c-ca3c7586c122", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 92, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_convergence(esc_gp)" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", - "metadata": { - "scrolled": true - }, + "execution_count": 10, + "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "name": "stdout", @@ -1300,339 +4903,1525 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8928\n", - "Function value obtained: -1.9366\n", - "Current minimum: -1.9366\n", + "Time taken: 1.2738\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8940\n", - "Function value obtained: -2.1499\n", - "Current minimum: -2.1499\n", + "Time taken: 1.2374\n", + "Function value obtained: -84.9404\n", + "Current minimum: -84.9404\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.7580\n", - "Function value obtained: -2.1207\n", - "Current minimum: -2.1499\n", + "Time taken: 1.2821\n", + "Function value obtained: -2.8484\n", + "Current minimum: -84.9404\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.7685\n", - "Function value obtained: -2.9358\n", - "Current minimum: -2.9358\n", + "Time taken: 1.2022\n", + "Function value obtained: -1.9672\n", + "Current minimum: -84.9404\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8323\n", - "Function value obtained: -7.0135\n", - "Current minimum: -7.0135\n", + "Time taken: 1.1629\n", + "Function value obtained: -3.1598\n", + "Current minimum: -84.9404\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.7688\n", - "Function value obtained: -75.4833\n", - "Current minimum: -75.4833\n", + "Time taken: 1.1314\n", + "Function value obtained: -75.1009\n", + "Current minimum: -84.9404\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.7837\n", - "Function value obtained: -6.7920\n", - "Current minimum: -75.4833\n", + "Time taken: 1.0974\n", + "Function value obtained: -7.0676\n", + "Current minimum: -84.9404\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8485\n", - "Function value obtained: -48.8146\n", - "Current minimum: -75.4833\n", + "Time taken: 1.1389\n", + "Function value obtained: -77.2938\n", + "Current minimum: -84.9404\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8639\n", - "Function value obtained: -49.1108\n", - "Current minimum: -75.4833\n", + "Time taken: 1.2380\n", + "Function value obtained: -0.0015\n", + "Current minimum: -84.9404\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 0.9739\n", - "Function value obtained: -68.7822\n", - "Current minimum: -75.4833\n", + "Time taken: 1.3707\n", + "Function value obtained: -0.0000\n", + "Current minimum: -84.9404\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0094\n", - "Function value obtained: -82.2816\n", - "Current minimum: -82.2816\n", + "Time taken: 1.3705\n", + "Function value obtained: -85.6942\n", + "Current minimum: -85.6942\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0761\n", - "Function value obtained: -78.0358\n", - "Current minimum: -82.2816\n", + "Time taken: 1.3672\n", + "Function value obtained: -79.2813\n", + "Current minimum: -85.6942\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1717\n", - "Function value obtained: -82.6843\n", - "Current minimum: -82.6843\n", + "Time taken: 1.3034\n", + "Function value obtained: -85.8253\n", + "Current minimum: -85.8253\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0236\n", - "Function value obtained: -70.0158\n", - "Current minimum: -82.6843\n", + "Time taken: 1.3911\n", + "Function value obtained: -82.0591\n", + "Current minimum: -85.8253\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9966\n", - "Function value obtained: -85.8629\n", - "Current minimum: -85.8629\n", + "Time taken: 1.4305\n", + "Function value obtained: -81.0534\n", + "Current minimum: -85.8253\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0580\n", - "Function value obtained: -83.4641\n", - "Current minimum: -85.8629\n", + "Time taken: 1.4108\n", + "Function value obtained: -85.8159\n", + "Current minimum: -85.8253\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0565\n", - "Function value obtained: -86.9627\n", - "Current minimum: -86.9627\n", + "Time taken: 1.4462\n", + "Function value obtained: -86.4994\n", + "Current minimum: -86.4994\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9480\n", - "Function value obtained: -86.1189\n", - "Current minimum: -86.9627\n", + "Time taken: 1.4249\n", + "Function value obtained: -84.1290\n", + "Current minimum: -86.4994\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9449\n", - "Function value obtained: -82.8694\n", - "Current minimum: -86.9627\n", + "Time taken: 1.3692\n", + "Function value obtained: -85.5404\n", + "Current minimum: -86.4994\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9600\n", - "Function value obtained: -84.5687\n", - "Current minimum: -86.9627\n", + "Time taken: 1.4300\n", + "Function value obtained: -84.1605\n", + "Current minimum: -86.4994\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9804\n", - "Function value obtained: -88.4548\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4671\n", + "Function value obtained: -83.6550\n", + "Current minimum: -86.4994\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0303\n", - "Function value obtained: -33.5852\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3878\n", + "Function value obtained: -87.2921\n", + "Current minimum: -87.2921\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9988\n", - "Function value obtained: -87.0987\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4872\n", + "Function value obtained: -85.9602\n", + "Current minimum: -87.2921\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0530\n", - "Function value obtained: -35.9950\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3882\n", + "Function value obtained: -88.6692\n", + "Current minimum: -88.6692\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9661\n", - "Function value obtained: -85.1322\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3337\n", + "Function value obtained: -85.1203\n", + "Current minimum: -88.6692\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3338\n", - "Function value obtained: -85.4144\n", - "Current minimum: -88.4548\n", + "Time taken: 1.2967\n", + "Function value obtained: -85.6372\n", + "Current minimum: -88.6692\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9657\n", - "Function value obtained: -85.9783\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4511\n", + "Function value obtained: -82.1948\n", + "Current minimum: -88.6692\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0462\n", - "Function value obtained: -81.8535\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4852\n", + "Function value obtained: -86.3376\n", + "Current minimum: -88.6692\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0058\n", - "Function value obtained: -85.4714\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3356\n", + "Function value obtained: -85.5868\n", + "Current minimum: -88.6692\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9512\n", - "Function value obtained: -84.0389\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4092\n", + "Function value obtained: -83.8516\n", + "Current minimum: -88.6692\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0799\n", - "Function value obtained: -84.3946\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3688\n", + "Function value obtained: -86.3473\n", + "Current minimum: -88.6692\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0637\n", - "Function value obtained: -86.6287\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3952\n", + "Function value obtained: -86.8939\n", + "Current minimum: -88.6692\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9846\n", - "Function value obtained: -88.3544\n", - "Current minimum: -88.4548\n", + "Time taken: 1.6647\n", + "Function value obtained: -83.0291\n", + "Current minimum: -88.6692\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9553\n", - "Function value obtained: -85.9460\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3723\n", + "Function value obtained: -83.8943\n", + "Current minimum: -88.6692\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0458\n", - "Function value obtained: -81.9748\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3419\n", + "Function value obtained: -84.5014\n", + "Current minimum: -88.6692\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0769\n", - "Function value obtained: -85.6594\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3678\n", + "Function value obtained: -82.5716\n", + "Current minimum: -88.6692\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0835\n", - "Function value obtained: -84.7670\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3051\n", + "Function value obtained: -85.6161\n", + "Current minimum: -88.6692\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1385\n", - "Function value obtained: -85.7179\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3638\n", + "Function value obtained: -86.3558\n", + "Current minimum: -88.6692\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0549\n", - "Function value obtained: -85.1600\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3622\n", + "Function value obtained: -83.8974\n", + "Current minimum: -88.6692\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1085\n", - "Function value obtained: -87.5070\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3498\n", + "Function value obtained: -84.9701\n", + "Current minimum: -88.6692\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1128\n", - "Function value obtained: -84.2948\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4081\n", + "Function value obtained: -84.4675\n", + "Current minimum: -88.6692\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1448\n", - "Function value obtained: -83.3965\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4185\n", + "Function value obtained: -83.7567\n", + "Current minimum: -88.6692\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1306\n", - "Function value obtained: -83.7405\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4727\n", + "Function value obtained: -84.7712\n", + "Current minimum: -88.6692\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1046\n", - "Function value obtained: -83.8566\n", - "Current minimum: -88.4548\n", + "Time taken: 1.5133\n", + "Function value obtained: -83.9677\n", + "Current minimum: -88.6692\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1216\n", - "Function value obtained: -83.0424\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4644\n", + "Function value obtained: -84.7957\n", + "Current minimum: -88.6692\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0563\n", - "Function value obtained: -83.3528\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3936\n", + "Function value obtained: -85.2244\n", + "Current minimum: -88.6692\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0197\n", - "Function value obtained: -25.1002\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3853\n", + "Function value obtained: -84.4571\n", + "Current minimum: -88.6692\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0718\n", - "Function value obtained: -29.6400\n", - "Current minimum: -88.4548\n", + "Time taken: 1.4347\n", + "Function value obtained: -84.5852\n", + "Current minimum: -88.6692\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9993\n", - "Function value obtained: -86.4158\n", - "Current minimum: -88.4548\n", + "Time taken: 1.3642\n", + "Function value obtained: -87.2573\n", + "Current minimum: -88.6692\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9361\n", - "Function value obtained: -84.7042\n", - "Current minimum: -88.4548\n", - "CPU times: user 17.7 s, sys: 4.08 s, total: 21.7 s\n", - "Wall time: 50.3 s\n" + "Time taken: 1.4864\n", + "Function value obtained: -84.0021\n", + "Current minimum: -88.6692\n", + "Iteration No: 51 started. Searching for the next optimal point.\n", + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4223\n", + "Function value obtained: -86.9292\n", + "Current minimum: -88.6692\n", + "Iteration No: 52 started. Searching for the next optimal point.\n", + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3931\n", + "Function value obtained: -87.8382\n", + "Current minimum: -88.6692\n", + "Iteration No: 53 started. Searching for the next optimal point.\n", + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4355\n", + "Function value obtained: -81.2581\n", + "Current minimum: -88.6692\n", + "Iteration No: 54 started. Searching for the next optimal point.\n", + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4613\n", + "Function value obtained: -87.3863\n", + "Current minimum: -88.6692\n", + "Iteration No: 55 started. Searching for the next optimal point.\n", + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3895\n", + "Function value obtained: -84.0942\n", + "Current minimum: -88.6692\n", + "Iteration No: 56 started. Searching for the next optimal point.\n", + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5234\n", + "Function value obtained: -85.0784\n", + "Current minimum: -88.6692\n", + "Iteration No: 57 started. Searching for the next optimal point.\n", + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3575\n", + "Function value obtained: -86.3505\n", + "Current minimum: -88.6692\n", + "Iteration No: 58 started. Searching for the next optimal point.\n", + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5053\n", + "Function value obtained: -86.2184\n", + "Current minimum: -88.6692\n", + "Iteration No: 59 started. Searching for the next optimal point.\n", + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3991\n", + "Function value obtained: -86.2284\n", + "Current minimum: -88.6692\n", + "Iteration No: 60 started. Searching for the next optimal point.\n", + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3794\n", + "Function value obtained: -86.4311\n", + "Current minimum: -88.6692\n", + "Iteration No: 61 started. Searching for the next optimal point.\n", + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4880\n", + "Function value obtained: -83.3662\n", + "Current minimum: -88.6692\n", + "Iteration No: 62 started. Searching for the next optimal point.\n", + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4224\n", + "Function value obtained: -83.2335\n", + "Current minimum: -88.6692\n", + "Iteration No: 63 started. Searching for the next optimal point.\n", + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4503\n", + "Function value obtained: -85.2090\n", + "Current minimum: -88.6692\n", + "Iteration No: 64 started. Searching for the next optimal point.\n", + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3703\n", + "Function value obtained: -83.4133\n", + "Current minimum: -88.6692\n", + "Iteration No: 65 started. Searching for the next optimal point.\n", + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3993\n", + "Function value obtained: -87.0669\n", + "Current minimum: -88.6692\n", + "Iteration No: 66 started. Searching for the next optimal point.\n", + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4523\n", + "Function value obtained: -87.1440\n", + "Current minimum: -88.6692\n", + "Iteration No: 67 started. Searching for the next optimal point.\n", + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3843\n", + "Function value obtained: -86.0671\n", + "Current minimum: -88.6692\n", + "Iteration No: 68 started. Searching for the next optimal point.\n", + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4799\n", + "Function value obtained: -88.7753\n", + "Current minimum: -88.7753\n", + "Iteration No: 69 started. Searching for the next optimal point.\n", + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3515\n", + "Function value obtained: -83.6733\n", + "Current minimum: -88.7753\n", + "Iteration No: 70 started. Searching for the next optimal point.\n", + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4462\n", + "Function value obtained: -84.8879\n", + "Current minimum: -88.7753\n", + "Iteration No: 71 started. Searching for the next optimal point.\n", + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3915\n", + "Function value obtained: -85.2340\n", + "Current minimum: -88.7753\n", + "Iteration No: 72 started. Searching for the next optimal point.\n", + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3713\n", + "Function value obtained: -87.2032\n", + "Current minimum: -88.7753\n", + "Iteration No: 73 started. Searching for the next optimal point.\n", + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3523\n", + "Function value obtained: -83.2681\n", + "Current minimum: -88.7753\n", + "Iteration No: 74 started. Searching for the next optimal point.\n", + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4769\n", + "Function value obtained: -84.2288\n", + "Current minimum: -88.7753\n", + "Iteration No: 75 started. Searching for the next optimal point.\n", + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5053\n", + "Function value obtained: -84.2294\n", + "Current minimum: -88.7753\n", + "Iteration No: 76 started. Searching for the next optimal point.\n", + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3957\n", + "Function value obtained: -82.0141\n", + "Current minimum: -88.7753\n", + "Iteration No: 77 started. Searching for the next optimal point.\n", + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3566\n", + "Function value obtained: -84.7554\n", + "Current minimum: -88.7753\n", + "Iteration No: 78 started. Searching for the next optimal point.\n", + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3880\n", + "Function value obtained: -84.1003\n", + "Current minimum: -88.7753\n", + "Iteration No: 79 started. Searching for the next optimal point.\n", + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5084\n", + "Function value obtained: -84.6515\n", + "Current minimum: -88.7753\n", + "Iteration No: 80 started. Searching for the next optimal point.\n", + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4507\n", + "Function value obtained: -88.2300\n", + "Current minimum: -88.7753\n", + "Iteration No: 81 started. Searching for the next optimal point.\n", + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5512\n", + "Function value obtained: -84.8982\n", + "Current minimum: -88.7753\n", + "Iteration No: 82 started. Searching for the next optimal point.\n", + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3564\n", + "Function value obtained: -84.9337\n", + "Current minimum: -88.7753\n", + "Iteration No: 83 started. Searching for the next optimal point.\n", + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4272\n", + "Function value obtained: -86.7523\n", + "Current minimum: -88.7753\n", + "Iteration No: 84 started. Searching for the next optimal point.\n", + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4170\n", + "Function value obtained: -84.3592\n", + "Current minimum: -88.7753\n", + "Iteration No: 85 started. Searching for the next optimal point.\n", + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4294\n", + "Function value obtained: -81.2812\n", + "Current minimum: -88.7753\n", + "Iteration No: 86 started. Searching for the next optimal point.\n", + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4893\n", + "Function value obtained: -84.3031\n", + "Current minimum: -88.7753\n", + "Iteration No: 87 started. Searching for the next optimal point.\n", + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4452\n", + "Function value obtained: -86.8587\n", + "Current minimum: -88.7753\n", + "Iteration No: 88 started. Searching for the next optimal point.\n", + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4892\n", + "Function value obtained: -83.2783\n", + "Current minimum: -88.7753\n", + "Iteration No: 89 started. Searching for the next optimal point.\n", + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4293\n", + "Function value obtained: -86.0555\n", + "Current minimum: -88.7753\n", + "Iteration No: 90 started. Searching for the next optimal point.\n", + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3899\n", + "Function value obtained: -85.7992\n", + "Current minimum: -88.7753\n", + "Iteration No: 91 started. Searching for the next optimal point.\n", + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4762\n", + "Function value obtained: -85.0568\n", + "Current minimum: -88.7753\n", + "Iteration No: 92 started. Searching for the next optimal point.\n", + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4345\n", + "Function value obtained: -85.5949\n", + "Current minimum: -88.7753\n", + "Iteration No: 93 started. Searching for the next optimal point.\n", + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5218\n", + "Function value obtained: -84.1127\n", + "Current minimum: -88.7753\n", + "Iteration No: 94 started. Searching for the next optimal point.\n", + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4572\n", + "Function value obtained: -83.7750\n", + "Current minimum: -88.7753\n", + "Iteration No: 95 started. Searching for the next optimal point.\n", + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4873\n", + "Function value obtained: -86.8196\n", + "Current minimum: -88.7753\n", + "Iteration No: 96 started. Searching for the next optimal point.\n", + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4875\n", + "Function value obtained: -86.7438\n", + "Current minimum: -88.7753\n", + "Iteration No: 97 started. Searching for the next optimal point.\n", + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4341\n", + "Function value obtained: -84.8433\n", + "Current minimum: -88.7753\n", + "Iteration No: 98 started. Searching for the next optimal point.\n", + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4127\n", + "Function value obtained: -82.4445\n", + "Current minimum: -88.7753\n", + "Iteration No: 99 started. Searching for the next optimal point.\n", + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4000\n", + "Function value obtained: -82.6203\n", + "Current minimum: -88.7753\n", + "Iteration No: 100 started. Searching for the next optimal point.\n", + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5646\n", + "Function value obtained: -85.3232\n", + "Current minimum: -88.7753\n", + "Iteration No: 101 started. Searching for the next optimal point.\n", + "Iteration No: 101 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4294\n", + "Function value obtained: -84.2406\n", + "Current minimum: -88.7753\n", + "Iteration No: 102 started. Searching for the next optimal point.\n", + "Iteration No: 102 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4485\n", + "Function value obtained: -80.7969\n", + "Current minimum: -88.7753\n", + "Iteration No: 103 started. Searching for the next optimal point.\n", + "Iteration No: 103 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3693\n", + "Function value obtained: -83.9303\n", + "Current minimum: -88.7753\n", + "Iteration No: 104 started. Searching for the next optimal point.\n", + "Iteration No: 104 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3341\n", + "Function value obtained: -79.4459\n", + "Current minimum: -88.7753\n", + "Iteration No: 105 started. Searching for the next optimal point.\n", + "Iteration No: 105 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5054\n", + "Function value obtained: -84.3764\n", + "Current minimum: -88.7753\n", + "Iteration No: 106 started. Searching for the next optimal point.\n", + "Iteration No: 106 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3530\n", + "Function value obtained: -84.3042\n", + "Current minimum: -88.7753\n", + "Iteration No: 107 started. Searching for the next optimal point.\n", + "Iteration No: 107 ended. Search finished for the next optimal point.\n", + "Time taken: 1.1555\n", + "Function value obtained: -86.0511\n", + "Current minimum: -88.7753\n", + "Iteration No: 108 started. Searching for the next optimal point.\n", + "Iteration No: 108 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2933\n", + "Function value obtained: -86.4837\n", + "Current minimum: -88.7753\n", + "Iteration No: 109 started. Searching for the next optimal point.\n", + "Iteration No: 109 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3160\n", + "Function value obtained: -83.2632\n", + "Current minimum: -88.7753\n", + "Iteration No: 110 started. Searching for the next optimal point.\n", + "Iteration No: 110 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2851\n", + "Function value obtained: -86.2764\n", + "Current minimum: -88.7753\n", + "Iteration No: 111 started. Searching for the next optimal point.\n", + "Iteration No: 111 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3986\n", + "Function value obtained: -84.9418\n", + "Current minimum: -88.7753\n", + "Iteration No: 112 started. Searching for the next optimal point.\n", + "Iteration No: 112 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3763\n", + "Function value obtained: -84.3836\n", + "Current minimum: -88.7753\n", + "Iteration No: 113 started. Searching for the next optimal point.\n", + "Iteration No: 113 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5051\n", + "Function value obtained: -85.5648\n", + "Current minimum: -88.7753\n", + "Iteration No: 114 started. Searching for the next optimal point.\n", + "Iteration No: 114 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3554\n", + "Function value obtained: -85.3083\n", + "Current minimum: -88.7753\n", + "Iteration No: 115 started. Searching for the next optimal point.\n", + "Iteration No: 115 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4003\n", + "Function value obtained: -82.2068\n", + "Current minimum: -88.7753\n", + "Iteration No: 116 started. Searching for the next optimal point.\n", + "Iteration No: 116 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4556\n", + "Function value obtained: -79.7834\n", + "Current minimum: -88.7753\n", + "Iteration No: 117 started. Searching for the next optimal point.\n", + "Iteration No: 117 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3963\n", + "Function value obtained: -79.6317\n", + "Current minimum: -88.7753\n", + "Iteration No: 118 started. Searching for the next optimal point.\n", + "Iteration No: 118 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5650\n", + "Function value obtained: -85.9209\n", + "Current minimum: -88.7753\n", + "Iteration No: 119 started. Searching for the next optimal point.\n", + "Iteration No: 119 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4567\n", + "Function value obtained: -83.9391\n", + "Current minimum: -88.7753\n", + "Iteration No: 120 started. Searching for the next optimal point.\n", + "Iteration No: 120 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5595\n", + "Function value obtained: -78.9029\n", + "Current minimum: -88.7753\n", + "Iteration No: 121 started. Searching for the next optimal point.\n", + "Iteration No: 121 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4266\n", + "Function value obtained: -82.8344\n", + "Current minimum: -88.7753\n", + "Iteration No: 122 started. Searching for the next optimal point.\n", + "Iteration No: 122 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4020\n", + "Function value obtained: -83.9858\n", + "Current minimum: -88.7753\n", + "Iteration No: 123 started. Searching for the next optimal point.\n", + "Iteration No: 123 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4144\n", + "Function value obtained: -85.5317\n", + "Current minimum: -88.7753\n", + "Iteration No: 124 started. Searching for the next optimal point.\n", + "Iteration No: 124 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4749\n", + "Function value obtained: -82.9057\n", + "Current minimum: -88.7753\n", + "Iteration No: 125 started. Searching for the next optimal point.\n", + "Iteration No: 125 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4246\n", + "Function value obtained: -84.9213\n", + "Current minimum: -88.7753\n", + "Iteration No: 126 started. Searching for the next optimal point.\n", + "Iteration No: 126 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4379\n", + "Function value obtained: -84.9719\n", + "Current minimum: -88.7753\n", + "Iteration No: 127 started. Searching for the next optimal point.\n", + "Iteration No: 127 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4319\n", + "Function value obtained: -86.2452\n", + "Current minimum: -88.7753\n", + "Iteration No: 128 started. Searching for the next optimal point.\n", + "Iteration No: 128 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4316\n", + "Function value obtained: -83.9911\n", + "Current minimum: -88.7753\n", + "Iteration No: 129 started. Searching for the next optimal point.\n", + "Iteration No: 129 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6276\n", + "Function value obtained: -87.3057\n", + "Current minimum: -88.7753\n", + "Iteration No: 130 started. Searching for the next optimal point.\n", + "Iteration No: 130 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4583\n", + "Function value obtained: -85.3982\n", + "Current minimum: -88.7753\n", + "Iteration No: 131 started. Searching for the next optimal point.\n", + "Iteration No: 131 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5829\n", + "Function value obtained: -84.8705\n", + "Current minimum: -88.7753\n", + "Iteration No: 132 started. Searching for the next optimal point.\n", + "Iteration No: 132 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5275\n", + "Function value obtained: -85.0487\n", + "Current minimum: -88.7753\n", + "Iteration No: 133 started. Searching for the next optimal point.\n", + "Iteration No: 133 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5128\n", + "Function value obtained: -86.5023\n", + "Current minimum: -88.7753\n", + "Iteration No: 134 started. Searching for the next optimal point.\n", + "Iteration No: 134 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4822\n", + "Function value obtained: -83.9732\n", + "Current minimum: -88.7753\n", + "Iteration No: 135 started. Searching for the next optimal point.\n", + "Iteration No: 135 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4147\n", + "Function value obtained: -84.4507\n", + "Current minimum: -88.7753\n", + "Iteration No: 136 started. Searching for the next optimal point.\n", + "Iteration No: 136 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4708\n", + "Function value obtained: -88.7570\n", + "Current minimum: -88.7753\n", + "Iteration No: 137 started. Searching for the next optimal point.\n", + "Iteration No: 137 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4485\n", + "Function value obtained: -85.6765\n", + "Current minimum: -88.7753\n", + "Iteration No: 138 started. Searching for the next optimal point.\n", + "Iteration No: 138 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4867\n", + "Function value obtained: -86.0032\n", + "Current minimum: -88.7753\n", + "Iteration No: 139 started. Searching for the next optimal point.\n", + "Iteration No: 139 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4112\n", + "Function value obtained: -84.8063\n", + "Current minimum: -88.7753\n", + "Iteration No: 140 started. Searching for the next optimal point.\n", + "Iteration No: 140 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4383\n", + "Function value obtained: -83.0949\n", + "Current minimum: -88.7753\n", + "Iteration No: 141 started. Searching for the next optimal point.\n", + "Iteration No: 141 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4879\n", + "Function value obtained: -83.9209\n", + "Current minimum: -88.7753\n", + "Iteration No: 142 started. Searching for the next optimal point.\n", + "Iteration No: 142 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4293\n", + "Function value obtained: -86.4783\n", + "Current minimum: -88.7753\n", + "Iteration No: 143 started. Searching for the next optimal point.\n", + "Iteration No: 143 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4721\n", + "Function value obtained: -84.1926\n", + "Current minimum: -88.7753\n", + "Iteration No: 144 started. Searching for the next optimal point.\n", + "Iteration No: 144 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4051\n", + "Function value obtained: -88.4225\n", + "Current minimum: -88.7753\n", + "Iteration No: 145 started. Searching for the next optimal point.\n", + "Iteration No: 145 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3753\n", + "Function value obtained: -84.2388\n", + "Current minimum: -88.7753\n", + "Iteration No: 146 started. Searching for the next optimal point.\n", + "Iteration No: 146 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6092\n", + "Function value obtained: -84.6202\n", + "Current minimum: -88.7753\n", + "Iteration No: 147 started. Searching for the next optimal point.\n", + "Iteration No: 147 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5036\n", + "Function value obtained: -85.0381\n", + "Current minimum: -88.7753\n", + "Iteration No: 148 started. Searching for the next optimal point.\n", + "Iteration No: 148 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5213\n", + "Function value obtained: -85.1823\n", + "Current minimum: -88.7753\n", + "Iteration No: 149 started. Searching for the next optimal point.\n", + "Iteration No: 149 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4883\n", + "Function value obtained: -84.8191\n", + "Current minimum: -88.7753\n", + "Iteration No: 150 started. Searching for the next optimal point.\n", + "Iteration No: 150 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5293\n", + "Function value obtained: -84.6122\n", + "Current minimum: -88.7753\n", + "Iteration No: 151 started. Searching for the next optimal point.\n", + "Iteration No: 151 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4194\n", + "Function value obtained: -86.2020\n", + "Current minimum: -88.7753\n", + "Iteration No: 152 started. Searching for the next optimal point.\n", + "Iteration No: 152 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4013\n", + "Function value obtained: -83.6851\n", + "Current minimum: -88.7753\n", + "Iteration No: 153 started. Searching for the next optimal point.\n", + "Iteration No: 153 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4529\n", + "Function value obtained: -85.1818\n", + "Current minimum: -88.7753\n", + "Iteration No: 154 started. Searching for the next optimal point.\n", + "Iteration No: 154 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6050\n", + "Function value obtained: -83.3640\n", + "Current minimum: -88.7753\n", + "Iteration No: 155 started. Searching for the next optimal point.\n", + "Iteration No: 155 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4887\n", + "Function value obtained: -83.8857\n", + "Current minimum: -88.7753\n", + "Iteration No: 156 started. Searching for the next optimal point.\n", + "Iteration No: 156 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4733\n", + "Function value obtained: -85.9781\n", + "Current minimum: -88.7753\n", + "Iteration No: 157 started. Searching for the next optimal point.\n", + "Iteration No: 157 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4233\n", + "Function value obtained: -86.1714\n", + "Current minimum: -88.7753\n", + "Iteration No: 158 started. Searching for the next optimal point.\n", + "Iteration No: 158 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3923\n", + "Function value obtained: -84.6146\n", + "Current minimum: -88.7753\n", + "Iteration No: 159 started. Searching for the next optimal point.\n", + "Iteration No: 159 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4267\n", + "Function value obtained: -85.8127\n", + "Current minimum: -88.7753\n", + "Iteration No: 160 started. Searching for the next optimal point.\n", + "Iteration No: 160 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4167\n", + "Function value obtained: -83.9807\n", + "Current minimum: -88.7753\n", + "Iteration No: 161 started. Searching for the next optimal point.\n", + "Iteration No: 161 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3953\n", + "Function value obtained: -84.7165\n", + "Current minimum: -88.7753\n", + "Iteration No: 162 started. Searching for the next optimal point.\n", + "Iteration No: 162 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4204\n", + "Function value obtained: -86.2735\n", + "Current minimum: -88.7753\n", + "Iteration No: 163 started. Searching for the next optimal point.\n", + "Iteration No: 163 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4264\n", + "Function value obtained: -83.9990\n", + "Current minimum: -88.7753\n", + "Iteration No: 164 started. Searching for the next optimal point.\n", + "Iteration No: 164 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3655\n", + "Function value obtained: -85.5030\n", + "Current minimum: -88.7753\n", + "Iteration No: 165 started. Searching for the next optimal point.\n", + "Iteration No: 165 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4762\n", + "Function value obtained: -84.4318\n", + "Current minimum: -88.7753\n", + "Iteration No: 166 started. Searching for the next optimal point.\n", + "Iteration No: 166 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5290\n", + "Function value obtained: -83.5650\n", + "Current minimum: -88.7753\n", + "Iteration No: 167 started. Searching for the next optimal point.\n", + "Iteration No: 167 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5768\n", + "Function value obtained: -83.7536\n", + "Current minimum: -88.7753\n", + "Iteration No: 168 started. Searching for the next optimal point.\n", + "Iteration No: 168 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4432\n", + "Function value obtained: -85.6041\n", + "Current minimum: -88.7753\n", + "Iteration No: 169 started. Searching for the next optimal point.\n", + "Iteration No: 169 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4792\n", + "Function value obtained: -82.7865\n", + "Current minimum: -88.7753\n", + "Iteration No: 170 started. Searching for the next optimal point.\n", + "Iteration No: 170 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4226\n", + "Function value obtained: -87.7634\n", + "Current minimum: -88.7753\n", + "Iteration No: 171 started. Searching for the next optimal point.\n", + "Iteration No: 171 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4100\n", + "Function value obtained: -82.4402\n", + "Current minimum: -88.7753\n", + "Iteration No: 172 started. Searching for the next optimal point.\n", + "Iteration No: 172 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3907\n", + "Function value obtained: -85.2052\n", + "Current minimum: -88.7753\n", + "Iteration No: 173 started. Searching for the next optimal point.\n", + "Iteration No: 173 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4836\n", + "Function value obtained: -86.7284\n", + "Current minimum: -88.7753\n", + "Iteration No: 174 started. Searching for the next optimal point.\n", + "Iteration No: 174 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4957\n", + "Function value obtained: -85.3608\n", + "Current minimum: -88.7753\n", + "Iteration No: 175 started. Searching for the next optimal point.\n", + "Iteration No: 175 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5068\n", + "Function value obtained: -85.3126\n", + "Current minimum: -88.7753\n", + "Iteration No: 176 started. Searching for the next optimal point.\n", + "Iteration No: 176 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5056\n", + "Function value obtained: -86.8896\n", + "Current minimum: -88.7753\n", + "Iteration No: 177 started. Searching for the next optimal point.\n", + "Iteration No: 177 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4675\n", + "Function value obtained: -88.4021\n", + "Current minimum: -88.7753\n", + "Iteration No: 178 started. Searching for the next optimal point.\n", + "Iteration No: 178 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4960\n", + "Function value obtained: -87.5108\n", + "Current minimum: -88.7753\n", + "Iteration No: 179 started. Searching for the next optimal point.\n", + "Iteration No: 179 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3982\n", + "Function value obtained: -87.9028\n", + "Current minimum: -88.7753\n", + "Iteration No: 180 started. Searching for the next optimal point.\n", + "Iteration No: 180 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5482\n", + "Function value obtained: -82.8189\n", + "Current minimum: -88.7753\n", + "Iteration No: 181 started. Searching for the next optimal point.\n", + "Iteration No: 181 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4298\n", + "Function value obtained: -84.1876\n", + "Current minimum: -88.7753\n", + "Iteration No: 182 started. Searching for the next optimal point.\n", + "Iteration No: 182 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4025\n", + "Function value obtained: -85.6067\n", + "Current minimum: -88.7753\n", + "Iteration No: 183 started. Searching for the next optimal point.\n", + "Iteration No: 183 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4611\n", + "Function value obtained: -84.4604\n", + "Current minimum: -88.7753\n", + "Iteration No: 184 started. Searching for the next optimal point.\n", + "Iteration No: 184 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4176\n", + "Function value obtained: -83.6871\n", + "Current minimum: -88.7753\n", + "Iteration No: 185 started. Searching for the next optimal point.\n", + "Iteration No: 185 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4218\n", + "Function value obtained: -85.8311\n", + "Current minimum: -88.7753\n", + "Iteration No: 186 started. Searching for the next optimal point.\n", + "Iteration No: 186 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4395\n", + "Function value obtained: -86.7896\n", + "Current minimum: -88.7753\n", + "Iteration No: 187 started. Searching for the next optimal point.\n", + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4326\n", + "Function value obtained: -87.9845\n", + "Current minimum: -88.7753\n", + "Iteration No: 188 started. Searching for the next optimal point.\n", + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5302\n", + "Function value obtained: -83.6515\n", + "Current minimum: -88.7753\n", + "Iteration No: 189 started. Searching for the next optimal point.\n", + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4213\n", + "Function value obtained: -86.1331\n", + "Current minimum: -88.7753\n", + "Iteration No: 190 started. Searching for the next optimal point.\n", + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4315\n", + "Function value obtained: -88.5491\n", + "Current minimum: -88.7753\n", + "Iteration No: 191 started. Searching for the next optimal point.\n", + "Iteration No: 191 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4231\n", + "Function value obtained: -82.9554\n", + "Current minimum: -88.7753\n", + "Iteration No: 192 started. Searching for the next optimal point.\n", + "Iteration No: 192 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5195\n", + "Function value obtained: -86.4731\n", + "Current minimum: -88.7753\n", + "Iteration No: 193 started. Searching for the next optimal point.\n", + "Iteration No: 193 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3332\n", + "Function value obtained: -83.1675\n", + "Current minimum: -88.7753\n", + "Iteration No: 194 started. Searching for the next optimal point.\n", + "Iteration No: 194 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3312\n", + "Function value obtained: -84.1838\n", + "Current minimum: -88.7753\n", + "Iteration No: 195 started. Searching for the next optimal point.\n", + "Iteration No: 195 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4420\n", + "Function value obtained: -87.4097\n", + "Current minimum: -88.7753\n", + "Iteration No: 196 started. Searching for the next optimal point.\n", + "Iteration No: 196 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4707\n", + "Function value obtained: -83.4385\n", + "Current minimum: -88.7753\n", + "Iteration No: 197 started. Searching for the next optimal point.\n", + "Iteration No: 197 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4637\n", + "Function value obtained: -85.3367\n", + "Current minimum: -88.7753\n", + "Iteration No: 198 started. Searching for the next optimal point.\n", + "Iteration No: 198 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4298\n", + "Function value obtained: -85.7653\n", + "Current minimum: -88.7753\n", + "Iteration No: 199 started. Searching for the next optimal point.\n", + "Iteration No: 199 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4964\n", + "Function value obtained: -83.3255\n", + "Current minimum: -88.7753\n", + "Iteration No: 200 started. Searching for the next optimal point.\n", + "Iteration No: 200 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4868\n", + "Function value obtained: -85.8886\n", + "Current minimum: -88.7753\n", + "Iteration No: 201 started. Searching for the next optimal point.\n", + "Iteration No: 201 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4770\n", + "Function value obtained: -85.2426\n", + "Current minimum: -88.7753\n", + "Iteration No: 202 started. Searching for the next optimal point.\n", + "Iteration No: 202 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4131\n", + "Function value obtained: -86.0469\n", + "Current minimum: -88.7753\n", + "Iteration No: 203 started. Searching for the next optimal point.\n", + "Iteration No: 203 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4776\n", + "Function value obtained: -83.8412\n", + "Current minimum: -88.7753\n", + "Iteration No: 204 started. Searching for the next optimal point.\n", + "Iteration No: 204 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4809\n", + "Function value obtained: -85.9582\n", + "Current minimum: -88.7753\n", + "Iteration No: 205 started. Searching for the next optimal point.\n", + "Iteration No: 205 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5408\n", + "Function value obtained: -85.2496\n", + "Current minimum: -88.7753\n", + "Iteration No: 206 started. Searching for the next optimal point.\n", + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4540\n", + "Function value obtained: -87.1598\n", + "Current minimum: -88.7753\n", + "Iteration No: 207 started. Searching for the next optimal point.\n", + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5098\n", + "Function value obtained: -88.3519\n", + "Current minimum: -88.7753\n", + "Iteration No: 208 started. Searching for the next optimal point.\n", + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4384\n", + "Function value obtained: -83.1859\n", + "Current minimum: -88.7753\n", + "Iteration No: 209 started. Searching for the next optimal point.\n", + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5123\n", + "Function value obtained: -88.2460\n", + "Current minimum: -88.7753\n", + "Iteration No: 210 started. Searching for the next optimal point.\n", + "Iteration No: 210 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5359\n", + "Function value obtained: -1.9555\n", + "Current minimum: -88.7753\n", + "Iteration No: 211 started. Searching for the next optimal point.\n", + "Iteration No: 211 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4553\n", + "Function value obtained: -85.1104\n", + "Current minimum: -88.7753\n", + "Iteration No: 212 started. Searching for the next optimal point.\n", + "Iteration No: 212 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4382\n", + "Function value obtained: -83.3690\n", + "Current minimum: -88.7753\n", + "Iteration No: 213 started. Searching for the next optimal point.\n", + "Iteration No: 213 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4212\n", + "Function value obtained: -86.3645\n", + "Current minimum: -88.7753\n", + "Iteration No: 214 started. Searching for the next optimal point.\n", + "Iteration No: 214 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5351\n", + "Function value obtained: -85.0548\n", + "Current minimum: -88.7753\n", + "Iteration No: 215 started. Searching for the next optimal point.\n", + "Iteration No: 215 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4136\n", + "Function value obtained: -87.6862\n", + "Current minimum: -88.7753\n", + "Iteration No: 216 started. Searching for the next optimal point.\n", + "Iteration No: 216 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3671\n", + "Function value obtained: -84.1991\n", + "Current minimum: -88.7753\n", + "Iteration No: 217 started. Searching for the next optimal point.\n", + "Iteration No: 217 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4252\n", + "Function value obtained: -83.7993\n", + "Current minimum: -88.7753\n", + "Iteration No: 218 started. Searching for the next optimal point.\n", + "Iteration No: 218 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4868\n", + "Function value obtained: -85.7197\n", + "Current minimum: -88.7753\n", + "Iteration No: 219 started. Searching for the next optimal point.\n", + "Iteration No: 219 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3858\n", + "Function value obtained: -85.5064\n", + "Current minimum: -88.7753\n", + "Iteration No: 220 started. Searching for the next optimal point.\n", + "Iteration No: 220 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3968\n", + "Function value obtained: -84.8681\n", + "Current minimum: -88.7753\n", + "Iteration No: 221 started. Searching for the next optimal point.\n", + "Iteration No: 221 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4500\n", + "Function value obtained: -83.1133\n", + "Current minimum: -88.7753\n", + "Iteration No: 222 started. Searching for the next optimal point.\n", + "Iteration No: 222 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4255\n", + "Function value obtained: -85.2460\n", + "Current minimum: -88.7753\n", + "Iteration No: 223 started. Searching for the next optimal point.\n", + "Iteration No: 223 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4709\n", + "Function value obtained: -86.5661\n", + "Current minimum: -88.7753\n", + "Iteration No: 224 started. Searching for the next optimal point.\n", + "Iteration No: 224 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4376\n", + "Function value obtained: -86.9153\n", + "Current minimum: -88.7753\n", + "Iteration No: 225 started. Searching for the next optimal point.\n", + "Iteration No: 225 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4839\n", + "Function value obtained: -86.7046\n", + "Current minimum: -88.7753\n", + "Iteration No: 226 started. Searching for the next optimal point.\n", + "Iteration No: 226 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5190\n", + "Function value obtained: -83.2514\n", + "Current minimum: -88.7753\n", + "Iteration No: 227 started. Searching for the next optimal point.\n", + "Iteration No: 227 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4422\n", + "Function value obtained: -86.8100\n", + "Current minimum: -88.7753\n", + "Iteration No: 228 started. Searching for the next optimal point.\n", + "Iteration No: 228 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5086\n", + "Function value obtained: -87.9662\n", + "Current minimum: -88.7753\n", + "Iteration No: 229 started. Searching for the next optimal point.\n", + "Iteration No: 229 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4060\n", + "Function value obtained: -84.7567\n", + "Current minimum: -88.7753\n", + "Iteration No: 230 started. Searching for the next optimal point.\n", + "Iteration No: 230 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5330\n", + "Function value obtained: -87.2429\n", + "Current minimum: -88.7753\n", + "Iteration No: 231 started. Searching for the next optimal point.\n", + "Iteration No: 231 ended. Search finished for the next optimal point.\n", + "Time taken: 1.2946\n", + "Function value obtained: -87.2583\n", + "Current minimum: -88.7753\n", + "Iteration No: 232 started. Searching for the next optimal point.\n", + "Iteration No: 232 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4330\n", + "Function value obtained: -86.1164\n", + "Current minimum: -88.7753\n", + "Iteration No: 233 started. Searching for the next optimal point.\n", + "Iteration No: 233 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3539\n", + "Function value obtained: -83.5643\n", + "Current minimum: -88.7753\n", + "Iteration No: 234 started. Searching for the next optimal point.\n", + "Iteration No: 234 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3255\n", + "Function value obtained: -85.4728\n", + "Current minimum: -88.7753\n", + "Iteration No: 235 started. Searching for the next optimal point.\n", + "Iteration No: 235 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4302\n", + "Function value obtained: -82.9335\n", + "Current minimum: -88.7753\n", + "Iteration No: 236 started. Searching for the next optimal point.\n", + "Iteration No: 236 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5344\n", + "Function value obtained: -86.8290\n", + "Current minimum: -88.7753\n", + "Iteration No: 237 started. Searching for the next optimal point.\n", + "Iteration No: 237 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4398\n", + "Function value obtained: -85.2549\n", + "Current minimum: -88.7753\n", + "Iteration No: 238 started. Searching for the next optimal point.\n", + "Iteration No: 238 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3549\n", + "Function value obtained: -84.4800\n", + "Current minimum: -88.7753\n", + "Iteration No: 239 started. Searching for the next optimal point.\n", + "Iteration No: 239 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3917\n", + "Function value obtained: -81.0330\n", + "Current minimum: -88.7753\n", + "Iteration No: 240 started. Searching for the next optimal point.\n", + "Iteration No: 240 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3942\n", + "Function value obtained: -83.7726\n", + "Current minimum: -88.7753\n", + "Iteration No: 241 started. Searching for the next optimal point.\n", + "Iteration No: 241 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3860\n", + "Function value obtained: -84.5568\n", + "Current minimum: -88.7753\n", + "Iteration No: 242 started. Searching for the next optimal point.\n", + "Iteration No: 242 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3424\n", + "Function value obtained: -83.2933\n", + "Current minimum: -88.7753\n", + "Iteration No: 243 started. Searching for the next optimal point.\n", + "Iteration No: 243 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4412\n", + "Function value obtained: -84.1330\n", + "Current minimum: -88.7753\n", + "Iteration No: 244 started. Searching for the next optimal point.\n", + "Iteration No: 244 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4131\n", + "Function value obtained: -84.7214\n", + "Current minimum: -88.7753\n", + "Iteration No: 245 started. Searching for the next optimal point.\n", + "Iteration No: 245 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4098\n", + "Function value obtained: -82.0758\n", + "Current minimum: -88.7753\n", + "Iteration No: 246 started. Searching for the next optimal point.\n", + "Iteration No: 246 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4728\n", + "Function value obtained: -84.5416\n", + "Current minimum: -88.7753\n", + "Iteration No: 247 started. Searching for the next optimal point.\n", + "Iteration No: 247 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4175\n", + "Function value obtained: -86.7355\n", + "Current minimum: -88.7753\n", + "Iteration No: 248 started. Searching for the next optimal point.\n", + "Iteration No: 248 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4663\n", + "Function value obtained: -85.3541\n", + "Current minimum: -88.7753\n", + "Iteration No: 249 started. Searching for the next optimal point.\n", + "Iteration No: 249 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4562\n", + "Function value obtained: -83.6708\n", + "Current minimum: -88.7753\n", + "Iteration No: 250 started. Searching for the next optimal point.\n", + "Iteration No: 250 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5194\n", + "Function value obtained: -84.3320\n", + "Current minimum: -88.7753\n", + "Iteration No: 251 started. Searching for the next optimal point.\n", + "Iteration No: 251 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4098\n", + "Function value obtained: -83.4144\n", + "Current minimum: -88.7753\n", + "Iteration No: 252 started. Searching for the next optimal point.\n", + "Iteration No: 252 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4772\n", + "Function value obtained: -82.3846\n", + "Current minimum: -88.7753\n", + "Iteration No: 253 started. Searching for the next optimal point.\n", + "Iteration No: 253 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4379\n", + "Function value obtained: -86.4315\n", + "Current minimum: -88.7753\n", + "Iteration No: 254 started. Searching for the next optimal point.\n", + "Iteration No: 254 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5181\n", + "Function value obtained: -85.0385\n", + "Current minimum: -88.7753\n", + "Iteration No: 255 started. Searching for the next optimal point.\n", + "Iteration No: 255 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4027\n", + "Function value obtained: -85.4571\n", + "Current minimum: -88.7753\n", + "Iteration No: 256 started. Searching for the next optimal point.\n", + "Iteration No: 256 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6383\n", + "Function value obtained: -83.8486\n", + "Current minimum: -88.7753\n", + "Iteration No: 257 started. Searching for the next optimal point.\n", + "Iteration No: 257 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4409\n", + "Function value obtained: -85.1107\n", + "Current minimum: -88.7753\n", + "Iteration No: 258 started. Searching for the next optimal point.\n", + "Iteration No: 258 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4200\n", + "Function value obtained: -87.1252\n", + "Current minimum: -88.7753\n", + "Iteration No: 259 started. Searching for the next optimal point.\n", + "Iteration No: 259 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4187\n", + "Function value obtained: -83.3954\n", + "Current minimum: -88.7753\n", + "Iteration No: 260 started. Searching for the next optimal point.\n", + "Iteration No: 260 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4288\n", + "Function value obtained: -85.4210\n", + "Current minimum: -88.7753\n", + "Iteration No: 261 started. Searching for the next optimal point.\n", + "Iteration No: 261 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4516\n", + "Function value obtained: -77.1173\n", + "Current minimum: -88.7753\n", + "Iteration No: 262 started. Searching for the next optimal point.\n", + "Iteration No: 262 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5318\n", + "Function value obtained: -81.6807\n", + "Current minimum: -88.7753\n", + "Iteration No: 263 started. Searching for the next optimal point.\n", + "Iteration No: 263 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3402\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.7753\n", + "Iteration No: 264 started. Searching for the next optimal point.\n", + "Iteration No: 264 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4758\n", + "Function value obtained: -86.9722\n", + "Current minimum: -88.7753\n", + "Iteration No: 265 started. Searching for the next optimal point.\n", + "Iteration No: 265 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3942\n", + "Function value obtained: -83.7070\n", + "Current minimum: -88.7753\n", + "Iteration No: 266 started. Searching for the next optimal point.\n", + "Iteration No: 266 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3956\n", + "Function value obtained: -84.6790\n", + "Current minimum: -88.7753\n", + "Iteration No: 267 started. Searching for the next optimal point.\n", + "Iteration No: 267 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3868\n", + "Function value obtained: -83.3753\n", + "Current minimum: -88.7753\n", + "Iteration No: 268 started. Searching for the next optimal point.\n", + "Iteration No: 268 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3639\n", + "Function value obtained: -83.2936\n", + "Current minimum: -88.7753\n", + "Iteration No: 269 started. Searching for the next optimal point.\n", + "Iteration No: 269 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5800\n", + "Function value obtained: -84.8240\n", + "Current minimum: -88.7753\n", + "Iteration No: 270 started. Searching for the next optimal point.\n", + "Iteration No: 270 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3950\n", + "Function value obtained: -81.8256\n", + "Current minimum: -88.7753\n", + "Iteration No: 271 started. Searching for the next optimal point.\n", + "Iteration No: 271 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4661\n", + "Function value obtained: -84.8804\n", + "Current minimum: -88.7753\n", + "Iteration No: 272 started. Searching for the next optimal point.\n", + "Iteration No: 272 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4392\n", + "Function value obtained: -86.0750\n", + "Current minimum: -88.7753\n", + "Iteration No: 273 started. Searching for the next optimal point.\n", + "Iteration No: 273 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4528\n", + "Function value obtained: -87.0051\n", + "Current minimum: -88.7753\n", + "Iteration No: 274 started. Searching for the next optimal point.\n", + "Iteration No: 274 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4274\n", + "Function value obtained: -84.9102\n", + "Current minimum: -88.7753\n", + "Iteration No: 275 started. Searching for the next optimal point.\n", + "Iteration No: 275 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4485\n", + "Function value obtained: -86.2219\n", + "Current minimum: -88.7753\n", + "Iteration No: 276 started. Searching for the next optimal point.\n", + "Iteration No: 276 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4116\n", + "Function value obtained: -84.4210\n", + "Current minimum: -88.7753\n", + "Iteration No: 277 started. Searching for the next optimal point.\n", + "Iteration No: 277 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4901\n", + "Function value obtained: -82.6327\n", + "Current minimum: -88.7753\n", + "Iteration No: 278 started. Searching for the next optimal point.\n", + "Iteration No: 278 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3865\n", + "Function value obtained: -77.5167\n", + "Current minimum: -88.7753\n", + "Iteration No: 279 started. Searching for the next optimal point.\n", + "Iteration No: 279 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3774\n", + "Function value obtained: -84.9690\n", + "Current minimum: -88.7753\n", + "Iteration No: 280 started. Searching for the next optimal point.\n", + "Iteration No: 280 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3862\n", + "Function value obtained: -83.6576\n", + "Current minimum: -88.7753\n", + "Iteration No: 281 started. Searching for the next optimal point.\n", + "Iteration No: 281 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5494\n", + "Function value obtained: -80.7605\n", + "Current minimum: -88.7753\n", + "Iteration No: 282 started. Searching for the next optimal point.\n", + "Iteration No: 282 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4972\n", + "Function value obtained: -83.6298\n", + "Current minimum: -88.7753\n", + "Iteration No: 283 started. Searching for the next optimal point.\n", + "Iteration No: 283 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5874\n", + "Function value obtained: -81.1308\n", + "Current minimum: -88.7753\n", + "Iteration No: 284 started. Searching for the next optimal point.\n", + "Iteration No: 284 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5012\n", + "Function value obtained: -86.6384\n", + "Current minimum: -88.7753\n", + "Iteration No: 285 started. Searching for the next optimal point.\n", + "Iteration No: 285 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4556\n", + "Function value obtained: -82.2282\n", + "Current minimum: -88.7753\n", + "Iteration No: 286 started. Searching for the next optimal point.\n", + "Iteration No: 286 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4690\n", + "Function value obtained: -87.2256\n", + "Current minimum: -88.7753\n", + "Iteration No: 287 started. Searching for the next optimal point.\n", + "Iteration No: 287 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3679\n", + "Function value obtained: -83.5084\n", + "Current minimum: -88.7753\n", + "Iteration No: 288 started. Searching for the next optimal point.\n", + "Iteration No: 288 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4671\n", + "Function value obtained: -87.1797\n", + "Current minimum: -88.7753\n", + "Iteration No: 289 started. Searching for the next optimal point.\n", + "Iteration No: 289 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4082\n", + "Function value obtained: -82.9494\n", + "Current minimum: -88.7753\n", + "Iteration No: 290 started. Searching for the next optimal point.\n", + "Iteration No: 290 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4070\n", + "Function value obtained: -87.5875\n", + "Current minimum: -88.7753\n", + "Iteration No: 291 started. Searching for the next optimal point.\n", + "Iteration No: 291 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4488\n", + "Function value obtained: -84.1121\n", + "Current minimum: -88.7753\n", + "Iteration No: 292 started. Searching for the next optimal point.\n", + "Iteration No: 292 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4438\n", + "Function value obtained: -84.7971\n", + "Current minimum: -88.7753\n", + "Iteration No: 293 started. Searching for the next optimal point.\n", + "Iteration No: 293 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4100\n", + "Function value obtained: -89.0073\n", + "Current minimum: -89.0073\n", + "Iteration No: 294 started. Searching for the next optimal point.\n", + "Iteration No: 294 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4276\n", + "Function value obtained: -84.2889\n", + "Current minimum: -89.0073\n", + "Iteration No: 295 started. Searching for the next optimal point.\n", + "Iteration No: 295 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4917\n", + "Function value obtained: -82.3117\n", + "Current minimum: -89.0073\n", + "Iteration No: 296 started. Searching for the next optimal point.\n", + "Iteration No: 296 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4100\n", + "Function value obtained: -83.1597\n", + "Current minimum: -89.0073\n", + "Iteration No: 297 started. Searching for the next optimal point.\n", + "Iteration No: 297 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5157\n", + "Function value obtained: -87.2920\n", + "Current minimum: -89.0073\n", + "Iteration No: 298 started. Searching for the next optimal point.\n", + "Iteration No: 298 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4789\n", + "Function value obtained: -86.9859\n", + "Current minimum: -89.0073\n", + "Iteration No: 299 started. Searching for the next optimal point.\n", + "Iteration No: 299 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4337\n", + "Function value obtained: -85.3427\n", + "Current minimum: -89.0073\n", + "Iteration No: 300 started. Searching for the next optimal point.\n", + "Iteration No: 300 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4983\n", + "Function value obtained: -83.2631\n", + "Current minimum: -89.0073\n", + "CPU times: user 2min 12s, sys: 27.3 s, total: 2min 39s\n", + "Wall time: 7min 9s\n" ] }, { "data": { "text/plain": [ - "(-88.45482307660751, [-1.9533840854652205])" + "(-89.00730788323125, [-1.8835640672410259])" ] }, - "execution_count": 94, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 300, verbose=True, n_jobs=-1)\n", "esc_gbrt.fun, esc_gbrt.x" ] }, - { - "cell_type": "code", - "execution_count": 95, - "id": "d85a57bd-e338-468d-9d63-45d82fe53aef", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 95, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_convergence(esc_gbrt)" - ] - }, { "cell_type": "markdown", "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", @@ -1643,9 +6432,13 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 11, "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -1655,597 +6448,1537 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8277\n", - "Function value obtained: -3.3906\n", - "Current minimum: -3.3906\n", + "Time taken: 1.3055\n", + "Function value obtained: -27.6420\n", + "Current minimum: -27.6420\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8487\n", - "Function value obtained: -47.0619\n", - "Current minimum: -47.0619\n", + "Time taken: 1.3289\n", + "Function value obtained: -78.1050\n", + "Current minimum: -78.1050\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.8061\n", - "Function value obtained: -15.8264\n", - "Current minimum: -47.0619\n", + "Time taken: 1.2986\n", + "Function value obtained: -19.7252\n", + "Current minimum: -78.1050\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.7809\n", - "Function value obtained: -2.1098\n", - "Current minimum: -47.0619\n", + "Time taken: 1.2351\n", + "Function value obtained: -44.3313\n", + "Current minimum: -78.1050\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8065\n", - "Function value obtained: -3.1192\n", - "Current minimum: -47.0619\n", + "Time taken: 1.2662\n", + "Function value obtained: -49.3958\n", + "Current minimum: -78.1050\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8604\n", - "Function value obtained: -15.0873\n", - "Current minimum: -47.0619\n", + "Time taken: 1.3035\n", + "Function value obtained: -81.1550\n", + "Current minimum: -81.1550\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8625\n", - "Function value obtained: -35.7408\n", - "Current minimum: -47.0619\n", + "Time taken: 1.3246\n", + "Function value obtained: -38.6728\n", + "Current minimum: -81.1550\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.7732\n", - "Function value obtained: -0.5765\n", - "Current minimum: -47.0619\n", + "Time taken: 1.3186\n", + "Function value obtained: -58.2459\n", + "Current minimum: -81.1550\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.8468\n", - "Function value obtained: -14.0440\n", - "Current minimum: -47.0619\n", + "Time taken: 1.2767\n", + "Function value obtained: -63.2675\n", + "Current minimum: -81.1550\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.1358\n", - "Function value obtained: -53.9416\n", - "Current minimum: -53.9416\n", + "Time taken: 6.7294\n", + "Function value obtained: -13.7136\n", + "Current minimum: -81.1550\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1185\n", - "Function value obtained: -37.9501\n", - "Current minimum: -53.9416\n", + "Time taken: 2.6489\n", + "Function value obtained: -79.4565\n", + "Current minimum: -81.1550\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1148\n", - "Function value obtained: -55.1610\n", - "Current minimum: -55.1610\n", + "Time taken: 2.6055\n", + "Function value obtained: -0.0000\n", + "Current minimum: -81.1550\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2095\n", - "Function value obtained: -53.4027\n", - "Current minimum: -55.1610\n", + "Time taken: 2.6350\n", + "Function value obtained: -0.0000\n", + "Current minimum: -81.1550\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0414\n", - "Function value obtained: -23.3036\n", - "Current minimum: -55.1610\n", + "Time taken: 2.6692\n", + "Function value obtained: -79.6332\n", + "Current minimum: -81.1550\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0363\n", - "Function value obtained: -60.5604\n", - "Current minimum: -60.5604\n", + "Time taken: 2.6754\n", + "Function value obtained: -74.3325\n", + "Current minimum: -81.1550\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0544\n", - "Function value obtained: -64.3094\n", - "Current minimum: -64.3094\n", + "Time taken: 2.5171\n", + "Function value obtained: -82.1995\n", + "Current minimum: -82.1995\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 0.9672\n", - "Function value obtained: -69.4757\n", - "Current minimum: -69.4757\n", + "Time taken: 2.7444\n", + "Function value obtained: -76.4244\n", + "Current minimum: -82.1995\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0518\n", - "Function value obtained: -75.2616\n", - "Current minimum: -75.2616\n", + "Time taken: 2.3227\n", + "Function value obtained: -59.0022\n", + "Current minimum: -82.1995\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0739\n", - "Function value obtained: -81.2147\n", - "Current minimum: -81.2147\n", + "Time taken: 1.4925\n", + "Function value obtained: -79.8453\n", + "Current minimum: -82.1995\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1083\n", - "Function value obtained: -81.5636\n", - "Current minimum: -81.5636\n", + "Time taken: 1.5988\n", + "Function value obtained: -82.0734\n", + "Current minimum: -82.1995\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1196\n", - "Function value obtained: -79.4084\n", - "Current minimum: -81.5636\n", + "Time taken: 1.5444\n", + "Function value obtained: -82.1329\n", + "Current minimum: -82.1995\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1764\n", - "Function value obtained: -0.0000\n", - "Current minimum: -81.5636\n", + "Time taken: 1.5446\n", + "Function value obtained: -75.1359\n", + "Current minimum: -82.1995\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0733\n", - "Function value obtained: -77.2342\n", - "Current minimum: -81.5636\n", + "Time taken: 1.4972\n", + "Function value obtained: -47.4599\n", + "Current minimum: -82.1995\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0143\n", - "Function value obtained: -79.9140\n", - "Current minimum: -81.5636\n", + "Time taken: 1.5302\n", + "Function value obtained: -82.9885\n", + "Current minimum: -82.9885\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1439\n", - "Function value obtained: -80.7929\n", - "Current minimum: -81.5636\n", + "Time taken: 1.4491\n", + "Function value obtained: -79.8435\n", + "Current minimum: -82.9885\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1345\n", - "Function value obtained: -85.4421\n", - "Current minimum: -85.4421\n", + "Time taken: 1.6897\n", + "Function value obtained: -78.2639\n", + "Current minimum: -82.9885\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1557\n", - "Function value obtained: -80.6570\n", - "Current minimum: -85.4421\n", + "Time taken: 1.4834\n", + "Function value obtained: -79.4805\n", + "Current minimum: -82.9885\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1955\n", - "Function value obtained: -82.7055\n", - "Current minimum: -85.4421\n", + "Time taken: 1.4405\n", + "Function value obtained: -31.7971\n", + "Current minimum: -82.9885\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1922\n", - "Function value obtained: -87.1918\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5430\n", + "Function value obtained: -81.7057\n", + "Current minimum: -82.9885\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0719\n", - "Function value obtained: -85.4975\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5597\n", + "Function value obtained: -86.2651\n", + "Current minimum: -86.2651\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1543\n", - "Function value obtained: -85.1530\n", - "Current minimum: -87.1918\n", + "Time taken: 1.3970\n", + "Function value obtained: -84.6473\n", + "Current minimum: -86.2651\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2110\n", - "Function value obtained: -81.3207\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5765\n", + "Function value obtained: -85.6389\n", + "Current minimum: -86.2651\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1746\n", - "Function value obtained: -81.8238\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5050\n", + "Function value obtained: -80.7363\n", + "Current minimum: -86.2651\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1516\n", - "Function value obtained: -82.0723\n", - "Current minimum: -87.1918\n", + "Time taken: 1.4977\n", + "Function value obtained: -81.0955\n", + "Current minimum: -86.2651\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1830\n", - "Function value obtained: -84.5704\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5693\n", + "Function value obtained: -1.9364\n", + "Current minimum: -86.2651\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1976\n", - "Function value obtained: -61.5135\n", - "Current minimum: -87.1918\n", + "Time taken: 1.6156\n", + "Function value obtained: -83.5928\n", + "Current minimum: -86.2651\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1740\n", - "Function value obtained: -81.7941\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5964\n", + "Function value obtained: -81.4378\n", + "Current minimum: -86.2651\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1302\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5503\n", + "Function value obtained: -83.7283\n", + "Current minimum: -86.2651\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2333\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5272\n", + "Function value obtained: -84.4892\n", + "Current minimum: -86.2651\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2138\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1918\n", + "Time taken: 1.6030\n", + "Function value obtained: -83.2422\n", + "Current minimum: -86.2651\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2293\n", - "Function value obtained: -76.3928\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5581\n", + "Function value obtained: -84.7703\n", + "Current minimum: -86.2651\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1403\n", + "Time taken: 1.5818\n", "Function value obtained: -0.0000\n", - "Current minimum: -87.1918\n", + "Current minimum: -86.2651\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3364\n", - "Function value obtained: -84.5465\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5588\n", + "Function value obtained: -86.1378\n", + "Current minimum: -86.2651\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3526\n", - "Function value obtained: -86.3146\n", - "Current minimum: -87.1918\n", + "Time taken: 1.7102\n", + "Function value obtained: -87.6390\n", + "Current minimum: -87.6390\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2450\n", - "Function value obtained: -50.8457\n", - "Current minimum: -87.1918\n", + "Time taken: 1.7003\n", + "Function value obtained: -88.1836\n", + "Current minimum: -88.1836\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2840\n", - "Function value obtained: -83.0865\n", - "Current minimum: -87.1918\n", + "Time taken: 1.7084\n", + "Function value obtained: -88.2088\n", + "Current minimum: -88.2088\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3018\n", - "Function value obtained: -85.2767\n", - "Current minimum: -87.1918\n", + "Time taken: 1.6072\n", + "Function value obtained: -84.0442\n", + "Current minimum: -88.2088\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2706\n", - "Function value obtained: -83.9122\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5923\n", + "Function value obtained: -83.8470\n", + "Current minimum: -88.2088\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2112\n", - "Function value obtained: -85.7570\n", - "Current minimum: -87.1918\n", + "Time taken: 1.7308\n", + "Function value obtained: -86.4331\n", + "Current minimum: -88.2088\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4107\n", - "Function value obtained: -82.9332\n", - "Current minimum: -87.1918\n", + "Time taken: 1.6601\n", + "Function value obtained: -84.3033\n", + "Current minimum: -88.2088\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1957\n", - "Function value obtained: -75.5497\n", - "Current minimum: -87.1918\n", + "Time taken: 1.6979\n", + "Function value obtained: -88.4533\n", + "Current minimum: -88.4533\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2399\n", - "Function value obtained: -84.9163\n", - "Current minimum: -87.1918\n", + "Time taken: 1.5749\n", + "Function value obtained: -84.0851\n", + "Current minimum: -88.4533\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3341\n", - "Function value obtained: -85.7154\n", - "Current minimum: -87.1918\n", + "Time taken: 1.6064\n", + "Function value obtained: -84.9920\n", + "Current minimum: -88.4533\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3625\n", - "Function value obtained: -88.0328\n", - "Current minimum: -88.0328\n", + "Time taken: 1.6048\n", + "Function value obtained: -84.2240\n", + "Current minimum: -88.4533\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3219\n", - "Function value obtained: -86.8834\n", - "Current minimum: -88.0328\n", + "Time taken: 1.6681\n", + "Function value obtained: -83.8135\n", + "Current minimum: -88.4533\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3578\n", - "Function value obtained: -85.5236\n", - "Current minimum: -88.0328\n", + "Time taken: 1.6173\n", + "Function value obtained: -2.3999\n", + "Current minimum: -88.4533\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2891\n", - "Function value obtained: -88.8933\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7242\n", + "Function value obtained: -83.6010\n", + "Current minimum: -88.4533\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3102\n", - "Function value obtained: -84.2244\n", - "Current minimum: -88.8933\n", + "Time taken: 1.5484\n", + "Function value obtained: -86.3004\n", + "Current minimum: -88.4533\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3314\n", - "Function value obtained: -82.4454\n", - "Current minimum: -88.8933\n", + "Time taken: 1.6542\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.4533\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2334\n", - "Function value obtained: -82.1581\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7897\n", + "Function value obtained: -81.3552\n", + "Current minimum: -88.4533\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3595\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7200\n", + "Function value obtained: -77.9104\n", + "Current minimum: -88.4533\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3186\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7528\n", + "Function value obtained: -84.1339\n", + "Current minimum: -88.4533\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4082\n", - "Function value obtained: -78.9668\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7421\n", + "Function value obtained: -3.8739\n", + "Current minimum: -88.4533\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3325\n", - "Function value obtained: -86.3067\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7754\n", + "Function value obtained: -84.1307\n", + "Current minimum: -88.4533\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3904\n", - "Function value obtained: -81.0560\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7195\n", + "Function value obtained: -78.8474\n", + "Current minimum: -88.4533\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3399\n", - "Function value obtained: -82.6791\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7647\n", + "Function value obtained: -87.5901\n", + "Current minimum: -88.4533\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3901\n", - "Function value obtained: -6.3653\n", - "Current minimum: -88.8933\n", + "Time taken: 1.8416\n", + "Function value obtained: -84.6699\n", + "Current minimum: -88.4533\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3662\n", - "Function value obtained: -87.1675\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7751\n", + "Function value obtained: -82.5775\n", + "Current minimum: -88.4533\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4481\n", - "Function value obtained: -85.4332\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7313\n", + "Function value obtained: -88.1452\n", + "Current minimum: -88.4533\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4340\n", - "Function value obtained: -52.2253\n", - "Current minimum: -88.8933\n", + "Time taken: 1.9032\n", + "Function value obtained: -85.1442\n", + "Current minimum: -88.4533\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3260\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7385\n", + "Function value obtained: -2.5050\n", + "Current minimum: -88.4533\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3548\n", - "Function value obtained: -86.3187\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7224\n", + "Function value obtained: -82.2524\n", + "Current minimum: -88.4533\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4130\n", - "Function value obtained: -83.7906\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7859\n", + "Function value obtained: -74.2668\n", + "Current minimum: -88.4533\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4170\n", - "Function value obtained: -84.1353\n", - "Current minimum: -88.8933\n", + "Time taken: 1.8074\n", + "Function value obtained: -76.8367\n", + "Current minimum: -88.4533\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4485\n", - "Function value obtained: -83.7904\n", - "Current minimum: -88.8933\n", + "Time taken: 1.7701\n", + "Function value obtained: -90.6333\n", + "Current minimum: -90.6333\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4173\n", - "Function value obtained: -84.7642\n", - "Current minimum: -88.8933\n", + "Time taken: 1.8479\n", + "Function value obtained: -85.4348\n", + "Current minimum: -90.6333\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3184\n", - "Function value obtained: -65.5597\n", - "Current minimum: -88.8933\n", + "Time taken: 1.8363\n", + "Function value obtained: -82.3339\n", + "Current minimum: -90.6333\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4865\n", - "Function value obtained: -89.2098\n", - "Current minimum: -89.2098\n", + "Time taken: 1.8753\n", + "Function value obtained: -85.6496\n", + "Current minimum: -90.6333\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4974\n", - "Function value obtained: -85.0183\n", - "Current minimum: -89.2098\n", + "Time taken: 1.8171\n", + "Function value obtained: -85.2793\n", + "Current minimum: -90.6333\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5393\n", - "Function value obtained: -83.8698\n", - "Current minimum: -89.2098\n", + "Time taken: 1.8682\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5302\n", - "Function value obtained: -87.2745\n", - "Current minimum: -89.2098\n", + "Time taken: 2.0042\n", + "Function value obtained: -72.8643\n", + "Current minimum: -90.6333\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5426\n", - "Function value obtained: -84.7901\n", - "Current minimum: -89.2098\n", + "Time taken: 1.8247\n", + "Function value obtained: -36.2201\n", + "Current minimum: -90.6333\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5858\n", - "Function value obtained: -85.0201\n", - "Current minimum: -89.2098\n", + "Time taken: 1.9199\n", + "Function value obtained: -52.9810\n", + "Current minimum: -90.6333\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5041\n", - "Function value obtained: -78.1778\n", - "Current minimum: -89.2098\n", + "Time taken: 1.9531\n", + "Function value obtained: -82.3026\n", + "Current minimum: -90.6333\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5008\n", - "Function value obtained: -77.2769\n", - "Current minimum: -89.2098\n", + "Time taken: 1.8739\n", + "Function value obtained: -85.8179\n", + "Current minimum: -90.6333\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5763\n", - "Function value obtained: -77.7452\n", - "Current minimum: -89.2098\n", + "Time taken: 1.8679\n", + "Function value obtained: -2.7283\n", + "Current minimum: -90.6333\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5668\n", - "Function value obtained: -82.0783\n", - "Current minimum: -89.2098\n", + "Time taken: 1.9346\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7369\n", - "Function value obtained: -81.9447\n", - "Current minimum: -89.2098\n", + "Time taken: 1.9970\n", + "Function value obtained: -85.0913\n", + "Current minimum: -90.6333\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5226\n", - "Function value obtained: -74.3187\n", - "Current minimum: -89.2098\n", + "Time taken: 1.9889\n", + "Function value obtained: -86.0498\n", + "Current minimum: -90.6333\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5942\n", - "Function value obtained: -3.8355\n", - "Current minimum: -89.2098\n", + "Time taken: 1.9690\n", + "Function value obtained: -89.3086\n", + "Current minimum: -90.6333\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6684\n", - "Function value obtained: -85.2797\n", - "Current minimum: -89.2098\n", + "Time taken: 2.0585\n", + "Function value obtained: -87.4380\n", + "Current minimum: -90.6333\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6661\n", - "Function value obtained: -71.3702\n", - "Current minimum: -89.2098\n", + "Time taken: 2.2492\n", + "Function value obtained: -79.2090\n", + "Current minimum: -90.6333\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6443\n", - "Function value obtained: -0.0000\n", - "Current minimum: -89.2098\n", + "Time taken: 2.0783\n", + "Function value obtained: -83.0764\n", + "Current minimum: -90.6333\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7330\n", - "Function value obtained: -80.8421\n", - "Current minimum: -89.2098\n", + "Time taken: 2.0430\n", + "Function value obtained: -86.2792\n", + "Current minimum: -90.6333\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7009\n", - "Function value obtained: -7.7503\n", - "Current minimum: -89.2098\n", + "Time taken: 2.1258\n", + "Function value obtained: -82.8770\n", + "Current minimum: -90.6333\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6462\n", - "Function value obtained: -78.0483\n", - "Current minimum: -89.2098\n", + "Time taken: 2.0408\n", + "Function value obtained: -82.4791\n", + "Current minimum: -90.6333\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8061\n", - "Function value obtained: -81.7959\n", - "Current minimum: -89.2098\n", + "Time taken: 2.0456\n", + "Function value obtained: -85.6827\n", + "Current minimum: -90.6333\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7677\n", - "Function value obtained: -88.2391\n", - "Current minimum: -89.2098\n", + "Time taken: 2.0294\n", + "Function value obtained: -74.7308\n", + "Current minimum: -90.6333\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7579\n", - "Function value obtained: -88.6091\n", - "Current minimum: -89.2098\n", + "Time taken: 2.1141\n", + "Function value obtained: -83.3760\n", + "Current minimum: -90.6333\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7046\n", - "Function value obtained: -82.8556\n", - "Current minimum: -89.2098\n", - "CPU times: user 5min 28s, sys: 32min 33s, total: 38min 2s\n", - "Wall time: 2min 8s\n" + "Time taken: 2.2029\n", + "Function value obtained: -14.3625\n", + "Current minimum: -90.6333\n", + "Iteration No: 101 started. Searching for the next optimal point.\n", + "Iteration No: 101 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1955\n", + "Function value obtained: -71.1589\n", + "Current minimum: -90.6333\n", + "Iteration No: 102 started. Searching for the next optimal point.\n", + "Iteration No: 102 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2321\n", + "Function value obtained: -77.2377\n", + "Current minimum: -90.6333\n", + "Iteration No: 103 started. Searching for the next optimal point.\n", + "Iteration No: 103 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2387\n", + "Function value obtained: -77.7340\n", + "Current minimum: -90.6333\n", + "Iteration No: 104 started. Searching for the next optimal point.\n", + "Iteration No: 104 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1820\n", + "Function value obtained: -83.7139\n", + "Current minimum: -90.6333\n", + "Iteration No: 105 started. Searching for the next optimal point.\n", + "Iteration No: 105 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2461\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", + "Iteration No: 106 started. Searching for the next optimal point.\n", + "Iteration No: 106 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2158\n", + "Function value obtained: -3.9035\n", + "Current minimum: -90.6333\n", + "Iteration No: 107 started. Searching for the next optimal point.\n", + "Iteration No: 107 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2611\n", + "Function value obtained: -75.1242\n", + "Current minimum: -90.6333\n", + "Iteration No: 108 started. Searching for the next optimal point.\n", + "Iteration No: 108 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3445\n", + "Function value obtained: -85.5275\n", + "Current minimum: -90.6333\n", + "Iteration No: 109 started. Searching for the next optimal point.\n", + "Iteration No: 109 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2808\n", + "Function value obtained: -84.5770\n", + "Current minimum: -90.6333\n", + "Iteration No: 110 started. Searching for the next optimal point.\n", + "Iteration No: 110 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2629\n", + "Function value obtained: -85.4486\n", + "Current minimum: -90.6333\n", + "Iteration No: 111 started. Searching for the next optimal point.\n", + "Iteration No: 111 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2529\n", + "Function value obtained: -75.6998\n", + "Current minimum: -90.6333\n", + "Iteration No: 112 started. Searching for the next optimal point.\n", + "Iteration No: 112 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2940\n", + "Function value obtained: -84.5648\n", + "Current minimum: -90.6333\n", + "Iteration No: 113 started. Searching for the next optimal point.\n", + "Iteration No: 113 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2838\n", + "Function value obtained: -70.1448\n", + "Current minimum: -90.6333\n", + "Iteration No: 114 started. Searching for the next optimal point.\n", + "Iteration No: 114 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4314\n", + "Function value obtained: -86.5986\n", + "Current minimum: -90.6333\n", + "Iteration No: 115 started. Searching for the next optimal point.\n", + "Iteration No: 115 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2736\n", + "Function value obtained: -83.5688\n", + "Current minimum: -90.6333\n", + "Iteration No: 116 started. Searching for the next optimal point.\n", + "Iteration No: 116 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4588\n", + "Function value obtained: -85.3449\n", + "Current minimum: -90.6333\n", + "Iteration No: 117 started. Searching for the next optimal point.\n", + "Iteration No: 117 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3671\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", + "Iteration No: 118 started. Searching for the next optimal point.\n", + "Iteration No: 118 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3850\n", + "Function value obtained: -84.6747\n", + "Current minimum: -90.6333\n", + "Iteration No: 119 started. Searching for the next optimal point.\n", + "Iteration No: 119 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4507\n", + "Function value obtained: -2.0290\n", + "Current minimum: -90.6333\n", + "Iteration No: 120 started. Searching for the next optimal point.\n", + "Iteration No: 120 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3261\n", + "Function value obtained: -84.2602\n", + "Current minimum: -90.6333\n", + "Iteration No: 121 started. Searching for the next optimal point.\n", + "Iteration No: 121 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4539\n", + "Function value obtained: -82.9736\n", + "Current minimum: -90.6333\n", + "Iteration No: 122 started. Searching for the next optimal point.\n", + "Iteration No: 122 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4714\n", + "Function value obtained: -67.7069\n", + "Current minimum: -90.6333\n", + "Iteration No: 123 started. Searching for the next optimal point.\n", + "Iteration No: 123 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3809\n", + "Function value obtained: -80.7035\n", + "Current minimum: -90.6333\n", + "Iteration No: 124 started. Searching for the next optimal point.\n", + "Iteration No: 124 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4970\n", + "Function value obtained: -81.0539\n", + "Current minimum: -90.6333\n", + "Iteration No: 125 started. Searching for the next optimal point.\n", + "Iteration No: 125 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5194\n", + "Function value obtained: -77.8282\n", + "Current minimum: -90.6333\n", + "Iteration No: 126 started. Searching for the next optimal point.\n", + "Iteration No: 126 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5481\n", + "Function value obtained: -85.7514\n", + "Current minimum: -90.6333\n", + "Iteration No: 127 started. Searching for the next optimal point.\n", + "Iteration No: 127 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6020\n", + "Function value obtained: -58.3485\n", + "Current minimum: -90.6333\n", + "Iteration No: 128 started. Searching for the next optimal point.\n", + "Iteration No: 128 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6162\n", + "Function value obtained: -84.7989\n", + "Current minimum: -90.6333\n", + "Iteration No: 129 started. Searching for the next optimal point.\n", + "Iteration No: 129 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6023\n", + "Function value obtained: -83.7495\n", + "Current minimum: -90.6333\n", + "Iteration No: 130 started. Searching for the next optimal point.\n", + "Iteration No: 130 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6529\n", + "Function value obtained: -84.6838\n", + "Current minimum: -90.6333\n", + "Iteration No: 131 started. Searching for the next optimal point.\n", + "Iteration No: 131 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6517\n", + "Function value obtained: -81.3237\n", + "Current minimum: -90.6333\n", + "Iteration No: 132 started. Searching for the next optimal point.\n", + "Iteration No: 132 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5658\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", + "Iteration No: 133 started. Searching for the next optimal point.\n", + "Iteration No: 133 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6196\n", + "Function value obtained: -57.2674\n", + "Current minimum: -90.6333\n", + "Iteration No: 134 started. Searching for the next optimal point.\n", + "Iteration No: 134 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5497\n", + "Function value obtained: -82.8458\n", + "Current minimum: -90.6333\n", + "Iteration No: 135 started. Searching for the next optimal point.\n", + "Iteration No: 135 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7238\n", + "Function value obtained: -80.1184\n", + "Current minimum: -90.6333\n", + "Iteration No: 136 started. Searching for the next optimal point.\n", + "Iteration No: 136 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8476\n", + "Function value obtained: -83.7794\n", + "Current minimum: -90.6333\n", + "Iteration No: 137 started. Searching for the next optimal point.\n", + "Iteration No: 137 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8646\n", + "Function value obtained: -83.6890\n", + "Current minimum: -90.6333\n", + "Iteration No: 138 started. Searching for the next optimal point.\n", + "Iteration No: 138 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6516\n", + "Function value obtained: -11.3171\n", + "Current minimum: -90.6333\n", + "Iteration No: 139 started. Searching for the next optimal point.\n", + "Iteration No: 139 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7437\n", + "Function value obtained: -82.8761\n", + "Current minimum: -90.6333\n", + "Iteration No: 140 started. Searching for the next optimal point.\n", + "Iteration No: 140 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6597\n", + "Function value obtained: -86.4469\n", + "Current minimum: -90.6333\n", + "Iteration No: 141 started. Searching for the next optimal point.\n", + "Iteration No: 141 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7797\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", + "Iteration No: 142 started. Searching for the next optimal point.\n", + "Iteration No: 142 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6914\n", + "Function value obtained: -84.1730\n", + "Current minimum: -90.6333\n", + "Iteration No: 143 started. Searching for the next optimal point.\n", + "Iteration No: 143 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8246\n", + "Function value obtained: -78.3581\n", + "Current minimum: -90.6333\n", + "Iteration No: 144 started. Searching for the next optimal point.\n", + "Iteration No: 144 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8528\n", + "Function value obtained: -86.4290\n", + "Current minimum: -90.6333\n", + "Iteration No: 145 started. Searching for the next optimal point.\n", + "Iteration No: 145 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7967\n", + "Function value obtained: -83.3510\n", + "Current minimum: -90.6333\n", + "Iteration No: 146 started. Searching for the next optimal point.\n", + "Iteration No: 146 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7849\n", + "Function value obtained: -83.6486\n", + "Current minimum: -90.6333\n", + "Iteration No: 147 started. Searching for the next optimal point.\n", + "Iteration No: 147 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8430\n", + "Function value obtained: -55.1289\n", + "Current minimum: -90.6333\n", + "Iteration No: 148 started. Searching for the next optimal point.\n", + "Iteration No: 148 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9347\n", + "Function value obtained: -85.6819\n", + "Current minimum: -90.6333\n", + "Iteration No: 149 started. Searching for the next optimal point.\n", + "Iteration No: 149 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7961\n", + "Function value obtained: -83.8089\n", + "Current minimum: -90.6333\n", + "Iteration No: 150 started. Searching for the next optimal point.\n", + "Iteration No: 150 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8090\n", + "Function value obtained: -83.1695\n", + "Current minimum: -90.6333\n", + "Iteration No: 151 started. Searching for the next optimal point.\n", + "Iteration No: 151 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9021\n", + "Function value obtained: -11.0483\n", + "Current minimum: -90.6333\n", + "Iteration No: 152 started. Searching for the next optimal point.\n", + "Iteration No: 152 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7946\n", + "Function value obtained: -85.6196\n", + "Current minimum: -90.6333\n", + "Iteration No: 153 started. Searching for the next optimal point.\n", + "Iteration No: 153 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9110\n", + "Function value obtained: -83.9758\n", + "Current minimum: -90.6333\n", + "Iteration No: 154 started. Searching for the next optimal point.\n", + "Iteration No: 154 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9064\n", + "Function value obtained: -85.1906\n", + "Current minimum: -90.6333\n", + "Iteration No: 155 started. Searching for the next optimal point.\n", + "Iteration No: 155 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0321\n", + "Function value obtained: -87.8375\n", + "Current minimum: -90.6333\n", + "Iteration No: 156 started. Searching for the next optimal point.\n", + "Iteration No: 156 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8503\n", + "Function value obtained: -85.1706\n", + "Current minimum: -90.6333\n", + "Iteration No: 157 started. Searching for the next optimal point.\n", + "Iteration No: 157 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8713\n", + "Function value obtained: -86.7744\n", + "Current minimum: -90.6333\n", + "Iteration No: 158 started. Searching for the next optimal point.\n", + "Iteration No: 158 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9642\n", + "Function value obtained: -88.2608\n", + "Current minimum: -90.6333\n", + "Iteration No: 159 started. Searching for the next optimal point.\n", + "Iteration No: 159 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9760\n", + "Function value obtained: -85.5418\n", + "Current minimum: -90.6333\n", + "Iteration No: 160 started. Searching for the next optimal point.\n", + "Iteration No: 160 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0818\n", + "Function value obtained: -83.7893\n", + "Current minimum: -90.6333\n", + "Iteration No: 161 started. Searching for the next optimal point.\n", + "Iteration No: 161 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1793\n", + "Function value obtained: -86.5298\n", + "Current minimum: -90.6333\n", + "Iteration No: 162 started. Searching for the next optimal point.\n", + "Iteration No: 162 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0893\n", + "Function value obtained: -85.0591\n", + "Current minimum: -90.6333\n", + "Iteration No: 163 started. Searching for the next optimal point.\n", + "Iteration No: 163 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0569\n", + "Function value obtained: -85.5105\n", + "Current minimum: -90.6333\n", + "Iteration No: 164 started. Searching for the next optimal point.\n", + "Iteration No: 164 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1089\n", + "Function value obtained: -86.4030\n", + "Current minimum: -90.6333\n", + "Iteration No: 165 started. Searching for the next optimal point.\n", + "Iteration No: 165 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1090\n", + "Function value obtained: -85.1444\n", + "Current minimum: -90.6333\n", + "Iteration No: 166 started. Searching for the next optimal point.\n", + "Iteration No: 166 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2387\n", + "Function value obtained: -88.1799\n", + "Current minimum: -90.6333\n", + "Iteration No: 167 started. Searching for the next optimal point.\n", + "Iteration No: 167 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0989\n", + "Function value obtained: -84.9582\n", + "Current minimum: -90.6333\n", + "Iteration No: 168 started. Searching for the next optimal point.\n", + "Iteration No: 168 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1239\n", + "Function value obtained: -89.2391\n", + "Current minimum: -90.6333\n", + "Iteration No: 169 started. Searching for the next optimal point.\n", + "Iteration No: 169 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1619\n", + "Function value obtained: -84.0053\n", + "Current minimum: -90.6333\n", + "Iteration No: 170 started. Searching for the next optimal point.\n", + "Iteration No: 170 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1452\n", + "Function value obtained: -83.0798\n", + "Current minimum: -90.6333\n", + "Iteration No: 171 started. Searching for the next optimal point.\n", + "Iteration No: 171 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2143\n", + "Function value obtained: -88.2145\n", + "Current minimum: -90.6333\n", + "Iteration No: 172 started. Searching for the next optimal point.\n", + "Iteration No: 172 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1834\n", + "Function value obtained: -85.2621\n", + "Current minimum: -90.6333\n", + "Iteration No: 173 started. Searching for the next optimal point.\n", + "Iteration No: 173 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3020\n", + "Function value obtained: -87.8510\n", + "Current minimum: -90.6333\n", + "Iteration No: 174 started. Searching for the next optimal point.\n", + "Iteration No: 174 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2385\n", + "Function value obtained: -88.9162\n", + "Current minimum: -90.6333\n", + "Iteration No: 175 started. Searching for the next optimal point.\n", + "Iteration No: 175 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2649\n", + "Function value obtained: -86.9675\n", + "Current minimum: -90.6333\n", + "Iteration No: 176 started. Searching for the next optimal point.\n", + "Iteration No: 176 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2222\n", + "Function value obtained: -83.9728\n", + "Current minimum: -90.6333\n", + "Iteration No: 177 started. Searching for the next optimal point.\n", + "Iteration No: 177 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2621\n", + "Function value obtained: -87.8963\n", + "Current minimum: -90.6333\n", + "Iteration No: 178 started. Searching for the next optimal point.\n", + "Iteration No: 178 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2759\n", + "Function value obtained: -84.1823\n", + "Current minimum: -90.6333\n", + "Iteration No: 179 started. Searching for the next optimal point.\n", + "Iteration No: 179 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3226\n", + "Function value obtained: -86.6570\n", + "Current minimum: -90.6333\n", + "Iteration No: 180 started. Searching for the next optimal point.\n", + "Iteration No: 180 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3956\n", + "Function value obtained: -88.0181\n", + "Current minimum: -90.6333\n", + "Iteration No: 181 started. Searching for the next optimal point.\n", + "Iteration No: 181 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3426\n", + "Function value obtained: -83.0062\n", + "Current minimum: -90.6333\n", + "Iteration No: 182 started. Searching for the next optimal point.\n", + "Iteration No: 182 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5089\n", + "Function value obtained: -85.3005\n", + "Current minimum: -90.6333\n", + "Iteration No: 183 started. Searching for the next optimal point.\n", + "Iteration No: 183 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3370\n", + "Function value obtained: -83.4699\n", + "Current minimum: -90.6333\n", + "Iteration No: 184 started. Searching for the next optimal point.\n", + "Iteration No: 184 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4299\n", + "Function value obtained: -86.1810\n", + "Current minimum: -90.6333\n", + "Iteration No: 185 started. Searching for the next optimal point.\n", + "Iteration No: 185 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5185\n", + "Function value obtained: -85.4634\n", + "Current minimum: -90.6333\n", + "Iteration No: 186 started. Searching for the next optimal point.\n", + "Iteration No: 186 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5824\n", + "Function value obtained: -84.4536\n", + "Current minimum: -90.6333\n", + "Iteration No: 187 started. Searching for the next optimal point.\n", + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5014\n", + "Function value obtained: -88.0504\n", + "Current minimum: -90.6333\n", + "Iteration No: 188 started. Searching for the next optimal point.\n", + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4922\n", + "Function value obtained: -87.6193\n", + "Current minimum: -90.6333\n", + "Iteration No: 189 started. Searching for the next optimal point.\n", + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6882\n", + "Function value obtained: -87.6822\n", + "Current minimum: -90.6333\n", + "Iteration No: 190 started. Searching for the next optimal point.\n", + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5456\n", + "Function value obtained: -84.8614\n", + "Current minimum: -90.6333\n", + "Iteration No: 191 started. Searching for the next optimal point.\n", + "Iteration No: 191 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5422\n", + "Function value obtained: -87.8404\n", + "Current minimum: -90.6333\n", + "Iteration No: 192 started. Searching for the next optimal point.\n", + "Iteration No: 192 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6575\n", + "Function value obtained: -84.9520\n", + "Current minimum: -90.6333\n", + "Iteration No: 193 started. Searching for the next optimal point.\n", + "Iteration No: 193 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6065\n", + "Function value obtained: -84.7831\n", + "Current minimum: -90.6333\n", + "Iteration No: 194 started. Searching for the next optimal point.\n", + "Iteration No: 194 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7370\n", + "Function value obtained: -84.4722\n", + "Current minimum: -90.6333\n", + "Iteration No: 195 started. Searching for the next optimal point.\n", + "Iteration No: 195 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7130\n", + "Function value obtained: -87.2530\n", + "Current minimum: -90.6333\n", + "Iteration No: 196 started. Searching for the next optimal point.\n", + "Iteration No: 196 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6288\n", + "Function value obtained: -84.8944\n", + "Current minimum: -90.6333\n", + "Iteration No: 197 started. Searching for the next optimal point.\n", + "Iteration No: 197 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7870\n", + "Function value obtained: -87.7330\n", + "Current minimum: -90.6333\n", + "Iteration No: 198 started. Searching for the next optimal point.\n", + "Iteration No: 198 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7568\n", + "Function value obtained: -87.8071\n", + "Current minimum: -90.6333\n", + "Iteration No: 199 started. Searching for the next optimal point.\n", + "Iteration No: 199 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8266\n", + "Function value obtained: -82.9887\n", + "Current minimum: -90.6333\n", + "Iteration No: 200 started. Searching for the next optimal point.\n", + "Iteration No: 200 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8193\n", + "Function value obtained: -85.0844\n", + "Current minimum: -90.6333\n", + "Iteration No: 201 started. Searching for the next optimal point.\n", + "Iteration No: 201 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7509\n", + "Function value obtained: -87.3898\n", + "Current minimum: -90.6333\n", + "Iteration No: 202 started. Searching for the next optimal point.\n", + "Iteration No: 202 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8625\n", + "Function value obtained: -83.5116\n", + "Current minimum: -90.6333\n", + "Iteration No: 203 started. Searching for the next optimal point.\n", + "Iteration No: 203 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8594\n", + "Function value obtained: -84.4034\n", + "Current minimum: -90.6333\n", + "Iteration No: 204 started. Searching for the next optimal point.\n", + "Iteration No: 204 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9295\n", + "Function value obtained: -88.9795\n", + "Current minimum: -90.6333\n", + "Iteration No: 205 started. Searching for the next optimal point.\n", + "Iteration No: 205 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9030\n", + "Function value obtained: -85.8064\n", + "Current minimum: -90.6333\n", + "Iteration No: 206 started. Searching for the next optimal point.\n", + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9488\n", + "Function value obtained: -88.4653\n", + "Current minimum: -90.6333\n", + "Iteration No: 207 started. Searching for the next optimal point.\n", + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8623\n", + "Function value obtained: -86.9521\n", + "Current minimum: -90.6333\n", + "Iteration No: 208 started. Searching for the next optimal point.\n", + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8212\n", + "Function value obtained: -88.2343\n", + "Current minimum: -90.6333\n", + "Iteration No: 209 started. Searching for the next optimal point.\n", + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9604\n", + "Function value obtained: -86.4872\n", + "Current minimum: -90.6333\n", + "Iteration No: 210 started. Searching for the next optimal point.\n", + "Iteration No: 210 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9938\n", + "Function value obtained: -86.5157\n", + "Current minimum: -90.6333\n", + "Iteration No: 211 started. Searching for the next optimal point.\n", + "Iteration No: 211 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8944\n", + "Function value obtained: -87.9709\n", + "Current minimum: -90.6333\n", + "Iteration No: 212 started. Searching for the next optimal point.\n", + "Iteration No: 212 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0389\n", + "Function value obtained: -83.9614\n", + "Current minimum: -90.6333\n", + "Iteration No: 213 started. Searching for the next optimal point.\n", + "Iteration No: 213 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1472\n", + "Function value obtained: -83.4505\n", + "Current minimum: -90.6333\n", + "Iteration No: 214 started. Searching for the next optimal point.\n", + "Iteration No: 214 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1988\n", + "Function value obtained: -88.4951\n", + "Current minimum: -90.6333\n", + "Iteration No: 215 started. Searching for the next optimal point.\n", + "Iteration No: 215 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1860\n", + "Function value obtained: -85.7315\n", + "Current minimum: -90.6333\n", + "Iteration No: 216 started. Searching for the next optimal point.\n", + "Iteration No: 216 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0564\n", + "Function value obtained: -86.7680\n", + "Current minimum: -90.6333\n", + "Iteration No: 217 started. Searching for the next optimal point.\n", + "Iteration No: 217 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2051\n", + "Function value obtained: -86.0125\n", + "Current minimum: -90.6333\n", + "Iteration No: 218 started. Searching for the next optimal point.\n", + "Iteration No: 218 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1440\n", + "Function value obtained: -84.4325\n", + "Current minimum: -90.6333\n", + "Iteration No: 219 started. Searching for the next optimal point.\n", + "Iteration No: 219 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2515\n", + "Function value obtained: -83.7888\n", + "Current minimum: -90.6333\n", + "Iteration No: 220 started. Searching for the next optimal point.\n", + "Iteration No: 220 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1997\n", + "Function value obtained: -85.1757\n", + "Current minimum: -90.6333\n", + "Iteration No: 221 started. Searching for the next optimal point.\n", + "Iteration No: 221 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1929\n", + "Function value obtained: -82.7933\n", + "Current minimum: -90.6333\n", + "Iteration No: 222 started. Searching for the next optimal point.\n", + "Iteration No: 222 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2707\n", + "Function value obtained: -84.3591\n", + "Current minimum: -90.6333\n", + "Iteration No: 223 started. Searching for the next optimal point.\n", + "Iteration No: 223 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2861\n", + "Function value obtained: -84.6210\n", + "Current minimum: -90.6333\n", + "Iteration No: 224 started. Searching for the next optimal point.\n", + "Iteration No: 224 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3462\n", + "Function value obtained: -86.3491\n", + "Current minimum: -90.6333\n", + "Iteration No: 225 started. Searching for the next optimal point.\n", + "Iteration No: 225 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4049\n", + "Function value obtained: -85.1895\n", + "Current minimum: -90.6333\n", + "Iteration No: 226 started. Searching for the next optimal point.\n", + "Iteration No: 226 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3751\n", + "Function value obtained: -84.9130\n", + "Current minimum: -90.6333\n", + "Iteration No: 227 started. Searching for the next optimal point.\n", + "Iteration No: 227 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4479\n", + "Function value obtained: -84.6399\n", + "Current minimum: -90.6333\n", + "Iteration No: 228 started. Searching for the next optimal point.\n", + "Iteration No: 228 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5505\n", + "Function value obtained: -86.8603\n", + "Current minimum: -90.6333\n", + "Iteration No: 229 started. Searching for the next optimal point.\n", + "Iteration No: 229 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6236\n", + "Function value obtained: -84.5484\n", + "Current minimum: -90.6333\n", + "Iteration No: 230 started. Searching for the next optimal point.\n", + "Iteration No: 230 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4163\n", + "Function value obtained: -85.6712\n", + "Current minimum: -90.6333\n", + "Iteration No: 231 started. Searching for the next optimal point.\n", + "Iteration No: 231 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6296\n", + "Function value obtained: -88.0456\n", + "Current minimum: -90.6333\n", + "Iteration No: 232 started. Searching for the next optimal point.\n", + "Iteration No: 232 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4658\n", + "Function value obtained: -87.9592\n", + "Current minimum: -90.6333\n", + "Iteration No: 233 started. Searching for the next optimal point.\n", + "Iteration No: 233 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6268\n", + "Function value obtained: -87.7705\n", + "Current minimum: -90.6333\n", + "Iteration No: 234 started. Searching for the next optimal point.\n", + "Iteration No: 234 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4828\n", + "Function value obtained: -84.6185\n", + "Current minimum: -90.6333\n", + "Iteration No: 235 started. Searching for the next optimal point.\n", + "Iteration No: 235 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6933\n", + "Function value obtained: -83.6364\n", + "Current minimum: -90.6333\n", + "Iteration No: 236 started. Searching for the next optimal point.\n", + "Iteration No: 236 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4868\n", + "Function value obtained: -86.9525\n", + "Current minimum: -90.6333\n", + "Iteration No: 237 started. Searching for the next optimal point.\n", + "Iteration No: 237 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7072\n", + "Function value obtained: -85.5208\n", + "Current minimum: -90.6333\n", + "Iteration No: 238 started. Searching for the next optimal point.\n", + "Iteration No: 238 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6665\n", + "Function value obtained: -84.9699\n", + "Current minimum: -90.6333\n", + "Iteration No: 239 started. Searching for the next optimal point.\n", + "Iteration No: 239 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4370\n", + "Function value obtained: -85.0854\n", + "Current minimum: -90.6333\n", + "Iteration No: 240 started. Searching for the next optimal point.\n", + "Iteration No: 240 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6051\n", + "Function value obtained: -86.2595\n", + "Current minimum: -90.6333\n", + "Iteration No: 241 started. Searching for the next optimal point.\n", + "Iteration No: 241 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6382\n", + "Function value obtained: -86.4817\n", + "Current minimum: -90.6333\n", + "Iteration No: 242 started. Searching for the next optimal point.\n", + "Iteration No: 242 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8350\n", + "Function value obtained: -83.1569\n", + "Current minimum: -90.6333\n", + "Iteration No: 243 started. Searching for the next optimal point.\n", + "Iteration No: 243 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6788\n", + "Function value obtained: -86.6800\n", + "Current minimum: -90.6333\n", + "Iteration No: 244 started. Searching for the next optimal point.\n", + "Iteration No: 244 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7233\n", + "Function value obtained: -85.5632\n", + "Current minimum: -90.6333\n", + "Iteration No: 245 started. Searching for the next optimal point.\n", + "Iteration No: 245 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7751\n", + "Function value obtained: -85.7283\n", + "Current minimum: -90.6333\n", + "Iteration No: 246 started. Searching for the next optimal point.\n", + "Iteration No: 246 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7752\n", + "Function value obtained: -85.8422\n", + "Current minimum: -90.6333\n", + "Iteration No: 247 started. Searching for the next optimal point.\n", + "Iteration No: 247 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7446\n", + "Function value obtained: -87.3973\n", + "Current minimum: -90.6333\n", + "Iteration No: 248 started. Searching for the next optimal point.\n", + "Iteration No: 248 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8226\n", + "Function value obtained: -86.2009\n", + "Current minimum: -90.6333\n", + "Iteration No: 249 started. Searching for the next optimal point.\n", + "Iteration No: 249 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2632\n", + "Function value obtained: -86.0677\n", + "Current minimum: -90.6333\n", + "Iteration No: 250 started. Searching for the next optimal point.\n", + "Iteration No: 250 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1870\n", + "Function value obtained: -85.0422\n", + "Current minimum: -90.6333\n", + "Iteration No: 251 started. Searching for the next optimal point.\n", + "Iteration No: 251 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0518\n", + "Function value obtained: -86.9540\n", + "Current minimum: -90.6333\n", + "Iteration No: 252 started. Searching for the next optimal point.\n", + "Iteration No: 252 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0203\n", + "Function value obtained: -83.2860\n", + "Current minimum: -90.6333\n", + "Iteration No: 253 started. Searching for the next optimal point.\n", + "Iteration No: 253 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0728\n", + "Function value obtained: -86.5753\n", + "Current minimum: -90.6333\n", + "Iteration No: 254 started. Searching for the next optimal point.\n", + "Iteration No: 254 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0231\n", + "Function value obtained: -87.2729\n", + "Current minimum: -90.6333\n", + "Iteration No: 255 started. Searching for the next optimal point.\n", + "Iteration No: 255 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1772\n", + "Function value obtained: -84.3028\n", + "Current minimum: -90.6333\n", + "Iteration No: 256 started. Searching for the next optimal point.\n", + "Iteration No: 256 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1883\n", + "Function value obtained: -84.6384\n", + "Current minimum: -90.6333\n", + "Iteration No: 257 started. Searching for the next optimal point.\n", + "Iteration No: 257 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2135\n", + "Function value obtained: -84.3169\n", + "Current minimum: -90.6333\n", + "Iteration No: 258 started. Searching for the next optimal point.\n", + "Iteration No: 258 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0527\n", + "Function value obtained: -85.2478\n", + "Current minimum: -90.6333\n", + "Iteration No: 259 started. Searching for the next optimal point.\n", + "Iteration No: 259 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1900\n", + "Function value obtained: -86.1178\n", + "Current minimum: -90.6333\n", + "Iteration No: 260 started. Searching for the next optimal point.\n", + "Iteration No: 260 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3379\n", + "Function value obtained: -86.5867\n", + "Current minimum: -90.6333\n", + "Iteration No: 261 started. Searching for the next optimal point.\n", + "Iteration No: 261 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3295\n", + "Function value obtained: -84.9588\n", + "Current minimum: -90.6333\n", + "Iteration No: 262 started. Searching for the next optimal point.\n", + "Iteration No: 262 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2179\n", + "Function value obtained: -86.0880\n", + "Current minimum: -90.6333\n", + "Iteration No: 263 started. Searching for the next optimal point.\n", + "Iteration No: 263 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2905\n", + "Function value obtained: -86.5985\n", + "Current minimum: -90.6333\n", + "Iteration No: 264 started. Searching for the next optimal point.\n", + "Iteration No: 264 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2963\n", + "Function value obtained: -84.9976\n", + "Current minimum: -90.6333\n", + "Iteration No: 265 started. Searching for the next optimal point.\n", + "Iteration No: 265 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3160\n", + "Function value obtained: -86.9113\n", + "Current minimum: -90.6333\n", + "Iteration No: 266 started. Searching for the next optimal point.\n", + "Iteration No: 266 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3405\n", + "Function value obtained: -86.0184\n", + "Current minimum: -90.6333\n", + "Iteration No: 267 started. Searching for the next optimal point.\n", + "Iteration No: 267 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3936\n", + "Function value obtained: -83.4898\n", + "Current minimum: -90.6333\n", + "Iteration No: 268 started. Searching for the next optimal point.\n", + "Iteration No: 268 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5504\n", + "Function value obtained: -87.5537\n", + "Current minimum: -90.6333\n", + "Iteration No: 269 started. Searching for the next optimal point.\n", + "Iteration No: 269 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5918\n", + "Function value obtained: -86.3580\n", + "Current minimum: -90.6333\n", + "Iteration No: 270 started. Searching for the next optimal point.\n", + "Iteration No: 270 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6319\n", + "Function value obtained: -86.8754\n", + "Current minimum: -90.6333\n", + "Iteration No: 271 started. Searching for the next optimal point.\n", + "Iteration No: 271 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6179\n", + "Function value obtained: -87.3622\n", + "Current minimum: -90.6333\n", + "Iteration No: 272 started. Searching for the next optimal point.\n", + "Iteration No: 272 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5324\n", + "Function value obtained: -87.1565\n", + "Current minimum: -90.6333\n", + "Iteration No: 273 started. Searching for the next optimal point.\n", + "Iteration No: 273 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5720\n", + "Function value obtained: -89.2305\n", + "Current minimum: -90.6333\n", + "Iteration No: 274 started. Searching for the next optimal point.\n", + "Iteration No: 274 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8214\n", + "Function value obtained: -86.7361\n", + "Current minimum: -90.6333\n", + "Iteration No: 275 started. Searching for the next optimal point.\n", + "Iteration No: 275 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7659\n", + "Function value obtained: -84.9475\n", + "Current minimum: -90.6333\n", + "Iteration No: 276 started. Searching for the next optimal point.\n", + "Iteration No: 276 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8156\n", + "Function value obtained: -85.5211\n", + "Current minimum: -90.6333\n", + "Iteration No: 277 started. Searching for the next optimal point.\n", + "Iteration No: 277 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7959\n", + "Function value obtained: -84.9771\n", + "Current minimum: -90.6333\n", + "Iteration No: 278 started. Searching for the next optimal point.\n", + "Iteration No: 278 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5755\n", + "Function value obtained: -88.0128\n", + "Current minimum: -90.6333\n", + "Iteration No: 279 started. Searching for the next optimal point.\n", + "Iteration No: 279 ended. Search finished for the next optimal point.\n", + "Time taken: 6.0321\n", + "Function value obtained: -85.9124\n", + "Current minimum: -90.6333\n", + "Iteration No: 280 started. Searching for the next optimal point.\n", + "Iteration No: 280 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8723\n", + "Function value obtained: -85.1234\n", + "Current minimum: -90.6333\n", + "Iteration No: 281 started. Searching for the next optimal point.\n", + "Iteration No: 281 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9973\n", + "Function value obtained: -84.9108\n", + "Current minimum: -90.6333\n", + "Iteration No: 282 started. Searching for the next optimal point.\n", + "Iteration No: 282 ended. Search finished for the next optimal point.\n", + "Time taken: 6.0118\n", + "Function value obtained: -87.5869\n", + "Current minimum: -90.6333\n", + "Iteration No: 283 started. Searching for the next optimal point.\n", + "Iteration No: 283 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1184\n", + "Function value obtained: -87.8984\n", + "Current minimum: -90.6333\n", + "Iteration No: 284 started. Searching for the next optimal point.\n", + "Iteration No: 284 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9292\n", + "Function value obtained: -84.3207\n", + "Current minimum: -90.6333\n", + "Iteration No: 285 started. Searching for the next optimal point.\n", + "Iteration No: 285 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1385\n", + "Function value obtained: -87.6335\n", + "Current minimum: -90.6333\n", + "Iteration No: 286 started. Searching for the next optimal point.\n", + "Iteration No: 286 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1387\n", + "Function value obtained: -86.9994\n", + "Current minimum: -90.6333\n", + "Iteration No: 287 started. Searching for the next optimal point.\n", + "Iteration No: 287 ended. Search finished for the next optimal point.\n", + "Time taken: 6.3565\n", + "Function value obtained: -85.1528\n", + "Current minimum: -90.6333\n", + "Iteration No: 288 started. Searching for the next optimal point.\n", + "Iteration No: 288 ended. Search finished for the next optimal point.\n", + "Time taken: 6.0750\n", + "Function value obtained: -84.0035\n", + "Current minimum: -90.6333\n", + "Iteration No: 289 started. Searching for the next optimal point.\n", + "Iteration No: 289 ended. Search finished for the next optimal point.\n", + "Time taken: 6.5232\n", + "Function value obtained: -85.4554\n", + "Current minimum: -90.6333\n", + "Iteration No: 290 started. Searching for the next optimal point.\n", + "Iteration No: 290 ended. Search finished for the next optimal point.\n", + "Time taken: 6.4644\n", + "Function value obtained: -87.0136\n", + "Current minimum: -90.6333\n", + "Iteration No: 291 started. Searching for the next optimal point.\n", + "Iteration No: 291 ended. Search finished for the next optimal point.\n", + "Time taken: 6.4834\n", + "Function value obtained: -84.7633\n", + "Current minimum: -90.6333\n", + "Iteration No: 292 started. Searching for the next optimal point.\n", + "Iteration No: 292 ended. Search finished for the next optimal point.\n", + "Time taken: 6.4423\n", + "Function value obtained: -85.8865\n", + "Current minimum: -90.6333\n", + "Iteration No: 293 started. Searching for the next optimal point.\n", + "Iteration No: 293 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1903\n", + "Function value obtained: -88.6420\n", + "Current minimum: -90.6333\n", + "Iteration No: 294 started. Searching for the next optimal point.\n", + "Iteration No: 294 ended. Search finished for the next optimal point.\n", + "Time taken: 6.4984\n", + "Function value obtained: -87.5296\n", + "Current minimum: -90.6333\n", + "Iteration No: 295 started. Searching for the next optimal point.\n", + "Iteration No: 295 ended. Search finished for the next optimal point.\n", + "Time taken: 6.5800\n", + "Function value obtained: -84.3343\n", + "Current minimum: -90.6333\n", + "Iteration No: 296 started. Searching for the next optimal point.\n", + "Iteration No: 296 ended. Search finished for the next optimal point.\n", + "Time taken: 6.4310\n", + "Function value obtained: -84.2970\n", + "Current minimum: -90.6333\n", + "Iteration No: 297 started. Searching for the next optimal point.\n", + "Iteration No: 297 ended. Search finished for the next optimal point.\n", + "Time taken: 6.6753\n", + "Function value obtained: -83.7032\n", + "Current minimum: -90.6333\n", + "Iteration No: 298 started. Searching for the next optimal point.\n", + "Iteration No: 298 ended. Search finished for the next optimal point.\n", + "Time taken: 6.5152\n", + "Function value obtained: -85.6559\n", + "Current minimum: -90.6333\n", + "Iteration No: 299 started. Searching for the next optimal point.\n", + "Iteration No: 299 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1695\n", + "Function value obtained: -86.4604\n", + "Current minimum: -90.6333\n", + "Iteration No: 300 started. Searching for the next optimal point.\n", + "Iteration No: 300 ended. Search finished for the next optimal point.\n", + "Time taken: 6.6265\n", + "Function value obtained: -83.0904\n", + "Current minimum: -90.6333\n", + "CPU times: user 2h 52min 17s, sys: 1h 11min 30s, total: 4h 3min 48s\n", + "Wall time: 16min 21s\n" ] }, { "data": { "text/plain": [ - "(-89.20981597465533,\n", - " [-1.7637732817759972, 0.7853961999069485, 0.29606695833461205])" + "(-90.63333622820284,\n", + " [-1.7521564679093693, 0.5440615729465406, 0.29119675741251316])" ] }, - "execution_count": 97, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 100, verbose=True, n_jobs=-1)\n", + "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 300, verbose=True, n_jobs=-1)\n", "cr_gp.fun, cr_gp.x" ] }, { "cell_type": "code", - "execution_count": 98, - "id": "faa3ef2e-e477-401d-b663-3e10e15d2023", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 98, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_convergence(cr_gp)" - ] - }, - { - "cell_type": "code", - "execution_count": 100, - "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", - "metadata": { - "scrolled": true - }, + "execution_count": 12, + "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, "outputs": [ { "name": "stdout", @@ -2253,592 +7986,1526 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 0.8555\n", - "Function value obtained: -82.0494\n", - "Current minimum: -82.0494\n", + "Time taken: 1.3671\n", + "Function value obtained: -80.5640\n", + "Current minimum: -80.5640\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 0.8180\n", - "Function value obtained: -27.8807\n", - "Current minimum: -82.0494\n", + "Time taken: 1.3095\n", + "Function value obtained: -0.0000\n", + "Current minimum: -80.5640\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 0.8761\n", - "Function value obtained: -20.9274\n", - "Current minimum: -82.0494\n", + "Time taken: 1.2839\n", + "Function value obtained: -39.9405\n", + "Current minimum: -80.5640\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 0.8165\n", - "Function value obtained: -83.8672\n", - "Current minimum: -83.8672\n", + "Time taken: 1.2410\n", + "Function value obtained: -1.9526\n", + "Current minimum: -80.5640\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 0.8392\n", - "Function value obtained: -58.3317\n", - "Current minimum: -83.8672\n", + "Time taken: 1.2487\n", + "Function value obtained: -42.9769\n", + "Current minimum: -80.5640\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 0.8122\n", - "Function value obtained: -75.1273\n", - "Current minimum: -83.8672\n", + "Time taken: 1.3445\n", + "Function value obtained: -22.6509\n", + "Current minimum: -80.5640\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 0.8032\n", - "Function value obtained: -29.1520\n", - "Current minimum: -83.8672\n", + "Time taken: 1.2643\n", + "Function value obtained: -33.6349\n", + "Current minimum: -80.5640\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 0.8224\n", - "Function value obtained: -75.0358\n", - "Current minimum: -83.8672\n", + "Time taken: 1.2897\n", + "Function value obtained: -15.0069\n", + "Current minimum: -80.5640\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 0.7970\n", - "Function value obtained: -0.0000\n", - "Current minimum: -83.8672\n", + "Time taken: 1.3150\n", + "Function value obtained: -64.6252\n", + "Current minimum: -80.5640\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.0994\n", - "Function value obtained: -2.3324\n", - "Current minimum: -83.8672\n", + "Time taken: 1.5217\n", + "Function value obtained: -3.4288\n", + "Current minimum: -80.5640\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1198\n", - "Function value obtained: -82.1685\n", - "Current minimum: -83.8672\n", + "Time taken: 1.5133\n", + "Function value obtained: -68.5431\n", + "Current minimum: -80.5640\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1385\n", - "Function value obtained: -68.2328\n", - "Current minimum: -83.8672\n", + "Time taken: 1.4744\n", + "Function value obtained: -85.3241\n", + "Current minimum: -85.3241\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0531\n", - "Function value obtained: -87.7303\n", - "Current minimum: -87.7303\n", + "Time taken: 1.4270\n", + "Function value obtained: -84.1832\n", + "Current minimum: -85.3241\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1378\n", - "Function value obtained: -80.4829\n", - "Current minimum: -87.7303\n", + "Time taken: 1.4482\n", + "Function value obtained: -81.6088\n", + "Current minimum: -85.3241\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1361\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5109\n", + "Function value obtained: -44.6087\n", + "Current minimum: -85.3241\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1869\n", - "Function value obtained: -85.6731\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5100\n", + "Function value obtained: -86.5479\n", + "Current minimum: -86.5479\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1151\n", - "Function value obtained: -68.5814\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6467\n", + "Function value obtained: -75.7266\n", + "Current minimum: -86.5479\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2229\n", - "Function value obtained: -84.3523\n", - "Current minimum: -87.7303\n", + "Time taken: 1.3240\n", + "Function value obtained: -81.4121\n", + "Current minimum: -86.5479\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1939\n", - "Function value obtained: -84.5253\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6180\n", + "Function value obtained: -69.6542\n", + "Current minimum: -86.5479\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1486\n", - "Function value obtained: -79.8591\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6148\n", + "Function value obtained: -86.6761\n", + "Current minimum: -86.6761\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1457\n", - "Function value obtained: -84.3700\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5092\n", + "Function value obtained: -86.3296\n", + "Current minimum: -86.6761\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1551\n", - "Function value obtained: -84.1606\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5560\n", + "Function value obtained: -85.7819\n", + "Current minimum: -86.6761\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1697\n", - "Function value obtained: -76.5916\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5364\n", + "Function value obtained: -84.3509\n", + "Current minimum: -86.6761\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1482\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5240\n", + "Function value obtained: -83.4330\n", + "Current minimum: -86.6761\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0297\n", - "Function value obtained: -62.5643\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5617\n", + "Function value obtained: -83.7592\n", + "Current minimum: -86.6761\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0952\n", - "Function value obtained: -80.1087\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5114\n", + "Function value obtained: -83.9225\n", + "Current minimum: -86.6761\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0540\n", - "Function value obtained: -79.2209\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5328\n", + "Function value obtained: -0.0000\n", + "Current minimum: -86.6761\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1351\n", - "Function value obtained: -76.4538\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6206\n", + "Function value obtained: -81.6106\n", + "Current minimum: -86.6761\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1745\n", - "Function value obtained: -84.9686\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5505\n", + "Function value obtained: -84.2248\n", + "Current minimum: -86.6761\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0644\n", - "Function value obtained: -73.2859\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5881\n", + "Function value obtained: -86.4688\n", + "Current minimum: -86.6761\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4059\n", - "Function value obtained: -83.9607\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6746\n", + "Function value obtained: -82.6019\n", + "Current minimum: -86.6761\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1826\n", - "Function value obtained: -82.2966\n", - "Current minimum: -87.7303\n", + "Time taken: 1.4213\n", + "Function value obtained: -87.1654\n", + "Current minimum: -87.1654\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0995\n", - "Function value obtained: -49.7182\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5361\n", + "Function value obtained: -84.6632\n", + "Current minimum: -87.1654\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1138\n", - "Function value obtained: -87.0738\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5604\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1654\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0403\n", - "Function value obtained: -84.9800\n", - "Current minimum: -87.7303\n", + "Time taken: 1.4963\n", + "Function value obtained: -47.3826\n", + "Current minimum: -87.1654\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1664\n", - "Function value obtained: -82.1302\n", - "Current minimum: -87.7303\n", + "Time taken: 1.4632\n", + "Function value obtained: -84.7640\n", + "Current minimum: -87.1654\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0682\n", - "Function value obtained: -2.0276\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6056\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1654\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2282\n", - "Function value obtained: -84.5040\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5335\n", + "Function value obtained: -78.1384\n", + "Current minimum: -87.1654\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1662\n", - "Function value obtained: -78.4776\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6209\n", + "Function value obtained: -82.6793\n", + "Current minimum: -87.1654\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1560\n", - "Function value obtained: -64.3111\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5587\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1654\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.0951\n", - "Function value obtained: -80.9890\n", - "Current minimum: -87.7303\n", + "Time taken: 1.4955\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1654\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1764\n", - "Function value obtained: -84.7831\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5314\n", + "Function value obtained: -79.9439\n", + "Current minimum: -87.1654\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2259\n", - "Function value obtained: -86.9937\n", - "Current minimum: -87.7303\n", + "Time taken: 1.5843\n", + "Function value obtained: -84.4630\n", + "Current minimum: -87.1654\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2247\n", - "Function value obtained: -82.5205\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6787\n", + "Function value obtained: -80.1143\n", + "Current minimum: -87.1654\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1729\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6241\n", + "Function value obtained: -76.6670\n", + "Current minimum: -87.1654\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1083\n", - "Function value obtained: -85.2571\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6217\n", + "Function value obtained: -82.3647\n", + "Current minimum: -87.1654\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2374\n", - "Function value obtained: -81.2485\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6778\n", + "Function value obtained: -82.8928\n", + "Current minimum: -87.1654\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2915\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6505\n", + "Function value obtained: -85.2244\n", + "Current minimum: -87.1654\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2097\n", - "Function value obtained: -85.7873\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6423\n", + "Function value obtained: -82.5976\n", + "Current minimum: -87.1654\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2805\n", - "Function value obtained: -81.6781\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6409\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1654\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2983\n", - "Function value obtained: -82.7063\n", - "Current minimum: -87.7303\n", + "Time taken: 1.6560\n", + "Function value obtained: -85.3694\n", + "Current minimum: -87.1654\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3231\n", - "Function value obtained: -83.9367\n", - "Current minimum: -87.7303\n", + "Time taken: 1.7153\n", + "Function value obtained: -85.7065\n", + "Current minimum: -87.1654\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3488\n", - "Function value obtained: -79.2575\n", - "Current minimum: -87.7303\n", + "Time taken: 1.7139\n", + "Function value obtained: -83.6194\n", + "Current minimum: -87.1654\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3788\n", - "Function value obtained: -85.5246\n", - "Current minimum: -87.7303\n", + "Time taken: 1.9258\n", + "Function value obtained: -84.4336\n", + "Current minimum: -87.1654\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2843\n", - "Function value obtained: -89.1864\n", - "Current minimum: -89.1864\n", + "Time taken: 1.7036\n", + "Function value obtained: -84.7038\n", + "Current minimum: -87.1654\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3775\n", - "Function value obtained: -75.4612\n", - "Current minimum: -89.1864\n", + "Time taken: 1.6683\n", + "Function value obtained: -84.0647\n", + "Current minimum: -87.1654\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1820\n", - "Function value obtained: -80.8734\n", - "Current minimum: -89.1864\n", + "Time taken: 1.8355\n", + "Function value obtained: -84.7367\n", + "Current minimum: -87.1654\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2727\n", - "Function value obtained: -87.1315\n", - "Current minimum: -89.1864\n", + "Time taken: 1.7087\n", + "Function value obtained: -0.0000\n", + "Current minimum: -87.1654\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3786\n", - "Function value obtained: -48.6218\n", - "Current minimum: -89.1864\n", + "Time taken: 1.8020\n", + "Function value obtained: -86.6965\n", + "Current minimum: -87.1654\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2821\n", - "Function value obtained: -84.0148\n", - "Current minimum: -89.1864\n", + "Time taken: 1.7731\n", + "Function value obtained: -83.7168\n", + "Current minimum: -87.1654\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2556\n", - "Function value obtained: -89.5829\n", - "Current minimum: -89.5829\n", + "Time taken: 1.7801\n", + "Function value obtained: -84.0911\n", + "Current minimum: -87.1654\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2678\n", - "Function value obtained: -85.6779\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8769\n", + "Function value obtained: -52.1267\n", + "Current minimum: -87.1654\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3682\n", - "Function value obtained: -89.0580\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8854\n", + "Function value obtained: -85.0718\n", + "Current minimum: -87.1654\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3095\n", - "Function value obtained: -86.1623\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8315\n", + "Function value obtained: -66.6768\n", + "Current minimum: -87.1654\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4135\n", - "Function value obtained: -83.1700\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8824\n", + "Function value obtained: -83.1847\n", + "Current minimum: -87.1654\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3607\n", - "Function value obtained: -87.2959\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8042\n", + "Function value obtained: -85.7831\n", + "Current minimum: -87.1654\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4241\n", - "Function value obtained: -86.2028\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8875\n", + "Function value obtained: -84.8040\n", + "Current minimum: -87.1654\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4970\n", - "Function value obtained: -89.1065\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8361\n", + "Function value obtained: -86.0435\n", + "Current minimum: -87.1654\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4113\n", - "Function value obtained: -85.5268\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9100\n", + "Function value obtained: -87.5948\n", + "Current minimum: -87.5948\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4445\n", - "Function value obtained: -82.6634\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0052\n", + "Function value obtained: -87.3832\n", + "Current minimum: -87.5948\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3563\n", - "Function value obtained: -82.7298\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9399\n", + "Function value obtained: -87.6509\n", + "Current minimum: -87.6509\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4265\n", - "Function value obtained: -86.5039\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8762\n", + "Function value obtained: -89.4458\n", + "Current minimum: -89.4458\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5006\n", - "Function value obtained: -80.6437\n", - "Current minimum: -89.5829\n", + "Time taken: 1.8609\n", + "Function value obtained: -84.4458\n", + "Current minimum: -89.4458\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4145\n", - "Function value obtained: -81.7166\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9677\n", + "Function value obtained: -76.8716\n", + "Current minimum: -89.4458\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7114\n", - "Function value obtained: -80.1674\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0256\n", + "Function value obtained: -76.2327\n", + "Current minimum: -89.4458\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5242\n", - "Function value obtained: -32.1797\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9435\n", + "Function value obtained: -70.5779\n", + "Current minimum: -89.4458\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5228\n", - "Function value obtained: -2.7370\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0506\n", + "Function value obtained: -85.7938\n", + "Current minimum: -89.4458\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5110\n", - "Function value obtained: -70.8688\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0131\n", + "Function value obtained: -2.3382\n", + "Current minimum: -89.4458\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5334\n", - "Function value obtained: -76.3349\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0270\n", + "Function value obtained: -83.8244\n", + "Current minimum: -89.4458\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5702\n", - "Function value obtained: -88.7394\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9941\n", + "Function value obtained: -64.2494\n", + "Current minimum: -89.4458\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6312\n", - "Function value obtained: -88.2038\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0532\n", + "Function value obtained: -79.9634\n", + "Current minimum: -89.4458\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5903\n", - "Function value obtained: -81.7246\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9294\n", + "Function value obtained: -65.3227\n", + "Current minimum: -89.4458\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5821\n", - "Function value obtained: -86.1727\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0383\n", + "Function value obtained: -88.5685\n", + "Current minimum: -89.4458\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5880\n", - "Function value obtained: -0.0000\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0428\n", + "Function value obtained: -84.7590\n", + "Current minimum: -89.4458\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6344\n", - "Function value obtained: -82.8846\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9657\n", + "Function value obtained: -78.7142\n", + "Current minimum: -89.4458\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6308\n", - "Function value obtained: -80.8315\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9812\n", + "Function value obtained: -86.3107\n", + "Current minimum: -89.4458\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6460\n", - "Function value obtained: -84.9013\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0941\n", + "Function value obtained: -40.1945\n", + "Current minimum: -89.4458\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5901\n", - "Function value obtained: -77.6854\n", - "Current minimum: -89.5829\n", + "Time taken: 1.9600\n", + "Function value obtained: -0.0000\n", + "Current minimum: -89.4458\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7287\n", - "Function value obtained: -78.7553\n", - "Current minimum: -89.5829\n", + "Time taken: 2.1713\n", + "Function value obtained: -27.2993\n", + "Current minimum: -89.4458\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6824\n", - "Function value obtained: -2.2109\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0064\n", + "Function value obtained: -81.6215\n", + "Current minimum: -89.4458\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7875\n", - "Function value obtained: -88.9535\n", - "Current minimum: -89.5829\n", + "Time taken: 2.0520\n", + "Function value obtained: -85.5144\n", + "Current minimum: -89.4458\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7372\n", - "Function value obtained: -85.3073\n", - "Current minimum: -89.5829\n", + "Time taken: 2.1437\n", + "Function value obtained: -68.1607\n", + "Current minimum: -89.4458\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6662\n", - "Function value obtained: -84.7486\n", - "Current minimum: -89.5829\n", + "Time taken: 2.1091\n", + "Function value obtained: -81.8875\n", + "Current minimum: -89.4458\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6876\n", - "Function value obtained: -87.9872\n", - "Current minimum: -89.5829\n", + "Time taken: 2.1652\n", + "Function value obtained: -85.0252\n", + "Current minimum: -89.4458\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7000\n", - "Function value obtained: -87.0723\n", - "Current minimum: -89.5829\n", + "Time taken: 2.1792\n", + "Function value obtained: -38.1945\n", + "Current minimum: -89.4458\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7661\n", - "Function value obtained: -85.2508\n", - "Current minimum: -89.5829\n", + "Time taken: 2.2576\n", + "Function value obtained: -86.5831\n", + "Current minimum: -89.4458\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8248\n", - "Function value obtained: -86.0122\n", - "Current minimum: -89.5829\n", + "Time taken: 2.2714\n", + "Function value obtained: -84.7071\n", + "Current minimum: -89.4458\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8281\n", - "Function value obtained: -84.9965\n", - "Current minimum: -89.5829\n", + "Time taken: 2.3242\n", + "Function value obtained: -82.0435\n", + "Current minimum: -89.4458\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8010\n", - "Function value obtained: -90.3341\n", - "Current minimum: -90.3341\n", + "Time taken: 2.2444\n", + "Function value obtained: -82.6330\n", + "Current minimum: -89.4458\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8328\n", + "Time taken: 2.2243\n", + "Function value obtained: -82.1444\n", + "Current minimum: -89.4458\n", + "Iteration No: 101 started. Searching for the next optimal point.\n", + "Iteration No: 101 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3079\n", + "Function value obtained: -3.8924\n", + "Current minimum: -89.4458\n", + "Iteration No: 102 started. Searching for the next optimal point.\n", + "Iteration No: 102 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2421\n", + "Function value obtained: -84.3560\n", + "Current minimum: -89.4458\n", + "Iteration No: 103 started. Searching for the next optimal point.\n", + "Iteration No: 103 ended. Search finished for the next optimal point.\n", + "Time taken: 2.2009\n", + "Function value obtained: -74.0913\n", + "Current minimum: -89.4458\n", + "Iteration No: 104 started. Searching for the next optimal point.\n", + "Iteration No: 104 ended. Search finished for the next optimal point.\n", + "Time taken: 2.1615\n", + "Function value obtained: -84.7180\n", + "Current minimum: -89.4458\n", + "Iteration No: 105 started. Searching for the next optimal point.\n", + "Iteration No: 105 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3078\n", + "Function value obtained: -74.5602\n", + "Current minimum: -89.4458\n", + "Iteration No: 106 started. Searching for the next optimal point.\n", + "Iteration No: 106 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3045\n", + "Function value obtained: -86.8558\n", + "Current minimum: -89.4458\n", + "Iteration No: 107 started. Searching for the next optimal point.\n", + "Iteration No: 107 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3949\n", + "Function value obtained: -84.7131\n", + "Current minimum: -89.4458\n", + "Iteration No: 108 started. Searching for the next optimal point.\n", + "Iteration No: 108 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3058\n", + "Function value obtained: -84.8969\n", + "Current minimum: -89.4458\n", + "Iteration No: 109 started. Searching for the next optimal point.\n", + "Iteration No: 109 ended. Search finished for the next optimal point.\n", + "Time taken: 2.3854\n", + "Function value obtained: -90.1080\n", + "Current minimum: -90.1080\n", + "Iteration No: 110 started. Searching for the next optimal point.\n", + "Iteration No: 110 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4104\n", + "Function value obtained: -83.7669\n", + "Current minimum: -90.1080\n", + "Iteration No: 111 started. Searching for the next optimal point.\n", + "Iteration No: 111 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4869\n", + "Function value obtained: -2.6536\n", + "Current minimum: -90.1080\n", + "Iteration No: 112 started. Searching for the next optimal point.\n", + "Iteration No: 112 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4273\n", + "Function value obtained: -77.3157\n", + "Current minimum: -90.1080\n", + "Iteration No: 113 started. Searching for the next optimal point.\n", + "Iteration No: 113 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4460\n", + "Function value obtained: -85.7271\n", + "Current minimum: -90.1080\n", + "Iteration No: 114 started. Searching for the next optimal point.\n", + "Iteration No: 114 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4237\n", + "Function value obtained: -87.5493\n", + "Current minimum: -90.1080\n", + "Iteration No: 115 started. Searching for the next optimal point.\n", + "Iteration No: 115 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4666\n", + "Function value obtained: -84.2363\n", + "Current minimum: -90.1080\n", + "Iteration No: 116 started. Searching for the next optimal point.\n", + "Iteration No: 116 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4197\n", + "Function value obtained: -75.9327\n", + "Current minimum: -90.1080\n", + "Iteration No: 117 started. Searching for the next optimal point.\n", + "Iteration No: 117 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4655\n", + "Function value obtained: -74.7333\n", + "Current minimum: -90.1080\n", + "Iteration No: 118 started. Searching for the next optimal point.\n", + "Iteration No: 118 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4448\n", + "Function value obtained: -85.6777\n", + "Current minimum: -90.1080\n", + "Iteration No: 119 started. Searching for the next optimal point.\n", + "Iteration No: 119 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4911\n", + "Function value obtained: -85.8749\n", + "Current minimum: -90.1080\n", + "Iteration No: 120 started. Searching for the next optimal point.\n", + "Iteration No: 120 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5112\n", + "Function value obtained: -84.6669\n", + "Current minimum: -90.1080\n", + "Iteration No: 121 started. Searching for the next optimal point.\n", + "Iteration No: 121 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6462\n", + "Function value obtained: -82.2886\n", + "Current minimum: -90.1080\n", + "Iteration No: 122 started. Searching for the next optimal point.\n", + "Iteration No: 122 ended. Search finished for the next optimal point.\n", + "Time taken: 2.4867\n", + "Function value obtained: -82.3150\n", + "Current minimum: -90.1080\n", + "Iteration No: 123 started. Searching for the next optimal point.\n", + "Iteration No: 123 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7028\n", + "Function value obtained: -83.6574\n", + "Current minimum: -90.1080\n", + "Iteration No: 124 started. Searching for the next optimal point.\n", + "Iteration No: 124 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6137\n", + "Function value obtained: -78.4962\n", + "Current minimum: -90.1080\n", + "Iteration No: 125 started. Searching for the next optimal point.\n", + "Iteration No: 125 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5376\n", "Function value obtained: -0.0000\n", - "Current minimum: -90.3341\n", - "CPU times: user 5min 42s, sys: 33min 45s, total: 39min 28s\n", - "Wall time: 2min 10s\n" + "Current minimum: -90.1080\n", + "Iteration No: 126 started. Searching for the next optimal point.\n", + "Iteration No: 126 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6664\n", + "Function value obtained: -2.3239\n", + "Current minimum: -90.1080\n", + "Iteration No: 127 started. Searching for the next optimal point.\n", + "Iteration No: 127 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5561\n", + "Function value obtained: -84.3863\n", + "Current minimum: -90.1080\n", + "Iteration No: 128 started. Searching for the next optimal point.\n", + "Iteration No: 128 ended. Search finished for the next optimal point.\n", + "Time taken: 2.5864\n", + "Function value obtained: -89.2723\n", + "Current minimum: -90.1080\n", + "Iteration No: 129 started. Searching for the next optimal point.\n", + "Iteration No: 129 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6874\n", + "Function value obtained: -85.7395\n", + "Current minimum: -90.1080\n", + "Iteration No: 130 started. Searching for the next optimal point.\n", + "Iteration No: 130 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6609\n", + "Function value obtained: -81.2216\n", + "Current minimum: -90.1080\n", + "Iteration No: 131 started. Searching for the next optimal point.\n", + "Iteration No: 131 ended. Search finished for the next optimal point.\n", + "Time taken: 2.6842\n", + "Function value obtained: -85.3949\n", + "Current minimum: -90.1080\n", + "Iteration No: 132 started. Searching for the next optimal point.\n", + "Iteration No: 132 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8074\n", + "Function value obtained: -83.9053\n", + "Current minimum: -90.1080\n", + "Iteration No: 133 started. Searching for the next optimal point.\n", + "Iteration No: 133 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7910\n", + "Function value obtained: -86.5381\n", + "Current minimum: -90.1080\n", + "Iteration No: 134 started. Searching for the next optimal point.\n", + "Iteration No: 134 ended. Search finished for the next optimal point.\n", + "Time taken: 2.7673\n", + "Function value obtained: -38.0584\n", + "Current minimum: -90.1080\n", + "Iteration No: 135 started. Searching for the next optimal point.\n", + "Iteration No: 135 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8259\n", + "Function value obtained: -19.5556\n", + "Current minimum: -90.1080\n", + "Iteration No: 136 started. Searching for the next optimal point.\n", + "Iteration No: 136 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8044\n", + "Function value obtained: -88.0263\n", + "Current minimum: -90.1080\n", + "Iteration No: 137 started. Searching for the next optimal point.\n", + "Iteration No: 137 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8218\n", + "Function value obtained: -83.8556\n", + "Current minimum: -90.1080\n", + "Iteration No: 138 started. Searching for the next optimal point.\n", + "Iteration No: 138 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9458\n", + "Function value obtained: -84.9582\n", + "Current minimum: -90.1080\n", + "Iteration No: 139 started. Searching for the next optimal point.\n", + "Iteration No: 139 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8685\n", + "Function value obtained: -71.6207\n", + "Current minimum: -90.1080\n", + "Iteration No: 140 started. Searching for the next optimal point.\n", + "Iteration No: 140 ended. Search finished for the next optimal point.\n", + "Time taken: 2.8345\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.1080\n", + "Iteration No: 141 started. Searching for the next optimal point.\n", + "Iteration No: 141 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9433\n", + "Function value obtained: -79.3504\n", + "Current minimum: -90.1080\n", + "Iteration No: 142 started. Searching for the next optimal point.\n", + "Iteration No: 142 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1014\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.1080\n", + "Iteration No: 143 started. Searching for the next optimal point.\n", + "Iteration No: 143 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9258\n", + "Function value obtained: -78.2937\n", + "Current minimum: -90.1080\n", + "Iteration No: 144 started. Searching for the next optimal point.\n", + "Iteration No: 144 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9821\n", + "Function value obtained: -79.0707\n", + "Current minimum: -90.1080\n", + "Iteration No: 145 started. Searching for the next optimal point.\n", + "Iteration No: 145 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0360\n", + "Function value obtained: -75.7946\n", + "Current minimum: -90.1080\n", + "Iteration No: 146 started. Searching for the next optimal point.\n", + "Iteration No: 146 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0021\n", + "Function value obtained: -32.5327\n", + "Current minimum: -90.1080\n", + "Iteration No: 147 started. Searching for the next optimal point.\n", + "Iteration No: 147 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9289\n", + "Function value obtained: -75.6591\n", + "Current minimum: -90.1080\n", + "Iteration No: 148 started. Searching for the next optimal point.\n", + "Iteration No: 148 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9720\n", + "Function value obtained: -79.7543\n", + "Current minimum: -90.1080\n", + "Iteration No: 149 started. Searching for the next optimal point.\n", + "Iteration No: 149 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0303\n", + "Function value obtained: -14.1465\n", + "Current minimum: -90.1080\n", + "Iteration No: 150 started. Searching for the next optimal point.\n", + "Iteration No: 150 ended. Search finished for the next optimal point.\n", + "Time taken: 2.9655\n", + "Function value obtained: -86.5903\n", + "Current minimum: -90.1080\n", + "Iteration No: 151 started. Searching for the next optimal point.\n", + "Iteration No: 151 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0833\n", + "Function value obtained: -2.2684\n", + "Current minimum: -90.1080\n", + "Iteration No: 152 started. Searching for the next optimal point.\n", + "Iteration No: 152 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0779\n", + "Function value obtained: -84.7120\n", + "Current minimum: -90.1080\n", + "Iteration No: 153 started. Searching for the next optimal point.\n", + "Iteration No: 153 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0388\n", + "Function value obtained: -86.9601\n", + "Current minimum: -90.1080\n", + "Iteration No: 154 started. Searching for the next optimal point.\n", + "Iteration No: 154 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0481\n", + "Function value obtained: -86.2894\n", + "Current minimum: -90.1080\n", + "Iteration No: 155 started. Searching for the next optimal point.\n", + "Iteration No: 155 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0682\n", + "Function value obtained: -84.2894\n", + "Current minimum: -90.1080\n", + "Iteration No: 156 started. Searching for the next optimal point.\n", + "Iteration No: 156 ended. Search finished for the next optimal point.\n", + "Time taken: 3.0720\n", + "Function value obtained: -86.1454\n", + "Current minimum: -90.1080\n", + "Iteration No: 157 started. Searching for the next optimal point.\n", + "Iteration No: 157 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1283\n", + "Function value obtained: -85.5008\n", + "Current minimum: -90.1080\n", + "Iteration No: 158 started. Searching for the next optimal point.\n", + "Iteration No: 158 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2131\n", + "Function value obtained: -83.7913\n", + "Current minimum: -90.1080\n", + "Iteration No: 159 started. Searching for the next optimal point.\n", + "Iteration No: 159 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1915\n", + "Function value obtained: -88.2591\n", + "Current minimum: -90.1080\n", + "Iteration No: 160 started. Searching for the next optimal point.\n", + "Iteration No: 160 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2995\n", + "Function value obtained: -88.1398\n", + "Current minimum: -90.1080\n", + "Iteration No: 161 started. Searching for the next optimal point.\n", + "Iteration No: 161 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2863\n", + "Function value obtained: -84.1293\n", + "Current minimum: -90.1080\n", + "Iteration No: 162 started. Searching for the next optimal point.\n", + "Iteration No: 162 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3000\n", + "Function value obtained: -82.8841\n", + "Current minimum: -90.1080\n", + "Iteration No: 163 started. Searching for the next optimal point.\n", + "Iteration No: 163 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2327\n", + "Function value obtained: -86.7044\n", + "Current minimum: -90.1080\n", + "Iteration No: 164 started. Searching for the next optimal point.\n", + "Iteration No: 164 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2941\n", + "Function value obtained: -83.2319\n", + "Current minimum: -90.1080\n", + "Iteration No: 165 started. Searching for the next optimal point.\n", + "Iteration No: 165 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2975\n", + "Function value obtained: -84.8725\n", + "Current minimum: -90.1080\n", + "Iteration No: 166 started. Searching for the next optimal point.\n", + "Iteration No: 166 ended. Search finished for the next optimal point.\n", + "Time taken: 3.1967\n", + "Function value obtained: -85.3258\n", + "Current minimum: -90.1080\n", + "Iteration No: 167 started. Searching for the next optimal point.\n", + "Iteration No: 167 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3404\n", + "Function value obtained: -83.5805\n", + "Current minimum: -90.1080\n", + "Iteration No: 168 started. Searching for the next optimal point.\n", + "Iteration No: 168 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2737\n", + "Function value obtained: -85.8725\n", + "Current minimum: -90.1080\n", + "Iteration No: 169 started. Searching for the next optimal point.\n", + "Iteration No: 169 ended. Search finished for the next optimal point.\n", + "Time taken: 3.2683\n", + "Function value obtained: -83.0707\n", + "Current minimum: -90.1080\n", + "Iteration No: 170 started. Searching for the next optimal point.\n", + "Iteration No: 170 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5759\n", + "Function value obtained: -86.8456\n", + "Current minimum: -90.1080\n", + "Iteration No: 171 started. Searching for the next optimal point.\n", + "Iteration No: 171 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4243\n", + "Function value obtained: -84.7315\n", + "Current minimum: -90.1080\n", + "Iteration No: 172 started. Searching for the next optimal point.\n", + "Iteration No: 172 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5115\n", + "Function value obtained: -84.6169\n", + "Current minimum: -90.1080\n", + "Iteration No: 173 started. Searching for the next optimal point.\n", + "Iteration No: 173 ended. Search finished for the next optimal point.\n", + "Time taken: 3.3010\n", + "Function value obtained: -81.6789\n", + "Current minimum: -90.1080\n", + "Iteration No: 174 started. Searching for the next optimal point.\n", + "Iteration No: 174 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5282\n", + "Function value obtained: -86.4641\n", + "Current minimum: -90.1080\n", + "Iteration No: 175 started. Searching for the next optimal point.\n", + "Iteration No: 175 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5046\n", + "Function value obtained: -87.2174\n", + "Current minimum: -90.1080\n", + "Iteration No: 176 started. Searching for the next optimal point.\n", + "Iteration No: 176 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4834\n", + "Function value obtained: -85.3013\n", + "Current minimum: -90.1080\n", + "Iteration No: 177 started. Searching for the next optimal point.\n", + "Iteration No: 177 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4234\n", + "Function value obtained: -85.1900\n", + "Current minimum: -90.1080\n", + "Iteration No: 178 started. Searching for the next optimal point.\n", + "Iteration No: 178 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5353\n", + "Function value obtained: -87.0985\n", + "Current minimum: -90.1080\n", + "Iteration No: 179 started. Searching for the next optimal point.\n", + "Iteration No: 179 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5676\n", + "Function value obtained: -88.9232\n", + "Current minimum: -90.1080\n", + "Iteration No: 180 started. Searching for the next optimal point.\n", + "Iteration No: 180 ended. Search finished for the next optimal point.\n", + "Time taken: 3.4110\n", + "Function value obtained: -84.1636\n", + "Current minimum: -90.1080\n", + "Iteration No: 181 started. Searching for the next optimal point.\n", + "Iteration No: 181 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6401\n", + "Function value obtained: -86.0473\n", + "Current minimum: -90.1080\n", + "Iteration No: 182 started. Searching for the next optimal point.\n", + "Iteration No: 182 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6908\n", + "Function value obtained: -84.9941\n", + "Current minimum: -90.1080\n", + "Iteration No: 183 started. Searching for the next optimal point.\n", + "Iteration No: 183 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6404\n", + "Function value obtained: -87.2634\n", + "Current minimum: -90.1080\n", + "Iteration No: 184 started. Searching for the next optimal point.\n", + "Iteration No: 184 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6747\n", + "Function value obtained: -86.1677\n", + "Current minimum: -90.1080\n", + "Iteration No: 185 started. Searching for the next optimal point.\n", + "Iteration No: 185 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5355\n", + "Function value obtained: -84.4485\n", + "Current minimum: -90.1080\n", + "Iteration No: 186 started. Searching for the next optimal point.\n", + "Iteration No: 186 ended. Search finished for the next optimal point.\n", + "Time taken: 3.5761\n", + "Function value obtained: -88.1312\n", + "Current minimum: -90.1080\n", + "Iteration No: 187 started. Searching for the next optimal point.\n", + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7427\n", + "Function value obtained: -87.8741\n", + "Current minimum: -90.1080\n", + "Iteration No: 188 started. Searching for the next optimal point.\n", + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 3.6982\n", + "Function value obtained: -85.0937\n", + "Current minimum: -90.1080\n", + "Iteration No: 189 started. Searching for the next optimal point.\n", + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8059\n", + "Function value obtained: -84.7989\n", + "Current minimum: -90.1080\n", + "Iteration No: 190 started. Searching for the next optimal point.\n", + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7532\n", + "Function value obtained: -84.9776\n", + "Current minimum: -90.1080\n", + "Iteration No: 191 started. Searching for the next optimal point.\n", + "Iteration No: 191 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7327\n", + "Function value obtained: -86.2600\n", + "Current minimum: -90.1080\n", + "Iteration No: 192 started. Searching for the next optimal point.\n", + "Iteration No: 192 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7536\n", + "Function value obtained: -82.7375\n", + "Current minimum: -90.1080\n", + "Iteration No: 193 started. Searching for the next optimal point.\n", + "Iteration No: 193 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7799\n", + "Function value obtained: -85.9629\n", + "Current minimum: -90.1080\n", + "Iteration No: 194 started. Searching for the next optimal point.\n", + "Iteration No: 194 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8153\n", + "Function value obtained: -85.5385\n", + "Current minimum: -90.1080\n", + "Iteration No: 195 started. Searching for the next optimal point.\n", + "Iteration No: 195 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8953\n", + "Function value obtained: -85.5226\n", + "Current minimum: -90.1080\n", + "Iteration No: 196 started. Searching for the next optimal point.\n", + "Iteration No: 196 ended. Search finished for the next optimal point.\n", + "Time taken: 3.8898\n", + "Function value obtained: -87.3023\n", + "Current minimum: -90.1080\n", + "Iteration No: 197 started. Searching for the next optimal point.\n", + "Iteration No: 197 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0235\n", + "Function value obtained: -84.0948\n", + "Current minimum: -90.1080\n", + "Iteration No: 198 started. Searching for the next optimal point.\n", + "Iteration No: 198 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7757\n", + "Function value obtained: -84.4794\n", + "Current minimum: -90.1080\n", + "Iteration No: 199 started. Searching for the next optimal point.\n", + "Iteration No: 199 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9343\n", + "Function value obtained: -86.1294\n", + "Current minimum: -90.1080\n", + "Iteration No: 200 started. Searching for the next optimal point.\n", + "Iteration No: 200 ended. Search finished for the next optimal point.\n", + "Time taken: 3.7612\n", + "Function value obtained: -84.8679\n", + "Current minimum: -90.1080\n", + "Iteration No: 201 started. Searching for the next optimal point.\n", + "Iteration No: 201 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0248\n", + "Function value obtained: -85.9920\n", + "Current minimum: -90.1080\n", + "Iteration No: 202 started. Searching for the next optimal point.\n", + "Iteration No: 202 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9046\n", + "Function value obtained: -87.3819\n", + "Current minimum: -90.1080\n", + "Iteration No: 203 started. Searching for the next optimal point.\n", + "Iteration No: 203 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0862\n", + "Function value obtained: -85.9375\n", + "Current minimum: -90.1080\n", + "Iteration No: 204 started. Searching for the next optimal point.\n", + "Iteration No: 204 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0536\n", + "Function value obtained: -83.4752\n", + "Current minimum: -90.1080\n", + "Iteration No: 205 started. Searching for the next optimal point.\n", + "Iteration No: 205 ended. Search finished for the next optimal point.\n", + "Time taken: 3.9329\n", + "Function value obtained: -82.0837\n", + "Current minimum: -90.1080\n", + "Iteration No: 206 started. Searching for the next optimal point.\n", + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1069\n", + "Function value obtained: -87.3389\n", + "Current minimum: -90.1080\n", + "Iteration No: 207 started. Searching for the next optimal point.\n", + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1476\n", + "Function value obtained: -83.5029\n", + "Current minimum: -90.1080\n", + "Iteration No: 208 started. Searching for the next optimal point.\n", + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1855\n", + "Function value obtained: -84.9128\n", + "Current minimum: -90.1080\n", + "Iteration No: 209 started. Searching for the next optimal point.\n", + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2695\n", + "Function value obtained: -82.9639\n", + "Current minimum: -90.1080\n", + "Iteration No: 210 started. Searching for the next optimal point.\n", + "Iteration No: 210 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2752\n", + "Function value obtained: -86.7421\n", + "Current minimum: -90.1080\n", + "Iteration No: 211 started. Searching for the next optimal point.\n", + "Iteration No: 211 ended. Search finished for the next optimal point.\n", + "Time taken: 4.1732\n", + "Function value obtained: -86.2449\n", + "Current minimum: -90.1080\n", + "Iteration No: 212 started. Searching for the next optimal point.\n", + "Iteration No: 212 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0882\n", + "Function value obtained: -88.0485\n", + "Current minimum: -90.1080\n", + "Iteration No: 213 started. Searching for the next optimal point.\n", + "Iteration No: 213 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3446\n", + "Function value obtained: -84.6975\n", + "Current minimum: -90.1080\n", + "Iteration No: 214 started. Searching for the next optimal point.\n", + "Iteration No: 214 ended. Search finished for the next optimal point.\n", + "Time taken: 4.0993\n", + "Function value obtained: -85.7307\n", + "Current minimum: -90.1080\n", + "Iteration No: 215 started. Searching for the next optimal point.\n", + "Iteration No: 215 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4278\n", + "Function value obtained: -89.1376\n", + "Current minimum: -90.1080\n", + "Iteration No: 216 started. Searching for the next optimal point.\n", + "Iteration No: 216 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3091\n", + "Function value obtained: -85.4064\n", + "Current minimum: -90.1080\n", + "Iteration No: 217 started. Searching for the next optimal point.\n", + "Iteration No: 217 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2130\n", + "Function value obtained: -85.2976\n", + "Current minimum: -90.1080\n", + "Iteration No: 218 started. Searching for the next optimal point.\n", + "Iteration No: 218 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4033\n", + "Function value obtained: -83.8911\n", + "Current minimum: -90.1080\n", + "Iteration No: 219 started. Searching for the next optimal point.\n", + "Iteration No: 219 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4745\n", + "Function value obtained: -82.3104\n", + "Current minimum: -90.1080\n", + "Iteration No: 220 started. Searching for the next optimal point.\n", + "Iteration No: 220 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5903\n", + "Function value obtained: -84.6281\n", + "Current minimum: -90.1080\n", + "Iteration No: 221 started. Searching for the next optimal point.\n", + "Iteration No: 221 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6327\n", + "Function value obtained: -86.7352\n", + "Current minimum: -90.1080\n", + "Iteration No: 222 started. Searching for the next optimal point.\n", + "Iteration No: 222 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5987\n", + "Function value obtained: -86.7216\n", + "Current minimum: -90.1080\n", + "Iteration No: 223 started. Searching for the next optimal point.\n", + "Iteration No: 223 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6257\n", + "Function value obtained: -85.3067\n", + "Current minimum: -90.1080\n", + "Iteration No: 224 started. Searching for the next optimal point.\n", + "Iteration No: 224 ended. Search finished for the next optimal point.\n", + "Time taken: 4.4578\n", + "Function value obtained: -83.1120\n", + "Current minimum: -90.1080\n", + "Iteration No: 225 started. Searching for the next optimal point.\n", + "Iteration No: 225 ended. Search finished for the next optimal point.\n", + "Time taken: 4.2785\n", + "Function value obtained: -87.8344\n", + "Current minimum: -90.1080\n", + "Iteration No: 226 started. Searching for the next optimal point.\n", + "Iteration No: 226 ended. Search finished for the next optimal point.\n", + "Time taken: 4.3754\n", + "Function value obtained: -85.6313\n", + "Current minimum: -90.1080\n", + "Iteration No: 227 started. Searching for the next optimal point.\n", + "Iteration No: 227 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6938\n", + "Function value obtained: -85.1359\n", + "Current minimum: -90.1080\n", + "Iteration No: 228 started. Searching for the next optimal point.\n", + "Iteration No: 228 ended. Search finished for the next optimal point.\n", + "Time taken: 4.6287\n", + "Function value obtained: -86.7383\n", + "Current minimum: -90.1080\n", + "Iteration No: 229 started. Searching for the next optimal point.\n", + "Iteration No: 229 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9528\n", + "Function value obtained: -86.4916\n", + "Current minimum: -90.1080\n", + "Iteration No: 230 started. Searching for the next optimal point.\n", + "Iteration No: 230 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7442\n", + "Function value obtained: -85.4737\n", + "Current minimum: -90.1080\n", + "Iteration No: 231 started. Searching for the next optimal point.\n", + "Iteration No: 231 ended. Search finished for the next optimal point.\n", + "Time taken: 4.5900\n", + "Function value obtained: -86.8351\n", + "Current minimum: -90.1080\n", + "Iteration No: 232 started. Searching for the next optimal point.\n", + "Iteration No: 232 ended. Search finished for the next optimal point.\n", + "Time taken: 4.7186\n", + "Function value obtained: -84.9945\n", + "Current minimum: -90.1080\n", + "Iteration No: 233 started. Searching for the next optimal point.\n", + "Iteration No: 233 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8898\n", + "Function value obtained: -86.3841\n", + "Current minimum: -90.1080\n", + "Iteration No: 234 started. Searching for the next optimal point.\n", + "Iteration No: 234 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8121\n", + "Function value obtained: -86.3058\n", + "Current minimum: -90.1080\n", + "Iteration No: 235 started. Searching for the next optimal point.\n", + "Iteration No: 235 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0193\n", + "Function value obtained: -84.2218\n", + "Current minimum: -90.1080\n", + "Iteration No: 236 started. Searching for the next optimal point.\n", + "Iteration No: 236 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9367\n", + "Function value obtained: -85.0513\n", + "Current minimum: -90.1080\n", + "Iteration No: 237 started. Searching for the next optimal point.\n", + "Iteration No: 237 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9656\n", + "Function value obtained: -87.7383\n", + "Current minimum: -90.1080\n", + "Iteration No: 238 started. Searching for the next optimal point.\n", + "Iteration No: 238 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9926\n", + "Function value obtained: -83.9105\n", + "Current minimum: -90.1080\n", + "Iteration No: 239 started. Searching for the next optimal point.\n", + "Iteration No: 239 ended. Search finished for the next optimal point.\n", + "Time taken: 4.8596\n", + "Function value obtained: -86.8565\n", + "Current minimum: -90.1080\n", + "Iteration No: 240 started. Searching for the next optimal point.\n", + "Iteration No: 240 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0548\n", + "Function value obtained: -85.1051\n", + "Current minimum: -90.1080\n", + "Iteration No: 241 started. Searching for the next optimal point.\n", + "Iteration No: 241 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0941\n", + "Function value obtained: -87.4271\n", + "Current minimum: -90.1080\n", + "Iteration No: 242 started. Searching for the next optimal point.\n", + "Iteration No: 242 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0175\n", + "Function value obtained: -85.0004\n", + "Current minimum: -90.1080\n", + "Iteration No: 243 started. Searching for the next optimal point.\n", + "Iteration No: 243 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0794\n", + "Function value obtained: -88.7432\n", + "Current minimum: -90.1080\n", + "Iteration No: 244 started. Searching for the next optimal point.\n", + "Iteration No: 244 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0018\n", + "Function value obtained: -87.7293\n", + "Current minimum: -90.1080\n", + "Iteration No: 245 started. Searching for the next optimal point.\n", + "Iteration No: 245 ended. Search finished for the next optimal point.\n", + "Time taken: 4.9117\n", + "Function value obtained: -86.6354\n", + "Current minimum: -90.1080\n", + "Iteration No: 246 started. Searching for the next optimal point.\n", + "Iteration No: 246 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1099\n", + "Function value obtained: -83.7823\n", + "Current minimum: -90.1080\n", + "Iteration No: 247 started. Searching for the next optimal point.\n", + "Iteration No: 247 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2423\n", + "Function value obtained: -87.3029\n", + "Current minimum: -90.1080\n", + "Iteration No: 248 started. Searching for the next optimal point.\n", + "Iteration No: 248 ended. Search finished for the next optimal point.\n", + "Time taken: 5.3016\n", + "Function value obtained: -84.9609\n", + "Current minimum: -90.1080\n", + "Iteration No: 249 started. Searching for the next optimal point.\n", + "Iteration No: 249 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2164\n", + "Function value obtained: -83.7024\n", + "Current minimum: -90.1080\n", + "Iteration No: 250 started. Searching for the next optimal point.\n", + "Iteration No: 250 ended. Search finished for the next optimal point.\n", + "Time taken: 5.0462\n", + "Function value obtained: -85.2059\n", + "Current minimum: -90.1080\n", + "Iteration No: 251 started. Searching for the next optimal point.\n", + "Iteration No: 251 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4431\n", + "Function value obtained: -85.5742\n", + "Current minimum: -90.1080\n", + "Iteration No: 252 started. Searching for the next optimal point.\n", + "Iteration No: 252 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1714\n", + "Function value obtained: -88.2958\n", + "Current minimum: -90.1080\n", + "Iteration No: 253 started. Searching for the next optimal point.\n", + "Iteration No: 253 ended. Search finished for the next optimal point.\n", + "Time taken: 5.1338\n", + "Function value obtained: -86.4350\n", + "Current minimum: -90.1080\n", + "Iteration No: 254 started. Searching for the next optimal point.\n", + "Iteration No: 254 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5651\n", + "Function value obtained: -87.6224\n", + "Current minimum: -90.1080\n", + "Iteration No: 255 started. Searching for the next optimal point.\n", + "Iteration No: 255 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4916\n", + "Function value obtained: -84.6867\n", + "Current minimum: -90.1080\n", + "Iteration No: 256 started. Searching for the next optimal point.\n", + "Iteration No: 256 ended. Search finished for the next optimal point.\n", + "Time taken: 5.2136\n", + "Function value obtained: -85.6839\n", + "Current minimum: -90.1080\n", + "Iteration No: 257 started. Searching for the next optimal point.\n", + "Iteration No: 257 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4824\n", + "Function value obtained: -88.2674\n", + "Current minimum: -90.1080\n", + "Iteration No: 258 started. Searching for the next optimal point.\n", + "Iteration No: 258 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5053\n", + "Function value obtained: -85.4622\n", + "Current minimum: -90.1080\n", + "Iteration No: 259 started. Searching for the next optimal point.\n", + "Iteration No: 259 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6444\n", + "Function value obtained: -85.1772\n", + "Current minimum: -90.1080\n", + "Iteration No: 260 started. Searching for the next optimal point.\n", + "Iteration No: 260 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4896\n", + "Function value obtained: -85.1338\n", + "Current minimum: -90.1080\n", + "Iteration No: 261 started. Searching for the next optimal point.\n", + "Iteration No: 261 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8690\n", + "Function value obtained: -85.7315\n", + "Current minimum: -90.1080\n", + "Iteration No: 262 started. Searching for the next optimal point.\n", + "Iteration No: 262 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4967\n", + "Function value obtained: -85.2266\n", + "Current minimum: -90.1080\n", + "Iteration No: 263 started. Searching for the next optimal point.\n", + "Iteration No: 263 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8225\n", + "Function value obtained: -85.2482\n", + "Current minimum: -90.1080\n", + "Iteration No: 264 started. Searching for the next optimal point.\n", + "Iteration No: 264 ended. Search finished for the next optimal point.\n", + "Time taken: 5.4418\n", + "Function value obtained: -85.4218\n", + "Current minimum: -90.1080\n", + "Iteration No: 265 started. Searching for the next optimal point.\n", + "Iteration No: 265 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7841\n", + "Function value obtained: -87.3934\n", + "Current minimum: -90.1080\n", + "Iteration No: 266 started. Searching for the next optimal point.\n", + "Iteration No: 266 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5509\n", + "Function value obtained: -86.6733\n", + "Current minimum: -90.1080\n", + "Iteration No: 267 started. Searching for the next optimal point.\n", + "Iteration No: 267 ended. Search finished for the next optimal point.\n", + "Time taken: 5.7302\n", + "Function value obtained: -86.7916\n", + "Current minimum: -90.1080\n", + "Iteration No: 268 started. Searching for the next optimal point.\n", + "Iteration No: 268 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6647\n", + "Function value obtained: -85.9177\n", + "Current minimum: -90.1080\n", + "Iteration No: 269 started. Searching for the next optimal point.\n", + "Iteration No: 269 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8071\n", + "Function value obtained: -85.0347\n", + "Current minimum: -90.1080\n", + "Iteration No: 270 started. Searching for the next optimal point.\n", + "Iteration No: 270 ended. Search finished for the next optimal point.\n", + "Time taken: 5.5069\n", + "Function value obtained: -87.4387\n", + "Current minimum: -90.1080\n", + "Iteration No: 271 started. Searching for the next optimal point.\n", + "Iteration No: 271 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6538\n", + "Function value obtained: -81.9073\n", + "Current minimum: -90.1080\n", + "Iteration No: 272 started. Searching for the next optimal point.\n", + "Iteration No: 272 ended. Search finished for the next optimal point.\n", + "Time taken: 5.6946\n", + "Function value obtained: -86.6597\n", + "Current minimum: -90.1080\n", + "Iteration No: 273 started. Searching for the next optimal point.\n", + "Iteration No: 273 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9044\n", + "Function value obtained: -85.9946\n", + "Current minimum: -90.1080\n", + "Iteration No: 274 started. Searching for the next optimal point.\n", + "Iteration No: 274 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9727\n", + "Function value obtained: -85.4345\n", + "Current minimum: -90.1080\n", + "Iteration No: 275 started. Searching for the next optimal point.\n", + "Iteration No: 275 ended. Search finished for the next optimal point.\n", + "Time taken: 6.6902\n", + "Function value obtained: -89.4217\n", + "Current minimum: -90.1080\n", + "Iteration No: 276 started. Searching for the next optimal point.\n", + "Iteration No: 276 ended. Search finished for the next optimal point.\n", + "Time taken: 6.2746\n", + "Function value obtained: -88.7301\n", + "Current minimum: -90.1080\n", + "Iteration No: 277 started. Searching for the next optimal point.\n", + "Iteration No: 277 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1494\n", + "Function value obtained: -85.3028\n", + "Current minimum: -90.1080\n", + "Iteration No: 278 started. Searching for the next optimal point.\n", + "Iteration No: 278 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9163\n", + "Function value obtained: -88.7193\n", + "Current minimum: -90.1080\n", + "Iteration No: 279 started. Searching for the next optimal point.\n", + "Iteration No: 279 ended. Search finished for the next optimal point.\n", + "Time taken: 5.9043\n", + "Function value obtained: -85.9005\n", + "Current minimum: -90.1080\n", + "Iteration No: 280 started. Searching for the next optimal point.\n", + "Iteration No: 280 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1046\n", + "Function value obtained: -88.5985\n", + "Current minimum: -90.1080\n", + "Iteration No: 281 started. Searching for the next optimal point.\n", + "Iteration No: 281 ended. Search finished for the next optimal point.\n", + "Time taken: 5.8468\n", + "Function value obtained: -87.1297\n", + "Current minimum: -90.1080\n", + "Iteration No: 282 started. Searching for the next optimal point.\n", + "Iteration No: 282 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1069\n", + "Function value obtained: -88.3291\n", + "Current minimum: -90.1080\n", + "Iteration No: 283 started. Searching for the next optimal point.\n", + "Iteration No: 283 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1237\n", + "Function value obtained: -86.3832\n", + "Current minimum: -90.1080\n", + "Iteration No: 284 started. Searching for the next optimal point.\n", + "Iteration No: 284 ended. Search finished for the next optimal point.\n", + "Time taken: 6.0980\n", + "Function value obtained: -85.8780\n", + "Current minimum: -90.1080\n", + "Iteration No: 285 started. Searching for the next optimal point.\n", + "Iteration No: 285 ended. Search finished for the next optimal point.\n", + "Time taken: 6.3353\n", + "Function value obtained: -85.0982\n", + "Current minimum: -90.1080\n", + "Iteration No: 286 started. Searching for the next optimal point.\n", + "Iteration No: 286 ended. Search finished for the next optimal point.\n", + "Time taken: 6.2966\n", + "Function value obtained: -85.5723\n", + "Current minimum: -90.1080\n", + "Iteration No: 287 started. Searching for the next optimal point.\n", + "Iteration No: 287 ended. Search finished for the next optimal point.\n", + "Time taken: 6.3444\n", + "Function value obtained: -87.1795\n", + "Current minimum: -90.1080\n", + "Iteration No: 288 started. Searching for the next optimal point.\n", + "Iteration No: 288 ended. Search finished for the next optimal point.\n", + "Time taken: 6.1063\n", + "Function value obtained: -83.4052\n", + "Current minimum: -90.1080\n", + "Iteration No: 289 started. Searching for the next optimal point.\n", + "Iteration No: 289 ended. Search finished for the next optimal point.\n", + "Time taken: 6.3829\n", + "Function value obtained: -86.3743\n", + "Current minimum: -90.1080\n", + "Iteration No: 290 started. Searching for the next optimal point.\n", + "Iteration No: 290 ended. Search finished for the next optimal point.\n", + "Time taken: 6.0629\n", + "Function value obtained: -84.3291\n", + "Current minimum: -90.1080\n", + "Iteration No: 291 started. Searching for the next optimal point.\n", + "Iteration No: 291 ended. Search finished for the next optimal point.\n", + "Time taken: 6.2690\n", + "Function value obtained: -87.2789\n", + "Current minimum: -90.1080\n", + "Iteration No: 292 started. Searching for the next optimal point.\n", + "Iteration No: 292 ended. Search finished for the next optimal point.\n", + "Time taken: 6.4390\n", + "Function value obtained: -83.5484\n", + "Current minimum: -90.1080\n", + "Iteration No: 293 started. Searching for the next optimal point.\n", + "Iteration No: 293 ended. Search finished for the next optimal point.\n", + "Time taken: 6.6583\n", + "Function value obtained: -86.7345\n", + "Current minimum: -90.1080\n", + "Iteration No: 294 started. Searching for the next optimal point.\n", + "Iteration No: 294 ended. Search finished for the next optimal point.\n", + "Time taken: 6.3726\n", + "Function value obtained: -85.4131\n", + "Current minimum: -90.1080\n", + "Iteration No: 295 started. Searching for the next optimal point.\n", + "Iteration No: 295 ended. Search finished for the next optimal point.\n", + "Time taken: 6.2427\n", + "Function value obtained: -85.6367\n", + "Current minimum: -90.1080\n", + "Iteration No: 296 started. Searching for the next optimal point.\n", + "Iteration No: 296 ended. Search finished for the next optimal point.\n", + "Time taken: 6.5675\n", + "Function value obtained: -85.2891\n", + "Current minimum: -90.1080\n", + "Iteration No: 297 started. Searching for the next optimal point.\n", + "Iteration No: 297 ended. Search finished for the next optimal point.\n", + "Time taken: 6.6454\n", + "Function value obtained: -85.0394\n", + "Current minimum: -90.1080\n", + "Iteration No: 298 started. Searching for the next optimal point.\n", + "Iteration No: 298 ended. Search finished for the next optimal point.\n", + "Time taken: 6.3081\n", + "Function value obtained: -86.2236\n", + "Current minimum: -90.1080\n", + "Iteration No: 299 started. Searching for the next optimal point.\n", + "Iteration No: 299 ended. Search finished for the next optimal point.\n", + "Time taken: 6.6895\n", + "Function value obtained: -84.9832\n", + "Current minimum: -90.1080\n", + "Iteration No: 300 started. Searching for the next optimal point.\n", + "Iteration No: 300 ended. Search finished for the next optimal point.\n", + "Time taken: 6.6400\n", + "Function value obtained: -88.0309\n", + "Current minimum: -90.1080\n", + "CPU times: user 3h 29min 43s, sys: 1h 10min 51s, total: 4h 40min 34s\n", + "Wall time: 16min 46s\n" ] }, { "data": { "text/plain": [ - "(-90.33409885861906,\n", - " [-1.7507018612191905, 0.7853961999069485, 0.23877043334814907])" + "(-90.10801912597402,\n", + " [-1.5802360403803877, 0.3781959292149372, 0.3293809377265017])" ] }, - "execution_count": 100, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gbrt = gp_minimize(cr_obj, cr_space, n_calls = 100, verbose=True, n_jobs=-1)\n", + "cr_gbrt = gp_minimize(cr_obj, cr_space, n_calls = 300, verbose=True, n_jobs=-1)\n", "cr_gbrt.fun, cr_gbrt.x" ] }, - { - "cell_type": "code", - "execution_count": 101, - "id": "dffeed5a-f975-4a6b-b91c-1d91e6c45140", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 101, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_convergence(cr_gbrt)" - ] - }, { "cell_type": "markdown", "id": "2c5e685e-7117-4b21-a7a5-3c975fe3acf8", @@ -2849,46 +9516,59 @@ }, { "cell_type": "code", - "execution_count": 103, + "execution_count": 106, "id": "6a61d3fa-97a9-4274-945c-be2742d1e956", "metadata": {}, "outputs": [], "source": [ - "def get_policy_df(policy_obj, minx=-1, maxx=1, nx=100):\n", + "def get_policy_df(policy_obj, minx=-1, maxx=1, nx=500):\n", " obs_list = np.linspace(minx, maxx, nx)\n", " return pd.DataFrame(\n", " {\n", " 'obs': obs_list,\n", - " 'pop': (obs_list + 1)/2,\n", - " 'pol': [policy_obj.predict(np.float32([obs]))[0][0] for obs in obs_list]\n", + " 'biomass': env.bound * (obs_list + 1)/2,\n", + " 'fishing_mortality': [\n", + " (1 + policy_obj.predict(np.float32([obs]))[0][0]) / 2 \n", + " for obs in obs_list\n", + " ]\n", " }\n", " )" ] }, { "cell_type": "code", - "execution_count": 104, + "execution_count": 108, "id": "b86effb9-d8ad-4b50-8174-ea76dcd60c32", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ - "cr_gp_preargs = {'log_radius': cr_gp.x[0], 'theta': cr_gp.x[1], 'y2': cr_gp.x[2]}\n", - "cr_gp_args = {}\n", - "cr_gp_args['x1'] = (10 ** cr_gp_preargs['log_radius']) * np.sin(cr_gp_preargs['theta'])\n", - "cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", - "cr_gp_args['y2'] = cr_gp_preargs['y2']\n", + "# cr_gp_preargs = {'log_radius': cr_gp.x[0], 'theta': cr_gp.x[1], 'y2': cr_gp.x[2]}\n", + "# cr_gp_args = {}\n", + "# cr_gp_args['x1'] = (10 ** cr_gp_preargs['log_radius']) * np.sin(cr_gp_preargs['theta'])\n", + "# cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", + "# cr_gp_args['y2'] = cr_gp_preargs['y2']\n", + "\n", + "# cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", + "# cr_gbrt_args = {}\n", + "# cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", + "# cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", + "# cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", "\n", - "cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", - "cr_gbrt_args = {}\n", - "cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", - "cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", - "cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", + "# msy_gp_args = {'mortality': msy_gp.x[0]}\n", + "# msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", "\n", - "msy_gp_args = {'mortality': msy_gp.x[0]}\n", - "msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", + "# esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", + "# esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", "\n", - "esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", - "esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", + "msy_gbrt_args = {'mortality': 0.05365088255575121}\n", + "esc_gbrt_args = {'escapement': 0.010338225232077163}\n", + "cr_gbrt_args = {\n", + " 'x1': 0.009159055923137423,\n", + " 'x2': 0.015139834077385755,\n", + " 'y2': 0.29119675741251316,\n", + "}\n", "\n", "#\n", "\n", @@ -2906,26 +9586,54 @@ }, { "cell_type": "code", - "execution_count": 105, + "execution_count": 109, "id": "88d5b45d-eeed-4321-9e9d-1a58ba63e84c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(,\n", - " ,\n", - " ,\n", - " )" + "(,\n", + " ,\n", + " ,\n", + " ,\n", + " )" ] }, - "execution_count": 105, + "execution_count": 109, "metadata": {}, "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " cr_gp_df[cr_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", + " esc_gp_df[esc_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", + " cr_gbrt_df[cr_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", + " esc_gbrt_df[esc_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GBRT policy'),\n", + " msy_gbrt_df[msy_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='MSY GP policy'),\n", + ") " + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "id": "7bd544a0-0ea7-4625-b391-14759d94f8b0", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", 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", + "image/png": 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", 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", 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", 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4+PBhqdUGKB9IDZR3qQHl/7Z++uknXLhwwaH1ZN++fdL+6rL/rfz555/X/VtJTEzEW2+9he+++w4//PADAgICEB8fX+3vItfDMTjkMl588UV4eXlh1KhRlZ4MC5Q3d9unlvbv3x8AMG/ePIc89v/THzBgQI2///KuEaC8FSIyMtJhOrK9gqvqKbiHDh2qtSm9VZVHq9Wibdu2EELAYrFArVZj0KBB+O6777Bz585Kx9tbLTQaTaUWjJUrV1516u2nn37q0FW4atUqnD59Gv369QNQ3grRvHlzzJ07t8qKuqrxJTfqkUcewcmTJ/Hxxx9X2nfx4kUUFxfX+JzX+g2rMm3aNOTn52P06NGwWCyV9tekdWjz5s0oKipCp06drpu3V69eiI6Oxrx581BaWlrt77ie999/X3ovhMD7778Pd3d39OnTB0D5vy2r1eqQDyh/3o9KpZL+DqrjjjvuQHh4OObNm1fpfl953zp27IiOHTvik08+wX//+18MHTq0WtPpyXXx1yeX0bx5c3z++efSlOLLn2T8888/Y+XKldKj6Dt16oQRI0bgo48+QkFBAXr27IkdO3Zg2bJlGDRoEHr37l3j72/bti169eqFqKgo+Pn5YefOnVi1apXDoMyoqCgAwDPPPIP4+HhoNBoMHToUAKQK4lrPVLncqlWrqux6uPfeexEUFIS+ffsiODgY3bp1Q1BQELKysvD+++9jwIAB0v9Zv/baa1i/fj169uwpTaM+ffo0Vq5ciW3btsHHxwf33XcfZsyYgeTkZHTt2hV//PEHli9fXmkshp2fnx+6d++O5ORk5ObmYt68eYiMjMTo0aMBlI/j+OSTT9CvXz+0a9cOycnJaNy4MU6ePInNmzfDYDDgu+++q95Nv47HHnsMX331FZ544gls3rwZ3bp1g9Vqxb59+/DVV1/hxx9/rHKA9bXYf8OXX34ZQ4cOhbu7O+6///6rts4MGzYMf/75J2bPno0dO3Zg6NChCA8PR3FxMf7880988cUXaNiwYaXp3IWFhfjPf/4DoPyZTfv378cHH3wADw+ParfIvPDCC3j44YexdOlSPPHEEzW6zqro9XqkpaVhxIgRiImJwQ8//IC1a9fipZdeksY53X///ejduzdefvllHDlyBJ06dcL69evx7bff4tlnn63R05LVajU++OAD3H///ejcuTOSk5MREhKCffv24a+//sKPP/7okD8xMRHPP/88ALB7ijhNnFzP33//LUaPHi2aNWsmtFqtaNiwoejWrZuYP3++KC0tlfJZLBYxffp0ER4eLtzd3UVYWJiYNGmSQx4hyqeyVjX9u2fPnqJnz57S51dffVVER0cLHx8f4eHhIVq3bi1mzZolzGazlKesrEw8/fTTIiAgQKhUKocp402bNhVNmza97vVda5o4Lpti++GHH4oePXqIRo0aCZ1OJ5o3by5eeOEFUVhY6HC+o0ePisTERGlacUREhBgzZowwmUxCiPJp4uPHjxchISHCw8NDdOvWTaSnp1e6fvsU3y+++EJMmjRJBAYGCg8PDzFgwABx9OjRStexZ88e8eCDD0rla9q0qXjkkUfExo0bK12rfQqy3YgRI4SXl1eVv8mVU+PNZrN4/fXXRbt27YROpxO+vr4iKipKTJ8+3eFeABBjxoypdM4rpzILIcTMmTNF48aNhVqtrvaU8S1btojBgweLkJAQ4e7uLgwGg+jSpYuYOnWqOH36dKXruPw3ValUws/PTzzwwANi165dDnnt08SrmupvtVpF8+bNRfPmzUVZWZmUfqPTxL28vMShQ4dE3759haenpwgKChJTp06t9BiBCxcuiOeee06EhoYKd3d30aJFC/Hmm286TO0W4vrTxO22bdsm7r33XtGwYUPh5eUlOnbs6DB13+706dNCo9GIli1bVvu6yHWphLjB0XNERJfZsmULevfujZUrV2Lw4MHOLg7VsqSkJKxateq643+cKT8/HyEhIZgyZQomT57s7OKQk3EMDhERuYSlS5fCarXisccec3ZRqA7gGBwiIqrXNm3ahL1792LWrFkYNGiQNKOLbm0McIiIqF6bMWMGfv75Z3Tr1g3z5893dnGojuAYHCIiInI5HINDRERELocBDhEREbmcW3IMjs1mw6lTp9CwYUPFH51PREREN0YIgQsXLiA0NBRq9bXbaG7JAOfUqVOVFtkjIiKi+uH48eO47bbbrpnnlgxw7I+pP378OAwGg5NLQ0RERNVhNBoRFhbmsJDr1dySAY69W8pgMDDAISIiqmeqM7yEg4yJiIjI5TDAISIiIpfDAIeIiIhczi05Bqe6rFYrLBaLs4tRZ2i12utOyyMiIqoLGOBUQQiBnJwcFBQUOLsodYparUZ4eDi0Wq2zi0JERHRNDHCqYA9uAgMD4enpyYcB4tLDEU+fPo0mTZrwnhARUZ0ma3/D1q1bcf/99yM0NBQqlQqrV6++7jFbtmzBHXfcAZ1Oh8jISCxdurRSngULFqBZs2bQ6/WIiYnBjh07aq3MVqtVCm4aNWoEDw8P6PX6W37z9PREQEAASkpKUFZWVmv3m4iISA6yBjjFxcXo1KkTFixYUK382dnZGDBgAHr37o3MzEw8++yzGDVqFH788Ucpz5dffonU1FRMnToVu3fvRqdOnRAfH4+8vLxaKbN9zI2np2etnM+V2LumrFark0tCRER0bSohhFDki1QqfPPNNxg0aNBV80yYMAFr167Fn3/+KaUNHToUBQUFSEtLAwDExMTgzjvvxPvvvw+gvOskLCwMTz/9NCZOnFitshiNRnh7e6OwsLDSg/5KS0uRnZ2N8PBw6PX6Gl6la+O9ISIiZ7pW/X2lOjUlJj09HXFxcQ5p8fHxSE9PBwCYzWbs2rXLIY9arUZcXJyUpyomkwlGo9FhIyIiItdVpwKcnJwcBAUFOaQFBQXBaDTi4sWLyM/Ph9VqrTJPTk7OVc87e/ZseHt7SxsX2qza0qVL4ePj4+xiEBER3bQ6FeDIZdKkSSgsLJS248ePO7tIREREJKM6NU08ODgYubm5Dmm5ubkwGAzw8PCARqOBRqOpMk9wcPBVz6vT6aDT6WQpMxERkasSQkAIwCoEbPb3tvL3NlG+v/xz+XubQMU+AU+tG/y8nPfctDoV4MTGxmLdunUOaRs2bEBsbCyA8lk8UVFR2LhxozRY2WazYePGjRg7dqzSxa1zevXqhfbt2wMAPvvsM7i7u+PJJ5/EjBkzoFKpcP78eYwbNw7fffcdTCYTevbsiffeew8tWrRwcsmJiGrOXrmWVVS4ZTYBm83x1XrFPqsQKLNWnd8qLuW32gCrzVb+Kir2V+SxXfadVpvjMTZx6VyXznmNdHualF6eZrusLDaHoMIxoLC/v7TvsuOvCEjEFeexH2e1Vc53+fE3anhME8z6R4fa+8FrSNYAp6ioCAcPHpQ+Z2dnIzMzE35+fmjSpAkmTZqEkydP4tNPPwUAPPHEE3j//ffx4osv4l//+hc2bdqEr776CmvXrpXOkZqaihEjRqBLly6Ijo7GvHnzUFxcjOTkZNmuQwiBixblp0Z7uGtq/EC9ZcuWYeTIkdixYwd27tyJlJQUNGnSBKNHj0ZSUhIOHDiANWvWwGAwYMKECejfvz/27t0Ld3d3ma6CiJQkKipui9UGi1WgzGqTPpdZBcps9vTy91fuK38tT7PahPT50r7yY6xWAYtNwHrZMdbLj7OJy17L81htjsdcmc9W8T2Vj69iq6iYqe5QqwC1SlW+qQE3tXMfCCtrgLNz50707t1b+pyamgoAGDFiBJYuXYrTp0/j2LFj0v7w8HCsXbsWzz33HN59913cdttt+OSTTxAfHy/lGTJkCM6cOYMpU6YgJycHnTt3RlpaWqWBx7XposWKtlN+vH7GWrZ3Rjw8tTX7icLCwvDOO+9ApVKhVatW+OOPP/DOO++gV69eWLNmDbZv346uXbsCAJYvX46wsDCsXr0aDz/8sByXQOQyhBCwWAXMVhvMZZdtVitMFe8tVlHxaoOp4tX+2Wy9lKc8+ChPs5Rd8dkqYKk4xmK77L3V8Vj7+0vBzKVAg8orWze1uqKiVUOtAjRqFTRqNTRqQKNSQa1WVaSpoFFd9l5dXknb06VzqFXQVJzHvl992bHlaVfsv+y8KhWuyFs5XaW69B0qKS8czmf/TrUKl96rLwUXVZ5TrYIKuOwclwUjl50fVeTRVORTScdUPlalQp17wr2sAU6vXr1wrcfsVPWU4l69emHPnj3XPO/YsWPZJXUVd911l8MfWWxsLN566y3s3bsXbm5uiImJkfY1atQIrVq1QlZWljOKSlRjNpuAqcyGUosVpWVWlFoq3lsq3pdZYbLYYCorTzOV2WCqyGMqK0+3p0nvK9LN9veW8kDDZLGWv0qBjO2mmuudSaNWwU2tgrtGDTeNCm5qNdw15RWau0YNN7UKbprL0tQV+Sr2lecrP87+2U06TlWRdul4++cr92sqAgW3y/KpVeVlkD5Lx5d/3+VBhz1drVbB/fLgxCFPeTBT1ypbUl6dGoNTV3m4a7B3Rvz1M8rwvUT1SZnVhhKLFSUmK4rNZbhotqLYVIYSixUXzVaUmK24aC4rf61Is7+WWKwotX+uSLMHLvY0c5nN2ZcocVOroHVTl28aNdw1augqPrtr7K8qaN000GpUl9I1arhLx5QHCtrL8rupL713rziv/b3b5e8rghOt26X39gDGXa2Gu9ulgETt5K4CImdggFMNKpWqxl1FzpKRkeHw+ZdffkGLFi3Qtm1blJWVISMjQ+qiOnv2LPbv34+2bds6o6hUBwghUGqx4YLJgqLSMhSZylBUWoYLFa9Fpktb8WWvJWYrikxlUiBTbCpDsVnZAMRdo4LeTQOduwZ6dzX0Fa86t0uvOjfHdJ2bGjr3ile3SwGJviJN61aezx606NwvBR/2fbqKfQwaiOq2+lFrU7UdO3YMqampePzxx7F7927Mnz8fb731Flq0aIGBAwdi9OjR+PDDD9GwYUNMnDgRjRs3xsCBA51dbLoJpRYrCi9aLm0l5a/G0orXi2UwllpwofTy92W4UPEqx5gNjVoFT60GnloNvLRu8Kh476F1g6e7/b0GHu4VrxXvPbUa6N0vS3fXSAGKXnqvgd6tvDWDiOhqGOC4mMTERFy8eBHR0dHQaDQYN24cUlJSAABLlizBuHHjcN9998FsNqNHjx5Yt24dZ1DVEUIIlJitOFtkxrkSM84Xm3Gu2IzzJZdezxdbcL7EjMKL5a8FJRaYaqHVRKUCGujc0FDnhoZ6d3jpNGigd0cDnQYNdG7w0rlJr+XvNfDUlqd5asvzeFQEM546DbQaNcdAEJFTKbbYZl3iqott9urVC507d8a8efNkOX99vjfOIoRA4UULzlwwlW9F5a/5RWbkF5mQX2TC2SIzzhaZcLbYfMPBiloFeHu4S5vhsleD3h0GD7eKV3c01LvBoC8PZBpWvHq6a9jlQkR1Xk0W22QLDtENKrVYkWssxenCUuQUlr/mGi9teRdMyDOaYLbWLGjRu6vRyEsHPy8tfDzd4eelha9nxeblDh9PLXw93eHjUb7f29MdDbRuDFCIiC7DAIfoKoylFhw/V4IT5y/ixPmLOHn+Ik4VXMSpwvLX/CJztc/l7eGOgIY6BDTQIaChDv4NdGjUQIuAitdGDXRo5KVFowbaejOgnYioLuN/SV3Ili1bnF2EekUIgTMXTDicX4yjZ4tx9GwJjp4rwbGzJTh6thjG0rLrnkPvrkaItweCDXqEeOsRaNAj2KBDkKH8fWBDHQINOujcOOWfiEhJDHDI5ZnLbDh6thgH84pwIK8IB/OKkJ1fjOz8YhSZrh3E+HlpEebrgdt8PdHY1wONfTwQ6uOBUB89Qr094OPpzsG0RER1EAOcq7gFx15fV12/J0IInDh/EftyLmB/jhFZORewP+cCjuQXX3UqtFoF3ObriWb+Xmjq54mmjTzRxM8TTRt54TZfD3jp+E+EiKg+4n+9r2CfMl1SUgIPDw8nl6ZuMZvLx5xoNM7vbrHZBLLPFuPPk4UVmxF/nSq8ardSA50bmgc2QGRAA0QGNkBEgBeaB3ghzM+T3UdERC6IAc4VNBoNfHx8kJeXBwDw9PRkFwQAm82GM2fOwNPTE25uyv/ZFJZYsPv4eew5VoDM4wXIPHa+ymDGXaNCZGBDtA6u2EIMaBnUAMEGPX9HIqJbCAOcKgQHBwOAFORQObVajSZNmigSKOQaS7Ej+xx2ZJ/Dr0fOYX/uhUoLHerc1GgXakD7xt5oH+qN9o29ERnYAFo3PuGWiOhWxwCnCiqVCiEhIQgMDITFYnF2ceoMrVYLtVqe4KHIVIaMw2fxvwP52HYwHwfziirlCff3wu1NfHB7mA9ub+KLVsEN4c7H9RMRURUY4FyDRqOpE+NNXFV2fjE2ZuViw95c7Dp63mEgsEoFtA0x4M5mfogJ90OXZn4IaKhzYmmJiKg+YYBDihFC4LcThfjhj9PYkJWLw2eKHfY38fNE9xb+uDvSH12b+8Pbk2tkERHRjWGAQ7ISQiDr9AV8//spfPf7KRw/d1Ha56ZWISbCD3FtgnBP60A0beTlxJISEZErYYBDsjhXbMbXu0/gq53H8XfupfE0Hu4a9GkTiIT2wejRMgAGPVtpiIio9jHAoVpjswn8fOgsvvj1GNb/lQOLtXxMjdZNjd6tAnB/p1Dc0zqQay0REZHsWNPQTSu1WPHNnpP45H+HceiycTUdGntjyJ1heKBzKFtqiIhIUQxw6IadKzbjs/Sj+OyXI9LK2g11bhh0e2MMuTMM7Rt7O7mERER0q2KAQzVWeNGCj7YewuJtR3DRYgUANPbxQHK3ZhhyZxgasrWGiIicjAEOVdtFsxVLfz6Chf93CIUXyx+A2L6xASk9mqN/+2C48aF7RERURzDAoeuy2QRW7T6BuT/uR94FEwCgZVADPN+3Fe5tG8Q1noiIqM5hgEPXdCD3Al7+5k/sOHIOABDm54Hn4lpiYOfG0KgZ2BARUd3EAIeqVGqx4v1NB/Hh1kOwWAU83DVIvbclRnRtxsUsiYiozmOAQ5VkHi/AuBV7cPRsCQAgrk0gpg9sj8Y+Hk4uGRERUfUwwCGJEAKLtmVjzg/7UGYTCDboMe2Bdohvx3E2RERUvzDAIQBAQYkZz6/8HT9l5QIA+ncIxpyHOvIBfUREVC8xwCHsOXYeYz/fg5MFF6HVqDH5vjZ49K6mbLUhIqJ6iwHOLe6nvbkY8/lumMpsaNrIEwuG3cEnEBMRUb2nyHSYBQsWoFmzZtDr9YiJicGOHTuumrdXr15QqVSVtgEDBkh5kpKSKu1PSEhQ4lJcyqpdJ/D4f3bBVGZD71YB+P7p7gxuiIjIJcjegvPll18iNTUVCxcuRExMDObNm4f4+Hjs378fgYGBlfJ//fXXMJvN0uezZ8+iU6dOePjhhx3yJSQkYMmSJdJnnU4n30W4oA//7xBm/7APAPDQHbdhzkMd4M4nERMRkYuQvUZ7++23MXr0aCQnJ6Nt27ZYuHAhPD09sXjx4irz+/n5ITg4WNo2bNgAT0/PSgGOTqdzyOfr6yv3pbgEIQReW5clBTcpPSIw9+GODG6IiMilyFqrmc1m7Nq1C3FxcZe+UK1GXFwc0tPTq3WORYsWYejQofDy8nJI37JlCwIDA9GqVSs8+eSTOHv2bK2W3VXNSduHj7YeBgBM6tcaL/Vvw8HERETkcmTtosrPz4fVakVQUJBDelBQEPbt23fd43fs2IE///wTixYtckhPSEjAgw8+iPDwcBw6dAgvvfQS+vXrh/T0dGg0mkrnMZlMMJlM0mej0XiDV1S/fZZ+BB/+X3lwM+fBDhga3cTJJSIiIpJHnZ5FtWjRInTo0AHR0dEO6UOHDpXed+jQAR07dkTz5s2xZcsW9OnTp9J5Zs+ejenTp8te3rrsp725mLrmLwDA+HtbMrghIiKXJmsXlb+/PzQaDXJzcx3Sc3NzERwcfM1ji4uLsWLFCowcOfK63xMREQF/f38cPHiwyv2TJk1CYWGhtB0/frz6F+ECfjtegKe/2AObAIZ0CcPYeyKdXSQiIiJZyRrgaLVaREVFYePGjVKazWbDxo0bERsbe81jV65cCZPJhEcfffS633PixAmcPXsWISEhVe7X6XQwGAwO263i+LkSjFz2Ky5arOjRMgCv/qM9x9wQEZHLk33qTGpqKj7++GMsW7YMWVlZePLJJ1FcXIzk5GQAQGJiIiZNmlTpuEWLFmHQoEFo1KiRQ3pRURFeeOEF/PLLLzhy5Ag2btyIgQMHIjIyEvHx8XJfTr1SarHiX0t/RX6RGW1DDPj38Ds4W4qIiG4Jso/BGTJkCM6cOYMpU6YgJycHnTt3RlpamjTw+NixY1CrHSvd/fv3Y9u2bVi/fn2l82k0Gvz+++9YtmwZCgoKEBoair59+2LmzJl8Fs4V3vxxPw7kFSGgoQ5Lku9EA12dHnJFRERUa1RCCOHsQijNaDTC29sbhYWFLttd9cvhs/jnx79ACGBJ0p3o3bryQxWJiIjqk5rU3+yvcEFFpjI8v/I3CAEMvTOMwQ0REd1yGOC4oFlrs3Di/EXc5uuBV+5r6+ziEBERKY4BjovZvD8PX+w4BgB4c3AnjrshIqJbEgMcF1JQYsaEVb8DAP7VLRyxzRtd5wgiIiLXxADHhbyz4W/kXTAhIsALLya0cnZxiIiInIYBjos4WXARX+wof0LzqwPbQ+9eeU0uIiKiWwUDHBfx/qaDMFttiI1ohK6R/s4uDhERkVMxwHEBx86WYOXO8tab1L4tnVwaIiIi52OA4wLe23QAZTaBu1v4485mfs4uDhERkdMxwKnnDp8pwte7TwAAxvflwGIiIiKAAU69997GA7AJoE/rQHQO83F2cYiIiOoEBjj12IHcC/j2t1MAgOfu5dgbIiIiOwY49di8nw5ACCChXTDaN/Z2dnGIiIjqDAY49dTxcyVY+8dpAMCz97ZwcmmIiIjqFgY49dTqPScBAN0iG6F18LWXjCciIrrVMMCph4QQ+LoiwHnw9tucXBoiIqK6hwFOPZR5vADZ+cXwcNcgoX2ws4tDRERU5zDAqYe+qWi9SWgfDC+dm5NLQ0REVPcwwKlnzGU2rKmYGv6P2xs7uTRERER1EwOcembL/jwUlFgQ2FCHblxUk4iIqEoMcOqZr3eXd08Nur0xNGqVk0tDRERUNzHAqUcKSyzYtC8PALuniIiIroUBTj3y/R+nYLba0Dq4IdqE8Nk3REREV8MApx6xd089dAeffUNERHQtDHDqiaNni7Hr6HmoVcDAzqHOLg4REVGdxgCnnvhGWprBH4EGvZNLQ0REVLcxwKkntv59BgBwX8cQJ5eEiIio7mOAUw9cNFvx+4lCAEBsBJ99Q0REdD0McOqBPcfOo8wmEOKtR5ifh7OLQ0REVOcxwKkHMrLPAQCiw/2gUvHhfkRERNfDAKceyMg+C6A8wCEiIqLrY4BTx5nKrNhzrAAAEMMAh4iIqFoUCXAWLFiAZs2aQa/XIyYmBjt27Lhq3qVLl0KlUjlser3jtGghBKZMmYKQkBB4eHggLi4OBw4ckPsynOKPE4UwldnQyEuL5gENnF0cIiKiekH2AOfLL79Eamoqpk6dit27d6NTp06Ij49HXl7eVY8xGAw4ffq0tB09etRh/xtvvIH33nsPCxcuREZGBry8vBAfH4/S0lK5L0dxHH9DRERUc7IHOG+//TZGjx6N5ORktG3bFgsXLoSnpycWL1581WNUKhWCg4OlLSgoSNonhMC8efPwyiuvYODAgejYsSM+/fRTnDp1CqtXr5b7chR3eYBDRERE1SNrgGM2m7Fr1y7ExcVd+kK1GnFxcUhPT7/qcUVFRWjatCnCwsIwcOBA/PXXX9K+7Oxs5OTkOJzT29sbMTExVz2nyWSC0Wh02OqDMqsNu44wwCEiIqopWQOc/Px8WK1WhxYYAAgKCkJOTk6Vx7Rq1QqLFy/Gt99+i//85z+w2Wzo2rUrTpw4AQDScTU55+zZs+Ht7S1tYWFhN3tpith72ohisxUGvRtaB3P1cCIiouqqc7OoYmNjkZiYiM6dO6Nnz574+uuvERAQgA8//PCGzzlp0iQUFhZK2/Hjx2uxxPLJOFzeenNnMz9o1Bx/Q0REVF2yBjj+/v7QaDTIzc11SM/NzUVwcHC1zuHu7o7bb78dBw8eBADpuJqcU6fTwWAwOGz1AcffEBER3RhZAxytVouoqChs3LhRSrPZbNi4cSNiY2OrdQ6r1Yo//vgDISHli0yGh4cjODjY4ZxGoxEZGRnVPmd9YLMJ/MrxN0RERDfETe4vSE1NxYgRI9ClSxdER0dj3rx5KC4uRnJyMgAgMTERjRs3xuzZswEAM2bMwF133YXIyEgUFBTgzTffxNGjRzFq1CgA5TOsnn32Wbz66qto0aIFwsPDMXnyZISGhmLQoEFyX45i/s67gMKLFnhqNWjf2NvZxSEiIqpXZA9whgwZgjNnzmDKlCnIyclB586dkZaWJg0SPnbsGNTqSw1J58+fx+jRo5GTkwNfX19ERUXh559/Rtu2baU8L774IoqLi5GSkoKCggJ0794daWlplR4IWJ/Zx99ENfWFu6bODZUiIiKq01RCCOHsQijNaDTC29sbhYWFdXY8zpjlu7H2j9MYf29LPN2nhbOLQ0RE5HQ1qb/ZNFAHCSE4wJiIiOgmMMCpg46eLUF+kQlajRqdwnycXRwiIqJ6hwFOHXQwrwgAEBnYAHp3jZNLQ0REVP8wwKmDjpwtBgCEB3g5uSRERET1EwOcOuhwfkWA04gBDhER0Y1ggFMHHakIcJr5M8AhIiK6EQxw6iB7gBPOAIeIiOiGMMCpYy6arThVWAqAAQ4REdGNYoBTxxw9V956Y9C7wdfT3cmlISIiqp8Y4NQx2WfsM6gaQKVSObk0RERE9RMDnDom2z5FvJGnk0tCRERUfzHAqWMuDTBu4OSSEBER1V8McOqYbGmKOFtwiIiIbhQDnDomO78EAGdQERER3QwGOHXIhVIL8otMAPiQPyIiopvBAKcOOVLReuPfQAuDnlPEiYiIbhQDnDrEPoOqGdegIiIiuikMcOoQ6Rk47J4iIiK6KQxw6pAjZ7nIJhERUW1ggFOHZHORTSIiolrBAKcOYYBDRERUOxjg1BHni80ovGgBwEHGREREN4sBTh1xuKL1JsRbDw+txsmlISIiqt8Y4NQR9jWo2HpDRER08xjg1BGcQUVERFR7GODUEfYuqggGOERERDeNAU4dIXVRMcAhIiK6aQxw6gAhhBTghPt7Ork0RERE9R8DnDrgzAUTis1WqFVAmB8DHCIiopvFAKcOsD/gr7GvB3RunCJORER0sxjg1AGXnmDcwMklISIicg2KBDgLFixAs2bNoNfrERMTgx07dlw178cff4y7774bvr6+8PX1RVxcXKX8SUlJUKlUDltCQoLclyGb7Iop4uGN2D1FRERUG2QPcL788kukpqZi6tSp2L17Nzp16oT4+Hjk5eVVmX/Lli345z//ic2bNyM9PR1hYWHo27cvTp486ZAvISEBp0+flrYvvvhC7kuRDWdQERER1S7ZA5y3334bo0ePRnJyMtq2bYuFCxfC09MTixcvrjL/8uXL8dRTT6Fz585o3bo1PvnkE9hsNmzcuNEhn06nQ3BwsLT5+vrKfSmyyTWaAAChPh5OLgkREZFrkDXAMZvN2LVrF+Li4i59oVqNuLg4pKenV+scJSUlsFgs8PPzc0jfsmULAgMD0apVKzz55JM4e/ZsrZZdSfZFNn09tU4uCRERkWtwk/Pk+fn5sFqtCAoKckgPCgrCvn37qnWOCRMmIDQ01CFISkhIwIMPPojw8HAcOnQIL730Evr164f09HRoNJVnIZlMJphMJumz0Wi8wSuSx/kSMwDAx9PdySUhIiJyDbIGODdrzpw5WLFiBbZs2QK9Xi+lDx06VHrfoUMHdOzYEc2bN8eWLVvQp0+fSueZPXs2pk+frkiZa8pqE1ILDgMcIiKi2iFrF5W/vz80Gg1yc3Md0nNzcxEcHHzNY+fOnYs5c+Zg/fr16Nix4zXzRkREwN/fHwcPHqxy/6RJk1BYWChtx48fr9mFyMh40QIhyt/7eLCLioiIqDbIGuBotVpERUU5DBC2DxiOjY296nFvvPEGZs6cibS0NHTp0uW633PixAmcPXsWISEhVe7X6XQwGAwOW11RUNF646XVQOvGxxIRERHVBtlr1NTUVHz88cdYtmwZsrKy8OSTT6K4uBjJyckAgMTEREyaNEnK//rrr2Py5MlYvHgxmjVrhpycHOTk5KCoqAgAUFRUhBdeeAG//PILjhw5go0bN2LgwIGIjIxEfHy83JdT6y6Nv2HrDRERUW2RfQzOkCFDcObMGUyZMgU5OTno3Lkz0tLSpIHHx44dg1p9Kc764IMPYDabMXjwYIfzTJ06FdOmTYNGo8Hvv/+OZcuWoaCgAKGhoejbty9mzpwJnU4n9+XUuoKKAMfXi+NviIiIaotKCPsIkFuH0WiEt7c3CgsLnd5d9fXuE0j96jd0j/THf0bFOLUsREREdVlN6m8O+nCy8yWcQUVERFTbGOA4mdRFxTE4REREtYYBjpMVsAWHiIio1jHAcTLOoiIiIqp9DHCczN6C48sWHCIiolrDAMfJCi5yHSoiIqLaxgDHyc4X28fgsIuKiIiotjDAcTLOoiIiIqp9DHCcyFxmQ7HZCoBjcIiIiGoTAxwnso+/UamAhnoGOERERLWFAY4T2WdQeXu4Q6NWObk0REREroMBjhNdmiLO8TdERES1iQGOE9kf8uftwe4pIiKi2sQAx4kuzaBigENERFSbGOA4EbuoiIiI5MEAx4nO2wcZswWHiIioVjHAcSI+5I+IiEgeDHCciAttEhERyYMBjhNJs6jYgkNERFSrGOA4EVtwiIiI5MEAx4nsSzVwDA4REVHtYoDjJEKIS7Oo+KA/IiKiWsUAx0kuWqwwl9kAAL5ebMEhIiKqTQxwnMTeeuOuUcFLq3FyaYiIiFwLAxwnKZDWodJCpeJK4kRERLWJAY6TcAYVERGRfBjgOMl5PsWYiIhINgxwnKSA61ARERHJhgGOk1xah4oBDhERUW1jgOMk56UxOOyiIiIiqm0McJzE3kXlwwCHiIio1jHAcRJ7F5UPu6iIiIhqnSIBzoIFC9CsWTPo9XrExMRgx44d18y/cuVKtG7dGnq9Hh06dMC6desc9gshMGXKFISEhMDDwwNxcXE4cOCAnJdQ685zDA4REZFsZA9wvvzyS6SmpmLq1KnYvXs3OnXqhPj4eOTl5VWZ/+eff8Y///lPjBw5Env27MGgQYMwaNAg/Pnnn1KeN954A++99x4WLlyIjIwMeHl5IT4+HqWlpXJfTq0puMguKiIiIrmohBBCzi+IiYnBnXfeiffffx8AYLPZEBYWhqeffhoTJ06slH/IkCEoLi7G999/L6Xddddd6Ny5MxYuXAghBEJDQzF+/Hg8//zzAIDCwkIEBQVh6dKlGDp06HXLZDQa4e3tjcLCQhgMhlq60pq5Y+YGnCs2I+3Zu9E62DllICIiqk9qUn/L2oJjNpuxa9cuxMXFXfpCtRpxcXFIT0+v8pj09HSH/AAQHx8v5c/OzkZOTo5DHm9vb8TExFz1nCaTCUaj0WFzJptNXDZNnC04REREtU3WACc/Px9WqxVBQUEO6UFBQcjJyanymJycnGvmt7/W5JyzZ8+Gt7e3tIWFhd3Q9dSWC6Yy2Crazbw9OAaHiIiott0Ss6gmTZqEwsJCaTt+/LhTy2NvvfFw10DvzpXEiYiIapusAY6/vz80Gg1yc3Md0nNzcxEcHFzlMcHBwdfMb3+tyTl1Oh0MBoPD5kznudAmERGRrGQNcLRaLaKiorBx40YpzWazYePGjYiNja3ymNjYWIf8ALBhwwYpf3h4OIKDgx3yGI1GZGRkXPWcdc2lZ+Bw/A0REZEc3OT+gtTUVIwYMQJdunRBdHQ05s2bh+LiYiQnJwMAEhMT0bhxY8yePRsAMG7cOPTs2RNvvfUWBgwYgBUrVmDnzp346KOPAAAqlQrPPvssXn31VbRo0QLh4eGYPHkyQkNDMWjQILkvp1ZceooxW3CIiIjkIHuAM2TIEJw5cwZTpkxBTk4OOnfujLS0NGmQ8LFjx6BWX2pI6tq1Kz7//HO88soreOmll9CiRQusXr0a7du3l/K8+OKLKC4uRkpKCgoKCtC9e3ekpaVBr9fLfTm14jxnUBEREclK9ufg1EXOfg7OOxv+xrsbD2B4TBPM+kcHxb+fiIioPqozz8GhqnEdKiIiInkxwHGCS7Oo2EVFREQkBwY4TsB1qIiIiOTFAMcJpC4qPsWYiIhIFgxwnECaReXFAIeIiEgODHCcoKCYXVRERERyYoCjMIvVhgumMgAcZExERCQXBjgKK6wYYAwABr3sz1kkIiK6JTHAUZh9gLFB7wY3DW8/ERGRHFjDKsy+DpWvF7uniIiI5MIAR2HG0vIAx6DnDCoiIiK5MMBRWKnFBgDQu/PWExERyYW1rMLMZeUBjs5N4+SSEBERuS4GOAozlVkBADo33noiIiK5sJZVmL0FR8sAh4iISDasZRVmkrqoeOuJiIjkwlpWYSaOwSEiIpIdAxyFmdhFRUREJDvWsgrjIGMiIiL5sZZVmKniOTg6PgeHiIhINqxlFWa2VnRRaTgGh4iISC4McBTGFhwiIiL5sZZVGMfgEBERyY+1rML4oD8iIiL5sZZVGJ+DQ0REJD8GOAqzd1GxBYeIiEg+rGUVZuZSDURERLJjLaswrkVFREQkP9ayCuMgYyIiIvmxllUYBxkTERHJjwGOwvgcHCIiIvnJWsueO3cOw4cPh8FggI+PD0aOHImioqJr5n/66afRqlUreHh4oEmTJnjmmWdQWFjokE+lUlXaVqxYIeel1BoOMiYiIpKfm5wnHz58OE6fPo0NGzbAYrEgOTkZKSkp+Pzzz6vMf+rUKZw6dQpz585F27ZtcfToUTzxxBM4deoUVq1a5ZB3yZIlSEhIkD77+PjIeSm1hl1URERE8pMtwMnKykJaWhp+/fVXdOnSBQAwf/589O/fH3PnzkVoaGilY9q3b4///ve/0ufmzZtj1qxZePTRR1FWVgY3t0vF9fHxQXBwsFzFl40U4HAtKiIiItnIVsump6fDx8dHCm4AIC4uDmq1GhkZGdU+T2FhIQwGg0NwAwBjxoyBv78/oqOjsXjxYgghaq3scimz2mC1lZdTq2GAQ0REJBfZWnBycnIQGBjo+GVubvDz80NOTk61zpGfn4+ZM2ciJSXFIX3GjBm455574OnpifXr1+Opp55CUVERnnnmmSrPYzKZYDKZpM9Go7GGV1M7zFab9J4tOERERPKpcYAzceJEvP7669fMk5WVdcMFsjMajRgwYADatm2LadOmOeybPHmy9P72229HcXEx3nzzzasGOLNnz8b06dNvukw3y2S5FOCwBYeIiEg+NQ5wxo8fj6SkpGvmiYiIQHBwMPLy8hzSy8rKcO7cueuOnblw4QISEhLQsGFDfPPNN3B3d79m/piYGMycORMmkwk6na7S/kmTJiE1NVX6bDQaERYWds1zysHegqNRq+DGAIeIiEg2NQ5wAgICEBAQcN18sbGxKCgowK5duxAVFQUA2LRpE2w2G2JiYq56nNFoRHx8PHQ6HdasWQO9Xn/d78rMzISvr2+VwQ0A6HS6q+5Tkr0Fh1PEiYiI5CXbGJw2bdogISEBo0ePxsKFC2GxWDB27FgMHTpUmkF18uRJ9OnTB59++imio6NhNBrRt29flJSU4D//+Q+MRqM0XiYgIAAajQbfffcdcnNzcdddd0Gv12PDhg147bXX8Pzzz8t1KbWGK4kTEREpQ9bn4Cxfvhxjx45Fnz59oFar8dBDD+G9996T9lssFuzfvx8lJSUAgN27d0szrCIjIx3OlZ2djWbNmsHd3R0LFizAc889ByEEIiMj8fbbb2P06NFyXkqt4EKbREREylCJ+jC/upYZjUZ4e3tLU9CVsuvoeTz0wc9o4ueJrS/2Vux7iYiIXEFN6m82JSiIK4kTEREpgzWtgrjQJhERkTJY0yqIY3CIiIiUwZpWQeyiIiIiUgZrWgVxJXEiIiJlMMBREMfgEBERKYM1rYLYRUVERKQM1rQKYhcVERGRMhjgKEhai8qdt52IiEhOrGkVZLZWrEXFlcSJiIhkxZpWQWzBISIiUgZrWgVxDA4REZEyGOAoyMwnGRMRESmCNa2C+BwcIiIiZbCmVZDZyufgEBERKYE1rYKkQcYMcIiIiGTFmlZBHGRMRESkDAY4CuJSDURERMpgTasgDjImIiJSBmtaBbGLioiISBkMcBTELioiIiJlsKZVkIkP+iMiIlIEa1oFSWNwuBYVERGRrFjTKsjegsPVxImIiOTFmlZBUheVOwcZExERyYkBjkKEEFxsk4iISCGsaRViX4cK4CwqIiIiubGmVYi9ewpgCw4REZHcWNMqxHxZgMNBxkRERPJiTasQ02UP+VOpVE4uDRERkWtjgKMQk4XrUBERESmFta1C7IOMGeAQERHJT9ba9ty5cxg+fDgMBgN8fHwwcuRIFBUVXfOYXr16QaVSOWxPPPGEQ55jx45hwIAB8PT0RGBgIF544QWUlZXJeSk3zWThQptERERKcZPz5MOHD8fp06exYcMGWCwWJCcnIyUlBZ9//vk1jxs9ejRmzJghffb09JTeW61WDBgwAMHBwfj5559x+vRpJCYmwt3dHa+99pps13KzuA4VERGRcmQLcLKyspCWloZff/0VXbp0AQDMnz8f/fv3x9y5cxEaGnrVYz09PREcHFzlvvXr12Pv3r346aefEBQUhM6dO2PmzJmYMGECpk2bBq1WK8v13CyuJE5ERKQc2Wrb9PR0+Pj4SMENAMTFxUGtViMjI+Oaxy5fvhz+/v5o3749Jk2ahJKSEofzdujQAUFBQVJafHw8jEYj/vrrryrPZzKZYDQaHTalSQttMsAhIiKSnWwtODk5OQgMDHT8Mjc3+Pn5IScn56rHDRs2DE2bNkVoaCh+//13TJgwAfv378fXX38tnffy4AaA9Plq5509ezamT59+M5dz0y51UXEMDhERkdxqHOBMnDgRr7/++jXzZGVl3XCBUlJSpPcdOnRASEgI+vTpg0OHDqF58+Y3dM5JkyYhNTVV+mw0GhEWFnbDZbwR7KIiIiJSTo0DnPHjxyMpKemaeSIiIhAcHIy8vDyH9LKyMpw7d+6q42uqEhMTAwA4ePAgmjdvjuDgYOzYscMhT25uLgBc9bw6nQ46na7a3ykHdlEREREpp8YBTkBAAAICAq6bLzY2FgUFBdi1axeioqIAAJs2bYLNZpOClurIzMwEAISEhEjnnTVrFvLy8qQusA0bNsBgMKBt27Y1vBrlSCuJuzPAISIikptstW2bNm2QkJCA0aNHY8eOHdi+fTvGjh2LoUOHSjOoTp48idatW0stMocOHcLMmTOxa9cuHDlyBGvWrEFiYiJ69OiBjh07AgD69u2Ltm3b4rHHHsNvv/2GH3/8Ea+88grGjBnj9Faaa5GWauA6VERERLKTtbZdvnw5WrdujT59+qB///7o3r07PvroI2m/xWLB/v37pVlSWq0WP/30E/r27YvWrVtj/PjxeOihh/Ddd99Jx2g0Gnz//ffQaDSIjY3Fo48+isTERIfn5tRFHGRMRESkHFkf9Ofn53fNh/o1a9YMQgjpc1hYGP7v//7vuudt2rQp1q1bVytlVIqJXVRERESKYW2rEPsgY3ZRERERyY+1rUKktajYgkNERCQ71rYKsa8mrtVwDA4REZHcGOAohC04REREymFtqxA+6I+IiEg5rG0VwqUaiIiIlMPaViF8Dg4REZFyGOAohF1UREREymFtqxB2URERESmHta1CLnVR8ZYTERHJjbWtQswcg0NERKQYBjgKMbGLioiISDGsbRXCQcZERETKYW2rEHsXlZ5PMiYiIpIda1uFSF1UXIuKiIhIdgxwFCLNomILDhERkexY2yqgzGqD1SYAAFoNbzkREZHcWNsqwGy1Se/ZgkNERCQ/1rYKMFkuBThswSEiIpIfa1sF2FtwNGoV3BjgEBERyY61rQLsLTh8Bg4REZEyWOMqgA/5IyIiUhZrXAVwmQYiIiJlscZVgIkLbRIRESmKAY4CLq0kzttNRESkBNa4CrCPwWEXFRERkTJY4yrAxBYcIiIiRbHGVYCZY3CIiIgUxQBHAZxFRUREpCzWuArgc3CIiIiUxRpXAVIXlTu7qIiIiJQga4Bz7tw5DB8+HAaDAT4+Phg5ciSKioqumv/IkSNQqVRVbitXrpTyVbV/xYoVcl7KTZG6qLgOFRERkSLc5Dz58OHDcfr0aWzYsAEWiwXJyclISUnB559/XmX+sLAwnD592iHto48+wptvvol+/fo5pC9ZsgQJCQnSZx8fn1ovf22R1qJyZ4BDRESkBNkCnKysLKSlpeHXX39Fly5dAADz589H//79MXfuXISGhlY6RqPRIDg42CHtm2++wSOPPIIGDRo4pPv4+FTKW1eZrRXPwWELDhERkSJkq3HT09Ph4+MjBTcAEBcXB7VajYyMjGqdY9euXcjMzMTIkSMr7RszZgz8/f0RHR2NxYsXQwhx1fOYTCYYjUaHTUlswSEiIlKWbC04OTk5CAwMdPwyNzf4+fkhJyenWudYtGgR2rRpg65duzqkz5gxA/fccw88PT2xfv16PPXUUygqKsIzzzxT5Xlmz56N6dOn39iF1AKzlc/BISIiUlKNmxQmTpx41YHA9m3fvn03XbCLFy/i888/r7L1ZvLkyejWrRtuv/12TJgwAS+++CLefPPNq55r0qRJKCwslLbjx4/fdPlqQmrB4TRxIiIiRdS4BWf8+PFISkq6Zp6IiAgEBwcjLy/PIb2srAznzp2r1tiZVatWoaSkBImJidfNGxMTg5kzZ8JkMkGn01Xar9PpqkxXCp+DQ0REpKwaBzgBAQEICAi4br7Y2FgUFBRg165diIqKAgBs2rQJNpsNMTEx1z1+0aJFeOCBB6r1XZmZmfD19XVqEHMtl7qoGOAQEREpQbYxOG3atEFCQgJGjx6NhQsXwmKxYOzYsRg6dKg0g+rkyZPo06cPPv30U0RHR0vHHjx4EFu3bsW6desqnfe7775Dbm4u7rrrLuj1emzYsAGvvfYann/+ebku5abZu6i4VAMREZEyZH0OzvLlyzF27Fj06dMHarUaDz30EN577z1pv8Viwf79+1FSUuJw3OLFi3Hbbbehb9++lc7p7u6OBQsW4LnnnoMQApGRkXj77bcxevRoOS/lppi42CYREZGiVOJa86tdlNFohLe3NwoLC2EwGGT/vkcWpmPHkXP4YPgd6NchRPbvIyIickU1qb/ZZ6IA+yBjdlEREREpgzWuAthFRUREpCwGOAq4tJo4bzcREZESWOMqgKuJExERKYs1rgKkB/2xBYeIiEgRrHEVwBYcIiIiZbHGVYA0yNidg4yJiIiUwABHZkKIS4OMOU2ciIhIEaxxZWZfhwrgc3CIiIiUwhpXZvbuKYAtOEREREphjSsz82UBDgcZExERKYM1rsykGVRuaqhUKieXhoiI6NbAAEdmJkvFM3DYPUVERKQY1roysw8y5jpUREREymGAIzOThVPEiYiIlMZaV2YmPgOHiIhIcax1ZWa+bJAxERERKYO1rsykhTYZ4BARESmGta7MLnVRcZAxERGRUhjgyExah8qdt5qIiEgprHVlZu+i4lOMiYiIlMNaV2ZswSEiIlIea12ZSUs1sAWHiIhIMax1ZcZBxkRERMpjgCMzE7uoiIiIFMdaV2YcZExERKQ81royk9aiYgsOERGRYljryoyriRMRESmPAY7M7C04XIuKiIhIOax1Zca1qIiIiJTHWldmZk4TJyIiUhwDHJlJD/pjCw4REZFiZKt1Z82aha5du8LT0xM+Pj7VOkYIgSlTpiAkJAQeHh6Ii4vDgQMHHPKcO3cOw4cPh8FggI+PD0aOHImioiIZrqB2sIuKiIhIebLVumazGQ8//DCefPLJah/zxhtv4L333sPChQuRkZEBLy8vxMfHo7S0VMozfPhw/PXXX9iwYQO+//57bN26FSkpKXJcQq241EXFAIeIiEgpbnKdePr06QCApUuXViu/EALz5s3DK6+8goEDBwIAPv30UwQFBWH16tUYOnQosrKykJaWhl9//RVdunQBAMyfPx/9+/fH3LlzERoaKsu1VFeRqQwFJeZKaQC7qIiIiJQkW4BTU9nZ2cjJyUFcXJyU5u3tjZiYGKSnp2Po0KFIT0+Hj4+PFNwAQFxcHNRqNTIyMvCPf/yjynObTCaYTCbps9FolOUa1mSewkvf/FHlPgY4REREyqkztW5OTg4AICgoyCE9KChI2peTk4PAwECH/W5ubvDz85PyVGX27Nnw9vaWtrCwsFoufTmNurwr6sqtZVADdGjsLct3EhERUWU1asGZOHEiXn/99WvmycrKQuvWrW+qULVt0qRJSE1NlT4bjUZZgpwhdzbBkDub1Pp5iYiIqGZqFOCMHz8eSUlJ18wTERFxQwUJDg4GAOTm5iIkJERKz83NRefOnaU8eXl5DseVlZXh3Llz0vFV0el00Ol0N1QuIiIiqn9qFOAEBAQgICBAloKEh4cjODgYGzdulAIao9GIjIwMaSZWbGwsCgoKsGvXLkRFRQEANm3aBJvNhpiYGFnKRURERPWPbGNwjh07hszMTBw7dgxWqxWZmZnIzMx0eGZN69at8c033wAAVCoVnn32Wbz66qtYs2YN/vjjDyQmJiI0NBSDBg0CALRp0wYJCQkYPXo0duzYge3bt2Ps2LEYOnSo02dQERERUd0h2yyqKVOmYNmyZdLn22+/HQCwefNm9OrVCwCwf/9+FBYWSnlefPFFFBcXIyUlBQUFBejevTvS0tKg1+ulPMuXL8fYsWPRp08fqNVqPPTQQ3jvvffkugwiIiKqh1RCCOHsQijNaDTC29sbhYWFMBgMzi4OERERVUNN6u86M02ciIiIqLYwwCEiIiKXwwCHiIiIXA4DHCIiInI5DHCIiIjI5TDAISIiIpfDAIeIiIhcDgMcIiIicjkMcIiIiMjlyLZUQ11mf3iz0Wh0ckmIiIiouuz1dnUWYbglA5wLFy4AAMLCwpxcEiIiIqqpCxcuwNvb+5p5bsm1qGw2G06dOoWGDRtCpVLV6rmNRiPCwsJw/PhxrnMlI95nZfA+K4P3WRm8z8qR614LIXDhwgWEhoZCrb72KJtbsgVHrVbjtttuk/U7DAYD/wEpgPdZGbzPyuB9Vgbvs3LkuNfXa7mx4yBjIiIicjkMcIiIiMjlMMCpZTqdDlOnToVOp3N2UVwa77MyeJ+VwfusDN5n5dSFe31LDjImIiIi18YWHCIiInI5DHCIiIjI5TDAISIiIpfDAIeIiIhcDgOcG7BgwQI0a9YMer0eMTEx2LFjxzXzr1y5Eq1bt4Zer0eHDh2wbt06hUpav9XkPn/88ce4++674evrC19fX8TFxV33d6FyNf17tluxYgVUKhUGDRokbwFdRE3vc0FBAcaMGYOQkBDodDq0bNmS/+2ohpre53nz5qFVq1bw8PBAWFgYnnvuOZSWlipU2vpp69atuP/++xEaGgqVSoXVq1df95gtW7bgjjvugE6nQ2RkJJYuXSp7OSGoRlasWCG0Wq1YvHix+Ouvv8To0aOFj4+PyM3NrTL/9u3bhUajEW+88YbYu3eveOWVV4S7u7v4448/FC55/VLT+zxs2DCxYMECsWfPHpGVlSWSkpKEt7e3OHHihMIlr19qep/tsrOzRePGjcXdd98tBg4cqExh67Ga3meTySS6dOki+vfvL7Zt2yays7PFli1bRGZmpsIlr19qep+XL18udDqdWL58ucjOzhY//vijCAkJEc8995zCJa9f1q1bJ15++WXx9ddfCwDim2++uWb+w4cPC09PT5Gamir27t0r5s+fLzQajUhLS5O1nAxwaig6OlqMGTNG+my1WkVoaKiYPXt2lfkfeeQRMWDAAIe0mJgY8fjjj8tazvqupvf5SmVlZaJhw4Zi2bJlchXRJdzIfS4rKxNdu3YVn3zyiRgxYgQDnGqo6X3+4IMPREREhDCbzUoV0SXU9D6PGTNG3HPPPQ5pqampolu3brKW05VUJ8B58cUXRbt27RzShgwZIuLj42UsmRDsoqoBs9mMXbt2IS4uTkpTq9WIi4tDenp6lcekp6c75AeA+Pj4q+anG7vPVyopKYHFYoGfn59cxaz3bvQ+z5gxA4GBgRg5cqQSxaz3buQ+r1mzBrGxsRgzZgyCgoLQvn17vPbaa7BarUoVu965kfvctWtX7Nq1S+rGOnz4MNatW4f+/fsrUuZbhbPqwVtysc0blZ+fD6vViqCgIIf0oKAg7Nu3r8pjcnJyqsyfk5MjWznruxu5z1eaMGECQkNDK/2joktu5D5v27YNixYtQmZmpgIldA03cp8PHz6MTZs2Yfjw4Vi3bh0OHjyIp556ChaLBVOnTlWi2PXOjdznYcOGIT8/H927d4cQAmVlZXjiiSfw0ksvKVHkW8bV6kGj0YiLFy/Cw8NDlu9lCw65nDlz5mDFihX45ptvoNfrnV0cl3HhwgU89thj+Pjjj+Hv7+/s4rg0m82GwMBAfPTRR4iKisKQIUPw8ssvY+HChc4umkvZsmULXnvtNfz73//G7t278fXXX2Pt2rWYOXOms4tGtYAtODXg7+8PjUaD3Nxch/Tc3FwEBwdXeUxwcHCN8tON3We7uXPnYs6cOfjpp5/QsWNHOYtZ79X0Ph86dAhHjhzB/fffL6XZbDYAgJubG/bv34/mzZvLW+h66Eb+nkNCQuDu7g6NRiOltWnTBjk5OTCbzdBqtbKWuT66kfs8efJkPPbYYxg1ahQAoEOHDiguLkZKSgpefvllqNVsA6gNV6sHDQaDbK03AFtwakSr1SIqKgobN26U0mw2GzZu3IjY2Ngqj4mNjXXIDwAbNmy4an66sfsMAG+88QZmzpyJtLQ0dOnSRYmi1ms1vc+tW7fGH3/8gczMTGl74IEH0Lt3b2RmZiIsLEzJ4tcbN/L33K1bNxw8eFAKIAHg77//RkhICIObq7iR+1xSUlIpiLEHlYLLNNYap9WDsg5hdkErVqwQOp1OLF26VOzdu1ekpKQIHx8fkZOTI4QQ4rHHHhMTJ06U8m/fvl24ubmJuXPniqysLDF16lROE6+Gmt7nOXPmCK1WK1atWiVOnz4tbRcuXHDWJdQLNb3PV+Isquqp6X0+duyYaNiwoRg7dqzYv3+/+P7770VgYKB49dVXnXUJ9UJN7/PUqVNFw4YNxRdffCEOHz4s1q9fL5o3by4eeeQRZ11CvXDhwgWxZ88esWfPHgFAvP3222LPnj3i6NGjQgghJk6cKB577DEpv32a+AsvvCCysrLEggULOE28rpo/f75o0qSJ0Gq1Ijo6Wvzyyy/Svp49e4oRI0Y45P/qq69Ey5YthVarFe3atRNr165VuMT1U03uc9OmTQWAStvUqVOVL3g9U9O/58sxwKm+mt7nn3/+WcTExAidTiciIiLErFmzRFlZmcKlrn9qcp8tFouYNm2aaN68udDr9SIsLEw89dRT4vz588oXvB7ZvHlzlf+9td/bESNGiJ49e1Y6pnPnzkKr1YqIiAixZMkS2cupEoLtcERERORaOAaHiIiIXA4DHCIiInI5DHCIiIjI5TDAISIiIpfDAIeIiIhcDgMcIiIicjkMcIiIiMjlMMAhIiIil8MAh4iIiFwOAxwiIiJyOQxwiKjO69WrF8aOHYuxY8fC29sb/v7+mDx5srTi8/nz55GYmAhfX194enqiX79+OHDggHT80qVL4ePjg9WrV6NFixbQ6/WIj4/H8ePHnXVJRCQzBjhEVC8sW7YMbm5u2LFjB9599128/fbb+OSTTwAASUlJ2LlzJ9asWYP09HQIIdC/f39YLBbp+JKSEsyaNQuffvoptm/fjoKCAgwdOtRZl0NEMuNim0RU5/Xq1Qt5eXn466+/oFKpAAATJ07EmjVr8O2336Jly5bYvn07unbtCgA4e/YswsLCsGzZMjz88MNYunQpkpOT8csvvyAmJgYAsG/fPrRp0wYZGRmIjo522rURkTzYgkNE9cJdd90lBTcAEBsbiwMHDmDv3r1wc3OTAhcAaNSoEVq1aoWsrCwpzc3NDXfeeaf0uXXr1vDx8XHIQ0SugwEOERERuRwGOERUL2RkZDh8/uWXX9CiRQu0bdsWZWVlDvvPnj2L/fv3o23btlJaWVkZdu7cKX3ev38/CgoK0KZNG/kLT0SKY4BDRPXCsWPHkJqaiv379+OLL77A/PnzMW7cOLRo0QIDBw7E6NGjsW3bNvz222949NFH0bhxYwwcOFA63t3dHU8//TQyMjKwa9cuJCUl4a677uL4GyIX5ebsAhARVUdiYiIuXryI6OhoaDQajBs3DikpKQCAJUuWYNy4cbjvvvtgNpvRo0cPrFu3Du7u7tLxnp6emDBhAoYNG4aTJ0/i7rvvxqJFi5x1OUQkM86iIqI6r1evXujcuTPmzZt3Q8cvXboUzz77LAoKCmq1XERUd7GLioiIiFwOAxwiIiJyOeyiIiIiIpfDFhwiIiJyOQxwiIiIyOUwwCEiIiKXwwCHiIiIXA4DHCIiInI5DHCIiIjI5TDAISIiIpfDAIeIiIhcDgMcIiIicjn/Dz+PAt42POnBAAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] @@ -2965,13 +9673,7 @@ } ], "source": [ - "(\n", - " cr_gp_df.plot(x='pop', y='pol', title='Cautionary Rule GP policy'),\n", - " esc_gp_df.plot(x='pop', y='pol', title='Const. Escapement GP policy'),\n", - " cr_gbrt_df.plot(x='pop', y='pol', title='Cautionary Rule GBRT policy'),\n", - " esc_gbrt_df.plot(x='pop', y='pol', title='Const. Escapement GBRT policy'),\n", - " # msy_gbrt_df.plot(x='pop', y='pol', title='MSY GP policy'),\n", - ") " + "plt.show()" ] }, { @@ -2992,17 +9694,45 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 16, "id": "dabc6e34-7a25-4b2d-b8b1-294b59f60ca0", "metadata": {}, "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "594baeecd7734c54a95536b73e98c531", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "msy_gp.pkl: 0%| | 0.00/147M [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.heatmap(ppo_pol_pivot)\n", + "ax.set_yticks(list(range(0, 101, 100//n_ticks + 1))) # locations as indices, not values\n", + "ax.set_yticklabels([eval(f\"{ (i / n_ticks) * BOUND * (maxx+1)/ 2 :.2f}\") for i in range(n_ticks)])\n", + "ax.set_xticks(list(range(0, 101, 100//n_ticks + 1))) # locations as indices, not values\n", + "ax.set_xticklabels([\n", + " eval(f\"{ MINWT + (i / n_ticks) * (MAXWT-MINWT) * (maxy+1)/ 2:.2f}\") for i in range(n_ticks)\n", + "])\n", + "ax.set_title(\"PPO policy\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "id": "917f548a-fa8d-4e0c-a6f4-3c799795418a", + "metadata": {}, + "outputs": [], + "source": [ + "wt_indexes = [40, 50, 60, 45]\n", + "\n", + "ppo_pol_1 = ppo_pol[ppo_pol.mean_wt == ppo_pol.mean_wt[wt_indexes[0]]]\n", + "ppo_pol_2 = ppo_pol[ppo_pol.mean_wt == ppo_pol.mean_wt[wt_indexes[1]]]\n", + "ppo_pol_3 = ppo_pol[ppo_pol.mean_wt == ppo_pol.mean_wt[wt_indexes[2]]]\n", + "ppo_pol_4 = ppo_pol[ppo_pol.mean_wt == ppo_pol.mean_wt[wt_indexes[3]]]\n", + "\n", + "\n", + "\n", + "ppo_plot = pd.DataFrame(\n", + " {\n", + " 'biomass': list(ppo_pol_1.biomass),\n", + " f'action at m. wt = {ppo_pol.mean_wt[wt_indexes[0]]:.3f}': list(ppo_pol_1.pol),\n", + " f'action at m. wt = {ppo_pol.mean_wt[wt_indexes[3]]:.3f}': list(ppo_pol_4.pol),\n", + " f'action at m. wt = {ppo_pol.mean_wt[wt_indexes[1]]:.3f}': list(ppo_pol_2.pol),\n", + " f'action at m. wt = {ppo_pol.mean_wt[wt_indexes[2]]:.3f}': list(ppo_pol_3.pol),\n", + " }\n", + ")\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "id": "ec3073c1-e293-4dab-bf6c-374a2ca55d7a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ppo_plot.plot(x='biomass', title=\"Fishing mortality as fn of biomass and mean weight\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "id": "3ba12feb-0253-471b-999f-4d4fe049f4fa", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_1226226/693145116.py:8: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + "/tmp/ipykernel_1226226/693145116.py:9: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + "/tmp/ipykernel_1226226/693145116.py:12: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + "/tmp/ipykernel_1226226/693145116.py:13: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + "/tmp/ipykernel_1226226/693145116.py:16: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + "/tmp/ipykernel_1226226/693145116.py:17: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + "/tmp/ipykernel_1226226/693145116.py:20: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + "/tmp/ipykernel_1226226/693145116.py:21: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n" + ] + } + ], + "source": [ + "cr_pol_df = cr_gbrt_df[cr_gbrt_df.biomass <= 7][['biomass', 'fishing_mortality']]\n", + "cr_pol_df['policy'] = 'cr'\n", + "\n", + "esc_pol_df = esc_gbrt_df[esc_gbrt_df.biomass <= 7][['biomass', 'fishing_mortality']]\n", + "esc_pol_df['policy'] = 'esc'\n", + "\n", + "ppo_pol_df_1 = ppo_pol_1\n", + "ppo_pol_df_1['policy'] = 'ppo_mwt_0.397'\n", + "ppo_pol_df_1['fishing_mortality'] = ppo_pol_df_1['pol']\n", + "\n", + "ppo_pol_df_2 = ppo_pol_2\n", + "ppo_pol_df_2['policy'] = 'ppo_mwt_0.494'\n", + "ppo_pol_df_2['fishing_mortality'] = ppo_pol_df_2['pol']\n", + "\n", + "ppo_pol_df_3 = ppo_pol_3\n", + "ppo_pol_df_3['policy'] = 'ppo_mwt_0.591'\n", + "ppo_pol_df_3['fishing_mortality'] = ppo_pol_df_3['pol']\n", + "\n", + "ppo_pol_df_4 = ppo_pol_4\n", + "ppo_pol_df_4['policy'] = 'ppo_mwt_0.446'\n", + "ppo_pol_df_4['fishing_mortality'] = ppo_pol_df_4['pol']\n", + "\n", + "df = pd.concat([\n", + " cr_pol_df,\n", + " esc_pol_df,\n", + " ppo_pol_df_1[esc_pol_df.columns],\n", + " ppo_pol_df_4[esc_pol_df.columns],\n", + " ppo_pol_df_2[esc_pol_df.columns],\n", + " ppo_pol_df_3[esc_pol_df.columns],\n", + "])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "id": "6e7ab2f3-bdeb-44fd-8fa4-579c8fd9b6e3", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "from plotnine import geom_line, scale_color_manual\n", + "\n", + "colors = {\n", + " 'ppo_mwt_0.397': '#94D2EC',\n", + " 'ppo_mwt_0.446': '#5FC3ED',\n", + " 'ppo_mwt_0.494': '#32AEE2',\n", + " 'ppo_mwt_0.591': '#1B96CA',\n", + " 'esc': '#3CCA33',\n", + " 'cr': '#C7324F',\n", + "}\n", + "\n", + "( \n", + " ggplot(df[df.biomass < 1.5], aes(x='biomass', y='fishing_mortality', color='policy')) \n", + " + geom_line() \n", + " + scale_color_manual(values=colors)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "42f0c0d7-ee61-425a-9b37-b37370df2982", + "metadata": {}, + "source": [ + "## Variable density plots" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "id": "5ec17309-a2a8-4a7e-a98a-5edc6aacf22c", + "metadata": {}, + "outputs": [], + "source": [ + "@ray.remote\n", + "def variable_values_over_ep(env, agent, n_obs=1):\n", + " obs1_list = []\n", + " obs2_list = []\n", + " act_list = []\n", + " rew_list = []\n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " action, info = agent.predict(obs)\n", + " new_obs, rew, term, trunc, info = env.step(action)\n", + " obs1_list.append(obs[0])\n", + " if n_obs == 2:\n", + " obs2_list.append(obs[1])\n", + " else:\n", + " obs2_list.append(0)\n", + " act_list.append(action[0])\n", + " rew_list.append(rew)\n", + " obs = new_obs\n", + " if term or trunc:\n", + " break\n", + " return obs1_list, obs2_list, act_list, rew_list\n", + "\n", + "\n", + "def get_var_distributions(agent, agent_name, env, n_obs=1):\n", + " var_tuples_of_lists = ray.get(\n", + " [\n", + " variable_values_over_ep.remote(env, agent) for _ in range(10)\n", + " ]\n", + " )\n", + " if ray.is_initialized():\n", + " ray.shutdown()\n", + " \n", + " obs1 = np.array([tup[0] for tup in var_tuples_of_lists]).flatten()\n", + " obs2 = np.array([tup[1] for tup in var_tuples_of_lists]).flatten()\n", + " act = np.array([tup[2] for tup in var_tuples_of_lists]).flatten()\n", + " rew = np.array([tup[3] for tup in var_tuples_of_lists]).flatten()\n", + "\n", + " biomass = BOUND * (obs1 + 1)/2\n", + " if n_obs==2:\n", + " mean_wt = MINWT + (MAXWT - MINWT) * (obs2 + 1)/2\n", + " else:\n", + " mean_wt = obs2\n", + " mortality = (act + 1)/2\n", + "\n", + " return pd.DataFrame({\n", + " 'agent': agent_name,\n", + " 'biomass': biomass,\n", + " 'mean_wt': mean_wt,\n", + " 'mortality': mortality,\n", + " 'rew': rew,\n", + " })" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "id": "36923b0c-e754-4b3b-8321-6dab4bf15ec3", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-19 20:32:29,101\tINFO worker.py:1752 -- Started a local Ray instance.\n", + "2024-04-19 20:32:38,134\tINFO worker.py:1752 -- Started a local Ray instance.\n", + "2024-04-19 20:32:45,098\tINFO worker.py:1752 -- Started a local Ray instance.\n" + ] + } + ], + "source": [ + "ppo_distr_df = get_var_distributions(\n", + " agent=ppo, \n", + " agent_name='ppo', \n", + " env = AsmEnv(config=PPO_CONFIG), \n", + " n_obs=2,\n", + ")\n", + "\n", + "cr_distr_df = get_var_distributions(\n", + " agent=CautionaryRule(env=pol_env, **cr_gbrt_args), \n", + " agent_name='cr', \n", + " env = AsmEnv(config=PPO_CONFIG), \n", + " n_obs=2,\n", + ")\n", + "\n", + "esc_distr_df = get_var_distributions(\n", + " agent=ConstEsc(env=pol_env, **esc_gbrt_args), \n", + " agent_name='esc', \n", + " env = AsmEnv(config=PPO_CONFIG), \n", + " n_obs=2,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "id": "79570a4c-2788-4b43-abdf-7257921bfff3", + "metadata": {}, + "outputs": [], + "source": [ + "vars_df = pd.concat([ppo_distr_df, cr_distr_df, esc_distr_df])" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "id": "92f50a18-9883-4f6e-acf6-d16c756bd9dd", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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cmyOv2x0+/1Cjuru7x7UeSXJ53Qrkhz+PA6PsA2gFgHV1dTp06NC47wUAAAAAADAeBIBIicm0ALe1tUmSfNm+Ec/r6emJBo35Ab+cjqF/3A0ZKsvPk2EYMk0zPMhjAq3AVhvwwfr6EfcBrKycFz3esGHDuO8DAAAAAAAwHgSASInYCkDPOCoA+4PB6Hu9owSAzc3NkiTDMJTnH7la0ON0qSg7W1I4OGyJtBmPR14kAOzr749WHg6lqmJ+9Hjjxo3jvg8AAAAAAMB4EAAiJSZaAdjR3i6rNm+kCkDTNKOVggGvV06Hc9Rr5wX8cjtdkqSGhgaFgsNX8Q3FqgCUwu29w8nJKVJOTrEkKgABAAAAAEDiEQAiJSa6B6AV6kkjB4Dt7e3RNtzcrNH3CpTCrcAlueF9AoPBoA41jW9/PrfPLX9e+HMZKQCUFJ0ETAAIAAAAAAASjQAQKTHRKcDWABBp9ABQkpwOh/xez5iv7/d6o+c3Nzervz845vdKUm5kGnB9fb3MEfYRtALAjRs3jngeAAAAAADAZBEAIiUGVQCOowXYqgB0eVxyeVxDnmOaZjRgDHi9koxxra0wO1wFGAqF1DzOKsDc4nAbcG9fX3QPwqFURQaBtLa2at++feO6BwAAAAAAwHgQACIlrIDO4XDJ5Rp7hd5YJgB3dXVF238DvpEHhQzF53bL7/VKkpqaW9Tf3z/m9+aU5ESPDzY0DHueVQEoSevXrx/3GgEAAAAAAMaKABApYQWA46n+kwZae0cKADsj1zYMQ37P2MPFWNZEYNMMqbmpeczv8wV88vjckqSD9fXDnldRMTd6zD6AAAAAAAAgkQgAkRLRAHAcA0BMSW1WAJgzfADYEWkv9rndMozxtf9avG73wF6ALc3RisJRGVJOcbgK8ODBg8Oe5vMGVFQ0TVJ4H0AAAAAAAIBEIQBESlh7AI5nAEhXV1e0HdcXGDoADAaD6unpkaRoG+9EFQTCawuFQmppaRnz+3KKw4NAWlpbo2sZSlXFfEm0AAMAAAAAgMQiAERKWBWAHk/WmN/THtn/Txq+Bbirsyt6PNH2X0uWxyuvO9zO29TUNOZpvVYFoDTKPoCRQSBbtmwZ1z6DAAAAAAAA40EAiJSwKgB946gAtPb/kyRv9tDBYVd3OAB0GIa87qGnBI+HVQXY39+v1tbWMb0nuyhHVudxwwhtwNYgkN7eXm3fvn1yCwUAAAAAABgGASBSIloB6B1HBaA13EOS1z90dV9XVzgADFfuTWz/v1jZPq/cznCQ2NTUFN6IcBQOp0OBgvAQkZH2AayqnB89ZhAIAAAAAABIFAJApER0D0DP2CsArem+Hr9HhuPIcC8UCkX33MuaZPvvAEMF2eFBJb29vero7BjTu2IHgYSGaR0uK50ppzPcYkwACAAAAAAAEoUAECkRnQLsHfsU4GjVoH/o4R49PT3Rffp8kb374iHHlyWnI/yoNDU1j+k9uZFBIH39/WppHvo9Tqdb5WWzJTEJGAAAAAAAJA4BIFJiYArw+ANA73ABYHd39DieAaBhGMrNCrcqd3Z2qLend9T3ZEcCQGnkNuCKirmSmAQMAAAAAAAShwAQKTEwBXgCAWBg6ACwO9L+63I65XDE90c7z++P7ijYNExFXyxfwCuPLxxCjrgPYEV4H8Da2tpoKAoAAAAAABBPBIBIOtM0x10B2NvXp96+vvB7RmgBliSva/LTfw/ncjoV8PkkSa2trQoGgyO/wQhPA5akxsbGYU+zJgGbpqnNmzfHZ7EAAAAAAAAxCACRdL29verv75ckecdYAWgNAJGGDgBN01Rvb7g11xvH9t9Y+YFA5F4htbS0jnq+FQA2Nzerr69/yHOqKudFjxkEAgAAAAAAEoEAEEkX2+rq9Y5tCnBHTADoGaIFOHYASKICQJ/bHb12c3NT9H7DySnKliSZkg4dGroKsKCgKvo1IAAEAAAAAACJQACIpBsU5nmyxv2eoSoArfZfKTEtwJaCQLhisb+/X+3t7SOeGyjMjh4P1wbscDhUGRkEQgAIAAAAAAASgQAQSTeZCkCHwyG398gKv+7ucADodDjkcjrjsMqhBXw+OZ3hx6Z5lGEgbq9bvki14kj7AFZVhgeBEAACAAAAAIBEIABE0g2q5hvjEJCBCcAeRcfxxujp6Q6/7k5c9Z8kGTKU7w+vuaurS93d3SOeb+0D2NDQMOw5FZFBIHV1dTp06FCcVgoAAAAAABBGAIikG1QBOMYhIB3W1OChJgCbpnp6IgNAXInZ/y9WbpZfhhFOIUerAsyOtAG3trVFh5QcrqqCQSAAAAAAACBxCACRdIMrAMfYAhzZb88zRADY198v0wyFX0/g/n8Wp8OhHJ9PktTW1hadaDwUqwJQGr4NuJIAEAAAAAAAJBABIJJuUAA4hiEgpmlGqwa9Q0wAjq2sS0YAKEn5kWEgpmmqubll2PPGMggkJ6dIuTklkqSNGzfGcZUAAAAAAAAEgEiB8VYAdnd3KxgKV/gN1QIcGwC6kxQAelxuZXk8kqSWlmaZpjnkeS63U1m54ZBz5H0Aw5OA169fH+eVAgAAAACAqS45aQniwpnA6baJFrv22MEZXm8gup/ecLq6ugbOD3h1+BQQKwB0OZ1yOEa+VjzlBwLq6u1VMBhUW2ubcvPyhjwvpzBHXa1damxsHPZzraqcr02bX9bGjRvlcDhG/ZrEi/V9SeeframC75H98PykD75H9sPzk174PtkPz1D64HtkPzw/mKoIANNIQUFBqpcwIU6nc9DaQ5FqPsNwKDs7d9Swq6+vL3rsC2TJ6RxcuNrbG37d43LJMdSI4ATJ9vnkdjrVFwyqqblZBYVDf39yinNUX1uv9o4OhUIhZWUd2fY8veYYSeE9Bdvb21VTU5PQtR8uNzc3qffD+Bz+DMFeeH7sjefH3nh+7I9nyN54huyN58feeH4w1RAAppGmpqZUL2FccnNz5XQ6FQwG1draGv24tRee1+sfdjJurJaY97q8LgWDoUGv9/b2SAq3/4Y0dCtuouQHAjrY2qqenm61t7crK+vIqcaBgoF9APft26fq6uojziktmRM9XrlypXJyco44JxGcTqdyc3PV2tqqYDCYlHti7IZ7hmAPPD/2xvNjbzw/9sczZG88Q/bG82Nvdn1+CIuRaASAacROv5zGK3btbW1tkiSvxz/s3nmxrAEgDochl8clxYR8wWAwem2P06kk53/KyfKpsa1NIdPUoUNNqqo6srovUBCQofDSGhsbVVVVdcQ55eUDAeDatWt1/vnnJ3DVR4r9OsKe+P7YF8+P/fH9sS+en/TA98i+eIbsj++PffH8YKphCAiSzgr0PN4jq+WG0mWdn+U5fPu/lEwAjuUwHMr1hz+Pjo72Qe3K0XNcjuggkMZDh4a8js8bUHFRuO2XScAAAAAAACCeCACRdNYUYK9nbAGgFRi6szxHvDY4AEzNJq75/oHPo7m5echzAoXhNuCmYQJAKTwIRGISMAAAAAAAiC8CQCRdNAAcawVgZAqwxzd8AOgwHHI6UhMAupxOBbxeSVJLS0t0yEksax/AtvZ29fQMve9hRcVcSdKWLVvU39+foNUCAAAAAICphgAQSWdV9Hk9gXGd7/EPHwCmqvrPkh8Ify6hUEgtLS1HvJ5dODAIpKlp6CpAqwKwt7dX27dvT8AqAQAAAADAVEQAiKSzKgA93iMHZhwuFAqpu7s7fP6QLcDhPffcKdj/L1aWxyOvO7yG5uZm6bDhJoGCgbDz0DBtwJUV86LHtAEDAAAAAIB4IQBE0kUrAL2jVwB2d3dHB/seEQCapvr7IwGgM7UVgJKU5w9/Pn19fWqPhJwWl8clXyDcJtzY2Djk+8tKZ8rpdEtiEAgAAAAAAIgfAkAk3cAQkNErADsj+/9JRwaAff39MiOVdnYIAHN8Pjkd4Ueqqan5iNetfQCHqwB0Ot0qL5stSdqwYUNiFgkAAAAAAKYcAkAk3XgqALsi50pDBIB9A4My3CneA1CSDMNQXmQicFdXp3p6ega9bk0CbmlpGXbIh9UGTAAIAAAAAADihQAQSTdQATh6ANg5KAD0Dnqtr29gmq4dKgAlKc+fJcMwJB1ZBZgdqQA0JTU1NQ35fisArK2tjX6dAAAAAAAAJoMAEEnV19cXndzrHcMQkK5IC7DDYcjlGTzow6oANAwj2nqbak6HU9k+nySpra1V/f3B6GuBwtEHgViTgE3T1JYtWxK4UgAAAAAAMFXYIzXBlBFb0TeWFmBrD0BPlkcyBr9mVQCGq/8OezGF8iNtwKZpqqWlOfpxT5ZHHl94yEfjsJOA50aPmQQMAAAAAADigQAQSTWopXcMQ0CsPQCPmACsgQpAu7T/Wrxut7I84fU2N7dEB5VIMYNAhpkEXFhYHQ1GmQQMAAAAAADigQAQSRW7r92YKgCjAaD3iNf6+vokSS6bBYCSosNAgsF+tbW1RT9utQE3NzcrFAod8T7DMKJVgAwCAQAAAAAA8UAAiKQaFAB6/KOeb+0B6M5yD/p4KBRSMGjPCkBJyvZ5o+uKHfhhVQAGQyE1NzcP+V5rH0ACQAAAAAAAEA8EgEiqwRWAIweAoVBI3d3dko5sAbaq/yTJ7Ro8HMQejGgVYE9PTzTIzC7Mjp4x3CAQaxJwXV3dsOcAAAAAAACMFQEgkmrwHoAjB4Dd3d2yds9z+w4PAPujx26nPX+Mc/1Zchjh4SRNTc2SJF/AJ5c7XBk4WgAoUQUIAAAAAAAmz57JCTLWePYAtKr/JEWn51qsCcCS5HLasQJQchgO5WSFB520t7epv69PMgbagIefBEwACAAAAAAA4ocAEEkVWwHoHWUKcGwAOFwFoNPhiFbZ2VFeYKDKsbm5RZIUKAgHn02HDg2aEGzJySlSbk6JJAJAAAAAAAAweQSASKrxVABa++ZJkvuICkD7TgCO5XG65PeGw8uW1haFQqYCkX0A+/oHTwiOVVkZrgIkAAQAAAAAAJNFAIikiq0AdLt9I547uAJwcADY358eAaAk5fvDQWcwGFRbW6uyCwaCz+H2AayKtAFv3LhxyCpBAAAAAACAsSIARFJZFYBej18Ox8g/flYA6HI75Ths0Ed/f7gF2J0GAaDf65E7sk9hc3OzsnL9cjjCbcujDQJpa2vTnj17krNQAAAAAACQkQgAkVRWBaDHO/IEYGmgBfjw6r9QyFQwGJQkuUYJEe3BUH5kL8Cenh51dXfJnx+uAhw2AKycHz2mDRgAAAAAAExGOqQnyCCxFYCj6YpUAB4+AMSq/pPSowVYknKyfNFhJc3NzcqOTAIeLgCsKD9KRuR8AkAAAAAAADAZBIBIKqsC0DuGCsDuSAWg54gAsC96nC4BoMNwKNcf/pzb29vlzQ3vf9jV3T1oX0SL1+tXcVGNJAJAAAAAAAAwOQSASKrxVAB2RysADxsA0hdTAZgWLcBhef6Bz9l0haLHh5qahjzfagPeuHFjYhcGAAAAAAAyWvqkJ8gIAxWAgRHPM00zJgAcugXYkORyps+PsNvpVMDrlSR1mz0yIh8ffhDIXEnS5s2b1dfXN+Q5AAAAAAAAo0mf9AQZwaoAHG0ISE9vr0KmKenICsC+SAuw0+mUojFaerCqAE2Z8gTCweahxqEDwKqKcAVgX1+ftm3blpwFAgAAAACAjEMAiKSKVgB6skY8z9r/T5I8h7cARyoAXY702P8vlt/rlcflkiQ5ssLrP3SocchzKyvnRY/ZBxAAAAAAAEwUASCSqssa7DFaABhp/5WGagEOVwCmU/tvrPxIFaDDFw4A29rb1TtEi29pyQy5nOHPnQAQAAAAAABMVHomKEhb0RbgUYaAdMVUALqzDmsBjgwBcafJBODDZWdlyWE45PK7oh9rGmIfQKfTrfLyOZIIAAEAAAAAwMQRACKprBbg8VUADgSAoVBIoVB4gq4rTQNAh2Eo1581KAAcfhBIuA2YScAAAAAAAGCiCACRNKZpRiv7vKNVAEYCQKfTIadrIOjrj1T/SenbAixJef4sOVwOOdzhz2G0ALC2tlbt7e1JWx8AAAAAAMgc6ZugIO309PREq/dGrQCMBIXDTQCW0nMIiMXtdCnL44lWAQ4XAFbFDALZvHlzUtYGAAAAAAAyCwEgksZq/5XG3gJ85ACQzKgAlKQ8vz8aADY3NysYDB1xjlUBKEnr169P2toAAAAAAEDmSO8EBWklNgD0esfWAnx4BaAVABqGIacjvX98s31eebLDAWfINNXc3HTEOQUFlcrKypXEIBAAAAAAADAx6Z2gIK3ETvb1uEeuAOwZJQAMh39GfBeYdIYKCnOif9q3b9+RZxiGKivmSmIQCAAAAAAAmBgCQCTNoBbgUSoAu0cJAF1pXv1nKSrMkcMZDjJrd+4c8hyrDZgKQAAAAAAAMBGZkaIgLXR0dESPvSPsAdgfDKrPCvo8hweAQUmS05m+A0BiuZ0ueQLhNuDmpib1B4NHnGMFgAcPHtTBgweTuj4AAAAAAJD+CACRNIOHgAxfAWi1/0pHVgAGg5lVAShJ2fnhMDRkmtpZW3vE61WV86PHtAEDAAAAAIDxypwUBbY3aA/AESoAe3p6osdub0wAaJoDLcAZUgEoSfmF2dHjodp8mQQMAAAAAAAmgwAQSTNoCvAIAWB3bAVgTAAY2x6b7hOAYwXyBr4WjYcOqalp8DTgQCBfeXllktgHEAAAAAAAjF/mpCiwvTG3AMdUALpiA8D+gQAwk1qAs7J9cjgGJhpv3br1iHOsKkBagAEAAAAAwHhlTooC2xtrC/CgCkCfK3ps7f8nSS5n5vzoGoYhf44v+uft27crGAwNOqeqcmAScCg0+DUAAAAAAICRZE6KAtuzKgBdTo+cTtew51kVgA6HY9C0X2v/P0lyOTJnD0BJ8se0AXf39GjPnt2DXq+sCA8C6ezs1K5du5K6NgAAAAAAkN4IAJE0VgDo8Q5f/ScNVAC6fS5poDM2GgAahiFHBrUAS1Ig1zfoz4e3AccOAqENGAAAAAAAjEdmpSiwtY6ODkmSd4T9/ySpuztcAThoArAG9gDMpAEglthBIJK0d+/eQXsmVpQfJcMIf95MAgYAAAAAAOOReUkKbMvaA9A9wv5/ktTTE64AdB0RAIYrADNpAIglkOuLLXaUKWnbtm3RP3s8PpWUzJBEBSAAAAAAABifzEtSYFtWRZt3lAAw2gJ8WABoDQGJ3RcwUzicTvkCHkmS1xXeH3Hr1q0yY86prJgrKTwIBAAAAAAAYKwIAJE00T0AR2kBtoaAuH1TpwJQGmgDNiKlgK1tbaqvq4u+XhUZBLJ161b19vYmfX0AAAAAACA9ZWaSAluyWoA9I1QAmqYZDQAHtQCbpoLB8B6ALmdm/thak4C7+/rljKSAscNArArA/v7+I4aEAAAAAAAADCczkxTY0lhagHt7exUyw42vsS3A/cGgzMjHnY7MawGWpOzcga9LaV6eJKl250719fVJkior50dfpw0YAAAAAACMFQEgkmYsLcDW/n/S4BZgawKwlLktwP6YADA3yycpXO23a9cuSVJpyQy5XF5JTAIGAAAAAABjl5lJCmwpWgHoHT4AtNp/JcntdUWPrQEgUua2ALu9Lnl84c+5PxiS3xMeCrJ9+3ZJksPhVEX5HElMAp7q+vv7FQqFUr0MAAAAAECayMwkBbYU3QPQ7Rv2nNgKwNg9AIMxFYDODK0AlKRApAqwqaNDM0tLJEn79++PhqdWGzAtwFPTrl279JGPfEQzZ87Uscceq+985zvRvTEBAAAAABhO5iYpsJ2Ojg5JkmeECsDuQRWAsXsADlQAZnQAGBkE0tzZqZqSYkmSKWnHjh2SpKqKeZKk3bt3q62tLSVrRGps27ZNF154oZ599ll1d3errq5O99xzj2655Zbo/pgAAAAAAAwlc5MU2IppmtEKQO8IewD2RCoADUmuQS3A4SqncPhnJGydqWZVAIZMU4akgkD4a2W1AVdGAkCJNuCppKenR9dff72ampokSSe97xRVzKuUJP35z3/Www8/nMLVAQAAAADsjgAQSdHV1RWtUnKPMAXY2gPQ5XHJMAaCvv7+cAVgJlf/SVIgb6A9uqm9QzNLSyVJh5qa1NTUpKqYScAMApk67r//fm3atEmS9N7/d4Wu/99/06f//P9UMiPcJv6Nb3wjGg4CAAAAAHC4zE5TYBtW9Z8keUcIAK09AF0xE4ClwysAM5fX75HLFf4cD3V0aHpJcbTecfv27crLK1PAny9JWrduXWoWiaRqamrS3XffLUmqOXa6Lrz5EkmSL9unj3z7OklSa2urfvCDH6RsjQAAAAAAe8vsNAW2YQ2xkCTPSC3AkQpAt8c16OPWFGCX05mA1dmJIb81CKS9Q36PR+X5+ZKk7Tt2yJRUVXW0JALAqeLHP/6x2tvbJUnv+/IH5IiZgn3U6XM176zwz8Mjjzwy6DkDAAAAAMBCAIikiA0mRtoDsLe3V5Lk8gyuAOzvnxoVgFLMIJCODpmmGZ0G3NnZqboDB1RdtUBSuAU4FAqlbJ1IvP7+fv3whz+UJM04YabmnHrUEeec9/HzJUktLS1aunRpMpcHAAAAAEgTmZ+mwBZiW4A9Ht+w51lTgGMHgJimOWVagCUpkBv++vQGg2rv7tG0okK5Ip/3tu3bVR2pAGxvb9euXbtStk4k3t/+9jft379fknTOv503aF9My/xzFqhoWpEk6Xe/+11S1wcAAAAASA+Zn6bAFjo6OqLHI7UA98YMAbFY4Z80RQLA/IGvT2N7u1xOp6YVhwOeXTt3qrxsbvR12oAz269+9StJUqAgoGMvOX7IcxwOh05+/6mSpJUrV+rAgQPJWh4AAAAAIE1kfpoCWxjUAuwdOgA0TXNgCrB3oAU4NgB0TYEA0J/tlTOyz9uhtvDebzNLwm3Aff396uvzyeEIB6QEgJmro6NDTz31lCTp5Pe9S26ve9hzT7z8JEnhZ2jZsmVJWR8AAAAAIH1kfpoCWxg0BMQ99BTgvr4+mZHj2BbgYP/UqgCUYSiQF24DbowMfyjLz1NWZF/E3bv2qLxstiQCwEz2z3/+MzoV+8T3njziuRVzK1U2p1yS9MwzzyR8bQAAAACA9DIF0hTYwaA9AL1DB4BW9Z80eApwf2QCsDRFAkBJ2ZE24EPt7QqZphyGoenFxZKkffv2qaJ8niQCwEz217/+VZLkzw/oqCGGfxxu4QWLJEkrVqyITg0GAAAAAEAiAESSjGUKcE9kArA0fAuw1Rqb6awAsD8UUmtnODydXhIOAEOmKb+/TJK0c+dOtbW1pWaRSJje3t5oJd9xFx8np9s1yjukBectlBSupF2+fHlC1wcAAAAASC9TI01Byg1qAfYMUwEYaXeUDhsC0h+uAHQ6HDJ05BTUTBTIG/gaWW3ARTk5yvZ5JUnB/kD0daoAM8/LL7+s1tZWSdLxl500pvfMOnm2vNnh1vEXX3wxYWsDAAAAAKSf0ctKMkB7e7vWrl2rrVu3atu2bdq6dataWlokSd/85je1aNGiCV23rq5On/jEJ0Y97/Of/7wWL148oXtkCqsF2OXyyuFwDnlOb2wFoGegArA/UgE4Vdp/JckX8Mjldqq/L6hDbe2aXVYqQ9L04hKt27NHPd3e6Lnr1q3TaaedlrrFIu6s4R/uLI8WnHvMmN7jdDs186RZ2rh8vVauXJnI5QEAAAAA0syUCABfffVVff/730/oPXJzc+UYJqDyeDwJvXc6sCoAvcNU/0mH7QEYMwSkv3/qBYCSoey8LDU3tEcrACVpRkmx1u3ZI7c7W/6sAnV2NVEBmIGsCr55Z8yX1++VaZqjvCNszrvmaOPy9Vq/fr2am5uVn5+fwFUCAAAAAMbijjvukCTNmDFDN9xwQ0rWMCUCQEkqKCjQ7NmzNWfOHFVWVuq+++6L6/XvvfdelZWVxfWamaSjo0OS5PEOvf+fNBAAGobkdA1UCQaDAy3AU0l2vl/NDe1q7uhQ0DTlNAzlB/zK9/vV3NmpgL+cADAD7d+/X1u2bJEkzT/r6HG9d/a75kiSTNPUa6+9posvvjju6wMAAAAAjM/Xv/51SdI555xDAJhI5557ri644ILon5mQmXxWBaDHPUIFYKQF2O11K3arv6lZASgF8sNfq6BpqrmjQ0XZ2ZLCw0Cad+6Sy1UkSdqwYYOCwaCczqFbq5FeYvfvm3/m+ALAmmNnyOV1qb+nXytXriQABAAAAABImiJDQAhGUs/aA3C4ASDSQAVg7AAQmVIoFA4AXVNkArDFmgQsSY1tA6H19OLwNOCAv1xS+Gu7Y8eO5C4OCfPCCy9IkgKF2apaUD2u97p9bk0/boYkacWKFfFeGgAAAAAgTU2tRAUpE90DcIQW4N5oADgwACQYCkb3P3MOMzwkU3l8LnkieyHGBoA5WT4VZWfLHwkAJWnt2rVJXx/izzRNvfTSS5Kko06fO+y+oiOZfUq4Dfjtt98eNH0bAAAAADB1EQDGyT333KOrr75aH/jAB/Sxj31Md999t1atWpXqZdlGtAV4LBWAMQNAgpEJwNLUawGWDGVH2oAPHda2PqOkWD5vsQwjHIqyD2Bm2L59u/bu3StJmrd4/oSuMfvUoyRJ/f39evPNN+O2NgAAAACI1d3drWXLlum2227TGWecoZKSErndbuXk5Oioo47Sv/7rv+rvf//7mK7V19enH/7wh1q8eLEKCwvl9/s1d+5c3Xrrrdq0aZOk8CANwzBkGIaef/75Udf205/+VO9973s1bdo0+Xw+5eXlaeHChbrtttu0efPmEd8/1L3eeOMNfexjH9OsWbPk8/lUVFSk8847Tw8//LBCodCQ17GuYVm+fHn0Y7H/e/jhh8f0dZqMKbEHYDJs2bJFfr9fDodDjY2NWrFihVasWKHFixfr9ttvl9vtHvUaS5Ys0aOPPjrs61dffbWuueaaeC47oazqJYfDod7I/n5Zvmx5vd4hz7fOcfvc0bbt2OmnLodDjpgHZyrILgjoUF2bWjo7FTRNuV3hR3ZGWane3FGrrKxSdXbu1+bNm1VQUDDu61u/iPLy8sY8aRaJ89Zbb0WPjzl3kawfd8PQsM/N4eaeOi96vGnTJl1++eVxXSMG8PzYW+x/gyby+xGJxfNjfzxD9sYzZG88P/bG8xM/CxYsGHI7qvb2dm3dulVbt27VkiVL9L73vU9LlixRdmRf+8MdOHBAl156qd55551BH9+yZYu2bNmiX/7yl/rlL3855nUtX75c1157bbS4wtLT06N169Zp3bp1euCBB3TXXXfpi1/84piu+T//8z/68pe/PKhIqaenR88//7yef/55LVu2TH/4wx/kctk3ZrPvytKAx+PRu9/9bp111lmaOXOm/P5we+uuXbv0pz/9Sc8995xefvllBQIB3XrrraNer6OjQ/X19cO+3tnZmZb7GRqGMagF2BgmxLMqAN3emBbgKV0BKOUWBCRJpsJtwBUF+ZKkgNersrw8BbLK1dm5X6tXr57Uz8ZEWk0Rf9a+fbmleSqbVaaBaTiGxpp9B/IDKplRqoO19XrrrbfS8ndGuuH5sTfDMHgObIznx/54huyNZ8jeeH7sjedn8jo7O5Wfn6/zzz9fJ5xwgqZPny6/36/W1latXr1ajz32mPbv369ly5bp3/7t3/T73//+iGt0d3froosuim5rVVxcrI9//OM69thj1dvbqxdffFG//vWv9dGPflSXXnrpqGv629/+pve9733q6+uTw+HQpZdeqgsvvFBVVVXq7u7W66+/rkceeUQtLS360pe+JEmjhoAPPfSQHn30UZWUlOiGG27QscceK4fDoVdeeUU/+9nP1NPTo6VLl+qee+6JXtPy+OOPS5Le//73S5KOOeYYfeMb3zjiHieeeOKon9tkEQBOQkFBgW666aYjPl5TU6NPf/rTys3N1bJly/T3v/9dV155paqrR97QPxAIqLS0dNjX/X7/oEDM7hwOhwzDkGma6ujokBRuAR7qX1lM04wZAjIQAFoTgKWpGQBm5/tlGJJpSvUtLSqPBICSNL20RG/5y6VGac+ePaqrq1NxZEDIWBmGIYfDoVAoxL9+2cDLL78sSZoT2ccvHP0akkyN59tTc+x0Hayt15tvvplWvzPSDc+PvcX+N2i4lgykDs+P/fEM2RvPkL3x/NibXZ+fdAyLf/nLX+rCCy8ctuPxm9/8pq699lotXbpUf/jDH/TSSy/pzDPPHHTO3XffHQ3/Fi5cqGeffXZQLnLDDTfo5ptv1oUXXqhly5aNuJ79+/fruuuuU19fn0pLS7Vs2TKddtppg8756Ec/qs9//vO69NJLtXbtWv33f/+33v/+92v+/OG3YHr00Ud1zjnnaNmyZcrLy4t+/JprrtGHPvQhXXDBBQoGg/re976nz372s/J4PNFzrrzyykHXKi4uPuJjyUIAmEDXXnut/va3v6m3t1erVq0aNQC87rrrdN111w37ekNDg5qamuK9zIQpKCiQ0+lUKBRSe2QPO6fTEw36YvX09Mr61et0O6KhRX9fn6RwBGIYUshGv6CTwXAa8uf41NHarfqWVoViwpzqwgJl+yujf37xxRd17rnnjuv6TqdTBQUFamlpIShKsfr6em3btk2SNP3Emerp6ZHX640GwEM9N8OpXFClN55YpS1btmjnzp3Kzc1N1LKnNJ4fe4v9b1A6/bdzquD5sT+eIXvjGbI3nh97s+vzM95iDju47LLLRnzd7/frV7/6lSorK9XR0aFf/epXgwLA3t5ePfDAA5Ikl8ulxx57bMiiqJNPPln33nuvbrzxxhHv953vfEeHDh2SJP3xj388IvyzVFVV6Q9/+IMWLlyoYDCo73//+/rxj3887HULCwv1pz/9aVD4ZznnnHN01VVX6bHHHlNDQ4NWrVqlxYsXj7jOVJl6JVVJ5PP5VFNTI0mqq6tL8WpSq6urS5Lk9Qw9BbindyDccHkHTwGWrPLsqbX/nyWnMNwG3NjWNuhfqHxut2ZVDuz3dvh+CUgvsUODZp40a1LXqllUEz1es2bNpK4FAAAAABOVm5urRYsWSZJWrlw56LWXXnpJDQ0NkqSLL75YCxYsGPY6H/3oR1VUVDTs66Zp6pFHHpEknX766TrrrLNGXNf8+fP1rne9S5L09NNPj3juaPe+6KKLosdWNaMdUQGIhAuFQjFTgIcOAHtjqptcnoEfS6sFeCq2/1pyCvw6UNuo3mBQLZ1dyg8MfA3nVNTI5y1Sd0+jnn/+ef3Xf/1XCleKybACQLfXrepjpk3qWtULBwLA1atX2/ZfoAAAAACkt6amJv3mN7/RU089pbVr16qxsVEdHR1Dtlfv2bNn0J9jiyDOO++8Ee/jdru1ePFiPfHEE0O+vn79ejU2NkoKV+EuXbp01LVbbdc7duxQd3e3fD7fkOedfvrpI14nttvTzlW/BIAJ1N3drV27dkmSysrKUrya1LGq/yTJ680a8pyeQQHgQAVgKEQAmBMZBCJJDW1tgwLA6qJCZQcq1d3TSAVgmnvttdckSTXHzxgUgk9EID+gwuoiHdrDzwUAAACAxFi2bJk+/vGPR4O30bS2tg768759+6LHs2fPHvX9s2YN3ylVW1sbPf7rX/+qv/71r2Nak+XQoUOqrKwc8rXR2rO9Xm/0uLu7e1z3TSYCwEkwTXPYibaS9Nvf/la9vb0yDEOnnHJKEldmL9YAEEnyuIcJAHt7o8duLxWAsbx+tzxel3p7+nWwtU1zygfCZI/Tqcri2Wo4tEZtbW1qbGwcsTQZ9tTd3R0N6ibb/muZtqhGh/Y0avXq1XG5HgAAAABYVqxYoauuukr9/f2SpGOPPVYXXnih5syZo4KCgsh+5uG85Ctf+YrWrVt3xFCc2KzA7x+6WzBWIBAY9rXm5uYJfBYDemMyicNlysToKRMAxibNVjuqFP6Bi33N7/fL5Rr4stx4442qr6/X+eefr0996lODrvmlL31JJ5xwgk455RTV1NREy0d37dqlxx9/XM8++6ykcD/4aANAMlns19vjHWYPwJiUPLb6iQpASTKUXeDXoQOtamhrPeLVedMWavXmpZKk3/3ud/qP//iPJK8Pk7VmzZrof3BmnTz6v3yNxbRFNXrnb29p69atam9vV3Z2dlyuCwAAAABf/epXo+Hfj370I91yyy3DnvvNb35zyI/HBnqxucFwYgPDw8X+fef222/XvffeO+r1ppopEwAON133W9/61qA/f/Ob34xuUDmagwcPasmSJVqyZImcTqf8fr96e3sHtbOec845+uQnPznxhWeA2Id0uCEgVvjhcBhyugbGn1MBGJYTCQBbu7rV09cvr3vg0T1u1vH6Qzhr1rJlywgA09Dbb78dPZ5+3PS4XLN6QfgfHUzT1KZNm3TSSSfF5boAAAAApra+vj49//zzkqSTTjppxPBPGtyeGyu25Xbbtm2j3nf79u3DvhZbdLV79+5RrzUVTe1UZZJuuOEGXXLJJZo1a5Zyc3Oje91VVFTovPPO0ze+8Q195jOfkdvtHuVKmS02AHR7ht5U0wpNXR5XdNhvKGTKNMMlwgSAg/cBjJUXKFAgK9z2u3bt2kEBNNKD1f6bX1GgnOLcuFyzYt7Af0w3bNgQl2sCAAAAQENDQ7T6b86cOSOeu2rVquik38PFbpX23HPPjXidvr4+vfzyy8O+fvzxxysvLy96Lbv9vdhqhx5qOEqyTJkKwOEmxYzmZz/72bCvnXnmmTrzzDMnuqQpI7aUd7gKwIEAcCAsDQb7o8dOx/B7LU4FgfwsOQwpZEoHW1tVVVgw6PWqkjnavKsx+i8xl1xySYpWiomwAsCaY2tGOXPs8isK5MvxqbutWxs3bozbdQEAAABMbbGtu1u3bh3x3K997WvDvrZ48WIVFRWpsbFRzzzzjNavX68FCxYMee4jjzwy4rARp9Opa6+9Vg888IAaGhp033336Ytf/OIon0nyZGdnq62tbcQ25kSb2mVVSIpBQ0BGCwBjBoAEgwMbhDqMqf2j6nA4FMgPf+3qW4/cB/CoqoFfkn/84x+Tti5MXkdHhzZv3ixJmrYwfgGgYRiqmBuuAiQABAAAABAvubm5mjt3riTpjTfeGPLvoMFgUJ/+9Kf1t7/9bdjreL3e6BZW/f39+vCHP6z6+vojznv99df1mc98ZtR1felLX1J+fr6k8OCR+++//4jBI7E6Ojr0s5/9TL/97W9HvfZkzZw5U1L472ZW92iyTZkKQKTOoApA78hTgAcHgDEVgM6pHQBKUl5RttqaOtXY1q7+YFAu58BeiTVlc6PHTz31lDo7O8c0RQmpt3bt2uh/lKYdG5/9/ywV8yq1443ttAADAAAAiKtPfepT0b3//uVf/kUf/vCHdc4556igoEBbt27Vb37zG23YsEELFy6U1+vVG2+8MeR1vvjFL+rPf/6z1q5dq7Vr1+qYY47Rxz/+cR133HHq7e3VCy+8oF//+tdyOBy64oorot2dQ03mraqq0u9//3tdfvnl6unp0ac//Wk98MADev/7368FCxZEq/B27Nih119/Xf/85z/V3d2tu+66K3FfqIgLL7xQq1evVkdHhy6//HJ99KMfVUlJSbQ1eNGiRaqqqkroGggAkXCDKgDdQweAvZEKQPegFuCBpN45xSsAJSm3KCBtlUKmqYNtbaqI/MuGJE0rPSp63N3drX/84x+64oorUrBKjJfV/iuFJ/fGk1UBWF9fr8bGRhUVFcX1+gAAAACmpptuukmvv/66fvGLX8g0Tf3ud7/T7373u0HnLFq0SMuWLdPHPvaxYa/j8/n0zDPP6NJLL9Xq1avV0NCg//mf/xl0jt/v1y9/+UutXr06GgDm5OQMeb2LLrpIL730kq677jpt2rRJW7Zs0T333DPs/Z1Op8rLy8f6aU/YZz7zGf3mN79RXV2dnn32WT377LODXv/lL3+pG264IaFrIFVBwsVWAHq842kBjt0DkB/VnMKAIv84oLrmwW3AOf4C5WeXRP/8+OOPJ3NpmAQrACyoLFBO0dD/EZuo2EEgtAEDAAAAiBfDMPTzn/9cf/rTn3TJJZeoqKhIbrdb5eXlOuecc/TDH/5Qr732WrT1dSQVFRV6/fXX9YMf/ECnn3668vPzlZWVpTlz5uiWW27Rm2++qX/5l38ZtAdgYWHhsNc7+eSTtX79ev3hD3/Qddddp6OOOkq5ublyOp3Ky8vTwoULdfXVV+unP/2p9uzZoxtvvDEuX5ORVFZW6s0339Ttt9+uY489Vjk5OdHqv2ShAhAJN1oFYMg01Wu1AHtiA8CgJMlhGEl/MOzI4XQoO9+vtqZO1be0HPH6tNKj1Nx+UJL0j3/8Q21tbcP+qwjswwoApy2Kb/uvNDgA3LRpkxYvXhz3ewAAAACYuj7wgQ/oAx/4wIjnPP/886Nex+1269Zbb9Wtt9467DmvvfaaJCk/P181NSN3TzkcDl111VW66qqrRr33UO644w7dcccdYzr33HPPHdN038rKSt17770TWk88UFaFhLMCQLfbO2Sffl9vr6xHxeWNbQEOB4BU/w3IK8qWJDW2tak/8vWxVB/WBvzUU08ldW0Yv46ODm3ZskVS/Nt/JSmnKEc5xeEQmApAAAAAAOlqxYoVevPNNyWFAzeKhMaPZAUJZwWAo00AloapACQAjMotDo9bD0k62NY26LVppXMG/Zk24MRpbW3V008/rV/84hf605/+pN27d0/oOoMGgCQgAJQG9gFkEAgAAAAAO3rzzTfVdtjfb2OtX79eV199dfTPN998czKWlXFoAUbCWSOuvWMIAN1DBIBUAA7IKQjIYUghM7wPYOwgkJrSuYPOff7559XU1KSCgoIkrzJztba26p577tEjjzxyxOj2Sy65RHfdddeY9riwvP3229HjRAWA5XMrtPmVTdq4caNM0+RfygAAAADYyi9+8Qs9/PDDuvjii3XqqaeqpqZGLpdLBw4c0AsvvKClS5eqvz88I+AjH/mILr744hSvOD0RACLhBioAh54A3BPZ/0+iBXg01j6ArUPsA5gbKFKOv0BtnU2SpL6+Pj355JO67rrrUrHUjLN69WrdcMMNw1b7Pf3003r55Zf14IMP6qKLLhrzNSWpoKow7gNALGVzwhOtmpub1djYqOLi4oTcBwAAAAAmqqOjQ48//viInWzXXnutfv7znydxVZmFABAJN1oA2DtKCzAB4GC5xdlqbeqM7gPocjolhacw1ZTN1bodr8rtdKovGNTSpUsJAOPgnXfe0Qc/+EG1RELX8xYu0L9feL4W1kzTgaZmLXnxZf16+Ytqb2/X9ddfr0ceeUQXXnjhqNe1KgBrElT9J0lls8qix1u3biUABAAAAGArn/vc51RTU6Ply5dr27ZtamxsVHNzswKBgKqqqrR48WLdcMMNOuOMM1K91LRGAIiE6+zslDR8C3BvbAWgFQCaJgHgMHKLAtKW8D6A9a2tqoxp8Z1eNl/rdryq/si+ci+++KLq6+tVWlqaotWmv3Xr1umqq65SS0uLHIahuz7yIV171uJoK21uVpbu/PBVumDRMfr3n/xM3X19uvHGG/XUU09p/vz5w163vb09oQNALFYFoCRt2bJFp512WsLuBQAAAADjVVNTo8997nP63Oc+l+qlZDSSFSRctALQO0wFYCQANAzJ6QpXswUjAZZEAHi4nIKAHI5w+LS/qXnQa9PLw4GTNYI8FArpL3/5S1LXl0laWlp0ww03qLm5WYZh6N7rr9V1Z5855D565yw4Wg/ddKOcDoc6Ojp08803q6+vb9hrr127Nvp9mrZoesI+h9zSPHkDXknStm3bEnYfAAAAAIB9kawg4awKQI975ADQ5XFJkVzFqv6TCAAP53A6lFsYnga8v7l50GvTy+ZFj4uysyUxDXiiTNPUbbfdptraWknS1z70AX3g1HeN+J6zFxytz1z+bknhgO+BBx4Y9txkDACRwq3hZbPDVYBWxSEAAAAAYGohWUHCDVQAjjwF2OU+cv8/SXI6mFp6uPzS8MCIls4udcTsoRjIylNJfpUkqTAnHAC++uqr2rt3b/IXmeZ+9atf6a9//ask6YqTT9IN5549pvd98qILtHBatSTpO9/5zrBVd9YAkMLqQmUXZsdhxcMrjewDuHXr1oTeBwAAAABgTwSASLiBPQCHqQCMtEk6YweA9FMBOJL8koGJsUe0AZeF24DburqiH3viiSeSsq5MsX//fn3961+XJM0sLdG3r/3IkG2/Q3E5nfrOR6+Vy+FQT0+PvvnNbw55nlUBmMj2X0vZ7HAAuHPnzkF7bgIAAAAApgaSFSTcwBTgYYaAWBWAsQFgiABwJFk5Xnl94a/X/qamQa9NLw+3AR9obtHcinDrJ23AY2eapj73uc+pvb1dkvQ/112tgM87rmssqK7SR84MT6j6y1/+ojVr1gx6vb29PVqNl8j2X0tpJAAMBoPRlmYAAAAAwNRBsoKEGwgAx7AHYITVAmxIcoyx8mpqMZQXqQI80NyiUGSYhDRQAShJx04Ph0tvvfWWduzYkdwlpqlnnnlGTz31lCTp2rMW69Sj5kzoOrdeepG8rvDP9P/8z/8Mem3NmjUxA0ASHwBaewBK7AMIAAAAAFMRASASKhgMqru7W5LkHa4CcIQA0OFwKDoZBIMUlOZKknqDQR1sbY1+vKp0jhyO8DTlgHegcm3p0qVJXV866u3t1de+9jVJUnFOjr7w/ismfK2KggJdc9ZiSdLTTz+td955J/pa7HFNEgLA4hkl0RZm9gEEAAAAMBGGYaTV/zBYXAPAa665Ri+88EI8L4k01xWzD91EKgBp/x1eXkm2rPkoexsH2oA9Lq+qimdJkmoPHtTxM8J7zBEAju4Xv/hFdGjHZ694j3Kzhv6ZHaubL7lQHlc4jH3ooYeiH7cCwMLqIgUKEjsARJI8Po8KqwslUQEIAAAAAFORa/RTxu53v/udHnvsMc2dO1ef/OQn9dGPflSFhYXxvAXSjNX+Kw0dAIZMc+ghIASAo3K6nMotzlbzwXbtOXRIJ8yaEa2VnF42X7vrt+jt2l36z8su1tu1O7V+/Xpt3LhR8+fPH/G6U1VbW5vuvfdeSdLRVZX6lzNOm/Q1y/Ly9N6TTtSfX12lpUuX6o477lBxcXE0AKw5NvEDQCyls8rUuLtR27dvT9o9AQAAAGSeb13zYR1dXZXqZQxpw569+tKjj6V6GbYU1wBQCm+gv3nzZn3mM5/Rl770JV111VX693//d5155pnxvhXSQGwAOFQLcF/MRNLYCsD+/tgWYAynsDxXzQfb1dbdrZbOTuX7w1/j6eXz9dKav6ils1PHz5guwzBkmqaWLl2qL3zhCyletT394he/UHNzsyTpix94X9zC5xvOPVt/fnWVenp69Otf/1qf+MQnkjoAxFIyo1Qblq9nCAgAAACASTm6ukqnzJmd6mVgnOKarjz//PP6yEc+Io/HI9M01d3drd/85jc655xzdMwxx+gHP/hB9C/YmBo6Ozujxx7vkRWAPbEBoHsgAAxFpgC7CABHVFCWFz3e23goejy9fKDKb3fjIb1rTrgleOnSpdHhExjQ2dmpn/zkJ5Kk42dM19lHx69K8rgZ03VCpA374Ycf1ltvvZXUASCW4hklkqSDBw+qra0tafcFAAAAAKReXNOVs88+W48++qj27Nmj73znO5o7d65M05Rpmtq4caM+9alPqaqqSh/72Me0YsWKeN4aNjXRCsDoEBA27hyRx+dWdl44WN0TEwCWFdYoyxOQJL2xfYcuP+lESdK2bdu0Zs2a5C/U5n7961+roaFBkvSfl10c9w1jrz/vbEnSvn379Pjjj0c/ntQKwOkl0WMmQgMAAADA1JKQ8qqioiJ95jOf0caNG/Xcc8/pwx/+cLQqsKurS4888ojOPPNMHXvssXrggQfUGjPBFJlltD0Ae4YIAE3TVCgUksQegGNRUB6eBtzQ3q6Onh5JksNwaEbFAknSm9t36LITjo9+LRkGMlhPT49+9KMfSQrv/XfBooVxv8dlxx+nHJ9PUrhSWpKKphUpkB+I+72GY1UASgSAAAAAADDVJDxdOeecc/Tb3/5We/bs0T333DOoKnDdunX6z//8T1VWVurGG2/Ua6+9lujlIMkGB4BHVgD2RgIrSXJ5wtNSg8FQ9GPsATi64or86PGuhsbo8azKYyRJG/fuk9ft0hnzjpIk/fnPf44GrJAee+wx7d+/X5L0H5fGv/pPknwej95z0gmSpD179kiSpiVxAIgUnjhsRMZGEwACAAAAwNSStHSlqKhIn/3sZ7Vx40Y9++yz+vCHPyy32y3TNNXZ2alf/vKXOv3003XCCSfooYceUldXV7KWhgSK3QPQO0QFoDUBWBqoALT2/5OoABwLX7ZXgdxwddnOgw3Rj8+sDFeyhUxTb9fu1PtOOVmStHfvXlrwI/r7+/WDH/xAkjSrtFTvPvH4hN3rg6e+S5JSsv+fJLm9bhVUhqeyEwACAAAAwNSSknTlvPPO07e//W3dcMMNkhStuDFNU6tXr9ZNN92kmpoafe9736NSKc3FVgC6hwoAYyoAnZEhINb+f5LkZA/AMSmqzJckNba3q727W5I0o2y+HEb4EX9923ZddsJx8rndkqTf//73KVmn3Tz++OPRqbi3XHpRQgPnU+bMUklubvTPNUkOACWpJNIGTAAIAAAAAFNLUgPAUCikpUuX6rLLLtPs2bP10EMPSQoHf9nZ2brooouiVYGNjY367Gc/q/PPP59qwDQ22hCQ3sgegE6XM9qeSAvw+BVXDkwD3hlpA/Z6slRVEh7N/sb2Hcr2+XTpCcdJkp544olB1ZlTUSgU0v333y9Jqi4s1JXvOjmh9zMMQ/MrK6J/LppdMsLZiVFMAAgAAAAAU1JS0pWdO3fqK1/5iqZNm6YPfvCDeuaZZxQKhWSaphYtWqQHHnhAe/fu1dNPP63du3frm9/8pkpKSmSapl588UXdd999yVgmEiA2ZHK7fUe8bgWAsROAQ7EVgA4qAMfC6/dGpwHX1h+UGfn4zIrwPoBv7ahVMBTSB049RZLU3t6up556KhVLtY0nn3xSmzdvliTddPEFcjudCb+nK3IPb4FXDS0No5wdfyXTSyVJBw4cGBTOAwAAAAAyW8ICwGAwqMcff1yXXnqpZs+erbvvvlv79++XaZpyu9265ppr9OKLL+qdd97RTTfdpOzsbElSSUmJvvjFL2rDhg065phjZJqmfvvb3yZqmUgwK2TweLKGrObriQaAA+FLMGYPQCoAx664ukCS1NzZqab2dkkDg0Dau3u0ad9+LZ43V6V54TbUqdwGbJqmvve970mSSvNy9aEzTkvKfa09Gv1VAe3cuTMp94xVPL14YC0puD8AAAAAIDXinq7U1tbqy1/+smpqanTVVVfp73//e7Tab8aMGbr77ru1Z88eLVmyRIsXLx72OoWFhfqv//ovSbSrpbNoAOg+cv8/aegKQGsPQIdhyBAVgGNVUpUvq2Bye129pIEKQEl6Y9t2uZzO6DCQ5557TnV1dUlfpx384x//0Jo1ayRJn7jw/OjeiInU2tWl7fXh74u/Mlt1dXVJ397AagGW+L0KAAAAAFNJXAPASy65RHPmzNG3v/3taLWfYRh6z3veoyeffFLbtm3T5z//eRUXF49+MUnV1dWSpO7IUAOkn2gA6D1y/z9puAAwvAcgE4DHx+VxKb8sXN1Xe7BBwVBIhbllys8Ohz6vbw8HPh+MtAGHQiH96U9/Ss1iUyi2+q8gENC1Zw7/DxHxtG73nuhxoDIgydSuXbuScm9LcQ0BIAAAAABMRXFNWGKr/UpLS/XFL35R27Zt01/+8hdddtll0Wm/Y+X3+1VTU6Pp06fHc5lIImsPQO8QE4ClgSnAztgAMNICTPvv+JVOK5Qk9fT3a++hJkkDbcBvbAsHPkdXV2lBdZUk6bHHHkvBKlPrlVde0apVqyRJ/3b+uQr4vEm575pdu6PHJTOLJCnpAaAny6O88nxJBIAAAAAAYNm2bZtuu+02LViwQDk5OcrOztbRRx+t66+/ftD++c8//7wMw4jmWytXrtRVV12liooKOZ1OfepTn0rRZzA61+injM9ZZ52lm2++WR/84AflnmRb3dlnn63a2tr4LAwpEbsH4FB6+/okSS73kUNAGAAyfvmlOfJ4XOrt7deWAwdUU1ykmRXH6M3Nz2t3Y6MONDerPD9f7z/1FK3fs1dr1qzRmjVrotW2U4E1VCjH59P1556VtPuurg2HfcVV+Zo5rUwb9+5VXd0B9fX1Tfp35XiUzChRy4FmAkAAAAAAkPTQQw/pP/7jP9QXySd8Pp+ysrK0adMmbdy4UcuWLVNzc/MR73vsscd03XXXqb+/X3l5eXImYbDkZMS1xGrNmjVavny5PvKRjyT1L7Swr4EA8MgWYFMDFYAuz8DPy8AegFQAjpdhGCqtCVcBHmhuUUtXl+ZUHRt9feXmrZKk951ykhyRf7F4+OGHk77OVHnjjTf0wgsvSJI+eu7ZyvMP3ZqeCKsj1X7T5pWpqjA8sCUUCmn//v1JW4MkFU8PtwETAAIAAACY6pYuXap///d/V19fn9797nfrzTffVFdXlw4dOqSWlhY98cQTuuyyy4Z874033qj3ve992rFjh5qbm9XZ2WnrCsC4JizHHHPM6CdhSrECwKFagPv7+hUyTUmHTQGOVgASAE5E2fTC6OiULfv2q7J4prK84Snbr24JB4BleXk655ijJUmPPPKIeiJBbKaz9v7L8nj08fPPSdp9mzs6ohOAp80rV0lurtzOcNXrnj17Rnpr3JXMKJUk7d27l/1VAQAAAExZfX190eGz73vf+/SXv/xFJ5xwQvT1nJwcXX755frtb3875PuPO+44/f73v9eMGTMkSS6XK3psR3FNWBwOh1wul5544olxve/pp5+W0+mUyxX3jmSkmLUH4FAVgL29A6FT7BCQUIghIJPhyfKooDw8DGRH/UEFTUWrAK0KQEm6evEZkqSGhgb99a9/Tf5Ck2zt2rV6+umnJUnXnHWGinJyknbv2P3/ps0rl8MwVF6QLykcxIXrYZPDqgA0zeQPIQEAAAAAu/jnP/+pXbt2yTAM3XfffeOeQ/CZz3wmrWYXxH2lpjmxv8iapjnh98K+RtoD0JoALA0MATFNMxoAOsY5NAYDymeEh0z0BoPaXlevOdXhAHB7fb3qWlokSecvOkYlueGg8JFHHknNQpPo/vvvlyR5XE598sILknrvdyL7/xmGVD03XIFXVRBuA+7q6lRj46GkraVkBpOAAQAAAGDFihWSpPnz52vWrFnjfv/pp58e7yUlVPpElUhLYw0ArQpAq/1XogJwMvKKs+XP8UmSNu7dp9lVx0VfezVSBeh2OvUvZ5wqSVq+fHlGD9zZunVrtDL5Q6efprL8vKTe39r/r7SmSN4sjySpsrBAijRrh6sAk8OqAJQIAAEAAABMXXV1dZKk6dOnT+j9JSUlo59kI7ZIWKw2UZ/Pl+KVIN6s763XO1QLMAFg4hiqnF0sSWrv6VFQecryBCQN7AMoSR9ePPAvFr/5zW+Su8Qkuv/++2WappwOh266+MKk33/1znAAWDO/PPoxn9utouzw3ox79uwe8n2J4Mv2KVAYvu/OnTuTdl8AAAAAyCR2n/p7OFskLCtXrpQklZaWpngliLdoBaD7yArAniEDwFD0Y+nUS29HxVUF8vrC05U37tuvWVULJUkrYgLAGSUlOvPo+ZKk3/72t+rv70/+QhNs165d+uMf/yhJuvKUk1VTXJTU+9e3tGp/U7MkqXpe2aDXKiPTgBsaGtXV1ZW0NRXXhMNhAkAAAAAAU1V5ebhAY6r8vWjCUzdWr16tt99+e8jX/vnPf6q5uXnE95umqY6ODr355ptasmSJDMPQKaecMtHlwIaCwWB0uqzHO7YW4NCgCkD2AJwMwzBUMbtYtev2q6mjUyUFc6Udr2rbgTodbG2N7v933Tln6qUNG1VXV6e///3vw444T1c//OEPFQwGZRiGbrn0oqTff03MoI1phwWAVYUFkddN7du3V7Nnz0nKmoqmFWnn27UMAQEAAAAwZVl7+G3cuFHbt2+f0D6A6WTCAeDjjz+uO++884iPm6apH/zgB+O6lmmaMgxDN91000SXAxuyqv8kyTvkFOBwAOhwGHI4w9V+wVBMAGhQAThZZTVF2rvloPp6+9VjFkY//uqWrXrvSSdKkt594gkqCATU1NGhJUuWZFQAuG/fvmhr87tPOE5zystGeUf8We2/DqdDlbMH7xFREAjI5/aou69X+/fvT14AGKkA3LVrV/T3LwAAAABMJeeff75qamq0a9cu3X777frzn/+c0Z2Ik/rMrMm9h0/wPfzjo/2vrKxMDz30kM4///xJf0KwD2v/P0nyjBAAWtV/0uEtwIQSk+VwOlR1VLi1PuQokMcVrsRcuXmgDdjrduuDp71LkvSPf/xDe/bsSf5CE+T73/9+9Ofs1ssuScka3okEgBUzi+Txuge9ZhhGdCDJvn37JSVnEnrRtHAA2NXVpfr6+qTcEwAAAADsxOVy6f7775ckLVu2TFdcccWgTtf29nb94Q9/0Pvf//7ULDDOJlwBeOWVV2rGjBmDPvaxj31MhmHo1ltv1Yknnjji+x0Oh7KzszVz5kwtWrQo7TZPxOhiKwCHnAIcaQ+ODQCtFmCH4ZA1IRWTUz69UPu3HVRPt5SbM10NTRv1yuYtg8655qwz9LNnn1MoFNIvfvELffWrX03RauNn3759WrJkiSTp0uOP04LqqqSvwTRNrdkZHvAxbV75kOeU5+dp58GD6u7uUnNzi/Lz8xO+rqJpA/sg7tq1S2Vlya+MBAAAAIBUe//7368f/ehHuu222/Tkk0/qySefVFZWlrKystTU1CTTNJWXl5fqZcbFhAPA4447Tscdd9ygj33sYx+TJF1wwQW64oorJrcypL3BLcDD7wHodMdUAEZagNn/L34Mh0PVc0u1bfVe+QMzpKaN2nagTvubmlRZGG4LnlNerrOPnq8XNmzUkiVL9NnPflZ+/5FVm+kktvrvv95zaUrWsK+pSQ1tbZJGCgDzo8f79+9LTgAYaQGWwgEg+68CAAAAmKpuueUWnX/++br//vv17LPPas+ePerv79f8+fN12mmn6Zprrkn1EuNiwgHgUH75y19K0qjVf5gaJtYCHKkAzOC++1QomVaovVsPKj93tqyxDy9u2KQPLz49es4N552jFzZsVFNTk/70pz/pX//1X1Oz2DjYv39/yqv/JOmtHbXR45qjhw4AA16vcnxZauvu0v79+3X00QsSvq6CikIZDkNmyFRtbe2o5wMAAABAJps/f75+8pOfjHreueeeO2gLvHQS15Tl+uuv1/XXX6/q6up4XhZpatQW4BECQCoA48swDNXML1dWVpnc7mxJ4QAw1nnHHK0ZJeEhFQ899FDa/lKT7FH9J0lvbq+VJHl8bpXPLB72vPLIPoAHDtQpFAoNe168ON1OFVQWSBKTgAEAAABgCqDMCgmTl5enSy65VHOPOk2BQMERr/dYLcCegf0frfDD6WBPyHgrqsxTXlG28nJmS5Je2LBhUNjkcDh0w7lnS5I2bNigl19+OSXrnKz9+/fr17/+tSTpkuOPTVn1nyS9uX2HpHD1n9M5/K/b8oJ8SVJ/f58OHjyYjKVFB4EQAAIAAABA5iMARMKcfPLJWrr0SX3hs0tVUlxzxOsjtgAbVADGn6GZCyuVnxsOAJs7OrVh775BZ1x1+ruU7fNKkn76058mfYXxcN999w1U/707ddV/3X19Wrs7PFF5xoLKEc8ty8uTNfTmwIH9iV6apIEAcOfOnUm5HwAAAAAgdSa0B+CsWbMkhdsKt23bdsTHJ+rw6yFzhUIh9ff3S5JcHnf04wMtwGTTieDPzdKcBSdra+2fJUm/ev4FnThndvT1nKws/cvpp+kXzy3XU089pU2bNmnevHmpWu64bd26NVr9d9kJx+mYaanbjmDNrt3qi/w8Tz+mYsRzPS6XirKz1djepn379uu4445P+PqsScB79+5VX1+f3G73KO8AAAAAAKSrCQWA1qbxxmFVWrW1tTIMY8J7hx1+PWQuq0JLklzucLtvKBSK/uwQACbOUcfP0wvPlamzq05LX3td3/7otYNKgW+88Dw9svxF9YdC+v73v68HHnggZWsdr2984xsKBoNyORz63PsuT+larPZfSZq+YOQAUArvA9jY3qaGhgb19fXK7fYkcnnRScChUEh79+7VjBkzEno/AAAAAEDqTCgArKmpGTKsG+7jwOFiA0BnpAU4FIzdj46fo0RxeVyqmXWcNq57Rt19ffr2n5fpS++/Ivp6VWGh3n/qKfrDilf15z//WZ/73OfSIhx69dVX9eSTT0qSrj7zDM0qK03peqwBICXTCpSdd+QU7MOV5edr3Z49Ms2Q6uvrVVWV2OpFqwVYCrcBp8P3GAAAAAAwMZOqABzrx4HD9fX1RY9d7vCPYTAUjH7MaVABmEjzjz9VG9c9I0l68Jl/6PKTTtDCmHbZmy++UH9c+ZqCwaB+9KMf6Tvf+U6qljompmnq61//uiQp4PWmdPKvtZ43d4QrAEfb/89Skpsjh+FQyAzpwIG6xAeANQMBIINAAAAAACCzkbIgJQa1AEemAFv7/0m0ACda9fSFcjgjlZemqc//+lH1x3z9Z5eX6T0nHi9JevTRR3XgwIFULHPMli5dqlWrVkmSPnnxBSrJzU3pevYealJ9S6uksbX/SuGf+aKcbElSXV1dwtZmySnOkScr3GbMIBAAAAAAyGykLEiJQS3AVgVgTADlIABMKLfHp+rpx0T/vHb3Hv3s2ecHnXPLJRdJCn+v/vd//zeZyxuX9vZ2ffWrX5UU3kfvExecl+IVDd7/b8YxY6sAlKTSvDxJUmNj46Aq2UQwDEOF1eFBIASAAAAAAJDZSFmQErHhhjNmCEj0Y+wBmHAzjzp50J/v+7+/akd9ffTPx0yr1oWLFkqSHn74Ydu2+N9zzz3RCsWvXvUB+b3eFK9IenNHrSTJ6/eofEbRmN9XlheuXDTNkA4ePJiIpQ1itQHTAgwAAAAAmW1CewBORldXl37yk5/oxRdfVH9/v44//njdfPPNqqgYW5scMsPgFuAhKgAZJpNwM+eerOVP/1ySZBhST1+fbv/VEv3xM5+KtmB//srL9c+169TX16e7775bP/3pT1O55COsX79eDz74oCTprKPn6d2RtuVUeyNSAVgzv1wO59j/naU4J3YfwAOaOXNmopYoSSqaFg4nCQABAAAAjNWGPXtTvYRh2XltqRbXAPCtt97S9ddfL8Mw9JOf/ESnn376oNdbW1t11llnae3atdGPPfnkk/rxj3+sZ555RieccEI8lwMbsyoAHQ4jGpBYAWA4fCIATLSCokrlF1WquXGfCsvz1Li/RW9ur9VD//inbrr4QknS3MoKXXX6qfr9Kyv15z//WTfffLOOP/741C48IhQK6XOf+5yCwaA8Lqfu/PCHbDGFvKO7R+t275E0vvZfSXI5nSrMzlZDW2tS9gG0JgE3NDSovb1d2dnZCb8nAAAAgPT2pUcfS/USMAFxbQH+4x//qLVr16q+vl6nnXbaEa9/+ctf1po1a2Sa5qD/NTY26oMf/KB6enriuRzYmFUBaLX/SgMtwFT/Jc/Mo06SJLU0tKt8ZjgMuvcvT2rj3n3Rc25/72Xyud2SpDvvvFOmaSZ/oUN48MEH9eqrr0qS/v3CCzSrrDTFKwp7fft2BSM/y7OPG/8kX6sNuLGxQf39/XFd2+GYBAwAAAAAU0NcKwBfffVVGYahiy666IhKnLa2Nv385z+XYRiaNm2avv/972vmzJl64IEH9OCDD2rnzp1asmSJPv7xj8dzSbCp3kgFoMs98CNoVQAyACR5Zs49WW+t/Iv6+4I67T2L9JefLFdvf1C3/2qJln7udnlcLlUUFOjj55+rHz39d7344ot66qmndNlll6V03Zs2bdI3vvENSdJRFeX6z3dfktL1xHp181ZJktPlGHcFoBQeBLJuzx6FQiHV1dWpunr8IeJYWS3AUjgAXLBgQcLuBQAAACC9PfPMM6leAiYhrgHg3r3hXuuhWnn/9re/qbu7W4Zh6Oc//7kuuOACSdJPfvITrVy5UmvWrNHSpUsJAKeIPqsC0BMbAIarphgAkjzV04+R25Olvt4uHaht1CU3nKG//uwlrdu9Rz/82zO6/fJ3S5JuuuRCPfbKSjW0temLX/yizjrrrJS1i/b19ek//uM/1NPTI5fDoe9df120QtEOVm4JB4A188vl8Y1/XcW5OTJkyJSp/fv3JTgAHKgAtOuQFwAAAAD2cNFFF6V6CZiEuJZaNTQ0SNKQAz2WL18efc0K/ywf+tCHZJqmVq9eHc/lwMasFmDXoBbgSAWgQQVgsjhdbk2ffZwkaeOr23Xuh09WzdHh5/eHTz2j1TvDbaG5WVn6ylVXSgoH/d/97ndTsl5Juvfee/XOO+9Ikm579yVaNL0mZWs5XGdPT/RrNvu4aRO6hjuyD6Ak7d+/P25rG4ov26dAYfhetAADAAAAQOaKa9LS0tISvugQLZwrVqyQYRhHhH+SVFMT/gv8wYMH47kc2Jg1BMQZ0wJs7QHopAU4qWYddbIkqflgu+pqG3XNFy6V2+tSMBTSpx/+tboj36srTzlZi+fNlRSu3H3jjTeSvtZ//OMfuu+++yRJx02v0S2XXpz0NYzkze216ou0sk9k/z9LWX6eJKm+/mDi9wFkEjAAAAAAZLy4Ji1+v1/SkUFeS0tLtLrvjDPOOOJ9Pp9P0sAecMh80SEgnoEKwOgegAwBSapZc0+RIl/zNS9tVWlNod7zibMkSVsP1Om7TzwpSTIMQ9+85l/kc7sVDAZ18803q729PWnr3Llzp2655RaZpqncrCz98OM3yO10jv7GJLLafx0OQzMWjn//P0tpZBBIKBRUfX19XNY2nOLIIJCdO3cm9D4AAAAAgNSJawA4Y8YMSdJLL7006OP/93//F63uWrx48RHva2xslCTl5eXFczmwsb7Dh4CYJhWAKRLIKVBF9TxJ0poXwwHWme8/QbOPD7ew/uzZ5/Talm2SpJmlpfrKB6+UJO3YsUNf+cpXkrLG5uZmXXPNNWpqapIk3f+xf1VNSfEo70q+FZu3SJKq55XLm+WZ8HVKcnMkhUPZ/fv3jXzyJBVG9gHctWuXbSY8AwAAAADiK65Jy1lnnSXTNPXEE09E9+hqbW3VPffcI0mqrKzUwoULj3jf2rVrJUkzZ86M53JgY72HDQEJRsI/KVw9heSac/RpkqT92w+qcV+zHA5DV3/+Enmz3DJNU5/+1a/V1tUlSbru7DN13sLwtNjf/OY3euSRRxK6tp6eHt1www3avHmzJOn2916mCxYd+Xsk1Vq7uvTWjlpJ0tyTJrcvodvpUmF2QJK0b19i9wG0WoA7OzvZhgEAAADAsAzDSKv/YbC4TgH+xCc+oR//+Mfq7u7Wu971Lp1wwgnatm2bDh06JMMw9IlPfGLI9/3zn/+UYRg69thj47mcjOO0WbvjeMQ+fMFgMBr4hYeAGNHqPykyBIRnNSmsL/NRR5+mF595WFK4DfjcD5+swoo8Xfmf5+mxe57RnsZDuuP3f9J9N/yrDMPQvR+9Tu+9+zva19SkL3zhCzr66KN12mmnxX19PT09+vjHP66XX35ZknTVae/Sf73nMlv+Mn9189boz/W8U2ZM+me4LC9Ph9rbVV9fr2AwmLDPuThmEvDevXuHHOKEoVm/k9P5d/NUwffIfnh+0gvfJ/vhGUoffI/sh+cHU1VcA8Bjjz1WX/va1/S1r31NfX19WrVqVbSl7Nhjj9X/+3//74j3rFmzRhs3bpRhGDrzzDPjuZyMU1BQkOoljFtfX0iGYcjr9UY/1hmpJJMkt9cjp9OhSEewJMnldMhBAphUBYWVKi6broa6nVrz0lZdcPWpkqTT33Oc1q/YoTUvbtEfV76my046Qe89+SRVlXj1q9tu0RV336Ou3j5dc801eu6553T88cfHbU1dXV26/vrr9fTTT0uSzlt4jL738RvkccX111bcvBxp//VmuTVrYbWcjsn9PxSl+fnasHevgsF+HTp0SKWlpfFY5hEq5gzsVdjY2JiWv2dSLTc3N9VLwAicTic/1zbG82N/PEP2xjNkbzw/9sbzM3Ef/tY1qjp64kMPE2nvhj167EuPpnoZthT3v0n/93//t4477jg99NBD2rp1qwKBgC6++GJ94QtfUFZW1hHn/+AHP5AkmaapSy65JN7LySjW/mfpIvwL1ZBpmtGWX0mDBkc4XA4Fg6HonoCSZMhQSOxFlgyGwl9vU6Zmzz9NDXU7Vbt2r5obWpVTGG5B/dBnLlTt2r1qa+rUZx7+tRZNm6by/DzNqyjXvdf/q/7jZ79Uc3OzLrzwQi1btkwLFiyY9LoaGhp07bXXatWqVZKkM+fP00///d9kBoPqsemwoOfWrJMkzT5+mgynFAxNbp3FkRZgKbwPYKL2SA0UZ8swws/p+vXr0+73TCo5nU7l5uaqtbWVIVY2lJubK6fTqWAwqNbW1lQvB4fh+bE/niF74xmyN54fe7Pr85NOYXHV0dWafcqcVC8D45SQUporrrhCV1xxxZjOffDBB/Xggw8mYhkZx06/nMYrdrhAb09P9NjpdkoyB31uTodD5H/JYRrhENCUNGf+aXp1+WMyTWntS9t0+uXhlvzsPL8+/LlL9LMvPq7mjk79v0eW6Fe33izDMPSeE49X+3Uf0ed+/Vs1Njbqsssu089//nOdd955E17TqlWr9MlPflK7d++WJJ23cIF+/Il/k9fttu2Qil0NjaqN7J837+Tpcfn59brdyvX71drZqQMH6jRv3vzJX3QITrdT+RX5atrXpNra2rT+PZMqwWCQr5vN8f2xL56f9MD3yL7+P3v3HR5llb9//P1MSzLpHQihVykCSpcigogodl3U1VX0q1h2V9ft1i3q7m9ZdXUtu+ra166oi4qKIqBIEZBOQm9pJKRN6sz8/pjMJBGQkpnMM8n9ui6uHeaZ58wnTg5sbs45H80h89PnY16aP9LeqN2qtLraJqv9/F2APWoCEnbpHbqTkOTbZrp2cU6zayeN6sGYGScDsHDDJp5fuChw7bIxo7n/8suwGAbl5eXMnDmTBx54oNmqz2Phcrl44IEHOPfccwPh3xXjxvL0jdcT4zjxjrqtYfHGTYHHfU/tFrRxMxq2JeTl5RHKVDyls68RyK5du0L2HiIiIiIiIhI+CgCl1dU1CYasDt85aU3/5cViwgYP7YFhGPTq52vkkfPtLirLqppdnzF7AunZvmXp9789l5z9eYFrV4wbyzM3/R+xUVG43W7+/ve/c8YZZ/DBBx80C3cPx+Vy8Z///IexY8fy97//HbfbTbTdzl+unMmfZ16KLQIO5/2sYftvcmZ84L9RMGQ0bPutqammtLQ0aON+n78T8M6dO0P2HiIiIiIiIhI+CgCl1TVdGRZYAej2hUQWw4JaAIdPnwG+Rjzueg9rF+U2u+aItnPl78/GYrVQU1fHz//zArX19YHrkwYO4P3f3MHQ7t0A2LRpE9dccw0jRozg3nvv5YMPPmD9+vVs2bKF5cuX88orrzB79mwGDx7Mr371K/bs2QPA8J49eP+3d/CjsaNN2e33+6pqa1m0aTMAA8b0DGrNGYmNBxMXFBQEbdzvS2noBLx3715tgxAREREREWmDQtZOc/Xq1Xz44YesW7eOkpISqqurj3qPYRh89tlnoSpJTKJpww/fGYCNDROs2v4bVh069yEhMYOy0gJWf7GZUdMHNbue3bcDU68ezYfPLmHd7j08/MGH/Or8cwPXe3bI5M1f/IwXFy7mnx9/QmFZGTt37uSf//znUd+7Z4dMfjptKucNPyUigj+/RRs3UdPwPT1gTM+gjh0XE02Mw0FVbS35+QX07t0nqOP7+VcA1tXVkZeXR1ZWVkjeR0RERERERMIj6AHg/v37ueaaa/jkk0+O6z6v1xtRP/TLifOvALRYDCxW3yJUd8M2UYtFi1LDyTAM+gw8jRVL3ibn212Ul7iIT3Y2e82ky0ew8Ztt7Fi/nyfmf8rpA09ieK/G4MtmtXLNpAnMPG007yxbwbxvV/PV5i3UH2YrcHJsLJMGDuCcU4cy8aT+Efn5f/LdOgCiYx30PDk7qGMbGGQkJrKzsDCkKwBTG1YAgm8bsAJAERERERGRtiWoAWBFRQWnn346OTk5pu3WKeHnbwJiczR++3kath3q/L/w6ztwHCuWvI3X4+W7hVsYe/6QZtetVguX//Zs5lz/AjVVdfzsPy/w4e9+TWJs86Aw2uFg5mljmHnaGKrr6thRUMje4mK8Xi/RdgfdM9PpmJQUkaGfn9vj4bOGALDfiO7Y7ME/rzAjMYGdhYVUVJTjcrlwOp1Hv+k4+VcAgq8RyJgxY4L+HiIiIiIiIhI+Qf3J+6GHHmLLli0AdO7cmSeeeILc3Fyqq6vxeDxH/aWzp9oHfxMQa5OwxN1wBqA1gsOgtiK9Q3eSUzsBsOrzzYd9TVpWEhfcOgmAvcUl3PHiyz8Y+kfb7fTL6sQZgwYyefAgTuvfl6yUlIgO/wC+3b6DAxUVQPC3//r5G4FA6M4BTMxMCsxHdQIWERERERFpe4L60/c777wDQIcOHVi+fDk33HADPXr0wOFwBPNtJML5VwBa7U1WAHq0AtAsDMMINAPZvnYPBwvLD/u64WcNYNjk/gDMX7OW/3y+sNVqNIv/rVwFgNVmof/I7iF5j6TYWGxW31wJVQBosVpI7pQCKAAUERERERFpi4IaAG7duhXDMLjpppvIzMwM5tDShvhXADbbAuzRCkAz6TtwHABeL6z5YsthX2MYBhffNpn07GQA7n97Lmt27Gy1GsPN7fHwwcpvAeg3ohvO+OiQvI/FMEhPiAegoCA/JO8BjduAFQCKiIiIiIi0PUFNW/whTt++fYM5rLQxtd/fAuwlsP070reEthWpGV1IzegKHHkbMEC008FVd5+DzW6lzu3m5qefo9Tlaq0yw+rrzTkUlvlWRw6d1C+k7+XfBlxcXEJdXW1I3sPfCEQBoIiIiIiISNsT1LSla1dfYFBefvgtgyLQGADaGrYAe5p0h7VqC7Bp9B3o2wa8a+N+DuwvPeLrsnplcP4tpwOw+8ABfv6fF5t9pm3V3BUrAXBE2xgwpldI3ysjMaHhkZeCgsKQvEdKwwrAffv2BeaoiIiIiIhIe5CTk8Ps2bPp06cPTqeT+Ph4hgwZwn333Udp6aE/D3u9Xl588UUmT55Meno6drud1NRU+vXrx5VXXskbb7xxxPdavXo1s2bNolevXjidTpKSkhg4cCA33XQTX331Vci+xqAGgDNmzMDr9bJkyZJgDittTF3gDEDfCkC3p7H5i1YAmkffAeMCj1ct2PSDrx197mCGneFbBbdg3Xr+/sGHIa0t3Grq6vho1RoABozpRVSMPaTvlxYfj4EvHA/VOYD+LcBer5c9e/aE5D1ERERERETM5plnnmHAgAE8+eST5OTkYBgGNTU1rFmzhnvvvZehQ4eydevWZvdcffXVXHXVVXz22WcUFRXhdDqprKxk8+bNvPzyy9x2222Hfa97772XYcOG8eyzz7J161YsFguGYbB+/XqeeOIJbrrpppB9nUFNW2699VaSk5N5+eWX2bTphwMDaZ+8NDYB8Z8B6O8ADGoCYiZJqR3J7ORb2bbykw0/2OXXMAwuveNMsnqlA/Dohx/zYUNA1hZ9vPo7yqqqAALBZyjZrFZS4uKA0AWAKZ1TA4+1DVhERERERNqDefPmcf3112O32/njH//I/v37qaysxOVysWTJEk499VS2b9/OhRdeGNjptmjRIl588UUsFgtz5szh4MGDlJaWUlVVRX5+Pq+99hrTpk075L0eeeQR7rvvPrxeL1dddRWbN2+moqKCkpISDhw4wCuvvMLo0aND9rUGNQDs2LEjr776KjabjSlTpvDll18Gc3hpA9z19Y0NPxz+LcCNKwDVBMRc+p/s29qbv7OYPVt+uAGFI9rONX88n9jEGABuf/5F1u7aHfIaw+HlRb5VzglpcfQLUfff7/NvAy4qKmq2ajZY/GcAAuze3TY/NxERERERET+3282tt96K1+vlpZde4s4776RDhw4A2Gw2xowZw8cff0zHjh357rvvePfddwH4+uuvAZgyZQq33347iQ1nthuGQUZGBpdeein//ve/m71XcXExv//97wHf4rnnn3+ePn36BK6npKQwc+ZMnnjiiZB9vbajv+TY/eEPfwBg8uTJzJ07l9NPP50hQ4YwevRo0tLSjml759133x3MksRk/Kv/AGwNW4A9TVcAWrQC0Ez6DRzPlx8/i8fjZvnH68nu2+EHX5/SIYGr7jmHp+54E1dNLdf88yne/dXtdE5NaaWKQy83L5+lObkAjDp7IFZr64TW6QkJbNy7F7e7nuIDxaSnpwd1/Pi0eBwxDmqratm5s/10cxYRERERkfZp4cKFbNu2jZ49e3LBBRcc9jUpKSlMmzaNZ599lvnz53PhhReSkOBbnFFYWIjH4zmmrOuNN96gsrKSuLg4/vznPwf16zhWQQ0A7733XoyGLZyGYeD1elm9ejWrV68+5jEUALZtdU2aC1gbmoA0Xc1kNbQC0ExiYhPo3vtUtm7+hlWfbWLG7ImB4PZIeg/twiW/mMJr/28+hWVlXP3YE7x9x20kxjpbqerQemWxb/WfYTEYOX1Qq71vWkJ84HFBQUHQA0DDMEjpnEpezn5tARYRERERkTbP33Bjz549gZV/h1NRUQE0HpV0xhln4HA4+Pbbb5kwYQLXX389kyZNonPnzkccw79qcNy4ccTHxx/xdaEU9LTF6/UGfn3/90f7JW1f0+6igRWAHq0ANLOThvi2AVeWVbPxm23HdM/Iswdx5tW+swty8/K59ol/UVldE7IaW0tFdTVvfr0MgJNGdSc5I+EodwRPtN1OQowvRM3P/+Ht2CfK3whEAaCIiIiIiLR1+/fvB6Cmpob8/Pwj/qqsrATA5XIB0Lt3b5588kmcTieLFy/m6quvJjs7m+zsbGbNmsXixYsPeS//z3Bdu3Ztpa/uUEFdAfj5558Hczhpg+qabAG2BpqA+FYA+hqAKAA0m+69TyU6Jp7qqnJWzN/AoNN6H9N9U68ezcH8MpZ9tJ4VW7dx7eNP8Z+bb8AZFRXiikPnlcVfUdrwh/7Y84a2+vunJyZQVuWisLAQr9cbWHEdLP5GIAoARURERESkrfNnEVOnTuWjjz46rnuvueYapk+fzuuvv87nn3/OkiVL2LNnD88++yzPPvsss2fP5vHHHw9F2ScsqAHghAkTgjmctEGHWwHo7wJ8LPvmpfVZbXb6DhzHmuXz2PD1NipLqwKNPn6IYRhccseZ1FTVsWbhFpbm5DLriX/z7E3/R4zD0QqVB1dNXR3//nQBAJ17Z9B3eOv/y01GQjxb8/KoqammrKyUxMSkoI7vbwRSWFhIZWUlsbGxQR1fRERERETELDIzM4ETXwCRkZHBLbfcwi233ALAmjVrmDNnDi+++CJPPPEE55xzDmeffTZAYItxOM9bV+Iirar2MCsA/V2ArUFezSTBc9KQSQC46z2sWrDpmO+zWi1ceefZDBrXC4CvNm/hx/94nIMNS6gjyVtLl1FQWgbAGVeMDPrqu2ORntC45bigoCDo4/u3AIPvHAwREREREZG2asyYMQBs2rSJrVu3tni8k08+mRdeeIFBg3xnxX/xxReBa6NH+47IWrRoEeXl5S1+rxOhAFBaVV2zFYD+LcBaAWh2mZ16kZLmO9B0+fwNx3Wv1Wblx3edw8CxPX33b93GRX97mL3FxUGvM1Sqa2t59MP5AGRkJzPotF5hqSM2OprohtWT+fnBDwBTGlYAQnj/ZUpERERERCTUJk2aRNeuXfF6vdx2223N+hN8X11dXaAZSNOdjYcTHR0N+M4W9Lv44ouJjY2loqKC3//+90Go/viFPHHZs2cP8+fP59VXX+WFF14I9duJyfnPALRYLRgNDT/8KwAt6gBsWoZh0P9kXzOQ3ZvyyNtx4Ljut9mtXH3fDEZMGwj4GoNc8NeHWLV9R7BLDYl/ffo5+0pKAJj6kzFYrOH5XjWAjIZVgKFeAahzAEVEREREpC2z2+08/vjjWCwW3n//faZOncrSpUsDQaDH42HDhg08+OCD9OnTh9WrVwNw8803M3PmTObOnUtxk4UtBw4c4K677mL58uUATJs2LXAtJSWFP/3pTwA8+uij/OQnPyEnJydwvbi4mGeffZZZs2aF7OsN6hmATT377LPMmTOHTZuabxe86qqrmv3+z3/+MwsXLiQ7O5tnnnkmVOWISfiTcv/5f9C4AtCqDsCm1n/wRL5a8DJer4dv/reW826eeFz3W60WLvvlmSSmxfHJi0vJLy3lkjmPcPclF/Lj8aeFZUvtscg/WMrjH38CQLcBHRlyet+w1pOekMCuoiIqKspxuVw4nc6gje1MdBKTEENVWZUCQBERERERafPOPvtsXnrpJWbNmsWnn37Kp59+SlRUFHFxcZSVlTVrZOr/mbWuro5XX32VV199FYD4+HgMw6CsrCzw2ptvvpmzzjqr2Xv9/Oc/p6CggAceeIDnn3+e559/nri4OGw2GwcPHgR824hDJejLWKqqqpg+fTrXX389mzZtwuv1Bn4dzqmnnsqnn37Kc889x8aNG4NdjpiMPwD0n/8HTVYAaguwqcUnptGt1zAAVsxfT31t/XGPYRgG064dy49+PRWbw0ad281dr77BT5993pTnAnq9Xu594y2qGr5vz7vp9LAHlemJ8YHH/lbywaROwCIiIiIi0p7MnDmTnJwcfvOb3zBkyBCioqI4ePAg8fHxjBo1ittvv53FixczduxYAO666y4efvhhZsyYQZ8+fQBfFpaVlcWFF17IvHnzeOyxxw77Xvfffz/ffPMNP/7xj+natSt1dXUYhsGgQYO4+eabeeqpp0L2dQZ9BeBVV13Fhx9+CEC3bt2YOXMmJSUlPPnkk4d9/ZQpU0hPT6eoqIgPPviA/v37B7skMRF/et50BaB/ea1FKwBNb9ApZ7I9ZwWVZdWsXZzL0En9TmicEWcNpFPPdJ6/930O7CvlvRXf8vWWXB64/DKmnDwoyFWfuHeWrWDet6sBGD51AF1P6hjegoBkZyx2q406dz0FBQV07949qOOnZqexd8MenQEoIiIiIiLtRlZWFg888AAPPPDAUV/bs2dPfvazn/Gzn/3shN5rxIgRYTkiL6hLrj777DPeeustDMNg5syZbN68mT//+c9MnTr1yAVYLEyZMgWv18vixYuDWY6YUGAFoN3fAdgTWB1q1RmApte996nExiUDsPSDtS0aq3PvTG5/6srAltrCsjKue/Lf3PivZ9hVdHxnDIbC7gMHuOe1NwFISo/j/FsmhregBoZhkBbvWwUYynMAd+/eHfSxRUREREREJDyCmrg899xzAPTo0YPnnnsOu91+TPf59zhrC3DbV+tfAdiwBdjjdgeuaQWg+VmsVgYMPQOAnFW7KNp7sEXjxcRFc9Xd53D1vecSl+w7y+7DVWs4474/8Zd336O00tXSkk9IWVUV1/7zX5RVVQHwo1+fRUxcdFhqOZyMRF8jkJKSkqN2oDpeqQ2dgEtLSyktLQ3q2CIiIiIiIhIeQQ0AlyxZgmEYXHXVVccc/gF06tQJgLy8vGCWIyZUF1gB6NsC7G7SZlsrACPDgKFTAo+XzmvZKkC/kyf04Vf/uZrR5w7GsBjU1rt5/ONPGXvnvfztvf+16vmA1XV13PTvZ9myfz8AZ141ij6ndG219z8W6Q2dgMEb9FWATTsBaxuwiIiIiIhI2xDUxMV/IH3fvsfXJTM62reyprq6OpjliAk1ngHoWwHo7wAMagISKZJSOtClh2/V7vIP1+Gudx/ljmMTl+jkktun8It//ZjeQ7sAUF5dzaMffsyo393Db19+lY179gblvY6kvKqKqx97gkUbNwMw7Ix+TP3JmJC+54lIjY/D0hCYB7sRSErDCkBQIxAREREREZG2IqiJi9XqW9XlabKq61gUFxcDkJSUFMxyxGS8HO4MQG0BjkQDh50JQHmJi/Vfbwvq2J16pjP775dw00OX0mtoNgBVtbW8svgrzvrzX7j4bw/z+ldLKXUFd3vwpr37uOhvD7N0Sy4A/UZ040e/mhr2rr+HY7VYSImPA4J/DmBK55TAYwWAIiIiIiIibUNQuwBnZmaybds2cnNzj+u+lStXApCdnR3McsRk6uvq8TQ0/LA5GsJid9MtwOYLWuTwevYbSYwzgSpXGUv/t5bB43oH/T16Dcmm15Bstq/by+J3VrFmYQ4et4flW7exfOs2fv/f1xjfvz/TTxnKuP59m2yLPT5lVVU8/ennPDH/E2obVjMOO6MfP/r1Wc26VZtNRkICRWVlHDhQRH19PTZbcP44j3JGEZ8WT3lRubYAi4iIiIiItBFBDQDHjBnD1q1beffdd7nzzjuP6Z7KykreeOMNDMPgtNNOC2Y5YjJ1dY3NChrPAGyyAlBnAEYMm83OSUMmsfKrd9m8bDsH9h0ktVNSSN6r+8Asug/M4rybK1n6wXd8M28tJfnl1Na7+XTtOj5duw6AflmdGNuvD8N79uSkzp3ITk094rbymro61uzYxQffruKdb5YHmn1YbRbOunYsp1823PQrUtMTE2CPb8X1gQNFZGZ2CNrYKdmplBeVqxOwiIiIiIhIGxHUAPCSSy7hxRdfZNWqVTz77LNce+21R71n9uzZlJSUYBgGV1xxRTDLEZPxdwCGxi7A/jMADcMw5VZLObLBp57Fyq/m4vV6WfLeGmbcOCGk75eQEsuZV41m8pWj2LVxP6sWbGLNwi2UHfA1CNm0dx+b9u7jmc++AMAZ5aBjcjLp8fEkxcYC4KqpoaCsjK15+dS5m59d2H1QFhf+dBJZvTJC+nUES3p8PGAAXvLzC4IaAKZmp7Fz1Q5tARYREREREWkjghoAnnPOOYwaNYqlS5dy4403kp+fz6233nrY165atYo777yTjz76CMMwmDZtGiNGjAhmOWIy/g7AcOgZgFaTr7aSQyWldKRbr2HsyF3JN/PWcdZPxuCIPvbu3yfKYjHoNqAT3QZ04rybJrI3t5At3+4kZ+VOtq3dR31tPQCumlq25uWzNe/ITTKsdiv9R3Rj7PlD6HNK14gKoR02G0lOJwddlRQUBLcRiL8T8O7du/F6vRH130VEREREREQOFdQAEOC1115j5MiR5OXlceedd/LHP/6RzMzMwPXhw4ezZ8+ewMH1Xq+XLl268NxzzwW7FDGZ2sMEgP4VgNr+G5mGjDibHbkrqSqvZtWCTYw8e1Crvr/FaiG7bybZfTM5Y+YI6mvryd9VzL6theTtOED5gUrKSiqpKvd1GLdH2UhIjSMtK4mu/TvSY3AWMXHRrVpzMKUnJjQEgIV4vR6MIM2jlM6+ANDlclFYWEhGRmSsihQREREREZHDC3oAmJ2dzTfffMNll13G0qVLqa6uZteuXYEVJN9++y3ehkYQACNHjuStt94iLS0t2KWIyTQNAANNQAIrABUARqJuvYaRmNyB0pI8Fr+7mhHTBoZ1tZjNYSOrV0bEbONtqYyEBHL276e+vo7i4hJSU1ODMm5qduOfx7t27VIAKCIiIiIiEuGCHgCCLwT86quveP/993n++ef58ssvKSoqClyPi4tjwoQJXH311Vx88cWhKEFMqK7pGYB2fwDoXwGoLYaRyLBYGHzqWSz65Dn25hSwc8N+ug3oFO6y2o2MxMbOxwUF+UEMABvH2bVrF6eeempQxhURERERkci3d+OecJdwRGauLdxCEgD6nXvuuZx77rmAbyvZwYMHiYuLIyEh4Sh3SlvUtAlI4xZg3wrAI3VrFfMbOHQyX33+Cu76Wha/u1oBYCuKcTiIi46morqa/PwC+vc/KSjjJndKwTAMvF6vGoGIiIiIiEgzr/3ulXCXICeg1VIXp9NJp06dFP61Y/4mIFarBaOh6Yf/DEBtAY5c0c54+g0aD8CahVsoL3GFuaL2Jb3hz1TfuareH37xMbI5bCR1TAJQACgiIiIiItIGKHWRVuM/A9DqaFx46j8DUFuAI9vJw88GwF3n5uv314S5mvbFHwBWV1dRVlYetHFTGs4BVAAoIiIiIiLga+IaSb+kuRPaAvyHP/wh2HUE3H333SEbW8LLfwZg4/l/jZPSalEAGMkyO/WkU3Z/9u3eyOJ3V3P6j4Zjd4T0hAFp0PQcwPz8/KCtsk7tnMLWb2Dnzp1BGU9ERERERETC54R+Qr/33ntD1ulTAWDbFVgB2HD+n3/1H4DF0GLUSHfKmPPY99pGKkpcrPxkI6OmDwp3Se1CfEwM0XYH1XW1FBQU0Lt376CM618BuHfvXtxuN1arNSjjioiIiIiISOs74dTlWJdbHs91adsatwD7ggR/AxDQGYBtQY++I0hM7gDAwjdWak63EgNIS4gHfCsAg8XfCbiuro68vLygjSsiIiIiIiKt74RWAH7++ec/eP3RRx/l7bffxmKxcOaZZ3LGGWfQq1cvYmNjqaysJDc3l88++4z58+fj8Xi48MILueWWW07oC5DI0bgF2L8C0BO4ZtEW4IhnsVgZNnoGn8/7F/k7D7Bp+Q76j+ge7rLahYyEBPYcOEBFRTkulwun09niMVMbVgCCbxtwVlZWi8cUERERERGR8DihAHDChAlHvHbbbbfxzjvv0L9/f1599VUGDTr8NsDbb7+ddevWcdlll/H222/TpUsX5syZcyLlSISo/V4A6O8ADNoC3FYMGHIGXy14hZrqCha+vkIBYCtpeg5gQUEB3bp1a/GY/hWA4GsEMmbMmBaPKSIiIiIiIuER1NTlk08+4ZFHHiElJYUFCxYcMfzzGzhwIAsWLCA5OZmHH36YTz/9NJjliMnUfW8LcLMzALUCsE2wO6IZfOpZAGxZuYu9uQVhrqh9SIqNxWbxzauCguD8N0/MTMLa0LBHnYBFRERERMQwjIj6Jc0FNQB88sknMQyDWbNmkZmZeUz3ZGZmMmvWLLxeL0899VQwyxET8dK4BTjQBKTpGYBaAdhmDBlxNhaL7zNe+MbKMFfTPlgMI+jnAFqsFpI7pQDqBCwiIiIiIhLpTmgL8JGsWLECgCFDhhzXfUOHDgVg2bJlwSxHTKS+rg5PQ1OIwBbghjMAlc63LXEJqfQbNJ4NaxawasEmps0aS3JGwtFvlBZJT0wg7+BBSkpKqK2txeFwtHjM1OxUinYWagWgiIiIiIgEXH7Z/XTO6h/uMg5rz96NvPLa78JdhikFNQD0bz2rqak5rvv8rw/W1jUxH38HYGjaBdgXAFoU/rU5p4w5nw1rFuCu9/D5qyu48KeTwl1Sm5eR4A9ZvRQWFpCV1bnFY/obgezevbvFY4mIiIiISNvQOas/vXoOD3cZcpyCuu8yOTkZgIULFx7Xff7XJyUlBbMcMRH/9l8Am735GYBWi7b/tjVpmV3p1W8UAEv/t5ay4sowV9T2pcXHB5rp5OcH5x9TUhoagezbt69ZiC8iIiIiIiKRJajJy6hRo/B6vbz00kt8/fXXx3TP0qVLeemllzAMg1GjRgWzHDGRZisAA12AfQGgVgC2TSPGXwJAfW09X7y+IszVtH1Wi4WUuFgACgqCcw6gvxOw1+tlz549QRlTREREREREWl9QA8AbbrgB8AU7U6dO5cknn2y28qupuro6nnrqKc466yzq6+sBmD17djDLEROpbboC0NHQBKThDECtAGybMjv1oluvUwD4au4aKkpdYa6o7Utv2AZcVHQAt7u+xeP5twCDOgGLiIiIiIhEsqCeATh16lRmzZrFM888Q2VlJTfffDO/+93vGDt2LL169cLpdOJyucjNzWXJkiWUlpbibWgMMWvWLM4888xgliMmUneYFYD+LcAWBYBt1sgJl7IjdyW11XV8+ea3nD3rtHCX1KZlJCawce9ePB43RUUHjrkb+5GkdE4NPFYAKCIiIiIiErmCGgAC/Otf/8LpdPLYY4/h9Xo5ePAg8+bNO+R1/uDPMAxuvfVWHnrooWCXIibS7AxANQFpNzpl9yO7+2B2b/+Oxe+s4vTLTiUmLjrcZbVZaQkJgAF4KSjIb3EAGJ8WjyPGQW1VLTt37gxKjSIiIiIiItL6gr70yjAMHnnkEb788kvOP/98HA4HXq/3kF9RUVFccMEFLFq0iIcffhhDIVCb1vwMwOYBoLYAt20jx18KQHVlLYveXhXmatq2KJuNpFgnAHl5LT8H0DCMwCpAdQIWERERERGJXEFfAeg3duxYxo4dS21tLWvWrGHfvn1UVFQQFxdHVlYWgwcPxuFwhOrtxWT8AaDVZsEwjIYgWCsA24PO3QbSKbs/+3Zv5IvXVzL2/CHEJsSEu6w2KzMxkYOVlRQWFuDxeFq8xT41O5W8nP3aAiwiIiIiIhLBQhYA+jkcDoYPHx7qtxGT8zcB+X4HYNAZgG2dYRiMmXQ5bz5/F9WVNSz473LOvWF8uMtqszISE9i8bx/19fUcOFBEenpGi8bzNwJRACgiIiIiIhK5lLxIq/A3AbHZm3cABm0Bbg+yuw+mS48hACx6exWlRRXhLagNy2joBAzB2Qbs3wJcWFhIZWVli8cTERERERGR1qfkRVpFYAVgQwMQT9MVgNoC3C6MPeNKAOpr6/nkxaVhrqbtirLbSXLGApCfn9fi8VKzGzsB6xxAERERERGRyKQAUFrF91cAuputAFQA2B50yOpNr/6jAVj6v7UU7i0Jc0VtV0aibxVgQUFBs9W2JyK1S1rgsToBi4iIiIiIRCYFgNIq6r63AtDfARjAYujbsL0YM+kKDMOCx+3hg6cWhbucNisjMRGg4RzAAy0aK61reuDx9u3bWzSWiIiIiIiImUycOBHDMLj33nuprq7mvvvuo3///sTExJCens6ll17Khg0bDrnviy++wDAMjIYdjV999RXnnnsu6enpxMTEMHjwYB566KFm/Q8OZ968ecyYMYMOHTrgcDjo0KED5513Hh999FHQv1YlL9Iqag85A1BNQNqj1PRsBg6bAsDaRTnkrtaW0lDwrwAEyM9v2TmA0XHRxKXGAbBjx44WjSUiIiIiImJGNTU1TJo0iXvvvZdt27bhcDgoKirijTfeYNiwYcyfP/+I97799ttMmDCBDz74gPr6eurr61m7di23334706dPD+QhTXm9Xm688UamT5/O+++/T2FhIbGxsRQWFvLee+8xbdo0brnlFrxeb9C+RiUv0ir83/D+LsCehhWABjoDsL0ZM+kKHFFOAOb+8/PA90JbUnHQxboluXz232W8+8/PeX3OJ7z9jwV8/PxXLP9oPXu25OOu/+F/CWqJaLudRKfvv3FeXsvPAUzr4lsFqABQRERERETaoieeeII1a9bw/PPPU1FRQWlpKWvWrOHUU0+lpqaGyy677Ig/W1177bVMnjyZbdu2UVJSQmlpKXPmzMFqtfLxxx9zzz33HHLPQw89xFNPPQXAr3/9a4qKiigpKaGwsJBf/OIXAPzzn//k0UcfDdrXaAvaSCJH4PV6A1uAbf4twA0rALX6r/1xxiYyasJlfDn/P+zNLWTZR+sYNX1wuMtqsZqqOlZ+soEV89ezY/3+o77e5rCR3TeTPqd0of/IHnTuk4kliOdhZiQmUupyBc4BbMlcS+uazo5V2xUAioiIiIhIm1RaWspLL73EFVdcEXhu8ODBfPzxx/Tr14/CwkL+/ve/89e//vWQezt37sy7775LVFQUAE6nk9tvvx2Xy8Vdd93Fww8/zC9/+UtSUlIAcLlc/PGPfwTg1ltv5cEHHwyMlZKSwt/+9jfKy8v517/+xX333cf1119PTExMi79GpS8ScnV1dfgXrfpXAPrPANT5f+3TkBHTSUrpBMC8Z5ZQVVEd5opOXH2dmy9eX8GfL/83bz706ffCP4MYZyIJSRnExqdgsVgb76utZ/vavXz83Nc8PPtl7r3oCV554EPWLs6htrquxXVlNmwDrq+vo7i4uEVjpXX1NQLZtWvXUc+wEBERERERiTRdu3bl8ssvP+T5lJQUZs+eDcAbb7xx2Ht/8YtfBMK/pn7+85/jdDqprq7m/fffDzw/f/58Dh48iNVq5Xe/+91hx7z77ruxWCwUFxfzySefnMiXdAitAJSQa7rf3Wb3BSD+MwDVAbh9strsjJ96De/9989UlLj4378Xc/Ftk8Nd1nHbuWE/r/2/j8nb0dhoIzm1E/0GT6RLj5PJ6NADm90RuObxuCkvLSJ/Xy55e3PYu3MdeXtzAS8VB6tYMX8DK+ZvwBFto+/w7gyZ0IeTRvfEGR993LX5G4EA5OfnkZaW9gOv/mH+RiB1dXXs3buXLl26nPBYIiIiIiIiZjNhwoRAQ4/DXQPfkUjFxcWBlXx+EydOPOx9cXFxnHLKKSxatIhvv/2Wq6++GoCVK1cCcNJJJ9GhQ4fD3puVlUX//v1Zv349K1euZMaMGSfyZTXTLgLAiooK1q1bR25uLlu3biU3N5fS0lIA/vznPzNo0KAWjV9fX88HH3zAwoUL2bdvH+D7sCZMmMD06dOx2drFf+YjahoAWh3fWwGoALDd6tFnOD36jmDb5mV8/f4aTj3zJLoN6BTuso6Jx+Pl81eXMe+ZJXg9vvWt6R26M+b0K+je59Qj/sVhsVhJTM4kMTmTPgPGAuCqLGXn1lVs37KSHTkrqamppLa6nrWLcli7KAeL1UKfYV0YeFovBp7Wi4SU2GOqMdpuJyHGSVmVi7y8fAYMGHjCX2/TTsA7duxQACgiIiIiIm1KVlbWMV0rLCw8JAA8lnsLCgqajXG0+8C3tXj9+vXN7m2JdpFMffPNNzzyyCMhGbuqqoq77rqLLVu2AOBw+Fb75Obmkpuby5IlS/jDH/5AdPTxr+BpK2p+aAWgtgC3W4ZhcPq0/2P3tu+oq6vm9Tmf8It/XYnVZj36zWFUW13Hy/fPY+2iXABs9ijGTrqSISOnN9vie6ycsYn0HzyR/oMn4q6vY8+OdeRs/Jqtm5fhqijB4/awafkONi3fwVsPf0r3QVmMOGsgJ0/sQ1SM4wfHzkxMoKyq5ecAfj8AHD9+/AmNIyIiIiIiIuHRLgJAgOTkZHr27EmvXr3o1KkTf//734My7uOPP86WLVuIjY3lpz/9KaNGjQJg6dKl/OMf/2DTpk088cQT3HbbbUF5v0jUbAVg4AxANQERSEhKZ8ykK1j48TPkbS/ii9dXcMblI8Nd1hFVllbxzO/fCZzzl5KezbmX/oaU9M5BGd9qs9O111C69hrKGdNvJG/vFnI2fk3uxqWUluTh9cK27/ay7bu9vPPoAk6ZchKnX3YqqZ2SDjteRlIiOXl51NXVUlJSTGrqiW0Djk+Lx+GMotZVo0YgIiIiIiLS5vh3cx7tWnp6+mGvd+vW7QfvzcjIOGSMvXv3/mBNe/bsOeTelmgXAeDEiRM544wzAr+vqKgIyrjbt2/nyy+/BHydW0aPHh24Nnr0aDweD3/5y1/44osvuPDCC+natWtQ3jfS1DVdAdiwBdjj8W0Bth5hq6S0H0NGTGfjd19QsH8rHz33NSeN7knH7id+Xl2olOSX8dSv3qJgl6+hRo8+w5l20S9wRLW8G9PhGBYLWV36k9WlPxPOvIaCvB3kbvyaDWs+p+xgPjVVdXz13hq+/uA7hk8dwNnXnXbI9uCMhITA47y8/BMOAA3DIK1rGvs27mX79u0t+rpERERERETMZuHChUe91q1bt0O2//qvHy4ArKysZMWKFQAMGzYs8Pypp54KwIYNG8jLyzvsOYD79u1j48aNAJxyyinH/oX8gHax/MpqDc2WwoULF+L1eunYsWOz8M9vzJgxdOzYEa/X+4PfTG1d8xWAVrxebyAA1ApAsVitTJlxCxaLDXedm5f+NI/62vpwl9VMSX4Z//z5a4Hwb+CwKZx72W9DFv59n2EYpHfoxujTZ3LtT5/koqv+QO+TxgAGXo+XZR+u44Ern2HJu6vxer2B+2IcDhJinICvEUhLpHXx/SuVVgCKiIiIiEhbs2PHDv773/8e8nxJSQlPPvkkAJdccslh750zZ06z3MPvH//4By6Xi+joaM4999zA81OmTCE5ORm32839999/2DHvu+8+PB4PqampTJky5US+pEMofWmB7777DoChQ4ce9tB/wzAYOnRos9e2R98PAP3hHygAFJ+Mjj0YffpMAPZvK+TD/3wV5ooaHSws5/Hb36A4rwyAkeMvZfK5N2MJ0T8sHI1hsdClx8mcc+mv+ckt/6TvwHEA1FTV8dYjn/H0b9+hsrQq8PqMRN8qwPz8Arxez2HHPBZpXX2rB3fs2NEsZBQREREREYl0iYmJXH/99bz00kvU1dUBsHbtWs466yzy8/NJSkri9ttvP+y9u3bt4oILLggslqiqquLhhx/mrrvuAuDnP/95s5WDTqczcO3RRx/lt7/9LSUlJQAUFxfzy1/+kn/9618A3HPPPcTEBGfhidKXE+T1egP7sX9oa6+/W+bu3btbpS4z8geANrsVwzACHYABLNoCLA1OHXsBnbL7A/DFa8vJXR3+OVN2oIInfvEGB/YdBGDkhMsYM+mKI3b5bW3JaVmcffEdXHrNAySl+Doob/xmO/+45b8U7vH9BZKZmAhAXV0txcUlJ/xe/kYgFRUVFBUVtbByERERERER85g9ezaDBg3ixz/+MfHx8SQlJTF48GCWLVtGVFQUr7766mG36gI8++yzzJ8/n+7du5OcnExCQgK33XYbbrebqVOncu+99x5yz89//nNuuOEGAB588EHS0tJISUkhPT2dv/3tbwDcdNNN3HLLLUH7GhUAnqCqqiqqq6sBDrsH3M9/raqqiqqqqiO+ri3zB4DW73UABrBqBaA0sFisnHXhbdgd0Xi98OIfPqC0KDjndZ6I8hIXT/ziDQp3+0Kz4addxOiJM8NWzw/J6noSV9zwd04aMgmAwj0lPHLzK+zNLQisAATIz88/4fdI79a8E7CIiIiIiEhbERUVxeeff869995Lt27dqKmpIS0tjUsuuYSVK1cyderUI9574YUXsnDhQs455xysVis2m41Bgwbx97//nf/9739ERUUdco9hGDz55JN88MEHnHPOOaSmplJeXk5qairnnnsu8+bN45///GdQF5+0iyYgodA0zDvch3m4a1VVVT+4dPOll17ilVdeOeL1mTNncvnllx9npeHj297rbVwB6LBhtVqbbR+0Wi1aBWgCFgwwwceQnNKBKTNuZt6bcygvcfHCfR9wyyM/wmZv3e22FQddPHnHm+Tv9J35d8qY8xk3+aqwrvw72jyJjnZy1vk/IzU9m0WfPI+rrJon73iTW/8xk4QYJ2VVLgoKCxgaNfSE3r9Tr6zA48LCQpKTk09onLbE//2QmJiobdEm5D9iwmKx6PvVhDR/zE9zyNw0h8xN88fcNH/kSKKjo7nnnnu45557jvveMWPG8P777x/3fdOnT2f69OnHfd+JUABoIpWVlRQUFBzxusvlCllDk9DxNlkB2LwDMIDV0ApAaa7/oAnk7dnCt0vfZ/u6vbz7z8+5+OeTW+39K8uqePwXr7N/WyEAQ0eey4QzrzHNtt8fYhgGI067iBhnAvPnPkplaRWP3/4ap/9mHGW4yNu/P/C645XSORWLzYqn3s327dsj8M+i0NFZpuZmGIa+X01M88f8NIfMTXPI3DR/zE3zR9obBYAnqOlKvpqamiO+rum1ox3cGBsbS0ZGxhGvO51O3G73Ea+bjf8P1MYzAH3fbk2/BovF/KGKtL7xZ15D/v6t7N25gUVvf0tmlxTGXTjs6De2kKu8mid+8Tp7c3xB/MnDp3H6tOsiIvxratCwKdTX1bJg3lOUHahk6VMryLq8B7XUUlhYSHp6+tEH+R6L1UJadioF2wvIzc2NqD+LQsUwDCwWCx6PR/96bEIWiwXDMJp1nhfz0PwxP80hc9McMjfNH3Mz6/xRWCyhpgDwBMXExBATE0NVVRXFxcVHfJ3/mv/1P+TKK6/kyiuvPOL1oqKiQGeYSOBb7m40WQFowe12U19fH3iNAXhM9Iduu2P4tv968IKJPgbDYmX6xb/ilX/9goryA7z1yKc4E6IZcnrfkL1ndWUNT/7yLXZv9p2TN3DYFE6f9n94IWz/x6Dptt/jnScnjzib0pJ8Vn79Lvm5Rbg/MOh2QU927dpFQkLC0Qc4jJQuaRRsL2Dz5s0R9WdRqFitVpKTkyktLVUgakLJyclYrb7O8/p+NR/NH/PTHDI3zSFz0/wxN7POn7S0tHCXIG2c1ryeIMMw6Ny5M+Br+Xwk/mvZ2dmtUpcZBQJAR8MW4IY/ZH0NQCJrZZW0ntj4ZC748b1ERcfh9cLL989j84odIXmvyrIqnvrVW+za6Nsie9LJk5h8zk0YEb4t4LTJV9GlxxAAir4tpGT9AfLy9p/weGldfP+nRE1AREREREREIktk/3QbZoMHDwZg1apVR3zN6tWrm722PTpkC3DDMng1/5CjScvowvlX3IXN5sBd7+HZO+eyadmOoL7HwcJyHvvpa+zc4AvG+g2awJTzbon48A/AYrVy9kW/wBmbBMDO97azZ+se3J4T+5fOtK6+rcOFhYVUVISvQ7OIiIiIiEgwfPHFF3i9Xu69997jum/ixIl4vV5TbSM/msj/CTeMxo8fj2EY7Nu3j6+//vqQ61999RX79u3DMAwmTpzY+gWagNvtprauDmhsAuJ2NwSAbSBgkdDrlN2Pcy77DRaLjbqaep75/TusWrApKGPnbS/iH7f8l/ydBwDftt+p5/8Mi6XtnL8RE5vAlPNuBaDeVc+2d3M5UHTghMZK79Z4dqBWAYqIiIiIiESOdpPAlJWVBX41XblSWVnZ7FrT8+kArrvuOmbMmMHDDz98yJjdu3dn/PjxADz66KMsXbo0kAAvXbqUxx57DPAlw126dAndF2diFeWN/62tDl+o4vH4twBrBaAcm+69T+G8y38fWAn44h//x7ynF+Nxn/ihyqs/38zDN73CwYJyAEaMu5jJ596MpQ0evtujz6kMGOrrpHxwQzEr5i07oXH8KwBBAaCIiIiIiEgkaTdNQI7UXOP+++9v9vs///nPDBo06JjHvemmm9i/fz9btmzh/vvvx+FwAI3bXvv168fs2bNPsOrIV1pWGnj8/S7AFqPd5M8SBN16DePCq/7A+6/eT5WrjE9f/oat3+3hR7+aSnrn5GMex1VezdzHv2D5R+sBMAwLE6Zey9BR54aqdFMYN+VqcjZ+TW11JYv++QVTZk7FHmU/rjFSuzQeTKwAUEREREREJHIogWmhmJgYHnzwQa699lp69uyJ1WrFarXSs2dPZs2axf333090dHS4ywybsrKywGOb3b8CUFuA5cRkdenP5f83h4yOPQHYvnYv/2/WC8x9/AvKiyt/8N7amjoWvrmSB6/+TyD8i3EmctFV97X58A8gxpnAsHGXAVBZUMnnT3923GM4oh0kZiYCCgBFREREREQiSbtZAfjee++d0H1PP/30UV9js9k4//zzOf/880/oPdqystLGANDfBdi/AtCqJiByAhKSMrjs2gdZuvA1Vix5m/raeha+sZLF76yi34hu9B/Zgw7dU4mOjaK+1k3BrmJyVu1i7aJcqitrAuP06j+aSWffQGz8sa8ejHSDhp3JxtWfUlq4i0+f+JjTrhyHMzH2uMZI65pOaX6pAkAREREREZEI0m4CQAmPsmZbgK3g9WoFoLSYze7gtMk/ps+AsXy14CW256zEXe9h/VfbWP/Vth+8Ny2zG2NOv5ye/Ua2UrXm4YyO5qSRF/L1Bw9TXV7NZ099wrm/Ov+4xkjrms7WZbls3749NEWKiIiIiIhI0CkAlJA6WNoYAFrtNtyexqYNagIiLZXRsQfnX3E3+fty2bDmc3I2fEVlefEhr3M4YujRdzh9B02ge69hGO00fLYYBp17nExaVl+K9m5m4bOfM/7q0wPbeo9FevcMAHbv3k1NTQ1RUVGhKldERERERExoz96N4S7hiMxcW7gpAJSQanoGoNVhC6z+AzUBkeDJ7NSLzE69mHjWdVRWlFBcuAe3uw7DMEhK6URiUka7Df2+z+lw0G/EBSx+50Fqq2r5/OlPOf/3Fx3z/endfAGg1+tlx44d9O3bN1SlioiIiIiICb3y2u/CXYKcAP1ELCHlPwPQAKw2C253kwBQKwAlyAzDIC4+hS49BtO99yl06zWMpJQOCv+aiHE4SM7sTkb2QAAWv7SIyoM/3EClqYweGYHH27b98HZrERERERERMQf9VCwhVdpwBqDVbsUwDDwed+CaVSsARVpdtN2OYRj0GnYWALWuGr58/otjvt+/AhBg69atwS5PRERERERMyuv1RtQvaU4JjISUfwuw1d68AzCoCYhIOBiGQbTdTmrH3qR27A3Al//5nBpXzVHu9HHEOEjq6OucrABQREREREQkMiiBkZDybwG2OawAzc4AtBraAiwSDs6Gxh09h0wFoLKkkpVzlx/z/RkNjUC0BVhERERERCQyKACUkCoLbAH2rwDUGYAi4RbjcACQ0WUAiamdAPjy+S+OeZl8esM5gFoBKCIiIiIiEhkUAEpIHSz1BYC2hgDQ07AF2NcBWAGgSDhE221YDAPDsNB7yBQA9m3cy7blucd0v/8cwPz8fCoqKkJWp4iIiIiIiASHAkAJqcAZgA1bgN0NTUCsWv0nEkZGYBVgx14jsDuiAfjy+YXHdHdGj8zAY60CFBERERERMT8FgBJS/jMArfbmZwBq+69IePkDQAwb/YZNBmDNh6s4mHfwqPf6zwAEnQMoIiIiIiISCRQASkiVNpwBaHM0PwPQtwVYRMLFGeUIPO4z7CwAPG4PS15edNR7U7PTsFh9c1gBoIiIiIiIiPkphZGQcbvdVFZWAo1NQDwNW4AtFn3riYSTw2bD2jAPY+LTyO41FICv/7sYd737B++12q2kZqcC2gIsIiIiIiISCZTCSMj4z/8DsDVsAXY3NAGxGtoCLBJejecAulwuBo8+B4CywjI2Ldxw1LvTu/vOAdQKQBEREREREfNTACghc/DgwcBj/xbgxjMA9a0nEm7+ALCuro6ufUcSFRMHwNI3vj7qvRk9fOcA5ubm4vV6Q1ekiIiIiIiItJhSGAmZ0tLSwGOr3QbeJisA1QREJOximpwDWFtXT7+hkwBY9+l3VBRX/OC96d18AWBpaSnFxcWhK1JERERERERaTAGghEzzANAaWP0HagIiYgYOqw1bQzMPl8vFwBHTAHDXuVk5d/kP3utfAQjaBiwiIiIiImJ2SmEkZBITEzl3xrkkd0jCEe3A7WlsLGDVFmARU4hxRAG+ADCzc19SO3QD4JujbAP2nwEIagQiIiIiIiJidkphJGSGDBnCsy8+y6ApJxMdH/29FYDaAixiBs6GcwDdbje1dbUMGH4WAHvW72bvhj1HvC+pYxL2KDugAFBERERERMTsFABKq3G7mwSAWgEoYgrOJucAulwuTjplCkbD/PzmzSOvArRYLKR1Swe0BVhERERERMTslMJIq/G4m24B1gpAETOwWqw4bL4u3S6Xi9iEFLr1HQ7At++vxNMkuP++jO6+cwC1AlBERERERMTcFABKq2l6BqCagIiYhzPKfw5gFV6vl35DzwCgrKCU3G9yjnhfekMAuH37drxeb+gLFRERERERkROiFEZaTdMzALUCUMQ8/OcAer0eqqqq6TVwLDab77lv31txxPv8jUBcLhd5eXmhL1REREREREROiAJAaTXuhi3AvgYgCgBFzCLaYQ/MSJfLhSPaSY8BowFYPe9b6mvrD3tfRo+MwGNtAxYRERERETEvBYDSavwrANUARMRcLIaFKLtvxZ/L5QIIbAN2lbrYtGjjYe9L76YAUEREREREJBIoiZFW418BaDW0+k/EbPzdgKurq/C4PXTvPxJHdCwAK+cuP+w98WnxxCTEAJCbm9s6hYqIiIiIiMhxUwAorUYrAEXMy38OIICryoXN7qD3oHEArP3kO2qrag+5xzAMMnr6zgHMyTlysxAREREREREJLyUx0mqanwEoImYS5bAH5mZgG/CwSQDUumpYv2DtYe/L7NkBUAAoIiIiIiJiZgoApdW43b4VgFatABQxHQODGEfzcwC79BpGdGwCAGs+XHXY+zJ7+QLA3bt3B+4TERERERERc1ESI63G42lYAagAUMSU/AFgbW0t9XX1WKxWeg0YC8D6Beuoq6475B7/CkCv18u2bdtar1gRERERERE5ZkpipNU0ngGoLcAiZuSMigo8dlX5VvP1HjwegJrKGjYt2nDIPZkNZwCCtgGLiIiIiIiYlQJAaRUejwev1wuA1dC3nYgZOWy2wBb9wDbgPsMC3YAPtw04rUs6VrsVUAAoIiIiIiJiVkpipFV4GhqAAFi1AlDEtPyrACsrfQGgzeag50mjAV834Pra+mavt9qtpHVNBxQAioiIiIiImJUCQGkV7obtvwAWrQAUMS3/OYBudz21NbVA4zbgqrIqcr7ecsg96gQsIiIiIiJibkpipFX4OwCDmoCImJmzIQAEcLkqAejWbzg2RzRw+G3AHRo6AW/duhV3k9W+IiIiIiIiYg5KYqRVaAuwSGSwWa3YrTYAKhvOAbQ7ounRfyQA381fjadJoA+Q0RAAVldXs3v37lasVkRERERERI6FAkBpFW5PYwCoLcAi5uaM8q0CrKqqCjTv8W8DrjhQwdZluc1e718BCNoGLCIiIiIiYkZKYqRVeJqcAagVgCLm5g8APR4P1dXVAPToPwqrzQ4cug04o0dm4HFubvNwUERERERERMJPAaC0Cv+5YBbDABQAiphZTLNzAH3bgB3RTrr2HQ7Amo9WNQv1o+OiSeyQBMCWLYc2CREREREREZHwUgAorcIfFqgBiIj5WQwLUXbfaj9/AAjQe9A4AErzS9m9dleze/zbgLUFWERERERExHyUxkir8K8AtBpa/ScSCWIbVgFWV1cHAvweJ43GaDjDc+38Nc1en9nTFwBqC7CIiIiIiIj5KACUVqEVgCKRJSYqCgCv10tVVRUAzrhEOnUfCMDaT75r9vqMnr5zAA8cOMCBAwdasVIRERERERE5GqUx0ioazwDUt5xIJIi22zEaVuw23Qbca+BYAPZv3kfRrsLA8007AescQBEREREREXNRGiOtwu32rQBUB2CRyGAYBjGOQ88B7DlgbODx2vmNqwA79O4YeLx58+ZWqFBERERERESOlQJAaRUeT8MKQG0BFokYTodvG3BNTQ319fUAJKdnkZrZFYC1nzSeAxifnkBsciwAGzdubOVKRURERERE5IcojZGQ83obzwDUCkCRyBHT0AgECJwDCNCzYRvwtuVbqSypAHwrBjv06QRoBaCIiIiIiIjZKACUkPN4PHi9XkBnAIpEkii7DWvDqt3KykPPAfS4Paz/fH3g+Y4N24AVAIqIiIiIiJiL0hgJOU9DAxAgECaISCQwAqsAXa7KwLMdsvsRm5AKwNr5jduAO/TxBYBFRUUUFRW1Yp0iIiIiIiLyQ5TGSMi5PY0BoMXQFmCRSOKM8gWA9fX11NbWAWBYLPQ8aTQAGxduoK7a93zHhi3AoFWAIiIiIiIiZqIAUELO3WQFoJqAiEQWfyMQaL4K0H8OYK2rhi1f+cI+/wpAUCMQERERERERM1EaIyHncXsCj9UERCSy2KxW7FYr0PwcwC69h2F3RAON3YDjU+OJT4sHtAJQRERERETETBQASsg13QJsVRMQkYjjjPKtAqyqcgUa+tjsDrr1GwHAuk++C3T67tDQCGTTpk1hqFREREREREQOR2mMhFzzLcBaASgSafwBoMfjobq6OvC8vxtwWWEZu9bsBBrPAdy8eXMgLBQREREREZHwUgAoIecPAH0NQBQAikSaGIc9MHObbgPu3n8kRsO5nv5twP5zAEtKSigoKGjVOkVEREREROTwFABKyPm3BqoBiEhkshgWoh2+bsBNG4HExCaS1X0QAGvnfwdAx76NnYC1DVhERERERMQclMhIyPlXAKoBiEjkionyBYDV1dXNtvX7twHn5eyncEcBHZt0AlYAKCIiIiIiYg4KACXkGrcA69tNJFLFOqICj12uxm3APRsCQPCtAnQmxpKQkQioE7CIiIiIiIhZKJGRkHO7tQVYJNJF2W1YG+Zw0wAwKbUTaR26A43nAPpXAWoFoIiIiIiIiDkokZGQ83gatgAb2gIsErkMYhrOAaysrGx2xb8KcNuKrVQUVwTOAdy0aZM6AYuIiIiIiJiAAkAJucYzAPXtJhLJnFG+bcD19fXU1tQGnvefA+j1eFn/2Vo69s0CoLy8nD179rR+oSIiIiIiItKMEhkJKY/H03gGoAJAkYjmbFgBCFDZpBtwZuc+xCWkAb5twFknZQWurV+/vvUKFBERERERkcNSIiMhVVHRGBJoC7BIZLNZrThsNqD5OYCGxULPgWMA2PTlRlKzUzEaun4rABQREREREQk/BYASUqUHDwYeawWgSOTzbwN2uaqane/n3wZcW1XLthXbyOiRCSgAFBERERERMQMlMhJSpaUHA48tWgEoEvH824C9Xg9VVVWB5zv3GoIjygnA2vlryOrv2wasAFBERERERCT8FABKSJU0WQGoJiAikS/G4cBoCPNdlY3bgG02B936jwBo1ghk+/bth3QNFhERERERkdalREZCqvRgaeCxtgCLRD7DMIi224HmjUAAeg3wbQMuLyrH5rAC4PV62bRpU+sWKSIiIiIiIs0okZGQOljaGACqCYhI2+A/B7Cmpob6enfg+e4njcJi8QV/RbsOBJ7fsGFD6xYoIiIiIiIizdjCXYAcO6vVGu4SjpuvCUgi0LACUBmgqRhN/terz8bcTPT5xEY5OFDue1xV5SI+PgGA6Jh4Ovc8mV0535Lz9WaciU5cpS42bNgQkX9+HY3/a2qLX1tbo8/IfDR/Ios+J/PRHIoc+ozMR/NH2isFgBEkOTk53CUct4OlB4FELIZFTUBMzMAwU74kh2Ex0ScUZXdgtVhwezy4XC6SkpIC13oPHseunG8p2JpPt6Hd2bFqO5s3b47IP7+OVUJCQrhLkB9gtVrb9PdfpNP8MT/NIXPTHDI3zR9z0/yR9kYBYAQpKSkJdwnHJSEhgdKGLcBWi4EHb5grku8z8IV/Xrz6dEyoaehntvnjjIqivKqKiopK3G43/iWKPfqP5jMeAcCw+p5bs2YNxcXFgeYhbYXVaiUhIYGysrKG/wZiJgkJCVitVtxuN2VlZeEuR75H88f8NIfMTXPI3DR/zM2s80dhsYSaAsAIYqY/nI5V6cFSiAeLxcBk+YXg2/Zr0PDR6PMxn6Z5mck+H6fDQXlVFW53PTU1NUQ1nAuYkJJJelYvCvfmUl7o2ydcVlbGzp07yc7ODmfJIeN2uyPyz+f2RJ+PeWn+RAZ9RualOWR++nzMS/NH2hs1AZGQ8jcBsRj6VhNpS5xRjsDjykpXs2v+bsBFuwoDz61fv751ChMREREREZFDKJWRkDrYsG3ZatG3mkhbYrVYibL5FpG7XJXNrvUc6AsA8RJYxagAUEREREREJHyUykhI+ZqAoAYgIm2Qs2Hbb1VVFR6PJ/B8RlYv4pMzAXDE+F6zbt261i9QREREREREAAWAEmKlB/1NQPStJtLWxDYEgF6vF1eTbcCGYdBrwBgA6qprAVi7dm3rFygiIiIiIiKAAkAJIY/HE+h6ZVEAKNLmRDvsgfM9K4+wDdjr8XUv2blzZ8R1MhcREREREWkrlMpIyJSVleH1+n74t2oLsEgbZASagVRWNg8AO/c8maiYuGbPaRWgiIiIiIhIeCgAlJBputpHKwBF2ib/NuD6+npqamoCz1utNrr3H9nstWvWrGnV2kRERERERMRHqYyETPMAUCsARdoi/wpAOHQVYC9/N+AGCgBFRERERETCQwGghExxcXHgsdXQt5pIW2S1WImy24FDA8Bu/UZgsdoCv//uu+9atTYRERERERHxUSojITNixAjee+dtslJSsNus4S5HRELEvw24qqoKt9sdeD4qOpYuvYcFfr99+/ZAYyARERERERFpPQoAJWQSEhI4ZegwYqOiAp1CRaTtcTYEgAAul6vZtd6Dxzf7vVYBioiIiIiItD6lMiIi0iLRdhvWhkY/h54DeBpGkyZACgBFRERERERanwJAERFpISOwCrCyshK8jVeccYlk9zw58PvVq1e3cm0iIiIiIiKiAFBERFrMfw6g2+2muqa62bXegycEHq9YsaJV6xIREREREREFgCIiEgROhyPw+PvbgHsPGgcYAOzevZuKiorWLE1ERERERKTdUwAoIiItZrFYiLb7QsDvB4CxCSlkZvUL/F7nAIqIiIiIiLQuBYAiIhIUsdG+ALC6upr6eneza32HTgw8/uSTT1qxKhEREREREVEAKCIiQeE/BxCgsrL5Nt+mAeCnn37aShWJiIiIiIgIKAAUEZEgcdjs2K1WACoqmm8DTkjOICmlOwBbt25t9dpERERERETaMwWAIiISNM6GVYAulwuPx9PsWrc+owCoq6tj2bJlrV6biIiIiIhIe6UAUEREgiYu2hcAer0eXC5Xs2v9T5kUePzcc8+1ZlkiIiIiIiLtmgJAEREJmhiHA4vh+6vl+9uAO3bvSayzIwBffvllq9cmIiIiIiLSXikAFBGRIDICzUAqKyvA6228YjHo2HkYAPn5+ezevTssFYqIiIiIiLQ3CgBFRCSoYhu2Abvdbqqqq5td69F/bODx22+/3ap1iYiIiIiItFcKAEVEJKicUQ4MwwCgoqKi2bWO3XsT6+wEwGuvvdbqtYmIiIiIiLRHCgBFRCSoLIaFGIcdOPQcwPi0eFJTBgGQk5PD1q1bW70+ERERERGR9kYBoIiIBF1sVDQAdXW11NbUBp6PckbRoePQwO/feeedVq9NRERERESkvVEAKCIiQedvBAJQUdl8G3B65y7Ex3UBfOcAeps0ChEREREREZHgUwAoIiJBZ7NaibL7twE3DwDj0xKabQNev359q9cnIiIiIiLSnigAFBGRkIiL9m0Drq6upq6uLvB8QloCKckDAV+jEHUDFhERERERCS0FgCIiEhJx0U22ATdZBRibEkdMdAKJ8T0AePfdd7UNWEREREREJIQUAIqISEjYrTai7DYAysvLA89brEazbsC7d+9m5cqVYalRRERERESkPVAAKCIiIXPEbcAZSaQkn4RhWAFtAxYREREREQklBYAiIhIy/gAQmm8DTsxMwGaLISmhF+DbBlxfX9/q9YmIiIiIiLQHCgBFRCRkjrQNOC41HovFIC31ZAAKCwv54osvwlGiiIiIiIhIm6cAUEREQupw24AtVgtxafEkJ/XDZvNdf/3118NWo4iIiIiISFumAFBERELqiNuAMxKxWOykJA0A4MMPP2y2SlBERERERESCQwGgiIiEVPNtwI0BYEJGIkBgG3B1dTXvv/9+6xcoIiIiIiLSxikAFBGRkGvcBlwV2AackJaAYUB8XFfi4tIBbQMWEREREREJBQWAIiISck23AftXAVpsFuJS4zEMCx0zTwVgyZIl7N69Oyw1ioiIiIiItFUKAEVEJOR824DtAJSXlwWeT8z0bQOOi+kTeO7NN99s3eJERERERETaOAWAIiLSKhJifKsAa2pqqKmpASC5YzIAUdFpdOzQH4A33ngDr9cbniJFRERERETaIAWAIiLSKuKiozEaHpeX+VYBxqUmYLX5/irK7jwagJycHFavXh2GCkVERERERNomBYAiItIqrBYrMVFRAJSVl4PXi8VqkJiZBECMozsWi69b8H//+99wlSkiIiIiItLmKAAUEZFW498GXF9fj6uqCoCkDr5twDW1cFL/iQC89dZbVDVcFxERERERkZZRACgiIq0mNioai+HbCFzWsA04qVNS4HrPbhMC1+bNm9fq9YmIiIiIiLRFCgBFRKTVGIZBbLRvFWBFRQUej4eYuBiiY31bg23WjiQmZgLw8ssvh61OERERERGRtkQBoIiItCr/NmCPx0NFeQUYkNwpBYD8/AJGDr8QgEWLFrFjx45wlSkiIiIiItJmKAAUEZFWFeNwYLdaASgtKwUgpbMvAKx3u+nRsA0Y1AxEREREREQkGBQAiohIKzNIcMYAUFVVRW1NLQkZiVhtvr+SXJXQu9coAF599VXcbnfYKhUREREREWkLFACKiEiri4+JCTwuLSvFYrWQ1NHXDXjPnj2MGXUpAPv27eOLL74IR4kiIiIiIiJthgJAERFpdTaLldgoX+OPsrIyvF4vKVm+bcCuqiq6ZI8gOjoeUDMQERERERGRllIAKCIiYZHgdALgdrupqKgguVMKRsO1vP2FDD/lPAA++ugjDhw4EKYqRUREREREIp8CQBERCYvYKAdWq++vodLSUuzRdhIyEgHYuXMnY0ZfBkBdXR1vvPFG2OoUERERERGJdAoARUQkTAwSo31nAbpcLmpraknrmgZAWXk5cc5OZHXqB8Arr7yC1+sNW6UiIiIiIiKRTAGgiIiETYLTGdj2W3LwIKnZaYHf79q1izGjfwTAxo0bWb58eVhqFBERERERiXQKAEVEJGxsViux0dEAlJeXYbVbScz0bQPesWMHI4dfiN3uu/7888+HrU4REREREZFIpgBQRETCKqmhGYjH46G0rJTULukAlFdUUFVVz6nDzgVg7ty5FBcXh61OERERERGRSKUAUEREwira4SDKbgPg4MGDpGanYjTsA962dSvjT7sSgJqaGl599dVwlSkiIiIiIhKxFACKiEjYJTpjAV/H35r6WlKyUgDYvn07nbMGkd15AODbBuzxeMJWp4iIiIiISCRSACgiImEXHx2N1eL7K6mkpJiM7pkAVNfUsG/fXsaN9a0C3LZtG4sXLw5bnSIiIiIiIpFIAaCIiISdYRgkNpwFWFVVRXRKDPYo37bgrVu3MvzU84iOigPgueeeC1eZIiIiIiIiEUkBoIiImEKS04ml4fC/koMHSe+WAcCePXvweCyMGH4BAB9++CF5eXlhq1NERERERCTSKAAUERFTsFgsJDSsAqysrCA5OxkAj9dLbk4O48ZeAUB9fT0vv/xy2OoUERERERGJNAoARUTENJKcToyGVYDVnhoS0hIA2LJlC5069qVH91MAePHFF3G73WGrU0REREREJJIoABQREdOwWa3ER0cDUF5eTnrPdAAqXS727NnD+NN8zUD27t3Lp59+GrY6RUREREREIokCQBERMZWkuFgAvF4v3hgCzUA2bdrEsCFnE+tMAtQMRERERERE5FjZwl1AayotLeXNN99k2bJlHDhwgKioKHr27MnZZ5/NqFGjjnu8/Px8rr/++qO+7te//jVjx449kZJFRNodh9VGfEwM5VVVlFeUk949g32b9rE/L4/ychejR13Cpwv+zWeffcauXbvo0qVLuEsWERERERExtXazAnDXrl3ccsstzJ07l/3792O1WqmsrGT16tXcf//9/Pvf/27R+AkJCSQlJR32l8PhCNJXISLSPqTExWI0PLanOrBYfL9bv34948b4moF4vV6tAhQRERERETkG7WIFYF1dHX/6058oLS2la9eu3H777XTv3p2amhrmzp3Lyy+/zPvvv0/37t2ZPHnyCb3HnDlzyMzMDHLlIiLtk71hFWBZVRWuGhcpXVIp2lHEjh07GDp0KP37jWfjpi956aWX+OUvf0lMTEy4SxYRERERETGtdrEC8OOPPyYvL4+oqCjuvvtuunfvDkBUVBSXXnop06ZNA+Cll16ivr4+nKWKiEiDlLi4QEfg6AxfYxCP18uGDRs4ffxPACgpKeHtt98OV4kiIiIiIiIRoV0EgF988QUA48ePJz09/ZDrF110EYZhUFxczNq1a1u5OhERORyb1UpCw8q+Gk8tSR2TANiyZQvdu40gLdV39t/TTz+N1+sNV5kiIiIiIiKm1+YDwKqqKnJycgAYNmzYYV+Tnp5O586dAVizZk2r1SYiIj8sJS4Wi38VYAffKkC3x8O69RuYMO4qANatW8c333wTthpFRERERETMrs2fAbhnz57AypCuXbse8XVdu3Zl9+7d7N69+4Te569//Sv79u2jpqaGxMRE+vTpw+TJkxk+fPgJjSciImC1WEmOi+NAeTluq4fEDomU5pWSk5PDWVOn8/68OdTWVvH000+fUDd3ERERERGR9qDNrwAsLi4OPE5JSTni6/zXSkpKTuh9cnJy8Hq9WCwWDhw4wNdff80f//hH/vKXv1BXV3dCY4qICCQ5ndisVgAcmVEYgMfjISd3JyOHXwjABx98wP79+8NYpYiIiIiIiHm1+RWA1dXVgcdRUVFHfJ3/WlVV1TGP7XA4OPvssxk3bhzdu3fH6XQCsGvXLt566y0+//xzlixZQmxsLLfccstRx3vppZd45ZVXjnh95syZXH755cdcX7hZLI35sn8Ln5iTBQP0EZlau55DhkFaQjx5JQfBDgkdEyjdX8bW3FxOGz+TRUtexu128+qrr/KHP/yhFcvyfSaJiYk6g9CE/H8HWSwWkpOTw1yNfJ/mj/lpDpmb5pC5af6Ym+aPtFdtPgAMpeTkZG688cZDnu/SpQu33XYbCQkJzJ07l08++YTzzz8/cM7gkVRWVlJQUHDE6y6XC2vDKhgRkfYkPjqGg/ZKquvqsKU5MPb7OgLv2XWQfn3HsmnzEp5++mnuvvvuH/zHnlBo+o8dYj6GYejvThPT/DE/zSFz0xwyN80fc9P8kfamzQeA0dHRgcc1NTWBVXrfV1NTA0BMQ8fJYLjiiiv48MMPqa2tZfny5UcNAGNjY8nIyDjidafTidvtDlp9oaY/UEUkWAwgIzGRXUVFWKIsxHWMp3x/Odu2b2fYkAvZtHkJBQUFvPrqq1x55ZWtU5NhYLFY8Hg8+tdjE7JYLBiGgdfrxePxhLsc+R7NH/PTHDI3zSFz0/wxN7POH4XFEmptPgBseu5fcXHxEQNA/1mBwVyiHR0dTZcuXcjNzSU/P/+or7/yyit/8AfXoqKiEz6jMBya/rf0mOgPVmnC8G3/9eAFfUSm03Tbr+YQOGw2Ep1OSl0uHBlRWAsrcdd7KDlgJyU5i+KSvTzyyCNMnz69VeqxWq0kJydTWloaUf84014kJydjtVrxeDwR9Xdne6H5Y36aQ+amOWRumj/mZtb5k5aWFu4SpI1r80u0OnfuHNjjv2vXriO+zn8tOzu7VeoSEZHjlxofh9ViwWK3ENspDoCSg6UMOMkX+q1atYqVK1eGs0QRERERERHTafMBYExMDL179wbg22+/PexrioqK2L17NwAnn3xy0N67uro6ECxmZmYGbVwRkfbKYlhIT0gAwJEWhT26YSG7Owu7zXf239NPPx2u8kREREREREypzQeAABMnTgTgyy+/pLCw8JDrb7/9Nl6vl5SUFAYNGnTM4x7tvID//ve/1NbWYhgGw4cPP66aRUTk8OKio3FGOTAsBjFZsQDU1Vvo2WMcAO+++y779+8PZ4kiIiIiIiKm0i4CwKlTp9KhQweqq6v54x//yPbt2wFf448333yT//3vf4DvDD6brfmxiNdddx0zZszg4YcfPmTc3/3ud7z++uts37692dkBu3bt4pFHHuGdd94BYMqUKUdtACIiIscuPSEBwzCISo4iKsEBQEzUSQDU19drFaCIiIiIiEgTbb4JCIDdbufOO+/k97//PTt27OBnP/sZTqeT6urqQFemc845h8mTJx/XuIWFhbz00ku89NJLWK1WnE4ntbW1gY7CABMmTOCGG24I6tcjItLe2a02UuPiKCovx5kVS01ZLVFR6XTIHERe/lqef/55brvtNuLi4sJdqoiIiIiISNi1iwAQoEuXLjz66KO89dZbLFu2jKKiImJjY+nRowfTp09n1KhRxz3mT37yE9asWUNOTg4lJSWUl5djtVrp2LEj/fr144wzzmDw4MEh+GpERCQp1klFdTXVsRCdFk11UTVJCcPIy19LaWkpr732GrNmzQp3mSIiIiIiImFneI92kJ2YRlFRUbhLOC6+1upl3P/YYjz6NjMnAywYePCCPiLTsTR0MAc0h46g1l3P7qIDuGvdlKw7gLvew/pNT1BRuZ9u3bqxdOlSrFZrSN7barWSnJxMSUlJs2MgxBySk5OxWq243W5KSkrCXY58j+aP+WkOmZvmkLlp/pibWedPWlpauEuQNq5dnAEoIiJtk6NhK7DFbsHZMRbDMMhIHwnAjh07+Pjjj8NcoYiIiIiISPgpABQRkYiWFOsk2m4nOjMGa5SVtJTB2O2+s/+eeOKJMFcnIiIiIiISfgoARUQkwhlkJiVisViI6xKHxWInM30EAEuXLmXVqlVhrk9ERERERCS8FACKiEjEs1ttpCck4EiMwpHgIDN9BBbD1+dKqwBFRERERKS9UwAoIiJtQkJMDLFR0cRlx2G3x5KWOgSA9957jz179oS3OBERERERkTBSACgiIm1GZmICjjgHMRkxdMwcA4Db7ebf//53mCsTEREREREJHwWAIiLSZlgsFjITE4nNiiU2PoOkxD4AvPjii5SXl4e5OhERERERkfBQACgiIm2K0xFFckI8zk5xdMwcC0B5eTkvvPBCmCsTEREREREJDwWAIiLS5qTGxZHYKZ6UjN7EOjsB8Nhjj1FdXR3mykRERERERFqfAkAREWlzDMOgY3ISCV0T6NRxPABFRUW89tprYa5MRERERESk9SkAFBGRNslutdE5O50OXU8mOjoNgIceeoj6+vowVyYiIiIiItK6FACKiEibFRcdTYfeGXTqMA6AvXv3Mnfu3DBXJSIiIiIi0roUAIqISJuW1SGVLn1G4nAkAnDffffh9XrDXJWIiIiIiEjrUQAoIiJtmmEY9B7UjU4dfB2B9+/fz5tvvhnmqkRERERERFqPAkAREWnz4uJj6Df4DGw2JwB33HEHdXV1Ya5KRERERESkdSgAFBGRdqHXoK506jAGAJfLxc033xzmikRERERERFqHAkAREWkX7FF2hoycjtUSBcA777zDu+++G96iREREREREWoECQBERaTe69utKhw4jA7+/5ZZb2LBhQxgrEhERERERCT0FgCIi0m7Y7FaGjToPi8UBQE1NDVdffTUlJSVhrkxERERERCR0FACKiEi70q1/dzp1GB34/Y4dO7jhhhtwu91hrEpERERERCR0FACKiEi7YrNbGTpqRuAsQIDPP/+ce++9N3xFiYiIiIiIhJACQBERaXe69e9Gp46jmz335JNP8swzz4SpIhERERERkdBRACgiIu2OzW7zrQK0+lYB2qy+vw5/97vfMX/+/HCWJiIiIiIiEnQKAEVEpF3q2q8rnTqMBaDe7SHGbsfj8XD99dezZs2aMFcnIiIiIiISPAoARUSkXfKtAjwXqzUagNSEeKyGgcvl4vLLL2fbtm1hrlBERERERCQ4FACKiEi71bVfF7I6+lYB7jlQzE9OHw9AQUEBF198Mfv27QtneSIiIiIiIkGhAFBERNotm93GkJHnYLPGAPDZ2g385vxzAdi9ezcXXXQRhYWF4SxRRERERESkxRQAiohIu9a1bxc6Z00EYEdhIZlJSdxy1pkA5ObmcuGFF5Kfnx/GCkVERERERFpGAaCIiLRrNoeNk4dPw+FIAuCBt+dyy7Qzueb0CQBs2rSJGTNmsHfv3jBWKSIiIiIicuIUAIqISLuX3acTXTtPBqCgrIyXvlzMPZdcyKwzJgKwbds2ZsyYocYgIiIiIiISkRQAiohIu2ePsjNg6EScMR0AeGTeR5RVVXHXRRdw67SpAOzatYuzzz6bZcuWhbFSERERERGR46cAUEREBMjq3YFuXXxhX3lVNU/O/xTDMLhjxnR+e8EMAA4cOMCFF17I3Llzw1mqiIiIiIjIcVEAKCIiAjii7fQeMJyE+B4APP3ZF+wvKQHgxjMn89isnxBls1FTU8N1113HH//4R+rr68NZsoiIiIiIyDFRACgiItIgq3cmXbN9HYBr6+uZ8/68wLVzTx3Gyz+/heTYWAAeeughpk6dSmFhYVhqFREREREROVYKAEVERBpExTjo3ncgqSmDAHhz6Tes3bU7cH14zx588NtfcnLXLgAsWLCA8ePH8+mnn4alXhERERERkWOhAFBERKSJrF4ZdMmagmHY8Hrhvtffwuv1Bq53Tk3hjV/8jCvGjQUgPz+fmTNn8qtf/QqXyxWuskVERERERI5IAaCIiEgT0bFRdO7RnU4dTgNg+dZtfLByVbPXRNntPHDFj/j3Tf9HotMJwH/+8x8mTZrEt99+2+o1i4iIiIiI/BAFgCIiIt+T1TuDrA7jcNgTALj/7blU1dYe8roZw0/lk7t+y/j+/QDYunUr06ZN409/+hM1NTWtWrOIiIiIiMiRKAAUERH5npi4aDKy0+nSeSoA+0pKeGr+Z4d9bYfkJJ6/5Ubuu+xiou12PB4PjzzyCJMnT2bNmjWtWbaIiIiIiMhhKQAUERE5jKzeGaSmDCI+ztfw44n5n7K3uPiwr7VYLPxk4ng+uvPXnNqzBwCbNm1i6tSpPPjgg9QeZvWgiIiIiIhIa1EAKCIichjO+BhSOybSNftswKC6ro4H33nvB+/pnpHB67f/lDsvOp8oux23282cOXM488wzWbduXesULiIiIiIi8j0KAEVERI6gc+9M4mKzSE8bCsB7K77lm5zcH7zHarFw/eRJzPvdrxjarSsA69evZ8qUKcyZM4e6urqQ1y0iIiIiItKUAkAREZEjiE2MISUzgeysyVgtUQDc+d83qK2vP+q9vTpk8uYdP+e3F8zAYbNSX1/Pgw8+yLRp09i4cWOoSxcREREREQlQACgiIvIDsvtlEmWPJztrMgBb9u/nmc8+P6Z7bVYrN545mf/99lcM6pINwJo1a5g8eTLPPPMMXq83ZHWLiIiIiIj4KQAUERH5Ac74GNKyksjMGEGssxMAD//vI3YVFR3zGH06deSdX93OHTOmY7daqa2t5Te/+Q233norVVVVoSpdREREREQEUAAoIiJyVNl9O2C1WOjedQb+hiB3v/rGca3gs1ut3DptKu/++nayU1MBeO211zjnnHPYvXt3iCoXERERERFRACgiInJUUU4HGV1TiYvNIjN9BAAL1m1g3spVxz3WwOxsPvjtHYzv3w+A7777jilTprBy5cqg1iwiIiIiIuKnAFBEROQYdO6dgdVqITtrMlGOBAB+/8qrVFRXH/dYSbGxPHfLjdw8dQoABw4c4IILLuDjjz8Oas0iIiIiIiKgAFBEROSY2KPsdOyRhs0WTXbnqQDsLznInPf+d0LjWS0WfnX+uTxyzVXYrVaqqqq46qqrePHFF4NZtoiIiIiIiAJAERGRY9WpZzp2h43U5EGkJPUG4D+fL2TV9h0nPOb5I07luVtuJC46Co/Hw+23384zzzwTpIpFREREREQUAIqIiBwzq81Kl/4dMAyDLp3PwWZ14PF6ueOFl6muqzvhcU/r15c3fvFzUuPiAPjNb37DU089FayyRURERESknVMAKCIichwyOicTlxhDdHQK2Vm+M/xy8/L5x/8+atG4J3XO4tXbbyU9IR6AO++8kyeeeKLF9YqIiIiIiCgAFBEROR6GQfeBnQDISB9BWnJPAJ785DPW7tzVoqH7dOzIq7f9lIxEX5ORu+++WysBRURERESkxRQAioiIHKe45FjSOydhGBaysnxbgd0eD3e8+Aq19fUtGrtXh0xeu+2ndEhKBHwrAV977bVglC0iIiIiIu2UAkAREZET0LV/R2x2KzHRaXTP9m0F3rR3H4+0cCswQI/MDF752S2kxMUC8LOf/YyPPmr5uCIiIiIi0j4pABQRETkB9mg73Qf4tgKnpI4gvWEr8OMff8KynK0tHr9nh0xeuGU2cdFRuN1urrvuOpYsWdLicUVEREREpP1RACgiInKC0rNTSEqPwzAsdM6agcMejcfr5efPvUCpy9Xi8Qd17cLTs/+PKJuNmpoarrzyStatWxeEykVEREREpD1RACgiInKCDKDH4M5YrRaiolPo3W0GAHuLS7jzv6/j9Xpb/B6j+/Tmn9ddg9VioaKigssvv5z9+/e3eFwREREREWk/FACKiIi0QJTTQdf+HQCISxhIdodhALy34lveWbY8KO8x5eRB/OlHlwCwf/9+Zs6cSUVFRVDGFhERERGRtk8BoIiISAtldkslpUMChmGQ2eEs4pwpANz16htsLygIyntcPm4ss8+cDMD69euZNWsW9S3sOCwiIiIiIu2DAkAREZEWM+h5cmeiom3YbDF063IBBgYV1TXc8NQzuGpqgvIuvzrvHM45ZSgACxYs4Ne//nVQthmLiIiIiEjbpgBQREQkCGx2G72GdsUA4uK60bPrVAA279vPb15+NShBncViYc7VV3JKj+4AvPDCCzz22GMtHldERERERNo2BYAiIiJBkpAaS5eG8wBT00bTIW0gAHOXr+S5L74MyntE2+08Pft6uqWnA/CHP/yBDz74IChji4iIiIhI26QAUEREJIg69UwnvXMShmGhc+cZxDt9Qd2f3nyH5Vu3BeU9UuLieO6WG0iKdQJw0003sWrVqqCMLSIiIiIibY8CQBERkaAy6DG4M/HJTt95gN0uxWZ1UO/xcONTz7D7wIGgvEv3jAz+dcN12K1WqqqquOKKK9izZ09QxhYRERERkbZFAaCIiEiQWSwW+p7alWing1hnB7p1mQFAUXk51/zzKUpdrqC8z8jevfjLlTMBKCws5PLLL6e8vDwoY4uIiIiISNuhAFBERCQE7FF2ThrVA0e0jbTUk+nc6XQAcvbnMftfz1JbXx+U97lo1AhuneZrOLJx40auu+466oM0toiIiIiItA22cBcgx85qtYa7hBNnhLsAORyjyf969RmZmz4f0zmW+RMV6+CkUT1Yv2QrWR1Pp7qmmKIDa1iyeQu//+/r/L8fX45htPzDvWPGdHYWFvLeim9ZsGABd955J3/961+DMnZbENF/f7ZR/s9En01k0OdkPppDkUOfkflo/kh7ZXi9Xm+4i5C2q7i4hPsfWxzuMkREwqqi1MX6r7dRW1PDxi3PU16xA4Dbzp3Oby48LyjvUV1Xx0V/mcOKhkYjDz/8MD/72c+CMraIiIiIiEQ2BYARpKSkJNwlHJeEhARKS8u4/7HFeNC3mRkZgIGBF68+IROyNFn2pzlkPsc7f1xl1Wz8ehsuVznrNv2L6uoiAH57wXnMnjo5KDUVlZVz3l/nsLvoAIZh8PLLL3PWWWcFZexIk5CQgNVqxe12U1ZWFu5y5HusVisJCQmUlZXhdrvDXY4chuaQuWkOmZvmj7mZdf4kJyeHuwRp47QFOIKY6Q+n46bswpS8RsP2RdBnZEZNd2/q8zGd450/zvhoBoztyYal2+jf5yes3/Q0tbUHeeCduTijHFw1YVyLa0qNj+PZm/6Pi/7fw5RVVXHdddfx/vvvM3jw4BaPHcki+u/PNs7tduvziQD6jMxLc8j89PmYl+aPtDdqAiIiItJKomOjGDi2FylpmZzU5xrs9ngA7nr1Dd5auiwo79GnY0eeuP5abBYLLpeLK6+8kv379wdlbBERERERiUwKAEVERFqRI9rOgDE96dilK/37/ASbzQnAHS+8zJtffxOU9zitf1/+NPNSAPbv388VV1xBRUVFUMYWEREREZHIowBQRESklVltVvoO70aP/v3p1/sqrNZoPF4vd7zwMq8sWhKU95h52hhumHIGAGvXrmX27Nna5iIiIiIi0k4pABQREQkDwzDoPjCLQSOGc1Kfa7BZY/ACv33lNf6zYGFQ3uM355/LWUNOBuCjjz7i3nvvDcq4IiIiIiISWRQAioiIhFGH7mmcOmksgwZch80WC8C9b7zFEx9/2uKxLRYLD1/zYwZ37QLAk08+yX/+858WjysiIiIiIpFFAaCIiEiYJaXHM3LKaQwdckOgMciD777Hg+/MxettWQvoGIeDp2dfT6fkZAB++9vfsmDBghbXLCIiIiIikUMBoIiIiAnExEcz6syxjBx5Cw5HIgBPzP+M2557EY/H06KxMxMTefam/yMuOgq3282sWbP47rvvglG2iIiIiIhEAAWAIiIiJmFz2Dh10gjGT/wF0VGpALyzbAVX/OOf1LWwgUf/zlk8NusaLIZBRUUFl112GTk5OcEoW0RERERETE4BoIiIiIkYFguDxgxm6rm/I9bZCYCvNudw9p//QlVtbYvGPn3gSfzlypkAFBUVcfHFF7N79+4W1ywiIiIiIuamAFBERMR0DHoM7MV5M+8hIb47AFv253H6vX/iYGVli0a+dMwo7rnkQgD27dvHRRddRH5+fosrFhERERER81IAKCIiYlKZ2R245Jr7SE05CYD9JQeZcM8f2V9S0qJxr500kdvPmQbA9u3bufTSSzl48GBLyxUREREREZNSACgiImJiCSmJXDrrbjpkngLAwUoXk+79Mzn781o07k/PPotZZ0wEYMOGDVxyySWUtDBYFBERERERc1IAKCIiYnLRsTFcfO1v6dJlAgCu2lqm/fkvfLtt+wmPaRgGd110AZeNGQXA6tWrueCCCygqKgpKzSIiIiIiYh4KAEVERCKAPcrOeT/+Kb17nwNAndvNxXMeYeGGjSc8pmEYPHDFj/jR2NEArF+/nvPPP19nAoqIiIiItDEKAEVERCKEzW7j7JmzGDjoMsDA7fFw9WNP8v6Kb094TKvFwgOXX8aPx58GwObNmznvvPPYs2dPkKoWEREREZFwUwAoIiISQSwWC5MvnMkpp16DYVjxer3c8sxzPL/wyxaN+ccfXRI4E3Dr1q1MmzaNtWvXBqlqEREREREJJwWAIiIiEcYwDMZNn8HI0bOxWBwA3P3qm/z9/Xl4vd4THvOuiy7gZ2efBUBeXh4zZszg888/D1rdIiIiIiISHgoARUREIpBhGIyeMpmx43+O3RYLwCPzPuJ3r7yGx+M54TFvP/dsHrziR1gtFioqKpg5cyZPPvnkCQeLIiIiIiISfgoARUREIpVhcOqEMYw//Q6iopIBeGXxV8z+97PU1NWd8LAzTxvD07OvxxnlwO12c9dddzF79mxcLlewKhcRERERkVakAFBERCSSGQaDxwxlwhm/wunsCMBHq7/jx48+TkV19QkPO2ngAN795e10S08H4K233mLq1KmsW7cuKGWLiIiIiEjrUQAoIiIS6QyDAcP7M/GMX5AQ3wOAb3K2ctHfHqaorPyEh+2b1Yn3fvMLJg0cAMCmTZuYOnUqjz32GG63Oyili4iIiIhI6CkAFBERaQsMg77DejFh8s9ISR4IwKa9+zjvr3PYVVh0wsMmOp08M/t67rzofBw2K7W1tdx3331MmzaN1atXB6l4EREREREJJQWAIiIibYVh0OvkrkyYPJvMjJEA7DlQzHl/ncO63btPeFiLxcL1kyfx3q/voG8n3zbjVatWceaZZ/LLX/6SvLy8oJQvIiIiIiKhoQBQRESkTTHoNiCLsaf/hOysyQAUV1RyyZxHWLxxc4tG7t85i/d/cwe/nHEO0XY7Xq+X5557jhEjRnDPPfdQWFgYjC9ARERERESCTAGgiIhIm2PQtX9HRk24lB5dzwcMXDW1/PjRx/nv4q9aNHKU3c4t087k03t+x1lDTgagqqqKxx9/nKFDh3LzzTezatWqln8JIiIiIiISNAoARURE2iSDzn0yOXXcdPr2ugKLxYHH6+U3L7/K/W/PxePxtGj07NRUnrphFu//5g4mDjgJgJqaGl5//XXOPPNMxo0bx9/+9je2bNmC1+sNxhckIiIiIiInyBbuAkRERCR0snplYLFMxOGIZ3POy9TWlfHUJ5+xo7CQR665ihiHo0XjD+7ahedvuZG1O3fx/MJFvLd8JTX19WzatIlNmzbxl7/8hU6dOnHaaacxbtw4Ro4cSbdu3TAMI0hfoYiIiIiIHI3h1T/LR4yiohPv4hgOycnJlJaWcf9ji/Ho28ycDLBg4MEL+ohMx9IkINEcMqEImz/5Ow+waeVGNuW+hMu1H/CFd0/Pvp7MxMSgvU9xRQVzl63k/ZXfsnLb9sO+Jj4+noEDBzJo0CB69+5Njx496NGjB506dcJiCc7mhOTkZKxWK263m5KSkqCMKcFjtVpJTk6mpKQEt9sd7nLkMDSHzE1zyNw0f8zNrPMnLS0t3CVIG6cAMIIoAJSgi7AAo71RAGhyETh/SvJK2bg8hy1b36Dk4CYAOiUn8exNN9C/c1bQ329vcTFfrN/IV5u38NXmLRRXVP7g66Ojo+nWrVsgEGz6KzMz87jCQf3wZW5m/eFLGmkOmZvmkLlp/pibWeePAkAJNW0BFhERaSeSOyQy+LT+2OxXsm37PPbnf8W+koNc+P8eYs7VV3L2sCFBfb+slBSuGDeWK8aNxePxsGV/Ht/t3MWGPXtZv3sPG/fspby6OvD66urqwNbh74uJiaF79+50796dHj160KtXLwYOHEjfvn2JiooKat0iIiIiIm2NAkAREZF2JC45lsGn9cHusBMdlcr2Xf/DVVvL7H8/y0/Pnspt06cFbRtuUxaLhX5ZneiX1SnwnNfr5UB5BdsLC9lRUMj2gkJ2FBT4/rewEFdNbeC1VVVVbNiwgQ0bNjQb12az0adPHwYOHMiAAQMYOHAgQ4cOJTk5Oehfg4iIiIhIpFIAKCIi0s5Ex0UxaFwvop0OoqPTydn2KvX1Lv4x72M27tnLQz/5MfExMSGvwzAM0hLiSUuIZ3jPHs2ueb1eCsrK2FlQxPbCAnYUFLKjsKjhfxvDwfr6+kOCQcMwGDBgAKNHj2bkyJH079+fXr16hSTYFBERERGJBDoDMILoDEAJugg8w6w90RmAJtcW5o/Xy85NeWzbsIUtua/gqsoDoGeHTJ6+8Xp6ZGaEucDD83q97D5QzMY9e9mwZw8b9uxlw5697DlQfMR7kpKSGDZsGKNGjWLs2LEMGTIERws7IMuJM+v5S9JIZ5iZm+aQuWn+mJtZ54/OAJRQ0wpAERGR9sow6Nq/I3GJMURHx7Ml9y2KS9axNS+fcx74fzx+/TVMHHBSuKs8hGEYdElLpUtaKlOHDA48X+pysW7XHr7dvp01O3excuu2QOORgwcPsmDBAhYsWACA0+lk+PDhjBkzhrFjxzJ06FAFgiIiIiLSZikAFBERaedSOyUxLGkg8YnxbNr4Mbv3fkplTQ1XP/Ykd8yYzi1nnYnRZEWqWSU6nYzt14ex/foEGoNsy8/nm81bWLltByu3bmPTvv14vV5cLhcLFy5k4cKFgK/JyPDhwxk3bhynn346gwYN0pZhEREREWkztAU4gmgLsARdW9jC2IZpC7DJtcH54/V62ZdbwHffLCJn+xu43b4OvcN79eDZm24goRXOBQyWqKgoDMPA6/VSU1MTeP5gZSXLcreydEsuX2/JYePefRzu/wqlp6dz+umnc/rppzNx4kRtywkys26/kkbawmhumkPmpvljbmadP/r/GhJqCgAjiAJACbo2GGC0JQoATa4Nz5/K0irWfv0tq1Y/S3W17++e2KgoHpv1EyYNGhDm6o7NkQLA7yutdLEsdytf5+Tw9eYcNuzZe8hrDMPg5JNP5uyzz+acc86hd+/eoSy9XTDrD1/SSAGGuWkOmZvmj7mZdf4oAJRQUwAYQRQAStC14QCjLVAAaHJtff54vezO3cMXHz1F0YG1gadP69eXh6/5MekJCWEs7uiONQD8vsKyMhZt3MQX6zeyaOOmwBmCTfXp04fp06czffp0Bg8eHBHbo83GrD98SSMFGOamOWRumj/mZtb5owBQQk0BYARRAChB19YDjAinANDk2sn8qa2uZeH/XmP9urfxej0A2CwWrpo4nhumTKJDUlJ4CzyCEw0Am/J4PKzbvYcv1m/kk+/W8t3OXYe8pkePHlx66aVccskldOnSpaVltxtm/eFLGinAMDfNIXPT/DE3s84fBYASagoAI4gCQAm6dhJgRCoFgCbXzubP9k1r+PCdOdTUlAaes1ksXDRqBP835Qx6dcgMY3WHCkYA+H17i4v5ePV3fLR6Dctztx0yL0ePHs2ll17KjBkzSDD5CslwM+sPX9JIAYa5aQ6Zm+aPuZl1/igAlFBTABhBFABK0LWzACPSKAA0uXY4f1wVB3nv1b+wf8+GQ66N69+XH48fxxmDBmCzWsNQXXOhCACbKior58NVq3l72XK+3baj2TWn08kFF1zANddcw8knnxz0924LzPrDlzRSgGFumkPmpvljbmadPwoAJdQUAEYQBYASdO0wwIgkCgBNrp3OH4/bzVefv8LyxW8e9nqn5GQuHzeGS0ePIjMpsZWraxTqALCp7QUFvPPNCt7+Zjm7Dxxodm3o0KFcffXVXHDBBTidzpDWEUnM+sOXNFKAYW6aQ+am+WNuZp0/CgAl1BQARhAFgBJ07TTAiBQKAE2unc+f8Ay+zAAAOYxJREFUbZuXM3/uP6hylQFgsRh4PI3/ISyGwfiT+nPxqBFMOXkQ0XZ7q9bXmgGgn9frZVnuVl5etIQPV62mtr7xh4rExESuvPJKrrvuOjp37twq9ZiZWX/4kkYKMMxNc8jcNH/MzazzRwGghJoCwAiiAFCCrp0HGGanANDkNH+oKC/m43ceZte2NQBYrBaS0uMpzitt9rqEmBhmnDqMi0ePZEi3rq3SNTccAWBTB8rLeePrb3h50RJ2FTWuCrRarZx77rnceOONnHLKKa1el1mY9YcvaaQAw9w0h8xN88fczDp/FABKqCkAjCAKACXoFGCYmgJAk9P8AcDr8bDy67ks+ewlPJ56ALoPyiKzWyrrF+dSXuJq9vqemRlcPHokF44cHtIOwuEOAP08Hg9fbtzEc198yefrmp+dOHz4cG688UbOPvtsbDZbmCoMD7P+8CWNFGCYm+aQuWn+mJtZ548CQAk1BYARRAGgBJ0CDFNTAGhymj/N5O/LZd6bczhYvA+A6FgH5/zfeBLT41jx8QbWfbUVd13j/8k2DINx/fpy0agRTB0ymBiHI6j1mCUAbCo3L59nF3zBW0uXUV1XF3g+Ozub66+/niuuuKLddA826w9f0kgBhrlpDpmb5o+5mXX+KACUUFMAGEEUAErQKcAwNQWAJqf5c4jamioWf/oCa5bPCzzX55QuXHrHmUQ5HaxesJllH61j9+b8ZvfFRUcxfdhQLhk9klN79gjKFmEzBoB+JRWVvLxoCc8v/JKC0rLA83FxcVxxxRXMmjWL7t27h7HC0DPrD1/SSAGGuWkOmZvmj7mZdf4oAJRQUwAYQRQAStApwDA1BYAmp/lzRLu3r+WT9x6jtCQPAEe0nak/Gc34i4ZhtVnJ23GA5R+vZ+UnGyg7UNns3q7paVw0cjgXjhpBdmrqCddg5gDQr7a+ng9Wfsu/P/2cDXv2Bp43DIPJkydz3XXXMXHiRCwWSxirDA2z/vAljRRgmJvmkLlp/pibWeePAkAJNQWAEUQBoASdAgxTUwBocpo/P6iutpoln73EqmUfQMP3b2bXFC786Rn0HtYFALfbw5aVO1nx8XrWLt5KfW19szFG9e7FZWNHM33YEKKOs4twJASAfl6vl6U5uTz96ed8tm49Tf+vWc+ePbn22muZOXMm8fHxYawyuMz6w5c0UoBhbppD5qb5Y25mnT8KACXUFABGEAWAEnQKMExNAaDJaf4ck327N7Hgf09SmLc98NyQ0/syY/YEktIbA62qihpWf7GZFR+vZ/u6fc3GSImL5UdjR3PFuNPonJpyTO8bSQFgUzsLC3lh4WJe/2opZVVVgedjY2O5+OKLmTlzJsOGDWuVTsqhZNYfvqSRAgxz0xwyN80fczPr/FEAKKGmADCCKACUoFOAYWoKAE1O8+eYedxuvlvxEV8teJmaGt+WX3uUjQmXnMKkHw0nOjaq2esL95SwYv4Gln+0joOFFYHnLYbBGYMGcNWEcYzr3+8HQ7BIDQD9XDU1vLtsBc998SWb9+1vdq1379786Ec/4tJLL6VDhw5hqrBlzPrDlzRSgGFumkPmpvljbmadPwoAJdQUAEYQBYASdAowTE0BoMlp/hw3V8VBFn/6AutXfxZ4Li4phjOvGs3ocwdjtVmbvd7t9rDh660smbuGLSt2NrvWL6sTN0yZxLmnnoLd2vw+iPwA0M/r9fJNTi4vfrmY+Wu+o7a+eSflkSNHMn36dKZPn052dnYYKz0+Zv3hSxopwDA3zSFz0/wxN7POHwWAEmoKACOIAkAJOgUYpqYA0OQ0f05Y3t4cFn3yHHt2rAs8l945mbOvO43B43sfdmVfwa5ivnp/Dcs+XE91ZWOg1zE5iWsnTWTm2NHEx8QEnm8rAWBTBysreW/Ft7zx9Td8t3PXIdcHDx7M1KlTGTduHKeccgoOhyMMVR4bs/7wJY0UYJib5pC5af6Ym1nnjwJACTUFgBFEAaAEnQIMU1MAaHKaPy3i9XrZnrOSRZ88R3Hh7sDznXtncNY1Y+k/qvthg8Caqlq+mbeOhW+spCS/LPB8QkwMV44fy7WTJpKekNAmA8CmNu/dxwffruKjVd+xZf/+Q647nU5GjRrF8OHDGTJkCEOGDDHVDxZm/eFLGinAMDfNIXPT/DE3s84fM/09LW2TAsAIogBQgk4BhqkpADS5/9/evUdHVR56H//NfSaT+42EREJABBSFQHkBL4CKh7eCrcci1UrbY7Wr1VZau9ZZPataL3jq0p5qWy+1p6d62lNoe1Q8L1VpqW0hergIclW8AJZ7gCTkPpn77PePScaEXJiEhOxMvp/lXnvP3s9+Zk/gcU9+PM9+aD8DIhaN6v3df9Omv62Sr+WTX5LGTC7Wp79yuS6aUdZtEBiNxrSncp/+9vttOr6/OrHfZbfr5stn657r/6/GjipM2QCwo49PntK63Xv05117tPvwkR7/fzF69GhdeOGFGj9+vC688EKVlpaqsLBQhYWFKigokKdDD8rBZtZfvvAJAgxzow2ZG+3H3MzafggAMdgIAIcRAkAMOAIMUyMANDnaz4AKh4LavW2t3tn4ivytn/TsG3dZif7v7VfowmndP9/OMAzt33FEf/v9tk7PCbRaLLpx1kx989MLNb6wYNCv3ywaW1u1Zd8Bbfxon7buP6CPqk4k/f8Pr9crr9ertLS0xNpms8lisXS7WK1WWSwW2Ww2Wa3WxNJ+zOFwKD09vcuSn5+voqIiTZw4UU6nU3a7fZB/KugPAgxzM2uAgTjaj7mZtf0QAGKwEQAOIwSAGHAEGKZGAGhytJ9BEQq2atfbr+udTf9PwcAnMwBPqBij6740W+OnlvY4++/Rj07pb7/bqj1v7lPHJnP1lIv1jYXXaeaF4wf78k3HHwrpvaPHtOfQYX1UdUJ/P1Wtg9U1qm1uHupLS8jLy9PYsWNVXl6eWMaOHauJEycqMzNzqC9vxCLAMDezBhiIo/2Ym1nbDwEgBhsB4DBCAIgBR4BhagSAJkf7GVTBgE87tryqHZvXKBRsTewvnzJa1942S5Nndf+MQEmqPlqnyhe3a+uf3lM0Ekvs/9T4cbp74QJdM+WSHs8dKZr8fp1qaFRNU5NqmppV09SkuuYW+UMhtYZCag2G5A8FFYnFZBjxnpaGYciQkXgdS7w2FIvFX8faysUMQ6FIRL5AUC2BgHzBQKcZjJN1wQUX6JJLLtHFF1+siy++WFOmTNG4ceNG/J/f+UCAYW5mDTAQR/sxN7O2HwJADDYCwGGEABADjgDD1AgATY72c14EWpu1ffP/0663X1co5E/sHz2+QAtum6XL5k6Q1Wbtcp7NZlNDTbM2vPiONv1hl4L+cOLYpJLR+qf5c/WZT82Q1+06L58DUigSUbPfr9PNLappblZ9q19Vtad1vK5Oh2trdbi6VkdPn1b4LL+MZWdnq6KiQtOnT9f06dNVUVGhgoKRM8z7fCHAMDezBhiIo/2Ym1nbDwEgBhsB4DBCAIgBR4BhagSAJkf7Oa8C/hbt3rZWOzb/QQH/J8NXC0pzNH/ppzR9wWS5PI7EfpvNlthuqm/RpjW79ebqHfI1fhIiprtdunHmp3TLlZdrygU9Dy3GwLNYLHK5XAoGg+r4VTQai6mqvl4HT1Xrw6oT+vBYlT44flwHTp7stQfhmDFjVFFRoRkzZqiiokKXXXaZ0tLSzsdHSVkEGOZm1gADcbQfczNr+yEAxGAjABxGCAAx4AgwTI0A0ORoP0MiHAro3R1vaPvG/1FL8+nEfk+6S//n01N05Y3TlDc6u1MA2P7lPhQI6+217+qtV3aq9nhDp3rLCwu0aHqFFs2o0OSS0YSBg6ynALAn4WhUH588pXePHNWuQ4e1+9BhfXDsuCKxWLflbTabJk+enAgEZ8yYoQkTJnT6e4HeEWCYm1kDDMTRfszNrO2HABCDjQBwGCEAxIAjwDA1AkCTo/0MqUgkrA/3bNA7G19R/emqxH6LRZo8a5xmXX+pplw+XnanvcuX+1jM0IGdR7T51T16938PKBbtHCKNzsnRFZMu0uUTL9IVEy/SqOys8/KZRpK+BoDdCYRC2nvsuHYfOqxdbcvhmp6/K3m9Xk2bNi0xdHjGjBkqLi7u70dIeQQY5mbWAANxtB9zM2v7IQDEYCMAHEYIADHgCDBMjQDQ5Gg/pmDEYjr8913a9fbrOrh/uzr+YXjSXaq4ZpKmXT1R5ZeWyNbNswKb61v17lv7tWvDR/p411F119QKszJ1cWmpLrmgVBcVF+mC/DxdkJengswMegr200AEgN2pb/ElegjubFvX+3w9li8qKtLUqVN1ySWXaPLkybrkkks0btw4egqKAMPszBpgII72Y25mbT8EgBhsBIDDCAEgBhwBhqkRAJoc7cd0GupOaPfWtfpgzwb5W5s6HUvLdGvyrHJdMme8JkwfI2+Wp8v5TXU+vfe/B7R/xxEd2HlEvqZAr+/ndjiUn5mh3PR05Xi9yk33KsfrVYbHo8w0jzI8bmV60trWHmV64vsyPB457fYB/ezDzWAFgGcyDENHamu169AR7Tp4SLsOH9beI8cUjER6PMftdmvixIm6+OKLNXnyZI0bN07jxo3TmDFj5HKNnEljCDDMzawBBuJoP+Zm1vZDAIjBRgA4jBAAYsARYJgaAaDJ0X5MKxqN6MjHO/X+7vX6+KOtikbCXcoUledr/GUlKr+0RCUTClVQktNpNuFYzNCJv9fo4LvHdfxAtY7vr9aJQ6cVDQ/MLwpuh6MtJPQo0+3+ZNsTX2d43MpNT1dJbo5K8/JUkpsjj9M5IO9tBucrAOxOKBLRR8ertPPQYe06eDipSUYkyWq1qrS0VOPGjVN5eblKSkpUXFys0aNHq7i4WMXFxSk18QgBhrmZNcBAHO3H3MzafggAMdgIAIcRAkAMOAIMUyMANDnaj6m1t59goFUHD+zQxx9t1aH92zvNINyRw2VX8bgClVxYoMIxucovyVZ+SbbyirJkd8Z760UjUdWfalbdyUadPtGo+lNNamnwy9f4ydLa5JffF1Ik1HMPs/7KS09XaV6uSvJyVZrbvs5RSdt2pqdrr0azGsoAsDvhaFQHT1Xrg+NV+vD4cX14/IQ+OH5cJ+ob+lRPdna2CgoKlJub22nJyclJrLOyspSdnZ3YTktLM+VQcgIMczNrgIE42o+5mbX9EABisBEADiMEgBhwBBimRgBocrQfU+uu/cSiUZ2s2q/jh/fGlyMfKBRs7bUei0XKLsxU3ugsZednKKsgXVn56couyFBWQfx1enaarNbOAU4kFJHfF1LAF5S/JZhYd9zuad1+nhHr21+sTI+nrcdgbiIULMnJSQxTzstIV3ZamqzWrs9CPN/MFgD2pCUQ0OGaWh2qrtHB6hodqqnRoeoaHa6tVU1T84Bcu8PhUHZ2diIYzMrK6hQUnnmsY3jo8XgGLTwkwDA3swYYiKP9mJtZ2w8BIAbbiAoAGxsb9fLLL2vr1q06ffq0XC6Xxo8fr+uvv16zZ8/ud72RSESvvfaaKisrVVUVn4mwpKRE8+bN06JFi2QfoOf8EABiwBFgmBoBoMnRfkwtmfYTi0VVf7pKNScPti1/V83JQ2r1NfTpvWx2qzLzvErP8SojO03p2R6l57ZvpykjN75Oz0mTN8vT7WQkZzIMQ75Gv+pPNanuZFOndft2wBfs03VKks1qbXteYbqy0jxK97iV4Y4POU53uz9Zu92djmUmnmvokWMAJsgYLgFgb8LRqKobG3WivkGnGhp1oqFBJ+obVNfSoroWnxp8PtW1tKjB16omv39QrsHpdCorK0v5+fkaNWqUCgsLNWrUqMRSVFSU2O7r8GQCDHMza4CBONqPuZm1/RAAYrCNmADwyJEjuu+++9TY2ChJ8ng8CgaDisVikqQbbrhBX/3qV/tcr9/v1/e//33t27dPUvyLmCSFQiFJ0qRJk7RixQq53e5z/gwEgBhwBBimRgBocrQfUzuX9hMMtKqx/qQa6k4klqaGarU0nVZL02mFw71PDtIbi0VKy/QoIydNGTleZeSeuW7bzvUqPcvT6bmEZ/K3BDsEgo1t282qa9vXUt9778b+8rpcykyLP68wKy0tEQ523E48yzARJH6y9jidslqtwz4A7ItwNKoGn08NvlY1traqsdWvxlafGn3+ttft++LbDR32BcNdn2HZHxkZGZ3CwfbAsKCgoNM6Ly8v8csxAYZ5mTXAQBztx9zM2n4IADHYRkQAGA6H9Y1vfEMnT55UWVmZvvOd76i8vFzBYFBr1qzRqlWrZBiGli9frgULFvSp7ieeeEKVlZXyer1avnx5oifhli1b9NRTT8nn8+nqq6/Wvffee86fgwAQA44Aw9QIAE2O9mNqg9V+DMNQMOBTS3OdWppq1dJ0Ws1Np+VrrlOrr0Gtvka1tjTI72tUKHRuvb4sVou8WR5l5HiVle9VdmGmckZlKLsgQzmjMpVTmKGs/PTEMwrPFAqE1Vjbopb6VrU0tqqlwa+WhrZ1fasCvqACrSEF2oYcB1pDCvqCivVx6HFf2axWpbdNfJLmdMrlcMhlt8vlcMhpt8vlsLet4/udDrvcdodcToc8Tqc8jra10ym30ymP06E0l0tpTqeyvGnK8XpTapblQDj8SUjo6yYs9LXqdHOLqpsaVd3YpOrGJvmCfe8d2s5qtSovL0/FxcUqKipSYWGhsrKyEiFhfn6+cnJyEkORMzIyTDGsfKQxa4CBOAJAczNr+yEAxGBLnW9HvVi3bp1Onjwpl8ulBx54QAUFBZIkl8ulpUuXqq6uTmvXrtXKlSs1f/78pIfsHjx4UG+++aYk6Z577tGcOXMSx+bMmaNYLKbHH39cGzZs0E033aSysrKB/3AAAOC8sVgscnvS5fakK79wTK9lI+FgPBBsX1oa2kLCeEDoa2lQa0uDfC313U5OYsSMeHhX36oTf6/p8X0ycr3KKcxQdmGGcgozlV0YfzZhdmE8LCy7uLjXnoSd3tMwFA5G4oGgL9QWELY/vzCQeI6hv7nDdof9rc3Bs06AEo3FEuHVYEl3u5Tt9SqnbRmVnaVRWVkqzslWUXaWinKyVZydrdz0dFNOwNGR2+GQOyt+/cnyBYKdAsHqxkadaltXNzapuim+v7s/g1gsppqaGtXU1GjPnj1nfS+r1Zp4VmHHYDAzM1NerzexpKWldVp7vV653W45HA7Z7XY5HI5O2+1rm80mwzB6XCR1eh2LxRSLxRSNRhPbHfd3XLrbH41Gu+y32WxyOBxyOp2J63Q6nbLb7Z322Ww20/99AgCMXCMiANywYYMkae7cuYnwr6PPfe5z+uMf/6i6ujq9++67qqioSKreyspKGYah4uLiTuFfu8svv1zFxcU6ceKEKisr9aUvfemcPgcAABg+7A6XMrMLlZldeNay0WikQyhYr1Zfg3xt4WB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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "ggplot(vars_df, aes(x='biomass', fill='agent')) + geom_density(alpha=0.6)" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "8fee734e-75a7-40bf-bd9f-2b40dbd07eb5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "# from plotnine import scale_x_log10, xlim, scale_y_log10\n", + "# ggplot(vars_df, aes(x='mortality', fill='agent')) + geom_density(alpha=0.6) + xlim(0,0.5) + scale_y_log10()\n", + "\n", + "ggplot(vars_df, aes(y='mortality', x='agent',color='agent')) + geom_point(alpha=0.6) + geom_jitter()" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "a0880b87-c703-43f2-961a-03a54b61cde6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "# ggplot(vars_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.6) + scale_x_log10()\n", + "ggplot(vars_df, aes(y='rew', x='agent',color='agent')) + geom_point(alpha=0.6) + geom_jitter()" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "19b6f01b-c7bc-4b78-a2e9-864f54d8050f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "ggplot(vars_df, aes(x='mean_wt', fill='agent')) + geom_density(alpha=0.6)\n", + "# ggplot(vars_df, aes(y='mean_wt', x='agent',color='agent')) + geom_point(alpha=0.6) + geom_jitter()" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "id": "2cb3b22a-a3e5-4196-bed7-0ef5ac571d4c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(0.00867406, 0.9701466)" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "MINWT, MAXWT" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c0531dd3-7caa-46cb-9af7-49c9cc4039c5", + "metadata": {}, + "outputs": [], + "source": [ + "from plotnine import xlim\n", + "\n", + "ggplot(vars_df, aes(x='mortality', fill='agent')) + geom_density(alpha=0.6) + xlim(0,0.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f574562c-f210-4b24-998b-41aa2ed51fe1", + "metadata": {}, + "outputs": [], + "source": [ + "ggplot(vars_df, aes(y='mortality', x='agent', color='agent')) + geom_point() + geom_jitter() + xlim(0,0.1)" + ] } ], "metadata": { diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index 41db2c6..6a753e0 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -3,7 +3,13 @@ import matplotlib.pyplot as plt from typing import Optional -from rl4fisheries.envs.asm_fns import observe_1o, observe_2o, asm_pop_growth, harvest, render_asm, get_r_devs +from rl4fisheries.envs.asm_fns import ( + observe_1o, observe_2o, + observe_total, observe_total_2o, + observe_total_2o_v2, + asm_pop_growth, harvest, + render_asm, get_r_devs, +) # equilibrium dist will in general depend on parameters, need a more robust way # to reset to random but not unrealistic starting distribution @@ -65,13 +71,14 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): self.reproducibility_mode = config.get('reproducibility_mode', False) if self.reproducibility_mode: self.fixed_r_devs = get_r_devs( - n_year=self.n_year, + n_year=config.get("n_year", 1000), p_big=self.parameters["p_big"], sdr=self.parameters["sdr"], rho=self.parameters["rho"], ) self.noiseless = config.get('noiseless', False) - self.flat_harv_vul = config.get('flat_harv_vul', False) + self.use_custom_vul = config.get('use_custom_vul', False) + self.custom_vul = config.get('custom_vul', np.ones(self.parameters["n_age"])) default_init = self.initialize_population() self.init_state = config.get("init_state", equib_init) @@ -91,7 +98,13 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): self._render_fn = config.get("render_fn", render_asm) # _observation_fn defaults to observe_2o unless "observation_fn_id" or "observation_fn" specified - obs_fn_choices = {"observe_1o": observe_1o, "observe_2o": observe_2o} + obs_fn_choices = { + "observe_1o": observe_1o, + "observe_2o": observe_2o, + "observe_total": observe_total, + "observe_total_2o": observe_total_2o, + "observe_total_2o_v2": observe_total_2o_v2, + } self._observation_fn = obs_fn_choices[ config.get("observation_fn_id", "observe_2o") ] @@ -126,11 +139,14 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): def reset(self, *, seed=None, options=None): self.timestep = 0 self.state = self.initialize_population() - if self.flat_harv_vul: - self.parameters["harvest_vul"] = np.ones(shape=len(self.parameters["ages"])) + # + if self.use_custom_vul: + self.parameters["harvest_vul"] = self.custom_vul + # self.state = self.init_state * np.array( np.random.uniform(0.1, 1), dtype=np.float32 ) + # if self.noiseless: self.r_devs = np.ones(shape = self.n_year) elif self.reproducibility_mode: @@ -142,6 +158,7 @@ def reset(self, *, seed=None, options=None): sdr=self.parameters["sdr"], rho=self.parameters["rho"], ) + # self.update_vuls() obs = self.observe() return obs, {} @@ -228,34 +245,34 @@ def initialize_population(self): mwt = ninit.copy() # mature weight # leading array calculations to get vul-at-age, wt-at-age, etc. - survey_vul = [ + survey_vul = np.float32([ (p["linf"] / p["lbar"]) * (1 - np.exp(-p["vbk"] * p["ages"][a])) ** (p["survey_phi"]) for a in range(p["n_age"]) - ] - harvest_vul = [ + ]) + harvest_vul = np.float32([ 1 / (1 + np.exp(-(p["ages"][a] - p["ahv"]) / p["asl"])) for a in range(p["n_age"]) - ] + ]) # - wt = [ + wt = np.float32([ (1 - np.exp(-p["vbk"] * p["ages"][a])) ** 3 for a in range(p["n_age"]) - ] - mat = [ + ]) + mat = np.float32([ 1 / (1 + np.exp(-p["asl"] * (p["ages"][a] - p["ahm"]))) for a in range(p["n_age"]) - ] + ]) mwt = mat * np.array(wt) # - Lo = [ + Lo = np.float32([ p["s"] ** a if a<(p["n_age"]-1) else (p["s"] ** a) / (1 - p["s"]) for a in range(p["n_age"]) - ] - Lf = [] - for a in range(p["n_age"]) + ]) + Lf = np.zeros(shape=p["n_age"], dtype=np.float32) + for a in range(p["n_age"]): if a==0: Lf[a] = 1 elif 0 Date: Wed, 24 Apr 2024 01:57:12 +0000 Subject: [PATCH 18/64] cautionary rule now has two possible obserrvations --- hyperpars/rppo-asm.yml | 51 +-- notebooks/popdyn_tests.ipynb | 363 ++++++++++++++++----- src/rl4fisheries/agents/cautionary_rule.py | 46 ++- 3 files changed, 353 insertions(+), 107 deletions(-) diff --git a/hyperpars/rppo-asm.yml b/hyperpars/rppo-asm.yml index cbf4bdc..b7227ca 100644 --- a/hyperpars/rppo-asm.yml +++ b/hyperpars/rppo-asm.yml @@ -8,8 +8,10 @@ additional_imports: ["torch"] # env overall env_id: "AsmEnv" -config: {'s': 0.94, 'p_big':0.05} -n_envs: 4 +config: + observation_fn_id: 'observe_2o' + n_observs: 2 +n_envs: 12 # io repo: "cboettig/rl-ecology" @@ -19,7 +21,18 @@ save_path: "../saved_agents" # id: "minimal" # algo_config: # policy: 'MlpLstmPolicy' -# tensorboard_log: "../../logs" +# tensorboard_log: "../../../logs" + +# MY GUESS CONFIG +id: "minimal" +algo_config: + policy: 'MlpLstmPolicy' + tensorboard_log: "../../../logs" + batch_size: 64 + n_steps: 1024 + gae_lambda: 0.98 + gamma: 0.995 + use_sde: True # # SLOW LEARN # id: "slow" @@ -46,7 +59,7 @@ save_path: "../saved_agents" # algo_config: # # normalize: True # not clear what this one actually does -- from the source code it seems to 'activate' VecNormalize, but more care & examination needed # policy: 'MlpLstmPolicy' -# tensorboard_log: "../../logs" +# tensorboard_log: "../../../logs" # n_steps: 256 # batch_size: 256 # gae_lambda: 0.95 @@ -68,7 +81,7 @@ save_path: "../saved_agents" # id: "cheetah" # algo_config: # policy: 'MlpLstmPolicy' -# tensorboard_log: "../../logs" +# tensorboard_log: "../../../logs" # batch_size: 64 # n_steps: 512 # gamma: 0.98 @@ -89,25 +102,25 @@ save_path: "../saved_agents" # INVERTED PENDULUM -id: "inv_pend" -algo_config: - tensorboard_log: "../../../logs" - policy: 'MlpLstmPolicy' - n_steps: 2048 - batch_size: 64 - gae_lambda: 0.95 - gamma: 0.99 - n_epochs: 10 - ent_coef: 0.0 - learning_rate: 2.5e-4 - clip_range: 0.2 +# id: "inv_pend" +# algo_config: +# tensorboard_log: "../../../logs" +# policy: 'MlpLstmPolicy' +# n_steps: 2048 +# batch_size: 64 +# gae_lambda: 0.95 +# gamma: 0.99 +# n_epochs: 10 +# ent_coef: 0.0 +# learning_rate: 2.5e-4 +# clip_range: 0.2 # # MOUNTAIN CAR NO VEL # id: "mount_car" # algo_config: - # tensorboard_log: "../../logs" + # tensorboard_log: "../../../logs" # policy: 'MlpLstmPolicy' # batch_size: 256 # n_steps: 1024 @@ -129,7 +142,7 @@ algo_config: # SPACE INVADERS V4 # id: "space_invaders" # algo_config: -# tensorboard_log: "../../logs" +# tensorboard_log: "../../../logs" # policy: 'MlpLstmPolicy' # batch_size: 512 # # clip_range: 0.1 diff --git a/notebooks/popdyn_tests.ipynb b/notebooks/popdyn_tests.ipynb index d137250..eaf9eec 100644 --- a/notebooks/popdyn_tests.ipynb +++ b/notebooks/popdyn_tests.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 48, "id": "3638cfd4-177b-4b24-b6a4-8d61d74faf80", "metadata": {}, "outputs": [], @@ -25,19 +25,19 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 49, "id": "c1131bf0-840c-4a40-b111-f3d74351795a", "metadata": {}, "outputs": [], "source": [ - "config = {'s':0.86, 'noiseless': False, 'flat_harv_vul': False}\n", + "config = {'s':0.86, 'reproducibility_mode': True}\n", "env = AsmEnv(config=config)\n", "_ = env.reset()" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 50, "id": "eb58ebf3-882d-4944-9e19-2332f3133a18", "metadata": {}, "outputs": [], @@ -52,6 +52,8 @@ " 'rew': [],\n", " 'total_pop': [],\n", " 'newborns': [],\n", + " 'children': [],\n", + " 'adults': [],\n", " 'non_random_newb': [],\n", " **{var_name: [] for var_name in other_vars}\n", " }\n", @@ -78,6 +80,8 @@ " simulation['rew'].append(rew)\n", " simulation['total_pop'].append(np.sum(env.state))\n", " simulation['newborns'].append(env.state[0])\n", + " simulation['children'].append(sum(env.state[:4]))\n", + " simulation['adults'].append(sum(env.state[4:]))\n", " simulation['non_random_newb'].append(\n", " env.parameters[\"bha\"] * env.ssb / (1 + env.parameters[\"bhb\"] * env.ssb)\n", " )\n", @@ -91,7 +95,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 51, "id": "9ab73841-a5f3-4704-ab7c-0a71ca683a90", "metadata": {}, "outputs": [], @@ -119,54 +123,209 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 52, "id": "a634dbf5-00af-44d8-b2d9-5ede8969e3e7", "metadata": {}, "outputs": [], "source": [ "trivp = Msy(env = env, mortality=0)\n", - "trivial_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), trivp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" + "trivial_ep = pd.DataFrame(simulate_ep(env, trivp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 53, "id": "6f4dc7c8-47d3-414f-bc97-d6c2290d455c", "metadata": {}, - "outputs": [], - "source": [ - "# trivial_ep.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "d4286e3d-ab4c-4244-8008-9e836c202e9c", - "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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tsurv_b_obsbare_surv_b_obsmean_wt_obsactrewtotal_popnewbornschildrenadultsnon_random_newbssbsurv_vul_bharv_vul_bstate
000.738230-0.9704710.622407-1.00.02.9535540.0243051.0903881.8631660.8066190.9100980.6348781.022081[0.024305389667785986, 0.41009481735214626, 0....
110.634877-0.9746050.622407-1.00.02.5709190.0308630.7077531.8631660.8065440.9098420.6347791.022080[0.03086255120635639, 0.020902635114295947, 0....
220.634779-0.9746090.629318-1.00.02.2109910.0000000.3478241.8631660.8059630.9078460.6331851.022039[0.0, 0.026541794037466496, 0.0179762661982945...
330.633185-0.9746730.648082-1.00.01.9014520.0000000.0382861.8631660.8040620.9013550.6269711.021398[0.0, 0.0, 0.022825942872221186, 0.01545958893...
440.626971-0.9749210.676797-1.00.01.6352490.0000000.0196301.6156180.7997390.8868260.6131871.014983[0.0, 0.0, 0.0, 0.019630310870110218, 0.013295...
\n", + "
" + ], + "text/plain": [ + " t surv_b_obs bare_surv_b_obs mean_wt_obs act rew total_pop newborns \\\n", + "0 0 0.738230 -0.970471 0.622407 -1.0 0.0 2.953554 0.024305 \n", + "1 1 0.634877 -0.974605 0.622407 -1.0 0.0 2.570919 0.030863 \n", + "2 2 0.634779 -0.974609 0.629318 -1.0 0.0 2.210991 0.000000 \n", + "3 3 0.633185 -0.974673 0.648082 -1.0 0.0 1.901452 0.000000 \n", + "4 4 0.626971 -0.974921 0.676797 -1.0 0.0 1.635249 0.000000 \n", + "\n", + " children adults non_random_newb ssb surv_vul_b harv_vul_b \\\n", + "0 1.090388 1.863166 0.806619 0.910098 0.634878 1.022081 \n", + "1 0.707753 1.863166 0.806544 0.909842 0.634779 1.022080 \n", + "2 0.347824 1.863166 0.805963 0.907846 0.633185 1.022039 \n", + "3 0.038286 1.863166 0.804062 0.901355 0.626971 1.021398 \n", + "4 0.019630 1.615618 0.799739 0.886826 0.613187 1.014983 \n", + "\n", + " state \n", + "0 [0.024305389667785986, 0.41009481735214626, 0.... \n", + "1 [0.03086255120635639, 0.020902635114295947, 0.... \n", + "2 [0.0, 0.026541794037466496, 0.0179762661982945... \n", + "3 [0.0, 0.0, 0.022825942872221186, 0.01545958893... \n", + "4 [0.0, 0.0, 0.0, 0.019630310870110218, 0.013295... " + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "trivial_ep = add_state_columns(trivial_ep, env)\n", - "melted_triv_ep = trivial_ep[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')" + "trivial_ep.head()" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 54, "id": "b5a371a2-d2d4-4a9a-87c7-30121b7d07df", "metadata": {}, "outputs": [], "source": [ "def prepare_for_altair(df):\n", - " df = add_state_columns(df, env)\n", - " melted_df = df[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')\n", + " # df = add_state_columns(df, env)\n", + " # melted_df = df[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')\n", + " # melted_df['population'] = melted_df['variable']\n", + " # melted_df['biomass'] = melted_df['value']\n", + " # return melted_df[['t', 'population', 'biomass']]\n", + " melted_df = df[['t', 'children', 'adults']].melt(id_vars='t')\n", " melted_df['population'] = melted_df['variable']\n", " melted_df['biomass'] = melted_df['value']\n", - " return melted_df[['t', 'population', 'biomass']]" + " return melted_df[['t', 'population', 'biomass']]\n", + " " ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 55, "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", "metadata": {}, "outputs": [ @@ -176,13 +335,13 @@ "" ] }, - "execution_count": 22, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -197,7 +356,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 56, "id": "7dc378fd-0a34-4279-8b7f-ae62b6f171f5", "metadata": {}, "outputs": [], @@ -208,7 +367,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 57, "id": "168e0fae-6b11-4fcc-9f64-c34c4ea5c3c2", "metadata": {}, "outputs": [ @@ -217,23 +376,23 @@ "text/html": [ "\n", "\n", - "
\n", + "
\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, - "execution_count": 14, + "execution_count": 57, "metadata": {}, "output_type": "execute_result" } @@ -297,7 +456,7 @@ "triv_population = prepare_for_altair(trivial_ep)\n", "\n", "triv_population_short = triv_population[triv_population.t < 100]\n", - "\n", + "# triv_population_short.head()\n", "alt.Chart(triv_population_short).mark_area().encode(\n", " x=\"t:T\",\n", " y=\"biomass:Q\",\n", @@ -315,18 +474,18 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 58, "id": "3e9aba5e-466a-4feb-8bc5-8bf34da520a3", "metadata": {}, "outputs": [], "source": [ - "escp = ConstEsc(env, escapement = 0.008)\n", - "esc_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), escp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" + "escp = ConstEsc(env, escapement = 0.01)\n", + "esc_ep = pd.DataFrame(simulate_ep(env, escp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" ] }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 59, "id": "ff08dfd1-c97c-407a-aec7-968d36ca6beb", "metadata": {}, "outputs": [ @@ -336,13 +495,13 @@ "" ] }, - "execution_count": 75, + "execution_count": 59, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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" ] @@ -363,7 +522,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 60, "id": "c5c5a541-abb1-44f2-b53a-01ae726f9cbd", "metadata": {}, "outputs": [ @@ -372,28 +531,28 @@ "text/html": [ "\n", "\n", - "
\n", + "
\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, - "execution_count": 76, + "execution_count": 60, "metadata": {}, "output_type": "execute_result" } @@ -468,18 +627,18 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 61, "id": "ade66528-f9fb-46b3-8d3e-9c0374c60e15", "metadata": {}, "outputs": [], "source": [ "msyp = Msy(env = env, mortality=0.057)\n", - "msy_ep = pd.DataFrame(simulate_ep(AsmEnv(config=config), msyp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" + "msy_ep = pd.DataFrame(simulate_ep(env, msyp, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))" ] }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 62, "id": "17930d75-ae56-4746-b3fc-3e24d4a894dc", "metadata": {}, "outputs": [ @@ -489,13 +648,13 @@ "" ] }, - "execution_count": 78, + "execution_count": 62, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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Ho9PpYLM5Mxj79u2Lb7/9FizLClaHP//8E0lJScjPz1f8DL/PBRdcgPvuu0/Ydvjw4Xa1TS5c1q9fj549e0KtVqNv376wWq0oKSkR3C41NTXYv38/+vXrJ3zGarVi06ZNgotl//79qKurQ9++fdvVtkBBbhc/CbOabARBEEQb6Nq1K0pKSnD06FFUV1fjvvvuQ3l5OR544AHs27cP//vf//Dss89ixowZUKlUip+x2+3o2bMnNm3ahKVLl+LAgQN4+umnsXHjxna1raysDDNmzMD+/fvx5Zdf4p133sGDDz4IAOjZsyeuvfZa3HXXXVizZg22b9+Ov/zlL+jcuTOuvfZa4RharRYPPPAASkpKsHnzZkyZMgXnn39+WMR7ACQ+/IbcLgRBEJHPI488ArVajX79+iEzMxMWiwU///wzNmzYgEGDBuGee+7B1KlT8dRTT7n9TFlZGf7v//4P119/PW6++WYMGzYMNTU1EitIW7j99tvR0tKCoUOHYtq0aXjwwQdx9913C+9/+umnGDx4MK666ioUFxeDZVn8/PPPkoXe4uPj8dhjj+HWW2/FhRdeiMTERHz11VftalcgofLqPtL18Z8AADcMzsc/bxzUwa0hCILoeKi8euAZOXIkzj77bLz55pttPsZnn32G6dOno66uLmDt4qHy6h0EWT4IgiAIon2Ef1RQmEHagyAIgmgLZWVlkqBQOXv27AlhazoWEh9+QpYPgiAIoi3k5eVh27ZtHt9fuXJlu88zZcoUTJkypd3HCSYkPvyEUm0JgiCItqDRaNCjR4+ObkZYQDEffkLl1QmCIAiifZD48BNyuxAEQRBE+yDx4SckPgiCIAiifZD48BPyuhAEQRBE+yDx4SdhVpONIAiCICIOEh9+QpYPgiAIIhzp2rWrz5VRGYbB4sWLg9oeT5D48BOK+SAIgiCI9kHiw0/I8kEQBEGIMZvNHd2EiIPEh59QnQ+CIIjI55tvvsGAAQMQFxeHjIwMjBo1Ck1NTRg5ciSmT58u2Xf8+PGSiqFdu3bFCy+8gNtvvx3Jycm4++67ccEFF+Cxxx6TfO706dPQarVYvXq1x7Y88cQTGDZsmMv2QYMG4fnnnwcAn9rlLxUVFRgzZgzi4uLQrVs3fPPNN20+lr+Q+PATcrsQBEF4gGUBc1PH/PjYP1dUVGDixIm48847sXfvXqxcuRLXX3+9XwkF//znPzFo0CBs3boVTz/9NCZNmoQFCxZIjvHVV18hLy8PF110kcdjTZo0CRs2bMDhw4eFbbt378aOHTtw6623+twmf3n66acxYcIEbN++HZMmTcItt9yCvXv3Bu18Yqi8up+Q+CAIgvCApRl4Oa9jzv3ESUCX4HW3iooKWK1WXH/99ejSpQsAYMCAAX6d6tJLL8XDDz8svL7pppswffp0rFmzRhAb8+fPx8SJE8EwjMdjnXXWWRg0aBDmz5+Pp59+GgAwb948DBs2LKjl2G+88Ub89a9/BQC88MILWLZsGd555x28//77QTsnD1k+/IS8LgRBEJHNoEGDcNlll2HAgAG48cYb8dFHH+HMmTN+HWPIkCGS15mZmbjiiiswb948AEBpaSnWrVuHSZMm+XS8SZMmYf78+QC4kg5ffvmlz59tK8XFxS6vyfIRplCdD4IgCA9o4zkLREed2wfUajWWLVuGtWvX4tdff8U777yDJ598EiUlJVCpVC79vMVicTlGQoKrhWXSpEn429/+hnfeeQfz58/HgAEDfLaoTJw4EY899hi2bNmClpYWlJeX4+abbxbe97VdkQJZPvyELB8EQRAeYBjO9dERP17cG9JmMrjwwgsxa9YsbN26FTqdDosWLUJmZiYqKiqE/Ww2G3bt2uXTMa+99lq0trZiyZIlmD9/vl+Wi/z8fFx88cWYN28e5s2bh8svvxxZWVnC++1plzvWr1/v8rpv377tOqavkOXDTyjmgyAIIrIpKSnB8uXLccUVVyArKwslJSU4ffo0+vbti4SEBMyYMQM//fQTunfvjtdffx11dXU+HTchIQHjx4/H008/jb1792LixIl+tWvSpEl49tlnYTab8cYbb0jeu/TSS9vcLncsXLgQQ4YMwfDhwzFv3jxs2LABn3zySbuO6SskPvyELB8EQRCRTXJyMlavXo0333wTRqMRXbp0wb/+9S+MGTMGFosF27dvx+233w6NRoOHHnoIl1xyic/HnjRpEsaOHYsRI0agsLDQr3bdcMMNuP/++6FWqzF+/HjJe3feeWe72qXErFmzsGDBAtx3333Izc3Fl19+iX79+rXrmL7CsGEWxGA0GpGSkoL6+nokJyd3dHMEuj7+EwBgYH4Kvr9/eAe3hiAIouNpbW1FaWkpioqKYDAYOro5RAjw9D/3Z/z2K+Zjzpw5GDhwIJKTk5GcnIzi4mL88ssvwvsjR44EwzCSn3vuucefU4Q95HYhCIIgiPbhl/jIz8/HK6+8gs2bN2PTpk249NJLce2112L37t3CPnfddRcqKiqEn9deey3gje5I7PaObgFBEAQRSfzxxx9ITEx0+xNo5s2b5/ZcZ511VsDP1xb8ivm4+uqrJa9feuklzJkzB+vXrxe+UHx8PHJycgLXwjCDLB8EQRCEPwwZMgTbtm0L2fmuueYaxXLtAKDVakPWDk+0OeDUZrNh4cKFaGpqkhQqmTdvHv773/8iJycHV199NZ5++mnEx/uWex0JkPYgCIIg/CEuLi6olUrlJCUlISkpKWTnawt+i4+dO3eiuLgYra2tSExMxKJFi4To2FtvvRVdunRBXl4eduzYgcceewz79+/Hd9995/Z4JpMJJpNJeG00GtvwNUKHjdQHQRAEQbQLv8VH7969sW3bNtTX1+Obb77B5MmTsWrVKvTr1w933323sN+AAQOQm5uLyy67DIcPH0b37t0Vjzd79mzMmjWr7d8gxJDbhSAIgiDah98VTnU6HXr06IHBgwdj9uzZGDRoEN566y3FfXmf06FDh9web+bMmaivrxd+ysvL/W1SSCHtQRAEQRDto91Fxux2u8RtIoYPsMnNzXX7eb1eD71e395mhAyyfBAEQRBE+/BLfMycORNjxoxBYWEhGhoaMH/+fKxcuRJLly7F4cOHMX/+fIwdOxYZGRnYsWMHHnroIYwYMQIDBw4MVvtDDokPgiAIgmgffrldTp06hdtvvx29e/fGZZddho0bN2Lp0qW4/PLLodPp8Ntvv+GKK65Anz598PDDD2PChAn44YcfgtX2DoHqfBAEQUQ+I0eOxPTp0zu6GQHns88+Q2pqqk/7Pvfcczj77LOD2h53+GX58LTgTEFBAVatWtXuBoU7YVaNniAIgiAiDr8DTmMdWliOIAiCkGOz2WAn07jPkPjwE6rzQRAEER3Y7XY8+uijSE9PR05ODp577jnhvddffx0DBgxAQkICCgoKcN9996GxsVF4n3dvfP/99+jXrx/0ej0+/vhjGAwGl6XuH3zwQVx66aUe22I0GhEXFydZLw0AFi1ahKSkJDQ3N2PlypVgGEZy/G3btoFhGBw9erStlwH//ve/UVBQgPj4eNx0002or69v87F8hcSHn5DbhSAIwj0sy6LZ0twhP/72z59//jkSEhJQUlKC1157Dc8//zyWLVsGAFCpVHj77bexe/dufP7551ixYgUeffRRyeebm5vx6quv4uOPP8bu3bsxadIkpKam4ttvvxX2sdls+OqrrzBp0iSPbUlOTsZVV12F+fPnS7bPmzcP48ePD1ql8EOHDuHrr7/GDz/8gCVLlmDr1q247777gnIuMe1OtY01yO1CEAThnhZrC4bNV15XJNiU3FqCeK3vg/TAgQPx7LPPAgB69uyJd999F8uXL8fll18uCUbt2rUrXnzxRdxzzz14//33he0WiwXvv/8+Bg0aJGy75ZZbMH/+fEydOhUAsHz5ctTV1WHChAle2zNp0iTcdtttaG5uRnx8PIxGI3766ScsWrTI5+/kL62trZg7dy46d+4MAHjnnXcwbtw4/Otf/wrqOm1k+fATSrX1j193V2LKpxtwukG5FgxBEERHIS8DkZubi1OnTgEAfvvtN1x22WXo3LkzkpKScNttt6GmpgbNzc3C/jqdzuUYkyZNwsqVK3Hy5EkAnOVi3LhxPmWgjB07FlqtFt9//z0A4Ntvv0VycjJGjRrVnq/pkcLCQkF4AEBxcTHsdjv2798ftHMCZPnwGzuZPvzi7i82AwBe+HEP3p54Tge3hiCIYBOniUPJrSUddm5/kK/wyjAM7HY7jh49iquuugr33nsvXnrpJaSnp2PNmjWYOnUqzGaz4AKJi4sDwzCSY5x33nno3r07FixYgHvvvReLFi3CZ5995lN7dDodbrjhBsyfP1+woNx8883QaLihWqXi7AVi95LFYvHrO4cLJD78hAwfbYMsHwQRGzAM45frIxzZvHkz7HY7/vWvfwkD/tdff+3z5ydNmoR58+YhPz8fKpUK48aN8+uzl19+OXbv3o0VK1bgxRdfFN7LzMwEAFRUVCAtLQ2As5J4WykrK8PJkyeRl5cHAFi/fj1UKhV69+7druN6g9wufkJul7ZBWUIEQUQKPXr0gMViwTvvvIMjR47giy++wAcffODz5ydNmoQtW7bgpZdewg033ODXEiIjRoxATk4OJk2ahKKiImGNNL5dBQUFeO6553Dw4EH89NNP+Ne//uXXd5NjMBgwefJkbN++HX/88Qf+9re/4aabbgpqvAdA4sNvyOvSNihLiCCISGHQoEF4/fXX8eqrr6J///6YN28eZs+e7fPne/TogaFDh2LHjh1es1zkMAyDiRMnYvv27S6f1Wq1+PLLL7Fv3z4MHDgQr776qsQy0hZ69OiB66+/HmPHjsUVV1yBgQMHSoJqgwXDhtmoYDQakZKSgvr6eiQnJ3d0cwS6Pv4TAECvUWH/i2M6uDWRA3/dBndJw7f3XtDBrSEIIpC0traitLQURUVFMBgMHd0cIgR4+p/7M36T5cNPwkuqRQ7kriIIgiB4SHz4CQ2ibYPcVQRBxDpjxoxBYmKi4s/LL78c8POdddZZbs83b968gJ/PHyjbxU9IfLQNSlEmCCLW+fjjj9HS0qL4Xnp6esDP9/PPP7tNxc3Ozg74+fyBxIef0BjaNki0EQQR64iLeYWCLl26hPR8/kBul3Zitdmx/kgNWi22jm5KWGMj1UYQBEE4IPHRTv756wHc8uF6/O3LrR3dlLCGDB8EEb3QUvKxQ6ASZMnt0k7+82cpAODXPVUd3JLwhtwuBBF96HQ6qFQqnDx5EpmZmdDpdC7lxonogWVZnD59GgzDuJSm9xcSH+1ETQ+aT5D4IIjoQ6VSoaioCBUVFcJCakR0wzAM8vPzoVar23UcEh/tREXawydIexBEdKLT6VBYWAir1QqbjWLfoh2tVttu4QGQ+Gg3KrJ8+ARZPggieuHN8O01xROxAwWcthPSHr5BC8sRBEEQPCQ+2oma/C4+QcHwBEEQBA+Jj3YidruU1zbjpx0VVM1TAXK7EARBEDwkPtqJOK3sotd+x7T5W7Bo64kObFF4QuKDIAiC4CHx0U7UCldw3ZGa0DckzCHtQRAEQfCQ+GgnStku5HZxhSwfBEEQBA+Jj3aiJD4os8MV0mMEQRAED4mPdqKUaksDrSu0sBxBEATBQ+KjnSi6Xcjy4QJdE4IgCIKHxEc7USrzQTEfrpD2IAiCIHhIfLQTxZgPEh8u0DUhCIIgeEh8tBOVgumDxllXyO1CEARB8JD4aCdKbheWBloX6IoQBEEQPH6Jjzlz5mDgwIFITk5GcnIyiouL8csvvwjvt7a2Ytq0acjIyEBiYiImTJiAqqqqgDe6oxGLC0q19Q2KgyEIgiB4/BIf+fn5eOWVV7B582Zs2rQJl156Ka699lrs3r0bAPDQQw/hhx9+wMKFC7Fq1SqcPHkS119/fVAa3pGI4xco5sM3yO1CEARB8Gj82fnqq6+WvH7ppZcwZ84crF+/Hvn5+fjkk08wf/58XHrppQCATz/9FH379sX69etx/vnnB67VHYCKccZyiLWFSkG+0TjrCukxgiAIgqfNMR82mw0LFixAU1MTiouLsXnzZlgsFowaNUrYp0+fPigsLMS6devcHsdkMsFoNEp+whGxhcPuze1CIy1BEARBuMVv8bFz504kJiZCr9fjnnvuwaJFi9CvXz9UVlZCp9MhNTVVsn92djYqKyvdHm/27NlISUkRfgoKCvz+EqFALDK8ul3I9EEQBEEQbvFbfPTu3Rvbtm1DSUkJ7r33XkyePBl79uxpcwNmzpyJ+vp64ae8vLzNxwomYo0htXy47kvZLgRBEAThHr9iPgBAp9OhR48eAIDBgwdj48aNeOutt3DzzTfDbDajrq5OYv2oqqpCTk6O2+Pp9Xro9Xr/Wx5i1CKVYbc7tzOK5dVD0SKCIAiCiEzaXefDbrfDZDJh8ODB0Gq1WL58ufDe/v37UVZWhuLi4vaepsNxH/Phui/FfBAEQRCEe/yyfMycORNjxoxBYWEhGhoaMH/+fKxcuRJLly5FSkoKpk6dihkzZiA9PR3Jycl44IEHUFxcHPGZLgAg1hg2LwGnlFZKEARBEO7xS3ycOnUKt99+OyoqKpCSkoKBAwdi6dKluPzyywEAb7zxBlQqFSZMmACTyYTRo0fj/fffD0rDOxJv2S4kPgiCIAjCPX6Jj08++cTj+waDAe+99x7ee++9djUq3BHHfCjV+RC/TxAEQRCEFFrbxUfEtgyyfBAEQRBE2yHx0QaovDpBEARBtB0SH21AbNhQynYhywdBEARBuIfEh4+IC4eJs13UCuqDDB8EQRAE4R4SH21AbNlQLjJG6oMgCIIg3EHiw0ckAad2KjJGEARBEG2FxEcbsEtiPlzVBxk+CIIgCMI9JD58RCwoKNuFIAiCINoOiY82II358Pw+QRAEQRBSSHy0AasXyweJD4IgCIJwD4kPH2FFIadit4pSqi25XQiCIAjCPSQ+2oBYXCi7XULYGIIgCIKIMEh8+Ig/AafkdnGilIpMEARBxDYkPtqAWFyolcQHmT4ElMQZQRAEEduQ+PARsZywenG72MjyIUDigyAIgpBD4qMNiC0bSjqDDB9OVHSHEQRBEDJoaGgDVi/qgiXLhwBZPgiCIAg5JD58xU3AKQtXoUGptk7EMTEkygiCIAiAxEebEAecktvFCyLDB2kPgiAIAiDx4TNiC4c3twvhROx2oUBcgiAIAiDx0SYkAacd2I5IQFwBltxRBEEQBEDiw2fEk3arl2wXwom4yBgVXyMIgiAAEh9twu4l4JRwInG7kOWDIAiCAImPNkExH74jFh92ewc2hCAIgggbSHz4iFhuSAInSYd4ROx2oYBTgiAIAiDx0SYo4NR3GHK7EARBEDJIfPiIuEAWuV3aBhUZIwiCIAASH21CurYLDai+Qm4XgiAIAiDx4TPuVrWl4dQzYnFGbheCIAgCADQd3YBIxM6yYFkWjSZrRzcloqBsF4IgCAIg8dEmbHYWjyzcgW+3HEeXjPiObk5YcvxMM/JS4txnCREEQRAxC4kPH5FXOP12y3EAwLGa5g5qUfiyaOtxPPTVdlx3TmfJdSO3C0EQBAH4GfMxe/ZsnHfeeUhKSkJWVhbGjx+P/fv3S/YZOXIkGIaR/Nxzzz0BbXRHY6dB1CPvLD8EAFi09YRkO5VXJwiCIAA/xceqVaswbdo0rF+/HsuWLYPFYsEVV1yBpqYmyX533XUXKioqhJ/XXnstoI3uaHxJtY3lLBiVqLKYuPw8WT4IgiAIwE+3y5IlSySvP/vsM2RlZWHz5s0YMWKEsD0+Ph45OTmBaWEY4ssM3s4CasbrblGJRqX8xcnyQRAEQQDtTLWtr68HAKSnp0u2z5s3D506dUL//v0xc+ZMNDe7j4swmUwwGo2Sn3DHavM+iMbyLF+8notYb1C2C0EQBAG0I+DUbrdj+vTpuPDCC9G/f39h+6233oouXbogLy8PO3bswGOPPYb9+/fju+++UzzO7NmzMWvWrLY2IyTIXSi+zOBjWXxo1GK3ixPKdiGCRZPJinidWlLOnyCI8KXN4mPatGnYtWsX1qxZI9l+9913C38PGDAAubm5uOyyy3D48GF0797d5TgzZ87EjBkzhNdGoxEFBQVtbVZI8EVYxPJAq3IzAMSyICOCR3ltMy567Xdc3CsTn985tKObQxCED7RJfNx///348ccfsXr1auTn53vcd9iwYQCAQ4cOKYoPvV4PvV7flmaEDLmO8CXgNJYHWnHMh8TtEsOCjAgeCzdzae+rDpzu4JYQBOErfokPlmXxwAMPYNGiRVi5ciWKioq8fmbbtm0AgNzc3DY1MBzxJdU2ltNxVW4CTmNZkBHBQ02uFoKIOPwSH9OmTcP8+fPxv//9D0lJSaisrAQApKSkIC4uDocPH8b8+fMxduxYZGRkYMeOHXjooYcwYsQIDBw4MChfIBTIh0xfLB+xvPKtdDBwXodYFmRE8NDEaloZQUQwfomPOXPmAOAKiYn59NNPMWXKFOh0Ovz2229488030dTUhIKCAkyYMAFPPfVUwBocDviWahu7A60k4FRc4TSGrwkRPNzFGBEEEb747XbxREFBAVatWtWuBkUCPgWcxvAsnwJOiVCiprW5CSLioMfWB+Sii8SHZyQBp6LtsXxNiOChVlE3RhCRBj21bYDEh2fcBZzGchwMETwo5IMgIg8SHz7QloDTWI5vkKbaUsApEVzU5HchiIiDnto24FPAaQwPtCo3bheyfBDBgFJtCSLyIPHhA20pMhbLA627heVi2RVFBA8yfBBE5EGPbRvwxaoRywOt2s3CcrEsyIjgIQ449ZaRRxBEeEDiow34Iixiuc6H+wqntKwtEXjElg/StwQRGZD48AEWlGrrD+4CTsnyQQQDcV0ZKwlcgogISHy0AV8yWWJZfLgLOI3la0IED43I7UL3GEFEBiQ+fIBWtfUPCjglQolaJbZ80D1GEJEAiY824FPAaSzHfIhTH8Vru9DAQAQBsdi12egeI4hIgMRHG6CYD8+IBwM7xXwQQUasdcPhHtteXod7vtiMo9VNHd0Ugghb/FpYjuAg8eEZsRncIroOsXxNiODBhpl17dr3/gQAHD7diGUzLu7g1hBEeEKWjzbgi0slllNtJT54m130d+xeEyI0hFO2yxGyfBCEW0h8+IBcR/hm+QhSYyIAtcTt4txOdT6IYBCuGVXh1BaCCDdIfLQB38RH7A60KjdrbYSDP56IbugeI4jIgMSHD7StyFiwWhP+uBMfsZwBRAQPcSE7sjYQRGRA4qMN+CQ+aKB1gdIgiWAgWTmZ7jGCiAhIfPiAS8yHLwGnNANzgUziRLAhywdBRAYkPtqALx1cLA+0cjcVDw0MRDCQrpwcw/5OgoggSHy0AZ9WtaWB1oVYFmREMKGYD4KINEh8+IC8O6OYD8+4++qxnAFEhAYSuAQRGZD4aAPkdmkbsZwBRASPcKtwShCEd0h8+AArm8pTwKln3H1zsnwQwYZEP0FEBiQ+2gCt7dI2aGAggoG0wikJXIKIBEh8tAGfAk5jOObDXdAHCTIiGIhvNwvV+SCIiIDEhw+0pTuL5Vm+u28ey9eECA3hIHBVygV+CYIQQeIjSIRDJxhu0DUhgoG4rkw4CFw1qQ+C8AqJDx9oiwclpgNO3Xz1cBgYiOgmHGI+SHwQhHdIfAQJGmhdiWVBRgQPSYXTMIj50KioWyUIb9BT4gttsXzEcMCpu/LqVPqaCAbSbJeOf+7I8EEQ3iHxESTCoRMMN+iaEMEmHCyOGjV1qwThDb+ektmzZ+O8885DUlISsrKyMH78eOzfv1+yT2trK6ZNm4aMjAwkJiZiwoQJqKqqCmijIwEqr+5KOAwMRPQhLgIYDgKXYj4Iwjt+iY9Vq1Zh2rRpWL9+PZYtWwaLxYIrrrgCTU1Nwj4PPfQQfvjhByxcuBCrVq3CyZMncf311we84aFE7EZgfOxXbGHgew43wmFgIKKbcBC4GhIfBOEVjT87L1myRPL6s88+Q1ZWFjZv3owRI0agvr4en3zyCebPn49LL70UAPDpp5+ib9++WL9+Pc4///zAtbyD0KpUMPuwSElMWz7cbA+HYEAiuqFsF4KIDNrlnKyvrwcApKenAwA2b94Mi8WCUaNGCfv06dMHhYWFWLduneIxTCYTjEaj5CfcEOsIXzuWWM7scL+qbexeEyJ4SLJdwuAeI/FBEN5ps/iw2+2YPn06LrzwQvTv3x8AUFlZCZ1Oh9TUVMm+2dnZqKysVDzO7NmzkZKSIvwUFBS0tUkhQaP2rWMJh04w3IhlaxARGsLB3UnigyC802bxMW3aNOzatQsLFixoVwNmzpyJ+vp64ae8vLxdxwsG4u7MV38updq6QpYPIhiEW4VTivkgCO/4FfPBc//99+PHH3/E6tWrkZ+fL2zPycmB2WxGXV2dxPpRVVWFnJwcxWPp9Xro9fq2NKND8DWNjgZaV6jOBxEMxDo/HJ47NRUZIwiv+PWUsCyL+++/H4sWLcKKFStQVFQkeX/w4MHQarVYvny5sG3//v0oKytDcXFxYFrcwWh9nNX4EJMavbiL+QgDkzgR3ZDlgyAiA78sH9OmTcP8+fPxv//9D0lJSUIcR0pKCuLi4pCSkoKpU6dixowZSE9PR3JyMh544AEUFxdHdKaLuI6A2seYj3CIug83wmFgIKIPqeWj4587ivkgCO/4JT7mzJkDABg5cqRk+6effoopU6YAAN544w2oVCpMmDABJpMJo0ePxvvvvx+QxoYDWh9NqrE8yXf31cPBJE5EN+EgcEl8EIR3/BIfrA9BlAaDAe+99x7ee++9Njcq3BB/a187lnCYgYUblO1CBINwW9tF3EfY7SxUJEYIwgWKjPITX8VHLBfUcidSKeaDCAbi+y0cLB/imI9waA9BhCMkPnxAPJZSnQ/v0NouREcRDgJXPEEJB0sMQYQjJD78gGF8T6OjgdYV6oiJYCC+q8LhuROLDwu5XwlCERIffuJrGp01hnNt3a7tQh0xEWTC4R4T9xHhYIkhiHCExIcPiCso+hzzEQYzsHDDzsb2mjdEkAiztV0AsnwQhDdIfPgBA7J8+IKnpBbKeCECjXhyEG6WBnI1EoQyJD58oQ2r2obHDCz8oM6YCCbh8dyJsm/CTAwRRLhA4sMPGIbxw/IRu52Ou4XlABIfROAJtwqnYsJDDBFE+EHiwwekRcZ8zXYJr04wXKDOmAg04ZbtEs5iiCDCBRIffuBXzEcYdIIdhceYjxi+LkTwCQeLo7gFljBoD0GEIyQ+/MTnImPU6ShCFiEi0LCSbJfwur9IbBOEMiQ+fEBS4dTntV2o01GCrgsRTMxhIPrF5d4tMZz1RhCeIPHhB/5UOI3lTsfTAoRkESICDSvJLun45y7cFrojiHCExIcPiDs3ivloG/x1s1OdDyLAiG+pcBP9FPNBEMqQ+PADBgzUPsd8hFcnGEqUuls+VoZEGRFMwsGyJs126fj2EEQ4QuLDB9oS80GDrBSNw10VDoMDEV1IskvCIOBUmvrb8e0hiHCExIc/MFTh1BeUPCtOywd1xkTwsFjD67kjsU0QypD48BNa26VtaNXcrUY+cCLgiNRuOIhbVtIeut8JQgkSHz7QlgqnsbyCq1J5dZ2ad7t0/OBARBfiu81sDa/7KxzEEEGEIyQ+/MCfCqdA7M56lNwuWofbhSwfRDAJt2eOAk4JQhkSHz4gNqP6GvMB0KxHDO92oWtCBBpJhdMwELfh1h6CCEdIfPgBw5DlwxeUU20p24UIPmab3WORu1AgdjuGW90RgggXSHz4ia91PgAaaMXoHNfNTJ0xEWDkYkPJ1fHxH0fw046KUDVJwBKjExCC8AaJDx8Q921aHwJOeeNItLoYWJbFw19vx6tL9rl533WbTkOWDyI4yO8oeVzR/soGvPjTXkybvyU07RFXXA2zAFiCCBdIfPgBA8anmI9oL6h16FQjvt1yHHNWHvbZxC1ckygVZET4IC80Vtds7qCWkNuFINxB4sNPND64Xfh9ojXSXfy1lONaXLdpNVTngwgOcv0rF/18vBG3b/DvP9br80EQBIkPP2B8rHDK7xOtsx6tSID5+h35mA+q80EEGle3i/QeE9+voYg5EgechlvdEYIIF0h8+IAva7uIOzhnWml0znq0opmkUueqXOeDt3xQZ0wEF/k9phHFaYXa8kb3O0EoQ+LDDxi4r3Aqtojwf0drzIdK5f9MUkPl1YkgIXelyO8xiaUuBJYIScApiQ+CUITEh5+4s3yIZ1daVewsouaz5SOGrgnRschde2Kx7E0MtFpsOHSqsV3nl6yyS2KbIBQh8eEBlmVRXtss8eG6i/kQB6KqhRVco7PjEc80lTpXpbVdNFRenQgR8ntMLIa9Wepu/vc6jHp9FVbsqwpIW6iuDUEoQ+LDAx/9cQQXvfY7XvmFq2fBMIyPlo/oTrWVdOY+mrGpwikRLOSWNlfrhmexLGb78XoAwIIN5e1okKgtFHBKEIr4LT5Wr16Nq6++Gnl5eWAYBosXL5a8P2XKFDAMI/m58sorA9XekPLyz5zo+GVXpbDNneVD7FfWqGPHxeCr20VHAadEiJA/d22JwWiP1ZLKqxOEd/wWH01NTRg0aBDee+89t/tceeWVqKioEH6+/PLLdjWyo2BkOoOB+zofErdLLFk+fA045dOPY0CQEaFF7uYzW2VuF8l7wRcfYsjNSBDKaPz9wJgxYzBmzBiP++j1euTk5LS5UeGCVq1y6azcZbtI3C5RXmTMWx0DWliO6EgCYvloh8WiLeKcIGKNoMR8rFy5EllZWejduzfuvfde1NTUuN3XZDLBaDRKfsIFvVp2eTysaqtRSLWNVpNrWzpzLRUZI4KEt5gP1o+YD572iGRptgvd7wShRMDFx5VXXom5c+di+fLlePXVV7Fq1SqMGTMGNptNcf/Zs2cjJSVF+CkoKAh0k9qMkovFfbaLQsBplFo+xPga88FbhmiVTyLQeFtYri1iOVAWCxIfBKGM324Xb9xyyy3C3wMGDMDAgQPRvXt3rFy5EpdddpnL/jNnzsSMGTOE10ajMWwEiFZu+YA0sNTddqHIWJQOtBIfuq+WD43DGkTR/0SQkVst2uIGaY/LVJKKbo3OPoAg2kvQU227deuGTp064dChQ4rv6/V6JCcnS37CBbn48FThVOx20US5i0Fa50Mp5kNhYbkYsgYRocV7qq0TXwNO22OxkLhdKMCaIBQJuvg4fvw4ampqkJubG+xTBRydxvXyuI35ELtdonxtF/G3Mil15kpuF3V0x8EQHYdc7HqO+Qh1tgvd7wShhN9ul8bGRokVo7S0FNu2bUN6ejrS09Mxa9YsTJgwATk5OTh8+DAeffRR9OjRA6NHjw5ow0OBXGgwDOM+5iOG1nZpiw+dsl2IUBGImI9AZbuQ24UglPFbfGzatAmXXHKJ8JqP15g8eTLmzJmDHTt24PPPP0ddXR3y8vJwxRVX4IUXXoBerw9cq0OEUsyHO8uHWJQ4U22jddbjf6otre1CBAu528XTPearGAhUfQ6yfBCEMn6Lj5EjR7qsIilm6dKl7WpQOKGVuV0Yxn22i3RV2+hewbUt5dV5IWeO0mtChA/tWduFp10Bp6K/qc4HQShDa7t4QKeQ2aJxE3Aq3jOWZvmKAacK4jTag3CJ8CEwMR/tuE+9BGQTBEHiwyNKQkPtJtVWPNzGVKqtn5YPivkILGsOVmPa/C2oaTR1dFM6DLnYlQvctsR8BM7tQvc7QSgR8Dof0YSL2wXuYz7EHVy0B1dKzdiu31GxvDqt7RIU/vJJCQBAzTB4e+I5Hdya8EB+T0orjvpa4TRAqbZU14YgFCHLhweU3S7K4kOMUEo8ai0fngNOlSDLR3A5VtPU0U3oMFwCTl0sH/7fr+2pxEtruxCEd0h8eEBe54NhGBdrCM9FPTsBABJ0alGqbXR2PN7M2ErxyLz4IB94cKBAXieeRH8oUm3bcj6CiDXI7eIBpZgPrZuA057ZSfhtxsXITNLjvd+5OihRu6qtl2wX5VVtqchYMInl6yq/3+T3ZFsWemvPoyu2DNpZrh9wlyVHELEKiQ8PKJVXd7e2S0aCDj2yEgGIV7WNUvEhdrv4u6ptlAqyjiamxYeXOh9tSQ0PZHssNjvUKnXQz0sQkQSJDw/oNN5Xtf349iE4Wd+C/p1ThG3O8urROSB482krptqqKOYjmIRiUI0UXAuJicVy6O8/s80Og5bEB0GIIfHhASVTKcNIt13WN8tlmy6GXAy+DnrkdgkusXxdva7t0oZUW1+pqG9BTrJB0ge4BsCS4CYIORRw6gF5J8IoeFzkwgMQVfOMgXUdlFe1dYUCToMLWT6cyK1xbYn58IWvN5ajePYKzPphj9vzBfqcBBEtkPjwQFulQ7QPtL760DWS9W7I7RJMYjmWhr8feUulS8BpkCwfryzZBwD4bO1Rj/uRMCQIV0h8eMA1dMG3iHU+HTdqxYe3Oh+OtzWi4FwqMhZcYnmA4+9GnbB+kKc6H4ETaXo3affymKdo7QcIoj2Q+PCIckflrdCYVhXd8Q2+ziTF2UJk+QgusWz54NFreXdnaNwu7sSHnGjNeiOI9kDiwwPuFu/VuEm35Yn2FVzF38qkWOeD20MnEh8aUaqtp1WRCcJvWOn9Fiq3i7wIoTuidRJCEO2BxIcf8LGl7gqN8Qhulyg1hbNeVu1kFdwu4mtGM0EikPB3k2D58DDYB9byoZw+K9fWVGKdIFwh8eGBtlo+YirV1le3i6hmSrTWPyE6Fl4MuLpdfK/zIXaperPQ+ex2idJJCEG0BxIfHpDXD+C7JY3ai+Uj2rNdRH+bLO4tHxK3C1k+iCAhv99cXIFit4sXISCeWHiLo3HndnGtO0L3O0HIIfHhAbeWD28Bp4L4iM5OR3xdWi02t/tJA05FnXqUijKiYwlEwKnUPeh5X/fZLtLXZpv7Z4QgYhUSHx6QSwch5iPGLR/iK9PqIeBUPItkGMa52i9lZhABRB7gLLd8iMWAUoC0GPE961qmXYqvAaexUGyQIPyFxIcH2hzzoYnumA95kTF3q/fK3VOaKE9BJjoG/n7Ua/mYD6mlwWtdGhFqkeXDW6Co24BTx29+ssIfx2KzU6YXQTgg8eEBue+Wx5vbhY9viFq3i+y13PXi9MHL17yJ7uvSEei8WOGike+3n8TeCqPLdt4N4lpkzPm3yerNBeI5k0vpfC5HUEj9bTRZUTx7Oe6au8nL+QkiNoi9nssf5Gu7OEJONd5Sbd1UWowW5JM3d3EfPbOTJK+FWh9Rel06Am9WuGhj3eEa/O3LrRjz1h/CNiHVVuM95sOb20VsxPMmPsRuFyXrn07UnuV7q1DdaMZve095PCZBxAq0qq0H3M3PY93tIqdFbvlw/O6fl4L3bj0X+WlxAJxuGLJ8BA5O6MZOQOOhUw1u3+PdIHaWE7j8/SZ2dbRabGBZVnFBSPm+3lw0YvHRarEhQc91p04xpEYDrLDY7NBrdB6PRRCxRsxbPj79sxQXvrICZTXNLu/J/bN+B5xGaX6//Lq4s3wwDDBuYC4GFaQCcJadpzofgcPXoMdoQen7Cm4+jfd4DTvrOeBZ/I43y6X4fBKLCh+DIrJ88Jk4AGCngGuCIPEx64c9OFHXglk/7HZ5z63lI9ZTbWWvWy3ufexiyPIReMQxH7HgzlIUH447UhyDIbZayO82T64XaSl2z/cpI1poUkmAi2NQ9O6ECkHEKDEvPniazFaXbfJB1FlkzNe1XaIzul3+leRuF767l18lbQxVfg0V4vop0RpjJEandmaYyJ8tjYoBPy8wK1gieEweatP443YRB6SLxYewyq7GmforzoxxfV4IIvYg8eHAn9mIt4BTyWw0Ck2s8iygFrN7t4sYWtk28OjczPajFUVXh+N2YhjpgM8jv199tXx4vZ5u6ofwAsaZ+muXPAskPgiCxIeAYplwN/tqvVk+ROuYROUs30u2i7f6KBaK+QgYKtGoFqviQ3y76RQyzeT3o0fxIdnPs0gQ76vodhGl2sqDXiOV15bsw98Xbo9Kiy4RWkh8OFDqaFwDTv1LtQWiM75B/o3czeQYmeOFv25k+QgcdtE9GguxBFpRvJXcfcIwDHQKi8u5ig/f3C7yWCZf93VdZdcmaYM7S2Ek8P7Kw1i4+Tj2KNRZIQh/IPHhQKnjbmuqrTggNSotHzJcLB9u9tNSnY+A40/p8GhAqWaHWAQo1frwFiDt/vheLB9eipeJi4yJva+RbPngaTJF/ncgOhYSHw4UO6Q2LizHMExUB1e6Fhlz8x3dxHzEQmBkqJCkhsaA+LB7cF8wEBX2srnGYPB4Cjj1x5Ikdbu4Wlr4tlhsrOS40RDzEQv3GhFcSHw4UHS7uCuv7kNJa2etj+hzMbgEnLrEfHi+buR2CRysZLCM/EHNG0qWHmEbI7U2CJ+RHcPXgFNvFgp3lg956i8X8+HcN1LdLrF2rxHBxW/xsXr1alx99dXIy8sDwzBYvHix5H2WZfHMM88gNzcXcXFxGDVqFA4ePBio9gYNJSXvkmorFBnzXtI6mmf5Lqm27rJdZK+pyFjgiTXLh1KQpyTgVMnt0uaAU99TbZUC1sWZN2wUWD78ygQiCC/4LT6ampowaNAgvPfee4rvv/baa3j77bfxwQcfoKSkBAkJCRg9ejRaW1vb3dhgohjz4WaCrvbidgHEhcai7yF18aG7rCKqjJDtQpaPwCEeEKLwXpPDenCLMGBEA777Ad7jrL2Nlg/xMyCssssHv9qiI+ZD7DqKhXuNCC5+r+0yZswYjBkzRvE9lmXx5ptv4qmnnsK1114LAJg7dy6ys7OxePFi3HLLLe1rbYhx53bxVl4dcK7oGpXiQ15e3Sx3u3C/5etnON0u0XdNOgppDET0X1clt4jzfnO6XaTCRB7z4f46tTV7yKQQ8+F0u9ii4v8ksQpF6HcgwoeAxnyUlpaisrISo0aNEralpKRg2LBhWLduXSBPFRLcu118iPnQxI7lw32qrRQdlVcPOOIr2axQpTfakFYVde/qCIjbxa9UW4VsF3HMh2h7NLhdTFHYrxGhJaCr2lZWVgIAsrOzJduzs7OF9+SYTCaYTCbhtdEYPvnj7oZIf9wu5igMOJXjsraLm/34LCEqMhY4/AmQjAaUgjx5QeI220V2DE/XSSIo/CkyprCv1O0iivmI1IBTSYxLZH4HInzo8GyX2bNnIyUlRfgpKCjo6CYJuK7twg2eWh/EhzDQRuMMwevaLhzy8uqU7RJ4xANCc4QOav4gjZ2QZbsg1JYP5X2d5dWjq8KpJOA0Gvs1IqQEVHzk5OQAAKqqqiTbq6qqhPfkzJw5E/X19cJPeXl5IJsUFHxJtdVFtdtFFvPhY6otFRkLPJIUzggd1PzBU7onw0hLmgufcVnbxZPlw7f9AFm8jYciYxYbGxX/J8p2IQJJQMVHUVERcnJysHz5cmGb0WhESUkJiouLFT+j1+uRnJws+Qklnl0o0k7L5ph2eatwCoizXaJvlu9aZMy/heXIXxw4oqF+hD+4K+wFSLNd2mL5cAmk9mb5cLOvS3l1WYXTSP0/SdwuJD6IduJ3zEdjYyMOHTokvC4tLcW2bduQnp6OwsJCTJ8+HS+++CJ69uyJoqIiPP3008jLy8P48eMD2e6Aodeo3Jqr3a0JofWytgsQ3cvHu9T58HEmp1T6mmgfbBTEEviDt0JXeh9iPty5U/xZA0a+v0lB7Igzb6RWksi8/8nyQQQSv8XHpk2bcMkllwivZ8yYAQCYPHkyPvvsMzz66KNoamrC3Xffjbq6OgwfPhxLliyBwWAIXKsDiFh8sCwrSQ91yepw7Ed1PqS4LzImvU4GxxLjNGsKHJJslwg15/uDNMBWurYLw7iL+fDN7eJPJVT5Jzxnu0THwnJ2L8KPIPzBb/ExcuRIj8spMwyD559/Hs8//3y7GhYquIh0CwDORaLTiMSH3Azr6Ix8qXCqi2bx4bguKoYLAHTJdnFze/CzUqoREDgkg3GEDmr+4K3CKZ9h4kk4uHOn+LMGDLe/a1u49vDl1Z3ZLlERcCr6OxaCm4ng0uHZLh0N75cFFNYoke3Lx3wkGbRej+ssrx59MR88cQ5Lhuuqts6ZqBi9D9UnCf+IvWwXTxVOpSXN3eHu/rOz8v38yHZR2FfsZpTEfESq+IgC6w0RPgS0zkckIl6h1mSxAXFOYeFuBj92QC4WbT2BoUXpbo8rFBmLQhcDf1nidBo0mW2+x3yQ2yXgREMWhT9I01ulFU7BMIoC15eA078v3I6aJrPX/SRtcVP3Ql7h1M5K1zOK2IFbdB1jQegSwSXmxYen6Hl3NgudRoXP7xzq8bh8LZBozIfnO9d4ndPyIY6X8ep2IfERMCSVM2NgQJDU4eBXtRVtVQpqdk21ld5/djuLhZuPu5zLv1Vt3We7yI8VqW4XsdUpFqrpEsEl5t0u8DBz9BTb4g1dFFs++IvGu13srLLIkq/twvvAI7XzDUfE92izJfoHBE+xE5zbxdW65i013O7mOfdu+XB/TADQqdWi90WWjwi9/8Xft8kUmd+BCB9iXnzYgxQIFs2zfP6SGXSiztXsvrPnieZr0lHEmh9eydog3qZ0j3kXH8rn8mtVW4WF5TRqRoh7EruBIlV8s2T5IAJIzIsPidnaxfLR9uM64xsis6PxBH9ZdGpGSDtWqvAozwnizdC0LkTgiD23i6iuidzywUjTW52f4TA47r8mk3TgdLd6tV8xH5L7X5T6q3bN8IoKy0cM3GtEcCHxIQmi8q1T8oVonuULS5iDEVwv4oHP3XUTUg+j8Jp0FJIiYxE6qPmDkqVHiDcF48bywe2RqOdC3OTBku4mGTY763kpADeWDx5xxdVWieXDDrs7c0sYI7YSywUcQfhLzIsP8QPVGEA/ZkzUtGCchcOUBj73qbZRfE1CTKzVXrArTBYkbhfe4qhQ7jzBIT7kA6e7mA/AczVSudWUFxSKbiBZPxCRz4As2yUSBRQRPsS8+BB3FC7m2Pa4XUQFhqIN8RLmvCm7VSHVUI7gdolCV1RHIY+BiPYBQRp3oOB2EerriJ47x0cSdMqWD0+XzJOLUB6QzgtwUeav0A/IxXkkWqnkl6mJ4j6IdhDz4kNMQMVHFA+0gtuFcWa8iDtTsRlcjEHjOisl2od81h6Jg5o/KFt6RKm2Hp67BD13/1ntrMfy6wBXvZc7jm+WD8B1MBaLc3nfEon/J/lloowXoj3EvPhgJW6XIMR8ROFAKxYXcTrf02edA0P0XZMOQ3aLRuKg5g/yjAvxawbKzx3/HMfrNJLP8ihZPjy5E919rtnkXCOKhz+nPEAzEoOD5UKXLB9Ee4h58WEPstslGgdacedqEGp3uJq5XWM+nK6oaHcPhAr5VYzEQc0fxM+kneWeL7ElTnFVW8f7WrUzAFQsBpQsH7xo8CSq5Z/jB2Ox24UX5/Jg9khMt3Wx9FDQKdEOYl58iK0b8oDT9gyPsbCOCcM4a30oDXouqbYa5+0WjbEwHYG7uINoRf5MNpttsgBP9wGnAIMEXgyIBk6lSQbvovEk5lwHY/m+jFAFWN63RKT4kF0ouaWYIPyBxIcHywffu4jXf/GVaHYxSGM+uO8pjflwl2qrXG6aaDtKg3E0Izf9iy0KjGhtl1arTRgsxferkhtEKdtFKZbJBXkMhEL2DX+cZlnfEol1MijmgwgkJD5Ef7srPhQnquTpK0ozsGiDASP4xpXEhNztolGrhKJk0SjKOgJ+4OQDG6O98qR8AGw22yRil39WWdZ17RcGzvWIvMV8xHmw6AltkakPecyH2O3iEnAagf8nV/ERed+BCB9IfHgKOHW8xc9e/CGa3S5CZy7KdvEl1RaI7kDcjsC5yJ/3GIVowJvbRRxUyg+OEssHX2jM5D7mw10Wl0tb3Fg+hOPAKXbklo5ItFDJxRa5XYj2QOJD7HZxqXDKEd8ey0cUzvDF18xzVoCruyqaRVlHIL9HI3FQ8wuPbhdArXJW3W1WqICaIIgBUcyH7BRi0eDR8uGS7SINOAVEbp6odLuQ+CDaDokP0d9yHyY/I7plaCEA4ILuGT4fV69QfCtacM4kxW4XpQA/V6JZlHUIsgJa0Z7topTeKr/f+GBRQWCI3CDxCoXG5DEfKtF97dHyITuzXFCInw+rrOHyGJBIgLJdiECi8b5LdCPueBpalS0fRZ0SsP2ZK5Bo8P1y+RSwFqGIOyFP31Me8wFEd/G1jkCoYaGP3vtNjNxF0iz6vnxRO05gmF0mE5z4cI3BkAsaf90ueo0KJqvdeUyJG0jZahqJFiq5SAvkchRE7EGWD0/ZLg4YACnxWiFY0hecxbeir6aFEFAHIE7nsPB4qZvAQzEfgcUZ8+HdTRANuNY1sUpiOgDXoFLxZ5RSaF1iPkTF83xJtZUvWOd083gSH5FnNSC3CxFISHzIVgW1iYSC2L3gL+JOR2m5+UhGXERJcLsoLGGudNXI7RJY+NmokjshGpHr+CaTzcX94VxAjs8+4bYzYBRTbV20MuNjtgvv8nKzYJ3YgiInMv9PVOGUCBwkPmSvlQLR/JcezsqfQKR2NN7h1q7wUGRMQbQZyO0SUPh7NMGPMveRjKeiavzd5mL5cKoPZ5ExSaqtPObDV7cp9zkXy4dCeXU5kdgnuAo/Eh9E2yHx4emBEgWq+YtKxQgDbdSZwhUCTlt8TrUly0cgEdwu+tiwfMhpMlldZhAJMuuGxA0is4oACjEfYPyK+eDFR6Ms24Vz3yh3sZE4cFORMSKQkPiQr89gUrB8tMX0AeesJ9qCAMVFm+IUsl14lN0uFPMRDOJl6aXRgkVWht+1wqnI8sHHfOilVUXF7lMly4e8D2i12vyK+eDjSORxHJzbRWr5iORAdKrzQQQSEh+y140m1xm8fGl4X4nz4JKIZJTKR0uKjHn4rJCCTG6XdiMeNPm4gxZL9AwIX6w/hrOeXYq1h6qFbfLZd4vZJrE0AJ4tH3GKqbbSY7Ksr9ku3AfdxZgArgGn7uJDIgFvRdUIwh9IfMiyBaSWD6evWEyzpRkbKzfCZvc8gMZFaeEnacCp69ouEL0vh58JRts16QjEg0Gigjsh0nl68S6YrXbcO2+LsE0pRktuuUgQqphKYz4YNzEfStlZvlg+eNGSZODvad7tIo75kIoP576R93+SW50iUUAR4UPMiw/+gZL7bQGx5UPKU38+hTuX3olvD37r8dhC+mMUzUYB8aDnZm0XD0EfCTKTONF2xIMBX4MmGgcEY6tF+NsXt4tSFVPAfcyH0t3qk+UD/PlcM2j49hi0cstH5E5I5I81uV2I9hDz4oN/npIUOm93qbbLji0DAMzdM9fjsZ2ZINEV3yBZ28XDDFHJ8qGU6ki0DfFYIFg+ovC6igc9Ib1VWKre6iIelAQG4D7mQ3FVW59SbeVuF9dVbV3cLjqplSQSEVYOtthhtUVX30aEjpgXH3zPlWjQAlAOOBXTam0V/k7RpXg8ND8gNIhmbtGEONXW1/LqCQruLaJtSNwuhsgf1PwhSfS8yrWDXGAoLTwnFml2hfHTn8BQcaqt3c6K3JKMS6qtc5ITeSKRlbmZgMj8HkR4EPPig5/1JAluF9fKh+IJfJ2pTvjbZDN5PHanRB0AoKbJHICWhg/iipJ8J2222YUCbZ4CdROieIYeasSxBYkRHMjoDqWCwvwzqeRm4i2UcsuHODtLqRKsJ8uHp7op8iJjgGvdEYNWJbEAOgODbRFX+Zi/Tjq1CjqH9aPBFJ0TKyL4xLz4kJdIVuq8xZ2H2eYUEpXNlS772lnnNKpTIjc7O93gWaREGpI6BiKftktHLRs87KwdWi3XWVHMR/uJ9oDTlDityzZ+vE4UTRbkQ7hbywfjTMNVClQVI18ZVwle1MTpVIJQajJL644wDIOcZIOzbW6ESiQgtuiE2/22/kgN/vJxCY6cbuzophA+QuKDt3wYXANOecQzeLG1o95UD6vduf9bW97CJV9fgt01u3HTDzdhWd3TAKxRJz7Eox7v/wWcnam8HgD3ERZTl07Fa/smQJO0g4LVAkyiaEZti7AZtTuUFnKUm/4llg/Hb7lrRSyW+ZgLlnW6Cj3GfFhsbkUKv1nFOI/bbHINgC1Iixe2xWvVwvZICzoVZw05xV94WD5u+XA91hyqxl1zN3V0UwgfCbj4eO6558AwjOSnT58+gT5NwBAsHx4DTp37m+1SF4rYDfPxzo9R21qLW368BXtr96LSdACa5N1RJz7EqbYqFSMKQJMF+In+NtlM2FTFdQyapD0R1/GGI+JBUzyjjpa4jwRRvARfbIwXtoke3BfyjColNyHgzIZR0mr8fizrvhqvJJZELw6AlR6wIN0pPtQqRigIF2kuMvFzn6Dgpg4HDp9u6ugmED4SFMvHWWedhYqKCuFnzZo1wThNQBBmUkIsgmudD/EgKna7AEBNS43H46v0FTjdGGXiQybK4mX1TJQmik0WZ6fAqJuoQFEAEF9ng1YFrZr7h0SLVUmcKdLQKhUKiSKxxd9LzvtRbvlwPscqFeO8Xx0Dp5LlQxwo6u568seVWD7MNpeYp9wUp9sFjDNY1hhhgejOGDjGGSPXGh33GhF6giI+NBoNcnJyhJ9OnToF4zTtRmxO5TuEhlZXywfcxHwAQE2rF/GhaYg+y4eoEwLEsyB5eWnnhWu2Nju3a+sl5mmibYiHTBXDIJkf1FqiY0AQ3z/1LY6B2nHvGbRqaByBFvwzy+8tL3fuVixbXLNheNQqZ1quuwFWfFxxLImz/dzv1Hhn7IqKYZCWwAWin2mONPHB/VYxzmscadYbInwIivg4ePAg8vLy0K1bN0yaNAllZWXBOE27EXc6inU+HL/dxXwAQG1rLQBpoKkYRtOIRpM1akzhEhyXRR6sq9SZN1uc4kOlqaNOKwDIYxGS4yJzRu0Oq8gfYnSID36LigFyHBaFstpmyed4MWyxsTCLXCb8cyxYRoRy6MoxHYke4sDEbRHHkjS2utYdSY4Tiw8gzSFG6pojKwtOEnDKT9bC5DnmrX5E5BBw8TFs2DB89tlnWLJkCebMmYPS0lJcdNFFaGhoUNzfZDLBaDRKfkKFpEiTQv69OMCKx2KTduy1LZz4ELsVxKi13PeuboisjsYTcoOQu/UqxN2BxPKhNqPJ0uQx24DwjvjqMQyQ7LiH+YE60hHHcvCWD7vwTDLokZUIwJlNJqTaiuI6mkVZLa5uQvcxH4CyNVSCyPIhFn7yFH1x1g4DBmnxDstHhKXgiys+J4aZ5YO3+hGRQ8DFx5gxY3DjjTdi4MCBGD16NH7++WfU1dXh66+/Vtx/9uzZSElJEX4KCgoC3SS3SMpTK5VXd/yWB06K4S0fDWZlcaXScKlf0RT3Ia/86iymJl1SXIzY8gEArLrBbSAf4Rti7caAiW7Lh+M7ib9z98xExc9p1CohCLpJqfy6y0JwbiwfXooEimNJeIEhcXk5zpcis3zwbphIc7vYRepDqb90h9Vmx5qD1UGNRUpSyIwiwpugp9qmpqaiV69eOHTokOL7M2fORH19vfBTXl4e7CYJSN0ujoqJYveIQnl1ebaLN/HBqhoA2KMq7kPeVbu6XVwtRmLLB8CJsmgJjOwoxIOmikHUxXwoWT6cbhcGGY4ifjxKxbyUKqC6s3wUpsfj/G7pmD6qJwDP6feANOYjWRREKn8+xDEfDCOyfESa20WcWuyH+Ph4TSn+8kkJ7vxsY9DaJnZtRVrxtlgl6HKxsbERhw8fxm233ab4vl6vh16vD3YzFBGnxHmM+fAQcOpNfIBhwaiboszyITUrC8Fn8oW1RDYjuVuK0TRwQafKk1fCBySWD4ZBclx0uV2sorrnvKASD/hJMlO72EIZr1OjtskhPmR7uGZnOYqFadVYcHexsLdX8SE6Ln/t61ssLtkuErdLBFs+xJaeRD+yXb7dfBwAsKG01q/z2e0sdpyoR5+cJJcF+uSILR8NrVakxJMbJtwJuOXjkUcewapVq3D06FGsXbsW1113HdRqNSZOnBjoU7UbpQqRFhsLk1XaKSml2sZp4gBw4uOY8Rh2Vu90ex4mCjNeAFcztqdZkNztwmgaKN22nUhiPuCc/dVHifgQT2AFy4fomUz2YGpXTH1l5O9JLR/yhRDl7kTX9jktfE63i/PaMwpulxaLDemObJdICzgVx7j4U84/tY1C4PN1RzH+vT/xwJdbve6rVjmHsrqWCLuuMUrALR/Hjx/HxIkTUVNTg8zMTAwfPhzr169HZmZmoE/VbuTZLlo1A4uNxekGE/LT4hVjF/iYj5yEHJTWl6KquQq3/nQrjGb3gbLRJj7EgWeAs0aK3Dfuye3CaBqiMwMohIjdLnLTfzQgsXy0ytwuKsbVzy+64eJFAZHyej3O92R1QGTqI1HvOeBU/Bw4r73rvuLCZg2t1oh1u9gV3C6+ZLukxOm87qPE3HXHAADL9lR53Vf8LNQ1W9Alo02nJEJIwMXHggULAn3IgNBksmLH8Xq0Wm24pHcWAKnbRa1iUJAejyOnm3CsppkTHx4qnOYm5KK0vhSnmk9JzpMVl4VTLdJtjMYYVeKDh++sc1I4K9DxMy0AvKfaApz4CLfqiJGGNNtFFHAaopiPZrPVZdXWQCJebVbJ8uHJ7SK2WrizfPCzduegKj2/0+3iLuCUPy4jWDfEVidG9D6PscXidLs0RZZIlCxkaPDd7dJWy4c/nxMvKRBpoi5WiZm1XcpqmzHxo/V4+OvtwjZ5tkDXjAQAQGm1PG1WFHDqcLvkJOQonqdnWk/h767JXQFwwZWRGvPBsizu+WIzHvpqm9Dxy2eS3TO563ZYtqiTUqptuiEdAKBSN1J1xHYiF3lCqm0ILB+rDpxGv2eW4v2VyoHkgUAa88Gn2jo2MJ4zHFId1oX6Fosoa80Rg+EY1Godg5RdIUAacB7ffaqtyAWk6HZxrT1hjGDLhzjLzR8rW6rI7eSPtZO/Tr5A4iPyiBnxkZHgfOD5G9UuM1sXOtZgKHcULXKaY53H4cVHij4FBrWobLKDbqndhL+7JHfhPq9pQHWEWj5qmsxYsrsSi7aeEM0+pft0c6Q8Hj/TApPVpriwHB9wWphUCIC7JqcaWoPY8uiHF4P8jD2UqbaPf7sDAPDakv1BO4dNZPkwyu49FcO4Wj5Ezyk/4NW1WJwiwfF+VhL33ArWSNExxXgLqhQHpIsDTj3R0GoRBtVms02IL4sExKUHlGJc3CEOFq1p9F0YiC0f3moCid8+WUf9SiQQM+KDL2nMss5AL3mRJn4Nhipjq7AvoFznQ6/WC7N4MU2WJswYPAOT+k7C+bnnc593xHxEelGt6kbZdXNcmE6JOmhUDFgWqBUXTmKAqqYqjFgwAosPLQYAFCY7xUdlPXUSbWV7eR3GvcOtmcTPsEOZaqu03H0gaTHbYBNZPmqa+HvPaW1IddOGn4/8jAYVZ+Gsaza71OvJSuKy604ZuWdZXLhMTJKXKp5idw5/PcRBpEo1NxtarUgyaATBWBdBGS/8dVKpnGKrwWT1mtpqE/V7NX4UVksXWT7kmXSeznH8TLOHPYlwIWbEh1atEszS/AApd7tkJ/PiwyR5X9wpWexcZ6FX65ER5xrVlGHIwB3978DjQx9Hp3huTRtG0wCzza4YjBbuiDsWfqYoTyVkROtV1DaZJdf1p9KfcMZ0RnhdkMQVkWM0jThZR51EW5k2f4uzsqdjm1LcQbBoqx/fF9YeqsZZzy6RpKLKn1l+ZdUk0QJzDBiUG8vx2B+PYfmZVwDGJBnc+ec4K9khPhyWN3cxH97iGpxCyOmGEI/DYi3DW1HOKUiFShWhtT5Ezz1/r7GsB7eUA3EfUtvkuwVYp3EOTzVe3NZitwsfe0aENzEjPgAgI5HrdITZuayjcIoP6YxcyfKhVWkllo/OiZ0xsc9E3N7vdmFbZhyX4aPROqqcRqDrRVxlko9bUXJH8bOU2iazxMd+ptUpPACR+GDsOGH0vCgf4Z5mhcqdKSK3iy3IhZZS25jB4AvP/7jHpeR5s9kmLZUOPtjZ6fpkGGDb6W3Ca3VcOepEdTd4eLfLmWYLzFa70/Iha4cQtOou4FRkUonXORe6U+Lnv12Ehy/vhafG9QPgFG+1EVRiXfzc6zVqGLTc8OHNzSe+F6v9cLtIP+e57xRblU/UkfiIBGJKfKSLZueANOZDxTDIdsyInG4X9zEfcrdLcV4xnhj2BFINqcK2TnEOy4eaK0AWieJD3AGc8uCOkl9bgLtuR+uPSo6Xok9BoiYZAFDdUh34BscI/PUGnANxeoIOaof7y1tn3V7SEpyWj1ZLYOMWMpOUiw7WNDqFLT/Oi8UHABw8c1D4Wx1Xjvpms0sMUmqcFmrHAc40myVxJGKSvQScip8DcbYRDwMG1S3VeGz1Y6i3H8YDl/UUgl15y0ckuV3kzz1v7fFmaRO7RPwRW/6IFvE5Thsjr5+NRWJSfDj9x04YOC0fTWYbGlpdo+QBp/jQqXUS8ZFhcHXB8OKDVZkAxhSRGS82BcsHj8TyIXG7OD/TaJFmwMRr4pHmuFZ1Zv8qHhJOJOLD8X9QqxhkJkoFdLBIEKXYBlpU58oEBS80aprMovVFGJd9GUjvN5XutMTywV8nzu3BDZw1jWZR4K5UfIiDKpXiGsSptoCyK+rlkpfxc+nPuPXnWyXbUyPQ7eIsxib9vt6+g/jaeXOfiJHEingTH6Lg5AaTFS1eYkSIjiemxEeGbHYuL9Ik9iFXGU2KdT54t4tcfCgFnyZoE4RKqJFaaEwyo5C1XyzK+MFQvFInA9eF+BJ1iciK59xRzbY6yZLnhO9kiMSH2ILHW++CHcwrvi9OBtjMLbd88JOCmkaTy+w7J1kqVFqtzu+t0lWjrll5EpGRwJ2jpskkSd8VwwsEO6vsWpBnG3VxZMsJMMD2U87UfvGzkCbU+ogc8SG3BPP1fbz9/8X3SqUfVgl/RIs8mD8S+9pYI6bEh6vbxfker+azRRkvSimjguVDpUNuYq7z2HGu4gNwWj9UmsaIfCBsigGnrtclTWRVEr/bYuU6ppH5I3Fz75vRM7UnshM48cFoGiJq5hdOiJcQt9jE4oO7fyuDbPkQ3xcn6wMrPhiZCuCzU6RuF2mBO4AbFPn7DQBU+lOobzGjwjE4urXUQSoieHQalRD34WkdFr69RZ2kCxUxjLQwV2l9qfP8ifz5I8jt4vjNX6b8NO7an/AS4Cm+Vyr9uFekosXz/SyPcTrdSJl04U5Mig+XtD1RpyOO+1CscMrHfOz8Fj1bnQ9Smj7NuRPLAkdWAZW7nHEfEWr5sNqUxAf3WnxdxHVUeBiGEWZ7UwdMxVPnPwWGYZApCLIGv/L+CSd2BQEIAF0yuNn3kdPyQnmBRRyI7G3wac+xASDTESBa3eRqjZS6XRi02JxtYdStYNRNWLztpON9J/yKuNWNZknZcDl8bItSrIK8LUWd4l32ES8rcKTuiPB3pwQ++D1y+gSn5YP7wp1THZWNvVk+xELVjxoc4s95CyK1yZ6HUxT3EfbElPjIEGYb0uJC4i5HPHNUjPlwlFfX7l6Mgm/uEban6lOBHV8DX/0F+O5uYO41wEeXopOKOx6jMYZlzMeBqgY8/8Met4Fg4kFOCMR1vBb31YLlo9EsCaYxWZ11UdByBji0HJ0cLipG04CaCOp8wwn5AM3TI4ubfS/aeiKodWVsIlF6xKUicDuPbZe64vjUWHF8Bn/r5aY6xYeNZdFikQ5SKt1p4W8lsVzbZHIb8wE4s7iU3CPySr+8SHLuwEosMUfqneKD74v8qXvR0TgDc7nfvOXDW2qrOB6jytjq85L3Nj8ELt+2To6YJ0997ZkmM6w2cvd2NMFbmCEMSU9wdmKAa8AY4BQfp0QxH2LMDp+ynmWhtjTh9V4P4XhSJ/SGFlh8L2AXRcbbTOhU55h1aRrDssrppI9LcLrBhMOnG/H5nUNd3hcPcmeaLWg0WUXXRexDV7J8QJiJGhg18MkVQPUBZJx9Lfc+WT7ajDvx0TM7CQCXgfDHwWqM6BWcBR3F5z9Q1RC0YwNAtmNQr20yQ6fm5ksqxwjYI9Pp6jh0qhGtkM6sVfrTsLUUAZA+5+mC5cHstrw64BTVSmZ/caotAGQmSdOPLawFdtY5yEnFB3d+f1JPOxr5ZMxXt4t4AmO1s6huMgnpzp4Q64MTdS1gWVaxZD23L3eOnBQ9qhtNbi0flfWtKH5lOc4pSMV3913otQ1E8Igpy4dQ2bBBWtlQ7OvlA9jEAXsSt4tjgTSd47OXNxhxR/87gD3fS4WHg05nuJUZGU1DWFo+eFfKqgOnFd+X+1LLa5sV3VVpCnU+AKflw3BiK1B9AACQdXAFAEClqY+omV84IbcO8Jydnyr8fehUo+I+gT7/wapGn2ezvh1bJj5ERcHkcVgatQq3F3eBRsXgqoG5QsBp77TeAGSWD9HnxG4XpWKCPAMd13Plftfnw1kfhPtcZqI8+FU6KItjPjIES2H49QnukIutzqmcm6nS2OrRkiD/f/oaDC0WLc1mG8pq3RclFMRHsqx0voyV+0+BZYEtZXUBvWcJ/4kp8cH7h2ubzGi12FwqdQKimI+GVkBhkDXZuAeHFx8oW8/93v8L9/uyZ4Bb5gMz9gFgkNnIFdJSaYyoaTQFvfhToJG3V9wB8JeluqUarOY0GIbrzKuF2BC74KbSH98kfC7P5AgA1NahmtZ3aRPiIFMxKhWDOy/kZvr//HV/0FwvYuuEyWp3PC+BPzYAdHbMsCvrW0Xpns73Z11zFrY+cznOKUwT3Bx9M/oCANR6US0Zx2cqmyrBqjkxwVk+uO1KNcIudliOdp6oc3lP7n7sJLN8yMXHUeNRWB0TFL4vOt1oCni2kDcsNnub1v+RT9aykvTQqhnY7KzHgFB5PEaFj+JD3vfsPFHvdl/+PhcKRbq5H7NFMULlVIa9Q4kp8ZESpxWq8lWJYjrEUyI+er6yvlVRnJht3EOr6+RYvfbkVqB8I1Bewr0eeDPQZxyQnAtk9kaOletsVNo62NngF3/yFz5oDFDOYlG0fIgGAJZlcceSO3D70pvQLZczv/NrYVjszu9qOLVH+DvHagXDAozKiopGKjTWFjyJWF5AN5ttbi1agT7/sZrAdeQ2mbDKc9yjFW6eSUa0yBxv+eibzokPrUF6f1nsFvzl57/grX33gdHUo6bR5LbC6YvrX8Tf1l4NdfxhVDeaXa+5LGYsXif1Yrc6XI7JumTEaeJgtVtxvOE4AM7tMrQoHSwLLNtT5eWKBJa75m7CwOd+9bsSqNztolIxwv9mS1md28/JLQwVPp5Xfr09WfJ4gcMvDuouDkXcxx2oCp5lkPBOTIkPhmGQmyLuyFzdLnmpzlRbs8OUyDBAeUM5rl50NRocA6o+fxiQmAPYLcAnowCwQNEIICVfdLBzke9YtVKlOwOADbvSv7zfFlD2Pyu7XZyUNZThqPEozHYzNOmrJftKxEfFTu6Pc2+HFkA6y610ebLpZPu+QIxicdybfXOT8cFfzpW8J/7/lHswVbcHuXWiLIDiQ3zsv4/uLVgJms02YcburpI5b/nol8GVMberawBwYpgBg02Vm1DVXAWTvQXa5G041aAccFpvqsdX+7+C0VwPXdp62Oysi4tEKWZs7IAcl7YkaBPQNbkrAKnrZWhXLvB6X6XR8wUJMLwLaX7JMcX3f9lZgb0Vrm1SqvjMu7L/9uVWt5Vu+T4kzrG6ra99IP85Xkx7CmzlvT5dMhIA8JMkV4EuthgGOlaJ8I+YEh+ANKZDaRaVmaiHXqOCnXWWVWYAfL77cxw1HhX206UUAgNvdB4471zgqjelJ+t8LnKsVu4iMxYwmoaApyW2F7WoFz982nUmYJXFFpTVNjuXKAeDHad3CO814qBkXyEzSKWBqrUeUOuAQRMBAJ2t3HuVjRUB+BaxB98x33NxN1zZn6s3w7Isyo3luGaQs/7M6SAFNPLn5xf/OlYbuIwXPp7kqXF9Me2SHojXaYRqoxX1rjU7eOysHa0Ot2h+Uj7iNfEAY4dKVyt85sCZA8L+6oQjaDbbhFobYhFR0+Jcd0iTcARKEwelwfiqgXnC37zbJU4Th6IUzhUmDjrtlcMFB++r7JhBUCkde9eJetw7bwvGvPWH28+Jv684YNxdejdvWeLTwMtrfRQfwuc4QeFptVr+f5GfFgcVw7kCleI+rCQ+woaYEx/8LEpiwhU9TAzDSFwR/Pv7a/dLtqVn9ARGPAoU3w9c/RZw1wogo7v0ZJ3PhRZANm9B0Z4JuxUXxQ+jkviQ15M4eKpR4usWLxxntFWC0Tj9smaH5cPAOMzRWX2BvHMARo3OZm6QqDFVBjUlNFrhrQNatfMR/mz3Zxi7aCyWnViIv4/mAi6DJXZ58dHdkW1yNAiWD/FCbcJz66gTIS9EBkirm8Zr4oUBnw86ZQA0mJ0Djib+GAC7EMcktqZI1h1SN4HR1mLh5uOS88niLwFI15rh3S5xmjh0S+kGQCo+ejrSooNdk8UdSucVl+VvkMWF2BUsREO6OusbHatR/h78vdKVt0r4GGthFz7nXbTwQsWgVQmuIKUAVfFkitwuHUvMiQ++c6isb3HJ0+fpnBYn28KgptU5Exrb2ARVahfAkAyMfgkYPEV5KpZ1lmOg5WYHKm0tToTZMvLih1GpM+LFSa/sRKhVDI6faRFmgAyAJov0M+p4Z+fKu10M/DkKhgHaOCCzD3IdsTBWVW1ELa4VLvDZBbzlimVZvL75dQDAPzf9EwXp3H2+vyo4Jn1+QOmWyQ0ogXS78MdWi4QV/9zy2VFKjxtv9QAAg8aArildAXDptvxnxOIDqlao9KcE15RkRt8qXXFZHVeOjaXStYjEkxeTzYRXNryC01ZnOXW+PXGaOHRL5cRHaX0pzrSewVNrnsLisg8AsKhvsaCuAyr9Hql2HXzjdGrhb3mMhdIc4amr+gl/uxOg/PyGt3z4OgGTWz48ZdXw9wzDMChI486jJD7EyzkcPt1I9T46kJgTH/wM6qQocl5eXCg/zdXy0WjmHsRpZ+rwVHUtkFrg/WRaA5DVF/lC0Glt2LldxP51pYAufraTEqdF31zOTLy9vA4A96DLF45Txzv9yGa7oyaKI90W3S7hfuedjc58LEwYWoMiAZvMOiAXgelp3OC556QRjSblVVnbAy9a++VyKxTvqzSiPkAi0pPlg0cpLZa3fOhVWqiWPoWuekclXcHyoXC/xh0VZuLifkC+4rLaUI6y2mZJ8CQrsn0sOrgI8/bOwyN/PID3b+uNuXcOhcUuEh8iy8e3B7/F/w7/D/P3fYFOGZUAAms58hWLjXWJ0xAPzgerlMWH+NonG7SYPooLvj/qptgcf80KHeKjvsXiU7aNM+bDAJ1aBZuddZspw7dNzTBC0KmSpUTc35mtdhwLUkwU4Z2YEx/5afyNKQpIcjxLh84cwhN/PIGEBNlqqywrzJjGNzQhSZsIGFJ9O2HuIHTmxYeuJuwCTsUBWAcVfKD8w6piGPTM4sTHYZGFhO/M+boKmrhy0bG52ZzBZuGuV/dLuTdyB6HI4ggc1J8i32sbEAZoh3XgjOmM5P3Sxh3ITTHAzgL7FIIH24tg+eiUgN7ZSbDYWKw5FJjMJcHyIREfsgkBuKUOJv8yGX/99a+w2q1CgKfBYgLWv4ei3T8CkNb6MJq5a5EVl8WdI/6okKmjJD5S9amO/Y5zcQSioFOx5WN9xXphu0m3EyN6ZQrtiVPrUKjPgJpRo8nShE1VzrTzhHQuC8ydyyLQyAPI5QLDU0CmkpsJcLpTSt18B16oJhm0whIXx32I+7AJrkVGsEa7m6jYRP0UL3IU3S4yS4dSn0eEhpgTH7yP+kh1k0uK3QvrX8APR37Aj6efgjhnwGw3wcpyAiLZbuesHm4q7bmQezZ6mPmBtgrHz7SEVYyD+GE8Wd/qUkZamGGrGXR3mNh5xBah83PPBwCo9BUAw31fIeaDZbn0Y61j9pp3Dro5rgmjPYOHv9kkZG8QvsG7w3jrQF1rneT9DRUb0MtR7XR/EDpYq0ggnNslFUDgsjaEY4uesaFF0oUbGQb4pfQXbDm1BSUVJfj16K+C5SPOUVW068ldAHi3C4sqY6twv16UfxF3jrijooM6/+QDTi/Ov5jbz3ASgA23fVIiPL/iucvJRmfW1urjXNaXID72/QLtO4NREJ8NAPjzxJ/CvhYdF0v26Z9H8d/1x4LuBpA/Z/J7Q2z5OCCzhMrrfCwpXYLn1j6HzBTuM+4tH9xvNcOgwCEiVuzznl4sERQOa0apm3PwLhqVCihId04w5cjr41DcR8cRc+Kjc1ocdBoVzFY7ftjOZVqoVAzMNjO2nNoCAGiy1XODqINmK3eDqsEgjmWBFB9cLjy5g9Cbj/nQV6HZbEZVGC16JJ8JyVPsxB1A90zpqp2A09zfI60HMgwZXHaBgeuI+ZgPvZ0Fuo10fihnANKhQqrNBoZhodKdDmo1zmiEn03y4kNu+dhUtQk9s7lOWD67DQRiUSqInHZkbWwtO4Odx+sdx7YLx+Y5r2u6MAAB3CC6r3af8HrJ0SXCIm4GR9u6WK1gADDqFjDqJpRWNwkWzAvyLoAKKqh0dUKQtMTy0cpZPs7NPhdJuiSAsUClr8SBqkaXtWwYhhEsKgCw9uRamG1mp/iwmoDmavRqdZ21N9jLwKgbsK28Dk8t3oUPVh3257L5jTxFWm4VE4uT3SfqpRMlkdvFYrPgyTVP4tuD32Le4dcAcJWj61tc3Sm8MFCrIGRmyYN3leDFjkbFoFc21/e4s5KyrFMM8wJHKbDVRXx1UKYREWPiY1X5KpRUrEO3TtwM/q3lXGooA6C2VepqMaTuEv7mxUcio+EmR+lFvp80pz86W+3cQKuyQh1Xjq83laPkSI33z4YAi6Oj51OQp3y2UeLXFscWdM+SLRku8qEnaZMwIHMAAEAdVwbAGXBnYFkgs4/zg9o4MFn90E3kelGqK0C4Rzz4A0CdqQ4AMCx3GJK0SWi0NCIpmZtdBqOD5S0vapUKvR3io63us1aLDde9vxZXv7sGxlaL6NhOMaBWMZj312HC6x3H6yXpsGtPrhUyr+JYFhj6fzCwLAodIQ0qw0mUVjcJ92tWfBZ6p3OuQt76wZ/tSN0RwTqRGZeJ/hn9HftxLsU9J7l7VbzIndHkvH+brc3YcmoLmh3CPM7xvyo+5azxAThXwlYnHHJ+j8PB7RcsVungu/14neS12PJR02SWuDnEAfrbT28XUunXVa5BTir3OaV7QDyBuXVoIQCuKJ3SYn2Kn1M5Ba67e0zJSlJpbHWJaeHFF5/RuOuk+6qpRHCJGfGxomwF7l9xPx774zFo9dIbzmpj3YgP7kZt4gdYfhaQ1Q8+o0uAKvssnN/CDcTqhIN4fdkB3PzheuzyUC44VPAdfW9HzQGz1S7pAMX+9y4Z8ZJ0RIZxWj4S7HYM4DtpAzeraWjgZo8GlgXSu0lP3HkwuovcUUt3V7ap5HMsUt1oQrOZ61TVKu4R5t0uGYYMDMkZAgAwMrsBBKeegViU8vUqjtU2o8WsXGjKE+KA2E1Ha12CaXkK0uMFoXNxr0zJM2uymbD86FIADrfLhX8DtPEY0MLdn+q4Mjx1VV/B8pGsTcS52VxxNnX8UQBcwLXRbMQdS+8Qjptxchv6p/UCAPQs4MTNjzs4yx4v0VnY0GDhjjsifwQAYM3xNWhpOsW1h1EDOQNR3Cy1mFzb41rueyY46+PsklsbAox85r/zRL1EcJhl7y/eekL4WxxwWtXsdJtY7VZ0yubcRzd+sA7/+lValsAuskqkxGtR5Jj87fDS/9lE7je+f1p7uMbFusKyrCR5ID1Bh7R4LVjW9d7nv//ZhakAOBGkZK0hgk/MiI/hnYejX0Y/1JnqcDr+Q0DldH00mKxCR1aQVACdSgeL6hRUeu4B4y0fSRbHZ/wRHwBQNAIXOMSHJtFZ5ChYpa/9gZ8J3DjEWZn1wz+OCB2g2Lev16iFjgOQ1k1I+vJWDNjyFQAgOa0cA/OTkesQeXq1AdDLXDb5Q9DHIT7UccewdHcVhr+yAl9tLAv8l4wiDlY1YOhLvwmLIwoxHw7LR6o+FRfmcat1HjRuhorhZrDltc0BXcSMd/uoVQw6JerRKVEHlm1bfIl4drr2UI3onnPtnr7+v2J8fudQXH9uvpAO2zONy7b4+divAIA4lY6rNNzzCgxo5b7z8P7NGH92Z8Hykfh+Mc6u5CwOfIbWngojSipKhL4gy86i6y9PY8DmBQAAu467N5furkJNo3PV6xarU1SMKRoDAPjz5J9oaeQyWeITsoBzbxcyvADAoDagOK+YO3/CIfBSxthqDWrRMQtfHE6tQkaCDq0Wu8T6YZZZRv617IDw/xGvqyOu7wMAtvitwt/vrDgkEVBiCwYADMxPAQDsKHeeVwmbSLT0EFldb/pgneT4Yq2mVjFgGAYDHAsCbj/uOtEEuGKSfFbjbrJ+dAgxIz50ah3+efE/kapPRROOIr/nYsn7/MOUn5gvdAqaJM710mR1zJasFiApD8g727+TF12MYof4UBmOCz7mElndgGBxytiK2z4pwcr9p1ze4wPcemcn4bcZI6BWMVh94LQQ2OX0u3K3ynldnYF/DAM0OcRHgt2Oc8s2I47RoMVei5dvSYPNMTuK0ye7NqrrRRjKW4PijgGMBcZWKx77did1Bh74dU8VxG573u3Cx3ykntiKC2o4y9PO6h3onctVBr3otd8x+MXfAmZtk1sn+NVfNx31/55utTgHvDWHqhUtH2XGMny570vYVA24uFcm1CpGEAk39bpJcjyDjpslo9+1GGjiTPv7z+xCk6VJWOI+yWrBOdu/AwCo9RWAyoScZIMQODpQn4kfy44jnmUx4DQXh3Gy+Si6Z3EF8/756wHBDdFo5VwuCdoEXNT5IqgYFQ7VHUJpA+emiUvuDPQbDzBq/LvyFJI18bgnsRfOrTwEnUoHldaIXgXNwqD8/fbgLTnAu110GhXO754BAPhTlKXEWwYu7JEhbLtrLpedI3a78Nd+eOfhAICTpt1g1M7YInFgqE0WQDyIXyn4wGmPVh7eCKNSMYjXaaB3VNPdX9WAEf/4Xei7xAvX8bfMIDcCxyKKlRrQ2bHPcepvOoKYER8AUBCXjTmj5kDDaFCv2oorznH6M/mHKT0uHaO6jAIAaFO2ArALs/tEux04705ArfXvxF0vRA7L4JzWVjAMC0MqV5J889Fal5lGMHh/5WH8cbAaUz7d6PKwC1kTahV6ZCUJ603waZP8+/ysRSw+ABZNjiC/RNYOPQsMb+au6fKy5Wht5iw7eqW05LQu6JKUjyyrFYzKxgkQB7/uDu1CW5FEgqgIFOCa7ZJW+icKlj2PrppkWFkrcnKlAYzvrzyE9tBituGvn28U6lLw98UwRzbKnJWHsfnYGbefV0Js+dhX2SBkTYgLqE39dSpeLnkZM1bOAMuysNltgrXnssLL0CW5i3CMOIOj6mbPK9DbrkKc3Q6j2YjNVZsBABqWhYFlkW2zoTOrAhgWF5x1Bv++bTAqmzhrxZBGIxc7kj8UnWx2dLaxYMGiqIALRF+09bjg+mrmJycsg5QlT2JgSg8AwB6LIwYltSuQmAn0uAwXtLTij4P7MHXbjzB8/wDO03GD/IThZ3DfSO5zc9ceRVMQarMATnGhVTO4sDtXB2XtIaeble+PCtPjca7DNfHHwWpsK6+TpBbz135ApwHom94XdtaGJ26wo4/DPfLVRmfKvdjtAgBjB+RCp1Fh87EzGPv2GrcF6uwy0fL1/xUL75XXtuCTNVwMjThoXiUTw3JhYbE60nc1KuGe/WpjeVhlIMYKsSM+rCZg3g3ov+0bXN39agCALYlbvyBOqxbER9qRP3DFhvlI1iZCpauBJmk37DbuBk6y24EBNykf3xP6JKDH5biqkXvIzup1GJ0SdWgy2/DFeuXFnQKJVpQ1IDfpygs6XdSL65BWH+DEhzjiHJCmPBrNTYLfO+Gix4CMnhjVwF2rn4/8jJZm7hj6eOcsSgzTbSTOc5jFNYkHhDLKK/a5WmgIjvoW6aDEW6TOONbISXXM7MZVc776GmaNZP+fd1a2y/qxdHclftvr/P/w98Wwbtz/uKbJjAlz1vpV8dRklcaJ8Ksi88c+XHdYEAWbqzZj7cm1qDPVwc7awQBI+/cluEHnXM+mnyNGA/pEaHuMwlDHPbb40CIA3HPMjJ8DaONxibEOAJCXvxeDClJR0cRdx9z6CoBRAzfNBRJzcEkj99ykZ3EZNq0Wu7D2U5Mj3iOlqRbY+gUuK98p+T7xaY5lF4Y/BIDhOl0NF+B95XGuzsdPpT/h8r5ZQr9w1rNL8fWm8jbF0HjCLIgPFYb34J71LWVnhLgHXpzo1Cp8e+8FOM9RPn38e38KlgYVwwiW4rTmelyRPRQAsLl6lVDWf/6GMkFAiYNBAa5aLX/uvRVGjHp9FWoVgk9tMtEyqCAVz197lvD+7F/2Ye2haqnbhWFwpP4Ivq94FZrkndhf1YAHFzhdQry7UKticOOQAsTr1CitbsLukxTwHmpiR3wcXAaUrgLWvIFbK7kBf3P1KsyZ3A1Lpl+EWkfkfEZtGeIPLMUtTZxLYEC/rTDXcwFhSdpEIK2L8vG9cfZEXNHUDA3LYv+Zfbj5As568sKPe7BkV3AXVxNXJPxw9RHJe1ZZWuOInpkAgLWHq9FstkqKjAHS6q/rSznzsJplYehyITD8IVza3IIkO4uTTSfxu5mzfMQlZCk3rPc4XNrEDVIZWXvw5V3ng2G4ILhwyQYKN+RBufF6zhJS53AXpGX2A3pdiWuNRjAASpt2IDn1OHpkJWJwF24gefjr7S4Dvq+0yLIH+IGhf57UtfbpWmlmhyfEbhelY2+o3CDZ/uGOD4XJQqrNBk19OW7YtBA5Vis0LIuR3cY4d+53LcY1cpaU38qWAwAS7SzQ9xpgyJ24xvHe72W/w2g2OsWH1QoUXQQk5wLn34srHPfpHydWYeIw58q1gMgt63iWrqk9DbF9KivXsepwlwuA2xYBlz8PPHIA6HctRjU2Qs9yZde3VW/Flf2dx370mx3o+8wSfPZnKQ6dCkwcCG/J1KpVKMyIR8+sRFjtrOCSNYnECcMwmDrcmdm33DEpYBinpTjtz7dx+fJ/AgDWVaxD99xWdOuUgIZWKxZu4qwfvGFCrWJgsVvw3cHvMKi78/uYbXac+8IyDH91hWRtGXmxudrWWtx8Xh7m3zUM4wZyYvPWj0skLh4Vw2DmHzOx8vgyxHWeB3XcEfxv20ncP58ro2ARWXoT9Bpc1JMTQb/tJWtrqIkd8dH3KuDqtwFGhT47F2MwkwAba8PBlmXokpGA2jOceTrNZgO0CZhYcRQ6MDhk3INVVRsBAEmpXdt+/l5XIjU+Exc73BL12pXCW/f8d4vwoHqjptHk9zLp/AwNABZtPYGtZdyshWVZ58PomEGflZeMrhnxaDbb8PPOSon/nWVZfHPwGxT1Wg5G3YQrunIzykQ7C6bzucDAm2BI64ZrGjjf7wkV99n4pM7KDet+KUYwiYi329Fgq0aVeT9uOJcLfH3zt4PKn4lhtpfXCabmIV3S8M8bByEriYtTKDfXAQAyu1wMjH4ZuaxK+D9kdf8WH0/pg/sv5cz6+6sacN17a9s0q5avLBqv0+DQmUO4Z/ndSM3/BWC4e+27LSfcLrEuh99vQOcUyaKOGjVXf+fLfV8CAG7ufTO0Ki22nNqCZUe54NJ0mw1IKUQiy+LLE5X4ptaEgm6XOw/eazRGmewoMjtFW6ImjguAvuAB9LGp0MNshtluxq9Hf0VlA2cxyrHZgAse4D4w5A4MYvXIt1jQaGkEkyJd8bWlhRMsKXY7MOlbpLMMRjQ5r1O/3POcO3e/BLjwQcCQAlz5KhK1CbjK8X96c/ObePzKPrh5iLSO0HM/7MGo11djhywtti2I3S4AcHk/rvDZr3u4wZd3S/CrFV/ZPxf/N4LLVPvjIGfJZMDgjEPsptts6GJqwUUtZthZO97f8R6mXNgVAPDp2qOw2VmRiADe2vwWnl37LD4rfRiv3BonETfHz7Tg+vfXYl7JMbSYbZLPLTm6BJd+fSmu+348CjJbMM3hogKAsW87/x+ttmbsqdkjvDbkfQMwZvy4owIf/3FEsN7wk61Rfbnv/8tOWuAy1MSO+ACAwZOBm74A1HpMqjwKAFh4YCGMZiPOGLlI9vQuI4ApP6AT1LjWyJnijtgc2S6derf93Bo9cOGDmGTkFP/SYz/i3b/0Et7++zc7sGRXpdfD3Pzhelz02u/YUubZr36qoRWVjnUQ5Gt73PbJBuw8Xi/xlYqzJm4YzAmARxZuxz+WcmlzKhWDP0/+iefXPY9q9TIUDfgcQzI4gZDIaABdAhcLc+lTmGQ0QiN6kHvlOeszSFBrYBh4M0Y5Ouq5e+Zi+uW9oGKAdUdqhHoKBMdzP+wW/h5/Tmfh//Tcn0/DDBYDWk0oOusmbnXl8+/B4zVnkG9jUdVcgZlrp2NI13hkJ+sBcJkdfZ9ZgpIjNT5X1fz0z1K89zsn0rtkxGPmmD7omhGPF9a/gJKKEtiSViGn51cAY0V9iwVPLtrlU4fOWz7idGpMHOoceNUqFf656Z84ajwKNRjc+Od/cC3DxRTM2fEBACCdZYBp64Fzb0cndRy6n/8goBLZHQwp0J73V8yscQbCdk5wuGiScsCce5tg/fh458eoNXMuqZycc4HulwnHUA2ZgvvPcO/9VjEfA7o6M4fMtdxgl6xLAXqOAi64Hy9U1+Cahka8mDQIapU0TkcgORe4+DHcW1cPA8ti2+ltWFb+I169YSD+O3WYS1XXa979E10f/wkjXvtdEiTqieNnmnHjB2vx+dqjXFtFlg0AgqVl2R4ug8dss0neB4Cbz5MVVWSAMw5LcVr3K4Bul+CeM9z1/aX0F9TpfkJKnBbHaprR/YmfhTLnapUKyx3WJytrxZy9s3DXJel44+ZBwqFP1LXgyUW70PeZJaLVhhn8Z+d/YGNtKG8ox13L7kJ2mgUvXdff5fseM3KWXYPagJyEHKh0tdB14s754k97heJmOsf3G9rdgASDCfurGrB42wmX4xHBI7bEB8BZQG6ai0taTOhmtqDOVIfZ61/GYUenk9Z9FNB5MHDFC7i7zuhckRVARt6Q9p178B0YYshGX5MZrTYTVtd+hFuHOlNc7/nvZvzPwwPQarEJlUDvnrvZ7UJeVpsd495eg4v/8TtW7KtCo8NU//iYPuiTk4RGkxVPLd4pKTWsUTN4Z+s7GPHVCCyrfwz6eKkQami1SMpCnzaV4ZGjXGptgtZZeRL9xqMg+2zc4hBZDAuclTXQ/TW54AHc1mQGw7JYdmwZ/qz6QZiNTZu/RRBQBLC1rE74O94ReHqm9QxKKjnL3FNmPZhMh0C++HEkduqD9ysqkGIHdtXswsw1j+PnBy/EpGGFwnFu/nA97p23xSeRMHedMz7p5vMK8H8Xd0eztRnbTztXcm1S78Sgc78HYMW3W46jaObP+GDVYUnhOjm85cOgVePGIQWCmV2tYrGkdAkA4NnT1ejdUIOpR3dCJ2prbmI+J3yveQd48iRwwf2uJxg+A8UwYEJDIxLsdtxz9n3O9y56GBNaGSTbbDjRyD178XY7ki95RrqEwoUPYQwbh/NaWtFibUFz+gdQGThrpameE2TJqY7revHjSOlxJV7SFuLakS94vqjD7kF2ek/cd6YOAPCPja9hQ8UGDOqix9f/V4ztz1yBR6+UTnrKapsx6eMSvPLLPq/xO0t3V2Hj0TN49vvd+HbzcYnbBQBM6oMo6PYnrKoK3PbJBuyr4J5b3vJxzHgMGn2tJPulrNqIekeBsbQ+1wI3foqBCfl4rIabEH206wOcO8B5T/C0WBtwvJEb/PMMnVDbWosHf38QF/eNx+GXx6J/Z4WsOAA21owDZ7gSBTqVFicaT+CRVY/gpiF5WPX3kZg4lLtn/u/ibih1iI9BZguePM0JpPjMNdAnSPtVjYrBtlPbcOPP46ApegG6jJWY/cueoAX6tgeWZfH04l146ac9bXaXhiNBEx/vvfceunbtCoPBgGHDhmHDhg3ePxQqel8JzeiXhdnQj6U/oVnFQMWyyO81jttn2D3I6TkG99VxD3ciy2BEj6vbd15dPJhxr+PvtWegZln8UvoLtrKP4/axO5GRxImcBxdsw9x1RxU/Xi2q01DdaMKYt1YrzoAq6ltxusEEk9WOu+duxu/7udiLLunxmDt1KBL1Gmw/Xo+Z3+0QPtNsbcAnOz8BABwxHoShyzvI7L4AKh3n5zVo1djsGOT+ZtIgF86Mn65JzsEMKhVw/Ud4qMmOB2rr8FTBGCTrlDsVAEBSDvoMnYYHHLPKl9a/iLi8r5GWtwZH64/h/NnL8dZvB2N+6Wu7nRUGhK4Z8bjMYS7+48QfsINFL5MZ/Xpd4xww9YnAxPkoSsjDu5WV0LMsVh1fhZc2PIErz6vDv24tFFIXl+2pwj3/3exV6CUZNMLf5xZy8SNbqrbAxtqQb2Px79P10IHBkeYNyOv1LQCuI3/ll3245r01+PNQtaLIaXV0qAaNCtnJBjw+pjvGD06BSl+BM6YziLfbcVVjE3DBA8hPKcKz1bVQsyw0LItbB9zp/eIlZAA3/xfP6ouwrssk9O45zvlech6SRz2H2adrhInGMFUimKLhLsdQXfUGXjtdjXyLBadaKpDc7QOMGb4Tdc3cgJrcyVHFVxcP3LoA+L9V3qsha3TATXNxeyuDAa0mNFgaMfXXqRjx1Qi8veVt6HRW3DeyB56+yrW20AerDmPiR+uxt8LotkCfOIbi4YXbMc0R+6DVqHC0/iju/u1u1Ol/QHy3t3HI8h02HeP6E51ahaVHl+KqRVdh3KJxsGd9CE3SDoAxYZB+H1jHfZbaawwQlwZM/Ap/MTF4oLYOALCpYS4K+81DfAonBjQqBnU27u8CiwUfH9yOZDuwp2YPJv54C3ZWb8eCu4fhy7vOxy8PXiQJki9rPAgba0Mnmx0Ly44hnuWWD7jpx5uwuXYpHhydhT3Pj8bMMX1xqJLLaOrRWIeRVYdxeVMzbKwNhb0XoHeBMxXYznKWrhZrC+ywQp+1BA3JH+HFX5yL/oULR2ua8cX6Y/joj1Jc++6fYbc4aVth2CA4ur766ivcfvvt+OCDDzBs2DC8+eabWLhwIfbv34+sLDfBhw6MRiNSUlJQX1+P5GQPg1Z7YVngl8fww54v8ElKMg7rdPhLfBEeu/F75z6tRrCL7sHS2p3IG/EEBg6YGJhzr3oNv2x4A890SkerI9YigTGg6UxvtDT1ha21M245+1zcPaI7NpbWggWLC7p3QnWjCde9vxYA0ClRh+pGMxgGmDayB649Ow/dMhOhVjFYe6gat35c4nLaL6YORUb6aby69hOsP9gKW0sBbC2FYK0peHtKK54seQ6drDacbTLhtwTOmqGBCt1wIW45exye3/Y4AGBZ2QnYGGBqTjZOaDV4e/gruKT7OOnJzhwDWuuA3EHwis0K9otr8VzjHnyXJCpGxgIq41loqB2JQVn9MfqsXCTqNbiyfw7S43VCWl0scPxMM4a/+jvUKgb7XrgSGhWD+Xvn4ZWNrwIA7qprwN9uXQpkylyDjaeAr27DiprtmJHVCTbRbL5rQj4ytUOwakca7OYMqG3puLxfHnrnJKFHViIu6Z0Fq52FscWCgvR4XDB7OU7Wt+LVCQNw83mFOHDmAJ5aNg17WypxfUMjZlXXYk2cAX/LzoSFYRBnN8Bc3wcNDefA1twNYLXolKjDOYVpKOqUgLEDcnF2QSo+WVOKF37cg2sG5eGBKxMxdelUyVo1Fze34N2efwFGPQe0nAG+uROVR1fB3GcsCm/4wvdFHt3BssBvz6J0w3tYl5iGaybMR2L+UOV9N3wE49LH8GxGmvCM8PzjwpdwZY9r2taGwytQsfB2PJ9iwB69DrVqzrKlYVToGp+HotTuyE8tQn5SASytaXhrSS1OG1mwrBawc5kzxd0ycOfwInROjYOx1YLumYmY9cNu/LiDi0lhGGdBriFd0jBiyFp8tOdzSTO0rRmor5yAl8dejQVl9+FQozQWTQcdihgd9rONSIUaf0ze5nzz2FqwX92Gd/QWfJSaImwenD4Ql3edhF1H5+HH2h0Y3diEf9YYcVjN4m/ZmSjTchOZOJUOPZK7oGdGP3RN6YXvN1lQVcdgdJ8SfHNqLUY2NeOdU9VYHWfA45md0CByDRUl5OGCzsPx1f6vYWWAZ20puKH3jTCunI1bs1NxTKsFAyDZUoiauv545vIrMHvbdLAA/lJvxNfJSTAzDDSWBDRUjUeu9jxcPbAzeuckoWdWEuJ0anTNiJcE74t5Z/lBHKttxlUDczGkazoS9RrF/ZQ4dKoRi7eeQHH3DJzfLUOyrAAArNx/ClM+3Si8TtRrMKZ/DvrkJqNfbjKGFaWHTV/oz/gdFPExbNgwnHfeeXj33XcBAHa7HQUFBXjggQfw+OOPe/xsyMQHwD2J2+YD6+egJSUfhvFzwMSnBfec/Hm3foH65bOwnm3C+2mpOKKT1g5JsKqQZkqAwZwMmNNgsycALANAhZykOFzaPxVzS1ei1tYAvU0DgzUOemsC4pGKpuY4WNk4dEtPQG4ai99Pb4Zd3YKiZAN2W6vRDKkVIdmihlHLzT7vqqvH387U44BWi7fSU7E6XrqUeWerDUuGPAtUbEf9iY040G8Mhpz/kNuH0mfMzbD/9DCWHVyMwzotthl0WBfnPHeiVYUUczwM5iTAnAqGMSBeZ0BaQjwS9QbEG+KQqI+DVqOHTqOHXqOBTqWBTqOBjtGgvsWGdYfOIEGnQ35qHFLidDBoVdBpVLCDhYrh4lrUjApqFcP9rVIBDKBiuE6O/44MAEalcmQAMY6xjwHDsNx74Dp6hgUYhoXJYoeVX0QPDOwsiyOnG9FitiI1ToskvRoaNaBW2/HHwdM4Wd+E9HgN0hI00GlUaDFZse34GTSZbMhP1eOO89Mw5/A32GnmLHd5Fis+7zUFOSMeU762Nivw55tYu/51/DcpHpUaNY5otRIhAnDtTbJqkWCOg9aSBLUlCWB1sLNqGDR6NJpVYO0a/N8FBdh+ZjMWG/cJd9KHiYNQXPwIsOFDrN2/CI9npuGM2hnroGaBeKsaBpsWOpseamscGGsCUnVJqGuxwwY1undKRLVuB3Zbpa6Ep+J74uYJ33BWNZ6WM4Ahtf3CQ0zNYUCfzNXk8MSxdWCXPo5f6g/g9fRUVGk0SGE0WHbrWsRp4jx/1hOn9wOrXgW77ycs1zH4Z3oaTmi9D2JJVjXirVoYLAborAmw2Q2w2wyAXQ/YdbBBi6v6ZeOkpRQrz+wFw9qRq43DXhUn8P5xqho2ALMz0lCvlsanxNntmFtRhZ8TEvBbQhzKtc5+6sqMQfjHVf+VNsZ4Evj1KRw88AMWJiZgYXIirLL/0aPJA3HbVR8DW+ai/s838JLejOXx8TB7GUAf0Bfi7qs/B0o+QN2Gf+MbPbA8IQ57dTrJvaxiWSy6dA66FV4EVO1B9bdT8AJqsEImFgGgh9mMRScqsU+nxcNZnQQhlGxVoVNzOtSWRNjscWDtOhg0BsRp4xCnNUDF6JGZnICUeD3sLItfdlUJJdhUahvyMjXITIgDy6qgVamRGm9AskEHFdTQazQwaLRQqzRgoMYP2ypwtLoVAIM4vRX6uCaAtSMjTgctAxyrboKGZZGXrAdYK47bD8GmbYDWpofKGodETSKyk1PQKTEZFrseVqsaifo4pMUlIjlOD7Bq2OyARq2BQauBRq0GAxXiDQm47NxRHq+5v3So+DCbzYiPj8c333yD8ePHC9snT56Muro6/O9//5PsbzKZYDI53QlGoxEFBQWhER8djdUMHF4O24FfsaVsBVbY6rBDr8c+nc7rg9ge+plMOMtkxk69Hgd0WtgdD66GZfHVuY+jV69rgKpdYI+sxh+lv2C+6SQO6jTQQ4Unzp2B4edMDVrbUFcGHFkFHN+A3SdL8LmtGr/HxwkWIsKJhmVxr7EZd17wNDRD7vD+gYZKYO8PQMU2GCu3Y23jMfyh12CPXofjGk2brvFlTc2YlHsRzrv2P05xUFcG88aPsLF0GZabqrA63oAqje8zQYPdji8qq7ErMQW6LsMxduwH0Gh0frctqLAsULoKzTu/xlprPboNfxTdsn2w8vmCuQk4thb2QytQeXwtDjdX4qitCSc0GhzXanBco8ZxjQZmhhHcH20ly87ip/7TYWBZVB9cijfrt2OFQSdYFe5hMjCtzySgpQ72iu1Yf3oLvlW1ojYlF89c9QWKUrspH7iuDNjzPU7s/x5zGw9grcGAZhWDc/Sd8PyNvyCeX27B0grs+gbWw7+j7NROHGw9hYMqOw7qtDih0aBRpUKtWoW+qni8dcOPSE3g3I0wNQKHVwDH/oSxaifW1R3AVpUVNVo9LhlwO8YOf9LZFqsZ2PEVTu76Cr/V7sJ6vQabDHoADF4ruh4jhz8FlK5C486v8fGJ3/F1gl5iVYlW8i0sfvnrLu87+kGHio+TJ0+ic+fOWLt2LYqLnRXpHn30UaxatQolJVJ3wHPPPYdZs2a5HCcmxIec1nqg9ghMp/djb9VW7KgtxSlbLU5ajGiwW2C2s7CyLFQqBnYVMFCTgtEJRTCyFpww1eFYqxFVbCvqWAussMOqYqAGg0HqJAwyZKJVo4cuPgOX9Lga+vhMoLUezXVl2FWzC/tN1ejf/1acU3S5QruMQPUBzqSvTwr5NWkuW4fDZX/giPEYSlurUGkyotluhZW1w2y3wwY7rCwLG1jYGBZWsLAxDKwArAxgdfxtc/zN3/AMALAiawW/zQd8eWh8fbBYMFA59lazgBrcj0poj7NVDMOZ4gfqMvBg70nIGnBz2/8nNivQUAHUHwdbV4bq+qMoN5bheEsVylprcNzcjFbWBqhYmO027lozLOxqNVI08bgz72KcfdZEINdDQHHLGbBVe1BVtQ01DcdR01yNatMZ1JiNOGVpQo3FDJvdBsAOjRpg9EkY0+NaXDb0Qf8rCUczVhPQUsf1Ea31gIn73dB0CkcbylHTUo2TrbWoNNej0dKMFtaCRtaGRrsNNrBgVQwS1FqM1echS5+OKtYEoz4Bl53/d+RlOLPuYGmB9egfOHxqB9j0bujd5zpXq6bVzMWq+IqpAag5xBVtyxng2VrFspxVq6na8V3ruIDigmHSLCalzzXXcrFOGr37/WxWoPYwbPXlYHMGQpMoCwOwtMJUuhKbS5dhx5n9qLU0osnWimbWihabDSbYYWLtMDP8qsbS0u4Mw0BjZ5FkZ2FjWdgZwAYu+skGrg/ifjOy14CdYaBhgRw7CzUL2MA4+zEwYNQM7AyDvowB/bWpqLObUWMzodpqQovdChNrh4Xh2mZy/LAA7I4fFoBdtC3Hpsa3d+1AIIko8RHTlg+CIAiCiBL8ER++20J9pFOnTlCr1aiqklaMq6qqQk5Ojsv+er0eer0HpUoQBEEQRFQRcMeWTqfD4MGDsXz5cmGb3W7H8uXLJZYQgiAIgiBik4BbPgBgxowZmDx5MoYMGYKhQ4fizTffRFNTE+64w4egOIIgCIIgopqgiI+bb74Zp0+fxjPPPIPKykqcffbZWLJkCbKzs4NxOoIgCIIgIoig1PloDyGt80EQBEEQREDwZ/yO/mRmgiAIgiDCChIfBEEQBEGEFBIfBEEQBEGEFBIfBEEQBEGEFBIfBEEQBEGEFBIfBEEQBEGEFBIfBEEQBEGEFBIfBEEQBEGEFBIfBEEQBEGElKCUV28PfMFVo9HYwS0hCIIgCMJX+HHbl8LpYSc+GhoaAAAFBQUd3BKCIAiCIPyloaEBKSkpHvcJu7Vd7HY7Tp48iaSkJDAME9BjG41GFBQUoLy8nNaNCSJ0nUMDXefQQdc6NNB1Dg3Bus4sy6KhoQF5eXlQqTxHdYSd5UOlUiE/Pz+o50hOTqYbOwTQdQ4NdJ1DB13r0EDXOTQE4zp7s3jwUMApQRAEQRAhhcQHQRAEQRAhJabEh16vx7PPPgu9Xt/RTYlq6DqHBrrOoYOudWig6xwawuE6h13AKUEQBEEQ0U1MWT4IgiAIguh4SHwQBEEQBBFSSHwQBEEQBBFSSHwQBEEQBBFSYkZ8vPfee+jatSsMBgOGDRuGDRs2dHSTIorZs2fjvPPOQ1JSErKysjB+/Hjs379fsk9rayumTZuGjIwMJCYmYsKECaiqqpLsU1ZWhnHjxiE+Ph5ZWVn4+9//DqvVGsqvElG88sorYBgG06dPF7bRdQ4cJ06cwF/+8hdkZGQgLi4OAwYMwKZNm4T3WZbFM888g9zcXMTFxWHUqFE4ePCg5Bi1tbWYNGkSkpOTkZqaiqlTp6KxsTHUXyVssdlsePrpp1FUVIS4uDh0794dL7zwgmT9D7rO/rN69WpcffXVyMvLA8MwWLx4seT9QF3THTt24KKLLoLBYEBBQQFee+21wHwBNgZYsGABq9Pp2P/85z/s7t272bvuuotNTU1lq6qqOrppEcPo0aPZTz/9lN21axe7bds2duzYsWxhYSHb2Ngo7HPPPfewBQUF7PLly9lNmzax559/PnvBBRcI71utVrZ///7sqFGj2K1bt7I///wz26lTJ3bmzJkd8ZXCng0bNrBdu3ZlBw4cyD744IPCdrrOgaG2tpbt0qULO2XKFLakpIQ9cuQIu3TpUvbQoUPCPq+88gqbkpLCLl68mN2+fTt7zTXXsEVFRWxLS4uwz5VXXskOGjSIXb9+PfvHH3+wPXr0YCdOnNgRXykseemll9iMjAz2xx9/ZEtLS9mFCxeyiYmJ7FtvvSXsQ9fZf37++Wf2ySefZL/77jsWALto0SLJ+4G4pvX19Wx2djY7adIkdteuXeyXX37JxsXFsf/+97/b3f6YEB9Dhw5lp02bJry22WxsXl4eO3v27A5sVWRz6tQpFgC7atUqlmVZtq6ujtVqtezChQuFffbu3csCYNetW8eyLPewqFQqtrKyUthnzpw5bHJyMmsymUL7BcKchoYGtmfPnuyyZcvYiy++WBAfdJ0Dx2OPPcYOHz7c7ft2u53Nyclh//GPfwjb6urqWL1ez3755Zcsy7Lsnj17WADsxo0bhX1++eUXlmEY9sSJE8FrfAQxbtw49s4775Rsu/7669lJkyaxLEvXORDIxUegrun777/PpqWlSfqNxx57jO3du3e72xz1bhez2YzNmzdj1KhRwjaVSoVRo0Zh3bp1HdiyyKa+vh4AkJ6eDgDYvHkzLBaL5Dr36dMHhYWFwnVet24dBgwYgOzsbGGf0aNHw2g0Yvfu3SFsffgzbdo0jBs3TnI9AbrOgeT777/HkCFDcOONNyIrKwvnnHMOPvroI+H90tJSVFZWSq51SkoKhg0bJrnWqampGDJkiLDPqFGjoFKpUFJSErovE8ZccMEFWL58OQ4cOAAA2L59O9asWYMxY8YAoOscDAJ1TdetW4cRI0ZAp9MJ+4wePRr79+/HmTNn2tXGsFtYLtBUV1fDZrNJOmIAyM7Oxr59+zqoVZGN3W7H9OnTceGFF6J///4AgMrKSuh0OqSmpkr2zc7ORmVlpbCP0v+Bf4/gWLBgAbZs2YKNGze6vEfXOXAcOXIEc+bMwYwZM/DEE09g48aN+Nvf/gadTofJkycL10rpWoqvdVZWluR9jUaD9PR0utYOHn/8cRiNRvTp0wdqtRo2mw0vvfQSJk2aBAB0nYNAoK5pZWUlioqKXI7Bv5eWltbmNka9+CACz7Rp07Br1y6sWbOmo5sSdZSXl+PBBx/EsmXLYDAYOro5UY3dbseQIUPw8ssvAwDOOecc7Nq1Cx988AEmT57cwa2LHr7++mvMmzcP8+fPx1lnnYVt27Zh+vTpyMvLo+scw0S926VTp05Qq9Uu2QBVVVXIycnpoFZFLvfffz9+/PFH/P7778jPzxe25+TkwGw2o66uTrK/+Drn5OQo/h/49wjOrXLq1Cmce+650Gg00Gg0WLVqFd5++21oNBpkZ2fTdQ4Qubm56Nevn2Rb3759UVZWBsB5rTz1HTk5OTh16pTkfavVitraWrrWDv7+97/j8ccfxy233IIBAwbgtttuw0MPPYTZs2cDoOscDAJ1TYPZl0S9+NDpdBg8eDCWL18ubLPb7Vi+fDmKi4s7sGWRBcuyuP/++7Fo0SKsWLHCxRQ3ePBgaLVayXXev38/ysrKhOtcXFyMnTt3Sm74ZcuWITk52WUQiFUuu+wy7Ny5E9u2bRN+hgwZgkmTJgl/03UODBdeeKFLuviBAwfQpUsXAEBRURFycnIk19poNKKkpERyrevq6rB582ZhnxUrVsBut2PYsGEh+BbhT3NzM1Qq6VCjVqtht9sB0HUOBoG6psXFxVi9ejUsFouwz7Jly9C7d+92uVwAxE6qrV6vZz/77DN2z5497N13382mpqZKsgEIz9x7771sSkoKu3LlSraiokL4aW5uFva555572MLCQnbFihXspk2b2OLiYra4uFh4n08BveKKK9ht27axS5YsYTMzMykF1AvibBeWpescKDZs2MBqNBr2pZdeYg8ePMjOmzePjY+PZ//73/8K+7zyyitsamoq+7///Y/dsWMHe+211yqmK55zzjlsSUkJu2bNGrZnz54xnQIqZ/LkyWznzp2FVNvvvvuO7dSpE/voo48K+9B19p+GhgZ269at7NatW1kA7Ouvv85u3bqVPXbsGMuygbmmdXV1bHZ2Nnvbbbexu3btYhcsWMDGx8dTqq0/vPPOO2xhYSGr0+nYoUOHsuvXr+/oJkUUABR/Pv30U2GflpYW9r777mPT0tLY+Ph49rrrrmMrKiokxzl69Cg7ZswYNi4uju3UqRP78MMPsxaLJcTfJrKQiw+6zoHjhx9+YPv378/q9Xq2T58+7Icffih53263s08//TSbnZ3N6vV69rLLLmP3798v2aempoadOHEim5iYyCYnJ7N33HEH29DQEMqvEdYYjUb2wQcfZAsLC1mDwcB269aNffLJJyXpm3Sd/ef3339X7JMnT57Msmzgrun27dvZ4cOHs3q9nu3cuTP7yiuvBKT9DMuKyswRBEEQBEEEmaiP+SAIgiAIIrwg8UEQBEEQREgh8UEQBEEQREgh8UEQBEEQREgh8UEQBEEQREgh8UEQBEEQREgh8UEQBEEQREgh8UEQBEEQREgh8UEQRMgYOXIkpk+f3tHNIAiigyHxQRAEQRBESKHy6gRBhIQpU6bg888/l2wrLS1F165dO6ZBBEF0GCQ+CIIICfX19RgzZgz69++P559/HgCQmZkJtVrdwS0jCCLUaDq6AQRBxAYpKSnQ6XSIj49HTk5ORzeHIIgOhGI+CIIgCIIIKSQ+CIIgCIIIKSQ+CIIIGTqdDjabraObQRBEB0PigyCIkNG1a1eUlJTg6NGjqK6uht1u7+gmEQTRAZD4IAgiZDzyyCNQq9Xo168fMjMzUVZW1tFNIgiiA6BUW4IgCIIgQgpZPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCkkPgiCIAiCCCn/DwtJAAztPzzsAAAAAElFTkSuQmCC", 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" ] @@ -510,7 +669,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 63, "id": "0f761edf-3096-4364-b675-b5f9547af94d", "metadata": {}, "outputs": [ @@ -519,28 +678,28 @@ "text/html": [ "\n", "\n", - "
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\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, - "execution_count": 79, + "execution_count": 63, "metadata": {}, "output_type": "execute_result" } @@ -607,7 +766,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 64, "id": "dbca68f2-67fb-4b04-a339-fe2c965066b9", "metadata": {}, "outputs": [ @@ -617,7 +776,7 @@ "" ] }, - "execution_count": 40, + "execution_count": 64, "metadata": {}, "output_type": "execute_result" }, @@ -647,6 +806,62 @@ "metadata": {}, "outputs": [], "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b20d251b-7971-408d-afbc-13cabd13c435", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2a25d361-3f38-4e43-8d6b-547fd79618ff", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "768301e7-efa8-4b7a-8ab3-ad01664a6d5c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07d3eb2a-b0cb-411f-ab72-8753529aea7f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f17b2e51-c3ae-4f34-a9e5-e8fdb0345c4d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2f82703d-a6b0-47f3-9b9d-1acfac75c446", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60901413-8127-4b1b-b518-67eb691bb1e3", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/src/rl4fisheries/agents/cautionary_rule.py b/src/rl4fisheries/agents/cautionary_rule.py index 2d51c2c..384da56 100644 --- a/src/rl4fisheries/agents/cautionary_rule.py +++ b/src/rl4fisheries/agents/cautionary_rule.py @@ -9,31 +9,49 @@ from rl4fisheries.agents.common import isVecObs class CautionaryRule: - def __init__(self, env, x1=0, x2=1, y2=1, obs_bounds=1, **kwargs): - self.ui = unitInterface(bounds=obs_bounds) + def __init__(self, env, x1=0, x2=1, y2=1, observed_var='biomass', **kwargs): + self.policy_type = f"CautionaryRule_{observed_var}" + self.env = env + self.observed_var = observed_var + self.x1 = x1 self.x2 = x2 self.y2 = y2 - self.policy_type = "CautionaryRule_piecewise_linear" - self.env = env + + self.x1_pm1 = self.convert_to_pm1(x1) + self.x2_pm1 = self.convert_to_pm1(x2) + self.y_pm1 = self.convert_to_pm1(y) assert x1 <= x2, "CautionaryRule error: x1 <= x2" + def convert_to_pm1(self, X): + if self.observed_var == 'biomass': + return self.env.bound * (X+1)/2 + elif self.observed_var == 'mean_wt': + MAX_WT = self.env.parameters["max_wt"] + MIN_WT = self.env.parameters["min_wt"] + return MIN_WT + ((X+1) / 2) * (MAX_WT - MIN_WT) + def predict(self, observation, **kwargs): if isVecObs(observation, self.env): observation = observation[0] - pop = self.ui.to_natural_units(observation) - raw_prediction = np.clip( self.predict_raw(pop), 0, 1) - return np.float32([2 * raw_prediction - 1]), {} + raw_prediction = np.clip(self.predict_raw(observation), -1, 1) + return np.float32([raw_prediction]), {} - def predict_raw(self, pop): - population = pop[0] - if population < self.x1: - return 0 - elif self.x1 <= population < self.x2: - return self.y2 * (population - self.x1) / (self.x2 - self.x1) + def predict_raw(self, observation): + if observation < self.x1_pm1: + return -1 + elif self.x1_pm1 <= observation < self.x2_pm1: + return ( + -1 + + ( + (self.y2_pm1 + 1) + * (observation - self.x1_pm1) + / (self.x2_pm1 - self.x1_pm1) + ) # -1 + (y2 - - 1) * fraction + ), else: - return self.y2 + return self.y2_pm1 def predict_effort(self, state): return (self.predict(state) + 1) / 2 From b2c8629c5a9f6c5e8597a8273054550912c1b47e Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 24 Apr 2024 22:28:22 +0000 Subject: [PATCH 19/64] added to pop-dyn tests, CR and Esc agents now admit biomass or mean_wt observation --- notebooks/popdyn_tests.ipynb | 549 ++++++++++++++------- src/rl4fisheries/agents/cautionary_rule.py | 32 +- src/rl4fisheries/agents/const_esc.py | 33 +- 3 files changed, 411 insertions(+), 203 deletions(-) diff --git a/notebooks/popdyn_tests.ipynb b/notebooks/popdyn_tests.ipynb index eaf9eec..49c2399 100644 --- a/notebooks/popdyn_tests.ipynb +++ b/notebooks/popdyn_tests.ipynb @@ -10,7 +10,64 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 1, + "id": "648c8aa8-6386-4a6a-b1ea-1ffe407623bd", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Obtaining file:///home/rstudio/boettiger-lab/rl4fisheries\n", + " Installing build dependencies ... \u001b[?25ldone\n", + "\u001b[?25h Checking if build backend supports build_editable ... \u001b[?25ldone\n", + "\u001b[?25h Getting requirements to build editable ... \u001b[?25ldone\n", + "\u001b[?25h Installing backend dependencies ... \u001b[?25ldone\n", + "\u001b[?25h Preparing editable metadata (pyproject.toml) ... \u001b[?25ldone\n", + "\u001b[?25hRequirement already satisfied: gymnasium in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (0.28.1)\n", + "Requirement already satisfied: numpy in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (1.26.4)\n", + "Requirement already satisfied: matplotlib in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (3.8.4)\n", + "Collecting typing (from rl4fisheries==1.0.0)\n", + " Using cached typing-3.7.4.3-py3-none-any.whl\n", + "Requirement already satisfied: polars in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (0.20.21)\n", + "Requirement already satisfied: tqdm in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (4.66.2)\n", + "Requirement already satisfied: jax-jumpy>=1.0.0 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (1.0.0)\n", + "Requirement already satisfied: cloudpickle>=1.2.0 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (3.0.0)\n", + "Requirement already satisfied: typing-extensions>=4.3.0 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (4.11.0)\n", + "Requirement already satisfied: farama-notifications>=0.0.1 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (0.0.4)\n", + "Requirement already satisfied: contourpy>=1.0.1 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (1.2.1)\n", + "Requirement already satisfied: cycler>=0.10 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (0.12.1)\n", + "Requirement already satisfied: fonttools>=4.22.0 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (4.51.0)\n", + "Requirement already satisfied: kiwisolver>=1.3.1 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (1.4.5)\n", + "Requirement already satisfied: packaging>=20.0 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (23.2)\n", + "Requirement already satisfied: pillow>=8 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (10.3.0)\n", + "Requirement already satisfied: pyparsing>=2.3.1 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (3.1.2)\n", + "Requirement already satisfied: python-dateutil>=2.7 in /opt/venv/lib/python3.10/site-packages (from matplotlib->rl4fisheries==1.0.0) (2.9.0.post0)\n", + "Requirement already satisfied: six>=1.5 in /opt/venv/lib/python3.10/site-packages (from python-dateutil>=2.7->matplotlib->rl4fisheries==1.0.0) (1.16.0)\n", + "Building wheels for collected packages: rl4fisheries\n", + " Building editable for rl4fisheries (pyproject.toml) ... \u001b[?25ldone\n", + "\u001b[?25h Created wheel for rl4fisheries: filename=rl4fisheries-1.0.0-0.editable-py3-none-any.whl size=2322 sha256=2f9f00a1bb6053567050d7fa7953167bf454e0d7177265e63ad9c43f43b15507\n", + " Stored in directory: /tmp/pip-ephem-wheel-cache-gn1d9bpy/wheels/55/1e/4a/9e3b1ec27a9439b41651c9753798340778b03ddfad8f7fc0af\n", + "Successfully built rl4fisheries\n", + "Installing collected packages: typing, rl4fisheries\n", + "Successfully installed rl4fisheries-1.0.0 typing-3.7.4.3\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%pip install -e .." + ] + }, + { + "cell_type": "code", + "execution_count": 1, "id": "3638cfd4-177b-4b24-b6a4-8d61d74faf80", "metadata": {}, "outputs": [], @@ -25,7 +82,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 2, "id": "c1131bf0-840c-4a40-b111-f3d74351795a", "metadata": {}, "outputs": [], @@ -37,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 3, "id": "eb58ebf3-882d-4944-9e19-2332f3133a18", "metadata": {}, "outputs": [], @@ -95,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 4, "id": "9ab73841-a5f3-4704-ab7c-0a71ca683a90", "metadata": {}, "outputs": [], @@ -123,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 5, "id": "a634dbf5-00af-44d8-b2d9-5ede8969e3e7", "metadata": {}, "outputs": [], @@ -134,214 +191,306 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 6, "id": "6f4dc7c8-47d3-414f-bc97-d6c2290d455c", "metadata": {}, + "outputs": [], + "source": [ + "# trivial_ep.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", + "metadata": {}, "outputs": [ { "data": { - 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tsurv_b_obsbare_surv_b_obsmean_wt_obsactrewtotal_popnewbornschildrenadultsnon_random_newbssbsurv_vul_bharv_vul_bstate
000.738230-0.9704710.622407-1.00.02.9535540.0243051.0903881.8631660.8066190.9100980.6348781.022081[0.024305389667785986, 0.41009481735214626, 0....
110.634877-0.9746050.622407-1.00.02.5709190.0308630.7077531.8631660.8065440.9098420.6347791.022080[0.03086255120635639, 0.020902635114295947, 0....
220.634779-0.9746090.629318-1.00.02.2109910.0000000.3478241.8631660.8059630.9078460.6331851.022039[0.0, 0.026541794037466496, 0.0179762661982945...
330.633185-0.9746730.648082-1.00.01.9014520.0000000.0382861.8631660.8040620.9013550.6269711.021398[0.0, 0.0, 0.022825942872221186, 0.01545958893...
440.626971-0.9749210.676797-1.00.01.6352490.0000000.0196301.6156180.7997390.8868260.6131871.014983[0.0, 0.0, 0.0, 0.019630310870110218, 0.013295...
\n", - "
" - ], "text/plain": [ - " t surv_b_obs bare_surv_b_obs mean_wt_obs act rew total_pop newborns \\\n", - "0 0 0.738230 -0.970471 0.622407 -1.0 0.0 2.953554 0.024305 \n", - "1 1 0.634877 -0.974605 0.622407 -1.0 0.0 2.570919 0.030863 \n", - "2 2 0.634779 -0.974609 0.629318 -1.0 0.0 2.210991 0.000000 \n", - "3 3 0.633185 -0.974673 0.648082 -1.0 0.0 1.901452 0.000000 \n", - "4 4 0.626971 -0.974921 0.676797 -1.0 0.0 1.635249 0.000000 \n", - "\n", - " children adults non_random_newb ssb surv_vul_b harv_vul_b \\\n", - "0 1.090388 1.863166 0.806619 0.910098 0.634878 1.022081 \n", - "1 0.707753 1.863166 0.806544 0.909842 0.634779 1.022080 \n", - "2 0.347824 1.863166 0.805963 0.907846 0.633185 1.022039 \n", - "3 0.038286 1.863166 0.804062 0.901355 0.626971 1.021398 \n", - "4 0.019630 1.615618 0.799739 0.886826 0.613187 1.014983 \n", - "\n", - " state \n", - "0 [0.024305389667785986, 0.41009481735214626, 0.... \n", - "1 [0.03086255120635639, 0.020902635114295947, 0.... \n", - "2 [0.0, 0.026541794037466496, 0.0179762661982945... \n", - "3 [0.0, 0.0, 0.022825942872221186, 0.01545958893... \n", - "4 [0.0, 0.0, 0.0, 0.019630310870110218, 0.013295... " + "" ] }, - "execution_count": 53, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "trivial_ep.head()" + "trivial_ep.plot(x='t', y = ['surv_vul_b'], title='populations')" ] }, { "cell_type": "code", - "execution_count": 54, - "id": "b5a371a2-d2d4-4a9a-87c7-30121b7d07df", + "execution_count": 8, + "id": "1e7fab6a-0ca1-41ad-83f2-17c6eeee69bd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "trivial_ep.plot(x='t', y = ['total_pop'], title='Total population over time')" + ] + }, + { + "cell_type": "markdown", + "id": "7de3ce71-70a5-4972-aae0-12c8ba14d2c8", + "metadata": {}, + "source": [ + "## Optimal escapement" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "5488a622-d16c-4d82-a4fa-4501107e5580", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "esc = ConstEsc(env=env, escapement = 0.010338225232077163)\n", + "esc_ep = pd.DataFrame(simulate_ep(env, esc, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))\n", + "esc_ep.plot(x='t', y = ['total_pop'], title='total pop. over time under optimal escapement', logy=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "3bc2f53d-94be-4fa8-916f-88f6e9eb57f2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "esc_ep.plot(x='total_pop', y = 'rew', title='reward-population relation', kind='scatter')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "a9204098-6d56-4a58-b77d-9af8cbef4613", "metadata": {}, "outputs": [], "source": [ - "def prepare_for_altair(df):\n", - " # df = add_state_columns(df, env)\n", - " # melted_df = df[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')\n", - " # melted_df['population'] = melted_df['variable']\n", - " # melted_df['biomass'] = melted_df['value']\n", - " # return melted_df[['t', 'population', 'biomass']]\n", - " melted_df = df[['t', 'children', 'adults']].melt(id_vars='t')\n", - " melted_df['population'] = melted_df['variable']\n", - " melted_df['biomass'] = melted_df['value']\n", - " return melted_df[['t', 'population', 'biomass']]\n", - " " + "from stable_baselines3 import PPO\n", + "\n", + "PPO_CONFIG = { \n", + " \"observation_fn_id\": 'observe_2o',\n", + " \"n_observs\": 2,\n", + "}\n", + "\n", + "ppo = PPO.load(\"../saved_agents/PPO-AsmEnv-2o.zip\", env=AsmEnv(config=PPO_CONFIG), device='cpu')" ] }, { "cell_type": "code", - "execution_count": 55, - "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", + "execution_count": 12, + "id": "aa0ef25f-8e6e-48c0-9d91-fbb90969290b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ppo_ep = pd.DataFrame(simulate_ep(env, ppo, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))\n", + "ppo_ep.plot(x='t', y = ['total_pop'], title='total pop. over time under optimal escapement', logy=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "4024227f-1e2f-468d-8151-8f3759e92ce3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ppo_ep.plot(x='t', y = ['rew'], title='harvest over time under RL policy')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "e64e134e-44f4-4546-9b7c-ee3031ba8f69", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "ppo_ep.plot(x='total_pop', y = 'rew', title='reward-population relation', kind='scatter')" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "489d45a2-0708-4626-9210-3e0c9207cf15", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-0.982, -0.970, -0.418\n" + ] + } + ], + "source": [ + "cr_args = {\n", + " 'x1': 50 * 0.009159055923137423,\n", + " 'x2': 50 * 0.015139834077385755,\n", + " 'y2': 0.29119675741251316,\n", + "}\n", + "cr = CautionaryRule(env=env, **cr_args)\n", + "cr_ep = pd.DataFrame(simulate_ep(env, cr, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))\n", + "# cr_ep.plot(x='t', y = ['act'], title='total pop. over time under CR')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "133dd750-22e1-4895-a4c7-87b87199ffc6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" ] }, - "execution_count": 55, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -351,9 +500,33 @@ } ], "source": [ - "trivial_ep.plot(x='t', y = ['total_pop', 'surv_vul_b', 'harv_vul_b'], title='populations')" + "cr_ep.plot(x='t', y = ['rew'], title='total pop. over time under CR')" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "80a64012-c141-44ba-bb91-23121a7e1edf", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "adf71d22-824e-46ed-8425-87079ad47442", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0682d592-12b5-40a7-8874-3c58b233847e", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": 56, @@ -365,6 +538,26 @@ "# %pip install vega_datasets" ] }, + { + "cell_type": "code", + "execution_count": 54, + "id": "b5a371a2-d2d4-4a9a-87c7-30121b7d07df", + "metadata": {}, + "outputs": [], + "source": [ + "def prepare_for_altair(df):\n", + " # df = add_state_columns(df, env)\n", + " # melted_df = df[['t', *[f'age_{i:02d}_b' for i in range(20)]]].melt(id_vars='t')\n", + " # melted_df['population'] = melted_df['variable']\n", + " # melted_df['biomass'] = melted_df['value']\n", + " # return melted_df[['t', 'population', 'biomass']]\n", + " melted_df = df[['t', 'children', 'adults']].melt(id_vars='t')\n", + " melted_df['population'] = melted_df['variable']\n", + " melted_df['biomass'] = melted_df['value']\n", + " return melted_df[['t', 'population', 'biomass']]\n", + " " + ] + }, { "cell_type": "code", "execution_count": 57, diff --git a/src/rl4fisheries/agents/cautionary_rule.py b/src/rl4fisheries/agents/cautionary_rule.py index 384da56..fd82d11 100644 --- a/src/rl4fisheries/agents/cautionary_rule.py +++ b/src/rl4fisheries/agents/cautionary_rule.py @@ -18,38 +18,48 @@ def __init__(self, env, x1=0, x2=1, y2=1, observed_var='biomass', **kwargs): self.x2 = x2 self.y2 = y2 - self.x1_pm1 = self.convert_to_pm1(x1) - self.x2_pm1 = self.convert_to_pm1(x2) - self.y_pm1 = self.convert_to_pm1(y) + self.x1_pm1 = self.convert_to_pm1(x1, var_type = self.observed_var) + self.x2_pm1 = self.convert_to_pm1(x2, var_type = self.observed_var) + self.y2_pm1 = self.convert_to_pm1(y2, var_type = 'action') + + print( + f"{self.x1_pm1:.3f}, {self.x2_pm1:.3f}, {self.y2_pm1:.3f}" + ) assert x1 <= x2, "CautionaryRule error: x1 <= x2" - def convert_to_pm1(self, X): - if self.observed_var == 'biomass': - return self.env.bound * (X+1)/2 - elif self.observed_var == 'mean_wt': + def convert_to_pm1(self, X, var_type): + if var_type == 'biomass': + return 2 * X / self.env.bound - 1 + elif var_type == 'mean_wt': MAX_WT = self.env.parameters["max_wt"] MIN_WT = self.env.parameters["min_wt"] - return MIN_WT + ((X+1) / 2) * (MAX_WT - MIN_WT) + return 2 * (X - MIN_WT) / (MAX_WT - MIN_WT) - 1 + elif var_type == 'action': + return 2 * X - 1 def predict(self, observation, **kwargs): if isVecObs(observation, self.env): observation = observation[0] - raw_prediction = np.clip(self.predict_raw(observation), -1, 1) + if self.observed_var == 'biomass': + raw_prediction = np.clip(self.predict_raw(observation[0]), -1, 1) + if self.observed_var == 'mean_wt': + raw_prediction = np.clip(self.predict_raw(observation[1]), -1, 1) return np.float32([raw_prediction]), {} def predict_raw(self, observation): if observation < self.x1_pm1: return -1 elif self.x1_pm1 <= observation < self.x2_pm1: - return ( + prediction = ( -1 + ( (self.y2_pm1 + 1) * (observation - self.x1_pm1) / (self.x2_pm1 - self.x1_pm1) ) # -1 + (y2 - - 1) * fraction - ), + ) + return prediction else: return self.y2_pm1 diff --git a/src/rl4fisheries/agents/const_esc.py b/src/rl4fisheries/agents/const_esc.py index 103a7ee..182b017 100644 --- a/src/rl4fisheries/agents/const_esc.py +++ b/src/rl4fisheries/agents/const_esc.py @@ -7,31 +7,36 @@ from rl4fisheries.agents.common import isVecObs class ConstEsc: - def __init__(self, env, escapement=0, bounds = 1, **kwargs): - from .unit_interface import unitInterface - self.ui = unitInterface(bounds=bounds) + def __init__(self, env, escapement, observed_var='biomass' **kwargs): self.escapement = escapement self.bounds = bounds self.policy_type = "constant_escapement" self.env = env + self.observed_var = observed_var def predict(self, observation, **kwargs): if isVecObs(observation, self.env): observation = observation[0] - pop = self.ui.to_natural_units(observation) - raw_prediction = self.predict_raw(pop) - return np.float32([2 * raw_prediction - 1]), {} - - def predict_raw(self, pop): - population = pop[0] - if population <= self.escapement or population == 0: + + if self.observed_var == 'biomass': + pop = self.env.bound * (observation[0] + 1) / 2 + predicted_effort = self.predict_effort(pop) + if self.observed_var == 'mean_wt': + MIN_WT = self.env.parameters['min_wt'] + MAX_WT = self.env.parameters['max_wt'] + mwt = ( + MIN_WT + (MAX_WT - MIN_WT) * (observation[1] + 1) / 2 + ) + predicted_effort = self.predict_effort(mwt) + + return np.float32([2 * predicted_effort - 1]), {} + + def predict_effort(self, obs): + if obs <= self.escapement or obs == 0: return 0 else: - return (population - self.escapement) / population - - def predict_effort(self, state): - return (self.predict(state) + 1) / 2 + return (obs - self.escapement) / obs def state_to_pop(self, state): return (state + 1 ) / 2 From e4554aaada112472cb7b28d0013bddc3e130ef20 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 25 Apr 2024 18:01:53 +0000 Subject: [PATCH 20/64] notebooks, deleted legacy debug, attributes, varnames for CR and esc --- hyperpars/ppo-asm.yml | 11 +- notebooks/optimal-fixed-policy.ipynb | 2307 +++++++++++++++++++- notebooks/popdyn_tests.ipynb | 222 +- src/rl4fisheries/agents/cautionary_rule.py | 4 - src/rl4fisheries/agents/const_esc.py | 9 +- 5 files changed, 2504 insertions(+), 49 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index bc0f381..4b2f98d 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,20 +1,19 @@ # algo algo: "PPO" -total_timesteps: 15000000 +total_timesteps: 5000000 algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' use_sde: True - # batch_size: 128 + batch_size: 128 gamma: 0.995 gae_lambda: 0.999 # env env_id: "AsmEnv" config: - observation_fn_id: 'observe_2o' - n_observs: 2 - use_custom_vul: True + observation_fn_id: 'observe_1o' + n_observs: 1 n_envs: 12 # io @@ -22,5 +21,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2o_flat_harv-long" +id: "1o-2" additional_imports: [] \ No newline at end of file diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index e995a5a..2aee89d 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -35,7 +35,19 @@ "execution_count": 1, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'rl4fisheries'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 14\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mstable_baselines3\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mevaluation\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m evaluate_policy\n\u001b[1;32m 12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mstable_baselines3\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmonitor\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Monitor\n\u001b[0;32m---> 14\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrl4fisheries\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AsmEnv, Msy, ConstEsc, CautionaryRule\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrl4fisheries\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01menvs\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01masm_fns\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_r_devs, observe_total\n", + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'rl4fisheries'" + ] + } + ], "source": [ "import numpy as np\n", "import pandas as pd\n", @@ -9516,7 +9528,7 @@ }, { "cell_type": "code", - "execution_count": 106, + "execution_count": 6, "id": "6a61d3fa-97a9-4274-945c-be2742d1e956", "metadata": {}, "outputs": [], @@ -10845,6 +10857,2297 @@ "source": [ "ggplot(vars_df, aes(y='mortality', x='agent', color='agent')) + geom_point() + geom_jitter() + xlim(0,0.1)" ] + }, + { + "cell_type": "markdown", + "id": "193d5f4b-4fcc-452b-986a-e59371e5ecdc", + "metadata": {}, + "source": [ + "# Observing mean weight instead of biomass\n", + "---\n", + "## Setup\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "813faf60-f3ed-44c0-a53b-baad312cf8ba", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import ray\n", + "\n", + "from skopt import gp_minimize, gbrt_minimize \n", + "from skopt import dump\n", + "from skopt.plots import plot_objective, plot_convergence\n", + "from skopt.space import Real\n", + "from skopt.utils import use_named_args\n", + "\n", + "from stable_baselines3.common.evaluation import evaluate_policy\n", + "from stable_baselines3.common.monitor import Monitor\n", + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.envs.asm_fns import get_r_devs, observe_total" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "90511c3c-3223-4d66-a6df-834f220d8445", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG = {\n", + " 'observation_fn_id': 'observe_2o', \n", + " 'n_observs': 2, \n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "1fa605e9-0085-455e-b507-f0c7385324f5", + "metadata": {}, + "outputs": [], + "source": [ + "@ray.remote\n", + "def generate_rew(policy, env_cls, config):\n", + " ep_rew = 0\n", + " env = env_cls(config=config)\n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, info = policy.predict(obs)\n", + " obs, rew, term, trunc, info = env.step(act)\n", + " ep_rew += rew\n", + " return ep_rew\n", + "\n", + "\n", + "def rew_batch(policy, env_cls, config, batch_size):\n", + " tmax = env_cls().Tmax\n", + " parallel = [generate_rew.remote(policy, env_cls, config) for _ in range(batch_size)]\n", + " rews = ray.get(parallel)\n", + " if ray.is_initialized():\n", + " ray.shutdown()\n", + " return rews\n", + "\n", + "def eval_pol(policy, env_cls, config, n_batches=4, batch_size=40, pb=False):\n", + " batch_iter = range(n_batches)\n", + " if pb:\n", + " from tqdm import tqdm\n", + " batch_iter = tqdm(iter)\n", + " #\n", + " rews = []\n", + " for i in batch_iter:\n", + " rews.append(\n", + " rew_batch(policy=policy, env_cls=env_cls, config=config, batch_size=batch_size)\n", + " )\n", + " return np.array(rews).flatten()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "5d636138-8f2e-416a-a974-0fa2f76d9fa7", + "metadata": {}, + "outputs": [], + "source": [ + "log_esc_space = [Real(-6, 2, name='log_escapement')]\n", + "cr_space = [\n", + " Real(-5, 0, name='log_radius'),\n", + " Real(0., np.pi/4.00001, name='theta'),\n", + " Real(0, 1, name='y2'),\n", + "]\n", + "\n", + "\n", + "@use_named_args(log_esc_space)\n", + "def esc_mw_obj(**x):\n", + " eval_env = AsmEnv(config=CONFIG)\n", + " escapement = 10 ** x['log_escapement']\n", + " agent = ConstEsc(\n", + " env=eval_env, \n", + " escapement=escapement, \n", + " observed_var='mean_wt',\n", + " )\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=1, batch_size=200\n", + " )\n", + " return -np.mean(rews)\n", + "\n", + "@use_named_args(cr_space)\n", + "def cr_mwt_obj(**x):\n", + " theta = x[\"theta\"]\n", + " radius = 10 ** x[\"log_radius\"]\n", + " x1 = np.sin(theta) * radius\n", + " x2 = np.cos(theta) * radius\n", + " #\n", + " eval_env = AsmEnv(config=CONFIG)\n", + " eval_env.reset()\n", + " agent = CautionaryRule(\n", + " env=eval_env, \n", + " x1=x1, x2=x2, y2=x[\"y2\"],\n", + " observed_var='mean_wt',\n", + " )\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, \n", + " config=CONFIG, \n", + " n_batches=1, batch_size=200\n", + " )\n", + " return -np.mean(rews) \n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "a1a495d4-9141-491e-8aeb-c9892c4bf83f", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:04,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 7.2468\n", + "Function value obtained: -1.9048\n", + "Current minimum: -1.9048\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:11,288\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 7.2018\n", + "Function value obtained: -1.9737\n", + "Current minimum: -1.9737\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:18,514\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 6.8578\n", + "Function value obtained: -1.9354\n", + "Current minimum: -1.9737\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:25,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 7.0262\n", + "Function value obtained: -2.0507\n", + "Current minimum: -2.0507\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:32,404\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 7.0535\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.0507\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:39,532\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 7.0462\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.0507\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:46,549\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 7.2075\n", + "Function value obtained: -2.0646\n", + "Current minimum: -2.0646\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:43:53,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 7.3153\n", + "Function value obtained: -1.9315\n", + "Current minimum: -2.0646\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:44:01,054\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 7.0475\n", + "Function value obtained: -2.1287\n", + "Current minimum: -2.1287\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:44:08,119\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.8057\n", + "Function value obtained: -1.8554\n", + "Current minimum: -2.1287\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:44:18,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3912\n", + "Function value obtained: -1.9575\n", + "Current minimum: -2.1287\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:44:27,320\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2712\n", + "Function value obtained: -1.9597\n", + "Current minimum: -2.1287\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:44:35,645\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8549\n", + "Function value obtained: -2.0411\n", + "Current minimum: -2.1287\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [0.3715626298528427]\n", + " warnings.warn(\n", + "2024-04-25 17:44:44,423\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4937\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.1287\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:44:52,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4121\n", + "Function value obtained: -1.9700\n", + "Current minimum: -2.1287\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-5.419977199986665]\n", + " warnings.warn(\n", + "2024-04-25 17:45:01,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4600\n", + "Function value obtained: -1.9894\n", + "Current minimum: -2.1287\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:45:09,877\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4054\n", + "Function value obtained: -2.0045\n", + "Current minimum: -2.1287\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-2.703683694288526]\n", + " warnings.warn(\n", + "2024-04-25 17:45:18,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1587\n", + "Function value obtained: -1.8827\n", + "Current minimum: -2.1287\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:45:26,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4855\n", + "Function value obtained: -1.9271\n", + "Current minimum: -2.1287\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:45:33,929\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 7.2841\n", + "Function value obtained: -2.0115\n", + "Current minimum: -2.1287\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:45:41,196\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 7.3577\n", + "Function value obtained: -1.9363\n", + "Current minimum: -2.1287\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:45:48,556\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7215\n", + "Function value obtained: -2.0020\n", + "Current minimum: -2.1287\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:45:56,290\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5647\n", + "Function value obtained: -1.9813\n", + "Current minimum: -2.1287\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:46:03,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6284\n", + "Function value obtained: -1.8912\n", + "Current minimum: -2.1287\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-1.0255907058676303]\n", + " warnings.warn(\n", + "2024-04-25 17:46:11,493\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6490\n", + "Function value obtained: -2.1065\n", + "Current minimum: -2.1287\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:46:19,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5100\n", + "Function value obtained: -2.0861\n", + "Current minimum: -2.1287\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:46:26,654\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 7.2805\n", + "Function value obtained: -2.0434\n", + "Current minimum: -2.1287\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:46:33,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6268\n", + "Function value obtained: -1.9285\n", + "Current minimum: -2.1287\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.3826217743275695]\n", + " warnings.warn(\n", + "2024-04-25 17:46:41,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6558\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.1287\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:46:49,242\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7707\n", + "Function value obtained: -2.0044\n", + "Current minimum: -2.1287\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.8102285992201157]\n", + " warnings.warn(\n", + "2024-04-25 17:46:57,024\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6583\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.1287\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.3859259110617854]\n", + " warnings.warn(\n", + "2024-04-25 17:47:05,710\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9140\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.1287\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:47:13,607\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4819\n", + "Function value obtained: -1.9521\n", + "Current minimum: -2.1287\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [0.10995143036891619]\n", + " warnings.warn(\n", + "2024-04-25 17:47:21,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7571\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.1287\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:47:28,882\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4464\n", + "Function value obtained: -1.9466\n", + "Current minimum: -2.1287\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:47:36,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5964\n", + "Function value obtained: -1.9455\n", + "Current minimum: -2.1287\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:47:43,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5785\n", + "Function value obtained: -2.1195\n", + "Current minimum: -2.1287\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:47:51,490\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6549\n", + "Function value obtained: -1.9578\n", + "Current minimum: -2.1287\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:47:59,156\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6839\n", + "Function value obtained: -2.0423\n", + "Current minimum: -2.1287\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:48:06,842\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5758\n", + "Function value obtained: -1.9169\n", + "Current minimum: -2.1287\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-0.12854283508189202]\n", + " warnings.warn(\n", + "2024-04-25 17:48:15,422\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7738\n", + "Function value obtained: -0.3884\n", + "Current minimum: -2.1287\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-1.7795068095198445]\n", + " warnings.warn(\n", + "2024-04-25 17:48:23,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6866\n", + "Function value obtained: -1.9185\n", + "Current minimum: -2.1287\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-4.462853949509887]\n", + " warnings.warn(\n", + "2024-04-25 17:48:30,947\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8422\n", + "Function value obtained: -1.8635\n", + "Current minimum: -2.1287\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.862197976179674]\n", + " warnings.warn(\n", + "2024-04-25 17:48:38,769\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0573\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.1287\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-2.4203438877690298]\n", + " warnings.warn(\n", + "2024-04-25 17:48:46,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8161\n", + "Function value obtained: -1.9774\n", + "Current minimum: -2.1287\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-3.4506555127302057]\n", + " warnings.warn(\n", + "2024-04-25 17:48:54,636\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9360\n", + "Function value obtained: -1.8775\n", + "Current minimum: -2.1287\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-2.4324444495959483]\n", + " warnings.warn(\n", + "2024-04-25 17:49:02,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8956\n", + "Function value obtained: -1.8945\n", + "Current minimum: -2.1287\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-3.6627032192701106]\n", + " warnings.warn(\n", + "2024-04-25 17:49:10,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7399\n", + "Function value obtained: -1.9696\n", + "Current minimum: -2.1287\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-4.859554148703219]\n", + " warnings.warn(\n", + "2024-04-25 17:49:18,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9707\n", + "Function value obtained: -1.9285\n", + "Current minimum: -2.1287\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-5.7446808564087695]\n", + " warnings.warn(\n", + "2024-04-25 17:49:26,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0019\n", + "Function value obtained: -1.9361\n", + "Current minimum: -2.1287\n", + "CPU times: user 6min 43s, sys: 9min 27s, total: 16min 10s\n", + "Wall time: 6min 29s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-2.1286563027031495, [-1.1965266045176186])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "esc_gp = gp_minimize(esc_mw_obj, log_esc_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "esc_gp.fun, esc_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "fc6249e8-b6d5-49a3-908d-8f1b89c1abdd", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:49:34,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 7.5362\n", + "Function value obtained: -3.0056\n", + "Current minimum: -3.0056\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:49:41,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 7.3328\n", + "Function value obtained: -2.4511\n", + "Current minimum: -3.0056\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:49:49,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 7.5459\n", + "Function value obtained: -2.0481\n", + "Current minimum: -3.0056\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:49:56,692\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 7.5742\n", + "Function value obtained: -4.0016\n", + "Current minimum: -4.0016\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:04,279\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 7.5454\n", + "Function value obtained: -2.5316\n", + "Current minimum: -4.0016\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:11,814\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 7.7054\n", + "Function value obtained: -16.9847\n", + "Current minimum: -16.9847\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:19,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 7.7268\n", + "Function value obtained: -13.3485\n", + "Current minimum: -16.9847\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:27,261\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 8.3116\n", + "Function value obtained: -6.8201\n", + "Current minimum: -16.9847\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:35,612\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 7.5522\n", + "Function value obtained: -43.3207\n", + "Current minimum: -43.3207\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:43,105\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 7.6797\n", + "Function value obtained: -2.1571\n", + "Current minimum: -43.3207\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:50,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8512\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.3207\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:50:58,633\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7731\n", + "Function value obtained: -41.5928\n", + "Current minimum: -43.3207\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:51:06,425\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0390\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.3207\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:51:14,553\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6942\n", + "Function value obtained: -39.7440\n", + "Current minimum: -43.3207\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:51:23,185\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9191\n", + "Function value obtained: -43.5548\n", + "Current minimum: -43.5548\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:51:32,107\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0632\n", + "Function value obtained: -44.1675\n", + "Current minimum: -44.1675\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:51:40,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2439\n", + "Function value obtained: -42.1269\n", + "Current minimum: -44.1675\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:51:48,410\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7441\n", + "Function value obtained: -44.3219\n", + "Current minimum: -44.3219\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:51:57,211\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1056\n", + "Function value obtained: -46.6821\n", + "Current minimum: -46.6821\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:52:05,280\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8339\n", + "Function value obtained: -47.3783\n", + "Current minimum: -47.3783\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:52:14,145\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9693\n", + "Function value obtained: -47.2997\n", + "Current minimum: -47.3783\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:52:22,093\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0583\n", + "Function value obtained: -45.8191\n", + "Current minimum: -47.3783\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:52:30,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0238\n", + "Function value obtained: -1.9344\n", + "Current minimum: -47.3783\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:52:38,113\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9621\n", + "Function value obtained: -46.0481\n", + "Current minimum: -47.3783\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:52:46,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8595\n", + "Function value obtained: -2.0613\n", + "Current minimum: -47.3783\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:52:54,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7663\n", + "Function value obtained: -48.8415\n", + "Current minimum: -48.8415\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:53:03,775\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2160\n", + "Function value obtained: -2.5755\n", + "Current minimum: -48.8415\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:53:12,023\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1004\n", + "Function value obtained: -2.9925\n", + "Current minimum: -48.8415\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:53:20,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8805\n", + "Function value obtained: -43.0760\n", + "Current minimum: -48.8415\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:53:29,008\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1147\n", + "Function value obtained: -1.5035\n", + "Current minimum: -48.8415\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:53:37,125\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5263\n", + "Function value obtained: -33.0037\n", + "Current minimum: -48.8415\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:53:45,647\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7627\n", + "Function value obtained: -2.8038\n", + "Current minimum: -48.8415\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:53:54,307\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6853\n", + "Function value obtained: -39.6488\n", + "Current minimum: -48.8415\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:54:03,120\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2671\n", + "Function value obtained: -2.1287\n", + "Current minimum: -48.8415\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:54:11,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7627\n", + "Function value obtained: -37.9392\n", + "Current minimum: -48.8415\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:54:20,156\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0250\n", + "Function value obtained: -48.8930\n", + "Current minimum: -48.8930\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:54:29,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6697\n", + "Function value obtained: -47.6254\n", + "Current minimum: -48.8930\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:54:37,875\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9464\n", + "Function value obtained: -46.8607\n", + "Current minimum: -48.8930\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:54:46,778\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8875\n", + "Function value obtained: -54.4202\n", + "Current minimum: -54.4202\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:54:55,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0514\n", + "Function value obtained: -6.1205\n", + "Current minimum: -54.4202\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:55:04,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0313\n", + "Function value obtained: -43.3462\n", + "Current minimum: -54.4202\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:55:13,790\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9432\n", + "Function value obtained: -59.7009\n", + "Current minimum: -59.7009\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:55:22,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1085\n", + "Function value obtained: -64.2411\n", + "Current minimum: -64.2411\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:55:30,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4671\n", + "Function value obtained: -68.1196\n", + "Current minimum: -68.1196\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:55:39,322\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2507\n", + "Function value obtained: -66.5993\n", + "Current minimum: -68.1196\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:55:47,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0281\n", + "Function value obtained: -66.7937\n", + "Current minimum: -68.1196\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:55:56,587\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8776\n", + "Function value obtained: -2.5539\n", + "Current minimum: -68.1196\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:56:05,476\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9121\n", + "Function value obtained: -67.5293\n", + "Current minimum: -68.1196\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:56:14,410\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1004\n", + "Function value obtained: -45.8205\n", + "Current minimum: -68.1196\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:56:23,505\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0912\n", + "Function value obtained: -34.1005\n", + "Current minimum: -68.1196\n", + "CPU times: user 7min 13s, sys: 9min 45s, total: 16min 58s\n", + "Wall time: 6min 58s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-68.11960248259545, [0.0, 0.4341115767435898, 0.5087638530904239])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "cr_gp = gp_minimize(cr_mwt_obj, cr_space, n_calls = 50, verbose=True, n_jobs=-1)\n", + "cr_gp.fun, cr_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "c1d240ba-15c2-47d3-909b-317951d5406e", + "metadata": {}, + "outputs": [], + "source": [ + "def get_policy_df(policy_obj, minx=-1, maxx=1, nx=500):\n", + " obs_list = np.array([\n", + " [-1, mwt_obs] \n", + " for mwt_obs in np.linspace(minx, maxx, nx)\n", + " ])\n", + " mwt_obs_list = np.linspace(minx, maxx, nx)\n", + "\n", + " env = policy_obj.env\n", + " MIN_WT = policy_obj.env.parameters['min_wt']\n", + " MAX_WT = policy_obj.env.parameters['max_wt']\n", + " \n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': mwt_obs_list,\n", + " 'mean_wt': MIN_WT + (MAX_WT - MIN_WT) * (mwt_obs_list + 1)/2,\n", + " 'fishing_mortality': [\n", + " (1 + policy_obj.predict(np.float32([obs]))[0][0]) / 2 \n", + " for obs in obs_list\n", + " ]\n", + " }\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "6b906bea-4b04-4e17-9441-b3bfd0c32623", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "cr_gp_preargs = {\n", + " 'log_radius': cr_gp.x[0], \n", + " 'theta': cr_gp.x[1], \n", + " 'y2': cr_gp.x[2],\n", + "}\n", + "cr_gp_args = {}\n", + "cr_gp_args['x1'] = (10 ** cr_gp_preargs['log_radius']) * np.sin(cr_gp_preargs['theta'])\n", + "cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", + "cr_gp_args['y2'] = cr_gp_preargs['y2']\n", + "\n", + "cr_gp_df = get_policy_df(CautionaryRule(env=AsmEnv(config=CONFIG), observed_var='mean_wt', **cr_gp_args))\n", + "\n", + "esc_gp_preargs = {'log_escapement': esc_gp.x[0]}\n", + "esc_gp_args = {'escapement': 10 ** esc_gp_preargs['log_escapement']}\n", + "\n", + "esc_gp_df = get_policy_df(\n", + " ConstEsc(env=AsmEnv(config=CONFIG), observed_var='mean_wt', **esc_gp_args)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "53cd6279-088f-4736-8b31-be4d26495ede", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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UKvHYY48BAP7zn/8AwG3nxLjRunXrKrwEtVevXvDy8kLv3r3h7e2NLl26wMvLC3FxcVi0aBH69etnGvswd+5c/P7774iMjDRdTnvx4kWsXbsWO3bsgLOzMx566CHMmjULo0ePRufOnXHkyBGsWrXK9L/km7m6uqJr164YPXo00tLSsGDBAjRp0gRPPfUUAEChUODzzz9H3759ER4ejtGjR8PPzw/nz5/H1q1bodPp8PPPP1fupN/B8OHD8f333+OZZ57B1q1b0aVLFxgMBpw4cQLff/89fvvttwoH/t5O2ffw9ddfx2OPPQZbW1v079//lq0hw4YNw9GjRzFv3jzs2bMHjz32GIKCgpCXl4ejR4/iu+++g1arNRtTUx2SkpIwYMAAPPDAA4iNjcU333yDYcOGoU2bNgCq/3fg448/RteuXXHvvfdi3LhxCAoKwpkzZ7Bx48ZyA3tHjBiBwYMHAwBmz55dLe+XGiC5LgcislR8fLx46qmnRGBgoFCpVEKr1YouXbqIhQsXisLCQtN6xcXFYubMmSIoKEjY2toKf39/MXXqVLN1hCi9XLiiy4BvvoTyrbfeEh07dhTOzs7Czs5OhIWFiTlz5gi9Xm9ap6SkREycOFF4eHgISZLMLh0OCAgQAQEBd3x/t7tcGIDYunWrEEKIzz77THTv3l24ubkJtVotQkJCxMsvvyyys7PN9nf27FkxYsQI4eHhIdRqtQgODhYTJkwQRUVFQojSy4Vfeukl4ePjI+zs7ESXLl1EbGxsufdfdrnwd999J6ZOnSo8PT2FnZ2d6NevX7lLSIUQ4uDBg+KRRx4x1RcQECCGDBkiYmJiyr3XjIwMs21HjhwpHBwcKvye3HyJtF6vF2+//bYIDw8XarVauLi4iHbt2omZM2eanQsAYsKECeX2GRAQYHYJshBCzJ49W/j5+QmFQlHpS4e3bdsmBg8eLHx8fIStra3Q6XSiffv2Yvr06eLixYt3fB+VVXbOjh8/LgYPHiy0Wq1wcXERzz33nCgoKDBbt7K/A5W5XFgIIY4ePSoGDRoknJ2dhUajEaGhoeLNN98sV2NRUZFwcXERTk5O5WoiqixJiBpqbySiemHbtm3o2bMn1q5da/rfMNW+GTNmYObMmcjIyLDaLpKSkhL4+vqif//+5cYuEVUWx5gQEVG12LBhAzIyMjBixAi5S6E6jGNMiIjoruzevRv//vsvZs+ejXvuuQeRkZFyl0R1GFtMiIjornz66ad49tln4enpWe4mmESW4hgTIiIishpsMSEiIiKrwWBCREREVqNODH41Go24cOECtFptrU/9TURERFUjhEBubi58fX1NdzO/kzoRTC5cuFDuplxERERUN6SkpKBRo0aVWrdOBJOyabZTUlKg0+lkroaIiIgqIycnB/7+/qbP8cqoE8GkrPtGp9MxmBAREdUxlgzD4OBXIiIishoMJkRERGQ1GEyIiIjIatSJMSZERHSdwWBAcXGx3GUQwdbWFkqlslr3yWBCRFRHCCGQmpqKrKwsuUshMnF2doa3t3e1zTPGYEJEVEeUhRJPT0/Y29tzwkmSlRAC+fn5SE9PBwD4+PhUy34ZTIiI6gCDwWAKJW5ubnKXQwQAsLOzAwCkp6fD09OzWrp1OPiViKgOKBtTYm9vL3MlRObKfiara9wTgwkRUR3C7huyNtX9M8lgQkRERFaDwYSIiGqUEALjxo2Dq6srJEmCs7MzXnzxxUpt26NHjzuuK0kSNmzYcNd11jejRo3CwIEDTc8rcy6tAQe/EhFRjdq8eTO+/PJLbNu2DcHBwVAoFKZBk9Xh4sWLcHFxqbb9WZsePXqgbdu2WLBgwV3tZ/369bC1tTU9DwwMxIsvvmh1YaVBB5MLWQWQJMBRbQMHlQ0UCvbdEhFVt8TERPj4+KBz5841sn9vb+8a2a/c9Ho9VCpVte3P1dW12vZVkxp0V86Law6h07wtaDXjdwS/tgktp/+G++bGoNcH2zHok50Y/sVujF+1H6+sO4zZvxzHh3/E4/O/T2P1nmT88u8FbI/PwP6zVxCflosLWQXIKSyG0SjkfltERFZj1KhRmDhxIpKTkyFJEgIDA8t1KXzyySdo2rQpNBoNvLy8MHjwYLN9GI1GvPLKK3B1dYW3tzdmzJhh9vqNXTlnzpyBJElYv349evbsCXt7e7Rp0waxsbFm2yxbtgz+/v6wt7fHoEGD8MEHH8DZ2blS72nGjBlo27Ytli9fjsaNG8PR0RHjx4+HwWDAO++8A29vb3h6emLOnDlm2yUnJ+Phhx+Go6MjdDodhgwZgrS0tHL7/fzzzxEUFASNRoNRo0Zh+/bt+OijjyBJEiRJwpkzZ2AwGDBmzBgEBQXBzs4OoaGh+Oijj25b943nvUePHjh79iwmTZpk2m9eXh50Oh3WrVtntt2GDRvg4OCA3NzcSp2fu9WgW0wkADYKCSXXwsTVohJcLSpBas7d7ddRbVP60JT+q9WUPkqX28JRYwOdxgY6jS10drbQ2ZV+7WRnC53GFloNW2+I6M6EECgoNtT6ce1slZW+EuOjjz5CSEgIli5dir1790KpVOLRRx81vb5v3z48//zz+Prrr9G5c2dcvnwZf//9t9k+Vq5ciejoaOzevRuxsbEYNWoUunTpgl69et3yuK+//jree+89NG3aFK+//joef/xxJCQkwMbGBjt37sQzzzyDt99+GwMGDMCff/6JN99806JzkJiYiF9//RWbN29GYmIiBg8ejNOnT6NZs2bYvn07du3ahSeffBJRUVGIiIiA0Wg0hZLt27ejpKQEEyZMwNChQ7Ft2zbTfhMSEvDDDz9g/fr1UCqVCAgIQHx8PFq2bIlZs2YBADw8PGA0GtGoUSOsXbsWbm5u2LVrF8aNGwcfHx8MGTLkjvWvX78ebdq0wbhx4/DUU08BABwcHPDYY49hxYoVZuGw7LlWq7XoHFVVgw4ma57uBCEEikqMyC0sDSVXC0uQW1Rc+rxsWVEJcgtLkFtYfMM619e9Wlj6+s0BB1UMOGXdS2XBxcnuhhBTFmDMltnAyd7W9NxBVfk/GkRUdxUUG9Bi2m+1ftzjs/rAXlW5jw8nJydotVoolcoKu1ySk5Ph4OCAhx56CFqtFgEBAbjnnnvM1mndujWmT58OAGjatCkWLVqEmJiY2waTyZMno1+/fgCAmTNnIjw8HAkJCQgLC8PChQvRt29fTJ48GQDQrFkz7Nq1C7/88kul3hNQ2oqzfPlyaLVatGjRAj179sTJkyexadMmKBQKhIaG4u2338bWrVsRERGBmJgYHDlyBElJSfD39wcAfPXVVwgPD8fevXvRoUMHAKXdN1999RU8PDxMx1KpVLC3tzc7f0qlEjNnzjQ9DwoKQmxsLL7//vtKBRNXV1colUpotVqz/Y4dOxadO3fGxYsX4ePjg/T0dGzatAl//vlnpc/N3WrQwQQobQLU2CqhsVXCQ6uu8n7KAk5ZiLkxtJiWmf4tRk5BadDJLihGTmEJcgqKkVNYjMJiI4TAtSBUgvNZBRbXolRIpS0yNwQZJ3tbuNjbwtlOBWd7Wzjbq+BsZwsXB1s42angYl+6no2yQffuEVEt69WrFwICAhAcHIwHHngADzzwAAYNGmQ2kVzr1q3Ntin7wLydG7cpmyo9PT0dYWFhOHnyJAYNGmS2fseOHS0KJoGBgWYtCF5eXlAqlVAoFGbLyuqMi4uDv7+/KZQAQIsWLeDs7Iy4uDhTMAkICDALJbezePFiLF++HMnJySgoKIBer0fbtm0r/R4q0rFjR4SHh2PlypWYMmUKvvnmGwQEBKB79+53tV9LNPhgUl1uDDjujlUPOEUlBuQUlCCnsPhaWCkpDS/XgkvZa9eXlSD32mvZBcUoNggYjAJX8otxJd/yWfi0Ghs429vCxV4FJ7vSf28OMjeGGxd7W2g1tlCy64mo1tnZKnF8Vh9ZjltdtFotDhw4gG3btuH333/HtGnTMGPGDOzdu9c05uPGK0mA0r+3RqPxtvu9cZuyFuQ7bWOJimqqSp03c3BwqNR6q1evxuTJk/H++++jU6dO0Gq1ePfdd7F7926LjleRsWPHYvHixZgyZQpWrFiB0aNH12orPIOJlVHbKOGhrVrrjRAChcXGG0JNaZDJKtAj61pQyc7XI6vg+tdX8ouRla9HTmEJgOstNSmXK99SI0mAs50tXB1UcHNQw9VBBVdHFdwcVKVf37DczVEFF3sVVDZsmSG6W5IkVbpLxZrZ2NggKioKUVFRmD59OpydnbFlyxY88sgjNXK80NBQ7N2712zZzc+rW/PmzZGSkoKUlBRTq8nx48eRlZWFFi1a3HZblUoFg8F8LNHOnTvRuXNnjB8/3rQsMTHRopoq2i8A/Pe//8Urr7yCjz/+GMePH8fIkSMt2u/dqvs/0WQiSRLsVErYqZTw0mks2rbEYEROYQmu5JeGmKyyfwuuf30lX4/sguIb1ikdcyMETC00iRl5lTqeVm0DV8ey0FIWYNTXv74WbNwc1XB3VEFtU33/QyMi6/HLL7/g9OnT6N69O1xcXLBp0yYYjUaEhobW2DEnTpyI7t2744MPPkD//v2xZcsW/PrrrzXaKhAVFYVWrVrhiSeewIIFC1BSUoLx48cjMjIS7du3v+22gYGB2L17N86cOQNHR0e4urqiadOm+Oqrr/Dbb78hKCgIX3/9Nfbu3YugoKBK1xQYGIi//voLjz32GNRqNdzd3QEALi4ueOSRR/Dyyy+jd+/eaNSo0V29d0sxmBAAwEapMLVuWKLYYERWfjEu5+lxKa8Il/P0uJKnx6U8/bVlely+ev3rK/l6GIwCuUWlA4jPXsqv1HF0Ght4aNVwd1TDQ6su97XHta/dHFQcJ0NUhzg7O2P9+vWYMWMGCgsL0bRpU3z33XcIDw+vsWN26dIFS5YswcyZM/HGG2+gT58+mDRpEhYtWlRjx5QkCT/99JMpFCkUCjzwwANYuHDhHbedPHkyRo4ciRYtWqCgoABJSUl4+umncfDgQQwdOhSSJOHxxx/H+PHj8euvv1a6plmzZuHpp59GSEgIioqKIMT16S7GjBmDb7/9Fk8++WSV3u/dkMSNlVipnJwcODk5ITs7GzqdTu5y6C4YjQI5hcXXg8u10HI5r8i07Mbll/KKUGyo/I+oJAEu9ipTUHF3VJULMp5aDbx0ajjZ2fLqJaozCgsLkZSUZJrfgqrXU089hRMnTpS7VLmh+vrrrzFp0iRcuHDhjpO83e5nsyqf32wxoVqlUEilA2ntVQipxMBzIQRyCkqQcbUQGbl6ZFwtQkZuETKv/Xvj15fySltjysLNybTbTwaksVXAS6eBl1YDLycNvHXq0uc6DbydNPDWaeChVUNTjQP9iMg6vPfee+jVqxccHBzw66+/YuXKlfjkk0/kLkt2+fn5uHjxIubPn4+nn366WmeerSwGE7JqkiTByb70cucmnrdf12gUuJJ/PbyUDzB6pOcWIj23CFn5pZdmn72Uf8fuJBd72+uBRVcWYkpbXXyc7ODnbAednQ1bX4jqkD179uCdd95Bbm4ugoOD8fHHH2Ps2LEAgPDwcJw9e7bC7T777DM88cQTtVlqrXrnnXcwZ84cdO/eHVOnTpWlBnblUINUWGxAek4RUnMKkZpTiPScQqRml319fbm+pHKX+jmolPB1tjM9/Jw1N3xtBy+dhlci0V1hV07tOXv2LIqLK55uwcvLq9ZmQK0r2JVDVA00tko0drNHYzf7W64jhEB2QXFpSMkuLB9kcgpxMasQl/L0yNMbcCr9Kk6lX61wX5IEeGrVZmHF16k0vPi52MHf1R46jW2F2xJR7QoICJC7hAaNwYToFiTp+niYMO9bJ/3CYgMuZBXgQlYhLmQV4HxWQenz7NJl57MKoC8xIi2nCGk5RTiYnFXhfpztbdHY1R7+Lvbwd7Uv/drVDo1d7eHrbAdbXm1ERA0AgwnRXdLYKhHs4YhgD8cKXxdC4FKe/lp4KcD5awGmLMScv1KAS3llc8Nk499z2eX2oZAAHyc7s7Di73o9wLg5qDjGpYGoztlLiapDdf9MMpgQ1TBJkuDuWHq5cutGzhWuk1dUgpQr+Ui+lI+UKwVIuZyP5Mv5pn+LSoylISarALGny2+vVdsg0N0BQe4OCHR3QPC1f4PcHOBkzy6i+kClUkGhUODChQvw8PCASsUwSvISQkCv1yMjIwMKhaLaruDh4FciKyeEQEZuUWlwuZyPlMsFptCScjkfF3MKcbvfYlcHFQLd7BHk7ogg99J/A93tEeTuUC+mM29I9Ho9Ll68iPz8yk1MSFQb7O3t4ePjU2EwqcrnN4MJUR1XWGxAyuV8nM7Mw5nMPCTd8EjPLbrttj5OGjTxdERTTy2aejmiqacjmng6wtm+9ucuoMoRQqCkpKTCe5wQ1TalUgkbm1tPl8BgQkRmrhaVmMKKKbRcKv036zZ3n3Z3VKOpp6MprIRcCy/ujuw+IKLKYzAhokq7kqdHYkbpJc4J1y51TkjLxYXswltu42xvi6aejgjz1iHMR1v6r7cWDmp2CRFReQwmRHTXrhaVIDH9emBJSM/FqfSrSL6cf8uxLAFu9gjz1qK5jw5h3jo099HC38UeCgVbV4gaMgYTIqoxhcUGnM7IQ3xaLk6k5iLuYg5OpOYgLaficSwOKiVCvbUI89GhhY8OrfycEOajhdqG9x4iaigYTIio1l3O0+PExRzE3RBW4tOuVjidv41CQqi3Fq38nNDSzwmtGzkh1Jthhai+YjAhIqtQYjAiKTPPFFaOXcjBkXNZuFLBgFtbpYRmXlq0blQaVlr5OSHMW8d7CxHVAwwmRGS1hBA4n1WAo+dLZ7c9cj4bR89nVxhWVDYKtPJzwr2NnXFvYxfc09gF3k68cR1RXcNgQkR1ihAC566UhpUjNzwqupTZ10mDewJccI+/M+4NcEG4r45dQERWjsGEiOo8IQSSMvNwMDkLB5Kv4EByFk6m5sB4018qlVKBcD8dOga6omOQK9oHusLJjtPvE1kTBhMiqpeuFpXg33NZpWHl7BUcTMnC5Ty92TqSBLTw0aFjkCsiglzRMcgNrg6cwZZITgwmRNQgCCFw9lI+9p+9gj1Jl7HnzGUkZeaVW6+ppyMigktDSucQN7g7qmWolqjhYjAhogYrLacQe5IuY3fSJew+fRmn0q+WW6e5jw5dm7iha1MPdAx0hZ2KY1SIahKDCRHRNZeuFmHvmSvYnXQJsYmXcCI11+x1lVKBdgEu6NrUHV2buKOlnxOUnKmWqFoxmBAR3ULm1SLsTMjEjlOZ2JGQiYs33RPIyc4W3Zq64/4wT/QI9eT4FKJqwGBCRFQJQgiczszDzoRM/H0qE/8kXkJuUYnpdUkC7vF3xv1hnrg/zAvNfbS8qzJRFTCYEBFVQYnBiEMpWdh6Mh1bTmQg7mKO2es+Thr0CPXE/WGe6NrEnWNTiCqJwYSIqBpcyCrA1pPp2HoiHTsSMlFYfP2+P3a2SvQI9cADLb1xf5gntBrOnUJ0KwwmRETVrLDYgH9OX8KWE+mIiUvH+awC02sqpQJdmrihb0sfRLXw4rgUopswmBAR1SAhBI6ez8HmYxfx69FUnM64PneKQgIigtzQr7UPHmzlw5BCBAYTIqJadSotF5uPpmLzsVQcu3B9XIqNQkJkMw8MaOuLXi28YK+ykbFKIvkwmBARyST5Uj5+PXoR/zt8wSyk2KuU6N3CCw+39UPXpu6wVSpkrJKodjGYEBFZgYT0XPx06AJ+OnQByZfzTctdHVTo39oHQzr4I9zXScYKiWoHgwkRkRURQuBQShZ+OnQBv/x7AZlXr994sKWfDkPb+2NAGz842fPKHqqfGEyIiKxUicGIHQmZWLv/HP44lga9ofQSZLWNAg+09MbQ9v64L9gNCk6LT/UIgwkRUR1wJU+PHw+ex/f7Uszu4dPY1R7D7wvAo+0bwdmeV/VQ3cdgQkRUhwghcOR8NtbsTcH/Dl0wTYuvsVVgYFs/DO8UwLEoVKcxmBAR1VEFegP+d/g8vtx11mxK/A6BLhjRKRB9wr2hsuEVPVS3VOXzu0o/5YsXL0ZgYCA0Gg0iIiKwZ8+e266/YMEChIaGws7ODv7+/pg0aRIKCwtvuw0RUUNip1JiaIfG2PR8V6x7phP6t/GFjULC3jNXMPG7g+j69hYs3pqA7PxiuUslqlEWt5isWbMGI0aMwJIlSxAREYEFCxZg7dq1OHnyJDw9Pcut/+233+LJJ5/E8uXL0blzZ8THx2PUqFF47LHH8MEHH1TqmGwxIaKGKD2nEN/uScaq3cnIyC0CADiolHi8Y2M82TUIvs52MldIdHu10pUTERGBDh06YNGiRQAAo9EIf39/TJw4EVOmTCm3/nPPPYe4uDjExMSYlr300kvYvXs3duzYUaljMpgQUUOmLzFi45EL+Gz7adNgWRuFhAFtfDEuMhhh3vy7SNapxrty9Ho99u/fj6ioqOs7UCgQFRWF2NjYCrfp3Lkz9u/fb+ruOX36NDZt2oQHH3zwlscpKipCTk6O2YOIqKFS2Sgw6J5G+PWFbvhydAd0CnZDiVFg/cHzeGDB3xjz5V78ey5L7jKJqoVFN3DIzMyEwWCAl5eX2XIvLy+cOHGiwm2GDRuGzMxMdO3aFUIIlJSU4JlnnsFrr712y+PMmzcPM2fOtKQ0IqJ6T5Ik9Aj1RI9QT/x7Lguf/XUavx65iJgT6Yg5kY6o5p544T/N0KoRr+ShuqvGh3hv27YNc+fOxSeffIIDBw5g/fr12LhxI2bPnn3LbaZOnYrs7GzTIyUlpabLJCKqU1o3csbiYffiz+hIPHKPHxQS8GdcOvov2oGxK/fiyLlsuUskqhKLxpjo9XrY29tj3bp1GDhwoGn5yJEjkZWVhZ9++qncNt26dcN9992Hd99917Tsm2++wbhx43D16lUoFHfORhxjQkR0e6czrmLRlgRsOHQexmt/1Xu18MIrfULR1Esrb3HUYNX4GBOVSoV27dqZDWQ1Go2IiYlBp06dKtwmPz+/XPhQKpUASicXIiKiuxfs4YgPhrbFH9GRGHStBeWP42nos+AvTPnhX6TlcIoGqhss7sqJjo7GsmXLsHLlSsTFxeHZZ59FXl4eRo8eDQAYMWIEpk6dalq/f//++PTTT7F69WokJSXhjz/+wJtvvon+/fubAgoREVWPEA9HfDi0LX6fFIk+4V4wCmD13hREvrsV7/52AjmFnAeFrJtFg18BYOjQocjIyMC0adOQmpqKtm3bYvPmzaYBscnJyWYtJG+88QYkScIbb7yB8+fPw8PDA/3798ecOXOq710QEZGZJp6O+Gx4e+w7cxnzfj2B/WevYPHWRHy3JwXRvZrh8Y6NoeQNA8kKcUp6IqJ6TgiB34+n4e3NJ3A6Iw8A0MJHh5kPh6NDoKvM1VF9xnvlEBHRLZUYjFi1Oxnv/34SOYWlNwx8uK0vpvZtDm8njczVUX3EYEJERHd06WoR3vs9Hqv3JkMIwF6lxPP/aYoxXYNgq+SNAqn6MJgQEVGlHTmXjen/O4oDyVkAgOY+Orz9f63QupGzrHVR/VFrdxcmIqK6r1UjJ/zwbGe8O7g1nO1tEXcxBwMX78RbvxxHvr5E7vKogWIwISJqwCRJwqPt/fFndCQGtPGFUQCf70hC7w//wvb4DLnLowaIwYSIiODuqMbHj9+DFaM6wM/ZDueuFGDk8j2Yuv5f5BWx9YRqD4MJERGZ9AzzxO+TumNU50BIEvDdnhT0/ehv7D1zWe7SqIFgMCEiIjMOahvMGBCOb8feBz9nOyRfzseQz2Ix/9cTKCoxyF0e1XMMJkREVKFOIW749cVuGNyuEYQAlmxPxKDFu5CUmSd3aVSPMZgQEdEt6TS2eO/RNvhseDu4Oqhw/GIOHvr4b/x06LzcpVE9xWBCRER31CfcG7++0A0RQa7I0xvwwupDeHXdvyjQs2uHqheDCRERVYqXToNvn7oPz/+nKSQJWLMvBQ8v3oHEjKtyl0b1CIMJERFVmlIhIbpXM6waEwEPrRrxaVcxcNFOxMSlyV0a1RMMJkREZLHOTdyx8fmu6BDogtyiEoz9ah8WxpyC0Wj1dzkhK8dgQkREVeKp1WDV2Psw/L4ACAG8/0c8nl21H1c5IRvdBQYTIiKqMpWNArMHtsTb/9cKKqUCvx1Lw/99sgvnswrkLo3qKAYTIiK6a0M7NMaap++Dp1aNk2m5GLR4J46ez5a7LKqDGEyIiKha3NPYBRsmdEGolxbpuUUY8lkstpzgoFiyDIMJERFVG19nO6x9thO6NnFHvt6AsSv34et/zspdFtUhDCZERFStdBpbrBjdAY+2awSjAN7ccBQf/H4SQvCKHbozBhMiIqp2tkoF3hncGpOimgEAPt6SgFm/HOflxHRHDCZERFQjJEnCC1FNMXNAOABgxc4zmLL+XxgYTug2GEyIiKhGjewciPcebQOFBHy/7xye/+4g9CVGucsiK8VgQkRENW5wu0ZYPOxe2ColbDxyEU9/vQ9FJbwBIJXHYEJERLWibysffD6yAzS2Cmw9mYEJqw6w5YTKYTAhIqJaE9nMA1+M7AC1jQJ/xqVj4ncHUGxgOKHrGEyIiKhWdWnijqUj2pumsH9x9SGUMJzQNQwmRERU6yKbeWDJ8OtjTl794QjnOSEADCZERCST+8O8sGjYvVAqJPxw4Bzm/3pC7pLICjCYEBGRbPqEe2P+I60AAJ/9dRpL/0qUuSKSG4MJERHJ6tH2/pjSNwwAMHfTCazbf07mikhODCZERCS7p7sH46luQQCAV3/4F3+fypC5IpILgwkREclOkiRM7dscg+7xg8EoMH7VASSk58pdFsmAwYSIiKyCQiFh/v+1QodAF+QWlmD0l3tx6WqR3GVRLWMwISIiq6G2UeKz4e3R2NUeKZcL8PTX+zl1fQPDYEJERFbF1UGF5aPaQ6uxwb6zVzB1Pec4aUgYTIiIyOo08dTi0yfaQamQsP7AeXzzz1m5S6JawmBCRERWqWtTd7z6QCgAYNYvx7H/7BWZK6LawGBCRERW66luwXiwlTeKDQLjV+1HRi4Hw9Z3DCZERGS1JEnCO4PboImnI9JyivDctwd4w796jsGEiIismqPaBkv+2w6OahvsTrqMD/+Ml7skqkEMJkREZPWaeDri7f9rDQD4ZFsidiVmylwR1RQGEyIiqhP6tfbB0Pb+EAKYtOYQLufp5S6JagCDCRER1RnTB7RAsIcD0nKK8Mq6fzm/ST3EYEJERHWGvcoGHz92D1RKBf6MS+P8JvUQgwkREdUpLf2c8GrfMADAWxvjcDrjqswVUXViMCEiojrnyS6B6NrEHUUlRry87l8YjOzSqS8YTIiIqM6RpNI7ETuqbbD/7BWs2Jkkd0lUTRhMiIioTmrkYo/XHmwOAHj3t5NIysyTuSKqDgwmRERUZz3e0f96l87aw+zSqQcYTIiIqM4q69JxUCmx7+wVrNx1Ru6S6C4xmBARUZ3WyMUeU6916bz/+0mkZhfKXBHdDQYTIiKq84Z1bIy2/s7I0xvw1sbjcpdDd4HBhIiI6jyFQsJbA1tCIQG//HsRf5/KkLskqiIGEyIiqhda+jlhRKdAAMC0n46hqMQgb0FUJQwmRERUb0T3bgYPrRpJmXlYuv203OVQFTCYEBFRvaHT2OKNfqUDYRdtTUDK5XyZKyJLMZgQEVG9MqCNLzoFu6GoxIh3fjspdzlkIQYTIiKqVyRJwhsPNYckAT8fvoD9Z6/IXRJZgMGEiIjqnXBfJzzarhEA4K2NxyEEZ4StKxhMiIioXprcOxT2KiUOJmfhl38vyl0OVVKVgsnixYsRGBgIjUaDiIgI7Nmz57brZ2VlYcKECfDx8YFarUazZs2wadOmKhVMRERUGZ46DZ6NDAEAzP/1BC8friMsDiZr1qxBdHQ0pk+fjgMHDqBNmzbo06cP0tPTK1xfr9ejV69eOHPmDNatW4eTJ09i2bJl8PPzu+viiYiIbmdst2B46dQ4n1WA1XtS5C6HKkESFna8RUREoEOHDli0aBEAwGg0wt/fHxMnTsSUKVPKrb9kyRK8++67OHHiBGxtbatUZE5ODpycnJCdnQ2dTlelfRARUcP0zT9n8caGo3B3VOOvV3rAXmUjd0kNRlU+vy1qMdHr9di/fz+ioqKu70ChQFRUFGJjYyvc5n//+x86deqECRMmwMvLCy1btsTcuXNhMNy6Sa2oqAg5OTlmDyIioqoY2sEfjV3tkXm1CCt2npG7HLoDi4JJZmYmDAYDvLy8zJZ7eXkhNTW1wm1Onz6NdevWwWAwYNOmTXjzzTfx/vvv46233rrlcebNmwcnJyfTw9/f35IyiYiITGyVCkT3agYA+Gx7IrLzi2WuiG6nxq/KMRqN8PT0xNKlS9GuXTsMHToUr7/+OpYsWXLLbaZOnYrs7GzTIyWF/YJERFR1/dv4ItRLi5zCEiz7m1PVWzOLgom7uzuUSiXS0tLMlqelpcHb27vCbXx8fNCsWTMolUrTsubNmyM1NRV6vb7CbdRqNXQ6ndmDiIioqpQKCdG9S1tNvtx1hq0mVsyiYKJSqdCuXTvExMSYlhmNRsTExKBTp04VbtOlSxckJCTAaDSalsXHx8PHxwcqlaqKZRMREVmmV3MvhHlrcbWoBCt2JcldDt2CxV050dHRWLZsGVauXIm4uDg8++yzyMvLw+jRowEAI0aMwNSpU03rP/vss7h8+TJeeOEFxMfHY+PGjZg7dy4mTJhQfe+CiIjoDhQKCc/d3wQAsGLnGeQWstXEGll8zdTQoUORkZGBadOmITU1FW3btsXmzZtNA2KTk5OhUFzPO/7+/vjtt98wadIktG7dGn5+fnjhhRfw6quvVt+7ICIiqoS+LX0Q4hGPxIw8fP3PWYzv0UTukugmFs9jIgfOY0JERNVl/YFziP7+MFwdVNjxak/Oa1KDanweEyIiorpuQBtfBLjZ43KeHmv28qpPa8NgQkREDYqNUoGnugUDAJbvTEKJwXiHLag2MZgQEVGD83/3NoKrgwoplwvw27G0O29AtYbBhIiIGhw7lRL/vS8AALD079OoA8MtGwwGEyIiapBGdAqAykaBwylZ2Hf2itzl0DUMJkRE1CC5O6rxf/f6AQCW/sVp6q0FgwkRETVYY7qWDoL9My4NZy/lyVwNAQwmRETUgDXxdET3Zh4QAli1O1nucggMJkRE1MCNuDYI9vt9KSgsNshcDTGYEBFRg9YzzBN+znbIyi/Gz4cvyF1Og8dgQkREDZpSIeGJ+xoDAL7+56zM1RCDCRERNXhD2/tDpVTg33PZOJSSJXc5DRqDCRERNXhujmr0a+0DAPgq9oy8xTRwDCZERESAaSbYTUcuIqewWOZqGi4GEyIiIgD3NnZGE09HFBYb8cvhi3KX02AxmBAREQGQJAlD2jcCUHrpMMmDwYSIiOiaQfc0go1CwqGULMSn5cpdToPEYEJERHSNh1aN+8M8AQBr2WoiCwYTIiKiGwxp7w8AWH/gPIoNRpmraXgYTIiIiG7QI9QDHlo1LuXpEROXLnc5DQ6DCRER0Q1slAo8cq8fAGDDwfMyV9PwMJgQERHdZGDb0mCy5WQ6sgs4p0ltYjAhIiK6SZi3Fs28HKEvMeK3Y6lyl9OgMJgQERHdRJIkPHyt1eR/h3jH4drEYEJERFSBAW18AQC7EjORnlMoczUNB4MJERFRBfxd7XFvY2cYBfDzv5yivrYwmBAREd3C9e4cXp1TWxhMiIiIbuHBVj5QKiQcPpeNM5l5cpfTIDCYEBER3YKHVo1OwW4AgM28OqdWMJgQERHdxgMtvQEAm48ymNQGBhMiIqLb6N3CC5IEHErJwsXsArnLqfcYTIiIiG7DU6dBu8YuAIDf2GpS4xhMiIiI7sDUncNxJjWOwYSIiOgO+oSXBpM9SZdx6WqRzNXUbwwmREREd+Dvao+WfjoYBfDH8TS5y6nXGEyIiIgqoW9LHwDArxxnUqMYTIiIiCqhT7gXACA28RLyikpkrqb+YjAhIiKqhBAPRzR2tYfeYMSOhEy5y6m3GEyIiIgqQZIk3B/mCQDYdjJd5mrqLwYTIiKiSup5LZhsPZEBIYTM1dRPDCZERESVFBHkCjtbJVJzCnH8Yo7c5dRLDCZERESVpLFVokuT0pv6bT3B7pyawGBCRERkgbLunC0MJjWCwYSIiMgCPUNLg8nBlCxcztPLXE39w2BCRERkAV9nO4R5ayEEsD2erSbVjcGEiIjIQtcvG86QuZL6h8GEiIjIQt2aegAAdiZc4mXD1YzBhIiIyEL3BjhDY6tA5tUixKddlbuceoXBhIiIyEJqGyU6BpVeNszp6asXgwkREVEVdL02n8kuBpNqxWBCRERUBZ1D3AEA/5y+hGKDUeZq6g8GEyIioipo4aODi70t8vQGHE7JkruceoPBhIiIqAoUCgmdm5S2mnCcSfVhMCEiIqqirteCya6ESzJXUn8wmBAREVVRl2vjTA4kX0FeUYnM1dQPDCZERERV1NjNHv6udigxCuxJuix3OfUCgwkREdFduO/afCZ7zjCYVAcGEyIiorvQMcgVALCXLSbVgsGEiIjoLpQFk8PnslBYbJC5mrqPwYSIiOguNHa1h6dWjWKDwCHOZ3LXGEyIiIjugiRJ6MDunGpTpWCyePFiBAYGQqPRICIiAnv27KnUdqtXr4YkSRg4cGBVDktERGSVOgaWBhMOgL17FgeTNWvWIDo6GtOnT8eBAwfQpk0b9OnTB+np6bfd7syZM5g8eTK6detW5WKJiIisUYdrweTA2Sso4X1z7orFweSDDz7AU089hdGjR6NFixZYsmQJ7O3tsXz58ltuYzAY8MQTT2DmzJkIDg6+q4KJiIisTai3FlqNDfL0BsRdzJW7nDrNomCi1+uxf/9+REVFXd+BQoGoqCjExsbecrtZs2bB09MTY8aMqdRxioqKkJOTY/YgIiKyVkqFZGo1YXfO3bEomGRmZsJgMMDLy8tsuZeXF1JTUyvcZseOHfjiiy+wbNmySh9n3rx5cHJyMj38/f0tKZOIiKjWlQUTDoC9OzV6VU5ubi6GDx+OZcuWwd3dvdLbTZ06FdnZ2aZHSkpKDVZJRER09zoGuQAA9p65DCGEzNXUXTaWrOzu7g6lUom0tDSz5WlpafD29i63fmJiIs6cOYP+/fublhmNpYOCbGxscPLkSYSEhJTbTq1WQ61WW1IaERGRrFr5OUNlo8ClPD3OXspHoLuD3CXVSRa1mKhUKrRr1w4xMTGmZUajETExMejUqVO59cPCwnDkyBEcOnTI9BgwYAB69uyJQ4cOsYuGiIjqDZWNAuG+OgCls8BS1VjUYgIA0dHRGDlyJNq3b4+OHTtiwYIFyMvLw+jRowEAI0aMgJ+fH+bNmweNRoOWLVuabe/s7AwA5ZYTERHVdW0aOeNgchYOJmfh4bZ+cpdTJ1kcTIYOHYqMjAxMmzYNqampaNu2LTZv3mwaEJucnAyFghPKEhFRw3NPY2d8uQucmv4uSKIOjNDJycmBk5MTsrOzodPp5C6HiIioQmcv5SHy3W1QKRU4MrM31DZKuUuSVVU+v9m0QUREVE0au9rDxd4WeoMRJzjRWpUwmBAREVUTSZLQxt8ZALtzqorBhIiIqBq1ZTC5KwwmRERE1aisxeQwg0mVMJgQERFVo7aNnAEApzPzkJ1fLG8xdRCDCRERUTVycVAh0M0eAHCIE61ZjMGEiIiomrE7p+oYTIiIiKoZB8BWHYMJERFRNWvdyAkAcOxCtsyV1D0MJkRERNUszFsHSQLScoqQebVI7nLqFAYTIiKiauagtkGQmwMA4NiFHJmrqVsYTIiIiGpAC9/Se8McZzCxCIMJERFRDSgLJhxnYhkGEyIiohoQ7ls6AJYtJpZhMCEiIqoBLXxKW0ySLuUhr6hE5mrqDgYTIiKiGuChVcNTq4YQwIlUtppUFoMJERFRDQk3jTNhMKksBhMiIqIawnEmlmMwISIiqiEt2GJiMQYTIiKiGlLWlXMyNRfFBqPM1dQNDCZEREQ1xN/FHlq1DfQGIxLSr8pdTp3AYEJERFRDFAoJzX3YnWMJBhMiIqIa1MLUncNgUhkMJkRERDWomZcWAHAyjV05lcFgQkREVINCvR0BAPGpuTJXUjcwmBAREdWgptdaTFJzCpGdXyxzNdaPwYSIiKgG6TS28HXSAADi09lqcicMJkRERDWsmfe1cSbszrkjBhMiIqIaFnqtOyc+jcHkThhMiIiIapjpyhy2mNwRgwkREVENC/W+3mIihJC5GuvGYEJERFTDmng6QpKAK/nFyLhaJHc5Vo3BhIiIqIZpbJUIdHMAAMSncqK122EwISIiqgUhHqUTrSVmMJjcDoMJERFRLQjxLG0xYTC5PQYTIiKiWtDkWotJQjqDye0wmBAREdWCEE925VQGgwkREVEtKBtjkpZThNxC3jPnVhhMiIiIaoGTnS08tGoAQGJGnszVWC8GEyIioloS4nFtACzHmdwSgwkREVEt4SXDd8ZgQkREVEuaePLKnDthMCEiIqolbDG5MwYTIiKiWlJ2yfDZS/koNhhlrsY6MZgQERHVEl8nDTS2CpQYBVIu58tdjlViMCEiIqolkiSZbuZ35hIvGa4IgwkREVEtMgWTTLaYVITBhIiIqBYFurPF5HYYTIiIiGpRkLs9ACApk8GkIgwmREREtYhjTG6PwYSIiKgWBV3ryjl/pQD6El4yfDMGEyIiolrkoVXDQaWEUQDJvGS4HAYTIiKiWiRJEgJMV+awO+dmDCZERES1LIhX5twSgwkREVEtC7x2ZQ6DSXkMJkRERLWMk6zdGoMJERFRLSvryuFcJuUxmBAREdWyxq6lXTkXswt4l+GbMJgQERHVMg+tGmobBYwCuJBVIHc5VoXBhIiIqJZJkgT/a60mKZcZTG7EYEJERCSDsu4cTrJmrkrBZPHixQgMDIRGo0FERAT27Nlzy3WXLVuGbt26wcXFBS4uLoiKirrt+kRERA2Bv4sdACDlCoPJjSwOJmvWrEF0dDSmT5+OAwcOoE2bNujTpw/S09MrXH/btm14/PHHsXXrVsTGxsLf3x+9e/fG+fPn77p4IiKiusqfLSYVkoQQwpINIiIi0KFDByxatAgAYDQa4e/vj4kTJ2LKlCl33N5gMMDFxQWLFi3CiBEjKnXMnJwcODk5ITs7GzqdzpJyiYiIrNJvx1Lx9Nf70aaRE356rqvc5dSIqnx+W9RiotfrsX//fkRFRV3fgUKBqKgoxMbGVmof+fn5KC4uhqur6y3XKSoqQk5OjtmDiIioPuEYk4pZFEwyMzNhMBjg5eVlttzLywupqamV2serr74KX19fs3Bzs3nz5sHJycn08Pf3t6RMIiIiq1fWlXMlvxi5hcUyV2M9avWqnPnz52P16tX48ccfodFobrne1KlTkZ2dbXqkpKTUYpVEREQ1z1FtA1cHFQBeMnwjG0tWdnd3h1KpRFpamtnytLQ0eHt733bb9957D/Pnz8eff/6J1q1b33ZdtVoNtVptSWlERER1jr+LHS7n6ZF8OR8tfDmGErCwxUSlUqFdu3aIiYkxLTMajYiJiUGnTp1uud0777yD2bNnY/PmzWjfvn3VqyUiIqpHyrpzzvGSYROLWkwAIDo6GiNHjkT79u3RsWNHLFiwAHl5eRg9ejQAYMSIEfDz88O8efMAAG+//TamTZuGb7/9FoGBgaaxKI6OjnB0dKzGt0JERFS3cABseRYHk6FDhyIjIwPTpk1Damoq2rZti82bN5sGxCYnJ0OhuN4Q8+mnn0Kv12Pw4MFm+5k+fTpmzJhxd9UTERHVYdenpWcwKWNxMAGA5557Ds8991yFr23bts3s+ZkzZ6pyCCIionrPz7l09tcLWYUyV2I9eK8cIiIimfiaggmvyinDYEJERCQTX+fSqTNyi0qQXcC5TAAGEyIiItnYq67PZcJWk1IMJkRERDIqazVhMCnFYEJERCQjX6fScSbnGUwAMJgQERHJys+FweRGDCZEREQyKrtk+PwVBhOAwYSIiEhWfrxk2AyDCRERkYx8OcmaGQYTIiIiGZUFk7TcQuhLjDJXIz8GEyIiIhm5O6qgslFACCAth60mDCZEREQykiTJNM7kHAfAMpgQERHJjZOsXcdgQkREJDPTJcMMJgwmREREcvO+NvtrKseYMJgQERHJzVtX2pWTls1gwmBCREQkMx+n0mBykcGEwYSIiEhuXmUtJuzKYTAhIiKSm/e1FpNLeXoUlRhkrkZeDCZEREQyc7G3hcqm9CM5PadI5mrkxWBCREQkM0mSTANgG/qVOQwmREREVqAsmDT0AbAMJkRERFagbJxJQ79kmMGEiIjICpQFE3blEBERkexMY0zYYkJERERyY4tJKQYTIiIiK+DFFhMADCZERERWoWxa+rScQhiNQuZq5MNgQkREZAU8tGpIElBiFLiUp5e7HNkwmBAREVkBW6UC7o5qAA27O4fBhIiIyEr4cAAsgwkREZG18NSWtphk5Dbc++UwmBAREVkJj2vBJD2XLSZEREQkMw9taVdOOltMiIiISG4e7MphMCEiIrIWnqauHAYTIiIikllZMMlkMCEiIiK53diVI0TDnP2VwYSIiMhKlAUTvcGI7IJimauRB4MJERGRlVDbKOFkZwug4Y4zYTAhIiKyIg19kjUGEyIiIivS0CdZYzAhIiKyImwxISIiIqvhqbs2+2sOgwkRERHJzMOxYU+yxmBCRERkRTx17MohIiIiK3G9xYSDX4mIiEhmbDEhIiIiq+GhLR38mlNYgsJig8zV1D4GEyIiIiui09hAZVP68dwQW00YTIiIiKyIJEmmcSaX8vQyV1P7GEyIiIisjJujCgCQyRYTIiIikpu7qcWEwYSIiIhk5uZwrcXkKrtyiIiISGbu1+6Xk3mVLSZEREQkM7aYEBERkdXwuNZicoktJkRERCQ3Nwd25RAREZGVcNeWduVcYlcOERERya3scuHL+XroS4wyV1O7GEyIiIisjJuDClq1DYQAkjLz5C6nVlUpmCxevBiBgYHQaDSIiIjAnj17brv+2rVrERYWBo1Gg1atWmHTpk1VKpaIiKghkCQJzby1AICTabkyV1O7LA4ma9asQXR0NKZPn44DBw6gTZs26NOnD9LT0ytcf9euXXj88ccxZswYHDx4EAMHDsTAgQNx9OjRuy6eiIiovmrmVRpM4lMbVjCRhBDCkg0iIiLQoUMHLFq0CABgNBrh7++PiRMnYsqUKeXWHzp0KPLy8vDLL7+Ylt13331o27YtlixZUqlj5uTkwMnJCdnZ2dDpdJaUS0REVCet2JmEmT8fR/dmHpg7qGWNH89Dq4baRlmt+6zK57eNJQfQ6/XYv38/pk6dalqmUCgQFRWF2NjYCreJjY1FdHS02bI+ffpgw4YNtzxOUVERioquXyKVk5NjSZlERER1Xui1FpO/4jPQ9e2tNX689eM7497GLjV+nDuxKJhkZmbCYDDAy8vLbLmXlxdOnDhR4TapqakVrp+amnrL48ybNw8zZ860pDQiIqJ65Z7GLmjl54T4WhpjItXKUe7MomBSW6ZOnWrWypKTkwN/f38ZKyIiIqpddiolfp7YVe4yap1FwcTd3R1KpRJpaWlmy9PS0uDt7V3hNt7e3hatDwBqtRpqtdqS0oiIiKgesOiqHJVKhXbt2iEmJsa0zGg0IiYmBp06dapwm06dOpmtDwB//PHHLdcnIiKihsvirpzo6GiMHDkS7du3R8eOHbFgwQLk5eVh9OjRAIARI0bAz88P8+bNAwC88MILiIyMxPvvv49+/fph9erV2LdvH5YuXVq974SIiIjqPIuDydChQ5GRkYFp06YhNTUVbdu2xebNm00DXJOTk6FQXG+I6dy5M7799lu88cYbeO2119C0aVNs2LABLVvW/KVPREREVLdYPI+JHDiPCRERUd1Tlc9v3iuHiIiIrAaDCREREVkNBhMiIiKyGgwmREREZDUYTIiIiMhqMJgQERGR1WAwISIiIqvBYEJERERWg8GEiIiIrIbFU9LLoWxy2pycHJkrISIiosoq+9y2ZJL5OhFMcnNzAQD+/v4yV0JERESWys3NhZOTU6XWrRP3yjEajbhw4QK0Wi0kSaryfnJycuDv74+UlBTec6cW8bzLg+ddHjzvtY/nXB6VOe9CCOTm5sLX19fsBr+3UydaTBQKBRo1alRt+9PpdPzhlQHPuzx43uXB8177eM7lcafzXtmWkjIc/EpERERWg8GEiIiIrEaDCiZqtRrTp0+HWq2Wu5QGheddHjzv8uB5r3085/KoqfNeJwa/EhERUcPQoFpMiIiIyLoxmBAREZHVYDAhIiIiq8FgQkRERFaj3gWTxYsXIzAwEBqNBhEREdizZ89t11+7di3CwsKg0WjQqlUrbNq0qZYqrV8sOe/Lli1Dt27d4OLiAhcXF0RFRd3x+0QVs/Tnvczq1ashSRIGDhxYswXWQ5ae86ysLEyYMAE+Pj5Qq9Vo1qwZ/85UgaXnfcGCBQgNDYWdnR38/f0xadIkFBYW1lK19cNff/2F/v37w9fXF5IkYcOGDXfcZtu2bbj33nuhVqvRpEkTfPnll5YfWNQjq1evFiqVSixfvlwcO3ZMPPXUU8LZ2VmkpaVVuP7OnTuFUqkU77zzjjh+/Lh44403hK2trThy5EgtV163WXrehw0bJhYvXiwOHjwo4uLixKhRo4STk5M4d+5cLVdet1l63sskJSUJPz8/0a1bN/Hwww/XTrH1hKXnvKioSLRv3148+OCDYseOHSIpKUls27ZNHDp0qJYrr9ssPe+rVq0SarVarFq1SiQlJYnffvtN+Pj4iEmTJtVy5XXbpk2bxOuvvy7Wr18vAIgff/zxtuufPn1a2Nvbi+joaHH8+HGxcOFCoVQqxebNmy06br0KJh07dhQTJkwwPTcYDMLX11fMmzevwvWHDBki+vXrZ7YsIiJCPP300zVaZ31j6Xm/WUlJidBqtWLlypU1VWK9VJXzXlJSIjp37iw+//xzMXLkSAYTC1l6zj/99FMRHBws9Hp9bZVYL1l63idMmCDuv/9+s2XR0dGiS5cuNVpnfVaZYPLKK6+I8PBws2VDhw4Vffr0sehY9aYrR6/XY//+/YiKijItUygUiIqKQmxsbIXbxMbGmq0PAH369Lnl+lReVc77zfLz81FcXAxXV9eaKrPeqep5nzVrFjw9PTFmzJjaKLNeqco5/9///odOnTphwoQJ8PLyQsuWLTF37lwYDIbaKrvOq8p579y5M/bv32/q7jl9+jQ2bdqEBx98sFZqbqiq6zO1TtzErzIyMzNhMBjg5eVlttzLywsnTpyocJvU1NQK109NTa2xOuubqpz3m7366qvw9fUt9wNNt1aV875jxw588cUXOHToUC1UWP9U5ZyfPn0aW7ZswRNPPIFNmzYhISEB48ePR3FxMaZPn14bZdd5VTnvw4YNQ2ZmJrp27QohBEpKSvDMM8/gtddeq42SG6xbfabm5OSgoKAAdnZ2ldpPvWkxobpp/vz5WL16NX788UdoNBq5y6m3cnNzMXz4cCxbtgzu7u5yl9NgGI1GeHp6YunSpWjXrh2GDh2K119/HUuWLJG7tHpt27ZtmDt3Lj755BMcOHAA69evx8aNGzF79my5S6NKqDctJu7u7lAqlUhLSzNbnpaWBm9v7wq38fb2tmh9Kq8q573Me++9h/nz5+PPP/9E69ata7LMesfS856YmIgzZ86gf//+pmVGoxEAYGNjg5MnTyIkJKRmi67jqvKz7uPjA1tbWyiVStOy5s2bIzU1FXq9HiqVqkZrrg+qct7ffPNNDB8+HGPHjgUAtGrVCnl5eRg3bhxef/11KBT8P3lNuNVnqk6nq3RrCVCPWkxUKhXatWuHmJgY0zKj0YiYmBh06tSpwm06depktj4A/PHHH7dcn8qrynkHgHfeeQezZ8/G5s2b0b59+9ootV6x9LyHhYXhyJEjOHTokOkxYMAA9OzZE4cOHYK/v39tll8nVeVnvUuXLkhISDCFQACIj4+Hj48PQ0klVeW85+fnlwsfZeFQ8PZwNabaPlMtG5dr3VavXi3UarX48ssvxfHjx8W4ceOEs7OzSE1NFUIIMXz4cDFlyhTT+jt37hQ2NjbivffeE3FxcWL69Om8XLgKLD3v8+fPFyqVSqxbt05cvHjR9MjNzZXrLdRJlp73m/GqHMtZes6Tk5OFVqsVzz33nDh58qT45ZdfhKenp3jrrbfkegt1kqXnffr06UKr1YrvvvtOnD59Wvz+++8iJCREDBkyRK63UCfl5uaKgwcPioMHDwoA4oMPPhAHDx4UZ8+eFUIIMWXKFDF8+HDT+mWXC7/88ssiLi5OLF68mJcLCyHEwoULRePGjYVKpRIdO3YU//zzj+m1yMhIMXLkSLP1v//+e9GsWTOhUqlEeHi42LhxYy1XXD9Yct4DAgIEgHKP6dOn137hdZylP+83YjCpGkvP+a5du0RERIRQq9UiODhYzJkzR5SUlNRy1XWfJee9uLhYzJgxQ4SEhAiNRiP8/f3F+PHjxZUrV2q/8Dps69atFf6tLjvXI0eOFJGRkeW2adu2rVCpVCI4OFisWLHC4uNKQrBdi4iIiKxDvRljQkRERHUfgwkRERFZDQYTIiIishoMJkRERGQ1GEyIiIjIajCYEBERkdVgMCEiIiKrwWBCREREVoPBhIgaDEmSsGHDBrnLIKLbYDAhIiIiq8FgQkQAgB49emDixIl48cUX4eLiAi8vLyxbtgx5eXkYPXo0tFotmjRpgl9//dW0zdGjR9G3b184OjrCy8sLw4cPR2Zmpun1zZs3o2vXrnB2doabmxseeughJCYmml4/c+YMJEnC+vXr0bNnT9jb26NNmzaIjY29Y71CCHh4eGDdunWmZW3btoWPj4/p+Y4dO6BWq5Gfn4/AwEAAwKBBgyBJkuk5EVkXBhMiMlm5ciXc3d2xZ88eTJw4Ec8++yweffRRdO7cGQcOHEDv3r0xfPhw5OfnIysrC/fffz/uuece7Nu3D5s3b0ZaWhqGDBli2l9eXh6io6Oxb98+xMTEQKFQYNCgQTAajWbHff311zF58mQcOnQIzZo1w+OPP46SkpLb1ipJErp3745t27YBAK5cuYK4uDgUFBTgxIkTAIDt27ejQ4cOsLe3x969ewEAK1aswMWLF03PicjK3OXNB4monoiMjBRdu3Y1PS8pKREODg5mtzW/ePGiACBiY2PF7NmzRe/evc32kZKSIgCIkydPVniMjIwMAUAcOXJECCFEUlKSACA+//xz0zrHjh0TAERcXNwda/74449FeHi4EEKIDRs2iIiICPHwww+LTz/9VAghRFRUlHjttddM6wMQP/744x33S0TyYYsJEZm0bt3a9LVSqYSbmxtatWplWubl5QUASE9Px+HDh7F161Y4OjqaHmFhYQBg6q45deoUHn/8cQQHB0On05m6T5KTk2953LKumPT09DvWGxkZiePHjyMjIwPbt29Hjx490KNHD2zbtg3FxcXYtWsXevToYfmJICLZ2MhdABFZD1tbW7PnkiSZLZMkCQBgNBpx9epV9O/fH2+//Xa5/ZSFi/79+yMgIADLli2Dr68vjEYjWrZsCb1ef8vj3niMO2nVqhVcXV2xfft2bN++HXPmzIG3tzfefvtt7N27F8XFxejcuXMl3z0RWQMGEyKqknvvvRc//PADAgMDYWNT/k/JpUuXcPLkSSxbtgzdunUDUDoYtTpJkoRu3brhp59+wrFjx9C1a1fY29ujqKgIn332Gdq3bw8HBwfT+ra2tjAYDNVaAxFVL3blEFGVTJgwAZcvX8bjjz+OvXv3IjExEb/99htGjx4Ng8EAFxcXuLm5YenSpUhISMCWLVsQHR1d7XX06NED3333Hdq2bQtHR0coFAp0794dq1atQmRkpNm6gYGBiImJQWpqKq5cuVLttRDR3WMwIaIq8fX1xc6dO2EwGNC7d2+0atUKL774IpydnaFQKKBQKLB69Wrs378fLVu2xKRJk/Duu+9Wex2RkZEwGAxmY0l69OhRbhkAvP/++/jjjz/g7++Pe+65p9prIaK7JwkhhNxFEBEREQFsMSEiIiIrwmBCRFarbFbZih5z586VuzwiqgHsyiEiq3X+/HkUFBRU+JqrqytcXV1ruSIiqmkMJkRERGQ12JVDREREVoPBhIiIiKwGgwkRERFZDQYTIiIishoMJkRERGQ1GEyIiIjIajCYEBERkdVgMCEiIiKr8f+5+gm3O78pMAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " cr_gp_df.plot(x='mean_wt', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", + " esc_gp_df.plot(x='mean_wt', y='fishing_mortality', title='Const. Escapement GP policy'),\n", + "\n", + ") " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "77be8a03-ae6c-469e-a537-5ffc9199cf5c", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-25 17:04:35,521\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-04-25 17:04:42,706\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-04-25 17:04:49,645\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-04-25 17:04:56,672\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + } + ], + "source": [ + "esc_rews = eval_pol(\n", + " policy=ConstEsc(env=AsmEnv(config=CONFIG), observed_var='mean_wt', **esc_gp_args), \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=2, batch_size=150\n", + ")\n", + "\n", + "cr_rews = eval_pol(\n", + " policy=CautionaryRule(env=AsmEnv(config=CONFIG), observed_var='mean_wt', **cr_gp_args), \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=2, batch_size=150\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "6fee7a5a-ad08-418b-b412-463f6dd9afce", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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atfjGHx8iFAqRn5/vVmBJkiQpwVgASpICsWfPHsaPHw9Al8Gnk5Tkl6QgtTupL/2/cQ0A77zzDq+//nqwgSRJkiSVG3/akiQF4uOPPyY/Px+AbqefEXAaAZz7k5/GtgLfcccdbNmyJeBEkiRJksqDBaAkKRBjxowBICUtjQ6nnBpwGgGk16jBpfeWTQXesGED9913X8CJJEmSJJUHC0BJUqWLRCKxArDDKf1JzcgIOJGiug05IzaQ5bnnnmPGjBkBJ5IkSZJ0vCwAJUmVbvbs2axevRooK5xUtVx4x12kpKURiUS4++67HQgiSZIkxTkLQElSpRs7diwAoVCILoNPDziNvqxOk6YMvv47QNlZjSNHjgw4kSRJkqTjYQEoSap0b7/9NgAt8rqTXa9+wGl0MEO+cyPZDRoA8Mtf/pLCwsKAE0mSJEk6VhaAkqRKtXnzZqZOnQpA54GnBZxGh5KWlcW5P/kpAMuWLeOf//xnwIkkSZIkHSsLQElSpXrvvfdiZ8p1GjAw4DQ6nBMvuoQmHTsB8Ne//pWdO3cGnEiSJEnSsbAAlCRVqvHjxwOQWbs2LbrlBZxGh5OUlMSwm38CwIYNG3jqqacCTiRJkiTpWFgASpIqTSQSYcKECQB0PHUASeFwwIn0VboNOSNW1D7yyCPs2LEj4ESSJEmSjpYFoCSp0syZM4f169cDbv+NF6FQiGE/ugUoO7/x8ccfDziRJEmSpKNlAShJqjTvvPNO7HbHU/sHmERHo9OAgbTufQIAjz32GPn5+QEnkiRJknQ0LAAlSZUmWgA27dSZWg0aBpxGRyoUCnH2D38EwLZt23jmmWeCDSRJkiTpqFgASpIqRX5+PpMnTwag04BBwYbRUetwyqk069IVgEcffZTCwsKAE0mSJEk6UhaAkqRK8cEHH1BcXAx4/l88CoVCnPHd7wOwdu1aXn755YATSZIkSTpSFoCSpEoR3f6bllWDVj17BZxGx6L7WWdTv2UuUDYRuKSkJNhAkiRJko6IBaAkqcJFIpFYAdjh5FNITk0NOJGORVI4zOAbvgvA4sWLGT16dMCJJEmSJB0JC0BJUoVbtmwZK1asAKCD03/j2okXXkTNevUBePzxxwNOI0mSJOlIWABKkircBx98ELvd4ZRTA0yi45WSls4pX78KgIkTJzJr1qyAE0mSJEn6KhaAkqQKFy0AazdqHDtDTvHr1CuvIpySAsATTzwRcBpJkiRJX8UCUJJUoUpLS/nwww8BaH/yKYRCoYAT6Xhl129Az2HnAvDqq6+ycePGgBNJkiRJOhwLQElShZo3b16sIGrf7+SA06i8DPrWtwEoLCzk3//+d8BpJEmSJB2OBaAkqULte/5f+36nBJhE5alFtzxa9eoNwNNPP01xcXHAiSRJkiQdigWgJKlCRQvABq3bULtRo4DTqDwN+MY1AKxZs4bx48cHnEaSJEnSoVgASpIqTHFxMR9//DEA7fv2CziNylvemWeRlZMD4DZgSZIkqQqzAJQkVZjp06eTn58PlA0AUWJJSUvnxAsvBuDtt9/miy++CDiRJEmSpIOxAJQkVZj3338fgFAoRLuTXAGYiPpddgVQNu35+eefDziNJEmSpIOxAJQkVZjo+X9NO3WObRVVYmnUth1t+pwIwLPPPktJSUnAiSRJkiR9mQWgJKlCFBQUMGXKFMDtv4nu5Mu/DsDq1auZMGFCwGkkSZIkfZkFoCSpQnz66acUFhYC0L7fyQGnUUXqfvYwMrKzAXjmmWcCTiNJkiTpyywAJUkV4qOPPgIgKRymzQknBpxGFSk1/X/DQMaOHcvatWsDTiRJkiRpXxaAkqQKMXHiRACad+1GWlZWwGlU0frt3QZcUlLCf//734DTSJIkSdqXBaAkqdwVFhby2WefAcQGRCixNWnfgWZdugLwn//8h0gkEnAiSZIkSVEWgJKkcjdt2rTY+X9tT+wbcBpVlug24Hnz5jF79uyA00iSJEmKsgCUJJW76PbfUChE694nBJxGlaX3eeeTFA4D8NJLLwWcRpIkSVJUctABVDnCe38gS5TX0bGL/h35dxWf4uXvbdKkSQA06diJrNq1gw0TgFBS6H//XxpwmEqUXa8+nQYMZM6Ed3j11Ve57777SE6Ov2814uV9Vt359Sy++fcWH3yfxTf/3iTtKxTxkB5JUjkqLi4mJyeH/Px8Bl97HVfc/+ugI6kSfTr8DR6/8TsAjBo1iqFDhwacSJIkSVL8/Vpex2TLli0Vdu3s7GzC4TAlJSVs3769wl5H5SMcDpOdnc327dspKSkJOo6OQLy9x6ZNm0Z+fj4Aub1PiJ0FWJ2EkkKkpqSyp2gPkdLq9Xu2DgMGkVEzm4Id2/nHP/5B377xcQZkvL3P5NezeOT7LP74Pos/ifI+y8nJCTqClHAsAKuJyvqC7TcG8aOkpMS/rzgUD39nH374Yex26xP6VM9psHu3/UZKI9Xu809JS6PH0GFMfOlFRo0axZYtW8jOzg461lGJh/eZ/sevZ/HJv7P44vssPvl3JmlfDgGRJJWr6ACQBq3bkF2vfsBpFIToNODdu3fz5ptvBpxGkiRJkgWgJKnclJaWxgaAtO1zYsBpFJRWvU+gTrNmALz66qsBp5EkSZJkAShJKjfz589n69atALSxAKy2kpKS6H3uBQB89NFHrFu3LuBEkiRJUvVmAShJKjfR7b8AbU48KcAkClqvc88DylaFDh8+POA0kiRJUvVmAShJKjfRArBO02bUadI04DQKUpMOHWnYpg0Ar732WsBpJEmSpOrNAlCSVC4ikUisAHT7r0KhEL3OOR+ATz75hNWrVwecSJIkSaq+LAAlSeViyZIlrF+/HrAAVJle55wbu/3GG28EmESSJEmq3iwAJUnlYt/z/9qe1DfAJKoqGrZpS9NOnQG3AUuSJElBsgCUJJWLSZMmAVCzXn3qt8wNNoyqjF7nlA0DmT59OkuWLAk4jSRJklQ9WQBKksrFJ598AkDr3r0JhUIBp1FV4TZgSZIkKXgWgJKk47ZhwwaWLl0KQKteJwScRlVJ3eYtaNm9J+A2YEmSJCkoFoCSpOM2ZcqU2O1WvXoHmERVUXQV4Lx581i0aFHAaSRJkqTqxwJQknTcott/U9LSaN6la8BpVNV0P+vs2O0RI0YEmESSJEmqniwAJUnHLVoAtsjrTnJqasBpVNXUadqMFt3yAAtASZIkKQgWgJKk47J7925mzJgBQKuebv/VwXU/aygAM2bMYMWKFQGnkSRJkqoXC0BJ0nGZOXMme/bsAaBVbweA6OC6nz00dnvkyJEBJpEkSZKqHwtASdJxiW7/BWjVs1eASVSVNchtRZMOHQEYPnx4wGkkSZKk6sUCUJJ0XKIFYIPWbahRp07AaVSVRbcBT5kyhbVr1wacRpIkSao+LAAlSccsEokwZcoUAFr38vw/HZ7bgCVJkqRgWABKko7ZkiVL2LhxI+D5f/pqjdu1p35uK8BpwJIkSVJlsgCUJB2z6Oo/cAWgvlooFIptA/74449j5bEkSZKkimUBKEk6ZtHz/7JycmjQuk3AaRQPeuzdBlxaWsro0aMDTiNJkiRVDxaAkqRjFi0AW/XsTSgUCjiN4kHzrt2o07QZ4DZgSZIkqbJYAEqSjsnWrVtZsGABAK3c/qsjFAqFyDvzLAA++OADtm3bFnAiSZIkKfFZAEqSjsl+5/85AERHIboNuKioiPHjxwecRpIkSUp8FoCSpGMSLQDDKSk075YXcBrFk9wevahRpy4Ao0aNCjiNJEmSlPgsACVJxyRaADbr3JXU9PSA0yieJIXDdB18OgDjx4+nsLAw4ESSJElSYrMAlCQdtZKSEqZNmwZAbs+eAadRPOo25EwA8vPz+eijjwJOI0mSJCU2C0BJ0lFbsGABO3fuBCC3hwWgjl6HU/uTmpEBwJgxYwJOI0mSJCU2C0BJ0lH77LPPYrdzu/cILojiVmp6Oh1PHQCUFYClpaUBJ5IkSZISlwWgJOmoTZ06FYAadepSp1nzgNMoXnUbcgYAa9asYcaMGQGnkSRJkhKXBaAk6ahFC8CW3XsQCoUCTqN41eW00wkllX0rMnr06IDTSJIkSYnLAlCSdFTy8/OZP38+ALk9egQbRnGtRp06tO7dB/AcQEmSJKkiWQBKko7KjBkzYue1tezuABAdn+g24Hnz5rFs2bJgw0iSJEkJygJQknRU9h0A0iIvL8AkSgTdhpwZu+0qQEmSJKliWABKko5K9Py/hm3akJldK+A0inf1W7akcbv2gOcASpIkSRXFAlCSdFSiKwDd/qvyEt0GPGnSJDZt2hRwGkmSJCnxWABKko7YF198wdq1a4GyCcBSeeh2xlkAlJaWMm7cuIDTSJIkSYnHAlCSdMT2Pf8v1wJQ5aR5127UatgQ8BxASZIkqSJYAEqSjlj0/L+UtDSadOgYcBoliqSkJLqeXrYNeMKECRQUFAScSJIkSUosFoCSpCMWXQHYvGs3wikpAadRIum2twDctWsXH3zwQcBpJEmSpMRiAShJOiLFxcXMmDED8Pw/lb92ffuRllUDcBqwJEmSVN4sACVJR2T+/Pns2rULcAKwyl9KWhqdBw4CYOzYsZSUlAQbSJIkSUogFoCSpCMSPf8PILdHj+CCKGF1G1K2DXjDhg37/fsmSZIk6fhYAEqSjkj0/L+a9eqT06RpwGmUiDoPPI2kcBhwG7AkSZJUniwAJUlHJLoiq2X3HoRCoYDTKBFl1qpF2xNPAsq2AUuSJEkqHxaAkqSvtGPHDhYsWABArgNAVIG67p0GvHDhQhYvXhxwGkmSJCkxWABKkr7S9OnTiUQiALT0/D9VoG6nD4nddhWgJEmSVD4sACVJXyl6/l8oFKJFt+4Bp1Eiq9u8BU06dAQ8B1CSJEkqLxaAkqSvFD3/r2GbtmTUrBlwGiW66DTgTz75hE2bNgWcRpIkSYp/FoCSpMOKRCKxFYBu/1VliJ4DWFpayrhx4wJOI0mSJMU/C0BJ0mGtXr2a9evXA5DbvWfAaVQdNO/ajVoNGwIwZsyYgNNIkiRJ8c8CUJJ0WNHVfwAtnQCsSpCUlETXwWXDQCZMmMDu3bsDTiRJkiTFNwtASdJhRQvA1IwMGrfvEHAaVRfRcwB37drFBx98EHAaSZIkKb5ZAEqSDitaADbv2o1wcnLAaVRdtOvbj9TMTMBtwJIkSdLxsgCUJB1SUVERM2fOBNz+q8qVkpZOp/4DARg7diylpaUBJ5IkSZLilwWgJOmQ5s6dGzt/zQJQlS26DXjdunVMnz492DCSJElSHLMAlCQd0tSpU2O3nQCsytZl0GBCSWXfqrgNWJIkSTp2FoCSpEOKnv+X3aABtRs3DjiNqpusnBxa9+4DWABKkiRJx8MCUJJ0SNEVgLndexIKhQJOo+ooug143rx5LFu2LNgwkiRJUpyyAJQkHdS2bdv4/PPPAc//U3C6nX5G7LarACVJkqRjYwEoSTqoadOmxW5bACoo9XNzadS2HVA2DViSJEnS0bMAlCQdVPT8v1AoRItueQGnUXXWde8qwIkTJ7Jly5aA00iSJEnxxwJQknRQ0fP/GrVrT3qNGgGnUXUWPQewpKSE8ePHB5xGkiRJij8WgJKkA0Qikf8NAOnRM+A0qu5adu9BzXr1ARg9enTAaSRJkqT4YwEoSTrAihUr2LhxI+D5fwpeUlISXQefDsA777xDYWFhwIkkSZKk+GIBKEk6QHT1H7gCUFVD9BzA/Px8Pvroo4DTSJIkSfHFAlCSdIDoAJC0rKzYBFYpSB1OOZWU9HQAxowZE3AaSZIkKb5YAEqSDhBdAdi8azeSwuGA00iQmp5Ox1MHADB27FgikUjAiSRJkqT4YQEoSdrPnj17mDlzJgC53d3+q6ojOg34iy++iP07KkmSJOmrWQBKkvYzd+7c2JCFlj16BBtG2keX0wYTCoUAtwFLkiRJR8MCUJK0n+j5f+AKQFUtNevWo1Wv3oAFoCRJknQ0LAAlSfuJnv9Xu1FjajVsGHAaaX/RacCzZ89m5cqVAaeRJEmS4oMFoCRpP9EVgC279wg2iHQQ0XMAoWwYiCRJkqSvZgEoSYrZunUrixcvBiDX8/9UBTVs3YYGrVoDbgOWJEmSjpQFoCQpJrr9F6Cl5/+pioquAvzoo4/Yvn17wGkkSZKkqs8CUJIUEy0Ak8JhmnftFnAa6eCi5wAWFxczfvz4gNNIkiRJVZ8FoCQpJnr+X+P2HUjLzAw4jXRwrXr2IiunDuA2YEmSJOlIWABKkgCIRCKxFYAOAFFVlhQO03Xw6QC8/fbbFBUVBZxIkiRJqtosACVJACxbtozNmzcDFoCq+qLnAG7fvp2JEycGnEaSJEmq2iwAJUnA/gNAch0Aoiquwyn9SUlLA2D06NEBp5EkSZKqNgtASRLwv/P/0rJq0LBNm4DTSIeXlplJ+5NPBcoKwEgkEnAiSZIkqeqyAJQkAf9bAdgyL4+kcDjgNNJX637W2QCsXr2aadOmBZxGkiRJqrosACVJFBYWMmvWLABauv1XcaLb6WfEyuoRI0YEnEaSJEmquiwAJUnMnj2bPXv2AA4AUfzIysmh7Ul9gbIC0G3AkiRJ0sFZAEqSYuf/AeT26BFcEOkodT9rKABLly5l7ty5AaeRJEmSqiYLQElS7Py/nCZNya7fIOA00pHrfuZZhEIhwG3AkiRJ0qFYAEqSYisA3f6reJNdvwGtep8AWABKkiRJh2IBKEnV3KZNm1i2bBkAuRaAikPRbcDz589n0aJFAaeRJEmSqh4LQEmq5qLbfwFa9nACsOJP97POjt0ePnx4gEkkSZKkqskCUJKquWgBmBQO07xL14DTSEevTpOmtMjrDrgNWJIkSToYC0BJquai5/816dCR1IyMgNNIx6b7mWWrAGfOnMny5csDTiNJkiRVLRaAklSNRSIRpk2bBrj9V/Gt+9lDY7dHjRoVYBJJkiSp6rEAlKRqbMmSJWzduhVwAIjiW4PcVjTp0BHwHEBJkiTpyywAJakai27/BWhpAag4F50GPGXKFNauXRtwGkmSJKnqsACUpGosWgBm1MymQes2AaeRjs++24BHjhwZYBJJkiSparEAlKRqLDoBuEVeHklJfklQfGvcrj0NWrUG3AYsSZIk7cuf9iSpmtq9ezdz5swB3P6rxBAKheixdxXgxx9/7DZgSZIkaS8LQEmqpmbNmkVRUREALbs7AViJoec55wFlE65dBShJkiSVsQCUpGpq3wEguT16BBdEKkdNOnSkYZu2ALz++uvBhpEkSZKqCAtASaqmouf/1W3enJp16wWcRiofoVCIXntXAX7yySesXr064ESSJElS8CwAJamaihaAbv9Voul1zrmx22+88UaASSRJkqSqwQJQkqqhjRs3snz5csABIEo8Ddu0pWmnzgC89tprAaeRJEmSgmcBKEnVUHT1H0CuBaASUHQb8PTp01m6dGnAaSRJkqRgWQBKUjUUHQASTkmhWZcuAaeRyt++24AdBiJJkqTqzgJQkqqh6ArAph07kZKWHnAaqfzVbd4itr3dAlCSJEnVnQWgJFUzpaWl+wwA6RFsGKkCRbcBz507lwULFgScRpIkSQqOBaAkVTOLFy9m+/btgBOAldh6DD0ndttVgJIkSarOLAAlqZqJnv8HkNujR3BBpAqW07gxbfqcCJRNA45EIgEnkiRJkoJhAShJ1Ux0+29mrVrUz20VcBqpYkW3AS9evJgZM2YEnEaSJEkKhgWgJFUz0RWALfJ6EAqFAk4jVayew84lKTkZgJdeeingNJIkSVIwLAAlqRopKChg7ty5AOQ6AETVQI06deg88DSgbBtwUVFRwIkkSZKkymcBKEnVyMyZMykuLgagpef/qZro87ULAdi4cSMTJkwIOI0kSZJU+SwAJaka2XcASMu8HsEFkSpR18Gnk1EzG3AbsCRJkqonC0BJqkaiBWD9lrnUqFMn4DRS5UhJS6fnsHMAGDNmDNu3bw84kSRJklS5LAAlqRqJFoAtPf9P1UyfCy8GoLCwkDfffDPgNJIkSVLlsgCUpGpi7dq1rF69GoDcHj0DTiNVrta9T6Bu8+YAvPzyywGnkSRJkiqXBaAkVRP7nf9nAahqJhQKccIFZcNAPv74Y1auXBlwIkmSJKnyWABKUjURLQCTU9No2rFTwGmkytfnaxfFbrsKUJIkSdWJBaAkVRNTp04FoFmXLiSnpgacRqp8DXJb0bJ72erXl19+mUgkEnAiSZIkqXJYAEpSNVBSUsK0adMAyO3u9l9VX32+VrYNeNGiRbFSXJIkSUp0yUEHkCRVvPnz57Nr1y4AcntaAFY1hYWFbN+xnd27d1O4u5Di4mIAQkkhUlNTSU9LJzMrk5o1apKU5O/ujkfvc8/ntV//ipKiPTz33HP07t076EiSJElShbMAlKRqYL8BIN17BBdElEZK2bhhI+vWrWPdunVs3ryZ3bt3H9FzQ6EQNbNrUq9uPRo2bEiDhg2olV2rghMnlqycHLqfdTZTR7zJq6++yn333UeNGjWCjiVJkiRVKAtASaoGogVgzXr1qdO0WcBpqqd169axdOlSVqxYccSF35dFIhG2b9vO9m3bWbJkCQA1a9akefPm5ObmUq9evfKMnLD6XXY5U0e8yc6dO3njjTe46qqrgo4kSZIkVSgLQEmqBqIFYMvuPQiFQgGnqT6Ki4tZtGgR8+fPZ9u2bQfcXzsrk3o1a1IrM5PszAwyU1NJTUkhee8230gkwp7iYnYXFbGzsJDtu3axZecuNm7fwe6iIgB27NjB3LlzmTt3LrVzatOubTtat25NWlpapX6u8aRd35Op27w5m1au5LnnnrMAlCRJUsKzAJSkBLd9+3YWLlwIQG4Pz/+rDMXFxSxYsIDp06fvt9ovKSmJJjm1aVmvHo1yapOW/NVfhlOTk6mRnk69mjVjH4sA+bt3s2bLFlZt2sy6bduIRGDrlq1MmTKFqVOn0rZdW7p07uL21oNISkqi7yWXMfLPf2TKlCksWLCAvn37Bh1LkiRJqjAWgJKU4KZNm0YkEgEgt0ePYMMkuEgkwpIlS5g6dSoFBQWxj2dnZNCuSSNaN2hASjh83K8TAmqmp1OzcWPaN27M7qIilm3YwOK169m2axclJSUsmL+AhQsW0qpVK/Ly8sjOzj7u100kJ150KaP+8mcipaU899xzFoCSJElKaNWqANy2bRuvvPIKn3zyCZs2bSItLY02bdowbNiw4/rGv7i4mBEjRvDee+/xxRdfANC0aVMGDhzIOeecQ/IhVngsXryYyZMnM2fOHFasWEF+fj7p6ek0a9aMk046iWHDhpGZmXnMuSQJ/rf9NxQK0bxrXsBpEtfmzZuZPHkyGzZsiH0sJyuLvJbNaVKnDhW58To9JYWOTZrQoUkTNu3YwdxVq1m1aXOskFy6dCntO7Sne1530tPTKzBJ/Mhp3JjOAwcxZ8I7vPTSS/zhD3/wa64kSZISVrUpAFesWMEdd9wRO4MpIyODnTt3Mn36dKZPn855553HDTfccNTXLSgo4K677optr0tNTQVg0aJFLFq0iI8++oj77rvvgB+43n33Xf70pz/F/jkUCpGZmcmuXbtYsGABCxYsYPTo0dxzzz20aNHiWD9tSYoVgI3atSdjn22kKh+lkVJmz5rNzJkzKS0tBSArLY0T2ramaU5OpWYJAfVq1mRAp45sKyhg3qrVLF2/nkgkwoL5C1i8eDF53fLo3LkzSXvPGazO+l12BXMmvMOmTZsYPnw4l19+edCRJEmSpApRLQrAoqIifvWrX7Ft2zZatmzJT37yE1q1akVhYSFvvPEGzz33HMOHD6dVq1YMGTLkqK796KOPsnDhQrKysrjppptiKwknTZrEX//6V+bPn89jjz3Gj3/84/2eV1JSQmpqKgMGDGDAgAF06tSJtLQ0du/ezccff8xTTz3Fhg0buP/++3nkkUc8zF3SMYlEIkydOhUoGwCi8rUjfwcfvP8BGzduBCApFKJL86Z0btaM1NQUSkpKYe/268pWKyODvu3a0qlpU2YsX86qTZspLipm6tSpLFmyhJP6nkTDBg0DyVZVdBk0mJr16rNj4waeeuopC0BJkiQlrGrx6/+xY8eydu1a0tLSuPvuu2nVqhUAaWlpXHbZZQwdOhSAZ599luLi4iO+7tKlS3n//fcB+OEPf0i/fv0IhUKEQiH69evHD37wA6Bstd/y5cv3e26HDh144oknuOmmm+jRo0es4EtPT2fw4MH87Gc/A2DdunV89NFHx/cHIKnaWrFiRayccgBI+Vq1ahUjR4yM/fnmZGVxds/udGvRgnA5nPNXXmplZjCgU0fOyOtKTlYWAFu3bmXsmLF8/PHH7CnaE3DC4IRTUjjxoosBGDdu3AFfqyVJkqREUS0KwHfffReAAQMGUL9+/QPuv/jiiwmFQmzevJlZs2Yd8XXfe+89IpEIjRs3pl+/fgfcf/LJJ9O4cWMikQjvvffefvc1a9aMnMNsDcvLy6NBgwZA2VmBknQsott/wQKwvEQiEaZPn84777zDnj1l5VmX5s04q0cetavwGXL1s7M5u2cevVu3Ijlc9uV/0aJFvPnmm6xZsybgdMHpd2nZqr9IJMITTzwRcBpJkiSpYiR8AVhQUMDnn38OQK9evQ76mPr169OsWTMAZsyYccTXnjlzJgA9e/YkFDrwePdQKETPnj33e+zRiE5sLCkpOernShL8rwBMy8qiUdt2AaeJf8Ulxbz73rux/6anhMMM7NyJ7i1bkHSQrwNVTYgQHZo05tzevWhWtw4Au3buYty4cUyZMoXikiNfBZ8oGrRqTft+JwPwxBNPUFhYGHAiSZIkqfwlfAG4atUqInvPX2rZsuUhHxe9b+XKlUd03UgkwqpVq77yutEBHkd63agdO3bEtiI5BETSsYoWgC265ZFUhbalxqPCwkLGvTWOlSvK/nuek5XF0J49aFqncgd9lIfM1FT6d+pIv/btSNn778W8efMYMWIEmzdvDjhd5et/9TcBWL9+Pf/9738DTiNJkiSVv4QfArLvDzJ16tQ55OOi923ZsuWIrltQUMDu3buP+LoFBQUUFBSQkZFxRNd/8cUXKSoqIiMjg1NOOeUrH//ss8/y/PPPH/L+r3/961x55ZVH9NpHKzpJMikp6bDbmlU1RFer1qpVK1aOq2o71vdYYWFh7FiDNr37OEzoOGzfsYMxY8bEJsk3q1uH/p06xbbSHkq4ik/abdu4EY3q5DBx/gLWbt3G9m3bGTV6FKecfAodOnYgRNVf1Vgeeg87l1cbN2HLmi947LHHKuzrpcqXX8/ij98zxh/fZ/HH95mkQ0n4AjBa0gGH/eE3el9BQcERXXffxx3JdaPPOZICcMqUKYwcORKAK6+8klq1an3lc3bu3Mn69esPef+uXbsq/FD6UChUpQ6+1+ElVfFiQgc62vfYrFmzYmfUte7V66BHFeirbd22lRHDR7Br1y4A2jVuxInt2pKUdAR/nnHwR14jPY0h3fOYv3o1UxcvpbSklA8++IA1a9bQv39/UlJSgo5Y4ZJTUhjwjW/yxu8eZOLEicycOTN2hIeqPr+exR+/Z4w/vs/ij+8zSV+W8AVgvFmyZAl//OMfKS0tpW/fvpx//vlH9LysrKzY0JCDyczMrLCzBJOSkgiFQkQiEUpLSyvkNVR+QqEQSUlJlJaW+pvcOHGs77GJEyfGbuf26OXf9zHYunUrI0eOjJV/3XNb0q1li7Je76v+OENH8JgqIgR0atqU+tnZvD9nHjsLC1m0aBEbN25kyJAh1WIFQf+vX8WIP/+RkqIiHnnkER5//PGgI+kr+PUs/vg9Y/zxfRZ/EuV9Znkplb+ELwDT09NjtwsLC8k8xITG6KHfR7pFd9/HHe7A8H3v+6prr1y5knvuuYddu3bRrVs3br311iNesXP11Vdz9dVXH/L+jRs3HvH25qOVk5NDOBymtLS0wl5D5SccDpOTk8O2bdscMBMnjvU99sEHHwBQp2kz0mvVcrjBUdq2bRtj3xrL7oKyleS9WufSsUkTSo/kfRMKEQ4nUVJaCnH0A1NOZiZDe3Zn4sLPWb15C1u3buX111+nf//+NG/ePOh4Fapmvfr0Puc8Pnn9VV544QVuv/32alF8xjO/nsUfv2eMP77P4k+ivM/q1asXdAQp4ST8Wu59z+c73MHm0fuO9Jv9jIyMWKF3JNfd9/EH88UXX3DXXXexbds2OnTowJ133klqauoRZZGkg5k6dSoALbv3CDZIHNq+fft+5V/v1q3o2KRJwKkqR2pyMgM6d6Jnq7IBV8XFxUyYMOGYptnHm9O+9W2g7MiOF154IeA0kiRJUvlJ+AKwWbNmsVV0K1asOOTjovcd6QqHUChEs2bNyuW6a9eu5c4772Tz5s20bt2ae+6554hXIkrSwWzcuJFly5YBkNvDs8yOxq6CXbz99tv7lX8dmjQOOFXlim4JPq1rZ1KTyzYLTJ8+nffee4+i4uJgw1Wg1r1PoHnXbgD885//jOutU5IkSdK+Er4AzMjIoF27dsD/VsN82caNG1m5ciUA3bt3P+Jr5+XlATBt2rRDPmb69On7PfbL1q9fzx133MHGjRtp2bIl9913HzVq1DjiDJJ0MPv+965ljx7BBYkze4r2MP7t8eTn5wPQI7dltSv/9tW4dm3O6pFHdmbZL6WWL1/OmNGjY38+iSYUCjHommsBWLZsGe+8807AiSRJkqTykfAFIMCgQYMAeP/999mwYcMB97/66qtEIhHq1KlDt27djvi6AwYMIBQK8cUXX+x32H7Uxx9/zBdffFH2A8XeDPvatGkTd955Jxs2bKBp06bcd999ZGdnH/HrS9KhfPbZZwCEU1Jo1rlrwGniQ0lJCRPemRA7L6dj0yZ0btY04FTBq5mezlnd82hWt+xIjS1btjBq9Cg2bdoUcLKKceIFXyOzVi0AB4FIkiQpYVSLAvCss86iUaNG7N69m/vvv5+lS5cCZQM6XnnlFUaOHAmUDdJITt5/Lsr111/P+eefz0MPPXTAdVu1asWAAQMAePjhh5k0aRKRSIRIJMKkSZN45JFHgLICskWLFvs9d+vWrdx5552sXbuWRo0a8atf/crDxiWVm2gB2LRjJ1L3GYakQ/vwow9Zt24dALn168XOwBOkhMP079SBLs3Ljr7YXbCbsWPHsnLVyoCTlb/UjExOvvxKACZMmMDcuXMDTiRJkiQdv4SfAgyQkpLCnXfeyR133MGyZcu4+eabyczMZPfu3bHzfc4991yGDBly1Nf+/ve/z5o1a1i4cCG//vWvY4M79uzZA0DHjh258cYbD3jemDFjWL16NVA2afLHP/7xIV+jY8eO/OIXvzjqbJKqp9LSUgeAHKUZM2awfNlyABrn1KZv+3aEOLIp7NVFiBDdW7agZkY6kz9fFBsO0qdPHzp17BR0vHI14Jvf4p2nnqC0uJjHHnuMhx9+OOhIkiRJ0nGpFgUgQIsWLXj44Yf573//yyeffMLGjRvJysqidevWnHPOOfTt2/eYrpuRkcGDDz7IiBEjeO+99/jiiy8AaNOmDYMGDeKcc845YFUhsN/B4gUFBRQUFBzyNRL1rCVJFePzzz9nx44dgANAjsSyZcuYMWMGALUyMzm1YweSQpZ/h9K6QQMyU9P4YN58ikpKmPLJFPJ35HPCCSfEhm7Fu9qNGtH73POZ8vqr/Pe//+WOO+6gUaNGQceSJEmSjlkoEolEgg6hirdx48YKu3ZOTg7hcJiSkpLY2VmqusLhMDk5OWzZsoWSkpKg4+gIHO177Pnnn+fmm28G4M6336VBbquKjhi3Nm3axJgxYygpKSE1OZmze3SnRnra8V84FCIcTqKkpBQS9Mvstl27mDBnLrsKy1a8N2/RnP6n9j/oL73iQVpaGqFQiEgkQmFhIavnzeW35w0F4Oabb+bOO+8MOKG+zK9n8cfvGeOP77P4kyjvs3r16gUdQUo41eIMQEmqTqLn/2XWrk39lrnBhqnCdu/ezYQJEygpKSEpFGJA547lU/5VE7UyMzmre3fq7J1cv3LFSsaNG0dhYWHAycpH006d6XDKqQD861//cjW+JEmS4poFoCQlmGgBmNu9R8JsySxvkUiEDz74gF27dgFwQpvWNHAK+1HLSE1hSF4XmtYpG2K1YcMGxowZw86dOwNOVj5O+/YNQNngrhdeeCHgNJIkSdKxswCUpASSn5/PvHnzAGjZo1fAaaquGTNmsGbNGgDaNmpI20YNA04Uv5KTwvTv1JE2DRsAZYOtRo8ezdatW4MNVg46DRhI4/YdAHj88cfd/iZJkqS4ZQEoSQlkxowZsSFDuU4APqjVq1czc+ZMAHKysujd2jMSj1dSKMSJ7drSpXkzAHbt2sWYMWNYv359wMmOTygU4rRvXw+UDYsZNWpUwIkkSZKkY2MBKEkJZOrUqbHbLS0AD7Bz504++PADAFLCZSvXwkl+KSwPIaB7yxb0blNWqO7Zs4dx48axctXKYIMdp97nXUB2/foAPPLIIzg7TZIkSfHIn3okKYF8+umnADRo3YbMWrUCTlO1RM/927N3au3JHdo59KMCdGjcmFM6ticpFKKkpIR3J7zL54s+DzrWMUtJS2PgNd8Gygr2999/P+BEkiRJ0tGzAJSkBBGJRJgyZQoArXp6/t+XzZo1K7YltWPTJjStUyfgRImrZb16DOrSmeRwEpFIhIkfT2TWrFlBxzpmp171DTL2Don505/+FHAaSZIk6ehZAEpSglixYgUbNmwAINcCcD8bNm5gxowZANTOyqR7yxYBJ0p8jWrXYkheN9JTUgCYNm0an3zySVxuoc2oWZMB3/wWAB9//DGTJ08ONpAkSZJ0lCwAJSlBRLf/gisA91VUVMQHH3xAJBIhnJTEKR07eO5fJamTlcUZ3btRIz0dgPnz5/PBBx9QsndQTTwZdM23Sc3MBODPf/5zwGkkSZKko+NPQJKUIKLbf9OyatCobbuA01Qdn3zyCfk78gHo1boVtTIyAk5UvdRMT+eM7t3IycoCyqbpvjN+PEVFRQEnOzpZOTmceuXVAIwfPz62olSSJEmKBxaAkpQgoisAc3v0ICkcDjhN1bBq1SoWL14MQNM6ObRt1DDgRNVTRkoKQ/K60nDvYJo1a9bw1ltvUbC7IOBkR+e0b19PcmrZ4BhXAUqSJCmeWABKUgLYtWsXc+bMATz/L6pwzx4mTpwIQGpyMie2a0so4EzVWUo4zKAunWhRry4AmzZtYszoMezI3xFwsiNXq0FD+l12OQAjR45k/vz5ASeSJEmSjowFoCQlgOnTp1NcXAxAq569A05TNXw6ZQoFBWUrzPq0bU3G3mEUCk7ZGYztade4EQA7duxg9OjRbN68OeBkR+7073yPpORkAP7yl78EnEaSJEk6MhaAkpQAouf/AeT26Blgkqph362/zerWoUW9egEnUlSIECe0aU3e3knMuwt2M3bsWNauXRtwsiNTp0lTTvzaRQC8+uqrfP755wEnkiRJkr6aBaAkJYDo+X8N27Qlc+85a9XVni9t/e3Tto1bf6uYENC1eTNObNsGKJvU/Pb4t1mxYkWwwY7QGTf+gKRwmNLSUn7/+98HHUeSJEn6ShaAkhTnIpFIrABs5fl/TPnUrb/xom2jhvTv1IGkUIjSklLefe9dFi5cGHSsr1S/ZUtOuvhSAF5//XXmzZsXcCJJkiTp8CwAJSnOLVu2jI0bNwIOAFmzdg2LF7n1N540r1uXwd26kBIOQwQmTZrEzJkzg471lc76vx8STkkhEonw29/+Nug4kiRJ0mFZAEpSnIuu/oPqPQCkpKSEyZMmA2UTZ/u0cetvvGiQnc2QvK6k712tOX36dCZPnkwkEgk42aHVadqMfpddAZRNBI6H0lKSJEnVlwWgJMW56ACQjJrZNGzbNuA0wZk9ezbbt28HoEerlmSkuvU3nuRkZXFm9zxqZqQDsGDBAt5//31KSkoCTnZoZ974A5JT0wBcBShJkqQqzQJQkuJcdAVgy+49SEqqnv9Z37Z9G7NmzQKgbs0atG3UMOBEOhY10tM4I68bdWrUAGD58uWMHz+eoqKigJMdXO1GjTj1yqsBeOutt/jss88CTiRJkiQdXPX8SVGSEsTOnTuZO3cuUL3P/5s8aTKlpaWEQnBi2zaE3Pwbt9JTUji9Wxca1S6bZr127VrGjh0bG+xS1Qz53o2kZmQA8OCDDwacRpIkSTo4C0BJimPTp0+PbZGsrhOAFy9ZzNq1awHo2LQJOVlZASfS8UoJhxnYpTMt65cNcdm8eTOjx4xm2/ZtASc7UHa9+vT/xjUAvPvuu3z00UcBJ5IkSZIOZAEoSXEsev5fKBSiZY8ewYYJQOGePXz2adm2y6y0NLq1aB5wIpWXcCjEyR3a0aFJYwDyd+QzetRo1q1bF3CyAw254Xuk16gJwH333Velh5dIkiSperIAlKQ4Fj3/r1HbdmRm1wo4TeWbMX06u3fvBuCENq1JTgoHnEjlKUSIXq1b0bNVSwD27NnDuHHjWLJkScDJ9peVk8OQ794IwNSpUxkxYkTAiSRJkqT9WQBKUpyKRCKxArA6nv+3ZesWFixYAECTOjk0rZMTcCJVhBDQqWlTTu3YgaSkJEpLS/nwww+ZOXNm0NH2M+hb3ya7QQMAHnjggSo7uESSJEnVkwWgJMWppUuXsmnTJqB6FoBTPplCJBIhKRSid+tWQcdRBWtRry5DunUhLSUZKDv/8qOPPqKktDTgZGVSMzIYdtNPAFi8eDHPP/98wIkkSZKk/7EAlKQ4FV39B9VvAMjy5cv3G/xRMz094ESqDPVq1uSs7nlk7526u3jxYsa//TZ79uwJOFmZky65lAat2wDwu9/9jp07dwacSJIkSSpjAShJcSpaAGZkZ8dKh+qguKQ49rmnp6bQpXmzgBOpMtVIT+fM7t1oUCsbgLVr1zJ69Gh25O8IOBmEk5M579afAbB+/Xr+/ve/B5xIkiRJKmMBKElxKjoBOLdHT5KSqs9/zufMmRNbWdUzN5eUsIM/qpvU5GRO69qF3Ab1Adi2bRujRo6KrQoNUt4ZZ8W25D/88MOxbfqSJElSkKrPT4ySlEDy8/OZO3cuALk9ewecpvLs3LmT2bNmA1CvZo1YAaTqJxwK0a99O7q1aA5AYWEh48aNY8HCBYHmCoVCXPCznwNl79M///nPgeaRJEmSwAJQkuLStGnTKN07/KA6nf83bdo0SkpKAOjdpjWhgPMoWCGgW4vmnNqxA+GkJCKRCJMnTWby5Mmx90cQ2vQ5ka6DhwDw1FNPsWzZssCySJIkSWABKElxKbr9NxQK0bJ7j2DDVJJNmzaxZMkSAFo1qE/dGjUCTqSqokW9upzZvRuZaakALFiwgHHjxrG7cHdgmc679TZCSUkUFRVx//33B5ZDkiRJAgtASYpL0SEYjdt3IKNmzYDTVI7PPvsMgKSkJPJatgg4jaqanKwszu7RnfrZZe+HdevWMWrkKLZs3RJInsbt29PvsisAePPNN5k8eXIgOSRJkiSwAJSkuBOJRGJlWG412f67evXq2ICHjk0ak5WWFnAiVUXpKSkM7taVNg0bAGVn8I0eNTqwLbjDfvQT0rKyALj77rsD3ZYsSZKk6s0CUJLizJIlS9i8eTNQPc7/27fwTEtJpnPzZgEnUlUWDoU4sV1berdpRSgExcXFvP/++3z66aeVXsBl16vPGd/7PwCmTp3K66+/XqmvL0mSJEVZAEpSnIme/wfVYwXgokWL2Lp1KwBdmzcnNRwONpCqvBDQoXFjBnftQnpKCgBz587lrbfeoqCgoFKzDLr2OnKaNAXg/vvvr/TXlyRJksACUJLiTvT8v8zatWnQqnXAaSpWUXEx06dPB6BGejptGzcKNpDiSsNatTi7Z3fq1SwbGLN+/XqGjxjOuvXrKi1Dano65936MwBWrVrF3//+90p7bUmSJCnKAlCS4ky0AMzt0ZNQKBRwmoo1b+7c2IqpHrktCSf456vyl5mayul53Wi/tzzeXbCbt8a+xbx58yotQ69zz49N637ooYdYv359pb22JEmSBBaAkhRX8vPzY8VFop//V1BQwOzZswGoV7MGzevVDTiR4lU4FOKENq3p16Ed4aQkIpEIU6ZM4b3336OoqKjCXz8pKYkLf3EnADt37uS3v/1thb+mJEmStC8LQEmKI/sOMmjVq3fAaSrWrFmzKC4uBqBnq1a49k/Hq1X9+pzVI48a6ekALF+2nOEjhrNp06YKf+3WvfvQY+g5ADz77LOVugJRkiRJsgCUpDjyySefAJAUDtOye8+A01ScnTt3snDhQgCa1a1D/eyaASdSoqidmcnZPbvTvG4dAPJ35DN69OjYatOKdP5PbyeckkppaSn33HNPhb+eJEmSFGUBKElxJFoANu3UmbTMzIDTVJwZM2bEVjrmtWwRcBolmtRwmFM7daRPm9YkhUKUlpYyceJExo4dS2FhYYW9br0WLRh4zbcAmDBhAuPHj6+w15IkSZL2ZQEoSXGiuLg4NgCkde8TAk5TcbZv387ixYsBaFm/HrUTuOhUcEJAu8aNOKtHHjUz9m4JXr6c//73vxU6pOPM7/+ArJwcAO65557YNndJkiSpIlkASlKcmDVrFjt37gSgVa/ELQCnz5hBJBIhFIJuLZoHHUcJLicri7N7dKdVwwZA2fbzsWPHMmvWLCKRSLm/XmZ2LYbe9GMAFixYwDPPPFPuryFJkiR9mQWgJMWJjz/+OHY7UVcAbtmyhWVLlwLQqkEDsjMyAk6k6iAlHObUjh04uWP72JTgadOm8fbbb1NQUFDur3fKFVfSsE0bAH73u9+xY8eOcn8NSZIkaV8WgJIUJ6IFYJ2mzajdqFHAaSrG9OnTAUgKhVz9p0rXplFDhvXuSa29287XrFnD8OHDWb16dbm+TjglhQtuuwOAjRs38tBDD5Xr9SVJkqQvswCUpDjx0UcfAdCqd++Ak1SMjRs3snLlSgDaNmpIVlpawIlUHdXOzOTsHnm0a1xWsu/evZvx48fz6aefUrJ3ME156HLaYNqffAoAf//731mxYkW5XVuSJEn6MgtASYoDK1asYNWqVQC07t0n4DQVY9q0aQCEk5Lo0tzVfwpOOCmJPm1a079TB1LCYQDmzp3L6NGj2L59e7m8RigU4sKf30koFKKwsJAHHnigXK4rSZIkHYwFoCTFgejqP0jM8//WrVvHmjVrAGjfpBEZqSkBJ5Kged26DOvVg/rZNQHYvGkzI0aMYPGSxeVy/aadOnPSxZcC8Oqrr8amfEuSJEnlzQJQkuJAtABMr1GTxu3aB5ym/M2YMQOA5HASnZs1CziN9D9ZaWmc3q0r3VqU/XtZXFzMRx9+xIcffkhRUdFxX/+cH99K6t4zB+++++4KmTwsSZIkWQBKUhyIFoC5PXuRtHdLYqJYt24da9euBaBDkyakJScHnEjaX9lQmhac3q0LGampACxZsoQRI0awadOm47p2rYYNOf2G7wEwZcoU3nzzzePOK0mSJH2ZBaAkVXE7duxg5syZALROwAEg0c8tOZxEx6ZNAk4jHVrDWrUY1qsHzerWAcrem6NHj2bu3LnHtXJv8HU3UKth2dCR+++/n8LCwnLJK0mSJEVZAEpSFTdp0iRK904fTbTz/zZs2PC/s/8aN3b1n6q8tORk+nfqyAltWpMUClFaWsqnn37K+PHjKdhdcGzXzMzk3Ft+CsDy5cv5xz/+UZ6RJUmSJAtASarqPv74YwCSwmFadu8ZcJryFT37L5zk6j/FjxDQvnEjzuqRR3ZGBgBffPEFw4cPjxXaR6vP1y6iWZeuAPzxj39k48aN5RVXkiRJsgCUpKouev5fs85dSNs7LCARbNy4kS+++AIom/ybnuLkX8WXnKwszu6ZR5tGDQHYXbCbcePG8dnUz2Krdo9UUlISF/78TqBsa/Hvf//7cs8rSZKk6ssCUJKqsOLiYiZPngxA2z4nBpymfEXP/itb/dc04DTSsUlOCnNS2zac0rE9KXsH9MyZPYcxY8awY8eOo7pWu7796DbkTAD+9a9/8fnnn5d7XkmSJFVPFoCSVIXNmTOHnTt3AolVAG7atIlVq1YB0LZxQzJc/ac417JePYb26kG9mjWAshWuI0aMYOmypUd1nQtu+zlJycmUlJRw7733VkBSSZIkVUcWgJJUhX3yySex221OSJwCMLr6Lykpic6u/lOCqJGWxpC8bnRp3gyAoqIiPnj/Az76+COKiouP6BoNWrWm/1XfAOCtt97i/fffr7C8kiRJqj4sACWpCosWgHWbN6d2o0YBpykfmzdvZuXKlQC0a9SQjNTUgBNJ5ScpFKJ7yxYM7tqF9NSyla2LFy1m5IgRbN68+YiucfYPbiYjOxuAu+++m5KSkgrLK0mSpOrBAlCSqrBoAdg2gVb/zZo9CygrSjo1c/WfElOj2rUY1rMHTXJyANi+fTujRo1i3rx5X/ncrJwczvq/m4CyYwBefPHFCs0qSZKkxGcBKElV1KpVq2JTctskyPl/27dvZ/ny5QC0btiATFf/KYGlp6QwsEsnerduRVIoRGlpKVOmTOGdd96hcM+ewz63/9XfpF6LlgD85je/YdeuXZURWZIkSQnKAlCSqqjo9F+Atif0CTBJ+ZkzZw5Eym67+k/VQQjo0KQxZ/bIo2ZGOlBW7o8aOZKtW7ce8nkpaWmc/7PbAVi3bh2PP/54JaSVJElSorIAlKQqKloAptesSZMOHQNOc/x2Fexi8eLFALSsX4+a6ekBJ5IqT52sLM7u0Z3c+vUA2LFjB6NGjWL5iuWHfE73s4bSsnsPAB5++GG2bNlSGVElSZKUgCwAJamKip7/17rXCSSFwwGnOX5z58yltLQUgM6u/lM1lBIO069De3q1ziUUguLiYt579z2mTZ9GJBI54PGhUIjzbr0NKNs+/5e//KWyI0uSJClBWABKUhW0Y8eO2LCAtglw/l9hYSELFy4EoHFObXKysgJOJAUjBHRs0oTTunQhNTkZgFkzZzFhwgSKiooOeHz7fifTsf9AAP7xj3+wevXqyowrSZKkBGEBKElV0KeffhpbLde2T/yf/7dgwQKKi4sB6NK8WcBppOA1ql2Ls3t2p3ZWJlB2LuCYMWPYuXPnAY89/6dlqwALCwv57W9/W6k5JUmSlBgsACWpCopu/00Kh8nt0TPgNMenqLg4tpqxXnZNGmRnB5xIqhpqpKVxZvc8WtSrC8CWLVsYNWoUmzZt2u9xzTp3off5FwDwn//8hwULFlR6VkmSJMU3C0BJqoKiBWCzzl1Iy4zv7bKLPv+cwsJCALo0c/WftK/kpCRO6dieLnvPxSwoKGDs2LGsXLVyv8ed86NbCaekUFpaygMPPBBEVEmSJMUxC0BJqmKKi4v59NNPAWjV+4SA0xyfktJS5sydA0DtrEya1MkJOJFU9YQI0T23JSe1axMbDjJhwoTYylmAei1acMoVVwIwevTo2C8JJEmSpCNhAShJVcycOXPYtWsXUDYBOJ4tW7qUXTvLPpfOzZoSCjiPVJW1adiQ07p0ISUchghMmTKFz6Z+Frv/zP/7IamZZWcG3n///QedHCxJkiQdjAWgJFUxkydPjt1uHecrAOfMKVv9l5WWRot69QJOI1V9jWrX4szu3chMSwVgzuw5TJw4kUgkQna9+gz+9g0ATJo0iXHjxgUZVZIkSXHEAlCSqpjo1r46zZpRq2HDgNMcu9VfrGbr1q0AdGzahKSQ6/+kI1ErM5Mzu+eRnZkBwOeff857771HSUkJp113A1k5dQD49a9/HZsWLkmSJB2OBaAkVSGRSCRWAMb79t+5c+YCkBIO07phg4DTSPElMzWVM/K6UbdmDQBWrFjBO++8Q3J6Omd+/wdA2QrbESNGBBlTkiRJccICUJKqkFWrVrFmzRoAWp/QJ+A0x27z5s2xz6Nd40ZlZ5pJOippyckM7tqFRrVrAbBmzRrGjx/PSZdcFlsd/Lvf/Y6SkpIgY0qSJCkOWABKUhWy72TPeD7/b+7cstV/SaEQHZo0DjiNFL9SwmEGdu5E87pl237Xr1/Pex9+yOAbvgfAggULePPNN4OMKEmSpDhgAShJVUh0AEhGzWwatWsfcJpjs2vXLpYuXQpAy/r1yEhNDTiRFN/CSUmc0rEDLerVBWDDhg3srFOP2o3LynVXAUqSJOmrWABKUhUSXQGY27MnSUnx+Z/oefPnEYlEAOjUrGnAaaTEkBQKcXKH9rSsXzZNe/PWrTQdeBoAixYt4r///W+Q8SRJklTFxedPl5KUgLZv3x7bOhuv23+LiopYuGAhAI1zalM7MzPgRFLiSAqF6Ne+XawETGvTjow6ZasCf//731NcXBxkPEmSJFVhFoCSVEV8+umnsZVzreJ0AvCiRYsoKioCoGPTJgGnkRJP2UrAduTWr0dSOJmGp/QHYNmyZbz00ksBp5MkSVJVZQEoSVVEdPtvUjhMy+49gg1zDEojpbEVjLWzMmlUu3awgaQEFSJE3/btaFa3DnXyepCWUzYg5A9/+EOsgJckSZL2ZQEoSVVEtABs1rkLaXG4dXbF8hXs3LkTgE5NmxIKOI+UyJJCIU7p0J4mdevQeMAgAFauXMnzzz8fbDBJkiRVSRaAklQFFBcX89lnnwHQunefgNMcmzlz5gCQkZpKi71nlEmqOOGkJAZ07kj7fieTVrfsLMB7773XVYCSJEk6gAWgJFUBc+bMYdeuXQC06t074DRHb926dWzatAmADk0aEw65/k+qDMlJYQbndaPtkLMAyM/P5//+7/8CTiVJkqSqxgJQkqqASZMmxW7H4wTgefPmAZAcTqJto4YBp5Gql9TkZC6/6irS65SdBfjaa6/x5ptvBpxKkiRJVYkFoCRVAdHz/+o2b06tBvFVoOXn57Ni5QoAWjVoQGpycsCJpOqnRno6Qy6/MvbP3/ve95gyZUqAiSRJklSVWABKUsAikUisAGzVK/5W/y1YsAAiZbc7NGkcbBipGhtwzjnUrFN2FmBRURFXX301S5YsCTiVJEmSqgILQEkK2MqVK1m7di0Qf9t/i4qL+fzzzwFonFOb7IyMgBNJ1VdyaiqDL7s89s+bN2/miiuuYMuWLQGmkiRJUlVgAShJAYuu/oP4KwCXLFnMnj17AOjYtEnAaST1HTqMrFq1Yv+8dOlSbrjhBoqLiwNMJUmSpKBZAEpSwKIFYEbNbBq1ax9wmqMzf958ALIz0mlUu9ZXPFpSRUvLyGDgRRfv97H33nuPe++9N5hAkiRJqhIsACUpYNECMLdnT5KS4uc/y1988QXbtm0DoH2TJoQIBZxIEsAp519AelYWUDYcBODvf/87zz//fJCxJEmSFKD4+UlTkhLQ9u3bmTt3LgCtT+gTcJqjM2/ePABSwmFaNagfcBpJURlZNTj1/K8BkL97N3VqlJWBP/3pT/c7ckCSJEnVhwWgJAVoypQpRCJlI3Rbx9EE4O3bt7N69WoA2jRqSEo4HHAiSfsacNHFpKaVrf5r07AhacnJ7Nmzh29961usWbMm4HSSJKmivfvuu4RCIUKh0CGPAhk0aFDsMUp8FoCSFKDoapyk5GRadu8RbJijMG/+vNjt9k0aB5hE0sHUqFWLfuecA8CUxUv48XlDAdiwYQPXX389RUVFQcaTJElSJbMAlKQARQvAZp27kJqREXCaI7OnaA+LFy0GoFndOtRISws4kaSDGXDRJSTtXZ27ZN0Grhs8CCj7786vfvWrAJNJkiSpslkASlJAioqKmDp1KhBf238Xfb6I4uJiADq4+k+qsnIaNKDHwEEAvP7JFL49eBC9WucC8OijjzJixIjgwkmSpMC9++67RCKR2JFESmwWgJIUkDlz5rBr1y4AWvXuHXCaIxOJRJg/fz4AtbMyaVCrVsCJJB3OaZdeBsCe4hKe//BjHr3+2thQkJtuuonFixcHGU+SJEmVxAJQkgIyefLk2O3WveNjBeCq1avIz88HoEOTJnhcsFS1NW3TlvY9ewHw7Psfkp2RyV+/fQ2hUIgdO3Zw3XXXxX4RIUmSpMRlAShJAYme/1e3eXNqNWgYcJojs2D+AgBSk5PJrV8v4DSSjsSgvasAt+3axUsTJ9G/U0d+fG7ZUJA5c+Zw9913BxlPkqS4d7CJuwsWLOCHP/whHTp0ICsri5ycHPr27cuf//xnCgsLv/KaBQUFPPLII5xxxhk0btyY1NRU6tatS58+fbjzzjv54osvjjv30UwB3rFjBw899BBDhw6lWbNmpKenk5GRQevWrbnwwgt57LHH2Lx5c+zxI0eOjF37hhtuOKI8//rXv2LPuf3224/589LBWQBKUgAikUhsBWDr3n0CTnNktm/fHvtGo02jBoST/BIixYMOvU+gcatWADw5/l2KS0r44dlnMrBzR6Dsm23PA5Qkqfz85z//oVevXjzyyCMsXLiQXbt2sXXrViZPnsxPfvITevTowfLlyw/5/ClTptChQwd++MMf8vbbb7N27VqKiorYvHkzn376KQ888ADt2rXjqaeeqpTP58UXXyQ3N5cf//jHjBkzhtWrV1NYWMju3btZunQpr7/+Ot///ve57rrrYs8ZOnQoLVu2jD1/x44dX/k6f//73wGOqjTUkfOnN0kKwIoVK1i3bh0QP9t/FyxcELvdrpHDP6R4EQqFGHRJ2SrAlZs2MWb6DJKSkvjjNVdTr2ZNAH784x+zevXqIGNKkpQQPvvsM6655hp2797NlVdeyZNPPsnzzz/PHXfcQePGZd9Dz58/n9NOO41t27Yd8PyZM2dy2mmnsXLlSgA6d+7Mb37zG1588UUeffRRzjzzTAB27drFddddx5NPPlmhn88jjzzC17/+9djqvp49e3Lffffx3HPP8cILL/D73/+eCy+8kMzMzP2GiSQlJfHd734XgPz8fJ5//vnDvs6sWbOYOHEiAEOGDKFNmzYV9BlVX8lBB5Ck6ii6/RegVRwUgMXFxSxeVDYsoEmdHGqkpwWcSNLR6DnoNEY+9Q+2b9rE4+Pe4ZxePamfnc0fr7mKax75G1u3buXGG2/ktddeIxwOBx1XkqS4NWLECDIzMxkzZgyDBg3a775bb72VYcOGMXHiRJYuXcptt93G3/72t9j9paWlXHXVVezcuROA66+/nscee4zk5P9VNzfeeCNPPvkkN9xwA5FIhJtuuonTTz+d3Nzccv9cPvnkE3784x8DkJyczKOPPnrIlXnbt2/f72ccgOuuu457772XPXv28Pjjj8cKwYN5/PHHY7cP9zgdO1cASlIAol8cM7KzadS2XcBpvtrSpUvZs2cPAO0bNwo4jaSjlZySwoALLwJgxvIVfLK30B/UpTPXnT4IgIkTJ/LQQw8FlFCSpMTx4IMPHlD+AdSuXZuXX36ZGjVqAPD000+zYcOG2P0jR45k9uzZAOTl5fG3v/1tv/Iv6rrrrouVZLt27eIvf/lLBXwWcM8991BcXAzAr3/968Nuy83OzmbIkCH7faxBgwZcfPHFAEydOpXPPvvsoM8tKCjg2WefBaBRo0acf/755RFfX2IBKEkBiBaArXr2IikOztKbP38+ADXS02mcUzvYMJKOSb9h55KWkQHA38eNj338tgvOo0vzZgD8/ve/329CuSRJOjq1a9c+bFHWtGlTrrrqKgAKCwsZPnx47L5XX301dvuWW2457Kr822+/PTa8Y9/nlZcNGzYwduxYoKyU+9GPfnRM17nxxhtjt6Nn/H3Zf/7zH7Zu3QrAt7/9bVJSUo7ptXR45fpT55VXXsn7779fnpeUpISzbds25s2bB8TH9t8NGzawZcsWANo1bkSIr54SJqnqyahRg77DzgFg/Kw5LF2/HoC0lBQe/vY1ZKSmUlJSwg9+8APy8/ODjCpJUtw69dRTSU9PP+xj9l0pt++22X1/CRc96+9QWrZsSceOZQO9VqxYwZo1a44l7iF9+OGHsTP9hg4desylXP/+/enatSsAL7zwwkG/x4gWg0lJSQ7/qEDlWgC++OKLnHbaaXTq1ImHHnpovxHQkqQyn376aeyLaeteVb8AnL+gbPVfOCmJNg0bBJxG0vHof8GFhPauOv73ux/EPt6mUUPuvuRCAJYtW8Yvf/nLQPJJkhTv2rX76uN99n3MF198EbsdLfFq1qxJo0ZffexO+/btD3hueVm1alXsdufOnY/rWtFVgAcbBjJr1iwmTZoElJWeFXGWocqU+76zSCTCwoULueWWW2jWrBnf/OY3+fDDD8v7ZSQpbkV/y5eUnEzL7j2CDfMVCnYXsHzZcgBa1q9H6kHOIJEUP+o0akSXvv0AeGniJPJ3747d9/VTT2ZQl7Jv8J9++mneeeedQDJKkhTPsrKyjuoxO3bsOOD2kVwDiJ0l+OXrlIft27cf9HWOxTe+8Y3YNfYd9gH7bwt2+EfFKtcC8N133+WKK64gNTWVSCTC7t27ee655xg4cCBdunTh4Ycfju3rlqTqKrq0v1nnLqTuPY+rqlr0+SJKS0sBaN+4ccBpJJWH/l8rW+mXv7uQVyb9b9tRKBTid1d/nVqZmQDcfPPNft8mSdJRik7wPdLH1KxZ84DbR3INYL/ttPtepzxkZ2cf9HWORc2aNWPnHn722WdMnToVKBtgEh3+0aRJE84999zjeh0dXrkWgAMGDOD5559n1apV/P73v6d9+/ZEIhEikQjz58/nRz/6EU2bNuXaa69l4sSJ5fnSkhQXioqKYl/wWlfx8/9KI6UsWLgAgLo1a1CnxpH9JlJS1da2ew8a5bYC4F8T3o+V/AANa9fi/isuBWDt2rX8/Oc/DySjJEnxatGiRUf1mCZNmsRuN977C/cdO3awbt26r7zOwoULD3qd8tCsWbPY7blz5x739b7//e/HbkdX/f3nP/9h27ZtQNlk44NNPFb5qZDRk3Xr1uWWW25h/vz5TJgwgcsvvzy2KrCgoIB///vfnHrqqeTl5fHoo4/ut7RUkhLZ7NmzKSgoAKp+Abhq5Sp27dwFuPpPSiShUCi2CnDJ+vW8P2/+fveff0IvzunVA4BXXnllv+mEkiTp8D744AMKCwsP+5i33347dvukk0466O233nrrsNdYsWIF8+eXfQ1v0aLFEZ0ZeDT69+8fmzI8evRoioqKjut6eXl5nHzyycD/hoFEtwMnJSVx/fXXH19gfaUKKQD3NXDgQF544QVWrVrF7373u/1WBc6ZM4cf/vCHNGnShOuvv36/6TeSlIj2nexV1QvABQvKVv+lpSTTol7dgNNIKk+9B59Oxt6tQv+c8P5+94VCIX719cuon112/6233sr6vRODJUnS4W3dupV//OMfh7x/zZo1PPfccwCkpaXtt+314osvjt3+4x//SElJySGv89vf/jY2WHDf55WXevXqMXToUKBsV8BDDz103NeMDgPZsWMHP//5z2PDP4YOHUqLFi2O+/o6vAovAKPq1q3Lrbfeyvz58xk/fjyXX345KSkpRCIRdu3axT//+U/69etHz549eeKJJ2IrZCQpkUR/0VG3eQuy61fdibrbtm+LTRJr27Ah4aRK+3IhqRKkpqfTd+gwAN6dM5cl6/Yv+OrUqMFvr/46AJs3b+ZnP/tZpWeUJCle3Xbbbbz//vsHfHz79u1cdtllsYEd1157LfXr14/dP2zYMLp16wbAjBkzuPHGGykuLj7gOk8//TR/+9vfAMjMzOTmm2+uiE+De++9N7Yt9xe/+AVPPPHEIR+7Y8cOxo8ff9jrXXrppdSrVw+ARx55JPZxh39UjkB+ojvttNN48MEH+da3vgUQW1YaiUSYOXMm3/ve92jRogV//vOf9zuXRpLiWSQSiRWAVX3138IF/ztPpG3j8t1OIKlqOOW8CwjtLff/9e6BP6Sc3q0rl/Yr24o0cuRItwJLknQEzj33XIqLixk8eDBXX301//znP3nxxRe5++676dSpEx9++CEArVq14re//e1+z01KSuLZZ5+NTQF+4okn6NmzJ7/73e946aWX+Nvf/sbQoUO59tprY13JX//6V1q2bFkhn0ufPn3485//DEBxcTHf+c536N27N7/61a94/vnnefHFF/nTn/7EZZddRpMmTXj44YcPe720tDS+/e1v7/exZs2aMWzYsArJr/1V6gmLpaWlvPnmm/z9739n3LhxseWqkUiEmjVr0rdvX9577z327NnDpk2buPXWW3njjTcYPXo0GVV8UqYkfZUVK1bEDvOtygVgUXFx7GDiZnXrkJWWFnAiSRWhTsOGdO13MrM++pCXJ07m1vPPoeaXvt+665ILeW/uPNZv285tt93GqaeeSk5OTkCJJUmq+nr37s03vvENrr32Wp577rnYdt99dejQgTFjxuw3aTcqLy+PCRMmcNFFF7Fq1Spmz57NbbfddsDjMjMz+etf/8p1111XIZ9H1A9+8ANq167ND37wA7Zt28bUqVNjQw2/LOkIdg1997vf5Q9/+EOswLz++usJh8PlmlkHVykrAJcvX86dd95J8+bNufjii3nrrbcoLS0lEonQrVs3Hn30UVavXs3YsWNZuXIlDzzwAPXr1ycSifDBBx/wpz/9qTJiSlKF2vf8v1ZVuABctmxp7JDfdq7+kxJadBjIzsJCXpl44FnMtTIz+dUVlwGwYcMG7r777krNJ0lSPLrsssuYOnUq//d//0e7du3IzMykVq1anHjiifzxj39kxowZ5ObmHvL5ffr0YeHChfz1r3/l9NNPp2HDhqSkpJCTk0Pv3r35xS9+weeff17h5V/U1VdfzdKlS/ntb3/LoEGDYnkyMjJo06YNF110EY8//jhPP/30V16rdevWtGnTBoBwOFxpn4MgFIkuwytnJSUlsdV+b7/9dmzwB0BqaiqXXHIJN954I6eccspBn79582YGDhzInDlz6Ny5M7Nnz66ImNXGxo0bK+zaOTk5hMNhSkpK2LJlS4W9jspHOBwmJyeHLVu2HPZQWZW/W2+9lX/9619kZGfzm09nHNFvyKBsqXwoFCISiXzlRLHyMGrUKDZu3EhWWhrn9+lFiFCFv2bCCYUIh5MoKSmFivkyq3IWDochBESoVv9tjEQi/OF7N7Bm6VJy69dnwr13HPS/Td9/4ilGTp0OwEsvvcRpp51WyUkP5Nez+OP3jPHH91n8SZT3WfScuHjx7rvvxr423nPPPdx7773BBqrCpk+fTs+ePQE4//zzeeONNwJOVH2U+wrAZcuWcccdd9CiRQsuueQSxo0bF1vtl5uby29+8xtWrVrFs88+e8jyD6BOnTqxgyyXLl1a3jElqdJFz/9r1av3EZd/lW3T5k2xXxi0bdzI8k9KcKFQiFMvKFsFuGzDBj7a5/zPff3y8kuolZkJwC233EJ+fn6lZZQkSYnjsccei92OTgVW5SjXn0DPOuss2rZty4MPPsiaNWuIRCKEQiHOOeccRo4cyeLFi7ntttuOuM1v1qwZALt37y7PmJJU6bZt28b8+fMBaN2r6m7//Xzh5wCEQtC6YdWdUiyp/PQ6bTDpmWWHjT/z/ocHfUz97GzuufQiAFauXMmvf/3rSssnSZISw+eff86//vUvADp27MhZZ50VcKLqpVwLwH1X+zVo0ICf//znLF68mOHDhzN06NDYtN8jlZmZSYsWLSpsoo0kVZYpU6bEjkGoquf/FRUVsWTJEgCa161LRkpKwIkkVYa0jAxOOOMMAN6eOZu1W7ce9HEXndSHgZ07AvCPf/wjtqpZkiTpUMaMGcOoUaN4+OGHGTJkSOxIo/vvv/+oOyIdn3Lfg9a/f3+ef/752DCP4ynvBgwYwLJly2I/kEpSvIr+oJyUnEzLvO4Bpzm4pUuXUlxcDEDbRg7/kKqTk885D4CS0lJe/HDiQR8TCoX49ZVXkJmWSiQS4ZZbbmHPnj2VGVOSJMWZoUOHcs4553DTTTexYsUKAC6//HIuueSSgJNVP+VaAM6aNYv33nuPK664ghRXjkhSTLQAbN6lK6kZGQGnObiFC8vO/qqZkU7D2rUCTiOpMjXKzaV1124AvPDRxxQf4rD/ZnXr8LPzy8rC+fPn87e//a3SMkqSpPiVlZVFXl4ef/3rX3nmmWeCjlMtJZfnxbp06VKel5OkhFBUVMTUqVOBsgEgVdHGjRvZvHkzULb6z8X4UvXT79zzWDJ7Fmu3bmP8rDmc1SPvoI/75qD+/HfyJ8xasZI//OEPfO1rX6NFixaVnFaSpKpj0KBBseN+tD//XKqOcl0BmJSURHJyMm+++eZRPW/s2LGEw2GSk8u1j5SkKmHWrFkUFBQA0LqKnv8XXf2XFArRumH9gNNICkL3U/uTVats9e9zHxx8GAhAOCmJX195OaFQiIKCAm6//Xa/uZckSariyv0MwGP9BjASifjNo6SEtO9B+VWxANxTtIdly5YB0LxeXdKSPcJBqo6SU1M58ayzAXhv7nyWb9hwyMfmtWzBNwf2B8qGwI0cObJSMkqSJOnYlHsBKEna3+TJkwGo27wF2fUbBJzmQEsWL4kN/2jX2OEfUnV28jnnxm4//+HHh33sreefQ4Na2QD84he/ID8/v0KzSZIk6dhViQJw165dAKSnpwecRJLKVyQSia0AbHNCn4DTHNzCz8u2/2ZnZFA/OzvgNJKCVLdxEzrs/W/VSx9PorCo6JCPzc7I4J5LLwJgzZo1PPjgg5WSUZIkSUevShSAkyZNAqBBg6q3MkaSjsfy5ctZv349AK2q4Pbf9evXs3XLVqBs9Z/DPySdcm7ZlN/N+TsZNW36YR97Tq+eDOzcCYAnnniCmTNnVnQ8SZIkHYNjnroxc+ZMpk+fftD73nnnHbZu3XrY50ciEXbu3MnUqVN59tlnCYVC9OlTNVfHSNKx2u/8v15VrwCMDf9ISqJVA4d/SIJOJ/Wldr36bN24gWff/4gLTzz092ehUIj7r7iEM+5/kMKiIm699VZGjx5NOByuxMSSJFW+cePGBR3hqJxxxhlBR1DAjrkAfO2117jvvvsO+HgkEuHhhx8+qmtFIhFCoRDf+973jjWOvkJlfSPuN/xVX/TvyL+ryjFlyhQAMrKzadSuHaHQ8a2xO97n76twTyHLly8HoGW9uqSmOPyjvIT2+f9IOf6dqZJU87+zcHIyJw07h7H/fppPFy9h0dp1hz0fNLdBA24aeha/f3ME06ZN45lnnuG6666r+Jx+PYtr/r3FB99n8c2/t4p15plnBh3hqDh0VcdcAMKh/wU62n+xGjZsyAMPPMDgwYOPJ44OIycnp8JfIxwOV8rrqHxke9ZbpYgWgG1OOJGMjIzjulYoFCItLa08YgFlq/9KSkoA6NC0CeFwlTgVIqEk+Wcaf0L4XgD6DRvGW8/+m0hpKa9M+oR7r7j0sI+/6bxhvD7lUz5fs5YHHniAa665hvr1K2dVsV/P4o/fM8Yf32fxx/eZpC875gLwa1/7Grm5uft97NprryUUCvGDH/yAXr16Hfb5SUlJ1KhRg1atWtGtWzd/O1HBtmzZUmHXzs7OJhwOU1JSwvbt2yvsdVQ+wuEw2dnZbN++PVb+qGJs3bqVOXPmAJDbsxeFhYXHdJ3U1FRCoRCRSIQ9e/aUW745c8uy1c7KpE5WFiUlpeV27eouRFn5V1pSir9rjQ/hpKS9SzahpNT3QnbdenQ8oQ/zPpnMfz6ayC3nDSM1+fDfNv7y8ku48qFH2Lp1K7fccgt/+ctfKjSjX8/ij98zxh/fZ/EnUd5n8VRe/vrKy+nUrGnQMQ5q3qrV/OL5/wQdQ1XEMReA3bt3p3v37vt97NprrwXg9NNP5/zzzz++ZCpXlfUF228M4kdJSYl/XxUsOuAIoFWv3uWy7L68lu6vW7eO7dvKvils26hR9OLlcm39b9tvBPxzjUf+nQFw0tnDmPfJZDbn5/PWjJmc06vnYR9/Sof2nNOrByOnTufZZ5/l6quv/spfCJcHv57FJ//O4ovvs/jk31nl6NSsKX3atgk6hvSVynWPyz//+U+eeuqpSvlmT5KquugAkKTkZFrmdf+KR1euBXuHf4STksh1+Iekg+jSty81atcG4D8fTTyi59x58YVkpKYSiUS4/fbbKXU1pSRJUpVQrgXgNddcwzXXXEOzZs3K87KSFJeiBWDzLt1IPc7z/8rT7sLdrNg7/CO3fj1SPYJB0kGEk5Ppc0bZAefvz1vA6s2bv/I5Terk8MOhZc+ZNm0azz33XIVmlCRJ0pHxlGtJqgBFRUVMmzYNgNa9ewecZn9LFi+Jrcppe5jJnpJ00tnDgLLjB17+ePIRPef6008jd+8AkF/96lcVeg6xJEmSjowFoCRVgFmzZlFQUABA694nBJxmfws/L9v+Wzsrkzo1agScRlJV1qB5c1p37QbASxMnHdGAlLSUFO697GIANm/ezG9+85sKzShJkqSvdkxDQFq3bg1AKBRi8eLFB3z8WH35epIUr6LbfwFaVaECcP369fsM/2hIKOA8kqq+k84eypLZs1i9eQsfzl/AwM6dvvI5p3XtzJndu/HWjFn861//4uqrryYvL68S0kqSJOlgjqkAXLZsGVBW2H3546FQ6JinVH75epIUr6ITgOu1aEl2vaozZOPzzz8HICkpKbZFT5IOJ6//AF579P+xe9dO/vPRxCMqAAHuuuQi3pszj8LiYm6//XZGjBhBUpKbTyRJkoJwTAVgixYtDlrWHerjklSdRCKR2ArAqrT9d0/RHpbvHf7Rol5dUpOP6UuApGomLSODXoMH8/GI4bw1Yxabduygbs2aX/m8FvXqcuNZQ3ho5BimTJnCyy+/zOWXX14JiSVJkirPsmXLePrppwG49957A81yOMe1AvBIPy5J1cmyZcvYsGEDULW2/y5buozi4mKgbPuvJB2pk84exscjhlNUUsKrk6dww5DBR/S8G88cwiuTPmHVps388pe/ZOjQoWRnZ1dwWkmSpMqzbNkyfvnLXwJVuwB0H4YklbN9z/9r3avqFIDR7b81M9Kp7w/gko5Cs3btaNqmLQAvfjTxiI97SU9N5Z5LLwJgw4YN/PGPf6ywjJIkSTo0C0BJKmfRAjAjO5uGbdsGnKbM5s2b2bRpEwBtGjr8Q9LRCYVCnHj2UAAWrV3H9GXLj/i5Z+R1Y2DnjgA8/vjjLFq0qEIySpIk6dAsACWpnEULwFa9eleZA+8/X1S2+i8UglYNGgScRlI86nXaaYRTUgB4ZdInX/Ho/wmFQtx1yUWEk5IoLi7mrrvuqqiIkiSpHCxevJibbrqJzp07U7NmTWrUqEGnTp245pprGDNmTOxx7777LqFQKDYLYtKkSVxyySU0btyYcDjMj370o2POEL3uu+++y/r16/nBD35Abm4uGRkZtGvXjvvvv589e/bEHj9hwgSGDh1K/fr1yczMpG/fvowYMeKA606aNIlQKETNmjVjxyPtq2vXroRCIdLS0ti1a9cB9/ft25dQKMTf/vY3AHJzcznttNMOyB39X1XaElzpP5kWFBTw5z//mYsuuojzzz+fu+++mzVr1lR2DEmqEFu3bmX+/PlA1dn+W1xSzNIlSwFoWqcOGakpASeSFI+ysmvRtW8/AN6c8hm7i4qO+LntGjfimoH9AXj77bcZN25chWSUJEnH54knnqBTp048/PDDzJs3j+LiYlJTU1mwYAH//ve/ueKKKw76vP/85z/079+f//73vxQUFBAOh8slz/Lly+nZsyf/7//9P7Zs2UJRURGLFi3i7rvv5utf/zoAjz32GEOGDOGtt95iz549FBQUMHnyZM4//3xeffXV/a53wgknkJWVRX5+Pp9++ul+923YsIG5c+cCsGfPHj7++OP97s/Pz+ezzz4DYNCgQQDUr1+fnJyc2GMaNmy43/9q1KhRLn8O5aFcC8Bp06aRl5dH9+7dmThx4gH3b9++nb59+3LrrbfyxhtvMHLkSB544AHy8vKYNm1aeUaRpEBMmTIldruqDABZsXxF7LdjbRz+Iek4nHDGmQBsLyjg7Zmzjuq5PzpnKDlZWQDcfffd+/3WXpIkBe/111/nO9/5DkVFRQwbNoypU6dSUFDA5s2b2bZtG2+++SZDhw496HOvv/56LrjgApYuXcrWrVvZtWvXca0AjPrRj35Ey5YtmTFjBtu2bWP79u3cf//9ALz66qv86le/4uabb+a2225j06ZNbNu2jWXLltGvXz8ikQg33XQTJSUlseslJydzyimnAGUrGPf13nvvEYlEYgPLvnz/hx9+SHFxMY0aNaJjx7LjTaZMmbJfybh27dr9/nfrrbce959BeSnXAvCVV15h9uzZrF+/nr59+x5w/x133MGsWbOIRCL7/W/Tpk1cfPHFFBYWlmccSap00QIwKTmZlnndA05TJjr8IyM1lSY5tYMNIymudTyhDzX3/pb7aLYBA9TKyuTW888BYNGiRTz11FPlnk+SJB2boqIibr75ZgAuuOAChg8fTs+ePWP316xZk/POO48XXnjhoM/v3r07L730Erm5uUBZ0Ra9fTxCoRCjRo0iLy8PgMzMTO68804GDx4MwF133cXVV1/Nr3/9a2rXrg1Ay5YteeGFFwiFQqxevfqAlXzR1XsHKwABbrrppsPeP3DgwOP+vIJQrgXg5MmTCYVCnHHGGbE94FE7duzgySefJBQK0aJFC1577TWmT5/Od77zHaBsWeezzz5bnnEkqdJFz/9r3qUrqRkZAacpW3m9bt06ANo0akDI8R+SjkM4OZnepw8B4L0581i3bdtRPf/rp55Mp6ZNAPj973/Phg0byj2jJEk6eu+88w4rVqwgFArxpz/96ajPMr/lllsq5Pzz733ve7Fib19DhgyJ3f75z39+wP0tW7ak7d6BjLNm7b9rIVrgffTRR/udAxgt/G688UYaNGjAlClT9jsHMHq/BSCwevVqgP1a4qjRo0eze/duAJ588kkuuOAC8vLy+Nvf/hZrcl9//fXyjCNJlaqoqIipU6cCZQNAqoJ9p222buj2X0nHL7oNuDQS4bXJn37Fo/cXTkrinssuBsp+QfHggw+Wez5JknT0ose4dezYkdatWx/18/v161fekQDo1q3bQT/eYO9gw/T09FjR92UN9/78s2XLlv0+3qdPnwPOAdy4cSNz5syhffv2NGnShIEDB+53DuDOnTtjj42uIIw35VoAbty4EYDGjRsfcF90qWTjxo05/fTT97vv0ksvJRKJMHPmzPKMI0mVavbs2RQUFADQugqc/1daWsqixWUFYKPataiRlhZwIkmJoEmr1jRr2w6A/076hEgkclTP79e+HcN69QDgmWee8fs/SZKqgOiuoZYtWx7T8+vXr1+ecWIO1i8BsSEjDRs2PGAH6pcfU/SlwWUpKSmcfPLJwP9W9UXP/4uWe1/eJhw9/69hw4Z06tTpWD+dQJVrAbht7zaQgy37nDhxIqFQ6IDyD6BFixYAbgORFNcmT54cu10VVgCuWrWK3QVlK6/bNmoUcBpJiaTPmWcBsHDNGmatWHnUz//FRReQlpxMJBLhjjvuOOoSUZIkVS3lNfW3sny54IsuWjtUARi9f8CAAZUVsdyVawGYmZkJHFjkbdu2Lfbb3WjLuq/09HSA/SazSFK8iZ7/V7d5c2o1CH677eeLyoZ/pKUk07ROzlc8WpKOXM/TBhNOTgaOfhgIQPO6dfnOGWW/FJ40aRJvvPFGueaTJElHp9HeBQPLly8POEnl+PI5gNGiL1r8de7cmYYNG8bOAfzy/fGoXAvA6ISXDz/8cL+PjxgxgtLSUoDYuOV9bdq0CYBatWqVZxxJqjSRSCQ2AbhVr+C3/+7ctTN2LmurBg0IV8CBvJKqrxq1atH5pL4AvDHlUwq/tLXmSHz/rCE0ql32vd8vf/nL/Q7ZliRJlSt6ht/8+fNZsmRJwGkq3oknnkhmZib5+fmMHTuW2bNn06FDh/22HEfPARw3btxhz//bdxdsVd7VUK4/Efbv359IJMKbb77JjBkzgLIDnn/3u98B0KRJE7p27XrA82bPng1Aq1atyjOOJFWalStXsnbtWqBqnP+3eNFi2Pu1p03DBsGGkZSQotuAt+7cxfhZc476+Zlpafz8wguAsiMLHn300XLNJ0mSjtzgwYNp0aIFkUiEn/zkJ7FFXIlq33MA77vvvv3O/4uK/vOvf/1rioqKaNCgAZ07dz7gWtnZ2bHbW7durajIx61cC8AbbriBpKQkdu/ezYknnkjfvn1p06YNs2fPJhQKccMNNxz0ee+88w6hUCg2DViS4k10+y8EXwBGIpHY9N96NWtSa+/xDJJUnjr1OZEatWoDZcNAjsUFfXrTu3XZL4D/+te/xlYuS5KkypWcnMxDDz0EwBtvvMH555/P9OnTY/fn5+fz8ssvc+GFFwYTsAJEtwFHf5Y7VAEYvf9Q5/+1b9+elJQUAP75z39WQNLyUa4FYF5eHvfccw+RSISioiKmTJnCpk2biEQidOvWjZ/+9KcHPGfWrFnMnz8fgFNPPbU840hSpYl+UciomU2jdu0DzbJ27Vry8/MBaNMo+LMIJSWmcHIyvQaXneM3Yc5cNm7fcdTXCIVC3HvZxQAUFBTwy1/+slwzSpKkI3fhhRfy//7f/yMcDjNy5Eh69uxJZmYmdevWJTs7m8suu4wJEyYEHbPcHKrwi+rUqRMNGzY85P1RmZmZXHXVVQDccsst1KhRg9zcXHJzc2OlalVQ7odC3XXXXbz++uucc845tG/fnl69enH77bfz/vvvk5GRccDjH374YaBsxcpZZ51V3nEkqVJEC8Dcnj0POgm9Mn3+ednwj+RwEi3q1Q00i6TEdsIZZwBQUlrK8M+mHtM18lq24NJ+JwHw2muvMXHixHLLJ0mSjs73v/99Zs+ezXe/+13atm1LJBKhuLiYjh07cu211/LKK68EHbHcRM8BBOjQoUNsEMq+9i39DjcA5LHHHuOuu+6ic+fOlJSUsHz5cpYvX16ltgSHIlX5hEKVm40bN1bYtXNycgiHw5SUlLBly5YKex2Vj3A4TE5ODlu2bHHydjnZsWMHbdq0IRKJMOxHP+HsH9xcrtdPS0sjFAoRiUQoLCw87GN3F+7mlZdfobS0lLaNGnJi2zblmuX/s3ffYU2f6x/H39+EDYKigKioOHCiuPeqWmfdHba1y9Pdnu7lqtrW2nVOp93D/uxp7d5Da+ves4qCiuLeqOyd3x8h1LYOhIQvIZ/XdXmVmuT5fpALSO48z31LCRkGVquFgoJC0K9Zt2C1WsEAbOhn40Ww2Ww8e8t4juzZQ1z9enzzyAOlWufo6VT6TH2C9OwcYmNjmT9/vv1rch76feZ+9JzR/ej7zP1Ulu+zGjVqmB3hggzDAOCrh++nQwV9zr1mZxIjn/0PULGHU0j50FhIEZEyWrt2bfEvVLP7/+1K2lXcsFfHf0XE1QzDoN0l/QDYmLyH3UePlmqd8JBg7h40ELC3h/n444+dllFEREREVAAUESkzx/Ffi9VKvdZtTM3iGP5RNTCA0KAgU7OIiGdw9AEE+Hr12lKvc2OfntQPCwPs0/ZSU1PLnE1ERERE7FQAFBEpI0cBsHaz5viaOHH32LFjxT0mGkZEYJiWREQ8SWhEBA1axgLw1eq1pT5i5OvtzeQxIwD7z7MXXnjBWRFFREREPJ6XqxbeuHEjP/30E1u2bOHkyZNkZ2df8DGGYbBgwQJXRRIRcbr8/HzWrrXveDH7+K9j+IfFMIgODzM1i4h4lnZ9+7Fry2b2HDvOxuQ9tImuX6p1+sa2pGezpizelsBbb73FuHHjaNSokXPDioiISLm45557mDt37kU95vDhwy5KI04vAB46dIgbb7yR+fPnX9TjbDZbcRNNERF3ER8fT2ZmJgDRbc0rAObl5ZGcnAxA3RrV8fFy2fs7IiL/0LpnL76c9SoFeXl8tXptqQuAhmEw5fJRDHxyJvn5+UyePFn9AEVERNzU6dOnOXLkiNkxpIhTjwCnp6fTp08f5s+fj81mu6g/IiLuaM2aNcUfR7dtZ1qO5ORk8vPzAQ3/EJHyF1ClCs06dATgu7XryCvDtNDGkTW5vndPAH799deLflNZREREKoYPPvhAtaEKxKkFwP/+979s374dgDp16vD666+zc+dOsrOzKSwsvOAfjZYXEXfj6P9XrVZtqkVGmpbDcfw3yM+P8JAQ03KIiOdq19c+DTglPYMl2xLKtNY9QwYSGhQIwOTJk8nNzS1zPhERERFP5tQC4FdffQVAzZo1WbNmDbfeeisNGjTAx8fHmZcREakwHAXABu3M2/138uRJjh8/Dth3/6mZgoiYoXmnzvgF2ot2X60q/TRggJCAAB4aNhSApKQk3nnnnTLnExEREfFkTi0AJiUlYRgGd9xxBxEROoImIpXbgQMHOHDgAGBu/z/H7j/DgAYa/iEiJvH28aF1D/vR3Xmb/iC9BAPgzufKbl1oXqc2AM8//zxHjx4tc0YRERERT+XUAmBhYSEATZo0ceayIiIVkmP3H5g3AbigoIBdu3YBUDs0FH/tuBYREzmOAWfn5TFv0x9lWstqsTD1itEApKWlMWPGjDLnExEREfFUTi0A1qtXD7A/SRMRqexWrVoFgG9gELWaNDUlw969e4t7YzXUzmsRMVmD2FZUrWHfiVzWY8AAnRo3Ymi7NgD873//Y9OmTWVeU0RERMQTeTlzsWHDhrF161aWLVvGjTfe6MylRUQqHMcE4PpxbbBYraZkcBz/9ffxIbJaVVMyiIg4WCwW2vbty29zP2FpQiJHT6cSHhJcpjUnjBrO/D+2kJOXx4QJE/j+++8xDHU7FRGRimHb/gNmRzinipxNyp9TC4B33303b775Jh999BEPPvggTZuasyNGRMTV0tPTiY+PB8w7/puWlsbhw4ftGSLCsegFsYhUAG0vsRcAC202vlu7jvF9+5Rpvdqhodx+aV9e/OFnVq9ezZdffsno0aOdlFZERKRsJvxvrtkRRErEqUeAIyMj+eSTT/Dy8qJ///4sXrzYmcuLiFQY69evp6CgAIDotuZMAN65c2fxxw0jwk3JICLyd7WiGxDZoAEAX65a45Q1b7u0H7WqVQNg2rRpZGRkOGVdEREREU/h1B2A06dPB6Bfv35888039OnTh7i4OLp06UKNGjWwWC5cb5wyZYozI4mIuIRjAIhhsVA/rk25X7/QVlhcAIwICSHIz6/cM4iInEu7S/ry/a5dbNm3n11HjtKgjG9S+Pv4MHH0cO585wMOHTrEyy+/zKRJk5yUVkRE5OLZbDazI4hcFKcWAKdOnVrck8UwDGw2Gxs3bmTjxo0lXkMFQBFxB44BILWaNMUvKKjcr3/gwAGysrIAaBSp4R8iUrHE9erD9++8DcB369Zzz+CBZV5zSNs2fNh4Cat2JPHaa69x3XXXUa1oV6CIiIiInJ9TjwCDvQru+PP3/7/QHxERd1BQUMC6desA8/r/OYZ/+Hh5USc01JQMIiLnEhoRQf3mzQH4fu0Gp6xpGAaPXz4awzDIyclh8uTJTllXRERExBM4dQfg77//7szlREQqpISEBNLS0gBzCoCZWZkcKJroFR0ehrUE7RVERMpbXK8+JG/dyvZDh0g8cJAmtWuVec0WUXUY260L/1u6nO+++47ff/+duLi4socVERERqeScWgDs1auXM5cTEamQHP3/AKJNKAAm7Uwq3jXdsKaO/4pIxRTXsxffvDELm83Gt2vX85ATCoAADw4bwvfrNpCalcU999zDggULilvQiIiIiMjZaduIiMhFchQAQyJqUi3SOS9oS8pms7Fjp/34b/UqQVQNCCjX64uIlFRw9eo0bNUasPcBdFa7l+pVqnDvEHtPwc2bN/Phhx86ZV0RERGRykwFQBGRi+QoADZo177cd50cPnKY9LR0ABpp95+IVHBxvXoDsOfYcTbv3ee0da/r3bP4Z+BTTz3FyZMnnba2iIhISRiG4VZ/RFxeANy/fz/z5s3jk08+0Tu0IuL2Dh8+zN69ewFz+v/t2LETAC+rhbo1apT79UVELkarHj2xFPUp/W7teqet62218vjlowE4efIkzzzzjNPWFhEREamMnNoD8EzvvfceL7zwAgkJCX/5++uuu+4v///UU0+xaNEioqKiePfdd10VR0TEKczs/5ednc3ePXsAqFejBt5Wa7leX0TkYgWFhBDTth0Ja9fw/boNPDZyWHFBsKx6tWjGpXGtmLfxDz744AOuv/56mjVr5pS1RURESurKJ2ZQu2nF/P1zIGEbcydPMDuGVBBOLwBmZWUxZswYfv75Z4C/9Hs527bT9u3bM3nyZAzD4MEHH9QTNxGp0BwFQJ+AgHL/Rb9z504KCwsBDf8QEfcR17s3CWvXcPDkSdbtTqZDwwZOW3v6VVfw++Z48goKmDRpEp9//rmOOYmISLmq3bQZDdt3MDuGyAU5/Qjwddddx08//YTNZqNevXo89thj3Hbbbee8f//+/QkLCwPg+++/d3YcERGnchQA67eOw+rlsk3UZ5WYmAhASEAA1atUKddri4iUVmzX7li9vQHnHgMGiI4IZ3zfPgAsXryYH3/80anri4iIiFQWTi0ALliwgC+++ALDMBg7diyJiYk89dRTDBgw4NwBLBb69++PzWZj6dKlzowjIuJUmZmZbN68GSj/479Hjx4lJSUFsA//0P4WEXEX/kFBNCvaGfHj+g0UFO1kdpZ/Dx5AWHAwAFOmTCErK8up64uIiIhUBk4tAH7wwQcANGjQgA8++ADvond7L6R169YAbNu2zZlxREScasOGDeTn5wMQ3aZduV7b0U/VYhjUDw8r12uLiJRVm972XXrHUtNYuX2nU9cO8vPjsZHDANi7dy8vv/yyU9cXERERqQycWgBctmwZhmFw3XXXlbj4B1CrVi3APl1TRKSiWrVqFWDvZxrdtm25XTcvL4+dO+0vmKNqVMe3nI8ei4iUVfPOXfD29QXgu3XOPQYMMKpTB9oX9RZ85ZVX2L17t9OvISIiIuLOnFoAPHLkCABNmjS5qMf5+fkB9gmXIiIV1Zo1awCIjGmCf5Xgcrtu0q6k4p2HDSM0/ENE3I+vvz8tOncB4KcNG8kt+pnmLIZh8MRVl2MxDHJycpg4caJT1xcRERFxd04tAFqtVoDiKZUl5ehrVbVqVWfGERFxmsLCwuICYHn3/0tMsA//CPLzI6Jq+RUeRUScKa6X/RjwqYxMlhb9XHOm5nVqM65XDwDmz5/PL7/84vRriIiIiLgrpxYAI4p2pjiOqpXUunXrAIiKinJmHBERp9m+fTunT58GoEHb8uv/d/LUSY4ePQpA48iaGBr/ISJuqlnHjvgGBADOnwbs8MBlg6keFATAxIkTNRBERERE3MbChQuZOnVq8XwNZ3NqAbBr167YbDa+/vrrEj8mIyODzz77DMMw6N69uzPjiIg4zerVq4s/blCOOwB37rC/oWIY0EDHf0XEjXn7+BDbtRsA8zdtJicvz+nXCAkI4LFRwwHYs2cPr776qtOvISIiIuIKCxcuZNq0ae5RALz88ssB+6TM9957r0SPuf322zl58iQA11xzjTPjiIg4jWMASHB4OKF1yme3ckFBAUm7kgCoHRpKgK9PuVxXRMRVWvfoCUBadjZLE7a75BqjO3WgbYP6ALz88svs2bPHJdcRERERcSdOLQAOHTqUzp07Y7PZuO2223j66adJT08/6303bNjAkCFD+OijjzAMg0GDBtGxY0dnxhERcRrHDsDoNu0wjPI5hrt3315yc3IBaBwZWS7XFBFxpZh27YuPAf+0YaNLrmGxWIoHgmRnZzNp0iSXXEdERETEnTi1AAgwd+5catasSX5+PpMmTSI8PJx77723+PYOHToQGRlJ+/bt+fnnn7HZbERFRblsi6OISFkdPXqU5ORkoHyP/+7YsQMAfx8faoVWK7frioi4irePDy062acB/7LxD6dPA3ZoGRXFNT3sx41//vln5s+f75LriIiIVEY7duzg9ttvJyYmhoCAAKpUqUJcXBzTpk0r7ot+JpvNxv/93//Rr18/wsLC8Pb2pnr16jRt2pRrr72Wzz777JzX2rhxI+PHj6dRo0YEBARQtWpVWrZsyR133MHy5cvL9HksXLgQwzCKN3CsX7+e0aNHExERQWBgIO3bt+eTTz75y+fxzjvv0LFjR4KDg6latSrDhw9n27Zt/1h75syZGIbBwIED/3HbsWPHsFgs52x1l56ejre3N4ZhkJCQQHJyMoZhMG3aNAAWLVpUnNvxZ+HChWX6twAXFACjoqJYtWpV8U7A7Oxs9u7d+5d/8CNHjmCz2bDZbHTq1Inly5dTo0YNZ0cREXEKx/RfKL8CYFpaGocPHQagUc0ILBYN/xCRyqFV0THg1KwsVmzf4bLrPDRsKKFBgQBMmDCB7Oxsl11LRESksnj33Xdp0aIFb7zxBjt27MAwDHJycti0aRNTp06lTZs2JCUl/eUx119/Pddddx0LFizg+PHjBAQEkJGRQWJiIh999BH33XffWa81depU2rZty3vvvUdSUlJx0Sw+Pp7XX3+dO+64w2mf1/fff0+XLl346quvyMnJITMzk3Xr1jF27FheeeUVbDYb11xzDTfffDMbN26ksLCQ06dP8+2339K9e3d27dr1l/V69eoFwLJly8j/2xuaixYtwmazAfbXkpmZmX+5fenSpeTn51OzZk2aNm2K1WotLkoCeHt7ExER8Zc/Pj5lbwfl9AIg2IuAy5cv55tvvmHUqFFUr169uOBns9kICgpiyJAhfPrpp6xYsYJatWq5IoaIiFM4CoDevr7Ubta8XK555jT1hjVrlss1RUTKQ9MOHfDx8wPgx/UbXXadkMAAHhkxDIDk5GRee+01l11LRESkMvjxxx+5+eab8fb25oknnuDQoUNkZGSQmZnJsmXLaN++Pbt372bUqFEUFhYCsGTJEv7v//4Pi8XCCy+8wKlTpzh9+jRZWVkcOXKEuXPnMmjQoH9c66WXXmLatGnYbDauu+46EhMTSU9P5+TJk5w4cYL//e9/dOnSxWmf27hx4xg3bhyHDh3i1KlTHD16lOHD7YPDJkyYwJQpU/juu+/4v//7P9LT00lLS2PJkiXUrFmTlJQUJkyY8Jf1OnToQGBgIOnp6axdu/Yvtzl26wUHB5Obm/uPnYyO2x1FxKioKA4fPsyDDz4I2AfsHj58+C9/unbtWuZ/A5cUAB0uu+wyPv/8c44ePUp6ejr79+/n1KlTpKam8t133zFmzBhXXl5ExCkcBcC6rVrj5YR3Xi6k0FZYXACMCAmhir+fy68pIlJefHx9ad6pM2A/BpxfUOCya13RpRNt6tcD7C809u3b57JriYiIuLOCggLuvvtubDYbc+bMYdKkSdQs2ojg5eVF165d+eWXX4iMjOSPP/7g66+/BmDFihUA9O/fn/vvv5+QkBAADMMgPDycK664grfffvsv10pJSWHixIkA3H333cyePZuYmJji20NDQxk7diyvv/660z6/Nm3a8M477xAREQFAWFgYH330EcHBwaSnp/Pkk0/y2muvce211+Lj41N8fPfZZ58F4JtvviEvL694PS8vL7p1s7cb+fvx3EWLFgHw73//+7y39+7d22mfX0m4tAB4poCAAGrVqkVwcHB5XVJEpMxyc3PZtGkTYB8AUh4OHDhAVlYWYD/+KyJS2TiOAZ/MyGDljp0XuHfpWSwWpl91OYZhkJWVpYEgIiIi57Bo0SJ27dpFw4YNGTly5FnvExoaWrybb968eQDFNZ5jx44V7wq8kM8++4yMjAyCgoJ46qmnnJD+wh599NF//F1gYCCdO9vflKxTpw7XXnvtP+7Tt29fALKzs4t7tDs4dvCdWeA7fvw48fHxxMTEMHbs2H/cnpGRUbxj0PH48lJuBUAREXe0efNmcnJyAKjfpm25XHNHUU8sHy8v6lQPLZdrioiUp2YdOuLt6wvATy48BgzQql5dru5uPzbz448/Fr9gERERkT85jqnu37+fmjVrnvPP3LlzAdi7dy9gL5D5+Piwfv16evXqxYcffsj+/fvPey3HrsEePXpQpUoVF35Wf4qNjT3r34eHhwPQvHlzLJZ/lsgcOwYBTp48+ZfbHDv4zuwD6Oj/17t3b5o3b054ePhf+gA6+v9FRETQrFmzMn9eF8OrNA+aPn26s3MUmzJlisvWFhG5WGcOAIlu6/oCYGZmJvsP2H9hRoeHYT3LLyEREXfn6+9P0w4d2bx0CT9v/IPpV13u0p93Dw8fyk8bNpKSnsGjjz5K9+7dCQgIcNn1RERE3M2hQ4cAyMnJ4ciRIxe8v6Og1bhxY9544w3uuusuli5dytKlSwH7jrpLL72UG2+88R+TcB3r16tXz5mfwnlFRkae9e+tVmuJbgf+cgQY/tkHsHPnzsW7/RzFwV69evHZZ5+xfPly+vXr94/+f+WpVAXAqVOnFk/1dTYVAEWkIlm9ejUAYfXqU6W666eVJyUlgX1gFA11/FdEKrHWPXqyeekSjqelsWZnEp1jGrvsWlUDA5k0eiT3z57Dvn37eOGFF5g8ebLLriciIuJuCop68g4YMICff/75oh574403Fg96/f3331m2bBn79+/nvffe47333uP2229n1qxZrohtKm9vb7p27cr8+fNZuHAhnTt3/kd/v969e/PZZ5+xcOFC+vXrV3y7GQXAUr/VeuZU33P9udD9/n67iEhFYrPZincAlsfxX5vNxo6d9uO/1asEUVW7U0SkEmvesRNe3t4A/Lhhk8uvN6pTBzo3bgTArFmzSEhIcPk1RURE3IXjqKvjaO/FCg8P56677uKLL77g8OHDbNy4kXHjxgHw+uuv8+OPPxbf1zFcZM+ePWVMbb4z+wCeOHGCLVu20KRJk+IdhX369Cm+/cz+f+U9AARKuQPw999/P+/tr7zyCl9++SUWi4VLL72Uvn370qhRIwIDA8nIyGDnzp0sWLCAefPmUVhYyKhRo7jrrrtK9QmIiLjKgQMHOHz4MADRbV0/AOTw4cOkp6UDGv4hIpWfX2AgTdp3IH7Fcn7asJGpl486a+8dZzEMgyfHXsGgp54hLz+fBx98kG+//dal1xQREXEXXbva++UmJCSQlJREw4YNy7Re69at+fDDD9m4cSObN29m4cKFDB48GIAuXbrwwQcfsGTJEtLS0sqtD6ArnNkHcMGCBcX9/xyaNWtGREQEa9asYf78+eTl5REeHk7z5s3/sZbjOYmrNsiVqgB4vq2K9913H1999RXNmjXjk08+OWejxfvvv58tW7Zw5ZVX8uWXX1K3bl1eeOGF0sQREXGJv/T/K4cdgI6pUl5WC3VruP64sYiI2Vr36En8iuUcPZ3Kut3JdGjYwKXXaxxZk1v79+XVn+exatUqPv74Y6655hqXXlNERMQdXHLJJdSrV489e/Zw33338fXXX5/zTbK8vDxycnIICgoiNzcXHx+fc67r5+cHUDxYEWDMmDHcf//9pKenM3HiRF5++WXnfjLlqGPHjgQEBJCenl5c0/r77r5evXrx6aef8vTTTxf//9k4JiqfOnXKJVmd+pbn/PnzeemllwgNDeW33347Z/HPoWXLlvz2229Uq1aNF198kV9//dWZcUREysRRAPQNDCQypolLr5WTk1O83b5eWBjeZzSbFRGprFp07oLVy/5+tKunATvcPehS6taoDsC0adM4ceJEuVxXRESkIvP29mbWrFlYLBa+++47BgwYwMqVKyksLASgsLCQrVu3MnPmTGJiYti4cSMAd955J2PHjuWbb74hJSWleL0TJ04wefLk4tdUgwYNKr4tNDSUJ598ErCfIL3hhhuKN0MApKSk8N577zF+/HhXf9pl5u3tTZcuXYA/+8f/vQDo+H/H7ecqALZs2RKArVu3smrVKqdndWoB8I033sAwDMaPH/+XUcnnExERwfjx47HZbLz55pvOjCMiUibF/f/i2mBxcUFu165dxb9cdfxXRDyFf1AQMUUtFn7csLH456Ar+fn48MRVlwNw8uRJpk2b5vJrioiIuIPBgwczZ84c/P39+fXXX+nSpQsBAQHUqFEDPz8/WrRowWOPPUZycnLxYNi8vDw++eQTRowYQfXq1QkODiYkJIQaNWoUF/nuvPNOBg4c+Jdr3XvvvTz22GMAzJ49m5iYGKpUqUK1atWoXr0648ePZ926deX7D1BKZxb8mjRpUtzj8Gy3n+3/z/z7xo0bk5+fT+fOnalevTr169enfv36rFy5ssw5nVoAdDQzjIuLu6jHtWnTBvizGioiYrbMzEy2bNkClM8AEMc7XlUDAwgNCnL59UREKorWPXoCcOjkKTbtKV3j8YvVu0VzhrazP//8+OOPWb58eblcV0REpKIbO3YsO3bs4NFHHyUuLg5fX19OnTpFlSpV6Ny5M/fffz9Lly6lW7duAEyePJkXX3yRYcOGERMTA0BWVha1a9dm1KhR/Pjjj7z66qtnvdaMGTNYtWoV48aNo169euTl5WEYBrGxsdx5551us0nszILe2Yp7zZo1Ky4KhoWF0aJFi7Ou4+XlxYIFC7jhhhuoW7cuaWlp7Nmzhz179pCdnV3mnKXqAXguR48eBf56trskHPd3PF5ExGwbN24kPz8fgOg2rh0AcuzYseI+Dw0jIjBcejURkYqlRZeuWKxWCgsK+GH9RtpE1y+X604ZM4qF8VtJz87h4Ycf5rfffjtvDyMRERFPUbt2bZ5++uninnXn07BhQ+655x7uueeeUl2rY8eOfPjhh6V67IX07t37ggM1PvjgAz744IPz3udCa3Tv3v2C9zl06NB5b3eIiori/fffL9F9L5ZTdwBWq1YNgEWLFl3U4xz3r1q1qjPjiIiUmmNHM9iPALuSY/efxTCoHx7m0muJiFQ0gcHBNC76OfvLxk0um3z3dxFVQ3hw2FAAEhMTef3118vluiIiIiJmcGoBsHPnzthsNubMmcOKFStK9JiVK1cyZ84cDMOgc+fOzowjIlJqjv5/NRs1JiAkxGXXycvLIzk5GYCoGtXx9XLqxmwREbcQ2607AHuPnyDxYMneIXeG63r1ILZuFAAvvPACe/bsKbdri4iIiJQnpxYAb731VgAKCgoYMGAAb7zxBnl5eWe9b15eHm+++SYDBw4sPmZ3++23OzOOiEip2Gy24gJgdFvXHv9NTk4u/hmo4R8i4qlaFE3PA/hl0x/ldl2rxcLTV1+JxTDIysrikUceKbcdiCIiIiLlyalbTQYMGMD48eN59913ycjI4M4772TChAl069aNRo0aERAQQGZmJjt37mTZsmWcPn26+EnW+PHjufTSS50ZR0SkVHbv3s2JEycA1w8A2b59OwBBfn6Eu3CnoYhIRRZSvQb1mjVjz7Zt/LLxD+4ZPPDCD3KS2Hp1ua5XDz5YuJgFCxbw7bffMnz48HK7voiIiJxfhw4d2LdvX4nv37VrV7788ksXJnJPTj9r9tZbbxEQEMCrr76KzWbj1KlT/Pjjj/+4n6PwZxgGd999N//973+dHUVEpFQcu/8AGrhwB+CJlBPFhcZGNTX8Q0Q8W8uu3dizbRvx+/az/0QKdaqHltu1Hxg2hB83bOTo6VQmTJhAr1691JtaRESkgjh27BhHjhwp8f1TUlJcmMZ9OfUIMNgLei+99BKLFy9mxIgR+Pj4YLPZ/vHH19eXkSNHsmTJEl588UUMQy99RaRicBQAA0JCCItu4LLr7Nj+5/CPBhHhLruOiIg7iO3avfjj+Zs2l+u1g/39mX7l5QAcPXqU6dOnl+v1RURE5NySk5PPWlc615+FCxeaHblCclm3+W7dutGtWzdyc3PZtGkTBw8eJD09naCgIGrXrk2rVq3w8fFx1eVFRErNMQG4fpu2WCxOf58EsPdB3bV7FwB1qofi5+3tkuuIiLiL8KgoIurW5cjevfy8aRM3XtKrXK8/qE1rBrRuxS+b/uD//u//GD16NN26dSvXDCIiIiKu4vJxkz4+PnTo0MHVlxERcYq0tDS2bt0KuHYASHJyMvl5juEfNV12HRERd9KyazeO7N3L6h1JnEzPoFpQYLlef/pVY1ieuJ207GweeOABFi5ciJ+fX7lmEBEREXEF12xtERFxU+vXry/uURrtwgEgZw7/iKga7LLriIi4k5ZFx4ALbTYWbN5S7tevWbUqj44cBkBSUhL/+c9/yj2DiIiIiCuoACgicgZH/z/DYqFeqziXXOPEib8P/1APVBERgKiYGEJq1ADgl01/mJLh6u5d6dDQ3v/1lVdeKd4VLiIiIuLOVAAUETnD6tWrAajVpCm+ga45erZjh4Z/iIicjcVioWWXrgAs3ppAVm6uKRmevuYqfLys5Ofnc//991NQUFDuOUREREScSQVAEZEihYWFrFu3DnBd/7+8vDx27dLwDxGRc2nZ1T54Izsvj0Vbt5mSoXFkTe4ccCkA69at47333jMlh4iIiIizuHwIiIiIu9i+fTupqamA6wqAu3fvJj9fwz9ERM6lUes4/AIDyc7IYN7GzQyMa21KjtsH9OP79RvYcegwTz31FIMGDaJOnTqmZBERkYrrQII5b1aVREXOJuVPBUARkSKO/n8A0W1cUwDcvkPDP0REzsfq5UXzTp1Z/9sCft28hfyCArys1nLP4evtzcxrrmLMCy+RkZHBww8/zEcffYRhqG+riIj8ae7kCWZHECkRHQEWESniKABWqRFG9agop69/4sQJUk6kABr+ISJyPrHd7NOAT2dmsmpHkmk52jdswLU97EeS58+fz9dff21aFhEREZGyUAFQRKSIowAY3aatS3Z4OHb/afiHiMj5NW3fAa+iHqnzTJoG7PDIiMuoWTUEgIkTJ3Ly5ElT84iISMVgs9nc6o+ICoAiIkBKSgo7d+4EILptW6evn5eXx+5duwGoU726hn+IiJyHr78/MUW9WOdt2mzqC5cq/v48cdXlABw7doypU6ealkVERESktFQAFBEB1q5dW/yxKwaAnDn8o3FkhNPXFxGpbBzHgA+ePMmWvftMzXJp61YMbhsHwP/+9z+WLFliah4RERGRi6UCoIgIfxYArd7eRLWMdfr627fbj/9W8fcjPCTE6euLiFQ2LTp3wbDYn6r+smmzyWlg6hWjCfb3B+D+++8nKyvL5EQiIiIiJacCoIgIf/b/q9O8Jd6+fk5d+8SJE6SknDn8Q0RELiSoalXqN28OwILNW0xOAxEhIUwYNRyA5ORknnvuOZMTiYiIiJScCoAi4vHy8/NZv349YB8A4myO3X8a/iEicnFadO4CwNb9BzhQ9EaKma7q1oXOMY0AmDVrFps2bTI5kYiIiEjJqAAoIh5v69atZGZmAs7v/5eXl8fu3fbhH1E1quPrpeEfIiIl5SgAAizYHG9iEjvDMHjmmrH4entTUFDAvffeS15entmxRERERC5IBUAR8XiO478A9Z28A3DX7l3Fwz8a1dTwDxGRixEeVZfqtWoB8Osf5h8DBqgfHsb9QwcBsGXLFmbNmmVyIhEREZELUwFQRDyeYwBItchaVIuMdOra2xM1/ENEpLQMw6BFJ/suwBXbt5ORnWNyIrt/9e1Dy6g6ADz33HMkJSWZnEhERETk/FQAFBGP59gB6Ozjv8ePH+fkyZMANKpZU8M/RERKoXnnzgDk5hewJCHB5DR2XlYrz4wbi9ViIScnh/vvv5/CwkKzY4mIiIickwqAIuLRjhw5wp49ewDnH/9NTEwENPxDRKQsGrSMxS8gEKgYfQAdWkZFcUu/SwBYvnw5c+bMMTmRiIiIyLmpACgiHs1x/BecuwMwJyeH3cn24R/1wmrg6+XltLVFRDyJl7c3TTt0AOD3LfEVaqfdvUMGEh0eBsDUqVM5dOiQyYlEREREzk4FQBHxaI7jv95+ftRp1txp6+7cuZPCAvuL1Jhazu0rKCLiaZp3sh8DPpaaxqY9e01O8yc/Hx9mXnMVAGlpaTzyyCPYbDaTU4mIiIj8kwqAIuLRHAXAurGtsHp7O2VNm81G4nb78d/QoEBCg4Kcsq6IiKdq1rEjhsX+tLWiTAN26BzTmKu7dwXgp59+4rvvvjM5kYiIiMg/qQAoIh4rJyeHTZs2ARDdxnnHfw8ePEh6WjoAjSM1/ENEpKwCg0OIbt4CgAWbK1YBEODRkcMIDwm2f/zoo8UDoEREREQqChUARcRjbd68mZycHMC5A0Acu/+8rVbqhYU5bV0REU/mmAa87cBB9p9IMTnNX4UEBPDkVVcAcOzYMR5//HGTE4mIiIj8lQqAIuKx/joAxDkFwPT0dPbv3w9Ag4hwvCz6MSsi4gwtOncp/vi3LRVnGrDDgLhWDG4bB8DHH3/MokWLzA0kIiIicga9MhURj7V69WoAwurVp0r1Gk5Zc8eOHVDU/71xZE2nrCkiIhAeVZfqtWoBFa8PoMO0K8YQEhAAwAMPPEBGRobJiURERETsVAAUEY9ks9mKB4A46/hvQUGBvQAI1KwaQrC/v1PWFRERMAyDFp3suwBXbN9ORnaOyYn+KTwkmEmjRwCwZ88ennnmGXMDiYiIiBRRAVBEPNKBAwc4fPgwANFtnTMAZO/evWRnZwPa/Sci4gqOY8C5+QUs2ZZgcpqzu7xLJ7o1iQHgzTffZMOGDSYnEhEREVEBUEQ8lGP3H0C0k3YAJibah3/4+/hQOzTUKWuKiMifGsTG4hcQCMCvFXAaMNh3Ks685ir8vL0pLCzkvvvuIy8vz+xYIiIi4uFUABQRj+QoAPoGBhIZ06TM6508eZKjR48C0CgyAothlHlNERH5K6uXF007dADgt83xFBYWmpzo7OqG1eCBYUMAiI+P55VXXjE5kYiIiHg6FQBFxCMV9/+La4PFai3zetu3bwfAMKBRRESZ1xMRkbNr3qkzAMfT0li/O9ncMOdxU59etKpXF4AXXnihuEesiIiIiBlUABQRj5OZmcmWLfajY84YAJKXl0dSUhIAUdWr4+/jU+Y1RUTk7Jp17IhhsT+Fnb/xD5PTnJuX1coz147Fy2IhNzeX++67r8LuWBQREZHKTwVAEfE4GzduJD8/H4DoNmUfALJr167i9TT8Q0TEtQKDQ6jfrDkAv1XQPoAOzevU5tZL+wGwatUqZs+ebXIiERER8VQqAIqIxzlzAEj9uDZlXs8x/CPY35/wkJAyryciIufXrGNHAP7Ys5ejp1NNTnN+/x48gIYR4QBMnz6dgwcPmpxIREREPJEKgCLicdauXQtAzUaNCShjwe7IkSOcOnUKgMa1aqLRHyIirte0Q8fijxfFbzUxyYX5eXsz85qxAKSnp/PQQw9hs9lMTiUiIiKeRgVAEfEoNputuADojP5/CYkJAHhZLUSHh5d5PRERubDaDRsRHFodgN+2VOwCIEDHxg25tmd3AObNm8fXX39tbiARERHxOCoAiohH2b17N8ePHwcguowFwIzMDPbu2QtA/bAwfJwwTVhERC7MMAyaFh0DXrItgfyCApMTXdijIy6jZlX7rvMJEyaQkpJiciIRERHxJCoAiohHcez+g7LvANyeuL34GFeTWpFlWktERC5Os46dAEjNymL9rmRzw5RAFX9/nhp7BQDHjx9n8uTJJicSERERT6ICoIh4FEcB0D84mIiGjUq9TkFBATt27AAgIiSEkIAAp+QTEZGSiWnbFkvRzuvf4+NNTlMy/VrFclk7+5tPn376Kb/99pvJiURERMRTqAAoIh7FMQG4Xus2WCyl/xGYnJxMdnY2AE1qa/efiEh58w8MokHLlgD87gZ9AB2mXjGaqoH2N40efPBB0tPTTU4kIiIinkAFQBHxGOnp6Wzdan+RWNb+f9sStgEQ6OtL7dBqZc4mIiIXr3mnzgBsO3CQw0UT2Su6GsFVmDJmFAD79u3j6aefNjmRiIiIeAIVAEXEY2zcuJHCwkKgbP3/jh49SsoJe/P2mFo1MTCckk9ERC6Oow8guNcuwFGdOtCzWVMA3n777b/0pxURERFxBRUARcRjOI7/GoZB/bi4Uq+TkJAAgNVioWFEhDOiiYhIKURGR1M1LAyA3+PdpwBoGAYzrrkSfx8fbDYb9913H7m5uWbHEhERkUpMBUAR8RiOHRY1GzXGv0pwqdbIzMxkz549AESHh+Hj5eW0fCIicnEMw6Bp0S7AZQmJ5Obnm5yo5KKqV+ehYUMA+xtLL7/8ssmJREREpDJTAVBEPILNZmPdunVA2Y7/Jm5PxGazARBTS8M/RETM1qxDRwDSs3NYm7TL5DQX54Y+vYirXw+A//znPyQmJpqcSERERCorFQBFxCPs2rWLEydOAKUvABYUFLBj+w4AwkOCqRoQ4LR8IiJSOo3btMVatBvbnfoAgr2VxDPXjsXLYiEvL4/77ruPgoICs2OJiIhIJeRRZ9dOnz7N559/zurVqzlx4gS+vr40bNiQwYMH07lz51Kvm5+fz/fff8+iRYs4ePAgALVr16ZXr14MGTIEr3McETxy5Ahbt25l586dJCUlsWvXLrKzswH49ttvS51HRP7pzAbrpZ0AnJycXPw92qRWLafkEhGRsvELCKBBbCt2bFjP7/FbmTh6hNmRLkrT2rW4Y2B/Xv7xF9asWcN7773HzTffbHYsERERqWQ8pgC4d+9eJk6cyOnTpwHw9/cnIyODjRs3snHjRi677LJSPdnKyspi8uTJbN++HQAfHx8Adu7cyc6dO1m2bBnTp0/Hz8/vH4/9+OOP+e2338rwWYlISTkKgP7BwYQ3aFiqNbYlbAMg0NeXOtWrOS2biIiUTbMOHdmxYT07Dh1m/4kU6lQPNTvSRblr4KX8uH4jOw8f4cknn2TQoEHUqVPH7FgiIiJSiXjEEeC8vDyefPJJTp8+Tb169XjppZeYO3cuc+fO5dprr8UwDL777jt+/fXXi1571qxZbN++ncDAQB577DE+++wzPvvsMx577DECAwNJSEjg9ddfP+tjDcMgMjKSHj16cMMNN3DllVeW9VMVkXNwTACuH9cGi+Xif/QdO3aMlBMpADSOrImB4dR8IiJSes06diz+eKEbTQN28PX25plrx2IYBpmZmTz44IPF/WZFREREnMEjCoC//PILhw8fxtfXlylTphAdHQ2Ar68vV1xxBYMGDQJgzpw55F/E9Ljdu3ezePFiAO6++266dOmCYRgYhkGXLl246667AFi4cGHx1NAz3XXXXbz55ps89NBDjBo1ioYNS7crSUTOLz09nW3b7Lv36rdpV6o1HI+3Wiw0rBnhtGwiIlJ24VF1CY2oCbhfH0CH9g0bcF2vHgAsWLCAL774wuREIiIiUpl4RAFw4cKFAPTs2ZOwsLB/3D569GgMwyAlJYXNmzeXeN1FixZhs9mIjIykS5cu/7i9a9euREZGYrPZWLRo0T9ut1qtJf8kRKTUNmzYQGFhIVC6/n+ZWZnFRfz64WH4nqOvp4iImMMwjOJdgMsSt5Odl2dyotJ5ePhQalWzt5iYOHEix48fNzmRiIiIVBaVvgCYlZXFjh32qZ1t2579hX9YWFhxn5VNmzaVeO0//vgDgDZt2mAY/zwOaBgGbdq0+ct9RaT8OY7/GoZBvdZxF/34xITE4qNYTWpFOjOaiIg4SdMO9gJgVm4uq3fsNDlN6QT5+fHU1VcAkJKSwqRJk0xOJCIiIpVFpS8A7t+/v/iFe7169c55P8dt+/btK9G6NpuN/fv3X3DdunXrXtS6IuJ8jgEgNRvH4F+lykU9Nj8/n8TtiQBEhIRQNSDA6flERKTsGrWOw+rtDcCirQkmpym9S1q2YHgHe7uKL774olQ9qkVERET+rtIXAFNSUoo/Dg0990Q4x20nT54s0bpZWVlkZ2eXeN2srCyysrJKtLaIOI/NZmPdunVA6Y7/Ju1KIjcnF4CmtWs5NZuIiDiPr78/DVrGArDYjQuAAI9fPopqgYEAPPbYY3oOKSIiImVW6RtZOYp0YB/6cS6O20r6BOvM+5VkXcdj/P39S7T+xZozZw7/+9//znn72LFjufrqq11ybcdEVYvFQrWivjVScTmOq4eEhHjEhMHt27cXvxHQqEPH836//p3NZiNhm/1FZLC/P1E1qp/1uH95Uu9Q92ItxcRpMZ++z9zLmd9nzTp0ZMeG9Ww/dIgTGZnUCnXP5yW1fH2ZcsVo7nv/Q5KTk3nzzTeZNm2a2bHKTM8Z3Y+nPW+sDPR9JiLnUukLgJ4iIyODo0ePnvP2zMxMl7+gMQxDL5rciMVDChOrV68u/rhh+w4XVcDbt28fp0+fBqBZVG0Mi7nFP0y+vJSCvmbuR18z93PG16xphw58+9YbACyK38rVPbubFKrsrurelY+XLmP1jiSee+45rrvuOmJiYsyO5RR6zuh+POV5Y2Wi7zMR+btKXwD08/Mr/jgnJ4eAc/TvysnJASjxDr0z7+d47PnWvZi1SyMwMJDw8PBz3h4QEEBBQYFLrm2xWDAMA5vNVjxpVSouwzCwWCwUFhZ6xDu5y5cvByAgpCrh0Q0u6nN2DO/x8fKiQXgEmPnPZWDu9eXi6WvmfvQ1cz9/+5rVim5AcPXqpJ44we9b4hnbo5tp0crKMAyeGXcN/aY+SW5uLnfccQc///yz6TvRy0LPGd2Ppz1vrAwqy/eZipcizlfpC4Bn9udLSUk5ZwHQcUSwpNuk/f398ff3Jysr6y99Bs+1ruP+rnLttddy7bXXnvP248ePl7i/4cWqVq0aVquVwsJCl11DnMdqtVKtWjVOnz7tsqJwRbJs2TIA6sfFkZeXV+LHpaSkcPDgQQAaR9bEwGbav9eZT4A84WtWKRgGVquFgsJC0Asmt6DvMzd0ju+zJm3bsWb+PBbFbyMzK8utj+I3CKvBTZf05u1ff2PBggW8//77jBw50uxYpabnjO7H0543VgaV5fusRo0aZkcQqXTc9xlRCdWpU6f4ndK9e/ee836O26Kiokq0rmEY1KlTx+nriojzpKens23bNgDqX+QAEMfjLIZBTGRNp2cTERHXaNK+AwCnMzP5Y8+5n6O5i3uHDKRm1RAAJk+eTFpamsmJRERExB1V+gKgv78/jRs3BmD9+vVnvc/x48fZt28fAK1bty7x2q1atQJgw4YN57zPxo0b/3JfESk/69evLz76EN2mXYkfl5mVye7duwGoF1YDfx8fl+QTERHni2nbrvjN38Vbt5mcpuyC/Px4/PLRABw5coSZM2eanEhERETcUaUvAAL07t0bgMWLF3Ps2LF/3P7ll19is9kIDQ0lNja2xOv27NkTwzA4ePAgK1as+Mfty5cv5+DBgxiGUZxBRMrPmjVrAPuO3bqtSl7cT0xMLC4cNq1dyyXZRETENYJCQqjT2D4sY9HWBJPTOMegNq3p1bwZAO+88w6bN282OZGIiIi4G48oAA4YMICaNWuSnZ3NE088UbyzJycnh88//5wffvgBsPfR8/L6a1vEf/3rXwwbNowXX3zxH+tGR0fTs2dPAF555RVWrlyJzWbDZrOxcuVKXn31VcBegKxbt+4/Hp+fn09qamrxn6ysrOLbzvz71NRUp/w7iHiatWvXAhAZ0wT/KlVK9Jj8gny2J24HICIkhGqBgS7LJyIirtGkXXsANibv4XRmpslpys4wDJ64agy+Xl4UFhby8MMPu3VzfxERESl/lX4ICIC3tzeTJk1i4sSJJCcnc8899xAQEEB2dnbxk6ehQ4fSr1+/i177jjvu4NChQ2zfvp0ZM2bgU3RUMDc3F4CmTZty++23n/Wx27ZtY+LEiWe97e8DPb799tuLzibiyWw2G+vWrQMurv/frqRdxdO7tftPRMQ9Ne3QgV8//oiCwkKWJWxncNs4syOVWb2wMO4c2J//fP8Ta9eu5aOPPmLcuHFmxxIRERE34RE7AAHq1q3LK6+8wvDhw4mMjCQvL4/AwEBat27NhAkTuOWWW0q1rr+/PzNnzuSmm26iYcOGWK1WrFYrDRs2ZPz48cyYMQM/Pz8nfzYiciFJSUnFk8+iS1gAtNlsbN22FYAq/n7UCq3qqngiIuJC9Zo2wy/AvoN78bbKcQwY4NZL+1E/LAyA6dOnc+LECZMTiYiIiLvwiB2ADlWrVmX8+PGMHz++xI955513LngfLy8vRowYwYgRIy4qT2xsrHb2ibiIo/8flHwH4MGDB0k9bT9y37R2LQwMl2QTERHXsnp50bhNGzYvW8rirduw2WzFg0HcmZ+3N09cNYZxr7zOqVOnePrpp3n++efNjiUiIiJuwGN2AIqIZ3H0/wuoWpXw6AYleszWrfbdfz5eXkSHh7ssm4iIuJ6jD+CBlJMkHTlqchrn6dm8GQPj7IOtPvzwQzZt2mRyIhEREXEHKgCKSKXkKADWj2tTol0fKSkpHDp0CIDGkTXxsujHo4iIO2vavkPxx4u3bjMxifNNGjMCX29vbDYbjz32GDabzexIIiIiUsHpFa6IVDppaWls22Z/sVfS/n/x8fEAWAyDmMiaLssmIiLlI7RmTcLq1AFg0dbK0wcQIKp6dW6/tC9gb3nx+eefm5xIREREKjoVAEWk0lm/fn3xboiS9P9LT08nOTkZgOjwMPyLpnmLiIh7a9LOvgtw5fYdZOflmZzGuW6/tB91QkMBmDZtGunp6SYnEhERkYpMBUARqXQcx38Ni4V6reIueP+tW7cWFwyb1antymgiIlKOmra39wHMzstj7c5dJqdxLj8fHyaNGQnAkSNH+M9//mNyIhEREanIVAAUkUrHUQCMjGmCX1DQee+bk5PDzp07AahTPZRgf3+X5xMRkfLRsFVrrN7eACyqZH0AAQbGtaJbkxgA3njjjeLfZyIiIiJ/pwKgiFQqNpuNdevWASXr/5eQmEB+fj4AzbX7T0SkUvH196dBi5YALN5WufoAAhiGwdQrR+NlsZCXl8fEiRM1EERERETOSgVAEalUkpKSOHnyJHDh/n/5+fkkFL0gDAsOpkaVKi7PJyIi5atJ0THghAMHOXLqtMlpnC8mMpLr+/QE4LfffmPevHkmJxIREZGKSAVAEalU1qxZU/zxhXYAJiUlkZOTA2j3n4hIZeUYBAKVcxcgwL1DBhW/iTVp0iSys7NNTiQiIiIVjQqAIlKpOPr/BVarRlj96HPer9BWSPzWeACCA/ypFVq1POKJiEg5q9WgAVWKpuUuroR9AAGC/f15ZMRlACQnJzNr1iyTE4mIiEhFowKgiFQqjgJg/bg2GIZxzvvt3bOX9LR0wL77z+Dc9xUREfdlGAZN2rYDYMm2RAoKC01O5BpjOnekTf16ALz00kscPnzY5EQiIiJSkagAKCKVRlpaGtu22Xd3XKj/35b4LQD4+/hQLyzM5dlERMQ8TdrbjwGfzMggft9+k9O4hsVi4fErRgOQmZnJU089ZXIiERERqUhUABSRSmP9+vXF0w/P1//v0OFDpJxIAaBp7VpYz7NTUERE3F/MGb8TllTSPoAAbaLrM7yDfbfj3Llz2bRpk8mJREREpKJQAVBEKg3H8V/DYqFeq7hz3m/LZvvuP2+rlUY1I8ojmoiImKhKtWrUatAQsB8DrsweGXEZvt7e2Gw2Jk+eXPzGmIiIiHg2FQBFpNJwTACu1aQpvoGBZ71PSkoKhw4dAqBxZE28rdZyyyciIuaJKeoDuG7XLrJyc01O4zq1Q0O5pd8lAKxYsYIffvjB5EQiIiJSEagAKCKVQmFhIevWrQPO3/9vS7x98q/FMGhSK7JcsomIiPkcg0By8wtYtWOnyWlc6/ZL+xEeEgzAtGnTyMnJMTmRiIiImE0FQBGpFJKSkjh16hRw7v5/qampJCfvtt8nPAx/H5/yiiciIiaLjo3Fy9sbqPzHgAP9fHlo2FAAkpOTeffdd01OJCIiImZTAVBEKgXH8V849w7A+Ph4KGqF1DyqTnnEEhGRCsLH15folrEALE2o3AVAgDGdO9Ki6HfdCy+8wPHjx01OJCIiImZSAVBEKgXHAJDAaqGE1av/j9szMjJISkoCoF5YDar4+ZVnPBERqQBi2trfIEo4cJCjp1NNTuNaFouFyWNGAvYd8M8++6zJiURERMRMKgCKSKXgKADWj2uDYRj/uD0+Pp7CwkKA4h0RIiLiWRx9AMEzdgF2iWnMgNatAPjwww9JTKz8n7OIiIicnQqAIuL2UlNTSUhIAM7e/y8rO4sdO3YAUKd6KFUDAso1n4iIVAy1GjYiMCQEgKWVvA+gw4RRw/G2WikoKGDKlClmxxERERGTqAAoIm5v/fr12Gz25n5n6/+3bes2CgoKAO3+ExHxZBaLhcZxbQBYkpBQ/LujMqsfHsb1vXsC8Ntvv7FgwQKTE4mIiIgZVAAUEbfnOP5rWCzUa9X6L7fl5OaSkGjfHVizagjVg4LKPZ+IiFQcMUXHgI+eTmXHocMmpykf/x48gGqBgQBMmzat+E0xERER8RwqAIqI23NMAK7VpCm+RS9wHBIStpGflw9o95+IiECTdn/2AVyyLcHEJOUnJCCAe4YMBGDbtm3MnTvX5EQiIiJS3lQAFBG3VlhYyLp164B/9v/Ly8tj27ZtANQIrkJ4Ud8nERHxXNXCIwirY39DaIkHDAJxuKZHN+qF1QBg5syZZGZmmpxIREREypMKgCLi1nbu3Mnp06cBqN+m3V9u2759O7k5uQC0jKrDP2cDi4iIJ3IcA161Yye5+fkmpykfPl5ePDx8KACHDh3i7bffNjmRiIiIlCcVAEXErTmO/8JfdwAWFBQQvzUegGqBgURWq1bu2UREpGJqUlQAzMzJZf2u3SanKT9D2rahdb26ALz00kucOHHC5EQiIiJSXlQAFBG35hgAElgtlBr16hX//c6dO8nOygbsvf+0+09ERBwatm6NxWJ/Grxkm+ccAzYMgwmjhgOQlpbGf/7zH5MTiYiISHlRAVBE3JqjABjdpi2GYS/zFRYWsmXLFgCC/f2JqhFqWj4REal4/AODqNu0GQBLPagPIEDnmMb0jW0BwPvvv09ycrK5gURERKRcqAAoIm4rNTWVxET7C7f6Zxz/3bVrFxkZGYBj95/2/4mIyF81adcegD/27OV0hmcNxHh0xDAshkFeXh4zZswwO46IiIiUAxUARcRtrVu3DpvNBvzZ/6/QVsgfm/8AINDXt3jioYiIyJkcg0AKbTaWJW43OU35iqkVyRVdOwPw1VdfsWHDBpMTiYiIiKupACgibstx/NditVK3VWsAdu/aTXpaOgAt69bBYmj3n4iI/FPdpk3xCwgEYMm2BJPTlL/7hw7Gz9sbgGnTphW/oSYiIiKVkwqAIuK2HBOAazVpim9AAIW2Qjb9sQmw7/6LDg83M56IiFRgVquVRq3tbx550iAQh4iqIfyrbx8Ali1bxq+//mpyIhEREXElFQBFxC0VFhaybt064M/+f9r9JyIiFyOmnf0Y8L4TJ9hz7JjJacrfbZf2JTTIvgvyiSeeoKCgwOREIiIi4ioqAIqIW9qxYwepqamAvf+fdv+JiMjFcvQBBM/cBVjF3597hgwCYNu2bXz66acmJxIRERFXUQFQRNyS4/gvQP027bT7T0RELlpY7TpUK3rDyBMLgABXd+9K3RrVAXj22WfJyckxOZGIiIi4ggqAIuKWHANAgkKrExpVR7v/RETkohmGUbwLcHnidgoKC01OVP58vLy4/7LBAOzfv5/Zs2ebnEhERERcQQVAEXFLjgJg/TZtSd6drN1/IiJSKo4CYGpWFn/s2WtyGnMMb9+OprVrAfDf//6X9PR0kxOJiIiIs6kAKCJu5/Tp0yQm2o9q1W/TRrv/RESk1Bq3aYtR9MaRpx4DtlgsPDRsCADHjx/nzTffNDmRiIiIOJsKgCLidhzTfwF8IyK1+09EREotKCSE2g0bAbA0IcHkNObpG9uSdg2iAXjttddISUkxOZGIiIg4kwqAIuJ2HMd/LVYrR3Ptzcq1+09EREorpp39GPD6XclkZHvmEAzDMHhkxGUApKWl8fLLL5ucSERERJxJBUARcTuOCcA1ohuQlZMHaPefiIiUnqMPYF5BASt37DQ5jXk6NW5Er+bNAHj33Xc5dOiQyYlERETEWVQAFBG3UlhYyPr16wHwCo8AtPtPRETKJrpFS7x8fABYus1zjwEDPDxiKADZ2dk8//zzJqcRERERZ1EBUETcSmJiIqmpqQD4RtQEtPtPRETKxtvHh4axrQBYkuCZg0AcWkZFMbRdGwA++ugjkpKSTE4kIiIizqACoIi4FcfxX4CgqHoE+flp95+IiJSZ4xjwjkOHOXzqlLlhTPbAZUOwWiwUFBQwc+ZMs+OIiIiIE6gAKCJuZfXq1QB4V6mCT0gIsfWitPtPRETKzFEABFi6zbN3ATaICOeKrp0B+Prrr/njjz9MTiQiIiJlpQKgiLiVVatWARBUpy5VAwOpH1bD5EQiIlIZREZHE1S1KqBjwAD3DB6Ar5cXADNmzDA5jYiIiJSVCoAi4jaOHTtGcnIyAIFRdWlVLwoD7f4TEZGys1gsxLSx7wJclpCIzWYzOZG5IqtV47rePQFYsGABK1asMDmRiIiIlIUKgCLiNhYvXlz8ca2YJtSpXt3ENCIiUtnEtGsLwLHUNLYdOGhyGvPdMaAfQX6+ADz55JMeXxQVERFxZyoAiojbePfddwEwvLzo3rWz9v6JiIhTndkHcMm2BBOTVAyhQUHc0u8SwN6Dd/78+SYnEhERkdJSAVBE3MKJEydYt24dAFWj6lG7RpjJiUREpLKpWiOMiHr1AA0CcRjftw/Vg4IAey/AwsJCkxOJiIhIaagAKCJu4cUXXyx+0dGkdSvt/hMREZdo0rY9AKt2JpGdl2dyGvMF+flx58D+AMTHx/PNN9+YnEhERERKQwVAEanwDh8+zHvvvVf8/83btDUxjYiIVGYx7ezHgHPy8li7c5fJaSqGa3p2J7JaVQBmzpxJfn6+uYFERETkoqkAKCIV3n/+8x9yc3OL/79+s+YmphERkcqsYWwrrF5eACxWH0AA/Ly9uWfwQAB27drFJ598YnIiERERuVgqAIpIhbZ3717mzJlT/P9htWsTVLWqeYFERKRS8/X3p36LFoAGgZxpTJdO1A+z9999/vnnycnJMTmRiIiIXAwVAEWkQnvuuefIO6MHU/3mLUxMIyIinsDRB3Dr/gMcS001OU3F4G21cv9lgwE4cOAAs2fPNjmRiIiIXAwVAEWkwkpMTOTTTz/9y9/Vb9HSpDQiIuIpmhT1AQRYlrDdxCQVy2Xt2tC0di3APpwrIyPD5EQiIiJSUioAikiF9dRTT1FYWIjV+HPmb7R2AIqIiIvVbtiIwOBgQMeAz2SxWHjwsiEAHDt2jLffftvkRCIiIlJSKgCKSIW0atUqfvrpJwAaR9YEwC8wkPC6dc2MJSIiHsBitdK4aOL8km2J2Gw2kxNVHP1atSSufj0AXn31VU6fPm1yIhERESkJFQBFpMKx2WxMnz4dgEBfXxwvu+o3a47Foh9bIiLiejFt7ceAj5w+zY5Dh01OU3EYhsFDw4cCcPr0aV577TWTE4mIiEhJ6JW0iFQ4v/zyC6tXrwbgxj49i194aQCIiIiUlzP7AOoY8F91b9qErk1iAHjzzTc5duyYyYlERETkQlQAFJEKJT8/nyeffBKAGlWqEFe/PoVFR6+iNQBERETKSbXwCMLrRAGweFuiyWkqnoeG2XsBZmZm8tJLL5mcRkRERC5EBUARqVDmzp1LYqL9hdY9Qwaydf9+AAyLhbpNm5oZTUREPExM0S7AVTt2kpOXZ3KaiqVtg2j6xdrfmHv//ffZX/T7WkRERComFQBFpMLIysri2WefBaB+WBhju3dl3a7dANRq0ABff38z44mIiIdpUtQHMCs3t/j3kfzpgaJdgLm5ubzwwgsmpxEREZHzUQFQRCqMd999l4MHDwLw4LAhWA2D9buSAfX/ExGR8tewdRwWqxWApToG/A/N69RmWHv7tOSPP/6YpKQkkxOJiIjIuagAKCIVwqlTp3jxxRcBiK0bxZC2cew4dJi07GxABUARESl/fgEB1G/WHIDFGgRyVvcNHYzVYqGgoKB4F7+IiIhUPCoAikiF8PLLL3P69GkAHh05DIvFwtozjltFqwAoIiImiCk6Brxl335S0tNNTlPxNIgIZ0znjgB89dVXxMfHm5xIREREzkYFQBEx3YEDB3jrrbcA6NmsKd2bNgFgXZK9ABhcvTrVIiJMyyciIp6rSbv2ANhsNpYlbDc5TcV0z5CB+HhZsdlszJw50+w4IiIichYqAIqI6Z555hlycnIAeGTkZcV/72i4Ht28BYZhmJJNREQ8W1RMDP5BQQAs0THgs6odGso1PboD8PPPP7Nu3TqTE4mIiMjfqQAoIqbavHkzn3zyCQDDO7SjZVQUAMdT00g+dgxQ/z8RETGPxWqlcVwbAJZsS8Rms5mcqGK6c2B//H18AJgxY4bJaUREROTvVAAUEdPYbDamTp2KzWbD18uLh4f/uftv/e4/+/+pACgiImZy9AE8ePIku44cNTlNxRQWHMxNfXoBsHjxYpYsWWJyIhERETmTCoAiYppff/2VxYsXA3DTJb2pUz20+La1Rf3/vLy9qd2okSn5RERE4M8+gKBpwOdza/++BPv7A/ZdgNotKSIiUnGoACgipsjPz2fq1KkAhAYFcsfA/n+53dH/L6pJE7y8vcs7noiISLHqkZHUqFUbgKXbEk1OU3GFBAZwa/++AKxdu5Z58+aZnEhEREQcVAAUEVPMmTOH7dvt0xTvGzq4eMcAQE5eHpv37AUgukVLU/KJiIicyXEMeMX2HeQVFJicpuK6sU8valSpAsDTTz9NYWGhyYlEREQEVAAUEROkpaXx7LPPAtAwIpyx3bv+5fb4ffvJyc8H1P9PREQqhibt7AXAjJwcNuxKNjdMBRbo58udRbv64+Pj+eabb0xOJCIiIqACoIiY4OWXX+ZY0YTfCaOG4221/uX2tbvOGADSrHm5ZhMRETmbRnFxWCz2p87qA3h+V/foRmS1qgDMnDmT/KI39URERMQ8KgCKSLk6cOAAb7zxBgBdYhrTN/afR3zX7twFQFidOgRVrVqe8URERM7KPzCIuk2bAbBUBcDz8vP25p7BAwHYtWsXn3zyicmJRERERAVAESlXM2bMIDs7G8MwmDh6BIZh/OV2m83GmqQkABq0jDUjooiIyFk5+gBu2rOX0xmZJqep2MZ06UR0eBgAzz//PDk5OSYnEhER8WwqAIpIudm0aROffvopAKM6diC2btQ/7rPryFFS0jMAiG6pASAiIlJxNGnXHoBCm41lidtNTlOxeVut3Dd0MGDf/T979myTE4mIiHg2FQBFpFzYbDamTJkCgK+3Nw8NH3LW+63emVT8cXQL7QAUEZGKo27TpvgFBAKwRMeAL+iydm1oWrsWAC+++CLp6ekmJxIREfFcKgCKSLn45ZdfWL58OQA39+1DZLVqZ73f2iR7/78q1apRo1atcssnIiJyIVarlUZxcYB9EIjNZjM3UAVnsVh48DL7G37Hjh3jlVdeMTmRiIiI51IBUERcLi8vj2nTpgEQFlyF2wf0O+d91xQVAKNbtPxHf0ARERGzNSnqA7j/RAp7jh03OU3F169VS9rUrwfACy+8wMmTJ01OJCIi4plUABQRl3vvvffYuXMnAPcNHUyQn99Z73fk9OniF1PRGgAiIiIVUExRH0CARVu3mZjEPRiGwUPDLwPg1KlTPP/88yYnEhER8UwqAIqISx0/fpxnn30WgKa1a3Fl187nvK/j+C9oArCIiFRMYbVrU72oRYUKgCXTrWkMXZvEAPDSSy9x5MgRkxOJiIh4HhUARcSlnnnmGVJTUwGYMmYUXlbrOe+7dqe9AOjj50ethg3LJZ+IiMjFatq+AwDLE3eQk5dnchr38NAwey/AjIwMnnnmGZPTiIiIeB4VAEXEZeLj4/nwww8BGBjXmm5NY857f8cE4PrNmmM9T6FQRETETM06dAQgKzeXNTt3XeDeAtC2QTSXxrUC4I033mD//v0mJxIREfEsKgCKiEvYbDYmTZpEYWEhPl5WJo4aft77p2dns3X/AUD9/0REpGJr2Ko1Vm9vABbqGHCJPTrS/lwgNzeXF154weQ0IiIinkUFQBFxiR9++IGlS5cCcHPfS6gbVuO899+wO5lCmw2A6JYtXZ5PRESktHz9/WlY9GbVwvitJqdxH82j6jCyk3335Mcff0xSUpLJiURERDyHCoAi4nTZ2dk8/vjjAISHBHPHwP4XfIzjCJXFYqFe02YuzSciIlJWTYuOAe84dJgDKSkmp3EfD4+4DKvFQkFBQfGQMBEREXE9FQBFxOneeOMN9u7dC8CjI4YR5Od3wcesKZoAXLtxY3z9/V2aT0REpKyaduhQ/PGieB0DLqkGNSO4qntXAL788ku2bNliciIRERHPoAKgiDjV4cOH+e9//wtAXP16jOzY/oKPySsoYMPuZAAatNDxXxERqfgi6tajWng4oD6AF+u+y4bg4+UFwMyZM01OIyIi4hlUABQRp3riiSfIzMwEYMrlo7BYLvxjJn7ffrJycwENABEREfdgGAZN2tt3AS5LSCSvoMDkRO6jTvVQru3RDYBffvmFtWvXmpxIRESk8lMBUEScZv369Xz66acAjOzYnnYNokv0uDU7/2wCHt2ihUuyiYiIOFuzoj6A6dk5rCtqZSElc8fA/gT4+gAwY8YMk9OIiIhUfioAiohTFBYWMmHCBAD8fXx4dOSwEj/W0f8vrE4dqlQLdUk+ERERZ2sc1waL1QrAIh0DvihhwcHc2Kc3AEuWLGHx4sVmxhEREan0VAAUEaf44osvWLduHQB3DOhPzapVS/Q4m83G2qIJwNHq/yciIm7ELzCQ6Jb2310LNQjkot3a7xKCiwZ/zZgxA5vNZnIiERGRyksFQBEps/T0dKZPnw5AndBQbunXp8SP3XXkKCfS0wFooP5/IiLiZpoW9QHcuv8AR06dNjmNewkJDODW/n0BWLduHfPmzTM5kYiISOWlAqCIlNlLL73E4cOHAZgwejh+Pj4lfuyaM3omOXZRiIiIuIum7TsWf6xjwBfvxj69qFGlCmDfBVhYWGhyIhERkcpJBUARKZOkpCRmzZoFQOfGjRjcJu6iHr+2qAAYVLUqNWrVdnY8ERERl6rVoAHBodUBFQBLI9DPl7sGXgrA1q1b+frrr80NJCIiUkmpACgipWaz2Zg4cSK5ublYLRamXzkGwzAuao01jv5/LWMv+rEiIiJmMwyDph3sx4AXb00gv6DA5ETu5+oeXalVrRoAM2fOJC8vz+REIiIilY8KgCJSar/88gsLFiwA4IbePWlSu9ZFPf7o6VSSjx0D1P9PRETcV9MO9mPAqVlZbEzeY3Ia9+Pr7c09QwYCsHv3bj755BOTE4mIiFQ+KgCKSKlkZWUxceJEAMKCq3Dv0EEXvcaanUnFH0e3aOG0bCIiIuUppk1bDIv9abWOAZfOmM4diQ4PA+CFF14gOzvb5EQiIiKViwqAIlIqr776Knv37gXgsZHDCfb3v+g1Vu7YCYCvvz+1GzV2aj4REZHyElClCvWbNQdgYbwKgKXhZbVy/9DBABw4cIDZs2ebnEhERKRyUQFQRC7anj17ePnllwFo1yCakR3bl2qd1UU7AOu3aInVanVaPhERkfLWtL29D+Afe/ZyPDXN5DTuaWi7NjQraify4osvkp6ebnIiERGRykMFQBG5aJMmTSI7OxuLYfDEVZdjsVz8j5KT6RkkHDgIQMPYVs6OKCIiUq4cfQABFsZvNTGJ+7JYLDw4bAgAx48f5/XXXzc5kYiISOWhAqCIXJT58+fz888/A3BNj260iKpTqnVWn9H/r2Gr1k7JJiIiYpbajRoRHFodgAVb4k1O4776xrakfcMGgL3dyOHDh01OJCIiUjmoACgiJZaTk1M8+CM0KLD4XfrSWFXU/8/b15eomBin5BMRETGLxWKheafOACzeuo3c/HyTE7knwzCYNHoEAJmZmTz99NPmBhIREakkVAAUkRKbNWsWu3fvBuDh4ZdRNTCw1Gs5BoDUb94CL29vp+QTERExU/PO9gJgenYOq3ckXeDeci5touszrH1bAD7++GO2bNliciIRERH3pwKgiJTI/v37+e9//wtA63p1ubJr51KvdTozk637DwDq/yciIpVH47g2xW9qLdisolVZPDziMny9vLDZbEydOhWbzWZ2JBEREbemAqCIlMiUKVPIysrCKMPgD4e1SbuKn8ir/5+IiFQWvv7+NG5j37n26+YtKlqVQVT16tx4SS8AFi1axIIFC0xOJCIi4t5UABSRC1q0aBHfffcdAFd160Lr+vXKtN7K7fbjv17e3tRt2rTM+URERCoKRx/AvcdPsPPwEZPTuLc7B15KaJC93cjUqVPJV19FERGRUlMBUETOKycnh0cffRSAkIAAHh4+tMxrOgaA1GvWHG8fnzKvJyIiUlE079Sp+OMFmzUNuCyC/f25d8ggABITE/noo49MTiQiIuK+VAAUkfN67bXX2LnTXrB7aNgQQoOCyrReenY2W/btB6BhK/X/ExGRyqVaeAS1GjQE4DcNryizq3t0o2FEOADPPPMMaWlpJicSERFxTyoAisg5JScnFw/+aFWvLlf36FbmNdcm7aKgsBCAhrHq/yciIpWP4xjw2qTdnMrIMDmNe/O2WpkwajgAx44d4+WXXzY5kYiIiHtSAVBEzspms/HYY4+RnZ2NxTCYMfYKrGUY/OHgOP5r9fKiXrNmZV5PRESkomne2V4ALCgsZGH8NpPTuL++sS3pEtMYgDfeeIP9+/ebnEhERMT9qAAoImf1ww8/8OuvvwJwXa8exNar65R1V+1IAqBuk6b4+Pk5ZU0REZGKpG6TpgSFVAXUB9AZDMNg0pgRGIZBdnY2U6dONTuSiIiI21EBUET+IT09nQkTJgAQFhzMA8OGOGXdrNxc/tizF1D/PxERqbwsFgvNioaBLIzfSl5BgcmJ3F/LqCiu7GrfWfnNN9+wbNkykxOJiIi4FxUAReQfnn32WQ4dOgTAlDEjCfb3d8q663btLn4R1CBWBUAREam8HH0AU7OyWJe0y+Q0lcNDw4YWPyeZMGEC+fn5JicSERFxHyoAishfxMfH89ZbbwHQo1kTLmvf1mlrO/r/WSwW6jdv4bR1RUREKpom7dpj9fICdAzYWWoEV+G+oYMA2Lp1K7NnzzY5kYiIiPtQAVBEihUWFvLQQw9RUFCAr5cXT1x1OYZhOG19RwGwTuMY/AICnLauiIhIReMXEEDDVvZp9wu2qADoLON69aBxZE0AZs6cyYkTJ0xOJCIi4h5UABSRYh999BFr1qwB4PYB/YgOD3fa2tl5eWzcvQdQ/z8REfEMjmPASYePsPvoUZPTVA7eVitTLx8NwKlTp5g5c6bJiURERNyDCoAiAsDx48eZPn06APXDwrh9QH+nrr9xdzI5Rb16HDsiREREKrMWnbsUf/zLxs0mJqlcujdrwsA4+3OJ2bNns3mz/m1FREQuRAVAEQFg2rRpnDp1CoAnrhqDn7e3U9dfsX0HAIbFQnTLlk5dW0REpCKqHhlJrQYNAZi36Q+T01Quk8aMwNfbG5vNxoQJE7DZbGZHEhERqdBUABQRVqxYwSeffALAZe3a0rN5M6dfY3mivQAY1TgG/8Agp68vIiJSEcV26w7A+t3JHD2danKayiOqenVu698XgJUrV/L555+bnEhERKRiUwFQxMPl5eXx8MMPAxDk58vkMSOdfo3MnBw27E4GoFFcG6evLyIiUlHFdusGgM1mY/4fOqrqTLcP6Eft0GoATJkypfgkg4iIiPyTCoAiHu61114jISEBgAcvG0pE1RCnX2Nt0i7yCgoAaBwX5/T1RUREKqrI6AZUj4wE4JeNm0xOU7n4+/gw/coxgL2X8ZNPPmlyIhERkYpLBUARD5aUlMTzzz8PQMuoOozr1d0l13Ec/7V6eRHdQv3/RETEcxiGUXwMeHniDlKzskxOVLn0axXLgLhWgH0gyJo1a0xOJCIiUjGpACjioWw2Gw899BA5OTlYLRaeGTcWL6vVJddanrgdgHrNmuPj5+eSa4iIiFRUjgJgXkEBv22ONzlN5TP18tEE+PoA8NBDD5Gfn29yIhERkYpHBUARD/XJJ5+wZMkSAMZf0puWUVEuuc7pzEw2790HQGP1/xMREQ9Ur2kzgqpWBeAXTQN2ulqh1bh/6GAA4uPjefvtt01OJCIiUvF4mR1AyofVRTu7zLqOlJ7VauXYsWNMmjQJgKjqodx/2WAMw3DJ9Vbv3EWhzQZA4zZtwEXX8Rj693MLxhn/telr5n70NXML7vR9ZvHyomXXbqz88QcWxm8lJy8PPx8fs2OZytnPO266pDdfrlrD1v0HeOaZZxgxYgR16tRx6jU8keO5vZ7juyd93UTkTCoAeohq1aq5/BpWq7VcriNlN27cOE6ePAnAs9dfS7XgYJdda9XOJAC8fX2JbtECq1Ubj0vNQP9+bsair5f70feZ23GX77PWPXqy8scfyMzJZWXSLgbEtTY7kmkMw8DX19epa/oCz90wjqFPPUNGRgZTpkzhq6++cuo1PFmwC58rimvotZmI/J0KgB7CUexxheDgYKxWKwUFBaSmprrsOuIcCxcuZM6cOQAM79CObjGNycnJcdn1lmzdBkCDlrEYFisFBYUuu1ZlZbVYira4QEGh/v3cgYG9KFFYUIjN7DBSIvo+cz/u9n3WsFVrfAMCyMnM5Ps16+jdrKnZkcqdj48PhmFgs9nIzc11+vqxdWpzdfeufLRkGV9//TVz5sxhyJAhTr+OJ7FarQQHB5OamkpBQYHZcaQEKstrMxUvRZxPBUAPUV6/sPXEoGLLzMzkvvvuAyAkIIDJY0Zis7nuZdPx1DQSDhwEoFFcHLjwWh5D/4ZuwXEc0Qb6mrkjfc3cgrt9n3l5e9O8Yyc2LPyd+Zs2k5ef77LhW+7AVc8/Hhl+GfM2/cGx1DQeeOABOnfuTNWi/otSegUFBXqe74b0NRORM7nHmQkRcYrnn3+ePXv2ADBp9AjCXHycY+WOHcUfawCIiIh4Osc04JMZGaxJ2mVymsopJDCA6VdeDsDRo0eZPHmyyYlEREQqBhUARTzE5s2bmTVrFgBdm8ZwRdfOLr/m8kR7AdAvMJDajRq7/HoiIiIVWdMOHfHy9gbgx/UbzQ1TiQ1uG8fgtnEAfPLJJyxYsMDcQCIiIhWACoAiHqCgoID777+fgoICfL28eP76cS6b+num5YnbAXvfI00hExERT+cXEEDTDh0B+GnDRvWbdKHpV46hamAAAA888ABpaWkmJxIRETGXCoAiHuCdd95h48aNANw9eAANa0a4/JoHU06y++gxABrHxbn8eiIiIu4grldvAI6lprF6Z5K5YSqxsOBgHr98NAAHDhzgiSeeMDmRiIiIuVQAFKnk9u/fz4wZMwBoHFmT2y7tVy7XXbH9z/5/jdT/T0REBIDmnTrj5eMDwPfrNpicpnIb2bE9l7RsAcD777/P0qVLTU4kIiJiHhUARSoxm83Gww8/TGZmJgAzr7kKH6/yGf69NCERgKCQqtSsV79crikiIlLR+QUE0LxjJwB+Wr+RfE3pdBnDMJhx9RVU8fMD4O677yY1NdXkVCIiIuZQAVCkEvviiy+YP38+ANf27E77hg3K5bo2m40l2+wFwMZt22Kx6EeNiIiIg+MY8In0dFbu2GlumEouslo1pl5hPwq8f/9+JkyYYHIiERERc+hVuUgldezYMSZOnAhArWrVeHTEZeV27cSDhzhW9A57k3btyu26IiIi7qBZx054+/oC8IOOAbvc6M4dGRjXGoC5c+fy3XffmZxIRESk/KkAKFJJPfbYY6SkpAAw4+orqeLvX27XXrwtofjjmLYqAIqIiJzJ19+f5p06A/DThk06BuxihmHw9DVXEhZcBYAHH3yQw4cPm5xKRESkfKkAKFIJ/fDDD3zzzTcAjOrUgT4tm5fr9ZdstRcAI+rVo2qNsHK9toiIiDtwHAM+mZHB8sTt5obxAKFBQTxz7dUApKSkcO+992Kz2UxOJSIiUn5UABSpZE6dOsXDDz8MQFhwFR6/fFS5Xj87L49VO5MAaNK2fbleW0RExF0069ARn6LhFJoGXD76xrbgmh7dAFiwYAEffPCBuYFERETKkQqAIpXM5MmTOXr0KADTr7ycqoGB5Xr9tTt3kZOXB6j/n4iIyLn4+PnRonMXAH7e+Ad5OgZcLiaOGkH9MPvphClTphAfH29yIhERkfKhAqBIJfLbb7/xySefADCoTWsGt40r9wyO/n9Wb28axLYq9+uLiIi4C8cx4NOZmSzdlmhuGA8R6OfLyzddh7fVSnZ2NjfffDPp6elmxxIREXE5FQBFKon09HQeeOABAEICAph+5eWm5FhSVACMbt4C33IcPCIiIuJumnboWPy78ru1601O4zla16/HoyOHAbBjxw4effRRkxOJiIi4ngqAIpXEE088wf79+wF4/PJRhIcEl3uGY6mpbN1/AIAm7dT/T0RE5Hy8fXyI7dYdgJ83biIrN9fkRJ5j/CW96RvbAoC5c+cyd+5ckxOJiIi4lgqAIpXAihUreO+99wDo1bwZozp1MCXH0oQ/jy+p/5+IiMiFtevbD4CMnBzmb9pschrPYRgGL1x3LZHVqgLw8MMPs2PHDnNDiYiIuJAKgCJuLisri3vvvReAID9fnr7mSgzDMCXLkq32AmBgSAi1GjYyJYOIiIg7aRzXhiqhoQB8uXqNyWk8S7WgQF656XqsFguZmZmMHz+ejIwMs2OJiIi4hAqAIm7u6aefZteuXQA8NnI4tYteRJQ3m81WPAAkpk1bLBb9eBEREbkQi9VK2z6XALB4awLHU9NMTuRZOjRqyP1DBwOwbds27r33Xmw2m8mpREREnE+v0EXc2MqVK3njjTcA6BLTmKu7dzUtS+LBQxxLTQXU/09ERORiOI4BFxQW8t06DQMpb3cM6Ef/Vi0B+Prrr5k1a5bJiURERJxPBUARN5WRkcHdd9+NzWYj0NeX56672tRdd47dfwAxbdX/T0REpKRqN2xERL16AHy9eq3JaTyPxWLhPzeMo2FEOADTp09n0aJFJqcSERFxLhUARdzUE088QXJyMgCTRo8gqnp1U/Ms2WovAEbUrUvVsDBTs4iIiLgTwzBod4l9F+DG5D3sOnLU5ESeJ9jfn7duu5kgP18KCwu5+eab2bNnj9mxREREnEYFQBE3tGTJEt59910AejVvylgTj/4CZObksLJocl7TDh1NzSIiIuKO2l7St/hj7QI0R6OaEfzn+nEAnDx5khtuuIH09HSTU4mIiDiHCoAibiY9PZ177rkHsL9b/cy1Y02b+uuwPHE7ufkFADTr2MnULCIiIu4oNCKChq1aA/DlqjUUFhaanMgzDYhrxb8HDwBgy5Yt3HbbbRQUFJicSkREpOxUABRxM48//jj79u0DYMrlo4isVs3kRPD7lq0A+Pr706BFS5PTiIiIuKd2fe27APedOMHqnUkmp/Fc9w0ZxMA4ezH2l19+YcqUKSYnEhERKTsVAEXcyG+//caHH34IQN/YFozpbP5xW5vNxu/x9gJg4zZt8fLxMTmRiIiIe4rr2RsfXz8APl2+yuQ0nstisfDijeNoXa8uAG+99RbvvPOOyalERETKRgVAETdx+vRp7r33XgBCAgJ4+pqrTD/6C7Dj0GEOpJwEdPxXRESkLPwCA2ndqxcAP6zfQGpWlsmJPJe/jw/v3H4LdUJDAZg4cSLz5s0zOZWIiEjpqQAo4iYmTZrEoUOHAJh+5RgiQkJMTmT3W9HxX4BmGgAiIiJSJp0GDAQgOy+P79euNzmNZwsPCeb9O2+lip9f8WTgDRs2mB1LRESkVFQAFHED8+bN45NPPgFgYFxrhndoZ3KiP/0eHw9AZIMGVA0LMzmNiIiIe4tuGUuNWrUB+HT5SpPTSEytSN64ZTxeFguZmZlceeWVJCYmmh1LRETkoqkAKFLBHT9+vPjob2hQIE+NvaJCHP0FSM3KYu3OXQA066DjvyIiImVlGAYdi3YBbkjew/aDh0xOJN2bNeH5668B4OTJk4wZM4a9e/eanEpEROTiqAAoUoHZbDbuv/9+jh07BsBTY6+kRnAVk1P9aem2RPILCwEd/xUREXGWDpdeimGxP03/dIWGgVQEIzt2YPqVYwA4fPgwo0eP5siRIyanEhERKTkVAEUqsI8++oiffvoJgMu7dGJw2zhzA/3NwqLpv36BgdRv3tzkNCIiIpVDSPUaNOvQAYAvV64mNz/f5EQCcH3vnjxw2RAAkpOTueKKKzh58qTJqUREREpGBUCRCmr37t1MnDgRgDrVQ3n88lEmJ/orm83G70UFwCbt2mP18jI5kYiISOXRccAgAE6kp/PrH1tMTiMOdw+6lH/17QPA1q1bGT16NCkpKSanEhERuTAVAEUqoPz8fO644w4yMzOxGAYv3jCOKv7+Zsf6iy1793H0dCoAzTrq+K+IiIgzNe/UmSrVqgEwZ/FSk9OIg2EYTBo9gqu6dQFg8+bNjBo1ihMnTpicTERE5PxUABSpgF566SXWrl0LwO0D+tOhUUOTE/3T/KLdCIZh0LxjZ5PTiIiIVC5e3t50GmjfBbgscTu7jhw1OZE4GIbB01dfydjuXQGIj49n1KhRxT2bRUREKiIVAEUqmPXr1/Pcc88B0DKqDvcOGWhyorOb/8dmAOo3b0FQ1armhhEREamEOg8eWjwMZM4S7QKsSCwWCzPGXsG1PbsD9uPAI0eO1GAQERGpsFQAFKlAMjIyuP322ykoKMDX25sXb7wOnwrYW2//iRS27j8AQIsuXU1OIyIiUjmFRkTQvGMnAD5fsZrs3FyTE8mZLBYLT151OTf07glAYmIiQ4cOZffu3SYnExER+ScVAEUqkMcff5xdu3YBMHHUcBpH1jQ50dn9uvnPZuQtVQAUERFxma5DLwPgdGYm363bYHIa+TvDMJh6xejiwSDJyckMGTKETZs2mZxMRETkr1QAFKkgfvnlF2bPng1Ar+bNuK5XD5MTndv8Tfbjv2F16hAeFWVyGhERkcqrSfsOhNaMBDQMpKJyDAZ5ZIS9WHvs2DGGDx/OokWLTE4mIiLyJxUARSqAQ4cO8e9//xuAaoGBPHfd1RiGYXKqs0vNymLl9h2Adv+JiIi4msViocuQIQBsTN7D5j17TU4kZ2MYBncM6M/z112D1WIhIyODsWPH8vnnn5sdTUREBFABUMR0BQUF3H777aSkpADw3LiriQgJMTnVuS3cspX8wkJA/f9ERETKQ6cBg7B6ewPwoXYBVmiXd+nEO7ffjL+PD3l5edx+++089dRTFBY9dxIRETGLCoAiJnvxxRdZtmwZADf07kn/1rEmJzq/+X/Y+/8FhoRQv1lzk9OIiIhUfkFVqxLXsxcA36xey/HUNJMTyflc0rIFH997FzWqVAHsz/Wuv/560tPTTU4mIiKeTAVAEROtWrWK5557DoDmdWrz2KjhJic6v7yCAhbGbwWgeafOWKxWkxOJiIh4hp4jRwOQk5+vXoBuoE10fb599AGa16kNwM8//8zgwYPZs2ePyclERMRTqQAoYpJTp05x2223UVBQgL+PD6+OvwG/ouM9FdWqHTtJzcoCoEVnHf8VEREpL1ExMTRoaT8l8H+Ll5Kdl2dyIrmQ2qGhfPHgvQxpGwfAtm3b6NevH7/88ou5wURExCOpAChiApvNxr333sv+/fsBeOKqy2lYM8LkVBf2y8Y/APDy9qZJu3YmpxEREfEsvUaPAeB4WhrfrllnchopiQBfX177143cP3QQYH8D+Nprr2Xq1KnkqYgrIiLlSAVAERPMnj2bH374AYDhHdoxpnNHkxNdWGFhIT9t2ARA0/Yd8PX3NzmRiIiIZ2nRuQvVIyMBePe3hdhsNpMTSUkYhsE9Qwbx3h23UjUwAIDXXnuNYcOGFb8ZLCIi4moqAIqUs23btjF58mQA6oXV4KmxV2AYhsmpLmzdrt0cS00FoFWPnianERER8TwWq5UeI0YBkHDgIMsSt5ucSC5G39gW/DThEdo2qA/A2rVr6dOnD1999ZW5wURExCOoAChSjjIzM7n55pvJzs7Gy2LhlZuup4qb7KT7cf1GAKxeXrTo0sXcMCIiIh6q44CB+AUEAvDOgt9NTiMXq1ZoNT69/x5u7d8XsB8JvuWWW/jXv/5FSkqKyelERKQyUwFQpJzYbDYeeughEhMTAXh4xGW0rl/P5FQlU1hYyE8b7cd/m7Rrh39gkMmJREREPJNfQACdBw8G4PctW0k8cNDkRHKxvK1WJowazuy7biMiJASAb775hh49ejB//nyT04mISGWlAqBIOZkzZw6ffvopAH1aNufmvn1MTlRym/bs5dDJUwC06q7jvyIiImbqMWIUVi8vAGbN+9XkNFJavVs0Z97kRxnewT5Y7ejRo1x99dXccccdHDt2zOR0IiJS2agAKFIO/vjjDx577DEA6oSG8uIN47BY3Ofbz3H812K10qJLV3PDiIiIeLhq4eG079cfgG/XrGPvseMmJ5LSqhoYyMs3Xc+sm2+kWqD9aPdnn31G165dmTNnDoWFhSYnFBGRysJ9KhAibur06dOMHz+enJwcvK1WZt18I1WLnuC5A5vNVjz9t3FcGwKDg01OJCIiIpdceRWGxUKhzcYb8xeYHUfKaEjbNsyf8hgjOrYH7L0B77vvPoYPH87WrVtNTiciIpWBCoAiLmSz2bj77rtJTk4GYMrlo9ym75/Dln372XfiBKDpvyIiIhVFWO06tC76vfzZipUcOXXa5ERSVmHBwbx043XM+fcd1AurAcDKlSvp06cPDz74oI4Fi4hImagAKOJCs2bN4qeffgJgWPt2jOvZ3eREF++nouO/hsVCbNdu5oYRERGRYn2vuhqA3PwC3tZE4EqjR7OmzJv0KHcOvBQfLyuFhYXMnj2bTp068dprr5GTk2N2RBERcUMqAIq4yIoVK3jiiScAaFQzgpnXXIVhGCanujg2m43v128AoEFsLEFVq5obSERERIrVbtiQ5p06AfDRkqWcTM8wOZE4i5+PDw8PH8qvUyYwqE1rANLS0pg6dSrdu3fnq6++Un9AERG5KCoAirjA4cOHufnmmykoKMDfx4fXb7mJQD9fs2NdtE179rKnqLF4296XmJxGRERE/q7vVdcAkJmTq12AlVC9sDDeuGU8c++7mxZRdQBITk7mlltu4ZJLLuHnn3/GZrOZnFJERNyBCoAiTpabm8tNN93EkSNHAHj6miuJiYw0OVXpfLN6LQBWLy9a9ehhchoRERH5u+gWLWgc1waA939fyIm0NJMTiSt0jmnMd48+yHPjriayWlUA4uPjGTduHAMGDOD3339XIVBERM5LBUARJ5swYQJr1qwB4KY+vRjZsYPJiUqnoLCQ79atB6Bp+w4EBoeYnEhERETOZuD1NwL2XYCvz9NE4MrKarFwRdfOLJw2mamXj6ZGlSoAbNiwgSuuuIJBgwbx008/6WiwiIiclQqAIk40e/ZsZs+eDUDnmEZMGD3C3EBlsCJxB8dS7bsI2vbR8V8REZGKKrpFC5p1tPcC/HDREk0EruT8vL258ZJeLHliCo+OuIyQgAAA1q1bx3XXXUevXr349NNPycvLMzmpiIhUJCoAijjJqlWreOyxxwCoHVqNWf+6EW+r1eRUpff1GvvxXx8/P5p37mJyGhERETmfgdfdAEBOXh6v/jzP3DBSLgJ8fbl9QH+WPvk4Dw8fSvWgIAASEhK488476dSpE++++y4ZGRoOIyIiKgCKOMWhQ4e46aabyMvLw8/bm7du+xfVi45luKPsvDx+3rAJgJZdu+Hr729yIhERETmfqJgYYrt1B+DjpcvZfyLF5ERSXoL9/blz4KUsf2oq068cQ53QUAD27dvHo48+SlxcHNOnT2ffvn0mJxURETOpAChSRtnZ2dxwww0cPXoUgGeuHUvLqCiTU5XN71u2kpadDUC7S/qanEZERERKYsB112MYBnkFBbz0489mx5Fy5ufjw/W9e7Jw+mT+e8O1NI6sCcCpU6d45ZVXaN++PTfeeCMrVqzQwBAREQ+kAqBIGdhsNh555BHWr7cPy7i53yWM6Nje5FRl903R8d/AkBBi2rYzOY2IiIiURK3oBsT17gPAZytWsW3/AZMTiRm8rVZGderIvEmPMvuu2+jVvBkAhYWFfP/99wwbNoy+ffvy8ccfk5WVZXJaEREpLyoAipTBrFmz+N///gdA96ZNeHTEZSYnKrvUrCx+2xwPQFzPXli9vExOJCIiIiU1+IabsHp7Y7PZmPHlN2bHERNZLBZ6t2jOh3ffzoLHJzKuZ3cCfH0A2Lx5M//+97+JjY1l4sSJbN++3eS0IiLiaioAipTSTz/9xLRp0wCoHxbGq+NvwMuNh344fLd2PTn5+QC01fFfERERt1I9MpIew0cCsHhbAou2bjM5kVQEjWpG8OTYK1g5YzqTRo+gTnV7n8DTp0/z1ltv0a1bN4YNG8YXX3xBTk6OyWlFRMQVVAAUKYU//viD2267DZvNRrC/P+/dcQvVggLNjuUUny5fCUBYnTrUb97C5DQiIiJysfpffQ0BRcPInvriawoKC01OJBVFSEAAN/e7hMXTp/DBnbfRv1VLLIYBwIoVK7jtttto1aoVU6dOJSkpyeS0IiLiTCoAilykw4cPc+2115KZmYmXxcLrt9xEw5oRZsdyiu0HD7ExeQ8AHS8diFH0hFBERETch39QEJdeex0AiQcPFb+5J+JgtVjo07I579x+C8uenMq9QwZSs2oIACkpKbz22mt07tyZkSNH8umnn5Kbm2tyYhERKSsVAEUuQmZmJuPGjePQoUMAPDn2Cro3bWJyKuf5dMUqAAyLhfb9+5ucRkREREqr69DLqFGrNgAvfPcjaRr2IOdQK7Qa9w0dzLInp/L2bf+id4vmxW8CL1q0iCuvvJKWLVsybdo07QoUEXFjKgCKlFBhYSF33nknGzduBOwTf8d272puKCfKKyjgq1VrAGjavgMh1WuYnEhERERKy8vbm6H/ugWAY6mpvPjDzyYnkorOy2rl0tatmH3XbSx5Ygp3DryUsOBgAI4fP86rr75avCvwyy+/VK9AERE3owKgSAnYbDYmTZrE999/D0C/2JY8NnKYyamc6/ct8RxPSwOg44CBJqcRERGRsort1o0m7doD8P7vi0g8cNDkROIuoqpX5+HhQ1n59HTev+t2erdoVrwrcOnSpdx66620atWKKVOmsGPHDpPTiohISagAKFICs2bN4u233wYgtm4UL990PVZL5fr2cfQHCgwOpkXnLianERERkbIyDIORd96F1cuLgsJCpsz9HJvNZnYscSPeViuD27Xhw7vvYMkTU/j34AFEhPzZK/D111+na9euDBs2jM8++4wsHTUXEamwKlcFQ8QFvvzyS6ZOnQrY3w19/85bCfTzNTeUkx09ncpvW7YC0LZvP7y8vU1OJCIiIs4QXieKPpdfAcDKHTv5Zs06kxOJu4qqXp0HLhvC8qem8s5tN3NJyxZ/mSB8xx130KpVKyZOnEhCQoLJaUVE5O9UABQ5jyVLlnDXXXcBUC0wkA/vvr24F0pl8uWq1RQUFgL26b8iIiJSefS96mqqhYcD8OQXX2sgiJSJl9VK/9axvH/nrSx7cir3DRlEZLWqAJw6dYq33nqLHj16MGTIEObOnUtmZqa5gUVEBFABUOSctmzZwvXXX09eXh5+3t68d8ctNIgINzuW0xUUFjJn8TIAomKaULthQ5MTiYiIiDP5+vsz/LY7AftAkGe/+d7kRFJZ1Aqtxr1DB7Hsyam8d8et9G/VsrhNzurVq7nrrruIjY3l0UcfZevWrSanFRHxbCoAipxFcnIyV111FWlpaVgMg9f+dQNtG0SbHcslFm3dxr4TJwDodlnlGmwiIiIidrHdutGsYycAPly0hNU7kkxOJJWJ1WKhb2wL3rn9FpY/NZUHLhtCndBQAFJTU3n33Xfp1asXgwYN4qOPPiIjI8PkxCIinkcFQJG/OXToEGPGjOHIkSMAPDX2Cvq1ijU5let8uGgJAP5VqhDXu4/JaURERMQVDMNgzL/vxdffH4BH5nxMdl6eyamkMqpZtSr/HjyAxU9MYfZdtzEwrnXxrsC1a9dy7733Ehsby8MPP8zmzZtNTisi4jlUABQ5w4kTJxgzZgx79uwB4KFhQ7m6RzeTU7nO3mPHWRi/DYBOAwbi41u5hpuIiIjIn6qFhzP0X7cAsOvoUV764SeTE0llZrVY6N2iOW/eOp4VM6bx8PChRFWvDkBaWhrvv/8+l1xyCf379+fjjz8mOzvb5MQiIpWbCoAiRdLS0rjyyivZvn07ALdd2pc7B/Y3OZVrzVmyDJvNBkDXoTr+KyIiUtl1GTKUBrGtAHhz/m9s3rvP5ETiCSJCQrhz4KUsnj6Zj/59J0PaxuFVtCtw48aN/Pvf/yYuLo6nnnqKgwcPmpxWRKRyUgFQBMjMzOSaa65h06ZNAFzboxuPjhiGYRgmJ3Od7Nxc5i5fAUDT9h2oUauWyYlERETE1SwWC1fcdz9ePj4UFBby4IcfkaOjwFJOLBYL3Zs1YdbNN7Hy6ek8NnJY8a7AEydO8OKLL9K2bVvGjx/PihUrit+oFhGRslMBUDxeTk4ON910EytW2Ithwzu044mrLq/UxT+A79dv4FRGJgDdhg03OY2IiIiUl/A6UQy87gYAEg4c5PlvfzA3kHiksOBgbru0H4umT+bd22+me9MmABQUFPDtt98ybNgwLrnkEj766COysrJMTisi4v5UABSPlpOTw4033siCBQsA6N+qJS9cfy0WS+X+1rDZbMz+fTEA1SIiaNaho8mJREREpDz1Hj2GBi3tQ87eXvA7K7bvMDmReCqrxUK/VrF8dM+dzJ/yGNf27E6Arw8AW7Zs4d577yUuLo4nnnhCx4NFRMqgclc5RM7DUfybP38+AD2bNeXVf92It9VqcjLXW7VjJ5v27AWg22XDsHjA5ywiIiJ/slitXP3wo/gGBGCz2Xhg9hxStctKTBYTGclTY69g5YzpTB4zkro17MeDU1JSePnll2nXrh133HGHpgeLiJSCCoDikf5e/OvRrAlv3/Yv/Ly9TU5WPmb9NA8AX39/ugweanIaERERMUNozZqMuuMuAA6knGTKJ5+ZnEjELiQggH/17cPCaZN5745b6NmsKQD5+fl89tlnXHLJJYwePZoFCxaoT6CISAmpACgex9Hz78zi3zu33Yyfj4/JycpH0uEj/LLRPuyk08DB+AcFmZxIREREzNK+/6W06t4DgK9Wr+WLlatNTiTyJ6vFQt/Ylvzfv+9g/uTHuKJrZ3y87CdXFi9ezFVXXUXPnj353//+R05OjslpRUQqNhUAxaNkZ2dz0003MW+efQecpxX/wN7nB+xT2HqOHGVyGhERETGTYRhcfu99hNSoAcDEjz9lx6HDJqcS+aeYWpE8N+5qlj05jbsGXkpIQAAACQkJ3HPPPbRt25b//ve/nDx50uSkIiIVkwqA4jHS09O5+uqri4t/3Zt6XvHveGoaX6xYBUCrnr0IrVnT5EQiIiJitsDgEMZNmITFYiErN5c73n6frNxcs2OJnFV4SDAPDR/KyhnTmH7lmOI+gUePHmXGjBnExcXxyCOPsGfPHpOTiohULCoAikc4efIkY8aMYcmSJQD0at6Md2/3rOIfwHu/LSQnPx+A3mMuNzmNiIiIVBQNWsYy6MabANh+6BBT5n5uciKR8wvw9eX/27vzuKrq/I/j78MFLosGmAsmioiWuUvlmqJmU7mWZuVSNi5pNT81a8aZtKY0s5zGtF1rajKbpjLLqWwcy33XTE0pV0zcQTZluVzuvb8/kJskKAh4Ofe+no+HD+B+z/nygZlPh/O+53zP8G5dtfLZp/TWQyMV16ihJCk7O1vvvvuu2rdvr4cfflgJCQmeLRQAqggCQHi9kydP6s4779T3338vSeod10bv+GD4l5GVrfdXrZYkXRsXpwbXNfVwRQAAoCrpPuheNb2pnSTpk/Ub9cn6jR6uCLg0i5+f7mjbWp//caI+e2KCbm/TWoZhyOFwaOHChYqPj9eQIUO0adMmT5cKAB5FAAivlpSUpL59+7rf+bunUwe9OvJBBfr7e7iyK++9Fat0NrdgceTb7n/Aw9UAAICqxs/PT0P+9Ofz1gP8WD8kHvJsUUAZ3BjbSHPHjNTyv07WvZ06KMBS8MCQZcuWqU+fPurTp4+WLVvGk4MB+CQCQHithIQE9e7dW4mJiZKkkbd008xhg2Xx873/25/JydE/lq+UJDVq2VKNW7fxaD0AAKBqqhYWpgefflb+AQHKy3foobnv6GR6hqfLAsqkUZ3amnn/EK197q8a3bOHQqwFd/5s2rRJQ4YMUffu3bVo0SLln1saBwB8ge8lIfAJq1evVp8+fXT8+HFJ0sQ+d+ipgXfJMAwPV+YZ81etUWZOjiTp1qH3e7gaAABQlUU3bapB4x+TJJ3KyNSYef+QzW73cFVA2UWGh2vKwDu1YfqzmtjnDkWEhkqSdu/erTFjxqhjx4765z//qdzcXA9XCgCVjwAQXueTTz7RfffdpzNnzsjPMPTcfYM0vvcdPhv+ncnJ0dvfrpAkNWh6va6Nu8HDFQEAgKrupt/dpq53DZQk/ZB4SFP+/Sm3TcK0wkNDNb73HVo//Rn9ddAA1Y0IlyQdOnRIf/zjHxUXF6dXXnlFmZmZni0UACoRASC8hsvl0qxZs/Too4/KbrcrODBQb48dpfvju3i6NI96+9sVSsvKklSw9p+vBqEAAKBs+j40Rk3axkkqeCjIeytWebgioHxCrFaN6NFNq6c+rZceGKrYyDqSpOTkZE2bNk1t2rTRtGnTdOrUKQ9XCgAVjwAQXsFut+vxxx/XjBkzJElXV6umjx/7P/Vs1dLDlXnW6TNn9M53BVf/NWrZSk1vvMnDFQEAALOwWCx6YPIU1YisK0mauvBzLd2+08NVAeUX6O+vQR3b69un/qK5Y0aqdXQDSdKZM2f0yiuv6IYbbtCf/vQn/fLLLx6uFAAqDgEgTO/06dMaNGiQPvjgA0lSo9q19cWfJqp1w2gPV+Z5r/93mbJsBU/+7T1iFFf/AQCAMgm9Kkyjpj2noNBQuVwu/d+772vbwURPlwVUCD8/P93eprUWT3pcH034g7pcf50kKTc3V++9957at2+vhx9+WAkJCR6uFADKjwAQprZ792797ne/07p16yRJ7RrHatEfH1ODWjU9XJnnHU1N1Qer10iSmrXvoJjmzT1cEQAAMKPI6IYa8cxUWQICZLPbNfLNeTp0KtnTZQEVxjAMdbruWi0Y96i+/PMT6hXXRoZhyOFwaOHChYqPj9eQIUO0adMmT5cKAJeNABCm9fXXX6tXr146fPiwJGnwzZ304fhHFVEt1MOVVQ0vfvGl8vIdkqRevx/h4WoAAICZNW7dRoOf+JMkKfVsloa/9pZOnznj4aqAitcquoHeHD1C3z39pO7t1EEBFoskadmyZerTp4/69u2rZcuW8VAcAKZDAAjTcTqdeumll/Tggw8qOztbFj8/Tb33bs0Ycq8C/f09XV6V8P3BRC3e8r0k6aZbf6drGsV6uCIAAGB2cd17qPfIUZKkQ8nJGvHGPJ3NzfVwVUDliI2so5n3D9Ha5/6qUbd0V4g1UJK0ceNGDRkyRN27d9eiRYuUn5/v4UoBoHQIAGEqqampGjJkiF588UVJUnhoiD74v0c0vFtX1rc7x+l0auqniyRJgUFB6jVipIcrAgAA3qLHPfepU59+kqTth37RyDfnKTcvz8NVAZUnMjxcT919lzZMf1YT+9yhiNCCu412796tMWPGqGPHjvrnP/+pXMJwAFUcASBMY+vWrerRo4e+++47SVLTetfoy0lPqHPTaz1cWdXyxZat2n6o4IllPQcPUdjVrIcIAAAqhmEYGvDoH9QmvpskaePe/Roz713lcRUUvFx4aKjG975D66c/o78OGqC6EeGSpEOHDumPf/yj4uLi9Morr+gMt8YDqKIIAFHluVwuzZ07V/369dPRo0clSYM6ttcXf5rIwz5+IzMnRzM+/48kqUadSMUPHOThigAAgLfxs1g0dNJf1Kx9B0nSyt0JGv/efOU7HB6uDKh8IVarRvToptVTn9ZLDwxVbGQdSVJycrKmTZumNm3aaPr06UpO5kE5AKoWAkBUaenp6RoxYoSmTJkiu90ua0CA/nb/EL30wFAFBwZ6urwqZ+YXX+pURqYkqd+YsQrgdwQAACqBxd9fw5/6q5q0aStJWrJtuyYt+EgOp9PDlQFXRqC/vwZ1bK9vn/qL5o4ZqdbRDSRJmZmZmj17tuLi4jRp0iT3AwsBwNMIAFFlrVmzRvHx8frqq68kSTG1a2nxnybqnk4dPFxZ1bTtYKIWrFknSWreoaNadr7ZwxUBAABvFhAYqBHPTlPDZs0kSQs3btYT8z8kBIRP8fPz0+1tWmvxpMf1r/F/UJfrr5Mk5ebm6t1331W7du00ZswY7dixw8OVAvB1BICocmw2m5555hkNHDhQx44dkyT1uzFOX/75CV0fVc/D1VVNooKl/gAALElJREFUdodDf/nXx3K5XAoMCtKAP/wfD0UBAACVzhocrNHPzVD9awtCj0WbtmgCtwPDBxmGoc5Nr9WCcY/qyz8/oV5xbWQYhhwOhxYtWqSePXuqX79++u9//ysnITkADyAARJXy888/67bbbtPrr78ul8ul6kFBmv37+/XqyAdVPTjY0+VVWW8u/VY/Hy0IS29/4EFF1K7j4YoAAICvCK5WTWNfnKno66+XJP1n6zb94R//lJ0QED6qVXQDvTl6hJb/dbIG39xJVn9/SdKGDRt0//33q2PHjnr33XeVlZXl4UoB+BICQFQpK1eu1O7duyVJ7RrH6pspk3RXu5s8XFXVtispSXO+/kaSFNW4ibrcNcDDFQEAAF8THFpNY2bMVEyLFpKkb37YoYfn/UO5druHKwM8p1Gd2nph6H1aP/1ZPdb7Dl1drZok6eDBg5o0aZLatm2r6dOn68SJEx6uFIAvMFwul8vTRaDypaSkVNrcERERslgscjgcSktLK9dcjjyb7r31VrVvEquxv+spix8Z9cXk2u3qO+Ml7T1+XP4BAZr4xluKjG548Z0MQxaLnxwOp0T7m4LFYpEMSS7JwdUU5kCfmQ59ZkL0WZVky8nRP56eov07tkuSOjRprLcfHq2rgoNltVplGIZcLpdsNptnC0WpGIYhq9Uqm80mThvLL9du1xebt+qd71Zo3/FfQ7+AgADdddddGjt2rFq2bFmu71GR52aeVLNmTU+XAHgdAkAfYZYA0GW3K+vzT+RH8Fcq0z/7QvO+XS5J6vfQWHW7e9Cld+KEyXQIJkyIPjMd+syE6LMqKy83V/+c+ox+3rpFktQsqp7++YexalC7NgGgyRAAVg6Xy6VVCT/p7W9XaO3Pe4qMtWvXTqNGjVLv3r0VGBhY5rkJAAGUhJQFVQ7hX+ms2JXgDv9iW7VW1wEDPVwRAACAFBgUpJFTn9MNt/SUJCUcOaoBf3tZB06c9HBlQNVgGIa6NW+mD8c/qv9OnqRBHdsrwGKRJG3evFkPPfSQ2rZtq5kzZ3J7MIAKwxWAPsJMVwDmLF5YQZV5r2Opabrj+ReVnpWt4OrV9fgbc1WjTikf/MEVE6bDlUkmRJ+ZDn1mQvRZled0OvXVO29r5cJPJEk1qlXT/PGP6sbYRlwBaBJcAXjlJGdm6qO1G/ThmrU6kZ7hft3f3199+vTRyJEj1b59exmGcdF5uAIQQEkIAH0EAaD3sDscumfWHG07eEiSNPLZaWresVPpJ+CEyXQIJkyIPjMd+syE6DPTWLnwE/1n3lxJktXfX7N+/4D6xLXxbFEoFQLAK8/ucOh/O3Zq/so12rhvf5Gx5s2ba8SIERowYICqnXugyG8RAAIoCQGgjyAA9B5TPvpEH6xeK0nqPuge9R09pmwTcMJkOgQTJkSfmQ59ZkL0malsW7Fc/35ppvLPPRX40dt/pyf69mLplyqOANCz9hw9pvmr1uizTVuUk5fnfj0kJER33XWX7r//fsXFxRW5KpAAEEBJCAB9BAGgd3h/5Wo9/XHB7yemRQs9MvPvsvj7l20STphMh2DChOgz06HPTIg+M52kvXv0zlOTdebc34u3tWmll4ffr9Agq4crQ0kIAKuGjOxsfbZxs+avWqPEU8lFxpo1a6ahQ4dq0KBBioiIIAAEUCICQB9BAGh+qxN+0oOvz5XD6VREnTqa8Mrrqh4RUfaJOGEyHYIJE6LPTIc+MyH6zHQsFotST53UO1Oe1NEDByRJ19atqzcfGqHGkaVcyxhXFAFg1eJyubRx3359tHa9/vvDDtny891jVqtVffv21cMPP6zu3bvL6XQSAAIoggDQRxAAmtuPh5M0+OVXdSY3V9bgYP3f7Fd0TUyjy5uMEybTIZgwIfrMdOgzE6LPTKewz2zZ2fpgxvP6cV3BkiYh1kC9OHSw+t10g4crxG8RAFZd6VlZWrRpiz5au0F7jx8vMhYTE6OhQ4eqX79+iomJ8VCF5UMACFQ8AkAfQQBoXgdPntLdL83W6bNnZfj5acQzU9W8Q8fLn5ATJtMhmDAh+sx06DMTos9M5/w+s9vtWvHpx1ry3rtyOZ2SpOHdumrygP6yBgR4tlC4EQBWfS6XS9sSD+nf6zboy63biqwVKEnt2rXTvffeq/79+yssLMxDVZYdASBQ8QgAfQQBoDkdTU3VoL/P0dHUgt/rfU/8Ue1+d3v5JuWEyXQIJkyIPjMd+syE6DPTKa7P9u/coQ+mT3OvC9iifpRm//4BNakb6cFKUYgA0FzO5OTofzt36dMNG7Vhz74iY1arVe+9955uvfVWD1VXNgSAQMUjAPQRBIDmczg5RYNnv6YjqamSpP5jHlb8wLvLPzEnTKZDMGFC9Jnp0GcmRJ+ZTkl9lnn6tD6YMV0Hdu6QJFkDAvSXu/ppeHwXnhLsYQSA5mO1WmUYhg6dPKWP167TZ5u26JfkFPlbLNq5Y4dq1THHepsEgEDFIwD0EQSA5nLgxEkNmfOaTqRnSJJuu3+4brv/gYqZnBMm0yGYMCH6zHToMxOiz0znYn3mcDi0/N8faemC+XKeG+ty/XV66YGhigwPv/LFQhIBoBkVBoAul8v9v9vWg4lKSDqisbPmyAgM9HSJpUIACFQ83lIDqphtBxM16O9z3OFf7xGjKi78AwAAqIIsFotuHTpM4+e8qtpR9SVJa37ao1unztCC1WvlPLdOIICyMQxDN8U20vBuXT1dCgAPIwAEqpAl27brvtmv6fTZs5Kk/mMf0S33DfZwVQAAAFdG/Wuv08Q33lLnfv0lSZk5OZr80Se6++9ztOfoMQ9XBwCAeREAAlWA0+nUnK+/0SPvvCeb3S5LQICG/WWy4gcM9HRpAAAAV1RgUJAG/mGcHp75kmrVqydJ+v5gono9P1Mzv/hSWbk2D1cIAID5EAACHpZ69qwefP0tzfrqG7lcLoVUr66HX5ipuO49PF0aAACAxzRp01ZPzH1Hvxt2vyz+/sp3OvX60mWK/+s0fbR2vRzcFgwAQKkRAAIetCrhJ90x/UWtSvhZknRNo1hNePUNNWrZysOVAQAAeF5AYKBuf+BBPfHWPMW2ai1JSs7M1J8//Ld6PT9TqxN+4uEUAACUgr+nCwB80ZmcHM34/D/6cM0692vtbrtdA/4wToFWqwcrAwAAqHrqNIjWI3/7u3atX6cv356nlGNH9fPRY7r/1TfVrnGsxvW6TTc3vU6GYXi6VAAAqiQCQOAKcjqdWrRpi1744j9KzjwjSQquXl0D/zCOW34BAAAuwjAMtex8s65v117rv/qP/rfgA2WfOaPN+w9o2CtvqG1MQ43rdZu6N29GEAgAwG8QAAJXyPcHEzXt00X64dAv7teub9de9zw2UWFX1/RgZQAAAObhHxCgrncN1E233qbVXyzS6kWfKefsWf2QeEi/f32urq1bV8O7ddGA9jcphDsrAACQJBkuFs3wCSkpKZU2d0REhCwWixwOh9LS0so1l8tuV87ihRVUWdWwZf8BzVnyX635aY/7tRp1ItV/7MNq0anzlX+H2jBksfjJ4XBKtL8pWCwWyZDkkhwOh6fLQWnQZ6ZDn5kQfWY6ldVnuVlZWvufxVr12afKysx0v35VcLAGdWqvITd3VuPIOhX2/XyJYRiyWq2y2WystWgSVqtVhmHI5XLJZiv6xOzgfgNlBAZ6qLKyqVmTCySAiuZTAWBGRoYWLlyozZs36/Tp07JarYqNjVWvXr3UoUOHy543Pz9fX331lVatWqVjx45JkurVq6f4+Hj17t1b/v4Xv9Dy4MGD+vzzz/Xjjz8qMzNTYWFhatGihQYMGKCYmJjLrut8BIBXlt3h0LIdP+r9Vau1ce9+9+uB1iDdct9gxd89yHNr/XHCZDoEEyZEn5kOfWZC9JnpVHaf2XJytGXZUq1dvFinkg4XGWsV3UAD2t+kfjfG6erq1Sv8e3srAkDzIQAEUBKfCQAPHz6syZMnKyMjQ5IUHBwsm80mp9MpSerbt69Gjx5d5nlzcnL01FNPae/evZKkwHP/Qc3Ly5MkNW3aVFOnTlVQUFCx+69atUpz5sxRfn6+JCk0NFRZWVmSJH9/fz322GPq0qVLmev6LQLAKyPx1Cl9vmmrPlq3Xqcyfn0H2hocrM797lS3gXerWni45wqUOGEyIYIJE6LPTIc+MyH6zHSuVJ+5XC7t3fa91i7+QgmbNhYJrvz9/NS56bW6tVVL9WzVQnUjIiqtDm9AAGg+BIAASuITAaDdbtejjz6qEydOKDo6WhMnTlRMTIxsNpsWL16sDz/8UC6XS+PGjVPPnj3LNPff//53rVq1SqGhoRo3bpz7SsKNGzfqlVdeUVZWlrp3767HHnvsgn0PHz6sCRMmKD8/XzfffLNGjRqlGjVqKDU1VW+//bbWrVungIAAzZkzR1FRUeX6HRAAVg6Xy6WDJ0/pfzt26svvf9DupCNFxqtHRKhj7z7qcuddCr0qzENV/gYnTKZDMGFC9Jnp0GcmRJ+Zjif6LO3UKW1b8Z2+//Zbnfjl0AXjLepHqUfL5up4bRPFNYpRUEDAFanLLAgAzYcAEEBJfCIA/OqrrzRv3jxZrVa98cYbqlWrVpHxt956S0uWLFGNGjX0zjvvXPKW3UKJiYmaMGGCXC6X/vznP6tTp05FxtetW6cXX3xRhmHolVdeUXR0dJHxGTNmaMOGDYqJidGsWbMK/ig6x+FwaOLEiUpMTFTnzp01adKky/zpCxAAVpwT6en6/kCi1v68R6sTftaR1NQLtolt1Vqd+/ZTi06d5V/V/pDkhMl0CCZMiD4zHfrMhOgz0/Fkn7lcLh09sF/bln+nH9ev0+lzy/acz+rvr7aNGqp948Zq3bCBWjSorzphVeQNXA8hADQfAkAAJfGJpwCvXLlSktS1a9cLwj9JGjhwoL755hulpqbqxx9/VNu2bUs176pVq+RyuVS3bl117NjxgvFOnTqpbt26On78uFatWqUHHnjAPZaVlaUtW7ZIku68884i4Z9U8AfSnXfeqZdfflmbN29Wdna2QkJCSvsjowI4nU4dS0vXvuMntPf4cW0/9It+SDyk42npxW5f/9rr1LprvNp0jVeNyMgrWywAAABKZBiGoho3UVTjJuo7eoxOJR3WrvXrtXvjeh3++Wc5nU7Z8vO1ce/+Ius31wkLU8sG9dWiQZRi69RRo8jaalS7Nk8XBgCYjtcHgDk5Odq3b58kKS4urthtatWqpaioKCUlJWnHjh2lDgB37twpSWrbtm2xT3I1DENt27bV8ePH3dsWSkhIcK/7V1Jdha/b7Xb99NNPuuGGG0pVF0rH5XIpMztHx9PTdSwtTcfT0nU0NU1HU1N14MRJHTh5Utm2vBL3t4aEqEmbtmp6401qeuNNhH4AAAAmYBiG6jSIVp0G0brlvsHKzcrSwd27dGDHdu3fsUNH9+9zrxN+MiNDJ3/M0Lc/7ioyxzUREWpYu5bq1YhQZHi46kac+xcerjrhYQoLCZHFz88TPx4AAMXy+gDwyJEj7svVf3sL7vmio6OVlJSkpKSkUs3rcrl05MiRS87boEEDSbpg3sKvw8PDFVbCrQVhYWEKCwtTRkaGDh8+7DMBoMvlkt3hkMPpLPjoOPfR6VC+06l8h0P5jnMfnU7Z8/OVk2dXrj1P2bY85eTlKTsvTzk2m3Ly7MrOy1NmdrbSsrKUdjZLaVlZSs/KVnpWlvLP/XFXGjWvqaeGzZopuun1ir7+etWNaSRLKW8XBwAAQNUUFBqqZu3aq1m79pKkPJtNxw4e0JF9e5W0d6+O7Nurk7/84g4FJelYWpqOXWTpG8MwdFVwsMJDQxQRGqrw0FBFhIaoWlCQQqxWhQQGKtgaqJDAQIVYrQoODFSINVDBgYHyt1gUYLHI32KRv8XP/XmgxV/+Fj/3uMXPT4ZhyM8winwEAKA4Xp9epJ63PluNGjVK3K5wrLRr2OXk5Cg3N7fU8+bk5CgnJ0fBwcFFvs/F9i0cz8jIuGRdCxYs0L/+9a8SxwcPHqwhQ4ZcdI7L5Xfu3U0/Pz9FlPNJaqnJp9TwkfEVUdZlCbBaFVGrtmpFRSkyuqHqNGigyIYNVad+AwWFhnqsrsrAu9Lm9NvlAlC10WfmRJ+ZC31mTlW5z4JDQhTboqViW7R0v+bIz1fK8WM6lZR07t9hpRw7pvSUZKWfOqV8u73IHC6XSxnZ2crIztYvyZW3FndxDMOQce5j0XBQMgw/GZL8/AwZMtwfKy43rJiJKirIrIhpjAr6maqChP53l/t8DYB5eX0AWBjSSQULopakcCwnJ6dU856/XWnmLdynMAAs3P9i+5alrqysLJ06darE8ezs7Er/Q8swjHJ/D2twxa5zGBQUpODgEFWvXk3hEREKCw9XeHiEwiPCFX7u88jISEXWrau611yj8PBw3jkFAADAhWJjin3Z5XIpPS1NJ06c0Injx5WcnKyM9HSlZ6QrPS1dGelpSk8v+Dwr66xycnKUnZ0ju73kpWbKw+VyyVXwiXikEc5nsVqrdPgOoHJ5fQDoK0JDQ1W7du0Sx0NCQirtaWt+524/cLlcRW6NuBzWoCC98MIL8vf3V0BAgPz9/Yt8fv5r538dEhKi0NBQ98fQ0FAFBwe7r07ErwzDkJ+fn5xOJ09zM4mK7DFcGfSZ+dBn5kOfmY9X91lMwzLvkp+fr6ysrCL/srOzZbfb3f/y8/OLfG2325WXl+cec7lc7t/nbz8vy2slMc5dQVi4z8VUVB9WpXnM+N+Wi/1vFhAYaJon3RNUAhXP6wPAoKAg9+c2m63EJ+kWPiK98Aq9Szl/u98+Xr24eX+7T+HnF9u3LHUNGzZMw4YNK3E8JSWl1Lc3l1VERIQsFoucTmeFfI+RI0eWe468vDzl5VXOu6pmZ7FYFBERoYyMDNP8AeDrKrrHUPnoM/Ohz8yHPjMf+qx4wcHBCg4OVs2aNT1dygUK+ywtLY0+M4nCPnM4HBf0WW5ubpE75KqyqtgPgNl5/eVR56+xd/56gL9VOFbaNREKD9Slnff87c+v62L7Xk5dAAAAAAAAwPm8PgCMiopyr+l2+PDhErcrHKtfv36p5jUMQ1FRUZc9b+HX6enpyszMLHbfjIwMZWRkSPr1acIAAAAAAABAWXh9ABgcHKwmTZpIkrZt21bsNikpKUpKSpIktW7dutRzt2rVSpL0ww8/lLjN9u3bi2xbqFmzZvL3979oXYXzBgQE6Prrry91XQAAAAAAAEAhrw8AJalbt26SpNWrVys5OfmC8UWLFsnlcqlGjRpq2bJlqeft2rWrDMPQsWPHtGHDhgvG169fr2PHjskwDHcNhUJCQnTTTTdJkhYvXnzBmhoOh0OLFy+WJLVr167EtQsBAAAAAACAi/GJAPC2225TZGSkcnNzNW3aNCUmJkoqeMDGwoUL9fXXX0sqeJBG4VV5hUaNGqV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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "esc_df_mwt = pd.DataFrame({'rew': esc_rews, 'policy': ['esc_mwt' for _ in esc_rews]})\n", + "cr_df_mwt = pd.DataFrame({'rew': cr_rews, 'policy': ['cr_mwt' for _ in cr_rews]})\n", + "\n", + "from plotnine import ggplot, aes, geom_density\n", + "\n", + "evaluation = pd.concat([esc_df_mwt, cr_df_mwt])\n", + "ggplot(evaluation, aes(x='rew', fill='policy')) + geom_density(alpha=0.6)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "bc5f9508-be4e-4ee9-9df1-0373715ae296", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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"execution_count": 3, + "execution_count": 25, "id": "eb58ebf3-882d-4944-9e19-2332f3133a18", "metadata": {}, "outputs": [], @@ -152,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 26, "id": "9ab73841-a5f3-4704-ab7c-0a71ca683a90", "metadata": {}, "outputs": [], @@ -180,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 27, "id": "a634dbf5-00af-44d8-b2d9-5ede8969e3e7", "metadata": {}, "outputs": [], @@ -201,7 +201,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 28, "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", "metadata": {}, "outputs": [ @@ -211,13 +211,13 @@ "" ] }, - "execution_count": 7, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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x4kSUlJQU+3CIQcbs9ba6fpPHgiAIT6HyWFDEgiAKDgkLgiA8RUQlLMhjQRSG119/HRUVFYZfTvPggw8a/q0jjjjC8b9nB/JYEAThKcSIhfh/ghhM5s6di3Xr1hXs711wwQW6LcIBIBgMFuw49CBhQRCEpxD7WIhGToIYTEpLSwe1g6aWyspKVFZWFuzv2YFSIQRBeAqKWBBEcSFhQRCEpxCjFFGaFeIYySSJtOGAE68zpUIIgvAU6ogFVYXkSygUgs/nw549e1BfX49QKGS7AybhfmRZRjQaxf79++Hz+RAKhXJ+LBIWBEF4CrEqJEYRi7zx+XyYOHEi9u7diz179hT7cIhBpqysDM3NzfD5ck9okLAgCMJTkMfCeUKhEJqbmxGPx5FIUBTIq/j9fgQC9meyaCFhQRCEp4glSFgMBpIkIRgMFr2UkXA/ZN4kCMJTxJNK+iNG5aYEUXBIWBAE4SkSgrCIUMSCIAoOCQuCIDyFKCyoQRZBFB4SFgRBeIoEpUIIoqjYEhYTJkyAJEkZX4sWLRqs4yMIgrBFPEnmTYIoJraqQlavXq0qNVq/fj3OOussXHLJJY4fGEEQRC6IQQqKWBBE4bElLOrr61Xf33bbbZg8eTJOOeUURw+KIAgiVxJJdYOsZFKGz0edIgmiUOTcxyIajeKBBx7ANddcY9pMIxKJIBKJ8O+7urpy/ZMEQRBZET0WQMrAWeLzF+loCGL4kbN586mnnkJHRwcuv/xy0/stWbIE1dXV/KupqSnXP0kQBJEVrbCgdAhBFJachcVf/vIXLFiwAGPGjDG93+LFi9HZ2cm/Wlpacv2TBEEQWYlnCAuaF0IQhSSnVMjOnTvx4osv4oknnsh633A4jHA4nMufIQiCsE1SVguJOEUsCKKg5BSxuPfee9HQ0IDzzjvP6eMhCILIi4yIRZIiFgRRSGwLi2QyiXvvvReXXXYZAgGaYUYQhHtIJmVoAhYUsSCIAmNbWLz44ovYtWsXrrjiisE4HoIgiJxJaFUFMiMYBEEMLrZDDmeffTZknQ8vQRBEsRErQkqCPgzEkoiTeZMgCgrNCiEIwjOI0YlwINW7gspNCaKwkLAgCMIzaCMWAKVCCKLQkLAgCMIzJHQiFmTeJIjCQsKCIAjPwISFJAFBf2rUAEUsCKKwkLAgCMIzMGER8EkI+tOpEDJvEkRBIWFBEIRniKcnm/okCYF0xCKWpFQIQRQSEhYEQXgGpiECPgkBH0UsCKIYkLAgCMIzsIiF3ych4EtFLBIUsSCIgkLCgiAIz8A8Fn6fkAqhiAVBFBQSFgRBeAbW0tvv8ynmTYpYEERBIWFBEIRnYH4Kvw88FUIRC4IoLCQsCILwDEq5qQ9+Mm8SRFEgYUEQhGdQUiESb5BF5k2CKCwkLAiC8Axq82bq8kapEIIoLCQsCILwDKKwCPpYS2+KWBBEISFhQRCEZxBbelO5KUEUBxIWBEF4BmUImUTmTYIoEiQsCILwDElZKTcl8yZBFAcSFgRBeAYmLHySMiskRmPTCaKgkLAgCMIzsOCEJCnlpvEERSwIopCQsCAIwjPwVIiUqgwByLxJEIWGhAVBEJ6BZT18ktLHgspNCaKwkLAgCMIzyILHIsjHplPEgiAKCQkLgiA8A9MQkgTqvEkQRYKEBUEQniEhRizIvEkQRYGEBUEQnoGnQnyCeZNSIQRRUEhYEAThGVR9LJh5kyIWBFFQSFgQBOEZWAEImTcJoniQsCAIwjMoEQsybxJEsSBhQRCEZ5DFPhY0Np0gigIJC4LwEO/v7cKjq3dxE+Nwg1WFSBKNTSeIYhEo9gEQBOEcl/xxOXoicSRl4NLjmg3vJ8syYgkZoYC39haqVIiPzJsEUQy8dVUhiGFOTyQOAPj78p2m9/vmA2vwsSUvoaMvWojDKhjMp+n3ScLYdIpYEEQhsS0sdu/ejS984Quoq6tDaWkpZs2ahbfeemswjo0giBxp6x4w/FkknsDzG/ahvTeKZZsPFPCoBh9Zp9yUUiEEUVhspUIOHTqEE044AaeddhqeffZZ1NfXY/PmzaitrR2s4yMIIickw59sbest4HEUlmSSeSxA5k2CKBK2hMUvfvELNDU14d577+W3TZw40fGDIgjCPjHBSyAZ6wpsO9DD/3+wJzKYh1RwknpVIRSxIIiCYisV8u9//xtz587FJZdcgoaGBsyZMwf33HOP6e9EIhF0dXWpvgiCcJ7etL8CMItXqO93wHPCQqePBUUsCKKg2BIW27Ztw1133YWpU6fi+eefx7e+9S1897vfxf3332/4O0uWLEF1dTX/ampqyvugCYLIpEcQDFGTSoi+aIL//0C318ybmUPIEhSxIIiCYktYJJNJHH300fj5z3+OOXPm4Otf/zq+9rWv4Y9//KPh7yxevBidnZ38q6WlJe+DJggik96IIhj6hP9rEYVFdyQ2qMdUaHgqxCfREDKCKBK2hMXo0aMxY8YM1W2HH344du3aZfg74XAYVVVVqi+CIJxHG7GIGUQt+gVhIYoMLyCmQoI0hIwgioItYXHCCSdg06ZNqts+/PBDjB8/3tGDIgjCPn3RuOZ7fdEg3t7vMWGh29KbUiEEUVBsCYvvfe97WLFiBX7+859jy5YteOihh3D33Xdj0aJFg3V8BEFYRBuh0AoNRn9MuX0g5i1hoZSbSkrEglIhBFFQbAmLY489Fk8++SQefvhhzJw5E7fccgtuv/12LFy4cLCOjyAIi2gbQYnVH+rbhYiFx4RFQlUVQn0sCKIY2J4Vcv755+P8888fjGMhCCIPtBGLgZj+gtrnaY9F6l+fJJg3EzJkWYZk1tyDIAjHoFkhBOERtF4Co5JTL6dCZNG86VMubzQvhCAKBwkLgvAI2ohFLJ49YuE18yavCvEpY9MB8lkQRCEhYUEQHkHrsTCKWESEFEl/LMF3+V5ATIUw8yZAwoIgCgkJC4LwCFqTYtQgYiEKjqQMRAzuNxRRtfT2CREL6mVBEAWDhAVBeAStkDAUFnGtydM76RBWbiqaNwEanU4QhYSEBUF4BG243ygVovVieKnklJ0CSZIgiU2yqOSUIAoGCQuC8Ahas6ZRikMbsYjFvbObF1MhgNDLgiIWBFEwSFgQhEfQDtsymhWSkTJJeCdiwXyoLA3CSk7JvEkQhYOEBUF4BK2QMPJYRBLWIhtDERaxYM2w/Dxi4Z3nSBBuh4QFQXgE7eKpJyxkWea3hwOpj7+XjI0ZqRCf954jQbgdEhYE4REy+ljoCAvxPpUlAcP7DVWYtvKlIxZBmhdCEAWHhAVBeISMVIhO+F+8rTzsPWEhG5g3KWJBEIWDhAVBeAQrwkKsHCkPBXR/byij9Vgw8ybNCiGIwkHCgiA8AiupDKVbWetFIpjY8PsklIb8ALxm3kz9y6pC2L9k3iSIwkHCgiA8AhMNZeGUYNAVFunbQn6fIkA8tOhm9rFImzcpYkEQBYOEBUF4BBaxYCkOPWHBohOhgA+hgHFkY6giC0PIAMG86SHxRBBuh4QFQXgE5pUoS6c4dM2bgrBg0z+95LFgXgrmsWAtvcm8SRCFg4QFQXgEFu4vCxubMpnYCPl9vI+FlyIWRn0syLxJEIWDhAVBeAQ22bMsaOyxYGJjuKRCAtTHgiAKDgkLgvAIbFduVu3Byk2Dfon7Dzxp3vQxYUGdNwmi0JCwIAiPwIWFScSCiYig35sRC20qJEjlpgRRcEhYEIRHSKQX1ZKgsXmTVY4E/D6E/Mb3G6okDVIhVG5KEIWDhAVBeAQlFWIcieAeC7/kzYhFUt+8SRELgigcJCwIwiOwNABLhehVhbCde8DnQ4jP0fDOoqtt6c0iFlQVQhCFg4QFQXgEKx4Lbt70aFVIRiqExqYTRMEhYUEQHoEJi5KQsbBgZZdBn0dTIVrzJnXeJIiCQ8KCIDxCRsRCt0FW6j5BYVZIxEOLLutj4fdpzJseeo4E4XZIWBCER0hoPBZ6fSzYzj3glxBMRyxiHoxYSNpUCHksCKJgkLAgCI+Q1DTI0jVvCi29vTjdNJGkVAhBFBsSFgThETL6WOiWm7I+Ft70WGRONyXzJkEUGhIWBOER2DgMlgpJypk79ZjYedPvPWGRMYQs/RxpVghBFA4SFgThEXhVSFpYAJlpjrho3mQeCw+lCbQeC6WlN0UsCKJQkLAgCI8Q11SFAJnRCCVioaRC9EyeQxXm0fRLNISMIIoFCQuC8Ahstx4K+JBeVzMW1JhqVoj3zJsyn26a+j5IY9MJouDYEhY33XQTJElSfU2fPn2wjo0gCBuwVIjfJwmmRWOPRdCDqZBERrkppUIIotAE7P7CEUccgRdffFF5gIDthyAIYhBICsIi5PchGk9miAZV500vmjfTT8WXkQrxznMkCLdjWxUEAgE0NjYOxrEQBJEHbLfulySeAtAuqNF42rwZ8CHswXJTw5be1CCLIAqGbY/F5s2bMWbMGEyaNAkLFy7Erl27TO8fiUTQ1dWl+iIIwnl4cyif0r+BCQkGi1gEPDorRNvHQhlC5p3nSBBux5awmDdvHu677z4899xzuOuuu7B9+3acdNJJ6O7uNvydJUuWoLq6mn81NTXlfdAEQWRix2MRCvg82TxKiVioZ4WQx4IgCoctYbFgwQJccsklOPLII3HOOefgmWeeQUdHB/7xj38Y/s7ixYvR2dnJv1paWvI+aIIgMuGpECEakSks0lUhPmFseiLJqymGOpmpEGqQRRCFJi/nZU1NDaZNm4YtW7YY3iccDiMcDufzZwiCyIIsy8pkT8FjYdbHgi26qdtlhAJSYQ52EGFWCp9PXRXipagMQbidvPpY9PT0YOvWrRg9erRTx0MQRA4kBHOimAox67zJzJuAdzwIFLEgiOJjS1h8//vfx2uvvYYdO3bgzTffxMUXXwy/349LL710sI6PIAgLJIRUhk/lsVDv1KNiHwu/d4WFRB4LgigatlIhH330ES699FIcPHgQ9fX1OPHEE7FixQrU19cP1vERBGEBcUPul5QeFRl9LNLfB/wS/D4JPimVPvBK982MPhZUFUIQBceWsHjkkUcG6zgIgsgDMdTv90kIBvT7WLAIBhMeQb8PkXjSMx4EWejlAVAfC4IoBjQrhCA8gBix8EmCx8LAvMlSBDyy4ZFeFkw/SNqx6R4RTgQxFCBhQRAeQPRYBEw8Fmznzn7utXkhCW0fC59+5IYgiMGDhAVBeACxKsTnM/ZYiOWm4r9e8VhkTjdlVSEUsSCIQkHCgiA8QFJojgXAcFaIWG4q/usVjwXvY6GpCqGIBUEUDhIWBOEBeDtvblrU72PBvmfVEkaRjaFKRh8LH3ksCKLQkLAgCA8gDiADBO+EdggZnxWiFiCeMW8mDfpYUIMsgigYJCwIwgNoIxbGHgtlVggAXpbqHY9F6l9/RipE9sw8FIJwOyQsCMIDJCx6LLh5M+BNj4W2KoSlQgC1wZUgiMGDhAVBeIBkUiss9D0WXFho7uc1j4XSx0IZrEaVIQRRGEhYEIQHyIxYZAqGRFLmVRPs594zb6b+9WnOA+Cd50gQboeEBUF4AG7eZB4LHfOmuLAGtH0sPGLelA2mmwJUGUIQhYKEBUF4gERGKiTTYyGmAoZLHwu/T+JpkRhVhhBEQSBhQRAeQBux0PNYiCWlXm3pndSYNwHqZUEQhYaEBUF4gMzOm5mCge3YfZJyPy95LGRZ5uWmPkVXKL0sSFgQREEgYUEQHoDpgkCGYBA9FukeFoLvwEuzQsSiDzFiwQeRUSqEIAoCCQuC8ABK5810xCKg47HQlJoCYudN4938no5+3PnKFnT2xZw9aIdJCg2wVKkQGp1OEAUlUOwDIAgif3gqROuxEHwV+hGL7KmQbz6wBu9+1In393bh958/2tkDdxBRWEjClokGkRFEYaGIBUF4gLg2YqEjGNi8jKDQNCpkwbz57kedAICn393r4BE7j2yYCqHR6QRRSEhYEIQHUDpvpr7X81jENXNCAK95LJTn6lelQph5c+g/R4IYCpCwIAgPYDQ2Xa+PhV/PY2Gw6CaH0C5fnAUiqapCvNWrgyDcDgkLgvAAfPiWpkFWVM+86bdu3uwaUBs23TzIK2tVCEUsCKIgkLAgCA/AIgu83FTHO6Fn3szWx6I/llB93xOJO3TEziOrqkKU23lVCJWbZiWeSGaISYKwCwkLgvAAGePCdSIRCY34SN3P3GPRHx06wsIwYsGrQtwbbXELVz26Dkfd/AIeWLGz2IdCDGFIWBCEB9DOCtGNWKR37OIo8WwtvbURi24X72ZV5aZixIJaelvmP+/uRVIGfvHcB8U+FGIIQ8KCIDxA5hCyzFkh+lUh5sbGgQxh4eaIhTLZVNKJWFAqxDokwoh8IGFBEB4gcwiZSedNsY9FNo9FVH17j5uFRfpQxTQIQFUhVonEFREpRn8Iwi4kLAjCA2iHkOn2sTApNxU7dIr0RdVCws3GPr3JpoDSwpz6WJgjtmxPJGWVGZYg7EDCgiA8AFsztamQRFLm0Qyl82ZmgywvVIUwYaHRFYp508Wlsm7gkCAs4knZ1a814W5IWBCEB0hoZ4UElI82Ew283NSnZ9605rEYiLl316+MTNdPhVDEwpxDfVHV9+29UYN7EoQ5JCwIwgMk0oumX9MgC1CEhWLwtNHHIqoVFgnd+7kB0bwpoqRCKGJhhtY/QxELIldIWBCEB2BrJu+86RMjFulUiEnnTcM+FpoIhdZz4SaSmnPA4OZNqgoxZSCuFo19UfeKSMLdkLAgCA/Ah5Cl11SfT8poZa0/Nt2ex0JbJeImtJUxDGUIGUUszNCmuXopYkHkCAkLgjDh/jd34KZ/b3B9vlk7KwTIrPjQ77xpPitEKzi0QsNNyAapED42nTwWpmjTXBSxIHIlL2Fx2223QZIkXH311Q4dDkG4h+6BGG789wbc9+YOPLxqV7EPxxTtdFMgMxrBO28KK69eh04R7WLsbo9F6t9M8yZVhVhB+9pSxILIlZyFxerVq/GnP/0JRx55pJPHQxCu4VCvUn7X1jVQxCPJDh9C5tcTDcxjoZcKMfdYsN4XlSUBAJlmTjehlJuqhUWIqkIsEYlr/TTufa0Jd5OTsOjp6cHChQtxzz33oLa21uljIghX0NmvCIuDLk+FxHX8BUFNxUfcZAiZccQi9TtVJUEAQJ+rIxYGqRAaQmYJrWjsdbFRl3A3OQmLRYsW4bzzzsOZZ56Z9b6RSARdXV2qL4IYCnT0K2LC7R4LbedNIDMawXbsAd2W3vqLLmuqxSIWAy7exRr2sWAeC6oKMSXDYxFx72tNuJuA3V945JFH8Pbbb2P16tWW7r9kyRLcfPPNtg+MIIqNGLFwu7DQq4jg0Yi4OmIR1EmFsA6dfs12P6aJWLjZvKkdxMagqhBraMtNKWJB5IqtiEVLSwuuuuoqPPjggygpKbH0O4sXL0ZnZyf/amlpyelACaLQdPQNnVRIwiRiofVY+HU6b6bul7mjZ1EO7rFwsbAwbulNQ8iswMpNK8Kp15oiFkSu2IpYrFmzBm1tbTj66KP5bYlEAsuWLcPvf/97RCIR+P1+1e+Ew2GEw2FnjpYgCogYsejqd+/wLUDoY2FS8cFnheh4LNj9SoLqz29sSJk3U/9mpkJobLoVWCqkujSInkg8I4JBEFaxJSzOOOMMvPfee6rbvvzlL2P69Om47rrrMkQFQQxlxC6TkXgS8URSVVHhJrRDyIBMj4VugyydDp0iSsTC/akQoz4WQV4VQhELM1jEoqYsiN0d/a4uLSbcjS1hUVlZiZkzZ6puKy8vR11dXcbtBDHUiWg7EUYTqC51q7BIzwox6WMR18wTAZQOnfGkrJsKSXghYpGl8oVIEUlHKGrKgunv6XwRueHOqyRBuIDM2QnuNbOZdd7UDiET0x/i/aI6CwmLYogRCxYZcBtGHosgrwpx53G7Bfb6M6MuRSyIXLFdFaLl1VdfdeAwCMJ9ZEQsXGxm46kQSaeUNN2uO8b7WKj3E0G/hP6YfpMsbbkpkNrJar0YbkDPZwJQxMIq7PVn5k3t7BCCsApFLAjCAG0o2M0tjpVFVbnNSh8LwLyttxKxUISFW9MhxqkQ8lhYIabx01DEgsgVEhYEYUDG7IShlgrJqAoxilgYDyJjYiQc8HMB4tbum0YtvYNUFWIJ9vozEUkeCyJXSFgQhAEZsxNcnApJWhhCZhSxMJsXEhd8GaXp9Id7IxbmVSFRiliYwt4nVaVp86ZLBSThfkhYEIQBkSHUiVCvQZa2XbferBDAfF6IWKLKhIVbQ+RGLb155IZ24KZENc3QBuh8ETlCwoIgDNCa19xt3jQeQsbc/nrTTcX76ZebKk21SkPpiIVLhYVxxILMm1bgEQsmLFz6OhPuh4QFQRjAUiGsrt/NF1qzIWRmnTcBc/Om2Aa8xOWpEC6uNM8vbPL8CAUmQCvCyvvdraXFhLshYUEQBrBUSHU65+zmFsd6i2owoN6px3RmhQBiZCNzEYklmS/Dh7J0xKLPpcLCqCrErE8HoaCtAErKNF+FyA0SFgRhAOtjwYWFi+v6TftYpBeHhM5009T3xqkCFrEQzZtujdxka+lN5k1ztB4LwN1imnAvJCwIwgBtxMLNLnklFaLcljkrxLwqxNS86fMpqRCXngcWsdCWm5qleogUsqy0dK8IB3j3Um2TOIKwAgkLgjAgM2LhzgUVMDdvsmqIuEFnypCJsOC+DL9g3nRtKkQ/YhGiVEhWEkmZV9WEAj7uS3Hze55wLyQsCMKAqKau382pEH3zpjrFYZwKMU4ViJUkZa6PWGSKK8A8IkOkEL0UoYASndKWXBOEFUhYEIQBvMUxm53g4otsQicaoaQA0rNCWCpEa9406fPAIhYB39CJWGREZALKELIkDSLTRYzmBP1ixILEGGEfEhYEoUMyKfOcPRvK5NYFFcjSx4J33jQeQgaYmzcDfsn9Hov04We09BY8JXrdRQn1eQkIpcWUCiFygYQFQegQE+ZKVAyBToTW+lgoIkHEyGMhy7Jqvkip24VFlqoQgNIhRrDzEvL7IEkSSgIsFULni7APCQuC0EGchKmMkXbnggoYRSw0s0IEI6aIkcciLqQNUubNdHjcpZEbo5beIZWwoFSIHuw9wt4bJUEybxK5Q8KCIHQQhQUbI+3mclN2uLqzQtKNr5QumtZaeovnIOD3oTSUEljubZClH7Hw+STuK6HKEH24sEh7K8I8FULni7APCQuC0EGVCuERC/deZPl0Uyt9LDLMm+nIhmbRFc9BwCcNgVRI6l+txwKgXhbZYF1X2XuGyk2JfCBhQRA6KEZHSQkLD4GqEFUqRLOYGpWbGnksxIhF0O9+j0XCIGIBKM+ZPAP6RAWPBQDFvOni9zzhXkhYEIQOYpfKoeCQ1+vhIHosRCOm4ayQDI9F6hxIUup3uMfCpedBNig3BaiXRTa4eTOgERYujtIR7oWEBUHowBbhoNDK2s0XWb2qEHFWiNaIKZLNYxFMezJKg+4uu2XpIL1UCE04NYelwbh5M8AiPO58rQl3Q8KCIHSIqyIW7t6pA1n6WMST/OdAyogpYtTHIq6Zhlo6RKebAspzJPOmPlFeFUIRCyJ/SFgQhA4xoZW10t446drOjUmdqhAxEhHTNEASMdrNKyPT08LC5Skho6oQINPISqiJJfTNm26uhCLcCwkLgtCB93wQuhAC7jX/JXSqQkIBJRKhKh018ljENR4LzWLjdvOmUR8LILO9OaEmZmDedOv7nXA3JCwIQgdVxCKgfEzculs3nW6q8VgYmTczIhaa8tSStHmzP5bgRkk3wapCdHSFKi1EZMLOCys9HgrpP8K9kLAgCB1Ej0XA7+OLq1vL78xaekcTSdUwsYxZGgapkLimPLUs3SBLlt25k+XnQC9iQVUhpmjLTcPU0pvIAxIWBKFDTFMR4XYzWzbzpjhMTEvIwLyZ0HgsxMiNGytDrKVC3Pn6FZtYhnmTIhZE7pCwIAgdtMZFt/eyMCs3BZTjDvoyP/JGfSxiQpMwIJUWYo/pRp8FM9bqPEVeFUI7cH14uWmAIhZE/pCwIAgd4oLHAnD/Di6h0/yK5csBpUTUrxOxMPIfaM2bgHIeXCksTFp6U4Msc5iI5KkQl7/fCXdDwoIgdIjznLM2YuHOhcksFQIowiJgFrHQ+EdY1EYUK2xuSvdA3InDdhSzclOeCqEduC5KH4vUyWMRCxIWRC6QsCAIHWJJlgYYGhELvT4WYlkpT4XoeSwC+j0etFEbAGioKgEA7OsacOConUWvrTkjRH0sTOFVIZoIHaVCiFwgYUEQOohVIQBQ4vIdHE+FCIuqJEl8QeWpEJ3tPGuGlJkKUXp5MEZXp4TF3o5+pw7dMcyEhVh6S2SiNW9SxILIBxIWBKGD1l/g9mmPfLKn5hPNIhR90Xj6+8yPvJGw4FEbIcrRyISFKyMWqX/NqkJoB64PExbhAEUsiPwZNsJi/e5O3L1sq2tbMhPuIib0fQDEVIg7L7RJo8mlAbXZUtt1ExBSIXH9clNRjIytKQUA7DjQ68RhO4qVlt5k3tRH29Lb7Z4iwt3YEhZ33XUXjjzySFRVVaGqqgrz58/Hs88+O1jH5hiyLOP8O97Az5/5AE+t213swyGGANqIRdjl5aYJg+ZQ7Pj7TVIhRh4LbbkpABzVVAMAWL3jkOtEOu9jYfIcybypj3YIWZimmxJ5YEtYjBs3DrfddhvWrFmDt956C6effjouvPBCbNiwYbCOzxG27u/h/9/U2l3EIyGGCjFDj4X7FiZZlg0XVa3HQi8VIo5XF8WCnnnzyHE1KA360d4bxYdt7vosKWPTM3/GqnvYAnrvf7fj03e9iUO90YIdn5uJZbT0TvexcOH7nXA/toTFJz7xCZx77rmYOnUqpk2bhltvvRUVFRVYsWLFYB2fI3x0SDGa7Xah6YxwH3FNVUhpyL1VIeJI9MyIRep7ngoxqQoB1FGLuCYdxO577MQRAIDlWw/me+iOkrBk3kxClmXc/H8b8dbOQ/jLG9sLeoxuhUcsfOqIRTTh3om+hHvJ2WORSCTwyCOPoLe3F/Pnz3fymBynsz/G/99yiIQFkZ24pq6fRyxcGBpOCAPBtBELbSpEr/OmkbCI6UQsAODo5hoAwAd73RWxYKdBd1YI95HI2C74Q1pdaEItBny6aUDtsQDIwEnYJ2D3F9577z3Mnz8fAwMDqKiowJNPPokZM2YY3j8SiSASifDvu7q6cjvSPBDDnR19FPokshPTzNZwc2g4KRyS1l4QtFBuKrb+Fg2ceuWmADC+rgwAsLPdXQZOK+bNaCKJne19/PadB931HIoFe91DAXXEAkhF6UpDft3fIwg9bEcsDjvsMKxbtw4rV67Et771LVx22WXYuHGj4f2XLFmC6upq/tXU1JTXAedChxCxaKecKmEBJQ2gLr9z4/CtpBCxMK4KSZWb6qVCxH4XKmGhU24KAM0jygEAuw72wU0k+dh0nVQIj1gk0NlH1wMtUU1Lb3GiL0UsCLvYFhahUAhTpkzBMcccgyVLlmD27Nn47W9/a3j/xYsXo7Ozk3+1tLTkdcC50CFcSLoH4lRyRmRFqQrRtPR2eypE0po3WR8LY/MmoN/nQTGwqn+naUSq5HRv1wCPargBsz4WYcGgekiIWpKwSMHauQeFSAWLWrjRV0S4m7z7WCSTSVWqQ0s4HOblqeyr0GjTH6LQIPLn9hc/xN+X7yj2YThKVLOourncVDTXaSMWrIOiWSoE0O9lwUyh2lRIXXkYkpTyNLS7KLUom6RCwrzhUwKHhM9/R39MZX4drmiHkAFC+o8iFoRNbHksFi9ejAULFqC5uRnd3d146KGH8Oqrr+L5558frONzhJ6IemBSR18U9ZXhIh2Nt9h+oBe3v7gZAHD2EY0YlZ4lMdThEQvWIIvv3tx3kTWrCmG7zt4I67xpICx0UiFG5k2/T8KIshAO9kZxsCeKhkp3vOZ8EJuJjyQaT6o2GrKcuh7UVQzv64HisVDOXYmLxTThbmxFLNra2vClL30Jhx12GM444wysXr0azz//PM4666zBOj5H6NPkxUXPBZEfHx1S8uyvbmor4pE4S1zTdZKZ19x4kTWrCmE7dbPppoDYJEt5ftp5KSIj0wvxgR7jaGWhUcamZ/5MTPUc0kQsKR0iVIX4FZNmmNqgEzliK2Lxl7/8ZbCOY1Dp1ywG2ggGkTu7hfLdPR3eKd3T7taVclP3XWRZVYj+gLHUcbP3vF5L79T9MhcRpZdH5u/UVYSAfcDBHvcsymZDyNh5iMaT6NJsLLoGaKOhTDdVzp2b03+EuxkWs0K0Tv5eEhaOITYcc9PuFQBeen8fXtjQynPvdsjoY8Eusi6sCjFq5w1kpkL0og+AvseCmzd1ohx1boxY6Ex4ZYjPjw1kY/RE3PeaFpqopo8FQBELIneGhbBgiruqJBWg6RkgYeEUYhjZTbvXLW09+Mr9b+Hrf1+DN7YcsP37Mc1unXfedGFVSJJ7CzJ/xhYHxbyZJRWi6mOhrowRqS5NfZa6XPRZYhPRzWaFROJJ9GqEBF0PxIiFaN6kqhAiN4aFsGCpEGbYpFSIc4j+FTftXsXGR5v39ZjcU5+4tiok4N6wcMJkpx4OqhsbhbKZN8XOm0n9clMAqCwJAgC6XZRGSPLITebPxN13bzpiUVOWeg49Efc8h2KhHZue+r973/OEuxkewiK9+DHDmXbHQuSOmFZyk7DY360cy95O+23cjfpYuLFBFp+RoeuxUH/E9UQCYF5uquexqExH/7pdtNtPmlWFCA2y2Oe/Ib3RcNNzKBZmEQtKhRB2GRbCgpUIKhEL2qE4hRixcNMFuk0QFrmYSmMZQ8jcbN5M79QtCAujBllh01TI0IhY8HJTE69JRPBYsNJo2mgIfSwoYkE4gOeFRTyR5OFdRVjQB8UpegUjXHeOKaZ/rduNm/69wdGOqPlHLLRj05WF123THs3NmxZTIQGdVIhJuWmVGyMWsrHACqmERerzz4TFcN9oyLKsTDeliAXhALaHkA01xB0mS4WQx8I5+gSRFo0nEYknMhazbFz1yDoAwLRRlfj8vGZHjkvsCNmZQ98S7W5dnPY4EE+gLJT/R6e9N4rasqDubAs7mDWGYn0sGIapkPTt4pC1OO+8qRexcKOwSP2rK7D8me/JBvJcAVCiFYA6YqEM3qONGGEPz0csWNhTkoC68hAAKjd1kl5N6Z7dsLJYVbJ21yFHjgkA+oTXOJfFjxsXfWqPBeBM983nN7Ti6FuW4s+vb8/7sXgfC5MUACPbrBC9iIVeBMDNqRA9naYVWD5JKZl1kzgqBuJrLrb0pnJTIlc8LywGoqkPRUnAjwpWbkrCwjG0XU3tirYtbUrFRmuXcw22evP0fmgjFn6fMgFU23AtF255OjUR+NZn3s+pz4ZIwiQFoI0eGbb01muQpRkdL1LFhYV7PkumqRCNoCoPBXjUZbhvNGLCa64XsSCPBWEXzwsL1qI4HPShIkx9LJxG22zI7kIjiokDDvbBEKs3+mMJ2/4NPX+Bk3X94kJ3MM+W0gkLfSwYhhELv9KZkqFtay7CFuWugVjewsgpzISFzyepqlvKwwFUhmmjASgRC5+kPncUsSByxfPCIiKUUTFhoQ3fE7mRSMo8LVBdynoC2Du3oshzslxV+xrbFZN6XSed3MHtEwRVa2d+kZqkmXkzw2Nh0NI7qFMVYqHcNJaQXbPwmFWFAGqRVRb2ozzsPp9IMVAGkKnfKxSxIHLF88KCf2j8Pn4hGe6hT6eIqoyxKf+KXYe9eP/23qhjFRfafhN2Fw9uXFRFLJy50EbjSVWqZl+eKSBT82ZGKsTcvKkeQmZcbloeCnAvg1tmbTCviZGwYCXDQOr4KTWaQq8iBFCEmBsn+hLuxvPCgjmewwElYjHcdyhOIZq+RqSNsXbPrRhJSCRlHOpzJh2iFY92Fz+9RbWUC4v8LrQd/ernmK+3xGxGRmYqJIdZITq/4/NJrvs8KV4T/Z+rhEXYz1Mhw32jodd1E1C6tkZc2MaecDeeFxZimI9dCCPxpKM9E4Yr4jmsKWMRC3sXaW3vC6dG2jODZXl6MbG7+A2mx6JDM7Z7X1d+KaCEhameDFsNsjRNwrQU08D53ked+Mp9q7HjgNK63Wy6KaAIQyAVsSgXPBZu8YkUA72umwBFLIjc8b6wSId2QwElFQLQLsUJxDRTZY4D3rSLkhOLVDSe5JGqUdUl6ce1GbFIZkYs2A4u36oQrbDQjvG2C8seWepjkW0IWUKsCjGOWABiL4vCp0K+9NeVeOmDNnzrwbf5bWYdSAGgVOg9UhZWUiFu8okUg5jOZFNA6GNBEQvCJt4XFsLiFwr4+IdnuOdVnSAmjBbPNaysFSJOLFKiv2JUJRMWuZo3lUXKsVSIJt2Tt7BIGqcAtOHtUCDLEDJVKsTYvAkUr0mWLMs4lBZn7+/t4rebRW4AoFQQWeUhP8oFoTGcrwcRg4hFiUPvd2L44XlhEdE4nlloXNt/gbCPuNPhDnu7wkLrhejP/wLfF0s9RsAnCd4Pe4t3zKTFcd6pEI2QyKUzqIjpdFNNKsQoYhHWad9sVm4KoGjl29r3CHutWLBFL3IDaFIh4QD8Pgll6evBcI5g8jkhBqkQilgQdvG8sNCWUpVT7bpjqEp5c0yFaMtCnYhYsNc8HPDlvKvWM286VRXCFjEWss+3qsLOdFMjkVCiM3CKTzc1SIVUlORWYpwvWvMrmwsjm5TdAlC1YWcbDLoeCB4Lw3JTilgQ9vC+sNDsPFn4s48GkeVNTFh8c202xGZT5FpVoocoJrmwsHFcsiwrxkW/Xiokv/cOi5aNTvs/8o1YmFaFBK2lQvQWESUVYhSxKM5uX+tRYVU1Zo3CAHVbdtaSnJrmCVUhhhELEhaEPbwvLDIiFumLITXJyhuxTC3XngBM+NXlmLLQI6ISFvZnWsSFXhpB3QZZ9i60/dEE7np1K/Z0pKassoV4THUpgPzTP2YRC214O1sqRBRNccFDowcT6T0F/ixpU0ltTFhk8ViUCeWmTMjS9UCMWKjPGw0hI3LF88JCq8apSZZzRFVdTXMrPWSPUZdusNXlRMQikRmxsPO4cWHaoxixYIuv3aqQXy/dhF889wE+e/dyAELEosaZiIWZxyLg96nMl4apECaahHx6jEdt9H+nvEi7fe35auOpkNT3xlUhmcKCRyyGcQSTf16Myk3JY0HYxPPCQhux4GYtMm/mDU8zBSSes7Yr2NjrM9LBSZNiJVAuoW6x5FK/QZa9987zG/YBAFra+zEQS/CoTmM6FdIfS6iqMexiNiMDUPssjKIPiscis9w0aPC4FUUS6Z2aqprOdGokW0vvSqHcXCsshvNGI1tL71hC5ueWIKww7IQFRSycIyZELNh5tVttwxznTFg40R5aec39fOHQDkszI64SFpktve1GLMSL8keH+vixNFaV8Nvzed7ZqiHCgrfAKPqgrXhJJmXeH8NIsCjpr8KKdG3Egn2fyNLH4rDGSv5/JRVC1wO9CihALUipMoSwg+eFRUQT5lPMm8P3QuIUYplaru56JWIxOB6L8hxC3XFhgZKkTPNmxKbHQhyutrdzAL3pY6ksCSqpmjzSIYp5U//nojhingItJZrnFksqzzFbKqTQi7I22sg8F0rnTf3fO2JsNf9/rUZYUFWIccQCsP+eJ4Y3gex3GdoYRiwoFZI3YldTMaQsy7JqQTZ/jMFLhYRzHDyn1xwLyK2PxUAsoXLV7+0c4BGL8pAfVSVBdA/E8/JZJLKkQsTu9awNtxa2iEQTSSSS6tC3UfqkokjGR9YAbUR5CO29UV4lkq2l99iaUlz38emQJCUFQlUhQj8ajYD0+yQE/RJiCZl8FoQthp+woIY4jhGLK+WmZelFJp5MtUcWdztGJJMyj3rUOSksVG3c7b/eRg2DckmFaAXD3g4lYlEeDqC6NIjdHf15mVazeQvEp6Hta8EoCarD3jHRwGpQScKrQgq8KDNh0VhVgvbeKI/2MAFlJLAA4FunTlZ9zwUxVYVkRCyAVIO1WCJOEQvCFp5PhWgH7FDEwjlEN7nYHtmqz0I0SdY5mAoRL5R88bMhLIxmZOTSIEsrLA72RpSIRdiPqtKA7v3skM28KQoDo0hSidChcyCWNPSZiBQrjcCEHesDwhpmZTsPeuSSKvMaUZ1mcAwepaOIBWED7wsLzUjgXHawhD5ixz6/T+IeBKvnVkwRjCxn5s38J03qVYVE4urF0gzeGMqB2QnaZk7tvVG+iJWFUhELID9hoTSGMhAWRuYLAZ9P4hGagVjC0Gciwvwhhf4sMWHBqmo6MqpCrD9WsZp8uYlsEQuAPBaEPTwvLLST+1hb3+F8IXGKmKaBkt0drFhiOSIdsUgk5bynh+qZNwHrUSo+I0PrsQjY91hoB44d6osKHosA7/9h5f24ekc7DvZkjlg362MBGA8R0yI2yTLymYiI0b9kAcsRBzQRi84M82YuEYvhez0wqgoB9BunEUQ2PC8sxN0rAKH8kD4o+RIziAZZLe1kJWyplIUfbD3IN2cvNsgKBXxc+FgVk0YRC9Zgyc5FVrtgHeyJ8vdeWdhvefT4mp2HcMkfl+OC3/83I6JjJxVihhiRiWeZbAoonyUA6CvgwsPOX2O6c2kknsRALJF1bLoexWry5SbE2TpaWMRigNp6EzbwvLDQTjelaYbOkeFfCdnLV4sXNEmS+EJld0Kq0ePm2rtEG4lhKN0prV9ktXNBWFtvILUwV1oc3vbapjYAwO6OfmzY06X6Ge9jYbBTP2nqSADqltZ6iPl0FrUxKjUFUq8bW8QLuTAz8+bIihD/+x19sawtvfUwMm/+Y3UL7nxlC/9bXsbo/Q44N9GXGF4Mv6oQcoE7htb0ZbeLodb/UhkOoHsgnn/EQhOlKg8F0NEXs54KMTCzMYOjncWGXZDH1JRib+cAr/7wSekZKxbF1EeCINm6vwczhZ4MSsRC/3evOXsaRlaGcfaMUaZ/Q5xwykSIkXETSBlBy0N+dA3EC5pKYOeUVdW090bR2R/jDb2MvCZ66L1nW9r78MN/vgsAqC4N4gsfG+/QkbsTba8fEacG7xHDC89HLLR98JXdK31Q8kXrX2GpELseC/baKAPDnBEWTLDYFTwxvlvXRCxCyo7eqsGURSzG1JSqbi8PBVJRGosRi10H+/j/PzrUr/pZto6TZaEAvnnKZEyqrzD9G2KTrHiWyaYM9poVMgLIzmlp0I+atPm1oy9qOuXViAodj8WW/T38/xv3dmX8jtcwGpsOKFGu4RC5IZzD+8JC86HhfSyi+VcfDHe0qZAy5l+xWRXChInSIjq/ktOo1rBrU/AYLaps4ZVl66OkmRG1viKs2v2zY9Jb2PQQW34bCQurTcmMKNEzb2apKClGlRU7pyVBH6qYsOgXUiE2rmpsoyGW2G7f38t/vnlftxOH7GqMGmQBynuePGmEHWwJiyVLluDYY49FZWUlGhoacNFFF2HTpk2DdWyOIHZhBJQLiSzbn/lAqFEuSKnFpyKkVAlYQYksqBdZpyIWWsNu3h4LodeD1fI7ttMrC/lRUxbitzM/SqXFcfPiaPW9nWphwQSynZ26HuKEU1ZuajQNlVGMqgoWlg8H/Lxct6s/pkw3tVUVorymLIq5q12JDu0QIkVexazclEcs6FpJ2MCWsHjttdewaNEirFixAkuXLkUsFsPZZ5+N3t7e7L9cJLS719Jg5oWEyA3tuc213JT9vlIh4bB506bgMSq/C/olnm6weqFlwqI05McIQVgoEQtr6R8xYnGoV13Cmq2lt1XCwoRTK+WmgHOdK9/f24VNrdmjA7IsK94cMWIh9AuxY94MB/xcQPakn8MhoUT4YE/E85M9zSIWrDyfUiGEHWyZN5977jnV9/fddx8aGhqwZs0anHzyyY4emFPENIuMz5cynPVGE+myyHARj25oo02F2G02pE2FWN29Z31cA8Fj9bjiBuWmkiShLORH90DcckmtErb3o6ZMmdPBZnZYEVOxRFIVim7X9MaI51BmqYeYCjE6B1qcaOu9dX8Pzvvd60jKwL8WnYDZTTWG940nZR6ZCPv9qEqfP1EM2DFvAilxdKgvxt8fokhJyilx0SBMovUa2s+xCKVCiFzIy2PR2dkJABgxYoThfSKRCLq6ulRfhUS7qwYUL8BwborjBNqdfZlNYyzrY8GrQtKLbb6vS2YlkD3BY9QgCxCm41q80PYJqRA2qhsAD+ErHgtjX4l28ml7j0ZYcBHgUCokllTKTbMs0k60xF67q4NXdKzcftD0vmJTtVBAiVgcEsSAXYGljbR1aM53W3dmUzIvwaq7KBVCOEXOwiKZTOLqq6/GCSecgJkzZxreb8mSJaiuruZfTU1Nuf7JnIjEM8N8zMBJKjw/tMO67EYGtAJA8Vjkad7UlpvaFJIxk4Xabh8U5gcoDfr5qG4gM2Ihph+0aAeU9UYTqvI/Fqq32mHTCP2IhfljOtHWe3ObkgLZuMd846EVFkpLdEVs2fWaaD04nZqI0L6uAVuPN9SIpgW+XsRCqQqhTRhhnZyFxaJFi7B+/Xo88sgjpvdbvHgxOjs7+VdLS0uufzIn9IxJ1MbXGbTlpnbHaGtLgR03b2oES5/FXbVZi+OysD1RylImJUE/aoVUSHX6/6qW4wbvRya0GqtKuHgQw/WKHyK/Ii/ex0KYbqqXdxexW2Ksx44Dikdr635zvxbbKPh9Kb8LE2iHepXzYdfDqhXELGIxJt3UrF3jafEaMZOIBaVCiFzI6Up05ZVX4umnn8Yrr7yCcePGmd43HA6jqqpK9VUoRKOXSliE7C00hD4Rw86bFj0WscHxWCiNt/zp40ovfhYFj1GDLEAxs1m90LKBZSVBH2rLxIhFgP8NFikwElTsPJeGlKjHwV4lPJ/gFRx5mjfTxxGJJVWj582wG6XS46CQ2mnNEh3Q9ihh02FFj0WuqZDugTiSSZnPHhlfVw4gvwFxQwFthE+EUiFELtgSFrIs48orr8STTz6Jl19+GRMnThys43IE0eilSoXY3FkT+hgNIbMq2LQCwKmqEK13oyzXBlm6Hgt77x12LCVBtceCeQOA7JUhSnmlj1eWiDt0tuP05xmxYBVT/dEEYnFr5aZW+3CYIZpRD/REDFNCADIED49Y9OWTClHSW6n+Nqnbx9eVZTy2F9FGHkWoQRaRC7auRIsWLcIDDzyAhx56CJWVlWhtbUVrayv6+/uz/3IR0OZjGXYXGkKfzM6b+ZWbsgXWsZbeOXbeNKuI4BELm5Uv4YA6YlGjE70wOm8sshMO+lFbnjpH4mKcSKoFXq6UstLCWCIjTWWE3SiVHmKqQZbNzZJazxQTaOwx/D4pp6oQIOVdYcZjv0/ilSCiMdSLKFUherNCKBVC2MeWsLjrrrvQ2dmJU089FaNHj+Zfjz766GAdX16IwiIsNDci86YzZDaisumx0IS1HUuFGMyHsVq5EDdokAUI5k2L752I0ARMjFIcP7mO/z9bx1FRnLCoR7swPj3mkHmzTPhcmLV5FqnI07wZTyR5qoGlhFo7jdMh2hJlZt6MJXJPB4mCmL13y0KKJ6bT68LCNGLBzMV0rSSsY6uPxVBrgc0uQgGfpMq7knnTGfjFPMd+EdqUBVukuhyuCqmwOc5dO1xNhD1HMTT81ze2Y+v+Hlx95jTUV6r7onDxFPRhemMlFs5rxvTGSoysUO6XzbQ6EMtMp7QLix0TQv4s0YVsKMIibto0SaTCZomxlg6hY+bk+gps2NOV0QBMRCsaWbSHEcwhHSRGtFgarzwU4BEmt6ZC1rV04NdLP8T5s0bjM8fmVm2n8qGZeCxoE0bYwdPTTY1a1ZbbDGcT+mgXcLa7iSVkROPJrMa/jM6bguCTZTnn2RcZs0JCdlMhxnMyyjQei46+KH769MbU8ZcE8aMF01X3Z+Ip5PfB55Nw68WzMh4zm09BFbFIL3bteubNvCMWSkpAeW2s9rHI7bPEohWV4QAaKsPYAPMqDG0beNb7hJEtwqIHfw7ClNbysNLQrMOlEYvfv7wZyz7cj2Uf7sfFR4/N6ofRIyH60EyrQuhaSVjH00PItDtiRrmQUyVyJ6opy2QpJsDaIq7dKbFFQpbz2yFlDDezufjxORk6u1+tQfUDoQ31+5pJmLIsK6IgaPxRq8hiWhXfx8yboS43dabzZrnQs8Cs5FakIs9yU+anqSgJ8IoXbWdREa0YDQV8qjb9+aZC2AJaHg4I59qdEYtNwoC0zft6TO5pTFQwypr1sRiwOBuHIADPCwuDiEURJjJ6EW1VSEAonbSy0GjLTUuCPr445lMZYtQgS5xgaYbZZE+2iLGIxYf7jIVFLCG0nxY8PloqhR2zHkrJqv4uOmFxYFg2Snnzr4TSjdHiELLeSG7TgtlnsCIcQB0TFmYRC1ZJJBwXKzkFcjsHlXyjIUQsQgHusXCjebM3EkdLu2Kaz3W8O6v+AcyrQqIJa58dggCGibDQXtTLbA6lIvSJ6zTWUQZ+WRAWmpSFJEmCgTO3i7lqSJWmpTcA9FkwoZnt1tljMY/FXsFo2NYdUZncWKRBPBY9KrJVhQgRC5b37xA6TVodcZ4N7h+J2TBvpn8nnpQtj5IXUVIPSsTiYI+xsOCpJeG4qgVTbDYhpIdo7mWRslQqJHU8/bGE68yL2m6gHx3KbQprJKE8Lz3zb0nQ3meHIACPCwsjj4XdYVlGdPRF8fCqXZ5voGNElC9omV1NrZj5tPlyIP/um3GdnHHI7+MXTSuvedykwqBMI5wO9qhLI8ULvroqyfijxlJAxuZN5Tyxjp1iHwunWnrzaEzEeiqECUn2e3bp0YlYmJkltZVEgNLLwsrx6iFGMHsFoVMZDoCdUrd9xrUluXs7cms7Lnbd1PM0hQM+fg4GaCNGWMTbwsLA7WzXzGfEHS9vweIn3sPn7l6R1+MMVbSpEMBeZYje7+crLPR6l0iSZO+4+EJtHLFgO1tt2F4slRRTcWZG1GyDyJQmW0rEQlzozI7XDuwcReJJVVMuM3w+SZifYn/hEVMh7LkdtFEVAqibjQWzmE31qBBSUew5lIUC8PkkHrVwW2WIVljs6cytlxAXagaCTJIkLjipMoSwiqeFRYRdHDXGOW7Ay/OD8ux7ewGkcutenyegJWHQ1dRONEh3kchzwqlKWKiOy3ovC7M+FqVBtUA5oAnbiy2pI1ku2oxsHUfFlF5NqXJ+2HNVyk2d6WMBKMLFihmSt8TOIX3FXo/ycAB1FayrqFkqRO89k5/HoopHjGKKeTN9Lmp0IkRuoC39PmM+ELPeH2ZwcW8iIEtttrEnCE8LC6OIhRPmzWg8qVpENuzpzPmxhiJi22UxFVJmoxOjXq8E7jfINWKRfkyfpD2u9K7L0nEZd97UeiyYoBxbUwoA2C/sJLk3wqQiBMhetaL0sUiNCZc04fmESRWLHcSwdwcXFtkfM59eFixKUxH2Y0R5qreHFfNmyG8QschFWKR/vzea4OeUiaUaPj3VXcKCnaPpjanZS2ZRHjPM5oQwlHkhZHYnrOFpYSG2QhaxYzA0oq17AEnBBP9hjuVeQxV1mVpmKsPK7kYvYsF+P9cmWYa9S2yUnJpON9UYf9nuenJDBQD1ohgRvBFmVGSpChH7WIgTPVkZpFPmTUmS+GeDdZvM1osEsN8yXYSJkYqSAO/R0ROJq4yvItpKIiB/82alEPFgZlwmIGtdWnLKhN/khtSgtEN9US4w7cBLxk1SSHY71xKEp4WFccTCXvmhHvu61DnO1hxznEMVZnAE1DtlO2O09Tpc5tvWWztLglERti4m4yazN8RoVzIp84mpE3QGVmmrU4zgfSwszAoBlPB3hyZika95E1BKTlnViZUIQD6j08WqkKrSAH8ORqkH7eA6QGvetH8Ogn4fT33sTX+O2TWiWnOu3QITfhPSE1hlOTcfiJWIRbZyaILQ4mlhYeSxEHPJuZZQtWnKvfbmmOMcqrBdsnbokx2TZFSndDBbs6jsj8l2tJooFV/8rJSbGpshWcQinpRxsDfKfSbNI1LCQiyV1Ntd61GZZfiaaN4EgOoytRfBLHVjF/b6sT4ZViIA+UUsFPOmJEmKp8FgkdQ3byoRh1zPAUuH8IhFiKVC7Jk344lkzn4HOzDhV1cR4ucsF5+Xleof6vtD2MXTwkKvmQ6Q2kGynZHVEd9atHXkhbiYuAm9ig5Af5H5n+c+wJfvXYVt+9XpIr3hR9y8mafHIqPbqo027hGdkkYGe34AsKcjtbsNBXwYXZ3yWIgLkFHnVy0sStMfS+iODNemVAY1YpGOirBzYC1ikXuUSWxIBSBrFYaZ4RfILRUCKOkUJmjZc7I7iOx/nt+Ejy15CY+s2pXTcViFeT5qSkO8TNes/4cReuW7WiqYuZWEBWERTwsLJYSsfpqSpJTI5RpyZ7uDGaNT5qnhF7HQNwxW8kFiqfPa1jWAP7y6Fa9s2o8/vLpV/RjxzO6Odttva8nmsbCy6zKKdAGpCA07RhY2ryoJKMPBRI+FQYM2LeWCWNE7Pq1AYYZClvdnqZt8PRapY1Efa2moMMKCRapqs8zn0BNravNmbuegSjNzJKMqxGLE4u5l2wAAP3rivZyOwyrs/FSXBVGXNr0e7DUeN2+ElYiFU31/iOGDp4WF2dQ+peQ0v+FJ00dXAkhFMJI5mKeGKkZlamzn15U+Pyu2t/OfLd96UHVfvYiFY+ZNA1+NlVSIXuMuESaedqebElWWBLmwENs/W60KCQV8fKHUSwGJLb0BZMwLMUvd2KVUaHgl/k0zKh1KhQDWIxZONsgC1OIEEKpCdGazGKE1eA5mJQmLoNSUBnVFrVWMxh6IlDvU94cYPnhaWCgDoDIvjvlOZWRh6KkNlfBJqZz7gRx2DEMVo1QIu8izi+qWNiX9sbujX3Xxi+mE2/M3b2b6NgB7uy6xvFMPdowsFVJZEkBtubKzZakJJYWR/WNm9rwzIhaDmAoRB8kB1oRFXhELg9SD0UKuJ0arVQ2ychUWakHFIjd2Jpzu7lAbuDcJA+qcJJ5I8rREdWmQ9//IJRUS0zFQa8lmLiYILZ4WFmaO53Le1yA3jwVbOOvKQ6ivTIUih5PPwmiXzCMW6YiDtlpmq+Cz0M4KAZSLWFeOuz2jVAjvr2FlhkmWiAXbXauERXpnK8vKe8NqKiT1GOpIj9nxaEsgnSo3BZTzxCi1ErHIw3Dbo4lY1JaZN8nS+0xrRUEuVGsiFkwg681mMUK7sO882Jv3cenRJZzn6tKg4rHIYWNj9HkRycecSwxPPC0szMxz5TbKD/UQc5yNaePecPJZxHVEAaCElNniqj0nLIIhy7Ju1IO58Dv78zNvGpWb5mveBBQRwIVFOIig38c7QLKojBVjHKPapBGTNoKi3UXHHZpuCqgrpgBrwoItwl02hYUsy7wfSGYqxMhjkfm+qxRSIaOrSmwdA0PrsWDv4+pS6xELbSpiT47zO7LBBGVlOICA35dXKkSvSZ2Wcio3JWzicWFhrMZ5G+IcPyxsZ1ldGkRDOmKxv3v4pEL4ADJN+F3xWKTOKxMWU9INpNgURnFYWNivLF5s0ezsj+Y0htvoNbczHE0p77TqsUh9P0IzRMuqxwIQFjALEQtx8Y0nkjwVYkXAZKOiRBOxCFkQFqXG0RYzInHl2JWGVGpjqt7vAOrX1++T8IWPNePUw+rxtZMn2ToGhuixCAV8gp8lyP9uf5ambwc0A+n2DlJvG/YeYT026irS5s08qkKsRCxyTU8Sw49hISz0LrhVWSZKaukaiOGRVbvQ1p1aTHi5V1mQp0KGk7Awys2y88pGb7NzMntcDQBlCqNYVil2/WOh51hCzmk2gXFViLUqoERS5s8tW8SCLSTse+3Yb6NmXXqwBcw0FcIiFiy60RdVdUC10iUzG2I5LWDNY1HFK4HsCQsxtF5ms9xUm1762UWzcN+Xj7N0vHqIqRDx/xVhpWlXtnQIa6utCM/BERbcuMmERR4RCyvD5uw0lyOKS28kntEKoRh4WlgYNUsClLys1Yvh3a9tw4+eeA8X3PFfJJKysmsoDaI+vWPY3zN8hEXcoCqksiTAZ1kc6ovy83vEmFRZLrvYGg0LKwn6+AKZS7fDrOWmWS6OYitpo0hDlWZXz95LI8q0EQtj87CWGoOQe0yISJQEtCWQMW4QBXLv4SCifW5GBlbV72iiVFZhwrE06Ic/vXhnNW9a2GHngvi8xf+rmnZlGUTGjvnwdAn6nsESFsK1B1AEbT5VIWaCLN/5PUThWPjnlTjxFy/jjc0HinocnhYWZqmQSmGioRXe3Jp6oVq7BvDuRx38Yl9dOlwjFmlhoUmF+IQ+Dy3tfTzdcbim3wdbILTDwiRJyujTYAejpmhKyZx5FERcqLOZNxnaiAW7wEcsjh4HjD0WEUGA8YhFWsD0xxI84ub3SY503hT9Cj7Jmlip0hh2rcJEntg7o7Y8S8TCgicgF9hnGMgsPa2xaODsTz8flvbb2zmQUzovG+z9xfxIdcI5s1vybiViUc4HC9KsEDfT1jWAdS0diCVk/O7lzUU9Fk8Li6iJeZOHby3ssmRZxoY9Xfz7VzftB5C6uJUG/RhZMfyEhd6cDwZbJHccTPkpKksCaBqRMri2dqb6fURNGvPYKfHTwi6UWm+AUrlg/pgD6fdM0C/xXbSWyhKtsEh9zy/wvZqIhRVhwRcvjbAQWs6zx6kMB/gUUpaac8JfAaifW2nQD0nKXmnCficaT/LzbwUm8sRKFMVjE9MdqmXHt2KHcbVl/P9a4WgUTdLSn37uk+tTwqJPmJbqJEx0MU8PE2NJ2X6Uz0pUTfFYuGteCqHm7V0d/P/b9vcOiqi1iseFhXHEospGxKKzP6baOa7ZeSj1GKVBSJI0LCMWRqkQQDm3rNyutiyEUVUlkKTUjvNgb9T0tWE7sVyEBbu4a6sZ2DFF4knDyZmAtYmkldoKAtY1UhOxyNZoSyRbxCLk9/FF3ueT+C6aDcNzKjUgPjcrxk0AqAgp6S87UQvWnE6sRGGvfVLW95vYqbSxw8h0LwhAiVBov8/2fmSpndoypQR0MHwWzMvBhIW6IsneNShbzxZASYXkM7SRGHzE1NuBnkhRqxQ9LSxMzZvcY5E9YqEVDO9+1AFA2V2xqpADPZGiqsRCYpQKAZRFcmc6YlFbHkLQ78OoylQp4J6Ofm6Q1AtpKw2gcjCjRY0jFnzxM4lSWYkyZEYsUsfLPBbtGR4LC+ZNwZBp5XjY/ZlRy6nUgLhbtyosfD6Jd9+0U2WlRCyUvxMK+Pgx6KVD7PQGsYMYmTl+cp3qZ1bfj6xqpCzkx+ia1Ht9MHrbtPcoA8gYuVaGWDmfYqqqNwdDNVEYRI/ftWdNc6T8PFc8LSzMdsV2PBZaYcHECFtAWSokEk8Om+50Zh37mGhTIhap88Qutns7+80jFnmkQvpj+qWi4uJnFp4eMPh9EW3EglWyZHgsWBdQG1Uh2mMzOk/s/vtYKsSh1IDYbIrNoLD2e/ZLTvu4x0KTehDMqVrsdDO1y0NfnYerzpiKz8xtUh+PxVQIN6OGAmhM99NoHQSHfrsmYiH+366B00rEIhzw8/fwUCs5vfOVLfjiX1Zi/e7OYh/KoMPWqR+ccxi+c8ZUlW+o0HhaWJipcd7Ux4LHginBRk3zHXbBKQ35+aI1XNIhZt0emeDafkBJhQDK+dvXFcnisWBNsnIRFsYud23zLj1yiViwnaO2tbKdiIVRHwtjYZH6W20sFeLQ7mSU8B630yE8lyZZvdHMiAWQ2VmUIcuy5YmxuXD8lJH43lnTMrw1Iyy2zBbTcI3VgxixYB6LskxhcdCmsLAaAeIR3kGcf+I0fdE4fvn8Jry++QD+5/lNxT6cQactvfY0FFFQMDwtLMzysVbNfABwIH1Bmd1UrbrYskgFgGHnszDr2McWBrbIsB3oKC4sBkwjFtV5VIX0R/U9FuLjml0cjWaNiGh3Akb9BKz4NfixCX0sRGe/0ULKIxZdzLzpTGpAFHqirygbuSw8fZqR6QyjiEU8KYOdGqdTIWaMtFhOLnpGeMRiMIQFi1iIqZBBjFgA4kZs6AiLd1qUKMXanYd0zcBegvlrxHWpWHhaWJjtbtjutTeayGpIYo18RpSHMaamlN8u5jhHDjthYZwKEUO0gLKzaqhKnaPsEQvjUHg2lKoQY8FiZjDUThLVQ/vBZYscy3P3xxLoi8Zt7a7ZsSVl9bAnw4hFKTNvDuj+3AnsPKYSsbD+mvGIRdhaxEKv9LYQMCF5IMtnu1/w97A2/06nQhJJOaMqRPy/XWFhNWJRaSHa5zY2tylD4Lojcd7116uwPiPa7rnFwNPCYsBkxyiGs7PlDZXRzn6Mr1PK0ihioZ8KqdUIi5r09w1p82Zb9wCfbKq3eLGFpdPBqhAgc/KqHlbEgFEZannIz5/PwZ6oLaNhOODnKQFxQdUb1AYovhWWCnEyNXDLRTNRUxbETZ84wvLvVNpILTJY3wdtxKKWC0uNsBBKWZ3uY2EGa4Cnbdmthb33BjNi0dEX5b1hah1IhViNWCiifOh4LNhng7HtwOAMhXMLrM+I9vNUDDwjLB5f8xH+ueYjPuQqkZT5B708nHlhD6Z7UADZL4ZMeJSFAmgeUc5vFyMWw637Zswk4jBCU65Xy1MhqXPUJkQstI2sAMEsl0NVCNs16kUceEmniWDh6QuLraHFWSmSJGGkcIGP2vBYAMr76YCQyzdKp7CoDotuOBmx+OLHxmPtDWdhdlON5d+pzuE1UzwW2lSI/iAysTmWz4ER8VZhG4iDvcYNqGKJJI/ilQUDg+axYGKrqiSg+uyx947dclOrJdFVeU4dLgba1tbb93tbWPRqJgUXE88Ii18+/wGufewdnHP7MrywoZWLCiDTdc6w2tZbfMGaRygRC9HoNtwiFnGeCskesWC7Ke6x6B5QhElAx/zpRIMsPWFRlj1cz1scZ1mov3fmNFSWBPDYN+erbh8hXODtzAoBlCqMg4I4Neo0qe214LSZ0UpjLJER5enXLEvbaxHuschIheh7bAazIsQMtmiLaQgt4lybVCok9V7vjsQdraQ4yEtN1em4Een3TruN8w9Y67wJmE/fdSvMzMiE4XYPRyyybaQLjWeExclT6zFtVAUSSRm3PvM+v2hJUvZhUtmEBQ8xhQPcJAUAc5pr+P+thku9gplHQmw2BCjVIMyt3NEX4/0O9PtYKF0o7fYFMeq8CVi7OPILbZaIxVVnTsW6n5yNOc21qtuZODjQE7XdJXJkhfK7jGzlpozB8FjYIdvwMD2MIha8rbdmkbRTZeMkQb+Pi50DBpUhLFLm90kI+lNt7VmlmJNRCxbFqdW8/op50971p8/iYpRr2/ZiwoTFvIkjAAA7DnpXWIgzkIw20oXEM8Lil5fMxlOLTkBp0I+dB/t4d8zyUMBw91VjITQOKBGL8rAfFxw1BucfORq//PSRqvDh8I1YZL6F2G6N0ZAWFtWlQb4Aso6EuubN9OsSjSdVkScrsByw3oeLhXPzLTdl6HktRHe+naoQQBFkYsTCyPNRq4lYFDuvqh0Zb4U+nVkhgLFIsdMXxGmyfb55RYjQBn1UtVIF5RRsYa/WzDMRe6jYEeN9Om3V9bDiT3IbrOLvqHRKb5uHUyFsjQr4pIJH9PSwfQTLli3DJz7xCYwZMwaSJOGpp54ahMPKjbJQgHfNe2HjvvRtxhd1/mHMcjFkarAiHEBJ0I/ff/5oXKJpojPchIXischcXLULKcv5SZLEfRYfHUoJC72ddllIachjJx3SF1XCznq13FamcLLFy8pUTz3qBHFgR6Sofrc3e8RCW5mibdpVaFgExU5Vgt6sEMB4wqmdabFOMzJLRLJfJ1I2upo1hHNQWKQXdu2gNCZoYwnZcpO+WCLJI49m10lALNUeOuZNttiyycp7OvtN2/kPZXqFqLrdNOZgYPvq2dvbi9mzZ+POO+8cjOPJmyPH1QAA3t6VjliYhIX4mOssF8OeiPEumMGExcHeqOfrpQHzVAhgHJpnlSGs9Etv9ylJEvdD2NkBM1FXEvTpGpispULyaxk9QkiFcIOqRWGh1y/BaEKvtqRX27Sr0LDjsSsEgVQ1jUitUcSiSB4LIPvGoV+n2ZfYt8UpuLDQCMmSoFJV1G6xrbfoC8kasbDoR3MTbLFtritDSdAHWQb2dhRvfsZg4ibjJpCDsFiwYAF+9rOf4eKLLx6M48mbwxorAShzKvRMfAwlfGjdvGnEiPIQJMnc4OUlzFIhAPCNkych5PfhjkvnqG5nEYuWduOIBaDswOzMPtjPO8+V6Kr2GoP+CCL5dnZkC5BYM291h63MexDMmwau/VBAGTwFuEBYCGLA6uhuHrEwaOkdiSf5gp36fvC6bmYjm0gQ23kzlIiFc4PIWKpPbL3OsFtyyoRd0C9l9ehYaS7nJqJxJRpTGQ7y6bUsUuo1eg2M0MVi0D+hkUgEXV1dqq/BZHpaWDDMTjRzsmcTAmKYyYig38cvrsMhHWKWCgGAa88+DOtuPAufmD1GdTuLWLCQspEwUUr8rJ3L3kgc3/vHOgCZnTEZ2iFheuQ75IotJkzYAtY9ASN1yk3NuseKlQHaHWyhYaItKVvf1RpFLCrCAV7GK3427UyLdRpmQDZKa/SZRCxaO527HhhFLAD73TeNUlF6DLXOm70R0czox7jaVMOyFo82ybISVS8kgy4slixZgurqav7V1NSU/ZfyoHlEmSpKUWryoWEhV7MPoizL3GORTQ3yUPawEhbGbyG9C9YozbwVw4gFW2S7rV0k//PuXh4F+cSRo3Xvw0pBB2LqnbCI1YZBRjDjKnOkS5Kx+NIyUidiYdZiXBRQxY5YiFNJLS9sUf2IhSRJugbOYlWFAMCYGvPoQ38sdY0Qrz1MZLZ2ORmx0PdYAGL3TWvXHyNhp0fVEGuQxRbacMCHgN+HJh6x8KawEH2AbmDQP6GLFy9GZ2cn/2ppaRnUv+fzSZg2qoJ/P6LMeCdnxcneF03wTnfZXrThZOBkzYACNh36WlOlkbDgZjmLF8nXNu8HAJw9YxQuP2Gi7n3KBVOoUdTCruFSi3ZQXTjgs2ymquPvxxhvM28WsRgv9FQptnkTsNeKPZZI8uemt7DpGTiLmQphLbqzRSxKBz1ioZ6sLML8PVZTIUapKD3Y3+uJxPmmws1oF1oesWj3ZiqkJ5IZMSsmg/4JDYfDqKqqUn0NNpMbFGHRoLnQi1ipvWchNZ9k7tcAhJkCw6CXRbZUiBHaiIXRImE3YrE13XH10uOaDe8jSRJq0+kvI4NbxMLYdDPKwwGV98FO2L62LMSH3LFdv1GDLEA9hEpr5iwGXKhbWNiyGQf1DJxGRtZCMEaIROnNFtIzb7KIxYGeCBdR+dJpkgoZaXEKK8NOxKK6NAimj4eCh0ybvh7n9YjFcEuFFINJI5W222YjZEcYNOIR6REmMGbbeQ6niAUzb9rtKcDMmwyjnfbIcuseC1mWuSmraUSp6X15h0KDi6OVIWTZGF2tHIOeyc4In09SVZUASiWE3mJ63IRU4x9JAg4fXZnx80JTa8HDwmCLWsCnbxzUjqAH7E2LdZq6ijACPgmJpKzbtl9PWIwoD/HPR1u3M9UISiok833Frj9Wq1DYtU2vmZwWv0/iHiU7hupi0cvHMKSeG7su2DFv2h3oVkyGfFVIT08P1q1bh3Xr1gEAtm/fjnXr1mHXrl1OH1vOTKpXIhZ1FcY7OfZB6YnEDeubrRg3GcNpXkiUDyGzmwpRRywqDc7ryEpmZMx+Ljv7Y/wiyXYmRjDDrlEe2mqLYzPEBmF6IWsz+K4zfXwRk5LV06c34LefOwr/ve50V9Sus1SOldesN0voVk+kFzMV4vdJPNq2R6dksY+3klfez5IkYVS1vcU+G2bmTSZorXb6ZK+B1cVIT+y5Fe1Cy64Lbd0R/hk3459rPsLRtyzFrf/ZOHgH6SBD3rz51ltvYc6cOZgzJ1VGeM0112DOnDn4yU9+4vjB5cqJU0fy/08aWWF4v8qSAO+eaFR/32OjjGc4RSxyTYVUlQZUC4PRiF9lbkb2ixi70NeVh7JGGrLNVBiI55cKAZQQOJCLsFCn05QGWZnHI0kSLjxqLMbUmEdpCgVLO2qnSuqhdN3Uf/2ZSBd3+vn6X/JltMlgMb2IBZC9msQO8USSG171zJuNaRFjdVS73fB5nY0oYrHRLrS1ZUGe8mFdf834+TPvAwDueX072hzsQzJY9NkUiYON7U/oqaeeClmWM77uu+++QTi83KgqCeL5q0/Gbz4723RCo88nCTMA9D8sdkJMw1FY2E2FpLpvKguv0XkdWakIi2wtitlETe3wMz1GlGWLWORfeaBKhdg0VWq9JcX0Fdilwcb7X688U/VYVXoRi+J13gSA0TXMwJm5MDGhpE0rNNqMIpjRLVRk6FUBib02rPQSsbvL1Zu+61a0121Jkiz3sujsi6kMsP/demCQjtI5emz4ZQqB+69WOXJYYyUunjMu6/2yNb7pzbKzEtHrnOhVWAvjkhzeyKLvxThikbqIRRPJrG2EWbSpxkJ0IFvEIuJAxGJ8nZKOsRux0L4fo0UM/9vFTqfJrBGLyszPklmFTCEwa9HdnxakWoN3Y1ogOSEsmHGzLOTXLfNONYZLVWzZ8blY3eXqlUO7FRbZESPNzGfR0m5u4Nyyv1v1/bpdHc4enE1e2NCKb/z9Lby/17gHFBu6aaXCpxC4/2o1yDRmKQnrN5jAqEe9ML3Tqz3pGUahXyuIEQsjj0VJ0M8X5WyhXS4syixELFhTNANjFjdv5mEQnCCYh+0KCx4658JiCEUsqlj6wgGPRUXqPLjFYwGYd9Lsj6rNggwesXAgnM6NmwZRsFDAx9MVVoQMn9pscYCd3QZcxUQvGmM1YrFVM6zsg9Zug3sOPl0DMVz7j3fw/IZ9+Or9bxlGb7mQKvIwQob7r1aDTCPPm+q/2XptLKC1ZUF+0XNyVLIb4XX7Oezs6y1ELADlQr4nS0tklgrRjhLXQ6m6MDdv5togCwAmCsJitGbSazb44pXOAw+lVMioSiVikS19xaeBGlwImUg50KPM3jGrkCkE/P2oZ97U6WMBiBuX/K8HPelUiFkzNO6zsPD37LaBrqtQXhO3o5fCttp9c1/63LHhZR/u67Y1MdZJ1uw4xIfK7e7oxzsfderej2/0hktLb7fDP/gGOwqjnYgekiRhbDoPu9ujPemBVHmn3jRHq0yuTy28Ib8PNaXGUQZmSsw2OIhFLGotCAtW7rrPoPwv4kC5aXVpEH+9fC5uufAIfM6kr4YeLI/PFoZih//twMRAJJ7M2qExW8RCb/ZOvu3W82VsjfGOt88gstno4IRTtsCYCouq9GfGQoTEbolinaZiyc3kE7FgEbfjJ9fBJ6UavhXLN/euRkis2HZQ934sZV9WJP+RFnfETYpItg9+r41UCACMrS3FtgO9+MiC83ioEokneTdSq+dF5NLjmlFTFsKYmlJTYWJ1iBMbKmYlFaL4ACKQZVlVpplIyryMNh9hAQCnTx+V0++x57yvO6I6nqEgLEqCflSWBNA9EMf+7gHTNBATpkbCgs3eOdgbxf7uCEZWhIueCmlOe2cO9ETQG4mrFi2j1CDbJbd2DSCWSJq2wM8GM29WmBiC2d+z0gjKtnkzh8GAxaJPp00AOze7s5wbVonUNKIME+rKse1ALzbt6zZttjhYfLgvlYZprCpBa9cAVm9vxzdPmZxxPzsp+0Lg/qvVIMMc/EaGM7teAuXN611hIXZNzCUVEvD78InZY3DM+FrT+7GIhV7oWYRFLKz4GdiuOhpPZpQYi76YfFIh+TCyIgx/uhHTgZ6IEv73u2Mnkg1RuJmRLRUCZDZ8KuasECD1/mLptl0aA2BfelaIVpA2VIZRGvQjkZSzmgaz0ZP2WBj5kgDFOLzzQPa/ZXe+BHs92rqzp7qKjfLcRPMmE4ZR/v7Tg0Un6ivCfFr2piL5LNgG9ZNHjwUAvLXzkG7FD28IRqkQd8BykoYRC5svGE+FeDhiwXaboYCP9wEZDKxHLFgqJHvEIhzw846r2vQXM26y+xUDv0/CqErlPckjFkVaTO3CXrNs738jT4KI9rOkNC8r3sWTzWcRp9cCQH809TppNyCSJPHFfsdBtSnQLj0WUiET6sot/y07zf8AJbo7EEtamgdTTHoimcK1ujTIz51ZOoR5SEZWhjF1VEpYsMhBoWHRlbOPaERp0I/O/hi27O/JuF+2CGChGRpXq0GEuba7B+L8zSjCOupZzV2NHQYRCzu+k3wYnWXwE8OOeRMQhkNlCIvUax30S4MqmLLRKBg4eVVIHiH0QsJ2hdl25/3cxW4iLDSfpWy9LwpBc3rh3tWuXrjNPhPMzLvdQhTBDJ4KsRCx2HGwN2tUwU7zPyAl6FjUYo/LN05G/hF2frYfMBZeLLVaWxbkAy0/3Je5mJvRE4nrzpSxw0AswUXO+BFlOHJcNYDM8tdoPMmHQlIqxCVUhAN8B7tD583WbzDa2Qhm8PJyxCKfihA7jOWpkH7Ti6SdVAggGDg1goWF2vMpNXWCsWmTWcuhPtOx6W7EaEevRYlYGH+ueFqxQy0sitm2WO/5ybKstPTWERas/Fjv+qLHlrYevKfj/mfmTbNKqnG1ZfD7JAzEklnLfnOZLzFmiERkjaIxU9LjHrbq7PqBVHdTZjyuKQvhsHTEYrONypCt+3tw0i9exmm/ejWvrp0sJRMK+FBTFsRRzTUAgLUtHar79asG+lHEwjWwKgW9N5t2mE022C5rb2e/pe53RsQSSXzlvtU45zfLTBujFIN+C2FsJxhdUwK/T0IknjTM2cuyrKRCLE74bDTwAfBQe5Gd1RPTu6pt+3v5TmQomDcBoDm98Go9CFr6LES9tFUY7LM42ILWjGadtEY2M/NEG+mJt3cdwsdvX4YL7nwDL72/T/UzpdzUWECHAj4uyM2ETDIp5yTUxtawklt3C4ueSKbHAgAmp4XFljZ9YSFWM9WUBjFhZDmCfgm90YRlMXXPsm041BdDS3s/7ntzRw5Hn4KVxNdXhCFJEuaku0iv0wgL5u8J+qW8zMFO4o6jKDJT0mPWt+q82ezmrkZVpsx3sYRsqVGQEc9vaMVLH7Rh075uLHn2g5wfx0lkWcZvln6Iz969AoD9dtV2Cfp9fNdqdFHujyW4D8F6xMI8FVIs4yaD7XDX71F2rWa7VDfBFt7swiL758ooFVLMiMXU9LViU6tyrchmZuYRCwvC4tFVLYgnZcgycMfLW1Q/4x6LLM+f/T1toyeRXsG8aCtiUa1EEd2KLMuGc1DMrvWAkgapDAcQ8PsQ9Pt4KmuzxXTIqh3t/P/PvLfX3sELsOobVubLxlNsau1SmU+V0m33XCNIWEBQsaYRC2svWsDv4zvi3R2551Rf27Sf//+Nzftd0e1u9Y5D+O1Lm/n37EM6mHAzmsHui7U5Dvgky33yx9ToGwydGJnuBOPTz3n97lSkKuT3FdWwaAfmsWjvjaJ7wNjgZyWdxkTlvu4BROIJpQ14EcO909Kh8QM9Ed7amh2XkZl5wsh0evSQ4pkx4s1tylyKdS0d2LhHiVay85lNZE5rYL4AY8MhW4z8PslWNMxqpVYxicSTiKejxVphMZkJi/36HhRmSq0pVzYp02wYOHsjcWwTBN2Og32qQXp2YP1CWCv10dWlGFUVRlKGKlWWTxfkwYKEBYQ3W5uJx8LGizaW15Lnruo3CBeUpAy89mFbzo/lFM+uV6vvMTa7SubCBGa2MtjtMWFRXRq0PDqcLdw7NY+pTDYt7sdC7NwJDJ1oBZCKYrFGZWY+Cyt196lptT7IcspsxzKLxZyHUB4O8HQPK0EcyBLVrK8IozzkR1I2j+TEEkkenZmbLsV+bE0L/3m3hc6bAHiJpNlCyI2bIb/lzw2gCAs39+kRI0jaFtcT6srh90noicR1myJ2MiO40LhPERbZIxbsMSvCAUxPvw5rdhyy+QxSMONmnZDiPUonHWI0AK+YkLCAYujZfqA3Y0dht0EWICyGFs1aWhJJGZvbUheFC48aAwB48f3iC4v1u1Mq+eRp9Thu4gh8Yf74Qf+bLKxrVJfPBpTpjZE2gjnDdx/q51NaASDCUiFFjg7UlgVRJSwe2RYSt8FK9MxmLLC8sNnFUJIkHrESd2jF9FgAysLNnh9P6xgclyRJmJj2cZkt9q2dA0jKKT/NN9JNkP7vnb28uqDHotnSirDIxbgJKJ+dbft7XNvLQvTiaCNIoYCPp7P0DLKHetncIeV6ws7nhj367bRFmCF8VFUYcyekxOHqHIWFkgpRRiAc1ZR6TLWwcNecEICEBYBUyLW6NIhoIokPWtVGyVwiFlMb0k5igzxeNg72RBBLyPBJwBc+llq8X/9wf97lS/kgyzIPy/6/8w7HP74xHw2VhYhYmOenWcTCjrAYVVmCcMCHeFJW5YrdkgqRJAmT6pU0k92Lf7GZOSZVFseEqB683DRLqSNLt73zUQeAVDSpmKXAAPhOlF0rrPTkmD2uBgCwdpfxIsNmWIytLcUp0+pRWxbEgZ4I3tyaauPcbcG8CaSuP5KU2vEazcQx8iBkY1J9asffPRDP2gStWGTrKDprbOr9+Z7O+7OjP3OgITNNbtrXbZreA5SIRWN1CeaOHwEAWGPympuhpEL0IxZM2Fl5/xUaEhZIXciZMeYdQQnGEkluDLSjBtnFcIvN2mcG69vQUFmCo5trUVsWRNdAPKPMqJB09MV49EYcCz7YsHO5bX9mNAlQp0Ks4vNJPJwthuvdYt4ElAFIwNATFrPGpY7dTFgou/wsfoF09OOdltRjuWFXxhYmtmu0ktZhXWbX7DReZFgaZFxtGUIBH847cjQA4Km1uyHLsqUGWUBqgWFlsUYVZb05GmHDAT+PyBaraVQ2sg1XY/0gtHM4AHUPC0ZDVQmaRpRCloG1WUaoM2ExqrIEc9Lloe/v6crqrdGDicI6QVjMbqpG0C9hb+cAT6v1usB7pKX4V1CXcBRrPtKivNlUbm8bLxpbDLcf6M0pysDfnNWpcsuTptYDAF75oHjpECZ2RpSHCmokHFdbiqqSAKKJpO6FrItFLGymC/R8FkrL6OJ/QNniBWTfoboNFrHYuLeLTyYVsTPEjoet0yLFDX6To9MiYXNbD7oGYpZ2jEc3p35n/e4uVet4EebJYuWiF89JtXF+fkMrDvXF+Lm0IjSP5BGSDt2f251sKmIl1VJMFP+I/nli5+bdjzoy0jls4F2NZqPCow8mwhAA2tJRnFHVJWgeUYaaMv1IuBV4KqRcSYWUhQKYk34vvb45ZfR125wQgIQFhzcfEcJW7AUL+CRbDYrG1pSiNOhHNJHMWnanB5tsOTpdXXLa9JSweFWoFCk0bF5DY4EH8UiShJnpRVYvx5lLxAJQfDDbBB+M0jK6+B+LmYKwsCuais2k+gqUhfzoiyZ0L6gDMbHvQxZhkY5YMEZY7FUymIysCKN5RBlkOdUFkZvnTATp+LoyjKwIIZpIYvV2/cXpIx6xSAmLo5tr0TSiFL3RBJ54+yMAgE+ylpY9On09e9sgDJ9t8TWDpXrdKixYxYuRAJs+uhKlQT8O9cUy0iGsJ452oCHzSyzbbH4NZtfuxqqSVCQ8LWLeySHafEBTbso4acpIAMAbaWFBqRAXc0zzCPh9ErYd6OXtiHtzbF3t80mYmm4F+/5e+x8+MU8HACdPrYckpXaARsPSBhvtMRUStsiy8kuRrgH7HgtA2XWJoWK3eCwAJQUAALPGVZvc0334fRKOn1wHQF8Miz0UshkxJ9SVqYSeuHsrJnOEhZs1VTITt5Ik4awZqYm3YqWHCJtIyoSFJEm46KhU1OLuZdsApESNlSoOFlVZu6vDdGhVLmm2w0enUl1vZ0kLFIts0ZhwwI/TpzcAAJ5d36r6mSIs1K/lmYenXru1uzpMZxfxaHN6AzabeyKyGz9FkkmZR09GVqjf8ydMTQmLN7ceQCIpu6IMWwsJizTVZUEckw4xvboplXLIJ8TETDbZQmd6tHaq35x1FWEevnutSFGLvZpjKiRMWKxtyTyXuUYsZqQ9DBv3dPFwKC83dUHPiFDAhx+ccxgWzGzEpcc1F/twbHPqYakLN/ssibDPVUnQB18WI2bA7+MXZ0BdeldMWGrj7V0dPC+fbVbN549LGbH//c4ebNbZ7X8keCwYF6aFBWu2N9qisD98dBVKgj7DoVW5mjcBYP7kOvh9Era09eQ9sXUwsDIO/uMzGwEA/3l3r0p4sblD2oGGo6pKeAnwcxoxIrJPswE7qil17WLmY6sc6ovy1Jc2Snfk2GpUlgTQNRDHux91WGqPX2hIWAicllaxrLSTubBzyUMys9Z/txzIcs9MeCpEuIicdlgqHfLCxn26vzPY7NM5pkLxsYmp/Ob63V0ZvfdZualdYTG1oRJBv4SugTi/oIsLnhtYdNoU3PWFY1wRQbHLqen365qdhzJesz6bgv3YdBgayAwLFwsmLNbuOoSDvfp5eS2zxlXj40c0QpaBm/9voyq/H08k+W63KR2xAFJ+LdFvwwbzZSPo9+HYCanPDQuZi/TYnGwqUl0a5KmWVz8sXnrWCCvRmDMOb0BlSQC72vvwsuBdY+Wm1ToikZlpH1/zke5jJpNKt2WWMmYbwq37e/gmyArsPVVbFsxo0x3w+3BiOh3y4vv7FJFIEQt3cs4RqXDX65v3Y09HP+92mUte95Rp9fD7JGza1207F6kNp6WOLaWwl23en7XkaTBoLZLHAki5stmF7KFVu1Q/U8yb9oRFKODj6Qbm3WBC0m5ahchkXG0Zjhlfi6QMPP62+kJsZU6IyNz0AgkUJ2Kmx+GjK1FVEkD3QByvphcmbV5ej8XnTkc44MMbWw7gX+v28Nv3dg4gkZQRCvgyQt/MxAnYS0WelA6Zv67jC+g1mKVhFRaRevJt/UW2mFipeCkLBbBwXiqCdPfr2/jtbPHXRiwA4KKjxiLk92HDni7dHhgHeiNIJFNtAliJ6MiKMCbVl0OW9QWeEQe6WUWIfuqPRVyeXd+qiBCXRPMAEhYqJtVXYN7EEUjKwKOrW9CeriPORVjUlIVw5uGpD9+dr2zJcm81+7iwUN5U0xsrMWlkOaLxpEphFwqenilCxAIArjhxIgDg/jd3qMbb55oKAZTKC9bApjNHkULo89ljmwAA/1jdotqd2+0NM3d8LerKQxhbU4rz07vGYhPw+3BKenHdk/5sZEuFAKlqpO+eMRUAcOsz73PDME+D1JRmpIc+dfQ4VIYD8Pskvmu2AqsmW7Gtnf8dRk8091QIAFxyzDiE/D68vasDbwmzMdyA1TTP5cdPQNAvYdX2dqxr6UA0nuTXFr3oU215iC/o9/53e8bP93UqLbgDQpThjHQk3M51e39PZg8LkdOnNyDk92Hb/l6s2HbQ9L7FgISFhoXphlR/W74DLekP+4gcDWPfOT11Afn3O3vwpsWUSE8kzkPFDcLuTJIknDsrdVH5z7u5D7bJFRaxKEYqBAA+fkQjJtSV4VBfTCXUFPOm/QvkKdNSF96X3t8HWZbzeiwik/NmjUZFOIAdB/uwPN3kCVDGf1td1CpLgnjlB6fihe+dbLiDKwZswWDo7XL1+NpJkzCmugT7uyP4Z3rH/5HQHEtLdVkQT115Ap7+zok8vWGF6Y2VGF1dgv5YAq9pUhZWm20Z0VBVgk8enYqkiPOD3IDRZFMtjdUluGB26jncs2wb31hIknHU8qsnpTY4/3pnD3/NGEYGd5Zif3VTm+V+FqzUVBu9YlSWBHFiOiLFXks3fTZIWGg4d2YjJo4sx6G+GHdi52oYmzm2Gp87tgmyDFz16DrDLngi+9MhsLKQPyNHyITFqx/ux6ECDiXrjyb4h65YoeiA34frz5sBAPjL69t5u/R8IhYnTatHyO/DjoN92Lq/l6dVcnksIpPycAAXzUm1pL/rta38dvbeHWFxIQZSUaRiTjXV47TD1MKCDWDLRijgw1dPmgQA+NNr2xBPJHWNmyKT6yt4NYZVxM3I05rNiBJqz32X++1TpyDgk/D65gN81+wGWArbSmrqayenhMKz6/fi3bTBsqokaNjd9chxNThxykgkkjLuWbZN9TO9FDYAHDthBBoqwzjYG8VT63Zbeg4HetQDyPRg0ROGW4zNAAmLDAJ+H75z+hTVbfnUzt/4iSMwtaEC+7sj+N6j63RLv0SY0a2hMvMNdfjoSswYXYVoPIkn1lp7gzoB+8CUBv1F7alw5uENOHlaPaKJJH729EZVc6J6nfOVjYpwAPPTZZH/eKslZ78GYcw3Tp4Mf3rxYZ0q2/vclxPOheqyIC5Kz/KpLAlgcn15lt9Q+NxxTRhRHsKu9j785729GT0snIKljpZubOWbFkBZuOrz2OU215Xhc8el0l3/+/wm18wOYWWaVhba6Y1VOHlaPZIycMvTGwGoU9B6fPvU1ByXR1a3qDaLbQY+tKDfh6+lheQfXtliKWpxIEsqBADOSpfAMihi4XIumD0G00YpsxpmjLG3UxApDflx58KjURL04fXNB1Q7Nz2Yq1hvDockSfj8vFTp4f1v7jDs4Oc0YpWKnUmITiNJEm78xAwEfBJe+qAND65IGTlry4I5d527/PgJAIAHV+zkuXIybzpH04gybj78xbMfQJZltPfkbop2G7dePAtfO2ki7vz80bY+G2WhAK44YQIA4Pcvb+H9VCaNtC5OrHBUUw1mN9VgIJbEHS+nUhbJpMwNf2Y7Yit85/SpCAd8eGvnoaI28BNhaQSrwvUbJ6cW/R3p9v5sPpER8yfX4aimGkTiSfxJuJ7z5lg66eLPz2vGyIoQdhzsw4Mrd1p+DmavT215iFcfVoQDrmqkR8JCh4Dfh9s/OwelQT8m1ZfbymvqMW1UJX56wUwAwK9e2GRaB82ERb2Bar54zliMrAhjV3sf/vz6dsQTSVtlTLmwzyDEVwwm11dwI+cvnvsAgH5e2iqnHlaPw0dXcSc5QKkQp/nu6VNREvRh+baD+NvynUrEwkYqxK2UhwO4/rwZODnt17HDl46fgMqSADa39WBjWlg43QxNkiR8/+xpAIC/Ld+J37+8Ge1Cj4R8y3dHVZXgsrQ4/98XNmWNyBYCOxELADh+ch1mjlU2jxOyiDtJknD1mSn/3N+W7+TXx1aTaHN5OIBrzjoMAHD7i5t57xMjlDkh5sLvl58+EuccMQoPf+1jRd30aSFhYcCMMVV47Qen4slvn+DINMVL5o7DZ+aOQ1IGrnzobTy/QV9c7OcRC/03VHk4gB9+PPUG/eXzm3DYDc9h9s0v4DN/Wo6tOo1wnGCviRIvBt85fQqfpwAATQZ5aStIkoTrzz1cdVutBXc/YZ3mujL88JzpAICfPr2Rl1m6KSdcDKpKgrju49P592OqS1Tva6c4aWo9rjwtld793xc+xNyfvQggFWbX9kjIhW+eMhkV4QA27OnCM+sLbywXGYgleHrUakRMkiRcedpU/j2LAphxyrR6zB1fi0g8iT+kzeRmEQsA+MzccThsVCU6+2O442XzSsEDPGJh/hwm1VfgT1+c67ruvCQsTGioKnFs9ypJEn5+8SxceNQYxJMyrnzobbyo0+yqrTv15jTzDFxyzDh89cSJkCTwnceq7e04/3dv4H+f3+S4wHBTxAJIOaJ/d+lRCKUvihem89y5cuLUkfh4uk/I5+c1u0r5e4UvnzABn5wzFomkzN+zhZyS61YWzmvGjxZMx+xx1fj1Z48atPfetWdPw22fnKUyhJ+QbrKULyPKQ/hKOop4/ZPrsXGP/YFbTsFM3RXhgK125eccMQo3X3AE/ufTR+LsGaOy3l+SJFyTjgQ9vKoFuw72YUd6oOFEg4hHyoCe2sT8bfkObGnTv06LzdLGDILQLAQkLApIwO/Dry6ZjU/MHoNYQsa3H3obqzU14PtNPBYMSZLw/86fgbU3nIUVi8/A6z88DSdOGYn+WAK/f2ULzvjVa/jWA2u4gtaSSMq2QpZ6nUCLzTHjR+Af35yP2z97FG8elg+/vfQo/GHh0bjunOnZ70zYRpIkLPnULD5jo7IkwOdZDGckScI3T5mMf115Ij42qW5Q/87njmvG8987GeccMQrj68q4v8gJvnXqZBzVVIPO/hguvPMNXP/ke9h1sPDtvllPjdlN1bZEmiRJuOz4CfjM3CbLv3f85JGYP6kO0UQSn717OWIJGeUhv2nU6eRp9ThjegNiCRmLn3gXMZ3p161d6WZpfl9e5tpi4h63xzAh4PfhN5+Zjf5oAi++vw9fvf8t/PNb8zElPTGQucOtLOJiOdXfrjgOT7+3F0+t3Y1XNrXh2fWteGPzAVx5+hSEAj6891Endrb3YW9HP/Z1R1AW8uPCo8bgqjOmZa2o2JMeuuOWiAXjqKYaPpMlX8IBPy/NIwaHcMCPB786D/cs246ZY6scCcMT9hhbU4o/fXGu449bEvTjr5cfix8+/g5efL8ND67chYdX7cI5RzTihCkjcfLUejQPcoQqlkjyLpofmzh4Ik3kxgtm4OI73+Tp4sNHV2UVJjdfeASWbzuI1TsO4dp/vIP/+fSRqrb9u9kaUFOSdZaOW5HkAtcIdXV1obq6Gp2dnaiqyr3aYqjTH03g839egbW7OjCmugS/+PSROGZ8LY648XnIMrD6+jNzKqEEgA9au3DdP9+zNKq3Ipxyp0+qr8C0UZU4fHSl6oORTMo44sbn0R9L4MVrTsGUhgqTRyMIYjgjyzJWbm/HH17dimWaplwnTR2JhfPG48zDG1SdKZ3iP+/uxaKH3kZdeQiv/fC0nCa35sLSjftw9SNr0RdL4C+XzcXp07OnUl7cuA/feGANEkkZ0xsr8b+XzObDFh9ZtQs/euI9nDhlJB746rzBPnxbWF2/cxIWd955J375y1+itbUVs2fPxh133IHjjjvO0QMbDrT3RvHpu97EtnRekDGyIoS3/t9ZeT12Iinjb8t34Nn3WlFdFsQRY6owbVSqE9+oqhJsP9CLXzz3Ad7V9LyfUFeGTx8zDh+fORojykP4cF83Pnf3CoQDPmy4+ZxBuSAQBOE91u/uxNKN+7Bi20Gs2tEOttJUlwYxc2wVZo6pxglTRuK4iSMcGbT3mT8ux6od7fju6VNwzdmH5f14duiJxNHRFzVscKbH65v343uPrsOBnij8PgmfOnosPj9vPB5euQuPvtWCb5wyCYsXHJ79gQrIoAmLRx99FF/60pfwxz/+EfPmzcPtt9+Oxx57DJs2bUJDQ0PW3ydhoaazL4ZfL92Ef769m7ei/eLHxuOWi2YO+t9OJmU8mU6dtHVH8N5HneiP6ffGmDdxBB79xvxBPyaCILxHS3sfHlq1C/9Y3cJ7aDBKgj58bFIdTp5aj1MOq8ekkeW2Tawb9nTivN+9gYBPwn9/dLrr0rZG7O+O4Kb/26A7puGuhUdjgcvSs4MmLObNm4djjz0Wv//97wEAyWQSTU1N+M53voMf/ehHjh3YcGMglsArH7RhZ3sfLps/AaVFGIHbG4nj2fWt+Oeaj/D2rkOIpDvE1ZYFce+Xj3PMz0AQxPAkGk9iU2s3Nu7txJqdh/Dah/uxr0s96mBcbSmOn1yHSfUVqCwJoCTgR2nIj9KgH+GgD6XB1PdBvw9Mftz27Ad4YeM+fGL2GNxx6ZzCP7E8WbOzHX/97w4s+3A/ugfiOHx0FZ789vGORHKcZFCERTQaRVlZGR5//HFcdNFF/PbLLrsMHR0d+Ne//uXYgRHFRZZlJGU40sODIAhCD1mWsWlfN5Z9uB/LPjyAVdvbEdWplLDKk98+HnOah261UTIpY/vBXjRWlbhuNg5gff22deQHDhxAIpHAqFFqc8qoUaPwwQcf6P5OJBJBJKIo0q6u4tU4E9aRJAl+0hQEQQwikiRhemMVpjdW4esnT0ZfNI7lWw/inY860dLeh95IHAPxJAaiCfTHUl8D6S8WUYWcGuz27dOmDGlRAQA+n4TJ9UPfID/okmjJkiW4+eabB/vPEARBEEOcslAAZxw+Cmccnr2ygnAvtiz+I0eOhN/vx7596o6R+/btQ2OjfpOixYsXo7Ozk3+1tLTkfrQEQRAEQbgaW8IiFArhmGOOwUsvvcRvSyaTeOmllzB/vn7FQDgcRlVVleqLIAiCIAhvYjsVcs011+Cyyy7D3Llzcdxxx+H2229Hb28vvvzlLw/G8REEQRAEMYSwLSw++9nPYv/+/fjJT36C1tZWHHXUUXjuuecyDJ0EQRAEQQw/qKU3QRAEQRBZsbp+U39mgiAIgiAcg4QFQRAEQRCOQcKCIAiCIAjHIGFBEARBEIRjkLAgCIIgCMIxSFgQBEEQBOEYJCwIgiAIgnAMEhYEQRAEQTgGCQuCIAiCIBxj0Mema2GNPru6ugr9pwmCIAiCyBG2bmdr2F1wYdHd3Q0AaGpqKvSfJgiCIAgiT7q7u1FdXW3484LPCkkmk9izZw8qKyshSZJjj9vV1YWmpia0tLTQDJJBhM5z4aBzXRjoPBcGOs+FY7DOtSzL6O7uxpgxY+DzGTspCh6x8Pl8GDdu3KA9flVVFb1pCwCd58JB57ow0HkuDHSeC8dgnGuzSAWDzJsEQRAEQTgGCQuCIAiCIBzDM8IiHA7jxhtvRDgcLvaheBo6z4WDznVhoPNcGOg8F45in+uCmzcJgiAIgvAunolYEARBEARRfEhYEARBEAThGCQsCIIgCIJwDBIWBEEQBEE4hmeExZ133okJEyagpKQE8+bNw6pVq4p9SEOGJUuW4Nhjj0VlZSUaGhpw0UUXYdOmTar7DAwMYNGiRairq0NFRQU+9alPYd++far77Nq1C+eddx7KysrQ0NCAH/zgB4jH44V8KkOK2267DZIk4eqrr+a30Xl2jt27d+MLX/gC6urqUFpailmzZuGtt97iP5dlGT/5yU8wevRolJaW4swzz8TmzZtVj9He3o6FCxeiqqoKNTU1+MpXvoKenp5CPxXXkkgkcMMNN2DixIkoLS3F5MmTccstt6hmSdB5zo1ly5bhE5/4BMaMGQNJkvDUU0+pfu7UeX333Xdx0kknoaSkBE1NTfif//mf/A9e9gCPPPKIHAqF5L/+9a/yhg0b5K997WtyTU2NvG/fvmIf2pDgnHPOke+99155/fr18rp16+Rzzz1Xbm5ulnt6evh9vvnNb8pNTU3ySy+9JL/11lvyxz72Mfn444/nP4/H4/LMmTPlM888U167dq38zDPPyCNHjpQXL15cjKfkelatWiVPmDBBPvLII+WrrrqK307n2Rna29vl8ePHy5dffrm8cuVKedu2bfLzzz8vb9myhd/ntttuk6urq+WnnnpKfuedd+QLLrhAnjhxotzf38/v8/GPf1yePXu2vGLFCvn111+Xp0yZIl966aXFeEqu5NZbb5Xr6urkp59+Wt6+fbv82GOPyRUVFfJvf/tbfh86z7nxzDPPyNdff738xBNPyADkJ598UvVzJ85rZ2enPGrUKHnhwoXy+vXr5YcfflguLS2V//SnP+V17J4QFscdd5y8aNEi/n0ikZDHjBkjL1mypIhHNXRpa2uTAcivvfaaLMuy3NHRIQeDQfmxxx7j93n//fdlAPLy5ctlWU59CHw+n9za2srvc9ddd8lVVVVyJBIp7BNwOd3d3fLUqVPlpUuXyqeccgoXFnSeneO6666TTzzxRMOfJ5NJubGxUf7lL3/Jb+vo6JDD4bD88MMPy7Isyxs3bpQByKtXr+b3efbZZ2VJkuTdu3cP3sEPIc477zz5iiuuUN32yU9+Ul64cKEsy3SenUIrLJw6r3/4wx/k2tpa1bXjuuuukw877LC8jnfIp0Ki0SjWrFmDM888k9/m8/lw5plnYvny5UU8sqFLZ2cnAGDEiBEAgDVr1iAWi6nO8fTp09Hc3MzP8fLlyzFr1iyMGjWK3+ecc85BV1cXNmzYUMCjdz+LFi3CeeedpzqfAJ1nJ/n3v/+NuXPn4pJLLkFDQwPmzJmDe+65h/98+/btaG1tVZ3r6upqzJs3T3Wua2pqMHfuXH6fM888Ez6fDytXrizck3Exxx9/PF566SV8+OGHAIB33nkHb7zxBhYsWACAzvNg4dR5Xb58OU4++WSEQiF+n3POOQebNm3CoUOHcj6+gg8hc5oDBw4gkUioLrQAMGrUKHzwwQdFOqqhSzKZxNVXX40TTjgBM2fOBAC0trYiFAqhpqZGdd9Ro0ahtbWV30fvNWA/I1I88sgjePvtt7F69eqMn9F5do5t27bhrrvuwjXXXIMf//jHWL16Nb773e8iFArhsssu4+dK71yK57qhoUH180AggBEjRtC5TvOjH/0IXV1dmD59Ovx+PxKJBG699VYsXLgQAOg8DxJOndfW1lZMnDgx4zHYz2pra3M6viEvLAhnWbRoEdavX4833nij2IfiOVpaWnDVVVdh6dKlKCkpKfbheJpkMom5c+fi5z//OQBgzpw5WL9+Pf74xz/isssuK/LReYd//OMfePDBB/HQQw/hiCOOwLp163D11VdjzJgxdJ6HMUM+FTJy5Ej4/f4M5/y+ffvQ2NhYpKMamlx55ZV4+umn8corr6hG2zc2NiIajaKjo0N1f/EcNzY26r4G7GdEKtXR1taGo48+GoFAAIFAAK+99hp+97vfIRAIYNSoUXSeHWL06NGYMWOG6rbDDz8cu3btAqCcK7PrRmNjI9ra2lQ/j8fjaG9vp3Od5gc/+AF+9KMf4XOf+xxmzZqFL37xi/je976HJUuWAKDzPFg4dV4H63oy5IVFKBTCMcccg5deeonflkwm8dJLL2H+/PlFPLKhgyzLuPLKK/Hkk0/i5ZdfzgiNHXPMMQgGg6pzvGnTJuzatYuf4/nz5+O9995TvZGXLl2KqqqqjAv8cOWMM87Ae++9h3Xr1vGvuXPnYuHChfz/dJ6d4YQTTsgomf7www8xfvx4AMDEiRPR2NioOtddXV1YuXKl6lx3dHRgzZo1/D4vv/wykskk5s2bV4Bn4X76+vrg86mXEb/fj2QyCYDO82Dh1HmdP38+li1bhlgsxu+zdOlSHHbYYTmnQQB4p9w0HA7L9913n7xx40b561//ulxTU6NyzhPGfOtb35Krq6vlV199Vd67dy//6uvr4/f55je/KTc3N8svv/yy/NZbb8nz58+X58+fz3/OyiDPPvtsed26dfJzzz0n19fXUxlkFsSqEFmm8+wUq1atkgOBgHzrrbfKmzdvlh988EG5rKxMfuCBB/h9brvtNrmmpkb+17/+Jb/77rvyhRdeqFuuN2fOHHnlypXyG2+8IU+dOnXYl0GKXHbZZfLYsWN5uekTTzwhjxw5Uv7hD3/I70PnOTe6u7vltWvXymvXrpUByL/+9a/ltWvXyjt37pRl2Znz2tHRIY8aNUr+4he/KK9fv15+5JFH5LKyMio3Zdxxxx1yc3OzHAqF5OOOO05esWJFsQ9pyABA9+vee+/l9+nv75e//e1vy7W1tXJZWZl88cUXy3v37lU9zo4dO+QFCxbIpaWl8siRI+Vrr71WjsViBX42QwutsKDz7Bz/93//J8+cOVMOh8Py9OnT5bvvvlv182QyKd9www3yqFGj5HA4LJ9xxhnypk2bVPc5ePCgfOmll8oVFRVyVVWV/OUvf1nu7u4u5NNwNV1dXfJVV10lNzc3yyUlJfKkSZPk66+/XlW+SOc5N1555RXd6/Jll10my7Jz5/Wdd96RTzzxRDkcDstjx46Vb7vttryPncamEwRBEAThGEPeY0EQBEEQhHsgYUEQBEEQhGOQsCAIgiAIwjFIWBAEQRAE4RgkLAiCIAiCcAwSFgRBEARBOAYJC4IgCIIgHIOEBUEQBEEQjkHCgiAIRzj11FNx9dVXF/swCIIoMiQsCIIgCIJwDGrpTRBE3lx++eW4//77Vbdt374dEyZMKM4BEQRRNEhYEASRN52dnViwYAFmzpyJn/70pwCA+vp6+P3+Ih8ZQRCFJlDsAyAIYuhTXV2NUCiEsrIyNDY2FvtwCIIoIuSxIAiCIAjCMUhYEARBEAThGCQsCIJwhFAohEQiUezDIAiiyJCwIAjCESZMmICVK1dix44dOHDgAJLJZLEPiSCIIkDCgiAIR/j+978Pv9+PGTNmoL6+Hrt27Sr2IREEUQSo3JQgCIIgCMegiAVBEARBEI5BwoIgCIIgCMcgYUEQBEEQhGOQsCAIgiAIwjFIWBAEQRAE4RgkLAiCIAiCcAwSFgRBEARBOAYJC4IgCIIgHIOEBUEQBEEQjkHCgiAIgiAIxyBhQRAEQRCEY5CwIAiCIAjCMf4/lxa1njQyCfMAAAAASUVORK5CYII=", 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", 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" ] @@ -232,23 +232,23 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 30, "id": "1e7fab6a-0ca1-41ad-83f2-17c6eeee69bd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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CIIioQjEfBEEQBEFEFbJ8EARBEAQRVUh8EARBEAQRVeKuyJjb7UZ1dTVycnKiWmKYIAiCIIjQEUURjY2N6NGjByyWwLaNuBMf1dXVKC0tjXUzCIIgCIIIgZ07d6JXr14B94k78cEWfNq5cydyc3Nj3BqCIAiCIPTQ0NCA0tJS2cKNWsSd+GCultzcXBIfBEEQBJFg6AmZoIBTgiAIgiCiCokPgiAIgiCiCokPgiAIgiCiStzFfBAEQRDJi8vlQmdnZ6ybQYSIw+EImkarBxIfBEEQRMQRRRE1NTWoq6uLdVOIMLBYLCgrK4PD4QjrOCQ+CIIgiIjDhEdRUREyMzOpiGQCwoqA7tmzB7179w7rHpL4IAiCICKKy+WShEfXrl1j3RwiDAoLC1FdXQ2n0wm73R7ycSjglCAIgogoLMYjMzMzxi0hwoW5W1wuV1jHIfFBEARBRAVytSQ+Zt1DEh8EQRAEQUQVEh8EQRAEEQdMmjQJF1xwQaybERVIfBAEQRCEBmPHjsWUKVMi/p5Ug8QHQRApQVunC6IoxroZBEGAxAdBECnA3oY2DH74S0yatSLWTSESiEmTJmHJkiV4/vnnIQgCBEHA9u3bsWTJEowcORJpaWno3r07HnjgATidzoDvcblcuP7661FWVoaMjAwMGjQIzz//fMhtGzt2LG6//XbcfvvtyMvLQ7du3fDwww/LBPahQ4dw7bXXokuXLsjMzMSECROwefNm6fXZs2cjPz8f8+fPx8CBA5Geno7x48dj586doV80nZD4IAgi6fl49W4AwJJN+2LcEoIhiiJaOpxR/zFi/Xr++edRXl6OG2+8EXv27MGePXtgt9tx1lln4bjjjsPatWvxyiuv4I033sBf/vIXzfeUlpbC7XajV69emDdvHjZs2IBHHnkEDz74ID744IOQr+Gbb74Jm82G5cuX4/nnn8ezzz6Lf/3rX9LrkyZNwsqVK/Hpp5+ioqICoijirLPOkpW3b2lpwZNPPom33noLP/74I+rq6nDFFVeE3Ca9UJExgiCSHguleMYdrZ0uDH1kQdQ/d8OfxyPToW/oy8vLg8PhQGZmJkpKSgAADz30EEpLS/HSSy9BEAQMHjwY1dXVuP/++/HII4+ovgcArFYrHn/8cen/srIyVFRU4IMPPsBll10W0rmUlpZixowZEAQBgwYNwrp16zBjxgzceOON2Lx5Mz799FP8+OOPOP744wEA7777LkpLSzF//nxceumlADw1WF566SWMGjUKgEfQDBkyBMuXL8fIkSNDapceyPJBEETSQ9qDMIvffvsN5eXlsnoXY8aMQVNTE3bt2hXwvTNnzsTw4cNRWFiI7OxsvPbaa6iqqgq5LaNHj5a1o7y8HJs3b4bL5cJvv/0Gm80miQoA6Nq1KwYNGoTffvtN2maz2XDcccdJ/w8ePBj5+fmyfSIBWT4Igkh6qLhV/JFht2LDn8fH5HNjwdy5c3HPPffgmWeeQXl5OXJycvD3v/8dy5Yti0l7Yg2JD4Igkh4LaY+4QxAE3e6PWOJwOGSlxIcMGYL//Oc/EEVRErU//vgjcnJy0KtXL9X3sH2OP/543HbbbdK2rVu3htU2pXBZunQpBg4cCKvViiFDhsDpdGLZsmWS2+XAgQOorKzE0KFDpfc4nU6sXLlScrFUVlairq4OQ4YMCattwTDkdunbt68Uvcv/TJ48GQDQ1taGyZMno2vXrsjOzsbFF1+M2traiDScIAhCLxTzQYRK3759sWzZMmzfvh379+/Hbbfdhp07d+KOO+7Axo0b8cknn+DRRx/F1KlTYbFYVN/jdrsxcOBArFy5EgsWLMCmTZvw8MMPY8WK8LKvqqqqMHXqVFRWVuK9997Diy++iDvvvBMAMHDgQJx//vm48cYb8cMPP2Dt2rW45ppr0LNnT5x//vnSMex2O+644w4sW7YMq1atwqRJkzB69OiIxnsABsXHihUrpOjdPXv2YOHChQAgBa7cdddd+OyzzzBv3jwsWbIE1dXVuOiii8xvNUEQhAFIexChcs8998BqtWLo0KEoLCxEZ2cnvvjiCyxfvhxHHXUUbrnlFlx//fX405/+pPmeqqoq3Hzzzbjoootw+eWXY9SoUThw4IDMChIK1157LVpbWzFy5EhMnjwZd955J2666Sbp9VmzZmH48OE455xzUF5eDlEU8cUXX8hWo83MzMT999+Pq666CmPGjEF2djbef//9sNqlB0EMo+rOlClT8Pnnn2Pz5s1oaGhAYWEh5syZg0suuQQAsHHjRgwZMgQVFRUYPXq0rmM2NDQgLy8P9fX1yM3NDbVpBEEQEm9XbMfDn/wKANj+9Nkxbk3q0dbWhm3btqGsrAzp6emxbk5SMHbsWBx99NF47rnnQj7G7NmzMWXKFNTV1el+T6B7aWT8DjnbpaOjA++88w7+8Ic/QBAErFq1Cp2dnRg3bpy0z+DBg9G7d29UVFRoHqe9vR0NDQ2yH4IgCDOhgFOCiC9CFh/z589HXV0dJk2aBACoqamBw+FAfn6+bL/i4mLU1NRoHmf69OnIy8uTfkpLS0NtEkEQhCqkPYhEoqqqCtnZ2Zo/4aTnxgshhxq/8cYbmDBhAnr06BFWA6ZNm4apU6dK/zc0NJAAIQjCVCjglEgkevTogTVr1gR8ffHixWF/zqRJkyQDQrQJSXzs2LEDX3/9NT766CNpW0lJCTo6OlBXVyezftTW1sqqvClJS0tDWlpaKM0gCILQBaXaEomEzWbDgAEDYt2MiBKS22XWrFkoKirC2Wf7AreGDx8Ou92ORYsWSdsqKytRVVWF8vLy8FtKEAQRIgJIfRBEPGHY8uF2uzFr1ixMnDgRNpvv7Xl5ebj++usxdepUFBQUIDc3F3fccQfKy8t1Z7oQBEFEBNIecYHb7Y51E4gwCSNBVoZh8fH111+jqqoKf/jDH/xemzFjBiwWCy6++GK0t7dj/PjxePnll01pKEEQRKjwMR9utwgL+WGiisPhgMViQXV1NQoLC+FwOCgDKQERRRH79u2DIAiyWiGhYFh8nHHGGZrKJz09HTNnzsTMmTPDahRBEISZ8MOcWxRhIVNIVLFYLCgrK8OePXtQXV0d6+YQYSAIAnr16gWrNbw1cuK/sD5BEESYWLjoNpcoUscXAxwOB3r37g2n0+m37gmRONjt9rCFB0DigyCIFEDudolhQ1IcZq4P12RPJD4hFxkjCIJIRNwmBcwRBBE6JD4Igkh6eMuHi8QHQcQcEh8EQSQ9fGKF203igyBiDYkPgiCSHr7IGGkPgog9JD4IgkgpXKQ+CCLmkPggCCLpEeETHBRwShCxh8QHQRBJD683SHwQROwh8UEQRNLDyw1yuxBE7CHxQRBE0sMvCUFFxggi9pD4IAgipSC3C0HEHhIfBEEkPbzgoCJjBBF7SHwQBJH0yAJOKeaDIGIOiQ+CIJIeebZL7NpBEIQHEh8EQSQ9lO1CEPEFiQ+CIJIeWbYLxXwQRMwh8UEQRNLDyw0SHwQRe0h8EASR/HB6g9wuBBF7SHwQBJH0uMntQhBxBYkPgiCSHrnbJWbNIAjCC4kPgiCSHpHcLgQRV5D4IAgi6RHBr+1C4oMgYg2JD4Igkh4qMkYQ8QWJD4Igkh5ZkTEKOCWImEPigyCI5EcktwtBxBMkPgiCSHrcFHBKEHEFiQ+CIJIeKq9OEPEFiQ+CIJIeKq9OEPEFiQ+CIJIeeZ2P2LWDIAgPJD4Igkh6yPJBEPEFiQ+CIJIeivkgiPiCxAdBECkFZbsQROwh8UEQRNIjX9U2hg0hCAIAiQ+CIFIAWXl1Uh8EEXNIfBAEkfRQeXWCiC8Mi4/du3fjmmuuQdeuXZGRkYEjjjgCK1eulF4XRRGPPPIIunfvjoyMDIwbNw6bN282tdEEQRBGkC8sR+KDIGKNIfFx6NAhjBkzBna7Hf/73/+wYcMGPPPMM+jSpYu0z9/+9je88MILePXVV7Fs2TJkZWVh/PjxaGtrM73xBEEQehBBa7sQRDxhM7LzX//6V5SWlmLWrFnStrKyMulvURTx3HPP4U9/+hPOP/98AMBbb72F4uJizJ8/H1dccYVJzSYIgtCPSGu7EERcYcjy8emnn2LEiBG49NJLUVRUhGOOOQavv/669Pq2bdtQU1ODcePGSdvy8vIwatQoVFRUqB6zvb0dDQ0Nsh+CIIhIQdqDIGKPIfHx+++/45VXXsHAgQOxYMEC3HrrrfjjH/+IN998EwBQU1MDACguLpa9r7i4WHpNyfTp05GXlyf9lJaWhnIeBEEQmvCuFor5IIjYY0h8uN1uHHvssXjqqadwzDHH4KabbsKNN96IV199NeQGTJs2DfX19dLPzp07Qz4WQRCEGrJsFzJ9EETMMSQ+unfvjqFDh8q2DRkyBFVVVQCAkpISAEBtba1sn9raWuk1JWlpacjNzZX9EARBmIk82yV27SAIwoMh8TFmzBhUVlbKtm3atAl9+vQB4Ak+LSkpwaJFi6TXGxoasGzZMpSXl5vQXIIgCOPIsl3I7UIQMcdQtstdd92F448/Hk899RQuu+wyLF++HK+99hpee+01AIAgCJgyZQr+8pe/YODAgSgrK8PDDz+MHj164IILLohE+wmCIIJC2S4EEV8YEh/HHXccPv74Y0ybNg1//vOfUVZWhueeew5XX321tM99992H5uZm3HTTTairq8MJJ5yAL7/8Eunp6aY3niAIQg+83CDLB0HEHkEU4+ub2NDQgLy8PNTX11P8B0EQpvDsV5V44ZstAIA/njoAU88YFOMWEUTyYWT8prVdCIJIenhPC63tQhCxh8QHQRBJjzzgNIYNIQgCAIkPgiBSAFmqLakPgog5JD4Igkh6qMgYQcQXJD4Igkh6qMgYQcQXJD4Igkh6qMgYQcQXJD4Igkh+qMgYQcQVJD4Igkh6qMgYQcQXJD4Igkh6+AwXEh8EEXtIfBBEktPudGFDdQPirJhxVKFsF4KIL0h8EESSc8ObK3HWC99j7oqdsW5KzKBsF4KIL0h8EESS8/3m/QCA2T9uj21DYogs24XUB0HEHBIfBJEipPKaJiKt7UIQcQWJD4JIEWjG74EuA0HEHhIfBJEipHKWBx9sSyKMIGIPiQ+CSBFS2d3gpiJjBBFXkPggiBTB7Y51C2IHlVcniPiCxAdBpAipPOOXp9qm7nUgiHiBxAdBpAip7HahImMEEV+Q+CCIFCGlK5xSkTGCiCtIfBBEipDaM36K+SCIeILEB0GkCKksPkTKdiGIuILEB0GkCKk85vLWDrJ8EETsIfFBEClCKg+6spiPFE45Joh4gcQHQaQIqexukGW7pLAII4h4gcQHQaQIqTzm8ufuTGERRhDxAokPgkgRUnnGL6twSuKDIGIOiQ+CSBFS2e0CynYhiLiCxAdBEEkPVTgliPiCxAdBEEkPn+mTyu4ngogXSHwQBJH0yFNtSXwQRKwh8UEQRNLDyw3KdiGI2EPigyCIpIdfVI9iPggi9pD4IAgi6eHlRipXeiWIeIHEB0EQyQ+l2hJEXGFIfDz22GMQBEH2M3jwYOn1trY2TJ48GV27dkV2djYuvvhi1NbWmt5ogiAII/BFxkh8EETsMWz5OPzww7Fnzx7p54cffpBeu+uuu/DZZ59h3rx5WLJkCaqrq3HRRReZ2mCCIAij8IvJUaotQcQem+E32GwoKSnx215fX4833ngDc+bMwamnngoAmDVrFoYMGYKlS5di9OjR4beWIAgiBMjyQRDxhWHLx+bNm9GjRw/069cPV199NaqqqgAAq1atQmdnJ8aNGyftO3jwYPTu3RsVFRXmtZggCMIgIsV8EERcYcjyMWrUKMyePRuDBg3Cnj178Pjjj+PEE0/E+vXrUVNTA4fDgfz8fNl7iouLUVNTo3nM9vZ2tLe3S/83NDQYOwOCIAgDkPggiNhjSHxMmDBB+vvII4/EqFGj0KdPH3zwwQfIyMgIqQHTp0/H448/HtJ7CYIg9ECptgQRX4SVapufn4/DDjsMW7ZsQUlJCTo6OlBXVyfbp7a2VjVGhDFt2jTU19dLPzt37gynSQRBEAGhCqcEEXvCEh9NTU3YunUrunfvjuHDh8Nut2PRokXS65WVlaiqqkJ5ebnmMdLS0pCbmyv7IQiCMBPe2CGK8oqnBEFEH0Nul3vuuQfnnnsu+vTpg+rqajz66KOwWq248sorkZeXh+uvvx5Tp05FQUEBcnNzcccdd6C8vJwyXQiCiCtcbhE2qxDrZhBEymJIfOzatQtXXnklDhw4gMLCQpxwwglYunQpCgsLAQAzZsyAxWLBxRdfjPb2dowfPx4vv/xyRBpOEAShH7mlw+kWYbPGqCkEQRgTH3Pnzg34enp6OmbOnImZM2eG1SiCIMzDIgAU5iCHgk4JIrbQ2i4EkeRYLeReUGoNSrcliNhC4oMgkhyLQOJDKTVIfBBEbCHxQRBJDokPf0h8EERsIfFBEEmOjdwufqm1tLgcQcQWEh8EkeRYSHz4QZYPgogtJD4IIsnRqz3qWztx+T8r8N7yqsg2KAZQzAdBxBckPggiydGb7fLqkq1Ytu0gpn20LsItij1ud6xbQBCpDYkPgkhyBC7gNFBZ8ZZ2ZzSaExOUp+0k9UEQMYXEB0EkOVZOfATyNggplBVDRcYIIraQ+CCIJId3uwSKdUjmYmT+MR8xaQZBEF5IfBBEkmPhvuWBxEcqpeSS24UgYouhtV0Igkg8+CJjavUttu1vxmvfbUVDWzLHfMjPm7QHQcQWEh8EkeTwMR8ul7/4uOr1pdhT3xbNJsUcsnwQRGwhtwtBJDl8kTE1y0eqCQ+A6nwQRKwh8UEQSQ4fyUEzfg9OEh8EEVNIfBBEksMPs6mqPfzqfKi4nwiCiB4kPggiyeGDLcny4aGTrgNBxBQSHwSRQqTqmCsqKn2oBd4SBBE9SHwQRJLDD7Opavmg8uoEEV+Q+CCIZIcbePWWFXcneUAmBZwSRGwh8UEQSY7c8qFv0E22wZkCTgkiviDxQRBJDh9wqlbfQq2serLXweikxV0IIqaQ+CCIFEJNVFhUxEeyxUT4BZwmubgiiHiHxAdBJDn8MEuWDw+dSX5+BBHvkPggiCSHj3dQExVWVctHcg3OypgPF7ldCCKmkPggiCSHdzmoiQpV8ZGkAZnMypNs4oogEg0SHwSR5PCzfrUUWjW3S/LFfHiwWz1dXmeSiiuCSBRIfBBECqE247cIqRPzYbN6ztWVZOKKIBINEh8EkeTIYj5UioylQswHM32Q5YMg4gMSHwSRQqitaaImPpLW8mFhlo/kPD+CSBRIfBBEkiNf1TY1A05Z0K1k+SC3C0HEFBIfBJHkBKvzoe52Sc7B2e6N+Ug2cUUQiQaJD4JIIdREhXq2S3INzsz4Y/NaPsjtQhCxhcQHQSQ5fIyp2ow/FbJd2NkwoUVruxBEbCHxQRBJjrzImIrlw5r8MR8MO1k+CCIuIPFBEEmOzPKhFvORCpYP70VgQotSbQkitoQlPp5++mkIgoApU6ZI29ra2jB58mR07doV2dnZuPjii1FbWxtuOwmCMAFVt4tKzEeyZoPYLZ4uL1kDagkiUQhZfKxYsQL//Oc/ceSRR8q233XXXfjss88wb948LFmyBNXV1bjooovCbihBEKHByw01y4fqqrZJZhmQYj6stLYLQcQDIYmPpqYmXH311Xj99dfRpUsXaXt9fT3eeOMNPPvsszj11FMxfPhwzJo1Cz/99BOWLl1qWqMJgtCPPODUf8afEhVOvbBsF7XrQBBE9AhJfEyePBlnn302xo0bJ9u+atUqdHZ2yrYPHjwYvXv3RkVFheqx2tvb0dDQIPshCMJMAhcZs1n8u4Hki/nw/HZYqcIpQcQDNqNvmDt3Ln7++WesWLHC77Wamho4HA7k5+fLthcXF6Ompkb1eNOnT8fjjz9utBkEQegkaKptChUZY0KLAk4JIrYYsnzs3LkTd955J959912kp6eb0oBp06ahvr5e+tm5c6cpxyUIwh81UaGSaZt0qbb+MR/JKa4IIlEwJD5WrVqFvXv34thjj4XNZoPNZsOSJUvwwgsvwGazobi4GB0dHairq5O9r7a2FiUlJarHTEtLQ25uruyHIAjzCBZwak0BtwvDLsV8JOf5EUSiYEh8nHbaaVi3bh3WrFkj/YwYMQJXX3219LfdbseiRYuk91RWVqKqqgrl5eWmN54giODIFpZTDTj1f0+wgNOWDifeX1GFfY3tYbcvKrA6HxbKdiGIeMBQzEdOTg6GDRsm25aVlYWuXbtK26+//npMnToVBQUFyM3NxR133IHy8nKMHj3avFYTBKGb4JYPtSJjgd0ST3z+G95bXoUBRdvw9dSTw21i1LDbWJ0PEh8EEUsMB5wGY8aMGbBYLLj44ovR3t6O8ePH4+WXXzb7YwiC0EmwgFM1t0uwwfmrXz0B5Fv2NoXXuCjBzsbOLB+UaksQMSVs8bF48WLZ/+np6Zg5cyZmzpwZ7qEJgjAZvQGnwWI+1DJkEgEbxXwQRFxAa7sQhEGcLjea252xboZu5DEf/oOuoLK2S7BUVLWqqPEMuwSU7UIQ8QGJD4IwyLkv/YjDH12Ag80dsW6KLoLFfPDihBEs5kMtTiQR8K3tQpYPgoglJD4IwiC/7fFU4V2yaW+MW6KTIKvaqg3DwQbnhLN8QL6qLbldCCK2kPggiBBJlAFMZvnQGWgZLOYj0SwfzLgj1fkgtwtBxBQSHwQRIolYiEstlkPF6xLU8pFo4oPBLDaJeO8IIpkg8UEQIZIocQN8TEewWA5GMAuJWnpuPOMLOKW1XQgiHkisHoQg4ohEmT0HDThVeU+yxXww7Faq80EQ8QCJD4IIkcSxfPj+VotTUc92SS63i1RkzErZLgQRD5D4IIgQ0evCiCf0Blome8wHiQ+CiC0kPggiRBJlABM5x4pqwKnKe1xBYiKsKoXJ4hlm3WGWD5dbVLX4EAQRHUh8EESIBBug4wV+jNUbp5K0lg+ulnyiiEeCSEZIfBBEiHQmyODFt7JTLdBSNdU2sHvGprYgTAJg47J0EqVOSzywfnd9wlT0JRIDEh8EESIJE/MRxPIhqqiPYFYBS4K5XRgOG2/5SJD7F2PW7qzDOS/+gFFPfR3rphBJBIkPggiRRDTb621zMJdSoqXaSnU+yPJhmB+37gdAtVEIcyHxQRAhkjAxH5xlQ222r17hNDkXluPbnYjiMRYkmtAkEgMSHwQRIokyeAWv8+H/nmCz3ESL+WACTABXaIzcLrpItGq2RGJATxVBhEgiVjjVazoPbvlI3K6DuV7I7aIPe4IJTSIxSNwehCBiTOJYPgKv7aIWcNrpDFbnQ/348YrURIEKjRklUV1sRHxD4oMgQiRhsl049M72O4Ocm4UbkBIhEJFvoY3WdzEExXwQkYDEB0GESKKY7YMuLKcWcGog2yVR3E8AIECQXEZk+dBHIrvYiPiFniqCCJFEGbxkAaeqbhd/VIuRcfADUjArSTzAu4Z8K9smxv2LNYkqNIn4hsQHQYRIInbEnS59a5oEFx++vxNpEBcEn9slEURTPGCVudjomhHmQOKDIEIkUVM1lZpJvc6HfkGRCLETspgPi29xOSI4fLYLiQ/CLEh8EESIJMLgpWbl0DOAdDoD78MfNlHWuAE8dT6YG4EGUn3wpfQTycpFxDckPggiRBIh5kPNquEvmlQESpBzkwWxJsIg7m2wIAiSGyERxGM8IAhk+SDMh8QHQYRIIgxeai1Uzl7Vs10MWD4SbDZst1KRMSPw1rMOEh+ESZD4IIgQSYTBS83toidWJZig4I+bCLEvUo0xPuCUBlJdyK1c8f/ME4kBiQ+CCJFEGHTVULqLQkm1DbZeTDxjI7eLIXihSYKNMAsSHwQRIgkR86GyTTmAhBKUKl8pNwGug+hbWI5luyRSoGwsSWQXGxG/kPggCAPI10mJ/45YX8CpP24RcAfYT275SKzZMHO7JGJ5/FggX5iQrhlhDiQ+CMIAieZu4C0UrFaUcvaqdRaBinCFslJuLJHFfEiptvHf7nggWIVcgggFEh8EYQB+uHIn0mquAGxWY8W1Ag3O7gQLOOWxUbaLIfh73RFktWOC0AuJD4IwgDzLI7E6YrtGcS0tDRXQnZJoFiCpiQIXcJpYoilWyBcmpGtGmAOJD4IwAN8RJ0LMB48049eR7QIEtnwkchwAuw7kdtEHZbsQkYDEB0EYINH833x7HTbmbtDX7kADTaJZgFjsCx/zkWjiMVZQtgsRCUh8EIQB+ABOVwJ0xHx7Hd4Zv7JKpdYqt4HcKW7ZgJRYIkwKOE0A8RgP8M9QItxrIjEwJD5eeeUVHHnkkcjNzUVubi7Ky8vxv//9T3q9ra0NkydPRteuXZGdnY2LL74YtbW1pjeaIOKBRKgTwQ+6aTZj7ga92S6JEPPBEEABp0ZJtAwvIjEwJD569eqFp59+GqtWrcLKlStx6qmn4vzzz8evv/4KALjrrrvw2WefYd68eViyZAmqq6tx0UUXRaThBBEL+I440cz2bE2TYCvWMvS6XRLhOqhZPhLBXRQP8JeJ1nYhzMJmZOdzzz1X9v+TTz6JV155BUuXLkWvXr3wxhtvYM6cOTj11FMBALNmzcKQIUOwdOlSjB492rxWE0QckAjFtfjh1SFZPvRmu+gMOE0g94UgCFKRsUS4f/GALL6HLB+ESYQc8+FyuTB37lw0NzejvLwcq1atQmdnJ8aNGyftM3jwYPTu3RsVFRWax2lvb0dDQ4PshyDilUSzfPADBxMfemevugNOE2hAEuCzACXC/YsHEjmziYhfDIuPdevWITs7G2lpabjlllvw8ccfY+jQoaipqYHD4UB+fr5s/+LiYtTU1Ggeb/r06cjLy5N+SktLDZ8EQUSLhFvThPvboZFiKmok2wZMtU2wgFMeK1U4NQSl2hKRwLD4GDRoENasWYNly5bh1ltvxcSJE7Fhw4aQGzBt2jTU19dLPzt37gz5WAQRaRLN8sGj5XbRIpBbQp5yHP/XQVpYTuBiX2gg1QWl2hKRwFDMBwA4HA4MGDAAADB8+HCsWLECzz//PC6//HJ0dHSgrq5OZv2ora1FSUmJ5vHS0tKQlpZmvOUEEQPk1R7jvyPmBw6tQVcr5iNQNo/MApRgg3iaQRGW6sgzm+iaEeYQdp0Pt9uN9vZ2DB8+HHa7HYsWLZJeq6ysRFVVFcrLy8P9GCKB2N/Ujgc/Xod1u+pj3RTT0aqJEa+0dDilv9Ps3pgPp07xESArJtFmw9LCchBg9wacKq8DoY6b3C5EBDBk+Zg2bRomTJiA3r17o7GxEXPmzMHixYuxYMEC5OXl4frrr8fUqVNRUFCA3Nxc3HHHHSgvL6dMlxTj4fnr8b/1NZizrArbnz471s2JKKIoQhCEWDdDkzvnrpH+TtMoMqZFoAqublHffvGI3eB1SHV4odmRAEKTSAwMiY+9e/fi2muvxZ49e5CXl4cjjzwSCxYswOmnnw4AmDFjBiwWCy6++GK0t7dj/PjxePnllyPScCJ+2bqvKdZNiBjKrrfTJcJhi1/xsXzbQelvKebDqS/gNPBAw8+G439AYgOoIBiPfUl1yO1CRAJD4uONN94I+Hp6ejpmzpyJmTNnhtUoIrFhM8tkROmicLrdcCTIKgVGYz70BpwmmvtCsnwkWLtjBWW7EJEgMXpNIqFgM8ukRDFQJ8Ksn2E820VfkbH2BBjE1da4SaR7F0tk8T0JEGRNJAZJPEoQsSKpLR8K9ZFIM0GtImNaw0mgmAg+CDHRLAhGi62lOjLLR4LdayJ+Sd5RgogZjmQWH4qROpEGXofB+ha63S4JMIjzMR9abpevfq3BuS/+gC17kzdmKRTkwcVk+SDMIXlHCSJmsFTGZETZ9SaU+NAIONUyfQQaaPhXOpyuMFsWefj2sudTKcJuensV1u2ux51zV0exZfGP7F4ngNAkEgMSH4TphBvz0dbpwpnPfYeH5683qUXmoazzkUidsdagq53tom9tl0QSYAIEn9tFo90Hmjqi2aS4R76OT+LcayK+IfFBmI7DZg3r/d9s3IuNNY14e+kOk1oUORJp4DVa3yJgwGkCu12CuZ8SrW5JpEm0gnJEYkDigzCdcN0uljj22ii73kTI9GCYmmqLxLR8AHzWj4bFJ8HOJ9KIspoudG0IcyDxQZhOuAGn8ZwtkxwBp/pmr4GKjCVenQ//heW0hCMFVcpJvHtNJAKGF5YjiGCEG/PBv9/tFmGJI1OIMj4iEVwODLtNK+ZDHb3ZLolk/QGCr2pLs3sf9324Fh+s3CX9T9eGMIv4nWISCQtvuQhlITb+/XE3uCtOp70z/jM9GA6rJxbHf2E59XsUONuFc7vE2z1SQYr5gBB0VVuKa/BwqLlDJjyAxLjXRGJA4oMwnXDFQ6TEhyiKmDRrOW55e1Xox1D8n0idsVa2ixaBi4xx+yWo5SPR2h1tLCoLJrZ30jUjzCGlxcfCDbU46/nvUVnTGOumJBUOLuA0FJO8jXOzmNnZ1Ta0Y3HlPnz5aw0a2zpDOkYix3zYNQItNSucBjq3BBMfrLmemA/P8+V0i3BTfIc2Kt7ORBLbRHyT0uLjxrdWYsOeBtz2bugzYcIfG2+5CHNgMrOz40NHXCEOOn4xHwkw8DIcGjN+Lc9YoHNLNLcLDx9T1ElptdqoPBeJ9LwT8U1Kiw/GgWYqKhQpQums5NUzTRQfnPoI1a/vZ/lIoIE3WKClkoDiI9EsH94GC1C49RKg7bFCrfgcXS/CLEh8IHAxJSI8QhIfEaqeKS+WZM5x470z5l1YzN2gd2G5do2y6at2HMTKHYek/+P9GijhU8EpuFQbNeNgot1rIn4h8YHEmr0mAuGmYUbK8mGGqEm0ImNWmfjQZ/kY0j0XgPb34uJXKmT/J0LsBB/zYbEIkiijwVQbtSyoeH/eicSB6nyA1iswm3CrX8rFi3mprLIMjRDvud/aLnHeGRfmpGHXoVYAASp7es/p/jMHw24VUJiThjvnrjF0bh0uN9It4ZXVjyZ2qwVOt4vqVgRATU52uNwQRRGCSiYMQRiBLB9QNy8SoSNf9yMU8RAZt4vLDMuHss5HnIuPQcU5AIATBnTzWT6UAads35Js3HBiP2SneeYkRq5RvF8H333zDJrS4nKc+IijWnZxgWYgMgk2wgRIfBCmw/dZIbldeMuHiR0d7xowqwONd8sHO+Pzju6hGfPBEBQDs5F7F+/XQYlarY94LusfC7SKzyXavSbiE/q2EebDdVrxFfMR/nH9s13iu8Kpm8vy0FrNVXlOaTb1SqiBiPfZsJTt4rVuOFQKroW7JlGyEVL9F4LQCX3bCNMJVzxEKo3TzR04VF+/WXU+Wjqc2FDdIJtd1tS34cznvsOcZVUhHVMNdniLIEgze7eoUeeEDcxJaPmQAk69vx0qJdbtYa5JlGxouV3i3cVGJAb0bSNMJ1zxIIZpOdHCHYGYj1CPc9HLP+GsF77Hot/2Stv+vqASG2sa8eDH60I6phpubsYvK67FDbpKQSUVIzMg0OJdfChRW9nWbqWgDx61Oh9A4t1rIj4h8UGYTtjZLtzf5lo+zD9uqO6Gjd6S/h+u8i3c5YxgtU3e8gHI2+1bdM2DZPkwsGhe3A9I7By9fhdf2rHvoaCYDzlagfjx7mIjEgP6thGmE3adD5lIMDPVNvyAU7+F5UwsH58WAbM/b/ngZ/bKjBfPPoKsHYYsH3Ee+6JEcrtw14FiPuRQwCkRSejbRpiO3HJhfFCK1Loh5rhd5B1yuG4hvh2OCIgPkZvxC4KgmvHiH3BqfNXXeI8D8Iv5UHEt2ThxFu9F06IBxXwQkYTEBxFRQhIPkQo45Q5lluXDVPFhNb9IF5/t4vkMf2GhFYzpFvUX4Eu02bDd5p/touWWIuSYWfiPSF1SWnxQgFlkCDvglPs7WQNOpffzbhe7sa/jmp11uPWdVag60KK5D5vAW5hLxe4ROIGuK2+B0Xv94118+KfaqgWcGj/vZMZNbhcigqR0eXW71YLOBPNVJwK82yT8mI/4qvOhtH2ELT7CiDm4YOaPAIBt+5vx5ZST1HeSxIfnd7oUTMq7XdQHZta+rLTgbUk0S4HaOjf8Inw0wAaocErXhjCBFLd8pPTpR46wLR+RSbV1mZDC619kLLz28SZs3vKhFeynxqbaRs3X3AphwSwfbSqmc1bh1Ga1SAvSBTs/RwjxIbHA51ryZruoBJzKYpUSTExFAs0iY3RtCBNI6dGX3C6Rwczy6pEKOG0zkEbKE9lsF1/Mh5HrFig20reaqzyThbd8qKEWG6JGKMGp8UCaSsCpGaseJxOU7UJEkpQWHzZLaDNNIjBimIO8TLwEGSQNHVfWrvhY24V/P59qa9Z5KwNOfTEfvvviy4jxvc9X5TTw/UvXEUMSLfY1tuPh+evx254Gv9eU5+hQcz9x+9MAqy1q4+FeE4lPSosPFvEOkCnRTHgd1xqK+DChHoca7jDbBZjvduEHOSsXc6DmFgkFvrw64BM4auKLtwOm6SyxnsGJmZYOJz5Zsxv1rZ1htjo0pn30C95eugMTnv8+6L7pKu6nSMUaJS5k+SAiR2qLDwtFt0cCvssK1/JhapExTn0Yqd7Joyw5HepxGHxHboZbSIkymDRNxaKhVkZbbywHEx+tHW489umvuHPuGtz41sqw2x0Kv+3Rjn1RniOLr2lTCbwFEq9oWiSggFMikqS0+LBSdHtE4DutkNwbEVtYzvd3vFg++PLeYV83FdghfZaPAG4SFbdLUPHh8IqPThc+Xr0bALB828EwWhw6elKVmQhjookXeZFK8U5UKOCUiCQpLT6os4kM/CwzJLdLFCqchis+7NKS7KLuQlxqyAIeue1mWT6kc2apttKMX93dwNC7uFxWmm8Qj3X2GB+wq0R5jpLbRWb58L3Oi8JURavOB/WVhBkY6i2mT5+O4447Djk5OSgqKsIFF1yAyspK2T5tbW2YPHkyunbtiuzsbFx88cWora01tdFmwX+5wjWfE+qEe13NDDg1J9vFc4xMh69ETptJnbHRQF3ecqd9TM/vQJYPZRqqZz99WTEZds91aO2IvfjQU56eZf2weidtGu4nsoQGKq9OfSURPoZ6iyVLlmDy5MlYunQpFi5ciM7OTpxxxhlobm6W9rnrrrvw2WefYd68eViyZAmqq6tx0UUXmd5wM4hUSmeqE37Aqe/vyAWchlfnI91ukUz4rR3mBocC+gSNnqJkbrnhQ3JNqIkKPtuFiZRg1z+Tc7vEWnykBfh85TgqWT461C1ANMBSzAcRWQxVOP3yyy9l/8+ePRtFRUVYtWoVTjrpJNTX1+ONN97AnDlzcOqppwIAZs2ahSFDhmDp0qUYPXq0eS03AZcsAJG+UJEglNgF2SAQIctHuBYZAQIy7Fa0dLhMFB/G2uewWYKKO3ZMizTjV8vyCD3glBcfkViV1wgBLR8KERYs20Xtud1T34rWDhf6FWaH29SEQOl2SbNZ0O50k/ggTCGs3qK+vh4AUFBQAABYtWoVOjs7MW7cOGmfwYMHo3fv3qioqAjnoyKCGUusE/6IYcZWyGIfTJyBhtsuzzE8vwWBy/QwLT7D97cuy4eOwV5Z3yKg5UPl2HoDTj0xH7Et2mdE/KSrZbtwr6u5vcqnf4NTn1mCg80dIbcxkWGCjcQHYQYhr+3idrsxZcoUjBkzBsOGDQMA1NTUwOFwID8/X7ZvcXExampqVI/T3t6O9vZ26f+GBv8CQZEiUjPsVCfsVFteJJhkVQAAXl+aEdCZbrL4MHrd9Ay2LI4hcKqtP76F1/QVGYv3mA+/66CW7aIz5mbrviYUZBWE09SEQGkQ01v7hSD0EHJvMXnyZKxfvx5z584NqwHTp09HXl6e9FNaWhrW8XR/7v9+w+66Vul/8vGaR7iiLhJZH4Ai2yVEUSMNYuDSTGPodgmGL+bD63ZRyfKQXBJc0IdkIVEZaHgLB1uMLR5iPvRcD4Zqqq0s5kP7uU2ViYqyNgpv5SKIcAmpt7j99tvx+eef49tvv0WvXr2k7SUlJejo6EBdXZ1s/9raWpSUlKgea9q0aaivr5d+du7cGUqTDPPPJb/L/idTonkoU2VdgRYfUXu/QfeD/uNyM9swF5YTBEGKdwilM7apZKoYrfMRKLXUd0wW88Heo23RkJVXD5Bqywe6sliS1k6XtFhbrODb1alot6hDhPHPbaB7mioTFeXXVhJs1FcSJmCotxBFEbfffjs+/vhjfPPNNygrK5O9Pnz4cNjtdixatEjaVllZiaqqKpSXl6seMy0tDbm5ubKfWGBmbEGqozTXGh+c5SmPRsWLFvxhQj0u/w42gLWEYPlQsxLoHfwYxmI+gqfa8gSKDbFwKoWl+7Z3uuGIdcwHV2QsmCss3a7ifpKJP/n7ZVapFBl8lYHINu/9bTPRFUqkLoZiPiZPnow5c+bgk08+QU5OjhTHkZeXh4yMDOTl5eH666/H1KlTUVBQgNzcXNxxxx0oLy+Pq0wXtej+1o7U6FCigfLqtna6kJWm/1FT3p52p0tWVyNUlNH7bQbbBcjLlYcTcJpm92WqOF1u2KwWhcVHR8wHJ2BcblG17oevwqnnd7qKO0U6J+59am4J5TEBn/iIB7cLv1BkW4cLuel26X+plgm7DjZ/lxl/Xsp7yuvUVLF8KL/HTHTSRI0wA0M97yuvvAIAGDt2rGz7rFmzMGnSJADAjBkzYLFYcPHFF6O9vR3jx4/Hyy+/bEpjzUJtwmtW0CARvuVDeXvaOt3IdITXJsD/vockPry/wxUfvIugzelGttUiH+B0uF14y0eH0y355HncnFgCfJYPtXvCu10CnRsv3guyPDcmHgJOjVSwTVdxIQRa9Vgej5MaExXl95hZz8wMAidSF0M9r55l59PT0zFz5kzMnDkz5EZFGrXzoCAqM/G3MBh6t+L2mJbKqlAf4RRAEyD4AvDCdLu0d7qQnWaTu110zC558dHW6VIVH/5uFxXLh8qx0wME07L9TxzYDacNKfLsp0i1FUVRFsAaDdw6xIOvzofnOrjcIjpdbtitloCBznLLR6qID/mTwa4dWT4IM0jJtV3UOtuWDmfU25EqGC00poyyN32dE+m4oQwinNvFEbrlgx+X2WBmNODUonIMJW7FoOuL5VBrs++AgSwf7JhPXXiEzB2mN1skUvAxpnotH4Dv+Qp0/flnMlXdLpKLjVzUhAmkpPhQWzCJvlDmEa7lwu/9Jpl51dwuoSIgPLdLsIFaT9sCBUgq95EqnNpVAk5V1HhmIMsHt386Z33hv1ehBOGGS6D6MNIriqwfwCc05EGlyoBT39+p6nZhYpesxIQZpKT4UOtsKebDPMyO+TBrpqkWcGoU/hAZdnPqfLDz491Ceiwf/NloWRr4AFmAXzDOf0E13hoTqIAaH/dis1qk+BV+31hYEl2y66d+T1iqrSAIfiv8ygJOleKF3C6SG43EB2EGJD68tJLbxTT83SYG3S6muEeCHzec0u+CIIRVZEy+zoxbdmxAn+AKNFOX9vH+DrSqLUMt20X1GvlZUzzdCG/tiIXlQ1ae3i9V1n9/nxVIxe2iuJ5uHdc62VBaCpnlw+mNkyGIcAg/fzEBUQ6OAFk+zMTsgNFIuV2MHvfzX6pR7a2KKyC88upqK//qcaPIjsH9rSXQlNYe5Wxf+bmMQMJKaSnJcFjR0OZEc7tPwMdGfATPdpFZd2xWAJ2Sy1VeZ0UZ8+EjZSwfin6Sr+/SFgep1URik5LiQz3VNjU6lGjgnyobXsyHWdH1yqJiRio1/ranAbfPWe3bIMhXdDUK37Gz9wfK1lBDT+0JZcxHQMsHN7gEOjdltdAMlWJrLe3RtyQaSbUFOCGmZvnwy3ZJvVRb5RdZFD3iTRQ91zeHq6NCEEZJSemqXmSM3C5mEX7MR3TcLkZSZKu5dYAAecCp2vlVbD2A2T9u00xPl1k+OvxjDgy7XTQtH972KmI+nG4RTpd/lg0jPUA8i1/BLu++sbZ88OJSVjyMO0HetZSuuH8Bs12oyBgsFl9xtpQRYETESEnxQUXGIku4qbIRq/MRhkUlwy6voeEJWNQur37l60vx2GcbsGTTPtXjqQY3GrR88Gifi+eYzPKRmeY7jxbFddUb86FM32UuGv46NJsk5vXUFvLt6/tb16rAivVdAi3sF6gAWbLCW3t65mfg8fOGhZVeThA8KSk+1Ap9UNU+E/GLrTAacCr/X88Kr3pQxj8YuedpSvEBfavabtnbpLqdb0qL5HbxbTOeaqvP8uGwWqRF7ZoVrhFZhdMAi+ZJn8tiPrzXxqlheQiVeSt34tgnFuLnqkO69ndpZAvx14l3LWUEynYJELCaMpYP7zkP6Z6LHx84FQOKsqXUasp4IcIlJcWHasApiQ/T8Iv5MNhZK98fuTof+kVRmmIRN4GL+QjUEWu3nR+ond4twVNF5UcIHuOgXNVWEASppHxzu0u2D0+m3bNPp0s7s0EZ88HTbMI9u/fDX3CopRO3vrNK1/5GYz6UqdL8ZeDdUspjp07AqQeZqyqMDC+C4ElJ8UFul+jgCHGW5BebYVadDxPKq/PoKTKm1Xa+KVK2hSzVU0edD9kx1N0cvs/xDSFZDnmMhm+Q8e2T7lBfIZa/N9JidSpl3c2MoWpp13efZNdUVsfEBz+QZnpFWIuK+AMU675w21NGfChqxADcgnzUXxJhkpLiQzXglL5MpsGub6CAzIDvV/xvlo89nCJjyvcKEHSl2mq5nPhnsKXT6f0M3+sdTrefWPI/hu9vrQBPt8LyAYCzfGi7XRxWi6+ipSx4k98/spYPhl7xKcsW0vH5kghTsXwA8udDnolk7NycLndCump86wL5tvnccakhwIjIkZLiQ61Pb+sM3tnrodPlxsINtahr6Qj7WIkKu4oZ9hA7qmgFnBo4rv8Kn+qBlkq0Bk61gFPlzDvYDFtXOXNFqi3AiQ+NQRfwFlFTEVdqVgSWsspjplm+0xX8e/nT1v34ZuNe6X/+usuyXQKIsIAp4hpWFT1MeP57DH/i64SLkxAVwcqAep0YggiFlBQfajEfgDnm/X8u2Yob31qJK15bGvaxEhXW1wdaHyTg+6O0sJyRQUTtiWGDc4fT7VdDhKE1A1dLtVV+SLDZMr+7Vjlzt4rpPCvNPzVWjQwHc0uoWwAERcApT7Bjm81Vry+T/a/nmctSnJ9/ZV3+vH3bjaaZbt7bhKZ2J37b02DofbHGV8/FR6jWTIJQkpriQ2MiZcZs7fNf9gAANtY0hn2sRIVdXqmOgtGA0zDrhGgf10S3iyBI4irQsYIFggJ8tov8M4LWytDhdmG7yCwf3kG3qV091oGR4fBfs0XmdgkQcKpM44022tYarpCaV4RJ1yFAQLKe4F41RD3WKZPZUN2A1TozhALhy2riLR8U80GYA4kPQHVhrFDJVAm+SzVYhxu65UOOeTEfnt8sc8VIVVs/twvkGTBaz47marPc32rZFkBw6wE/IGoFZaqt4JytDLRU8e0D3CyXj/mATH0AUA84jUWFUx7Ne8udo991UOyqZfkI1V0XjQwRURRx1gvf48KXf8Kh5vBcv8p6LgBfmI1iPojwSEnxoeyQ2QzIjM4hg8SHL+aDBacZzA4wOgjrhblGmK/f2CCitHwo4iI0nh1NQasyKCkHv8Zg4kOlVojWPhaL2oxfWWRMrj5UYz64z7QEcLvEosIpj1aQLE+mZAGSu11Yllaz7Bhyy4fe4mduFQtXJOHdf7sVVXmN4rOa+bbpyfAiCD2kpPhQdhuZJn6h1DrilMN7gdm1MFokjM2umUXK7GqZeupz+LdJDr+oGhDI8hF8wTc2KCnHs6a2YJYPH1qprWp+eya+WjQCLRmBKrgCgbNdzBAfVosQfCcNtFx9stgXFjCsuA7ZiusDyO+NKOqf+eu5R2biCiMrR4nPIkYBp4T5pKb44L6g8yeP0ZW1oBcWpJfKMPEQbGDWyi5ityc7XV4MK1zYx7GYByOWLq22BrN86HO7sFRb+Wc0BbV8+PbXukZqGQvs/JWiTul2UXObyWM+PKhZ+7QCYI2gLOxmhFYtVxGHVtZPliIWhH+NEezeMHRlJJmIm9NE4U+m/N0u7JrpPX8i9qzbVY+9DW2xboYfKSo+PL8z7FYcXZqP3AzP6owNrZ2GjrPzYAu+5dL7PMdMyUsqQ1RYPtQG5oc+XofR0xep+qWVM1CzOjo2EOSkq9e5CISf5YMFWwYRWNoBp8H3CXbeWkW1GPsa26U0VbUUU5+7Qf34zC0hD970z3ZJj5DlQ+24etG6pvKBVFFszXshstM8/YFWlg//nmDoqcViJnLLR3hxGez54oWr9J0MYpUj4oNNtY0496UfMPKpRbFuih8pOVL6lhn3/M73io86g+LjxL99i+tmr8D3m32Lh/EmaCOLYiUTvhmktoXh3WVV2NvYjreX7tA8TrZGMaxQYZ0pEx9GRI1/tovndzAfuJZFRJY9oZHqacTtomZpuP8/v/i1FwCy0+TuBmmGq2H54C0kbpnlw/OGLBVrXzgDrSiKcLlFaR2RUNCy1vBkaQTe5qT5W4aUh9D77EQ74NRoiflAKNfwAUL77hCxY83Oulg3QZOUFB++2geeb1V+pgMAUN9iTHwwftxyQPqbd7ukekS41FF1ODXdFqqDFJuBpvvqMJhRAM5n+fCIzeYO/YGDytFHcjmE6nZRmRErTzFoB8+b9FXcLr/squfaywWcOtQHEGXAqVolVLWCXfxKuYxwBto7565B+fRF6OCKi2nVUdHC6RZV66QIau4nZgHybs9WsYwZdYmpvS86bhfO8hHm54kqbhf23SHLR2IQz9mXKSk+lOnreZLlI7TUNH7WyfupzQqUTDRYp8U6KlH0CBA11Gbs7P6wGShgTqYA65hzMzzHdblF3QLRb+zzPjxq8QE8WseXxXx4syeUsQlBYz64v1tUMjCY+APkGQu+FNNgbhfmltComeE9pprlo8Pl1lyQLhifrq3G3sZ27G9ql7aFEkMSLFYok3OZudyidP2UC+8BxoOBGXJLRBQCTnnxEWbRRLUUbPbsBMvEIuID/rsZbyX+U1J8KPPX8zO94iNEy4fWjEbvgljJBuu00u0W2K2eq6zVWatdO9/7rVLGgxmuF9YvM58+YMB8rhAG7NkJNhPs0BqAFdkT7U63nzuwMZjbhTuGyy36fVYWZ5EQ1MqrB1jbhd+PH/jVioxpza7MnOmHcixfLIdvm1rwpOf4Ti7WyL8CrFLY6Z1Y8KI12jEf4X6eb10gLuZDcruE1lcS0YUPBjcrcN8sUlJ8KFPIQo35YMj9y74vf6r6RX2uYkEanLUGUjXzvHQNuWXrzbiWrDO1WQS/lV2Dv1f+P+uPWWfMn58eV45aNVNfTIpX0BgoMgb4i11+1sNbPpTXVKu1yoXXlDtL1yDN3/IBmJPxwghFfAa7fmk2CyduXb4sK4VlCAg95kNPFVoz4bNdzCr0xotSZo0MJoyJ+IAXjtFe8iAYKSk+WI/AOuRQs10YWgF5Zna+iQRvrs0JMlMK5HYRYG7QqSj67rvRlEG/ImPe3zlp/uenFCpq8QrKLZ7rIHcLNbUFfh6VGkfpmuJn9nw8h7/bxd+3D3BLzvMWAD7bRdovPi0fauXj+YGUL5Hf3OGU9lN7NvxiPkJxu0Q54FRZRM4ovjmAiuWjzZmwAfU/bd0fdgG2RMEdx5PhlBQfbmlw9Hypgs3Og8HPOPmbbeay4omFbzBjA12DxrVVu0a8ZcrMugL8fc82GLXvH/LheXbU0oH9rRoqAkuxT0Ork8u20Gf5UGoaZRGrLA2LRBaXzaG14ivA1wPRqPPhfYPDaoFNpSCYmW7HcMRHIHwFxdQsH9p1PvRbzHg3SHRjPsL9PLVFCVlf6QnoTbyA+lU7DuGq15dhzNPfxLopUUE2HpH4iD1K33q49SRaOvmZIbc9zm52tFCzfBhyu3h/C1AP/gsVl2T5EAxbVLRmeez8eHHlXxNC+xx98UYdfnVIgs1c/eIQFPszdyIA2Kx8zIfV+35vsKvG8TNVYh9kq9qy34pF9hhmDrZGjmVTxAmpxakweBeUJP5Uitv5Z7voex5l/UHULR/hXX+1CqeZdqskRhLR9bI2jlNPIwH/2JLlIw7wfUGZ5SO8wjlaxYji7WZHCz7mgwV3al1btcA9kZtxqQX/hdwu73GtFv+VXYO/V/4/646zVQJOlfs2qLhP2D4FWZ4074MtHdI25gY0GtSnHNxYKewBRdkyK0gGN4Dwg67S8eJLRVUX12pZEIHaEw5GxKeR7zO7/vub2v3cLs0BLB96743cEhq5/mDu8iqc+o/F2La/WdoW7vWX95IeLBYB2Qa/O/GEVnxSssI/txRwGgcoLR++2XmI2S4aKXmxXlwrVvABo7lBrm0gP7gA4yIhECwYLxR3jtLFwdIY1axmyoEqUBZVgbfGzKGWTl+Ksc7BM5grgCW/nD60WLZdEAS/Ghee7fLjsRT0ei4WSs3tAvhiAQCf5cFU8RFk4OaL+7GF4dQCapXn2KtLJgBg16FWP7dLoFRbvR25rD+IYOf/wEfr8Pv+Zkz7aJ20LVTBfqi5Axe9/CPe8RYAVF6z7DD7y1jCxyeFmgqeSJDbJc5Q+jKlzqbDZbiYESA3CfNFflK3zocHAcErIgZKtRVCcI8Egk8dNFpiXeniYCZnNaGgNNHXKwKZ+WN18c6865o5twuXURAoqI/N1FnGRqNiNu47X//38qXFtT6DFx/suZYKTymO2cUrogCuSJeJz38wIZbGLWtgs8jFRyB65mcAAHbXtfiV9ZdbfBT3PwSLWTQsBfsafbVRQr3+r3//O36uqpOqY1oUNzuRS6zzFsB4G4wjQTxb4lNSfDDYl4qftYXyheXLGLujNNNJBPjATi3/sHq2iy9gVbn4Vzj41qrgi4PpO65f9VGF+OBngcHFh+9v3vLBxjfmdgkW1MeOw0SC8hqLnNhSolbrQ7kXi0dxi1yROFF9X1585EagCqaR+AJlbZhAAq5nF4/4qK5r863tku5b04ZNRpT3P5SA03Zn6IXX9OLkA05D7H9ciuulvNfSMx9ng5kerNx3IRFjVowid7vE1/mmpPhQFhlLs1ml5dtDeSA7uTLQ8aw0owX/wLPoeLW4B0B+7fzeL2gXxAqtXb7B2Phx1S0fahUflQNVXYu8ci7/jBRkO6R9+Jm3nqA+tj9zbSlTxZVZXTz8yrZaQ3O63Sq5MNjSA9KtURyTWXAAn2jRuuehECzGgn/mSgsyvO9RK68u/5+JJv768/VR2MTCP7jXuPgAomstCLX/yVHERfi7XRK3xDp/P8x8PuMV2XgUZ5b4lBQfalHc4Qad+o7NPdwh1g1JdHi3SygmWr67ZgGnZnR0bEYnCPAFzemu1yD/n1UT5VN22b33T6NVWD64v32Wjw4uINYX1BfIr846Fi3LB3vdqmr54EqnBxAp+Yq4Dy6cR0ZBli+zJk+qm2Oi2yVo2rGnYZcO74VTBhXJ3hPIkZoru3+ebWqVdZX3X+8kRU/wcaQINebGPyhTfrdzTEx/jzYyN1gCiiejxPP5pqb48P6WReubVDaY76RSQVmrwWerBEu1BeC3aBxf3EgqAGfCtWQfY7VwdT50zga0LPesJoco+lxDyn0DuV2YxeBQS6fs2dFVh0ThplFeI97NpIRlIfH3RWU3v6BTtdoPgNztwhZqNPP511tqfvIpAwLG8yhTbdVq/FgEX3VX33aFBSPELKlomvqbAyzoGAhm2WAon59wSxPEEt4SkApuFwo4jTPUOtBgxbCC0eH1zfM3WznopBqCwPn/Azz4yjgbPqhRLeMiVPiA0yyDFhml+ZyRbvcV2GLHUu6rLNvPBy92zfI3+/MBsbrcLpL40Ij5UFEfrIpqQ1tnQMuAct0jTbcLJz7yMtTdQOEQXHxwVi1FkbZAhTizVVxWgiAgL1MpujyvZUqipDOkMvrRnJCIYmimdrtVfm+1sl0ScXLFJxQoA7STEV57hlvx1mwMi4/vvvsO5557Lnr06AFBEDB//nzZ66Io4pFHHkH37t2RkZGBcePGYfPmzWa11xR8qbbhuV0c/Aq2KuZZM83OiQRvudCTlqcUJrxpX1pxOMRF/+TH9WV/BEsB9nuvxnZ5tVT5QMXQa/mQW4zYjFy7fWz/XI0KvVpWCkBd1OnZT6sUewEf85HhUG2PHrQGdL3VXj3CUttVpzxHyUrCuSj4544NsMrgXreoLwhaeTbRnm2HIgCVgsnfWpS42S6ywTgB228UMZksH83NzTjqqKMwc+ZM1df/9re/4YUXXsCrr76KZcuWISsrC+PHj0dbW1vYjTULtQ5UOVvSAz+hbFKJrE9VywdvuVCbwWulrSox3fLB1fnI8w6Qeo8baJartJop99VT56OhrRNOl++5zE4zYvkIHHCqlu3CX9dA58auU12rJ2iWr17LY1bAqVZTlEG7Stwyy4ci1TeAgSInXRnfILfYNSjcTRkOq2Tp0iNclQN59MWH8c9zKxJy/CwfCex2kcXkpYD44MVWvFl6DJd7mzBhAiZMmKD6miiKeO655/CnP/0J559/PgDgrbfeQnFxMebPn48rrrgivNaaBG/eZoRSaIy/sfWtnSgFuV0A+QCilg2irKWiVQdDgMAFL4Z/Lfny6kZFTSALe36mHbsOtUoDpNLy4Rdwyr3OzPui6GuLxSKolm3XapMv4FR/nQ+Z+PBuU85w2bmx/XiU+3bJVAk4DUF8aLm3DjYHFh+8O6hrdhoAoLahDW63qLoYHiPN5sno6eBSmvnnThloaxE8cUgHmzvQ0OpE97zA5+MvtCPTJ2Sn2VTFQCifp7wHSvGaLJaPVIj54J99M6zHZmJqzMe2bdtQU1ODcePGSdvy8vIwatQoVFRUqL6nvb0dDQ0Nsp9IIwVhyRZMCuELxT3I7MbyD3drp0vWqaUKfDYRcx90ON1o91YF1Ts485aPxnYnnGHWSODLq/M+/VB89zwFWZ7B7kCT1zqAwOKKP5bd6hMabIAV4HNjHAow6LLP0XK7qLkXGcqZPRDE7dIiH4QDWT7SvdVGQ5p1a1k+WjsDFgDkXWqlXTJgtwpo63Sjuj746qW5igBLCGrn7Tt+joGYB+VjcyhCA0CWxsrCoczu/R51P8uH7zuZaMhLIcTXYBwJZBPkZBYfNTU1AIDiYnk55+LiYuk1JdOnT0deXp70U1paamaTVFGzfKjN0IPBP8gHpVlv7ALM4gW+SBiftqcVkOln+fD+5sUHYLwjFUURv+9rkgYOvu4FSyHtdImyInHax9J+jQWNMvHgV+dDIXD4ly2CIAVrHmBCQxDQzTt739/UDi2YeVzL0uBzRWi7XRpaO4NadQCVbBfFfnxtCBYLpTcoU63NSkQxsOuFdzHZrBb07ZoFANiyt0mzJDyDt9p4jqES68LeD4ETe3rcLvL/A4nJcOBrk/CYE/MhJ1jhwHgm1bJd+O9fY7szrkrKxzzbZdq0aaivr5d+du7cGfHPVOtAcxUzHSPHAXwdo19efwq6XvjZsdUi+KUtBrtGvtc9AwkTMEbdWM8u3IRTn1mClxdvBSDPdsnkfPd6zJGsSUeV5uPsI7pj1nXHSa8VKMWHYsRxuUXFsvTy19ngd6jFZ/nQIz4YbKBs65RX0GSWAlW3C2/5CRAUoQz4VRPugGdQv+GEMpwyqBAnDOgGQH9QJk8grRLI9aKM4+rlrVy6tzH49eOtNoDnXHIDpBizGBs9z41yIA/mPgoVu1W9Kw/F9etX4VTL7ZKAlgP+1FJBfASb6MUSU8VHSUkJAKC2tla2vba2VnpNSVpaGnJzc2U/EUfFdMxmr/t0dPYMfozxzXrj92ZHGxYXoKyl4H+NtFNtAX4ANNZxv/jNFgDA3xdUej/Xs90isKBT/XEfrM0FmXbMvPpYqZAV4BMfzHLBTi/D7qucy7edP3tB8NXF8IkFAV2z2fMYfMDlgyblgb3sfAMHnPJtCbYfv2igkj+dMxSzrhuJTIdVStc0Kr7VLB8sM+lAgIFbWc2VXdP6FnkqsVotk4JMhfiAf+0U3pVYnJMOANhTHzyIPlriQ0tAHjL4nQH8rTVK8cruR7yZ8fUgq3CaAn2z8usUT3EfpoqPsrIylJSUYNGiRdK2hoYGLFu2DOXl5WZ+VFiozd665bCZpr4vq1ZGg39Fw+RX10qU3aAymFc5s9JKRWV3x6yMF+VaJ8paDoHf7G2TygjdzSsUDniFq1RZ1OJfL8LTDt97BQh+Zn9B4CwfAWbu7DA2i0WqP8F3qIECTqWYjzanZpwFEMj9oI0gCNzxwxcfhd7vptbAzX8XLUrB2ip/j5rA8rd8aBdXswi+9WB21wWPJ1GeTqTEh9Y91Nuf8Sj7Nq11fBrawo/DijayCaNBYfbK4q047ZnFuqyR8YJ/2n9knr9QMCw+mpqasGbNGqxZswaAJ8h0zZo1qKqqgiAImDJlCv7yl7/g008/xbp163DttdeiR48euOCCC0xueuiodnAGzNyeY8j/J8sHh8KylC+5FbwDmKK/Ulo0+JgPIHTxoUyjZJYFf4uKfsuH2kDOAk7ZM6AWsyJruywGQWXwg/x51Iqb4N1bLIaFn+nqiflwuUUpKFq1vHqmPCVZDCDCeKSgTINBp2pnyoSYluVDLaaDv7fB4k740vCAMttFXqJdELiVcA8ZFx+BrDfhoFXJ9EAIA6XyWMp7nZdhl75DygJ68Q7fPxuNv/nrlxuxdV8znvt6k9nNihjK8ehQc/zcL8OptitXrsQpp5wi/T916lQAwMSJEzF79mzcd999aG5uxk033YS6ujqccMIJ+PLLL5Genm5eq8NEzRzNOriDzR1wu0XVqpA8fjdVI+YjFcUHH3AKcDERGkG5fq4uLtUWCF18dM1yyNwQvEUC8A3Yesyvvhb7PxdKtwsfW6LMmvAcS360Lgqzv0UQ0C3Hs63d6UZzh0tlvQ35cYrz0lFd34YazhUQqM5Hut0Ch9UirVGjBWt/kxSsJhdwwd5ndKavFKYAZ/nQmMW7VSwfUmVWZYqwasCpv+VDuVgfbzXr4RUfe3Rk0vDPnMstSmv4BBNvRtEK1A1F7Ch1jLKpNqsFuel21Ld2oq6lQ+o7EwFeiLIMKmuQvl7JPh1xRPGCn4U+jsYjw5aPsWPHQhRFv5/Zs2cD8Hy5//znP6OmpgZtbW34+uuvcdhhh5nd7rBQq/zIfOysgwiGfwqd+sAayswj0VGmY0rio0n9GilNw0rLh7LEt14KFBYF5WAcSsyHWj+lzHbhK5UqF2bj2+HZx9/tAgHIdNgkV4qW64UX0T3y2IDYxr2u3WZPUKVi9VKVz8jlrEd8Zkyw7poN0NU6XBM8gd0u6tdBeT0BrtBZa+Dy8YD/cwKoxbp4jw/5RCUY7LPZZ7jcYkQqHysFAwumDsny4ed20RbcB+NoJq0H/jrxtXWMEE9xE8EItsJ2LIl5tkssUIv5sFst0iCgx0+qZc5i25lptupgS7jNTTiUVgKpZoVGES5lB6kc4CTLgsGOlLlDAKClw+k3GGvFBaihVd8CAAq8wrWlw4W2TpdM5OQpXE6eY8ln6vkqAY9A8IwXN9emkjyPZbGmQZ/lA/AFVUqfq7KbzWqR0mjrWjuhDOzUorQgEwCwS4drgieQ+NB0u/BPnCRY5YIwEEq3F2+xavLWl+HdTWyicqilM+jCbex80u2+rK0DGiIqHJTXrchgDFugY6nGyWSGZtmKNf4BwMbvRSJZs1Mm4DRREFUsH4Cx9EZty4fn/77dPJ1v1YEUFB+K66usY+FnHfK6uqT3S6Z9zwGKc/0HVj1kOHyFl/Y3dvgNnHmKeIZAKINVeXLSbFJ2x4HmDpmVxGcV8T1TsuwLrs4Hg30GC2TVfh5917m7V3zwlgapHRpm5T5egRCM/CxfthG7N8Es1SzVdechY8+/2lgezNLAP07s2sljZgJ/pl+2i1cQMrGwsaZRZi3twmUnBXt2+OdGKcLNRHmOhd7vTFO7E2066tjwKO+BmiBk1yAS5xJJlOemJxVbSSKJD/9FLuPnfqWo+PD8Vs7eWCenx6envKls1ss6G1bkaEcKWz7Y1ZVmihriQ9mJK/s6n/gw1lHwn7OvqU2WygpwQZo6TMdKVxCPwA0sB5s6FLNkefVTwP/88lWyXQDuedSYvfosRAK6e90u6jEf6uc0ql9X+edqOFN834sOru2B1Qdrz16DglEtODRYtotazEchN/MPtMAe4O92EeCJ0TiubxcAwLJtB2XWUofNIgXUBrNi8K6xLpIFz/wBQFn9NT/DLqV5G4370LMeTZcICqlIony+ag0+n0B8WQ+CoTzfSFXYDYWUFB8q1dUB8Om2xsQH6/Bq6tukYzOf94Gm9qCm2WRDKe78LR+e1x02i2Te5q+5cqBnLgWjAxl/3T0Dp3zWzu63ntou7FhaA3RXVmK9uV1m+fAJCP785IMhE2cMQdE+zZgPbn92jdRjPtTbPKAwW3W7kkLuHAK5n3i6SlYbowOf9ufryXZh59o1ywFB8AzKwVwDakXGAOCInnkAWJVUeRB1NxVRqQbf1yhjg8xEKRhsFp97yKi7UtlfqWWF6Cn/H48oz01PrRYleioixwt+WZkREL6hkpLiQ9vtor/QGH9Te3XxmK+r61qlToB1NG4xviKMo4HS8qHsqFgHYBUE1WvOz+gBoMRr+djb2B5wfQ8l/L77mtp9lgCLv2le9zlpDLq+jr5D1n5+u/JgkmUoS54twM47mBuQHxB75HuuUW2Dz8ITbMavJXqUMCvCvsZ2v0wmLbpl6Q/K5GHHt1sFnHVECa4e1Vv2/KhZRtTcAjarxVc40CvetNqc5ZCvi8L26+21XlYdbPbLkFNWtdWCvwfKrC8z8c9QETgBaNRiKP9fzTXRRYqpSay+TXlutSGIj0RCKo4oZeTFTwJEaooP72/ljNBX2ElH5yATHx4rx666VtmsnpnTUzHjBVDJdvEOHr6OHKpuCeX7u2U7YPHOYo1cS76j2dfIWyS84iNHPjjpOZZWoCV/jrzlQ03g+ISM51gOm0WW8cI+ojDI4MELosLsNFgEwMldI6WbSYkyRVJrcJaJD52WDxaE29rpQkuHkfWSPL8tgoCXrx6OJy88Qrq2To1MEf4+8+fKrI9b9zUF/ExBECSh4vnf87tPV8+kYseBFt9nKJ7pYC4NXrQos77MRCnKnG63sf6MQynm1FwTyiUBEgXluYVi+QDU3YPxCGtmoU5LXTRJTfEhqs/eCkN0u5R6LR+7D7XKTN2sQwsl4jyhUXwxWafb4fLUrOCXtlcfnOX3x2a1SPfGSNCpLOajkbN8SIO7x1rQ2BY8KC9Q2iogH4x4ocJmnwe5oFq1tYXY+bH3AbzlI0jMh+BZA6dIUfY7WLaL0vKhhVoslJb7iZHlsCLNu8CckQ7PrSKY0u1WKfhzX5PK/ZeJD9/fR/byuE3W7KzztDmAYuqe76tDxPZjAbnVda3ocLlkx++qM35DVLN8RMHtcqilU8p42dto0F2pGFfbVVbm7qJTfMUb7DKxDC4jMR/84olG1yyKFey5kOKmWjoMWY8jSYqKD89vZadsxAzPf9l7ceWWeTNrV4NVU5MFpYsi02FDut3zqB1UBACyUtWVNY1+B+BvD3O91BoIOuW/ZHylUHbfczNshoPytIYvXwwA9zkWn0vF6Rb91gnhnz+Z+GDHDCKGlSKGDaCs+FUwwZTpsCHDzrkcgrhd9jfJ41kCIQi+lXmNDH5alpX+hR4XSGWNvxWD/y7yAoPFbGzc0+j3HiWsTgpPYU4aMuxWuEVg10HPNWWiyycqAz+PvACMpNtFOaDsqWuVxKiR7wzgP6svLfC/NmzCxa8anQiwZ4V9V4xMZthqzUDsY11+2rIf5730A9bvrg+4H7s1Bd4YKFGMn/TolBQfShMqw1i2i/cQ3ABaXdcqLXPuKfzkecD1rAGRTChjNgBIHWFNQ5vUWVktAsr7ezIuvt+83/d+729+IPEFVOq/lkrLh7K8usDHnAS550qXjZJCaZbZLhtwHDaLVKiLiQipVdyheBeIRWH50JxdK1xB3fPULR+BZvzsugZC3e0SLOrD970wUutD6zoP7eFZcPLXav/OVi34G4BfJdJALS7rluW3TRAE9PZaP7YdaPYc39tjFkgBxkEsH1zaOEvpjYTpWzn+721sR3FuaJYP9j058/ASXDO6N2ZNGum3z4CibNitAhrbnIZrucQSZULAvsZ23evT8GtSGU3R3V3XislzfsaqHYcMvU+Lq/61DL/sqsc1bywLuB/7btitFmkiFEqGTyRISfGhVauAL2YUzDTFz6KltR44y4dFENCHpdt6O65UQVRGVIKLiznUIhucj+tbAEHwXDsWq6DmFuvrHRy27g3sv+fhByU+GNjKl9UPklEinZOGYGUUceJDaWFRLlqodn6F2bzbxds2rzDSqtWgbFJJrrzKqR4rBYtr8BxHQ1jx2S7ah/KDzY5DER9KbTOgKAeAJ/5CCd8mmWD1Wsv0LO7Yv0g984cVS2Of6wsG9tybYIMQn+2iVgjOLNSLs4Vm+WBt7tklA3+54AgMULk2DpsF/b3ZUlsMfCdjjeSGyE6DzSLALepfyZzPlDE6gD/26a/47y97cPErPxl6XzCCpf3KJsn58TUZTknx4esQFG6XnDRpDYbgM2F2DN8Mb08dX0vCV2hs235zxMeWvU047ZnF+M+qXaYczyyUZldlhVKAFx+tnAVCQHaaTaqJ8mt1g+z9/AFYWuiWIMGDPLyA3NvYLtUS4Ytu6XW1BYufYJadfY1tsmcD8GV+SJYPFdeCmtslO80mmXrVnkdl1pa02qp3sA/WZkBeaCxYtkuH0y1dQx2GD8lcv8tAoTGtNvcIYPnSEizFCqtOoDYf17dAdTsTZ9u932F2jF6Ka62Fr9CbT3zsb2qXFvPTQ1unC/d/+Au++rUmwOd4fj8wYTAA4MGzBqMoV78llyeYu47Ry8DqvvECOzebVZDqB+kNOuXno0YDVUMpZmYG/ESbt9DHAykpPnifPI/VIqDY29FWBzHv8xaO4tx0WARPQGWt18TJm2x3HjTnZv99gWdVxbvnrTXleGZQWdOIUU8twps/bZe2qZnm2Sx4+/5mvxn5kO6eWe2mWo9v3qc9fO9ns6/NtQYsH4r+nVke+E5Vr6stWIop6+j3N3VIVgp2+mwQrFF0WPz5qQWcChoBub42yY/DLHC76hQxHwG+5Vozfp50u1Wa6W/zij894oOloBt7/tUHPrU6JtI7NARLTppvfRwgcJBsWbcsvH7tCLx342jZdiY+mHuF3Zue+Z7tNQ1tAc32ygB0h80CUTQ2c/5g5U68v3Inbnp7leY+7Dt17lE9sPaRM3DTSf2lwXVvY5uhuIxgLkZGzxDX74klvCuSuaX0ptvyk5kaA+5fwGcZNQtZrFYA+O+GkdWYo0HKiI99je349w/b8M8lW1VjEhjd831WjEDwQZV2q0Uy8TITs8fM5eugzIgwtlnj73Y981Ul9ja249FPf5W2qXkohnmD/1bvrPMbLJi/nVmI1PpJJj54C0YwXBodLi+KWAe0J8hgoDXAMbpmOSQhs3L7Qdm+kig4xEQBa4fv/XLx4dvORI3aYKU8jnI27rMIaA8ix/fvqvkaz+AST8zFb97gzWDZLgBQGkKJdU3Lh/ca7lXx0fOp2zyCIEjfSz2cPrRYikFi9FaUoGefUZSTBrvVYyUN5EbhhbggCFJcjhFrQQuXWaElInhBz9YTYsK10yUaqmyprIejRaiLB8YS/joZdYPx/YlRywcvPoxYvbTgqyIHEpZuzsrcIz++LFXxN5pFiEMtHfjz5xvw8uKtfhUmebrrDGxUpgQykxY/SBXmePyKLrdoSpBPD86MrDdIKtJkqS31rmIGP7Z3FwAegcGirdlS1mXdPMJiuzc2Ru3+5KTbpYFEr4+ZCb5uipRSfmBTuiq00CpMxxAEAScO7AYAWLpNKT7kA45aqm137t7y21kWRrWKGFZep95dMyEIHivJnnp58LMW/QuzMf7wYozuV+C3xgnPoBKPdWpjTYP3mJq7SpRyqap6xbeWYOqW7fsuKVOPfdfTv1HFvPjQ0WYlLG5LeQiLxdeZB4ppUbrgmND+fZ9+VywTyIC2j599Dh/PxNePMRJ0yruOA+ETH/ERwKgHXtyyGCm9lgC3zPJh7JzzuEUczRgL+MlKIPHElxfoSeIjNrBZYX1rJ+pbmN9axfIRwLzLo5xtsS8iwyJ4BtfuJgb58GWgQy2OYzZ8toRS0fODQV6mXVL/TGSwy1/GYmP2yS0fyrszsNgjUvQGnTLBoDV7BXyugWD3hw/c0oJZZ9higspYDDZDZF0YLwq6c6meTe2+AElWuVRtdqnMZslNt+Po0nwAwHeb9ukKOBUEAf/8vxGYe1N5wJkuC/hlqzTryXYpzk2H3Sqg06VffDPBpDy81eLz0StdooEquerJ5glEz/wM2fXj75meuA/lPRjofUaYi1EP/GdqPadaoq0kz7h1IlhZfka8zaT1wJ/bYd7+5DevoA5GOJaPcOJFlMz6cRt+2eXL+grkiua/G/FmqUoZ8ZHpsEkzYLbYm9pXiw0CQS0fii9oTz/x4dneI4Qvvxa8dc3oaqGRIp9T9Gw2oFWrgfnPmXuFXSMWcFpd3ybL6vCv9eCN+9irr+N2aYoP/wFk16GWgOZLPSmm7BlgMxFlfMBuRSwG/wDyFiS+c2LPo2oHryLSjin1WJg865F4tgUbRPTAXCjMfK/niFad1gGeQIKpRCN2JtB58paPUK6Cw2aRTSz4j1C609RQtu2wYo8FaXXVId1tcLp8z6Va8K6yajBPb2/Qr5G4Gz0p2oD8eY+XwlXB4Adj5gpet6s+aEwMf40Bj/XCyJpdvKXaSLkANR7/bIPs/0BClp/osLi7/U0dsglOrEgZ8QH4zMBsZqrWwfXI12f5UM622OyWodxuRi68rBMyKYg1XPjZgLJjVF7e3gUekcHcJuz6F2Q5pFoY2w80c6mo8iMwy8dm3W4X9rna4qN7XgYEAWjrdAes2aDmKlGifAZ8VjHPM1XX0onmdqdqTAwPH6fA3B2rdhzyzypScU/JS4Lrm8HqoVRxDfWO5Ezc7dS5unMgIcGskkohryV2AUiz23CQpSPLhKv3Wh/UdqEo3XUnDyqERQDW7qrXfU2cXOS0Wj+iVV4e8D37VQZW19ZbSM5st3I04N0uA4uzIQieVOxg9VqUOsPpFnWn6LL9GWa7qQK5oXlLT16mz3W9oVqftSeSpJb4kDoLbdMxm+UEmykoZwf+bhfP9l4mmrpcXCcUL5YPl2xWxtwK6jOCY3rnA/AVFGNmfkEQJF/49v3Nmou4McuHXn85m5n0Vvjt+ewPh82CYm+abCDzuZqrREkfDZGTk26XxFV1XaumFWX+5DG4/8zBOP/oHtK24X26IM1mwd7Gdj/RpRY43burb7Bx6RxE9NAzP0N2P/Qekn3n9D6vgQQTE3fKgTTQe/gUWrUy4XpgohmQn/fQ7p4g3GW/H9R8r7KfKMpJx6gyT1DrF+v26Pr8TpXvmPwzfK+bIz7Uj6XEahE070m8wgurNJsV3b2DsVr9GB7essPiN7YbKKHAv9/saxXI8qGcJLMlB37ZVWdqG0IhpcRHbx2WDzYI7m9qR2NboAhxecfeVznAKQJRt5tQaIxXz0ZSTiMJ3yZm+dAqyHXG4cWy//nOra+U8dKiGfPRz7vPrkMtaHcGX1tBKqWc54k9UPtcQF6DRItgAacAUJSbLgsKVost8XQ86sc6ujQft47tL8tqSrdbMbLMM4B+t2mfvE3e3zLLBzfYSEHRJqiPdLtVEmmez9R3TGYx0Wv50xKegLb4DPSeXl0ypBL6ocJbPvhn58hST0e+u64VH6zcqfpetYKGpw/1fA+Wb9MWLTz8wKVmLZGJD8Wplkrp/gbEB1t1Wsdzo8xUi3eUljW914e/xiy2y8g58/3k7wZqFfm1Q8XVs3mvdol7ZU2rwV7BHA+F4VJKfLCiRx2S/83/y5WTbpciiQPNsJWzg1JFJ8e+t0d7ffCrdhwKunhZMPhOaF2Qmv7RgjcJb/eKOp/2kF/fopx0WYoY37f5OrEmrkKq/P2FOWnITrPBLerrTNnM32YRZDE5yj61l47Zm974iaO91h1APkDznbSWuNLi+P6eLJrV3gXSfG3ydwX16pIJi+BJz2SFjcywfADyNT70HtOo2yWQFUOromYgl5ggCBg7qFBfYzUY5I3TAOTrshTlpGPMAI8VY/7q3arvVStoeIR39rlhjz7TdycXL7BJJd6JH3eU141l61QdDBzTJG9zcKHN6NeNCcLYD2Z64FNPAaCfd82g34LcC77vZesMbTMwoeSt1uEINaeK+Ghsc2pWsVXGArG2B1vpORqkmPiQm8W1vlxshv37fj1RxJ6D2KwWqaIpv/2w4mwU56ahrdONldv1B5mpwT94u+taY764EaBQ9N7rFchKwFuILCqD8/YAlg/ePbNVh+uFn8GxOhXKz/V8dvAOVMuVpIRVYvV8Dv8ZnnZvrGnUbdZmsLgF7Rm/7zgOm0UKUmX1IfRaKYLBp53qqfMB+Cw+ui0fAVxF7NrWNLTJAuZ8xdTU2zQwzLiPkw/ziRelufqpC48A4LFiNKhYStUKvQ32xvHsqW/TtciXU2b5aPULFgzkdmHuspYOF1bqXFfEyPNZVphYlg+lK5JZFX/cul/rLbL3AZzlw0C6NH8P9zYGs6oHOo7cdchcQFpB+MrvhlHXdSRJKfExsChH9r/W7K2fjhvkq6Hg29ZfZeDx1H/wdF7fb5abzY2ijChfr7LIVrThYz5+39cMt1sMGFA5kKuoqWYZ+D1AzAe/n57OzsUJxMN7aIuP/kXBZwN6O+R+hernN9hbxfXTNdXSGjZ6NYGvw2iSRc1rBVoqF0kzI+AU8HXURmDWkj31rTpdZZ7fam3Oy7RLhdz4dOtgVik2Ow8VXtS0dco7/z5ds9C/MAtOt4gfNvsPYGpty0m3S66cYDNuwL+mj2wFaMj7BeUlcNgsUiG5d5fuCPpZnjbrjxXqF0LdkliivB8sJmjjnsaAxb94dwcTH0Zc6XyyABC6WOtUHIfFcGzScMMrrVisbzjQ3BHz1W1TSnwU5qTJCk5pzd6YaSqw28XfPMwvwMR3WKO8nfYahdncKErVGw+uF17Rt3S4UFnb6LfaKs/wPl2kv3lXfF8u1qbJuxCY2v3pJ92b4GZDdrmsFgGH99QWHyz98bc9jZoDZKCMCp5h3OfwhZ3GH16C7nnp6HC5OfeJXutBBvIz7Wh3uvFfb5Aib0JXHoXNrBlmuV1494XeOJLC7DTkpntcZVv36rdWaV2aAUXyjCnAv5CXknFDi5Fht2IE9+wZZWCAMvTMLbZWJYhPq/4GC1bVJT4Ukw6l+OBfVovTuO74MgD63TxGsqTKuPovnXFS+DAQboUloGd+BrLTbHC6xYBiQu52YeKjRf+KuIp7GKpY4z/v3vGDpLo+WzQsH0oxz6f0n/X892GHAoRDSokPwJe6CPgHZzGYif7Hrfs1b47aYKRm+QCAw3v4fLxG1lhQwh7gHO8DtD4uxIf8y/f95n0BLRcneKuAAsD63b7OMDfdLglDNrCovZ8JvEodAbf8KrZDu+dJ2zsVbR5QmI1u2Wlo7XRpLnmtdzY4gLOu8RlTdqtFEqGvLtkKQL/lw2a14IrjegMAvtu039se3+vKgY0XWp42m6M+inLS8fwVR+P4/l0xzbuAWTAEwefyqqwNPvgFszCxY/EDabAy8nkZdqx+5HS8d9No1df18Pq1IzCqrACzrzvO7zXWpyhFgadtnt/KljHxoSflUTlr3qgoiiUGcLsAvudh675mXYONK8g94CnJTUeOd/COhyDGYCjTiAVvyi0AWeEu//ex/T0ZXDlpNnQ43ZoWByXKfnKjyrOiB7767ORTBkgTJ63nSC0eisUpNXc4VZeyiBapJz6KfR2zluWjvH9XdM9LR11LJyp+P6C6jy+K3XeMoT1yVfcdWJwNh9WCxjZnWPU+WCfEghrjwfLBvgxdvdVXv9u0XzUQktGrS6ZfQTbGUE6kab2fddprd9ahpSNwoRzpi2rxlKjumZ+BgiyHf0E4i4BR/QJbp9TiK7R47vKjAQCXjegl236Mt8R8o2TZ0c9xfT3vXbe7TtYeteMwsSu9bpLlAwDOP7on5tw4Gicdpj+Ik30v1lTVBd03mMjjC0P53oOA7wE82Tr2MLJe+nbLwvs3l2PsoCK/14Zwz6T/ujPq58Peo8cawcQyE+fKgUte58P//SW5nkBvl06BoLfOB+D57qjdk3hFTdye5HWLf7JGPWjY8z5ff2+xCFLQsJq1Sw3WFzFLRaiprp3e47CMOHa8tbvqsTfA+k/8+d43fjAmHd8Xi+4+GRkOfQvURYKUEx/M9w5od8pWi4Dyfh51qNVhqpXb7sf52g81+wKK7FYLDivxqOtfw4jTYObXo3rlA/DMrOtaYuu3Y4KIdcrLtx/kAh3V3/PW9SPRLduByaf0l20/ulfwQbNv1ywUeIXOy99uDdg2yfJh8Szq9e09Y/HdfacgXWVFyCO8HaiWNUmKkg/4iR4uOKYnFt19Mh4/b5hs+1WjekudBWBMFLD2bdnb5ClUxrtdFMfp1y0LaTY+88pE9RECzOKjJeR52FlptZn5uNdX10sdupHsjEhwVK88dM1y4FBLJ5Yp0me14lGYINuytymoNYJ9x5g436iwoLplz4L/RRAEwWdp0SF2ggXwKpFqR3iFcTyjJgbPPrI7AGDl9kOabhT2rLG1c45ig75OVzrru9kaV+t21xuqkCodx9s+m/cEenXJkEpI/G1Bpd/+aud7VGk+HjvvcBTlhLf0QLiknPjg/daBfHysIJYyvZGh5he1WS24+aR+GNYzF8cPkK+Oyb784Vgr2ANckOWQHjjedRELWJsGl+SgR146OpxuKcVTa6juX5iNFQ+Nw73j5ab7I72iiqHWkVosAm46qR8A4IctgSPUlbMch82CbJWF8ADgGG9nsvT3g6odkBHLB+A5R+Wswm61yJZs10qPU6MoNx0luelwi173Hfea0oJns1oCBthGm1FeIb+ptgn7g1SFDOZC6V+YjQy7FS0dLmyTsqs8r8XqPG1WiyS+K7bKBZaWMOqe57FG6HFXuLjvmN0qoKHNKXPpud3+A4wS9jzoGSx96+vou57MCpAQlg+Vc+tfmI3sNBtaO12afQpvRQV8E0C9cXzs/UO65yDN5rGC7wih2BgLOGXiQxAE/PG0gQC8Lm+FH0VvqfxYkHLig1d7gQZuZiJfU3VIVaFqmVOnnTUEn99xIjId8kFuhDeqemmAaojBYLniNqsgzTZW7gj9eGbglMyAgiFTvNqXgRVtCsZZwzwzlV+r61XTGxk+/2jwL97wPl2Qn2nHweYO1ZREs2bXGQ4rHLbQvnbsnntKrfu2CyqHG93PJ37NCjgNlYIshxQE+99fAlf15FfhVMNqEaSgXpa6ruYCjTbMuqMsHKYlWnlrxMINtQGPzQI5Mx1WycXxxg+/c5Yfz36BioKxGfe7y6rw+ne/B/w8I24XADiyZz4Ajyhu7YhdAKMe1CaNVouA04Z4xOPLi9WtqXz8GAAc652cVtY2or41eNosu4fpdqtk9fpZZ+ozD4sd4V2IZx/RHXargNqGdr/K3GYusWA2KSc+AGCkVwgoUxJ5BpXkwGGzoKHNiX4PfoGV2+WditFaDcyNs3ZnHZpDXNTHKaleC8YM8ARuqqX3RRNJEFn8xYfR570oJ12xjob6fqUFGRhQlI1OlxhwMDNSqdFmteC0wZ7Kkwt+rfF7XU9cgV5GciW/jcBSJn/YvF9ualfZl3Wm8cKVIz0Bs898VRmwPo2ezpJll7Ay/fGwptlILqONd6MEGsiZIHh+0eaAM2j2vbdbLVJ11DcrduDCl39Eh9Md1FoE+KxPAPDkF78FTHtWDrTBKC3IQM/8DHS6RCzbFty1Fku0xO1d4w4D4BEEaouu+SwfnjcW5aajrFsWRBGoCFIjhH+/zSJIE4Nglls1pDGAq9ic4bBKblnl9dezGnesSEnx8er/DcfE8j545ZpjNfexWy1SkB8A/PvHbbLXfZXy9H1maUEmSgsy4HSLWL49NGsF/wCf4BUfK3cciukSycwMaLVYMKZ/N9mXOpTnnQ0snverH0EQBFx0bE8AwJfr/YUCw2WwEz1zWAkA4Ktfa/0XcdNY7C4Uxns/xygnesXd8u0HZTNMtUHn2N5dcNrgIgwsypbWe4klV4/qjUHFOWhoc+LzX6o199OTVXTSYV7hvWU/XG6RS580r71G6dM1E8W5aehwuXHrO6ukmhFqFU4ZvFj/cJWnPLva6rCdnMC/5SRfnNQvu+rxxbo9uiwVBVkO/OfWcun/QKXdjU6sPLWMPPdk9k/bdb0nVoga4rZvtyz07ZoJp1vE0q3+AoqPH2MwIXjLOz+rrjbM4+QmQidxdZ+Mxn1IlmbFw84EzStLtipqiBizYkWTlBQfBVkOPH7+MFnVSzXuOWOQ9Pfiyn2KGY3ntxFfGhMM3/y210BrffAPcGlBpmS5Of7pb4KabiMFL4jyMu2SuwoIzc945chS6e9DAYJpz/B+8Su2HkBTuxPb9jf7ddxGXSUnDuyGTIcVu+ta/VxyvkBIfccKxFUje+Pmk/ph5lXa4leNft2y0DM/Ax1ONybP+VnartYkQRDwr4kjsHDqyUizxS6inWGzWnDJcE/2z8Of/IoVGgJcykgMcNOO6pWP3HQb6ls78eGqnTGP+QA81/vBs4YAAL6t3IcvvdYztQqnjOP6dsGZh3uE6DtLq9D3gf+i/4Nf+K0T45vtWmCxCLh3vK9f+nRtte7zH96nAJeP8Hy/vtmo3QeF4mJkhRQXV+7zi3uJJwKdGzuHG95aiZnfbpGlTkuuLe6Nlx/n66tO+Ou3mL96t2atExfnnh7epwsyHVbsb+owXCiSxaPxa1UBwKQxfVGQ5cDv+5px7b+X+VxyBuN3oklKig+9HNO7C35/6iyU5KajpcOFxz79VaoKp7ZgVDDO8HY0H67ahc/WVuNP89cZWhOBf4AB4K7TD5Neu/GtlWHVEAkVp6JNrDMFgKwQ0rj4oNMDTdrio39hNsq6ZaHD5cbU99fglH8sxuOf/Srbhy8ypod0u1Uqpa10vUhuDhO+xFaLgGlnDZGi7PXCW3x+4jp4rSbFW4dzJmfxuer1pdisshqnnlm8zWrBteV9AQAPfbxeWl001md7/tE9cfPJnmDotyu2A+DrAalnocy4/Gi/5/Ph+etlrlle4AOe+g5f/PFEWC0Cvtm4F6f8YzEAfeLrVK87btaP2/Hx6l2q+xi1fAAeNx8bEK98fSn6PvBfvPTNZt3vjxaBzo13Vf59QSXOfuF7LPNmaLkkS7c8UJVl3gHAlPfX4IVF6ufs5CzEDpsFp3gDlOev1rYCquGzNMvbX5STjk8mj0Gmw4qdB1vxj688mS8U85HAWCwCJhzh6TTnrtiJY59YiC17G0OabZ00sBDH9e2C1k4X7nhvNd5ZWoVTn1mC1VX6Ao9YsBF78M47qgdG9/PFD+hdu8FMXIo2XTWqN64a1Rt/uWCYrOKrEf49aQSG9+mCW7wduRqCIOBc7+D9ldfq81bFDuzgMphcKqbSYIz3iqcv1u+RiTkzYz7C4baxA/y2meEKigalBZmY4BUgnS4R5770g1+sg8/CFPicpowbiKN65cHpFvGX/27Q9Z5o8IcxZbBZBKzYfggbqhukwlVabctwWPHAmYPRr1sWzj2qBwCg3enGv773uXnZbJr38w/tkYvJYz0uGDYB0PNs8uvUPDz/V9WZeiBrjRbpdis+unWMbNs/vtoUF4UQt+5rQvn0RXjzp+0Bxe2YAd1k5RKcbhGvf+8JzpVSbRXX5L9/PEEShQDw4jdbVKuNKgXkxcM9k4j5a3Zjy95G1KrU6FBDLeCUUVqQKWW+vPH9NuxrbA8awB1LSHzo4NryvrIMhSnvr0GDN8LZyOzSahGkwCaeif9eritiWvkAA8B7N46WZsPPfrVJcg1tqm3EnXNX440ftvkfyEQ6uSBYwFO+96kLj8A1o/uEPPM+dXAx/nPr8RjIrSaqxpWjevtte+mbLdLfRrJdGKcMLkKazYLf9zXjsn9W4Ka3Vsq+xLEe6DMcVnx7z1jZtjgYc3XzyjXDsfyh0zCyrABtnW48+NE62SxfbyVZm9WCB88aAqtFwKEW9l2MWLN1U5ybLsX0nPXC9/jPzx7rQqCm3XhSP3xzz1i8eOUxePayowAALy/eIhWNYgLBrlADd51+mBRrAejri9LtVszyVmltanfif+tr0NzulFlgQ/neAJ6lBWyKGzdj4aaQ6lmYyYerdmFPfRse/fRXyZqqVsPEbrVgwV0nYeMTZ2LR3ScDAL7+bS8+WLlTMwi3e14GNj85Af83uo+07YwZ3/mllHcqJmknDSxEUU4aDjZ3YNyz32HUU4vw0c/qligepaVZyS0n98dRpfnocLlx59zV0rMTD98NJSQ+dFDWLQvrHjsDr1zt8dGv392AW9/1+NyNKsry/l2lAjUnDOiGLIcVDW1OjPjLQvxp/rqAi5v5Yj58t00QBNzmnQFV/H4Agx/+EhOe/x5nzPgOn6ypxhOfb0DF1gM40NSOTSpm7nBRuoKiSfe8DFxb3gf5mXbc6VX881btwv+9sUxmATFi+cjLsEs+9RXbD+GrDbWY+sEasDl5PHyJy7plSYIzESnKScczlx6FLIcVG/Y04Mznv8P9H/6CvQ1thmKpRvXriqs5AapnpeNoMNHrEuLpGyCzjufCY3pieJ8uaHe6MfWDtZi7vArfVnoXpFRcEkEQ8MIVx0j/qwWrqnHKoCJpEvTH91bj8EcX4NRnluCP763G1n1NUvq6UfEhCALmTx6DI3rmSbV4Fm3ci3/9EDi1N9I4OCsBK3Sn9XzZrRak263oX5iNC4/xfMce+/RXqTK1mmgRBAFPXDAM3917ChxWC9wicOmrFbKF6ti9Ya4pm9UiXSPG1A/WBl1wzqmY7KnBLGI/bT2AT9d63DrxYBVUQuJDJ2k2KyYc0R13ny63XPyqY20GHkEQ8Pb1I/H11JPx9vUjMfsPI+GwWdDpEvHO0iqc9swSPPtVpepsQc3yAXjWE5lY7lPeysWqrnx9KYb/5WucMeM7PPH5Buk4ze1O/G/dHqzbVY+DzR14u2I7Zn67xdACUU6NNkWLP58/DD//6XTcdfphOHWwx4/6/eb9OPnvi6V9jDZt4vF9ZSXYv9+8H+8t3xnSsSLF9IuOwIkDu+HsI7urVmyNd0oLMvH8FcfAIngq9b6/cidGPrUIX3ljbfRe5/vOHCwtK949L7YVGxkjywpw3Zi+vv/7FkgThGAIgoD7zxwMq0XAD1v244GP1kmv5agUyOuS5cCfzvZYgP5x6ZG623jdCX2Rmy4/3qdrq3HaM0ukYGsjop0xrGcePrvjBDx41hA85A3AfXbhJjz53w2Y+O/lmPntFkncRCtGTa0WkJ5Te+bSo3Bs73y0dLhwm3eyGeia9O6aiQfP8hRO3La/WRb/wYQIP3G8hrOWMB74zy8B+1+tgFOeMw4v8bOwx1v8FxBB8TFz5kz07dsX6enpGDVqFJYvXx6pj4oqt586AP+780SpaBKrvWCE3HQ7BhRlQxAEHNe3AHNuGCUtFQ4AL3yzBQ9/sl4SIOxLqhVsBACPnXc4HjlnqGzbq9cci+LcNNm2N37YhtOfXYJXFm/FcU9+jVvf/RnnvvQDjn1iIR7+5Ff8fUElzpjxHZb+fgBtnS786/vf8eqSrZp1AdiXIZSOyizYbOQflx6FG08sk73msFkMD852qwXv3DAKl48olfLnGfHyJU6zWfH29aMMZ8zEE+OGFuOj28bIqs7OX2NsppadZsPyh07DPWcchhneNXXigUfPPRyL7xmL+ZPH4INbyg09gyPLCvDc5UdLVrbsNBv+MKYMpwxWr91yw4n9UPnEmThzmP4A5tx0OyqmnSbFZY1RVGTOclil5eZD5YYTyzBmQFe0dbrx+vfbsGTTPvx9QSVG/OVrnP3C9xj6yAJMeP57WVyIKIqmixI1l7bShaWGxSLgb5cchQzu3u04EDildtKYMrxwpcca9dK3WzDu2SXo+8B/safe40LjJ2npdis+uLkcJw7shtf+bziyHFYs23YQd72/BnOXV2HJJv+KpdLaLkHaf/upA2SrOMciGSEYghiBVr3//vu49tpr8eqrr2LUqFF47rnnMG/ePFRWVqKoKHDxo4aGBuTl5aG+vh65uYFTYWOJ0+XGx6t345je+bKVTENFFEW0drowb+UuPPbZr36rDZ53VA/JhDbnhlE4fkA3laN4gqsW/FqD+pZO3H/mYGw70Ixb31klrb5oswh+S3Tr4fAeubjiuFK4RY+q37qvCcN65uEVb0XAd64fJVuxNpa0drhw8zursKbqEJ688AgpkC9Unvt6E5772jOLeWDCYNxysr5ZLKGP1g4XahraMGXuaqz1BmhOv+gIqTBZqvLLrjo0t7tQHsIERy/1rZ34ZVcdThjQDb/sqseL32zBwOJsnH1Ed6maajjUtXTgjvdWSwXhtHDYPEsC7KlrQ066DdeW90HPLhnocIo4ZXBhWOniN7y5El//VovHzh2K7QdasOtQK56++AjZhC8Q327ci+tmrwAAjO5XgLk3lQd5B/DUF7/hNUUl2dx0G76/71TkZdpV37NwQy1ueWeVzH12XN8uOGVwEXLS7eiSaUdlTSNe/GYLThzYDW9fPypgG/Y2tGHkU4sAADMuPwoXHtMr4P5mYGT8joj4GDVqFI477ji89NJLAAC3243S0lLccccdeOCBBwK+N1HERyT5ZM1uTPtonbRAm5L3bxotq1gYDKfLje8378exvbvgYEsHHvv0VyzZtA/9C7Mw+7qRcIsiLIKA7nnpaOl04U8fr5eEjl7m3jRaVtI7HnC7Rd2LYwVCFEW8VbEDX/9Wi8fPOxz9CkPL4iEC09bpwuyftuOY0nxDzzcR3zhdbvy09QCO7dMFLreIfy7ZikMtnUizWbD09wNBl5dna1l1y06TlkHYfagVGQ5PbIZF8FgRWjtd6HC6YbUIaGpzwmYV0CXLgTvmrEZTuxMzrzrWcHo7z6odh1BakKFrQTZRFPHiN1vwwqLNGFCUjcfPOxyH98zTXFuKsei3Wtwzb60URK3FKYMKMeu6kUHbsbehDT9tPYAzh5VExT0bU/HR0dGBzMxMfPjhh7jggguk7RMnTkRdXR0++eQT2f7t7e1ob/dFBjc0NKC0tDSlxQcA7DzYgjd/2g7B+8XafqAFn62thtUiYPE9Y1FaEF7VykADsyiKqNh6ABW/H8C4IcXonp+OFxZtxje/7cX+5g50ON3Iy7Cjf2EWft/fjD5dszDnhlHICvLFIgiC4HG7RXyzcS827GlAl0w7CrLSsHLHQSyp3IeahjbNCVgoxJN1NhCdLjcEAPua2vHyt1uxeW8j9tS3wekSsdtbzXrS8X3x2HmHx7ahKsRUfFRXV6Nnz5746aefUF7uM0/dd999WLJkCZYtWybb/7HHHsPjjz/ud5xUFx9qHGzuQHO7M2zhQRAEkQg4XW4s23YQm2sb0eZ045dddahr6URxbjpEUcTv+5shCALaO13IdFhhtQho906OAE+hwr2N7eiW7cC8W8qRk67u8kgU9je1Y/v+ZhzeI89v1ex4wIj4iPlUddq0aZg6dar0P7N8EP4UZDlkFfUIgiCSGZvVs4jmGI0Yt1SjW3aa7liVeMd08dGtWzdYrVbU1srXGqmtrUVJif+CWmlpaUhLS46LSRAEQRBEcExPtXU4HBg+fDgWLVokbXO73Vi0aJHMDUMQBEEQRGoSEbfL1KlTMXHiRIwYMQIjR47Ec889h+bmZlx33XWR+DiCIAiCIBKIiIiPyy+/HPv27cMjjzyCmpoaHH300fjyyy9RXFwciY8jCIIgCCKBiEidj3CgOh8EQRAEkXgYGb9pbReCIAiCIKIKiQ+CIAiCIKIKiQ+CIAiCIKIKiQ+CIAiCIKIKiQ+CIAiCIKIKiQ+CIAiCIKIKiQ+CIAiCIKIKiQ+CIAiCIKIKiQ+CIAiCIKJKRMqrhwMruNrQ0BDjlhAEQRAEoRc2buspnB534qOxsREAUFpaGuOWEARBEARhlMbGRuTl5QXcJ+7WdnG73aiurkZOTg4EQTD12A0NDSgtLcXOnTtp3ZgIQtc5OtB1jh50raMDXefoEKnrLIoiGhsb0aNHD1gsgaM64s7yYbFY0KtXr4h+Rm5uLj3YUYCuc3Sg6xw96FpHB7rO0SES1zmYxYNBAacEQRAEQUQVEh8EQRAEQUSVlBIfaWlpePTRR5GWlhbrpiQ1dJ2jA13n6EHXOjrQdY4O8XCd4y7glCAIgiCI5CalLB8EQRAEQcQeEh8EQRAEQUQVEh8EQRAEQUQVEh8EQRAEQUSVlBEfM2fORN++fZGeno5Ro0Zh+fLlsW5SQjF9+nQcd9xxyMnJQVFRES644AJUVlbK9mlra8PkyZPRtWtXZGdn4+KLL0Ztba1sn6qqKpx99tnIzMxEUVER7r33XjidzmieSkLx9NNPQxAETJkyRdpG19k8du/ejWuuuQZdu3ZFRkYGjjjiCKxcuVJ6XRRFPPLII+jevTsyMjIwbtw4bN68WXaMgwcP4uqrr0Zubi7y8/Nx/fXXo6mpKdqnEre4XC48/PDDKCsrQ0ZGBvr3748nnnhCtv4HXWfjfPfddzj33HPRo0cPCIKA+fPny14365r+8ssvOPHEE5Geno7S0lL87W9/M+cExBRg7ty5osPhEP/973+Lv/76q3jjjTeK+fn5Ym1tbaybljCMHz9enDVrlrh+/XpxzZo14llnnSX27t1bbGpqkva55ZZbxNLSUnHRokXiypUrxdGjR4vHH3+89LrT6RSHDRsmjhs3Tly9erX4xRdfiN26dROnTZsWi1OKe5YvXy727dtXPPLII8U777xT2k7X2RwOHjwo9unTR5w0aZK4bNky8ffffxcXLFggbtmyRdrn6aefFvPy8sT58+eLa9euFc877zyxrKxMbG1tlfY588wzxaOOOkpcunSp+P3334sDBgwQr7zyylicUlzy5JNPil27dhU///xzcdu2beK8efPE7Oxs8fnnn5f2oetsnC+++EJ86KGHxI8++kgEIH788cey1824pvX19WJxcbF49dVXi+vXrxffe+89MSMjQ/znP/8ZdvtTQnyMHDlSnDx5svS/y+USe/ToIU6fPj2GrUps9u7dKwIQlyxZIoqiKNbV1Yl2u12cN2+etM9vv/0mAhArKipEUfR8WSwWi1hTUyPt88orr4i5ublie3t7dE8gzmlsbBQHDhwoLly4UDz55JMl8UHX2Tzuv/9+8YQTTtB83e12iyUlJeLf//53aVtdXZ2YlpYmvvfee6IoiuKGDRtEAOKKFSukff73v/+JgiCIu3fvjlzjE4izzz5b/MMf/iDbdtFFF4lXX321KIp0nc1AKT7MuqYvv/yy2KVLF1m/cf/994uDBg0Ku81J73bp6OjAqlWrMG7cOGmbxWLBuHHjUFFREcOWJTb19fUAgIKCAgDAqlWr0NnZKbvOgwcPRu/evaXrXFFRgSOOOALFxcXSPuPHj0dDQwN+/fXXKLY+/pk8eTLOPvts2fUE6DqbyaeffooRI0bg0ksvRVFREY455hi8/vrr0uvbtm1DTU2N7Frn5eVh1KhRsmudn5+PESNGSPuMGzcOFosFy5Yti97JxDHHH388Fi1ahE2bNgEA1q5dix9++AETJkwAQNc5Eph1TSsqKnDSSSfB4XBI+4wfPx6VlZU4dOhQWG2Mu4XlzGb//v1wuVyyjhgAiouLsXHjxhi1KrFxu92YMmUKxowZg2HDhgEAampq4HA4kJ+fL9u3uLgYNTU10j5q94G9RniYO3cufv75Z6xYscLvNbrO5vH777/jlVdewdSpU/Hggw9ixYoV+OMf/wiHw4GJEydK10rtWvLXuqioSPa6zWZDQUEBXWsvDzzwABoaGjB48GBYrVa4XC48+eSTuPrqqwGArnMEMOua1tTUoKyszO8Y7LUuXbqE3MakFx+E+UyePBnr16/HDz/8EOumJB07d+7EnXfeiYULFyI9PT3WzUlq3G43RowYgaeeegoAcMwxx2D9+vV49dVXMXHixBi3Lnn44IMP8O6772LOnDk4/PDDsWbNGkyZMgU9evSg65zCJL3bpVu3brBarX7ZALW1tSgpKYlRqxKX22+/HZ9//jm+/fZb9OrVS9peUlKCjo4O1NXVyfbnr3NJSYnqfWCvER63yt69e3HsscfCZrPBZrNhyZIleOGFF2Cz2VBcXEzX2SS6d++OoUOHyrYNGTIEVVVVAHzXKlDfUVJSgr1798pedzqdOHjwIF1rL/feey8eeOABXHHFFTjiiCPwf//3f7jrrrswffp0AHSdI4FZ1zSSfUnSiw+Hw4Hhw4dj0aJF0ja3241FixahvLw8hi1LLERRxO23346PP/4Y33zzjZ8pbvjw4bDb7bLrXFlZiaqqKuk6l5eXY926dbIHfuHChcjNzfUbBFKV0047DevWrcOaNWuknxEjRuDqq6+W/qbrbA5jxozxSxfftGkT+vTpAwAoKytDSUmJ7Fo3NDRg2bJlsmtdV1eHVatWSft88803cLvdGDVqVBTOIv5paWmBxSIfaqxWK9xuNwC6zpHArGtaXl6O7777Dp2dndI+CxcuxKBBg8JyuQBInVTbtLQ0cfbs2eKGDRvEm266SczPz5dlAxCBufXWW8W8vDxx8eLF4p49e6SflpYWaZ9bbrlF7N27t/jNN9+IK1euFMvLy8Xy8nLpdZYCesYZZ4hr1qwRv/zyS7GwsJBSQIPAZ7uIIl1ns1i+fLlos9nEJ598Uty8ebP47rvvipmZmeI777wj7fP000+L+fn54ieffCL+8ssv4vnnn6+arnjMMceIy5YtE3/44Qdx4MCBKZ0CqmTixIliz549pVTbjz76SOzWrZt43333SfvQdTZOY2OjuHr1anH16tUiAPHZZ58VV69eLe7YsUMURXOuaV1dnVhcXCz+3//9n7h+/Xpx7ty5YmZmJqXaGuHFF18Ue/fuLTocDnHkyJHi0qVLY92khAKA6s+sWbOkfVpbW8XbbrtN7NKli5iZmSleeOGF4p49e2TH2b59uzhhwgQxIyND7Natm3j33XeLnZ2dUT6bxEIpPug6m8dnn30mDhs2TExLSxMHDx4svvbaa7LX3W63+PDDD4vFxcViWlqaeNppp4mVlZWyfQ4cOCBeeeWVYnZ2tpibmyted911YmNjYzRPI65paGgQ77zzTrF3795ienq62K9fP/Ghhx6SpW/SdTbOt99+q9onT5w4URRF867p2rVrxRNOOEFMS0sTe/bsKT799NOmtF8QRa7MHEEQBEEQRIRJ+pgPgiAIgiDiCxIfBEEQBEFEFRIfBEEQBEFEFRIfBEEQBEFEFRIfBEEQBEFEFRIfBEEQBEFEFRIfBEEQBEFEFRIfBEEQBEFEFRIfBEFEjbFjx2LKlCmxbgZBEDGGxAdBEARBEFGFyqsTBBEVJk2ahDfffFO2bdu2bejbt29sGkQQRMwg8UEQRFSor6/HhAkTMGzYMPz5z38GABQWFsJqtca4ZQRBRBtbrBtAEERqkJeXB4fDgczMTJSUlMS6OQRBxBCK+SAIgiAIIqqQ+CAIgiAIIqqQ+CAIImo4HA64XK5YN4MgiBhD4oMgiKjRt29fLFu2DNu3b8f+/fvhdrtj3SSCIGIAiQ+CIKLGPffcA6vViqFDh6KwsBBVVVWxbhJBEDGAUm0JgiAIgogqZPkgCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKqkPggCIIgCCKq/D9S/ANqmVbHcAAAAABJRU5ErkJggg==", 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", "text/plain": [ "
" ] @@ -258,7 +258,11 @@ } ], "source": [ - "trivial_ep.plot(x='t', y = ['total_pop'], title='Total population over time')" + "trivial_ep.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='Total population over time', \n", + " kind='scatter',\n", + ")" ] }, { @@ -304,23 +308,23 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 31, "id": "3bc2f53d-94be-4fa8-916f-88f6e9eb57f2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 10, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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C4o16vR6nT59G+/btXVrqnoiIiOwnCALOnz+PmJgY+Pk5p0+n1QVFp0+fRmxsrLubQURERHY4efIkrrjiCqccu9UFRYaFGk+ePImwsDA3t4aIiIiUqKmpQWxsrNmCy1prdUGRYcgsLCyMQREREZGXcWbqCxOtiYiIiMCgiIiIiAgAgyIiIiIiAAyKiIiIiAAwKCIiIiICwKCIiIiICACDIiIiIiIADIqIiIiIADAoIiIiIgLAoIiIiIgIgIcERStWrEB8fDyCg4ORnJyMnJwcm/s2NTXhpZdeQvfu3REcHIyBAwdi27ZtLmwt2augvBbb88pQeLbO3U0hIiKy4va1zzZt2oSMjAysXLkSycnJWLZsGSZMmIC8vDx06tTJav/nn38eH374Id59911cddVV+Prrr3HHHXcgOzsbgwcPdsMZkEFBeS2Kz9UjvmMoEqJCjdur6hsxZ8NB7MwvN24b3TMay6cORnhIgDuaSkREZEUnCILgzgYkJycjKSkJ//znPwEAer0esbGxeOyxx/DMM89Y7R8TE4PnnnsOs2bNMm7705/+hLZt2+LDDz+Ufb2amhqEh4ejurqaC8JqRC7oSVuVg93Hz6LF5KPmr9NhRI8orJs+zOxYtgIrIiJq3Vxx/3ZrT1FjYyP27duHefPmGbf5+flh3Lhx2LNnj+hzGhoaEBwcbLatbdu22LVrl1PbSrbN2XAQu4+fNdu2+/hZPLbhAF6c2McsWDJoEQTszC9H4dk6JESFsjeJiIjczq05RWfPnkVLSws6d+5str1z584oKSkRfc6ECROwdOlS5OfnQ6/X49tvv8WWLVtw5swZ0f0bGhpQU1Nj9uPrnJW7I3bcgvJa7MwvN+sFAi4HPXsLz0kes6ji0rGkAisiIiJXcHtOkVpvv/02Zs6ciauuugo6nQ7du3dHeno6Vq9eLbr/okWLsHDhQhe30nVMh5siQwJEe1ueGN8T5+qbJIekpIatpHpxis/Vy7RQenQ2vmOoMbCyZNmbJNdOIiIiR7g1KIqKioK/vz9KS0vNtpeWlqJLly6iz4mOjsZnn32GixcvoqKiAjExMXjmmWeQmJgouv+8efOQkZFh/L2mpgaxsbHanYQbFJTX4pfTNVibXYTc4krj9siQAFTXN5ntuzO/3CzgGBoXifSUePTpFg5BEHDkTA3WZRcht+jycZLiIzEtJR59Y8KREBUqOzwm5drEKIzuGW0zpyghKhTb88okj1FUUWcz4OPwGhERacWtQVFgYCCGDBmCzMxMTJo0CcClROvMzEzMnj1b8rnBwcHo1q0bmpqa8Mknn2Dy5Mmi+wUFBSEoKEjrpruFWI+NqUqLgEjMj8WV+NEkkBKTW1RpDJKS4iPNAiYDQy+OTqeTDXr+Pqkfbl+xy6x9YW3b4JVJ/QAAcR1CJNsT31E6MLNM1iYiIrKH2+sUZWRk4N1338XatWtx9OhRPPLII6irq0N6ejoAIC0tzSwRe+/evdiyZQsKCgrw/fff48Ybb4Rer8dTTz3lrlNwGbHAwNn2yQRQRRV1WD51MEb0iDLbPqJHFJZPvVQi4fnPDqPmQrPZ4zUXmvHcZ4cBAInR7TC6ZzT8dTqzffz/CLiEPwIwW3lLrHtERERacHtO0ZQpU1BeXo758+ejpKQEgwYNwrZt24zJ1ydOnICf3+XY7eLFi3j++edRUFCAdu3a4eabb8YHH3yAiIgIN52B8xWU12JvYYXNHiJn0ssUbIjvGApBIm9Iab7QE+N74VxdAw6fvpwIbwis9p+UDsz2FlQwv4iIiBzm9jpFruZNdYrkhstcyQ+A3uR30zpDUnWI0kfGI31Nrs3jLr93MDbn/m52jv26heHVO/pjwBURAC4FVtct2SHZPuYXERH5Nlfcv90+fEa2qR0u89ddSrZ2hr4x5h9AQy+O3JR8f/MRMSvrsouszvGX0zV4+YtfjL/bGl4zxen7RETkKLcPn5E4W8NOUkb0uNRbcq6+EUUVdegYEojF3/yqSU/TodM1xllpYcFt0CIA5+obZafktwiwmYg9+MoI0SRuvXAp2fvud7Lx3rQkhIcEYPnUwXhswwGb5yI2fZ+IiEgNBkUeSr7+zyWW0+cBIDwkwPj/66YPQ+HZOhw5XX1pCr9IEAIASXGRmDw0Fv/58aTZNH9T+4srcbys1mwW2dC4SMn2xXcMFQ1oRvSIwpShV0jOhNtXXGmcXRYeEoB104dhQ84JzNtyyOZziioYFBERkX0YFHkouWnqi+7sj2sTO0oGAKaFDm8dEINbB8Sg8GwdiirqEN/x0vMM/284zt1Jsdj5aznSVudYHa9FsJ72f+BEFSJDAlBzodnmlHzgcnBm+noF5bWS56gHrHp/khM6SD7HcF5ERERqMSjyUIY8GlsJzFOHXWnzuVIVqBOizCtBiwVVlvlBUloEAZX1TVb1jK6OaY+5E3qZ7Wv52oZz3HW8XHKWm2nvj9x1YS8RERHZi4nWHkyu/o8tjq4j1sGOZO1Hx/bA1lkp6PdHQvbhUzWY+M/dSFuVY1Vl29TyqYMxRMEQnOVz7LkuREREUthT5MEMeTSWw05S1KwjZsuSb/JVtzW+YygWbD2Co2fOm22XqzodHhKAzQ+n4O53srGvuFJ02r9le5VeF66TRkREajAo8gKWw05S5BK05RKR7Zn1lhQXiRMVdYqCMVuBynvTkkSTsZ8Y3xPb88pEAxtb10Vq+JB1jIiIyBYGRT5GyTpiUpTOejN1vqEZ0yQKNALAf348gR9N1lQDLgcqFXUNKD5Xj4W39wVwKXDrEBKAJd/k4/YV2Vb7ywU2XCeNiIjswaDIxziaiCwXVIk5VnJedp93sgqstu3ML8foN7ej+oL5FP/0lHj83/+OY/+JKrP9lQQ2WgwfEhFR68REax/kSCKykurRWjINiADgx+JKzNpwALnFlTarZO/8tRzb88pEF4JVMnxIREQkhj1FPsQ0X0dtgrYpsWKLwxM74mJTCw6crHJCy9UxraFkOaQm19P1f/87jmtiI5lbREREVrggrA/QOrHYEFy18dOhWS8Yg6rteWWSi7u6g+nCtAZiC9RK7U9ERJ6PC8KSIo7WJQIuBUJf/HQad7+TjeuW7ED6mlw8sCoHa3YVoUNIIADl+UZ+APp3c03AaZorZLB86mBcExeheH8iIiKAQZHXk1ulXu7mX1XfiLRVObhuyQ7M/iOXx5RlcNWvWxj8ZNKN9AAOnapBZEiAyz5gewsqjP8fHhKAR8f2kNyfuUVERGSJQZGXczSxWKyXyZQhuDL0IB0+VWO1JMfontEYHBtuFSxV1zdJDt+ldO+I4YkdbT4uF3yZembLIbPq2Y6WJiAiotaHidZezpGbv5pCjfssepD8APSJCcPye6+BIAi4bskOq+focWkB2ZX3X4PK+iboAHSLbGuWpwQAhWfrcOR0NdZmF5nVMRrZIxpNLXrkFJ5TtB6b6ZR9rpFGRERqsafIy520o9iigZpCjXqR3w+frlF0nLmbf8K8LYfwzJZDVnlKwKXK1CN7RKFtgHWM/safBliVF7DF0Kv1/R+BHtdIIyIiNTj7zEuJzTgTE9cxBMunDsaAKyKsHisorxXt4THlp4PkCvZr0pMQ1yFE9jimlM4YM91v56/lZlPx5ZjOvrO3NAEREXkOzj4jm+RygQyKK+ptrlavpFCjkhXsE6PboV+M8g+oZRK4kmRxJcNnpkwTxBOiQjG2dycGREREJIlBkQcrKK8VrdxsK4iQsiu/XHSKvtgQU1J8JP5572Bsn5uKzQ+niAZO/jodRveMNgYar9zRX3FbDAxJ4EqSxdUuP6J26r2ta01ERK0HE609kFwxRnsWbdUDxiBBEARj5WtBEJA+Mh4zRydYJUAbiFW4tszNGRgbgdE9o7HreLnkcJspQ3VpJcniCVGhoonTcj7/6RQmDuxms5dI68KXRETkvZhT5IHk8mt25JXJrkpvS7sgf9Q2tIg+ZhkMmC4bkhAVapabYxpYGQKO6vomq+ApMiQANRea0CLyKTM9p6n//gF7TGoNGQxP7IgNf7nWePwZ63LNZqj17xaGQ6dqZM/bVqAjd62JiMgzuOL+zZ4iD6NklXfLmWBq2AqIAGDX8XLMWJeLd9OG2uw9iQwJkOxZsVxzrUNIoFUgI3ZOttKaDNsNPTqmx0mKi8R705Lw2IYDsj1Iu/LLMWNtLjY/kmLcpuRaMw+JiKj1YE6Rh3FGfo1SegHILarE6De2Y/dx82DBkLisZEmRhKhQxHUIQVFFHc7VN8pWl95+rBTZv1n3EgFA9m8VKDxbJ/q6+09U4bENB7B86mAMS+ggfW4AcosrcffKbGPCuaOFL4mIyLewp8iDVNU3YsX/jkvuI5Vf4wdgZM9ozB3fC49t2I/icxfsakfNxWarbYbeEzGmPStiPUlDZWawbcg9Ifn4//vplGSPzrn6RgT4+8mWDwAuFaF8bMMBvDixD0qqL0ruy6rXREStC3uKPMicDQdx4ESV6GOWs73Eekf0AJr1esR1DMWadNfnwxRViPfoHDhRhbBg2/F3fql0j8zSb/MlH1+bXYSd+coSvPXCpYTz65bswLwthyT3XbD1iFUZAyIi8l0MijyE3DT70CB/vDKpn/H38JAAY++Iqb0F5/DYhgOKahBpbek3eTbrDYn1Pmnl/ewipxzXcliQiIh8G4MiDyGX31J7sRnPfXbY+LshiLLsHTEdyhKrQeSIyJAADE/saDPQOnJafhaYN1Fb64iIiLwbgyIPIZc8bVpnCFCWJGyYDbZ9bip6dmoHNX1G/iKfjOr6Juh0wDVxEeJtlBm+SoqLtFkEMtKDawIx4ZqIqHVgUOQhDMNdlsNhlgw3aCUFD4FLydtPffwT8stqobQgVVhwG7SIzPvX49JssNhI6de2/FAZAp/3piXZXKD181kjPTYwYsI1EVHrwNlnHmT51ME2a/oYGG7QhiDKVuFBQ0L2nA0Hsa/Y9vEsJcVF4sGUeMySyKXZcuCU5DGGxEUi1+Q1DYGPWB0jQzvDQwJwYP54fJ9fjv0nKnHNlZF4d2eh6grWWkuKi2StIiKiVoJBkQcJDwnA5odTcPc72dhXXGlWpNEy2AHkl9+wVZzQ0gfThxmX+IgMCcCMtT/afQ6RIQHY/EiK5Mr0CVHm2wrKa7G3sAKADtcmdsSontEAgAHdIjB9bS5+VBHUae3BlHi3vTYREbmWRwRFK1aswJtvvomSkhIMHDgQy5cvx7BhtqeUL1u2DO+88w5OnDiBqKgo3HXXXVi0aBGCg4Nd2GrbLJfHUMtQpVlqrTEAkj0vVfWNmLV+v+xrRYYEYEC3COPyF2mrcmyWBVCisr7JWAk6ISrUuNCq2LWoqm/Eo+v3WxVuHJ7YEa//aQCe/+ywWwMi4NLMtpE9o7kOGhFRK+D2tc82bdqEtLQ0rFy5EsnJyVi2bBk2b96MvLw8dOrUyWr/jz76CH/+85+xevVqpKSk4Ndff8WDDz6Ie+65B0uXLpV9PWeunaL14qJSvS1y0lblKOol8tcBI3pEY930YSgor8V1S3aobqelfjFh+L/7rsHznx2RvBZSbby0ZlqzW4fOAK6DRkTkKVyx9pnbE62XLl2KmTNnIj09HX369MHKlSsREhKC1atXi+6fnZ2NESNG4N5770V8fDzGjx+PqVOnIicnx8Utt/bIh/utbvI788vx8If7FD3f0KtimGGWEBWKsb07qQ6IlA6bAUCLcHlWm9yMNqV+OV2D21fsllwOZEdemWQbK+ubFAVEf7omxrHGyuC0fCKi1sOtQVFjYyP27duHcePGGbf5+flh3Lhx2LNnj+hzUlJSsG/fPmMQVFBQgK+++go333yz6P4NDQ2oqakx+3GGgvJa0VXeAWBPQYXkTbWqvhFpq3Jw3ZIdSF+Ti7GLs5C2KsdmNeUdeWV4O/NXfC8SVBSU1+I/+06qbv/a7CL4a1TnUQ/xoMYQYNy9MhvT1uRq8lo//+6a2kiPbdjP6tZERD7OrTlFZ8+eRUtLCzp37my2vXPnzjh27Jjoc+69916cPXsWI0eOhCAIaG5uxsMPP4xnn31WdP9FixZh4cKFmrfd0t7Cc5KP/1BQYbPHR2qRVdNhm+KKOkxasRuVJjfnyJAAfD5rJNq3bWM1dKfG+9lFTqsMbUnNbDg5+WW1mh1Lyi+na4xrpjmSL0ZERJ7L7cNnamVlZeHVV1/F//3f/2H//v3YsmULvvzyS7z88sui+8+bNw/V1dXGn5Mn1feiKCM91GOrE8bW8h5iwzaWARFwqUdm4opdooGVp1KyRpkabQOslzvRmumaaUp684iIyPu4tacoKioK/v7+KC0tNdteWlqKLl26iD7nhRdewAMPPIAZM2YAAPr374+6ujr85S9/wXPPPQc/P/M4LygoCEFBQc45ARPJCR2lH08Uf1xJZWpBEPDFz2esAiKDyvomu3uIfMGFJr1bonux3jwiIvJebu0pCgwMxJAhQ5CZmWncptfrkZmZieHDh4s+p76+3irw8ff3BwC4cyJdYnQ7hLcVn2EW3jbA5lCLXGXq//vfcVy3ZAeWfvurw230ZSIFuJ2OSdhERL7F7cNnGRkZePfdd7F27VocPXoUjzzyCOrq6pCeng4ASEtLw7x584z733bbbXjnnXewceNGFBYW4ttvv8ULL7yA2267zRgcuUNBeS2qL4j35FRfaLJ547S1mr2/TofIkADsd6BmELkG10YjIvINbi/eOGXKFJSXl2P+/PkoKSnBoEGDsG3bNmPy9YkTJ8x6hp5//nnodDo8//zzOHXqFKKjo3HbbbfhlVdecdcpAFA2DGart0isMvU1cRGSy320RmHBbVBzsdndzbDCtdGIiHyD24s3upqzij/JFT7cPjdVdraSabHGooo6pGs0bd1RPTuH4reyOs0TpO3Rv1sYDp1yzTR8JcKC2+D7p65jxWsiIidrFcUbfYXUMNjontGKpm8nRIUirkMIiirqNKsZ5Ah/HZAUH4nHr+uFIVdGurs5AICHR3dHWLDbOziNai42I3Xxds5CIyLyAewp0lB1fZPVMJjSZT7ElgiJDAlAdX2TWRKxH1yXVBzRNgBVJnlSSfGRmJYSj74x4Viw9YjVCvb+Oh0C/HW42Oy8Fi64tQ+GxEXi/lV7PWoobVBsBD6bNcLdzSAi8lmu6CliUOQE9qxZlrYqB7vyy60CoHYWeTSje0ajWa/H3oJzsstg6HSAlu+u6TpgtgLAh0Yn4r5Ve7V7URuGJ3ZE9YUm/HLGc4bSlAyREhGRfVxx//accQgfkhAVCkEQjLOS5G6UB09UitYZ0uPS8Ez/bmF4aEx39I0JR0JUqGhAIkbrcNd0CnpCVCjWTR9mDAD9dTq0CAJiIttidM9o7Dpe7tQcpL0FFRgSF+lROUZSVcuJiMjzMSjS2E8nK/Hcp4dx+PTlG7XUEFpVfSPul+lZOXK6Bv/J/R3rpl9a/DQ8JMAsICmpvoh5Ww5peyISTGfSRYYEYMHWIrMAbXhiR1yb2BHZv4mvBacFPYDc4koMjg1HeNsAm+UQXMkD0sCIiMgBTLTWiGFR19tXZJsFRID56vCWZqz9EbUNLZLH1pusZG8qISoUY3t3QnJCB8car5K/TofteWUoPFsnurxITuE5NDbrsejO/njihp5ObcvB36sRExGM/t2c05Wqhq2q5URE5B3YU6SRORsOYtdx8eEsy2Eng4LyWvyoYnFUW7WODDPfLBOf/XRASKA/6htaNEnO9sOlXqq01TmS+7UIAn4srlR1bvYSBODomfMAgMFXhONisx5HS847/XUtpXTvyKEzIiIvx54iDRgWdZXLobGsfCxX8NGSvw7GHhpLy6cOxogeUWbb9AJQa2dAdFWX9kjpbt7zER7iGcNUthz4vdotAVFSXCTeuW+Iy1+XiIi0xZ4iDSgNbiwrH8ute2YpbfXlYo79YsLw6h39MSA2AoB5ntFjH+3HL6drzIIhHQA1ec+Th8Zi7FWdAFxKIP79XB1WZBWoam9rkVtciRlrc/HetCQWcSQi8mKckq8BuWrWOgCjekabraYuVpfIHpZJ3HJtUSsyJACVLEyoSGRIALLmjmVgRETkBKxo7SVsVbM2EAA0tejNqh6LJSjbY9fxcrMkbrVDcnIYEClXWd+EGes8Y2kWIiJSj0GRRsRyekztLagwBi878sqwM79ctviiEpYz09QOyZG2cosqRXO+iIjI8zEo0oghp8fW1HA9LgUvd7+TjWlOWOjVkMRt6LXykyma0zbA9956T1gvDgAe+2g/10IjIvJCvndndKOC8lrZ6sr7nDRN3TSJe/nUwRgSJ72A64UmV62g5hrtgvzRYmfHm59O238IR07X2KxLRUREnotBkYaU5PNoHYr46S4lW5vWyAkPCcDmh1OQFBfpc29wSveOGG5RJDEpLhKv/WmA3cfUC9bvS7sgf7uPJ0C82CYREXk2TsnXkDvyeUb2uDT7TMx705IUrZGmRq9Oofi1zPk3+6S4SDyYEo8+3cIBwGqBXctFdwvKax1+TT8d0CcmDMunXoOEqFAUnq3DL6eqMffjn+zqWXtsw36sn34tZ6MREXkJBkUaOqnxzC8lZo5OEL3pFpTXovhcPRbe3hcANFsjbc64XvhP7u9W1bNt6dftUj2lxV//KhmchQW3wYczknHkdA3Onm9AdPsg9OkWbgyCLKtFJ0SFmm2zWdUbwLXdO6KxWS9bYVsvAIdNhj8Nr3FFhxDcvmK37LlaOnyqBo+s34ePZl6r+rlEROR6DIo0oFXNIXs8sCrHrFaRWFsMj1d0aHD49d7+Lh9L7h4IAKLnO7pnNOZO6IWKukaznp0nxveUvD41F5uxYOthHDhZbbZ98JUReP/BYYp6W5ZPHYyHP9yHPQWXF6I19O+smpaE+1f9IJvzBVivdj8wNgJJ8ZHILVKfD5b9W4XV8i5EROSZWLxRA2mrchT3nDiDaXFIsbb463QY0SPK+Piu/HKHc5tMg582fjo06wWzIMjS9rwypNs5605NUcS0VTnYddx8yRXD+T8xviduX5Gt6DVH94zGE+N74lx9E+I7hqJDSCCGv/Yd6hvVX7kFt/VB+ogE1c8jIqLLXFG8kT1FDjKse6bGa3f2hwA4PJRlYEjs/e+hM6JtMV2QdvnUwZi+NtfhxVoNhSdNq3RLcSTfqrK+CTPW5mLzIymS+9l6Lwznf1P/Lopfc2d+uVVv26zUnnjzmzzlDf/D+7uLGBQREXkBX5uc5HL2VJBOTuyI5IQOmrdlwdbDko8fPl2NxzYc0GT1ekOg8b3CgNCQ82Ov3OJKbMw5YTajq6C81myBXPn3wv6evO/zy7H14O92Pbf4XD1nohEReQH2FDlITQ+IYRgnISoUG3KKNW9LWW2j5OOrvy/EgZNVVtuv7tIez95yNV7fduzSQrIqYgfLnCZbCsprMTnpCpy/2GTVhkFXRODg79btsvTMHz1rKd07QhBgljtkGO6S0jcmXDQZWwkBcGjW3S+nqplXRETk4RgUOcjWrCd/HRDW1nwx1RE9okymz7uu/LK/TofBV0bY7CE6WnIeV0SGYP30azFjXa7qhOJd+eW4770fsPzea6xu/D+drMRznx7G4dOXE5yT4iJx84CuCA7wx7WJHZEQFYq0VTmKhyGzf6uw2rb7eDkOnaqSfN7ir3/F8qmDNS9ToMS7uwpxy8AYl74mERGpw6BIA2I32hF/1A86V99oVWMHgFOGz2wZ0SMKqb2jJIfNth8rRVbeWbtmWOkBHD5dg7GLs4y9RgIEmzPy9p+oQtvANmb5SGIzx9RoEeQXr92ZX45z9Y1YN30YCs/W4bEN+1X3jNnr4MkqzkIjIvJwDIo0YFj3zLKgoOExd90IH0yJx7SU+D+G605I7rsh5yR+06AA4u7jZ41LXOw6Lt4bY5r4bXqdNvzlWvz30Bm8/MURnK52vHyAmKKKOmP9ofXTr3Vpr9H2Y2VIGMmEayIiT8WgSEOWBQWlfPHzaSe3Bng/uwgF5ZdmnMWEB0vum1/meEAEXA54lDAEKIB4rae2ATpcaNK2G8d0jTjTYPaHgrOoqG1Ex3ZB+GBPMX45I1/PSK0NOSfwZwZFREQei0GRixVX1GHSit2yQz1a2X28HKmLt7vs9dQwDVDmbDhonOZvoHVABAALth4xSwqvqm/Egq1HXNJblF9WyyE0IiIPxin5LubKgAhQlmvjan4wX8R2R14ZduaXu6T4penwHiAejDlTUQWn5hMReSr2FLnQjrwyjwtQtGYoOwDA5tT3kT2j8cT4Xvjip9NYm12EXA3qJillGN5b/r98QMVQn1Y6hga69PWIiEg5BkVOZliY1V8HfHrwlLubo9rC2/pgwf/7RfH+l5bT6IXfz9XjQmOzWcDTr1sY5t14Nf61s8CuBVa1tOSbX1Xt76eDJrPUXvvvMS4QS0TkoRgUaaigvBZ7CysA6NCna3ss+SbfLYvEasEPl3p0po1IQOaxckUFDxfe1geZx8rNAp6k+EhMS4lH35hwYz0iVw5XaWVInH0LwlriArFERJ6LQZEGquob8ej6/aJFBb3VNXGRmDL0CuN6aUqmrov1KO0vrkLbgN+xbnqM6nXiwtu2QfWFZtVt19rc8b1wy4AYLNh6xGqxWXtkcWo+EZFH0gmCm5Z2dxNnrLKrphqzpxrdMxpzx/dCcWU91mUXmfWKGAoy/vR7JdJW27fS/fa5qSiqqEP6GmXP/2D6MIzqGf3HdPkK/CvrOIrOXbDrtbWS0r0jLjQ248DJaoeO07NTKL7NSNWmUURErYQz7t+WPGL22YoVKxAfH4/g4GAkJycjJyfH5r6pqanQ6XRWP7fccosLW3yZ2t4PT9OvWxg+nz0C66YPw4DYCGzO/R37i6vM9jHM2BrdqxNG94yGv079EiVFFXWK1onz1+kwumc0Rv2xeGxCVCimDrsSW2ePQqTI2mp+OlhtT4qPxPDEjna1U8regnNoHxyIpLhIh/7h5JfVcYFYIiIP5PagaNOmTcjIyMCCBQuwf/9+DBw4EBMmTEBZWZno/lu2bMGZM2eMP4cPH4a/vz/uvvtuF7f8EvmV2T3Xa3f2xxePjcKAKyIAXA7wLHOHTCtQL5862Di7TI34jqHGdeKkghXz9eEuCw8JQNbcsUiKjzTbPrJHNLLmjsX2ualYk56E7XNTsfnhFKy8f4hVO8WCKjUM1+GFW/tg5B9Bm0FEW3XH5tR8IiLP4/acoqVLl2LmzJlIT08HAKxcuRJffvklVq9ejWeeecZq/w4dzNcM27hxI0JCQtwWFB353bGhFHdKTuxo9rtcgGeoQL1u+jDs/LVM0VCaYYq+IbFYLD/JMhnblvCQAGx+OEXRcipiS690CAkUXV9tWHwHAAJyFCZSV5isn2bajsKzdUhbtRcnK+WH+UwLVxIRkWdwa1DU2NiIffv2Yd68ecZtfn5+GDduHPbs2aPoGKtWrcI999yD0FDxm0xDQwMaGi6vo1VTo+3yDcfParM8hiv56y4tWGsZgMgNb5neyA1DaXKz0ix7fqTWiVNKzXIqlvtu+Mu1xjwlHS4FhobHC8/WYW9BBcprGySn7Buug+mxDZWxlQREAPB7ZT1noBEReRi3BkVnz55FS0sLOnfubLa9c+fOOHbsmOzzc3JycPjwYaxatcrmPosWLcLChQsdbqstwxM64rMDzl/HTEsjekSLDlEZhrcsZ1gZensEQcD2vDLEdwyFIAiYnHQFLjQ1WyVlz53QCxV1jZIBj5rARmu2Xtt0e25hpVXAZ9nrZUptZezVuwqMeVNEROQZ3D585ohVq1ahf//+GDZsmM195s2bh4yMDOPvNTU1iI2N1awNSQkd5HfyIA+mxGFaSoJx7S9TVfWNaGrRW005HxIXgaYWPa5bskP0mElxkXgwJR59ukkPf3kTsWE+W/lO9iTb7z9R5WgTiYhIY24NiqKiouDv74/S0lKz7aWlpejSpYvkc+vq6rBx40a89NJLkvsFBQUhKCjI4bba4m2J1u9nF+P97GLjNHvT4GjOhoPIKTxntr8fgGMl51F70Xa9oP0nqtA28HesGxjjrGa7nJphPns+A9UXmlnEkYjIw7h19llgYCCGDBmCzMxM4za9Xo/MzEwMHz5c8rmbN29GQ0MD7r//fmc3U5KSaeaeyHJhVFszz/QAai42Qy9xLNPZab4mISoUY3t3kgxe7P0McAYaEZFncfuU/IyMDLz77rtYu3Ytjh49ikceeQR1dXXG2WhpaWlmidgGq1atwqRJk9CxY0erx1xJyTRzT2QZyGjR49Vab/L2fgbO1TbI70RERC7j9qBoypQpWLx4MebPn49Bgwbh4MGD2LZtmzH5+sSJEzhz5ozZc/Ly8rBr1y5Mnz7dHU22Ym/tHk9gCGS06PFqzdPM7fkMPP/ZYSe1hoiI7MFlPjRSVd+ImWt/NFsV3htsn5tqHBoyLNYqt/CrJcOsrHXTbSe8txaFZ+vw+U+n8Na3+Yr2NyxnQkRE0lrNMh++YM6Gg143oyjSouChvT1etmZl+aKC8lpszyuzmT+VEBWK2wYoTzjPPCpeuZ2IiFzPq6fkewpnrH+WFBeJZr2AAyerND2uqcr6JrMZUJYzrv5v+3HsL65Ei0XHUUigP5ZOHoigAH+7ii96o6r6RszZcNDsfRabwQdcyjEaGheJHxX0Gka1C9S8rUREZB/2FGlAy2n5s8d2v7R+1yMpmJx0hWbHtUUsOdow4+q9tCSEiazpVd/Ygoc/3I81u4rQIaR13NTFijNazuAzlZ4Sr+i4t6joVSIiIudiUKQBLafldwgNQmRIANJW5WDeFulE3OA2js94a+Nn+xgVdQ2orG+y+fiu/HKbQYEvUbJQrqWrY5SNd5+/YPv6EhGRazEo0oBhSrYWF3NtdpHiJSMuNjueI99sWb7ahFwPmB7w2fpEppQslGvJ8JmQ88j6fXa3i4iItMWgSANV9Y1o1uslCxwqVXyuXrRXwlmkptEr7QHz9fpEahbKNbV86mCEBftLPvdU1UWfDyqJiLwFgyINPLp+P7J/q7DaHi6Sj+Mp/HU6jO4ZLZkkbewBkxml8/X6RLaKM8pdw/CQADx3cx/Z4/t6UElE5C0YFDmooLxWNCACgOoLTege7ZkBg5Jp9AXltZicdAWGxEWKPq4ksPJ2hin4cyf0sipXoOQaThl2JeQyv3w9qCQi8hacku+gvYXiAZHBjX07Y0VWgeLjXd2lPUpqLkomODtKrmCg2PTz7tGhEAAUlF/u1fDl+kS2puB/PmsEKuobVZUiGHxlhM0aVpa1ooiIyH0YFDlMuh/gm19KMbpntOJK0UEB/qhx0owkQ+VpuQrKYonev/0RDCXFReLBlHj06Rbu0zdzW1PwAaiq3F1QXitZ1LOyvgnZx88ixUuXiSEi8iUcPnNQckIHycfzy+owd7z10IuYtgF+OHiyyqpYor38LeK1q2PaY+6EXpLPsTX93GBfcSU2/fi7TwdE9kzBt0VJDau/fPCj6jYSEZH2GBQ5KDG6Ha7u2l5ynxMKizteaNJi/tplLQKw5K4B6NmpHQDg8KkaTPznbtz6j+/xs41K2ZyGb98UfFuUzOCrbWjB9xpXRCciIvUYFGngtTv7Sz6+NrtIUd0hZ3jyk5+RX1Zrtu3w6RpMXLEbaatyUG2Ru8Rp+PZPwXdE9m/u+XwQEdFlDIo00D5Yeup9bnGlqrpDWr4pErUZseu4dUVqTsO3fwq+GKVLwOzKZ1BERORuDIo0oOXaZwBsToHXml4QHwpbPnUwRvYQT8ZuDdPwgUvXwJ4p+JaU9rwdOlXj00OSRETegLPPNKDl2md+OmDzIynGlerb+OnQrBdw6PdqLP32V81ex1RRRZ1ZkBMeEoB104fh55NVePbTQzh8usb4mC9PwzdluAaG90HNFHxTidHtkBQfidyiStl9Ld8HIiJyLQZFGkiMbofIkADR2kKRIZeG1pTWHdILwPf55Rj1R29MVX0jZq77UfamGtQGaGhW33bA9lDYgNgIfDFnlMOBgTdLiHL8nN9LS0LyK9/gYov0fr48JElE5A04fKaBgvJam0FPZX2T6kKM+09cCoCq6hsxdnGWol4GewIiJUNhBeW1rTYg0kp4SADuGBIru9/vldoOwxIRkTrsKdKA1jlFAX6XYtUZa390amVrqaEwWxWdl08djPAQz13TzVMFt5FeGBYAMo+WyhbWJCIi52FPkQbayC1upVKTXo+C8lr8WCzfQ2SPq7q0x+ezRmDd9GE2Axyxis5is9VImV5d2snuU3vRzvFPIiLSBIMiDczZeNDmY6N7RotO75ZyzZWRmvc+mTpWch6Lv7GdtG2rorNhtpqtwo9kW3JCR9l9pMonEBGR8zEoctCOvDLJIa57h8Xi75P6IaytspHKyJAA9O8WjhX/O65VE0VJVaWWC8ie/fSQM5rk0xKj2+GKyLaS+8REBLuoNUREJIZBkYMO/l4l+Xhe2Xk8/9lh1FyQHxqJDAnA57NG4tH1+502dGbKVlVquRIDh0+zpk5BeS2255Wpug4r7r1G8vEdeVzqg4jInZho7aAu7aW/3bfR6cySlaX07xaBc/UNyP6tQoumyWpjo2y1YT23o2fO23xua62p40gCevtg6X9uh/4INlvjdSUi8gTsKXJQp3DpoKhZxfIeu4+fxdzNPyvePzRQekaTv0waU7NEEktwG+mPRmutqSOWgL77+FmzBHRbvUh7C+WD3S9+Pq1NQ4mISDX2FDlIbqhJrifJVIsgWC3eKqWusQUfTB+G6gtNWJtdZFbPKCk+Eo9f3wv3rdpr8/m2ApuC8locOFlt83lJcZGtsjfDkIBuqUUQsDO/HD+drMSSb/IlepHkk+3P1TZq2WQiIlKBQZGDEqPbIbxtAKovWCdbh7cNkO1JclSzXsCtA2Jw64AY0crTo3tGY9fxctGZTQu2HhEd9pFLtH4wJV6r5nsVuevy3KeHrYYcDb1I66YPw9Vd2su+xnVXd3KojUREZD8OnzmooLxWNCACgOoLTbJDWGL6x4Qp3tdfpzMO1SREhWJs705mvThSi7taDvsYyPV+9ekWrrh9vkRJArplGQNDL1Lh2Tos/TZf9jXUlG4gIiJtMShykFyeyOmqi6rqFKV074j2beUrRvvh0my1tNU5SF+Ti7GLs5C2KgfVFuUBwkMC8OLEPqLHML1hm0qMbifaZiXLgvgyqevSr5t0IPtDQYWihPsZ6350qI1ERGQ/zYKiqqoqrQ7lZaSDHQGXemtG9IhSdLQLjc2KZp+FhwSgxqKHylbPj9ywj9jUfLE2Sy0L0lrYui6vTOon+Tyl/T/1jS34XuFsRSIi0pZdOUWvv/464uPjMWXKFADA5MmT8cknn6BLly746quvMHDgQE0b6cmSEzpIPn5tYkeEhwRg3fRh2PlrGdJW50ruL5XgDAB/u6EnBsdGIm11jtVjpj0/pr05csM+YgnXhjaL5Sm1ZlLXZXTPaOw+ftZsCM1fp8OIHlEYJvM5MZV1rIxroBERuYFdPUUrV65EbOylVb+//fZbfPvtt/jvf/+Lm266CU8++aSmDfR0idHtEGaj/kxYcBuzQGJ0r04Y3TMaNsoDKTJxYDervBVLlj0/jgyHieUpkfh1kepds/UeiNmQc0Lz9hIRkTy7eopKSkqMQdEXX3yByZMnY/z48YiPj0dycrKmDfR0BeW1qLGxkGfNxWarXpvlUwfjvlU/4PCpGpvH7B8Thl/OnBftcUiICoUgExSJ9fwsnzoYj204YJbXwuEwbcn1rom9B2Lqm/T4Pr+cvUVERC5mV09RZGQkTp48CQDYtm0bxo0bBwAQBAEtLS2qj7dixQrEx8cjODgYycnJyMmxHhoyVVVVhVmzZqFr164ICgpCr1698NVXX6k/EQ3IJVrvLTB/PDwkAE+M7y35nIfHdJfM50mMboek+EirHiepnh/DDXv73FSsSU/C9rmpWDd9mGwVZlLPVu+a6XuQ0l16OC3zaKkzm0hERCLs6im68847ce+996Jnz56oqKjATTfdBAA4cOAAevTooepYmzZtQkZGBlauXInk5GQsW7YMEyZMQF5eHjp1sq7Z0tjYiBtuuAGdOnXCxx9/jG7duqG4uBgRERH2nIrDys9LF9srr22w2qZkyvu6geJ1h6rqGzFz3Y9mhRoNlPT8JEQxN8jdEqJCEd8xFNm/nbO5D6fmExG5nl1B0VtvvYX4+HicPHkSb7zxBtq1awcAOHPmDB599FFVx1q6dClmzpyJ9PR0AJfylb788kusXr0azzzzjNX+q1evxrlz55CdnY2AgEu9HPHx8fachkakh7LEbm2J0e0QGRKAynrr+kaRIQHGoMUygKmqb8SYN7Ns1kWSUlBei+Jz9UyY9hBZMou/2vMeExGRY+wKigICAjB37lyr7X/7299UHaexsRH79u3DvHnzjNv8/Pwwbtw47NmzR/Q5n3/+OYYPH45Zs2Zh69atiI6Oxr333ounn34a/v7Wa4E1NDSgoeFyb01Nje1cHntEtw+SfDyqnfXjBeW1ogERAFTWN9lcFHTG2h8lb5a7jpcbqycbOLKAKTlHQXktTldflNzn859OY/HkQa5pEBERAXCgTlFeXh5mz56N66+/Htdffz1mz56NvLw8Vcc4e/YsWlpa0LlzZ7PtnTt3RklJiehzCgoK8PHHH6OlpQVfffUVXnjhBSxZsgR///vfRfdftGgRwsPDjT+GBHGtJCd0lH480fpxe+oGFZTX4sdi6yEzU3oBVsUYxRYw3ZVfjhlrpUsD0CW2Fnd1hNz7DwCNLQLrFRERuZhdQdEnn3yCfv36Yd++fRg4cCAGDhyI/fv3o1+/fvjkk0+0bqMZvV6PTp064d///jeGDBmCKVOm4LnnnsPKlStF9583bx6qq6uNP4YEca0kRrdDSnfxwCile0fRHh976gYpuZEaGIIqwwKmllP49QByiytx98psqwrYdElVfSPSVuXguiU7JCuG20Pu/TfYYxHMEhGRc9kVFD311FOYN28e9uzZg6VLl2Lp0qXIzs7Gs88+i6eeekrxcaKiouDv74/SUvOZNqWlpejSpYvoc7p27YpevXqZDZVdffXVKCkpQWOjddJzUFAQwsLCzH609uxNV6ONxVSwNn46PH/z1aL7q60bVFXfiBX/O664PYagSi6Q2ldcKVoBm8R72GxVDFcrMbod4jq0ld3vv4fFe0uJiMg57AqKzpw5g7S0NKvt999/P86cOaP4OIGBgRgyZAgyMzON2/R6PTIzMzF8+HDR54wYMQLHjx+HXq83bvv111/RtWtXBAYGqjgL7Tywei+aLZahb9YLuG/VXpvPUbOMxpwNB3HgRJWitvTrFmYMquR6JMSG28h2D5utteLs8fRN4gGzqcKKer43REQuZFdQlJqaiu+//95q+65duzBq1ChVx8rIyMC7776LtWvX4ujRo3jkkUdQV1dnnI2WlpZmloj9yCOP4Ny5c/jrX/+KX3/9FV9++SVeffVVzJo1y55TcdiOvDLJpGlbeSFK6wbZukHbMnvs5ZIIhh4puTdZLIepNbMn50utm/t3RUig/D+/L38+7fBrERGRMopnn33++efG/584cSKefvpp7Nu3D9deey0A4IcffsDmzZuxcOFCVQ2YMmUKysvLMX/+fJSUlGDQoEHYtm2bMfn6xIkT8PO7fPOIjY3F119/jb/97W8YMGAAunXrhr/+9a94+umnVb2uVg7+XiX5+P4TlZKVieXqBqnJJQKAoADzGXjLpw7GtNU5ku0Uy2FqzezJ+bLHPUmxWL27WHKfgvJaTV6LiIjk6QS5NSP+YBqYSB5Qp7OrqrWr1NTUIDw8HNXV1ZrkF+3IK8O0NbZncn0wfZhDyzUUlNfiuiU7FO+/fW6qVZCVtirH5tISo3tGm03hp0vSVuXYXNxVq+sl99kBgNlju2PuhKs0eT0iIm+m9f1bjOLhM71er+jHkwMiZ4iV6VW4IlLZTCNblA6B2UrSNgy/2TJ3Qi+H2uer1OR82WtM705oGyD9zjLZmojIdewq3kiXKck/cbSC9PKpg5G6eLvN3CXA9g1brn0VddLLlLRWcou7auXmfl3xyYFTNh//rbzOZjFPIiLSlt3FG3fs2IHbbrsNPXr0QI8ePTBx4kTR5Gtf54r8k4q6BsmA6IPpw2wu7uqq/BhfZWtxV63ERcn3JFouKkxERM5hV1D04YcfYty4cQgJCcGcOXMwZ84ctG3bFtdffz0++ugjrdvo0dTWHLKHXG+PZTkAV7eP7HfrgBjZfZTNOyQiIkfZFRS98soreOONN7Bp0yZjULRp0ya89tprePnll7Vuo8dzdv6J3JtkWTjSkivyY8g+idHt0Ltze8l9roiUL/RIRESOsyunqKCgALfddpvV9okTJ+LZZ591uFHextn5J3qZx6V6ilzRPnLM5KQr8PIXR20+/vPJKodmMBIRkTJ29RTFxsaaVaE2+O677zRfcNWbOCv/RKu8IGfnx/g6ZywOCwAhgf6Sj/9zu/IlXoiIyH529RQ98cQTmDNnDg4ePIiUlBQAwO7du/H+++/j7bff1rSBdDkvyFbdHAY5zlVV34g5Gw6alTZIiovEe9OSRJPb1UpOEF9Q2OBCkx7f55ezt4iIyMns6il65JFHsHHjRhw6dAiPP/44Hn/8cRw+fBibNm3CQw89pHUbCcwLcqc5Gw5il0Wtp9ziSqQu3o5qiVmBSiVGt0OXsCDJff53tMzh1yEiIml21ym64447cMcdd0jus2HDBkycOBGhoezJcBTzgtxDqvhlZX0TZqzLxeaHUxx+nZv7d8Xq3UU2H+/Qzj2LHRMRtSZ21ylS4qGHHkJpaakzX6LVYV6Qa8mVQ8gtqtQkx+jn36slH1cydZ+IiBzj1KBI4bJqRB5LLskduFS1XIzSxOyC8lr8WFxp8/H+3cIYBBMRuQCX+SCSkBjdDkPjIiWDFsvZf2KJ2aN7RmP51MGiidlKinNW1zdpktRNRES2ObWniMgXrJqWhEiRgMRfB9Gq4HM2HMTu42fNtu0+fhaPbTggeny53qi8kvM2n0tERNphUEQkIzwkAFlzxyIpPtJs+4ge0Vaz/wyJ2S0WQ8ctgoCd+eX4XiRp21BywdY/Rr0A7Mwvx88nqxw5DSIiksHhMyIFwkMCsPnhFNnZf3JDYQ+syhEdSls+dTDue+8HHD5dY/O5T3/yM/77+Gj7T4KIiCQ5tacoLi4OAQHMgyBlnFUxWktys/+UJGaLDaWFhwTgHzI1p46WnEe2xbAcERFpx66gKDExERUVFVbbq6qqkJiYaPz98OHDrXrZD1Kmqr4RaatycN2SHUhfk4uxi7OQtipHk8KIrmYYCvPX2V6k1zCUZhr8FZTXovhcPeI6Si/++uf392rWViIiMmdXUFRUVISWlhar7Q0NDTh16pTDjaLWRW1isqcTqz4upqiiziogLK64IPmci80QzUsiIiLHqcop+vzzz43///XXXyM8PNz4e0tLCzIzMxEfH69Z48j32aoYbdqb4m01egzVx3f+Wo601Tk294vvGCoaEMr5dP/vXAeNiMgJVAVFkyZNAgDodDpMmzbN7LGAgADEx8djyZIlmjWOfJ9cYnJRhfcFRQaje0VLLuQr/BH4qVXb0KxlM4mI6A+qhs/0ej30ej2uvPJKlJWVGX/X6/VoaGhAXl4ebr31Vme1lXyQXGKyZWFEbyO1kK9cQGjLlZHyydxERKSeXVPyjx49iuDgYK3bQq2QITHZVm+Kt/YSGUgt5KtkppqYDbkn8fxtfbVsJhERwc5E64iICIwePRovvPACMjMzceGCdHIokRSp3hRfITaV39ZMNX/bE9cAAHWNLUy2JiJyAp1gx6qtu3btws6dO5GVlYXs7Gw0Nzdj6NChGDNmDFJTU3HDDTc4o62aqKmpQXh4OKqrqxEWFubu5pAJucKIvqi6vgmPbThgllsUGRKASplyBCN6dMT6Gdc6u3lERB7DFfdvu4IiU83NzcjNzcW//vUvrF+/Hnq9XnS6vqfwpqDIULumNQUJrZUhIPTXAWmrc2X39wNQ8Notzm8YEZGHcMX92+5lPn799VdkZWUZfxoaGnDrrbciNTVVw+a1TmpXWSfvlxB1KfDdnlemaH89gG2Hz+DGfl2d2zAiolbErqCoW7duuHDhAlJTU5Gamoqnn34aAwYMgE6iii8pJ1XMcN30YW5qle9zVc+c1OuoSb6ev/UIgyIiIg3ZFRRFR0fj2LFjKCkpQUlJCUpLS3HhwgWEhHCqsKN8sZihp3NVz5zU61TUNRgDJbHZeGLKzjfw80BEpCG7Zp8dPHgQJSUleOaZZ9DQ0IBnn30WUVFRSElJwXPPPad1G1sVJcUMSVuuWmZE7HV25ZcjdfF2s3XfmvV6DEvooOiY/DwQEWnH7pyiiIgITJw4ESNGjEBKSgq2bt2KDRs2YO/evXjllVe0bGOr4uvFDD2Nq3rmbL2OHrCaaba3oAJhbZX1UJ04Wwf0drh5REQEO3uKtmzZgjlz5mDAgAHo3LkzHnnkEdTW1mLJkiXYv3+/1m1sVWzXrtFhdM9oDpVozFU9c2qqV7cI1oGSLat3F9rbJCIismBXT9HDDz+M0aNH4y9/+QvGjBmD/v37a92uVm351MFWtWt8rZihp3BVz5y91avlFJ+7wLwiIiKN2NVTVFZWho8//hizZ8+WDIhee+01VFVVyR5vxYoViI+PR3BwMJKTk5GTY3tl8ffffx86nc7sx9eWHDEsDbF9birWpCdh+9xUrJs+jNPxncBVPXO2XkcLv5yq1vyYREStkV1BkVKvvvoqzp07J7nPpk2bkJGRgQULFmD//v0YOHAgJkyYgLIy2/VawsLCcObMGeNPcXGx1k33CGJLQ5D2tFxmpKC8FtvzylB41nrYTex1IkMCZJf1kPN+dpFjByAiIgAOJForoaRY9tKlSzFz5kykp6cDAFauXIkvv/wSq1evxjPPPCP6HJ1Ohy5dumjaVnINT6zSLbVoq1JKpvWLvU6HkEDRZT6q65ugV/jaucWVHEIjItKAU4MiOY2Njdi3bx/mzZtn3Obn54dx48Zhz549Np9XW1uLuLg46PV6XHPNNXj11VfRt6/4quENDQ1oaGgw/l5TU6PdCZBi3lCl21BV2h5qCm5avo6SQElOUQWDIiIiRzl1+EzO2bNn0dLSgs6dO5tt79y5M0pKSkSf07t3b6xevRpbt27Fhx9+CL1ej5SUFPz++++i+y9atAjh4eHGn9jYWM3Pg+S5qhaQOxim21sWWzRM69+Qc0J0OM2U6VCpZU7Z63+Sn8jQxo/V5ImIHOXWoMgew4cPR1paGgYNGoQxY8Zgy5YtiI6Oxr/+9S/R/efNm4fq6mrjz8mTJ13cYpILGuQCBk8nN91+3pZDGLs4C2mrclCtcKo9cDlQmpJ0JdoF+Uvu26x3aF1nIiKCm4OiqKgo+Pv7o7S01Gx7aWmp4pyhgIAADB48GMePHxd9PCgoCGFhYWY/5Fq+XqVb6XR7R3rG/nX/UMnHWdSTiMhxTg2KRo0ahbZt29p8PDAwEEOGDEFmZqZxm16vR2ZmJoYPH67oNVpaWnDo0CF07cqFMT2Vr1fpVjrd3pGesa4RvlV2gojIE9mdaK3X63H8+HGUlZVBrzefJzN69GgAwFdffSV7nIyMDEybNg1Dhw7FsGHDsGzZMtTV1Rlno6WlpaFbt25YtGgRAOCll17Ctddeix49eqCqqgpvvvkmiouLMWPGDHtPhZzMEDRYLnLqr9NhRI8oj0sQtmeGnFjBTVvsSYqW62375VS1x11HIiJvY1dQ9MMPP+Dee+9FcXGx1bR7nU6HlpYWxceaMmUKysvLMX/+fJSUlGDQoEHYtm2bMfn6xIkT8PO73KFVWVmJmTNnoqSkBJGRkRgyZAiys7PRp08fe06FXMQbqnQ7MkPOdLr9DwVnMW/LYZv72tMzJtfb9n52EW4ZGKP6uEREdJlOUFJMyMKgQYPQq1cvLFy4EF27doXOYtggPDxcswZqraamBuHh4aiurmZ+kRs4UgvI2dJW5djszbKcVu/KYxncvTIbuUWVNh//fNYIDIiNsOvYRESezhX3b7tyivLz8/Hqq6/i6quvRkREhNmUd08OiMj9PLVKt9Yz5LSskm0wLSVe8vF73/tB1ew2IiIyZ9fwWXJyMo4fP44ePXpo3R4it1AyQ05NIKdFlWxLfbpKfzOqbWjBjHW52PxwikOvQ0TUWtkVFD322GN44oknUFJSgv79+yMgwDzfYsCAAZo0jnyHJy7vYcpZM+QcqZJtKTG6Hfp1C8PhU7arsucWcckPIiJ72RUU/elPfwIA/PnPfzZu0+l0EARBdaI1+TZvWN4D8J4Zcq9M6ofbV2RL7sMlP4iI7GNXUFRYWKh1O8hHqVkTzN28YYbcwNhIDI2LxI/FthOuvb3uExGRu9g1+8ybcfaZ6xSU1+K6JTtsPr59bqrmPRpaDNN58gw5AKiub0Lq4u2otJFUnRQXifemJXlUTxwRkaNccf+2u3gjAPzyyy84ceIEGhsbzbZPnDjRoUaRb9A6eVmKlsN0WuYBOUN4SACy5o7FNX//Bi1668dziys9sieOiMjT2RUUFRQU4I477sChQ4eMuUQAjPWKmFNEgGuX93DXMJ27EsgPnqwUDYgMDGUEPDm4IyLyNHbVKfrrX/+KhIQElJWVISQkBEeOHMHOnTsxdOhQZGVladxE8la21gTz1+kwume0ZjdsrWsMKVFV34i0VTm4bskOpK/JxdjFWUhbleOyOkEHf6+S3Se3qML5DSEi8iF2BUV79uzBSy+9hKioKPj5+cHPzw8jR47EokWLMGfOHK3bSF7MGUUMLSkZptOaVM+UKwy6IkJ2n5c+/8X5DSEi8iF2DZ+1tLSgffv2AICoqCicPn0avXv3RlxcHPLy8jRtIHk3ZxQxtOTKYTrgcs+UJdOeKWcPW43p3QmRIQE2k60BoLaxBd/nl2NUz2intoWIyFfY1VPUr18//PTTTwAuVbd+4403sHv3brz00ktITEzUtIHkG8SW9ygor8X2vDKHh7dcNUxn4I6eKTH/nHqN7D6f7j/lgpYQEfkGu3qKnn/+edTVXfrD/9JLL+HWW2/FqFGj0LFjR2zatEnTBpLvcUZBR1fWGHJ1z5QtjXqJTOs/1DZwLTQiIqU0q1N07tw5REZGGmegeSrWKXI/Z6wgb+CqGkPOPAel5OpAAUBwGz98+7cxiO0oHcgREXk6V9y/7Ro+Mzh+/Di+/vprXLhwAR06dNCqTeTDnD1TTGyYzhlckUAuJzG6HZLiIyX3udisx8QVu1zUIiIi72bX8FlFRQUmT56M7du3Q6fTIT8/H4mJiZg+fToiIyOxZMkSrdtJPsKVBR2dyRUJ5HKq6hvRxk/+e01lfRMTromIFLCrp+hvf/sbAgICcOLECYSEXO6WnzJlCrZt26ZZ41orrRKQPZGn5ONoxdGeKUfe6zkbDiKn8JyifbcdPqP6+ERErY1dPUXffPMNvv76a1xxxRVm23v27Ini4mJNGtYaecuK8o7wltXonc3R99pWWQBb1u89iVfuGGBXW4mIWgu7eorq6urMeogMzp07h6CgIIcb1Vq5uyCgq3hCPo4zKen9cfS9lhuGFDP2zSyXVdwmIvJGdvUUjRo1CuvWrcPLL78M4NKaZ3q9Hm+88QbGjh2raQNbC08oCOgqnpCP4wxKe3+0eK/lhiHFFFbUcaFYIiIJdgVFb7zxBq6//nr8+OOPaGxsxFNPPYUjR47g3Llz2L17t9ZtbBV8JQFZDVetRu+qRVuVLkqrxXttaxhSjq8F2EREWrIrKOrXrx/y8vKwYsUKtG/fHrW1tbjzzjsxa9YsdO3aVes2tgq+loDsCVyZo6Wm90er91qsYKUSPxZWMCgiIhJhV1AEAMHBwbjhhhswcOBA6P+orJubmwsAmDhxojata0WckYDsqh4ST6W050YLanp/tHqvLYchO4YEYsq/9+BCk3Sl64Vf/IK7k65U9BpERK2JXUHRtm3b8MADD+DcuXOwLIit0+nQ0tKiSeNaG62WqmgNs9jkuDpHS23vj5bLkpgOQ/4wbxyu+fs3aJGIi2obWnDb8u/x4fRrW83ngYhICbuW+ejZsyfGjx+P+fPno3Pnzs5ol9N4wzIfjiYge8ISFO62Pa8M6WtybT6+Jj0JY3t30vQ17bnuzkg2P1lRj+uWbkeTxHcTHYBRPaNbzeeBiLyfxy7zUVpaioyMDK8LiLyFIwUBnb2MhjupKXTojhwte0oNOGNZktiOIXgvLUlyHwHw+s8DEZHW7Bo+u+uuu5CVlYXu3btr3R5ykC/OYrNnONAdRSI9qdTAmN6dEBbcBjUXmyX388bPAxGRs9gVFP3zn//E3Xffje+//x79+/dHQID5jWnOnDmaNI7U88VZbPYmTGuZt6OGq0oNyHnhlqvx5CeHJPdp46dzUWuIiDyfXUHRhg0b8M033yA4OBhZWVnQ6S7/YdXpdAyK3MjXltFwJGHak3pu3GFIfAfZfZr1qlMKiYh8ll05Rc899xwWLlyI6upqFBUVobCw0PhTUFCgdRtJJV9aRkPJcKAcZ+TteIMOoYEIC5b+3vN//zvOpT+IiP5gV09RY2MjpkyZAj8/u2IqcjJf6iHxxeFAZzKtTbVg6xHUyuQU7T9RxaU/iIj+YFdQNG3aNGzatAnPPvus1u0hDXlKbosjHB0ObC0FLMWS0ZXwxbX1iIjsZVdQ1NLSgjfeeANff/01BgwYYJVovXTpUk0aRwTYlzDd2gpYiiWjq8FZaEREdgZFhw4dwuDBl25Ihw8fNnvMNOlaqRUrVuDNN99ESUkJBg4ciOXLl2PYMPnu/I0bN2Lq1Km4/fbb8dlnn6l+XV/nK70k9gwHunKJD2eTex9tJaOrwWFIIiI7g6Lt27dr1oBNmzYhIyMDK1euRHJyMpYtW4YJEyYgLy8PnTrZrjhcVFSEuXPnYtSoUZq1xVf4ai+J0uFAVy/x4SxK30e5ZHQp3jorkYjIGdyeKb106VLMnDkT6enp6NOnD1auXImQkBCsXr3a5nNaWlpw3333YeHChUhMTHRha72DVC9Ja6DFjDVPoPR9lEtGNxVpERSbDkOqqRhOROSL7Oop0kpjYyP27duHefPmGbf5+flh3Lhx2LNnj83nvfTSS+jUqROmT5+O77//XvI1Ghoa0NDQYPy9pqbG8YZ7MF/pJXGEL8xYU/M+yiWjL7y9r9mwY+HZOvxQUAEdgOTEjhAgIG1Vjs/1LBIRqeXWoOjs2bNoaWmxWkOtc+fOOHbsmOhzdu3ahVWrVuHgwYOKXmPRokVYuHCho031Gr64zIdavlDAUu37KJWMHh4SYNy3qr4RC7YeMdsvMiTAqlaRt+ZfERE5wq1BkVrnz5/HAw88gHfffRdRUVHyTwAwb948ZGRkGH+vqalBbGyss5rodr7QS6IFdy3xoRW176PSZHSxIblKkeKNralnkYjIwK1BUVRUFPz9/VFaWmq2vbS0FF26dLHa/7fffkNRURFuu+024za9Xg8AaNOmDfLy8qwWqQ0KCkJQUJATWu+ZfKGXRAveXsDS3vdRKhndnllqraFnkYjIwK2J1oGBgRgyZAgyMzON2/R6PTIzMzF8+HCr/a+66iocOnQIBw8eNP5MnDgRY8eOxcGDB326B0gNX1rmQ45ccrA3L/Gh9ftozyy1Nn46JmATUavh9uGzjIwMTJs2DUOHDsWwYcOwbNky1NXVIT09HQCQlpaGbt26YdGiRQgODka/fv3Mnh8REQEAVttbM2/vJVHCV8sOmNL6fVQzS83gpf/3C/LLao2/+9o1JiIy5fagaMqUKSgvL8f8+fNRUlKCQYMGYdu2bcbk6xMnTnCNNTv5wjIftgoX+lJxRlNi56vl+3hVl/Y4VnJe8f6mAREA7Mov9/prTERki04QTBIWWoGamhqEh4ejuroaYWFh7m4O2SDVE1RR14Drluyw+dztc1M9OhgUC3yc2fNl77poUj6fPQIDrojQ7HhERHJccf9mFwx5JKmeIG8tzlhV34i0VTm4bskOpK/JxdjFWUhblYPq+ianFtx0dF00Mc9+ekjT4xEReQIGReRxDLOkWiw6MQ3TxP1lltdTWnbA1QnEtgKf6WtzJc/XkfbZupaOOnyqhonXRORz3J5TRGRJrieoRYBDZQfckaQtVaH6x+JKyec6Mi3ekXXR5HC6PhH5GvYUkcdRUrjQkenq7lgbzpHgxJGCm0pmnPnBek00JVpLIVAiaj3YU0QeR2nhQnumq7trbTi54CQsuA3qGlo0L7hp61qaGtkzGk+M74VfztTg15LzWJNdJHvcpPhICIKA7XllPlnygYhaJwZFJMnWlHhnU7pMh9rp6u5aGy4xuh2GxkXaHCqrudiMpLhI5Jo8rlXBTbFrmRQfiWkp8YiNDMGSb37F7St2Kz5e2wAdmvWC2QxAw/H6xoQzQCIir8WgiETJ5d04O1hyVgFKd64Nl54SL5k/9Oh1PRDfMVTzgptS1zJtVY7qmWkXmgQcOFFlti23qBK5RZfObWhcJNJT4tGnGwMkIvIuDIpIlK28m0fW70MbPz+XJSlrXYDSnWvDXR0jXVfDEKw4qw2Wx7ZnLTQlfiyuNAZ/rIBNRN6EidZkRWpKfPZvFdhlcSN1dpKy1uxN0nZ0Cr8hIPPXmdcU8NfpMLpntEt6VQzn8NPJSsyRec8eSe2OoDaO/Ynwts8GEbVu7CkiK3J5N3qL352dpKw1tUNzWk7hV5or5QilFbPlvJP1m8Nt8bbPBhG1bgyKWgk1OUD2LBwKeF/dGqVDVVqus+bMxXqlgjdnVLVWw9s+G0TUOjEo8nH29HLYyrvx0wF6icLIvli3xllT+J2RO2QreLvvvR9w+HSNpq+lVhs/mTLkREQegDlFHkJtvorS/e0tVCiWdzOyRzSGJ3Z0a06MM0hdS29ZZ00qD8zZAVFooL/sPs1S0TQRkYdgT5Gbqe3JUbO/I70ctoZ5quubnJ4T4ypKrqU7p/ADyoc9tVjOw1+nw+ArI2SXHbF0oalFdh/L6+Su+ldERFIYFLmZ2nwVNftrUajQcpjHmTkxrqbkWrprCr/aYNnePDBThuD2sQ0HJCtgW1LaCVRQXotfTtdgbXaRWZFKTtsnIk/B4TM3klsN3nI4R+3+zuzlSIgKxdjenZweEDlrJXs119KRddYMr6X2HNQOe9qa7i9ldM9ofD57BNakJ2H73FSsmz4M4SEBoufbLkh+iEzKYxv247olOzB7wwGzgAjgtH0i8hzsKXIjtT05v8jkhlju785ChY5y9kr2aq69vb1j9p6DvcOey6cOxvS1uYqGvz6YPgyjekaLPlZR14D0kfGYOToBzXrBeL47fy1D2upc2WOLkfrscto+EXkK9hS5kdqenPdlFuoU6/lxtJfDXexJEFfTI2NPL5ra3jGpc3BGcnd4SABmXddD8rl+ukuBmVhAVFXfiLRVObhuyQ6kr8nFA6tysGZXETqEBKKgvBYtApAUF2kz0X50z2irPyiG35UMsX3+0ynNewSJiNRgT5EbqenJKSivlewBSIqPFL1Ze2MOkNqeEi3LDmjViyZ3DqaLqWqZ3C333O7R7TB3Qi/Rx8SDuHKkLt6Oyvom47bIkACz302DbMsk/D4xYYpnv731bT7e+jYfSfGReC8tiTlGRORy7ClyM6U9OXK9B9NS4iUfd1UOkKOq6hsxZ6N0follj4KWZQe06kVTMxvMsq2OLAcil1uUX1aLif/cjbRVOaiubzL2WO38tdxGjhXMAiAAqLnQjKT4SKtcJEMAvn1uqvGxf9hxLXOLKpG6eDuqLV6XiMjZdIKgcIqJj6ipqUF4eDiqq6sRFia9QKcryfXkFJTXmvUuWNo+N9XjAx4l0lblYNfxckXDLaN7RuOJ8b1w+4rdNvdRcl2c0Ysm936JMW2rWOkDpTlVYs+15K8DwtoGWAU89rZXStqqHFWz2QyS4iKx+ZEUe5tHRD7GFfdvDp95CLkKx96cNK2U2lXbdx8/i3N1DZL72FN2QAu23i8pWiR3Wz73h4KzmLflsNU+Yj1AaoldW7H6Q2LrvSXFR2JofCTeySqwefzc4komXxORSzEo8iKuWEzUndQWIFRSrdmdS4+IvV9SbCV32xsUJESFOrXitml75fK6xAK8gvJayaAI4JppRORaDIq8iDcmTathbwHCft3CcPT0eY/rQRN7vxZsPeLU3j7LnhpHizpGhgSgur4JepNtYu1VUgjTMsBLjG6HpPhI5BbZnkDgi+vpEZHnYlDkhZwx3OMJ7F2I9tU7+mPx1796bA+a6fvlrN4+qZ4atcN4H0wfZqxP1CEkULa9amcLmgZu76UlWc1uAy7NABnpxevpEZF3YlBEHkUsaBjZIxpNLXrkFJ4T7WEZcEWE1/SgOaO3r6C8FnM2HLAqkLjreDnuW/UDXr2jPwCYXVOpHiDLGkZy7VVaCNNW4Pb5rJHI+M9Bs0rX18RFYsrQK2RziriGGhFpibPPyCMpWYi2ta+ZJRZk2DK6ZzTmju+FivpGmz1A9l5PpTMjxWahGQIxQ+B1+HQ11mUXmQ2pibXL2RXPicjzuOL+zaCIvIo39Aa5ipqp7qbBhymtrqdcwKNV4KT09YjI97ji/s3ijeRVvKUIpbPZWtDWFluLBtt7PS2XKZErhKlkiE3pIr1qF0YmIlKKOUVEXkht+QIDR6e4Sw1bSeUeKVm6RK58gKHtahdSJiJSij1FPkTNgqikjKdeU3un2js6xV1uSRVbPU9yy48s2HoEHWRygQxtV7M2nKe+f0TkmdhT5APsSToVm7XDmTyXeXoir1T5gpBAf9Q3tMjWFlJL7dR7S1LFLA2BlpKq7Uqqu3v6+0dEnomJ1j5ATdKp2M0ipXtHCAKwp6DCuK2130CUJA67O4C0NSPvlUn98NxnhzULCAznWlp9Ec9sOWRzvzXpSRjbu5PssaQSrj+fNQKLv/lVtu1ysxGZiE3ke1rN2mcrVqzAm2++iZKSEgwcOBDLly/HsGHif7i2bNmCV199FcePH0dTUxN69uyJJ554Ag888ICLW+0Z1H57Fxv+yP6twvLpVtWIPYUrghG5a3r3ymzZKeOuaKdUzSMtaiGpmfIPKBuak8sHqqhvVNT2iroGpI+Mx8zRCcZCk6Y9nmp7tHbkleHg71W45spIqzpNRNR6uD0o2rRpEzIyMrBy5UokJydj2bJlmDBhAvLy8tCpk/W3zg4dOuC5557DVVddhcDAQHzxxRdIT09Hp06dMGHCBDecgXupSTpVs+Cq0iERVxG7QfeLCcOrd/THgNgITV9L7pruKzZflsI0gHTHsI2tCueOVj4XC6DFqBmak0tibON3KefIVtulrq+Bmn8TxRV1mLRit1lF7ciQAHw+ayRiOzq2RAoReR+3J1ovXboUM2fORHp6Ovr06YOVK1ciJCQEq1evFt0/NTUVd9xxB66++mp0794df/3rXzFgwADs2rXLxS33DGqSTu2ZseTMBUXVELtBHz5dg4krdiNtVQ6qHVzx3ZTcNbVccsQ0gJRLRPYWaqb8q1mmRC/zeLPUei6QT/QG1P2bsAyIAKCyvgkTV7TOvydErZ1bg6LGxkbs27cP48aNM27z8/PDuHHjsGfPHtnnC4KAzMxM5OXlYfTo0aL7NDQ0oKamxuzHl9ia1eOv02G0xdpR9sxY8oQFOXfklUneoHcdL9c06LB1TeX+sfxQcNZn6ufIBdCL7uyPNelJ2D43FeumD1PcC6YmYLGktD6R0n8TO/LKrAIig8r6JnyvsFeViHyHW4Ois2fPoqWlBZ07dzbb3rlzZ5SUlNh8XnV1Ndq1a4fAwEDccsstWL58OW644QbRfRctWoTw8HDjT2xsrKbn4AnkCucZyE2LNiUWVLlaVX0j0lblYNqaXMn99AI0DzrEruk1cZEyz5K+rp7S66aEXPBybWJHu4o+Jka3Q1J8JPwsLpXc562gvBb/7+fTksc2vb5K/k0c/L1K8nj7T1RKPk5EvsftOUX2aN++PQ4ePIja2lpkZmYiIyMDiYmJSE1Ntdp33rx5yMjIMP5eU1Pjc4GRacLtDwUV0AFITuwo+u1dalq0qWuujHD7KvNKc1oM7C3aJ5YUbSuJWWpWU3JCB8nX8YReN6WUTHtXynB9O4QEYMk3+WZJ6ga2huDUJHubXl8lC+8OuiJC8njXXCkXBBORr3FrUBQVFQV/f3+UlpaabS8tLUWXLl1sPs/Pzw89evQAAAwaNAhHjx7FokWLRIOioKAgBAUFadpuT1RV34gFW4/IJvgabhYbc05ITq9+9Loedi0MqtWMKzVJ4QZqgw4lSdGWCb9iQaXhhh4eEqBZIOEJpM5VCSUBjR+AIXGRNmc5KgmMpa6vVLL5mN6dEBkSIDqEFhkSoGoWWkF5LfYWVgDQ4drEjl73XhPRJW4NigIDAzFkyBBkZmZi0qRJAAC9Xo/MzEzMnj1b8XH0ej0aGhqc1Ern0iqQkEpAFbvhDNOwV8MZM67UJIXbG3SovWaAfA+Eo4GEs9jzOVPS2yJFSUCjB5BbXCk6y1FpYGy4vvac4+ezRmLiil2is8+UqKpvxKPr91uVtRie2BEr7x/Saut8EXkrtw+fZWRkYNq0aRg6dCiGDRuGZcuWoa6uDunp6QCAtLQ0dOvWDYsWLQJwKUdo6NCh6N69OxoaGvDVV1/hgw8+wDvvvOPO0zBS+odZy0DCnrosWg6P2BNcyFGTFK4k6LB8XxytzmyrB8LRQEJrWnzO7Jnar7anT2zoUy4w1gEYGheJf0wdJFnI0bJdpp+D2I4hODB/PL7PL8f+E5Wq6xTN2XBQtM7XnoIKj6zzpSVPKGBKpDW3B0VTpkxBeXk55s+fj5KSEgwaNAjbtm0zJl+fOHECfn6X88Hr6urw6KOP4vfff0fbtm1x1VVX4cMPP8SUKVPcdQoA1N98tAwk7F0gU4teDUeDC1vkgraFt/dVFHTYel8mJ10h+fpS+UlKbgaO1gjSijMCViXUln8Q65mUC4wFXOplmrn2R+w/UWX2mOU5yv37HNUzWnXRRrnAz5PqfGmJS6iQL3N7UAQAs2fPtjlclpWVZfb73//+d/z97393QavUUXPz0TqQsHeasxa9Gs5csVwuf8fQ47M9r0y07QXltZiz8QB+OW1ehmH38bO40NQs+dpi18zbbgbOCliVUNrTJ9UzaQiMdx0vt6oNZSq32Dpx2/IcnREcKgn8HPn8eyp3BdpEruARQZG3U3vz0TqQcHQozJFeDUfqzsiRCtqkAhQBgmSCb4sgILeoEklxkdh/okrxNfO2m4EzA1Y5tj6TlsLatsErk/rZfHz51MGYsS5XdMaaEkUVdRD++HdoSSo4VNIbqCTw86YZh0q4M9AmcgW3V7T2BUpuPqacEUgorVWkNTXFI+2VEBVqVRNHKkBROpX/wZR4xddMaeFAT1FQXouS6guS+9h7wzb0zsmds9hn0lLNhWY899lhm4+HhwTg9T8NQM9O7ayqQPnrdEiKl542H98xVNW/T0NtrOuW7ED6mlyMXZxls2K64bNvi7vrfMlR+j6aUvu3jsjbsKdIA2qDHFvfov0AjLTzD6k7E3xdPeNK7tuqUn26hWPdwBhF10ztGnPuSkBVMg3e3tl6aocPBcgvESLVwyB3LobP2GMbDkj2kgoyS5WY/vtU2xu4fOpgPLJ+n+jsM3fPOLTFkWFgZ/YME3kCBkUasGf4avnUwXj4w33YU3D5j6keQLNej+r6JrtzVNyR4OvqgMyeNdxMWb4vSq6Z3M2gpPoifjpZhSXf/OrWnCMlvWT2BqxqAwY1xTfFhvLEnu+nA/rEhGH51GuM+8sF5Ur/fdozNBQeEoCPZl6LwrN12FtQAQHw+DpFjgwDazlrlcgTMSjSiNrekvCQAAT4+8FPZ77A6N6Ccx6boyLHVQGZPWu4mbInKJDLkZlnoxCmK3OO5GZDLbqzv903bLUBg9op+ZY9DLaerxeAw6fME+eVBOW2/n0+Mb6XMVHfkRwsT5ltKEeLnCBPrcVFpAUGRRpR21vChEX7yX1bBSA6NNknJgzL773G7uuqdIkUU658P+Vu6l3Cg+1ug9qAQWlvnq0eBnsCFKnAxPLfZ4eQQCz55lfcvmK3cR+5/CR/nc7mTEe13DXEqkXyvafV4iLSEoMijSn9xujOmUHeQurGIfdt1fKxkQ4OYxnasvD2vgCAHwrOYt4W2wnClmy9n1reHJ2Z76Hm2FX1jVjxv+OKjmurh0FuBojp66m5hoZ/n4Y17EztL65CGz8dmkXm/7fx0yFtdY7xd3uHRZ1d1kHuWmj5GfGW3jEiNRgUuYncH/2S6outtrdIyY1D7tuqVt9k7S3+aMnyZuOMm6Mz8z3UHHvOhoM4YFFM0XT/a66MwKPX9RB9X+SSq01fz95rKNVLays33DJQsndY1FllHZReC+YEEUnjlHwXM0z5nbYmV3K/eVsOSU4H9lT2TPO1JHXjsCQ2XV/JY462ZW12kaLn+0F8araac1TDmaUZlBzbVukCg2viIvDetCSb78uj6/dLDk+avp6919DRRH3AvlIMzizroOZauKt8B5E3YE+Ri6mZkQOIf4v0xDWHtOr58KRcK6m25BZVIiy4DWouSlfGvjRTyvxm48xzdGa+h5JjywUcj47tYfPzUFBeK7qOmEH/P65leEiAQ9fQ0UR9U2qGuZ01ZK72WjAniMg29hS5kNy3aDGmf9jUFJZzNa16PjypOJxcW2plAiIAWH7vNVZBgCvOUUkvmb29elLHdiRnZW+h7YAIAA6frjF+nhy5hlIFRyNDAqy2SzEkXyu5hs7K+bL3WmjRk0rkaxgUuZAj3fZFFXVOG3JxlJbDAp5UHE6uLXqJx6Qqerv7HJ0ZXDtW4Vw6GBFweZFVR6+hrSGkz2eNtNoeGRJg9YfS74/taatzjNfw7pXZ+OLn0zY/786q/u7uzxORL+HwmQs50m3vr9N5zLCSJS2HBZyZCKp22NFm5XGL2lJipHI03J3s6uw13OytY5Oc0EHR8Ysq6jC2dyeHrqHUEJLl9g4hgVbnEx4SgJoL5kFkblGlcY02W0PHzqjx4+7PE5Ev0QlyNfB9TE1NDcLDw1FdXY2wsDCXv75hKrDS+jqGx9JHxiNdIjl7Tfql5FV3KCivxXVLdth8fPvcVFV/mKvrm6xuHI7MzHIk30msLUnxkZILlH4wfRhGSayJZeu4rqh+rfV7JcWenJWp//7BrMq7GEMbXX0NDefjrzOfni/G8O/WVpCpdT6Puz5PRK7kivs3gyIXk/rjBVjX1zE8VlHX4LKbmT2kgj17ex+0unFo0TbLtmh1vq5Odt2eV+axwTUg/u/DwNb19bRraLavi/9dMnmafBmDIidwd1BkIPXHy9ZjYjdiA3d/K/TUb6rO6hlx5HyVDOM5a4ahK3uKHPHz71V49tNDZkt6eMLnCZC/hqbcHWQS+RIGRU7gKUGRPez5Fu1qnvZN1dk9I2rOV8kwnrMrHgPO6dVTS2nQ52mfJwOpLyimPCXIJPIFrrh/c/aZFwkPCcCLE/uIPqZFATgteNo0X2fPzFFzvkpmD7pihqE7i/epnfnmaZ8nA7FraMrRGWVE5B6cfeZlXLlmmjOGcFxdeNJTZuYoKbAn/PH/Uvto0V57Fi/W6j1z9sw3VzG9hr+cqsb72UXILb6cfM8K0UTeiUGRB5K6CbmiJomaIRylN0y5YzozWNJyGrS97dSiYKPWiwTLLeip9VCeJ1Ur14rhGt4yMMZjh/qISDkGRR5EyU3IFT0fSr7Nq71h2jrmI+v3oY2fn1NzaLRY1sDRAEFJMCuX3ufqInxa9+q4spfTHbhqPJH3Y06RB1GaT+LMnBCl1anV5L5IHTP7twrssug9cFaVbkfyUxzN9VFSzdhZFY/t4YzFS5X2cmqxqDB5Lr6/5MnYU+Qh1AwtOHNBRyXf5tXmvsgd03K5DE8bTtFq2EfJMJ4zKh7bwxm9OlIVwkf2iL60bMaqHI8r60DacMXMSiJHMSjyEPbchNR21yvJh1HybV4u/8WyrfYub+IpwylaBAiGa7/w9r7G54i9D56ygrmzcteWTx2MR9bvQ/Zvl6tW6wWgqUWPR9fvx96Cc2b7e2MSNonzlSR78m0MijyEMxOo1XxDU5KzpDb3xd41xDxlIUtH3ht7vx27Oz/FWblr4SEBaOPnBz+Y9xDuLagQXWDX03oN5Wg1YcDVszSdzReT7Mk3MafIQzgzn0RtPoxczpI9bRU75sge0Rie2NEjcmikOPLeuKLukLM4I3fNcHO0DIDEAiJTSmbnuZPa+kvOPo6n0WL2JZErsKK1B3HGUhmOLOsgNYRjq61PjO+Jc/VNNr/hWh5T6Tm7+5uzPe+NtyypIUfLoTw164aZWvfnJLQI8NieE62qhHtCtXFn8JV/C+Rerrh/c/jMgzgjn8SRfBipIRzLtnYICcCSb/Jx+4ps4z5iQYPlMeXO2VOSM+15b3xlCrqWQ3lyQ5GWQ6r+OiCsbQDSVl8OpDwtOVeroSFfHmLylCKqRHI4fOaBtFzawFXLXCz5Jt+hYSJb56x2+MnZ033VvDdy1/7//nfc64dF1JIaihye2BEje0SbbQ9rG2B1jTxt+FGroSFfH2Jy5/IyREqxp8jHueIbmrO+4ao5rqf0KJkO89m69gb7T1S1ypk3UmUHwkMCjL1x/jqY9RAZeFrPiVZfPFxRrV6Mq4amPWVmJZEUBkWtgLNr3zhrmEjNcbWa7mvvDcJWUPbKpH7I2HwQuUWVVs/xtJu7q8jdHA3DddvzyiSP4ynDj1p98XD1EJO7vki4e2YlOZ+7c0AdwaCoFTC9Cf1QcBaADtcmdtTsD5+zvuGqqYDsaE+VozcIW0HZc58dxqNje0gmF3vKzd3V5G6O7uo5sYdWXzxcWbyTdYNIa57SY+8IBkWtRFV9IxZsPaL5zDbDtwGtvuGKDT/tOl5ulnzrB6BPzOWZB1r0VDlyg5ALymaMipd8vifd3D2JNyXnajU05KohJl9O6ib38YVA2yMSrVesWIH4+HgEBwcjOTkZOTk5Nvd99913MWrUKERGRiIyMhLjxo2T3J8u0bJejlgtlWa9HsMSOpjtp+Ybrtgx7333B1xobLYq8KgHcPh0jbGGSweZoE4u6HB0nS+5oKxFgMesaeZtvC05V6tJElpOthDj60nd5HrOWC/RHdzeU7Rp0yZkZGRg5cqVSE5OxrJlyzBhwgTk5eWhU6dOVvtnZWVh6tSpSElJQXBwMF5//XWMHz8eR44cQbdu3dxwBp5P62+FYgHW3oJzGNEjCtvnptr1DVfsmKZLQdhieI4jPQqO9jQpGebxlDXNvA2Tc53Dm4YmyTv4SgkStwdFS5cuxcyZM5Geng4AWLlyJb788kusXr0azzzzjNX+69evN/v9vffewyeffILMzEykpaW5pM3eRssPq1yABQBje1sHs/YcUwnD634+awQA2BV0OHqDUDrMw5u7/VyVnOvNCaJqeNPQJHkHXwm03RoUNTY2Yt++fZg3b55xm5+fH8aNG4c9e/YoOkZ9fT2amprQoUMH0ccbGhrQ0NBg/L2mpsaxRnshLT+szvg2IHdMJSrqG+0OOrS4QdjqCXpifE9szysztoczbzyTLySIqsXeS9KSrwTabg2Kzp49i5aWFnTu3Nlse+fOnXHs2DFFx3j66acRExODcePGiT6+aNEiLFy40OG2ejMtP6zO+DYgd0wlDK9rb9Dh6A3C3grf5Bl8IUFULQ5NktZ8IdB2+/CZI1577TVs3LgRWVlZCA4OFt1n3rx5yMjIMP5eU1OD2NhYVzURgGd0yWvxYTWcR1J8JPYXVykKsJScu1yRQylafQvR6gZhCMoMa1iZ8vWbrLdq7TOx2HtJWvGFQNutQVFUVBT8/f1RWlpqtr20tBRdunSRfO7ixYvx2muv4bvvvsOAAQNs7hcUFISgoCBN2quWJ3XJW35Y/XWXZkWdq29EeEiAZPAidh6RIQGoNFl+wTLAUnvuYkHb4NgIHDhZJXleWn8L0eIG0dpvst7GVxJEiTyFNwfabg2KAgMDMWTIEGRmZmLSpEkAAL1ej8zMTMyePdvm89544w288sor+PrrrzF06FAXtVY9T+ySjwwJwIKtRZIBjiF4qahrQPG5evzf9uPYX1xldpyaC81IiovEo9f1EA2k1J672DeMHwrOSgZFr93ZH/cMu1LF2bsGb7LexVcSRInIcW4fPsvIyMC0adMwdOhQDBs2DMuWLUNdXZ1xNlpaWhq6deuGRYsWAQBef/11zJ8/Hx999BHi4+NRUlICAGjXrh3atWvntvOw5Km9BWLBSqXVgpvlSF283Wq7qRZBQG5xpWhA5Mi5J0SFIjIkwKqXSUxyYkfJx92FN1nv4isJokTkOLcXb5wyZQoWL16M+fPnY9CgQTh48CC2bdtmTL4+ceIEzpw5Y9z/nXfeQWNjI+666y507drV+LN48WJ3nYIoTyyOZqu4lqUWwTpQskXsPBw9d7HAzZSnFz2UWgnek9vdmnlbkUgicg639xQBwOzZs20Ol2VlZZn9XlRU5PwGacATewu0mPpuSew8HDl3JTWLvOFm5QuzMFoTX0gQJSLHeURQ5Is8sUtei6nvBn4ARtro9bDn3A2J3qXVFyVfd9Gd/THVA/OILGl1k/WEmYutiTcniBKR4xgUOZGn9RY4MvXdUp+YMMnzUHruYrPUpFzroXlEtth7k/WkmYtERK2FThAcvDt6mZqaGoSHh6O6uhphYWHyT9CAJ3XJV9c3WQUrlrPPIkMCUFXfBKkPxva5qbLnUlBei72F56DDpaRosf0N9XzkgjRDL1NrqfEjdl1a2zUgIjLlivs3e4pcwJO65G0N65j+3iEk0CpwMlAy/Ke0l0PNmmetKR/HU2cuEhH5OgZFrZRloGb5+7rpw/Dz71V49tNDOHzq8npxSoITpTWK5BK/F93ZH13Cgz2ih82VWOeIiMg9GBQ5iTMSZF2ddDvgigh88dgoVcN/ano55BK/r7Ux5ObrPHHmIhFRa8CgSGPOSJAVO2a/mDC8ekd/DIiNcLTJoiwDMKXBiZpeDk+coecJeF2IiNzD7cUbfY3U0JGWxzx8ugYTV+xG2qocVP+RJF1QXovteWUoPGt/Yciq+kakrcrBdUt2IH1NLsYuzjJ7DTlqezlYNE8crwuR59Liby15Js4+01BBeS2uW7LD5uNKZmypPaaf7tIwUxs/P016p7SY9WTPMTxphp4n4XUh8hwsleFerph9xp4iDTljaQ+5Y+oFIPu3CuyyyOOxp3dqR16Z6DIgpvlAStjTy5EQFYqxvTvxxm+B14XIczhjJIA8C3OKNOSMBFmlVaj1Fr+rmb6ttICi0llPXDKBiHwNS2W0Duwp0pAzFgI1HNPeN0pJ75TcAqwGaoM69nKQJ2EeCDnCExf5Ju2xp0hjzljaQ+yYBn66S0NotsgFMkoKKHLWE3kz5oGQFlgqo3VgUKQxZwwdGY4pVkxxZI9oNLXokVN4zq7p23LffgDOeiLvprSYKJEUlspoHRgUOYkzlvawVUxRbD0zpYGM3LefD6YPw6ie0Q63ncgdmAdCWvK0Rb5JewyKvJBlwOVI75Tctx8GROTNuGQKaYmTSHwfE619iL2JzSwUSL6KeSDkDJxE4rvYU+TjlKyXxm8/5KuYB0JEajAo8lH2zLhxRh4UkbsxD4SIlOIyHz5Ki+U6iHwJe0KJvJsr7t/sKfJBnHFDZI09oUQkh4nWPoiVV4mIiNRjUOSDOOOGiIhIPQZFPsgZa7ARERH5OgZFPoq1h4iIiNRhorWPYu0hIiIidRgU+TjOuCEiIlKGw2dEREREYFBEREREBIBBEREREREABkVEREREABgUEREREQFgUEREREQEwEOCohUrViA+Ph7BwcFITk5GTk6OzX2PHDmCP/3pT4iPj4dOp8OyZctc11AiIiLyWW4PijZt2oSMjAwsWLAA+/fvx8CBAzFhwgSUlZWJ7l9fX4/ExES89tpr6NKli4tbS0RERL7K7UHR0qVLMXPmTKSnp6NPnz5YuXIlQkJCsHr1atH9k5KS8Oabb+Kee+5BUFCQi1tLREREvsqtQVFjYyP27duHcePGGbf5+flh3Lhx2LNnjyav0dDQgJqaGrMfIiIiIktuXebj7NmzaGlpQefOnc22d+7cGceOHdPkNRYtWoSFCxdabWdwRERE5D0M921BEJz2Gj6/9tm8efOQkZFh/P3UqVPo06cPYmNj3dgqIiIissf58+cRHh7ulGO7NSiKioqCv78/SktLzbaXlpZqlkQdFBRklnvUrl07nDx5Eu3bt4dOp3P4+DU1NYiNjcXJkycRFhbm8PG8Ha+HOV4Pc7we5ng9zPF6XMZrYc5wPX755RfExMQ47XXcGhQFBgZiyJAhyMzMxKRJkwAAer0emZmZmD17tlNe08/PD1dccYXmxw0LC+MH1wSvhzleD3O8HuZ4PczxelzGa2GuW7du8PNzXjq024fPMjIyMG3aNAwdOhTDhg3DsmXLUFdXh/T0dABAWloaunXrhkWLFgG4lJz9yy+/GP//1KlTOHjwINq1a4cePXq47TyIiIjIu7k9KJoyZQrKy8sxf/58lJSUYNCgQdi2bZsx+frEiRNmUeHp06cxePBg4++LFy/G4sWLMWbMGGRlZbm6+UREROQj3B4UAcDs2bNtDpdZBjrx8fFOzTxXKygoCAsWLGDNpD/wepjj9TDH62GO18Mcr8dlvBbmXHU9dIInRRhEREREbuL2itZEREREnoBBEREREREYFBEREREBYFBEREREBIBBkagVK1YgPj4ewcHBSE5ORk5OjuT+mzdvxlVXXYXg4GD0798fX331ldnjgiBg/vz56Nq1K9q2bYtx48YhPz/fmaegKTXX491338WoUaMQGRmJyMhIjBs3zmr/Bx98EDqdzuznxhtvdPZpaEbN9Xj//fetzjU4ONhsn9b0+UhNTbW6HjqdDrfccotxH2/9fOzcuRO33XYbYmJioNPp8Nlnn8k+JysrC9dccw2CgoLQo0cPvP/++1b7qP175CnUXo8tW7bghhtuQHR0NMLCwjB8+HB8/fXXZvu8+OKLVp+Nq666yolnoR211yMrK0v030pJSYnZft74+VB7LcT+Juh0OvTt29e4j1afDQZFFjZt2oSMjAwsWLAA+/fvx8CBAzFhwgSUlZWJ7p+dnY2pU6di+vTpOHDgACZNmoRJkybh8OHDxn3eeOMN/OMf/8DKlSuxd+9ehIaGYsKECbh48aKrTstuaq9HVlYWpk6diu3bt2PPnj2IjY3F+PHjcerUKbP9brzxRpw5c8b4s2HDBlecjsPUXg/gUkVa03MtLi42e7w1fT62bNlidi0OHz4Mf39/3H333Wb7eePno66uDgMHDsSKFSsU7V9YWIhbbrkFY8eOxcGDB/H4449jxowZZoGAPZ83T6H2euzcuRM33HADvvrqK+zbtw9jx47FbbfdhgMHDpjt17dvX7PPxq5du5zRfM2pvR4GeXl5ZufbqVMn42Pe+vlQey3efvtts2tw8uRJdOjQwervhiafDYHMDBs2TJg1a5bx95aWFiEmJkZYtGiR6P6TJ08WbrnlFrNtycnJwkMPPSQIgiDo9XqhS5cuwptvvml8vKqqSggKChI2bNjghDPQltrrYam5uVlo3769sHbtWuO2adOmCbfffrvWTXUJtddjzZo1Qnh4uM3jtfbPx1tvvSW0b99eqK2tNW7z5s+HAQDh008/ldznqaeeEvr27Wu2bcqUKcKECROMvzt6fT2Fkushpk+fPsLChQuNvy9YsEAYOHCgdg1zEyXXY/v27QIAobKy0uY+vvD5sOez8emnnwo6nU4oKioybtPqs8GeIhONjY3Yt28fxo0bZ9zm5+eHcePGYc+ePaLP2bNnj9n+ADBhwgTj/oWFhSgpKTHbJzw8HMnJyTaP6SnsuR6W6uvr0dTUhA4dOphtz8rKQqdOndC7d2888sgjqKio0LTtzmDv9aitrUVcXBxiY2Nx++2348iRI8bHWvvnY9WqVbjnnnsQGhpqtt0bPx9qyf3t0OL6ejO9Xo/z589b/e3Iz89HTEwMEhMTcd999+HEiRNuaqFrDBo0CF27dsUNN9yA3bt3G7e35s/HqlWrMG7cOMTFxZlt1+KzwaDIxNmzZ9HS0mJcYsSgc+fOVuO4BiUlJZL7G/6r5piewp7rYenpp59GTEyM2T/cG2+8EevWrUNmZiZef/117NixAzfddBNaWlo0bb/W7LkevXv3xurVq7F161Z8+OGH0Ov1SElJwe+//w6gdX8+cnJycPjwYcyYMcNsu7d+PtSy9bejpqYGFy5c0OTfnzdbvHgxamtrMXnyZOO25ORkvP/++9i2bRveeecdFBYWYtSoUTh//rwbW+ocXbt2xcqVK/HJJ5/gk08+QWxsLFJTU7F//34A2vx99kanT5/Gf//7X6u/G1p9NjximQ/yTa+99ho2btyIrKwss+Tie+65x/j//fv3x4ABA9C9e3dkZWXh+uuvd0dTnWb48OEYPny48feUlBRcffXV+Ne//oWXX37ZjS1zv1WrVqF///4YNmyY2fbW9PkgcR999BEWLlyIrVu3muXQ3HTTTcb/HzBgAJKTkxEXF4f//Oc/mD59ujua6jS9e/dG7969jb+npKTgt99+w1tvvYUPPvjAjS1zr7Vr1yIiIgKTJk0y267VZ4M9RSaioqLg7++P0tJSs+2lpaXo0qWL6HO6dOkiub/hv2qO6SnsuR4GixcvxmuvvYZvvvkGAwYMkNw3MTERUVFROH78uMNtdiZHrodBQEAABg8ebDzX1vr5qKurw8aNGxX9sfKWz4datv52hIWFoW3btpp83rzRxo0bMWPGDPznP/+xGl60FBERgV69evncZ8OWYcOGGc+1NX4+BEHA6tWr8cADDyAwMFByX3s/GwyKTAQGBmLIkCHIzMw0btPr9cjMzDT7tm9q+PDhZvsDwLfffmvcPyEhAV26dDHbp6amBnv37rV5TE9hz/UALs2mevnll7Ft2zYMHTpU9nV+//13VFRUoGvXrpq021nsvR6mWlpacOjQIeO5tsbPB3CpjEVDQwPuv/9+2dfxls+HWnJ/O7T4vHmbDRs2ID09HRs2bDAr02BLbW0tfvvtN5/7bNhy8OBB47m2xs/Hjh07cPz4cUVfpuz+bDicqu1jNm7cKAQFBQnvv/++8Msvvwh/+ctfhIiICKGkpEQQBEF44IEHhGeeeca4/+7du4U2bdoIixcvFo4ePSosWLBACAgIEA4dOmTc57XXXhMiIiKErVu3Cj///LNw++23CwkJCcKFCxdcfn5qqb0er732mhAYGCh8/PHHwpkzZ4w/58+fFwRBEM6fPy/MnTtX2LNnj1BYWCh89913wjXXXCP07NlTuHjxolvOUQ2112PhwoXC119/Lfz222/Cvn37hHvuuUcIDg4Wjhw5YtynNX0+DEaOHClMmTLFars3fz7Onz8vHDhwQDhw4IAAQFi6dKlw4MABobi4WBAEQXjmmWeEBx54wLh/QUGBEBISIjz55JPC0aNHhRUrVgj+/v7Ctm3bjPvIXV9PpvZ6rF+/XmjTpo2wYsUKs78dVVVVxn2eeOIJISsrSygsLBR2794tjBs3ToiKihLKyspcfn5qqb0eb731lvDZZ58J+fn5wqFDh4S//vWvgp+fn/Ddd98Z9/HWz4faa2Fw//33C8nJyaLH1OqzwaBIxPLly4Urr7xSCAwMFIYNGyb88MMPxsfGjBkjTJs2zWz///znP0KvXr2EwMBAoW/fvsKXX35p9rherxdeeOEFoXPnzkJQUJBw/fXXC3l5ea44FU2ouR5xcXECAKufBQsWCIIgCPX19cL48eOF6OhoISAgQIiLixNmzpzp8f+ITam5Ho8//rhx386dOws333yzsH//frPjtabPhyAIwrFjxwQAwjfffGN1LG/+fBimUFv+GM5/2rRpwpgxY6yeM2jQICEwMFBITEwU1qxZY3VcqevrydRejzFjxkjuLwiXShZ07dpVCAwMFLp16yZMmTJFOH78uGtPzE5qr8frr78udO/eXQgODhY6dOggpKamCv/73/+sjuuNnw97/q1UVVUJbdu2Ff7973+LHlOrz4ZOEARBXd8SERERke9hThERERERGBQRERERAWBQRERERASAQRERERERAAZFRERERAAYFBEREREBYFBEREREBIBBERGRqPj4eCxbtkzRvjqdDp999plT20NEzsegiIiIiAgMiojIwzQ2Nrq7CUTUSjEoIiKHffzxx+jfvz/atm2Ljh07Yty4cairq0Nqaioef/xxs30nTZqEBx980Ph7fHw8Xn75ZaSlpSEsLAx/+ctfkJKSgqefftrseeXl5QgICMDOnTsl2/Lss88iOTnZavvAgQPx0ksvAYCidql15swZ3HTTTWjbti0SExPx8ccf230sInIPBkVE5JAzZ85g6tSp+POf/4yjR48iKysLd955J9Qsq7h48WIMHDgQBw4cwAsvvID77rsPGzduNDvGpk2bEBMTg1GjRkke67777kNOTg5+++0347YjR47g559/xr333qv+BBV64YUX8Kc//Qk//fQT7rvvPtxzzz04evSo016PiLTHoIiIHHLmzBk0NzfjzjvvRHx8PPr3749HH30U7dq1U3yM6667Dk888QS6d++O7t27Y/LkyTh9+jR27dpl3Oejjz7C1KlTodPpJI/Vt29fDBw4EB999JFx2/r165GcnIwePXqoP0GF7r77bsyYMQO9evXCyy+/jKFDh2L58uVOez0i0h6DIiJyyMCBA3H99dejf//+uPvuu/Huu++isrJS1TGGDh1q9nt0dDTGjx+P9evXAwAKCwuxZ88e3HfffYqOd9999xmDIkEQsGHDBsXPtdfw4cOtfmdPEZF3YVBERA7x9/fHt99+i//+97/o06cPli9fjt69e6OwsBB+fn5Ww2hNTU1WxwgNDbXadt999+Hjjz9GU1MTPvroI/Tv3x/9+/dX1KapU6ciLy8P+/fvR3Z2Nk6ePIkpU6YYH1faLiJqXRgUEZHDdDodRowYgYULF+LAgQMIDAzEp59+iujoaJw5c8a4X0tLCw4fPqzomLfffjsuXryIbdu24aOPPlLV03PFFVdgzJgxWL9+PdavX48bbrgBnTp1Mj7uSLts+eGHH6x+v/rqqx06JhG5Vht3N4CIvNvevXuRmZmJ8ePHo1OnTti7dy/Ky8tx9dVXIzQ0FBkZGfjyyy/RvXt3LF26FFVVVYqOGxoaikmTJuGFF17A0aNHMXXqVFXtuu+++7BgwQI0NjbirbfeMnvsuuuus7tdtmzevBlDhw7FyJEjsX79euTk5GDVqlUOHZOIXItBERE5JCwsDDt37sSyZctQU1ODuLg4LFmyBDfddBOamprw008/IS0tDW3atMHf/vY3jB07VvGx77vvPtx8880YPXo0rrzySlXtuuuuuzB79mz4+/tj0qRJZo/9+c9/dqhdYhYuXIiNGzfi0UcfRdeuXbFhwwb06dPHoWMSkWvpBDXzZomIiIh8FHOKiIiIiMCgiIi8zPfff4927drZ/NHa+vXrbb5W3759NX89InIfDp8RkVe5cOECTp06ZfNxrQs0nj9/HqWlpaKPBQQEIC4uTtPXIyL3YVBEREREBA6fEREREQFgUEREREQEgEEREREREQAGRUREREQAGBQRERERAWBQRERERASAQRERERERAAZFRERERACA/w/aBHaw3IXVpAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] @@ -330,7 +334,11 @@ } ], "source": [ - "esc_ep.plot(x='total_pop', y = 'rew', title='reward-population relation', kind='scatter')" + "esc_ep.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='Total population over time', \n", + " kind='scatter',\n", + ")" ] }, { @@ -384,7 +392,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 33, "id": "4024227f-1e2f-468d-8151-8f3759e92ce3", "metadata": {}, "outputs": [ @@ -394,7 +402,7 @@ "" ] }, - "execution_count": 22, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" }, @@ -415,23 +423,23 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 34, "id": "e64e134e-44f4-4546-9b7c-ee3031ba8f69", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 13, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -441,13 +449,16 @@ } ], "source": [ - "\n", - "ppo_ep.plot(x='total_pop', y = 'rew', title='reward-population relation', kind='scatter')" + "ppo_ep.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='Total population over time', \n", + " kind='scatter',\n", + ")" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 35, "id": "489d45a2-0708-4626-9210-3e0c9207cf15", "metadata": { "scrolled": true @@ -474,23 +485,23 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 37, "id": "133dd750-22e1-4895-a4c7-87b87199ffc6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 17, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -500,9 +511,156 @@ } ], "source": [ - "cr_ep.plot(x='t', y = ['rew'], title='total pop. over time under CR')" + "cr_ep.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='Total population over time', \n", + " kind='scatter',\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "5ce8ea08-536d-45d4-b34e-26b9bdd97e29", + "metadata": {}, + "source": [ + "## Focusing on biomass-mean wt scatter plots" ] }, + { + "cell_type": "code", + "execution_count": 42, + "id": "fe696c5e-5bfa-4750-abaf-29fddbb46d77", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 100/100 [00:13<00:00, 7.38it/s]\n", + "100%|██████████| 100/100 [00:13<00:00, 7.66it/s]\n", + "100%|██████████| 100/100 [00:35<00:00, 2.83it/s]\n", + "100%|██████████| 100/100 [00:13<00:00, 7.59it/s]\n" + ] + } + ], + "source": [ + "from tqdm import tqdm\n", + "N = 100\n", + "\n", + "trivial_eps = pd.concat([\n", + " pd.DataFrame(simulate_ep(env, trivp, other_vars=['surv_vul_b']))\n", + " for _ in tqdm(range(N))\n", + "])\n", + "\n", + "esc_eps = pd.concat([\n", + " pd.DataFrame(simulate_ep(env, esc, other_vars=['surv_vul_b']))\n", + " for _ in tqdm(range(N))\n", + "])\n", + "\n", + "ppo_eps = pd.concat([\n", + " pd.DataFrame(simulate_ep(env, ppo, other_vars=['surv_vul_b']))\n", + " for _ in tqdm(range(N))\n", + "])\n", + "\n", + "cr_eps = pd.concat([\n", + " pd.DataFrame(simulate_ep(env, cr, other_vars=['surv_vul_b']))\n", + " for _ in tqdm(range(N))\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "a15b6856-d7a2-438c-80f0-cd0538908efe", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " ,\n", + " ,\n", + " )" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " trivial_eps.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='Unfished surv vul vs mean wt', \n", + " kind='scatter',\n", + " ),\n", + " esc_eps.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='Esc surv vul vs mean wt', \n", + " kind='scatter',\n", + " ),\n", + " cr_eps.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='CR surv vul vs mean wt', \n", + " kind='scatter',\n", + " ),\n", + " ppo_eps.plot(\n", + " x='surv_vul_b', y = 'mean_wt_obs', \n", + " title='RL surv vul vs mean wt', \n", + " kind='scatter',\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87a25e9b-e362-4a7f-bc88-a2d52cb42ffe", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, diff --git a/src/rl4fisheries/agents/cautionary_rule.py b/src/rl4fisheries/agents/cautionary_rule.py index fd82d11..ee7eb19 100644 --- a/src/rl4fisheries/agents/cautionary_rule.py +++ b/src/rl4fisheries/agents/cautionary_rule.py @@ -22,10 +22,6 @@ def __init__(self, env, x1=0, x2=1, y2=1, observed_var='biomass', **kwargs): self.x2_pm1 = self.convert_to_pm1(x2, var_type = self.observed_var) self.y2_pm1 = self.convert_to_pm1(y2, var_type = 'action') - print( - f"{self.x1_pm1:.3f}, {self.x2_pm1:.3f}, {self.y2_pm1:.3f}" - ) - assert x1 <= x2, "CautionaryRule error: x1 <= x2" def convert_to_pm1(self, X, var_type): diff --git a/src/rl4fisheries/agents/const_esc.py b/src/rl4fisheries/agents/const_esc.py index 182b017..f8c78f1 100644 --- a/src/rl4fisheries/agents/const_esc.py +++ b/src/rl4fisheries/agents/const_esc.py @@ -7,9 +7,8 @@ from rl4fisheries.agents.common import isVecObs class ConstEsc: - def __init__(self, env, escapement, observed_var='biomass' **kwargs): + def __init__(self, env, escapement, observed_var='biomass', **kwargs): self.escapement = escapement - self.bounds = bounds self.policy_type = "constant_escapement" self.env = env self.observed_var = observed_var @@ -32,11 +31,11 @@ def predict(self, observation, **kwargs): return np.float32([2 * predicted_effort - 1]), {} - def predict_effort(self, obs): - if obs <= self.escapement or obs == 0: + def predict_effort(self, obs_value): + if obs_value <= self.escapement or obs_value == 0: return 0 else: - return (obs - self.escapement) / obs + return (obs_value - self.escapement) / obs_value def state_to_pop(self, state): return (state + 1 ) / 2 From e85cf9a99ca5452a980d9b829ce00d9fc7b3ed48 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 2 May 2024 18:33:40 +0000 Subject: [PATCH 21/64] Added get_r_devs_v2 option --- src/rl4fisheries/envs/asm_env.py | 23 ++++++++++++++-------- src/rl4fisheries/envs/asm_fns.py | 33 ++++++++++++++++++++++++++++++++ 2 files changed, 48 insertions(+), 8 deletions(-) diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index 6a753e0..41356c5 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -8,7 +8,9 @@ observe_total, observe_total_2o, observe_total_2o_v2, asm_pop_growth, harvest, - render_asm, get_r_devs, + render_asm, + get_r_devs, + get_r_devs_v2, ) # equilibrium dist will in general depend on parameters, need a more robust way @@ -69,13 +71,18 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): 1, self.parameters["n_age"] + 1 ) # vector of ages for calculations self.reproducibility_mode = config.get('reproducibility_mode', False) + self.get_r_devs_version = config.get('get_r_devs_version', 'v1') + self.get_r_devs = {'v1': get_r_devs, 'v2': get_r_devs_v2}[self.get_r_devs_version] if self.reproducibility_mode: - self.fixed_r_devs = get_r_devs( - n_year=config.get("n_year", 1000), - p_big=self.parameters["p_big"], - sdr=self.parameters["sdr"], - rho=self.parameters["rho"], - ) + if "r_devs" in config: + self.fixed_r_devs = config["r_devs"] + else: + self.fixed_r_devs = self.get_r_devs( + n_year=config.get("n_year", 1000), + p_big=self.parameters["p_big"], + sdr=self.parameters["sdr"], + rho=self.parameters["rho"], + ) self.noiseless = config.get('noiseless', False) self.use_custom_vul = config.get('use_custom_vul', False) self.custom_vul = config.get('custom_vul', np.ones(self.parameters["n_age"])) @@ -152,7 +159,7 @@ def reset(self, *, seed=None, options=None): elif self.reproducibility_mode: self.r_devs = self.fixed_r_devs else: - self.r_devs = get_r_devs( + self.r_devs = self.get_r_devs( n_year=self.n_year, p_big=self.parameters["p_big"], sdr=self.parameters["sdr"], diff --git a/src/rl4fisheries/envs/asm_fns.py b/src/rl4fisheries/envs/asm_fns.py index b30c244..eda38cc 100644 --- a/src/rl4fisheries/envs/asm_fns.py +++ b/src/rl4fisheries/envs/asm_fns.py @@ -153,6 +153,39 @@ def get_r_devs(n_year, p_big=0.05, sdr=0.3, rho=0): dev_last = sdr * n_rand[t] + rho * dev_last return r_mult +def get_r_devs_v2(n_year, p_big=0.05, sdr=0.3, rho=0): + """ + f(x) to create recruitment deviates, which are multiplied + by the stock-recruitment prediction in the age-structured model + + args: + n_year: number of deviates required for simulation + p_big: Pr(big year class) + r_big: magnitude of big year class + sdr: sd of recruitment + rho: autocorrelation in recruitment sequence + returns: + vector of recruitment deviates of length n_year + + differs from get_r_devs by having the small-school randomness be a gaussian centered at 1. + """ + def one_rdev(p_big=p_big, r_big_lims=[10,30], r_small_sigma = 1): + x = np.random.binomial(n=2,p=p_big) + return ( + x * np.random.uniform(*r_big_lims) # big school + + (1-x) * max( # small school + 1 + r_small_sigma * np.random.normal(), + 0 + ) + ) + + r_devs = np.float32([1] * n_year) + r_devs[0] = one_rdev() + for t in range(1, n_year): + r_devs[t] = one_rdev() + rho * r_devs[t-1] + return r_devs + + def render_asm(env): if env.render_mode is None: assert env.spec is not None From 50089358ec3ec5b59656655a0e747084cb6cd596 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 2 May 2024 18:34:08 +0000 Subject: [PATCH 22/64] added ray simulator --- src/rl4fisheries/utils/__init__.py | 3 +- src/rl4fisheries/utils/simulation.py | 62 +++++++++++++++++++++++++++- 2 files changed, 63 insertions(+), 2 deletions(-) diff --git a/src/rl4fisheries/utils/__init__.py b/src/rl4fisheries/utils/__init__.py index 30b32da..9b19916 100644 --- a/src/rl4fisheries/utils/__init__.py +++ b/src/rl4fisheries/utils/__init__.py @@ -1 +1,2 @@ -from rl4fisheries.utils.sb3 import sb3_train \ No newline at end of file +from rl4fisheries.utils.sb3 import sb3_train +from rl4fisheries.utils.simulation import evaluate_agent, get_simulator, simulator_old \ No newline at end of file diff --git a/src/rl4fisheries/utils/simulation.py b/src/rl4fisheries/utils/simulation.py index bb230ce..484e0db 100644 --- a/src/rl4fisheries/utils/simulation.py +++ b/src/rl4fisheries/utils/simulation.py @@ -1,4 +1,64 @@ -class simulator: +import numpy as np +import ray + +class evaluate_agent: + def __init__(self, *, agent, env=None, ray_remote=False): + self.agent = agent + self.env = env or agent.env + self.simulator = get_simulator(ray_remote=ray_remote) + self.ray_remote = ray_remote + + def evaluate(self, return_episode_rewards=False, n_eval_episodes=50): + if self.ray_remote: + rewards = ray.get([ + self.simulator.remote(env=self.env, agent=self.agent) + for _ in range(n_eval_episodes) + ]) + if ray.is_initialized(): + ray.shutdown() + else: + rewards = [ + self.simulator.remote(env=self.env, agent=self.agent) + for _ in range(n_eval_episodes) + ] + # + if return_episode_rewards: + return rewards + else: + return np.mean(rewards) + + + +def get_simulator(ray_remote = False): + if ray_remote: + @ray.remote + def simulator(env, agent): + results = [] + episode_reward = 0.0 + observation, _ = env.reset() + for t in range(env.Tmax): + action, _ = agent.predict(observation, deterministic=True) + observation, reward, terminated, done, info = env.step(action) + episode_reward += reward + if terminated or done: + break + return episode_reward + return simulator + else: + def simulator(env, agent): + results = [] + episode_reward = 0.0 + observation, _ = env.reset() + for t in range(env.Tmax): + action, _ = agent.predict(observation, deterministic=True) + observation, reward, terminated, done, info = env.step(action) + episode_reward += reward + if terminated or done: + break + return episode_reward + return simulator + +class simulator_old: def __init__(self, env, agent): self.env = env self.agent = agent From 8dfc89758e8aa5d09492c33e092f4d38e023c52c Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 2 May 2024 18:34:36 +0000 Subject: [PATCH 23/64] now fixed_policy_opt script admits config files for env --- scripts/fixed_policy_opt.py | 38 ++++++++++++++++------------------ scripts/tune_fixed_policies.sh | 12 +++++------ 2 files changed, 24 insertions(+), 26 deletions(-) diff --git a/scripts/fixed_policy_opt.py b/scripts/fixed_policy_opt.py index 5caa900..7403f3f 100644 --- a/scripts/fixed_policy_opt.py +++ b/scripts/fixed_policy_opt.py @@ -5,20 +5,20 @@ parser.add_argument("-v", "--verbose", help="Verbosity of tuning method", type=bool) parser.add_argument("-o", "--opt-algo", choices=["gp", "gbrt"], help="Optimization algo used") parser.add_argument("-ncalls", "--n-calls", help="Number of objective function calls used by optimizing algo", type=int) +parser.add_argument("-f", "--config-file", help="yaml file with env config.") args = parser.parse_args() from huggingface_hub import hf_hub_download, HfApi, login import numpy as np +import yaml from skopt import dump from skopt.space import Real from skopt.utils import use_named_args -from stable_baselines3.common.evaluation import evaluate_policy -from stable_baselines3.common.monitor import Monitor - from rl4fisheries import AsmEnv +from rl4fisheries.utils import evaluate_agent # optimization algo if args.opt_algo == "gp": @@ -39,6 +39,11 @@ from rl4fisheries import CautionaryRule policy_cls = CautionaryRule +# config +with open(args.config_file, "r") as stream: + config_file = yaml.safe_load(stream) + config = config_file["config"] + # optimizing space msy_space = [Real(0.0002, 0.5, name='mortality')] @@ -51,21 +56,17 @@ space = {'msy':msy_space, 'esc':esc_space, 'cr':cr_space}[args.policy] # optimizing function -from stable_baselines3.common.monitor import Monitor - @use_named_args(space) def msy_fn(**params): - agent = Msy(AsmEnv(), mortality=params['mortality']) - env = AsmEnv() - mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100) - return -mean + agent = Msy(AsmEnv(config=config), mortality=params['mortality']) + m_reward = evaluate_agent(agent=agent, ray_remote=True).evaluate(n_eval_episodes=200) + return -m_reward @use_named_args(space) def esc_fn(**params): - agent = ConstEsc(AsmEnv(), escapement=params['escapement']) - env = AsmEnv() - mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100) - return -mean + agent = ConstEsc(AsmEnv(config=config), escapement=params['escapement']) + m_reward = evaluate_agent(agent=agent, ray_remote=True).evaluate(n_eval_episodes=200) + return -m_reward @use_named_args(space) def cr_fn(**params): @@ -73,13 +74,10 @@ def cr_fn(**params): radius = params["radius"] x1 = np.sin(theta) * radius x2 = np.cos(theta) * radius - - assert x1 <= x2, ("CautionaryRule error: x1 < x2, " + str(x1) + ", ", str(x2) ) - - agent = CautionaryRule(AsmEnv(), x1 = x1, x2 = x2, y2 = params["y2"]) - env = AsmEnv() - mean, sd = evaluate_policy(agent, Monitor(env), n_eval_episodes=100) - return -mean + # + agent = CautionaryRule(AsmEnv(config=config), x1 = x1, x2 = x2, y2 = params["y2"]) + m_reward = evaluate_agent(agent=agent, ray_remote=True).evaluate(n_eval_episodes=200) + return -m_reward opt_fn = {'msy':msy_fn, 'esc':esc_fn, 'cr':cr_fn}[args.policy] diff --git a/scripts/tune_fixed_policies.sh b/scripts/tune_fixed_policies.sh index 9d0c2df..7cf6062 100644 --- a/scripts/tune_fixed_policies.sh +++ b/scripts/tune_fixed_policies.sh @@ -8,11 +8,11 @@ cd "$scriptdir" python hf_login.py # gp -python fixed_policy_opt.py -p msy -v True -o gp -nc 100 & -python fixed_policy_opt.py -p esc -v True -o gp -nc 100 & -python fixed_policy_opt.py -p cr -v True -o gp -nc 100 & +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gp -nc 100 & +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gp -nc 100 & +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gp -nc 100 & # gbrt -python fixed_policy_opt.py -p msy -v True -o gbrt -nc 100 & -python fixed_policy_opt.py -p esc -v True -o gbrt -nc 100 & -python fixed_policy_opt.py -p cr -v True -o gbrt -nc 100 & \ No newline at end of file +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gbrt -nc 100 & +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gbrt -nc 100 & +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gbrt -nc 100 & \ No newline at end of file From ed791585d1ef1c920cf61f0097a5b94b0a4140b1 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 2 May 2024 18:34:54 +0000 Subject: [PATCH 24/64] notebooks --- notebooks/optimal-fixed-policy.ipynb | 7084 +++++++++----------------- notebooks/popdyn_tests.ipynb | 337 +- 2 files changed, 2744 insertions(+), 4677 deletions(-) diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index 2aee89d..4c05041 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -32,22 +32,12 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", - "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'rl4fisheries'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 14\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mstable_baselines3\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mevaluation\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m evaluate_policy\n\u001b[1;32m 12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mstable_baselines3\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcommon\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmonitor\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Monitor\n\u001b[0;32m---> 14\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrl4fisheries\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AsmEnv, Msy, ConstEsc, CautionaryRule\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mrl4fisheries\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01menvs\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01masm_fns\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_r_devs, observe_total\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'rl4fisheries'" - ] - } - ], + "metadata": { + "scrolled": true + }, + "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", @@ -68,16 +58,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "236788a7-ed25-46bd-a9b0-f7301e96cacf", "metadata": {}, "outputs": [], "source": [ "# CONFIG = {\"s\": 0.86, \"noiseless\": False, \"testing_harvs\": False}\n", "CONFIG = {\n", - " 'observation_fn_id': 'observe_1o', \n", - " 'n_observs': 1, \n", - " 'wrong_harv_vul': False,\n", + " 'get_r_devs_version': 'v2'\n", "}" ] }, @@ -130,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 4, "id": "38838cb2-44df-404b-9cd8-4ecfc9347dd9", "metadata": {}, "outputs": [], @@ -179,7 +167,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 8, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], @@ -199,7 +187,7 @@ " rews = eval_pol(\n", " policy=agent, \n", " env_cls=AsmEnv, config=CONFIG, \n", - " n_batches=5, batch_size=40\n", + " n_batches=1, batch_size=200\n", " )\n", " return -np.mean(rews)\n", "\n", @@ -211,7 +199,7 @@ " rews = eval_pol(\n", " policy=agent, \n", " env_cls=AsmEnv, config=CONFIG, \n", - " n_batches=5, batch_size=40\n", + " n_batches=1, batch_size=200\n", " )\n", " return -np.mean(rews)\n", "\n", @@ -229,7 +217,7 @@ " policy=agent, \n", " env_cls=AsmEnv, \n", " config=CONFIG, \n", - " n_batches=5, batch_size=40\n", + " n_batches=1, batch_size=200\n", " )\n", " return -np.mean(rews) \n", "\n" @@ -4893,7 +4881,7 @@ ], "source": [ "%%time\n", - "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 300, verbose=True, n_jobs=-1)\n", + "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", "esc_gp.fun, esc_gp.x" ] }, @@ -4902,10 +4890,6 @@ "execution_count": 10, "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -4913,3077 +4897,579 @@ "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:38,545\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.2738\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 2 started. Evaluating function at random point.\n", + "Time taken: 9.8552\n", + "Function value obtained: -335.4193\n", + "Current minimum: -335.4193\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:48,401\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.2374\n", - "Function value obtained: -84.9404\n", - "Current minimum: -84.9404\n", - "Iteration No: 3 started. Evaluating function at random point.\n", + "Time taken: 10.3734\n", + "Function value obtained: -0.0000\n", + "Current minimum: -335.4193\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:58,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.2821\n", - "Function value obtained: -2.8484\n", - "Current minimum: -84.9404\n", - "Iteration No: 4 started. Evaluating function at random point.\n", + "Time taken: 10.6599\n", + "Function value obtained: -427.5246\n", + "Current minimum: -427.5246\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:09,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.2022\n", - "Function value obtained: -1.9672\n", - "Current minimum: -84.9404\n", - "Iteration No: 5 started. Evaluating function at random point.\n", + "Time taken: 10.6912\n", + "Function value obtained: -3.8238\n", + "Current minimum: -427.5246\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:20,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.1629\n", - "Function value obtained: -3.1598\n", - "Current minimum: -84.9404\n", - "Iteration No: 6 started. Evaluating function at random point.\n", + "Time taken: 10.4139\n", + "Function value obtained: -60.5882\n", + "Current minimum: -427.5246\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:30,592\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.1314\n", - "Function value obtained: -75.1009\n", - "Current minimum: -84.9404\n", - "Iteration No: 7 started. Evaluating function at random point.\n", + "Time taken: 9.9004\n", + "Function value obtained: -3.1751\n", + "Current minimum: -427.5246\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:40,491\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.0974\n", - "Function value obtained: -7.0676\n", - "Current minimum: -84.9404\n", - "Iteration No: 8 started. Evaluating function at random point.\n", + "Time taken: 9.9277\n", + "Function value obtained: -5.4295\n", + "Current minimum: -427.5246\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:50,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.1389\n", - "Function value obtained: -77.2938\n", - "Current minimum: -84.9404\n", - "Iteration No: 9 started. Evaluating function at random point.\n", + "Time taken: 10.4066\n", + "Function value obtained: -37.1784\n", + "Current minimum: -427.5246\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:00,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.2380\n", - "Function value obtained: -0.0015\n", - "Current minimum: -84.9404\n", - "Iteration No: 10 started. Evaluating function at random point.\n", + "Time taken: 9.7842\n", + "Function value obtained: -6.5697\n", + "Current minimum: -427.5246\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:10,599\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.3707\n", - "Function value obtained: -0.0000\n", - "Current minimum: -84.9404\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", + "Time taken: 10.2117\n", + "Function value obtained: -3.1815\n", + "Current minimum: -427.5246\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:20,827\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3705\n", - "Function value obtained: -85.6942\n", - "Current minimum: -85.6942\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", + "Time taken: 10.2058\n", + "Function value obtained: -220.1786\n", + "Current minimum: -427.5246\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:31,016\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3672\n", - "Function value obtained: -79.2813\n", - "Current minimum: -85.6942\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", + "Time taken: 10.1665\n", + "Function value obtained: -434.8020\n", + "Current minimum: -434.8020\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:41,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3034\n", - "Function value obtained: -85.8253\n", - "Current minimum: -85.8253\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", + "Time taken: 10.6603\n", + "Function value obtained: -435.4278\n", + "Current minimum: -435.4278\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:51,876\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3911\n", - "Function value obtained: -82.0591\n", - "Current minimum: -85.8253\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", + "Time taken: 10.3507\n", + "Function value obtained: -432.5803\n", + "Current minimum: -435.4278\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:02,216\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4305\n", - "Function value obtained: -81.0534\n", - "Current minimum: -85.8253\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", + "Time taken: 10.7200\n", + "Function value obtained: -434.2554\n", + "Current minimum: -435.4278\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:12,862\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4108\n", - "Function value obtained: -85.8159\n", - "Current minimum: -85.8253\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4462\n", - "Function value obtained: -86.4994\n", - "Current minimum: -86.4994\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4249\n", - "Function value obtained: -84.1290\n", - "Current minimum: -86.4994\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", + "Time taken: 10.0872\n", + "Function value obtained: -438.5429\n", + "Current minimum: -438.5429\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:23,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0968\n", + "Function value obtained: -433.8495\n", + "Current minimum: -438.5429\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:33,164\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4912\n", + "Function value obtained: -437.4978\n", + "Current minimum: -438.5429\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:43,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3692\n", - "Function value obtained: -85.5404\n", - "Current minimum: -86.4994\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", + "Time taken: 10.6329\n", + "Function value obtained: -0.0000\n", + "Current minimum: -438.5429\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:54,293\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4300\n", - "Function value obtained: -84.1605\n", - "Current minimum: -86.4994\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", + "Time taken: 10.3247\n", + "Function value obtained: -433.3639\n", + "Current minimum: -438.5429\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:04,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4671\n", - "Function value obtained: -83.6550\n", - "Current minimum: -86.4994\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", + "Time taken: 10.8444\n", + "Function value obtained: -438.8648\n", + "Current minimum: -438.8648\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:15,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3878\n", - "Function value obtained: -87.2921\n", - "Current minimum: -87.2921\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", + "Time taken: 10.4880\n", + "Function value obtained: -430.0188\n", + "Current minimum: -438.8648\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:26,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4872\n", - "Function value obtained: -85.9602\n", - "Current minimum: -87.2921\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", + "Time taken: 10.1281\n", + "Function value obtained: -436.7534\n", + "Current minimum: -438.8648\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:37,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3882\n", - "Function value obtained: -88.6692\n", - "Current minimum: -88.6692\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", + "Time taken: 11.3385\n", + "Function value obtained: -412.0634\n", + "Current minimum: -438.8648\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:47,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3337\n", - "Function value obtained: -85.1203\n", - "Current minimum: -88.6692\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", + "Time taken: 11.2627\n", + "Function value obtained: -437.4297\n", + "Current minimum: -438.8648\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:58,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2967\n", - "Function value obtained: -85.6372\n", - "Current minimum: -88.6692\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", + "Time taken: 10.4811\n", + "Function value obtained: -435.9596\n", + "Current minimum: -438.8648\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:09,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4511\n", - "Function value obtained: -82.1948\n", - "Current minimum: -88.6692\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", + "Time taken: 10.2521\n", + "Function value obtained: -431.8186\n", + "Current minimum: -438.8648\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:19,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4852\n", - "Function value obtained: -86.3376\n", - "Current minimum: -88.6692\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", + "Time taken: 10.7418\n", + "Function value obtained: -435.4472\n", + "Current minimum: -438.8648\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:30,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3356\n", - "Function value obtained: -85.5868\n", - "Current minimum: -88.6692\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", + "Time taken: 10.5565\n", + "Function value obtained: -428.0797\n", + "Current minimum: -438.8648\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:40,804\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4092\n", - "Function value obtained: -83.8516\n", - "Current minimum: -88.6692\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3688\n", - "Function value obtained: -86.3473\n", - "Current minimum: -88.6692\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3952\n", - "Function value obtained: -86.8939\n", - "Current minimum: -88.6692\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6647\n", - "Function value obtained: -83.0291\n", - "Current minimum: -88.6692\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3723\n", - "Function value obtained: -83.8943\n", - "Current minimum: -88.6692\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3419\n", - "Function value obtained: -84.5014\n", - "Current minimum: -88.6692\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3678\n", - "Function value obtained: -82.5716\n", - "Current minimum: -88.6692\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3051\n", - "Function value obtained: -85.6161\n", - "Current minimum: -88.6692\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3638\n", - "Function value obtained: -86.3558\n", - "Current minimum: -88.6692\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3622\n", - "Function value obtained: -83.8974\n", - "Current minimum: -88.6692\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3498\n", - "Function value obtained: -84.9701\n", - "Current minimum: -88.6692\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4081\n", - "Function value obtained: -84.4675\n", - "Current minimum: -88.6692\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4185\n", - "Function value obtained: -83.7567\n", - "Current minimum: -88.6692\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4727\n", - "Function value obtained: -84.7712\n", - "Current minimum: -88.6692\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5133\n", - "Function value obtained: -83.9677\n", - "Current minimum: -88.6692\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4644\n", - "Function value obtained: -84.7957\n", - "Current minimum: -88.6692\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3936\n", - "Function value obtained: -85.2244\n", - "Current minimum: -88.6692\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3853\n", - "Function value obtained: -84.4571\n", - "Current minimum: -88.6692\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4347\n", - "Function value obtained: -84.5852\n", - "Current minimum: -88.6692\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3642\n", - "Function value obtained: -87.2573\n", - "Current minimum: -88.6692\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4864\n", - "Function value obtained: -84.0021\n", - "Current minimum: -88.6692\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4223\n", - "Function value obtained: -86.9292\n", - "Current minimum: -88.6692\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3931\n", - "Function value obtained: -87.8382\n", - "Current minimum: -88.6692\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4355\n", - "Function value obtained: -81.2581\n", - "Current minimum: -88.6692\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4613\n", - "Function value obtained: -87.3863\n", - "Current minimum: -88.6692\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3895\n", - "Function value obtained: -84.0942\n", - "Current minimum: -88.6692\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5234\n", - "Function value obtained: -85.0784\n", - "Current minimum: -88.6692\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3575\n", - "Function value obtained: -86.3505\n", - "Current minimum: -88.6692\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5053\n", - "Function value obtained: -86.2184\n", - "Current minimum: -88.6692\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3991\n", - "Function value obtained: -86.2284\n", - "Current minimum: -88.6692\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3794\n", - "Function value obtained: -86.4311\n", - "Current minimum: -88.6692\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4880\n", - "Function value obtained: -83.3662\n", - "Current minimum: -88.6692\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4224\n", - "Function value obtained: -83.2335\n", - "Current minimum: -88.6692\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4503\n", - "Function value obtained: -85.2090\n", - "Current minimum: -88.6692\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3703\n", - "Function value obtained: -83.4133\n", - "Current minimum: -88.6692\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3993\n", - "Function value obtained: -87.0669\n", - "Current minimum: -88.6692\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4523\n", - "Function value obtained: -87.1440\n", - "Current minimum: -88.6692\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3843\n", - "Function value obtained: -86.0671\n", - "Current minimum: -88.6692\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4799\n", - "Function value obtained: -88.7753\n", - "Current minimum: -88.7753\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3515\n", - "Function value obtained: -83.6733\n", - "Current minimum: -88.7753\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4462\n", - "Function value obtained: -84.8879\n", - "Current minimum: -88.7753\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3915\n", - "Function value obtained: -85.2340\n", - "Current minimum: -88.7753\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3713\n", - "Function value obtained: -87.2032\n", - "Current minimum: -88.7753\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3523\n", - "Function value obtained: -83.2681\n", - "Current minimum: -88.7753\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4769\n", - "Function value obtained: -84.2288\n", - "Current minimum: -88.7753\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5053\n", - "Function value obtained: -84.2294\n", - "Current minimum: -88.7753\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3957\n", - "Function value obtained: -82.0141\n", - "Current minimum: -88.7753\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3566\n", - "Function value obtained: -84.7554\n", - "Current minimum: -88.7753\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3880\n", - "Function value obtained: -84.1003\n", - "Current minimum: -88.7753\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5084\n", - "Function value obtained: -84.6515\n", - "Current minimum: -88.7753\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4507\n", - "Function value obtained: -88.2300\n", - "Current minimum: -88.7753\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5512\n", - "Function value obtained: -84.8982\n", - "Current minimum: -88.7753\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3564\n", - "Function value obtained: -84.9337\n", - "Current minimum: -88.7753\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4272\n", - "Function value obtained: -86.7523\n", - "Current minimum: -88.7753\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4170\n", - "Function value obtained: -84.3592\n", - "Current minimum: -88.7753\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4294\n", - "Function value obtained: -81.2812\n", - "Current minimum: -88.7753\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4893\n", - "Function value obtained: -84.3031\n", - "Current minimum: -88.7753\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4452\n", - "Function value obtained: -86.8587\n", - "Current minimum: -88.7753\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4892\n", - "Function value obtained: -83.2783\n", - "Current minimum: -88.7753\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4293\n", - "Function value obtained: -86.0555\n", - "Current minimum: -88.7753\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3899\n", - "Function value obtained: -85.7992\n", - "Current minimum: -88.7753\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4762\n", - "Function value obtained: -85.0568\n", - "Current minimum: -88.7753\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4345\n", - "Function value obtained: -85.5949\n", - "Current minimum: -88.7753\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5218\n", - "Function value obtained: -84.1127\n", - "Current minimum: -88.7753\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4572\n", - "Function value obtained: -83.7750\n", - "Current minimum: -88.7753\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4873\n", - "Function value obtained: -86.8196\n", - "Current minimum: -88.7753\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4875\n", - "Function value obtained: -86.7438\n", - "Current minimum: -88.7753\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4341\n", - "Function value obtained: -84.8433\n", - "Current minimum: -88.7753\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4127\n", - "Function value obtained: -82.4445\n", - "Current minimum: -88.7753\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4000\n", - "Function value obtained: -82.6203\n", - "Current minimum: -88.7753\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5646\n", - "Function value obtained: -85.3232\n", - "Current minimum: -88.7753\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4294\n", - "Function value obtained: -84.2406\n", - "Current minimum: -88.7753\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4485\n", - "Function value obtained: -80.7969\n", - "Current minimum: -88.7753\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3693\n", - "Function value obtained: -83.9303\n", - "Current minimum: -88.7753\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3341\n", - "Function value obtained: -79.4459\n", - "Current minimum: -88.7753\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5054\n", - "Function value obtained: -84.3764\n", - "Current minimum: -88.7753\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3530\n", - "Function value obtained: -84.3042\n", - "Current minimum: -88.7753\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 1.1555\n", - "Function value obtained: -86.0511\n", - "Current minimum: -88.7753\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2933\n", - "Function value obtained: -86.4837\n", - "Current minimum: -88.7753\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3160\n", - "Function value obtained: -83.2632\n", - "Current minimum: -88.7753\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2851\n", - "Function value obtained: -86.2764\n", - "Current minimum: -88.7753\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3986\n", - "Function value obtained: -84.9418\n", - "Current minimum: -88.7753\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3763\n", - "Function value obtained: -84.3836\n", - "Current minimum: -88.7753\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5051\n", - "Function value obtained: -85.5648\n", - "Current minimum: -88.7753\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3554\n", - "Function value obtained: -85.3083\n", - "Current minimum: -88.7753\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4003\n", - "Function value obtained: -82.2068\n", - "Current minimum: -88.7753\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4556\n", - "Function value obtained: -79.7834\n", - "Current minimum: -88.7753\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3963\n", - "Function value obtained: -79.6317\n", - "Current minimum: -88.7753\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5650\n", - "Function value obtained: -85.9209\n", - "Current minimum: -88.7753\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4567\n", - "Function value obtained: -83.9391\n", - "Current minimum: -88.7753\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5595\n", - "Function value obtained: -78.9029\n", - "Current minimum: -88.7753\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4266\n", - "Function value obtained: -82.8344\n", - "Current minimum: -88.7753\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4020\n", - "Function value obtained: -83.9858\n", - "Current minimum: -88.7753\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4144\n", - "Function value obtained: -85.5317\n", - "Current minimum: -88.7753\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4749\n", - "Function value obtained: -82.9057\n", - "Current minimum: -88.7753\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4246\n", - "Function value obtained: -84.9213\n", - "Current minimum: -88.7753\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4379\n", - "Function value obtained: -84.9719\n", - "Current minimum: -88.7753\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4319\n", - "Function value obtained: -86.2452\n", - "Current minimum: -88.7753\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4316\n", - "Function value obtained: -83.9911\n", - "Current minimum: -88.7753\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6276\n", - "Function value obtained: -87.3057\n", - "Current minimum: -88.7753\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4583\n", - "Function value obtained: -85.3982\n", - "Current minimum: -88.7753\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5829\n", - "Function value obtained: -84.8705\n", - "Current minimum: -88.7753\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5275\n", - "Function value obtained: -85.0487\n", - "Current minimum: -88.7753\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5128\n", - "Function value obtained: -86.5023\n", - "Current minimum: -88.7753\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4822\n", - "Function value obtained: -83.9732\n", - "Current minimum: -88.7753\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4147\n", - "Function value obtained: -84.4507\n", - "Current minimum: -88.7753\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4708\n", - "Function value obtained: -88.7570\n", - "Current minimum: -88.7753\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4485\n", - "Function value obtained: -85.6765\n", - "Current minimum: -88.7753\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4867\n", - "Function value obtained: -86.0032\n", - "Current minimum: -88.7753\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4112\n", - "Function value obtained: -84.8063\n", - "Current minimum: -88.7753\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4383\n", - "Function value obtained: -83.0949\n", - "Current minimum: -88.7753\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4879\n", - "Function value obtained: -83.9209\n", - "Current minimum: -88.7753\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4293\n", - "Function value obtained: -86.4783\n", - "Current minimum: -88.7753\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4721\n", - "Function value obtained: -84.1926\n", - "Current minimum: -88.7753\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4051\n", - "Function value obtained: -88.4225\n", - "Current minimum: -88.7753\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3753\n", - "Function value obtained: -84.2388\n", - "Current minimum: -88.7753\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6092\n", - "Function value obtained: -84.6202\n", - "Current minimum: -88.7753\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5036\n", - "Function value obtained: -85.0381\n", - "Current minimum: -88.7753\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5213\n", - "Function value obtained: -85.1823\n", - "Current minimum: -88.7753\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4883\n", - "Function value obtained: -84.8191\n", - "Current minimum: -88.7753\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5293\n", - "Function value obtained: -84.6122\n", - "Current minimum: -88.7753\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4194\n", - "Function value obtained: -86.2020\n", - "Current minimum: -88.7753\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4013\n", - "Function value obtained: -83.6851\n", - "Current minimum: -88.7753\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4529\n", - "Function value obtained: -85.1818\n", - "Current minimum: -88.7753\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6050\n", - "Function value obtained: -83.3640\n", - "Current minimum: -88.7753\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4887\n", - "Function value obtained: -83.8857\n", - "Current minimum: -88.7753\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4733\n", - "Function value obtained: -85.9781\n", - "Current minimum: -88.7753\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4233\n", - "Function value obtained: -86.1714\n", - "Current minimum: -88.7753\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3923\n", - "Function value obtained: -84.6146\n", - "Current minimum: -88.7753\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4267\n", - "Function value obtained: -85.8127\n", - "Current minimum: -88.7753\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4167\n", - "Function value obtained: -83.9807\n", - "Current minimum: -88.7753\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3953\n", - "Function value obtained: -84.7165\n", - "Current minimum: -88.7753\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4204\n", - "Function value obtained: -86.2735\n", - "Current minimum: -88.7753\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4264\n", - "Function value obtained: -83.9990\n", - "Current minimum: -88.7753\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3655\n", - "Function value obtained: -85.5030\n", - "Current minimum: -88.7753\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4762\n", - "Function value obtained: -84.4318\n", - "Current minimum: -88.7753\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5290\n", - "Function value obtained: -83.5650\n", - "Current minimum: -88.7753\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5768\n", - "Function value obtained: -83.7536\n", - "Current minimum: -88.7753\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4432\n", - "Function value obtained: -85.6041\n", - "Current minimum: -88.7753\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4792\n", - "Function value obtained: -82.7865\n", - "Current minimum: -88.7753\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4226\n", - "Function value obtained: -87.7634\n", - "Current minimum: -88.7753\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4100\n", - "Function value obtained: -82.4402\n", - "Current minimum: -88.7753\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3907\n", - "Function value obtained: -85.2052\n", - "Current minimum: -88.7753\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4836\n", - "Function value obtained: -86.7284\n", - "Current minimum: -88.7753\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4957\n", - "Function value obtained: -85.3608\n", - "Current minimum: -88.7753\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5068\n", - "Function value obtained: -85.3126\n", - "Current minimum: -88.7753\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5056\n", - "Function value obtained: -86.8896\n", - "Current minimum: -88.7753\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4675\n", - "Function value obtained: -88.4021\n", - "Current minimum: -88.7753\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4960\n", - "Function value obtained: -87.5108\n", - "Current minimum: -88.7753\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3982\n", - "Function value obtained: -87.9028\n", - "Current minimum: -88.7753\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5482\n", - "Function value obtained: -82.8189\n", - "Current minimum: -88.7753\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4298\n", - "Function value obtained: -84.1876\n", - "Current minimum: -88.7753\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4025\n", - "Function value obtained: -85.6067\n", - "Current minimum: -88.7753\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4611\n", - "Function value obtained: -84.4604\n", - "Current minimum: -88.7753\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4176\n", - "Function value obtained: -83.6871\n", - "Current minimum: -88.7753\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4218\n", - "Function value obtained: -85.8311\n", - "Current minimum: -88.7753\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4395\n", - "Function value obtained: -86.7896\n", - "Current minimum: -88.7753\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4326\n", - "Function value obtained: -87.9845\n", - "Current minimum: -88.7753\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5302\n", - "Function value obtained: -83.6515\n", - "Current minimum: -88.7753\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4213\n", - "Function value obtained: -86.1331\n", - "Current minimum: -88.7753\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4315\n", - "Function value obtained: -88.5491\n", - "Current minimum: -88.7753\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4231\n", - "Function value obtained: -82.9554\n", - "Current minimum: -88.7753\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5195\n", - "Function value obtained: -86.4731\n", - "Current minimum: -88.7753\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3332\n", - "Function value obtained: -83.1675\n", - "Current minimum: -88.7753\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3312\n", - "Function value obtained: -84.1838\n", - "Current minimum: -88.7753\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4420\n", - "Function value obtained: -87.4097\n", - "Current minimum: -88.7753\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4707\n", - "Function value obtained: -83.4385\n", - "Current minimum: -88.7753\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4637\n", - "Function value obtained: -85.3367\n", - "Current minimum: -88.7753\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4298\n", - "Function value obtained: -85.7653\n", - "Current minimum: -88.7753\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4964\n", - "Function value obtained: -83.3255\n", - "Current minimum: -88.7753\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4868\n", - "Function value obtained: -85.8886\n", - "Current minimum: -88.7753\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4770\n", - "Function value obtained: -85.2426\n", - "Current minimum: -88.7753\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4131\n", - "Function value obtained: -86.0469\n", - "Current minimum: -88.7753\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4776\n", - "Function value obtained: -83.8412\n", - "Current minimum: -88.7753\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4809\n", - "Function value obtained: -85.9582\n", - "Current minimum: -88.7753\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5408\n", - "Function value obtained: -85.2496\n", - "Current minimum: -88.7753\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4540\n", - "Function value obtained: -87.1598\n", - "Current minimum: -88.7753\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5098\n", - "Function value obtained: -88.3519\n", - "Current minimum: -88.7753\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4384\n", - "Function value obtained: -83.1859\n", - "Current minimum: -88.7753\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5123\n", - "Function value obtained: -88.2460\n", - "Current minimum: -88.7753\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5359\n", - "Function value obtained: -1.9555\n", - "Current minimum: -88.7753\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4553\n", - "Function value obtained: -85.1104\n", - "Current minimum: -88.7753\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4382\n", - "Function value obtained: -83.3690\n", - "Current minimum: -88.7753\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4212\n", - "Function value obtained: -86.3645\n", - "Current minimum: -88.7753\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5351\n", - "Function value obtained: -85.0548\n", - "Current minimum: -88.7753\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4136\n", - "Function value obtained: -87.6862\n", - "Current minimum: -88.7753\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3671\n", - "Function value obtained: -84.1991\n", - "Current minimum: -88.7753\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4252\n", - "Function value obtained: -83.7993\n", - "Current minimum: -88.7753\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4868\n", - "Function value obtained: -85.7197\n", - "Current minimum: -88.7753\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3858\n", - "Function value obtained: -85.5064\n", - "Current minimum: -88.7753\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3968\n", - "Function value obtained: -84.8681\n", - "Current minimum: -88.7753\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4500\n", - "Function value obtained: -83.1133\n", - "Current minimum: -88.7753\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4255\n", - "Function value obtained: -85.2460\n", - "Current minimum: -88.7753\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4709\n", - "Function value obtained: -86.5661\n", - "Current minimum: -88.7753\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4376\n", - "Function value obtained: -86.9153\n", - "Current minimum: -88.7753\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4839\n", - "Function value obtained: -86.7046\n", - "Current minimum: -88.7753\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5190\n", - "Function value obtained: -83.2514\n", - "Current minimum: -88.7753\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4422\n", - "Function value obtained: -86.8100\n", - "Current minimum: -88.7753\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5086\n", - "Function value obtained: -87.9662\n", - "Current minimum: -88.7753\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4060\n", - "Function value obtained: -84.7567\n", - "Current minimum: -88.7753\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5330\n", - "Function value obtained: -87.2429\n", - "Current minimum: -88.7753\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2946\n", - "Function value obtained: -87.2583\n", - "Current minimum: -88.7753\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4330\n", - "Function value obtained: -86.1164\n", - "Current minimum: -88.7753\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3539\n", - "Function value obtained: -83.5643\n", - "Current minimum: -88.7753\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3255\n", - "Function value obtained: -85.4728\n", - "Current minimum: -88.7753\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4302\n", - "Function value obtained: -82.9335\n", - "Current minimum: -88.7753\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5344\n", - "Function value obtained: -86.8290\n", - "Current minimum: -88.7753\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4398\n", - "Function value obtained: -85.2549\n", - "Current minimum: -88.7753\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3549\n", - "Function value obtained: -84.4800\n", - "Current minimum: -88.7753\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3917\n", - "Function value obtained: -81.0330\n", - "Current minimum: -88.7753\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3942\n", - "Function value obtained: -83.7726\n", - "Current minimum: -88.7753\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3860\n", - "Function value obtained: -84.5568\n", - "Current minimum: -88.7753\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3424\n", - "Function value obtained: -83.2933\n", - "Current minimum: -88.7753\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4412\n", - "Function value obtained: -84.1330\n", - "Current minimum: -88.7753\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4131\n", - "Function value obtained: -84.7214\n", - "Current minimum: -88.7753\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4098\n", - "Function value obtained: -82.0758\n", - "Current minimum: -88.7753\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4728\n", - "Function value obtained: -84.5416\n", - "Current minimum: -88.7753\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4175\n", - "Function value obtained: -86.7355\n", - "Current minimum: -88.7753\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4663\n", - "Function value obtained: -85.3541\n", - "Current minimum: -88.7753\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4562\n", - "Function value obtained: -83.6708\n", - "Current minimum: -88.7753\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5194\n", - "Function value obtained: -84.3320\n", - "Current minimum: -88.7753\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4098\n", - "Function value obtained: -83.4144\n", - "Current minimum: -88.7753\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4772\n", - "Function value obtained: -82.3846\n", - "Current minimum: -88.7753\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4379\n", - "Function value obtained: -86.4315\n", - "Current minimum: -88.7753\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5181\n", - "Function value obtained: -85.0385\n", - "Current minimum: -88.7753\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4027\n", - "Function value obtained: -85.4571\n", - "Current minimum: -88.7753\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6383\n", - "Function value obtained: -83.8486\n", - "Current minimum: -88.7753\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4409\n", - "Function value obtained: -85.1107\n", - "Current minimum: -88.7753\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4200\n", - "Function value obtained: -87.1252\n", - "Current minimum: -88.7753\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4187\n", - "Function value obtained: -83.3954\n", - "Current minimum: -88.7753\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4288\n", - "Function value obtained: -85.4210\n", - "Current minimum: -88.7753\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4516\n", - "Function value obtained: -77.1173\n", - "Current minimum: -88.7753\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5318\n", - "Function value obtained: -81.6807\n", - "Current minimum: -88.7753\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3402\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.7753\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4758\n", - "Function value obtained: -86.9722\n", - "Current minimum: -88.7753\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3942\n", - "Function value obtained: -83.7070\n", - "Current minimum: -88.7753\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3956\n", - "Function value obtained: -84.6790\n", - "Current minimum: -88.7753\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3868\n", - "Function value obtained: -83.3753\n", - "Current minimum: -88.7753\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3639\n", - "Function value obtained: -83.2936\n", - "Current minimum: -88.7753\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5800\n", - "Function value obtained: -84.8240\n", - "Current minimum: -88.7753\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3950\n", - "Function value obtained: -81.8256\n", - "Current minimum: -88.7753\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4661\n", - "Function value obtained: -84.8804\n", - "Current minimum: -88.7753\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4392\n", - "Function value obtained: -86.0750\n", - "Current minimum: -88.7753\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4528\n", - "Function value obtained: -87.0051\n", - "Current minimum: -88.7753\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4274\n", - "Function value obtained: -84.9102\n", - "Current minimum: -88.7753\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4485\n", - "Function value obtained: -86.2219\n", - "Current minimum: -88.7753\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4116\n", - "Function value obtained: -84.4210\n", - "Current minimum: -88.7753\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4901\n", - "Function value obtained: -82.6327\n", - "Current minimum: -88.7753\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3865\n", - "Function value obtained: -77.5167\n", - "Current minimum: -88.7753\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3774\n", - "Function value obtained: -84.9690\n", - "Current minimum: -88.7753\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3862\n", - "Function value obtained: -83.6576\n", - "Current minimum: -88.7753\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5494\n", - "Function value obtained: -80.7605\n", - "Current minimum: -88.7753\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4972\n", - "Function value obtained: -83.6298\n", - "Current minimum: -88.7753\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5874\n", - "Function value obtained: -81.1308\n", - "Current minimum: -88.7753\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5012\n", - "Function value obtained: -86.6384\n", - "Current minimum: -88.7753\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4556\n", - "Function value obtained: -82.2282\n", - "Current minimum: -88.7753\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4690\n", - "Function value obtained: -87.2256\n", - "Current minimum: -88.7753\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3679\n", - "Function value obtained: -83.5084\n", - "Current minimum: -88.7753\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4671\n", - "Function value obtained: -87.1797\n", - "Current minimum: -88.7753\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4082\n", - "Function value obtained: -82.9494\n", - "Current minimum: -88.7753\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4070\n", - "Function value obtained: -87.5875\n", - "Current minimum: -88.7753\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4488\n", - "Function value obtained: -84.1121\n", - "Current minimum: -88.7753\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4438\n", - "Function value obtained: -84.7971\n", - "Current minimum: -88.7753\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4100\n", - "Function value obtained: -89.0073\n", - "Current minimum: -89.0073\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4276\n", - "Function value obtained: -84.2889\n", - "Current minimum: -89.0073\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4917\n", - "Function value obtained: -82.3117\n", - "Current minimum: -89.0073\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4100\n", - "Function value obtained: -83.1597\n", - "Current minimum: -89.0073\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5157\n", - "Function value obtained: -87.2920\n", - "Current minimum: -89.0073\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4789\n", - "Function value obtained: -86.9859\n", - "Current minimum: -89.0073\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4337\n", - "Function value obtained: -85.3427\n", - "Current minimum: -89.0073\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4983\n", - "Function value obtained: -83.2631\n", - "Current minimum: -89.0073\n", - "CPU times: user 2min 12s, sys: 27.3 s, total: 2min 39s\n", - "Wall time: 7min 9s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-89.00730788323125, [-1.8835640672410259])" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 300, verbose=True, n_jobs=-1)\n", - "esc_gbrt.fun, esc_gbrt.x" - ] - }, - { - "cell_type": "markdown", - "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", - "metadata": {}, - "source": [ - "### CR" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.3055\n", - "Function value obtained: -27.6420\n", - "Current minimum: -27.6420\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.3289\n", - "Function value obtained: -78.1050\n", - "Current minimum: -78.1050\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.2986\n", - "Function value obtained: -19.7252\n", - "Current minimum: -78.1050\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.2351\n", - "Function value obtained: -44.3313\n", - "Current minimum: -78.1050\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.2662\n", - "Function value obtained: -49.3958\n", - "Current minimum: -78.1050\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.3035\n", - "Function value obtained: -81.1550\n", - "Current minimum: -81.1550\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.3246\n", - "Function value obtained: -38.6728\n", - "Current minimum: -81.1550\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.3186\n", - "Function value obtained: -58.2459\n", - "Current minimum: -81.1550\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.2767\n", - "Function value obtained: -63.2675\n", - "Current minimum: -81.1550\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 6.7294\n", - "Function value obtained: -13.7136\n", - "Current minimum: -81.1550\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6489\n", - "Function value obtained: -79.4565\n", - "Current minimum: -81.1550\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6055\n", - "Function value obtained: -0.0000\n", - "Current minimum: -81.1550\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6350\n", - "Function value obtained: -0.0000\n", - "Current minimum: -81.1550\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6692\n", - "Function value obtained: -79.6332\n", - "Current minimum: -81.1550\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6754\n", - "Function value obtained: -74.3325\n", - "Current minimum: -81.1550\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5171\n", - "Function value obtained: -82.1995\n", - "Current minimum: -82.1995\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7444\n", - "Function value obtained: -76.4244\n", - "Current minimum: -82.1995\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3227\n", - "Function value obtained: -59.0022\n", - "Current minimum: -82.1995\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4925\n", - "Function value obtained: -79.8453\n", - "Current minimum: -82.1995\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5988\n", - "Function value obtained: -82.0734\n", - "Current minimum: -82.1995\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5444\n", - "Function value obtained: -82.1329\n", - "Current minimum: -82.1995\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5446\n", - "Function value obtained: -75.1359\n", - "Current minimum: -82.1995\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4972\n", - "Function value obtained: -47.4599\n", - "Current minimum: -82.1995\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5302\n", - "Function value obtained: -82.9885\n", - "Current minimum: -82.9885\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4491\n", - "Function value obtained: -79.8435\n", - "Current minimum: -82.9885\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6897\n", - "Function value obtained: -78.2639\n", - "Current minimum: -82.9885\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4834\n", - "Function value obtained: -79.4805\n", - "Current minimum: -82.9885\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4405\n", - "Function value obtained: -31.7971\n", - "Current minimum: -82.9885\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5430\n", - "Function value obtained: -81.7057\n", - "Current minimum: -82.9885\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5597\n", - "Function value obtained: -86.2651\n", - "Current minimum: -86.2651\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3970\n", - "Function value obtained: -84.6473\n", - "Current minimum: -86.2651\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5765\n", - "Function value obtained: -85.6389\n", - "Current minimum: -86.2651\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5050\n", - "Function value obtained: -80.7363\n", - "Current minimum: -86.2651\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4977\n", - "Function value obtained: -81.0955\n", - "Current minimum: -86.2651\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5693\n", - "Function value obtained: -1.9364\n", - "Current minimum: -86.2651\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6156\n", - "Function value obtained: -83.5928\n", - "Current minimum: -86.2651\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5964\n", - "Function value obtained: -81.4378\n", - "Current minimum: -86.2651\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5503\n", - "Function value obtained: -83.7283\n", - "Current minimum: -86.2651\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5272\n", - "Function value obtained: -84.4892\n", - "Current minimum: -86.2651\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6030\n", - "Function value obtained: -83.2422\n", - "Current minimum: -86.2651\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5581\n", - "Function value obtained: -84.7703\n", - "Current minimum: -86.2651\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5818\n", - "Function value obtained: -0.0000\n", - "Current minimum: -86.2651\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5588\n", - "Function value obtained: -86.1378\n", - "Current minimum: -86.2651\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7102\n", - "Function value obtained: -87.6390\n", - "Current minimum: -87.6390\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7003\n", - "Function value obtained: -88.1836\n", - "Current minimum: -88.1836\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7084\n", - "Function value obtained: -88.2088\n", - "Current minimum: -88.2088\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6072\n", - "Function value obtained: -84.0442\n", - "Current minimum: -88.2088\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5923\n", - "Function value obtained: -83.8470\n", - "Current minimum: -88.2088\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7308\n", - "Function value obtained: -86.4331\n", - "Current minimum: -88.2088\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6601\n", - "Function value obtained: -84.3033\n", - "Current minimum: -88.2088\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6979\n", - "Function value obtained: -88.4533\n", - "Current minimum: -88.4533\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5749\n", - "Function value obtained: -84.0851\n", - "Current minimum: -88.4533\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6064\n", - "Function value obtained: -84.9920\n", - "Current minimum: -88.4533\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6048\n", - "Function value obtained: -84.2240\n", - "Current minimum: -88.4533\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6681\n", - "Function value obtained: -83.8135\n", - "Current minimum: -88.4533\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6173\n", - "Function value obtained: -2.3999\n", - "Current minimum: -88.4533\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7242\n", - "Function value obtained: -83.6010\n", - "Current minimum: -88.4533\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5484\n", - "Function value obtained: -86.3004\n", - "Current minimum: -88.4533\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6542\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.4533\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7897\n", - "Function value obtained: -81.3552\n", - "Current minimum: -88.4533\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7200\n", - "Function value obtained: -77.9104\n", - "Current minimum: -88.4533\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7528\n", - "Function value obtained: -84.1339\n", - "Current minimum: -88.4533\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7421\n", - "Function value obtained: -3.8739\n", - "Current minimum: -88.4533\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7754\n", - "Function value obtained: -84.1307\n", - "Current minimum: -88.4533\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7195\n", - "Function value obtained: -78.8474\n", - "Current minimum: -88.4533\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7647\n", - "Function value obtained: -87.5901\n", - "Current minimum: -88.4533\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8416\n", - "Function value obtained: -84.6699\n", - "Current minimum: -88.4533\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7751\n", - "Function value obtained: -82.5775\n", - "Current minimum: -88.4533\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7313\n", - "Function value obtained: -88.1452\n", - "Current minimum: -88.4533\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9032\n", - "Function value obtained: -85.1442\n", - "Current minimum: -88.4533\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7385\n", - "Function value obtained: -2.5050\n", - "Current minimum: -88.4533\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7224\n", - "Function value obtained: -82.2524\n", - "Current minimum: -88.4533\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7859\n", - "Function value obtained: -74.2668\n", - "Current minimum: -88.4533\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8074\n", - "Function value obtained: -76.8367\n", - "Current minimum: -88.4533\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7701\n", - "Function value obtained: -90.6333\n", - "Current minimum: -90.6333\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8479\n", - "Function value obtained: -85.4348\n", - "Current minimum: -90.6333\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8363\n", - "Function value obtained: -82.3339\n", - "Current minimum: -90.6333\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8753\n", - "Function value obtained: -85.6496\n", - "Current minimum: -90.6333\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8171\n", - "Function value obtained: -85.2793\n", - "Current minimum: -90.6333\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8682\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0042\n", - "Function value obtained: -72.8643\n", - "Current minimum: -90.6333\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8247\n", - "Function value obtained: -36.2201\n", - "Current minimum: -90.6333\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9199\n", - "Function value obtained: -52.9810\n", - "Current minimum: -90.6333\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9531\n", - "Function value obtained: -82.3026\n", - "Current minimum: -90.6333\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8739\n", - "Function value obtained: -85.8179\n", - "Current minimum: -90.6333\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8679\n", - "Function value obtained: -2.7283\n", - "Current minimum: -90.6333\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9346\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9970\n", - "Function value obtained: -85.0913\n", - "Current minimum: -90.6333\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9889\n", - "Function value obtained: -86.0498\n", - "Current minimum: -90.6333\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9690\n", - "Function value obtained: -89.3086\n", - "Current minimum: -90.6333\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0585\n", - "Function value obtained: -87.4380\n", - "Current minimum: -90.6333\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2492\n", - "Function value obtained: -79.2090\n", - "Current minimum: -90.6333\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0783\n", - "Function value obtained: -83.0764\n", - "Current minimum: -90.6333\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0430\n", - "Function value obtained: -86.2792\n", - "Current minimum: -90.6333\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1258\n", - "Function value obtained: -82.8770\n", - "Current minimum: -90.6333\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0408\n", - "Function value obtained: -82.4791\n", - "Current minimum: -90.6333\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0456\n", - "Function value obtained: -85.6827\n", - "Current minimum: -90.6333\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0294\n", - "Function value obtained: -74.7308\n", - "Current minimum: -90.6333\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1141\n", - "Function value obtained: -83.3760\n", - "Current minimum: -90.6333\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2029\n", - "Function value obtained: -14.3625\n", - "Current minimum: -90.6333\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1955\n", - "Function value obtained: -71.1589\n", - "Current minimum: -90.6333\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2321\n", - "Function value obtained: -77.2377\n", - "Current minimum: -90.6333\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2387\n", - "Function value obtained: -77.7340\n", - "Current minimum: -90.6333\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1820\n", - "Function value obtained: -83.7139\n", - "Current minimum: -90.6333\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2461\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2158\n", - "Function value obtained: -3.9035\n", - "Current minimum: -90.6333\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2611\n", - "Function value obtained: -75.1242\n", - "Current minimum: -90.6333\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3445\n", - "Function value obtained: -85.5275\n", - "Current minimum: -90.6333\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2808\n", - "Function value obtained: -84.5770\n", - "Current minimum: -90.6333\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2629\n", - "Function value obtained: -85.4486\n", - "Current minimum: -90.6333\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2529\n", - "Function value obtained: -75.6998\n", - "Current minimum: -90.6333\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2940\n", - "Function value obtained: -84.5648\n", - "Current minimum: -90.6333\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2838\n", - "Function value obtained: -70.1448\n", - "Current minimum: -90.6333\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4314\n", - "Function value obtained: -86.5986\n", - "Current minimum: -90.6333\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2736\n", - "Function value obtained: -83.5688\n", - "Current minimum: -90.6333\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4588\n", - "Function value obtained: -85.3449\n", - "Current minimum: -90.6333\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3671\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3850\n", - "Function value obtained: -84.6747\n", - "Current minimum: -90.6333\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4507\n", - "Function value obtained: -2.0290\n", - "Current minimum: -90.6333\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3261\n", - "Function value obtained: -84.2602\n", - "Current minimum: -90.6333\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4539\n", - "Function value obtained: -82.9736\n", - "Current minimum: -90.6333\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4714\n", - "Function value obtained: -67.7069\n", - "Current minimum: -90.6333\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3809\n", - "Function value obtained: -80.7035\n", - "Current minimum: -90.6333\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4970\n", - "Function value obtained: -81.0539\n", - "Current minimum: -90.6333\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5194\n", - "Function value obtained: -77.8282\n", - "Current minimum: -90.6333\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5481\n", - "Function value obtained: -85.7514\n", - "Current minimum: -90.6333\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6020\n", - "Function value obtained: -58.3485\n", - "Current minimum: -90.6333\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6162\n", - "Function value obtained: -84.7989\n", - "Current minimum: -90.6333\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6023\n", - "Function value obtained: -83.7495\n", - "Current minimum: -90.6333\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6529\n", - "Function value obtained: -84.6838\n", - "Current minimum: -90.6333\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6517\n", - "Function value obtained: -81.3237\n", - "Current minimum: -90.6333\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5658\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6196\n", - "Function value obtained: -57.2674\n", - "Current minimum: -90.6333\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5497\n", - "Function value obtained: -82.8458\n", - "Current minimum: -90.6333\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7238\n", - "Function value obtained: -80.1184\n", - "Current minimum: -90.6333\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8476\n", - "Function value obtained: -83.7794\n", - "Current minimum: -90.6333\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8646\n", - "Function value obtained: -83.6890\n", - "Current minimum: -90.6333\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6516\n", - "Function value obtained: -11.3171\n", - "Current minimum: -90.6333\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7437\n", - "Function value obtained: -82.8761\n", - "Current minimum: -90.6333\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6597\n", - "Function value obtained: -86.4469\n", - "Current minimum: -90.6333\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7797\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6914\n", - "Function value obtained: -84.1730\n", - "Current minimum: -90.6333\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8246\n", - "Function value obtained: -78.3581\n", - "Current minimum: -90.6333\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8528\n", - "Function value obtained: -86.4290\n", - "Current minimum: -90.6333\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7967\n", - "Function value obtained: -83.3510\n", - "Current minimum: -90.6333\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7849\n", - "Function value obtained: -83.6486\n", - "Current minimum: -90.6333\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8430\n", - "Function value obtained: -55.1289\n", - "Current minimum: -90.6333\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9347\n", - "Function value obtained: -85.6819\n", - "Current minimum: -90.6333\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7961\n", - "Function value obtained: -83.8089\n", - "Current minimum: -90.6333\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8090\n", - "Function value obtained: -83.1695\n", - "Current minimum: -90.6333\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9021\n", - "Function value obtained: -11.0483\n", - "Current minimum: -90.6333\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7946\n", - "Function value obtained: -85.6196\n", - "Current minimum: -90.6333\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9110\n", - "Function value obtained: -83.9758\n", - "Current minimum: -90.6333\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9064\n", - "Function value obtained: -85.1906\n", - "Current minimum: -90.6333\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0321\n", - "Function value obtained: -87.8375\n", - "Current minimum: -90.6333\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8503\n", - "Function value obtained: -85.1706\n", - "Current minimum: -90.6333\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8713\n", - "Function value obtained: -86.7744\n", - "Current minimum: -90.6333\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9642\n", - "Function value obtained: -88.2608\n", - "Current minimum: -90.6333\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9760\n", - "Function value obtained: -85.5418\n", - "Current minimum: -90.6333\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0818\n", - "Function value obtained: -83.7893\n", - "Current minimum: -90.6333\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1793\n", - "Function value obtained: -86.5298\n", - "Current minimum: -90.6333\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0893\n", - "Function value obtained: -85.0591\n", - "Current minimum: -90.6333\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0569\n", - "Function value obtained: -85.5105\n", - "Current minimum: -90.6333\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1089\n", - "Function value obtained: -86.4030\n", - "Current minimum: -90.6333\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1090\n", - "Function value obtained: -85.1444\n", - "Current minimum: -90.6333\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2387\n", - "Function value obtained: -88.1799\n", - "Current minimum: -90.6333\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0989\n", - "Function value obtained: -84.9582\n", - "Current minimum: -90.6333\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1239\n", - "Function value obtained: -89.2391\n", - "Current minimum: -90.6333\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1619\n", - "Function value obtained: -84.0053\n", - "Current minimum: -90.6333\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1452\n", - "Function value obtained: -83.0798\n", - "Current minimum: -90.6333\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2143\n", - "Function value obtained: -88.2145\n", - "Current minimum: -90.6333\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1834\n", - "Function value obtained: -85.2621\n", - "Current minimum: -90.6333\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3020\n", - "Function value obtained: -87.8510\n", - "Current minimum: -90.6333\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2385\n", - "Function value obtained: -88.9162\n", - "Current minimum: -90.6333\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2649\n", - "Function value obtained: -86.9675\n", - "Current minimum: -90.6333\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2222\n", - "Function value obtained: -83.9728\n", - "Current minimum: -90.6333\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2621\n", - "Function value obtained: -87.8963\n", - "Current minimum: -90.6333\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2759\n", - "Function value obtained: -84.1823\n", - "Current minimum: -90.6333\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3226\n", - "Function value obtained: -86.6570\n", - "Current minimum: -90.6333\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3956\n", - "Function value obtained: -88.0181\n", - "Current minimum: -90.6333\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3426\n", - "Function value obtained: -83.0062\n", - "Current minimum: -90.6333\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5089\n", - "Function value obtained: -85.3005\n", - "Current minimum: -90.6333\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3370\n", - "Function value obtained: -83.4699\n", - "Current minimum: -90.6333\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4299\n", - "Function value obtained: -86.1810\n", - "Current minimum: -90.6333\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5185\n", - "Function value obtained: -85.4634\n", - "Current minimum: -90.6333\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5824\n", - "Function value obtained: -84.4536\n", - "Current minimum: -90.6333\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5014\n", - "Function value obtained: -88.0504\n", - "Current minimum: -90.6333\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4922\n", - "Function value obtained: -87.6193\n", - "Current minimum: -90.6333\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6882\n", - "Function value obtained: -87.6822\n", - "Current minimum: -90.6333\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5456\n", - "Function value obtained: -84.8614\n", - "Current minimum: -90.6333\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5422\n", - "Function value obtained: -87.8404\n", - "Current minimum: -90.6333\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6575\n", - "Function value obtained: -84.9520\n", - "Current minimum: -90.6333\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6065\n", - "Function value obtained: -84.7831\n", - "Current minimum: -90.6333\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7370\n", - "Function value obtained: -84.4722\n", - "Current minimum: -90.6333\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7130\n", - "Function value obtained: -87.2530\n", - "Current minimum: -90.6333\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6288\n", - "Function value obtained: -84.8944\n", - "Current minimum: -90.6333\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7870\n", - "Function value obtained: -87.7330\n", - "Current minimum: -90.6333\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7568\n", - "Function value obtained: -87.8071\n", - "Current minimum: -90.6333\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8266\n", - "Function value obtained: -82.9887\n", - "Current minimum: -90.6333\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8193\n", - "Function value obtained: -85.0844\n", - "Current minimum: -90.6333\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7509\n", - "Function value obtained: -87.3898\n", - "Current minimum: -90.6333\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8625\n", - "Function value obtained: -83.5116\n", - "Current minimum: -90.6333\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8594\n", - "Function value obtained: -84.4034\n", - "Current minimum: -90.6333\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9295\n", - "Function value obtained: -88.9795\n", - "Current minimum: -90.6333\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9030\n", - "Function value obtained: -85.8064\n", - "Current minimum: -90.6333\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9488\n", - "Function value obtained: -88.4653\n", - "Current minimum: -90.6333\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8623\n", - "Function value obtained: -86.9521\n", - "Current minimum: -90.6333\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8212\n", - "Function value obtained: -88.2343\n", - "Current minimum: -90.6333\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9604\n", - "Function value obtained: -86.4872\n", - "Current minimum: -90.6333\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9938\n", - "Function value obtained: -86.5157\n", - "Current minimum: -90.6333\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8944\n", - "Function value obtained: -87.9709\n", - "Current minimum: -90.6333\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0389\n", - "Function value obtained: -83.9614\n", - "Current minimum: -90.6333\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1472\n", - "Function value obtained: -83.4505\n", - "Current minimum: -90.6333\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1988\n", - "Function value obtained: -88.4951\n", - "Current minimum: -90.6333\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1860\n", - "Function value obtained: -85.7315\n", - "Current minimum: -90.6333\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0564\n", - "Function value obtained: -86.7680\n", - "Current minimum: -90.6333\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2051\n", - "Function value obtained: -86.0125\n", - "Current minimum: -90.6333\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1440\n", - "Function value obtained: -84.4325\n", - "Current minimum: -90.6333\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2515\n", - "Function value obtained: -83.7888\n", - "Current minimum: -90.6333\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1997\n", - "Function value obtained: -85.1757\n", - "Current minimum: -90.6333\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1929\n", - "Function value obtained: -82.7933\n", - "Current minimum: -90.6333\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2707\n", - "Function value obtained: -84.3591\n", - "Current minimum: -90.6333\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2861\n", - "Function value obtained: -84.6210\n", - "Current minimum: -90.6333\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3462\n", - "Function value obtained: -86.3491\n", - "Current minimum: -90.6333\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4049\n", - "Function value obtained: -85.1895\n", - "Current minimum: -90.6333\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3751\n", - "Function value obtained: -84.9130\n", - "Current minimum: -90.6333\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4479\n", - "Function value obtained: -84.6399\n", - "Current minimum: -90.6333\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5505\n", - "Function value obtained: -86.8603\n", - "Current minimum: -90.6333\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6236\n", - "Function value obtained: -84.5484\n", - "Current minimum: -90.6333\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4163\n", - "Function value obtained: -85.6712\n", - "Current minimum: -90.6333\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6296\n", - "Function value obtained: -88.0456\n", - "Current minimum: -90.6333\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4658\n", - "Function value obtained: -87.9592\n", - "Current minimum: -90.6333\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6268\n", - "Function value obtained: -87.7705\n", - "Current minimum: -90.6333\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4828\n", - "Function value obtained: -84.6185\n", - "Current minimum: -90.6333\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6933\n", - "Function value obtained: -83.6364\n", - "Current minimum: -90.6333\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4868\n", - "Function value obtained: -86.9525\n", - "Current minimum: -90.6333\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7072\n", - "Function value obtained: -85.5208\n", - "Current minimum: -90.6333\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6665\n", - "Function value obtained: -84.9699\n", - "Current minimum: -90.6333\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4370\n", - "Function value obtained: -85.0854\n", - "Current minimum: -90.6333\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6051\n", - "Function value obtained: -86.2595\n", - "Current minimum: -90.6333\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6382\n", - "Function value obtained: -86.4817\n", - "Current minimum: -90.6333\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8350\n", - "Function value obtained: -83.1569\n", - "Current minimum: -90.6333\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6788\n", - "Function value obtained: -86.6800\n", - "Current minimum: -90.6333\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7233\n", - "Function value obtained: -85.5632\n", - "Current minimum: -90.6333\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7751\n", - "Function value obtained: -85.7283\n", - "Current minimum: -90.6333\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7752\n", - "Function value obtained: -85.8422\n", - "Current minimum: -90.6333\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7446\n", - "Function value obtained: -87.3973\n", - "Current minimum: -90.6333\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8226\n", - "Function value obtained: -86.2009\n", - "Current minimum: -90.6333\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2632\n", - "Function value obtained: -86.0677\n", - "Current minimum: -90.6333\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1870\n", - "Function value obtained: -85.0422\n", - "Current minimum: -90.6333\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0518\n", - "Function value obtained: -86.9540\n", - "Current minimum: -90.6333\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0203\n", - "Function value obtained: -83.2860\n", - "Current minimum: -90.6333\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0728\n", - "Function value obtained: -86.5753\n", - "Current minimum: -90.6333\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0231\n", - "Function value obtained: -87.2729\n", - "Current minimum: -90.6333\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1772\n", - "Function value obtained: -84.3028\n", - "Current minimum: -90.6333\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1883\n", - "Function value obtained: -84.6384\n", - "Current minimum: -90.6333\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2135\n", - "Function value obtained: -84.3169\n", - "Current minimum: -90.6333\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0527\n", - "Function value obtained: -85.2478\n", - "Current minimum: -90.6333\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1900\n", - "Function value obtained: -86.1178\n", - "Current minimum: -90.6333\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3379\n", - "Function value obtained: -86.5867\n", - "Current minimum: -90.6333\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3295\n", - "Function value obtained: -84.9588\n", - "Current minimum: -90.6333\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2179\n", - "Function value obtained: -86.0880\n", - "Current minimum: -90.6333\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2905\n", - "Function value obtained: -86.5985\n", - "Current minimum: -90.6333\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2963\n", - "Function value obtained: -84.9976\n", - "Current minimum: -90.6333\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3160\n", - "Function value obtained: -86.9113\n", - "Current minimum: -90.6333\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3405\n", - "Function value obtained: -86.0184\n", - "Current minimum: -90.6333\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3936\n", - "Function value obtained: -83.4898\n", - "Current minimum: -90.6333\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5504\n", - "Function value obtained: -87.5537\n", - "Current minimum: -90.6333\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5918\n", - "Function value obtained: -86.3580\n", - "Current minimum: -90.6333\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6319\n", - "Function value obtained: -86.8754\n", - "Current minimum: -90.6333\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6179\n", - "Function value obtained: -87.3622\n", - "Current minimum: -90.6333\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5324\n", - "Function value obtained: -87.1565\n", - "Current minimum: -90.6333\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5720\n", - "Function value obtained: -89.2305\n", - "Current minimum: -90.6333\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8214\n", - "Function value obtained: -86.7361\n", - "Current minimum: -90.6333\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7659\n", - "Function value obtained: -84.9475\n", - "Current minimum: -90.6333\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8156\n", - "Function value obtained: -85.5211\n", - "Current minimum: -90.6333\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7959\n", - "Function value obtained: -84.9771\n", - "Current minimum: -90.6333\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5755\n", - "Function value obtained: -88.0128\n", - "Current minimum: -90.6333\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0321\n", - "Function value obtained: -85.9124\n", - "Current minimum: -90.6333\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8723\n", - "Function value obtained: -85.1234\n", - "Current minimum: -90.6333\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9973\n", - "Function value obtained: -84.9108\n", - "Current minimum: -90.6333\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0118\n", - "Function value obtained: -87.5869\n", - "Current minimum: -90.6333\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1184\n", - "Function value obtained: -87.8984\n", - "Current minimum: -90.6333\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9292\n", - "Function value obtained: -84.3207\n", - "Current minimum: -90.6333\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1385\n", - "Function value obtained: -87.6335\n", - "Current minimum: -90.6333\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1387\n", - "Function value obtained: -86.9994\n", - "Current minimum: -90.6333\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3565\n", - "Function value obtained: -85.1528\n", - "Current minimum: -90.6333\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0750\n", - "Function value obtained: -84.0035\n", - "Current minimum: -90.6333\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5232\n", - "Function value obtained: -85.4554\n", - "Current minimum: -90.6333\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4644\n", - "Function value obtained: -87.0136\n", - "Current minimum: -90.6333\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4834\n", - "Function value obtained: -84.7633\n", - "Current minimum: -90.6333\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4423\n", - "Function value obtained: -85.8865\n", - "Current minimum: -90.6333\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1903\n", - "Function value obtained: -88.6420\n", - "Current minimum: -90.6333\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4984\n", - "Function value obtained: -87.5296\n", - "Current minimum: -90.6333\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5800\n", - "Function value obtained: -84.3343\n", - "Current minimum: -90.6333\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4310\n", - "Function value obtained: -84.2970\n", - "Current minimum: -90.6333\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6753\n", - "Function value obtained: -83.7032\n", - "Current minimum: -90.6333\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5152\n", - "Function value obtained: -85.6559\n", - "Current minimum: -90.6333\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1695\n", - "Function value obtained: -86.4604\n", - "Current minimum: -90.6333\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6265\n", - "Function value obtained: -83.0904\n", - "Current minimum: -90.6333\n", - "CPU times: user 2h 52min 17s, sys: 1h 11min 30s, total: 4h 3min 48s\n", - "Wall time: 16min 21s\n" + "Time taken: 10.1785\n", + "Function value obtained: -436.0723\n", + "Current minimum: -438.8648\n", + "CPU times: user 34.4 s, sys: 51.8 s, total: 1min 26s\n", + "Wall time: 5min 12s\n" ] }, { "data": { "text/plain": [ - "(-90.63333622820284,\n", - " [-1.7521564679093693, 0.5440615729465406, 0.29119675741251316])" + "(-438.8647758926598, [-0.08374338090501876])" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 300, verbose=True, n_jobs=-1)\n", - "cr_gp.fun, cr_gp.x" + "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "esc_gbrt.fun, esc_gbrt.x" + ] + }, + { + "cell_type": "markdown", + "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", + "metadata": {}, + "source": [ + "### CR" ] }, { "cell_type": "code", - "execution_count": 12, - "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", + "execution_count": 11, + "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", "metadata": { "collapsed": true, "jupyter": { @@ -7998,1523 +5484,2096 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.3671\n", - "Function value obtained: -80.5640\n", - "Current minimum: -80.5640\n", + "Time taken: 1.3055\n", + "Function value obtained: -27.6420\n", + "Current minimum: -27.6420\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.3095\n", - "Function value obtained: -0.0000\n", - "Current minimum: -80.5640\n", + "Time taken: 1.3289\n", + "Function value obtained: -78.1050\n", + "Current minimum: -78.1050\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.2839\n", - "Function value obtained: -39.9405\n", - "Current minimum: -80.5640\n", + "Time taken: 1.2986\n", + "Function value obtained: -19.7252\n", + "Current minimum: -78.1050\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.2410\n", - "Function value obtained: -1.9526\n", - "Current minimum: -80.5640\n", + "Time taken: 1.2351\n", + "Function value obtained: -44.3313\n", + "Current minimum: -78.1050\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.2487\n", - "Function value obtained: -42.9769\n", - "Current minimum: -80.5640\n", + "Time taken: 1.2662\n", + "Function value obtained: -49.3958\n", + "Current minimum: -78.1050\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.3445\n", - "Function value obtained: -22.6509\n", - "Current minimum: -80.5640\n", + "Time taken: 1.3035\n", + "Function value obtained: -81.1550\n", + "Current minimum: -81.1550\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.2643\n", - "Function value obtained: -33.6349\n", - "Current minimum: -80.5640\n", + "Time taken: 1.3246\n", + "Function value obtained: -38.6728\n", + "Current minimum: -81.1550\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.2897\n", - "Function value obtained: -15.0069\n", - "Current minimum: -80.5640\n", + "Time taken: 1.3186\n", + "Function value obtained: -58.2459\n", + "Current minimum: -81.1550\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.3150\n", - "Function value obtained: -64.6252\n", - "Current minimum: -80.5640\n", + "Time taken: 1.2767\n", + "Function value obtained: -63.2675\n", + "Current minimum: -81.1550\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.5217\n", - "Function value obtained: -3.4288\n", - "Current minimum: -80.5640\n", + "Time taken: 6.7294\n", + "Function value obtained: -13.7136\n", + "Current minimum: -81.1550\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5133\n", - "Function value obtained: -68.5431\n", - "Current minimum: -80.5640\n", + "Time taken: 2.6489\n", + "Function value obtained: -79.4565\n", + "Current minimum: -81.1550\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4744\n", - "Function value obtained: -85.3241\n", - "Current minimum: -85.3241\n", + "Time taken: 2.6055\n", + "Function value obtained: -0.0000\n", + "Current minimum: -81.1550\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4270\n", - "Function value obtained: -84.1832\n", - "Current minimum: -85.3241\n", + "Time taken: 2.6350\n", + "Function value obtained: -0.0000\n", + "Current minimum: -81.1550\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4482\n", - "Function value obtained: -81.6088\n", - "Current minimum: -85.3241\n", + "Time taken: 2.6692\n", + "Function value obtained: -79.6332\n", + "Current minimum: -81.1550\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5109\n", - "Function value obtained: -44.6087\n", - "Current minimum: -85.3241\n", + "Time taken: 2.6754\n", + "Function value obtained: -74.3325\n", + "Current minimum: -81.1550\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5100\n", - "Function value obtained: -86.5479\n", - "Current minimum: -86.5479\n", + "Time taken: 2.5171\n", + "Function value obtained: -82.1995\n", + "Current minimum: -82.1995\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6467\n", - "Function value obtained: -75.7266\n", - "Current minimum: -86.5479\n", + "Time taken: 2.7444\n", + "Function value obtained: -76.4244\n", + "Current minimum: -82.1995\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3240\n", - "Function value obtained: -81.4121\n", - "Current minimum: -86.5479\n", + "Time taken: 2.3227\n", + "Function value obtained: -59.0022\n", + "Current minimum: -82.1995\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6180\n", - "Function value obtained: -69.6542\n", - "Current minimum: -86.5479\n", + "Time taken: 1.4925\n", + "Function value obtained: -79.8453\n", + "Current minimum: -82.1995\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6148\n", - "Function value obtained: -86.6761\n", - "Current minimum: -86.6761\n", + "Time taken: 1.5988\n", + "Function value obtained: -82.0734\n", + "Current minimum: -82.1995\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5092\n", - "Function value obtained: -86.3296\n", - "Current minimum: -86.6761\n", + "Time taken: 1.5444\n", + "Function value obtained: -82.1329\n", + "Current minimum: -82.1995\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5560\n", - "Function value obtained: -85.7819\n", - "Current minimum: -86.6761\n", + "Time taken: 1.5446\n", + "Function value obtained: -75.1359\n", + "Current minimum: -82.1995\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5364\n", - "Function value obtained: -84.3509\n", - "Current minimum: -86.6761\n", + "Time taken: 1.4972\n", + "Function value obtained: -47.4599\n", + "Current minimum: -82.1995\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5240\n", - "Function value obtained: -83.4330\n", - "Current minimum: -86.6761\n", + "Time taken: 1.5302\n", + "Function value obtained: -82.9885\n", + "Current minimum: -82.9885\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5617\n", - "Function value obtained: -83.7592\n", - "Current minimum: -86.6761\n", + "Time taken: 1.4491\n", + "Function value obtained: -79.8435\n", + "Current minimum: -82.9885\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5114\n", - "Function value obtained: -83.9225\n", - "Current minimum: -86.6761\n", + "Time taken: 1.6897\n", + "Function value obtained: -78.2639\n", + "Current minimum: -82.9885\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5328\n", - "Function value obtained: -0.0000\n", - "Current minimum: -86.6761\n", + "Time taken: 1.4834\n", + "Function value obtained: -79.4805\n", + "Current minimum: -82.9885\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6206\n", - "Function value obtained: -81.6106\n", - "Current minimum: -86.6761\n", + "Time taken: 1.4405\n", + "Function value obtained: -31.7971\n", + "Current minimum: -82.9885\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5505\n", - "Function value obtained: -84.2248\n", - "Current minimum: -86.6761\n", + "Time taken: 1.5430\n", + "Function value obtained: -81.7057\n", + "Current minimum: -82.9885\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5881\n", - "Function value obtained: -86.4688\n", - "Current minimum: -86.6761\n", + "Time taken: 1.5597\n", + "Function value obtained: -86.2651\n", + "Current minimum: -86.2651\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6746\n", - "Function value obtained: -82.6019\n", - "Current minimum: -86.6761\n", + "Time taken: 1.3970\n", + "Function value obtained: -84.6473\n", + "Current minimum: -86.2651\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4213\n", - "Function value obtained: -87.1654\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5765\n", + "Function value obtained: -85.6389\n", + "Current minimum: -86.2651\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5361\n", - "Function value obtained: -84.6632\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5050\n", + "Function value obtained: -80.7363\n", + "Current minimum: -86.2651\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5604\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1654\n", + "Time taken: 1.4977\n", + "Function value obtained: -81.0955\n", + "Current minimum: -86.2651\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4963\n", - "Function value obtained: -47.3826\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5693\n", + "Function value obtained: -1.9364\n", + "Current minimum: -86.2651\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4632\n", - "Function value obtained: -84.7640\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6156\n", + "Function value obtained: -83.5928\n", + "Current minimum: -86.2651\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6056\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5964\n", + "Function value obtained: -81.4378\n", + "Current minimum: -86.2651\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5335\n", - "Function value obtained: -78.1384\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5503\n", + "Function value obtained: -83.7283\n", + "Current minimum: -86.2651\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6209\n", - "Function value obtained: -82.6793\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5272\n", + "Function value obtained: -84.4892\n", + "Current minimum: -86.2651\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5587\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6030\n", + "Function value obtained: -83.2422\n", + "Current minimum: -86.2651\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4955\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5581\n", + "Function value obtained: -84.7703\n", + "Current minimum: -86.2651\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5314\n", - "Function value obtained: -79.9439\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5818\n", + "Function value obtained: -0.0000\n", + "Current minimum: -86.2651\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5843\n", - "Function value obtained: -84.4630\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5588\n", + "Function value obtained: -86.1378\n", + "Current minimum: -86.2651\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6787\n", - "Function value obtained: -80.1143\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7102\n", + "Function value obtained: -87.6390\n", + "Current minimum: -87.6390\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6241\n", - "Function value obtained: -76.6670\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7003\n", + "Function value obtained: -88.1836\n", + "Current minimum: -88.1836\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6217\n", - "Function value obtained: -82.3647\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7084\n", + "Function value obtained: -88.2088\n", + "Current minimum: -88.2088\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6778\n", - "Function value obtained: -82.8928\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6072\n", + "Function value obtained: -84.0442\n", + "Current minimum: -88.2088\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6505\n", - "Function value obtained: -85.2244\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5923\n", + "Function value obtained: -83.8470\n", + "Current minimum: -88.2088\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6423\n", - "Function value obtained: -82.5976\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7308\n", + "Function value obtained: -86.4331\n", + "Current minimum: -88.2088\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6409\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6601\n", + "Function value obtained: -84.3033\n", + "Current minimum: -88.2088\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6560\n", - "Function value obtained: -85.3694\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6979\n", + "Function value obtained: -88.4533\n", + "Current minimum: -88.4533\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7153\n", - "Function value obtained: -85.7065\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5749\n", + "Function value obtained: -84.0851\n", + "Current minimum: -88.4533\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7139\n", - "Function value obtained: -83.6194\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6064\n", + "Function value obtained: -84.9920\n", + "Current minimum: -88.4533\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9258\n", - "Function value obtained: -84.4336\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6048\n", + "Function value obtained: -84.2240\n", + "Current minimum: -88.4533\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7036\n", - "Function value obtained: -84.7038\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6681\n", + "Function value obtained: -83.8135\n", + "Current minimum: -88.4533\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6683\n", - "Function value obtained: -84.0647\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6173\n", + "Function value obtained: -2.3999\n", + "Current minimum: -88.4533\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8355\n", - "Function value obtained: -84.7367\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7242\n", + "Function value obtained: -83.6010\n", + "Current minimum: -88.4533\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7087\n", - "Function value obtained: -0.0000\n", - "Current minimum: -87.1654\n", + "Time taken: 1.5484\n", + "Function value obtained: -86.3004\n", + "Current minimum: -88.4533\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8020\n", - "Function value obtained: -86.6965\n", - "Current minimum: -87.1654\n", + "Time taken: 1.6542\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.4533\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7731\n", - "Function value obtained: -83.7168\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7897\n", + "Function value obtained: -81.3552\n", + "Current minimum: -88.4533\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7801\n", - "Function value obtained: -84.0911\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7200\n", + "Function value obtained: -77.9104\n", + "Current minimum: -88.4533\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8769\n", - "Function value obtained: -52.1267\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7528\n", + "Function value obtained: -84.1339\n", + "Current minimum: -88.4533\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8854\n", - "Function value obtained: -85.0718\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7421\n", + "Function value obtained: -3.8739\n", + "Current minimum: -88.4533\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8315\n", - "Function value obtained: -66.6768\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7754\n", + "Function value obtained: -84.1307\n", + "Current minimum: -88.4533\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8824\n", - "Function value obtained: -83.1847\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7195\n", + "Function value obtained: -78.8474\n", + "Current minimum: -88.4533\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8042\n", - "Function value obtained: -85.7831\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7647\n", + "Function value obtained: -87.5901\n", + "Current minimum: -88.4533\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8875\n", - "Function value obtained: -84.8040\n", - "Current minimum: -87.1654\n", + "Time taken: 1.8416\n", + "Function value obtained: -84.6699\n", + "Current minimum: -88.4533\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8361\n", - "Function value obtained: -86.0435\n", - "Current minimum: -87.1654\n", + "Time taken: 1.7751\n", + "Function value obtained: -82.5775\n", + "Current minimum: -88.4533\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9100\n", - "Function value obtained: -87.5948\n", - "Current minimum: -87.5948\n", + "Time taken: 1.7313\n", + "Function value obtained: -88.1452\n", + "Current minimum: -88.4533\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0052\n", - "Function value obtained: -87.3832\n", - "Current minimum: -87.5948\n", + "Time taken: 1.9032\n", + "Function value obtained: -85.1442\n", + "Current minimum: -88.4533\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9399\n", - "Function value obtained: -87.6509\n", - "Current minimum: -87.6509\n", + "Time taken: 1.7385\n", + "Function value obtained: -2.5050\n", + "Current minimum: -88.4533\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8762\n", - "Function value obtained: -89.4458\n", - "Current minimum: -89.4458\n", + "Time taken: 1.7224\n", + "Function value obtained: -82.2524\n", + "Current minimum: -88.4533\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8609\n", - "Function value obtained: -84.4458\n", - "Current minimum: -89.4458\n", + "Time taken: 1.7859\n", + "Function value obtained: -74.2668\n", + "Current minimum: -88.4533\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9677\n", - "Function value obtained: -76.8716\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8074\n", + "Function value obtained: -76.8367\n", + "Current minimum: -88.4533\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0256\n", - "Function value obtained: -76.2327\n", - "Current minimum: -89.4458\n", + "Time taken: 1.7701\n", + "Function value obtained: -90.6333\n", + "Current minimum: -90.6333\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9435\n", - "Function value obtained: -70.5779\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8479\n", + "Function value obtained: -85.4348\n", + "Current minimum: -90.6333\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0506\n", - "Function value obtained: -85.7938\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8363\n", + "Function value obtained: -82.3339\n", + "Current minimum: -90.6333\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0131\n", - "Function value obtained: -2.3382\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8753\n", + "Function value obtained: -85.6496\n", + "Current minimum: -90.6333\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0270\n", - "Function value obtained: -83.8244\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8171\n", + "Function value obtained: -85.2793\n", + "Current minimum: -90.6333\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9941\n", - "Function value obtained: -64.2494\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8682\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0532\n", - "Function value obtained: -79.9634\n", - "Current minimum: -89.4458\n", + "Time taken: 2.0042\n", + "Function value obtained: -72.8643\n", + "Current minimum: -90.6333\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9294\n", - "Function value obtained: -65.3227\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8247\n", + "Function value obtained: -36.2201\n", + "Current minimum: -90.6333\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0383\n", - "Function value obtained: -88.5685\n", - "Current minimum: -89.4458\n", + "Time taken: 1.9199\n", + "Function value obtained: -52.9810\n", + "Current minimum: -90.6333\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0428\n", - "Function value obtained: -84.7590\n", - "Current minimum: -89.4458\n", + "Time taken: 1.9531\n", + "Function value obtained: -82.3026\n", + "Current minimum: -90.6333\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9657\n", - "Function value obtained: -78.7142\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8739\n", + "Function value obtained: -85.8179\n", + "Current minimum: -90.6333\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9812\n", - "Function value obtained: -86.3107\n", - "Current minimum: -89.4458\n", + "Time taken: 1.8679\n", + "Function value obtained: -2.7283\n", + "Current minimum: -90.6333\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0941\n", - "Function value obtained: -40.1945\n", - "Current minimum: -89.4458\n", + "Time taken: 1.9346\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9600\n", - "Function value obtained: -0.0000\n", - "Current minimum: -89.4458\n", + "Time taken: 1.9970\n", + "Function value obtained: -85.0913\n", + "Current minimum: -90.6333\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1713\n", - "Function value obtained: -27.2993\n", - "Current minimum: -89.4458\n", + "Time taken: 1.9889\n", + "Function value obtained: -86.0498\n", + "Current minimum: -90.6333\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0064\n", - "Function value obtained: -81.6215\n", - "Current minimum: -89.4458\n", + "Time taken: 1.9690\n", + "Function value obtained: -89.3086\n", + "Current minimum: -90.6333\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0520\n", - "Function value obtained: -85.5144\n", - "Current minimum: -89.4458\n", + "Time taken: 2.0585\n", + "Function value obtained: -87.4380\n", + "Current minimum: -90.6333\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1437\n", - "Function value obtained: -68.1607\n", - "Current minimum: -89.4458\n", + "Time taken: 2.2492\n", + "Function value obtained: -79.2090\n", + "Current minimum: -90.6333\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1091\n", - "Function value obtained: -81.8875\n", - "Current minimum: -89.4458\n", + "Time taken: 2.0783\n", + "Function value obtained: -83.0764\n", + "Current minimum: -90.6333\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1652\n", - "Function value obtained: -85.0252\n", - "Current minimum: -89.4458\n", + "Time taken: 2.0430\n", + "Function value obtained: -86.2792\n", + "Current minimum: -90.6333\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1792\n", - "Function value obtained: -38.1945\n", - "Current minimum: -89.4458\n", + "Time taken: 2.1258\n", + "Function value obtained: -82.8770\n", + "Current minimum: -90.6333\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2576\n", - "Function value obtained: -86.5831\n", - "Current minimum: -89.4458\n", + "Time taken: 2.0408\n", + "Function value obtained: -82.4791\n", + "Current minimum: -90.6333\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2714\n", - "Function value obtained: -84.7071\n", - "Current minimum: -89.4458\n", + "Time taken: 2.0456\n", + "Function value obtained: -85.6827\n", + "Current minimum: -90.6333\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3242\n", - "Function value obtained: -82.0435\n", - "Current minimum: -89.4458\n", + "Time taken: 2.0294\n", + "Function value obtained: -74.7308\n", + "Current minimum: -90.6333\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2444\n", - "Function value obtained: -82.6330\n", - "Current minimum: -89.4458\n", + "Time taken: 2.1141\n", + "Function value obtained: -83.3760\n", + "Current minimum: -90.6333\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2243\n", - "Function value obtained: -82.1444\n", - "Current minimum: -89.4458\n", + "Time taken: 2.2029\n", + "Function value obtained: -14.3625\n", + "Current minimum: -90.6333\n", "Iteration No: 101 started. Searching for the next optimal point.\n", "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3079\n", - "Function value obtained: -3.8924\n", - "Current minimum: -89.4458\n", + "Time taken: 2.1955\n", + "Function value obtained: -71.1589\n", + "Current minimum: -90.6333\n", "Iteration No: 102 started. Searching for the next optimal point.\n", "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2421\n", - "Function value obtained: -84.3560\n", - "Current minimum: -89.4458\n", + "Time taken: 2.2321\n", + "Function value obtained: -77.2377\n", + "Current minimum: -90.6333\n", "Iteration No: 103 started. Searching for the next optimal point.\n", "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2009\n", - "Function value obtained: -74.0913\n", - "Current minimum: -89.4458\n", + "Time taken: 2.2387\n", + "Function value obtained: -77.7340\n", + "Current minimum: -90.6333\n", "Iteration No: 104 started. Searching for the next optimal point.\n", "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1615\n", - "Function value obtained: -84.7180\n", - "Current minimum: -89.4458\n", + "Time taken: 2.1820\n", + "Function value obtained: -83.7139\n", + "Current minimum: -90.6333\n", "Iteration No: 105 started. Searching for the next optimal point.\n", "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3078\n", - "Function value obtained: -74.5602\n", - "Current minimum: -89.4458\n", + "Time taken: 2.2461\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 106 started. Searching for the next optimal point.\n", "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3045\n", - "Function value obtained: -86.8558\n", - "Current minimum: -89.4458\n", + "Time taken: 2.2158\n", + "Function value obtained: -3.9035\n", + "Current minimum: -90.6333\n", "Iteration No: 107 started. Searching for the next optimal point.\n", "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3949\n", - "Function value obtained: -84.7131\n", - "Current minimum: -89.4458\n", + "Time taken: 2.2611\n", + "Function value obtained: -75.1242\n", + "Current minimum: -90.6333\n", "Iteration No: 108 started. Searching for the next optimal point.\n", "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3058\n", - "Function value obtained: -84.8969\n", - "Current minimum: -89.4458\n", + "Time taken: 2.3445\n", + "Function value obtained: -85.5275\n", + "Current minimum: -90.6333\n", "Iteration No: 109 started. Searching for the next optimal point.\n", "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3854\n", - "Function value obtained: -90.1080\n", - "Current minimum: -90.1080\n", + "Time taken: 2.2808\n", + "Function value obtained: -84.5770\n", + "Current minimum: -90.6333\n", "Iteration No: 110 started. Searching for the next optimal point.\n", "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4104\n", - "Function value obtained: -83.7669\n", - "Current minimum: -90.1080\n", + "Time taken: 2.2629\n", + "Function value obtained: -85.4486\n", + "Current minimum: -90.6333\n", "Iteration No: 111 started. Searching for the next optimal point.\n", "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4869\n", - "Function value obtained: -2.6536\n", - "Current minimum: -90.1080\n", + "Time taken: 2.2529\n", + "Function value obtained: -75.6998\n", + "Current minimum: -90.6333\n", "Iteration No: 112 started. Searching for the next optimal point.\n", "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4273\n", - "Function value obtained: -77.3157\n", - "Current minimum: -90.1080\n", + "Time taken: 2.2940\n", + "Function value obtained: -84.5648\n", + "Current minimum: -90.6333\n", "Iteration No: 113 started. Searching for the next optimal point.\n", "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4460\n", - "Function value obtained: -85.7271\n", - "Current minimum: -90.1080\n", + "Time taken: 2.2838\n", + "Function value obtained: -70.1448\n", + "Current minimum: -90.6333\n", "Iteration No: 114 started. Searching for the next optimal point.\n", "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4237\n", - "Function value obtained: -87.5493\n", - "Current minimum: -90.1080\n", + "Time taken: 2.4314\n", + "Function value obtained: -86.5986\n", + "Current minimum: -90.6333\n", "Iteration No: 115 started. Searching for the next optimal point.\n", "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4666\n", - "Function value obtained: -84.2363\n", - "Current minimum: -90.1080\n", + "Time taken: 2.2736\n", + "Function value obtained: -83.5688\n", + "Current minimum: -90.6333\n", "Iteration No: 116 started. Searching for the next optimal point.\n", "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4197\n", - "Function value obtained: -75.9327\n", - "Current minimum: -90.1080\n", + "Time taken: 2.4588\n", + "Function value obtained: -85.3449\n", + "Current minimum: -90.6333\n", "Iteration No: 117 started. Searching for the next optimal point.\n", "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4655\n", - "Function value obtained: -74.7333\n", - "Current minimum: -90.1080\n", + "Time taken: 2.3671\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 118 started. Searching for the next optimal point.\n", "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4448\n", - "Function value obtained: -85.6777\n", - "Current minimum: -90.1080\n", + "Time taken: 2.3850\n", + "Function value obtained: -84.6747\n", + "Current minimum: -90.6333\n", "Iteration No: 119 started. Searching for the next optimal point.\n", "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4911\n", - "Function value obtained: -85.8749\n", - "Current minimum: -90.1080\n", + "Time taken: 2.4507\n", + "Function value obtained: -2.0290\n", + "Current minimum: -90.6333\n", "Iteration No: 120 started. Searching for the next optimal point.\n", "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5112\n", - "Function value obtained: -84.6669\n", - "Current minimum: -90.1080\n", + "Time taken: 2.3261\n", + "Function value obtained: -84.2602\n", + "Current minimum: -90.6333\n", "Iteration No: 121 started. Searching for the next optimal point.\n", "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6462\n", - "Function value obtained: -82.2886\n", - "Current minimum: -90.1080\n", + "Time taken: 2.4539\n", + "Function value obtained: -82.9736\n", + "Current minimum: -90.6333\n", "Iteration No: 122 started. Searching for the next optimal point.\n", "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4867\n", - "Function value obtained: -82.3150\n", - "Current minimum: -90.1080\n", + "Time taken: 2.4714\n", + "Function value obtained: -67.7069\n", + "Current minimum: -90.6333\n", "Iteration No: 123 started. Searching for the next optimal point.\n", "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7028\n", - "Function value obtained: -83.6574\n", - "Current minimum: -90.1080\n", + "Time taken: 2.3809\n", + "Function value obtained: -80.7035\n", + "Current minimum: -90.6333\n", "Iteration No: 124 started. Searching for the next optimal point.\n", "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6137\n", - "Function value obtained: -78.4962\n", - "Current minimum: -90.1080\n", + "Time taken: 2.4970\n", + "Function value obtained: -81.0539\n", + "Current minimum: -90.6333\n", "Iteration No: 125 started. Searching for the next optimal point.\n", "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5376\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.1080\n", + "Time taken: 2.5194\n", + "Function value obtained: -77.8282\n", + "Current minimum: -90.6333\n", "Iteration No: 126 started. Searching for the next optimal point.\n", "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6664\n", - "Function value obtained: -2.3239\n", - "Current minimum: -90.1080\n", + "Time taken: 2.5481\n", + "Function value obtained: -85.7514\n", + "Current minimum: -90.6333\n", "Iteration No: 127 started. Searching for the next optimal point.\n", "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5561\n", - "Function value obtained: -84.3863\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6020\n", + "Function value obtained: -58.3485\n", + "Current minimum: -90.6333\n", "Iteration No: 128 started. Searching for the next optimal point.\n", "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5864\n", - "Function value obtained: -89.2723\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6162\n", + "Function value obtained: -84.7989\n", + "Current minimum: -90.6333\n", "Iteration No: 129 started. Searching for the next optimal point.\n", "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6874\n", - "Function value obtained: -85.7395\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6023\n", + "Function value obtained: -83.7495\n", + "Current minimum: -90.6333\n", "Iteration No: 130 started. Searching for the next optimal point.\n", "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6609\n", - "Function value obtained: -81.2216\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6529\n", + "Function value obtained: -84.6838\n", + "Current minimum: -90.6333\n", "Iteration No: 131 started. Searching for the next optimal point.\n", "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6842\n", - "Function value obtained: -85.3949\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6517\n", + "Function value obtained: -81.3237\n", + "Current minimum: -90.6333\n", "Iteration No: 132 started. Searching for the next optimal point.\n", "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8074\n", - "Function value obtained: -83.9053\n", - "Current minimum: -90.1080\n", + "Time taken: 2.5658\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 133 started. Searching for the next optimal point.\n", "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7910\n", - "Function value obtained: -86.5381\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6196\n", + "Function value obtained: -57.2674\n", + "Current minimum: -90.6333\n", "Iteration No: 134 started. Searching for the next optimal point.\n", "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7673\n", - "Function value obtained: -38.0584\n", - "Current minimum: -90.1080\n", + "Time taken: 2.5497\n", + "Function value obtained: -82.8458\n", + "Current minimum: -90.6333\n", "Iteration No: 135 started. Searching for the next optimal point.\n", "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8259\n", - "Function value obtained: -19.5556\n", - "Current minimum: -90.1080\n", + "Time taken: 2.7238\n", + "Function value obtained: -80.1184\n", + "Current minimum: -90.6333\n", "Iteration No: 136 started. Searching for the next optimal point.\n", "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8044\n", - "Function value obtained: -88.0263\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8476\n", + "Function value obtained: -83.7794\n", + "Current minimum: -90.6333\n", "Iteration No: 137 started. Searching for the next optimal point.\n", "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8218\n", - "Function value obtained: -83.8556\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8646\n", + "Function value obtained: -83.6890\n", + "Current minimum: -90.6333\n", "Iteration No: 138 started. Searching for the next optimal point.\n", "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9458\n", - "Function value obtained: -84.9582\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6516\n", + "Function value obtained: -11.3171\n", + "Current minimum: -90.6333\n", "Iteration No: 139 started. Searching for the next optimal point.\n", "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8685\n", - "Function value obtained: -71.6207\n", - "Current minimum: -90.1080\n", + "Time taken: 2.7437\n", + "Function value obtained: -82.8761\n", + "Current minimum: -90.6333\n", "Iteration No: 140 started. Searching for the next optimal point.\n", "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8345\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6597\n", + "Function value obtained: -86.4469\n", + "Current minimum: -90.6333\n", "Iteration No: 141 started. Searching for the next optimal point.\n", "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9433\n", - "Function value obtained: -79.3504\n", - "Current minimum: -90.1080\n", + "Time taken: 2.7797\n", + "Function value obtained: -0.0000\n", + "Current minimum: -90.6333\n", "Iteration No: 142 started. Searching for the next optimal point.\n", "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1014\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.1080\n", + "Time taken: 2.6914\n", + "Function value obtained: -84.1730\n", + "Current minimum: -90.6333\n", "Iteration No: 143 started. Searching for the next optimal point.\n", "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9258\n", - "Function value obtained: -78.2937\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8246\n", + "Function value obtained: -78.3581\n", + "Current minimum: -90.6333\n", "Iteration No: 144 started. Searching for the next optimal point.\n", "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9821\n", - "Function value obtained: -79.0707\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8528\n", + "Function value obtained: -86.4290\n", + "Current minimum: -90.6333\n", "Iteration No: 145 started. Searching for the next optimal point.\n", "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0360\n", - "Function value obtained: -75.7946\n", - "Current minimum: -90.1080\n", + "Time taken: 2.7967\n", + "Function value obtained: -83.3510\n", + "Current minimum: -90.6333\n", "Iteration No: 146 started. Searching for the next optimal point.\n", "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0021\n", - "Function value obtained: -32.5327\n", - "Current minimum: -90.1080\n", + "Time taken: 2.7849\n", + "Function value obtained: -83.6486\n", + "Current minimum: -90.6333\n", "Iteration No: 147 started. Searching for the next optimal point.\n", "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9289\n", - "Function value obtained: -75.6591\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8430\n", + "Function value obtained: -55.1289\n", + "Current minimum: -90.6333\n", "Iteration No: 148 started. Searching for the next optimal point.\n", "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9720\n", - "Function value obtained: -79.7543\n", - "Current minimum: -90.1080\n", + "Time taken: 2.9347\n", + "Function value obtained: -85.6819\n", + "Current minimum: -90.6333\n", "Iteration No: 149 started. Searching for the next optimal point.\n", "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0303\n", - "Function value obtained: -14.1465\n", - "Current minimum: -90.1080\n", + "Time taken: 2.7961\n", + "Function value obtained: -83.8089\n", + "Current minimum: -90.6333\n", "Iteration No: 150 started. Searching for the next optimal point.\n", "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9655\n", - "Function value obtained: -86.5903\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8090\n", + "Function value obtained: -83.1695\n", + "Current minimum: -90.6333\n", "Iteration No: 151 started. Searching for the next optimal point.\n", "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0833\n", - "Function value obtained: -2.2684\n", - "Current minimum: -90.1080\n", + "Time taken: 2.9021\n", + "Function value obtained: -11.0483\n", + "Current minimum: -90.6333\n", "Iteration No: 152 started. Searching for the next optimal point.\n", "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0779\n", - "Function value obtained: -84.7120\n", - "Current minimum: -90.1080\n", + "Time taken: 2.7946\n", + "Function value obtained: -85.6196\n", + "Current minimum: -90.6333\n", "Iteration No: 153 started. Searching for the next optimal point.\n", "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0388\n", - "Function value obtained: -86.9601\n", - "Current minimum: -90.1080\n", + "Time taken: 2.9110\n", + "Function value obtained: -83.9758\n", + "Current minimum: -90.6333\n", "Iteration No: 154 started. Searching for the next optimal point.\n", "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0481\n", - "Function value obtained: -86.2894\n", - "Current minimum: -90.1080\n", + "Time taken: 2.9064\n", + "Function value obtained: -85.1906\n", + "Current minimum: -90.6333\n", "Iteration No: 155 started. Searching for the next optimal point.\n", "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0682\n", - "Function value obtained: -84.2894\n", - "Current minimum: -90.1080\n", + "Time taken: 3.0321\n", + "Function value obtained: -87.8375\n", + "Current minimum: -90.6333\n", "Iteration No: 156 started. Searching for the next optimal point.\n", "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0720\n", - "Function value obtained: -86.1454\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8503\n", + "Function value obtained: -85.1706\n", + "Current minimum: -90.6333\n", "Iteration No: 157 started. Searching for the next optimal point.\n", "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1283\n", - "Function value obtained: -85.5008\n", - "Current minimum: -90.1080\n", + "Time taken: 2.8713\n", + "Function value obtained: -86.7744\n", + "Current minimum: -90.6333\n", "Iteration No: 158 started. Searching for the next optimal point.\n", "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2131\n", - "Function value obtained: -83.7913\n", - "Current minimum: -90.1080\n", + "Time taken: 2.9642\n", + "Function value obtained: -88.2608\n", + "Current minimum: -90.6333\n", "Iteration No: 159 started. Searching for the next optimal point.\n", "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1915\n", - "Function value obtained: -88.2591\n", - "Current minimum: -90.1080\n", + "Time taken: 2.9760\n", + "Function value obtained: -85.5418\n", + "Current minimum: -90.6333\n", "Iteration No: 160 started. Searching for the next optimal point.\n", "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2995\n", - "Function value obtained: -88.1398\n", - "Current minimum: -90.1080\n", + "Time taken: 3.0818\n", + "Function value obtained: -83.7893\n", + "Current minimum: -90.6333\n", "Iteration No: 161 started. Searching for the next optimal point.\n", "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2863\n", - "Function value obtained: -84.1293\n", - "Current minimum: -90.1080\n", + "Time taken: 3.1793\n", + "Function value obtained: -86.5298\n", + "Current minimum: -90.6333\n", "Iteration No: 162 started. Searching for the next optimal point.\n", "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3000\n", - "Function value obtained: -82.8841\n", - "Current minimum: -90.1080\n", + "Time taken: 3.0893\n", + "Function value obtained: -85.0591\n", + "Current minimum: -90.6333\n", "Iteration No: 163 started. Searching for the next optimal point.\n", "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2327\n", - "Function value obtained: -86.7044\n", - "Current minimum: -90.1080\n", + "Time taken: 3.0569\n", + "Function value obtained: -85.5105\n", + "Current minimum: -90.6333\n", "Iteration No: 164 started. Searching for the next optimal point.\n", "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2941\n", - "Function value obtained: -83.2319\n", - "Current minimum: -90.1080\n", + "Time taken: 3.1089\n", + "Function value obtained: -86.4030\n", + "Current minimum: -90.6333\n", "Iteration No: 165 started. Searching for the next optimal point.\n", "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2975\n", - "Function value obtained: -84.8725\n", - "Current minimum: -90.1080\n", + "Time taken: 3.1090\n", + "Function value obtained: -85.1444\n", + "Current minimum: -90.6333\n", "Iteration No: 166 started. Searching for the next optimal point.\n", "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1967\n", - "Function value obtained: -85.3258\n", - "Current minimum: -90.1080\n", + "Time taken: 3.2387\n", + "Function value obtained: -88.1799\n", + "Current minimum: -90.6333\n", "Iteration No: 167 started. Searching for the next optimal point.\n", "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3404\n", - "Function value obtained: -83.5805\n", - "Current minimum: -90.1080\n", + "Time taken: 3.0989\n", + "Function value obtained: -84.9582\n", + "Current minimum: -90.6333\n", "Iteration No: 168 started. Searching for the next optimal point.\n", "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2737\n", - "Function value obtained: -85.8725\n", - "Current minimum: -90.1080\n", + "Time taken: 3.1239\n", + "Function value obtained: -89.2391\n", + "Current minimum: -90.6333\n", "Iteration No: 169 started. Searching for the next optimal point.\n", "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2683\n", - "Function value obtained: -83.0707\n", - "Current minimum: -90.1080\n", + "Time taken: 3.1619\n", + "Function value obtained: -84.0053\n", + "Current minimum: -90.6333\n", "Iteration No: 170 started. Searching for the next optimal point.\n", "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5759\n", - "Function value obtained: -86.8456\n", - "Current minimum: -90.1080\n", + "Time taken: 3.1452\n", + "Function value obtained: -83.0798\n", + "Current minimum: -90.6333\n", "Iteration No: 171 started. Searching for the next optimal point.\n", "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4243\n", - "Function value obtained: -84.7315\n", - "Current minimum: -90.1080\n", + "Time taken: 3.2143\n", + "Function value obtained: -88.2145\n", + "Current minimum: -90.6333\n", "Iteration No: 172 started. Searching for the next optimal point.\n", "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5115\n", - "Function value obtained: -84.6169\n", - "Current minimum: -90.1080\n", + "Time taken: 3.1834\n", + "Function value obtained: -85.2621\n", + "Current minimum: -90.6333\n", "Iteration No: 173 started. Searching for the next optimal point.\n", "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3010\n", - "Function value obtained: -81.6789\n", - "Current minimum: -90.1080\n", + "Time taken: 3.3020\n", + "Function value obtained: -87.8510\n", + "Current minimum: -90.6333\n", "Iteration No: 174 started. Searching for the next optimal point.\n", "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5282\n", - "Function value obtained: -86.4641\n", - "Current minimum: -90.1080\n", + "Time taken: 3.2385\n", + "Function value obtained: -88.9162\n", + "Current minimum: -90.6333\n", "Iteration No: 175 started. Searching for the next optimal point.\n", "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5046\n", - "Function value obtained: -87.2174\n", - "Current minimum: -90.1080\n", + "Time taken: 3.2649\n", + "Function value obtained: -86.9675\n", + "Current minimum: -90.6333\n", "Iteration No: 176 started. Searching for the next optimal point.\n", "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4834\n", - "Function value obtained: -85.3013\n", - "Current minimum: -90.1080\n", + "Time taken: 3.2222\n", + "Function value obtained: -83.9728\n", + "Current minimum: -90.6333\n", "Iteration No: 177 started. Searching for the next optimal point.\n", "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4234\n", - "Function value obtained: -85.1900\n", - "Current minimum: -90.1080\n", + "Time taken: 3.2621\n", + "Function value obtained: -87.8963\n", + "Current minimum: -90.6333\n", "Iteration No: 178 started. Searching for the next optimal point.\n", "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5353\n", - "Function value obtained: -87.0985\n", - "Current minimum: -90.1080\n", + "Time taken: 3.2759\n", + "Function value obtained: -84.1823\n", + "Current minimum: -90.6333\n", "Iteration No: 179 started. Searching for the next optimal point.\n", "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5676\n", - "Function value obtained: -88.9232\n", - "Current minimum: -90.1080\n", + "Time taken: 3.3226\n", + "Function value obtained: -86.6570\n", + "Current minimum: -90.6333\n", "Iteration No: 180 started. Searching for the next optimal point.\n", "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4110\n", - "Function value obtained: -84.1636\n", - "Current minimum: -90.1080\n", + "Time taken: 3.3956\n", + "Function value obtained: -88.0181\n", + "Current minimum: -90.6333\n", "Iteration No: 181 started. Searching for the next optimal point.\n", "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6401\n", - "Function value obtained: -86.0473\n", - "Current minimum: -90.1080\n", + "Time taken: 3.3426\n", + "Function value obtained: -83.0062\n", + "Current minimum: -90.6333\n", "Iteration No: 182 started. Searching for the next optimal point.\n", "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6908\n", - "Function value obtained: -84.9941\n", - "Current minimum: -90.1080\n", + "Time taken: 3.5089\n", + "Function value obtained: -85.3005\n", + "Current minimum: -90.6333\n", "Iteration No: 183 started. Searching for the next optimal point.\n", "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6404\n", - "Function value obtained: -87.2634\n", - "Current minimum: -90.1080\n", + "Time taken: 3.3370\n", + "Function value obtained: -83.4699\n", + "Current minimum: -90.6333\n", "Iteration No: 184 started. Searching for the next optimal point.\n", "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6747\n", - "Function value obtained: -86.1677\n", - "Current minimum: -90.1080\n", + "Time taken: 3.4299\n", + "Function value obtained: -86.1810\n", + "Current minimum: -90.6333\n", "Iteration No: 185 started. Searching for the next optimal point.\n", "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5355\n", - "Function value obtained: -84.4485\n", - "Current minimum: -90.1080\n", + "Time taken: 3.5185\n", + "Function value obtained: -85.4634\n", + "Current minimum: -90.6333\n", "Iteration No: 186 started. Searching for the next optimal point.\n", "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5761\n", - "Function value obtained: -88.1312\n", - "Current minimum: -90.1080\n", + "Time taken: 3.5824\n", + "Function value obtained: -84.4536\n", + "Current minimum: -90.6333\n", "Iteration No: 187 started. Searching for the next optimal point.\n", "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7427\n", - "Function value obtained: -87.8741\n", - "Current minimum: -90.1080\n", + "Time taken: 3.5014\n", + "Function value obtained: -88.0504\n", + "Current minimum: -90.6333\n", "Iteration No: 188 started. Searching for the next optimal point.\n", "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6982\n", - "Function value obtained: -85.0937\n", - "Current minimum: -90.1080\n", + "Time taken: 3.4922\n", + "Function value obtained: -87.6193\n", + "Current minimum: -90.6333\n", "Iteration No: 189 started. Searching for the next optimal point.\n", "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8059\n", - "Function value obtained: -84.7989\n", - "Current minimum: -90.1080\n", + "Time taken: 3.6882\n", + "Function value obtained: -87.6822\n", + "Current minimum: -90.6333\n", "Iteration No: 190 started. Searching for the next optimal point.\n", "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7532\n", - "Function value obtained: -84.9776\n", - "Current minimum: -90.1080\n", + "Time taken: 3.5456\n", + "Function value obtained: -84.8614\n", + "Current minimum: -90.6333\n", "Iteration No: 191 started. Searching for the next optimal point.\n", "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7327\n", - "Function value obtained: -86.2600\n", - "Current minimum: -90.1080\n", + "Time taken: 3.5422\n", + "Function value obtained: -87.8404\n", + "Current minimum: -90.6333\n", "Iteration No: 192 started. Searching for the next optimal point.\n", "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7536\n", - "Function value obtained: -82.7375\n", - "Current minimum: -90.1080\n", + "Time taken: 3.6575\n", + "Function value obtained: -84.9520\n", + "Current minimum: -90.6333\n", "Iteration No: 193 started. Searching for the next optimal point.\n", "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7799\n", - "Function value obtained: -85.9629\n", - "Current minimum: -90.1080\n", + "Time taken: 3.6065\n", + "Function value obtained: -84.7831\n", + "Current minimum: -90.6333\n", "Iteration No: 194 started. Searching for the next optimal point.\n", "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8153\n", - "Function value obtained: -85.5385\n", - "Current minimum: -90.1080\n", + "Time taken: 3.7370\n", + "Function value obtained: -84.4722\n", + "Current minimum: -90.6333\n", "Iteration No: 195 started. Searching for the next optimal point.\n", "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8953\n", - "Function value obtained: -85.5226\n", - "Current minimum: -90.1080\n", + "Time taken: 3.7130\n", + "Function value obtained: -87.2530\n", + "Current minimum: -90.6333\n", "Iteration No: 196 started. Searching for the next optimal point.\n", "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8898\n", - "Function value obtained: -87.3023\n", - "Current minimum: -90.1080\n", + "Time taken: 3.6288\n", + "Function value obtained: -84.8944\n", + "Current minimum: -90.6333\n", "Iteration No: 197 started. Searching for the next optimal point.\n", "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0235\n", - "Function value obtained: -84.0948\n", - "Current minimum: -90.1080\n", + "Time taken: 3.7870\n", + "Function value obtained: -87.7330\n", + "Current minimum: -90.6333\n", "Iteration No: 198 started. Searching for the next optimal point.\n", "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7757\n", - "Function value obtained: -84.4794\n", - "Current minimum: -90.1080\n", + "Time taken: 3.7568\n", + "Function value obtained: -87.8071\n", + "Current minimum: -90.6333\n", "Iteration No: 199 started. Searching for the next optimal point.\n", "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9343\n", - "Function value obtained: -86.1294\n", - "Current minimum: -90.1080\n", + "Time taken: 3.8266\n", + "Function value obtained: -82.9887\n", + "Current minimum: -90.6333\n", "Iteration No: 200 started. Searching for the next optimal point.\n", "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7612\n", - "Function value obtained: -84.8679\n", - "Current minimum: -90.1080\n", + "Time taken: 3.8193\n", + "Function value obtained: -85.0844\n", + "Current minimum: -90.6333\n", "Iteration No: 201 started. Searching for the next optimal point.\n", "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0248\n", - "Function value obtained: -85.9920\n", - "Current minimum: -90.1080\n", + "Time taken: 3.7509\n", + "Function value obtained: -87.3898\n", + "Current minimum: -90.6333\n", "Iteration No: 202 started. Searching for the next optimal point.\n", "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9046\n", - "Function value obtained: -87.3819\n", - "Current minimum: -90.1080\n", + "Time taken: 3.8625\n", + "Function value obtained: -83.5116\n", + "Current minimum: -90.6333\n", "Iteration No: 203 started. Searching for the next optimal point.\n", "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0862\n", - "Function value obtained: -85.9375\n", - "Current minimum: -90.1080\n", + "Time taken: 3.8594\n", + "Function value obtained: -84.4034\n", + "Current minimum: -90.6333\n", "Iteration No: 204 started. Searching for the next optimal point.\n", "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0536\n", - "Function value obtained: -83.4752\n", - "Current minimum: -90.1080\n", + "Time taken: 3.9295\n", + "Function value obtained: -88.9795\n", + "Current minimum: -90.6333\n", "Iteration No: 205 started. Searching for the next optimal point.\n", "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9329\n", - "Function value obtained: -82.0837\n", - "Current minimum: -90.1080\n", + "Time taken: 3.9030\n", + "Function value obtained: -85.8064\n", + "Current minimum: -90.6333\n", "Iteration No: 206 started. Searching for the next optimal point.\n", "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1069\n", - "Function value obtained: -87.3389\n", - "Current minimum: -90.1080\n", + "Time taken: 3.9488\n", + "Function value obtained: -88.4653\n", + "Current minimum: -90.6333\n", "Iteration No: 207 started. Searching for the next optimal point.\n", "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1476\n", - "Function value obtained: -83.5029\n", - "Current minimum: -90.1080\n", + "Time taken: 3.8623\n", + "Function value obtained: -86.9521\n", + "Current minimum: -90.6333\n", "Iteration No: 208 started. Searching for the next optimal point.\n", "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1855\n", - "Function value obtained: -84.9128\n", - "Current minimum: -90.1080\n", + "Time taken: 3.8212\n", + "Function value obtained: -88.2343\n", + "Current minimum: -90.6333\n", "Iteration No: 209 started. Searching for the next optimal point.\n", "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2695\n", - "Function value obtained: -82.9639\n", - "Current minimum: -90.1080\n", + "Time taken: 3.9604\n", + "Function value obtained: -86.4872\n", + "Current minimum: -90.6333\n", "Iteration No: 210 started. Searching for the next optimal point.\n", "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2752\n", - "Function value obtained: -86.7421\n", - "Current minimum: -90.1080\n", + "Time taken: 3.9938\n", + "Function value obtained: -86.5157\n", + "Current minimum: -90.6333\n", "Iteration No: 211 started. Searching for the next optimal point.\n", "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1732\n", - "Function value obtained: -86.2449\n", - "Current minimum: -90.1080\n", + "Time taken: 3.8944\n", + "Function value obtained: -87.9709\n", + "Current minimum: -90.6333\n", "Iteration No: 212 started. Searching for the next optimal point.\n", "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0882\n", - "Function value obtained: -88.0485\n", - "Current minimum: -90.1080\n", + "Time taken: 4.0389\n", + "Function value obtained: -83.9614\n", + "Current minimum: -90.6333\n", "Iteration No: 213 started. Searching for the next optimal point.\n", "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3446\n", - "Function value obtained: -84.6975\n", - "Current minimum: -90.1080\n", + "Time taken: 4.1472\n", + "Function value obtained: -83.4505\n", + "Current minimum: -90.6333\n", "Iteration No: 214 started. Searching for the next optimal point.\n", "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0993\n", - "Function value obtained: -85.7307\n", - "Current minimum: -90.1080\n", + "Time taken: 4.1988\n", + "Function value obtained: -88.4951\n", + "Current minimum: -90.6333\n", "Iteration No: 215 started. Searching for the next optimal point.\n", "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4278\n", - "Function value obtained: -89.1376\n", - "Current minimum: -90.1080\n", + "Time taken: 4.1860\n", + "Function value obtained: -85.7315\n", + "Current minimum: -90.6333\n", "Iteration No: 216 started. Searching for the next optimal point.\n", "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3091\n", - "Function value obtained: -85.4064\n", - "Current minimum: -90.1080\n", + "Time taken: 4.0564\n", + "Function value obtained: -86.7680\n", + "Current minimum: -90.6333\n", "Iteration No: 217 started. Searching for the next optimal point.\n", "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2130\n", - "Function value obtained: -85.2976\n", - "Current minimum: -90.1080\n", + "Time taken: 4.2051\n", + "Function value obtained: -86.0125\n", + "Current minimum: -90.6333\n", "Iteration No: 218 started. Searching for the next optimal point.\n", "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4033\n", - "Function value obtained: -83.8911\n", - "Current minimum: -90.1080\n", + "Time taken: 4.1440\n", + "Function value obtained: -84.4325\n", + "Current minimum: -90.6333\n", "Iteration No: 219 started. Searching for the next optimal point.\n", "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4745\n", - "Function value obtained: -82.3104\n", - "Current minimum: -90.1080\n", + "Time taken: 4.2515\n", + "Function value obtained: -83.7888\n", + "Current minimum: -90.6333\n", "Iteration No: 220 started. Searching for the next optimal point.\n", "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5903\n", - "Function value obtained: -84.6281\n", - "Current minimum: -90.1080\n", + "Time taken: 4.1997\n", + "Function value obtained: -85.1757\n", + "Current minimum: -90.6333\n", "Iteration No: 221 started. Searching for the next optimal point.\n", "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6327\n", - "Function value obtained: -86.7352\n", - "Current minimum: -90.1080\n", + "Time taken: 4.1929\n", + "Function value obtained: -82.7933\n", + "Current minimum: -90.6333\n", "Iteration No: 222 started. Searching for the next optimal point.\n", "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5987\n", - "Function value obtained: -86.7216\n", - "Current minimum: -90.1080\n", + "Time taken: 4.2707\n", + "Function value obtained: -84.3591\n", + "Current minimum: -90.6333\n", "Iteration No: 223 started. Searching for the next optimal point.\n", "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6257\n", - "Function value obtained: -85.3067\n", - "Current minimum: -90.1080\n", + "Time taken: 4.2861\n", + "Function value obtained: -84.6210\n", + "Current minimum: -90.6333\n", "Iteration No: 224 started. Searching for the next optimal point.\n", "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4578\n", - "Function value obtained: -83.1120\n", - "Current minimum: -90.1080\n", + "Time taken: 4.3462\n", + "Function value obtained: -86.3491\n", + "Current minimum: -90.6333\n", "Iteration No: 225 started. Searching for the next optimal point.\n", "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2785\n", - "Function value obtained: -87.8344\n", - "Current minimum: -90.1080\n", + "Time taken: 4.4049\n", + "Function value obtained: -85.1895\n", + "Current minimum: -90.6333\n", "Iteration No: 226 started. Searching for the next optimal point.\n", "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3754\n", - "Function value obtained: -85.6313\n", - "Current minimum: -90.1080\n", + "Time taken: 4.3751\n", + "Function value obtained: -84.9130\n", + "Current minimum: -90.6333\n", "Iteration No: 227 started. Searching for the next optimal point.\n", "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6938\n", - "Function value obtained: -85.1359\n", - "Current minimum: -90.1080\n", + "Time taken: 4.4479\n", + "Function value obtained: -84.6399\n", + "Current minimum: -90.6333\n", "Iteration No: 228 started. Searching for the next optimal point.\n", "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6287\n", - "Function value obtained: -86.7383\n", - "Current minimum: -90.1080\n", + "Time taken: 4.5505\n", + "Function value obtained: -86.8603\n", + "Current minimum: -90.6333\n", "Iteration No: 229 started. Searching for the next optimal point.\n", "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9528\n", - "Function value obtained: -86.4916\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6236\n", + "Function value obtained: -84.5484\n", + "Current minimum: -90.6333\n", "Iteration No: 230 started. Searching for the next optimal point.\n", "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7442\n", - "Function value obtained: -85.4737\n", - "Current minimum: -90.1080\n", + "Time taken: 4.4163\n", + "Function value obtained: -85.6712\n", + "Current minimum: -90.6333\n", "Iteration No: 231 started. Searching for the next optimal point.\n", "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5900\n", - "Function value obtained: -86.8351\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6296\n", + "Function value obtained: -88.0456\n", + "Current minimum: -90.6333\n", "Iteration No: 232 started. Searching for the next optimal point.\n", "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7186\n", - "Function value obtained: -84.9945\n", - "Current minimum: -90.1080\n", + "Time taken: 4.4658\n", + "Function value obtained: -87.9592\n", + "Current minimum: -90.6333\n", "Iteration No: 233 started. Searching for the next optimal point.\n", "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8898\n", - "Function value obtained: -86.3841\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6268\n", + "Function value obtained: -87.7705\n", + "Current minimum: -90.6333\n", "Iteration No: 234 started. Searching for the next optimal point.\n", "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8121\n", - "Function value obtained: -86.3058\n", - "Current minimum: -90.1080\n", + "Time taken: 4.4828\n", + "Function value obtained: -84.6185\n", + "Current minimum: -90.6333\n", "Iteration No: 235 started. Searching for the next optimal point.\n", "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0193\n", - "Function value obtained: -84.2218\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6933\n", + "Function value obtained: -83.6364\n", + "Current minimum: -90.6333\n", "Iteration No: 236 started. Searching for the next optimal point.\n", "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9367\n", - "Function value obtained: -85.0513\n", - "Current minimum: -90.1080\n", + "Time taken: 4.4868\n", + "Function value obtained: -86.9525\n", + "Current minimum: -90.6333\n", "Iteration No: 237 started. Searching for the next optimal point.\n", "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9656\n", - "Function value obtained: -87.7383\n", - "Current minimum: -90.1080\n", + "Time taken: 4.7072\n", + "Function value obtained: -85.5208\n", + "Current minimum: -90.6333\n", "Iteration No: 238 started. Searching for the next optimal point.\n", "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9926\n", - "Function value obtained: -83.9105\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6665\n", + "Function value obtained: -84.9699\n", + "Current minimum: -90.6333\n", "Iteration No: 239 started. Searching for the next optimal point.\n", "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8596\n", - "Function value obtained: -86.8565\n", - "Current minimum: -90.1080\n", + "Time taken: 4.4370\n", + "Function value obtained: -85.0854\n", + "Current minimum: -90.6333\n", "Iteration No: 240 started. Searching for the next optimal point.\n", "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0548\n", - "Function value obtained: -85.1051\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6051\n", + "Function value obtained: -86.2595\n", + "Current minimum: -90.6333\n", "Iteration No: 241 started. Searching for the next optimal point.\n", "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0941\n", - "Function value obtained: -87.4271\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6382\n", + "Function value obtained: -86.4817\n", + "Current minimum: -90.6333\n", "Iteration No: 242 started. Searching for the next optimal point.\n", "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0175\n", - "Function value obtained: -85.0004\n", - "Current minimum: -90.1080\n", + "Time taken: 4.8350\n", + "Function value obtained: -83.1569\n", + "Current minimum: -90.6333\n", "Iteration No: 243 started. Searching for the next optimal point.\n", "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0794\n", - "Function value obtained: -88.7432\n", - "Current minimum: -90.1080\n", + "Time taken: 4.6788\n", + "Function value obtained: -86.6800\n", + "Current minimum: -90.6333\n", "Iteration No: 244 started. Searching for the next optimal point.\n", "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0018\n", - "Function value obtained: -87.7293\n", - "Current minimum: -90.1080\n", + "Time taken: 4.7233\n", + "Function value obtained: -85.5632\n", + "Current minimum: -90.6333\n", "Iteration No: 245 started. Searching for the next optimal point.\n", "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9117\n", - "Function value obtained: -86.6354\n", - "Current minimum: -90.1080\n", + "Time taken: 4.7751\n", + "Function value obtained: -85.7283\n", + "Current minimum: -90.6333\n", "Iteration No: 246 started. Searching for the next optimal point.\n", "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1099\n", - "Function value obtained: -83.7823\n", - "Current minimum: -90.1080\n", + "Time taken: 4.7752\n", + "Function value obtained: -85.8422\n", + "Current minimum: -90.6333\n", "Iteration No: 247 started. Searching for the next optimal point.\n", "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2423\n", - "Function value obtained: -87.3029\n", - "Current minimum: -90.1080\n", + "Time taken: 4.7446\n", + "Function value obtained: -87.3973\n", + "Current minimum: -90.6333\n", "Iteration No: 248 started. Searching for the next optimal point.\n", "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3016\n", - "Function value obtained: -84.9609\n", - "Current minimum: -90.1080\n", + "Time taken: 4.8226\n", + "Function value obtained: -86.2009\n", + "Current minimum: -90.6333\n", "Iteration No: 249 started. Searching for the next optimal point.\n", "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2164\n", - "Function value obtained: -83.7024\n", - "Current minimum: -90.1080\n", + "Time taken: 5.2632\n", + "Function value obtained: -86.0677\n", + "Current minimum: -90.6333\n", "Iteration No: 250 started. Searching for the next optimal point.\n", "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0462\n", - "Function value obtained: -85.2059\n", - "Current minimum: -90.1080\n", + "Time taken: 5.1870\n", + "Function value obtained: -85.0422\n", + "Current minimum: -90.6333\n", "Iteration No: 251 started. Searching for the next optimal point.\n", "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4431\n", - "Function value obtained: -85.5742\n", - "Current minimum: -90.1080\n", + "Time taken: 5.0518\n", + "Function value obtained: -86.9540\n", + "Current minimum: -90.6333\n", "Iteration No: 252 started. Searching for the next optimal point.\n", "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1714\n", - "Function value obtained: -88.2958\n", - "Current minimum: -90.1080\n", + "Time taken: 5.0203\n", + "Function value obtained: -83.2860\n", + "Current minimum: -90.6333\n", "Iteration No: 253 started. Searching for the next optimal point.\n", "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1338\n", - "Function value obtained: -86.4350\n", - "Current minimum: -90.1080\n", + "Time taken: 5.0728\n", + "Function value obtained: -86.5753\n", + "Current minimum: -90.6333\n", "Iteration No: 254 started. Searching for the next optimal point.\n", "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5651\n", - "Function value obtained: -87.6224\n", - "Current minimum: -90.1080\n", + "Time taken: 5.0231\n", + "Function value obtained: -87.2729\n", + "Current minimum: -90.6333\n", "Iteration No: 255 started. Searching for the next optimal point.\n", "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4916\n", - "Function value obtained: -84.6867\n", - "Current minimum: -90.1080\n", + "Time taken: 5.1772\n", + "Function value obtained: -84.3028\n", + "Current minimum: -90.6333\n", "Iteration No: 256 started. Searching for the next optimal point.\n", "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2136\n", - "Function value obtained: -85.6839\n", - "Current minimum: -90.1080\n", + "Time taken: 5.1883\n", + "Function value obtained: -84.6384\n", + "Current minimum: -90.6333\n", "Iteration No: 257 started. Searching for the next optimal point.\n", "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4824\n", - "Function value obtained: -88.2674\n", - "Current minimum: -90.1080\n", + "Time taken: 5.2135\n", + "Function value obtained: -84.3169\n", + "Current minimum: -90.6333\n", "Iteration No: 258 started. Searching for the next optimal point.\n", "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5053\n", - "Function value obtained: -85.4622\n", - "Current minimum: -90.1080\n", + "Time taken: 5.0527\n", + "Function value obtained: -85.2478\n", + "Current minimum: -90.6333\n", "Iteration No: 259 started. Searching for the next optimal point.\n", "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6444\n", - "Function value obtained: -85.1772\n", - "Current minimum: -90.1080\n", + "Time taken: 5.1900\n", + "Function value obtained: -86.1178\n", + "Current minimum: -90.6333\n", "Iteration No: 260 started. Searching for the next optimal point.\n", "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4896\n", - "Function value obtained: -85.1338\n", - "Current minimum: -90.1080\n", + "Time taken: 5.3379\n", + "Function value obtained: -86.5867\n", + "Current minimum: -90.6333\n", "Iteration No: 261 started. Searching for the next optimal point.\n", "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8690\n", - "Function value obtained: -85.7315\n", - "Current minimum: -90.1080\n", + "Time taken: 5.3295\n", + "Function value obtained: -84.9588\n", + "Current minimum: -90.6333\n", "Iteration No: 262 started. Searching for the next optimal point.\n", "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4967\n", - "Function value obtained: -85.2266\n", - "Current minimum: -90.1080\n", + "Time taken: 5.2179\n", + "Function value obtained: -86.0880\n", + "Current minimum: -90.6333\n", "Iteration No: 263 started. Searching for the next optimal point.\n", "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8225\n", - "Function value obtained: -85.2482\n", - "Current minimum: -90.1080\n", + "Time taken: 5.2905\n", + "Function value obtained: -86.5985\n", + "Current minimum: -90.6333\n", "Iteration No: 264 started. Searching for the next optimal point.\n", "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4418\n", - "Function value obtained: -85.4218\n", - "Current minimum: -90.1080\n", + "Time taken: 5.2963\n", + "Function value obtained: -84.9976\n", + "Current minimum: -90.6333\n", "Iteration No: 265 started. Searching for the next optimal point.\n", "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7841\n", - "Function value obtained: -87.3934\n", - "Current minimum: -90.1080\n", + "Time taken: 5.3160\n", + "Function value obtained: -86.9113\n", + "Current minimum: -90.6333\n", "Iteration No: 266 started. Searching for the next optimal point.\n", "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5509\n", - "Function value obtained: -86.6733\n", - "Current minimum: -90.1080\n", + "Time taken: 5.3405\n", + "Function value obtained: -86.0184\n", + "Current minimum: -90.6333\n", "Iteration No: 267 started. Searching for the next optimal point.\n", "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7302\n", - "Function value obtained: -86.7916\n", - "Current minimum: -90.1080\n", + "Time taken: 5.3936\n", + "Function value obtained: -83.4898\n", + "Current minimum: -90.6333\n", "Iteration No: 268 started. Searching for the next optimal point.\n", "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6647\n", - "Function value obtained: -85.9177\n", - "Current minimum: -90.1080\n", + "Time taken: 5.5504\n", + "Function value obtained: -87.5537\n", + "Current minimum: -90.6333\n", "Iteration No: 269 started. Searching for the next optimal point.\n", "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8071\n", - "Function value obtained: -85.0347\n", - "Current minimum: -90.1080\n", + "Time taken: 5.5918\n", + "Function value obtained: -86.3580\n", + "Current minimum: -90.6333\n", "Iteration No: 270 started. Searching for the next optimal point.\n", "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5069\n", - "Function value obtained: -87.4387\n", - "Current minimum: -90.1080\n", + "Time taken: 5.6319\n", + "Function value obtained: -86.8754\n", + "Current minimum: -90.6333\n", "Iteration No: 271 started. Searching for the next optimal point.\n", "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6538\n", - "Function value obtained: -81.9073\n", - "Current minimum: -90.1080\n", + "Time taken: 5.6179\n", + "Function value obtained: -87.3622\n", + "Current minimum: -90.6333\n", "Iteration No: 272 started. Searching for the next optimal point.\n", "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6946\n", - "Function value obtained: -86.6597\n", - "Current minimum: -90.1080\n", + "Time taken: 5.5324\n", + "Function value obtained: -87.1565\n", + "Current minimum: -90.6333\n", "Iteration No: 273 started. Searching for the next optimal point.\n", "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9044\n", - "Function value obtained: -85.9946\n", - "Current minimum: -90.1080\n", + "Time taken: 5.5720\n", + "Function value obtained: -89.2305\n", + "Current minimum: -90.6333\n", "Iteration No: 274 started. Searching for the next optimal point.\n", "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9727\n", - "Function value obtained: -85.4345\n", - "Current minimum: -90.1080\n", + "Time taken: 5.8214\n", + "Function value obtained: -86.7361\n", + "Current minimum: -90.6333\n", "Iteration No: 275 started. Searching for the next optimal point.\n", "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6902\n", - "Function value obtained: -89.4217\n", - "Current minimum: -90.1080\n", + "Time taken: 5.7659\n", + "Function value obtained: -84.9475\n", + "Current minimum: -90.6333\n", "Iteration No: 276 started. Searching for the next optimal point.\n", "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2746\n", - "Function value obtained: -88.7301\n", - "Current minimum: -90.1080\n", + "Time taken: 5.8156\n", + "Function value obtained: -85.5211\n", + "Current minimum: -90.6333\n", "Iteration No: 277 started. Searching for the next optimal point.\n", "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1494\n", - "Function value obtained: -85.3028\n", - "Current minimum: -90.1080\n", + "Time taken: 5.7959\n", + "Function value obtained: -84.9771\n", + "Current minimum: -90.6333\n", "Iteration No: 278 started. Searching for the next optimal point.\n", "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9163\n", - "Function value obtained: -88.7193\n", - "Current minimum: -90.1080\n", + "Time taken: 5.5755\n", + "Function value obtained: -88.0128\n", + "Current minimum: -90.6333\n", "Iteration No: 279 started. Searching for the next optimal point.\n", "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9043\n", - "Function value obtained: -85.9005\n", - "Current minimum: -90.1080\n", + "Time taken: 6.0321\n", + "Function value obtained: -85.9124\n", + "Current minimum: -90.6333\n", "Iteration No: 280 started. Searching for the next optimal point.\n", "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1046\n", - "Function value obtained: -88.5985\n", - "Current minimum: -90.1080\n", + "Time taken: 5.8723\n", + "Function value obtained: -85.1234\n", + "Current minimum: -90.6333\n", "Iteration No: 281 started. Searching for the next optimal point.\n", "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8468\n", - "Function value obtained: -87.1297\n", - "Current minimum: -90.1080\n", + "Time taken: 5.9973\n", + "Function value obtained: -84.9108\n", + "Current minimum: -90.6333\n", "Iteration No: 282 started. Searching for the next optimal point.\n", "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1069\n", - "Function value obtained: -88.3291\n", - "Current minimum: -90.1080\n", + "Time taken: 6.0118\n", + "Function value obtained: -87.5869\n", + "Current minimum: -90.6333\n", "Iteration No: 283 started. Searching for the next optimal point.\n", "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1237\n", - "Function value obtained: -86.3832\n", - "Current minimum: -90.1080\n", + "Time taken: 6.1184\n", + "Function value obtained: -87.8984\n", + "Current minimum: -90.6333\n", "Iteration No: 284 started. Searching for the next optimal point.\n", "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0980\n", - "Function value obtained: -85.8780\n", - "Current minimum: -90.1080\n", + "Time taken: 5.9292\n", + "Function value obtained: -84.3207\n", + "Current minimum: -90.6333\n", "Iteration No: 285 started. Searching for the next optimal point.\n", "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3353\n", - "Function value obtained: -85.0982\n", - "Current minimum: -90.1080\n", + "Time taken: 6.1385\n", + "Function value obtained: -87.6335\n", + "Current minimum: -90.6333\n", "Iteration No: 286 started. Searching for the next optimal point.\n", "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2966\n", - "Function value obtained: -85.5723\n", - "Current minimum: -90.1080\n", + "Time taken: 6.1387\n", + "Function value obtained: -86.9994\n", + "Current minimum: -90.6333\n", "Iteration No: 287 started. Searching for the next optimal point.\n", "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3444\n", - "Function value obtained: -87.1795\n", - "Current minimum: -90.1080\n", + "Time taken: 6.3565\n", + "Function value obtained: -85.1528\n", + "Current minimum: -90.6333\n", "Iteration No: 288 started. Searching for the next optimal point.\n", "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1063\n", - "Function value obtained: -83.4052\n", - "Current minimum: -90.1080\n", + "Time taken: 6.0750\n", + "Function value obtained: -84.0035\n", + "Current minimum: -90.6333\n", "Iteration No: 289 started. Searching for the next optimal point.\n", "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3829\n", - "Function value obtained: -86.3743\n", - "Current minimum: -90.1080\n", + "Time taken: 6.5232\n", + "Function value obtained: -85.4554\n", + "Current minimum: -90.6333\n", "Iteration No: 290 started. Searching for the next optimal point.\n", "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0629\n", - "Function value obtained: -84.3291\n", - "Current minimum: -90.1080\n", + "Time taken: 6.4644\n", + "Function value obtained: -87.0136\n", + "Current minimum: -90.6333\n", "Iteration No: 291 started. Searching for the next optimal point.\n", "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2690\n", - "Function value obtained: -87.2789\n", - "Current minimum: -90.1080\n", + "Time taken: 6.4834\n", + "Function value obtained: -84.7633\n", + "Current minimum: -90.6333\n", "Iteration No: 292 started. Searching for the next optimal point.\n", "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4390\n", - "Function value obtained: -83.5484\n", - "Current minimum: -90.1080\n", + "Time taken: 6.4423\n", + "Function value obtained: -85.8865\n", + "Current minimum: -90.6333\n", "Iteration No: 293 started. Searching for the next optimal point.\n", "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6583\n", - "Function value obtained: -86.7345\n", - "Current minimum: -90.1080\n", + "Time taken: 6.1903\n", + "Function value obtained: -88.6420\n", + "Current minimum: -90.6333\n", "Iteration No: 294 started. Searching for the next optimal point.\n", "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3726\n", - "Function value obtained: -85.4131\n", - "Current minimum: -90.1080\n", + "Time taken: 6.4984\n", + "Function value obtained: -87.5296\n", + "Current minimum: -90.6333\n", "Iteration No: 295 started. Searching for the next optimal point.\n", "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 6.2427\n", - "Function value obtained: -85.6367\n", - "Current minimum: -90.1080\n", + "Time taken: 6.5800\n", + "Function value obtained: -84.3343\n", + "Current minimum: -90.6333\n", "Iteration No: 296 started. Searching for the next optimal point.\n", "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5675\n", - "Function value obtained: -85.2891\n", - "Current minimum: -90.1080\n", + "Time taken: 6.4310\n", + "Function value obtained: -84.2970\n", + "Current minimum: -90.6333\n", "Iteration No: 297 started. Searching for the next optimal point.\n", "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6454\n", - "Function value obtained: -85.0394\n", - "Current minimum: -90.1080\n", + "Time taken: 6.6753\n", + "Function value obtained: -83.7032\n", + "Current minimum: -90.6333\n", "Iteration No: 298 started. Searching for the next optimal point.\n", "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3081\n", - "Function value obtained: -86.2236\n", - "Current minimum: -90.1080\n", + "Time taken: 6.5152\n", + "Function value obtained: -85.6559\n", + "Current minimum: -90.6333\n", "Iteration No: 299 started. Searching for the next optimal point.\n", "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6895\n", - "Function value obtained: -84.9832\n", - "Current minimum: -90.1080\n", + "Time taken: 6.1695\n", + "Function value obtained: -86.4604\n", + "Current minimum: -90.6333\n", "Iteration No: 300 started. Searching for the next optimal point.\n", "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6400\n", - "Function value obtained: -88.0309\n", - "Current minimum: -90.1080\n", - "CPU times: user 3h 29min 43s, sys: 1h 10min 51s, total: 4h 40min 34s\n", - "Wall time: 16min 46s\n" + "Time taken: 6.6265\n", + "Function value obtained: -83.0904\n", + "Current minimum: -90.6333\n", + "CPU times: user 2h 52min 17s, sys: 1h 11min 30s, total: 4h 3min 48s\n", + "Wall time: 16min 21s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-90.63333622820284,\n", + " [-1.7521564679093693, 0.5440615729465406, 0.29119675741251316])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "cr_gp.fun, cr_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:51,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 10.3604\n", + "Function value obtained: -204.8880\n", + "Current minimum: -204.8880\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:12:01,442\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 10.9740\n", + "Function value obtained: -366.4789\n", + "Current minimum: -366.4789\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:12:12,420\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 10.0220\n", + "Function value obtained: -410.2703\n", + "Current minimum: -410.2703\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:12:22,444\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 10.9982\n", + "Function value obtained: -24.3890\n", + "Current minimum: -410.2703\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:12:33,378\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.2479\n", + "Function value obtained: -354.9929\n", + "Current minimum: -410.2703\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:12:43,724\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 11.0869\n", + "Function value obtained: -282.0534\n", + "Current minimum: -410.2703\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:12:54,778\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 10.7217\n", + "Function value obtained: -409.6809\n", + "Current minimum: -410.2703\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:13:05,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 11.0860\n", + "Function value obtained: -370.5645\n", + "Current minimum: -410.2703\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:13:16,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 11.4416\n", + "Function value obtained: -399.4599\n", + "Current minimum: -410.2703\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:13:27,993\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 14.8176\n", + "Function value obtained: -165.9382\n", + "Current minimum: -410.2703\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:13:42,871\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4239\n", + "Function value obtained: -417.1804\n", + "Current minimum: -417.1804\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:13:54,279\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5685\n", + "Function value obtained: -18.8272\n", + "Current minimum: -417.1804\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:14:05,864\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4953\n", + "Function value obtained: -415.8945\n", + "Current minimum: -417.1804\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:14:18,451\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1344\n", + "Function value obtained: -411.5031\n", + "Current minimum: -417.1804\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:14:30,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6181\n", + "Function value obtained: -341.4892\n", + "Current minimum: -417.1804\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:14:42,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5405\n", + "Function value obtained: -411.7262\n", + "Current minimum: -417.1804\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:14:54,660\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4247\n", + "Function value obtained: -424.1434\n", + "Current minimum: -424.1434\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:15:07,143\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6295\n", + "Function value obtained: -427.8426\n", + "Current minimum: -427.8426\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:15:19,767\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3900\n", + "Function value obtained: -414.4530\n", + "Current minimum: -427.8426\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:15:31,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4676\n", + "Function value obtained: -432.9289\n", + "Current minimum: -432.9289\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:15:42,588\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7375\n", + "Function value obtained: -427.3274\n", + "Current minimum: -432.9289\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:15:53,318\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7837\n", + "Function value obtained: -418.1603\n", + "Current minimum: -432.9289\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:16:04,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5257\n", + "Function value obtained: -434.0414\n", + "Current minimum: -434.0414\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:16:14,643\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8756\n", + "Function value obtained: -436.0045\n", + "Current minimum: -436.0045\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:16:26,573\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0482\n", + "Function value obtained: -426.7072\n", + "Current minimum: -436.0045\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:16:37,552\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1580\n", + "Function value obtained: -436.8424\n", + "Current minimum: -436.8424\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:16:48,779\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6512\n", + "Function value obtained: -440.6005\n", + "Current minimum: -440.6005\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:17:00,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1795\n", + "Function value obtained: -435.5124\n", + "Current minimum: -440.6005\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:17:11,681\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9372\n", + "Function value obtained: -0.0000\n", + "Current minimum: -440.6005\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:17:23,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4215\n", + "Function value obtained: -412.5347\n", + "Current minimum: -440.6005\n", + "CPU times: user 3min 17s, sys: 5min 45s, total: 9min 3s\n", + "Wall time: 5min 43s\n" ] }, { "data": { "text/plain": [ - "(-90.10801912597402,\n", - " [-1.5802360403803877, 0.3781959292149372, 0.3293809377265017])" + "(-440.6004877953126, [0.0, 0.7853961999069485, 0.2264118934036974])" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gbrt = gp_minimize(cr_obj, cr_space, n_calls = 300, verbose=True, n_jobs=-1)\n", + "cr_gbrt = gp_minimize(cr_obj, cr_space, n_calls = 30, verbose=True, n_jobs=-1)\n", "cr_gbrt.fun, cr_gbrt.x" ] }, @@ -9528,7 +7587,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 12, "id": "6a61d3fa-97a9-4274-945c-be2742d1e956", "metadata": {}, "outputs": [], @@ -9549,7 +7608,7 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 13, "id": "b86effb9-d8ad-4b50-8174-ea76dcd60c32", "metadata": { "scrolled": true @@ -9562,110 +7621,60 @@ "# cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", "# cr_gp_args['y2'] = cr_gp_preargs['y2']\n", "\n", - "# cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", - "# cr_gbrt_args = {}\n", - "# cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", - "# cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", - "# cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", + "cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", + "cr_gbrt_args = {}\n", + "cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", "\n", "# msy_gp_args = {'mortality': msy_gp.x[0]}\n", "# msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", "\n", "# esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", - "# esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", + "esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", "\n", - "msy_gbrt_args = {'mortality': 0.05365088255575121}\n", - "esc_gbrt_args = {'escapement': 0.010338225232077163}\n", - "cr_gbrt_args = {\n", - " 'x1': 0.009159055923137423,\n", - " 'x2': 0.015139834077385755,\n", - " 'y2': 0.29119675741251316,\n", - "}\n", + "# msy_gbrt_args = {'mortality': 0.05365088255575121}\n", + "# esc_gbrt_args = {'escapement': 0.010338225232077163}\n", + "# cr_gbrt_args = {\n", + "# 'x1': 0.009159055923137423,\n", + "# 'x2': 0.015139834077385755,\n", + "# 'y2': 0.29119675741251316,\n", + "# }\n", "\n", "#\n", "\n", "env = AsmEnv(config=CONFIG)\n", "\n", "cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", - "cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))\n", + "# cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))\n", "\n", "esc_gbrt_df = get_policy_df(ConstEsc(env, **esc_gbrt_args))\n", - "esc_gp_df = get_policy_df(ConstEsc(env, **esc_gp_args))\n", + "# esc_gp_df = get_policy_df(ConstEsc(env, **esc_gp_args))\n", "\n", - "msy_gbrt_df = get_policy_df(Msy(env, **msy_gbrt_args))\n", - "msy_gp_df = get_policy_df(Msy(env, **msy_gp_args))" + "# msy_gbrt_df = get_policy_df(Msy(env, **msy_gbrt_args))\n", + "# msy_gp_df = get_policy_df(Msy(env, **msy_gp_args))" ] }, { "cell_type": "code", - "execution_count": 109, + "execution_count": 14, "id": "88d5b45d-eeed-4321-9e9d-1a58ba63e84c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(,\n", - " ,\n", - " ,\n", - " ,\n", - " )" + "(,\n", + " )" ] }, - "execution_count": 109, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" - } - ], - "source": [ - "(\n", - " cr_gp_df[cr_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", - " esc_gp_df[esc_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", - " cr_gbrt_df[cr_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", - " esc_gbrt_df[esc_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GBRT policy'),\n", - " msy_gbrt_df[msy_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='MSY GP policy'),\n", - ") " - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "id": "7bd544a0-0ea7-4625-b391-14759d94f8b0", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", 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", 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", 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", 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", + "image/png": 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", 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" ] @@ -9685,7 +7694,13 @@ } ], "source": [ - "plt.show()" + "(\n", + " # cr_gp_df[cr_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", + " # esc_gp_df[esc_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", + " cr_gbrt_df[cr_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", + " esc_gbrt_df[esc_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GBRT policy'),\n", + " # msy_gbrt_df[msy_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='MSY GP policy'),\n", + ") " ] }, { @@ -9937,29 +7952,25 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 15, "id": "f9c0a041-1921-40fd-beaa-1dacabf46574", "metadata": {}, "outputs": [], "source": [ - "msy_gbrt_args = {'mortality': 0.05365088255575121}\n", - "esc_gbrt_args = {'escapement': 0.010338225232077163}\n", - "cr_gbrt_args = {\n", - " 'x1': 0.009159055923137423,\n", - " 'x2': 0.015139834077385755,\n", - " 'y2': 0.29119675741251316,\n", - "}" + "# msy_gbrt_args = {'mortality': 0.05365088255575121}\n", + "# esc_gbrt_args = {'escapement': 0.010338225232077163}\n", + "# cr_gbrt_args = {\n", + "# 'x1': 0.009159055923137423,\n", + "# 'x2': 0.015139834077385755,\n", + "# 'y2': 0.29119675741251316,\n", + "# }" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "5163a6f7-e13d-473e-8180-6d686a969004", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -9967,54 +7978,42 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-19 19:57:16,746\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:57:23,514\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:57:30,652\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:57:37,784\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:57:44,630\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:57:51,285\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:57:58,210\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:58:05,222\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:58:11,999\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:58:18,799\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:58:25,769\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:58:32,700\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:58:39,627\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 19:58:46,438\tINFO worker.py:1752 -- Started a local Ray instance.\n" + "2024-04-26 22:24:10,322\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-04-26 22:24:21,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], "source": [ "pol_env = AsmEnv(config=CONFIG)\n", "\n", - "msy_rews = eval_pol(\n", - " policy=Msy(env=pol_env, **msy_gbrt_args), \n", - " env_cls=AsmEnv, config=CONFIG, \n", - " n_batches=5, batch_size=70\n", - ")\n", + "# msy_rews = eval_pol(\n", + "# policy=Msy(env=pol_env, **msy_gbrt_args), \n", + "# env_cls=AsmEnv, config=CONFIG, \n", + "# n_batches=5, batch_size=70\n", + "# )\n", "\n", "esc_rews = eval_pol(\n", " policy=ConstEsc(env=pol_env, **esc_gbrt_args), \n", " env_cls=AsmEnv, config=CONFIG, \n", - " n_batches=5, batch_size=70\n", + " n_batches=1, batch_size=200\n", ")\n", "\n", "cr_rews = eval_pol(\n", " policy=CautionaryRule(env=pol_env, **cr_gbrt_args), \n", " env_cls=AsmEnv, config=CONFIG, \n", - " n_batches=5, batch_size=70\n", + " n_batches=1, batch_size=200\n", ")" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "id": "56a537f8-545d-4ef9-9671-d0906464400c", "metadata": {}, "outputs": [ { "data": { - "image/png": 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" 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bbUydOjXYUJIkSVIT1TA+JUiSpBopKyvj+9//Pvn5+cSEQtx37VVkNG8edKxdpCYn8eAN3yIhNpbi4uJd1imUJEmSVH8sACVJaoQefPBBPvnkE6Bi443Du3UNONGe9e3Qgd9ddD4AK1as4JZbbnE9QEmSJKmeWQBKktTIzJ8/nz/96U8A9GqXzS2nnxpwon27eOgQzjuyYlOQCRMm8OyzzwacSJIkSWpaLAAlSWpEIpEIP/3pTykqKiI2JoZ7rrqchLi4oGPtUygU4ncXnUf7jAwAfvnLX7Js2bKAU0mSJElNhwWgJEmNyJgxY/jggw8AuP7E4+jToX3AiaqnRWIif7v6CkKhEHl5edx0002UlZUFHUuSJElqEiwAJUlqJHJzc/nNb34DQPuMDL5/6skBJ6qZI3p048YTjwfg008/5T//+U/AiSRJkqSmwQJQkqRG4o9//CMbNmwA4LcXnkdSQkLAiWrultNPpUdWWwDuvPNOVq5cGXAiSZIkKfpZAEqS1AjMmzePxx9/HIAT+vXlxAH9gg10gBLi4vjz5ZcQCoXIz8/nJz/5ibsCS5IkSXXMAlCSpEbgd7/7HeXl5cSFw9x+/jlBx/lGBnXtwpUjjgbgrbfe4qWXXgo4kSRJkhTdLAAlSWrg3nvvPd58800ArhxxNJ1bZwac6Jv76Vmnk5WeBsDtt9/Otm3bgg0kSZIkRTELQEmSGrDy8vKqjT9SEhMb3cYfe9O8WTN+e+F5AKxfv56//vWvASeSJEmSopcFoCRJDdhLL73EjBkzAPjeqSeR3jw54ES15+QB/RnW6yAAHnroIRYsWBBwIkmSJCk6WQBKktRAlZaWctdddwHQLiOdq44ZHnCi2hUKhfjthecRGxNDaWkpt912mxuCSJIkSXXAAlCSpAZqzJgxLF68GIAfnHYKzeLiAk5U+3pkteXqY0cA8L///Y///ve/ASeSJEmSoo8FoCRJDVBJSUnVungdW7XkvMFHBJyo7tw88hQyU1oA8Ktf/YrCwsKAE0mSJEnRxQJQkqQG6Pnnn2fp0qVAxei/uHA42EB1KCUxkZ+dfSYAy5Yt47HHHgs4kSRJkhRdLAAlSWpgSkpKuOeeewDonJnJOUccFnCiunfekYfTu307AP72t7+Rm5sbcCJJkiQpelgASpLUwIwbN47ly5cD8IPTTiY2ikf/VYqJieEX51SMAszJyeG+++4LOJEkSZIUPSwAJUlqQCKRCA888ABQsfPvmYcPCjhR/Tn64F4MPagnAA8//DBr1qwJOJEkSZIUHSwAJUlqQCZNmsSsWbMAuO7446J67b+vC4VCVaMACwsL+fOf/xxwIkmSJCk6WABKktSAVI7+S0tO4qKhgwNOU//6derImYdVjHp89tlnmTdvXsCJJEmSpMbPAlCSpAZiypQpvP/++wBcOeJokhISAk4UjJ+cOZK4cJjy8nL+9Kc/BR1HkiRJavQsACVJaiDuv/9+ABLi4rj6mOEBpwlOx8xWXDLsKABee+01ZsyYEXAiSZIkqXGzAJQkqQFYvHgxr776KgAXDjmSli1aBJwoWN895UQSYmMB+Mtf/hJwGkmSJKlxswCUJKkB+Pe//00kEiEmFOK6E44NOk7g2qalcenRQwF4/fXXmTZtWsCJJEmSpMbLAlCSpIBt376d0aNHA3DSgP50yswMOFHD8J2TTyAhLg6Au+66K+A0kiRJUuNlAShJUsCef/55tm/fDsBVxxwdcJqGo01qKpfvGAU4ceJEpkyZEnAiSZIkqXGyAJQkKUCRSIT//Oc/APTIasuQnj0CTtSw3HjSCTTbMQrwz3/+c8BpJEmSpMbJAlCSpAC99957zJ8/H4CrRhxNKBQKOFHD0jo1hStGVIyKfPvtt10LUJIkSToAFoCSJAWocvRfi2bNOPfIIwJO0zBdf8JxVTsC33vvvQGnkSRJkhofC0BJkgKyYsUK3njjDQDOH3Ikyc0SAk7UMLVOTeGCowYD8Oqrr7JgwYKAE0mSJEmNiwWgJEkBefzxxykvLwfgiuHDAk7TsN1w4vGEY2KIRCLcf//9QceRJEmSGhULQEmSAlBcXMwzzzwDwPCDe9GtbZuAEzVsHVu15MzDDgXghRdeYOXKlQEnkiRJkhoPC0BJkgLwxhtvsHHjRgAuPXpowGkah5tOPhGA0tJS/vnPfwacRpIkSWo8LAAlSQrA008/DUCrFi04oX/fgNM0Dj2zszh5QH+g4vevskCVJEmStG8WgJIk1bMVK1bwzjvvAHD+kCOIC4eDDdSI3HRKxSjAgoICHn744YDTSJIkSY2DBaAkSfXs2WefJRKJAHDRUUMCTtO4HNK5E0MP6gnAf/7zH7Zu3RpwIkmSJKnhswCUJKkelZWVVW3+cWSPbnRt0zrgRI1P5SjArVu3Vk2lliRJkrR3FoCSJNWjd955h1WrVgFw8VBH/x2IoQf1pE+H9gA8/PDDlJSUBJxIkiRJatgsACVJqkejRo0CoEWzZpw68JBgwzRSoVCI6044FoBVq1bxyiuvBJxIkiRJatgsACVJqicbNmzgjTfeAOCsIw4jMT4+4ESN1+mDDiUrPQ2Af/3rX1VrKkqSJEnanQWgJEn15MUXX6yarnrxUYMDTtO4xYXDXH3MCACmTp3KRx99FHAiSZIkqeGyAJQkqZ688MILAByUnUXfjh0CTtP4XTJsCMkJCUDFKEBJkiRJe2YBKElSPZg3bx7Tp08H4NwjDycUCgWcqPFLTUqq2kjlv//9L4sWLQo4kSRJktQwWQBKklQPnn/+eaBiA4uzDh8UcJrocc1xI4gJhYhEIjz44INBx5EkSZIaJAtASZLqWHl5OWPGjAFg6EE9yUpPDzhR9OjQsiWnDhwAwOjRo9m0aVPAiSRJkqSGxwJQkqQ69sEHH7B69WqgYvqvatd1JxwHQGFhIY8//niwYSRJkqQGyAJQkqQ6Vjn9NzE+nlMOGRBwmugzsEtnBnXtAsDjjz9etdOyJEmSpAoWgJIk1aH8/HxeeeUVAE4+pD/JzRICThSdrjl2BABr167l1VdfDTiNJEmS1LDEBh1AjUM4HI7Kc6l2Vf7s/BlGD3+W39zEiRPJy8sD4Lwjj6jX3X8rz9UUdhw+9dBDaDMmlXW5uTzyyCOcf/75QUeqE16TjZfvkdHHn2Xj5jUZffxZSvsWikQikaBDSJIUrUaOHMmECRNok5bKl3f/H7H+5bTO/O2V1/i/seMA+Pzzzxk0yN2WJUmSJHAEoKopJyenTo+fkpJCOBymrKyMrVu31um5VHfC4TApKSls3bqVsrKyoOPoAHk91p7NmzczceJEAE4/dCBlpaWUlZbW2/lDoRDx8fEUFxfTFL7vu2jIkfxt/GsUlZby17/+lX/84x9BR6oVXpPRwffI6OD1GD28JqNDXV+T6enptX5MKSgWgKqW+nxT9A248SsrK/PnGCX8OX4z48ePp3RH4XfGYYcGVsJFIpEmUQBmNG/OGYcdypiPP+XFF1/k9ttvJzMzM+hYtcprsvHzPTJ6+HOMDl6T0cOfo7RvbgIiSVIdGTeuYjpq+5YZHNK5U8BpmoarjxkOQHFxMU8++WTAaSRJkqSGwQJQkqQ6sH79et577z0Azhh0aJPYiKMh6NepI4d16wrA448/TklJScCJJEmSpOBZAEqSVAdeffVVysvLATj9sIEBp2laKkcBrl27lldffTXgNJIkSVLwLAAlSaoDL7/8MgBdWmfSp337YMM0MacMHECb1FQA/v3vfwecRpIkSQqeBaAkSbVszZo1fPzxxwCc7vTfehcXDnPFiGEAfPbZZ0ybNi3gRJIkSVKwLAAlSapl48aNq9p198zDDg04TdN0ydCjiI8NA44ClCRJkiwAJUmqZZW7//bMyqJndlbAaZqmViktOGPQIKDi57F58+aAE0mSJEnBsQCUJKkWrVixgs8//xxw84+gVU4DLiwsZPTo0QGnkSRJkoJjAShJUi2qHP0HcMYgp/8G6ZDOnejToWIDlscff7xqV2ZJkiSpqbEAlCSpFr300ksA9OnQnq5tWgecpmkLhUJcMbxiFOCSJUuYPHlywIkkSZKkYFgASpJUS5YuXcr06dMBOH2Q038bgrMOH0RKYiJQMQpQkiRJaoosACVJqiUTJkyoun3qwAEBJlGlpIQEzht8BABvvPEGq1atCjiRJEmSVP8sACVJqiWvvvoqAL3aZdOltdN/G4rLjh4KQHl5OU899VTAaSRJkqT6ZwEoSVItWLt2LZ999hkApxzSP+A02lmPrLYM6dkDgKeeeoqSkpKAE0mSJEn1ywJQkqRa8Prrr1fdPuUQp/82NJWbgaxfv36XqdqSJElSU2ABKElSLXjttdcA6JTZil7tsgNOo6876ZD+ZKakAPDYY48FnEaSJEmqXxaAkiR9Qzk5OXzwwQdAxei/UCgUcCJ9XVw4zCXDhgDwwQcfMH/+/IATSZIkSfXHAlCSpG9o4sSJlJaWAq7/15BdOuwowjEVf/VxFKAkSZKaEgtASZK+ocrpv21SUzmkc6eA02hvstLTOaFfXwCee+458vLyAk4kSZIk1Q8LQEmSvoHt27fzv//9D4CTD+lPTIxvrQ3ZFSMqNgPZtm0bY8eODTiNJEmSVD/8lCJJ0jcwadIkCgsLAXf/bQyGHtSTzpmZADz66KNEIpGAE0mSJEl1zwJQkqRvoHL6b1pyEkf26BZwGu1PTEwMlw8fCsDMmTP54osvAk4kSZIk1T0LQEmSDlBRURETJ04E4MT+/YgNhwNOpOq4YMiRJMTFAW4GIkmSpKbBAlCSpAP03nvvsX37dgBOHXhIsGFUbWnJyZwxaCAA48aNIycnJ+BEkiRJUt2yAJQk6QD997//BSAxPp6hvXoGnEY1cfnwis1AioqKeO655wJOI0mSJNUtC0BJkg5AJBLhjTfeAGB471402zGlVI3DIZ070bt9OwAef/xxNwORJElSVLMAlCTpAEyfPp21a9cCFev/qXEJhUJVowAXLVrE+++/H3AiSZIkqe5YAEqSdAAqp/+GQiGO7dM74DQ6EGcdPojmzRKAilGAkiRJUrSyAJQk6QBUTv89tEtnWqW0CDiNDkTzZs04+4jDAZgwYULViE5JkiQp2lgASpJUQ6tWrWLGjBkAnNi/b8Bp9E1cfvRQAEpLS3nmmWcCTiNJkiTVDQtASZJqaOLEiVW3T3D9v0bt4PbtGNS1CwBPPfUUZWVlASeSJEmSap8FoCRJNVQ5/bdTZiu6t20TcBp9U5cPrxgFuHLlSt5+++2A00iSJEm1zwJQkqQa2L59e9WOsSf070soFAo4kb6p0w4dSFpyEuBmIJIkSYpOFoCSJNXA//73P4qLiwE40em/UaFZXBwXDBkMwFtvvcWKFSsCTiRJkiTVLgtASZJq4L///S8AKYmJHNata8BpVFsuHXYUAJFIhCeffDLgNJIkSVLtsgCUJKmaysrKePPNNwE4tm9v4sLhgBOptnRt05qhB/UEYNSoUVWjPCVJkqRoYAEoSVI1ffbZZ2zevBlw+m80unz4MAA2bNjA66+/HnAaSZIkqfZYAEqSVE0TJ04EIDYmhhF9Dg44jWrbiQP6kZmSArgZiCRJkqKLBaAkSdX0xhtvAHBkj+6kJCYGnEa1LS4c5uKhQwB4//33WbBgQcCJJEmSpNphAShJUjUsWrSoqhBy+m/0umTYEGJCIQA3A5EkSVLUsACUJKkaKjf/ADi+f98Ak6gutcvI4Li+fQAYPXo0BQUFASeSJEmSvjkLQEmSquGtt94CoEdWWzq2ahlwGtWly4YPBWDLli2MGzcu4DSSJEnSN2cBKEnSfmzfvp0PP/wQgGP79A44jeraiN4H075lBgBPPPFEwGkkSZKkb84CUJKk/XjvvfcoKSkB4Lh+fQJOo7oWjonh0mFHAfD5558zY8aMgBNJkiRJ34wFoCRJ+1G5/l/zZgkc1q1rwGlUHy48ajBx4TDgKEBJkiQ1fhaAkiTtQyQSqVr/7+iDe1WVQopumSkpnHLIAADGjBnD9u3bA04kSZIkHTgLQEmS9mH27NmsWbMGgGP7uv5fU1K5GUheXh5jxowJOI0kSZJ04CwAJUnah8rRfwDH9LYAbEoG9+hOt7ZtAHj88ceJRCIBJ5IkSZIOjAWgJEn7UFkA9unQnjZpqQGnUX0KhUJcfnTFKMBZs2bx+eefB5xIkiRJOjAWgJIk7cWWLVv47LPPADi2j6P/mqLzjjyChLg4oGIUoCRJktQYWQBKkrQX77zzDmVlZYDr/zVVqclJnHnYoQCMGzeOzZs3B5xIkiRJqjkLQEmS9qJy+m9achIDu3QONowCc9mOacBFRUU899xzAaeRJEmSas4CUJKkPSgvL2fSpEkADD/4YMIxvmU2VYd07kSfDu0BNwORJElS4+SnGUmS9mD69Ols2LABcPpvU7fzZiCLFy/mvffeCziRJEmSVDMWgJIk7UHl9N9QKMSI3r0CTqOgnXX4YTRvlgC4GYgkSZIaHwtASZL2oLIAPKRTR1q2aBFwGgUtuVkC5xxxOACvv/46a9euDTiRJEmSVH0WgJIkfc3GjRv58ssvAaf/6iuVm4GUlpYyatSogNNIkiRJ1WcBKEnS10yaNKlqo4dj+/YJOI0aioPbt2NQ1y4APPXUU5SVlQWcSJIkSaoeC0BJkr6mcvpvqxYt6Ltj91cJ4PLhwwBYtWoVb7/9dsBpJEmSpOqxAJQkaSelpaX873//A+CYPgcTE+Nbpb5y2qGHkJacBMBjjz0WcBpJkiSpevxUI0nSTr744gu2bNkCuP6fdtcsLo4LhgwG4O2332b58uUBJ5IkSZL2zwJQkqSdVE7rjAmFOLpXr4DTqCG67OijAIhEIjz11FMBp5EkSZL2zwJQkqSdVE7/HdilM6k7pnpKO+vSujXDeh0EwKhRoyguLg44kSRJkrRvFoCSJO2wceNGpk2bBsCIPgcHnEYN2WVHDwVgw4YNTJgwIeA0kiRJ0r5ZAEqStMPkyZOJRCIAjOhtAai9O3FAP1qnpgDwxBNPBJxGkiRJ2jcLQEmSdpg0aRIAaclJ9OvYIeA0asjiwmEuHjoEgPfff58FCxYEnEiSJEnaOwtASZKA8vLyqvX/hh/ci3CMb5Hat0uGHkVMKAQ4ClCSJEkNm59uJEkCZs2axYYNGwAY7vRfVUN2RjrH9+sDwOjRoykoKAg4kSRJkrRnFoCSJPHV7r9QMQJQqo7Ljh4GQG5uLuPGjQs4jSRJkrRnFoCSJPFVAXhwu2zapKUGnEaNxfDevWjfMgOAxx9/PNgwkiRJ0l7EBh1AkqSgbd++nU8++QRw+m9jFolE2Lx9Ozl5+WwvLGR7YSGFxcVEIhAKQSgUIiEujtTERFokJpKenExKUiKhHev4HYhwTAyXHT2UP7/8Cl988QXTp0+nf//+tfiqJEmSpG/OAlCS1OR98MEHlJSUABUjutRwlZWXs3zjRhasWcv81WtZuHYtq3NyWJOzhXVbcikqLa3R8ZIS4mmXkUF2ejrd27ahV7tserXLpmdWW5rFx1frGBcMOZJ7XplASVkZTz75JHffffeBvDRJkiSpzlgASpKavEmTJgGQGB/P4d26BpxGO1uTk8OXS5by5eKlTFmylJkrVlK0o6ytDflFxSxYs5YFa9Yyefacql+PjYmhX8cOHN69G0d078bgnt1pkZi4x2NkpqRwyiEDeOWLL3nhhRf4zW9+Q4sWLWotoyRJkvRNWQBKkpq8ygJwSM8eJMTFBZymaVuTk8P7c+fz/tx5fLJgIWtytuz1saFQiIysLFplZZPaqhWprVqR1iqT5mlpJCQlkZCYREKzZoRiQkQiEYhAcVEhBdu3U5iXx/bcXHLWr2fL+vVsXreGtUuXUZifB0BpeTlTli5jytJlPPzWJOLCYY7o3o3j+vXhxP596ZSZuUuWy4cP5ZUvviQ/P58xY8ZwzTXX1OVvkyRJklQjFoCSpCZtyZIlLF26FHD6bxAKS0r4aN4C3pk1m/fmzmPR2nV7fFxcQgIdeh5Ep4MPJrtLV9p27kxm+w7EJyTUWpZIJELO+vWsWbyIZXPnsmTWTJbNnUNpcTElZWV8MG8+H8ybzx/GvMQhnTtx1uGDGDloIG1SUzmyR3e6tW3DorXrePzxx7n66qu/0dqCkiRJUm2yAJQkNWmVu/8CHNPHDUDqw+bt25k0YxZvTp/Ju3PmkF9UvNtjmqel0WPgoXTp04fOB/cmq0tXwrF1+9eWUChERps2ZLRpQ58hRwFQWlzM0rlzmPPpJ8z+5GPWLVsGwNSly5i6dBl/GPMSx/XtwxUjhnHZsKP4/ZiXmD17Np999hlHHHFEneaVJEmSqssCUJLUpFVO/+3QsiWdvzatU7Vnyfr1vDl9Jm9Om8HnixZTHonscn98QjO69u9Pz4GH0nPQILI6d2kQI+hi4+Pp3n8A3fsP4IxvX8/G1auZOvkdvpz0NmuXLaU8EuGtGTN5a8ZM2rfMIDYmhtLycp544gkLQEmSJDUYFoCSpCaruLiY999/H4ARvXs1iMIpWkQiEeasWs3rU6byxpTpzF+zZrfHpGS0pM+QIfQdchTdDxlIXDV33Q1Sq+xsTrjkUk645FJWL1nMp2+8wWdv/peC7dtZuWlz1eNefPFFvvvd79K7d+8A00qSJEkVLAAlSU3WZ599Rl5exaYPI5z++42V79g4440p03hj6jSWb9y022Oyunal7+Cj6DNkCO179CQmJiaApLUju0tXzv7OTZx2zbeY8s7/+PDVV1gxfx4AZWVlHHfccVx88cV8//vfp1u3bgGnlSRJUlNmAShJarLefvttAGJjYhjSs0fAaRqn0rIyPlmwiDemTuO/U6ezLjd3l/tDoRBd+vSl39Bh9D1qKC2zsgJKWnfimzXjyFNO5chTTmXxrFmMfvhBNs6ZTVlZGaNGjWL06NFcfPHF/OQnP6Fdu3ZBx5UkSVITZAEoSWqyKjcAOaxbV1okJgacpvEoLCnhw3nzeX3KNN6cNoOcHaMoK8WEw/Q4ZCD9hg6j39ChtEjPCChp/evapw8X33Y7k957n7UfvEfO7JlVReCYMWO45ppruPnmm2nVqlXQUSVJktSEWABKkpqkdevWMXPmTACG9+4VcJqGb01ODv+bOZu3Z8zig3nzKSjedefe2Ph4eg06jH7DjqbP4CEktWgRUNLgdWrVivT27Uk69wKaX3Ah2z7/lC9eGU9RUREPPvggTz/9NLfccgs33HADCQkJQceVJElSE2ABKElqkt55552q28N7u/7f15WWlTFt2XImzZjFpJmzmL1y1W6PSUhMpPeRg+k/7Gh6HX4ECY6iBCAcE0P3tm2ZtWIl28sinPWbP3D8dTfy6j1/YfY7/2P79u384Q9/4Omnn+aOO+7gxBNPdAMaSZIk1SkLQElSkzRp0iQAMpo3p1Xz5izfuInYmBhiw2HiwmHiYsMkxcc36k0qaqK8vJzZq1bx4bwFfDRvAZ8uXMj2wqLdHpfRpi0HH3kkvY84stHs3BuEHlltmb1yJZEIzJk7hyGDh3DjI4+z8NNPGHvn71k5ayZLlizhsssu47jjjuOOO+6gRw/XoZQkSVLdsACUJEWt0tJSFi5cyNy5c5k7dy4LFixgzZo1rFu3juXLlwOweft2Bt/2mz0+PxQKkZqUSFpSMmnJSaQlJ5OZ0oK2aWlkpafRNi2NtmmpZKWnkZ6c3KhGcW3Jy2Pq0mVMXbKMKUuXMWXJUnLz83d7XExMDJ379KX3kUfS+4jBtOnUqVG9zqAkxcfTsVUrlm3YyOJFizl04KEkJCTQ/YgjuXXseD5+4Xle+etd5OVsZtKkSQwfPpzvfve7/PjHPybRkZSSJEmqZRaAkqSoEYlEmDZtGu+99x7vv/8+n3zyCXlf26CipsfbkpfPlrx82LDvxybExVWVgdnp6WTtKAmzM9Jpm1bxa2nJSfVenhWXljJv1WrmrV7DgjVrmb9mDXNWrmbphr2/oDYdO9J9wCF0P2Qg3QccQnJKSj0mjh49s7NYtmEjZWVlLFy4kD59+gAVm6QcdfElHHLaabxx3728+/QTlJaWcu+99zJu3Dj++te/Mnz48IDTS5IkKZpYAEqSGr1p06YxZswYXnnlFVat2n2tOoBwXBytu3QlPTub0nAs24pLiE1M5NCe3UlOSiYcG0t5eTnlpaWUlZVSVlJKQV4e+du2kb9tK/lbt5K3bSvbNuewZeMGSr+2CUZRSQnLNmxk2YaNe83ZLC6OrPQ0stLTyU5Po01aGuk7RhamJiWSmpREalISKYmJJMTFEhcbWzEdORwmHBNDWXk5xaWllJSWUVRaSnFpKbn5+eTk5bElL4+c7Xmsy93K6s05rMrZzKrNOazJyaG0rHyvmWJiYsjq0pWOvXrRtV9/egw4hJSWLQ/sB6FdtGrRgozmzdm8fTtz587l4N4HExP6akp5Ukoq5/7q1xx18SU8d/svWfTZpyxdupTzzjuPiy66iN/97ne09GchSZKkWmABKElqlAoKChgzZgxPPPEE06ZN2+3+tt170GPwELodfgTZB/Uis1NnwnFxALzxxhusX7+e9ORkRgwcUONzRyIR8rdtZcuGjeRu3MCWDRX/5G7cwJaNG9myYT1bNmygpGjXNfQKS0pYsn4DS9bvZzhhHQnHxpLZvgNtO3WiQ8+D6NSrF+179CS+WbNA8kS7EHBQdhYfzV9AXl4eK1asoFPHTrs9rm33Hnx/1HN8/MJzjPvzHynYupXnnnuOt956iz/96U9cc8019R9ekiRJUcUCUJLUqOTl5fHEE0/wj3/8g/Xr11f9ekxsLAcdNZRDTh1Jn2OPI6VV5h6fX1xSzIYd01+z09MOKEMoFCI5JZXklFTadeu2x8dUlITbvioGN2yoKgYrfy134yaKiwoPKMPexMbFkd66NWmt25Depg0t27aldYeOtO3UiVbZ7QjH+tZfnzq2asmUJUspLClh7py5eywAoWIk5lEXXULf445n7B2/58vXXmHTpk1cf/31TJw4kX/961+kp6fXc3pJkiRFCz8FSJIahbKyMp555hn+9Kc/VRV4AK06dmLoJZdyxLkX0KIa0yXXrllLJBIBICuj7gqVipIwheSUlL2WhAClxcXkb99OwfZtO6Ybb6Ng+3bKSkt3+yccGyYcF09sXByxsbHExsXRLDmZpJTUqnM123kzklCIcDiGsrJy2PGaVb/CMTH0yGrDjOUrWbduHZs3byYjI2Ovj0/JbM3V9z7A4eecy+jbfkHuurWMGTOGd999l4ceeohhw4bVY3pJkiRFiyZVAObm5jJmzBg+/fRTNm3aREJCAt26deO0005j8ODBB3zc0tJSXn31VSZPnszq1asBaNeuHSNGjGDkyJHE7me0xeLFi3nppZeYMWMGW7duJTU1lb59+3LuuefSpUuXfT53wYIFjBs3jtmzZ7NlyxaSk5Pp2rUrp5xyCkOGDDng1yRJDcnHH3/Mz3/+c2bNmlX1a+179+Hk7/2AfiecRExMzD6evavKP6djwzG0atGi1rPWVGx8PCkZGaTsoxRS49a9bRazVqyiPBJh7ty5HHXUUft9Tp9jjuMXr0/kxd//ls9eHsv69es555xzuOiii7jzzjtJTU2t++CSJEmKGqFIpGkMCVi+fDm33XYbubm5ACQmJlJUVER5ecXC6GeccQbXXXddjY9bUFDA7bffzvz58wGIj48HoHjH4vC9evXi97//Pc32sr7S5MmTuffeeyktLQUgOTm5asfK2NhYbrnlFo4++ug9Pvell17iiSeeoLy8vGKkSXIyBQUFlJWVAXDCCSfw/e9/v1Z2nNy4ce+L2teG9PR0wuEwZWVl5OTk1Om5VHfC4TDp6enk5ORU/X+oxqchXY95eXnceeedPPLII1Wj9jI7d+Gsn/2SfieceEB/vr344ovk5eXRvmUGww/uVduRGxZHADYYH86bz9INGwmHw5x3/nk0S6j+uouzJ73NqF/8hG2bNgGQnZ3N/fff707BjYzvkdGhIb1H6pvxmowOdX1NtmrVqtaPKQWl+kMmGrGSkhLuuOMOcnNz6dSpE/feey/PPfcczz33HJdffjmhUIhXXnmFt956q8bH/uc//8n8+fNJTk7mF7/4BS+88AIvvPACv/jFL0hOTmbu3Ln861//2uNzly9fXlX+DRs2jMcff5xnn32Wxx9/nKFDh1JaWsrf//53Vq5cudtzP/vsMx577DHKy8s55phjeOyxx3jmmWcYPXo0119/PbGxsbz11luMHTu2xq9JkhqCL7/8kmOOOYZ///vfRCIREpKTOfsXv+IXEybS/8STDqj827p1a9WXLFlpabWcWNq7g9plAxVT2RfMX1Cj5w489TR+O+ldBp46EqgYxXr++efz+9//npKSklrPKkmSpOjTJArA//73v6xdu5aEhAR+/etfV02rTUhI4MILL+TUU08F4Omnn64aiVcdS5Ys4d133wXg+9//PkOGDCEUChEKhRgyZAjf+973AHjnnXdYtmzZbs8fNWoUpaWldOnShR//+MdVawJlZGRw66230qVLF0pKShg1atQenwvQo0cPbrnllqrnJiQkcPrpp3P++ecD8Pzzz7N9+/ZqvyZJClokEuGhhx7i9NNPZ+nSpQD0GjacX0yYyHHXXkfsjpHWB2LV6lVVt7MOcAMQ6UC0bN6cli2aAzBv3ryqGQjV1aJlK2546BGu+Ovfada8BZFIhPvvv5/TTz+dJUuW1EVkSZIkRZEmUQC+8847AAwfPpzMzN13hTzvvPMIhUJs3ryZGTNmVPu4kydPJhKJkJWVtcf19o466iiysrKIRCJMnjx5l/vy8vL47LPPADj77LMJh8O73B8Ohzn77LMB+PTTT8nPz6+6Lycnh8WLFwNw1lln7XEUzNlnn00oFKKgoICPPvqo2q9JkoKUn5/Ptddey69+9StKSkqIS0jgoj/8ke889iQZ7dp/4+NXrv/XvFkzmu9laQaprhyUXTEKMD8/n+XLl9f4+aFQiMPPOoefvTKBzgMPBSpGyh533HG88MILtZpVkiRJ0SXqC8CCggIWLKiYanPooYfu8TGZmZm0b1/xwXLatGnVPvb06dMBGDhw4B5LuFAoxMCBA3d5bKXZs2dXjTbcW67KXy8pKWHOnDlVv75+/fqq25W5vy4pKalqVODUqVOr83IkKVBr167lzDPP5JVXXgGgdZeu/OjFcQy95LJaWcu0rKyMdWvXAY7+UzA6tGpJ4o4RrLNnzz7g47Ts0JGbn32Bk79bsc7v9u3buemmm7jpppsc9S9JkqQ9ivoCcOXKlVULx3fq1Gmvj6u8b8WKFdU6biQSqVqbb1/H7dix4x6PW/nfaWlpe93JLzU1teq+nUcK7PxBeF9TiCoXsz2QUQaSVJ/mzJnDySefXPUlTN/jTuDWl16hXa+Da+0cGzZsqPrixQJQQQiHQvTMzgIqNtfa+Qu9Gh8rNpaRt9zK954eTVrbimO+8MILnHDCCbt8aShJkiQBxAYdoK5t3ry56nbliLg9qbyvujsHFRQUUFhYWO3jFhQUUFBQQGJi4i7n2ddzK+/Pzc3dJdfO05iXL19O9+7dd3ve1q1b2bJlC7Dr78HePP300zzzzDN7vf+SSy7h0ksv3e9xDlRMTEzVv9PT0+vsPKpbleV0amoqTWSD8ahU39fjZ599xtlnn131Z9UJ193Aebf9mpivLY3wTa1bVzH6LxSC7IyM3ZZeiGbhmKj/vq/ROKhdNjOXr6CsvJy5c+fSoUOH/T6n8s/WUChEQkLCLvf1HT6CX0+cxJM//TFT35jAokWLOPnkk/nXv/7F5ZdfXievQQfG98jo4N9Zo4fXZHTwmpSqL+oLwMqSDtjtL807q7yvoKCgWsfd+XHVOW7lcyoLwMrn7+u5e8uVnp5Oly5dWLJkCWPHjmXEiBG7fZAdM2bMHrPuTV5e3j5HIuTn59fLh+VQKNSkPpRHqxjLhqhQH9fju+++y+mnn862bdsAuOSOP3Hs1d+qk3NVjtrOTEkhLraJ/TnzzWdQq5YkxMXSPast81atZunSpWzbto2UlJRqP39P0+GbZ2TwnX8/ytv/eZgxd/yegoICrr76aj766CP+/ve/08z1LhsU3yOjg39njR5ek9HBa1Lav6gvAKPVxRdfzJ/+9CeWL1/OnXfeyRVXXEGHDh3Izc3ljTfeYPz48cTGxlJaWlqtN7Xk5GRat2691/uTkpKqphTXhZiYGEKhEJFIpMY7I6rhCIVCxMTEUF5e7jepjVh9XY/vv/8+p512Gvn5+cSEw1z1178z+LwL6uT/nfyCAjZt2gRAdkY6NKX/PUM0rdfbCBzcrh3zVlVsSDNjxgyOOuqofT5+59JvX9fH8ddeT+cBA3n4O9ezZe0aHnroIT777DOee+45unTpUjvhdcB8j4wO/p01enhNRoe6viYtFRVNor4A3Plb76KiIpKSkvb4uKKiIoCqEXr7s/PjKp+7r+N+/TmVt/f13H3lGjJkCJdffjmjRo3i888/5/PPP9/l/u7du9O9e3feeOMNkpOT9/Nq4PLLL9/nVKGNGzdWe3r0gUhPTyccDlNeXl6n51HdCofDpKenk5ubW6eFsepWfVyPU6dO5dxzz60YXRwXx9X3PsCAk07Z75+JB2rZ0qVVt9umpjad/z9DIcLhGMrKy8EPNw1GUnwc7VtmsHLTZubNm0ffvn33O5ug8sPN/q6R9v3685Nxr/Lkj25m3gfv8+WXX3LYYYfxr3/9ixNPPLG2X4pqwPfI6ODfWaOH12R0qOtrslWrVrV+TCkoUT/eeec19va1Fl7lfdVdNyAxMbGqlKvOcXd+/M659rc+375yXXjhhdx9992ccMIJdOrUiczMTHr16sU111zDn//856oPCdnZ2dV6TZJUH+bOncuFF17Itm3bCMXEcOU99zLgpFPq9JyrV1eMtkqIiyW9+f6/FJHq2sHt2gFQWlrK/Pnza/XYLVq24juPPsnJ3/sBALm5uVx22WXcd999jnKRJElqoqJ+BGD79u2rvjVfvnw57du33+PjKnfKrc5i3FAxZLx9+/YsWLBgn7vs7u24lf+9ZcsWtm7dusf1f3Jzc8nNzQW+2k3463r06EGPHj32eN/ixYsB6NWr135ejSTVj7Vr13LxxRdXfUN72Z//ysBTR9bpOSORSFUB2DYtjZAL4qkBaJXSgpYtmrNp23bmzp1L7z59anWzlphwmJE//DFdBh7KEz/8AQXbtvKHP/yBWbNm8be//W2vMyIkSZIUnaJ+BGBiYmJVQfbll1/u8TEbN25kxYoVAAwYMKDax+7fvz8AU6ZM2etjpk6dustjK/Xu3ZvY2Nh95qo8blxcHAcffHC1cwEsXbqUZcuWAXDMMcfU6LmSVBe2b9/OJZdcwqpVqwA4/9e/44hzzq3z8+bk5FRtCJWVnlbn55OqI8RXowALCgpYumRJnZyn94hj+fHYcbTp1g2AsWPHcsYZZ1Rdh5IkSWoaor4AhK8KsHfffZcNGzbsdv/YsWOJRCJkZGTQr1+/ah93+PDhhEIhVq9ezUcffbTb/R9++CGrV68mFArtVsIlJSVx+OGHAzBu3Ljd1p0oKytj3LhxABxxxBE1+qa+pKSEBx98sOq5nTp1qvZzJakulJWVcd111zFz5kwAjvv29Qy/8up6OXfl6D+ArLS0ejmnVB3tW2aQvGPtv9mzZ9fZeVp36cqPxrxMn2OPA2D69OmceOKJfPLJJ3V2TkmSJDUsTaIAPPnkk2nbti2FhYX84Q9/YMmOb9mLiooYM2YMr732GlCxEUblqLxK3/72tznzzDP5+9//vttxu3TpwvDhwwG4//77+fjjj4lEIkQiET7++GMeeOABoKKA3NMU3ssuu4zY2FgWLVrEPffcUzUlLicnh3vuuYdFixYRFxfHZZddtttzc3JyePzxx1mwYAHFxcVAxQfs6dOn84tf/ILZs2eTnp7Od77znQP8XZOk2vOnP/2Jt956C4BDTjmNM3/6i3o7d2UBmJacRGJ8fL2dV9qfmFCIXu0q1unNyclhzZo1dXauxBYpXPfgI5x443cB2LBhA+eccw7PPPNMnZ1TkiRJDUfUrwEIFVNof/WrX3HbbbexdOlSbr75ZpKSkigsLKzaKvz000/nhBNOqPGxb7rpJtasWcP8+fP54x//SPyOD5eVpVyvXr32WsJ17NiRm2++mXvvvZf33nuP999/n6SkJPLy8gCIjY3l5ptv3uO6hcXFxYwdO5axY8cC0Lx5cwoKCqpGEmZnZ/OrX/2Kli1b1vg1SVJtmjBhAvfeey8AHfr24/K7/0ZMLa51ti8lpaWsX78eqFj/T2pourZpzfRlyykpK2PWrFlkZWXV2bliwmHOuPWnZPfqxTM//wklhYXcfPPNLFu2jJ///OeEQq6PKUmSFK2aRAEIFWXb/fffz4svvsinn37Kxo0bSU5OpmvXrowcOZLBgwcf0HETExP5v//7P1599VUmT55cNdKkW7duHHPMMYwcOXK3UYU7GzFiBB06dGDs2LHMnDmTrVu3Vk1FPvfcc+nSpcsen5eamsqll17KjBkzWLVqFVu3biU5OZn27dszbNgwTj75ZOLi4g7oNUlSbVm4cCHf/W7FiKPk9HSu/ceDxDdrVm/nX7d2bdUXPa7/p4YoLhyme1Yb5qxczerVq9myZQtpdVxWDzr9TDI7d+Hh665h64YN3HPPPSxfvpy///3vJOyYkixJkqToEopEIpGgQ6jh27hxY50ePz09nXA4TFlZWdVUaDU+4XCY9PR0cnJydlvXUo1HbV2P27dv5+STT2b+/PmEYmK46bGnOGjosFpMun+fffYZc+bMISYmhgsGH1Gru6w2CqEQ4XAMZWXl4Nt9g5VfXMS4z74gEqn4AnHo0KG73J+QkEAoFCISiVBUVFRr5928ehUPXXs1axbMB+Coo47iiSeeqPMCsqnyPTI6+HfW6OE1GR3q+pps1apVrR9TCkoT+yQkSaovP/vZz5g/v6JYOP1HP6n38g9g1eqKnU7bpKY0vfJPjUZSfAKdMzMBWLx4cdVSIHUtI7sdP3z+RXoeVVE4fvjhh5x22mksW7asXs4vSZKk+uOnIUlSrXvppZd4/vnnAeh3wkmccEP9b0iUl5fH1tytgNN/1fD1bt8OgEgkwuw5dbcj8Ncltkjhxkce58jzLgBgwYIFjBw5kjlz5tRbBkmSJNU9C0BJUq1auXIlt956KwCpbdpw6Z/uCmRzgco1WQGynNKoBi41KYl2GekALJi/oFan+u5PbHw8l/7fXzj15h8BsG7dOs4880w+//zzessgSZKkumUBKEmqNWVlZXz3u99l69aKkXeX/fmvJKenB5Jl1Y4CMDE+npSkpEAySDXRu317AEpLS5k7b269njsUCnHq92/mgt/dQSgUYsuWLZx33nlMnjy5XnNIkiSpblgASpJqzT/+8Q8+/PBDAI655lp6DTs6kBzlkXLWrlkDVEz/rf/xh1LNZaa0IDOlBQBz58ylpLS03jMcfdkVXPm3+4iJjSU/P59LL72UV199td5zSJIkqXZZAEqSasXcuXP5v//7PwCyex3MGbf+NLAsmzZuori4GHD9PzUulaMAi4qKWLhwQSAZBp1+Jtc9+G/imjWjuLiYa6+9lmeeeSaQLJIkSaodFoCSpG+srKyMW265hZKSEsJxcVz5178Tl9AssDw7r//X1vX/1IhkZ6STumPK+uxZsykvLw8kR59jjuOmx58msUUK5eXl3HzzzTz99NOBZJEkSdI3ZwEoSfrG/vOf/1RtGHDiDTeRfVCvQPNUFoAtWzQnITY20CxSTYT4akfgvLw8li5dGliWbocdzvdHja5ax/OWW26xBJQkSWqkLAAlSd/IihUruPPOOwFo0607J37nu4HmKS4uZuPGjYCj/9Q4dcpsRXJCAgAzZ84kEokElqV97z5876lnLQElSZIaOQtASdIBi0Qi3HrrreTn5xMKhbj0T3cRt6O4CMqaNWuqCpNs1/9TIxQTCtGrXTYAW7ZsYfny5YHmadfrYEtASZKkRs4CUJJ0wF566SUmTZoEwNGXX0mXQwcFnAhWr6mY/hsXDtOyRYuA00gHplvbNiTEVUxfnzZtWsBpdi8Bf/SjH/Hiiy8GnEqSJEnVZQEoSTog27dv5ze/+Q0AaW2zOP3Hwe36u7PVqyoKwDZpqcSEQgGnkQ5MbEwMPbOzAFi3bh1r164NONFXJWBSWhqRSITvfe97TJw4MehYkiRJqgYLQEnSAbnnnnuqSolzfnk7zZo3DzgR5G7NJS8vD4Asp/+qkeuZlUVsuOKval9O+TLgNBXa9TqY7/znCRKSkyktLeXaa6/lo48+CjqWJEmS9sMCUJJUY4sWLeLBBx8EoMfgIRxy6mkBJ6pQufsvQFZaeoBJpG8uITaWHlltAVi5YiUbNmwIOFGFTgMO4dv/ephwXDyFhYVcdtllTJ8+PehYkiRJ2gcLQElSjUQiEW677TZKSkqICYc5/9e/J9RAptpWFoDNmzWjebNgNyORakOv7HaEYyr+ujZlypSA03zloKOGcfW99xOKiWHbtm1cdNFFLFq0KOhYkiRJ2gsLQElSjUycOJG3334bgKOvuIqsnj0DTlShrKyMdWvXAU7/VfRIjI+rGgW4bNkycnJyAk70lQEnncIlf/wzABs3buSSSy5h06ZNAaeSJEnSnlgASpKqrbi4mNtvvx2AFi1bceoPfhhsoJ1s2LCB0tJSwAJQ0aV3h/ZVG9rMmDEj4DS7Gnz+hZz5018AsGTJEq666iqKiooCTiVJkqSvswCUJFXbk08+yZIlSwAY+aNbSUpJDTjRV1atXgVAKARtUhtOLumbSk5IoFvbNgAsXbqU3NzcgBPt6vjrbuCoiy4B4JNPPuHmm28mEokEnEqSJEk7swCUJFXLtm3buPvuuwHI6tGTwedfGHCiXa1ZvQaAzJQU4sLhgNNItatvxw5ULrXZ0EYBhkIhLvjtHzho6NEAvPjii9x1110Bp5IkSdLOLAAlSdVy//33V63vdebPfkFMAyrZCgoK2Lx5MwBZaWnBhpHqQPPEZnRt3RqomGq7bdu2gBPtKhwXx7ce+CdZPSrWBL377rt57rnnAk4lSZKkShaAkqT9WrNmDQ8++CAAPQYPofeIYwNOtKs1a9ZU3Xb9P0Wrvp06AhU7cc+cOTPgNLtLbJHCDY88RotWmQD8+Mc/ZurUqcGGkiRJEmABKEmqhj//+c8UFBQAcNbPfkmoci5iA7F69WoAEuJiSW+eHHAaqW6kJCbSKbMVAIsWLSIvLy/gRLvLaNee6x78N+G4eIqKirj66qvZsGFD0LEkSZKaPAtASdI+zZs3j2effRaAQ08/k479+gecaHeVBWDbtDRCNKxyUqpNfTq0B6C8vJyZsxreKECAzocM5MLf/QGAVatWcd1111Xt0C1JkqRgWABKkvbprrvuory8nHBcHKf/6CdBx9nNps2bKCwsBJz+q+iXlpRE+5YZACxYsID8gvyAE+3ZkAsvZuillwPwwQcf8Nvf/jbYQJIkSU2cBaAkaa9mzpzJ+PHjARh8wUW06tgx4ES7W71qddXtrLT0AJNI9aNvhw4AlJeVM2vmrIDT7N15v/oNXQ4dBMBDDz1U9WeJJEmS6p8FoCRpr/7yl78AEI6L56Qbvxtwmj1btWoVAOnJySTGxwWcRqp7Gc2TaZdRUXbPnz+/wY4CjI2P51v3/4sWLSvWLfzhD3/I0qVLgw0lSZLURFkASpL26IsvvmDChAkADL34EtKzswNOtLvikuKqDQayMxz9p6aj347RuGVlZcyc0TDXAgRIbdOGK++5l1AoxLZt27j++uspLi4OOpYkSVKTYwEoSdqj3/3udwDEJSRwYgMd/bdm9RoikQjg+n9qWjKaJ1etBTh/wXzy8xvmKECAg4YO46SbvgfAlClT+MMf/hBwIkmSpKbHAlCStJtPPvnkq9F/l15Oaps2ASfas8rpv3HhMK1atAg4jVS/+nX8ai3AGTNnBJxm3075/g/pdvgRADz44IP897//DTiRJElS02IBKEnaTeXov/jERE644TsBp9m71asrNgBpm5ZKTCgUcBqpfqUnfzUKcMH8BeTl5wWcaO/CsbFc9bf7SU6vmKr/wx/+sGr6viRJkuqeBaAkaRdffvklr7/+OgDDLruClFaZASfas5ycnKppj67/p6aqahRgeXmDXgsQIK1tWy79U8XGQhs3buRHP/pR1RR+SZIk1S0LQEnSLv785z8DEJuQwLHf+nbAafaucvQfuP6fmq705GQ6VI4CXLCAvLyGOwoQoN8JJzL4gosAeOONNxg1alTAiSRJkpoGC0BJUpX58+czduxYAIZedAmprRvm2n/w1fp/aclJJMUnBJxGCk6/ThU7ApeXlzNjRsNeCxDg3Nt+TcsOFSMXb7vtNpYsWRJwIkmSpOhnAShJqnLfffcRiUSICYc56cabgo6zVyUlJaxfvx5w9J+UlpREx1YtAVi4cCHbt28PONG+NWvenCvu/huhmBjy8/P53ve+R1lZWdCxJEmSopoFoCQJgOXLlzNmzBgAjjz3fFp16Bhwor1bu3Yt5eXlAGSnu/6ftPNagI1hFGDXQYdz/HU3AvDpp5/y6KOPBpxIkiQpulkASpIAeOCBBygrKyMUCnHKd78fdJx9qpz+GxuOoVVKSsBppOClJiXRKbMVUDEKcNv2bQEn2r9Tf/BD2nTrDsAdd9zB8uXLA04kSZIUvSwAJUmsX7+eZ555BoCBp40kq3uPgBPtW2UB2DYtjXAoFHAaqWHou2NdvUgkwozpDX8UYFxCApf+6S5CoRD5+fn8+Mc/dldgSZKkOmIBKEni0UcfpaioCIBTbmrYo/9yc3OrdjrNcvqvVCU1KbFqFOCiRYvYunVrwIn2r8uhgxh+1TUAvPPOOzz33HMBJ5IkSYpOFoCS1MTl5+fz2GOPAdD9yMF06j8g4ET7Vjn6DyDbDUCkXVSuBRiJRJg+fXrAaarn9FtuJaN9ewBuv/121q1bF3AiSZKk6GMBKElN3AsvvMDmzZsBOO7a6wNOs3+VBWBKYiLJCQkBp5EalpTERLq2aQ3A4sWLydmSE3Ci/UtITubiO/4PgC1btvDb3/422ECSJElRyAJQkpqw8vJy/vWvfwHQums3eh9zbMCJ9q2ktLRqdFB2htN/pT3p27EDMTvWxpw2dVrAaaqn17CjOeyscwAYM2YMH3zwQcCJJEmSoosFoCQ1YW+++SaLFi0C4NhvfZuYmIb9trBu7VrKy8sByHL6r7RHzRMS6Na2DQDLly9n48aNASeqnrN//kuaNW8BwM9+9jNKSkoCTiRJkhQ9GvYnPUlSnfrnP/8JQPOMlhx+9rkBp9m/yum/4ZgYWqekBJxGarj6dmhPeEehP2XKlIDTVE9KZmtG/ujHAMybN4+HHnoo4ESSJEnRwwJQkpqoadOm8eGHHwIw7LIriG/WLOBE+7dqdUUB2CY1tarckLS7xPh4ema3BWDNmjWsXbs24ETVM+zSK2h3cG8A/vKXv7B69eqAE0mSJEUHPz1JUhNVOfovNj6Boy+/IuA0+7d161a2b9sOQHZGWrBhpEagd/v2xIXDQOMZBRiOjeXC390BVOxQfvvttwecSJIkKTpYAEpSE7Rq1SrGjRsHwBHnnEuLlq0CTrR/ldN/AbLS3QBE2p+E2Fh6tcsGYMOGDbtcQw1Zl0MHMfiCiwAYP348H330UcCJJEmSGj8LQElqgh599FHKysoAOOaaawNOUz2V039bJDajRSOYriw1BL3aZRMfGwtUjAKMRCIBJ6qe03/8ExKSmwNw++23V23+I0mSpANjAShJTUxhYSFPP/00AL2OHkHb7j0CTrR/paWlrFu7DoCstLRgw0iNSFw4TJ8O7QDYvHkzy5cvDzhR9aS0yuSkm74HVKxX+sILLwScSJIkqXGzAJSkJubll19m8+bNAAy/4qqA01TP2rVrq0YstmuZEXAaqXHpmZVFYnw8AFOnTm00owCPufoaWnboAMAdd9xBXl5ewIkkSZIaLwtASWpCIpEIjzzyCAAtO3Sg94hjgg1UTStXrgQgNhxD65SUgNNIjUs4Joa+HdoDkJuby+LFiwNOVD1xCc0486e/ACq+BPjHP/4RcCJJkqTGywJQkpqQL7/8kmnTpgEw7LIriNmxQ2hDt3JVRQHYNi2NcIxvXVJNdW3bhuSEBKBiSm1ZI1lT75BTTqPb4UcA8MADD7B69eqAE0mSJDVOfoqSpCbkP//5DwBxCQkMPv+igNNUT05ODvl5+QBku/uvdEDCoRD9O3UEYPv27SxcsCDgRNUTCoU455e3A1BQUMDdd98dcCJJkqTGyQJQkpqI9evXM27cOAAGnXk2yY1kM43K6b8A7TIsAKUD1bl1K1ISEwGYPn06paWlASeqno79+nPo6WcC8Mwzz7Bw4cKAE0mSJDU+FoCS1EQ8/fTTFBcXA3D05VcGnKb6KgvA9OTkqo0MJNVciK9GARYUFDBv3ryAE1XfyB/+mJjYWMrKyvjjH/8YdBxJkqRGxwJQkpqA0tJSHn/8cQC6DjqMDn36BhuomoqKitiwcQMA7Vo6+k/6pjq0yiA9ORmAGTNnUFJSEnCi6sns3JkhF14MwCuvvMKUKVMCTiRJktS4WABKUhPw+uuvs2bNGgCOvuKqgNNU36pVqyBScbtdRkawYaQoECLEgM4VowCLi4qZPXt2wImq75Tv/YC4Zs0AuPPOOwNOI0mS1LhYAEpSE/DYY48BkJKZyYCTTgk4TfVVTv9tFhdHRvPkgNNI0SErPZ3MlBQAZs2aRWFRYcCJqie1dRuOufpaACZPnszkyZMDTiRJktR4WABKUpRbtGgR7733HgCDL7iI2Eayjl55pJzVq1cDkJ2RTohQwImk6BACDtkxCrC0tJSZM2YGG6gGjr/+BpJSUwH44x//SCQSCTiRJElS42ABKElR7umnnwYgFApVraHVGGxYv6Fq05LsdNf/k2pTZkoK2elpAMydN5e8/LxgA1VTUkoqx337BgC+/PJLJk2aFHAiSZKkxsECUJKiWFFREc8++ywAvY4eTsv2HQJOVH0rV1VM/w2FIGtHUSGp9vTv3AmA8rJypk+fHnCa6ht+xVUk7/hS4C9/+YujACVJkqrBAlCSotiECRPYtGkTAEddfGnAaWpm1cpVALROSSUuHA44jRR9MpKT6diqJQALFyxk69atASeqnmbNm3PctdcD8MUXXzgKUJIkqRosACUpij311FMApLRuTd9jjw84TfVt376dLVu2ABXr/0mqG/07dSQUgkgkwtRp04KOU21HX36lowAlSZJqwAJQkqLULpt/nH8h4bi4gBNVX+XuvwDtLAClOpOSmEjX1q0BWLpkCZs3bw44UfU4ClCSJKlmLAAlKUrtsvnHBRcFnKZmKgvA5s2akZKYGHAaKbr17diBmFDFLttTp04NNkwN7DwK8K677nIUoCRJ0j5YAEpSFNp584+Dhg2nZYeOASeqvpLSUtauWws4+k+qD8kJCfTIagtUlO/r168POFH17DwK8Msvv+Tdd98NOJEkSVLDZQEoSVHo9ddfr9r8Y+gljWvzj9WrV1FeVg5Au4yMgNNITUOfDu2JDVf8tXDKlCkBp6m+oy+/ksSUFADuu+++gNNIkiQ1XBaAkhSFnnzySQBSMjMb1eYfACuWrwAgLhymdWpKwGmkpqFZXBwHZWcDsG7dOlavXh1woupp1rw5R19+JQDvvvtuoyovJUmS6pMFoCRFmaVLl1Zt/nHkeY1r84/ySDkrV1Ws/5edkV61Lpmkundw+3bEx8YCjWsU4IirriEuIQGAe++9N+A0kiRJDZMFoCRFmeeee67q9uDzLwwwSc2tX7ee4qJiANq3dPqvVJ/iw2F6t28HwKZNm1i2fFnAiaqnRctWDN6x0dGECRNYsGBBwIkkSZIaHgtASYoi5eXlVQVgt8OPJLNz52AD1dCKlRXTf2NCIbLT3QBEqm89s7NoFl8xanjqlKmNZmfd4759PTHhMJFIhAceeCDoOJIkSQ2OBaAkRZH333+fFSsqSrTB518QcJqaq8zeJi2VuHA44DRS0xMbE0O/Dh0AyM3NZfHixQEnqp6W7Ttw6OlnAvDCCy80mjUMJUmS6osFoCRFkWeeeQaA+KQkDjnltIDT1EzOlhy2b9sOQHt3/5UC07VtG5J3rKk3depUysrKAk5UPSdcfyMAJSUlPPjggwGnkSRJalgsACUpSuTm5vLaa68BcOhpp5OQnBxwopqp3P0XoJ3r/0mBCYdC9O/UEYC8vLxGs6Ze9kG96LNj1/MnnniCzZs3B5xIkiSp4bAAlKQo8fLLL1NYWAjAkY1s8w/4avpvRvPmJMXHB5xGato6t25FalISANOnT6ektDTgRNVz4o3fASA/P5/HH3882DCSJEkNiAWgJEWJyum/mZ270HXQYQGnqZn8gnw2bdoEuPuv1BCE+GoUYGFhIXPnzgk4UfV0HXQ4nQceCsCjjz5KcXFxwIkkSZIaBgtASYoC8+bN48svvwTgyPMuIBQKBZyoZipH/4EFoNRQtG+ZQcsWzQGYNXNWoynTjr3m2wCsW7eOcePGBZxGkiSpYbAAlKQo8OyzzwIQionhiHPOCzhNzVWu/5eckFA17VBSsELAgE6dACguLmbWrFnBBqqm/iedTHp2OwAefPBBIpFIwIkkSZKCZwEoSY1cSUkJzz//PAC9hh1NWtu2ASeqmZKSEtauXQtUjDhqXGMXpejWNi2VNqmpAMyZM4eCgoKAE+1fODaW4VdeBVSsX/jxxx8HnEiSJCl4FoCS1Mi9/fbbbNiwAYDB518UcJqaW716NeXl5YDTf6WGaEDnirUAS0tLmTFjRsBpqmfIhRcTv2M08UMPPRRwGkmSpOBZAEpSI1c5/TcpLY2+x58QcJqaq1z/Lz42lsyUlIDTSPq6Vi1aVJXz8+fPZ/v27QEn2r+klFQGn3cBABMmTGDp0qXBBpIkSQqYBaAkNWIbN25k4sSJABx2xlnEJSQEnKhmysvLWblyJQDZGenENLLNS6SmonJH4PLycqZNnxZwmuoZcdW3CIVCRCIRHnnkkaDjSJIkBcoCUJIasZdffpnS0lIAjtgx2qUxWbduXdXOou0znP4rNVRpSUl0zmwFwKJFi8jNzQ040f5ldu5Mn+MqRkWPGjWKbdu2BZxIkiQpOBaAktSIvfDCCwC06dadDn36Bpym5pYvXw5ATEwMWelpwYaRtE/9OnUkFAIiMHXq1KDjVMsxV38LgO3btzNq1KiA00iSJAXHAlCSGqmFCxfy5ZdfAnD42ecSamTTZyORCMuWLwMgOz2NuHA44ESS9qVFs2Z0b9MGgGXLlrFp06aAE+1fj8FDaHdwbwD+85//VG04JEmS1NRYAEpSI1U5+g/gsLPODi7IAVq/fj2FBYUAdGjVMuA0kqqjT8cOxMRU/PVxypQpAafZv1AoxNGXXwnA0qVLeeedd4INJEmSFBALQElqhMrLyxkzZgwA3Y8cTEZ2u4AT1VzV9N9QiHau/yc1Cknx8RyU1RaA1atXs27duoAT7d9hZ55NYouKHcYfe+yxgNNIkiQFwwJQkhqhTz75pKpAO/zscwNOc2Aqp/+2TUsl3um/UqPRu0N7YsMVf4WsXIagIYtPTOTIHZskTZw4kRUrVgScSJIkqf5ZAEpSI1Q5/TcuIYFDTjkt4DQ1t3HjRvLz8gGn/0qNTUJsLAe3qxh1vGHDBlauXBlwov0beullQMXo6SeeeCLgNJIkSfXPAlCSGpnCwkLGjRsHQL8TTiKxRYuAE9Vc5ei/UAjat7QAlBqbXu2ySYiLBSrWAoxEIgEn2rc2Xbtx0NBhAIwaNYqioqKAE0mSJNWv2KADqHEI1+P0vPo8l2pX5c/On2Hdeuutt9i6dSsAh59Tt7v/1tWxly+rmL7cOjWVhLi4OjmHILTTvyONbJdo7UUD+TnGxcbSp0N7vly8lJycHJYvX07nzp2DjrVPR19+FfM+eJ+NGzcyYcIEzj///Ho9v++R0cefZePmNRl9/FlK+xaKNPSvbCVJuzjrrLMYP348LVq25M+fTyO2kRVomzZt4sUXXwTgyB7d6dkuK+BEkg5EWXk5L3/yGflFxaSmpnLBhRcQE2q4k0vKSkv55ZDDyVmzmqFDh/L+++8HHUmSJKneOAJQ1ZKTk1Onx09JSSEcDlNWVlY1skmNTzgcJiUlha1bt1JWVhZ0nKi0adMmJkyYAMChp59JWXk5ZbU8lS0+Pp5QKEQkEqG4uLhWjw2wYMGCqtvZGemUlZXX+jlUIQTEhGMoLyvHb/sar3BMzI5hnBWlW0PSt0MHPl24iNzcXGbPmk2PHj2CjrRPR118Ka/97W4++OAD3nvvPfr27Vtv5/Y9Mjr4d9bo4TUZHer6mkxPT6/1Y0pBsQBUtdTnm6JvwI1fWVmZP8c6MnbsWEpLS4GK3X/rehB3XRx/2bKK9f8yU1JIjIsDB6LXmcppvxHw9zlaNLCfY9c2rZmzahXbCgqZOm0qXbp0adBTsIZceBFvPHAvZSUlPPLII/z1r3+t9wy+R0YPf47RwWsyevhzlPat4c7TkCTtpnL33zbdutGhb7+A09Rcbm4uubm5AHR091+p0YsJhejfsSMA+Xn5zJs3L+BE+5aS2ZoBJ58KwJgxY9i2bVvAiSRJkuqHBaAkNRKLFy/m888/B+Dws+p284+6Ujn6D6B9y4wAk0iqLR0zW5KWnATAzJkzKSkpCTjRvg29+FIA8vPzeemllwJOI0mSVD8sACWpkdj5g+qgM88KMMmBW7p0KQCtWjQnOSEh2DCSakWIEAM6dQKgsLCQOXPmBJxo37ofOZjMzl0AeOqppwJOI0mSVD8sACWpEYhEIlU753Y5dBAt23cIOFHN5WzJYcuWLQB0yswMNoykWpWdkU6rFi0AmDVrFkW1vDlRbQqFQgy58GIApk6dyowZMwJOJEmSVPcsACWpEZg5c2bV7rmDzmiko/+WLK267fp/UnQJAQM6V6wFWFJSwsyZM4MNtB9HnHseMbEVe+E5ClCSJDUFFoCS1AhUTv+NCYcZeNrIgNMcmCVLlwDQOjWFxPj4gNNIqm1tUlPJSk8DYO7cuRQUFAQbaB9SWmXS7/gTAXjxxRfJz88POJEkSVLdsgCUpAauvLycsWPHAtBzyFBatGwVcKKa27RpE9u3bQec/itFs/6dKkYBlpWVMXNWwx4FWDkNeOvWrYwfPz7gNJIkSXXLAlCSGrhPP/2UVatWATDojDMDTnNgKjf/CIWgYyt3/5WiVcvmzcnOSAdg/rz55Bc03JF1vYYdTXp2O8BpwJIkKfpZAEpSA1c5+i82PoH+J50ccJqai0QiVdN/26alkRAbF3AiSXWpf8edRgHOaLijAGPCYQZfcBFQ8UXLvHnzAk4kSZJUdywAJakBKykpqZqa1ufYY0lskRJwoprbsGED+XkVo4A6ZTa+6cuSaiajeTLtW1aM9J2/YH6DXl9v8PkXEoqp+Ovw008/HXAaSZKkumMBKEkN2LvvvsumTZsAOPT0xjn9t3L0X0woRPuW7v4rNQX9OnYAoLysnBkzZwScZu/Ss7LoPeIYAJ5//nmKioqCDSRJklRHLAAlqQGrnP6bkNycPsceH3CamotEIixbugyA7Ix04sPhgBNJqg/pyV+NAlwwfwF5eXkBJ9q7IRdeAsDmzZt5/fXXA04jSZJUNywAJamBKigo4LXXXgNgwEknE9+sWcCJam7turUUFhYC0KmV03+lpqRqFGB5OTNnNty1APscc2zV7urPPfdcwGkkSZLqhgWgJDVQb775ZtWomcY6/XfpkqUAhGNiaNcyPdgwkupVenIyHVtVTPtfsGAB27dvDzjRnoXj4jjsrLMBmDRpEmvXrg02kCRJUh2wAJSkBqpy+m/zjJYcdNTQgNPUXFlZGUuXLgWgXUYGsTFO/5Wamp1HATbktQCPOPd8oCLnmDFjAk4jSZJU+ywAJakB2rp1K2+99RYAh5x6GuG4uIAT1dzKlSspKSkBoEvrzIDTSApCalISHXdM/1+4YGGDHQXYrtfBtO/TF4DRo0cTiUQCTiRJklS7LAAlqQF67bXXqnajHHTGWQGnOTCLFi0CoFlcHFnpacGGkRSYylGAkUiE6dOnB5xm7448r2IU4Lx585g6dWqwYSRJkmqZBaAkNUCV03/Ts7LpcuiggNPUXGFhIatWrQKgU2YrYkKhgBNJCkpqUiKdMitGAS5atIht27YFnGjPBp1+VtVo62effTbgNJIkSbXLAlCSGpgNGzbw7rvvAnDoGWcSE9P4/qhesnRJ1RQ6p/9K2mUU4IyGOQqweUYGfY87HoCXXnqpagdzSZKkaND4PlVKUpR79dVXKS8vB+DQkWcEnObALF60GICUpETSmzcPOI2koKUkJtJ5x5cBixctZuvWrQEn2rMjz7sQgC1btvDf//434DSSJEm1xwJQkhqYcePGAZDZuQvte/cJOE3N5ebmsmnTJgC6tG6Nk38lAfTr2J5QqGGvBXjw0cNp0aqiqBw9enTAaSRJkmqPBaAkNSDr1q3jww8/BGDgaSMJNcK18xYvXlx1u/OOdb8kqUWzRLq0bg3A4iUNcxRgOC6Ow886G4BJkyaxdu3aYANJkiTVEgtASWpAXn311aq18waednrAaWouEolUFYBtUlNJTkgIOJGkhqRPh4pRgERg2vRpQcfZoyPOrdgNuLy8nBdeeCHgNJIkSbXDAlCSGpDK6b+tu3Yj+6BeAaepuXXr1pGXlwdAlzZu/iFpVy2aNaPrjlGASxYvITc3N+BEu8s+qBcd+vYDKqYBV34pI0mS1JhZAEpSA7F27Vo+/vhjAA497fRGPf03HBNDh5YtA04jqSHq07EDlX+8zZgxI9gwe3HkjlGA8+fPZ8qUKQGnkSRJ+uYsACWpgRg/fnyjnv5bUlrK0mVLAWjfMoO4cDjYQJIapOYJCVWjABvqWoCDzjiLcFwcgNOAJUlSVLAAlKQGonL6b9vuPcjq2TPgNDW3fNkySktKAejapnXAaSQ1ZL13WguwIY4CTE5Pp/eIYwF4+eWXKSkpCTiRJEnSN2MBKEkNwOrVq/n000+Bxjn6D2DBggUAJCXE0zYtNeA0khqyFs2a0TmzYp3QxYsXs23btoAT7e6wHbsBb9y4kXfeeSfQLJIkSd+UBaAkNQDjx4+vun3IqacFmOTAbN26lfXr1wPQrU0bQjS+9Qsl1a8+HdoDFbuHN8RRgH2PO55mzVsAMGbMmIDTSJIkfTMWgJLUAFQWgFk9DyKrR+Ob/rtg4YKq207/lVQdKYmJdM5sBcCiRYvYvn17wIl2FZfQrOoLmddff73B5ZMkSaoJC0BJCtjKlSv57LPPABh42siA09RceXk5ixYuAqBtWhrJCQkBJ5LUWPTp2AGoGAU4c+bMgNPs7rAzzwagoKCACRMmBBtGkiTpG7AAlKSAvfLKK1W3B57a+ArAVatWUVhYCEC3to7+k1R9qYmJdNoxCnDhwoXk5eUFnGhX3Y8cTFrbLMDdgCVJUuNmAShJAavc/Te718G06dY94DQ1V7n5R3xsLO0zMgJOI6mx6btjLcDy8vIGNwowJiaGQWeeBcC7777LunXrAk4kSZJ0YCwAJSlAy5cv54svvgAa5/Tf/IJ8Vq5aCUCX1pmEY3xbkVQzqUlJdGjVEqj4QiE/Pz/gRLs6/KxzgIqC8qWXXgo4jSRJ0oHxk5okBaixT/9duGAhRCpud2vbJtgwkhqthjwKMPugXmT3OhhwN2BJktR4WQBKUoBefvllANod3JvWXboGG6aGIpEI8xfMB6BVi+akJSUFnEhSY5WenEz7lhVLCCxYsID8goY1CrByM5Bp06Yxf/78YMNIkiQdAAtASQrI0qVLmTp1KgADTzs92DAHYOXKleTnVXxI75GVFXAaSY1d3w4VOwKXlZUxa9asgNPsatDpZxIKhQBHAUqSpMbJAlCSAjJ+/Piq242xAJw3bx5QsflHxx3rd0nSgcponky7jHQA5s+bT0FBQcCJvpKenU33IwcD8OKLLxKJRAJOJEmSVDMWgJIUkMrdfzv07Udmp04Bp6mZbdu2sXr1agC6tW3t5h+SakXfjl+NApw9e3bAaXZ12I7NQJYvX86nn34acBpJkqSa8RObJAVg8eLFTJ8+HWico/8q1/4D6N62bYBJJEWTls2bk5WeBlSMMi4sLAw20E4OOeVUYuMTAKcBS5KkxscCUJICsMv031NPCzBJzZWVlVXs/gtkpafRolmzgBNJiiaVowBLS0sb1CjAxBYp9D3ueKBiBHdxcXHAiSRJkqrPAlCSAlA5/bdj/wG07NAx4DQ1s2zZMoqKigDokeXoP0m1K7NFC9qmpQIwd+7cqj9vGoLKacA5OTlMmjQp4DSSJEnVZwEoSfVsyZIlzJw5E2h8o//gq80/khLiqxbsl6Ta1G/nUYBzGs4owN4jjiEptaKcfOmllwJOI0mSVH0WgJJUz1577bWq2/1POjXAJDW3YeMGNmzYAECPtm0JEQo4kaRolJmSQuvUFADmzplLUQOZbhsbH0//k04B4I033iAvLy/gRJIkSdVjAShJ9ayyAGx3cO9Gt/vvnDlzAYiJiaF7VpuA00iKZpWjAEtKSpg7Z07Aab4y6IwzAcjPz2fixIkBp5EkSaoeC0BJqkerV6/m888/B2DAyacEnKZm8vLzWLZ0KQBdWmeSEBsXbCBJUa1NamrVKMA5c+ZQXNIwRgH2OHIILVplAvDyyy8HG0aSJKmaLAAlqR5NmDCh6vaARjb9d97ceUQiEQB6ZWcFnEZSU9C3Q8UowOLiYubuGIEctJhwuGr91rfeeovc3NyAE0mSJO2fBaAk1aNXX30VgNZdu9G2R4+A01RfaWkp8xfMB6BtWiqpSUkBJ5LUFLRJS6VVixYAzJ4zm5KSkoATVTj09DOAimJy5y92JEmSGioLQEmqJxs3buSjjz4CYMBJpxAKNZ4NNBYvXkxxUcX0u4PaZQecRlJTEQL6ddoxCrComLnzGsYowM4DB5Ge3Q5wN2BJktQ4WABKUj15/fXXKS8vB2DAKY1r+u+cHQvwpyQ2Izs9LdgwkpqUtmlptGzRHIDZsxrGKMCYmBgOHXk6AO+++y4bN24MOJEkSdK+WQBKUj2pnP6b0a49Hfr0DThN9a1atapqjauDsrMJ0XhGLkpq/EJA3x07AhcVFTF//vxgA+1w6MiKacBlZWW88sorAaeRJEnaNwtASaoHubm5vPfeewD0P+nkRjX9d8bMGQDEx8bSpU1mwGkkNUXZ6elkNE8GYNasWZSWlgacCNr36Utm5y6A04AlSVLDZwEoSfVg4sSJVdPWDmlE0383bNjA+nXrATgouy2xMeGAE0lqinYeBVhYWNggRgGGQiEGnX4mAB9//DGrV68OOJEkSY3fMcccQygUqpcBE1dffXXVuZYuXfqNjrV06dKqY1199dW1kq+2WQBKUj147bXXAEjJzKTzwEEBp6m+mTNnAhCOiaFndlbAaSQ1Ze0yMkhLrtiBfOasmZSWBT8KcOCOdQAjkQjjx48POI0kSdLeWQBKUh3Ly8tj0qRJAPQ/8WRiYhrHH705OTmsWLECgO5t25AQGxdwIklNWQjoVzkKsKCQBQsWBBsIyOrRk+xeBwMwduzYgNNIkiTtXeP4FCpJjdikSZMoKCgAYMDJjWf677Tp0wAIhaBXu+yA00gStG+50yjAGTMpKysLONFXm4FMmTKFJUuWBJxGkqTG7Z133iESiRCJRIKOEnUsACWpjlXu/puUlkb3I44MOE31bN++nYULFgLQOTOT5ISEgBNJEoQI0bdDxSjAgoICFi5cGHAiGHT6GVW3X3755eCCSJIk7YMFoCTVoaKiIiZOnAhAv+NPJBzXOKbRTp8+vepbt97t2wWcRpK+0qFVBilJiQDMmDEj8FGALTt0pNOAgYC7AUuSpIbLAlCS6tDkyZPZvn070Him/+bn5zNnzhwA2mWkk5qUFHAiSfrKzqMA8/PzWbRoUcCJ4NAdowDnzJlT9eenJEn1paysjOzsbEKhEC1atCA/P3+/zykuLqZVq1aEQiFatmxJcXFx1X2FhYWMGzeOH/zgBxx11FFkZmYSFxdHixYt6NGjB1dccQVvvvnmfs/x29/+tmpn3HfeeQeomOJ7xRVX0LVrV5KSkna5D6q3C/C2bdsYPXo0N9xwA4cffjgZGRnExcWRlpZG7969ue666/j000/3m29Pxo4dy8iRI2nfvj0JCQm0a9eOCy64oGpN99oydepUbr75ZgYMGEBGRgYJCQlkZ2czcuRIHn30UUpLa3+zs9haP6IkqUrl9N+E5OYcNHRowGmqZ9q0aVUjavp17BhwGknaXafMlsxc3oytBYXMmDGDbt27Ew5wg6WBp47k5T/+gUgkwssvv8zBBx8cWBZJUtMTDoe57LLLuPvuu9m+fTtjx47l8ssv3+dzJkyYwKZNmwC46KKLiI+Pr7qvd+/ee1zXdvv27SxcuJCFCxfy9NNPc9ZZZ/H000/TvHnzauX8wQ9+wP3331+DV7a74uJiWrduTWFh4W735ebmkpuby5w5c3jkkUe44YYbeOCBB4iN3X/1VVpaysUXX8xzzz23y6+vXr2aMWPGMGbMGG666SYeeOCBfZaT+1NUVMRNN93EY489tts6h2vWrGHNmjVMmDCBe+65h/Hjx9O1a9cDPtfXWQBKUh0pLS3ljTfeAKDPsccRl9As4ET7l1/w1ei/9i0zyGieHHAiSdpdiBB9OnTgo/kLyMvLY/GiRfTo0SOwPGlt29Lt8CNZ+OnHvPTSS/z85z//Rh8OJEmqqauuuoq7774bgKeeemq/BeCTTz5ZdfvKK6/c5b78/HzS0tI47rjjGDhwIJ06dSIpKYmtW7cyffp0nnvuOdasWcO4ceP41re+xfPPP7/ffHfddRevv/46mZmZXHXVVfTv3x+o2EQrJSWl2q+zvLycwsJC2rRpw/HHH8+AAQPIzs4mMTGRnJwcPv/8c55//nlycnJ46KGHSElJ4a677trvcX/2s58xduxYsrKy+Na3vkWfPn0oKCjg7bffZvTo0ZSXl/PPf/6TZs2a8de//rXaeXdWWlrKKaecUjXiMTs7m4svvpj+/fuTlJTEypUrGTt2LO+//z6zZs1i+PDhTJkyhczMzAM639dZAEpSHfnwww/JyckBYMDJpwScpnpmzZxVNfqvf+dOAaeRpL3rlNmKGctXsL1wxyjAbt2ICXAU4KAzzmThpx+zZMkSpk2bxiGHHBJYFklS09O3b18GDhzIlClTePvtt1mzZg1ZWVl7fOzmzZt57bXXAOjZsyeDBw/e5f7HHnuME044gbi9rF9+5513ctlll/Hyyy/zwgsv8P777zNs2LB95nv99dcZMmQIr732Gunp6VW/fsUVV9TkZRIXF8eECRM4+eST9/i+/+1vf5s777yTM844g48++oh77rmH7373u3TqtO/PNmPHjmXIkCFMmDCBtLS0ql//1re+xXXXXcfIkSPJz8/nb3/7G+eddx5HHXVUjXID3H777VXl33XXXcd9991Hs2a7DhK55ZZbuO+++7j55ptZtWoVt9xyC08//XSNz7UnrgEoSXWkcvpvXEICvYcfE2yYasgvyGf+/PlAxei/ltUcyi9JQYgJhejbsT1QMSVpT1OV6tOAk08lJhwGYPz48YFmkSQ1TZUj+crKyvZZGj3//PNVa/7tqYA79dRT91r+ASQlJfHEE0+QnFwxW+iJJ57Yb7bk5GReeOGFXcq/AxEOhzn11FP3+aVfy5Ytq0Y47u/3olLz5s0ZM2bMLuVfpWOOOYY//elPAEQikaqRljWxfv16/v73vwNwwgkn8PDDD+9W/lX6wQ9+wKWXXgrA6NGjWbVqVY3PtycWgJJUB8rLy5kwYQIABw8/hoTkhj+VdufRfwMc/SepEeicmUlyQgJQsXt5eaQ8sCzNMzLoMbhiNMC4ceN2W9dHkqS6dumll1atd/fUU0/t9XGV5VgoFKrxCLxKKSkp9OvXD4CPP/54v48/99xzadeu3QGd60B0796dtm3bAtXLd/nll5Odnb3X+6+//npSU1OBioEee1qDcF+ee+65quf85Cc/2e/jr7rqKqCiwHz77bdrdK69qdUpwJdeeik33ngjw4cPr83DSlKj89lnn7Fu3ToA+p/U8Kf/5uXnMW/+PGDH2n8tmoOfXSU1cJWjAD9ZsIht27axdMnSWl0su6YGnjaSeR+8x/Lly5k6dSoDBw4MLIskqelp3bo1p5xyCq+++iozZsxg6tSpuy1JsXDhQj766CMAhg8fvtepsTk5OYwaNYo33niDmTNnsmnTJvLy8vb4BdfKlSv3m+3oo4+u+Qvah9WrV/PUU0/x9ttvM3v2bHJycva6+3F18p1wwgn7vL9Zs2YMGzaM1157jZKSEqZOnbrb1Ol9effdd6tur1u3jpdffnmfj9951N/s2bOrfZ59qdUCcPTo0Tz33HP07NmTG264gSuvvJKMjIzaPIUkNQqVa2qE4+Loe/zxAafZv2lTp1FeVjFyxtF/khqTzq1bM3P5SvKKipg+fTpdunQJbAOO/ieezPO/vo3ysjLGjx9vAShJqndXXnll1VJETz755G4F4M7TYb+++UelcePGce2111btErw/W7du3e9j2rdvX61jVcdDDz3Ej370o70Wfl9XnXzV2Uxs58esXr26WueutHTp0qrbe/t935vNmzfX6PF7U+ubgEQiEebPn8+Pf/xjfvnLX3L++edz/fXX73dBSEmKFpFIpOpNt+eQo0hKSQ040b5t2bKFhYsWAhWL6me49p+kRiQcCtG7Q3s+W7iIrVu3snTZUrp07hJIluYZGfQcMpS577/LuHHj+PWvf+1uwJKkenXmmWeSnp5OTk4Ozz77LH/5y18I71ijFr6aGpyUlMQFF1yw2/M/+ugjzj//fEpLSwHo378/J5xwAt27dyc9PZ2EhISq97Zf/epXzJo1i/Ly/S/BkZiYWBsvjxdeeIEbb7yx6r+HDBnCiBEj6NKlC6mpqSTsWBoEKqbtbtiwoWqZo31JrsaSTTs/Ztu2bTXKvWXLlho9fmeV6zV+U7VaAL7zzjs8+OCDvPTSSxQVFVFYWMioUaMYNWoUvXr14sYbb+SKK67Y46KKkhQtpk+fzooVKwAYcNKpAafZvylTpkCkYirdgE4dg44jSTXWtXUms1asIL+omOnTptO5U+fAireBp41k7vvvsmLFCqZMmcKhhx4aSA5JUtOUkJDAhRdeyEMPPcTatWuZOHEip55a8Znkgw8+YPHixQCcffbZtGjRYrfn//rXv64q//7xj39w00037fVcd955Zx28gn375S9/CVRsBvLSSy9xxhln7PWx1113XbWPm5eXV6PH7On3bl+a7zTIYuvWrTV+fm2o1U1Ahg8fzjPPPMPKlSv5y1/+Qs+ePYlEIkQiEebOncsPf/hD2rVrxzXXXFM151ySok3l6L9QTAz9Tjwx4DT7tn79+qqysnvbNjTfy05UktSQhWNi6L1jalFubi7Lli0LLEv/E08mZscC7OPGjQsshySp6dp5imnlhh9fv72naaglJSW88847AAwaNGif5R/sOq21PixZsoSFCytmLp199tn7LP+2bt1ao6mzlcet7mP2tWHInuw8Bbry81d9q5NdgFu2bMmPf/xj5s6dy//+9z8uuugi4uPjiUQiFBQU8OSTTzJs2DD69+/PP//5z2rNx5akxqJy/b9uhx1Bi5atAk6zb19++SUAseEY+nbsEHAaSTpw3dq0JjE+HoDpM6YHtgtvcno6Bx01FHA3YElSMI466qiq9erGjRvHtm3bKCoq4vnnnwcgKytrj5tebNy4sWr0X/fu3fd5js8++4yNGzfWcvJ9W7t2bdXt/eX773//W62pyZXefPPNfd5fVFTE+++/D0B8fPxuayvuz4gRI6puv/766zV6bm2pkwJwZyNGjODZZ59l5cqV3HXXXbuMCpw1axbf//73yc7O5tvf/jaffvppXceRpDo1b948FixYAMCAUxr27r8rVqxg/fr1ABzcrh3N4uICTiRJB65iFGA7ALbkbAns23WAgaedDlTs4PfFF18ElkOS1HRdccUVABQUFPDCCy/w6quvVq1Dd9lll+2yLmClnde429+IuN/85je1F7aaqpuvuLiYO+64o0bHHjVqFGvWrNnr/Y888kjV79/pp59OsxrOnLr44our1ie855576r08hXooACu1bNmSW2+9lblz5/L2229z0UUXERcXRyQSIT8/n8cee4whQ4YwcOBA/v3vf1NQUFBf0SSp1lRO/wXof2LDLQDLysv5/PPPAUiIi6VXu5oNYZekhqh72zZVX2ZMmzYtsBz9Tjipahrw+PHjA8shSWq6rrjiiqr1cJ988sn9Tv8FSElJoWfPngB88cUXjBkzZrfHlJWVccsttwQyiq1Xr15Va+mNHz9+j0vLFRQUcPnllzN9+vQaHXvbtm1ceOGFe5yh+u677/Kzn/0MgFAoxK233lrj7O3bt+cHP/gBULGD8Mknn1y1HuPeTJs2jRtuuKHG59qbWt8FuDqOPfZYunbtSmpqKg8//HDV/5SRSITp06dz44038stf/pJf/vKX3HzzzcTE1FtPKUnfSGUB2GnAQNKzsgJOs3dz586p2rlqQKdOxO3hG0BJamzCMTEc3L4dU5YsJScnhxUrVtChQ/0vb5CclkavocOYPfkdxo8fz29/+9s9jrSQJKmudO7cmeHDhzN58mTefffdqvehQw45hH79+u31eT/84Q+r1v678MILueiiixgxYgTp6eksXLiQUaNGMWfOHPr27UtCQkK9jnSPj4/npptu4q677qKkpIQRI0Zw9dVXc8QRR5CcnMzs2bN54oknWLFiBccffzzz5s1j5cqV1Tr2eeedx4svvsjBBx/MtddeS+/evSkoKODtt99m9OjRVTsJ33LLLQwZMuSA8v/xj39k2rRpTJw4kS+//JJevXpx5plncvTRR5OVlUV5eTkbN25k5syZ/O9//2P+/PmEw2EeeuihAzrf19VrAVheXs748eN56KGHePPNN6vWRIlEIrRo0YLBgwczefJkiouL2bRpE7feeivjxo3j9ddfr7UtoyWprixdupSZM2cCcEgDnv5bUFDA9GkV34ilJSfRrW3rgBNJUu3pkdWWOStXUVhSwrTp0wIpAKFiGvDsye9UTQMePHhwIDkkSU3XlVdeyeTJk4lEIlVr++1t9F+lG2+8kc8//5xHH32USCTC6NGjGT169C6P6devH+PGjeOaa66ps+x78//s3Xd8VGX6///XmUmvEAi9JYEQQgmdhBZ6FxHL2lbX1S26urrqfj+76+7+/Oiu+tld22J3UUEEUQRDR2qooYdeQwm9BRLSk5n5/THJLBhKCCczKe/n48HDMPc517nCOMmZa+77vl599VW2b9/OwoULKSoq4tNPP+XTTz+96pjExESmT59Ot27dyh33jTfewMfHh2nTpvHqq69e85gnn3ySf/7znxXO3cvLi7lz5/LHP/6Rd999l6KiIr777ju+++67655zZfOQ2+WWqXVHjx7lz3/+M82bN+fuu+/mhx9+wG6343A46NixIx988AEnTpxg0aJFHDt2jL///e+Eh4fjcDhYtWoVb731ljvSFBG5LaXNPwA6DRvpwUxuLDU1laKiIgC6R0ViYHg4IxER83hZLK5tDTIuZJT7k3+zdRwyDGvJcmR1AxYREU+49957CQgIcP3dy8uLBx988IbnGIbBxIkT+e677xg+fDj16tXD29ubRo0akZiYyHvvvceGDRuIiIio7PSvycfHh3nz5jFx4kT69+9PaGgoPj4+NG3alBEjRjBp0iSWLVtGvXr1bimul5cXU6dOZcaMGYwaNYomTZrg4+ND48aNGT9+PEuWLOGDDz647RWq3t7e/Otf/+LgwYP89a9/pV+/fjRq1AgfHx/8/Pxo2rQpAwcO5A9/+APLly+/6TLhW2E4Kqk1mc1mc832W7JkiavxBzifsHvuuYcnn3ySPn36XPP8jIwMEhMT2bVrF7Gxsa5ZNeIZlb1BZd26dbFardhsNi5evFip15LKY7VaqVu3LhcvXnRNka5NRo4cyaZNm2jaLpb/meOZzk43c+HCBVehskX9evSNaVvmGKvVCgbgoFY+jzWKYWC1WrDZ7KBOpNWWXpO3rshmI2njZgqLi6lfvz6jRo3ySB4f/+Ixdi1fRuPGjdmxYwf16tWrtb8jawrds9Yctf2+taao7Ndk/fr1TY8p4immzwA8cuQIL730Ei1atOCee+5h8eLFrtl+rVq14vXXX+f48eNMmTLlusU/gLCwMJ599lkADh8+bHaaIiKmOnXqlKupRqdhVXf578aNGwGwWCx0iWjl2WRERCqJt9VKu2bOWYDnz5/32CzAziNHA87fERs2bPBIDiIiIiJg8h6Aw4cPZ+nSpVfN9rNYLIwaNYqnnnqKESNGuBp+lEfpWuf8/Hwz0xQRMd2Vy387D6+ay38PHjzI2bNnAYht1oTAkjb0IiI1UXTjxuw9cZKComJSU1NN3UOnvDoOGYrV2xtbURHff/89I0dWzd8PIiIiUvOZOgPwytl+DRo04I9//CNpaWnMmTOHkSNH3lLxDyAgIIAWLVrQsmVLM9MUETFdaQGwQUQkjdq08XA2ZeUX5Ls6dAX6+hLrgTfCIiLu5G21EtusKeDcWiY9Pd3tOQSEhBLTtz8Ac+bMwW63uz0HEREREaiEJcD9+vVj6tSprmYet1O869+/P0eOHDF100MREbOdP3+etWvXAhA3/NY/7HCHzZs3U1BQAECP1pF43ebmtSIi1UGbxo3xK2nEkZqaSiVtfX1DXUaNAZzLgEt/V4iIiIi4m6nvAHfs2EFycjL3338/3iU3WyIiNd2CBQtcszrihle9/f/OnDlD2sE0wNn4o0nduh7OSETEPbwsFto3d854vnTpEkeOHnF7Dh2HDMHq7QPAN9984/bri4iIiIDJBcD27dubGU5EpFooXf4b1rQZzTt09HA2V7PZ7aSkpADO5XDdIiM8nJGIiHu1btQQfx9nAW7btm1unwXoHxxCu/6JAMyYMUPdRkVERMQjTC0AWiwWvLy8mD179i2dt2jRIqxWK15epvYkERGpdJmZmaxcuRKATsOGV7nlvzt37CAzMxOATq1auN4Ei4jUFlaLhQ4lswCzMrM4dNj9W8t0GTkKcC4DXr9+vduvLyIiImL6JlAV/VT1ys7BIiLVxeLFiykqKgKc+/9VJRkZGWzfvh2AesFBRDdu5OGMREQ8I7JRQ1fn823btmF3uLcZR4fBQ/HycV7/+++/d+u1RURERKASCoAiIrXJ3LlzAQgJDyeiazcPZ/NfdrudNWvW4HA4sBgG8W3aYFC1ZieKiLiL1TDo0MI5CzD7cjZpaWluvb5/cLBrGfCcOXO0DFhERETcrkoUAHNzcwHw8/PzcCYiIuWXk5PDsmXLAOg4dDiWKtRZd8fOHVy8eBGATi1bEBrg7+GMREQ8K6JBA4JK7jW3b9uOze7eWYBdRzu7AZ85c8a1N6uIiIiIu1SJd6ulN0ENGjTwcCYiIuW3bNky8vLyAOhchZb/ZmRksH2bc+lvWFAQMU2beDgjERHPsxgGHVs0B5wf4Bw8eMCt1+8waAheJcuQk5KS3HptERERkQp33di+fTupqanXHFu2bBmXLl264fkOh4OcnBy2bNnClClTMAyDHj16VDQdERG3K13+GxAaSuuevTycjZPNZrtq6W9CdGssVawxiYiIp7RqUJ9dx46TlZfHju07aB3VGqvV6pZr+wUF0XHgYLYunM/cuXN5/fXX3XZtERGpuapaE8KbUe8Hz6lwAXDWrFm88sorZR53OBxMmDDhlmI5HA4Mw+DXv/51RdMREXGrgoICfvjhBwA6DhmG1dvbwxk5bd261bX0t2PLFoQGBHg4IxGRqsPAoGPL5qzZu5/c3Fz2799Pu3bt3Hb9bmPuYOvC+Zw7d45169bRt29ft11bREREarcKFwDh+pXbW63oNmzYkL///e8MGjTodtIREXGb5ORksrOzgarT/ffkyZPs3r0bgAahIcQ209JfEZEfa1G/HrsCA7iUk8uOHTto3bo13m76EKfTkGF4+/pSVFBAUlKSCoAiImKa1x78Ce2aNfV0Gte05/gJ/jR1uqfTqPUqXAAcN24crVq1uuqxxx57DMMwePrpp+natesNz7dYLAQFBREREUHHjh3dsgQiMzOTGTNmsGHDBi5cuICvry9RUVGMGjWK+Pj4CsctLi5m7ty5JCcnc/LkSQCaNm1KYmIio0ePxsvrxv/Mhw4dYtasWezYsYOsrCxCQ0Pp0KED48ePJyIi4qbXLyoq4ocffmDNmjUcO3aMnJwcQkNDadKkCZ06dWLcuHH4luw5IyLmmDdvHgC+gYG07dPHw9lAfkE+a9asAcDbaiUhWl1/RUSuxcCgU8sWrNy9l/z8fPbs2UOnTp3ccm2/oCBiBwxi26IFrmXAN7tPFBERKY92zZrSo3WUp9OQKqzCdxxxcXHExcVd9dhjjz0GwODBgxk7duztZWay9PR0XnrpJTIzMwHw9/cnJyeH1NRUUlNTueOOO/jFL35xy3Hz8vL4y1/+wv79+wHw8fEB4ODBgxw8eJA1a9bwyiuvXLfDcXJyMu+++y7FxcUABAYGcuHCBZKTk1mzZg2/+93v6Nev33Wvf/LkSV599VVOnDgBgNVqxc/PjwsXLnDhwgV27NjB4MGDVQAUMVFxcTELFy4EoP3AwXj7er6D+bp161wNSXq2iSJQr3kRketqGhZG/eAgzl/OZueunUS3jcbPTT/Lu4wazbZFCzh//jxr166lf//+brmuiIiI1G6mfuT4+eefA9x09p+7FRUV8be//Y3MzExatmzJ888/T0REBAUlyy+++uor5syZQ0REBEOGDLml2B988AH79+8nMDCQ3/72t66ZhCkpKfz73/9m7969fPjhh/zud78rc256erqr+Ne3b1+eeOIJwsLCyMjI4NNPP2XNmjW88847RERE0KxZszLnZ2Rk8Kc//YmMjAzatm3Lww8/TIcOHbBarRQUFHD06FHWrl3rKkqKiDnWrVtHRkYGAHHDRng4G9izdw/H0o8BENEgnJb163s4IxGRqs0AOke0Ysn2nRQXFbNjxw56dHdPM7oOAwfj7edHUX4+s2fPVgFQRERE3MJiZrBHH32URx999JrFKk9atGgRp0+fxtfXl7/+9a+uZbW+vr7cd999jBzp3L9rypQprpl45XH48GFWrlwJwDPPPENCQgKGYWAYBgkJCTz99NMArFixgqNHj5Y5/6uvvqK4uJiIiAheeOEFwsLCAAgLC+PFF18kIiKCoqIivvrqq2te/6OPPiIjI4PY2Fhee+014uLiXEupfX19iY6O5mc/+xkhISHl/p5E5ObmzJkDgLevL7GJAzyay7nz59i8aTMAQX5+dI+K9Gg+IiLVRYOQEJrUrQPAvr37XPu6VjbfwEDaD3Duez137txbuvcUERERqShTC4BV1YoVKwDo378/4eHhZcbvvvtuDMMgIyODHTt2lDtucnIyDoeDxo0bk5CQUGa8d+/eNG7cGIfDQXJy8lVjOTk5bNy4EXDup/jjPRCtVivjxo0DYMOGDeTm5l41fvToUVJSUgB46qmn3LZ5tUhtZ7fbmT9/PgAx/RLxDQz0WC4FBQWsTF6J3W7HYhj0a9cWbzfspyoiUlPEtWoJOH+2b9u2zW3X7TxyNAAXLlxw7d8qIiIiUplqfAEwLy+PAwcOANdfmhweHu6atXgrN3/bt28HoEuXLhhG2c32DcOgS5cuVx1bavfu3a5PfK+XV+njRUVF7Nmz56qx0qJmREQELVq0KHfOInJ7Nm3axJkzZwDPdv91OBysXrOanJwcALpHRVLXg8VIEZHqqG5gIK3CndsmpKWlcfHSRbdct/3AQXiX7A+dlJTklmuKiIhI7VahPQAjI51LzAzDIC0trczjFfXjeGY4fvw4DocDgJYtW173uJYtW3Ls2DGOHTtWrrgOh4Pjx4/fNG5pce7HcUv/XqdOHUJDQ695bmhoKKGhoWRmZpKenk63bt1cY6UFwcjISHJycvjmm29Yt24d58+fJzAwkDZt2jBq1Ci6d+9eru9HRMpn7ty5AFi8vOgwaLDH8ti5aycnjjub/0Q0CCeqUUOP5SIiUp11atmS9PMXsDscbN26lUEDB1X6NX0DAmg/cDCpC+Yxb948/u///k+rOURERKRSVagAeOTIEYAys96OHDmCYRiugtututYsuttVulE/4Npj71pKxy5eLN8nv3l5eeTn55c7bl5eHnl5efj7+191nRudWzqemZlZJq9Tp065vv7d737H6dOnsVqt+Pv7k5WVxaZNm9i0aRN33nknjz/++E2/nylTpjB16tTrjj/wwAM8+OCDN41TURaLxfXfunXrVtp1pHKVvoZDQ0Mr/HOgKnM4HCxYsACAmD79qNuggUfyOHnyJFu3bgUgNDCAXtFt8Kqkpb8/3p5AqierpcZP+K819Jo0X2hgAG2aNGbfiZMcP3acixcv0qhRo0q7Xmlztp53jiN1wTwyMjJITU1l2LBhlXZNMY/uWWuOmn7fWlvoNSlSfhUqALZo0eKaxbrrPe5JpUU6cDbGuJ7Ssby8vHLFvfK48sQtPae0AFh6/o3OvVFepRtVL1++HMMweOKJJxg+fDi+vr5kZGQwadIkli9fTlJSElFRUQwYMOCG18nJyeHs2bPXHc/NzXXLmw7DMPTmpgaw1NBiw5YtW1wfgHQbNdojP+8uX77MkiVLwAFeVguJ7dvh7VVJr5mq9eNcboeey5pBz2Ol6dSyBWmnT1Nss7Nx40bGjh1badcq/d3RcfAQfPz9KczLY+bMma6mdFI96J615qip9621jV6TIjd3WzMAy/u4mK/0Uyq73c4999xz1Y1qWFgYzz33HMeOHePgwYN8++23Ny0ABgYG0uAGs5kCAgKw2Wym5H4tFovFNXvUbrdX2nWkchmGgcViwW6318hPUmfMmAGAYbHQadhwt3+PRcVFLFq0iIKCAgB6t21LqH8AVEYaBpUTV9xPz2XNoOexUvl5exPbrBnbj6Zz+vRpjh49Wil7LF+5UsbHz59OQ4axaU4SM2fOZMKECVoGXA3onrXmqOn3rbVFZb8mVVSUmqRCBcDqxK9kg2VwdswMCAi45nGlb6hLZ+jdzJXHlZ57o7g/Pqf06xude6O8/P39uXz5MgB33nlnmfMMw+DOO+/kzTff5NixY2RkZNxwufHDDz/Mww8/fN3x8+fPl3t5dEXUrVsXq9WK3W6v1OtI5bJardStW5fMzMxKLRh7SmkBMKp7T3yDQ276+jXbiuRk17YGHVo0o1lY3Ur5d77yRqcmPo+1imFgtVqw2e2gNzfVll6T7tG2SWP2nTxJQVEx69evJ7xBOBbDvJlBhmHg6+tLYWGhq9gQN2Ikm+YkkZGRwezZsxk0qPL3H5Tbo3vWmqOm37fWFpX9mqxfv77pMUU8pcbPd76y6HXlfoA/VjpW3n0D/P39XUW58sS98vgr87rRuTfKq/T84ODg6zYRKe1sDM4CnohU3P79+10dxeOGj3D79bdv30760aMANKsXRscWzd2eg4hITeZttdKhufNn66VLlzh44GClX7Nd4kB8Sj6cVjdgERERqUw1vgDYrFkz114r6enp1z2udKx58/K9qTYMw1Vgq0jc5lfcYGZlZV3z3MzMTDIzMwHKLEO51WUpVW1vRpHqZs6cOa6vOw0d7tZrHzt2jNTUVABCAwJIiG6Doc3ARERM16ZxI4L9natHUlNTKSoqqtTr+fj50XHwEADmz59PYWFhpV5PRESkOklLS+O3v/0tsbGxBAcHExQURLt27Xj00UdZuHCh67gVK1ZgGIar7pGSksI999xD48aNsVqtPPfccx76DqoWtxcA8/LyePvttxk/fjxjx47lr3/961Udbc3m7+9PmzZtAOcG/tdy/vx5jh07BkBcXFy5Y3fq1AnA1Y3zWkrftJceWyo2NhYvL68b5lUa19vbm3bt2l011rlzZ8DZEKC0SPhjx48fd30dHh5+3RxF5Obmzp0LQMu4ztRt0sRt1z13/hwrV64EwMfLi/6xMXhrLxIRkUphMQy6RLQCnI3kdu7cWenX7DxyNOD8ULj0572IiEht9+mnn9KuXTsmTJjAnj17KC4uxsfHh3379jF58mTuv//+a543ffp0+vXrx3fffUdeXp72cbyCqQXArVu30qlTJ+Li4li3bl2Z8aysLOLj43nxxRdJSkpi3rx5/P3vf6dTp043LKLdrtIGGCtXruTcuXNlxmfOnInD4SAsLIyOHTuWO27//v0xDIOTJ09e8/tdu3YtJ0+exDCMMk04AgIC6NGjB+Bc8vHjfSdsNptrKUjPnj3L7F2YkJDgWlL8/fffl7m2w+Fwnd+mTRvq1KlT7u9LRK525MgR15vAuOHu69KYlZXFsqXLsNlsWAyDfu3aEnzFvqYiImK+pmFhNAgNAWD37t3k5ORU6vXa9R+Ab2AgALNnz67Ua4mIiFQH33//Pb/85S8pKipi1KhRbNmyhby8PDIyMsjMzGT27NmMHHnt92VPPPEEd955J4cPH+bSpUvk5uZqBmAJUwuAM2bMYOfOnZw9e5b4+Pgy4y+99BI7duzA4XBc9efChQvcfffdlbah/vDhw2nUqBH5+fm8+uqrHD58GHA22JgxYwbz5s0DnI0wSmfllXriiScYO3Ys77zzTpm4ERER9O/fH4AJEyaQkpLi+p5SUlJ47733AGcB8lpLdh966CG8vLxIS0vjrbfecm1aevHiRd566y3S0tLw9vbmoYceKnNuUFAQ9913H+B8ccyZM8f173fx4kXeeecdDh48iGEYPPjggxX5ZxOREqU/IwDihrln/7+8vDyWLFniel3HR7eh4XX2+xQREfMYQNeICMD5geyWrddeqWEWHz8/OmgZsIiICABFRUU8++yzgLPh6Zw5c+jSpYtrPDg4mDvuuINp06Zd8/y4uDi++eYbWrVqBYCXl5fr69rO1C7A69evxzAMhg4dWmbPucuXLzNx4kQMw6B58+a8++67RERE8MEHH/DJJ59w9OhRpkyZwuOPP25mSoBzCe2f//xnXnrpJY4cOcKzzz5LQEAA+fn5rlbhY8aMYciQIbcc+6mnnuLUqVPs37+f1157DR8fHwDXzVtMTAxPPvnkNc9t0aIFzz77LO+++y6rVq1i9erVBAQEuD5p9vLy4tlnn72qmceVxo8fz/Hjx1m6dCmffvopn3/+Of7+/mRnZ+NwOLBYLPz85z+nW7dut/x9ich/lRYAm8S0I9wNvzyKiopYunQp2dnZAHSJaEmrcHUgExFxl7CgQCIbNuDQmbMcPnSYdjHtKrUTZJeRY9g8O4nMzEySk5MZOnRopV1LRESkKlu2bBnp6ekYhsFbb72FxXJr89ZeeOGFWz6ntjC1AHjixAmAq6qzpRYsWEB+fj6GYTBx4kQGDx4MwEcffURKSgo7duzg+++/r5QCIDiLbRMmTOC7775jw4YNnD9/nsDAQCIjIxk9evQ1ZyyWh7+/P2+88QZz584lOTmZkydPAhAVFcWAAQMYPXp0mVmFV0pMTKR58+bMnDmTnTt3kpWV5VqKPH78eCJKPoG+FsMwePbZZ+nRoweLFi0iLS2N3NxcwsLCaN++PXfeeadr/0MRqZhTp06xceNGwD3Lf+12O8nJya4O4G2bNCamadNKv66IiFytU8sWHD13HpvdzsaNG6+71MgM7fr3xzcwiIKcbJKSklQAFBGRWqt0e7WYmBgiIyNv+fyEhASzU6oxTC0Anj9/HoDGjRuXGUtOTnaNlRb/St17771s376d7du3m5lOGXXq1OHxxx+/pSLjf/7zn5se4+Xlxbhx4xg3blyF8oqMjOTFF1+s0LkAvXv3pnfv3hU+X0Sub/78+a6v44ZX/vLfdevWuT5IaFG/Hl0jW6nfr4iIBwT4+BDbrAk70o9z7tw5jh49SsuWLSvlWt6+fnQcMpRNSbNYsGABBQUF+Pr6Vsq1REREqrIzZ84AVPh3rhqgXp+p8yJLu9Fea7rlunXrMAyjTPEPcO2Pd60GHSIinlTa/bdBRCSN20RX6rW2pm4lLS3Neb3QEBKi22Co/Cci4jHtmjXFz8cbgM2bN5dp2mamLqPGAM4GUKUfnIuIiMitUdff6zO1AFjaqfbHhbzMzEzX7L5rzVTzK+lqWZk3VSIit+r8+fOsXbsWgE7DRpTZ29RM+/bvY8f2HQCEBgTQv10MVu1dISLiUV4WK51bOWcgZGdns2vXrkq7VkzffvgFBQOQlJRUadcRERGpyho1agTA0aNHPZxJzWPqu8vSziqrV6++6vG5c+e6mm306dOnzHkXLlwAIFQdLkWkClm4cKHrZ1fnEZW399OxY8dYv349AP4+Pgxo3w6fG+wdKiIi7hPRIJx6wUEA7Nixw9WgyWzevr50GjoMwLUMWEREpLYp3cNv7969HDp0yMPZ1CymFgD79euHw+Fg9uzZbNu2DXAuY/jHP/4BQJMmTejQoUOZ83bu3Alww4YXIiLuVrr8t26TpjTv0LFSrnHu3DlWrlwJDvC2WhnYIZZA7fskIlJlGBh0j3JuQm6z2di0aVOlXavzyNEAXL58mRUrVlTadURERKqqQYMG0aJFCxwOB88//7xrQobcPlMLgL/4xS+wWCzk5+fTs2dP4uPjiYqKYufOnRiGwS9+8Ytrnrds2TIMw6BTp05mpiMiUmFZWVnOwhwQV0nLfzOzMlm6bCk2mw2LYdA/NoY6JVspiIhI1VEvKIjWjRoCkJ6e7mrWZLa2ffriHxwCaBmwiIjUTl5eXrzzzjuA83fh2LFjSU1NdY1nZ2fz7bffctddd3kmwWrM1AJgp06d+P/+v/8Ph8NBUVERGzdu5MKFCzgcDjp27Mjvf//7Mufs2LGDvXv3AtC3b18z0xERqbAffviBoqIiAOIqYflvXl4eS5cspbCgEICEtm1oqG0QRESqrLhWLVzbM2zYuAFbJcxI8Pb1peMVy4Dz8/NNv4aIiEhVd9ddd/H+++9jtVqZN28eXbp0ISAggHr16hESEsJ9993H8uXLPZ1mtWP6DvN/+ctf+P777xk9ejTR0dF07dqVP/zhD6xcuRJ/f/8yx0+YMAEAh8PB8OHDzU5HRKRCSpf/BtcPJ6JLV1NjFxUVsXTpUtc+Ul0jW9Gyfn1TryEiIuby9fImrmULALIys9i7Z0+lXKfLKOcy4OzsbL25ERGRWuupp55i586d/OpXv6J169Y4HA6Ki4uJiYnhscceY8aMGZ5OsdqplF3mx44dy9ixY8t17CeffMInn3xSGWmIiFRITk4Oy5YtA6DTsOFYTGwlb7PbWbFiBRkZGQC0bdqYmCZNTIsvIiKVp3Xjhhw4fZpLObls27aNiMgIAvzN3bqhbe+++IeEkJeVRVJSEiNHVl4TKhERkaosJiaGjz766KbHDRgwAIfD4YaMqjfTZwCKiFR3y5cvJy8vD3Du/2emdWvXcurUKQBa1K9H14hWpsYXEZHKY2DQIyoKgOLiYjZv3mz6Nbx8fOg0zLkqZuHCha7fRyIiIiK3QwVAEZEfKV3+GxAaSpte8abF3bJli6uVfYPQEBKi22BgfnMRERGpPOEhwbRqEA7A4UOHOXX6lOnX6DJyDOCcka5lwCIiImIGFQBFRK5QUFDADz/8AECHwUOxenubEnfv3r3s3LkTgNCAAPq3i8Fq0Y9gEZHqqEurVniXbA+Rsi4Fm81mavy2vfsQUNIYSt2ARURExAyVsgcgQGpqKgsWLGDnzp1cvHixXF3MDMNg6dKllZWSiMhNrVy5ksuXLwMQN9ycfZfS09PZsGEDAAG+Pgzs0M7VSVJERKoffx9vOke0YuPBNC5fvsyOHTvo3LmzafGt3t50GjaClG+nu5YBX6uZnoiIiEh5mf4O9NSpUzz22GMsXrz4ls5zOBwYhpbCiYhnlS7/9Q0MJKZv39uOd/bsWVatWgWAt9XKgPaxBPj43nZcERHxrNaNGnD47FnOZ11m586dtGrVijp16pgWv8vI0aR8O53c3FyWLl3KmDFjTIstIiIitY+p68+ys7MZOHAgixcvxuFw3NIfERFPKy4uZuHChQC0HzAIb1+/24qXmZnJsmXLsNlsWAyD/rEx1Akwt1ukiIh4hoFBr9ZRWAwDu91OSkqKqfe00Qm9CSgpKGoZsIiIiNwuUwuAb7/9Nvv37wegWbNmfPjhhxw8eJD8/HzsdvtN/5i9f4qIyK1Yt24dGRkZwO0v/83Ly2PJkiUUFhYCkNC2DQ1L9nMSEZGaITQggHbNmgLOGd8HDx40LbbV29vVif6HH34gNzfXtNgiIiJS+5haAJw1axYAjRo1YuPGjfzqV78iMjISHx8fMy8jIlIpSpf/evv6Eps4oMJxioqKWLp0KTk5OQB0jWxFy/r1zUhRRESqmA7NmxHk55wxvnnzZvLy8kyL3WWUc9lvbm4uS5YsMS2uiIiI1D6mFgDT0tIwDIOnnnqKhg0bmhlaRKRS2e125s2bB0BMv0R8AwMrFsdhZ+Wqla6ZhG2bNCamSRPT8hQRkarFarHQs3UUAIWFhaxfv9602G3iEwisWxeA2bNnmxZXREREah9TC4B2ux2Atm3bmhlWRKTSbdq0iTNnzgAQN3xEheNsWL+BE8dPANCsXhhdI1uZkZ6IiFRhjeqEEtmwAeDs/H74yGFT4lq9vFxbUixevNg1s1xERETkVplaAGzZsiUAly9fNjOsiEilK539Z/HyosOgIRWKsWPnDtc+qPWCg+jTNhoDdTcXEakNuka0wr9k25sN6zeQl2/OUuAuo0YDWgYsIiIit8fLzGBjx45l9+7drFmzhscee8zM0CIilcbhcLj2/4tO6ENABZp1HD58mK1btgIQ5OdHYmw7rBZTP2MREZEqzMfLi55tokjetYeCggLWp6xnwIABtx23dc94gsLqkZ1xgaSkJO68887bT1ZERGqcPSWrkKqiqpxbbWJqAfCZZ57h448/5quvvuLFF18kJibGzPAiIpVix44dpKenAxVb/nv69GnWrFkDgK+3FwM7xOLn7W1qjiIiUvU1rVuXyIYNOHTmLOnp6Rw5coRWrVrdVkznMuARrJn2FUuWLCE7O5ugoCBzEhYRkRrjT1OnezoFqeJMnZ7SuHFjvv76a7y8vBg6dCgrV640M7yISKUonf1nGAadhg67pXMvX77MiuQV2O12LBYLibHtCC7pBikiIrXPlUuB169fb8pS4NJlwHl5eSxevPi244mIiEjtY+oMwFdeeQWAIUOGkJSUxMCBA+ncuTMJCQnUr18fSzmWw/31r381MyURkZsq3f8vsntPguvVL/d5RUVFLFu2jMKCQgB6R7ehfnBwpeQoIiLVg4+XFz1bR5G827kUOCUlhYEDBt5WzKgevQiuV5/LF86TlJTEXXfdZVK2IiJS3TkcDk+nINWEqQXAl19+GcNwbnhvGAYOh4PU1FRSU1PLHUMFQBFxp/3797sad3QeMbLc5zkcDlauXElmZiYAnVq2oEX9epWSo4iIVC9Nw/67FPhY+jEOHDhAdHR0heOVLgNePXUKS5cu1TJgERERuWWm71DvcDhcf37895v9ERFxtzlz5ri+7jSs/Pv/bdmyhRMnnJvZtgyvT/vmzUzPTUREqq9ukREE+voCsHHjRrIuZ91WvC6jxgCQn5+vZcAiIiJyy0ydAbh8+XIzw4mIVLrS/f9axnWhbuPG5Trn4MGD7Nq1C4CwoCDi27TGqLQMRUSkOvK2WundNprF23dQXFzMqpWrGDduXIXjRfXoSXD9cC6fP6dlwCIiInLLTC0AJiYmmhlORKRSHTlyhJ07dwLl7/579uxZUlJSAPD38SExNgZrOfY3FRGR2ic8JJj2zZux69hxzp8/z9atW+nQoUOFYlmsVjqPGMmqKZNZsmQJly9fJlj7zoqIiEg56V2riNRapbP/AOKG33z/v9y8XFas+G/H3/6xMa5OjyIiItfSsUVzwkr269u8ZTNnz52tcKyuo+8AoKCggPnz55uSn4iIiNQOKgCKSK1VWgBs2i6W8JYtb3is3W4neUUy+fn5AMS3iaKeNmAXEZGbsBgGvdu2cc4Wd8CqlasoLCysUKyIbt2p08i5XcWsWbPMTFNERKopwzCq1R/xnEovAB4/fpwffviBr7/+msmTJ1f25UREyuXkyZNs3rwZKN/y382bN3Pu3DkA2jZpTKvw8ErNT0REao4Qf3+6RUYAkJ2dzdq1aysUx2Kx0HW0sxlIcnIyFy5cMC1HERERqdlM3QPwSp999hlvvvkme/fuverxRx555Kq///3vfyc5OZnmzZszceLEykpHROQqt7L89/Dhw+zZswdw7ufUJaJVZaYmIiI1UOtGDTmblcWRs+dIT09n7969xMTE3HKcrmPGsmzipxQXFzN37lweffTRSshWRESqm5+8+hpNY9p5Oo1rOrF3D9P/8idPp1HrmV4AzMvL45577mHhwoUAOBwO19i1pnt2796dv/zlLxiGwYsvvki7dlXzf1gRqVlKC4ANo6Jo3Cb6usddvHSRdevWAeDn7U3fmLZYNHVdRERulWEQH92G81mXyc7PZ9OmTYSHh1OvXr1bCtO8Q0fCW7bi3NEjzJw5UwVAEREBoGlMO6K69/B0GlKFmb4E+JFHHmHBggU4HA5atmzJH//4R379619f9/ihQ4cSXrKU7soZOSIileXKTr43mv1XVFTEiuUrKC4uxjCgb7u2avohIiIV5u1lpV875wdJdrud5JXJFBbd2n6AhmHQ9Y6xAKxbt45Tp05VRqoiIiJSw5haAFy6dCnfffcdhmHwwAMPsG/fPv7+978zfPjw6ydgsTB06FAcDgerV682Mx0RkWsq/ZACblwATFmfwuXLlwHoEtGKBiEhbslPRERqrrpBQf/dD/ByNmvXrrvlGKXdgB0OB0lJSabmJyIiIjWTqQXAL774AoDIyEi++OILvL29y3VeXFwcgGuPLRGRylQ627he8+Y0i21/zWPS0tI4fOgwAM3qhdG2SRO35SciIjVb68aNaFHfufQ3/ehRdu/efUvnN24TTZOSfZ5mzpxpen4iIiJS85haAFyzZg2GYfDII4+Uu/gH0KTkjfXp06fNTEdEpIyLFy+6ZhvHDR95zb1JM7MyWb9+PQABvj70atMa7fonIiJmMYBebVoT7O8HwKbNmzh1+taW8pbOAty6dSuHDh0yO0URERGpYUwtAJ45cwaAtm3b3tJ5fn7Om5/8/Hwz0xERKWPhwoUUFxcD117+a7PZWJm80nVMn7bR+HpVWsN0ERGppbytVvq3a4eX1QIOWJm8kuzs7HKf323MHa6vv//++0rIUERERGoSUwuAVqsVALvdfkvnZWRkAFCnTh0z0xERKaN0+W9ow0a0jOtcZnzz5s1cvHgRgE4tWxCuff9ERKSShAb4kxDdBoCCggJWrFhBsa24XOfWa96ClnFdAJg1a1al5SgiIiI1g6kFwIYNGwJw8ODBWzpv8+bNADRv3tzMdERErnL58mVWrFgBQNzwEVgsV/8IPH78OHv37gWgQWgI7Zs3dXeKIiJSyzSvV4/2zZsBzg/FU9allPvcbiXdgPfu3au9tEVEROSGTC0A9u7dG4fDcUvLEHJycvj2228xDIO+ffuamY6IyFUWL15MYWEhUHb5b35BPmvXrgXAx8uLPm2jMbTzn4iIuEGnls1pXLcOAIcOHSp3Ma/LqNGuvWzVDERERERuxNQC4L333gs4NyP+7LPPynXOk08+6Vpu99BDD5mZjojIVUqX/wbXq09U9x5XjaWsS3HtQ9qzdRT+Pj5uz09ERGonA4M+baMJKtkXe9OmTZw6dfOmIKENGtK6Vzzg3AfQ4XBUap4iIiJSfZlaABwzZgzx8fE4HA5+/etf8/rrr193M+OtW7cyevRovvrqKwzDYOTIkfTs2dPMdEREXHJzc1m6dCkAHYcOw1KyZyk4Z1ukp6cD0Cq8Pi3q1/NIjiIiUnv5eHnRPzYGL6sFh8NBcnIymZmZNz2v25g7AThy5Ahbt26t7DRFRESkmjK1AAgwffp0GjVqRHFxMX/+859p0KABzz33nGu8R48eNG7cmO7du7Nw4UIcDgfNmzfniy++MDsVERGX5cuXk5ubC1y9/DcnN4f169cD4O/jQ/eoSI/kJyIiUicggN5towEoLCxk6bKl5Bfk3/CcuOEjsJR0q9cyYBEREbke0wuAzZs3Z/369a6ZgPn5+aSnp7v2J9myZQtnzpzB4XDgcDjo1asXa9eupX79+manIiLiUrr8NyA0lOj4BNfja9espaioCID46Nb4lLyJEhER8YRmYWF0iWgFQPblbFYsX4HNZrvu8YF169KuX3/AuQz4RseKiIhUJwcOHODJJ58kOjqagIAAgoOD6dy5M//7v/97zVnyDoeDL7/8kiFDhhAeHo63tzf16tUjJiaGhx9+mG+//fa610pNTeXxxx+ndevWBAQEUKdOHTp06MBTTz3l2iu+uquUd7rNmzdn7dq1zJkzh0mTJrFy5UrOnz/vGg8KCiIxMZFHH32Ue+65pzJSEBFxKSgoYNGiRQB0GDwUq7c3APv27XPtsdSmcSMa16njqRRFRERcYpo2ISsvj7TTZzh79iwpKSn06dPnusd3HX0Hu5Yv48yZMzc9VkREpDqYOHEiTz75pGuyRkBAAAUFBWzbto1t27YxadIkFi9eTFRUlOucRx99lC+//NL195CQEHJycsjIyGDfvn2sWLHC1bviSi+//DKvvPKKay/dwMBADMNg165d7Nq1i7Vr15Kamlq537AbmD4D8Ep33HEHM2bM4OzZs2RnZ3P8+HEuXbpEVlYWc+bMUfFPRNxi5cqVXL58Gfjv8t+cnBw2b94MQLC/H10iWnosPxERkSsZQI+oSBqGhgKQlpbGjp07rnt8xyHD8Pb1BbQMWEREqr/58+fzi1/8Am9vb1599VVOnTpFTk4Oubm5rFmzhu7du3P48GHGjx+P3W4HYNWqVXz55ZdYLBbefPNNLl26RGZmJnl5eZw5c4bp06czcuTIMtd69913+d///V8cDgePPPII+/btIzs7m4sXL3LhwgWmTp1KQkJCmfOqo0otAF4pICCAJk2aEBIS4q5LiogA/13+6xsYSEzfvgCsX7+e4uJiAHq1aY2XxXrd80VERNzNYhj0a9eWEH9nZ+CtW7Zy5MiRax7rFxRE+0FDAJgzZ45rtoSIiEh1Y7PZeOaZZ3A4HEyZMoU///nPNGrUCAAvLy969+7NokWLaNy4Mdu3b+f7778HYN26dQAMHTqU559/ntCSD9EMw6BBgwbcd999fPrpp1ddKyMjg5deegmAZ555hkmTJhEdHe0aDwsL44EHHuDDDz+s7G/bLdxWABQR8YTi4mIWLlwIQPuBg/H29ePwkcMcP34ccC79baAPJkREpAry8fIisX2sa3/a1atXc/r06Wse223MHQBcvHiRFStWuCtFERERUyUnJ3Po0CGioqK46667rnlMWFiYazbfDz/8AOCabHbu3DnXrMCb+fbbb8nJySEoKIi///3vJmRftVVoD8BXXnnF7Dxc/vrXv1ZabBGpfdauXUtGRgYAccNGUFBQwMYNGwFn19/OrbT0V0REqq5gPz8SY9uxdOcu7HY7y5cvZ8SIEdStW/eq42IHDMQ3MIiCnGxmzZrF0KFDPZSxiIhIxZU23Dh+/Lhr5t+1ZGdnA5Ceng7A4MGD8fHxYcuWLSQmJvKLX/yCQYMG0axZs+vGKJ012K9fP4KDg836FqqsChUAX375ZVdXX7OpACgiZipd/uvt60ts4gA2bdpEfn4+AD1aR+Jt1dJfERGp2sJDgunTNppVe/ZSVFTE0qVLGTlyJIGBga5jvH39iBs+gg0zZzBv3jxycnKuGhcREakOSps0FhQUcObMmZsen5ubC0CbNm346KOPePrpp1m9ejWrV68GoFmzZgwbNozHHnuMviXbQZUqjd+yZe2YFFLhJcAOh+Omf2523I/HRUTMZLfbmTdvHgDt+g/gQmYmaWlpALSoX49mYWGeTE9ERKTcmtcLo0frSMD5Zmfp0qUUFBZedUyPO+9yjZdufyEiIlKd2Gw2AIYPH16uutOV21489thjHD58mAkTJjB+/HgaNmzI8ePH+eyzz+jXrx9PPfWUh76rqqFCMwCXL19+w/EJEyYwc+ZMLBYLw4YNY/DgwbRu3ZrAwEBycnI4ePAgS5cu5YcffsButzN+/HiefvrpCn0DIiLXs2HDBs6ePQtAh6HDSFmfAjj3VOoWFenJ1ERERG5Zm0aNyC0oZNex41y6dInly5cxdMhQrCWz2dvEJxDSoAFZZ88yY8YM7r77bg9nLCIicmsaNmwI/Hdp761q0KABTz/9tKvGtG3bNt58802+/PJLPvzwQ8aMGcOoUaMAXEuMjx49akLmVV+FCoCJiYnXHfvd737HrFmzaNeuHV9//TUdO3a85nHPP/88O3fu5Cc/+QkzZ86kRYsWvPnmmxVJR0TkmkqX/1q9vbE0akz2Qefsvy4RrfD39vZkaiIiIhXSqWUL8goLOXTmLGfPnGXV6tUk9u+PYRhYrFa6jRnL8s/+w/Llyzl37hzh4eGeTllERKTcevfuDcDevXtJS0sjKirqtuLFxcUxefJkUlNT2bFjBytWrHAVABMSEvjiiy9YtWoVly9frvH7AJraBXjx4sW8++67hIWFsWzZsusW/0p16NCBZcuWUbduXd555x2WLFliZjoiUos5HA7X8t+onvHsP3wYgPohwUQ21JshERGpngygZ+soGtetA0D60aNs2LjBNd597DjAuYQqKSnJ/QmKiIjchkGDBtGyZUscDge/+93vbtjRt6ioyNUMpPBH22L8mJ+fH+DcW7DUPffcQ2BgINnZ2bz00ksmZF+1mVoA/OijjzAMg8cff9w1bfNmGjZsyOOPP47D4eDjjz82Mx0RqcVSU1M5fvw4AAFRrbHbnL84ekRFYlA5TYxERETcwWIY9I1pS1hQEAD79u5jx44dADRr34GGUa0BmDFjhsdyFBERqQhvb28++OADLBYLc+bMYfjw4aSkpLgKgXa7nd27d/PGG28QHR1NamoqAL/5zW944IEHSEpKIiMjwxXvwoUL/OUvf2Hjxo0AjBw50jUWFhbG3/72N8C5ld3PfvYzDhw44BrPyMjgs88+4/HHH6/sb9stKrQE+Ho2bdoEQOfOnW/pvC5dugDO/bpERMwwZ84cAAyLFUcD5wcS0Y0bUVcdEUVEpAbwtloZ0L4di7fv4HJePlu3bsXPz482bdrQ/c5xzHvrX2zevJlDhw4RGal9b0VEpPoYNWoUU6ZM4fHHH2fJkiUsWbIEX19fgoKCyMrKoqioyHWsYTgndxQVFfH111/z9ddfAxAcHIxhGGRlZbmO/c1vfsOIESOuutZzzz3H2bNnef3115k0aRKTJk0iKCgILy8vLl26BDiXEdcEps4ALN1s/8opleVRenzp+SIit8PhcLj2/wuNjMQ7IBA/b286tWzh4cxERETM4+ftzcD27fEr2dd2Xco6jh07Rvc77nQd891333kqPRERkQp74IEHOHDgAH/4wx/o3Lkzvr6+XLp0ieDgYOLj43n++edZvXo1ffr0AeAvf/kL77zzDmPHjiU6OhqAvLw8mjZtyvjx45k/fz7vvffeNa/12muvsX79en7605/SsmVLioqKMAyDjh078pvf/KbGrFY1dQZg3bp1OXPmDMnJyTz66KPlPi85ORmAOnXqmJmOiNRSu3fv5nDJnn8hbdoCzsYfPl6m/sgTERHxuCA/XwZ2iGXJ9p0U2WysXLmSIUOGENmtO4c2b2LGjBm8+OKLrhkSIiIi1UXTpk15/fXXef311296bFRUFM8++yzPPvtsha7Vs2dPJk+eXKFzqwtTZwDGx8fjcDiYMmUK69atK9c5KSkpTJkyBcMwiI+PNzMdEamlZs+e7fzCMKjbLpb6IcG0aqDGHyIiUjPVDQykf2wMFsPAZrOxfPlyYocOB+DQoUNs3brVwxmKiIiIp5laAPzVr34FOLuODR8+nI8++uiqtdlXKioq4uOPP2bEiBEUFxcD8OSTT5qZjojUQg6Hw1UADGreEu+g4JLGHyIiIjVXw9BQ+sQ4lzwVFhZy3ssHa8nM92+//daTqYmIiEgVYOp6uOHDh/P4448zceJEcnJy+M1vfsOf/vQn+vTpQ+vWrQkICCA3N5eDBw+yZs0aMjMzcTgcADz++OMMGzbMzHREpBbas2cPBw8eBCAstj2tGzVU4w8REakVmterR4/WkWw8eIhii4W6bWM4v2sn33//Pa+88greJXsFioiISO1j+oZYn3zyCQEBAbz33ns4HA4uXbrE/PnzyxxXWvgzDINnnnmGt99+2+xURKQWSkpKKvnKoH6HDnRU4w8REalF2jRqRH5hETvSjxHSrj3nd+3k/PnzJCcnM2TIEE+nJyIiIh5i6hJgcBb03n33XVauXMm4cePw8fHB4XCU+ePr68tdd93FqlWreOedd7QxsYiYYurUqQAEtWhBl9hY/DXbQUREapkOLZrTplFD6rRpi8XHF9AyYBERkdqu0lpi9unThz59+lBYWMi2bds4efIk2dnZBAUF0bRpUzp16oSPj09lXV5EaqHU1FROnz4NQMOOccQ0aeLhjERERNzPALq3jiSvqIijse25kLqFpKQk/vWvfxEcHOzp9ERERMQDKq0AWMrHx4cePXpU9mVERHj55ZddXw8YMRKrxfRJziIiItWCgUGfttGc7BXPhdQt2Gw2fvnLXzJt2jRPpyYiIiIeoHfHIlIjnD59mrVr1wJQp1UEsW2jPZyRiIiIZ1ktFsbdcQe+ISEALFmyhPfff9/DWYmIiIgnqAAoIjXCn//8Z1dzoe4DB6FdRUVERMDPx4ceQ4a6/v7yyy8zffp0D2YkIiIinqACoIhUe2lpacyePdv1995XvNERERGp7XoNHXbV35999lkWL17soWxERETEE1QAFJFq74033nDN/mvWNoY64eEezkhERKTqaBIZRaOWrQCwGAY2m40nHn+cTZs2eTYxERERcZtKbwIiIlKZtm3bxvfff+/6e7cBAz2XjIiISBVkGAbdhw5j7n8+we5w4GWxkJuXx4MPPsjcuXOJjta+uSIi1d2JvXs8ncJ1VeXcahMVAEWkWnvttdeu+nunfv09lImIiEjV1X3wEOZ99h8cdjuJse1YunMXFy9e5L777mP+/Pk0adLE0ymKiMhtmP6XP3k6BanitARYRKqtNWvWsGzZMtffW7ZrR90GDTyYkYiISNUUUq8ebbt2A2B7+jH+cvddAJw4cYL77ruPixcvejI9ERERqWQqAIpIteRwOPjb3/521WNx/RI9lI2IiEjV16OkGci5rCyiGjXkN8OdTbP27dvHww8/TG5urifTExGRCnA4HNXqj3iOCoAiUi0tXLiwzOblWv4rIiJyfe1798EvIBCA71I28Ps7x3Bf73gANmzYwC9/+UuKi4s9maKIiIhUEhUARaTasdvtvPHGGwBYLc4fYy3axhDWsKEn0xIREanSfHx9iUt0zpb/Ydt2svLyeP3BnzC4Y3sAFi1axAsvvKAZGiIiIjWQCoAiUu3MnTuX3bt3A2Cz2wGI66/lvyIiIjdTugy4oLiYeZu34mW18v4Tj9EtMgKAqVOnlmmwJSIiItWfCoAiUq3Y7Xb+9a9/ARDk6+t6PE7Lf0VERG4qon0H6pV0/J2RsgEAfx8fPnvql7Rp3AiAd955h+nTp3ssRxERETGfCoAiUq3MmTOHPXv2ABDk7w9A87ZtCWvUyJNpiYiIVAuGYdB9iLP5x+ZDhzl89iwAdQIDmfz0k4SHhADw/PPPs2HDBo/lKSIiIuZSAVBEqo0rZ//VDw7i9KVLgGb/iYiI3IoeQ4a5vv4uZaPr6yZhdfn010/g6+VFYWEhP/vZzzh+/LgnUhQRERGTqQAoItXG7Nmz2bt3LwCdW7VyPR7XT/v/iYiIlFdYo0ZEdYoDYOb6DdhL9tMF6BLRin/89EEAzp07x8MPP0x2drZH8hQRERHzqAAoItXClbP/GtUJ5dTFSwA0axNNvcaNPZiZiIhI9VPaDORExkVSDhy8amxcz+78ZoRzfNeuXTz99NNXFQlFRESk+lEBUESqhdmzZ7Nv3z4A7u+TwK6SJUlx/bX8V0RE5FZ16tcfH18/AL5LKbvX34t3jGJ4504AzJs3jzfeeMOt+YmIiIi5VAAUkSrvx7P/vCxW11jn/lr+KyIicqv8AgLo2LcvAPO3ppKTX3DVuMVi4e1Hf0pss6YAvP3228ydO9fteYqIiIg5VAAUkSpvwYIFrtl/Tw0fyqJt2wFo1roN9Ro38WRqIiIi1VbpMuDcgkIWpm4rMx7o58t/nvwFYUGBADzzzDMcOHDArTmKiIiIOVQAFJEqzeFw8M477wAQHhJC77bR7Eg/BjiXL4mIiEjFtI7rTJ364QDMuMYyYICmYWFMePxnWAyD7Oxsfvazn6kpiIiISDWkAqCIVGkrV64kNTUVgCcGD2Tpjp2usTgt/xUREakwi9VKtyFDAFi3/wAnMjKueVzfmLb8vzvHALB//36ee+45HA6H2/IUERGR26cCoIhUaaWz/0L8/Xm4fx/mbNoCQNPWrQlv2tSDmYmIiFR/PYYOB5wz7q83CxDg18OGuJqCJCUl8fHHH7slPxERETGHCoAiUmVt3ryZ1atXA/DogP6cz7rMzmPO7r+dEwd4MDMREZGaoUHz5rSKjQXg27Xrsdvt1zzOMAzefOQhIhs0AODll18mJSXFbXmKiIjI7VEBUESqrHfffRcAP29vHhvYnzmbt7jGOvcf4KGsREREapaew0cCcOzCBdbtP3jd44L9/fn4V48T4OuDzWbjV7/6FRnXWTYsIiIiVYuXpxOQ6sFqtdbIa4m5Sp87M57D3bt3s2DBAgAe7NeH+iEhzN28FYAWMTHUa6Luv25hGJ7OQG6DccV/HXouawY9j9VWVX49dh4wkO8/fJ/C/Hy+XZdC33Ztr3ts26ZN+NsD9/H8F1M4efIkzz33HFOmTMGoYt+TO+ietXoz875VqgY9lyI3pgKglEvdunXdch2r1eq2a0nlCQkJue0YH330EQDeVitPjxrB0QsZ7D1xEoCuAwdhtWoCc6Uz0L9zDWHR81gz6DVZI1TF12NgcBBdBgxk/cIFLNi6jf+z2QgNCLju8Q8l9idlfxrfrF3HggULmDJlCr/97W/dmLHn6Z615jDjvlU8T69JkZtTAVDK5eLFi5UaPyQkBKvVis1mIysrq1KvJZXHarUSEhJCVlYWNputwnGOHj3KtGnTALirVw/qBwUyeXmya7xTv0RstmvvUSS3z2qxlExRAdt19oKS6sHAWWyw2+yoX2f1pddkzVDVX489h49k/cIF5BcV8c2qNTwyoP8Nj//f++5mU1oah86c5fe//z2dOnUiLi7OTdl6ju5Zaw6z7lvFsyr7NamiotQkKgBKubjzl6J+AVd/Npvttp7Hf//739hsNgzD4NdDB2O325mzaTMAER06UKd+fXBUxbdPNZD+nau10mWGDtBzWVPoeay2qvrrsVVsLA2aNefs8WNMX5vCTxP73fD4AF8f3nv8Z9z1j7coKCzk5z//OcuWLSMoKMhNGXue7llrhtu9b5WqQ8+jyI1VvTUIIlKrnT17lqlTpwIwskscUY0asufESdLOnAWgc+JAT6YnIiJSIxmGQc8RIwDYkX6M3cdP3PSc9s2b8dLd4wA4fPgw//M//1OZKYqIiMhtUAFQRKqUiRMnUlBQAMBTw4YAMHeTs/uvYbEQ1+/GS5JERESkYroPGYbF4nx78M3alHKd80hiP4Z37uQ855tvmDt3bqXlJyIiIhWnAqCIVBm5ubl88cUXAMRHt6ZjyxY4HA7mbHYWAKM6diIkLMyDGYqIiNRcIWFhxPaKB2DWho0UFBXd9BzDMHjjofsJDwkG4IUXXuDMmTOVmqeIiIjcOhUARaTKmD59OhkZGQD8csggwLkMKf38BQA6Jw7wVGoiIiK1Qs8RIwG4lJPLD9t2lOucsKAg/u/hBwHIyMjgueeew1EF9zkUERGpzVQAFJEqwW6389FHHwEQ1bABA9vHAjCnZPmvxWKhk5b/ioiIVKp2PXsRXDLbvrzLgAEGd2zPg317A7BkyRK+/PLLSslPREREKkYFQBGpEhYtWsShQ4cAeGLwQCwWCw6Hg3lbtgLQpms3gkJDPZmiiIhIjWe1WukxdBgAq/bu4/iFjHKf++e776JleH0A/vKXv7h+r4uIiIjnqQAoIlXCBx98AEC9oCDG9+oBwJbDRziRcRGALlr+KyIi4hY9hzm7ATscDmasW1/u8wL9fHnr0YexGAa5ubk8/fTT2Gy2ykpTREREboEKgCLicVu3biUlxbnM6JHEfvj5+AD/Xf5r9fKiQ+8+HstPRESkNmnQvDkRHToA8O269djt9nKf2z0qkieHDQFg48aNTJw4sVJyFBERkVujAqCIeNyHH34IgK+3Nz9N7AuAzW53Lf9t2607AcHBHstPRESktulV0gzkeEYGa/cduKVznx09gjaNGwHw97//naNHj5qen4iIiNwaFQBFxKOOHz/O7NmzAbi7Vw/qlRT6Nh5M42xmFqDuvyIiIu4W1y8RX39/AKavXXdL5/p6e/OPhx/AKFkK/MILL6grsIiIiIepACgiHvXJJ5+49gd6fPBA1+NzNjtn/3n5+NAhobdHchMREamtfP396TzA+Xt5Uep2LuXk3NL5XSMj+PnARACSk5OZOnWq6TmKiIhI+akAKCIek5WVxZdffgnA4I7tad2oIQDFNhsLtqQC0K5nL/wCAz2VooiISK1Vugy4oLiYmes33vL5L44dTYv69QD461//yunTp03NT0RERMpPBUAR8ZipU6eSnZ0NwC+GDHI9nrL/IBdKHlf3XxEREc9oGdOOxhERAExdvfaWl/EG+PryxkMPAM4P/f7f//t/WgosIiLiISoAiohH2Gw2V2fA2GZNiW/T2jU2Z7Oz+6+Prx/tevbySH4iIiK1nWEYxI8aA8CBU6fZlHbolmP0iYnm/j4JACxYsID58+ebmqOIiIiUjwqAIuIRS5cu5ciRIwD8bGB/DMMAoMhmY2HqNgBi4+NdG5CLiIiI+3UfPARvX18Avlq1pkIx/jT+TsJDQpxf/+lPrtn/IiIi4j4qAIqIR3z66acA1A0M5M7u3VyPr9qzl0s5uQB0Thx4zXNFRETEPfyDguhcsh3H/C2pt9wMBCA0IIC/3HMXACdPnuRf//qXmSmKiIhIOagAKCJut3//flasWAHAA30T8PPxcY0lbdwMgF9gIO169vREeiIiInKFhNHOZcAFxcV8l7KhQjHGdu9Kn7bRAHz00Ufs3r3btPxERETk5lQAFBG3+89//gOA1WLh4f59XY/nFhTww7btAHTq2w/vKwqDIiIi4hktY9rRODISqFgzEHDuJ/i3B+7Dx8uKzWbj97//PXa73exURURE5DpUABQRt8rKymL69OkADIvrSNOwMNfYku07yS0oBKDrwEHXPF9ERETcyzAMEkaNBuDg6TNsPHjrzUAAIhs24NfDhgCwYcMGpk2bZlqOIiIicmMqAIqIW02dOpXcXOcef48NTLxqbPYm5/Lf4Lp1aR3X2d2piYiIyHV0u6IZyNTVFWsGAvCb4UNpUb8eAK+88goXLlwwJT8RERG5MRUARcRtbDYbEydOBCC2WVN6to5yjV3KyWHFrj0AdE4cgMVq9UiOIiIiUpZ/YBBdBjibc83fksrF7FtvBgLg5+PDq/ffC0BGRgZvvPGGaTmKiIjI9akAKCJus3TpUo4cOQLAowP6YxiGa2zB1m0U2WwAdB042BPpiYiIyA0kjLqiGcj6ijUDARjQPpYRneMAmDx5Mjt37jQlPxEREbk+FQBFxG0+/fRTAOoEBjCuR7erxr7fuAmAeo0b0yImxu25iYiIyI21iIm57WYgpV66exy+Xl7Y7XZeeuml24olIiIiN6cCoIi4xf79+1mxYgUAD/btjd8VHX5PX7rE+gNpAHQZMOiqmYEiIiJSNRiGQe+SWYBpp8+w4WBahWO1qF+PXwxxNvxau3Ytc+bMMSVHERERuTYVAEXELT777DMALIbBw/37XjU2Z9MW1yf/XQep+6+IiEhV1XXwYHx8/QDnLMDb8dTwoTQMDQXg5ZdfJi8v77bzExERkWtTAVBEKl12djbffPMNAEM7daRpWNhV40kbnd1/m0RG0ahlK3enJyIiIuXkHxhE5wEDAFhwG81AAAL9fPnj+LEAHDt2jA8++MCMFEVEROQaVAAUkUo3a9YsLl++DMDD/ftcNXbozFl2pB8DoMvAgW7PTURERG6NWc1AAMb16E7XyFYAvPvuu5w4ceJ20xMREZFrUAFQRCqVw+FwLf9tFR5O35i2V43PLpn9B879/0RERKRqaxETQ5PIKACmrlpzWw08DMPg5XvvBiAvL4+//e1vpuQoIiIiV1MBUEQq1ebNm9m5cycAD/Xvg8Xy3x87DofDtfw3okMHwho29EiOIiIiUn6GYZAwuqQZyJmzrNt/4LbixbVqyb0JvQCYMWMG27Ztu+0cRURE5GoqAIpIpfr8888B8PXy4t74XleN7Uw/xqGzZwHoOnCw23MTERGRiuk2aDC+/v4AfLly9W3He3HsaPy8vQFnQ5DbmVUoIiIiZakAKCKVJiMjg6SkJADGdOtK3aDAq8a/L5n9Z7FYiOvX3+35iYiISMX4BQbSfchQABalbuf0pUu3Fa9RnTo8Mdi5F/Dq1atZvHjx7aYoIiIiV1ABUEQqzbRp0ygoKADgp4l9rxqz2e3M2bQFgOhu3QmqU8fd6YmIiMht6D3G2cHXZrczbfXa247362GDqRcUBMArr7xCcXHxbccUERERJxUARaRS2O12vvjiCwDaN29G51YtrxrfcDCNM5mZAHQdqOYfIiIi1U3jiAgiO3YCYOrqtRTZbLcVL9jfn2dHjwBg3759TJs27bZzFBEREScVAEWkUiQnJ3PkyBEAftq/L4ZhXDVe2vzDy8eHDr37uDs9ERERMUHfsXcCcDYzix9St992vAf79SGyQQMA3njjDXJycm47poiIiKgAKCKVpHT2X7CfH3f26HbVWEFREfO3pALQIaE3fgEBbs5OREREzNChdx+Cw8IAmLxy1W3H87Za+Z+77gDg7NmzfPjhh7cdU0RERFQAFJFKcOLECRYuXAjA3fE9CfD1vWp8xa49ZObmAlr+KyIiUp15eXuTMGo0ACn7D7L/5Knbjjk8rhPdoyIBmDBhAufOnbvtmCIiIrWdCoAiYrpJkyZht9sBeKh/2eW9M9dvBCAgOJiYHj3dmpuIiIiYK37UaCwW59uKL1euvu14hmHwx7ucDUZyc3P597//fdsxRUREajsVAEXEVEVFRUyZMgWA+DatiW7c+KrxzJxclu3cCUDnxIF4eXu7PUcRERExT5364a79fGeu30B2fv5tx+weFcngju0B+Pzzzzlx4sRtxxQREanNVAAUEVMlJSVx+vRpAB7u37fM+LwtWyksdnYJ7D5kiFtzExERkcrR5w5nM5Ds/AJmlcz0v10vjh0DQEFBAW+++aYpMUVERGorFQBFxFSffPIJAPWDgxneuVOZ8dLlv/WaNKFlu1i35iYiIiKVo3XnzjRo3gJwLgN2OBy3HTO2WVPGdu8KwNSpU0lLS7vtmCIiIrWVCoAiYpqjR4+yePFiAO5N6IWPl9dV4+nnL7Ax7RAA3QYNwTAMt+coIiIi5jMMgz53OPft23fyFBsPHjIl7u/GjMJqsWCz2fjHP/5hSkwREZHaSAVAETFN6d5/APf3SSgz/v2GTa6vuw3W8l8REZGapPvQofj4+QEwOXmVKTEjGzbg3oReAMycOZOdJfsIi4iIyK1RAVBETFFcXMzUqVMB6N22Da0ahF817nA4XHsCtYqNJbxpU7fnKCIiIpXHPzDI9QHfgq2pnM3MMiXus6NG4ONlBeCNN94wJaaIiEhtowKgiJhiyZIlnDp1CoAH+/YpM77taDqHzp4FoNvgoW7NTURERNyjdBlwsd3O12vWmRKzSVhdftq/HwCLFi1i40ZzmoyIiIjUJioAiogpJk+eDEBYUOA1m3+Uzv6zennROTHRrbmJiIiIezSJjCKiQwcAvlq1miKbzZS4Tw0fSoCvDwCvvfaaKTFFRERqExUAReS2nTx5kqVLlwJwb+8EfL29rxovstmYs2kLAO169CQwJNTtOYqIiIh79L3jTgBOX8rkh9TtpsSsHxLMzwcOAGD16tWsXr3alLgiIiK1hQqAInLbpk6dit1uB+DhxH5lxlfu3sOF7GwAug3R8l8REZGarFO//oTUqwfA58uTTYv7y6GDCPH3B+Cf//ynaXFFRERqAxUAReS22Gw2vvrqKwB6tI4kuknjMsfMWu/s/usXGEhsr3i35iciIiLuZfXyos8Y516AG9MOsSP9mClxQwMC+Pkg5zYia9euZc2aNabEFRERqQ1UABSR27J8+XKOHz8OwAN9e5cZz8rL44ftOwDo3H8A3j4+bs1PRERE3C9+1GisJVuCfGHiLMCfDxxAsJ8fAP/4xz9MiysiIlLTqQAoIrdlypQpAIT4+zO6a5cy4wu2plJQVARA9yFD3JqbiIiIeEZw3bp0HTAQgNmbNnM+67IpcUMDA/j5oAGAZgGKiIjcChUARaTCzpw5w6JFiwAY17M7/teY3Ve6/Lduw4a0at/BrfmJiIiI5/S98y4ACottTF291rS4jw/SLEAREZFbpQKgiFTY119/TXFxMXDt5b8nMy6ScuAgAN0GDcFi0Y8cERGR2qJ5dDQRJR/+fblyFUU2mylxNQtQRETk1unduIhUiN1udy3/7dyqJbHNmpY5JmnjJhwOBwDd1f1XRESk1uk3zjkL8GxmFgu2pJoW98pZgOoILCIicnMqAIpIhaxevZojR44AcH+fhDLjDoeDmSXLf5u3bUuD5s3dmZ6IiIhUAR379CW0fn0APl9hXjOQ0MAAHivpCLxmzRrNAhQREbkJFQBFpEK+/PJLAAJ9fRnbvVuZ8R3px9h/6hQA3Qdr9p+IiEhtZPXyos8dYwHYcugI244cNS22ZgGKiIiUnwqAInLLLly4wPz58wG4s0c3Av18yxzz7br1gPPGv8vAQW7NT0RERKqO+JGj8fL2BuCLFStNi1snMPCqWYBr15rXaERERKSmUQFQRG7ZN998Q2FhIXDt5h8FRUUkbdwMQGx8AkGhoW7NT0RERKqOoDp16DpoMABzNm3hbGaWabGfGDSQoJIPIt9++23T4oqIiNQ0KgCKyC1xOBxMnjwZgNhmTenYouzefou37yQzNxeAnsOGuzU/ERERqXr63jkOgCKbjWmrzduvLzQwgJ/27wfAihUr2Lp1q2mxRUREahIVAEXklmzYsIGDBw8Cztl/hmGUOWbGuhQAguvWJaZ7D7fmJyIiIlVPs9ZtiOzQEYAvV66hsLjYtNiPDx6Ab8kS43feece0uCIiIjWJCoAickumTp0KgK+3N3f2KNv848ylS6zYtQeAboOHYPXycmt+IiIiUjX1G3cXAOeyspi/JdW0uOEhITzQJwGA+fPns2fPHtNii4iI1BQqAIpIuWVnZ/P9998DMLJLHKEBAWWOmbFuPXaHA4DuQ4e5Mz0RERGpwjr06Uud+uEAfLZsBY6S+wUz/GroYLwszrc27777rmlxRUREagoVAEWk3GbPnk1uyd5+9yXElxl3OBxMX+3swNesTTRNIiLdmp+IiIhUXVarlb7jxgGw7Wg6mw4dNi12k7C6jI/vCcCsWbM4fNi82CIiIjWBCoAiUm6ly3+b1QsjIbp1mfHtR9PZd/IUAD3U/ENERER+JH7kaHx8/QCYuHS5qbGfGj4Ei2Fgt9uZMGGCqbFFRESqOxUARaRc0tLSWL9+PQD3JfTCYin74+Pbdc5xq5cXXQcOdGt+IiIiUvUFBAfTc8QIABalbif93HnTYkc0aMCYbl0A+Prrrzl58qRpsUVERKo7FQBFpFxKZ/8ZhsHd8b3KjOcXFZG0cTMA7RN6ExgS6tb8REREpHroN248hmFgdzj4fHmyqbF/M8K5/3BRURHvv/++qbFFRESqMxUAReSmiouLmT59OgB9Y6JpVi+szDFLt+8ks2R/QC3/FRERkesJb9qU9vHOrr3T16aQlZdnWuyYpk0Y2qkDAF9++SXnzp0zLbaIiEh1pgKgiNzUsmXLOHPmDHDt5h8A35Qs/w2uW5eY7j3clpuIiIhUP4l33wtATkEBX69ZZ2rsp0c6P4jMy8vj448/NjW2iIhIdaUCoIjc1LRp0wAI8fdnWOdOZcbPXMpk5e49AHQfMhSrl5db8xMREZHqJbJjR5q1bgPAF8uTKbbZTIvduVVL+sa0BeCzzz4jMzPTtNgiIiLVlQqAInJD58+fZ9GiRQCM69kdP2/vMsfM2rARu8MBQM/hI9yan4iIiFQ/hmGQePc9AJzIuMjC1G2mxn96pHMvwMuXL/P555+bGltERKQ6UgFQRG5oxowZFBUVAXBf77LLfx0Oh2v5b7M20TSJjHRrfiIiIlI9xfVPJLR+fQA+XbIcR8mHiWaIb9OaLq1aAvDJJ5+Qn59vWmwREZHqSAVAEbkuh8PhWv7brmkTOjRvVuaYzYcOk3bauT+gZv+JiIhIeXl5e9N37DgAUo8cZfOhw6bFNgyDXw8fAsC5c+dczcxERERqKxUAReS6tm3bxu7duwHn7D/DMMocU7pxt5ePD10HDXZrfiIiIlK9xY8ajY+vHwATl60wNfawTh2JatgAgPfffx+bifsMioiIVDcqAIrIdU2dOhUAb6uVcT27lxm/nJfH3M1bAYjr15+A4GC35iciIiLVW2BICD2GO7v2Lty6jfTzF0yLbbFY+OVQ54eThw8fZu7cuabFFhERqW5UABSRa8rLy+O7774DYGhcR8KCgsocM3fzVvIKCwHoNWKkW/MTERGRmqH/XeMxDAO7w8EXy5NNjX1Xz+40DA0FYMKECabuMygiIlKdqAAoItc0f/58srKyALgvoWzzD/jv8t/6TZoS1SnObbmJiIhIzRHetBmx8QkATF+7jqy8PNNi+3p78/NBAwDn1iarVq0yLbaIiEh1ogKgiFxT6fLfRnVC6R8bU2Z874mTpB45Cjhn/11rf0ARERGR8ki8+x4AsvMLmF7yAaNZHurXmxB/f8A5C1BERKQ2UgFQRMpIT09n5cqVANwd3wurpeyPitKbc4vFQo+hw9yan4iIiNQsUR070bR1awA+X55MsYkNO4L9/Xm4fx8AVqxYwbZt20yLLSIiUl2oACgiZXz99deur+9L6FVmPL+oiJkbNgLQrlc8IfXquS03ERERqXkMwyBxvHMW4ImMiyxMNbdI99jAAfh6eQHOjsAiIiK1jQqAInIVu93OtGnTAOjVJopWDcLLHPND6nYu5eQCEK/mHyIiImKCzokDXB8qfrx4makNOxqEhnB3fE8AkpKSOHLkiGmxRUREqgMVAEXkKqtWreL48ePA9Zt/TF+bAkBIWD1iepadISgiIiJyq7y8vel/190AbD+aTsqBg6bG/+XQQc5uw3Y7H3zwgamxRUREqjoVAEXkKqXNPwJ9fRnVtXOZ8fTzF1i9dx8APYYNw2q1ujM9ERERqcESRo/GNyAAgI8XLzU1dkSDBozsEgfAtGnTOHfunKnxRUREqjIVAEXE5dKlS8ybNw+AO7p3JcDXt8wx35TM/gPoOVzLf0VERMQ8/oFBJIwaA8DynbvZd+KkqfGfHDYEgPz8fP7zn/+YGltERKQqUwFQRFxmzZpFQUEBAPdeo/mHzW7n23XOAmDruM6EN23q1vxERESk5ut/13gsJSsMPlmyzNTYnVq2oHfbaAA+++wzsrOzTY0vIiJSVakAKCIupct/oxo2oFtkRJnx5N17OH0pE4Beav4hIiIilaBOeDhdBw4CIGnjZk5fumRq/CeHDQacKx+mTJliamwREZGqSgVAEQFg165dpKamAnBf73gMwyhzzNdr1gHgHxREx7793JmeiIiI1CID7r0PgCKbjc+WJZsau1+7GNo3bwbAhx9+SGFhoanxRUREqiIVAEUEcG6GDWC1WLirV48y42cuZbJk+04Aug4ajM819gcUERERMUOTiEhievQEYOqqNWTl5ZkW2zAMfj3UOQvw5MmTzJw507TYIiIiVZUKgCJCYWEh3377LQAD28fSMDS0zDFfr12HzW4HIGH0GLfmJyIiIrXPwJJZgJfz85m6aq2psUd17UzzevUAeO+997CX3OOIiIjUVCoAigiLFi0iIyMDcC7//bFim41pq5033hHtO9AkItKt+YmIiEjt0zquM83aOBt2fL58BYXFxabF9rJa+eVQ5z6D+/btY8mSJabFFhERqYpUABQRV/OP+sHBDOrYvsz4il27OXXxEqDZfyIiIuIehmEw6L6fAHD6UiazN242Nf69Cb0ICwoEYMKECabGFhERqWq8PJ2AO2VmZjJjxgw2bNjAhQsX8PX1JSoqilGjRhEfX3bWU3kVFxczd+5ckpOTOXnyJABNmzYlMTGR0aNH4+V143/mQ4cOMWvWLHbs2EFWVhahoaF06NCB8ePHExFRthMrwIULF1i5ciUHDhwgPT2dS5cukZOTg7+/P82aNaNXr16MHDmSgICACn9fUjucOnWKZcuWAXBXrx54W61ljpmyag0AAcHBxPVPdGt+IiIiUnt17NuPsEaNyTh9io8XL+Pu+J7XbFRWEf4+PvxsYCJvzZlPSkoKGzdupEePsvsgi4iI1AS1ZgZgeno6Tz/9NElJSZw6dQqr1UpOTg6pqam89tprfPrppxWKm5eXxx/+8Ac+++wz0tLSsNls2Gw2Dh48yMSJE/nTn/5Efn7+dc9PTk7mxRdfJDk5mYyMDHx9fblw4QLJycm88MILrFq16prn7dq1i88//5zVq1eTnp5Obm4ufn5+ZGdns3fvXiZNmsTTTz9Nenp6hb4vqT2mT5/u2vfmvoReZcaPXbjAil17AOg5fATePj5uzU9ERERqL6vVSuLd9wCw/9Qplu/abWr8R/r3w7/k3ua9994zNbaIiEhVUitmABYVFfG3v/2NzMxMWrZsyfPPP09ERAQFBQUkJSXx1VdfMWfOHCIiIhgyZMgtxf7ggw/Yv38/gYGB/Pa3v3XNJExJSeHf//43e/fu5cMPP+R3v/tdmXPT09N59913KS4upm/fvjzxxBOEhYWRkZHBp59+ypo1a3jnnXeIiIigWbNmV50bHh7O/fffT/v27YmIiCAkJASAgoICUlJSmDhxIufPn+f111/nvffew3qNWV0iDofD1f23S6uWRDdpXOaYaavX4XA4AIgfNdqt+YmIiIj0HDacRZO/IPfyZT5evJRBHcpuV1JRdYMCub9PAp8vT2bBggUcOHCANm3amBZfRESkqqgVMwAXLVrE6dOn8fX15a9//atrWa2vry/33XcfI0eOBGDKlCkU38LmwocPH2blypUAPPPMMyQkJGAYBoZhkJCQwNNPPw3AihUrOHr0aJnzv/rqK4qLi4mIiOCFF14gLCwMgLCwMF588UUiIiIoKiriq6++KnNuu3btePDBB4mLi3MV/0q/p8TERJ5//nkATpw4wb59+8r9PUntkpKSwqFDhwC49xrNPwqLi/lm7ToA2nTpSoNmzd2an4iIiIivvz997xwHQMr+g2w/au4KlycGD8RqseBwOHj//fdNjS0iIlJV1IoC4IoVKwDo378/4eHhZcbvvvtuDMMgIyODHTt2lDtucnIyDoeDxo0bk5CQUGa8d+/eNG7cGIfDQXJy8lVjOTk5bNy4EYBx48aVmaFntVoZN24cABs2bCA3N7fceQFER0e7vr5w4cItnSu1R+nsP19vb+7o3rXM+OJtOziXdRmA3mr+ISIiIh7Sd+w4vEqW6n68eKmpsZvVC3PdB3377becPn3a1PgiIiJVQY0vAObl5XHgwAEAunYtW+AA53La0iW227ZtK3fs7du3A9ClS5drbkZsGAZdunS56thSu3fvds02vF5epY8XFRWxZ8+ecucFXHV8o0aNbulcqR2ys7NJSkoCYFSXOEL8/cscU9r8IzgsjA69+7g1PxEREZFSQXXq0HPYcADmb0nl6Llzpsb/9dDBABQWFvLJJ5+YGltERKQqqPEFwOPHj7v2L2vZsuV1jysdO3bsWLniOhwOjh8/ftO4LVq0uGbc0r/XqVOH0NDQa54bGhrqGitPM4/i4mLOnTvHwoULefvttwGIiYnRPiZyTbNnz3bNLL03oezy37TTZ1i7bz8AvYaPxHqTbtYiIiIilSnx7nsxLBbsDgcfL15maux2zZqSGNsOgC+++IKsrCxT44uIiHhajX9Hn5GR4fq6dI+9aykdu3jxYrni5uXlubr7liduXl4eeXl5+JfMsiq9zo3OLR3PzMy8YV7PPvsshw8fLvN4ly5dXHsBivzY1KlTAeeyl4To1mXHV68FnDNZ1fxDREREPC28aVPi+vUnNXkF365L4dnRI2h4nQ/SK+LJ4UNI3r2Hy5cvM2nSJJ555hnTYouIiHhajS8AlhbpwNkg43pKx/Ly8soV98rjyhO39JzSAmDp+Tc6t7x5hYSEUKdOHQoLC10zurp168ajjz563dmFPzZlyhRXQehaHnjgAR588MFyxaoIi8Xi+m/dunUr7TritH//ftavXw/A/X17u/6/LJVXWMh3KRsAaNezF+FNmtxSfKulxk8urjXUQbxm0Guy5tBrsvrT6/H2DH3gIVKTV1BYbOOLFav46313mxY7sUN7Oke0IvXwET799FP+53/+p8y9uu5Za47SLZxCQ0NdK8ak+tFrUqT8anwBsDZ49dVXXV9nZWWxcuVKpk2bxnPPPccTTzzBmDE3b96Qk5PD2bNnrzuem5vrljcdhmHozY0bfPnll4Dz3/v+vn3K7GE5b/MWLubkANBn7Fgou8Xljd3q8VI16XmsOfRc1gx6HmsGPY+3pVl0G9r17MmeDRuYtCKZZ8eMpE5goCmxDcPg6ZHDeeKDjzl16hTTpk3j8ccfv+6xumetGSwqytcIek2K3FyNLwD6+fm5vi4oKCAgIOCaxxUUFACUmQl1PVceV3rujeL++JzSr290bkXyCgkJYcyYMbRr144XXniB//znP7Rr146oqKgbnhcYGEiDBg2uOx4QEIDNZitXDhVhsVgwDAOHw4Hdbq+06wjYbDYmTZoEQN+YtjSrF1bmU88vljm7Vtdp0IDYHr3gVj4UNbi146Vq0vNYc+i5rBn0PNYMeh5NMeSBh9izYQM5+QV8vnQFz90xyrTYI7t2JqJBAw6fPcs///lPHnnkkasKRLpnrTkMw8BisWC32zUDsBqr7NekiopSk9T4AuCVe+xlZGRctwBYuldgeacN+/v74+/vT15e3lX7DF4vbunxP87rRudWJK9SUVFRxMbGsnPnTpYsWXLTAuDDDz/Mww8/fN3x8+fPl3t/xIqoW7cuVqsVu91eqdcRWLJkCSdPngTgnvieZYrQO9KPsSntEAAJI0fjgPIXfw0Dq9WCzW4H3UhVW1fe6FRm4V/cQK/JGkGvyRpCr0fTtIptT6vY9hzZvYtPFi/hZwP64e/jY1r8XwwZyJ+mTmffvn1MmzaNUaP+W2DUPWvNYbVaqVu3LpmZmfrZWo1V9muyfv36pscU8ZQaP9+5WbNmruWNN+qkWzrWvHnzcsU1DINmzZpVOG7p3y9dunTdLmOZmZlkZmYC/+0mfCvq1asHwOnTp2/5XKm5pk2bBkCIvz8jOncqMz5pxUoArN7eav4hIiIiVY5hGAz+yf0AZGTn8PWadabGvzu+J/WDgwGYMGGCZoeJiEiNUOMLgP7+/rRp0waALVu2XPOY8+fPc+zYMQDi4uLKHbtTJ2fxZOvWrdc9JjU19apjS8XGxuLl5XXDvErjent7065du3LnVaq08HflMmip3TIyMli4cCEAY7t3xe9Hn5ZnZGcze+NmALokDiBYG+mKiIhIFdSuVzyNWkUA8OmSZRSZOIPLz9ubxwYmArBp0yZSUlJMiy0iIuIpNb4ACDBgwAAAVq5cyblz58qMz5w5E4fDQVhYGB07dix33P79+2MYBidPnmTdurKfPK5du5aTJ09iGIYrh1IBAQH06NEDgKSkpDLTzm02G0lJSQD07NmzzNLlm01T37lzJ/v37wegffv25f6epGb77rvvKCwsBODe3vFlxqevWUdBcTEAfcaOc2dqIiIiIuVmsVhcswBPZFx0fYBplp/270tgSQfg9957z9TYIiIinlArCoDDhw+nUaNG5Ofn8+qrr3L48GHA2WBjxowZzJs3D3Dug1c6K6/UE088wdixY3nnnXfKxI2IiKB///6Ac3lASkoKDocDh8NBSkqK62ZhwIAB11zC+9BDD+Hl5UVaWhpvvfWWa8+Cixcv8tZbb5GWloa3tzcPPfRQmXP/8Ic/8M0335Cenn5VMTAjI4NZs2bx6quv4nA4CA8PZ/DgwRX4V5OaaOrUqQBEN25MXMur/58sttn4cuVqAFq0jaFlTIzb8xMREREpr84DBhLWsBEAHyxabGoDgNDAAB7o2xuAH374gb1795oWW0RExBNqfBMQcC6h/fOf/8xLL73EkSNHePbZZwkICCA/P991ozBmzBiGDBlyy7GfeuopTp06xf79+3nttdfwKVlSWTrLKiYmhieffPKa57Zo0YJnn32Wd999l1WrVrF69WoCAgLIyckBwMvLi2effda11+CVLl68yJQpU5gyZQpWq5WAgACKi4vJy8tzHdO0aVNeeumlcncQlppt+/bt7Ny5E4B7e/dy7Y1ZaumOXZzIcBah+945zt3piYiIiNwSq9XKwHvv47v3/s3B02dYsmMnw+LK7m9cUY8PGsAXy5Mpttt57733NBNQRESqtVpRAARnsW3ChAl89913bNiwgfPnzxMYGEhkZCSjR48mPr7scsjy8Pf354033mDu3LkkJye7uqtGRUUxYMAARo8eXWZW4ZUSExNp3rw5M2fOZOfOnWRlZbmWIo8fP56IiIhrnvfcc8+xefNmdu/ezblz51yNROrXr09kZCTx8fEkJibi7e1doe9Lap7S5h9eFgt39exeZvyLkuYfQaF16Nw/0a25iYiIiFREj+EjWDRlMtmXLvHBwsUM7dSxzIecFdUkrC7jenZnRsoGvvvuO/70pz9RV/sji4hINWU41NZKyuH8+fOVGr+0fbvNZquU9u21XUFBAR07duTixYsMj+vEJ79+4qrx/adOMfSV1wEY8sBDjHrs5xW7kGFgtVqw2eygHy3VltVqBQNw3Hy/Uani9JqsEfSarCH0eqw0S7+exrzP/gPAtOeepnfbaNNi7z95iqGvOu+RnnzySSZMmKB71hrCarVSt25dLl68qJ+t1Vhlv4+sX7++6TFFPKVW7AEoUtstXLjQ9Qvx3oReZcYnrVgFODfU7j3mDrfmJiIiInI7et9xB34BgYBzL0AzRTdpzOCOzoZ6kydPVtFPRESqLRUARWqB0uYf4SHBDOgQe9VYVl4eM9dvAKBjn77UCQ93e34iIiIiFeUfGETvO8YCsGrPPnYcTTc1/q+HOvcJz8nJ4aOPPjI1toiIiLuoAChSw508eZIVK1YAcFfPHnhbrVeNz1i3ntwCZ9OaPmr+ISIiItVQ4vjxeJU043vf5FmAPVpH0iWiFQATJkwgPz/f1PgiIiLuoAKgSA03ffp0V7fre3tfvfzXbrczOdm5/LdxRARRHc3rnCciIiLiLsF1w+g1fAQAC1O3s//UKdNiG4bBk8OcswDPnj3L5MmTTYstIiLiLioAitRgDofD1f23S6uWRDdufNX48l27OXz2HAB9x44zrWueiIiIiLsNvO9+LFYrDoeD9xeaOwtwaKcORDVsAMA///lPNY0QEZFqRwVAkRosJSWFw4cPA3Bf7/gy458uWQ5AYEgI3YYMdWtuIiIiImYKa9iQ7iX3M7M3buZIyYecZrBYLPxy6GAADh48SFJSkmmxRURE3EEFQJEarHT2n5+3N2O6d71qbNex46zbfwCA3mPG4uPr6/b8RERERMw0+P4HMSwW7A6H6R2B7+rZnYahoQD84x//wOFwmBpfRESkMqkAKFJDZWdnuz6dHtkljhB//6vGP1u2AgCrlxd9SjrniYiIiFRn4U2b0mXAQAC+S9nA8QsZpsX29fbmF8OcswA3bdrE2rVrTYstIiJS2VQAFKmhZs+eTW5uLgD3Jly9/PdsZhazN20GoMuAgYTUq+f2/EREREQqw5AHHsQwDIrtdj76YYmpsR9J7E+Qnx8A//73v02NLSIiUplUABSpoaZOnQpAs3phJES3vmrsy5WrKCx2bl6dePc9bs9NREREpLI0atmKTn37AfDN2hTOXMo0LXZIgD+PDuwPwLJly9i1a5dpsUVERCqTCoAiNVBaWhrr168H4N74Xlgs/32p5xcWMmXlagCi4uJoGtX6mjFEREREqqshDz4EQEFxMR8vWWpq7F8OHYK31QrAe++9Z2psERGRyqICoEgNVNr8wzAM7knoddXYrA2byMjOAWDAeM3+ExERkZqnaVRr2scnAPDVyjWcz7psWuxGdetwT8n2KrNmzSI9Pd202CIiIpVFBUCRGsZmszF9+nQA+rSNplm9MNeYw+Hgs2XJgHOT7Ha94q8ZQ0RERKS6G/LgwwDkFxUxcdlyU2M/NXIYhmFgs9k0C1BERKoFFQBFapjly5dz+vRpAO790ey/VXv2sv/UKQD63TX+qqXBIiIiIjVJy5gY2nbrDsCkFau4lJNjWuw2jRsxsksc4Nx3ufTeS0REpKrSu3+RGqa0+UeIvz8jOne6auw/S52ffvsHBdFj6HC35yYiIiLiTkNL9gLMKSjg8+XJpsb+zYihABQUFPDhhx+aGltERMRsKgCK1CAXLlxg4cKFAIzt3hU/Hx/X2L4TJ0nevReA+FGj8fX390iOIiIiIu4S2bETUZ2cM/U+W5bM5bw802J3aN6cgR1iAfjiiy+4cOGCabFFRETMpgKgSA3y7bffUlRUBMBP+iRcNfbx4mUAWL286HfnXW7PTURERMQTSmcBZuXlMTl5lamxnxnpXFGRm5vLJ598YmpsERERM6kAKFJDOBwOpkyZAkBss6Z0bNHcNXYy4yJJGzcB0HXQYOqEh3skRxERERF3a9OlKy1i2gHO7VByCwpMi90tMoKE6DbO2P/5D1lZWabFFhERMZMKgCI1xKZNm9i3bx/gnP1nGIZr7D/LllNstwMw8N77PJKfiIiIiCcYhsGwh5wdgTOyc5iyao2p8UtnAWZlZTFx4kRTY4uIiJhFBUCRGuKrr74CwNfLi7t6dHc9npmTy7TVawFoH59Ao5atPJGeiIiIiMe069mLpq1bA/DxD0tNnQXYu20bukS0csb++GNyTOw2LCIiYhYVAEVqgOzsbGbNmgXAyK6dCQ0McI1NXrmK3IJCAAbe9xOP5CciIiLiSYZhMPynjwJw/vJlvly52tTYz4wcBjgbsn355ZemxRYRETGLCoAiNcCsWbPIzc0F4Ce9412P5xcW8sXylQC0im1PZIeOHslPRERExNPaxyfQrLVzvz6zZwEO6tCe2GZNAXj//fcpMDG2iIiIGVQAFKkBSpf/tgyvT3yb1q7HZ6Rs4PzlywAM0uw/ERERqcWcswAfAeBCdjaTk82dBfj0COcswNOnT/P111+bFltERMQMKgCKVHO7d+9m8+bNgHP2n8XifFnb7HY+WbIMgAbNWxAbn+CxHEVERESqgtj4BJq1iQbg48VLyMk3b6beiC5xRDVsAMC///1vioqKTIstIiJyu1QAFKnmSmf/WS0W7onv5Xp84dZtHD13HnB2/i0tDIqIiIjUVlfOAszIzuHLlatMi221WPhNySzA9PR0vv32W9Nii4iI3C5VBESqsYKCAtfN5aAOsTSsEwqAw+Hgwx+WABBSrx7dBg32WI4iIiIiVUlsr3iat20LwMeLl5o6C/DOHt1oGV4fgLfeekuzAEVEpMpQAVCkGps/fz4XL14E4P4+/13iu2bffnakHwOg/1134+Xj45H8RERERKqaKzsCZ2TnMCl5pWmxvaxWfjtyOABHjx7lm2++MS22iIjI7VABUKQaK13+2yA0hAHtY12PT5i/CAD/oCASRo/2SG4iIiIiVVW7Hj1p0TYGgE8WLyM7P9+02ON6dqdVeDgAb7/9tmYBiohIlaACoEg1dfToUZKTkwG4N74XXlYrABsOpJFy4CAA/cbdhX9gkMdyFBEREamKrtwL8GJODpNWmDwLcNR/ZwGqI7CIiFQFKgCKVFNTp051fX1f73jX1+8tdM7+8/X3p9+4u9yel4iIiEh1ENOjJy1i2gHwyZJlXM7LMy32nT26EdHgv7MACwsLTYstIiJSESoAilRDNpuNadOmAZAQ3YZWJTeY244cJXn3XgB63zGWwJBQj+UoIiIiUpVdOQvwUk4uk1aY1xH4ylmAx44dY/r06abFFhERqQgVAEWqoWXLlnHq1Cng6uYf7y38AQBvX18G3H2PR3ITERERqS5iuvegZbvKmQU4tns3Ihs0AJwdgTULUEREPEkFQJFqqLT5R2hAACO6xAGw5/gJfti2A4D4UaMJrhvmsfxEREREqgPDMBjx058BkJmby+fLTd4LcLRzFuDx48ddqzdEREQ8QQVAkWrmzJkzLFrk3OdvXM/u+Hl7A/+d/Wf19mbgPfd5LD8RERGR6iS6WzdaxcYC8OmSZWSZPAswqqFzFqD2AhQREU9SAVCkmvnmm28oLi4G/rv89+DpM8zbkgpAz2HDqRMe7qn0RERERKoV516AjwKQlZfHxKXLTYtttVj47agRAJw4cYIvv/zStNgiIiK3QgVAkWrEbrczefJkADq1bEFss6YAfLBwMQ6HA4vFwqD77vdkiiIiIiLVTnTXbkR27ATAp0uWk5GdbVrsO7p3JbpxYwDefPNNcnJyTIstIiJSXioAilQjq1at4siRIwA82Lc3AOnnzvP9xk0AdBs8hHolN5giIiIiUj6GYTDqsZ8DkFNQwIeLlpgW22qx8Ps7RwNw7tw5PvnkE9Nii4iIlJcKgCLVyKRJkwAI8vNlbPduAPx7wSJsdjuGYTD4/gc9mZ6IiIhItRXZoSMx3XsAMCl5FWcuZZoWe2injnSJaAXAe++9x8WLF02LLSIiUh4qAIpUE2fOnGHBggUAjOvZg0A/Xw6fPct3KRsA6DJwEA2aN/dkiiIiIiLV2sifOWcBFhQV8e8Fi0yLaxgG/zPuDgCysrKYMGGCabFFRETKQwVAkWpi6tSpruYfD/XrA8A78xZiL9n7b/hPH/FkeiIiIiLVXvPoaDr17QfA16vXkn7+gmmxE6Lb0L9dDACffvopp06dMi22iIjIzagAKFIN2O12pkyZAkCXiFbENmvK/lOnSNq4GYDuQ4cR3rSZJ1MUERERqRFGPPozDMOg2G7n3XkLTI39/+4cA0B+fj5vvvmmqbFFRERuRAVAkWpg+fLlpKenA/+d/ffuvIXOzr9WK0MffNiT6YmIiIjUGI1atqLb4CEAzFy/kQOnTpsWu2PLFozu2hmAKVOmkJaWZlpsERGRG1EBUKQamDx5MgAh/v6M6daFPcdPMHfzVgB6Dh+hzr8iIiIiJhr+00ewWK3YHQ7emjvf1Ngv3DEaq8WCzWbj//7v/0yNLSIicj0qAIpUcadOnWLRIucm1HfH98Tfx4e3S5ajWL29GfrgQ55MT0RERKTGqde4CfEjRwMwf0sqO9KPmRY7qlFD7usdD8CsWbPYvn27abFFRESuRwVAkSruq6++wmazAfBgv97sSD/GolTnjWL8yFHUbdDQk+mJiIiI1EhDH3oILx8fAP41e56psZ8dNRxfb28AXn75ZRwOh6nxRUREfkwFQJEqzGazuZp/9IiKJLpxY94uWYbi5e3NkAce9GR6IiIiIjVWaL369B17JwArdu1mY9oh02I3rluXxwclArBq1SoWL15sWmwREZFrUQFQpApbunQpJ06cAODBfn3YevgIS3fsAqD3mLGE1qvvyfREREREarRBP3kAX39/AP6ZNMfUmXpPDR9KvaAgwDkLsKioyLTYIiIiP6YCoEgVNmnSJADqBAYwsksc//f9HAC8fX0ZfP/9nkxNREREpMYLCg0l8e57AFh/II1lJR/EmiHY35/n7xgFwIEDB1xN30RERCqDCoAiVdTx48dZsmQJAPfE92LDwTTW7T8AQOL4uwmuG+bJ9ERERERqhQF330tgaCgAf5sxE5vdblrs+/sk0KZxIwD++c9/kpmZaVpsERGRK6kAKFJFTZkyBXvJDeb9fRJ4Y9ZsAAKCgxl43088mZqIiIhIreEXGMjQBx8GYM/xE8xYm2JabC+rlT/fPQ6ACxcu8M4775gWW0RE5EoqAIpUQcXFxXz11VcAxEe3Ztex4+w+7twLcMgDD+EfGOTJ9ERERERqld6jxxDWqDEA/zcriXwT9+sb0D6W/u1iAPjkk084evSoabFFRERKqQAoUgX98MMPnD59GoD7eyfwr9nzAKgT3oA+Jd3oRERERMQ9vHx8GPXYzwE4kXGRz5YuNzX+S3ePw2IYFBYW8vLLL5saW0REBFQAFKmSPvvsMwDqBQVxITubYxcuADDi0Ufx9vHxZGoiIiIitVLnxAE0j44G4N/zFpCZk2ta7JimTbi/TwIAc+fOJTk52bTYIiIioAKgSJVz4MAB103f+PiefLBwMQCNWrai++ChnkxNREREpNayWCzc8YtfAXApJ5f3Fy02Nf7v7xxDaEAAAH/84x8pLCw0Nb6IiNRuKgCKVDGls/8shoHNbuNCdjYAo3/+OBar1ZOpiYiIiNRqbbt2I6Z7DwC+WJ7MiYwM02KHBQXx+7GjAecHwp9++qlpsUVERFQAFKlCsrOzmT59OgD9Y2OYvsbZZS6iQwdi4xM8mZqIiIiIAHf88pcYhkFBcTFvz11gauwH+/UhtllTAP75z3+69oQWERG5XSoAilQh3377LZcvXwbA2+pFTkEBAGMed95oioiIiIhnNWvdhm6DhwAwI2UDe0+cNC221WLh1fvvBSAnJ0cNQURExDQqAIpUEQ6Hw7X8t3n9eizbuQuADgm9iWjf3pOpiYiIiMgVRj32c6ze3jgcDt74frapsbtHRXJPfE8AvvvuO9asWWNqfBERqZ1UABSpItauXcvevXsB8PP2xma3Y7FaGfOLX3o4MxERERG5Ur1Gjel7x1gAlu/czbr9B0yN/4e7xhLs5wc4G4IUFRWZGl9ERGofFQBFqoiJEycC4OvtzYFTzv1e+o4dR4NmzT2ZloiIiIhcw5AHH8IvMBCA12YmYbfbTYsdHhLC83eMAmDPnj289957psUWEZHaSQVAkSrg1KlTzJ8/H3DO/gMICA5m2MM/9WRaIiIiInIdgSGhDP7JAwBsP5rO9xs3mxr/kcR+dGzh/CD4zTffJC0tzdT4IiJSu6gAKFIFTJo0CZvNBkBmbi4Aw3/6KAHBwZ5MS0RERERuoN9d46nboAEA/0iaQ15hoWmxvaxW/u/hB7BaLBQUFPD888+bOstQRERqFxUARTyssLCQyZMnA/9/e/cdXmV5/3H8fXIySMJK2DOEvUTR4kAFRFpFVJwoAuICrXXiqLt1a7Vuq1XrxmrFQUWroK0oikVRBCrKlBV2QgLZ4/z+wOQHMgzkJAdO3q/r4jLJM+7vIX55cj55nvve8oMeQNM2bel7/AmRLEuSJEm/ID4hgePPHwPAqqyNPPXhv8N6/h5tWjN20EBgy3zR48ePD+v5JUm1hwGgFGGTJk1i3bp1AJT8dBfgiWMvJBgbG8myJEmSVAkHDDiKdt27A/DEBx+yZmN2WM9/xZBjSWvSGIA//vGPrF69OqznlyTVDgaAUoSVL/5RrvOBB9Ht4EMiVI0kSZJ2RyAQYOiFFwOQX1TEff+cFNbz14mP5+6zzgQgJyeHG264IaznlyTVDgaAUgTNmTOHGTNmVHweiIlh6IW/JRAIRLAqSZIk7Y60bt048KijAZjwxQzmLFse1vMf3rUzpx+25RfE77zzDv/85z/Den5JUvQzAJQi6Omnn97m80MHH0eL9PQIVSNJkqQ9NeT884mNjycUCnH7hDcJhUJhPf9Np55Ek/r1AbjmmmtYs2ZNWM8vSYpuBoBShKxbt44JEyZUfJ5Urx7HnXteBCuSJEnSnkpp2owBp54OwH8XLOL9WbPDev6GycncO3I4AJmZmYwbNy7sIaMkKXoZAEoR8sILL1BcXFzx+XHnnk9y/QYRrEiSJElVcfSZw6mXmgrA3W9NpHCrn/XCcv79ejD8iL4ATJ48mZdffjms55ckRS8DQCkCCgsLt3n8t03nLhw6+LgIViRJkqSqSkhM5LhztjzRsXTdel6Y+mnYx7jp1JNo06gRADfffDM//vhj2MeQJEUfA0ApAt5++20yMzO3fBIIcMollxETDEa2KEmSJFVZn1//hlYdOgLwyLvvsy4nJ6znr1unDg+MHkkgECA3N5dLL72U0tLSsI4hSYo+BoBSDQuFQvz5z3+u+PyQY48lrWvXCFYkSZKkcIkJBhn624sB2FRQwL1vvxP2MQ7u1IELfz0QgC+++ILHHnss7GNIkqKLAaBUwz755BOWLFkCQEJyMkPOGxPhiiRJkhROHXvtT++jtgR0r0//LzMXLwn7GOOOP46urVoCcPfddzNjxoywjyFJih4GgFINu/HGGys+HnzOedRt4MIfkiRJ0eaEMWOJr1MHgD+8NoHSsrKwnj8hLo5Hzx9NYnw8paWljB07lqysrLCOIUmKHgaAUg36/PPP+eGHHwBIbduWI44/IcIVSZIkqTo0bNyEX48YCcCcZct57bPpYR+jc4sW3H7m6QCsXLmSyy67jFAoFPZxJEn7PgNAqYaEQiEuueSSnz4LcOqll7vwhyRJUhTrf/KpNGndGoA/TZzExtzcsI9x2qEHc8ohfQB4//33+etf/xr2MSRJ+z4DQKmGvPrqqyxfvhyA9COPpNv+B0S2IEmSJFWr2Ph4Tvrt7wDIys3l/n++G/YxAoEAd5w5jA7NmgJw66238sUXX4R9HEnSvs0AUKoBGzdu5Prrrwcgrl59hl4wNsIVSZIkqSZ063MwPQ/rC8D4Tz9j7k+/EA6n5DoJPH7BudSJi6OkpITzzjuPjIyMsI8jSdp3GQBKNeCPf/wjuT898tHt5FNp06JFhCuSJElSTRl60cXExsVRFgpxy6sTqmWevm6tW3HfqLMAWLduHeeeey6FhYVhH0eStG8yAJSq2eeff8748eMBaNi1G/1/cwyBCNckSZKkmtOoRQsGnjEcgJmLl/DWjC+rZZwT+xzE2EEDAfj666/5/e9/76IgkiTAAFCqVoWFhVx11VUAxMQn0OXEk0lr0jjCVUmSJKmmDTzjTFKaNQPgrjcnkp2XVy3j/P6kEzi8S2cAxo8fz9NPP10t40iS9i0GgFI1euSRR1i4cCEArY/+Nft370ZMwPv/JEmSapv4hAROuuhiANblbOJPb79TLePEBoM8fsG5tG6UCsDNN9/MBx98UC1jSZL2HQaAUjWZN28eDz74IADJrdrQ8uBD6fDTb30lSZJU++x3+BH0KF8QZNrnfL14SbWMk1I3med+dyH1ExMpKytj7NixfPvtt9UyliRp32AAKFWD4uJiLr30UoqLiwnEBEk7/kS6tGpJXDAY6dIkSZIUQaf87hLi69QhFApxwyuvUVxaWi3jdG7RgifGnkdsTAx5eXmMGDGClStXVstYkqS9nwGgVA0effTRit+ytug3gLrNW9C5pSv/SpIk1XYpTZtx7NmjAZi3MoNn//1xtY11RNcu3DXiDADWrFnDmWeeSWZmZrWNJ0naexkASmE2b9487r//fgCSWrSk+eFHkt60CYnx8RGuTJIkSXuDI08+lZbtOwDw4KR/sWJD9YVyZ/Q9jN8d+xsAvv/+e4YPH87mzZurbTxJ0t7JAFAKo60f/Y0JxtLuxJOJCQbp2rpVpEuTJEnSXiIYDHL6FeMIBALkFxVxy2uvEwqFqm28a04cwvAjtsw9+PXXXzN69GgKCgqqbTxJ0t7HAFAKo60f/W3Z/yiSmjWnVWoKDRITI1yZJEmS9iZpXbvS9/gTAPhozv94f9bsahsrEAhw5/BhDDnwAAA++eQTLrzwQoqLi6ttTEnS3sUAUAqTrR/9bdy+A00POxyA7t79J0mSpB047rzzqZeaCsAfXptATn5+tY0VjInhoXPPpn/3rgC89957jB071hBQkmoJA0ApDLZ+9DcYF0frIScSEwzSqF5dY6sb0AAARCJJREFUGtevH+nyJEmStBdKTK7Lyb/9HQBrsrO5682J1TpefGwsT449n0M6bZl/cNKkSYwZM4aioqJqHVeSFHmxkS5A+4ZgMBiVY4XLvffeW/Ho70FnDKcsZctvcnu2aUMgEIhkaTUqsNV/Q7XodUc1v4/7NHsyCvl93GfZj1EoTN/H/fsPoOd//s3czz/j79M+58RfHcjhXbuE5dw7klynDs//7rec+/iTfLFgIe+++y5jxozh2WefJb4WLVpX/p5jX3zvoR3zeyntWiBUnbPNSrXA559/zpFHHklZWRntDuhN69OHU1BYSEpyMsf/6sD//4lfkiRJ2oHs9eu5+9zR5Ofm0rZJYz6+/Q8kJyRU65i5hYWMeugxPvv+BwCOOeYYJkyYQN26dat1XElSZBgAqlKysrKq9fz169cnGAxSWlpKTk5OtY4VTps2baJfv34sXbqU+MREhj3yF75fvgKAI7p2oW2TxhGusGYFgJhgDGWlZfgPy74rGBPz0y0qUFpWFulyVAX2ZHSwJ6OD/RgdqrMf//v+v3jtz/cBcN7AAfxx2KlhPf+O5BcVcf5fnmLaTyHggQceyKuvvkrjxtH/M2wwGKR+/frk5ORQWloa6XK0h6r7fWRKSkrYzylFio8Aq1Jq8qK4L12Ar7vuOpYuXQrAyTfczIqsjQDUT0ykTeNUqGX5evkjTSGoda89avl93KfZk1HI7+M+y36MQmH+Ph78m2P45j//Zv7XM3nuP1MZcuAB/KpD+7CO8XN14uL428VjueK5F/nXN9/y9ddfM3jwYF5//XXatGlTrWPvLUpLS/ep9x/aOb+P0q65CIi0h9555x3+/ve/A9Dz6F/TrM8hbN68GYAebVoT8NlfSZIkVVIgEGDYFeOIr1OHUCjEtS//nYIaWKG3Tlwcj19wLiOPPByARYsWceyxx/L1119X+9iSpJpjACjtgdWrV3PVVVcBUK9xE4bfeQ9z584FIDkhgbRa9uivJEmSqi61eXOGnD8GgEWr1/DIu+/XyLjBmBjuGD6McccPBmDt2rUMHTqUt956q0bGlyRVPwNAaTeVlZVx6aWXVsyLeNY9f2L95k0Vc070aNOaGFf3kyRJ0h44/IQTSe/ZE4Anp3zEtz8urZFxA4EAlw8ZzJ/PHkF8bJCCggLGjh3LPffcQ5nzj0rSPs8AUNpNTz75JB9//DEAR4wYRff+RzFnzhwAkhLiSW/aJILVSZIkaV8WExPDGeOuJi4hgdKyMq58/iXyi4pqbPzTDjuEV664lEY/rQb85z//mZEjR5KZmVljNUiSws8AUNoNM2fO5PbbbwegWYeOnHTdjaxYsYKNPy3+0a1Vqy2rw0mSJEl7qGnrNhxf/ijwmrXc+/Y7NTp+nw7tmXjdVXRt1RKAKVOmcPTRRzNz5swarUOSFD4mFVIlbdy4kTFjxlBSUkJcQgLnPvoX4hMTmT17NrBlAuWOzZtFuEpJkiRFg8NPHErn3gcC8Nx/pjJt3g81On6bRo1465orOeWQPgCsWLGCE044gaeeeoqQK1lL0j7HAFCqhFAoxBVXXMHy5csBOPWWW2nZuQvLly9nw4YNAHRt1dK7/yRJkhQWMTExnHHVNdRJTgbg6pfGk52XV6M1JCUk8MDokdw7cjgJcXEUFxdz4403cvbZZ7N27doarUWSVDWmFVIlPPvss7z77rsAHHTCiRw27ExCoRCzZs0Cttz917ll8whWKEmSpGiT0rQpp15yGQCrsjbyh9cm1HgNgUCAMw8/jLevHVcx1/X7779Pv379eOedmn00WZK05wwApV8we/ZsbrnlFgCapLVj2G13EQgEWLZsWcVKwN3btCI2JhjJMiVJkhSFDhx4NPsf2Q+At2Z8xbtffxOROrq3bsU7113NsL6HArBhwwbOO+88Lr74YrKzsyNSkySp8gwApV3YvHkzF1xwAUVFRQTj4jnn4cdIrFePUCjEt99+C0BifDydmnv3nyRJksIvEAhw6mVXUC81FYAbX/kHazZGJnCrl5jIfaPO4m+/HUOT+vUAeP311zn88MP55z//6dyAkrQXMwCUdiIUCnHZZZexZMkSAE6+/kba9NwPgB9//JGNGzcC0KONK/9KkiSp+tRt0IAzxl0NQFZuLlc8/xKlZWURq2dQr/2YfPP1DDnwAADWrFnD+eefz4gRI1i2bFnE6pIk7ZyphbQTf/nLXyrmNdn/mMEcOWo0AGWhsoq7/5IS4unQzJV/JUmSVL26H3wIh584FIDPf5jPEx98GNF6UuvW5fELzuUvY86laYP6AEyZMoUjjzySRx99lKKioojWJ0nalgGgtAPTpk3jtttuA6BZhw6MuPd+AoEAAEsWLyEnJweAnm3aePefJEmSasSJYy+iRfv2ADww6T2+WrQ4ovUEAgGGHNibj/5wI6MH9CMQCJCXl8dtt93GkUceyfvvv+9jwZK0lzC5kH4mIyODMWPGUFZWRkJyMuc//lfq1K0LQFlZGd/O3nL3X3JCAu2bNY1kqZIkSapF4uLjOfuGm4lPqENpWRmXPfsC2bl5kS6L+omJ3HbGabx97Th6tGkNwOLFixk1ahSnnXYa//vf/yJcoSTJAFDaSlFREeeffz7r168H4Ky776N5x04V2xcsWMDmTZsB6Nm2DTE/3RUoSZIk1YRmbdtyyiWXArAyM4vfj//7XnOX3QHt0njnuqu5d+RwGtfbskjIJ598wsCBA7nqqqtYvXp1hCuUpNrLAFDays0338xXX30FwMDzx9D7uCEV24qLiyvm/qufmEh60yYRqVGSJEm1W5/fHEPvowYC8K9vvmX8p59FuKL/F4yJ4czDD+PjW2/i4mMGER8bpKysjBdffJGDDz6Y22+/vWIxPUlSzTEAlH7y6quv8uyzzwLQ8eBDOeGa67bZPm/ePAoKCgA4ID3Nu/8kSZIUEYFAgNMvu4JGLVoAcNuEt5i3YmWEq9pWvcREfn/SiXz0h5sqVgvOz8/nkUce4aCDDuLBBx8kNzc3skVKUi1iACgBX331FVdddRUA9Zs25ZyHHyUYG1uxvaCggLlz5wLQuF49WqWmRqROSZIkCaBOcjKjbriJmGCQwuJiLnrqWbLzIj8f4M+1bdyIv4w5j3/+/iqO7NYFgJycHO666y769OnD008/TWFhYYSrlKToZwCoWi8jI4Ozzz6boqIiYuMTuOAvT1G/ybaLe8yePZuSkhIAeqen4b1/kiRJirS2Xbpy4tiLAPhx3TqufnE8ZWVlEa5qx/Zvl8bLl/2Ov19xCb3bpQGwbt06brjhBg455BBeeukliouLI1ylJEUvA0DVanl5eYwaNYp169YBMPyue2h3QO9t9tm0aRPz588HoFVqCk3q16/xOiVJkqQdOfKkkyvmA5z87RyenPJRhCvatb5dOvPWteN4+qIL6PzTI8wrV65k3Lhx9O3bl9dee43S0tIIVylJ0ccAULVWKBTi8ssvZ/bs2QAcPfYi+px0ynb7zZo1q+I3qQf89NtKSZIkaW8QCAQYdsU4mqVt+Tn1vomTmPb9DxGuatcCgQC/2b8X79/0ex4+9+yKxfV+/PFHLrnkEo444gjeeuutvfZuRknaFxkAqtZ68MEHefvttwHocdRATrjq2u322bBhA0uWLAGgfbOmNEhKqskSJUmSpF+UkJjIOTf/kYTERMpCIS772wusysqKdFm/KBgTw0kH/4oPb7mB+88eQetGW+bZXrhwIWPHjuWoo47i3XffJRQKRbhSSdr3GQCqVnrvvfe4++67AWjWoSNnP/AIMcHgdvt9+dWXAMTExLBf2zY1WqMkSZJUWc3atuXMq64BYMPmzVz4179RUFQU4aoqJzYY5PTDDuE/f7yJu846gxYpDQH47rvvOOeccxg0aBBTpkwxCJSkKjAAVK3zzTffcNFFWyZLTmrQgLF//RuJ9eptt9/SpUtZu2YtAN1atSQ5IaFG65QkSZJ2x/79+jPgtGEAfLt0Gb8f/+o+FZrFx8Yy4sjD+fjWm/nj6afSpP6Wn9Fnz57NWWedxXHHHcfUqVP3qdckSXsLA0DVKsuWLWPEiBHk5+cTjIvjvMeepEm7dtvtV1paysyZMwGoEx9H99atarhSSZIkafcdf/4FdP1VHwDenvEVT07+MMIV7b46cXGcO7A/n97+B244ZSipdZMB+OqrrzjttNM46aSTmD59eoSrlKR9iwGgao3s7GyGDx++1Yq/99L5sL473Pe7ed+xefNmYMvCH3E7eDxYkiRJ2tvEBIOMuuEmmrbeMn3NvRMn8dGcuRGuas8kxsdz4a+P5tPb/8A1Jx5P/cREAD7//HNOPPFETj/99Ipf2kuSds0AULVCUVER55xzDvPnzwdg8GVXcvDJp+5w3/z8fObMngNAat26FauSSZIkSfuCxLp1Oe+220msW5dQKMRlz77A/FWrIl3WHqtbpw6XDP4N0+74A5cfdyx162yZmufjjz/m2GOPZcSIEcyePTvCVUrS3s0AUFEvFAoxbtw4pk2bBsDBJ5/KsZdevtP9v/nmG0pKSgA4qH06AQI1UqckSZIULk1bt+HsG24mEBPD5oJCzv/LU6zP2RTpsqqkQVIS4044jmm3/5Hf/mYQifHxAEyePJmjjz6ac889l++//z7CVUrS3skAUFHv/vvv57XXXgOg06GHcead9xAI7DjU27BhAwsXLgQgrUnjiomHJUmSpH1Nl1/9iqEXbln8btn6DZz/xFPk7yMrA+9KSt1krjv5RD69/RbOP3oACbGxAEyaNIl+/fpx4YUXsmjRoghXKUl7FwNARbXnn3+eP/3pTwA069CB8x//K7E//abw50KhEDNmzAAgJiaGA9ql1VidkiRJUnU48qRTOGLoSQDM+nEplz37AqVlZZEtKkya1K/PLaedwie338KofkcQFwwSCoV488036du3L5deeilLly6NdJmStFcwAFTUeuedd7j22msBqN+0KRf97QWSGjTY6f4LFy2sWCCkR+uWJCck1EidkiRJUnUJBAKcdNHF9Php8bvJ387hj/94g1AoFOHKwqd5w4bcMXwYH996M2cefhjBmBjKysp49dVXOfTQQ7nmmmsqfs6XpNrKAFBRadq0aVx00UWEQiES69fn4udeotFPK6HtSGFhIV/P/BrYMslw99ata6pUSZIkqVrFBIOMuv5G2nbpCsCLUz/l6Y/+E+Gqwq91o1TuHTmcf//hRk45pA8xgQAlJSU8//zzHHLIITzxxBMURcEj0JK0JwwAFXVmz57NqFGjKCoqIi4hgbFPPUvLn37Y2Zmvv/6awsJCAH7VIZ1gjK0hSZKk6BFfpw7n33YHqc1bAHDnG2/z5n9nRLiq6tGuaRMePGcUU265geMOPACATZs2ccstt9CvXz8mT54cVXdASlJlmHIoqixevJgzzzyTzZs3ExMMcs7Dj9PhV312ecy6detYsGABAG0apdIyJaUmSpUkSZJqVL2UFMbeeTfJ9esDcPWLrzD529kRrqr6dGzejCfGnMc/xl1G99atAFi0aBEjRoxg2LBhzJs3L8IVSlLNMQBUVFm1ahWbc3MBOOOOu9lv0K93uX9ZqIwvvvgCgNhgDAe2T6/2GiVJkqRIadqmDWPuvJuExERKy8q45Jnn+fyH+ZEuq1od0qkjk66/hntGnElq3WQAPvroI3r16sWNN97I5s2bI1yhJFW/QMh7n1UJ69evr9bzp6SkEAwGKS0tJSsrq0rn+tv0GXz55Zf0H33uL+47b948vvzySwB6p6fRrVWrKo1d6wUCBIMxlJaWgf+07LOCwSAEgBCUlpZGuhxVhT0ZFezJKGE/RoVo6seF387iqRuuo6S4mOSEBF654hIOaJcW6bKqXXZeHo+89wHP/2cqJT+thtyiRQvuuusuhgwZQiAQiHCF2h3hfB+5I40bNw77OaVI8Q5ARZ0OvfavVPiXm5vLN998A0CDpCS6tGxZ3aVJkiRJe4WO+x/A6JtuISYmhtzCQkY/9gTfr8yIdFnVrkFSEjefdjJTbrmBAT26A1ueIjr33HMZOXIky5Yti3CFklQ9DABVa02fPp2SkhIADu7Ynhh/2ydJkqRapMdhfRl+ze8JBAJszM1j+EOP8kMtCAEBOjRvxqtXXc5jF5xDk5/mRJw8eTJHHnkkjz76KMXFxRGuUJLCywBQtdKiRYvIyNjyw03nFs0rLvqSJElSbXLQ0YM49dLLAcjcnMuZDz1aK+4EBAgEApz4q4P46A83MKrfEQQCAfLy8rjtttsYNGhQxVRBkhQNDABV6+Tl51VczJMTEti/Fsx1IkmSJO1M3+NP4LTLrgC2hIDDH3qUeStWRraoGtQgKYk7hg/j7WvHVawW/N133zFkyBBuvvlm8vLyIlyhJFWdAaBqnRn/nUFRUREAB3fqQFwwGOGKJEmSpMjqe/wJnH75lUB5CPhYrQoBAQ5ol8Y7113NzaedTFJCPKFQiCeffJIBAwbw+eefR7o8SaoSA0DVKj/++GPFxL4dmjWlRcOGkS1IkiRJ2kscNuT4ihAwKzeXYQ88wszFSyJcVc2KDQa54Oij+OCm6+nbpTMAS5YsYejQoVx//fXk5uZGuEJJ2jMGgKo1CgoKmDFjBgCJ8fH0Tm8X2YIkSZKkvcxhQ45n2JXjCAQC5OTnM+Lhx5n63bxIl1Xj2jZuxCuX/467zzqDunUSAHjmmWfo378/06ZNi3B1krT7DABVa0yfPp2CggIA+nRsT3xsbIQrkiRJkvY+hw4ewqgbbiIYG0t+URHn/+Up3vnq60iXVeMCgQBnHXk4k2++nn7dugKwdOlSTj75ZK699lrvBpS0TzEAVK2wYMECli9fDkD7Zk1pnZoa4YokSZKkvdcB/Qdw/m13EJ9Qh+LSUi599gVemvpppMuKiFapqbx46W/506jh1E9MBOC5555j4MCBzJw5M8LVSVLlGAAq6uXk5FSs+lu3TgIHtU+PcEWSJEnS3q/rr/pw0Z/uI7FePUKhEDe9+jp3vvE2ZWVlkS6txgUCAc7oexhTbrme/t233A24ePFihgwZwp/+9CeKi4sjXKEk7ZoBoKJaWVkZn376KSUlJQAc1qWzq/5KkiRJldSuW3cu/fNDNGzcBICnPvw3Fz31LHmFhRGuLDKaN2zIC5f8ltvPPJ06cXGUlpZy3333cdxxx7Fw4cJIlydJO2UAqKj27exv2bBhAwA927amSb16Ea5IkiRJ2rc0b9eOyx99jNYdOwHwwbezOf3PD7NmY3aEK4uMQCDA2f2P5L0brmX/tLYAzJo1i4EDB/LMM88QCoUiXKEkbc8AUFFrzdo1zJkzB4BG9erSs02bCFckSZIk7ZsaNGrM7/78ID0P6wvA3OUrOPHe+5n149IIVxY5HZo3441rruTKIYMJxsSQn5/P9ddfz7Bhw1i1alWky5OkbRgAKioVFBTw6SefQghigzH07dKJmEAg0mVJkiRJ+6yExETOueWPDDhtGACrN2Zz+p8f4pVPP6u1d73FBYNccfxg3rrmSto3bQrAxx9/TL9+/Zg4cWKEq5Ok/2cAqKgTCoWYNm0aeXl5APTp0IF6dRIjXJUkSZK074sJBjlx7IWcMe5qYuPiKCop5fpXXuOal16hoKgo0uVFzP7t0njvxmsZPaAfABs3buSCCy7gd7/7HZs2bYpwdZJkAKgo9PHH/yEjIwOADs2akt60SYQrkiRJkqLLIccO5tIHHyGlWTMAXp/+X065/yGWrlsX4coiJzE+ntvOOI0XL/0tTerXB+Af//gHAwYM4IsvvohwdZJqOwNARZVp06bx4YcfAtAwOYlfdWgf4YokSZKk6NSmc2fGPf4EXX7VB4D/LV/B4Dv/xOvT/1trHwkG6N+9G5Nvvo5jDugFwLJlyxg6dCh33XUXxcXFEa5OUm1lAKioEggESE5MJDYYwxFduxCM8X9xSZIkqbok12/AmNvv5DcjRxEIBMgtLOTqF8fzu2eeIzs3L9LlRUxq3br8dez5/GnUcJIS4ikrK+PBBx/kuOOOY+HChZEuT1ItFAjV5l/NqNLWr19fredPSUkhGAxSWlpKVlZWlc719n9nsCCvkOYNG4SpOlVaIEAwGENpaRn4T8s+KxgMQgAIQWlpaaTLUVXYk1HBnowS9mNUsB93bdHs2bzyp7vJWrsWgBYpDbn/7BEc0bVLhCvbXiAQICEhgcLCwmq/W3HpunVc/txLfLPkRwASExO57bbbGD16NAEXKqyScL6P3JHGjRuH/ZxSpHh7lKJO3aQkwz9JkiSphnXo1Yurn3ya3kcNBGBV1kZGPPw417z0Sq2+GzCtSRMmXHU5444fTDAmhvz8fK655hpGjhzJulo8Z6KkmmUAKEmSJEkKi8S6dRl1/Y2cde111ElOBuAfn3/B0bfdybszv6m1cwPGBoNcPmQwb1x9Be2abFmkcPLkyfTv35/JkydHuDpJtYEBoCRJkiQprH416Ndc98xz9DriSADW5Wzi4mee4/wnnmLJT48I10a909vx3g3XcubhhwGwbt06RowYwTXXXENubm6Eq5MUzZwDUJWyL80B+OGcuawqKQtTZdotzm8UFZzfKIrYk1HBnowS9mNUsB/3zJzPpvHGY4+Qs2EDAHHBIOcc1Z9LB/+GBklJEampJucA3JkPZs3m9y//nayfgr8OHTrw5JNPcsABB0Sknn2RcwBKlecdgJIkSZKkarPf4Ufw+2ee5YihJxETE0NxaSlPf/hvBvzhdl6a+inFtTRMPeaAXnxw83X0794NgEWLFjF48GAeeOABA2ZJYecdgKoU7wBUpXh3Q1Tw7oYoYk9GBXsyStiPUcF+rLrVP/7IxL8+wQ8zv6r4WtvGjbh08DGcfEgf4oLBGqljb7gDsFwoFOLFqZ9y55sTKSwuBuDggw/mL3/5C2lpadU2bllZGTk5OWRlZZGdnU1WVhYbN25k8+bNlJSUUFxcXPGnrKyMhIQE4uPjSUhIICEhgYYNG9KwYUNSU1NJSUkhNTWVmJiavcfIOwClyjMAVKUYAKpSfHMTFXxzE0XsyahgT0YJ+zEq2I/hEQqFmPflDP755BOsXbG84utpTRpz6eBjOOngX1V7ELg3BYDl5q9axeXPvsh3K1YCULduXe655x6GDRtGIBDY7fOVlZWxcuVKFi1axKJFi1ixYgUZGRkVf1atWkXxT4FjOMTFxdGyZUtatWpF69atSUtLo1OnTnTp0oUOHTqQkJAQtrHKGQBKlWcAqEoxAFSl+OYmKvjmJorYk1HBnowS9mNUsB/Dq7S0lJkfTWHK+JfZsGpVxddbpDTk7P5HMvzwvqTUTa6WsffGABCgqKSEB955jyenfFRR14knnsj9999PSkrKDo8JhUIsXbqUOXPmMGfOHBYsWMDixYtZvHgxBQUFYakrEBNDqGzP32PFxMTQrl07br/9dn7zm9+EpSYwAJR2hwGgKsUAUJXim5uo4JubKGJPRgV7MkrYj1HBfqwepSUlzPzoQyaPf5nM1f8fBNaJi+OUQ/pwdv8j6da6VVjH3FsDwHJfzF/AuBdeZmXmlvdGzZs357HHHuPwww9n/vz5FWHfnDlzmDt3Ljk5Ob94zjp165HSogUNmrcgpUULGjZvQf0mTUhq0JCkBg0q/iQk1yUYF7flT2wsMcEggUCA0pISSoqKKCkqoriggPycHHI3ZpGXvZHNmZlkr11L1soVZK3KIHPlSjJXrqD0Z3cYvvLGG/y6X7+w/T0ZAEqVZwCoSjEAVKX45iYq+OYmitiTUcGejBL2Y1SwH6tXaUkJ3376CZ+8+QbLfvh+m2092rTmtEMPZmifg2hUr16Vx9rbA0CA1Rs3cs1Lr/DJd///d1H+nmlngnFxNGvfgabp7Wmank6T9PY0bZdO0/T2JO/kDsLqUlpczPrly1i9cAGrFy5g1fz5PPqne+ncJHyhmgGgVHkGgKoUA0BVim9uooJvbqKIPRkV7MkoYT9GBfux5vw47zs+efMNZn/6CWVbPXoaGxNDv+7d+M3++zGoV0+a1K+/R+ff2wLAjbm5/G/5SuYuX87/lq/gf8tXsHjNWsp2UVtCcjKtunWndfceFX+ad+xEbHx8DVa+ewYmJ9AsNnzzOxoASpUXG+kCJEmSJEnaWrtu3Wl3Y3dyNmxg5r8/4sspk1n94xJKysr499z/8e+5/yPwSoAD2qUxaL+eHN61Mz3btqmxVYT3VFlZGUvXr+e7FSuZtyKD71asYN6KDDJ+IbxKbtiQxGbNiW3chKTmLajbshV9+g9gv169anzlXUn7Ju8AVKV4B6AqxbsbooJ3N0QRezIq2JNRwn6MCvZj5IRCIVYuXMCXH05h7mfTyFq7drt9khLiOah9Ogd37Mj+7drSrVUrmjbY8R2C1X0HYElpKSs2ZLJozVoWrVnD4jVr+SEjgx9WriK3sHCXx6Y2b0Grjh1p3aEjrTpu+VM/tREEYN6KDGYvXVZxZ2BKSgp9+/alUaNGYX8N1cE7AKXIMQBUpRgAqlJ8cxMVfHMTRezJqGBPRgn7MSrYj3uHUChExuLF/G/658yd/jkrFszf6b6N69WjW+uWdGzenNaNUmnTqBGtG6XSKjWVJikNKSku3u0AsKysjJz8fDbm5rEuJ4eVmVlkZGWR8dN/l63fwNJ16ygq2fX/I8G4OJqnpdGyfQdatu9Aqw4daNWhI4l16+7yuI15eXwxfyGZmzdv+UIAevTowf77709scO9+yM8AUIocA0BVigGgKsU3N1HBNzdRxJ6MCvZklLAfo4L9uHfanJ3N4jlzWDTnWxbPmU3GokWVCvUCgQD1ExNJSU6mQVIicbGxxAWDxAWDxAaDlJaVUlhSQnFJKUUlJeQWFJKVm0t2Xt4u5+bbkYaNm9C0TRtadtgS9rXs0IFmbdoSjN2zwK4sFOKHjAy+Xbq8Yo7EevXq0bdvX5o1a7ZH56wJBoBS5BgAqlIMAFUpvrmJCr65iSL2ZFSwJ6OE/RgV7Md9Q0FeHquWLCFj8aKKP+szMsjNzq62MQOBAPVSU0lp2pSUps1o2qYNTVq3odlP/01ITKyWcTcVFPDfBQtZm51T8bXOnTvT+8ADSdgLFwMxAJQiZ+++P1iSJEmSpN1QJymJ9B49SO/RY5uvF+bnk7l6NZlrVpO9YQMFuZvZnJ1NXk4O+Zs3U1pSTGlJKaUlJZSWlBATDBIbF1fxJz4xkeT69UmqV4+kevVJrl+f5IYNSWnSlAaNGxMbF1fjr7VenTocvV8PFq5eyzdLllBSWsb8+fNZtmwZBx10EB06dKjxmiTtnQwAJUmSJElRLyExkRbp6bRIT4+qu3IDBOjUvBmtUhvy5cLFrMzMoqCggM8++4wFCxZwyCGHkJKSEukyJUWY64VLkiRJkrSPS4pPoH/3bvTv3o3khAQA1q5dy6RJk/jyyy8pLi6OcIWSIskAUJIkSZKkKNEqNYXjD+pNz7atiQkECIVCzJs3j7feeosFCxbs9qrHkqKDAaAkSZIkSVEkGBNDr7ZtGXLQATRv2BCAgoICpk+fzjuT3iEjIyOyBUqqcQaAkiRJkiRFoXp1EjmqZ3eO7NaFunXqALAxayMffvghH374IRs3boxsgZJqjAGgJEmSJElRKgC0adSIIQf15qD26cTHblkLNCMjg3++80+mT59Obm5uZIuUVO1cBViSJEmSpCgXDATo0rIF6U2bMHf5CuZnrKIsFGLBggUsWrSITp06sV+v/UhKTIp0qZKqgQGgJEmSJEm1RHxsLAemt6NTi+Z8++Mylq1fT1lZGT/88AMLFy6kc5fO9OzRk8TExEiXKimMDAAlSZIkSapl6tWpwxFdO5OV24o5y5azYkMmpaWlzPtuHvN/mE/Hjh3p3qM79erWi3SpksLAAFCSJEmSpFoqJTmZft26krl5M7OXLicjK4vS0lJ++OEH5s+fT7t27ejRowepqamRLlVSFRgASpIkSZJUy6XWrcuAHt3YsHkz/1u+ghUbMgmFQixZsoQlS5bQsmVLunbtSqtWrQgEApEuV9JuMgCUJEmSJEkANKpbl37dupKTn8+8FStZsnYdZaEQGRkZZGRkULdeXbp07kLHjh1JSEiIdLmSKskAUJIkSZIkbaN+YiKHdOpIr7S2fJ+RwaLVaykqKWHzps3MnDmTWbNm0S69HR07dqRZ02aRLlfSLzAAlCRJkiRJO5QYH0/vdu3Yr21blq5bx/yM1WTl5lJaWsqihYtYtHARdevVpWOHjrRv3566detGumRJO2AAKEmSJEmSdik2JoYOzZrRvlkzNmzaxPyMVSzbkElZWRmbN21m1qxZzJo1i2bNmpGenk6btm1IrJMY6bIl/cQAUJIkSZIkVUoAaFyvHo271ONXpaUsW7eexWvWsn7TJgDWrFnDmjVr+OK/X9CsaTPS0tJom9aWpMSkyBYu1XIGgJIkSZIkabfFB4N0bN6Mjs2bkZOfz5K161i6bh2bCwoh9P9h4IwZM2jcuDEJLZpyyoB+kS5bqpVqVQCYnZ3NhAkTmDFjBhs2bCAhIYEOHTpw3HHHceihh+7xeUtKSpg0aRJTp04lIyMDgFatWtG/f3+GDBlCbOyu/5oXL17MW2+9xZw5c8jJyaFBgwb07NmTU045hfT09GodW5IkSZKkqqqfmMj+aW3pldaWrNxclq/fwLL169mUXwDA+vXrKUmtH+EqpdorEAqFQpEuoiYsW7aMG2+8kezsbAASExMpLCykrKwMgBNOOIExY8bs9nnz8/O5+eabmT9/PgDx8fEAFBUVAdC1a1duu+026tSps8Pjp06dysMPP0xJSQkAycnJ5ObmAhAbG8uVV17JkUceWS1j747169dX+Ry7kpKSQjAYpLS0lKysrCqd68M5c1lVUhamyrRbAgGCwRhKS8ugdvzTEpWCweCWZztCUFpaGulyVBX2ZFSwJ6OE/RgV7McoYk/WiBCQnZfH8vUbWJWVxa1HHUn7tLSwnT+c7yN3pHHjxmE/pxQpteL2sOLiYu644w6ys7NJS0tj3LhxpKenU1hYyMSJExk/fjzvvPMO6enpDBo0aLfO/Ze//IX58+eTnJzMZZddVnEn4RdffMEjjzzC999/zxNPPMGVV1653bHLli2rCP+OOOIILrjgAlJTU8nMzOTpp5/ms88+46GHHiI9PZ3WrVuHdWxJkiRJkqpTAGiYlETDtkns17YNiYkuCiJFSkykC6gJH3zwAatXryYhIYFbbrml4rHahIQEhg0bxuDBgwF4+eWXK+7Eq4wlS5bwySefAHDppZdy2GGHEQgECAQCHHbYYVxyySUAfPzxxyxdunS748ePH09JSQnp6elcddVVpKamApCamsrVV19Neno6xcXFjB8/PuxjS5IkSZIkqXaoFQHgxx9/DEC/fv1o0qTJdttPPfVUAoEAmZmZzJkzp9LnnTp1KqFQiBYtWnDYYYdtt71v3760aNGCUCjE1KlTt9mWm5vLl19+CcBJJ5205XGCrQSDQU466SQAZsyYQV5eXtjGliRJkiRJUu0R9QFgfn4+CxYsAODAAw/c4T5NmjSpeMT222+/rfS5Z8+eDUDv3r0JBALbbQ8EAvTu3Xubfct99913FXcb7qyu8q8XFxczb968sI0tSZIkSZKk2iPqA8AVK1ZQvs5J2i4mGy3ftnz58kqdNxQKsWLFil88b9u2bXd43vLPGzZsSIMGDXZ4bIMGDSq2LVu2LGxjS5IkSZIkqfaI+gAwMzOz4uPyOfZ2pHxbZVcOys/Pp6CgoNLnzc/PJz8/v+Lr5ePs6tid1VXVsSVJkiRJklR7RP0qwOVBGWxZ9GNnyrdVNijber/KnLf8mPJVj8qP39WxO6urqmPvyMsvv8wrr7yy0+3Dhw/nrLPO2mWtVRETE1Px35SUlCqdKy01haTcvF/eUdUgQCAAW266DUW6GO0xv4/Rw+9ldPD7GB38PkYHv4/Rw+9lJDRt3LjK7/e2Fs73kVK0i/oAUJWTm5vL2rVrd7o9Ly9vu4VKqkMgEKjyOIftv3+YqpEkSZIk7e3C8T5SinZRHwDWqVOn4uPCwkKSkpJ2uF9hYSHALu+S29rW+5Ufu6vz/vyY8o93dezO6qrq2DuSnJxM06ZNd7o9KSmJ0tLSXZ6jKmJiYggEAoRCIcrKyqptHFWvQCBATEwMZWVlFXNvat9jP0YPezI62JPRwX6MDvZj9LAno0N196ShoqJJ1AeAW8+Rl5mZudMAsHyuwMreNpyYmEhiYiL5+fnbzDO4s/OW7//zunZ17M7qqurYOzJy5EhGjhy50+3r16+v9PyIeyIlJYVgMEhZWVm1jqPqFQwGSUlJITs7u1oDY1Uv+zF62JPRwZ6MDvZjdLAfo4c9GR2quycbN24c9nNKkRL1i4C0bt2aQCAAbLuS7s+Vb2vTpk2lzhsIBGjduvUen7f8840bN5KTk7PDY7Ozs8nOzgb+f0XfcIwtSZIkSZKk2iPqA8DExEQ6deoEwNdff73DfdavX8/y5csB2H835o/r1asXAN98881O95k1a9Y2+5br3r07sbGxu6yr/LxxcXF069YtbGNLkiRJkiSp9oj6ABBgwIABAHzyySesW7duu+1vvvkmoVCI1NRU9ttvv0qft1+/fgQCATIyMpg+ffp22z///HMyMjIIBAIVNZRLSkqiT58+AEycOHG7285LS0uZOHEiAAcffPB2jy5XZWxJkiRJkiTVHrUiADzmmGNo3rw5BQUF3H777SxZsgTYskjGhAkTePfdd4Et8+CV35VX7oILLuDEE0/koYce2u686enp9OvXD4BHH32UL774glAoRCgU4osvvuCxxx4DtgSQWz/CW27EiBHExsayaNEiHnjggYo5C7KysnjggQdYtGgRcXFxjBgxIuxjS5IkSZIkqXaI+kVAYMsjtDfddBM33ngjP/74I5dffjlJSUkUFBRUrBR0/PHHM2jQoN0+98UXX8yqVauYP38+d911F/Hx8QAUFRUB0LVrV37729/u8Ni2bdty+eWX8/DDD/Ppp58ybdo0kpKSyM3NBSA2NpbLL7+8Yr6/cI4tSZIkSZKk2qFWBICwJWx79NFHeeONN5gxYwbr168nOTmZ9u3bM2TIEA499NA9Om9iYiL33HMPkyZNYurUqWRkZADQoUMHBgwYwJAhQ7a7q3Br/fv3p02bNrz55pvMnTuXnJycikeRTznlFNLT06ttbEmSJEmSJEW/QCgUCkW6CO391q9fX63nL1++vbS0tFqWb1fNCAaDpKSkkJWVtd28ltp32I/Rw56MDvZkdLAfo4P9GD3syehQ3T3ZuHHjsJ9TipRaMQegJEmSJEmSVFsZAEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJkiRJkhTFDAAlSZIkSZKkKGYAKEmSJEmSJEUxA0BJkiRJkiQpihkASpIkSZIkSVHMAFCSJEmSJEmKYgaAkiRJkiRJUhQzAJQkSZIkSZKimAGgJEmSJEmSFMUMACVJkiRJkqQoZgAoSZIkSZIkRTEDQEmSJEmSJCmKGQBKkiRJkiRJUcwAUJIkSZIkSYpiBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxQwAJUmSJEmSpChmAChJkiRJkiRFMQNASZIkSZIkKYoZAEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUC4RCoVCki5BefvllcnNzSU5OZuTIkZEuR6rV7Edp72JPSnsP+1Hau9iTUuUZAGqvcNxxx7F27VqaNm3Ke++9F+lypFrNfpT2LvaktPewH6W9iz0pVZ6PAEuSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJkiRJkhTFDAAlSZIkSZKkKBYb6QIkgLPOOovc3FySk5MjXYpU69mP0t7FnpT2HvajtHexJ6XKC4RCoVCki5AkSZIkSZJUPXwEWJIkSZIkSYpiBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxVwFWHtk4cKFzJgxgwULFpCRkUFOTg6FhYXUq1eP9u3b069fP/r3709MzPYZ8wUXXMDatWt3ef7jjjuOiy66aKfbs7OzmTBhAjNmzGDDhg0kJCTQoUMHjjvuOA499NAqvz4pGtxxxx3MmDEDgIEDB3LFFVfsdN/p06fzr3/9i0WLFlFYWEjjxo3p06cPp59+OvXr19/lOPajVDmV6UmvkVL4ffTRRzz88MO/uN/LL7+802ue10kpPKrSj14jpaoxANQemTx5Mu+//37F53Xq1CE2NpasrCxmzpzJzJkzmTJlCjfddBNJSUk7PEdSUhLx8fE73bYzy5Yt48YbbyQ7OxuAxMREcnNzmTVrFrNmzeKEE05gzJgxVXh10r7vs88+qwgafsmTTz7Je++9B0BMTAwJCQlkZGQwceJEpk6dyp133kmbNm12eKz9KFXO7vQkeI2UqkNMTMwuw7pAILDDr3udlMJvT/sRvEZKe8oAUHukS5cutGrViu7du9OqVauKf2g3btzIlClTGD9+PHPnzuXZZ5/lkksu2eE5xowZw9FHH71b4xYXF3PHHXeQnZ1NWloa48aNIz09ncLCQiZOnMj48eN55513SE9PZ9CgQVV+ndK+KDc3l6effprk5GRSUlJYsWLFTvf94IMPeO+99wgEAowYMYKhQ4eSkJDAkiVLeOCBB1i6dCl33HEHjz32GHFxcdscaz9KlbM7PVnOa6QUfo0bN+aZZ57ZrWO8TkrVY0/6sZzXSGnPOAeg9sjRRx/N0KFD6dSp0za/ZWnYsCGnn346p512GgAff/wxJSUlYRv3gw8+YPXq1SQkJHDLLbeQnp4OQEJCAsOGDWPw4MHAllvGwzmutC95/vnnyczMZOTIkTRs2HCn+xUXF/PKK68AWx6XGDZsGAkJCQCkp6dz8803k5CQwKpVq5gyZcp2x9uPUuVUtieryp6UwsvrpBQ97EfJAFDVpFOnTgAUFRWxadOmsJ33448/BqBfv340adJku+2nnnoqgUCAzMxM5syZE7ZxpX3Fd999x+TJk+nUqVPFDzI7M3v2bLKysggEApxyyinbbW/atCn9+vUD/r/3tmY/Sr9sd3qyquxJKby8TkrRw36UDABVTb7//ntgy9yA4brbIT8/nwULFgBw4IEH7nCfJk2a0Lp1awC+/fbbsIwr7SuKi4t57LHHCAQCXHzxxTtchGdrs2fPBqBNmzY7/EEIoHfv3gD88MMPFBQUVHzdfpR+2e72ZFXYk1L4eZ2UooP9KG3hHIAKm8LCQtatW8d//vMf3nrrLQCGDBmy0wlc33rrLV566SVycnJISkqiXbt29O3bl0GDBu1wUtcVK1YQCoUASEtL22kdaWlpLF++nOXLl4fhVUn7jtdff50VK1Zwwgkn0KFDh1/cv7xHfqmfAEKhECtWrKBjx46A/ShVxu725Na8Rkrhl52dzRVXXMHKlSsBaNSoET179uT444+nXbt22+3vdVKqPrvbj1vzGintGQNAVcnmzZs566yztvt6bGwsxx9/PCNHjtzpscuWLSM+Pp6EhARycnKYPXs2s2fP5l//+he33HLLdr9pzczMrPg4NTV1p+ct35aVlbW7L0faZy1fvpwJEyaQmprKiBEjKnVMeU9Vpp9g256yH6Vd25Oe3JrXSCn8CgsLWbJkCcnJyRQUFJCRkUFGRgYffvgho0eP5uSTT95mf6+TUvXZ3X7cmtdIac8YAKpKYmJiKh7xzcvLo6ioiEAgwPHHH8/JJ59MMBjc7phDDjmEHj160LNnz4ql3zMzM5kyZQqvvfYaS5cu5dZbb+XBBx/cZjW1rR+rKJ+AeUfKt+Xn54fjJUp7vVAoxOOPP05JSQkXXHDBNgvz7Ep5T1Wmn2BLj//82Moebz+qNtnTngSvkVJ1SE1NZfjw4fTt25eWLVsSFxdHSUkJ3333HS+++CLz58/nueeeIzU1lf79+1cc53VSCr897UfwGilVlXMAqkqSkpJ48cUXefHFF3n99dd5+umnOeGEE3jnnXe45JJL+O6777Y7ZsyYMfTt27fiH23YciE444wz+P3vfw9s+a3ORx99VGOvQ9qXffDBB3z33XccdNBBHHHEEZEuR6r1qtKTXiOl8OvduzfDhw8nLS2tIhSIjY2lV69e3H333XTp0gWAF154gbKyskiWKkW9qvSj10ipagwAFTaBQIBmzZpxwQUXcO6557Jp0ybuu+8+CgsLK32OQw45hO7duwPw5ZdfbrOtTp06FR/v6pzl2xITE3enfGmflJmZyQsvvEB8fDwXXnjhbh1b3lOV6Sdgm7uY7Edpx6rSk7/Ea6QUfnFxcRVT1qxfv57FixdXbPM6KdWsXfXjL/EaKf0yA0BVi2OPPZa4uDg2bNjAzJkzd+vY8t/6rF69epuvbz1fw9bzOPxc+baUlJTdGlfaF7344ovk5uYydOhQGjRoQH5+/jZ/yn9zWlpaut3XynuqMv0E2/aU/SjtWFV6sjK8RkrhV95XsG1veZ2Uat7O+nF3jvUaKe2YcwCqWsTHx1OvXj0yMzNZtWpVWM7ZunVrAoEAoVCIZcuWVSzT/nPLli0DoE2bNmEZV9qbrV27Ftiy2ujrr7++0/2mTp3K1KlTAXjooYdo3749bdq04auvvqromR0p3xYIBLbpOftR2rGq9GRV2JNS+HmdlKKD/Sht4R2Aqhb5+fnk5OQAu38L9Q8//ABAs2bNtvl6YmIinTp1AuDrr7/e4bHr16+vWLZ9//33361xpdqmV69ewJYfdtavX7/Dfb755htgy29Ut358wn6UIsNrpBR+5X0F2/aW10mp5u2sH3fnWK+R0o55B6B2W2lpKTExMQQCgZ3uM3HiREpKSgDo0aNHxddDodAuj/vyyy8rFg45+OCDt9s+YMAA5s+fzyeffMIZZ5yx3RLvb775JqFQiNTUVPbbb7/del3Svuiuu+7a5fYbbriBuXPnMnDgQK644opttvXq1YuUlBSysrJ46623GDNmzDbb161bxyeffAJs6b2fsx+l7VWlJ71GSuH3S31VUlLC+PHjAWjUqBEdOnSo2OZ1UgqvqvSj10ip6rwDULtt/fr1XHnllUyePJl169ZVfD0UCrF8+XKefPJJ/v73vwNw2GGHkZaWVrHPU089xVNPPcXcuXO3mYA1KyuL119/nXvvvReAtm3bcvTRR2839jHHHEPz5s0pKCjg9ttvZ8mSJcCWCVsnTJjAu+++C8DIkSOJjTXflnYlLi6Os846C4BJkyYxYcKEir5csmQJt99+OwUFBbRo0YJf//rX2x1vP0rh5TVSCr+1a9dy9dVX88EHH7BmzZqKr5eWljJ37lxuuOEGvv/+ewBGjx5NTMz/vz3yOimFV1X60WukVHWBUCgUinQR2resWbNmm9+AxsfHU6dOHQoKCigqKqr4ep8+fbjmmmu2eRzioYce4t///jewZa6U8tXScnNzK/Zp3749N95443a/lSm3bNkybrzxRrKzs4EtK64VFBRUTKJ+/PHHM3bs2DC9Wmnftqu7jco9+eSTvPfeewAEg0ESEhLIy8sDoGHDhtx55507nQvFfpR2z6560mukFH47+7k1Ly+v4mmV2NhYRo8ezdChQ3d4Dq+TUnhUpR+9RkpVZwCo3VZcXMx///tfZs+ezfz588nKyiInJ4e4uDgaNWpE586d6d+/PwceeOB2x37//fdMnz6dH374gbVr17Jp0ybKysqoV68eHTp04PDDD6dfv36/+FuXjRs38sYbbzBjxgzWr19PnTp1aN++PUOGDOHQQw+trpcu7XMqEwACTJ8+nffee4/FixdTUFBA48aNOfjggznttNNo0KDBLsewH6XK21VPeo2Uwq+wsJApU6Ywb948lixZQnZ2Nnl5eSQkJNCsWTP2228/Bg8eTKtWrXZ5Hq+TUtVVpR+9RkpVZwAoSZIkSZIkRTHnAJQkSZIkSZKimAGgJEmSJEmSFMUMACVJkiRJkqQoZgAoSZIkSZIkRTEDQEmSJEmSJCmKGQBKkiRJkiRJUcwAUJIkSZIkSYpiBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxQwAJUmSJEmSpChmAChJkiRJkiRFMQNASZIkSZIkKYoZAEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJ0l7m+eefJxAIEAgEeP755yNdjiRJkvZxBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxQwAJUmSJEmSpChmAChJkiRJkiRFMQNASZJUa5WWltKyZUsCgQD16tUjLy/vF48pKiqicePGBAIBGjVqRFFRUcW2goICJk6cyGWXXUbfvn1p0qQJcXFx1KtXj06dOjFq1CimTJlS5bp//PHHilWCzznnnF/cv127dgQCAdq1a/eL+y5atIjrrruOPn360KRJE+Lj42nWrBkDBw7k4YcfrtTfkSRJkvYusZEuQJIkKVKCwSAjRozg/vvvZ/Pmzbz55puMHDlyl8e89957bNiwAYAzzjiD+Pj4im3du3dnyZIl2x2zefNmFi5cyMKFC3n55ZcZOnQoL7/8MnXr1g3vC6qCsrIybrrpJu677z5KSkq22bZ27VrWrl3Lf/7zH+6//37efvttDjrooAhVKkmSpN1lAChJkmq10aNHc//99wPw0ksv/WIA+OKLL1Z8fPbZZ2+zLS8vj4YNGzJw4EB69+5NWloaSUlJ5OTkMHv2bF577TVWrVrFxIkTOe+88/jHP/4R/he0h0aPHs3LL78MQGpqKmeccQYHHXQQ9evXZ+3atbz77rv861//YsWKFRx11FF89dVXdO7cOcJVS5IkqTIMACVJUq3Ws2dPevfuzTfffMNHH33EqlWraNGixQ73zczM5N133wWgc+fOHHroodtsf+655xg0aBBxcXE7PP7OO+9kxIgRvP3227z++utMmzaNI444IrwvaA/89a9/rQj/TjjhBF588UUaNmy4zT6/+93vePPNNznjjDPYtGkT5513HtOmTYtAtZIkSdpdzgEoSZJqvfI7+UpLSyuCsB35xz/+UTHn36hRo7bbPnjw4J2GfwBJSUm88MILJCcnA/DCCy9UpeywKCws5NZbbwWgW7duTJgwYbvwr9wpp5zCtddeC8Bnn33Gf//735oqU5IkSVVgAChJkmq9s846i9jYLQ9GvPTSSzvdr/zx30AgsMMAsDLq16/PfvvtB8AXX3yxR+cIp8mTJ7Nq1SoArrjiim3mNNyR0aNHV3z8wQcfVGttkiRJCg8fAZYkSbVe06ZNOfbYY5k0aRJz5sxh1qxZHHDAAdvss3DhQqZPnw5Av379SEtL2+G5srKyGD9+PO+//z5z585lw4YN5ObmEgqFttt3xYoVYX8tu+uTTz6p+HjTpk28/fbbu9y/uLi44uPvvvuuusqSJElSGBkASpIkseUx4EmTJgFb7vT7eQC49aPBP1/8o9zEiRM5//zzK1YJ/iU5OTl7VmwY/fjjjxUfX3311bt1bGZmZpirkSRJUnUwAJQkSQJOPPFEUlJSyMrK4u9//zv33XcfwWCwYnv5o8FJSUmcfvrp2x0/ffp0TjvtNEpKSgDo1asXgwYNomPHjqSkpJCQkEAgEADgpptu4n//+x9lZWU18Mp2bePGjXt8bPl8iJIkSdq7GQBKkiQBCQkJDBs2jL/+9a+sXr2ayZMnM3jwYGDLgheLFy8G4KSTTqJevXrbHX/LLbdUhH+PP/44F1988U7HuvPOO6vhFexcaWnpTrfVrVu34uPZs2dXzE8oSZKk6OEiIJIkST/Z+tHe8gU/fv7xjh7/LS4u5uOPPwbgoIMO2mX4B9s+drsnEhISKj7+pbvwQqHQLh/Vbd26dcXHy5cvr1JdkiRJ2jsZAEqSJP2kb9++dOrUCdgyn9+mTZsoLCzkH//4BwAtWrRg0KBB2x23fv36irv/OnbsuMsxvvzyS9avX1+lOhs2bFjx8cqVK3e576xZs8jLy9vp9v79+1d8/K9//atKdUmSJGnvZAAoSZK0lVGjRgGQn5/P66+/zqRJkyrmyRsxYsQ28wKWS05Orvh44cKFuzz/H/7whyrXmJiYSPv27QGYMWPGLhcTeeCBB3Z5rsGDB9OkSRMAnn322V+sX5IkSfseA0BJkqStjBo1qmKxjhdffPEXH/8FqF+/Pp07dwZg5syZTJgwYbt9SktLufLKK8N2l135/IQFBQVcf/31O9znoYce2mb14h1JTk7mj3/8IwB5eXkcc8wxfPPNN7s8ZuHChYwbN461a9fufuGSJEmqcYFQKBSKdBGSJEl7kwEDBjB16lQCgQDBYJCSkhIOOOCAXQZjTzzxRMXcf4FAgDPOOIP+/fuTkpLCwoULGT9+PPPmzaNnz54kJCQwc+ZMYMscfT/3/PPPc+655wLw3HPPcc4552y3z4IFC+jVqxcFBQUADBo0iNNPP52UlBSWL1/OhAkTmD59Ov3792fhwoWsXLmStLS0nc4/eP755/Pss89W1H/MMcdw9NFH07p1awKBAJmZmcybN49PP/2UWbNmAVvmDNx6DkFJkiTtnVwFWJIk6WfOPvtspk6dSigUqpjbb2d3/5W76KKL+Oqrr3j22WcJhUK8+uqrvPrqq9vss99++zFx4sSKcK8qOnXqxNNPP80555xDaWkpH374IR9++OE2+/Tr148333yTAw888BfP98wzz9ClSxduvfVW8vLyeP/993n//fd3un/jxo2pU6dOlV+HJEmSqp+PAEuSJP3M6aefTlJSUsXnsbGxnHXWWbs8JhAI8Le//Y033niDY445hkaNGhEXF0fz5s3p378/jz32GDNmzCA9PT1sdY4cOZKZM2cycuRI2rRpQ3x8PI0bN6Zfv34888wz/Pvf/yY1NbVS5woEAlx77bX8+OOP3HPPPQwaNIiWLVuSkJBAQkICzZo14/DDD+fyyy9n0qRJZGRk0Lhx47C9FkmSJFUfHwGWJEmSJEmSoph3AEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJkiRJkhTFDAAlSZIkSZKkKGYAKEmSJEmSJEUxA0BJkiRJkiQpihkASpIkSZIkSVHMAFCSJEmSJEmKYgaAkiRJkiRJUhQzAJQkSZIkSZKimAGgJEmSJEmSFMUMACVJkiRJkqQoZgAoSZIkSZIkRTEDQEmSJEmSJCmKGQBKkiRJkiRJUcwAUJIkSZIkSYpi/wcZfcOOL1zoCQAAAABJRU5ErkJggg==" }, "metadata": { "image/png": { @@ -10029,7 +8028,7 @@ "from plotnine import ggplot, aes, geom_point, geom_jitter, geom_density\n", "\n", "df = pd.DataFrame({\n", - " 'msy': msy_rews,\n", + " # 'msy': msy_rews,\n", " 'esc': esc_rews,\n", " 'cr': cr_rews,\n", "}).melt()\n", @@ -11020,7 +9019,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:04,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:36:40,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11028,9 +9027,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 7.2468\n", - "Function value obtained: -1.9048\n", - "Current minimum: -1.9048\n", + "Time taken: 8.5964\n", + "Function value obtained: -1.9301\n", + "Current minimum: -1.9301\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -11038,7 +9037,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:11,288\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:36:48,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11046,9 +9045,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 7.2018\n", - "Function value obtained: -1.9737\n", - "Current minimum: -1.9737\n", + "Time taken: 7.8739\n", + "Function value obtained: -1.8447\n", + "Current minimum: -1.9301\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -11056,7 +9055,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:18,514\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:36:56,547\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11064,9 +9063,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 6.8578\n", - "Function value obtained: -1.9354\n", - "Current minimum: -1.9737\n", + "Time taken: 8.6655\n", + "Function value obtained: -2.9466\n", + "Current minimum: -2.9466\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -11074,7 +9073,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:25,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:37:05,224\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11082,9 +9081,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 7.0262\n", - "Function value obtained: -2.0507\n", - "Current minimum: -2.0507\n", + "Time taken: 8.6346\n", + "Function value obtained: -2.0565\n", + "Current minimum: -2.9466\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -11092,7 +9091,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:32,404\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:37:13,859\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11100,9 +9099,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 7.0535\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.0507\n", + "Time taken: 8.4440\n", + "Function value obtained: -1.9924\n", + "Current minimum: -2.9466\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -11110,7 +9109,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:39,532\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:37:22,326\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11118,9 +9117,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 7.0462\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.0507\n", + "Time taken: 7.8105\n", + "Function value obtained: -1.9986\n", + "Current minimum: -2.9466\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -11128,7 +9127,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:46,549\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:37:30,148\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11136,9 +9135,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 7.2075\n", - "Function value obtained: -2.0646\n", - "Current minimum: -2.0646\n", + "Time taken: 8.6142\n", + "Function value obtained: -1.8612\n", + "Current minimum: -2.9466\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -11146,7 +9145,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:43:53,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:37:38,743\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11154,9 +9153,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 7.3153\n", - "Function value obtained: -1.9315\n", - "Current minimum: -2.0646\n", + "Time taken: 8.7192\n", + "Function value obtained: -1.9489\n", + "Current minimum: -2.9466\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -11164,7 +9163,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:44:01,054\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:37:47,463\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11172,9 +9171,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 7.0475\n", - "Function value obtained: -2.1287\n", - "Current minimum: -2.1287\n", + "Time taken: 8.6512\n", + "Function value obtained: -3.6397\n", + "Current minimum: -3.6397\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -11182,7 +9181,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:44:08,119\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:37:56,166\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11190,9 +9189,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 10.8057\n", - "Function value obtained: -1.8554\n", - "Current minimum: -2.1287\n", + "Time taken: 12.5335\n", + "Function value obtained: -1.9026\n", + "Current minimum: -3.6397\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -11200,7 +9199,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:44:18,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:38:08,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11208,9 +9207,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3912\n", - "Function value obtained: -1.9575\n", - "Current minimum: -2.1287\n", + "Time taken: 9.9853\n", + "Function value obtained: -4.1769\n", + "Current minimum: -4.1769\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -11218,7 +9217,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:44:27,320\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:38:18,707\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11226,9 +9225,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2712\n", - "Function value obtained: -1.9597\n", - "Current minimum: -2.1287\n", + "Time taken: 10.0685\n", + "Function value obtained: -4.9104\n", + "Current minimum: -4.9104\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -11236,7 +9235,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:44:35,645\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:38:28,753\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11244,9 +9243,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8549\n", - "Function value obtained: -2.0411\n", - "Current minimum: -2.1287\n", + "Time taken: 9.9638\n", + "Function value obtained: -30.9084\n", + "Current minimum: -30.9084\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -11254,9 +9253,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [0.3715626298528427]\n", - " warnings.warn(\n", - "2024-04-25 17:44:44,423\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:38:38,726\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11264,9 +9261,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4937\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.1287\n", + "Time taken: 10.1723\n", + "Function value obtained: -43.9345\n", + "Current minimum: -43.9345\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -11274,7 +9271,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:44:52,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:38:48,878\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11282,9 +9279,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4121\n", - "Function value obtained: -1.9700\n", - "Current minimum: -2.1287\n", + "Time taken: 9.4033\n", + "Function value obtained: -35.1148\n", + "Current minimum: -43.9345\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -11292,9 +9289,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-5.419977199986665]\n", - " warnings.warn(\n", - "2024-04-25 17:45:01,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:38:58,300\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11302,9 +9297,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4600\n", - "Function value obtained: -1.9894\n", - "Current minimum: -2.1287\n", + "Time taken: 9.9715\n", + "Function value obtained: -39.9467\n", + "Current minimum: -43.9345\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -11312,7 +9307,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:45:09,877\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:39:08,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11320,9 +9315,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4054\n", - "Function value obtained: -2.0045\n", - "Current minimum: -2.1287\n", + "Time taken: 9.6872\n", + "Function value obtained: -41.4673\n", + "Current minimum: -43.9345\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -11330,9 +9325,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-2.703683694288526]\n", - " warnings.warn(\n", - "2024-04-25 17:45:18,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:39:18,044\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11340,9 +9333,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1587\n", - "Function value obtained: -1.8827\n", - "Current minimum: -2.1287\n", + "Time taken: 9.2898\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.9345\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -11350,7 +9343,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:45:26,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:39:27,300\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11358,9 +9351,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 7.4855\n", - "Function value obtained: -1.9271\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0895\n", + "Function value obtained: -39.4750\n", + "Current minimum: -43.9345\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -11368,7 +9361,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:45:33,929\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:39:36,401\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11376,9 +9369,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 7.2841\n", - "Function value obtained: -2.0115\n", - "Current minimum: -2.1287\n", + "Time taken: 9.1824\n", + "Function value obtained: -39.9131\n", + "Current minimum: -43.9345\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -11386,7 +9379,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:45:41,196\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:39:45,549\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11394,9 +9387,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 7.3577\n", - "Function value obtained: -1.9363\n", - "Current minimum: -2.1287\n", + "Time taken: 8.9877\n", + "Function value obtained: -38.6377\n", + "Current minimum: -43.9345\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -11404,7 +9397,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:45:48,556\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:39:54,606\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11412,9 +9405,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7215\n", - "Function value obtained: -2.0020\n", - "Current minimum: -2.1287\n", + "Time taken: 8.9698\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.9345\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -11422,7 +9415,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:45:56,290\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:40:03,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11430,9 +9423,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5647\n", - "Function value obtained: -1.9813\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0596\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.9345\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -11440,7 +9433,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:46:03,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:40:12,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11448,9 +9441,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6284\n", - "Function value obtained: -1.8912\n", - "Current minimum: -2.1287\n", + "Time taken: 9.2469\n", + "Function value obtained: -41.3403\n", + "Current minimum: -43.9345\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -11458,9 +9451,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-1.0255907058676303]\n", - " warnings.warn(\n", - "2024-04-25 17:46:11,493\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:40:21,858\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11468,9 +9459,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6490\n", - "Function value obtained: -2.1065\n", - "Current minimum: -2.1287\n", + "Time taken: 8.9188\n", + "Function value obtained: -1.9286\n", + "Current minimum: -43.9345\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -11478,7 +9469,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:46:19,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:40:30,757\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11486,9 +9477,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5100\n", - "Function value obtained: -2.0861\n", - "Current minimum: -2.1287\n", + "Time taken: 9.2686\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.9345\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -11496,7 +9487,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:46:26,654\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:40:40,087\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11504,9 +9495,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 7.2805\n", - "Function value obtained: -2.0434\n", - "Current minimum: -2.1287\n", + "Time taken: 9.1510\n", + "Function value obtained: -38.9835\n", + "Current minimum: -43.9345\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -11514,7 +9505,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:46:33,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:40:49,211\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11522,9 +9513,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6268\n", - "Function value obtained: -1.9285\n", - "Current minimum: -2.1287\n", + "Time taken: 9.3303\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.9345\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -11532,9 +9523,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.3826217743275695]\n", - " warnings.warn(\n", - "2024-04-25 17:46:41,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:40:58,611\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11542,9 +9531,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6558\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0922\n", + "Function value obtained: -1.9758\n", + "Current minimum: -43.9345\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -11552,7 +9541,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:46:49,242\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:41:07,726\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11560,9 +9549,9 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7707\n", - "Function value obtained: -2.0044\n", - "Current minimum: -2.1287\n", + "Time taken: 8.9833\n", + "Function value obtained: -40.0722\n", + "Current minimum: -43.9345\n", "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, @@ -11570,9 +9559,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.8102285992201157]\n", - " warnings.warn(\n", - "2024-04-25 17:46:57,024\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:41:16,645\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11580,9 +9567,9 @@ "output_type": "stream", "text": [ "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6583\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0641\n", + "Function value obtained: -1.9500\n", + "Current minimum: -43.9345\n", "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, @@ -11590,9 +9577,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.3859259110617854]\n", - " warnings.warn(\n", - "2024-04-25 17:47:05,710\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:41:25,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11600,9 +9585,9 @@ "output_type": "stream", "text": [ "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9140\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.1287\n", + "Time taken: 9.1091\n", + "Function value obtained: -1.9343\n", + "Current minimum: -43.9345\n", "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, @@ -11610,7 +9595,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:47:13,607\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:41:34,844\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11618,9 +9603,9 @@ "output_type": "stream", "text": [ "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 7.4819\n", - "Function value obtained: -1.9521\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0716\n", + "Function value obtained: -39.6939\n", + "Current minimum: -43.9345\n", "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, @@ -11628,9 +9613,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [0.10995143036891619]\n", - " warnings.warn(\n", - "2024-04-25 17:47:21,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:41:43,914\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11638,9 +9621,9 @@ "output_type": "stream", "text": [ "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7571\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0792\n", + "Function value obtained: -1.9958\n", + "Current minimum: -43.9345\n", "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, @@ -11648,7 +9631,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:47:28,882\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:41:52,954\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11656,9 +9639,9 @@ "output_type": "stream", "text": [ "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 7.4464\n", - "Function value obtained: -1.9466\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0826\n", + "Function value obtained: -1.9054\n", + "Current minimum: -43.9345\n", "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, @@ -11666,7 +9649,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:47:36,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:42:02,075\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11674,9 +9657,9 @@ "output_type": "stream", "text": [ "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5964\n", - "Function value obtained: -1.9455\n", - "Current minimum: -2.1287\n", + "Time taken: 9.0319\n", + "Function value obtained: -40.6130\n", + "Current minimum: -43.9345\n", "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, @@ -11684,7 +9667,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:47:43,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:42:11,075\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11692,9 +9675,9 @@ "output_type": "stream", "text": [ "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5785\n", - "Function value obtained: -2.1195\n", - "Current minimum: -2.1287\n", + "Time taken: 9.1230\n", + "Function value obtained: -40.7349\n", + "Current minimum: -43.9345\n", "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, @@ -11702,7 +9685,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:47:51,490\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:42:20,210\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11710,9 +9693,9 @@ "output_type": "stream", "text": [ "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6549\n", - "Function value obtained: -1.9578\n", - "Current minimum: -2.1287\n", + "Time taken: 8.6547\n", + "Function value obtained: -39.1674\n", + "Current minimum: -43.9345\n", "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, @@ -11720,7 +9703,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:47:59,156\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:42:28,910\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11728,9 +9711,9 @@ "output_type": "stream", "text": [ "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6839\n", - "Function value obtained: -2.0423\n", - "Current minimum: -2.1287\n", + "Time taken: 9.2671\n", + "Function value obtained: -2.0267\n", + "Current minimum: -43.9345\n", "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, @@ -11738,7 +9721,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:48:06,842\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:42:38,183\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11746,9 +9729,9 @@ "output_type": "stream", "text": [ "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5758\n", - "Function value obtained: -1.9169\n", - "Current minimum: -2.1287\n", + "Time taken: 8.5154\n", + "Function value obtained: -39.9648\n", + "Current minimum: -43.9345\n", "Iteration No: 41 started. Searching for the next optimal point.\n" ] }, @@ -11756,9 +9739,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-0.12854283508189202]\n", - " warnings.warn(\n", - "2024-04-25 17:48:15,422\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:42:46,708\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11766,9 +9747,9 @@ "output_type": "stream", "text": [ "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7738\n", - "Function value obtained: -0.3884\n", - "Current minimum: -2.1287\n", + "Time taken: 9.2752\n", + "Function value obtained: -39.9524\n", + "Current minimum: -43.9345\n", "Iteration No: 42 started. Searching for the next optimal point.\n" ] }, @@ -11776,9 +9757,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-1.7795068095198445]\n", - " warnings.warn(\n", - "2024-04-25 17:48:23,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:42:55,952\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11786,9 +9765,9 @@ "output_type": "stream", "text": [ "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6866\n", - "Function value obtained: -1.9185\n", - "Current minimum: -2.1287\n", + "Time taken: 9.2019\n", + "Function value obtained: -39.9497\n", + "Current minimum: -43.9345\n", "Iteration No: 43 started. Searching for the next optimal point.\n" ] }, @@ -11796,9 +9775,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-4.462853949509887]\n", - " warnings.warn(\n", - "2024-04-25 17:48:30,947\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:43:05,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11806,9 +9783,9 @@ "output_type": "stream", "text": [ "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8422\n", - "Function value obtained: -1.8635\n", - "Current minimum: -2.1287\n", + "Time taken: 9.3917\n", + "Function value obtained: -40.6759\n", + "Current minimum: -43.9345\n", "Iteration No: 44 started. Searching for the next optimal point.\n" ] }, @@ -11816,9 +9793,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [1.862197976179674]\n", - " warnings.warn(\n", - "2024-04-25 17:48:38,769\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:43:14,602\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11826,9 +9801,9 @@ "output_type": "stream", "text": [ "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0573\n", + "Time taken: 8.7284\n", "Function value obtained: -0.0000\n", - "Current minimum: -2.1287\n", + "Current minimum: -43.9345\n", "Iteration No: 45 started. Searching for the next optimal point.\n" ] }, @@ -11836,9 +9811,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-2.4203438877690298]\n", - " warnings.warn(\n", - "2024-04-25 17:48:46,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:43:23,310\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11846,9 +9819,9 @@ "output_type": "stream", "text": [ "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8161\n", - "Function value obtained: -1.9774\n", - "Current minimum: -2.1287\n", + "Time taken: 9.4948\n", + "Function value obtained: -40.7349\n", + "Current minimum: -43.9345\n", "Iteration No: 46 started. Searching for the next optimal point.\n" ] }, @@ -11856,9 +9829,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-3.4506555127302057]\n", - " warnings.warn(\n", - "2024-04-25 17:48:54,636\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:43:32,785\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11866,9 +9837,9 @@ "output_type": "stream", "text": [ "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9360\n", - "Function value obtained: -1.8775\n", - "Current minimum: -2.1287\n", + "Time taken: 9.5088\n", + "Function value obtained: -41.3343\n", + "Current minimum: -43.9345\n", "Iteration No: 47 started. Searching for the next optimal point.\n" ] }, @@ -11876,9 +9847,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-2.4324444495959483]\n", - " warnings.warn(\n", - "2024-04-25 17:49:02,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:43:42,304\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11886,9 +9855,9 @@ "output_type": "stream", "text": [ "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8956\n", - "Function value obtained: -1.8945\n", - "Current minimum: -2.1287\n", + "Time taken: 9.2649\n", + "Function value obtained: -0.0000\n", + "Current minimum: -43.9345\n", "Iteration No: 48 started. Searching for the next optimal point.\n" ] }, @@ -11896,9 +9865,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-3.6627032192701106]\n", - " warnings.warn(\n", - "2024-04-25 17:49:10,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:43:51,573\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11906,9 +9873,9 @@ "output_type": "stream", "text": [ "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7399\n", - "Function value obtained: -1.9696\n", - "Current minimum: -2.1287\n", + "Time taken: 9.1430\n", + "Function value obtained: -40.2793\n", + "Current minimum: -43.9345\n", "Iteration No: 49 started. Searching for the next optimal point.\n" ] }, @@ -11916,9 +9883,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-4.859554148703219]\n", - " warnings.warn(\n", - "2024-04-25 17:49:18,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:44:00,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11926,9 +9891,9 @@ "output_type": "stream", "text": [ "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9707\n", - "Function value obtained: -1.9285\n", - "Current minimum: -2.1287\n", + "Time taken: 8.9883\n", + "Function value obtained: -39.1546\n", + "Current minimum: -43.9345\n", "Iteration No: 50 started. Searching for the next optimal point.\n" ] }, @@ -11936,9 +9901,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [-6.0] before, using random point [-5.7446808564087695]\n", - " warnings.warn(\n", - "2024-04-25 17:49:26,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:44:09,744\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11946,17 +9909,17 @@ "output_type": "stream", "text": [ "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0019\n", - "Function value obtained: -1.9361\n", - "Current minimum: -2.1287\n", - "CPU times: user 6min 43s, sys: 9min 27s, total: 16min 10s\n", - "Wall time: 6min 29s\n" + "Time taken: 9.3150\n", + "Function value obtained: -38.7926\n", + "Current minimum: -43.9345\n", + "CPU times: user 7min 7s, sys: 9min 53s, total: 17min 1s\n", + "Wall time: 7min 38s\n" ] }, { "data": { "text/plain": [ - "(-2.1286563027031495, [-1.1965266045176186])" + "(-43.93454607110205, [-0.18751693186661367])" ] }, "execution_count": 5, @@ -11989,7 +9952,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:49:34,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:44:19,075\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -11997,9 +9960,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 7.5362\n", - "Function value obtained: -3.0056\n", - "Current minimum: -3.0056\n", + "Time taken: 8.9138\n", + "Function value obtained: -1.9730\n", + "Current minimum: -1.9730\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -12007,7 +9970,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:49:41,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:44:28,024\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12015,9 +9978,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 7.3328\n", - "Function value obtained: -2.4511\n", - "Current minimum: -3.0056\n", + "Time taken: 8.9834\n", + "Function value obtained: -2.8469\n", + "Current minimum: -2.8469\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -12025,7 +9988,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:49:49,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:44:37,007\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12033,9 +9996,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 7.5459\n", - "Function value obtained: -2.0481\n", - "Current minimum: -3.0056\n", + "Time taken: 8.4480\n", + "Function value obtained: -2.4274\n", + "Current minimum: -2.8469\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -12043,7 +10006,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:49:56,692\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:44:45,460\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12051,9 +10014,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 7.5742\n", - "Function value obtained: -4.0016\n", - "Current minimum: -4.0016\n", + "Time taken: 9.0373\n", + "Function value obtained: -3.2697\n", + "Current minimum: -3.2697\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -12061,7 +10024,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:04,279\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:44:54,514\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12069,9 +10032,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 7.5454\n", - "Function value obtained: -2.5316\n", - "Current minimum: -4.0016\n", + "Time taken: 9.1095\n", + "Function value obtained: -2.3260\n", + "Current minimum: -3.2697\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -12079,7 +10042,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:11,814\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:45:03,648\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12087,9 +10050,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 7.7054\n", - "Function value obtained: -16.9847\n", - "Current minimum: -16.9847\n", + "Time taken: 9.0462\n", + "Function value obtained: -2.0956\n", + "Current minimum: -3.2697\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -12097,7 +10060,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:19,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:45:12,669\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12105,9 +10068,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 7.7268\n", - "Function value obtained: -13.3485\n", - "Current minimum: -16.9847\n", + "Time taken: 10.2570\n", + "Function value obtained: -3.4491\n", + "Current minimum: -3.4491\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -12115,7 +10078,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:27,261\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:45:22,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12123,9 +10086,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 8.3116\n", - "Function value obtained: -6.8201\n", - "Current minimum: -16.9847\n", + "Time taken: 8.6393\n", + "Function value obtained: -2.2414\n", + "Current minimum: -3.4491\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -12133,7 +10096,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:35,612\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:45:31,612\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12141,9 +10104,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 7.5522\n", - "Function value obtained: -43.3207\n", - "Current minimum: -43.3207\n", + "Time taken: 8.9456\n", + "Function value obtained: -2.1366\n", + "Current minimum: -3.4491\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -12151,7 +10114,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:43,105\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:45:40,530\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12159,9 +10122,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 7.6797\n", - "Function value obtained: -2.1571\n", - "Current minimum: -43.3207\n", + "Time taken: 9.3515\n", + "Function value obtained: -2.1085\n", + "Current minimum: -3.4491\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -12169,7 +10132,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:50,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:45:49,852\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12177,9 +10140,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8512\n", - "Function value obtained: -0.0000\n", - "Current minimum: -43.3207\n", + "Time taken: 9.2617\n", + "Function value obtained: -3.4426\n", + "Current minimum: -3.4491\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -12187,7 +10150,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:50:58,633\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:45:59,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12195,9 +10158,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7731\n", - "Function value obtained: -41.5928\n", - "Current minimum: -43.3207\n", + "Time taken: 9.3741\n", + "Function value obtained: -3.2485\n", + "Current minimum: -3.4491\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -12205,7 +10168,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:51:06,425\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:46:08,527\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12213,9 +10176,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0390\n", - "Function value obtained: -0.0000\n", - "Current minimum: -43.3207\n", + "Time taken: 8.7478\n", + "Function value obtained: -3.6404\n", + "Current minimum: -3.6404\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -12223,7 +10186,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:51:14,553\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:46:17,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12231,9 +10194,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6942\n", - "Function value obtained: -39.7440\n", - "Current minimum: -43.3207\n", + "Time taken: 8.8650\n", + "Function value obtained: -8.7778\n", + "Current minimum: -8.7778\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -12241,7 +10204,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:51:23,185\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:46:26,125\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12249,9 +10212,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9191\n", - "Function value obtained: -43.5548\n", - "Current minimum: -43.5548\n", + "Time taken: 9.1656\n", + "Function value obtained: -36.8555\n", + "Current minimum: -36.8555\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -12259,7 +10222,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:51:32,107\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:46:35,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12267,9 +10230,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0632\n", - "Function value obtained: -44.1675\n", - "Current minimum: -44.1675\n", + "Time taken: 9.0623\n", + "Function value obtained: -0.0000\n", + "Current minimum: -36.8555\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -12277,7 +10240,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:51:40,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:46:44,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12285,9 +10248,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2439\n", - "Function value obtained: -42.1269\n", - "Current minimum: -44.1675\n", + "Time taken: 9.2907\n", + "Function value obtained: -42.3661\n", + "Current minimum: -42.3661\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -12295,7 +10258,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:51:48,410\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:46:53,712\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12303,9 +10266,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7441\n", - "Function value obtained: -44.3219\n", - "Current minimum: -44.3219\n", + "Time taken: 10.0204\n", + "Function value obtained: -46.0048\n", + "Current minimum: -46.0048\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -12313,7 +10276,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:51:57,211\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:47:03,753\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12321,9 +10284,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1056\n", - "Function value obtained: -46.6821\n", - "Current minimum: -46.6821\n", + "Time taken: 9.0442\n", + "Function value obtained: -39.5346\n", + "Current minimum: -46.0048\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -12331,7 +10294,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:52:05,280\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:47:12,725\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12339,9 +10302,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8339\n", - "Function value obtained: -47.3783\n", - "Current minimum: -47.3783\n", + "Time taken: 9.3413\n", + "Function value obtained: -46.5219\n", + "Current minimum: -46.5219\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -12349,7 +10312,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:52:14,145\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:47:22,106\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12357,9 +10320,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9693\n", - "Function value obtained: -47.2997\n", - "Current minimum: -47.3783\n", + "Time taken: 9.5130\n", + "Function value obtained: -45.6431\n", + "Current minimum: -46.5219\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -12367,7 +10330,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:52:22,093\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:47:31,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12375,9 +10338,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0583\n", - "Function value obtained: -45.8191\n", - "Current minimum: -47.3783\n", + "Time taken: 9.3061\n", + "Function value obtained: -47.4524\n", + "Current minimum: -47.4524\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -12385,7 +10348,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:52:30,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:47:40,947\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12393,9 +10356,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0238\n", - "Function value obtained: -1.9344\n", - "Current minimum: -47.3783\n", + "Time taken: 9.4190\n", + "Function value obtained: -46.2837\n", + "Current minimum: -47.4524\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -12403,7 +10366,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:52:38,113\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:47:50,368\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12411,9 +10374,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9621\n", - "Function value obtained: -46.0481\n", - "Current minimum: -47.3783\n", + "Time taken: 9.1818\n", + "Function value obtained: -46.0733\n", + "Current minimum: -47.4524\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -12421,7 +10384,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:52:46,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:47:59,552\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12429,9 +10392,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8595\n", - "Function value obtained: -2.0613\n", - "Current minimum: -47.3783\n", + "Time taken: 9.6298\n", + "Function value obtained: -45.0519\n", + "Current minimum: -47.4524\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -12439,7 +10402,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:52:54,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:48:09,184\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12447,9 +10410,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7663\n", - "Function value obtained: -48.8415\n", - "Current minimum: -48.8415\n", + "Time taken: 9.2747\n", + "Function value obtained: -48.3007\n", + "Current minimum: -48.3007\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -12457,7 +10420,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:53:03,775\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:48:18,463\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12465,9 +10428,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2160\n", - "Function value obtained: -2.5755\n", - "Current minimum: -48.8415\n", + "Time taken: 9.4191\n", + "Function value obtained: -44.6605\n", + "Current minimum: -48.3007\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -12475,7 +10438,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:53:12,023\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:48:27,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12483,9 +10446,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1004\n", - "Function value obtained: -2.9925\n", - "Current minimum: -48.8415\n", + "Time taken: 9.5384\n", + "Function value obtained: -46.6828\n", + "Current minimum: -48.3007\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -12493,7 +10456,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:53:20,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:48:37,417\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12501,9 +10464,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8805\n", - "Function value obtained: -43.0760\n", - "Current minimum: -48.8415\n", + "Time taken: 9.4294\n", + "Function value obtained: -47.0291\n", + "Current minimum: -48.3007\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -12511,7 +10474,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:53:29,008\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:48:46,949\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12519,9 +10482,9 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1147\n", - "Function value obtained: -1.5035\n", - "Current minimum: -48.8415\n", + "Time taken: 10.2622\n", + "Function value obtained: -44.6340\n", + "Current minimum: -48.3007\n", "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, @@ -12529,7 +10492,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:53:37,125\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:48:57,114\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12537,9 +10500,9 @@ "output_type": "stream", "text": [ "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5263\n", - "Function value obtained: -33.0037\n", - "Current minimum: -48.8415\n", + "Time taken: 9.8834\n", + "Function value obtained: -43.5292\n", + "Current minimum: -48.3007\n", "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, @@ -12547,7 +10510,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:53:45,647\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:49:07,051\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12555,9 +10518,9 @@ "output_type": "stream", "text": [ "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7627\n", - "Function value obtained: -2.8038\n", - "Current minimum: -48.8415\n", + "Time taken: 9.5472\n", + "Function value obtained: -48.3121\n", + "Current minimum: -48.3121\n", "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, @@ -12565,7 +10528,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:53:54,307\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:49:16,590\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12573,9 +10536,9 @@ "output_type": "stream", "text": [ "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6853\n", - "Function value obtained: -39.6488\n", - "Current minimum: -48.8415\n", + "Time taken: 9.5588\n", + "Function value obtained: -45.2423\n", + "Current minimum: -48.3121\n", "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, @@ -12583,7 +10546,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:54:03,120\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:49:26,168\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12591,9 +10554,9 @@ "output_type": "stream", "text": [ "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2671\n", - "Function value obtained: -2.1287\n", - "Current minimum: -48.8415\n", + "Time taken: 9.3964\n", + "Function value obtained: -48.4500\n", + "Current minimum: -48.4500\n", "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, @@ -12601,7 +10564,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:54:11,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:49:35,526\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12609,9 +10572,9 @@ "output_type": "stream", "text": [ "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7627\n", - "Function value obtained: -37.9392\n", - "Current minimum: -48.8415\n", + "Time taken: 9.1369\n", + "Function value obtained: -45.9784\n", + "Current minimum: -48.4500\n", "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, @@ -12619,7 +10582,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:54:20,156\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:49:44,632\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12627,9 +10590,9 @@ "output_type": "stream", "text": [ "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0250\n", - "Function value obtained: -48.8930\n", - "Current minimum: -48.8930\n", + "Time taken: 9.9915\n", + "Function value obtained: -46.5027\n", + "Current minimum: -48.4500\n", "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, @@ -12637,7 +10600,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:54:29,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:49:54,670\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12645,9 +10608,9 @@ "output_type": "stream", "text": [ "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6697\n", - "Function value obtained: -47.6254\n", - "Current minimum: -48.8930\n", + "Time taken: 9.4928\n", + "Function value obtained: -44.2130\n", + "Current minimum: -48.4500\n", "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, @@ -12655,7 +10618,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:54:37,875\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:50:04,188\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12663,9 +10626,9 @@ "output_type": "stream", "text": [ "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9464\n", - "Function value obtained: -46.8607\n", - "Current minimum: -48.8930\n", + "Time taken: 9.6264\n", + "Function value obtained: -45.5473\n", + "Current minimum: -48.4500\n", "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, @@ -12673,7 +10636,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:54:46,778\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:50:13,788\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12681,9 +10644,9 @@ "output_type": "stream", "text": [ "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8875\n", - "Function value obtained: -54.4202\n", - "Current minimum: -54.4202\n", + "Time taken: 9.2103\n", + "Function value obtained: -46.8801\n", + "Current minimum: -48.4500\n", "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, @@ -12691,7 +10654,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:54:55,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:50:23,024\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12699,9 +10662,9 @@ "output_type": "stream", "text": [ "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0514\n", - "Function value obtained: -6.1205\n", - "Current minimum: -54.4202\n", + "Time taken: 9.6922\n", + "Function value obtained: -47.4527\n", + "Current minimum: -48.4500\n", "Iteration No: 41 started. Searching for the next optimal point.\n" ] }, @@ -12709,7 +10672,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:55:04,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:50:32,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12717,9 +10680,9 @@ "output_type": "stream", "text": [ "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0313\n", - "Function value obtained: -43.3462\n", - "Current minimum: -54.4202\n", + "Time taken: 9.9327\n", + "Function value obtained: -46.2565\n", + "Current minimum: -48.4500\n", "Iteration No: 42 started. Searching for the next optimal point.\n" ] }, @@ -12727,7 +10690,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:55:13,790\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:50:42,659\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12735,9 +10698,9 @@ "output_type": "stream", "text": [ "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9432\n", - "Function value obtained: -59.7009\n", - "Current minimum: -59.7009\n", + "Time taken: 8.9960\n", + "Function value obtained: -44.8700\n", + "Current minimum: -48.4500\n", "Iteration No: 43 started. Searching for the next optimal point.\n" ] }, @@ -12745,7 +10708,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:55:22,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:50:51,673\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12753,9 +10716,9 @@ "output_type": "stream", "text": [ "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1085\n", - "Function value obtained: -64.2411\n", - "Current minimum: -64.2411\n", + "Time taken: 9.3922\n", + "Function value obtained: -46.5495\n", + "Current minimum: -48.4500\n", "Iteration No: 44 started. Searching for the next optimal point.\n" ] }, @@ -12763,7 +10726,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:55:30,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:51:01,066\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12771,9 +10734,9 @@ "output_type": "stream", "text": [ "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4671\n", - "Function value obtained: -68.1196\n", - "Current minimum: -68.1196\n", + "Time taken: 9.7832\n", + "Function value obtained: -46.3355\n", + "Current minimum: -48.4500\n", "Iteration No: 45 started. Searching for the next optimal point.\n" ] }, @@ -12781,7 +10744,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:55:39,322\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:51:10,843\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12789,9 +10752,9 @@ "output_type": "stream", "text": [ "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2507\n", - "Function value obtained: -66.5993\n", - "Current minimum: -68.1196\n", + "Time taken: 9.3502\n", + "Function value obtained: -46.5732\n", + "Current minimum: -48.4500\n", "Iteration No: 46 started. Searching for the next optimal point.\n" ] }, @@ -12799,7 +10762,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:55:47,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:51:20,213\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12807,9 +10770,9 @@ "output_type": "stream", "text": [ "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0281\n", - "Function value obtained: -66.7937\n", - "Current minimum: -68.1196\n", + "Time taken: 9.7277\n", + "Function value obtained: -46.9420\n", + "Current minimum: -48.4500\n", "Iteration No: 47 started. Searching for the next optimal point.\n" ] }, @@ -12817,7 +10780,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:55:56,587\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:51:29,953\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12825,9 +10788,9 @@ "output_type": "stream", "text": [ "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8776\n", - "Function value obtained: -2.5539\n", - "Current minimum: -68.1196\n", + "Time taken: 9.5000\n", + "Function value obtained: -45.7326\n", + "Current minimum: -48.4500\n", "Iteration No: 48 started. Searching for the next optimal point.\n" ] }, @@ -12835,7 +10798,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:56:05,476\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:51:39,471\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12843,9 +10806,9 @@ "output_type": "stream", "text": [ "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9121\n", - "Function value obtained: -67.5293\n", - "Current minimum: -68.1196\n", + "Time taken: 9.8745\n", + "Function value obtained: -45.8471\n", + "Current minimum: -48.4500\n", "Iteration No: 49 started. Searching for the next optimal point.\n" ] }, @@ -12853,7 +10816,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:56:14,410\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:51:49,357\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12861,9 +10824,9 @@ "output_type": "stream", "text": [ "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1004\n", - "Function value obtained: -45.8205\n", - "Current minimum: -68.1196\n", + "Time taken: 9.6378\n", + "Function value obtained: -46.9230\n", + "Current minimum: -48.4500\n", "Iteration No: 50 started. Searching for the next optimal point.\n" ] }, @@ -12871,7 +10834,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-25 17:56:23,505\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-04-25 18:51:58,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -12879,17 +10842,17 @@ "output_type": "stream", "text": [ "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0912\n", - "Function value obtained: -34.1005\n", - "Current minimum: -68.1196\n", - "CPU times: user 7min 13s, sys: 9min 45s, total: 16min 58s\n", - "Wall time: 6min 58s\n" + "Time taken: 9.5251\n", + "Function value obtained: -45.7893\n", + "Current minimum: -48.4500\n", + "CPU times: user 7min 10s, sys: 10min 10s, total: 17min 20s\n", + "Wall time: 7min 49s\n" ] }, { "data": { "text/plain": [ - "(-68.11960248259545, [0.0, 0.4341115767435898, 0.5087638530904239])" + "(-48.44995861931082, [-5.0, 0.7853961999069485, 0.05886258745624268])" ] }, "execution_count": 6, @@ -12905,7 +10868,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "c1d240ba-15c2-47d3-909b-317951d5406e", "metadata": {}, "outputs": [], @@ -12935,7 +10898,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "id": "6b906bea-4b04-4e17-9441-b3bfd0c32623", "metadata": { "scrolled": true @@ -12964,7 +10927,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "id": "53cd6279-088f-4736-8b31-be4d26495ede", "metadata": {}, "outputs": [ @@ -12975,13 +10938,13 @@ " )" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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", + "image/png": 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" - ], - "text/plain": [ - " 0\n", - "0 46.167234\n", - "1 13.035419\n", - "2 52.331254\n", - "3 18.609789\n", - "4 39.136333" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "esc_df_mwt.head()" + "## Noiseless" ] }, { "cell_type": "code", "execution_count": null, - "id": "4eaacf4b-d485-4668-92b5-a76b2c1d7992", + "id": "906ae44e-fc60-4dfd-9209-00a5a8c4765f", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "CONFIG_NOISELESS = {\n", + " ''\n", + "}" + ] } ], "metadata": { diff --git a/notebooks/popdyn_tests.ipynb b/notebooks/popdyn_tests.ipynb index aba4610..24fb923 100644 --- a/notebooks/popdyn_tests.ipynb +++ b/notebooks/popdyn_tests.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "648c8aa8-6386-4a6a-b1ea-1ffe407623bd", "metadata": { "collapsed": true, @@ -33,8 +33,7 @@ "\u001b[?25hRequirement already satisfied: gymnasium in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (0.28.1)\n", "Requirement already satisfied: numpy in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (1.26.4)\n", "Requirement already satisfied: matplotlib in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (3.8.4)\n", - "Collecting typing (from rl4fisheries==1.0.0)\n", - " Using cached typing-3.7.4.3-py3-none-any.whl\n", + "Requirement already satisfied: typing in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (3.7.4.3)\n", "Requirement already satisfied: polars in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (0.20.21)\n", "Requirement already satisfied: tqdm in /opt/venv/lib/python3.10/site-packages (from rl4fisheries==1.0.0) (4.66.2)\n", "Requirement already satisfied: jax-jumpy>=1.0.0 in /opt/venv/lib/python3.10/site-packages (from gymnasium->rl4fisheries==1.0.0) (1.0.0)\n", @@ -52,11 +51,15 @@ "Requirement already satisfied: six>=1.5 in /opt/venv/lib/python3.10/site-packages (from python-dateutil>=2.7->matplotlib->rl4fisheries==1.0.0) (1.16.0)\n", "Building wheels for collected packages: rl4fisheries\n", " Building editable for rl4fisheries (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for rl4fisheries: filename=rl4fisheries-1.0.0-0.editable-py3-none-any.whl size=2322 sha256=2f9f00a1bb6053567050d7fa7953167bf454e0d7177265e63ad9c43f43b15507\n", - " Stored in directory: /tmp/pip-ephem-wheel-cache-gn1d9bpy/wheels/55/1e/4a/9e3b1ec27a9439b41651c9753798340778b03ddfad8f7fc0af\n", + "\u001b[?25h Created wheel for rl4fisheries: filename=rl4fisheries-1.0.0-0.editable-py3-none-any.whl size=2322 sha256=167f8ef7c72ffd6b586e3626261ae93f9f2177918983d5de0bd6d65593f74c40\n", + " Stored in directory: /tmp/pip-ephem-wheel-cache-y5wprx9q/wheels/55/1e/4a/9e3b1ec27a9439b41651c9753798340778b03ddfad8f7fc0af\n", "Successfully built rl4fisheries\n", - "Installing collected packages: typing, rl4fisheries\n", - "Successfully installed rl4fisheries-1.0.0 typing-3.7.4.3\n", + "Installing collected packages: rl4fisheries\n", + " Attempting uninstall: rl4fisheries\n", + " Found existing installation: rl4fisheries 1.0.0\n", + " Uninstalling rl4fisheries-1.0.0:\n", + " Successfully uninstalled rl4fisheries-1.0.0\n", + "Successfully installed rl4fisheries-1.0.0\n", "Note: you may need to restart the kernel to use updated packages.\n" ] } @@ -67,7 +70,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 1, "id": "3638cfd4-177b-4b24-b6a4-8d61d74faf80", "metadata": {}, "outputs": [], @@ -77,24 +80,26 @@ "from typing import List, Text, Optional\n", "\n", "from rl4fisheries import Msy, ConstEsc, CautionaryRule, AsmEnv\n", - "from rl4fisheries.envs.asm_fns import get_r_devs" + "from rl4fisheries.envs.asm_fns import get_r_devs, get_r_devs_v2" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 5, "id": "c1131bf0-840c-4a40-b111-f3d74351795a", "metadata": {}, "outputs": [], "source": [ - "config = {'s':0.86, 'reproducibility_mode': True}\n", + "r_devs = get_r_devs(n_year=1000)\n", + "\n", + "config = {'reproducibility_mode': True, \"r_devs\": r_devs}\n", "env = AsmEnv(config=config)\n", "_ = env.reset()" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 6, "id": "eb58ebf3-882d-4944-9e19-2332f3133a18", "metadata": {}, "outputs": [], @@ -133,7 +138,7 @@ " * (obs[1]+1)/2\n", " )\n", " )\n", - " simulation['act'].append(act[0])\n", + " simulation['act'].append((1+act[0])/2)\n", " simulation['rew'].append(rew)\n", " simulation['total_pop'].append(np.sum(env.state))\n", " simulation['newborns'].append(env.state[0])\n", @@ -152,7 +157,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 7, "id": "9ab73841-a5f3-4704-ab7c-0a71ca683a90", "metadata": {}, "outputs": [], @@ -180,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 8, "id": "a634dbf5-00af-44d8-b2d9-5ede8969e3e7", "metadata": {}, "outputs": [], @@ -191,7 +196,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 10, "id": "6f4dc7c8-47d3-414f-bc97-d6c2290d455c", "metadata": {}, "outputs": [], @@ -201,23 +206,23 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 11, "id": "9bbd93d1-ef39-423d-84ae-3367dfcb6511", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 28, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -227,28 +232,54 @@ } ], "source": [ - "trivial_ep.plot(x='t', y = ['surv_vul_b'], title='populations')" + "trivial_ep.plot(x='t', y = ['surv_vul_b', 'mean_wt_obs'])" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 48, "id": "1e7fab6a-0ca1-41ad-83f2-17c6eeee69bd", + "metadata": { + "jupyter": { + "source_hidden": true + } + }, + "outputs": [], + "source": [ + "# trivial_ep.plot(\n", + "# x='surv_vul_b', y = 'mean_wt_obs', \n", + "# title='Total population over time', \n", + "# # kind='scatter',\n", + "# )" + ] + }, + { + "cell_type": "markdown", + "id": "7de3ce71-70a5-4972-aae0-12c8ba14d2c8", + "metadata": {}, + "source": [ + "## Optimal escapement" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "5488a622-d16c-4d82-a4fa-4501107e5580", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 30, + "execution_count": 73, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -258,40 +289,30 @@ } ], "source": [ - "trivial_ep.plot(\n", - " x='surv_vul_b', y = 'mean_wt_obs', \n", - " title='Total population over time', \n", - " kind='scatter',\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "7de3ce71-70a5-4972-aae0-12c8ba14d2c8", - "metadata": {}, - "source": [ - "## Optimal escapement" + "esc = ConstEsc(env=env, escapement = 10 ** (-0.083743))\n", + "esc_ep = pd.DataFrame(simulate_ep(env, esc, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))\n", + "esc_ep.plot(x='t', y = ['surv_vul_b', 'act'], title='total pop. over time under optimal escapement')" ] }, { "cell_type": "code", - "execution_count": 9, - "id": "5488a622-d16c-4d82-a4fa-4501107e5580", + "execution_count": 74, + "id": "9583a2bf-2357-4b5d-92fb-86c274bcb862", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 74, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -301,16 +322,20 @@ } ], "source": [ - "esc = ConstEsc(env=env, escapement = 0.010338225232077163)\n", - "esc_ep = pd.DataFrame(simulate_ep(env, esc, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))\n", - "esc_ep.plot(x='t', y = ['total_pop'], title='total pop. over time under optimal escapement', logy=True)" + "esc_ep[esc_ep.t>0].plot(x='surv_vul_b', y = 'rew', kind='scatter')" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 24, "id": "3bc2f53d-94be-4fa8-916f-88f6e9eb57f2", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true, + "source_hidden": true + } + }, "outputs": [ { "data": { @@ -318,13 +343,13 @@ "" ] }, - "execution_count": 31, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -343,40 +368,35 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 51, "id": "a9204098-6d56-4a58-b77d-9af8cbef4613", "metadata": {}, "outputs": [], "source": [ "from stable_baselines3 import PPO\n", "\n", - "PPO_CONFIG = { \n", - " \"observation_fn_id\": 'observe_2o',\n", - " \"n_observs\": 2,\n", - "}\n", - "\n", - "ppo = PPO.load(\"../saved_agents/PPO-AsmEnv-2o.zip\", env=AsmEnv(config=PPO_CONFIG), device='cpu')" + "ppo = PPO.load(\"../saved_agents/PPO-AsmEnv-2o.zip\", env=AsmEnv(config=config), device='cpu')" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 52, "id": "aa0ef25f-8e6e-48c0-9d91-fbb90969290b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -387,28 +407,28 @@ ], "source": [ "ppo_ep = pd.DataFrame(simulate_ep(env, ppo, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))\n", - "ppo_ep.plot(x='t', y = ['total_pop'], title='total pop. over time under optimal escapement', logy=True)" + "ppo_ep.plot(x='t', y = ['surv_vul_b', 'act'], title='vul. biomass over time under PPO management')" ] }, { "cell_type": "code", - "execution_count": 33, - "id": "4024227f-1e2f-468d-8151-8f3759e92ce3", + "execution_count": 57, + "id": "8bee46bf-a620-44e9-9bce-0e4e50cfd902", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 33, + "execution_count": 57, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -418,14 +438,20 @@ } ], "source": [ - "ppo_ep.plot(x='t', y = ['rew'], title='harvest over time under RL policy')" + "ppo_ep.plot(x='surv_vul_b', y = 'rew', kind='scatter')" ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 36, "id": "e64e134e-44f4-4546-9b7c-ee3031ba8f69", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true, + "source_hidden": true + } + }, "outputs": [ { "data": { @@ -433,13 +459,13 @@ "" ] }, - "execution_count": 34, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -458,36 +484,86 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 75, "id": "489d45a2-0708-4626-9210-3e0c9207cf15", - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "-0.982, -0.970, -0.418\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ + "cr_preargs = {'log_radius': 0, 'theta': 0.785396, 'y2':0.22641}\n", + "\n", "cr_args = {\n", - " 'x1': 50 * 0.009159055923137423,\n", - " 'x2': 50 * 0.015139834077385755,\n", - " 'y2': 0.29119675741251316,\n", + " 'x1': (10 ** cr_preargs['log_radius']) * np.sin(cr_preargs['theta']),\n", + " 'x2': (10 ** cr_preargs['log_radius']) * np.cos(cr_preargs['theta']),\n", + " 'y2': cr_preargs['y2'],\n", "}\n", "cr = CautionaryRule(env=env, **cr_args)\n", "cr_ep = pd.DataFrame(simulate_ep(env, cr, other_vars=['ssb', 'surv_vul_b', 'harv_vul_b', 'state']))\n", - "# cr_ep.plot(x='t', y = ['act'], title='total pop. over time under CR')" + "cr_ep.plot(x='t', y = ['surv_vul_b', 'act'], title='total pop. over time under CR')" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "id": "8958c1b5-a6a6-4195-9db0-88502370bf89", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cr_ep.plot(x='surv_vul_b', y = 'rew', kind='scatter')" ] }, { "cell_type": "code", "execution_count": 37, "id": "133dd750-22e1-4895-a4c7-87b87199ffc6", - "metadata": {}, + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true, + "source_hidden": true + } + }, "outputs": [ { "data": { @@ -518,6 +594,95 @@ ")" ] }, + { + "cell_type": "code", + "execution_count": 39, + "id": "4024227f-1e2f-468d-8151-8f3759e92ce3", + "metadata": {}, + "outputs": [], + "source": [ + "def reward_cumulative_dist(df):\n", + " sorted_rews = pd.Series(-np.sort(-df.rew))\n", + " total_reward = np.sum(sorted_rews)\n", + " return pd.DataFrame(sorted_rews.cumsum()/total_reward)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "6700f4fb-b392-4166-887e-814fc6cbefb4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(6.509983972560702, 42.254150074129974, 33.10548271172751)" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sum(esc_ep.rew), sum(cr_ep.rew), sum(ppo_ep.rew), " + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "83c039fa-cc98-43e9-806c-6bcd9e50d41c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(, , )" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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JVt0bnRVcMdLiSgAAsI7fYWTu3Lmqra3V8uXL5XK5NG3aNG3ZssU3qbWysrJHT8hDDz0km82mhx56SMePH9eoUaM0e/ZsPfbYY4H7FWGq3BdGMiyuBAAA69hMGIyVuN1upaWlqaGhQampqVaXExCnmto0/dGtkqTtDxZqVErkz5EBAESX/t6/WUtqkT8d6uwVmZCZTBABAEQ1wohFyrvCyCzmiwAAohxhxCLvMF8EAABJhBFL1LhbdLDmjGw26frL2QIeABDdCCMW6B6imTQ6VelJ8RZXAwCAtQgjFuievFpwOfNFAAAgjFhg2+F6SVI+YQQAAMJIqNWdadWfa5skSdflDre4GgAArEcYCbEdRzp7Ra52pjBfBAAAEUZC7t2uIZqZ41lFAwCARBgJue1dPSPXEUYAAJBEGAkpd0u7PjrhliTNzCWMAAAgEUZCquLoKXmNNG5EkrLSEqwuBwCAIYEwEkLbmS8CAMAFCCMhtI0wAgDABQgjIdLS7tH7xxokMV8EAIBPI4yEyPvHGtTm8WpUikOXjUyyuhwAAIYMwkiI7K46JUmaMW64bDabxdUAADB0EEZCZHfVaUnS1Jx0S+sAAGCoIYyEyHtVnfNFphFGAADogTASAjWNLTp++qxsNmnK2DSrywEAYEghjIRAd6/IhMxkJTtiLa4GAIChhTASAt2TVxmiAQDgQoSREOjeX+TasenWFgIAwBBEGAkyY4z2HO8MI1OymS8CAMD5CCNBdqKhRaea2xVrt+nqrBSrywEAYMghjATZB11DNBOcKUqIi7G4GgAAhh7CSJCdG6JJtbgSAACGJsJIkH3AfBEAAC6KMBJEn568+hnCCAAAvSKMBJHL3aKTTW2Ksds0aTTDNAAA9IYwEkS+yauZyUxeBQCgD4SRIOoeopnMEA0AAH0ijARR9+TVyWMYogEAoC+EkSD66BO3JHpGAAC4GMJIkJxublO1u1WS2HkVAICLIIwEyV5XoyQpOz1RKQlxFlcDAMDQRRgJkn1dYWQivSIAAFwUYSRIuntGGKIBAODiCCNBss/VOXmVMAIAwMURRoLAGKP91WckSROzWNYLAMDFEEaC4PjpszrT2qG4GJvGZwyzuhwAAIY0wkgQdE9evTwjWfGxNDEAABfDnTIImLwKAED/EUaCYB9hBACAfiOMBAF7jAAA0H+EkQBr6/Dqz7WdK2noGQEA4NIIIwF2uK5JHV6jFEesstMTrS4HAIAhjzASYHu7Nju7KitFNpvN4moAABj6CCMB1j1f5ConQzQAAPQHYSTADtR0zhe5yplscSUAAIQHwkiA/bkrjEzIpGcEAID+IIwEUGuHR0frmyVJV2bSMwIAQH8QRgLoSF2zPF6jZEesnKkOq8sBACAsEEYC6GDXEM2VmcmspAEAoJ8IIwH06TACAAD6hzASQAdrCSMAAPiLMBJAB6o79xi5chRhBACA/hpQGFmzZo1yc3OVkJCg/Px8bdu27aLnnz59WosWLdLo0aPlcDh01VVXafPmzQMqeKjyeI0O1TVJkiawxwgAAP0W6+8FGzduVElJidauXav8/HytXr1aRUVF2rdvnzIzMy84v62tTV/60peUmZmpF198UdnZ2Tp69KjS09MDUf+QcexUs9o6vIqPtWvs8CSrywEAIGz4HUZWrVqlhQsXqri4WJK0du1abdq0SevXr9fSpUsvOH/9+vWqr6/XO++8o7i4OElSbm7u4Koegronr16eMUwxdlbSAADQX34N07S1tamiokKFhYXnPsBuV2FhocrLy3u95re//a0KCgq0aNEiOZ1OTZ48WY8//rg8Hk+f39Pa2iq3293jNdQdYCUNAAAD4lcYqaurk8fjkdPp7HHc6XTK5XL1es2hQ4f04osvyuPxaPPmzXr44Yf1xBNP6Cc/+Umf31NaWqq0tDTfKycnx58yLXGQbeABABiQoK+m8Xq9yszM1FNPPaUZM2Zo7ty5evDBB7V27do+r1m2bJkaGhp8r6qqqmCXOWjsMQIAwMD4NWckIyNDMTExqq6u7nG8urpaWVlZvV4zevRoxcXFKSYmxnfsmmuukcvlUltbm+Lj4y+4xuFwyOEIn+3UjTGEEQAABsivnpH4+HjNmDFDZWVlvmNer1dlZWUqKCjo9ZobbrhBBw8elNfr9R3bv3+/Ro8e3WsQCUfV7ladae2Q3SblZrCSBgAAf/g9TFNSUqJ169bp3//93/Xxxx/rnnvuUVNTk291zfz587Vs2TLf+ffcc4/q6+u1ePFi7d+/X5s2bdLjjz+uRYsWBe5XWOzPXTuvXjZymByxMZc4GwAAfJrfS3vnzp2r2tpaLV++XC6XS9OmTdOWLVt8k1orKytlt5/LODk5OXrttdd033336dprr1V2drYWL16s+++/P3C/wmJHTnZudjY+Y5jFlQAAEH5sxhhjdRGX4na7lZaWpoaGBqWmplpdzgUe3/yxnnrrkIpvyNWK2Z+xuhwAAIaE/t6/eTZNABzp2gY+dyQ9IwAA+IswEgBHTzZLksaNZPIqAAD+IowMkjFGR+vpGQEAYKAII4NU09iqlnavYuw2ZacnWl0OAABhhzAySN3zRbLTExUfS3MCAOAv7p6DdLS+c77IZcwXAQBgQAgjg3S0a48RwggAAANDGBmkI10raZi8CgDAwBBGBqnyZPcwDWEEAICBIIwMgjHGtxU8wzQAAAwMYWQQTjW3q7GlQ5I0bgRhBACAgSCMDEJ3r8jotAQlxPG0XgAABoIwMgjn5ovQKwIAwEARRgbBN19kBJNXAQAYKMLIIHQ/IO+yDHpGAAAYKMLIIHRveMYeIwAADBxhZBCOMmcEAIBBI4wMUGNLu042tUliwzMAAAaDMDJA3b0iGcnxSnbEWlwNAADhizAyQEfZBh4AgIAgjAzQ0fruZb3MFwEAYDAIIwNUVX9WkjSWMAIAwKAQRgbo2KnOYZqc4YkWVwIAQHgjjAxQZX1XGKFnBACAQSGMDIDHa3TidOcwDU/rBQBgcAgjA+Byt6jdYxQXY5MzNcHqcgAACGuEkQGo6hqiyU5PVIzdZnE1AACEN8LIAFQxXwQAgIAhjAxA1amuZb3DCSMAAAwWYWQAjvl6RljWCwDAYBFGBqDKt8cIPSMAAAwWYWQATpxukSRls+EZAACDRhjxk8dr5HJ3hpExaYQRAAAGizDip9rGVnm8RrF2m0alOKwuBwCAsEcY8dPxrp1XnakJ7DECAEAAEEb89ElDZxgZk87OqwAABAJhxE+fdE1eHc18EQAAAoIw4qcTXT0jo+kZAQAgIAgjfuruGWElDQAAgUEY8VP3nJHRafSMAAAQCIQRPx3v7hlJp2cEAIBAIIz4obXDo7ozrZLoGQEAIFAII36obugMIo5Yu0YMi7e4GgAAIgNhxA8nfHuMJMpmY8MzAAACgTDiByavAgAQeIQRP5xgwzMAAAKOMOKHE6fZCh4AgEAjjPjhkwZ6RgAACDTCiB/oGQEAIPAII37o7hlhwzMAAAKHMNJPzW0dajjbLknKYjUNAAABQxjpp2p354Znw+JjlJoQZ3E1AABEDsJIP7m6hmicqfSKAAAQSISRfqppJIwAABAMhJF+Otcz4rC4EgAAIgthpJ+654w4mbwKAEBAEUb6qdrd1TOSQhgBACCQCCP91B1GWNYLAEBgDSiMrFmzRrm5uUpISFB+fr62bdvWr+s2bNggm82mOXPmDORrLVXdyJwRAACCwe8wsnHjRpWUlGjFihXauXOnpk6dqqKiItXU1Fz0uiNHjujv//7vddNNNw24WKsYY87NGWE1DQAAAeV3GFm1apUWLlyo4uJiTZo0SWvXrlVSUpLWr1/f5zUej0fz5s3TI488ossvv3xQBVvhdHO72jq8kqRM5owAABBQfoWRtrY2VVRUqLCw8NwH2O0qLCxUeXl5n9f9+Mc/VmZmpu66665+fU9ra6vcbnePl5VcXfNFRg6LV3ws02wAAAgkv+6sdXV18ng8cjqdPY47nU65XK5er3n77bf161//WuvWrev395SWliotLc33ysnJ8afMgOuevJrJEA0AAAEX1P+b39jYqDvvvFPr1q1TRkZGv69btmyZGhoafK+qqqogVnlpvpU0TF4FACDgYv05OSMjQzExMaquru5xvLq6WllZWRec/+c//1lHjhzR7Nmzfce83s65F7Gxsdq3b5+uuOKKC65zOBxyOIbOjZ/JqwAABI9fPSPx8fGaMWOGysrKfMe8Xq/KyspUUFBwwfkTJ07UBx98oN27d/teX/3qV3XzzTdr9+7dlg+/9JeLYRoAAILGr54RSSopKdGCBQuUl5enmTNnavXq1WpqalJxcbEkaf78+crOzlZpaakSEhI0efLkHtenp6dL0gXHh7Ia3zANYQQAgEDzO4zMnTtXtbW1Wr58uVwul6ZNm6YtW7b4JrVWVlbKbo+sFSfnhmmGztARAACRwmaMMVYXcSlut1tpaWlqaGhQampqyL//usf+V7WNrXr1+zdqcnZayL8fAIBw1N/7d2R1YQRBh8erujNMYAUAIFgII5dQe6ZVxkixdptGDou3uhwAACIOYeQSuueLZKY4ZLfbLK4GAIDIQxi5BHZfBQAguAgjl1DbeK5nBAAABB5h5BJqusLIKMIIAABBQRi5hHM9IwzTAAAQDISRS6ilZwQAgKAijFxCbWPnBFbCCAAAwUEYuQR6RgAACC7CyEUYY1R7htU0AAAEE2HkIhrOtqvd0/nonpHJ7L4KAEAwEEYuontZb3pSnByxMRZXAwBAZCKMXIRvvkgyQzQAAAQLYeQifHuMpBJGAAAIFsLIRdAzAgBA8BFGLqKGPUYAAAg6wshFsMcIAADBRxi5iHN7jPBcGgAAgoUwchE1bnpGAAAINsLIRXT3jBBGAAAIHsJIH1o7PDrd3C6JreABAAgmwkgfTp5pkyTFxdiUlhhncTUAAEQuwkgfaj61x4jNZrO4GgAAIhdhpA8s6wUAIDQII304F0ZY1gsAQDARRvrA7qsAAIQGYaQPdd3LepPjLa4EAIDIRhjpQ31T52qakTwkDwCAoCKM9KHuTHcYoWcEAIBgIoz04WTXMM2IYYQRAACCiTDSh5NdwzQZDNMAABBUhJFedHi8vq3gR9IzAgBAUBFGelHf3NkrYrdJ6UmEEQAAgokw0ovu59IMT4pXjJ2t4AEACCbCSC/OLeulVwQAgGAjjPSie8OzkcOYvAoAQLARRnrRPUwzgp4RAACCjjDSi5NNnT0jGaykAQAg6AgjvWAreAAAQocw0ovureDZfRUAgOAjjPSieyv4DOaMAAAQdISRXjBMAwBA6BBGenGSYRoAAEKGMHKe1g6PGls7JEkZ7DMCAEDQEUbO0z1EE2u3KTUx1uJqAACIfISR83x6iMZm47k0AAAEG2HkPL6t4Jm8CgBASBBGztPdM8KyXgAAQoMwch7fsl5W0gAAEBKEkfPUdT2XZgQraQAACAnCyHm6h2lGMkwDAEBIEEbO0z1Mw5wRAABCgzBynu7n0jBMAwBAaBBGzlPHMA0AACFFGDnPya4JrGwFDwBAaBBGPqW5rUMt7V5J0gh6RgAACIkBhZE1a9YoNzdXCQkJys/P17Zt2/o8d926dbrppps0fPhwDR8+XIWFhRc930rdK2kcsXYNi4+xuBoAAKKD32Fk48aNKikp0YoVK7Rz505NnTpVRUVFqqmp6fX8N998U3fccYfeeOMNlZeXKycnR7fccouOHz8+6OIDrXsr+IxkB8+lAQAgRPwOI6tWrdLChQtVXFysSZMmae3atUpKStL69et7Pf/ZZ5/V9773PU2bNk0TJ07Ur371K3m9XpWVlQ26+EA71dzZMzJ8WJzFlQAAED38CiNtbW2qqKhQYWHhuQ+w21VYWKjy8vJ+fUZzc7Pa29s1YsQI/yoNgfqmdknS8CTmiwAAECqx/pxcV1cnj8cjp9PZ47jT6dTevXv79Rn333+/xowZ0yPQnK+1tVWtra2+P7vdbn/KHLBTXRuejeC5NAAAhExIV9OsXLlSGzZs0Msvv6yEhIQ+zystLVVaWprvlZOTE5L6fMM09IwAABAyfoWRjIwMxcTEqLq6usfx6upqZWVlXfTaf/7nf9bKlSv1+9//Xtdee+1Fz122bJkaGhp8r6qqKn/KHDDCCAAAoedXGImPj9eMGTN6TD7tnoxaUFDQ53U//elP9eijj2rLli3Ky8u75Pc4HA6lpqb2eIXCqe45I0xgBQAgZPyaMyJJJSUlWrBggfLy8jRz5kytXr1aTU1NKi4uliTNnz9f2dnZKi0tlST94z/+o5YvX67nnntOubm5crlckqTk5GQlJycH8KcMXj09IwAAhJzfYWTu3Lmqra3V8uXL5XK5NG3aNG3ZssU3qbWyslJ2+7kOlyeffFJtbW362te+1uNzVqxYoX/4h38YXPUBdpowAgBAyNmMMcbqIi7F7XYrLS1NDQ0NQR2yyfvJ/6ruTKs2/d2N+syYtKB9DwAA0aC/92+eTdPFGOPrGWFpLwAAoUMY6dLY2qEOb2cnEcM0AACEDmGky+mulTSJcTFKiOMheQAAhAphpMu5lTQs6wUAIJQII13OPSSPIRoAAEKJMNKl+7k0zBcBACC0CCNdTjV3775KGAEAIJQII13O9YwwZwQAgFAijHThIXkAAFiDMNLlFKtpAACwBGGky7kn9tIzAgBAKBFGujBMAwCANQgjXU7xXBoAACxBGFHnQ/K6h2nSmTMCAEBIEUYkNbd51ObxSqJnBACAUCOMSKrv2mPEEWtXIg/JAwAgpAgj6jl51WazWVwNAADRhTAitoIHAMBKhBGxFTwAAFYijOhTwzT0jAAAEHKEEdEzAgCAlQgjOjdnZAS7rwIAEHKEEUn1XcM06YQRAABCjjAi6TRbwQMAYBnCiKR6toIHAMAyhBHRMwIAgJUIIzq3Hfxw5owAABByUR9GWto9au3ofEheaiLDNAAAhFrUhxF3S+d8EZtNSnHEWlwNAADRhzBytjOMpCbEyW7nIXkAAIRa1IeRhrMdkqTURHpFAACwQtSHke6ekTTmiwAAYImoDyMNhBEAACwV9WGkewJragJhBAAAK0R9GGlopmcEAAArRX0Y8fWMEEYAALBE1IcR5owAAGAtwshZekYAALBS1IcRd/c+IwnsMwIAgBWiPowwTAMAgLWiPox0T2AljAAAYI2oDyPMGQEAwFpRHUY8XqPGls45I/SMAABgjagOI2e6gojEDqwAAFglqsNI9xBNYlyM4mOjuikAALBMVN+BWUkDAID1ojqMnNsKnj1GAACwSlSHEXpGAACwXlSHEXf3sl4mrwIAYJmoDiP0jAAAYD3CiNjwDAAAK0V1GDk3gZUwAgCAVaI6jDScZfdVAACsFtVhxM2cEQAALBfVYcQ3ZySBfUYAALBKVN+F516Xo/zLR+jKzGSrSwEAIGpFdRi5Y+Y4q0sAACDqRfUwDQAAsN6AwsiaNWuUm5urhIQE5efna9u2bRc9/4UXXtDEiROVkJCgKVOmaPPmzQMqFgAARB6/w8jGjRtVUlKiFStWaOfOnZo6daqKiopUU1PT6/nvvPOO7rjjDt11113atWuX5syZozlz5mjPnj2DLh4AAIQ/mzHG+HNBfn6+rrvuOv3iF7+QJHm9XuXk5Oj73/++li5desH5c+fOVVNTk1599VXfseuvv17Tpk3T2rVr+/WdbrdbaWlpamhoUGpqqj/lAgAAi/T3/u1Xz0hbW5sqKipUWFh47gPsdhUWFqq8vLzXa8rLy3ucL0lFRUV9ni9Jra2tcrvdPV4AACAy+RVG6urq5PF45HQ6exx3Op1yuVy9XuNyufw6X5JKS0uVlpbme+Xk5PhTJgAACCNDcjXNsmXL1NDQ4HtVVVVZXRIAAAgSv/YZycjIUExMjKqrq3scr66uVlZWVq/XZGVl+XW+JDkcDjkcDn9KAwAAYcqvnpH4+HjNmDFDZWVlvmNer1dlZWUqKCjo9ZqCgoIe50vS1q1b+zwfAABEF793YC0pKdGCBQuUl5enmTNnavXq1WpqalJxcbEkaf78+crOzlZpaakkafHixfr85z+vJ554Qrfddps2bNigHTt26KmnngrsLwEAAGHJ7zAyd+5c1dbWavny5XK5XJo2bZq2bNnim6RaWVkpu/1ch8usWbP03HPP6aGHHtIDDzygCRMm6JVXXtHkyZMD9ysAAEDY8nufESuwzwgAAOEnKPuMAAAABFpYPLW3u/OGzc8AAAgf3fftSw3ChEUYaWxslCQ2PwMAIAw1NjYqLS2tz/fDYs6I1+vViRMnlJKSIpvNFrDPdbvdysnJUVVVFXNRgoy2Dg3aOTRo59CgnUMnWG1tjFFjY6PGjBnTY3HL+cKiZ8Rut2vs2LFB+/zU1FT+ix4itHVo0M6hQTuHBu0cOsFo64v1iHRjAisAALAUYQQAAFgqqsOIw+HQihUreA5OCNDWoUE7hwbtHBq0c+hY3dZhMYEVAABErqjuGQEAANYjjAAAAEsRRgAAgKUIIwAAwFJRHUbWrFmj3NxcJSQkKD8/X9u2bbO6pLBRWlqq6667TikpKcrMzNScOXO0b9++Hue0tLRo0aJFGjlypJKTk/XXf/3Xqq6u7nFOZWWlbrvtNiUlJSkzM1M//OEP1dHREcqfElZWrlwpm82mJUuW+I7RzoFz/PhxffOb39TIkSOVmJioKVOmaMeOHb73jTFavny5Ro8ercTERBUWFurAgQM9PqO+vl7z5s1Tamqq0tPTddddd+nMmTOh/ilDlsfj0cMPP6zx48crMTFRV1xxhR599NEezy6hnQfmrbfe0uzZszVmzBjZbDa98sorPd4PVLu+//77uummm5SQkKCcnBz99Kc/HXzxJkpt2LDBxMfHm/Xr15sPP/zQLFy40KSnp5vq6mqrSwsLRUVF5umnnzZ79uwxu3fvNl/+8pfNuHHjzJkzZ3zn3H333SYnJ8eUlZWZHTt2mOuvv97MmjXL935HR4eZPHmyKSwsNLt27TKbN282GRkZZtmyZVb8pCFv27ZtJjc311x77bVm8eLFvuO0c2DU19ebyy67zHzrW98y7777rjl06JB57bXXzMGDB33nrFy50qSlpZlXXnnFvPfee+arX/2qGT9+vDl79qzvnL/4i78wU6dONX/605/MH//4R3PllVeaO+64w4qfNCQ99thjZuTIkebVV181hw8fNi+88IJJTk42P//5z33n0M4Ds3nzZvPggw+al156yUgyL7/8co/3A9GuDQ0Nxul0mnnz5pk9e/aY3/zmNyYxMdH827/926Bqj9owMnPmTLNo0SLfnz0ejxkzZowpLS21sKrwVVNTYySZP/zhD8YYY06fPm3i4uLMCy+84Dvn448/NpJMeXm5Mabzfzh2u924XC7fOU8++aRJTU01ra2tof0BQ1xjY6OZMGGC2bp1q/n85z/vCyO0c+Dcf//95sYbb+zzfa/Xa7Kyssw//dM/+Y6dPn3aOBwO85vf/MYYY8xHH31kJJnt27f7zvmf//kfY7PZzPHjx4NXfBi57bbbzLe//e0ex/7qr/7KzJs3zxhDOwfK+WEkUO36y1/+0gwfPrzHvx3333+/ufrqqwdVb1QO07S1tamiokKFhYW+Y3a7XYWFhSovL7ewsvDV0NAgSRoxYoQkqaKiQu3t7T3aeOLEiRo3bpyvjcvLyzVlyhQ5nU7fOUVFRXK73frwww9DWP3Qt2jRIt1222092lOinQPpt7/9rfLy8vT1r39dmZmZmj59utatW+d7//Dhw3K5XD3aOi0tTfn5+T3aOj09XXl5eb5zCgsLZbfb9e6774buxwxhs2bNUllZmfbv3y9Jeu+99/T222/r1ltvlUQ7B0ug2rW8vFyf+9znFB8f7zunqKhI+/bt06lTpwZcX1g8KC/Q6urq5PF4evzjLElOp1N79+61qKrw5fV6tWTJEt1www2aPHmyJMnlcik+Pl7p6ek9znU6nXK5XL5zevs76H4PnTZs2KCdO3dq+/btF7xHOwfOoUOH9OSTT6qkpEQPPPCAtm/frr/7u79TfHy8FixY4Gur3try022dmZnZ4/3Y2FiNGDGCtu6ydOlSud1uTZw4UTExMfJ4PHrsscc0b948SaKdgyRQ7epyuTR+/PgLPqP7veHDhw+ovqgMIwisRYsWac+ePXr77betLiXiVFVVafHixdq6dasSEhKsLieieb1e5eXl6fHHH5ckTZ8+XXv27NHatWu1YMECi6uLHM8//7yeffZZPffcc/rMZz6j3bt3a8mSJRozZgztHMWicpgmIyNDMTExF6w4qK6uVlZWlkVVhad7771Xr776qt544w2NHTvWdzwrK0ttbW06ffp0j/M/3cZZWVm9/h10v4fOYZiamhp99rOfVWxsrGJjY/WHP/xB//Iv/6LY2Fg5nU7aOUBGjx6tSZMm9Th2zTXXqLKyUtK5trrYvxtZWVmqqanp8X5HR4fq6+tp6y4//OEPtXTpUv3t3/6tpkyZojvvvFP33XefSktLJdHOwRKodg3WvydRGUbi4+M1Y8YMlZWV+Y55vV6VlZWpoKDAwsrChzFG9957r15++WW9/vrrF3TbzZgxQ3FxcT3aeN++faqsrPS1cUFBgT744IMe/+XfunWrUlNTL7gpRKsvfvGL+uCDD7R7927fKy8vT/PmzfP9Z9o5MG644YYLlqfv379fl112mSRp/PjxysrK6tHWbrdb7777bo+2Pn36tCoqKnznvP766/J6vcrPzw/Brxj6mpubZbf3vPXExMTI6/VKop2DJVDtWlBQoLfeekvt7e2+c7Zu3aqrr756wEM0kqJ7aa/D4TDPPPOM+eijj8x3v/tdk56e3mPFAfp2zz33mLS0NPPmm2+aTz75xPdqbm72nXP33XebcePGmddff93s2LHDFBQUmIKCAt/73UtOb7nlFrN7926zZcsWM2rUKJacXsKnV9MYQzsHyrZt20xsbKx57LHHzIEDB8yzzz5rkpKSzH/913/5zlm5cqVJT083//3f/23ef/9985d/+Ze9Lo2cPn26effdd83bb79tJkyYEPVLTj9twYIFJjs727e096WXXjIZGRnmRz/6ke8c2nlgGhsbza5du8yuXbuMJLNq1Sqza9cuc/ToUWNMYNr19OnTxul0mjvvvNPs2bPHbNiwwSQlJbG0dzD+9V//1YwbN87Ex8ebmTNnmj/96U9WlxQ2JPX6evrpp33nnD171nzve98zw4cPN0lJSeb22283n3zySY/POXLkiLn11ltNYmKiycjIMD/4wQ9Me3t7iH9NeDk/jNDOgfO73/3OTJ482TgcDjNx4kTz1FNP9Xjf6/Wahx9+2DidTuNwOMwXv/hFs2/fvh7nnDx50txxxx0mOTnZpKammuLiYtPY2BjKnzGkud1us3jxYjNu3DiTkJBgLr/8cvPggw/2WCpKOw/MG2+80eu/ywsWLDDGBK5d33vvPXPjjTcah8NhsrOzzcqVKwddu82YT217BwAAEGJROWcEAAAMHYQRAABgKcIIAACwFGEEAABYijACAAAsRRgBAACWIowAAABLEUYAAIClCCMAAMBShBEAAGApwggAALAUYQQAAFjq/wPL/au3Qz276QAAAABJRU5ErkJggg==", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " reward_cumulative_dist(esc_ep).plot(),\n", + " reward_cumulative_dist(cr_ep).plot(),\n", + " reward_cumulative_dist(ppo_ep).plot(),\n", + ")" + ] + }, { "cell_type": "markdown", "id": "5ce8ea08-536d-45d4-b34e-26b9bdd97e29", From 42b272868455b238b114c55f1cc7c693d5b136a0 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 2 May 2024 18:37:13 +0000 Subject: [PATCH 25/64] hyperpars --- hyperpars/ppo-asm.yml | 13 +++++---- hyperpars/rppo-asm.yml | 64 +++++++++++++++++++++--------------------- hyperpars/tqc-asm.yml | 3 +- 3 files changed, 41 insertions(+), 39 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 4b2f98d..05f4cd8 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -5,15 +5,16 @@ algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' use_sde: True - batch_size: 128 - gamma: 0.995 - gae_lambda: 0.999 + # batch_size: 64 + # gamma: 0.995 + # gae_lambda: 0.999 # env env_id: "AsmEnv" config: - observation_fn_id: 'observe_1o' - n_observs: 1 + observation_fn_id: 'observe_2o' + n_observs: 2 + upow: 0.6 n_envs: 12 # io @@ -21,5 +22,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "1o-2" +id: "2o-upow0.6" additional_imports: [] \ No newline at end of file diff --git a/hyperpars/rppo-asm.yml b/hyperpars/rppo-asm.yml index b7227ca..c57a55f 100644 --- a/hyperpars/rppo-asm.yml +++ b/hyperpars/rppo-asm.yml @@ -2,15 +2,15 @@ # algo overall algo: "RPPO" -total_timesteps: 5000000 +total_timesteps: 35000000 additional_imports: ["torch"] # env overall env_id: "AsmEnv" config: - observation_fn_id: 'observe_2o' - n_observs: 2 + observation_fn_id: 'observe_1o' + n_observs: 1 n_envs: 12 # io @@ -24,15 +24,15 @@ save_path: "../saved_agents" # tensorboard_log: "../../../logs" # MY GUESS CONFIG -id: "minimal" -algo_config: - policy: 'MlpLstmPolicy' - tensorboard_log: "../../../logs" - batch_size: 64 - n_steps: 1024 - gae_lambda: 0.98 - gamma: 0.995 - use_sde: True +# id: "guess" +# algo_config: +# policy: 'MlpLstmPolicy' +# tensorboard_log: "../../../logs" +# batch_size: 64 +# n_steps: 1024 +# gae_lambda: 0.98 +# gamma: 0.995 +# use_sde: True # # SLOW LEARN # id: "slow" @@ -118,26 +118,26 @@ algo_config: # # MOUNTAIN CAR NO VEL -# id: "mount_car" -# algo_config: - # tensorboard_log: "../../../logs" - # policy: 'MlpLstmPolicy' - # batch_size: 256 - # n_steps: 1024 - # gamma: 0.9999 - # learning_rate: !!float 7.77e-05 - # ent_coef: 0.00429 - # clip_range: 0.1 - # n_epochs: 10 - # gae_lambda: 0.9 - # max_grad_norm: 5 - # vf_coef: 0.19 - # use_sde: True - # sde_sample_freq: 8 - # policy_kwargs: "dict(log_std_init=0.0, ortho_init=False, - # lstm_hidden_size=32, - # enable_critic_lstm=True, - # net_arch=dict(pi=[64], vf=[64]))" +id: "mount_car" +algo_config: + tensorboard_log: "../../../logs" + policy: 'MlpLstmPolicy' + batch_size: 256 + n_steps: 1024 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + n_epochs: 10 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + use_sde: True + sde_sample_freq: 8 + policy_kwargs: "dict(log_std_init=0.0, ortho_init=False, + lstm_hidden_size=32, + enable_critic_lstm=True, + net_arch=dict(pi=[64], vf=[64]))" # SPACE INVADERS V4 # id: "space_invaders" diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index 449bdc9..3b0f587 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -13,6 +13,7 @@ env_id: "AsmEnv" config: observation_fn_id: 'observe_2o' n_observs: 2 + upow: 0.6 n_envs: 12 # io @@ -20,5 +21,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2o" +id: "2o-upow0.6" additional_imports: [] From 40e2cf2bfbe38414e2a60688d05141cb56665518 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 2 May 2024 21:56:46 +0000 Subject: [PATCH 26/64] added config file input to fixed_policy_opt, added optional id input --- scripts/fixed_policy_opt.py | 14 ++++++++------ scripts/tune_fixed_policies.sh | 12 ++++++------ 2 files changed, 14 insertions(+), 12 deletions(-) diff --git a/scripts/fixed_policy_opt.py b/scripts/fixed_policy_opt.py index 7403f3f..5bda2c2 100644 --- a/scripts/fixed_policy_opt.py +++ b/scripts/fixed_policy_opt.py @@ -5,7 +5,8 @@ parser.add_argument("-v", "--verbose", help="Verbosity of tuning method", type=bool) parser.add_argument("-o", "--opt-algo", choices=["gp", "gbrt"], help="Optimization algo used") parser.add_argument("-ncalls", "--n-calls", help="Number of objective function calls used by optimizing algo", type=int) -parser.add_argument("-f", "--config-file", help="yaml file with env config.") +parser.add_argument("-f", "--config-file", help="yaml file with env config") +parser.add_argument("-id", "--id", help="Identifier string", default="") args = parser.parse_args() from huggingface_hub import hf_hub_download, HfApi, login @@ -46,12 +47,12 @@ # optimizing space -msy_space = [Real(0.0002, 0.5, name='mortality')] -esc_space = [Real(0.0002, 0.25, name='escapement')] +msy_space = [Real(0.0001, 0.5, name='mortality')] +esc_space = [Real(0.0001, 10, name='escapement')] cr_space = [ - Real(0.00001, 1, name='radius'), + Real(0.00001, 10, name='radius'), Real(0.00001, np.pi/4.00001, name='theta'), - Real(0, 0.4, name='y2') + Real(0, 0.8, name='y2') ] space = {'msy':msy_space, 'esc':esc_space, 'cr':cr_space}[args.policy] @@ -94,7 +95,8 @@ def cr_fn(**params): # save path = "../saved_agents/" -fname = f"{args.policy}_{args.opt_algo}.pkl" +save_id = "" if args.id == "" else f"_{args.id}" +fname = f"{args.policy}_{args.opt_algo}{save_id}.pkl" dump(results, path+fname) # hf diff --git a/scripts/tune_fixed_policies.sh b/scripts/tune_fixed_policies.sh index 7cf6062..cb6eba4 100644 --- a/scripts/tune_fixed_policies.sh +++ b/scripts/tune_fixed_policies.sh @@ -8,11 +8,11 @@ cd "$scriptdir" python hf_login.py # gp -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gp -nc 100 & -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gp -nc 100 & -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gp -nc 100 & +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gp -nc 100 +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gp -nc 100 +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gp -nc 100 # gbrt -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gbrt -nc 100 & -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gbrt -nc 100 & -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gbrt -nc 100 & \ No newline at end of file +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gbrt -nc 100 +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gbrt -nc 100 +python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gbrt -nc 100 \ No newline at end of file From d993bf65220be551902ff4419de992620fd2544c Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 3 May 2024 18:30:53 +0000 Subject: [PATCH 27/64] hyperpars --- hyperpars/ppo-asm.yml | 7 +++---- hyperpars/tqc-asm.yml | 14 +++++++++++--- 2 files changed, 14 insertions(+), 7 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 05f4cd8..fdff0a3 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -5,9 +5,8 @@ algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' use_sde: True - # batch_size: 64 - # gamma: 0.995 - # gae_lambda: 0.999 + # policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" + clip_range: 0.1 # env env_id: "AsmEnv" @@ -23,4 +22,4 @@ save_path: "../saved_agents" # misc id: "2o-upow0.6" -additional_imports: [] \ No newline at end of file +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index 3b0f587..e8e61b1 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -4,9 +4,17 @@ total_timesteps: 5000000 algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' - learning_rate: 0.0001 - learning_starts: 1000 + learning_rate: !!float 7.3e-4 + buffer_size: 400000 + batch_size: 512 + ent_coef: 'auto' + gamma: 0.98 + tau: 0.02 + train_freq: 64 + gradient_steps: 64 + learning_starts: 20000 use_sde: True + policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" # env env_id: "AsmEnv" @@ -22,4 +30,4 @@ save_path: "../saved_agents" # misc id: "2o-upow0.6" -additional_imports: [] +additional_imports: ["torch"] From aeb91fd76908c1452c286fa9d7fdefc5d85213ce Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 3 May 2024 22:39:45 +0000 Subject: [PATCH 28/64] hyperparams --- hyperpars/ppo-asm.yml | 20 ++++++++++++++++---- hyperpars/tqc-asm.yml | 10 +++++----- 2 files changed, 21 insertions(+), 9 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index fdff0a3..882a18e 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -3,16 +3,28 @@ algo: "PPO" total_timesteps: 5000000 algo_config: tensorboard_log: "../../../logs" + normalize: true policy: 'MlpPolicy' + batch_size: 256 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 use_sde: True + policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False)" + # policy: 'MlpPolicy' + # use_sde: True # policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" config: - observation_fn_id: 'observe_2o' - n_observs: 2 + observation_fn_id: 'observe_1o' + n_observs: 1 upow: 0.6 n_envs: 12 @@ -21,5 +33,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2o-upow0.6" +id: "1o-upow0.6" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index e8e61b1..5947e89 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -5,7 +5,7 @@ algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' learning_rate: !!float 7.3e-4 - buffer_size: 400000 + buffer_size: 200000 batch_size: 512 ent_coef: 'auto' gamma: 0.98 @@ -14,13 +14,13 @@ algo_config: gradient_steps: 64 learning_starts: 20000 use_sde: True - policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" + policy_kwargs: "dict(log_std_init=-3, net_arch=[256, 128])" # env env_id: "AsmEnv" config: - observation_fn_id: 'observe_2o' - n_observs: 2 + observation_fn_id: 'observe_1o' + n_observs: 1 upow: 0.6 n_envs: 12 @@ -29,5 +29,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2o-upow0.6" +id: "1o-upow0.6" additional_imports: ["torch"] From 904ef390fabab71f0cc1f7c3253bf6189b2f44cc Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Sat, 4 May 2024 00:41:00 +0000 Subject: [PATCH 29/64] mntCar --- hyperpars/ppo-asm.yml | 4 +- notebooks/optimal-fixed-policy.ipynb | 13277 ++++++++++++++----------- 2 files changed, 7618 insertions(+), 5663 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 882a18e..f7cfecd 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -3,7 +3,7 @@ algo: "PPO" total_timesteps: 5000000 algo_config: tensorboard_log: "../../../logs" - normalize: true + # policy: 'MlpPolicy' batch_size: 256 gamma: 0.9999 @@ -33,5 +33,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "1o-upow0.6" +id: "1o-mtCarContv0-upow0.6" additional_imports: ["torch"] \ No newline at end of file diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index 4c05041..6921c02 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "dee5cba2-cdc3-4bf5-9ea4-788ca5d4a4d9", "metadata": { "scrolled": true @@ -65,7 +65,9 @@ "source": [ "# CONFIG = {\"s\": 0.86, \"noiseless\": False, \"testing_harvs\": False}\n", "CONFIG = {\n", - " 'get_r_devs_version': 'v2'\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " 'upow': 0.6,\n", "}" ] }, @@ -167,7 +169,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], @@ -241,13 +243,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ @@ -262,7 +260,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-18 20:07:06,260\tINFO worker.py:1752 -- Started a local Ray instance.\n" + "2024-05-03 23:11:14,787\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -270,5206 +268,5416 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 5.4834\n", - "Function value obtained: -45.4869\n", - "Current minimum: -45.4869\n", - "Iteration No: 2 started. Evaluating function at random point.\n", + "Time taken: 7.6175\n", + "Function value obtained: -54.8470\n", + "Current minimum: -54.8470\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:11:22,686\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.2390\n", - "Function value obtained: -45.4833\n", - "Current minimum: -45.4869\n", - "Iteration No: 3 started. Evaluating function at random point.\n", + "Time taken: 8.3440\n", + "Function value obtained: -10.2549\n", + "Current minimum: -54.8470\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:11:30,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.3095\n", - "Function value obtained: -10.7505\n", - "Current minimum: -45.4869\n", - "Iteration No: 4 started. Evaluating function at random point.\n", + "Time taken: 7.0552\n", + "Function value obtained: -10.3992\n", + "Current minimum: -54.8470\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:11:37,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.2724\n", - "Function value obtained: -5.0272\n", - "Current minimum: -45.4869\n", - "Iteration No: 5 started. Evaluating function at random point.\n", + "Time taken: 7.1076\n", + "Function value obtained: -61.3399\n", + "Current minimum: -61.3399\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:11:44,744\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.2496\n", - "Function value obtained: -3.9916\n", - "Current minimum: -45.4869\n", - "Iteration No: 6 started. Evaluating function at random point.\n", + "Time taken: 7.1964\n", + "Function value obtained: -123.6052\n", + "Current minimum: -123.6052\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:11:51,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.2104\n", - "Function value obtained: -33.0886\n", - "Current minimum: -45.4869\n", - "Iteration No: 7 started. Evaluating function at random point.\n", + "Time taken: 7.2913\n", + "Function value obtained: -122.0412\n", + "Current minimum: -123.6052\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:11:59,247\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.2964\n", - "Function value obtained: -45.3213\n", - "Current minimum: -45.4869\n", - "Iteration No: 8 started. Evaluating function at random point.\n", + "Time taken: 7.4194\n", + "Function value obtained: -117.4966\n", + "Current minimum: -123.6052\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:12:06,673\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.2228\n", - "Function value obtained: -46.4804\n", - "Current minimum: -46.4804\n", - "Iteration No: 9 started. Evaluating function at random point.\n", + "Time taken: 7.3481\n", + "Function value obtained: -34.1646\n", + "Current minimum: -123.6052\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:12:14,028\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.2179\n", - "Function value obtained: -37.1732\n", - "Current minimum: -46.4804\n", - "Iteration No: 10 started. Evaluating function at random point.\n", + "Time taken: 6.9550\n", + "Function value obtained: -48.1777\n", + "Current minimum: -123.6052\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:12:21,452\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 5.4263\n", - "Function value obtained: -17.7539\n", - "Current minimum: -46.4804\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", + "Time taken: 12.4731\n", + "Function value obtained: -55.4513\n", + "Current minimum: -123.6052\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:12:33,525\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8543\n", - "Function value obtained: -44.8017\n", - "Current minimum: -46.4804\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", + "Time taken: 8.4841\n", + "Function value obtained: -122.4503\n", + "Current minimum: -123.6052\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:12:42,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8846\n", - "Function value obtained: -47.1156\n", - "Current minimum: -47.1156\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", + "Time taken: 8.6229\n", + "Function value obtained: -127.2857\n", + "Current minimum: -127.2857\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:12:50,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7248\n", - "Function value obtained: -2.1069\n", - "Current minimum: -47.1156\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", + "Time taken: 8.5412\n", + "Function value obtained: -123.8198\n", + "Current minimum: -127.2857\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:12:59,232\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6298\n", - "Function value obtained: -47.2816\n", - "Current minimum: -47.2816\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", + "Time taken: 10.1859\n", + "Function value obtained: -124.7299\n", + "Current minimum: -127.2857\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:13:09,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7281\n", - "Function value obtained: -48.4797\n", - "Current minimum: -48.4797\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", + "Time taken: 8.5702\n", + "Function value obtained: -119.6652\n", + "Current minimum: -127.2857\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:13:17,991\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6663\n", - "Function value obtained: -45.8552\n", - "Current minimum: -48.4797\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", + "Time taken: 8.9790\n", + "Function value obtained: -124.1273\n", + "Current minimum: -127.2857\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:13:26,921\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6468\n", - "Function value obtained: -44.8384\n", - "Current minimum: -48.4797\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", + "Time taken: 8.9641\n", + "Function value obtained: -126.8413\n", + "Current minimum: -127.2857\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:13:35,910\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2501\n", - "Function value obtained: -47.2674\n", - "Current minimum: -48.4797\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4988\n", - "Function value obtained: -47.9821\n", - "Current minimum: -48.4797\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4442\n", - "Function value obtained: -48.3160\n", - "Current minimum: -48.4797\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4421\n", - "Function value obtained: -48.4776\n", - "Current minimum: -48.4797\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4981\n", - "Function value obtained: -46.0047\n", - "Current minimum: -48.4797\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", + "Time taken: 8.9626\n", + "Function value obtained: -121.7985\n", + "Current minimum: -127.2857\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:13:44,884\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8622\n", + "Function value obtained: -123.6838\n", + "Current minimum: -127.2857\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:13:52,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2900\n", + "Function value obtained: -9.0585\n", + "Current minimum: -127.2857\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:01,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2339\n", + "Function value obtained: -124.7479\n", + "Current minimum: -127.2857\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:09,291\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0172\n", + "Function value obtained: -121.9862\n", + "Current minimum: -127.2857\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:17,307\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5107\n", - "Function value obtained: -47.0921\n", - "Current minimum: -48.4797\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", + "Time taken: 7.9542\n", + "Function value obtained: -123.1853\n", + "Current minimum: -127.2857\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:25,282\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4536\n", - "Function value obtained: -45.4472\n", - "Current minimum: -48.4797\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", + "Time taken: 8.0674\n", + "Function value obtained: -120.4783\n", + "Current minimum: -127.2857\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:33,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5842\n", - "Function value obtained: -44.6242\n", - "Current minimum: -48.4797\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", + "Time taken: 8.1974\n", + "Function value obtained: -120.4659\n", + "Current minimum: -127.2857\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:41,668\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5491\n", - "Function value obtained: -45.6832\n", - "Current minimum: -48.4797\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", + "Time taken: 8.1946\n", + "Function value obtained: -122.7296\n", + "Current minimum: -127.2857\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:49,727\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5361\n", - "Function value obtained: -47.7525\n", - "Current minimum: -48.4797\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", + "Time taken: 8.2397\n", + "Function value obtained: -121.5272\n", + "Current minimum: -127.2857\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:14:58,015\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5167\n", - "Function value obtained: -48.0074\n", - "Current minimum: -48.4797\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", + "Time taken: 8.1334\n", + "Function value obtained: -119.4227\n", + "Current minimum: -127.2857\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:15:06,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4705\n", - "Function value obtained: -45.3860\n", - "Current minimum: -48.4797\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", + "Time taken: 8.3177\n", + "Function value obtained: -125.5835\n", + "Current minimum: -127.2857\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:15:14,468\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5557\n", - "Function value obtained: -47.2246\n", - "Current minimum: -48.4797\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", + "Time taken: 8.2952\n", + "Function value obtained: -123.7889\n", + "Current minimum: -127.2857\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:15:22,796\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4705\n", - "Function value obtained: -46.7993\n", - "Current minimum: -48.4797\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", + "Time taken: 8.5224\n", + "Function value obtained: -123.3614\n", + "Current minimum: -127.2857\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:15:31,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4802\n", - "Function value obtained: -47.5363\n", - "Current minimum: -48.4797\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", + "Time taken: 8.1022\n", + "Function value obtained: -123.0724\n", + "Current minimum: -127.2857\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:15:39,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5252\n", - "Function value obtained: -44.5044\n", - "Current minimum: -48.4797\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", + "Time taken: 8.5146\n", + "Function value obtained: -120.6817\n", + "Current minimum: -127.2857\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:15:47,986\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5382\n", - "Function value obtained: -46.5751\n", - "Current minimum: -48.4797\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", + "Time taken: 8.3151\n", + "Function value obtained: -124.2780\n", + "Current minimum: -127.2857\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:15:56,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5391\n", - "Function value obtained: -46.4138\n", - "Current minimum: -48.4797\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5699\n", - "Function value obtained: -46.8731\n", - "Current minimum: -48.4797\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5144\n", - "Function value obtained: -44.6237\n", - "Current minimum: -48.4797\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5497\n", - "Function value obtained: -47.7694\n", - "Current minimum: -48.4797\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5183\n", - "Function value obtained: -45.6401\n", - "Current minimum: -48.4797\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5764\n", - "Function value obtained: -44.6487\n", - "Current minimum: -48.4797\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6051\n", - "Function value obtained: -48.4921\n", - "Current minimum: -48.4921\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", + "Time taken: 8.4350\n", + "Function value obtained: -122.4030\n", + "Current minimum: -127.2857\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:16:04,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4938\n", + "Function value obtained: -119.6260\n", + "Current minimum: -127.2857\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:16:13,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2929\n", + "Function value obtained: -120.0802\n", + "Current minimum: -127.2857\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:16:21,536\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2857\n", + "Function value obtained: -125.4253\n", + "Current minimum: -127.2857\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:16:29,771\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4954\n", + "Function value obtained: -120.5625\n", + "Current minimum: -127.2857\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:16:38,229\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3361\n", + "Function value obtained: -121.0406\n", + "Current minimum: -127.2857\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:16:46,607\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3899\n", + "Function value obtained: -118.3589\n", + "Current minimum: -127.2857\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:16:55,979\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5972\n", - "Function value obtained: -45.5842\n", - "Current minimum: -48.4921\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", + "Time taken: 8.2630\n", + "Function value obtained: -123.8028\n", + "Current minimum: -127.2857\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:17:04,240\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7220\n", - "Function value obtained: -46.4373\n", - "Current minimum: -48.4921\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", + "Time taken: 8.1514\n", + "Function value obtained: -122.1566\n", + "Current minimum: -127.2857\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:17:12,396\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5566\n", - "Function value obtained: -47.1885\n", - "Current minimum: -48.4921\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", + "Time taken: 7.8708\n", + "Function value obtained: -122.6544\n", + "Current minimum: -127.2857\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:17:20,285\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5261\n", - "Function value obtained: -45.9221\n", - "Current minimum: -48.4921\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", + "Time taken: 8.0417\n", + "Function value obtained: -124.6074\n", + "Current minimum: -127.2857\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:17:28,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5645\n", - "Function value obtained: -43.6403\n", - "Current minimum: -48.4921\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", + "Time taken: 8.8086\n", + "Function value obtained: -126.2508\n", + "Current minimum: -127.2857\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:17:37,112\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5970\n", - "Function value obtained: -45.2802\n", - "Current minimum: -48.4921\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", + "Time taken: 7.7718\n", + "Function value obtained: -118.2078\n", + "Current minimum: -127.2857\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:17:44,988\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6565\n", - "Function value obtained: -45.3725\n", - "Current minimum: -48.4921\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", + "Time taken: 8.0034\n", + "Function value obtained: -124.1550\n", + "Current minimum: -127.2857\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:17:52,929\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6801\n", - "Function value obtained: -47.2802\n", - "Current minimum: -48.4921\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", + "Time taken: 7.9937\n", + "Function value obtained: -123.0761\n", + "Current minimum: -127.2857\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:00,929\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6020\n", - "Function value obtained: -46.1278\n", - "Current minimum: -48.4921\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", + "Time taken: 7.9815\n", + "Function value obtained: -120.6253\n", + "Current minimum: -127.2857\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:08,896\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5772\n", - "Function value obtained: -45.1661\n", - "Current minimum: -48.4921\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", + "Time taken: 7.7605\n", + "Function value obtained: -123.7669\n", + "Current minimum: -127.2857\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:16,664\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6349\n", - "Function value obtained: -48.4165\n", - "Current minimum: -48.4921\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", + "Time taken: 7.5621\n", + "Function value obtained: -122.1211\n", + "Current minimum: -127.2857\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:24,248\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6452\n", - "Function value obtained: -46.2293\n", - "Current minimum: -48.4921\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6030\n", - "Function value obtained: -47.8491\n", - "Current minimum: -48.4921\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6037\n", - "Function value obtained: -47.8606\n", - "Current minimum: -48.4921\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6668\n", - "Function value obtained: -47.1706\n", - "Current minimum: -48.4921\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", + "Time taken: 8.0676\n", + "Function value obtained: -125.7559\n", + "Current minimum: -127.2857\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:32,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0255\n", + "Function value obtained: -124.4625\n", + "Current minimum: -127.2857\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:40,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7814\n", + "Function value obtained: -125.2109\n", + "Current minimum: -127.2857\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:48,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9452\n", + "Function value obtained: -123.2743\n", + "Current minimum: -127.2857\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:18:56,074\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6347\n", - "Function value obtained: -44.8855\n", - "Current minimum: -48.4921\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", + "Time taken: 8.4101\n", + "Function value obtained: -120.6169\n", + "Current minimum: -127.2857\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:19:04,524\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7118\n", - "Function value obtained: -48.2741\n", - "Current minimum: -48.4921\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", + "Time taken: 8.0182\n", + "Function value obtained: -121.7291\n", + "Current minimum: -127.2857\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:19:12,556\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6909\n", - "Function value obtained: -46.0191\n", - "Current minimum: -48.4921\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", + "Time taken: 8.1671\n", + "Function value obtained: -125.1627\n", + "Current minimum: -127.2857\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:19:20,682\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6286\n", - "Function value obtained: -46.5769\n", - "Current minimum: -48.4921\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", + "Time taken: 8.2038\n", + "Function value obtained: -121.9801\n", + "Current minimum: -127.2857\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:19:28,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7985\n", - "Function value obtained: -45.2123\n", - "Current minimum: -48.4921\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", + "Time taken: 7.9633\n", + "Function value obtained: -121.9620\n", + "Current minimum: -127.2857\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:19:37,853\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6588\n", - "Function value obtained: -47.8129\n", - "Current minimum: -48.4921\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", + "Time taken: 9.1470\n", + "Function value obtained: -125.8936\n", + "Current minimum: -127.2857\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:19:46,012\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6954\n", - "Function value obtained: -47.5916\n", - "Current minimum: -48.4921\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", + "Time taken: 7.9083\n", + "Function value obtained: -125.7380\n", + "Current minimum: -127.2857\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:19:53,947\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7652\n", - "Function value obtained: -47.5889\n", - "Current minimum: -48.4921\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", + "Time taken: 7.8940\n", + "Function value obtained: -124.1102\n", + "Current minimum: -127.2857\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:01,809\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6750\n", - "Function value obtained: -45.0518\n", - "Current minimum: -48.4921\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", + "Time taken: 8.0331\n", + "Function value obtained: -121.7327\n", + "Current minimum: -127.2857\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:09,912\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7389\n", - "Function value obtained: -45.4444\n", - "Current minimum: -48.4921\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", + "Time taken: 8.3531\n", + "Function value obtained: -122.7979\n", + "Current minimum: -127.2857\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:18,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7756\n", - "Function value obtained: -45.8260\n", - "Current minimum: -48.4921\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", + "Time taken: 8.5848\n", + "Function value obtained: -126.2115\n", + "Current minimum: -127.2857\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:26,810\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7541\n", - "Function value obtained: -46.2042\n", - "Current minimum: -48.4921\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", + "Time taken: 8.2814\n", + "Function value obtained: -123.5397\n", + "Current minimum: -127.2857\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:35,177\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6736\n", - "Function value obtained: -46.1098\n", - "Current minimum: -48.4921\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", + "Time taken: 8.0697\n", + "Function value obtained: -122.2537\n", + "Current minimum: -127.2857\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:43,142\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8213\n", - "Function value obtained: -47.9813\n", - "Current minimum: -48.4921\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", + "Time taken: 8.0422\n", + "Function value obtained: -125.0775\n", + "Current minimum: -127.2857\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:51,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7609\n", - "Function value obtained: -47.3720\n", - "Current minimum: -48.4921\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", + "Time taken: 8.0092\n", + "Function value obtained: -122.9532\n", + "Current minimum: -127.2857\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:20:59,207\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7459\n", - "Function value obtained: -45.8506\n", - "Current minimum: -48.4921\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7373\n", - "Function value obtained: -47.3937\n", - "Current minimum: -48.4921\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7282\n", - "Function value obtained: -47.7427\n", - "Current minimum: -48.4921\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7312\n", - "Function value obtained: -46.9223\n", - "Current minimum: -48.4921\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9500\n", - "Function value obtained: -45.0708\n", - "Current minimum: -48.4921\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7779\n", - "Function value obtained: -47.4218\n", - "Current minimum: -48.4921\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", + "Time taken: 8.0968\n", + "Function value obtained: -123.0806\n", + "Current minimum: -127.2857\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:21:07,293\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0032\n", + "Function value obtained: -125.7564\n", + "Current minimum: -127.2857\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:21:16,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2578\n", + "Function value obtained: -125.3020\n", + "Current minimum: -127.2857\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:21:24,627\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2321\n", + "Function value obtained: -122.3374\n", + "Current minimum: -127.2857\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:21:32,799\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3429\n", + "Function value obtained: -121.8593\n", + "Current minimum: -127.2857\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:21:41,179\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1065\n", + "Function value obtained: -124.8048\n", + "Current minimum: -127.2857\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:21:49,280\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7577\n", - "Function value obtained: -47.6362\n", - "Current minimum: -48.4921\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", + "Time taken: 8.2792\n", + "Function value obtained: -122.4037\n", + "Current minimum: -127.2857\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:21:57,608\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8317\n", - "Function value obtained: -46.0445\n", - "Current minimum: -48.4921\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", + "Time taken: 8.1012\n", + "Function value obtained: -123.3177\n", + "Current minimum: -127.2857\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:22:05,678\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8320\n", - "Function value obtained: -44.9416\n", - "Current minimum: -48.4921\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", + "Time taken: 8.4301\n", + "Function value obtained: -124.2213\n", + "Current minimum: -127.2857\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:22:14,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8045\n", - "Function value obtained: -47.1192\n", - "Current minimum: -48.4921\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", + "Time taken: 9.1197\n", + "Function value obtained: -125.2965\n", + "Current minimum: -127.2857\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:22:23,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8466\n", - "Function value obtained: -48.4313\n", - "Current minimum: -48.4921\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", + "Time taken: 8.2129\n", + "Function value obtained: -122.8271\n", + "Current minimum: -127.2857\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:22:31,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8834\n", - "Function value obtained: -47.3605\n", - "Current minimum: -48.4921\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", + "Time taken: 8.1701\n", + "Function value obtained: -123.6942\n", + "Current minimum: -127.2857\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:22:40,672\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8080\n", - "Function value obtained: -48.2420\n", - "Current minimum: -48.4921\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", + "Time taken: 9.4587\n", + "Function value obtained: -123.5216\n", + "Current minimum: -127.2857\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:22:49,131\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8395\n", - "Function value obtained: -46.2903\n", - "Current minimum: -48.4921\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", + "Time taken: 8.3058\n", + "Function value obtained: -127.2533\n", + "Current minimum: -127.2857\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:22:57,413\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8343\n", - "Function value obtained: -47.3175\n", - "Current minimum: -48.4921\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", + "Time taken: 8.2952\n", + "Function value obtained: -124.6334\n", + "Current minimum: -127.2857\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:23:05,742\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8653\n", - "Function value obtained: -45.3488\n", - "Current minimum: -48.4921\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", + "Time taken: 8.1572\n", + "Function value obtained: -123.4150\n", + "Current minimum: -127.2857\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:23:13,874\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9204\n", - "Function value obtained: -48.0706\n", - "Current minimum: -48.4921\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", + "Time taken: 8.1534\n", + "Function value obtained: -126.7773\n", + "Current minimum: -127.2857\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:23:22,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9728\n", - "Function value obtained: -44.7884\n", - "Current minimum: -48.4921\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", + "Time taken: 9.1753\n", + "Function value obtained: -120.3155\n", + "Current minimum: -127.2857\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:23:31,232\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9866\n", - "Function value obtained: -44.1032\n", - "Current minimum: -48.4921\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", + "Time taken: 8.1793\n", + "Function value obtained: -122.5142\n", + "Current minimum: -127.2857\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:23:39,415\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0576\n", - "Function value obtained: -47.2277\n", - "Current minimum: -48.4921\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0363\n", - "Function value obtained: -46.7563\n", - "Current minimum: -48.4921\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0899\n", - "Function value obtained: -46.3911\n", - "Current minimum: -48.4921\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0240\n", - "Function value obtained: -48.2728\n", - "Current minimum: -48.4921\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0093\n", - "Function value obtained: -48.0412\n", - "Current minimum: -48.4921\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", + "Time taken: 8.3417\n", + "Function value obtained: -120.7373\n", + "Current minimum: -127.2857\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:23:47,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6652\n", + "Function value obtained: -124.0888\n", + "Current minimum: -127.2857\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:23:56,399\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1963\n", + "Function value obtained: -121.1684\n", + "Current minimum: -127.2857\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:24:05,685\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2017\n", + "Function value obtained: -122.1243\n", + "Current minimum: -127.2857\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:24:14,839\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3457\n", + "Function value obtained: -118.2673\n", + "Current minimum: -127.2857\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:24:23,169\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0485\n", - "Function value obtained: -48.0344\n", - "Current minimum: -48.4921\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", + "Time taken: 9.3580\n", + "Function value obtained: -125.4271\n", + "Current minimum: -127.2857\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:24:32,535\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0404\n", - "Function value obtained: -48.5009\n", - "Current minimum: -48.5009\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", + "Time taken: 9.8470\n", + "Function value obtained: -123.5324\n", + "Current minimum: -127.2857\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:24:42,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9809\n", - "Function value obtained: -44.2641\n", - "Current minimum: -48.5009\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", + "Time taken: 8.5936\n", + "Function value obtained: -118.8865\n", + "Current minimum: -127.2857\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:24:50,976\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9447\n", - "Function value obtained: -49.1602\n", - "Current minimum: -49.1602\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", + "Time taken: 8.6656\n", + "Function value obtained: -125.6696\n", + "Current minimum: -127.2857\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:24:59,748\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0264\n", - "Function value obtained: -47.1086\n", - "Current minimum: -49.1602\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", + "Time taken: 8.8550\n", + "Function value obtained: -125.7615\n", + "Current minimum: -127.2857\n", + "Iteration No: 101 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:25:08,527\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1010\n", - "Function value obtained: -48.3980\n", - "Current minimum: -49.1602\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", + "Time taken: 8.6321\n", + "Function value obtained: -122.5695\n", + "Current minimum: -127.2857\n", + "Iteration No: 102 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:25:17,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0427\n", - "Function value obtained: -47.8815\n", - "Current minimum: -49.1602\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", + "Time taken: 8.8353\n", + "Function value obtained: -123.4955\n", + "Current minimum: -127.2857\n", + "Iteration No: 103 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:25:25,992\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0931\n", - "Function value obtained: -47.5502\n", - "Current minimum: -49.1602\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", + "Time taken: 8.7245\n", + "Function value obtained: -120.5857\n", + "Current minimum: -127.2857\n", + "Iteration No: 104 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:25:34,738\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2007\n", - "Function value obtained: -47.4727\n", - "Current minimum: -49.1602\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", + "Time taken: 9.3886\n", + "Function value obtained: -123.0827\n", + "Current minimum: -127.2857\n", + "Iteration No: 105 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:25:44,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0616\n", - "Function value obtained: -47.9100\n", - "Current minimum: -49.1602\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", + "Time taken: 8.5134\n", + "Function value obtained: -121.5040\n", + "Current minimum: -127.2857\n", + "Iteration No: 106 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:25:52,638\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1357\n", - "Function value obtained: -46.7392\n", - "Current minimum: -49.1602\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", + "Time taken: 9.0207\n", + "Function value obtained: -122.5403\n", + "Current minimum: -127.2857\n", + "Iteration No: 107 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:26:01,677\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0894\n", - "Function value obtained: -47.8489\n", - "Current minimum: -49.1602\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", + "Time taken: 8.8901\n", + "Function value obtained: -126.4895\n", + "Current minimum: -127.2857\n", + "Iteration No: 108 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:26:10,620\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0558\n", - "Function value obtained: -46.5916\n", - "Current minimum: -49.1602\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", + "Time taken: 8.8920\n", + "Function value obtained: -122.3992\n", + "Current minimum: -127.2857\n", + "Iteration No: 109 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:26:19,434\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1618\n", - "Function value obtained: -48.1301\n", - "Current minimum: -49.1602\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", + "Time taken: 9.6350\n", + "Function value obtained: -124.4872\n", + "Current minimum: -127.2857\n", + "Iteration No: 110 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:26:29,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2526\n", - "Function value obtained: -46.3323\n", - "Current minimum: -49.1602\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1880\n", - "Function value obtained: -46.9814\n", - "Current minimum: -49.1602\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1675\n", - "Function value obtained: -48.6653\n", - "Current minimum: -49.1602\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1985\n", - "Function value obtained: -46.3422\n", - "Current minimum: -49.1602\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1815\n", - "Function value obtained: -46.4887\n", - "Current minimum: -49.1602\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", + "Time taken: 9.4430\n", + "Function value obtained: -120.1646\n", + "Current minimum: -127.2857\n", + "Iteration No: 111 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:26:38,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 111 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9071\n", + "Function value obtained: -125.2676\n", + "Current minimum: -127.2857\n", + "Iteration No: 112 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:26:47,487\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 112 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4783\n", + "Function value obtained: -124.0320\n", + "Current minimum: -127.2857\n", + "Iteration No: 113 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:26:56,961\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 113 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1311\n", + "Function value obtained: -126.5364\n", + "Current minimum: -127.2857\n", + "Iteration No: 114 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:27:06,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 114 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4202\n", + "Function value obtained: -124.6390\n", + "Current minimum: -127.2857\n", + "Iteration No: 115 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:27:15,487\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1457\n", - "Function value obtained: -47.0818\n", - "Current minimum: -49.1602\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", + "Time taken: 9.5468\n", + "Function value obtained: -126.4374\n", + "Current minimum: -127.2857\n", + "Iteration No: 116 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:27:25,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1414\n", - "Function value obtained: -46.6261\n", - "Current minimum: -49.1602\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", + "Time taken: 9.4789\n", + "Function value obtained: -120.6114\n", + "Current minimum: -127.2857\n", + "Iteration No: 117 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:27:34,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1700\n", - "Function value obtained: -47.6725\n", - "Current minimum: -49.1602\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", + "Time taken: 9.6505\n", + "Function value obtained: -120.5101\n", + "Current minimum: -127.2857\n", + "Iteration No: 118 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:27:44,185\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2580\n", - "Function value obtained: -47.3460\n", - "Current minimum: -49.1602\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", + "Time taken: 9.5307\n", + "Function value obtained: -120.8552\n", + "Current minimum: -127.2857\n", + "Iteration No: 119 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:27:53,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2411\n", - "Function value obtained: -46.7710\n", - "Current minimum: -49.1602\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", + "Time taken: 9.7483\n", + "Function value obtained: -125.5909\n", + "Current minimum: -127.2857\n", + "Iteration No: 120 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:28:03,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2818\n", - "Function value obtained: -46.3773\n", - "Current minimum: -49.1602\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", + "Time taken: 9.7541\n", + "Function value obtained: -124.2085\n", + "Current minimum: -127.2857\n", + "Iteration No: 121 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:28:13,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2879\n", - "Function value obtained: -46.3798\n", - "Current minimum: -49.1602\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", + "Time taken: 9.4951\n", + "Function value obtained: -125.5847\n", + "Current minimum: -127.2857\n", + "Iteration No: 122 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:28:22,785\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2791\n", - "Function value obtained: -46.6607\n", - "Current minimum: -49.1602\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", + "Time taken: 9.6318\n", + "Function value obtained: -121.2312\n", + "Current minimum: -127.2857\n", + "Iteration No: 123 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:28:33,372\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3396\n", - "Function value obtained: -47.6516\n", - "Current minimum: -49.1602\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", + "Time taken: 10.7448\n", + "Function value obtained: -126.6954\n", + "Current minimum: -127.2857\n", + "Iteration No: 124 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:28:43,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2591\n", - "Function value obtained: -47.4018\n", - "Current minimum: -49.1602\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", + "Time taken: 9.5822\n", + "Function value obtained: -126.0589\n", + "Current minimum: -127.2857\n", + "Iteration No: 125 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:28:52,737\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3125\n", - "Function value obtained: -46.9759\n", - "Current minimum: -49.1602\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", + "Time taken: 9.0652\n", + "Function value obtained: -124.4110\n", + "Current minimum: -127.2857\n", + "Iteration No: 126 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:29:01,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4122\n", - "Function value obtained: -47.9909\n", - "Current minimum: -49.1602\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", + "Time taken: 9.6240\n", + "Function value obtained: -121.1013\n", + "Current minimum: -127.2857\n", + "Iteration No: 127 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:29:11,431\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4453\n", - "Function value obtained: -47.1735\n", - "Current minimum: -49.1602\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", + "Time taken: 9.7675\n", + "Function value obtained: -123.3102\n", + "Current minimum: -127.2857\n", + "Iteration No: 128 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:29:21,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3740\n", - "Function value obtained: -46.0115\n", - "Current minimum: -49.1602\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", + "Time taken: 9.6895\n", + "Function value obtained: -127.3494\n", + "Current minimum: -127.3494\n", + "Iteration No: 129 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:29:30,891\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4357\n", - "Function value obtained: -43.6239\n", - "Current minimum: -49.1602\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3402\n", - "Function value obtained: -47.6954\n", - "Current minimum: -49.1602\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3421\n", - "Function value obtained: -46.7463\n", - "Current minimum: -49.1602\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3503\n", - "Function value obtained: -47.3892\n", - "Current minimum: -49.1602\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4501\n", - "Function value obtained: -47.0282\n", - "Current minimum: -49.1602\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", + "Time taken: 9.9907\n", + "Function value obtained: -125.9170\n", + "Current minimum: -127.3494\n", + "Iteration No: 130 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:29:40,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 130 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7159\n", + "Function value obtained: -124.2533\n", + "Current minimum: -127.3494\n", + "Iteration No: 131 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:29:50,580\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 131 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7052\n", + "Function value obtained: -122.8221\n", + "Current minimum: -127.3494\n", + "Iteration No: 132 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:30:00,301\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 132 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0584\n", + "Function value obtained: -124.4080\n", + "Current minimum: -127.3494\n", + "Iteration No: 133 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:30:09,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 133 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6471\n", + "Function value obtained: -125.7858\n", + "Current minimum: -127.3494\n", + "Iteration No: 134 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:30:19,018\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4205\n", - "Function value obtained: -46.1954\n", - "Current minimum: -49.1602\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", + "Time taken: 9.7007\n", + "Function value obtained: -125.9075\n", + "Current minimum: -127.3494\n", + "Iteration No: 135 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:30:28,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5106\n", - "Function value obtained: -48.0156\n", - "Current minimum: -49.1602\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", + "Time taken: 9.7827\n", + "Function value obtained: -124.2837\n", + "Current minimum: -127.3494\n", + "Iteration No: 136 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:30:38,516\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5138\n", - "Function value obtained: -45.6801\n", - "Current minimum: -49.1602\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", + "Time taken: 9.5199\n", + "Function value obtained: -121.9445\n", + "Current minimum: -127.3494\n", + "Iteration No: 137 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:30:48,054\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4558\n", - "Function value obtained: -47.0258\n", - "Current minimum: -49.1602\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", + "Time taken: 9.7894\n", + "Function value obtained: -119.8468\n", + "Current minimum: -127.3494\n", + "Iteration No: 138 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:30:57,835\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5781\n", - "Function value obtained: -45.6934\n", - "Current minimum: -49.1602\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", + "Time taken: 9.7647\n", + "Function value obtained: -123.7169\n", + "Current minimum: -127.3494\n", + "Iteration No: 139 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:31:07,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4864\n", - "Function value obtained: -47.4580\n", - "Current minimum: -49.1602\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", + "Time taken: 9.8808\n", + "Function value obtained: -124.3117\n", + "Current minimum: -127.3494\n", + "Iteration No: 140 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:31:17,506\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5932\n", - "Function value obtained: -45.6992\n", - "Current minimum: -49.1602\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", + "Time taken: 9.8833\n", + "Function value obtained: -125.4229\n", + "Current minimum: -127.3494\n", + "Iteration No: 141 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:31:27,381\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4581\n", - "Function value obtained: -45.1805\n", - "Current minimum: -49.1602\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", + "Time taken: 9.9655\n", + "Function value obtained: -124.4755\n", + "Current minimum: -127.3494\n", + "Iteration No: 142 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:31:37,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6622\n", - "Function value obtained: -46.3799\n", - "Current minimum: -49.1602\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", + "Time taken: 9.9059\n", + "Function value obtained: -120.1788\n", + "Current minimum: -127.3494\n", + "Iteration No: 143 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:31:47,249\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5337\n", - "Function value obtained: -46.6137\n", - "Current minimum: -49.1602\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", + "Time taken: 9.7793\n", + "Function value obtained: -125.4044\n", + "Current minimum: -127.3494\n", + "Iteration No: 144 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:31:57,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5876\n", - "Function value obtained: -46.7286\n", - "Current minimum: -49.1602\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", + "Time taken: 9.8150\n", + "Function value obtained: -122.4493\n", + "Current minimum: -127.3494\n", + "Iteration No: 145 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:32:06,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5612\n", - "Function value obtained: -46.9521\n", - "Current minimum: -49.1602\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", + "Time taken: 10.0360\n", + "Function value obtained: -122.3720\n", + "Current minimum: -127.3494\n", + "Iteration No: 146 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:32:16,783\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5794\n", - "Function value obtained: -46.0575\n", - "Current minimum: -49.1602\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", + "Time taken: 9.7202\n", + "Function value obtained: -123.4715\n", + "Current minimum: -127.3494\n", + "Iteration No: 147 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:32:26,637\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5318\n", - "Function value obtained: -46.8464\n", - "Current minimum: -49.1602\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", + "Time taken: 9.9255\n", + "Function value obtained: -122.1531\n", + "Current minimum: -127.3494\n", + "Iteration No: 148 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:32:36,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5888\n", - "Function value obtained: -48.7687\n", - "Current minimum: -49.1602\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7167\n", - "Function value obtained: -47.1604\n", - "Current minimum: -49.1602\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6717\n", - "Function value obtained: -45.7514\n", - "Current minimum: -49.1602\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6518\n", - "Function value obtained: -48.3608\n", - "Current minimum: -49.1602\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5351\n", - "Function value obtained: -45.0135\n", - "Current minimum: -49.1602\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", + "Time taken: 9.8876\n", + "Function value obtained: -122.1446\n", + "Current minimum: -127.3494\n", + "Iteration No: 149 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:32:46,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 149 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0552\n", + "Function value obtained: -122.2754\n", + "Current minimum: -127.3494\n", + "Iteration No: 150 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:32:56,534\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 150 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0659\n", + "Function value obtained: -122.3044\n", + "Current minimum: -127.3494\n", + "Iteration No: 151 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:33:07,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 151 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1496\n", + "Function value obtained: -123.7074\n", + "Current minimum: -127.3494\n", + "Iteration No: 152 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:33:17,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 152 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0512\n", + "Function value obtained: -125.5542\n", + "Current minimum: -127.3494\n", + "Iteration No: 153 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:33:27,776\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6665\n", - "Function value obtained: -48.4784\n", - "Current minimum: -49.1602\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", + "Time taken: 10.0940\n", + "Function value obtained: -126.0177\n", + "Current minimum: -127.3494\n", + "Iteration No: 154 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:33:37,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6906\n", - "Function value obtained: -47.8889\n", - "Current minimum: -49.1602\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", + "Time taken: 10.1943\n", + "Function value obtained: -124.2800\n", + "Current minimum: -127.3494\n", + "Iteration No: 155 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:33:48,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6694\n", - "Function value obtained: -47.0118\n", - "Current minimum: -49.1602\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", + "Time taken: 9.5941\n", + "Function value obtained: -122.3352\n", + "Current minimum: -127.3494\n", + "Iteration No: 156 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:33:57,702\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7407\n", - "Function value obtained: -46.7522\n", - "Current minimum: -49.1602\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", + "Time taken: 9.5312\n", + "Function value obtained: -122.2072\n", + "Current minimum: -127.3494\n", + "Iteration No: 157 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:34:07,268\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7208\n", - "Function value obtained: -48.2136\n", - "Current minimum: -49.1602\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", + "Time taken: 10.2864\n", + "Function value obtained: -122.5458\n", + "Current minimum: -127.3494\n", + "Iteration No: 158 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:34:17,483\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8332\n", - "Function value obtained: -46.3153\n", - "Current minimum: -49.1602\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", + "Time taken: 10.1300\n", + "Function value obtained: -122.5309\n", + "Current minimum: -127.3494\n", + "Iteration No: 159 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:34:27,649\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7492\n", - "Function value obtained: -45.8129\n", - "Current minimum: -49.1602\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", + "Time taken: 9.6743\n", + "Function value obtained: -122.6837\n", + "Current minimum: -127.3494\n", + "Iteration No: 160 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:34:37,296\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9116\n", - "Function value obtained: -46.4367\n", - "Current minimum: -49.1602\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", + "Time taken: 10.2804\n", + "Function value obtained: -123.9210\n", + "Current minimum: -127.3494\n", + "Iteration No: 161 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:34:47,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8496\n", - "Function value obtained: -45.6333\n", - "Current minimum: -49.1602\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", + "Time taken: 10.1555\n", + "Function value obtained: -122.0798\n", + "Current minimum: -127.3494\n", + "Iteration No: 162 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:34:57,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8590\n", - "Function value obtained: -46.2112\n", - "Current minimum: -49.1602\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", + "Time taken: 10.2372\n", + "Function value obtained: -122.3340\n", + "Current minimum: -127.3494\n", + "Iteration No: 163 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:35:08,048\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8651\n", - "Function value obtained: -45.0481\n", - "Current minimum: -49.1602\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", + "Time taken: 10.1899\n", + "Function value obtained: -121.3459\n", + "Current minimum: -127.3494\n", + "Iteration No: 164 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:35:18,201\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8631\n", - "Function value obtained: -46.4866\n", - "Current minimum: -49.1602\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", + "Time taken: 10.3174\n", + "Function value obtained: -126.2553\n", + "Current minimum: -127.3494\n", + "Iteration No: 165 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:35:29,554\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8506\n", - "Function value obtained: -46.0082\n", - "Current minimum: -49.1602\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", + "Time taken: 11.3120\n", + "Function value obtained: -121.0753\n", + "Current minimum: -127.3494\n", + "Iteration No: 166 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:35:39,856\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9569\n", - "Function value obtained: -47.5285\n", - "Current minimum: -49.1602\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", + "Time taken: 10.4820\n", + "Function value obtained: -120.2387\n", + "Current minimum: -127.3494\n", + "Iteration No: 167 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:35:50,358\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9269\n", - "Function value obtained: -47.8298\n", - "Current minimum: -49.1602\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9630\n", - "Function value obtained: -48.0272\n", - "Current minimum: -49.1602\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9377\n", - "Function value obtained: -48.8270\n", - "Current minimum: -49.1602\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8955\n", - "Function value obtained: -48.3741\n", - "Current minimum: -49.1602\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0323\n", - "Function value obtained: -46.7494\n", - "Current minimum: -49.1602\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9283\n", - "Function value obtained: -48.7623\n", - "Current minimum: -49.1602\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", + "Time taken: 10.4620\n", + "Function value obtained: -126.7493\n", + "Current minimum: -127.3494\n", + "Iteration No: 168 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:36:00,723\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 168 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8545\n", + "Function value obtained: -125.1645\n", + "Current minimum: -127.3494\n", + "Iteration No: 169 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:36:10,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 169 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4415\n", + "Function value obtained: -122.6830\n", + "Current minimum: -127.3494\n", + "Iteration No: 170 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:36:21,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 170 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4778\n", + "Function value obtained: -121.4214\n", + "Current minimum: -127.3494\n", + "Iteration No: 171 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:36:31,643\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 171 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4139\n", + "Function value obtained: -121.5312\n", + "Current minimum: -127.3494\n", + "Iteration No: 172 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:36:42,048\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 172 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0658\n", + "Function value obtained: -122.2049\n", + "Current minimum: -127.3494\n", + "Iteration No: 173 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:36:52,123\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0291\n", - "Function value obtained: -48.1221\n", - "Current minimum: -49.1602\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", + "Time taken: 10.5942\n", + "Function value obtained: -123.3033\n", + "Current minimum: -127.3494\n", + "Iteration No: 174 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:37:02,692\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0170\n", - "Function value obtained: -48.7643\n", - "Current minimum: -49.1602\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", + "Time taken: 10.4186\n", + "Function value obtained: -124.3143\n", + "Current minimum: -127.3494\n", + "Iteration No: 175 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:37:14,157\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1282\n", - "Function value obtained: -46.4082\n", - "Current minimum: -49.1602\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", + "Time taken: 11.6351\n", + "Function value obtained: -119.8759\n", + "Current minimum: -127.3494\n", + "Iteration No: 176 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:37:24,805\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9267\n", - "Function value obtained: -47.9548\n", - "Current minimum: -49.1602\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", + "Time taken: 10.4779\n", + "Function value obtained: -123.4730\n", + "Current minimum: -127.3494\n", + "Iteration No: 177 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:37:35,294\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0769\n", - "Function value obtained: -47.4106\n", - "Current minimum: -49.1602\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", + "Time taken: 10.8561\n", + "Function value obtained: -120.8972\n", + "Current minimum: -127.3494\n", + "Iteration No: 178 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:37:46,101\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1087\n", - "Function value obtained: -48.8447\n", - "Current minimum: -49.1602\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", + "Time taken: 10.5419\n", + "Function value obtained: -122.7453\n", + "Current minimum: -127.3494\n", + "Iteration No: 179 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:37:56,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0330\n", - "Function value obtained: -46.6117\n", - "Current minimum: -49.1602\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", + "Time taken: 10.3095\n", + "Function value obtained: -123.9806\n", + "Current minimum: -127.3494\n", + "Iteration No: 180 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:38:06,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2589\n", - "Function value obtained: -48.5135\n", - "Current minimum: -49.1602\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", + "Time taken: 10.5235\n", + "Function value obtained: -128.5401\n", + "Current minimum: -128.5401\n", + "Iteration No: 181 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:38:17,493\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2152\n", - "Function value obtained: -45.4152\n", - "Current minimum: -49.1602\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", + "Time taken: 10.9341\n", + "Function value obtained: -121.9214\n", + "Current minimum: -128.5401\n", + "Iteration No: 182 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:38:28,405\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0810\n", - "Function value obtained: -45.7898\n", - "Current minimum: -49.1602\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", + "Time taken: 10.7589\n", + "Function value obtained: -122.9882\n", + "Current minimum: -128.5401\n", + "Iteration No: 183 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:38:39,188\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3461\n", - "Function value obtained: -47.2987\n", - "Current minimum: -49.1602\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", + "Time taken: 10.7362\n", + "Function value obtained: -122.1737\n", + "Current minimum: -128.5401\n", + "Iteration No: 184 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:38:49,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1987\n", - "Function value obtained: -46.2405\n", - "Current minimum: -49.1602\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", + "Time taken: 10.6880\n", + "Function value obtained: -122.2317\n", + "Current minimum: -128.5401\n", + "Iteration No: 185 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:39:00,611\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3101\n", - "Function value obtained: -46.9703\n", - "Current minimum: -49.1602\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", + "Time taken: 10.9029\n", + "Function value obtained: -126.0234\n", + "Current minimum: -128.5401\n", + "Iteration No: 186 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:39:11,535\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3039\n", - "Function value obtained: -47.3671\n", - "Current minimum: -49.1602\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2898\n", - "Function value obtained: -49.2781\n", - "Current minimum: -49.2781\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2604\n", - "Function value obtained: -45.6923\n", - "Current minimum: -49.2781\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5017\n", - "Function value obtained: -47.5145\n", - "Current minimum: -49.2781\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4741\n", - "Function value obtained: -46.3412\n", - "Current minimum: -49.2781\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", + "Time taken: 10.7352\n", + "Function value obtained: -123.9945\n", + "Current minimum: -128.5401\n", + "Iteration No: 187 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:39:22,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9393\n", + "Function value obtained: -121.1404\n", + "Current minimum: -128.5401\n", + "Iteration No: 188 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:39:33,215\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2148\n", + "Function value obtained: -121.9307\n", + "Current minimum: -128.5401\n", + "Iteration No: 189 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:39:43,468\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5466\n", + "Function value obtained: -123.8632\n", + "Current minimum: -128.5401\n", + "Iteration No: 190 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:39:53,995\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8137\n", + "Function value obtained: -122.4648\n", + "Current minimum: -128.5401\n", + "Iteration No: 191 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:40:04,927\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4891\n", - "Function value obtained: -47.0852\n", - "Current minimum: -49.2781\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", + "Time taken: 11.0605\n", + "Function value obtained: -122.3731\n", + "Current minimum: -128.5401\n", + "Iteration No: 192 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:40:15,873\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4091\n", - "Function value obtained: -46.4869\n", - "Current minimum: -49.2781\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", + "Time taken: 10.9528\n", + "Function value obtained: -127.2429\n", + "Current minimum: -128.5401\n", + "Iteration No: 193 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:40:27,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5463\n", - "Function value obtained: -47.2560\n", - "Current minimum: -49.2781\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", + "Time taken: 12.1784\n", + "Function value obtained: -124.8846\n", + "Current minimum: -128.5401\n", + "Iteration No: 194 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:40:39,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4077\n", - "Function value obtained: -45.5755\n", - "Current minimum: -49.2781\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", + "Time taken: 10.5402\n", + "Function value obtained: -123.3939\n", + "Current minimum: -128.5401\n", + "Iteration No: 195 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:40:49,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5328\n", - "Function value obtained: -47.5300\n", - "Current minimum: -49.2781\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", + "Time taken: 11.2673\n", + "Function value obtained: -123.9125\n", + "Current minimum: -128.5401\n", + "Iteration No: 196 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:41:00,860\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4624\n", - "Function value obtained: -46.2453\n", - "Current minimum: -49.2781\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", + "Time taken: 10.8785\n", + "Function value obtained: -125.1409\n", + "Current minimum: -128.5401\n", + "Iteration No: 197 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:41:11,695\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5501\n", - "Function value obtained: -45.9818\n", - "Current minimum: -49.2781\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", + "Time taken: 11.1730\n", + "Function value obtained: -127.1347\n", + "Current minimum: -128.5401\n", + "Iteration No: 198 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:41:22,910\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6110\n", - "Function value obtained: -44.2845\n", - "Current minimum: -49.2781\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", + "Time taken: 11.3097\n", + "Function value obtained: -118.8484\n", + "Current minimum: -128.5401\n", + "Iteration No: 199 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:41:34,257\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5313\n", - "Function value obtained: -50.3900\n", - "Current minimum: -50.3900\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", + "Time taken: 10.8070\n", + "Function value obtained: -125.6811\n", + "Current minimum: -128.5401\n", + "Iteration No: 200 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:41:45,000\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5884\n", - "Function value obtained: -47.5778\n", - "Current minimum: -50.3900\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", + "Time taken: 11.1180\n", + "Function value obtained: -124.9164\n", + "Current minimum: -128.5401\n", + "Iteration No: 201 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:41:56,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5219\n", - "Function value obtained: -45.7308\n", - "Current minimum: -50.3900\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", + "Time taken: 11.4135\n", + "Function value obtained: -122.6802\n", + "Current minimum: -128.5401\n", + "Iteration No: 202 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:42:07,577\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4850\n", - "Function value obtained: -46.5011\n", - "Current minimum: -50.3900\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", + "Time taken: 11.2825\n", + "Function value obtained: -121.4802\n", + "Current minimum: -128.5401\n", + "Iteration No: 203 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:42:18,842\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7918\n", - "Function value obtained: -47.2935\n", - "Current minimum: -50.3900\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", + "Time taken: 11.1379\n", + "Function value obtained: -121.5595\n", + "Current minimum: -128.5401\n", + "Iteration No: 204 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:42:30,983\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7020\n", - "Function value obtained: -46.3767\n", - "Current minimum: -50.3900\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", + "Time taken: 12.2644\n", + "Function value obtained: -123.3149\n", + "Current minimum: -128.5401\n", + "Iteration No: 205 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:42:42,327\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6193\n", - "Function value obtained: -47.5970\n", - "Current minimum: -50.3900\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6386\n", - "Function value obtained: -46.2089\n", - "Current minimum: -50.3900\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7037\n", - "Function value obtained: -47.2441\n", - "Current minimum: -50.3900\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7155\n", - "Function value obtained: -45.6728\n", - "Current minimum: -50.3900\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7618\n", - "Function value obtained: -47.8828\n", - "Current minimum: -50.3900\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", + "Time taken: 11.5011\n", + "Function value obtained: -126.7555\n", + "Current minimum: -128.5401\n", + "Iteration No: 206 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:42:53,830\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2261\n", + "Function value obtained: -123.2405\n", + "Current minimum: -128.5401\n", + "Iteration No: 207 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:43:05,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4226\n", + "Function value obtained: -120.8481\n", + "Current minimum: -128.5401\n", + "Iteration No: 208 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:43:17,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5591\n", + "Function value obtained: -125.9200\n", + "Current minimum: -128.5401\n", + "Iteration No: 209 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:43:29,028\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4403\n", + "Function value obtained: -120.6302\n", + "Current minimum: -128.5401\n", + "Iteration No: 210 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:43:40,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7382\n", - "Function value obtained: -46.1474\n", - "Current minimum: -50.3900\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", + "Time taken: 11.3829\n", + "Function value obtained: -124.2500\n", + "Current minimum: -128.5401\n", + "Iteration No: 211 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:43:51,852\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7545\n", - "Function value obtained: -47.6435\n", - "Current minimum: -50.3900\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", + "Time taken: 11.3774\n", + "Function value obtained: -129.2935\n", + "Current minimum: -129.2935\n", + "Iteration No: 212 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:44:03,252\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9274\n", - "Function value obtained: -46.2764\n", - "Current minimum: -50.3900\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", + "Time taken: 11.2410\n", + "Function value obtained: -128.0971\n", + "Current minimum: -129.2935\n", + "Iteration No: 213 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:44:14,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8311\n", - "Function value obtained: -47.7107\n", - "Current minimum: -50.3900\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", + "Time taken: 11.6965\n", + "Function value obtained: -125.7516\n", + "Current minimum: -129.2935\n", + "Iteration No: 214 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:44:26,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7216\n", - "Function value obtained: -45.7783\n", - "Current minimum: -50.3900\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", + "Time taken: 11.7463\n", + "Function value obtained: -122.6122\n", + "Current minimum: -129.2935\n", + "Iteration No: 215 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:44:37,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8901\n", - "Function value obtained: -46.7034\n", - "Current minimum: -50.3900\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", + "Time taken: 11.5021\n", + "Function value obtained: -123.3440\n", + "Current minimum: -129.2935\n", + "Iteration No: 216 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:44:49,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7970\n", - "Function value obtained: -48.6155\n", - "Current minimum: -50.3900\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", + "Time taken: 11.7160\n", + "Function value obtained: -121.1527\n", + "Current minimum: -129.2935\n", + "Iteration No: 217 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:45:01,143\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9145\n", - "Function value obtained: -45.7807\n", - "Current minimum: -50.3900\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", + "Time taken: 11.8249\n", + "Function value obtained: -124.9355\n", + "Current minimum: -129.2935\n", + "Iteration No: 218 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:45:13,992\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8581\n", - "Function value obtained: -47.6175\n", - "Current minimum: -50.3900\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", + "Time taken: 12.5388\n", + "Function value obtained: -123.1285\n", + "Current minimum: -129.2935\n", + "Iteration No: 219 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:45:25,521\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1427\n", - "Function value obtained: -46.7095\n", - "Current minimum: -50.3900\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", + "Time taken: 11.5193\n", + "Function value obtained: -121.8120\n", + "Current minimum: -129.2935\n", + "Iteration No: 220 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:45:37,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9117\n", - "Function value obtained: -48.1388\n", - "Current minimum: -50.3900\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", + "Time taken: 11.1476\n", + "Function value obtained: -123.5880\n", + "Current minimum: -129.2935\n", + "Iteration No: 221 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:45:48,144\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1734\n", - "Function value obtained: -46.8995\n", - "Current minimum: -50.3900\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", + "Time taken: 11.1725\n", + "Function value obtained: -123.6150\n", + "Current minimum: -129.2935\n", + "Iteration No: 222 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:45:59,395\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0980\n", - "Function value obtained: -50.1261\n", - "Current minimum: -50.3900\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", + "Time taken: 11.6523\n", + "Function value obtained: -123.3699\n", + "Current minimum: -129.2935\n", + "Iteration No: 223 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:46:11,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0633\n", - "Function value obtained: -44.6711\n", - "Current minimum: -50.3900\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", + "Time taken: 11.5702\n", + "Function value obtained: -121.6367\n", + "Current minimum: -129.2935\n", + "Iteration No: 224 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:46:22,608\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9759\n", - "Function value obtained: -47.1576\n", - "Current minimum: -50.3900\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0273\n", - "Function value obtained: -47.7665\n", - "Current minimum: -50.3900\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2018\n", - "Function value obtained: -46.0928\n", - "Current minimum: -50.3900\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2215\n", - "Function value obtained: -46.2331\n", - "Current minimum: -50.3900\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1366\n", - "Function value obtained: -48.4136\n", - "Current minimum: -50.3900\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0939\n", - "Function value obtained: -45.8923\n", - "Current minimum: -50.3900\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", + "Time taken: 11.6610\n", + "Function value obtained: -123.2568\n", + "Current minimum: -129.2935\n", + "Iteration No: 225 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:46:34,320\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 225 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0946\n", + "Function value obtained: -124.8260\n", + "Current minimum: -129.2935\n", + "Iteration No: 226 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:46:46,400\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 226 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3049\n", + "Function value obtained: -124.8341\n", + "Current minimum: -129.2935\n", + "Iteration No: 227 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:46:58,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 227 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7320\n", + "Function value obtained: -122.3812\n", + "Current minimum: -129.2935\n", + "Iteration No: 228 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:47:10,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 228 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7175\n", + "Function value obtained: -123.0293\n", + "Current minimum: -129.2935\n", + "Iteration No: 229 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:47:22,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 229 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2024\n", + "Function value obtained: -122.8992\n", + "Current minimum: -129.2935\n", + "Iteration No: 230 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:47:34,375\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2826\n", - "Function value obtained: -47.9723\n", - "Current minimum: -50.3900\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", + "Time taken: 12.2708\n", + "Function value obtained: -121.7995\n", + "Current minimum: -129.2935\n", + "Iteration No: 231 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:47:46,648\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2689\n", - "Function value obtained: -46.6460\n", - "Current minimum: -50.3900\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", + "Time taken: 11.8999\n", + "Function value obtained: -122.8777\n", + "Current minimum: -129.2935\n", + "Iteration No: 232 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:47:58,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0645\n", - "Function value obtained: -45.9143\n", - "Current minimum: -50.3900\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", + "Time taken: 12.0767\n", + "Function value obtained: -122.3955\n", + "Current minimum: -129.2935\n", + "Iteration No: 233 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:48:10,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3859\n", - "Function value obtained: -46.5508\n", - "Current minimum: -50.3900\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", + "Time taken: 12.1483\n", + "Function value obtained: -125.5816\n", + "Current minimum: -129.2935\n", + "Iteration No: 234 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:48:22,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4730\n", - "Function value obtained: -47.9804\n", - "Current minimum: -50.3900\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", + "Time taken: 11.9495\n", + "Function value obtained: -128.2199\n", + "Current minimum: -129.2935\n", + "Iteration No: 235 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:48:35,740\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3902\n", - "Function value obtained: -47.0151\n", - "Current minimum: -50.3900\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", + "Time taken: 12.9145\n", + "Function value obtained: -120.8283\n", + "Current minimum: -129.2935\n", + "Iteration No: 236 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:48:47,700\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2887\n", - "Function value obtained: -44.4297\n", - "Current minimum: -50.3900\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", + "Time taken: 12.3823\n", + "Function value obtained: -122.4194\n", + "Current minimum: -129.2935\n", + "Iteration No: 237 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:49:00,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3634\n", - "Function value obtained: -46.6838\n", - "Current minimum: -50.3900\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", + "Time taken: 12.4055\n", + "Function value obtained: -124.5596\n", + "Current minimum: -129.2935\n", + "Iteration No: 238 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:49:12,467\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2440\n", - "Function value obtained: -48.1649\n", - "Current minimum: -50.3900\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", + "Time taken: 12.2159\n", + "Function value obtained: -122.4044\n", + "Current minimum: -129.2935\n", + "Iteration No: 239 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:49:24,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2938\n", - "Function value obtained: -46.2227\n", - "Current minimum: -50.3900\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", + "Time taken: 12.1730\n", + "Function value obtained: -121.4884\n", + "Current minimum: -129.2935\n", + "Iteration No: 240 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:49:36,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4050\n", - "Function value obtained: -45.0731\n", - "Current minimum: -50.3900\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", + "Time taken: 12.3723\n", + "Function value obtained: -123.5492\n", + "Current minimum: -129.2935\n", + "Iteration No: 241 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:49:49,237\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4776\n", - "Function value obtained: -45.9867\n", - "Current minimum: -50.3900\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", + "Time taken: 12.2555\n", + "Function value obtained: -123.9846\n", + "Current minimum: -129.2935\n", + "Iteration No: 242 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:50:01,499\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4071\n", - "Function value obtained: -47.1149\n", - "Current minimum: -50.3900\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", + "Time taken: 12.2907\n", + "Function value obtained: -124.0299\n", + "Current minimum: -129.2935\n", + "Iteration No: 243 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:50:13,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5018\n", - "Function value obtained: -48.3418\n", - "Current minimum: -50.3900\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3588\n", - "Function value obtained: -46.9173\n", - "Current minimum: -50.3900\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5967\n", - "Function value obtained: -47.6389\n", - "Current minimum: -50.3900\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5045\n", - "Function value obtained: -47.4420\n", - "Current minimum: -50.3900\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6585\n", - "Function value obtained: -46.9558\n", - "Current minimum: -50.3900\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", + "Time taken: 12.1261\n", + "Function value obtained: -122.7358\n", + "Current minimum: -129.2935\n", + "Iteration No: 244 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:50:25,916\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 244 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3272\n", + "Function value obtained: -123.5404\n", + "Current minimum: -129.2935\n", + "Iteration No: 245 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:50:38,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 245 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4230\n", + "Function value obtained: -124.5492\n", + "Current minimum: -129.2935\n", + "Iteration No: 246 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:50:50,698\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 246 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7645\n", + "Function value obtained: -127.7367\n", + "Current minimum: -129.2935\n", + "Iteration No: 247 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:51:03,337\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 247 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0274\n", + "Function value obtained: -123.5547\n", + "Current minimum: -129.2935\n", + "Iteration No: 248 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:51:15,359\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5302\n", - "Function value obtained: -47.2430\n", - "Current minimum: -50.3900\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", + "Time taken: 12.0625\n", + "Function value obtained: -125.6569\n", + "Current minimum: -129.2935\n", + "Iteration No: 249 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:51:28,603\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6487\n", - "Function value obtained: -46.9436\n", - "Current minimum: -50.3900\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", + "Time taken: 13.6057\n", + "Function value obtained: -124.3901\n", + "Current minimum: -129.2935\n", + "Iteration No: 250 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:51:41,173\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7154\n", - "Function value obtained: -47.2870\n", - "Current minimum: -50.3900\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", + "Time taken: 12.6674\n", + "Function value obtained: -125.5029\n", + "Current minimum: -129.2935\n", + "Iteration No: 251 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:51:53,944\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7374\n", - "Function value obtained: -46.1422\n", - "Current minimum: -50.3900\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", + "Time taken: 12.8753\n", + "Function value obtained: -121.8113\n", + "Current minimum: -129.2935\n", + "Iteration No: 252 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:52:06,692\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5813\n", - "Function value obtained: -46.9244\n", - "Current minimum: -50.3900\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", + "Time taken: 12.4818\n", + "Function value obtained: -123.7452\n", + "Current minimum: -129.2935\n", + "Iteration No: 253 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:52:19,223\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5524\n", - "Function value obtained: -47.1142\n", - "Current minimum: -50.3900\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", + "Time taken: 12.3979\n", + "Function value obtained: -124.0198\n", + "Current minimum: -129.2935\n", + "Iteration No: 254 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:52:31,589\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6731\n", - "Function value obtained: -47.1417\n", - "Current minimum: -50.3900\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", + "Time taken: 12.3888\n", + "Function value obtained: -125.6926\n", + "Current minimum: -129.2935\n", + "Iteration No: 255 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:52:44,015\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6971\n", - "Function value obtained: -48.0082\n", - "Current minimum: -50.3900\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", + "Time taken: 12.7041\n", + "Function value obtained: -120.1428\n", + "Current minimum: -129.2935\n", + "Iteration No: 256 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:52:56,737\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6721\n", - "Function value obtained: -44.1149\n", - "Current minimum: -50.3900\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", + "Time taken: 12.7209\n", + "Function value obtained: -123.8140\n", + "Current minimum: -129.2935\n", + "Iteration No: 257 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:53:09,465\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7240\n", - "Function value obtained: -48.7647\n", - "Current minimum: -50.3900\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", + "Time taken: 12.4704\n", + "Function value obtained: -120.2622\n", + "Current minimum: -129.2935\n", + "Iteration No: 258 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:53:21,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8619\n", - "Function value obtained: -48.4711\n", - "Current minimum: -50.3900\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", + "Time taken: 12.4322\n", + "Function value obtained: -123.3920\n", + "Current minimum: -129.2935\n", + "Iteration No: 259 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:53:34,265\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9958\n", - "Function value obtained: -46.1754\n", - "Current minimum: -50.3900\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", + "Time taken: 12.5801\n", + "Function value obtained: -120.6963\n", + "Current minimum: -129.2935\n", + "Iteration No: 260 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:53:46,985\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7924\n", - "Function value obtained: -47.3461\n", - "Current minimum: -50.3900\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", + "Time taken: 12.9716\n", + "Function value obtained: -123.2907\n", + "Current minimum: -129.2935\n", + "Iteration No: 261 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:53:59,967\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9955\n", - "Function value obtained: -47.7343\n", - "Current minimum: -50.3900\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", + "Time taken: 13.1139\n", + "Function value obtained: -125.5411\n", + "Current minimum: -129.2935\n", + "Iteration No: 262 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:54:13,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9547\n", - "Function value obtained: -47.4042\n", - "Current minimum: -50.3900\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8644\n", - "Function value obtained: -47.5446\n", - "Current minimum: -50.3900\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9177\n", - "Function value obtained: -46.0754\n", - "Current minimum: -50.3900\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1236\n", - "Function value obtained: -46.5039\n", - "Current minimum: -50.3900\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1350\n", - "Function value obtained: -47.5166\n", - "Current minimum: -50.3900\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0588\n", - "Function value obtained: -47.5519\n", - "Current minimum: -50.3900\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", + "Time taken: 13.1115\n", + "Function value obtained: -123.5109\n", + "Current minimum: -129.2935\n", + "Iteration No: 263 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:54:26,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 263 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8200\n", + "Function value obtained: -123.7584\n", + "Current minimum: -129.2935\n", + "Iteration No: 264 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:54:38,996\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 264 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9946\n", + "Function value obtained: -125.6160\n", + "Current minimum: -129.2935\n", + "Iteration No: 265 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:54:51,986\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 265 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2403\n", + "Function value obtained: -122.1496\n", + "Current minimum: -129.2935\n", + "Iteration No: 266 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:55:05,250\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 266 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5788\n", + "Function value obtained: -124.2446\n", + "Current minimum: -129.2935\n", + "Iteration No: 267 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:55:18,813\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 267 ended. Search finished for the next optimal point.\n", + "Time taken: 13.1190\n", + "Function value obtained: -123.9094\n", + "Current minimum: -129.2935\n", + "Iteration No: 268 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:55:31,965\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9890\n", - "Function value obtained: -48.8447\n", - "Current minimum: -50.3900\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", + "Time taken: 13.1145\n", + "Function value obtained: -125.5709\n", + "Current minimum: -129.2935\n", + "Iteration No: 269 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:55:45,061\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1606\n", - "Function value obtained: -47.1201\n", - "Current minimum: -50.3900\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", + "Time taken: 13.1283\n", + "Function value obtained: -122.8718\n", + "Current minimum: -129.2935\n", + "Iteration No: 270 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:55:58,171\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0070\n", - "Function value obtained: -48.6648\n", - "Current minimum: -50.3900\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", + "Time taken: 12.9732\n", + "Function value obtained: -119.5956\n", + "Current minimum: -129.2935\n", + "Iteration No: 271 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:56:11,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2681\n", - "Function value obtained: -46.2319\n", - "Current minimum: -50.3900\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", + "Time taken: 13.2341\n", + "Function value obtained: -123.2431\n", + "Current minimum: -129.2935\n", + "Iteration No: 272 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:56:24,445\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0337\n", - "Function value obtained: -46.0469\n", - "Current minimum: -50.3900\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", + "Time taken: 12.9155\n", + "Function value obtained: -123.9309\n", + "Current minimum: -129.2935\n", + "Iteration No: 273 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:56:37,385\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2960\n", - "Function value obtained: -47.4200\n", - "Current minimum: -50.3900\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", + "Time taken: 13.8917\n", + "Function value obtained: -123.3262\n", + "Current minimum: -129.2935\n", + "Iteration No: 274 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:56:51,269\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1563\n", - "Function value obtained: -47.0962\n", - "Current minimum: -50.3900\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", + "Time taken: 14.1295\n", + "Function value obtained: -122.3763\n", + "Current minimum: -129.2935\n", + "Iteration No: 275 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:57:05,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3941\n", - "Function value obtained: -46.4848\n", - "Current minimum: -50.3900\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1359\n", - "Function value obtained: -46.1953\n", - "Current minimum: -50.3900\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3135\n", - "Function value obtained: -44.3502\n", - "Current minimum: -50.3900\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2371\n", - "Function value obtained: -48.6788\n", - "Current minimum: -50.3900\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3045\n", - "Function value obtained: -48.1817\n", - "Current minimum: -50.3900\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3008\n", - "Function value obtained: -47.5294\n", - "Current minimum: -50.3900\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4910\n", - "Function value obtained: -46.3327\n", - "Current minimum: -50.3900\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3888\n", - "Function value obtained: -45.6673\n", - "Current minimum: -50.3900\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4214\n", - "Function value obtained: -45.5122\n", - "Current minimum: -50.3900\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4576\n", - "Function value obtained: -46.6317\n", - "Current minimum: -50.3900\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4995\n", - "Function value obtained: -48.3950\n", - "Current minimum: -50.3900\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5975\n", - "Function value obtained: -47.3764\n", - "Current minimum: -50.3900\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4760\n", - "Function value obtained: -46.1770\n", - "Current minimum: -50.3900\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4981\n", - "Function value obtained: -48.4162\n", - "Current minimum: -50.3900\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6847\n", - "Function value obtained: -46.3198\n", - "Current minimum: -50.3900\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7812\n", - "Function value obtained: -44.1499\n", - "Current minimum: -50.3900\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6644\n", - "Function value obtained: -48.3996\n", - "Current minimum: -50.3900\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4829\n", - "Function value obtained: -45.9433\n", - "Current minimum: -50.3900\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7236\n", - "Function value obtained: -45.6916\n", - "Current minimum: -50.3900\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3748\n", - "Function value obtained: -45.3838\n", - "Current minimum: -50.3900\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6545\n", - "Function value obtained: -47.8300\n", - "Current minimum: -50.3900\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8150\n", - "Function value obtained: -49.2014\n", - "Current minimum: -50.3900\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7817\n", - "Function value obtained: -45.3947\n", - "Current minimum: -50.3900\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8951\n", - "Function value obtained: -47.4768\n", - "Current minimum: -50.3900\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8960\n", - "Function value obtained: -47.9250\n", - "Current minimum: -50.3900\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8756\n", - "Function value obtained: -45.0798\n", - "Current minimum: -50.3900\n", - "CPU times: user 2h 2min 7s, sys: 1h 11min 48s, total: 3h 13min 56s\n", - "Wall time: 15min 22s\n" + "Time taken: 13.3133\n", + "Function value obtained: -126.2470\n", + "Current minimum: -129.2935\n", + "Iteration No: 276 started. Searching for the next optimal point.\n" ] }, { - "data": { - "text/plain": [ - "(-50.39000406549121, [0.05365088255575121])" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", - "msy_gp.fun, msy_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-03 23:57:18,723\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] }, - "scrolled": true - }, - "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.3560\n", - "Function value obtained: -46.5391\n", - "Current minimum: -46.5391\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.1664\n", - "Function value obtained: -4.6581\n", - "Current minimum: -46.5391\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.3000\n", - "Function value obtained: -14.8136\n", - "Current minimum: -46.5391\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.2598\n", - "Function value obtained: -3.6463\n", - "Current minimum: -46.5391\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.1637\n", - "Function value obtained: -4.3602\n", - "Current minimum: -46.5391\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.2462\n", - "Function value obtained: -4.0893\n", - "Current minimum: -46.5391\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.2717\n", - "Function value obtained: -10.5623\n", - "Current minimum: -46.5391\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.2456\n", - "Function value obtained: -38.1398\n", - "Current minimum: -46.5391\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.2314\n", - "Function value obtained: -48.0675\n", - "Current minimum: -48.0675\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.4094\n", - "Function value obtained: -6.6195\n", - "Current minimum: -48.0675\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4140\n", - "Function value obtained: -49.6017\n", - "Current minimum: -49.6017\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4435\n", - "Function value obtained: -46.6843\n", - "Current minimum: -49.6017\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4193\n", - "Function value obtained: -45.0990\n", - "Current minimum: -49.6017\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5035\n", - "Function value obtained: -46.8608\n", - "Current minimum: -49.6017\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5919\n", - "Function value obtained: -49.3540\n", - "Current minimum: -49.6017\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4357\n", - "Function value obtained: -47.5765\n", - "Current minimum: -49.6017\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4996\n", - "Function value obtained: -45.1326\n", - "Current minimum: -49.6017\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4617\n", - "Function value obtained: -46.9510\n", - "Current minimum: -49.6017\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4780\n", - "Function value obtained: -12.6043\n", - "Current minimum: -49.6017\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4956\n", - "Function value obtained: -48.6197\n", - "Current minimum: -49.6017\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4565\n", - "Function value obtained: -45.1803\n", - "Current minimum: -49.6017\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3789\n", - "Function value obtained: -48.0291\n", - "Current minimum: -49.6017\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4518\n", - "Function value obtained: -47.8936\n", - "Current minimum: -49.6017\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4929\n", - "Function value obtained: -46.8791\n", - "Current minimum: -49.6017\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5805\n", - "Function value obtained: -48.7646\n", - "Current minimum: -49.6017\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4410\n", - "Function value obtained: -45.4169\n", - "Current minimum: -49.6017\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5256\n", - "Function value obtained: -46.7357\n", - "Current minimum: -49.6017\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5359\n", - "Function value obtained: -46.2242\n", - "Current minimum: -49.6017\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5400\n", - "Function value obtained: -12.6620\n", - "Current minimum: -49.6017\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6019\n", - "Function value obtained: -43.9229\n", - "Current minimum: -49.6017\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4984\n", - "Function value obtained: -47.8351\n", - "Current minimum: -49.6017\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5293\n", - "Function value obtained: -44.4191\n", - "Current minimum: -49.6017\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4842\n", - "Function value obtained: -47.5384\n", - "Current minimum: -49.6017\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6029\n", - "Function value obtained: -47.4318\n", - "Current minimum: -49.6017\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4040\n", - "Function value obtained: -44.8686\n", - "Current minimum: -49.6017\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5284\n", - "Function value obtained: -47.4501\n", - "Current minimum: -49.6017\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3685\n", - "Function value obtained: -47.0818\n", - "Current minimum: -49.6017\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4836\n", - "Function value obtained: -46.7556\n", - "Current minimum: -49.6017\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5081\n", - "Function value obtained: -46.9364\n", - "Current minimum: -49.6017\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4114\n", - "Function value obtained: -46.0513\n", - "Current minimum: -49.6017\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4602\n", - "Function value obtained: -47.1258\n", - "Current minimum: -49.6017\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4598\n", - "Function value obtained: -44.6687\n", - "Current minimum: -49.6017\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4767\n", - "Function value obtained: -45.9894\n", - "Current minimum: -49.6017\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5332\n", - "Function value obtained: -46.3990\n", - "Current minimum: -49.6017\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5325\n", - "Function value obtained: -47.7062\n", - "Current minimum: -49.6017\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5390\n", - "Function value obtained: -47.8023\n", - "Current minimum: -49.6017\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4629\n", - "Function value obtained: -45.6460\n", - "Current minimum: -49.6017\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5021\n", - "Function value obtained: -44.3852\n", - "Current minimum: -49.6017\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4780\n", - "Function value obtained: -46.6708\n", - "Current minimum: -49.6017\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4235\n", - "Function value obtained: -45.2947\n", - "Current minimum: -49.6017\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4191\n", - "Function value obtained: -47.4422\n", - "Current minimum: -49.6017\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5193\n", - "Function value obtained: -47.2893\n", - "Current minimum: -49.6017\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4471\n", - "Function value obtained: -48.0579\n", - "Current minimum: -49.6017\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5124\n", - "Function value obtained: -46.6369\n", - "Current minimum: -49.6017\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5033\n", - "Function value obtained: -48.1478\n", - "Current minimum: -49.6017\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5597\n", - "Function value obtained: -48.1605\n", - "Current minimum: -49.6017\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4899\n", - "Function value obtained: -45.0397\n", - "Current minimum: -49.6017\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4978\n", - "Function value obtained: -46.5459\n", - "Current minimum: -49.6017\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4811\n", - "Function value obtained: -43.7516\n", - "Current minimum: -49.6017\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5171\n", - "Function value obtained: -47.2481\n", - "Current minimum: -49.6017\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4386\n", - "Function value obtained: -46.4790\n", - "Current minimum: -49.6017\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4536\n", - "Function value obtained: -47.3387\n", - "Current minimum: -49.6017\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6102\n", - "Function value obtained: -47.5327\n", - "Current minimum: -49.6017\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5174\n", - "Function value obtained: -45.3859\n", - "Current minimum: -49.6017\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4711\n", - "Function value obtained: -46.8727\n", - "Current minimum: -49.6017\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5031\n", - "Function value obtained: -48.0277\n", - "Current minimum: -49.6017\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5509\n", - "Function value obtained: -48.6187\n", - "Current minimum: -49.6017\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5195\n", - "Function value obtained: -48.3695\n", - "Current minimum: -49.6017\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4830\n", - "Function value obtained: -44.5009\n", - "Current minimum: -49.6017\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5454\n", - "Function value obtained: -45.3096\n", - "Current minimum: -49.6017\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4323\n", - "Function value obtained: -47.1526\n", - "Current minimum: -49.6017\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4273\n", - "Function value obtained: -47.3175\n", - "Current minimum: -49.6017\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5579\n", - "Function value obtained: -46.5905\n", - "Current minimum: -49.6017\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5067\n", - "Function value obtained: -46.8752\n", - "Current minimum: -49.6017\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5313\n", - "Function value obtained: -47.8672\n", - "Current minimum: -49.6017\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5224\n", - "Function value obtained: -45.6860\n", - "Current minimum: -49.6017\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5298\n", - "Function value obtained: -46.8637\n", - "Current minimum: -49.6017\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7157\n", - "Function value obtained: -47.9359\n", - "Current minimum: -49.6017\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4869\n", - "Function value obtained: -48.3924\n", - "Current minimum: -49.6017\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4701\n", - "Function value obtained: -45.2819\n", - "Current minimum: -49.6017\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4596\n", - "Function value obtained: -48.8099\n", - "Current minimum: -49.6017\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4203\n", - "Function value obtained: -44.6818\n", - "Current minimum: -49.6017\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3309\n", - "Function value obtained: -48.0720\n", - "Current minimum: -49.6017\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5261\n", - "Function value obtained: -47.3489\n", - "Current minimum: -49.6017\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4705\n", - "Function value obtained: -48.0898\n", - "Current minimum: -49.6017\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4849\n", - "Function value obtained: -45.8602\n", - "Current minimum: -49.6017\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6133\n", - "Function value obtained: -47.4123\n", - "Current minimum: -49.6017\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5090\n", - "Function value obtained: -46.1113\n", - "Current minimum: -49.6017\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5676\n", - "Function value obtained: -48.4236\n", - "Current minimum: -49.6017\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4747\n", - "Function value obtained: -47.6057\n", - "Current minimum: -49.6017\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4737\n", - "Function value obtained: -45.1571\n", - "Current minimum: -49.6017\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4616\n", - "Function value obtained: -48.5987\n", - "Current minimum: -49.6017\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4667\n", - "Function value obtained: -47.1953\n", - "Current minimum: -49.6017\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4862\n", - "Function value obtained: -46.9125\n", - "Current minimum: -49.6017\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4970\n", - "Function value obtained: -47.4312\n", - "Current minimum: -49.6017\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4997\n", - "Function value obtained: -47.1148\n", - "Current minimum: -49.6017\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6946\n", - "Function value obtained: -46.7082\n", - "Current minimum: -49.6017\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5323\n", - "Function value obtained: -47.0256\n", - "Current minimum: -49.6017\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4895\n", - "Function value obtained: -45.8617\n", - "Current minimum: -49.6017\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4927\n", - "Function value obtained: -46.0801\n", - "Current minimum: -49.6017\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5328\n", - "Function value obtained: -47.8178\n", - "Current minimum: -49.6017\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5578\n", - "Function value obtained: -45.8014\n", - "Current minimum: -49.6017\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5063\n", - "Function value obtained: -48.7166\n", - "Current minimum: -49.6017\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4746\n", - "Function value obtained: -46.6069\n", - "Current minimum: -49.6017\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5559\n", - "Function value obtained: -47.1771\n", - "Current minimum: -49.6017\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4994\n", - "Function value obtained: -47.1168\n", - "Current minimum: -49.6017\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5939\n", - "Function value obtained: -46.4010\n", - "Current minimum: -49.6017\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5162\n", - "Function value obtained: -48.2321\n", - "Current minimum: -49.6017\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4968\n", - "Function value obtained: -45.6238\n", - "Current minimum: -49.6017\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5985\n", - "Function value obtained: -47.4828\n", - "Current minimum: -49.6017\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5077\n", - "Function value obtained: -46.7207\n", - "Current minimum: -49.6017\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5293\n", - "Function value obtained: -46.3870\n", - "Current minimum: -49.6017\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4890\n", - "Function value obtained: -47.6239\n", - "Current minimum: -49.6017\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5437\n", - "Function value obtained: -46.1445\n", - "Current minimum: -49.6017\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4350\n", - "Function value obtained: -47.7099\n", - "Current minimum: -49.6017\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4450\n", - "Function value obtained: -47.2153\n", - "Current minimum: -49.6017\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5301\n", - "Function value obtained: -46.0510\n", - "Current minimum: -49.6017\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6147\n", - "Function value obtained: -46.7348\n", - "Current minimum: -49.6017\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4782\n", - "Function value obtained: -48.0223\n", - "Current minimum: -49.6017\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5107\n", - "Function value obtained: -45.9638\n", - "Current minimum: -49.6017\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5445\n", - "Function value obtained: -47.4704\n", - "Current minimum: -49.6017\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4802\n", - "Function value obtained: -46.3621\n", - "Current minimum: -49.6017\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4472\n", - "Function value obtained: -48.2987\n", - "Current minimum: -49.6017\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4813\n", - "Function value obtained: -45.8185\n", - "Current minimum: -49.6017\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5345\n", - "Function value obtained: -46.9240\n", - "Current minimum: -49.6017\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6460\n", - "Function value obtained: -45.6050\n", - "Current minimum: -49.6017\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5271\n", - "Function value obtained: -45.5833\n", - "Current minimum: -49.6017\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5524\n", - "Function value obtained: -45.4827\n", - "Current minimum: -49.6017\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5740\n", - "Function value obtained: -48.2536\n", - "Current minimum: -49.6017\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4685\n", - "Function value obtained: -46.3540\n", - "Current minimum: -49.6017\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5441\n", - "Function value obtained: -47.9790\n", - "Current minimum: -49.6017\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5442\n", - "Function value obtained: -46.5460\n", - "Current minimum: -49.6017\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4367\n", - "Function value obtained: -49.8897\n", - "Current minimum: -49.8897\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5285\n", - "Function value obtained: -48.0609\n", - "Current minimum: -49.8897\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5231\n", - "Function value obtained: -45.9417\n", - "Current minimum: -49.8897\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5069\n", - "Function value obtained: -48.1052\n", - "Current minimum: -49.8897\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4651\n", - "Function value obtained: -47.1823\n", - "Current minimum: -49.8897\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5213\n", - "Function value obtained: -46.5411\n", - "Current minimum: -49.8897\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4664\n", - "Function value obtained: -44.4394\n", - "Current minimum: -49.8897\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7325\n", - "Function value obtained: -48.4451\n", - "Current minimum: -49.8897\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5663\n", - "Function value obtained: -46.7940\n", - "Current minimum: -49.8897\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5296\n", - "Function value obtained: -47.4213\n", - "Current minimum: -49.8897\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5615\n", - "Function value obtained: -44.7370\n", - "Current minimum: -49.8897\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4711\n", - "Function value obtained: -46.5875\n", - "Current minimum: -49.8897\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4040\n", - "Function value obtained: -46.5380\n", - "Current minimum: -49.8897\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4615\n", - "Function value obtained: -47.0075\n", - "Current minimum: -49.8897\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5457\n", - "Function value obtained: -47.6239\n", - "Current minimum: -49.8897\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4523\n", - "Function value obtained: -45.9532\n", - "Current minimum: -49.8897\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5191\n", - "Function value obtained: -47.6434\n", - "Current minimum: -49.8897\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4987\n", - "Function value obtained: -45.9662\n", - "Current minimum: -49.8897\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5810\n", - "Function value obtained: -46.5016\n", - "Current minimum: -49.8897\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4548\n", - "Function value obtained: -46.2267\n", - "Current minimum: -49.8897\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4238\n", - "Function value obtained: -47.4453\n", - "Current minimum: -49.8897\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5048\n", - "Function value obtained: -47.2020\n", - "Current minimum: -49.8897\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4631\n", - "Function value obtained: -47.1068\n", - "Current minimum: -49.8897\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3817\n", - "Function value obtained: -48.2429\n", - "Current minimum: -49.8897\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4986\n", - "Function value obtained: -44.8097\n", - "Current minimum: -49.8897\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4233\n", - "Function value obtained: -46.8809\n", - "Current minimum: -49.8897\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5612\n", - "Function value obtained: -45.5597\n", - "Current minimum: -49.8897\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6052\n", - "Function value obtained: -46.4952\n", - "Current minimum: -49.8897\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5001\n", - "Function value obtained: -46.6400\n", - "Current minimum: -49.8897\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6195\n", - "Function value obtained: -46.5302\n", - "Current minimum: -49.8897\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5431\n", - "Function value obtained: -47.6782\n", - "Current minimum: -49.8897\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4370\n", - "Function value obtained: -47.6993\n", - "Current minimum: -49.8897\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5255\n", - "Function value obtained: -10.5757\n", - "Current minimum: -49.8897\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4695\n", - "Function value obtained: -48.1290\n", - "Current minimum: -49.8897\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5103\n", - "Function value obtained: -46.8644\n", - "Current minimum: -49.8897\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4537\n", - "Function value obtained: -46.8415\n", - "Current minimum: -49.8897\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4604\n", - "Function value obtained: -47.4611\n", - "Current minimum: -49.8897\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5201\n", - "Function value obtained: -45.5961\n", - "Current minimum: -49.8897\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5280\n", - "Function value obtained: -44.9130\n", - "Current minimum: -49.8897\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4738\n", - "Function value obtained: -47.5096\n", - "Current minimum: -49.8897\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5386\n", - "Function value obtained: -46.5298\n", - "Current minimum: -49.8897\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5460\n", - "Function value obtained: -48.4569\n", - "Current minimum: -49.8897\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4322\n", - "Function value obtained: -46.6290\n", - "Current minimum: -49.8897\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5870\n", - "Function value obtained: -46.9834\n", - "Current minimum: -49.8897\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5292\n", - "Function value obtained: -45.0813\n", - "Current minimum: -49.8897\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5267\n", - "Function value obtained: -49.7659\n", - "Current minimum: -49.8897\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5247\n", - "Function value obtained: -47.7063\n", - "Current minimum: -49.8897\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4800\n", - "Function value obtained: -46.8807\n", - "Current minimum: -49.8897\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5016\n", - "Function value obtained: -46.6104\n", - "Current minimum: -49.8897\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3970\n", - "Function value obtained: -45.0529\n", - "Current minimum: -49.8897\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5808\n", - "Function value obtained: -47.7305\n", - "Current minimum: -49.8897\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5231\n", - "Function value obtained: -46.8753\n", - "Current minimum: -49.8897\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4697\n", - "Function value obtained: -46.4229\n", - "Current minimum: -49.8897\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4536\n", - "Function value obtained: -46.3220\n", - "Current minimum: -49.8897\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4468\n", - "Function value obtained: -45.0930\n", - "Current minimum: -49.8897\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4897\n", - "Function value obtained: -46.2899\n", - "Current minimum: -49.8897\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5649\n", - "Function value obtained: -45.7537\n", - "Current minimum: -49.8897\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5258\n", - "Function value obtained: -47.8918\n", - "Current minimum: -49.8897\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4762\n", - "Function value obtained: -44.7468\n", - "Current minimum: -49.8897\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4744\n", - "Function value obtained: -45.6541\n", - "Current minimum: -49.8897\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4850\n", - "Function value obtained: -47.9981\n", - "Current minimum: -49.8897\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6339\n", - "Function value obtained: -48.7292\n", - "Current minimum: -49.8897\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4541\n", - "Function value obtained: -45.9848\n", - "Current minimum: -49.8897\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4691\n", - "Function value obtained: -47.4092\n", - "Current minimum: -49.8897\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4781\n", - "Function value obtained: -47.0885\n", - "Current minimum: -49.8897\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4757\n", - "Function value obtained: -46.2062\n", - "Current minimum: -49.8897\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5059\n", - "Function value obtained: -47.5081\n", - "Current minimum: -49.8897\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5575\n", - "Function value obtained: -45.9276\n", - "Current minimum: -49.8897\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5190\n", - "Function value obtained: -46.9264\n", - "Current minimum: -49.8897\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4911\n", - "Function value obtained: -46.2056\n", - "Current minimum: -49.8897\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4858\n", - "Function value obtained: -47.2440\n", - "Current minimum: -49.8897\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4779\n", - "Function value obtained: -46.6488\n", - "Current minimum: -49.8897\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5805\n", - "Function value obtained: -46.4220\n", - "Current minimum: -49.8897\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4339\n", - "Function value obtained: -46.7641\n", - "Current minimum: -49.8897\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3939\n", - "Function value obtained: -46.9997\n", - "Current minimum: -49.8897\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5466\n", - "Function value obtained: -48.8444\n", - "Current minimum: -49.8897\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4416\n", - "Function value obtained: -46.6399\n", - "Current minimum: -49.8897\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4550\n", - "Function value obtained: -45.9676\n", - "Current minimum: -49.8897\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5161\n", - "Function value obtained: -48.5639\n", - "Current minimum: -49.8897\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4859\n", - "Function value obtained: -46.1388\n", - "Current minimum: -49.8897\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5181\n", - "Function value obtained: -46.3721\n", - "Current minimum: -49.8897\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5108\n", - "Function value obtained: -46.5996\n", - "Current minimum: -49.8897\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5101\n", - "Function value obtained: -48.4447\n", - "Current minimum: -49.8897\n", - "Iteration No: 216 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.047611662929937286] before, using random point [0.018415831307791897]\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4304\n", - "Function value obtained: -29.1544\n", - "Current minimum: -49.8897\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6251\n", - "Function value obtained: -47.1906\n", - "Current minimum: -49.8897\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3746\n", - "Function value obtained: -47.6795\n", - "Current minimum: -49.8897\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4408\n", - "Function value obtained: -46.9766\n", - "Current minimum: -49.8897\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4518\n", - "Function value obtained: -47.4589\n", - "Current minimum: -49.8897\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4711\n", - "Function value obtained: -46.4065\n", - "Current minimum: -49.8897\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4315\n", - "Function value obtained: -46.8208\n", - "Current minimum: -49.8897\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4927\n", - "Function value obtained: -48.4958\n", - "Current minimum: -49.8897\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4322\n", - "Function value obtained: -48.3613\n", - "Current minimum: -49.8897\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3822\n", - "Function value obtained: -47.1586\n", - "Current minimum: -49.8897\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4858\n", - "Function value obtained: -46.6550\n", - "Current minimum: -49.8897\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5341\n", - "Function value obtained: -45.6371\n", - "Current minimum: -49.8897\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6043\n", - "Function value obtained: -46.8676\n", - "Current minimum: -49.8897\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4331\n", - "Function value obtained: -45.4488\n", - "Current minimum: -49.8897\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4794\n", - "Function value obtained: -43.7159\n", - "Current minimum: -49.8897\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4488\n", - "Function value obtained: -47.7269\n", - "Current minimum: -49.8897\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3763\n", - "Function value obtained: -47.0402\n", - "Current minimum: -49.8897\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4456\n", - "Function value obtained: -46.3409\n", - "Current minimum: -49.8897\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5082\n", - "Function value obtained: -44.8427\n", - "Current minimum: -49.8897\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5316\n", - "Function value obtained: -45.9650\n", - "Current minimum: -49.8897\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3972\n", - "Function value obtained: -47.7037\n", - "Current minimum: -49.8897\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4648\n", - "Function value obtained: -47.3788\n", - "Current minimum: -49.8897\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5315\n", - "Function value obtained: -48.0615\n", - "Current minimum: -49.8897\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5314\n", - "Function value obtained: -45.4083\n", - "Current minimum: -49.8897\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4335\n", - "Function value obtained: -48.1749\n", - "Current minimum: -49.8897\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4931\n", - "Function value obtained: -44.8295\n", - "Current minimum: -49.8897\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5030\n", - "Function value obtained: -46.7296\n", - "Current minimum: -49.8897\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4114\n", - "Function value obtained: -45.8937\n", - "Current minimum: -49.8897\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5107\n", - "Function value obtained: -47.4962\n", - "Current minimum: -49.8897\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4967\n", - "Function value obtained: -46.7295\n", - "Current minimum: -49.8897\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4799\n", - "Function value obtained: -43.7786\n", - "Current minimum: -49.8897\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4795\n", - "Function value obtained: -47.1058\n", - "Current minimum: -49.8897\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4587\n", - "Function value obtained: -49.6577\n", - "Current minimum: -49.8897\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5489\n", - "Function value obtained: -49.3541\n", - "Current minimum: -49.8897\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5626\n", - "Function value obtained: -47.7101\n", - "Current minimum: -49.8897\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4293\n", - "Function value obtained: -45.9207\n", - "Current minimum: -49.8897\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3498\n", - "Function value obtained: -47.1748\n", - "Current minimum: -49.8897\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4637\n", - "Function value obtained: -48.7569\n", - "Current minimum: -49.8897\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4763\n", - "Function value obtained: -48.4897\n", - "Current minimum: -49.8897\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4182\n", - "Function value obtained: -40.4936\n", - "Current minimum: -49.8897\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5062\n", - "Function value obtained: -45.8526\n", - "Current minimum: -49.8897\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4394\n", - "Function value obtained: -47.1508\n", - "Current minimum: -49.8897\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5217\n", - "Function value obtained: -45.7852\n", - "Current minimum: -49.8897\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4756\n", - "Function value obtained: -46.8237\n", - "Current minimum: -49.8897\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4404\n", - "Function value obtained: -46.1407\n", - "Current minimum: -49.8897\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6887\n", - "Function value obtained: -48.1504\n", - "Current minimum: -49.8897\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4078\n", - "Function value obtained: -47.5959\n", - "Current minimum: -49.8897\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5040\n", - "Function value obtained: -46.7583\n", - "Current minimum: -49.8897\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4849\n", - "Function value obtained: -47.5103\n", - "Current minimum: -49.8897\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4771\n", - "Function value obtained: -47.8489\n", - "Current minimum: -49.8897\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4587\n", - "Function value obtained: -45.8764\n", - "Current minimum: -49.8897\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4583\n", - "Function value obtained: -46.5789\n", - "Current minimum: -49.8897\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4331\n", - "Function value obtained: -46.0664\n", - "Current minimum: -49.8897\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4405\n", - "Function value obtained: -47.8028\n", - "Current minimum: -49.8897\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4182\n", - "Function value obtained: -46.2383\n", - "Current minimum: -49.8897\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5164\n", - "Function value obtained: -45.5827\n", - "Current minimum: -49.8897\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4859\n", - "Function value obtained: -47.0983\n", - "Current minimum: -49.8897\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5458\n", - "Function value obtained: -48.8226\n", - "Current minimum: -49.8897\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4604\n", - "Function value obtained: -47.5462\n", - "Current minimum: -49.8897\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4289\n", - "Function value obtained: -47.3570\n", - "Current minimum: -49.8897\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3581\n", - "Function value obtained: -46.5619\n", - "Current minimum: -49.8897\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4701\n", - "Function value obtained: -45.2298\n", - "Current minimum: -49.8897\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4266\n", - "Function value obtained: -49.0624\n", - "Current minimum: -49.8897\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4952\n", - "Function value obtained: -45.3503\n", - "Current minimum: -49.8897\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4420\n", - "Function value obtained: -48.2820\n", - "Current minimum: -49.8897\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3905\n", - "Function value obtained: -46.8497\n", - "Current minimum: -49.8897\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4410\n", - "Function value obtained: -46.8442\n", - "Current minimum: -49.8897\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 1.2640\n", - "Function value obtained: -47.1821\n", - "Current minimum: -49.8897\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4318\n", - "Function value obtained: -45.5262\n", - "Current minimum: -49.8897\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6499\n", - "Function value obtained: -49.1007\n", - "Current minimum: -49.8897\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5032\n", - "Function value obtained: -46.3078\n", - "Current minimum: -49.8897\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5046\n", - "Function value obtained: -44.4964\n", - "Current minimum: -49.8897\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4397\n", - "Function value obtained: -46.7686\n", - "Current minimum: -49.8897\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5065\n", - "Function value obtained: -46.5951\n", - "Current minimum: -49.8897\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4144\n", - "Function value obtained: -49.6134\n", - "Current minimum: -49.8897\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4564\n", - "Function value obtained: -46.9677\n", - "Current minimum: -49.8897\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4083\n", - "Function value obtained: -46.6134\n", - "Current minimum: -49.8897\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3414\n", - "Function value obtained: -47.6949\n", - "Current minimum: -49.8897\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4464\n", - "Function value obtained: -45.4689\n", - "Current minimum: -49.8897\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4637\n", - "Function value obtained: -45.1194\n", - "Current minimum: -49.8897\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5177\n", - "Function value obtained: -48.8048\n", - "Current minimum: -49.8897\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5104\n", - "Function value obtained: -46.8760\n", - "Current minimum: -49.8897\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4363\n", - "Function value obtained: -46.8663\n", - "Current minimum: -49.8897\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4296\n", - "Function value obtained: -47.4900\n", - "Current minimum: -49.8897\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5483\n", - "Function value obtained: -47.6654\n", - "Current minimum: -49.8897\n", - "CPU times: user 2min 10s, sys: 26.7 s, total: 2min 36s\n", - "Wall time: 7min 25s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-49.8897409867848, [0.05286591768013252])" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", - "msy_gbrt.fun, msy_gbrt.x" - ] - }, - { - "cell_type": "markdown", - "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", - "metadata": {}, - "source": [ - "### Esc" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.1826\n", - "Function value obtained: -7.4553\n", - "Current minimum: -7.4553\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.1341\n", - "Function value obtained: -0.0000\n", - "Current minimum: -7.4553\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.2756\n", - "Function value obtained: -4.4028\n", - "Current minimum: -7.4553\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.1568\n", - "Function value obtained: -5.8711\n", - "Current minimum: -7.4553\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.1990\n", - "Function value obtained: -0.2118\n", - "Current minimum: -7.4553\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.1679\n", - "Function value obtained: -0.0000\n", - "Current minimum: -7.4553\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.1591\n", - "Function value obtained: -2.3609\n", - "Current minimum: -7.4553\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.2370\n", - "Function value obtained: -0.0000\n", - "Current minimum: -7.4553\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.1136\n", - "Function value obtained: -0.9760\n", - "Current minimum: -7.4553\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 6.0222\n", - "Function value obtained: -0.0000\n", - "Current minimum: -7.4553\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6276\n", - "Function value obtained: -9.8312\n", - "Current minimum: -9.8312\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5292\n", - "Function value obtained: -16.3186\n", - "Current minimum: -16.3186\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5773\n", - "Function value obtained: -52.3397\n", - "Current minimum: -52.3397\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5389\n", - "Function value obtained: -80.4999\n", - "Current minimum: -80.4999\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5486\n", - "Function value obtained: -83.3830\n", - "Current minimum: -83.3830\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5781\n", - "Function value obtained: -85.2906\n", - "Current minimum: -85.2906\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6010\n", - "Function value obtained: -83.7895\n", - "Current minimum: -85.2906\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1588\n", - "Function value obtained: -84.0034\n", - "Current minimum: -85.2906\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8256\n", - "Function value obtained: -84.9165\n", - "Current minimum: -85.2906\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4439\n", - "Function value obtained: -85.3266\n", - "Current minimum: -85.3266\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3466\n", - "Function value obtained: -83.1760\n", - "Current minimum: -85.3266\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3850\n", - "Function value obtained: -85.6441\n", - "Current minimum: -85.6441\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6499\n", - "Function value obtained: -86.0217\n", - "Current minimum: -86.0217\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4183\n", - "Function value obtained: -81.2758\n", - "Current minimum: -86.0217\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4525\n", - "Function value obtained: -86.4711\n", - "Current minimum: -86.4711\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4082\n", - "Function value obtained: -84.7038\n", - "Current minimum: -86.4711\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4371\n", - "Function value obtained: -85.5746\n", - "Current minimum: -86.4711\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3616\n", - "Function value obtained: -83.9651\n", - "Current minimum: -86.4711\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4229\n", - "Function value obtained: -84.9482\n", - "Current minimum: -86.4711\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4596\n", - "Function value obtained: -87.2128\n", - "Current minimum: -87.2128\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4209\n", - "Function value obtained: -1.9491\n", - "Current minimum: -87.2128\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4119\n", - "Function value obtained: -82.4391\n", - "Current minimum: -87.2128\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4297\n", - "Function value obtained: -84.4656\n", - "Current minimum: -87.2128\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3742\n", - "Function value obtained: -87.5589\n", - "Current minimum: -87.5589\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4501\n", - "Function value obtained: -84.6758\n", - "Current minimum: -87.5589\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3994\n", - "Function value obtained: -83.8463\n", - "Current minimum: -87.5589\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3315\n", - "Function value obtained: -82.0701\n", - "Current minimum: -87.5589\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4285\n", - "Function value obtained: -84.5005\n", - "Current minimum: -87.5589\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4393\n", - "Function value obtained: -85.6002\n", - "Current minimum: -87.5589\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4556\n", - "Function value obtained: -84.1980\n", - "Current minimum: -87.5589\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4592\n", - "Function value obtained: -82.4640\n", - "Current minimum: -87.5589\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6511\n", - "Function value obtained: -87.7919\n", - "Current minimum: -87.7919\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5517\n", - "Function value obtained: -81.3267\n", - "Current minimum: -87.7919\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4859\n", - "Function value obtained: -83.6141\n", - "Current minimum: -87.7919\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4735\n", - "Function value obtained: -87.8643\n", - "Current minimum: -87.8643\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4527\n", - "Function value obtained: -83.2510\n", - "Current minimum: -87.8643\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5046\n", - "Function value obtained: -86.9130\n", - "Current minimum: -87.8643\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4827\n", - "Function value obtained: -83.3556\n", - "Current minimum: -87.8643\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4384\n", - "Function value obtained: -83.4610\n", - "Current minimum: -87.8643\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4393\n", - "Function value obtained: -85.4573\n", - "Current minimum: -87.8643\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4980\n", - "Function value obtained: -87.0808\n", - "Current minimum: -87.8643\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5822\n", - "Function value obtained: -88.7936\n", - "Current minimum: -88.7936\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4725\n", - "Function value obtained: -84.3028\n", - "Current minimum: -88.7936\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5056\n", - "Function value obtained: -85.6013\n", - "Current minimum: -88.7936\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5053\n", - "Function value obtained: -83.5249\n", - "Current minimum: -88.7936\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5376\n", - "Function value obtained: -82.9111\n", - "Current minimum: -88.7936\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5847\n", - "Function value obtained: -85.2942\n", - "Current minimum: -88.7936\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5688\n", - "Function value obtained: -86.9849\n", - "Current minimum: -88.7936\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5754\n", - "Function value obtained: -83.3894\n", - "Current minimum: -88.7936\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5956\n", - "Function value obtained: -87.2385\n", - "Current minimum: -88.7936\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7217\n", - "Function value obtained: -88.1977\n", - "Current minimum: -88.7936\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6260\n", - "Function value obtained: -85.9176\n", - "Current minimum: -88.7936\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5686\n", - "Function value obtained: -86.1229\n", - "Current minimum: -88.7936\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6506\n", - "Function value obtained: -87.0458\n", - "Current minimum: -88.7936\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5661\n", - "Function value obtained: -84.9915\n", - "Current minimum: -88.7936\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5983\n", - "Function value obtained: -82.9268\n", - "Current minimum: -88.7936\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5894\n", - "Function value obtained: -87.0604\n", - "Current minimum: -88.7936\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5748\n", - "Function value obtained: -83.9895\n", - "Current minimum: -88.7936\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6066\n", - "Function value obtained: -84.5049\n", - "Current minimum: -88.7936\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5568\n", - "Function value obtained: -85.2982\n", - "Current minimum: -88.7936\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6147\n", - "Function value obtained: -82.4611\n", - "Current minimum: -88.7936\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6405\n", - "Function value obtained: -86.2719\n", - "Current minimum: -88.7936\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6894\n", - "Function value obtained: -87.1919\n", - "Current minimum: -88.7936\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6873\n", - "Function value obtained: -86.2144\n", - "Current minimum: -88.7936\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7893\n", - "Function value obtained: -84.4256\n", - "Current minimum: -88.7936\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6642\n", - "Function value obtained: -85.9299\n", - "Current minimum: -88.7936\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7292\n", - "Function value obtained: -84.2092\n", - "Current minimum: -88.7936\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6602\n", - "Function value obtained: -83.4907\n", - "Current minimum: -88.7936\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7371\n", - "Function value obtained: -85.7356\n", - "Current minimum: -88.7936\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7526\n", - "Function value obtained: -86.5642\n", - "Current minimum: -88.7936\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7205\n", - "Function value obtained: -84.9649\n", - "Current minimum: -88.7936\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8873\n", - "Function value obtained: -84.4085\n", - "Current minimum: -88.7936\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7784\n", - "Function value obtained: -85.5729\n", - "Current minimum: -88.7936\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7582\n", - "Function value obtained: -85.6790\n", - "Current minimum: -88.7936\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7340\n", - "Function value obtained: -83.7601\n", - "Current minimum: -88.7936\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6939\n", - "Function value obtained: -83.4566\n", - "Current minimum: -88.7936\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9619\n", - "Function value obtained: -81.6177\n", - "Current minimum: -88.7936\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7582\n", - "Function value obtained: -87.3755\n", - "Current minimum: -88.7936\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7490\n", - "Function value obtained: -84.8986\n", - "Current minimum: -88.7936\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7268\n", - "Function value obtained: -85.6259\n", - "Current minimum: -88.7936\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8012\n", - "Function value obtained: -83.1990\n", - "Current minimum: -88.7936\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9378\n", - "Function value obtained: -84.7424\n", - "Current minimum: -88.7936\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8454\n", - "Function value obtained: -84.3947\n", - "Current minimum: -88.7936\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8884\n", - "Function value obtained: -81.2216\n", - "Current minimum: -88.7936\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8839\n", - "Function value obtained: -83.8132\n", - "Current minimum: -88.7936\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9101\n", - "Function value obtained: -83.3671\n", - "Current minimum: -88.7936\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9602\n", - "Function value obtained: -88.2126\n", - "Current minimum: -88.7936\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9470\n", - "Function value obtained: -84.5989\n", - "Current minimum: -88.7936\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9378\n", - "Function value obtained: -82.4315\n", - "Current minimum: -88.7936\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0896\n", - "Function value obtained: -85.8491\n", - "Current minimum: -88.7936\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1454\n", - "Function value obtained: -84.4998\n", - "Current minimum: -88.7936\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9997\n", - "Function value obtained: -85.8866\n", - "Current minimum: -88.7936\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0399\n", - "Function value obtained: -86.4996\n", - "Current minimum: -88.7936\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0249\n", - "Function value obtained: -84.7751\n", - "Current minimum: -88.7936\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0895\n", - "Function value obtained: -85.8201\n", - "Current minimum: -88.7936\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0012\n", - "Function value obtained: -86.1520\n", - "Current minimum: -88.7936\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0896\n", - "Function value obtained: -84.1424\n", - "Current minimum: -88.7936\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0959\n", - "Function value obtained: -83.4526\n", - "Current minimum: -88.7936\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9556\n", - "Function value obtained: -84.7809\n", - "Current minimum: -88.7936\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0623\n", - "Function value obtained: -86.2088\n", - "Current minimum: -88.7936\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0576\n", - "Function value obtained: -82.8475\n", - "Current minimum: -88.7936\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0564\n", - "Function value obtained: -82.2386\n", - "Current minimum: -88.7936\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1342\n", - "Function value obtained: -82.7799\n", - "Current minimum: -88.7936\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1511\n", - "Function value obtained: -86.5301\n", - "Current minimum: -88.7936\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0862\n", - "Function value obtained: -84.3601\n", - "Current minimum: -88.7936\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0905\n", - "Function value obtained: -82.8963\n", - "Current minimum: -88.7936\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1330\n", - "Function value obtained: -82.3177\n", - "Current minimum: -88.7936\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0847\n", - "Function value obtained: -83.1737\n", - "Current minimum: -88.7936\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2786\n", - "Function value obtained: -83.6992\n", - "Current minimum: -88.7936\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2530\n", - "Function value obtained: -85.0952\n", - "Current minimum: -88.7936\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3448\n", - "Function value obtained: -88.1863\n", - "Current minimum: -88.7936\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3633\n", - "Function value obtained: -86.2675\n", - "Current minimum: -88.7936\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2945\n", - "Function value obtained: -85.9106\n", - "Current minimum: -88.7936\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3613\n", - "Function value obtained: -84.3397\n", - "Current minimum: -88.7936\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2880\n", - "Function value obtained: -85.3764\n", - "Current minimum: -88.7936\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3144\n", - "Function value obtained: -86.4584\n", - "Current minimum: -88.7936\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3437\n", - "Function value obtained: -84.1038\n", - "Current minimum: -88.7936\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4015\n", - "Function value obtained: -83.6414\n", - "Current minimum: -88.7936\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4514\n", - "Function value obtained: -82.4285\n", - "Current minimum: -88.7936\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5143\n", - "Function value obtained: -83.9299\n", - "Current minimum: -88.7936\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4768\n", - "Function value obtained: -84.0752\n", - "Current minimum: -88.7936\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4899\n", - "Function value obtained: -85.5614\n", - "Current minimum: -88.7936\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4991\n", - "Function value obtained: -82.9782\n", - "Current minimum: -88.7936\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5405\n", - "Function value obtained: -82.5327\n", - "Current minimum: -88.7936\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4868\n", - "Function value obtained: -83.9966\n", - "Current minimum: -88.7936\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5473\n", - "Function value obtained: -88.9424\n", - "Current minimum: -88.9424\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5489\n", - "Function value obtained: -83.7380\n", - "Current minimum: -88.9424\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4844\n", - "Function value obtained: -84.4171\n", - "Current minimum: -88.9424\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5307\n", - "Function value obtained: -82.4263\n", - "Current minimum: -88.9424\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5930\n", - "Function value obtained: -85.9834\n", - "Current minimum: -88.9424\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5014\n", - "Function value obtained: -83.8756\n", - "Current minimum: -88.9424\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6132\n", - "Function value obtained: -82.3975\n", - "Current minimum: -88.9424\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6866\n", - "Function value obtained: -86.5412\n", - "Current minimum: -88.9424\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6383\n", - "Function value obtained: -88.2652\n", - "Current minimum: -88.9424\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5024\n", - "Function value obtained: -83.6148\n", - "Current minimum: -88.9424\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5122\n", - "Function value obtained: -84.3451\n", - "Current minimum: -88.9424\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6220\n", - "Function value obtained: -85.2411\n", - "Current minimum: -88.9424\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6338\n", - "Function value obtained: -86.6159\n", - "Current minimum: -88.9424\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6826\n", - "Function value obtained: -85.3567\n", - "Current minimum: -88.9424\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6434\n", - "Function value obtained: -86.8232\n", - "Current minimum: -88.9424\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7826\n", - "Function value obtained: -83.9509\n", - "Current minimum: -88.9424\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7286\n", - "Function value obtained: -85.4207\n", - "Current minimum: -88.9424\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8137\n", - "Function value obtained: -86.3905\n", - "Current minimum: -88.9424\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7077\n", - "Function value obtained: -84.2835\n", - "Current minimum: -88.9424\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8523\n", - "Function value obtained: -84.8326\n", - "Current minimum: -88.9424\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8403\n", - "Function value obtained: -84.5681\n", - "Current minimum: -88.9424\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8305\n", - "Function value obtained: -85.5560\n", - "Current minimum: -88.9424\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8183\n", - "Function value obtained: -82.0426\n", - "Current minimum: -88.9424\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7790\n", - "Function value obtained: -85.3996\n", - "Current minimum: -88.9424\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8958\n", - "Function value obtained: -83.6048\n", - "Current minimum: -88.9424\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9179\n", - "Function value obtained: -87.0923\n", - "Current minimum: -88.9424\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8525\n", - "Function value obtained: -83.6731\n", - "Current minimum: -88.9424\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8948\n", - "Function value obtained: -85.2705\n", - "Current minimum: -88.9424\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8606\n", - "Function value obtained: -83.5560\n", - "Current minimum: -88.9424\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0209\n", - "Function value obtained: -85.5659\n", - "Current minimum: -88.9424\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9857\n", - "Function value obtained: -84.7900\n", - "Current minimum: -88.9424\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9454\n", - "Function value obtained: -84.1219\n", - "Current minimum: -88.9424\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9525\n", - "Function value obtained: -83.1055\n", - "Current minimum: -88.9424\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0326\n", - "Function value obtained: -85.0939\n", - "Current minimum: -88.9424\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0220\n", - "Function value obtained: -83.6331\n", - "Current minimum: -88.9424\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9313\n", - "Function value obtained: -83.9011\n", - "Current minimum: -88.9424\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0664\n", - "Function value obtained: -85.1330\n", - "Current minimum: -88.9424\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0426\n", - "Function value obtained: -85.6506\n", - "Current minimum: -88.9424\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0477\n", - "Function value obtained: -85.4941\n", - "Current minimum: -88.9424\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1297\n", - "Function value obtained: -83.8772\n", - "Current minimum: -88.9424\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0690\n", - "Function value obtained: -87.7085\n", - "Current minimum: -88.9424\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1604\n", - "Function value obtained: -83.2798\n", - "Current minimum: -88.9424\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1356\n", - "Function value obtained: -83.6723\n", - "Current minimum: -88.9424\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1426\n", - "Function value obtained: -84.5765\n", - "Current minimum: -88.9424\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1975\n", - "Function value obtained: -86.8002\n", - "Current minimum: -88.9424\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2572\n", - "Function value obtained: -85.6453\n", - "Current minimum: -88.9424\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2087\n", - "Function value obtained: -83.9469\n", - "Current minimum: -88.9424\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1656\n", - "Function value obtained: -86.0028\n", - "Current minimum: -88.9424\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2144\n", - "Function value obtained: -85.4008\n", - "Current minimum: -88.9424\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3211\n", - "Function value obtained: -88.3011\n", - "Current minimum: -88.9424\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2718\n", - "Function value obtained: -83.7345\n", - "Current minimum: -88.9424\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4193\n", - "Function value obtained: -84.5432\n", - "Current minimum: -88.9424\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4525\n", - "Function value obtained: -82.9519\n", - "Current minimum: -88.9424\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3937\n", - "Function value obtained: -86.8457\n", - "Current minimum: -88.9424\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3132\n", - "Function value obtained: -83.9400\n", - "Current minimum: -88.9424\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3959\n", - "Function value obtained: -84.7115\n", - "Current minimum: -88.9424\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4165\n", - "Function value obtained: -83.8742\n", - "Current minimum: -88.9424\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4788\n", - "Function value obtained: -84.1349\n", - "Current minimum: -88.9424\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4574\n", - "Function value obtained: -85.6765\n", - "Current minimum: -88.9424\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4817\n", - "Function value obtained: -85.5814\n", - "Current minimum: -88.9424\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4379\n", - "Function value obtained: -84.1399\n", - "Current minimum: -88.9424\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5142\n", - "Function value obtained: -85.3376\n", - "Current minimum: -88.9424\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5114\n", - "Function value obtained: -84.7863\n", - "Current minimum: -88.9424\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5168\n", - "Function value obtained: -82.2336\n", - "Current minimum: -88.9424\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6195\n", - "Function value obtained: -87.5592\n", - "Current minimum: -88.9424\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6604\n", - "Function value obtained: -84.5312\n", - "Current minimum: -88.9424\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4938\n", - "Function value obtained: -83.7691\n", - "Current minimum: -88.9424\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5901\n", - "Function value obtained: -81.1916\n", - "Current minimum: -88.9424\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7502\n", - "Function value obtained: -83.9095\n", - "Current minimum: -88.9424\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7670\n", - "Function value obtained: -87.8404\n", - "Current minimum: -88.9424\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6893\n", - "Function value obtained: -85.6244\n", - "Current minimum: -88.9424\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6738\n", - "Function value obtained: -85.1493\n", - "Current minimum: -88.9424\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6733\n", - "Function value obtained: -88.5660\n", - "Current minimum: -88.9424\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7156\n", - "Function value obtained: -87.2563\n", - "Current minimum: -88.9424\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7896\n", - "Function value obtained: -85.2322\n", - "Current minimum: -88.9424\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7659\n", - "Function value obtained: -85.6738\n", - "Current minimum: -88.9424\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7728\n", - "Function value obtained: -81.9408\n", - "Current minimum: -88.9424\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7804\n", - "Function value obtained: -84.1900\n", - "Current minimum: -88.9424\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8427\n", - "Function value obtained: -83.3240\n", - "Current minimum: -88.9424\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9387\n", - "Function value obtained: -84.1631\n", - "Current minimum: -88.9424\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7826\n", - "Function value obtained: -85.6438\n", - "Current minimum: -88.9424\n", - "Iteration No: 217 started. Searching for the next optimal point.\n", - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8798\n", - "Function value obtained: -82.5955\n", - "Current minimum: -88.9424\n", - "Iteration No: 218 started. Searching for the next optimal point.\n", - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7385\n", - "Function value obtained: -83.4224\n", - "Current minimum: -88.9424\n", - "Iteration No: 219 started. Searching for the next optimal point.\n", - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8461\n", - "Function value obtained: -83.1485\n", - "Current minimum: -88.9424\n", - "Iteration No: 220 started. Searching for the next optimal point.\n", - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9106\n", - "Function value obtained: -84.5849\n", - "Current minimum: -88.9424\n", - "Iteration No: 221 started. Searching for the next optimal point.\n", - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8486\n", - "Function value obtained: -84.3890\n", - "Current minimum: -88.9424\n", - "Iteration No: 222 started. Searching for the next optimal point.\n", - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9103\n", - "Function value obtained: -85.0342\n", - "Current minimum: -88.9424\n", - "Iteration No: 223 started. Searching for the next optimal point.\n", - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8383\n", - "Function value obtained: -85.6265\n", - "Current minimum: -88.9424\n", - "Iteration No: 224 started. Searching for the next optimal point.\n", - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8497\n", - "Function value obtained: -84.4915\n", - "Current minimum: -88.9424\n", - "Iteration No: 225 started. Searching for the next optimal point.\n", - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8692\n", - "Function value obtained: -86.3210\n", - "Current minimum: -88.9424\n", - "Iteration No: 226 started. Searching for the next optimal point.\n", - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8890\n", - "Function value obtained: -86.6679\n", - "Current minimum: -88.9424\n", - "Iteration No: 227 started. Searching for the next optimal point.\n", - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0577\n", - "Function value obtained: -86.0960\n", - "Current minimum: -88.9424\n", - "Iteration No: 228 started. Searching for the next optimal point.\n", - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8758\n", - "Function value obtained: -82.2918\n", - "Current minimum: -88.9424\n", - "Iteration No: 229 started. Searching for the next optimal point.\n", - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9900\n", - "Function value obtained: -86.4659\n", - "Current minimum: -88.9424\n", - "Iteration No: 230 started. Searching for the next optimal point.\n", - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0141\n", - "Function value obtained: -88.0084\n", - "Current minimum: -88.9424\n", - "Iteration No: 231 started. Searching for the next optimal point.\n", - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0637\n", - "Function value obtained: -85.8032\n", - "Current minimum: -88.9424\n", - "Iteration No: 232 started. Searching for the next optimal point.\n", - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0320\n", - "Function value obtained: -85.6518\n", - "Current minimum: -88.9424\n", - "Iteration No: 233 started. Searching for the next optimal point.\n", - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1576\n", - "Function value obtained: -83.9464\n", - "Current minimum: -88.9424\n", - "Iteration No: 234 started. Searching for the next optimal point.\n", - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1127\n", - "Function value obtained: -84.2372\n", - "Current minimum: -88.9424\n", - "Iteration No: 235 started. Searching for the next optimal point.\n", - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2002\n", - "Function value obtained: -82.7422\n", - "Current minimum: -88.9424\n", - "Iteration No: 236 started. Searching for the next optimal point.\n", - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0266\n", - "Function value obtained: -84.0363\n", - "Current minimum: -88.9424\n", - "Iteration No: 237 started. Searching for the next optimal point.\n", - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1392\n", - "Function value obtained: -84.0081\n", - "Current minimum: -88.9424\n", - "Iteration No: 238 started. Searching for the next optimal point.\n", - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1213\n", - "Function value obtained: -84.2905\n", - "Current minimum: -88.9424\n", - "Iteration No: 239 started. Searching for the next optimal point.\n", - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2836\n", - "Function value obtained: -83.6245\n", - "Current minimum: -88.9424\n", - "Iteration No: 240 started. Searching for the next optimal point.\n", - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1579\n", - "Function value obtained: -85.9179\n", - "Current minimum: -88.9424\n", - "Iteration No: 241 started. Searching for the next optimal point.\n", - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4125\n", - "Function value obtained: -84.8672\n", - "Current minimum: -88.9424\n", - "Iteration No: 242 started. Searching for the next optimal point.\n", - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2033\n", - "Function value obtained: -87.8986\n", - "Current minimum: -88.9424\n", - "Iteration No: 243 started. Searching for the next optimal point.\n", - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2769\n", - "Function value obtained: -82.4511\n", - "Current minimum: -88.9424\n", - "Iteration No: 244 started. Searching for the next optimal point.\n", - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3056\n", - "Function value obtained: -83.2432\n", - "Current minimum: -88.9424\n", - "Iteration No: 245 started. Searching for the next optimal point.\n", - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3734\n", - "Function value obtained: -86.2849\n", - "Current minimum: -88.9424\n", - "Iteration No: 246 started. Searching for the next optimal point.\n", - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3651\n", - "Function value obtained: -84.2954\n", - "Current minimum: -88.9424\n", - "Iteration No: 247 started. Searching for the next optimal point.\n", - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2664\n", - "Function value obtained: -85.9061\n", - "Current minimum: -88.9424\n", - "Iteration No: 248 started. Searching for the next optimal point.\n", - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5226\n", - "Function value obtained: -84.1788\n", - "Current minimum: -88.9424\n", - "Iteration No: 249 started. Searching for the next optimal point.\n", - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6910\n", - "Function value obtained: -83.5698\n", - "Current minimum: -88.9424\n", - "Iteration No: 250 started. Searching for the next optimal point.\n", - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6748\n", - "Function value obtained: -86.8285\n", - "Current minimum: -88.9424\n", - "Iteration No: 251 started. Searching for the next optimal point.\n", - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6907\n", - "Function value obtained: -86.2896\n", - "Current minimum: -88.9424\n", - "Iteration No: 252 started. Searching for the next optimal point.\n", - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6244\n", - "Function value obtained: -86.5565\n", - "Current minimum: -88.9424\n", - "Iteration No: 253 started. Searching for the next optimal point.\n", - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7568\n", - "Function value obtained: -84.7245\n", - "Current minimum: -88.9424\n", - "Iteration No: 254 started. Searching for the next optimal point.\n", - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7726\n", - "Function value obtained: -83.1910\n", - "Current minimum: -88.9424\n", - "Iteration No: 255 started. Searching for the next optimal point.\n", - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8861\n", - "Function value obtained: -86.4182\n", - "Current minimum: -88.9424\n", - "Iteration No: 256 started. Searching for the next optimal point.\n", - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8083\n", - "Function value obtained: -85.5617\n", - "Current minimum: -88.9424\n", - "Iteration No: 257 started. Searching for the next optimal point.\n", - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7195\n", - "Function value obtained: -85.4845\n", - "Current minimum: -88.9424\n", - "Iteration No: 258 started. Searching for the next optimal point.\n", - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8084\n", - "Function value obtained: -82.9101\n", - "Current minimum: -88.9424\n", - "Iteration No: 259 started. Searching for the next optimal point.\n", - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1051\n", - "Function value obtained: -85.7685\n", - "Current minimum: -88.9424\n", - "Iteration No: 260 started. Searching for the next optimal point.\n", - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8924\n", - "Function value obtained: -82.1995\n", - "Current minimum: -88.9424\n", - "Iteration No: 261 started. Searching for the next optimal point.\n", - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0344\n", - "Function value obtained: -83.7582\n", - "Current minimum: -88.9424\n", - "Iteration No: 262 started. Searching for the next optimal point.\n", - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9853\n", - "Function value obtained: -83.0905\n", - "Current minimum: -88.9424\n", - "Iteration No: 263 started. Searching for the next optimal point.\n", - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9829\n", - "Function value obtained: -85.3908\n", - "Current minimum: -88.9424\n", - "Iteration No: 264 started. Searching for the next optimal point.\n", - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0274\n", - "Function value obtained: -83.6712\n", - "Current minimum: -88.9424\n", - "Iteration No: 265 started. Searching for the next optimal point.\n", - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1189\n", - "Function value obtained: -85.2795\n", - "Current minimum: -88.9424\n", - "Iteration No: 266 started. Searching for the next optimal point.\n", - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 4.9782\n", - "Function value obtained: -87.4455\n", - "Current minimum: -88.9424\n", - "Iteration No: 267 started. Searching for the next optimal point.\n", - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0205\n", - "Function value obtained: -84.6936\n", - "Current minimum: -88.9424\n", - "Iteration No: 268 started. Searching for the next optimal point.\n", - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1304\n", - "Function value obtained: -85.3183\n", - "Current minimum: -88.9424\n", - "Iteration No: 269 started. Searching for the next optimal point.\n", - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1316\n", - "Function value obtained: -80.6488\n", - "Current minimum: -88.9424\n", - "Iteration No: 270 started. Searching for the next optimal point.\n", - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1816\n", - "Function value obtained: -84.6192\n", - "Current minimum: -88.9424\n", - "Iteration No: 271 started. Searching for the next optimal point.\n", - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2824\n", - "Function value obtained: -86.3812\n", - "Current minimum: -88.9424\n", - "Iteration No: 272 started. Searching for the next optimal point.\n", - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2275\n", - "Function value obtained: -83.9857\n", - "Current minimum: -88.9424\n", - "Iteration No: 273 started. Searching for the next optimal point.\n", - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1941\n", - "Function value obtained: -86.2361\n", - "Current minimum: -88.9424\n", - "Iteration No: 274 started. Searching for the next optimal point.\n", - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2506\n", - "Function value obtained: -85.5450\n", - "Current minimum: -88.9424\n", - "Iteration No: 275 started. Searching for the next optimal point.\n", - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2945\n", - "Function value obtained: -84.8205\n", - "Current minimum: -88.9424\n", - "Iteration No: 276 started. Searching for the next optimal point.\n", - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1573\n", - "Function value obtained: -83.0944\n", - "Current minimum: -88.9424\n", - "Iteration No: 277 started. Searching for the next optimal point.\n", - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2734\n", - "Function value obtained: -83.9087\n", - "Current minimum: -88.9424\n", - "Iteration No: 278 started. Searching for the next optimal point.\n", - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2244\n", - "Function value obtained: -84.3036\n", - "Current minimum: -88.9424\n", - "Iteration No: 279 started. Searching for the next optimal point.\n", - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3524\n", - "Function value obtained: -84.5203\n", - "Current minimum: -88.9424\n", - "Iteration No: 280 started. Searching for the next optimal point.\n", - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1440\n", - "Function value obtained: -83.2822\n", - "Current minimum: -88.9424\n", - "Iteration No: 281 started. Searching for the next optimal point.\n", - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4573\n", - "Function value obtained: -87.1670\n", - "Current minimum: -88.9424\n", - "Iteration No: 282 started. Searching for the next optimal point.\n", - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4217\n", - "Function value obtained: -81.0240\n", - "Current minimum: -88.9424\n", - "Iteration No: 283 started. Searching for the next optimal point.\n", - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5427\n", - "Function value obtained: -87.7591\n", - "Current minimum: -88.9424\n", - "Iteration No: 284 started. Searching for the next optimal point.\n", - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3975\n", - "Function value obtained: -80.9265\n", - "Current minimum: -88.9424\n", - "Iteration No: 285 started. Searching for the next optimal point.\n", - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5825\n", - "Function value obtained: -83.4174\n", - "Current minimum: -88.9424\n", - "Iteration No: 286 started. Searching for the next optimal point.\n", - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 5.4088\n", - "Function value obtained: -87.5917\n", - "Current minimum: -88.9424\n", - "Iteration No: 287 started. Searching for the next optimal point.\n", - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6184\n", - "Function value obtained: -83.8790\n", - "Current minimum: -88.9424\n", - "Iteration No: 288 started. Searching for the next optimal point.\n", - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5515\n", - "Function value obtained: -88.2637\n", - "Current minimum: -88.9424\n", - "Iteration No: 289 started. Searching for the next optimal point.\n", - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6982\n", - "Function value obtained: -83.4047\n", - "Current minimum: -88.9424\n", - "Iteration No: 290 started. Searching for the next optimal point.\n", - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7383\n", - "Function value obtained: -84.9295\n", - "Current minimum: -88.9424\n", - "Iteration No: 291 started. Searching for the next optimal point.\n", - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7732\n", - "Function value obtained: -87.1347\n", - "Current minimum: -88.9424\n", - "Iteration No: 292 started. Searching for the next optimal point.\n", - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7829\n", - "Function value obtained: -86.7605\n", - "Current minimum: -88.9424\n", - "Iteration No: 293 started. Searching for the next optimal point.\n", - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6685\n", - "Function value obtained: -87.0208\n", - "Current minimum: -88.9424\n", - "Iteration No: 294 started. Searching for the next optimal point.\n", - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7354\n", - "Function value obtained: -81.1226\n", - "Current minimum: -88.9424\n", - "Iteration No: 295 started. Searching for the next optimal point.\n", - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8814\n", - "Function value obtained: -87.2329\n", - "Current minimum: -88.9424\n", - "Iteration No: 296 started. Searching for the next optimal point.\n", - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7860\n", - "Function value obtained: -84.2515\n", - "Current minimum: -88.9424\n", - "Iteration No: 297 started. Searching for the next optimal point.\n", - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9065\n", - "Function value obtained: -87.4453\n", - "Current minimum: -88.9424\n", - "Iteration No: 298 started. Searching for the next optimal point.\n", - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8620\n", - "Function value obtained: -87.0349\n", - "Current minimum: -88.9424\n", - "Iteration No: 299 started. Searching for the next optimal point.\n", - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9848\n", - "Function value obtained: -87.0860\n", - "Current minimum: -88.9424\n", - "Iteration No: 300 started. Searching for the next optimal point.\n", - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0444\n", - "Function value obtained: -86.2412\n", - "Current minimum: -88.9424\n", - "CPU times: user 2h 1min 35s, sys: 1h 11min 36s, total: 3h 13min 11s\n", - "Wall time: 15min 6s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-88.94242714465256, [-1.985554010378551])" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", - "esc_gp.fun, esc_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-26 22:06:38,545\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 9.8552\n", - "Function value obtained: -335.4193\n", - "Current minimum: -335.4193\n", - "Iteration No: 2 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-26 22:06:48,401\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 10.3734\n", - "Function value obtained: -0.0000\n", - "Current minimum: -335.4193\n", - "Iteration No: 3 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-26 22:06:58,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 10.6599\n", - "Function value obtained: -427.5246\n", - "Current minimum: -427.5246\n", - "Iteration No: 4 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-26 22:07:09,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 10.6912\n", - "Function value obtained: -3.8238\n", - "Current minimum: -427.5246\n", - "Iteration No: 5 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-26 22:07:20,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 10.4139\n", - "Function value obtained: -60.5882\n", - "Current minimum: -427.5246\n", - "Iteration No: 6 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-26 22:07:30,592\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 9.9004\n", - "Function value obtained: -3.1751\n", - "Current minimum: -427.5246\n", - "Iteration No: 7 started. Evaluating function at random point.\n" + "Iteration No: 276 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4202\n", + "Function value obtained: -126.7206\n", + "Current minimum: -129.2935\n", + "Iteration No: 277 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:07:40,491\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:57:32,138\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 9.9277\n", - "Function value obtained: -5.4295\n", - "Current minimum: -427.5246\n", - "Iteration No: 8 started. Evaluating function at random point.\n" + "Iteration No: 277 ended. Search finished for the next optimal point.\n", + "Time taken: 14.0313\n", + "Function value obtained: -124.9717\n", + "Current minimum: -129.2935\n", + "Iteration No: 278 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:07:50,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:57:46,212\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 10.4066\n", - "Function value obtained: -37.1784\n", - "Current minimum: -427.5246\n", - "Iteration No: 9 started. Evaluating function at random point.\n" + "Iteration No: 278 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7681\n", + "Function value obtained: -121.6040\n", + "Current minimum: -129.2935\n", + "Iteration No: 279 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:00,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:57:59,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 9.7842\n", - "Function value obtained: -6.5697\n", - "Current minimum: -427.5246\n", - "Iteration No: 10 started. Evaluating function at random point.\n" + "Iteration No: 279 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4558\n", + "Function value obtained: -126.0912\n", + "Current minimum: -129.2935\n", + "Iteration No: 280 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:10,599\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:58:13,397\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 10.2117\n", - "Function value obtained: -3.1815\n", - "Current minimum: -427.5246\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" + "Iteration No: 280 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2457\n", + "Function value obtained: -124.1140\n", + "Current minimum: -129.2935\n", + "Iteration No: 281 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:20,827\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:58:26,649\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2058\n", - "Function value obtained: -220.1786\n", - "Current minimum: -427.5246\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" + "Iteration No: 281 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8276\n", + "Function value obtained: -124.7883\n", + "Current minimum: -129.2935\n", + "Iteration No: 282 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:31,016\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:58:40,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1665\n", - "Function value obtained: -434.8020\n", - "Current minimum: -434.8020\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" + "Iteration No: 282 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2322\n", + "Function value obtained: -123.5840\n", + "Current minimum: -129.2935\n", + "Iteration No: 283 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:41,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:58:53,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6603\n", - "Function value obtained: -435.4278\n", - "Current minimum: -435.4278\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" + "Iteration No: 283 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4608\n", + "Function value obtained: -123.2283\n", + "Current minimum: -129.2935\n", + "Iteration No: 284 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:51,876\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:59:08,203\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3507\n", - "Function value obtained: -432.5803\n", - "Current minimum: -435.4278\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" + "Iteration No: 284 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8278\n", + "Function value obtained: -120.5888\n", + "Current minimum: -129.2935\n", + "Iteration No: 285 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:02,216\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:59:22,049\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7200\n", - "Function value obtained: -434.2554\n", - "Current minimum: -435.4278\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" + "Iteration No: 285 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4681\n", + "Function value obtained: -122.4606\n", + "Current minimum: -129.2935\n", + "Iteration No: 286 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:12,862\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:59:35,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0872\n", - "Function value obtained: -438.5429\n", - "Current minimum: -438.5429\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" + "Iteration No: 286 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5274\n", + "Function value obtained: -122.7946\n", + "Current minimum: -129.2935\n", + "Iteration No: 287 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:23,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-03 23:59:49,040\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0968\n", - "Function value obtained: -433.8495\n", - "Current minimum: -438.5429\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" + "Iteration No: 287 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7501\n", + "Function value obtained: -119.4591\n", + "Current minimum: -129.2935\n", + "Iteration No: 288 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:33,164\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:00:02,845\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4912\n", - "Function value obtained: -437.4978\n", - "Current minimum: -438.5429\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" + "Iteration No: 288 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5659\n", + "Function value obtained: -125.5548\n", + "Current minimum: -129.2935\n", + "Iteration No: 289 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:43,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:00:16,323\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6329\n", - "Function value obtained: -0.0000\n", - "Current minimum: -438.5429\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" + "Iteration No: 289 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5787\n", + "Function value obtained: -121.6925\n", + "Current minimum: -129.2935\n", + "Iteration No: 290 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:54,293\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:00:29,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3247\n", - "Function value obtained: -433.3639\n", - "Current minimum: -438.5429\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" + "output_type": "stream", + "text": [ + "Iteration No: 290 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5465\n", + "Function value obtained: -124.0893\n", + "Current minimum: -129.2935\n", + "Iteration No: 291 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:04,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:00:43,490\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8444\n", - "Function value obtained: -438.8648\n", - "Current minimum: -438.8648\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" + "Iteration No: 291 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2565\n", + "Function value obtained: -121.8256\n", + "Current minimum: -129.2935\n", + "Iteration No: 292 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:15,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:00:57,679\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4880\n", - "Function value obtained: -430.0188\n", - "Current minimum: -438.8648\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" + "Iteration No: 292 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4305\n", + "Function value obtained: -125.1479\n", + "Current minimum: -129.2935\n", + "Iteration No: 293 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:26,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:01:11,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1281\n", - "Function value obtained: -436.7534\n", - "Current minimum: -438.8648\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" + "Iteration No: 293 ended. Search finished for the next optimal point.\n", + "Time taken: 14.3814\n", + "Function value obtained: -122.9420\n", + "Current minimum: -129.2935\n", + "Iteration No: 294 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:37,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:01:25,559\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3385\n", - "Function value obtained: -412.0634\n", - "Current minimum: -438.8648\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" + "Iteration No: 294 ended. Search finished for the next optimal point.\n", + "Time taken: 14.0078\n", + "Function value obtained: -125.4004\n", + "Current minimum: -129.2935\n", + "Iteration No: 295 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:47,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:01:39,555\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2627\n", - "Function value obtained: -437.4297\n", - "Current minimum: -438.8648\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" + "Iteration No: 295 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9684\n", + "Function value obtained: -127.3408\n", + "Current minimum: -129.2935\n", + "Iteration No: 296 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:58,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:01:53,564\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4811\n", - "Function value obtained: -435.9596\n", - "Current minimum: -438.8648\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" + "Iteration No: 296 ended. Search finished for the next optimal point.\n", + "Time taken: 14.0920\n", + "Function value obtained: -122.1963\n", + "Current minimum: -129.2935\n", + "Iteration No: 297 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:09,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:02:07,699\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2521\n", - "Function value obtained: -431.8186\n", - "Current minimum: -438.8648\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" + "Iteration No: 297 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2051\n", + "Function value obtained: -121.9924\n", + "Current minimum: -129.2935\n", + "Iteration No: 298 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:19,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:02:21,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7418\n", - "Function value obtained: -435.4472\n", - "Current minimum: -438.8648\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" + "Iteration No: 298 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0910\n", + "Function value obtained: -125.7286\n", + "Current minimum: -129.2935\n", + "Iteration No: 299 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:30,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:02:37,061\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5565\n", - "Function value obtained: -428.0797\n", - "Current minimum: -438.8648\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" + "Iteration No: 299 ended. Search finished for the next optimal point.\n", + "Time taken: 14.1944\n", + "Function value obtained: -123.3073\n", + "Current minimum: -129.2935\n", + "Iteration No: 300 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:40,804\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:02:51,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1785\n", - "Function value obtained: -436.0723\n", - "Current minimum: -438.8648\n", - "CPU times: user 34.4 s, sys: 51.8 s, total: 1min 26s\n", - "Wall time: 5min 12s\n" + "Iteration No: 300 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2314\n", + "Function value obtained: -123.9449\n", + "Current minimum: -129.2935\n", + "CPU times: user 2h 2min 28s, sys: 1h 17min 47s, total: 3h 20min 15s\n", + "Wall time: 51min 49s\n" ] }, { "data": { "text/plain": [ - "(-438.8647758926598, [-0.08374338090501876])" + "(-129.29352912639592, [0.04473718126536452])" ] }, - "execution_count": 10, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", - "esc_gbrt.fun, esc_gbrt.x" - ] - }, - { - "cell_type": "markdown", - "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", - "metadata": {}, - "source": [ - "### CR" + "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", + "msy_gp.fun, msy_gp.x" ] }, { "cell_type": "code", - "execution_count": 11, - "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", + "execution_count": 8, + "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", "metadata": { "collapsed": true, "jupyter": { @@ -5484,1516 +5692,3268 @@ "text": [ "Iteration No: 1 started. Evaluating function at random point.\n", "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.3055\n", - "Function value obtained: -27.6420\n", - "Current minimum: -27.6420\n", + "Time taken: 1.3560\n", + "Function value obtained: -46.5391\n", + "Current minimum: -46.5391\n", "Iteration No: 2 started. Evaluating function at random point.\n", "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.3289\n", - "Function value obtained: -78.1050\n", - "Current minimum: -78.1050\n", + "Time taken: 1.1664\n", + "Function value obtained: -4.6581\n", + "Current minimum: -46.5391\n", "Iteration No: 3 started. Evaluating function at random point.\n", "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.2986\n", - "Function value obtained: -19.7252\n", - "Current minimum: -78.1050\n", + "Time taken: 1.3000\n", + "Function value obtained: -14.8136\n", + "Current minimum: -46.5391\n", "Iteration No: 4 started. Evaluating function at random point.\n", "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.2351\n", - "Function value obtained: -44.3313\n", - "Current minimum: -78.1050\n", + "Time taken: 1.2598\n", + "Function value obtained: -3.6463\n", + "Current minimum: -46.5391\n", "Iteration No: 5 started. Evaluating function at random point.\n", "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.2662\n", - "Function value obtained: -49.3958\n", - "Current minimum: -78.1050\n", + "Time taken: 1.1637\n", + "Function value obtained: -4.3602\n", + "Current minimum: -46.5391\n", "Iteration No: 6 started. Evaluating function at random point.\n", "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.3035\n", - "Function value obtained: -81.1550\n", - "Current minimum: -81.1550\n", + "Time taken: 1.2462\n", + "Function value obtained: -4.0893\n", + "Current minimum: -46.5391\n", "Iteration No: 7 started. Evaluating function at random point.\n", "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.3246\n", - "Function value obtained: -38.6728\n", - "Current minimum: -81.1550\n", + "Time taken: 1.2717\n", + "Function value obtained: -10.5623\n", + "Current minimum: -46.5391\n", "Iteration No: 8 started. Evaluating function at random point.\n", "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.3186\n", - "Function value obtained: -58.2459\n", - "Current minimum: -81.1550\n", + "Time taken: 1.2456\n", + "Function value obtained: -38.1398\n", + "Current minimum: -46.5391\n", "Iteration No: 9 started. Evaluating function at random point.\n", "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.2767\n", - "Function value obtained: -63.2675\n", - "Current minimum: -81.1550\n", + "Time taken: 1.2314\n", + "Function value obtained: -48.0675\n", + "Current minimum: -48.0675\n", "Iteration No: 10 started. Evaluating function at random point.\n", "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 6.7294\n", - "Function value obtained: -13.7136\n", - "Current minimum: -81.1550\n", + "Time taken: 1.4094\n", + "Function value obtained: -6.6195\n", + "Current minimum: -48.0675\n", "Iteration No: 11 started. Searching for the next optimal point.\n", "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6489\n", - "Function value obtained: -79.4565\n", - "Current minimum: -81.1550\n", + "Time taken: 1.4140\n", + "Function value obtained: -49.6017\n", + "Current minimum: -49.6017\n", "Iteration No: 12 started. Searching for the next optimal point.\n", "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6055\n", - "Function value obtained: -0.0000\n", - "Current minimum: -81.1550\n", + "Time taken: 1.4435\n", + "Function value obtained: -46.6843\n", + "Current minimum: -49.6017\n", "Iteration No: 13 started. Searching for the next optimal point.\n", "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6350\n", - "Function value obtained: -0.0000\n", - "Current minimum: -81.1550\n", + "Time taken: 1.4193\n", + "Function value obtained: -45.0990\n", + "Current minimum: -49.6017\n", "Iteration No: 14 started. Searching for the next optimal point.\n", "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6692\n", - "Function value obtained: -79.6332\n", - "Current minimum: -81.1550\n", + "Time taken: 1.5035\n", + "Function value obtained: -46.8608\n", + "Current minimum: -49.6017\n", "Iteration No: 15 started. Searching for the next optimal point.\n", "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6754\n", - "Function value obtained: -74.3325\n", - "Current minimum: -81.1550\n", + "Time taken: 1.5919\n", + "Function value obtained: -49.3540\n", + "Current minimum: -49.6017\n", "Iteration No: 16 started. Searching for the next optimal point.\n", "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5171\n", - "Function value obtained: -82.1995\n", - "Current minimum: -82.1995\n", + "Time taken: 1.4357\n", + "Function value obtained: -47.5765\n", + "Current minimum: -49.6017\n", "Iteration No: 17 started. Searching for the next optimal point.\n", "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7444\n", - "Function value obtained: -76.4244\n", - "Current minimum: -82.1995\n", + "Time taken: 1.4996\n", + "Function value obtained: -45.1326\n", + "Current minimum: -49.6017\n", "Iteration No: 18 started. Searching for the next optimal point.\n", "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3227\n", - "Function value obtained: -59.0022\n", - "Current minimum: -82.1995\n", + "Time taken: 1.4617\n", + "Function value obtained: -46.9510\n", + "Current minimum: -49.6017\n", "Iteration No: 19 started. Searching for the next optimal point.\n", "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4925\n", - "Function value obtained: -79.8453\n", - "Current minimum: -82.1995\n", + "Time taken: 1.4780\n", + "Function value obtained: -12.6043\n", + "Current minimum: -49.6017\n", "Iteration No: 20 started. Searching for the next optimal point.\n", "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5988\n", - "Function value obtained: -82.0734\n", - "Current minimum: -82.1995\n", + "Time taken: 1.4956\n", + "Function value obtained: -48.6197\n", + "Current minimum: -49.6017\n", "Iteration No: 21 started. Searching for the next optimal point.\n", "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5444\n", - "Function value obtained: -82.1329\n", - "Current minimum: -82.1995\n", + "Time taken: 1.4565\n", + "Function value obtained: -45.1803\n", + "Current minimum: -49.6017\n", "Iteration No: 22 started. Searching for the next optimal point.\n", "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5446\n", - "Function value obtained: -75.1359\n", - "Current minimum: -82.1995\n", + "Time taken: 1.3789\n", + "Function value obtained: -48.0291\n", + "Current minimum: -49.6017\n", "Iteration No: 23 started. Searching for the next optimal point.\n", "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4972\n", - "Function value obtained: -47.4599\n", - "Current minimum: -82.1995\n", + "Time taken: 1.4518\n", + "Function value obtained: -47.8936\n", + "Current minimum: -49.6017\n", "Iteration No: 24 started. Searching for the next optimal point.\n", "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5302\n", - "Function value obtained: -82.9885\n", - "Current minimum: -82.9885\n", + "Time taken: 1.4929\n", + "Function value obtained: -46.8791\n", + "Current minimum: -49.6017\n", "Iteration No: 25 started. Searching for the next optimal point.\n", "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4491\n", - "Function value obtained: -79.8435\n", - "Current minimum: -82.9885\n", + "Time taken: 1.5805\n", + "Function value obtained: -48.7646\n", + "Current minimum: -49.6017\n", "Iteration No: 26 started. Searching for the next optimal point.\n", "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6897\n", - "Function value obtained: -78.2639\n", - "Current minimum: -82.9885\n", + "Time taken: 1.4410\n", + "Function value obtained: -45.4169\n", + "Current minimum: -49.6017\n", "Iteration No: 27 started. Searching for the next optimal point.\n", "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4834\n", - "Function value obtained: -79.4805\n", - "Current minimum: -82.9885\n", + "Time taken: 1.5256\n", + "Function value obtained: -46.7357\n", + "Current minimum: -49.6017\n", "Iteration No: 28 started. Searching for the next optimal point.\n", "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4405\n", - "Function value obtained: -31.7971\n", - "Current minimum: -82.9885\n", + "Time taken: 1.5359\n", + "Function value obtained: -46.2242\n", + "Current minimum: -49.6017\n", "Iteration No: 29 started. Searching for the next optimal point.\n", "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5430\n", - "Function value obtained: -81.7057\n", - "Current minimum: -82.9885\n", + "Time taken: 1.5400\n", + "Function value obtained: -12.6620\n", + "Current minimum: -49.6017\n", "Iteration No: 30 started. Searching for the next optimal point.\n", "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5597\n", - "Function value obtained: -86.2651\n", - "Current minimum: -86.2651\n", + "Time taken: 1.6019\n", + "Function value obtained: -43.9229\n", + "Current minimum: -49.6017\n", "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3970\n", - "Function value obtained: -84.6473\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4984\n", + "Function value obtained: -47.8351\n", + "Current minimum: -49.6017\n", "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5765\n", - "Function value obtained: -85.6389\n", - "Current minimum: -86.2651\n", + "Time taken: 1.5293\n", + "Function value obtained: -44.4191\n", + "Current minimum: -49.6017\n", "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5050\n", - "Function value obtained: -80.7363\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4842\n", + "Function value obtained: -47.5384\n", + "Current minimum: -49.6017\n", "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4977\n", - "Function value obtained: -81.0955\n", - "Current minimum: -86.2651\n", + "Time taken: 1.6029\n", + "Function value obtained: -47.4318\n", + "Current minimum: -49.6017\n", "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5693\n", - "Function value obtained: -1.9364\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4040\n", + "Function value obtained: -44.8686\n", + "Current minimum: -49.6017\n", "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6156\n", - "Function value obtained: -83.5928\n", - "Current minimum: -86.2651\n", + "Time taken: 1.5284\n", + "Function value obtained: -47.4501\n", + "Current minimum: -49.6017\n", "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5964\n", - "Function value obtained: -81.4378\n", - "Current minimum: -86.2651\n", + "Time taken: 1.3685\n", + "Function value obtained: -47.0818\n", + "Current minimum: -49.6017\n", "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5503\n", - "Function value obtained: -83.7283\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4836\n", + "Function value obtained: -46.7556\n", + "Current minimum: -49.6017\n", "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5272\n", - "Function value obtained: -84.4892\n", - "Current minimum: -86.2651\n", + "Time taken: 1.5081\n", + "Function value obtained: -46.9364\n", + "Current minimum: -49.6017\n", "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6030\n", - "Function value obtained: -83.2422\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4114\n", + "Function value obtained: -46.0513\n", + "Current minimum: -49.6017\n", "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5581\n", - "Function value obtained: -84.7703\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4602\n", + "Function value obtained: -47.1258\n", + "Current minimum: -49.6017\n", "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5818\n", - "Function value obtained: -0.0000\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4598\n", + "Function value obtained: -44.6687\n", + "Current minimum: -49.6017\n", "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5588\n", - "Function value obtained: -86.1378\n", - "Current minimum: -86.2651\n", + "Time taken: 1.4767\n", + "Function value obtained: -45.9894\n", + "Current minimum: -49.6017\n", "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7102\n", - "Function value obtained: -87.6390\n", - "Current minimum: -87.6390\n", + "Time taken: 1.5332\n", + "Function value obtained: -46.3990\n", + "Current minimum: -49.6017\n", "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7003\n", - "Function value obtained: -88.1836\n", - "Current minimum: -88.1836\n", + "Time taken: 1.5325\n", + "Function value obtained: -47.7062\n", + "Current minimum: -49.6017\n", "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7084\n", - "Function value obtained: -88.2088\n", - "Current minimum: -88.2088\n", + "Time taken: 1.5390\n", + "Function value obtained: -47.8023\n", + "Current minimum: -49.6017\n", "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6072\n", - "Function value obtained: -84.0442\n", - "Current minimum: -88.2088\n", + "Time taken: 1.4629\n", + "Function value obtained: -45.6460\n", + "Current minimum: -49.6017\n", "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5923\n", - "Function value obtained: -83.8470\n", - "Current minimum: -88.2088\n", + "Time taken: 1.5021\n", + "Function value obtained: -44.3852\n", + "Current minimum: -49.6017\n", "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7308\n", - "Function value obtained: -86.4331\n", - "Current minimum: -88.2088\n", + "Time taken: 1.4780\n", + "Function value obtained: -46.6708\n", + "Current minimum: -49.6017\n", "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6601\n", - "Function value obtained: -84.3033\n", - "Current minimum: -88.2088\n", + "Time taken: 1.4235\n", + "Function value obtained: -45.2947\n", + "Current minimum: -49.6017\n", "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6979\n", - "Function value obtained: -88.4533\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4191\n", + "Function value obtained: -47.4422\n", + "Current minimum: -49.6017\n", "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5749\n", - "Function value obtained: -84.0851\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5193\n", + "Function value obtained: -47.2893\n", + "Current minimum: -49.6017\n", "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6064\n", - "Function value obtained: -84.9920\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4471\n", + "Function value obtained: -48.0579\n", + "Current minimum: -49.6017\n", "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6048\n", - "Function value obtained: -84.2240\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5124\n", + "Function value obtained: -46.6369\n", + "Current minimum: -49.6017\n", "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6681\n", - "Function value obtained: -83.8135\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5033\n", + "Function value obtained: -48.1478\n", + "Current minimum: -49.6017\n", "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6173\n", - "Function value obtained: -2.3999\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5597\n", + "Function value obtained: -48.1605\n", + "Current minimum: -49.6017\n", "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7242\n", - "Function value obtained: -83.6010\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4899\n", + "Function value obtained: -45.0397\n", + "Current minimum: -49.6017\n", "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5484\n", - "Function value obtained: -86.3004\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4978\n", + "Function value obtained: -46.5459\n", + "Current minimum: -49.6017\n", "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6542\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4811\n", + "Function value obtained: -43.7516\n", + "Current minimum: -49.6017\n", "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7897\n", - "Function value obtained: -81.3552\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5171\n", + "Function value obtained: -47.2481\n", + "Current minimum: -49.6017\n", "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7200\n", - "Function value obtained: -77.9104\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4386\n", + "Function value obtained: -46.4790\n", + "Current minimum: -49.6017\n", "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7528\n", - "Function value obtained: -84.1339\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4536\n", + "Function value obtained: -47.3387\n", + "Current minimum: -49.6017\n", "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7421\n", - "Function value obtained: -3.8739\n", - "Current minimum: -88.4533\n", + "Time taken: 1.6102\n", + "Function value obtained: -47.5327\n", + "Current minimum: -49.6017\n", "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7754\n", - "Function value obtained: -84.1307\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5174\n", + "Function value obtained: -45.3859\n", + "Current minimum: -49.6017\n", "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7195\n", - "Function value obtained: -78.8474\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4711\n", + "Function value obtained: -46.8727\n", + "Current minimum: -49.6017\n", "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7647\n", - "Function value obtained: -87.5901\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5031\n", + "Function value obtained: -48.0277\n", + "Current minimum: -49.6017\n", "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8416\n", - "Function value obtained: -84.6699\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5509\n", + "Function value obtained: -48.6187\n", + "Current minimum: -49.6017\n", "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7751\n", - "Function value obtained: -82.5775\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5195\n", + "Function value obtained: -48.3695\n", + "Current minimum: -49.6017\n", "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7313\n", - "Function value obtained: -88.1452\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4830\n", + "Function value obtained: -44.5009\n", + "Current minimum: -49.6017\n", "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9032\n", - "Function value obtained: -85.1442\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5454\n", + "Function value obtained: -45.3096\n", + "Current minimum: -49.6017\n", "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7385\n", - "Function value obtained: -2.5050\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4323\n", + "Function value obtained: -47.1526\n", + "Current minimum: -49.6017\n", "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7224\n", - "Function value obtained: -82.2524\n", - "Current minimum: -88.4533\n", + "Time taken: 1.4273\n", + "Function value obtained: -47.3175\n", + "Current minimum: -49.6017\n", "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7859\n", - "Function value obtained: -74.2668\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5579\n", + "Function value obtained: -46.5905\n", + "Current minimum: -49.6017\n", "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8074\n", - "Function value obtained: -76.8367\n", - "Current minimum: -88.4533\n", + "Time taken: 1.5067\n", + "Function value obtained: -46.8752\n", + "Current minimum: -49.6017\n", "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7701\n", - "Function value obtained: -90.6333\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5313\n", + "Function value obtained: -47.8672\n", + "Current minimum: -49.6017\n", "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8479\n", - "Function value obtained: -85.4348\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5224\n", + "Function value obtained: -45.6860\n", + "Current minimum: -49.6017\n", "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8363\n", - "Function value obtained: -82.3339\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5298\n", + "Function value obtained: -46.8637\n", + "Current minimum: -49.6017\n", "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8753\n", - "Function value obtained: -85.6496\n", - "Current minimum: -90.6333\n", + "Time taken: 1.7157\n", + "Function value obtained: -47.9359\n", + "Current minimum: -49.6017\n", "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8171\n", - "Function value obtained: -85.2793\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4869\n", + "Function value obtained: -48.3924\n", + "Current minimum: -49.6017\n", "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8682\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4701\n", + "Function value obtained: -45.2819\n", + "Current minimum: -49.6017\n", "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0042\n", - "Function value obtained: -72.8643\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4596\n", + "Function value obtained: -48.8099\n", + "Current minimum: -49.6017\n", "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8247\n", - "Function value obtained: -36.2201\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4203\n", + "Function value obtained: -44.6818\n", + "Current minimum: -49.6017\n", "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9199\n", - "Function value obtained: -52.9810\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3309\n", + "Function value obtained: -48.0720\n", + "Current minimum: -49.6017\n", "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9531\n", - "Function value obtained: -82.3026\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5261\n", + "Function value obtained: -47.3489\n", + "Current minimum: -49.6017\n", "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8739\n", - "Function value obtained: -85.8179\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4705\n", + "Function value obtained: -48.0898\n", + "Current minimum: -49.6017\n", "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.8679\n", - "Function value obtained: -2.7283\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4849\n", + "Function value obtained: -45.8602\n", + "Current minimum: -49.6017\n", "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9346\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6133\n", + "Function value obtained: -47.4123\n", + "Current minimum: -49.6017\n", "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9970\n", - "Function value obtained: -85.0913\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5090\n", + "Function value obtained: -46.1113\n", + "Current minimum: -49.6017\n", "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9889\n", - "Function value obtained: -86.0498\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5676\n", + "Function value obtained: -48.4236\n", + "Current minimum: -49.6017\n", "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.9690\n", - "Function value obtained: -89.3086\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4747\n", + "Function value obtained: -47.6057\n", + "Current minimum: -49.6017\n", "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0585\n", - "Function value obtained: -87.4380\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4737\n", + "Function value obtained: -45.1571\n", + "Current minimum: -49.6017\n", "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2492\n", - "Function value obtained: -79.2090\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4616\n", + "Function value obtained: -48.5987\n", + "Current minimum: -49.6017\n", "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0783\n", - "Function value obtained: -83.0764\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4667\n", + "Function value obtained: -47.1953\n", + "Current minimum: -49.6017\n", "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0430\n", - "Function value obtained: -86.2792\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4862\n", + "Function value obtained: -46.9125\n", + "Current minimum: -49.6017\n", "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1258\n", - "Function value obtained: -82.8770\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4970\n", + "Function value obtained: -47.4312\n", + "Current minimum: -49.6017\n", "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0408\n", - "Function value obtained: -82.4791\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4997\n", + "Function value obtained: -47.1148\n", + "Current minimum: -49.6017\n", "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0456\n", - "Function value obtained: -85.6827\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6946\n", + "Function value obtained: -46.7082\n", + "Current minimum: -49.6017\n", "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 2.0294\n", - "Function value obtained: -74.7308\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5323\n", + "Function value obtained: -47.0256\n", + "Current minimum: -49.6017\n", "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1141\n", - "Function value obtained: -83.3760\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4895\n", + "Function value obtained: -45.8617\n", + "Current minimum: -49.6017\n", "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2029\n", - "Function value obtained: -14.3625\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4927\n", + "Function value obtained: -46.0801\n", + "Current minimum: -49.6017\n", "Iteration No: 101 started. Searching for the next optimal point.\n", "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1955\n", - "Function value obtained: -71.1589\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5328\n", + "Function value obtained: -47.8178\n", + "Current minimum: -49.6017\n", "Iteration No: 102 started. Searching for the next optimal point.\n", "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2321\n", - "Function value obtained: -77.2377\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5578\n", + "Function value obtained: -45.8014\n", + "Current minimum: -49.6017\n", "Iteration No: 103 started. Searching for the next optimal point.\n", "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2387\n", - "Function value obtained: -77.7340\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5063\n", + "Function value obtained: -48.7166\n", + "Current minimum: -49.6017\n", "Iteration No: 104 started. Searching for the next optimal point.\n", "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 2.1820\n", - "Function value obtained: -83.7139\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4746\n", + "Function value obtained: -46.6069\n", + "Current minimum: -49.6017\n", "Iteration No: 105 started. Searching for the next optimal point.\n", "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2461\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5559\n", + "Function value obtained: -47.1771\n", + "Current minimum: -49.6017\n", "Iteration No: 106 started. Searching for the next optimal point.\n", "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2158\n", - "Function value obtained: -3.9035\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4994\n", + "Function value obtained: -47.1168\n", + "Current minimum: -49.6017\n", "Iteration No: 107 started. Searching for the next optimal point.\n", "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2611\n", - "Function value obtained: -75.1242\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5939\n", + "Function value obtained: -46.4010\n", + "Current minimum: -49.6017\n", "Iteration No: 108 started. Searching for the next optimal point.\n", "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3445\n", - "Function value obtained: -85.5275\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5162\n", + "Function value obtained: -48.2321\n", + "Current minimum: -49.6017\n", "Iteration No: 109 started. Searching for the next optimal point.\n", "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2808\n", - "Function value obtained: -84.5770\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4968\n", + "Function value obtained: -45.6238\n", + "Current minimum: -49.6017\n", "Iteration No: 110 started. Searching for the next optimal point.\n", "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2629\n", - "Function value obtained: -85.4486\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5985\n", + "Function value obtained: -47.4828\n", + "Current minimum: -49.6017\n", "Iteration No: 111 started. Searching for the next optimal point.\n", "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2529\n", - "Function value obtained: -75.6998\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5077\n", + "Function value obtained: -46.7207\n", + "Current minimum: -49.6017\n", "Iteration No: 112 started. Searching for the next optimal point.\n", "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2940\n", - "Function value obtained: -84.5648\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5293\n", + "Function value obtained: -46.3870\n", + "Current minimum: -49.6017\n", "Iteration No: 113 started. Searching for the next optimal point.\n", "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2838\n", - "Function value obtained: -70.1448\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4890\n", + "Function value obtained: -47.6239\n", + "Current minimum: -49.6017\n", "Iteration No: 114 started. Searching for the next optimal point.\n", "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4314\n", - "Function value obtained: -86.5986\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5437\n", + "Function value obtained: -46.1445\n", + "Current minimum: -49.6017\n", "Iteration No: 115 started. Searching for the next optimal point.\n", "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 2.2736\n", - "Function value obtained: -83.5688\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4350\n", + "Function value obtained: -47.7099\n", + "Current minimum: -49.6017\n", "Iteration No: 116 started. Searching for the next optimal point.\n", "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4588\n", - "Function value obtained: -85.3449\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4450\n", + "Function value obtained: -47.2153\n", + "Current minimum: -49.6017\n", "Iteration No: 117 started. Searching for the next optimal point.\n", "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3671\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5301\n", + "Function value obtained: -46.0510\n", + "Current minimum: -49.6017\n", "Iteration No: 118 started. Searching for the next optimal point.\n", "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3850\n", - "Function value obtained: -84.6747\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6147\n", + "Function value obtained: -46.7348\n", + "Current minimum: -49.6017\n", "Iteration No: 119 started. Searching for the next optimal point.\n", "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4507\n", - "Function value obtained: -2.0290\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4782\n", + "Function value obtained: -48.0223\n", + "Current minimum: -49.6017\n", "Iteration No: 120 started. Searching for the next optimal point.\n", "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3261\n", - "Function value obtained: -84.2602\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5107\n", + "Function value obtained: -45.9638\n", + "Current minimum: -49.6017\n", "Iteration No: 121 started. Searching for the next optimal point.\n", "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4539\n", - "Function value obtained: -82.9736\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5445\n", + "Function value obtained: -47.4704\n", + "Current minimum: -49.6017\n", "Iteration No: 122 started. Searching for the next optimal point.\n", "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4714\n", - "Function value obtained: -67.7069\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4802\n", + "Function value obtained: -46.3621\n", + "Current minimum: -49.6017\n", "Iteration No: 123 started. Searching for the next optimal point.\n", "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 2.3809\n", - "Function value obtained: -80.7035\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4472\n", + "Function value obtained: -48.2987\n", + "Current minimum: -49.6017\n", "Iteration No: 124 started. Searching for the next optimal point.\n", "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 2.4970\n", - "Function value obtained: -81.0539\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4813\n", + "Function value obtained: -45.8185\n", + "Current minimum: -49.6017\n", "Iteration No: 125 started. Searching for the next optimal point.\n", "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5194\n", - "Function value obtained: -77.8282\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5345\n", + "Function value obtained: -46.9240\n", + "Current minimum: -49.6017\n", "Iteration No: 126 started. Searching for the next optimal point.\n", "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5481\n", - "Function value obtained: -85.7514\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6460\n", + "Function value obtained: -45.6050\n", + "Current minimum: -49.6017\n", "Iteration No: 127 started. Searching for the next optimal point.\n", "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6020\n", - "Function value obtained: -58.3485\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5271\n", + "Function value obtained: -45.5833\n", + "Current minimum: -49.6017\n", "Iteration No: 128 started. Searching for the next optimal point.\n", "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6162\n", - "Function value obtained: -84.7989\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5524\n", + "Function value obtained: -45.4827\n", + "Current minimum: -49.6017\n", "Iteration No: 129 started. Searching for the next optimal point.\n", "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6023\n", - "Function value obtained: -83.7495\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5740\n", + "Function value obtained: -48.2536\n", + "Current minimum: -49.6017\n", "Iteration No: 130 started. Searching for the next optimal point.\n", "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6529\n", - "Function value obtained: -84.6838\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4685\n", + "Function value obtained: -46.3540\n", + "Current minimum: -49.6017\n", "Iteration No: 131 started. Searching for the next optimal point.\n", "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6517\n", - "Function value obtained: -81.3237\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5441\n", + "Function value obtained: -47.9790\n", + "Current minimum: -49.6017\n", "Iteration No: 132 started. Searching for the next optimal point.\n", "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5658\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5442\n", + "Function value obtained: -46.5460\n", + "Current minimum: -49.6017\n", "Iteration No: 133 started. Searching for the next optimal point.\n", "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6196\n", - "Function value obtained: -57.2674\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4367\n", + "Function value obtained: -49.8897\n", + "Current minimum: -49.8897\n", "Iteration No: 134 started. Searching for the next optimal point.\n", "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 2.5497\n", - "Function value obtained: -82.8458\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5285\n", + "Function value obtained: -48.0609\n", + "Current minimum: -49.8897\n", "Iteration No: 135 started. Searching for the next optimal point.\n", "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7238\n", - "Function value obtained: -80.1184\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5231\n", + "Function value obtained: -45.9417\n", + "Current minimum: -49.8897\n", "Iteration No: 136 started. Searching for the next optimal point.\n", "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8476\n", - "Function value obtained: -83.7794\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5069\n", + "Function value obtained: -48.1052\n", + "Current minimum: -49.8897\n", "Iteration No: 137 started. Searching for the next optimal point.\n", "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8646\n", - "Function value obtained: -83.6890\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4651\n", + "Function value obtained: -47.1823\n", + "Current minimum: -49.8897\n", "Iteration No: 138 started. Searching for the next optimal point.\n", "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6516\n", - "Function value obtained: -11.3171\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5213\n", + "Function value obtained: -46.5411\n", + "Current minimum: -49.8897\n", "Iteration No: 139 started. Searching for the next optimal point.\n", "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7437\n", - "Function value obtained: -82.8761\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4664\n", + "Function value obtained: -44.4394\n", + "Current minimum: -49.8897\n", "Iteration No: 140 started. Searching for the next optimal point.\n", "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6597\n", - "Function value obtained: -86.4469\n", - "Current minimum: -90.6333\n", + "Time taken: 1.7325\n", + "Function value obtained: -48.4451\n", + "Current minimum: -49.8897\n", "Iteration No: 141 started. Searching for the next optimal point.\n", "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7797\n", - "Function value obtained: -0.0000\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5663\n", + "Function value obtained: -46.7940\n", + "Current minimum: -49.8897\n", "Iteration No: 142 started. Searching for the next optimal point.\n", "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 2.6914\n", - "Function value obtained: -84.1730\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5296\n", + "Function value obtained: -47.4213\n", + "Current minimum: -49.8897\n", "Iteration No: 143 started. Searching for the next optimal point.\n", "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8246\n", - "Function value obtained: -78.3581\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5615\n", + "Function value obtained: -44.7370\n", + "Current minimum: -49.8897\n", "Iteration No: 144 started. Searching for the next optimal point.\n", "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8528\n", - "Function value obtained: -86.4290\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4711\n", + "Function value obtained: -46.5875\n", + "Current minimum: -49.8897\n", "Iteration No: 145 started. Searching for the next optimal point.\n", "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7967\n", - "Function value obtained: -83.3510\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4040\n", + "Function value obtained: -46.5380\n", + "Current minimum: -49.8897\n", "Iteration No: 146 started. Searching for the next optimal point.\n", "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7849\n", - "Function value obtained: -83.6486\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4615\n", + "Function value obtained: -47.0075\n", + "Current minimum: -49.8897\n", "Iteration No: 147 started. Searching for the next optimal point.\n", "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8430\n", - "Function value obtained: -55.1289\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5457\n", + "Function value obtained: -47.6239\n", + "Current minimum: -49.8897\n", "Iteration No: 148 started. Searching for the next optimal point.\n", "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9347\n", - "Function value obtained: -85.6819\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4523\n", + "Function value obtained: -45.9532\n", + "Current minimum: -49.8897\n", "Iteration No: 149 started. Searching for the next optimal point.\n", "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7961\n", - "Function value obtained: -83.8089\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5191\n", + "Function value obtained: -47.6434\n", + "Current minimum: -49.8897\n", "Iteration No: 150 started. Searching for the next optimal point.\n", "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8090\n", - "Function value obtained: -83.1695\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4987\n", + "Function value obtained: -45.9662\n", + "Current minimum: -49.8897\n", "Iteration No: 151 started. Searching for the next optimal point.\n", "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9021\n", - "Function value obtained: -11.0483\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5810\n", + "Function value obtained: -46.5016\n", + "Current minimum: -49.8897\n", "Iteration No: 152 started. Searching for the next optimal point.\n", "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 2.7946\n", - "Function value obtained: -85.6196\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4548\n", + "Function value obtained: -46.2267\n", + "Current minimum: -49.8897\n", "Iteration No: 153 started. Searching for the next optimal point.\n", "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9110\n", - "Function value obtained: -83.9758\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4238\n", + "Function value obtained: -47.4453\n", + "Current minimum: -49.8897\n", "Iteration No: 154 started. Searching for the next optimal point.\n", "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9064\n", - "Function value obtained: -85.1906\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5048\n", + "Function value obtained: -47.2020\n", + "Current minimum: -49.8897\n", "Iteration No: 155 started. Searching for the next optimal point.\n", "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0321\n", - "Function value obtained: -87.8375\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4631\n", + "Function value obtained: -47.1068\n", + "Current minimum: -49.8897\n", "Iteration No: 156 started. Searching for the next optimal point.\n", "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8503\n", - "Function value obtained: -85.1706\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3817\n", + "Function value obtained: -48.2429\n", + "Current minimum: -49.8897\n", "Iteration No: 157 started. Searching for the next optimal point.\n", "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 2.8713\n", - "Function value obtained: -86.7744\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4986\n", + "Function value obtained: -44.8097\n", + "Current minimum: -49.8897\n", "Iteration No: 158 started. Searching for the next optimal point.\n", "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9642\n", - "Function value obtained: -88.2608\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4233\n", + "Function value obtained: -46.8809\n", + "Current minimum: -49.8897\n", "Iteration No: 159 started. Searching for the next optimal point.\n", "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 2.9760\n", - "Function value obtained: -85.5418\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5612\n", + "Function value obtained: -45.5597\n", + "Current minimum: -49.8897\n", "Iteration No: 160 started. Searching for the next optimal point.\n", "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0818\n", - "Function value obtained: -83.7893\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6052\n", + "Function value obtained: -46.4952\n", + "Current minimum: -49.8897\n", "Iteration No: 161 started. Searching for the next optimal point.\n", "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1793\n", - "Function value obtained: -86.5298\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5001\n", + "Function value obtained: -46.6400\n", + "Current minimum: -49.8897\n", "Iteration No: 162 started. Searching for the next optimal point.\n", "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0893\n", - "Function value obtained: -85.0591\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6195\n", + "Function value obtained: -46.5302\n", + "Current minimum: -49.8897\n", "Iteration No: 163 started. Searching for the next optimal point.\n", "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0569\n", - "Function value obtained: -85.5105\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5431\n", + "Function value obtained: -47.6782\n", + "Current minimum: -49.8897\n", "Iteration No: 164 started. Searching for the next optimal point.\n", "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1089\n", - "Function value obtained: -86.4030\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4370\n", + "Function value obtained: -47.6993\n", + "Current minimum: -49.8897\n", "Iteration No: 165 started. Searching for the next optimal point.\n", "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1090\n", - "Function value obtained: -85.1444\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5255\n", + "Function value obtained: -10.5757\n", + "Current minimum: -49.8897\n", "Iteration No: 166 started. Searching for the next optimal point.\n", "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2387\n", - "Function value obtained: -88.1799\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4695\n", + "Function value obtained: -48.1290\n", + "Current minimum: -49.8897\n", "Iteration No: 167 started. Searching for the next optimal point.\n", "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 3.0989\n", - "Function value obtained: -84.9582\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5103\n", + "Function value obtained: -46.8644\n", + "Current minimum: -49.8897\n", "Iteration No: 168 started. Searching for the next optimal point.\n", "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1239\n", - "Function value obtained: -89.2391\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4537\n", + "Function value obtained: -46.8415\n", + "Current minimum: -49.8897\n", "Iteration No: 169 started. Searching for the next optimal point.\n", "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1619\n", - "Function value obtained: -84.0053\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4604\n", + "Function value obtained: -47.4611\n", + "Current minimum: -49.8897\n", "Iteration No: 170 started. Searching for the next optimal point.\n", "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1452\n", - "Function value obtained: -83.0798\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5201\n", + "Function value obtained: -45.5961\n", + "Current minimum: -49.8897\n", "Iteration No: 171 started. Searching for the next optimal point.\n", "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2143\n", - "Function value obtained: -88.2145\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5280\n", + "Function value obtained: -44.9130\n", + "Current minimum: -49.8897\n", "Iteration No: 172 started. Searching for the next optimal point.\n", "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 3.1834\n", - "Function value obtained: -85.2621\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4738\n", + "Function value obtained: -47.5096\n", + "Current minimum: -49.8897\n", "Iteration No: 173 started. Searching for the next optimal point.\n", "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3020\n", - "Function value obtained: -87.8510\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5386\n", + "Function value obtained: -46.5298\n", + "Current minimum: -49.8897\n", "Iteration No: 174 started. Searching for the next optimal point.\n", "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2385\n", - "Function value obtained: -88.9162\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5460\n", + "Function value obtained: -48.4569\n", + "Current minimum: -49.8897\n", "Iteration No: 175 started. Searching for the next optimal point.\n", "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2649\n", - "Function value obtained: -86.9675\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4322\n", + "Function value obtained: -46.6290\n", + "Current minimum: -49.8897\n", "Iteration No: 176 started. Searching for the next optimal point.\n", "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2222\n", - "Function value obtained: -83.9728\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5870\n", + "Function value obtained: -46.9834\n", + "Current minimum: -49.8897\n", "Iteration No: 177 started. Searching for the next optimal point.\n", "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2621\n", - "Function value obtained: -87.8963\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5292\n", + "Function value obtained: -45.0813\n", + "Current minimum: -49.8897\n", "Iteration No: 178 started. Searching for the next optimal point.\n", "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 3.2759\n", - "Function value obtained: -84.1823\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5267\n", + "Function value obtained: -49.7659\n", + "Current minimum: -49.8897\n", "Iteration No: 179 started. Searching for the next optimal point.\n", "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3226\n", - "Function value obtained: -86.6570\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5247\n", + "Function value obtained: -47.7063\n", + "Current minimum: -49.8897\n", "Iteration No: 180 started. Searching for the next optimal point.\n", "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3956\n", - "Function value obtained: -88.0181\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4800\n", + "Function value obtained: -46.8807\n", + "Current minimum: -49.8897\n", "Iteration No: 181 started. Searching for the next optimal point.\n", "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3426\n", - "Function value obtained: -83.0062\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5016\n", + "Function value obtained: -46.6104\n", + "Current minimum: -49.8897\n", "Iteration No: 182 started. Searching for the next optimal point.\n", "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5089\n", - "Function value obtained: -85.3005\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3970\n", + "Function value obtained: -45.0529\n", + "Current minimum: -49.8897\n", "Iteration No: 183 started. Searching for the next optimal point.\n", "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 3.3370\n", - "Function value obtained: -83.4699\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5808\n", + "Function value obtained: -47.7305\n", + "Current minimum: -49.8897\n", "Iteration No: 184 started. Searching for the next optimal point.\n", "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4299\n", - "Function value obtained: -86.1810\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5231\n", + "Function value obtained: -46.8753\n", + "Current minimum: -49.8897\n", "Iteration No: 185 started. Searching for the next optimal point.\n", "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5185\n", - "Function value obtained: -85.4634\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4697\n", + "Function value obtained: -46.4229\n", + "Current minimum: -49.8897\n", "Iteration No: 186 started. Searching for the next optimal point.\n", "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5824\n", - "Function value obtained: -84.4536\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4536\n", + "Function value obtained: -46.3220\n", + "Current minimum: -49.8897\n", "Iteration No: 187 started. Searching for the next optimal point.\n", "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5014\n", - "Function value obtained: -88.0504\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4468\n", + "Function value obtained: -45.0930\n", + "Current minimum: -49.8897\n", "Iteration No: 188 started. Searching for the next optimal point.\n", "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 3.4922\n", - "Function value obtained: -87.6193\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4897\n", + "Function value obtained: -46.2899\n", + "Current minimum: -49.8897\n", "Iteration No: 189 started. Searching for the next optimal point.\n", "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6882\n", - "Function value obtained: -87.6822\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5649\n", + "Function value obtained: -45.7537\n", + "Current minimum: -49.8897\n", "Iteration No: 190 started. Searching for the next optimal point.\n", "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5456\n", - "Function value obtained: -84.8614\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5258\n", + "Function value obtained: -47.8918\n", + "Current minimum: -49.8897\n", "Iteration No: 191 started. Searching for the next optimal point.\n", "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 3.5422\n", - "Function value obtained: -87.8404\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4762\n", + "Function value obtained: -44.7468\n", + "Current minimum: -49.8897\n", "Iteration No: 192 started. Searching for the next optimal point.\n", "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6575\n", - "Function value obtained: -84.9520\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4744\n", + "Function value obtained: -45.6541\n", + "Current minimum: -49.8897\n", "Iteration No: 193 started. Searching for the next optimal point.\n", "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6065\n", - "Function value obtained: -84.7831\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4850\n", + "Function value obtained: -47.9981\n", + "Current minimum: -49.8897\n", "Iteration No: 194 started. Searching for the next optimal point.\n", "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7370\n", - "Function value obtained: -84.4722\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6339\n", + "Function value obtained: -48.7292\n", + "Current minimum: -49.8897\n", "Iteration No: 195 started. Searching for the next optimal point.\n", "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7130\n", - "Function value obtained: -87.2530\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4541\n", + "Function value obtained: -45.9848\n", + "Current minimum: -49.8897\n", "Iteration No: 196 started. Searching for the next optimal point.\n", "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 3.6288\n", - "Function value obtained: -84.8944\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4691\n", + "Function value obtained: -47.4092\n", + "Current minimum: -49.8897\n", "Iteration No: 197 started. Searching for the next optimal point.\n", "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7870\n", - "Function value obtained: -87.7330\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4781\n", + "Function value obtained: -47.0885\n", + "Current minimum: -49.8897\n", "Iteration No: 198 started. Searching for the next optimal point.\n", "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7568\n", - "Function value obtained: -87.8071\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4757\n", + "Function value obtained: -46.2062\n", + "Current minimum: -49.8897\n", "Iteration No: 199 started. Searching for the next optimal point.\n", "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8266\n", - "Function value obtained: -82.9887\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5059\n", + "Function value obtained: -47.5081\n", + "Current minimum: -49.8897\n", "Iteration No: 200 started. Searching for the next optimal point.\n", "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8193\n", - "Function value obtained: -85.0844\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5575\n", + "Function value obtained: -45.9276\n", + "Current minimum: -49.8897\n", "Iteration No: 201 started. Searching for the next optimal point.\n", "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 3.7509\n", - "Function value obtained: -87.3898\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5190\n", + "Function value obtained: -46.9264\n", + "Current minimum: -49.8897\n", "Iteration No: 202 started. Searching for the next optimal point.\n", "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8625\n", - "Function value obtained: -83.5116\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4911\n", + "Function value obtained: -46.2056\n", + "Current minimum: -49.8897\n", "Iteration No: 203 started. Searching for the next optimal point.\n", "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8594\n", - "Function value obtained: -84.4034\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4858\n", + "Function value obtained: -47.2440\n", + "Current minimum: -49.8897\n", "Iteration No: 204 started. Searching for the next optimal point.\n", "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9295\n", - "Function value obtained: -88.9795\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4779\n", + "Function value obtained: -46.6488\n", + "Current minimum: -49.8897\n", "Iteration No: 205 started. Searching for the next optimal point.\n", "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9030\n", - "Function value obtained: -85.8064\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5805\n", + "Function value obtained: -46.4220\n", + "Current minimum: -49.8897\n", "Iteration No: 206 started. Searching for the next optimal point.\n", "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9488\n", - "Function value obtained: -88.4653\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4339\n", + "Function value obtained: -46.7641\n", + "Current minimum: -49.8897\n", "Iteration No: 207 started. Searching for the next optimal point.\n", "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8623\n", - "Function value obtained: -86.9521\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3939\n", + "Function value obtained: -46.9997\n", + "Current minimum: -49.8897\n", "Iteration No: 208 started. Searching for the next optimal point.\n", "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8212\n", - "Function value obtained: -88.2343\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5466\n", + "Function value obtained: -48.8444\n", + "Current minimum: -49.8897\n", "Iteration No: 209 started. Searching for the next optimal point.\n", "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9604\n", - "Function value obtained: -86.4872\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4416\n", + "Function value obtained: -46.6399\n", + "Current minimum: -49.8897\n", "Iteration No: 210 started. Searching for the next optimal point.\n", "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 3.9938\n", - "Function value obtained: -86.5157\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4550\n", + "Function value obtained: -45.9676\n", + "Current minimum: -49.8897\n", "Iteration No: 211 started. Searching for the next optimal point.\n", "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 3.8944\n", - "Function value obtained: -87.9709\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5161\n", + "Function value obtained: -48.5639\n", + "Current minimum: -49.8897\n", "Iteration No: 212 started. Searching for the next optimal point.\n", "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0389\n", - "Function value obtained: -83.9614\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4859\n", + "Function value obtained: -46.1388\n", + "Current minimum: -49.8897\n", "Iteration No: 213 started. Searching for the next optimal point.\n", "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1472\n", - "Function value obtained: -83.4505\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5181\n", + "Function value obtained: -46.3721\n", + "Current minimum: -49.8897\n", "Iteration No: 214 started. Searching for the next optimal point.\n", "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1988\n", - "Function value obtained: -88.4951\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5108\n", + "Function value obtained: -46.5996\n", + "Current minimum: -49.8897\n", "Iteration No: 215 started. Searching for the next optimal point.\n", "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1860\n", - "Function value obtained: -85.7315\n", - "Current minimum: -90.6333\n", - "Iteration No: 216 started. Searching for the next optimal point.\n", + "Time taken: 1.5101\n", + "Function value obtained: -48.4447\n", + "Current minimum: -49.8897\n", + "Iteration No: 216 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.047611662929937286] before, using random point [0.018415831307791897]\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 4.0564\n", - "Function value obtained: -86.7680\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4304\n", + "Function value obtained: -29.1544\n", + "Current minimum: -49.8897\n", "Iteration No: 217 started. Searching for the next optimal point.\n", "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2051\n", - "Function value obtained: -86.0125\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6251\n", + "Function value obtained: -47.1906\n", + "Current minimum: -49.8897\n", "Iteration No: 218 started. Searching for the next optimal point.\n", "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1440\n", - "Function value obtained: -84.4325\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3746\n", + "Function value obtained: -47.6795\n", + "Current minimum: -49.8897\n", "Iteration No: 219 started. Searching for the next optimal point.\n", "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2515\n", - "Function value obtained: -83.7888\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4408\n", + "Function value obtained: -46.9766\n", + "Current minimum: -49.8897\n", "Iteration No: 220 started. Searching for the next optimal point.\n", "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1997\n", - "Function value obtained: -85.1757\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4518\n", + "Function value obtained: -47.4589\n", + "Current minimum: -49.8897\n", "Iteration No: 221 started. Searching for the next optimal point.\n", "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 4.1929\n", - "Function value obtained: -82.7933\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4711\n", + "Function value obtained: -46.4065\n", + "Current minimum: -49.8897\n", "Iteration No: 222 started. Searching for the next optimal point.\n", "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2707\n", - "Function value obtained: -84.3591\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4315\n", + "Function value obtained: -46.8208\n", + "Current minimum: -49.8897\n", "Iteration No: 223 started. Searching for the next optimal point.\n", "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 4.2861\n", - "Function value obtained: -84.6210\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4927\n", + "Function value obtained: -48.4958\n", + "Current minimum: -49.8897\n", "Iteration No: 224 started. Searching for the next optimal point.\n", "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3462\n", - "Function value obtained: -86.3491\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4322\n", + "Function value obtained: -48.3613\n", + "Current minimum: -49.8897\n", "Iteration No: 225 started. Searching for the next optimal point.\n", "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4049\n", - "Function value obtained: -85.1895\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3822\n", + "Function value obtained: -47.1586\n", + "Current minimum: -49.8897\n", "Iteration No: 226 started. Searching for the next optimal point.\n", "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 4.3751\n", - "Function value obtained: -84.9130\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4858\n", + "Function value obtained: -46.6550\n", + "Current minimum: -49.8897\n", "Iteration No: 227 started. Searching for the next optimal point.\n", "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4479\n", - "Function value obtained: -84.6399\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5341\n", + "Function value obtained: -45.6371\n", + "Current minimum: -49.8897\n", "Iteration No: 228 started. Searching for the next optimal point.\n", "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 4.5505\n", - "Function value obtained: -86.8603\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6043\n", + "Function value obtained: -46.8676\n", + "Current minimum: -49.8897\n", "Iteration No: 229 started. Searching for the next optimal point.\n", "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6236\n", - "Function value obtained: -84.5484\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4331\n", + "Function value obtained: -45.4488\n", + "Current minimum: -49.8897\n", "Iteration No: 230 started. Searching for the next optimal point.\n", "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4163\n", - "Function value obtained: -85.6712\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4794\n", + "Function value obtained: -43.7159\n", + "Current minimum: -49.8897\n", "Iteration No: 231 started. Searching for the next optimal point.\n", "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6296\n", - "Function value obtained: -88.0456\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4488\n", + "Function value obtained: -47.7269\n", + "Current minimum: -49.8897\n", "Iteration No: 232 started. Searching for the next optimal point.\n", "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4658\n", - "Function value obtained: -87.9592\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3763\n", + "Function value obtained: -47.0402\n", + "Current minimum: -49.8897\n", "Iteration No: 233 started. Searching for the next optimal point.\n", "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6268\n", - "Function value obtained: -87.7705\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4456\n", + "Function value obtained: -46.3409\n", + "Current minimum: -49.8897\n", "Iteration No: 234 started. Searching for the next optimal point.\n", "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4828\n", - "Function value obtained: -84.6185\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5082\n", + "Function value obtained: -44.8427\n", + "Current minimum: -49.8897\n", "Iteration No: 235 started. Searching for the next optimal point.\n", "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6933\n", - "Function value obtained: -83.6364\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5316\n", + "Function value obtained: -45.9650\n", + "Current minimum: -49.8897\n", "Iteration No: 236 started. Searching for the next optimal point.\n", "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4868\n", - "Function value obtained: -86.9525\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3972\n", + "Function value obtained: -47.7037\n", + "Current minimum: -49.8897\n", "Iteration No: 237 started. Searching for the next optimal point.\n", "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7072\n", - "Function value obtained: -85.5208\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4648\n", + "Function value obtained: -47.3788\n", + "Current minimum: -49.8897\n", "Iteration No: 238 started. Searching for the next optimal point.\n", "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6665\n", - "Function value obtained: -84.9699\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5315\n", + "Function value obtained: -48.0615\n", + "Current minimum: -49.8897\n", "Iteration No: 239 started. Searching for the next optimal point.\n", "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 4.4370\n", - "Function value obtained: -85.0854\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5314\n", + "Function value obtained: -45.4083\n", + "Current minimum: -49.8897\n", "Iteration No: 240 started. Searching for the next optimal point.\n", "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6051\n", - "Function value obtained: -86.2595\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4335\n", + "Function value obtained: -48.1749\n", + "Current minimum: -49.8897\n", "Iteration No: 241 started. Searching for the next optimal point.\n", "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6382\n", - "Function value obtained: -86.4817\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4931\n", + "Function value obtained: -44.8295\n", + "Current minimum: -49.8897\n", "Iteration No: 242 started. Searching for the next optimal point.\n", "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8350\n", - "Function value obtained: -83.1569\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5030\n", + "Function value obtained: -46.7296\n", + "Current minimum: -49.8897\n", "Iteration No: 243 started. Searching for the next optimal point.\n", "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 4.6788\n", - "Function value obtained: -86.6800\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4114\n", + "Function value obtained: -45.8937\n", + "Current minimum: -49.8897\n", "Iteration No: 244 started. Searching for the next optimal point.\n", "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7233\n", - "Function value obtained: -85.5632\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5107\n", + "Function value obtained: -47.4962\n", + "Current minimum: -49.8897\n", "Iteration No: 245 started. Searching for the next optimal point.\n", "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7751\n", - "Function value obtained: -85.7283\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4967\n", + "Function value obtained: -46.7295\n", + "Current minimum: -49.8897\n", "Iteration No: 246 started. Searching for the next optimal point.\n", "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7752\n", - "Function value obtained: -85.8422\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4799\n", + "Function value obtained: -43.7786\n", + "Current minimum: -49.8897\n", "Iteration No: 247 started. Searching for the next optimal point.\n", "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 4.7446\n", - "Function value obtained: -87.3973\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4795\n", + "Function value obtained: -47.1058\n", + "Current minimum: -49.8897\n", "Iteration No: 248 started. Searching for the next optimal point.\n", "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 4.8226\n", - "Function value obtained: -86.2009\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4587\n", + "Function value obtained: -49.6577\n", + "Current minimum: -49.8897\n", "Iteration No: 249 started. Searching for the next optimal point.\n", "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2632\n", - "Function value obtained: -86.0677\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5489\n", + "Function value obtained: -49.3541\n", + "Current minimum: -49.8897\n", "Iteration No: 250 started. Searching for the next optimal point.\n", "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1870\n", - "Function value obtained: -85.0422\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5626\n", + "Function value obtained: -47.7101\n", + "Current minimum: -49.8897\n", "Iteration No: 251 started. Searching for the next optimal point.\n", "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0518\n", - "Function value obtained: -86.9540\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4293\n", + "Function value obtained: -45.9207\n", + "Current minimum: -49.8897\n", "Iteration No: 252 started. Searching for the next optimal point.\n", "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0203\n", - "Function value obtained: -83.2860\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3498\n", + "Function value obtained: -47.1748\n", + "Current minimum: -49.8897\n", "Iteration No: 253 started. Searching for the next optimal point.\n", "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0728\n", - "Function value obtained: -86.5753\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4637\n", + "Function value obtained: -48.7569\n", + "Current minimum: -49.8897\n", "Iteration No: 254 started. Searching for the next optimal point.\n", "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0231\n", - "Function value obtained: -87.2729\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4763\n", + "Function value obtained: -48.4897\n", + "Current minimum: -49.8897\n", "Iteration No: 255 started. Searching for the next optimal point.\n", "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1772\n", - "Function value obtained: -84.3028\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4182\n", + "Function value obtained: -40.4936\n", + "Current minimum: -49.8897\n", "Iteration No: 256 started. Searching for the next optimal point.\n", "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1883\n", - "Function value obtained: -84.6384\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5062\n", + "Function value obtained: -45.8526\n", + "Current minimum: -49.8897\n", "Iteration No: 257 started. Searching for the next optimal point.\n", "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2135\n", - "Function value obtained: -84.3169\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4394\n", + "Function value obtained: -47.1508\n", + "Current minimum: -49.8897\n", "Iteration No: 258 started. Searching for the next optimal point.\n", "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 5.0527\n", - "Function value obtained: -85.2478\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5217\n", + "Function value obtained: -45.7852\n", + "Current minimum: -49.8897\n", "Iteration No: 259 started. Searching for the next optimal point.\n", "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 5.1900\n", - "Function value obtained: -86.1178\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4756\n", + "Function value obtained: -46.8237\n", + "Current minimum: -49.8897\n", "Iteration No: 260 started. Searching for the next optimal point.\n", "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3379\n", - "Function value obtained: -86.5867\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4404\n", + "Function value obtained: -46.1407\n", + "Current minimum: -49.8897\n", "Iteration No: 261 started. Searching for the next optimal point.\n", "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3295\n", - "Function value obtained: -84.9588\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6887\n", + "Function value obtained: -48.1504\n", + "Current minimum: -49.8897\n", "Iteration No: 262 started. Searching for the next optimal point.\n", "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2179\n", - "Function value obtained: -86.0880\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4078\n", + "Function value obtained: -47.5959\n", + "Current minimum: -49.8897\n", "Iteration No: 263 started. Searching for the next optimal point.\n", "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2905\n", - "Function value obtained: -86.5985\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5040\n", + "Function value obtained: -46.7583\n", + "Current minimum: -49.8897\n", "Iteration No: 264 started. Searching for the next optimal point.\n", "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 5.2963\n", - "Function value obtained: -84.9976\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4849\n", + "Function value obtained: -47.5103\n", + "Current minimum: -49.8897\n", "Iteration No: 265 started. Searching for the next optimal point.\n", "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3160\n", - "Function value obtained: -86.9113\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4771\n", + "Function value obtained: -47.8489\n", + "Current minimum: -49.8897\n", "Iteration No: 266 started. Searching for the next optimal point.\n", "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3405\n", - "Function value obtained: -86.0184\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4587\n", + "Function value obtained: -45.8764\n", + "Current minimum: -49.8897\n", "Iteration No: 267 started. Searching for the next optimal point.\n", "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 5.3936\n", - "Function value obtained: -83.4898\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4583\n", + "Function value obtained: -46.5789\n", + "Current minimum: -49.8897\n", "Iteration No: 268 started. Searching for the next optimal point.\n", "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5504\n", - "Function value obtained: -87.5537\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4331\n", + "Function value obtained: -46.0664\n", + "Current minimum: -49.8897\n", "Iteration No: 269 started. Searching for the next optimal point.\n", "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5918\n", - "Function value obtained: -86.3580\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4405\n", + "Function value obtained: -47.8028\n", + "Current minimum: -49.8897\n", "Iteration No: 270 started. Searching for the next optimal point.\n", "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6319\n", - "Function value obtained: -86.8754\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4182\n", + "Function value obtained: -46.2383\n", + "Current minimum: -49.8897\n", "Iteration No: 271 started. Searching for the next optimal point.\n", "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 5.6179\n", - "Function value obtained: -87.3622\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5164\n", + "Function value obtained: -45.5827\n", + "Current minimum: -49.8897\n", "Iteration No: 272 started. Searching for the next optimal point.\n", "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5324\n", - "Function value obtained: -87.1565\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4859\n", + "Function value obtained: -47.0983\n", + "Current minimum: -49.8897\n", "Iteration No: 273 started. Searching for the next optimal point.\n", "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5720\n", - "Function value obtained: -89.2305\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5458\n", + "Function value obtained: -48.8226\n", + "Current minimum: -49.8897\n", "Iteration No: 274 started. Searching for the next optimal point.\n", "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8214\n", - "Function value obtained: -86.7361\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4604\n", + "Function value obtained: -47.5462\n", + "Current minimum: -49.8897\n", "Iteration No: 275 started. Searching for the next optimal point.\n", "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7659\n", - "Function value obtained: -84.9475\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4289\n", + "Function value obtained: -47.3570\n", + "Current minimum: -49.8897\n", "Iteration No: 276 started. Searching for the next optimal point.\n", "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8156\n", - "Function value obtained: -85.5211\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3581\n", + "Function value obtained: -46.5619\n", + "Current minimum: -49.8897\n", "Iteration No: 277 started. Searching for the next optimal point.\n", "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 5.7959\n", - "Function value obtained: -84.9771\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4701\n", + "Function value obtained: -45.2298\n", + "Current minimum: -49.8897\n", "Iteration No: 278 started. Searching for the next optimal point.\n", "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 5.5755\n", - "Function value obtained: -88.0128\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4266\n", + "Function value obtained: -49.0624\n", + "Current minimum: -49.8897\n", "Iteration No: 279 started. Searching for the next optimal point.\n", "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0321\n", - "Function value obtained: -85.9124\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4952\n", + "Function value obtained: -45.3503\n", + "Current minimum: -49.8897\n", "Iteration No: 280 started. Searching for the next optimal point.\n", "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 5.8723\n", - "Function value obtained: -85.1234\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4420\n", + "Function value obtained: -48.2820\n", + "Current minimum: -49.8897\n", "Iteration No: 281 started. Searching for the next optimal point.\n", "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9973\n", - "Function value obtained: -84.9108\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3905\n", + "Function value obtained: -46.8497\n", + "Current minimum: -49.8897\n", "Iteration No: 282 started. Searching for the next optimal point.\n", "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0118\n", - "Function value obtained: -87.5869\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4410\n", + "Function value obtained: -46.8442\n", + "Current minimum: -49.8897\n", "Iteration No: 283 started. Searching for the next optimal point.\n", "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1184\n", - "Function value obtained: -87.8984\n", - "Current minimum: -90.6333\n", + "Time taken: 1.2640\n", + "Function value obtained: -47.1821\n", + "Current minimum: -49.8897\n", "Iteration No: 284 started. Searching for the next optimal point.\n", "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 5.9292\n", - "Function value obtained: -84.3207\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4318\n", + "Function value obtained: -45.5262\n", + "Current minimum: -49.8897\n", "Iteration No: 285 started. Searching for the next optimal point.\n", "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1385\n", - "Function value obtained: -87.6335\n", - "Current minimum: -90.6333\n", + "Time taken: 1.6499\n", + "Function value obtained: -49.1007\n", + "Current minimum: -49.8897\n", "Iteration No: 286 started. Searching for the next optimal point.\n", "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1387\n", - "Function value obtained: -86.9994\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5032\n", + "Function value obtained: -46.3078\n", + "Current minimum: -49.8897\n", "Iteration No: 287 started. Searching for the next optimal point.\n", "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 6.3565\n", - "Function value obtained: -85.1528\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5046\n", + "Function value obtained: -44.4964\n", + "Current minimum: -49.8897\n", "Iteration No: 288 started. Searching for the next optimal point.\n", "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 6.0750\n", - "Function value obtained: -84.0035\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4397\n", + "Function value obtained: -46.7686\n", + "Current minimum: -49.8897\n", "Iteration No: 289 started. Searching for the next optimal point.\n", "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5232\n", - "Function value obtained: -85.4554\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5065\n", + "Function value obtained: -46.5951\n", + "Current minimum: -49.8897\n", "Iteration No: 290 started. Searching for the next optimal point.\n", "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4644\n", - "Function value obtained: -87.0136\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4144\n", + "Function value obtained: -49.6134\n", + "Current minimum: -49.8897\n", "Iteration No: 291 started. Searching for the next optimal point.\n", "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4834\n", - "Function value obtained: -84.7633\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4564\n", + "Function value obtained: -46.9677\n", + "Current minimum: -49.8897\n", "Iteration No: 292 started. Searching for the next optimal point.\n", "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4423\n", - "Function value obtained: -85.8865\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4083\n", + "Function value obtained: -46.6134\n", + "Current minimum: -49.8897\n", "Iteration No: 293 started. Searching for the next optimal point.\n", "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1903\n", - "Function value obtained: -88.6420\n", - "Current minimum: -90.6333\n", + "Time taken: 1.3414\n", + "Function value obtained: -47.6949\n", + "Current minimum: -49.8897\n", "Iteration No: 294 started. Searching for the next optimal point.\n", "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4984\n", - "Function value obtained: -87.5296\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4464\n", + "Function value obtained: -45.4689\n", + "Current minimum: -49.8897\n", "Iteration No: 295 started. Searching for the next optimal point.\n", "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5800\n", - "Function value obtained: -84.3343\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4637\n", + "Function value obtained: -45.1194\n", + "Current minimum: -49.8897\n", "Iteration No: 296 started. Searching for the next optimal point.\n", "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 6.4310\n", - "Function value obtained: -84.2970\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5177\n", + "Function value obtained: -48.8048\n", + "Current minimum: -49.8897\n", "Iteration No: 297 started. Searching for the next optimal point.\n", "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6753\n", - "Function value obtained: -83.7032\n", - "Current minimum: -90.6333\n", + "Time taken: 1.5104\n", + "Function value obtained: -46.8760\n", + "Current minimum: -49.8897\n", "Iteration No: 298 started. Searching for the next optimal point.\n", "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 6.5152\n", - "Function value obtained: -85.6559\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4363\n", + "Function value obtained: -46.8663\n", + "Current minimum: -49.8897\n", "Iteration No: 299 started. Searching for the next optimal point.\n", "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 6.1695\n", - "Function value obtained: -86.4604\n", - "Current minimum: -90.6333\n", + "Time taken: 1.4296\n", + "Function value obtained: -47.4900\n", + "Current minimum: -49.8897\n", "Iteration No: 300 started. Searching for the next optimal point.\n", "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 6.6265\n", - "Function value obtained: -83.0904\n", - "Current minimum: -90.6333\n", - "CPU times: user 2h 52min 17s, sys: 1h 11min 30s, total: 4h 3min 48s\n", - "Wall time: 16min 21s\n" + "Time taken: 1.5483\n", + "Function value obtained: -47.6654\n", + "Current minimum: -49.8897\n", + "CPU times: user 2min 10s, sys: 26.7 s, total: 2min 36s\n", + "Wall time: 7min 25s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-49.8897409867848, [0.05286591768013252])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", + "msy_gbrt.fun, msy_gbrt.x" + ] + }, + { + "cell_type": "markdown", + "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", + "metadata": {}, + "source": [ + "### Esc" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:03:05,375\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 10.2250\n", + "Function value obtained: -68.8738\n", + "Current minimum: -68.8738\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:03:15,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 9.8107\n", + "Function value obtained: -0.0000\n", + "Current minimum: -68.8738\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:03:25,571\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 9.5427\n", + "Function value obtained: -43.5459\n", + "Current minimum: -68.8738\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:03:35,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 9.9456\n", + "Function value obtained: -10.1035\n", + "Current minimum: -68.8738\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:03:45,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.0813\n", + "Function value obtained: -8.7085\n", + "Current minimum: -68.8738\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:03:55,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 10.6818\n", + "Function value obtained: -45.4951\n", + "Current minimum: -68.8738\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:04:05,872\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.4252\n", + "Function value obtained: -26.4654\n", + "Current minimum: -68.8738\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:04:15,251\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 9.7255\n", + "Function value obtained: -2.9836\n", + "Current minimum: -68.8738\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:04:24,974\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 10.0814\n", + "Function value obtained: -0.0594\n", + "Current minimum: -68.8738\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:04:35,114\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.6014\n", + "Function value obtained: -5.1890\n", + "Current minimum: -68.8738\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:04:45,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9135\n", + "Function value obtained: -96.0981\n", + "Current minimum: -96.0981\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:04:55,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0205\n", + "Function value obtained: -101.3239\n", + "Current minimum: -101.3239\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:05:06,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3060\n", + "Function value obtained: -111.5467\n", + "Current minimum: -111.5467\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:05:16,961\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2348\n", + "Function value obtained: -110.4850\n", + "Current minimum: -111.5467\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:05:27,168\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7985\n", + "Function value obtained: -111.5378\n", + "Current minimum: -111.5467\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:05:37,019\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1714\n", + "Function value obtained: -105.7690\n", + "Current minimum: -111.5467\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:05:47,202\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6702\n", + "Function value obtained: -109.6503\n", + "Current minimum: -111.5467\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:05:57,836\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1571\n", + "Function value obtained: -109.8605\n", + "Current minimum: -111.5467\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:06:08,036\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5515\n", + "Function value obtained: -108.9471\n", + "Current minimum: -111.5467\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:06:18,568\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4781\n", + "Function value obtained: -110.0320\n", + "Current minimum: -111.5467\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:06:29,039\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4556\n", + "Function value obtained: -110.6004\n", + "Current minimum: -111.5467\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:06:39,465\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1902\n", + "Function value obtained: -108.7321\n", + "Current minimum: -111.5467\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:06:49,714\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1862\n", + "Function value obtained: -108.6183\n", + "Current minimum: -111.5467\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:06:59,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5379\n", + "Function value obtained: -108.0801\n", + "Current minimum: -111.5467\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:07:10,492\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1486\n", + "Function value obtained: -107.2665\n", + "Current minimum: -111.5467\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:07:21,408\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9154\n", + "Function value obtained: -110.2048\n", + "Current minimum: -111.5467\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:07:31,987\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5671\n", + "Function value obtained: -111.3242\n", + "Current minimum: -111.5467\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:07:42,105\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3319\n", + "Function value obtained: -111.4795\n", + "Current minimum: -111.5467\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:07:52,528\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2865\n", + "Function value obtained: -110.5394\n", + "Current minimum: -111.5467\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:08:02,666\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0351\n", + "Function value obtained: -110.2251\n", + "Current minimum: -111.5467\n", + "CPU times: user 3min 7s, sys: 4min 24s, total: 7min 31s\n", + "Wall time: 5min 7s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-111.54673721989337, [-0.4009066620757826])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "esc_gp.fun, esc_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:38,545\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 9.8552\n", + "Function value obtained: -335.4193\n", + "Current minimum: -335.4193\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:48,401\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 10.3734\n", + "Function value obtained: -0.0000\n", + "Current minimum: -335.4193\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:58,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 10.6599\n", + "Function value obtained: -427.5246\n", + "Current minimum: -427.5246\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:09,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 10.6912\n", + "Function value obtained: -3.8238\n", + "Current minimum: -427.5246\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:20,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.4139\n", + "Function value obtained: -60.5882\n", + "Current minimum: -427.5246\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:30,592\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 9.9004\n", + "Function value obtained: -3.1751\n", + "Current minimum: -427.5246\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:40,491\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.9277\n", + "Function value obtained: -5.4295\n", + "Current minimum: -427.5246\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:50,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 10.4066\n", + "Function value obtained: -37.1784\n", + "Current minimum: -427.5246\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:00,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 9.7842\n", + "Function value obtained: -6.5697\n", + "Current minimum: -427.5246\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:10,599\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.2117\n", + "Function value obtained: -3.1815\n", + "Current minimum: -427.5246\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:20,827\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2058\n", + "Function value obtained: -220.1786\n", + "Current minimum: -427.5246\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:31,016\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1665\n", + "Function value obtained: -434.8020\n", + "Current minimum: -434.8020\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:41,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6603\n", + "Function value obtained: -435.4278\n", + "Current minimum: -435.4278\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:51,876\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3507\n", + "Function value obtained: -432.5803\n", + "Current minimum: -435.4278\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:02,216\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7200\n", + "Function value obtained: -434.2554\n", + "Current minimum: -435.4278\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:12,862\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0872\n", + "Function value obtained: -438.5429\n", + "Current minimum: -438.5429\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:23,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0968\n", + "Function value obtained: -433.8495\n", + "Current minimum: -438.5429\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:33,164\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4912\n", + "Function value obtained: -437.4978\n", + "Current minimum: -438.5429\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:43,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6329\n", + "Function value obtained: -0.0000\n", + "Current minimum: -438.5429\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:54,293\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3247\n", + "Function value obtained: -433.3639\n", + "Current minimum: -438.5429\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:04,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8444\n", + "Function value obtained: -438.8648\n", + "Current minimum: -438.8648\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:15,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4880\n", + "Function value obtained: -430.0188\n", + "Current minimum: -438.8648\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:26,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1281\n", + "Function value obtained: -436.7534\n", + "Current minimum: -438.8648\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:37,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3385\n", + "Function value obtained: -412.0634\n", + "Current minimum: -438.8648\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:47,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2627\n", + "Function value obtained: -437.4297\n", + "Current minimum: -438.8648\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:58,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4811\n", + "Function value obtained: -435.9596\n", + "Current minimum: -438.8648\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:09,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2521\n", + "Function value obtained: -431.8186\n", + "Current minimum: -438.8648\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:19,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7418\n", + "Function value obtained: -435.4472\n", + "Current minimum: -438.8648\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:30,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5565\n", + "Function value obtained: -428.0797\n", + "Current minimum: -438.8648\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:40,804\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1785\n", + "Function value obtained: -436.0723\n", + "Current minimum: -438.8648\n", + "CPU times: user 34.4 s, sys: 51.8 s, total: 1min 26s\n", + "Wall time: 5min 12s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-438.8647758926598, [-0.08374338090501876])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "esc_gbrt.fun, esc_gbrt.x" + ] + }, + { + "cell_type": "markdown", + "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", + "metadata": {}, + "source": [ + "### CR" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:08:12,828\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 10.3011\n", + "Function value obtained: -99.8134\n", + "Current minimum: -99.8134\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:08:23,122\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 10.2543\n", + "Function value obtained: -4.3723\n", + "Current minimum: -99.8134\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:08:33,405\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 10.1405\n", + "Function value obtained: -89.1873\n", + "Current minimum: -99.8134\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:08:43,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 10.7200\n", + "Function value obtained: -5.0205\n", + "Current minimum: -99.8134\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:08:54,273\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.3095\n", + "Function value obtained: -96.3897\n", + "Current minimum: -99.8134\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:09:04,576\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 9.9369\n", + "Function value obtained: -31.0103\n", + "Current minimum: -99.8134\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:09:14,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.7821\n", + "Function value obtained: -87.8720\n", + "Current minimum: -99.8134\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:09:24,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 10.2030\n", + "Function value obtained: -20.2042\n", + "Current minimum: -99.8134\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:09:34,578\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 10.1948\n", + "Function value obtained: -5.4816\n", + "Current minimum: -99.8134\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:09:44,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.1699\n", + "Function value obtained: -11.1607\n", + "Current minimum: -99.8134\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:09:54,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4739\n", + "Function value obtained: -105.0631\n", + "Current minimum: -105.0631\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:10:05,391\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9163\n", + "Function value obtained: -125.7116\n", + "Current minimum: -125.7116\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:10:16,238\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2771\n", + "Function value obtained: -84.7120\n", + "Current minimum: -125.7116\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:10:26,613\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7363\n", + "Function value obtained: -122.5362\n", + "Current minimum: -125.7116\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:10:37,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7098\n", + "Function value obtained: -128.8377\n", + "Current minimum: -128.8377\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:10:48,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1119\n", + "Function value obtained: -134.7188\n", + "Current minimum: -134.7188\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:10:59,137\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3283\n", + "Function value obtained: -142.1377\n", + "Current minimum: -142.1377\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:11:09,506\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5330\n", + "Function value obtained: -0.0000\n", + "Current minimum: -142.1377\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:11:19,995\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1965\n", + "Function value obtained: -138.5557\n", + "Current minimum: -142.1377\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:11:30,257\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6037\n", + "Function value obtained: -142.2689\n", + "Current minimum: -142.2689\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:11:40,869\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9340\n", + "Function value obtained: -143.3762\n", + "Current minimum: -143.3762\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:11:51,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8845\n", + "Function value obtained: -147.0960\n", + "Current minimum: -147.0960\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:12:02,629\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2859\n", + "Function value obtained: -148.8915\n", + "Current minimum: -148.8915\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:12:12,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3438\n", + "Function value obtained: -147.6152\n", + "Current minimum: -148.8915\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:12:23,310\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4375\n", + "Function value obtained: -145.7412\n", + "Current minimum: -148.8915\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:12:33,745\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4064\n", + "Function value obtained: -147.5697\n", + "Current minimum: -148.8915\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:12:44,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1361\n", + "Function value obtained: -141.3143\n", + "Current minimum: -148.8915\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:12:55,323\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8591\n", + "Function value obtained: -124.4355\n", + "Current minimum: -148.8915\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:13:06,167\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1335\n", + "Function value obtained: -143.9636\n", + "Current minimum: -148.8915\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-04 00:13:17,380\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5822\n", + "Function value obtained: -45.8358\n", + "Current minimum: -148.8915\n", + "CPU times: user 3min 9s, sys: 4min 44s, total: 7min 54s\n", + "Wall time: 5min 14s\n" ] }, { "data": { "text/plain": [ - "(-90.63333622820284,\n", - " [-1.7521564679093693, 0.5440615729465406, 0.29119675741251316])" + "(-148.89152376228486, [0.0, 0.0, 0.13207767948328275])" ] }, - "execution_count": 11, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -7009,6 +8969,10 @@ "execution_count": 11, "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -7587,7 +9551,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "id": "6a61d3fa-97a9-4274-945c-be2742d1e956", "metadata": {}, "outputs": [], @@ -7608,30 +9572,30 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "id": "b86effb9-d8ad-4b50-8174-ea76dcd60c32", "metadata": { "scrolled": true }, "outputs": [], "source": [ - "# cr_gp_preargs = {'log_radius': cr_gp.x[0], 'theta': cr_gp.x[1], 'y2': cr_gp.x[2]}\n", - "# cr_gp_args = {}\n", - "# cr_gp_args['x1'] = (10 ** cr_gp_preargs['log_radius']) * np.sin(cr_gp_preargs['theta'])\n", - "# cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", - "# cr_gp_args['y2'] = cr_gp_preargs['y2']\n", + "cr_gp_preargs = {'log_radius': cr_gp.x[0], 'theta': cr_gp.x[1], 'y2': cr_gp.x[2]}\n", + "cr_gp_args = {}\n", + "cr_gp_args['x1'] = (10 ** cr_gp_preargs['log_radius']) * np.sin(cr_gp_preargs['theta'])\n", + "cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", + "cr_gp_args['y2'] = cr_gp_preargs['y2']\n", "\n", - "cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", - "cr_gbrt_args = {}\n", - "cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", - "cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", - "cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", + "# cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", + "# cr_gbrt_args = {}\n", + "# cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", + "# cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", + "# cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", "\n", - "# msy_gp_args = {'mortality': msy_gp.x[0]}\n", + "msy_gp_args = {'mortality': msy_gp.x[0]}\n", "# msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", "\n", - "# esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", - "esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", + "esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", + "# esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", "\n", "# msy_gbrt_args = {'mortality': 0.05365088255575121}\n", "# esc_gbrt_args = {'escapement': 0.010338225232077163}\n", @@ -7645,11 +9609,11 @@ "\n", "env = AsmEnv(config=CONFIG)\n", "\n", - "cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", - "# cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))\n", + "# cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", + "cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))\n", "\n", - "esc_gbrt_df = get_policy_df(ConstEsc(env, **esc_gbrt_args))\n", - "# esc_gp_df = get_policy_df(ConstEsc(env, **esc_gp_args))\n", + "# esc_gbrt_df = get_policy_df(ConstEsc(env, **esc_gbrt_args))\n", + "esc_gp_df = get_policy_df(ConstEsc(env, **esc_gp_args))\n", "\n", "# msy_gbrt_df = get_policy_df(Msy(env, **msy_gbrt_args))\n", "# msy_gp_df = get_policy_df(Msy(env, **msy_gp_args))" @@ -7657,24 +9621,24 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "id": "88d5b45d-eeed-4321-9e9d-1a58ba63e84c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(,\n", - " )" + "(,\n", + " )" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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", + "image/png": 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hhRcwYMAAyGQyjBo1CgDQr18/ALjlnBX/tHHjxnqHi/bv3x9eXl544IEH4O3tjZ49e8LLywunTp3C4sWLMXjwYENfhnfeeQc//fQTevfubRj6evnyZWzYsAF79uyBs7MzHnzwQbz11lsYO3YsevTogWPHjmHNmjWGv4Zv5OrqinvvvRdjx45FTk4OkpKS0KZNG0yYMAEAIJVK8dlnn2HQoEGIiIjA2LFj4efnh4sXL2Lnzp1Qq9X4/vvvG3bQb+Opp57C119/jWeffRY7d+5Ez549odPpcPr0aXz99df48ccf6+28eyu1P8M33ngDo0aNgq2tLYYMGXLTsx6PP/44jh8/jsTERBw4cACjRo1CUFAQysrKcPz4cXz11VdQqVRGfWSaQnp6Oh566CEMHDgQ+/btw+rVq/H444+jc+fOAJr+38BHH32Ee++9F//6178wceJEBAUF4fz589i6dWudzrmjR4/G8OHDAQBz5sxpks9LVkKsYTxEjZWSkiJMmDBBCAwMFORyuaBSqYSePXsKixYtEiorKw3rVVdXC7NnzxaCgoIEW1tbwd/fX5g+fbrROoJQM7S3viG7Nw53fPvtt4Xo6GjB2dlZsLOzE9q1ayfMnTtX0Gg0hnW0Wq3w/PPPCx4eHoJEIjEa5hsQECAEBATc9vPdamgvAGHnzp2CIAjCp59+KvTq1Utwc3MTFAqFEBISIvznP/8RioqKjN4vIyNDGD16tODh4SEoFAohODhYiI+PF6qqqgRBqBna+/LLLws+Pj6CnZ2d0LNnT2Hfvn11Pn/t0N6vvvpKmD59uuDp6SnY2dkJgwcPrjPcUxAE4c8//xQeeeQRQ30BAQHCiBEjhOTk5DqfNS8vz2jbuLg4wcHBod6fyY3DmTUajfDuu+8KERERgkKhEFxcXITIyEhh9uzZRscCgBAfH1/nPQMCAoyGCwuCIMyZM0fw8/MTpFJpg4f57tq1Sxg+fLjg4+Mj2NraCmq1WoiKihISEhKEy5cv3/ZzNFTtMTt58qQwfPhwQaVSCS4uLsLkyZOFiooKo3Ub+m+gIUN7BUEQjh8/Ljz88MOCs7OzoFQqhbCwMGHGjBl1aqyqqhJcXFwEJyenOjUR3YpEEJrpXCIRtQi7du1C3759sWHDBsNfvWR6s2bNwuzZs5GXl2e2zR9arRa+vr4YMmRInb5IRLfCPiNERNQkNm/ejLy8PIwePVrsUsjCsM8IERHdlf379+Pvv//GnDlzcM8996B3795il0QWhmdGiIjornzyySd47rnn4OnpWedCk0QNwT4jREREJCqeGSEiIiJRMYwQERGRqCyiA6ter8elS5egUqlMPu02ERER3RlBEFBSUgJfX1/DVcLrYxFh5NKlS3UufEVERESWISsrC61atbrp6xYRRmqnuM7KyjJcUp6IiIjMW3FxMfz9/Q3f4zdjEWGktmlGrVYzjBAREVmY23WxYAdWIiIiEhXDCBEREYmKYYSIiIhEZRF9RhpCr9dDo9GIXQYRAEAul99yGBsREV3XIsKIRqNBeno69Hq92KUQAQCkUimCgoIgl8vFLoWIyOxZfBgRBAGXL1+GTCaDv78//xol0dVO0nf58mW0bt2aE/UREd2GxYcRrVaL8vJy+Pr6wt7eXuxyiAAAHh4euHTpErRaLWxtbcUuh4jIrFn8aQSdTgcAPB1OZqX297H295OIiG7O4sNILZ4KJ3PC30ciooZrMWGEiIiILBPDiEgEQcDEiRPh6uoKiUQCZ2dnvPjiiw3atk+fPrddVyKRYPPmzXddZ0szZswYDBs2zPC8IceSiIial8V3YLVU27dvx3//+1/s2rULwcHBkEqlsLOza7L3v3z5MlxcXJrs/cxNnz590KVLFyQlJd3V+2zatMmog2lgYCBefPFFBhQiIhNiGBFJWloafHx80KNHj2Z5f29v72Z5X7FpNJom7azs6uraZO9FRGRJ9HoBFdU6lGm0KK/SwdtJCaWtTJRa2EwjgjFjxuD5559HZmYmJBIJAgMD6zQXfPzxxwgNDYVSqYSXlxeGDx9u9B56vR6vvPIKXF1d4e3tjVmzZhm9/s9mmvPnz0MikWDTpk3o27cv7O3t0blzZ+zbt89om+XLl8Pf3x/29vZ4+OGHsWDBAjg7OzfoM82aNQtdunTBihUr0Lp1azg6OmLSpEnQ6XR477334O3tDU9PT8ydO9dou8zMTAwdOhSOjo5Qq9UYMWIEcnJy6rzvZ599hqCgICiVSowZMwa7d+/GwoULIZFIIJFIcP78eeh0OowbNw5BQUGws7NDWFgYFi5ceMu6/3nc+/Tpg4yMDLz00kuG9y0rK4NarcbGjRuNttu8eTMcHBxQUlLSoONDRHQ3BEFAhUaHvJIqnM8vw/GLRTiQXoCdp3Ox5e9LWH8wEyv2pGNR8lnM++E0Zn53HC9//ReeW30Yo1ccwPBP9mLQwt/Q+/2diHr7Z4TP3I7g17chIuFHRM9NRp8PduFsTqlon6/FnRkRhJqkJwY7W1mDRlEsXLgQISEhWLZsGQ4ePAiZTIZHH33U8PqhQ4fwwgsv4Msvv0SPHj1QUFCA3377zeg9Vq1ahalTp2L//v3Yt28fxowZg549e6J///433e8bb7yBDz74AKGhoXjjjTfw2GOPITU1FTY2Nvj999/x7LPP4t1338VDDz2En3/+GTNmzGjU509LS8MPP/yA7du3Iy0tDcOHD8e5c+fQtm1b7N69G3v37sXTTz+N2NhYxMTEQK/XG4LI7t27odVqER8fj5EjR2LXrl2G901NTcU333yDTZs2QSaTISAgACkpKejQoQPeeustADXzeuj1erRq1QobNmyAm5sb9u7di4kTJ8LHxwcjRoy4bf2bNm1C586dMXHiREyYMAEA4ODggFGjRmHlypVGgbD2uUqlatQxIiLrIQgCqrR6FFdWo7RSi9Iq7fX7a7eSSi3K/vH8+mNdzeNKLco0Ncv1QvPUKZEA9rYyaESciqDFhZGKah3CZ/4oyr5PvjUA9vLbH1InJyeoVCrIZLJ6m1MyMzPh4OCABx98ECqVCgEBAbjnnnuM1unUqRMSEhIAAKGhoVi8eDGSk5NvGUamTZuGwYMHAwBmz56NiIgIpKamol27dli0aBEGDRqEadOmAQDatm2LvXv3YsuWLQ3+/Hq9HitWrIBKpUJ4eDj69u2LM2fOYNu2bZBKpQgLC8O7776LnTt3IiYmBsnJyTh27BjS09Ph7+8PAPjiiy8QERGBgwcPomvXrgBqmma++OILeHh4GPYll8thb29vdPxkMhlmz55teB4UFIR9+/bh66+/blAYcXV1hUwmg0qlMnrf8ePHo0ePHrh8+TJ8fHyQm5uLbdu24eeff27wsSEiy6LXCyip0qKksholldprt2rDfXFlbZioWVZau861ZbXBQ9sMCcJBLoO9wgaOChs4KGSwl9c8tpfLrt3bwFFRs46DvOZ1B4UMdrXL5TZwkNvAXiGDg9wGSlup6NMRtLgw0hL0798fAQEBCA4OxsCBAzFw4EA8/PDDRjPMdurUyWib2i/JW/nnNj4+PgCA3NxctGvXDmfOnMHDDz9stH50dHSjwkhgYKDRmQIvLy/IZDKjKfq9vLwMdZ46dQr+/v6GIAIA4eHhcHZ2xqlTpwxhJCAgwCiI3MqSJUuwYsUKZGZmoqKiAhqNBl26dGnwZ6hPdHQ0IiIisGrVKrz22mtYvXo1AgIC0KtXr7t6XyJqPoIgoLRKi6KKahRVVKO4QoviymoU1z6v1KK4ovrasuuvlVTWPC6t0kJoohwhkQCOchs4KGygUl6/dzQEiuvLHRQ2UClqH8sMr9fe29vKIJW2vHmMWlwYsbOV4eRbA0Tbd1NQqVQ4cuQIdu3ahZ9++gkzZ87ErFmzcPDgQUMfjhunGJdIJLe9UOA/t6lNwU15ccH6arqTOm/k4ODQoPXWrVuHadOmYf78+ejevTtUKhXef/997N+/v1H7q8/48eOxZMkSvPbaa1i5ciXGjh0r+l8SRC2dIAiorNajsEKDwvJqFJZXo+ja49qQUWgIGzWvF1def94UJyXkMinUdjZQKW2hUtaEBpWi9vE/ll177qi4/txRYQtHZcsNEE2pxYURiUTSoKYSc2djY4PY2FjExsYiISEBzs7O+OWXX/DII480y/7CwsJw8OBBo2U3Pm9q7du3R1ZWFrKysgxnR06ePInCwkKEh4ffclu5XF5nqvXff/8dPXr0wKRJkwzL0tLSGlVTfe8LAE8++SReeeUVfPTRRzh58iTi4uIa9b5E1k6r06OwohqF5RpcLa9GQZnG8LgmaGhwtfx66CisqHlNo727P5jkNlI42dlCrbSpubezhVppe+1xTYBwsqsJFWplzeu1j1VKG9FGl1gby//WboG2bNmCc+fOoVevXnBxccG2bdug1+sRFhbWbPt8/vnn0atXLyxYsABDhgzBL7/8gh9++KFZ//qPjY1Fx44d8cQTTyApKQlarRaTJk1C7969ERUVdcttAwMDsX//fpw/fx6Ojo5wdXVFaGgovvjiC/z4448ICgrCl19+iYMHDyIoKKjBNQUGBuLXX3/FqFGjoFAo4O7uDgBwcXHBI488gv/85z944IEH0KpVq7v67ESWrLYJpKBMgytlGhSUalBQrkFBmQZXy67dX3teeyuu1N7x/mykEjjb14QGZ3t5zf21YFG7vL6b2s6WYcJCMIyYIWdnZ2zatAmzZs1CZWUlQkND8dVXXyEiIqLZ9tmzZ08sXboUs2fPxptvvokBAwbgpZdewuLFi5ttnxKJBN99950hCEmlUgwcOBCLFi267bbTpk1DXFwcwsPDUVFRgfT0dDzzzDP4888/MXLkSEgkEjz22GOYNGkSfvjhhwbX9NZbb+GZZ55BSEgIqqqqIPyj0XjcuHFYu3Ytnn766Tv6vETmrLJah/zSKuSXanCltApXSjXIL6u5LyjTIL/0+uOCMg00ujs7Y6FW2sDVQQ5nezlc7G3hYn/9sbO97bXH8muPa547yBs2UpEsl0QQmqqLTvMpLi6Gk5MTioqKoFarjV6rrKxEenq6YQ4KajoTJkzA6dOn6wwrtlZffvklXnrpJVy6dOm2E6/x95LMQW3AyCupueWXaq7dVxnuawNIaVXjz1zY2crg6iCHm6Mcrg5yuNrX3Ls4XLu/9tzVoSZ0ONnZwkbG6a2sya2+v/+JZ0bI4IMPPkD//v3h4OCAH374AatWrcLHH38sdlmiKy8vx+XLlzFv3jw888wzTToDLNGdKKvSIqe4EjnFVcgtqURu7f210FF7X1RR3aj3lcukcHeUw12lqAkZDgq4O9aGDQXcHOVwuxY03BwUsJOzCYSaBsMIGRw4cADvvfceSkpKEBwcjI8++gjjx48HAERERCAjI6Pe7T799FM88cQTpizVpN577z3MnTsXvXr1wvTp08Uuh1owrU6PvNIqXC6qRE5RJbKvBY6c4kpkF1Ui51rwaMxZDLlMCg+VAu4qBTwc5TWPHRWG+5pbTQBRKWzYHEKiYDMNNUhGRgaqq+v/K8vLy4szkd6Av5d0I61Oj9ySKlwuqsClwkpcLqrA5aKakFF7n1tS2eDhqI4KG3iqFPBUK+CpUho99lApap6rlFDbMWCQeNhMQ00qICBA7BKIzFpJZTUuFlbgUmEFLl6twMXCSsPzy4UVyCmpgq4BScNGKoGXWgkvtQLeTkp4qZXwViuvLVPC26kmeDgo+N83tRz8bSYiaoDSKi2yCspx4WoFLlytuf/n84YMXa0NGn7OdvBxVsLHyQ4+TjUBo/be3UHBCbLI6rSYMGIBrU1kRfj7aHl0egGXiyqQeaUcmQXlyLpajsyCiprHBeUoKNPc9j2c7Gzh52wHPxe7mntnO/g628HXWQlfZzu4OyogY9AgqsPiw4itrS0kEgny8vLg4eHBtlESnSAIyMvLq3c6fBKXVqfHhasVSL9Shoz8Mpy/FjzOXynDhYKK286d4WxvC38Xe7RysUMrFzv4u9Y89nO2h5+LHRzZdEJ0Ryz+X45MJkOrVq1w4cIFnD9/XuxyiADUTOjWqlUryGQc+mhqgiAgt6QKabmlSMsvw/n8MqRfu88sKL/lVVRtZRL4u9ijtZs9Wrvaw9/FHv6u1x672kGlZLgkag4WH0YAwNHREaGhoTcd7UFkara2tgwizUyj1eP8lTKk5pYiNbcU5/JKcS6/DOfyym459FVhI0WgmwMC3e0R6OaA1m7X7l3t4etsx2YUIhG0iDAC1Jwh4X/+RC1PlVaHtNwypOSUIDW3FGdzS3A2txQZV8pvOjpFKgFau9oj2MMRQe4OhluguwN81Ep2ECUyMy0mjBCRZdPpBWRcKcOZ7BKcySlBSk4JzmSX4PwtQoejwgYhno5o4+GIEE8HBLs7IsSj5myHwoZ/nBBZCoYRIjK5ovJqnM4uxqnLxTidXYJTl4txJqcEldX1dyBVK20Q5q1CqJcKbTwcEerliDaejvBWK9lpnagFYBghomZT25n0xKUiHL9YjBOXinDiUjEuXK2od32lrRRtvVQI81IhzFtV89hbBU+VgqGDqAVjGCGiJpNbXIm/LhTh2IVC/H2xCMcvFiG/tP75Ofyc7dDeR4X2Pmq081ajvY8KAW4O7EBKZIUYRojojhRXVuOvrEIczSysCSAXC5FTXFVnPakEaOPpiAhfJ0T4qhHh64RwXzWc7DhMlohqMIwQ0W3p9AJSckrwZ2Yh/sy8ij+zCpGWV4obJ5qVSoBQTxU6tnJC51ZOiPBzQntvNS81T0S3xDBCRHWUVWlxNKsQB88X4HDGVRzJuIoyja7Oeq1d7dHF3xmdWjmhs78zwn3UvIAbETUa/9cgIhSUaXAg/Qr2pxfg0PmrOHm5uM5wWkeFDTr7O+Eefxd08XdGl9bOcHdUiFQxEbUkDCNEVii/tAoH0gvwx7kr2H+uAGdySuqs4+dsh6hAF0QFuCAq0BVtvVTsXEpEzYJhhMgKlFZpsf/cFexJzcfvqflIySmts06Ylwoxwa6ICnRFVIALfJ3tRKiUiKwRwwhRC1St0+OvrELsSc3HnrP5OJpVWOcCce28VegW7IZuwa6IDnKDq4NcpGqJyNoxjBC1EDnFldh9Jg+7UnLx29l8lFQaXywuwM0ePdu447427ogJZvggIvPBMEJkobQ6Pf7MKsTO07nYeSYPpy4XG73uYm+LHm3cce+1m7+rvUiVEhHdGsMIkQUp12jxa0o+dpzMwS+nc3C1vNrwmkQCdGrljD5tPdAnzAOdWjmzwykRWQSGESIzl19ahR0nc7DjZA72pOZDo71+MTlne1v0buuBvmGeuC/UHW4caktEFohhhMgM5ZVUYfuJbGz7+zL2p1/BP/ue+rvaoX97b/QP90LXQBfYyKTiFUpE1AQYRojMRG5JJX48no2txy7jQHqBUQDp1MoJD4R7oX+4N9p6OfIKtkTUojCMEImorEqL7cezsfnoRfyemm8UQDr7O2NwR28M6uDDzqdE1KIxjBCZmFanx2+p+dj850X8dCIHFdXXr/nCAEJE1ohhhMhEzuaUYN3BLHx39CLySzWG5UHuDnj4Hj8M6+KH1m4MIERkfRhGiJpRuUaLLX9fxvqDWTiccdWw3NVBjoc6+2LYPX7o3MqJfUCIyKoxjBA1g78vFGLdwSz87+gllFbVzIQqk0rQr50nRkT5o3eYB2w5CoaICADDCFGTqdLqsO3YZfz39/P460KRYXmAmz1GdvXH8MhW8FQpRayQiMg8MYwQ3aWc4kqs2Z+JtfszDH1B5DIpBnX0xqiurRET5AopZ0IlIrophhGiO/Rn5lWs/P08th27bLgirrdaiSe7tcao6NZw52yoREQNwjBC1AiCIGB3Sh4+2ZWG/ekFhuVdA10wpkcQHojwYl8QIqJGYhghagCtTo9tx7Pxya40w9VxbWUSDO3ihzE9AtHBz0nkComILBfDCNEtVFbrsPHwBSz79RwyC8oBAPZyGR6Pbo1x9wXBx8lO5AqJiCzfHZ1PXrJkCQIDA6FUKhETE4MDBw7ccv2kpCSEhYXBzs4O/v7+eOmll1BZWXlHBROZgkarx5r9Gej7wS68ufk4MgvK4WJvi6n922Lva/fjzQfDGUSIiJpIo8+MrF+/HlOnTsXSpUsRExODpKQkDBgwAGfOnIGnp2ed9deuXYvXXnsNK1asQI8ePZCSkoIxY8ZAIpFgwYIFTfIhiJqKVqfH5qOXsDA5BVkFFQBqOqU+2zsYI7r6w17Ok4lERE1NIgiCcPvVrouJiUHXrl2xePFiAIBer4e/vz+ef/55vPbaa3XWnzx5Mk6dOoXk5GTDspdffhn79+/Hnj17GrTP4uJiODk5oaioCGq1ujHlEjWIXi9gy7HLSPo5BefyygAA7o4KxPcNwWPRraG0lYlcIRGR5Wno93ej/szTaDQ4fPgwpk+fblgmlUoRGxuLffv21btNjx49sHr1ahw4cADR0dE4d+4ctm3bhqeeeqoxuyZqNr+n5mPOlpM4nV0CAHCxt8WzvUMwunsg7OQMIUREza1RYSQ/Px86nQ5eXl5Gy728vHD69Ol6t3n88ceRn5+Pe++9F4IgQKvV4tlnn8Xrr79+0/1UVVWhqqrK8Ly4uLgxZRI1SHp+GeZuPYWfT+UAAFRKG0y4LxhjewZCpbQVuToiIuvR7BMi7Nq1C++88w4+/vhjHDlyBJs2bcLWrVsxZ86cm26TmJgIJycnw83f37+5yyQrUlRejTlbTuKBD3fj51M5kEklGNMjEL/+py9e6BfKIEJEZGKN6jOi0Whgb2+PjRs3YtiwYYblcXFxKCwsxHfffVdnm/vuuw/dunXD+++/b1i2evVqTJw4EaWlpZBK6+ah+s6M+Pv7s88I3RWtTo+vDmRiwY4UXC2vBgD0DfPAG4Pbo42nSuTqiIhanmbpMyKXyxEZGYnk5GRDGNHr9UhOTsbkyZPr3aa8vLxO4JDJatrhb5aDFAoFFApOpU1N5+8LhZi+6RhOXKpp8mvj6Yg3B7dHn7C6I8CIiMi0Gj1OcerUqYiLi0NUVBSio6ORlJSEsrIyjB07FgAwevRo+Pn5ITExEQAwZMgQLFiwAPfccw9iYmKQmpqKGTNmYMiQIYZQQtRcyqq0WLAjBSt/T4deANRKG0wbEIbHo1vDhtO2ExGZhUaHkZEjRyIvLw8zZ85EdnY2unTpgu3btxs6tWZmZhqdCXnzzTchkUjw5ptv4uLFi/Dw8MCQIUMwd+7cpvsURPX45XQOZmw+gYuFNfOFPNTZFzMeDIeHimfdiIjMSaPnGRED5xmhxsgtqcTs709i69+XAQB+znZ4++EO6MsmGSIik2qWPiNE5m7r35fx+rfHUFRRDakEGHdvEF7q35YzpxIRmTH+D00tQkllNRL+dwKbjlwEAET4qvHu/3Xi1XSJiCwAwwhZvMMZBXhx/VFkFVRAKgEm9WmDKbGhsGUHVSIii8AwQharWqfHouSzWLwzFXqhpm/IhyO7IDrIVezSiIioERhGyCJlXCnDlHVHcTSrEADw8D1+mD00AmrOnkpEZHEYRsji7DyTiylf/YniSi1UShvMfbgjHursK3ZZRER0hxhGyGLo9QI+3pWK+TtSIAjAPa2dsfjxf8HP2U7s0oiI6C4wjJBFKKmsxstf/4WfTtZcYffxmNZIGBIOhQ1n8SUisnQMI2T20vJKMfGLQ0jLK4NcJsVbQyMwKrq12GUREVETYRghs7bjZA5eWn8UpVVaeKuV+OTJf+Ge1i5il0VERE2IYYTM1ud70jFny0kAQHSgK5Y88S9eV4aIqAViGCGzIwgC5m0/jU93nwMAPNUtADOHhHMSMyKiFophhMxKtU6PV7/52zCt+ysDw/Bc7xBIJBKRKyMioubCMEJmo6xKi0lrjmB3Sh5kUgnmPdIRj0b5i10WERE1M4YRMgtXSqvw9H8P4q8LRbCzleHjJ/6Fvu08xS6LiIhMgGGERJdVUI7RKw4gPb8MLva2WDGmK0fMEBFZEYYRElVWQTlGfroPl4oq4edshy/GRSPEw1HssoiIyIQYRkg0lwor8Phnf+BSUSWCPRzw1YRu8FIrxS6LiIhMjGMlSRS5xZV44rP9yCqoQICbPdaOZxAhIrJWDCNkcvmlVXj8s/1Izy+Dn7Md1k7oBm8nBhEiImvFMEImdbVMgyc/24/U3FL4OCnx1YRuvOouEZGVYxghkymqqMZTK/bjdHYJPFQKrBkfg9Zu9mKXRUREImMYIZMoq9IibsUBHL9YDDcHOdaOj0EwR80QEREYRsgEdHoBU9YdxdGsQjjb22L1+BiEeqnELouIiMwEwwg1u/e2n8bPp3Igt5Hi87iuaO+jFrskIiIyIwwj1Ky+PpiFT3+tufru+8M7ITKAM6sSEZExhhFqNn+cu4LXvz0GAHihXyiGdvETuSIiIjJHDCPULM7nl+HZ1Yeh1QsY3MkHL/YLFbskIiIyUwwj1OSKyqvx9KqDKCyvRmd/Z8x/tDOkUonYZRERkZliGKEmVa3TI37tEZzLK4OPkxLLn4qE0lYmdllERGTGGEaoSb295ST2pObDXi7DZ3FR8OT1ZoiI6DYYRqjJbD+ejVX7MgAAC0fdgwhfJ5ErIiIiS8AwQk3iclEFXtv0NwDgmV7B6B/uJXJFRERkKRhG6K7p9AJeWn8UheXV6NTKCS8/ECZ2SUREZEEYRuiuLd2dhj/OFcBeLsPCUfdAbsNfKyIiajh+a9Bd+TPzKhbsSAEAzH4oAkHuDiJXREREloZhhO5YSWU1pqw7Cp1ewJDOvhge2UrskoiIyAIxjNAdm/ndCWQWlMPP2Q5vD+sAiYQTmxERUeMxjNAd+fbPC/j2z4uQSSX46LEucLKzFbskIiKyUAwj1GhZBeWYsfkEAGBKv1BEBriKXBEREVkyhhFqFEEQMPO74yit0qJroAvi+7YRuyQiIrJwDCPUKD+eyMHOM3mwlUkw7/86QcYL4BER0V1iGKEGK6vS4q3va5pnnukVghAPR5ErIiKiloBhhBrso1/O4lJRJfxd7TD5fjbPEBFR02AYoQZJySnB57+lAwBmDYmA0lYmckVERNRSMIzQbQmCgDc3H4dWL+CBcC/0a8+L4BERUdNhGKHb2nTkIg6kF8DOVoaZQ8LFLoeIiFoYhhG6paLyaryz7RQA4IV+oWjlYi9yRURE1NIwjNAtvf/TaVwp0yDU0xHj7g0SuxwiImqBGEbopo5mFWLN/kwAwJxhHSC34a8LERE1PX67UL0EQUDCd8chCMAj9/ihW7Cb2CUREVELxTBC9dpxMgd/XSiCvVyG6f9uL3Y5RETUgjGMUB16vYAPfz4LABjbMxAeKoXIFRERUUvGMEJ1/HgiG6cuF8NRYYMJ9wWLXQ4REbVwDCNkRKcX8OHPKQCAp+8NgrO9XOSKiIiopWMYISNbj11GSk4p1EobDuUlIiKTYBghA51eQNK1syIT7guGk52tyBUREZE1YBghg//9dRHn8srgbG+LMT0DxS6HiIisBMMIAQC0Oj0WXhtBM7FXMFRKnhUhIiLTYBghAMCmPy/i/JVyuDnIEdc9UOxyiIjIijCMEKp1enyUXHNW5NneIXBQ2IhcERERWZM7CiNLlixBYGAglEolYmJicODAgVuuX1hYiPj4ePj4+EChUKBt27bYtm3bHRVMTW/j4Qu4cLUC7o4KPNktQOxyiIjIyjT6T+D169dj6tSpWLp0KWJiYpCUlIQBAwbgzJkz8PT0rLO+RqNB//794enpiY0bN8LPzw8ZGRlwdnZuivrpLlVpdVj8SyoAYFKfENjJZSJXRERE1qbRYWTBggWYMGECxo4dCwBYunQptm7dihUrVuC1116rs/6KFStQUFCAvXv3wta2plNkYGDg3VVNTebbIxdxsbACXmoFHo9pLXY5RERkhRrVTKPRaHD48GHExsZefwOpFLGxsdi3b1+92/zvf/9D9+7dER8fDy8vL3To0AHvvPMOdDrdTfdTVVWF4uJioxs1PUEQ8N+95wHUzCuitOVZESIiMr1GhZH8/HzodDp4eXkZLffy8kJ2dna925w7dw4bN26ETqfDtm3bMGPGDMyfPx9vv/32TfeTmJgIJycnw83f378xZVIDHc64itPZJVDaSvFoJI8xERGJo9lH0+j1enh6emLZsmWIjIzEyJEj8cYbb2Dp0qU33Wb69OkoKioy3LKyspq7TKv05R8ZAIChnf3gZM95RYiISByN6jPi7u4OmUyGnJwco+U5OTnw9vaudxsfHx/Y2tpCJrveBNC+fXtkZ2dDo9FALq97ITaFQgGFgpetb055JVXYduwyAOCp7hxBQ0RE4mnUmRG5XI7IyEgkJycblun1eiQnJ6N79+71btOzZ0+kpqZCr9cblqWkpMDHx6feIEKmsf5gJqp1Au5p7YwOfk5il0NERFas0c00U6dOxfLly7Fq1SqcOnUKzz33HMrKygyja0aPHo3p06cb1n/uuedQUFCAKVOmICUlBVu3bsU777yD+Pj4pvsU1ChanR5r92cCAJ7ivCJERCSyRg/tHTlyJPLy8jBz5kxkZ2ejS5cu2L59u6FTa2ZmJqTS6xnH398fP/74I1566SV06tQJfn5+mDJlCl599dWm+xTUKMmnc3GpqBKuDnL8u6OP2OUQEZGVkwiCIIhdxO0UFxfDyckJRUVFUKvVYpdj8Z76fD9+O5uPZ3uH4LVB7cQuh4iIWqiGfn/z2jRW5lxeKX47mw+JBHiCk5wREZEZYBixMqv/qOkrcn+YJ/xd7UWuhoiIiGHEqpRrtNhwuGbOFg7nJSIic8EwYkX+d/QSSiq1CHCzR69QD7HLISIiAsAwYjUEQcAX+2pmXH0yJgBSqUTkioiIiGowjFiJI5mFOHm5GAobKR6NaiV2OURERAYMI1biy33nAQAPdfaFsz1nviUiIvPBMGIFSiqrse14zVWVn+SMq0REZGYYRqzAz6dyoNHqEeLhgE6teB0aIiIyLwwjVmDr3zVnRQZ39IFEwo6rRERkXhhGWriSymr8ejYPAPDvTrwODRERmR+GkRYu+VQuNFo9gj0cEOalErscIiKiOhhGWrgtf18GADzIJhoiIjJTDCMtGJtoiIjIEjCMtGBsoiEiIkvAMNKCbT1W00TDUTRERGTOGEZaqJLKauxOqWmiGcwmGiIiMmMMIy0Um2iIiMhSMIy0UGyiISIiS8Ew0gL9s4nm3x3ZRENEROaNYaQFMjTRuDugnTebaIiIyLwxjLRAhiaaTmyiISIi88cw0sKwiYaIiCwNw0gL88tpNtEQEZFlYRhpYbZeuxbNvzmKhoiILATDSAtSUlmNXZzojIiILAzDSAvCJhoiIrJEDCMtyO4zNWdFHojwZhMNERFZDIaRFkIQBOxNuwIAuC/UXeRqiIiIGo5hpIVIzy9DdnEl5DIpIgNcxC6HiIiowRhGWojfr50V+VeAM5S2MpGrISIiajiGkRZiX1o+AKBnCJtoiIjIsjCMtAB6vYB9186M9GjjJnI1REREjcMw0gKcyi7G1fJqOMhl6NTKWexyiIiIGoVhpAWoPSsSHeQKWxl/pEREZFn4zdUC1A7p7cH+IkREZIEYRixctU6P/edqwkj3EPYXISIiy8MwYuH+vlCEMo0Ozva2CPdRi10OERFRozGMWLjaIb3dg90glXIKeCIisjwMIxbuen8RNtEQEZFlYhixYJXVOhzKuAoA6M7Oq0REZKEYRizYkYyr0Gj18FIrEOLhIHY5REREd4RhxIL9c0ivRML+IkREZJkYRizY3trOq+wvQkREFoxhxEKVVFbjrwtFANh5lYiILBvDiIU6eL4AOr2AADd7tHKxF7scIiKiO8YwYqH2pnJILxERtQwMIxaqtvMqh/QSEZGlYxixQAVlGpy8XAygZuZVIiIiS8YwYoH+uHZhvDAvFTxUCpGrISIiujsMIxaIQ3qJiKglYRixQLX9RXq2YX8RIiKyfAwjFuZKaRXO5ZUBAKKDXEWuhoiI6O4xjFiYE5dqOq4GuzvAyc5W5GqIiIjuHsOIhTl+qWbW1Qg/J5ErISIiahoMIxbmxMWaMyMRvmqRKyEiImoaDCMW5sS1MyMdfHlmhIiIWgaGEQtSXFmN81fKAfDMCBERtRwMIxbk5LXOq37OdnBxkItcDRERUdNgGLEgtSNpeFaEiIhakjsKI0uWLEFgYCCUSiViYmJw4MCBBm23bt06SCQSDBs27E52a/VOXLzWX4QjaYiIqAVpdBhZv349pk6dioSEBBw5cgSdO3fGgAEDkJube8vtzp8/j2nTpuG+++6742KtXe2w3g5+PDNCREQtR6PDyIIFCzBhwgSMHTsW4eHhWLp0Kezt7bFixYqbbqPT6fDEE09g9uzZCA4OvquCrVWFRofU3FIAQARH0hARUQvSqDCi0Whw+PBhxMbGXn8DqRSxsbHYt2/fTbd766234OnpiXHjxjVoP1VVVSguLja6WbvT2cXQC4C7owKevFIvERG1II0KI/n5+dDpdPDy8jJa7uXlhezs7Hq32bNnDz7//HMsX768wftJTEyEk5OT4ebv79+YMluk49c6r3bwU0MikYhcDRERUdNp1tE0JSUleOqpp7B8+XK4uzf8CrPTp09HUVGR4ZaVldWMVVoGQ+dVNtEQEVELY9OYld3d3SGTyZCTk2O0PCcnB97e3nXWT0tLw/nz5zFkyBDDMr1eX7NjGxucOXMGISEhdbZTKBRQKNgU8U+Ga9JwWC8REbUwjTozIpfLERkZieTkZMMyvV6P5ORkdO/evc767dq1w7Fjx3D06FHD7aGHHkLfvn1x9OhRNr80kEarR0p2TedVDuslIqKWplFnRgBg6tSpiIuLQ1RUFKKjo5GUlISysjKMHTsWADB69Gj4+fkhMTERSqUSHTp0MNre2dkZAOosp5s7m1sCjU4PtdIGrVzsxC6HiIioSTU6jIwcORJ5eXmYOXMmsrOz0aVLF2zfvt3QqTUzMxNSKSd2bUrXr9TrxM6rRETU4kgEQRDELuJ2iouL4eTkhKKiIqjV1tdnIuG741i1LwMT7gvCG4PDxS6HiIioQRr6/c1TGBbg+rBe9hchIqKWh2HEzOn0guFqvZx5lYiIWiKGETOXnl+Kimod7GxlCHJ3ELscIiKiJscwYuZOXDsrEu6rhkzKzqtERNTyMIyYueOGmVetr+MuERFZB4YRM3f8IvuLEBFRy8YwYsYEQcCJ2mng/XhmhIiIWiaGETN24WoFiiu1kMukCPVUiV0OERFRs2AYMWO1/UXaejtCbsMfFRERtUz8hjNjtVfq7cD+IkRE1IIxjJix2mG9EZx5lYiIWjCGETMlCAKH9RIRkVVgGDFTuSVVyC/VQCoB2nkzjBARUcvFMGKmaof0tvF0hJ1cJnI1REREzYdhxEzVTnbGzqtERNTSMYyYqbS8UgBAW2/OL0JERC0bw4iZOn+lHAAQ6GYvciVERETNi2HETGVeKQMABLg5iFwJERFR82IYMUNF5dW4Wl4NAGjtyjMjRETUsjGMmKGMgpqzIh4qBRwUNiJXQ0RE1LwYRsxQxrX+IgE8K0JERFaAYcQMZbC/CBERWRGGETNkODPCkTRERGQFGEbMEMMIERFZE4YRM1TbgZXNNEREZA0YRsxMhUaHnOIqAJzwjIiIrAPDiJnJLKhpolErbeBsLxe5GiIioubHMGJmzl8bSRPoziYaIiKyDgwjZibzWudVzrxKRETWgmHEzBjOjLDzKhERWQmGETNT22ekNTuvEhGRlWAYMTM8M0JERNaGYcSMaLR6XLxaAYATnhERkfVgGDEjFwsroBcApa0UniqF2OUQERGZBMOIGTFcIM/VARKJRORqiIiITINhxIzwmjRERGSNGEbMCMMIERFZI4YRM2JopuFIGiIisiIMI2Yko4BnRoiIyPowjJgJvV4wTHjGOUaIiMiaMIyYieziSmi0ethIJfBxUopdDhERkckwjJiJ2plX/V3tYSPjj4WIiKwHv/XMBK/WS0RE1ophxEycv1LbX4RhhIiIrAvDiJnILKhppmnNzqtERGRlGEbMxPl8nhkhIiLrxDBiBgTh+rBezjFCRETWhmHEDFwp06C0SguJBGjlwjBCRETWhWHEDNRek8ZHrYTSViZyNURERKbFMGIGeE0aIiKyZgwjZoBX6yUiImvGMGIGeGaEiIisGcOIGeDVeomIyJoxjJgBNtMQEZE1YxgRWXFlNQrKNADYTENERNaJYURktRfIc3eUw1FhI3I1REREpscwIrLz7LxKRERWjmFEZIb+Iq7sL0JERNaJYURkHNZLRETWjmFEZBxJQ0RE1u6OwsiSJUsQGBgIpVKJmJgYHDhw4KbrLl++HPfddx9cXFzg4uKC2NjYW65vbRhGiIjI2jU6jKxfvx5Tp05FQkICjhw5gs6dO2PAgAHIzc2td/1du3bhsccew86dO7Fv3z74+/vjgQcewMWLF++6eEtXWa1DdnElADbTEBGR9ZIIgiA0ZoOYmBh07doVixcvBgDo9Xr4+/vj+eefx2uvvXbb7XU6HVxcXLB48WKMHj26QfssLi6Gk5MTioqKoFarG1OuWUvPL0PfD3bBXi7DidkDIJFIxC6JiIioyTT0+7tRZ0Y0Gg0OHz6M2NjY628glSI2Nhb79u1r0HuUl5ejuroarq6ujdl1i5RfWgUA8FApGESIiMhqNWqWrfz8fOh0Onh5eRkt9/LywunTpxv0Hq+++ip8fX2NAs2NqqqqUFVVZXheXFzcmDItRl7JtTDiqBC5EiIiIvGYdDTNvHnzsG7dOnz77bdQKpU3XS8xMRFOTk6Gm7+/vwmrNB1DGFExjBARkfVqVBhxd3eHTCZDTk6O0fKcnBx4e3vfctsPPvgA8+bNw08//YROnTrdct3p06ejqKjIcMvKympMmRajtpnGnWdGiIjIijUqjMjlckRGRiI5OdmwTK/XIzk5Gd27d7/pdu+99x7mzJmD7du3Iyoq6rb7USgUUKvVRreWiGdGiIiIGtlnBACmTp2KuLg4REVFITo6GklJSSgrK8PYsWMBAKNHj4afnx8SExMBAO+++y5mzpyJtWvXIjAwENnZ2QAAR0dHODo6NuFHsTwMI0RERHcQRkaOHIm8vDzMnDkT2dnZ6NKlC7Zv327o1JqZmQmp9PoJl08++QQajQbDhw83ep+EhATMmjXr7qq3cGymISIiuoN5RsTQUucZ6ZGYjEtFldgc3xNd/J3FLoeIiKhJNcs8I9R0BEFAfqkGAJtpiIjIujGMiKS4QguNTg8AcHOQi1wNERGReBhGRJJXWnNNGrXSBkpbmcjVEBERiYdhRCS5HElDREQEgGFENLX9RTiShoiIrB3DiEg4xwgREVENhhGRMIwQERHVYBgRCSc8IyIiqsEwIhKeGSEiIqrBMCIShhEiIqIaDCMiqW2m8WAzDRERWTmGERHo9AKulHEqeCIiIoBhRBRXyzXQ6QVIJIArp4InIiIrxzAigtomGhd7OWxl/BEQEZF14zehCAydV9lfhIiIiGFEDBxJQ0REdB3DiAiuT3jG/iJEREQMIyLgmREiIqLrGEZEUHvFXoYRIiIihhFR1J4Z4XVpiIiIGEZEwWYaIiKi6xhGRGCYCp5hhIiIiGHE1Kp1ehSU1/QZYTMNERERw4jJFZRpIAiATCqBiz2H9hIRETGMmFhtfxE3BzlkUonI1RAREYmPYcTE8ko5koaIiOifGEZMjCNpiIiIjDGMmBhH0hARERljGDExTnhGRERkjGHExNhMQ0REZIxhxMTYTENERGSMYcTErjfTcI4RIiIigGHE5GrDiCfPjBAREQFgGDGpKq0OxZVaAICHo1LkaoiIiMwDw4gJ5ZfWXJNGLpNCbWcjcjVERETmgWHEhP7ZX0Qi4VTwREREAMOISeVzWC8REVEdDCMmxOvSEBER1cUwYkKc8IyIiKguhhET4oRnREREdTGMmBCvS0NERFQXw4gJsZmGiIioLoYRE2IzDRERUV0MIybEZhoiIqK6GEZMpFyjRZlGB4BnRoiIiP6JYcRE8ktqpoK3s5XBQS4TuRoiIiLzwTBiInmllQAAdxWngiciIvonhhETMYykYX8RIiIiIwwjJpJ37Yq97C9CRERkjGHERDiShoiIqH4MIybCCc+IiIjqxzBiIpzwjIiIqH4MIybCZhoiIqL6MYyYCJtpiIiI6scwYgKCIFxvpuGZESIiIiMMIyZQUqVFlVYPgGdGiIiIbsQwYgK1TTQqhQ2UtpwKnoiI6J8YRkwgn/1FiIiIbophxATySjmShoiI6GYYRkyAI2mIiIhujmHEBDjhGRER0c3dURhZsmQJAgMDoVQqERMTgwMHDtxy/Q0bNqBdu3ZQKpXo2LEjtm3bdkfFWprSKi2W/ZqGdQeyAADujnKRKyIiIjI/jQ4j69evx9SpU5GQkIAjR46gc+fOGDBgAHJzc+tdf+/evXjssccwbtw4/Pnnnxg2bBiGDRuG48eP33Xx5qqwXIOkn1PQc94veGfbaVwp08DP2Q4DO/iIXRoREZHZkQiCIDRmg5iYGHTt2hWLFy8GAOj1evj7++P555/Ha6+9Vmf9kSNHoqysDFu2bDEs69atG7p06YKlS5c2aJ/FxcVwcnJCUVER1Gp1Y8q9pdySSmiuzf/RFCqr9dhwKAur/8hAmUYHAAh2d8CzfUIwrIsf5DZsFSMiIuvR0O9vm8a8qUajweHDhzF9+nTDMqlUitjYWOzbt6/ebfbt24epU6caLRswYAA2b9580/1UVVWhqqrK8Ly4uLgxZTbYs18expHMwmZ573beKky+vw0GdfCBTCppln0QERG1BI0KI/n5+dDpdPDy8jJa7uXlhdOnT9e7TXZ2dr3rZ2dn33Q/iYmJmD17dmNKuyO2MikUTXy2oqOfE57rE4L723lCImEIISIiup1GhRFTmT59utHZlOLiYvj7+zf5ftY/073J35OIiIgap1FhxN3dHTKZDDk5OUbLc3Jy4O3tXe823t7ejVofABQKBRQKDoMlIiKyBo1qo5DL5YiMjERycrJhmV6vR3JyMrp3r/8sQ/fu3Y3WB4AdO3bcdH0iIiKyLo1uppk6dSri4uIQFRWF6OhoJCUloaysDGPHjgUAjB49Gn5+fkhMTAQATJkyBb1798b8+fMxePBgrFu3DocOHcKyZcua9pMQERGRRWp0GBk5ciTy8vIwc+ZMZGdno0uXLti+fbuhk2pmZiak0usnXHr06IG1a9fizTffxOuvv47Q0FBs3rwZHTp0aLpPQURERBar0fOMiKG55hkhIiKi5tPQ72/OwkVERESiYhghIiIiUTGMEBERkagYRoiIiEhUDCNEREQkKoYRIiIiEhXDCBEREYmKYYSIiIhExTBCREREomr0dPBiqJ0ktri4WORKiIiIqKFqv7dvN9m7RYSRkpISAIC/v7/IlRAREVFjlZSUwMnJ6aavW8S1afR6PS5dugSVSgWJRNJk71tcXAx/f39kZWVZ7TVveAxq8DjwGAA8BgCPQS0eh6Y5BoIgoKSkBL6+vkYX0b2RRZwZkUqlaNWqVbO9v1qtttpftlo8BjV4HHgMAB4DgMegFo/D3R+DW50RqcUOrERERCQqhhEiIiISlVWHEYVCgYSEBCgUCrFLEQ2PQQ0eBx4DgMcA4DGoxeNg2mNgER1YiYiIqOWy6jMjREREJD6GESIiIhIVwwgRERGJimGEiIiIRGXVYWTJkiUIDAyEUqlETEwMDhw4IHZJJvXrr79iyJAh8PX1hUQiwebNm8UuyaQSExPRtWtXqFQqeHp6YtiwYThz5ozYZZncJ598gk6dOhkmNurevTt++OEHscsSzbx58yCRSPDiiy+KXYpJzZo1CxKJxOjWrl07scsyuYsXL+LJJ5+Em5sb7Ozs0LFjRxw6dEjsskwqMDCwzu+CRCJBfHx8s+3TasPI+vXrMXXqVCQkJODIkSPo3LkzBgwYgNzcXLFLM5mysjJ07twZS5YsEbsUUezevRvx8fH4448/sGPHDlRXV+OBBx5AWVmZ2KWZVKtWrTBv3jwcPnwYhw4dwv3334+hQ4fixIkTYpdmcgcPHsSnn36KTp06iV2KKCIiInD58mXDbc+ePWKXZFJXr15Fz549YWtrix9++AEnT57E/Pnz4eLiInZpJnXw4EGj34MdO3YAAB599NHm26lgpaKjo4X4+HjDc51OJ/j6+gqJiYkiViUeAMK3334rdhmiys3NFQAIu3fvFrsU0bm4uAifffaZ2GWYVElJiRAaGirs2LFD6N27tzBlyhSxSzKphIQEoXPnzmKXIapXX31VuPfee8Uuw+xMmTJFCAkJEfR6fbPtwyrPjGg0Ghw+fBixsbGGZVKpFLGxsdi3b5+IlZGYioqKAACurq4iVyIenU6HdevWoaysDN27dxe7HJOKj4/H4MGDjf5fsDZnz56Fr68vgoOD8cQTTyAzM1Pskkzqf//7H6KiovDoo4/C09MT99xzD5YvXy52WaLSaDRYvXo1nn766Sa9UO2NrDKM5OfnQ6fTwcvLy2i5l5cXsrOzRaqKxKTX6/Hiiy+iZ8+e6NChg9jlmNyxY8fg6OgIhUKBZ599Ft9++y3Cw8PFLstk1q1bhyNHjiAxMVHsUkQTExOD//73v9i+fTs++eQTpKen47777kNJSYnYpZnMuXPn8MknnyA0NBQ//vgjnnvuObzwwgtYtWqV2KWJZvPmzSgsLMSYMWOadT8WcdVeouYWHx+P48ePW10bea2wsDAcPXoURUVF2LhxI+Li4rB7926rCCRZWVmYMmUKduzYAaVSKXY5ohk0aJDhcadOnRATE4OAgAB8/fXXGDdunIiVmY5er0dUVBTeeecdAMA999yD48ePY+nSpYiLixO5OnF8/vnnGDRoEHx9fZt1P1Z5ZsTd3R0ymQw5OTlGy3NycuDt7S1SVSSWyZMnY8uWLdi5cydatWoldjmikMvlaNOmDSIjI5GYmIjOnTtj4cKFYpdlEocPH0Zubi7+9a9/wcbGBjY2Nti9ezc++ugj2NjYQKfTiV2iKJydndG2bVukpqaKXYrJ+Pj41Ang7du3t7rmqloZGRn4+eefMX78+Gbfl1WGEblcjsjISCQnJxuW6fV6JCcnW107uTUTBAGTJ0/Gt99+i19++QVBQUFil2Q29Ho9qqqqxC7DJPr164djx47h6NGjhltUVBSeeOIJHD16FDKZTOwSRVFaWoq0tDT4+PiIXYrJ9OzZs87w/pSUFAQEBIhUkbhWrlwJT09PDB48uNn3ZbXNNFOnTkVcXByioqIQHR2NpKQklJWVYezYsWKXZjKlpaVGf/Wkp6fj6NGjcHV1RevWrUWszDTi4+Oxdu1afPfdd1CpVIb+Qk5OTrCzsxO5OtOZPn06Bg0ahNatW6OkpARr167Frl278OOPP4pdmkmoVKo6/YQcHBzg5uZmVf2Hpk2bhiFDhiAgIACXLl1CQkICZDIZHnvsMbFLM5mXXnoJPXr0wDvvvIMRI0bgwIEDWLZsGZYtWyZ2aSan1+uxcuVKxMXFwcbGBFGh2cbpWIBFixYJrVu3FuRyuRAdHS388ccfYpdkUjt37hQA1LnFxcWJXZpJ1PfZAQgrV64UuzSTevrpp4WAgABBLpcLHh4eQr9+/YSffvpJ7LJEZY1De0eOHCn4+PgIcrlc8PPzE0aOHCmkpqaKXZbJff/990KHDh0EhUIhtGvXTli2bJnYJYnixx9/FAAIZ86cMcn+JIIgCM0feYiIiIjqZ5V9RoiIiMh8MIwQERGRqBhGiIiISFQMI0RERCQqhhEiIiISFcMIERERiYphhIiIiETFMEJEdfTp0wcvvvjiTV8PDAxEUlKSyeohopbNaqeDJ6I7d/DgQTg4OIhdBhG1EAwjRNRoHh4eYpdARC0Im2mIqF5arRaTJ0+Gk5MT3N3dMWPGDNRePeLGZprMzEwMHToUjo6OUKvVGDFiBHJycgyvz5o1C126dMGKFSvQunVrODo6YtKkSdDpdHjvvffg7e0NT09PzJ0716iGBQsWoGPHjnBwcIC/vz8mTZqE0tJSw+sZGRkYMmQIXFxc4ODggIiICGzbtg0AcPXqVTzxxBPw8PCAnZ0dQkNDsXLlymY8YkR0p3hmhIjqtWrVKowbNw4HDhzAoUOHMHHiRLRu3RoTJkwwWk+v1xuCyO7du6HVahEfH4+RI0di165dhvXS0tLwww8/YPv27UhLS8Pw4cNx7tw5tG3bFrt378bevXvx9NNPIzY2FjExMQAAqVSKjz76CEFBQTh37hwmTZqEV155BR9//DGAmisvazQa/Prrr3BwcMDJkyfh6OgIAJgxYwZOnjyJH374Ae7u7khNTUVFRYVpDh4RNY5JLsdHRBald+/eQvv27QW9Xm9Y9uqrrwrt27cXBEEQAgIChA8//FAQBEH46aefBJlMJmRmZhrWPXHihABAOHDggCAIgpCQkCDY29sLxcXFhnUGDBggBAYGCjqdzrAsLCxMSExMvGldGzZsENzc3AzPO3bsKMyaNavedYcMGSKMHTu2EZ+aiMTCZhoiqle3bt0gkUgMz7t3746zZ89Cp9MZrXfq1Cn4+/vD39/fsCw8PBzOzs44deqUYVlgYCBUKpXhuZeXF8LDwyGVSo2W5ebmGp7//PPP6NevH/z8/KBSqfDUU0/hypUrKC8vBwC88MILePvtt9GzZ08kJCTg77//Nmz73HPPYd26dejSpQteeeUV7N27twmOChE1B4YRIjIJW1tbo+cSiaTeZXq9HgBw/vx5PPjgg+jUqRO++eYbHD58GEuWLAEAaDQaAMD48eNx7tw5PPXUUzh27BiioqKwaNEiAMCgQYOQkZGBl156CZcuXUK/fv0wbdq05v6YRHQHGEaIqF779+83ev7HH38gNDQUMpnMaHn79u2RlZWFrKwsw7KTJ0+isLAQ4eHhd7z/w4cPQ6/XY/78+ejWrRvatm2LS5cu1VnP398fzz77LDZt2oSXX34Zy5cvN7zm4eGBuLg4rF69GklJSVi2bNkd10NEzYcdWImoXpmZmZg6dSqeeeYZHDlyBIsWLcL8+fPrrBcbG4uOHTviiSeeQFJSErRaLSZNmoTevXsjKirqjvffpk0bVFdXY9GiRRgyZAh+//13LF261GidF198EYMGDULbtm1x9epV7Ny5E+3btwcAzJw5E5GRkYiIiEBVVRW2bNlieI2IzAvPjBBRvUaPHo2KigpER0cjPj4eU6ZMwcSJE+usJ5FI8N1338HFxQW9evVCbGwsgoODsX79+rvaf+fOnbFgwQK8++676NChA9asWYPExESjdXQ6HeLj49G+fXsMHDgQbdu2NYy0kcvlmD59Ojp16oRevXpBJpNh3bp1d1UTETUPiSBcmziAiIiISAQ8M0JERESiYhghIiIiUTGMEBERkagYRoiIiEhUDCNEREQkKoYRIiIiEhXDCBEREYmKYYSIiIhExTBCREREomIYISIiIlExjBAREZGoGEaIiIhIVP8P2X44ExdVZvUAAAAASUVORK5CYII=", "text/plain": [ "
" ] @@ -7695,10 +9659,10 @@ ], "source": [ "(\n", - " # cr_gp_df[cr_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", - " # esc_gp_df[esc_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", - " cr_gbrt_df[cr_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", - " esc_gbrt_df[esc_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GBRT policy'),\n", + " cr_gp_df[cr_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", + " esc_gp_df[esc_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", + " # cr_gbrt_df[cr_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", + " # esc_gbrt_df[esc_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GBRT policy'),\n", " # msy_gbrt_df[msy_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='MSY GP policy'),\n", ") " ] @@ -7968,7 +9932,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "id": "5163a6f7-e13d-473e-8180-6d686a969004", "metadata": { "scrolled": true @@ -7978,28 +9942,29 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:24:10,322\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-04-26 22:24:21,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-04 00:34:48,975\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-04 00:34:59,419\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-04 00:35:09,675\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], "source": [ "pol_env = AsmEnv(config=CONFIG)\n", "\n", - "# msy_rews = eval_pol(\n", - "# policy=Msy(env=pol_env, **msy_gbrt_args), \n", - "# env_cls=AsmEnv, config=CONFIG, \n", - "# n_batches=5, batch_size=70\n", - "# )\n", + "msy_rews = eval_pol(\n", + " policy=Msy(env=pol_env, **msy_gp_args), \n", + " env_cls=AsmEnv, config=CONFIG, \n", + " n_batches=1, batch_size=200\n", + ")\n", "\n", "esc_rews = eval_pol(\n", - " policy=ConstEsc(env=pol_env, **esc_gbrt_args), \n", + " policy=ConstEsc(env=pol_env, **esc_gp_args), \n", " env_cls=AsmEnv, config=CONFIG, \n", " n_batches=1, batch_size=200\n", ")\n", "\n", "cr_rews = eval_pol(\n", - " policy=CautionaryRule(env=pol_env, **cr_gbrt_args), \n", + " policy=CautionaryRule(env=pol_env, **cr_gp_args), \n", " env_cls=AsmEnv, config=CONFIG, \n", " n_batches=1, batch_size=200\n", ")" @@ -8007,13 +9972,13 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "id": "56a537f8-545d-4ef9-9671-d0906464400c", "metadata": {}, "outputs": [ { "data": { - "image/png": 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bbUydOjXYUJIkSVIT1TA+JUiSpBopKyvj+9//Pvn5+cSEQtx37VVkNG8edKxdpCYn8eAN3yIhNpbi4uJd1imUJEmSVH8sACVJaoQefPBBPvnkE6Bi443Du3UNONGe9e3Qgd9ddD4AK1as4JZbbnE9QEmSJKmeWQBKktTIzJ8/nz/96U8A9GqXzS2nnxpwon27eOgQzjuyYlOQCRMm8OyzzwacSJIkSWpaLAAlSWpEIpEIP/3pTykqKiI2JoZ7rrqchLi4oGPtUygU4ncXnUf7jAwAfvnLX7Js2bKAU0mSJElNhwWgJEmNyJgxY/jggw8AuP7E4+jToX3AiaqnRWIif7v6CkKhEHl5edx0002UlZUFHUuSJElqEiwAJUlqJHJzc/nNb34DQPuMDL5/6skBJ6qZI3p048YTjwfg008/5T//+U/AiSRJkqSmwQJQkqRG4o9//CMbNmwA4LcXnkdSQkLAiWrultNPpUdWWwDuvPNOVq5cGXAiSZIkKfpZAEqS1AjMmzePxx9/HIAT+vXlxAH9gg10gBLi4vjz5ZcQCoXIz8/nJz/5ibsCS5IkSXXMAlCSpEbgd7/7HeXl5cSFw9x+/jlBx/lGBnXtwpUjjgbgrbfe4qWXXgo4kSRJkhTdLAAlSWrg3nvvPd58800ArhxxNJ1bZwac6Jv76Vmnk5WeBsDtt9/Otm3bgg0kSZIkRTELQEmSGrDy8vKqjT9SEhMb3cYfe9O8WTN+e+F5AKxfv56//vWvASeSJEmSopcFoCRJDdhLL73EjBkzAPjeqSeR3jw54ES15+QB/RnW6yAAHnroIRYsWBBwIkmSJCk6WQBKktRAlZaWctdddwHQLiOdq44ZHnCi2hUKhfjthecRGxNDaWkpt912mxuCSJIkSXXAAlCSpAZqzJgxLF68GIAfnHYKzeLiAk5U+3pkteXqY0cA8L///Y///ve/ASeSJEmSoo8FoCRJDVBJSUnVungdW7XkvMFHBJyo7tw88hQyU1oA8Ktf/YrCwsKAE0mSJEnRxQJQkqQG6Pnnn2fp0qVAxei/uHA42EB1KCUxkZ+dfSYAy5Yt47HHHgs4kSRJkhRdLAAlSWpgSkpKuOeeewDonJnJOUccFnCiunfekYfTu307AP72t7+Rm5sbcCJJkiQpelgASpLUwIwbN47ly5cD8IPTTiY2ikf/VYqJieEX51SMAszJyeG+++4LOJEkSZIUPSwAJUlqQCKRCA888ABQsfPvmYcPCjhR/Tn64F4MPagnAA8//DBr1qwJOJEkSZIUHSwAJUlqQCZNmsSsWbMAuO7446J67b+vC4VCVaMACwsL+fOf/xxwIkmSJCk6WABKktSAVI7+S0tO4qKhgwNOU//6derImYdVjHp89tlnmTdvXsCJJEmSpMbPAlCSpAZiypQpvP/++wBcOeJokhISAk4UjJ+cOZK4cJjy8nL+9Kc/BR1HkiRJavQsACVJaiDuv/9+ABLi4rj6mOEBpwlOx8xWXDLsKABee+01ZsyYEXAiSZIkqXGzAJQkqQFYvHgxr776KgAXDjmSli1aBJwoWN895UQSYmMB+Mtf/hJwGkmSJKlxswCUJKkB+Pe//00kEiEmFOK6E44NOk7g2qalcenRQwF4/fXXmTZtWsCJJEmSpMbLAlCSpIBt376d0aNHA3DSgP50yswMOFHD8J2TTyAhLg6Au+66K+A0kiRJUuNlAShJUsCef/55tm/fDsBVxxwdcJqGo01qKpfvGAU4ceJEpkyZEnAiSZIkqXGyAJQkKUCRSIT//Oc/APTIasuQnj0CTtSw3HjSCTTbMQrwz3/+c8BpJEmSpMbJAlCSpAC99957zJ8/H4CrRhxNKBQKOFHD0jo1hStGVIyKfPvtt10LUJIkSToAFoCSJAWocvRfi2bNOPfIIwJO0zBdf8JxVTsC33vvvQGnkSRJkhofC0BJkgKyYsUK3njjDQDOH3Ikyc0SAk7UMLVOTeGCowYD8Oqrr7JgwYKAE0mSJEmNiwWgJEkBefzxxykvLwfgiuHDAk7TsN1w4vGEY2KIRCLcf//9QceRJEmSGhULQEmSAlBcXMwzzzwDwPCDe9GtbZuAEzVsHVu15MzDDgXghRdeYOXKlQEnkiRJkhoPC0BJkgLwxhtvsHHjRgAuPXpowGkah5tOPhGA0tJS/vnPfwacRpIkSWo8LAAlSQrA008/DUCrFi04oX/fgNM0Dj2zszh5QH+g4vevskCVJEmStG8WgJIk1bMVK1bwzjvvAHD+kCOIC4eDDdSI3HRKxSjAgoICHn744YDTSJIkSY2DBaAkSfXs2WefJRKJAHDRUUMCTtO4HNK5E0MP6gnAf/7zH7Zu3RpwIkmSJKnhswCUJKkelZWVVW3+cWSPbnRt0zrgRI1P5SjArVu3Vk2lliRJkrR3FoCSJNWjd955h1WrVgFw8VBH/x2IoQf1pE+H9gA8/PDDlJSUBJxIkiRJatgsACVJqkejRo0CoEWzZpw68JBgwzRSoVCI6044FoBVq1bxyiuvBJxIkiRJatgsACVJqicbNmzgjTfeAOCsIw4jMT4+4ESN1+mDDiUrPQ2Af/3rX1VrKkqSJEnanQWgJEn15MUXX6yarnrxUYMDTtO4xYXDXH3MCACmTp3KRx99FHAiSZIkqeGyAJQkqZ688MILAByUnUXfjh0CTtP4XTJsCMkJCUDFKEBJkiRJe2YBKElSPZg3bx7Tp08H4NwjDycUCgWcqPFLTUqq2kjlv//9L4sWLQo4kSRJktQwWQBKklQPnn/+eaBiA4uzDh8UcJrocc1xI4gJhYhEIjz44INBx5EkSZIaJAtASZLqWHl5OWPGjAFg6EE9yUpPDzhR9OjQsiWnDhwAwOjRo9m0aVPAiSRJkqSGxwJQkqQ69sEHH7B69WqgYvqvatd1JxwHQGFhIY8//niwYSRJkqQGyAJQkqQ6Vjn9NzE+nlMOGRBwmugzsEtnBnXtAsDjjz9etdOyJEmSpAoWgJIk1aH8/HxeeeUVAE4+pD/JzRICThSdrjl2BABr167l1VdfDTiNJEmS1LDEBh1AjUM4HI7Kc6l2Vf7s/BlGD3+W39zEiRPJy8sD4Lwjj6jX3X8rz9UUdhw+9dBDaDMmlXW5uTzyyCOcf/75QUeqE16TjZfvkdHHn2Xj5jUZffxZSvsWikQikaBDSJIUrUaOHMmECRNok5bKl3f/H7H+5bTO/O2V1/i/seMA+Pzzzxk0yN2WJUmSJHAEoKopJyenTo+fkpJCOBymrKyMrVu31um5VHfC4TApKSls3bqVsrKyoOPoAHk91p7NmzczceJEAE4/dCBlpaWUlZbW2/lDoRDx8fEUFxfTFL7vu2jIkfxt/GsUlZby17/+lX/84x9BR6oVXpPRwffI6OD1GD28JqNDXV+T6enptX5MKSgWgKqW+nxT9A248SsrK/PnGCX8OX4z48ePp3RH4XfGYYcGVsJFIpEmUQBmNG/OGYcdypiPP+XFF1/k9ttvJzMzM+hYtcprsvHzPTJ6+HOMDl6T0cOfo7RvbgIiSVIdGTeuYjpq+5YZHNK5U8BpmoarjxkOQHFxMU8++WTAaSRJkqSGwQJQkqQ6sH79et577z0Azhh0aJPYiKMh6NepI4d16wrA448/TklJScCJJEmSpOBZAEqSVAdeffVVysvLATj9sIEBp2laKkcBrl27lldffTXgNJIkSVLwLAAlSaoDL7/8MgBdWmfSp337YMM0MacMHECb1FQA/v3vfwecRpIkSQqeBaAkSbVszZo1fPzxxwCc7vTfehcXDnPFiGEAfPbZZ0ybNi3gRJIkSVKwLAAlSapl48aNq9p198zDDg04TdN0ydCjiI8NA44ClCRJkiwAJUmqZZW7//bMyqJndlbAaZqmViktOGPQIKDi57F58+aAE0mSJEnBsQCUJKkWrVixgs8//xxw84+gVU4DLiwsZPTo0QGnkSRJkoJjAShJUi2qHP0HcMYgp/8G6ZDOnejToWIDlscff7xqV2ZJkiSpqbEAlCSpFr300ksA9OnQnq5tWgecpmkLhUJcMbxiFOCSJUuYPHlywIkkSZKkYFgASpJUS5YuXcr06dMBOH2Q038bgrMOH0RKYiJQMQpQkiRJaoosACVJqiUTJkyoun3qwAEBJlGlpIQEzht8BABvvPEGq1atCjiRJEmSVP8sACVJqiWvvvoqAL3aZdOltdN/G4rLjh4KQHl5OU899VTAaSRJkqT6ZwEoSVItWLt2LZ999hkApxzSP+A02lmPrLYM6dkDgKeeeoqSkpKAE0mSJEn1ywJQkqRa8Prrr1fdPuUQp/82NJWbgaxfv36XqdqSJElSU2ABKElSLXjttdcA6JTZil7tsgNOo6876ZD+ZKakAPDYY48FnEaSJEmqXxaAkiR9Qzk5OXzwwQdAxei/UCgUcCJ9XVw4zCXDhgDwwQcfMH/+/IATSZIkSfXHAlCSpG9o4sSJlJaWAq7/15BdOuwowjEVf/VxFKAkSZKaEgtASZK+ocrpv21SUzmkc6eA02hvstLTOaFfXwCee+458vLyAk4kSZIk1Q8LQEmSvoHt27fzv//9D4CTD+lPTIxvrQ3ZFSMqNgPZtm0bY8eODTiNJEmSVD/8lCJJ0jcwadIkCgsLAXf/bQyGHtSTzpmZADz66KNEIpGAE0mSJEl1zwJQkqRvoHL6b1pyEkf26BZwGu1PTEwMlw8fCsDMmTP54osvAk4kSZIk1T0LQEmSDlBRURETJ04E4MT+/YgNhwNOpOq4YMiRJMTFAW4GIkmSpKbBAlCSpAP03nvvsX37dgBOHXhIsGFUbWnJyZwxaCAA48aNIycnJ+BEkiRJUt2yAJQk6QD997//BSAxPp6hvXoGnEY1cfnwis1AioqKeO655wJOI0mSJNUtC0BJkg5AJBLhjTfeAGB471402zGlVI3DIZ070bt9OwAef/xxNwORJElSVLMAlCTpAEyfPp21a9cCFev/qXEJhUJVowAXLVrE+++/H3AiSZIkqe5YAEqSdAAqp/+GQiGO7dM74DQ6EGcdPojmzRKAilGAkiRJUrSyAJQk6QBUTv89tEtnWqW0CDiNDkTzZs04+4jDAZgwYULViE5JkiQp2lgASpJUQ6tWrWLGjBkAnNi/b8Bp9E1cfvRQAEpLS3nmmWcCTiNJkiTVDQtASZJqaOLEiVW3T3D9v0bt4PbtGNS1CwBPPfUUZWVlASeSJEmSap8FoCRJNVQ5/bdTZiu6t20TcBp9U5cPrxgFuHLlSt5+++2A00iSJEm1zwJQkqQa2L59e9WOsSf070soFAo4kb6p0w4dSFpyEuBmIJIkSYpOFoCSJNXA//73P4qLiwE40em/UaFZXBwXDBkMwFtvvcWKFSsCTiRJkiTVLgtASZJq4L///S8AKYmJHNata8BpVFsuHXYUAJFIhCeffDLgNJIkSVLtsgCUJKmaysrKePPNNwE4tm9v4sLhgBOptnRt05qhB/UEYNSoUVWjPCVJkqRoYAEoSVI1ffbZZ2zevBlw+m80unz4MAA2bNjA66+/HnAaSZIkqfZYAEqSVE0TJ04EIDYmhhF9Dg44jWrbiQP6kZmSArgZiCRJkqKLBaAkSdX0xhtvAHBkj+6kJCYGnEa1LS4c5uKhQwB4//33WbBgQcCJJEmSpNphAShJUjUsWrSoqhBy+m/0umTYEGJCIQA3A5EkSVLUsACUJKkaKjf/ADi+f98Ak6gutcvI4Li+fQAYPXo0BQUFASeSJEmSvjkLQEmSquGtt94CoEdWWzq2ahlwGtWly4YPBWDLli2MGzcu4DSSJEnSN2cBKEnSfmzfvp0PP/wQgGP79A44jeraiN4H075lBgBPPPFEwGkkSZKkb84CUJKk/XjvvfcoKSkB4Lh+fQJOo7oWjonh0mFHAfD5558zY8aMgBNJkiRJ34wFoCRJ+1G5/l/zZgkc1q1rwGlUHy48ajBx4TDgKEBJkiQ1fhaAkiTtQyQSqVr/7+iDe1WVQopumSkpnHLIAADGjBnD9u3bA04kSZIkHTgLQEmS9mH27NmsWbMGgGP7uv5fU1K5GUheXh5jxowJOI0kSZJ04CwAJUnah8rRfwDH9LYAbEoG9+hOt7ZtAHj88ceJRCIBJ5IkSZIOjAWgJEn7UFkA9unQnjZpqQGnUX0KhUJcfnTFKMBZs2bx+eefB5xIkiRJOjAWgJIk7cWWLVv47LPPADi2j6P/mqLzjjyChLg4oGIUoCRJktQYWQBKkrQX77zzDmVlZYDr/zVVqclJnHnYoQCMGzeOzZs3B5xIkiRJqjkLQEmS9qJy+m9achIDu3QONowCc9mOacBFRUU899xzAaeRJEmSas4CUJKkPSgvL2fSpEkADD/4YMIxvmU2VYd07kSfDu0BNwORJElS4+SnGUmS9mD69Ols2LABcPpvU7fzZiCLFy/mvffeCziRJEmSVDMWgJIk7UHl9N9QKMSI3r0CTqOgnXX4YTRvlgC4GYgkSZIaHwtASZL2oLIAPKRTR1q2aBFwGgUtuVkC5xxxOACvv/46a9euDTiRJEmSVH0WgJIkfc3GjRv58ssvAaf/6iuVm4GUlpYyatSogNNIkiRJ1WcBKEnS10yaNKlqo4dj+/YJOI0aioPbt2NQ1y4APPXUU5SVlQWcSJIkSaoeC0BJkr6mcvpvqxYt6Ltj91cJ4PLhwwBYtWoVb7/9dsBpJEmSpOqxAJQkaSelpaX873//A+CYPgcTE+Nbpb5y2qGHkJacBMBjjz0WcBpJkiSpevxUI0nSTr744gu2bNkCuP6fdtcsLo4LhgwG4O2332b58uUBJ5IkSZL2zwJQkqSdVE7rjAmFOLpXr4DTqCG67OijAIhEIjz11FMBp5EkSZL2zwJQkqSdVE7/HdilM6k7pnpKO+vSujXDeh0EwKhRoyguLg44kSRJkrRvFoCSJO2wceNGpk2bBsCIPgcHnEYN2WVHDwVgw4YNTJgwIeA0kiRJ0r5ZAEqStMPkyZOJRCIAjOhtAai9O3FAP1qnpgDwxBNPBJxGkiRJ2jcLQEmSdpg0aRIAaclJ9OvYIeA0asjiwmEuHjoEgPfff58FCxYEnEiSJEnaOwtASZKA8vLyqvX/hh/ci3CMb5Hat0uGHkVMKAQ4ClCSJEkNm59uJEkCZs2axYYNGwAY7vRfVUN2RjrH9+sDwOjRoykoKAg4kSRJkrRnFoCSJPHV7r9QMQJQqo7Ljh4GQG5uLuPGjQs4jSRJkrRnFoCSJPFVAXhwu2zapKUGnEaNxfDevWjfMgOAxx9/PNgwkiRJ0l7EBh1AkqSgbd++nU8++QRw+m9jFolE2Lx9Ozl5+WwvLGR7YSGFxcVEIhAKQSgUIiEujtTERFokJpKenExKUiKhHev4HYhwTAyXHT2UP7/8Cl988QXTp0+nf//+tfiqJEmSpG/OAlCS1OR98MEHlJSUABUjutRwlZWXs3zjRhasWcv81WtZuHYtq3NyWJOzhXVbcikqLa3R8ZIS4mmXkUF2ejrd27ahV7tserXLpmdWW5rFx1frGBcMOZJ7XplASVkZTz75JHffffeBvDRJkiSpzlgASpKavEmTJgGQGB/P4d26BpxGO1uTk8OXS5by5eKlTFmylJkrVlK0o6ytDflFxSxYs5YFa9Yyefacql+PjYmhX8cOHN69G0d078bgnt1pkZi4x2NkpqRwyiEDeOWLL3nhhRf4zW9+Q4sWLWotoyRJkvRNWQBKkpq8ygJwSM8eJMTFBZymaVuTk8P7c+fz/tx5fLJgIWtytuz1saFQiIysLFplZZPaqhWprVqR1iqT5mlpJCQlkZCYREKzZoRiQkQiEYhAcVEhBdu3U5iXx/bcXHLWr2fL+vVsXreGtUuXUZifB0BpeTlTli5jytJlPPzWJOLCYY7o3o3j+vXhxP596ZSZuUuWy4cP5ZUvviQ/P58xY8ZwzTXX1OVvkyRJklQjFoCSpCZtyZIlLF26FHD6bxAKS0r4aN4C3pk1m/fmzmPR2nV7fFxcQgIdeh5Ep4MPJrtLV9p27kxm+w7EJyTUWpZIJELO+vWsWbyIZXPnsmTWTJbNnUNpcTElZWV8MG8+H8ybzx/GvMQhnTtx1uGDGDloIG1SUzmyR3e6tW3DorXrePzxx7n66qu/0dqCkiRJUm2yAJQkNWmVu/8CHNPHDUDqw+bt25k0YxZvTp/Ju3PmkF9UvNtjmqel0WPgoXTp04fOB/cmq0tXwrF1+9eWUChERps2ZLRpQ58hRwFQWlzM0rlzmPPpJ8z+5GPWLVsGwNSly5i6dBl/GPMSx/XtwxUjhnHZsKP4/ZiXmD17Np999hlHHHFEneaVJEmSqssCUJLUpFVO/+3QsiWdvzatU7Vnyfr1vDl9Jm9Om8HnixZTHonscn98QjO69u9Pz4GH0nPQILI6d2kQI+hi4+Pp3n8A3fsP4IxvX8/G1auZOvkdvpz0NmuXLaU8EuGtGTN5a8ZM2rfMIDYmhtLycp544gkLQEmSJDUYFoCSpCaruLiY999/H4ARvXs1iMIpWkQiEeasWs3rU6byxpTpzF+zZrfHpGS0pM+QIfQdchTdDxlIXDV33Q1Sq+xsTrjkUk645FJWL1nMp2+8wWdv/peC7dtZuWlz1eNefPFFvvvd79K7d+8A00qSJEkVLAAlSU3WZ599Rl5exaYPI5z++42V79g4440p03hj6jSWb9y022Oyunal7+Cj6DNkCO179CQmJiaApLUju0tXzv7OTZx2zbeY8s7/+PDVV1gxfx4AZWVlHHfccVx88cV8//vfp1u3bgGnlSRJUlNmAShJarLefvttAGJjYhjSs0fAaRqn0rIyPlmwiDemTuO/U6ezLjd3l/tDoRBd+vSl39Bh9D1qKC2zsgJKWnfimzXjyFNO5chTTmXxrFmMfvhBNs6ZTVlZGaNGjWL06NFcfPHF/OQnP6Fdu3ZBx5UkSVITZAEoSWqyKjcAOaxbV1okJgacpvEoLCnhw3nzeX3KNN6cNoOcHaMoK8WEw/Q4ZCD9hg6j39ChtEjPCChp/evapw8X33Y7k957n7UfvEfO7JlVReCYMWO45ppruPnmm2nVqlXQUSVJktSEWABKkpqkdevWMXPmTACG9+4VcJqGb01ODv+bOZu3Z8zig3nzKSjedefe2Ph4eg06jH7DjqbP4CEktWgRUNLgdWrVivT27Uk69wKaX3Ah2z7/lC9eGU9RUREPPvggTz/9NLfccgs33HADCQkJQceVJElSE2ABKElqkt55552q28N7u/7f15WWlTFt2XImzZjFpJmzmL1y1W6PSUhMpPeRg+k/7Gh6HX4ECY6iBCAcE0P3tm2ZtWIl28sinPWbP3D8dTfy6j1/YfY7/2P79u384Q9/4Omnn+aOO+7gxBNPdAMaSZIk1SkLQElSkzRp0iQAMpo3p1Xz5izfuInYmBhiw2HiwmHiYsMkxcc36k0qaqK8vJzZq1bx4bwFfDRvAZ8uXMj2wqLdHpfRpi0HH3kkvY84stHs3BuEHlltmb1yJZEIzJk7hyGDh3DjI4+z8NNPGHvn71k5ayZLlizhsssu47jjjuOOO+6gRw/XoZQkSVLdsACUJEWt0tJSFi5cyNy5c5k7dy4LFixgzZo1rFu3juXLlwOweft2Bt/2mz0+PxQKkZqUSFpSMmnJSaQlJ5OZ0oK2aWlkpafRNi2NtmmpZKWnkZ6c3KhGcW3Jy2Pq0mVMXbKMKUuXMWXJUnLz83d7XExMDJ379KX3kUfS+4jBtOnUqVG9zqAkxcfTsVUrlm3YyOJFizl04KEkJCTQ/YgjuXXseD5+4Xle+etd5OVsZtKkSQwfPpzvfve7/PjHPybRkZSSJEmqZRaAkqSoEYlEmDZtGu+99x7vv/8+n3zyCXlf26CipsfbkpfPlrx82LDvxybExVWVgdnp6WTtKAmzM9Jpm1bxa2nJSfVenhWXljJv1WrmrV7DgjVrmb9mDXNWrmbphr2/oDYdO9J9wCF0P2Qg3QccQnJKSj0mjh49s7NYtmEjZWVlLFy4kD59+gAVm6QcdfElHHLaabxx3728+/QTlJaWcu+99zJu3Dj++te/Mnz48IDTS5IkKZpYAEqSGr1p06YxZswYXnnlFVat2n2tOoBwXBytu3QlPTub0nAs24pLiE1M5NCe3UlOSiYcG0t5eTnlpaWUlZVSVlJKQV4e+du2kb9tK/lbt5K3bSvbNuewZeMGSr+2CUZRSQnLNmxk2YaNe83ZLC6OrPQ0stLTyU5Po01aGuk7RhamJiWSmpREalISKYmJJMTFEhcbWzEdORwmHBNDWXk5xaWllJSWUVRaSnFpKbn5+eTk5bElL4+c7Xmsy93K6s05rMrZzKrNOazJyaG0rHyvmWJiYsjq0pWOvXrRtV9/egw4hJSWLQ/sB6FdtGrRgozmzdm8fTtz587l4N4HExP6akp5Ukoq5/7q1xx18SU8d/svWfTZpyxdupTzzjuPiy66iN/97ne09GchSZKkWmABKElqlAoKChgzZgxPPPEE06ZN2+3+tt170GPwELodfgTZB/Uis1NnwnFxALzxxhusX7+e9ORkRgwcUONzRyIR8rdtZcuGjeRu3MCWDRX/5G7cwJaNG9myYT1bNmygpGjXNfQKS0pYsn4DS9bvZzhhHQnHxpLZvgNtO3WiQ8+D6NSrF+179CS+WbNA8kS7EHBQdhYfzV9AXl4eK1asoFPHTrs9rm33Hnx/1HN8/MJzjPvzHynYupXnnnuOt956iz/96U9cc8019R9ekiRJUcUCUJLUqOTl5fHEE0/wj3/8g/Xr11f9ekxsLAcdNZRDTh1Jn2OPI6VV5h6fX1xSzIYd01+z09MOKEMoFCI5JZXklFTadeu2x8dUlITbvioGN2yoKgYrfy134yaKiwoPKMPexMbFkd66NWmt25Depg0t27aldYeOtO3UiVbZ7QjH+tZfnzq2asmUJUspLClh7py5eywAoWIk5lEXXULf445n7B2/58vXXmHTpk1cf/31TJw4kX/961+kp6fXc3pJkiRFCz8FSJIahbKyMp555hn+9Kc/VRV4AK06dmLoJZdyxLkX0KIa0yXXrllLJBIBICuj7gqVipIwheSUlL2WhAClxcXkb99OwfZtO6Ybb6Ng+3bKSkt3+yccGyYcF09sXByxsbHExsXRLDmZpJTUqnM123kzklCIcDiGsrJy2PGaVb/CMTH0yGrDjOUrWbduHZs3byYjI2Ovj0/JbM3V9z7A4eecy+jbfkHuurWMGTOGd999l4ceeohhw4bVY3pJkiRFiyZVAObm5jJmzBg+/fRTNm3aREJCAt26deO0005j8ODBB3zc0tJSXn31VSZPnszq1asBaNeuHSNGjGDkyJHE7me0xeLFi3nppZeYMWMGW7duJTU1lb59+3LuuefSpUuXfT53wYIFjBs3jtmzZ7NlyxaSk5Pp2rUrp5xyCkOGDDng1yRJDcnHH3/Mz3/+c2bNmlX1a+179+Hk7/2AfiecRExMzD6evavKP6djwzG0atGi1rPWVGx8PCkZGaTsoxRS49a9bRazVqyiPBJh7ty5HHXUUft9Tp9jjuMXr0/kxd//ls9eHsv69es555xzuOiii7jzzjtJTU2t++CSJEmKGqFIpGkMCVi+fDm33XYbubm5ACQmJlJUVER5ecXC6GeccQbXXXddjY9bUFDA7bffzvz58wGIj48HoHjH4vC9evXi97//Pc32sr7S5MmTuffeeyktLQUgOTm5asfK2NhYbrnlFo4++ug9Pvell17iiSeeoLy8vGKkSXIyBQUFlJWVAXDCCSfw/e9/v1Z2nNy4ce+L2teG9PR0wuEwZWVl5OTk1Om5VHfC4TDp6enk5ORU/X+oxqchXY95eXnceeedPPLII1Wj9jI7d+Gsn/2SfieceEB/vr344ovk5eXRvmUGww/uVduRGxZHADYYH86bz9INGwmHw5x3/nk0S6j+uouzJ73NqF/8hG2bNgGQnZ3N/fff707BjYzvkdGhIb1H6pvxmowOdX1NtmrVqtaPKQWl+kMmGrGSkhLuuOMOcnNz6dSpE/feey/PPfcczz33HJdffjmhUIhXXnmFt956q8bH/uc//8n8+fNJTk7mF7/4BS+88AIvvPACv/jFL0hOTmbu3Ln861//2uNzly9fXlX+DRs2jMcff5xnn32Wxx9/nKFDh1JaWsrf//53Vq5cudtzP/vsMx577DHKy8s55phjeOyxx3jmmWcYPXo0119/PbGxsbz11luMHTu2xq9JkhqCL7/8kmOOOYZ///vfRCIREpKTOfsXv+IXEybS/8STDqj827p1a9WXLFlpabWcWNq7g9plAxVT2RfMX1Cj5w489TR+O+ldBp46EqgYxXr++efz+9//npKSklrPKkmSpOjTJArA//73v6xdu5aEhAR+/etfV02rTUhI4MILL+TUU08F4Omnn64aiVcdS5Ys4d133wXg+9//PkOGDCEUChEKhRgyZAjf+973AHjnnXdYtmzZbs8fNWoUpaWldOnShR//+MdVawJlZGRw66230qVLF0pKShg1atQenwvQo0cPbrnllqrnJiQkcPrpp3P++ecD8Pzzz7N9+/ZqvyZJClokEuGhhx7i9NNPZ+nSpQD0GjacX0yYyHHXXkfsjpHWB2LV6lVVt7MOcAMQ6UC0bN6cli2aAzBv3ryqGQjV1aJlK2546BGu+Ovfada8BZFIhPvvv5/TTz+dJUuW1EVkSZIkRZEmUQC+8847AAwfPpzMzN13hTzvvPMIhUJs3ryZGTNmVPu4kydPJhKJkJWVtcf19o466iiysrKIRCJMnjx5l/vy8vL47LPPADj77LMJh8O73B8Ohzn77LMB+PTTT8nPz6+6Lycnh8WLFwNw1lln7XEUzNlnn00oFKKgoICPPvqo2q9JkoKUn5/Ptddey69+9StKSkqIS0jgoj/8ke889iQZ7dp/4+NXrv/XvFkzmu9laQaprhyUXTEKMD8/n+XLl9f4+aFQiMPPOoefvTKBzgMPBSpGyh533HG88MILtZpVkiRJ0SXqC8CCggIWLKiYanPooYfu8TGZmZm0b1/xwXLatGnVPvb06dMBGDhw4B5LuFAoxMCBA3d5bKXZs2dXjTbcW67KXy8pKWHOnDlVv75+/fqq25W5vy4pKalqVODUqVOr83IkKVBr167lzDPP5JVXXgGgdZeu/OjFcQy95LJaWcu0rKyMdWvXAY7+UzA6tGpJ4o4RrLNnzz7g47Ts0JGbn32Bk79bsc7v9u3buemmm7jpppsc9S9JkqQ9ivoCcOXKlVULx3fq1Gmvj6u8b8WKFdU6biQSqVqbb1/H7dix4x6PW/nfaWlpe93JLzU1teq+nUcK7PxBeF9TiCoXsz2QUQaSVJ/mzJnDySefXPUlTN/jTuDWl16hXa+Da+0cGzZsqPrixQJQQQiHQvTMzgIqNtfa+Qu9Gh8rNpaRt9zK954eTVrbimO+8MILnHDCCbt8aShJkiQBxAYdoK5t3ry56nbliLg9qbyvujsHFRQUUFhYWO3jFhQUUFBQQGJi4i7n2ddzK+/Pzc3dJdfO05iXL19O9+7dd3ve1q1b2bJlC7Dr78HePP300zzzzDN7vf+SSy7h0ksv3e9xDlRMTEzVv9PT0+vsPKpbleV0amoqTWSD8ahU39fjZ599xtlnn131Z9UJ193Aebf9mpivLY3wTa1bVzH6LxSC7IyM3ZZeiGbhmKj/vq/ROKhdNjOXr6CsvJy5c+fSoUOH/T6n8s/WUChEQkLCLvf1HT6CX0+cxJM//TFT35jAokWLOPnkk/nXv/7F5ZdfXievQQfG98jo4N9Zo4fXZHTwmpSqL+oLwMqSDtjtL807q7yvoKCgWsfd+XHVOW7lcyoLwMrn7+u5e8uVnp5Oly5dWLJkCWPHjmXEiBG7fZAdM2bMHrPuTV5e3j5HIuTn59fLh+VQKNSkPpRHqxjLhqhQH9fju+++y+mnn862bdsAuOSOP3Hs1d+qk3NVjtrOTEkhLraJ/TnzzWdQq5YkxMXSPast81atZunSpWzbto2UlJRqP39P0+GbZ2TwnX8/ytv/eZgxd/yegoICrr76aj766CP+/ve/08z1LhsU3yOjg39njR5ek9HBa1Lav6gvAKPVxRdfzJ/+9CeWL1/OnXfeyRVXXEGHDh3Izc3ljTfeYPz48cTGxlJaWlqtN7Xk5GRat2691/uTkpKqphTXhZiYGEKhEJFIpMY7I6rhCIVCxMTEUF5e7jepjVh9XY/vv/8+p512Gvn5+cSEw1z1178z+LwL6uT/nfyCAjZt2gRAdkY6NKX/PUM0rdfbCBzcrh3zVlVsSDNjxgyOOuqofT5+59JvX9fH8ddeT+cBA3n4O9ezZe0aHnroIT777DOee+45unTpUjvhdcB8j4wO/p01enhNRoe6viYtFRVNor4A3Plb76KiIpKSkvb4uKKiIoCqEXr7s/PjKp+7r+N+/TmVt/f13H3lGjJkCJdffjmjRo3i888/5/PPP9/l/u7du9O9e3feeOMNkpOT9/Nq4PLLL9/nVKGNGzdWe3r0gUhPTyccDlNeXl6n51HdCofDpKenk5ubW6eFsepWfVyPU6dO5dxzz60YXRwXx9X3PsCAk07Z75+JB2rZ0qVVt9umpjad/z9DIcLhGMrKy8EPNw1GUnwc7VtmsHLTZubNm0ffvn33O5ug8sPN/q6R9v3685Nxr/Lkj25m3gfv8+WXX3LYYYfxr3/9ixNPPLG2X4pqwPfI6ODfWaOH12R0qOtrslWrVrV+TCkoUT/eeec19va1Fl7lfdVdNyAxMbGqlKvOcXd+/M659rc+375yXXjhhdx9992ccMIJdOrUiczMTHr16sU111zDn//856oPCdnZ2dV6TZJUH+bOncuFF17Itm3bCMXEcOU99zLgpFPq9JyrV1eMtkqIiyW9+f6/FJHq2sHt2gFQWlrK/Pnza/XYLVq24juPPsnJ3/sBALm5uVx22WXcd999jnKRJElqoqJ+BGD79u2rvjVfvnw57du33+PjKnfKrc5i3FAxZLx9+/YsWLBgn7vs7u24lf+9ZcsWtm7dusf1f3Jzc8nNzQW+2k3463r06EGPHj32eN/ixYsB6NWr135ejSTVj7Vr13LxxRdXfUN72Z//ysBTR9bpOSORSFUB2DYtjZAL4qkBaJXSgpYtmrNp23bmzp1L7z59anWzlphwmJE//DFdBh7KEz/8AQXbtvKHP/yBWbNm8be//W2vMyIkSZIUnaJ+BGBiYmJVQfbll1/u8TEbN25kxYoVAAwYMKDax+7fvz8AU6ZM2etjpk6dustjK/Xu3ZvY2Nh95qo8blxcHAcffHC1cwEsXbqUZcuWAXDMMcfU6LmSVBe2b9/OJZdcwqpVqwA4/9e/44hzzq3z8+bk5FRtCJWVnlbn55OqI8RXowALCgpYumRJnZyn94hj+fHYcbTp1g2AsWPHcsYZZ1Rdh5IkSWoaor4AhK8KsHfffZcNGzbsdv/YsWOJRCJkZGTQr1+/ah93+PDhhEIhVq9ezUcffbTb/R9++CGrV68mFArtVsIlJSVx+OGHAzBu3Ljd1p0oKytj3LhxABxxxBE1+qa+pKSEBx98sOq5nTp1qvZzJakulJWVcd111zFz5kwAjvv29Qy/8up6OXfl6D+ArLS0ejmnVB3tW2aQvGPtv9mzZ9fZeVp36cqPxrxMn2OPA2D69OmceOKJfPLJJ3V2TkmSJDUsTaIAPPnkk2nbti2FhYX84Q9/YMmOb9mLiooYM2YMr732GlCxEUblqLxK3/72tznzzDP5+9//vttxu3TpwvDhwwG4//77+fjjj4lEIkQiET7++GMeeOABoKKA3NMU3ssuu4zY2FgWLVrEPffcUzUlLicnh3vuuYdFixYRFxfHZZddtttzc3JyePzxx1mwYAHFxcVAxQfs6dOn84tf/ILZs2eTnp7Od77znQP8XZOk2vOnP/2Jt956C4BDTjmNM3/6i3o7d2UBmJacRGJ8fL2dV9qfmFCIXu0q1unNyclhzZo1dXauxBYpXPfgI5x443cB2LBhA+eccw7PPPNMnZ1TkiRJDUfUrwEIFVNof/WrX3HbbbexdOlSbr75ZpKSkigsLKzaKvz000/nhBNOqPGxb7rpJtasWcP8+fP54x//SPyOD5eVpVyvXr32WsJ17NiRm2++mXvvvZf33nuP999/n6SkJPLy8gCIjY3l5ptv3uO6hcXFxYwdO5axY8cC0Lx5cwoKCqpGEmZnZ/OrX/2Kli1b1vg1SVJtmjBhAvfeey8AHfr24/K7/0ZMLa51ti8lpaWsX78eqFj/T2pourZpzfRlyykpK2PWrFlkZWXV2bliwmHOuPWnZPfqxTM//wklhYXcfPPNLFu2jJ///OeEQq6PKUmSFK2aRAEIFWXb/fffz4svvsinn37Kxo0bSU5OpmvXrowcOZLBgwcf0HETExP5v//7P1599VUmT55cNdKkW7duHHPMMYwcOXK3UYU7GzFiBB06dGDs2LHMnDmTrVu3Vk1FPvfcc+nSpcsen5eamsqll17KjBkzWLVqFVu3biU5OZn27dszbNgwTj75ZOLi4g7oNUlSbVm4cCHf/W7FiKPk9HSu/ceDxDdrVm/nX7d2bdUXPa7/p4YoLhyme1Yb5qxczerVq9myZQtpdVxWDzr9TDI7d+Hh665h64YN3HPPPSxfvpy///3vJOyYkixJkqToEopEIpGgQ6jh27hxY50ePz09nXA4TFlZWdVUaDU+4XCY9PR0cnJydlvXUo1HbV2P27dv5+STT2b+/PmEYmK46bGnOGjosFpMun+fffYZc+bMISYmhgsGH1Gru6w2CqEQ4XAMZWXl4Nt9g5VfXMS4z74gEqn4AnHo0KG73J+QkEAoFCISiVBUVFRr5928ehUPXXs1axbMB+Coo47iiSeeqPMCsqnyPTI6+HfW6OE1GR3q+pps1apVrR9TCkoT+yQkSaovP/vZz5g/v6JYOP1HP6n38g9g1eqKnU7bpKY0vfJPjUZSfAKdMzMBWLx4cdVSIHUtI7sdP3z+RXoeVVE4fvjhh5x22mksW7asXs4vSZKk+uOnIUlSrXvppZd4/vnnAeh3wkmccEP9b0iUl5fH1tytgNN/1fD1bt8OgEgkwuw5dbcj8Ncltkjhxkce58jzLgBgwYIFjBw5kjlz5tRbBkmSJNU9C0BJUq1auXIlt956KwCpbdpw6Z/uCmRzgco1WQGynNKoBi41KYl2GekALJi/oFan+u5PbHw8l/7fXzj15h8BsG7dOs4880w+//zzessgSZKkumUBKEmqNWVlZXz3u99l69aKkXeX/fmvJKenB5Jl1Y4CMDE+npSkpEAySDXRu317AEpLS5k7b269njsUCnHq92/mgt/dQSgUYsuWLZx33nlMnjy5XnNIkiSpblgASpJqzT/+8Q8+/PBDAI655lp6DTs6kBzlkXLWrlkDVEz/rf/xh1LNZaa0IDOlBQBz58ylpLS03jMcfdkVXPm3+4iJjSU/P59LL72UV199td5zSJIkqXZZAEqSasXcuXP5v//7PwCyex3MGbf+NLAsmzZuori4GHD9PzUulaMAi4qKWLhwQSAZBp1+Jtc9+G/imjWjuLiYa6+9lmeeeSaQLJIkSaodFoCSpG+srKyMW265hZKSEsJxcVz5178Tl9AssDw7r//X1vX/1IhkZ6STumPK+uxZsykvLw8kR59jjuOmx58msUUK5eXl3HzzzTz99NOBZJEkSdI3ZwEoSfrG/vOf/1RtGHDiDTeRfVCvQPNUFoAtWzQnITY20CxSTYT4akfgvLw8li5dGliWbocdzvdHja5ax/OWW26xBJQkSWqkLAAlSd/IihUruPPOOwFo0607J37nu4HmKS4uZuPGjYCj/9Q4dcpsRXJCAgAzZ84kEokElqV97z5876lnLQElSZIaOQtASdIBi0Qi3HrrreTn5xMKhbj0T3cRt6O4CMqaNWuqCpNs1/9TIxQTCtGrXTYAW7ZsYfny5YHmadfrYEtASZKkRs4CUJJ0wF566SUmTZoEwNGXX0mXQwcFnAhWr6mY/hsXDtOyRYuA00gHplvbNiTEVUxfnzZtWsBpdi8Bf/SjH/Hiiy8GnEqSJEnVZQEoSTog27dv5ze/+Q0AaW2zOP3Hwe36u7PVqyoKwDZpqcSEQgGnkQ5MbEwMPbOzAFi3bh1r164NONFXJWBSWhqRSITvfe97TJw4MehYkiRJqgYLQEnSAbnnnnuqSolzfnk7zZo3DzgR5G7NJS8vD4Asp/+qkeuZlUVsuOKval9O+TLgNBXa9TqY7/znCRKSkyktLeXaa6/lo48+CjqWJEmS9sMCUJJUY4sWLeLBBx8EoMfgIRxy6mkBJ6pQufsvQFZaeoBJpG8uITaWHlltAVi5YiUbNmwIOFGFTgMO4dv/ephwXDyFhYVcdtllTJ8+PehYkiRJ2gcLQElSjUQiEW677TZKSkqICYc5/9e/J9RAptpWFoDNmzWjebNgNyORakOv7HaEYyr+ujZlypSA03zloKOGcfW99xOKiWHbtm1cdNFFLFq0KOhYkiRJ2gsLQElSjUycOJG3334bgKOvuIqsnj0DTlShrKyMdWvXAU7/VfRIjI+rGgW4bNkycnJyAk70lQEnncIlf/wzABs3buSSSy5h06ZNAaeSJEnSnlgASpKqrbi4mNtvvx2AFi1bceoPfhhsoJ1s2LCB0tJSwAJQ0aV3h/ZVG9rMmDEj4DS7Gnz+hZz5018AsGTJEq666iqKiooCTiVJkqSvswCUJFXbk08+yZIlSwAY+aNbSUpJDTjRV1atXgVAKARtUhtOLumbSk5IoFvbNgAsXbqU3NzcgBPt6vjrbuCoiy4B4JNPPuHmm28mEokEnEqSJEk7swCUJFXLtm3buPvuuwHI6tGTwedfGHCiXa1ZvQaAzJQU4sLhgNNItatvxw5ULrXZ0EYBhkIhLvjtHzho6NEAvPjii9x1110Bp5IkSdLOLAAlSdVy//33V63vdebPfkFMAyrZCgoK2Lx5MwBZaWnBhpHqQPPEZnRt3RqomGq7bdu2gBPtKhwXx7ce+CdZPSrWBL377rt57rnnAk4lSZKkShaAkqT9WrNmDQ8++CAAPQYPofeIYwNOtKs1a9ZU3Xb9P0Wrvp06AhU7cc+cOTPgNLtLbJHCDY88RotWmQD8+Mc/ZurUqcGGkiRJEmABKEmqhj//+c8UFBQAcNbPfkmoci5iA7F69WoAEuJiSW+eHHAaqW6kJCbSKbMVAIsWLSIvLy/gRLvLaNee6x78N+G4eIqKirj66qvZsGFD0LEkSZKaPAtASdI+zZs3j2effRaAQ08/k479+gecaHeVBWDbtDRCNKxyUqpNfTq0B6C8vJyZsxreKECAzocM5MLf/QGAVatWcd1111Xt0C1JkqRgWABKkvbprrvuory8nHBcHKf/6CdBx9nNps2bKCwsBJz+q+iXlpRE+5YZACxYsID8gvyAE+3ZkAsvZuillwPwwQcf8Nvf/jbYQJIkSU2cBaAkaa9mzpzJ+PHjARh8wUW06tgx4ES7W71qddXtrLT0AJNI9aNvhw4AlJeVM2vmrIDT7N15v/oNXQ4dBMBDDz1U9WeJJEmS6p8FoCRpr/7yl78AEI6L56Qbvxtwmj1btWoVAOnJySTGxwWcRqp7Gc2TaZdRUXbPnz+/wY4CjI2P51v3/4sWLSvWLfzhD3/I0qVLgw0lSZLURFkASpL26IsvvmDChAkADL34EtKzswNOtLvikuKqDQayMxz9p6aj347RuGVlZcyc0TDXAgRIbdOGK++5l1AoxLZt27j++uspLi4OOpYkSVKTYwEoSdqj3/3udwDEJSRwYgMd/bdm9RoikQjg+n9qWjKaJ1etBTh/wXzy8xvmKECAg4YO46SbvgfAlClT+MMf/hBwIkmSpKbHAlCStJtPPvnkq9F/l15Oaps2ASfas8rpv3HhMK1atAg4jVS/+nX8ai3AGTNnBJxm3075/g/pdvgRADz44IP897//DTiRJElS02IBKEnaTeXov/jERE644TsBp9m71asrNgBpm5ZKTCgUcBqpfqUnfzUKcMH8BeTl5wWcaO/CsbFc9bf7SU6vmKr/wx/+sGr6viRJkuqeBaAkaRdffvklr7/+OgDDLruClFaZASfas5ycnKppj67/p6aqahRgeXmDXgsQIK1tWy79U8XGQhs3buRHP/pR1RR+SZIk1S0LQEnSLv785z8DEJuQwLHf+nbAafaucvQfuP6fmq705GQ6VI4CXLCAvLyGOwoQoN8JJzL4gosAeOONNxg1alTAiSRJkpoGC0BJUpX58+czduxYAIZedAmprRvm2n/w1fp/aclJJMUnBJxGCk6/ThU7ApeXlzNjRsNeCxDg3Nt+TcsOFSMXb7vtNpYsWRJwIkmSpOhnAShJqnLfffcRiUSICYc56cabgo6zVyUlJaxfvx5w9J+UlpREx1YtAVi4cCHbt28PONG+NWvenCvu/huhmBjy8/P53ve+R1lZWdCxJEmSopoFoCQJgOXLlzNmzBgAjjz3fFp16Bhwor1bu3Yt5eXlAGSnu/6ftPNagI1hFGDXQYdz/HU3AvDpp5/y6KOPBpxIkiQpulkASpIAeOCBBygrKyMUCnHKd78fdJx9qpz+GxuOoVVKSsBppOClJiXRKbMVUDEKcNv2bQEn2r9Tf/BD2nTrDsAdd9zB8uXLA04kSZIUvSwAJUmsX7+eZ555BoCBp40kq3uPgBPtW2UB2DYtjXAoFHAaqWHou2NdvUgkwozpDX8UYFxCApf+6S5CoRD5+fn8+Mc/dldgSZKkOmIBKEni0UcfpaioCIBTbmrYo/9yc3OrdjrNcvqvVCU1KbFqFOCiRYvYunVrwIn2r8uhgxh+1TUAvPPOOzz33HMBJ5IkSYpOFoCS1MTl5+fz2GOPAdD9yMF06j8g4ET7Vjn6DyDbDUCkXVSuBRiJRJg+fXrAaarn9FtuJaN9ewBuv/121q1bF3AiSZKk6GMBKElN3AsvvMDmzZsBOO7a6wNOs3+VBWBKYiLJCQkBp5EalpTERLq2aQ3A4sWLydmSE3Ci/UtITubiO/4PgC1btvDb3/422ECSJElRyAJQkpqw8vJy/vWvfwHQums3eh9zbMCJ9q2ktLRqdFB2htN/pT3p27EDMTvWxpw2dVrAaaqn17CjOeyscwAYM2YMH3zwQcCJJEmSoosFoCQ1YW+++SaLFi0C4NhvfZuYmIb9trBu7VrKy8sByHL6r7RHzRMS6Na2DQDLly9n48aNASeqnrN//kuaNW8BwM9+9jNKSkoCTiRJkhQ9GvYnPUlSnfrnP/8JQPOMlhx+9rkBp9m/yum/4ZgYWqekBJxGarj6dmhPeEehP2XKlIDTVE9KZmtG/ujHAMybN4+HHnoo4ESSJEnRwwJQkpqoadOm8eGHHwIw7LIriG/WLOBE+7dqdUUB2CY1tarckLS7xPh4ema3BWDNmjWsXbs24ETVM+zSK2h3cG8A/vKXv7B69eqAE0mSJEUHPz1JUhNVOfovNj6Boy+/IuA0+7d161a2b9sOQHZGWrBhpEagd/v2xIXDQOMZBRiOjeXC390BVOxQfvvttwecSJIkKTpYAEpSE7Rq1SrGjRsHwBHnnEuLlq0CTrR/ldN/AbLS3QBE2p+E2Fh6tcsGYMOGDbtcQw1Zl0MHMfiCiwAYP348H330UcCJJEmSGj8LQElqgh599FHKysoAOOaaawNOUz2V039bJDajRSOYriw1BL3aZRMfGwtUjAKMRCIBJ6qe03/8ExKSmwNw++23V23+I0mSpANjAShJTUxhYSFPP/00AL2OHkHb7j0CTrR/paWlrFu7DoCstLRgw0iNSFw4TJ8O7QDYvHkzy5cvDzhR9aS0yuSkm74HVKxX+sILLwScSJIkqXGzAJSkJubll19m8+bNAAy/4qqA01TP2rVrq0YstmuZEXAaqXHpmZVFYnw8AFOnTm00owCPufoaWnboAMAdd9xBXl5ewIkkSZIaLwtASWpCIpEIjzzyCAAtO3Sg94hjgg1UTStXrgQgNhxD65SUgNNIjUs4Joa+HdoDkJuby+LFiwNOVD1xCc0486e/ACq+BPjHP/4RcCJJkqTGywJQkpqQL7/8kmnTpgEw7LIriNmxQ2hDt3JVRQHYNi2NcIxvXVJNdW3bhuSEBKBiSm1ZI1lT75BTTqPb4UcA8MADD7B69eqAE0mSJDVOfoqSpCbkP//5DwBxCQkMPv+igNNUT05ODvl5+QBku/uvdEDCoRD9O3UEYPv27SxcsCDgRNUTCoU455e3A1BQUMDdd98dcCJJkqTGyQJQkpqI9evXM27cOAAGnXk2yY1kM43K6b8A7TIsAKUD1bl1K1ISEwGYPn06paWlASeqno79+nPo6WcC8Mwzz7Bw4cKAE0mSJDU+FoCS1EQ8/fTTFBcXA3D05VcGnKb6KgvA9OTkqo0MJNVciK9GARYUFDBv3ryAE1XfyB/+mJjYWMrKyvjjH/8YdBxJkqRGxwJQkpqA0tJSHn/8cQC6DjqMDn36BhuomoqKitiwcQMA7Vo6+k/6pjq0yiA9ORmAGTNnUFJSEnCi6sns3JkhF14MwCuvvMKUKVMCTiRJktS4WABKUhPw+uuvs2bNGgCOvuKqgNNU36pVqyBScbtdRkawYaQoECLEgM4VowCLi4qZPXt2wImq75Tv/YC4Zs0AuPPOOwNOI0mS1LhYAEpSE/DYY48BkJKZyYCTTgk4TfVVTv9tFhdHRvPkgNNI0SErPZ3MlBQAZs2aRWFRYcCJqie1dRuOufpaACZPnszkyZMDTiRJktR4WABKUpRbtGgR7733HgCDL7iI2Eayjl55pJzVq1cDkJ2RTohQwImk6BACDtkxCrC0tJSZM2YGG6gGjr/+BpJSUwH44x//SCQSCTiRJElS42ABKElR7umnnwYgFApVraHVGGxYv6Fq05LsdNf/k2pTZkoK2elpAMydN5e8/LxgA1VTUkoqx337BgC+/PJLJk2aFHAiSZKkxsECUJKiWFFREc8++ywAvY4eTsv2HQJOVH0rV1VM/w2FIGtHUSGp9vTv3AmA8rJypk+fHnCa6ht+xVUk7/hS4C9/+YujACVJkqrBAlCSotiECRPYtGkTAEddfGnAaWpm1cpVALROSSUuHA44jRR9MpKT6diqJQALFyxk69atASeqnmbNm3PctdcD8MUXXzgKUJIkqRosACUpij311FMApLRuTd9jjw84TfVt376dLVu2ABXr/0mqG/07dSQUgkgkwtRp04KOU21HX36lowAlSZJqwAJQkqLULpt/nH8h4bi4gBNVX+XuvwDtLAClOpOSmEjX1q0BWLpkCZs3bw44UfU4ClCSJKlmLAAlKUrtsvnHBRcFnKZmKgvA5s2akZKYGHAaKbr17diBmFDFLttTp04NNkwN7DwK8K677nIUoCRJ0j5YAEpSFNp584+Dhg2nZYeOASeqvpLSUtauWws4+k+qD8kJCfTIagtUlO/r168POFH17DwK8Msvv+Tdd98NOJEkSVLDZQEoSVHo9ddfr9r8Y+gljWvzj9WrV1FeVg5Au4yMgNNITUOfDu2JDVf8tXDKlCkBp6m+oy+/ksSUFADuu+++gNNIkiQ1XBaAkhSFnnzySQBSMjMb1eYfACuWrwAgLhymdWpKwGmkpqFZXBwHZWcDsG7dOlavXh1woupp1rw5R19+JQDvvvtuoyovJUmS6pMFoCRFmaVLl1Zt/nHkeY1r84/ySDkrV1Ws/5edkV61Lpmkundw+3bEx8YCjWsU4IirriEuIQGAe++9N+A0kiRJDZMFoCRFmeeee67q9uDzLwwwSc2tX7ee4qJiANq3dPqvVJ/iw2F6t28HwKZNm1i2fFnAiaqnRctWDN6x0dGECRNYsGBBwIkkSZIaHgtASYoi5eXlVQVgt8OPJLNz52AD1dCKlRXTf2NCIbLT3QBEqm89s7NoFl8xanjqlKmNZmfd4759PTHhMJFIhAceeCDoOJIkSQ2OBaAkRZH333+fFSsqSrTB518QcJqaq8zeJi2VuHA44DRS0xMbE0O/Dh0AyM3NZfHixQEnqp6W7Ttw6OlnAvDCCy80mjUMJUmS6osFoCRFkWeeeQaA+KQkDjnltIDT1EzOlhy2b9sOQHt3/5UC07VtG5J3rKk3depUysrKAk5UPSdcfyMAJSUlPPjggwGnkSRJalgsACUpSuTm5vLaa68BcOhpp5OQnBxwopqp3P0XoJ3r/0mBCYdC9O/UEYC8vLxGs6Ze9kG96LNj1/MnnniCzZs3B5xIkiSp4bAAlKQo8fLLL1NYWAjAkY1s8w/4avpvRvPmJMXHB5xGato6t25FalISANOnT6ektDTgRNVz4o3fASA/P5/HH3882DCSJEkNiAWgJEWJyum/mZ270HXQYQGnqZn8gnw2bdoEuPuv1BCE+GoUYGFhIXPnzgk4UfV0HXQ4nQceCsCjjz5KcXFxwIkkSZIaBgtASYoC8+bN48svvwTgyPMuIBQKBZyoZipH/4EFoNRQtG+ZQcsWzQGYNXNWoynTjr3m2wCsW7eOcePGBZxGkiSpYbAAlKQo8OyzzwIQionhiHPOCzhNzVWu/5eckFA17VBSsELAgE6dACguLmbWrFnBBqqm/iedTHp2OwAefPBBIpFIwIkkSZKCZwEoSY1cSUkJzz//PAC9hh1NWtu2ASeqmZKSEtauXQtUjDhqXGMXpejWNi2VNqmpAMyZM4eCgoKAE+1fODaW4VdeBVSsX/jxxx8HnEiSJCl4FoCS1Mi9/fbbbNiwAYDB518UcJqaW716NeXl5YDTf6WGaEDnirUAS0tLmTFjRsBpqmfIhRcTv2M08UMPPRRwGkmSpOBZAEpSI1c5/TcpLY2+x58QcJqaq1z/Lz42lsyUlIDTSPq6Vi1aVJXz8+fPZ/v27QEn2r+klFQGn3cBABMmTGDp0qXBBpIkSQqYBaAkNWIbN25k4sSJABx2xlnEJSQEnKhmysvLWblyJQDZGenENLLNS6SmonJH4PLycqZNnxZwmuoZcdW3CIVCRCIRHnnkkaDjSJIkBcoCUJIasZdffpnS0lIAjtgx2qUxWbduXdXOou0znP4rNVRpSUl0zmwFwKJFi8jNzQ040f5ldu5Mn+MqRkWPGjWKbdu2BZxIkiQpOBaAktSIvfDCCwC06dadDn36Bpym5pYvXw5ATEwMWelpwYaRtE/9OnUkFAIiMHXq1KDjVMsxV38LgO3btzNq1KiA00iSJAXHAlCSGqmFCxfy5ZdfAnD42ecSamTTZyORCMuWLwMgOz2NuHA44ESS9qVFs2Z0b9MGgGXLlrFp06aAE+1fj8FDaHdwbwD+85//VG04JEmS1NRYAEpSI1U5+g/gsLPODi7IAVq/fj2FBYUAdGjVMuA0kqqjT8cOxMRU/PVxypQpAafZv1AoxNGXXwnA0qVLeeedd4INJEmSFBALQElqhMrLyxkzZgwA3Y8cTEZ2u4AT1VzV9N9QiHau/yc1Cknx8RyU1RaA1atXs27duoAT7d9hZ55NYouKHcYfe+yxgNNIkiQFwwJQkhqhTz75pKpAO/zscwNOc2Aqp/+2TUsl3um/UqPRu0N7YsMVf4WsXIagIYtPTOTIHZskTZw4kRUrVgScSJIkqf5ZAEpSI1Q5/TcuIYFDTjkt4DQ1t3HjRvLz8gGn/0qNTUJsLAe3qxh1vGHDBlauXBlwov0beullQMXo6SeeeCLgNJIkSfXPAlCSGpnCwkLGjRsHQL8TTiKxRYuAE9Vc5ei/UAjat7QAlBqbXu2ySYiLBSrWAoxEIgEn2rc2Xbtx0NBhAIwaNYqioqKAE0mSJNWv2KADqHEI1+P0vPo8l2pX5c/On2Hdeuutt9i6dSsAh59Tt7v/1tWxly+rmL7cOjWVhLi4OjmHILTTvyONbJdo7UUD+TnGxcbSp0N7vly8lJycHJYvX07nzp2DjrVPR19+FfM+eJ+NGzcyYcIEzj///Ho9v++R0cefZePmNRl9/FlK+xaKNPSvbCVJuzjrrLMYP348LVq25M+fTyO2kRVomzZt4sUXXwTgyB7d6dkuK+BEkg5EWXk5L3/yGflFxaSmpnLBhRcQE2q4k0vKSkv55ZDDyVmzmqFDh/L+++8HHUmSJKneOAJQ1ZKTk1Onx09JSSEcDlNWVlY1skmNTzgcJiUlha1bt1JWVhZ0nKi0adMmJkyYAMChp59JWXk5ZbU8lS0+Pp5QKEQkEqG4uLhWjw2wYMGCqtvZGemUlZXX+jlUIQTEhGMoLyvHb/sar3BMzI5hnBWlW0PSt0MHPl24iNzcXGbPmk2PHj2CjrRPR118Ka/97W4++OAD3nvvPfr27Vtv5/Y9Mjr4d9bo4TUZHer6mkxPT6/1Y0pBsQBUtdTnm6JvwI1fWVmZP8c6MnbsWEpLS4GK3X/rehB3XRx/2bKK9f8yU1JIjIsDB6LXmcppvxHw9zlaNLCfY9c2rZmzahXbCgqZOm0qXbp0adBTsIZceBFvPHAvZSUlPPLII/z1r3+t9wy+R0YPf47RwWsyevhzlPat4c7TkCTtpnL33zbdutGhb7+A09Rcbm4uubm5AHR091+p0YsJhejfsSMA+Xn5zJs3L+BE+5aS2ZoBJ58KwJgxY9i2bVvAiSRJkuqHBaAkNRKLFy/m888/B+Dws+p284+6Ujn6D6B9y4wAk0iqLR0zW5KWnATAzJkzKSkpCTjRvg29+FIA8vPzeemllwJOI0mSVD8sACWpkdj5g+qgM88KMMmBW7p0KQCtWjQnOSEh2DCSakWIEAM6dQKgsLCQOXPmBJxo37ofOZjMzl0AeOqppwJOI0mSVD8sACWpEYhEIlU753Y5dBAt23cIOFHN5WzJYcuWLQB0yswMNoykWpWdkU6rFi0AmDVrFkW1vDlRbQqFQgy58GIApk6dyowZMwJOJEmSVPcsACWpEZg5c2bV7rmDzmiko/+WLK267fp/UnQJAQM6V6wFWFJSwsyZM4MNtB9HnHseMbEVe+E5ClCSJDUFFoCS1AhUTv+NCYcZeNrIgNMcmCVLlwDQOjWFxPj4gNNIqm1tUlPJSk8DYO7cuRQUFAQbaB9SWmXS7/gTAXjxxRfJz88POJEkSVLdsgCUpAauvLycsWPHAtBzyFBatGwVcKKa27RpE9u3bQec/itFs/6dKkYBlpWVMXNWwx4FWDkNeOvWrYwfPz7gNJIkSXXLAlCSGrhPP/2UVatWATDojDMDTnNgKjf/CIWgYyt3/5WiVcvmzcnOSAdg/rz55Bc03JF1vYYdTXp2O8BpwJIkKfpZAEpSA1c5+i82PoH+J50ccJqai0QiVdN/26alkRAbF3AiSXWpf8edRgHOaLijAGPCYQZfcBFQ8UXLvHnzAk4kSZJUdywAJakBKykpqZqa1ufYY0lskRJwoprbsGED+XkVo4A6ZTa+6cuSaiajeTLtW1aM9J2/YH6DXl9v8PkXEoqp+Ovw008/HXAaSZKkumMBKEkN2LvvvsumTZsAOPT0xjn9t3L0X0woRPuW7v4rNQX9OnYAoLysnBkzZwScZu/Ss7LoPeIYAJ5//nmKioqCDSRJklRHLAAlqQGrnP6bkNycPsceH3CamotEIixbugyA7Ix04sPhgBNJqg/pyV+NAlwwfwF5eXkBJ9q7IRdeAsDmzZt5/fXXA04jSZJUNywAJamBKigo4LXXXgNgwEknE9+sWcCJam7turUUFhYC0KmV03+lpqRqFGB5OTNnNty1APscc2zV7urPPfdcwGkkSZLqhgWgJDVQb775ZtWomcY6/XfpkqUAhGNiaNcyPdgwkupVenIyHVtVTPtfsGAB27dvDzjRnoXj4jjsrLMBmDRpEmvXrg02kCRJUh2wAJSkBqpy+m/zjJYcdNTQgNPUXFlZGUuXLgWgXUYGsTFO/5Wamp1HATbktQCPOPd8oCLnmDFjAk4jSZJU+ywAJakB2rp1K2+99RYAh5x6GuG4uIAT1dzKlSspKSkBoEvrzIDTSApCalISHXdM/1+4YGGDHQXYrtfBtO/TF4DRo0cTiUQCTiRJklS7LAAlqQF67bXXqnajHHTGWQGnOTCLFi0CoFlcHFnpacGGkRSYylGAkUiE6dOnB5xm7448r2IU4Lx585g6dWqwYSRJkmqZBaAkNUCV03/Ts7LpcuiggNPUXGFhIatWrQKgU2YrYkKhgBNJCkpqUiKdMitGAS5atIht27YFnGjPBp1+VtVo62effTbgNJIkSbXLAlCSGpgNGzbw7rvvAnDoGWcSE9P4/qhesnRJ1RQ6p/9K2mUU4IyGOQqweUYGfY87HoCXXnqpagdzSZKkaND4PlVKUpR79dVXKS8vB+DQkWcEnObALF60GICUpETSmzcPOI2koKUkJtJ5x5cBixctZuvWrQEn2rMjz7sQgC1btvDf//434DSSJEm1xwJQkhqYcePGAZDZuQvte/cJOE3N5ebmsmnTJgC6tG6Nk38lAfTr2J5QqGGvBXjw0cNp0aqiqBw9enTAaSRJkmqPBaAkNSDr1q3jww8/BGDgaSMJNcK18xYvXlx1u/OOdb8kqUWzRLq0bg3A4iUNcxRgOC6Ow886G4BJkyaxdu3aYANJkiTVEgtASWpAXn311aq18waednrAaWouEolUFYBtUlNJTkgIOJGkhqRPh4pRgERg2vRpQcfZoyPOrdgNuLy8nBdeeCHgNJIkSbXDAlCSGpDK6b+tu3Yj+6BeAaepuXXr1pGXlwdAlzZu/iFpVy2aNaPrjlGASxYvITc3N+BEu8s+qBcd+vYDKqYBV34pI0mS1JhZAEpSA7F27Vo+/vhjAA497fRGPf03HBNDh5YtA04jqSHq07EDlX+8zZgxI9gwe3HkjlGA8+fPZ8qUKQGnkSRJ+uYsACWpgRg/fnyjnv5bUlrK0mVLAWjfMoO4cDjYQJIapOYJCVWjABvqWoCDzjiLcFwcgNOAJUlSVLAAlKQGonL6b9vuPcjq2TPgNDW3fNkySktKAejapnXAaSQ1ZL13WguwIY4CTE5Pp/eIYwF4+eWXKSkpCTiRJEnSN2MBKEkNwOrVq/n000+Bxjn6D2DBggUAJCXE0zYtNeA0khqyFs2a0TmzYp3QxYsXs23btoAT7e6wHbsBb9y4kXfeeSfQLJIkSd+UBaAkNQDjx4+vun3IqacFmOTAbN26lfXr1wPQrU0bQjS+9Qsl1a8+HdoDFbuHN8RRgH2PO55mzVsAMGbMmIDTSJIkfTMWgJLUAFQWgFk9DyKrR+Ob/rtg4YKq207/lVQdKYmJdM5sBcCiRYvYvn17wIl2FZfQrOoLmddff73B5ZMkSaoJC0BJCtjKlSv57LPPABh42siA09RceXk5ixYuAqBtWhrJCQkBJ5LUWPTp2AGoGAU4c+bMgNPs7rAzzwagoKCACRMmBBtGkiTpG7AAlKSAvfLKK1W3B57a+ArAVatWUVhYCEC3to7+k1R9qYmJdNoxCnDhwoXk5eUFnGhX3Y8cTFrbLMDdgCVJUuNmAShJAavc/Te718G06dY94DQ1V7n5R3xsLO0zMgJOI6mx6btjLcDy8vIGNwowJiaGQWeeBcC7777LunXrAk4kSZJ0YCwAJSlAy5cv54svvgAa5/Tf/IJ8Vq5aCUCX1pmEY3xbkVQzqUlJdGjVEqj4QiE/Pz/gRLs6/KxzgIqC8qWXXgo4jSRJ0oHxk5okBaixT/9duGAhRCpud2vbJtgwkhqthjwKMPugXmT3OhhwN2BJktR4WQBKUoBefvllANod3JvWXboGG6aGIpEI8xfMB6BVi+akJSUFnEhSY5WenEz7lhVLCCxYsID8goY1CrByM5Bp06Yxf/78YMNIkiQdAAtASQrI0qVLmTp1KgADTzs92DAHYOXKleTnVXxI75GVFXAaSY1d3w4VOwKXlZUxa9asgNPsatDpZxIKhQBHAUqSpMbJAlCSAjJ+/Piq242xAJw3bx5QsflHxx3rd0nSgcponky7jHQA5s+bT0FBQcCJvpKenU33IwcD8OKLLxKJRAJOJEmSVDMWgJIUkMrdfzv07Udmp04Bp6mZbdu2sXr1agC6tW3t5h+SakXfjl+NApw9e3bAaXZ12I7NQJYvX86nn34acBpJkqSa8RObJAVg8eLFTJ8+HWico/8q1/4D6N62bYBJJEWTls2bk5WeBlSMMi4sLAw20E4OOeVUYuMTAKcBS5KkxscCUJICsMv031NPCzBJzZWVlVXs/gtkpafRolmzgBNJiiaVowBLS0sb1CjAxBYp9D3ueKBiBHdxcXHAiSRJkqrPAlCSAlA5/bdj/wG07NAx4DQ1s2zZMoqKigDokeXoP0m1K7NFC9qmpQIwd+7cqj9vGoLKacA5OTlMmjQp4DSSJEnVZwEoSfVsyZIlzJw5E2h8o//gq80/khLiqxbsl6Ta1G/nUYBzGs4owN4jjiEptaKcfOmllwJOI0mSVH0WgJJUz1577bWq2/1POjXAJDW3YeMGNmzYAECPtm0JEQo4kaRolJmSQuvUFADmzplLUQOZbhsbH0//k04B4I033iAvLy/gRJIkSdVjAShJ9ayyAGx3cO9Gt/vvnDlzAYiJiaF7VpuA00iKZpWjAEtKSpg7Z07Aab4y6IwzAcjPz2fixIkBp5EkSaoeC0BJqkerV6/m888/B2DAyacEnKZm8vLzWLZ0KQBdWmeSEBsXbCBJUa1NamrVKMA5c+ZQXNIwRgH2OHIILVplAvDyyy8HG0aSJKmaLAAlqR5NmDCh6vaARjb9d97ceUQiEQB6ZWcFnEZSU9C3Q8UowOLiYubuGIEctJhwuGr91rfeeovc3NyAE0mSJO2fBaAk1aNXX30VgNZdu9G2R4+A01RfaWkp8xfMB6BtWiqpSUkBJ5LUFLRJS6VVixYAzJ4zm5KSkoATVTj09DOAimJy5y92JEmSGioLQEmqJxs3buSjjz4CYMBJpxAKNZ4NNBYvXkxxUcX0u4PaZQecRlJTEQL6ddoxCrComLnzGsYowM4DB5Ge3Q5wN2BJktQ4WABKUj15/fXXKS8vB2DAKY1r+u+cHQvwpyQ2Izs9LdgwkpqUtmlptGzRHIDZsxrGKMCYmBgOHXk6AO+++y4bN24MOJEkSdK+WQBKUj2pnP6b0a49Hfr0DThN9a1atapqjauDsrMJ0XhGLkpq/EJA3x07AhcVFTF//vxgA+1w6MiKacBlZWW88sorAaeRJEnaNwtASaoHubm5vPfeewD0P+nkRjX9d8bMGQDEx8bSpU1mwGkkNUXZ6elkNE8GYNasWZSWlgacCNr36Utm5y6A04AlSVLDZwEoSfVg4sSJVdPWDmlE0383bNjA+nXrATgouy2xMeGAE0lqinYeBVhYWNggRgGGQiEGnX4mAB9//DGrV68OOJEkSY3fMcccQygUqpcBE1dffXXVuZYuXfqNjrV06dKqY1199dW1kq+2WQBKUj147bXXAEjJzKTzwEEBp6m+mTNnAhCOiaFndlbAaSQ1Ze0yMkhLrtiBfOasmZSWBT8KcOCOdQAjkQjjx48POI0kSdLeWQBKUh3Ly8tj0qRJAPQ/8WRiYhrHH705OTmsWLECgO5t25AQGxdwIklNWQjoVzkKsKCQBQsWBBsIyOrRk+xeBwMwduzYgNNIkiTtXeP4FCpJjdikSZMoKCgAYMDJjWf677Tp0wAIhaBXu+yA00gStG+50yjAGTMpKysLONFXm4FMmTKFJUuWBJxGkqTG7Z133iESiRCJRIKOEnUsACWpjlXu/puUlkb3I44MOE31bN++nYULFgLQOTOT5ISEgBNJEoQI0bdDxSjAgoICFi5cGHAiGHT6GVW3X3755eCCSJIk7YMFoCTVoaKiIiZOnAhAv+NPJBzXOKbRTp8+vepbt97t2wWcRpK+0qFVBilJiQDMmDEj8FGALTt0pNOAgYC7AUuSpIbLAlCS6tDkyZPZvn070Him/+bn5zNnzhwA2mWkk5qUFHAiSfrKzqMA8/PzWbRoUcCJ4NAdowDnzJlT9eenJEn1paysjOzsbEKhEC1atCA/P3+/zykuLqZVq1aEQiFatmxJcXFx1X2FhYWMGzeOH/zgBxx11FFkZmYSFxdHixYt6NGjB1dccQVvvvnmfs/x29/+tmpn3HfeeQeomOJ7xRVX0LVrV5KSkna5D6q3C/C2bdsYPXo0N9xwA4cffjgZGRnExcWRlpZG7969ue666/j000/3m29Pxo4dy8iRI2nfvj0JCQm0a9eOCy64oGpN99oydepUbr75ZgYMGEBGRgYJCQlkZ2czcuRIHn30UUpLa3+zs9haP6IkqUrl9N+E5OYcNHRowGmqZ9q0aVUjavp17BhwGknaXafMlsxc3oytBYXMmDGDbt27Ew5wg6WBp47k5T/+gUgkwssvv8zBBx8cWBZJUtMTDoe57LLLuPvuu9m+fTtjx47l8ssv3+dzJkyYwKZNmwC46KKLiI+Pr7qvd+/ee1zXdvv27SxcuJCFCxfy9NNPc9ZZZ/H000/TvHnzauX8wQ9+wP3331+DV7a74uJiWrduTWFh4W735ebmkpuby5w5c3jkkUe44YYbeOCBB4iN3X/1VVpaysUXX8xzzz23y6+vXr2aMWPGMGbMGG666SYeeOCBfZaT+1NUVMRNN93EY489tts6h2vWrGHNmjVMmDCBe+65h/Hjx9O1a9cDPtfXWQBKUh0pLS3ljTfeAKDPsccRl9As4ET7l1/w1ei/9i0zyGieHHAiSdpdiBB9OnTgo/kLyMvLY/GiRfTo0SOwPGlt29Lt8CNZ+OnHvPTSS/z85z//Rh8OJEmqqauuuoq7774bgKeeemq/BeCTTz5ZdfvKK6/c5b78/HzS0tI47rjjGDhwIJ06dSIpKYmtW7cyffp0nnvuOdasWcO4ceP41re+xfPPP7/ffHfddRevv/46mZmZXHXVVfTv3x+o2EQrJSWl2q+zvLycwsJC2rRpw/HHH8+AAQPIzs4mMTGRnJwcPv/8c55//nlycnJ46KGHSElJ4a677trvcX/2s58xduxYsrKy+Na3vkWfPn0oKCjg7bffZvTo0ZSXl/PPf/6TZs2a8de//rXaeXdWWlrKKaecUjXiMTs7m4svvpj+/fuTlJTEypUrGTt2LO+//z6zZs1i+PDhTJkyhczMzAM639dZAEpSHfnwww/JyckBYMDJpwScpnpmzZxVNfqvf+dOAaeRpL3rlNmKGctXsL1wxyjAbt2ICXAU4KAzzmThpx+zZMkSpk2bxiGHHBJYFklS09O3b18GDhzIlClTePvtt1mzZg1ZWVl7fOzmzZt57bXXAOjZsyeDBw/e5f7HHnuME044gbi9rF9+5513ctlll/Hyyy/zwgsv8P777zNs2LB95nv99dcZMmQIr732Gunp6VW/fsUVV9TkZRIXF8eECRM4+eST9/i+/+1vf5s777yTM844g48++oh77rmH7373u3TqtO/PNmPHjmXIkCFMmDCBtLS0ql//1re+xXXXXcfIkSPJz8/nb3/7G+eddx5HHXVUjXID3H777VXl33XXXcd9991Hs2a7DhK55ZZbuO+++7j55ptZtWoVt9xyC08//XSNz7UnrgEoSXWkcvpvXEICvYcfE2yYasgvyGf+/PlAxei/ltUcyi9JQYgJhejbsT1QMSVpT1OV6tOAk08lJhwGYPz48YFmkSQ1TZUj+crKyvZZGj3//PNVa/7tqYA79dRT91r+ASQlJfHEE0+QnFwxW+iJJ57Yb7bk5GReeOGFXcq/AxEOhzn11FP3+aVfy5Ytq0Y47u/3olLz5s0ZM2bMLuVfpWOOOYY//elPAEQikaqRljWxfv16/v73vwNwwgkn8PDDD+9W/lX6wQ9+wKWXXgrA6NGjWbVqVY3PtycWgJJUB8rLy5kwYQIABw8/hoTkhj+VdufRfwMc/SepEeicmUlyQgJQsXt5eaQ8sCzNMzLoMbhiNMC4ceN2W9dHkqS6dumll1atd/fUU0/t9XGV5VgoFKrxCLxKKSkp9OvXD4CPP/54v48/99xzadeu3QGd60B0796dtm3bAtXLd/nll5Odnb3X+6+//npSU1OBioEee1qDcF+ee+65quf85Cc/2e/jr7rqKqCiwHz77bdrdK69qdUpwJdeeik33ngjw4cPr83DSlKj89lnn7Fu3ToA+p/U8Kf/5uXnMW/+PGDH2n8tmoOfXSU1cJWjAD9ZsIht27axdMnSWl0su6YGnjaSeR+8x/Lly5k6dSoDBw4MLIskqelp3bo1p5xyCq+++iozZsxg6tSpuy1JsXDhQj766CMAhg8fvtepsTk5OYwaNYo33niDmTNnsmnTJvLy8vb4BdfKlSv3m+3oo4+u+Qvah9WrV/PUU0/x9ttvM3v2bHJycva6+3F18p1wwgn7vL9Zs2YMGzaM1157jZKSEqZOnbrb1Ol9effdd6tur1u3jpdffnmfj9951N/s2bOrfZ59qdUCcPTo0Tz33HP07NmTG264gSuvvJKMjIzaPIUkNQqVa2qE4+Loe/zxAafZv2lTp1FeVjFyxtF/khqTzq1bM3P5SvKKipg+fTpdunQJbAOO/ieezPO/vo3ysjLGjx9vAShJqndXXnll1VJETz755G4F4M7TYb+++UelcePGce2111btErw/W7du3e9j2rdvX61jVcdDDz3Ej370o70Wfl9XnXzV2Uxs58esXr26WueutHTp0qrbe/t935vNmzfX6PF7U+ubgEQiEebPn8+Pf/xjfvnLX3L++edz/fXX73dBSEmKFpFIpOpNt+eQo0hKSQ040b5t2bKFhYsWAhWL6me49p+kRiQcCtG7Q3s+W7iIrVu3snTZUrp07hJIluYZGfQcMpS577/LuHHj+PWvf+1uwJKkenXmmWeSnp5OTk4Ozz77LH/5y18I71ijFr6aGpyUlMQFF1yw2/M/+ugjzj//fEpLSwHo378/J5xwAt27dyc9PZ2EhISq97Zf/epXzJo1i/Ly/S/BkZiYWBsvjxdeeIEbb7yx6r+HDBnCiBEj6NKlC6mpqSTsWBoEKqbtbtiwoWqZo31JrsaSTTs/Ztu2bTXKvWXLlho9fmeV6zV+U7VaAL7zzjs8+OCDvPTSSxQVFVFYWMioUaMYNWoUvXr14sYbb+SKK67Y46KKkhQtpk+fzooVKwAYcNKpAafZvylTpkCkYirdgE4dg44jSTXWtXUms1asIL+omOnTptO5U+fAireBp41k7vvvsmLFCqZMmcKhhx4aSA5JUtOUkJDAhRdeyEMPPcTatWuZOHEip55a8Znkgw8+YPHixQCcffbZtGjRYrfn//rXv64q//7xj39w00037fVcd955Zx28gn375S9/CVRsBvLSSy9xxhln7PWx1113XbWPm5eXV6PH7On3bl+a7zTIYuvWrTV+fm2o1U1Ahg8fzjPPPMPKlSv5y1/+Qs+ePYlEIkQiEebOncsPf/hD2rVrxzXXXFM151ySok3l6L9QTAz9Tjwx4DT7tn79+qqysnvbNjTfy05UktSQhWNi6L1jalFubi7Lli0LLEv/E08mZscC7OPGjQsshySp6dp5imnlhh9fv72naaglJSW88847AAwaNGif5R/sOq21PixZsoSFCytmLp199tn7LP+2bt1ao6mzlcet7mP2tWHInuw8Bbry81d9q5NdgFu2bMmPf/xj5s6dy//+9z8uuugi4uPjiUQiFBQU8OSTTzJs2DD69+/PP//5z2rNx5akxqJy/b9uhx1Bi5atAk6zb19++SUAseEY+nbsEHAaSTpw3dq0JjE+HoDpM6YHtgtvcno6Bx01FHA3YElSMI466qiq9erGjRvHtm3bKCoq4vnnnwcgKytrj5tebNy4sWr0X/fu3fd5js8++4yNGzfWcvJ9W7t2bdXt/eX773//W62pyZXefPPNfd5fVFTE+++/D0B8fPxuayvuz4gRI6puv/766zV6bm2pkwJwZyNGjODZZ59l5cqV3HXXXbuMCpw1axbf//73yc7O5tvf/jaffvppXceRpDo1b948FixYAMCAUxr27r8rVqxg/fr1ABzcrh3N4uICTiRJB65iFGA7ALbkbAns23WAgaedDlTs4PfFF18ElkOS1HRdccUVABQUFPDCCy/w6quvVq1Dd9lll+2yLmClnde429+IuN/85je1F7aaqpuvuLiYO+64o0bHHjVqFGvWrNnr/Y888kjV79/pp59OsxrOnLr44our1ie855576r08hXooACu1bNmSW2+9lblz5/L2229z0UUXERcXRyQSIT8/n8cee4whQ4YwcOBA/v3vf1NQUFBf0SSp1lRO/wXof2LDLQDLysv5/PPPAUiIi6VXu5oNYZekhqh72zZVX2ZMmzYtsBz9Tjipahrw+PHjA8shSWq6rrjiiqr1cJ988sn9Tv8FSElJoWfPngB88cUXjBkzZrfHlJWVccsttwQyiq1Xr15Va+mNHz9+j0vLFRQUcPnllzN9+vQaHXvbtm1ceOGFe5yh+u677/Kzn/0MgFAoxK233lrj7O3bt+cHP/gBULGD8Mknn1y1HuPeTJs2jRtuuKHG59qbWt8FuDqOPfZYunbtSmpqKg8//HDV/5SRSITp06dz44038stf/pJf/vKX3HzzzcTE1FtPKUnfSGUB2GnAQNKzsgJOs3dz586p2rlqQKdOxO3hG0BJamzCMTEc3L4dU5YsJScnhxUrVtChQ/0vb5CclkavocOYPfkdxo8fz29/+9s9jrSQJKmudO7cmeHDhzN58mTefffdqvehQw45hH79+u31eT/84Q+r1v678MILueiiixgxYgTp6eksXLiQUaNGMWfOHPr27UtCQkK9jnSPj4/npptu4q677qKkpIQRI0Zw9dVXc8QRR5CcnMzs2bN54oknWLFiBccffzzz5s1j5cqV1Tr2eeedx4svvsjBBx/MtddeS+/evSkoKODtt99m9OjRVTsJ33LLLQwZMuSA8v/xj39k2rRpTJw4kS+//JJevXpx5plncvTRR5OVlUV5eTkbN25k5syZ/O9//2P+/PmEw2EeeuihAzrf19VrAVheXs748eN56KGHePPNN6vWRIlEIrRo0YLBgwczefJkiouL2bRpE7feeivjxo3j9ddfr7UtoyWprixdupSZM2cCcEgDnv5bUFDA9GkV34ilJSfRrW3rgBNJUu3pkdWWOStXUVhSwrTp0wIpAKFiGvDsye9UTQMePHhwIDkkSU3XlVdeyeTJk4lEIlVr++1t9F+lG2+8kc8//5xHH32USCTC6NGjGT169C6P6devH+PGjeOaa66ps+x78//s3Xd8VGX6///XmUmvEAi9JYEQQgmdhBZ6FxHL2lbX1S26urrqfj+76+7+/Oiu+tld22J3UUEEUQRDR2qooYdeQwm9BRLSk5n5/THJLBhKCCczKe/n48HDMPc517nCOMmZa+77vl599VW2b9/OwoULKSoq4tNPP+XTTz+96pjExESmT59Ot27dyh33jTfewMfHh2nTpvHqq69e85gnn3ySf/7znxXO3cvLi7lz5/LHP/6Rd999l6KiIr777ju+++67655zZfOQ2+WWqXVHjx7lz3/+M82bN+fuu+/mhx9+wG6343A46NixIx988AEnTpxg0aJFHDt2jL///e+Eh4fjcDhYtWoVb731ljvSFBG5LaXNPwA6DRvpwUxuLDU1laKiIgC6R0ViYHg4IxER83hZLK5tDTIuZJT7k3+zdRwyDGvJcmR1AxYREU+49957CQgIcP3dy8uLBx988IbnGIbBxIkT+e677xg+fDj16tXD29ubRo0akZiYyHvvvceGDRuIiIio7PSvycfHh3nz5jFx4kT69+9PaGgoPj4+NG3alBEjRjBp0iSWLVtGvXr1bimul5cXU6dOZcaMGYwaNYomTZrg4+ND48aNGT9+PEuWLOGDDz647RWq3t7e/Otf/+LgwYP89a9/pV+/fjRq1AgfHx/8/Pxo2rQpAwcO5A9/+APLly+/6TLhW2E4Kqk1mc1mc832W7JkiavxBzifsHvuuYcnn3ySPn36XPP8jIwMEhMT2bVrF7Gxsa5ZNeIZlb1BZd26dbFardhsNi5evFip15LKY7VaqVu3LhcvXnRNka5NRo4cyaZNm2jaLpb/meOZzk43c+HCBVehskX9evSNaVvmGKvVCgbgoFY+jzWKYWC1WrDZ7KBOpNWWXpO3rshmI2njZgqLi6lfvz6jRo3ySB4f/+Ixdi1fRuPGjdmxYwf16tWrtb8jawrds9Yctf2+taao7Ndk/fr1TY8p4immzwA8cuQIL730Ei1atOCee+5h8eLFrtl+rVq14vXXX+f48eNMmTLlusU/gLCwMJ599lkADh8+bHaaIiKmOnXqlKupRqdhVXf578aNGwGwWCx0iWjl2WRERCqJt9VKu2bOWYDnz5/32CzAziNHA87fERs2bPBIDiIiIiJg8h6Aw4cPZ+nSpVfN9rNYLIwaNYqnnnqKESNGuBp+lEfpWuf8/Hwz0xQRMd2Vy387D6+ay38PHjzI2bNnAYht1oTAkjb0IiI1UXTjxuw9cZKComJSU1NN3UOnvDoOGYrV2xtbURHff/89I0dWzd8PIiIiUvOZOgPwytl+DRo04I9//CNpaWnMmTOHkSNH3lLxDyAgIIAWLVrQsmVLM9MUETFdaQGwQUQkjdq08XA2ZeUX5Ls6dAX6+hLrgTfCIiLu5G21EtusKeDcWiY9Pd3tOQSEhBLTtz8Ac+bMwW63uz0HEREREaiEJcD9+vVj6tSprmYet1O869+/P0eOHDF100MREbOdP3+etWvXAhA3/NY/7HCHzZs3U1BQAECP1pF43ebmtSIi1UGbxo3xK2nEkZqaSiVtfX1DXUaNAZzLgEt/V4iIiIi4m6nvAHfs2EFycjL3338/3iU3WyIiNd2CBQtcszrihle9/f/OnDlD2sE0wNn4o0nduh7OSETEPbwsFto3d854vnTpEkeOHnF7Dh2HDMHq7QPAN9984/bri4iIiIDJBcD27dubGU5EpFooXf4b1rQZzTt09HA2V7PZ7aSkpADO5XDdIiM8nJGIiHu1btQQfx9nAW7btm1unwXoHxxCu/6JAMyYMUPdRkVERMQjTC0AWiwWvLy8mD179i2dt2jRIqxWK15epvYkERGpdJmZmaxcuRKATsOGV7nlvzt37CAzMxOATq1auN4Ei4jUFlaLhQ4lswCzMrM4dNj9W8t0GTkKcC4DXr9+vduvLyIiImL6JlAV/VT1ys7BIiLVxeLFiykqKgKc+/9VJRkZGWzfvh2AesFBRDdu5OGMREQ8I7JRQ1fn823btmF3uLcZR4fBQ/HycV7/+++/d+u1RURERKASCoAiIrXJ3LlzAQgJDyeiazcPZ/NfdrudNWvW4HA4sBgG8W3aYFC1ZieKiLiL1TDo0MI5CzD7cjZpaWluvb5/cLBrGfCcOXO0DFhERETcrkoUAHNzcwHw8/PzcCYiIuWXk5PDsmXLAOg4dDiWKtRZd8fOHVy8eBGATi1bEBrg7+GMREQ8K6JBA4JK7jW3b9uOze7eWYBdRzu7AZ85c8a1N6uIiIiIu1SJd6ulN0ENGjTwcCYiIuW3bNky8vLyAOhchZb/ZmRksH2bc+lvWFAQMU2beDgjERHPsxgGHVs0B5wf4Bw8eMCt1+8waAheJcuQk5KS3HptERERkQp33di+fTupqanXHFu2bBmXLl264fkOh4OcnBy2bNnClClTMAyDHj16VDQdERG3K13+GxAaSuuevTycjZPNZrtq6W9CdGssVawxiYiIp7RqUJ9dx46TlZfHju07aB3VGqvV6pZr+wUF0XHgYLYunM/cuXN5/fXX3XZtERGpuapaE8KbUe8Hz6lwAXDWrFm88sorZR53OBxMmDDhlmI5HA4Mw+DXv/51RdMREXGrgoICfvjhBwA6DhmG1dvbwxk5bd261bX0t2PLFoQGBHg4IxGRqsPAoGPL5qzZu5/c3Fz2799Pu3bt3Hb9bmPuYOvC+Zw7d45169bRt29ft11bREREarcKFwDh+pXbW63oNmzYkL///e8MGjTodtIREXGb5ORksrOzgarT/ffkyZPs3r0bgAahIcQ209JfEZEfa1G/HrsCA7iUk8uOHTto3bo13m76EKfTkGF4+/pSVFBAUlKSCoAiImKa1x78Ce2aNfV0Gte05/gJ/jR1uqfTqPUqXAAcN24crVq1uuqxxx57DMMwePrpp+natesNz7dYLAQFBREREUHHjh3dsgQiMzOTGTNmsGHDBi5cuICvry9RUVGMGjWK+Pj4CsctLi5m7ty5JCcnc/LkSQCaNm1KYmIio0ePxsvrxv/Mhw4dYtasWezYsYOsrCxCQ0Pp0KED48ePJyIi4qbXLyoq4ocffmDNmjUcO3aMnJwcQkNDadKkCZ06dWLcuHH4luw5IyLmmDdvHgC+gYG07dPHw9lAfkE+a9asAcDbaiUhWl1/RUSuxcCgU8sWrNy9l/z8fPbs2UOnTp3ccm2/oCBiBwxi26IFrmXAN7tPFBERKY92zZrSo3WUp9OQKqzCdxxxcXHExcVd9dhjjz0GwODBgxk7duztZWay9PR0XnrpJTIzMwHw9/cnJyeH1NRUUlNTueOOO/jFL35xy3Hz8vL4y1/+wv79+wHw8fEB4ODBgxw8eJA1a9bwyiuvXLfDcXJyMu+++y7FxcUABAYGcuHCBZKTk1mzZg2/+93v6Nev33Wvf/LkSV599VVOnDgBgNVqxc/PjwsXLnDhwgV27NjB4MGDVQAUMVFxcTELFy4EoP3AwXj7er6D+bp161wNSXq2iSJQr3kRketqGhZG/eAgzl/OZueunUS3jcbPTT/Lu4wazbZFCzh//jxr166lf//+brmuiIiI1G6mfuT4+eefA9x09p+7FRUV8be//Y3MzExatmzJ888/T0REBAUlyy+++uor5syZQ0REBEOGDLml2B988AH79+8nMDCQ3/72t66ZhCkpKfz73/9m7969fPjhh/zud78rc256erqr+Ne3b1+eeOIJwsLCyMjI4NNPP2XNmjW88847RERE0KxZszLnZ2Rk8Kc//YmMjAzatm3Lww8/TIcOHbBarRQUFHD06FHWrl3rKkqKiDnWrVtHRkYGAHHDRng4G9izdw/H0o8BENEgnJb163s4IxGRqs0AOke0Ysn2nRQXFbNjxw56dHdPM7oOAwfj7edHUX4+s2fPVgFQRERE3MJiZrBHH32URx999JrFKk9atGgRp0+fxtfXl7/+9a+uZbW+vr7cd999jBzp3L9rypQprpl45XH48GFWrlwJwDPPPENCQgKGYWAYBgkJCTz99NMArFixgqNHj5Y5/6uvvqK4uJiIiAheeOEFwsLCAAgLC+PFF18kIiKCoqIivvrqq2te/6OPPiIjI4PY2Fhee+014uLiXEupfX19iY6O5mc/+xkhISHl/p5E5ObmzJkDgLevL7GJAzyay7nz59i8aTMAQX5+dI+K9Gg+IiLVRYOQEJrUrQPAvr37XPu6VjbfwEDaD3Duez137txbuvcUERERqShTC4BV1YoVKwDo378/4eHhZcbvvvtuDMMgIyODHTt2lDtucnIyDoeDxo0bk5CQUGa8d+/eNG7cGIfDQXJy8lVjOTk5bNy4EXDup/jjPRCtVivjxo0DYMOGDeTm5l41fvToUVJSUgB46qmn3LZ5tUhtZ7fbmT9/PgAx/RLxDQz0WC4FBQWsTF6J3W7HYhj0a9cWbzfspyoiUlPEtWoJOH+2b9u2zW3X7TxyNAAXLlxw7d8qIiIiUplqfAEwLy+PAwcOANdfmhweHu6atXgrN3/bt28HoEuXLhhG2c32DcOgS5cuVx1bavfu3a5PfK+XV+njRUVF7Nmz56qx0qJmREQELVq0KHfOInJ7Nm3axJkzZwDPdv91OBysXrOanJwcALpHRVLXg8VIEZHqqG5gIK3CndsmpKWlcfHSRbdct/3AQXiX7A+dlJTklmuKiIhI7VahPQAjI51LzAzDIC0trczjFfXjeGY4fvw4DocDgJYtW173uJYtW3Ls2DGOHTtWrrgOh4Pjx4/fNG5pce7HcUv/XqdOHUJDQ695bmhoKKGhoWRmZpKenk63bt1cY6UFwcjISHJycvjmm29Yt24d58+fJzAwkDZt2jBq1Ci6d+9eru9HRMpn7ty5AFi8vOgwaLDH8ti5aycnjjub/0Q0CCeqUUOP5SIiUp11atmS9PMXsDscbN26lUEDB1X6NX0DAmg/cDCpC+Yxb948/u///k+rOURERKRSVagAeOTIEYAys96OHDmCYRiugtututYsuttVulE/4Npj71pKxy5eLN8nv3l5eeTn55c7bl5eHnl5efj7+191nRudWzqemZlZJq9Tp065vv7d737H6dOnsVqt+Pv7k5WVxaZNm9i0aRN33nknjz/++E2/nylTpjB16tTrjj/wwAM8+OCDN41TURaLxfXfunXrVtp1pHKVvoZDQ0Mr/HOgKnM4HCxYsACAmD79qNuggUfyOHnyJFu3bgUgNDCAXtFt8Kqkpb8/3p5AqierpcZP+K819Jo0X2hgAG2aNGbfiZMcP3acixcv0qhRo0q7Xmlztp53jiN1wTwyMjJITU1l2LBhlXZNMY/uWWuOmn7fWlvoNSlSfhUqALZo0eKaxbrrPe5JpUU6cDbGuJ7Ssby8vHLFvfK48sQtPae0AFh6/o3OvVFepRtVL1++HMMweOKJJxg+fDi+vr5kZGQwadIkli9fTlJSElFRUQwYMOCG18nJyeHs2bPXHc/NzXXLmw7DMPTmpgaw1NBiw5YtW1wfgHQbNdojP+8uX77MkiVLwAFeVguJ7dvh7VVJr5mq9eNcboeey5pBz2Ol6dSyBWmnT1Nss7Nx40bGjh1badcq/d3RcfAQfPz9KczLY+bMma6mdFI96J615qip9621jV6TIjd3WzMAy/u4mK/0Uyq73c4999xz1Y1qWFgYzz33HMeOHePgwYN8++23Ny0ABgYG0uAGs5kCAgKw2Wym5H4tFovFNXvUbrdX2nWkchmGgcViwW6318hPUmfMmAGAYbHQadhwt3+PRcVFLFq0iIKCAgB6t21LqH8AVEYaBpUTV9xPz2XNoOexUvl5exPbrBnbj6Zz+vRpjh49Wil7LF+5UsbHz59OQ4axaU4SM2fOZMKECVoGXA3onrXmqOn3rbVFZb8mVVSUmqRCBcDqxK9kg2VwdswMCAi45nGlb6hLZ+jdzJXHlZ57o7g/Pqf06xude6O8/P39uXz5MgB33nlnmfMMw+DOO+/kzTff5NixY2RkZNxwufHDDz/Mww8/fN3x8+fPl3t5dEXUrVsXq9WK3W6v1OtI5bJardStW5fMzMxKLRh7SmkBMKp7T3yDQ276+jXbiuRk17YGHVo0o1lY3Ur5d77yRqcmPo+1imFgtVqw2e2gNzfVll6T7tG2SWP2nTxJQVEx69evJ7xBOBbDvJlBhmHg6+tLYWGhq9gQN2Ikm+YkkZGRwezZsxk0qPL3H5Tbo3vWmqOm37fWFpX9mqxfv77pMUU8pcbPd76y6HXlfoA/VjpW3n0D/P39XUW58sS98vgr87rRuTfKq/T84ODg6zYRKe1sDM4CnohU3P79+10dxeOGj3D79bdv30760aMANKsXRscWzd2eg4hITeZttdKhufNn66VLlzh44GClX7Nd4kB8Sj6cVjdgERERqUw1vgDYrFkz114r6enp1z2udKx58/K9qTYMw1Vgq0jc5lfcYGZlZV3z3MzMTDIzMwHKLEO51WUpVW1vRpHqZs6cOa6vOw0d7tZrHzt2jNTUVABCAwJIiG6Doc3ARERM16ZxI4L9natHUlNTKSoqqtTr+fj50XHwEADmz59PYWFhpV5PRESkOklLS+O3v/0tsbGxBAcHExQURLt27Xj00UdZuHCh67gVK1ZgGIar7pGSksI999xD48aNsVqtPPfccx76DqoWtxcA8/LyePvttxk/fjxjx47lr3/961Udbc3m7+9PmzZtAOcG/tdy/vx5jh07BkBcXFy5Y3fq1AnA1Y3zWkrftJceWyo2NhYvL68b5lUa19vbm3bt2l011rlzZ8DZEKC0SPhjx48fd30dHh5+3RxF5Obmzp0LQMu4ztRt0sRt1z13/hwrV64EwMfLi/6xMXhrLxIRkUphMQy6RLQCnI3kdu7cWenX7DxyNOD8ULj0572IiEht9+mnn9KuXTsmTJjAnj17KC4uxsfHh3379jF58mTuv//+a543ffp0+vXrx3fffUdeXp72cbyCqQXArVu30qlTJ+Li4li3bl2Z8aysLOLj43nxxRdJSkpi3rx5/P3vf6dTp043LKLdrtIGGCtXruTcuXNlxmfOnInD4SAsLIyOHTuWO27//v0xDIOTJ09e8/tdu3YtJ0+exDCMMk04AgIC6NGjB+Bc8vHjfSdsNptrKUjPnj3L7F2YkJDgWlL8/fffl7m2w+Fwnd+mTRvq1KlT7u9LRK525MgR15vAuOHu69KYlZXFsqXLsNlsWAyDfu3aEnzFvqYiImK+pmFhNAgNAWD37t3k5ORU6vXa9R+Ab2AgALNnz67Ua4mIiFQH33//Pb/85S8pKipi1KhRbNmyhby8PDIyMsjMzGT27NmMHHnt92VPPPEEd955J4cPH+bSpUvk5uZqBmAJUwuAM2bMYOfOnZw9e5b4+Pgy4y+99BI7duzA4XBc9efChQvcfffdlbah/vDhw2nUqBH5+fm8+uqrHD58GHA22JgxYwbz5s0DnI0wSmfllXriiScYO3Ys77zzTpm4ERER9O/fH4AJEyaQkpLi+p5SUlJ47733AGcB8lpLdh966CG8vLxIS0vjrbfecm1aevHiRd566y3S0tLw9vbmoYceKnNuUFAQ9913H+B8ccyZM8f173fx4kXeeecdDh48iGEYPPjggxX5ZxOREqU/IwDihrln/7+8vDyWLFniel3HR7eh4XX2+xQREfMYQNeICMD5geyWrddeqWEWHz8/OmgZsIiICABFRUU8++yzgLPh6Zw5c+jSpYtrPDg4mDvuuINp06Zd8/y4uDi++eYbWrVqBYCXl5fr69rO1C7A69evxzAMhg4dWmbPucuXLzNx4kQMw6B58+a8++67RERE8MEHH/DJJ59w9OhRpkyZwuOPP25mSoBzCe2f//xnXnrpJY4cOcKzzz5LQEAA+fn5rlbhY8aMYciQIbcc+6mnnuLUqVPs37+f1157DR8fHwDXzVtMTAxPPvnkNc9t0aIFzz77LO+++y6rVq1i9erVBAQEuD5p9vLy4tlnn72qmceVxo8fz/Hjx1m6dCmffvopn3/+Of7+/mRnZ+NwOLBYLPz85z+nW7dut/x9ich/lRYAm8S0I9wNvzyKiopYunQp2dnZAHSJaEmrcHUgExFxl7CgQCIbNuDQmbMcPnSYdjHtKrUTZJeRY9g8O4nMzEySk5MZOnRopV1LRESkKlu2bBnp6ekYhsFbb72FxXJr89ZeeOGFWz6ntjC1AHjixAmAq6qzpRYsWEB+fj6GYTBx4kQGDx4MwEcffURKSgo7duzg+++/r5QCIDiLbRMmTOC7775jw4YNnD9/nsDAQCIjIxk9evQ1ZyyWh7+/P2+88QZz584lOTmZkydPAhAVFcWAAQMYPXp0mVmFV0pMTKR58+bMnDmTnTt3kpWV5VqKPH78eCJKPoG+FsMwePbZZ+nRoweLFi0iLS2N3NxcwsLCaN++PXfeeadr/0MRqZhTp06xceNGwD3Lf+12O8nJya4O4G2bNCamadNKv66IiFytU8sWHD13HpvdzsaNG6+71MgM7fr3xzcwiIKcbJKSklQAFBGRWqt0e7WYmBgiIyNv+fyEhASzU6oxTC0Anj9/HoDGjRuXGUtOTnaNlRb/St17771s376d7du3m5lOGXXq1OHxxx+/pSLjf/7zn5se4+Xlxbhx4xg3blyF8oqMjOTFF1+s0LkAvXv3pnfv3hU+X0Sub/78+a6v44ZX/vLfdevWuT5IaFG/Hl0jW6nfr4iIBwT4+BDbrAk70o9z7tw5jh49SsuWLSvlWt6+fnQcMpRNSbNYsGABBQUF+Pr6Vsq1REREqrIzZ84AVPh3rhqgXp+p8yJLu9Fea7rlunXrMAyjTPEPcO2Pd60GHSIinlTa/bdBRCSN20RX6rW2pm4lLS3Neb3QEBKi22Co/Cci4jHtmjXFz8cbgM2bN5dp2mamLqPGAM4GUKUfnIuIiMitUdff6zO1AFjaqfbHhbzMzEzX7L5rzVTzK+lqWZk3VSIit+r8+fOsXbsWgE7DRpTZ29RM+/bvY8f2HQCEBgTQv10MVu1dISLiUV4WK51bOWcgZGdns2vXrkq7VkzffvgFBQOQlJRUadcRERGpyho1agTA0aNHPZxJzWPqu8vSziqrV6++6vG5c+e6mm306dOnzHkXLlwAIFQdLkWkClm4cKHrZ1fnEZW399OxY8dYv349AP4+Pgxo3w6fG+wdKiIi7hPRIJx6wUEA7Nixw9WgyWzevr50GjoMwLUMWEREpLYp3cNv7969HDp0yMPZ1CymFgD79euHw+Fg9uzZbNu2DXAuY/jHP/4BQJMmTejQoUOZ83bu3Alww4YXIiLuVrr8t26TpjTv0LFSrnHu3DlWrlwJDvC2WhnYIZZA7fskIlJlGBh0j3JuQm6z2di0aVOlXavzyNEAXL58mRUrVlTadURERKqqQYMG0aJFCxwOB88//7xrQobcPlMLgL/4xS+wWCzk5+fTs2dP4uPjiYqKYufOnRiGwS9+8Ytrnrds2TIMw6BTp05mpiMiUmFZWVnOwhwQV0nLfzOzMlm6bCk2mw2LYdA/NoY6JVspiIhI1VEvKIjWjRoCkJ6e7mrWZLa2ffriHxwCaBmwiIjUTl5eXrzzzjuA83fh2LFjSU1NdY1nZ2fz7bffctddd3kmwWrM1AJgp06d+P/+v/8Ph8NBUVERGzdu5MKFCzgcDjp27Mjvf//7Mufs2LGDvXv3AtC3b18z0xERqbAffviBoqIiAOIqYflvXl4eS5cspbCgEICEtm1oqG0QRESqrLhWLVzbM2zYuAFbJcxI8Pb1peMVy4Dz8/NNv4aIiEhVd9ddd/H+++9jtVqZN28eXbp0ISAggHr16hESEsJ9993H8uXLPZ1mtWP6DvN/+ctf+P777xk9ejTR0dF07dqVP/zhD6xcuRJ/f/8yx0+YMAEAh8PB8OHDzU5HRKRCSpf/BtcPJ6JLV1NjFxUVsXTpUtc+Ul0jW9Gyfn1TryEiIuby9fImrmULALIys9i7Z0+lXKfLKOcy4OzsbL25ERGRWuupp55i586d/OpXv6J169Y4HA6Ki4uJiYnhscceY8aMGZ5OsdqplF3mx44dy9ixY8t17CeffMInn3xSGWmIiFRITk4Oy5YtA6DTsOFYTGwlb7PbWbFiBRkZGQC0bdqYmCZNTIsvIiKVp3Xjhhw4fZpLObls27aNiMgIAvzN3bqhbe+++IeEkJeVRVJSEiNHVl4TKhERkaosJiaGjz766KbHDRgwAIfD4YaMqjfTZwCKiFR3y5cvJy8vD3Du/2emdWvXcurUKQBa1K9H14hWpsYXEZHKY2DQIyoKgOLiYjZv3mz6Nbx8fOg0zLkqZuHCha7fRyIiIiK3QwVAEZEfKV3+GxAaSpte8abF3bJli6uVfYPQEBKi22BgfnMRERGpPOEhwbRqEA7A4UOHOXX6lOnX6DJyDOCcka5lwCIiImIGFQBFRK5QUFDADz/8AECHwUOxenubEnfv3r3s3LkTgNCAAPq3i8Fq0Y9gEZHqqEurVniXbA+Rsi4Fm81mavy2vfsQUNIYSt2ARURExAyVsgcgQGpqKgsWLGDnzp1cvHixXF3MDMNg6dKllZWSiMhNrVy5ksuXLwMQN9ycfZfS09PZsGEDAAG+Pgzs0M7VSVJERKoffx9vOke0YuPBNC5fvsyOHTvo3LmzafGt3t50GjaClG+nu5YBX6uZnoiIiEh5mf4O9NSpUzz22GMsXrz4ls5zOBwYhpbCiYhnlS7/9Q0MJKZv39uOd/bsWVatWgWAt9XKgPaxBPj43nZcERHxrNaNGnD47FnOZ11m586dtGrVijp16pgWv8vI0aR8O53c3FyWLl3KmDFjTIstIiIitY+p68+ys7MZOHAgixcvxuFw3NIfERFPKy4uZuHChQC0HzAIb1+/24qXmZnJsmXLsNlsWAyD/rEx1Akwt1ukiIh4hoFBr9ZRWAwDu91OSkqKqfe00Qm9CSgpKGoZsIiIiNwuUwuAb7/9Nvv37wegWbNmfPjhhxw8eJD8/HzsdvtN/5i9f4qIyK1Yt24dGRkZwO0v/83Ly2PJkiUUFhYCkNC2DQ1L9nMSEZGaITQggHbNmgLOGd8HDx40LbbV29vVif6HH34gNzfXtNgiIiJS+5haAJw1axYAjRo1YuPGjfzqV78iMjISHx8fMy8jIlIpSpf/evv6Eps4oMJxioqKWLp0KTk5OQB0jWxFy/r1zUhRRESqmA7NmxHk55wxvnnzZvLy8kyL3WWUc9lvbm4uS5YsMS2uiIiI1D6mFgDT0tIwDIOnnnqKhg0bmhlaRKRS2e125s2bB0BMv0R8AwMrFsdhZ+Wqla6ZhG2bNCamSRPT8hQRkarFarHQs3UUAIWFhaxfv9602G3iEwisWxeA2bNnmxZXREREah9TC4B2ux2Atm3bmhlWRKTSbdq0iTNnzgAQN3xEheNsWL+BE8dPANCsXhhdI1uZkZ6IiFRhjeqEEtmwAeDs/H74yGFT4lq9vFxbUixevNg1s1xERETkVplaAGzZsiUAly9fNjOsiEilK539Z/HyosOgIRWKsWPnDtc+qPWCg+jTNhoDdTcXEakNuka0wr9k25sN6zeQl2/OUuAuo0YDWgYsIiIit8fLzGBjx45l9+7drFmzhscee8zM0CIilcbhcLj2/4tO6ENABZp1HD58mK1btgIQ5OdHYmw7rBZTP2MREZEqzMfLi55tokjetYeCggLWp6xnwIABtx23dc94gsLqkZ1xgaSkJO68887bT1ZERGqcPSWrkKqiqpxbbWJqAfCZZ57h448/5quvvuLFF18kJibGzPAiIpVix44dpKenAxVb/nv69GnWrFkDgK+3FwM7xOLn7W1qjiIiUvU1rVuXyIYNOHTmLOnp6Rw5coRWrVrdVkznMuARrJn2FUuWLCE7O5ugoCBzEhYRkRrjT1OnezoFqeJMnZ7SuHFjvv76a7y8vBg6dCgrV640M7yISKUonf1nGAadhg67pXMvX77MiuQV2O12LBYLibHtCC7pBikiIrXPlUuB169fb8pS4NJlwHl5eSxevPi244mIiEjtY+oMwFdeeQWAIUOGkJSUxMCBA+ncuTMJCQnUr18fSzmWw/31r381MyURkZsq3f8vsntPguvVL/d5RUVFLFu2jMKCQgB6R7ehfnBwpeQoIiLVg4+XFz1bR5G827kUOCUlhYEDBt5WzKgevQiuV5/LF86TlJTEXXfdZVK2IiJS3TkcDk+nINWEqQXAl19+GcNwbnhvGAYOh4PU1FRSU1PLHUMFQBFxp/3797sad3QeMbLc5zkcDlauXElmZiYAnVq2oEX9epWSo4iIVC9Nw/67FPhY+jEOHDhAdHR0heOVLgNePXUKS5cu1TJgERERuWWm71DvcDhcf37895v9ERFxtzlz5ri+7jSs/Pv/bdmyhRMnnJvZtgyvT/vmzUzPTUREqq9ukREE+voCsHHjRrIuZ91WvC6jxgCQn5+vZcAiIiJyy0ydAbh8+XIzw4mIVLrS/f9axnWhbuPG5Trn4MGD7Nq1C4CwoCDi27TGqLQMRUSkOvK2WundNprF23dQXFzMqpWrGDduXIXjRfXoSXD9cC6fP6dlwCIiInLLTC0AJiYmmhlORKRSHTlyhJ07dwLl7/579uxZUlJSAPD38SExNgZrOfY3FRGR2ic8JJj2zZux69hxzp8/z9atW+nQoUOFYlmsVjqPGMmqKZNZsmQJly9fJlj7zoqIiEg56V2riNRapbP/AOKG33z/v9y8XFas+G/H3/6xMa5OjyIiItfSsUVzwkr269u8ZTNnz52tcKyuo+8AoKCggPnz55uSn4iIiNQOKgCKSK1VWgBs2i6W8JYtb3is3W4neUUy+fn5AMS3iaKeNmAXEZGbsBgGvdu2cc4Wd8CqlasoLCysUKyIbt2p08i5XcWsWbPMTFNERKopwzCq1R/xnEovAB4/fpwffviBr7/+msmTJ1f25UREyuXkyZNs3rwZKN/y382bN3Pu3DkA2jZpTKvw8ErNT0REao4Qf3+6RUYAkJ2dzdq1aysUx2Kx0HW0sxlIcnIyFy5cMC1HERERqdlM3QPwSp999hlvvvkme/fuverxRx555Kq///3vfyc5OZnmzZszceLEykpHROQqt7L89/Dhw+zZswdw7ufUJaJVZaYmIiI1UOtGDTmblcWRs+dIT09n7969xMTE3HKcrmPGsmzipxQXFzN37lweffTRSshWRESqm5+8+hpNY9p5Oo1rOrF3D9P/8idPp1HrmV4AzMvL45577mHhwoUAOBwO19i1pnt2796dv/zlLxiGwYsvvki7dlXzf1gRqVlKC4ANo6Jo3Cb6usddvHSRdevWAeDn7U3fmLZYNHVdRERulWEQH92G81mXyc7PZ9OmTYSHh1OvXr1bCtO8Q0fCW7bi3NEjzJw5UwVAEREBoGlMO6K69/B0GlKFmb4E+JFHHmHBggU4HA5atmzJH//4R379619f9/ihQ4cSXrKU7soZOSIileXKTr43mv1XVFTEiuUrKC4uxjCgb7u2avohIiIV5u1lpV875wdJdrud5JXJFBbd2n6AhmHQ9Y6xAKxbt45Tp05VRqoiIiJSw5haAFy6dCnfffcdhmHwwAMPsG/fPv7+978zfPjw6ydgsTB06FAcDgerV682Mx0RkWsq/ZACblwATFmfwuXLlwHoEtGKBiEhbslPRERqrrpBQf/dD/ByNmvXrrvlGKXdgB0OB0lJSabmJyIiIjWTqQXAL774AoDIyEi++OILvL29y3VeXFwcgGuPLRGRylQ627he8+Y0i21/zWPS0tI4fOgwAM3qhdG2SRO35SciIjVb68aNaFHfufQ3/ehRdu/efUvnN24TTZOSfZ5mzpxpen4iIiJS85haAFyzZg2GYfDII4+Uu/gH0KTkjfXp06fNTEdEpIyLFy+6ZhvHDR95zb1JM7MyWb9+PQABvj70atMa7fonIiJmMYBebVoT7O8HwKbNmzh1+taW8pbOAty6dSuHDh0yO0URERGpYUwtAJ45cwaAtm3b3tJ5fn7Om5/8/Hwz0xERKWPhwoUUFxcD117+a7PZWJm80nVMn7bR+HpVWsN0ERGppbytVvq3a4eX1QIOWJm8kuzs7HKf323MHa6vv//++0rIUERERGoSUwuAVqsVALvdfkvnZWRkAFCnTh0z0xERKaN0+W9ow0a0jOtcZnzz5s1cvHgRgE4tWxCuff9ERKSShAb4kxDdBoCCggJWrFhBsa24XOfWa96ClnFdAJg1a1al5SgiIiI1g6kFwIYNGwJw8ODBWzpv8+bNADRv3tzMdERErnL58mVWrFgBQNzwEVgsV/8IPH78OHv37gWgQWgI7Zs3dXeKIiJSyzSvV4/2zZsBzg/FU9allPvcbiXdgPfu3au9tEVEROSGTC0A9u7dG4fDcUvLEHJycvj2228xDIO+ffuamY6IyFUWL15MYWEhUHb5b35BPmvXrgXAx8uLPm2jMbTzn4iIuEGnls1pXLcOAIcOHSp3Ma/LqNGuvWzVDERERERuxNQC4L333gs4NyP+7LPPynXOk08+6Vpu99BDD5mZjojIVUqX/wbXq09U9x5XjaWsS3HtQ9qzdRT+Pj5uz09ERGonA4M+baMJKtkXe9OmTZw6dfOmIKENGtK6Vzzg3AfQ4XBUap4iIiJSfZlaABwzZgzx8fE4HA5+/etf8/rrr193M+OtW7cyevRovvrqKwzDYOTIkfTs2dPMdEREXHJzc1m6dCkAHYcOw1KyZyk4Z1ukp6cD0Cq8Pi3q1/NIjiIiUnv5eHnRPzYGL6sFh8NBcnIymZmZNz2v25g7AThy5Ahbt26t7DRFRESkmjK1AAgwffp0GjVqRHFxMX/+859p0KABzz33nGu8R48eNG7cmO7du7Nw4UIcDgfNmzfniy++MDsVERGX5cuXk5ubC1y9/DcnN4f169cD4O/jQ/eoSI/kJyIiUicggN5towEoLCxk6bKl5Bfk3/CcuOEjsJR0q9cyYBEREbke0wuAzZs3Z/369a6ZgPn5+aSnp7v2J9myZQtnzpzB4XDgcDjo1asXa9eupX79+manIiLiUrr8NyA0lOj4BNfja9espaioCID46Nb4lLyJEhER8YRmYWF0iWgFQPblbFYsX4HNZrvu8YF169KuX3/AuQz4RseKiIhUJwcOHODJJ58kOjqagIAAgoOD6dy5M//7v/97zVnyDoeDL7/8kiFDhhAeHo63tzf16tUjJiaGhx9+mG+//fa610pNTeXxxx+ndevWBAQEUKdOHTp06MBTTz3l2iu+uquUd7rNmzdn7dq1zJkzh0mTJrFy5UrOnz/vGg8KCiIxMZFHH32Ue+65pzJSEBFxKSgoYNGiRQB0GDwUq7c3APv27XPtsdSmcSMa16njqRRFRERcYpo2ISsvj7TTZzh79iwpKSn06dPnusd3HX0Hu5Yv48yZMzc9VkREpDqYOHEiTz75pGuyRkBAAAUFBWzbto1t27YxadIkFi9eTFRUlOucRx99lC+//NL195CQEHJycsjIyGDfvn2sWLHC1bviSi+//DKvvPKKay/dwMBADMNg165d7Nq1i7Vr15Kamlq537AbmD4D8Ep33HEHM2bM4OzZs2RnZ3P8+HEuXbpEVlYWc+bMUfFPRNxi5cqVXL58Gfjv8t+cnBw2b94MQLC/H10iWnosPxERkSsZQI+oSBqGhgKQlpbGjp07rnt8xyHD8Pb1BbQMWEREqr/58+fzi1/8Am9vb1599VVOnTpFTk4Oubm5rFmzhu7du3P48GHGjx+P3W4HYNWqVXz55ZdYLBbefPNNLl26RGZmJnl5eZw5c4bp06czcuTIMtd69913+d///V8cDgePPPII+/btIzs7m4sXL3LhwgWmTp1KQkJCmfOqo0otAF4pICCAJk2aEBIS4q5LiogA/13+6xsYSEzfvgCsX7+e4uJiAHq1aY2XxXrd80VERNzNYhj0a9eWEH9nZ+CtW7Zy5MiRax7rFxRE+0FDAJgzZ45rtoSIiEh1Y7PZeOaZZ3A4HEyZMoU///nPNGrUCAAvLy969+7NokWLaNy4Mdu3b+f7778HYN26dQAMHTqU559/ntCSD9EMw6BBgwbcd999fPrpp1ddKyMjg5deegmAZ555hkmTJhEdHe0aDwsL44EHHuDDDz+s7G/bLdxWABQR8YTi4mIWLlwIQPuBg/H29ePwkcMcP34ccC79baAPJkREpAry8fIisX2sa3/a1atXc/r06Wse223MHQBcvHiRFStWuCtFERERUyUnJ3Po0CGioqK46667rnlMWFiYazbfDz/8AOCabHbu3DnXrMCb+fbbb8nJySEoKIi///3vJmRftVVoD8BXXnnF7Dxc/vrXv1ZabBGpfdauXUtGRgYAccNGUFBQwMYNGwFn19/OrbT0V0REqq5gPz8SY9uxdOcu7HY7y5cvZ8SIEdStW/eq42IHDMQ3MIiCnGxmzZrF0KFDPZSxiIhIxZU23Dh+/Lhr5t+1ZGdnA5Ceng7A4MGD8fHxYcuWLSQmJvKLX/yCQYMG0axZs+vGKJ012K9fP4KDg836FqqsChUAX375ZVdXX7OpACgiZipd/uvt60ts4gA2bdpEfn4+AD1aR+Jt1dJfERGp2sJDgunTNppVe/ZSVFTE0qVLGTlyJIGBga5jvH39iBs+gg0zZzBv3jxycnKuGhcREakOSps0FhQUcObMmZsen5ubC0CbNm346KOPePrpp1m9ejWrV68GoFmzZgwbNozHHnuMviXbQZUqjd+yZe2YFFLhJcAOh+Omf2523I/HRUTMZLfbmTdvHgDt+g/gQmYmaWlpALSoX49mYWGeTE9ERKTcmtcLo0frSMD5Zmfp0qUUFBZedUyPO+9yjZdufyEiIlKd2Gw2AIYPH16uutOV21489thjHD58mAkTJjB+/HgaNmzI8ePH+eyzz+jXrx9PPfWUh76rqqFCMwCXL19+w/EJEyYwc+ZMLBYLw4YNY/DgwbRu3ZrAwEBycnI4ePAgS5cu5YcffsButzN+/HiefvrpCn0DIiLXs2HDBs6ePQtAh6HDSFmfAjj3VOoWFenJ1ERERG5Zm0aNyC0oZNex41y6dInly5cxdMhQrCWz2dvEJxDSoAFZZ88yY8YM7r77bg9nLCIicmsaNmwI/Hdp761q0KABTz/9tKvGtG3bNt58802+/PJLPvzwQ8aMGcOoUaMAXEuMjx49akLmVV+FCoCJiYnXHfvd737HrFmzaNeuHV9//TUdO3a85nHPP/88O3fu5Cc/+QkzZ86kRYsWvPnmmxVJR0TkmkqX/1q9vbE0akz2Qefsvy4RrfD39vZkaiIiIhXSqWUL8goLOXTmLGfPnGXV6tUk9u+PYRhYrFa6jRnL8s/+w/Llyzl37hzh4eGeTllERKTcevfuDcDevXtJS0sjKirqtuLFxcUxefJkUlNT2bFjBytWrHAVABMSEvjiiy9YtWoVly9frvH7AJraBXjx4sW8++67hIWFsWzZsusW/0p16NCBZcuWUbduXd555x2WLFliZjoiUos5HA7X8t+onvHsP3wYgPohwUQ21JshERGpngygZ+soGtetA0D60aNs2LjBNd597DjAuYQqKSnJ/QmKiIjchkGDBtGyZUscDge/+93vbtjRt6ioyNUMpPBH22L8mJ+fH+DcW7DUPffcQ2BgINnZ2bz00ksmZF+1mVoA/OijjzAMg8cff9w1bfNmGjZsyOOPP47D4eDjjz82Mx0RqcVSU1M5fvw4AAFRrbHbnL84ekRFYlA5TYxERETcwWIY9I1pS1hQEAD79u5jx44dADRr34GGUa0BmDFjhsdyFBERqQhvb28++OADLBYLc+bMYfjw4aSkpLgKgXa7nd27d/PGG28QHR1NamoqAL/5zW944IEHSEpKIiMjwxXvwoUL/OUvf2Hjxo0AjBw50jUWFhbG3/72N8C5ld3PfvYzDhw44BrPyMjgs88+4/HHH6/sb9stKrQE+Ho2bdoEQOfOnW/pvC5dugDO/bpERMwwZ84cAAyLFUcD5wcS0Y0bUVcdEUVEpAbwtloZ0L4di7fv4HJePlu3bsXPz482bdrQ/c5xzHvrX2zevJlDhw4RGal9b0VEpPoYNWoUU6ZM4fHHH2fJkiUsWbIEX19fgoKCyMrKoqioyHWsYTgndxQVFfH111/z9ddfAxAcHIxhGGRlZbmO/c1vfsOIESOuutZzzz3H2bNnef3115k0aRKTJk0iKCgILy8vLl26BDiXEdcEps4ALN1s/8opleVRenzp+SIit8PhcLj2/wuNjMQ7IBA/b286tWzh4cxERETM4+ftzcD27fEr2dd2Xco6jh07Rvc77nQd891333kqPRERkQp74IEHOHDgAH/4wx/o3Lkzvr6+XLp0ieDgYOLj43n++edZvXo1ffr0AeAvf/kL77zzDmPHjiU6OhqAvLw8mjZtyvjx45k/fz7vvffeNa/12muvsX79en7605/SsmVLioqKMAyDjh078pvf/KbGrFY1dQZg3bp1OXPmDMnJyTz66KPlPi85ORmAOnXqmJmOiNRSu3fv5nDJnn8hbdoCzsYfPl6m/sgTERHxuCA/XwZ2iGXJ9p0U2WysXLmSIUOGENmtO4c2b2LGjBm8+OKLrhkSIiIi1UXTpk15/fXXef311296bFRUFM8++yzPPvtsha7Vs2dPJk+eXKFzqwtTZwDGx8fjcDiYMmUK69atK9c5KSkpTJkyBcMwiI+PNzMdEamlZs+e7fzCMKjbLpb6IcG0aqDGHyIiUjPVDQykf2wMFsPAZrOxfPlyYocOB+DQoUNs3brVwxmKiIiIp5laAPzVr34FOLuODR8+nI8++uiqtdlXKioq4uOPP2bEiBEUFxcD8OSTT5qZjojUQg6Hw1UADGreEu+g4JLGHyIiIjVXw9BQ+sQ4lzwVFhZy3ssHa8nM92+//daTqYmIiEgVYOp6uOHDh/P4448zceJEcnJy+M1vfsOf/vQn+vTpQ+vWrQkICCA3N5eDBw+yZs0aMjMzcTgcADz++OMMGzbMzHREpBbas2cPBw8eBCAstj2tGzVU4w8REakVmterR4/WkWw8eIhii4W6bWM4v2sn33//Pa+88greJXsFioiISO1j+oZYn3zyCQEBAbz33ns4HA4uXbrE/PnzyxxXWvgzDINnnnmGt99+2+xURKQWSkpKKvnKoH6HDnRU4w8REalF2jRqRH5hETvSjxHSrj3nd+3k/PnzJCcnM2TIEE+nJyIiIh5i6hJgcBb03n33XVauXMm4cePw8fHB4XCU+ePr68tdd93FqlWreOedd7QxsYiYYurUqQAEtWhBl9hY/DXbQUREapkOLZrTplFD6rRpi8XHF9AyYBERkdqu0lpi9unThz59+lBYWMi2bds4efIk2dnZBAUF0bRpUzp16oSPj09lXV5EaqHU1FROnz4NQMOOccQ0aeLhjERERNzPALq3jiSvqIijse25kLqFpKQk/vWvfxEcHOzp9ERERMQDKq0AWMrHx4cePXpU9mVERHj55ZddXw8YMRKrxfRJziIiItWCgUGfttGc7BXPhdQt2Gw2fvnLXzJt2jRPpyYiIiIeoHfHIlIjnD59mrVr1wJQp1UEsW2jPZyRiIiIZ1ktFsbdcQe+ISEALFmyhPfff9/DWYmIiIgnqAAoIjXCn//8Z1dzoe4DB6FdRUVERMDPx4ceQ4a6/v7yyy8zffp0D2YkIiIinqACoIhUe2lpacyePdv1995XvNERERGp7XoNHXbV35999lkWL17soWxERETEE1QAFJFq74033nDN/mvWNoY64eEezkhERKTqaBIZRaOWrQCwGAY2m40nHn+cTZs2eTYxERERcZtKbwIiIlKZtm3bxvfff+/6e7cBAz2XjIiISBVkGAbdhw5j7n8+we5w4GWxkJuXx4MPPsjcuXOJjta+uSIi1d2JvXs8ncJ1VeXcahMVAEWkWnvttdeu+nunfv09lImIiEjV1X3wEOZ99h8cdjuJse1YunMXFy9e5L777mP+/Pk0adLE0ymKiMhtmP6XP3k6BanitARYRKqtNWvWsGzZMtffW7ZrR90GDTyYkYiISNUUUq8ebbt2A2B7+jH+cvddAJw4cYL77ruPixcvejI9ERERqWQqAIpIteRwOPjb3/521WNx/RI9lI2IiEjV16OkGci5rCyiGjXkN8OdTbP27dvHww8/TG5urifTExGRCnA4HNXqj3iOCoAiUi0tXLiwzOblWv4rIiJyfe1798EvIBCA71I28Ps7x3Bf73gANmzYwC9/+UuKi4s9maKIiIhUEhUARaTasdvtvPHGGwBYLc4fYy3axhDWsKEn0xIREanSfHx9iUt0zpb/Ydt2svLyeP3BnzC4Y3sAFi1axAsvvKAZGiIiIjWQCoAiUu3MnTuX3bt3A2Cz2wGI66/lvyIiIjdTugy4oLiYeZu34mW18v4Tj9EtMgKAqVOnlmmwJSIiItWfCoAiUq3Y7Xb+9a9/ARDk6+t6PE7Lf0VERG4qon0H6pV0/J2RsgEAfx8fPnvql7Rp3AiAd955h+nTp3ssRxERETGfCoAiUq3MmTOHPXv2ABDk7w9A87ZtCWvUyJNpiYiIVAuGYdB9iLP5x+ZDhzl89iwAdQIDmfz0k4SHhADw/PPPs2HDBo/lKSIiIuZSAVBEqo0rZ//VDw7i9KVLgGb/iYiI3IoeQ4a5vv4uZaPr6yZhdfn010/g6+VFYWEhP/vZzzh+/LgnUhQRERGTqQAoItXG7Nmz2bt3LwCdW7VyPR7XT/v/iYiIlFdYo0ZEdYoDYOb6DdhL9tMF6BLRin/89EEAzp07x8MPP0x2drZH8hQRERHzqAAoItXClbP/GtUJ5dTFSwA0axNNvcaNPZiZiIhI9VPaDORExkVSDhy8amxcz+78ZoRzfNeuXTz99NNXFQlFRESk+lEBUESqhdmzZ7Nv3z4A7u+TwK6SJUlx/bX8V0RE5FZ16tcfH18/AL5LKbvX34t3jGJ4504AzJs3jzfeeMOt+YmIiIi5VAAUkSrvx7P/vCxW11jn/lr+KyIicqv8AgLo2LcvAPO3ppKTX3DVuMVi4e1Hf0pss6YAvP3228ydO9fteYqIiIg5VAAUkSpvwYIFrtl/Tw0fyqJt2wFo1roN9Ro38WRqIiIi1VbpMuDcgkIWpm4rMx7o58t/nvwFYUGBADzzzDMcOHDArTmKiIiIOVQAFJEqzeFw8M477wAQHhJC77bR7Eg/BjiXL4mIiEjFtI7rTJ364QDMuMYyYICmYWFMePxnWAyD7Oxsfvazn6kpiIiISDWkAqCIVGkrV64kNTUVgCcGD2Tpjp2usTgt/xUREakwi9VKtyFDAFi3/wAnMjKueVzfmLb8vzvHALB//36ee+45HA6H2/IUERGR26cCoIhUaaWz/0L8/Xm4fx/mbNoCQNPWrQlv2tSDmYmIiFR/PYYOB5wz7q83CxDg18OGuJqCJCUl8fHHH7slPxERETGHCoAiUmVt3ryZ1atXA/DogP6cz7rMzmPO7r+dEwd4MDMREZGaoUHz5rSKjQXg27Xrsdvt1zzOMAzefOQhIhs0AODll18mJSXFbXmKiIjI7VEBUESqrHfffRcAP29vHhvYnzmbt7jGOvcf4KGsREREapaew0cCcOzCBdbtP3jd44L9/fn4V48T4OuDzWbjV7/6FRnXWTYsIiIiVYuXpxOQ6sFqtdbIa4m5Sp87M57D3bt3s2DBAgAe7NeH+iEhzN28FYAWMTHUa6Luv25hGJ7OQG6DccV/HXouawY9j9VWVX49dh4wkO8/fJ/C/Hy+XZdC33Ztr3ts26ZN+NsD9/H8F1M4efIkzz33HFOmTMGoYt+TO+ietXoz875VqgY9lyI3pgKglEvdunXdch2r1eq2a0nlCQkJue0YH330EQDeVitPjxrB0QsZ7D1xEoCuAwdhtWoCc6Uz0L9zDWHR81gz6DVZI1TF12NgcBBdBgxk/cIFLNi6jf+z2QgNCLju8Q8l9idlfxrfrF3HggULmDJlCr/97W/dmLHn6Z615jDjvlU8T69JkZtTAVDK5eLFi5UaPyQkBKvVis1mIysrq1KvJZXHarUSEhJCVlYWNputwnGOHj3KtGnTALirVw/qBwUyeXmya7xTv0RstmvvUSS3z2qxlExRAdt19oKS6sHAWWyw2+yoX2f1pddkzVDVX489h49k/cIF5BcV8c2qNTwyoP8Nj//f++5mU1oah86c5fe//z2dOnUiLi7OTdl6ju5Zaw6z7lvFsyr7NamiotQkKgBKubjzl6J+AVd/Npvttp7Hf//739hsNgzD4NdDB2O325mzaTMAER06UKd+fXBUxbdPNZD+nau10mWGDtBzWVPoeay2qvrrsVVsLA2aNefs8WNMX5vCTxP73fD4AF8f3nv8Z9z1j7coKCzk5z//OcuWLSMoKMhNGXue7llrhtu9b5WqQ8+jyI1VvTUIIlKrnT17lqlTpwIwskscUY0asufESdLOnAWgc+JAT6YnIiJSIxmGQc8RIwDYkX6M3cdP3PSc9s2b8dLd4wA4fPgw//M//1OZKYqIiMhtUAFQRKqUiRMnUlBQAMBTw4YAMHeTs/uvYbEQ1+/GS5JERESkYroPGYbF4nx78M3alHKd80hiP4Z37uQ855tvmDt3bqXlJyIiIhWnAqCIVBm5ubl88cUXAMRHt6ZjyxY4HA7mbHYWAKM6diIkLMyDGYqIiNRcIWFhxPaKB2DWho0UFBXd9BzDMHjjofsJDwkG4IUXXuDMmTOVmqeIiIjcOhUARaTKmD59OhkZGQD8csggwLkMKf38BQA6Jw7wVGoiIiK1Qs8RIwG4lJPLD9t2lOucsKAg/u/hBwHIyMjgueeew1EF9zkUERGpzVQAFJEqwW6389FHHwEQ1bABA9vHAjCnZPmvxWKhk5b/ioiIVKp2PXsRXDLbvrzLgAEGd2zPg317A7BkyRK+/PLLSslPREREKkYFQBGpEhYtWsShQ4cAeGLwQCwWCw6Hg3lbtgLQpms3gkJDPZmiiIhIjWe1WukxdBgAq/bu4/iFjHKf++e776JleH0A/vKXv7h+r4uIiIjnqQAoIlXCBx98AEC9oCDG9+oBwJbDRziRcRGALlr+KyIi4hY9hzm7ATscDmasW1/u8wL9fHnr0YexGAa5ubk8/fTT2Gy2ykpTREREboEKgCLicVu3biUlxbnM6JHEfvj5+AD/Xf5r9fKiQ+8+HstPRESkNmnQvDkRHToA8O269djt9nKf2z0qkieHDQFg48aNTJw4sVJyFBERkVujAqCIeNyHH34IgK+3Nz9N7AuAzW53Lf9t2607AcHBHstPRESktulV0gzkeEYGa/cduKVznx09gjaNGwHw97//naNHj5qen4iIiNwaFQBFxKOOHz/O7NmzAbi7Vw/qlRT6Nh5M42xmFqDuvyIiIu4W1y8RX39/AKavXXdL5/p6e/OPhx/AKFkK/MILL6grsIiIiIepACgiHvXJJ5+49gd6fPBA1+NzNjtn/3n5+NAhobdHchMREamtfP396TzA+Xt5Uep2LuXk3NL5XSMj+PnARACSk5OZOnWq6TmKiIhI+akAKCIek5WVxZdffgnA4I7tad2oIQDFNhsLtqQC0K5nL/wCAz2VooiISK1Vugy4oLiYmes33vL5L44dTYv69QD461//yunTp03NT0RERMpPBUAR8ZipU6eSnZ0NwC+GDHI9nrL/IBdKHlf3XxEREc9oGdOOxhERAExdvfaWl/EG+PryxkMPAM4P/f7f//t/WgosIiLiISoAiohH2Gw2V2fA2GZNiW/T2jU2Z7Oz+6+Prx/tevbySH4iIiK1nWEYxI8aA8CBU6fZlHbolmP0iYnm/j4JACxYsID58+ebmqOIiIiUjwqAIuIRS5cu5ciRIwD8bGB/DMMAoMhmY2HqNgBi4+NdG5CLiIiI+3UfPARvX18Avlq1pkIx/jT+TsJDQpxf/+lPrtn/IiIi4j4qAIqIR3z66acA1A0M5M7u3VyPr9qzl0s5uQB0Thx4zXNFRETEPfyDguhcsh3H/C2pt9wMBCA0IIC/3HMXACdPnuRf//qXmSmKiIhIOagAKCJut3//flasWAHAA30T8PPxcY0lbdwMgF9gIO169vREeiIiInKFhNHOZcAFxcV8l7KhQjHGdu9Kn7bRAHz00Ufs3r3btPxERETk5lQAFBG3+89//gOA1WLh4f59XY/nFhTww7btAHTq2w/vKwqDIiIi4hktY9rRODISqFgzEHDuJ/i3B+7Dx8uKzWbj97//PXa73exURURE5DpUABQRt8rKymL69OkADIvrSNOwMNfYku07yS0oBKDrwEHXPF9ERETcyzAMEkaNBuDg6TNsPHjrzUAAIhs24NfDhgCwYcMGpk2bZlqOIiIicmMqAIqIW02dOpXcXOcef48NTLxqbPYm5/Lf4Lp1aR3X2d2piYiIyHV0u6IZyNTVFWsGAvCb4UNpUb8eAK+88goXLlwwJT8RERG5MRUARcRtbDYbEydOBCC2WVN6to5yjV3KyWHFrj0AdE4cgMVq9UiOIiIiUpZ/YBBdBjibc83fksrF7FtvBgLg5+PDq/ffC0BGRgZvvPGGaTmKiIjI9akAKCJus3TpUo4cOQLAowP6YxiGa2zB1m0U2WwAdB042BPpiYiIyA0kjLqiGcj6ijUDARjQPpYRneMAmDx5Mjt37jQlPxEREbk+FQBFxG0+/fRTAOoEBjCuR7erxr7fuAmAeo0b0yImxu25iYiIyI21iIm57WYgpV66exy+Xl7Y7XZeeuml24olIiIiN6cCoIi4xf79+1mxYgUAD/btjd8VHX5PX7rE+gNpAHQZMOiqmYEiIiJSNRiGQe+SWYBpp8+w4WBahWO1qF+PXwxxNvxau3Ytc+bMMSVHERERuTYVAEXELT777DMALIbBw/37XjU2Z9MW1yf/XQep+6+IiEhV1XXwYHx8/QDnLMDb8dTwoTQMDQXg5ZdfJi8v77bzExERkWtTAVBEKl12djbffPMNAEM7daRpWNhV40kbnd1/m0RG0ahlK3enJyIiIuXkHxhE5wEDAFhwG81AAAL9fPnj+LEAHDt2jA8++MCMFEVEROQaVAAUkUo3a9YsLl++DMDD/ftcNXbozFl2pB8DoMvAgW7PTURERG6NWc1AAMb16E7XyFYAvPvuu5w4ceJ20xMREZFrUAFQRCqVw+FwLf9tFR5O35i2V43PLpn9B879/0RERKRqaxETQ5PIKACmrlpzWw08DMPg5XvvBiAvL4+//e1vpuQoIiIiV1MBUEQq1ebNm9m5cycAD/Xvg8Xy3x87DofDtfw3okMHwho29EiOIiIiUn6GYZAwuqQZyJmzrNt/4LbixbVqyb0JvQCYMWMG27Ztu+0cRURE5GoqAIpIpfr8888B8PXy4t74XleN7Uw/xqGzZwHoOnCw23MTERGRiuk2aDC+/v4AfLly9W3He3HsaPy8vQFnQ5DbmVUoIiIiZakAKCKVJiMjg6SkJADGdOtK3aDAq8a/L5n9Z7FYiOvX3+35iYiISMX4BQbSfchQABalbuf0pUu3Fa9RnTo8Mdi5F/Dq1atZvHjx7aYoIiIiV1ABUEQqzbRp0ygoKADgp4l9rxqz2e3M2bQFgOhu3QmqU8fd6YmIiMht6D3G2cHXZrczbfXa247362GDqRcUBMArr7xCcXHxbccUERERJxUARaRS2O12vvjiCwDaN29G51YtrxrfcDCNM5mZAHQdqOYfIiIi1U3jiAgiO3YCYOrqtRTZbLcVL9jfn2dHjwBg3759TJs27bZzFBEREScVAEWkUiQnJ3PkyBEAftq/L4ZhXDVe2vzDy8eHDr37uDs9ERERMUHfsXcCcDYzix9St992vAf79SGyQQMA3njjDXJycm47poiIiKgAKCKVpHT2X7CfH3f26HbVWEFREfO3pALQIaE3fgEBbs5OREREzNChdx+Cw8IAmLxy1W3H87Za+Z+77gDg7NmzfPjhh7cdU0RERFQAFJFKcOLECRYuXAjA3fE9CfD1vWp8xa49ZObmAlr+KyIiUp15eXuTMGo0ACn7D7L/5Knbjjk8rhPdoyIBmDBhAufOnbvtmCIiIrWdCoAiYrpJkyZht9sBeKh/2eW9M9dvBCAgOJiYHj3dmpuIiIiYK37UaCwW59uKL1euvu14hmHwx7ucDUZyc3P597//fdsxRUREajsVAEXEVEVFRUyZMgWA+DatiW7c+KrxzJxclu3cCUDnxIF4eXu7PUcRERExT5364a79fGeu30B2fv5tx+weFcngju0B+Pzzzzlx4sRtxxQREanNVAAUEVMlJSVx+vRpAB7u37fM+LwtWyksdnYJ7D5kiFtzExERkcrR5w5nM5Ds/AJmlcz0v10vjh0DQEFBAW+++aYpMUVERGorFQBFxFSffPIJAPWDgxneuVOZ8dLlv/WaNKFlu1i35iYiIiKVo3XnzjRo3gJwLgN2OBy3HTO2WVPGdu8KwNSpU0lLS7vtmCIiIrWVCoAiYpqjR4+yePFiAO5N6IWPl9dV4+nnL7Ax7RAA3QYNwTAMt+coIiIi5jMMgz53OPft23fyFBsPHjIl7u/GjMJqsWCz2fjHP/5hSkwREZHaSAVAETFN6d5/APf3SSgz/v2GTa6vuw3W8l8REZGapPvQofj4+QEwOXmVKTEjGzbg3oReAMycOZOdJfsIi4iIyK1RAVBETFFcXMzUqVMB6N22Da0ahF817nA4XHsCtYqNJbxpU7fnKCIiIpXHPzDI9QHfgq2pnM3MMiXus6NG4ONlBeCNN94wJaaIiEhtowKgiJhiyZIlnDp1CoAH+/YpM77taDqHzp4FoNvgoW7NTURERNyjdBlwsd3O12vWmRKzSVhdftq/HwCLFi1i40ZzmoyIiIjUJioAiogpJk+eDEBYUOA1m3+Uzv6zennROTHRrbmJiIiIezSJjCKiQwcAvlq1miKbzZS4Tw0fSoCvDwCvvfaaKTFFRERqExUAReS2nTx5kqVLlwJwb+8EfL29rxovstmYs2kLAO169CQwJNTtOYqIiIh79L3jTgBOX8rkh9TtpsSsHxLMzwcOAGD16tWsXr3alLgiIiK1hQqAInLbpk6dit1uB+DhxH5lxlfu3sOF7GwAug3R8l8REZGarFO//oTUqwfA58uTTYv7y6GDCPH3B+Cf//ynaXFFRERqAxUAReS22Gw2vvrqKwB6tI4kuknjMsfMWu/s/usXGEhsr3i35iciIiLuZfXyos8Y516AG9MOsSP9mClxQwMC+Pkg5zYia9euZc2aNabEFRERqQ1UABSR27J8+XKOHz8OwAN9e5cZz8rL44ftOwDo3H8A3j4+bs1PRERE3C9+1GisJVuCfGHiLMCfDxxAsJ8fAP/4xz9MiysiIlLTqQAoIrdlypQpAIT4+zO6a5cy4wu2plJQVARA9yFD3JqbiIiIeEZw3bp0HTAQgNmbNnM+67IpcUMDA/j5oAGAZgGKiIjcChUARaTCzpw5w6JFiwAY17M7/teY3Ve6/Lduw4a0at/BrfmJiIiI5/S98y4ACottTF291rS4jw/SLEAREZFbpQKgiFTY119/TXFxMXDt5b8nMy6ScuAgAN0GDcFi0Y8cERGR2qJ5dDQRJR/+fblyFUU2mylxNQtQRETk1unduIhUiN1udy3/7dyqJbHNmpY5JmnjJhwOBwDd1f1XRESk1uk3zjkL8GxmFgu2pJoW98pZgOoILCIicnMqAIpIhaxevZojR44AcH+fhDLjDoeDmSXLf5u3bUuD5s3dmZ6IiIhUAR379CW0fn0APl9hXjOQ0MAAHivpCLxmzRrNAhQREbkJFQBFpEK+/PJLAAJ9fRnbvVuZ8R3px9h/6hQA3Qdr9p+IiEhtZPXyos8dYwHYcugI244cNS22ZgGKiIiUnwqAInLLLly4wPz58wG4s0c3Av18yxzz7br1gPPGv8vAQW7NT0RERKqO+JGj8fL2BuCLFStNi1snMPCqWYBr15rXaERERKSmUQFQRG7ZN998Q2FhIXDt5h8FRUUkbdwMQGx8AkGhoW7NT0RERKqOoDp16DpoMABzNm3hbGaWabGfGDSQoJIPIt9++23T4oqIiNQ0KgCKyC1xOBxMnjwZgNhmTenYouzefou37yQzNxeAnsOGuzU/ERERqXr63jkOgCKbjWmrzduvLzQwgJ/27wfAihUr2Lp1q2mxRUREahIVAEXklmzYsIGDBw8Cztl/hmGUOWbGuhQAguvWJaZ7D7fmJyIiIlVPs9ZtiOzQEYAvV66hsLjYtNiPDx6Ab8kS43feece0uCIiIjWJCoAickumTp0KgK+3N3f2KNv848ylS6zYtQeAboOHYPXycmt+IiIiUjX1G3cXAOeyspi/JdW0uOEhITzQJwGA+fPns2fPHtNii4iI1BQqAIpIuWVnZ/P9998DMLJLHKEBAWWOmbFuPXaHA4DuQ4e5Mz0RERGpwjr06Uud+uEAfLZsBY6S+wUz/GroYLwszrc27777rmlxRUREagoVAEWk3GbPnk1uyd5+9yXElxl3OBxMX+3swNesTTRNIiLdmp+IiIhUXVarlb7jxgGw7Wg6mw4dNi12k7C6jI/vCcCsWbM4fNi82CIiIjWBCoAiUm6ly3+b1QsjIbp1mfHtR9PZd/IUAD3U/ENERER+JH7kaHx8/QCYuHS5qbGfGj4Ei2Fgt9uZMGGCqbFFRESqOxUARaRc0tLSWL9+PQD3JfTCYin74+Pbdc5xq5cXXQcOdGt+IiIiUvUFBAfTc8QIABalbif93HnTYkc0aMCYbl0A+Prrrzl58qRpsUVERKo7FQBFpFxKZ/8ZhsHd8b3KjOcXFZG0cTMA7RN6ExgS6tb8REREpHroN248hmFgdzj4fHmyqbF/M8K5/3BRURHvv/++qbFFRESqMxUAReSmiouLmT59OgB9Y6JpVi+szDFLt+8ks2R/QC3/FRERkesJb9qU9vHOrr3T16aQlZdnWuyYpk0Y2qkDAF9++SXnzp0zLbaIiEh1pgKgiNzUsmXLOHPmDHDt5h8A35Qs/w2uW5eY7j3clpuIiIhUP4l33wtATkEBX69ZZ2rsp0c6P4jMy8vj448/NjW2iIhIdaUCoIjc1LRp0wAI8fdnWOdOZcbPXMpk5e49AHQfMhSrl5db8xMREZHqJbJjR5q1bgPAF8uTKbbZTIvduVVL+sa0BeCzzz4jMzPTtNgiIiLVlQqAInJD58+fZ9GiRQCM69kdP2/vMsfM2rARu8MBQM/hI9yan4iIiFQ/hmGQePc9AJzIuMjC1G2mxn96pHMvwMuXL/P555+bGltERKQ6UgFQRG5oxowZFBUVAXBf77LLfx0Oh2v5b7M20TSJjHRrfiIiIlI9xfVPJLR+fQA+XbIcR8mHiWaIb9OaLq1aAvDJJ5+Qn59vWmwREZHqSAVAEbkuh8PhWv7brmkTOjRvVuaYzYcOk3bauT+gZv+JiIhIeXl5e9N37DgAUo8cZfOhw6bFNgyDXw8fAsC5c+dczcxERERqKxUAReS6tm3bxu7duwHn7D/DMMocU7pxt5ePD10HDXZrfiIiIlK9xY8ajY+vHwATl60wNfawTh2JatgAgPfffx+bifsMioiIVDcqAIrIdU2dOhUAb6uVcT27lxm/nJfH3M1bAYjr15+A4GC35iciIiLVW2BICD2GO7v2Lty6jfTzF0yLbbFY+OVQ54eThw8fZu7cuabFFhERqW5UABSRa8rLy+O7774DYGhcR8KCgsocM3fzVvIKCwHoNWKkW/MTERGRmqH/XeMxDAO7w8EXy5NNjX1Xz+40DA0FYMKECabuMygiIlKdqAAoItc0f/58srKyALgvoWzzD/jv8t/6TZoS1SnObbmJiIhIzRHetBmx8QkATF+7jqy8PNNi+3p78/NBAwDn1iarVq0yLbaIiEh1ogKgiFxT6fLfRnVC6R8bU2Z874mTpB45Cjhn/11rf0ARERGR8ki8+x4AsvMLmF7yAaNZHurXmxB/f8A5C1BERKQ2UgFQRMpIT09n5cqVANwd3wurpeyPitKbc4vFQo+hw9yan4iIiNQsUR070bR1awA+X55MsYkNO4L9/Xm4fx8AVqxYwbZt20yLLSIiUl2oACgiZXz99deur+9L6FVmPL+oiJkbNgLQrlc8IfXquS03ERERqXkMwyBxvHMW4ImMiyxMNbdI99jAAfh6eQHOjsAiIiK1jQqAInIVu93OtGnTAOjVJopWDcLLHPND6nYu5eQCEK/mHyIiImKCzokDXB8qfrx4makNOxqEhnB3fE8AkpKSOHLkiGmxRUREqgMVAEXkKqtWreL48ePA9Zt/TF+bAkBIWD1iepadISgiIiJyq7y8vel/190AbD+aTsqBg6bG/+XQQc5uw3Y7H3zwgamxRUREqjoVAEXkKqXNPwJ9fRnVtXOZ8fTzF1i9dx8APYYNw2q1ujM9ERERqcESRo/GNyAAgI8XLzU1dkSDBozsEgfAtGnTOHfunKnxRUREqjIVAEXE5dKlS8ybNw+AO7p3JcDXt8wx35TM/gPoOVzLf0VERMQ8/oFBJIwaA8DynbvZd+KkqfGfHDYEgPz8fP7zn/+YGltERKQqUwFQRFxmzZpFQUEBAPdeo/mHzW7n23XOAmDruM6EN23q1vxERESk5ut/13gsJSsMPlmyzNTYnVq2oHfbaAA+++wzsrOzTY0vIiJSVakAKCIupct/oxo2oFtkRJnx5N17OH0pE4Beav4hIiIilaBOeDhdBw4CIGnjZk5fumRq/CeHDQacKx+mTJliamwREZGqSgVAEQFg165dpKamAnBf73gMwyhzzNdr1gHgHxREx7793JmeiIiI1CID7r0PgCKbjc+WJZsau1+7GNo3bwbAhx9+SGFhoanxRUREqiIVAEUEcG6GDWC1WLirV48y42cuZbJk+04Aug4ajM819gcUERERMUOTiEhievQEYOqqNWTl5ZkW2zAMfj3UOQvw5MmTzJw507TYIiIiVZUKgCJCYWEh3377LQAD28fSMDS0zDFfr12HzW4HIGH0GLfmJyIiIrXPwJJZgJfz85m6aq2psUd17UzzevUAeO+997CX3OOIiIjUVCoAigiLFi0iIyMDcC7//bFim41pq5033hHtO9AkItKt+YmIiEjt0zquM83aOBt2fL58BYXFxabF9rJa+eVQ5z6D+/btY8mSJabFFhERqYpUABQRV/OP+sHBDOrYvsz4il27OXXxEqDZfyIiIuIehmEw6L6fAHD6UiazN242Nf69Cb0ICwoEYMKECabGFhERqWq8PJ2AO2VmZjJjxgw2bNjAhQsX8PX1JSoqilGjRhEfX3bWU3kVFxczd+5ckpOTOXnyJABNmzYlMTGR0aNH4+V143/mQ4cOMWvWLHbs2EFWVhahoaF06NCB8ePHExFRthMrwIULF1i5ciUHDhwgPT2dS5cukZOTg7+/P82aNaNXr16MHDmSgICACn9fUjucOnWKZcuWAXBXrx54W61ljpmyag0AAcHBxPVPdGt+IiIiUnt17NuPsEaNyTh9io8XL+Pu+J7XbFRWEf4+PvxsYCJvzZlPSkoKGzdupEePsvsgi4iI1AS1ZgZgeno6Tz/9NElJSZw6dQqr1UpOTg6pqam89tprfPrppxWKm5eXxx/+8Ac+++wz0tLSsNls2Gw2Dh48yMSJE/nTn/5Efn7+dc9PTk7mxRdfJDk5mYyMDHx9fblw4QLJycm88MILrFq16prn7dq1i88//5zVq1eTnp5Obm4ufn5+ZGdns3fvXiZNmsTTTz9Nenp6hb4vqT2mT5/u2vfmvoReZcaPXbjAil17AOg5fATePj5uzU9ERERqL6vVSuLd9wCw/9Qplu/abWr8R/r3w7/k3ua9994zNbaIiEhVUitmABYVFfG3v/2NzMxMWrZsyfPPP09ERAQFBQUkJSXx1VdfMWfOHCIiIhgyZMgtxf7ggw/Yv38/gYGB/Pa3v3XNJExJSeHf//43e/fu5cMPP+R3v/tdmXPT09N59913KS4upm/fvjzxxBOEhYWRkZHBp59+ypo1a3jnnXeIiIigWbNmV50bHh7O/fffT/v27YmIiCAkJASAgoICUlJSmDhxIufPn+f111/nvffew3qNWV0iDofD1f23S6uWRDdpXOaYaavX4XA4AIgfNdqt+YmIiIj0HDacRZO/IPfyZT5evJRBHcpuV1JRdYMCub9PAp8vT2bBggUcOHCANm3amBZfRESkqqgVMwAXLVrE6dOn8fX15a9//atrWa2vry/33XcfI0eOBGDKlCkU38LmwocPH2blypUAPPPMMyQkJGAYBoZhkJCQwNNPPw3AihUrOHr0aJnzv/rqK4qLi4mIiOCFF14gLCwMgLCwMF588UUiIiIoKiriq6++KnNuu3btePDBB4mLi3MV/0q/p8TERJ5//nkATpw4wb59+8r9PUntkpKSwqFDhwC49xrNPwqLi/lm7ToA2nTpSoNmzd2an4iIiIivvz997xwHQMr+g2w/au4KlycGD8RqseBwOHj//fdNjS0iIlJV1IoC4IoVKwDo378/4eHhZcbvvvtuDMMgIyODHTt2lDtucnIyDoeDxo0bk5CQUGa8d+/eNG7cGIfDQXJy8lVjOTk5bNy4EYBx48aVmaFntVoZN24cABs2bCA3N7fceQFER0e7vr5w4cItnSu1R+nsP19vb+7o3rXM+OJtOziXdRmA3mr+ISIiIh7Sd+w4vEqW6n68eKmpsZvVC3PdB3377becPn3a1PgiIiJVQY0vAObl5XHgwAEAunYtW+AA53La0iW227ZtK3fs7du3A9ClS5drbkZsGAZdunS56thSu3fvds02vF5epY8XFRWxZ8+ecucFXHV8o0aNbulcqR2ys7NJSkoCYFSXOEL8/cscU9r8IzgsjA69+7g1PxEREZFSQXXq0HPYcADmb0nl6Llzpsb/9dDBABQWFvLJJ5+YGltERKQqqPEFwOPHj7v2L2vZsuV1jysdO3bsWLniOhwOjh8/ftO4LVq0uGbc0r/XqVOH0NDQa54bGhrqGitPM4/i4mLOnTvHwoULefvttwGIiYnRPiZyTbNnz3bNLL03oezy37TTZ1i7bz8AvYaPxHqTbtYiIiIilSnx7nsxLBbsDgcfL15maux2zZqSGNsOgC+++IKsrCxT44uIiHhajX9Hn5GR4fq6dI+9aykdu3jxYrni5uXlubr7liduXl4eeXl5+JfMsiq9zo3OLR3PzMy8YV7PPvsshw8fLvN4ly5dXHsBivzY1KlTAeeyl4To1mXHV68FnDNZ1fxDREREPC28aVPi+vUnNXkF365L4dnRI2h4nQ/SK+LJ4UNI3r2Hy5cvM2nSJJ555hnTYouIiHhajS8AlhbpwNkg43pKx/Ly8soV98rjyhO39JzSAmDp+Tc6t7x5hYSEUKdOHQoLC10zurp168ajjz563dmFPzZlyhRXQehaHnjgAR588MFyxaoIi8Xi+m/dunUr7TritH//ftavXw/A/X17u/6/LJVXWMh3KRsAaNezF+FNmtxSfKulxk8urjXUQbxm0Guy5tBrsvrT6/H2DH3gIVKTV1BYbOOLFav46313mxY7sUN7Oke0IvXwET799FP+53/+p8y9uu5Za47SLZxCQ0NdK8ak+tFrUqT8anwBsDZ49dVXXV9nZWWxcuVKpk2bxnPPPccTTzzBmDE3b96Qk5PD2bNnrzuem5vrljcdhmHozY0bfPnll4Dz3/v+vn3K7GE5b/MWLubkANBn7Fgou8Xljd3q8VI16XmsOfRc1gx6HmsGPY+3pVl0G9r17MmeDRuYtCKZZ8eMpE5goCmxDcPg6ZHDeeKDjzl16hTTpk3j8ccfv+6xumetGSwqytcIek2K3FyNLwD6+fm5vi4oKCAgIOCaxxUUFACUmQl1PVceV3rujeL++JzSr290bkXyCgkJYcyYMbRr144XXniB//znP7Rr146oqKgbnhcYGEiDBg2uOx4QEIDNZitXDhVhsVgwDAOHw4Hdbq+06wjYbDYmTZoEQN+YtjSrF1bmU88vljm7Vtdp0IDYHr3gVj4UNbi146Vq0vNYc+i5rBn0PNYMeh5NMeSBh9izYQM5+QV8vnQFz90xyrTYI7t2JqJBAw6fPcs///lPHnnkkasKRLpnrTkMw8BisWC32zUDsBqr7NekiopSk9T4AuCVe+xlZGRctwBYuldgeacN+/v74+/vT15e3lX7DF4vbunxP87rRudWJK9SUVFRxMbGsnPnTpYsWXLTAuDDDz/Mww8/fN3x8+fPl3t/xIqoW7cuVqsVu91eqdcRWLJkCSdPngTgnvieZYrQO9KPsSntEAAJI0fjgPIXfw0Dq9WCzW4H3UhVW1fe6FRm4V/cQK/JGkGvyRpCr0fTtIptT6vY9hzZvYtPFi/hZwP64e/jY1r8XwwZyJ+mTmffvn1MmzaNUaP+W2DUPWvNYbVaqVu3LpmZmfrZWo1V9muyfv36pscU8ZQaP9+5WbNmruWNN+qkWzrWvHnzcsU1DINmzZpVOG7p3y9dunTdLmOZmZlkZmYC/+0mfCvq1asHwOnTp2/5XKm5pk2bBkCIvz8jOncqMz5pxUoArN7eav4hIiIiVY5hGAz+yf0AZGTn8PWadabGvzu+J/WDgwGYMGGCZoeJiEiNUOMLgP7+/rRp0waALVu2XPOY8+fPc+zYMQDi4uLKHbtTJ2fxZOvWrdc9JjU19apjS8XGxuLl5XXDvErjent7065du3LnVaq08HflMmip3TIyMli4cCEAY7t3xe9Hn5ZnZGcze+NmALokDiBYG+mKiIhIFdSuVzyNWkUA8OmSZRSZOIPLz9ubxwYmArBp0yZSUlJMiy0iIuIpNb4ACDBgwAAAVq5cyblz58qMz5w5E4fDQVhYGB07dix33P79+2MYBidPnmTdurKfPK5du5aTJ09iGIYrh1IBAQH06NEDgKSkpDLTzm02G0lJSQD07NmzzNLlm01T37lzJ/v37wegffv25f6epGb77rvvKCwsBODe3vFlxqevWUdBcTEAfcaOc2dqIiIiIuVmsVhcswBPZFx0fYBplp/270tgSQfg9957z9TYIiIinlArCoDDhw+nUaNG5Ofn8+qrr3L48GHA2WBjxowZzJs3D3Dug1c6K6/UE088wdixY3nnnXfKxI2IiKB///6Ac3lASkoKDocDh8NBSkqK62ZhwIAB11zC+9BDD+Hl5UVaWhpvvfWWa8+Cixcv8tZbb5GWloa3tzcPPfRQmXP/8Ic/8M0335Cenn5VMTAjI4NZs2bx6quv4nA4CA8PZ/DgwRX4V5OaaOrUqQBEN25MXMur/58sttn4cuVqAFq0jaFlTIzb8xMREREpr84DBhLWsBEAHyxabGoDgNDAAB7o2xuAH374gb1795oWW0RExBNqfBMQcC6h/fOf/8xLL73EkSNHePbZZwkICCA/P991ozBmzBiGDBlyy7GfeuopTp06xf79+3nttdfwKVlSWTrLKiYmhieffPKa57Zo0YJnn32Wd999l1WrVrF69WoCAgLIyckBwMvLi2effda11+CVLl68yJQpU5gyZQpWq5WAgACKi4vJy8tzHdO0aVNeeumlcncQlppt+/bt7Ny5E4B7e/dy7Y1ZaumOXZzIcBah+945zt3piYiIiNwSq9XKwHvv47v3/s3B02dYsmMnw+LK7m9cUY8PGsAXy5Mpttt57733NBNQRESqtVpRAARnsW3ChAl89913bNiwgfPnzxMYGEhkZCSjR48mPr7scsjy8Pf354033mDu3LkkJye7uqtGRUUxYMAARo8eXWZW4ZUSExNp3rw5M2fOZOfOnWRlZbmWIo8fP56IiIhrnvfcc8+xefNmdu/ezblz51yNROrXr09kZCTx8fEkJibi7e1doe9Lap7S5h9eFgt39exeZvyLkuYfQaF16Nw/0a25iYiIiFREj+EjWDRlMtmXLvHBwsUM7dSxzIecFdUkrC7jenZnRsoGvvvuO/70pz9RV/sji4hINWU41NZKyuH8+fOVGr+0fbvNZquU9u21XUFBAR07duTixYsMj+vEJ79+4qrx/adOMfSV1wEY8sBDjHrs5xW7kGFgtVqw2eygHy3VltVqBQNw3Hy/Uani9JqsEfSarCH0eqw0S7+exrzP/gPAtOeepnfbaNNi7z95iqGvOu+RnnzySSZMmKB71hrCarVSt25dLl68qJ+t1Vhlv4+sX7++6TFFPKVW7AEoUtstXLjQ9Qvx3oReZcYnrVgFODfU7j3mDrfmJiIiInI7et9xB34BgYBzL0AzRTdpzOCOzoZ6kydPVtFPRESqLRUARWqB0uYf4SHBDOgQe9VYVl4eM9dvAKBjn77UCQ93e34iIiIiFeUfGETvO8YCsGrPPnYcTTc1/q+HOvcJz8nJ4aOPPjI1toiIiLuoAChSw508eZIVK1YAcFfPHnhbrVeNz1i3ntwCZ9OaPmr+ISIiItVQ4vjxeJU043vf5FmAPVpH0iWiFQATJkwgPz/f1PgiIiLuoAKgSA03ffp0V7fre3tfvfzXbrczOdm5/LdxRARRHc3rnCciIiLiLsF1w+g1fAQAC1O3s//UKdNiG4bBk8OcswDPnj3L5MmTTYstIiLiLioAitRgDofD1f23S6uWRDdufNX48l27OXz2HAB9x44zrWueiIiIiLsNvO9+LFYrDoeD9xeaOwtwaKcORDVsAMA///lPNY0QEZFqRwVAkRosJSWFw4cPA3Bf7/gy458uWQ5AYEgI3YYMdWtuIiIiImYKa9iQ7iX3M7M3buZIyYecZrBYLPxy6GAADh48SFJSkmmxRURE3EEFQJEarHT2n5+3N2O6d71qbNex46zbfwCA3mPG4uPr6/b8RERERMw0+P4HMSwW7A6H6R2B7+rZnYahoQD84x//wOFwmBpfRESkMqkAKFJDZWdnuz6dHtkljhB//6vGP1u2AgCrlxd9SjrniYiIiFRn4U2b0mXAQAC+S9nA8QsZpsX29fbmF8OcswA3bdrE2rVrTYstIiJS2VQAFKmhZs+eTW5uLgD3Jly9/PdsZhazN20GoMuAgYTUq+f2/EREREQqw5AHHsQwDIrtdj76YYmpsR9J7E+Qnx8A//73v02NLSIiUplUABSpoaZOnQpAs3phJES3vmrsy5WrKCx2bl6dePc9bs9NREREpLI0atmKTn37AfDN2hTOXMo0LXZIgD+PDuwPwLJly9i1a5dpsUVERCqTCoAiNVBaWhrr168H4N74Xlgs/32p5xcWMmXlagCi4uJoGtX6mjFEREREqqshDz4EQEFxMR8vWWpq7F8OHYK31QrAe++9Z2psERGRyqICoEgNVNr8wzAM7knoddXYrA2byMjOAWDAeM3+ExERkZqnaVRr2scnAPDVyjWcz7psWuxGdetwT8n2KrNmzSI9Pd202CIiIpVFBUCRGsZmszF9+nQA+rSNplm9MNeYw+Hgs2XJgHOT7Ha94q8ZQ0RERKS6G/LgwwDkFxUxcdlyU2M/NXIYhmFgs9k0C1BERKoFFQBFapjly5dz+vRpAO790ey/VXv2sv/UKQD63TX+qqXBIiIiIjVJy5gY2nbrDsCkFau4lJNjWuw2jRsxsksc4Nx3ufTeS0REpKrSu3+RGqa0+UeIvz8jOne6auw/S52ffvsHBdFj6HC35yYiIiLiTkNL9gLMKSjg8+XJpsb+zYihABQUFPDhhx+aGltERMRsKgCK1CAXLlxg4cKFAIzt3hU/Hx/X2L4TJ0nevReA+FGj8fX390iOIiIiIu4S2bETUZ2cM/U+W5bM5bw802J3aN6cgR1iAfjiiy+4cOGCabFFRETMpgKgSA3y7bffUlRUBMBP+iRcNfbx4mUAWL286HfnXW7PTURERMQTSmcBZuXlMTl5lamxnxnpXFGRm5vLJ598YmpsERERM6kAKFJDOBwOpkyZAkBss6Z0bNHcNXYy4yJJGzcB0HXQYOqEh3skRxERERF3a9OlKy1i2gHO7VByCwpMi90tMoKE6DbO2P/5D1lZWabFFhERMZMKgCI1xKZNm9i3bx/gnP1nGIZr7D/LllNstwMw8N77PJKfiIiIiCcYhsGwh5wdgTOyc5iyao2p8UtnAWZlZTFx4kRTY4uIiJhFBUCRGuKrr74CwNfLi7t6dHc9npmTy7TVawFoH59Ao5atPJGeiIiIiMe069mLpq1bA/DxD0tNnQXYu20bukS0csb++GNyTOw2LCIiYhYVAEVqgOzsbGbNmgXAyK6dCQ0McI1NXrmK3IJCAAbe9xOP5CciIiLiSYZhMPynjwJw/vJlvly52tTYz4wcBjgbsn355ZemxRYRETGLCoAiNcCsWbPIzc0F4Ce9412P5xcW8sXylQC0im1PZIeOHslPRERExNPaxyfQrLVzvz6zZwEO6tCe2GZNAXj//fcpMDG2iIiIGVQAFKkBSpf/tgyvT3yb1q7HZ6Rs4PzlywAM0uw/ERERqcWcswAfAeBCdjaTk82dBfj0COcswNOnT/P111+bFltERMQMKgCKVHO7d+9m8+bNgHP2n8XifFnb7HY+WbIMgAbNWxAbn+CxHEVERESqgtj4BJq1iQbg48VLyMk3b6beiC5xRDVsAMC///1vioqKTIstIiJyu1QAFKnmSmf/WS0W7onv5Xp84dZtHD13HnB2/i0tDIqIiIjUVlfOAszIzuHLlatMi221WPhNySzA9PR0vv32W9Nii4iI3C5VBESqsYKCAtfN5aAOsTSsEwqAw+Hgwx+WABBSrx7dBg32WI4iIiIiVUlsr3iat20LwMeLl5o6C/DOHt1oGV4fgLfeekuzAEVEpMpQAVCkGps/fz4XL14E4P4+/13iu2bffnakHwOg/1134+Xj45H8RERERKqaKzsCZ2TnMCl5pWmxvaxWfjtyOABHjx7lm2++MS22iIjI7VABUKQaK13+2yA0hAHtY12PT5i/CAD/oCASRo/2SG4iIiIiVVW7Hj1p0TYGgE8WLyM7P9+02ON6dqdVeDgAb7/9tmYBiohIlaACoEg1dfToUZKTkwG4N74XXlYrABsOpJFy4CAA/cbdhX9gkMdyFBEREamKrtwL8GJODpNWmDwLcNR/ZwGqI7CIiFQFKgCKVFNTp051fX1f73jX1+8tdM7+8/X3p9+4u9yel4iIiEh1ENOjJy1i2gHwyZJlXM7LMy32nT26EdHgv7MACwsLTYstIiJSESoAilRDNpuNadOmAZAQ3YZWJTeY244cJXn3XgB63zGWwJBQj+UoIiIiUpVdOQvwUk4uk1aY1xH4ylmAx44dY/r06abFFhERqQgVAEWqoWXLlnHq1Cng6uYf7y38AQBvX18G3H2PR3ITERERqS5iuvegZbvKmQU4tns3Ihs0AJwdgTULUEREPEkFQJFqqLT5R2hAACO6xAGw5/gJfti2A4D4UaMJrhvmsfxEREREqgPDMBjx058BkJmby+fLTd4LcLRzFuDx48ddqzdEREQ8QQVAkWrmzJkzLFrk3OdvXM/u+Hl7A/+d/Wf19mbgPfd5LD8RERGR6iS6WzdaxcYC8OmSZWSZPAswqqFzFqD2AhQREU9SAVCkmvnmm28oLi4G/rv89+DpM8zbkgpAz2HDqRMe7qn0RERERKoV516AjwKQlZfHxKXLTYtttVj47agRAJw4cYIvv/zStNgiIiK3QgVAkWrEbrczefJkADq1bEFss6YAfLBwMQ6HA4vFwqD77vdkiiIiIiLVTnTXbkR27ATAp0uWk5GdbVrsO7p3JbpxYwDefPNNcnJyTIstIiJSXioAilQjq1at4siRIwA82Lc3AOnnzvP9xk0AdBs8hHolN5giIiIiUj6GYTDqsZ8DkFNQwIeLlpgW22qx8Ps7RwNw7tw5PvnkE9Nii4iIlJcKgCLVyKRJkwAI8vNlbPduAPx7wSJsdjuGYTD4/gc9mZ6IiIhItRXZoSMx3XsAMCl5FWcuZZoWe2injnSJaAXAe++9x8WLF02LLSIiUh4qAIpUE2fOnGHBggUAjOvZg0A/Xw6fPct3KRsA6DJwEA2aN/dkiiIiIiLV2sifOWcBFhQV8e8Fi0yLaxgG/zPuDgCysrKYMGGCabFFRETKQwVAkWpi6tSpruYfD/XrA8A78xZiL9n7b/hPH/FkeiIiIiLVXvPoaDr17QfA16vXkn7+gmmxE6Lb0L9dDACffvopp06dMi22iIjIzagAKFIN2O12pkyZAkCXiFbENmvK/lOnSNq4GYDuQ4cR3rSZJ1MUERERqRFGPPozDMOg2G7n3XkLTI39/+4cA0B+fj5vvvmmqbFFRERuRAVAkWpg+fLlpKenA/+d/ffuvIXOzr9WK0MffNiT6YmIiIjUGI1atqLb4CEAzFy/kQOnTpsWu2PLFozu2hmAKVOmkJaWZlpsERGRG1EBUKQamDx5MgAh/v6M6daFPcdPMHfzVgB6Dh+hzr8iIiIiJhr+00ewWK3YHQ7emjvf1Ngv3DEaq8WCzWbj//7v/0yNLSIicj0qAIpUcadOnWLRIucm1HfH98Tfx4e3S5ajWL29GfrgQ55MT0RERKTGqde4CfEjRwMwf0sqO9KPmRY7qlFD7usdD8CsWbPYvn27abFFRESuRwVAkSruq6++wmazAfBgv97sSD/GolTnjWL8yFHUbdDQk+mJiIiI1EhDH3oILx8fAP41e56psZ8dNRxfb28AXn75ZRwOh6nxRUREfkwFQJEqzGazuZp/9IiKJLpxY94uWYbi5e3NkAce9GR6IiIiIjVWaL369B17JwArdu1mY9oh02I3rluXxwclArBq1SoWL15sWmwREZFrUQFQpApbunQpJ06cAODBfn3YevgIS3fsAqD3mLGE1qvvyfREREREarRBP3kAX39/AP6ZNMfUmXpPDR9KvaAgwDkLsKioyLTYIiIiP6YCoEgVNmnSJADqBAYwsksc//f9HAC8fX0ZfP/9nkxNREREpMYLCg0l8e57AFh/II1lJR/EmiHY35/n7xgFwIEDB1xN30RERCqDCoAiVdTx48dZsmQJAPfE92LDwTTW7T8AQOL4uwmuG+bJ9ERERERqhQF330tgaCgAf5sxE5vdblrs+/sk0KZxIwD++c9/kpmZaVpsERGRK6kAKFJFTZkyBXvJDeb9fRJ4Y9ZsAAKCgxl43088mZqIiIhIreEXGMjQBx8GYM/xE8xYm2JabC+rlT/fPQ6ACxcu8M4775gWW0RE5EoqAIpUQcXFxXz11VcAxEe3Ztex4+w+7twLcMgDD+EfGOTJ9ERERERqld6jxxDWqDEA/zcriXwT9+sb0D6W/u1iAPjkk084evSoabFFRERKqQAoUgX98MMPnD59GoD7eyfwr9nzAKgT3oA+Jd3oRERERMQ9vHx8GPXYzwE4kXGRz5YuNzX+S3ePw2IYFBYW8vLLL5saW0REBFQAFKmSPvvsMwDqBQVxITubYxcuADDi0Ufx9vHxZGoiIiIitVLnxAE0j44G4N/zFpCZk2ta7JimTbi/TwIAc+fOJTk52bTYIiIioAKgSJVz4MAB103f+PiefLBwMQCNWrai++ChnkxNREREpNayWCzc8YtfAXApJ5f3Fy02Nf7v7xxDaEAAAH/84x8pLCw0Nb6IiNRuKgCKVDGls/8shoHNbuNCdjYAo3/+OBar1ZOpiYiIiNRqbbt2I6Z7DwC+WJ7MiYwM02KHBQXx+7GjAecHwp9++qlpsUVERFQAFKlCsrOzmT59OgD9Y2OYvsbZZS6iQwdi4xM8mZqIiIiIAHf88pcYhkFBcTFvz11gauwH+/UhtllTAP75z3+69oQWERG5XSoAilQh3377LZcvXwbA2+pFTkEBAGMed95oioiIiIhnNWvdhm6DhwAwI2UDe0+cNC221WLh1fvvBSAnJ0cNQURExDQqAIpUEQ6Hw7X8t3n9eizbuQuADgm9iWjf3pOpiYiIiMgVRj32c6ze3jgcDt74frapsbtHRXJPfE8AvvvuO9asWWNqfBERqZ1UABSpItauXcvevXsB8PP2xma3Y7FaGfOLX3o4MxERERG5Ur1Gjel7x1gAlu/czbr9B0yN/4e7xhLs5wc4G4IUFRWZGl9ERGofFQBFqoiJEycC4OvtzYFTzv1e+o4dR4NmzT2ZloiIiIhcw5AHH8IvMBCA12YmYbfbTYsdHhLC83eMAmDPnj289957psUWEZHaSQVAkSrg1KlTzJ8/H3DO/gMICA5m2MM/9WRaIiIiInIdgSGhDP7JAwBsP5rO9xs3mxr/kcR+dGzh/CD4zTffJC0tzdT4IiJSu6gAKFIFTJo0CZvNBkBmbi4Aw3/6KAHBwZ5MS0RERERuoN9d46nboAEA/0iaQ15hoWmxvaxW/u/hB7BaLBQUFPD888+bOstQRERqFxUARTyssLCQyZMnA/9/e/cdXmV5/3H8fXIySMJK2DOEvUTR4kAFRFpFVJwoAuICrXXiqLt1a7Vuq1XrxmrFQUWroK0oikVRBCrKlBV2QgLZ4/z+wOQHMgzkJAdO3q/r4jLJM+7vIX55cj55nvve8oMeQNM2bel7/AmRLEuSJEm/ID4hgePPHwPAqqyNPPXhv8N6/h5tWjN20EBgy3zR48ePD+v5JUm1hwGgFGGTJk1i3bp1AJT8dBfgiWMvJBgbG8myJEmSVAkHDDiKdt27A/DEBx+yZmN2WM9/xZBjSWvSGIA//vGPrF69OqznlyTVDgaAUoSVL/5RrvOBB9Ht4EMiVI0kSZJ2RyAQYOiFFwOQX1TEff+cFNbz14mP5+6zzgQgJyeHG264IaznlyTVDgaAUgTNmTOHGTNmVHweiIlh6IW/JRAIRLAqSZIk7Y60bt048KijAZjwxQzmLFse1vMf3rUzpx+25RfE77zzDv/85z/Den5JUvQzAJQi6Omnn97m80MHH0eL9PQIVSNJkqQ9NeT884mNjycUCnH7hDcJhUJhPf9Np55Ek/r1AbjmmmtYs2ZNWM8vSYpuBoBShKxbt44JEyZUfJ5Urx7HnXteBCuSJEnSnkpp2owBp54OwH8XLOL9WbPDev6GycncO3I4AJmZmYwbNy7sIaMkKXoZAEoR8sILL1BcXFzx+XHnnk9y/QYRrEiSJElVcfSZw6mXmgrA3W9NpHCrn/XCcv79ejD8iL4ATJ48mZdffjms55ckRS8DQCkCCgsLt3n8t03nLhw6+LgIViRJkqSqSkhM5LhztjzRsXTdel6Y+mnYx7jp1JNo06gRADfffDM//vhj2MeQJEUfA0ApAt5++20yMzO3fBIIcMollxETDEa2KEmSJFVZn1//hlYdOgLwyLvvsy4nJ6znr1unDg+MHkkgECA3N5dLL72U0tLSsI4hSYo+BoBSDQuFQvz5z3+u+PyQY48lrWvXCFYkSZKkcIkJBhn624sB2FRQwL1vvxP2MQ7u1IELfz0QgC+++ILHHnss7GNIkqKLAaBUwz755BOWLFkCQEJyMkPOGxPhiiRJkhROHXvtT++jtgR0r0//LzMXLwn7GOOOP46urVoCcPfddzNjxoywjyFJih4GgFINu/HGGys+HnzOedRt4MIfkiRJ0eaEMWOJr1MHgD+8NoHSsrKwnj8hLo5Hzx9NYnw8paWljB07lqysrLCOIUmKHgaAUg36/PPP+eGHHwBIbduWI44/IcIVSZIkqTo0bNyEX48YCcCcZct57bPpYR+jc4sW3H7m6QCsXLmSyy67jFAoFPZxJEn7PgNAqYaEQiEuueSSnz4LcOqll7vwhyRJUhTrf/KpNGndGoA/TZzExtzcsI9x2qEHc8ohfQB4//33+etf/xr2MSRJ+z4DQKmGvPrqqyxfvhyA9COPpNv+B0S2IEmSJFWr2Ph4Tvrt7wDIys3l/n++G/YxAoEAd5w5jA7NmgJw66238sUXX4R9HEnSvs0AUKoBGzdu5Prrrwcgrl59hl4wNsIVSZIkqSZ063MwPQ/rC8D4Tz9j7k+/EA6n5DoJPH7BudSJi6OkpITzzjuPjIyMsI8jSdp3GQBKNeCPf/wjuT898tHt5FNp06JFhCuSJElSTRl60cXExsVRFgpxy6sTqmWevm6tW3HfqLMAWLduHeeeey6FhYVhH0eStG8yAJSq2eeff8748eMBaNi1G/1/cwyBCNckSZKkmtOoRQsGnjEcgJmLl/DWjC+rZZwT+xzE2EEDAfj666/5/e9/76IgkiTAAFCqVoWFhVx11VUAxMQn0OXEk0lr0jjCVUmSJKmmDTzjTFKaNQPgrjcnkp2XVy3j/P6kEzi8S2cAxo8fz9NPP10t40iS9i0GgFI1euSRR1i4cCEArY/+Nft370ZMwPv/JEmSapv4hAROuuhiANblbOJPb79TLePEBoM8fsG5tG6UCsDNN9/MBx98UC1jSZL2HQaAUjWZN28eDz74IADJrdrQ8uBD6fDTb30lSZJU++x3+BH0KF8QZNrnfL14SbWMk1I3med+dyH1ExMpKytj7NixfPvtt9UyliRp32AAKFWD4uJiLr30UoqLiwnEBEk7/kS6tGpJXDAY6dIkSZIUQaf87hLi69QhFApxwyuvUVxaWi3jdG7RgifGnkdsTAx5eXmMGDGClStXVstYkqS9nwGgVA0effTRit+ytug3gLrNW9C5pSv/SpIk1XYpTZtx7NmjAZi3MoNn//1xtY11RNcu3DXiDADWrFnDmWeeSWZmZrWNJ0naexkASmE2b9487r//fgCSWrSk+eFHkt60CYnx8RGuTJIkSXuDI08+lZbtOwDw4KR/sWJD9YVyZ/Q9jN8d+xsAvv/+e4YPH87mzZurbTxJ0t7JAFAKo60f/Y0JxtLuxJOJCQbp2rpVpEuTJEnSXiIYDHL6FeMIBALkFxVxy2uvEwqFqm28a04cwvAjtsw9+PXXXzN69GgKCgqqbTxJ0t7HAFAKo60f/W3Z/yiSmjWnVWoKDRITI1yZJEmS9iZpXbvS9/gTAPhozv94f9bsahsrEAhw5/BhDDnwAAA++eQTLrzwQoqLi6ttTEnS3sUAUAqTrR/9bdy+A00POxyA7t79J0mSpB047rzzqZeaCsAfXptATn5+tY0VjInhoXPPpn/3rgC89957jB071hBQkmoJA0ApDLZ+9DcYF0frIScSEwzSqF5dY6sb0AAARCJJREFUGtevH+nyJEmStBdKTK7Lyb/9HQBrsrO5682J1TpefGwsT449n0M6bZl/cNKkSYwZM4aioqJqHVeSFHmxkS5A+4ZgMBiVY4XLvffeW/Ho70FnDKcsZctvcnu2aUMgEIhkaTUqsNV/Q7XodUc1v4/7NHsyCvl93GfZj1EoTN/H/fsPoOd//s3czz/j79M+58RfHcjhXbuE5dw7klynDs//7rec+/iTfLFgIe+++y5jxozh2WefJb4WLVpX/p5jX3zvoR3zeyntWiBUnbPNSrXA559/zpFHHklZWRntDuhN69OHU1BYSEpyMsf/6sD//4lfkiRJ2oHs9eu5+9zR5Ofm0rZJYz6+/Q8kJyRU65i5hYWMeugxPvv+BwCOOeYYJkyYQN26dat1XElSZBgAqlKysrKq9fz169cnGAxSWlpKTk5OtY4VTps2baJfv34sXbqU+MREhj3yF75fvgKAI7p2oW2TxhGusGYFgJhgDGWlZfgPy74rGBPz0y0qUFpWFulyVAX2ZHSwJ6OD/RgdqrMf//v+v3jtz/cBcN7AAfxx2KlhPf+O5BcVcf5fnmLaTyHggQceyKuvvkrjxtH/M2wwGKR+/frk5ORQWloa6XK0h6r7fWRKSkrYzylFio8Aq1Jq8qK4L12Ar7vuOpYuXQrAyTfczIqsjQDUT0ykTeNUqGX5evkjTSGoda89avl93KfZk1HI7+M+y36MQmH+Ph78m2P45j//Zv7XM3nuP1MZcuAB/KpD+7CO8XN14uL428VjueK5F/nXN9/y9ddfM3jwYF5//XXatGlTrWPvLUpLS/ep9x/aOb+P0q65CIi0h9555x3+/ve/A9Dz6F/TrM8hbN68GYAebVoT8NlfSZIkVVIgEGDYFeOIr1OHUCjEtS//nYIaWKG3Tlwcj19wLiOPPByARYsWceyxx/L1119X+9iSpJpjACjtgdWrV3PVVVcBUK9xE4bfeQ9z584FIDkhgbRa9uivJEmSqi61eXOGnD8GgEWr1/DIu+/XyLjBmBjuGD6McccPBmDt2rUMHTqUt956q0bGlyRVPwNAaTeVlZVx6aWXVsyLeNY9f2L95k0Vc070aNOaGFf3kyRJ0h44/IQTSe/ZE4Anp3zEtz8urZFxA4EAlw8ZzJ/PHkF8bJCCggLGjh3LPffcQ5nzj0rSPs8AUNpNTz75JB9//DEAR4wYRff+RzFnzhwAkhLiSW/aJILVSZIkaV8WExPDGeOuJi4hgdKyMq58/iXyi4pqbPzTDjuEV664lEY/rQb85z//mZEjR5KZmVljNUiSws8AUNoNM2fO5PbbbwegWYeOnHTdjaxYsYKNPy3+0a1Vqy2rw0mSJEl7qGnrNhxf/ijwmrXc+/Y7NTp+nw7tmXjdVXRt1RKAKVOmcPTRRzNz5swarUOSFD4mFVIlbdy4kTFjxlBSUkJcQgLnPvoX4hMTmT17NrBlAuWOzZtFuEpJkiRFg8NPHErn3gcC8Nx/pjJt3g81On6bRo1465orOeWQPgCsWLGCE044gaeeeoqQK1lL0j7HAFCqhFAoxBVXXMHy5csBOPWWW2nZuQvLly9nw4YNAHRt1dK7/yRJkhQWMTExnHHVNdRJTgbg6pfGk52XV6M1JCUk8MDokdw7cjgJcXEUFxdz4403cvbZZ7N27doarUWSVDWmFVIlPPvss7z77rsAHHTCiRw27ExCoRCzZs0Cttz917ll8whWKEmSpGiT0rQpp15yGQCrsjbyh9cm1HgNgUCAMw8/jLevHVcx1/X7779Pv379eOedmn00WZK05wwApV8we/ZsbrnlFgCapLVj2G13EQgEWLZsWcVKwN3btCI2JhjJMiVJkhSFDhx4NPsf2Q+At2Z8xbtffxOROrq3bsU7113NsL6HArBhwwbOO+88Lr74YrKzsyNSkySp8gwApV3YvHkzF1xwAUVFRQTj4jnn4cdIrFePUCjEt99+C0BifDydmnv3nyRJksIvEAhw6mVXUC81FYAbX/kHazZGJnCrl5jIfaPO4m+/HUOT+vUAeP311zn88MP55z//6dyAkrQXMwCUdiIUCnHZZZexZMkSAE6+/kba9NwPgB9//JGNGzcC0KONK/9KkiSp+tRt0IAzxl0NQFZuLlc8/xKlZWURq2dQr/2YfPP1DDnwAADWrFnD+eefz4gRI1i2bFnE6pIk7ZyphbQTf/nLXyrmNdn/mMEcOWo0AGWhsoq7/5IS4unQzJV/JUmSVL26H3wIh584FIDPf5jPEx98GNF6UuvW5fELzuUvY86laYP6AEyZMoUjjzySRx99lKKioojWJ0nalgGgtAPTpk3jtttuA6BZhw6MuPd+AoEAAEsWLyEnJweAnm3aePefJEmSasSJYy+iRfv2ADww6T2+WrQ4ovUEAgGGHNibj/5wI6MH9CMQCJCXl8dtt93GkUceyfvvv+9jwZK0lzC5kH4mIyODMWPGUFZWRkJyMuc//lfq1K0LQFlZGd/O3nL3X3JCAu2bNY1kqZIkSapF4uLjOfuGm4lPqENpWRmXPfsC2bl5kS6L+omJ3HbGabx97Th6tGkNwOLFixk1ahSnnXYa//vf/yJcoSTJAFDaSlFREeeffz7r168H4Ky776N5x04V2xcsWMDmTZsB6Nm2DTE/3RUoSZIk1YRmbdtyyiWXArAyM4vfj//7XnOX3QHt0njnuqu5d+RwGtfbskjIJ598wsCBA7nqqqtYvXp1hCuUpNrLAFDays0338xXX30FwMDzx9D7uCEV24qLiyvm/qufmEh60yYRqVGSJEm1W5/fHEPvowYC8K9vvmX8p59FuKL/F4yJ4czDD+PjW2/i4mMGER8bpKysjBdffJGDDz6Y22+/vWIxPUlSzTEAlH7y6quv8uyzzwLQ8eBDOeGa67bZPm/ePAoKCgA4ID3Nu/8kSZIUEYFAgNMvu4JGLVoAcNuEt5i3YmWEq9pWvcREfn/SiXz0h5sqVgvOz8/nkUce4aCDDuLBBx8kNzc3skVKUi1iACgBX331FVdddRUA9Zs25ZyHHyUYG1uxvaCggLlz5wLQuF49WqWmRqROSZIkCaBOcjKjbriJmGCQwuJiLnrqWbLzIj8f4M+1bdyIv4w5j3/+/iqO7NYFgJycHO666y769OnD008/TWFhYYSrlKToZwCoWi8jI4Ozzz6boqIiYuMTuOAvT1G/ybaLe8yePZuSkhIAeqen4b1/kiRJirS2Xbpy4tiLAPhx3TqufnE8ZWVlEa5qx/Zvl8bLl/2Ov19xCb3bpQGwbt06brjhBg455BBeeukliouLI1ylJEUvA0DVanl5eYwaNYp169YBMPyue2h3QO9t9tm0aRPz588HoFVqCk3q16/xOiVJkqQdOfKkkyvmA5z87RyenPJRhCvatb5dOvPWteN4+qIL6PzTI8wrV65k3Lhx9O3bl9dee43S0tIIVylJ0ccAULVWKBTi8ssvZ/bs2QAcPfYi+px0ynb7zZo1q+I3qQf89NtKSZIkaW8QCAQYdsU4mqVt+Tn1vomTmPb9DxGuatcCgQC/2b8X79/0ex4+9+yKxfV+/PFHLrnkEo444gjeeuutvfZuRknaFxkAqtZ68MEHefvttwHocdRATrjq2u322bBhA0uWLAGgfbOmNEhKqskSJUmSpF+UkJjIOTf/kYTERMpCIS772wusysqKdFm/KBgTw0kH/4oPb7mB+88eQetGW+bZXrhwIWPHjuWoo47i3XffJRQKRbhSSdr3GQCqVnrvvfe4++67AWjWoSNnP/AIMcHgdvt9+dWXAMTExLBf2zY1WqMkSZJUWc3atuXMq64BYMPmzVz4179RUFQU4aoqJzYY5PTDDuE/f7yJu846gxYpDQH47rvvOOeccxg0aBBTpkwxCJSkKjAAVK3zzTffcNFFWyZLTmrQgLF//RuJ9eptt9/SpUtZu2YtAN1atSQ5IaFG65QkSZJ2x/79+jPgtGEAfLt0Gb8f/+o+FZrFx8Yy4sjD+fjWm/nj6afSpP6Wn9Fnz57NWWedxXHHHcfUqVP3qdckSXsLA0DVKsuWLWPEiBHk5+cTjIvjvMeepEm7dtvtV1paysyZMwGoEx9H99atarhSSZIkafcdf/4FdP1VHwDenvEVT07+MMIV7b46cXGcO7A/n97+B244ZSipdZMB+OqrrzjttNM46aSTmD59eoSrlKR9iwGgao3s7GyGDx++1Yq/99L5sL473Pe7ed+xefNmYMvCH3E7eDxYkiRJ2tvEBIOMuuEmmrbeMn3NvRMn8dGcuRGuas8kxsdz4a+P5tPb/8A1Jx5P/cREAD7//HNOPPFETj/99Ipf2kuSds0AULVCUVER55xzDvPnzwdg8GVXcvDJp+5w3/z8fObMngNAat26FauSSZIkSfuCxLp1Oe+220msW5dQKMRlz77A/FWrIl3WHqtbpw6XDP4N0+74A5cfdyx162yZmufjjz/m2GOPZcSIEcyePTvCVUrS3s0AUFEvFAoxbtw4pk2bBsDBJ5/KsZdevtP9v/nmG0pKSgA4qH06AQI1UqckSZIULk1bt+HsG24mEBPD5oJCzv/LU6zP2RTpsqqkQVIS4044jmm3/5Hf/mYQifHxAEyePJmjjz6ac889l++//z7CVUrS3skAUFHv/vvv57XXXgOg06GHcead9xAI7DjU27BhAwsXLgQgrUnjiomHJUmSpH1Nl1/9iqEXbln8btn6DZz/xFPk7yMrA+9KSt1krjv5RD69/RbOP3oACbGxAEyaNIl+/fpx4YUXsmjRoghXKUl7FwNARbXnn3+eP/3pTwA069CB8x//K7E//abw50KhEDNmzAAgJiaGA9ql1VidkiRJUnU48qRTOGLoSQDM+nEplz37AqVlZZEtKkya1K/PLaedwie338KofkcQFwwSCoV488036du3L5deeilLly6NdJmStFcwAFTUeuedd7j22msBqN+0KRf97QWSGjTY6f4LFy2sWCCkR+uWJCck1EidkiRJUnUJBAKcdNHF9Php8bvJ387hj/94g1AoFOHKwqd5w4bcMXwYH996M2cefhjBmBjKysp49dVXOfTQQ7nmmmsqfs6XpNrKAFBRadq0aVx00UWEQiES69fn4udeotFPK6HtSGFhIV/P/BrYMslw99ata6pUSZIkqVrFBIOMuv5G2nbpCsCLUz/l6Y/+E+Gqwq91o1TuHTmcf//hRk45pA8xgQAlJSU8//zzHHLIITzxxBMURcEj0JK0JwwAFXVmz57NqFGjKCoqIi4hgbFPPUvLn37Y2Zmvv/6awsJCAH7VIZ1gjK0hSZKk6BFfpw7n33YHqc1bAHDnG2/z5n9nRLiq6tGuaRMePGcUU265geMOPACATZs2ccstt9CvXz8mT54cVXdASlJlmHIoqixevJgzzzyTzZs3ExMMcs7Dj9PhV312ecy6detYsGABAG0apdIyJaUmSpUkSZJqVL2UFMbeeTfJ9esDcPWLrzD529kRrqr6dGzejCfGnMc/xl1G99atAFi0aBEjRoxg2LBhzJs3L8IVSlLNMQBUVFm1ahWbc3MBOOOOu9lv0K93uX9ZqIwvvvgCgNhgDAe2T6/2GiVJkqRIadqmDWPuvJuExERKy8q45Jnn+fyH+ZEuq1od0qkjk66/hntGnElq3WQAPvroI3r16sWNN97I5s2bI1yhJFW/QMh7n1UJ69evr9bzp6SkEAwGKS0tJSsrq0rn+tv0GXz55Zf0H33uL+47b948vvzySwB6p6fRrVWrKo1d6wUCBIMxlJaWgf+07LOCwSAEgBCUlpZGuhxVhT0ZFezJKGE/RoVo6seF387iqRuuo6S4mOSEBF654hIOaJcW6bKqXXZeHo+89wHP/2cqJT+thtyiRQvuuusuhgwZQiAQiHCF2h3hfB+5I40bNw77OaVI8Q5ARZ0OvfavVPiXm5vLN998A0CDpCS6tGxZ3aVJkiRJe4WO+x/A6JtuISYmhtzCQkY/9gTfr8yIdFnVrkFSEjefdjJTbrmBAT26A1ueIjr33HMZOXIky5Yti3CFklQ9DABVa02fPp2SkhIADu7Ynhh/2ydJkqRapMdhfRl+ze8JBAJszM1j+EOP8kMtCAEBOjRvxqtXXc5jF5xDk5/mRJw8eTJHHnkkjz76KMXFxRGuUJLCywBQtdKiRYvIyNjyw03nFs0rLvqSJElSbXLQ0YM49dLLAcjcnMuZDz1aK+4EBAgEApz4q4P46A83MKrfEQQCAfLy8rjtttsYNGhQxVRBkhQNDABV6+Tl51VczJMTEti/Fsx1IkmSJO1M3+NP4LTLrgC2hIDDH3qUeStWRraoGtQgKYk7hg/j7WvHVawW/N133zFkyBBuvvlm8vLyIlyhJFWdAaBqnRn/nUFRUREAB3fqQFwwGOGKJEmSpMjqe/wJnH75lUB5CPhYrQoBAQ5ol8Y7113NzaedTFJCPKFQiCeffJIBAwbw+eefR7o8SaoSA0DVKj/++GPFxL4dmjWlRcOGkS1IkiRJ2kscNuT4ihAwKzeXYQ88wszFSyJcVc2KDQa54Oij+OCm6+nbpTMAS5YsYejQoVx//fXk5uZGuEJJ2jMGgKo1CgoKmDFjBgCJ8fH0Tm8X2YIkSZKkvcxhQ45n2JXjCAQC5OTnM+Lhx5n63bxIl1Xj2jZuxCuX/467zzqDunUSAHjmmWfo378/06ZNi3B1krT7DABVa0yfPp2CggIA+nRsT3xsbIQrkiRJkvY+hw4ewqgbbiIYG0t+URHn/+Up3vnq60iXVeMCgQBnHXk4k2++nn7dugKwdOlSTj75ZK699lrvBpS0TzEAVK2wYMECli9fDkD7Zk1pnZoa4YokSZKkvdcB/Qdw/m13EJ9Qh+LSUi599gVemvpppMuKiFapqbx46W/506jh1E9MBOC5555j4MCBzJw5M8LVSVLlGAAq6uXk5FSs+lu3TgIHtU+PcEWSJEnS3q/rr/pw0Z/uI7FePUKhEDe9+jp3vvE2ZWVlkS6txgUCAc7oexhTbrme/t233A24ePFihgwZwp/+9CeKi4sjXKEk7ZoBoKJaWVkZn376KSUlJQAc1qWzq/5KkiRJldSuW3cu/fNDNGzcBICnPvw3Fz31LHmFhRGuLDKaN2zIC5f8ltvPPJ06cXGUlpZy3333cdxxx7Fw4cJIlydJO2UAqKj27exv2bBhAwA927amSb16Ea5IkiRJ2rc0b9eOyx99jNYdOwHwwbezOf3PD7NmY3aEK4uMQCDA2f2P5L0brmX/tLYAzJo1i4EDB/LMM88QCoUiXKEkbc8AUFFrzdo1zJkzB4BG9erSs02bCFckSZIk7ZsaNGrM7/78ID0P6wvA3OUrOPHe+5n149IIVxY5HZo3441rruTKIYMJxsSQn5/P9ddfz7Bhw1i1alWky5OkbRgAKioVFBTw6SefQghigzH07dKJmEAg0mVJkiRJ+6yExETOueWPDDhtGACrN2Zz+p8f4pVPP6u1d73FBYNccfxg3rrmSto3bQrAxx9/TL9+/Zg4cWKEq5Ok/2cAqKgTCoWYNm0aeXl5APTp0IF6dRIjXJUkSZK074sJBjlx7IWcMe5qYuPiKCop5fpXXuOal16hoKgo0uVFzP7t0njvxmsZPaAfABs3buSCCy7gd7/7HZs2bYpwdZJkAKgo9PHH/yEjIwOADs2akt60SYQrkiRJkqLLIccO5tIHHyGlWTMAXp/+X065/yGWrlsX4coiJzE+ntvOOI0XL/0tTerXB+Af//gHAwYM4IsvvohwdZJqOwNARZVp06bx4YcfAtAwOYlfdWgf4YokSZKk6NSmc2fGPf4EXX7VB4D/LV/B4Dv/xOvT/1trHwkG6N+9G5Nvvo5jDugFwLJlyxg6dCh33XUXxcXFEa5OUm1lAKioEggESE5MJDYYwxFduxCM8X9xSZIkqbok12/AmNvv5DcjRxEIBMgtLOTqF8fzu2eeIzs3L9LlRUxq3br8dez5/GnUcJIS4ikrK+PBBx/kuOOOY+HChZEuT1ItFAjV5l/NqNLWr19fredPSUkhGAxSWlpKVlZWlc719n9nsCCvkOYNG4SpOlVaIEAwGENpaRn4T8s+KxgMQgAIQWlpaaTLUVXYk1HBnowS9mNUsB93bdHs2bzyp7vJWrsWgBYpDbn/7BEc0bVLhCvbXiAQICEhgcLCwmq/W3HpunVc/txLfLPkRwASExO57bbbGD16NAEXKqyScL6P3JHGjRuH/ZxSpHh7lKJO3aQkwz9JkiSphnXo1Yurn3ya3kcNBGBV1kZGPPw417z0Sq2+GzCtSRMmXHU5444fTDAmhvz8fK655hpGjhzJulo8Z6KkmmUAKEmSJEkKi8S6dRl1/Y2cde111ElOBuAfn3/B0bfdybszv6m1cwPGBoNcPmQwb1x9Be2abFmkcPLkyfTv35/JkydHuDpJtYEBoCRJkiQprH416Ndc98xz9DriSADW5Wzi4mee4/wnnmLJT48I10a909vx3g3XcubhhwGwbt06RowYwTXXXENubm6Eq5MUzZwDUJWyL80B+OGcuawqKQtTZdotzm8UFZzfKIrYk1HBnowS9mNUsB/3zJzPpvHGY4+Qs2EDAHHBIOcc1Z9LB/+GBklJEampJucA3JkPZs3m9y//nayfgr8OHTrw5JNPcsABB0Sknn2RcwBKlecdgJIkSZKkarPf4Ufw+2ee5YihJxETE0NxaSlPf/hvBvzhdl6a+inFtTRMPeaAXnxw83X0794NgEWLFjF48GAeeOABA2ZJYecdgKoU7wBUpXh3Q1Tw7oYoYk9GBXsyStiPUcF+rLrVP/7IxL8+wQ8zv6r4WtvGjbh08DGcfEgf4oLBGqljb7gDsFwoFOLFqZ9y55sTKSwuBuDggw/mL3/5C2lpadU2bllZGTk5OWRlZZGdnU1WVhYbN25k8+bNlJSUUFxcXPGnrKyMhIQE4uPjSUhIICEhgYYNG9KwYUNSU1NJSUkhNTWVmJiavcfIOwClyjMAVKUYAKpSfHMTFXxzE0XsyahgT0YJ+zEq2I/hEQqFmPflDP755BOsXbG84utpTRpz6eBjOOngX1V7ELg3BYDl5q9axeXPvsh3K1YCULduXe655x6GDRtGIBDY7fOVlZWxcuVKFi1axKJFi1ixYgUZGRkVf1atWkXxT4FjOMTFxdGyZUtatWpF69atSUtLo1OnTnTp0oUOHTqQkJAQtrHKGQBKlWcAqEoxAFSl+OYmKvjmJorYk1HBnowS9mNUsB/Dq7S0lJkfTWHK+JfZsGpVxddbpDTk7P5HMvzwvqTUTa6WsffGABCgqKSEB955jyenfFRR14knnsj9999PSkrKDo8JhUIsXbqUOXPmMGfOHBYsWMDixYtZvHgxBQUFYakrEBNDqGzP32PFxMTQrl07br/9dn7zm9+EpSYwAJR2hwGgKsUAUJXim5uo4JubKGJPRgV7MkrYj1HBfqwepSUlzPzoQyaPf5nM1f8fBNaJi+OUQ/pwdv8j6da6VVjH3FsDwHJfzF/AuBdeZmXmlvdGzZs357HHHuPwww9n/vz5FWHfnDlzmDt3Ljk5Ob94zjp165HSogUNmrcgpUULGjZvQf0mTUhq0JCkBg0q/iQk1yUYF7flT2wsMcEggUCA0pISSoqKKCkqoriggPycHHI3ZpGXvZHNmZlkr11L1soVZK3KIHPlSjJXrqD0Z3cYvvLGG/y6X7+w/T0ZAEqVZwCoSjEAVKX45iYq+OYmitiTUcGejBL2Y1SwH6tXaUkJ3376CZ+8+QbLfvh+m2092rTmtEMPZmifg2hUr16Vx9rbA0CA1Rs3cs1Lr/DJd///d1H+nmlngnFxNGvfgabp7Wmank6T9PY0bZdO0/T2JO/kDsLqUlpczPrly1i9cAGrFy5g1fz5PPqne+ncJHyhmgGgVHkGgKoUA0BVim9uooJvbqKIPRkV7MkoYT9GBfux5vw47zs+efMNZn/6CWVbPXoaGxNDv+7d+M3++zGoV0+a1K+/R+ff2wLAjbm5/G/5SuYuX87/lq/gf8tXsHjNWsp2UVtCcjKtunWndfceFX+ad+xEbHx8DVa+ewYmJ9AsNnzzOxoASpUXG+kCJEmSJEnaWrtu3Wl3Y3dyNmxg5r8/4sspk1n94xJKysr499z/8e+5/yPwSoAD2qUxaL+eHN61Mz3btqmxVYT3VFlZGUvXr+e7FSuZtyKD71asYN6KDDJ+IbxKbtiQxGbNiW3chKTmLajbshV9+g9gv169anzlXUn7Ju8AVKV4B6AqxbsbooJ3N0QRezIq2JNRwn6MCvZj5IRCIVYuXMCXH05h7mfTyFq7drt9khLiOah9Ogd37Mj+7drSrVUrmjbY8R2C1X0HYElpKSs2ZLJozVoWrVnD4jVr+SEjgx9WriK3sHCXx6Y2b0Grjh1p3aEjrTpu+VM/tREEYN6KDGYvXVZxZ2BKSgp9+/alUaNGYX8N1cE7AKXIMQBUpRgAqlJ8cxMVfHMTRezJqGBPRgn7MSrYj3uHUChExuLF/G/658yd/jkrFszf6b6N69WjW+uWdGzenNaNUmnTqBGtG6XSKjWVJikNKSku3u0AsKysjJz8fDbm5rEuJ4eVmVlkZGWR8dN/l63fwNJ16ygq2fX/I8G4OJqnpdGyfQdatu9Aqw4daNWhI4l16+7yuI15eXwxfyGZmzdv+UIAevTowf77709scO9+yM8AUIocA0BVigGgKsU3N1HBNzdRxJ6MCvZklLAfo4L9uHfanJ3N4jlzWDTnWxbPmU3GokWVCvUCgQD1ExNJSU6mQVIicbGxxAWDxAWDxAaDlJaVUlhSQnFJKUUlJeQWFJKVm0t2Xt4u5+bbkYaNm9C0TRtadtgS9rXs0IFmbdoSjN2zwK4sFOKHjAy+Xbq8Yo7EevXq0bdvX5o1a7ZH56wJBoBS5BgAqlIMAFUpvrmJCr65iSL2ZFSwJ6OE/RgV7Md9Q0FeHquWLCFj8aKKP+szMsjNzq62MQOBAPVSU0lp2pSUps1o2qYNTVq3odlP/01ITKyWcTcVFPDfBQtZm51T8bXOnTvT+8ADSdgLFwMxAJQiZ+++P1iSJEmSpN1QJymJ9B49SO/RY5uvF+bnk7l6NZlrVpO9YQMFuZvZnJ1NXk4O+Zs3U1pSTGlJKaUlJZSWlBATDBIbF1fxJz4xkeT69UmqV4+kevVJrl+f5IYNSWnSlAaNGxMbF1fjr7VenTocvV8PFq5eyzdLllBSWsb8+fNZtmwZBx10EB06dKjxmiTtnQwAJUmSJElRLyExkRbp6bRIT4+qu3IDBOjUvBmtUhvy5cLFrMzMoqCggM8++4wFCxZwyCGHkJKSEukyJUWY64VLkiRJkrSPS4pPoH/3bvTv3o3khAQA1q5dy6RJk/jyyy8pLi6OcIWSIskAUJIkSZKkKNEqNYXjD+pNz7atiQkECIVCzJs3j7feeosFCxbs9qrHkqKDAaAkSZIkSVEkGBNDr7ZtGXLQATRv2BCAgoICpk+fzjuT3iEjIyOyBUqqcQaAkiRJkiRFoXp1EjmqZ3eO7NaFunXqALAxayMffvghH374IRs3boxsgZJqjAGgJEmSJElRKgC0adSIIQf15qD26cTHblkLNCMjg3++80+mT59Obm5uZIuUVO1cBViSJEmSpCgXDATo0rIF6U2bMHf5CuZnrKIsFGLBggUsWrSITp06sV+v/UhKTIp0qZKqgQGgJEmSJEm1RHxsLAemt6NTi+Z8++Mylq1fT1lZGT/88AMLFy6kc5fO9OzRk8TExEiXKimMDAAlSZIkSapl6tWpwxFdO5OV24o5y5azYkMmpaWlzPtuHvN/mE/Hjh3p3qM79erWi3SpksLAAFCSJEmSpFoqJTmZft26krl5M7OXLicjK4vS0lJ++OEH5s+fT7t27ejRowepqamRLlVSFRgASpIkSZJUy6XWrcuAHt3YsHkz/1u+ghUbMgmFQixZsoQlS5bQsmVLunbtSqtWrQgEApEuV9JuMgCUJEmSJEkANKpbl37dupKTn8+8FStZsnYdZaEQGRkZZGRkULdeXbp07kLHjh1JSEiIdLmSKskAUJIkSZIkbaN+YiKHdOpIr7S2fJ+RwaLVaykqKWHzps3MnDmTWbNm0S69HR07dqRZ02aRLlfSLzAAlCRJkiRJO5QYH0/vdu3Yr21blq5bx/yM1WTl5lJaWsqihYtYtHARdevVpWOHjrRv3566detGumRJO2AAKEmSJEmSdik2JoYOzZrRvlkzNmzaxPyMVSzbkElZWRmbN21m1qxZzJo1i2bNmpGenk6btm1IrJMY6bIl/cQAUJIkSZIkVUoAaFyvHo271ONXpaUsW7eexWvWsn7TJgDWrFnDmjVr+OK/X9CsaTPS0tJom9aWpMSkyBYu1XIGgJIkSZIkabfFB4N0bN6Mjs2bkZOfz5K161i6bh2bCwoh9P9h4IwZM2jcuDEJLZpyyoB+kS5bqpVqVQCYnZ3NhAkTmDFjBhs2bCAhIYEOHTpw3HHHceihh+7xeUtKSpg0aRJTp04lIyMDgFatWtG/f3+GDBlCbOyu/5oXL17MW2+9xZw5c8jJyaFBgwb07NmTU045hfT09GodW5IkSZKkqqqfmMj+aW3pldaWrNxclq/fwLL169mUXwDA+vXrKUmtH+EqpdorEAqFQpEuoiYsW7aMG2+8kezsbAASExMpLCykrKwMgBNOOIExY8bs9nnz8/O5+eabmT9/PgDx8fEAFBUVAdC1a1duu+026tSps8Pjp06dysMPP0xJSQkAycnJ5ObmAhAbG8uVV17JkUceWS1j747169dX+Ry7kpKSQjAYpLS0lKysrCqd68M5c1lVUhamyrRbAgGCwRhKS8ugdvzTEpWCweCWZztCUFpaGulyVBX2ZFSwJ6OE/RgV7McoYk/WiBCQnZfH8vUbWJWVxa1HHUn7tLSwnT+c7yN3pHHjxmE/pxQpteL2sOLiYu644w6ys7NJS0tj3LhxpKenU1hYyMSJExk/fjzvvPMO6enpDBo0aLfO/Ze//IX58+eTnJzMZZddVnEn4RdffMEjjzzC999/zxNPPMGVV1653bHLli2rCP+OOOIILrjgAlJTU8nMzOTpp5/ms88+46GHHiI9PZ3WrVuHdWxJkiRJkqpTAGiYlETDtkns17YNiYkuCiJFSkykC6gJH3zwAatXryYhIYFbbrml4rHahIQEhg0bxuDBgwF4+eWXK+7Eq4wlS5bwySefAHDppZdy2GGHEQgECAQCHHbYYVxyySUAfPzxxyxdunS748ePH09JSQnp6elcddVVpKamApCamsrVV19Neno6xcXFjB8/PuxjS5IkSZIkqXaoFQHgxx9/DEC/fv1o0qTJdttPPfVUAoEAmZmZzJkzp9LnnTp1KqFQiBYtWnDYYYdtt71v3760aNGCUCjE1KlTt9mWm5vLl19+CcBJJ5205XGCrQSDQU466SQAZsyYQV5eXtjGliRJkiRJUu0R9QFgfn4+CxYsAODAAw/c4T5NmjSpeMT222+/rfS5Z8+eDUDv3r0JBALbbQ8EAvTu3Xubfct99913FXcb7qyu8q8XFxczb968sI0tSZIkSZKk2iPqA8AVK1ZQvs5J2i4mGy3ftnz58kqdNxQKsWLFil88b9u2bXd43vLPGzZsSIMGDXZ4bIMGDSq2LVu2LGxjS5IkSZIkqfaI+gAwMzOz4uPyOfZ2pHxbZVcOys/Pp6CgoNLnzc/PJz8/v+Lr5ePs6tid1VXVsSVJkiRJklR7RP0qwOVBGWxZ9GNnyrdVNijber/KnLf8mPJVj8qP39WxO6urqmPvyMsvv8wrr7yy0+3Dhw/nrLPO2mWtVRETE1Px35SUlCqdKy01haTcvF/eUdUgQCAAW266DUW6GO0xv4/Rw+9ldPD7GB38PkYHv4/Rw+9lJDRt3LjK7/e2Fs73kVK0i/oAUJWTm5vL2rVrd7o9Ly9vu4VKqkMgEKjyOIftv3+YqpEkSZIk7e3C8T5SinZRHwDWqVOn4uPCwkKSkpJ2uF9hYSHALu+S29rW+5Ufu6vz/vyY8o93dezO6qrq2DuSnJxM06ZNd7o9KSmJ0tLSXZ6jKmJiYggEAoRCIcrKyqptHFWvQCBATEwMZWVlFXNvat9jP0YPezI62JPRwX6MDvZj9LAno0N196ShoqJJ1AeAW8+Rl5mZudMAsHyuwMreNpyYmEhiYiL5+fnbzDO4s/OW7//zunZ17M7qqurYOzJy5EhGjhy50+3r16+v9PyIeyIlJYVgMEhZWVm1jqPqFQwGSUlJITs7u1oDY1Uv+zF62JPRwZ6MDvZjdLAfo4c9GR2quycbN24c9nNKkRL1i4C0bt2aQCAAbLuS7s+Vb2vTpk2lzhsIBGjduvUen7f8840bN5KTk7PDY7Ozs8nOzgb+f0XfcIwtSZIkSZKk2iPqA8DExEQ6deoEwNdff73DfdavX8/y5csB2H835o/r1asXAN98881O95k1a9Y2+5br3r07sbGxu6yr/LxxcXF069YtbGNLkiRJkiSp9oj6ABBgwIABAHzyySesW7duu+1vvvkmoVCI1NRU9ttvv0qft1+/fgQCATIyMpg+ffp22z///HMyMjIIBAIVNZRLSkqiT58+AEycOHG7285LS0uZOHEiAAcffPB2jy5XZWxJkiRJkiTVHrUiADzmmGNo3rw5BQUF3H777SxZsgTYskjGhAkTePfdd4Et8+CV35VX7oILLuDEE0/koYce2u686enp9OvXD4BHH32UL774glAoRCgU4osvvuCxxx4DtgSQWz/CW27EiBHExsayaNEiHnjggYo5C7KysnjggQdYtGgRcXFxjBgxIuxjS5IkSZIkqXaI+kVAYMsjtDfddBM33ngjP/74I5dffjlJSUkUFBRUrBR0/PHHM2jQoN0+98UXX8yqVauYP38+d911F/Hx8QAUFRUB0LVrV37729/u8Ni2bdty+eWX8/DDD/Ppp58ybdo0kpKSyM3NBSA2NpbLL7+8Yr6/cI4tSZIkSZKk2qFWBICwJWx79NFHeeONN5gxYwbr168nOTmZ9u3bM2TIEA499NA9Om9iYiL33HMPkyZNYurUqWRkZADQoUMHBgwYwJAhQ7a7q3Br/fv3p02bNrz55pvMnTuXnJycikeRTznlFNLT06ttbEmSJEmSJEW/QCgUCkW6CO391q9fX63nL1++vbS0tFqWb1fNCAaDpKSkkJWVtd28ltp32I/Rw56MDvZkdLAfo4P9GD3syehQ3T3ZuHHjsJ9TipRaMQegJEmSJEmSVFsZAEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJkiRJkhTFDAAlSZIkSZKkKGYAKEmSJEmSJEUxA0BJkiRJkiQpihkASpIkSZIkSVHMAFCSJEmSJEmKYgaAkiRJkiRJUhQzAJQkSZIkSZKimAGgJEmSJEmSFMUMACVJkiRJkqQoZgAoSZIkSZIkRTEDQEmSJEmSJCmKGQBKkiRJkiRJUcwAUJIkSZIkSYpiBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxQwAJUmSJEmSpChmAChJkiRJkiRFMQNASZIkSZIkKYoZAEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUC4RCoVCki5BefvllcnNzSU5OZuTIkZEuR6rV7Edp72JPSnsP+1Hau9iTUuUZAGqvcNxxx7F27VqaNm3Ke++9F+lypFrNfpT2LvaktPewH6W9iz0pVZ6PAEuSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJkiRJkhTFDAAlSZIkSZKkKBYb6QIkgLPOOovc3FySk5MjXYpU69mP0t7FnpT2HvajtHexJ6XKC4RCoVCki5AkSZIkSZJUPXwEWJIkSZIkSYpiBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxVwFWHtk4cKFzJgxgwULFpCRkUFOTg6FhYXUq1eP9u3b069fP/r3709MzPYZ8wUXXMDatWt3ef7jjjuOiy66aKfbs7OzmTBhAjNmzGDDhg0kJCTQoUMHjjvuOA499NAqvz4pGtxxxx3MmDEDgIEDB3LFFVfsdN/p06fzr3/9i0WLFlFYWEjjxo3p06cPp59+OvXr19/lOPajVDmV6UmvkVL4ffTRRzz88MO/uN/LL7+802ue10kpPKrSj14jpaoxANQemTx5Mu+//37F53Xq1CE2NpasrCxmzpzJzJkzmTJlCjfddBNJSUk7PEdSUhLx8fE73bYzy5Yt48YbbyQ7OxuAxMREcnNzmTVrFrNmzeKEE05gzJgxVXh10r7vs88+qwgafsmTTz7Je++9B0BMTAwJCQlkZGQwceJEpk6dyp133kmbNm12eKz9KFXO7vQkeI2UqkNMTMwuw7pAILDDr3udlMJvT/sRvEZKe8oAUHukS5cutGrViu7du9OqVauKf2g3btzIlClTGD9+PHPnzuXZZ5/lkksu2eE5xowZw9FHH71b4xYXF3PHHXeQnZ1NWloa48aNIz09ncLCQiZOnMj48eN55513SE9PZ9CgQVV+ndK+KDc3l6effprk5GRSUlJYsWLFTvf94IMPeO+99wgEAowYMYKhQ4eSkJDAkiVLeOCBB1i6dCl33HEHjz32GHFxcdscaz9KlbM7PVnOa6QUfo0bN+aZZ57ZrWO8TkrVY0/6sZzXSGnPOAeg9sjRRx/N0KFD6dSp0za/ZWnYsCGnn346p512GgAff/wxJSUlYRv3gw8+YPXq1SQkJHDLLbeQnp4OQEJCAsOGDWPw4MHAllvGwzmutC95/vnnyczMZOTIkTRs2HCn+xUXF/PKK68AWx6XGDZsGAkJCQCkp6dz8803k5CQwKpVq5gyZcp2x9uPUuVUtieryp6UwsvrpBQ97EfJAFDVpFOnTgAUFRWxadOmsJ33448/BqBfv340adJku+2nnnoqgUCAzMxM5syZE7ZxpX3Fd999x+TJk+nUqVPFDzI7M3v2bLKysggEApxyyinbbW/atCn9+vUD/r/3tmY/Sr9sd3qyquxJKby8TkrRw36UDABVTb7//ntgy9yA4brbIT8/nwULFgBw4IEH7nCfJk2a0Lp1awC+/fbbsIwr7SuKi4t57LHHCAQCXHzxxTtchGdrs2fPBqBNmzY7/EEIoHfv3gD88MMPFBQUVHzdfpR+2e72ZFXYk1L4eZ2UooP9KG3hHIAKm8LCQtatW8d//vMf3nrrLQCGDBmy0wlc33rrLV566SVycnJISkqiXbt29O3bl0GDBu1wUtcVK1YQCoUASEtL22kdaWlpLF++nOXLl4fhVUn7jtdff50VK1Zwwgkn0KFDh1/cv7xHfqmfAEKhECtWrKBjx46A/ShVxu725Na8Rkrhl52dzRVXXMHKlSsBaNSoET179uT444+nXbt22+3vdVKqPrvbj1vzGintGQNAVcnmzZs566yztvt6bGwsxx9/PCNHjtzpscuWLSM+Pp6EhARycnKYPXs2s2fP5l//+he33HLLdr9pzczMrPg4NTV1p+ct35aVlbW7L0faZy1fvpwJEyaQmprKiBEjKnVMeU9Vpp9g256yH6Vd25Oe3JrXSCn8CgsLWbJkCcnJyRQUFJCRkUFGRgYffvgho0eP5uSTT95mf6+TUvXZ3X7cmtdIac8YAKpKYmJiKh7xzcvLo6ioiEAgwPHHH8/JJ59MMBjc7phDDjmEHj160LNnz4ql3zMzM5kyZQqvvfYaS5cu5dZbb+XBBx/cZjW1rR+rKJ+AeUfKt+Xn54fjJUp7vVAoxOOPP05JSQkXXHDBNgvz7Ep5T1Wmn2BLj//82Moebz+qNtnTngSvkVJ1SE1NZfjw4fTt25eWLVsSFxdHSUkJ3333HS+++CLz58/nueeeIzU1lf79+1cc53VSCr897UfwGilVlXMAqkqSkpJ48cUXefHFF3n99dd5+umnOeGEE3jnnXe45JJL+O6777Y7ZsyYMfTt27fiH23YciE444wz+P3vfw9s+a3ORx99VGOvQ9qXffDBB3z33XccdNBBHHHEEZEuR6r1qtKTXiOl8OvduzfDhw8nLS2tIhSIjY2lV69e3H333XTp0gWAF154gbKyskiWKkW9qvSj10ipagwAFTaBQIBmzZpxwQUXcO6557Jp0ybuu+8+CgsLK32OQw45hO7duwPw5ZdfbrOtTp06FR/v6pzl2xITE3enfGmflJmZyQsvvEB8fDwXXnjhbh1b3lOV6Sdgm7uY7Edpx6rSk7/Ea6QUfnFxcRVT1qxfv57FixdXbPM6KdWsXfXjL/EaKf0yA0BVi2OPPZa4uDg2bNjAzJkzd+vY8t/6rF69epuvbz1fw9bzOPxc+baUlJTdGlfaF7344ovk5uYydOhQGjRoQH5+/jZ/yn9zWlpaut3XynuqMv0E2/aU/SjtWFV6sjK8RkrhV95XsG1veZ2Uat7O+nF3jvUaKe2YcwCqWsTHx1OvXj0yMzNZtWpVWM7ZunVrAoEAoVCIZcuWVSzT/nPLli0DoE2bNmEZV9qbrV27Ftiy2ujrr7++0/2mTp3K1KlTAXjooYdo3749bdq04auvvqromR0p3xYIBLbpOftR2rGq9GRV2JNS+HmdlKKD/Sht4R2Aqhb5+fnk5OQAu38L9Q8//ABAs2bNtvl6YmIinTp1AuDrr7/e4bHr16+vWLZ9//33361xpdqmV69ewJYfdtavX7/Dfb755htgy29Ut358wn6UIsNrpBR+5X0F2/aW10mp5u2sH3fnWK+R0o55B6B2W2lpKTExMQQCgZ3uM3HiREpKSgDo0aNHxddDodAuj/vyyy8rFg45+OCDt9s+YMAA5s+fzyeffMIZZ5yx3RLvb775JqFQiNTUVPbbb7/del3Svuiuu+7a5fYbbriBuXPnMnDgQK644opttvXq1YuUlBSysrJ46623GDNmzDbb161bxyeffAJs6b2fsx+l7VWlJ71GSuH3S31VUlLC+PHjAWjUqBEdOnSo2OZ1UgqvqvSj10ip6rwDULtt/fr1XHnllUyePJl169ZVfD0UCrF8+XKefPJJ/v73vwNw2GGHkZaWVrHPU089xVNPPcXcuXO3mYA1KyuL119/nXvvvReAtm3bcvTRR2839jHHHEPz5s0pKCjg9ttvZ8mSJcCWCVsnTJjAu+++C8DIkSOJjTXflnYlLi6Os846C4BJkyYxYcKEir5csmQJt99+OwUFBbRo0YJf//rX2x1vP0rh5TVSCr+1a9dy9dVX88EHH7BmzZqKr5eWljJ37lxuuOEGvv/+ewBGjx5NTMz/vz3yOimFV1X60WukVHWBUCgUinQR2resWbNmm9+AxsfHU6dOHQoKCigqKqr4ep8+fbjmmmu2eRzioYce4t///jewZa6U8tXScnNzK/Zp3749N95443a/lSm3bNkybrzxRrKzs4EtK64VFBRUTKJ+/PHHM3bs2DC9Wmnftqu7jco9+eSTvPfeewAEg0ESEhLIy8sDoGHDhtx55507nQvFfpR2z6560mukFH47+7k1Ly+v4mmV2NhYRo8ezdChQ3d4Dq+TUnhUpR+9RkpVZwCo3VZcXMx///tfZs+ezfz588nKyiInJ4e4uDgaNWpE586d6d+/PwceeOB2x37//fdMnz6dH374gbVr17Jp0ybKysqoV68eHTp04PDDD6dfv36/+FuXjRs38sYbbzBjxgzWr19PnTp1aN++PUOGDOHQQw+trpcu7XMqEwACTJ8+nffee4/FixdTUFBA48aNOfjggznttNNo0KDBLsewH6XK21VPeo2Uwq+wsJApU6Ywb948lixZQnZ2Nnl5eSQkJNCsWTP2228/Bg8eTKtWrXZ5Hq+TUtVVpR+9RkpVZwAoSZIkSZIkRTHnAJQkSZIkSZKimAGgJEmSJEmSFMUMACVJkiRJkqQoZgAoSZIkSZIkRTEDQEmSJEmSJCmKGQBKkiRJkiRJUcwAUJIkSZIkSYpiBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxQwAJUmSJEmSpChmAChJkiRJkiRFMQNASZIkSZIkKYoZAEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJ0l7m+eefJxAIEAgEeP755yNdjiRJkvZxBoCSJEmSJElSFDMAlCRJkiRJkqKYAaAkSZIkSZIUxQwAJUmSJEmSpChmAChJkiRJkiRFMQNASZJUa5WWltKyZUsCgQD16tUjLy/vF48pKiqicePGBAIBGjVqRFFRUcW2goICJk6cyGWXXUbfvn1p0qQJcXFx1KtXj06dOjFq1CimTJlS5bp//PHHilWCzznnnF/cv127dgQCAdq1a/eL+y5atIjrrruOPn360KRJE+Lj42nWrBkDBw7k4YcfrtTfkSRJkvYusZEuQJIkKVKCwSAjRozg/vvvZ/Pmzbz55puMHDlyl8e89957bNiwAYAzzjiD+Pj4im3du3dnyZIl2x2zefNmFi5cyMKFC3n55ZcZOnQoL7/8MnXr1g3vC6qCsrIybrrpJu677z5KSkq22bZ27VrWrl3Lf/7zH+6//37efvttDjrooAhVKkmSpN1lAChJkmq10aNHc//99wPw0ksv/WIA+OKLL1Z8fPbZZ2+zLS8vj4YNGzJw4EB69+5NWloaSUlJ5OTkMHv2bF577TVWrVrFxIkTOe+88/jHP/4R/he0h0aPHs3LL78MQGpqKmeccQYHHXQQ9evXZ+3atbz77rv861//YsWKFRx11FF89dVXdO7cOcJVS5IkqTIMACVJUq3Ws2dPevfuzTfffMNHH33EqlWraNGixQ73zczM5N133wWgc+fOHHroodtsf+655xg0aBBxcXE7PP7OO+9kxIgRvP3227z++utMmzaNI444IrwvaA/89a9/rQj/TjjhBF588UUaNmy4zT6/+93vePPNNznjjDPYtGkT5513HtOmTYtAtZIkSdpdzgEoSZJqvfI7+UpLSyuCsB35xz/+UTHn36hRo7bbPnjw4J2GfwBJSUm88MILJCcnA/DCCy9UpeywKCws5NZbbwWgW7duTJgwYbvwr9wpp5zCtddeC8Bnn33Gf//735oqU5IkSVVgAChJkmq9s846i9jYLQ9GvPTSSzvdr/zx30AgsMMAsDLq16/PfvvtB8AXX3yxR+cIp8mTJ7Nq1SoArrjiim3mNNyR0aNHV3z8wQcfVGttkiRJCg8fAZYkSbVe06ZNOfbYY5k0aRJz5sxh1qxZHHDAAdvss3DhQqZPnw5Av379SEtL2+G5srKyGD9+PO+//z5z585lw4YN5ObmEgqFttt3xYoVYX8tu+uTTz6p+HjTpk28/fbbu9y/uLi44uPvvvuuusqSJElSGBkASpIkseUx4EmTJgFb7vT7eQC49aPBP1/8o9zEiRM5//zzK1YJ/iU5OTl7VmwY/fjjjxUfX3311bt1bGZmZpirkSRJUnUwAJQkSQJOPPFEUlJSyMrK4u9//zv33XcfwWCwYnv5o8FJSUmcfvrp2x0/ffp0TjvtNEpKSgDo1asXgwYNomPHjqSkpJCQkEAgEADgpptu4n//+x9lZWU18Mp2bePGjXt8bPl8iJIkSdq7GQBKkiQBCQkJDBs2jL/+9a+sXr2ayZMnM3jwYGDLgheLFy8G4KSTTqJevXrbHX/LLbdUhH+PP/44F1988U7HuvPOO6vhFexcaWnpTrfVrVu34uPZs2dXzE8oSZKk6OEiIJIkST/Z+tHe8gU/fv7xjh7/LS4u5uOPPwbgoIMO2mX4B9s+drsnEhISKj7+pbvwQqHQLh/Vbd26dcXHy5cvr1JdkiRJ2jsZAEqSJP2kb9++dOrUCdgyn9+mTZsoLCzkH//4BwAtWrRg0KBB2x23fv36irv/OnbsuMsxvvzyS9avX1+lOhs2bFjx8cqVK3e576xZs8jLy9vp9v79+1d8/K9//atKdUmSJGnvZAAoSZK0lVGjRgGQn5/P66+/zqRJkyrmyRsxYsQ28wKWS05Orvh44cKFuzz/H/7whyrXmJiYSPv27QGYMWPGLhcTeeCBB3Z5rsGDB9OkSRMAnn322V+sX5IkSfseA0BJkqStjBo1qmKxjhdffPEXH/8FqF+/Pp07dwZg5syZTJgwYbt9SktLufLKK8N2l135/IQFBQVcf/31O9znoYce2mb14h1JTk7mj3/8IwB5eXkcc8wxfPPNN7s8ZuHChYwbN461a9fufuGSJEmqcYFQKBSKdBGSJEl7kwEDBjB16lQCgQDBYJCSkhIOOOCAXQZjTzzxRMXcf4FAgDPOOIP+/fuTkpLCwoULGT9+PPPmzaNnz54kJCQwc+ZMYMscfT/3/PPPc+655wLw3HPPcc4552y3z4IFC+jVqxcFBQUADBo0iNNPP52UlBSWL1/OhAkTmD59Ov3792fhwoWsXLmStLS0nc4/eP755/Pss89W1H/MMcdw9NFH07p1awKBAJmZmcybN49PP/2UWbNmAVvmDNx6DkFJkiTtnVwFWJIk6WfOPvtspk6dSigUqpjbb2d3/5W76KKL+Oqrr3j22WcJhUK8+uqrvPrqq9vss99++zFx4sSKcK8qOnXqxNNPP80555xDaWkpH374IR9++OE2+/Tr148333yTAw888BfP98wzz9ClSxduvfVW8vLyeP/993n//fd3un/jxo2pU6dOlV+HJEmSqp+PAEuSJP3M6aefTlJSUsXnsbGxnHXWWbs8JhAI8Le//Y033niDY445hkaNGhEXF0fz5s3p378/jz32GDNmzCA9PT1sdY4cOZKZM2cycuRI2rRpQ3x8PI0bN6Zfv34888wz/Pvf/yY1NbVS5woEAlx77bX8+OOP3HPPPQwaNIiWLVuSkJBAQkICzZo14/DDD+fyyy9n0qRJZGRk0Lhx47C9FkmSJFUfHwGWJEmSJEmSoph3AEqSJEmSJElRzABQkiRJkiRJimIGgJIkSZIkSVIUMwCUJEmSJEmSopgBoCRJkiRJkhTFDAAlSZIkSZKkKGYAKEmSJEmSJEUxA0BJkiRJkiQpihkASpIkSZIkSVHMAFCSJEmSJEmKYgaAkiRJkiRJUhQzAJQkSZIkSZKimAGgJEmSJEmSFMUMACVJkiRJkqQoZgAoSZIkSZIkRTEDQEmSJEmSJCmKGQBKkiRJkiRJUcwAUJIkSZIkSYpi/wcZfcOOL1zoCQAAAABJRU5ErkJggg==" + "image/png": 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}, "metadata": { "image/png": { @@ -8039,17 +10004,17 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 17, "id": "74970aaa-ed62-454f-9964-2b8d37eafa94", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "84.61410688701288" + "110.270450891279" ] }, - "execution_count": 22, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -8061,7 +10026,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 18, "id": "acf589e0-f08b-44c6-b24e-c837d36817f3", "metadata": { "scrolled": true @@ -8070,14 +10035,12 @@ { "data": { "text/plain": [ - "({'mortality': 0.05365088255575121},\n", - " {'escapement': 0.010338225232077163},\n", - " {'x1': 0.009159055923137423,\n", - " 'x2': 0.015139834077385755,\n", - " 'y2': 0.29119675741251316})" + "({'mortality': 0.04473718126536452},\n", + " {'escapement': 0.3972769224603838},\n", + " {'x1': 0.0, 'x2': 1.0, 'y2': 0.13207767948328275})" ] }, - "execution_count": 41, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -8124,26 +10087,18 @@ "execution_count": 19, "id": "83b0ac8e-01ca-412b-b31d-f7eaad268a5c", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-19 20:01:42,264\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:01:50,971\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:01:58,657\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:02:06,722\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:02:14,103\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:02:21,969\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:02:29,441\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:02:37,001\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:02:45,499\tINFO worker.py:1752 -- Started a local Ray instance.\n" + "ename": "NameError", + "evalue": "name 'msy_gbrt_args' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[19], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m pol_env \u001b[38;5;241m=\u001b[39m AsmEnv(config\u001b[38;5;241m=\u001b[39mCONFIG)\n\u001b[1;32m 3\u001b[0m msy_rews \u001b[38;5;241m=\u001b[39m eval_pol(\n\u001b[0;32m----> 4\u001b[0m policy\u001b[38;5;241m=\u001b[39mMsy(env\u001b[38;5;241m=\u001b[39mpol_env, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[43mmsy_gbrt_args\u001b[49m), \n\u001b[1;32m 5\u001b[0m env_cls\u001b[38;5;241m=\u001b[39mAsmEnv, config\u001b[38;5;241m=\u001b[39mPPO_CONFIG, \n\u001b[1;32m 6\u001b[0m n_batches\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, batch_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m200\u001b[39m,\n\u001b[1;32m 7\u001b[0m )\n\u001b[1;32m 9\u001b[0m esc_rews \u001b[38;5;241m=\u001b[39m eval_pol(\n\u001b[1;32m 10\u001b[0m policy\u001b[38;5;241m=\u001b[39mConstEsc(env\u001b[38;5;241m=\u001b[39mpol_env, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mesc_gbrt_args), \n\u001b[1;32m 11\u001b[0m env_cls\u001b[38;5;241m=\u001b[39mAsmEnv, config\u001b[38;5;241m=\u001b[39mPPO_CONFIG, \n\u001b[1;32m 12\u001b[0m n_batches\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, batch_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m200\u001b[39m,\n\u001b[1;32m 13\u001b[0m )\n\u001b[1;32m 15\u001b[0m cr_rews \u001b[38;5;241m=\u001b[39m eval_pol(\n\u001b[1;32m 16\u001b[0m policy\u001b[38;5;241m=\u001b[39mCautionaryRule(env\u001b[38;5;241m=\u001b[39mpol_env, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mcr_gbrt_args), \n\u001b[1;32m 17\u001b[0m env_cls\u001b[38;5;241m=\u001b[39mAsmEnv, config\u001b[38;5;241m=\u001b[39mPPO_CONFIG, \n\u001b[1;32m 18\u001b[0m n_batches\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, batch_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m200\u001b[39m,\n\u001b[1;32m 19\u001b[0m )\n", + "\u001b[0;31mNameError\u001b[0m: name 'msy_gbrt_args' is not defined" ] } ], @@ -8153,19 +10108,19 @@ "msy_rews = eval_pol(\n", " policy=Msy(env=pol_env, **msy_gbrt_args), \n", " env_cls=AsmEnv, config=PPO_CONFIG, \n", - " n_batches=3, batch_size=120\n", + " n_batches=1, batch_size=200,\n", ")\n", "\n", "esc_rews = eval_pol(\n", " policy=ConstEsc(env=pol_env, **esc_gbrt_args), \n", " env_cls=AsmEnv, config=PPO_CONFIG, \n", - " n_batches=3, batch_size=120\n", + " n_batches=1, batch_size=200,\n", ")\n", "\n", "cr_rews = eval_pol(\n", " policy=CautionaryRule(env=pol_env, **cr_gbrt_args), \n", " env_cls=AsmEnv, config=PPO_CONFIG, \n", - " n_batches=3, batch_size=120\n", + " n_batches=1, batch_size=200,\n", ")" ] }, From 659fdc4f951699d24d9715f1f7c8900e44eeeaeb Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Mon, 6 May 2024 20:44:34 +0000 Subject: [PATCH 30/64] added a ray train util --- src/rl4fisheries/utils/ray.py | 49 +++++++++++++++++++++++++++++++++++ 1 file changed, 49 insertions(+) create mode 100644 src/rl4fisheries/utils/ray.py diff --git a/src/rl4fisheries/utils/ray.py b/src/rl4fisheries/utils/ray.py new file mode 100644 index 0000000..43267e2 --- /dev/null +++ b/src/rl4fisheries/utils/ray.py @@ -0,0 +1,49 @@ +import gymnasium as gym +from ray.tune.registry import register_env +from ray.rllib.algorithms.ppo import PPOConfig + +from rl4fisheries import AsmEnv + +def algorithm(algo_name, algo_config, env_name): + algo_configs = {'PPO': PPOConfig, 'ppo': PPOConfig} + return ( + algo_configs[algo_name] + .training(algo_config) + .build(env = env_name) + ) + + +def ray_train(config_file, **kwargs): + with open(config_file, "r") as stream: + options = yaml.safe_load(stream) + options = {**options, **kwargs} + + register_env(options["env_id"], lambda config: gym.make(options["env_id"], kwargs=options["config"])) + + # getting the config translated to Ray + algo_config_sb3 = options["algo_config"] + algo_config = {} + if "learning_rate" in algo_config_sb3: + algo_config["lr"] = algo_config_sb3["learning_rate"] + if "labmda" in algo_config_sb3: + algo_config["lambda"] = algo_config_sb3["lambda"] + if "tau" in algo_config_sb3: + algo_config["tau"] = algo_config_sb3["tau"] + if "clip_range" in algo_config_sb3: + algo_config["clip_param"] = algo_config_sb3["clip_range"] + if "batch_size" in algo_config_sb3: + algo_config["train_batch_size"] = algo_config_sb3["batch_size"] + # + agent = algorithm( + algo_name = options["algo"], + algo_config=algo_config, + env_name=options["env_id"], + ) + # + iterations = options.get("iterations", 300) + for i in range(iterations): + print(f"{options['algo']} iteration nr. {i} ", end="\r") + agent.train() + + agent.save_checkpoint(options["save_path"]) + \ No newline at end of file From 2aa8bd86cc5589fdb087cbba3e6adbb6bab749db Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Mon, 6 May 2024 20:45:52 +0000 Subject: [PATCH 31/64] allow custom harvest and vulnerability curves --- src/rl4fisheries/envs/asm_env.py | 38 ++++++++++++++++++++++++-------- 1 file changed, 29 insertions(+), 9 deletions(-) diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index 41356c5..c990918 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -84,8 +84,16 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): rho=self.parameters["rho"], ) self.noiseless = config.get('noiseless', False) - self.use_custom_vul = config.get('use_custom_vul', False) - self.custom_vul = config.get('custom_vul', np.ones(self.parameters["n_age"])) + self.use_custom_harv_vul = config.get('use_custom_harv_vul', False) + self.custom_harv_vul = config.get( + 'custom_harv_vul', + np.ones(self.parameters["n_age"]), + ) + self.use_custom_surv_vul = config.get('use_custom_surv_vul', False) + self.custom_surv_vul = config.get( + 'custom_surv_vul', + np.ones(self.parameters["n_age"]), + ) default_init = self.initialize_population() self.init_state = config.get("init_state", equib_init) @@ -147,8 +155,10 @@ def reset(self, *, seed=None, options=None): self.timestep = 0 self.state = self.initialize_population() # - if self.use_custom_vul: - self.parameters["harvest_vul"] = self.custom_vul + # if self.use_custom_harv_vul: + # self.parameters["harvest_vul"] = self.custom_harv_vul + # if self.use_custom_surv_vul: + # self.parameters["survey_vul"] = self.custom_surv_vul # self.state = self.init_state * np.array( np.random.uniform(0.1, 1), dtype=np.float32 @@ -302,17 +312,27 @@ def initialize_population(self): # put it all in self so we can reference later self.parameters["Lo"] = Lo self.parameters["Lf"] = Lf - self.parameters["survey_vul"] = survey_vul - self.parameters["harvest_vul"] = harvest_vul # TBD: change! + # + # + if self.use_custom_harv_vul: + self.parameters["harvest_vul"] = self.custom_harv_vul + else: + self.parameters["harvest_vul"] = harvest_vul + # + if self.use_custom_surv_vul: + self.parameters["survey_vul"] = self.custom_surv_vul + else: + self.parameters["survey_vul"] = survey_vul + # + # self.parameters["wt"] = wt self.parameters["min_wt"] = np.min(wt) self.parameters["max_wt"] = np.max(wt) self.parameters["mwt"] = mwt + # self.parameters["bha"] = bha self.parameters["bhb"] = bhb - # self.parameters["p_big"] = 0.05 no need to reinitialize - # self.parameters["sdr"] = 0.3 - # self.parameters["rho"] = 0 + # n = np.array(ninit, dtype=np.float32) self.state = np.clip(n, 0, np.Inf) return self.state From 233381b721f3eeee9d4a3779b02ad38e4a4461b0 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Tue, 7 May 2024 18:20:07 +0000 Subject: [PATCH 32/64] added asm CR-like --- src/rl4fisheries/envs/asm_cr_like.py | 77 ++++++++++++++++++++++++++++ 1 file changed, 77 insertions(+) create mode 100644 src/rl4fisheries/envs/asm_cr_like.py diff --git a/src/rl4fisheries/envs/asm_cr_like.py b/src/rl4fisheries/envs/asm_cr_like.py new file mode 100644 index 0000000..08266c4 --- /dev/null +++ b/src/rl4fisheries/envs/asm_cr_like.py @@ -0,0 +1,77 @@ +import gymnasium as gym +import numpy as np + +from rl4fisheries import AsmEnv + +class AsmCRLike(AsmEnv): + """ observe mean weight, decide on a CR-like policy for biomass. """ + def __init__(self, render_mode = 'rgb_array', config={}): + super().__init__(render_mode=render_mode, config=config) + assert config.get("observation_fn_id", "observe_2o") == "observe_2o", ( + "AsmCRLike only compatible with observe_2o observation function atm, sorry!" + ) + self.action_space = gym.spaces.Box( + np.array(3 * [-1], dtype=np.float32), + np.array(3 * [1], dtype=np.float32), + dtype=np.float32, + ) + self.observation_space = gym.spaces.Box( + np.array([-1], dtype=np.float32), + np.array([1], dtype=np.float32), + dtype=np.float32, + ) + + def reset(self, *, seed=None, options=None): + obs, info = super().reset(seed=seed, options=options) + return np.array([obs[1]]), info + + def step(self, action): + self.update_vuls() + self.update_ssb() + # + x1, x2, y2 = self.unnormalize_action(action) + self.state, reward = self.harvest(x1, x2, y2) + # + self.update_vuls() + self.update_ssb() + # + self.state = self.population_growth() + self.timestep += 1 + terminated = bool(self.timestep >= self.n_year) + # + observation = self.observe() + # + return observation, reward, terminated, False, {} + + def unnormalize_action(self, action): + x1 = self.bound * (action[0] + 1) / 2 + x2 = self.bound * (action[1] + 1) / 2 + y2 = (action[2] + 1) / 2 + return np.float32([x1,x2,y2]) + + def harvest(self, x1, x2, y2): + if self.surv_vul_b < x1: + intensity = 0 + elif x1 <= self.surv_vul_b < x2: + intensity = y2 * (self.surv_vul_b - x1) / (x2 - x1) + else: # vul_b >= x2 + intensity = y2 + + f_yield = self.harv_vul_b * intensity + new_state = self.parameters["s"] * self.state * (1 - self.parameters["harvest_vul"] * intensity) + + return new_state, reward + + + + + + + + + + + + + + \ No newline at end of file From 1942489fbc0716558dab039fb0d61e31cdabb2fb Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Tue, 7 May 2024 19:48:32 +0000 Subject: [PATCH 33/64] good hyperpars for ppo? --- hyperpars/ppo-asm.yml | 17 +- hyperpars/rppo-asm.yml | 8 +- hyperpars/tqc-asm.yml | 14 +- notebooks/optimal-fixed-policy.ipynb | 11009 ++++++++++--------------- src/rl4fisheries/__init__.py | 3 + src/rl4fisheries/envs/asm_cr_like.py | 46 +- src/rl4fisheries/envs/asm_fns.py | 17 + 7 files changed, 4433 insertions(+), 6681 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index f7cfecd..00ff07e 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,11 +1,11 @@ # algo algo: "PPO" -total_timesteps: 5000000 +total_timesteps: 15000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 256 + batch_size: 512 gamma: 0.9999 learning_rate: !!float 7.77e-05 ent_coef: 0.00429 @@ -14,18 +14,21 @@ algo_config: max_grad_norm: 5 vf_coef: 0.19 use_sde: True - policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False)" + policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + # in policy_kwargs: net_arch=[256, 128] # policy: 'MlpPolicy' # use_sde: True # policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" # clip_range: 0.1 # env -env_id: "AsmEnv" +env_id: "AsmCRLike" config: - observation_fn_id: 'observe_1o' - n_observs: 1 + observation_fn_id: 'observe_2o' + n_observs: 2 upow: 0.6 + use_custom_harv_vul: True + use_custom_surv_vul: True n_envs: 12 # io @@ -33,5 +36,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "1o-mtCarContv0-upow0.6" +id: "2o-lgBatch-256,128-upow0.6-flatHarvSurv" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/rppo-asm.yml b/hyperpars/rppo-asm.yml index c57a55f..848177b 100644 --- a/hyperpars/rppo-asm.yml +++ b/hyperpars/rppo-asm.yml @@ -118,7 +118,7 @@ save_path: "../saved_agents" # # MOUNTAIN CAR NO VEL -id: "mount_car" +id: "MtCar-[256,128]" algo_config: tensorboard_log: "../../../logs" policy: 'MlpLstmPolicy' @@ -134,10 +134,10 @@ algo_config: vf_coef: 0.19 use_sde: True sde_sample_freq: 8 - policy_kwargs: "dict(log_std_init=0.0, ortho_init=False, - lstm_hidden_size=32, + policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, + lstm_hidden_size=64, enable_critic_lstm=True, - net_arch=dict(pi=[64], vf=[64]))" + net_arch=dict(pi=[256,128], vf=[256,128]))" # SPACE INVADERS V4 # id: "space_invaders" diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index 5947e89..ea8defd 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -1,11 +1,11 @@ # algo algo: "TQC" -total_timesteps: 5000000 +total_timesteps: 10000000 algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' learning_rate: !!float 7.3e-4 - buffer_size: 200000 + buffer_size: 500000 batch_size: 512 ent_coef: 'auto' gamma: 0.98 @@ -14,14 +14,16 @@ algo_config: gradient_steps: 64 learning_starts: 20000 use_sde: True - policy_kwargs: "dict(log_std_init=-3, net_arch=[256, 128])" + policy_kwargs: "dict(log_std_init=-3, net_arch=[128, 64])" # env env_id: "AsmEnv" config: - observation_fn_id: 'observe_1o' - n_observs: 1 + observation_fn_id: 'observe_2o' + n_observs: 2 upow: 0.6 + use_custom_harv_vul: True + use_custom_surv_vul: True n_envs: 12 # io @@ -29,5 +31,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "1o-upow0.6" +id: "2o-upow0.6-flatHarvSurv" additional_imports: ["torch"] diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index 6921c02..92ee099 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "236788a7-ed25-46bd-a9b0-f7301e96cacf", "metadata": {}, "outputs": [], @@ -68,6 +68,8 @@ " 'observation_fn_id': 'observe_1o',\n", " 'n_observs': 1,\n", " 'upow': 0.6,\n", + " 'use_custom_harv_vul': True,\n", + " 'use_custom_surv_vul': True,\n", "}" ] }, @@ -120,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "38838cb2-44df-404b-9cd8-4ecfc9347dd9", "metadata": {}, "outputs": [], @@ -169,7 +171,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 12, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], @@ -177,7 +179,7 @@ "msy_space = [Real(0.001, 0.25, name='mortality')]\n", "log_esc_space = [Real(-6, 2, name='log_escapement')]\n", "cr_space = [\n", - " Real(-5, 0, name='log_radius'),\n", + " Real(-5, 2, name='log_radius'),\n", " Real(0., np.pi/4.00001, name='theta'),\n", " Real(0, 1, name='y2'),\n", "]\n", @@ -243,7 +245,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 31, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { "scrolled": true @@ -260,7 +262,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:11:14,787\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:38:19,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -268,9 +270,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 7.6175\n", - "Function value obtained: -54.8470\n", - "Current minimum: -54.8470\n", + "Time taken: 10.9241\n", + "Function value obtained: -5.0780\n", + "Current minimum: -5.0780\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -278,7 +280,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:11:22,686\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:38:30,649\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -286,9 +288,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 8.3440\n", - "Function value obtained: -10.2549\n", - "Current minimum: -54.8470\n", + "Time taken: 10.5288\n", + "Function value obtained: -6.5391\n", + "Current minimum: -6.5391\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -296,7 +298,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:11:30,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:38:41,187\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -304,9 +306,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 7.0552\n", - "Function value obtained: -10.3992\n", - "Current minimum: -54.8470\n", + "Time taken: 10.3549\n", + "Function value obtained: -11.9424\n", + "Current minimum: -11.9424\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -314,7 +316,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:11:37,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:38:51,452\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -322,9 +324,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 7.1076\n", - "Function value obtained: -61.3399\n", - "Current minimum: -61.3399\n", + "Time taken: 10.4696\n", + "Function value obtained: -5.0848\n", + "Current minimum: -11.9424\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -332,7 +334,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:11:44,744\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:39:01,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -340,9 +342,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 7.1964\n", - "Function value obtained: -123.6052\n", - "Current minimum: -123.6052\n", + "Time taken: 10.6285\n", + "Function value obtained: -96.7727\n", + "Current minimum: -96.7727\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -350,7 +352,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:11:51,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:39:12,586\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -358,9 +360,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 7.2913\n", - "Function value obtained: -122.0412\n", - "Current minimum: -123.6052\n", + "Time taken: 11.2769\n", + "Function value obtained: -16.2514\n", + "Current minimum: -96.7727\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -368,7 +370,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:11:59,247\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:39:23,874\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -376,9 +378,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 7.4194\n", - "Function value obtained: -117.4966\n", - "Current minimum: -123.6052\n", + "Time taken: 10.7036\n", + "Function value obtained: -25.2132\n", + "Current minimum: -96.7727\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -386,7 +388,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:12:06,673\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:39:34,554\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -394,9 +396,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 7.3481\n", - "Function value obtained: -34.1646\n", - "Current minimum: -123.6052\n", + "Time taken: 10.2216\n", + "Function value obtained: -4.5589\n", + "Current minimum: -96.7727\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -404,7 +406,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:12:14,028\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:39:44,818\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -412,9 +414,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 6.9550\n", - "Function value obtained: -48.1777\n", - "Current minimum: -123.6052\n", + "Time taken: 10.4010\n", + "Function value obtained: -103.1378\n", + "Current minimum: -103.1378\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -422,7 +424,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:12:21,452\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:39:55,261\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -430,9 +432,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 12.4731\n", - "Function value obtained: -55.4513\n", - "Current minimum: -123.6052\n", + "Time taken: 15.1215\n", + "Function value obtained: -4.4069\n", + "Current minimum: -103.1378\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -440,7 +442,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:12:33,525\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:40:10,290\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -448,9 +450,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4841\n", - "Function value obtained: -122.4503\n", - "Current minimum: -123.6052\n", + "Time taken: 12.0153\n", + "Function value obtained: -23.1285\n", + "Current minimum: -103.1378\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -458,7 +460,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:12:42,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:40:22,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -466,9 +468,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6229\n", - "Function value obtained: -127.2857\n", - "Current minimum: -127.2857\n", + "Time taken: 12.5079\n", + "Function value obtained: -107.7270\n", + "Current minimum: -107.7270\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -476,7 +478,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:12:50,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:40:34,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -484,9 +486,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5412\n", - "Function value obtained: -123.8198\n", - "Current minimum: -127.2857\n", + "Time taken: 12.2868\n", + "Function value obtained: -109.1133\n", + "Current minimum: -109.1133\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -494,7 +496,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:12:59,232\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:40:47,242\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -502,9 +504,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1859\n", - "Function value obtained: -124.7299\n", - "Current minimum: -127.2857\n", + "Time taken: 11.7974\n", + "Function value obtained: -111.9426\n", + "Current minimum: -111.9426\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -512,7 +514,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:13:09,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:40:58,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -520,9 +522,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5702\n", - "Function value obtained: -119.6652\n", - "Current minimum: -127.2857\n", + "Time taken: 12.0254\n", + "Function value obtained: -110.3378\n", + "Current minimum: -111.9426\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -530,7 +532,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:13:17,991\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:41:11,075\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -538,9 +540,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9790\n", - "Function value obtained: -124.1273\n", - "Current minimum: -127.2857\n", + "Time taken: 11.9932\n", + "Function value obtained: -111.3267\n", + "Current minimum: -111.9426\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -548,7 +550,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:13:26,921\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:41:23,018\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -556,9 +558,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9641\n", - "Function value obtained: -126.8413\n", - "Current minimum: -127.2857\n", + "Time taken: 11.9634\n", + "Function value obtained: -109.2417\n", + "Current minimum: -111.9426\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -566,7 +568,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:13:35,910\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:41:34,958\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -574,9 +576,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9626\n", - "Function value obtained: -121.7985\n", - "Current minimum: -127.2857\n", + "Time taken: 11.3712\n", + "Function value obtained: -108.7872\n", + "Current minimum: -111.9426\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -584,7 +586,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:13:44,884\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:41:46,326\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -592,9 +594,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8622\n", - "Function value obtained: -123.6838\n", - "Current minimum: -127.2857\n", + "Time taken: 10.8733\n", + "Function value obtained: -107.6917\n", + "Current minimum: -111.9426\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -602,7 +604,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:13:52,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:41:57,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -610,9 +612,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2900\n", - "Function value obtained: -9.0585\n", - "Current minimum: -127.2857\n", + "Time taken: 11.8074\n", + "Function value obtained: -109.3046\n", + "Current minimum: -111.9426\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -620,7 +622,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:01,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:42:09,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -628,9 +630,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2339\n", - "Function value obtained: -124.7479\n", - "Current minimum: -127.2857\n", + "Time taken: 11.4811\n", + "Function value obtained: -94.0775\n", + "Current minimum: -111.9426\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -638,7 +640,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:09,291\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:42:20,608\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -646,9 +648,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0172\n", - "Function value obtained: -121.9862\n", - "Current minimum: -127.2857\n", + "Time taken: 10.6783\n", + "Function value obtained: -108.1891\n", + "Current minimum: -111.9426\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -656,7 +658,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:17,307\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:42:31,278\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -664,9 +666,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9542\n", - "Function value obtained: -123.1853\n", - "Current minimum: -127.2857\n", + "Time taken: 11.0614\n", + "Function value obtained: -107.6197\n", + "Current minimum: -111.9426\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -674,7 +676,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:25,282\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:42:42,359\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -682,9 +684,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0674\n", - "Function value obtained: -120.4783\n", - "Current minimum: -127.2857\n", + "Time taken: 11.4596\n", + "Function value obtained: -110.1922\n", + "Current minimum: -111.9426\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -692,7 +694,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:33,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:42:53,809\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -700,9 +702,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1974\n", - "Function value obtained: -120.4659\n", - "Current minimum: -127.2857\n", + "Time taken: 10.8389\n", + "Function value obtained: -107.7807\n", + "Current minimum: -111.9426\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -710,7 +712,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:41,668\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:43:04,600\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -718,9 +720,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1946\n", - "Function value obtained: -122.7296\n", - "Current minimum: -127.2857\n", + "Time taken: 10.6981\n", + "Function value obtained: -113.1969\n", + "Current minimum: -113.1969\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -728,7 +730,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:49,727\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:43:16,765\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -736,9 +738,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2397\n", - "Function value obtained: -121.5272\n", - "Current minimum: -127.2857\n", + "Time taken: 11.8803\n", + "Function value obtained: -8.2370\n", + "Current minimum: -113.1969\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -746,7 +748,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:14:58,015\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:43:27,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -754,9 +756,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1334\n", - "Function value obtained: -119.4227\n", - "Current minimum: -127.2857\n", + "Time taken: 11.0923\n", + "Function value obtained: -108.0523\n", + "Current minimum: -113.1969\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -764,7 +766,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:15:06,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:43:39,948\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -772,9 +774,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3177\n", - "Function value obtained: -125.5835\n", - "Current minimum: -127.2857\n", + "Time taken: 12.8120\n", + "Function value obtained: -110.0747\n", + "Current minimum: -113.1969\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -782,7 +784,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:15:14,468\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 23:43:51,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -790,5990 +792,1131 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2952\n", - "Function value obtained: -123.7889\n", - "Current minimum: -127.2857\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" + "Time taken: 11.1298\n", + "Function value obtained: -110.4563\n", + "Current minimum: -113.1969\n", + "CPU times: user 3min 9s, sys: 4min 58s, total: 8min 8s\n", + "Wall time: 5min 42s\n" ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:15:22,796\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] + "data": { + "text/plain": [ + "(-113.19689737573121, [0.027374341105189527])" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "msy_gp.fun, msy_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true, + "source_hidden": true }, + "scrolled": true + }, + "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 1.3560\n", + "Function value obtained: -46.5391\n", + "Current minimum: -46.5391\n", + "Iteration No: 2 started. Evaluating function at random point.\n", + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 1.1664\n", + "Function value obtained: -4.6581\n", + "Current minimum: -46.5391\n", + "Iteration No: 3 started. Evaluating function at random point.\n", + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 1.3000\n", + "Function value obtained: -14.8136\n", + "Current minimum: -46.5391\n", + "Iteration No: 4 started. Evaluating function at random point.\n", + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 1.2598\n", + "Function value obtained: -3.6463\n", + "Current minimum: -46.5391\n", + "Iteration No: 5 started. Evaluating function at random point.\n", + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 1.1637\n", + "Function value obtained: -4.3602\n", + "Current minimum: -46.5391\n", + "Iteration No: 6 started. Evaluating function at random point.\n", + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 1.2462\n", + "Function value obtained: -4.0893\n", + "Current minimum: -46.5391\n", + "Iteration No: 7 started. Evaluating function at random point.\n", + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 1.2717\n", + "Function value obtained: -10.5623\n", + "Current minimum: -46.5391\n", + "Iteration No: 8 started. Evaluating function at random point.\n", + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 1.2456\n", + "Function value obtained: -38.1398\n", + "Current minimum: -46.5391\n", + "Iteration No: 9 started. Evaluating function at random point.\n", + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 1.2314\n", + "Function value obtained: -48.0675\n", + "Current minimum: -48.0675\n", + "Iteration No: 10 started. Evaluating function at random point.\n", + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 1.4094\n", + "Function value obtained: -6.6195\n", + "Current minimum: -48.0675\n", + "Iteration No: 11 started. Searching for the next optimal point.\n", + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4140\n", + "Function value obtained: -49.6017\n", + "Current minimum: -49.6017\n", + "Iteration No: 12 started. Searching for the next optimal point.\n", + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4435\n", + "Function value obtained: -46.6843\n", + "Current minimum: -49.6017\n", + "Iteration No: 13 started. Searching for the next optimal point.\n", + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4193\n", + "Function value obtained: -45.0990\n", + "Current minimum: -49.6017\n", + "Iteration No: 14 started. Searching for the next optimal point.\n", + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5035\n", + "Function value obtained: -46.8608\n", + "Current minimum: -49.6017\n", + "Iteration No: 15 started. Searching for the next optimal point.\n", + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5919\n", + "Function value obtained: -49.3540\n", + "Current minimum: -49.6017\n", + "Iteration No: 16 started. Searching for the next optimal point.\n", + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4357\n", + "Function value obtained: -47.5765\n", + "Current minimum: -49.6017\n", + "Iteration No: 17 started. Searching for the next optimal point.\n", + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4996\n", + "Function value obtained: -45.1326\n", + "Current minimum: -49.6017\n", + "Iteration No: 18 started. Searching for the next optimal point.\n", + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4617\n", + "Function value obtained: -46.9510\n", + "Current minimum: -49.6017\n", + "Iteration No: 19 started. Searching for the next optimal point.\n", + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4780\n", + "Function value obtained: -12.6043\n", + "Current minimum: -49.6017\n", + "Iteration No: 20 started. Searching for the next optimal point.\n", + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4956\n", + "Function value obtained: -48.6197\n", + "Current minimum: -49.6017\n", + "Iteration No: 21 started. Searching for the next optimal point.\n", + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4565\n", + "Function value obtained: -45.1803\n", + "Current minimum: -49.6017\n", + "Iteration No: 22 started. Searching for the next optimal point.\n", + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3789\n", + "Function value obtained: -48.0291\n", + "Current minimum: -49.6017\n", + "Iteration No: 23 started. Searching for the next optimal point.\n", + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4518\n", + "Function value obtained: -47.8936\n", + "Current minimum: -49.6017\n", + "Iteration No: 24 started. Searching for the next optimal point.\n", + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4929\n", + "Function value obtained: -46.8791\n", + "Current minimum: -49.6017\n", + "Iteration No: 25 started. Searching for the next optimal point.\n", + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5805\n", + "Function value obtained: -48.7646\n", + "Current minimum: -49.6017\n", + "Iteration No: 26 started. Searching for the next optimal point.\n", + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4410\n", + "Function value obtained: -45.4169\n", + "Current minimum: -49.6017\n", + "Iteration No: 27 started. Searching for the next optimal point.\n", + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5256\n", + "Function value obtained: -46.7357\n", + "Current minimum: -49.6017\n", + "Iteration No: 28 started. Searching for the next optimal point.\n", + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5359\n", + "Function value obtained: -46.2242\n", + "Current minimum: -49.6017\n", + "Iteration No: 29 started. Searching for the next optimal point.\n", + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5400\n", + "Function value obtained: -12.6620\n", + "Current minimum: -49.6017\n", + "Iteration No: 30 started. Searching for the next optimal point.\n", + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6019\n", + "Function value obtained: -43.9229\n", + "Current minimum: -49.6017\n", + "Iteration No: 31 started. Searching for the next optimal point.\n", "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5224\n", - "Function value obtained: -123.3614\n", - "Current minimum: -127.2857\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:15:31,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4984\n", + "Function value obtained: -47.8351\n", + "Current minimum: -49.6017\n", + "Iteration No: 32 started. Searching for the next optimal point.\n", "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1022\n", - "Function value obtained: -123.0724\n", - "Current minimum: -127.2857\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:15:39,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5293\n", + "Function value obtained: -44.4191\n", + "Current minimum: -49.6017\n", + "Iteration No: 33 started. Searching for the next optimal point.\n", "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5146\n", - "Function value obtained: -120.6817\n", - "Current minimum: -127.2857\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:15:47,986\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4842\n", + "Function value obtained: -47.5384\n", + "Current minimum: -49.6017\n", + "Iteration No: 34 started. Searching for the next optimal point.\n", "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3151\n", - "Function value obtained: -124.2780\n", - "Current minimum: -127.2857\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:15:56,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6029\n", + "Function value obtained: -47.4318\n", + "Current minimum: -49.6017\n", + "Iteration No: 35 started. Searching for the next optimal point.\n", "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4350\n", - "Function value obtained: -122.4030\n", - "Current minimum: -127.2857\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:16:04,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4040\n", + "Function value obtained: -44.8686\n", + "Current minimum: -49.6017\n", + "Iteration No: 36 started. Searching for the next optimal point.\n", "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4938\n", - "Function value obtained: -119.6260\n", - "Current minimum: -127.2857\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:16:13,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5284\n", + "Function value obtained: -47.4501\n", + "Current minimum: -49.6017\n", + "Iteration No: 37 started. Searching for the next optimal point.\n", "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2929\n", - "Function value obtained: -120.0802\n", - "Current minimum: -127.2857\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:16:21,536\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.3685\n", + "Function value obtained: -47.0818\n", + "Current minimum: -49.6017\n", + "Iteration No: 38 started. Searching for the next optimal point.\n", "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2857\n", - "Function value obtained: -125.4253\n", - "Current minimum: -127.2857\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:16:29,771\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4836\n", + "Function value obtained: -46.7556\n", + "Current minimum: -49.6017\n", + "Iteration No: 39 started. Searching for the next optimal point.\n", "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4954\n", - "Function value obtained: -120.5625\n", - "Current minimum: -127.2857\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:16:38,229\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5081\n", + "Function value obtained: -46.9364\n", + "Current minimum: -49.6017\n", + "Iteration No: 40 started. Searching for the next optimal point.\n", "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3361\n", - "Function value obtained: -121.0406\n", - "Current minimum: -127.2857\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:16:46,607\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4114\n", + "Function value obtained: -46.0513\n", + "Current minimum: -49.6017\n", + "Iteration No: 41 started. Searching for the next optimal point.\n", "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3899\n", - "Function value obtained: -118.3589\n", - "Current minimum: -127.2857\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:16:55,979\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4602\n", + "Function value obtained: -47.1258\n", + "Current minimum: -49.6017\n", + "Iteration No: 42 started. Searching for the next optimal point.\n", "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2630\n", - "Function value obtained: -123.8028\n", - "Current minimum: -127.2857\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:17:04,240\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4598\n", + "Function value obtained: -44.6687\n", + "Current minimum: -49.6017\n", + "Iteration No: 43 started. Searching for the next optimal point.\n", "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1514\n", - "Function value obtained: -122.1566\n", - "Current minimum: -127.2857\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:17:12,396\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4767\n", + "Function value obtained: -45.9894\n", + "Current minimum: -49.6017\n", + "Iteration No: 44 started. Searching for the next optimal point.\n", "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8708\n", - "Function value obtained: -122.6544\n", - "Current minimum: -127.2857\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:17:20,285\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5332\n", + "Function value obtained: -46.3990\n", + "Current minimum: -49.6017\n", + "Iteration No: 45 started. Searching for the next optimal point.\n", "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0417\n", - "Function value obtained: -124.6074\n", - "Current minimum: -127.2857\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:17:28,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5325\n", + "Function value obtained: -47.7062\n", + "Current minimum: -49.6017\n", + "Iteration No: 46 started. Searching for the next optimal point.\n", "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8086\n", - "Function value obtained: -126.2508\n", - "Current minimum: -127.2857\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:17:37,112\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5390\n", + "Function value obtained: -47.8023\n", + "Current minimum: -49.6017\n", + "Iteration No: 47 started. Searching for the next optimal point.\n", "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7718\n", - "Function value obtained: -118.2078\n", - "Current minimum: -127.2857\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:17:44,988\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4629\n", + "Function value obtained: -45.6460\n", + "Current minimum: -49.6017\n", + "Iteration No: 48 started. Searching for the next optimal point.\n", "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0034\n", - "Function value obtained: -124.1550\n", - "Current minimum: -127.2857\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:17:52,929\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5021\n", + "Function value obtained: -44.3852\n", + "Current minimum: -49.6017\n", + "Iteration No: 49 started. Searching for the next optimal point.\n", "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9937\n", - "Function value obtained: -123.0761\n", - "Current minimum: -127.2857\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:00,929\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4780\n", + "Function value obtained: -46.6708\n", + "Current minimum: -49.6017\n", + "Iteration No: 50 started. Searching for the next optimal point.\n", "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9815\n", - "Function value obtained: -120.6253\n", - "Current minimum: -127.2857\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:08,896\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4235\n", + "Function value obtained: -45.2947\n", + "Current minimum: -49.6017\n", + "Iteration No: 51 started. Searching for the next optimal point.\n", "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7605\n", - "Function value obtained: -123.7669\n", - "Current minimum: -127.2857\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:16,664\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4191\n", + "Function value obtained: -47.4422\n", + "Current minimum: -49.6017\n", + "Iteration No: 52 started. Searching for the next optimal point.\n", "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5621\n", - "Function value obtained: -122.1211\n", - "Current minimum: -127.2857\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:24,248\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5193\n", + "Function value obtained: -47.2893\n", + "Current minimum: -49.6017\n", + "Iteration No: 53 started. Searching for the next optimal point.\n", "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0676\n", - "Function value obtained: -125.7559\n", - "Current minimum: -127.2857\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:32,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4471\n", + "Function value obtained: -48.0579\n", + "Current minimum: -49.6017\n", + "Iteration No: 54 started. Searching for the next optimal point.\n", "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0255\n", - "Function value obtained: -124.4625\n", - "Current minimum: -127.2857\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:40,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5124\n", + "Function value obtained: -46.6369\n", + "Current minimum: -49.6017\n", + "Iteration No: 55 started. Searching for the next optimal point.\n", "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7814\n", - "Function value obtained: -125.2109\n", - "Current minimum: -127.2857\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:48,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5033\n", + "Function value obtained: -48.1478\n", + "Current minimum: -49.6017\n", + "Iteration No: 56 started. Searching for the next optimal point.\n", "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9452\n", - "Function value obtained: -123.2743\n", - "Current minimum: -127.2857\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:18:56,074\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5597\n", + "Function value obtained: -48.1605\n", + "Current minimum: -49.6017\n", + "Iteration No: 57 started. Searching for the next optimal point.\n", "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4101\n", - "Function value obtained: -120.6169\n", - "Current minimum: -127.2857\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:19:04,524\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4899\n", + "Function value obtained: -45.0397\n", + "Current minimum: -49.6017\n", + "Iteration No: 58 started. Searching for the next optimal point.\n", "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0182\n", - "Function value obtained: -121.7291\n", - "Current minimum: -127.2857\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:19:12,556\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4978\n", + "Function value obtained: -46.5459\n", + "Current minimum: -49.6017\n", + "Iteration No: 59 started. Searching for the next optimal point.\n", "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1671\n", - "Function value obtained: -125.1627\n", - "Current minimum: -127.2857\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:19:20,682\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4811\n", + "Function value obtained: -43.7516\n", + "Current minimum: -49.6017\n", + "Iteration No: 60 started. Searching for the next optimal point.\n", "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2038\n", - "Function value obtained: -121.9801\n", - "Current minimum: -127.2857\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:19:28,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5171\n", + "Function value obtained: -47.2481\n", + "Current minimum: -49.6017\n", + "Iteration No: 61 started. Searching for the next optimal point.\n", "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9633\n", - "Function value obtained: -121.9620\n", - "Current minimum: -127.2857\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:19:37,853\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4386\n", + "Function value obtained: -46.4790\n", + "Current minimum: -49.6017\n", + "Iteration No: 62 started. Searching for the next optimal point.\n", "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1470\n", - "Function value obtained: -125.8936\n", - "Current minimum: -127.2857\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:19:46,012\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4536\n", + "Function value obtained: -47.3387\n", + "Current minimum: -49.6017\n", + "Iteration No: 63 started. Searching for the next optimal point.\n", "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9083\n", - "Function value obtained: -125.7380\n", - "Current minimum: -127.2857\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:19:53,947\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6102\n", + "Function value obtained: -47.5327\n", + "Current minimum: -49.6017\n", + "Iteration No: 64 started. Searching for the next optimal point.\n", "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8940\n", - "Function value obtained: -124.1102\n", - "Current minimum: -127.2857\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:01,809\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5174\n", + "Function value obtained: -45.3859\n", + "Current minimum: -49.6017\n", + "Iteration No: 65 started. Searching for the next optimal point.\n", "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0331\n", - "Function value obtained: -121.7327\n", - "Current minimum: -127.2857\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:09,912\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4711\n", + "Function value obtained: -46.8727\n", + "Current minimum: -49.6017\n", + "Iteration No: 66 started. Searching for the next optimal point.\n", "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3531\n", - "Function value obtained: -122.7979\n", - "Current minimum: -127.2857\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:18,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5031\n", + "Function value obtained: -48.0277\n", + "Current minimum: -49.6017\n", + "Iteration No: 67 started. Searching for the next optimal point.\n", "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5848\n", - "Function value obtained: -126.2115\n", - "Current minimum: -127.2857\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:26,810\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5509\n", + "Function value obtained: -48.6187\n", + "Current minimum: -49.6017\n", + "Iteration No: 68 started. Searching for the next optimal point.\n", "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2814\n", - "Function value obtained: -123.5397\n", - "Current minimum: -127.2857\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:35,177\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5195\n", + "Function value obtained: -48.3695\n", + "Current minimum: -49.6017\n", + "Iteration No: 69 started. Searching for the next optimal point.\n", "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0697\n", - "Function value obtained: -122.2537\n", - "Current minimum: -127.2857\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:43,142\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4830\n", + "Function value obtained: -44.5009\n", + "Current minimum: -49.6017\n", + "Iteration No: 70 started. Searching for the next optimal point.\n", "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0422\n", - "Function value obtained: -125.0775\n", - "Current minimum: -127.2857\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:51,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5454\n", + "Function value obtained: -45.3096\n", + "Current minimum: -49.6017\n", + "Iteration No: 71 started. Searching for the next optimal point.\n", "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0092\n", - "Function value obtained: -122.9532\n", - "Current minimum: -127.2857\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:20:59,207\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4323\n", + "Function value obtained: -47.1526\n", + "Current minimum: -49.6017\n", + "Iteration No: 72 started. Searching for the next optimal point.\n", "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0968\n", - "Function value obtained: -123.0806\n", - "Current minimum: -127.2857\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:21:07,293\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4273\n", + "Function value obtained: -47.3175\n", + "Current minimum: -49.6017\n", + "Iteration No: 73 started. Searching for the next optimal point.\n", "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0032\n", - "Function value obtained: -125.7564\n", - "Current minimum: -127.2857\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:21:16,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5579\n", + "Function value obtained: -46.5905\n", + "Current minimum: -49.6017\n", + "Iteration No: 74 started. Searching for the next optimal point.\n", "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2578\n", - "Function value obtained: -125.3020\n", - "Current minimum: -127.2857\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:21:24,627\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5067\n", + "Function value obtained: -46.8752\n", + "Current minimum: -49.6017\n", + "Iteration No: 75 started. Searching for the next optimal point.\n", "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2321\n", - "Function value obtained: -122.3374\n", - "Current minimum: -127.2857\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:21:32,799\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5313\n", + "Function value obtained: -47.8672\n", + "Current minimum: -49.6017\n", + "Iteration No: 76 started. Searching for the next optimal point.\n", "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3429\n", - "Function value obtained: -121.8593\n", - "Current minimum: -127.2857\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:21:41,179\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5224\n", + "Function value obtained: -45.6860\n", + "Current minimum: -49.6017\n", + "Iteration No: 77 started. Searching for the next optimal point.\n", "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1065\n", - "Function value obtained: -124.8048\n", - "Current minimum: -127.2857\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:21:49,280\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5298\n", + "Function value obtained: -46.8637\n", + "Current minimum: -49.6017\n", + "Iteration No: 78 started. Searching for the next optimal point.\n", "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2792\n", - "Function value obtained: -122.4037\n", - "Current minimum: -127.2857\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:21:57,608\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.7157\n", + "Function value obtained: -47.9359\n", + "Current minimum: -49.6017\n", + "Iteration No: 79 started. Searching for the next optimal point.\n", "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1012\n", - "Function value obtained: -123.3177\n", - "Current minimum: -127.2857\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:22:05,678\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4869\n", + "Function value obtained: -48.3924\n", + "Current minimum: -49.6017\n", + "Iteration No: 80 started. Searching for the next optimal point.\n", "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4301\n", - "Function value obtained: -124.2213\n", - "Current minimum: -127.2857\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:22:14,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4701\n", + "Function value obtained: -45.2819\n", + "Current minimum: -49.6017\n", + "Iteration No: 81 started. Searching for the next optimal point.\n", "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1197\n", - "Function value obtained: -125.2965\n", - "Current minimum: -127.2857\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:22:23,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4596\n", + "Function value obtained: -48.8099\n", + "Current minimum: -49.6017\n", + "Iteration No: 82 started. Searching for the next optimal point.\n", "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2129\n", - "Function value obtained: -122.8271\n", - "Current minimum: -127.2857\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:22:31,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4203\n", + "Function value obtained: -44.6818\n", + "Current minimum: -49.6017\n", + "Iteration No: 83 started. Searching for the next optimal point.\n", "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1701\n", - "Function value obtained: -123.6942\n", - "Current minimum: -127.2857\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:22:40,672\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.3309\n", + "Function value obtained: -48.0720\n", + "Current minimum: -49.6017\n", + "Iteration No: 84 started. Searching for the next optimal point.\n", "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4587\n", - "Function value obtained: -123.5216\n", - "Current minimum: -127.2857\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:22:49,131\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5261\n", + "Function value obtained: -47.3489\n", + "Current minimum: -49.6017\n", + "Iteration No: 85 started. Searching for the next optimal point.\n", "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3058\n", - "Function value obtained: -127.2533\n", - "Current minimum: -127.2857\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:22:57,413\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4705\n", + "Function value obtained: -48.0898\n", + "Current minimum: -49.6017\n", + "Iteration No: 86 started. Searching for the next optimal point.\n", "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2952\n", - "Function value obtained: -124.6334\n", - "Current minimum: -127.2857\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:23:05,742\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4849\n", + "Function value obtained: -45.8602\n", + "Current minimum: -49.6017\n", + "Iteration No: 87 started. Searching for the next optimal point.\n", "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1572\n", - "Function value obtained: -123.4150\n", - "Current minimum: -127.2857\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:23:13,874\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6133\n", + "Function value obtained: -47.4123\n", + "Current minimum: -49.6017\n", + "Iteration No: 88 started. Searching for the next optimal point.\n", "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1534\n", - "Function value obtained: -126.7773\n", - "Current minimum: -127.2857\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:23:22,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5090\n", + "Function value obtained: -46.1113\n", + "Current minimum: -49.6017\n", + "Iteration No: 89 started. Searching for the next optimal point.\n", "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1753\n", - "Function value obtained: -120.3155\n", - "Current minimum: -127.2857\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:23:31,232\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5676\n", + "Function value obtained: -48.4236\n", + "Current minimum: -49.6017\n", + "Iteration No: 90 started. Searching for the next optimal point.\n", "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1793\n", - "Function value obtained: -122.5142\n", - "Current minimum: -127.2857\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:23:39,415\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4747\n", + "Function value obtained: -47.6057\n", + "Current minimum: -49.6017\n", + "Iteration No: 91 started. Searching for the next optimal point.\n", "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3417\n", - "Function value obtained: -120.7373\n", - "Current minimum: -127.2857\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:23:47,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4737\n", + "Function value obtained: -45.1571\n", + "Current minimum: -49.6017\n", + "Iteration No: 92 started. Searching for the next optimal point.\n", "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6652\n", - "Function value obtained: -124.0888\n", - "Current minimum: -127.2857\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:23:56,399\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4616\n", + "Function value obtained: -48.5987\n", + "Current minimum: -49.6017\n", + "Iteration No: 93 started. Searching for the next optimal point.\n", "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1963\n", - "Function value obtained: -121.1684\n", - "Current minimum: -127.2857\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:24:05,685\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4667\n", + "Function value obtained: -47.1953\n", + "Current minimum: -49.6017\n", + "Iteration No: 94 started. Searching for the next optimal point.\n", "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2017\n", - "Function value obtained: -122.1243\n", - "Current minimum: -127.2857\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:24:14,839\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4862\n", + "Function value obtained: -46.9125\n", + "Current minimum: -49.6017\n", + "Iteration No: 95 started. Searching for the next optimal point.\n", "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3457\n", - "Function value obtained: -118.2673\n", - "Current minimum: -127.2857\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:24:23,169\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4970\n", + "Function value obtained: -47.4312\n", + "Current minimum: -49.6017\n", + "Iteration No: 96 started. Searching for the next optimal point.\n", "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3580\n", - "Function value obtained: -125.4271\n", - "Current minimum: -127.2857\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:24:32,535\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4997\n", + "Function value obtained: -47.1148\n", + "Current minimum: -49.6017\n", + "Iteration No: 97 started. Searching for the next optimal point.\n", "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8470\n", - "Function value obtained: -123.5324\n", - "Current minimum: -127.2857\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:24:42,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6946\n", + "Function value obtained: -46.7082\n", + "Current minimum: -49.6017\n", + "Iteration No: 98 started. Searching for the next optimal point.\n", "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5936\n", - "Function value obtained: -118.8865\n", - "Current minimum: -127.2857\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:24:50,976\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5323\n", + "Function value obtained: -47.0256\n", + "Current minimum: -49.6017\n", + "Iteration No: 99 started. Searching for the next optimal point.\n", "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6656\n", - "Function value obtained: -125.6696\n", - "Current minimum: -127.2857\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:24:59,748\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4895\n", + "Function value obtained: -45.8617\n", + "Current minimum: -49.6017\n", + "Iteration No: 100 started. Searching for the next optimal point.\n", "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8550\n", - "Function value obtained: -125.7615\n", - "Current minimum: -127.2857\n", - "Iteration No: 101 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:25:08,527\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4927\n", + "Function value obtained: -46.0801\n", + "Current minimum: -49.6017\n", + "Iteration No: 101 started. Searching for the next optimal point.\n", "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6321\n", - "Function value obtained: -122.5695\n", - "Current minimum: -127.2857\n", - "Iteration No: 102 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:25:17,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5328\n", + "Function value obtained: -47.8178\n", + "Current minimum: -49.6017\n", + "Iteration No: 102 started. Searching for the next optimal point.\n", "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8353\n", - "Function value obtained: -123.4955\n", - "Current minimum: -127.2857\n", - "Iteration No: 103 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:25:25,992\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5578\n", + "Function value obtained: -45.8014\n", + "Current minimum: -49.6017\n", + "Iteration No: 103 started. Searching for the next optimal point.\n", "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7245\n", - "Function value obtained: -120.5857\n", - "Current minimum: -127.2857\n", - "Iteration No: 104 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:25:34,738\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5063\n", + "Function value obtained: -48.7166\n", + "Current minimum: -49.6017\n", + "Iteration No: 104 started. Searching for the next optimal point.\n", "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3886\n", - "Function value obtained: -123.0827\n", - "Current minimum: -127.2857\n", - "Iteration No: 105 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:25:44,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4746\n", + "Function value obtained: -46.6069\n", + "Current minimum: -49.6017\n", + "Iteration No: 105 started. Searching for the next optimal point.\n", "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5134\n", - "Function value obtained: -121.5040\n", - "Current minimum: -127.2857\n", - "Iteration No: 106 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:25:52,638\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5559\n", + "Function value obtained: -47.1771\n", + "Current minimum: -49.6017\n", + "Iteration No: 106 started. Searching for the next optimal point.\n", "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0207\n", - "Function value obtained: -122.5403\n", - "Current minimum: -127.2857\n", - "Iteration No: 107 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:26:01,677\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4994\n", + "Function value obtained: -47.1168\n", + "Current minimum: -49.6017\n", + "Iteration No: 107 started. Searching for the next optimal point.\n", "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8901\n", - "Function value obtained: -126.4895\n", - "Current minimum: -127.2857\n", - "Iteration No: 108 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:26:10,620\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5939\n", + "Function value obtained: -46.4010\n", + "Current minimum: -49.6017\n", + "Iteration No: 108 started. Searching for the next optimal point.\n", "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8920\n", - "Function value obtained: -122.3992\n", - "Current minimum: -127.2857\n", - "Iteration No: 109 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:26:19,434\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5162\n", + "Function value obtained: -48.2321\n", + "Current minimum: -49.6017\n", + "Iteration No: 109 started. Searching for the next optimal point.\n", "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6350\n", - "Function value obtained: -124.4872\n", - "Current minimum: -127.2857\n", - "Iteration No: 110 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:26:29,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4968\n", + "Function value obtained: -45.6238\n", + "Current minimum: -49.6017\n", + "Iteration No: 110 started. Searching for the next optimal point.\n", "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4430\n", - "Function value obtained: -120.1646\n", - "Current minimum: -127.2857\n", - "Iteration No: 111 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:26:38,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5985\n", + "Function value obtained: -47.4828\n", + "Current minimum: -49.6017\n", + "Iteration No: 111 started. Searching for the next optimal point.\n", "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9071\n", - "Function value obtained: -125.2676\n", - "Current minimum: -127.2857\n", - "Iteration No: 112 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:26:47,487\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5077\n", + "Function value obtained: -46.7207\n", + "Current minimum: -49.6017\n", + "Iteration No: 112 started. Searching for the next optimal point.\n", "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4783\n", - "Function value obtained: -124.0320\n", - "Current minimum: -127.2857\n", - "Iteration No: 113 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:26:56,961\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5293\n", + "Function value obtained: -46.3870\n", + "Current minimum: -49.6017\n", + "Iteration No: 113 started. Searching for the next optimal point.\n", "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1311\n", - "Function value obtained: -126.5364\n", - "Current minimum: -127.2857\n", - "Iteration No: 114 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:27:06,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4890\n", + "Function value obtained: -47.6239\n", + "Current minimum: -49.6017\n", + "Iteration No: 114 started. Searching for the next optimal point.\n", "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4202\n", - "Function value obtained: -124.6390\n", - "Current minimum: -127.2857\n", - "Iteration No: 115 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:27:15,487\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5437\n", + "Function value obtained: -46.1445\n", + "Current minimum: -49.6017\n", + "Iteration No: 115 started. Searching for the next optimal point.\n", "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5468\n", - "Function value obtained: -126.4374\n", - "Current minimum: -127.2857\n", - "Iteration No: 116 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:27:25,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4350\n", + "Function value obtained: -47.7099\n", + "Current minimum: -49.6017\n", + "Iteration No: 116 started. Searching for the next optimal point.\n", "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4789\n", - "Function value obtained: -120.6114\n", - "Current minimum: -127.2857\n", - "Iteration No: 117 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:27:34,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4450\n", + "Function value obtained: -47.2153\n", + "Current minimum: -49.6017\n", + "Iteration No: 117 started. Searching for the next optimal point.\n", "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6505\n", - "Function value obtained: -120.5101\n", - "Current minimum: -127.2857\n", - "Iteration No: 118 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:27:44,185\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5301\n", + "Function value obtained: -46.0510\n", + "Current minimum: -49.6017\n", + "Iteration No: 118 started. Searching for the next optimal point.\n", "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5307\n", - "Function value obtained: -120.8552\n", - "Current minimum: -127.2857\n", - "Iteration No: 119 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:27:53,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6147\n", + "Function value obtained: -46.7348\n", + "Current minimum: -49.6017\n", + "Iteration No: 119 started. Searching for the next optimal point.\n", "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7483\n", - "Function value obtained: -125.5909\n", - "Current minimum: -127.2857\n", - "Iteration No: 120 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:28:03,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4782\n", + "Function value obtained: -48.0223\n", + "Current minimum: -49.6017\n", + "Iteration No: 120 started. Searching for the next optimal point.\n", "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7541\n", - "Function value obtained: -124.2085\n", - "Current minimum: -127.2857\n", - "Iteration No: 121 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:28:13,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5107\n", + "Function value obtained: -45.9638\n", + "Current minimum: -49.6017\n", + "Iteration No: 121 started. Searching for the next optimal point.\n", "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4951\n", - "Function value obtained: -125.5847\n", - "Current minimum: -127.2857\n", - "Iteration No: 122 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:28:22,785\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5445\n", + "Function value obtained: -47.4704\n", + "Current minimum: -49.6017\n", + "Iteration No: 122 started. Searching for the next optimal point.\n", "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6318\n", - "Function value obtained: -121.2312\n", - "Current minimum: -127.2857\n", - "Iteration No: 123 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:28:33,372\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4802\n", + "Function value obtained: -46.3621\n", + "Current minimum: -49.6017\n", + "Iteration No: 123 started. Searching for the next optimal point.\n", "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7448\n", - "Function value obtained: -126.6954\n", - "Current minimum: -127.2857\n", - "Iteration No: 124 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:28:43,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4472\n", + "Function value obtained: -48.2987\n", + "Current minimum: -49.6017\n", + "Iteration No: 124 started. Searching for the next optimal point.\n", "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5822\n", - "Function value obtained: -126.0589\n", - "Current minimum: -127.2857\n", - "Iteration No: 125 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:28:52,737\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4813\n", + "Function value obtained: -45.8185\n", + "Current minimum: -49.6017\n", + "Iteration No: 125 started. Searching for the next optimal point.\n", "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0652\n", - "Function value obtained: -124.4110\n", - "Current minimum: -127.2857\n", - "Iteration No: 126 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:29:01,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5345\n", + "Function value obtained: -46.9240\n", + "Current minimum: -49.6017\n", + "Iteration No: 126 started. Searching for the next optimal point.\n", "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6240\n", - "Function value obtained: -121.1013\n", - "Current minimum: -127.2857\n", - "Iteration No: 127 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:29:11,431\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6460\n", + "Function value obtained: -45.6050\n", + "Current minimum: -49.6017\n", + "Iteration No: 127 started. Searching for the next optimal point.\n", "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7675\n", - "Function value obtained: -123.3102\n", - "Current minimum: -127.2857\n", - "Iteration No: 128 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:29:21,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5271\n", + "Function value obtained: -45.5833\n", + "Current minimum: -49.6017\n", + "Iteration No: 128 started. Searching for the next optimal point.\n", "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6895\n", - "Function value obtained: -127.3494\n", - "Current minimum: -127.3494\n", - "Iteration No: 129 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:29:30,891\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5524\n", + "Function value obtained: -45.4827\n", + "Current minimum: -49.6017\n", + "Iteration No: 129 started. Searching for the next optimal point.\n", "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9907\n", - "Function value obtained: -125.9170\n", - "Current minimum: -127.3494\n", - "Iteration No: 130 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:29:40,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5740\n", + "Function value obtained: -48.2536\n", + "Current minimum: -49.6017\n", + "Iteration No: 130 started. Searching for the next optimal point.\n", "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7159\n", - "Function value obtained: -124.2533\n", - "Current minimum: -127.3494\n", - "Iteration No: 131 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:29:50,580\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4685\n", + "Function value obtained: -46.3540\n", + "Current minimum: -49.6017\n", + "Iteration No: 131 started. Searching for the next optimal point.\n", "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7052\n", - "Function value obtained: -122.8221\n", - "Current minimum: -127.3494\n", - "Iteration No: 132 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:30:00,301\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5441\n", + "Function value obtained: -47.9790\n", + "Current minimum: -49.6017\n", + "Iteration No: 132 started. Searching for the next optimal point.\n", "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0584\n", - "Function value obtained: -124.4080\n", - "Current minimum: -127.3494\n", - "Iteration No: 133 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:30:09,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5442\n", + "Function value obtained: -46.5460\n", + "Current minimum: -49.6017\n", + "Iteration No: 133 started. Searching for the next optimal point.\n", "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6471\n", - "Function value obtained: -125.7858\n", - "Current minimum: -127.3494\n", - "Iteration No: 134 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:30:19,018\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4367\n", + "Function value obtained: -49.8897\n", + "Current minimum: -49.8897\n", + "Iteration No: 134 started. Searching for the next optimal point.\n", "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7007\n", - "Function value obtained: -125.9075\n", - "Current minimum: -127.3494\n", - "Iteration No: 135 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:30:28,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5285\n", + "Function value obtained: -48.0609\n", + "Current minimum: -49.8897\n", + "Iteration No: 135 started. Searching for the next optimal point.\n", "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7827\n", - "Function value obtained: -124.2837\n", - "Current minimum: -127.3494\n", - "Iteration No: 136 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:30:38,516\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5231\n", + "Function value obtained: -45.9417\n", + "Current minimum: -49.8897\n", + "Iteration No: 136 started. Searching for the next optimal point.\n", "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5199\n", - "Function value obtained: -121.9445\n", - "Current minimum: -127.3494\n", - "Iteration No: 137 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:30:48,054\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5069\n", + "Function value obtained: -48.1052\n", + "Current minimum: -49.8897\n", + "Iteration No: 137 started. Searching for the next optimal point.\n", "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7894\n", - "Function value obtained: -119.8468\n", - "Current minimum: -127.3494\n", - "Iteration No: 138 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:30:57,835\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4651\n", + "Function value obtained: -47.1823\n", + "Current minimum: -49.8897\n", + "Iteration No: 138 started. Searching for the next optimal point.\n", "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7647\n", - "Function value obtained: -123.7169\n", - "Current minimum: -127.3494\n", - "Iteration No: 139 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:31:07,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5213\n", + "Function value obtained: -46.5411\n", + "Current minimum: -49.8897\n", + "Iteration No: 139 started. Searching for the next optimal point.\n", "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8808\n", - "Function value obtained: -124.3117\n", - "Current minimum: -127.3494\n", - "Iteration No: 140 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:31:17,506\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4664\n", + "Function value obtained: -44.4394\n", + "Current minimum: -49.8897\n", + "Iteration No: 140 started. Searching for the next optimal point.\n", "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8833\n", - "Function value obtained: -125.4229\n", - "Current minimum: -127.3494\n", - "Iteration No: 141 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:31:27,381\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.7325\n", + "Function value obtained: -48.4451\n", + "Current minimum: -49.8897\n", + "Iteration No: 141 started. Searching for the next optimal point.\n", "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9655\n", - "Function value obtained: -124.4755\n", - "Current minimum: -127.3494\n", - "Iteration No: 142 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:31:37,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5663\n", + "Function value obtained: -46.7940\n", + "Current minimum: -49.8897\n", + "Iteration No: 142 started. Searching for the next optimal point.\n", "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9059\n", - "Function value obtained: -120.1788\n", - "Current minimum: -127.3494\n", - "Iteration No: 143 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:31:47,249\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5296\n", + "Function value obtained: -47.4213\n", + "Current minimum: -49.8897\n", + "Iteration No: 143 started. Searching for the next optimal point.\n", "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7793\n", - "Function value obtained: -125.4044\n", - "Current minimum: -127.3494\n", - "Iteration No: 144 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:31:57,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5615\n", + "Function value obtained: -44.7370\n", + "Current minimum: -49.8897\n", + "Iteration No: 144 started. Searching for the next optimal point.\n", "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8150\n", - "Function value obtained: -122.4493\n", - "Current minimum: -127.3494\n", - "Iteration No: 145 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:32:06,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4711\n", + "Function value obtained: -46.5875\n", + "Current minimum: -49.8897\n", + "Iteration No: 145 started. Searching for the next optimal point.\n", "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0360\n", - "Function value obtained: -122.3720\n", - "Current minimum: -127.3494\n", - "Iteration No: 146 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:32:16,783\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4040\n", + "Function value obtained: -46.5380\n", + "Current minimum: -49.8897\n", + "Iteration No: 146 started. Searching for the next optimal point.\n", "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7202\n", - "Function value obtained: -123.4715\n", - "Current minimum: -127.3494\n", - "Iteration No: 147 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:32:26,637\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4615\n", + "Function value obtained: -47.0075\n", + "Current minimum: -49.8897\n", + "Iteration No: 147 started. Searching for the next optimal point.\n", "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9255\n", - "Function value obtained: -122.1531\n", - "Current minimum: -127.3494\n", - "Iteration No: 148 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:32:36,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5457\n", + "Function value obtained: -47.6239\n", + "Current minimum: -49.8897\n", + "Iteration No: 148 started. Searching for the next optimal point.\n", "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8876\n", - "Function value obtained: -122.1446\n", - "Current minimum: -127.3494\n", - "Iteration No: 149 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:32:46,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4523\n", + "Function value obtained: -45.9532\n", + "Current minimum: -49.8897\n", + "Iteration No: 149 started. Searching for the next optimal point.\n", "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0552\n", - "Function value obtained: -122.2754\n", - "Current minimum: -127.3494\n", - "Iteration No: 150 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:32:56,534\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5191\n", + "Function value obtained: -47.6434\n", + "Current minimum: -49.8897\n", + "Iteration No: 150 started. Searching for the next optimal point.\n", "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0659\n", - "Function value obtained: -122.3044\n", - "Current minimum: -127.3494\n", - "Iteration No: 151 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:33:07,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4987\n", + "Function value obtained: -45.9662\n", + "Current minimum: -49.8897\n", + "Iteration No: 151 started. Searching for the next optimal point.\n", "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1496\n", - "Function value obtained: -123.7074\n", - "Current minimum: -127.3494\n", - "Iteration No: 152 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:33:17,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5810\n", + "Function value obtained: -46.5016\n", + "Current minimum: -49.8897\n", + "Iteration No: 152 started. Searching for the next optimal point.\n", "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0512\n", - "Function value obtained: -125.5542\n", - "Current minimum: -127.3494\n", - "Iteration No: 153 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:33:27,776\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4548\n", + "Function value obtained: -46.2267\n", + "Current minimum: -49.8897\n", + "Iteration No: 153 started. Searching for the next optimal point.\n", "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0940\n", - "Function value obtained: -126.0177\n", - "Current minimum: -127.3494\n", - "Iteration No: 154 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:33:37,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4238\n", + "Function value obtained: -47.4453\n", + "Current minimum: -49.8897\n", + "Iteration No: 154 started. Searching for the next optimal point.\n", "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1943\n", - "Function value obtained: -124.2800\n", - "Current minimum: -127.3494\n", - "Iteration No: 155 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:33:48,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5048\n", + "Function value obtained: -47.2020\n", + "Current minimum: -49.8897\n", + "Iteration No: 155 started. Searching for the next optimal point.\n", "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5941\n", - "Function value obtained: -122.3352\n", - "Current minimum: -127.3494\n", - "Iteration No: 156 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:33:57,702\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4631\n", + "Function value obtained: -47.1068\n", + "Current minimum: -49.8897\n", + "Iteration No: 156 started. Searching for the next optimal point.\n", "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5312\n", - "Function value obtained: -122.2072\n", - "Current minimum: -127.3494\n", - "Iteration No: 157 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:34:07,268\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.3817\n", + "Function value obtained: -48.2429\n", + "Current minimum: -49.8897\n", + "Iteration No: 157 started. Searching for the next optimal point.\n", "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2864\n", - "Function value obtained: -122.5458\n", - "Current minimum: -127.3494\n", - "Iteration No: 158 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:34:17,483\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4986\n", + "Function value obtained: -44.8097\n", + "Current minimum: -49.8897\n", + "Iteration No: 158 started. Searching for the next optimal point.\n", "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1300\n", - "Function value obtained: -122.5309\n", - "Current minimum: -127.3494\n", - "Iteration No: 159 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:34:27,649\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6743\n", - "Function value obtained: -122.6837\n", - "Current minimum: -127.3494\n", - "Iteration No: 160 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:34:37,296\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4233\n", + "Function value obtained: -46.8809\n", + "Current minimum: -49.8897\n", + "Iteration No: 159 started. Searching for the next optimal point.\n", + "Iteration No: 159 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5612\n", + "Function value obtained: -45.5597\n", + "Current minimum: -49.8897\n", + "Iteration No: 160 started. Searching for the next optimal point.\n", "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2804\n", - "Function value obtained: -123.9210\n", - "Current minimum: -127.3494\n", - "Iteration No: 161 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:34:47,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6052\n", + "Function value obtained: -46.4952\n", + "Current minimum: -49.8897\n", + "Iteration No: 161 started. Searching for the next optimal point.\n", "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1555\n", - "Function value obtained: -122.0798\n", - "Current minimum: -127.3494\n", - "Iteration No: 162 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:34:57,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5001\n", + "Function value obtained: -46.6400\n", + "Current minimum: -49.8897\n", + "Iteration No: 162 started. Searching for the next optimal point.\n", "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2372\n", - "Function value obtained: -122.3340\n", - "Current minimum: -127.3494\n", - "Iteration No: 163 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:35:08,048\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.6195\n", + "Function value obtained: -46.5302\n", + "Current minimum: -49.8897\n", + "Iteration No: 163 started. Searching for the next optimal point.\n", "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1899\n", - "Function value obtained: -121.3459\n", - "Current minimum: -127.3494\n", - "Iteration No: 164 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:35:18,201\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5431\n", + "Function value obtained: -47.6782\n", + "Current minimum: -49.8897\n", + "Iteration No: 164 started. Searching for the next optimal point.\n", "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3174\n", - "Function value obtained: -126.2553\n", - "Current minimum: -127.3494\n", - "Iteration No: 165 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:35:29,554\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4370\n", + "Function value obtained: -47.6993\n", + "Current minimum: -49.8897\n", + "Iteration No: 165 started. Searching for the next optimal point.\n", "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3120\n", - "Function value obtained: -121.0753\n", - "Current minimum: -127.3494\n", - "Iteration No: 166 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:35:39,856\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5255\n", + "Function value obtained: -10.5757\n", + "Current minimum: -49.8897\n", + "Iteration No: 166 started. Searching for the next optimal point.\n", "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4820\n", - "Function value obtained: -120.2387\n", - "Current minimum: -127.3494\n", - "Iteration No: 167 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:35:50,358\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4695\n", + "Function value obtained: -48.1290\n", + "Current minimum: -49.8897\n", + "Iteration No: 167 started. Searching for the next optimal point.\n", "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4620\n", - "Function value obtained: -126.7493\n", - "Current minimum: -127.3494\n", - "Iteration No: 168 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:36:00,723\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5103\n", + "Function value obtained: -46.8644\n", + "Current minimum: -49.8897\n", + "Iteration No: 168 started. Searching for the next optimal point.\n", "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8545\n", - "Function value obtained: -125.1645\n", - "Current minimum: -127.3494\n", - "Iteration No: 169 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:36:10,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4537\n", + "Function value obtained: -46.8415\n", + "Current minimum: -49.8897\n", + "Iteration No: 169 started. Searching for the next optimal point.\n", "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4415\n", - "Function value obtained: -122.6830\n", - "Current minimum: -127.3494\n", - "Iteration No: 170 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:36:21,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4604\n", + "Function value obtained: -47.4611\n", + "Current minimum: -49.8897\n", + "Iteration No: 170 started. Searching for the next optimal point.\n", "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4778\n", - "Function value obtained: -121.4214\n", - "Current minimum: -127.3494\n", - "Iteration No: 171 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:36:31,643\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5201\n", + "Function value obtained: -45.5961\n", + "Current minimum: -49.8897\n", + "Iteration No: 171 started. Searching for the next optimal point.\n", "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4139\n", - "Function value obtained: -121.5312\n", - "Current minimum: -127.3494\n", - "Iteration No: 172 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:36:42,048\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5280\n", + "Function value obtained: -44.9130\n", + "Current minimum: -49.8897\n", + "Iteration No: 172 started. Searching for the next optimal point.\n", "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0658\n", - "Function value obtained: -122.2049\n", - "Current minimum: -127.3494\n", - "Iteration No: 173 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:36:52,123\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4738\n", + "Function value obtained: -47.5096\n", + "Current minimum: -49.8897\n", + "Iteration No: 173 started. Searching for the next optimal point.\n", "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5942\n", - "Function value obtained: -123.3033\n", - "Current minimum: -127.3494\n", - "Iteration No: 174 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:37:02,692\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5386\n", + "Function value obtained: -46.5298\n", + "Current minimum: -49.8897\n", + "Iteration No: 174 started. Searching for the next optimal point.\n", "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4186\n", - "Function value obtained: -124.3143\n", - "Current minimum: -127.3494\n", - "Iteration No: 175 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:37:14,157\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5460\n", + "Function value obtained: -48.4569\n", + "Current minimum: -49.8897\n", + "Iteration No: 175 started. Searching for the next optimal point.\n", "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6351\n", - "Function value obtained: -119.8759\n", - "Current minimum: -127.3494\n", - "Iteration No: 176 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:37:24,805\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.4322\n", + "Function value obtained: -46.6290\n", + "Current minimum: -49.8897\n", + "Iteration No: 176 started. Searching for the next optimal point.\n", "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4779\n", - "Function value obtained: -123.4730\n", - "Current minimum: -127.3494\n", - "Iteration No: 177 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:37:35,294\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5870\n", + "Function value obtained: -46.9834\n", + "Current minimum: -49.8897\n", + "Iteration No: 177 started. Searching for the next optimal point.\n", "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8561\n", - "Function value obtained: -120.8972\n", - "Current minimum: -127.3494\n", - "Iteration No: 178 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:37:46,101\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5292\n", + "Function value obtained: -45.0813\n", + "Current minimum: -49.8897\n", + "Iteration No: 178 started. Searching for the next optimal point.\n", "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5419\n", - "Function value obtained: -122.7453\n", - "Current minimum: -127.3494\n", - "Iteration No: 179 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:37:56,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Time taken: 1.5267\n", + "Function value obtained: -49.7659\n", + "Current minimum: -49.8897\n", + "Iteration No: 179 started. Searching for the next optimal point.\n", "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3095\n", - "Function value obtained: -123.9806\n", - "Current minimum: -127.3494\n", - "Iteration No: 180 started. Searching for the next optimal point.\n" + "Time taken: 1.5247\n", + "Function value obtained: -47.7063\n", + "Current minimum: -49.8897\n", + "Iteration No: 180 started. Searching for the next optimal point.\n", + "Iteration No: 180 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4800\n", + "Function value obtained: -46.8807\n", + "Current minimum: -49.8897\n", + "Iteration No: 181 started. Searching for the next optimal point.\n", + "Iteration No: 181 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5016\n", + "Function value obtained: -46.6104\n", + "Current minimum: -49.8897\n", + "Iteration No: 182 started. Searching for the next optimal point.\n", + "Iteration No: 182 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3970\n", + "Function value obtained: -45.0529\n", + "Current minimum: -49.8897\n", + "Iteration No: 183 started. Searching for the next optimal point.\n", + "Iteration No: 183 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5808\n", + "Function value obtained: -47.7305\n", + "Current minimum: -49.8897\n", + "Iteration No: 184 started. Searching for the next optimal point.\n", + "Iteration No: 184 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5231\n", + "Function value obtained: -46.8753\n", + "Current minimum: -49.8897\n", + "Iteration No: 185 started. Searching for the next optimal point.\n", + "Iteration No: 185 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4697\n", + "Function value obtained: -46.4229\n", + "Current minimum: -49.8897\n", + "Iteration No: 186 started. Searching for the next optimal point.\n", + "Iteration No: 186 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4536\n", + "Function value obtained: -46.3220\n", + "Current minimum: -49.8897\n", + "Iteration No: 187 started. Searching for the next optimal point.\n", + "Iteration No: 187 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4468\n", + "Function value obtained: -45.0930\n", + "Current minimum: -49.8897\n", + "Iteration No: 188 started. Searching for the next optimal point.\n", + "Iteration No: 188 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4897\n", + "Function value obtained: -46.2899\n", + "Current minimum: -49.8897\n", + "Iteration No: 189 started. Searching for the next optimal point.\n", + "Iteration No: 189 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5649\n", + "Function value obtained: -45.7537\n", + "Current minimum: -49.8897\n", + "Iteration No: 190 started. Searching for the next optimal point.\n", + "Iteration No: 190 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5258\n", + "Function value obtained: -47.8918\n", + "Current minimum: -49.8897\n", + "Iteration No: 191 started. Searching for the next optimal point.\n", + "Iteration No: 191 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4762\n", + "Function value obtained: -44.7468\n", + "Current minimum: -49.8897\n", + "Iteration No: 192 started. Searching for the next optimal point.\n", + "Iteration No: 192 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4744\n", + "Function value obtained: -45.6541\n", + "Current minimum: -49.8897\n", + "Iteration No: 193 started. Searching for the next optimal point.\n", + "Iteration No: 193 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4850\n", + "Function value obtained: -47.9981\n", + "Current minimum: -49.8897\n", + "Iteration No: 194 started. Searching for the next optimal point.\n", + "Iteration No: 194 ended. Search finished for the next optimal point.\n", + "Time taken: 1.6339\n", + "Function value obtained: -48.7292\n", + "Current minimum: -49.8897\n", + "Iteration No: 195 started. Searching for the next optimal point.\n", + "Iteration No: 195 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4541\n", + "Function value obtained: -45.9848\n", + "Current minimum: -49.8897\n", + "Iteration No: 196 started. Searching for the next optimal point.\n", + "Iteration No: 196 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4691\n", + "Function value obtained: -47.4092\n", + "Current minimum: -49.8897\n", + "Iteration No: 197 started. Searching for the next optimal point.\n", + "Iteration No: 197 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4781\n", + "Function value obtained: -47.0885\n", + "Current minimum: -49.8897\n", + "Iteration No: 198 started. Searching for the next optimal point.\n", + "Iteration No: 198 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4757\n", + "Function value obtained: -46.2062\n", + "Current minimum: -49.8897\n", + "Iteration No: 199 started. Searching for the next optimal point.\n", + "Iteration No: 199 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5059\n", + "Function value obtained: -47.5081\n", + "Current minimum: -49.8897\n", + "Iteration No: 200 started. Searching for the next optimal point.\n", + "Iteration No: 200 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5575\n", + "Function value obtained: -45.9276\n", + "Current minimum: -49.8897\n", + "Iteration No: 201 started. Searching for the next optimal point.\n", + "Iteration No: 201 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5190\n", + "Function value obtained: -46.9264\n", + "Current minimum: -49.8897\n", + "Iteration No: 202 started. Searching for the next optimal point.\n", + "Iteration No: 202 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4911\n", + "Function value obtained: -46.2056\n", + "Current minimum: -49.8897\n", + "Iteration No: 203 started. Searching for the next optimal point.\n", + "Iteration No: 203 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4858\n", + "Function value obtained: -47.2440\n", + "Current minimum: -49.8897\n", + "Iteration No: 204 started. Searching for the next optimal point.\n", + "Iteration No: 204 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4779\n", + "Function value obtained: -46.6488\n", + "Current minimum: -49.8897\n", + "Iteration No: 205 started. Searching for the next optimal point.\n", + "Iteration No: 205 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5805\n", + "Function value obtained: -46.4220\n", + "Current minimum: -49.8897\n", + "Iteration No: 206 started. Searching for the next optimal point.\n", + "Iteration No: 206 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4339\n", + "Function value obtained: -46.7641\n", + "Current minimum: -49.8897\n", + "Iteration No: 207 started. Searching for the next optimal point.\n", + "Iteration No: 207 ended. Search finished for the next optimal point.\n", + "Time taken: 1.3939\n", + "Function value obtained: -46.9997\n", + "Current minimum: -49.8897\n", + "Iteration No: 208 started. Searching for the next optimal point.\n", + "Iteration No: 208 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5466\n", + "Function value obtained: -48.8444\n", + "Current minimum: -49.8897\n", + "Iteration No: 209 started. Searching for the next optimal point.\n", + "Iteration No: 209 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4416\n", + "Function value obtained: -46.6399\n", + "Current minimum: -49.8897\n", + "Iteration No: 210 started. Searching for the next optimal point.\n", + "Iteration No: 210 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4550\n", + "Function value obtained: -45.9676\n", + "Current minimum: -49.8897\n", + "Iteration No: 211 started. Searching for the next optimal point.\n", + "Iteration No: 211 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5161\n", + "Function value obtained: -48.5639\n", + "Current minimum: -49.8897\n", + "Iteration No: 212 started. Searching for the next optimal point.\n", + "Iteration No: 212 ended. Search finished for the next optimal point.\n", + "Time taken: 1.4859\n", + "Function value obtained: -46.1388\n", + "Current minimum: -49.8897\n", + "Iteration No: 213 started. Searching for the next optimal point.\n", + "Iteration No: 213 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5181\n", + "Function value obtained: -46.3721\n", + "Current minimum: -49.8897\n", + "Iteration No: 214 started. Searching for the next optimal point.\n", + "Iteration No: 214 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5108\n", + "Function value obtained: -46.5996\n", + "Current minimum: -49.8897\n", + "Iteration No: 215 started. Searching for the next optimal point.\n", + "Iteration No: 215 ended. Search finished for the next optimal point.\n", + "Time taken: 1.5101\n", + "Function value obtained: -48.4447\n", + "Current minimum: -49.8897\n", + "Iteration No: 216 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-03 23:38:06,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5235\n", - "Function value obtained: -128.5401\n", - "Current minimum: -128.5401\n", - "Iteration No: 181 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:38:17,493\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9341\n", - "Function value obtained: -121.9214\n", - "Current minimum: -128.5401\n", - "Iteration No: 182 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:38:28,405\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7589\n", - "Function value obtained: -122.9882\n", - "Current minimum: -128.5401\n", - "Iteration No: 183 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:38:39,188\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7362\n", - "Function value obtained: -122.1737\n", - "Current minimum: -128.5401\n", - "Iteration No: 184 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:38:49,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6880\n", - "Function value obtained: -122.2317\n", - "Current minimum: -128.5401\n", - "Iteration No: 185 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:39:00,611\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9029\n", - "Function value obtained: -126.0234\n", - "Current minimum: -128.5401\n", - "Iteration No: 186 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:39:11,535\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7352\n", - "Function value obtained: -123.9945\n", - "Current minimum: -128.5401\n", - "Iteration No: 187 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:39:22,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9393\n", - "Function value obtained: -121.1404\n", - "Current minimum: -128.5401\n", - "Iteration No: 188 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:39:33,215\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2148\n", - "Function value obtained: -121.9307\n", - "Current minimum: -128.5401\n", - "Iteration No: 189 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:39:43,468\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5466\n", - "Function value obtained: -123.8632\n", - "Current minimum: -128.5401\n", - "Iteration No: 190 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:39:53,995\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8137\n", - "Function value obtained: -122.4648\n", - "Current minimum: -128.5401\n", - "Iteration No: 191 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:40:04,927\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0605\n", - "Function value obtained: -122.3731\n", - "Current minimum: -128.5401\n", - "Iteration No: 192 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:40:15,873\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9528\n", - "Function value obtained: -127.2429\n", - "Current minimum: -128.5401\n", - "Iteration No: 193 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:40:27,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1784\n", - "Function value obtained: -124.8846\n", - "Current minimum: -128.5401\n", - "Iteration No: 194 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:40:39,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5402\n", - "Function value obtained: -123.3939\n", - "Current minimum: -128.5401\n", - "Iteration No: 195 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:40:49,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2673\n", - "Function value obtained: -123.9125\n", - "Current minimum: -128.5401\n", - "Iteration No: 196 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:41:00,860\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8785\n", - "Function value obtained: -125.1409\n", - "Current minimum: -128.5401\n", - "Iteration No: 197 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:41:11,695\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1730\n", - "Function value obtained: -127.1347\n", - "Current minimum: -128.5401\n", - "Iteration No: 198 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:41:22,910\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3097\n", - "Function value obtained: -118.8484\n", - "Current minimum: -128.5401\n", - "Iteration No: 199 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:41:34,257\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8070\n", - "Function value obtained: -125.6811\n", - "Current minimum: -128.5401\n", - "Iteration No: 200 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:41:45,000\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1180\n", - "Function value obtained: -124.9164\n", - "Current minimum: -128.5401\n", - "Iteration No: 201 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:41:56,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4135\n", - "Function value obtained: -122.6802\n", - "Current minimum: -128.5401\n", - "Iteration No: 202 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:42:07,577\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2825\n", - "Function value obtained: -121.4802\n", - "Current minimum: -128.5401\n", - "Iteration No: 203 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:42:18,842\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1379\n", - "Function value obtained: -121.5595\n", - "Current minimum: -128.5401\n", - "Iteration No: 204 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:42:30,983\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2644\n", - "Function value obtained: -123.3149\n", - "Current minimum: -128.5401\n", - "Iteration No: 205 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:42:42,327\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5011\n", - "Function value obtained: -126.7555\n", - "Current minimum: -128.5401\n", - "Iteration No: 206 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:42:53,830\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2261\n", - "Function value obtained: -123.2405\n", - "Current minimum: -128.5401\n", - "Iteration No: 207 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:43:05,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4226\n", - "Function value obtained: -120.8481\n", - "Current minimum: -128.5401\n", - "Iteration No: 208 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:43:17,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5591\n", - "Function value obtained: -125.9200\n", - "Current minimum: -128.5401\n", - "Iteration No: 209 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:43:29,028\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4403\n", - "Function value obtained: -120.6302\n", - "Current minimum: -128.5401\n", - "Iteration No: 210 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:43:40,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3829\n", - "Function value obtained: -124.2500\n", - "Current minimum: -128.5401\n", - "Iteration No: 211 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:43:51,852\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3774\n", - "Function value obtained: -129.2935\n", - "Current minimum: -129.2935\n", - "Iteration No: 212 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:44:03,252\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2410\n", - "Function value obtained: -128.0971\n", - "Current minimum: -129.2935\n", - "Iteration No: 213 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:44:14,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6965\n", - "Function value obtained: -125.7516\n", - "Current minimum: -129.2935\n", - "Iteration No: 214 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:44:26,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7463\n", - "Function value obtained: -122.6122\n", - "Current minimum: -129.2935\n", - "Iteration No: 215 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:44:37,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5021\n", - "Function value obtained: -123.3440\n", - "Current minimum: -129.2935\n", - "Iteration No: 216 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:44:49,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 216 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7160\n", - "Function value obtained: -121.1527\n", - "Current minimum: -129.2935\n", - "Iteration No: 217 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:45:01,143\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 217 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8249\n", - "Function value obtained: -124.9355\n", - "Current minimum: -129.2935\n", - "Iteration No: 218 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:45:13,992\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 218 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5388\n", - "Function value obtained: -123.1285\n", - "Current minimum: -129.2935\n", - "Iteration No: 219 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:45:25,521\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 219 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5193\n", - "Function value obtained: -121.8120\n", - "Current minimum: -129.2935\n", - "Iteration No: 220 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:45:37,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 220 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1476\n", - "Function value obtained: -123.5880\n", - "Current minimum: -129.2935\n", - "Iteration No: 221 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:45:48,144\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 221 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1725\n", - "Function value obtained: -123.6150\n", - "Current minimum: -129.2935\n", - "Iteration No: 222 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:45:59,395\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 222 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6523\n", - "Function value obtained: -123.3699\n", - "Current minimum: -129.2935\n", - "Iteration No: 223 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:46:11,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 223 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5702\n", - "Function value obtained: -121.6367\n", - "Current minimum: -129.2935\n", - "Iteration No: 224 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:46:22,608\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 224 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6610\n", - "Function value obtained: -123.2568\n", - "Current minimum: -129.2935\n", - "Iteration No: 225 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:46:34,320\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 225 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0946\n", - "Function value obtained: -124.8260\n", - "Current minimum: -129.2935\n", - "Iteration No: 226 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:46:46,400\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 226 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3049\n", - "Function value obtained: -124.8341\n", - "Current minimum: -129.2935\n", - "Iteration No: 227 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:46:58,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 227 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7320\n", - "Function value obtained: -122.3812\n", - "Current minimum: -129.2935\n", - "Iteration No: 228 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:47:10,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 228 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7175\n", - "Function value obtained: -123.0293\n", - "Current minimum: -129.2935\n", - "Iteration No: 229 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:47:22,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 229 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2024\n", - "Function value obtained: -122.8992\n", - "Current minimum: -129.2935\n", - "Iteration No: 230 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:47:34,375\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 230 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2708\n", - "Function value obtained: -121.7995\n", - "Current minimum: -129.2935\n", - "Iteration No: 231 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:47:46,648\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 231 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8999\n", - "Function value obtained: -122.8777\n", - "Current minimum: -129.2935\n", - "Iteration No: 232 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:47:58,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 232 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0767\n", - "Function value obtained: -122.3955\n", - "Current minimum: -129.2935\n", - "Iteration No: 233 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:48:10,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 233 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1483\n", - "Function value obtained: -125.5816\n", - "Current minimum: -129.2935\n", - "Iteration No: 234 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:48:22,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 234 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9495\n", - "Function value obtained: -128.2199\n", - "Current minimum: -129.2935\n", - "Iteration No: 235 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:48:35,740\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 235 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9145\n", - "Function value obtained: -120.8283\n", - "Current minimum: -129.2935\n", - "Iteration No: 236 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:48:47,700\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 236 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3823\n", - "Function value obtained: -122.4194\n", - "Current minimum: -129.2935\n", - "Iteration No: 237 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:49:00,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 237 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4055\n", - "Function value obtained: -124.5596\n", - "Current minimum: -129.2935\n", - "Iteration No: 238 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:49:12,467\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 238 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2159\n", - "Function value obtained: -122.4044\n", - "Current minimum: -129.2935\n", - "Iteration No: 239 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:49:24,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 239 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1730\n", - "Function value obtained: -121.4884\n", - "Current minimum: -129.2935\n", - "Iteration No: 240 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:49:36,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 240 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3723\n", - "Function value obtained: -123.5492\n", - "Current minimum: -129.2935\n", - "Iteration No: 241 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:49:49,237\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 241 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2555\n", - "Function value obtained: -123.9846\n", - "Current minimum: -129.2935\n", - "Iteration No: 242 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:50:01,499\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 242 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2907\n", - "Function value obtained: -124.0299\n", - "Current minimum: -129.2935\n", - "Iteration No: 243 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:50:13,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 243 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1261\n", - "Function value obtained: -122.7358\n", - "Current minimum: -129.2935\n", - "Iteration No: 244 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:50:25,916\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 244 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3272\n", - "Function value obtained: -123.5404\n", - "Current minimum: -129.2935\n", - "Iteration No: 245 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:50:38,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 245 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4230\n", - "Function value obtained: -124.5492\n", - "Current minimum: -129.2935\n", - "Iteration No: 246 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:50:50,698\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 246 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7645\n", - "Function value obtained: -127.7367\n", - "Current minimum: -129.2935\n", - "Iteration No: 247 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:51:03,337\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 247 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0274\n", - "Function value obtained: -123.5547\n", - "Current minimum: -129.2935\n", - "Iteration No: 248 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:51:15,359\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 248 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0625\n", - "Function value obtained: -125.6569\n", - "Current minimum: -129.2935\n", - "Iteration No: 249 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:51:28,603\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 249 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6057\n", - "Function value obtained: -124.3901\n", - "Current minimum: -129.2935\n", - "Iteration No: 250 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:51:41,173\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 250 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6674\n", - "Function value obtained: -125.5029\n", - "Current minimum: -129.2935\n", - "Iteration No: 251 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:51:53,944\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 251 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8753\n", - "Function value obtained: -121.8113\n", - "Current minimum: -129.2935\n", - "Iteration No: 252 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:52:06,692\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 252 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4818\n", - "Function value obtained: -123.7452\n", - "Current minimum: -129.2935\n", - "Iteration No: 253 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:52:19,223\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 253 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3979\n", - "Function value obtained: -124.0198\n", - "Current minimum: -129.2935\n", - "Iteration No: 254 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:52:31,589\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 254 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3888\n", - "Function value obtained: -125.6926\n", - "Current minimum: -129.2935\n", - "Iteration No: 255 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:52:44,015\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 255 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7041\n", - "Function value obtained: -120.1428\n", - "Current minimum: -129.2935\n", - "Iteration No: 256 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:52:56,737\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 256 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7209\n", - "Function value obtained: -123.8140\n", - "Current minimum: -129.2935\n", - "Iteration No: 257 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:53:09,465\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 257 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4704\n", - "Function value obtained: -120.2622\n", - "Current minimum: -129.2935\n", - "Iteration No: 258 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:53:21,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 258 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4322\n", - "Function value obtained: -123.3920\n", - "Current minimum: -129.2935\n", - "Iteration No: 259 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:53:34,265\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 259 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5801\n", - "Function value obtained: -120.6963\n", - "Current minimum: -129.2935\n", - "Iteration No: 260 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:53:46,985\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 260 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9716\n", - "Function value obtained: -123.2907\n", - "Current minimum: -129.2935\n", - "Iteration No: 261 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:53:59,967\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 261 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1139\n", - "Function value obtained: -125.5411\n", - "Current minimum: -129.2935\n", - "Iteration No: 262 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:54:13,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 262 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1115\n", - "Function value obtained: -123.5109\n", - "Current minimum: -129.2935\n", - "Iteration No: 263 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:54:26,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 263 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8200\n", - "Function value obtained: -123.7584\n", - "Current minimum: -129.2935\n", - "Iteration No: 264 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:54:38,996\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 264 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9946\n", - "Function value obtained: -125.6160\n", - "Current minimum: -129.2935\n", - "Iteration No: 265 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:54:51,986\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 265 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2403\n", - "Function value obtained: -122.1496\n", - "Current minimum: -129.2935\n", - "Iteration No: 266 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:55:05,250\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 266 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5788\n", - "Function value obtained: -124.2446\n", - "Current minimum: -129.2935\n", - "Iteration No: 267 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:55:18,813\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 267 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1190\n", - "Function value obtained: -123.9094\n", - "Current minimum: -129.2935\n", - "Iteration No: 268 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:55:31,965\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 268 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1145\n", - "Function value obtained: -125.5709\n", - "Current minimum: -129.2935\n", - "Iteration No: 269 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:55:45,061\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 269 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1283\n", - "Function value obtained: -122.8718\n", - "Current minimum: -129.2935\n", - "Iteration No: 270 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:55:58,171\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 270 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9732\n", - "Function value obtained: -119.5956\n", - "Current minimum: -129.2935\n", - "Iteration No: 271 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:56:11,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 271 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2341\n", - "Function value obtained: -123.2431\n", - "Current minimum: -129.2935\n", - "Iteration No: 272 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:56:24,445\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 272 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9155\n", - "Function value obtained: -123.9309\n", - "Current minimum: -129.2935\n", - "Iteration No: 273 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:56:37,385\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 273 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8917\n", - "Function value obtained: -123.3262\n", - "Current minimum: -129.2935\n", - "Iteration No: 274 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:56:51,269\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 274 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1295\n", - "Function value obtained: -122.3763\n", - "Current minimum: -129.2935\n", - "Iteration No: 275 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:57:05,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 275 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3133\n", - "Function value obtained: -126.2470\n", - "Current minimum: -129.2935\n", - "Iteration No: 276 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:57:18,723\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 276 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4202\n", - "Function value obtained: -126.7206\n", - "Current minimum: -129.2935\n", - "Iteration No: 277 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:57:32,138\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 277 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0313\n", - "Function value obtained: -124.9717\n", - "Current minimum: -129.2935\n", - "Iteration No: 278 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:57:46,212\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 278 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7681\n", - "Function value obtained: -121.6040\n", - "Current minimum: -129.2935\n", - "Iteration No: 279 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:57:59,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 279 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4558\n", - "Function value obtained: -126.0912\n", - "Current minimum: -129.2935\n", - "Iteration No: 280 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:58:13,397\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 280 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2457\n", - "Function value obtained: -124.1140\n", - "Current minimum: -129.2935\n", - "Iteration No: 281 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:58:26,649\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 281 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8276\n", - "Function value obtained: -124.7883\n", - "Current minimum: -129.2935\n", - "Iteration No: 282 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:58:40,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 282 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2322\n", - "Function value obtained: -123.5840\n", - "Current minimum: -129.2935\n", - "Iteration No: 283 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:58:53,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 283 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4608\n", - "Function value obtained: -123.2283\n", - "Current minimum: -129.2935\n", - "Iteration No: 284 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:59:08,203\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 284 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8278\n", - "Function value obtained: -120.5888\n", - "Current minimum: -129.2935\n", - "Iteration No: 285 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:59:22,049\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 285 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4681\n", - "Function value obtained: -122.4606\n", - "Current minimum: -129.2935\n", - "Iteration No: 286 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:59:35,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 286 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5274\n", - "Function value obtained: -122.7946\n", - "Current minimum: -129.2935\n", - "Iteration No: 287 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-03 23:59:49,040\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 287 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7501\n", - "Function value obtained: -119.4591\n", - "Current minimum: -129.2935\n", - "Iteration No: 288 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:00:02,845\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 288 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5659\n", - "Function value obtained: -125.5548\n", - "Current minimum: -129.2935\n", - "Iteration No: 289 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:00:16,323\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 289 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5787\n", - "Function value obtained: -121.6925\n", - "Current minimum: -129.2935\n", - "Iteration No: 290 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:00:29,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 290 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5465\n", - "Function value obtained: -124.0893\n", - "Current minimum: -129.2935\n", - "Iteration No: 291 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:00:43,490\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 291 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2565\n", - "Function value obtained: -121.8256\n", - "Current minimum: -129.2935\n", - "Iteration No: 292 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:00:57,679\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 292 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4305\n", - "Function value obtained: -125.1479\n", - "Current minimum: -129.2935\n", - "Iteration No: 293 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:01:11,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 293 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3814\n", - "Function value obtained: -122.9420\n", - "Current minimum: -129.2935\n", - "Iteration No: 294 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:01:25,559\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 294 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0078\n", - "Function value obtained: -125.4004\n", - "Current minimum: -129.2935\n", - "Iteration No: 295 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:01:39,555\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 295 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9684\n", - "Function value obtained: -127.3408\n", - "Current minimum: -129.2935\n", - "Iteration No: 296 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:01:53,564\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 296 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0920\n", - "Function value obtained: -122.1963\n", - "Current minimum: -129.2935\n", - "Iteration No: 297 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:02:07,699\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 297 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2051\n", - "Function value obtained: -121.9924\n", - "Current minimum: -129.2935\n", - "Iteration No: 298 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:02:21,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 298 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0910\n", - "Function value obtained: -125.7286\n", - "Current minimum: -129.2935\n", - "Iteration No: 299 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:02:37,061\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 299 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1944\n", - "Function value obtained: -123.3073\n", - "Current minimum: -129.2935\n", - "Iteration No: 300 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-04 00:02:51,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 300 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2314\n", - "Function value obtained: -123.9449\n", - "Current minimum: -129.2935\n", - "CPU times: user 2h 2min 28s, sys: 1h 17min 47s, total: 3h 20min 15s\n", - "Wall time: 51min 49s\n" - ] - }, - { - "data": { - "text/plain": [ - "(-129.29352912639592, [0.04473718126536452])" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", - "msy_gp.fun, msy_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "4b420c3d-c941-43dd-b7e4-fcf4a28f80e7", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n", - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 1.3560\n", - "Function value obtained: -46.5391\n", - "Current minimum: -46.5391\n", - "Iteration No: 2 started. Evaluating function at random point.\n", - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 1.1664\n", - "Function value obtained: -4.6581\n", - "Current minimum: -46.5391\n", - "Iteration No: 3 started. Evaluating function at random point.\n", - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 1.3000\n", - "Function value obtained: -14.8136\n", - "Current minimum: -46.5391\n", - "Iteration No: 4 started. Evaluating function at random point.\n", - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 1.2598\n", - "Function value obtained: -3.6463\n", - "Current minimum: -46.5391\n", - "Iteration No: 5 started. Evaluating function at random point.\n", - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 1.1637\n", - "Function value obtained: -4.3602\n", - "Current minimum: -46.5391\n", - "Iteration No: 6 started. Evaluating function at random point.\n", - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 1.2462\n", - "Function value obtained: -4.0893\n", - "Current minimum: -46.5391\n", - "Iteration No: 7 started. Evaluating function at random point.\n", - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 1.2717\n", - "Function value obtained: -10.5623\n", - "Current minimum: -46.5391\n", - "Iteration No: 8 started. Evaluating function at random point.\n", - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 1.2456\n", - "Function value obtained: -38.1398\n", - "Current minimum: -46.5391\n", - "Iteration No: 9 started. Evaluating function at random point.\n", - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 1.2314\n", - "Function value obtained: -48.0675\n", - "Current minimum: -48.0675\n", - "Iteration No: 10 started. Evaluating function at random point.\n", - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 1.4094\n", - "Function value obtained: -6.6195\n", - "Current minimum: -48.0675\n", - "Iteration No: 11 started. Searching for the next optimal point.\n", - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4140\n", - "Function value obtained: -49.6017\n", - "Current minimum: -49.6017\n", - "Iteration No: 12 started. Searching for the next optimal point.\n", - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4435\n", - "Function value obtained: -46.6843\n", - "Current minimum: -49.6017\n", - "Iteration No: 13 started. Searching for the next optimal point.\n", - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4193\n", - "Function value obtained: -45.0990\n", - "Current minimum: -49.6017\n", - "Iteration No: 14 started. Searching for the next optimal point.\n", - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5035\n", - "Function value obtained: -46.8608\n", - "Current minimum: -49.6017\n", - "Iteration No: 15 started. Searching for the next optimal point.\n", - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5919\n", - "Function value obtained: -49.3540\n", - "Current minimum: -49.6017\n", - "Iteration No: 16 started. Searching for the next optimal point.\n", - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4357\n", - "Function value obtained: -47.5765\n", - "Current minimum: -49.6017\n", - "Iteration No: 17 started. Searching for the next optimal point.\n", - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4996\n", - "Function value obtained: -45.1326\n", - "Current minimum: -49.6017\n", - "Iteration No: 18 started. Searching for the next optimal point.\n", - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4617\n", - "Function value obtained: -46.9510\n", - "Current minimum: -49.6017\n", - "Iteration No: 19 started. Searching for the next optimal point.\n", - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4780\n", - "Function value obtained: -12.6043\n", - "Current minimum: -49.6017\n", - "Iteration No: 20 started. Searching for the next optimal point.\n", - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4956\n", - "Function value obtained: -48.6197\n", - "Current minimum: -49.6017\n", - "Iteration No: 21 started. Searching for the next optimal point.\n", - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4565\n", - "Function value obtained: -45.1803\n", - "Current minimum: -49.6017\n", - "Iteration No: 22 started. Searching for the next optimal point.\n", - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3789\n", - "Function value obtained: -48.0291\n", - "Current minimum: -49.6017\n", - "Iteration No: 23 started. Searching for the next optimal point.\n", - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4518\n", - "Function value obtained: -47.8936\n", - "Current minimum: -49.6017\n", - "Iteration No: 24 started. Searching for the next optimal point.\n", - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4929\n", - "Function value obtained: -46.8791\n", - "Current minimum: -49.6017\n", - "Iteration No: 25 started. Searching for the next optimal point.\n", - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5805\n", - "Function value obtained: -48.7646\n", - "Current minimum: -49.6017\n", - "Iteration No: 26 started. Searching for the next optimal point.\n", - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4410\n", - "Function value obtained: -45.4169\n", - "Current minimum: -49.6017\n", - "Iteration No: 27 started. Searching for the next optimal point.\n", - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5256\n", - "Function value obtained: -46.7357\n", - "Current minimum: -49.6017\n", - "Iteration No: 28 started. Searching for the next optimal point.\n", - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5359\n", - "Function value obtained: -46.2242\n", - "Current minimum: -49.6017\n", - "Iteration No: 29 started. Searching for the next optimal point.\n", - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5400\n", - "Function value obtained: -12.6620\n", - "Current minimum: -49.6017\n", - "Iteration No: 30 started. Searching for the next optimal point.\n", - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6019\n", - "Function value obtained: -43.9229\n", - "Current minimum: -49.6017\n", - "Iteration No: 31 started. Searching for the next optimal point.\n", - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4984\n", - "Function value obtained: -47.8351\n", - "Current minimum: -49.6017\n", - "Iteration No: 32 started. Searching for the next optimal point.\n", - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5293\n", - "Function value obtained: -44.4191\n", - "Current minimum: -49.6017\n", - "Iteration No: 33 started. Searching for the next optimal point.\n", - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4842\n", - "Function value obtained: -47.5384\n", - "Current minimum: -49.6017\n", - "Iteration No: 34 started. Searching for the next optimal point.\n", - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6029\n", - "Function value obtained: -47.4318\n", - "Current minimum: -49.6017\n", - "Iteration No: 35 started. Searching for the next optimal point.\n", - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4040\n", - "Function value obtained: -44.8686\n", - "Current minimum: -49.6017\n", - "Iteration No: 36 started. Searching for the next optimal point.\n", - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5284\n", - "Function value obtained: -47.4501\n", - "Current minimum: -49.6017\n", - "Iteration No: 37 started. Searching for the next optimal point.\n", - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3685\n", - "Function value obtained: -47.0818\n", - "Current minimum: -49.6017\n", - "Iteration No: 38 started. Searching for the next optimal point.\n", - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4836\n", - "Function value obtained: -46.7556\n", - "Current minimum: -49.6017\n", - "Iteration No: 39 started. Searching for the next optimal point.\n", - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5081\n", - "Function value obtained: -46.9364\n", - "Current minimum: -49.6017\n", - "Iteration No: 40 started. Searching for the next optimal point.\n", - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4114\n", - "Function value obtained: -46.0513\n", - "Current minimum: -49.6017\n", - "Iteration No: 41 started. Searching for the next optimal point.\n", - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4602\n", - "Function value obtained: -47.1258\n", - "Current minimum: -49.6017\n", - "Iteration No: 42 started. Searching for the next optimal point.\n", - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4598\n", - "Function value obtained: -44.6687\n", - "Current minimum: -49.6017\n", - "Iteration No: 43 started. Searching for the next optimal point.\n", - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4767\n", - "Function value obtained: -45.9894\n", - "Current minimum: -49.6017\n", - "Iteration No: 44 started. Searching for the next optimal point.\n", - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5332\n", - "Function value obtained: -46.3990\n", - "Current minimum: -49.6017\n", - "Iteration No: 45 started. Searching for the next optimal point.\n", - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5325\n", - "Function value obtained: -47.7062\n", - "Current minimum: -49.6017\n", - "Iteration No: 46 started. Searching for the next optimal point.\n", - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5390\n", - "Function value obtained: -47.8023\n", - "Current minimum: -49.6017\n", - "Iteration No: 47 started. Searching for the next optimal point.\n", - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4629\n", - "Function value obtained: -45.6460\n", - "Current minimum: -49.6017\n", - "Iteration No: 48 started. Searching for the next optimal point.\n", - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5021\n", - "Function value obtained: -44.3852\n", - "Current minimum: -49.6017\n", - "Iteration No: 49 started. Searching for the next optimal point.\n", - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4780\n", - "Function value obtained: -46.6708\n", - "Current minimum: -49.6017\n", - "Iteration No: 50 started. Searching for the next optimal point.\n", - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4235\n", - "Function value obtained: -45.2947\n", - "Current minimum: -49.6017\n", - "Iteration No: 51 started. Searching for the next optimal point.\n", - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4191\n", - "Function value obtained: -47.4422\n", - "Current minimum: -49.6017\n", - "Iteration No: 52 started. Searching for the next optimal point.\n", - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5193\n", - "Function value obtained: -47.2893\n", - "Current minimum: -49.6017\n", - "Iteration No: 53 started. Searching for the next optimal point.\n", - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4471\n", - "Function value obtained: -48.0579\n", - "Current minimum: -49.6017\n", - "Iteration No: 54 started. Searching for the next optimal point.\n", - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5124\n", - "Function value obtained: -46.6369\n", - "Current minimum: -49.6017\n", - "Iteration No: 55 started. Searching for the next optimal point.\n", - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5033\n", - "Function value obtained: -48.1478\n", - "Current minimum: -49.6017\n", - "Iteration No: 56 started. Searching for the next optimal point.\n", - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5597\n", - "Function value obtained: -48.1605\n", - "Current minimum: -49.6017\n", - "Iteration No: 57 started. Searching for the next optimal point.\n", - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4899\n", - "Function value obtained: -45.0397\n", - "Current minimum: -49.6017\n", - "Iteration No: 58 started. Searching for the next optimal point.\n", - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4978\n", - "Function value obtained: -46.5459\n", - "Current minimum: -49.6017\n", - "Iteration No: 59 started. Searching for the next optimal point.\n", - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4811\n", - "Function value obtained: -43.7516\n", - "Current minimum: -49.6017\n", - "Iteration No: 60 started. Searching for the next optimal point.\n", - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5171\n", - "Function value obtained: -47.2481\n", - "Current minimum: -49.6017\n", - "Iteration No: 61 started. Searching for the next optimal point.\n", - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4386\n", - "Function value obtained: -46.4790\n", - "Current minimum: -49.6017\n", - "Iteration No: 62 started. Searching for the next optimal point.\n", - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4536\n", - "Function value obtained: -47.3387\n", - "Current minimum: -49.6017\n", - "Iteration No: 63 started. Searching for the next optimal point.\n", - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6102\n", - "Function value obtained: -47.5327\n", - "Current minimum: -49.6017\n", - "Iteration No: 64 started. Searching for the next optimal point.\n", - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5174\n", - "Function value obtained: -45.3859\n", - "Current minimum: -49.6017\n", - "Iteration No: 65 started. Searching for the next optimal point.\n", - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4711\n", - "Function value obtained: -46.8727\n", - "Current minimum: -49.6017\n", - "Iteration No: 66 started. Searching for the next optimal point.\n", - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5031\n", - "Function value obtained: -48.0277\n", - "Current minimum: -49.6017\n", - "Iteration No: 67 started. Searching for the next optimal point.\n", - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5509\n", - "Function value obtained: -48.6187\n", - "Current minimum: -49.6017\n", - "Iteration No: 68 started. Searching for the next optimal point.\n", - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5195\n", - "Function value obtained: -48.3695\n", - "Current minimum: -49.6017\n", - "Iteration No: 69 started. Searching for the next optimal point.\n", - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4830\n", - "Function value obtained: -44.5009\n", - "Current minimum: -49.6017\n", - "Iteration No: 70 started. Searching for the next optimal point.\n", - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5454\n", - "Function value obtained: -45.3096\n", - "Current minimum: -49.6017\n", - "Iteration No: 71 started. Searching for the next optimal point.\n", - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4323\n", - "Function value obtained: -47.1526\n", - "Current minimum: -49.6017\n", - "Iteration No: 72 started. Searching for the next optimal point.\n", - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4273\n", - "Function value obtained: -47.3175\n", - "Current minimum: -49.6017\n", - "Iteration No: 73 started. Searching for the next optimal point.\n", - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5579\n", - "Function value obtained: -46.5905\n", - "Current minimum: -49.6017\n", - "Iteration No: 74 started. Searching for the next optimal point.\n", - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5067\n", - "Function value obtained: -46.8752\n", - "Current minimum: -49.6017\n", - "Iteration No: 75 started. Searching for the next optimal point.\n", - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5313\n", - "Function value obtained: -47.8672\n", - "Current minimum: -49.6017\n", - "Iteration No: 76 started. Searching for the next optimal point.\n", - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5224\n", - "Function value obtained: -45.6860\n", - "Current minimum: -49.6017\n", - "Iteration No: 77 started. Searching for the next optimal point.\n", - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5298\n", - "Function value obtained: -46.8637\n", - "Current minimum: -49.6017\n", - "Iteration No: 78 started. Searching for the next optimal point.\n", - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7157\n", - "Function value obtained: -47.9359\n", - "Current minimum: -49.6017\n", - "Iteration No: 79 started. Searching for the next optimal point.\n", - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4869\n", - "Function value obtained: -48.3924\n", - "Current minimum: -49.6017\n", - "Iteration No: 80 started. Searching for the next optimal point.\n", - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4701\n", - "Function value obtained: -45.2819\n", - "Current minimum: -49.6017\n", - "Iteration No: 81 started. Searching for the next optimal point.\n", - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4596\n", - "Function value obtained: -48.8099\n", - "Current minimum: -49.6017\n", - "Iteration No: 82 started. Searching for the next optimal point.\n", - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4203\n", - "Function value obtained: -44.6818\n", - "Current minimum: -49.6017\n", - "Iteration No: 83 started. Searching for the next optimal point.\n", - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3309\n", - "Function value obtained: -48.0720\n", - "Current minimum: -49.6017\n", - "Iteration No: 84 started. Searching for the next optimal point.\n", - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5261\n", - "Function value obtained: -47.3489\n", - "Current minimum: -49.6017\n", - "Iteration No: 85 started. Searching for the next optimal point.\n", - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4705\n", - "Function value obtained: -48.0898\n", - "Current minimum: -49.6017\n", - "Iteration No: 86 started. Searching for the next optimal point.\n", - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4849\n", - "Function value obtained: -45.8602\n", - "Current minimum: -49.6017\n", - "Iteration No: 87 started. Searching for the next optimal point.\n", - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6133\n", - "Function value obtained: -47.4123\n", - "Current minimum: -49.6017\n", - "Iteration No: 88 started. Searching for the next optimal point.\n", - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5090\n", - "Function value obtained: -46.1113\n", - "Current minimum: -49.6017\n", - "Iteration No: 89 started. Searching for the next optimal point.\n", - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5676\n", - "Function value obtained: -48.4236\n", - "Current minimum: -49.6017\n", - "Iteration No: 90 started. Searching for the next optimal point.\n", - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4747\n", - "Function value obtained: -47.6057\n", - "Current minimum: -49.6017\n", - "Iteration No: 91 started. Searching for the next optimal point.\n", - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4737\n", - "Function value obtained: -45.1571\n", - "Current minimum: -49.6017\n", - "Iteration No: 92 started. Searching for the next optimal point.\n", - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4616\n", - "Function value obtained: -48.5987\n", - "Current minimum: -49.6017\n", - "Iteration No: 93 started. Searching for the next optimal point.\n", - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4667\n", - "Function value obtained: -47.1953\n", - "Current minimum: -49.6017\n", - "Iteration No: 94 started. Searching for the next optimal point.\n", - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4862\n", - "Function value obtained: -46.9125\n", - "Current minimum: -49.6017\n", - "Iteration No: 95 started. Searching for the next optimal point.\n", - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4970\n", - "Function value obtained: -47.4312\n", - "Current minimum: -49.6017\n", - "Iteration No: 96 started. Searching for the next optimal point.\n", - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4997\n", - "Function value obtained: -47.1148\n", - "Current minimum: -49.6017\n", - "Iteration No: 97 started. Searching for the next optimal point.\n", - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6946\n", - "Function value obtained: -46.7082\n", - "Current minimum: -49.6017\n", - "Iteration No: 98 started. Searching for the next optimal point.\n", - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5323\n", - "Function value obtained: -47.0256\n", - "Current minimum: -49.6017\n", - "Iteration No: 99 started. Searching for the next optimal point.\n", - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4895\n", - "Function value obtained: -45.8617\n", - "Current minimum: -49.6017\n", - "Iteration No: 100 started. Searching for the next optimal point.\n", - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4927\n", - "Function value obtained: -46.0801\n", - "Current minimum: -49.6017\n", - "Iteration No: 101 started. Searching for the next optimal point.\n", - "Iteration No: 101 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5328\n", - "Function value obtained: -47.8178\n", - "Current minimum: -49.6017\n", - "Iteration No: 102 started. Searching for the next optimal point.\n", - "Iteration No: 102 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5578\n", - "Function value obtained: -45.8014\n", - "Current minimum: -49.6017\n", - "Iteration No: 103 started. Searching for the next optimal point.\n", - "Iteration No: 103 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5063\n", - "Function value obtained: -48.7166\n", - "Current minimum: -49.6017\n", - "Iteration No: 104 started. Searching for the next optimal point.\n", - "Iteration No: 104 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4746\n", - "Function value obtained: -46.6069\n", - "Current minimum: -49.6017\n", - "Iteration No: 105 started. Searching for the next optimal point.\n", - "Iteration No: 105 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5559\n", - "Function value obtained: -47.1771\n", - "Current minimum: -49.6017\n", - "Iteration No: 106 started. Searching for the next optimal point.\n", - "Iteration No: 106 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4994\n", - "Function value obtained: -47.1168\n", - "Current minimum: -49.6017\n", - "Iteration No: 107 started. Searching for the next optimal point.\n", - "Iteration No: 107 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5939\n", - "Function value obtained: -46.4010\n", - "Current minimum: -49.6017\n", - "Iteration No: 108 started. Searching for the next optimal point.\n", - "Iteration No: 108 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5162\n", - "Function value obtained: -48.2321\n", - "Current minimum: -49.6017\n", - "Iteration No: 109 started. Searching for the next optimal point.\n", - "Iteration No: 109 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4968\n", - "Function value obtained: -45.6238\n", - "Current minimum: -49.6017\n", - "Iteration No: 110 started. Searching for the next optimal point.\n", - "Iteration No: 110 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5985\n", - "Function value obtained: -47.4828\n", - "Current minimum: -49.6017\n", - "Iteration No: 111 started. Searching for the next optimal point.\n", - "Iteration No: 111 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5077\n", - "Function value obtained: -46.7207\n", - "Current minimum: -49.6017\n", - "Iteration No: 112 started. Searching for the next optimal point.\n", - "Iteration No: 112 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5293\n", - "Function value obtained: -46.3870\n", - "Current minimum: -49.6017\n", - "Iteration No: 113 started. Searching for the next optimal point.\n", - "Iteration No: 113 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4890\n", - "Function value obtained: -47.6239\n", - "Current minimum: -49.6017\n", - "Iteration No: 114 started. Searching for the next optimal point.\n", - "Iteration No: 114 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5437\n", - "Function value obtained: -46.1445\n", - "Current minimum: -49.6017\n", - "Iteration No: 115 started. Searching for the next optimal point.\n", - "Iteration No: 115 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4350\n", - "Function value obtained: -47.7099\n", - "Current minimum: -49.6017\n", - "Iteration No: 116 started. Searching for the next optimal point.\n", - "Iteration No: 116 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4450\n", - "Function value obtained: -47.2153\n", - "Current minimum: -49.6017\n", - "Iteration No: 117 started. Searching for the next optimal point.\n", - "Iteration No: 117 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5301\n", - "Function value obtained: -46.0510\n", - "Current minimum: -49.6017\n", - "Iteration No: 118 started. Searching for the next optimal point.\n", - "Iteration No: 118 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6147\n", - "Function value obtained: -46.7348\n", - "Current minimum: -49.6017\n", - "Iteration No: 119 started. Searching for the next optimal point.\n", - "Iteration No: 119 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4782\n", - "Function value obtained: -48.0223\n", - "Current minimum: -49.6017\n", - "Iteration No: 120 started. Searching for the next optimal point.\n", - "Iteration No: 120 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5107\n", - "Function value obtained: -45.9638\n", - "Current minimum: -49.6017\n", - "Iteration No: 121 started. Searching for the next optimal point.\n", - "Iteration No: 121 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5445\n", - "Function value obtained: -47.4704\n", - "Current minimum: -49.6017\n", - "Iteration No: 122 started. Searching for the next optimal point.\n", - "Iteration No: 122 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4802\n", - "Function value obtained: -46.3621\n", - "Current minimum: -49.6017\n", - "Iteration No: 123 started. Searching for the next optimal point.\n", - "Iteration No: 123 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4472\n", - "Function value obtained: -48.2987\n", - "Current minimum: -49.6017\n", - "Iteration No: 124 started. Searching for the next optimal point.\n", - "Iteration No: 124 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4813\n", - "Function value obtained: -45.8185\n", - "Current minimum: -49.6017\n", - "Iteration No: 125 started. Searching for the next optimal point.\n", - "Iteration No: 125 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5345\n", - "Function value obtained: -46.9240\n", - "Current minimum: -49.6017\n", - "Iteration No: 126 started. Searching for the next optimal point.\n", - "Iteration No: 126 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6460\n", - "Function value obtained: -45.6050\n", - "Current minimum: -49.6017\n", - "Iteration No: 127 started. Searching for the next optimal point.\n", - "Iteration No: 127 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5271\n", - "Function value obtained: -45.5833\n", - "Current minimum: -49.6017\n", - "Iteration No: 128 started. Searching for the next optimal point.\n", - "Iteration No: 128 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5524\n", - "Function value obtained: -45.4827\n", - "Current minimum: -49.6017\n", - "Iteration No: 129 started. Searching for the next optimal point.\n", - "Iteration No: 129 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5740\n", - "Function value obtained: -48.2536\n", - "Current minimum: -49.6017\n", - "Iteration No: 130 started. Searching for the next optimal point.\n", - "Iteration No: 130 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4685\n", - "Function value obtained: -46.3540\n", - "Current minimum: -49.6017\n", - "Iteration No: 131 started. Searching for the next optimal point.\n", - "Iteration No: 131 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5441\n", - "Function value obtained: -47.9790\n", - "Current minimum: -49.6017\n", - "Iteration No: 132 started. Searching for the next optimal point.\n", - "Iteration No: 132 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5442\n", - "Function value obtained: -46.5460\n", - "Current minimum: -49.6017\n", - "Iteration No: 133 started. Searching for the next optimal point.\n", - "Iteration No: 133 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4367\n", - "Function value obtained: -49.8897\n", - "Current minimum: -49.8897\n", - "Iteration No: 134 started. Searching for the next optimal point.\n", - "Iteration No: 134 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5285\n", - "Function value obtained: -48.0609\n", - "Current minimum: -49.8897\n", - "Iteration No: 135 started. Searching for the next optimal point.\n", - "Iteration No: 135 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5231\n", - "Function value obtained: -45.9417\n", - "Current minimum: -49.8897\n", - "Iteration No: 136 started. Searching for the next optimal point.\n", - "Iteration No: 136 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5069\n", - "Function value obtained: -48.1052\n", - "Current minimum: -49.8897\n", - "Iteration No: 137 started. Searching for the next optimal point.\n", - "Iteration No: 137 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4651\n", - "Function value obtained: -47.1823\n", - "Current minimum: -49.8897\n", - "Iteration No: 138 started. Searching for the next optimal point.\n", - "Iteration No: 138 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5213\n", - "Function value obtained: -46.5411\n", - "Current minimum: -49.8897\n", - "Iteration No: 139 started. Searching for the next optimal point.\n", - "Iteration No: 139 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4664\n", - "Function value obtained: -44.4394\n", - "Current minimum: -49.8897\n", - "Iteration No: 140 started. Searching for the next optimal point.\n", - "Iteration No: 140 ended. Search finished for the next optimal point.\n", - "Time taken: 1.7325\n", - "Function value obtained: -48.4451\n", - "Current minimum: -49.8897\n", - "Iteration No: 141 started. Searching for the next optimal point.\n", - "Iteration No: 141 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5663\n", - "Function value obtained: -46.7940\n", - "Current minimum: -49.8897\n", - "Iteration No: 142 started. Searching for the next optimal point.\n", - "Iteration No: 142 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5296\n", - "Function value obtained: -47.4213\n", - "Current minimum: -49.8897\n", - "Iteration No: 143 started. Searching for the next optimal point.\n", - "Iteration No: 143 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5615\n", - "Function value obtained: -44.7370\n", - "Current minimum: -49.8897\n", - "Iteration No: 144 started. Searching for the next optimal point.\n", - "Iteration No: 144 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4711\n", - "Function value obtained: -46.5875\n", - "Current minimum: -49.8897\n", - "Iteration No: 145 started. Searching for the next optimal point.\n", - "Iteration No: 145 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4040\n", - "Function value obtained: -46.5380\n", - "Current minimum: -49.8897\n", - "Iteration No: 146 started. Searching for the next optimal point.\n", - "Iteration No: 146 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4615\n", - "Function value obtained: -47.0075\n", - "Current minimum: -49.8897\n", - "Iteration No: 147 started. Searching for the next optimal point.\n", - "Iteration No: 147 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5457\n", - "Function value obtained: -47.6239\n", - "Current minimum: -49.8897\n", - "Iteration No: 148 started. Searching for the next optimal point.\n", - "Iteration No: 148 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4523\n", - "Function value obtained: -45.9532\n", - "Current minimum: -49.8897\n", - "Iteration No: 149 started. Searching for the next optimal point.\n", - "Iteration No: 149 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5191\n", - "Function value obtained: -47.6434\n", - "Current minimum: -49.8897\n", - "Iteration No: 150 started. Searching for the next optimal point.\n", - "Iteration No: 150 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4987\n", - "Function value obtained: -45.9662\n", - "Current minimum: -49.8897\n", - "Iteration No: 151 started. Searching for the next optimal point.\n", - "Iteration No: 151 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5810\n", - "Function value obtained: -46.5016\n", - "Current minimum: -49.8897\n", - "Iteration No: 152 started. Searching for the next optimal point.\n", - "Iteration No: 152 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4548\n", - "Function value obtained: -46.2267\n", - "Current minimum: -49.8897\n", - "Iteration No: 153 started. Searching for the next optimal point.\n", - "Iteration No: 153 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4238\n", - "Function value obtained: -47.4453\n", - "Current minimum: -49.8897\n", - "Iteration No: 154 started. Searching for the next optimal point.\n", - "Iteration No: 154 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5048\n", - "Function value obtained: -47.2020\n", - "Current minimum: -49.8897\n", - "Iteration No: 155 started. Searching for the next optimal point.\n", - "Iteration No: 155 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4631\n", - "Function value obtained: -47.1068\n", - "Current minimum: -49.8897\n", - "Iteration No: 156 started. Searching for the next optimal point.\n", - "Iteration No: 156 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3817\n", - "Function value obtained: -48.2429\n", - "Current minimum: -49.8897\n", - "Iteration No: 157 started. Searching for the next optimal point.\n", - "Iteration No: 157 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4986\n", - "Function value obtained: -44.8097\n", - "Current minimum: -49.8897\n", - "Iteration No: 158 started. Searching for the next optimal point.\n", - "Iteration No: 158 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4233\n", - "Function value obtained: -46.8809\n", - "Current minimum: -49.8897\n", - "Iteration No: 159 started. Searching for the next optimal point.\n", - "Iteration No: 159 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5612\n", - "Function value obtained: -45.5597\n", - "Current minimum: -49.8897\n", - "Iteration No: 160 started. Searching for the next optimal point.\n", - "Iteration No: 160 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6052\n", - "Function value obtained: -46.4952\n", - "Current minimum: -49.8897\n", - "Iteration No: 161 started. Searching for the next optimal point.\n", - "Iteration No: 161 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5001\n", - "Function value obtained: -46.6400\n", - "Current minimum: -49.8897\n", - "Iteration No: 162 started. Searching for the next optimal point.\n", - "Iteration No: 162 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6195\n", - "Function value obtained: -46.5302\n", - "Current minimum: -49.8897\n", - "Iteration No: 163 started. Searching for the next optimal point.\n", - "Iteration No: 163 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5431\n", - "Function value obtained: -47.6782\n", - "Current minimum: -49.8897\n", - "Iteration No: 164 started. Searching for the next optimal point.\n", - "Iteration No: 164 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4370\n", - "Function value obtained: -47.6993\n", - "Current minimum: -49.8897\n", - "Iteration No: 165 started. Searching for the next optimal point.\n", - "Iteration No: 165 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5255\n", - "Function value obtained: -10.5757\n", - "Current minimum: -49.8897\n", - "Iteration No: 166 started. Searching for the next optimal point.\n", - "Iteration No: 166 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4695\n", - "Function value obtained: -48.1290\n", - "Current minimum: -49.8897\n", - "Iteration No: 167 started. Searching for the next optimal point.\n", - "Iteration No: 167 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5103\n", - "Function value obtained: -46.8644\n", - "Current minimum: -49.8897\n", - "Iteration No: 168 started. Searching for the next optimal point.\n", - "Iteration No: 168 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4537\n", - "Function value obtained: -46.8415\n", - "Current minimum: -49.8897\n", - "Iteration No: 169 started. Searching for the next optimal point.\n", - "Iteration No: 169 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4604\n", - "Function value obtained: -47.4611\n", - "Current minimum: -49.8897\n", - "Iteration No: 170 started. Searching for the next optimal point.\n", - "Iteration No: 170 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5201\n", - "Function value obtained: -45.5961\n", - "Current minimum: -49.8897\n", - "Iteration No: 171 started. Searching for the next optimal point.\n", - "Iteration No: 171 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5280\n", - "Function value obtained: -44.9130\n", - "Current minimum: -49.8897\n", - "Iteration No: 172 started. Searching for the next optimal point.\n", - "Iteration No: 172 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4738\n", - "Function value obtained: -47.5096\n", - "Current minimum: -49.8897\n", - "Iteration No: 173 started. Searching for the next optimal point.\n", - "Iteration No: 173 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5386\n", - "Function value obtained: -46.5298\n", - "Current minimum: -49.8897\n", - "Iteration No: 174 started. Searching for the next optimal point.\n", - "Iteration No: 174 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5460\n", - "Function value obtained: -48.4569\n", - "Current minimum: -49.8897\n", - "Iteration No: 175 started. Searching for the next optimal point.\n", - "Iteration No: 175 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4322\n", - "Function value obtained: -46.6290\n", - "Current minimum: -49.8897\n", - "Iteration No: 176 started. Searching for the next optimal point.\n", - "Iteration No: 176 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5870\n", - "Function value obtained: -46.9834\n", - "Current minimum: -49.8897\n", - "Iteration No: 177 started. Searching for the next optimal point.\n", - "Iteration No: 177 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5292\n", - "Function value obtained: -45.0813\n", - "Current minimum: -49.8897\n", - "Iteration No: 178 started. Searching for the next optimal point.\n", - "Iteration No: 178 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5267\n", - "Function value obtained: -49.7659\n", - "Current minimum: -49.8897\n", - "Iteration No: 179 started. Searching for the next optimal point.\n", - "Iteration No: 179 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5247\n", - "Function value obtained: -47.7063\n", - "Current minimum: -49.8897\n", - "Iteration No: 180 started. Searching for the next optimal point.\n", - "Iteration No: 180 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4800\n", - "Function value obtained: -46.8807\n", - "Current minimum: -49.8897\n", - "Iteration No: 181 started. Searching for the next optimal point.\n", - "Iteration No: 181 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5016\n", - "Function value obtained: -46.6104\n", - "Current minimum: -49.8897\n", - "Iteration No: 182 started. Searching for the next optimal point.\n", - "Iteration No: 182 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3970\n", - "Function value obtained: -45.0529\n", - "Current minimum: -49.8897\n", - "Iteration No: 183 started. Searching for the next optimal point.\n", - "Iteration No: 183 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5808\n", - "Function value obtained: -47.7305\n", - "Current minimum: -49.8897\n", - "Iteration No: 184 started. Searching for the next optimal point.\n", - "Iteration No: 184 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5231\n", - "Function value obtained: -46.8753\n", - "Current minimum: -49.8897\n", - "Iteration No: 185 started. Searching for the next optimal point.\n", - "Iteration No: 185 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4697\n", - "Function value obtained: -46.4229\n", - "Current minimum: -49.8897\n", - "Iteration No: 186 started. Searching for the next optimal point.\n", - "Iteration No: 186 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4536\n", - "Function value obtained: -46.3220\n", - "Current minimum: -49.8897\n", - "Iteration No: 187 started. Searching for the next optimal point.\n", - "Iteration No: 187 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4468\n", - "Function value obtained: -45.0930\n", - "Current minimum: -49.8897\n", - "Iteration No: 188 started. Searching for the next optimal point.\n", - "Iteration No: 188 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4897\n", - "Function value obtained: -46.2899\n", - "Current minimum: -49.8897\n", - "Iteration No: 189 started. Searching for the next optimal point.\n", - "Iteration No: 189 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5649\n", - "Function value obtained: -45.7537\n", - "Current minimum: -49.8897\n", - "Iteration No: 190 started. Searching for the next optimal point.\n", - "Iteration No: 190 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5258\n", - "Function value obtained: -47.8918\n", - "Current minimum: -49.8897\n", - "Iteration No: 191 started. Searching for the next optimal point.\n", - "Iteration No: 191 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4762\n", - "Function value obtained: -44.7468\n", - "Current minimum: -49.8897\n", - "Iteration No: 192 started. Searching for the next optimal point.\n", - "Iteration No: 192 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4744\n", - "Function value obtained: -45.6541\n", - "Current minimum: -49.8897\n", - "Iteration No: 193 started. Searching for the next optimal point.\n", - "Iteration No: 193 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4850\n", - "Function value obtained: -47.9981\n", - "Current minimum: -49.8897\n", - "Iteration No: 194 started. Searching for the next optimal point.\n", - "Iteration No: 194 ended. Search finished for the next optimal point.\n", - "Time taken: 1.6339\n", - "Function value obtained: -48.7292\n", - "Current minimum: -49.8897\n", - "Iteration No: 195 started. Searching for the next optimal point.\n", - "Iteration No: 195 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4541\n", - "Function value obtained: -45.9848\n", - "Current minimum: -49.8897\n", - "Iteration No: 196 started. Searching for the next optimal point.\n", - "Iteration No: 196 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4691\n", - "Function value obtained: -47.4092\n", - "Current minimum: -49.8897\n", - "Iteration No: 197 started. Searching for the next optimal point.\n", - "Iteration No: 197 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4781\n", - "Function value obtained: -47.0885\n", - "Current minimum: -49.8897\n", - "Iteration No: 198 started. Searching for the next optimal point.\n", - "Iteration No: 198 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4757\n", - "Function value obtained: -46.2062\n", - "Current minimum: -49.8897\n", - "Iteration No: 199 started. Searching for the next optimal point.\n", - "Iteration No: 199 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5059\n", - "Function value obtained: -47.5081\n", - "Current minimum: -49.8897\n", - "Iteration No: 200 started. Searching for the next optimal point.\n", - "Iteration No: 200 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5575\n", - "Function value obtained: -45.9276\n", - "Current minimum: -49.8897\n", - "Iteration No: 201 started. Searching for the next optimal point.\n", - "Iteration No: 201 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5190\n", - "Function value obtained: -46.9264\n", - "Current minimum: -49.8897\n", - "Iteration No: 202 started. Searching for the next optimal point.\n", - "Iteration No: 202 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4911\n", - "Function value obtained: -46.2056\n", - "Current minimum: -49.8897\n", - "Iteration No: 203 started. Searching for the next optimal point.\n", - "Iteration No: 203 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4858\n", - "Function value obtained: -47.2440\n", - "Current minimum: -49.8897\n", - "Iteration No: 204 started. Searching for the next optimal point.\n", - "Iteration No: 204 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4779\n", - "Function value obtained: -46.6488\n", - "Current minimum: -49.8897\n", - "Iteration No: 205 started. Searching for the next optimal point.\n", - "Iteration No: 205 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5805\n", - "Function value obtained: -46.4220\n", - "Current minimum: -49.8897\n", - "Iteration No: 206 started. Searching for the next optimal point.\n", - "Iteration No: 206 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4339\n", - "Function value obtained: -46.7641\n", - "Current minimum: -49.8897\n", - "Iteration No: 207 started. Searching for the next optimal point.\n", - "Iteration No: 207 ended. Search finished for the next optimal point.\n", - "Time taken: 1.3939\n", - "Function value obtained: -46.9997\n", - "Current minimum: -49.8897\n", - "Iteration No: 208 started. Searching for the next optimal point.\n", - "Iteration No: 208 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5466\n", - "Function value obtained: -48.8444\n", - "Current minimum: -49.8897\n", - "Iteration No: 209 started. Searching for the next optimal point.\n", - "Iteration No: 209 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4416\n", - "Function value obtained: -46.6399\n", - "Current minimum: -49.8897\n", - "Iteration No: 210 started. Searching for the next optimal point.\n", - "Iteration No: 210 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4550\n", - "Function value obtained: -45.9676\n", - "Current minimum: -49.8897\n", - "Iteration No: 211 started. Searching for the next optimal point.\n", - "Iteration No: 211 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5161\n", - "Function value obtained: -48.5639\n", - "Current minimum: -49.8897\n", - "Iteration No: 212 started. Searching for the next optimal point.\n", - "Iteration No: 212 ended. Search finished for the next optimal point.\n", - "Time taken: 1.4859\n", - "Function value obtained: -46.1388\n", - "Current minimum: -49.8897\n", - "Iteration No: 213 started. Searching for the next optimal point.\n", - "Iteration No: 213 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5181\n", - "Function value obtained: -46.3721\n", - "Current minimum: -49.8897\n", - "Iteration No: 214 started. Searching for the next optimal point.\n", - "Iteration No: 214 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5108\n", - "Function value obtained: -46.5996\n", - "Current minimum: -49.8897\n", - "Iteration No: 215 started. Searching for the next optimal point.\n", - "Iteration No: 215 ended. Search finished for the next optimal point.\n", - "Time taken: 1.5101\n", - "Function value obtained: -48.4447\n", - "Current minimum: -49.8897\n", - "Iteration No: 216 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.047611662929937286] before, using random point [0.018415831307791897]\n", - " warnings.warn(\n" + "/opt/venv/lib/python3.10/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point [0.047611662929937286] before, using random point [0.018415831307791897]\n", + " warnings.warn(\n" ] }, { @@ -7211,32 +2354,2451 @@ { "data": { "text/plain": [ - "(-49.8897409867848, [0.05286591768013252])" + "(-49.8897409867848, [0.05286591768013252])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", + "msy_gbrt.fun, msy_gbrt.x" + ] + }, + { + "cell_type": "markdown", + "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", + "metadata": {}, + "source": [ + "### Esc" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:44:26,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 9.4956\n", + "Function value obtained: -2.3549\n", + "Current minimum: -2.3549\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:44:35,768\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 9.5832\n", + "Function value obtained: -76.5912\n", + "Current minimum: -76.5912\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:44:45,350\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 9.5966\n", + "Function value obtained: -1.4268\n", + "Current minimum: -76.5912\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:44:54,942\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 9.5925\n", + "Function value obtained: -1.6818\n", + "Current minimum: -76.5912\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:45:04,561\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 9.6298\n", + "Function value obtained: -1.0852\n", + "Current minimum: -76.5912\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:45:14,172\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 9.7183\n", + "Function value obtained: -0.0000\n", + "Current minimum: -76.5912\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:45:23,877\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.3285\n", + "Function value obtained: -1.5627\n", + "Current minimum: -76.5912\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:45:33,211\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 9.4120\n", + "Function value obtained: -22.1856\n", + "Current minimum: -76.5912\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:45:42,635\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 9.6492\n", + "Function value obtained: -1.3382\n", + "Current minimum: -76.5912\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:45:52,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 14.1676\n", + "Function value obtained: -84.7758\n", + "Current minimum: -84.7758\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:46:06,527\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9592\n", + "Function value obtained: -82.5314\n", + "Current minimum: -84.7758\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:46:17,409\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1233\n", + "Function value obtained: -82.6363\n", + "Current minimum: -84.7758\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:46:28,578\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9767\n", + "Function value obtained: -80.6832\n", + "Current minimum: -84.7758\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:46:39,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4019\n", + "Function value obtained: -82.1781\n", + "Current minimum: -84.7758\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:46:50,974\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4549\n", + "Function value obtained: -82.2314\n", + "Current minimum: -84.7758\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:47:02,467\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2693\n", + "Function value obtained: -85.0952\n", + "Current minimum: -85.0952\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:47:13,676\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1551\n", + "Function value obtained: -82.6191\n", + "Current minimum: -85.0952\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:47:24,911\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5349\n", + "Function value obtained: -6.5931\n", + "Current minimum: -85.0952\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:47:35,436\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7792\n", + "Function value obtained: -84.5019\n", + "Current minimum: -85.0952\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:47:46,183\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0469\n", + "Function value obtained: -84.5658\n", + "Current minimum: -85.0952\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:47:56,213\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9517\n", + "Function value obtained: -83.2918\n", + "Current minimum: -85.0952\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:48:06,165\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0707\n", + "Function value obtained: -85.0394\n", + "Current minimum: -85.0952\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:48:16,302\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9502\n", + "Function value obtained: -83.4533\n", + "Current minimum: -85.0952\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:48:26,281\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7623\n", + "Function value obtained: -83.1873\n", + "Current minimum: -85.0952\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:48:36,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4188\n", + "Function value obtained: -83.3113\n", + "Current minimum: -85.0952\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:48:47,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5156\n", + "Function value obtained: -81.1631\n", + "Current minimum: -85.0952\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:48:57,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4621\n", + "Function value obtained: -82.2480\n", + "Current minimum: -85.0952\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:49:08,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3142\n", + "Function value obtained: -84.6498\n", + "Current minimum: -85.0952\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:49:18,752\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6948\n", + "Function value obtained: -82.5131\n", + "Current minimum: -85.0952\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:49:29,450\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3540\n", + "Function value obtained: -81.5260\n", + "Current minimum: -85.0952\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:49:39,810\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7156\n", + "Function value obtained: -83.9358\n", + "Current minimum: -85.0952\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:49:50,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2034\n", + "Function value obtained: -82.3135\n", + "Current minimum: -85.0952\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:50:00,745\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4620\n", + "Function value obtained: -81.1277\n", + "Current minimum: -85.0952\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:50:11,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3740\n", + "Function value obtained: -80.9333\n", + "Current minimum: -85.0952\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:50:21,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0352\n", + "Function value obtained: -82.5077\n", + "Current minimum: -85.0952\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:50:31,617\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1330\n", + "Function value obtained: -85.3373\n", + "Current minimum: -85.3373\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:50:41,797\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0345\n", + "Function value obtained: -83.6639\n", + "Current minimum: -85.3373\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:50:51,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5533\n", + "Function value obtained: -83.4928\n", + "Current minimum: -85.3373\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:51:02,363\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2894\n", + "Function value obtained: -81.7251\n", + "Current minimum: -85.3373\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:51:12,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5308\n", + "Function value obtained: -84.4095\n", + "Current minimum: -85.3373\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:51:23,160\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2579\n", + "Function value obtained: -83.0318\n", + "Current minimum: -85.3373\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:51:33,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2153\n", + "Function value obtained: -87.6813\n", + "Current minimum: -87.6813\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:51:43,614\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3620\n", + "Function value obtained: -84.7869\n", + "Current minimum: -87.6813\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:51:54,026\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7934\n", + "Function value obtained: -83.3213\n", + "Current minimum: -87.6813\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:52:04,799\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1173\n", + "Function value obtained: -81.0243\n", + "Current minimum: -87.6813\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:52:14,978\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0989\n", + "Function value obtained: -84.5181\n", + "Current minimum: -87.6813\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:52:25,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2763\n", + "Function value obtained: -81.5069\n", + "Current minimum: -87.6813\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:52:35,366\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7214\n", + "Function value obtained: -85.9161\n", + "Current minimum: -87.6813\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:52:46,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1385\n", + "Function value obtained: -85.9747\n", + "Current minimum: -87.6813\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:52:57,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5808\n", + "Function value obtained: -82.4476\n", + "Current minimum: -87.6813\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:53:07,799\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2523\n", + "Function value obtained: -84.2489\n", + "Current minimum: -87.6813\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:53:18,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8880\n", + "Function value obtained: -82.3852\n", + "Current minimum: -87.6813\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:53:28,979\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7186\n", + "Function value obtained: -84.4496\n", + "Current minimum: -87.6813\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:53:39,669\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2500\n", + "Function value obtained: -83.0723\n", + "Current minimum: -87.6813\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:53:49,898\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1780\n", + "Function value obtained: -84.1800\n", + "Current minimum: -87.6813\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:54:00,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5773\n", + "Function value obtained: -82.3404\n", + "Current minimum: -87.6813\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:54:10,716\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0534\n", + "Function value obtained: -84.3037\n", + "Current minimum: -87.6813\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:54:21,798\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9300\n", + "Function value obtained: -83.7342\n", + "Current minimum: -87.6813\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:54:32,705\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1280\n", + "Function value obtained: -83.7201\n", + "Current minimum: -87.6813\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:54:42,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7030\n", + "Function value obtained: -85.1614\n", + "Current minimum: -87.6813\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:54:53,543\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5661\n", + "Function value obtained: -82.2000\n", + "Current minimum: -87.6813\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:55:04,078\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3530\n", + "Function value obtained: -81.5854\n", + "Current minimum: -87.6813\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:55:15,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3942\n", + "Function value obtained: -81.9932\n", + "Current minimum: -87.6813\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:55:25,907\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4690\n", + "Function value obtained: -83.0830\n", + "Current minimum: -87.6813\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:55:36,346\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8111\n", + "Function value obtained: -83.3864\n", + "Current minimum: -87.6813\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:55:47,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9900\n", + "Function value obtained: -83.8025\n", + "Current minimum: -87.6813\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:55:58,149\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3083\n", + "Function value obtained: -85.9399\n", + "Current minimum: -87.6813\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:56:08,444\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4192\n", + "Function value obtained: -81.4979\n", + "Current minimum: -87.6813\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:56:18,851\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6227\n", + "Function value obtained: -84.4786\n", + "Current minimum: -87.6813\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:56:29,506\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4163\n", + "Function value obtained: -81.7339\n", + "Current minimum: -87.6813\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:56:39,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8384\n", + "Function value obtained: -84.2707\n", + "Current minimum: -87.6813\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:56:50,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6763\n", + "Function value obtained: -84.9098\n", + "Current minimum: -87.6813\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:57:01,519\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4021\n", + "Function value obtained: -84.8740\n", + "Current minimum: -87.6813\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:57:12,850\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5167\n", + "Function value obtained: -82.2318\n", + "Current minimum: -87.6813\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:57:24,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7558\n", + "Function value obtained: -83.3389\n", + "Current minimum: -87.6813\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:57:35,125\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3781\n", + "Function value obtained: -81.7042\n", + "Current minimum: -87.6813\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:57:46,585\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6069\n", + "Function value obtained: -84.0424\n", + "Current minimum: -87.6813\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:57:57,169\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5971\n", + "Function value obtained: -83.3943\n", + "Current minimum: -87.6813\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:58:07,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4682\n", + "Function value obtained: -81.6657\n", + "Current minimum: -87.6813\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:58:18,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8296\n", + "Function value obtained: -80.3942\n", + "Current minimum: -87.6813\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:58:29,077\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8820\n", + "Function value obtained: -84.0638\n", + "Current minimum: -87.6813\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:58:40,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7674\n", + "Function value obtained: -85.8976\n", + "Current minimum: -87.6813\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:58:50,836\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0881\n", + "Function value obtained: -83.2915\n", + "Current minimum: -87.6813\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:59:01,863\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7816\n", + "Function value obtained: -82.4830\n", + "Current minimum: -87.6813\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:59:12,630\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8340\n", + "Function value obtained: -82.3044\n", + "Current minimum: -87.6813\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:59:23,482\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0930\n", + "Function value obtained: -83.4512\n", + "Current minimum: -87.6813\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:59:34,508\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5722\n", + "Function value obtained: -81.6248\n", + "Current minimum: -87.6813\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:59:45,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4563\n", + "Function value obtained: -84.0662\n", + "Current minimum: -87.6813\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 22:59:56,572\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1103\n", + "Function value obtained: -83.8722\n", + "Current minimum: -87.6813\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:00:07,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2511\n", + "Function value obtained: -82.7655\n", + "Current minimum: -87.6813\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:00:18,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6790\n", + "Function value obtained: -83.7293\n", + "Current minimum: -87.6813\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:00:30,621\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2543\n", + "Function value obtained: -83.6100\n", + "Current minimum: -87.6813\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:00:42,002\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6022\n", + "Function value obtained: -85.6795\n", + "Current minimum: -87.6813\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:00:53,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8464\n", + "Function value obtained: -83.3303\n", + "Current minimum: -87.6813\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:01:04,437\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0150\n", + "Function value obtained: -84.7113\n", + "Current minimum: -87.6813\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:01:15,485\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0428\n", + "Function value obtained: -83.2035\n", + "Current minimum: -87.6813\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:01:27,600\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5873\n", + "Function value obtained: -84.2205\n", + "Current minimum: -87.6813\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:01:39,082\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1665\n", + "Function value obtained: -82.9162\n", + "Current minimum: -87.6813\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:01:50,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3967\n", + "Function value obtained: -84.0656\n", + "Current minimum: -87.6813\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 23:02:01,628\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1795\n", + "Function value obtained: -82.6607\n", + "Current minimum: -87.6813\n", + "CPU times: user 20min 19s, sys: 24min, total: 44min 19s\n", + "Wall time: 17min 45s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-87.68129914399789, [-0.01050109469304239])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 100, verbose=True, n_jobs=-1)\n", + "esc_gp.fun, esc_gp.x" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true, + "source_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:38,545\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 9.8552\n", + "Function value obtained: -335.4193\n", + "Current minimum: -335.4193\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:48,401\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 10.3734\n", + "Function value obtained: -0.0000\n", + "Current minimum: -335.4193\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:06:58,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 10.6599\n", + "Function value obtained: -427.5246\n", + "Current minimum: -427.5246\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:09,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 10.6912\n", + "Function value obtained: -3.8238\n", + "Current minimum: -427.5246\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:20,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.4139\n", + "Function value obtained: -60.5882\n", + "Current minimum: -427.5246\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:30,592\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 9.9004\n", + "Function value obtained: -3.1751\n", + "Current minimum: -427.5246\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:40,491\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.9277\n", + "Function value obtained: -5.4295\n", + "Current minimum: -427.5246\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:07:50,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 10.4066\n", + "Function value obtained: -37.1784\n", + "Current minimum: -427.5246\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:00,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 9.7842\n", + "Function value obtained: -6.5697\n", + "Current minimum: -427.5246\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:10,599\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.2117\n", + "Function value obtained: -3.1815\n", + "Current minimum: -427.5246\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:20,827\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2058\n", + "Function value obtained: -220.1786\n", + "Current minimum: -427.5246\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:31,016\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1665\n", + "Function value obtained: -434.8020\n", + "Current minimum: -434.8020\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:41,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6603\n", + "Function value obtained: -435.4278\n", + "Current minimum: -435.4278\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:08:51,876\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3507\n", + "Function value obtained: -432.5803\n", + "Current minimum: -435.4278\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:02,216\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7200\n", + "Function value obtained: -434.2554\n", + "Current minimum: -435.4278\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:12,862\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0872\n", + "Function value obtained: -438.5429\n", + "Current minimum: -438.5429\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:23,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0968\n", + "Function value obtained: -433.8495\n", + "Current minimum: -438.5429\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:33,164\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4912\n", + "Function value obtained: -437.4978\n", + "Current minimum: -438.5429\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:43,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6329\n", + "Function value obtained: -0.0000\n", + "Current minimum: -438.5429\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:09:54,293\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3247\n", + "Function value obtained: -433.3639\n", + "Current minimum: -438.5429\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:04,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8444\n", + "Function value obtained: -438.8648\n", + "Current minimum: -438.8648\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:15,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4880\n", + "Function value obtained: -430.0188\n", + "Current minimum: -438.8648\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:26,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1281\n", + "Function value obtained: -436.7534\n", + "Current minimum: -438.8648\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:37,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3385\n", + "Function value obtained: -412.0634\n", + "Current minimum: -438.8648\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:47,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2627\n", + "Function value obtained: -437.4297\n", + "Current minimum: -438.8648\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:10:58,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4811\n", + "Function value obtained: -435.9596\n", + "Current minimum: -438.8648\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:09,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2521\n", + "Function value obtained: -431.8186\n", + "Current minimum: -438.8648\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:19,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7418\n", + "Function value obtained: -435.4472\n", + "Current minimum: -438.8648\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:30,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5565\n", + "Function value obtained: -428.0797\n", + "Current minimum: -438.8648\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-26 22:11:40,804\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1785\n", + "Function value obtained: -436.0723\n", + "Current minimum: -438.8648\n", + "CPU times: user 34.4 s, sys: 51.8 s, total: 1min 26s\n", + "Wall time: 5min 12s\n" + ] + }, + { + "data": { + "text/plain": [ + "(-438.8647758926598, [-0.08374338090501876])" ] }, - "execution_count": 8, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "msy_gbrt = gbrt_minimize(msy_obj, msy_space, n_calls = 300, verbose=True, n_jobs=-1)\n", - "msy_gbrt.fun, msy_gbrt.x" + "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "esc_gbrt.fun, esc_gbrt.x" ] }, { "cell_type": "markdown", - "id": "9a378e12-6eda-4d47-b560-3ef2ff06bbd5", + "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", "metadata": {}, "source": [ - "### Esc" + "### CR" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", + "execution_count": 17, + "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", "metadata": { "scrolled": true }, @@ -7252,7 +4814,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:03:05,375\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:05:36,343\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7260,9 +4822,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 10.2250\n", - "Function value obtained: -68.8738\n", - "Current minimum: -68.8738\n", + "Time taken: 8.1115\n", + "Function value obtained: -7.6290\n", + "Current minimum: -7.6290\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -7270,7 +4832,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:03:15,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:05:44,548\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7278,9 +4840,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 9.8107\n", - "Function value obtained: -0.0000\n", - "Current minimum: -68.8738\n", + "Time taken: 8.9869\n", + "Function value obtained: -0.0278\n", + "Current minimum: -7.6290\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -7288,7 +4850,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:03:25,571\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:05:53,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7296,9 +4858,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 9.5427\n", - "Function value obtained: -43.5459\n", - "Current minimum: -68.8738\n", + "Time taken: 8.9109\n", + "Function value obtained: -2.9872\n", + "Current minimum: -7.6290\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -7306,7 +4868,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:03:35,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:06:02,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7314,9 +4876,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 9.9456\n", - "Function value obtained: -10.1035\n", - "Current minimum: -68.8738\n", + "Time taken: 8.8692\n", + "Function value obtained: -114.4860\n", + "Current minimum: -114.4860\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -7324,7 +4886,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:03:45,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:06:11,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7332,9 +4894,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 10.0813\n", - "Function value obtained: -8.7085\n", - "Current minimum: -68.8738\n", + "Time taken: 9.0040\n", + "Function value obtained: -1.8067\n", + "Current minimum: -114.4860\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -7342,7 +4904,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:03:55,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:06:20,252\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7350,9 +4912,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 10.6818\n", - "Function value obtained: -45.4951\n", - "Current minimum: -68.8738\n", + "Time taken: 8.9358\n", + "Function value obtained: -1.6200\n", + "Current minimum: -114.4860\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -7360,7 +4922,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:04:05,872\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:06:29,234\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7368,9 +4930,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 9.4252\n", - "Function value obtained: -26.4654\n", - "Current minimum: -68.8738\n", + "Time taken: 8.8870\n", + "Function value obtained: -22.4254\n", + "Current minimum: -114.4860\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -7378,7 +4940,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:04:15,251\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:06:38,107\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7386,9 +4948,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 9.7255\n", - "Function value obtained: -2.9836\n", - "Current minimum: -68.8738\n", + "Time taken: 9.1721\n", + "Function value obtained: -11.3443\n", + "Current minimum: -114.4860\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -7396,7 +4958,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:04:24,974\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:06:47,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7404,9 +4966,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 10.0814\n", - "Function value obtained: -0.0594\n", - "Current minimum: -68.8738\n", + "Time taken: 9.0016\n", + "Function value obtained: -0.4134\n", + "Current minimum: -114.4860\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -7414,7 +4976,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:04:35,114\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:06:56,272\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7422,9 +4984,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 10.6014\n", - "Function value obtained: -5.1890\n", - "Current minimum: -68.8738\n", + "Time taken: 9.2513\n", + "Function value obtained: -79.7388\n", + "Current minimum: -114.4860\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -7432,7 +4994,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:04:45,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:07:05,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7440,9 +5002,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9135\n", - "Function value obtained: -96.0981\n", - "Current minimum: -96.0981\n", + "Time taken: 8.5514\n", + "Function value obtained: -0.0000\n", + "Current minimum: -114.4860\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -7450,7 +5012,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:04:55,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:07:14,075\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7458,9 +5020,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0205\n", - "Function value obtained: -101.3239\n", - "Current minimum: -101.3239\n", + "Time taken: 9.1391\n", + "Function value obtained: -99.9411\n", + "Current minimum: -114.4860\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -7468,7 +5030,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:05:06,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:07:23,196\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7476,9 +5038,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3060\n", - "Function value obtained: -111.5467\n", - "Current minimum: -111.5467\n", + "Time taken: 9.1645\n", + "Function value obtained: -0.0000\n", + "Current minimum: -114.4860\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -7486,7 +5048,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:05:16,961\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:07:32,396\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7494,9 +5056,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2348\n", - "Function value obtained: -110.4850\n", - "Current minimum: -111.5467\n", + "Time taken: 9.2975\n", + "Function value obtained: -38.4953\n", + "Current minimum: -114.4860\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -7504,7 +5066,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:05:27,168\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:07:41,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7512,9 +5074,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7985\n", - "Function value obtained: -111.5378\n", - "Current minimum: -111.5467\n", + "Time taken: 9.4653\n", + "Function value obtained: -113.7155\n", + "Current minimum: -114.4860\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -7522,7 +5084,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:05:37,019\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:07:51,132\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7530,9 +5092,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1714\n", - "Function value obtained: -105.7690\n", - "Current minimum: -111.5467\n", + "Time taken: 9.2698\n", + "Function value obtained: -114.0410\n", + "Current minimum: -114.4860\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -7540,7 +5102,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:05:47,202\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:08:00,425\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7548,9 +5110,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6702\n", - "Function value obtained: -109.6503\n", - "Current minimum: -111.5467\n", + "Time taken: 9.4442\n", + "Function value obtained: -112.5988\n", + "Current minimum: -114.4860\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -7558,7 +5120,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:05:57,836\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:08:09,879\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7566,9 +5128,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1571\n", - "Function value obtained: -109.8605\n", - "Current minimum: -111.5467\n", + "Time taken: 9.7591\n", + "Function value obtained: -110.7040\n", + "Current minimum: -114.4860\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -7576,7 +5138,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:06:08,036\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:08:19,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7584,9 +5146,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5515\n", - "Function value obtained: -108.9471\n", - "Current minimum: -111.5467\n", + "Time taken: 10.1960\n", + "Function value obtained: -97.3440\n", + "Current minimum: -114.4860\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -7594,7 +5156,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:06:18,568\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:08:29,839\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7602,9 +5164,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4781\n", - "Function value obtained: -110.0320\n", - "Current minimum: -111.5467\n", + "Time taken: 9.1163\n", + "Function value obtained: -100.1929\n", + "Current minimum: -114.4860\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -7612,7 +5174,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:06:29,039\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:08:38,979\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7620,9 +5182,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4556\n", - "Function value obtained: -110.6004\n", - "Current minimum: -111.5467\n", + "Time taken: 9.7422\n", + "Function value obtained: -116.8670\n", + "Current minimum: -116.8670\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -7630,7 +5192,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:06:39,465\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:08:48,712\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7638,9 +5200,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1902\n", - "Function value obtained: -108.7321\n", - "Current minimum: -111.5467\n", + "Time taken: 9.4041\n", + "Function value obtained: -115.7852\n", + "Current minimum: -116.8670\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -7648,7 +5210,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:06:49,714\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:08:58,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -7656,9 +5218,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1862\n", - "Function value obtained: -108.6183\n", - "Current minimum: -111.5467\n", + "Time taken: 9.1661\n", + "Function value obtained: -112.5786\n", + "Current minimum: -116.8670\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -7666,1312 +5228,1415 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:06:59,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:09:07,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5259\n", + "Function value obtained: -116.7535\n", + "Current minimum: -116.8670\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:09:16,837\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0995\n", + "Function value obtained: -117.7504\n", + "Current minimum: -117.7504\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:09:25,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5610\n", + "Function value obtained: -80.7927\n", + "Current minimum: -117.7504\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:09:35,460\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7079\n", + "Function value obtained: -115.0328\n", + "Current minimum: -117.7504\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:09:45,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4450\n", + "Function value obtained: -115.6605\n", + "Current minimum: -117.7504\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:09:54,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5070\n", + "Function value obtained: -113.3710\n", + "Current minimum: -117.7504\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:10:04,202\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5401\n", + "Function value obtained: -0.0000\n", + "Current minimum: -117.7504\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:10:13,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6143\n", + "Function value obtained: -0.0000\n", + "Current minimum: -117.7504\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:10:23,446\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5379\n", - "Function value obtained: -108.0801\n", - "Current minimum: -111.5467\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5648\n", + "Function value obtained: -113.4145\n", + "Current minimum: -117.7504\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:07:10,492\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:10:32,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1486\n", - "Function value obtained: -107.2665\n", - "Current minimum: -111.5467\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6172\n", + "Function value obtained: -1.6111\n", + "Current minimum: -117.7504\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:07:21,408\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:10:42,571\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9154\n", - "Function value obtained: -110.2048\n", - "Current minimum: -111.5467\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5673\n", + "Function value obtained: -113.1052\n", + "Current minimum: -117.7504\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:07:31,987\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:10:52,090\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5671\n", - "Function value obtained: -111.3242\n", - "Current minimum: -111.5467\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0585\n", + "Function value obtained: -120.8722\n", + "Current minimum: -120.8722\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:07:42,105\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:11:01,149\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3319\n", - "Function value obtained: -111.4795\n", - "Current minimum: -111.5467\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4334\n", + "Function value obtained: -123.5789\n", + "Current minimum: -123.5789\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:07:52,528\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:11:10,627\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2865\n", - "Function value obtained: -110.5394\n", - "Current minimum: -111.5467\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7011\n", + "Function value obtained: -126.7480\n", + "Current minimum: -126.7480\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:08:02,666\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:11:20,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0351\n", - "Function value obtained: -110.2251\n", - "Current minimum: -111.5467\n", - "CPU times: user 3min 7s, sys: 4min 24s, total: 7min 31s\n", - "Wall time: 5min 7s\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5923\n", + "Function value obtained: -122.9114\n", + "Current minimum: -126.7480\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { - "data": { - "text/plain": [ - "(-111.54673721989337, [-0.4009066620757826])" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gp = gp_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", - "esc_gp.fun, esc_gp.x" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "82d02ca4-6569-42ca-91fe-dbb3bd140845", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:11:29,899\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] }, - "scrolled": true - }, - "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3993\n", + "Function value obtained: -126.0715\n", + "Current minimum: -126.7480\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:06:38,545\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:11:39,298\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 9.8552\n", - "Function value obtained: -335.4193\n", - "Current minimum: -335.4193\n", - "Iteration No: 2 started. Evaluating function at random point.\n" + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5846\n", + "Function value obtained: -1.1401\n", + "Current minimum: -126.7480\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:06:48,401\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:11:48,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 10.3734\n", - "Function value obtained: -0.0000\n", - "Current minimum: -335.4193\n", - "Iteration No: 3 started. Evaluating function at random point.\n" + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5929\n", + "Function value obtained: -124.3263\n", + "Current minimum: -126.7480\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:06:58,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:11:58,560\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 10.6599\n", - "Function value obtained: -427.5246\n", - "Current minimum: -427.5246\n", - "Iteration No: 4 started. Evaluating function at random point.\n" + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6709\n", + "Function value obtained: -111.2009\n", + "Current minimum: -126.7480\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:07:09,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:12:08,277\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 10.6912\n", - "Function value obtained: -3.8238\n", - "Current minimum: -427.5246\n", - "Iteration No: 5 started. Evaluating function at random point.\n" + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7202\n", + "Function value obtained: -121.5537\n", + "Current minimum: -126.7480\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:07:20,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:12:17,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 10.4139\n", - "Function value obtained: -60.5882\n", - "Current minimum: -427.5246\n", - "Iteration No: 6 started. Evaluating function at random point.\n" + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6736\n", + "Function value obtained: -108.7414\n", + "Current minimum: -126.7480\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:07:30,592\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:12:27,593\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 9.9004\n", - "Function value obtained: -3.1751\n", - "Current minimum: -427.5246\n", - "Iteration No: 7 started. Evaluating function at random point.\n" + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2501\n", + "Function value obtained: -0.0000\n", + "Current minimum: -126.7480\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:07:40,491\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:12:36,834\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 9.9277\n", - "Function value obtained: -5.4295\n", - "Current minimum: -427.5246\n", - "Iteration No: 8 started. Evaluating function at random point.\n" + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6360\n", + "Function value obtained: -4.1430\n", + "Current minimum: -126.7480\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:07:50,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:12:46,449\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 10.4066\n", - "Function value obtained: -37.1784\n", - "Current minimum: -427.5246\n", - "Iteration No: 9 started. Evaluating function at random point.\n" + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7744\n", + "Function value obtained: -110.3508\n", + "Current minimum: -126.7480\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:00,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:12:56,292\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 9.7842\n", - "Function value obtained: -6.5697\n", - "Current minimum: -427.5246\n", - "Iteration No: 10 started. Evaluating function at random point.\n" + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8822\n", + "Function value obtained: -106.6135\n", + "Current minimum: -126.7480\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:10,599\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:13:06,116\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 10.2117\n", - "Function value obtained: -3.1815\n", - "Current minimum: -427.5246\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8239\n", + "Function value obtained: -71.3470\n", + "Current minimum: -126.7480\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:20,827\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:13:16,010\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2058\n", - "Function value obtained: -220.1786\n", - "Current minimum: -427.5246\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8542\n", + "Function value obtained: -101.8507\n", + "Current minimum: -126.7480\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:31,016\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:13:25,879\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1665\n", - "Function value obtained: -434.8020\n", - "Current minimum: -434.8020\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1099\n", + "Function value obtained: -103.4892\n", + "Current minimum: -126.7480\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:41,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:13:35,931\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6603\n", - "Function value obtained: -435.4278\n", - "Current minimum: -435.4278\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3624\n", + "Function value obtained: -0.0000\n", + "Current minimum: -126.7480\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:08:51,876\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:13:45,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3507\n", - "Function value obtained: -432.5803\n", - "Current minimum: -435.4278\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7868\n", + "Function value obtained: -103.6936\n", + "Current minimum: -126.7480\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:02,216\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:13:55,095\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7200\n", - "Function value obtained: -434.2554\n", - "Current minimum: -435.4278\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6495\n", + "Function value obtained: -46.2318\n", + "Current minimum: -126.7480\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:12,862\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:14:04,753\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0872\n", - "Function value obtained: -438.5429\n", - "Current minimum: -438.5429\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2243\n", + "Function value obtained: -125.8399\n", + "Current minimum: -126.7480\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:23,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:14:13,969\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0968\n", - "Function value obtained: -433.8495\n", - "Current minimum: -438.5429\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8535\n", + "Function value obtained: -127.1430\n", + "Current minimum: -127.1430\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:33,164\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:14:23,819\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4912\n", - "Function value obtained: -437.4978\n", - "Current minimum: -438.5429\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7854\n", + "Function value obtained: -123.4513\n", + "Current minimum: -127.1430\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:43,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:14:33,625\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6329\n", - "Function value obtained: -0.0000\n", - "Current minimum: -438.5429\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9281\n", + "Function value obtained: -126.7540\n", + "Current minimum: -127.1430\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:09:54,293\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:14:43,629\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3247\n", - "Function value obtained: -433.3639\n", - "Current minimum: -438.5429\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0651\n", + "Function value obtained: -124.7018\n", + "Current minimum: -127.1430\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:04,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:14:52,612\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8444\n", - "Function value obtained: -438.8648\n", - "Current minimum: -438.8648\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1865\n", + "Function value obtained: -128.2840\n", + "Current minimum: -128.2840\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:15,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:15:02,851\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4880\n", - "Function value obtained: -430.0188\n", - "Current minimum: -438.8648\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6958\n", + "Function value obtained: -125.8897\n", + "Current minimum: -128.2840\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:26,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:15:12,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1281\n", - "Function value obtained: -436.7534\n", - "Current minimum: -438.8648\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5091\n", + "Function value obtained: -93.7244\n", + "Current minimum: -128.2840\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:37,108\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:15:22,020\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3385\n", - "Function value obtained: -412.0634\n", - "Current minimum: -438.8648\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8084\n", + "Function value obtained: -88.5590\n", + "Current minimum: -128.2840\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:47,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:15:31,853\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2627\n", - "Function value obtained: -437.4297\n", - "Current minimum: -438.8648\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4474\n", + "Function value obtained: -0.0000\n", + "Current minimum: -128.2840\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:10:58,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:15:41,409\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4811\n", - "Function value obtained: -435.9596\n", - "Current minimum: -438.8648\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9009\n", + "Function value obtained: -96.3448\n", + "Current minimum: -128.2840\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:09,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:15:51,245\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2521\n", - "Function value obtained: -431.8186\n", - "Current minimum: -438.8648\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9191\n", + "Function value obtained: -86.2623\n", + "Current minimum: -128.2840\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:19,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:16:01,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7418\n", - "Function value obtained: -435.4472\n", - "Current minimum: -438.8648\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9864\n", + "Function value obtained: -0.0000\n", + "Current minimum: -128.2840\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:30,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:16:11,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5565\n", - "Function value obtained: -428.0797\n", - "Current minimum: -438.8648\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6534\n", + "Function value obtained: -127.8728\n", + "Current minimum: -128.2840\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:40,804\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:16:20,796\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1785\n", - "Function value obtained: -436.0723\n", - "Current minimum: -438.8648\n", - "CPU times: user 34.4 s, sys: 51.8 s, total: 1min 26s\n", - "Wall time: 5min 12s\n" + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9080\n", + "Function value obtained: -112.3430\n", + "Current minimum: -128.2840\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" ] }, { - "data": { - "text/plain": [ - "(-438.8647758926598, [-0.08374338090501876])" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%time\n", - "esc_gbrt = gbrt_minimize(esc_obj, log_esc_space, n_calls = 30, verbose=True, n_jobs=-1)\n", - "esc_gbrt.fun, esc_gbrt.x" - ] - }, - { - "cell_type": "markdown", - "id": "015f56dc-d581-40c7-a32e-72bfb8887e4e", - "metadata": {}, - "source": [ - "### CR" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", - "metadata": { - "scrolled": true - }, - "outputs": [ + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-06 21:16:30,716\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n" + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6776\n", + "Function value obtained: -129.4016\n", + "Current minimum: -129.4016\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:08:12,828\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:16:40,395\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 10.3011\n", - "Function value obtained: -99.8134\n", - "Current minimum: -99.8134\n", - "Iteration No: 2 started. Evaluating function at random point.\n" + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9430\n", + "Function value obtained: -0.0000\n", + "Current minimum: -129.4016\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:08:23,122\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:16:50,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 10.2543\n", - "Function value obtained: -4.3723\n", - "Current minimum: -99.8134\n", - "Iteration No: 3 started. Evaluating function at random point.\n" + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1001\n", + "Function value obtained: -126.7829\n", + "Current minimum: -129.4016\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:08:33,405\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:17:00,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 10.1405\n", - "Function value obtained: -89.1873\n", - "Current minimum: -99.8134\n", - "Iteration No: 4 started. Evaluating function at random point.\n" + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0197\n", + "Function value obtained: -132.4043\n", + "Current minimum: -132.4043\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:08:43,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:17:10,468\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 10.7200\n", - "Function value obtained: -5.0205\n", - "Current minimum: -99.8134\n", - "Iteration No: 5 started. Evaluating function at random point.\n" + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6961\n", + "Function value obtained: -130.9898\n", + "Current minimum: -132.4043\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:08:54,273\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:17:20,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 10.3095\n", - "Function value obtained: -96.3897\n", - "Current minimum: -99.8134\n", - "Iteration No: 6 started. Evaluating function at random point.\n" + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6961\n", + "Function value obtained: -106.3181\n", + "Current minimum: -132.4043\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:09:04,576\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:17:29,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 9.9369\n", - "Function value obtained: -31.0103\n", - "Current minimum: -99.8134\n", - "Iteration No: 7 started. Evaluating function at random point.\n" + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1588\n", + "Function value obtained: -99.9605\n", + "Current minimum: -132.4043\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:09:14,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:17:40,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 9.7821\n", - "Function value obtained: -87.8720\n", - "Current minimum: -99.8134\n", - "Iteration No: 8 started. Evaluating function at random point.\n" + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1432\n", + "Function value obtained: -97.3045\n", + "Current minimum: -132.4043\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:09:24,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:17:50,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 10.2030\n", - "Function value obtained: -20.2042\n", - "Current minimum: -99.8134\n", - "Iteration No: 9 started. Evaluating function at random point.\n" + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0644\n", + "Function value obtained: -2.0225\n", + "Current minimum: -132.4043\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:09:34,578\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:18:00,284\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 10.1948\n", - "Function value obtained: -5.4816\n", - "Current minimum: -99.8134\n", - "Iteration No: 10 started. Evaluating function at random point.\n" + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0968\n", + "Function value obtained: -128.2107\n", + "Current minimum: -132.4043\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:09:44,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:18:10,413\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 10.1699\n", - "Function value obtained: -11.1607\n", - "Current minimum: -99.8134\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1542\n", + "Function value obtained: -129.6949\n", + "Current minimum: -132.4043\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:09:54,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:18:20,541\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4739\n", - "Function value obtained: -105.0631\n", - "Current minimum: -105.0631\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0670\n", + "Function value obtained: -96.3537\n", + "Current minimum: -132.4043\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:10:05,391\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:18:30,587\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9163\n", - "Function value obtained: -125.7116\n", - "Current minimum: -125.7116\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9939\n", + "Function value obtained: -6.0704\n", + "Current minimum: -132.4043\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:10:16,238\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:18:40,622\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2771\n", - "Function value obtained: -84.7120\n", - "Current minimum: -125.7116\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8829\n", + "Function value obtained: -0.0000\n", + "Current minimum: -132.4043\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:10:26,613\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:18:50,512\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7363\n", - "Function value obtained: -122.5362\n", - "Current minimum: -125.7116\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3976\n", + "Function value obtained: -115.1299\n", + "Current minimum: -132.4043\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:10:37,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:19:01,896\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7098\n", - "Function value obtained: -128.8377\n", - "Current minimum: -128.8377\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3103\n", + "Function value obtained: -124.1162\n", + "Current minimum: -132.4043\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:10:48,083\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:19:12,177\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1119\n", - "Function value obtained: -134.7188\n", - "Current minimum: -134.7188\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2746\n", + "Function value obtained: -92.9865\n", + "Current minimum: -132.4043\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:10:59,137\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:19:22,466\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3283\n", - "Function value obtained: -142.1377\n", - "Current minimum: -142.1377\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9574\n", + "Function value obtained: -131.7860\n", + "Current minimum: -132.4043\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:11:09,506\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:19:32,483\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5330\n", - "Function value obtained: -0.0000\n", - "Current minimum: -142.1377\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9363\n", + "Function value obtained: -130.3836\n", + "Current minimum: -132.4043\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:11:19,995\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:19:42,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1965\n", - "Function value obtained: -138.5557\n", - "Current minimum: -142.1377\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5956\n", + "Function value obtained: -132.4495\n", + "Current minimum: -132.4495\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:11:30,257\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:19:53,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6037\n", - "Function value obtained: -142.2689\n", - "Current minimum: -142.2689\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4258\n", + "Function value obtained: -132.7402\n", + "Current minimum: -132.7402\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:11:40,869\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:20:03,358\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9340\n", - "Function value obtained: -143.3762\n", - "Current minimum: -143.3762\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0293\n", + "Function value obtained: -107.4279\n", + "Current minimum: -132.7402\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:11:51,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:20:13,458\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8845\n", - "Function value obtained: -147.0960\n", - "Current minimum: -147.0960\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2054\n", + "Function value obtained: -131.8842\n", + "Current minimum: -132.7402\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:12:02,629\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:20:23,719\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2859\n", - "Function value obtained: -148.8915\n", - "Current minimum: -148.8915\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4196\n", + "Function value obtained: -125.2470\n", + "Current minimum: -132.7402\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:12:12,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:20:34,081\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3438\n", - "Function value obtained: -147.6152\n", - "Current minimum: -148.8915\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3703\n", + "Function value obtained: -128.0604\n", + "Current minimum: -132.7402\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:12:23,310\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:20:44,500\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4375\n", - "Function value obtained: -145.7412\n", - "Current minimum: -148.8915\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6884\n", + "Function value obtained: -112.6622\n", + "Current minimum: -132.7402\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:12:33,745\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:20:55,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4064\n", - "Function value obtained: -147.5697\n", - "Current minimum: -148.8915\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3170\n", + "Function value obtained: -115.6452\n", + "Current minimum: -132.7402\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:12:44,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:21:05,539\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1361\n", - "Function value obtained: -141.3143\n", - "Current minimum: -148.8915\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7750\n", + "Function value obtained: -10.3103\n", + "Current minimum: -132.7402\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:12:55,323\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:21:16,247\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8591\n", - "Function value obtained: -124.4355\n", - "Current minimum: -148.8915\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2461\n", + "Function value obtained: -114.9304\n", + "Current minimum: -132.7402\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:13:06,167\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:21:26,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1335\n", - "Function value obtained: -143.9636\n", - "Current minimum: -148.8915\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1882\n", + "Function value obtained: -111.3750\n", + "Current minimum: -132.7402\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-04 00:13:17,380\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:21:36,735\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5822\n", - "Function value obtained: -45.8358\n", - "Current minimum: -148.8915\n", - "CPU times: user 3min 9s, sys: 4min 44s, total: 7min 54s\n", - "Wall time: 5min 14s\n" + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7355\n", + "Function value obtained: -124.6877\n", + "Current minimum: -132.7402\n", + "CPU times: user 26min 12s, sys: 22min 45s, total: 48min 58s\n", + "Wall time: 16min 10s\n" ] }, { "data": { "text/plain": [ - "(-148.89152376228486, [0.0, 0.0, 0.13207767948328275])" + "(-132.7401767704845, [0.9991043655916663, 0.0, 0.3647240347805972])" ] }, - "execution_count": 8, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 100, verbose=True, n_jobs=-1)\n", "cr_gp.fun, cr_gp.x" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, "id": "04bccbfe-6ad1-4db4-8e58-c773c3ceeb7e", "metadata": { "collapsed": true, "jupyter": { - "outputs_hidden": true + "outputs_hidden": true, + "source_hidden": true }, "scrolled": true }, @@ -8987,7 +6652,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:11:51,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 20:59:36,218\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -8995,9 +6660,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 10.3604\n", - "Function value obtained: -204.8880\n", - "Current minimum: -204.8880\n", + "Time taken: 8.0076\n", + "Function value obtained: -7.6151\n", + "Current minimum: -7.6151\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -9005,7 +6670,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:12:01,442\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 20:59:44,233\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9013,9 +6678,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 10.9740\n", - "Function value obtained: -366.4789\n", - "Current minimum: -366.4789\n", + "Time taken: 8.7556\n", + "Function value obtained: -2.1105\n", + "Current minimum: -7.6151\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -9023,7 +6688,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:12:12,420\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 20:59:53,004\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9031,9 +6696,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 10.0220\n", - "Function value obtained: -410.2703\n", - "Current minimum: -410.2703\n", + "Time taken: 8.6924\n", + "Function value obtained: -4.8491\n", + "Current minimum: -7.6151\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -9041,7 +6706,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:12:22,444\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:02,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9049,9 +6714,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 10.9982\n", - "Function value obtained: -24.3890\n", - "Current minimum: -410.2703\n", + "Time taken: 9.1699\n", + "Function value obtained: -32.5008\n", + "Current minimum: -32.5008\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -9059,7 +6724,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:12:33,378\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:10,872\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9067,9 +6732,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 10.2479\n", - "Function value obtained: -354.9929\n", - "Current minimum: -410.2703\n", + "Time taken: 7.9775\n", + "Function value obtained: -26.0639\n", + "Current minimum: -32.5008\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -9077,7 +6742,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:12:43,724\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:18,855\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9085,9 +6750,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 11.0869\n", - "Function value obtained: -282.0534\n", - "Current minimum: -410.2703\n", + "Time taken: 8.7016\n", + "Function value obtained: -3.7636\n", + "Current minimum: -32.5008\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -9095,7 +6760,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:12:54,778\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:27,530\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9103,9 +6768,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 10.7217\n", - "Function value obtained: -409.6809\n", - "Current minimum: -410.2703\n", + "Time taken: 7.8543\n", + "Function value obtained: -2.5356\n", + "Current minimum: -32.5008\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -9113,7 +6778,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:13:05,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:35,490\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9121,9 +6786,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 11.0860\n", - "Function value obtained: -370.5645\n", - "Current minimum: -410.2703\n", + "Time taken: 8.0558\n", + "Function value obtained: -73.9101\n", + "Current minimum: -73.9101\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -9131,7 +6796,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:13:16,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:43,520\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9139,9 +6804,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 11.4416\n", - "Function value obtained: -399.4599\n", - "Current minimum: -410.2703\n", + "Time taken: 8.0379\n", + "Function value obtained: -23.1672\n", + "Current minimum: -73.9101\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -9149,7 +6814,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:13:27,993\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:51,500\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9157,9 +6822,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 14.8176\n", - "Function value obtained: -165.9382\n", - "Current minimum: -410.2703\n", + "Time taken: 8.2103\n", + "Function value obtained: -2.8659\n", + "Current minimum: -73.9101\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -9167,7 +6832,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:13:42,871\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:00:59,723\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9175,9 +6840,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4239\n", - "Function value obtained: -417.1804\n", - "Current minimum: -417.1804\n", + "Time taken: 8.2680\n", + "Function value obtained: -0.0000\n", + "Current minimum: -73.9101\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -9185,7 +6850,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:13:54,279\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:01:07,995\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9193,9 +6858,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5685\n", - "Function value obtained: -18.8272\n", - "Current minimum: -417.1804\n", + "Time taken: 8.5733\n", + "Function value obtained: -54.4296\n", + "Current minimum: -73.9101\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -9203,7 +6868,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:14:05,864\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:01:16,589\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9211,9 +6876,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4953\n", - "Function value obtained: -415.8945\n", - "Current minimum: -417.1804\n", + "Time taken: 8.9145\n", + "Function value obtained: -0.0000\n", + "Current minimum: -73.9101\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -9221,7 +6886,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:14:18,451\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:01:25,505\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9229,9 +6894,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1344\n", - "Function value obtained: -411.5031\n", - "Current minimum: -417.1804\n", + "Time taken: 8.5797\n", + "Function value obtained: -0.0000\n", + "Current minimum: -73.9101\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -9239,7 +6904,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:14:30,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:01:34,012\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9247,9 +6912,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6181\n", - "Function value obtained: -341.4892\n", - "Current minimum: -417.1804\n", + "Time taken: 8.5551\n", + "Function value obtained: -74.3119\n", + "Current minimum: -74.3119\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -9257,7 +6922,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:14:42,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:01:42,627\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9265,9 +6930,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5405\n", - "Function value obtained: -411.7262\n", - "Current minimum: -417.1804\n", + "Time taken: 8.1481\n", + "Function value obtained: -73.9939\n", + "Current minimum: -74.3119\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -9275,7 +6940,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:14:54,660\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:01:50,803\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9283,9 +6948,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4247\n", - "Function value obtained: -424.1434\n", - "Current minimum: -424.1434\n", + "Time taken: 8.5273\n", + "Function value obtained: -0.0000\n", + "Current minimum: -74.3119\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -9293,7 +6958,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:15:07,143\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:01:59,324\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9301,9 +6966,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6295\n", - "Function value obtained: -427.8426\n", - "Current minimum: -427.8426\n", + "Time taken: 8.1950\n", + "Function value obtained: -73.2760\n", + "Current minimum: -74.3119\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -9311,7 +6976,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:15:19,767\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:02:07,512\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9319,9 +6984,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3900\n", - "Function value obtained: -414.4530\n", - "Current minimum: -427.8426\n", + "Time taken: 8.5854\n", + "Function value obtained: -77.2326\n", + "Current minimum: -77.2326\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -9329,7 +6994,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:15:31,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:02:17,120\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9337,9 +7002,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4676\n", - "Function value obtained: -432.9289\n", - "Current minimum: -432.9289\n", + "Time taken: 9.1798\n", + "Function value obtained: -97.3001\n", + "Current minimum: -97.3001\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -9347,7 +7012,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:15:42,588\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:02:25,318\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9355,9 +7020,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7375\n", - "Function value obtained: -427.3274\n", - "Current minimum: -432.9289\n", + "Time taken: 9.3999\n", + "Function value obtained: -75.2733\n", + "Current minimum: -97.3001\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -9365,7 +7030,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:15:53,318\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:02:34,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9373,9 +7038,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7837\n", - "Function value obtained: -418.1603\n", - "Current minimum: -432.9289\n", + "Time taken: 8.3813\n", + "Function value obtained: -103.3574\n", + "Current minimum: -103.3574\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -9383,7 +7048,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:16:04,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:02:43,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9391,9 +7056,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5257\n", - "Function value obtained: -434.0414\n", - "Current minimum: -434.0414\n", + "Time taken: 8.4427\n", + "Function value obtained: -0.0000\n", + "Current minimum: -103.3574\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -9401,7 +7066,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:16:14,643\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:02:51,535\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9409,9 +7074,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8756\n", - "Function value obtained: -436.0045\n", - "Current minimum: -436.0045\n", + "Time taken: 9.0357\n", + "Function value obtained: -105.3841\n", + "Current minimum: -105.3841\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -9419,7 +7084,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:16:26,573\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:03:00,594\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9427,9 +7092,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0482\n", - "Function value obtained: -426.7072\n", - "Current minimum: -436.0045\n", + "Time taken: 9.2495\n", + "Function value obtained: -90.3753\n", + "Current minimum: -105.3841\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -9437,7 +7102,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:16:37,552\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:03:09,822\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9445,9 +7110,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1580\n", - "Function value obtained: -436.8424\n", - "Current minimum: -436.8424\n", + "Time taken: 9.6097\n", + "Function value obtained: -105.9809\n", + "Current minimum: -105.9809\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -9455,7 +7120,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:16:48,779\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:03:19,466\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9463,9 +7128,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6512\n", - "Function value obtained: -440.6005\n", - "Current minimum: -440.6005\n", + "Time taken: 9.2575\n", + "Function value obtained: -105.2077\n", + "Current minimum: -105.9809\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -9473,7 +7138,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:17:00,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:03:28,666\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9481,9 +7146,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1795\n", - "Function value obtained: -435.5124\n", - "Current minimum: -440.6005\n", + "Time taken: 8.3588\n", + "Function value obtained: -6.1640\n", + "Current minimum: -105.9809\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -9491,7 +7156,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:17:11,681\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:03:37,045\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9499,9 +7164,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9372\n", - "Function value obtained: -0.0000\n", - "Current minimum: -440.6005\n", + "Time taken: 9.3041\n", + "Function value obtained: -105.1358\n", + "Current minimum: -105.9809\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -9509,7 +7174,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-26 22:17:23,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-06 21:03:46,383\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -9517,20 +7182,21 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4215\n", - "Function value obtained: -412.5347\n", - "Current minimum: -440.6005\n", - "CPU times: user 3min 17s, sys: 5min 45s, total: 9min 3s\n", - "Wall time: 5min 43s\n" + "Time taken: 9.1853\n", + "Function value obtained: -104.3392\n", + "Current minimum: -105.9809\n", + "CPU times: user 2min 59s, sys: 4min 28s, total: 7min 27s\n", + "Wall time: 4min 19s\n" ] }, { "data": { "text/plain": [ - "(-440.6004877953126, [0.0, 0.7853961999069485, 0.2264118934036974])" + "(-105.98093310643762,\n", + " [-0.18399347174637892, 0.0872639874320283, 0.019982143201265623])" ] }, - "execution_count": 11, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -9541,6 +7207,37 @@ "cr_gbrt.fun, cr_gbrt.x" ] }, + { + "cell_type": "code", + "execution_count": 33, + "id": "1abcccf2-89f9-497d-ac43-1af009a637ef", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(msy_gp)" + ] + }, { "cell_type": "markdown", "id": "2c5e685e-7117-4b21-a7a5-3c975fe3acf8", @@ -9551,7 +7248,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 21, "id": "6a61d3fa-97a9-4274-945c-be2742d1e956", "metadata": {}, "outputs": [], @@ -9572,7 +7269,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 29, "id": "b86effb9-d8ad-4b50-8174-ea76dcd60c32", "metadata": { "scrolled": true @@ -9585,13 +7282,13 @@ "cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", "cr_gp_args['y2'] = cr_gp_preargs['y2']\n", "\n", - "# cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", - "# cr_gbrt_args = {}\n", - "# cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", - "# cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", - "# cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", + "cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", + "cr_gbrt_args = {}\n", + "cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", + "cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", "\n", - "msy_gp_args = {'mortality': msy_gp.x[0]}\n", + "# msy_gp_args = {'mortality': msy_gp.x[0]}\n", "# msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", "\n", "esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", @@ -9609,7 +7306,7 @@ "\n", "env = AsmEnv(config=CONFIG)\n", "\n", - "# cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", + "cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", "cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))\n", "\n", "# esc_gbrt_df = get_policy_df(ConstEsc(env, **esc_gbrt_args))\n", @@ -9621,7 +7318,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 30, "id": "88d5b45d-eeed-4321-9e9d-1a58ba63e84c", "metadata": {}, "outputs": [ @@ -9632,13 +7329,13 @@ " )" ] }, - "execution_count": 13, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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QhPXr1wuurq6CTCZTuzS0ust4s7OzhdDQUMHKykqQy+WCh4dHlUuHH17W/Omnn1bZT/zr0tYbN24Ir7zyimBhYSGYm5sLw4YNEzIzM6uMe3hZc25u7iN/hrdu3RJkMpnQrl27R475t4eX1qakpFR5TKFQCG5uboKbm5tQWVkpCIIgbNq0SXB1dRXkcrng7e0t7Nmzp0aXNQvCg5/dlClTBEdHR0FfX1+ws7MT+vbtK6xbt65GWSsrK4WYmBjhhRdeEJo3by7o6ekJVlZWQt++fYWoqKgqlwIDEKZMmVLjn8U/9e7dW3B3dxeOHDkidO/eXTA0NBScnJyE1atXVxlbk9+Jh3ked1nzQz///LPQo0cPwcjISDAzMxP8/PyErVu3VtlecnKyAEDo379/rfaRSFMSQaiHY5lE1OTk5eXB3t4eCxYswPz588WO06j16dMHeXl5NT4hXAzHjx+Ht7c3NmzYgDFjxogdh5oAnsNCRHUiNjYWCoWCb15NxPr162FiYoJXX31V7CjURPAcFiJ6Kn/88QfOnDmDjz/+GEOGDKnR9/pQ4/XLL7/gzJkzWLduHaZOnVpnX4BJ9CT8SIiInkqfPn1w6NAh9OzZE5s2barVdweROm3+SMjZ2RnZ2dkIDAzExo0bNT7Zm6i2WFiIiIhI6/EcFiIiItJ6LCxERESk9XTipFulUonMzEyYmpryy7eIiIgaCUEQcO/ePTg4ODzxS0F1orBkZmbC0dFR7BhERERUCxkZGWjVqtVjx+hEYXl4lnpGRgbMzMxETkNEREQ1UVhYCEdHxxpdbaYTheXhx0BmZmYsLERERI1MTU7n4Em3REREpPVYWIiIiEjrsbAQERGR1tOJc1hqSqFQoKKiQuwYRNDX14dMJhM7BhFRo9EkCosgCMjKykJ+fr7YUYhULCwsYGdnx7mDiIhqoEkUlodlxcbGBs2aNeMbBIlKEASUlJQgJycHAGBvby9yIiIi7afzhUWhUKjKSosWLcSOQwQAMDIyAgDk5OTAxsaGHw8RET2Bzp90+/CclWbNmomchEjdw99JnldFRPRkOl9YHuLHQKRt+DtJRFRzTaawEBERUePFwqLFBEHA+PHj0bx5c0gkElhYWGDGjBk1WrdPnz5PHCuRSPDjjz8+dU5dExISgiFDhqju1+RnSURE9UvnT7ptzOLj4xEbG4v9+/fD1dUVUqlUdbJmXbh16xYsLS3rbHvapk+fPvD29kZkZORTbWfHjh3Q19dX3Xd2dsaMGTNYYoiIGhALixa7fPky7O3t0aNHj3rZvp2dXb1sV2zl5eWQy+V1tr3mzZvX2baIGkp+STmKyirFjkE6ppWleBewsLBoqZCQEMTFxQF48NGNk5MTnJ2d1Y4YfPHFF/jss8+QkZEBc3NzPPfcc/juu+9U21AqlZgzZw6++uoryOVyTJw4EYsWLVI9LpFI8MMPP2DIkCG4du0aXFxc8P3332PVqlVISkpC27ZtERUVhe7du6vWWb9+PT744APcvn0bgYGBeO655/DBBx/UaFK+RYsW4ccff8Rbb72FRYsW4c6dOwgKCsKqVauwfPlyrFixAkqlEtOnT8d7772nWi89PR3Tpk1DQkICpFIpBgwYgFWrVsHW1lZtu1OnTsXHH3+M69evIygoCAcOHMCBAwfw+eefAwCuXr0KR0dHjB8/Hn/88QeysrLQunVrTJ48GdOnT39k7n8eqenTpw+uX7+OmTNnYubMmQCAoqIi2NvbIzo6GkOHDlWt9+OPP2L06NHIysqq0VenE9WF4rJKLI0/hw2Hr0MQxE5DukSuJ8WFjwaK9vxNsrAIgoD7FQpRnttIX1ajq0M+//xzuLm5Yd26dUhJSYFMJsOwYcNUjx85cgRvvfUWNm7ciB49euDOnTv43//+p7aNuLg4hIeHIykpCYmJiQgJCUHPnj3Rr1+/Rz7ve++9h2XLlqFt27Z47733MGrUKFy6dAl6eno4ePAgJk6ciCVLluA///kPfv/9d8yfP1+j/b98+TJ2796N+Ph4XL58GUOHDsWVK1fQrl07HDhwAIcOHUJYWBgCAgLg7+8PpVKJwYMHw8TEBAcOHEBlZSWmTJmCESNGYP/+/artXrp0Cd9//z127NgBmUwGJycnXLhwAZ07d8YHH3wAALC2toZSqUSrVq3w7bffokWLFjh06BDGjx8Pe3t7DB8+/In5d+zYAS8vL4wfPx5vvvkmAMDY2BgjR45ETEyMWmF5eJ9lhRrKoUt5eGfHCWTcuQ8AMNDjaYpUd+Qi/z41ycJyv0KBTgv2iPLcZz4IRDP5k3/s5ubmMDU1hUwmq/ajm/T0dBgbG+Pll1+GqakpnJyc0KVLF7Uxnp6eWLhwIQCgbdu2WL16NRISEh5bWGbNmoWXXnoJAPD+++/D3d0dly5dQocOHbBq1SoMHDgQs2bNAgC0a9cOhw4dws6dO2u8/0qlEtHR0TA1NUWnTp3w/PPP4/z589i1axekUinat2+PJUuWYN++ffD390dCQgJOnjypOjoCABs2bIC7uztSUlLg6+sL4MHHQBs2bIC1tbXqueRyOZo1a6b285PJZHj//fdV911cXJCYmIhvvvmmRoWlefPmkMlkMDU1VdvuuHHj0KNHD9y6dQv29vbIycnBrl278Pvvv9f4Z0P0NDYnXcd7P5wCALS0MMLi1zzwXFvrJ6xF1HiwfjdS/fr1g5OTE1xdXTFmzBhs3rwZJSUlamM8PT3V7j98I32cf67zcMr4h+ucP38efn5+auP/ff9JnJ2d1Y442NraolOnTpBKpWrLHj7n2bNn4ejoqCorANCpUydYWFjg7NmzqmVOTk5qZeVx1qxZg27dusHa2homJiZYt24d0tPTNdqPf/Pz84O7u7vqY7xNmzbByckJvXr1eqrtEtVE/KkszP/xQVkZ4eOIPTN7sayQzmmSR1iM9GU480GgaM9dF0xNTZGWlob9+/fjt99+w4IFC7Bo0SKkpKTAwsICANSubAEenLOiVCofu91/rvPwo6snraOJ6jLVJue/GRsb12jctm3bMGvWLCxfvhzdu3eHqakpPv30UyQlJWn0fNUZN24c1qxZg7lz5yImJgahoaGcHI7qXcq1O3hr21EoBWCUnyM+ecWDv3ekk5pkYZFIJDX6WEbb6enpISAgAAEBAVi4cCEsLCzwxx9/4NVXX62X52vfvj1SUlLUlv37fl3r2LEjMjIykJGRoTrKcubMGeTn56NTp06PXVcul0OhUD9X6eDBg+jRowcmT56sWnb58mWNMlW3XQB44403MGfOHKxcuRJnzpxBcHCwRtsl0tSF7HsYG5uC8kolAjra4sPBnVlWSGfxI6FGaufOnVi5ciWOHTuG69evY8OGDVAqlWjfvn29Pee0adOwa9curFixAhcvXsSXX36J3bt31+sLZEBAADw8PDB69GikpaUhOTkZQUFB6N27N3x8fB67rrOzM5KSknDt2jXk5eVBqVSibdu2OHLkCPbs2YMLFy5g/vz5GpcuZ2dn/Pnnn7h58yby8vJUyy0tLfHqq69i9uzZ6N+/P1q1alWrfSaqiVsF9xEcnYzC0kp0bW2BVaO6QE/Gl3TSXfztbqQsLCywY8cOvPDCC+jYsSOioqKwdetWuLu719tz9uzZE1FRUVixYgW8vLwQHx+PmTNnwtDQsN6eUyKR4KeffoKlpSV69eqFgIAAuLq6Yvv27U9cd9asWZDJZOjUqROsra2Rnp6OCRMm4NVXX8WIESPg7++P27dvqx1tqYkPPvgA165dg5ubW5XzZsaOHYvy8nKEhYVptE0iTRSUVCA4Ohm3CkrhZm2Mr4N9YSTnN36TbpMIQuO/Ur+wsBDm5uYoKCiAmZmZ2mOlpaW4evUqXFxc6vWNtal68803ce7cuSqXVDdVGzduxMyZM5GZmfnEyev4u0m1UVqhQNDXyUi+dge2Zgb4flIPUSfzInoaj3v//rfGfyIHNahly5ahX79+MDY2xu7duxEXF4cvvvhC7FiiKykpwa1bt7B48WJMmDChTmfaJXpIoRQwY9sxJF+7A1MDPcSG+rGsUJNRq4+E1qxZA2dnZxgaGsLf3x/JycmPHLtjxw74+PjAwsICxsbG8Pb2xsaNG9XGhISEQCKRqN0GDBhQm2hUz5KTk9GvXz94eHggKioKK1euxLhx4wAA7u7uMDExqfa2efNmkZPXr6VLl6JDhw6ws7PDvHnzxI5DOkgQBCz6+TTiT2dBLpNiXZAPOto//l+kRLpE4yMs27dvR3h4OKKiouDv74/IyEgEBgbi/PnzsLGxqTK+efPmeO+999ChQwfI5XLs3LkToaGhsLGxQWDg35cWDxgwADExMar7BgYGtdwlqk/ffPPNIx/btWsXKioqqn3s4TT6umrRokVqX3tAVNe+2H8ZGw9fh0QCfDbCG93dWogdiahBaVxYVqxYgTfffBOhoaEAgKioKPz666+Ijo7G3Llzq4zv06eP2v3p06cjLi4Of/31l1phMTAw0Nkv42sqnJycxI5ApJO+OZKBT/ecBwAsfLkTXvK0FzkRUcPT6COh8vJypKamIiAg4O8NSKUICAhAYmLiE9cXBAEJCQk4f/58lRlA9+/fDxsbG7Rv3x6TJk3C7du3H7mdsrIyFBYWqt2IiHTRH+eyMW/HSQDApD5uCOnpInIiInFodIQlLy8PCoWiyuF9W1tbnDt37pHrFRQUoGXLligrK4NMJsMXX3yh9n02AwYMwKuvvgoXFxdcvnwZ7777LgYOHIjExETIZFUv1YuIiFD7PpiaqMvZWonqAn8n6UmOpt/FlM1HoVAKeLVrS8wJrL95loi0XYNcJWRqaopjx46hqKgICQkJCA8Ph6urq+rjopEjR6rGenh4wNPTE25ubti/fz/69u1bZXvz5s1DeHi46n5hYaHad838k1wuh1QqRWZmJqytrSGXyzkTJIlKEASUl5cjNzcXUqmUVxRRta7kFiEsNgX3KxTo1c4aS17z5GsXNWkaFRYrKyvIZDJkZ2erLc/Ozn7s+SdSqRRt2rQBAHh7e+Ps2bOIiIiocn7LQ66urrCyssKlS5eqLSwGBgY1PilXKpXCxcUFt27dQmZmZo3WIWoIzZo1Q+vWrdW++JEIAHLulSIoOhl3Syrg2coca0d3hT5nsaUmTqPCIpfL0a1bNyQkJGDIkCEAHhzWTkhIwNSpU2u8HaVSibKyskc+fuPGDdy+fVv1bcFPSy6Xo3Xr1qisrKz2O2CIGppMJoOenh7/xUxV3CutQEh0Cm7cvQ+nFs0QHeILYwNOmUWk8d+C8PBwBAcHw8fHB35+foiMjERxcbHqqqGgoCC0bNkSERERAB6cb+Lj4wM3NzeUlZVh165d2LhxI9auXQsAKCoqwvvvv4/XXnsNdnZ2uHz5MubMmYM2bdqoXUX0tB5+K/C/vxmYiEhblFcqMXFTKs7cKoSViRwbwvxgZcIpHoiAWhSWESNGIDc3FwsWLEBWVha8vb0RHx+vOhE3PT1d7RB3cXExJk+ejBs3bsDIyAgdOnTApk2bMGLECAAP/qV54sQJxMXFIT8/Hw4ODujfvz8+/PBDzsVCRE2GUilg1rfHcfDSbRjLZYgJ8YNTC2OxYxFpDZ3/LiEiosbgo51n8NVfV6EnlSA6xBe92lk/eSWiRk6T92+exUVEJLL1f17BV39dBQB8OsyTZYWoGiwsREQi+unYTXy86ywAYN7ADnilSyuRExFpJxYWIiKR/O9iLmZ9exwAENbTBeN7uYqciEh7sbAQEYng1M0CTNyYigqFgJc97fHflzryMneix2BhISJqYOm3SxASk4LicgW6u7bA8uFekEpZVogeh4WFiKgB3S4qQ1B0EvKKytDR3gxfBnWDgV7V70wjInUsLEREDaS4rBJhsSm4drsELS2MEBfqCzNDTmZJVBMsLEREDaBCocSULWk4fqMAls30sWGsH2zMDMWORdRosLAQEdUzQRAw9/uT2H8+F4b6Unwd4gs3axOxYxE1KiwsRET1bNlv5/F92g3IpBKseb0rura2FDsSUaPDwkJEVI/iDl3Dmn2XAQCfvNIZfTvaipyIqHFiYSEiqie7Tt7Col9OAwDe7tcOI3xbi5yIqPFiYSEiqgeHr9zGjG3HIAjAaP/WmPpCG7EjETVqLCxERHXsXFYh3txwBOUKJfp3ssUHgztzFluip8TCQkRUh27m30dIdArulVbCx8kSK0d1gYyz2BI9NRYWIqI6kl9SjuDoZGQVlqKtjQm+CvaBoT5nsSWqCywsRER1oLRCgbFxR3Appwh2ZoaIC/ODRTO52LGIdAYLCxHRU6pUKDFt61GkXr8LM0M9xIX5wcHCSOxYRDqFhYWI6CkIgoD5P53G3jPZkOtJsT7IB+3tTMWORaRzWFiIiJ7CyoRL2JqcDokEWDnSG/6uLcSORKSTWFiIiGppW3I6Pvv9AgDgg/+4Y0Bne5ETEekuFhYiolrYeyYb7/5wEgAw9fk2GNPdWdxARDqOhYWISEOp1+9i2tY0KAVguE8rvN2/ndiRiHQeCwsRkQYu5RRhbFwKSiuUeL69NT5+xYOz2BI1ABYWIqIayi4sRXB0MvJLKuDlaIE1o7tCX8aXUaKGwL9pREQ1UFhageDoZNzMvw8XK2NEB/ugmVxP7FhETQYLCxHRE5RVKjB+wxGcy7oHa1MDbAjzQwsTA7FjETUpLCxERI+hVAoI/+Y4Dl+5AxMDPcSE+MKxeTOxYxE1OSwsRESPIAgCPth5Br+euAV9mQRfjumGzi3NxY5F1CSxsBARPcKXf15B7KFrAIBlw7zQs42VuIGImjAWFiKiauxIu4HFu88BAP77UkcM9m4pciKipo2FhYjoXw5cyMWc704AAN58zgXjnnMVORERsbAQEf3DiRv5mLQpFZVKAYO9HTBvYEexIxERWFiIiFSu5RUjNCYFJeUKPNvGCp8O9YJUyllsibQBCwsREYDce2UIjknG7eJyuDuYIWpMN8j1+BJJpC1q9bdxzZo1cHZ2hqGhIfz9/ZGcnPzIsTt27ICPjw8sLCxgbGwMb29vbNy4UW2MIAhYsGAB7O3tYWRkhICAAFy8eLE20YiINFZcVomw2BRcv10Cx+ZGiAn1hYkBZ7El0iYaF5bt27cjPDwcCxcuRFpaGry8vBAYGIicnJxqxzdv3hzvvfceEhMTceLECYSGhiI0NBR79uxRjVm6dClWrlyJqKgoJCUlwdjYGIGBgSgtLa39nhER1UB5pRITN6Xi5M0CNDeWY0OYP2xMDcWORUT/IhEEQdBkBX9/f/j6+mL16tUAAKVSCUdHR0ybNg1z586t0Ta6du2Kl156CR9++CEEQYCDgwPefvttzJo1CwBQUFAAW1tbxMbGYuTIkU/cXmFhIczNzVFQUAAzMzNNdoeImjClUsDb3x7HD0dvwkhfhq3jn4G3o4XYsYiaDE3evzU6wlJeXo7U1FQEBAT8vQGpFAEBAUhMTHzi+oIgICEhAefPn0evXr0AAFevXkVWVpbaNs3NzeHv71+jbRIR1daSPefww9GbkEkl+OKNriwrRFpMow9p8/LyoFAoYGtrq7bc1tYW586de+R6BQUFaNmyJcrKyiCTyfDFF1+gX79+AICsrCzVNv69zYeP/VtZWRnKyspU9wsLCzXZDSIiRP91FV8euAIAWPyqB55vbyNyIiJ6nAY5q8zU1BTHjh1DUVEREhISEB4eDldXV/Tp06dW24uIiMD7779ftyGJqMn45XgmPvz1DABgdmB7DPNxFDkRET2JRh8JWVlZQSaTITs7W215dnY27OzsHv0kUinatGkDb29vvP322xg6dCgiIiIAQLWeJtucN28eCgoKVLeMjAxNdoOImrBDl/Pw9jfHIQhAcHcnTO7jJnYkIqoBjQqLXC5Ht27dkJCQoFqmVCqRkJCA7t2713g7SqVS9ZGOi4sL7Ozs1LZZWFiIpKSkR27TwMAAZmZmajcioic5k1mICRtSUa5Q4kUPOywY5A6JhBPDETUGGn8kFB4ejuDgYPj4+MDPzw+RkZEoLi5GaGgoACAoKAgtW7ZUHUGJiIiAj48P3NzcUFZWhl27dmHjxo1Yu3YtAEAikWDGjBn46KOP0LZtW7i4uGD+/PlwcHDAkCFD6m5PiahJy7hTgpCYZNwrq4SfS3OsGO4NGWexJWo0NC4sI0aMQG5uLhYsWICsrCx4e3sjPj5eddJseno6pNK/D9wUFxdj8uTJuHHjBoyMjNChQwds2rQJI0aMUI2ZM2cOiouLMX78eOTn5+PZZ59FfHw8DA05FwIRPb27xeUIjklGzr0ytLc1xfogHxjqy8SORUQa0HgeFm3EeViI6FHulyvw+leHcTQ9Hw7mhvh+cg/YmxuJHYuIUI/zsBARNSaVCiWmbknD0fR8mBvpIy7Mj2WFqJFiYSEinSQIAv774ykknMuBgZ4UXwf7oK2tqdixiKiWWFiISCd99vtFbEvJgFQCrBzVBT7OzcWORERPgYWFiHTO5qTrWJnw4BvfPxzSGYHuj54niogaBxYWItIpe05nYf6PpwAAb/Vti9H+TiInIqK6wMJCRDoj5dodvLX1KJQCMNLXETMD2oodiYjqCAsLEemEi9n3MDY2BWWVSgR0tMFHQzpzFlsiHcLCQkSN3q2C+wiOTkZhaSW6trbAqlFdoSfjyxuRLuHfaCJq1AruVyAkOgWZBaVwtTbG18G+MJJzFlsiXcPCQkSNVmmFAm9uOILz2fdgY2qADWF+sDSWix2LiOoBCwsRNUoKpYCZ248h+eodmBroITbUD60sm4kdi4jqCQsLETU6giDg/V9OY/epLMhlUnwZ1A2dHPg9YkS6jIWFiBqdL/ZfxobE65BIgBUjvNDDzUrsSERUz1hYiKhR+fZIBj7dcx4AsODlTnjZ00HkRETUEFhYiKjR2HcuB3N3nAQATOzthtCeLiInIqKGwsJCRI3CsYx8TN6cBoVSwKtdWuKdAe3FjkREDYiFhYi03pXcIoTFpuB+hQK92lljyVBPzmJL1MSwsBCRVsu5V4rgmGTcKS6HZytzrB3dFfqcxZaoyeHfeiLSWvdKKxAak4KMO/fh1KIZokN8YWygJ3YsIhIBCwsRaaXySiUmbkrF6cxCWJnIsSHMD1YmBmLHIiKRsLAQkdZRKgXM/u44Dl66jWZyGaJDfOHUwljsWEQkIhYWItI6EbvP4qdjmdCTSrD2jW7wbGUhdiQiEhkLCxFpla/+dwXr/3cVALB0qCd6t7MWORERaQMWFiLSGj8du4mPfj0LAJg7sANe7dpK5EREpC1YWIhIK/x1MQ+zvj0OAAjt6YwJvVxFTkRE2oSFhYhEd+pmASZsPIIKhYCXPO0x/6VOnBiOiNSwsBCRqDLulCAkJgXF5Qp0d22BFcO9IJWyrBCROhYWIhLN7aIyBEUnI6+oDB3sTPFlUDcY6MnEjkVEWoiFhYhEUVJeibC4I7iaV4yWFkaIC/ODmaG+2LGISEuxsBBRg6tQKDFlcxqOZ+TDopk+Noz1g62ZodixiEiLsbAQUYMSBAHzdpzEvvO5MNSX4utgX7hZm4gdi4i0HAsLETWo5b9dwHepNyCVAKtHdUU3J0uxIxFRI8DCQkQNZkPiNazedwkA8MkrHgjoZCtyIiJqLFhYiKhB7D55Cwt/Pg0ACO/XDiP9WouciIgaExYWIqp3SVduY/r2YxAE4HX/1pj2QhuxIxFRI1OrwrJmzRo4OzvD0NAQ/v7+SE5OfuTY9evX47nnnoOlpSUsLS0REBBQZXxISAgkEonabcCAAbWJRkRa5lxWIcZtOILySiX6d7LFh4M7cxZbItKYxoVl+/btCA8Px8KFC5GWlgYvLy8EBgYiJyen2vH79+/HqFGjsG/fPiQmJsLR0RH9+/fHzZs31cYNGDAAt27dUt22bt1auz0iIq2RmX8fIdEpuFdaCR8nS6wc1QUyzmJLRLUgEQRB0GQFf39/+Pr6YvXq1QAApVIJR0dHTJs2DXPnzn3i+gqFApaWlli9ejWCgoIAPDjCkp+fjx9//FHzPQBQWFgIc3NzFBQUwMzMrFbbIKK6lV9SjqFRibiUU4Q2Nib4bmJ3WDSTix2LiLSIJu/fGh1hKS8vR2pqKgICAv7egFSKgIAAJCYm1mgbJSUlqKioQPPmzdWW79+/HzY2Nmjfvj0mTZqE27dvaxKNiLRIaYUC4+KO4FJOEezMDBEX5seyQkRPRU+TwXl5eVAoFLC1Vb8U0dbWFufOnavRNt555x04ODiolZ4BAwbg1VdfhYuLCy5fvox3330XAwcORGJiImSyqt8rUlZWhrKyMtX9wsJCTXaDiOqRQingra1HceT6XZga6iEuzA8tLYzEjkVEjZxGheVpLV68GNu2bcP+/fthaPj3NNwjR45U/dnDwwOenp5wc3PD/v370bdv3yrbiYiIwPvvv98gmYmo5gRBwPyfTuG3M9mQ60mxPsgH7e1MxY5FRDpAo4+ErKysIJPJkJ2drbY8OzsbdnZ2j1132bJlWLx4MX777Td4eno+dqyrqyusrKxw6dKlah+fN28eCgoKVLeMjAxNdoOI6smqPy5hS1I6JBLg8xHeeMa1hdiRiEhHaFRY5HI5unXrhoSEBNUypVKJhIQEdO/e/ZHrLV26FB9++CHi4+Ph4+PzxOe5ceMGbt++DXt7+2ofNzAwgJmZmdqNiMS1LTkdK/ZeAAC8/x93DPSo/u8vEVFtaHxZc3h4ONavX4+4uDicPXsWkyZNQnFxMUJDQwEAQUFBmDdvnmr8kiVLMH/+fERHR8PZ2RlZWVnIyspCUVERAKCoqAizZ8/G4cOHce3aNSQkJGDw4MFo06YNAgMD62g3iag+/X4mG+/+cBIAMOV5NwR1dxY3EBHpHI3PYRkxYgRyc3OxYMECZGVlwdvbG/Hx8aoTcdPT0yGV/t2D1q5di/LycgwdOlRtOwsXLsSiRYsgk8lw4sQJxMXFIT8/Hw4ODujfvz8+/PBDGBgYPOXuEVF9S0u/i6lb06AUgKHdWmFW//ZiRyIiHaTxPCzaiPOwEInjUk4RhkYdQn5JBfq0t8b6IB/oy/iNH0RUM/U2DwsR0UPZhaUIjk5GfkkFvFqZ44vRXVlWiKje8NWFiDRWWFqBkJgU3My/DxcrY0SH+KKZvEFnSSCiJoaFhYg0UlapwIQNqTh7qxBWJgbYEOaHFiY834yI6hcLCxHVmFIpIPyb40i8chsmBnqIDfWFY/NmYscioiaAhYWIakQQBHz46xn8euIW9GUSRL3RDZ1bmosdi4iaCBYWIqqRdX9eQczBawCAZcO88GxbK3EDEVGTwsJCRE+0I+0GInY/+ILT/77UEYO9W4qciIiaGhYWInqsPy/kYs53JwAA4551wbjnXEVORERNEQsLET3SiRv5mLgpFZVKAf/xcsC7L3YUOxIRNVEsLERUreu3ixEWm4KScgWebWOFZcO8IJVKxI5FRE0UCwsRVZFXVIag6GTkFZWjk70Z1r7RFXI9vlwQkXj4CkREaorLKhEWm4Lrt0vg2NwIsWG+MDXUFzsWETVxLCxEpFKhUGLS5jScuFGA5sZyxIX6wcbUUOxYREQsLET0gCAIeOe7E/jzQi6M9GWIDvGFq7WJ2LGIiACwsBDR/1sSfx47jt6ETCrBF6O7wtvRQuxIREQqLCxEhJiDVxF14DIAYPGrHni+g43IiYiI1LGwEDVxO09k4oOdZwAAswPbY5iPo8iJiIiqYmEhasIOXc5D+PbjEAQgqLsTJvdxEzsSEVG1WFiImqiztwoxYUMqyhVKDOxsh4WD3CGRcGI4ItJOLCxETdCNuyUIjk7GvbJK+Lk0x2cjvCHjLLZEpMVYWIiamLvF5QiOTkbOvTK0tzXF+iAfGOrLxI5FRPRYLCxETcj9cgXGxqXgcm4x7M0NERvmC3MjzmJLRNqPhYWoiahUKDFtaxrS0vNhbqSPDWF+sDc3EjsWEVGNsLAQNQGCIGD+T6fw+9kcGOhJ8VWwD9ramoodi4ioxlhYiJqAyN8vYmtyBqQSYOWoLvB1bi52JCIijbCwEOm4zUnX8XnCRQDAB4M7I9DdTuRERESaY2Eh0mG/nc7C/B9PAQDeeqEN3njGSeRERES1w8JCpKOOXLuDaVuPQikAI3wcMbNfO7EjERHVGgsLkQ66mH0PY+OOoKxSib4dbPDxK505iy0RNWosLEQ6JqugFMHRySi4X4EurS2w+vWu0JPxrzoRNW58FSPSIQX3KxAcnYzMglK4Whvj62BfGMk5iy0RNX4sLEQ6orRCgfEbjuB89j3YmBogLtQPzY3lYsciIqoTLCxEOkChFBD+zTEkXb0DUwM9xIb6wbF5M7FjERHVGRYWokZOEAR88Mtp7DqZBblMii+DuqGTg5nYsYiI6hQLC1Ejt/bAZcQlXgcALB/uhR5uViInIiKqe7UqLGvWrIGzszMMDQ3h7++P5OTkR45dv349nnvuOVhaWsLS0hIBAQFVxguCgAULFsDe3h5GRkYICAjAxYsXaxONqEn59kgGlsafBwAseLkTBnk5iJyIiKh+aFxYtm/fjvDwcCxcuBBpaWnw8vJCYGAgcnJyqh2/f/9+jBo1Cvv27UNiYiIcHR3Rv39/3Lx5UzVm6dKlWLlyJaKiopCUlARjY2MEBgaitLS09ntGpOP2nc/B3B0nAQATersi7FkXkRMREdUfiSAIgiYr+Pv7w9fXF6tXrwYAKJVKODo6Ytq0aZg7d+4T11coFLC0tMTq1asRFBQEQRDg4OCAt99+G7NmzQIAFBQUwNbWFrGxsRg5cuQTt1lYWAhzc3MUFBTAzIyf3ZPuO5aRj1HrDuN+hQKvdGmJ5cO8IJVyYjgialw0ef/W6AhLeXk5UlNTERAQ8PcGpFIEBAQgMTGxRtsoKSlBRUUFmjd/8G2xV69eRVZWlto2zc3N4e/vX+NtEjUlV/OKERabgvsVCjzX1gpLXvNkWSEinaenyeC8vDwoFArY2tqqLbe1tcW5c+dqtI133nkHDg4OqoKSlZWl2sa/t/nwsX8rKytDWVmZ6n5hYWGN94GoMcu5V4qg6CTcKS6HR0tzrH2jG+R6PHeeiHRfg77SLV68GNu2bcMPP/wAQ0PDWm8nIiIC5ubmqpujo2MdpiTSTkVllQiNSUHGnftwatEM0SG+MDHQ6N8cRESNlkaFxcrKCjKZDNnZ2WrLs7OzYWdn99h1ly1bhsWLF+O3336Dp6enavnD9TTZ5rx581BQUKC6ZWRkaLIbRI1OeaUSEzem4nRmIVoYyxEX6gdrUwOxYxERNRiNCotcLke3bt2QkJCgWqZUKpGQkIDu3bs/cr2lS5fiww8/RHx8PHx8fNQec3FxgZ2dndo2CwsLkZSU9MhtGhgYwMzMTO1GpKuUSgFzvjuOvy7loZlchphQXzhbGYsdi4ioQWl8PDk8PBzBwcHw8fGBn58fIiMjUVxcjNDQUABAUFAQWrZsiYiICADAkiVLsGDBAmzZsgXOzs6q81JMTExgYmICiUSCGTNm4KOPPkLbtm3h4uKC+fPnw8HBAUOGDKm7PSVqpBbHn8OPxzKhJ5Vg7Rvd4NnKQuxIREQNTuPCMmLECOTm5mLBggXIysqCt7c34uPjVSfNpqenQyr9+8DN2rVrUV5ejqFDh6ptZ+HChVi0aBEAYM6cOSguLsb48eORn5+PZ599FvHx8U91nguRLvjqf1ew7s8rAIClQz3Ru521yImIiMSh8Tws2ojzsJAu+vl4Jt7aehQA8M6ADpjUx03kREREdave5mEhooZx8FIe3v7mGAAgpIczJvZ2FTcQEZHIWFiItMzpzAJM2JiKCoWAlzztseDlTpBIODEcETVtLCxEWiTjTglCYlJQVFaJZ1ybY8VwTrlPRASwsBBpjTvF5QiKTkbuvTJ0sDPFuiAfGOjJxI5FRKQVWFiItEBJeSXCYlNwNa8YLS2MEBfmBzNDfbFjERFpDRYWIpFVKJSYsjkNxzLyYdFMH3FhfrA14yX9RET/xMJCJCJBEPDeDyex73wuDPWl+DrYF21sTMSORUSkdVhYiES0Yu8FfHPkBqQSYPWorujmZCl2JCIircTCQiSSjYnXsOqPSwCAT17xQEAnW5ETERFpLxYWIhHEn7qFBT+fBgDMDGiHkX6tRU5ERKTdWFiIGljy1Tt4a9sxCAIwyq813urbRuxIRERaj4WFqAGdz7qHcXEpKK9Uol8nW3w42J2z2BIR1QALC1EDycy/j+DoZBSWVqKbkyVWjeoCPRn/ChIR1QRfLYkaQEFJBYKjk5FVWIo2Nib4OtgHhvqcxZaIqKZYWIjqWWmFAuM2pOBiThFszQwQF+YHi2ZysWMRETUqLCxE9UihFDB921GkXLsLU0M9xIX5oaWFkdixiIgaHRYWonoiCAIW/HQKe05nQy6TYn2QDzrYmYkdi4ioUWJhIaonq/+4hM1J6ZBIgMiR3njGtYXYkYiIGi0WFqJ68E1KBpbvvQAAWDTIHS962IuciIiocWNhIapjCWezMe+HkwCAyX3cENzDWdxAREQ6gIWFqA6lpd/FlC1pUCgFvNa1FWYHthc7EhGRTmBhIaojl3OLMDY2BaUVSvRpb43Fr3lwFlsiojrCwkJUB7ILSxH0dTLullTAq5U51rzeFfqcxZaIqM7wFZXoKRWWViAkJgU38+/DuUUzRIf4wthAT+xYREQ6hYWF6CmUVSowcWMqzt4qhJWJATaE+aOFiYHYsYiIdA4LC1EtKZUC3v7mOA5dvg1juQyxob5o3aKZ2LGIiHQSCwtRLQiCgI9+PYudJ25BXyZB1Jhu6NzSXOxYREQ6i4WFqBbW/+8Kog9eBQAsG+aF59pai5yIiEi3sbAQaeiHozfwya5zAID3XuyIwd4tRU5ERKT7WFiINPDnhVzM/vYEAGDssy54s5eryImIiJoGFhaiGjp5owCTNqWiUilgkJcD3nuxo9iRiIiaDBYWohq4frsYobHJKC5XoGebFlg2zBNSKWexJSJqKCwsRE+QV1SG4Ohk5BWVo5O9GaLe6AYDPZnYsYiImhQWFqLHKC6rRFhsCq7dLkErSyPEhvrC1FBf7FhERE0OCwvRI1QolJi8OQ0nbhSgubEcG8L8YGNmKHYsIqImqVaFZc2aNXB2doahoSH8/f2RnJz8yLGnT5/Ga6+9BmdnZ0gkEkRGRlYZs2jRIkgkErVbhw4dahONqE4IgoB3vj+BAxdyYaQvw9fBPnC1NhE7FhFRk6VxYdm+fTvCw8OxcOFCpKWlwcvLC4GBgcjJyal2fElJCVxdXbF48WLY2dk9crvu7u64deuW6vbXX39pGo2ozizdcx470m5CJpVgzegu6NLaUuxIRERNmsaFZcWKFXjzzTcRGhqKTp06ISoqCs2aNUN0dHS14319ffHpp59i5MiRMDB49JfC6enpwc7OTnWzsrLSNBpRnYg9eBVr918GAES86oEXOtiKnIiIiDQqLOXl5UhNTUVAQMDfG5BKERAQgMTExKcKcvHiRTg4OMDV1RWjR49Genr6U22PqDZ+PXEL7+88AwCY1b8dhvs4ipyIiIgADQtLXl4eFAoFbG3V/8Vpa2uLrKysWofw9/dHbGws4uPjsXbtWly9ehXPPfcc7t27V+34srIyFBYWqt2Inlbi5duYuf0YBAEY84wTpjzfRuxIRET0//TEDgAAAwcOVP3Z09MT/v7+cHJywjfffIOxY8dWGR8REYH333+/ISOSjjt7qxDjNxxBuUKJAe52WPQfd0gknBiOiEhbaHSExcrKCjKZDNnZ2WrLs7OzH3tCraYsLCzQrl07XLp0qdrH582bh4KCAtUtIyOjzp6bmp4bd0sQEpOMe2WV8HNujsiR3pBxFlsiIq2iUWGRy+Xo1q0bEhISVMuUSiUSEhLQvXv3OgtVVFSEy5cvw97evtrHDQwMYGZmpnYjqo27xeUIjk5GdmEZ2tmaYH2QDwz1OYstEZG20fgjofDwcAQHB8PHxwd+fn6IjIxEcXExQkNDAQBBQUFo2bIlIiIiADw4UffMmTOqP9+8eRPHjh2DiYkJ2rR5cI7ArFmzMGjQIDg5OSEzMxMLFy6ETCbDqFGj6mo/iaq4X67A2LgUXM4thr25IeLC/GDejLPYEhFpI40Ly4gRI5Cbm4sFCxYgKysL3t7eiI+PV52Im56eDqn07wM3mZmZ6NKli+r+smXLsGzZMvTu3Rv79+8HANy4cQOjRo3C7du3YW1tjWeffRaHDx+GtbX1U+4eUfUqFUpM23oUaen5MDPUQ1yYH+zNjcSORUREjyARBEEQO8TTKiwshLm5OQoKCvjxED2RIAh494dT2JqcDgM9KTaN84evc3OxYxERNTmavH/zu4Soyfk84SK2JqdDKgE+H9mFZYWIqBFgYaEmZUtSOiJ/vwgA+GBwZwzoXHdXtxERUf1hYaEmY++ZbPz3x5MAgGkvtMEbzziJnIiIiGqKhYWahNTrdzB1SxqUAjDcpxXC+7UTOxIREWmAhYV03qWcewiLPYKySiX6drDBJ694cBZbIqJGhoWFdFpWQSmCo1NQcL8C3o4WWPV6F+jJ+GtPRNTY8JWbdFbB/QqExCTjZv59uFoZIzrEF83kWvH1WUREpCEWFtJJpRUKjN9wBOey7sHa1ABxYX5obiwXOxYREdUSCwvpHIVSQPg3x5B09Q5MDPQQG+oLx+bNxI5FRERPgYWFdIogCPhw5xnsOpkFfZkE68Z0g7uDudixiIjoKbGwkE6JOnAFsYeuAQBWDPdGjzZW4gYiIqI6wcJCOuO71BtYEn8OADD/5U4Y5OUgciIiIqorLCykE/afz8E7358AAEzo5Yqxz7qInIiIiOoSCws1escz8jF5cxoUSgFDvB3wzoAOYkciIqI6xsJCjdrVvGKExaagpFyB59paYelQL0ilnMWWiEjXsLBQo5V7rwxB0Um4XVyOzi3NsPaNbpDr8VeaiEgX8dWdGqWiskqExiYj4859tG7eDDEhfjAx4Cy2RES6ioWFGp3ySiUmbUrFqZuFaGEsR1yYH6xNDcSORURE9YiFhRoVpVLAnO+O438X89BMLkN0iC9crIzFjkVERPWMhYUalSXx5/DjsUzoSSX4YnRXeDlaiB2JiIgaAAsLNRpf/3UVX/55BQCw5DVP9GlvI3IiIiJqKCws1Cj8fDwTH+48AwB4Z0AHvNatlciJiIioIbGwkNY7dCkPb39zDAAQ0sMZE3u7ihuIiIgaHAsLabXTmQUYvzEVFQoBL3nYY/7LnSCRcGI4IqKmhoWFtFbGnRKExKSgqKwS/i7NsXy4F2ScxZaIqEliYSGtdKe4HMHRyci9V4YOdqZYF+QDQ32Z2LGIiEgkLCykdUrKKxEWm4IrecVoaWGE2FA/mBvpix2LiIhExMJCWqVSocTULUdxLCMf5kb6iAvzhZ25odixiIhIZCwspDUEQcC7P5zEH+dyYKAnRXSID9rYmIodi4iItAALC2mNz/ZewDdHbkAqAVa/3hXdnJqLHYmIiLQECwtphY2Hr2PlH5cAAB+/4oF+nWxFTkRERNqEhYVEF38qCwt+OgUAmBHQFqP8WouciIiItA0LC4kq5dodvLXtKAQBGOXXGtP7thU7EhERaSEWFhLNhex7GBubgvJKJQI62uLDwe6cxZaIiKrFwkKiyMy/j+DoZBSWVqKbkyVWjeoCPRl/HYmIqHp8h6AGV1BSgZCYZNwqKIWbtTG+DvaBkZyz2BIR0aPVqrCsWbMGzs7OMDQ0hL+/P5KTkx859vTp03jttdfg7OwMiUSCyMjIp94mNV6lFQq8ueEILmQXwdbMAHFhfrBoJhc7FhERaTmNC8v27dsRHh6OhQsXIi0tDV5eXggMDEROTk6140tKSuDq6orFixfDzs6uTrZJjZNCKWDGtmNIvnYHpoZ6iAvzQyvLZmLHIiKiRkAiCIKgyQr+/v7w9fXF6tWrAQBKpRKOjo6YNm0a5s6d+9h1nZ2dMWPGDMyYMaPOtgkAhYWFMDc3R0FBAczMzDTZHWoggiBgwU+nsfHwdchlUsSF+aG7WwuxYxERkYg0ef/W6AhLeXk5UlNTERAQ8PcGpFIEBAQgMTGxVmFrs82ysjIUFhaq3Ui7rdl3CRsPX4dEAnw2wptlhYiINKJRYcnLy4NCoYCtrfospLa2tsjKyqpVgNpsMyIiAubm5qqbo6NjrZ6bGsY3RzKw7LcLAICFL3fCS572IiciIqLGplFeJTRv3jwUFBSobhkZGWJHokf441w25u04CQCY1McNIT1dRE5ERESNkZ4mg62srCCTyZCdna22PDs7+5En1NbHNg0MDGBgYFCr56OGczT9LiZvToNCKeDVri0xJ7C92JGIiKiR0ugIi1wuR7du3ZCQkKBaplQqkZCQgO7du9cqQH1sk8R3JbcIYbEpKK1Qonc7ayx5zZOz2BIRUa1pdIQFAMLDwxEcHAwfHx/4+fkhMjISxcXFCA0NBQAEBQWhZcuWiIiIAPDgpNozZ86o/nzz5k0cO3YMJiYmaNOmTY22SY1LTmEpgqKTcbekAp6tzPHF6K7Q5yy2RET0FDQuLCNGjEBubi4WLFiArKwseHt7Iz4+XnXSbHp6OqTSv9+cMjMz0aVLF9X9ZcuWYdmyZejduzf2799fo21S43GvtALBMSm4cfc+nFs0Q3SIL4wNNP41IyIiUqPxPCzaiPOwaIeySgXCYlNw8NJtWJnIsWNST7RuwYnhiIioevU2DwvRoyiVAmZ9ewIHL92GsVyGmBA/lhUiIqozLCxUJz7ZdRa/HM+EnlSCqDHd4NHKXOxIRESkQ1hY6Kmt//MKvvrrKgBg2TAvPNfWWuRERESka1hY6Kn8ePQmPt51FgDw7osdMKRLS5ETERGRLmJhoVr738VczP7uOABg7LMuePM5V5ETERGRrmJhoVo5dbMAEzemokIhYJCXA957sSMnhiMionrDwkIaS79dgpCYZBSXK9DDrQWWDfOEVMqyQkRE9YeFhTSSV1SGoOgk5BWVo6O9Gb4c0w0GejKxYxERkY5jYaEaKy6rxNjYFFy7XYKWFkaIC/WFqaG+2LGIiKgJYGGhGqlQKDF5cxqO3yiAZTN9bBjrBxszQ7FjERFRE8HCQk8kCALmfn8SBy7kwlBfiugQX7hZm4gdi4iImhAWFnqiT/ecx/dpNyCTSrDm9a7o0tpS7EhERNTEsLDQY8UduoYv9l8GAES84oG+HfkN2kRE1PBYWOiRdp28hUW/nAYAvN2vHYb7OoqciIiImioWFqrW4Su3MWPbMQgC8MYzrTH1hTZiRyIioiaMhYWqOJdViDc3HEG5QokB7nZ4/z+dOYstERGJioWF1NzMv4/g6GTcK62Er7MlIkd6Q8ZZbImISGQsLKSSX1KO4OhkZBeWoZ2tCb4K8oWhPmexJSIi8bGwEACgtEKBsXFHcCmnCHZmhogN9YN5M85iS0RE2oGFhVCpUGLa1qNIvX4XZoZ62DDWDw4WRmLHIiIiUmFhaeIEQcD8n05j75lsyPWk+CrYF+1sTcWORUREpIaFpYlbmXAJW5PTIZEAK0d6w8+ludiRiIiIqmBhacK2Jqfjs98vAAA+GNwZAzrbi5yIiIioeiwsTdTeM9l474eTAIBpL7TBmGecRE5ERET0aCwsTVDq9TuYuiUNSgEY7tMK4f3aiR2JiIjosVhYmphLOUUYG3cEZZVKvNDBBp+84sFZbImISOuxsDQh2YWlCI5ORn5JBbwdLbD69S7Qk/FXgIiItB/frZqIgvsVCI5Oxs38+3C1MkZ0iC+ayfXEjkVERFQjLCxNQFmlAhM2HsG5rHuwNjVAXJgfmhvLxY5FRERUYywsOk6pFBC+/TgOX7kDEwM9xIb6wrF5M7FjERERaYSFRYcJgoAPdp7BrydvQV8mwZdjusHdwVzsWERERBpjYdFhX/55BbGHrgEAlg/3Rs82VuIGIiIiqiUWFh31feoNLN59DgDw35c64j9eDiInIiIiqj0WFh20/3wO3vn+BABgfC9XjHvOVeRERERET4eFRcecuJGPyZvTUKkUMMTbAXMHdBA7EhER0VOrVWFZs2YNnJ2dYWhoCH9/fyQnJz92/LfffosOHTrA0NAQHh4e2LVrl9rjISEhkEgkarcBAwbUJlqTdi2vGKExKSgpV+C5tlZYOtQLUilnsSUiosZP48Kyfft2hIeHY+HChUhLS4OXlxcCAwORk5NT7fhDhw5h1KhRGDt2LI4ePYohQ4ZgyJAhOHXqlNq4AQMG4NatW6rb1q1ba7dHTVTuvTIERSfjdnE5Orc0w9o3ukGuxwNoRESkGySCIAiarODv7w9fX1+sXr0aAKBUKuHo6Ihp06Zh7ty5VcaPGDECxcXF2Llzp2rZM888A29vb0RFRQF4cIQlPz8fP/74Y612orCwEObm5igoKICZmVmtttGYFZVVYtS6wzh5swCOzY3w/aQesDE1FDsWERHRY2ny/q3RP8HLy8uRmpqKgICAvzcglSIgIACJiYnVrpOYmKg2HgACAwOrjN+/fz9sbGzQvn17TJo0Cbdv335kjrKyMhQWFqrdmqrySiUmbUrFyZsFaG4sx4Ywf5YVIiLSORoVlry8PCgUCtja2qott7W1RVZWVrXrZGVlPXH8gAEDsGHDBiQkJGDJkiU4cOAABg4cCIVCUe02IyIiYG5urro5Ojpqshs6Q6kU8M73J/C/i3kw0pchJsQXLlbGYsciIiKqc1rx7XcjR45U/dnDwwOenp5wc3PD/v370bdv3yrj582bh/DwcNX9wsLCJllaluw5hx+O3oRMKsEXb3SFl6OF2JGIiIjqhUZHWKysrCCTyZCdna22PDs7G3Z2dtWuY2dnp9F4AHB1dYWVlRUuXbpU7eMGBgYwMzNTuzU10X9dxZcHrgAAlrzmiefb24iciIiIqP5oVFjkcjm6deuGhIQE1TKlUomEhAR079692nW6d++uNh4A9u7d+8jxAHDjxg3cvn0b9vb2msRrMn45nokPfz0DAJgzoD2GdmslciIiIqL6pfF1r+Hh4Vi/fj3i4uJw9uxZTJo0CcXFxQgNDQUABAUFYd68earx06dPR3x8PJYvX45z585h0aJFOHLkCKZOnQoAKCoqwuzZs3H48GFcu3YNCQkJGDx4MNq0aYPAwMA62k3dcehSHt7+5jgEAQju7oRJvd3EjkRERFTvND6HZcSIEcjNzcWCBQuQlZUFb29vxMfHq06sTU9Ph1T6dw/q0aMHtmzZgv/+979499130bZtW/z444/o3LkzAEAmk+HEiROIi4tDfn4+HBwc0L9/f3z44YcwMDCoo93UDWcyCzF+YyrKFUq86GGHBYPcIZFwYjgiItJ9Gs/Doo2awjwsGXdK8NraQ8i5VwZ/l+aIC/ODob5M7FhERES1Vm/zsJA47hSXIzgmGTn3ytDBzhTrgnxYVoiIqElhYdFy98sVGBuXgiu5xXAwN0RsqB/MjfTFjkVERNSgWFi0WKVCialb0nA0PR/mRvrYMNYPduacxZaIiJoeFhYtJQgC3vvhFBLO5cBAT4qvg33QxsZU7FhERESiYGHRUp/9fhHbj2RAKgFWjeoCH+fmYkciIiISDQuLFtp0+DpWJlwEAHw0xAP93R89KzAREVFTwMKiZfaczsKCn04BAKb3bYvX/VuLnIiIiEh8LCxaJOXaHby19SiUAjDKzxEzAtqKHYmIiEgrsLBoiQvZ9zA2NgVllUoEdLTFh4M7cxZbIiKi/8fCogVuFdxHcHQyCksr0bW1BVaN6gI9Gf/XEBERPcR3RZEVlFQgJDoFtwpK4WZtjK+DfWEk5yy2RERE/8TCIqLSCgXe3HAE57PvwdbMAHFhfrA0losdi4iISOuwsIhEoRQwY9sxJF+7A1MDPcSG+qGVZTOxYxEREWklFhYRCIKA9385jfjTWZDLpFgX5IOO9rr5LdNERER1gYVFBF/sv4wNidchkQArRnihu1sLsSMRERFpNRaWBvbtkQx8uuc8AGDhy53wsqeDyImIiIi0HwtLA9p3Lgdzd5wEAEzs7YaQni4iJyIiImocWFgayLGMfEzenAaFUsCrXVvinQHtxY5ERETUaLCwNIAruUUIi03B/QoFerWzxpLXPDmLLRERkQZYWOpZzr1SBEUn405xOTxbmWPt6K7Q5yy2REREGuE7Zz26V/pgFtsbd+/DqUUzRIf4wthAT+xYREREjQ4LSz0pr1Ri4qZUnLlVCCsTOTaE+cHKxEDsWERERI0SC0s9UCoFzPr2OA5euo1mchliQvzg1MJY7FhERESNFgtLPYjYfRY/H8+EnlSCqDe6waOVudiRiIiIGjUWljq2/s8rWP+/qwCAT4d5olc7a5ETERERNX4sLHXop2M38fGuswCAeQM74JUurUROREREpBtYWOrIXxfzMOvb4wCAsJ4uGN/LVeREREREuoOFpQ6culmACRuPoEIh4GVPe/z3pY6cGI6IiKgOsbA8pfTbJQiJSUFxuQLdXVtg+XAvSKUsK0RERHWJheUp3C4qQ3BMMvKKytDR3gxfBnWDgZ5M7FhEREQ6h4WllorLKhEWm4KrecVoaWGEuFBfmBnqix2LiIhIJ7Gw1EKFQokpW9Jw/EYBLJvpY8NYP9iYGYodi4iISGexsGhIEATM23ES+8/nwlBfiq9DfOFmbSJ2LCIiIp3GwqKhZb+dx3epNyCTSrDm9a7o2tpS7EhEREQ6j4VFAxsSr2HNvssAgE9e6Yy+HW1FTkRERNQ01KqwrFmzBs7OzjA0NIS/vz+Sk5MfO/7bb79Fhw4dYGhoCA8PD+zatUvtcUEQsGDBAtjb28PIyAgBAQG4ePFibaLVm10nb2Hhz6cBAOH92mGEb2uRExERETUdGheW7du3Izw8HAsXLkRaWhq8vLwQGBiInJycascfOnQIo0aNwtixY3H06FEMGTIEQ4YMwalTp1Rjli5dipUrVyIqKgpJSUkwNjZGYGAgSktLa79ndSjpym3M2H4MggCM9m+NaS+0ETsSERFRkyIRBEHQZAV/f3/4+vpi9erVAAClUglHR0dMmzYNc+fOrTJ+xIgRKC4uxs6dO1XLnnnmGXh7eyMqKgqCIMDBwQFvv/02Zs2aBQAoKCiAra0tYmNjMXLkyCdmKiwshLm5OQoKCmBmZqbJ7jzRuaxCDItKxL3SSvTvZIu1b3SDjBPDERERPTVN3r81OsJSXl6O1NRUBAQE/L0BqRQBAQFITEysdp3ExES18QAQGBioGn/16lVkZWWpjTE3N4e/v/8jt1lWVobCwkK1W324mX8fIdEpuFdaCR8nS6wc1YVlhYiISAQaFZa8vDwoFArY2qqfbGpra4usrKxq18nKynrs+If/1WSbERERMDc3V90cHR012Y0a05dK0NxYjrY2Jvgq2AeG+pzFloiISAyN8iqhefPmoaCgQHXLyMiol+exMTPE9gnPYONYf1g0k9fLcxAREdGT6Wky2MrKCjKZDNnZ2WrLs7OzYWdnV+06dnZ2jx3/8L/Z2dmwt7dXG+Pt7V3tNg0MDGBgYKBJ9FozNdSHKafcJyIiEpVGR1jkcjm6deuGhIQE1TKlUomEhAR079692nW6d++uNh4A9u7dqxrv4uICOzs7tTGFhYVISkp65DaJiIioadHoCAsAhIeHIzg4GD4+PvDz80NkZCSKi4sRGhoKAAgKCkLLli0REREBAJg+fTp69+6N5cuX46WXXsK2bdtw5MgRrFu3DgAgkUgwY8YMfPTRR2jbti1cXFwwf/58ODg4YMiQIXW3p0RERNRoaVxYRowYgdzcXCxYsABZWVnw9vZGfHy86qTZ9PR0SKV/H7jp0aMHtmzZgv/+979499130bZtW/z444/o3LmzasycOXNQXFyM8ePHIz8/H88++yzi4+NhaMgvFCQiIqJazMOijepzHhYiIiKqH/U2DwsRERGRGFhYiIiISOuxsBAREZHWY2EhIiIircfCQkRERFqPhYWIiIi0HgsLERERaT0WFiIiItJ6LCxERESk9TSeml8bPZyst7CwUOQkREREVFMP37drMum+ThSWe/fuAQAcHR1FTkJERESaunfvHszNzR87Rie+S0ipVCIzMxOmpqaQSCR1uu3CwkI4OjoiIyOjSXxPUVPbX6Dp7XNT21+g6e0z91f36co+C4KAe/fuwcHBQe2Lk6ujE0dYpFIpWrVqVa/PYWZm1qh/KTTV1PYXaHr73NT2F2h6+8z91X26sM9POrLyEE+6JSIiIq3HwkJERERaj4XlCQwMDLBw4UIYGBiIHaVBNLX9BZrePje1/QWa3j5zf3VfU9xnnTjploiIiHQbj7AQERGR1mNhISIiIq3HwkJERERaj4WFiIiItB4LyxOsWbMGzs7OMDQ0hL+/P5KTk8WOVC8iIiLg6+sLU1NT2NjYYMiQITh//rzYsRrM4sWLIZFIMGPGDLGj1KubN2/ijTfeQIsWLWBkZAQPDw8cOXJE7Fj1QqFQYP78+XBxcYGRkRHc3Nzw4Ycf1ug7SxqLP//8E4MGDYKDgwMkEgl+/PFHtccFQcCCBQtgb28PIyMjBAQE4OLFi+KErQOP29+Kigq888478PDwgLGxMRwcHBAUFITMzEzxAteBJ/0//qeJEydCIpEgMjKywfI1JBaWx9i+fTvCw8OxcOFCpKWlwcvLC4GBgcjJyRE7Wp07cOAApkyZgsOHD2Pv3r2oqKhA//79UVxcLHa0epeSkoIvv/wSnp6eYkepV3fv3kXPnj2hr6+P3bt348yZM1i+fDksLS3FjlYvlixZgrVr12L16tU4e/YslixZgqVLl2LVqlViR6szxcXF8PLywpo1a6p9fOnSpVi5ciWioqKQlJQEY2NjBAYGorS0tIGT1o3H7W9JSQnS0tIwf/58pKWlYceOHTh//jz+85//iJC07jzp//FDP/zwAw4fPgwHB4cGSiYCgR7Jz89PmDJliuq+QqEQHBwchIiICBFTNYycnBwBgHDgwAGxo9Sre/fuCW3bthX27t0r9O7dW5g+fbrYkerNO++8Izz77LNix2gwL730khAWFqa27NVXXxVGjx4tUqL6BUD44YcfVPeVSqVgZ2cnfPrpp6pl+fn5goGBgbB161YREtatf+9vdZKTkwUAwvXr1xsmVD171D7fuHFDaNmypXDq1CnByclJ+Oyzzxo8W0PgEZZHKC8vR2pqKgICAlTLpFIpAgICkJiYKGKyhlFQUAAAaN68uchJ6teUKVPw0ksvqf1/1lU///wzfHx8MGzYMNjY2KBLly5Yv3692LHqTY8ePZCQkIALFy4AAI4fP46//voLAwcOFDlZw7h69SqysrLUfrfNzc3h7+/fJF7DgAevYxKJBBYWFmJHqTdKpRJjxozB7Nmz4e7uLnaceqUTX35YH/Ly8qBQKGBra6u23NbWFufOnRMpVcNQKpWYMWMGevbsic6dO4sdp95s27YNaWlpSElJETtKg7hy5QrWrl2L8PBwvPvuu0hJScFbb70FuVyO4OBgsePVublz56KwsBAdOnSATCaDQqHAxx9/jNGjR4sdrUFkZWUBQLWvYQ8f02WlpaV45513MGrUqEb/5YCPs2TJEujp6eGtt94SO0q9Y2GhKqZMmYJTp07hr7/+EjtKvcnIyMD06dOxd+9eGBoaih2nQSiVSvj4+OCTTz4BAHTp0gWnTp1CVFSUThaWb775Bps3b8aWLVvg7u6OY8eOYcaMGXBwcNDJ/aW/VVRUYPjw4RAEAWvXrhU7Tr1JTU3F559/jrS0NEgkErHj1Dt+JPQIVlZWkMlkyM7OVluenZ0NOzs7kVLVv6lTp2Lnzp3Yt28fWrVqJXacepOamoqcnBx07doVenp60NPTw4EDB7By5Uro6elBoVCIHbHO2dvbo1OnTmrLOnbsiPT0dJES1a/Zs2dj7ty5GDlyJDw8PDBmzBjMnDkTERERYkdrEA9fp5raa9jDsnL9+nXs3btXp4+u/O9//0NOTg5at26teh27fv063n77bTg7O4sdr86xsDyCXC5Ht27dkJCQoFqmVCqRkJCA7t27i5isfgiCgKlTp+KHH37AH3/8ARcXF7Ej1au+ffvi5MmTOHbsmOrm4+OD0aNH49ixY5DJZGJHrHM9e/ascqn6hQsX4OTkJFKi+lVSUgKpVP0lTiaTQalUipSoYbm4uMDOzk7tNaywsBBJSUk6+RoG/F1WLl68iN9//x0tWrQQO1K9GjNmDE6cOKH2Oubg4IDZs2djz549Yserc/xI6DHCw8MRHBwMHx8f+Pn5ITIyEsXFxQgNDRU7Wp2bMmUKtmzZgp9++gmmpqaqz7jNzc1hZGQkcrq6Z2pqWuX8HGNjY7Ro0UJnz9uZOXMmevTogU8++QTDhw9HcnIy1q1bh3Xr1okdrV4MGjQIH3/8MVq3bg13d3ccPXoUK1asQFhYmNjR6kxRUREuXbqkun/16lUcO3YMzZs3R+vWrTFjxgx89NFHaNu2LVxcXDB//nw4ODhgyJAh4oV+Co/bX3t7ewwdOhRpaWnYuXMnFAqF6nWsefPmkMvlYsV+Kk/6f/zvUqavrw87Ozu0b9++oaPWP7EvU9J2q1atElq3bi3I5XLBz89POHz4sNiR6gWAam8xMTFiR2swun5ZsyAIwi+//CJ07txZMDAwEDp06CCsW7dO7Ej1prCwUJg+fbrQunVrwdDQUHB1dRXee+89oaysTOxodWbfvn3V/r0NDg4WBOHBpc3z588XbG1tBQMDA6Fv377C+fPnxQ39FB63v1evXn3k69i+ffvEjl5rT/p//G+6fFmzRBB0aNpHIiIi0kk8h4WIiIi0HgsLERERaT0WFiIiItJ6LCxERESk9VhYiIiISOuxsBAREZHWY2EhIiIircfCQkS10qdPH8yYMeORjzs7OyMyMrLB8hCRbuPU/ERUL1JSUmBsbCx2DCLSESwsRFQvrK2txY5ARDqEHwkRUa1VVlZi6tSpMDc3h5WVFebPn4+H3/bx74+E0tPTMXjwYJiYmMDMzAzDhw9Hdna26vFFixbB29sb0dHRaN26NUxMTDB58mQoFAosXboUdnZ2sLGxwccff6yWYcWKFfDw8ICxsTEcHR0xefJkFBUVqR6/fv06Bg0aBEtLSxgbG8Pd3R27du0CANy9exejR4+GtbU1jIyM0LZtW8TExNTjT4yIaotHWIio1uLi4jB27FgkJyfjyJEjGD9+PFq3bo0333xTbZxSqVSVlQMHDqCyshJTpkzBiBEjsH//ftW4y5cvY/fu3YiPj8fly5cxdOhQXLlyBe3atcOBAwdw6NAhhIWFISAgAP7+/gAAqVSKlStXwsXFBVeuXMHkyZMxZ84cfPHFFwAefBN5eXk5/vzzTxgbG+PMmTMwMTEBAMyfPx9nzpzB7t27YWVlhUuXLuH+/fsN88MjIs2I/OWLRNRI9e7dW+jYsaOgVCpVy9555x2hY8eOgiCof2vsb7/9JshkMiE9PV019vTp0wIAITk5WRAEQVi4cKHQrFkzobCwUDUmMDBQcHZ2FhQKhWpZ+/bthYiIiEfm+vbbb4UWLVqo7nt4eAiLFi2qduygQYOE0NBQDfaaiMTCj4SIqNaeeeYZSCQS1f3u3bvj4sWLUCgUauPOnj0LR0dHODo6qpZ16tQJFhYWOHv2rGqZs7MzTE1NVfdtbW3RqVMnSKVStWU5OTmq+7///jv69u2Lli1bwtTUFGPGjMHt27dRUlICAHjrrbfw0UcfoWfPnli4cCFOnDihWnfSpEnYtm0bvL29MWfOHBw6dKgOfipEVB9YWIhIa+jr66vdl0gk1S5TKpUAgGvXruHll1+Gp6cnvv/+e6SmpmLNmjUAgPLycgDAuHHjcOXKFYwZMwYnT56Ej48PVq1aBQAYOHAgrl+/jpkzZyIzMxN9+/bFrFmz6ns3iagWWFiIqNaSkpLU7h8+fBht27aFTCZTW96xY0dkZGQgIyNDtezMmTPIz89Hp06dav38qampUCqVWL58OZ555hm0a9cOmZmZVcY5Ojpi4sSJ2LFjB95++22sX79e9Zi1tTWCg4OxadMmREZGYt26dbXOQ0T1hyfdElGtpaenIzw8HBMmTEBaWhpWrVqF5cuXVxkXEBAADw8PjB49GpGRkaisrMTkyZPRu3dv+Pj41Pr527Rpg4qKCqxatQqDBg3CwYMHERUVpTZmxowZGDhwINq1a4e7d+9i37596NixIwBgwYIF6NatG9zd3VFWVoadO3eqHiMi7cIjLERUa0FBQbh//z78/PwwZcoUTJ8+HePHj68yTiKR4KeffoKlpSV69eqFgIAAuLq6Yvv27U/1/F5eXlixYgWWLFmCzp07Y/PmzYiIiFAbo1AoMGXKFHTs2BEDBgxAu3btVFcQyeVyzJs3D56enujVqxdkMhm2bdv2VJmIqH5IBOH/J00gIiIi0lI8wkJERERaj4WFiIiItB4LCxEREWk9FhYiIiLSeiwsREREpPVYWIiIiEjrsbAQERGR1mNhISIiIq3HwkJERERaj4WFiIiItB4LCxEREWk9FhYiIiLSev8HlYi5Qi41Lg4AAAAASUVORK5CYII=", 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", 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", 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" ] @@ -9659,9 +7356,9 @@ ], "source": [ "(\n", - " cr_gp_df[cr_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", + " cr_gp_df[cr_gp_df.biomass <= 15].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", " esc_gp_df[esc_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", - " # cr_gbrt_df[cr_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", + " # cr_gbrt_df[cr_gbrt_df.biomass <= 15].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", " # esc_gbrt_df[esc_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GBRT policy'),\n", " # msy_gbrt_df[msy_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='MSY GP policy'),\n", ") " diff --git a/src/rl4fisheries/__init__.py b/src/rl4fisheries/__init__.py index 15b09e9..09287c6 100644 --- a/src/rl4fisheries/__init__.py +++ b/src/rl4fisheries/__init__.py @@ -3,6 +3,7 @@ from rl4fisheries.envs.asm_2o import Asm2o from rl4fisheries.envs.asm_esc import AsmEsc from rl4fisheries.envs.asm_env import AsmEnv +from rl4fisheries.envs.asm_cr_like import AsmCRLike from rl4fisheries.agents.cautionary_rule import CautionaryRule from rl4fisheries.agents.const_esc import ConstEsc @@ -18,4 +19,6 @@ register(id="Asm2o-v0", entry_point="rl4fisheries.envs.asm_2o:Asm2o") # action is harvest, but observes both total count and mean biomass register(id="AsmEnv", entry_point="rl4fisheries.envs.asm_env:AsmEnv") +# CR-like actions +register(id="AsmCRLike", entry_point="rl4fisheries.envs.asm_cr_like:AsmCRLike") diff --git a/src/rl4fisheries/envs/asm_cr_like.py b/src/rl4fisheries/envs/asm_cr_like.py index 08266c4..77e5f59 100644 --- a/src/rl4fisheries/envs/asm_cr_like.py +++ b/src/rl4fisheries/envs/asm_cr_like.py @@ -2,14 +2,15 @@ import numpy as np from rl4fisheries import AsmEnv +from rl4fisheries.envs.asm_fns import observe_mwt class AsmCRLike(AsmEnv): """ observe mean weight, decide on a CR-like policy for biomass. """ def __init__(self, render_mode = 'rgb_array', config={}): super().__init__(render_mode=render_mode, config=config) - assert config.get("observation_fn_id", "observe_2o") == "observe_2o", ( - "AsmCRLike only compatible with observe_2o observation function atm, sorry!" - ) + + self._observation_fn = observe_mwt + self.action_space = gym.spaces.Box( np.array(3 * [-1], dtype=np.float32), np.array(3 * [1], dtype=np.float32), @@ -20,10 +21,34 @@ def __init__(self, render_mode = 'rgb_array', config={}): np.array([1], dtype=np.float32), dtype=np.float32, ) - def reset(self, *, seed=None, options=None): - obs, info = super().reset(seed=seed, options=options) - return np.array([obs[1]]), info + self.timestep = 0 + self.state = self.initialize_population() + # + # if self.use_custom_harv_vul: + # self.parameters["harvest_vul"] = self.custom_harv_vul + # if self.use_custom_surv_vul: + # self.parameters["survey_vul"] = self.custom_surv_vul + # + self.state = self.init_state * np.array( + np.random.uniform(0.1, 1), dtype=np.float32 + ) + # + if self.noiseless: + self.r_devs = np.ones(shape = self.n_year) + elif self.reproducibility_mode: + self.r_devs = self.fixed_r_devs + else: + self.r_devs = self.get_r_devs( + n_year=self.n_year, + p_big=self.parameters["p_big"], + sdr=self.parameters["sdr"], + rho=self.parameters["rho"], + ) + # + self.update_vuls() + obs = self.observe() + return obs, {} def step(self, action): self.update_vuls() @@ -44,8 +69,9 @@ def step(self, action): return observation, reward, terminated, False, {} def unnormalize_action(self, action): - x1 = self.bound * (action[0] + 1) / 2 - x2 = self.bound * (action[1] + 1) / 2 + x1 = 10 * (action[0] + 1) / 2 + x2 = 10 * (action[1] + 1) / 2 + x2 = max(x2,x1) y2 = (action[2] + 1) / 2 return np.float32([x1,x2,y2]) @@ -59,9 +85,13 @@ def harvest(self, x1, x2, y2): f_yield = self.harv_vul_b * intensity new_state = self.parameters["s"] * self.state * (1 - self.parameters["harvest_vul"] * intensity) + reward = f_yield ** self.parameters["upow"] return new_state, reward + def observe(self): + return observe_mwt(self) + diff --git a/src/rl4fisheries/envs/asm_fns.py b/src/rl4fisheries/envs/asm_fns.py index eda38cc..747954d 100644 --- a/src/rl4fisheries/envs/asm_fns.py +++ b/src/rl4fisheries/envs/asm_fns.py @@ -70,6 +70,23 @@ def observe_2o(env): observation = np.clip(np.array([biomass_obs, mean_wt_obs]), -1, 1) return np.float32(observation) +def observe_mwt(env): + # mean weight: + if env.surv_vul_n==0: + vulnuerable_mean_wt = 0 + else: + vulnuerable_mean_wt = env.surv_vul_b / env.surv_vul_n + + # mean weight obs: + max_wt, min_wt = env.parameters["max_wt"], env.parameters["min_wt"] # for readability + mean_wt_obs = ( + 2 * (vulnuerable_mean_wt - min_wt) / (max_wt - min_wt) - 1 + ) + + # gathering results: + observation = np.clip(np.array([mean_wt_obs]), -1, 1) + return np.float32(observation) + def asm_pop_growth(env): n_age = env.parameters["n_age"] new_state = np.zeros(shape = n_age) From bed678d280649269f685c651cc9ea375367893d5 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 8 May 2024 01:50:07 +0000 Subject: [PATCH 34/64] added cr-like env, added trophy harvesting, messed with hyperpars --- hyperpars/ppo-asm.yml | 35 ++++++++++++++-------------- hyperpars/tqc-asm.yml | 31 ++++++++++++------------ src/rl4fisheries/envs/asm_cr_like.py | 13 ++++++----- src/rl4fisheries/envs/asm_env.py | 8 +++++-- src/rl4fisheries/envs/asm_fns.py | 32 +++++++++++++++++++++++++ 5 files changed, 79 insertions(+), 40 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 00ff07e..40a4f3e 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,34 +1,35 @@ # algo algo: "PPO" -total_timesteps: 15000000 +total_timesteps: 5000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 - use_sde: True - policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - # in policy_kwargs: net_arch=[256, 128] + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 + # use_sde: True + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + # in policy_kwargs: net_arch=[400, 300] # policy: 'MlpPolicy' # use_sde: True # policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" # clip_range: 0.1 # env -env_id: "AsmCRLike" +env_id: "AsmEnv" config: observation_fn_id: 'observe_2o' n_observs: 2 - upow: 0.6 - use_custom_harv_vul: True - use_custom_surv_vul: True + harvest_fn_name: "trophy" + # upow: 0.6 + # use_custom_harv_vul: True + # use_custom_surv_vul: True n_envs: 12 # io @@ -36,5 +37,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2o-lgBatch-256,128-upow0.6-flatHarvSurv" +id: "trophy-basehyperpars" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index ea8defd..56756a1 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -4,26 +4,27 @@ total_timesteps: 10000000 algo_config: tensorboard_log: "../../../logs" policy: 'MlpPolicy' - learning_rate: !!float 7.3e-4 - buffer_size: 500000 - batch_size: 512 - ent_coef: 'auto' - gamma: 0.98 - tau: 0.02 - train_freq: 64 - gradient_steps: 64 - learning_starts: 20000 - use_sde: True - policy_kwargs: "dict(log_std_init=-3, net_arch=[128, 64])" + # learning_rate: !!float 7.3e-4 + # buffer_size: 500000 + # batch_size: 512 + # ent_coef: 'auto' + # gamma: 0.98 + # tau: 0.02 + # train_freq: 64 + # gradient_steps: 64 + # learning_starts: 20000 + # use_sde: True + # policy_kwargs: "dict(log_std_init=-3, net_arch=[128, 64])" # env env_id: "AsmEnv" config: observation_fn_id: 'observe_2o' n_observs: 2 - upow: 0.6 - use_custom_harv_vul: True - use_custom_surv_vul: True + harvest_fn_name: "trophy" + # upow: 0.6 + # use_custom_harv_vul: True + # use_custom_surv_vul: True n_envs: 12 # io @@ -31,5 +32,5 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents" # misc -id: "2o-upow0.6-flatHarvSurv" +id: "trophy-basehyperpars" additional_imports: ["torch"] diff --git a/src/rl4fisheries/envs/asm_cr_like.py b/src/rl4fisheries/envs/asm_cr_like.py index 77e5f59..551c16c 100644 --- a/src/rl4fisheries/envs/asm_cr_like.py +++ b/src/rl4fisheries/envs/asm_cr_like.py @@ -12,8 +12,8 @@ def __init__(self, render_mode = 'rgb_array', config={}): self._observation_fn = observe_mwt self.action_space = gym.spaces.Box( - np.array(3 * [-1], dtype=np.float32), - np.array(3 * [1], dtype=np.float32), + np.array(2 * [-1], dtype=np.float32), + np.array(2 * [1], dtype=np.float32), dtype=np.float32, ) self.observation_space = gym.spaces.Box( @@ -69,11 +69,12 @@ def step(self, action): return observation, reward, terminated, False, {} def unnormalize_action(self, action): - x1 = 10 * (action[0] + 1) / 2 - x2 = 10 * (action[1] + 1) / 2 + # x1 = 10 * (action[0] + 1) / 2 + x1 = 0 + x2 = 10 * (action[0] + 1) / 2 x2 = max(x2,x1) - y2 = (action[2] + 1) / 2 - return np.float32([x1,x2,y2]) + y2 = (action[1] + 1) / 2 + return np.float32([x1, x2,y2]) def harvest(self, x1, x2, y2): if self.surv_vul_b < x1: diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index c990918..af89a2c 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -7,7 +7,8 @@ observe_1o, observe_2o, observe_total, observe_total_2o, observe_total_2o_v2, - asm_pop_growth, harvest, + asm_pop_growth, + harvest, trophy_harvest, render_asm, get_r_devs, get_r_devs_v2, @@ -108,7 +109,10 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): # # functions - self._harvest_fn = config.get("harvest_fn", harvest) + HARV_FNS = {'default': harvest, 'trophy': trophy_harvest} + self.harv_fn_name = config.get("harvest_fn_name", "default") + self._harvest_fn = HARV_FNS[self.harv_fn_name] + self._pop_growth_fn = config.get("pop_growth_fn", asm_pop_growth) self._render_fn = config.get("render_fn", render_asm) diff --git a/src/rl4fisheries/envs/asm_fns.py b/src/rl4fisheries/envs/asm_fns.py index 747954d..698f1dd 100644 --- a/src/rl4fisheries/envs/asm_fns.py +++ b/src/rl4fisheries/envs/asm_fns.py @@ -135,6 +135,38 @@ def harvest(env, mortality): new_state = p["s"] * env.state * (1 - p["harvest_vul"] * true_mortality) # remove fish return new_state, reward +def trophy_harvest(env, mortality): + # self.vulb = sum(p["harvest_vul"] * n * p["wt"]) + # self.vbobs = self.vulb # could multiply this by random deviate # now done in env.update_vuls() + p = env.parameters + # env.ssb = sum(p["mwt"] * env.state) # now done in env.update_ssb() + + # Side effect portion of fn (tbd: discuss - abar and wbar not otherwise used in env) + # + if (sum(env.state) > 0) and (sum(env.state * p["wt"]) > 0): + env.abar = ( + sum(p["survey_vul"] * np.array(p["ages"]) * env.state) + / sum(env.state) + ) + env.wbar = ( + sum(p["survey_vul"] * p["wt"] * env.state) + / sum(env.state * p["wt"]) + ) + else: + env.abar = 0 + env.wbar = 0 + # + age_resolved_harvests = mortality[0] * env.harv_vul_pop + new_state = p['s'] * (env.state - age_resolved_harvests) + # + n_trophy_ages = 5 + trophy_reward_dist = np.array( + (env.parameters['n_age'] - n_trophy_ages) * [0] + + n_trophy_ages * [1] + ) + reward = sum(trophy_reward_dist * age_resolved_harvests) + return new_state, reward + def get_r_devs(n_year, p_big=0.05, sdr=0.3, rho=0): """ f(x) to create recruitment deviates, which are multiplied From 0b363e5de767305b5550d64cbb47c36381341458 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 00:04:38 +0000 Subject: [PATCH 35/64] hyperpars --- hyperpars/ppo-asm.yml | 14 ++++++-------- hyperpars/tqc-asm.yml | 9 +++++---- 2 files changed, 11 insertions(+), 12 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 40a4f3e..f997c7d 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,6 +1,6 @@ # algo algo: "PPO" -total_timesteps: 5000000 +total_timesteps: 10000000 algo_config: tensorboard_log: "../../../logs" # @@ -13,12 +13,8 @@ algo_config: # gae_lambda: 0.9 # max_grad_norm: 5 # vf_coef: 0.19 - # use_sde: True # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - # in policy_kwargs: net_arch=[400, 300] - # policy: 'MlpPolicy' - # use_sde: True - # policy_kwargs: "dict(log_std_init=-3, net_arch=[400, 300])" + use_sde: True # clip_range: 0.1 # env @@ -27,6 +23,7 @@ config: observation_fn_id: 'observe_2o' n_observs: 2 harvest_fn_name: "trophy" + n_trophy_ages: 10 # upow: 0.6 # use_custom_harv_vul: True # use_custom_surv_vul: True @@ -34,8 +31,9 @@ n_envs: 12 # io repo: "cboettig/rl-ecology" -save_path: "../saved_agents" +save_path: "../saved_agents/results/" # misc -id: "trophy-basehyperpars" +id: "results-trophy-nage-10" +# id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/tqc-asm.yml b/hyperpars/tqc-asm.yml index 56756a1..bb35f04 100644 --- a/hyperpars/tqc-asm.yml +++ b/hyperpars/tqc-asm.yml @@ -12,8 +12,8 @@ algo_config: # tau: 0.02 # train_freq: 64 # gradient_steps: 64 - # learning_starts: 20000 - # use_sde: True + # learning_starts: 30000 + use_sde: True # policy_kwargs: "dict(log_std_init=-3, net_arch=[128, 64])" # env @@ -22,6 +22,7 @@ config: observation_fn_id: 'observe_2o' n_observs: 2 harvest_fn_name: "trophy" + n_trophy_ages: 10 # upow: 0.6 # use_custom_harv_vul: True # use_custom_surv_vul: True @@ -29,8 +30,8 @@ n_envs: 12 # io repo: "cboettig/rl-ecology" -save_path: "../saved_agents" +save_path: "../saved_agents/results" # misc -id: "trophy-basehyperpars" +id: "results-trophy-nage-10" additional_imports: ["torch"] From a4fe73d2c6e562199c01e7488c62d8b20e56aa42 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 00:05:12 +0000 Subject: [PATCH 36/64] now n_trophy_ages is an input parameter --- src/rl4fisheries/envs/asm_env.py | 2 ++ src/rl4fisheries/envs/asm_fns.py | 5 ++--- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index af89a2c..50d48e0 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -112,6 +112,8 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): HARV_FNS = {'default': harvest, 'trophy': trophy_harvest} self.harv_fn_name = config.get("harvest_fn_name", "default") self._harvest_fn = HARV_FNS[self.harv_fn_name] + if self.harv_fn_name == 'trophy': + self.n_trophy_ages = config.get("n_trophy_ages", 10) self._pop_growth_fn = config.get("pop_growth_fn", asm_pop_growth) self._render_fn = config.get("render_fn", render_asm) diff --git a/src/rl4fisheries/envs/asm_fns.py b/src/rl4fisheries/envs/asm_fns.py index 698f1dd..557d061 100644 --- a/src/rl4fisheries/envs/asm_fns.py +++ b/src/rl4fisheries/envs/asm_fns.py @@ -159,10 +159,9 @@ def trophy_harvest(env, mortality): age_resolved_harvests = mortality[0] * env.harv_vul_pop new_state = p['s'] * (env.state - age_resolved_harvests) # - n_trophy_ages = 5 trophy_reward_dist = np.array( - (env.parameters['n_age'] - n_trophy_ages) * [0] - + n_trophy_ages * [1] + (env.parameters['n_age'] - env.n_trophy_ages) * [0] + + env.n_trophy_ages * [1] ) reward = sum(trophy_reward_dist * age_resolved_harvests) return new_state, reward From da45ca0da6efec5901cd60387e536bfbd1e7f179 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 00:05:57 +0000 Subject: [PATCH 37/64] training script/util handles hf properly now --- scripts/train.py | 20 +++++++++++++++++++- src/rl4fisheries/utils/sb3.py | 2 +- 2 files changed, 20 insertions(+), 2 deletions(-) diff --git a/scripts/train.py b/scripts/train.py index 9b40f1e..9708894 100644 --- a/scripts/train.py +++ b/scripts/train.py @@ -11,6 +11,10 @@ import rl4fisheries from rl4fisheries.utils import sb3_train +# hf login +from huggingface_hub import hf_hub_download, HfApi, login +login() + import os # transform to absolute file path @@ -22,4 +26,18 @@ os.chdir(dname) # train -sb3_train(abs_filepath, progress_bar = args.progress_bar) +save_id, options = sb3_train(abs_filepath, progress_bar = args.progress_bar) +fname = os.path.basename(save_id) + +# hf upload +api = HfApi() +try: + api.upload_file( + path_or_fileobj=save_id, + path_in_repo="sb3/rl4fisheries/"+fname, + repo_id="boettiger-lab/rl4eco", + repo_type="model", + ) +except Exception as ex: + print("Couldn't upload to hf :(.") + print(ex) diff --git a/src/rl4fisheries/utils/sb3.py b/src/rl4fisheries/utils/sb3.py index d07ef31..be59ed1 100644 --- a/src/rl4fisheries/utils/sb3.py +++ b/src/rl4fisheries/utils/sb3.py @@ -104,7 +104,7 @@ def sb3_train(config_file, **kwargs): if "id" in options: options["id"] = "-" + options["id"] model_id = options["algo"] + "-" + options["env_id"] + options.get("id", "") - save_id = os.path.join(options["save_path"], model_id) + save_id = os.path.join(options["save_path"], model_id) + ".zip" model = ALGO( env=env, From 1f24258ce49d08ba2d944120e7b0927463e1b6b4 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 00:07:10 +0000 Subject: [PATCH 38/64] simulator not remote now --- src/rl4fisheries/utils/simulation.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/rl4fisheries/utils/simulation.py b/src/rl4fisheries/utils/simulation.py index 484e0db..c21778f 100644 --- a/src/rl4fisheries/utils/simulation.py +++ b/src/rl4fisheries/utils/simulation.py @@ -18,7 +18,7 @@ def evaluate(self, return_episode_rewards=False, n_eval_episodes=50): ray.shutdown() else: rewards = [ - self.simulator.remote(env=self.env, agent=self.agent) + self.simulator(env=self.env, agent=self.agent) for _ in range(n_eval_episodes) ] # @@ -37,7 +37,7 @@ def simulator(env, agent): episode_reward = 0.0 observation, _ = env.reset() for t in range(env.Tmax): - action, _ = agent.predict(observation, deterministic=True) + action = agent.predict(observation, deterministic=True)[0] observation, reward, terminated, done, info = env.step(action) episode_reward += reward if terminated or done: From 5a0d925ca4647a26d4fb619044edbe909811ff0c Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 00:07:45 +0000 Subject: [PATCH 39/64] notebooks --- .../optimal-fixed-policy-cases-results.ipynb | 17092 ++++++++++++++++ notebooks/optimal-fixed-policy.ipynb | 3544 +++- 2 files changed, 19504 insertions(+), 1132 deletions(-) create mode 100644 notebooks/optimal-fixed-policy-cases-results.ipynb diff --git a/notebooks/optimal-fixed-policy-cases-results.ipynb b/notebooks/optimal-fixed-policy-cases-results.ipynb new file mode 100644 index 0000000..38be570 --- /dev/null +++ b/notebooks/optimal-fixed-policy-cases-results.ipynb @@ -0,0 +1,17092 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "7ff29091-615f-4d91-8198-20d8ae2fb197", + "metadata": {}, + "source": [ + "# Finding optimal fixed policies for several cases to explore in the paper\n", + "---\n", + "## Setup" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "d11f82f4-1819-452a-8174-0808cdcb7c8f", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import ray\n", + "\n", + "from skopt import gp_minimize, gbrt_minimize \n", + "from skopt import dump\n", + "from skopt.plots import plot_objective, plot_convergence\n", + "from skopt.space import Real\n", + "from skopt.utils import use_named_args\n", + "\n", + "from stable_baselines3.common.evaluation import evaluate_policy\n", + "from stable_baselines3.common.monitor import Monitor\n", + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.envs.asm_fns import get_r_devs, observe_total" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "716cd9fe-37cc-4b0e-b25a-813a1fe7c49c", + "metadata": {}, + "outputs": [], + "source": [ + "@ray.remote\n", + "def generate_rew(policy, env_cls, config):\n", + " ep_rew = 0\n", + " env = env_cls(config=config)\n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, info = policy.predict(obs)\n", + " obs, rew, term, trunc, info = env.step(act)\n", + " ep_rew += rew\n", + " return ep_rew\n", + "\n", + "\n", + "def rew_batch(policy, env_cls, config, batch_size):\n", + " tmax = env_cls().Tmax\n", + " parallel = [generate_rew.remote(policy, env_cls, config) for _ in range(batch_size)]\n", + " rews = ray.get(parallel)\n", + " if ray.is_initialized():\n", + " ray.shutdown()\n", + " return rews\n", + "\n", + "def eval_pol(policy, env_cls, config, n_batches=4, batch_size=40, pb=False):\n", + " batch_iter = range(n_batches)\n", + " if pb:\n", + " from tqdm import tqdm\n", + " batch_iter = tqdm(iter)\n", + " #\n", + " rews = []\n", + " for i in batch_iter:\n", + " rews.append(\n", + " rew_batch(policy=policy, env_cls=env_cls, config=config, batch_size=batch_size)\n", + " )\n", + " return np.array(rews).flatten()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "80aa7183-0fb0-4a0e-a112-ffa536334413", + "metadata": {}, + "outputs": [], + "source": [ + "msy_space = [Real(0.001, 0.25, name='mortality')]\n", + "log_esc_space = [Real(-6, 2, name='log_escapement')]\n", + "cr_space = [\n", + " Real(-5, 2, name='log_radius'),\n", + " Real(- np.pi/4.00001, np.pi/4.00001, name='theta'),\n", + " Real(0, 0.3, name='y2'),\n", + "]\n", + "def msy_obj_generator(config):\n", + " @use_named_args(msy_space)\n", + " def msy_obj(**x):\n", + " eval_env = AsmEnv(config=config)\n", + " agent = Msy(env=eval_env, mortality = x['mortality'])\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, config=config, \n", + " n_batches=1, batch_size=200\n", + " )\n", + " return -np.mean(rews)\n", + " return msy_obj\n", + "\n", + "def esc_obj_generator(config):\n", + " @use_named_args(log_esc_space)\n", + " def esc_obj(**x):\n", + " eval_env = AsmEnv(config=config)\n", + " escapement = 10 ** x['log_escapement']\n", + " agent = ConstEsc(env=eval_env, escapement = escapement)\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, config=config, \n", + " n_batches=1, batch_size=200\n", + " )\n", + " return -np.mean(rews)\n", + " return esc_obj\n", + "\n", + "def cr_obj_generator(config):\n", + " @use_named_args(cr_space)\n", + " def cr_obj(**x):\n", + " theta = x[\"theta\"]\n", + " radius = 10 ** x[\"log_radius\"]\n", + " x1 = np.sin(theta) * radius\n", + " x2 = np.cos(theta) * radius\n", + " #\n", + " eval_env = AsmEnv(config=config)\n", + " eval_env.reset()\n", + " agent = CautionaryRule(env=eval_env, x1 = x1, x2 = x2, y2 = x[\"y2\"])\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnv, \n", + " config=config, \n", + " n_batches=1, batch_size=200\n", + " )\n", + " return -np.mean(rews)\n", + " return cr_obj" + ] + }, + { + "cell_type": "markdown", + "id": "8226ea99-2cf1-494f-8335-365c036f43ac", + "metadata": {}, + "source": [ + "## upow=0.6, non-trophy fishing" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "800575c8-7adf-4afb-9d1e-095148727fa0", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG1 = {\n", + " \"upow\": 0.6\n", + "}\n", + "\n", + "cr_obj1 = cr_obj_generator(CONFIG1)\n", + "esc_obj1 = esc_obj_generator(CONFIG1)\n", + "msy_obj1 = msy_obj_generator(CONFIG1)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "a9cc0d3d-66de-49fa-910a-7731bba0a8aa", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:06,448\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 7.1426\n", + "Function value obtained: -50.2248\n", + "Current minimum: -50.2248\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:13,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 7.2930\n", + "Function value obtained: -100.0810\n", + "Current minimum: -100.0810\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:20,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 6.9121\n", + "Function value obtained: -40.3280\n", + "Current minimum: -100.0810\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:27,708\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 7.0030\n", + "Function value obtained: -75.6427\n", + "Current minimum: -100.0810\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:34,746\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 7.0246\n", + "Function value obtained: -13.8655\n", + "Current minimum: -100.0810\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:41,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 7.1452\n", + "Function value obtained: -23.8341\n", + "Current minimum: -100.0810\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:48,925\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 6.9714\n", + "Function value obtained: -133.4123\n", + "Current minimum: -133.4123\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:55:55,992\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 7.2094\n", + "Function value obtained: -44.7161\n", + "Current minimum: -133.4123\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:03,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 7.0324\n", + "Function value obtained: -10.0156\n", + "Current minimum: -133.4123\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:10,134\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 7.4595\n", + "Function value obtained: -0.0036\n", + "Current minimum: -133.4123\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:17,575\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 7.3179\n", + "Function value obtained: -0.0000\n", + "Current minimum: -133.4123\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:24,887\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 7.2691\n", + "Function value obtained: -131.0600\n", + "Current minimum: -133.4123\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:33,250\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7377\n", + "Function value obtained: -61.4294\n", + "Current minimum: -133.4123\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:40,944\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4950\n", + "Function value obtained: -131.3133\n", + "Current minimum: -133.4123\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:48,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5838\n", + "Function value obtained: -135.3706\n", + "Current minimum: -135.3706\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:56:56,022\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6447\n", + "Function value obtained: -137.0071\n", + "Current minimum: -137.0071\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:03,674\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5230\n", + "Function value obtained: -138.9258\n", + "Current minimum: -138.9258\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:11,201\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5191\n", + "Function value obtained: -135.8094\n", + "Current minimum: -138.9258\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:18,725\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5404\n", + "Function value obtained: -132.4386\n", + "Current minimum: -138.9258\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:26,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7329\n", + "Function value obtained: -136.2971\n", + "Current minimum: -138.9258\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:34,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6322\n", + "Function value obtained: -140.0636\n", + "Current minimum: -140.0636\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:41,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5808\n", + "Function value obtained: -141.1176\n", + "Current minimum: -141.1176\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:49,269\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6479\n", + "Function value obtained: -142.4183\n", + "Current minimum: -142.4183\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:57:56,915\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8256\n", + "Function value obtained: -138.9429\n", + "Current minimum: -142.4183\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:04,712\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8529\n", + "Function value obtained: -138.5246\n", + "Current minimum: -142.4183\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:12,597\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8736\n", + "Function value obtained: -131.4659\n", + "Current minimum: -142.4183\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:20,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7868\n", + "Function value obtained: -146.7316\n", + "Current minimum: -146.7316\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:28,233\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9675\n", + "Function value obtained: -149.3556\n", + "Current minimum: -149.3556\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:36,231\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7273\n", + "Function value obtained: -149.8641\n", + "Current minimum: -149.8641\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:43,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9885\n", + "Function value obtained: -148.2691\n", + "Current minimum: -149.8641\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:51,942\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7775\n", + "Function value obtained: -145.5978\n", + "Current minimum: -149.8641\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:58:59,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7742\n", + "Function value obtained: -145.9430\n", + "Current minimum: -149.8641\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:59:07,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6758\n", + "Function value obtained: -145.8356\n", + "Current minimum: -149.8641\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:59:15,208\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0398\n", + "Function value obtained: -0.0000\n", + "Current minimum: -149.8641\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:59:23,245\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8355\n", + "Function value obtained: -123.7036\n", + "Current minimum: -149.8641\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:59:31,113\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9280\n", + "Function value obtained: -146.8933\n", + "Current minimum: -149.8641\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:59:40,058\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6553\n", + "Function value obtained: -96.2864\n", + "Current minimum: -149.8641\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:59:47,710\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9087\n", + "Function value obtained: -18.2684\n", + "Current minimum: -149.8641\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 17:59:55,578\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8215\n", + "Function value obtained: -143.3425\n", + "Current minimum: -149.8641\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:00:03,438\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9729\n", + "Function value obtained: -144.0208\n", + "Current minimum: -149.8641\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:00:11,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9140\n", + "Function value obtained: -59.0199\n", + "Current minimum: -149.8641\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:00:19,314\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7575\n", + "Function value obtained: -0.0000\n", + "Current minimum: -149.8641\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:00:27,090\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1577\n", + "Function value obtained: -102.7227\n", + "Current minimum: -149.8641\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:00:36,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9665\n", + "Function value obtained: -146.7394\n", + "Current minimum: -149.8641\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:00:44,188\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9532\n", + "Function value obtained: -146.6516\n", + "Current minimum: -149.8641\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:00:53,184\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2294\n", + "Function value obtained: -148.3380\n", + "Current minimum: -149.8641\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:01,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0417\n", + "Function value obtained: -141.8872\n", + "Current minimum: -149.8641\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:09,451\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2552\n", + "Function value obtained: -148.2297\n", + "Current minimum: -149.8641\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:17,766\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0794\n", + "Function value obtained: -146.6327\n", + "Current minimum: -149.8641\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:25,818\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4322\n", + "Function value obtained: -145.1000\n", + "Current minimum: -149.8641\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:34,245\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8712\n", + "Function value obtained: -147.2085\n", + "Current minimum: -149.8641\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:42,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4857\n", + "Function value obtained: -146.0308\n", + "Current minimum: -149.8641\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:50,642\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1465\n", + "Function value obtained: -143.2042\n", + "Current minimum: -149.8641\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:01:58,789\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3069\n", + "Function value obtained: -147.6975\n", + "Current minimum: -149.8641\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:02:07,078\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1248\n", + "Function value obtained: -146.0510\n", + "Current minimum: -149.8641\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:02:15,255\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8741\n", + "Function value obtained: -146.7015\n", + "Current minimum: -149.8641\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:02:23,104\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9997\n", + "Function value obtained: -147.0754\n", + "Current minimum: -149.8641\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:02:31,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1482\n", + "Function value obtained: -142.8745\n", + "Current minimum: -149.8641\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:02:39,233\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9888\n", + "Function value obtained: -151.0266\n", + "Current minimum: -151.0266\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:02:48,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0642\n", + "Function value obtained: -149.0134\n", + "Current minimum: -151.0266\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:02:56,321\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0512\n", + "Function value obtained: -149.8404\n", + "Current minimum: -151.0266\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:03:04,355\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2602\n", + "Function value obtained: -147.3890\n", + "Current minimum: -151.0266\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:03:12,642\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5360\n", + "Function value obtained: -144.6945\n", + "Current minimum: -151.0266\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:03:21,182\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2329\n", + "Function value obtained: -146.6455\n", + "Current minimum: -151.0266\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:03:29,392\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0400\n", + "Function value obtained: -146.3620\n", + "Current minimum: -151.0266\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:03:38,446\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0667\n", + "Function value obtained: -147.1161\n", + "Current minimum: -151.0266\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:03:46,598\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2680\n", + "Function value obtained: -147.8922\n", + "Current minimum: -151.0266\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:03:54,797\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0775\n", + "Function value obtained: -149.2322\n", + "Current minimum: -151.0266\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:04:03,866\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1962\n", + "Function value obtained: -145.0572\n", + "Current minimum: -151.0266\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:04:13,070\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1596\n", + "Function value obtained: -143.8009\n", + "Current minimum: -151.0266\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:04:21,253\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1386\n", + "Function value obtained: -146.0845\n", + "Current minimum: -151.0266\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:04:30,346\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3585\n", + "Function value obtained: -145.9828\n", + "Current minimum: -151.0266\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:04:38,749\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1646\n", + "Function value obtained: -146.7597\n", + "Current minimum: -151.0266\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:04:47,936\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2258\n", + "Function value obtained: -147.4701\n", + "Current minimum: -151.0266\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:04:56,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5693\n", + "Function value obtained: -145.4419\n", + "Current minimum: -151.0266\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:05:04,728\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5831\n", + "Function value obtained: -147.1113\n", + "Current minimum: -151.0266\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:05:13,313\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5982\n", + "Function value obtained: -142.1284\n", + "Current minimum: -151.0266\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:05:21,932\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2327\n", + "Function value obtained: -145.6544\n", + "Current minimum: -151.0266\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:05:31,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3888\n", + "Function value obtained: -148.4968\n", + "Current minimum: -151.0266\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:05:39,547\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3289\n", + "Function value obtained: -146.2288\n", + "Current minimum: -151.0266\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:05:48,908\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2651\n", + "Function value obtained: -147.4892\n", + "Current minimum: -151.0266\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:05:58,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7033\n", + "Function value obtained: -144.5124\n", + "Current minimum: -151.0266\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:06:06,856\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5694\n", + "Function value obtained: -147.1889\n", + "Current minimum: -151.0266\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:06:15,440\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2216\n", + "Function value obtained: -145.0250\n", + "Current minimum: -151.0266\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:06:24,727\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7992\n", + "Function value obtained: -146.3057\n", + "Current minimum: -151.0266\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:06:33,451\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2868\n", + "Function value obtained: -147.3213\n", + "Current minimum: -151.0266\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:06:42,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6152\n", + "Function value obtained: -147.7221\n", + "Current minimum: -151.0266\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:06:51,381\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4433\n", + "Function value obtained: -145.4214\n", + "Current minimum: -151.0266\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:07:00,830\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3968\n", + "Function value obtained: -147.6219\n", + "Current minimum: -151.0266\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:07:10,196\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8338\n", + "Function value obtained: -147.6337\n", + "Current minimum: -151.0266\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:07:19,058\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9760\n", + "Function value obtained: -146.3274\n", + "Current minimum: -151.0266\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:07:28,031\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3455\n", + "Function value obtained: -144.4779\n", + "Current minimum: -151.0266\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:07:37,416\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4949\n", + "Function value obtained: -145.8979\n", + "Current minimum: -151.0266\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:07:46,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3499\n", + "Function value obtained: -144.4805\n", + "Current minimum: -151.0266\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:07:56,276\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6696\n", + "Function value obtained: -144.4206\n", + "Current minimum: -151.0266\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:08:05,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4384\n", + "Function value obtained: -148.4113\n", + "Current minimum: -151.0266\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:08:15,344\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3791\n", + "Function value obtained: -147.8722\n", + "Current minimum: -151.0266\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:08:24,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5231\n", + "Function value obtained: -143.9188\n", + "Current minimum: -151.0266\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:08:34,269\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7191\n", + "Function value obtained: -146.1422\n", + "Current minimum: -151.0266\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:08:44,000\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4630\n", + "Function value obtained: -146.4104\n", + "Current minimum: -151.0266\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:08:53,464\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 8.5263\n", + "Function value obtained: -3.1148\n", + "Current minimum: -3.1148\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:02,040\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 7.9127\n", + "Function value obtained: -100.4878\n", + "Current minimum: -100.4878\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:09,954\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 7.9788\n", + "Function value obtained: -5.2865\n", + "Current minimum: -100.4878\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:17,946\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 8.6109\n", + "Function value obtained: -43.6996\n", + "Current minimum: -100.4878\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:26,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 8.5982\n", + "Function value obtained: -98.7542\n", + "Current minimum: -100.4878\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:35,160\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 8.8102\n", + "Function value obtained: -7.9154\n", + "Current minimum: -100.4878\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:43,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 7.8920\n", + "Function value obtained: -8.4514\n", + "Current minimum: -100.4878\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:51,869\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 8.0056\n", + "Function value obtained: -32.3352\n", + "Current minimum: -100.4878\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:09:59,867\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 8.5909\n", + "Function value obtained: -6.4695\n", + "Current minimum: -100.4878\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:10:08,470\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 8.2068\n", + "Function value obtained: -81.0671\n", + "Current minimum: -100.4878\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:10:16,686\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0693\n", + "Function value obtained: -109.5436\n", + "Current minimum: -109.5436\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:10:25,768\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1009\n", + "Function value obtained: -110.8605\n", + "Current minimum: -110.8605\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:10:34,908\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3745\n", + "Function value obtained: -110.1220\n", + "Current minimum: -110.8605\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:10:44,216\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3563\n", + "Function value obtained: -2.7774\n", + "Current minimum: -110.8605\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:10:53,620\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1550\n", + "Function value obtained: -109.1802\n", + "Current minimum: -110.8605\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:11:02,813\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2128\n", + "Function value obtained: -110.1629\n", + "Current minimum: -110.8605\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:11:11,965\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9456\n", + "Function value obtained: -108.1219\n", + "Current minimum: -110.8605\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:11:20,930\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9004\n", + "Function value obtained: -109.3257\n", + "Current minimum: -110.8605\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:11:29,817\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0523\n", + "Function value obtained: -110.5202\n", + "Current minimum: -110.8605\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:11:38,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0686\n", + "Function value obtained: -108.1390\n", + "Current minimum: -110.8605\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:11:47,961\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2281\n", + "Function value obtained: -111.1747\n", + "Current minimum: -111.1747\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:11:56,224\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1119\n", + "Function value obtained: -110.5373\n", + "Current minimum: -111.1747\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:12:05,328\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0879\n", + "Function value obtained: -106.8115\n", + "Current minimum: -111.1747\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:12:14,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5319\n", + "Function value obtained: -108.8923\n", + "Current minimum: -111.1747\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:12:22,925\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3492\n", + "Function value obtained: -110.6728\n", + "Current minimum: -111.1747\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:12:31,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8975\n", + "Function value obtained: -106.7525\n", + "Current minimum: -111.1747\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:12:40,175\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1815\n", + "Function value obtained: -111.4289\n", + "Current minimum: -111.4289\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:12:49,393\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5026\n", + "Function value obtained: -109.1199\n", + "Current minimum: -111.4289\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:12:57,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1353\n", + "Function value obtained: -107.6682\n", + "Current minimum: -111.4289\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:13:07,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9578\n", + "Function value obtained: -112.1221\n", + "Current minimum: -112.1221\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:13:15,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1668\n", + "Function value obtained: -109.1704\n", + "Current minimum: -112.1221\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:13:25,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4409\n", + "Function value obtained: -106.2691\n", + "Current minimum: -112.1221\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:13:34,634\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1184\n", + "Function value obtained: -113.3081\n", + "Current minimum: -113.3081\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:13:43,751\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2273\n", + "Function value obtained: -108.3703\n", + "Current minimum: -113.3081\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:13:52,955\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1702\n", + "Function value obtained: -109.6190\n", + "Current minimum: -113.3081\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:14:02,106\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2777\n", + "Function value obtained: -109.8952\n", + "Current minimum: -113.3081\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:14:11,452\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2352\n", + "Function value obtained: -111.6577\n", + "Current minimum: -113.3081\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:14:20,673\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1924\n", + "Function value obtained: -109.6728\n", + "Current minimum: -113.3081\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:14:29,878\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1180\n", + "Function value obtained: -110.6084\n", + "Current minimum: -113.3081\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:14:39,025\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3525\n", + "Function value obtained: -106.4812\n", + "Current minimum: -113.3081\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:14:48,378\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1724\n", + "Function value obtained: -111.7625\n", + "Current minimum: -113.3081\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:14:57,599\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4404\n", + "Function value obtained: -109.5424\n", + "Current minimum: -113.3081\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:15:06,980\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2450\n", + "Function value obtained: -109.6388\n", + "Current minimum: -113.3081\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:15:16,266\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3724\n", + "Function value obtained: -111.0515\n", + "Current minimum: -113.3081\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:15:25,644\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3912\n", + "Function value obtained: -106.5638\n", + "Current minimum: -113.3081\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:15:35,007\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3482\n", + "Function value obtained: -109.9455\n", + "Current minimum: -113.3081\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:15:44,332\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3430\n", + "Function value obtained: -110.1465\n", + "Current minimum: -113.3081\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:15:53,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5137\n", + "Function value obtained: -108.0023\n", + "Current minimum: -113.3081\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:16:03,240\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4510\n", + "Function value obtained: -109.0760\n", + "Current minimum: -113.3081\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:16:13,660\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3444\n", + "Function value obtained: -109.7235\n", + "Current minimum: -113.3081\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:16:23,019\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4180\n", + "Function value obtained: -108.2542\n", + "Current minimum: -113.3081\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:16:32,429\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7001\n", + "Function value obtained: -112.5849\n", + "Current minimum: -113.3081\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:16:42,145\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0735\n", + "Function value obtained: -105.9648\n", + "Current minimum: -113.3081\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:16:51,223\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3049\n", + "Function value obtained: -104.6931\n", + "Current minimum: -113.3081\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:17:00,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1241\n", + "Function value obtained: -109.6909\n", + "Current minimum: -113.3081\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:17:10,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4527\n", + "Function value obtained: -107.6980\n", + "Current minimum: -113.3081\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:17:20,127\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3407\n", + "Function value obtained: -109.3408\n", + "Current minimum: -113.3081\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:17:29,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1528\n", + "Function value obtained: -110.0202\n", + "Current minimum: -113.3081\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:17:38,635\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2478\n", + "Function value obtained: -108.3832\n", + "Current minimum: -113.3081\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:17:47,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8375\n", + "Function value obtained: -108.9196\n", + "Current minimum: -113.3081\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:17:57,733\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4495\n", + "Function value obtained: -109.2279\n", + "Current minimum: -113.3081\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:18:07,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5630\n", + "Function value obtained: -110.3166\n", + "Current minimum: -113.3081\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:18:17,760\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3607\n", + "Function value obtained: -112.1051\n", + "Current minimum: -113.3081\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:18:27,112\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5396\n", + "Function value obtained: -110.6268\n", + "Current minimum: -113.3081\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:18:36,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3452\n", + "Function value obtained: -108.8991\n", + "Current minimum: -113.3081\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:18:45,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6449\n", + "Function value obtained: -107.6218\n", + "Current minimum: -113.3081\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:18:55,686\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5317\n", + "Function value obtained: -109.5969\n", + "Current minimum: -113.3081\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:19:05,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0276\n", + "Function value obtained: -107.6892\n", + "Current minimum: -113.3081\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:19:15,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6048\n", + "Function value obtained: -106.5261\n", + "Current minimum: -113.3081\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:19:24,860\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8810\n", + "Function value obtained: -105.0934\n", + "Current minimum: -113.3081\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:19:34,742\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5930\n", + "Function value obtained: -109.4023\n", + "Current minimum: -113.3081\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:19:44,353\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4152\n", + "Function value obtained: -111.5302\n", + "Current minimum: -113.3081\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:19:54,797\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8567\n", + "Function value obtained: -111.2069\n", + "Current minimum: -113.3081\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:20:04,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8912\n", + "Function value obtained: -109.4680\n", + "Current minimum: -113.3081\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:20:15,529\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8526\n", + "Function value obtained: -109.8335\n", + "Current minimum: -113.3081\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:20:25,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7092\n", + "Function value obtained: -109.6025\n", + "Current minimum: -113.3081\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:20:35,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6532\n", + "Function value obtained: -106.9613\n", + "Current minimum: -113.3081\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:20:44,752\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9265\n", + "Function value obtained: -110.8921\n", + "Current minimum: -113.3081\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:20:54,637\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9273\n", + "Function value obtained: -106.4988\n", + "Current minimum: -113.3081\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:21:05,626\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5533\n", + "Function value obtained: -106.9844\n", + "Current minimum: -113.3081\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:21:15,137\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8004\n", + "Function value obtained: -112.6856\n", + "Current minimum: -113.3081\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:21:24,993\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8939\n", + "Function value obtained: -106.2492\n", + "Current minimum: -113.3081\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:21:34,909\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1197\n", + "Function value obtained: -110.9822\n", + "Current minimum: -113.3081\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:21:45,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9651\n", + "Function value obtained: -110.7704\n", + "Current minimum: -113.3081\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:21:54,974\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1038\n", + "Function value obtained: -108.1396\n", + "Current minimum: -113.3081\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:22:05,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6300\n", + "Function value obtained: -108.5247\n", + "Current minimum: -113.3081\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:22:14,775\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3881\n", + "Function value obtained: -108.0111\n", + "Current minimum: -113.3081\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:22:25,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0992\n", + "Function value obtained: -109.6469\n", + "Current minimum: -113.3081\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:22:35,200\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2008\n", + "Function value obtained: -110.2677\n", + "Current minimum: -113.3081\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:22:45,367\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6477\n", + "Function value obtained: -110.3927\n", + "Current minimum: -113.3081\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:22:55,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9332\n", + "Function value obtained: -110.6995\n", + "Current minimum: -113.3081\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:23:05,017\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2438\n", + "Function value obtained: -108.0380\n", + "Current minimum: -113.3081\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:23:15,240\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1308\n", + "Function value obtained: -109.5009\n", + "Current minimum: -113.3081\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:23:25,355\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1166\n", + "Function value obtained: -109.2512\n", + "Current minimum: -113.3081\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:23:35,505\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0187\n", + "Function value obtained: -109.6719\n", + "Current minimum: -113.3081\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:23:45,544\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2409\n", + "Function value obtained: -106.2462\n", + "Current minimum: -113.3081\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:23:56,743\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2279\n", + "Function value obtained: -107.9563\n", + "Current minimum: -113.3081\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:24:06,960\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4646\n", + "Function value obtained: -110.8636\n", + "Current minimum: -113.3081\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:24:17,441\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4714\n", + "Function value obtained: -108.2392\n", + "Current minimum: -113.3081\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:24:27,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1199\n", + "Function value obtained: -108.1512\n", + "Current minimum: -113.3081\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:24:38,053\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 10.0648\n", + "Function value obtained: -17.6242\n", + "Current minimum: -17.6242\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:24:48,179\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 9.2865\n", + "Function value obtained: -17.5461\n", + "Current minimum: -17.6242\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:24:57,430\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 9.5097\n", + "Function value obtained: -37.2531\n", + "Current minimum: -37.2531\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:25:06,971\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 9.5651\n", + "Function value obtained: -121.9332\n", + "Current minimum: -121.9332\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:25:16,650\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 9.6386\n", + "Function value obtained: -27.4291\n", + "Current minimum: -121.9332\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:25:26,197\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 9.8095\n", + "Function value obtained: -109.6144\n", + "Current minimum: -121.9332\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:25:36,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.4082\n", + "Function value obtained: -62.5131\n", + "Current minimum: -121.9332\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:25:45,425\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 9.6892\n", + "Function value obtained: -25.3334\n", + "Current minimum: -121.9332\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:25:55,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 9.8643\n", + "Function value obtained: -73.6274\n", + "Current minimum: -121.9332\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:26:04,977\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 9.6215\n", + "Function value obtained: -11.9736\n", + "Current minimum: -121.9332\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:26:14,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9584\n", + "Function value obtained: -120.6884\n", + "Current minimum: -121.9332\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:26:24,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7566\n", + "Function value obtained: -121.4256\n", + "Current minimum: -121.9332\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:26:34,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7532\n", + "Function value obtained: -123.2711\n", + "Current minimum: -123.2711\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:26:44,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9136\n", + "Function value obtained: -119.5122\n", + "Current minimum: -123.2711\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:26:53,972\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8257\n", + "Function value obtained: -122.9657\n", + "Current minimum: -123.2711\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:27:03,845\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7340\n", + "Function value obtained: -125.2013\n", + "Current minimum: -125.2013\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:27:13,622\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8894\n", + "Function value obtained: -123.6988\n", + "Current minimum: -125.2013\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:27:23,424\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7726\n", + "Function value obtained: -124.8692\n", + "Current minimum: -125.2013\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:27:33,187\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6934\n", + "Function value obtained: -122.4800\n", + "Current minimum: -125.2013\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:27:42,968\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9766\n", + "Function value obtained: -124.7319\n", + "Current minimum: -125.2013\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:27:52,952\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1488\n", + "Function value obtained: -122.1076\n", + "Current minimum: -125.2013\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:28:03,055\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5009\n", + "Function value obtained: -8.8643\n", + "Current minimum: -125.2013\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:28:13,579\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7307\n", + "Function value obtained: -125.2242\n", + "Current minimum: -125.2242\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:28:23,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0418\n", + "Function value obtained: -123.6909\n", + "Current minimum: -125.2242\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:28:33,382\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9569\n", + "Function value obtained: -123.1854\n", + "Current minimum: -125.2242\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:28:43,348\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3169\n", + "Function value obtained: -124.0511\n", + "Current minimum: -125.2242\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:28:53,632\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8593\n", + "Function value obtained: -128.2024\n", + "Current minimum: -128.2024\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:29:03,496\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0411\n", + "Function value obtained: -125.8631\n", + "Current minimum: -128.2024\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:29:13,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6858\n", + "Function value obtained: -122.9178\n", + "Current minimum: -128.2024\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:29:23,342\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2887\n", + "Function value obtained: -119.8288\n", + "Current minimum: -128.2024\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:29:33,529\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8899\n", + "Function value obtained: -121.8036\n", + "Current minimum: -128.2024\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:29:43,426\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7102\n", + "Function value obtained: -124.2616\n", + "Current minimum: -128.2024\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:29:53,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8853\n", + "Function value obtained: -122.2972\n", + "Current minimum: -128.2024\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:30:03,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5582\n", + "Function value obtained: -125.4430\n", + "Current minimum: -128.2024\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:30:12,580\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9967\n", + "Function value obtained: -122.9375\n", + "Current minimum: -128.2024\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:30:22,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1173\n", + "Function value obtained: -122.7530\n", + "Current minimum: -128.2024\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:30:32,659\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1666\n", + "Function value obtained: -122.6971\n", + "Current minimum: -128.2024\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:30:42,879\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9232\n", + "Function value obtained: -124.7774\n", + "Current minimum: -128.2024\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:30:52,821\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8226\n", + "Function value obtained: -127.6329\n", + "Current minimum: -128.2024\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:31:03,602\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7612\n", + "Function value obtained: -123.4035\n", + "Current minimum: -128.2024\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:31:13,377\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7890\n", + "Function value obtained: -121.5322\n", + "Current minimum: -128.2024\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:31:23,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0559\n", + "Function value obtained: -121.3806\n", + "Current minimum: -128.2024\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:31:33,229\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1698\n", + "Function value obtained: -119.6925\n", + "Current minimum: -128.2024\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:31:43,436\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5240\n", + "Function value obtained: -124.7613\n", + "Current minimum: -128.2024\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:31:54,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9256\n", + "Function value obtained: -123.7052\n", + "Current minimum: -128.2024\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:32:03,916\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3407\n", + "Function value obtained: -124.0130\n", + "Current minimum: -128.2024\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:32:14,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9008\n", + "Function value obtained: -122.6460\n", + "Current minimum: -128.2024\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:32:24,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0070\n", + "Function value obtained: -126.5892\n", + "Current minimum: -128.2024\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:32:34,182\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4073\n", + "Function value obtained: -123.4009\n", + "Current minimum: -128.2024\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:32:44,569\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3187\n", + "Function value obtained: -121.8074\n", + "Current minimum: -128.2024\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:32:54,921\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1348\n", + "Function value obtained: -124.6643\n", + "Current minimum: -128.2024\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:33:05,067\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7630\n", + "Function value obtained: -121.6280\n", + "Current minimum: -128.2024\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:33:15,790\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4211\n", + "Function value obtained: -118.4107\n", + "Current minimum: -128.2024\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:33:26,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4146\n", + "Function value obtained: -119.7914\n", + "Current minimum: -128.2024\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:33:36,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0937\n", + "Function value obtained: -124.2212\n", + "Current minimum: -128.2024\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:33:46,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6871\n", + "Function value obtained: -119.5058\n", + "Current minimum: -128.2024\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:33:57,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1315\n", + "Function value obtained: -122.0702\n", + "Current minimum: -128.2024\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:34:07,583\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8392\n", + "Function value obtained: -123.9594\n", + "Current minimum: -128.2024\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:34:18,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4072\n", + "Function value obtained: -122.4237\n", + "Current minimum: -128.2024\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:34:28,876\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9652\n", + "Function value obtained: -122.4054\n", + "Current minimum: -128.2024\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:34:38,793\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2593\n", + "Function value obtained: -122.6365\n", + "Current minimum: -128.2024\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:34:49,065\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4918\n", + "Function value obtained: -124.1046\n", + "Current minimum: -128.2024\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:34:59,572\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4629\n", + "Function value obtained: -122.7987\n", + "Current minimum: -128.2024\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:35:10,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1056\n", + "Function value obtained: -125.7414\n", + "Current minimum: -128.2024\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:35:20,151\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0253\n", + "Function value obtained: -121.5002\n", + "Current minimum: -128.2024\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:35:30,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3737\n", + "Function value obtained: -125.4692\n", + "Current minimum: -128.2024\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:35:40,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2547\n", + "Function value obtained: -123.6835\n", + "Current minimum: -128.2024\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:35:50,806\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9426\n", + "Function value obtained: -123.3200\n", + "Current minimum: -128.2024\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:36:00,780\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1437\n", + "Function value obtained: -121.6043\n", + "Current minimum: -128.2024\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:36:10,949\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6519\n", + "Function value obtained: -122.7514\n", + "Current minimum: -128.2024\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:36:20,917\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1888\n", + "Function value obtained: -123.8053\n", + "Current minimum: -128.2024\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:36:31,791\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1231\n", + "Function value obtained: -125.6889\n", + "Current minimum: -128.2024\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:36:41,934\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8388\n", + "Function value obtained: -127.7351\n", + "Current minimum: -128.2024\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:36:52,737\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6161\n", + "Function value obtained: -126.6123\n", + "Current minimum: -128.2024\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:37:03,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9526\n", + "Function value obtained: -122.3208\n", + "Current minimum: -128.2024\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:37:14,356\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1861\n", + "Function value obtained: -125.1156\n", + "Current minimum: -128.2024\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:37:25,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7912\n", + "Function value obtained: -123.1862\n", + "Current minimum: -128.2024\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:37:35,349\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3672\n", + "Function value obtained: -124.2510\n", + "Current minimum: -128.2024\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:37:45,683\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5638\n", + "Function value obtained: -125.1671\n", + "Current minimum: -128.2024\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:37:56,314\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8461\n", + "Function value obtained: -122.6942\n", + "Current minimum: -128.2024\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:38:07,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7002\n", + "Function value obtained: -124.6567\n", + "Current minimum: -128.2024\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:38:17,878\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9417\n", + "Function value obtained: -121.7817\n", + "Current minimum: -128.2024\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:38:28,778\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1075\n", + "Function value obtained: -120.5220\n", + "Current minimum: -128.2024\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:38:39,884\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1988\n", + "Function value obtained: -124.6843\n", + "Current minimum: -128.2024\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:38:51,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8785\n", + "Function value obtained: -120.8858\n", + "Current minimum: -128.2024\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:39:01,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6365\n", + "Function value obtained: -122.1166\n", + "Current minimum: -128.2024\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:39:12,602\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5517\n", + "Function value obtained: -123.6217\n", + "Current minimum: -128.2024\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:39:23,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5972\n", + "Function value obtained: -123.3492\n", + "Current minimum: -128.2024\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:39:33,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6335\n", + "Function value obtained: -126.9866\n", + "Current minimum: -128.2024\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:39:44,455\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4923\n", + "Function value obtained: -121.4247\n", + "Current minimum: -128.2024\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:39:54,864\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4419\n", + "Function value obtained: -123.7017\n", + "Current minimum: -128.2024\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:40:05,342\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5760\n", + "Function value obtained: -124.2262\n", + "Current minimum: -128.2024\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:40:15,925\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8301\n", + "Function value obtained: -125.8693\n", + "Current minimum: -128.2024\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:40:26,808\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9323\n", + "Function value obtained: -124.1342\n", + "Current minimum: -128.2024\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:40:37,671\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8595\n", + "Function value obtained: -123.5373\n", + "Current minimum: -128.2024\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:40:48,569\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3228\n", + "Function value obtained: -120.4915\n", + "Current minimum: -128.2024\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:40:59,894\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4824\n", + "Function value obtained: -122.1312\n", + "Current minimum: -128.2024\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:41:11,438\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7418\n", + "Function value obtained: -124.1009\n", + "Current minimum: -128.2024\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:41:22,147\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5864\n", + "Function value obtained: -124.0157\n", + "Current minimum: -128.2024\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:41:33,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3634\n", + "Function value obtained: -121.5518\n", + "Current minimum: -128.2024\n", + "CPU times: user 1h 7min 7s, sys: 1h 8min 14s, total: 2h 15min 22s\n", + "Wall time: 46min 37s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "cr_gp1 = gp_minimize(cr_obj1, cr_space, n_calls = 100, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "esc_gp1 = gp_minimize(esc_obj1, log_esc_space, n_calls = 100, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "msy_gp1 = gp_minimize(msy_obj1, msy_space, n_calls = 100, verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "7793ff2e-dc78-4900-ac38-431b5f5b201d", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "cr.: -151.03, [-0.32011410817668384, 0.03317549293764699, 0.09032157726866336] \n", + "esc: -113.31, [-0.39913963226889937]\n", + "msy: -128.20, [0.04076301400384111]\n", + "\n" + ] + } + ], + "source": [ + "print(f\"\"\"\n", + "cr.: {cr_gp1.fun:.2f}, {cr_gp1.x} \n", + "esc: {esc_gp1.fun:.2f}, {esc_gp1.x}\n", + "msy: {msy_gp1.fun:.2f}, {msy_gp1.x}\n", + "\"\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "3ea1e603-3c5d-4fbd-aefb-f3531b99a8c3", + "metadata": {}, + "outputs": [], + "source": [ + "import ray\n", + "ray.shutdown()" + ] + }, + { + "cell_type": "markdown", + "id": "acc1d2fc-e50e-40bf-bbdb-35cff1a151b4", + "metadata": {}, + "source": [ + "## upow=1, non-trophy fishing" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "8983ccaa-ee40-4161-b691-d095b51a8d57", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG2 = {\n", + " \"upow\": 1\n", + "}\n", + "\n", + "cr_obj2 = cr_obj_generator(CONFIG2)\n", + "esc_obj2 = esc_obj_generator(CONFIG2)\n", + "msy_obj2 = msy_obj_generator(CONFIG2)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "883f8c50-0897-4c2f-92d2-0a6b683d638c", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:41:45,178\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 10.0248\n", + "Function value obtained: -5.9724\n", + "Current minimum: -5.9724\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:41:55,275\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 9.8660\n", + "Function value obtained: -15.9630\n", + "Current minimum: -15.9630\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:42:05,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 11.0314\n", + "Function value obtained: -47.8077\n", + "Current minimum: -47.8077\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:42:16,166\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 9.9788\n", + "Function value obtained: -14.5273\n", + "Current minimum: -47.8077\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:42:26,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.0417\n", + "Function value obtained: -24.0273\n", + "Current minimum: -47.8077\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:42:37,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 11.2892\n", + "Function value obtained: -30.1455\n", + "Current minimum: -47.8077\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:42:47,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 10.8662\n", + "Function value obtained: -48.4105\n", + "Current minimum: -48.4105\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:42:58,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 10.1717\n", + "Function value obtained: -6.2904\n", + "Current minimum: -48.4105\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:43:08,532\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 10.5277\n", + "Function value obtained: -83.9195\n", + "Current minimum: -83.9195\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:43:19,109\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 11.4224\n", + "Function value obtained: -50.3316\n", + "Current minimum: -83.9195\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:43:30,426\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7138\n", + "Function value obtained: -36.0910\n", + "Current minimum: -83.9195\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:43:41,191\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1741\n", + "Function value obtained: -85.0784\n", + "Current minimum: -85.0784\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:43:51,369\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6964\n", + "Function value obtained: -87.0753\n", + "Current minimum: -87.0753\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:44:03,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6453\n", + "Function value obtained: -88.6745\n", + "Current minimum: -88.6745\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:44:13,714\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2225\n", + "Function value obtained: -84.4254\n", + "Current minimum: -88.6745\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:44:24,887\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2571\n", + "Function value obtained: -85.4937\n", + "Current minimum: -88.6745\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:44:36,131\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6072\n", + "Function value obtained: -83.8924\n", + "Current minimum: -88.6745\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:44:46,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5894\n", + "Function value obtained: -83.9604\n", + "Current minimum: -88.6745\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:44:57,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7857\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:45:08,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6423\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:45:19,863\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0857\n", + "Function value obtained: -82.2186\n", + "Current minimum: -88.6745\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:45:30,927\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6316\n", + "Function value obtained: -84.6019\n", + "Current minimum: -88.6745\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:45:41,622\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7340\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:45:52,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2421\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:46:02,519\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7104\n", + "Function value obtained: -84.9129\n", + "Current minimum: -88.6745\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:46:13,275\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3763\n", + "Function value obtained: -26.1337\n", + "Current minimum: -88.6745\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:46:23,691\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4086\n", + "Function value obtained: -84.0755\n", + "Current minimum: -88.6745\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:46:34,090\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4468\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:46:44,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9374\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:46:55,480\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0186\n", + "Function value obtained: -81.5174\n", + "Current minimum: -88.6745\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:47:07,522\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5568\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:47:18,142\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7516\n", + "Function value obtained: -77.7110\n", + "Current minimum: -88.6745\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:47:28,809\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6104\n", + "Function value obtained: -83.2199\n", + "Current minimum: -88.6745\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:47:39,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8024\n", + "Function value obtained: -79.7576\n", + "Current minimum: -88.6745\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:47:50,236\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5249\n", + "Function value obtained: -84.3443\n", + "Current minimum: -88.6745\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:48:00,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2010\n", + "Function value obtained: -77.2008\n", + "Current minimum: -88.6745\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:48:11,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1662\n", + "Function value obtained: -80.2271\n", + "Current minimum: -88.6745\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:48:23,175\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6192\n", + "Function value obtained: -8.5063\n", + "Current minimum: -88.6745\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:48:34,800\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8566\n", + "Function value obtained: -3.7862\n", + "Current minimum: -88.6745\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:48:45,653\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4481\n", + "Function value obtained: -3.2344\n", + "Current minimum: -88.6745\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:48:57,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2688\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:49:08,384\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7288\n", + "Function value obtained: -84.4595\n", + "Current minimum: -88.6745\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:49:19,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7063\n", + "Function value obtained: -78.4889\n", + "Current minimum: -88.6745\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:49:30,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0449\n", + "Function value obtained: -59.8454\n", + "Current minimum: -88.6745\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:49:41,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6049\n", + "Function value obtained: -73.6175\n", + "Current minimum: -88.6745\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:49:53,728\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9459\n", + "Function value obtained: -84.3413\n", + "Current minimum: -88.6745\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:50:05,445\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2590\n", + "Function value obtained: -84.9368\n", + "Current minimum: -88.6745\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:50:16,757\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7428\n", + "Function value obtained: -0.0000\n", + "Current minimum: -88.6745\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:50:28,479\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9108\n", + "Function value obtained: -81.6157\n", + "Current minimum: -88.6745\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:50:39,385\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5106\n", + "Function value obtained: -83.9244\n", + "Current minimum: -88.6745\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:50:51,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 13.3788\n", + "Function value obtained: -89.3415\n", + "Current minimum: -89.3415\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:51:03,265\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8804\n", + "Function value obtained: -86.8953\n", + "Current minimum: -89.3415\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:51:16,589\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2644\n", + "Function value obtained: -85.1525\n", + "Current minimum: -89.3415\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:51:29,555\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8981\n", + "Function value obtained: -86.7892\n", + "Current minimum: -89.3415\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:51:40,348\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1355\n", + "Function value obtained: -82.2920\n", + "Current minimum: -89.3415\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:51:51,494\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1931\n", + "Function value obtained: -86.9512\n", + "Current minimum: -89.3415\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:52:02,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2295\n", + "Function value obtained: -83.3199\n", + "Current minimum: -89.3415\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:52:13,891\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2705\n", + "Function value obtained: -83.8452\n", + "Current minimum: -89.3415\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:52:25,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1241\n", + "Function value obtained: -84.1858\n", + "Current minimum: -89.3415\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:52:36,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5172\n", + "Function value obtained: -90.2582\n", + "Current minimum: -90.2582\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:52:47,878\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5751\n", + "Function value obtained: -84.5137\n", + "Current minimum: -90.2582\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:52:59,421\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0454\n", + "Function value obtained: -87.1609\n", + "Current minimum: -90.2582\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:53:11,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2004\n", + "Function value obtained: -85.9424\n", + "Current minimum: -90.2582\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:53:22,894\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1849\n", + "Function value obtained: -86.5487\n", + "Current minimum: -90.2582\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:53:34,892\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2276\n", + "Function value obtained: -86.7229\n", + "Current minimum: -90.2582\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:53:47,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1792\n", + "Function value obtained: -85.0491\n", + "Current minimum: -90.2582\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:53:58,296\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5159\n", + "Function value obtained: -87.3644\n", + "Current minimum: -90.2582\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:54:09,842\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7261\n", + "Function value obtained: -85.6815\n", + "Current minimum: -90.2582\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:54:21,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6967\n", + "Function value obtained: -88.1699\n", + "Current minimum: -90.2582\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:54:33,364\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0597\n", + "Function value obtained: -86.3618\n", + "Current minimum: -90.2582\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:54:45,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8961\n", + "Function value obtained: -88.4223\n", + "Current minimum: -90.2582\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:54:57,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1781\n", + "Function value obtained: -83.5344\n", + "Current minimum: -90.2582\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:55:09,464\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4290\n", + "Function value obtained: -85.1680\n", + "Current minimum: -90.2582\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:55:20,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6026\n", + "Function value obtained: -84.1598\n", + "Current minimum: -90.2582\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:55:32,496\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6667\n", + "Function value obtained: -87.6237\n", + "Current minimum: -90.2582\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:55:44,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1505\n", + "Function value obtained: -88.6482\n", + "Current minimum: -90.2582\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:55:55,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0393\n", + "Function value obtained: -84.7632\n", + "Current minimum: -90.2582\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:56:07,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4367\n", + "Function value obtained: -86.1388\n", + "Current minimum: -90.2582\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:56:18,781\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3000\n", + "Function value obtained: -89.3813\n", + "Current minimum: -90.2582\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:56:31,117\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5670\n", + "Function value obtained: -88.2972\n", + "Current minimum: -90.2582\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:56:43,688\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5073\n", + "Function value obtained: -84.9865\n", + "Current minimum: -90.2582\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:56:56,137\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3699\n", + "Function value obtained: -86.3100\n", + "Current minimum: -90.2582\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:57:08,504\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7616\n", + "Function value obtained: -86.2788\n", + "Current minimum: -90.2582\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:57:20,255\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8280\n", + "Function value obtained: -88.0902\n", + "Current minimum: -90.2582\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:57:32,105\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1601\n", + "Function value obtained: -87.5204\n", + "Current minimum: -90.2582\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:57:43,326\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0240\n", + "Function value obtained: -88.1710\n", + "Current minimum: -90.2582\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:57:55,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7394\n", + "Function value obtained: -87.2143\n", + "Current minimum: -90.2582\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:58:07,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6356\n", + "Function value obtained: -84.6836\n", + "Current minimum: -90.2582\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:58:19,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6862\n", + "Function value obtained: -85.0274\n", + "Current minimum: -90.2582\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:58:32,391\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2858\n", + "Function value obtained: -85.5836\n", + "Current minimum: -90.2582\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:58:45,944\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 14.1340\n", + "Function value obtained: -88.2977\n", + "Current minimum: -90.2582\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:58:57,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0673\n", + "Function value obtained: -82.4661\n", + "Current minimum: -90.2582\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:59:09,963\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9388\n", + "Function value obtained: -84.0442\n", + "Current minimum: -90.2582\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:59:21,924\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0997\n", + "Function value obtained: -86.7391\n", + "Current minimum: -90.2582\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:59:33,991\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4722\n", + "Function value obtained: -85.9318\n", + "Current minimum: -90.2582\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:59:46,448\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4782\n", + "Function value obtained: -85.0170\n", + "Current minimum: -90.2582\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 18:59:58,931\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8382\n", + "Function value obtained: -86.4555\n", + "Current minimum: -90.2582\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:00:10,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5420\n", + "Function value obtained: -83.6674\n", + "Current minimum: -90.2582\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:00:23,435\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3492\n", + "Function value obtained: -85.2587\n", + "Current minimum: -90.2582\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:00:35,743\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4814\n", + "Function value obtained: -85.7160\n", + "Current minimum: -90.2582\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:00:48,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 12.0917\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:01:00,304\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 10.5236\n", + "Function value obtained: -21.3872\n", + "Current minimum: -21.3872\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:01:10,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 11.3990\n", + "Function value obtained: -61.4340\n", + "Current minimum: -61.4340\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:01:23,183\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 11.6861\n", + "Function value obtained: -30.5749\n", + "Current minimum: -61.4340\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:01:35,561\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 12.9329\n", + "Function value obtained: -3.9297\n", + "Current minimum: -61.4340\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:01:46,889\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 11.7872\n", + "Function value obtained: -10.5661\n", + "Current minimum: -61.4340\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:01:58,647\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 10.6260\n", + "Function value obtained: -1.9804\n", + "Current minimum: -61.4340\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:02:11,346\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 12.8230\n", + "Function value obtained: -5.2969\n", + "Current minimum: -61.4340\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:02:22,286\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 12.5219\n", + "Function value obtained: -1.9594\n", + "Current minimum: -61.4340\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:02:34,675\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 11.8681\n", + "Function value obtained: -79.6325\n", + "Current minimum: -79.6325\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:02:46,579\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1325\n", + "Function value obtained: -82.9123\n", + "Current minimum: -82.9123\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:02:57,657\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0311\n", + "Function value obtained: -84.5376\n", + "Current minimum: -84.5376\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:03:08,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7218\n", + "Function value obtained: -84.4892\n", + "Current minimum: -84.5376\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:03:20,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4979\n", + "Function value obtained: -1.9761\n", + "Current minimum: -84.5376\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:03:31,971\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0924\n", + "Function value obtained: -83.5743\n", + "Current minimum: -84.5376\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:03:44,020\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8763\n", + "Function value obtained: -84.5529\n", + "Current minimum: -84.5529\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:03:55,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3417\n", + "Function value obtained: -81.7204\n", + "Current minimum: -84.5529\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:04:07,197\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9443\n", + "Function value obtained: -85.3490\n", + "Current minimum: -85.3490\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:04:18,234\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9346\n", + "Function value obtained: -84.3531\n", + "Current minimum: -85.3490\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:04:30,141\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0929\n", + "Function value obtained: -85.9082\n", + "Current minimum: -85.9082\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:04:42,457\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5980\n", + "Function value obtained: -86.7586\n", + "Current minimum: -86.7586\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:04:54,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2158\n", + "Function value obtained: -83.0358\n", + "Current minimum: -86.7586\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:05:07,119\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7629\n", + "Function value obtained: -84.8722\n", + "Current minimum: -86.7586\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:05:18,868\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3968\n", + "Function value obtained: -85.8878\n", + "Current minimum: -86.7586\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:05:30,356\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9633\n", + "Function value obtained: -84.8926\n", + "Current minimum: -86.7586\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:05:42,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4213\n", + "Function value obtained: -86.3130\n", + "Current minimum: -86.7586\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:05:53,606\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4698\n", + "Function value obtained: -87.6020\n", + "Current minimum: -87.6020\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:06:05,189\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1861\n", + "Function value obtained: -83.4369\n", + "Current minimum: -87.6020\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:06:17,374\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 13.0788\n", + "Function value obtained: -85.9242\n", + "Current minimum: -87.6020\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:06:30,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8591\n", + "Function value obtained: -85.3490\n", + "Current minimum: -87.6020\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:06:42,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8357\n", + "Function value obtained: -84.9675\n", + "Current minimum: -87.6020\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:06:55,145\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7458\n", + "Function value obtained: -87.6662\n", + "Current minimum: -87.6662\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:07:06,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4007\n", + "Function value obtained: -84.6370\n", + "Current minimum: -87.6662\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:07:19,287\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 13.1146\n", + "Function value obtained: -86.4096\n", + "Current minimum: -87.6662\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:07:32,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0060\n", + "Function value obtained: -85.3912\n", + "Current minimum: -87.6662\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:07:44,521\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9291\n", + "Function value obtained: -85.0626\n", + "Current minimum: -87.6662\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:07:57,219\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7253\n", + "Function value obtained: -86.2307\n", + "Current minimum: -87.6662\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:08:11,201\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4998\n", + "Function value obtained: -86.3373\n", + "Current minimum: -87.6662\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:08:23,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4992\n", + "Function value obtained: -87.0573\n", + "Current minimum: -87.6662\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:08:36,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6326\n", + "Function value obtained: -85.6411\n", + "Current minimum: -87.6662\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:08:48,911\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5245\n", + "Function value obtained: -82.7747\n", + "Current minimum: -87.6662\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:09:01,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 13.1244\n", + "Function value obtained: -88.5028\n", + "Current minimum: -88.5028\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:09:14,326\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6625\n", + "Function value obtained: -86.1438\n", + "Current minimum: -88.5028\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:09:26,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1965\n", + "Function value obtained: -84.6050\n", + "Current minimum: -88.5028\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:09:38,313\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 13.1221\n", + "Function value obtained: -84.3418\n", + "Current minimum: -88.5028\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:09:51,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 13.0093\n", + "Function value obtained: -84.4929\n", + "Current minimum: -88.5028\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:10:04,357\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9171\n", + "Function value obtained: -85.1945\n", + "Current minimum: -88.5028\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:10:16,226\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 14.3140\n", + "Function value obtained: -81.8894\n", + "Current minimum: -88.5028\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:10:30,569\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4836\n", + "Function value obtained: -86.0075\n", + "Current minimum: -88.5028\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:10:43,112\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4976\n", + "Function value obtained: -85.6050\n", + "Current minimum: -88.5028\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:10:55,651\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8227\n", + "Function value obtained: -86.3416\n", + "Current minimum: -88.5028\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:11:08,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3011\n", + "Function value obtained: -86.3921\n", + "Current minimum: -88.5028\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:11:20,770\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3639\n", + "Function value obtained: -86.7170\n", + "Current minimum: -88.5028\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:11:32,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2249\n", + "Function value obtained: -87.9136\n", + "Current minimum: -88.5028\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:11:44,400\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 13.0663\n", + "Function value obtained: -83.7074\n", + "Current minimum: -88.5028\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:11:57,419\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1646\n", + "Function value obtained: -83.9611\n", + "Current minimum: -88.5028\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:12:09,545\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2143\n", + "Function value obtained: -86.3481\n", + "Current minimum: -88.5028\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:12:23,844\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5183\n", + "Function value obtained: -87.8012\n", + "Current minimum: -88.5028\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:12:38,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8534\n", + "Function value obtained: -86.6255\n", + "Current minimum: -88.5028\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:12:52,214\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5267\n", + "Function value obtained: -85.6845\n", + "Current minimum: -88.5028\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:13:07,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4344\n", + "Function value obtained: -86.8237\n", + "Current minimum: -88.5028\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:13:19,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8941\n", + "Function value obtained: -83.2762\n", + "Current minimum: -88.5028\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:13:32,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5444\n", + "Function value obtained: -84.9381\n", + "Current minimum: -88.5028\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:13:44,694\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4875\n", + "Function value obtained: -84.4635\n", + "Current minimum: -88.5028\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:13:58,249\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 13.3168\n", + "Function value obtained: -86.0736\n", + "Current minimum: -88.5028\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:14:11,501\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2999\n", + "Function value obtained: -86.1583\n", + "Current minimum: -88.5028\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:14:23,715\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5058\n", + "Function value obtained: -85.1833\n", + "Current minimum: -88.5028\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:14:38,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6764\n", + "Function value obtained: -88.9795\n", + "Current minimum: -88.9795\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:14:50,942\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2883\n", + "Function value obtained: -85.7122\n", + "Current minimum: -88.9795\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:15:04,292\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7493\n", + "Function value obtained: -83.0249\n", + "Current minimum: -88.9795\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:15:16,964\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9523\n", + "Function value obtained: -84.1864\n", + "Current minimum: -88.9795\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:15:31,018\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9677\n", + "Function value obtained: -85.4601\n", + "Current minimum: -88.9795\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:15:42,980\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5693\n", + "Function value obtained: -86.4198\n", + "Current minimum: -88.9795\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:15:55,522\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2483\n", + "Function value obtained: -83.5641\n", + "Current minimum: -88.9795\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:16:07,763\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7245\n", + "Function value obtained: -83.6426\n", + "Current minimum: -88.9795\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:16:20,526\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1246\n", + "Function value obtained: -85.6648\n", + "Current minimum: -88.9795\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:16:34,656\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8312\n", + "Function value obtained: -83.9867\n", + "Current minimum: -88.9795\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:16:48,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4259\n", + "Function value obtained: -82.5118\n", + "Current minimum: -88.9795\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:17:02,821\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2356\n", + "Function value obtained: -86.3403\n", + "Current minimum: -88.9795\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:17:15,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 13.1240\n", + "Function value obtained: -83.6473\n", + "Current minimum: -88.9795\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:17:28,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2001\n", + "Function value obtained: -83.6651\n", + "Current minimum: -88.9795\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:17:41,491\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4735\n", + "Function value obtained: -88.4078\n", + "Current minimum: -88.9795\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:17:55,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2596\n", + "Function value obtained: -84.0268\n", + "Current minimum: -88.9795\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:18:07,199\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9511\n", + "Function value obtained: -83.4724\n", + "Current minimum: -88.9795\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:18:20,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 13.0713\n", + "Function value obtained: -84.1173\n", + "Current minimum: -88.9795\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:18:33,271\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4891\n", + "Function value obtained: -83.2998\n", + "Current minimum: -88.9795\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:18:46,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1511\n", + "Function value obtained: -85.3088\n", + "Current minimum: -88.9795\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:18:59,004\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9693\n", + "Function value obtained: -84.9342\n", + "Current minimum: -88.9795\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:19:12,964\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7960\n", + "Function value obtained: -85.0579\n", + "Current minimum: -88.9795\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:19:25,709\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2893\n", + "Function value obtained: -85.8128\n", + "Current minimum: -88.9795\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:19:38,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5893\n", + "Function value obtained: -87.8402\n", + "Current minimum: -88.9795\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:19:51,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2243\n", + "Function value obtained: -88.0271\n", + "Current minimum: -88.9795\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:20:07,431\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 15.5916\n", + "Function value obtained: -83.6923\n", + "Current minimum: -88.9795\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:20:22,527\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 15.5075\n", + "Function value obtained: -86.1168\n", + "Current minimum: -88.9795\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:20:35,911\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5386\n", + "Function value obtained: -85.5532\n", + "Current minimum: -88.9795\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:20:49,534\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 13.3971\n", + "Function value obtained: -85.4601\n", + "Current minimum: -88.9795\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:21:03,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 14.7992\n", + "Function value obtained: -83.5207\n", + "Current minimum: -88.9795\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:21:17,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4445\n", + "Function value obtained: -84.3831\n", + "Current minimum: -88.9795\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:21:31,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1385\n", + "Function value obtained: -82.4670\n", + "Current minimum: -88.9795\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:21:43,676\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 17.0420\n", + "Function value obtained: -85.7595\n", + "Current minimum: -88.9795\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:22:00,403\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 13.3441\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:22:13,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 12.1430\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:22:25,855\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 11.3214\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:22:40,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 16.0620\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:22:53,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 12.6246\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:23:05,830\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 12.3825\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:23:18,327\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 12.4799\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:23:30,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 12.8842\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:23:43,630\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 12.1856\n", + "Function value obtained: -1.8994\n", + "Current minimum: -1.8994\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:23:55,883\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 12.3818\n", + "Function value obtained: -2.5139\n", + "Current minimum: -2.5139\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:24:08,156\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4094\n", + "Function value obtained: -2.0813\n", + "Current minimum: -2.5139\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:24:22,304\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0544\n", + "Function value obtained: -2.2911\n", + "Current minimum: -2.5139\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:24:35,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3254\n", + "Function value obtained: -1.9797\n", + "Current minimum: -2.5139\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:24:47,968\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8745\n", + "Function value obtained: -2.4750\n", + "Current minimum: -2.5139\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:25:00,985\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8067\n", + "Function value obtained: -2.2776\n", + "Current minimum: -2.5139\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:25:14,733\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9730\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.5139\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:25:27,773\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9588\n", + "Function value obtained: -0.0000\n", + "Current minimum: -2.5139\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:25:40,671\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7669\n", + "Function value obtained: -2.5372\n", + "Current minimum: -2.5372\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:25:54,474\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8422\n", + "Function value obtained: -2.8429\n", + "Current minimum: -2.8429\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:26:09,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 16.3344\n", + "Function value obtained: -1.8454\n", + "Current minimum: -2.8429\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:26:22,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4106\n", + "Function value obtained: -3.0755\n", + "Current minimum: -3.0755\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:26:36,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5436\n", + "Function value obtained: -3.5748\n", + "Current minimum: -3.5748\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:26:49,655\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9905\n", + "Function value obtained: -5.5441\n", + "Current minimum: -5.5441\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:27:03,700\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8164\n", + "Function value obtained: -8.0095\n", + "Current minimum: -8.0095\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:27:15,447\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3010\n", + "Function value obtained: -35.1492\n", + "Current minimum: -35.1492\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:27:27,688\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5499\n", + "Function value obtained: -39.1156\n", + "Current minimum: -39.1156\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:27:39,920\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 18.0375\n", + "Function value obtained: -45.9205\n", + "Current minimum: -45.9205\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:27:57,365\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 14.1468\n", + "Function value obtained: -26.0641\n", + "Current minimum: -45.9205\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:28:11,474\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8943\n", + "Function value obtained: -45.2668\n", + "Current minimum: -45.9205\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:28:25,868\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9876\n", + "Function value obtained: -47.7713\n", + "Current minimum: -47.7713\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:28:38,348\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4895\n", + "Function value obtained: -46.4605\n", + "Current minimum: -47.7713\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:28:50,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4254\n", + "Function value obtained: -47.5786\n", + "Current minimum: -47.7713\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:29:05,253\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2774\n", + "Function value obtained: -46.2635\n", + "Current minimum: -47.7713\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:29:19,573\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7253\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:29:32,377\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4799\n", + "Function value obtained: -46.7317\n", + "Current minimum: -47.7713\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:29:45,771\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1492\n", + "Function value obtained: -45.8123\n", + "Current minimum: -47.7713\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:29:58,249\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 15.9250\n", + "Function value obtained: -46.8353\n", + "Current minimum: -47.7713\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:30:14,294\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8402\n", + "Function value obtained: -45.9584\n", + "Current minimum: -47.7713\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:30:28,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8060\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:30:42,514\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8741\n", + "Function value obtained: -46.1857\n", + "Current minimum: -47.7713\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:30:55,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 13.3373\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:31:08,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4183\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:31:21,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 16.4462\n", + "Function value obtained: -46.1164\n", + "Current minimum: -47.7713\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:31:37,625\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8656\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:31:50,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 18.9770\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:32:08,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9229\n", + "Function value obtained: -45.8909\n", + "Current minimum: -47.7713\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:32:21,456\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8126\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:32:35,356\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 14.0452\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:32:49,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 13.6907\n", + "Function value obtained: -46.4117\n", + "Current minimum: -47.7713\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:33:03,022\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 14.0216\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:33:17,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 13.6671\n", + "Function value obtained: -44.7488\n", + "Current minimum: -47.7713\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:33:30,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 13.6474\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:33:44,328\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2026\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:33:58,127\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 16.3246\n", + "Function value obtained: -46.0245\n", + "Current minimum: -47.7713\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:34:12,950\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7276\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:34:26,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0483\n", + "Function value obtained: -47.2695\n", + "Current minimum: -47.7713\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:34:39,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 17.9769\n", + "Function value obtained: -0.0000\n", + "Current minimum: -47.7713\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:34:56,634\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9255\n", + "Function value obtained: -49.3547\n", + "Current minimum: -49.3547\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:35:09,666\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 13.6407\n", + "Function value obtained: -1.9186\n", + "Current minimum: -49.3547\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:35:23,286\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5259\n", + "Function value obtained: -47.3805\n", + "Current minimum: -49.3547\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:35:37,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0457\n", + "Function value obtained: -2.0854\n", + "Current minimum: -49.3547\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:35:50,810\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9219\n", + "Function value obtained: -43.3179\n", + "Current minimum: -49.3547\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:36:04,767\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9386\n", + "Function value obtained: -1.9662\n", + "Current minimum: -49.3547\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:36:18,677\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 17.2462\n", + "Function value obtained: -44.9149\n", + "Current minimum: -49.3547\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:36:35,914\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2240\n", + "Function value obtained: -0.0000\n", + "Current minimum: -49.3547\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:36:48,733\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 17.8964\n", + "Function value obtained: -48.2577\n", + "Current minimum: -49.3547\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:37:06,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4908\n", + "Function value obtained: -48.0746\n", + "Current minimum: -49.3547\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:37:19,440\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2178\n", + "Function value obtained: -0.0000\n", + "Current minimum: -49.3547\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:37:33,858\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2289\n", + "Function value obtained: -47.3106\n", + "Current minimum: -49.3547\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:37:47,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 14.1989\n", + "Function value obtained: -48.8041\n", + "Current minimum: -49.3547\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:38:01,250\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7207\n", + "Function value obtained: -46.2191\n", + "Current minimum: -49.3547\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:38:14,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 14.1385\n", + "Function value obtained: -47.1541\n", + "Current minimum: -49.3547\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:38:28,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5416\n", + "Function value obtained: -46.1420\n", + "Current minimum: -49.3547\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:38:41,689\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8685\n", + "Function value obtained: -48.2708\n", + "Current minimum: -49.3547\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:38:55,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6398\n", + "Function value obtained: -48.8198\n", + "Current minimum: -49.3547\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:39:08,120\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4267\n", + "Function value obtained: -47.6542\n", + "Current minimum: -49.3547\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:39:22,659\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 14.7383\n", + "Function value obtained: -47.0740\n", + "Current minimum: -49.3547\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:39:37,391\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4720\n", + "Function value obtained: -46.1323\n", + "Current minimum: -49.3547\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:39:51,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2977\n", + "Function value obtained: -0.0000\n", + "Current minimum: -49.3547\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:40:04,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 19.8883\n", + "Function value obtained: -46.6693\n", + "Current minimum: -49.3547\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:40:24,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 13.3358\n", + "Function value obtained: -49.0673\n", + "Current minimum: -49.3547\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:40:37,336\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9920\n", + "Function value obtained: -0.0000\n", + "Current minimum: -49.3547\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:40:51,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 13.0761\n", + "Function value obtained: -46.7308\n", + "Current minimum: -49.3547\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:41:04,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2108\n", + "Function value obtained: -47.5447\n", + "Current minimum: -49.3547\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:41:17,663\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5748\n", + "Function value obtained: -0.0000\n", + "Current minimum: -49.3547\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:41:31,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8805\n", + "Function value obtained: -47.6168\n", + "Current minimum: -49.3547\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:41:45,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 15.3012\n", + "Function value obtained: -48.1308\n", + "Current minimum: -49.3547\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:42:00,414\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0945\n", + "Function value obtained: -0.0000\n", + "Current minimum: -49.3547\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:42:15,554\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8922\n", + "Function value obtained: -45.4751\n", + "Current minimum: -49.3547\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:42:30,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 13.3004\n", + "Function value obtained: -46.3762\n", + "Current minimum: -49.3547\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:42:44,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 15.5564\n", + "Function value obtained: -46.1720\n", + "Current minimum: -49.3547\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:42:59,490\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4438\n", + "Function value obtained: -47.1809\n", + "Current minimum: -49.3547\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:43:13,776\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5516\n", + "Function value obtained: -48.3087\n", + "Current minimum: -49.3547\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:43:28,398\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 15.3101\n", + "Function value obtained: -48.2784\n", + "Current minimum: -49.3547\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:43:43,548\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9981\n", + "Function value obtained: -47.1562\n", + "Current minimum: -49.3547\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:43:58,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7765\n", + "Function value obtained: -47.6764\n", + "Current minimum: -49.3547\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:44:15,704\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 18.8005\n", + "Function value obtained: -47.3652\n", + "Current minimum: -49.3547\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:44:30,190\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4907\n", + "Function value obtained: -45.5958\n", + "Current minimum: -49.3547\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:44:44,714\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9495\n", + "Function value obtained: -47.5417\n", + "Current minimum: -49.3547\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:44:58,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5283\n", + "Function value obtained: -46.9092\n", + "Current minimum: -49.3547\n", + "CPU times: user 1h 14min 6s, sys: 1h 14min 6s, total: 2h 28min 12s\n", + "Wall time: 1h 3min 26s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "cr_gp2 = gp_minimize(cr_obj2, cr_space, n_calls = 100, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "esc_gp2 = gp_minimize(esc_obj2, log_esc_space, n_calls = 100, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "msy_gp2 = gp_minimize(msy_obj2, log_esc_space, n_calls = 100, verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "8104f281-815e-4d55-86c3-9e22c4634149", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "cr.: -90.26, [-0.03355168327278335, 0.7853961999069485, 0.2463992248494044] \n", + "esc: -88.98, [-0.28034215083975056]\n", + "msy: -49.35, [0.05773712246669316]\n", + "\n" + ] + } + ], + "source": [ + "print(f\"\"\"\n", + "cr.: {cr_gp2.fun:.2f}, {cr_gp2.x} \n", + "esc: {esc_gp2.fun:.2f}, {esc_gp2.x}\n", + "msy: {msy_gp2.fun:.2f}, {msy_gp2.x}\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "14cd665f-e859-41f7-b6f7-d14b16566bab", + "metadata": {}, + "source": [ + "## upow=1, trophy fishing 10 age classes" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "6e5b88dd-3725-48ea-b227-f6ca5357f189", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG3 = {\n", + " \"upow\": 1,\n", + " \"harvest_fn_name\": \"trophy\"\n", + "}\n", + "\n", + "cr_obj3 = cr_obj_generator(CONFIG3)\n", + "esc_obj3 = esc_obj_generator(CONFIG3)\n", + "msy_obj3 = msy_obj_generator(CONFIG3)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "1b4333db-83ce-46c2-87cf-943da18b3370", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:45:13,273\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 12.7166\n", + "Function value obtained: -3.3422\n", + "Current minimum: -3.3422\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:45:26,282\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 12.8683\n", + "Function value obtained: -2.2590\n", + "Current minimum: -3.3422\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:45:40,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 15.2559\n", + "Function value obtained: -3.6202\n", + "Current minimum: -3.6202\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:45:54,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 13.0518\n", + "Function value obtained: -1.2145\n", + "Current minimum: -3.6202\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:46:07,121\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 12.8836\n", + "Function value obtained: -6.0471\n", + "Current minimum: -6.0471\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:46:20,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 12.0856\n", + "Function value obtained: -21.7106\n", + "Current minimum: -21.7106\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:46:38,999\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 18.7035\n", + "Function value obtained: -12.7459\n", + "Current minimum: -21.7106\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:46:51,415\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 18.5711\n", + "Function value obtained: -15.7186\n", + "Current minimum: -21.7106\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:47:09,354\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 13.6057\n", + "Function value obtained: -18.5392\n", + "Current minimum: -21.7106\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:47:23,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 13.3696\n", + "Function value obtained: -19.8398\n", + "Current minimum: -21.7106\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:47:36,331\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8086\n", + "Function value obtained: -0.2499\n", + "Current minimum: -21.7106\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:47:50,212\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2382\n", + "Function value obtained: -20.6884\n", + "Current minimum: -21.7106\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:48:04,438\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2872\n", + "Function value obtained: -24.0880\n", + "Current minimum: -24.0880\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:48:18,896\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8952\n", + "Function value obtained: -23.9823\n", + "Current minimum: -24.0880\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:48:32,592\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7013\n", + "Function value obtained: -24.5750\n", + "Current minimum: -24.5750\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:48:45,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5461\n", + "Function value obtained: -24.1093\n", + "Current minimum: -24.5750\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:48:59,854\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9551\n", + "Function value obtained: -24.0773\n", + "Current minimum: -24.5750\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:49:13,565\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8085\n", + "Function value obtained: -24.3747\n", + "Current minimum: -24.5750\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:49:26,694\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2552\n", + "Function value obtained: -24.6860\n", + "Current minimum: -24.6860\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:49:40,915\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2444\n", + "Function value obtained: -25.1980\n", + "Current minimum: -25.1980\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:49:56,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5093\n", + "Function value obtained: -22.1760\n", + "Current minimum: -25.1980\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:50:08,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5840\n", + "Function value obtained: -2.8943\n", + "Current minimum: -25.1980\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:50:22,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4374\n", + "Function value obtained: -24.1276\n", + "Current minimum: -25.1980\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:50:36,040\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5980\n", + "Function value obtained: -25.1970\n", + "Current minimum: -25.1980\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:50:50,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5959\n", + "Function value obtained: -25.4101\n", + "Current minimum: -25.4101\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:51:04,983\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 13.4430\n", + "Function value obtained: -24.6311\n", + "Current minimum: -25.4101\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:51:18,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2002\n", + "Function value obtained: -24.6536\n", + "Current minimum: -25.4101\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:51:33,629\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 15.6360\n", + "Function value obtained: -24.3260\n", + "Current minimum: -25.4101\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:51:49,198\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7697\n", + "Function value obtained: -24.1331\n", + "Current minimum: -25.4101\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:52:04,458\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9642\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.4101\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:52:17,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 20.1782\n", + "Function value obtained: -25.8992\n", + "Current minimum: -25.8992\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:52:40,983\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 17.5726\n", + "Function value obtained: -24.7605\n", + "Current minimum: -25.8992\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:52:58,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 19.3697\n", + "Function value obtained: -10.2977\n", + "Current minimum: -25.8992\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:53:15,139\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1188\n", + "Function value obtained: -27.2983\n", + "Current minimum: -27.2983\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:53:29,265\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9095\n", + "Function value obtained: -25.3650\n", + "Current minimum: -27.2983\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:53:44,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6142\n", + "Function value obtained: -25.1707\n", + "Current minimum: -27.2983\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:53:57,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 18.8586\n", + "Function value obtained: -17.8434\n", + "Current minimum: -27.2983\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:54:15,637\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5371\n", + "Function value obtained: -28.1856\n", + "Current minimum: -28.1856\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:54:31,609\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 16.2483\n", + "Function value obtained: -27.6668\n", + "Current minimum: -28.1856\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:54:48,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 16.9095\n", + "Function value obtained: -24.7152\n", + "Current minimum: -28.1856\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:55:02,315\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8592\n", + "Function value obtained: -21.1227\n", + "Current minimum: -28.1856\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:55:16,213\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8794\n", + "Function value obtained: -12.3416\n", + "Current minimum: -28.1856\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:55:31,469\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 16.5303\n", + "Function value obtained: -25.8644\n", + "Current minimum: -28.1856\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:55:46,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9911\n", + "Function value obtained: -30.2845\n", + "Current minimum: -30.2845\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:56:01,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8762\n", + "Function value obtained: -28.9319\n", + "Current minimum: -30.2845\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:56:15,582\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1724\n", + "Function value obtained: -31.5466\n", + "Current minimum: -31.5466\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:56:30,652\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 14.7560\n", + "Function value obtained: -29.8928\n", + "Current minimum: -31.5466\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:56:45,654\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5281\n", + "Function value obtained: -28.7802\n", + "Current minimum: -31.5466\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:57:00,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1077\n", + "Function value obtained: -31.4449\n", + "Current minimum: -31.5466\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:57:15,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 15.3850\n", + "Function value obtained: -30.1364\n", + "Current minimum: -31.5466\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:57:30,679\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6837\n", + "Function value obtained: -30.5866\n", + "Current minimum: -31.5466\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:57:45,198\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 14.7768\n", + "Function value obtained: -3.2644\n", + "Current minimum: -31.5466\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:58:00,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2291\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.5466\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:58:15,318\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 14.7794\n", + "Function value obtained: -19.3080\n", + "Current minimum: -31.5466\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:58:30,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 15.3003\n", + "Function value obtained: -27.0818\n", + "Current minimum: -31.5466\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:58:45,381\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 17.2853\n", + "Function value obtained: -29.7998\n", + "Current minimum: -31.5466\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:59:02,564\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5723\n", + "Function value obtained: -29.8916\n", + "Current minimum: -31.5466\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:59:17,300\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 14.0231\n", + "Function value obtained: -30.5911\n", + "Current minimum: -31.5466\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:59:31,324\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 15.7449\n", + "Function value obtained: -22.9761\n", + "Current minimum: -31.5466\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 19:59:47,028\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5489\n", + "Function value obtained: -27.8065\n", + "Current minimum: -31.5466\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:00:01,576\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 15.3040\n", + "Function value obtained: -29.3063\n", + "Current minimum: -31.5466\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:00:16,976\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 15.6854\n", + "Function value obtained: -25.4359\n", + "Current minimum: -31.5466\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:00:32,551\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 14.7504\n", + "Function value obtained: -26.8313\n", + "Current minimum: -31.5466\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:00:47,301\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9350\n", + "Function value obtained: -18.2366\n", + "Current minimum: -31.5466\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:01:02,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5534\n", + "Function value obtained: -30.1370\n", + "Current minimum: -31.5466\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:01:16,981\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 18.7948\n", + "Function value obtained: -23.5834\n", + "Current minimum: -31.5466\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:01:36,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 18.2109\n", + "Function value obtained: -29.5153\n", + "Current minimum: -31.5466\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:01:53,935\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8581\n", + "Function value obtained: -6.6769\n", + "Current minimum: -31.5466\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:02:08,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2246\n", + "Function value obtained: -31.2148\n", + "Current minimum: -31.5466\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:02:23,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4528\n", + "Function value obtained: -31.8623\n", + "Current minimum: -31.8623\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:02:38,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 15.8004\n", + "Function value obtained: -30.5065\n", + "Current minimum: -31.8623\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:02:54,213\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 15.8590\n", + "Function value obtained: -1.2338\n", + "Current minimum: -31.8623\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:03:10,144\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 18.5292\n", + "Function value obtained: -30.6296\n", + "Current minimum: -31.8623\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:03:28,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6776\n", + "Function value obtained: -28.7260\n", + "Current minimum: -31.8623\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:03:43,257\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 15.7452\n", + "Function value obtained: -31.6708\n", + "Current minimum: -31.8623\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:03:58,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6056\n", + "Function value obtained: -31.9045\n", + "Current minimum: -31.9045\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:04:12,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 24.4298\n", + "Function value obtained: -30.3985\n", + "Current minimum: -31.9045\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:04:36,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2909\n", + "Function value obtained: -30.8683\n", + "Current minimum: -31.9045\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:04:50,143\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 20.7625\n", + "Function value obtained: -30.5748\n", + "Current minimum: -31.9045\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:05:11,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 19.2616\n", + "Function value obtained: -30.0262\n", + "Current minimum: -31.9045\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:05:30,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 20.4224\n", + "Function value obtained: -32.0205\n", + "Current minimum: -32.0205\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:05:49,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0436\n", + "Function value obtained: -31.4876\n", + "Current minimum: -32.0205\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:06:04,931\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 16.2155\n", + "Function value obtained: -30.6195\n", + "Current minimum: -32.0205\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:06:21,089\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 16.3091\n", + "Function value obtained: -1.9054\n", + "Current minimum: -32.0205\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:06:37,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4208\n", + "Function value obtained: -24.7538\n", + "Current minimum: -32.0205\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:06:52,913\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 16.2272\n", + "Function value obtained: -26.3072\n", + "Current minimum: -32.0205\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:07:09,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0176\n", + "Function value obtained: -31.3672\n", + "Current minimum: -32.0205\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:07:25,091\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2073\n", + "Function value obtained: -0.0000\n", + "Current minimum: -32.0205\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:07:40,362\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0951\n", + "Function value obtained: -31.2598\n", + "Current minimum: -32.0205\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:07:56,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0373\n", + "Function value obtained: -30.7222\n", + "Current minimum: -32.0205\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:08:12,497\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 16.5148\n", + "Function value obtained: -0.0000\n", + "Current minimum: -32.0205\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:08:29,082\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 16.1886\n", + "Function value obtained: -26.7533\n", + "Current minimum: -32.0205\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:08:45,214\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8299\n", + "Function value obtained: -23.7794\n", + "Current minimum: -32.0205\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:09:02,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8097\n", + "Function value obtained: -1.5413\n", + "Current minimum: -32.0205\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:09:17,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 17.8100\n", + "Function value obtained: -31.2005\n", + "Current minimum: -32.0205\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:09:34,698\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 15.7735\n", + "Function value obtained: -30.6715\n", + "Current minimum: -32.0205\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:09:50,424\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 16.4205\n", + "Function value obtained: -29.5495\n", + "Current minimum: -32.0205\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:10:06,978\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9746\n", + "Function value obtained: -24.1894\n", + "Current minimum: -32.0205\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:10:21,854\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8627\n", + "Function value obtained: -30.7302\n", + "Current minimum: -32.0205\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:10:38,650\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4924\n", + "Function value obtained: -28.2524\n", + "Current minimum: -32.0205\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:10:54,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 14.3592\n", + "Function value obtained: -13.7919\n", + "Current minimum: -13.7919\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:11:08,657\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 15.3803\n", + "Function value obtained: -0.8608\n", + "Current minimum: -13.7919\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:11:24,057\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 14.4865\n", + "Function value obtained: -0.8770\n", + "Current minimum: -13.7919\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:11:38,474\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 12.5861\n", + "Function value obtained: -0.9897\n", + "Current minimum: -13.7919\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:11:51,804\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 20.9790\n", + "Function value obtained: -0.0000\n", + "Current minimum: -13.7919\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:12:12,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 23.4379\n", + "Function value obtained: -0.8367\n", + "Current minimum: -13.7919\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:12:35,572\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 14.2344\n", + "Function value obtained: -0.8237\n", + "Current minimum: -13.7919\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:12:49,725\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 14.7844\n", + "Function value obtained: -0.8734\n", + "Current minimum: -13.7919\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:13:04,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 15.3880\n", + "Function value obtained: -0.9060\n", + "Current minimum: -13.7919\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:13:19,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 13.7719\n", + "Function value obtained: -0.8580\n", + "Current minimum: -13.7919\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:13:34,159\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 18.7448\n", + "Function value obtained: -9.9804\n", + "Current minimum: -13.7919\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:13:52,743\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0185\n", + "Function value obtained: -14.1624\n", + "Current minimum: -14.1624\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:14:08,467\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2708\n", + "Function value obtained: -13.4188\n", + "Current minimum: -14.1624\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:14:23,883\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4794\n", + "Function value obtained: -13.0523\n", + "Current minimum: -14.1624\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:14:39,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6075\n", + "Function value obtained: -13.6092\n", + "Current minimum: -14.1624\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:14:53,788\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5097\n", + "Function value obtained: -2.2971\n", + "Current minimum: -14.1624\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:15:08,349\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 15.8102\n", + "Function value obtained: -13.3907\n", + "Current minimum: -14.1624\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:15:24,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8886\n", + "Function value obtained: -7.8471\n", + "Current minimum: -14.1624\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:15:39,116\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8942\n", + "Function value obtained: -13.8512\n", + "Current minimum: -14.1624\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:15:54,191\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8543\n", + "Function value obtained: -13.2317\n", + "Current minimum: -14.1624\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:16:10,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 16.7105\n", + "Function value obtained: -13.4035\n", + "Current minimum: -14.1624\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:16:25,607\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9611\n", + "Function value obtained: -13.6324\n", + "Current minimum: -14.1624\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:16:39,781\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 15.9912\n", + "Function value obtained: -13.4511\n", + "Current minimum: -14.1624\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:16:55,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4858\n", + "Function value obtained: -13.7319\n", + "Current minimum: -14.1624\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:17:10,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9089\n", + "Function value obtained: -13.3498\n", + "Current minimum: -14.1624\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:17:25,081\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 13.2782\n", + "Function value obtained: -13.3748\n", + "Current minimum: -14.1624\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:17:41,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 18.6530\n", + "Function value obtained: -13.4548\n", + "Current minimum: -14.1624\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:17:56,816\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0746\n", + "Function value obtained: -13.9134\n", + "Current minimum: -14.1624\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:18:12,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 16.1300\n", + "Function value obtained: -13.5699\n", + "Current minimum: -14.1624\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:18:28,153\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2037\n", + "Function value obtained: -13.9893\n", + "Current minimum: -14.1624\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:18:43,248\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8263\n", + "Function value obtained: -13.2808\n", + "Current minimum: -14.1624\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:18:57,392\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5138\n", + "Function value obtained: -13.3273\n", + "Current minimum: -14.1624\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:19:11,314\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 20.4689\n", + "Function value obtained: -13.1557\n", + "Current minimum: -14.1624\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:19:31,667\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 20.5685\n", + "Function value obtained: -13.7990\n", + "Current minimum: -14.1624\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:19:52,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 23.6767\n", + "Function value obtained: -13.4255\n", + "Current minimum: -14.1624\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:20:18,638\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 17.6619\n", + "Function value obtained: -13.0218\n", + "Current minimum: -14.1624\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:20:33,352\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 17.5666\n", + "Function value obtained: -13.4393\n", + "Current minimum: -14.1624\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:20:51,685\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 17.3208\n", + "Function value obtained: -13.3430\n", + "Current minimum: -14.1624\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:21:08,025\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9746\n", + "Function value obtained: -13.6745\n", + "Current minimum: -14.1624\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:21:23,796\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6023\n", + "Function value obtained: -13.2590\n", + "Current minimum: -14.1624\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:21:38,113\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 21.0679\n", + "Function value obtained: -13.3283\n", + "Current minimum: -14.1624\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:21:59,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8964\n", + "Function value obtained: -13.7560\n", + "Current minimum: -14.1624\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:22:15,656\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 15.7662\n", + "Function value obtained: -13.2686\n", + "Current minimum: -14.1624\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:22:31,371\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8372\n", + "Function value obtained: -13.4258\n", + "Current minimum: -14.1624\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:22:48,176\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7827\n", + "Function value obtained: -13.1792\n", + "Current minimum: -14.1624\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:23:04,620\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 17.8800\n", + "Function value obtained: -13.5241\n", + "Current minimum: -14.1624\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:23:19,924\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 16.1300\n", + "Function value obtained: -13.3398\n", + "Current minimum: -14.1624\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:23:35,946\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 16.7410\n", + "Function value obtained: -13.5360\n", + "Current minimum: -14.1624\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:23:52,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 16.1024\n", + "Function value obtained: -13.0472\n", + "Current minimum: -14.1624\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:24:08,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 16.2336\n", + "Function value obtained: -13.3045\n", + "Current minimum: -14.1624\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:24:24,966\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 13.6231\n", + "Function value obtained: -12.9234\n", + "Current minimum: -14.1624\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:24:39,591\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 21.3430\n", + "Function value obtained: -13.7088\n", + "Current minimum: -14.1624\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:25:00,769\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 24.7311\n", + "Function value obtained: -13.6131\n", + "Current minimum: -14.1624\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:25:25,328\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 22.7744\n", + "Function value obtained: -12.8286\n", + "Current minimum: -14.1624\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:25:47,609\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 15.8792\n", + "Function value obtained: -12.7727\n", + "Current minimum: -14.1624\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:26:03,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 16.6997\n", + "Function value obtained: -13.8037\n", + "Current minimum: -14.1624\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:26:20,169\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0160\n", + "Function value obtained: -13.8822\n", + "Current minimum: -14.1624\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:26:36,175\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8208\n", + "Function value obtained: -13.9756\n", + "Current minimum: -14.1624\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:26:53,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9429\n", + "Function value obtained: -13.6753\n", + "Current minimum: -14.1624\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:27:07,497\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 19.8395\n", + "Function value obtained: -13.2046\n", + "Current minimum: -14.1624\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:27:26,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0558\n", + "Function value obtained: -13.3153\n", + "Current minimum: -14.1624\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:27:43,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1606\n", + "Function value obtained: -13.6479\n", + "Current minimum: -14.1624\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:27:58,757\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 19.3947\n", + "Function value obtained: -13.7278\n", + "Current minimum: -14.1624\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:28:17,517\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9217\n", + "Function value obtained: -13.8681\n", + "Current minimum: -14.1624\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:28:32,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 20.9789\n", + "Function value obtained: -13.1946\n", + "Current minimum: -14.1624\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:28:53,342\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 13.0279\n", + "Function value obtained: -13.1855\n", + "Current minimum: -14.1624\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:29:07,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 26.8780\n", + "Function value obtained: -13.0255\n", + "Current minimum: -14.1624\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:29:33,337\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 15.4052\n", + "Function value obtained: -13.6944\n", + "Current minimum: -14.1624\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:29:48,667\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 14.1011\n", + "Function value obtained: -13.3326\n", + "Current minimum: -14.1624\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:30:03,465\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 23.8231\n", + "Function value obtained: -13.4103\n", + "Current minimum: -14.1624\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:30:26,579\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 16.7662\n", + "Function value obtained: -13.1638\n", + "Current minimum: -14.1624\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:30:43,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 22.4772\n", + "Function value obtained: -13.2211\n", + "Current minimum: -14.1624\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:31:05,978\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 16.5034\n", + "Function value obtained: -13.8004\n", + "Current minimum: -14.1624\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:31:22,454\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8258\n", + "Function value obtained: -13.0706\n", + "Current minimum: -14.1624\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:31:39,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 17.5066\n", + "Function value obtained: -13.2345\n", + "Current minimum: -14.1624\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:31:56,757\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 17.2684\n", + "Function value obtained: -13.7316\n", + "Current minimum: -14.1624\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:32:14,021\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 18.6246\n", + "Function value obtained: -13.2624\n", + "Current minimum: -14.1624\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:32:32,746\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 16.4163\n", + "Function value obtained: -13.3726\n", + "Current minimum: -14.1624\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:32:49,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8531\n", + "Function value obtained: -13.5893\n", + "Current minimum: -14.1624\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:33:03,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 24.8330\n", + "Function value obtained: -13.6783\n", + "Current minimum: -14.1624\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:33:27,834\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 15.5875\n", + "Function value obtained: -13.4919\n", + "Current minimum: -14.1624\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:33:45,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 19.0128\n", + "Function value obtained: -13.7669\n", + "Current minimum: -14.1624\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:34:02,511\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 14.2241\n", + "Function value obtained: -12.9329\n", + "Current minimum: -14.1624\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:34:17,050\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 23.9931\n", + "Function value obtained: -13.1596\n", + "Current minimum: -14.1624\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:34:40,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 14.9950\n", + "Function value obtained: -13.3585\n", + "Current minimum: -14.1624\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:34:55,945\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 21.4343\n", + "Function value obtained: -13.8398\n", + "Current minimum: -14.1624\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:35:17,074\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 14.3189\n", + "Function value obtained: -13.5490\n", + "Current minimum: -14.1624\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:35:31,951\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 24.0823\n", + "Function value obtained: -13.3595\n", + "Current minimum: -14.1624\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:35:55,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 15.9351\n", + "Function value obtained: -12.9894\n", + "Current minimum: -14.1624\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:36:11,302\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 16.9627\n", + "Function value obtained: -13.4997\n", + "Current minimum: -14.1624\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:36:28,352\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 15.5490\n", + "Function value obtained: -12.7742\n", + "Current minimum: -14.1624\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:36:44,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 15.7321\n", + "Function value obtained: -13.8610\n", + "Current minimum: -14.1624\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:36:59,632\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 18.0026\n", + "Function value obtained: -13.2046\n", + "Current minimum: -14.1624\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:37:17,816\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6302\n", + "Function value obtained: -13.6597\n", + "Current minimum: -14.1624\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:37:32,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 24.7897\n", + "Function value obtained: -13.3522\n", + "Current minimum: -14.1624\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:37:57,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6996\n", + "Function value obtained: -13.4632\n", + "Current minimum: -14.1624\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:38:12,396\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 23.6777\n", + "Function value obtained: -13.3483\n", + "Current minimum: -14.1624\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:38:35,559\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 17.5413\n", + "Function value obtained: -13.8656\n", + "Current minimum: -14.1624\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:38:53,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 16.5719\n", + "Function value obtained: -13.1648\n", + "Current minimum: -14.1624\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:39:09,681\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 17.1363\n", + "Function value obtained: -14.3016\n", + "Current minimum: -14.3016\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:39:26,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 15.8634\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 2 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:39:42,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 16.2954\n", + "Function value obtained: -25.1807\n", + "Current minimum: -25.1807\n", + "Iteration No: 3 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:39:59,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 16.1448\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 4 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:40:15,099\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 16.5112\n", + "Function value obtained: -0.9482\n", + "Current minimum: -25.1807\n", + "Iteration No: 5 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:40:31,890\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 15.6452\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 6 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:40:47,648\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 17.2778\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 7 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:41:05,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 24.3452\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 8 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:41:29,313\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 21.3204\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 9 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:41:50,357\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 15.3876\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 10 started. Evaluating function at random point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:42:08,224\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 18.3777\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:42:24,148\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 16.9908\n", + "Function value obtained: -23.9636\n", + "Current minimum: -25.1807\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:42:41,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 15.9118\n", + "Function value obtained: -15.5843\n", + "Current minimum: -25.1807\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:42:57,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 15.7454\n", + "Function value obtained: -17.2209\n", + "Current minimum: -25.1807\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:43:12,913\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 20.4829\n", + "Function value obtained: -4.9900\n", + "Current minimum: -25.1807\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:43:33,368\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8254\n", + "Function value obtained: -22.7081\n", + "Current minimum: -25.1807\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:43:50,079\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 16.9089\n", + "Function value obtained: -0.8624\n", + "Current minimum: -25.1807\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:44:06,950\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 13.5610\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:44:22,300\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 25.9277\n", + "Function value obtained: -0.9049\n", + "Current minimum: -25.1807\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:44:47,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 28.4779\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:45:15,988\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 19.1985\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:45:34,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 17.4535\n", + "Function value obtained: -23.4528\n", + "Current minimum: -25.1807\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:45:51,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 17.3519\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:46:08,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 15.8159\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:46:24,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0803\n", + "Function value obtained: -0.9133\n", + "Current minimum: -25.1807\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:46:40,914\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1441\n", + "Function value obtained: -0.8762\n", + "Current minimum: -25.1807\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:46:56,632\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 18.0000\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:47:14,125\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0803\n", + "Function value obtained: -24.8374\n", + "Current minimum: -25.1807\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:47:30,485\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 17.5908\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:47:47,766\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0137\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:48:03,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 16.9997\n", + "Function value obtained: -23.7273\n", + "Current minimum: -25.1807\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:48:19,750\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0223\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:48:35,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 15.8198\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:48:51,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 16.2813\n", + "Function value obtained: -24.7542\n", + "Current minimum: -25.1807\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:49:07,518\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 25.7638\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.1807\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:49:32,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 16.8646\n", + "Function value obtained: -24.7489\n", + "Current minimum: -25.1807\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:49:50,121\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 17.2418\n", + "Function value obtained: -0.8548\n", + "Current minimum: -25.1807\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:50:06,689\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 16.4862\n", + "Function value obtained: -0.8529\n", + "Current minimum: -25.1807\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:50:23,363\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6256\n", + "Function value obtained: -25.7620\n", + "Current minimum: -25.7620\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:50:38,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 22.1361\n", + "Function value obtained: -0.8844\n", + "Current minimum: -25.7620\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:51:00,109\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 15.0743\n", + "Function value obtained: -0.8696\n", + "Current minimum: -25.7620\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:51:17,563\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 18.4293\n", + "Function value obtained: -24.9961\n", + "Current minimum: -25.7620\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:51:33,697\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 18.6820\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:51:52,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 14.8649\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:52:08,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 19.6056\n", + "Function value obtained: -24.9433\n", + "Current minimum: -25.7620\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:52:26,862\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6143\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:52:42,117\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 25.0543\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:53:06,415\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 17.6200\n", + "Function value obtained: -25.0296\n", + "Current minimum: -25.7620\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:53:24,147\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 17.6422\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:53:41,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 15.7354\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:53:57,618\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 20.0075\n", + "Function value obtained: -24.6033\n", + "Current minimum: -25.7620\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:54:22,610\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 22.2062\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:54:39,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 16.0193\n", + "Function value obtained: -24.7025\n", + "Current minimum: -25.7620\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:54:55,755\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 27.5433\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:55:23,246\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 16.5501\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:55:39,981\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 17.6153\n", + "Function value obtained: -23.3715\n", + "Current minimum: -25.7620\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:55:57,271\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 17.1656\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:56:14,653\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 18.4854\n", + "Function value obtained: -25.1107\n", + "Current minimum: -25.7620\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:56:33,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 16.3453\n", + "Function value obtained: -24.7787\n", + "Current minimum: -25.7620\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:56:49,851\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 16.9631\n", + "Function value obtained: -0.8623\n", + "Current minimum: -25.7620\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:57:06,450\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 20.3394\n", + "Function value obtained: -25.7061\n", + "Current minimum: -25.7620\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:57:26,696\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 16.4044\n", + "Function value obtained: -24.9317\n", + "Current minimum: -25.7620\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:57:43,405\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 19.7760\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:58:03,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 18.0187\n", + "Function value obtained: -24.1865\n", + "Current minimum: -25.7620\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:58:21,210\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 18.5912\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:58:39,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4120\n", + "Function value obtained: -23.8400\n", + "Current minimum: -25.7620\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:58:54,829\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 30.0197\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:59:24,147\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 19.0750\n", + "Function value obtained: -24.2439\n", + "Current minimum: -25.7620\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 20:59:43,121\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 17.1814\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:00:01,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 19.5890\n", + "Function value obtained: -23.9463\n", + "Current minimum: -25.7620\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:00:19,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 17.2594\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:00:37,149\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 18.3128\n", + "Function value obtained: -24.4614\n", + "Current minimum: -25.7620\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:00:55,520\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 17.1803\n", + "Function value obtained: -24.9506\n", + "Current minimum: -25.7620\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:01:12,583\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 25.0919\n", + "Function value obtained: -24.0691\n", + "Current minimum: -25.7620\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:01:37,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 17.7718\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:01:55,568\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 18.1646\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:02:13,760\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 17.6818\n", + "Function value obtained: -24.4948\n", + "Current minimum: -25.7620\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:02:31,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 21.9875\n", + "Function value obtained: -24.4039\n", + "Current minimum: -25.7620\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:02:53,520\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 17.7110\n", + "Function value obtained: -25.4551\n", + "Current minimum: -25.7620\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:03:11,225\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 17.7361\n", + "Function value obtained: -24.0056\n", + "Current minimum: -25.7620\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:03:28,984\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 19.8734\n", + "Function value obtained: -24.5530\n", + "Current minimum: -25.7620\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:03:48,772\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 17.3307\n", + "Function value obtained: -23.9856\n", + "Current minimum: -25.7620\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:04:05,967\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 17.2184\n", + "Function value obtained: -25.0607\n", + "Current minimum: -25.7620\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:04:23,417\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 16.7710\n", + "Function value obtained: -1.3204\n", + "Current minimum: -25.7620\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:04:40,159\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 19.7425\n", + "Function value obtained: -24.2707\n", + "Current minimum: -25.7620\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:05:00,460\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 22.5330\n", + "Function value obtained: -24.3694\n", + "Current minimum: -25.7620\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:05:22,969\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 25.0221\n", + "Function value obtained: -24.8173\n", + "Current minimum: -25.7620\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:05:48,384\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 19.2994\n", + "Function value obtained: -25.0125\n", + "Current minimum: -25.7620\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:06:06,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 18.0873\n", + "Function value obtained: -24.0236\n", + "Current minimum: -25.7620\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:06:24,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 18.2515\n", + "Function value obtained: -24.9301\n", + "Current minimum: -25.7620\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:06:43,088\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 18.4844\n", + "Function value obtained: -24.4818\n", + "Current minimum: -25.7620\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:07:01,680\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 17.5678\n", + "Function value obtained: -24.8025\n", + "Current minimum: -25.7620\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:07:19,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 19.2867\n", + "Function value obtained: -24.6682\n", + "Current minimum: -25.7620\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:07:38,449\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 17.9912\n", + "Function value obtained: -24.4891\n", + "Current minimum: -25.7620\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:07:57,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 20.2703\n", + "Function value obtained: -24.1971\n", + "Current minimum: -25.7620\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:08:16,715\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 18.3892\n", + "Function value obtained: -23.2317\n", + "Current minimum: -25.7620\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:08:35,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 18.0607\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.7620\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:08:53,207\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 17.9907\n", + "Function value obtained: -24.7574\n", + "Current minimum: -25.7620\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:09:11,114\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 19.4152\n", + "Function value obtained: -25.0136\n", + "Current minimum: -25.7620\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:09:30,517\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 23.5589\n", + "Function value obtained: -24.5597\n", + "Current minimum: -25.7620\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-22 21:09:54,195\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 15.6735\n", + "Function value obtained: -24.6703\n", + "Current minimum: -25.7620\n", + "CPU times: user 1h 39min 42s, sys: 1h 20min 34s, total: 3h 17s\n", + "Wall time: 1h 24min 54s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "cr_gp3 = gp_minimize(cr_obj3, cr_space, n_calls = 100, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "esc_gp3 = gp_minimize(esc_obj3, log_esc_space, n_calls = 100, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "msy_gp3 = gp_minimize(msy_obj3, log_esc_space, n_calls = 100, verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "fb84909e-3816-493a-b888-cb394c6beed6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "cr.: -32.02, [-0.383730004464649, 0.7853961999069485, 0.08034226735043051] \n", + "esc: -14.30, [0.06615357610240746]\n", + "msy: -25.76, [0.045615795667256265]\n", + "\n" + ] + } + ], + "source": [ + "print(f\"\"\"\n", + "cr.: {cr_gp3.fun:.2f}, {cr_gp3.x} \n", + "esc: {esc_gp3.fun:.2f}, {esc_gp3.x}\n", + "msy: {msy_gp3.fun:.2f}, {msy_gp3.x}\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "624c8d13-95cd-402c-a61f-18e497194db6", + "metadata": {}, + "source": [ + "## Saving models" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "9196be9f-11aa-4a9e-8e41-718bcec76091", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "path = \"../saved_agents/results/\"\n", + "\n", + "def to_cr(log_polar_params):\n", + " theta = log_polar_params[1]\n", + " radius = 10 ** log_polar_params[0]\n", + " x1 = np.sin(theta) * radius\n", + " x2 = np.cos(theta) * radius\n", + " y2 = log_polar_params[2]\n", + " return {'x1': x1, 'x2': x2, 'y2': y2}\n", + "\n", + "def to_esc(log_params):\n", + " return {'escapement': 10 ** log_params[0]}\n", + "\n", + "def to_msy(params):\n", + " return {'msy': params[0]}\n", + "\n", + "#\n", + "eval_env1 = AsmEnv(config=CONFIG1)\n", + "eval_env2 = AsmEnv(config=CONFIG2)\n", + "eval_env3 = AsmEnv(config=CONFIG3)\n", + "\n", + "# \n", + "cr1_fname = \"cr_case_1.pkl\"\n", + "cr1 = CautionaryRule(env=eval_env1, **to_cr(cr_gp1.x))\n", + "dump(cr1, path+cr1_fname)\n", + "\n", + "esc1_fname = \"esc_case_1.pkl\"\n", + "esc1 = ConstEsc(env=eval_env1, **to_esc(esc_gp1.x))\n", + "dump(esc1, path+esc1_fname)\n", + "\n", + "msy1_fname = \"msy_case_1.pkl\"\n", + "msy1 = Msy(env=eval_env1, **to_msy(msy_gp1.x))\n", + "dump(msy1, path+msy1_fname)\n", + "\n", + "# \n", + "cr2_fname = \"cr_case_2.pkl\"\n", + "cr2 = CautionaryRule(env=eval_env2, **to_cr(cr_gp2.x))\n", + "dump(cr2, path+cr2_fname)\n", + "\n", + "esc2_fname = \"esc_case_2.pkl\"\n", + "esc2 = ConstEsc(env=eval_env2, **to_esc(esc_gp2.x))\n", + "dump(esc2, path+esc2_fname)\n", + "\n", + "msy2_fname = \"msy_case_2.pkl\"\n", + "msy2 = Msy(env=eval_env2, **to_msy(msy_gp2.x))\n", + "dump(msy2, path+msy2_fname)\n", + "\n", + "# \n", + "cr3_fname = \"cr_case_3.pkl\"\n", + "cr3 = CautionaryRule(env=eval_env3, **to_cr(cr_gp3.x))\n", + "dump(cr3, path+cr3_fname)\n", + "\n", + "esc3_fname = \"esc_case_3.pkl\"\n", + "esc3 = ConstEsc(env=eval_env3, **to_esc(esc_gp3.x))\n", + "dump(esc3, path+esc3_fname)\n", + "\n", + "msy3_fname = \"msy_case_3.pkl\"\n", + "msy3 = Msy(env=eval_env3, **to_msy(msy_gp3.x))\n", + "dump(msy3, path+msy3_fname)\n", + "\n", + "\n", + "## Didn't work for the gp objects since I used a fn generator :(\n", + "\n", + "# cr1_fname = \"cr_case_1.pkl\"\n", + "# dump(cr_gp1, path+cr1_fname)\n", + "\n", + "# esc1_fname = \"esc_case_1.pkl\"\n", + "# dump(esc_gp1, path+esc1_fname)\n", + "\n", + "# msy1_fname = \"msy_case_1.pkl\"\n", + "# dump(msy_gp1, path+msy1_fname)\n", + "\n", + "# #\n", + "\n", + "# cr2_fname = \"cr_case_2.pkl\"\n", + "# dump(cr_gp2, path+cr2_fname)\n", + "\n", + "# esc2_fname = \"esc_case_2.pkl\"\n", + "# dump(esc_gp2, path+esc2_fname)\n", + "\n", + "# msy2_fname = \"msy_case_2.pkl\"\n", + "# dump(msy_gp2, path+msy2_fname)\n", + "\n", + "# #\n", + "\n", + "# cr3_fname = \"cr_case_3.pkl\"\n", + "# dump(cr_gp3, path+cr3_fname)\n", + "\n", + "# esc3_fname = \"esc_case_3.pkl\"\n", + "# dump(esc_gp3, path+esc3_fname)\n", + "\n", + "# msy3_fname = \"msy_case_3.pkl\"\n", + "# dump(msy_gp3, path+msy3_fname)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4df50600-c069-4974-a7fc-6630e13e8057", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "a5f554a4-dd95-4bff-bf24-d60ef1215cf5", + "metadata": {}, + "source": [ + "## Objective plots" + ] + }, + { + "cell_type": "markdown", + "id": "491ddf8b-9039-49d8-b027-7b7e89046f4a", + "metadata": {}, + "source": [ + "### 1" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "aa3f2db6-75b0-47aa-8c08-8511faf6290b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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", 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", 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5ebn0PgCQb7/9lsTGxpLU1FRCCCErVqwg06ZNk5b/7rvvyMmTJ8mzZ8/Iw4cPycKFCwmTyWzQ1W6LtHpDlJy7fPkyIYSQtLQ0MmDAAGJlZUU4HA7x8vIiS5cuJaWlpUrV8eDBAzJ48GDp9e7u7mT27NkkIyOj0ToJES8Qnjt3LrG0tCTGxsZk/PjxJDs7W+l7CwkJUTiGlK0DMgtvq6qqyPDhw4mtrS0xNDQkbm5uZObMmVLDUsS2bduIq6srYbPZxN/fn0RHR0vfGzhwIAkJCZErf+TIEdKxY0fCZrOJr68v+euvv5S+H0JeuiPqvyT1hISEkIEDB0rLb9iwgbRv354YGRkRKysrMmjQIHLp0iWV6myt0KBvCkUH0Gn3BYWiL1BDpFB0AGqIFIoOQA2RQtEBqCFSKDoANUQKRQdoVYbI5/OxevXqRiNcaJ20ztZKq/IjlpWVwdzcHKWlpeDxeLROWmeboVW1iBRKW4UaIoWiA6i9+kIkEiErKwtmZmZK77zUXMrKyuT+0jr1o05CCMrLy+Hk5AQms222HWqPETMyMuDi4qJpfSiURklPT4ezs7O21WgR1G4RJanq09PT9X6gTWlZysrK4OLi0qa3R1DbECXdUR6PRw2xrfD4MTB2LHDqFODrq21tGvC6hkDaoG12uCnqwecDSUniv5TXCjVECkUHoIZIAQCIRK0mrqNN0iZ2DKY0j/m/xuBRZinODzQF59XFKS0AbREpuJKQj+eFVUi1dATOnQO8vLStkt5BW0Q9hxCC6lpxZvBqI1MgOFjLGukntEXUc2qFBMIX40OSnQWsXg1kZ2tXKT2EGqKeI2kNAYBkZQNr1lBD1ALUEPUcvowh1gpFWtSkdVFXV4eLFy/ixx9/RHl5OQBxJvqKigq15NExop4j2yIK6qghKkNqaipGjBiBtLQ08Pl8DBs2DGZmZtiwYQP4fD527typskzaIuo51XItIvUlKsPChQvRu3dvFBcXg8vlSs+PHz8ekZGRasmkLaKeUy14aYiVxqbAlCmApaUWNdJ9/vnnH9y8eRNsNlvuvLu7OzIzM9WSSVtEPUe2RSyydwYOHAA8PLSoUfO5du0aRo8eDScnJzAYDJw8eVLufUIIVq1aBUdHR3C5XAwdOhTPnj1TWr5IJGqwGSwgXhqo7goRaoh6To2MIdZVVAOJiUBNjRY1aj6VlZXw8/PD9u3bFb7/9ddfY+vWrdi5cydu3boFExMTBAcHo0bJ+x4+fDg2b94sPWYwGKioqEBYWBhGjRqlntLq7l5TWlpKACi9yxJFN/kzLou4Lf+TuC3/kxzaeZIQgJB797StlhzN+a2h3k7FIpGIODg4kI0bN0rPlZSUEA6HQ3777TelZKanp5POnTuTTp06EQMDA9K3b19ibW1NvL29SW5urso6EqLCjsF8Pl8u7d3rTKlAaTnkJmvqGna3dIn6vzkOh9NgN+lXkZKSgpycHAwdOlR6ztzcHAEBAYiKisL777//ShnOzs6Ii4vD4cOHERcXh4qKCsyYMQNTpkyRm7xRBaUNMTw8HGvWrFGrEoruIue+0PFZ0/qpWcLCwrB69WqVZOTk5AAA7O3t5c7b29tL31MGAwMDTJkyBVOmTFGp/kblKVtw5cqVWLx4sfRYkr6A0rppTQ79+mlZVG0NNUV4eDjs7e3x4Ycfyp3fs2cP8vPzsXz5cpVlKj1Zw+FwpGkxaHqMtoOs+0Kg44ZY//enjiE6ODgAAHJzc+XO5+bmSt97FT/++CN8fHwanPf19VXLmQ/QWVO9R7ZrmuLqDRAC9OypRY1aFg8PDzg4OMg53svKynDr1i0EBgYqJSMnJweOjo4Nztva2iJbzThd6tDXc2QNkd9GQtwqKiqQmJgoPU5JScH9+/dhZWUFV1dXfPLJJ1i3bh06dOgADw8PfP7553BycsK4ceOUku/i4oIbN27Ao56/9caNG3ByclJLZ2qIeo6sH9EiLRkInAdERADe3tpTqpncvXsXgwcPlh5L5jZCQkIQERGBZcuWobKyEh9//DFKSkrQr18/nDt3DkZGRkrJnzlzJj755BPU1tbizTffBABERkZi2bJl+PTTT9XSmRqiniM7RmRWVwHR0UBlpRY1aj6DBg0CaSJvNoPBwNq1a7F27Vq15C9duhSFhYWYO3cuBAIBAMDIyAjLly/HypUr1ZJJDVHPkfcjto2uaUvDYDCwYcMGfP7554iPjweXy0WHDh2aNYtLDVHPqa59aXy6Pmuqa5iamqJPnz4akUUNUc+pEdD1iKpSWVmJr776CpGRkcjLy4NIJP+5JScnqyyTGqKeI9s1zTC3A/bvB9zdtadQK+Cjjz7C1atXMW3aNDg6OmpkKwBqiHqO7KxpAdsUmDpGi9q0Ds6ePYu//voLb7zxhsZkUoe+niPbInJLi4Dt24H8fC1qpPtYWlrCyspKozKpIeo5si2iVWEOMH8+kJ6uRY10ny+++AKrVq1CVVWVxmTSrqmeI+tHpDlrlGPTpk1ISkqCvb093N3dYWhoKPd+TEyMyjKpIeoxRCbLN0DdF8qibCicKlBD1GMEQhFkN4FSbxN3/SMsLEzjMukYUY+pEci3gJVsLuqGDgPa8BbZmqKkpAQ//fQTVq5ciaKiIgDiLqm6Wdxoi6jHSLqlLCYDQhHBc6t2KPn2NGxM6eZsTfHgwQMMHToU5ubmeP78OWbOnAkrKyucOHECaWlp2Ldvn8oyaYuox0gM0diQBTaLCaZIiNqiEkBBqkDKSxYvXozQ0FA8e/ZMbsXGqFGjcO3aNbVkUkPUYySuCyM2CxwDJjrlpcDRzQGIi9OyZrrNnTt3MGvWrAbn27Vrp1LeG1lo11SPkbSIXENWk8uGKPJwOByFWQyfPn0KW1tbtWTSFlGPkQR8GxkywWbRn4KyjBkzBmvXrkVtbS0A8bKotLQ0LF++HBMmTFBLJv309RjZFpFjyNKyNq2HTZs2oaKiAnZ2dqiursbAgQPh5eUFMzMzrF+/Xi2ZtGuqx0gM0ciQ1Wby1bwOzM3NceHCBVy/fh0PHjxARUUFevbsKZe0WFWoIeoxkvA2LpuFmlohHtu649r1RxjQtaOWNWsd9OvXD/369dOILGqIekyNTNe00oCJOpYBKnhWQL3YSQqwdetWpcsuWLBAZfnUEPUYuTGiAQuuxdnoMT8E2PMD0L69lrXTLb777ju54/z8fFRVVcHCwgKAONLG2NgYdnZ2ahkinazRY6pfhLhJ/Ihm/Eo4XrsAlJZqWTPdIyUlRfpav349unfvjvj4eBQVFaGoqAjx8fHo2bMnvvjiC7XkU0PUY2rqZGdN6U9BWT7//HNs27YN3jK5X729vfHdd9/hs88+U0sm/fT1GOlkzYsQN4pyZGdno66ursF5oVDYYE8NZaGfvh4jDXEzZIJjQP2IyjJkyBDMmjVLbgHwvXv3MGfOHLVdGNQQ9RhZPyLHkIlcM2tc+Xg50K6dljXTbfbs2QMHBwf07t1bulmqv78/7O3t8dNPP6klk86a6jGyfkSOARMFJpaIGhmCQfU28aTIY2trizNnzuDp06d48uQJAMDHxwcdO6rvf6WGqMfIui/YBkzwairQ/upZINABsLTUsna6T8eOHZtlfLJQQ9Rjaur5EV1KcjDxl0+B9wZRQ2wCoVCIiIiIRjN9X7p0SWWZ1BD1mOp66xEpyrFw4UJERETgrbfeQpcuXWimb0rzkHVfUENUnkOHDuHIkSMYNWqUxmTST1+PqXmxExRdBqUabDYbXl5eGpVJDVGPkY4R2WKHfo0BB89dvQEuV8ua6TaffvoptmzZotGsBrRrqsdIx4gGYj9iko0Llv9vLw536qRlzXSb69ev4/Llyzh79ix8fX0bZPo+ceKEyjJpi6inyGb5NmK/jKxpCwuEV69eDQaDIffy8fHRmHwLCwuMHz8eAwcOhI2NDczNzeVe6kBbRD2FXyeSZvaWTNb45ibh6DdLgKBbQI8e2lWwmfj6+uLixYvSYwMDzf3U9+7dqzFZEqgh6imyu0AZvXDogxAYCmvbRO59AwMDODg4tJj8uro6XLlyBUlJSZg8eTLMzMyQlZUFHo8HU1NTleUpbYh8Ph98Pl96rCidHKX1IOmWGrIYMGQxW4X7ov5vThLnqYhnz57ByckJRkZGCAwMRHh4OFxdXTWiR2pqKkaMGIG0tDTw+XwMGzYMZmZm2LBhA/h8Pnbu3KmyTKU//fDwcLl+sIuLi8qVUXSHasHLgG8ArWL1hYuLi9xvMDw8XGG5gIAARERE4Ny5c/jhhx+QkpKC/v37o7y8XCN6LFy4EL1790ZxcTG4MjPM48ePR2RkpFoylW4RV65cicWLF0uPy8rKqDG2YmTjTAG0ioXB6enp4PF40uPGWsORI0dK/+/WrRsCAgLg5uaGI0eOYMaMGc3W459//sHNmzfBZrPlzru7u7f8JjRNdQMorQ9ZHyIAsFlMJFq74K2Pf8BfOuq+4PF4coaoLBYWFujYsSMSExM1oodIJIJQwf4gGRkZMFNzJy3dfwxSWgTZqBpA3CLyDTn418oFRGZjlbZARUUFkpKS4OjoqBF5w4cPx+bNm6XHDAYDFRUVCAsLUzvsjRqiniIZI3JkxojtSvMQfmYrapOfa1Gz5rNkyRJcvXoVz58/x82bNzF+/HiwWCxMmjRJI/I3bdqEGzduoHPnzqipqcHkyZOl3dINGzaoJZO6L/SUl2NE8bOYY8CERXUZ3n/wNyrz8sFu76FN9ZpFRkYGJk2ahMLCQtja2qJfv36Ijo5We4OY+jg7OyMuLg6HDh2SZvqeMWMGpkyZIjd5owrUEPWU+pM1ssmjBEIRTLSilWY4dOhQi9dhYGCAqVOnak6exiRRWhX1J2uYTLE/EQDqhK0/zK2lSUhIwLZt2xAfHw8A6NSpE+bPn692KB0dI+op9f2IAMBmiRe4Cupaf2RNS3L8+HF06dIF9+7dg5+fH/z8/BATE4OuXbvi+PHjasmkLaKeUr9rCgDlFtbY0fcdDLey1pZarYJly5Zh5cqVWLt2rdz5sLAwLFu2TK09EmmLqKcoMsRSSzt8PTAUlTYtF6PZFsjOzsYHH3zQ4PzUqVORnZ2tlkxqiHpKjUB+jAgAFkI++qY9QB3d+6JJBg0ahH/++afB+evXr6N///5qyaRdUz1F4tCXHSN6Fmfh+9/+h9iJ/kAXN22ppvOMGTMGy5cvx71799C3b18AQHR0NI4ePYo1a9bgjz/+kCurDNQQ9RTZLN8SDA3EkzW1dNa0SebOnQsA2LFjB3bs2KHwPUAccaMoFE4R1BD1FEVjRIn7QtAGVum3JPXzmGoCOkbUU176EV/+BCRO/VohdV8oS01NjUbkUEPUU2RzmkpgstnINrUGn0F/Fk0hFArxxRdfoF27djA1NUVycjIA8b6JP//8s1oy6SeupygaIxZ4dkTgvF+Q566Z/RzaKuvXr0dERAS+/vpruTWJXbp0UXs3KGqIeoqiMaKka8qvpWPEpti3bx927dqFKVOmgMV6+fn5+flJd4dSFWqIeooiP6JbZjKitofA9Fm8ttRqFWRmZirM9C0SiVBbW6uWTGqIeoqiFtGIIYRjRSGENfzGLqMA6Ny5s0KH/rFjx9BDzTSU1H2hpygaI0q6pgI6a9okq1atQkhICDIzMyESiXDixAkkJCRg3759+PPPP9WSSVtEPYQQojCyxoBFHfrKMHbsWJw+fRoXL16EiYkJVq1ahfj4eJw+fRrDhg1TSyZtEfUQ2bT6smNE9ouUigJqiK+kf//+uHDhgsbk0RZRD5H4EAHASCaxcLWbB96f9CWybJ21oZZeQ1tEPUQyPmSzmDCQSZHB5PEQ7doN1oZ0W7b6WFpaKr0zcFFRkcryqSHqIS8nauQ7RBbF+Vh2NQLJDtO1oZZOI5s+sbCwEOvWrUNwcDACAwMBAFFRUTh//jw+//xzteRTQ9RDqhX4EAHArLQQc6OP4fPho7Whlk4TEhIi/X/ChAlYu3Yt5s+fLz23YMECfP/997h48SIWLVqksnw6RtRDahT4EAHA8MV4sZauvmiS8+fPY8SIEQ3OjxgxQm4rOFWghqiHKPIhArJ+RGqITWFtbY1Tp041OH/q1ClYW6uX74d2TfUQRRncABlDpC1ik6xZswYfffQRrly5goCAAADArVu3cO7cOezevVstmdQQ9ZCaOvl9L6TYWONQt+Eo5Ki+0aY+ERoaik6dOmHr1q04ceIEAHFe0+vXr0sNU1WoIeohigK+AYDh5oYVIxfAmUfdF68iICAABw8e1Jg8OkbUQxQFfAOAUa0AHfJTgepqbail11BD1EMam6wxff4MF/bMQ7vsFG2opddQQ9RDXvoR5b9+QyZNua8tqCHqIY35EdkSP6JIBEKoMb5OqCHqIY2NEQ1fpH0ghGZye93QWVM9ROpHZDdsEfksA4DBAL9OKG0hKcDbb7+tdFmJS0MVqCHqIdLJGoN6LWLvXvBcchKAeM2i2etWTIcxNzdvUfnUEPUQyer8+n5EJpMBNosJgVBEo2vqsXfv3haVT/seekhjkzWIj8fJPf9F+4J0uVX8lJaHGqIe0pgfEdXV6JyTBKM6Pvh1ym2eoqts374d7u7uMDIyQkBAAG7fvq1R+ceOHcPEiRPRt29f9OzZU+6lDi1miEIRoVPgOkpj6xFlac1Jhg8fPozFixcjLCwMMTEx8PPzQ3BwMPLy8jQif+vWrZg+fTrs7e0RGxsLf39/WFtbIzk5GSNHjlRLZosYYkpBJXqvu4C5B2NaQvxrp0pQh1vJhRCJWv+DRSgiqBLUAVDQNZWhNS+F+vbbbzFz5kxMnz4dnTt3xs6dO2FsbIw9e/ZoRP6OHTuwa9cubNu2DWw2G8uWLcOFCxewYMEClKq5yavSkzV8Ph98/svEs2VlZY2W/epsPIqranH2UQ4eZZaiS7uWnXFqSZ7klGHuwRgk51di0dCOWDi0Q4Myv8dmYP1fT7D7g17o4WqpBS0bQghBSkElrj7Nx7Wn+XiaW4Gy6lqU8+ukZeqnypBFF1vE+r85DocDDocjd04gEODevXtYuXKl9ByTycTQoUMRFRWlET3S0tIQFBQEAOByuSgvLwcATJs2DX379sX333+vskylW8Tw8HCYm5tLXy4uLgrL3X1ehPOPc6XHu/9JVlmp+uSW1SB0722ceaje/uTqQAjBodtpGPv9DSTnVwIA9kenNsj5WScU4etzCSio4L9W/ZriyN109P/6Mt7cdBVrTv+Lywn5yCypljNCHwczdLSv56Dw8MCGD9ci3cJBJ8eILi4ucr/B8PDwBmUKCgogFAphb28vd97e3h45OTka0cPBwUGaIMrV1RXR0dEAgJSUFLWHY0q3iCtXrsTixYulx2VlZQ2MkRCCL8+I903wd7fC7edF+PNBNpaP8IGTReNLa0QigsgnefB14iks98OVJFxJyEdmcTVGdXVUVmW1qRLU4X8nHuLk/SwAwCBvWzzOKkN+OR8X/s2V0+FifB6yS8V75KUUVLa4bq8iJq0YK44/gIiIF/r28bDEgA626O1uCUtjNsy5hjAzMlTsrLe0xN0+Q1D2vFgnZ03T09PB4/Gkx/Vbw9fFm2++iT/++AM9evTA9OnTsWjRIhw7dgx3795VyfEvi9KGqKgbUJ9zj3IQk1YCriEL2yb3wILfYnErpQi/3HyOlaM6NXrdhnNP8OO1ZPg4mOHMgv5gMl+mrasWCHEiJgMA8CyvAvnlfNiatewX8OWZeJy8nwUWk4Elw70xa4AnNl1IwPbLSfjtdpqcIR6ITpX+n6xlQ6wWCLHkSBxEBBjt54QNE7rCmK2Cqzg3F+MuHUaKfR+d9CPyeDw5Q1SEjY0NWCwWcnNz5c7n5ubCwcFBI3rs2rVLumvwvHnzYG1tjZs3b2LMmDGYNWuWWjI1NllTKxRhwznxllQz+3vAnmeEmf09AQC/3k5DhUy3SJb90an48Zq4+/okpxyXnsjPbP35IAtlNS+vjU4u1JTKCkkvqsKh2+kAgF3TemHOoPZgMhl4v48rGAzgn2cFSC0UG1xSfgWuJxbIXVunxUmOjecTkFxQCXseB+vGdlHNCAEgMxNTjm6FfXmhTnZNlYHNZqNXr16IjIyUnhOJRIiMjJSmPmwuTCYTBgYvP9v3338fW7duxX//+1+5/RJVkqkRzQD8djsNzwurYGPKxscD2wMA3vSxg6etCcpr6nD4TnqDay4/yUPYqUcAAE9bEwDAjiuJcv3sX2+nAQB4RuIbj2phQ9wS+Qx1IoL+HWwwpNPLcYaLlTEGdLAFAPz2wlAlreGbPnbgGDBRKyTILNHOotqopELsuSFeR7hhQjeYGxs2S54udk2VZfHixdi9ezd++eUXxMfHY86cOaisrMT06erna33w4IG0FXzw4EGTL3XQiCGWVtdiy8VnAICFQzvClCM2GiaTgRn9PAAAe66nyLUWjzJLMe/XGIgI8G4vZxya2RdsAyZi0kpwO0U8EP43qwyxaSUwYDKkXdvopJYzxOT8Cmk3ePGwhrvmTvJ3BQAcu5eO0qpaHLsnLvtBoBs8bMQPEm10Tyv4dVh6LO6Fji4Y5G3XbJm6OGuqLO+99x6++eYbrFq1Ct27d8f9+/dx7ty5BhM4qtC9e3cUFBRI/+/Rowe6d+/e4KXVbdnWnv4XhZUCeNqa4P0+8hM4E3o645vzCcgsqcbGvxNgZMBCckElbiQWoEogxBte1vjy7a4wZDHxTi9n/HorDTuuJCHA0xq/3ha3OMG+DhjV1RH/9/tDJBdUIqe0Bg7mRppQXY7NF59BRIAhPnYK3RBDOtnBzoyDvHI+/nsoFuU1dXCzFreUh++k40lOOVLyKzHYW+OqNcn6v+KRUVwNZ0su/u+tzhqRKetHTMwrx/30UhizWTBms2DCMYCXrSksTdTrhqlCnVCEhxklKl83f/58uQTAzSUlJQW2trbS/zVNsw0xMj4Xx2MywGQAG9/pBkOWfCNrZMjCtL5u2HopET9elXdleNubYceUXtJrZg3wxKHbabj6NB93nhfhZKx41nJygCvMuYbwdTLHw8xSRCUXYHwPzW6UkpBTjtMPxPUtUtAaAoAhi4n3+rhg26VEXHuaDwCYGuAGJpMB9xct4uueOT3/OAe/3U4DgwFsfMdP2htRC3NzPOkzCOUcE/BfhMEJRQTv/RiNwkqBXFGuIQub3++OYF/NTIA0RkZxNSbtvtWidSiDm5ub9P/U1FQEBQXJjRMBoK6uDjdv3pQrqyzN7pquPf0YADBzgCd6uVkpLPNhPw+84WWNPu6WeK+3C1aM9MGuab1wav4bMOe+HMu4WZvgP92cAACz9t9DBb8OHjYmCPQUJ20NbC/+G9UC3dPvLjwFIcCorg5NBiC818cFkr1IOAZMvNtb/ECQdE2fF74+Q8wtq8GK4+Ixycf9PaWfj9q0b4/jYduRZukoHSOmFFSgsFIANosJf3cr+Drx4MAzQnWtELMP3MMPV5JaNJQxtaiqxWSry+DBgxVuNFNaWorBgwerJbPZLWJhZS18XC0VjqkkWBizcfCjvkrJmzOoPf6Iy0LRiyfwJH8XqTsj0NMau64la3zC5lFmKc49zgGDASwa2vh9AICzpTEGdrTFlYR8jPFzgoWxuHvmKRkj5r8eQxSJCBYfuY/iqlp0acfDp8M10B+urYVFRSkMhHVSQ3yUKY5m6epsjiOzxbOOtUIR1p7+F/ujU7Hh3BMk5lXgy7e7gGPQeMicuqS9xgebshBCFO4MVVhYCBMTE7VkNtsQDZgMfDuxu8a+hE6OPLzpY4dLT/LAZjHxTq+XY84+HlZgMRlIL6pGRnEVnC2NNVLnrhfuk7F+TuhQP9pEAV+M7YID0an4eICn9JykRcwqrUZNrbDhygYN89P1ZNxILATXkIUt7/fQzGr6hw8x7/0gnAnZDH6d+N4eZYpjJ7s4vfTfGbKY+GJcF3SwN8Wa0//ieEwGskqqsW+Gf4OhSXNJLdSdFlHirGcwGAgNDZXzqwuFQjx48EAa+qYqzf7UZg1or/FY0sXDOsKYzcK0QDdYyUwImHIM0PVFXZrqnuaX83H2kTg07aP+nq8oLcbFyhgrR3WCtenLL8LKhA2ekQEIafkfz6PMUmw8nwAAWDW6M9rbaj4zt8SP+DhL3CL6KviOPwh0x97QPjDlGCAquRA7ryRpXA9d6ppKQusIITAzM5MLt3NwcMDHH3+MAwcOqCW72S3iRwM8miuiAV3amePR6mC5CBsJge2tcT+9BFHJhXi3t+J4V1U4cjcdtUKCHq4WzXqgMBgMeNiYIC6jFCkFFfB2aJlEEyIRwdJjD1ArJAj2tW8wS60p+HXiTG6Ps8Qtoq+T4oiWAR1tsW5cF3xy+D62XnqGYb728HFoOvpFFdJ0qEXcu3evdDy8bds2mJpq7gHY7BZR010RCYqMEIB04iY6qbDZkwRCEcHBF075aX1Vn+mqj4d05rTlfjyn4jIRn10GMyMDhL/dTeldbFWFXytCRnE1ymrqwGYx0cGu8QfL2O5OGNbZHrVCgiVH4xoExqsLIQRpOtQiAmKdDh48iOxszQb4t7oV+r3dLWHIYiCrtKbZX9KlJ3nIKq2BpbGhRoLJPWzET8iUgopmy1IEv06ITX8/BQDMHthertveEnVJxofeDmZNjkEZDAbWj+sCc64hHmWWScfczSW/nI/qWiEaeSZrBSaTiQ4dOqCwULMThq3OEI3ZBvBztgAA3GzmOHH/i9ZwYh8XjUyueNi2rC/xYHQaMoqrYWfGwYdvaH5IAD8/nLvxBPF2HhDUifDoFd1SWex4Rlg9RhxMsPniUyTklDdbHcn40J6n+eCN5vDVV19h6dKlePTokcZktjpDBF76E4/fy1B7lcDzgkpce5oPBgOY4t/8bikAeFi3nCGW19Ti+8uJAIBPhnZsMs2F2rBYYFlYQMRkgV8nanKiRhHjurfD0E52qBUSLDsW1+yMBpJJL1crzcyOa4oPPvgAt2/fhp+fH7hcLqysrORe6tAq0ymO79EOP19Pwd3UYqw48QCb3vVTeax08Ja4NRzU0Rau1pr5ot1txHIKKgQoq6kFz6h5gdey7P4nBUWVAnjamGBib81GFUl59gy9Zn0M906TUONghkeZYkPookSLCLzooo7vilspVxGXUYo/4rIwrkc7tdWR+BBdrHRrm7jNmzdrXGarNERPW1Nsn9wTH+27ixMxmXC24GKxCg7tmlohjtwVB2xPC9RMawgAZkaGsDXjIL+cj+cFlej2ogvdXPLL+fjpRaaDJcHeMGihCTKUl8Pq+hWYtB+HtJJqlNfUgcmASrOg9jwjzB7YHhvPJ2DThQSM6uqoto9T0jXVlL9YU4SEhGhcZqvsmgLAYB87rB/XBQCw9VIifnuxXEoZ9kelorS6Fs6WXAzs2PyVCrJ4aDjmlBCCDeeeoEoghJ+zOUZ2adnYTgnlL9aAetmZqtwN/vAND9iZcZBeVI1fb6W++oJG0NWuqSw1NTUoKyuTe6lDqzVEAHjf3xUL3vQCAHx28hGuJLw6Xd7lJ3kIPytO5zFrgCdYGp6S03So25bIZ9LlVitGdmoxd0VjdHFS3bfKZbOkSba2XUpsdFH4q0iTtoi61TWtrKzE/PnzYWdnBxMTE1haWsq91KFVGyIgXikxoaczhCKCTw7fR1YTC3Nl10BO7O2MqRrwHdZHk6swIm6kYPOLdZ5rxvg2P6hbDZSdqKnPxN4u8LAxQWGlQNqtVoXymlppvLGLjrWIy5Ytw6VLl/DDDz+Aw+Hgp59+wpo1a+Dk5IR9+/apJbPVGyKDwUD4213RzdkcJVW1WHgoVmG6iuzSasz45Y50DeT68V1bpHXRVNf0ZGwmVp/+FwDwydAOCAlyb65qr8bFBcUbvkU2z1Z6ShnXhSIMWUx8OlwcQL/7WjIKKvivuEIeSbfUyoQNMw1OemmC06dPY8eOHZgwYQIMDAzQv39/fPbZZ/jyyy9x8OBBtWS2ekMExNuJbZvUA6YcA9x5Xoytkc/k3i+s4GP63jvILeOjg52p3BpITSPpmj4vqFQ78ufSk1x8elS84j40yB0LhzTMpdoi2Nqids4cFBm/bAU7q2mIADCqiyO6tjNHpUCI7y8lqnStpFuqi+PDoqIieHqK45J5PJ50SVS/fv1w7do1tWS2CUMExGsZv3y7KwBg2+VE3EwsQLVAiO2XEzFo4xU8ySmHjSkHe6f3kVsDqWlcrY3BYADl/DoUVAhefUE9HmaUYt7BWAhFBON7tMOq/3R+fePCoiKYHj0E82qxM97d2rhZLhgmk4HlI3wAiN1FSfnKRxxJWkQ3DbmWNImnp6d0lb6Pjw+OHDkCQNxSWlhYqCWzzRgiAIzxc8L7fVxACLDgUCwGfXMZG88noJxfB18nHvZ96N/iU+EcA5Z0ckHV7mlGcRU+/OUOqmuF6N/BBl+/063RmNsW4flzGM+YDudScSpCXzUmaurTr4MN3vQRO/lX//FY6V6CpEV008EWcfr06YiLE/dYVqxYge3bt8PIyAiLFi3C0qVL1ZLZKv2ITRE22hf3UovxLE/89HW25GLJcG+M8XN6bT9qd2sTpBdVY96vMejtZomerpbo6WaJbs7mjXaJy2pq8WHEHeSX8+HjYIYdU3q2WPdZWXzbaWYVxar/dMb1ZwX451kBzj/OxQglXDBpReKHmKu1egttW5JFixZJ/x86dCiePHmCe/fuwcvLC926dVNLZpszRC6bhZ3TemHD2ScI8LTG1L6uLbJyvCnGdW+H6OTCF2sdc3D2kTjVuynHAH09rdDPywb+HtbgcQ3AMWDBkMXA/F9j8TS3AnZmHOwJ7aPVCQrJA0Ad14Ui3G1M8PEAT3x/ORFf/PkvBna0faVvUhe7piKRCBs3bsQff/wBgUCAIUOGICwsDG5ubmrlqZGlzRkiALS3NcWuD3prrf4JvZwxqqsjHmSUICatBDFpxbj7vAjFVbW4GJ+Hi/GK/Z3GbBb2hPZpcnuC14G7jTFSuIbwc7HQmMy5g9vjREwGMkuq8cPVpCZTqwjqRFI3lLhrqvpYuyVYv349Vq9ejaFDh4LL5WLLli3Iy8vTyC5TbdIQdQEum4UAT2sEvFg/KRIRPM4qw/XEAlxPzMfjrDJUC4TS3DAWxob4bmJ37e6cZWIC9O2LDdMCwffqoNFYWWO2AT77T2fMPRiDnVeT8E5P50ZjfDNLqiEi4kxxtmYclJfrhiHu27cPO3bskKbVv3jxIt566y389NNPYDKbN4xgEDXn2MvKymBubo7S0tJX7kdAaRxCCARCEZgMhtbHhC0NIQTTfr6N64kF6OlqgSXB3ujrYd1g7H4lIQ+he+/A294M5xcN0JnfGofDQWJiotzmS0ZGRkhMTISzc/MC8dv2N98KYDAYL8aJbf+rYDAYWD2mszSj++TdtzBg42V8d+EpcstqpOWkPkQdGh8C4rylRkbyayMNDQ1RW1vbbNm0a0p5SUwM0KsXcO8eoOZe8K/Cy84Mf8x/A/uiUnH6fhYyiquxJfIZ9kU9x5FZgehgb/ZyokbHXBeEkAbZ22pqajB79my5NIonTpxQWTY1RMprx8eBhy/Hd8Xnb3XG3//m4IcrSXiSU46pP9/CsdlBOjljCihe/jR16lSNyKaGSNEaXDYLY7u3w4AOtnh/VzQScssx+adovNh0Sed8iHv37m0x2W1/YELReSxN2Ng/wx9u1sZIL6qWbm2na13TloQaIkUnsOMZ4cCMADi8SBTFYjLQTsfWIbYk1BApL+ncGXj2TPxXC7hYGePAR/5wtuQi2NdeL2aSJVA/IkXnEImInG9RH35r+vPIobyalBRg6lTxXy3yWlec6AjUECkvKS4GDh4U/6W8VqghUig6ADVECkUHUNuhL5njUTePI0UHqah4+VeHvlfJb6wltwjXNmobYnm5OK+JbCQ6pY0wcKC2NVBIeXk5zM21uEysBVHbfSESiZCVlQUzM7PXnvSWol8QQlBeXg4nJ6dmr/vTVdQ2RAqFojna5uOFQmllUEOkUHQAaogUig5ADZFC0QGoIVIoOgA1RApFB6CGSKHoAP8PuBchLJAgIbMAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(msy_gp3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "78583c73-cb01-47a9-a338-bb28fb813dc4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21893d39-3aa1-48b5-8677-6ac836cabc42", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b041ad87-48c7-4c85-80f1-86f33891f3c2", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index 92ee099..b633549 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -67,9 +67,10 @@ "CONFIG = {\n", " 'observation_fn_id': 'observe_1o',\n", " 'n_observs': 1,\n", - " 'upow': 0.6,\n", - " 'use_custom_harv_vul': True,\n", - " 'use_custom_surv_vul': True,\n", + " 'harvest_fn_name': \"trophy\"\n", + " # 'upow': 0.6,\n", + " # 'use_custom_harv_vul': True,\n", + " # 'use_custom_surv_vul': True,\n", "}" ] }, @@ -83,14 +84,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 16, "id": "b59deb35-b67d-4232-bce4-ae9c8c2f0fcc", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b92ef02995e64837905f934c9b53f6dc", + "model_id": "ebd1a37fb2bc4afcbda442cae44f95dc", "version_major": 2, "version_minor": 0 }, @@ -171,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "id": "c122a0c1-1c51-4c31-8f7b-84fd1725abf3", "metadata": {}, "outputs": [], @@ -245,7 +246,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 5, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { "scrolled": true @@ -262,7 +263,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:38:19,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:27:18,013\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -270,9 +271,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 10.9241\n", - "Function value obtained: -5.0780\n", - "Current minimum: -5.0780\n", + "Time taken: 6.8686\n", + "Function value obtained: -1.6067\n", + "Current minimum: -1.6067\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -280,7 +281,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:38:30,649\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:27:24,755\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -288,9 +289,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 10.5288\n", - "Function value obtained: -6.5391\n", - "Current minimum: -6.5391\n", + "Time taken: 6.8123\n", + "Function value obtained: -1.4543\n", + "Current minimum: -1.6067\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -298,7 +299,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:38:41,187\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:27:31,651\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -306,9 +307,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 10.3549\n", - "Function value obtained: -11.9424\n", - "Current minimum: -11.9424\n", + "Time taken: 7.1185\n", + "Function value obtained: -23.6318\n", + "Current minimum: -23.6318\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -316,7 +317,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:38:51,452\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:27:38,788\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -324,9 +325,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 10.4696\n", - "Function value obtained: -5.0848\n", - "Current minimum: -11.9424\n", + "Time taken: 6.8663\n", + "Function value obtained: -1.5761\n", + "Current minimum: -23.6318\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -334,7 +335,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:39:01,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:27:45,692\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -342,9 +343,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 10.6285\n", - "Function value obtained: -96.7727\n", - "Current minimum: -96.7727\n", + "Time taken: 6.8807\n", + "Function value obtained: -1.7399\n", + "Current minimum: -23.6318\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -352,7 +353,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:39:12,586\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:27:52,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -360,9 +361,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 11.2769\n", - "Function value obtained: -16.2514\n", - "Current minimum: -96.7727\n", + "Time taken: 6.9930\n", + "Function value obtained: -10.2676\n", + "Current minimum: -23.6318\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -370,7 +371,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:39:23,874\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:27:59,556\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -378,9 +379,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 10.7036\n", - "Function value obtained: -25.2132\n", - "Current minimum: -96.7727\n", + "Time taken: 6.8931\n", + "Function value obtained: -23.7849\n", + "Current minimum: -23.7849\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -388,7 +389,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:39:34,554\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:28:06,451\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -396,9 +397,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 10.2216\n", - "Function value obtained: -4.5589\n", - "Current minimum: -96.7727\n", + "Time taken: 7.0198\n", + "Function value obtained: -19.5838\n", + "Current minimum: -23.7849\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -406,7 +407,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:39:44,818\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:28:13,497\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -414,9 +415,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 10.4010\n", - "Function value obtained: -103.1378\n", - "Current minimum: -103.1378\n", + "Time taken: 6.9986\n", + "Function value obtained: -2.5242\n", + "Current minimum: -23.7849\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -424,7 +425,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:39:55,261\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:28:21,478\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -432,9 +433,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 15.1215\n", - "Function value obtained: -4.4069\n", - "Current minimum: -103.1378\n", + "Time taken: 11.8461\n", + "Function value obtained: -2.1985\n", + "Current minimum: -23.7849\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -442,7 +443,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:40:10,290\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:28:32,352\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -450,9 +451,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0153\n", - "Function value obtained: -23.1285\n", - "Current minimum: -103.1378\n", + "Time taken: 8.3823\n", + "Function value obtained: -25.1574\n", + "Current minimum: -25.1574\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -460,7 +461,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:40:22,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:28:40,742\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -468,9 +469,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5079\n", - "Function value obtained: -107.7270\n", - "Current minimum: -107.7270\n", + "Time taken: 8.6339\n", + "Function value obtained: -1.3162\n", + "Current minimum: -25.1574\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -478,7 +479,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:40:34,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:28:49,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -486,9 +487,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2868\n", - "Function value obtained: -109.1133\n", - "Current minimum: -109.1133\n", + "Time taken: 8.1603\n", + "Function value obtained: -23.7694\n", + "Current minimum: -25.1574\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -496,7 +497,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:40:47,242\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:28:57,516\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -504,9 +505,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7974\n", - "Function value obtained: -111.9426\n", - "Current minimum: -111.9426\n", + "Time taken: 8.3573\n", + "Function value obtained: -24.0656\n", + "Current minimum: -25.1574\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -514,7 +515,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:40:58,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:29:05,899\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -522,9 +523,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0254\n", - "Function value obtained: -110.3378\n", - "Current minimum: -111.9426\n", + "Time taken: 8.4364\n", + "Function value obtained: -24.3323\n", + "Current minimum: -25.1574\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -532,7 +533,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:41:11,075\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:29:14,344\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -540,9 +541,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9932\n", - "Function value obtained: -111.3267\n", - "Current minimum: -111.9426\n", + "Time taken: 8.4510\n", + "Function value obtained: -23.9958\n", + "Current minimum: -25.1574\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -550,269 +551,1529 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:41:23,018\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:29:22,870\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3352\n", + "Function value obtained: -24.1041\n", + "Current minimum: -25.1574\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:29:31,154\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1115\n", + "Function value obtained: -24.2515\n", + "Current minimum: -25.1574\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:29:39,255\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4161\n", + "Function value obtained: -24.0693\n", + "Current minimum: -25.1574\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:29:46,685\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 7.3623\n", + "Function value obtained: -25.3020\n", + "Current minimum: -25.3020\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:29:54,057\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 7.2222\n", + "Function value obtained: -23.8156\n", + "Current minimum: -25.3020\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:01,278\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 7.3769\n", + "Function value obtained: -24.6337\n", + "Current minimum: -25.3020\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:08,645\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6214\n", + "Function value obtained: -25.2654\n", + "Current minimum: -25.3020\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:16,289\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 7.2112\n", + "Function value obtained: -25.2750\n", + "Current minimum: -25.3020\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:23,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 7.3662\n", + "Function value obtained: -24.9076\n", + "Current minimum: -25.3020\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:30,870\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4579\n", + "Function value obtained: -24.7124\n", + "Current minimum: -25.3020\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:38,342\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6532\n", + "Function value obtained: -24.7817\n", + "Current minimum: -25.3020\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:46,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4499\n", + "Function value obtained: -24.4427\n", + "Current minimum: -25.3020\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:30:53,518\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7113\n", + "Function value obtained: -24.6929\n", + "Current minimum: -25.3020\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:01,177\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9036\n", + "Function value obtained: -23.7830\n", + "Current minimum: -25.3020\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:09,084\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4580\n", + "Function value obtained: -24.4437\n", + "Current minimum: -25.3020\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:16,555\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4454\n", + "Function value obtained: -23.6802\n", + "Current minimum: -25.3020\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:25,025\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5563\n", + "Function value obtained: -24.7015\n", + "Current minimum: -25.3020\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:32,572\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 7.4632\n", + "Function value obtained: -24.3289\n", + "Current minimum: -25.3020\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:41,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6063\n", + "Function value obtained: -24.3068\n", + "Current minimum: -25.3020\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:48,634\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5178\n", + "Function value obtained: -24.2538\n", + "Current minimum: -25.3020\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:31:56,195\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5609\n", + "Function value obtained: -24.2966\n", + "Current minimum: -25.3020\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:03,749\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5399\n", + "Function value obtained: -24.3529\n", + "Current minimum: -25.3020\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:11,308\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6176\n", + "Function value obtained: -24.4345\n", + "Current minimum: -25.3020\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:18,898\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6352\n", + "Function value obtained: -23.6096\n", + "Current minimum: -25.3020\n", + "Iteration No: 41 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:26,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 41 ended. Search finished for the next optimal point.\n", + "Time taken: 7.5760\n", + "Function value obtained: -24.4691\n", + "Current minimum: -25.3020\n", + "Iteration No: 42 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:34,205\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 42 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7726\n", + "Function value obtained: -24.1670\n", + "Current minimum: -25.3020\n", + "Iteration No: 43 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:41,904\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 43 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6755\n", + "Function value obtained: -24.0898\n", + "Current minimum: -25.3020\n", + "Iteration No: 44 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:50,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 44 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7092\n", + "Function value obtained: -23.8886\n", + "Current minimum: -25.3020\n", + "Iteration No: 45 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:32:58,325\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 45 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6576\n", + "Function value obtained: -25.5150\n", + "Current minimum: -25.5150\n", + "Iteration No: 46 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:33:05,988\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 46 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8140\n", + "Function value obtained: -25.4366\n", + "Current minimum: -25.5150\n", + "Iteration No: 47 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:33:13,801\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 47 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7949\n", + "Function value obtained: -23.8130\n", + "Current minimum: -25.5150\n", + "Iteration No: 48 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:33:21,563\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 48 ended. Search finished for the next optimal point.\n", + "Time taken: 7.6521\n", + "Function value obtained: -23.9176\n", + "Current minimum: -25.5150\n", + "Iteration No: 49 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:33:29,281\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 49 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7949\n", + "Function value obtained: -24.0365\n", + "Current minimum: -25.5150\n", + "Iteration No: 50 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:33:37,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 50 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8229\n", + "Function value obtained: -24.5317\n", + "Current minimum: -25.5150\n", + "Iteration No: 51 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:33:44,924\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 51 ended. Search finished for the next optimal point.\n", + "Time taken: 7.7424\n", + "Function value obtained: -25.4172\n", + "Current minimum: -25.5150\n", + "Iteration No: 52 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:33:52,637\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 52 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9909\n", + "Function value obtained: -24.3656\n", + "Current minimum: -25.5150\n", + "Iteration No: 53 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:00,614\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 53 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0818\n", + "Function value obtained: -24.5522\n", + "Current minimum: -25.5150\n", + "Iteration No: 54 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:08,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 54 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8603\n", + "Function value obtained: -24.6705\n", + "Current minimum: -25.5150\n", + "Iteration No: 55 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:16,597\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 55 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8075\n", + "Function value obtained: -24.1748\n", + "Current minimum: -25.5150\n", + "Iteration No: 56 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:24,397\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 56 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9296\n", + "Function value obtained: -24.2659\n", + "Current minimum: -25.5150\n", + "Iteration No: 57 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:32,352\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 57 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8644\n", + "Function value obtained: -25.6411\n", + "Current minimum: -25.6411\n", + "Iteration No: 58 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:40,187\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 58 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8258\n", + "Function value obtained: -24.4454\n", + "Current minimum: -25.6411\n", + "Iteration No: 59 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:48,061\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 59 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8974\n", + "Function value obtained: -23.9487\n", + "Current minimum: -25.6411\n", + "Iteration No: 60 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:34:56,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 60 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0916\n", + "Function value obtained: -25.3748\n", + "Current minimum: -25.6411\n", + "Iteration No: 61 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:35:05,019\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 61 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9288\n", + "Function value obtained: -24.3888\n", + "Current minimum: -25.6411\n", + "Iteration No: 62 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:35:13,984\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 62 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7603\n", + "Function value obtained: -23.8326\n", + "Current minimum: -25.6411\n", + "Iteration No: 63 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:35:21,691\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 63 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8378\n", + "Function value obtained: -24.1685\n", + "Current minimum: -25.6411\n", + "Iteration No: 64 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:35:29,536\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 64 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9078\n", + "Function value obtained: -24.5211\n", + "Current minimum: -25.6411\n", + "Iteration No: 65 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:35:37,469\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 65 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9601\n", + "Function value obtained: -24.8248\n", + "Current minimum: -25.6411\n", + "Iteration No: 66 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:35:45,544\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 66 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1198\n", + "Function value obtained: -24.0151\n", + "Current minimum: -25.6411\n", + "Iteration No: 67 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:35:53,590\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 67 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9493\n", + "Function value obtained: -24.6980\n", + "Current minimum: -25.6411\n", + "Iteration No: 68 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:01,522\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 68 ended. Search finished for the next optimal point.\n", + "Time taken: 7.8959\n", + "Function value obtained: -25.2712\n", + "Current minimum: -25.6411\n", + "Iteration No: 69 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:09,419\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 69 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1085\n", + "Function value obtained: -24.9859\n", + "Current minimum: -25.6411\n", + "Iteration No: 70 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:18,588\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 70 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1948\n", + "Function value obtained: -24.2225\n", + "Current minimum: -25.6411\n", + "Iteration No: 71 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:26,750\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 71 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1867\n", + "Function value obtained: -24.6552\n", + "Current minimum: -25.6411\n", + "Iteration No: 72 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:34,923\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 72 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0989\n", + "Function value obtained: -23.8279\n", + "Current minimum: -25.6411\n", + "Iteration No: 73 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:43,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 73 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1609\n", + "Function value obtained: -24.3691\n", + "Current minimum: -25.6411\n", + "Iteration No: 74 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:51,200\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 74 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1314\n", + "Function value obtained: -23.8675\n", + "Current minimum: -25.6411\n", + "Iteration No: 75 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:36:59,329\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 75 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9147\n", + "Function value obtained: -24.1955\n", + "Current minimum: -25.6411\n", + "Iteration No: 76 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:37:08,145\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 76 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0159\n", + "Function value obtained: -25.5330\n", + "Current minimum: -25.6411\n", + "Iteration No: 77 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:37:17,289\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 77 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9020\n", + "Function value obtained: -24.5606\n", + "Current minimum: -25.6411\n", + "Iteration No: 78 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:37:26,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 78 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2182\n", + "Function value obtained: -24.5709\n", + "Current minimum: -25.6411\n", + "Iteration No: 79 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:37:34,403\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 79 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1679\n", + "Function value obtained: -24.0397\n", + "Current minimum: -25.6411\n", + "Iteration No: 80 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:37:42,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 80 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9277\n", + "Function value obtained: -25.2763\n", + "Current minimum: -25.6411\n", + "Iteration No: 81 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:37:51,508\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 81 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2416\n", + "Function value obtained: -24.4807\n", + "Current minimum: -25.6411\n", + "Iteration No: 82 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:37:59,751\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 82 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0910\n", + "Function value obtained: -24.1984\n", + "Current minimum: -25.6411\n", + "Iteration No: 83 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:38:08,824\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 83 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0323\n", + "Function value obtained: -24.7295\n", + "Current minimum: -25.6411\n", + "Iteration No: 84 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:38:17,859\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 84 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3531\n", + "Function value obtained: -24.8407\n", + "Current minimum: -25.6411\n", + "Iteration No: 85 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:38:26,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 85 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1833\n", + "Function value obtained: -24.6985\n", + "Current minimum: -25.6411\n", + "Iteration No: 86 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:38:34,417\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 86 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9834\n", + "Function value obtained: -24.5221\n", + "Current minimum: -25.6411\n", + "Iteration No: 87 started. Searching for the next optimal point.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-14 21:38:43,403\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9634\n", - "Function value obtained: -109.2417\n", - "Current minimum: -111.9426\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" + "Iteration No: 87 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9983\n", + "Function value obtained: -24.2723\n", + "Current minimum: -25.6411\n", + "Iteration No: 88 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:41:34,958\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:38:52,429\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3712\n", - "Function value obtained: -108.7872\n", - "Current minimum: -111.9426\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" + "Iteration No: 88 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4214\n", + "Function value obtained: -24.5579\n", + "Current minimum: -25.6411\n", + "Iteration No: 89 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:41:46,326\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:39:00,822\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8733\n", - "Function value obtained: -107.6917\n", - "Current minimum: -111.9426\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" + "Iteration No: 89 ended. Search finished for the next optimal point.\n", + "Time taken: 8.2151\n", + "Function value obtained: -24.8131\n", + "Current minimum: -25.6411\n", + "Iteration No: 90 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:41:57,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:39:09,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8074\n", - "Function value obtained: -109.3046\n", - "Current minimum: -111.9426\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" + "Iteration No: 90 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3279\n", + "Function value obtained: -24.4567\n", + "Current minimum: -25.6411\n", + "Iteration No: 91 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:42:09,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:39:17,421\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4811\n", - "Function value obtained: -94.0775\n", - "Current minimum: -111.9426\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" + "Iteration No: 91 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2568\n", + "Function value obtained: -24.9744\n", + "Current minimum: -25.6411\n", + "Iteration No: 92 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:42:20,608\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:39:26,685\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6783\n", - "Function value obtained: -108.1891\n", - "Current minimum: -111.9426\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" + "Iteration No: 92 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1906\n", + "Function value obtained: -24.3968\n", + "Current minimum: -25.6411\n", + "Iteration No: 93 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:42:31,278\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:39:35,867\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0614\n", - "Function value obtained: -107.6197\n", - "Current minimum: -111.9426\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" + "Iteration No: 93 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2782\n", + "Function value obtained: -24.2173\n", + "Current minimum: -25.6411\n", + "Iteration No: 94 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:42:42,359\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:39:45,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4596\n", - "Function value obtained: -110.1922\n", - "Current minimum: -111.9426\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" + "Iteration No: 94 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6272\n", + "Function value obtained: -25.1702\n", + "Current minimum: -25.6411\n", + "Iteration No: 95 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:42:53,809\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:39:53,776\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8389\n", - "Function value obtained: -107.7807\n", - "Current minimum: -111.9426\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" + "Iteration No: 95 ended. Search finished for the next optimal point.\n", + "Time taken: 8.3095\n", + "Function value obtained: -24.9751\n", + "Current minimum: -25.6411\n", + "Iteration No: 96 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:43:04,600\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:40:02,101\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6981\n", - "Function value obtained: -113.1969\n", - "Current minimum: -113.1969\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" + "Iteration No: 96 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3866\n", + "Function value obtained: -24.2728\n", + "Current minimum: -25.6411\n", + "Iteration No: 97 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:43:16,765\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:40:11,460\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8803\n", - "Function value obtained: -8.2370\n", - "Current minimum: -113.1969\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" + "Iteration No: 97 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5848\n", + "Function value obtained: -24.5347\n", + "Current minimum: -25.6411\n", + "Iteration No: 98 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:43:27,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:40:20,089\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0923\n", - "Function value obtained: -108.0523\n", - "Current minimum: -113.1969\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" + "Iteration No: 98 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2427\n", + "Function value obtained: -24.8783\n", + "Current minimum: -25.6411\n", + "Iteration No: 99 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:43:39,948\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:40:29,331\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8120\n", - "Function value obtained: -110.0747\n", - "Current minimum: -113.1969\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" + "Iteration No: 99 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3042\n", + "Function value obtained: -24.2518\n", + "Current minimum: -25.6411\n", + "Iteration No: 100 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:43:51,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:40:38,623\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1298\n", - "Function value obtained: -110.4563\n", - "Current minimum: -113.1969\n", - "CPU times: user 3min 9s, sys: 4min 58s, total: 8min 8s\n", - "Wall time: 5min 42s\n" + "Iteration No: 100 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6958\n", + "Function value obtained: -24.0351\n", + "Current minimum: -25.6411\n", + "CPU times: user 19min 7s, sys: 22min 47s, total: 41min 55s\n", + "Wall time: 13min 28s\n" ] }, { "data": { "text/plain": [ - "(-113.19689737573121, [0.027374341105189527])" + "(-25.641051330631125, [0.041589547825106155])" ] }, - "execution_count": 31, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 30, verbose=True, n_jobs=-1)\n", + "msy_gp = gp_minimize(msy_obj, msy_space, n_calls = 100, verbose=True, n_jobs=-1)\n", "msy_gp.fun, msy_gp.x" ] }, @@ -2378,7 +3639,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 6, "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", "metadata": { "scrolled": true @@ -2395,7 +3656,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:44:26,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:40:47,371\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2403,9 +3664,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 9.4956\n", - "Function value obtained: -2.3549\n", - "Current minimum: -2.3549\n", + "Time taken: 8.5361\n", + "Function value obtained: -0.8805\n", + "Current minimum: -0.8805\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -2413,7 +3674,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:44:35,768\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:40:55,950\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2421,9 +3682,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 9.5832\n", - "Function value obtained: -76.5912\n", - "Current minimum: -76.5912\n", + "Time taken: 8.0200\n", + "Function value obtained: -10.7652\n", + "Current minimum: -10.7652\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -2431,7 +3692,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:44:45,350\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:41:03,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2439,9 +3700,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 9.5966\n", - "Function value obtained: -1.4268\n", - "Current minimum: -76.5912\n", + "Time taken: 8.5756\n", + "Function value obtained: -1.6751\n", + "Current minimum: -10.7652\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -2449,7 +3710,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:44:54,942\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:41:12,574\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2457,9 +3718,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 9.5925\n", - "Function value obtained: -1.6818\n", - "Current minimum: -76.5912\n", + "Time taken: 7.8685\n", + "Function value obtained: -0.8836\n", + "Current minimum: -10.7652\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -2467,7 +3728,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:45:04,561\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:41:20,409\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2475,9 +3736,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 9.6298\n", - "Function value obtained: -1.0852\n", - "Current minimum: -76.5912\n", + "Time taken: 7.8538\n", + "Function value obtained: -0.8886\n", + "Current minimum: -10.7652\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -2485,7 +3746,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:45:14,172\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:41:28,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2493,9 +3754,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 9.7183\n", + "Time taken: 8.5961\n", "Function value obtained: -0.0000\n", - "Current minimum: -76.5912\n", + "Current minimum: -10.7652\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -2503,7 +3764,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:45:23,877\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:41:36,912\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2511,9 +3772,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 9.3285\n", - "Function value obtained: -1.5627\n", - "Current minimum: -76.5912\n", + "Time taken: 7.8133\n", + "Function value obtained: -0.8618\n", + "Current minimum: -10.7652\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -2521,7 +3782,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:45:33,211\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:41:45,667\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2529,9 +3790,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 9.4120\n", - "Function value obtained: -22.1856\n", - "Current minimum: -76.5912\n", + "Time taken: 8.8872\n", + "Function value obtained: -8.4861\n", + "Current minimum: -10.7652\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -2539,7 +3800,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:45:42,635\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:41:53,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2547,9 +3808,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 9.6492\n", - "Function value obtained: -1.3382\n", - "Current minimum: -76.5912\n", + "Time taken: 8.4864\n", + "Function value obtained: -0.0000\n", + "Current minimum: -10.7652\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -2557,7 +3818,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:45:52,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:42:02,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2565,9 +3826,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 14.1676\n", - "Function value obtained: -84.7758\n", - "Current minimum: -84.7758\n", + "Time taken: 8.8322\n", + "Function value obtained: -1.3449\n", + "Current minimum: -10.7652\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -2575,7 +3836,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:46:06,527\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:42:10,883\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2583,9 +3844,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9592\n", - "Function value obtained: -82.5314\n", - "Current minimum: -84.7758\n", + "Time taken: 8.8533\n", + "Function value obtained: -13.4718\n", + "Current minimum: -13.4718\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -2593,7 +3854,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:46:17,409\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:42:19,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2601,9 +3862,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1233\n", - "Function value obtained: -82.6363\n", - "Current minimum: -84.7758\n", + "Time taken: 8.8479\n", + "Function value obtained: -13.9073\n", + "Current minimum: -13.9073\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -2611,7 +3872,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:46:28,578\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:42:28,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2619,9 +3880,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9767\n", - "Function value obtained: -80.6832\n", - "Current minimum: -84.7758\n", + "Time taken: 8.7382\n", + "Function value obtained: -13.1815\n", + "Current minimum: -13.9073\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -2629,7 +3890,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:46:39,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:42:37,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2637,9 +3898,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4019\n", - "Function value obtained: -82.1781\n", - "Current minimum: -84.7758\n", + "Time taken: 8.8847\n", + "Function value obtained: -13.5012\n", + "Current minimum: -13.9073\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -2647,7 +3908,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:46:50,974\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:42:46,232\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2655,9 +3916,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4549\n", - "Function value obtained: -82.2314\n", - "Current minimum: -84.7758\n", + "Time taken: 8.8741\n", + "Function value obtained: -14.0129\n", + "Current minimum: -14.0129\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -2665,7 +3926,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:47:02,467\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:42:55,122\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2673,9 +3934,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2693\n", - "Function value obtained: -85.0952\n", - "Current minimum: -85.0952\n", + "Time taken: 8.9245\n", + "Function value obtained: -0.8662\n", + "Current minimum: -14.0129\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -2683,7 +3944,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:47:13,676\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:43:04,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2691,9 +3952,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1551\n", - "Function value obtained: -82.6191\n", - "Current minimum: -85.0952\n", + "Time taken: 9.0960\n", + "Function value obtained: -12.8761\n", + "Current minimum: -14.0129\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -2701,7 +3962,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:47:24,911\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:43:13,129\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2709,9 +3970,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5349\n", - "Function value obtained: -6.5931\n", - "Current minimum: -85.0952\n", + "Time taken: 9.3763\n", + "Function value obtained: -13.1871\n", + "Current minimum: -14.0129\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -2719,7 +3980,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:47:35,436\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:43:22,621\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2727,9 +3988,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7792\n", - "Function value obtained: -84.5019\n", - "Current minimum: -85.0952\n", + "Time taken: 8.8706\n", + "Function value obtained: -13.4050\n", + "Current minimum: -14.0129\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -2737,7 +3998,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:47:46,183\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:43:31,391\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2745,9 +4006,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0469\n", - "Function value obtained: -84.5658\n", - "Current minimum: -85.0952\n", + "Time taken: 8.8529\n", + "Function value obtained: -12.9947\n", + "Current minimum: -14.0129\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -2755,7 +4016,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:47:56,213\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:43:40,261\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2763,9 +4024,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9517\n", - "Function value obtained: -83.2918\n", - "Current minimum: -85.0952\n", + "Time taken: 8.8490\n", + "Function value obtained: -13.1612\n", + "Current minimum: -14.0129\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -2773,7 +4034,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:48:06,165\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:43:49,130\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2781,9 +4042,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0707\n", - "Function value obtained: -85.0394\n", - "Current minimum: -85.0952\n", + "Time taken: 8.9548\n", + "Function value obtained: -13.4515\n", + "Current minimum: -14.0129\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -2791,7 +4052,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:48:16,302\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:43:58,056\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2799,9 +4060,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9502\n", - "Function value obtained: -83.4533\n", - "Current minimum: -85.0952\n", + "Time taken: 8.8747\n", + "Function value obtained: -13.4279\n", + "Current minimum: -14.0129\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -2809,7 +4070,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:48:26,281\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:44:06,970\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2817,9 +4078,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7623\n", - "Function value obtained: -83.1873\n", - "Current minimum: -85.0952\n", + "Time taken: 8.2274\n", + "Function value obtained: -13.1176\n", + "Current minimum: -14.0129\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -2827,7 +4088,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:48:36,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:44:15,168\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2835,9 +4096,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4188\n", - "Function value obtained: -83.3113\n", - "Current minimum: -85.0952\n", + "Time taken: 8.8806\n", + "Function value obtained: -13.4339\n", + "Current minimum: -14.0129\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -2845,7 +4106,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:48:47,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:44:24,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2853,9 +4114,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5156\n", - "Function value obtained: -81.1631\n", - "Current minimum: -85.0952\n", + "Time taken: 8.8061\n", + "Function value obtained: -13.8720\n", + "Current minimum: -14.0129\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -2863,7 +4124,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:48:57,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:44:32,875\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2871,9 +4132,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4621\n", - "Function value obtained: -82.2480\n", - "Current minimum: -85.0952\n", + "Time taken: 8.3807\n", + "Function value obtained: -13.7968\n", + "Current minimum: -14.0129\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -2881,7 +4142,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:49:08,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:44:41,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2889,9 +4150,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3142\n", - "Function value obtained: -84.6498\n", - "Current minimum: -85.0952\n", + "Time taken: 9.0522\n", + "Function value obtained: -13.7010\n", + "Current minimum: -14.0129\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -2899,7 +4160,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:49:18,752\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:44:50,335\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2907,9 +4168,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6948\n", - "Function value obtained: -82.5131\n", - "Current minimum: -85.0952\n", + "Time taken: 8.9705\n", + "Function value obtained: -13.6812\n", + "Current minimum: -14.0129\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -2917,7 +4178,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:49:29,450\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:44:59,315\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2925,9 +4186,9 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3540\n", - "Function value obtained: -81.5260\n", - "Current minimum: -85.0952\n", + "Time taken: 8.9994\n", + "Function value obtained: -13.0669\n", + "Current minimum: -14.0129\n", "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, @@ -2935,7 +4196,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:49:39,810\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:45:08,400\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2943,9 +4204,9 @@ "output_type": "stream", "text": [ "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7156\n", - "Function value obtained: -83.9358\n", - "Current minimum: -85.0952\n", + "Time taken: 9.0171\n", + "Function value obtained: -13.2544\n", + "Current minimum: -14.0129\n", "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, @@ -2953,7 +4214,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:49:50,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:45:17,331\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2961,9 +4222,9 @@ "output_type": "stream", "text": [ "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2034\n", - "Function value obtained: -82.3135\n", - "Current minimum: -85.0952\n", + "Time taken: 8.9555\n", + "Function value obtained: -13.6768\n", + "Current minimum: -14.0129\n", "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, @@ -2971,7 +4232,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:50:00,745\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:45:26,285\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2979,9 +4240,9 @@ "output_type": "stream", "text": [ "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4620\n", - "Function value obtained: -81.1277\n", - "Current minimum: -85.0952\n", + "Time taken: 8.9634\n", + "Function value obtained: -13.4295\n", + "Current minimum: -14.0129\n", "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, @@ -2989,7 +4250,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:50:11,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:45:35,341\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -2997,9 +4258,9 @@ "output_type": "stream", "text": [ "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3740\n", - "Function value obtained: -80.9333\n", - "Current minimum: -85.0952\n", + "Time taken: 9.1202\n", + "Function value obtained: -13.9210\n", + "Current minimum: -14.0129\n", "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, @@ -3007,7 +4268,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:50:21,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:45:44,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3015,9 +4276,9 @@ "output_type": "stream", "text": [ "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0352\n", - "Function value obtained: -82.5077\n", - "Current minimum: -85.0952\n", + "Time taken: 8.9664\n", + "Function value obtained: -13.5400\n", + "Current minimum: -14.0129\n", "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, @@ -3025,7 +4286,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:50:31,617\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:45:53,350\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3033,9 +4294,9 @@ "output_type": "stream", "text": [ "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1330\n", - "Function value obtained: -85.3373\n", - "Current minimum: -85.3373\n", + "Time taken: 9.0724\n", + "Function value obtained: -12.9979\n", + "Current minimum: -14.0129\n", "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, @@ -3043,7 +4304,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:50:41,797\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:46:02,446\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3051,9 +4312,9 @@ "output_type": "stream", "text": [ "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0345\n", - "Function value obtained: -83.6639\n", - "Current minimum: -85.3373\n", + "Time taken: 8.9292\n", + "Function value obtained: -13.6014\n", + "Current minimum: -14.0129\n", "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, @@ -3061,7 +4322,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:50:51,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:46:11,358\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3069,9 +4330,9 @@ "output_type": "stream", "text": [ "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5533\n", - "Function value obtained: -83.4928\n", - "Current minimum: -85.3373\n", + "Time taken: 9.0041\n", + "Function value obtained: -13.4956\n", + "Current minimum: -14.0129\n", "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, @@ -3079,7 +4340,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:51:02,363\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:46:20,385\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3087,9 +4348,9 @@ "output_type": "stream", "text": [ "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2894\n", - "Function value obtained: -81.7251\n", - "Current minimum: -85.3373\n", + "Time taken: 9.0723\n", + "Function value obtained: -13.3291\n", + "Current minimum: -14.0129\n", "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, @@ -3097,7 +4358,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:51:12,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:46:29,465\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3105,9 +4366,9 @@ "output_type": "stream", "text": [ "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5308\n", - "Function value obtained: -84.4095\n", - "Current minimum: -85.3373\n", + "Time taken: 9.4223\n", + "Function value obtained: -13.1945\n", + "Current minimum: -14.0129\n", "Iteration No: 41 started. Searching for the next optimal point.\n" ] }, @@ -3115,7 +4376,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:51:23,160\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:46:38,901\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3123,9 +4384,9 @@ "output_type": "stream", "text": [ "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2579\n", - "Function value obtained: -83.0318\n", - "Current minimum: -85.3373\n", + "Time taken: 9.0134\n", + "Function value obtained: -13.7415\n", + "Current minimum: -14.0129\n", "Iteration No: 42 started. Searching for the next optimal point.\n" ] }, @@ -3133,7 +4394,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:51:33,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:46:47,900\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3141,9 +4402,9 @@ "output_type": "stream", "text": [ "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2153\n", - "Function value obtained: -87.6813\n", - "Current minimum: -87.6813\n", + "Time taken: 9.1325\n", + "Function value obtained: -13.7261\n", + "Current minimum: -14.0129\n", "Iteration No: 43 started. Searching for the next optimal point.\n" ] }, @@ -3151,7 +4412,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:51:43,614\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:46:57,014\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3159,9 +4420,9 @@ "output_type": "stream", "text": [ "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3620\n", - "Function value obtained: -84.7869\n", - "Current minimum: -87.6813\n", + "Time taken: 9.1291\n", + "Function value obtained: -14.3607\n", + "Current minimum: -14.3607\n", "Iteration No: 44 started. Searching for the next optimal point.\n" ] }, @@ -3169,7 +4430,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:51:54,026\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:47:06,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3177,9 +4438,9 @@ "output_type": "stream", "text": [ "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7934\n", - "Function value obtained: -83.3213\n", - "Current minimum: -87.6813\n", + "Time taken: 9.2340\n", + "Function value obtained: -13.4453\n", + "Current minimum: -14.3607\n", "Iteration No: 45 started. Searching for the next optimal point.\n" ] }, @@ -3187,7 +4448,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:52:04,799\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:47:15,419\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3195,9 +4456,9 @@ "output_type": "stream", "text": [ "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1173\n", - "Function value obtained: -81.0243\n", - "Current minimum: -87.6813\n", + "Time taken: 9.2534\n", + "Function value obtained: -13.3665\n", + "Current minimum: -14.3607\n", "Iteration No: 46 started. Searching for the next optimal point.\n" ] }, @@ -3205,7 +4466,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:52:14,978\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:47:24,687\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3213,9 +4474,9 @@ "output_type": "stream", "text": [ "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0989\n", - "Function value obtained: -84.5181\n", - "Current minimum: -87.6813\n", + "Time taken: 9.2221\n", + "Function value obtained: -13.2631\n", + "Current minimum: -14.3607\n", "Iteration No: 47 started. Searching for the next optimal point.\n" ] }, @@ -3223,7 +4484,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:52:25,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:47:33,915\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3231,9 +4492,9 @@ "output_type": "stream", "text": [ "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2763\n", - "Function value obtained: -81.5069\n", - "Current minimum: -87.6813\n", + "Time taken: 8.7154\n", + "Function value obtained: -12.5937\n", + "Current minimum: -14.3607\n", "Iteration No: 48 started. Searching for the next optimal point.\n" ] }, @@ -3241,7 +4502,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:52:35,366\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:47:42,671\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3249,9 +4510,9 @@ "output_type": "stream", "text": [ "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7214\n", - "Function value obtained: -85.9161\n", - "Current minimum: -87.6813\n", + "Time taken: 9.0410\n", + "Function value obtained: -13.3757\n", + "Current minimum: -14.3607\n", "Iteration No: 49 started. Searching for the next optimal point.\n" ] }, @@ -3259,7 +4520,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:52:46,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:47:51,680\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3267,9 +4528,9 @@ "output_type": "stream", "text": [ "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1385\n", - "Function value obtained: -85.9747\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3935\n", + "Function value obtained: -13.9987\n", + "Current minimum: -14.3607\n", "Iteration No: 50 started. Searching for the next optimal point.\n" ] }, @@ -3277,7 +4538,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:52:57,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:48:01,053\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3285,9 +4546,9 @@ "output_type": "stream", "text": [ "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5808\n", - "Function value obtained: -82.4476\n", - "Current minimum: -87.6813\n", + "Time taken: 9.2853\n", + "Function value obtained: -13.2363\n", + "Current minimum: -14.3607\n", "Iteration No: 51 started. Searching for the next optimal point.\n" ] }, @@ -3295,7 +4556,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:53:07,799\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:48:10,353\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3303,9 +4564,9 @@ "output_type": "stream", "text": [ "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2523\n", - "Function value obtained: -84.2489\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3286\n", + "Function value obtained: -13.8577\n", + "Current minimum: -14.3607\n", "Iteration No: 52 started. Searching for the next optimal point.\n" ] }, @@ -3313,7 +4574,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:53:18,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:48:19,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3321,9 +4582,9 @@ "output_type": "stream", "text": [ "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8880\n", - "Function value obtained: -82.3852\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3766\n", + "Function value obtained: -13.4389\n", + "Current minimum: -14.3607\n", "Iteration No: 53 started. Searching for the next optimal point.\n" ] }, @@ -3331,7 +4592,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:53:28,979\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:48:29,093\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3339,9 +4600,9 @@ "output_type": "stream", "text": [ "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7186\n", - "Function value obtained: -84.4496\n", - "Current minimum: -87.6813\n", + "Time taken: 9.2926\n", + "Function value obtained: -13.5549\n", + "Current minimum: -14.3607\n", "Iteration No: 54 started. Searching for the next optimal point.\n" ] }, @@ -3349,7 +4610,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:53:39,669\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:48:38,397\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3357,9 +4618,9 @@ "output_type": "stream", "text": [ "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2500\n", - "Function value obtained: -83.0723\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3219\n", + "Function value obtained: -12.8309\n", + "Current minimum: -14.3607\n", "Iteration No: 55 started. Searching for the next optimal point.\n" ] }, @@ -3367,7 +4628,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:53:49,898\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:48:47,703\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3375,9 +4636,9 @@ "output_type": "stream", "text": [ "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1780\n", - "Function value obtained: -84.1800\n", - "Current minimum: -87.6813\n", + "Time taken: 9.1870\n", + "Function value obtained: -13.4366\n", + "Current minimum: -14.3607\n", "Iteration No: 56 started. Searching for the next optimal point.\n" ] }, @@ -3385,7 +4646,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:54:00,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:48:56,908\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3393,9 +4654,9 @@ "output_type": "stream", "text": [ "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5773\n", - "Function value obtained: -82.3404\n", - "Current minimum: -87.6813\n", + "Time taken: 9.5847\n", + "Function value obtained: -13.3848\n", + "Current minimum: -14.3607\n", "Iteration No: 57 started. Searching for the next optimal point.\n" ] }, @@ -3403,7 +4664,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:54:10,716\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:49:06,469\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3411,9 +4672,9 @@ "output_type": "stream", "text": [ "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0534\n", - "Function value obtained: -84.3037\n", - "Current minimum: -87.6813\n", + "Time taken: 8.9276\n", + "Function value obtained: -13.0915\n", + "Current minimum: -14.3607\n", "Iteration No: 58 started. Searching for the next optimal point.\n" ] }, @@ -3421,7 +4682,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:54:21,798\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:49:15,421\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3429,9 +4690,9 @@ "output_type": "stream", "text": [ "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9300\n", - "Function value obtained: -83.7342\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3176\n", + "Function value obtained: -13.7467\n", + "Current minimum: -14.3607\n", "Iteration No: 59 started. Searching for the next optimal point.\n" ] }, @@ -3439,7 +4700,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:54:32,705\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:49:24,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3447,9 +4708,9 @@ "output_type": "stream", "text": [ "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1280\n", - "Function value obtained: -83.7201\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3248\n", + "Function value obtained: -13.0519\n", + "Current minimum: -14.3607\n", "Iteration No: 60 started. Searching for the next optimal point.\n" ] }, @@ -3457,7 +4718,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:54:42,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:49:34,096\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3465,9 +4726,9 @@ "output_type": "stream", "text": [ "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7030\n", - "Function value obtained: -85.1614\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3662\n", + "Function value obtained: -13.7485\n", + "Current minimum: -14.3607\n", "Iteration No: 61 started. Searching for the next optimal point.\n" ] }, @@ -3475,7 +4736,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:54:53,543\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:49:43,396\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3483,9 +4744,9 @@ "output_type": "stream", "text": [ "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5661\n", - "Function value obtained: -82.2000\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4224\n", + "Function value obtained: -13.2279\n", + "Current minimum: -14.3607\n", "Iteration No: 62 started. Searching for the next optimal point.\n" ] }, @@ -3493,7 +4754,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:55:04,078\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:49:52,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3501,9 +4762,9 @@ "output_type": "stream", "text": [ "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3530\n", - "Function value obtained: -81.5854\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4771\n", + "Function value obtained: -13.4308\n", + "Current minimum: -14.3607\n", "Iteration No: 63 started. Searching for the next optimal point.\n" ] }, @@ -3511,7 +4772,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:55:15,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:50:02,324\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3519,9 +4780,9 @@ "output_type": "stream", "text": [ "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3942\n", - "Function value obtained: -81.9932\n", - "Current minimum: -87.6813\n", + "Time taken: 9.5040\n", + "Function value obtained: -13.4533\n", + "Current minimum: -14.3607\n", "Iteration No: 64 started. Searching for the next optimal point.\n" ] }, @@ -3529,7 +4790,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:55:25,907\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:50:11,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3537,9 +4798,9 @@ "output_type": "stream", "text": [ "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4690\n", - "Function value obtained: -83.0830\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4804\n", + "Function value obtained: -13.6154\n", + "Current minimum: -14.3607\n", "Iteration No: 65 started. Searching for the next optimal point.\n" ] }, @@ -3547,7 +4808,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:55:36,346\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:50:21,363\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3555,9 +4816,9 @@ "output_type": "stream", "text": [ "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8111\n", - "Function value obtained: -83.3864\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4486\n", + "Function value obtained: -13.1647\n", + "Current minimum: -14.3607\n", "Iteration No: 66 started. Searching for the next optimal point.\n" ] }, @@ -3565,7 +4826,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:55:47,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:50:30,801\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3573,9 +4834,9 @@ "output_type": "stream", "text": [ "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9900\n", - "Function value obtained: -83.8025\n", - "Current minimum: -87.6813\n", + "Time taken: 9.6126\n", + "Function value obtained: -13.5591\n", + "Current minimum: -14.3607\n", "Iteration No: 67 started. Searching for the next optimal point.\n" ] }, @@ -3583,7 +4844,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:55:58,149\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:50:40,430\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3591,9 +4852,9 @@ "output_type": "stream", "text": [ "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3083\n", - "Function value obtained: -85.9399\n", - "Current minimum: -87.6813\n", + "Time taken: 9.0655\n", + "Function value obtained: -13.4407\n", + "Current minimum: -14.3607\n", "Iteration No: 68 started. Searching for the next optimal point.\n" ] }, @@ -3601,7 +4862,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:56:08,444\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:50:49,435\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3609,9 +4870,9 @@ "output_type": "stream", "text": [ "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4192\n", - "Function value obtained: -81.4979\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4012\n", + "Function value obtained: -13.8073\n", + "Current minimum: -14.3607\n", "Iteration No: 69 started. Searching for the next optimal point.\n" ] }, @@ -3619,7 +4880,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:56:18,851\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:50:58,984\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3627,9 +4888,9 @@ "output_type": "stream", "text": [ "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6227\n", - "Function value obtained: -84.4786\n", - "Current minimum: -87.6813\n", + "Time taken: 9.5553\n", + "Function value obtained: -13.0539\n", + "Current minimum: -14.3607\n", "Iteration No: 70 started. Searching for the next optimal point.\n" ] }, @@ -3637,7 +4898,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:56:29,506\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:51:08,437\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3645,9 +4906,9 @@ "output_type": "stream", "text": [ "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4163\n", - "Function value obtained: -81.7339\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4417\n", + "Function value obtained: -13.1679\n", + "Current minimum: -14.3607\n", "Iteration No: 71 started. Searching for the next optimal point.\n" ] }, @@ -3655,7 +4916,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:56:39,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:51:17,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3663,9 +4924,9 @@ "output_type": "stream", "text": [ "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8384\n", - "Function value obtained: -84.2707\n", - "Current minimum: -87.6813\n", + "Time taken: 9.0360\n", + "Function value obtained: -13.8827\n", + "Current minimum: -14.3607\n", "Iteration No: 72 started. Searching for the next optimal point.\n" ] }, @@ -3673,7 +4934,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:56:50,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:51:26,901\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3681,9 +4942,9 @@ "output_type": "stream", "text": [ "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6763\n", - "Function value obtained: -84.9098\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4049\n", + "Function value obtained: -13.7694\n", + "Current minimum: -14.3607\n", "Iteration No: 73 started. Searching for the next optimal point.\n" ] }, @@ -3691,7 +4952,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:57:01,519\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:51:36,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3699,9 +4960,9 @@ "output_type": "stream", "text": [ "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4021\n", - "Function value obtained: -84.8740\n", - "Current minimum: -87.6813\n", + "Time taken: 9.8337\n", + "Function value obtained: -13.5275\n", + "Current minimum: -14.3607\n", "Iteration No: 74 started. Searching for the next optimal point.\n" ] }, @@ -3709,7 +4970,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:57:12,850\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:51:46,184\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3717,9 +4978,9 @@ "output_type": "stream", "text": [ "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5167\n", - "Function value obtained: -82.2318\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4928\n", + "Function value obtained: -13.0264\n", + "Current minimum: -14.3607\n", "Iteration No: 75 started. Searching for the next optimal point.\n" ] }, @@ -3727,7 +4988,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:57:24,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:51:55,673\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3735,9 +4996,9 @@ "output_type": "stream", "text": [ "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7558\n", - "Function value obtained: -83.3389\n", - "Current minimum: -87.6813\n", + "Time taken: 9.3700\n", + "Function value obtained: -13.1872\n", + "Current minimum: -14.3607\n", "Iteration No: 76 started. Searching for the next optimal point.\n" ] }, @@ -3745,7 +5006,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:57:35,125\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:52:05,043\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3753,9 +5014,9 @@ "output_type": "stream", "text": [ "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3781\n", - "Function value obtained: -81.7042\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4565\n", + "Function value obtained: -13.2624\n", + "Current minimum: -14.3607\n", "Iteration No: 77 started. Searching for the next optimal point.\n" ] }, @@ -3763,7 +5024,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:57:46,585\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:52:14,517\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3771,9 +5032,9 @@ "output_type": "stream", "text": [ "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6069\n", - "Function value obtained: -84.0424\n", - "Current minimum: -87.6813\n", + "Time taken: 9.7772\n", + "Function value obtained: -13.8218\n", + "Current minimum: -14.3607\n", "Iteration No: 78 started. Searching for the next optimal point.\n" ] }, @@ -3781,7 +5042,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:57:57,169\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:52:24,301\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3789,9 +5050,9 @@ "output_type": "stream", "text": [ "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5971\n", - "Function value obtained: -83.3943\n", - "Current minimum: -87.6813\n", + "Time taken: 9.9578\n", + "Function value obtained: -13.4855\n", + "Current minimum: -14.3607\n", "Iteration No: 79 started. Searching for the next optimal point.\n" ] }, @@ -3799,7 +5060,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:58:07,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:52:34,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3807,9 +5068,9 @@ "output_type": "stream", "text": [ "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4682\n", - "Function value obtained: -81.6657\n", - "Current minimum: -87.6813\n", + "Time taken: 9.5770\n", + "Function value obtained: -13.2441\n", + "Current minimum: -14.3607\n", "Iteration No: 80 started. Searching for the next optimal point.\n" ] }, @@ -3817,7 +5078,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:58:18,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:52:43,855\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3825,9 +5086,9 @@ "output_type": "stream", "text": [ "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8296\n", - "Function value obtained: -80.3942\n", - "Current minimum: -87.6813\n", + "Time taken: 9.6434\n", + "Function value obtained: -13.0880\n", + "Current minimum: -14.3607\n", "Iteration No: 81 started. Searching for the next optimal point.\n" ] }, @@ -3835,7 +5096,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:58:29,077\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:52:53,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3843,9 +5104,9 @@ "output_type": "stream", "text": [ "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8820\n", - "Function value obtained: -84.0638\n", - "Current minimum: -87.6813\n", + "Time taken: 9.8181\n", + "Function value obtained: -13.9839\n", + "Current minimum: -14.3607\n", "Iteration No: 82 started. Searching for the next optimal point.\n" ] }, @@ -3853,7 +5114,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:58:40,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:53:04,332\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3861,9 +5122,9 @@ "output_type": "stream", "text": [ "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7674\n", - "Function value obtained: -85.8976\n", - "Current minimum: -87.6813\n", + "Time taken: 10.6416\n", + "Function value obtained: -13.1697\n", + "Current minimum: -14.3607\n", "Iteration No: 83 started. Searching for the next optimal point.\n" ] }, @@ -3871,7 +5132,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:58:50,836\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:53:13,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3879,9 +5140,9 @@ "output_type": "stream", "text": [ "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0881\n", - "Function value obtained: -83.2915\n", - "Current minimum: -87.6813\n", + "Time taken: 9.4978\n", + "Function value obtained: -13.2596\n", + "Current minimum: -14.3607\n", "Iteration No: 84 started. Searching for the next optimal point.\n" ] }, @@ -3889,7 +5150,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:59:01,863\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:53:23,479\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3897,9 +5158,9 @@ "output_type": "stream", "text": [ "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7816\n", - "Function value obtained: -82.4830\n", - "Current minimum: -87.6813\n", + "Time taken: 9.7327\n", + "Function value obtained: -13.3961\n", + "Current minimum: -14.3607\n", "Iteration No: 85 started. Searching for the next optimal point.\n" ] }, @@ -3907,7 +5168,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:59:12,630\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:53:33,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3915,9 +5176,9 @@ "output_type": "stream", "text": [ "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8340\n", - "Function value obtained: -82.3044\n", - "Current minimum: -87.6813\n", + "Time taken: 9.9664\n", + "Function value obtained: -13.4210\n", + "Current minimum: -14.3607\n", "Iteration No: 86 started. Searching for the next optimal point.\n" ] }, @@ -3925,7 +5186,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:59:23,482\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:53:43,187\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3933,9 +5194,9 @@ "output_type": "stream", "text": [ "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0930\n", - "Function value obtained: -83.4512\n", - "Current minimum: -87.6813\n", + "Time taken: 10.0445\n", + "Function value obtained: -12.9784\n", + "Current minimum: -14.3607\n", "Iteration No: 87 started. Searching for the next optimal point.\n" ] }, @@ -3943,7 +5204,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:59:34,508\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:53:53,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3951,9 +5212,9 @@ "output_type": "stream", "text": [ "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5722\n", - "Function value obtained: -81.6248\n", - "Current minimum: -87.6813\n", + "Time taken: 9.5459\n", + "Function value obtained: -13.6958\n", + "Current minimum: -14.3607\n", "Iteration No: 88 started. Searching for the next optimal point.\n" ] }, @@ -3961,7 +5222,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:59:45,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:54:02,776\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3969,9 +5230,9 @@ "output_type": "stream", "text": [ "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4563\n", - "Function value obtained: -84.0662\n", - "Current minimum: -87.6813\n", + "Time taken: 9.5783\n", + "Function value obtained: -13.5590\n", + "Current minimum: -14.3607\n", "Iteration No: 89 started. Searching for the next optimal point.\n" ] }, @@ -3979,7 +5240,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 22:59:56,572\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:54:12,344\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3987,9 +5248,9 @@ "output_type": "stream", "text": [ "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1103\n", - "Function value obtained: -83.8722\n", - "Current minimum: -87.6813\n", + "Time taken: 9.5002\n", + "Function value obtained: -13.6632\n", + "Current minimum: -14.3607\n", "Iteration No: 90 started. Searching for the next optimal point.\n" ] }, @@ -3997,7 +5258,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:00:07,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:54:21,860\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4005,9 +5266,9 @@ "output_type": "stream", "text": [ "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2511\n", - "Function value obtained: -82.7655\n", - "Current minimum: -87.6813\n", + "Time taken: 10.0646\n", + "Function value obtained: -13.4114\n", + "Current minimum: -14.3607\n", "Iteration No: 91 started. Searching for the next optimal point.\n" ] }, @@ -4015,7 +5276,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:00:18,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:54:31,949\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4023,9 +5284,9 @@ "output_type": "stream", "text": [ "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6790\n", - "Function value obtained: -83.7293\n", - "Current minimum: -87.6813\n", + "Time taken: 9.7824\n", + "Function value obtained: -13.3392\n", + "Current minimum: -14.3607\n", "Iteration No: 92 started. Searching for the next optimal point.\n" ] }, @@ -4033,7 +5294,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:00:30,621\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:54:41,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4041,9 +5302,9 @@ "output_type": "stream", "text": [ "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2543\n", - "Function value obtained: -83.6100\n", - "Current minimum: -87.6813\n", + "Time taken: 10.0170\n", + "Function value obtained: -13.5392\n", + "Current minimum: -14.3607\n", "Iteration No: 93 started. Searching for the next optimal point.\n" ] }, @@ -4051,7 +5312,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:00:42,002\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:54:51,768\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4059,9 +5320,9 @@ "output_type": "stream", "text": [ "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6022\n", - "Function value obtained: -85.6795\n", - "Current minimum: -87.6813\n", + "Time taken: 9.8686\n", + "Function value obtained: -13.9509\n", + "Current minimum: -14.3607\n", "Iteration No: 94 started. Searching for the next optimal point.\n" ] }, @@ -4069,7 +5330,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:00:53,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:55:01,596\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4077,9 +5338,9 @@ "output_type": "stream", "text": [ "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8464\n", - "Function value obtained: -83.3303\n", - "Current minimum: -87.6813\n", + "Time taken: 9.9030\n", + "Function value obtained: -13.0878\n", + "Current minimum: -14.3607\n", "Iteration No: 95 started. Searching for the next optimal point.\n" ] }, @@ -4087,7 +5348,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:01:04,437\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:55:11,580\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4095,9 +5356,9 @@ "output_type": "stream", "text": [ "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0150\n", - "Function value obtained: -84.7113\n", - "Current minimum: -87.6813\n", + "Time taken: 10.1832\n", + "Function value obtained: -13.7215\n", + "Current minimum: -14.3607\n", "Iteration No: 96 started. Searching for the next optimal point.\n" ] }, @@ -4105,7 +5366,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:01:15,485\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:55:21,759\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4113,9 +5374,9 @@ "output_type": "stream", "text": [ "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0428\n", - "Function value obtained: -83.2035\n", - "Current minimum: -87.6813\n", + "Time taken: 10.1138\n", + "Function value obtained: -14.1164\n", + "Current minimum: -14.3607\n", "Iteration No: 97 started. Searching for the next optimal point.\n" ] }, @@ -4123,7 +5384,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:01:27,600\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:55:31,857\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4131,9 +5392,9 @@ "output_type": "stream", "text": [ "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5873\n", - "Function value obtained: -84.2205\n", - "Current minimum: -87.6813\n", + "Time taken: 9.8295\n", + "Function value obtained: -13.3599\n", + "Current minimum: -14.3607\n", "Iteration No: 98 started. Searching for the next optimal point.\n" ] }, @@ -4141,7 +5402,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:01:39,082\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:55:41,665\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4149,9 +5410,9 @@ "output_type": "stream", "text": [ "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1665\n", - "Function value obtained: -82.9162\n", - "Current minimum: -87.6813\n", + "Time taken: 10.3818\n", + "Function value obtained: -13.8206\n", + "Current minimum: -14.3607\n", "Iteration No: 99 started. Searching for the next optimal point.\n" ] }, @@ -4159,7 +5420,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:01:50,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:55:52,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4167,9 +5428,9 @@ "output_type": "stream", "text": [ "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3967\n", - "Function value obtained: -84.0656\n", - "Current minimum: -87.6813\n", + "Time taken: 9.8385\n", + "Function value obtained: -13.2202\n", + "Current minimum: -14.3607\n", "Iteration No: 100 started. Searching for the next optimal point.\n" ] }, @@ -4177,7 +5438,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 23:02:01,628\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:56:01,897\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4185,20 +5446,20 @@ "output_type": "stream", "text": [ "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1795\n", - "Function value obtained: -82.6607\n", - "Current minimum: -87.6813\n", - "CPU times: user 20min 19s, sys: 24min, total: 44min 19s\n", - "Wall time: 17min 45s\n" + "Time taken: 10.1404\n", + "Function value obtained: -13.2628\n", + "Current minimum: -14.3607\n", + "CPU times: user 19min 26s, sys: 22min 32s, total: 41min 59s\n", + "Wall time: 15min 24s\n" ] }, { "data": { "text/plain": [ - "(-87.68129914399789, [-0.01050109469304239])" + "(-14.360743668778438, [0.06853157734816939])" ] }, - "execution_count": 25, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -4797,7 +6058,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 7, "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", "metadata": { "scrolled": true @@ -4814,7 +6075,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:05:36,343\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:56:12,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4822,9 +6083,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 8.1115\n", - "Function value obtained: -7.6290\n", - "Current minimum: -7.6290\n", + "Time taken: 9.1369\n", + "Function value obtained: -6.9098\n", + "Current minimum: -6.9098\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -4832,7 +6093,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:05:44,548\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:56:22,405\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4840,9 +6101,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 8.9869\n", - "Function value obtained: -0.0278\n", - "Current minimum: -7.6290\n", + "Time taken: 10.6116\n", + "Function value obtained: -23.3946\n", + "Current minimum: -23.3946\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -4850,7 +6111,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:05:53,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:56:31,936\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4858,9 +6119,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 8.9109\n", - "Function value obtained: -2.9872\n", - "Current minimum: -7.6290\n", + "Time taken: 9.2578\n", + "Function value obtained: -0.8235\n", + "Current minimum: -23.3946\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -4868,7 +6129,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:06:02,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:56:41,090\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4876,9 +6137,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 8.8692\n", - "Function value obtained: -114.4860\n", - "Current minimum: -114.4860\n", + "Time taken: 9.1994\n", + "Function value obtained: -11.9550\n", + "Current minimum: -23.3946\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -4886,7 +6147,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:06:11,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:56:50,327\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4894,9 +6155,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 9.0040\n", - "Function value obtained: -1.8067\n", - "Current minimum: -114.4860\n", + "Time taken: 9.2443\n", + "Function value obtained: -6.0755\n", + "Current minimum: -23.3946\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -4904,7 +6165,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:06:20,252\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:56:59,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4912,9 +6173,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 8.9358\n", - "Function value obtained: -1.6200\n", - "Current minimum: -114.4860\n", + "Time taken: 9.5648\n", + "Function value obtained: -1.0681\n", + "Current minimum: -23.3946\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -4922,7 +6183,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:06:29,234\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:57:09,177\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4930,9 +6191,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 8.8870\n", - "Function value obtained: -22.4254\n", - "Current minimum: -114.4860\n", + "Time taken: 9.3175\n", + "Function value obtained: -0.9120\n", + "Current minimum: -23.3946\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -4940,7 +6201,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:06:38,107\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:57:18,500\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4948,9 +6209,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 9.1721\n", - "Function value obtained: -11.3443\n", - "Current minimum: -114.4860\n", + "Time taken: 9.0635\n", + "Function value obtained: -0.9355\n", + "Current minimum: -23.3946\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -4958,7 +6219,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:06:47,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:57:27,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4966,9 +6227,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 9.0016\n", - "Function value obtained: -0.4134\n", - "Current minimum: -114.4860\n", + "Time taken: 9.2800\n", + "Function value obtained: -10.8811\n", + "Current minimum: -23.3946\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -4976,7 +6237,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:06:56,272\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:57:36,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4984,9 +6245,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 9.2513\n", - "Function value obtained: -79.7388\n", - "Current minimum: -114.4860\n", + "Time taken: 9.9878\n", + "Function value obtained: -3.4166\n", + "Current minimum: -23.3946\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -4994,7 +6255,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:07:05,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:57:46,765\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5002,9 +6263,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5514\n", - "Function value obtained: -0.0000\n", - "Current minimum: -114.4860\n", + "Time taken: 9.4451\n", + "Function value obtained: -9.8946\n", + "Current minimum: -23.3946\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -5012,7 +6273,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:07:14,075\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:57:56,285\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5020,9 +6281,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1391\n", - "Function value obtained: -99.9411\n", - "Current minimum: -114.4860\n", + "Time taken: 9.1931\n", + "Function value obtained: -22.9488\n", + "Current minimum: -23.3946\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -5030,7 +6291,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:07:23,196\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:58:05,456\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5038,9 +6299,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1645\n", - "Function value obtained: -0.0000\n", - "Current minimum: -114.4860\n", + "Time taken: 9.6181\n", + "Function value obtained: -23.4292\n", + "Current minimum: -23.4292\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -5048,7 +6309,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:07:32,396\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:58:15,074\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5056,9 +6317,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2975\n", - "Function value obtained: -38.4953\n", - "Current minimum: -114.4860\n", + "Time taken: 9.6677\n", + "Function value obtained: -22.9264\n", + "Current minimum: -23.4292\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -5066,7 +6327,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:07:41,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:58:24,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5074,9 +6335,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4653\n", - "Function value obtained: -113.7155\n", - "Current minimum: -114.4860\n", + "Time taken: 9.5065\n", + "Function value obtained: -24.0237\n", + "Current minimum: -24.0237\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -5084,7 +6345,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:07:51,132\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:58:34,247\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5092,9 +6353,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2698\n", - "Function value obtained: -114.0410\n", - "Current minimum: -114.4860\n", + "Time taken: 9.4501\n", + "Function value obtained: -24.7583\n", + "Current minimum: -24.7583\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -5102,7 +6363,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:08:00,425\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:58:43,717\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5110,9 +6371,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4442\n", - "Function value obtained: -112.5988\n", - "Current minimum: -114.4860\n", + "Time taken: 9.4086\n", + "Function value obtained: -22.9982\n", + "Current minimum: -24.7583\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -5120,7 +6381,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:08:09,879\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:58:53,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5128,9 +6389,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7591\n", - "Function value obtained: -110.7040\n", - "Current minimum: -114.4860\n", + "Time taken: 9.8888\n", + "Function value obtained: -24.8285\n", + "Current minimum: -24.8285\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -5138,7 +6399,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:08:19,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:59:03,017\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5146,9 +6407,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1960\n", - "Function value obtained: -97.3440\n", - "Current minimum: -114.4860\n", + "Time taken: 10.0818\n", + "Function value obtained: -25.0659\n", + "Current minimum: -25.0659\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -5156,7 +6417,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:08:29,839\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:59:13,115\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5164,9 +6425,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1163\n", - "Function value obtained: -100.1929\n", - "Current minimum: -114.4860\n", + "Time taken: 10.0422\n", + "Function value obtained: -24.9174\n", + "Current minimum: -25.0659\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -5174,7 +6435,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:08:38,979\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:59:23,116\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5182,9 +6443,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7422\n", - "Function value obtained: -116.8670\n", - "Current minimum: -116.8670\n", + "Time taken: 9.5188\n", + "Function value obtained: -25.0539\n", + "Current minimum: -25.0659\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -5192,7 +6453,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:08:48,712\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:59:32,666\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5200,9 +6461,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4041\n", - "Function value obtained: -115.7852\n", - "Current minimum: -116.8670\n", + "Time taken: 10.2766\n", + "Function value obtained: -16.8033\n", + "Current minimum: -25.0659\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -5210,7 +6471,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:08:58,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:59:43,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5218,9 +6479,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1661\n", - "Function value obtained: -112.5786\n", - "Current minimum: -116.8670\n", + "Time taken: 9.5464\n", + "Function value obtained: -0.0000\n", + "Current minimum: -25.0659\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -5228,7 +6489,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:09:07,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 21:59:52,511\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5236,9 +6497,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5259\n", - "Function value obtained: -116.7535\n", - "Current minimum: -116.8670\n", + "Time taken: 9.6295\n", + "Function value obtained: -24.0511\n", + "Current minimum: -25.0659\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -5246,7 +6507,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:09:16,837\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:00:02,164\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5254,9 +6515,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0995\n", - "Function value obtained: -117.7504\n", - "Current minimum: -117.7504\n", + "Time taken: 9.7257\n", + "Function value obtained: -24.1822\n", + "Current minimum: -25.0659\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -5264,7 +6525,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:09:25,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:00:11,920\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5272,9 +6533,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5610\n", - "Function value obtained: -80.7927\n", - "Current minimum: -117.7504\n", + "Time taken: 9.7583\n", + "Function value obtained: -23.5604\n", + "Current minimum: -25.0659\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -5282,7 +6543,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:09:35,460\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:00:21,661\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5290,9 +6551,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7079\n", - "Function value obtained: -115.0328\n", - "Current minimum: -117.7504\n", + "Time taken: 10.4272\n", + "Function value obtained: -14.0642\n", + "Current minimum: -25.0659\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -5300,7 +6561,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:09:45,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:00:32,105\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5308,9 +6569,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4450\n", - "Function value obtained: -115.6605\n", - "Current minimum: -117.7504\n", + "Time taken: 10.0236\n", + "Function value obtained: -0.0525\n", + "Current minimum: -25.0659\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -5318,7 +6579,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:09:54,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:00:42,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5326,9 +6587,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5070\n", - "Function value obtained: -113.3710\n", - "Current minimum: -117.7504\n", + "Time taken: 10.3373\n", + "Function value obtained: -24.3139\n", + "Current minimum: -25.0659\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -5336,7 +6597,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:10:04,202\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:00:52,499\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5344,9 +6605,9 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5401\n", - "Function value obtained: -0.0000\n", - "Current minimum: -117.7504\n", + "Time taken: 10.2966\n", + "Function value obtained: -24.0899\n", + "Current minimum: -25.0659\n", "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, @@ -5354,7 +6615,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:10:13,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:01:02,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5362,9 +6623,9 @@ "output_type": "stream", "text": [ "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6143\n", - "Function value obtained: -0.0000\n", - "Current minimum: -117.7504\n", + "Time taken: 10.1054\n", + "Function value obtained: -0.0016\n", + "Current minimum: -25.0659\n", "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, @@ -5372,7 +6633,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:10:23,446\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:01:12,898\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5380,9 +6641,9 @@ "output_type": "stream", "text": [ "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5648\n", - "Function value obtained: -113.4145\n", - "Current minimum: -117.7504\n", + "Time taken: 9.9714\n", + "Function value obtained: -0.8500\n", + "Current minimum: -25.0659\n", "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, @@ -5390,7 +6651,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:10:32,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:01:22,851\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5398,9 +6659,9 @@ "output_type": "stream", "text": [ "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6172\n", - "Function value obtained: -1.6111\n", - "Current minimum: -117.7504\n", + "Time taken: 10.3239\n", + "Function value obtained: -23.9861\n", + "Current minimum: -25.0659\n", "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, @@ -5408,7 +6669,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:10:42,571\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:01:33,171\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5416,9 +6677,9 @@ "output_type": "stream", "text": [ "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5673\n", - "Function value obtained: -113.1052\n", - "Current minimum: -117.7504\n", + "Time taken: 9.9635\n", + "Function value obtained: -28.6469\n", + "Current minimum: -28.6469\n", "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, @@ -5426,7 +6687,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:10:52,090\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:01:43,113\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5434,9 +6695,9 @@ "output_type": "stream", "text": [ "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0585\n", - "Function value obtained: -120.8722\n", - "Current minimum: -120.8722\n", + "Time taken: 9.8086\n", + "Function value obtained: -29.9544\n", + "Current minimum: -29.9544\n", "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, @@ -5444,7 +6705,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:11:01,149\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:01:52,960\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5452,9 +6713,9 @@ "output_type": "stream", "text": [ "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4334\n", - "Function value obtained: -123.5789\n", - "Current minimum: -123.5789\n", + "Time taken: 9.9066\n", + "Function value obtained: -31.4997\n", + "Current minimum: -31.4997\n", "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, @@ -5462,7 +6723,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:11:10,627\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:02:02,873\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5470,9 +6731,9 @@ "output_type": "stream", "text": [ "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7011\n", - "Function value obtained: -126.7480\n", - "Current minimum: -126.7480\n", + "Time taken: 10.1156\n", + "Function value obtained: -31.0628\n", + "Current minimum: -31.4997\n", "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, @@ -5480,7 +6741,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:11:20,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:02:12,984\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5488,9 +6749,9 @@ "output_type": "stream", "text": [ "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5923\n", - "Function value obtained: -122.9114\n", - "Current minimum: -126.7480\n", + "Time taken: 9.8326\n", + "Function value obtained: -30.5120\n", + "Current minimum: -31.4997\n", "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, @@ -5498,7 +6759,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:11:29,899\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:02:22,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5506,9 +6767,9 @@ "output_type": "stream", "text": [ "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3993\n", - "Function value obtained: -126.0715\n", - "Current minimum: -126.7480\n", + "Time taken: 9.6122\n", + "Function value obtained: -30.8646\n", + "Current minimum: -31.4997\n", "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, @@ -5516,7 +6777,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:11:39,298\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:02:32,436\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5524,9 +6785,9 @@ "output_type": "stream", "text": [ "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5846\n", - "Function value obtained: -1.1401\n", - "Current minimum: -126.7480\n", + "Time taken: 9.9241\n", + "Function value obtained: -0.8351\n", + "Current minimum: -31.4997\n", "Iteration No: 41 started. Searching for the next optimal point.\n" ] }, @@ -5534,7 +6795,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:11:48,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:02:42,366\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5542,9 +6803,9 @@ "output_type": "stream", "text": [ "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5929\n", - "Function value obtained: -124.3263\n", - "Current minimum: -126.7480\n", + "Time taken: 10.0497\n", + "Function value obtained: -1.7610\n", + "Current minimum: -31.4997\n", "Iteration No: 42 started. Searching for the next optimal point.\n" ] }, @@ -5552,7 +6813,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:11:58,560\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:02:52,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5560,9 +6821,9 @@ "output_type": "stream", "text": [ "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6709\n", - "Function value obtained: -111.2009\n", - "Current minimum: -126.7480\n", + "Time taken: 9.8420\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.4997\n", "Iteration No: 43 started. Searching for the next optimal point.\n" ] }, @@ -5570,7 +6831,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:12:08,277\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:03:02,235\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5578,9 +6839,9 @@ "output_type": "stream", "text": [ "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7202\n", - "Function value obtained: -121.5537\n", - "Current minimum: -126.7480\n", + "Time taken: 10.0922\n", + "Function value obtained: -17.3562\n", + "Current minimum: -31.4997\n", "Iteration No: 44 started. Searching for the next optimal point.\n" ] }, @@ -5588,7 +6849,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:12:17,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:03:12,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5596,9 +6857,9 @@ "output_type": "stream", "text": [ "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6736\n", - "Function value obtained: -108.7414\n", - "Current minimum: -126.7480\n", + "Time taken: 10.0011\n", + "Function value obtained: -29.8605\n", + "Current minimum: -31.4997\n", "Iteration No: 45 started. Searching for the next optimal point.\n" ] }, @@ -5606,7 +6867,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:12:27,593\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:03:22,363\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5614,9 +6875,9 @@ "output_type": "stream", "text": [ "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2501\n", - "Function value obtained: -0.0000\n", - "Current minimum: -126.7480\n", + "Time taken: 10.2451\n", + "Function value obtained: -0.9353\n", + "Current minimum: -31.4997\n", "Iteration No: 46 started. Searching for the next optimal point.\n" ] }, @@ -5624,7 +6885,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:12:36,834\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:03:32,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5632,9 +6893,9 @@ "output_type": "stream", "text": [ "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6360\n", - "Function value obtained: -4.1430\n", - "Current minimum: -126.7480\n", + "Time taken: 10.2935\n", + "Function value obtained: -17.2944\n", + "Current minimum: -31.4997\n", "Iteration No: 47 started. Searching for the next optimal point.\n" ] }, @@ -5642,7 +6903,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:12:46,449\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:03:42,913\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5650,9 +6911,9 @@ "output_type": "stream", "text": [ "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7744\n", - "Function value obtained: -110.3508\n", - "Current minimum: -126.7480\n", + "Time taken: 10.7296\n", + "Function value obtained: -31.2677\n", + "Current minimum: -31.4997\n", "Iteration No: 48 started. Searching for the next optimal point.\n" ] }, @@ -5660,7 +6921,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:12:56,292\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:03:54,648\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5668,9 +6929,9 @@ "output_type": "stream", "text": [ "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8822\n", - "Function value obtained: -106.6135\n", - "Current minimum: -126.7480\n", + "Time taken: 11.0657\n", + "Function value obtained: -31.9079\n", + "Current minimum: -31.9079\n", "Iteration No: 49 started. Searching for the next optimal point.\n" ] }, @@ -5678,7 +6939,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:13:06,116\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:04:04,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5686,9 +6947,9 @@ "output_type": "stream", "text": [ "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8239\n", - "Function value obtained: -71.3470\n", - "Current minimum: -126.7480\n", + "Time taken: 9.9339\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.9079\n", "Iteration No: 50 started. Searching for the next optimal point.\n" ] }, @@ -5696,7 +6957,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:13:16,010\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:04:14,653\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5704,9 +6965,9 @@ "output_type": "stream", "text": [ "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8542\n", - "Function value obtained: -101.8507\n", - "Current minimum: -126.7480\n", + "Time taken: 10.2234\n", + "Function value obtained: -31.1134\n", + "Current minimum: -31.9079\n", "Iteration No: 51 started. Searching for the next optimal point.\n" ] }, @@ -5714,7 +6975,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:13:25,879\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:04:24,882\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5722,9 +6983,9 @@ "output_type": "stream", "text": [ "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1099\n", - "Function value obtained: -103.4892\n", - "Current minimum: -126.7480\n", + "Time taken: 9.8494\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.9079\n", "Iteration No: 52 started. Searching for the next optimal point.\n" ] }, @@ -5732,7 +6993,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:13:35,931\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:04:34,781\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5740,9 +7001,9 @@ "output_type": "stream", "text": [ "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3624\n", - "Function value obtained: -0.0000\n", - "Current minimum: -126.7480\n", + "Time taken: 10.2401\n", + "Function value obtained: -3.7063\n", + "Current minimum: -31.9079\n", "Iteration No: 53 started. Searching for the next optimal point.\n" ] }, @@ -5750,7 +7011,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:13:45,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:04:45,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5758,9 +7019,9 @@ "output_type": "stream", "text": [ "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7868\n", - "Function value obtained: -103.6936\n", - "Current minimum: -126.7480\n", + "Time taken: 10.5893\n", + "Function value obtained: -30.3539\n", + "Current minimum: -31.9079\n", "Iteration No: 54 started. Searching for the next optimal point.\n" ] }, @@ -5768,7 +7029,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:13:55,095\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:04:55,597\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5776,9 +7037,9 @@ "output_type": "stream", "text": [ "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6495\n", - "Function value obtained: -46.2318\n", - "Current minimum: -126.7480\n", + "Time taken: 10.3607\n", + "Function value obtained: -0.0497\n", + "Current minimum: -31.9079\n", "Iteration No: 55 started. Searching for the next optimal point.\n" ] }, @@ -5786,7 +7047,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:14:04,753\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:05:05,976\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5794,9 +7055,9 @@ "output_type": "stream", "text": [ "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2243\n", - "Function value obtained: -125.8399\n", - "Current minimum: -126.7480\n", + "Time taken: 10.9248\n", + "Function value obtained: -0.9863\n", + "Current minimum: -31.9079\n", "Iteration No: 56 started. Searching for the next optimal point.\n" ] }, @@ -5804,7 +7065,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:14:13,969\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:05:16,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5812,9 +7073,9 @@ "output_type": "stream", "text": [ "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8535\n", - "Function value obtained: -127.1430\n", - "Current minimum: -127.1430\n", + "Time taken: 10.0825\n", + "Function value obtained: -31.1810\n", + "Current minimum: -31.9079\n", "Iteration No: 57 started. Searching for the next optimal point.\n" ] }, @@ -5822,7 +7083,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:14:23,819\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:05:26,986\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5830,9 +7091,9 @@ "output_type": "stream", "text": [ "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7854\n", - "Function value obtained: -123.4513\n", - "Current minimum: -127.1430\n", + "Time taken: 10.0164\n", + "Function value obtained: -1.1996\n", + "Current minimum: -31.9079\n", "Iteration No: 58 started. Searching for the next optimal point.\n" ] }, @@ -5840,7 +7101,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:14:33,625\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:05:37,005\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5848,9 +7109,9 @@ "output_type": "stream", "text": [ "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9281\n", - "Function value obtained: -126.7540\n", - "Current minimum: -127.1430\n", + "Time taken: 10.4896\n", + "Function value obtained: -6.1262\n", + "Current minimum: -31.9079\n", "Iteration No: 59 started. Searching for the next optimal point.\n" ] }, @@ -5858,7 +7119,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:14:43,629\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:05:47,481\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5866,9 +7127,9 @@ "output_type": "stream", "text": [ "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0651\n", - "Function value obtained: -124.7018\n", - "Current minimum: -127.1430\n", + "Time taken: 10.2772\n", + "Function value obtained: -1.1863\n", + "Current minimum: -31.9079\n", "Iteration No: 60 started. Searching for the next optimal point.\n" ] }, @@ -5876,7 +7137,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:14:52,612\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:05:57,863\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5884,9 +7145,9 @@ "output_type": "stream", "text": [ "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1865\n", - "Function value obtained: -128.2840\n", - "Current minimum: -128.2840\n", + "Time taken: 10.3443\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.9079\n", "Iteration No: 61 started. Searching for the next optimal point.\n" ] }, @@ -5894,7 +7155,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:15:02,851\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:06:08,137\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5902,9 +7163,9 @@ "output_type": "stream", "text": [ "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6958\n", - "Function value obtained: -125.8897\n", - "Current minimum: -128.2840\n", + "Time taken: 10.3022\n", + "Function value obtained: -31.7855\n", + "Current minimum: -31.9079\n", "Iteration No: 62 started. Searching for the next optimal point.\n" ] }, @@ -5912,7 +7173,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:15:12,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:06:18,448\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5920,9 +7181,9 @@ "output_type": "stream", "text": [ "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5091\n", - "Function value obtained: -93.7244\n", - "Current minimum: -128.2840\n", + "Time taken: 10.4315\n", + "Function value obtained: -30.2362\n", + "Current minimum: -31.9079\n", "Iteration No: 63 started. Searching for the next optimal point.\n" ] }, @@ -5930,7 +7191,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:15:22,020\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:06:28,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5938,9 +7199,9 @@ "output_type": "stream", "text": [ "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8084\n", - "Function value obtained: -88.5590\n", - "Current minimum: -128.2840\n", + "Time taken: 10.1617\n", + "Function value obtained: -30.2748\n", + "Current minimum: -31.9079\n", "Iteration No: 64 started. Searching for the next optimal point.\n" ] }, @@ -5948,7 +7209,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:15:31,853\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:06:39,049\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5956,9 +7217,9 @@ "output_type": "stream", "text": [ "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4474\n", - "Function value obtained: -0.0000\n", - "Current minimum: -128.2840\n", + "Time taken: 10.0964\n", + "Function value obtained: -30.9953\n", + "Current minimum: -31.9079\n", "Iteration No: 65 started. Searching for the next optimal point.\n" ] }, @@ -5966,7 +7227,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:15:41,409\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:06:49,138\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5974,9 +7235,9 @@ "output_type": "stream", "text": [ "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9009\n", - "Function value obtained: -96.3448\n", - "Current minimum: -128.2840\n", + "Time taken: 10.2431\n", + "Function value obtained: -29.0489\n", + "Current minimum: -31.9079\n", "Iteration No: 66 started. Searching for the next optimal point.\n" ] }, @@ -5984,7 +7245,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:15:51,245\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:06:59,386\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -5992,9 +7253,9 @@ "output_type": "stream", "text": [ "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9191\n", - "Function value obtained: -86.2623\n", - "Current minimum: -128.2840\n", + "Time taken: 10.1596\n", + "Function value obtained: -1.0807\n", + "Current minimum: -31.9079\n", "Iteration No: 67 started. Searching for the next optimal point.\n" ] }, @@ -6002,7 +7263,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:16:01,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:07:09,575\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6010,9 +7271,9 @@ "output_type": "stream", "text": [ "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9864\n", + "Time taken: 10.2613\n", "Function value obtained: -0.0000\n", - "Current minimum: -128.2840\n", + "Current minimum: -31.9079\n", "Iteration No: 68 started. Searching for the next optimal point.\n" ] }, @@ -6020,7 +7281,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:16:11,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:07:19,842\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6028,9 +7289,9 @@ "output_type": "stream", "text": [ "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6534\n", - "Function value obtained: -127.8728\n", - "Current minimum: -128.2840\n", + "Time taken: 10.4371\n", + "Function value obtained: -30.3426\n", + "Current minimum: -31.9079\n", "Iteration No: 69 started. Searching for the next optimal point.\n" ] }, @@ -6038,7 +7299,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:16:20,796\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:07:30,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6046,9 +7307,9 @@ "output_type": "stream", "text": [ "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9080\n", - "Function value obtained: -112.3430\n", - "Current minimum: -128.2840\n", + "Time taken: 10.2413\n", + "Function value obtained: -31.8127\n", + "Current minimum: -31.9079\n", "Iteration No: 70 started. Searching for the next optimal point.\n" ] }, @@ -6056,7 +7317,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:16:30,716\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:07:40,563\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6064,9 +7325,9 @@ "output_type": "stream", "text": [ "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6776\n", - "Function value obtained: -129.4016\n", - "Current minimum: -129.4016\n", + "Time taken: 10.2939\n", + "Function value obtained: -32.8555\n", + "Current minimum: -32.8555\n", "Iteration No: 71 started. Searching for the next optimal point.\n" ] }, @@ -6074,7 +7335,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:16:40,395\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:07:50,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6082,9 +7343,9 @@ "output_type": "stream", "text": [ "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9430\n", - "Function value obtained: -0.0000\n", - "Current minimum: -129.4016\n", + "Time taken: 10.0908\n", + "Function value obtained: -32.3108\n", + "Current minimum: -32.8555\n", "Iteration No: 72 started. Searching for the next optimal point.\n" ] }, @@ -6092,7 +7353,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:16:50,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:08:00,916\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6100,9 +7361,9 @@ "output_type": "stream", "text": [ "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1001\n", - "Function value obtained: -126.7829\n", - "Current minimum: -129.4016\n", + "Time taken: 10.5437\n", + "Function value obtained: -31.5213\n", + "Current minimum: -32.8555\n", "Iteration No: 73 started. Searching for the next optimal point.\n" ] }, @@ -6110,7 +7371,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:17:00,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:08:11,481\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6118,9 +7379,9 @@ "output_type": "stream", "text": [ "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0197\n", - "Function value obtained: -132.4043\n", - "Current minimum: -132.4043\n", + "Time taken: 10.3399\n", + "Function value obtained: -30.4829\n", + "Current minimum: -32.8555\n", "Iteration No: 74 started. Searching for the next optimal point.\n" ] }, @@ -6128,7 +7389,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:17:10,468\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:08:22,487\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6136,9 +7397,9 @@ "output_type": "stream", "text": [ "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6961\n", - "Function value obtained: -130.9898\n", - "Current minimum: -132.4043\n", + "Time taken: 11.1122\n", + "Function value obtained: -30.9168\n", + "Current minimum: -32.8555\n", "Iteration No: 75 started. Searching for the next optimal point.\n" ] }, @@ -6146,7 +7407,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:17:20,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:08:32,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6154,9 +7415,9 @@ "output_type": "stream", "text": [ "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6961\n", - "Function value obtained: -106.3181\n", - "Current minimum: -132.4043\n", + "Time taken: 10.4317\n", + "Function value obtained: -31.6978\n", + "Current minimum: -32.8555\n", "Iteration No: 76 started. Searching for the next optimal point.\n" ] }, @@ -6164,7 +7425,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:17:29,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:08:43,380\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6172,9 +7433,9 @@ "output_type": "stream", "text": [ "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1588\n", - "Function value obtained: -99.9605\n", - "Current minimum: -132.4043\n", + "Time taken: 10.3351\n", + "Function value obtained: -31.9563\n", + "Current minimum: -32.8555\n", "Iteration No: 77 started. Searching for the next optimal point.\n" ] }, @@ -6182,7 +7443,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:17:40,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:08:53,744\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6190,9 +7451,9 @@ "output_type": "stream", "text": [ "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1432\n", - "Function value obtained: -97.3045\n", - "Current minimum: -132.4043\n", + "Time taken: 10.3068\n", + "Function value obtained: -32.4057\n", + "Current minimum: -32.8555\n", "Iteration No: 78 started. Searching for the next optimal point.\n" ] }, @@ -6200,7 +7461,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:17:50,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:09:04,028\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6208,9 +7469,9 @@ "output_type": "stream", "text": [ "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0644\n", - "Function value obtained: -2.0225\n", - "Current minimum: -132.4043\n", + "Time taken: 10.4173\n", + "Function value obtained: -31.7042\n", + "Current minimum: -32.8555\n", "Iteration No: 79 started. Searching for the next optimal point.\n" ] }, @@ -6218,7 +7479,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:18:00,284\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:09:14,828\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6226,9 +7487,9 @@ "output_type": "stream", "text": [ "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0968\n", - "Function value obtained: -128.2107\n", - "Current minimum: -132.4043\n", + "Time taken: 10.8446\n", + "Function value obtained: -31.1569\n", + "Current minimum: -32.8555\n", "Iteration No: 80 started. Searching for the next optimal point.\n" ] }, @@ -6236,7 +7497,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:18:10,413\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:09:25,307\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6244,9 +7505,9 @@ "output_type": "stream", "text": [ "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1542\n", - "Function value obtained: -129.6949\n", - "Current minimum: -132.4043\n", + "Time taken: 10.4382\n", + "Function value obtained: -30.5244\n", + "Current minimum: -32.8555\n", "Iteration No: 81 started. Searching for the next optimal point.\n" ] }, @@ -6254,7 +7515,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:18:20,541\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:09:35,754\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6262,9 +7523,9 @@ "output_type": "stream", "text": [ "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0670\n", - "Function value obtained: -96.3537\n", - "Current minimum: -132.4043\n", + "Time taken: 10.2644\n", + "Function value obtained: -32.0479\n", + "Current minimum: -32.8555\n", "Iteration No: 82 started. Searching for the next optimal point.\n" ] }, @@ -6272,7 +7533,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:18:30,587\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:09:46,050\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6280,9 +7541,9 @@ "output_type": "stream", "text": [ "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9939\n", - "Function value obtained: -6.0704\n", - "Current minimum: -132.4043\n", + "Time taken: 11.0399\n", + "Function value obtained: -32.1043\n", + "Current minimum: -32.8555\n", "Iteration No: 83 started. Searching for the next optimal point.\n" ] }, @@ -6290,7 +7551,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:18:40,622\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:09:57,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6298,9 +7559,9 @@ "output_type": "stream", "text": [ "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8829\n", - "Function value obtained: -0.0000\n", - "Current minimum: -132.4043\n", + "Time taken: 10.5165\n", + "Function value obtained: -30.6095\n", + "Current minimum: -32.8555\n", "Iteration No: 84 started. Searching for the next optimal point.\n" ] }, @@ -6308,7 +7569,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:18:50,512\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:10:07,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6316,9 +7577,9 @@ "output_type": "stream", "text": [ "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3976\n", - "Function value obtained: -115.1299\n", - "Current minimum: -132.4043\n", + "Time taken: 10.3169\n", + "Function value obtained: -31.5152\n", + "Current minimum: -32.8555\n", "Iteration No: 85 started. Searching for the next optimal point.\n" ] }, @@ -6326,7 +7587,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:19:01,896\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:10:17,918\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6334,9 +7595,9 @@ "output_type": "stream", "text": [ "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3103\n", - "Function value obtained: -124.1162\n", - "Current minimum: -132.4043\n", + "Time taken: 11.0497\n", + "Function value obtained: -31.5870\n", + "Current minimum: -32.8555\n", "Iteration No: 86 started. Searching for the next optimal point.\n" ] }, @@ -6344,7 +7605,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:19:12,177\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:10:28,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6352,9 +7613,9 @@ "output_type": "stream", "text": [ "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2746\n", - "Function value obtained: -92.9865\n", - "Current minimum: -132.4043\n", + "Time taken: 10.9724\n", + "Function value obtained: -31.6473\n", + "Current minimum: -32.8555\n", "Iteration No: 87 started. Searching for the next optimal point.\n" ] }, @@ -6362,7 +7623,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:19:22,466\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:10:39,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6370,9 +7631,9 @@ "output_type": "stream", "text": [ "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9574\n", - "Function value obtained: -131.7860\n", - "Current minimum: -132.4043\n", + "Time taken: 10.5459\n", + "Function value obtained: -31.2402\n", + "Current minimum: -32.8555\n", "Iteration No: 88 started. Searching for the next optimal point.\n" ] }, @@ -6380,7 +7641,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:19:32,483\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:10:50,510\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6388,9 +7649,9 @@ "output_type": "stream", "text": [ "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9363\n", - "Function value obtained: -130.3836\n", - "Current minimum: -132.4043\n", + "Time taken: 10.5694\n", + "Function value obtained: -30.2150\n", + "Current minimum: -32.8555\n", "Iteration No: 89 started. Searching for the next optimal point.\n" ] }, @@ -6398,7 +7659,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:19:42,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:11:02,370\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6406,9 +7667,9 @@ "output_type": "stream", "text": [ "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5956\n", - "Function value obtained: -132.4495\n", - "Current minimum: -132.4495\n", + "Time taken: 11.8468\n", + "Function value obtained: -31.7185\n", + "Current minimum: -32.8555\n", "Iteration No: 90 started. Searching for the next optimal point.\n" ] }, @@ -6416,7 +7677,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:19:53,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:11:12,936\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6424,9 +7685,9 @@ "output_type": "stream", "text": [ "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4258\n", - "Function value obtained: -132.7402\n", - "Current minimum: -132.7402\n", + "Time taken: 10.3980\n", + "Function value obtained: -30.8204\n", + "Current minimum: -32.8555\n", "Iteration No: 91 started. Searching for the next optimal point.\n" ] }, @@ -6434,7 +7695,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:20:03,358\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:11:23,367\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6442,9 +7703,9 @@ "output_type": "stream", "text": [ "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0293\n", - "Function value obtained: -107.4279\n", - "Current minimum: -132.7402\n", + "Time taken: 10.9277\n", + "Function value obtained: -30.9855\n", + "Current minimum: -32.8555\n", "Iteration No: 92 started. Searching for the next optimal point.\n" ] }, @@ -6452,7 +7713,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:20:13,458\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:11:34,287\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6460,9 +7721,9 @@ "output_type": "stream", "text": [ "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2054\n", - "Function value obtained: -131.8842\n", - "Current minimum: -132.7402\n", + "Time taken: 11.0378\n", + "Function value obtained: -29.8477\n", + "Current minimum: -32.8555\n", "Iteration No: 93 started. Searching for the next optimal point.\n" ] }, @@ -6470,7 +7731,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:20:23,719\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:11:46,329\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6478,9 +7739,9 @@ "output_type": "stream", "text": [ "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4196\n", - "Function value obtained: -125.2470\n", - "Current minimum: -132.7402\n", + "Time taken: 11.9450\n", + "Function value obtained: -31.7651\n", + "Current minimum: -32.8555\n", "Iteration No: 94 started. Searching for the next optimal point.\n" ] }, @@ -6488,7 +7749,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:20:34,081\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:11:57,273\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6496,9 +7757,9 @@ "output_type": "stream", "text": [ "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3703\n", - "Function value obtained: -128.0604\n", - "Current minimum: -132.7402\n", + "Time taken: 11.4737\n", + "Function value obtained: -31.7404\n", + "Current minimum: -32.8555\n", "Iteration No: 95 started. Searching for the next optimal point.\n" ] }, @@ -6506,7 +7767,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:20:44,500\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:12:08,812\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6514,9 +7775,9 @@ "output_type": "stream", "text": [ "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6884\n", - "Function value obtained: -112.6622\n", - "Current minimum: -132.7402\n", + "Time taken: 11.2712\n", + "Function value obtained: -31.2791\n", + "Current minimum: -32.8555\n", "Iteration No: 96 started. Searching for the next optimal point.\n" ] }, @@ -6524,7 +7785,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:20:55,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:12:20,044\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6532,9 +7793,9 @@ "output_type": "stream", "text": [ "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3170\n", - "Function value obtained: -115.6452\n", - "Current minimum: -132.7402\n", + "Time taken: 10.8059\n", + "Function value obtained: -30.9690\n", + "Current minimum: -32.8555\n", "Iteration No: 97 started. Searching for the next optimal point.\n" ] }, @@ -6542,7 +7803,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:21:05,539\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:12:30,848\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6550,9 +7811,9 @@ "output_type": "stream", "text": [ "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7750\n", - "Function value obtained: -10.3103\n", - "Current minimum: -132.7402\n", + "Time taken: 10.6705\n", + "Function value obtained: -31.7814\n", + "Current minimum: -32.8555\n", "Iteration No: 98 started. Searching for the next optimal point.\n" ] }, @@ -6560,7 +7821,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:21:16,247\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:12:41,544\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6568,9 +7829,9 @@ "output_type": "stream", "text": [ "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2461\n", - "Function value obtained: -114.9304\n", - "Current minimum: -132.7402\n", + "Time taken: 10.7419\n", + "Function value obtained: -31.3608\n", + "Current minimum: -32.8555\n", "Iteration No: 99 started. Searching for the next optimal point.\n" ] }, @@ -6578,7 +7839,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:21:26,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:12:52,875\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6586,9 +7847,9 @@ "output_type": "stream", "text": [ "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1882\n", - "Function value obtained: -111.3750\n", - "Current minimum: -132.7402\n", + "Time taken: 12.2464\n", + "Function value obtained: -32.3479\n", + "Current minimum: -32.8555\n", "Iteration No: 100 started. Searching for the next optimal point.\n" ] }, @@ -6596,7 +7857,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-06 21:21:36,735\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-14 22:13:04,520\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -6604,27 +7865,28 @@ "output_type": "stream", "text": [ "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7355\n", - "Function value obtained: -124.6877\n", - "Current minimum: -132.7402\n", - "CPU times: user 26min 12s, sys: 22min 45s, total: 48min 58s\n", - "Wall time: 16min 10s\n" + "Time taken: 11.2425\n", + "Function value obtained: -30.9741\n", + "Current minimum: -32.8555\n", + "CPU times: user 25min 7s, sys: 23min 52s, total: 48min 59s\n", + "Wall time: 17min 3s\n" ] }, { "data": { "text/plain": [ - "(-132.7401767704845, [0.9991043655916663, 0.0, 0.3647240347805972])" + "(-32.855509214315326,\n", + " [-0.3794368872527265, 0.7853961999069485, 0.0664998393458039])" ] }, - "execution_count": 17, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", - "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 100, verbose=True, n_jobs=-1)\n", + "cr_gp = gp_minimize(cr_obj, cr_space, n_calls = 100, verbose=True)\n", "cr_gp.fun, cr_gp.x" ] }, @@ -6635,8 +7897,7 @@ "metadata": { "collapsed": true, "jupyter": { - "outputs_hidden": true, - "source_hidden": true + "outputs_hidden": true }, "scrolled": true }, @@ -7209,7 +8470,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 11, "id": "1abcccf2-89f9-497d-ac43-1af009a637ef", "metadata": {}, "outputs": [ @@ -7219,15 +8480,15 @@ "" ] }, - "execution_count": 33, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -7235,7 +8496,7 @@ } ], "source": [ - "plot_objective(msy_gp)" + "plot_objective(cr_gp)" ] }, { @@ -7248,7 +8509,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "id": "6a61d3fa-97a9-4274-945c-be2742d1e956", "metadata": {}, "outputs": [], @@ -7269,7 +8530,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 20, "id": "b86effb9-d8ad-4b50-8174-ea76dcd60c32", "metadata": { "scrolled": true @@ -7282,43 +8543,45 @@ "cr_gp_args['x2'] = (10 ** cr_gp_preargs['log_radius']) * np.cos(cr_gp_preargs['theta'])\n", "cr_gp_args['y2'] = cr_gp_preargs['y2']\n", "\n", - "cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", - "cr_gbrt_args = {}\n", - "cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", - "cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", - "cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", + "# cr_gbrt_preargs = {'log_radius': cr_gbrt.x[0], 'theta': cr_gbrt.x[1], 'y2': cr_gbrt.x[2]}\n", + "# cr_gbrt_args = {}\n", + "# cr_gbrt_args['x1'] = (10 ** cr_gbrt_preargs['log_radius']) * np.sin(cr_gbrt_preargs['theta'])\n", + "# cr_gbrt_args['x2'] = (10 ** cr_gbrt_preargs['log_radius']) * np.cos(cr_gbrt_preargs['theta'])\n", + "# cr_gbrt_args['y2'] = cr_gbrt_preargs['y2']\n", "\n", - "# msy_gp_args = {'mortality': msy_gp.x[0]}\n", + "msy_gp_args = {'mortality': msy_gp.x[0]}\n", "# msy_gbrt_args = {'mortality': msy_gbrt.x[0]}\n", "\n", "esc_gp_args = {'escapement': 10 ** esc_gp.x[0]}\n", "# esc_gbrt_args = {'escapement': 10 ** esc_gbrt.x[0]}\n", "\n", - "# msy_gbrt_args = {'mortality': 0.05365088255575121}\n", - "# esc_gbrt_args = {'escapement': 0.010338225232077163}\n", - "# cr_gbrt_args = {\n", - "# 'x1': 0.009159055923137423,\n", - "# 'x2': 0.015139834077385755,\n", - "# 'y2': 0.29119675741251316,\n", + "# cr_preargs = {'log_radius': 0.9991043655916663, 'theta': 0.0, 'y2': 0.3647240347805972}\n", + "# cr_args = {\n", + "# 'x1': (10 ** cr_preargs['log_radius']) * np.sin(cr_preargs['theta']),\n", + "# 'x2': (10 ** cr_preargs['log_radius']) * np.cos(cr_preargs['theta']),\n", + "# 'y2': cr_preargs['y2'],\n", "# }\n", "\n", + "# esc_args = {'escapement': 10 ** (-0.01050109469304239)}\n", + "# msy_args = {'mortality': 0.027374341105189527}\n", + "\n", "#\n", "\n", "env = AsmEnv(config=CONFIG)\n", "\n", - "cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", + "# cr_gbrt_df = get_policy_df(CautionaryRule(env, **cr_gbrt_args))\n", "cr_gp_df = get_policy_df(CautionaryRule(env, **cr_gp_args))\n", "\n", "# esc_gbrt_df = get_policy_df(ConstEsc(env, **esc_gbrt_args))\n", "esc_gp_df = get_policy_df(ConstEsc(env, **esc_gp_args))\n", "\n", "# msy_gbrt_df = get_policy_df(Msy(env, **msy_gbrt_args))\n", - "# msy_gp_df = get_policy_df(Msy(env, **msy_gp_args))" + "msy_gp_df = get_policy_df(Msy(env, **msy_gp_args))" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 22, "id": "88d5b45d-eeed-4321-9e9d-1a58ba63e84c", "metadata": {}, "outputs": [ @@ -7326,16 +8589,27 @@ "data": { "text/plain": [ "(,\n", - " )" + " ,\n", + " )" ] }, - "execution_count": 30, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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", 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", + "image/png": 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", "text/plain": [ "
" ] @@ -7356,11 +8630,11 @@ ], "source": [ "(\n", - " cr_gp_df[cr_gp_df.biomass <= 15].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", - " esc_gp_df[esc_gp_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", + " cr_gp_df[cr_gp_df.biomass <= 10].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GP policy'),\n", + " esc_gp_df[esc_gp_df.biomass <= 10].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GP policy'),\n", " # cr_gbrt_df[cr_gbrt_df.biomass <= 15].plot(x='biomass', y='fishing_mortality', title='Cautionary Rule GBRT policy'),\n", " # esc_gbrt_df[esc_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='Const. Escapement GBRT policy'),\n", - " # msy_gbrt_df[msy_gbrt_df.biomass <= 7].plot(x='biomass', y='fishing_mortality', title='MSY GP policy'),\n", + " msy_gp_df[msy_gp_df.biomass <= 10].plot(x='biomass', y='fishing_mortality', title='MSY GP policy'),\n", ") " ] }, @@ -7382,33 +8656,19 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 23, "id": "dabc6e34-7a25-4b2d-b8b1-294b59f60ca0", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "594baeecd7734c54a95536b73e98c531", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "msy_gp.pkl: 0%| | 0.00/147M [00:00 4\u001b[0m policy\u001b[38;5;241m=\u001b[39mMsy(env\u001b[38;5;241m=\u001b[39mpol_env, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[43mmsy_gbrt_args\u001b[49m), \n\u001b[1;32m 5\u001b[0m env_cls\u001b[38;5;241m=\u001b[39mAsmEnv, config\u001b[38;5;241m=\u001b[39mPPO_CONFIG, \n\u001b[1;32m 6\u001b[0m n_batches\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, batch_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m200\u001b[39m,\n\u001b[1;32m 7\u001b[0m )\n\u001b[1;32m 9\u001b[0m esc_rews \u001b[38;5;241m=\u001b[39m eval_pol(\n\u001b[1;32m 10\u001b[0m policy\u001b[38;5;241m=\u001b[39mConstEsc(env\u001b[38;5;241m=\u001b[39mpol_env, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mesc_gbrt_args), \n\u001b[1;32m 11\u001b[0m env_cls\u001b[38;5;241m=\u001b[39mAsmEnv, config\u001b[38;5;241m=\u001b[39mPPO_CONFIG, \n\u001b[1;32m 12\u001b[0m n_batches\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, batch_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m200\u001b[39m,\n\u001b[1;32m 13\u001b[0m )\n\u001b[1;32m 15\u001b[0m cr_rews \u001b[38;5;241m=\u001b[39m eval_pol(\n\u001b[1;32m 16\u001b[0m policy\u001b[38;5;241m=\u001b[39mCautionaryRule(env\u001b[38;5;241m=\u001b[39mpol_env, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mcr_gbrt_args), \n\u001b[1;32m 17\u001b[0m env_cls\u001b[38;5;241m=\u001b[39mAsmEnv, config\u001b[38;5;241m=\u001b[39mPPO_CONFIG, \n\u001b[1;32m 18\u001b[0m n_batches\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, batch_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m200\u001b[39m,\n\u001b[1;32m 19\u001b[0m )\n", - "\u001b[0;31mNameError\u001b[0m: name 'msy_gbrt_args' is not defined" + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-07 20:36:25,106\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-07 20:36:32,062\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-07 20:36:38,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], @@ -7803,19 +9050,19 @@ "pol_env = AsmEnv(config=CONFIG)\n", "\n", "msy_rews = eval_pol(\n", - " policy=Msy(env=pol_env, **msy_gbrt_args), \n", + " policy=Msy(env=pol_env, **msy_args), \n", " env_cls=AsmEnv, config=PPO_CONFIG, \n", " n_batches=1, batch_size=200,\n", ")\n", "\n", "esc_rews = eval_pol(\n", - " policy=ConstEsc(env=pol_env, **esc_gbrt_args), \n", + " policy=ConstEsc(env=pol_env, **esc_args), \n", " env_cls=AsmEnv, config=PPO_CONFIG, \n", " n_batches=1, batch_size=200,\n", ")\n", "\n", "cr_rews = eval_pol(\n", - " policy=CautionaryRule(env=pol_env, **cr_gbrt_args), \n", + " policy=CautionaryRule(env=pol_env, **cr_args), \n", " env_cls=AsmEnv, config=PPO_CONFIG, \n", " n_batches=1, batch_size=200,\n", ")" @@ -7823,43 +9070,37 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "id": "da2bf763-6df6-410f-84de-00e6d0d8d26a", "metadata": {}, "outputs": [], "source": [ "from stable_baselines3 import PPO\n", + "from rl4fisheries import AsmCRLike\n", "\n", - "PPO_CONFIG = { \n", + "PPO_CONFIG = {\n", " \"observation_fn_id\": 'observe_2o',\n", " \"n_observs\": 2,\n", + " \"upow\": 0.6,\n", + " \"use_custom_harv_vul\": True,\n", + " \"use_custom_surv_vul\": True,\n", "}\n", "\n", - "ppo = PPO.load(\"../saved_agents/PPO-AsmEnv-2o.zip\", env=AsmEnv(config=PPO_CONFIG), device='cpu')" + "ppo = PPO.load(\n", + " \"../saved_agents/PPO-AsmCRLike-2o-lgBatch-slow-deep-upow0.6-flatHarvSurv\", \n", + " env=AsmCRLike(config=PPO_CONFIG), \n", + " device='cpu',\n", + ")" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "id": "44089c81-f0f2-482c-835f-09187ab5f7cc", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-04-19 20:02:53,005\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:03:07,046\tINFO worker.py:1752 -- Started a local Ray instance.\n", - "2024-04-19 20:03:21,700\tINFO worker.py:1752 -- Started a local Ray instance.\n" - ] - } - ], + "outputs": [], "source": [ "# ppo_rews = evaluate_policy(\n", "# ppo, env=Monitor(AsmEnv(\n", @@ -7871,8 +9112,8 @@ "\n", "ppo_rews = eval_pol(\n", " policy=ppo, \n", - " env_cls=AsmEnv, config=PPO_CONFIG, \n", - " n_batches=3, batch_size=120\n", + " env_cls=AsmCRLike, config=PPO_CONFIG, \n", + " n_batches=1, batch_size=200\n", ")" ] }, @@ -7922,7 +9163,7 @@ "outputs": [ { "data": { - "image/png": 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" }, "metadata": { "image/png": { @@ -7948,10 +9189,22 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 1, "id": "c4885e9a-dde0-4c78-a12f-a6e018500e02", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'AsmEnv' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mitertools\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m env \u001b[38;5;241m=\u001b[39m \u001b[43mAsmEnv\u001b[49m()\n\u001b[1;32m 3\u001b[0m BOUND \u001b[38;5;241m=\u001b[39m env\u001b[38;5;241m.\u001b[39mbound\n\u001b[1;32m 4\u001b[0m MAXWT \u001b[38;5;241m=\u001b[39m env\u001b[38;5;241m.\u001b[39mparameters[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmax_wt\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n", + "\u001b[0;31mNameError\u001b[0m: name 'AsmEnv' is not defined" + ] + } + ], "source": [ "import itertools\n", "env = AsmEnv()\n", @@ -7959,6 +9212,33 @@ "MAXWT = env.parameters[\"max_wt\"]\n", "MINWT = env.parameters[\"min_wt\"]\n", "\n", + "def harv_per_biomass(policy_obj, biomass_obs_list, column_name='fishing_mortality'):\n", + " return [\n", + " (1 + policy_obj.predict(np.float32([obs]))[0][0]) / 2 \n", + " for obs in biomass_obs_list\n", + " ]\n", + "\n", + "\n", + "def policy_crlike(policy_obj, minx=-1, maxx=1, nx=5):\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " policy_dict = {}\n", + " for obs in obs_list:\n", + " x1_act, x2_act, y2_act = policy_obj.predict(np.array([obs]))[0]\n", + " x1 = 10 * (x1_act + 1) / 2\n", + " x2 = 10 * (x2_act + 1) / 2\n", + " y2 = (y2 + 1) / 2 \n", + "\n", + " harvests_at_mwt = harv_per_biomass(\n", + " CautionaryRule(AsmEnv(config=CONFIG), x1=x1, x2=x2, y2=y2),\n", + " np.linspace(-1, 1, 200),\n", + " )\n", + "\n", + " mwt = MINWT + (MAXWT - MINWT) * (obs+1)/2\n", + "\n", + " policy_dict[f\"mwt_{mwt}\"] = harvests_at_mwt\n", + " \n", + " return policy_dict\n", + "\n", "def policy_1obs(policy_obj, minx=-1, maxx=1, nx=200):\n", " obs_list = np.linspace(minx, maxx, nx)\n", " return {\n", From 29ef7a887a66c610105f6a6f4054bae68be61fc4 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 05:18:09 +0000 Subject: [PATCH 40/64] plot reproduction notebook --- notebooks/result_plots.ipynb | 595 +++++++++++++++++++++++++++++++++++ 1 file changed, 595 insertions(+) create mode 100644 notebooks/result_plots.ipynb diff --git a/notebooks/result_plots.ipynb b/notebooks/result_plots.ipynb new file mode 100644 index 0000000..3f706bd --- /dev/null +++ b/notebooks/result_plots.ipynb @@ -0,0 +1,595 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "01518a86-e3ec-480c-b118-7fd7361870f2", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import ray\n", + "\n", + "from plotnine import ggplot, aes, geom_density, geom_line, geom_point\n", + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.envs.asm_fns import get_r_devs, observe_total" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "2119a088-27b1-490f-9114-23c4e3f69ca6", + "metadata": {}, + "outputs": [], + "source": [ + "def nat_units(obs, env):\n", + " biomass = env.bound * (obs[0] + 1) / 2\n", + " mwt = MINWT + (MAXWT - MINWT) * (obs[1]+1)/2\n", + " return biomass, mwt\n", + "\n", + "#\n", + "\n", + "def full_ep(policy, env):\n", + " episode = {\n", + " 't': [],\n", + " 'biomass': [],\n", + " 'mwt': [],\n", + " 'rew': [],\n", + " }\n", + " \n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " action = policy.predict(obs)[0]\n", + " new_obs, rew, term, trunc, info = env.step(action)\n", + " #\n", + " biomass, mwt = nat_units(obs, env)\n", + " episode['t'].append(t)\n", + " episode['biomass'].append(biomass)\n", + " episode['mwt'].append(mwt)\n", + " episode['rew'].append(rew)\n", + " #\n", + " obs=new_obs\n", + "\n", + " return episode\n", + "\n", + "\n", + "#\n", + "\n", + "@ray.remote\n", + "def generate_rew(policy, env_cls, config):\n", + " ep_rew = 0\n", + " env = env_cls(config=config)\n", + " obs, info = env.reset()\n", + " for t in range(env.Tmax):\n", + " act, info = policy.predict(obs)\n", + " obs, rew, term, trunc, info = env.step(act)\n", + " ep_rew += rew\n", + " return ep_rew\n", + "\n", + "\n", + "def rew_batch(policy, env_cls, config, batch_size):\n", + " tmax = env_cls().Tmax\n", + " parallel = [generate_rew.remote(policy, env_cls, config) for _ in range(batch_size)]\n", + " rews = ray.get(parallel)\n", + " if ray.is_initialized():\n", + " ray.shutdown()\n", + " return rews\n", + "\n", + "def eval_pol(policy, env_cls, config, n_batches=1, batch_size=200, pb=False):\n", + " batch_iter = range(n_batches)\n", + " if pb:\n", + " from tqdm import tqdm\n", + " batch_iter = tqdm(batch_iter)\n", + " #\n", + " rews = []\n", + " for i in batch_iter:\n", + " rews.append(\n", + " rew_batch(policy=policy, env_cls=env_cls, config=config, batch_size=batch_size)\n", + " )\n", + " return np.array(rews).flatten()" + ] + }, + { + "cell_type": "markdown", + "id": "7711b648-df4f-4395-8308-808c29b05f64", + "metadata": {}, + "source": [ + "# Reproduction of figures\n", + "---\n", + "\n", + "Here we will reproduce the figures from the paper.\n", + "\n", + "## Case 3: trophy fishing (RL advantage)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "9fc5702e-71b1-4af9-abd3-20e0ed6d0915", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Check: False\n" + ] + } + ], + "source": [ + "CONFIG3 = {\n", + " \"upow\": 1,\n", + " \"harvest_fn_name\": \"trophy\"\n", + "}\n", + "eval_env3 = AsmEnv(config=CONFIG3)\n", + "\n", + "MAXWT = eval_env3.parameters[\"max_wt\"]\n", + "MINWT = eval_env3.parameters[\"min_wt\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "81938413-d860-4195-b5dc-12bc110e39ba", + "metadata": {}, + "outputs": [], + "source": [ + "from stable_baselines3 import PPO\n", + "\n", + "ppoAgent1 = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10.zip', device='cpu')\n", + "ppoAgent2 = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10-run2.zip', device='cpu')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "9142ccb9-82fb-4d68-84fb-2ea76215e200", + "metadata": {}, + "outputs": [], + "source": [ + "import pickle\n", + "# still trying to figure out how to load pickle files\n", + "\n", + "# with open('../saved_agents/results/cr_case_3.pkl', 'rb') as pickle_file:\n", + "# cr_3 = pickle.load(pickle_file)\n", + "\n", + "# cr_3 = pickle.load('../saved_agents/results/cr_case_3.pkl')" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "99ed7e7d-8a48-4a4f-89eb-5e01718a8fec", + "metadata": {}, + "outputs": [], + "source": [ + "def to_cr(log_polar_params):\n", + " theta = log_polar_params[1]\n", + " radius = 10 ** log_polar_params[0]\n", + " x1 = np.sin(theta) * radius\n", + " x2 = np.cos(theta) * radius\n", + " y2 = log_polar_params[2]\n", + " return {'x1': x1, 'x2': x2, 'y2': y2}\n", + "\n", + "def to_esc(log_params):\n", + " return {'escapement': 10 ** log_params[0]}\n", + "\n", + "def to_msy(params):\n", + " return {'msy': params[0]}\n", + "\n", + "cr3 = CautionaryRule(env=eval_env3, **to_cr(\n", + " [-0.383730004464649, 0.7853961999069485, 0.08034226735043051]\n", + "))\n", + "esc3 = ConstEsc(env=eval_env3, **to_esc(\n", + " [0.06615357610240746]\n", + "))\n", + "msy3 = Msy(env=eval_env3, **to_msy(\n", + " [0.045615795667256265]\n", + "))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "52f366c2-1879-4954-9800-ec97f85f364e", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-23 04:33:50,627\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-23 04:33:57,766\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-23 04:34:11,618\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + } + ], + "source": [ + "cr3_rews = eval_pol(\n", + " policy=cr3, env_cls=AsmEnv, config=CONFIG3\n", + ")\n", + "ppoAgent1_rews = eval_pol(\n", + " policy=ppoAgent1, env_cls=AsmEnv, config=CONFIG3\n", + ")\n", + "ppoAgent2_rews = eval_pol(\n", + " policy=ppoAgent2, env_cls=AsmEnv, config=CONFIG3\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "7b5b2627-ca46-419c-86a2-60d8911dee99", + "metadata": {}, + "outputs": [], + "source": [ + "cr_rews_df = pd.DataFrame({\n", + " 'rew': cr3_rews,\n", + " 'agent': 'CR',\n", + "})\n", + "\n", + "ppo1_rews_df = pd.DataFrame({\n", + " 'rew': ppoAgent1_rews,\n", + " 'agent': 'ppo_nr1',\n", + "})\n", + "\n", + "ppo2_rews_df = pd.DataFrame({\n", + " 'rew': ppoAgent2_rews,\n", + " 'agent': 'ppo_nr2',\n", + "})\n", + "\n", + "rews_df_case3 = pd.concat(\n", + " [cr_rews_df, ppo1_rews_df, ppo2_rews_df]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "44484162-7774-425d-9447-82f178faf9b2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(32.22015427213389, 31.13889000095473, 49.50303713191011)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# means\n", + "(\n", + " np.mean(cr_rews_df.rew),\n", + " np.mean(ppo1_rews_df.rew),\n", + " np.mean(ppo2_rews_df.rew),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "495142e1-2607-4168-986e-aee3163f96ad", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "# plot\n", + "(\n", + " ggplot(rews_df_case3, aes(x='rew', fill='agent'))+geom_density(alpha=0.7)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "fee15370-568a-4fdc-8c16-a3db8e33256f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Check: True\n" + ] + } + ], + "source": [ + "reprod_env_3 = AsmEnv(\n", + " config={\n", + " 'reproducibility_mode': True,\n", + " **CONFIG3\n", + " }\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "55d46a8d-1f8f-4f25-b58a-f036c64ce18b", + "metadata": {}, + "outputs": [], + "source": [ + "cr_ep = pd.DataFrame(\n", + " full_ep(policy=cr3, env=reprod_env_3)\n", + ")\n", + "\n", + "ppo1_ep = pd.DataFrame(\n", + " full_ep(policy=ppoAgent1, env=reprod_env_3)\n", + ")\n", + "\n", + "ppo2_ep = pd.DataFrame(\n", + " full_ep(policy=ppoAgent2, env=reprod_env_3)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "6866d87d-6193-45af-bf54-b8ef1e4db651", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "(\n", + " cr_ep.plot(x='t', title=f'CR episode, rew={sum(cr_ep.rew):.2f}'),\n", + " ppo1_ep.plot(x='t', title=f'PPO1 episode, rew={sum(ppo1_ep.rew):.2f}'),\n", + " ppo2_ep.plot(x='t', title=f'PPO2 episode, rew={sum(ppo2_ep.rew):.2f}'),\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "2c18c213-7003-4dfd-a9bb-f706de7ea08c", + "metadata": {}, + "source": [ + "## Policy functions" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "a20d7ed0-8a57-42aa-84f1-ecc148e7988d", + "metadata": {}, + "outputs": [], + "source": [ + "def get_policy_df(policy_obj, mwt, minx=-1, maxx=1, nx=500):\n", + " env=AsmEnv(config=CONFIG3)\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'mwt': [mwt for _ in obs_list],\n", + " 'biomass': env.bound * (obs_list + 1)/2,\n", + " 'fishing_mortality': [\n", + " (1 + policy_obj.predict(np.float32([obs, mwt]))[0][0]) / 2 \n", + " for obs in obs_list\n", + " ]\n", + " }\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "245547ba-b2ba-4e61-8409-4e98c79d47fc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n", + "Check: False\n" + ] + } + ], + "source": [ + "cr_df = get_policy_df(cr3, mwt=0.5, maxx=-1+0.14)\n", + "\n", + "ppo1_df_mwt1 = get_policy_df(ppoAgent1, mwt=0.3, maxx=-1+0.14)\n", + "ppo1_df_mwt2 = get_policy_df(ppoAgent1, mwt=0.4, maxx=-1+0.14)\n", + "ppo1_df_mwt3 = get_policy_df(ppoAgent1, mwt=0.5, maxx=-1+0.14)\n", + "ppo1_df_mwt4 = get_policy_df(ppoAgent1, mwt=0.6, maxx=-1+0.14)\n", + "ppo1_df_mwt5 = get_policy_df(ppoAgent1, mwt=0.8, maxx=-1+0.14)\n", + "\n", + "ppo2_df_mwt1 = get_policy_df(ppoAgent2, mwt=0.3, maxx=-1+0.14)\n", + "ppo2_df_mwt2 = get_policy_df(ppoAgent2, mwt=0.4, maxx=-1+0.14)\n", + "ppo2_df_mwt3 = get_policy_df(ppoAgent2, mwt=0.5, maxx=-1+0.14)\n", + "ppo2_df_mwt4 = get_policy_df(ppoAgent2, mwt=0.6, maxx=-1+0.14)\n", + "ppo2_df_mwt5 = get_policy_df(ppoAgent1, mwt=0.8, maxx=-1+0.14)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "7473b83a-64db-45c2-aec7-c6055d881a7f", + "metadata": {}, + "outputs": [], + "source": [ + "ppo1_df = pd.concat(\n", + " [ppo1_df_mwt1,\n", + " ppo1_df_mwt2,\n", + " ppo1_df_mwt3,\n", + " ppo1_df_mwt4,\n", + " ppo1_df_mwt5,\n", + " ]\n", + ")\n", + "\n", + "ppo2_df = pd.concat(\n", + " [ppo2_df_mwt1,\n", + " ppo2_df_mwt2,\n", + " ppo2_df_mwt3,\n", + " ppo2_df_mwt4,\n", + " ppo2_df_mwt5,\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "339e8de2-9152-4cd5-be35-2234ca5dac5a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "ggplot(\n", + " ppo1_df,\n", + " aes(x='biomass', y='fishing_mortality', color='mwt')\n", + ")+geom_point()" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "a4f825c2-8935-4152-8feb-daee36c7bf3a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "ggplot(\n", + " ppo2_df,\n", + " aes(x='biomass', y='fishing_mortality', color='mwt')\n", + ")+geom_point()" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "e9d562ac-f0d7-4601-9404-bf8d1992ed8f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "ggplot(\n", + " cr_df,\n", + " aes(x='biomass', y='fishing_mortality', color='mwt')\n", + ")+geom_point()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30cd4d6a-4012-48ae-92ba-aaaf683362e9", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 3d3fd3b5b28ed717c8b9760b6d9b5619fa12fb72 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 05:18:31 +0000 Subject: [PATCH 41/64] fixed policy by cases notebook --- notebooks/optimal-fixed-policy-cases-results.ipynb | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/notebooks/optimal-fixed-policy-cases-results.ipynb b/notebooks/optimal-fixed-policy-cases-results.ipynb index 38be570..5bc3fe0 100644 --- a/notebooks/optimal-fixed-policy-cases-results.ipynb +++ b/notebooks/optimal-fixed-policy-cases-results.ipynb @@ -17049,7 +17049,9 @@ "id": "78583c73-cb01-47a9-a338-bb28fb813dc4", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "cr_gp1" + ] }, { "cell_type": "code", From 0bfbd3c15ed4b148c538beacb80d19adfbbea9e7 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 05:20:00 +0000 Subject: [PATCH 42/64] hyperpars --- hyperpars/ppo-asm.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index f997c7d..309f4d9 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -34,6 +34,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "results-trophy-nage-10" +id: "results-trophy-nage-10-run2" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file From f1ef728dc221f69b5a4a53c4d7975f693cac8743 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 05:20:08 +0000 Subject: [PATCH 43/64] notebook --- notebooks/optimal-fixed-policy.ipynb | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/notebooks/optimal-fixed-policy.ipynb b/notebooks/optimal-fixed-policy.ipynb index b633549..df62a44 100644 --- a/notebooks/optimal-fixed-policy.ipynb +++ b/notebooks/optimal-fixed-policy.ipynb @@ -249,6 +249,10 @@ "execution_count": 5, "id": "812edc32-f0f9-4ff4-9792-77acf6962179", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -3642,6 +3646,10 @@ "execution_count": 6, "id": "fafa0c26-8a50-4ed3-b8c7-99984a41c6ea", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ @@ -6061,6 +6069,10 @@ "execution_count": 7, "id": "f3334db1-0dab-47ed-b266-f2c5da4bee13", "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, "scrolled": true }, "outputs": [ From b3bb3bac864c00c9a28263276322cc2a7d77358a Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 21:22:14 +0000 Subject: [PATCH 44/64] added AsmEnvEsc for escapement actions --- src/rl4fisheries/__init__.py | 5 +- src/rl4fisheries/envs/asm_esc.py | 219 ++++--------------------------- 2 files changed, 32 insertions(+), 192 deletions(-) diff --git a/src/rl4fisheries/__init__.py b/src/rl4fisheries/__init__.py index 09287c6..e3472a8 100644 --- a/src/rl4fisheries/__init__.py +++ b/src/rl4fisheries/__init__.py @@ -1,8 +1,9 @@ # Importing from sub-directories here makes these available as 'top-level' imports from rl4fisheries.envs.asm import Asm from rl4fisheries.envs.asm_2o import Asm2o -from rl4fisheries.envs.asm_esc import AsmEsc from rl4fisheries.envs.asm_env import AsmEnv + +from rl4fisheries.envs.asm_esc import AsmEnvEsc from rl4fisheries.envs.asm_cr_like import AsmCRLike from rl4fisheries.agents.cautionary_rule import CautionaryRule @@ -14,7 +15,7 @@ # action is 'harvest' register(id="Asm-v0", entry_point="rl4fisheries.envs.asm:Asm") # action is 'escapement' -register(id="AsmEsc-v0", entry_point="rl4fisheries.envs.asm_esc:AsmEsc") +register(id="AsmEsc-v0", entry_point="rl4fisheries.envs.asm_esc:AsmEnvEsc") # action is harvest, but observes both total count and mean biomass register(id="Asm2o-v0", entry_point="rl4fisheries.envs.asm_2o:Asm2o") # action is harvest, but observes both total count and mean biomass diff --git a/src/rl4fisheries/envs/asm_esc.py b/src/rl4fisheries/envs/asm_esc.py index ca40561..1521a6e 100644 --- a/src/rl4fisheries/envs/asm_esc.py +++ b/src/rl4fisheries/envs/asm_esc.py @@ -1,200 +1,39 @@ -## Identical to asm but with actions defined as escapement rather than as harvest - - -import numpy as np import gymnasium as gym +import numpy as np -# equilibrium dist will in general depend on parameters, need a more robust way -# to reset to random but not unrealistic starting distribution -equib_init = [ - 0.99999999, - 0.86000001, - 0.73960002, - 0.63605603, - 0.54700819, - 0.47042705, - 0.40456727, - 0.34792786, - 0.29921796, - 0.25732745, - 0.22130161, - 0.19031939, - 0.16367468, - 0.14076023, - 0.1210538, - 0.10410627, - 0.08953139, - 0.076997, - 0.06621742, - 0.40676419, -] - - -class AsmEsc(gym.Env): - """an age-structured model following the gym API standard""" +from rl4fisheries import AsmEnv +from rl4fisheries.envs.asm_fns import observe_mwt - def __init__(self, config=None): - config = config or {} - parameters = { - "n_age": 20, # number of age classes - "vbk": np.float32(0.23), # von Bertalanffy kappa - "s": np.float32(0.86), # average survival - "cr": np.float32(6.0), # Goodyear compensation ratio - "rinit": np.float32(0.01), # initial number age-1 recruits - "ro": np.float32(1.0), # average unfished recruitment - "uo": np.float32(0.12), # average historical exploitation rate - "asl": np.float32(0.5), # vul par 1 - "ahv": np.float32(5.0), # vul par 2 - "ahm": np.float32(6.0), # age 50% maturity - "upow": np.float32(1.0), # 1 = max yield objective, < 1 = HARA - "p_big": np.float32(0.05), # probability of big year class - "sdr": np.float32(0.3), # recruit sd given stock-recruit relationship - "rho": np.float32(0.0), # autocorrelation in recruitment sequence - "sdv": np.float32(1e-9), # sd in vulnerable biomass (survey) - "sigma": config.get("sigma", 1.5), - } - # these parameters can be specified in config - self.n_year = config.get("n_year", 1000) - self.Tmax = self.n_year - self.threshold = config.get("threshold", np.float32(1e-4)) - self.training = config.get("training", True) - self.parameters = config.get("parameters", parameters) - self.timestep = 0 - self.bound = 50 # a rescaling parameter - self.esc_bound = 10 - self.parameters["ages"] = range( - 1, self.parameters["n_age"] + 1 - ) # vector of ages for calculations - default_init = self.initialize_population() - self.init_state = config.get("init_state", equib_init) +class AsmEnvEsc(AsmEnv): + """ actions are escapement levels (instead of exploitation rates). """ + def __init__(self, render_mode = 'rgb_array', config={}): + super().__init__(render_mode=render_mode, config=config) - self.reset() - self.action_space = gym.spaces.Box( - np.array([-1], dtype=np.float32), - np.array([1], dtype=np.float32), - dtype=np.float32, - ) - self.observation_space = gym.spaces.Box( - np.array([-1], dtype=np.float32), - np.array([1], dtype=np.float32), - dtype=np.float32, - ) + def reset(self, *, seed=None, options=None): + return super().reset(seed=seed, options=options) def step(self, action): - action = np.clip(action, [-1], [1]) - observation = self.observe() - escapement = (action + 1.0) * self.esc_bound / 2.0 - obs = (observation + 1.0) * self.bound / 2.0 - if obs > 0: - mortality = 1.0 - escapement / obs - mortality = mortality * (mortality > np.array([0.0])) + self.update_vuls() + self.update_ssb() + # + escapement = self.escapement_units(action) + current_pop = self.population_units() + if current_pop <= 0: + mortality = 0 else: - mortality = np.array([0]) - self.state, reward = self.harvest(self.state, mortality) - self.state = self.population_growth(self.state) + mortality = (current_pop - escapement) / current_pop + self.state, reward = self.harvest(mortality) + # + self.update_vuls() + self.update_ssb() + # + self.state = self.population_growth() self.timestep += 1 - terminated = bool(self.timestep > self.n_year) - + terminated = bool(self.timestep >= self.n_year) + # observation = self.observe() - return observation, np.float64(reward), terminated, False, {} - - def initialize_population(self): - p = self.parameters # snag those pars - ninit = np.float32([0] * p["n_age"]) # initial numbers - survey_vul = ninit.copy() # vulnerability - wt = ninit.copy() # weight - mat = ninit.copy() # maturity - Lo = ninit.copy() # survivorship unfished - Lf = ninit.copy() # survivorship fished - mwt = ninit.copy() # mature weight - - # leading array calculations to get vul-at-age, wt-at-age, etc. - for a in range(0, p["n_age"], 1): - survey_vul[a] = 1 / (1 + np.exp(-p["asl"] * (p["ages"][a] - p["ahv"]))) - wt[a] = pow( - (1 - np.exp(-p["vbk"] * p["ages"][a])), 3 - ) # 3 --> isometric growth - mat[a] = 1 / (1 + np.exp(-p["asl"] * (p["ages"][a] - p["ahm"]))) - if a == 0: - Lo[a] = 1 - Lf[a] = 1 - elif a > 0 and a < (p["n_age"] - 1): - Lo[a] = Lo[a - 1] * p["s"] - Lf[a] = Lf[a - 1] * p["s"] * (1 - survey_vul[a - 1] * p["uo"]) - elif a == (p["n_age"] - 1): - Lo[a] = Lo[a - 1] * p["s"] / (1 - p["s"]) - Lf[a] = ( - Lf[a - 1] - * p["s"] - * (1 - survey_vul[a - 1] * p["uo"]) - / (1 - p["s"] * (1 - survey_vul[a - 1] * p["uo"])) - ) - ninit = np.array(p["rinit"]) * Lf - mwt = mat * np.array(wt) - sbro = sum(Lo * mwt) # spawner biomass per recruit in the unfished condition - bha = p["cr"] / sbro # beverton-holt alpha - bhb = (p["cr"] - 1) / (p["ro"] * sbro) # beverton-holt beta - - # put it all in self so we can reference later - self.parameters["Lo"] = Lo - self.parameters["Lf"] = Lf - self.parameters["survey_vul"] = survey_vul - self.parameters["harvest_vul"] = survey_vul - self.parameters["wt"] = wt - self.parameters["mwt"] = mwt - self.parameters["bha"] = bha - self.parameters["bhb"] = bhb - n = np.array(ninit, dtype=np.float32) - self.state = np.clip(n, 0, np.Inf) - return self.state - - def harvest(self, n, mortality): - p = self.parameters - self.vulb = sum(p["harvest_vul"] * n * p["wt"]) - self.vbobs = self.vulb # could multiply this by random deviate - self.ssb = sum(p["mwt"] * n) - if sum(n) > 0: - self.abar = sum(p["harvest_vul"] * np.array(p["ages"]) * n) / sum(n) - self.wbar = sum(p["harvest_vul"] * n * p["wt"]) / sum(n * p["wt"]) - else: - self.abar = 0 - self.wbar = 0 - self.yieldf = mortality[0] * self.vulb # fishery yield - reward = self.yieldf ** p["upow"] # this is utility - n = p["s"] * n * (1 - p["harvest_vul"] * mortality) # eat fish - return n, reward - - def population_growth(self, n): - p = self.parameters - mu = np.log(1) - p["sigma"] ** 2 / 2 - bh_alpha = p["bha"] * np.random.lognormal(mu, p["sigma"]) - - n[p["n_age"] - 1] = ( - n[p["n_age"] - 1] + n[p["n_age"] - 2] - ) # plus group accounting - for a in range(p["n_age"] - 2, 0, -1): - n[a] = n[a - 1] # advance fish one a - n[0] = ( - (bh_alpha) * self.ssb / (1 + p["bhb"] * self.ssb) * 1.0 - ) # NOTE eventually needs to be r_devs[t] - return n - - def observe(self): - self.vulb = sum(self.parameters["survey_vul"] * self.state * self.parameters["wt"]) # update vulnerable biomass - observation = 2 * np.array([self.vulb]) / self.bound - 1 - observation = np.clip(observation, -1.0, 1.0) - return np.float32(observation) - - def population_units(self): - total = np.array([sum(self.state)]) - return total - - def reset(self, *, seed=None, options=None): - self.timestep = 0 - self.state = self.initialize_population() - self.state = self.init_state * np.array( - np.random.uniform(0.1, 1), dtype=np.float32 - ) - obs = self.observe() - return obs, {} + # + return observation, reward, terminated, False, {} + def escapement_units(self, action): + return self.bound * (action + 1) / 2 \ No newline at end of file From 40ff31c3549fd9074cf1b4515e30232a8a676fc9 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 21:22:36 +0000 Subject: [PATCH 45/64] hyperpars --- hyperpars/ppo-asm.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 309f4d9..918b25e 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -20,8 +20,8 @@ algo_config: # env env_id: "AsmEnv" config: - observation_fn_id: 'observe_2o' - n_observs: 2 + observation_fn_id: 'observe_1o' + n_observs: 1 harvest_fn_name: "trophy" n_trophy_ages: 10 # upow: 0.6 @@ -34,6 +34,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "results-trophy-nage-10-run2" +id: "results-trophy-nage-10-1obs" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file From 33b02042768fa2539120520827cdf33badb50be1 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 21:22:41 +0000 Subject: [PATCH 46/64] notebooks --- .../optimal-fixed-policy-cases-results.ipynb | 4 +- notebooks/result_plots.ipynb | 168 ++++++++++++++---- 2 files changed, 133 insertions(+), 39 deletions(-) diff --git a/notebooks/optimal-fixed-policy-cases-results.ipynb b/notebooks/optimal-fixed-policy-cases-results.ipynb index 5bc3fe0..1d1e40f 100644 --- a/notebooks/optimal-fixed-policy-cases-results.ipynb +++ b/notebooks/optimal-fixed-policy-cases-results.ipynb @@ -16730,7 +16730,9 @@ "id": "4df50600-c069-4974-a7fc-6630e13e8057", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "esc3" + ] }, { "cell_type": "markdown", diff --git a/notebooks/result_plots.ipynb b/notebooks/result_plots.ipynb index 3f706bd..792e27f 100644 --- a/notebooks/result_plots.ipynb +++ b/notebooks/result_plots.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 28, "id": "2119a088-27b1-490f-9114-23c4e3f69ca6", "metadata": {}, "outputs": [], @@ -77,7 +77,7 @@ " ray.shutdown()\n", " return rews\n", "\n", - "def eval_pol(policy, env_cls, config, n_batches=1, batch_size=200, pb=False):\n", + "def eval_pol(policy, env_cls, config, n_batches=1, batch_size=300, pb=False):\n", " batch_iter = range(n_batches)\n", " if pb:\n", " from tqdm import tqdm\n", @@ -106,18 +106,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 3, "id": "9fc5702e-71b1-4af9-abd3-20e0ed6d0915", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Check: False\n" - ] - } - ], + "outputs": [], "source": [ "CONFIG3 = {\n", " \"upow\": 1,\n", @@ -126,12 +118,13 @@ "eval_env3 = AsmEnv(config=CONFIG3)\n", "\n", "MAXWT = eval_env3.parameters[\"max_wt\"]\n", - "MINWT = eval_env3.parameters[\"min_wt\"]" + "MINWT = eval_env3.parameters[\"min_wt\"]\n", + "BOUND = eval_env3.bound" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 4, "id": "81938413-d860-4195-b5dc-12bc110e39ba", "metadata": {}, "outputs": [], @@ -160,7 +153,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 21, "id": "99ed7e7d-8a48-4a4f-89eb-5e01718a8fec", "metadata": {}, "outputs": [], @@ -177,7 +170,7 @@ " return {'escapement': 10 ** log_params[0]}\n", "\n", "def to_msy(params):\n", - " return {'msy': params[0]}\n", + " return {'mortality': params[0]}\n", "\n", "cr3 = CautionaryRule(env=eval_env3, **to_cr(\n", " [-0.383730004464649, 0.7853961999069485, 0.08034226735043051]\n", @@ -192,7 +185,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 29, "id": "52f366c2-1879-4954-9800-ec97f85f364e", "metadata": {}, "outputs": [ @@ -200,9 +193,11 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-23 04:33:50,627\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-23 04:33:57,766\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-23 04:34:11,618\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-23 15:59:12,105\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-23 15:59:19,536\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-23 15:59:26,869\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-23 15:59:34,060\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-23 15:59:47,739\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], @@ -210,6 +205,12 @@ "cr3_rews = eval_pol(\n", " policy=cr3, env_cls=AsmEnv, config=CONFIG3\n", ")\n", + "esc3_rews = eval_pol(\n", + " policy=esc3, env_cls=AsmEnv, config=CONFIG3\n", + ")\n", + "msy3_rews = eval_pol(\n", + " policy=msy3, env_cls=AsmEnv, config=CONFIG3\n", + ")\n", "ppoAgent1_rews = eval_pol(\n", " policy=ppoAgent1, env_cls=AsmEnv, config=CONFIG3\n", ")\n", @@ -220,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 30, "id": "7b5b2627-ca46-419c-86a2-60d8911dee99", "metadata": {}, "outputs": [], @@ -230,6 +231,16 @@ " 'agent': 'CR',\n", "})\n", "\n", + "esc_rews_df = pd.DataFrame({\n", + " 'rew': esc3_rews,\n", + " 'agent': 'Esc',\n", + "})\n", + "\n", + "msy_rews_df = pd.DataFrame({\n", + " 'rew': msy3_rews,\n", + " 'agent': 'MSY',\n", + "})\n", + "\n", "ppo1_rews_df = pd.DataFrame({\n", " 'rew': ppoAgent1_rews,\n", " 'agent': 'ppo_nr1',\n", @@ -241,23 +252,27 @@ "})\n", "\n", "rews_df_case3 = pd.concat(\n", - " [cr_rews_df, ppo1_rews_df, ppo2_rews_df]\n", + " [cr_rews_df, esc_rews_df, msy_rews_df, ppo1_rews_df, ppo2_rews_df]\n", ")" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 31, "id": "44484162-7774-425d-9447-82f178faf9b2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(32.22015427213389, 31.13889000095473, 49.50303713191011)" + "(31.619016124666274,\n", + " 13.479394979731,\n", + " 25.510153709904834,\n", + " 32.45709450494806,\n", + " 51.48817420739415)" ] }, - "execution_count": 21, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -266,6 +281,8 @@ "# means\n", "(\n", " np.mean(cr_rews_df.rew),\n", + " np.mean(esc_rews_df.rew),\n", + " np.mean(msy_rews_df.rew),\n", " np.mean(ppo1_rews_df.rew),\n", " np.mean(ppo2_rews_df.rew),\n", ")" @@ -273,13 +290,13 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 32, "id": "495142e1-2607-4168-986e-aee3163f96ad", "metadata": {}, "outputs": [ { "data": { - "image/png": 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" }, "metadata": { "image/png": { @@ -342,13 +359,13 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 51, "id": "6866d87d-6193-45af-bf54-b8ef1e4db651", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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", 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", 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", 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", "text/plain": [ "
" ] @@ -380,9 +397,9 @@ "source": [ "import matplotlib.pyplot as plt\n", "(\n", - " cr_ep.plot(x='t', title=f'CR episode, rew={sum(cr_ep.rew):.2f}'),\n", - " ppo1_ep.plot(x='t', title=f'PPO1 episode, rew={sum(ppo1_ep.rew):.2f}'),\n", - " ppo2_ep.plot(x='t', title=f'PPO2 episode, rew={sum(ppo2_ep.rew):.2f}'),\n", + " cr_ep[cr_ep.t < 400].plot(x='t', title=f'CR episode, rew={sum(cr_ep.rew):.2f}'),\n", + " ppo1_ep[ppo1_ep.t < 400].plot(x='t', title=f'PPO1 episode, rew={sum(ppo1_ep.rew):.2f}'),\n", + " ppo2_ep[ppo2_ep.t < 400].plot(x='t', title=f'PPO2 episode, rew={sum(ppo2_ep.rew):.2f}'),\n", ")\n", "plt.show()" ] @@ -538,13 +555,13 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 52, "id": "e9d562ac-f0d7-4601-9404-bf8d1992ed8f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -558,16 +575,91 @@ "source": [ "ggplot(\n", " cr_df,\n", - " aes(x='biomass', y='fishing_mortality', color='mwt')\n", + " aes(x='biomass', y='fishing_mortality')\n", ")+geom_point()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "30cd4d6a-4012-48ae-92ba-aaaf683362e9", "metadata": {}, "outputs": [], + "source": [ + "def policy_2obs(policy_obj, minx=-1, miny=-1, maxx=1, maxy=1, nx=100, ny=100, obs1_name = 'obs1', obs2_name='obs2'):\n", + " x_obs = np.linspace(minx, maxx, nx)\n", + " y_obs = np.linspace(miny, maxy, ny)\n", + " obs_generator = itertools.product(x_obs, y_obs)\n", + " # obs_list = list(obs_generator)\n", + " out_dict = {obs1_name: [], obs2_name: [], 'pol': []}\n", + " for (obs1, obs2) in obs_generator:\n", + " out_dict[obs1_name].append( BOUND * (obs1+1)/2 )\n", + " out_dict[obs2_name].append( MINWT + (MAXWT - MINWT) * (obs2+1)/2 )\n", + " action = policy_obj.predict(np.float32([obs1, obs2]))[0][0]\n", + " mortality = (action+1)/2\n", + " out_dict['pol'].append(mortality)\n", + " \n", + " return out_dict" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "b6c8e43c-c13e-49cc-b1aa-b2054a84b9dc", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# !pip install seaborn" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "3af7392d-52ba-47c4-9617-9bb09c84385b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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tQ0xMjKZ+VFQU/vWvf6FDhw4IDg7G+vXrMXnyZMTExCApKclVb+TIkVi5cqWrbLfbffLzEBER1QpO6/jOggULcMcdd2Dy5MkAgKVLl2LDhg1YsWIFZs2apak/dOhQVfn+++/Hiy++iC1btqg6J3a7HXFxcbXadiIiswqWpnWCdZYO26WBdrkcJNTTOnYP09XLS4dtivulwpqyTR0sapWXCsvTNFKDLJqlxur2ytM4nNapXX6d1iktLUV+fj4SExNd+ywWCxITE5GXl6d7vhACOTk52LdvHwYPHqw6lpubi5iYGLRv3x533303Tp065fX2ExER+QyndXzj5MmTcDgciI2NVe2PjY3F3r17Kz3vzJkzaNasGUpKSmC1WrF48WJcf/31ruMjR47EX/7yF7Rq1QoHDx7E7NmzMWrUKOTl5cFqtVZ6XSIiIsMyScfCG0w5MBUeHo6dO3fi/PnzyMnJQVpaGlq3bu2a8rnttttcdbt27Ypu3bqhTZs2yM3NxfDhwzXXKykpQUlJiWqfEAKKIudQJCIiotrm185JdHQ0rFYrioqKVPuLiorcxotYLBa0bdsWANCjRw98//33yMzM1MSjXNa6dWtER0fjwIEDFXZOMjMzMXfuXNU+xVIfirWBhz8REZE56MecqMs2KQrAJi0dtuukq9csFZbL8GzpsCYdvSa9vF76evfp6C06S4cVm++/vAoROEnY/BpzEhwcjF69eiEnJ8e1z+l0IicnB/369avydZxOp2bko7wjR47g1KlTaNKkSYXH09PTcebMGdWmWMKr/oMQERHVNsac+E5aWhomTpyI3r17o2/fvli4cCGKi4tdq3dSU1PRrFkzZGZmArg0ytG7d2+0adMGJSUleP/99/Hyyy9jyZIlAIDz589j7ty5uPnmmxEXF4eDBw/iwQcfRNu2bVWrecqz2+2apcac0iEiIvIPv3dOxo4dixMnTmDOnDkoLCxEjx49sHHjRleQbEFBASyWKwM8xcXFuOeee3DkyBGEhoaiQ4cOeOWVVzB27FgAgNVqxbfffosXX3wRp0+fRtOmTTFixAg89thjzHVCRETmFUB5ThQhpIk/AgDYgpv5uwlERLUmtl6kqtwkJEpVjgtSx9zFWUJV5cZQB2U0cqqjBBpKn6MRDvVHTQPpIXb1lDJVOSz4oqpsD1IfD7ary0Eh6uvZ7E63ZYuc58TDGBO5HJn9KWrb7znPe+U6ocPv9Mp1apPfR06IiIioCgJo5MQQz9YhIiIiuowjJ0REAaL8RIS8dDhIJ319kJyuXnfpsFyW0tNLS4dt0lJhOT29vBTY07L8lGG9dPRKsPtpHMXmh+/2Jllp4w3snBAREZkBp3WIiIiILsnKykJ8fDxCQkKQkJCA7du3u62/cOFCtG/fHqGhoWjevDlmzJiBP/74o8r348gJERGRGfhpWic7OxtpaWlYunQpEhISsHDhQiQlJWHfvn2IiYnR1F+9ejVmzZqFFStWoH///vjhhx8wadIkKIqCBQsWVOme7JwQEQUIW7mU9UEWdZSIXYoxsUsD68FS2S7FlGjKTjldvZSeXpHKVmkpsE0ue5a+Xo4xkZcKa5YOexpj4of09f7qnCxYsAB33HGHKznq0qVLsWHDBqxYsQKzZs3S1N+6dSsGDBiAcePGAQDi4+ORkpKCL774osr35LQOERERVai0tBT5+flITEx07bNYLEhMTEReXl6F5/Tv3x/5+fmuqZ8ff/wR77//Pv70pz9V+b4cOSEiIjIDLwXElpSUaJ5HV9FjXADg5MmTcDgcrqztl8XGxmLv3r0VXn/cuHE4efIkBg4cCCEEysrKcNddd2H27NlVbiNHToiIiMzASw/+y8zMREREhGq7/Pw6b8jNzcW8efOwePFi7NixA2+//TY2bNiAxx57rMrX4MgJEVGACLFeiTOR85wEK+7znNg1eU2ksk5eEzvU5WC9vCZyjIkm5kR9PWuwXFa3x+MYk2CLdFyOOTHvd/v09HSkpaWp9lX27Lno6GhYrVYUFRWp9hcVFSEuLq7Ccx5++GFMmDABU6ZMAQB07doVxcXFuPPOO/Gvf/1L9by8ypj3t0tERBRIhNMrm91uR4MGDVRbZZ2T4OBg9OrVCzk5Oa59TqcTOTk56NevX4XnXLhwQdMBsVovdXar+jg/jpwQERGZgZ9W66SlpWHixIno3bs3+vbti4ULF6K4uNi1eic1NRXNmjVzTQ0lJydjwYIF6NmzJxISEnDgwAE8/PDDSE5OdnVS9LBzQkQUIILLLSWWp3Xs8rSOZimxetpDu3RYKkvfkPWWDgcFebZ0WLOUWJrmUfSmcTTTNvJx9YeoYpUmGix+WErspwyxY8eOxYkTJzBnzhwUFhaiR48e2LhxoytItqCgQDVS8tBDD0FRFDz00EM4evQoGjdujOTkZDz++ONVvqciqjrGEmBswc383QQiIq9qFBru+u9mYdGqY82CIlXlOEuoqhwrPT2nsVP9Yd2oTH2vhg51ZyNcUVeoH1SqKoeGXFSV7SHq+kEhUmcmVF22Sr0lSwikcu12TsIXf4Da9vvb87xyndC/VH3VjL9w5ISIiMgM+OA/IiIiMhR2ToiIqK6xl1tKbNekr5fS02vS1evEnMgxJpqlw1JMid7SYQ9jTLTp6fXS0Xs4jaNZSly1wE6qHnZOiIiIzCCAQkTZOSEiIjKDAJrWYRI2IiIiMhSOnBAR1VEWRUoxXy7OxC6lpw+GXK5ZuvpgSDEmUrp6j/OaBLuPMfE4r4kcYxIkxZBIMSWa9PVVTCbmVQE0csLOCRERkRn4KQmbP3Bah4iIiAyFIydERHVUsFW9XFj1VGJFTl+vt5RYfW05XX2w9K0+SJGmeWxSRldpGsdml47LTx2WM8Bqlg7L0zYeTuMEq38fetM4ij+WEnNah4iIiAyFS4mJiIjIUAJo5IQxJ0RERGQoHDkhIqqjQmzqmJPycSZ2KeYk2Nvp6q3u09Vrlw7LMSbq415fKizHmARJH4c2+anF0vmKH77bB9DICTsnREREZsClxMaSlZWF+Ph4hISEICEhAdu3b6+07tChQ6Eoima74YYbfNhiIiIiqi7Dd06ys7ORlpaGjIwM7NixA927d0dSUhJ++eWXCuu//fbbOH78uGvbvXs3rFYrbr31Vh+3nIiIyHuEU3hlMwPDT+ssWLAAd9xxByZPngwAWLp0KTZs2IAVK1Zg1qxZmvpRUVGq8po1axAWFsbOCREFnCCLlMtElb5eJ68J3MecBEsxJ3ZFiimxuk9Hr81roj6uzWOibo8lRIopkcsexpgo0nFNeno55sSibo9PBFDMiaFHTkpLS5Gfn4/ExETXPovFgsTEROTl5VXpGsuXL8dtt92GevXq1VYziYiIyIsMPXJy8uRJOBwOxMbGqvbHxsZi7969uudv374du3fvxvLly2uriURERL4RQAGxhu6c1NTy5cvRtWtX9O3b1229kpISlJSUqPYJIaAofhi2IyIiqohJ4kW8wdCdk+joaFitVhQVFan2FxUVIS4uzu25xcXFWLNmDR599FHd+2RmZmLu3LmqfYqlPhRrA88bTURkECFWOc/JlbiJYKhjKEKkWf5gnWfp2KVv8XJekyDpWTpBQTV7do5uXpOaxpho8pxI15OfrWMxdFSE6Rn6txscHIxevXohJyfHtc/pdCInJwf9+vVze+4bb7yBkpIS/O1vf9O9T3p6Os6cOaPaFEt4jdtPRETkNU6ndzYTMPTICQCkpaVh4sSJ6N27N/r27YuFCxeiuLjYtXonNTUVzZo1Q2Zmpuq85cuXY8yYMWjUqJHuPex2O+x2u2ofp3SIiMhQTNKx8AbDd07Gjh2LEydOYM6cOSgsLESPHj2wceNGV5BsQUEBLNLw2r59+7BlyxZ89NFH/mgyEZFfWKX3wiCLNK1jKZ++XprG0Vk6rJeu3mbRS08vLyV2v3TY59M4QerflSZdvbx0WF5q7At8KrGxTJs2DdOmTavwWG5urmZf+/btIQLofyIREVFdYorOCRERUcDjtA4REREZCpcSExGR2dilpcPyUuIQ5cpbfoi0lNguPEtXH6yolwYHy0uHg9VlTYyJtJRYkdPVa9LTSx9X3o4x0UtfLy8d9kfMSQBh54SIiMgMmCGWiIiIDCWApnUMnYSNiIiIAg9HToiI6gi7TU5Xb5PK5dPXq7+b2nXznMjp6tVlTXp6nTwncl4Ti5zHRCeviRIsl6WPM7t0AzkmRc5jIsWgGDHmRHC1DhERERkKp3WIiIiI/IMjJ0REdUT59PQAYJfS19vLfR/VncZxuk9XH2R1P41js0vH5acOh0jp6UP0pnH0lga7LyvytI3OU4e1x6Xr+SV9Pad1iIiIyEgCaFqHnRMiIiIzCKCAWMacEBERkaFw5IQAQJp99kzgDDQSGZvdql4+W37pMACEqJYS6y0ddp+uPkiKMZHT1Vul9PTy0mElWIo5kZYGy+npdWNI5HT0muPS9Wzu09VrlhpbddLb+wKndYiIiMhQAiggltM6REREZCgcOSEiIjIDTuuQ2enFkChKTaJMJNLcdOC8fIj8yyqlVJfznGjS15fPcyLU7wFSiAiChJzXRMpjYpNjTKR09XZ1WdHEnNQwPb1U1hyXY0bkGBM5RkWT50QnxkTx/cRDIKWv57QOERERGQpHToiIiMyA0zrkb55OuuhN03h1GkcPp3mIfCJInsaRyiHSUmK36eulGYNgyE8hlpYSy08h1lk6rH3qsGdLh/WXCntW1pwvT9vIS4flaR5fvqdeFkCdE07rEBERkaFw5ISIiMgMAijPCTsnREREZhBA0zrsnNQSf8eMKDVKSO8hnVsJETgvKCJfCpbiIuwWdRyFnL5evZRYfS05XX2QFHNik5YSy0uHbVLQijZdvc7SYd309J7FpHgco6KXnl4Tc+KPpcSB817KmBMiIiIyFI6cEBERmUEAjZywc0JERGQGAZQhlp2TSlhquIa9tmNEPL1+TX4ep17MiHxYupXCvCdEtcJulWNMpBgUqOMmgsq9OPXS1Qdb1B+E2rwmUoyJdEElWJHKUhSBXvp5+XhN85joxZjoHZceFaA5Tl7l15iTzz77DMnJyWjatCkURcHatWt1z8nNzcU111wDu92Otm3bYtWqVarjjzzyCBRFUW0dOnSonR+AiIjIV5zCO5sJ+LVzUlxcjO7duyMrK6tK9Q8dOoQbbrgBw4YNw86dOzF9+nRMmTIFH374oape586dcfz4cde2ZcuW2mg+ERGR7wRQ58Sv41KjRo3CqFGjqlx/6dKlaNWqFf7zn/8AADp27IgtW7bg6aefRlJSkquezWZDXFyc19tLREREtc9Uk2Z5eXlITExU7UtKSsL06dNV+/bv34+mTZsiJCQE/fr1Q2ZmJlq0aOHRvSxeXsNe2zEitZnXxKJzaU2IltQxl3925j0h8g45z4mc1yRIeu3ZhVLuv6VrSdlHg+S8JjY5z4n7Z+l4mtdEzluin+dEijGR85JozpcaqPcsHb2yHIPiA4H03mmqPCeFhYWIjY1V7YuNjcXZs2fx+++/AwASEhKwatUqbNy4EUuWLMGhQ4cwaNAgnDt3zh9NJiIi8g5O65hX+Wmibt26ISEhAS1btsTrr7+O22+/vcJzSkpKUFJSotonhPDtk3yJiIgIgMk6J3FxcSgqKlLtKyoqQoMGDRAaGlrhOZGRkWjXrh0OHDhQ6XUzMzMxd+5c1T6bLQLBQZE1bvNlNZ12qenS5ppR31teWixP+8jTPJqfPYCGJolqU7CUrj7ITbp6ALC7W0oszcfK6eptmmkddVnRmdbRXTpsk6dl5OPS+Zr6Hqaj10zzGH9axyyjHt5gqmmdfv36IScnR7Vv06ZN6NevX6XnnD9/HgcPHkSTJk0qrZOeno4zZ86otiBbhNfaTUREVFPCKbyymYFfOyfnz5/Hzp07sXPnTgCXlgrv3LkTBQUFAC51GlJTU13177rrLvz444948MEHsXfvXixevBivv/46ZsyY4aozc+ZMbN68GYcPH8bWrVtx0003wWq1IiUlpdJ22O12NGjQQLVxSoeIiAyFMSe+8dVXX2HYsGGuclpaGgBg4sSJWLVqFY4fP+7qqABAq1atsGHDBsyYMQOLFi3CVVddhRdeeEG1jPjIkSNISUnBqVOn0LhxYwwcOBDbtm1D48aNffeDERERUbUpIpDWJnmgQb3WtXr9mo7MWGpx6TAAON0kmZf/ZOQYFIe0JFGu73Cq02DzD5CoaqxSnEPbiKaqcit7tKrc2lJfVW7hvBKX0fyi+pUX6yxVlRuF/aEqN2j4u6oc2vCiqhwUpX5PskbZVWVLeIiqrISp4wSVelLcYIj6fEhxhYpdOm6TYk7k4zWNMdGJOQkdNgW17cyE4V65TsTLOfqV/MxUAbFERESByizxIt5gqoBYIiIiqvvYOSEiIjIDPwbEZmVlIT4+HiEhIUhISMD27dvd1j99+jSmTp2KJk2awG63o127dnj//ferfD9O61TC6uX09XqMtjrIWi6mRRNjIjVV/k0JKR7GIZ3PdPZE1RNkUb9l2+S8JlLZJr0Wy0dlBEmvuyBFynNiU8eGyXlNdNPVW6V3BjnPiJznRHNcJz29Xrp6T2NI9GJSFPnnk+7nC5pnhfhGdnY20tLSsHTpUiQkJGDhwoVISkrCvn37EBMTo6lfWlqK66+/HjExMXjzzTfRrFkz/PTTT4iMjKzyPdk5ISIiokotWLAAd9xxByZPngzg0kN4N2zYgBUrVmDWrFma+itWrMCvv/6KrVu3Iuj/dxrj4+M9uiendYiIiEzAH0nYSktLkZ+fr3rorsViQWJiIvLy8io8591330W/fv0wdepUxMbGokuXLpg3bx4cDkeF9SvCkZNKyEv2fM3X0zzuplbkkUSLVFWe5lGEeofmZ+EsDlG1aJ5CLE3zBEnfN4MgP5W4/DFpGsfi/inEFqtnTyHWTVevmZbRmXax6UzDyMdrOo0jlTXTOH5JX++dy1T0PDm73Q67vPwawMmTJ+FwOCp86O7evXsrvP6PP/6ITz75BOPHj8f777+PAwcO4J577sHFixeRkZFRpTZy5ISIiCiAZGZmIiIiQrVlZmZ67fpOpxMxMTF4/vnn0atXL4wdOxb/+te/sHTp0ipfgyMnREREJuCtPCfp6emujOyXVTRqAgDR0dGwWq0VPnQ3Li6uwnOaNGmCoKAgWMuNjnXs2BGFhYUoLS1FcHBwheeVx5ETIiIiM3B6Z6voeXKVdU6Cg4PRq1cv1UN3nU4ncnJyKn3o7oABA3DgwAE4nVfmoX744Qc0adKkSh0TgCMnlfL1UmK/k+JCyqevl38TejEoQl4qLM17OzUxKAxCIaqKIIu8dFiKQZFerXY5BqV8zIm8lNiqDla0STEn1mApJYBNii2zWdyW5RgTxSbFnNjkGA/5uLxUWF5aXLOYEt0YE5309b4g/LSUOC0tDRMnTkTv3r3Rt29fLFy4EMXFxa7VO6mpqWjWrJlraujuu+/Gc889h/vvvx/33nsv9u/fj3nz5uG+++6r8j3ZOSEiIqJKjR07FidOnMCcOXNQWFiIHj16YOPGja4g2YKCAljKddaaN2+ODz/8EDNmzEC3bt3QrFkz3H///fjnP/9Z5Xuyc0JERGQGfho5AYBp06Zh2rRpFR7Lzc3V7OvXrx+2bdtW7fuxc0JERGQC/prW8Qd2TiphqWMxJ8LD5CLl40j00tXLrxdFijHR5D2BsVL1E5lFkBT3ECS9T2nK0su+fKoSq5znxOo+r4kil+UYE7109XKMiSbdvPsYFI/zmHg7xkQTcyK1l7yKnRMiIiIz4MgJERERGQmndcjj9PXGf7KutJxXr73lquulq9c8lViaxtF7moI8yWP03ySRvwTJTx2WynK6ek1Zlb5emsaRXuiePoUYmqXEOk8R1ltarPcUYl9P4xghfX0AYeeEiIjIBDhyQkRERIYSSJ0TjksRERGRoXDkpBJy+nrdmBI5JbufOXUiN6xyinnp51M9X0qOMZEu7dC5l0W6l2Kw3xWRWdgs0lJiOT29VLZJL83gcq9zqyLFmMhLiW3y0mG5MdLrWCdmRJuu3rsxJHrp5WscYyLHrCh+WEosAue9k50TIiIiEwikaR12ToiIiExAyEsl6zDGnBAREZGhcOSkEhY50MLHcRJ6MSN6rHAfU6K5n5vcJU75VPlXI6erl39XTFxCVC1yvFawFHOin+dEzVrufSDIop4jsNp00tdLnxaa9PU2Oe+JTp4S+REhenlN5LwiclkvhkQ3/b1OjIl83A+POOG0DhERERmKnOCyLuO0DhERERkKR04qYanhMjFPnwIs8/TuQme8Ty+Oyl2Kes1TiKW68hSY0Fk6LA9VE1HFrNKTb+UUB/JTiOXpXGlmBkFwt5RYXdYuJZZe13pPIfY0XX1Np208XTosP1VYPl/+DNBMQ/n+45PTOkRERGQoXK1jIJ999hmSk5PRtGlTKIqCtWvXVvnc//u//4PNZkOPHj1qrX1ERETkXYbvnBQXF6N79+7Iysry6LzTp08jNTUVw4cPr6WWERER+Y4Q3tnMwPDTOqNGjcKoUaM8Pu+uu+7CuHHjYLVaPRptuUyTvt7jGBLPht+cNf2L0VnWJsewyDEqmqXEovJj3v7rlmNSdB8VQBQggqS4CHnpsBxjollKLL2Uyi8ltlrkpcPqsqJZSizHhEgxKJoYEvlNRTpfL4ZDLsv19WJSPLyfYvEwvb0cs+IDnNbR8eKLL2LDhg2u8oMPPojIyEj0798fP/30k9caV10rV67Ejz/+iIyMDH83hYiIiDxUrc7JvHnzEBoaCgDIy8tDVlYWnnzySURHR2PGjBlebaCn9u/fj1mzZuGVV16BTU66Q0REZFLCqXhlM4NqfXr//PPPaNu2LQBg7dq1uPnmm3HnnXdiwIABGDp0qDfb5xGHw4Fx48Zh7ty5aNeuXZXPKykpQUlJiWqfUzhh8UMGQCIioooE0ox3tTon9evXx6lTp9CiRQt89NFHSEtLAwCEhITg999/92oDPXHu3Dl89dVX+PrrrzFt2jQAgNPphBACNpsNH330Ea677jrNeZmZmZg7d65qX6OwJoiu16zcntqNIbHq5P7Qj3lRn697f6njZXETgyLnQJHzmAg5fb1U1jwKgIiqxKYTcxIEOc+JdL6bskV6YctvQRb5ZDmGRCfGRBODoinrxIjIZZ3085q8JHoxInoxLJqyzvV9wCyjHt5Qrd/u9ddfjylTpqBnz5744Ycf8Kc//QkAsGfPHsTHx3uzfR5p0KABdu3apdq3ePFifPLJJ3jzzTfRqlWrCs9LT093dbAu691mWK21k4iIiCpXrc5JVlYWHnroIfz8889466230KhRIwBAfn4+UlJSvNrA8+fP48CBA67yoUOHsHPnTkRFRaFFixZIT0/H0aNH8dJLL8FisaBLly6q82NiYhASEqLZX57dbofdblft45QOEREZSSA9W6danZPIyEg899xzmv3y1Ig3fPXVVxg27MooxuURjokTJ2LVqlU4fvw4CgoKvH5fIiIiIwmk9PWKqEZSiY0bN6J+/foYOHAggEsjKcuWLUOnTp2QlZWFhg0ber2hvtY5NkFVrnEeEklNn72j1x6968vny/XL50FxSK8IT8tlDoeqXOosU5UvOtRlb/+uicyqUWi4qty6fhNVua1N/V7bBqGqcnyZ+pt287KLrv+OCbugOhbRSF0Oa6x+XQbFqL/LWhqGqcuR9VVlpX49VRlSWQlTn48wqX6IdDw4xG1Zsat/dtiC1eUg9ei4Jq9JkFRf59k8ijS6Hty6L2rbgU5JXrlO2+8+9Mp1alO15i4eeOABnD17FgCwa9cu/OMf/8Cf/vQnHDp0SBO7QURERDXnFIpXNjOo1rTOoUOH0KlTJwDAW2+9hT//+c+YN28eduzY4QqOJSIiIu9hzImO4OBgXLhwaQjw448/RmpqKgAgKirKNaJidvJy2Jov9dXeoTxPpzLkVX0yp7z8V2qfRZHvL9e/Qk4vL/9ulAB6wRD5khyYLy8dDpKOSxnnYZPKSrlXtqJI7wmadPWaxkjH9Zb+ykuNPVy66+lSX019naXDeunxpbI8jeOPpcSBpFq/3YEDByItLQ0DBgzA9u3bkZ2dDQD44YcfcNVVV3m1gURERBRYeU6qFXPy3HPPwWaz4c0338SSJUvQrNmlZGUffPABRo4c6dUGEhEREZ9KrKtFixZYv369Zv/TTz9d4wYRERGRViCNnNR40uyPP/5AaWmpal+DBg1qelm/k2My9NVuDIlMjhHRu55eDIpMNb8qHJVXJKJaY5XiKqxyjIn0vmOTY+Wk17mtXJyJ1ape8q8TcgFFflPRxHjIx6UYFb3z9WJMNDEgOjEtntaXY1Q8TWdPXlWtzklxcTH++c9/4vXXX8epU6c0xx0OfpgRERF5k1mWAXtDtWJOHnzwQXzyySdYsmQJ7HY7XnjhBcydOxdNmzbFSy+95O02EhERBTwhFK9sZlCtkZP33nsPL730EoYOHYrJkydj0KBBaNu2LVq2bIlXX30V48eP93Y7iYiIKEBUq3Py66+/onXr1gAuxZf8+uuvAC4tMb777ru91zo/skqDSk4P85h4GkPiacyKp3lO9GJQ5OOOcve3SG0TUlmexJPrE1H1BElxEnLMiTbGRM0ivc6tqjwn6mNy3hPNuLomr4leDEoN85b4Oi+KXl4TvbIPmGWljTdU67fbunVrHDp0CADQoUMHvP766wAujahERkZ6rXFERER0SSClr69W52Ty5Mn45ptvAACzZs1CVlYWQkJCMGPGDDzwwANebSAREREFlmpN68yYMcP134mJidi7dy/y8/PRtm1bdOvWzWuN8yc5Zbs8PFqFK6hK3p4Wqml6enfTOIA6Rb1ey/XupacaD8YmCggWeVpH+j4pv03I6evlaZ7yUzcWaSmxRcp1Ly/9ld8TNW8imrJ3p1n0p2100tXrTcN4unRYPu4DZglm9QavPBygZcuWaNmypTcuRURERBUIpO9x1e6cfPnll/j000/xyy+/wOlU98AXLFhQ44YRERFRYKpW52TevHl46KGH0L59e8TGxqqG+zRDf0RERFRjZglm9YZqdU4WLVqEFStWYNKkSV5ujnHIy2Fr+kgDvZgVOSZF0Szf9SymRC89vUy+n36kCRHVNk26eul1Ly8llqMgLNI8gKXcG5FFkWNM5JPlspyO3uK2rKGJMfHwTVUvRkXiabp6T5cOa+r7AGNOdFgsFgwYMMDbbSEiIqJKBNLISbW6fjNmzEBWVpa320JERERUvZGTmTNn4oYbbkCbNm3QqVMnBAUFqY6//fbbXmkcERERXRJIk+3V6pzcd999+PTTTzFs2DA0atSoTgbB1jTPiSaGROd3pB+T4p6n6em1uUgqj2kR8gCb0GsNEVWHJm+JHHMCuSzFoOhkoC9fWxMyoYlB8XBgXS/viSZPiod5UPR4GgOim/fE/3lNZIE0rVOtzsmLL76It956CzfccIO320NEREQBrlqdk6ioKLRp08bbbSEiIqJKcLWOjkceeQQZGRlYuXIlwsLCvN0mQ9AsrfV01Zun00DS9eWU7pqlzV6efZSXJsvp7MvTTFHVsCmBNI9K5I7FIi8dVpfdTdNUVLZKry6r5cqUrOYpxJrGyGWdaRuZl6dZ9JcGe/mpxXr8MM0TSBPq1eqcPPPMMzh48CBiY2MRHx+vCYjdsWOHVxpHREREgadanZMxY8Z4uRlERETkjvB0CN/EqtU5ycjI8HY7iIiIyA1Pn/huZjV6KnF+fj6+//57AEDnzp3Rs2dPrzTKCLQxHh7S6eDqxpR4HIOi5unSYV9yBtKjNYk8YJFjTKT4LjkGRT99feX3Uix66et1lv7qpXuXeRrj4Yf08O7ur5venryqWp2TX375Bbfddhtyc3MRGRkJADh9+jSGDRuGNWvWoHHjxt5sIxERUcBzBtC0TrW6fvfeey/OnTuHPXv24Ndff8Wvv/6K3bt34+zZs7jvvvuqfJ3PPvsMycnJaNq0KRRFwdq1a93WnzRpEhRF0WydO3d21XnkkUc0xzt06FCdH5OIiMgwBBSvbGZQrc7Jxo0bsXjxYnTs2NG1r1OnTsjKysIHH3xQ5esUFxeje/fuVX5Oz6JFi3D8+HHX9vPPPyMqKgq33nqrql7nzp1V9bZs2VLlNhERERmR00ubGVRrWsfpdGqWDwNAUFAQnM6q/+ijRo3CqFGjqlw/IiICERERrvLatWvx22+/YfLkyap6NpsNcXFxVb5uVcgxHjJNunqpvtBJZ1/TGBRPeZLXxFPy78LbOVmI6iq9dPV6eU60x+XHUrjJX+TtEApv5wHRi3mRafKaWCuuV9XrkU9V6//Gddddh/vvvx/Hjh1z7Tt69ChmzJiB4cOHe61xepYvX47ExES0bNlStX///v1o2rQpWrdujfHjx6OgoMBnbSIiIqoNnNbR8dxzz+Hs2bOIj49HmzZt0KZNG7Rq1Qpnz57Fs88+6+02VujYsWP44IMPMGXKFNX+hIQErFq1Chs3bsSSJUtw6NAhDBo0COfOnfNJu4iIiGoDp3V0NG/eHDt27MDHH3+MvXv3AgA6duyIxMRErzbOnRdffBGRkZGahHDlp4m6deuGhIQEtGzZEq+//jpuv/32Cq9VUlKCkpIS1T6ncGqW9REREVHtq3aeE0VRcP311+P666/3ZnuqRAiBFStWYMKECQgODnZbNzIyEu3atcOBAwcqrZOZmYm5c+eq9jWr3xLNG7Ry24by9GNSdHia10ROQSBNJWvv5724D7ltnuYtqWm8DFFdJceCybFp2hgUqb7OS6v85eRHZGnq6j1Lx9Nn7eip6bNuPPwyqclb4u321AKzjHp4Q5U7J8888wzuvPNOhISE4JlnnnFb15PlxNWxefNmHDhwoNKRkPLOnz+PgwcPYsKECZXWSU9PR1pammrf9R2Sa9xOIiIibzFLvIg3VLlz8vTTT2P8+PEICQnB008/XWk9RVGq3Dk5f/68akTj0KFD2LlzJ6KiotCiRQukp6fj6NGjeOmll1TnLV++HAkJCejSpYvmmjNnzkRycjJatmyJY8eOISMjA1arFSkpKZW2w263w263q/ZxSoeIiMg/qtw5OXToUIX/fXmIXh5+rIqvvvoKw4YNc5Uvj15MnDgRq1atwvHjxzUrbc6cOYO33noLixYtqvCaR44cQUpKCk6dOoXGjRtj4MCB2LZtm8dZa7Xp4d0vBZbpp5t3P/6qt9TYU7W5dJiIvEOzlFhOZy/V97Ss+HIpsd4NjPYFUG+pcU3re4E8nV+XVfuvY/ny5ejSpQtCQkIQEhKCLl264IUXXvDoGkOHDoUQQrOtWrUKALBq1Srk5uaqzomIiMCFCxdwxx13VHjNNWvW4NixYygpKcGRI0ewZs0atGnTpjo/IhERkWE4oXhlq46srCzEx8cjJCQECQkJ2L59e5XOW7NmDRRF0Sxe0VOtzsmcOXNw//33Izk5GW+88QbeeOMNJCcnY8aMGZgzZ051LklEREQGlJ2djbS0NGRkZGDHjh3o3r07kpKS8Msvv7g97/Dhw5g5cyYGDRrk8T2r1TlZsmQJli1bhszMTNx444248cYbkZmZieeffx6LFy+uziWJiIjIDeGlzVMLFizAHXfcgcmTJ6NTp05YunQpwsLCsGLFikrPcTgcGD9+PObOnYvWrVt7fM9qdU4uXryI3r17a/b36tULZWVl1bmk4VmguN1k8sMH9a4n/zOziqbqVJv0j4gu0TzYVPcfVJtFZ1PdyyJUGxmft5KwlZSU4OzZs6pNzvV1WWlpKfLz81V5zCwWCxITE5GXl1dpWx999FHExMRUaVVtRarVOZkwYQKWLFmi2f/8889j/Pjx1WoIERERVc6pKF7ZMjMzXc+qu7xlZmZWeM+TJ0/C4XAgNjZWtT82NhaFhYUVnrNlyxYsX74cy5Ytq/bPWuXVOuXzgCiKghdeeAEfffQRrr32WgDAF198gYKCAqSmpla7MURERFS7KsrtJafTqK5z585hwoQJWLZsGaKjo6t9nSp3Tr7++mtVuVevXgCAgwcPAgCio6MRHR2NPXv2VLsxREREVDFvTb5VlNurMtHR0bBarSgqKlLtLyoqQlxcnKb+wYMHcfjwYSQnX0lk6nReym1rs9mwb9++Kq2grXLn5NNPP61q1TpBPx29Z3lMapq3RD5fk65ebq6B8pjI6e2Zvp6oYnI+Ivl9Ra+sf/0Afu0ZLa9KNfgjfX1wcDB69eqFnJwc13Jgp9OJnJwcTJs2TVO/Q4cO2LVrl2rfQw89hHPnzmHRokVo3rx5le5b7WfrEBERUd2XlpaGiRMnonfv3ujbty8WLlyI4uJiTJ48GQCQmpqKZs2aITMz05X3rLzIyEgAqDCre2XYOSEiIjIBf2WIHTt2LE6cOIE5c+agsLAQPXr0wMaNG11BsgUFBbB4+cGI7JxUk940jqfp6rX11Yy85FZum6dPKSaiS+R09fJ0rt5nkzzdq3jyvqGX+578rrrZXb1h2rRpFU7jANBkcpddzvruCf75ERERkaFw5ISIiMgEAmlMmp0TIiIiEwikpxKzc1IJzcpcb1+/hkuLfUkIdQSMXvyM5nxwKTFRVWhSBshLh3VSCnh0L6as90wdWIpsJuycEBERmYA/8pz4CzsnREREJhBIY13snBAREZkAY05IQy8Gxdt5T8xEjiHRiympOz85kXcpNUxPb+jPLil2TVP29f1rfL61Ztcjt9g5ISIiMgHGnBAREZGhsHNCmiV7ckr22l5q7G/uUtB7uhSY6eyJqkZ+35HfZzzNMF+jxa++/iR0Ot2XKaCwc0JERGQCwtBBRd7FzgkREZEJBNJYElPeERERkaFw5KSW1KWlw3ptl4/LZaarJ6oaOX29qTil17mvY0Z8vTTZD+r+T3gFOydEREQmEEhf8zitQ0RERIbCkRMiIiITYPp60jB73hO5vXplT64l06SzN9xvg8gctHlPvPfpJORPOk8DGuQYE095GpMi1/d2jInToS5bjffxGEgxJ4ae1snMzESfPn0QHh6OmJgYjBkzBvv27XN7zp49e3DzzTcjPj4eiqJg4cKFvmksERFRLXJ6aTMDQ3dONm/ejKlTp2Lbtm3YtGkTLl68iBEjRqC4uLjScy5cuIDWrVtj/vz5iIuL82FriYiIyBuMN25VzsaNG1XlVatWISYmBvn5+Rg8eHCF5/Tp0wd9+vQBAMyaNavW2+gt8hJCizRi6vDx1Ej5qRjdpwxzqTCRVxj6KcS1PY3j7acWy+dL0zZCOm6GcI5Aeqc1dOdEdubMGQBAVFSUn1tCRETkW4EUEGvoaZ3ynE4npk+fjgEDBqBLly7+bg4RERHVEtOMnEydOhW7d+/Gli1bvH7tkpISlJSUqPY5hRMWxTR9NyIiquPMEszqDab49J02bRrWr1+PTz/9FFdddZXXr5+ZmYmIiAjVVnDuMJRy/3zNCaHajERI/5zC/SakjYgqpiiKepP+eaomqzSEU6i2Cip4ttWQEA7VpuF0qrea8vb1vEB4aTMDQ3dOhBCYNm0a3nnnHXzyySdo1apVrdwnPT0dZ86cUW0tw2vnXkREROSeoad1pk6ditWrV2PdunUIDw9HYWEhACAiIgKhoaEAgNTUVDRr1gyZmZkAgNLSUnz33Xeu/z569Ch27tyJ+vXro23bthXex263w263q/ZxSoeIiIzEaKPotcnQn8BLlizBmTNnMHToUDRp0sS1ZWdnu+oUFBTg+PHjrvKxY8fQs2dP9OzZE8ePH8dTTz2Fnj17YsqUKf74EYiIiLwikJKwGXrkpCrxCbm5uapyfHy8T+Ia9NLZ+1pNf2Y5xXz5HACe9ta11wqc3j6RWemGhdQ07kJ+H5Cvp1f2tD2etlfvFyBfT6kg7oW8xtCdEyIiIrokkL7msXNCRERkAmaZkvEGdk6IiIhMIJAyxLJzYhDejsvQxH3olD26tnAfUyLH3wTSUCRRTXj6bB1POcWV6wu9Tzq9Z+nIx/XKMk/f8+SYD0+fxaN51o5UturUJ59i54SIiMgEAmkpMTsnREREJhA4XRN2Tuj/k6diyvfQNdM2cF8mIu+o7Wme8vSXErt/nQtpmkTxdGmwp9M0OuQU97q/SZ1pHiG1J4DCP/yCnRMiIiITCKQoGHZOiIiITCCQRqkNnb6eiIiIAg9HTkyqpj3o2ky3z3T1RL6h90oTUmSEKL+UWO9keQ5BijnRxJjoXM7jdPV6S4c19XXSyetdT1Nfup5V+rj0w1LjQHpnZeeEiIjIBAIp5oTTOkRERGQoHDkhIiIygUAKiGXnpI7Q5B7RSSkv06S3L1dfk45erxxALyAiI/HklSenr9emGalp+noPY0b01DRPiub+6pgS3TwmeunufSCQ3lnZOSEiIjIBxpwQERER+QlHTkzCn8tz5WkavSkjLiUmqh5F8e73RfmbttuXpnC/GFh+XSvyNI5mGsXD9wFPp31qetzT9nj7+tUQSFPm7JwQERGZAKd1iIiIiPyEIydEREQmwKXEVOdplw6rBww9eRG4W4ZMRLVHk2FeJ4e8U5W+3v1SYr309RVcXCqrLyAvTVb0Ykx0lgILoV4KrHgag6J3f3mpsOb+TF9fmzitQ0RERIbCkRMiIiIT4LQOERERGUogrdZh58Sg9Naz66WM1yt71BadPCaaPCfVvhMRlVfTb8ruPsz0QiY06ev18prIMRt66ey9Xa5pjIrez6Ooz4eVH5+1ib9dIiIiE2ASNiIiIjIUTuuQLr2n/Hp8PR/3iDUp6N09lVhOXx9AvXciI9E8SkJaOqxJVy89W7f88mGnZimxfDHpPUH3KcR66ex10ttryp4+Zdj9U4d157EkHj+l2AcCaeSES4mJiIjIUPzaOcnMzESfPn0QHh6OmJgYjBkzBvv27avy+WvWrIGiKBgzZoxq/6RJk6AoimobOXKkl1tPRETkO04vbWbg187J5s2bMXXqVGzbtg2bNm3CxYsXMWLECBQXF+uee/jwYcycORODBg2q8PjIkSNx/Phx1/baa695u/lEREQ+4xTCK5sZ+DXmZOPGjaryqlWrEBMTg/z8fAwePLjS8xwOB8aPH4+5c+fi888/x+nTpzV17HY74uLivN3kSnn6v9vTFO81XlLo6f3c1NdbWkxE1VPTlOh66ezlOBPVvXVCOvRiULTp6PViVHy8tFimaa8Uo6JI3911f0HkTYaKOTlz5gwAICoqym29Rx99FDExMbj99tsrrZObm4uYmBi0b98ed999N06dOuXVthIREfmS8NJmBoZZreN0OjF9+nQMGDAAXbp0qbTeli1bsHz5cuzcubPSOiNHjsRf/vIXtGrVCgcPHsTs2bMxatQo5OXlwWqVn+ZERERkfIG0UtIwnZOpU6di9+7d2LJlS6V1zp07hwkTJmDZsmWIjo6utN5tt93m+u+uXbuiW7duaNOmDXJzczF8+HBN/ZKSEpSUlKj2OYUTFnlYj4iIiGqdITon06ZNw/r16/HZZ5/hqquuqrTewYMHcfjwYSQnJ7v2Of//PKPNZsO+ffvQpk0bzXmtW7dGdHQ0Dhw4UGHnJDMzE3PnzlXtaxneCq0aaK9VVTXNDaIXx6G5vk5Kec313eQ18bQtgbT2nsifNGEgmtde5TElgHpIX8h5TuR4FO3NpLL7mBIhxYBo0sV7GjPiaV4Rb8eoyPX9MAgfSO+1fu2cCCFw77334p133kFubi5atWrltn6HDh2wa9cu1b6HHnoI586dw6JFi9C8efMKzzty5AhOnTqFJk2aVHg8PT0daWlpqn3JHW/y4CchIiKqXYEUguvXeYupU6filVdewerVqxEeHo7CwkIUFhbi999/d9VJTU1Feno6ACAkJARdunRRbZGRkQgPD0eXLl0QHByM8+fP44EHHsC2bdtw+PBh5OTkYPTo0Wjbti2SkpIqbIfdbkeDBg1UG6d0iIiILsnKykJ8fDxCQkKQkJCA7du3V1p32bJlGDRoEBo2bIiGDRsiMTHRbf2K+PUTeMmSJThz5gyGDh2KJk2auLbs7GxXnYKCAhw/frzK17Rarfj2229x4403ol27drj99tvRq1cvfP7557Db7bXxYxAREdU6J4RXNk9lZ2cjLS0NGRkZ2LFjB7p3746kpCT88ssvFdbPzc1FSkoKPv30U+Tl5aF58+YYMWIEjh49WuV7KoJJKio07KrrVWXNMy3kXB/S+XoxJ/KvXRtD4nR73CEd1yuXSY8LL3OWqcoXNcevlEsd6rra8kWp7fyTIqqO5uHqQP+WoY3VZVuEuj7UX7iucqi/bza5qH4faKxcCfyPCv9ddax+wz9U5ZAo9XuCLUodZGFtGKIqK+Gh6nL9elI5TF2upy4jJFSnLNeXysFSe4KkL6PB0vVswer6Nqm+fL5VHQWhSOcHt7wGte2Wljd65Tpv/vSuR/UTEhLQp08fPPfccwAuxXo2b94c9957L2bNmqV7vsPhQMOGDfHcc88hNTW1Svc0REAsERERueetmJOKVqja7fYKZxdKS0uRn5/vCq8AAIvFgsTEROTl5VXpfhcuXMDFixd1c5iVx8AKIiKiAJKZmYmIiAjVlpmZWWHdkydPwuFwIDY2VrU/NjYWhYWFVbrfP//5TzRt2hSJiYlVbiNHTirh6yVbevfTpIyXp4l0yh63p9z9dO/NaRwin9BMJ+us/pVfmeWXC8svW6HJda+5uWdlTbp3nfT3tZ3OXk5Pr5eOXq4vTev4I329t95rK1qhWlsxmfPnz8eaNWuQm5uLkJAQ/RP+P3ZOiIiITMBbGWIrm8KpSHR0NKxWK4qKilT7i4qKdJ9f99RTT2H+/Pn4+OOP0a1bN4/ayGkdIiIiqlBwcDB69eqFnJwc1z6n04mcnBz069ev0vOefPJJPPbYY9i4cSN69+7t8X05ckJERGQC/krClpaWhokTJ6J3797o27cvFi5ciOLiYkyePBnApXxkzZo1c8WtPPHEE5gzZw5Wr16N+Ph4V2xK/fr1Ub9+/Srdk50TP/H1A5w06e1rEDeit4yaiKpH77EU2pQF1S/LMSbaGBT3FxMOOT29XkyKXvp4uQE6DZJSGuimu9c77ml9xQ8xJ356tx07dixOnDiBOXPmoLCwED169MDGjRtdQbIFBQWwWK5MxCxZsgSlpaW45ZZbVNfJyMjAI488UqV7snNCREREbk2bNg3Tpk2r8Fhubq6qfPjw4Rrfj50TIiIiE/D1iLs/sXNCRERkAoGUtoGdkyqqaZyFp39UNe0h1zSFfPn71yQ+hYhqj+a1KR9X5LiSK2WHU71Y01mmLmvTgHiY10SO0XA43JdrmsdEikERcrp5nZgSIT3CQ79+ID0j2PfYOSEiIjKBQOoOsXNCRERkAv5areMP7Jx4id5TiPXoTZXoLTHUm8bRSzmvmbZyk76eiHxD72nn2mkcnfPL7dBduevwcjp7T5cW6y3trfHS4Bqms1d8n8M0kAJimSGWiIiIDIUjJ0RERCYQSKPY7JwQERGZQCBN67BzYlA17SF7Gjjlrr52GXXgvECIfEkTC6aJMZGPw8PylTgSp5CWGcvp7OUQjDKpLVIMiSiT0tlLS4WFFAOit1S3xjEltZ3OnkuJaxU7J0RERCYQSF8M2TkhIiIygZom1zQTrtYhIiIiQ+HIiZ/UNCZEr6w5X5of1QusctdDD6SIcSIj0Yty0MSYaPKeXNkh5JgT3RgU6XVf5j5viTbGxH1iFVGmkz5eTnfvacyIhzEluunsFak9PhBI77zsnBAREZlAIK3W4bQOERERGQpHTipR08AjvSWBmvt5uUesSW+vk77eXVkv9T0ReYenj8HQTWcPRSqXq6vzUGHNSllPn1Isl/WeQizfsKZPLZanaRwXVWXFJn38eZrO3g9LiQNp5ISdEyIiIhMIpC+G7JwQERGZQCCNnDDmhIiIiAyFIydVpPfocq/HjHi41LemMTLufh5t+noiqg16sWC6MSbS0mGHXC4Xg+Jwqr+bymWndLIok28mtcWhs3RYb2mwXn3N+VKDapqu3tOlyYrvY06YIZaIiIgMJZBiTgw9rZOZmYk+ffogPDwcMTExGDNmDPbt26d73sKFC9G+fXuEhoaiefPmmDFjBv744w8ftJiIiIhqytCdk82bN2Pq1KnYtm0bNm3ahIsXL2LEiBEoLi6u9JzVq1dj1qxZyMjIwPfff4/ly5cjOzsbs2fP9mHLiYiIvMsJ4ZXNDAw9rbNx40ZVedWqVYiJiUF+fj4GDx5c4Tlbt27FgAEDMG7cOABAfHw8UlJS8MUXX9R6ez3h6fCcpzElerlJPLleIA0lEhmJNsZEjkGR61e97NRNVy+X1dcSmvT1enlNdOqX6cSQ6MWEyDEoctmq/rjT5D2Rjuumsxe+/24fSO/Fhh45kZ05cwYAEBUVVWmd/v37Iz8/H9u3bwcA/Pjjj3j//ffxpz/9ySdtJCIiopox9MhJeU6nE9OnT8eAAQPQpUuXSuuNGzcOJ0+exMCBAyGEQFlZGe666y630zolJSUoKSlR3084YVFM1XcjIqI6zCxTMt5gmk/fqVOnYvfu3VizZo3berm5uZg3bx4WL16MHTt24O2338aGDRvw2GOPVXpOZmYmIiIiVNvP5w57tf1C+qc5LoRq8/b19erL969JW4ioepxCqDbNcWlzQKg2AehsSrlNOibUm9OhqDbhhGrTNMYpVJuQNjgcqk2UqTe5AZrj0vnaBjvdb/IPIB93lKk3p0O9aY5L5/uA5n27mv/MwBSdk2nTpmH9+vX49NNPcdVVV7mt+/DDD2PChAmYMmUKunbtiptuugnz5s1DZmYmnJX8AaWnp+PMmTOqrXl4fC38JERERKTH0NM6Qgjce++9eOedd5Cbm4tWrVrpnnPhwgVYLOo+l9VqdV2vIna7HXa7XbWPUzpERGQkNU22aSaG7pxMnToVq1evxrp16xAeHo7CwkIAQEREBEJDQwEAqampaNasGTIzMwEAycnJWLBgAXr27ImEhAQcOHAADz/8MJKTk12dFCIiIrMxy5SMNxi6c7JkyRIAwNChQ1X7V65ciUmTJgEACgoKVCMlDz30EBRFwUMPPYSjR4+icePGSE5OxuOPP+6rZgOoeeCSZimwTllzvrQMribp8APpBUHkT7qve/l1qrhPb+9UFKl85b816esd6rJmKbEmnb3UtjIpfX2ZeumtkKbVlZqmk5eXHgcFuT9fZ2mx7tJki/rLrby02Bc4cmIQVQnGzM3NVZVtNhsyMjKQkZFRS60iIiKi2mTozgkRERFdEkij2OycEBERmQCndUj7KHJN2mj3c8F6vJ1Mx+P09jr1y/fQmeuEyD80MSaamBQ1OQqiTHP8StyInFhByOnspYvrZZPX5sqX09PLMSQepruXY0CEFGMix6BYPYsx0aanl9srtU/zCyBvYueEiIjIBDitQ0RERIYSSNM6zDRGREREhsKREx/Ri9vQxLS4yTtSUVnveroxJm6OM+aEyDf0Yky0YR7uj0thJKrjAuqDDimviVPKe+Isky/mPs+JcOjkNSnTiTGRYkiElMdE0eRFkc6Xj+vlMdHLe6KXN8UHOK1DREREhiIn16zLOK1DREREhsKRk1qin17eu8NzummudYeL3aWvJyJf0JuOlV/nmmkeN9M4AOAol86+TE5PLy8l1syayOnr5ZvLZZ309tINRJm8lFdnmkaz9NjDaRibzf1xa5D74354OKy3U1AYGTsnREREJhBI8X/snBAREZlAII2cMOaEiIiIDIUjJ15S0x6tboyKzqPUPb5fDZYWE1Ht0F9KrBeDoi47pOXCniwldjjdLyXWxKSU6cSYaGJQdNLFy0uN9WJM5JiQMqu67OFSYeG4qG6fRfou74eVM4H0vszOCRERkQkwQywRERGRn3DkhIiIyASYIZb053o9HF7zNCbF0z9COXOg3ty09vzA+aMnMip52F5+3TqEHFMil6XryXlPypXleBRtnhP5uHQtKcRDyOnnNeno9dLVS8flmA6nHBMixax4ms5eL329zv01ZR8IpPdpTusQERGRoXDkhIiIyAQCKc8JOye1xNOnEHuqplHbek85DqS5TSKj0ntdevqU4vJTOZpjQn4qsVQuUw+0C4eczl5eKqwzzaNZGqyz1Fh3KbF0vEyettFZWixP80hLh4VUX/HHU4k5rUNERETkHxw5ISIiMoFAynPCzgkREZEJBNK0DjsnXlLTGA29GBC9HrPuo9b1yjVcKk1ENaf3utTElMj1paXD7pYWa1LbC5309XKMiWadsvsYE+GQ09NL6e11YlB0Y0x00tF7vJRYr74ixbD4QCAFxDLmhIiIiAyFIydEREQmEEgj2uycEBERmQADYklD71Hmnp5fU57GuPi7vUSkTzemRBOTolYmn+8mBkVzTE5fL11cTm+viUGR09nr5TmRY1KcOjEoOjEmmnT2eufbdGJKbO5jUISQI3rIm/wac7JkyRJ069YNDRo0QIMGDdCvXz988MEHldbfs2cPbr75ZsTHx0NRFCxcuFBT55FHHoGiKKqtQ4cOtfhTEBER1T7hpX9m4NeRk6uuugrz58/H1VdfDSEEXnzxRYwePRpff/01OnfurKl/4cIFtG7dGrfeeitmzJhR6XU7d+6Mjz/+2FW2yT1gIiIik+G0jo8kJyeryo8//jiWLFmCbdu2Vdg56dOnD/r06QMAmDVrVqXXtdlsiIuLq1HbapxeXu8pwDpPDdYra65Xw6XHgfRHT2RUni4ldkhJ6OVXsSdLiQXcLyV2aJYSS9eWs79r0tlL0zbyU4jL5KXG6uMep7PXK2vS29vcH1ekiQYLF7vWJsP8dh0OB9asWYPi4mL069evRtfav38/mjZtitatW2P8+PEoKCjwUiuJiIj8Qwjhlc0M/D7fsWvXLvTr1w9//PEH6tevj3feeQedOnWq9vUSEhKwatUqtG/fHsePH8fcuXMxaNAg7N69G+Hh4V5sORERke+YJV7EG/w+ctK+fXvs3LkTX3zxBe6++25MnDgR3333XbWvN2rUKNx6663o1q0bkpKS8P777+P06dN4/fXXKz2npKQEZ8+eVW1OecySiIgoQGVlZSE+Ph4hISFISEjA9u3b3dZ/44030KFDB4SEhKBr1654//33Pbqf3zsnwcHBaNu2LXr16oXMzEx0794dixYt8tr1IyMj0a5dOxw4cKDSOpmZmYiIiFBtR8/95NF99IbNnBCqraaEcKo2+fqaf54O/QGujYh8wymE203+5wR0NvX7Qhng2uS6ZUJRbUJA2hTV5nSoN+GEapNvIMqEaoNT2hwO9SZfUK7vdKo3+XxHmftN/gE1x53uN/n+PuCvaZ3s7GykpaUhIyMDO3bsQPfu3ZGUlIRffvmlwvpbt25FSkoKbr/9dnz99dcYM2YMxowZg927d1f5nn7vnMicTidKSkq8dr3z58/j4MGDaNKkSaV10tPTcebMGdXWLLyl19pARERUU/7qnCxYsAB33HEHJk+ejE6dOmHp0qUICwvDihUrKqy/aNEijBw5Eg888AA6duyIxx57DNdccw2ee+65Kt/Tr52T9PR0fPbZZzh8+DB27dqF9PR05ObmYvz48QCA1NRUpKenu+qXlpZi586d2LlzJ0pLS3H06FHs3LlTNSoyc+ZMbN68GYcPH8bWrVtx0003wWq1IiUlpdJ22O12V66Vy5tFjswmIiLyI+GlzROlpaXIz89HYmKia5/FYkFiYiLy8vIqPCcvL09VHwCSkpIqrV8RvwbE/vLLL0hNTcXx48cRERGBbt264cMPP8T1118PACgoKICl3HKtY8eOoWfPnq7yU089haeeegpDhgxBbm4uAODIkSNISUnBqVOn0LhxYwwcOBDbtm1D48aNffqzERERGVFJSYlmhsJut8Nut2vqnjx5Eg6HA7Gxsar9sbGx2Lt3b4XXLywsrLB+YWFh1RspSOOPP/4QGRkZ4o8//vB3U6rETO01U1uFYHtrk5naKgTbW5vM1FYhzNdeWUZGhmZAJSMjo8K6R48eFQDE1q1bVfsfeOAB0bdv3wrPCQoKEqtXr1bty8rKEjExMVVuoyKESRY9+9DZs2cRERGBM2fOoEGDBv5uji4ztddMbQXY3tpkprYCbG9tMlNbAfO1V+bJyElpaSnCwsLw5ptvYsyYMa79EydOxOnTp7Fu3TrNOS1atEBaWhqmT5/u2peRkYG1a9fim2++qVIbGVhBREQUQCqKs6yoYwJcWlHbq1cv5OTkuPY5nU7k5ORUmjC1X79+qvoAsGnTJo8SrPo9CRsREREZV1paGiZOnIjevXujb9++WLhwIYqLizF58mQAlxavNGvWDJmZmQCA+++/H0OGDMF//vMf3HDDDVizZg2++uorPP/881W+JzsnREREVKmxY8fixIkTmDNnDgoLC9GjRw9s3LjRFfQqL17p378/Vq9ejYceegizZ8/G1VdfjbVr16JLly5Vvic7JxWw2+3IyMiodJjLaMzUXjO1FWB7a5OZ2gqwvbXJTG0FzNdeb5g2bRqmTZtW4bHLq2XLu/XWW3HrrbdW+34MiCUiIiJDYUAsERERGQo7J0RERGQo7JwQERGRobBzQkRERIbCzgkREREZCpcS6ygqKsJ///tfzJkzx99NIVL5/fff8dprr2HLli04fvw4LBYLWrdujTFjxmD48OH+bp4G20uXrV+/Htu3b0dSUhIGDBiATz75BE899RScTif+8pe/4M477/R3E13uvfde/PWvf8WgQYP83ZTAUuWn8ASonTt3CovF4u9mVNmBAwfEsGHD/N0Ml2PHjomXX35ZbNiwQZSUlKiOnT9/XsydO9dPLavYRx99JObMmSNycnKEEEJs3rxZjBw5UgwbNkysWLHCz627Yv/+/aJly5YiJiZGNG/eXCiKIm644QaRkJAgrFaruPXWW8XFixf93UwXtrd2Pfvss2LChAnitddeE0II8dJLL4mOHTuK9u3bi/T0dEO1denSpcJms4levXqJBg0aiJdfflmEh4eLKVOmiL///e8iNDRULFy40N/NdFEURVgsFnH11VeL+fPni+PHj/u7SQEh4Dsn33zzjdstOzvbVJ0TI3Wmtm/fLiIjI0WDBg1EaGioaNu2rdi9e7freGFhoWHaKoQQL7/8srDZbOKaa64R9evXFytXrhSRkZFiypQp4n/+539EcHCweOONN/zdTCGEEKNGjRJ///vfhdPpFEIIMX/+fDFq1CghhBA//PCDiI+Pr/Qpo/7A9taexx57TISHh4ubb75ZxMXFifnz54tGjRqJf//732LevHmicePGYs6cOf5upkunTp3E888/L4QQ4pNPPhEhISEiKyvLdXzlypWiY8eO/mqehqIo4uOPPxb333+/iI6OFkFBQeLGG28U7733nnA4HP5uXp0V8J2Ty71iRVE02+X9RvoAXbRokdvtwQcfNEx7ExMTxeTJk4XD4RBnz54Vd999t2jUqJHYsWOHEMJ4nZMePXqIRYsWCSGE+Pjjj0VoaKhYsGCB6/hTTz0lBgwY4K/mqYSFhYkffvjBVS4pKRFBQUHi5MmTQggh1q5dK+Lj4/3VPA22t/a0adNGvPXWW0KIS19OrFareOWVV1zH3377bdG2bVt/NU8jNDRU/PTTT65yUFCQ2LVrl6t86NAhERYW5o+mVUhRFFFUVCSEEKK0tFRkZ2eLpKQkYbVaRdOmTcXs2bPF/v37/dzKuifgY06ioqLw5JNPVjqHvGfPHiQnJ/u4VZWbPn06mjRpguDg4AqPl5aW+rhFlcvPz0dWVhYsFgvCw8OxePFitGjRAsOHD8eHH36IFi1a+LuJKvv373f9vx4+fDjKyspUfxc33HCD68FW/hYZGYlz5865yhcuXEBZWZnr76Jbt244fvy4v5qnwfbWnmPHjqF3794AgO7du8NisaBHjx6u49dccw2OHTvmp9ZpNWrUCD/99BNatGiBY8eOoaysDAUFBa7nrvz000+IiorycysrFhQUhL/+9a/461//ioKCAqxYsQKrVq3C/Pnz4XA4/N28OiXgOye9evXCsWPH0LJlywqPnz59GsJAGf5btmyJJ554An/9618rPL5z50706tXLx62q3B9//KEqz5o1CzabDSNGjMCKFSv81KqKBQUFqTp3drsd9evXV5V///13fzRN4/rrr0daWhqWLl0Ku92O9PR09OjRA+Hh4QAuPYgrJibGz628gu2tPXFxcfjuu+/QokUL7N+/Hw6HA9999x06d+4M4NIXLKO0FQBGjx6N22+/HRMnTsS7776L1NRU/OMf/4DFYoGiKHjggQcwYsQIfzdTV4sWLfDII48gIyMDH3/8sb+bU+cEfOfkrrvuQnFxcaXHW7RogZUrV/qwRe716tUL+fn5lXZOFEUxTGeqS5cu2Lp1K7p166baP3PmTDidTqSkpPipZRVr27Yt9u7di/bt2wMAjh496vowAoCDBw/iqquu8lfzVJ588kmMHj0anTp1gqIoaN68Od555x3X8RMnTuCBBx7wYwvV2N7aM378eKSmpmL06NHIycnBgw8+iJkzZ+LUqVNQFAWPP/44brnlFn830+WJJ55AaWkp1qxZg/79++PZZ5/FM888g9GjR+PixYsYMmSIYUYogUtfCK1Wa6XHFUXB9ddf78MWBQY++M9kvvvuO1y4cME1jCu7ePGi25EgX3rhhRewefNmvPzyyxUef+KJJ7B06VIcOnTIxy2r2DvvvINGjRph8ODBFR6fP38+iouL8dhjj/m4ZZXbv38/SkpK0KFDB9hsxv+uwfZ6n9PpxPz585GXl4f+/ftj1qxZyM7OxoMPPogLFy4gOTkZzz33HOrVq+fvprr1xx9/4OLFi6ovBBS42DkhIr85dOgQmjdvbtgPfiJ3hBBQFMXfzaiTmCEWl0Yj7rnnHvTs2RNNmjRBkyZN0LNnT9xzzz347rvv/N08ogpt2rQJGRkZ+OSTTwAAn332GUaNGoXrrrvOUFOR7rRv3x779+/3dzN0HTt2DBkZGRg/fjxmzpyJvXv3+rtJusrKyvzdhAolJyfj5ZdfNkz8lp6SkhLMnDkTgwcPxhNPPAEA+Pe//4369esjPDwc48aNw9mzZ/3cyron4EdOPvjgA4wZMwbXXHMNkpKSEBsbC+BSZthNmzYhPz8f69atQ1JSkp9bWjWzZ89GYWGh4YJNK2KmtgLGau8rr7yCyZMno1u3bvjhhx/w7LPPYsaMGbjlllvgdDrxyiuv4NVXXzVMrMFf/vKXCvevW7cO1113nWso/+233/ZlsyoVFhaGn376CY0bN8Z3332H/v37o3HjxujZsyd27dqFgoIC5OXlaeKp/GHjxo1o1qwZunbtCqfTiccffxxLly5FYWEhmjRpgmnTpuGf//ynYb7hWywWWK1W1KtXDykpKZgyZYqhgvhlaWlpyM7ORkpKCt5//30MGzYM69evx7x582CxWDBnzhyMGjUKzzzzjL+bWrf4bRGzQXTr1k08/PDDlR7PyMgQXbt29WGLambChAmGyhDrjpnaKoSx2mumnCxCXMoVMWTIEDFp0iTVZrFYxJgxY1xloyif22L06NEiOTnZlWXV4XCI2267Tfz5z3/2ZxNd2rdvLz777DMhhBDz5s0TjRo1EgsWLBAffPCBWLhwoYiNjRXz58/3cyuvUBRF7NmzRzz99NOia9euwmKxiO7du4tnn31W/Prrr/5unkbz5s3Fpk2bhBBCHDx4UFgsFrF27VrX8Y8++ki0bNnST62ruwK+cxISEiL27t1b6fG9e/eKkJAQH7aISF+9evXEjz/+6CoHBQWJb775xlX+/vvvRaNGjfzRtAq99tpr4qqrrtI8AsBms4k9e/b4qVWVK985ad68uevD/7IdO3aIJk2a+KNpGna73ZXUrEuXLuL1119XHV+/fr2hkrCV/90KIcQXX3wh7rzzThERESFCQ0NFSkqK6/ERRlBR0rjyma6NljSurgj4KLT4+Hhs2LDBtXxUtmHDBkOsfCnv5MmTWLFiBfLy8lBYWAjgUq6D/v37Y9KkSWjcuLGfW3iFmdoKmKe9ZsrJAgC33XYbrr32Wvztb3/D+vXr8cILL6Bhw4b+blalFEVxTYNYLBZERESojkdGRuK3337zR9M0oqKicOzYMbRo0QInTpxA27ZtVcfbtWuHo0eP+ql1+vr27Yu+ffvi6aefxuuvv47ly5fj+uuvN0xSsxYtWiAvLw8tWrTAl19+CUVRsH37dlcemS+++ALNmjXzcyvrnoDvnDz66KMYN24ccnNzkZiYqIo5ycnJwcaNG7F69Wo/t/KKL7/8EklJSQgLC0NiYiLatWsH4FJ7n3nmGcyfPx8ffvhhpUuNfclMbQXM1V4z5WS5LD4+Hp999hnmzp2L7t27Y9myZYaJg5AJIdCuXTsoioLz58/j22+/VcWXHDhwAHFxcX5s4RU33XQTHn/8caxduxajR4/G4sWL8fzzz7t+t88++6wqY6xRhYWFYdKkSZg0aRJ++OEHfzfH5a677sKkSZPwwgsvID8/H0899RRmz56NvXv3wmKxYMmSJfjHP/7h72bWOQEfEAsAW7duxTPPPKP5ttyvXz/cf//96Nevn59beMW1116L7t27Y+nSpZo3diEE7rrrLnz77bfIy8vzUwuvMFNbAXO114w5WcrbsmULUlNT8dNPP2HXrl3o1KmTv5uk8uKLL6rK7du3x7XXXusqP/bYY/jtt9+wYMECXzdN48yZM0hMTMTp06fRr18/vPHGG4iNjUW7du1w4MAB/Prrr/jwww+RkJDg76YCAIYNG4Z33nkHkZGR/m5Kla1evdqVRyYlJQW5ubmYM2eOK4/Mww8/DIuFi1+9iZ0TkwkNDcXXX3+NDh06VHh879696NmzpyGG9M3UVsB87TW78+fP4+DBg+jYsWOlz4qiqrl48SKWL1+O9957Dz/++COcTieaNGmCAQMG4O677zbcKBqRnoCf1jGbuLg4bN++vdIP0O3bt7umpvzNTG0FzNdes6tfvz66d+/u72bUCUFBQbjrrrtw1113+bspRF7BzokOI+W2AC49l+bOO+9Efn4+hg8fromRWbZsGZ566ik/t/ISM7UVMF973THa360etpcuM9vv1mztNQt2TnQcOXIER44c8XczXKZOnYro6Gg8/fTTWLx4sSui3Wq1olevXli1alWlDwX0NTO1FTBfe90x2t+tHra39pjtw9NMv1vAfO01C8acmNjFixdx8uRJAEB0dDSCgoL83KLKmamtgPnaS1SZ1NRUHDlyxPWYAyIzYOcE5sltQVSe2f5u2V66zGy/W7O1ty4I+M6JnNtCjjO4cOGCYXJbEF1mtr9btrd2menD02y/W7O1t64I+M6JmXJbEF1mtr9btrf2mO3D00y/W8B87a0rAr5zwtwWZEZm+7tle2uP2T48zfS7BczX3roi4FPaXc5tURnmtiAjMtvfLdtbe7755hvMmDGjwkcBKIqCGTNmYOfOnb5vWCXM9LsFzNfeuiLglxLXpdwWFDjM9nfL9tYesyUPNNPvFjBfe+sMnz3/2MDWrFkjEhIShM1mE4qiCEVRhM1mEwkJCSI7O9vfzSOqkNn+btne2vHcc88Ju90u7rvvPrFu3Tqxbds2sW3bNrFu3Tpx3333idDQUJGVleXvZqqY5Xd7mdnaWxcEfMxJecxtQWZktr9bttf7srOz8fTTTyM/P1+TPDAtLc2wyQPN8Lstz2ztNTN2ToiI6gh+eFJdwc4JERERGUrAr9YhIiIiY2HnhIiIiAyFnRMiIiIyFHZOiIiIyFDYOSEiQ1IUBWvXrvV3M4jID9g5ISIiIkNh54TIhIYOHYp7770X06dPR8OGDREbG4tly5ahuLgYkydPRnh4ONq2bYsPPvjAdc7u3bsxatQo1K9fH7GxsZgwYYIrJwYAbNy4EQMHDkRkZCQaNWqEP//5zzh48KDr+OHDh6EoCt5++20MGzYMYWFh6N69e5UeKCeEQOPGjfHmm2+69vXo0QNNmjRxlbds2QK73Y4LFy4gPj4eAHDTTTdBURRXmYgCAzsnRCb14osvIjo6Gtu3b8e9996Lu+++G7feeiv69++PHTt2YMSIEZgwYQIuXLiA06dP47rrrkPPnj3x1VdfYePGjSgqKlJlDi0uLkZaWhq++uor5OTkwGKx4KabboLT6VTd91//+hdmzpyJnTt3ol27dkhJSUFZWZnbtiqKgsGDByM3NxcA8Ntvv+H777/H77//jr179wIANm/ejD59+iAsLAxffvklAGDlypU4fvy4q0xEAcKPqfOJqJqGDBkiBg4c6CqXlZWJevXqiQkTJrj2HT9+XAAQeXl54rHHHhMjRoxQXePnn38WAMS+ffsqvMeJEycEALFr1y4hhBCHDh0SAMQLL7zgqrNnzx4BQHz//fe6bX7mmWdE586dhRBCrF27ViQkJIjRo0eLJUuWCCGESExMFLNnz3bVByDeeecd3esSUd3DkRMik+rWrZvrv61WKxo1aoSuXbu69l1+euovv/yCb775Bp9++inq16/v2i4/xfby1M3+/fuRkpKC1q1bo0GDBq6plIKCgkrve3la5pdfftFt75AhQ/Ddd9/hxIkT2Lx5M4YOHYqhQ4ciNzcXFy9exNatWzF06FDPfxFEVOfY/N0AIqoe+bkpiqKo9imKAgBwOp04f/48kpOT8cQTT2iuc7mDkZycjJYtW2LZsmVo2rQpnE4nunTpgtLS0krvW/4eerp27YqoqChs3rwZmzdvxuOPP464uDg88cQT+PLLL3Hx4kX079+/ij89EdVl7JwQBYBrrrkGb731FuLj42GzaV/2p06dwr59+7Bs2TIMGjQIwKUAVW9SFAWDBg3CunXrsGfPHgwcOBBhYWEoKSnBf//7X/Tu3Rv16tVz1Q8KCnI9YZeIAgundYgCwNSpU/Hrr78iJSUFX375JQ4ePIgPP/wQkydPhsPhQMOGDdGoUSM8//zzOHDgAD755BOkpaV5vR1Dhw7Fa6+9hh49eqB+/fqwWCwYPHgwXn31VQwZMkRVNz4+Hjk5OSgsLMRvv/3m9bYQkXGxc0IUAJo2bYr/+7//g8PhwIgRI9C1a1dMnz4dkZGRsFgssFgsWLNmDfLz89GlSxfMmDED//u//+v1dgwZMgQOh0MVWzJ06FDNPgD4z3/+g02bNqF58+bo2bOn19tCRMalCCGEvxtBREREdBlHToiIiMhQ2DkhIq+4nH22om3evHn+bh4RmQindYjIK44ePYrff/+9wmNRUVGIiorycYuIyKzYOSEiIiJD4bQOERERGQo7J0RERGQo7JwQERGRobBzQkRERIbCzgkREREZCjsnREREZCjsnBAREZGhsHNCREREhvL/ACI46yRSKHZJAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import itertools\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "maxx=-1+0.14\n", + "maxy=1\n", + "n_ticks = 10\n", + "\n", + "ppo_pol = pd.DataFrame(policy_2obs(ppoAgent2, maxx=maxx, maxy=maxy, obs1_name='biomass', obs2_name='mean_wt'))\n", + "ppo_pol_pivot = ppo_pol.pivot(index='biomass', columns='mean_wt', values='pol')\n", + "\n", + "ax = sns.heatmap(ppo_pol_pivot)\n", + "ax.set_yticks(list(range(0, 101, 100//n_ticks + 1))) # locations as indices, not values\n", + "ax.set_yticklabels([eval(f\"{ (i / n_ticks) * BOUND * (maxx+1)/ 2 :.2f}\") for i in range(n_ticks)])\n", + "ax.set_xticks(list(range(0, 101, 100//n_ticks + 1))) # locations as indices, not values\n", + "ax.set_xticklabels([\n", + " eval(f\"{ MINWT + (i / n_ticks) * (MAXWT-MINWT) * (maxy+1)/ 2:.2f}\") for i in range(n_ticks)\n", + "])\n", + "ax.set_title(\"PPO policy\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4b4b671d-e1f5-4980-982a-2399e83e1f47", + "metadata": {}, + "outputs": [], "source": [] } ], From f9b6d1c0e706286b4c3efd742d8b548a85accfd9 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 23 May 2024 23:14:01 +0000 Subject: [PATCH 47/64] AsmEnvEsc bugs --- src/rl4fisheries/__init__.py | 2 +- src/rl4fisheries/envs/asm_esc.py | 3 ++- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/src/rl4fisheries/__init__.py b/src/rl4fisheries/__init__.py index e3472a8..6c71b1b 100644 --- a/src/rl4fisheries/__init__.py +++ b/src/rl4fisheries/__init__.py @@ -15,7 +15,7 @@ # action is 'harvest' register(id="Asm-v0", entry_point="rl4fisheries.envs.asm:Asm") # action is 'escapement' -register(id="AsmEsc-v0", entry_point="rl4fisheries.envs.asm_esc:AsmEnvEsc") +register(id="AsmEnvEsc", entry_point="rl4fisheries.envs.asm_esc:AsmEnvEsc") # action is harvest, but observes both total count and mean biomass register(id="Asm2o-v0", entry_point="rl4fisheries.envs.asm_2o:Asm2o") # action is harvest, but observes both total count and mean biomass diff --git a/src/rl4fisheries/envs/asm_esc.py b/src/rl4fisheries/envs/asm_esc.py index 1521a6e..3617349 100644 --- a/src/rl4fisheries/envs/asm_esc.py +++ b/src/rl4fisheries/envs/asm_esc.py @@ -19,9 +19,10 @@ def step(self, action): escapement = self.escapement_units(action) current_pop = self.population_units() if current_pop <= 0: - mortality = 0 + mortality = np.float32([0]) else: mortality = (current_pop - escapement) / current_pop + mortality = np.clip(mortality, 0, np.inf) self.state, reward = self.harvest(mortality) # self.update_vuls() From ed970603a48ea9adf340dff394992691d0bb3d2f Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 24 May 2024 02:56:45 +0000 Subject: [PATCH 48/64] notebook, AsmEnvEsc.get_mortality method --- notebooks/result_plots.ipynb | 229 +++++++++++++++++++++---------- src/rl4fisheries/envs/asm_esc.py | 27 ++-- 2 files changed, 178 insertions(+), 78 deletions(-) diff --git a/notebooks/result_plots.ipynb b/notebooks/result_plots.ipynb index 792e27f..ec96ef8 100644 --- a/notebooks/result_plots.ipynb +++ b/notebooks/result_plots.ipynb @@ -13,13 +13,13 @@ "\n", "from plotnine import ggplot, aes, geom_density, geom_line, geom_point\n", "\n", - "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries import AsmEnv, AsmEnvEsc, Msy, ConstEsc, CautionaryRule\n", "from rl4fisheries.envs.asm_fns import get_r_devs, observe_total" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 4, "id": "2119a088-27b1-490f-9114-23c4e3f69ca6", "metadata": {}, "outputs": [], @@ -106,7 +106,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "9fc5702e-71b1-4af9-abd3-20e0ed6d0915", "metadata": {}, "outputs": [], @@ -124,7 +124,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "81938413-d860-4195-b5dc-12bc110e39ba", "metadata": {}, "outputs": [], @@ -132,7 +132,8 @@ "from stable_baselines3 import PPO\n", "\n", "ppoAgent1 = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10.zip', device='cpu')\n", - "ppoAgent2 = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10-run2.zip', device='cpu')" + "ppoAgent2 = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10-run2.zip', device='cpu')\n", + "ppoAgentEsc = PPO.load('../saved_agents/results/PPO-AsmEnvEsc-results-trophy-nage-10.zip', device='cpu')" ] }, { @@ -153,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 7, "id": "99ed7e7d-8a48-4a4f-89eb-5e01718a8fec", "metadata": {}, "outputs": [], @@ -185,7 +186,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 8, "id": "52f366c2-1879-4954-9800-ec97f85f364e", "metadata": {}, "outputs": [ @@ -193,15 +194,20 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-23 15:59:12,105\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-23 15:59:19,536\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-23 15:59:26,869\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-23 15:59:34,060\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-23 15:59:47,739\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 02:11:00,452\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-24 02:11:14,730\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-24 02:11:22,206\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-24 02:11:29,520\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-24 02:11:37,095\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-24 02:11:51,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], "source": [ + "ppoAgentEsc_rews = eval_pol(\n", + " policy=ppoAgentEsc, env_cls=AsmEnvEsc, config=CONFIG3\n", + ")\n", + "\n", "cr3_rews = eval_pol(\n", " policy=cr3, env_cls=AsmEnv, config=CONFIG3\n", ")\n", @@ -221,7 +227,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 9, "id": "7b5b2627-ca46-419c-86a2-60d8911dee99", "metadata": {}, "outputs": [], @@ -251,28 +257,34 @@ " 'agent': 'ppo_nr2',\n", "})\n", "\n", + "ppoEsc_rews_df = pd.DataFrame({\n", + " 'rew': ppoAgentEsc_rews,\n", + " 'agent': 'ppo_esc',\n", + "})\n", + "\n", "rews_df_case3 = pd.concat(\n", - " [cr_rews_df, esc_rews_df, msy_rews_df, ppo1_rews_df, ppo2_rews_df]\n", + " [cr_rews_df, esc_rews_df, msy_rews_df, ppo1_rews_df, ppo2_rews_df, ppoEsc_rews_df]\n", ")" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 10, "id": "44484162-7774-425d-9447-82f178faf9b2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(31.619016124666274,\n", - " 13.479394979731,\n", - " 25.510153709904834,\n", - " 32.45709450494806,\n", - " 51.48817420739415)" + "(32.120517542052035,\n", + " 13.716304965534043,\n", + " 23.867732405070303,\n", + " 38.70609230040449,\n", + " 51.815898659947536,\n", + " 56.49522702267767)" ] }, - "execution_count": 31, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -285,18 +297,19 @@ " np.mean(msy_rews_df.rew),\n", " np.mean(ppo1_rews_df.rew),\n", " np.mean(ppo2_rews_df.rew),\n", + " np.mean(ppoEsc_rews_df.rew),\n", ")" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 11, "id": "495142e1-2607-4168-986e-aee3163f96ad", "metadata": {}, "outputs": [ { "data": { - "image/png": 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k3UcvNrbutoi33HKLLrnkEj377LPHnDc3N9e3L9+kSZO0ePFieTweeTweLV68WM8//7wkbwDZtWvXOq/1H+rx3HPP6bPPPlN5ebkkqaSkRO+9957+97//SZIGDBigXr16BejdQCT45z//KUmKi4vV9XeMtbSWbj2P7LGxadMmCysBAAAAAAAtEfVDQCTJbrfrwQcf1AMPPKBt27bp7rvvVmJioiorK33Tli666CKdffbZzT73HXfcoT179mjjxo3685//rLi4OElS9eEBDf369dPtt99+zOsSExP1u9/9To899pjKysr0/PPP6/nnn1diYqIvCJSkTp066b777mvJh40IlZ+fr2nTpkmSzr9sqDKzky2tJzHJoZyOqdqXV0QHIAAAAAAAEahNBICS1LVrV02aNEnvvfeevvnmG+Xn5yspKUk9evTQ+PHjNWLEiBadNyEhQU888YSmT5+uefPmKS8vT5LUs2dPjRs3TuPHjz+mq9A0cOBA/eMf/9CMGTO0fPly7dmzR5WVlUpOTlaXLl00cuRInX/++YqPt2bvN1jjgw8+UE1NjSTpx9eeYnE1Xt17ZmtfXhEdgAAAAAAARCDDY24yh6iWn5/foteZo+lra2sZTR8i5513npYvX64efdrptU8n+qZYH49hGLLb4+RyVSvQt/X/+8N0vfu/JcrOzta6desCeu62insrcthsNqWnp+vgwYNMwg5z3FeRhXsrcnBvRRburcjBvdUyWVlZxz8IwDHaxB6AQKTYu3evb1r1ORcPbnL4F2wduqRL8k6tLisrs7gaAAAAAADQHASAQBj59NNPfY/HnNPfwkrq6tQ13fd4586dFlYCAAAAAACaiwAQCCOzZ8+W5A3cevRpZ3E1R3TsciQA3LFjh4WVAAAAAACA5iIABMKEy+XSwoULJUkjxvQOm+W/ktSx85EAcPv27RZWAgAAAAAAmosAEAgT3333nW9/vZNH97C4mrqSnfFypiZIIgAEAAAAACDSEAACYWLBggWSvNN8TxyRa3E1xzIHgbAEGAAAAACAyEIACISJb7/9VpLUo087paYlWlzNsTp2TpNEAAgAAAAAQKQhAATCgMfj0XfffSdJGnhCZ4urqZ85CGT79u3yeDwWVwMAAAAAAJqKABAIA7t27dKBAwckSQOGhmkA2DVDklRaWqqDBw9aXA0AAAAAAGgqAkAgDCxfvtz3eODQThZW0jCzA1BiGTAAAAAAAJGEABAIA+byX0e8Xbl92llcTf3MPQAlJgEDAAAAABBJCACBMGB2APYb1FGxsTaLq6lfewJAAAAAAAAiEgEgYLGamhqtXLlSkjQgTJf/SpLDYVdWuxRJ0u7duy2uBgAAAAAANBUBIGCxjRs3qry8XJI0IEwnAJvatXdKkvbs2WNxJQAAAAAAoKkIAAGLbdiwwfe4T//2FlZyfNkdvAFgXl6exZUAAAAAAICmIgAELPb9999LkuxxNnXqlmFxNY1r1z5VEgEgAAAAAACRhAAQsJgZAHbNzQrbASAmcwnwgQMHVF1dbXE1AAAAAACgKQgAAYuZAWCPPu0sruT42h1eAixJe/futbASAAAAAADQVASAgIWqqqq0detWSVJur2yLqzm+7JwjASDLgAEAAAAAiAwEgICFtmzZotraWklS996R0AGY6nvMJGAAAAAAACIDASBgIXP5ryTl9o6ADsD2Kb7HdAACAAAAABAZCAABC23cuFGSFGu3qUu3TIurOT6Hw660jERJdAACAAAAABApCAABC23YsEGS1DU3U7H28J4AbDInAdMBCAAAAABAZCAABCxkdgBGwgAQU3Z77z6AdAACAAAAABAZCAABi9TW1vomAHfrGTkBYLsOdAACAAAAABBJCAABi+zZs0cul0uS1KlbhsXVNJ25BHjfvn2qqamxuBoAAAAAAHA8BICARbZt2+Z73KlLunWFNFO7Dt4lwLW1tTpw4IDF1QAAAAAAgOMhAAQsUicAjMAOQIllwAAAAAAARAICQMAiZgDocMQqMzvZ2mKaIatdiu/x/v37LawEAAAAAAA0BQEgYJHt27dLkjp2TVdMTOTcihl+YSUBIAAAAAAA4S9yUgcgypgdgJ26Rs7yX0lypibIHmeT5B0EAgAAAAAAwhsBIGARswMw0gJAwzCUmeXtAqQDEAAAAACA8EcACFigqKhIBw8elBR5AaAkZWR79wEkAAQAAAAAIPwRAAIWqDMBuGu6dYW0kDm0hAAQAAAAAIDwRwAIWKBOANgt8joAzQCQPQABAAAAAAh/BICABcz9/wzDUIfOadYW0wL+HYAej8fiagAAAAAAQGMIAAELmAFgVk6KHA67xdU0X2Y77x6A1dXVKioqsrgaAAAAAADQGAJAwAK7du2SJLXvlGZtIS1kdgBK7AMIAAAAAEC4IwAELJCXlydJyungtLiSlsk8PAVYYh9AAAAAAADCHQEgYIHdu3dLknI6pFpcSctk0AEIAAAAAEDEIAAEQqykpEQlJSWSpHYRGgCyBBgAAAAAgMhBAAiEmNn9J0ntO0VmAOhw2JXijJfEEmAAAAAAAMIdASAQYv4BYKQuAZaOLAOmAxAAAAAAgPBGAAiEmH8AGKlLgKUjg0AIAAEAAAAACG8EgECImQFgXFys0jOTLK6m5bLa0QEIAAAAAEAkIAAEQswMANt1cMowDIurabmMLAJAAAAAAAAiAQEgEGJ5eXmSInv5ryRf92JhYaFqa2strgYAAAAAADSEABAIMbMDsH3HSA8AvR2AHo9HhYWFFlcDAAAAAAAaQgAIhJDH44m6DkBJys/Pt7ASAAAAAADQGAJAIIQKCwtVWVkpScqJ+A7AIwFgQUGBhZUAAAAAAIDGEAACIWQu/5WknCjqADxw4ICFlQAAAAAAgMYQAAIhZC7/lbxTgCMZS4ABAAAAAIgMBIBACO3bt8/3ODsnsgPAhMQ4ORyxklgCDAAAAABAOCMABEJo7969kiR7nE3OtASLq2kdwzB8XYB0AAIAAAAAEL4IAIEQMjsAM7NTZBiGxdW0XnpWsiQCQAAAAAAAwhkBIBBCZgdgdk6KxZUERlpGoiQCQAAAAAAAwhkBIBBCvg7AdtERAKZn0gEIAAAAAEC4IwAEQsgMALOyoyUA9O4ByBAQAAAAAADCFwEgECK1tbU6cOCAJCkrSpYAp2d4A8BDhw6purra4moAAAAAAEB9CACBEDlw4IDcbrckKStalgBnJfkeFxYWWlgJAAAAAABoCAEgECLm8l8pigLAjCMBIPsAAgAAAAAQnggAgRDxDwCjZwgIASAAAAAAAOGOABAIkb179/oeZ0fLHoB+ASCDQAAAAAAACE8EgECImB2AsXabUtMTLa4mMNL8AkBzwAkAAAAAAAgvBIBAiJgBYFZ2sgzDsLiawIiPtysxKU4SS4ABAAAAAAhXBIBAiJhLgKNl/z9T2uFBICwBBgAAAAAgPBEAAiHi6wCMkv3/TGmHlzMfPHjQ4koAAAAAAEB9CACBEDE7ALOyoysAdB4OAOkABAAAAAAgPBEAAiHgdrt9QzKibQlwalqCJDoAAQAAAAAIVwSAQAgUFhaqtrZWkpSZnWxxNYFl7gFYWFhocSUAAAAAAKA+BIBACPhPyE3PTLKwksDz7wD0eDwWVwMAAAAAAI5GAAiEgLn8V5IysqKrA9DcA7CmpkYlJSUWVwMAAAAAAI5GAAiEQJ0AMNqWAB8OACWWAQMAAAAAEI4IAIEQ2L9/v+9xtHUApvoFgAwCAQAAAAAg/BAAAiFgdgAmJjsUH2+3uJrA8g8ACwoKLKwEAAAAAADUhwAQCAFzCEhGlA0AkeouAaYDEAAAAACA8EMACISA2QGYHmXLf6UjQ0Ak9gAEAAAAACAcEQACIWAGgBlZ0dcBGB9vl+PwsmYCQAAAAAAAwg8BIBACRwLA6OsAlKTU9ARJLAEGAAAAACAcEQACQebxeI7sARilAaC5DyAdgAAAAAAAhB8CQCDISkpKVFVVJSl6A0BzH0A6AAEAAAAACD8EgECQmct/JSk9CqcAS1JqmjcALCgosLgSAAAAAABwNAJAIMj279/vexytHYBpdAACAAAAABC2Yq0uAKFhs9nC4hxtkX9XXGZ2sgzDCMp1zPMG6/yNSc04EgDyddJ8vGfhzfz88HmKLHy+wh/3VmTi8xX+uLciE58vAMFGANhGpKent+r1Nput1edoq8rLy32PczpkyG6PC+r1YmPtQT1/fTIynZKkiooKORwOJSYmhryGSMW9FTmcTqfVJaCJuK8iC/dW5ODeiizcW5GDewtAKBAAthEtXZrpdDpls9lUW1ur4uLiAFfVNmzbtk2S5HDEKs5hyOWqDsp1DMNQbKxdNTUueTyeoFyjISmpR0LNLVu2qHPnziG9fiTi3oocNptNTqdTxcXFqq2ttbocNIL7KrJwb0UO7q3Iwr0VObi3WoawFGgZAsA2IhDf/PkLRMuYewCaA0CCHc55PJ6QB4DOtCMdf/n5+erQoUNIrx/puLciQ21tLZ+rCMLnKnJwb0UWPleRg3srsvC5AhBsDAEBgiw/P19S9A4AkaTUtATf48LCQgsrAQAAAAAARyMABILMDADTDncARqO0jCMfGwEgAAAAAADhhQAQCDIzEPMPyaKNfwdgS/ebBAAAAAAAwUEACARZQUGBJCktPXon4yYmO2SL9f5xQgAIAAAAAEB4IQAEgqi2ttYXiKVlRm8AaBiGUg8PAjEDTwAAAAAAEB4IAIEgOnjwoG8ib1p69C4BlqS0DG8ASAcgAAAAAADhhQAQCCL/bjgzIItWZgcgQ0AAAAAAAAgvBIBAENUNAKO7A9CZ7h0EQgAIAAAAAEB4IQAEgqgtBYDmEmeWAAMAAAAAEF4IAIEg8u+Gi/olwHQAAgAAAAAQlggAgSDKz8+XJNlsMUpxxltcTXCZewCWlJSourra4moAAAAAAICJABAIIrMbLjU9UYZhWFxNcKX6dTiyDBgAAAAAgPBBAAgEkbkHYHpmdC//lSRnaoLv8aFDh6wrBAAAAAAA1EEACASRGQCmpkf3ABBJcqYdCTkJAAEAAAAACB8EgEAQ+ToAo3wAiCQ5U4/scUgACAAAAABA+CAABILI1wGYQQcgAAAAAACwBgEgECQej8c3BKQtdACm+HUAMgQEAAAAAIDwQQAIBElZWZkqKyslSWltoAPQ4bDLEW+XJBUVFVlcDQAAAAAAMBEAAkFidv9JUlob6ACUjuwDSAcgAAAAAADhgwAQCBJz/z+pbXQASpIzLUESHYAAAAAAAIQTAkAgSOoEgOltowMwxekNAOkABAAAAAAgfBAAAkFSJwDMpAMQAAAAAABYgwAQCBL/PQBT09pIB2AqHYAAAAAAAIQbAkAgSPLz8yVJSSkOxTliLa4mNJypdAACAAAAABBuCACBIDE7ANvK/n9S3Q5Aj8djcTUAAAAAAEAiAASCxtwDsK1MAJaO7AFYW1ursrIyi6sBAAAAAAASASAQNOYS4LSMttMBaC4BltgHEAAAAACAcEEACASJbwlwW+oA9AsADx06ZF0hAAAAAADAhwAQCBLfEuA2uAegRAAIAAAAAEC4IAAEgqCmpsYXgLWpDsA0lgADAAAAABBuCACBIDCX/0ptdw/AoqIiCysBAAAAAAAmAkAgCOoGgG2nAzDZGe97TAcgAAAAAADhgQAQCAJz/z9JSm1DewDabDFKTvGGgOwBCAAAAABAeCAABILAv/st1W9fvLYgJZUAEAAAAACAcEIACARBnQCwDXUASpIzzfvxEgACAAAAABAeCACBIPAPAFNS6QAEAAAAAADWIQAEgsAMv1Kc8bLZ2tZtlno48CQABAAAAAAgPLStZAIIEXMKcFtb/isd6XgkAAQAAAAAIDwQAAJBYC4BNvfDa0ucaQSAAAAAAACEEwJAIAiOBIBta/8/SUpxej/mkpIS1dTUWFwNAAAAAAAgAASCwAwAU9tgAOgfehYVFVlYCQAAAAAAkAgAgaAw9wBsi0uA/aceswwYAAAAAADrEQACAebxeHzBV2p62+sA9O96JAAEAAAAAMB6BIBAgJWVlam6ulqSlNrGOwDNpdAAAAAAAMA6BIBAgPmHXm1xCIgzlT0AAQAAAAAIJwSAQID5B4B0ANIBCAAAAACA1QgAgQCrEwCmt70AMDEpTrZY7x8tdAACAAAAAGA9AkAgwMwJwFLbXAJsGIZvGTAdgAAAAAAAWI8AEAgw/8m3bXEJsCQCQAAAAAAAwggBIBBgZgegzRajpBSHxdVYw9wHsLi42OJKAAAAAAAAASAQYGYHoDMtQYZhWFuMRZKd8ZLYAxAAAAAAgHBAAAgEmNkB2Bb3/zM5UwkAAQAAAAAIFwSAQICZ+9452+j+f5KU7PSGnwSAAAAAAABYjwAQCDBzCXBqG+4ATGEJMAAAAAAAYYMAEAgwcwlwanrb7QBMOdwBWFpaqpqaGourAQAAAACgbSMABALMtwQ4te12AJpDQCQmAQMAAAAAYDUCQCCA3G73kSXAbboD8EgAyDJgAAAAAACsRQAIBFBxcbHcbrektj0FOMWv+5EAEAAAAAAAaxEAAgFk7v8nSalteAowHYAAAAAAAIQPAkAggMzlv1LbXgKcTAAIAAAAAEDYIAAEAsi/A7AtLwF2sgQYAAAAAICwQQAIBJA5AVhq20uAk1IcvscEgAAAAAAAWIsAEAigOgFgetvtAIyNtSkxKU4SASAAAAAAAFYjAAQCyAwA4+Ji5Yi3W1yNtcxJwASAAAAAAABYiwAQCCAzAExNT5BhGBZXY63kFO8gEAJAAAAAAACsRQAIBJAZALblASCmFCcBIAAAAAAA4YAAEAggcwqwsw0PADGxBBgAAAAAgPBAAAgE0KFDhyRJqekEgHQAAgAAAAAQHggAgQDyLQFOZQlwMgEgAAAAAABhgQAQCCBzCTAdgEeWABcXF1tcCQAAAAAAbRsBIBAgLpdLJSUlkqRU9gD0LQGurKxUZWWlxdUAAAAAANB2EQACAWLu/ycxBVg6sgRYYhkwAAAAAABWIgAEAsTc/0+SUtMJAJ3OI+8By4ABAAAAALAOASAQIHUCQJYA1+kA9O+OBAAAAAAAoUUACASIfwDIEuAjewBKLAEGAAAAAMBKBIBAgJgTgCWmAEtSMkuAAQAAAAAICwSAQIDUGQKSSgegM5UlwAAAAAAAhAMCQCBAzA7AxKQ42eNiLa7GeglJcYqJMSSxBBgAAAAAACsRAAIBYna50f3nFRMTo+QUbxcgS4ABAAAAALAOASAQIOYQEAaAHJFyeBkwS4ABAAAAALAOASAQIOYyV2caA0BM5iAQlgADAAAAAGAdAkAgQMwutxRnfOMHtiHme8ESYAAAAAAArEMACASILwBkD0AfMwBkCTAAAAAAANZpU6NKi4qK9O677+qbb75RQUGBHA6HevbsqQsvvFAjRoxo8Xlramo0ffp0zZs3T3l5eZKkTp06aezYsRo/frxiY4//Nv/www/65JNPtGrVKhUUFMhutysjI0N9+/bVmWeeqUGDBrW4PoSGbwgIewD6sAQYAAAAAADrtZkAcMeOHXrggQd8QURCQoLKysq0YsUKrVixQhdffLF+/vOfN/u8FRUVeuihh7Rx40ZJUlxcnCRp8+bN2rx5sxYuXKhHH31U8fENLwt9/fXX9fbbb8vtdkuSEhMTVV1drZ07d2rnzp0yDIMAMMzV1tb6lrkyBfgIlgADAAAAAGC9NhEAulwuPfbYYyoqKlK3bt3061//Wrm5uaqqqtK0adP02muv6eOPP1Zubq7OPvvsZp37hRde0MaNG5WUlKS77rrL10m4ePFi/f3vf9eGDRv04osv6le/+lW9r3/zzTf15ptvym636+qrr9Y555yjjIwMeTweHTx4UCtWrFBNTU2r3wMEV3FxsTwejySWAPszpwAXFRXJ4/HIMAyLKwIAAAAAoO1pE3sAzpo1S3v37pXD4dAf/vAH5ebmSpIcDoeuvPJKXXDBBZKkqVOnNits27p1q7766itJ0p133qmRI0fKMAwZhqGRI0dq4sSJkqS5c+dq+/btx7x+8+bNevPNN2UYhu6//35dddVVysjIkCQZhqGMjAydeeaZOvfcc1v18SP4/Pe4owPwiJTDS4Bra2tVVlZmcTUAAAAAALRNbSIAnDt3riRpzJgxys7OPub5yy+/XIZhqLCwUKtXr27yeefNmyePx6MOHTpo5MiRxzw/atQodejQQR6PR/PmzTvm+XfffVdut1ujRo3SySef3PQPCGHHPwCkA/CIZL+JyOwDCAAAAACANaI+AKyoqNCmTZskSSeeeGK9x2RnZ6tz586SpJUrVzb53KtWrZIkDRs2rN6ljYZhaNiwYXWONZWXl2vJkiWSpLFjxzb5mghPdTsAG97vsa3x74ZkEjAAAAAAANaI+j0Ad+3a5dubrVu3bg0e161bN9/QjabweDzatWvXcc/btWtXSTrmvJs2bVJtba0kqWfPnlq+fLk++OADbd68WS6XSzk5ORo+fLguu+wyOZ3OJtUE69QJANMSrSskzNABCAAAAACA9aI+ACwsLPQ9NvfXq4/53MGDB5t03oqKClVWVjb5vBUVFaqoqFBCgrcjas+ePb5jvvzyS02dOlWSdwKwJF8YOXfuXD366KPq0qVLk+qCNeouAaYD0JTiFwAyCRgAAAAAAGtEfQBohnSSd+hHQ8znKioqmnRe/+Oacl7zNWYAWFpa6vv9119/XX379tUvf/lLde/eXbW1tfr22281adIkFRQU6C9/+YsmTZokm83W4HWmTp2q119/vcHnr776al1zzTVN+tj8xcTE+P4/PT292a9vK6qqqiR5l32nZaT43jcrxNrtll37aOlZR7pXXS4XX0N+uLcih7nFQ2pqqq+jHOGJ+yqycG9FDu6tyMK9FTm4twCEUtQHgOHK7Xb7HsfHx+uhhx7yLfW12WwaPny47rzzTj322GPatWuXvv76a5122mkNnq+srEz79+9v8Pny8vJGA8TjMQyjVa+PdubyVmdqgmwx1r5Pho7dj9IqTueR5dDFxcV8DdWDeytyWBnso3m4ryIL91bk4N6KLNxbkYN7C0AoRH0AGB9/ZAliVVWVb4nt0cwOLrND73j8jzNf29h5j36Nfx3jxo2rd5+/4cOHq2PHjsrLy9PKlSsbDQCTkpLUrl27Bp9PTEz07TnYHDExMTIMQx6Pp05oiboKCgokSSlpCfLIup+0GjIsvf7R4uJtssfZ5KquVWFhYYu+BqMV91bkMAxDMTExcrvddFKEOe6ryMK9FTm4tyIL91bk4N5qGcJSoGWiPgD035+vsLCwwQDQ3Cuwqa3XCQkJSkhIUEVFRZ19Bhs6r3l8fXWZE4jr07lzZ+Xl5Sk/P7/ReiZMmKAJEyY0+Hx+fn6T9zf0l56eLpvNJrfb3aLXtxVm92WKM16u6mpLajAMQ3Z7nGpcrrD6y16KM0GF+aXau3cvX0N+uLcih81mU3p6uoqKigixwxz3VWTh3ooc3FuRhXsrcnBvtUxWVpbVJQARKer7wjt37uzbB2PHjh0NHmc+19RhG4Zh+IK7lpzXnA7cVObHgPBkDgFxpjatg7QtMQeBMAUYAAAAAABrRH0AmJCQoN69e0uSli9fXu8x+fn52rlzpyRp6NChTT73kCFDJEnfffddg8esWLGizrGmTp06KTs7W5K0a9euBl9vPtfY8l5YzwwAmQB8rOTDASBTgAEAAAAAsEbUB4CSd489Sfrqq6904MCBY55///335fF4lJGRocGDBzf5vGPGjJFhGMrLy9PXX399zPOLFi1SXl6eDMPw1WAyDENnnHGGJGnu3Ln1hiNLlixRXl6eJOnkk09ucl0IvSMBIB2ARzPfE/M9AgAAAAAAodUmAsDzzjtP7du3V2Vlpf70pz9p69atkrwDOt59913NmDFDkncfvdjYutsi3nLLLbrkkkv07LPPHnPe3NxcjRkzRpI0adIkLV68WB6PRx6PR4sXL9bzzz8vyRtA1rfk97LLLlN6errKy8v12GOPafv27ZK8E4KXLl3qe32/fv100kknBebNQFCwBLhhKXQAAgAAAABgqagfAiJJdrtdDz74oB544AFt27ZNd999txITE1VZWembtnTRRRfp7LPPbva577jjDu3Zs0cbN27Un//8Z8XFxUmSqg8PgujXr59uv/32el+blJSkhx56SA8//LA2bNigO++8U0lJSXK5XL7Xd+vWTb/97W/ZAzCMuVwulZWVSSIArE8yewACAAAAAGCpNhEASt6hG5MmTdJ7772nb775Rvn5+UpKSlKPHj00fvx4jRgxokXnTUhI0BNPPKHp06dr3rx5viW7PXv21Lhx4zR+/Phjugr99erVS88//7zef/99LVu2TAcOHJDNZlPv3r112mmn6cILL5TD4WhRbQgN/6WtLAE+lpMlwAAAAAAAWKrNBICSlJaWpptvvlk333xzk1/zn//857jHxMbG6tJLL9Wll17aorrS09ObXRfCh39nmzONAPBoySneDsDS0lLV1NQ0GogDAAAAAIDAaxN7AALBdPDgQd9jOgCPZe4BKLEPIAAAAAAAViAABFrJf2krewAeyz8UJQAEAAAAACD0CACBVqqzBJgA8BjJfh2ADAIBAAAAACD0CACBVqq7BDi+kSPbphQCQAAAAAAALEUACLSSGWrF2m1KSIyzuJrwk+w80hVJAAgAAAAAQOgRAAKtZO4BmOKMl2EY1hYThugABAAAAADAWgSAQCuZS4DZ/69+ySkO32OGgAAAAAAAEHoEgEArmV1tzjQCwPrY42IVn2CXRAcgAAAAAABWIAAEWsm3BJgOwAaZ7w0BIAAAAAAAoUcACLSS/x6AqJ/53rAEGAAAAACA0CMABFrJDACdaYnWFhLGkg8HgOZ7BQAAAAAAQocAEGgl3x6AqXQANsTsAGQJMAAAAAAAoUcACLRCRUWFKisrJbEHYGOSU1gCDAAAAACAVQgAgVbw72hzEgA2KMXJEBAAAAAAAKxCAAi0gv+ednQANiwllSXAAAAAAABYhQAQaIWDBw/6HhMANiz5cAdgeXm5XC6XxdUAAAAAANC2EAACreDf0ZaaRgDYEHMIiEQXIAAAAAAAoUYACLQCS4CbJpkAEAAAAAAAyxAAAq1QNwCMb/jANs6/A5BJwAAAAAAAhBYBINAKZgDoiLfL4bBbW0wYYwkwAAAAAADWIQAEWsEMAJ10/zXKHAIiEQACAAAAABBqBIBAK/gCQAaANMp/eTRLgAEAAAAACC0CQKAVzAAwxUkA2JikZIfvMR2AbY/H41Ftba3VZQAAAABAm0UACLSCGWYxAbhxsbE2JR4OAf0HpyB6uVwuvfLKKzr33HPVsWNHdezYUaNHj9Zf//pXvgYAAAAAIMQIAIFWOHjwoCSWADeFOQiEJcDRb/v27TrvvPN033336bvvvlNNTY3cbrc2btyop556SiNHjtScOXOsLhMAAAAA2gwCQKAV6ABsuuQUbwDIEuDotnnzZl1wwQVavXq1JCmzfa7GXHKHzrz8V+ra52RJUn5+vq699lp98MEHVpYKAAAAAG1GrNUFAJHK4/EcGQLiZArw8ZgdgASA0auoqEhXXXWVDhw4IEkad+ldGnfpnbLZvN9qzrj0Lq1bNkvv/eteVVeW6dZbb5UkXXbZZZbVDAAAAABtAR2AQAuVlZWppqZGkuRMS7S4mvBndkmyBDg6eTwe/frXv9aOHTskSedf84DOuvxXvvDPNODk83TDb/+n+ESnPB6P7rnnHm3YsMGKkgEAAACgzSAABFrIf5BBSiodgMdDB2B0e/PNN/XRRx9JkgadepFGnX9zg8d26TVM1/56smJibCovL9eNN96o0tLSUJUKAAAAAG0OASDQQnUDQPYAPJ7kwwEgE2CjT2lpqf70pz9JktKyOumSGx+XYRiNvqZ73+E696e/k+TdN/Cpp54Kep0AAAAA0FYRAAIt5B9kOQkAj4spwNFr0qRJvn3/xv/sj0pIcjbpdaPOv1m9Bp8uSfr3v//tGxwCAAAAAAgsAkCghQgAmyfZ6X2PKisrVVlZaXE1CJS9e/fqxRdflCR173eq+g47q8mvNQxDF13/qGLtcaqtrdVvfvMbeTyeYJUKAAAAIAL88Y9/1B//+EdNmTLF6lKiCgEg0EIHDx70PWYJ8PGl+E1KpgswevzrX/9SRUWFJOm8q+8/7tLfo2XmdNeYi38pSVq2bJlmzpwZ8BoBAAAARI5HHnlEjzzyCAFggBEAAi3kP8yCISDHl0wAGHVKS0v16quvSpJ6Dxmrzj2Gtug8oy/8uZJTsyVJTzzxhGprawNWIwAAAACAABBoMXMJcGKyQ7GxNmuLiQD+XZJMAo4Ob775pi/MHXX+TS0+T5wjQeN+NFGStGHDBr3//vsBqQ8AAAAA4EUACLSQGQA6nXT/NYX/EmACwMjndrv173//W5LUrlMf9Rx0eqvOd9IZP1VaVidJ0rPPPiu3293qGgEAAAAAXgSAQAv5AsA09v9rimQCwKjy9ddfa+vWrZKkkefd0Oy9/44WGxun08bfKknauHGj5syZ0+oaAQAAgHBRWVmpadOm6a677tKoUaOUnZ0tu92ulJQU9e7dWz/72c80e/bsJp3L5XLp+eef1+jRo5WRkaHExET16dNHEydO1Pfffy/JO0jDMAwZhqG5c+cet7Z//etfuuiii9SlSxfFx8crNTVVgwYN0l133aWNGzc2+vr6rvXtt9/qxhtvVI8ePRQfH6/MzEydccYZmjJlSoM/7DfPYZo3b57v9/x/sTdgy8RaXQAQqcwQiwEgTUMHYHR56623JEn2uHgNHnFxQM457PQr9MV7z6i89KBeeOEFnXPOOQE5LwAAAGC1AQMG+H6A7q+0tFSbN2/W5s2bNXXqVP3oRz/S1KlTlZycXO959u7dq/PPP18rV66s8/ubNm3Spk2b9PLLL+vll19ucl3z5s3Ttddeq927d9f5/aqqKq1du1Zr167VCy+8oD/96U+6//77m3TOJ598Ug888ECdvb2rqqo0d+5czZ07V9OmTdM777yj2FgiqVDi3QZayJwCTADYNEnJDhmGIY/HQwAY4crLy/XRRx9JkvqffJ4cCfX/5aS54hwJOuWsazVv2vNasGCBVq5cqaFDWzZYBAAAAAgn5eXlSktL05lnnqlhw4apW7duSkxMVHFxsVatWqW33npLe/bs0bRp03TTTTfp7bffPuYclZWVOuecc7RmzRpJUlZWlm6++WYNGTJE1dXVmj9/vv73v//puuuu0/nnn3/cmj755BP96Ec/ksvlUkxMjM4//3ydffbZ6tSpkyorK7Vs2TK9+uqrKioq0u9//3tJOm4IOHnyZL3++uvKzs7WDTfcoCFDhigmJkaLFi3Sf/7zH1VVVenDDz/UU0895Tun6YMPPpAkXXbZZZKkgQMH6rHHHjvmGieeeOJxPzYciwAQaCEzxHISADZJTEyMkpIdKi2pJACMcDNnzlRZWZkkadhpPw7ouUecc50WzPi3amuqNWXKFD3zzDMBPT8AAABghZdffllnn3227HZ7vc8//vjjuvbaa/Xhhx/qnXfe0YIFC3TaaafVOeYvf/mLL/wbNGiQ5syZo3bt2vmev+GGG3T77bfr7LPP1rRp0xqtZ8+ePZowYYJcLpfatWunadOmacSIEXWOue666/Tb3/5W559/vtasWaOHHnpIl112mfr169fgeV9//XWNHTtW06ZNU2pqqu/3r7nmGv3kJz/RWWedpdraWj3zzDO67777FBcX5zvm0ksvrXOurKysY34PLccegEALmXsA0gHYdCmp3mXA5uRYRKZ33nlHkpSSnqMeA0cH9NzJqdkacIr3p5Xvv/++SkpKAnp+AAAAwAoXXHBBg+GfJCUmJuqVV15RUlKSJOmVV16p83x1dbVeeOEFSVJsbKzeeuutOuGf6eSTT9bf/va349bz17/+VYWFhZKkd99995jwz9SpUye98847stlsqq2t1XPPPdfoeTMyMvTee+/VCf9MY8eO1RVXXCFJys/P19KlS49bJwKHABBoAbfb7etiS2UISJOZ+wDSARi5iouLNX/+fEnS4FMvUkyMLeDXOOWMqyV5l0m8++67AT8/AAAAEI6cTqcGDx4sSVq8eHGd5xYsWKD8/HxJ0rnnnqsBAwY0eJ7rrrtOmZmZDT7v8Xj06quvSpJGjhyp008/vdG6+vXrp+HDh0uSZs2a1eixx7u2/z7fZjcjQoMlwEALFBcXy+PxSKIDsDmSnd73yuyeROT5/PPP5XK5JEn9Tz43KNfo3u9UZXXoofw9P+iVV17RDTe0fsowAAAAYLWDBw/qtdde06effqo1a9aooKBAZWVlvn9b+tu1a1ed//bvljvjjDMavY7dbtfo0aN9+3Yfbd26dSooKJAkpaen68MPPzxu7Tab9wf/W7duVWVlpeLj4+s9buTIkY2ep3Pnzr7H5r76CA0CQKAF/AMs/+m2aJz5XrEEOHLNmDFDkpSUkqmuvU8KyjUMw9DJZ1ytT19/XGvXrtXq1as1ZMiQoFwLAAAACIVp06bp5ptv9gVvx3P0v5ny8vJ8j3v27Hnc1/fo0aPB57Zt2+Z7PHPmTM2cObNJNZkKCwvVsWPHep/Lyspq9LUOh8P3uLKyslnXResQAAIt4B8AOtMSrSskwiSzBDiiVVZWas6cOZKkfiedHZTlv6aho36kz958Qm53rd577z0CQAAAAESsr7/+WldccYVqamokSUOGDNHZZ5+tXr16KT09XQ6Hw7fi5cEHH9TatWvldrvrnMMcwid59ws8HnMvwfq0dkVWdXV1g8/FxLDTXLgiAARaoE4AmEoHYFPRARjZvvrqK99fPAacdF5Qr5Wcmq2eg07TplXz9P777+sPf/iDb9kBAAAAEEn+8Ic/+MK/f/zjH7rjjjsaPPbxxx+v9/f9A73y8vLjXtM/MDxacnKy7/Gvf/3rJg0NQeQjmgVaoM4SYPYAbDL/DsD69rlAePv8888lSXGORPUYOCro1xsy6keSpL1792rRokVBvx4AAAAQaC6XS3PnzpUknXTSSY2Gf1Ld5bn+/Jfcbtmy5bjX/eGHHxp8zn8fvp07dx73XIgOBIBAC9RdAkwA2FQph4eAVFdXs99DBPryyy8lSbn9RyjW7jjO0a3X/6RzZY/zfs0wDRgAAACRKD8/39f916tXr0aPXbp0qW/S79FOOeUU32Pz7+UNcblcWrhwYYPPn3DCCUpNTfWdq6qqqtHzhZq5HJqmkcAiAARawAwADcNQUnLwg5Bo4T8whX0AI8vWrVt9P43sNWRMSK7piE9Sv5POkSR9/PHHhMYAAACIOP5Ldzdv3tzosQ8//HCDz40ePVqZmZmSpM8++0zr1q1r8NhXX3210WEjNptN1157rSRvQPn00083WleomUuUG1vGjOYjAARawAyvUpzxbHLaDMkEgBHL/6eMvQeHJgCUvMNAJKmkpESzZ88O2XUBAACAQHA6nerTp48k6dtvv613ZUttba1+9atf6ZNPPmnwPA6HQ7/85S8lSTU1Nbrqqqu0f//+Y45btmyZ7r333uPW9fvf/15paWmSvINHnn322WMGj/grKyvTf/7zH73xxhvHPXdr5ebmSpI2bNigioqKoF+vrWAICNACBw8elMTy3+YylwBLBICRxgwA07O7KCOne8iu22vQ6UpMyVB5SaE+/PBDXXzxxSG7NgAAABAI99xzj2/vvyuvvFJXXXWVxo4dq/T0dG3evFmvvfaa1q9fr0GDBsnhcOjbb7+t9zz333+/3n//fa1Zs0Zr1qzRwIEDdfPNN2vo0KGqrq7WV199pf/973+KiYnRJZdcoo8++khS/ZN5O3XqpLffflsXX3yxqqqq9Ktf/UovvPCCLrvsMg0YMEDJyckqKSnR1q1btWzZMn3xxReqrKzUn/70p+C9UYedffbZWrVqlcrKynTxxRfruuuuU3Z2tm9p8ODBg9WpU6eg1xFtCACBFjCXADMApHnoAIxMLpdL8+fPlyT1Gny67xtvKNhi7Rpw0rlaNvdNzZkzR5WVlYqPZ/I2AAAAIsdtt92mZcuW6b///a88Ho/efPNNvfnmm3WOGTx4sKZNm6Ybb7yxwfPEx8frs88+0/nnn69Vq1YpPz9fTz75ZJ1jEhMT9fLLL2vVqlW+ADAlJaXe851zzjlasGCBJkyYoO+//16bNm3SU0891eD1bTab2rdv39QPu8Xuvfdevfbaa9q3b5/mzJmjOXPm1Hn+5Zdf1g033BD0OqINaxeBFvBfAoym83+/iouLLawEzfHdd9/59t/oOej0kF+//8nnSfIuO/jqq69Cfn0AAACgNQzD0EsvvaT33ntP5513njIzM2W329W+fXuNHTtWzz//vL755hvf0tfGdOjQQcuWLdOkSZM0cuRIpaWlKSEhQb169dIdd9yh5cuX68orr6yzB2BGRkaD5zv55JO1bt06vfPOO5owYYJ69+4tp9Mpm82m1NRUDRo0SFdffbX+9a9/adeuXbrlllsC8p40pmPHjlq+fLl+/etfa8iQIUpJSQlpE0K0ogMQaAGWALeMf8ckHYCRY9GiRb7Huf1ODfn1ewwYKUd8sqoqSzV9+nSde+65Ia8BAAAAaK0f//jH+vGPf9zoMXPnzj3ueex2uyZOnKiJEyc2eMw333wjSUpLS1PXrl0bPV9MTIyuuOIKXXHFFce9dn3++Mc/6o9//GOTjh03blyTpvt27NhRf/vb31pUD+pHByDQAr4OQJYAN0tiUpxiYrw/uSEAjBxmAJjTpa8SU9JDfv1Yu0N9TjhDkjRr1izV1NSEvAYAAAAgUnz99ddavny5JG/gRvccJAJAoEXMPQCdBIDNYhiGbx9AAsDI4HK5fD897G5B95+p/8nerr/CwkItWbLEsjoAAAAAKy1fvlwlJSUNPr9u3TpdffXVvv++/fbbQ1EWIgBLgIFmcrlcKi0tlUQA2BIpzngVH6ogAIwQ5vQtydoAsM+QcYq1x6nGVa0ZM2Zo9OjRltUCAAAAWOW///2vpkyZonPPPVennnqqunbtqtjYWO3du1dfffWVPvzwQ9+KmZ/+9KdsnwMfAkCgmfyDK5YAN1+yM0HSQQLACOG//1/3vsMtq8ORkKweA0/TxhVf6JNPPtHjjz/OUgYAAAC0SWVlZfrggw/0wQcfNHjMtddeq5deeimEVSHcEQACzVQ3AGQKcHOZk4CZAhwZzAAwu1NvJadmWVrLgJPO1cYVX2jXrl1avXq1hgwZYmk9AAAAQKj95je/UdeuXTVv3jxt2bJFBQUFOnTokJKSktSpUyeNHj1aN9xwg0aNGmV1qQgzBIBAM5kTgCXJmZZoYSWRiT0AI4fb7dayZcskSd37nmJxNVLfYWf6Hn/++ecEgAAAAGhzunbtqt/85jf6zW9+Y3UpiDAMAQGayRwAIklOJx2AzZXi9C6bJgAMfz/88IPv671LrxOtLUZScmq2OuV6Q7/PP//c4moAAAAAIHIQAALNxB6ArZNCB2DEMLv/JKlzrxOsK8RP76HjJEnffvutCgsLrS0GAAAAACIEASDQTHWXABMANpf/EmCPx2NxNWjMt99+K0lKSEpVZk6uxdV49TkcALrdbs2dO9fSWgAAAAAgUhAAAs1kdq7ZYmOUkBhncTWRx+wArK2tVVlZmcXVoDFmB2DnnicoJiY8vl106jFEiSkZklgGDAAAAABNFR7/ogMiiLknmjM1QYZhWFtMBEr22zeRScDhq6ysTOvWrZMkde45zOJqjoiJsan3kDGSpDlz5qi2ttbiigAAAAAg/BEAAs1kLgF2sv9fi5hDQCT2AQxnK1askNvtliR1CZP9/0x9hp4hSSosLNR3331ncTUAAADAsQzDiJhfs2fPtvrtQggQAALNZIZWDABpmZTUIx2ABIDhy9z/T/IuAQ4nvQaPkWF4v33xlxUAAAAAOL5YqwsAIo1vCTADQFokhSXAEWH58uWSpKyOPZWQlGpxNXUlJqepS69h2rHpW3355Ze6//77rS4JAAAAqNdjl12ifh06WF3GMTbs2aMHP/jI6jIQQgSAQDOZAaB/kIWmS/ZbAmy+lwgvHo9HS5culSR1CaP9//z1HHS6dmz6VitWrNDBgweVnp5udUkAAADAMfp16KBTcrtZXQbAEmCguXwBIEuAW8Q/OGUJcHjavXu39u/fL0nq0is8A8Beg06T5A0r58+fb3E1AAAAABDeCACBZjJDq1SWALdIfIJdtljvHz0sAQ5Py5Yt8z0Ot/3/TJ16DpUjIUWSNG/ePIurAQAAAIDwRgAINENlZaUqKiok0QHYUoZh+LoA6QAMT6tWrZIkxdodate5j8XV1M9mi1Vu/xGSCAABAAAA4HgIAIFm8N+zjgCw5ZIJAMPa6tWrJUntu/STzRa+W8Way4C3b9+urVu3WlwNAAAAAIQvAkCgGfwDKycBYIs5Dw8CIQAMPx6PxxcAdug+yOJqGtfzcAAo0QUIAAAAAI0hAASa4eDBg77HdAC2HB2A4SsvL08FBQWSpI7dB1pcTeMy2+cqNbOjJGnu3LnWFgMAAAAAYYwAEGiGuh2A8Y0cicawB2D4Mvf/k6QO3cI7ADQMw7cMeMGCBaqtrbW4IgAAAAAITwSAQDP4dwA60xItrCSyJR9eAswU4PBjLv+NscWqXee+FldzfD0HnS7JGyavWLHC2mIAAACANqCqqkr//e9/dfnllys3N1fJyclKSEhQ586dNX78eD3//PMqLCys85obbrhBhmEc8yspKUk9e/bUtddey7Y+QUYACDRD3SEgdAC2FEuAw5fZAdiuU2/Z4xwWV3N8PQaOkmEYktgHEAAAAAi22bNnq3fv3rr55pv1/vvva9u2bXK73XI4HNq9e7dmzpypO++8U927d9dLL710zOvtdrtycnJ8v6qrq/XDDz/o9ddf17hx4/S73/3Ogo+qbSAABJrBDKwcjlg5HHaLq4lc5hLg4uJiud1ui6uBPzMADPflv6aklAxfrQSAAAAAQPC88cYbuvDCC7Vz50717NlTL730kvbu3avy8nIdOnRIZWVlmjlzpn7yk5+otLRUH3/88THnGDVqlPbu3ev7VVlZqWXLlun0070re5588knNmjUr1B9am0AACDSDuQTYmcYAkNYwB6i43W6VlZVZXA1MBw4c0J49eySF/wAQf+Y04KVLl6q0tNTiagAAAIDos3btWt18882qqanReeedp5UrV+qmm25STk6O75jExERdcMEFevvtt7Vw4UJ17dr1uOe12Ww66aSTNG3aNGVlZUmSpkyZEqwPo00jAASawewAZAJw65gdgBLLgMOJuf+fJHXoPsjCSpqnx4BRkiSXy6VvvvnG4moAAACA6PPggw+qoqJCHTt21JtvvqmkpKRGjx85cqSeffbZJp8/PT1dw4cPl+QNGxF4BIBAM5h7AKY4CQBbI9kvAPTfVxHWMpf/Goah9l37W1xN03Xtc7JsNu+S/AULFlhcDQAAABBd8vLyNG3aNEnSXXfdpbS0tCa9LiameZGTx+ORJLaJChICQKAZzLCKJcCtQwdgeDI7ADPb58oR3/hP9MJJnCNBnXudIElauHChtcUAAAAAUWbu3Lm+cO6SSy4JyjUKCwt9q3l69OgRlGu0dbFWF4DQsNlsYXGOSGeGVc7UBN/k0XBh1hNuddXHfwl1aWlpm//aCpeP3wwAO3QbGBFfR/56DBip7d8v1YoVK1RWVian0xmwc5ufn3D5PKFp+HyFP+6tyMTnK/xxb0UmPl8IZ+vWrZMkORwO9evXL6Dnrq2t1YoVK/SrX/1KBQUFkqTrrrsuoNeAFwFgG5Gent6q19tstlafIxqYAWBaRrLs9jiLq6lfbGz4TydOzzgSztTU1LTpr61wubdKS0u1detWSVLnHoMVZw//ryN/fQafri8/+LvcbrdWr16tiy66KODXCGSoiOAKl/sKTcO9FTm4tyIL91bk4N5CuDODufT09FY3CixatEjt27evc+6amhrff9966626/PLLW3UN1I8AsI0wp9c2l9PplM1mU21trYqLiwNcVWTxeDwqLCyUJCWlxMnlqra4oroMw1BsrF01NS5fe3a4ik888hPOvLy8Fn99RrJwu7eWLVvme5zVsbeqXS4Lq2m+9t0HK9buUI2rSp988olGjx4dsHPbbDY5nU4VFxertrY2YOdF4IXbfYXGcW9FDu6tyMK9FTm4t1qGsDSyuVwu7du375jft9lsmjJliiZMmGBBVW0DAWAbEYhv/m39LxClpaW+n0ykOOPDNmTzeDxhW5vJ4YhVXFysqqtrdOjQoTb/tRUOH/+aNWt8j3M69wn7r6Gjxdod6tr7JP2wbpHmz58flPe0trY2LD5XaBo+V5GDeyuy8LmKHNxbkYXPFcJZZmamJG9jkcfjaVUX4NixYzV37lxJ3jDwhx9+0KRJk/SPf/xDd999t4YMGaIhQ4YEomwchSEgQBP5D6tgCEjrmZOAmQIcHtavXy9Jik9MkTOjg8XVtExu/xGSvGFmW+wqBQAAAIJhwIABkqSqqipt2LAhYOe12+3q27evnn/+ed11110qLCzUFVdcofLy8oBdA0cQAAJN5B8o+A+xQMuYk4CZAhwezAAwp3PfiBsAYsodMFKStwt20aJFFlcDAAAARIdx48b5/o3w0UcfBeUaf/7zn9WuXTtt2rRJf/vb34JyjbaOABBoojodgASArWZ2ALLfifU8Ho9vsldOl8BO9QqlTj2GyB7nvTcXLFhgcTUAAABAdOjYsaMuueQSSdKkSZOavIrL7XY3+RpJSUm67777JEl//etfffvvI3AIAIEm8v9DjgCw9egADB/79u3zfYON5AAwNjZO3fqeIklauHChxdUAAAAA0eOxxx5TfHy8du/erZ/+9KfHXab79ddf65577mnWNW677TalpaWppKREzzzzTCuqRX0IAIEmYglwYCUTAIYNc/mvJOV06WthJa1nLgNev3698vPzLa4GAAAAiA6DBg3S5MmTZbPZNGvWLA0dOlQvv/yy9u/f7zumvLxcn376qa666iqNHj1aO3bsaNY1UlJSNHHiREnS3//+d/b1DjACQKCJ/IMqs3sNLWeGqCwBtl6dALBzHwsrab0ehweBSHQBAgAAAIE0YcIETZ8+XZ06ddLmzZt10003KScnR0lJSUpLS1NSUpIuuOACvf3220pNTdWPf/zjZl/j7rvvVmJiooqLi/Xss88G/oNowwgAgSYylwAnJjsUa7dZW0wUaCtLgLdv365p06Zp8uTJmjJlir7++mu5XC6ry6rD3P8vNbOj4hOdFlfTOh26D5IjPlkS+wACAAAAgXb++edry5Ytmjx5si699FJ17dpVHo9HlZWV6ty5s8aPH68XX3xR27Zt03XXXdfs82dlZemWW26RJD333HNN3m8QxxdrdQFApDD/4HHS/RcQ/kNAamtrZbNFT6jq8Xg0ffp0Pf/881q+fPkxz3fs2FETJ07UPffco7i4OAsqrMs3ATiC9/8z2Wyx6tZvuDau+IIAEAAAAAgCh8OhW265xRfUNcWUKVM0ZcqUJh373HPP6bnnnmthdWgIHYBAE5kBIPv/BUaK88j7WFJSYmElgbVz505deumluummm+oN/yQpLy9Pv//973XKKado9erVIa6wrpqaGm3cuFGSlNM5svf/M/U4vA/g5s2btXfvXourAQAAAADr0QEINJGvAzCNADAQkv06KYuKipSWlmZdMQEyd+5c/eIXv/BtVpvSLl3Df3aB+p9zitI6tVNNVbU2z1+hRf+drrzVW7R27VqNGjVKU6dO1ZgxYyypeevWraqsrJQkte8a+R2AkpTbf6Tv8cKFC3X55ZdbWA0AAAAAWI8OQKCJ6AAMrJSUugFgpPvoo4909dVX+8K/035xqe7+4nmNm3iFcvp2kyM5QUmZqRp66Vjd+uGTuvChG2Wzx6qiokITJkzQ/PnzLanb3P9Pip4OwPZd+yshKVUS+wACAAAAgEQACDSZLwB0EgAGgn8HYKRPAp42bZp+8YtfqKamRnFJ8brm37/TefdfJ0dS/V8rMTExGnvbj/Wzyb+XLc4bAl5//fX64YcfQly5fMt/Y2yxyuyQG/LrB0NMTIy69ztVEgEgAAAAAEgEgECTmV1qLAEODKdfJ2UkdwB+/fXXuuOOO1RbWytHcoKuf+UP6n/O8Ca9dsA5wzXhX7+TYRgqKSnRTTfdpPLy8iBXXNfmzZslSRntuio21vqBJIGS23+EJGnbtm3atWuXxdUAAAAAgLUIAIEmcLvdR/YATGUKcCD4dwBG6mj3H374Qddff72qq6sV64jTdVMeUteTmreP3oBzT9UZ91wlSVq7dq3++Mc/BqHShm3atEmSlNWhZ0ivG2w9BozyPaYLEAAAAEBbRwAINEFJSYk8Ho8k9gAMlOSUyF4CXFFRoZtuukkHDx6UYRi64pm7mx3+mcZOvEK9xpwgSXr55Ze1ZMmSAFbaMLfbrS1btkiSsjtGVwDYrnMfJaVkSpJl+ysCAAAAQLggAASawL9DzUkAGBBxjlg54u2SInMJ8IMPPqi1a9dKks645yoNvGDkcV7RsJiYGF36lzsUl+QNRX/961+rqqoqIHU2Ji8vz7fkOKtDj6BfL5QMw1DuAO8y4IULF/oCfAAAAABoiwgAgSbwDwDpAAyclMPLgCMtAJw1a5ZeffVVSVLP04Zq7C8vb/U5Uztm6Zz7rpXkHczx8ssvt/qcx2Pu/ydF3xJgScrt7w1ld+/erW3btllbDAAAAABYiAAQaAL/ADCVISABY+4DGElLgA8dOqR7771XkpSY4dQVT9+tGJstIOce/rPz1b5/d0nS008/HfT3xdz/T4q+DkBJvg5AiX0AAQAAALRtBIBAExw8eND3mA7AwDHfy0jqAHzwwQe1b98+SdLFj/5CydlpATt3jM2mc3/7M0ner7m///3vATt3fcwAMCklU4nJaUG9lhWy2vdQSnqOJAJAAAAAAG1brNUFAJHAP6By0gEYMJG2BPjzzz/XW2+9JUkacP4IDRo/6jivaL5eY05Qj1GD9cOi1fr3v/+t2267TVlZWQG/jiTfAJCsjtHX/Scd3gew/witWjRNCxYskMfjkWEYVpcFAACANmTDnj1Wl1CvcK0LwUMACDSB2QFoGIaSkh0WVxM9zCXA/kusw1VlZaV+97vfSZIS01N08aO/CMp1DMPQ2fddq3//+HeqqKjQ5MmTdf/99wflWmYHYHYU7v9n6jFglFYtmqb9+/dr06ZN6tOnj9UlAQAAoA158IOPrC4BkMQSYKBJzA61lNR4xcRw2wSKOVE5EgLAF154Qdu3b5cknXf/dQFd+nu0LsP6KHfkIEnSSy+9pJKSkoBfo7S0VHsO/9QvGvf/M/Xof2Q6M8uAAQAAALRVJBlAE5gdgE72/wsoZ4TsAZiXl6fnnntOktR5aG+dcPkZQb/m2Du8k4WLioo0ZcqUgJ/fXP4rSVkdo7cDML1dF6VldZIkzZ8/3+JqAAAA0FZ4PJ6I+XXOOedY/XYhBAgAgSYwO9QYABJY5n6KFRUVqqystLiahj366KMqLy+XJF348M0h6QLtMXqIOg3xBnMvvfSSampqAnp+/wnA0bwEWPIuA5akRYsWye12W1wNAAAAAIQeASDQBGaHGh2AgeUfqIbrMuBvv/1W7733niRp2OVnqMuw0OwhZxiGRtxwkSRp9+7d+vTTTwN6fjMAtMXGKS27c0DPHW5y+4+QJBUWFmr9+vUWVwMAAAAAoUcACDSBuQQ4JTXe4kqiizMCAsDHH39ckmRPcOic31wb0msPunCUkjJTJUn/+c9/AnpuMwDMzOmumBhbQM8dbnIHHNkHkGXAAAAAANoiAkCgCXwdgGmJFlcSXfw7AM2QNZzMmzfPFxiNvPEipbTLCOn1Yx12nXLNuZKkhQsXBrR7zdwDMKtj9A4AMaVmdFBm++6SvO8jAAAAALQ1BIBAE/g6AJ10AAZSatqRADDcBoF4PB5f919CarJOu/VSS+o45drzFGPz/lE9derUgJyztrbWFwBG+/5/ptzD04AXLVqk2tpai6sBAAAAgNAiAASOw+VyqaysTBIdgIHmTAvfDsAZM2bou+++kySddtulSnAmWVKHMydDvcedKEl67733VF1d3epz7ty5U1VVVZKkrA7R3wEoHRkEUlxcrNWrV1tcDQAAAKKdYRgR82v27NlWv10IgYAGgNdcc42++uqrQJ4SsJz/3nRO9gAMqBRneHYAut1uPfXUU5Kk5Ow0jbh+vKX1nPiTMyVJBQUF+uyzz1p9vs2bN/seZ3VsKx2Ap/oeL1iwwMJKAAAAACD0YgN5sjfffFNvvfWW+vTpo1tvvVXXXXedMjJCu2cWEGj+wVQKU4ADKs4Rq/gEuyorXGHVAThr1izffntjbr9ccQkOS+vpc8ZJSsxwqrywWG+88YYuuuiiVp2vTgDYRjoAk1Oz1a5TH+3fvVHz58/XxIkTrS4JAAAAbcBvHrtEvft1sLqMY2zasEdPPfiR1WUghAIaAErefbM2btyoe++9V7///e91xRVX6Be/+IVOO+20QF8KCIm6HYAEgIGWkpqgygpX2EwB9ng8evrppyVJSZmpOvnqsy2uSIqNs2vopWP09X+na86cOdq3b59ycnJafD5zAnBKWjvFJ6QEqsywlztghPbv3qjFixfL5XLJbrdbXRIAAACiXO9+HTT0lG5WlwEEdgnw3Llz9dOf/lRxcXHyeDyqrKzUa6+9prFjx2rgwIGaNGlS2PwjH2gq/840OgADzwxVw+XPhrlz52rFihWSpFG3XCx7vLXdf6YTr/AuA66trdU777zTqnOZAWBWGxkAYjIHgZSXl/s+xwAAAADQFgQ0ABwzZoxef/117dq1S3/961/Vp08feTweeTwebdiwQffcc486deqkG2+8UV9//XUgLw0Ejf8SYP+ptQiMcAsAn3nmGUneyb/Drz3f4mqOaN+/uzoO9gZ2b7zxhjweT4vPZS4Bzm4j+/+ZcvudKsMwJEnz58+3uBoAAAAACJ2gTAHOzMzUvffeqw0bNujLL7/UVVdd5esKrKio0KuvvqrTTjtNQ4YM0QsvvKDi4uJglAEEBB2AwWVOAg6HAHDJkiW+H06MuOFCxaeE19TnYT8eJ0nauHGj1q1b16JzHDp0SAcOHJDUdvb/MyWmpCuna39J0sKFCy2uBgAAAABCJygBoL+xY8fqjTfe0K5du/TUU0/V6Qpcu3at7rzzTnXs2FG33HKLvvnmm2CXAzSb2QFoj7MpPoE9wwLNDADDYQjIiy++KEmyJzg04gZrJ//WZ+D4UTJivH9sf/DBBy06R1scAOKvxwDvMuBvvvlGlZWVFlcDAAAAAKER9ADQlJmZqfvuu08bNmzQnDlzdNVVV8lut8vj8ai8vFwvv/yyRo4cqWHDhmny5MmqqKgIVWlAo8xgKsWZ4Fs+iMBJcXoDQP+l1lbYtm2bZs6cKUk68SdnKjEt/IZjpGSnK3fEQEnStGnTWrQM2D8ADNgSYI9H+QfytXnTZq34boVWrlipTZs2ebs6W75SOSh6DBglSaqsrNTSpUstrgYAAAAAQiNkAaC/M844Q0888YRuuOEGSfKFKh6PR6tWrdJtt92mrl276plnnpHb7baiRMDHXJqakhpvbSFRyn8JsJX3++TJk+XxeGQYhkbeeJFldRzPoPGjJXkDy5YMsjAHgNjj4uXM6Ni6YjzS7t27NX/+An377bfasmWL9u3bp7179+qHLT9oyeIlWvLNEpWWlrbuOgHUvd+pstm8nbxz5861thgAAAAACJGQBoBut1sffvihLrjgAvXs2VOTJ0+W5A3+kpOTdc455/i6AgsKCnTffffpzDPPpBsQljIDQGdaeO0HFy3MfRXdbrdlQVFxcbFee+01SVLfs09RZvcOltTRFAPOH6GYWJukli0DNjsAM9vnKiam5d8CqquqtXz5cq1ZvUbl5eWSvD/MSYl3KDne4fvBzqGDh/T1okXasWNHi68VSI74JHXpNUySNG/ePIurAQAAAIDQCEkAuH37dj344IPq0qWLLr/8cn322Wdyu93yeDwaPHiwXnjhBe3evVuzZs3Szp079fjjjys7O1sej0fz58/X008/HYoygXr5AkA6AIPC6TdZ2ap9AKdOnaqysjJJ0uibL7akhqZKynCq52lDJUkffvhhs7smzQAwq0PLl/+Wl5Vp8eKvfcNEEuLs6t+xvcb1661Te+RqRI9cjenTS7nZmYoxDLndHq1ft14/bNkSFkuCew46TZK0atUqFRQUWFwNAAAAEP5uuOEGGYbRpF/mak+El6AFgLW1tfrggw90/vnnq2fPnvrLX/6iPXv2yOPxyG6365prrtH8+fO1cuVK3XbbbUpOTpYkZWdn6/7779f69es1cOBAeTwevfHGG8EqEzguc286JxOAg8L/fbViEnBtba3+85//SJI6Du6pbsMHhLyG5hp8kXcZ8J49e7RkyZImv87lcmnr1q2SWr7/X0lxiZYs+UYVFd4BGp3SUnVqj1x1SkuTzTjyLcVus6lndrZOye0mhz1WkrRp02Zt37G9RdcNJDMA9Hg8+uqrryyuBgAAAIgcdrtdOTk5jf5KTU21ukzUIzbQJ9y2bZsmT56sKVOmaO/evZLk26i+e/fuuvXWW3XzzTcrKyur0fNkZGTo7rvv1i9+8QvfP1gBK/iGgBAABoXVAeCcOXO0c+dOSdKI6y+MiEEv/c8ZLltcrGqrazR9+nSNHDmySa/bsWOHXC6XpJZ1AJaXl2vZt8tUXV0tSeqT005dMzMafU1KfLxO7t5Ny7fvUEW1S99v+F4pySnKOM7rgqlTjyGKT3SqsrxY8+bN02WXXWZZLQAAAEAkGTVqFHtpR6iAdgCed9556tWrl5544glft59hGBo/frxmzJihLVu26Le//e1xwz9T586dJXmnNQJW8Hg8RzoA0wgAg8H/fbUiAHz55ZclSQlpyRp0uLMu3MU7k9Rz9BBJ0ieffNLkacDmABBJyurQo1nXdFW79O2yb1Vd5Q3/+ndsf9zwz5Rgt2tol86yxcTI4/Fo5cqVvvNYISbG5psGPG/evBZNUwYAAACASBLQAHD27Nm+vf3atWun+++/X1u2bNHHH3+sCy64oNmdNYmJieratau6desWyDKBJquoqFBVVZUkKcVJABgMKRZ2AG7fvl1z5syRJJ34k7Nkd8SF9Pqt0f+cUyVJO3fu1OrVq5v0GnP/P0nKap/b5GuZoZ057KNXu2x1SktrerGSkh0ODezoHa5SXV2t9evXN+v1gWYuA961a5d++OEHS2sBAAAAotnq1at14403qkePHoqPj1dSUpJyc3N11lln6cknn2xwX+6ioiL9+c9/1ogRI5SRkaH4+Hj16NFDF110kV555RWaxZop4EuATz/9dN1+++26/PLLZbfbW3WuMWPGaNu2bYEpDGgBs/tPYg/AYElO8U6M9Xg8IR8C8sorr/i6v0655tyQXru1+p19ij564J/yeDz65JNPNGTIkOO+xuwATM3sqLj4pk+13rRxk++bcse0VHXPatny3XbOFHVIS9WeQ0Xau3evOuzroHY57Vp0rtbqNfh03+O5c+eqZ8+WD0UBAAAAUL9PP/1UP/rRj3zbCDkcDtntdm3btk3btm3TF198oZNOOklnn312ndctWbJEP/rRj7Rv3z5JUmxsrJxOp3bu3KmtW7dqxowZGjp0qE444YRQf0gRK6AdgKtXr9a8efP005/+tNXhHxAO/AMplgAHR0xMjFKc3gnL/oFrsFVVVen111+XJPUac4Iyu3cI2bUDITk7TV1O6ivJuwy4KcwAsDnLfwvyC3z7sDoT4tWvQ3tJLd8nsU9OO8XF2iRJGzasl7u2eVOMAyWjXVelt+sqybsMGAAAAEDg/fKXv1R1dbUuvPBCrV+/XpWVlTp06JBKSkq0ZMkS3XXXXXI6nXVes23bNl1wwQXat2+f+vXrpxkzZqi8vFwFBQUqLy/XwoULdeuttyouLnJWcIWDgHYADhw4MJCnAyznvySVISDB40xLUHFRRUg7AGfMmOHraht+7fkhu24gDTj3VO1YtkFr167Vtm3b1L1790aP37JliyQpu4kDQFzVLt/y4lhbjIZ07qSYVg5Jsdts6p3TTmt371FFRaV27Nih7rmN1x0svQadpqVfvK4FCxaopqZGsbEBb4oHAAAAosqiRYvUvn37Ro95//33NWrUKO3fv9+33c5LL71U53XJyckaPny4hg8ffszr77//fh08eFDdunXTwoULlZFxZAWS3W7XqFGjNGrUqAB9RG1HQDsAY2JiFBsbq48++qhZr5s1a5ZsNhv/+ELY8Q8A6QAMHnN5dSj3ADS7/1JyMtTnzJNCdt1A6nfOkW+Wx+sCLCgoUGFhoSQpq2MTAkCPtGbtGt8emP07tFd8gDq72zudSon3dn3+8MMPvsnEoWbuA1hSUqLly5dbUgMAAAAQSVwul/bt29foL3O5b3JysmJivLHT3r17m3T+srIyvfvuu5Kkhx9+uE74h9YJaAAoqcXTFD0eD5MYEXbqdAAyBCRoUkIcAO7atUtfffWVJOmEH4+T7fCS1EiT2b2D2vX1LmOdMWNGo8c2dwLw7rzd2r9vvySpQ1qqco5qy28NwzDUOydbkvcvENu2bgvYuZujx4BRMgzvt0GWAQMAAADHN3bsWF9+09CvcePGSfIOdh07dqwk6bzzztOjjz6qb7/9VrW1tQ2ef+nSpaqpqZEkjR8/PugfT1sS8AAQiCZ1h4DEW1hJdDO7K0MVAL711lu+HziceMWZIblmsAw41zsN+JtvvtGBAwcaPM4/ADzeEuDq6mp9//33kqSEOLv6tg/8oI6MpCRlJCVJknbs2KEaV03Ar3E8CUmp6pQ7WJL05Zdfhvz6AAAAQLT7z3/+owEDBmj//v16+OGHdfLJJ8vpdOq8887T5MmTfSuOTObQj/j4eLVrZ83AwGgVFgFgeXm5JO8nGAgn5p50CYlxssexRD1YQtkB6Ha79eabb0qSup7UV1k9Ogb9msHU/1zvMmCPx6NZs2Y1eJy5/19cfJJS0nMaPef3338vV7V3WW6/9u0VGxOcDsncrExJUk1NjXbs2BGUaxyPuQx4+fLlKi4utqQGAAAAIFr16NFDq1at0kcffaTbb79dgwcPVkVFhT777DP94he/0KBBg5SXl2d1mW1CWASAixcvliTSXYQdM5BKofsvqEK5B+DXX3+tbdu2SZKGRXj3nyR1GNhDqR2zJEkzZ85s8DizAzC7Q08ZjQzyKCwsVN5u7zfgHGeKMpOTAlhtXelJCUpN9H7ut2/f3uhSgGAxA8Da2lotWLAg5NcHAAAAop3NZtPFF1+sF154QatWrdL+/fv1/PPPy+l0avPmzbrnnnt8x5qDQiorK7V//36LKo5OLW5pWrVqlVasWFHvc1988cVx/yHv8XhUVlam5cuXa+rUqTIMQ6ecckpLywGCwvw6djIBOKjMDsCysjJVV1cHdZz7G2+8IUmyx8dp0PjRQbtOqBiGof7nDNfiV2Zq/vz5Ki8vV2Ji4jHHmQFgZofcBs/ldru1bu06Sd6pv33aN94p2HqGcrMytWLHLlVXV2vPnj3q3LlzkK9ZV9feJ8kRn6yqylLNmTNHF154YUivDwAAALQ1WVlZ+uUvf6nKykrdd999mjt3ru+5k08+WXa7XS6XSzNmzNCNN95oXaFRpsUB4AcffKBHH330mN/3eDyaNGlSs87l8XhkGIZuu+22lpYDBMWRDkACwGBK9ZuwfOjQoaB1A5eWlurjjz+WJA24YKTiU44NyiJR3zNP1uJXZqqyslILFizQueeeW+f5qqoq3xLbxvb/2/rDVpWVlUmSerXLliMEk9kzk5KUGBen8upq7di+Q507dZYablAMOFusXT0Gjdb6ZbM0Z84c3/cjAAAAAK1zvOaOhATvvwP99wFMSkrSFVdcoTfeeEOPPPKILr30UqWnpwe91ragVUuAj5700tDvH+9XTk6OJk+erDPPjPzleIguvg7ANALAYPLvsPQfvBJo06ZN8+05GunDP/x1P3Wg4hK9y9Rnz559zPPbtm3zLa/N6lh/AFheVq4ffvhBkpSaEK9OaWnBKfYohmGoc4b3WiUlJTp4sDAk1/XXZ+g4SdLu3bu1YcOGkF8fAAAAiEaLFi3SCSecoEmTJmnTpk2+3KimpkYzZ870NZVdcMEFdV73+OOPKy0tTdu3b9fo0aP1ySefyOXy7lHucrk0f/58/exnP9O6detC+wFFuBa3d1x66aXq3r17nd+78cYbZRiGJk6cqBNPPLHR18fExCg5OVm5ubkaPHiwbLbgbDIPtAZLgEPDv8PSHLwSDG+//bYkKa1zO3UfMTBo1wm1WIddPUYP0YbZ32j27NnHdLH5TwDO6tDj2BN4pHXr1srtdsswDPXr0D6kXXAd01K1ZX++at1ubd++Q+kZGSG7tiT1HjLW93jOnDnq379/SK8PAAAARIpFixb59ulryKBBg/T5559LklauXKm77rpLkhQXF6fk5GQdOnRIbrdbktSnTx89/fTTdV6fm5ur6dOn69JLL9X69et14YUXym63y+l0qri42BcG3nvvvYH+8KJaiwPAoUOHaujQoXV+z1ybfdZZZ+mSSy5pXWVAGCAADA3nUUuAgyEvL09ff/21JGnopWMUExMWM5ACpu+ZJ2nD7G+0e/durVu3TgMHHgk4N2/eLMnbbZeZc+wegHl78lRQ4O2865qRrpQQT2SPjbGpQ5pTuwoPaf+B/aquqlacI3j7QB4tNaODcrr0076dG/T5559r4sSJIbs2AAAAEElcLpf27dvX6DFmQHjKKaforbfe0pw5c7R06VLl5eWpoKBATqdT/fv312WXXaZf/vKX9e5hPnr0aH3//fd67rnn9PHHH2vz5s0qKytTly5dNHDgQP3kJz/hB/fNFNANnl5++WVJOm73HxAJ3G63bzkqewAGl38AGKwOwGnTpvlazodccnpQrmGlPmec5Hs8e/bsOgGg2QGYlt1F9jhHnde5ql36fsP3kqR4u109srNCUO2xOqWlaVfhIXncHu3Zk6duR3WYB1ufoeO0b+cGLVmyRCUlJUpJSQnp9QEAAIBwNmXKFE2ZMqVZr0lKStKVV16pK6+8skXXzMjI0COPPKJHHnmkRa9HXQFtgbn++ut1/fXXh3yKIxAMpaWlvrZkAsDgCkUA+P7770uScvp1U7veXYJyDSs5czLUcZB3ee/R+wCaHYD1DQDZuHGjqqurJUl9O+TIZlFnZEp8vFLiveHkrl27Jc9xXhBg5jLgmpoazZs3L7QXBwAAAIAgi641cEAA+QdRDAEJLofDroRE75LPwsLAD4HYsmWLVqxYISk6u/9MZhfgsmXLfO+jx+PxdQAevf/fwcKD2rVrlySpnTNF2cnJIaz2WB0PDx4pLS1VUXHwhsHUp2vvk+RI8Hb9zZkzJ6TXBgAAAIBgIwAEGuC/F53TSQAYbKmHQ9ZgdAB++OGHvseDLxod8POHCzMAdLvd+uKLLyRJ+/fvV0lJiaS6AaDH7fFNzYq1xahvTk6Iqz1W+1SnYg4PH9m9e3dIr22LtavnIO/Xxpw5c+pMtgcAAACASNeiPQB79PD+I9IwDG3ZsuWY32+po88HWKlOAEgHYNA50xO1N68o4B2AHo9HH3zwgSSpy7A+Su9ifdAVLJ2G9lJSplNlBcWaPXu2rrjiCt/yX0nK7nhkCfDWrVtVWloqSeqZnS2HPaBbwraI3WZTdkqy9hWXaM+ePerXt59ibKH7OVWfoWdo3dJPtWfPnmMGqQAAAABAJGvRv/i2bdsmyRvYHf37hmG0uHPi6PMBVvIPANkDMPhS07yTnwLdAbhu3Tp9/713yMXgi6N3+a8kxcTEqM+4k/Tde19qzpw5qqmp8S3/lY50AJaXl2vLD94ftjgT4tU5Pc2KcuvVMS1N+4pLVOOq0f79+9S+Q4eQXdvcB1CSPv/8cwJAAAAAAFGjRQFg165d6w3rGvp9IBLRARhaqene9zjQHYBm958RE6NB40cG9NzhqM8Z3gCwqKhIS5cu9XUAxic6leTMkjzS+nXr5K51yzCkfh3ah9Wf2xlJiYqLjVV1TY327Nkb0gDQmZ6j9l37a++O9ZozZ47uvvvukF0bAAAAAIKpVR2ATf19IBKZAaBhGEpOcVhbTBtgdgAGMgD0eDy+/f9yRwxUSruMgJ07XPU6fahiYm1y19Rq9uzZvg7A7I49ZRiG8vLylJ9fIEnqkpEuZ3y8leUewzAM5ThTtLPwoPLzD6jGVaPYEC5P7jP0DO3dsV7ffPONioqKlJqaGrJrAwAAAECwMAQEaEBRkXcKaXKKQzEx3CrBlpoe+CXAK1eu1Pbt2yVJgy8+LWDnDWfxziR1O6W/JGn27Nm+DsCs9j1UXV2t7zds8B4XZ1eP7GzL6mxM+1SnJMnt9mjfvn0hvXbvod5lwLW1tZo3b15Irw0AAAAAwUKqATTADKJY/hsaZgBYWVmp8vLygJxz+vTpkqQYW4z6n3tqQM4ZCfoenga8YcMG7dy5U5KU1bGnvt+wQdXVLklSv/Y5ig3TYDs1IV7xcXZJ0t69e0J67S69TlR8ojeAnD17dkivDQAAAADBEp7/+gPCgLkEmAEgoWEGgFJgugA9Ho8vAOx+6kAlZThbfc5I0ftwACjJN5TJkZStvDxvmNY+1ams5GRLamsa7zJgSSooKFR1VXXIrmyzxarXYO+wmDlz5sjtdofs2gAAAAAQLKHbWOmwiooK/fOf/9T8+fNVU1OjE044Qbfffrs6hHCjd6ApzADQSQAYEv4BYGFhoTp16tSq823cuFFbtngn3Q44b0SrzhVpsnt2Ulrndjq0a7/v9wpLXIpxSHabTX1y2llYXdO0dzq1Pb9QHo93GXCXrl1Cdu0+J5yhNUtm6MCBA1q5cqVOPvnkkF0bAAAA0WXThtCuaGmqcK0LwRPQAPC7777T9ddfL8Mw9M9//lMjR9aduFlcXKzTTz9da9as8f3ejBkz9OKLL+qzzz7TsGHDAlkO0Cp0AIZWqt9S60AMAjG7/ySp/7nDW32+SGIYhvqMG6Zvps46/N8xUqy3A7JP+3aKiw35z36aLSXeocS4OJVXV2vPnj2hDQCHjJNhGPJ4PJo9ezYBIAAAAFrsqQc/sroEQFKAlwC/++67WrNmjfbv368RI47tuHnggQe0evVqeTyeOr8KCgp0+eWXq6qqKpDlAK3i6wBkD8CQOLoDsLVmzJghSeoyrI+c7TNbfb5I03vsib7H8cnZirHFKiM5SR1SI2UptKGcVO8y4IOHDob0+0OSM1Ode54giX0AAQAAAESHgLaBLFmyRIZh6JxzzpFhGHWeKykp0UsvvSTDMNSlSxc999xzys3N1QsvvKB///vf2r59u6ZOnaqbb745kCUBLcYS4NBKTQvcHoDbt2/X6tWrJbW95b+mHqMG+x4npObIFhOj/h3aSzIaflGYaZeSoq0HCiSPtH//fnXpEsIuwKFnaOfm77RixQrt27dP6enpIbs2AAAAIt9nn31mdQlNNmDAAKtLQAgENADcvXu3JNW7lPeTTz5RZWWlDMPQSy+9pLPOOkuS9M9//lOLFy/W6tWr9eGHHxIAIiy4XC6VlpZKklKcBIChkJTikC02RrU17lYHgDNnzvQ97n9e25n+6y82Pk6KMSS3RwkpOerTvp0S7Hary2qWlHiHEuLsqqh2af++faENAE84U3Pee1qS9Pnnn6tfv34huzYAAAAi3znnnGN1CUAdAV0CnJ+fL0n1DvSYN2+e7zkz/DP95Cc/kcfj0apVqwJZDtBiRUVFvscsAQ4NwzB83ZatXQJs7v+X06+bMru3zQFD29ZtktzeCcAJqe2VkZRkcUUtYSg75fA04MJC1bhqQnblDt0GKCU9R1Jk/fQWAAAAAOoT0ADQDE1iYo497ddffy3DMI4J/ySpa9eukqQDBw4EshygxfwDwJTUeAsraVvMfQBb0wG4d+9eLV26VJI04Py2ufzX5arWinmLff+d6GyvgsMdrZGmXUqyJMnj9oT0e4RhGOozdJwk6csvv1R1dXXIrg0AAAAAgRbQADAx0fuP96P/kVZUVOTr7hs1atQxr4uP9wYstbW1gSwHaDH/AMrptzcdgivtcADYmg7ATz/9VB6Pt/Otre7/t3r1GhXtzPf9d4IzR/mlZRZW1HKpCQm+qcX79u0L6bX7DD1TklRaWqr58+eH9NoAAAAAEEgBDQC7d+8uSVqwYEGd358+fbrcbrckafTo0ce8rqCgQJKUmpoayHKAFjMHgEiS00kHYKikBigAlKT0rjnK6ds1IHVFku3bt+nAgQOq2HtIkhSXkCK7I1kHy8rlPhyMRhLDMJR9uAswPz9f7lp3yK7dc9Bo2WLjJB2ZKg0AAAAAkSigAeDpp58uj8ejjz76SCtXrpQkFRcX66mnnpIkdezYUYMGDTrmdWvWrJEk5ebmBrIcoMXqBIB0AIaM+V63dAlwWVmZ7wcQ/c46+Zhp5NGuuLhIG7/fKEmqOlAsSXK284agtW63DpWXW1Zba7Q7vA9gbW2t8gvyj3N04Djik5Tb3ztEhgAQAAAAzWEYRsT8mj17ttVvF0IgoAHgz3/+c8XExKiyslLDhw/XiBEj1LNnT61Zs0aGYejnP/95va/74osvZBiGhgwZEshygBbzDwDZAzB0UtNbNwRk3rx5qqqqkiT1PeuUgNUVCWprarRy5Uq5PR7FGIaq93sDwIxO3WXEeIPQSF0GnJ6UqFib99vV/pAvAz5DkrRx40b98MMPIb02AAAAAARKbCBPNmTIED388MN6+OGH5XK5tHTpUt9eXEOGDNH//d//HfOa1atXa8OGDTIMQ6eddlogywFazAwAbbExSkiMs7aYNiT1cAdgcXGxampqFBvbvD+iZs2aJUlypCSq2yn9A15fOFuzdq3KyyskSbnONH2V7x1kk5bTTQnOJJUfKvUOAslpZ2WZLRJjGMpKTtbeomLtP3BAHrfHF2oGW98TztTMqY9K8k4DbugHWQAAAEB9LnnsVnXo193qMo6xZ8M2ffTgv6wuAyEU0ABQkh566CENHTpUkydP1ubNm5WUlKRzzz1Xv/vd75SQkHDM8ZMmTZIkeTwenXfeeYEuB2gRMwB0pia0uWWkVjL3AJS8y4Czs7Ob/Fq32+1rXe895gTFxtkDXl+42rZtm/bu3SvJOzXXUXpkYm1q+65KTk9W+aFSlVVVq8LlUoI98t6bdikp2ltULFe1SwcPHlRGZkZIrpuR001ZHXoof88PBIAAAABotg79ure55gSEp4AHgJJ0ySWX6JJLLmnSsf/+97/173//OxhlAC1m7kHnTD02tEbwmEuApeYHgCtWrPBNIO975skBry1cFRYWaOPG7yVJiXF2DejYQeu++M73fFpON8WnJEtbvf9dUFqqzunpVpTaKhnJSYqJMeR2e7T/wP6QBYCStwswf88PWrRokUpLS5WcnByyawMAAABAIAR0D0AgWhQVeZdPOtMIAEMp1W/gijkdvKnM5b9GTIz6nHFSQOsKV5WVlVq5cqU8HskWY2hol86KtcUof8d+SVKMLVbJme0Vl+CQPd7b9Rep+wDGxsQoPdH79XFg/wEphAON+5xwpiSpurpa8+bNC92FAQAAACBAgtIBGK6Kior07rvv6ptvvlFBQYEcDod69uypCy+8UCNGjGjxeWtqajR9+nTNmzdPeXl5kqROnTpp7NixGj9+fLP2MSsvL9fEiROVn++ddHn33XfrrLPOanFtaBlzCXAKHYAhdfQS4OYwA8CuJ/ZVYnpKQOsKR263WytWfKfqapckaWDHDkpyePerNANAZ7vOirF5//xJSk/RoT2FOlhWJrfHrRgj8n7+k52SrILSMpWXl6usrExJyUkhuW63vicrPiFFlRUlmj17tsaPHx+S6wIAAABAoLSZAHDHjh164IEHfJ1dCQkJKisr04oVK7RixQpdfPHFLdrbqaKiQg899JA2btwoSYqL8/4DfPPmzdq8ebMWLlyoRx99VPHxTZsk++qrr/rCP1jHfw9AhI5/ANicScC7d+/W2rVrJUl9zmob3X/r169TUZF30m/3zAy1cx4JPQsOB4BpOd18v5eUnqxDewpV6/boYFmFMkMUngVSVnKyJO8U4AMHDoQsAIyNjVPvIWO0eskMff755/J4POwNCgAAACCiBC0AXLFihT755BOtWbNGBw8eVGVl5XFfYxiG5syZE/BaXC6XHnvsMRUVFalbt2769a9/rdzcXFVVVWnatGl67bXX9PHHHys3N1dnn312s879wgsvaOPGjUpKStJdd93l6yRcvHix/v73v2vDhg168cUX9atf/eq459qwYYM+/fRT9e3bV99//32LPlYEBh2A1vBfct2cDsDPPvvM97jfWacEtKZwtGvXTu3atVuSlJGUqJ7tjuyV6K51q2Cndy/E1Jyuvt9PTE2SEWPI4/aooKwsIgPAeLtdKfEOlVRWaf/+/eqe2z1k1+5/4llavWSG9u3bp1WrVmno0KEhuzYAAAAAtFbAA8A9e/boxhtv9E3jbKpgdlTMmjVLe/fulcPh0B/+8AffYAGHw6Err7xShYWFmjlzpqZOnapx48Y1ecnu1q1b9dVXX0mS7rzzTo0cOdL33MiRI+V2u/Xkk09q7ty5+vGPf6xu3bo1dCrV1NToH//4hwzD0B133KG77767FR8xWutIB2DTOjcRGLGxNiWnxKu0pLJZAaC5/De9a46ye3UOVnlhoajokNavWy9JirfHalCnjvL/o7No30HVVNdIqhsAxsTEKNGZpLJDpcovLVWfnHYhrTtQspKTVVJZpUOHDslV7ZI9RNOe+x7eB1CSPv/8cwJAAAAAABEloJtAlZaW6owzztDs2bPl8Xia9SuY5s6dK0kaM2ZMvVNFL7/8chmGocLCQq1evbrJ5503b548Ho86dOhQJ/wzjRo1Sh06dJDH4znuxvHvv/++tm/frosuuki5ublNrgGBV1FRoaqqKkmS028oBULDnATc1CXAFRUVWrhwoSTv9N9oXppZVVWl775bIbfHoxjD0JDOnRQXa6tzTP7O/b7Hae271nkuKcM7vba8qloVLlfwCw6CrBTvx+DxeEK6XUJKWrY69fCGfs39ARcAAAAAWC2gAeAzzzzj2wuvc+fOevHFF7V582ZVVlbK7XYf91dtbW0gy5HkDQc2bdokSTrxxBPrPSY7O1udO3u7hlauXNnkc69atUqSNGzYsHpDB8MwNGzYsDrH1icvL09vv/22srKydM011zT5+ggOs/tPklKcdACGmjkJuKkB4JIlS3xbDPQeOyxodVnN43Fr5cqVvnC6f4ccOROO/frM334kAPTvAJS8+wCaCkpLg1RpcDnj4xV3uEt7/4H9xzk6sPqecIYkafny5ezVCgAAgDblhhtukGEYMgxDMTEx2rZtW6PH79y5UzabzfeaG2644Zhjamtr9b///U/jx49Xx44d5XA4lJaWpr59++rcc8/Vo48+6mu8kqRvvvlGsbGxMgxDU6ZMOW7Nf/zjH2UYhpxOp7Zv396Cjzq6BDQA/OCDDyRJ7du319KlS3XrrbeqR48evsEYVti1a5fvi6WxJbjmczt37mzSeT0ej3bt2nXc83bt2vW45/3HP/6h6upq/fznP1dCAnvOWc0/AKQDMPSc6c0LAM0OX1tcrLoPHxCssiy3YcP3vmXRXTLS1CEttd7jzAnACc4MxSUk13kuLt4he/zhScGlZUGsNngMw1DW4f0L8/Pz5XEHt4Pcn7kM2OPxBGW/WgAAACASeDwevfrqq40e88orr8jtdjf4fEFBgUaPHq3rrrtOM2fO1J49exQTEyPDMLRp0ybNnj1bDz/8sMaNG+cb5jp8+HDdd999kqRf/epXysvLa/D8q1at0p///GdJ0l//+tdGc5u2IqAB4JYtW3x72OXk5ATy1C3mHyJkZGQ0eJz5XFP3HauoqPB1HTXlvBUVFaqoqDjm+dmzZ2v16tU65ZRT6l1GjNDz/xpIYQ/AkEs9PAikqfeiGQB2O7m/4hKj8/OVl5enHTt2SJLSEhPUu5H9+/LrmQDsz+wCLCwrk9vT8DfkcGYuA65x1TRrr8jW6tB9kJJTvdtIsAwYAAAAbZEZpL366quNbuf2yiuv1Dn+aNdee62WLFmipKQk/eUvf9Hu3btVUVGhgwcPqrS0VPPmzdO9996rdu3q/tvnkUceUf/+/XXo0CHdeuut9Z67pqZGN954o1wul84666wGj2trAjoExEx3+/btG8jTtor/9GGHw9HgceZz9YV09fE/rinnNV/j3+F36NAhvfzyy3I4HK3+gpw6dapef/31Bp+/+uqrW7S8OCYmxvf/6enpLa4vkvgvRc/MdspuYQdrS8TaQzMUIVgyslIkeQPA433N7dmzR2vXrpUk9R13ouJCNBAiMAzf/zdW96FDRb6P0REbq6FdOis2xtbg8QU7Dk8Abt+t3q0JktNTdGhPodxuj4oqKpWZnHzMMeEuKzlZMYYht8ej/IJ8tW/fPiTXdcQ51G/YWVo29019+eWXSk5Olj3C77do0xa/Z0Uy88+o1NTUoO8Hjdbh3oos3FuRg3sLkeiEE05QSkqK1qxZowULFuj0008/5piFCxdq8+bNGjx4sHr06HHM8tsNGzb4Bjn+97//1ZVXXlnn+cTERI0ZM0ZjxozRn//85zqDWh0Oh6ZMmaJRo0Zp+vTp+t///qef/exndV7/1FNPafny5UpJSdFLL70UqA894gU0AOzWrZvWr1+vkpKSQJ42ak2ePFmlpaW6/vrrj0m1m6usrEz79ze8H1Z5eblstoZDg+MxDKNVr48kZnuxJDlTk2QosoZKRFq9R0vP9AZSBQUFvv0lGvLll1/6Hvcde1JEfuyG3/8ezVXj0rffLpPb7VaMIQ3t2lmORqaUV5ZWqLSwWJKUdtT+f6bE1CQZMYY8bo8OlJRGZAAYa7MpIzlJ+SWl2r9vvzSooXcwsAxD6n+iNwAsLi7W4sWLNW7cuBBcGc3Vlr5nRYPG/pxHeOHeiizcW5GDewuR5vrrr9f//d//6ZVXXqk3ADT357v++us1f/78Y573H7568cUXN3qt+raUM5cCP/nkk7rnnnt0zjnn+JoC1q1bp0cffVQSS3+PFtAA8JJLLtG6deu0cOFC3XjjjYE8dYvFxx9ZElhVVaXExPr3dDM31m/qHnz+x5mvbey8R7/m22+/1fz589WtWzf96Ec/atI1G5OUlNRoiJiYmNiiISvmGnyPx9Po+v1o4r+5f0pqvDyKnJ+cGjIiqt76pGd693dzu906cOCAsrKyGjzW/KlRclaacgZ0i7CP3RtXeis+tm6PR1q5YqXKy73dxn3bt1facf58OrB9n+9xavv6A8AYW4wSU5NUdrA0YgeBSN4uwPySUpWVlamkpEQpySlBvZ5heD8nvQePkc1mV22tSx9//HG9f+GBddri96xIZv6Qx+1206UU5ri3Igv3VuTg3moZwlLrXXvttfrd736nd955R3//+9/r5CwVFRV6++23ZbPZdO2119YbAPrLy8tTz549m13DI488oo8++kjr16/X7bffrg8++EC1tbW66aabVFVVxdLfegQ0ALzzzjv1r3/9S6+99pruu+8+9evXL5CnbxH//fkKCwsbDADNvQKb2nqdkJCghIQEVVRUNDqswHzOPN704osvSvJO0nG5XHK5XPW+3uVyqaKiQoZh1AkzjzZhwgRNmDChwefz8/NbtFdWenq6bDab3G53SPfastKePXskSfEJdhmGW67qaosrahrDMGS3x6nG5Yrov+w5044sm9+8eXOD3+Ddbrc+++wzSVKP0UNUU1MrKfCTxIPFu+zXGwFWVx97/+/atUt5h78Wc5wp6pSWetw9+/Zv2+t7nJrTrcGvg6T0ZJUdLFVZVbXKKiuVEGHL3CUp8/AgEEnak7dHjtyGt2JoLcMwFGe3y1XjkhEbp279huuHtQs1ffp03X///UG7LpqvLX7PimQ2m03p6ekqKvr/7N13fNwF/fjx1+f2yk6apE3TPYFSSmVKW6AsCwjIEBREQb+AoAiKXxVkiIp+ZQn+AAeCojJkCIiy20Jbyi4dtKV00Dbzsm+vz++Pz30uaZs0ueRG7u79fDz4fs/kM96XXJLmnffoGtYfKUXmyNdWbpGvrdwhX1vDs78CAZEZtbW1nHjiifznP//h6aef5itf+UrifU8//TTd3d184QtfGHBUz/z58xPJ729/+9v85S9/Sborsm8r8DPPPMPf//53GhoaWL16tbT+DiCldeG1tbU8+uijmEwmTjjhBJYvX57Kyw9LXV1dYg6GPkS/P/r7xo8fP6TrKopCXV3dsK+rt+vefPPNnHfeefv8p/t//+//cd55542aispCoP/wLSqRjczZUFrem9jpW425t/Xr19Paqs27m3rMwWmPK5M8Hg8ff/wxAHaziVm1NUPqcXXHKwBNFhuusoF/gDrLeqvlcnUbsN1sxmXTkn77G3+QDjMOPhaAzZs37zPPRAghhBBCiELwta99Dehd9qHr2/47kEmTJiXe/+KLL1JXV8dxxx3Hj3/8Y5566qlEUc5g+m4Fvuqqq/jpT38KSOvvQFJaAaj3WS9evJh//etfHHvsscydO5cjjzySysrKIc2h0D9hqWK325k2bRqbN2/m/fff56ijjtrnGLfbzc6dOwE4+OChJxLmzJnDJ598wgcffDDgMR9++GHiWJEb9BmAxZIAzIqyPgnAtra2AY/Tt/9CfiUAY7EoH61ZQywWQ1HgwHHjMBmH9rea1h1aIqykuh5lP99vLTYLZruFsD9Em9fL+PLcHDpd5XLhCQTp7OwkHApjztASmOlzj+U/f78V0LYBX3rppRm5rxBCCCGEEKPFF7/4RUpLS3n11VfZtWsXdXV17Nq1i1dffZWysrJBR5098MADVFVV8dvf/pZgMMjrr7++x4z3OXPmcPnll3PppZfusQRkb31bgQFp/d2PlCYAb7rppkS1nV7O+eGHHyaSYEOR6gQgwKJFi9i8eTPLly/nvPPOo6qqao/3P/XUU6iqSnl5OQcddNCQr7tgwQKeeuopGhoaWLVqFUceeeQe71+5ciUNDQ0oirLPoPhnn312v9c+/fTTAfjud7/L8ccfP+SYxMjpFYCSAMyO0orkEoDVMyZQNKZ8wONyzZZPttATn803paqSEsfArf970ysAS2sG/2uXs9RFp7+ddq+XmBrDoOTeoPDKIhfb3G2oqorb7aZ2bG1m7ls7mYqaibQ1bZcEoBBCCCGEKEg2m43zzjuPBx54gL/+9a/86Ec/4q9//SuxWIzzzjsPq3X/I3osFgu//vWv+eEPf8jTTz/N8uXLeffdd9m0aROxWIyPPvqIyy+/nMcee4wXXnhhwH0NVquVX/7yl5xxxhkA3H777al+qnkj5b/xqaqa+G/v/z3Yf+ly0kknUVNTQyAQ4Gc/+xnbtm0DtAUd//znP/n3v/8NaHP09s4sX3rppZx++uncdddd+1x30qRJLFiwAIB77rmHt956K/Fc3nrrLe69915AS0DW1/c/kF+MPokKwFJJAGZDUbENo0n71jRQAtDn8/HWW28B+VX919nZybbt2wEocziYUFEx5HPDwTAdjdrHq7Rm4qDHO8u07b+xmEqH1590rKNBsc2GxaTNiGxpzWwb8PSDjwNgxYoVeL252UYthBBCCCHESOzdBqz///21/+6toqKCSy+9lL/85S9s2LCBjo4OHn/8cebOnQtohR8/+clP9nuNkpKSfh+LPaW0ArBvueZoYjabuf766/nJT37C9u3b+e53v4vD4SAQCCS2LZ166qksXrw46WtfccUVNDY2snnzZn7xi18kVlSH4osjZs6cyeWXX566JyPSrrOzE5AZgNmiKApl5U7cLT2JGX97W7VqVeJrbOqCuRmMLn1isSjr1q0FwGhQmD22BmUIc/907btaUWPaH1KGUgHoKHGiGBTUmEqbx7PHUo1coSgKlS4XDZ1duN1u1JiKYkjigzYCM+Yey6oXHyQYDPLGG29w8sknZ+S+QgghhBBCjBZHHnkk06dPZ9OmTdx5551s2rSJ6dOnc8QRRwz7msXFxZxzzjmceuqpzJ8/nw0bNvDQQw/xm9/8Zkhj5cTAUpoAXLhwYSovl1L19fXcc889PPnkk7z99tu43W6cTieTJ09myZIlw36B2u12brvtNp5//nmWLVtGQ0MDAFOmTGHRokUsWbJkv/3qYvRJJACLh956KVKrtNyBu6VnwApAvf3XZLUw4XOzMhhZ+mzZ8ilerw+AqWPGYE9ynp37s94KuJKawSuODQYDjhIn3g4Pbo+X6cmFO2pUFmkJwEg4Qkdnxx6b39NpwszDsNichAJeXn75ZUkACiGEEEKIgnTRRRdx/fXX88Mf/hBIrvpvf+x2O1/96lf58Y9/TEdHB62trVRXV6fk2oWqoDJTpaWlXHLJJVxyySVDPuePf/zjoMeYTCbOOOOMRM95Kgw2I1Ckh6qqiRZgqQDMHn0O4EAJQL3aeOJhszHb9j9bIhd4PD1s366NJihzOKgrK036Gq3x+X+KwUhxVd2QznGWufB2ePCFQvhCIRzxCuZcUu50YlAUYqpKa0trxhKAJpOFKQd+no/ffZFXXnkFVVUTM3CFEEIIIYQoFBdeeCE33HAD4XAYg8HAhRdemLJrO529XUqWHPxdZbQpqASgEIPp7u4mGo0CUFLmyHI0hat8PwnAhoYGNm3aBOTH/D9VhQ0bPkZVwaDAzNrqpFp/de74BuDiqnEYTUOrHnSWFQFNALR5vDjKc++HqslgoMzpoM3jpaWlhRkzZkCG8nAzDj6Wj999kYaGBtavX8+BBx6YmRsLIYQQQggxStTX1/N///d/NDY2MnbsWMaPHz/oOZ9++imgdU4OJBqN8uijjwIwYcIEysrKUhNwAUt7AnDXrl1s2LCB9vZ2QqEQF110UbpvKcSw6RuAAUpkCUjWlJZrCUC3273P+/T2X4Apx8zNUETps3v37sTrbkJFBU7r8JJwrUlsANZZbBYsdgshf4g2r5fx5bn5Q7XS5aLN48Xn8+H1eff4S2E6TZ97bOLxK6+8IglAIYQQQghRkK699tqkjl+7di1nn302p556Kl/+8pc55phjGDduHACBQIAVK1Zw6623smrVKgC++93vpjzmQpS2BOCDDz7I7bffzsaNG/d4+94JwJ///OcsW7aM8ePH86c//Sld4QgxJPr8P4DiUqkAzBY9Adje3k4sFttj2KueAHRVlVI9I7e3a4cjYTZs2ACAzWxiYuXQt/72FYvGaIvPAEwmAQjgKHMR8rfT7vUSVWMYldwbrFtZ5GJTk5YAbW1pxTkpMwnAotIx1EyYTdOODSxfvpyrr746I/cVQgghhBAil5nNZqLRKP/617/417/+BYDNZsNms+3xOznAVVddJf/OTpGU/6bn9/tZsmQJ3/zmN9m4cSOqqib+68/8+fN55ZVXeOihh/j4449THY4QSWlvb088LpYKwKwpi7cAR6PRPX4AxGIxli1bBsDUY+bm/My1LVu2EAwGAZhRU41xmBtsO5s7iIQiAJQkmQB0lRYBEIupdHr9w7p/ttnNZlzxWZAtrS2DHJ1aUw44GoDVq1fj8/kyem8hhBBCCCFy0ZIlS9i0aRN33HEHZ555JtOmTcNoNNLT00NxcTFz5szhsssuY/Xq1fz2t7/N+d/7RouUVwBedNFF/Oc//wFg4sSJnH/++XR0dHD//ff3e/wJJ5xAVVUVbreb559/nlmz8mOjp8hNe1YASgIwW0rLe6sv29raEosd1q5dm0jSTl0wNxuhpYzfH2Dr1q0AlDsdVLlcw76WO97+C1BaMzGpc+0lDhSDghpTcXs8VLgyUz2XapUuF55AkM6OTsLhMGZzcluUh2vKAUez4oU/EAqFePvtt1m0aFFG7iuEEEIIIUQmPfTQQzz00ENJn/fMM8/0+/bp06czffp0vve9740sMGDRokUDFp2JXimtAHz11Vd58sknURSF888/n02bNvHzn/+ck046aeAADAZOOOEEVFXlzTffTGU4QiRtzxmA0gKcLWUVvcmwvnMA9e2/AFOOnpPRmFJt8+bNRKMxAKaOqRrR4gp9AQhASXVybdEGgwFHSXzpisc7/CCyrKpIe82oqoq7dd/ZkekyYfrnMJq0uY3Lly/P2H2FEEIIIYQQIhkpTQDq2eDJkyfz0EMPDbkC4+CDtU2e0gIssk2vADSaDDicubcRNV+U9akA7JsA1Of/1R4wCVdlaYajSh2v18POnZ8BUFNSTLHdNqLr6QtAnKVjsNiST1xr24DBFwrhC4VGFEu2FNtsWExGAFpbWzN2X4vNQf20eQCJ9nQhhBBCCCGEGG1SmgBcsWIFiqJw0UUXJdV+NXbsWACamppSGY4QSdPbS4tL7DJnIItKK3rbUNva2gDweDy8/fbbgDb/L5d9svkTVBUUJV79N0J6C3Cy8/90zrLeistcrQJUFIXKeBt1q7sVNZa5FoDJs48CtBZ1/fUqhBBCCCGEEKNJShOAzc3aL6EzZsxI6jybTat+CQQCqQxHiKTpFYAy/y+7ioptGI3atyc9obJy5UrC4TCQ2wnAnp5umlu0lt26sjIclpFVmqqqmqgATHYDsM5is2Cxa3G0eTwjiiebKuNtwJFwhI7OjkGOTp0pB34eQEZZCCGEEEIIIUatlCYAjUat/SoWiyV1nl51VVpamspwhEiaPgOwpEzm/2WTwWBILALRW4D1+X9mm4X6Q2dmLbaR0hd/GBSYVFU54ut5Oz0EerTtvcNNAEJvFWC7z0dUTe57+GhR7nRiiFfutrZkrg147KSDsNq1Nuo33ngjY/cVQgghhBBCiKFKaQKwuroagC1btiR13nvvvQfA+PHjUxmOEElLVACWSAVgtpWWxxdTxCsA9fl/E484EJM1MxteU83r9dDUpFXrjS0rw2Ya+SL2PTcAjyQBqCWwYjGVTq9/xHFlg8lgoMypJY5bWlsGOTp1jEYTk2YdAcgcQCGEEEIIIcTolNIE4FFHHYWqqgOuee6P1+vliSeeQFEUPv/5z6cyHCGSlpgBKBuAs64sPgfQ7Xazc+fOxB8Wpi2Ym8WoRmbr1m2ANvtvUmVFSq7Z2mcDcGntxGFfx17sQDFo1XPuXG4Djs8B9Hl9+LyZm2c45cCjAdi+fTs7duzI2H2FEEIIIYQQYihSmgA855xzAPjggw948MEHh3TO5Zdfnmi7/MpXvpLKcIRImswAHD30FuC2trZE9R/AlByd/+f3+2hsbACgtrgYexKLkvandbu2PMnqLMbmKh32dQwGA46SeNVlLicAi3oXmrRksA14ygG9f8Bavnx5xu4rhBBCCCGEEEOR0gTgqaeeyhFHHIGqqlx22WX88pe/xDPAL5IffPABS5Ys4W9/+xuKonDKKadw2GGHpTIcIZISi8V6ZwBKAjDryiq0RI7b7U4kAItrK6iaMi6LUQ3f9u07UOOLaSekqPoPoGWrlgAsq5004s3VehuwLxTGFwqNOLZssJvNuGxWAFpbM5cArKydTFGZNgZDEoBCCCGEEEKI0SalCUCAxx57jJqaGiKRCNdffz1jxozh6quvTrz/c5/7HLW1tcyfP5///ve/qKrK+PHjeeihh1IdihBJ8Xg8iQU20gKcfWV9KgD1hMrUY+aOOMmVDZFImN27dwMwpsiF0zqyzb99tWyLJwDHTh7xtfRFIJAfbcAdHR1EwpGM3FNRFKYcoLUBv/nmm6h6tlcIIYQQQgghRoGUJwDHjx/P6tWrE5WAgUCAzz77LPFL+/vvv09zczOqqqKqKocffjgrV66ksnLk2zCFGAl9/h9IC/BoUBqfARiNRhOt2VOPOTiLEQ3f7l27iUajAIwvL0vZdT0dPfg6tURd2dhJI76exWbBYteSk22ezM3PS7WqeBuwqqq0ujNXBThp1pGAVrW6efPmjN1XCCGEEEIIIQYz8hWU/Rg/fjwrV67kueee4+GHH2b58uW43e7E+10uFwsXLuRrX/saZ599djpCECJpepIJZAvwaKBvAdYpisLko+ZkKZoRUFV2fPYZAEU2K2WO1FWX6u2/kJoKQNCqAEP+djp8PqJqDKOS8r8TpV2xzYbFZCQUidLa0kptbW1G7jtp5uGJxytXrmTGjBkZua8QQgghhBi9Gjduz3YI/RqtcYn0SUsCUHfaaadx2mmnAeDz+ejs7MTlclFcXJzO2woxLPr8P4CSMmkBzrbyij0TgGMPmoyzPPe+d7S0tuD3+4F49V8KO5hbtjUmHpfVjrwCELQ5gB0N7cRiKh1eX6KdNpcoikKFy0VjZxet7lbUmJrYcJxOpVV1FJfX0t3eyKpVq/j617+e9nsKIYQQQojR7dnrH8h2CEIAaWgBHojD4WDs2LGS/BOj1h4VgNICnHWleyUAp3x+bnYCGaEdO3YAYDEaqUnx9z99/p+jpBKrMzXXthc7UYxasiyn24DjictIOLJHcj+dFEVh4kxtmdXKlStlDqAQQgghhBBi1Mi93i4h0qTvDMASaQHOurK9WoCnLZibnUBGwOv10N6uJZ/GlZViSHEVWmIDcArm/+kMBgVHsfaxz+VFIOUuZ+Lj3dzcnLH76m3Azc3NbN26NWP3FUIIIYQQo4u+9yAX/jvhhBOy/eESGTCsFuBbbrkl1XEk/PSnP03btYXYH70C0Ggy4HBZsxuMoKjEhqKAqoLJbqXukOnZDilpu3Zpm38VtARgKqmqmmgBTtX8P52rrAhvhwd/KIwvFMJhSd3W4kwxGQyUO524ezy0tLQwa9aslLZfD2TiXnMAp0yZkv6bCiGEEEIIIcQghpUAvOmmmxJbfVNNEoAiW/Q2weISe9pe32LoDAYDBoOBaDRG9UGTMFnM2Q4pKbFYjIYGLQFY4XJiM6d25GpXSychXxBIbQUggKOsd+6f2+Ohvrw8pdfPlDFFLtw9HgKBAN3d3RSXpH8ERUXNJFwlVXi6Wlm1ahUXXnhh2u8phBBCCCGEEIMZdgvwUMpIBztu7/cLkU2JBKDM/xsVdn/WTjQaA6Dy4InZDWYYWlpaCIXCAIwtLU399bf2XQCS2gpAi82Cxa5V/eXyHMBKlws9l9/ckpk2YG0OoFYFKHMAhRBCCCGEEKPFsEpSXn/99f2+/5577uGpp57CYDBw4okncvzxxzN16lScTider5ctW7bw6quv8tJLLxGLxTjrrLO48sorh/UEhEiV3gSgbAAeDVa/sSXxuGzW+CxGMjy7d+0CwGIyUlnkHOTo5OkLQABKayak/PrOMhchfzsdPh/RWAyjIfdGxlpMJkrsDjp9PlqaW5g2bVpG7jtp5uGsW/08u3fvZufOndTX12fkvkIIIYQQQggxkGElABcuXDjg+773ve/x9NNPM2vWLB599FEOOuigfo+75pprWLduHeeddx5PPfUU9fX13H777cMJR4iU0GcAlkgF4KigJwCt5S7MFbmVlPX7/bjb2gAYW1KCIQ0t5a3xBGBRRS1mW+o/Ps6yIjoa2onFVDp8PipdrsFPGoXGFLno9PnweDz4vD4czvS/libO2nMOoCQAhRBCCCGEENmW0pKOl19+mbvvvpvy8nJee+21AZN/ugMPPJDXXnuNsrIy7rrrLl555ZVUhiNEUqQCcPSIRKK8u1LboFo6uy7RSpsrdu/elXg8NsXLP3R6BWCqF4Do7MVODEbtR0QutwFXFRclHmeqDbhq7FQcrjIA3n777YzcUwghhBBCjC6KouTMfy+//HK2P1wiA1KaALz//vtRFIVLLrmE6urqIZ1TXV3NJZdcgqqqPPDAA6kMR4ikyAzA0WPDmt14e+ILLmaPJxqNEo1GshzV0DU2avP5Sh12HGlYXhKLxmjdricAU7sARGcwKNhLtNZlt8cD5OYsO7vZTJFN2+rd0tySkXsqisL4afMAeOeddzJyTyGEEEIIIYTYn5SupXz33XcBmDt3blLnHXLIIYBUSojsicVie2wBFtmlt/8qBoXSGeMACAZDOByp3aSbDp2dnfh8fgBqS0rSco+2Xa1EQlpCtGzslLTcA8BV6sLb3oM/FMYbCuO0WNJ2r3SqKiqiJxCks7OTYDCI1WpN+z3rpx3Kpg9eZePGjXR1dVGSpteCEEIIIYQY3U7/+q3Ujp+Z7TD20bhzI8/++fpshyEyKKW/Tbe0aNUVwWAwqfP04/Xzhcg0j8dDLKZtnC0pkxbgbHs7ngAcc0AdJqeWrAmFgjgco/9z09jQAIBBgeo+7aep1LSlIfG4Ynz6Fls4ynrn/rV5PDjLy9N2r3SqKnKxtdUNQGtLC3Xj079Upj5eAQjaH8eOP/74tN9TCCGEEEKMPrXjZzJhxueyHYYQqW0BLivTZh4tW7YsqfP040tLS1MZjhBDplf/gbQAZ1tPt5/1H2oz9CYeNT3x9mAwlK2QhkxVYzQ1aa25lS4XJmN6Nuc2fbIbAKPZSvGYurTcA8Bis2BxaAnYXJ4DWGSzYo+3YjdnqA147KQ5GIza39ikDVgIIYQQQgiRbSn97fSII45AVVUeeeQRVq1aNaRz3nrrLR555BEUReGII45IZThCDNkeCUBpAc6qd1duJRbT5s1NXthbKp9sZXE2uN1uQmFtYUlNGls+m7ZoCcDycZMxGIxpuw+As1SrAuzw+YjGq2Rzj0JVkVaN2d7eRiSS/nmSFqudsRMOAGS8hRBCCCGEECL7UpoA/J//+R8AotEoJ510Evfffz/hcP/bO8PhMA888AAnn3xy4pexyy+/PJXhCDFkfROAJVIBmFWrl2vtv1aXjfFzJ2IwKIDWAjzaNTRoyz9MRgOVLmfa7qO3AJfXpa/9V+eMtwHHYiodPl/a75cuY4p6n0dra2tG7jl+2qEAvPfeexlJOgohhBBCCCHEQFI6A/Ckk07ikksu4U9/+hNer5dvf/vb/PjHP+boo49m6tSpOBwOfD4fW7ZsYcWKFXR1daGqWqXPJZdcwoknnpjKcIQYss7OzsTjYpkBmDWqqvJWPAE44cipGC1GLBYjgUBk1LcAR6ORxBzT6qKiROIy1XrauvG29wBQUTc1Lffoy17sxGA0EIvGcHu8VLpcg580CpXY7VhMJkKRCM1NTdTW1qb9nvXT5rHqxQfx+Xxs2LCBOXPmpP2eQgghhBBCCNGflK/U/P3vf4/D4eDee+9FVVU6Ozt54YUX9jlOT/wpisJVV13FnXfemepQhBiyPSoApQU4a3Zub6dpdycAk47R2n/NVhOBQGTUVwC2trQmFsnUlBSn7T56+y9kpgLQYFBwlDjxtPfQ5vEAY4D0JDfTSVEUxhS72NXeSavbTTQSxWhKb/v0+D6LQN555x1JAAohhBBCCCGyJuUT6hVF4e6772b58uWcccYZWCwWVFXd5z+r1cqZZ57JG2+8wV133YWi5N4vlCJ/6AlAo9GAw2XNcjSFS9/+CzDp8zMAsFi0v1OM9hmATc3a8g+LyUhpGrcVN30S3wCsKJSPnZy2+/SltwH7Q2G8odFdibk/1UVaYjYWjdHamv5lICXltZRUjAVkEYgQQgghhBAiu1JeAag7+uijOfroowmFQqxZs4aGhgY8Hg8ul4tx48YxZ84cLBZLum4vRFL0BGBxqV2S0Vm0Op4ALK2voKy+AuhNAIZGcQtwNBqhtdUNwJiiItL5EtIrAEuq6jDbMtOuri8CAWjr8eKsyM0keamjtw24qamZmky0AU+fz9pVz8oiECGEEEIIIQQATU1NLF++nHfffZf33nuP999/PzGWbNu2bUycODEt901bAlBnsVj43Oc+l+7bCDEifROAIjsi4SjvrdoK9Fb/AZitWptmcBS3ALe2uhPtv2OKi9J6r0wuANGZbRYsDishX5A2r5f6ivKM3TuVFEVhTJGLXR2dtLpbM9IGXD9tHmtXPcvOnTtpbGzMyOxBIYQQQgghxOh1//33c/PNN2f8vilvARYiF+nZ9uJSWQCSLes+2InPq1X5TT6mNwGoVwDGYiqRSP9bxbOtqSne/ms0UuZIXxI55A/StlPbYJuJBSB96W3AHV4f0XiyMxdVxxO0Whtw+rcB18c3AYO0AQshhBBCCCG0woT6+nrOPPNMbr31Vu6+++6M3FcSgELQpwJQFoBkjd7+qxgN1B/Rm9wyW3oLlUfjHMBoNIrbrbX/VhW50tpC3ry1EeILlMrHZ64CEHrbgGOqSrvPl9F7p1Kpw4ElXvWnJ27TqXr8TMwW7fuKJACFEEIIIYQQ119/PTt27OCpp57iJz/5CQsWLMjIfSUBKAS9CcASaQHOmtXLtQTguLkTsBX1fh4s1t4WzdE4B9DtbiUajQJQXZy+7b/Q2/4Lma8AdJQ4MRi1HxnaNuDcpLUBa1WAehtwOhmNJuqmzAUkASiEEEIIIXLXokWLUBSFm266iUAgwM0338ysWbOw2+1UVVVx7rnnsmHDhn3OW7p0KYqiJAolVq5cyWmnnUZVVRV2u505c+Zw5513Jn6nGsgLL7zA6aefTk1NDRaLhZqaGr74xS/y3//+N2XP8eKLL0ZRFC6++GIA/v73v3P00UdTXFxMUVERRx11FP/85z8HPF9/nkuXLmX37t1cccUVTJ48GavVyty5cxPHGY3pHUM0EEkACkGfFuAyaQHOhq4OHx+v1ZJbk/q0/0JvCzCMzjmAzc3NAJiNRsqc6U0gN27eBYCtqAx7cUVa77U3RVFwlDgBaPN4ATWj90+lMRluAx4/9RAA1q5dSyiHtygLIYQQQggRDAY57rjjuOmmm9i6dSsWiwW3280TTzzBvHnzeOmllwY896mnnmLhwoU8//zzRCIRIpEIa9eu5ZprrmHJkiX9/ltZVVUuu+wylixZwnPPPUdraytOp5PW1laeffZZTjnlFK688kpUNbW/n1x22WV85StfYfXq1SiKgsfjYdWqVZxzzjnce++9+z138+bNzJ07l/vuu4/m5mbMZnNKYxsuSQCKgqeqqrQAZ9k7Kz5NfMPuuwAERncLsKrGEtt/q1zOtG+Q3v3xZwBU1s/IyrZqfQ6gPxTGOwqrMYeqLMNtwOMmHwxAKBTq96+iQgghhBBC5Ir77ruPNWvW8PDDD+PxeOjq6mLNmjXMnz+fYDDIeeedN+C/sb/xjW+wePFitm7dSkdHB11dXdx+++0YjUZefPFFbrzxxn3OufPOO3nggQcA+OEPf4jb7aajo4PW1lauvfZaAH73u99xzz33pOw5Pvvsszz88MPcd999dHd309XVxdatWxOtutdddx3t7e0Dnn/ttddSW1vLihUr8Hq9eDye/VYOZookAEXB6+npSZQbyxbg7Fj9xqcA2Irt1B40fo/3GY0KRpP2rSo4ypJOHR0dRCIRACqL0rv9NxQI0bJN+0FaNXF2Wu81EGdZ73PUqgBzU6bbgOumHJx4/MEHH6T1XkIIIYQQQqRTV1cXv//977nooosSlW1z5szhxRdfpKqqis7OTu64445+z62rq+OZZ55h0qRJADgcDq655hpuuukmAO666649Ems+n4+f/exnAFx11VXcdtttlJWVAVBeXs5vfvMbvvWtbwFw88034/f7U/IcOzo6+OMf/8hll12Gw6F1CU6aNIl//OMfWCwW/H4/zz///IDnm0wmXn75ZY466qjE26ZOzewIp/5IAlAUPL36D2QGYDaoqsrbb2rz/yYeNT0xZ64vi0Wr1gqNshbglhatfdSgKJQ709s+3vTJbtSotn23auKstN5rIGarGYvDCoDbm7sJQMhsG3BxWTXFZTUAvP/++2m9lxBCCCGEEOk0YcIELrjggn3eXl5ezuWXXw7AE0880e+51157LVardZ+3X3311TgcDgKBAM8991zi7S+99BKdnZ0YjUZ+/OMf93vNn/70pxgMBtrb23n55ZeH85T2UV9f3+9zHDt2LIcddhgA69atG/D8iy66iOrq6pTEkkqSABQFT5//B1BcKjMAM23HVjfNDV0ATPr89H6P0ecAjrYKwJaWFgDKnQ5M/SQuU0lv/wWomjAzrffaH70NuNPrIxKLZS2Okcp8G/AcQCoAhRBCCCFEblu4cOGA44gWLlwIwPbt2/ttkV20aFG/57lcLg499FBgzz+Yv/feewDMnj2bmpqafs8dN24cs2bN2uP4kZo/f/6Az3HcuHHAnoVEezvyyCNTEkeqSQJQFLy+35ikAjDz9O2/ABP3mv+nMycSgKOnAtDj6UmUmFcWudJ+Pz0BWFQ5FpurNO33G4jeBhxTVTq8vqzFMVKKolAVbwN2u91pbwPW5wBu3rwZTw5vURZCCCGEEIVNT4AN9r7+umyGcq5eZNH3Gvs7D7TW4r3PHYmi/Yx3stlsAITD4QGPqaqqSkkcqSYJQFHwpAIwu1a/oSUAyydVUVpX3u8xFqveAjx6KgD19l+AKlcGEoAb4wtAslj9B+AodiTatNtyPJFVHW8DjkajaW8D1ucAqqrKmjVr0novIYQQQgghRPYYjcZsh9AvSQCKgiczALMnFIzw/lvbgH23//altwCHQsGUr3cfrtZW7a9LxTYrVrNpkKNHxtflpWN3G5C9+X86RVFwlDgBaPN6gdHx+RiOTLYBj514UOKxzAEUQgghhBC5qqGhYUjv668KbijnjhkzZp9r7N69e78x7dq1a59zxb4kASgKnp4ANBoNOFz7DiQV6bPm3R0E/Frp9OQFA1e2Waxagk1VR0cVYDAYpLNTm1uY7u2/0Fv9B1A1ITsbgPvS5wD6Q2G8o2wuYzIURUksA2l1tyY2OqeD3VlMZe1kQOYACiGEEEKI3LVs2bJB3zdx4kTKy/ft7hroXK/Xy7vvvgvAvHnzEm+fP38+ABs2bBjwD/YNDQ18/PHHAIk5gqJ/kgAUBU9PABaX2gcc9CnS4634/D+j2Uj94VMGPE5PAAIEA4G0xzUYd5920aoMzv9TDEYqxk9L+/0Go88BBHB7cnsbcHVxMaBtA25pTs3MkIHocwAlASiEEEIIIXLV9u3b+cc//rHP2zs6Orj//vsBOOecc/o99/bbb++3oOO3v/0tPp8Pm83Gaaedlnj7CSecQFlZGdFolF/84hf9XvPmm28mFotRUVHBCSecMJynVDAkASgKXiIBWCLtv5n21rJPAKibPxmLY+DqS2ufBGBgFCwCaYm3/9rMJor6WWOfag0bdwJQVjsRszX7r1Oz1Zz4fLXleAKw1G7HFm/hbmxsTOu96uKbgHft2pWyAcVCCCGEEEJkUklJCd/85jd55JFHEosw1q5dy8knn0xzczOlpaVcc801/Z772WefceaZZ7J9+3YA/H4/d911FzfccAMAV1999R6Vgw6HI/G+e+65hx/96EeJ39/b29v5wQ9+wO9//3sAbrzxRuz27P+uNBSxWAy32534r+9ego6Ojj3eF4vFUnbf9A6uEiIH6F9sxWWyACSTWpu7+XRTMwCTjxl4/h+AxWpOPA4Gs1sBGIvFaGvT5vFVulyQ5qJRVVUTFYCVWZ7/15ezzEXIF6TT5yMSi2Ey5ObfkxRFobq4mB1t7bS1tREKhbBYLGm5l14BCPDhhx9y4oknpuU+QgghhBBCpMvll1/O0qVLufDCC7n00kux2Wx0dWnjkaxWK48++ig1NTX9nvvggw9y3nnnMWnSJEpLS/F4PIkxPCeddBI33XTTPudcffXVbNq0iQceeIDbbruNX//615SUlNDV1ZVIjl1xxRVceeWV6XnCafDZZ58xadKkft/XtwUaYNu2bUycODEl983N39iESCGpAMwOffsv7H/+H4DJZMBg0DJtgUB2KwA7OtqJRrUfNJUZ2P7b2diOt0Pbtls1YfQkAF3xNuCYqtLhze0qwOoSrQ1YVVWam5rTdp+a+tkYjVoyWxaBCCGEEEKIXGS1Wnn99de56aabmDhxIsFgkMrKSs455xzee+89TjrppAHPPeuss1i2bBmnnnoqRqMRk8nEQQcdxB133MG///1vrP10VymKwv3338/zzz/PqaeeSkVFBT09PVRUVHDaaafxwgsv8Lvf/U7GeQ2BVACKgqcnAGUDcGatjs//c40ppmpG7f4PVsBqM+H3hbNeAeh2uwEwKAplzvRXjX62dlvicfXkg/ZzZGbZix0YjAZi0RhtHi9VGViGki7FNisOiwVfKERjYyPj68en5T5mi5Xq+pk0bFsrCUAhhBBCCJGzbDYbN954IzfeeGPS5x511FE899xzSZ+3ZMkSlixZkvR5yXjooYd46KGHhn2MqqpDus/EiROHfGwqSQWgKHiJFmBJAGZMNBpLVABO+vyMIf21xmLR/l4RzHIFoJ4ALHPYMRrS/1emzz7aCoDFUURpzYS032+oFEXBUeIEwO31Apn/AZY6CtUlWgKzo6ODQBoXzdTF24A//PDDrPzQF0IIIYQQQhQmSQCKgqaqap8twDIDMFM2rm2gu9MPwKRB5v/pLDYtAZjNJSCBgB9PfOlFRQbaf6G3ArBmyhyUUTZnz1mmfQwCoTDe4L7bvHJJTXwbMEBTU1Pa7qPPAezo6GDbtm2DHC2EEEIIIYQQqTG6fpsUIsM8Hg/RaBSQCsBMWr1c2/6LojDp6OlDOidRAZjFFmC9+g+gwuVM+/18XV5at2sz6aqnjJ72X52zrLft153j24CdVitFNm3mSDq3AY+b1Pt5/Oijj9J2HyGEEEIIIYToSxKAoqC1t7cnHssMwMxZFZ//V3tQHY7yoVXSWW3a8oRwOEIsFk1bbPujJwBtZhPONG2K7Wvnuu2Jx9VT5qT9fskyW81YHFrSrM3jyXI0I6cvA+nu6sbn9aXlHpVjp2C22ABJAAohhBBCCJFqK1eupKamJqn/HnvssWyHnRGyBEQUNH3+H0BxibQAZ0JPt58NH+4CYNIx+9/+25fF2vvtKhAI4nBk9vOlqjHa2toAqHA6IQNLpnbE5/8ZzRYq64fWKp1pzjIXIV+QTp+fSCyGaZS1KSejuriYLc2tADQ1NTJ5ypSU38NoNFFTP4udWz5g7dq1Kb++EEIIIYQQ6bB06dJhnbdo0aKMzr4OhUI0NzcndY7f709TNKNL7v6mJkQK6AkdgJJySQBmwjsrthKNxgCYPMT5f9DbAgzZaQPu7OwkEtEqDzM2/y+eAKyaMAujOf0Vh8PhircBx1SVDm9utwHbzWZKHFolcGNjU9r2mtROOACANWvWyCIQIYQQQgghUkhPOCbz38UXX5ztsDNCEoCioOkLQABKZAlIRqyOt/9ai2yMmzv0rbZWW98EYOYXgejtv4oC5c70v1YC3gC7N+4EoGba3LTfb7jsxQ4MRu1HSa7PAYTeZSAej4eenp603GPsxAMB7fvPrl270nIPIYQQQgghhOhLEoCioPWtACyVCsC0U1WVt+ILQCYeNQ2DyTjkc82WPVuAM01PAJba7ZiM6f/WuWPNp6jxSsmxMw5N+/2GS1EUHKXaQpQ2j5e0lc1lyJjiIpR4e3djU3qWgdTGE4AgcwCFEEIIIYQQmSEJQFHQ9ApAi8WEzW7OcjT5b/unrTQ3dAHJzf8DMBoVTGbtW1amW4CDwSDd3Vo1WCa2/wJse09LlBrNVsZMOiAj9xwufRtwIBzGGwxlOZqRsZpMlMXnSzY1pacNeEzdNIwmraV7zZo1qb+BEEIIIYQQQuxFEoCioOkVgCXlDhQlA1sdCpze/gvJzf/TWeOLQDJdAdi3UjRT8/+2xhOANVPnjNr5fzpnae/HJB/agPVtwH6fn86uzpRf32SyUD1ee/1LBaAQQgghhBAiEyQBKAqaXgFYWibtv5nw1jItqVUxZQwl48qTPl/fBJzpGYB6AtBiNOKyWtN+P09HDy1btfbT2lHc/qszW81YHNrHpc3jyXI0IzemqAhD/A8CTY1NabnH2PgikI8++kgWgQghhBBCCCHSThKAoqC1t7cDUCIJwLQLBMJ8sHo7AJOGUf0HYLFqbdqZbgHWE4BlTgeZKBTd9n5vpeRonv/Xl6tMqwLs9PmJxGJZjmZkzEYj5fFW76amprQk6PQ5gK2trVqrsRBCCCGEEEKkkWnwQ4TIX5IAzJw1b+8gGIwAMDnJ+X+6bLQAe72eRMVhuTMz8/+2rN4IgMVRRMX4aRm550g5y4po391GTFXp8HqpKirKdkgjUlNcjLtH+9y3t7dTW1OT0uuPnbTnIpDa2tqUXl8IIYQQQowOjTs3ZjuEfo3WuET6SAJQFDRJAGaOvv3XaDFRf9iUYV1DbwGOxWKEw2HM5vQvbmlra088Lnem/3USi8XYsvpjAOpmH47BMPRNydlkL3ZgMBqIRWO4PbmfAKwqcmE0KERjKo2NjSlPAFbXzcRgMBKLRfnoo4846aSTUnp9IYQQQggxOjz75+uzHYIQgLQAiwKnJwBlBmD66QnA8Z+bjNk+vKUWegIQMtcGrLf/2s1m7Jb0JxwbNu7E26HN0Rt/4JFpv1+qKIqCo1SrkGzzeEnL+twMMhoMVMYXvjQ3NROLpfb5mC1WqsZp1Z2yCEQIIYQQQgiRblIBKAqWz+cjENCSSFIBmF7NDV1s+6QVGH77L+yZAAwEgrhc6a0yU1U1kSTORPUfwCdvadV/KAp1sw/LyD1TxVlWhKeth0A4jCcYysjClHSqKSmmubuHcDhMS0sL5RXJL67Zn7ETD6R550bWrFmT0usKIYQQQojsk0VvYrSRCkBRsPTEDkgCMN1Wv9G71GLyguEtAIHeGYCQmU3A3d1dRCLa3MJMzf/bvGoDAGMmHoDNVZqRe6aKs9SVeKxVAea2CpcLk1H7Mbm7YXfKr6/PAWxsbKSlpSXl1xdCCCGEEEIInSQARcGSBGDmrFq6GYCi6hIqpw1/lprZYkps4Q0G0t8C3Hf+X1kGKgB73N00btoF5Fb7r85sNWN1aFV/bo8ny9GMnEFRGBOfZdjU1EQ0Gk3p9cdO6F0Esnbt2pReWwghhBBCCCH6kgSgKFh9E4AyAzB9IuEoq9/8FIApi2ah6Bm8YVCU3jbgQAZmAOrz/4psViym9C/j+Hh57yy4+oOOSvv90sFZpiXMunx+IrFYlqMZueriYgCikSitra0pvXZNfe/Xg7QBCyGEEEIIIdJJEoCiYHV0dCQel5RLAjBd1ry7A59Ha9edsmjWiK9ntWqLOPz+9CYAo9EonZ3aayRT8//WL9WSQCVjxlM2bnibkrPNWaa1AcdUlQ5v7rcBlzsdmI1a8repsSml17bYHFTWap/ndevWpfTaQgghhBBCCNGXLAERBUuv7gIoKZUEYLqsfF1r/zWYjUw4ctqIr2e1maCLxAKXdOns7Ehsfs3E/L+etm52rNkKwMR5x46oUjKb7MUODEYDsWgMt8dLVVF6F7Wkm6IojCkuYndHJ62trUQjUYwprAatmTCb1oYtkgAUQgghhMgzL7/8crZDGLLZs2czbty4bIch0kwSgKJg6RWAZosRh9OS5Wjy18r4/L/6w6ZgddlGfD2rTasADAT8I77W/ujz/wwKlDrSnyD+ePlaiG8KmzTv2LTfL10URcFR6sLT1k2bxwOoQG4mM3U18QRgNKq1AdfUDn+O5d5q62exdtWzbNu2DY/Hg8vlGvwkIYQQQggx6p144onZDmHIXnrpJUkAFgBpARYFS68ALCl15Gy11WjXsKuDbZ9oc9OmLBx5+y/EKwCBSCSa2NCbDonXh92O0ZD+18eGpR8CUDymjvIcbf/V6W3AgXAETzCU5WhGrtTpwGLSXndNTY0pvXZNfe/Xxfr161N6bSGEEEIIIYTQSQWgKFj6EhDZAJw+evsvwJRjU5QAjM8ABK0K0OVKfYtpOBymu7sbgLIMtP92NLaz/QNtUcqkecflfEJaTwACtHm8uKzWLEYzcgoK1SXF7Gxrp9XtJhqJYDSl5sdn7YTZicfr16/n8MMPT8l1hRBCCCHE6HDD6bcyvXZmtsPYx+bGjfzs2euzHYbIIEkAioKltwBLAjB99ARgaX0F5ROrUnJNvQIQtDmA6UgA9t0QXZGBBSBr/vtO4vG0I05O+/3SzWwxY3XaCHoDuD0eJlSUZzukEasp1hKAsWiM5pYWxo4dm5LrukqqcJVU4elqlTmAQgghhBB5aHrtTOZN+Fy2wxBCWoBF4dJbPEslAZgWgUCY91ZqSy2mLJqVsqo2fQagdo/0LAJpj782TAYDxfaRzy3cn1gsxof/0RKA1VPmUDJmfFrvlynOUq0KsNPnJxKLZjmakSt12LGa423AKd4GrFcBSgJQCCGEEEIIkS6SABQFK1EBWC4JwHR4/61tBIPajL6pi2YPcvTQmc1GDPGZfH5/mhKAHVoFYKnDnvZ23O0ffkpnk3a/6Ud+Ia33yiS9DVhVVTq8vixHM3KKolBdrFWbtrW5iYRTN39SnwP48ccfp3WupRBCCCGEEKJwSQJQFKzEDMBSSQCmw8rXtPZfk81M/eEpXGqh9LYBp6MCMBQK4fF4gcxs/333XysBMFlsTMzh7b97sxc7MBi1HzFt8Y9nrqsuLgYgFlNpbm5O2XVr6rUEeSAQYOvWrSm7rhBCCCGEEELoJAEoCpLf78fn06qSSqUCMOVUVWXF65sAmHjkNEx9Fnekgt4GnI4EoF4ZClCW5gRgV3MHG5atAWDqYSdhseXPa1FRFBwl2gKVNq8XULMbUAqU2O3YzNprr6kpdW3AfReBSBuwEEIIIYQQIh0kASgKUt8kj1QApt6OrW4ad3UCMOXY1LX/6qxWvQLQn/Jrd8Tbf40GhSJ7erfXvv30m8SiMQBmH/ultN4rG/Q2YH8ojDcUznI0qdHbBtxGOEXPqaJmImaLNmtSEoBCCCGEEEKIdJAtwAXCaDSOimuMFl1dXYnHpeXOtM95ywT9OYyG56Jv/wWYsmg2kNqYeisAgyl/vu3tWnK41G7HoKTvbyShQIh3n1sFwNiZn6OsdlLa7pUtjvgiEIB2jxdnuSWL0YyA0vv/q0uK2dHWjqqqNLc0M378yJe2GI0mqsfPYNena1i3bl1efa/NJvk4jn7650g+V7lFPl+jn3xt5Sb5fAkh0k0SgAWirKxsROcbjcYRX2M0CYVCiccVVcWYzTmamOiHyZTadtvhWLV0CwBV02spqytP+fVtdu3zFYvFUNUYVktqKvVC4TA9PT0AlDmdGNKYTH3vuVX4u7U29AOPO2dUJG5TzWq3YrFbCPlDtHm9TKisyHZII2JQDJQ4HNgtZvyhMM3NzUyZPDkl1x438UB2fbqGDRs25NX32mzJt59Z+a44Pl9TjH7ytZVb5Gsrd8jXlhCFZdOmTTz99NMsXbqUtWvX0trais1mY+rUqZxyyil85zvfobq6OuX3lQRggejb8pqM4uJijEYj0WiU7u7uFEeVPTt27Eg8dhVbCIdD+zk6NyiKgslkJhIJo6rZm7fm6Qnw/mptkcGURbOIxVIfi8Xa+xfS7u4eSkpSU6nX2tKSeFzqsBNL08cxHAzxxiOvAlBeN5W62Ydn9XOWTo4yFyF/O+1eL5FoNK1J1bRRtORfTI2Bqi0D2e5uo83dhsfjxWId+R8QxoyfCUBzczMbN25Myw/8QpCvP7PyldFopLi4mO7ubqLRaLbDEfshX1u5Rb62cod8bQ2PJEtFLluxYgWf//zn93hbSUkJPT09fPDBB3zwwQfcf//9PP300yxYsCCl95YEYIFIxQ//fPoHhNvtTjwuKbXnVfJFVdWsPp+339xCNKLNtZuycCbpWP5g7bNUJBDwp+wv3PpmaIOiUGyzka7FFe89uwpPu/aPvHlLvo5iyN9xrM5SF50N7cRiKh1eHxUuZ7ZDSp6K1gYcfzmMKS5iu7st0QZcV1c34lvUjJ+VeLxmzRqOP/74EV+z0OXTz6x8F41G5fOVQ+RzlTvkayu3yOdKiMIQDocxmUyceeaZfPWrX2XRokUUFxcTDAZ56aWXuOqqq9ixYwenn346mzZtSmlhQP7+1inEfuiJHqPJgMOV3kUPhWbl658AYC2yMW5eeubaWWy9f7vw+1O3Cbg9vgCkxG7DYEhPpVrQF+CNv/VW/02Yc0xa7jNaOEqcKPGPpbYNOPcV26zYLVoSurmpOSXXrB4/I9EGLotAhBBCCCGEyE9Tp05l48aNPP7445x++umJYhar1cppp53Gf/7zH2w2G11dXTzwwAMpvbckAEVB0hOApWWOvJy9li2qqrJqqbYAZNLnZ2A0p2eYsclkwGTSvn0FAqlJAEajkUTrRakjfZuh33jkVbzt2pzBQ0+9NK+r/wAMBgP2Yq3qr92THwlAUKgqim8Dbm8jEo6M+IpWu4vy6gkArF+/fsTXE0IIIYQQIpUWLVqEoijcdNNNBAIBbr75ZmbNmoXdbqeqqopzzz2XDRs27HPe0qVLURQl8Xv3ypUrOe2006iqqsJutzNnzhzuvPPOQatgX3jhBU4//XRqamqwWCzU1NTwxS9+kf/+978pe44XX3wxiqJw8cUXA/D3v/+do48+muLiYoqKijjqqKP45z//OeD5+vNcunQpu3fv5oorrmDy5MlYrVbmzp0LQF1dHVOmTBnwGrNmzeLwww8H4L333kvZcwNJAIoCpScAS8rSl+gpRJs3NOJu0ZJbUxbNGuTokendBJyaBGBHRyd653SZMz2vi47GdlY9vgyA2unzqJ9zdFruM9o4y7RtwJ5gkEA4nOVoUmNMPAGoxlRaWlsGOXpoaupnA1IBKIQQQgghRq9gMMhxxx3HTTfdxNatW7FYLLjdbp544gnmzZvHSy+9NOC5Tz31FAsXLuT5558nEokQiURYu3Yt11xzDUuWLNljWadOVVUuu+wylixZwnPPPUdraytOp5PW1laeffZZTjnlFK688sqUj8G67LLL+MpXvsLq1atRFAWPx8OqVas455xzuPfee/d77ubNm5k7dy733Xcfzc3NmM3JLeqsrKwEIBIZeaFBX5IAFAVJEoDpseK1zYnHUxamOwGotQGnLgGoz/+DErs9Jdfc24v3PkM0FAFF4YhzriqY6lNnqSvxOF/agEvsNqxm7TXY3JyaNuCaeu1rZsuWLXjz5OMkhBBCCCHyy3333ceaNWt4+OGH8Xg8dHV1sWbNGubPn08wGOS8886jqamp33O/8Y1vsHjxYrZu3UpHRwddXV3cfvvtGI1GXnzxRW688cZ9zrnzzjsTrbA//OEPcbvddHR00NrayrXXXgvA7373O+65556UPcdnn32Whx9+mPvuu4/u7m66urrYunVrYinHddddl8gp9Ofaa6+ltraWFStW4PV68Xg8+60c7CsSibBixQoADjzwwJE/mT4kASgKkiQA00Nv/605aDzOyqK03ktfBBII+FNyvfZ2bVN2sc2OMQ3z/zYs+4iNb2iVXTOPPp2Kumkpv8doZXVYMcU/X2150gasKL1twG63m2hk5IO7aydoFYCqqrJx48YRX08IIYQQQohU6+rq4ve//z0XXXRRorJtzpw5vPjii1RVVdHZ2ckdd9zR77l1dXU888wzTJqkzYp3OBxcc8013HTTTQDcddddeyTWfD4fP/vZzwC46qqruO222xJboMvLy/nNb37Dt771LQBuvvlm/P7U/G7Y0dHBH//4Ry677DIc8fFQkyZN4h//+AcWiwW/38/zzz8/4Pkmk4mXX36Zo446KvG2qVOnDune9957L01NTRgMBr72ta+N7InsRRKAoiB1dGjJnlJJAKZMZ7uXdR/sAmBqmtt/obcCMBgMoqqxEV0rGo3S3dUFQKkj9dV//h4/L9z1FAD24nLmn/E/Kb/HaKdXAbZ7vXmzdbu6SHtOsWiM1tbWEV+vNt4CDNIGLIQQQgghRqcJEyZwwQUX7PP28vJyLr/8cgCeeOKJfs+99tprsVr3XcJ59dVX43A4CAQCPPfcc4m3v/TSS3R2dmI0Gvnxj3/c7zV/+tOfYjAYaG9v5+WXXx7OU9pHfX19v89x7NixHHbYYcD+/71+0UUXDWt77/vvv594nldddRWzZ88e5IzkSAJQFKS2tjZAKgBT6a3lWxKJnXTP/4PeGYCqCoFAcETX6urqJBaPPR3z/16480k8bdqCkSPPvRqrI73VkaORPgcwEo3RlaK/zGVbqcOBxaQtuklFG3BRWTWOonJAFoEIIYQQQojRaeHChQOOMlq4cCEA27dv77dFdtGiRf2e53K5OPTQQwEtCabTl2DMnj2bmpqafs8dN24cs2bN2uP4kZo/f/6Az3HcuHFAb1FRf4488sik7/nZZ5/xxS9+Eb/fz2GHHcavfvWrpK8xGEkAioITDAYT87UkAZg6K+Ptv45yF7UHjU/7/Wz23kGqIy311r95K6R+/t9HL7/H2le0H2KT5h3LxEMWpfT6ucJR4tQ+wORZG7BLS2y2trYSi46sElVRlMQcQKkAFEIIIYQQo5GeABvsff11yAzl3JaW3gV7+jX2dx5orcV7nzsSRUUDF2zYbDYAwvtZblhVVZXU/RobG1m8eDG7du3igAMO4IUXXui3UnKkJAEoCk7fTL20AKdGNBrjrWWfADB54UwUQ/q/tegVgDDyBKD+16kimw2TMXWxdza18+87ngTAUVrF0ed/v2AWf+zNaDJiL9K+3vJlEQjAmOJiQGsjd7e5R3y92ngCcP369USjI58rKIQQQgghhMgso9E45GNbWlo4/vjj+eSTT5g6dSqvvPIKFRUVaYlLEoCi4OjtvyAVgKmy/sNddHdqSbhMtP8CWKwm9DzjSBKAsViMzs7Uz/+LRWM8devfCXoDoCgs/NpPsDqLU3b9XKTPAewOBAileKV9tpQ5HYmkcSragGvii0B8Ph/bt28f8fWEEEIIIYRIpYaGhiG9r78quKGcO2bMmH2usXv37v3GtGvXrn3OzQVtbW0sXryYjz/+mAkTJvDqq68O2OqcCpIAFAWnbwWgJABTY+XrWvuvYjQw6fMzMnJPRemtAhxJArCrq4tYTGvdTOX8vxX/eI3PPtoKwEHHn8fYGYem7Nq5yhGfA4iqLQPJBwZFoSq+DKSlpQU1NrIFJ7IIRAghhBBCjGbLli0b9H0TJ06kvLx8yOd6vV7effddAObNm5d4+/z58wHYsGEDTU1N/Z7b0NDAxx9/DJCYI5gLOjo6OOGEE1i7di1jx47ltddeo76+Pq33lASgKDhSAZh6K1/fBEDdvInYSzL3MU1FArCjo3c4bakjNbHv/vgzXv/TfwEor5vKoad9MyXXzXU2pw2jWSuHb/P6shxN6oyJzwiJhCO0tbcNcvT+VdZOxmiyAJIAFEIIIYQQo8/27dv5xz/+sc/bOzo6uP/++wE455xz+j339ttvJxQK7fP23/72t/h8Pmw2G6eddlri7SeccAJlZWVEo1F+8Ytf9HvNm2++mVgsRkVFBSeccMJwnlLGdXd3c9JJJ/HBBx9QXV3Na6+9xuTJk9N+X0kAioKzxwzAckkAjlRLUzebN2h/jZmyMDPtvzp9EUhgJAnAdu31UGSzYk7B/L+gL8iTP/sbsWgMo9nCoq//FKPZMuLr5gNFUXDE24DbPN7E1uhcV+50YjBosx1bRzh42GgyU103HZAEoBBCCCGEGH1KSkr45je/ySOPPJJYhLF27VpOPvlkmpubKS0t5Zprrun33M8++4wzzzwzMerG7/dz1113ccMNNwBw9dVX71E56HA4Eu+75557+NGPfpT4fb69vZ0f/OAH/P73vwfgxhtvxJ7ihY7p4PV6WbJkCe+88w6VlZW88sorzJiRmS46U0buIsQoolcAGo0GXEW2LEeT+/TlHwBTjs1wAjBeARgIBlDVGIqSXAJPVWN0dHYCqav+e/HeZ2jfpW2rOuysb1NWOykl180XzlIXPa1dhCIRPMEgRbbc/xo0GgxUOJ209nhoaWll1iwSG4+Ho6Z+Fg3b17F+/fqUxSiEEEIIIUQqXH755SxdupQLL7yQSy+9FJvNRleXNlPdarXy6KOPDjjH7sEHH+S8885j0qRJlJaW4vF4iMRng5900kncdNNN+5xz9dVXs2nTJh544AFuu+02fv3rX1NSUrLHKKcrrriCK6+8Mj1POMWefPJJ3nzzTUCb+7148eIBjx0/fjzvvPNOyu4tFYCi4Oh/MSgutRfsRtZUWhFv/y2qKaVqem1G722NVwCqKgQCwaTP7+7uTmxaLUvBApANyz7i/edXA1B3wBHMWnDmiK+Zb5z6HEC0KsB8URVvAw4EAnT3dI/oWjXxTcCNjY17jCwQQgghhBAi26xWK6+//jo33XQTEydOJBgMUllZyTnnnMN7773HSSedNOC5Z511FsuWLePUU0/FaDRiMpk46KCDuOOOO/j3v/+N1Wrd5xxFUbj//vt5/vnnOfXUU6moqKCnp4eKigpOO+00XnjhBX73u9/lzO/2etIStARgc3PzgP+1tram9N5SASgKjv4LtbT/jlw4FOGdNz8FYMqimRn/pqtXAAL4/b6kS773aAcfYQWgp6OH537zhBZXURkLLvxRzvwQyiST2YTVZSPoCdDm9TKxMj0r7jOt0uVEUbRkdEtzC8XFw9/4rCcAAdavX8+CBQtSEaIQQgghhBApYbPZuPHGG7nxxhuTPveoo47iueeeS/q8JUuWsGTJkqTPS8ZDDz3EQw89NOxjhjLi6OKLL+biiy9OPrgUkApAUXDcbjcAZRWuQY4Ug/nwnR34vNoQ16mLZg9ydOrpFYAwvEUg7e3aAhCn1YLFZBxRLC/e+y/8XVpF2zFf/V/sxftuvRIaZ3wOYKfPTyQWzXI0qWExmSiJJ6BbRjgHsEY2AQshhBBCCCFSTBKAouAkEoBSAThiK1/fDIDRbGTCkdMyfn+LxZRYvpB0AlBV6ejoBKBshNV/W97eyNqX3wdgyudOoP6go0Z0vXyntwGrqkpHHm0D1tuAe3p68PuGv5jG7iymtHIcgMwBFEIIIYQQQqSEJABFweltAXZmOZLct3KplgCsP3wqFue+8xrSTVHAatMmGfj9gaTO7e7pSQycLR3B/L9QIMTzt/8TAKuzmMPPvmrY1yoU9iIHhvjG5fyaA9hbVdzSmpoqQEkACiGEEEIIIVJBEoCioKiq2psArJAE4Ejs/qydHZ9q1ZRTFmV2+29f+hzAZCsAOzraE49HUgH4xl9fobNRu9ZhZ12Bvahs2NcqFIqi4CjVvv7avF5g8FkZucBhseC0WoBUtAFrX1ObNm0iGEx+wY0QQgghhBCFaOXKldTU1CT132OPPZbtsDNCloCIguLxeAiFtJl1ZVIBOCJ6+y9kNwGozwFMPgGoLQBxWMxYzcP7VtjV3MGqx5YCUDP1YKYd8YVhXacQOUtdeNp68IfCeEMhnJbMV5CmQ1WRC2+wnY72DsLhMGazefCT+qEnACORCJs3b+aggw5KZZhCCCGEEEIkZenSpcM6b9GiRUNajpEqoVCI5ubmpM4Zzjz5XCQVgKKg6PP/QLYAj5Te/ls2sYryiVVZi8MWTwAGgwFUNTbI0TqVjnYtATiS7b+v/fE/REIRUBQOP+c7svU3CfoiEMi3NmBtDqCqqrhb3YMcPbDaCbIIRAghhBBCiGTpCcdk/svWVt5MkwSgKCh6+y9AWaVsAR6ugD/E+6u2ATBl0cysxqK3AKsqBAJDmwPo8XgJhcMAlA1z/l/Tlt2seek9AKYedhKV46cP6zqFymyzYLFr7bLteZQALLbZsJi0itLmluT+8thXaWUdVpv2PUrmAAohhBBCCCFGShKAoqD0rQCULcDD996qbQSD2gKNqYtmD3J0euktwDD00u2+8/+GWwG49M8vgapiNFk49LRLh3WNQqdvA273+YgOuXpzdFMUhSqXNl7A7XYTiw3veRkMBmrqteS6VAAKIYQQQgghRkoSgKKg7NkCLDMAh2tFfP6f2W5h/OemZDUWvQIQwO8bWgKwPd7+azObsFuSn9HW9GkDG99YC8CMo0/FVV6d9DUEOEu1dtlYTKXTmz9zNyqLtecVjURpb2sf5OiB6XMA169fn9G5KUIIIYQQQoj8IwlAUVD0FmBFUSgpkwrA4VBVNbEAZOJR0zBZs7tLyGwxYTBos/d8SVYADnf77/KHXwbAYDIz58SvDOsaAuwlDpT4507bBpwfyp0OjPHn1dI6/G3ANfE5gJ2dnTQ0NKQkNiGEEEIIIURhkgSgKCh6ArC41I7RKC//4di+pZWm3Z0ATDk2u+2/AIoCVtvQNwH7fF6CQW0T9HDaf9t2tbJh2UcATD9yCc6yMUlfQ2gMBgP2Yq0St83jyXI0qWNUDFQ4tefV0tICwyze0ysAQdqAhRBCCCGEECOT3dIdITJMTwCWVUj773CteG1z4vGUBdldAKKzO8z4fSH8Pt+gx+rtvwBlzuQTgKuffANUFUUxMOeE85M+X+zJWebC1+nBGwwRCIexmZNvyR6NqoqLaOnxEAwE6e7uorikJOlrVNfNQFEMqGqMdevWcdJJJ6UhUiGEEEIIkU6bGzdmO4R+jda4RPpIAlAUFH0GYJnM/xu2lUu1BGDVjFqKx5ZlORqNzW4BvPj8gycA9fZfq8mII8lkk7/HzwcvvA1A/ZzPU1Q5NulYxZ6cpS5a44/bvF7GlZZmM5yUqXA5QQFUaGltHVYC0GyxUVk7mdaGLVIBKIQQQgiRo3727PXZDkEIQFqARYHRE4ClsgF4WDzdAda8uwOAqYtmDXJ05tjim4BDoTDRSGS/x+oVgKUOh5agScIH/15N2K+1Dx94/LnJByr2YXVYMVm1z1+bJ3/mAFqMJkrtdgBaW1sHOXpgfReBCCGEEEIIIcRwSQJQFBS9BbhUWoCH5e03txCNxACYsij78/90dntvJZ93P23Afr+fQCAAJL8ARFVV3v3XSgAqxk+jesqcYUQq+uMsdQHQ7vUSy6Ntt5Uu7Xl1d3UTDAaHdQ19Ecj27dvx5NGcRCGEEEKIfKeqas78d8IJJ2T7wyUyQBKAomCoqto7A1BagIdl5dJPALAV2xl3yIQsR9PL5rAkHvv30wast/8ClDrsSd1j+4ef0r5bqyCdecwZKEqS5YNiQM4yLVEWicboGuIm51xQ6er9PjPcKsDaeAWgqqps2LAhJXEJIYQQQgghCo/MABQFw+v1Jqq/SiUBmLRYLMbK17X5f5OOmYHBZMxyRL1sfSoAfb6BE0h6+6/FaMRltSZ1j/efewsAk9XO5PmLhxGlGIiz1IViUFBjKu4eT9LVmaOVy2bFZjYTCIdxt7ZSV1eX9DVq6nsrbdevX89hhx2WyhBHrK2tjU8++YRt27bR0tJCa2srra2teDyeRMVtJBLBZDJhsVgwm81YrVZKS0upqKigvLyc8vJyxo0bx4QJE6irq8Oa5NemEEIIIYQQYnCSABQFQ6/+AyirlARgsjavb6TdrbUgThlF8/8ADAYFq81EMBDBt58WYL0CsNRhT2r+n6/by4blHwEw+dDjsNjyI0E1WhiMBuzFTnydHtweD9Oqx2Q7pBRRqHQ52dXRidvdRiwaw2BMrvC+qLQKZ3EF3u62rC8CaW1t5b333uOdd97hvffe4+OPP6a9vX3wE5OgKAo1NTWMHz+e6dOnM3PmTGbNmsWsWbOoqqpK6b2EEEIIIYQoJJIAFAVjjwSgVAAmTa/+Q1GYvGBmdoPph81uJhiIDNgCHAwGEtWBpUlWmK175QOiIW25yIyjTxtZoKJfrnIXvk4P3mAIXyiEw2IZ/KQcUFnkYldHJ9FolPaOdiorK5O+Rk39LD5d92bGF4HEYjE++OADXn75ZV566SXWrl273+MVRaHMUU65s5IiWxE2sw2r2YbJYCISDROOhonEIvjDfrp9nXT4OugOdKH2mfuoqiqNjY00Njby9ttv73H9yspKDjzwQA499FDmzZvHoYceSkVFRVqeuxBCCCGEEPlGEoCiYOgbgEG2AA/HingCsHbOeJwVRVmOZl82u4WuDv+ALcAd8fZfgDJncp//j15+H4CS6glUTRw9y0/yibOsCGgCwO3xUF9ent2AUqTM6cBgUIjFVFpbW4eVAKytn82n695kw4YNRKNRjMb0tt9/8sknPPbYYzzxxBM0NDTs836z0cLssQdywLiDmFQ5hUlVU5hQMYlKVxUmY3L/rIjGonT6Omjs3M2ujp3s7thFQ+cudrbv4NPWLbR0NyWOdbvdLF26lKVLlybeNnHiRObNm8fhhx/O0UcfzeGHHz7s5y2EEEIIIUQ+kwSgKBh9E4BlsgU4KR1tXjas2Q3AlIWjq/1Xp28CDgT8qGoMRdmz1bI93v5rMhqSmv/X3tDGrvXbAZhy2Amy/CNNLDYLFoeVkC+I2+PNmwSgUTFQ7nTi7vHQ2trKrJmzkmo/B60CELQt1tu2bWPq1KkpjzMcDvPcc8/xhz/8gXfffXeP9xkUA3PGH8KC6cdy2OSjmFU7G4spNXP6jAYjFa5KKlyVHFh38D7v7/J1sqVlM580b2Jz80bW7f6IT5o2EolpFbnbt29n+/btPPXUUwCMGTOGRYsWsXDhQg455BCmTp0qX7NCCCGEEEIgCUBRQPq2AJeUSgVgMt5a9kmiTW/qsaOzAk7fBKyqWqLE4dgzyasvACm120kmH7DulfcTj6fI8o+0cpa5CPmCdHp9RGIxTIb8WFRf6XLh7vHg9/nxer04Xcn9AaJmQu/X3Lp161KaAOzp6eEvf/kLf/jDH9i9e3fi7YqicNikozj14DNYNPN4Sh1lKbtnMkocpRw68TAOndi7/CQQDvBxwzrW7l7D2p0fsmbn+zR2aZWKLS0tPP744zz++OMAVFdXs2jRIhYvXsyiRYsoLS3NxtMQQgghhBAi6yQBKAqGngAsLrVjMo+eDba5YOVSrf3XWVlEzQHjshxN//beBNw3ARgKhfB6vQBJbZhVVTXR/ls16QCKq0bnc88XrrIiOna3EVNV2r1exhSNvlbz4ajsk/BraW1hkmtScufXTsZkthAJh1i3bh1nnHHGiGPy+/08+OCD/Pa3v91jkUd1cS3nfu4CTpt7JrWlo/P1bjPbOGTCfA6ZMD/xtt0du3h72yre2/E2b29dSWOnlhBsbm7mscce47HHHsNoNDJ//nwWL17M8ccfz4EHHijVgUIIIYQQomBIAlAUDL0FWBaAJCcSibJ6+RYAJi+ciTJKq7Ls9t6lEXtvAta3/wKUJjH/r3V7M+4dzYBU/2WCvdiBwWQgFonh7vHkTQLQZjZTZLPSEwjS2trKpEnJJQCNRhNj6mbQsG3tiBeBRKNR/va3v/F///d/NDX1ztebPfYgvnb0pZxwwCmYjeb9XGF0GldWx5ll53DuEV8BVHa2fcaqzW+w6tM3WbFlOd3+LqLRKKtXr2b16tX8/Oc/p7a2llNOOYXTTjuNI444ApNJ/kkkhBBCCCHyl/xrVxQMvQKwVBKASVn3wS66u7TFGqN1/h+AyWzAZDYQCcf22QSst/8aDQrFtqHPLtv4Ru/W04mHLExNoGJAiqLgLC2ix92F2+NFVdW8qdCqdLnoCQTp7OgkHA5jNieXZKsZP4uGbWtZt27dsGN47733+OEPf8iaNWsSb5tVewDfOeEHHD11Qd58rBVFYXzFBGoOreXMQ88lEo2wbvcalm9+nTc/WcbHDdrHsLGxkQcffJAHH3yQiooKTjnlFJYsWcKCBQuw5MkWaiGEEEIIIXSSABQFI5EArJD5f8lYFW//VYwGJn1+Rpaj2T+73UJPONBPBWB8/p/DnlSSY+ObWqKgauIsnKVVqQtUDMhZ5qLH3UUoEqEnGKTYZst2SClRWeRim7sNVVVpc7upqa1N6vya+pkANDU14Xa7k9om3NnZyc0338wjjzySeNuEiol8Z/EPWDz7ZAyjtKo3VUxGE3PrD2Vu/aF8Z/H3ae1p4c3NS3lt48us3LKcUCREW1sbjzzyCI888gjFxcWcfPLJnHPOORxzzDFp37oshBBCCCFEJkgCUBQMaQEenhWvbQJg/KGTsBXbsxzN/tnsZnq6A/h8/sTbwuEwPT09AJQmMf+vq7mDho07AZgw55jUBioG5CpzaVtyVXD3ePImAVhss2ExGQlForS2tiadAKztswhk/fr1LFw4tIrUV155he9973uJdl+72c63Fl3FRUd9I2WbfHNNVdEYzjz0XM489Fy8QQ9vbF7Ky+v/wxufLMUf8tHd3Z1YJFJdXc1ZZ53F2WefzUEHHZQ3VZJCCCGEEKLw5Pef/YXoQ1qAk9fS2MWWjfEZeItGb/uvTl8E0rcFuDNe/QfJLQDRq/8AJhwsCcBMMZpN2F3a58nt8WQ5mtRRFIUKlwuAVrc7sVV7qKrH9379DWUOYE9PD9/73vc4//zzE8m/xbNP5l/feZlLF1xesMm/vTmtLk4+6FRu//LvWP6/73H3BQ9w6sFnYLdor8Hm5mbuu+8+jj/+eBYsWMDdd99NQ0NDlqMWQgghhBAieZIAFAXB5/Ml2kLLKiQBOFQrl36SeDxl0ez9HDk62Bza3K5oNEYwGACgPb4AxKAoSVWT6QnAkup6SmsnpjZQsV/Oci1R1u0PEIxEshxN6ujbgMOhMJ2dnUmda3cWU1pZBwyeAFyzZg3HHXdcouW3xF7K/517D3eef9+o3ew7GtjMNo6bdSK/PPtOlv7wHX51zt0cM/1YjAatBXjjxo3ceuutHHLIIXzlK1/hxRdfJJJHr08hhBBCCJHfJAEoCoJe/QeSAEzGyte19t/isWVUTqvOcjSD22MTsFdL+Orz/0ocdgyGobXv+bq9bP/wU0Cq/7LBVda7/TefqgArnM5EC2lra2vS59fUa1WAAy0CUVWVP/3pT3zhC19g+/btACyauZhnrnqJkw86dXhBFyiHxcEX5pzO/7vwQV75wSr+9ws/5cBxcwCIxWK89NJLfPWrX2XevHn86le/YteuXVmOWAghhBBCiP2TBKAoCH1/2S6vdGUxktwRCkZ4Z8VWQGv/zYXZV3ZnbwLQ6/MSjUTo7u4GoMwx9PmFn6z6GDUaAyQBmA1Wpw2TVWvnbuvJnwSgyWikNP46dA8jAajPAdy8eTPBYHCP93k8Hi699FL+93//l1AohMVk4YbTbuW3F/yeyiJZYDMSla4qvnLk1/nHZf/imate4sKjLqHEXgpom4R/85vfMG/ePM4//3xefvllYrFYdgMWQgghhBCiH5IAFAWhpaUl8bi8UioAh+LDd3bg94WA3Jj/B2AxGzGZtG9rXq+Pjs4O9FFrycz/27RSa7F0lFRQNSE3nnu+cZVpifo2r49YkvPyRrPK+BzAnh4Pfr9/kKP3pFcARiIRNm3alHj7zp07OfXUU3n22WcBqC+fyCPffIpzD/tKTiTuc8mUMdO47pTrefUHb3Hb2Xcxf+LhgFZ9+corr3DBBRdw9NFH8+c//xmv15vlaIUQQgghhOglCUBREKQCMHl6+6/RYmLCEVOzHM0QKWCPzwH0er20t2vtvwYFiu1DqwCMRqJsfXczAHWzj0AxyLfJbHCWa23A0ViM9jxKpFQW9f4BItk24Nr6PTcBA6xevZoTTzwx8b+Pn3USj13+LLPGHpCCaMVArGYrSw7+In++5FH+9Z1X+NrRl1JsLwFgy5YtXHfddcydO5dbbrmF3bt3ZzlaIYQQQgghJAEoCoReAWg0GiguHXoraCFb+bqWBKs/fAoWR+5sDNUTgD6fNzH/r9huxzjE+X8NG3cS6NEqs8bNPiw9QYpBOUpcGIzaj6jWPGoDdlosOCxae3OyCcDSqjqsdi0xun79eh599FHOOuss3G43AP+z6Cru+PL/w2Ur2t9lRIpNrprC90/+CS9/fyU3nP5zJlVOAaCzs5N77rmHQw89lG9+85usWbMmy5EKIYQQQohCJglAURD0X7TLKpwYpKJrUDu3t/HZNm1xytRjR//23756E4B+uro6ARJz14Ziy9sbAVAUA+Nmzk95fGJoDAYFZ7wNuLWnBzVv2oCVRBtwe3s70Uh06GcqCjXjZwDwwgsvcNVVVxEKhbCarPz6nN9y5fHXyPe3LHJYHJz7uQt45qqXuP+ihzh62kIAotEozzzzDIsXL+a8885j1apVWY5UCCGEEEIUIvlNQRQEPQEo8/+GRq/+A5iyMLdm4OmLQFRVHdb8v0/f0VqfKyfMxOosTnl8Yuhc5drHPxSJ0uUPZDma1Kks0hKAsWiM9va2QY7eU3X9TECb+wdQVTSGP1/yKKfMOS21QYphMxgMHD1tIfdf9BD/uuplzvncBVhM2vel1157jdNPP51TTz2VV155JY8S20IIIYQQYrSTBKAoCL0JQJn/NxSrlmoJwPLJYyibUJnlaJJjd5j3+N+KAiVDnP/n6/ay++PPAKibfXjKYxPJcZa5EkssWnt6shxN6pQ6HBjjlXqtre4hnxcJB9n1aW8baX35RB751pMcVDc31SGKFJk8Zio/Pf3nvHjNm3z98/+Dw6L9EWr16tWcf/75HH/88fz3v/+VRKAQQgghhEg7SQCKgiAJwKHz+0K8/9Z2IPeq/wDsdsse/7vIZsNkHNq3uq3vfoIa034Rl/l/2Wc0GbGXaAmTlp4eID+SJAZFocIVf16tLUN6WkG/h0duv4SGbWsBqHNN4M6zHmBsaV06QxUpUllUxTUn/S8vfX8F3z7ue5TYSwFYu3YtF154ISeddBKvvfaaJAKFEEIIIUTaSAJQFITEDEBJAA7q3ZVbCYUiAExZlHsJQKPJgMVqTPzvpNp/4/P/LHYXVRNmpjw2kbyiCm2hhT8UxhMMZTma1NHnAAYDQbp7uvd7bMDfw8O//hqfrl8BwLSSmfzPgd/DGDXu9zwx+pTYS7js2O/w0rVv8v2Tf0y5swKADz74gPPOO4/TTjuNFStWZDlKIYQQQgiRjyQBKPJeMBikq6sLkArAodDn/1mcVsbPn5zlaIbHZu9tAx7qAhBVVdkSn/83duZ8DEZTWmITyXGV9260zac24EqXE+KLqVtbBt4GHPB185dff42dW94H4OipJ3PZoddhM9no6c6fj0ehcVidfO3ob/Kfa5Zz9Qk/pNheAmitwWeccQZnn302H330UZajFEIIIYQQ+UQSgCLvud29M7ZkCcj+qarKyvj8v4lHTcNkzc0k2HAqAN07Wuhp1RLFddL+O2qYLGZsRVoSt7XHk+VoUsdiMiVmU7a0tvR7jN/bzcO/uoidWz4AYNGM0/nByXfhcpYD0J1HCdFC5bA4uGTBZfz3muVccezVuKxawnvZsmUsXryYb3/72+zevTvLUQohhBBCiHwgCUCR9/T2X5AKwMFs3dxCc4OWBMvF+X86syX5b23bPtiSeDx25vxUhiNGSK8C7PYHCITDWY4mdfQ24O6uboLB4B7v83u7efjXF7Jrq7b049iZZ3D1Cf+H0WDC6tDO8/l8RKLRzAYt0qLIVszlx32X/16znEuOuRyryYqqqjz++OMcccQR3HrrrfRIwlcIIYQQQoyAJABF3mtp6a2ukQTg/q14fVPicS7O/wNQVejbvesPDW1u3PZ4AtBVXkNRRW06QhPDVFRRnHicT1WAVa7eiuS+bcBBv4eHf30hu7dqLaDHzTyT7y7+FUaDVtlqs/e2RUtSKL+UOEq5+sTreP7q1zh97lkABAIB7r77bg477DD+/Oc/E5WkrxBCCCGEGAZJAIq8JxWAQ7fq9U8AGDNrLEU1pdkNZpgikcgeFYC+0OAVY6qqJhKAtdMPSVtsYngsdisWhxXIrzmALpsVm0WbV6m3AYdDAR6549JE8u/4WV/iO4tvSyT/AKz23u9jkgDMTzUlY/n5l27nscuf47BJRwLaOIvrrruOxYsX8/bbb2c5QiGEEEIIkWskASjynp4ANBgUSsuHvhG20PR0+/novc8AmLpodpajGb5wOITZYkCJL1jwDqECsGVbE74uLyAJwNFKbwPu8PkJ500FlEJVvA24ra2NYNDPo/d8m+0bVwOwYPqpXHX8L/ZI/gGYzFZMZgsgCcB8N3vsgfzx63/jd1/9E5MqpwCwbt06lixZwpVXXrlHhbsQQgghhBD7IwlAkff0BGBJmQOjUV7yA1m9fAvRaAzI3fZfgFAojKIomC1a0sQ3hATg9j7z/2qnz0tbbGL49ASgqqp51QaszwGMhiM8du932fzhawDMn3gs3zvh//ZJ/un0KsCe7u7MBCqyRlEUFsw4jiev/A/fP/nHOCxa6/hjjz3GkUceye9//3sikUiWoxRCCCGEEKOdZENE3tMTgNL+u38rl2rtv7YSO2MPrs9yNMOjqhCOL4mw27VBgN69liv0R08AFlWOxVVenb4AxbDZiuyYrPF22TyqeitzOjAoClve+TuffPgyAAeNO5z//cI9mIzmAc/T5wD2eDyoqpqRWEV2mY1mvnb0N3nuu69yykGnA9Dd3c1PfvITFi9ezJo1a7IcoRBCCCGEGM0kASjynt4iJQnAgcViMVYt3QzA5AUzMZj6rzoa7SKRSCIZ4nBoyRNvMMT+8iOxWIzta7YCUDtN2n9HKwUlsQyk3ePNmzZgg6LQsvFFmre8CcC0MXO4/rQHsJps+z3PGk8ARqNRvF5v2uMUo8eY4mp+fe7dPPiNfzB1zHQA1q9fz4knnsjNN9+Mz+fLcoRCCCGEEGI0kgSgyHu9FYDOQY4sXBvXNtDRpiURpizM3fZfvfoPwOXUZqTFVBV/eOBFIC3bmvDL/L+cUFSpJQBjedQG/P67/2bju08BUFs8geuX3I/DMvgfK2yO3s3IXdIGXJA+N+kIHr/iea456X+xmqzEYjHuvfdeFi1axIoVK7IdnhBCCCGEGGUkASjynrQAD25lvPoPRWHygpnZDWYEwmFt3p/RYMDpsCTevr824D3n/0kCcDTLtzbgTzat5rl/3Q5Aia2C7y28A5thaH+osFjtGA1am3u3JAALltlo5uuf/x+euvK/fG7SEQBs27aNM844g+9///vy2hBCCCGEEAmSABR5LRwO09HRAUgCcH9WvqYlAMceXI+jPEc/Tqq2AATAbDRit/fOT9tfAnDHh58CUFQ1DmfZmPTGKEZEQUlUAeZ6G3DD7k08/uiNqLEYdrODa4+9k0pnLcEhzKwEQFGwOrQ2YEnyiPqKifzx4r9x4xd/gcuqvS4efvhhjjnmGN54440sRyeEEEIIIUYDSQCKvOZ2uxOPy6tyNLGVZu1uDxs+2g3k9vbfvvP/zEYjRqOCzabNMvQG+98ErKoqn63dBkDN1IMzE6gYEX0OYC63AXe0N/K3v/wv4VAAo2Lif4+/gxlVBwDa6zgW38Y9GFufBKCsAREGg4Gz55/PM995iUUzjgegoaGBs846ixtuuIFAIJDlCIUQQgghRDZJAlDkNX0BCEgF4EAS7b/A1EWzsxjJyIT6zPkzG7XEX+8ikP6rqtp3u/F2aEmk6skHpTlCkQp7tAHnYOWb39/DIw9fh9ejVSZfecyNHFJ3FJY+i3dCoaFVAeoJwGg0ik8WgYi46uIafvuVP/CLL92RqAa8//77OeGEE1i3bl2WoxNCCCGEENkiCUCR1/T5fyBLQAait/+6xhRTfcC4LEczfH3n/xkNCgAOuzYHcKBNwHr1H0D1FEkA5oK+bcBtXl9OtQFHoxEe/8eNtLl3AnDBod/m+OlfBLTXrcGg/UgODlCxujebvXcRiLQBi74UReG0uWfy1JX/ScwG3LhxIyeeeCL33nsvsdjQqkyFEEIIIUT+kASgyGt7JgClAnBv4VCE1W9qSzCmLJqFoihZjmj49ApAvfoPwB6vAIyqKoF+NgHvjCcArc4SSqrrMxClSAW9DVjNsTbg//77XrZ9+j4Ax047jfPmfmuP91vir91QOJRoZ98fi82BwaCdI5uARX9qS8fxx4v/xrUn/Qiz0UI4HObmm2/mggsuoK2tLdvhCSGEEEKIDJIEoMhrfROAZeVSAbi3Ne9+hrdHazecemzutv9GIhHUmD7/r/fbmt4CDP23AX+2djugVf/lcvKz0NiLHJhzrA34ndX/4p3VzwAwc8xcrvz8jfu85qwmbasvqko4NIQqQEXZYw6gEP0xGAxc/Plv8Y/LnmHqmOkAvPrqqxx77LG89dZbWY5OCCGEEEJkiiQARV7TE4AlZQ5MZuMgRxeeFa9tAsBoNjLxqOlZjmb4+pv/B+CwmxKP914E4uv24t7RDED15APTHKFINVcOtQFv/fR9Xnj+bgCqXLX8+IQ7MRst+xxnNhpR0JKCwaEkAAGrXRaBiKGZUTOLv//PM5w571wAGhsbOeOMM7j77rulJVgIIYQQogBIAlDkNT0BKPP/+rfydW3+X/3hU7E4rVmOZvjCIS0BaDQoGA2939aMRgM2q5YQ9OxVAbhz3fbEY5n/l3uKKksAvQ24J8vRDKytbReP/+NG1FgMm8nO9Sf8llJ7xYDHm+PLQELBIEPJ6OkVgJFIBL/Pl5KYRf6yW+zccuav+MWXbsduthONRrn11ls5//zz6ejoyHZ4QgghhBAijSQBKPJac7NW4VUxpijLkYw+O7e3sWOrG4Apx87KcjQjE+5n/p/OntgEvGdFlT7/z2AyU1E/I80RilSzu+yYbdrntqlrdCYA/f4e/vHXHxPwa/Fds+iXTKrY/2tNbwOOxWKJ1/X+2ByyCEQk77S5Z/HoZc8ydYz2enzttdc48cQT2bBhQ5YjE0IIIYQQ6SIJQJHXmpqaAKiskgTg3vTqP4Cpi3J5/l800b7WXwJQnwPoDe1ZUaVvAK6sn4HJnLvVj4VMrwJs93kJRiJZjmZPsViUJx/7Ge7WzwC4cP53OGLicYOeZzH1voaDoX3nVu5zvM2Z2B4sCUCRjMljpvL3/3ma0w/5EgDbt2/nlFNO4ZlnnsluYEIIIYQQIi0kASjyml4BWFktCcC9vfmqNv+vYsoYyiZUZjma4QsPMP9P57DHNwHHVPzxYyOhCLs37gSgesqcDEQp0qG4qlR7oEJT1+hKfr32yoNs+eRtABZOWcLZB18ypPMUlMTreChtwIqi7DEHUIhk2C12bj3z//jRkpswGoz4fD6++c1vcssttxAd5bM1hRBCCCFEciQBKPKW1+ulJz4brFJagPfg9QT54O3tAEzJ4eo/gFB8WYJhr/l/Ooezd9mCPgewcfMuoiGtYkzm/+Uuq8OK1WUDRlcCcMP65by57G8ATK08gKuOuSmpLdN6G3A0GiUSHbyy0RZPAHZJAlAMg6IoXHDE1/jDxY9Q7tTmU95zzz2cf/75dHV1ZTk6IYQQQgiRKpIAFHlLr/4DmQG4t3dWfEokrFV3TD02txOAegWgpZ/qP9BagPXcS09ASwDq7b8gG4BzXXG8DbgnEMAbHLxlNt1aW3fwzD9/CUCxrYwfLb4Diym5FnOLqXd7dWgIz0lfBBIOh/H7/UndSwjd5yYdwWOXP8vssdofRV5//XW+8IUvsGPHjixHJoQQQgghUkESgCJv9U0AVkkCcA8rXtPaf61FNuoOnZTlaIZvsPl/oG0Gttu1hIonEABg5zotAVhSXY/NVZr+QEXaFFeVQDzB25jlKsBg0Mdjf7uBUMiPQTHwg2N/RZWrNunrGJTeNuDgkBKAvYtApApQjERNyVgevvRxlsz5IgCbN2/m5JNP5p133slyZEIIIYQQYqQkASjyllQA9i8WiyUWgEz6/AyM5v4TZ7lgsPl/Ome8DbgnGERVVT5bux2A6snS/pvrTBYzjhInAE3d3ajqIEPz0kRVVZ558rY9ln4cPO6IYV9PrwKMRCKDzmKz2JwoiiwCEalhM9v45dl3csVx3wPA7XZz5pln8vTTT2c5MiGEEEIIMRKSABR5S98ADDIDsK/N6xtpa/UAMPW4XG//jc//U/qf/6fTE4D+UJjWna34OrXnP0baf/OCvgwkEArTmaUW2BVvPMrH65cDcNTExZw15+sjup61zzbgwdqAFYMBm90FSAJQpIaiKFx+7He47ey7MBstBINBvvWtb3H77bdnLckuhBBCCCFGRhKAIm+1tLQA4CyyYndYBjm6cLwZb/9FUZiyYFZ2gxmhUEirADSb9l/F6HSYE4+3rt2aeDxm0gHpCUxkVFFFEYpB6wPOxjKQT7e8y6sv/QGA8aWT+c6CnyW19KM/BsWAKZ7UHkobsDU+B7BHEoAihZYc/EX+9PW/UeYoB+C2227j2muvJRIZfDmNEEIIIYQYXUyDH5I/urq6+Oc//8nbb79NW1sbVquVKVOm8IUvfIEjjhh+q1YkEuH5559n2bJlNDQ0ADBu3DgWLlzIkiVLMJn6/zB/+umnrF69mvXr1/PZZ5/h8Xiw2WzU1dVx+OGH84UvfAGHwzHsuAqd3gJcWSXVf32tfE1r/x07ZzyOCleWoxm+SHTw+X86Z59NwDs3aAPtzVY7JTX16QtQZIzBaMRVXkSPu5uW7h5m1FRjGGECbqi6Olv452O3oKox7GYnP1p8Jw6LMyXXtphMREIhwuEwsWgMg3Hgv9npi0CCoRCBQACbzZaSGIQ4ZMJ8/vY/T/Ptv36Dbe5P+etf/4rb7eaBBx7AbrdnOzwhhBBCCDFEBZMA/Oyzz/jJT35CV1cXAHa7Ha/Xy4cffsiHH37Iaaedxje/+c2kr+v3+7nhhhvYvFlLqlgsWqJhy5YtbNmyhRUrVnDLLbfs88vY0qVLueOOOxL/W1EUHA4HPp+PTZs2sWnTJv7zn/9w4403Ul8vSYrh0FuAZf5fr7ZWDxs+2g3A1ONyu/otHBra/D8Ai8WIxWwgFI7RtHEnAJUTZmEw5O78Q7Gn4qpSetzdhKNR2jweqorS/3UfjUb452O34PdpVXdXL7yVutLULdWxmkz4QlqbezAYxO4YONmyxyKQri5JAIqUGl9ez1+++QTffuQSPtr5Af/5z38455xzeOSRRygtLc12eEIIIYQQYggKogU4HA5z66230tXVxYQJE7j77rt57LHHeOyxx/jqV7+Koig899xzvPLKK0lf+//9v//H5s2bcTqd/OhHP+KJJ57giSee4Ec/+hFOp5ONGzdy33337XNeNBrFYrGwePFibrnlFh5//HH+8Y9/8Nhjj3H11VdTXFxMa2srP/vZz4bU/iX2lagArJYEoG7V0s2Jx1MW5Xb7r74AxKAoiVbJ/XE4LcSiUTq2aa+Lqom5/fzFnpxlrsRCm0xtA3715T+y87N1AJxx0EUcOfH4lF7faDAkZlsGg4H9Hmu1uTDEj9X/0CVEKpU6yvjDxY+wYPpxAKxevZrTTz+dxsbGLEcmhBBCCCGGoiASgC+++CJNTU1YrVZ++tOfMmmSVqFhtVo599xzOeWUUwB45JFHkpprs23bNpYv14a+X3XVVRx55JEoioKiKBx55JFceeWVgFbtt2PHjj3OnTFjBn/4wx/4zne+w9y5c7FarQDYbDaOO+44rrvuOkBLYq1YsWJkH4ACJS3A+1oRn//nqi6meva4LEczMqH4ApDBqv90TqcF3+52YhFto2rVBEkA5hNFUSiqLAHA3eMhFE3vjLJNH69k5RuPAjBzzMFc9LnvpuU+1vgICa0NeOBtwIrBgNWufa/r6pYEoEgPh8XBXRfcz+mHfAmAjz/+mC984Qt88sknWY5MCCGEEEIMpiASgEuXLgVgwYIFVFVV7fP+L33pSyiKQnt7O2vXrh3ydZctW4aqqtTW1nLkkUfu8/6jjjqK2tpaVFVl2bJle7yvrq6OsrKyAa89Z84cxowZA2izAkVy/H4/nZ2dgFQA6sKhCKvf1F5LUxfNHvGSgmyKRmPEokOb/6dzOc30bG9N/G+pAMw/JWNKAYipalqXgXR2NPH0k78EoMhawg+O+z9MBvMgZw2Ptc8M2cGqwfU24K6ubmRPq0gXs9HMrWf+H9845jIAdu3axZIlS/jwww+zG5gQQgghhNivvE8A+v3+xF+m582b1+8xVVVV1NXVAbBmzZohX/ujjz4C4JBDDuk3maIoCocccsgexyajuFj7ZS66n6oP0T99AzBApcwABODDd3bg82gJhCmLZmc5mpEJx6v/YPANwDqn00JPvP3XXlKJs2xMWmIT2WNz2bE6tdl3DZ1dkIY0WCQS5olHbybg7wHge4t+QZWrJuX30fVtAw4E9p8AtDuL4zFG8Hm9aYtJCEVR+N6JP+S6U24AoKOjg7POOovVq1dnOTIhhBBCCDGQvE8A7tq1C1XVfgmcMGHCgMfp79u5c+eQrquqKrt27Rr0uvoCj6FeV9fT05NoG5YlIMnT239BloDoVryuzf8zWkxMPGpalqMZmVAoufl/ADa7CU+8ArC8fkbaYhPZpVcBegJBugdJmA3HKy8+wO5dHwPwpTnfYP74Y1J+j71ZTVp1YSQS3u8fhPouAumUOYAiAy486hv84ku3Y1AM9PT0cO655yZGowghhBBCiNEl77cAt7e3Jx6Xl5cPeJz+vo6OjiFd1+/3EwgEhnxdv9+P3+/Hbh94i2Nfjz76KOFwGLvdztFHHz3o8Y888gh///vfB3z/+eefzwUXXDCke/elD5U3GAz7bVkebTweT+Jx7bhyzPHtzIXAZO6/FXHla1oCcMIRU7EWDe11OFrpC0C09t+htTKHvUF8TdrXd9n4GaOqBXo0xZLriseU0rqjGTWm0tjZRelYR8quvfHjN3lr5T8BmF09jws/d1VGPnc2swlfSEtmhoJBnE5Xv8dZ7S6MRhPRaASPp6egvu/plD7/vxCffzacddiXcdhcfP8f38bn83HBBRfw2GOPceqppw56rv71U1JSkvhjrRidcvXfg4VKvrZyh3xtCSEyKe8TgHqSDkgs2uiP/j6/3z+k6/Y9bijX1c8ZSgLwnXfe4d///jcAF1xwASUlJYOe4/V692h73ZvP58M4xFlp/VEUZUTnZ1rfCsCq6mKUISaJ8kF/z/Wzra18ts0NwNRjZ+f0RyMajSaqoIba/gvQuH53oiO0ZNw0VIaaOhS5xGQ24SovosfdTWNXF9NrqhMttCPR3t7AM/+8DYBiWxnXHf9rjIbM/Ag1GgyYDEYisSiBwMAJQAUFm6MYb087nR2dFHReWZGv70w65eBTsVtsXPXXbxEMBjn77LP5+9//zjnnnDOk8w0p+BoVmZFr/x4sdPK1lTvka0sIkQl5nwDMNVu3buX2228nFotxxBFHcPrppw/pPKfTmVga0h+HwzGsWYIGgwFFUVBVlVgslvT52aK3Z9sdFhwuK2qBjMRXUPp9rm+8+nHi8ZRjZ+f0RyMU6jP/L4l/KDWu1V4TKArFddOIxmJDbh8WuaWkuowedzeRaIyW7h5qSwf/I8r+RCJhHv/7TQQCHhQUrj32Niqc1SmKdmisZhORYJRIJEwkEsFk6v/Ht91Zgrenna7ubqLRWMH98qfo/0dNxwRIsT8LZy7mga8/zBUPfR1/2M+Xv/xlvF4vF1544YDnKIqCwWAgFotJldIol6v/HixU8rWVO+Rra3gkWSrE8OR9AtBmsyUeB4NBHI7+28H07YpDbdHte9z+NjP2fd9g1965cyc33ngjPp+Pgw46iO9///tDbi/76le/yle/+tUB3+92u4fc3txXWVkZRqORWCw2rPOzRZ+fWDmmiHCfhFE+UxQFs9lCJBze5x97y17eAEDFlGpK68pRc/gfGMGg9vnsnf83tH/YNq7T5nC6quow251EolGMWSyR6vu1Lf84Ty1HiROT1UwkGGZ3RwfVxSObA/raKw/SsHsjAOfMvZRDxh2Z8c+Z1WTCG/95Egj4cTid/R/n0J5rLBajvb2dkuLifo/LV2aLRc//Fcz3/tFkfv3hPPC1v3DFX7+BJ9jD17/+ddxuNxdffHG/xxuNRsrKyujq6pKFZ6Ncrv57sFDJ11bukK+t4amsrMx2CELkpLwvDeg7n6/vPMC96e8b6uwFu92eSOgN5bp9j+9PQ0MDN9xwA11dXcyYMYPrr78ei8wvGja9BVg2AIPXE+TDt7WE6NRjZ2U5mpELxTcAJ1P9B70VgGXjtQUgYfkHcd5SFCWxDKTd68M/gkTQ9m1reHO5Nl91xpg5nD/v8lSEmDSDoiRe84FAYMC8t73PIpAuWQQisuCQCfP549f/Rom9FIAf/OAHPPjgg9kNSgghhBBC5H8CsK6uLlFp89lnnw14nP6+8ePHD+m6iqJQV1eXkus2NTVx/fXX097ezuTJk7nxxhuHXIko+qcnACvG9D8rq5C8/eYWImEt2TX12NlZjmZkItEosahWvZjM/L+e5i56WroBqJg4M36t3K2CFIMrjicAARqGmQjz+3t46omfg6piNzu4ZtEvMzb3rz/WeNtvNBolHAn3e4zJYsNk1mbPSgJQZMsB4w7iwW/8g3JnBQA//OEPJQkohBBCCJFleZ8AtNvtTJs2DYD333+/32Pcbjc7d2rtgQcffPCQrz1nzhwAPvjggwGP+fDDD/c4dm8tLS385Cc/we12M2HCBG655RZcLklajVSiArC6sNrf+rMivv3XWmRj3LxJWY5mZMKh3qRHMhWADet2JR5XTdKSoJFYTGaE5TGLzYKjRGuTbezsSrplV1VVnv/XHXR3acuV/ueoH1NbPLQ/EKWL1dybfOy74GpvehWgJABFNk2vmcmfvv53SQIKIYQQQowSeZ8ABFi0n1/5FQAAou5JREFUaBEAy5cvp7W1dZ/3P/XUU6iqSnl5OQcddNCQr7tgwQIURaGhoYFVq1bt8/6VK1fS0NCAoiiJGPpqa2vj+uuvp7W1lXHjxnHLLbdQXGDzmtIhGAwmWq8rqwq7BTgWi7HydS0BOHnBTIzm3B6YGw7vPf9vaPT2X6PJTHn9ZABUVKI5PAtRDK6kuhSAQDiC2+NN6tyPPnyZ9WtfB+Dzk07iuGlDW8iUTgpKogowGAjCAElNm1P7OeL1eIhIq7vIoqnV0/dJAv75z3/OclRCCCGEEIWpIBKAJ510EjU1NQQCAX72s5+xbds2QEsU/fOf/+Tf//43oC3S2Huz4qWXXsrpp5/OXXfdtc91J02axIIFCwC45557eOutt1BVFVVVeeutt7j33nsBLQFZX1+/x7mdnZ1cf/31NDU1UVNTw6233jrk+YNi/1paWhKPC70FeNO6RtrdHgCmLMrt9l+AULwCMJn2X4DGeAVgef00rDZr4u0yBzC/uSpKEknv3UkM1m5vb+Dfz90FQKWzmis+f8OQFzKlm9VsBkBVY4mFOHvTKwBVoLtbqgBFdu2dBLzuuuskCSiEEEIIkQV5vwUYwGw2c/311/OTn/yE7du3893vfheHw0EgEEisWz/11FNZvHhx0te+4ooraGxsZPPmzfziF79ILO4IxYfOz5w5k8sv33do/H//+192794NaG1a3/ve9wa8x8yZM/nxj3+cdGyFqqmpKfG4qsBbgN98bZP2QFGYsmBmdoMZoUgkmvh6tSTR/huLxmhcp32tVU6ahdGgYFAUYqqqzQE0pyVcMQoYDNoykPbdbbi9XvzhMHbz/j/h0WiEp574OaGgDwWF7y38BS7r6Pk+YjEaURQFVVUJBAJ7JLR11r6LQDq7KC8r3+cYITJJTwJe8ucLaPe2cd111wHaH1mFEEIIIURmFEQCEKC+vp577rmHJ598krfffhu3243T6WTy5MksWbKEI444YljXtdvt3HbbbTz//PMsW7aMhoYGAKZMmcKiRYtYsmTJPlWFQCKRAeD3+/H7/QPew+PxDCu2QqV/DgDG1IyeX9yzQW//HTd3Ao6K3K6G1Nt/Ibn5f+3b3YS8QQCqJmtbkE0mA6FwlEhMKgDzXUlNOe2720DVqgCnjhmz3+PfWPoIuz5bD8BZB3+Dg8Z+LhNhJsVmMuEPhwmFgsSiMQzGPYv5jSYzFquDUNBHp8wBFKNEf0lAg8HAtddem+3QhBBCCCEKQsEkAAFKS0u55JJLuOSSS4Z8zh//+MdBjzGZTJxxxhmcccYZQ77uBRdcwAUXXDDk48XQNTY2Jh5XFXACsK21h48/0irfphw7K8vRjJze/ms0KBiTmP/XsLbPApD4BuDeBGAMVVVHTXunSD2LzYKz1IW300NDZxeTq6owDPD53vnZepYv/QsAUytnc8G8KzIZ6pBZzWb8Ye3rIRAI4HA69jnG7izREoCdnRmOToiB7Z0E/P73v4/L5eLcc8/NdmhCCCGEEHmvIGYAisKiVwAWl9ixOyxZjiZ79Oo/gKn5MP8vXgGYTPUfQOM6bcO31VlM0ZhxgJYA1IVlEUjeK63V5quGIlFaurv7PSYQ8PLk47cSi8Wwmmxcs+iXmI2jsz/cZDBgMmhfB4GAn/7WWdtdJYA269a/n43BQmTa3jMBL7vsMv72t79lOSohhBBCiPwnCUCRd/QEYCFX/wGsiCcAi6pLGDNrbJajGZlIJIIa07IcySYAGz7SKgArJ81MVPqZTAb0GjBZBJL/nGVFmKxaMm9XR2e/x/zn+d/S2aFVD19yxHXUlU7KVHjDYrNoBfzRaHSP9nid3VGSeCxVgGK0mVo9nT9+/W+UOrTk/He+8x2efPLJLEclhBBCCJHfJAEo8o6eAKweWzLIkfkrFIzw9htbAK39N9dbXPX2X0guARgOhGn9RFsKUzWptw1aUcAYn5smCcD8pygKpdVaoqHT58ezV0Xcuo9eY80HLwJw+IRjOWnGlzIeY7KsJnPi67q/GbJWuwtDvEpQEoBiNJpWPYM/XPxXiu0lqKrKt7/9bZ577rlshyWEEEIIkbckASjyjj4DsJAXgHz4zg58Xq0qKB/af/UKJ6PBkNT8v5aNjcQiWotv5aQ9tyCb423AkWisvw5KkWdKqsu0zC+ws08VYGdnM8//6w4AyuyVXHXMTTmRMFcAa3zBVDCoLQPZ8wAFu1P7I4gkAMVoNWvsgfzpkr/htLqIRqN861vf4sUXX8x2WEIIIYQQeUkSgCKvRKNRmpq0iq9CTgCufH0TAEaLiQlHTctyNCOjqr0VgEm3/67rswBk0p6LUExm7dufikpEqgDznslioqhS+57Q2NVFOBolFovy9D9/QSCgbVq/euGtFNvKshlmUmzm3hmFgeC+c/7sTu359nR3E5VZl2KUmlN/CPdd9BB2i4NIJMI3vvENXn/99WyHJYQQQgiRdyQBKPJKa2srkUgEgDG1hdsC/OZrWgJwwhFTsTisWY5mZCKRCKqq1ehZkl0A8pG2AMRVWYutqHSP9+2xCGTv6imRl8pqywGIxVR2d3Sy4o1H2bFtDQBfPPBCDqk7KpvhJa3vMhC/z69ly/uwOUsBiKkq3V1dmQ5PiCGbN2E+937lj1hNVkKhEBdddBErVqzIdlhCCCGEEHlFEoAir+jtv1C4S0A+2+pm1/Z2AKYemz/tvwBm0/AqAKv2av8FMBgUjEat1VPmABYGe5EDW5EdgPWffMDrrzwIwMTy6Vw4/zvZDG3Y7BatCjAWixIM7rkMRG8BBuiUBKAY5Q6bfCR3X/AAZqOFQCDABRdcwOrVq7MdlhBCCCFE3pAEoMgr+gIQgDG1hZkAXBGv/gOYkgcJQL3912QwYEhiNpu/00fnTi0RWrlX+69OTyhKC3DhKBtbQTQSZN2yPxCLRbEYrXz/2NuwmHKzUtZqMvVZBuLb431GkxmL1QHIHECRG46etpA7vvw7TAYTPp+PL3/5y7z//vvZDksIIYQQIi9IAlDklT0SgDWF2QKst/9WTq2mtK48y9GMjKpCOByf/5ds9d/anYnH/VUAQm8bcAyViMxIKwhFFcVs//Ap/D3NAFx82PeoL5ua5ahGxh6fBRgOh4mEw3u+TxaBiByzaOZifn3ubzEajHg8Hs4991zWrl2b7bCEEEIIIXKeJABFXtFbgJ1FVpyu3KzoGQlPT4AP3t4OwNTjcr/6LxIJJ+b/JbsApDHe/qsYDFTUT+/3mD3nAEoVYCHYseYNGjctA+DA2iM4aeZ5WY5o5PouA/H7/Xu8z+7SEoDBYHCf9wkxWp1wwCn8/KzbURSFrq4uzj77bD7++ONshyWEEEIIkdMkASjyil4BWKgbgFcv/4RoRKtkm7Io9xOAevsvDCMBuFZLAJaNm4zJauv3GKNRwWiQOYCFwtvp5s2//RqAImsplxz2EwJ7VczlIoOiJJKAgUCAWJ+lNnZH3zmAnZkOTYhhW3LwF7n5jF8B0N7ezpe+9CW2bNmS5aiEEEIIIXKXJABFXulNABZm++/yV7QKCVuxnbp5E7MbTAro7b8mY3Lz/1RVTSwAGWj+n84Uby0ORyQBmM/UWIzlf/kFQa+2DOObR/+UEnsFwUiEmJr77d/2PlWAPl/vLECr3YUhvim4s6Mz02EJMSJnzjuHG067FYDW1lbOOussduzYkeWohBBCCCFykyQARV7RW4ALcQFILBZjxWsbAZi0YCaGJGfmjTba/D9tq2my1X9duzrwd2hJkIHm/+nMZpkDWAjWv/4EDRvfAeDEA8/jsGnHJ97nC+V+FaDRYMBiMgEQCPiJ6a9lRemdAyibgEUOOvewr3DdKTcA2s/4s88+O/GzXgghhBBCDJ0kAEXeUFW1oFuAN65toN3tAWDqov1XveWCcDhMfPwfliQTgHr1H0DV5EEqAM0yBzDfte3awjv/egCAcWWTufDIazEYDZgs8YRZOExMf7HlMIfFAmjfC/19qgD1BGBPd7dsvBY56cKjvsGVx18DwPbt2/nSl76E2+3OclRCCCGEELlFEoAib7S1tREKaRVjVQXYAvzmq9r2XxSFyQv2X/WWC/TqPwDTMOf/maw2Smon7PdYo6F3DmBI2oDzTiQUZOmfbyEWCWM0mPjuCb/CarYDYLZZEsflwyxAk8GQqJb1+/2oMS2paXeVAhBTVbqkClDkqG8tvJJvHHMZAJ988gnnnHOOvJ6FEEIIIZIgCUCRN/TqPyjMFuAVr2sJwHGHTMBR7spyNCOnLwAxJzn/D3o3AFdOmJGYf7Y/ZnN8DmA0Su7XgYm+3nnmPjobtwFwwRFXM7GyNzluNBkxxj/3/nA4Lz73e1QB+rUqQLuzBAXta6izoyNrsQkxEoqicPUJ1/Hlwy8EYN26dXz5y1/G4/FkOTIhhBBCiNwgCUCRN/rOBCq0FmB3Sw8b12oJ0Kl5sP1XVVUiYT0BaErq3Gg4StOG3cDgC0B0+hxAFVVaJPPIznWr2LD0SQAOqjucJQdfuM8xZpsV0F5z+VAFaDYaE1WAPp8PNRbDYDRhtWt/FOiQBKDIYYqi8KMv3MTph3wJgHfffZcLL7wQv9+f5ciEEEIIIUY/SQCKvLF79+7E4zG1hdUCvPL1zYnHU487IIuRpEaoTzWWOcllJq1bmokEI8Dg8/90JpMRvcYwJAnAvODv6WD5X38JgMtawreP+zkGZd8feSazEYPeNhsK7fP+XNS3CtDrjVcBxtuAOzo7UfNg3qEoXAaDgZu/eBsnHvAFAN58800uueSSxAgQIYQQQgjRP0kAiryhtwDb7GaKim1Zjiaz9PbfotpSqmbUZjmakQvHf5FTALMhuW9T+vw/GHoFoMEARpN2n7DMAcx5qqryxl9/SaBHq3b71qIbKXdVD3i8xa4lzGJ5VAWobwT2+31Eo1Ec8QRgNBqlu6c7i9EJMXImo4nbzr6TBdOPA+Dll1/m8ssvJyp/wBFCCCGEGJAkAEXe0FuAx9QUoyQ5My6XhYIR3n7jU0Br/82H567P/zMZjUk/H33+n72kHGdZ1ZDP0ysNI7GoVEjluI+XP8POdasAOG7WWRwx5YT9Hm80m1CM2o9DX55UETktvQtOfF5vogIQoKOjM/MBCZFiZpOF27/8Ow6bdCQAzz77LFdffTWxWCzLkQkhhBBCjE6SABR5Q28Briqw+X8fvL0dv09LWkzLg/bfWEwlEtFaeC1Jtv8CNKzdCWjVf8kkD3vnAGrLQERu6mjcxttP3QtATUk9F3/+h4OeoyhgsWuzAPOlCtBoMGAzmwEIBAKAAYvVAcgcQJE/bGYb93zlD8wZfwgAjz76KD/60Y/kjzhCCCGEEP2QBKDIG7t2aZVfNeNKsxtIhunz/0xWMxOPmpblaEau7xwnfZnBUAW9QdyftgJQNcT2X53JZEhsSpU5gLkpGg6x9M8/IxoOYTSY+M7iX2EzO4Z0rikPqwAdfaoAezyeRBuwbAIW+cRhdfL/LvwzM2u0BVgPPvggP/vZzyQJKIQQQgixF0kAirwQjUYTFYCFlABUVZUVr2nz/+qPmIrZbhnkjNEvFI7P/1MUTEkmAJs27Ib4L31Vk2Ymda6i9FYBhmQOYE5677k/0L7rEwDO+dwVTK0+cMjnKgpY86wK0KAoiSRgJBzGZNGSocFQCK/Pm83QhEipEnsJD1z8FyZVTgHgnnvu4c4778xyVEIIIYQQo4skAEVeaG5uTrSN1hZQAnDHVje7drQD2vy/fKAvALEYezfzDlXfBSAVE2ckfW89ARhVY0SleiSn7N74LmtfeRSAWbXzOOOQbyR9DaMlP6sAjfFFOlHMibd3tEsVoMgv5c4K/vD1RxhXNh6AX/7ylzzwwANZjkoIIYQQYvSQBKDICzt37kw8LqQKwBWvbko8nnpc7icAo9Eo0ag2wD3Z9l+AhngCsKRmPFZHUdLnm8299wzFE8pi9At4ulj+8M8BcFiKuHLx/2fvvsPbKs8+jn/P0LK8R3biOJOEDPYmBAhQRpktm0BboJSWWUrLKC+UQksHhVJaaGkptHRB2XuGHQjN3nsnjh1vyVrnnPePI8k2WY4s+Ujy/bkuX1GsddvWsayf7ue5f4aq7v3jR6FrF2B7HnQBAhR67K9JUV1omh0Cyj6AIh/1Lx7AY994in7FAwC4/fbb+dvf/uZwVUIIIYQQ2UECQJEXEst/oW8FgB/Fl/9WjR1IyeByh6vpucT0X0htAEiiA7CyJrUwVNUUNNXuO5RBILnBsiw+euoXBJvrAbj8mNupKhqU8u1pbh01Hj4HIxEscr8T1KVpuHUdRQEtvgy4sanJ2aKEyJAhZUP502V/p9xfAcD3v/99nn32WYerEkIIIYRwngSAIi8kOgAVRaH/wL4xBbiluZ35X6wH8mP6L3QMAFFVJblssbva6lporW0G9n7/vwSFji7ASMzIg+gn/y3/5BXWzfsAgKPHnMZRo0/p0e0pgDu+l6ZlWQQj+dMFqCgKLo8fgGAwSDgcdrgqITJjRNVI/njpkxR5i7Esi6uvvprXXnvN6bKEEEIIIRwlAaDIC4kJwJX9CnG5dYer6R0z31+RXC478tjcX/4LHQNA3Kks/53fsf9f5V5OAO5Mj+8DaGERky7ArNa8bQMzn34QgKqiwXzr6FvTcru6W0eLd6C2RyKYebAfpKooFHo86G5/8nMNsgxY5LGxA8fzyPS/UuD2YxgGl19+OTNmzHC6LCGEEEIIx0gAKPJCogOwLy7/9ZX5GTR5mMPV9Fw0GsMy7aDFpe19iLt5vv0Y0HQX5UNHplyHS+8YPhKRADBrmUaMGY/fTSwSQlFUrpn2Mwo8e7/v4664CzzJ0/kyEMSj6xT4ClHi+yNu3LhhD9cQIrdNGro/v7v4MTy6h0gkwqWXXsrMmTOdLksIIYQQwhESAIq8kOgA7CsBYCxmMHPGCgBGHTseVcv9Qzka7QhZUtn/b/MCO8woHzYaTXft4dK7pqqg6/b3UwaBZK/ZrzxO/bolAJxz4JXsM3D/tN6+pmvobvtxFIpGiZlmWm/fKUU+L+74MuCG7Q0EggGHKxIisw6uOYzfXPAIuuYiGAxy4YUXMm/ePKfLEkIIIYTodbmfGog+z7KsPtcBuOB/G2hpbgfsADAfJAaA6KqKqih7uHRXpmGydZE9CKZqRM+/H4l9AGOmmRfLP/PNlhVzmfeGPdlzdP9JnHPQtzNyP4m9AAECebJfnoJCYWEZABYwZ/YcDOl0FXnu6DFT+cXXH0RVVFpbWznvvPNYuXKl02UJIYQQQvQqCQBFzmtsbCQYDAJ9JwBMLP9VdZWao8Y6XE3PWVZHB6Arhe6/+lXbiATt61eNSH3/v4REAAgyDTjbhIOtvP/ET8Gy8LoKuGbaz9HUzOz7qWoqLq8dAkZisbxZEl5UWJo83RYIsHjJYueKEaKXnLDvyfzkrF8AsH37dr72ta+xadMmh6sSQgghhOg9EgCKnJfo/gMY2EcCwI/jAeCwQ0biKfI6XE3PRaNREo12qQwA2bKg4zFQVdPzDkBNU5JdiJFYfoQ++cCyLD75168JNNQC8M2jb2VAydCM3qfb60aJPxbawuG8mAzt8fjROu2zuWnTZtasXetcQUL0kjP2P4cfnHw7AJs2beLrX/8627dvd7gqIYQQQojeIQGgyHmJ/f8ABgwucbCS3rFxXQNrV9YBMOq4fR2uJj0i8SELCqCnEABuig8A8RaVUlg5oMf1KAq44tOAI4bsA5gtVn3+Jqu/eAeAw0eexDFjT8/4fSqqkhwIYpom7XkyEKSgoBggGXQvX7aM2m3bnCxJiF4x/YhvccUx3wVgxYoVnH/++bS1tTlclRBCCCFE5kkAKHJe5w7AvrAEONH9B/mz/19i+a+u7f3+fwBb5tshcNWI8clurZ5KLAM2LStvBkDkstb6zXzy7/sBqPD354pjfpy2n/We6B4XanxpejASwbRy//FQUGC/WWJaFrqqYgHz58+npaXF2cKE6AXXHP99zj34IgDmzp3L9OnTCYVCDlclhBBCCJFZEgCKnJfoACwu9VHg9zhcTeZ99I4dAFaM7EdZdaXD1fScaVlEo3aXnUvf+73cwoEwdavszqWqmp7v/5eQ6AAEmQbsNNOI8f4TPyUaCqKg8N1p91Lo7b1uXwXwFHQstW8L534XoK+g4/s3pKwUVVEwDIPZc+bQLkGIyHOKonDraXfxlQmnAfDhhx9y1VVXEZPf9UIIIYTIYxIAipyXCAD7QvdfoDXEnM/XAvmz/Dcan/4Lqe3/t3XRJhIbCKZjAEiCqiroWmIZsOwD6KR5b/yN2lULADh9/28wYfAhvV6Dpmu4PJ0HguR2UODxFKBpLsB+fI8d0B+AUCjEF198kVyWL0S+0lSNe8/5NUeOPgaAV155he9///tYMvldCCGEEHlKAkCR8xJLgPvCAJDPPlxJLGqHUfmy/De5/5+S2v5/m+P7/6EoVA7fJ52lJZcBxwxDXhQ6pHb1Qua8+gQANVXjOO+Q7zlWi9vnRlHtZcetoTBWjo8ESewD2BgIMrislJrKCgACgQD/+9//iEnwLfKcS3dz//m/Z79hBwLwj3/8g7vuukt+3wshhBAiL0kAKHJeX+oA/Ojd5QB4i30MOWC4s8WkSSIAdGkaqezolggASwYMw11QmMbKOpYBW0BUwpBeF2lvY8bjP8EyDTy6j+um3Yce71pzgqIqyaXAlmURyPGlwIl9ANujUdojUUZWVTKkrBSA5pYW5syejSH7X4o8V+Au4HcX/5nR/ccC8PDDD/Pb3/7W4aqEEEIIIdJPAkCR0wKBAA0NDUD+B4CGYfLpDDsAHHHMPsmhBLnMMEyMeLDm1vZ+/z/Lsti8wA4A+41If0ekrqso8VhSlgH3vk/+dT9t27cAcNlRP2RQWY3DFYHu1tHd9mM1FI3mdDBc4O/YB7AxGABFYeyA/gwotjsDtzc0MH/+POmGEnmvxFfCo5c+yZCyYQD89Kc/5cknn3S4KiGEEEKI9JIAUOS0RPcfwIDBvTcUwAlL5m+icXsAyJ/9/zrvM+ZKIdBs2dpMoL4NgMo07v+XoCgdXYCRWO4GPblo5WdvsGrWWwAcOuIEjht3tsMVdXAXeJMTiHN5KbDb7UPX7Y7KhkAQsIcjjB80kMpCPwC1tdtYuGhRjn6FQnRfVVE//njZ36gsrALgpptu4sUXX3S4KiGEEEKI9JEAUOS0xP5/kP97AH749lIAFE1lxNFjHa4mPRIBoKoq6Ore/zraMr/j55/OCcCdJQJAwzIxpBOqV7TUb+aTf98PQIW/P9+e+n/JwC0bqKqCO74U2LTMnF4KnFgG3BgIJofpqKrCxCGDKfX5ANi0aRNLly51rEYhesvQ8mE8eumTFHmLsSyLq6++mk8++cTpsoQQQggh0kICQJHT1q1blzw9aFi5g5Vk3sfvLgNgyAHD8ZX6Ha6m5ywLIlE7OEll+S/A5gV2B6ju9lI2ODPLQxODQMCe/ioyyzRizPjLXURDQRQUrpn2Mwq92dfd6/LoaK6OpcC5OhW4wF8KQDgWoy0cTn5eU1X2GzaEIq8HsH/Xrly1yokShehVYwbsw+8ufgy37iYcDjN9+nQJwIUQQgiRFyQAFDktEQAWFXspLvE5XE3mbN3UxMqltQCMPj4/lv/GYjEs0+44cqe4n2FiAEhF9RjUFEPEPVE1BS0++TWX93vLFXNe/St1axcDcOYBlzN+8MEOV7RrHr+3y1RgMwc7RP3xABA6lgEn6JrG/sOGUuB2A7By5coub7oIka8OqD6Y+772IIqi0NzczHnnncfmzZudLksIIYQQokckABQ5LfFiNN+7/z6Kd/8BjDo2/cMunNBl/z9t7wNAI2qwdfEmAKoyMAAkQaGjCzAaM2QvtAzasmIu817/GwCj+k3k6wd/x+GKdk/90lTg1lDI4Yr2nq678bjtN08aAoEdznfrOgdUD8Ub73ZcsnQpmyQIEX3AtH2/wi2n3gnA5s2bOf/882lubna2KCGEEEKIHpAAUOS0RAA4eGiZw5VkVmL5b+mwCspH9HO4mvRIBIAuTUVNYX+3uhVbiYXtZZdVGRgA0lliH0ATi5h0AWZEONjK+3+9G8sy8boKuPaE+9A1l9Nl7ZHu1nF57Q65qGHQHo06XNHeSywDbgwGMc0dI26vy8UBw4bijgf1CxcupHbbtt4sUQhHXHDodC6fcjUAS5YsYfr06YRyMOgXQgghhAAJAEUOsyyLtWvXAjBoWP4GgO3BCP/7ZA0Ao44bn1XDEFJlWhbReFDi6uH+f5C5ASAJuksj8V2PSACYdpZl8fE/fkmg0Q6VvnX0bQwoGepwVd3n9nlQNfvpNBAOEzNNhyvaO4kA0DAtmtuDO7+Mx8P+w4aiqyqWZTFv3jy2b9/ei1UK4Yxrp93E6fvZU8g/+eQTvvvd72Lm2DEuhBBCCAESAIoctn37dgLxJWuD83gJ8KyPVhGJ2J1uo4/Lj/3/op2W/6a6/9+muesBKCirxF+e2a5IVQFdt39dyiCQ9Fsx81XWzH4PgCNHn8yUsV91uKK9oyjgKfSRSIlb2tsxc2ixeEFBcfKNhe07WQacUOTzMnnoEDRFwTRNZs+ZQ0tLS2+VKYQjFEXhzjN/zpGjpgDw4osv8uMf/xgrB/f8FEIIIUTfJgGgyFldJgDn8RLgxP5/br+HoQeNcLia9IhE7O4/RbEHDaRi4xz7599v5MS01bU7iX0AY6aZk8MeslVz7Xo+/c+DAFQVDeKKKT/OyS5XTVOT+wGalkVre+4sE1RVDZ+vCICGtp13ACaU+QuYOHQwqqJgGAazZ88m1Gl6sBD5yKW5+PX5DzNu0AQA/vjHP/L73//e4aqEEEIIIfaOBIAiZ3UOAPO1A9A0TT55bzkAI47eB82dmUm3vS0SsQMDt6aTStTTVtdC86ZGAPqPmpDGynYtEQCCTANOFyMWZcbjPyEWbkdRVK6Z9nMKPEVOl5Uyl8eF7rH3LYwaBsFOna7ZrqCgFIDWUIhobPeP78rCQvYZ0B+AUDjM7NmzZW9Mkff8nkJ+f/FfGFxmb09w55138swzzzhclRBCCCFE90kAKHJWYv8/VVUYMKjE2WIyZPmiLdRvawVg1PH5Mf03ZhgYhr1/UirTfwE2xpf/AvQb1TvLojVNSQ4riewhIBHdM+v5R6hfb3e4fu2gq9hn4P4OV9RzngIvavxxHYxEciYs9vvt36EWO58G/GWDykqprrDfeGlpaWH+/PlYObTsWYhUVBZV8eilT1BWYD/2r732Wj7++GOHqxJCCCGE6B4JAEXOSnQA9h9Ugu5KLUjKdh++Y4cjKAojp2R20EVvSef+f7rbS/mQUWmpa08UpWMacMSQfQB7av2Cj1n07n8AGDfwAM4+8AqHK0oPRQFvodc+AbSEQjmxZNzjK0RT7Q7j7gSAAKP7VdGvqBCAbdu2sWL5iozVJ0S2qK6o4XcXP4bX5SUajXLZZZexcuVKp8sSQgghhNgjCQBFzkoEgPm6/Bfg4/j+f4P3q6agotDhatIjEg8ANVVFU1P7FZQIACtr9kHVe29ZdGIZsGlZOTfpNZsEGrfxwZP3AlDkLeXaE+5Lhk/5QNVUvH57P0DLsmgNZf9+gAoKBfEuwO2BIHQntFQU9h08iGKv/bWuXrOGbdu2ZbJMIbLCpKH7c+8596MoCk1NTVxwwQXU19c7XZYQQgghxG5JAChyViIAzNcBIHW1LSxdsBmAUcfmx/Jfy+oYAJLq8t9oKMrWxfb3pd/I3tn/LyHRAQgyDThVphHjvb/cRThgT4/97nH3UFE4wOGq0k9367i8bsDeDzCQA4MyEgFgKBrt9v6Fmqoyaejg5PE8f8ECgsHdDxIRIh+csO/J3HjijwB7S5Lp06cTyoGwXwghhBB9lwSAIidFIhE2bdoEwOBh+RkAfvzu8uTpfNn/LxqLYsU7i1Jd/rt18SbM+B58vbX/X4KqKuhaYhlwbuztlm3mvPpXalfNB+C0ydM5YPgUhyvKHLfPgxp/nLdHo4SzPDT2+zt+l9a3dW8ZMIDX5WLC4EEoQCwWY87cuRjSISv6gEuPvIJzD74IgFmzZnHNNddgymNfCCGEEFlKAkCRkzZs2JAMkvJ1CXBi+W/xoDKqxgx0uJr0iIbtriKF1DsAN83pNABkRO8GgNCxDDhmGMnHoOiezUu/YO7rTwIwst8ELjzsemcLyjB7P0AfimrvB9gWCmNY2RsOuFwePJ4CYO8CQICKQj8jqioBaG1tZfmyZWmvT4hsoygKt5x6J0eOPgaA559/np/97GcOVyWEEEIIsXMSAIqclFj+C/kZAIZCUWZ9vAqwl/8q8YECuS4StQNAXVOTE3X31sa59s++ZGA1nsLitNXWXYllwBbkzITXbNDe0sCMv94NloXPXcj1J/wCXXM5XVbGqaqCx+8DwMKipT2U1bNy/f5SAJqCwb3u4quprKDc7wdg3fr11NXVpbs8IbKOrun86tyHGN1/LAAPPPAATz31lMNVCSGEEELsSAJAkZM6B4CD8nAJ8OyZawi123vljTouP5b/mqZFNGovgXSnOLjDsiw2zbM7APuN7P3uPwBdV1Gww0tZBtw9lmky468/pb2lAYCrpt5J/5KhDlfVe3SXhtvnAcAwTdqyeJ8wf6H9+9S0rG5PA05SFPYdNBB3vLt34cKFhHNg70MheqrQW8TvL/kLVUX9ALjpppv44IMPHK5KCCGEEKIrCQBFTkoEgIVFXopLfA5Xk34fvWMvn3P53FQfNsrhatIj0mmoQKrLfxvXbae90R4w0H/UxLTUtbcUpaMLMBKTALA75r/5FJuXzgLghH3P5fBRJzlcUe9z+dxoLjv4DsdihKJRhyvaOZ+vGFW1j8/61r0MAAGPS2fcIHuoSzgSYdGiRWmtT4hsNaBkEA9d9Bg+l49YLMY3vvENlslSeCGEEEJkEQkARU5au3YtYHf/5cvy2ATLspL7/w0/cgy6Jz+WSSYCQEVR0FMMADfO7bT/Xy8PAOksEQAalokh+wDuVu2q+fzv5T8DUF0xhkuP/IHDFTlDAbx+L4pqP3bawmFiWTgsQFEU/PFpwNsDAXt0916qKipicGkpANvq6ti8ZUs6SxQia+07eCL3ff1BFEWhpaWFCy+8kG3btjldlhBCCCEEIAGgyFHJAHBo/i3/XbFkK7WbmwF7/798kQgA3ZpGqpHtpvj+f57CYor7O7eENDEIBCCS5ZNdndTe2sh7f74LyzTw6D6uP/GXuHWv02U5RlEVvIUdX39LKISVhTsCJqYBh6JR2sKRPVx650b3r8Lrst+8WLJkiSwFFn3GseNO4Icn/xiA9evXc+mll9Le3u5wVUIIIYQQEgCKHGRZFmvWrAFg6PAKh6tJvw/eWmKfUBRGH+9cl1s6xWIxzHi3k1tPrfsPYOMcOwDsN2JfRzs/VU1Bi092lUEgO2eaBjMev5tAk939cvmU2xlcNsLhqpyn6Roevx0CmqZJayj7grHEPoAA29vaUroNXdMYN9BeChyNRlm8ZElaahMiF1x0+De44NDpAHzxxRdce+21yedAIYQQQginSAAock5tbS3BoL0PXD4GgB++bS//HbxfNf7KIoerSY9wpy6iVAeABLa3sX21PVW0/5jJaakrVQodXYDRmJGFPVzOm/vqX5P7/h0//hyO2ed0hyvKHi6PC91td8dFsnA/QF134/HY03zr2/Z+H8CEikI/g0rt5cS1tbXUylJI0YfcfPKPOWr0VACef/557rvvPmcLEkIIIUSfJwGgyDmrVq1Kns63ALB2czPLFm4GyJvuP+hY/qtrKmqKnXsb/rc2eXrAmEnpKKtHEvsAmljEpAuwi42LPmPOa08AUFM5jm8cdYvDFWUfz5f2AzSyrDuoMN4F2NTe3qPH95j+/fDEQ/+lS5diyLEi+ghd0/nlub9lVL+xANx///38+9//drgqIYQQQvRlEgCKnLN69erk6aE1+RUAfvjO0uTp0dMmOFhJ+piWRTTe4eTWUuv+g44AUPd4qRg2Jh2l9Yju6tjLMCKhRlJbQy0z/no3WBZ+TxE3nvRr3LrH6bKyjqLQZT/AbFsK7C8sBewtF7YHUu8C1DWNUf2rAGhvb+/y+1uIfFfoLeLhSx6jorASgBtuuIFPP/3U4aqEEEII0VdJAChyTmL/vwK/m4qqQoerSa8P37IDwLLqSipG9nO4mvSIdFn+m/r+f+u/sH/u/UZNRE1xGXE6qQrouv0rNCqDQAAwYlHefewOwgF7iM13j7uH/iXODWvJdpqu4fbZ4WjMNAhGUhu4kQleXxFaPLCvb01tH8CEgcXFlBX4AFizdi2B+BYOQvQFg0qH8NBFf8Kje4hGo1x22WUShAshhBDCERIAipyT+MN5SHW5o4Mg0q2tJcT/Ztoh1+hpE/Lma0ss/1UUBV1LLQBsbw5St6IWgAEO7//XWXIfQNPEtGQnwM+ffZi6tYsBOGP/b3JQzbEOV5T9XF43ajwYD0YixLJkKbCCkpwGXN8WwOrJ41tRGDugP4qiYJomS5YsTlOVQuSGiUP2455zfg1AQ0MDF154IU1NTc4WJYQQQog+RwJAkXMSAWC+7f8384MVxKL2UtJ83P/PrXcsmd1bG2evg3gAkQ37/yUkAkCQacCrvnibxTP+C8D4QQdx/qHXOFxRblAU8Pq99gmgNRRyuKIOhUXlgP3Ybgq29+y2vF6GlcUDxfrt1NbW9rg+IXLJSRNO5dppNwH2Xsbf+MY3ks+PQgghhBC9QQJAkVNM00wuAR6SZwHgB2/by399ZX6GHDDc2WLSJBqNYcY7mtwpdv9Bx/JfzeWmcvg+aaktHTRNSQ41icT6bgDYtGUtHz31CwBKCyq5/sRfoqnOL9POFaqm4va5ATBMM2uWAvv9pclO5J4uAwaoqapIDgRZtny5dM2KPufyKVdz+v7nAPDRRx9x880396y7VgghhBBiL0gAKHLKli1bCMU7ZPJpAEgsavDpe8sBGDl1XHJJYK7r3N3g7sG+fRviAWDVyH3RXO4e15UuitIxDThi9M19ACPtbbz96K3Ewu2oisb1J/yC0oJKp8vKOS5P16XA2TAVWFU1CgpKAKhra0124aZK1zRG9rMHggSDQdavX9/jGoXIJYqicOfp93LQ8EMBeOqpp3j44YcdrkoIIYQQfYUEgCKndJkAnEcdgHNnraO1xQ42x+TJ9F/oCABdmprslNtbodYQtUu3ADBgdPYs/01ILAM2LStr9m/rLZZpMuPxu2netgGACw+7nvGDD3a4qtykKODxd0wFbgtnx1TgxDLgYCRKW7jnnYkDS4op9NiDT1avWiUDdESf49Ld/OaCP1BdMRyAn/zkJ7z88svOFiWEEEKIPkECQJFT8jUA/DC+/Fdz69QcNdbhatLDNC2i0SgArh50/22auw7LjO//N3a/dJSWVokOQIBIHwsz5rz6OBsWfgLAkaNP5qv7XepwRblN01Rc8anAUcMgFD9+nFRYWJ48XdfW2uPbUxSF0f3tCeeRaFSmoYo+qbSgjN9d/GeKfSVYlsXVV1/N3LlznS5LCCGEEHlOAkCRU1atWgWAv8hDWYXf4WrSw7IsPnhrCQDDjxiN2+9xuKL06LL8twf7/234Yi0Aqu6iasT4npaVdqqqoGuJZcB9Zx/AtXM/YM6rfwWgumIsV029K28mVzvJ7XWjqPbjKRCJYOHs/mC67sbrLQTSsw8gQEWhnwq//ft7/bp1tGfR4BMhesvwyhE8cMEj6JqL9vZ2Lr74YjZt2uR0WUIIIYTIYxIAipzSeQJwvoQNq5bVsmVjE5Cf039VRUFPwwCQqpp90N3ZGY4mlgHHDKNPbOjetGUtHzzxUwAKPSX84OQH8Lh8DleVHzovBbYsi0Aalt32VGIZcHN7iHA0PV2uo/pXoWAPPVmxfHlablOIXHNwzWHccfo9ANTW1nLRRRfR1paeoF0IIYQQ4sskABQ5pXMAmC8+eGtp8vSo4/IkALQ6AkC3rpFqVBsJRti62O6I6D96cpqKS7/EMmALe+lmPksM/YiG21EUletP/CX9ioc4XVZe0V0amsteNh+KRh0fCNJ5GXB9msKJIq+XgaX2gJHNW7bQ2trz5cVC5KKzDvg63zr6OwAsWrSIb3/72xh5/jwihBBCCGdIAChyhmEYrFu3DsivAPCj+P5/AycNpah/icPVpEc0FsOMhxYurWf7/5kx+3YGjM3eAFDXVZR4zJnPy4C/PPTjosNuYNLQwx2uKj95Cjq6XZ0eCOLxFOBy2fXUpTGoG1FVmRwOtHLVyrTdrhC55tppN3HC+K8A8Oabb/J///d/DlckhBBCiHwkAaDIGRs3bkx2leVLAFhX28Li+XaH2+i8mv7bEVi49dSX/66dae/5qOou+o3K3u+PonR0AUZi+RsAzn7lLzL0o5eomorL6wbsrtKwwwNmEsuAGwJBYmkKub0uF4PLSgGord1Gc0tLWm5XiFyjqir3nHM/Ewbbk+4fffRRHn/8cYerEkIIIUS+kQBQ5IwuE4Br8iMA/OidZcnTebX/X3zfMpemJjt8UpEIAPuN3BeXJ7v3mEsEgIZlYuThPoBrZr/H3NeeAGToR29x+zwoqv09DkSc3QuwqKgSANOyqEvjHmU1FRVo8cfRihUr0na7QuQan9vHby/6EwNKBgFwyy238O677zpclRBCCCHyiQSAImckJgBD/gSAiem/pUPLqRoz0OFq0sMwTaLxbiW3nvry32BjgNqlWwAYNO7AtNSWSYlBIAARh7u10q1+/TLef8LeqF6GfvQeRbFDQADTNGmPRh2rxecrQtftjsRtLelbBux26QwpLwOgvr6exqamtN22ELmmqqgfv7v4MQrcfgzD4PLLL2fp0qV7vqIQQgghRDdIAChyxvL4pMiyCj8lpQUOV9NzgdYQX3xidzWOOn7fvOmminSaWuruwf5/6z9fDfFOukHjsz8AVDUFLd6tlU8BYKCpnrf+8COMaBhN1bnpK7+RoR+9SPe4UONTtIORCBbOdZcWFdlvvGxvC6RtGTBAdUU5umr/ObJSugBFHzd2wDh+ed5DqIpKa2srF110EXV1dU6XJYQQQog8IAGgyBkrV9qbxA8fWeVwJenxyYzlRCP2i+ixJ05yuJr0Ccf3/9NUBV1L/VdMYvmvy+enonpMWmrLJAVwu+2gJmoYWHmwDDgWCfH2Iz8i2FwPwBVTfsz4wQc7XFXfogBun915Z1kW7RHnugATAaBpWWmbBgx2p/DQeBfg9oYGGhoa0nbbQuSiKWOO5eZTfgzA+vXrmT59Ou3t7Q5XJYQQQohcJwGgyBmJ/aGqR1Y6XEl6zHh9MQAF5YUMObDG4WrSw7IsovG9ynqy/Bc6AsCBY/dD7UEnYW9KLAO2yP1pwJZp8v4T91C/3t6n8rTJl3Lc+LMdrqpv0t06anyYTnskiulQuOwrKELXXUB6lwFD1y7Azts9CNFXXXTYZZx/6CUAfPHFF1x77bWYpulwVUIIIYTIZRIAipzQ2trK1q1bAajOgw7AUCjKJzPsQHPMCRNQe9Apl00ikWhi1W6Plv82bWygaaPdBTQwB5b/Juh6x9CTXF8GPOfVx1k7ZwYAB1Qfw8WH3+BsQX2cp8DeC9DCIujYQBClyzJgI41hhK5pXboAZS9AIeCHJ9/BkaOPAeD555/nF7/4hcMVCSGEECKX5UZbjegxTdP2fKFeuI1UdZ4APHxkVc7vlzfro1W0B+0X8WNOnIS90C+dnPn+JJb/Kgq49NQfL+s+6+gAyoUBIAmKYncBhiMxIrHc7QBcNett5rz6VwCGlY/muhPuQ1WdO/4FaLqG5tIxojFC0SgFbnePJmynqrCogsbGrRiWRX1rG/1LitN228Mqylnf0IhhmqxetYqDDjqoR7eX688TfUHiZyQ/q51z6S5+fd7vuORPX2NF7TJ+/etfM3r0aM4991xH63Ly70HRPYmfkfyscov8vIQQmSYBYB9RVlbWo+trmtbj2+iJTZs2JU+PHjcIl8vtWC3p8MGb9lQ/T6GXEUeOQVXT9+Innbe1Nyw6BoC4dR2lByFkYvlvQWklJQOqcSrQTIXbbQeAJhZRw+jWUuhsevFbu2oBH/7tZwCU+Mr54akP43MXOlxVtnD25+Qp8BBstjtLg5EIRV5vr9dQUFCCrrmIGVG2tbYxsKw0bbftUVWGlpextn47dfX1BIJBSktLUrotRQGX25W22kRm6S75c3RXytzlPPrNJ/n6Q6eyva2ea6+9ln333ZejjjrKkXqc/ntQ7J3i4vS9SSMyS44tIURvkL+4+ojGxsaUrldcXIymaRiGQUtLS5qr6r65c+cC4PHoVPQrIBp1aglcz8WiBu+/Ze//N+q4fVF0DdNMz55eqqqk7bb2VjQaTe5PZC//Ta0O0zBZ84k98GXQ+AOxs7HcGajhcqko2BWHYzFcu3g3t3Poly0DQ5pr1/PmH36EEYugqy5u+sqDVBUNJJe+/5mT+Kk6R9VUdLeLWCTqcBdgOU1NtdS3tRKNxdDU9G1hMKy8jA3bGzAsi2XLlnLA/gfs1fV1lwtFsQeIx6LODUwR3aMoCrpLJxaNZc3vwWzUz9+fhy76E9/48/mEI2HOOOMM3nrrLWpqem//4Gz5e1B0j6ZpFBcX09LSgpHjexLnOzm2UiNhqRCpkQCwj0jHk7+Tf0AsX74cgGEjKlEUJadfKMz+bA0tTfY0v7EnTSR9oULnIKD3vz/hcDh52t2D5b+bF2wg1GJ/fwZPOLTHdfW2xDLgSNSw9wH0eJwuqVvaWxt54+EfEA40A/C9afcyduB+zhYlduD2uYnFJwEHIxEKHXh8FRVX0tRUi2GmfxmwW9cZXFbK+oZGamu30dLSQlFRUUq3lcvPE32NZVny89qDiUP2455zfs1N//4eDQ0NnHfeebz22muUlpb2ei0SKOUOwzDk55VD5GclhMi0/Jg8IPJePk0ATkz/1b0uao4e63A16ROJDyZwaVqPupJWf2iHvYqiMnh8z/YAc4rbbQeghmUvA8520XA7b/7+h7TWbwbgkiNu4ohRX3G4KrEziS5AgFDUmYnAvoLi5DTgrRnoVqiuKE/+DlnVaf9XIfq6kyacyrXTbgJg5cqVfPOb3yQqna5CCCGE6CYJAEXWi0ajrFmzBsj9CcCmafL+m0sAGDFlH9wFudEdtieGYRKLT73tSfcfwOqP7ACwasR4PIW5uXeNy6Ul+zHDWT4N2DQNZjz+E+rX2Y/Lr0y8kNMmT3e4KrE7bl/HHqhOTARWUCgqtt+M2d4WIJrmgTcel4tB8b3/arduJRAIpPX2hchll0+5mtP3PweADz/8kJtvvlm6J4UQQgjRLRIAiqy3bt265Dvcw3O8A3DR3I3Ub2sFYOyJEx2uJn06L//1dGPoxa4E6tvYutjuQhs88ZAe1+UUVbVDQMjuANCyLGb+50HWz/8IgINrjuOyI2/OqqEkYkfZ0AVYXGy/GWNaFttaM9EFWGFv90DXKfBC9HWKovB/p9/DgcPt58i///3vPPTQQw5XJYQQQohcIAGgyHqJ5b8Aw3O8AzCx/FfVVUYdt6/D1aRPYvmvpqo9Ggiw+pOOn/WQHNz/r7PEMmAzi5cBL3j7nyz54DkARvefxLXTfo6q9qyDU/QOp7sAvd5C3G57CvHW5vQHgD63i4HxvQU3b9lCMBhM+30IkavcuocHLniEYeXDAbj77rv5xz/+4WxRQgghhMh6EgCKrJcIABVFYWhNhcPVpM6yLGa8YQeA1YePxlvsc7ii9DAti2g8gEjX8l9vURkVw0b3uDYnudzZvQx4xczXmfXcHwDoXzyUH57yEB5Xfjwm+4Js6gJsDLYTysA+ZMMrKuzZy5aV3AZCCGErLSjj99P/Qrnf/rvohhtu4JVXXnG4KiGEEEJkMwkARdZLBIADBpfg7dT1kmuWL97CpvWNQH4t/42EI8mZwz1Z/msaJmviHYBDJh6C0oNOwmygKp2WAUezKwBcP/9jPvz7zwEo9pVz62l/oNhX7nBVYm+5HO4CTOwDCJnpAizwuOlfbE8A3rR5E6FOWw0IIaC6ooZHpj9BoacI0zS58sor+eCDD5wuSwghhBBZKrdfYYs+YeXKlUDuDwB555WFACiqwpg8CgAT+/+pioKupd4BuGXBRkLN7QAMzvHlvwnJZcBYRLJkGfCWFXN59893YJkGPpefW0/9PQNLq50uS6RA01R0tx26O9EF6Hb78HoLgcwEgADDK+3uJtO0WCtdgELsYNygfXno4j/h0T1EIhGmT5/OnDlznC5LCCGEEFlIAkCR1SzLYtmyZUBuDwCxLIu3X7YDwOrDR+OvKHK4ovSwLCu5/59b1+nJ6IgV79lTaBVVZfC+B6ehOue53RpK/LuSDV2A2zes4K0//AgjGsGlubn5lIcY0S9/9qLsi1y+jkni7Q50ARaX2L+X28Jh2kKhtN9+oddLVZEdMm7YuDH5+0YI0eGg4Yfyq/N+h6ZqBAIBzj//fJYvX+50WUIIIYTIMhIAiqy2efNmWlvtqbkjxvR3uJrULZm/ic0b7OW/406e7HA16ROJRLDiXUc9Wf4LsPxde3/EAWP3w+PPj4BUUTq6AMOxWPJ75YTmbRt4/XffJxoKoCgq153wC/YdnB9Ba1+maSqayz722h3oAiwqqkqG3BnrAqywuwANw2DtunUZuQ8hct3UfaZx91m/BKChoYGzzz6bVatWOVyVEEIIIbKJBIAiqy1ZsiR5esSYfg5W0jOJ7j9VVxlz0iSHq0mfcNjuxlEUBVcPBoBsX11Hw9p6AIbtd1RaassWHo/9fbGwCMecWQYcaKrn9Ye+T6jVDqG/PfVODhlxvCO1iPTrPBG4PQPDOHZH110U+EsA2NLckpGQu6TAR7m/AID169cTy8KhOkJkg6/udxY/OvX/AKitreWss86SATpCCCGESJIAUGS1xPJfgJrRuRkAmqbJO6/aAeDwI8ZQUOZ3uKL0sKyO/f88upaW5b8Aw/Y7soeVZRddV9FU+7sTivVuOAMQamvi9YdupG37FgAuPvxGjht3Vq/XITJH07VkF2AoEsWid7sAS0rs383hWIztbYGM3EdNfC/AWCzGuvXrM3IfQuSDiw67jO+fdAsAW7Zs4ayzzmLt2rXOFiWEEEKIrCABoMhqiQ7AAYNL8Rd69nDp7LRo7kZqNzcDMO7U/ZwtJo0i0Y7lv+40Lf8tHzaaworcXeq9M4oCbo/9/YkaBoZp9tp9h4OtvPbbG2naYneAnL7fNzh9/2/02v2L3uP22l2AFhbtkd4NmguLytFU+zG+uak5I/dRVlBAic8HwLp164hlyVAdIbLRZUddyXUn3AzApk2bOOuss1gvwbkQQgjR50kAKLLa0qVLARg5Nje7/6DT8l+XxuhpExyuJn0S3X+KAu4eTP9tq2th84KNAFTvn1/LfxM87o7vT6iXli9G2gO8/tD3adi4AoAT9z2Piw6/oVfuW/Q+zaWhxZfht0d7twtQUdTkMJD6tjaimXiMK0qyCzASibBp48b034cQeeTyKd/hmuO/D8DGjRs566yz2CjHjRBCCNGnSQAospZpmskpdrk6AMQ0Td6NL/8dcdRYfCUFDleUJhZE4vv/uTUdRUl9AfDKGUvt9cTk3/5/CZqm4NLtX7ehXtijLRoK8ubvf0D9OruDduo+Z/LNKbf26Ocksl9iIrBlWbRHenefvOL4MmDTsjI2DKSy0E+R1/4a16xdi9mL3bRC5KIrp36Pq4+z3/hZv349Z5xxhiwHFkIIIfowCQBF1lq3bh3t7e1A7g4AmTdrPXW19hTj/Fr+G02++O759F87pCqsHEDZkBE9ri1beeLLgE3LIpzBLsBYJMRbf/gRtasWAHDU6FO4auqdqIr8us93uktDTXYBRnp1J0CvtxCPx36DY1NTczLUTytFSU4EDoVCbN68Of33IUSe+c6x1/LtqdcAdgh42mmnJVdXCCGEEKJvkVeEImt1/gM1VwPAd16xu/80t87o4/Nw+S/0aPpve3OQtTNXAlC9/9F53aHmdmuo8a8vU5NaY9Ewbz96K1tWzAHg0BEn8N3j70FVU/8ZidyS3AvQsnql27SzklL793RbOExrKJyR++hXXESB2/4aV69Zk5Gpw0Lkm+8dfyPXTfsBYE8HPuOMM5g7d66zRQkhhBCi10kAKLJWIgBUVYXqkVUOV7P3DMPk3dcWATDymH3wFHkdrig9Ok//det6MtRKxfK3F2HG7E7CmoOPTUt92UpROroAo4ZBLM3LF41ohHf/9GM2LZkFwIHDp3LdCfclhzOIvkF366jxPTmDkd7tAiwurkqG+JkaBqIoCsPjewEGg0G2bt2akfsRIt9cfszV3HraXQA0NDRw1lln8cknnzhclRBCCCF6kwSAImslAsAh1eV4vS6Hq9l7cz5bS0N9GwDjTt3f4WrSJ5rG5b9LXreXqRZWDqCyZlyPa8t2Ho9GIi5tj0TSdruJzr8NCz8FYPLQI7nxpF+ja7l33Iiec/s6ugDDvdgFqGkuCgvLAdja0pyxPfoGFBfjddmP7dWrV/dqyClELrvg0Oncc/avUBWVtrY2zjvvPF5++WWnyxJCCCFEL5EAUGStRABYk6PLf19/fh4ALp+bUceOd7ia9AmFQ4C9/Nfdg+W/gfo21n2+GoCag47N6+W/CZqm4HLZ37NQNIaZhuWL9p5/t7Bx8WcATB56BD84+QFcmrvHty1yk+bWUTT76T0Y6e1lwPbApqhhUtvSmpH7UFWF6go7aGxta2Pbtm0ZuR8h8tHp+5/D/ef/HpfmJhQK8c1vfpNHH33U6bKEEEII0QskABRZKRqNsnKlvTfcyBycABwKRZPLf8ecMAG33+NwRenx5eW/PQntlr29EMu0A7CaQ45LS325wOu1uyYtLELRng0DiYbbefP3P2TzUnvZ7/7DjuYHJ/8Wt54fy81FahTAHZ8IbFomoVjvhYB+fwkul/3429DYmLH7GVxaknwDYvXq1Rm7HyHy0fHjT+LRS5+gyFuMZVncfvvt3H777RiG4XRpQgghhMggCQBFVlqzZg2R+BLJXBwA8uHbSwm22UHZvmcc6HA16ROJRJKhncfVs+W/i1+zl/8W9x9K+dBRPa4tV+guFS3endUeiaQ8LDUSCvLmwz9gy/LZABw0fCo3nfwAbj0/wmbRM7pLR1Gd6AJUKC2z37RpaQ/R0h7KyL2oqkp1ud0F2NzcTP327Rm5HyHy1cE1h/H3K/7L4NIhADz66KN861vfIhgMOlyZEEIIITJFAkCRlZYsWZI8PXJs7nUAvv7cXAD8lUXUHDnG2WLSKDn9VwG3lvry35atzWycsw6AEYcc1yeW/yYogC/eBWhYJuEUurMi7QHe+N332brSXmZ+yIhp3HjS/bLsVyQpSsdegKZpEo71rNt0b5SU9Ese05sy2QVYVoorHqZLF6AQe29Ev1H8/cpnGT9oIgCvvPIKp5xyCuvWrXO4MiGEEEJkggSAIistWmQvn3W5NYYOr3C4mr3TuD3AzPft5cvjT9sftQf75GWTzst/PT1c/rvktfkkWt/yffrvzrjdWnJ6cvtedmdF2tt4/aEb2bZ6IQCHjTyR60/4hQz8EDvQ3a5OXYDpGzqzJ5rmoqioEoCtLS3EMrSsUNc0hpaVAfZU08ampozcjxD5rLKoise/9S+m7jMNsP/+OuGEE/jggw8crkwIIYQQ6SYBoMhKCxfa4caIMf3RXbkVoL310gIMw55+OeHMgxyuJn0ikQhWPLTryfRfy7KY//z/AKioHkPpoOHpKC+nKErHXoBR0yDazYCkvbWRVx+4lrq1iwE4avQpXHfCfRL+iZ1SFHB77S5Ao5e7AEvLBsTv12JLU3PG7mdoeTmaKl2AQvREgbuABy94lKumXgtAY2MjX//61/nDH/6QfN4XQgghRO6TAFBkpUQAOGb8AIcr2XuJ6b+Vo/rTf9/BDleTPqFQfPqvouDqQQC4ZcFGtq+uA2D0kSenpbZc5PXqKNhdgN3Zo62toZZX7v8e2zesAGDK2NP53vH3oqk924tR5Dfd40JRE4+z3usC9PmK8Hj8AGxsbCLlzS73wKVrDCkrBaCuro7m5syFjULkM1VV+e7xN/DABY9S4PZjmiZ33HEH3/rWt+S4EkIIIfKEBIAi69TX17NlyxYARo8b6HA1e2fdqjoWz9sI2MM/8mVvO9OyiEQ6Lf/twW0luv9U3cWIQ45PQ3W5SVGUZBdgxIgRM81dXra5dj0v3/9dmmvXA3DShPO5+ri7UdXc6o4VvU9RwNWpCzBi9GYXoL1/ayASoSGDgwWqy8uTS+qXL1+esfsRoi84fvyJ/PPbzzO8ogaAl156iWOPPZZPP/3U4cqEEEII0VMSAIqsk9j/D3KvAzDR/Qf5Nf03HAonG3i8PZj+Gw1FWfK6Pf132H5H4iksTkd5Ocvr1ZJh6q66s7ZvWMHL93+PQEMtAGcfeCXfPPpWVEV+fYvucXncHV2A4d6bCFxcXIUWD6nXN2RuGIjbpTM43gW4detWmjK45FiIvmBEv1H886oXOHniVwHYsGEDU6dO5d5778XI0J6eQgghhMg8eQUpsk5i+S/A6HG5EwAahslrz84FYNghIykZVOZsQWmUWP6rqSquHkz/Xf7OYsKt9m315eW/Caqq4vHYgWo4tmMX4NaV83nlN9cQarXDk+lH3MT5h16TN52loncoih0CAsT2Ys/JnlJVjZJSuwuwvrWNYHyIUCbUVFSgxY+LZcuWZux+hOgrCr1F3Pf1B/nJmffhc/kwDIPbbruNadOmsWbNGqfLE0IIIUQKJAAUWWfBArtDbEh1Of4ir8PVdN+sj1axdbPdeTLp64c4XE36xAyDaNTuGupJ9x/Agvjy34LSSgbtmz8DUnrC3gvQ1rkLcOOiz3j9oRuJhgIoispVx/6E0/a71JkiRc5zed3J4Lg39wIsLRuYvN9MdwEOKbffdKmt3UZDQ0PG7kuIvkJRFM468Fz+ddWLjB04DoAPP/yQqVOn8uijj2LuZusKIYQQQmQfCQBF1kl0AOZS9x/AS/+xwy1PoZd9vjLZ4WrSJxzv/oOeTf/dvqaOtTNXATDqiJNk/7o4TevaBWiYJqtmvc1bj/wIIxpGU3VuOPFXHDfuLIcrFbms816AUaP3ugBdLg+FRRUAbGluJprBScTVFR0TgZctW5ax+xGirxnRbxT/+e7LXD71alRFJRgMcvvtt/PVr36VVatWOV2eEEIIIbpJAkCRVdrb21mxwp5yOnp87gwAadwe4P237GVn408/AJfP7XBF6ZNY/uvStOSL61TM/vdnACiKythjvpqW2vJFogvQsixmv/EUMx6/C9OI4dF93HLqwxw28gSnSxR5wOVx2UkgEAj3XhdgefkgAAzTYmNTU8bux63rVFeUA/YwKekCFCJ9PC4vPzjlNv713RcZWTUagM8//5wpU6Zw7733EszgoB8hhBBCpIcEgCKrLF26NLmkZEwOBYCvPz+PWNTuqJl87qEOV5M+kUgUw7B/Hj1Z/hsOhFn4wmwAhu53BIUVudXdmWmapuByqSx66Y/Mf+mPABR5y7jjjMeYNPQIh6sT+UJRFdzejr0AwxnsxuvM6y3E5ysCYGNDE6ZpZey+qisqcMXfqEi8mSSESJ9JQ/fnP1e/xBVTrkZTNSKRCL/5zW848sgjefnll7GszB3fQgghhOgZCQBFVuk8ACRXJgBblsWL//4CgH7jBjFg3yEOV5Q+ie4/Bbu7JlWLXppDuM0eADDuOFnK+mWxaJhZf/8Zqz96HoCqosHcffaTjO4/ydnCRN5xeTtNBO7FvQATXYDhWIzalpaM3Y9L06iutJccNzY1UbttW8buS4i+yq17uPaEH/Dv77zEAdUHA7Bx40a+8Y1vcO6553b5W04IIYQQ2UMCQJFVEgNASsoKqBpQ7HA13bNo7kbWrKgDYPLXD82bCa2WZRGOT+30uHTUFL8uy7L43z9nAlAysJqB+xyQthrzQTjYylu/uZl1/5sBwPDKcfzfGU8yoGS4o3WJ/KQo4PZ5ADBMk1B8wE+mFRaV43LZQ53WbW+ADHYJVVdUJPcrXb5sGaZ0JAmREWMHjOOv3/o3P/vab6gsrAJgxowZHHfccVx99dWsX7/e4QqFEEII0ZkEgCKrJN41HjN+YM4EaS/8yx7+obl19j3jQIerSZ9QKJxcyuNxuVK+nXUzV7F9tR2QjjvurJz5ufaGQMM2Xv35NWxdPg+AycOO4NbTHqOkoAJDpiuKDNHdLhTNfvoPRCJY9EZAplBebm/r0BYOU9fWlrF70jSVkf3sMCIQDLJhw4aM3ZcQfZ2iKJw2+Uxeuu4dLjvyClyaG8uyePrppznssMO49dZbqa2tdbpMIYQQQiABoMgyV155JdOvOJnjT9nX6VK6JdAW5p1X7K7FsV+ZhK+kwOGK0ifU3g6Apqq4tNQn9s78ywcAuHx+Rh1+YlpqyweNm1bz8s+upmnzGgCmjP0qN5/yEIXeQgBMyyKDW6WJPkxRwBPvArQsi/ZI73QBlpT2R9ftNxPW1G3PaBfg4NJSCj3217hq1UpivbTfoRB9VaG3iO9/5VZeuf5dztj/ayiKQjQa5U9/+hMHHnggN998s4TxQgghhMMkABRZ5cwzz+SmOy7gzAsPdrqUbnntubkEA/Y+Wvt9PX+Gf0SjMaLxF8xelz2hNhWbF2xg7cxVAIw79kxc3vwJSHti85L/8erPryHYaHdGnnXg5Vx9/E/RNReq1vHdNkzDqRJFntPdOqpuB/vBSKRXlskqikpZ+WAAWkIhtgcyNzVUURRG97e7ACORKKtXr87YfQkhOgwsHcxPz/4l//3ua0wdezwA4XCYxx9/nEMOOYRrrrmGVatWOVylEEII0TdJAChEiizL4pknPwOgYmR/hh02yuGK0qc9ZHf/KYC3B8t/P/3T+wBobg/jp30tHaXlvOUfvMybD9xMpL0NBYVvTrmV8w+7Nrk0WgG0+JAG00L2LxMZ4ynwJk+3xff7zLTS0v5omr0/39r6+ozeV4XfT7nfftNh3bp1tMeHGgkhMm90/7E8dPFj/OuqF5k2/isAxGIx/vWvf3H44Yczffp0PvzwQ5kaLIQQQvQiCQCFSNEXn6xm7Uq7g+vAS47Km73tTMsiHLLDALee+vCPbcu3suK9JQCMOfo0fMVlaasxF1mmyaxnHuXjJ3+FZRh4dB8/OOW3nDTxgh0uq2pKsutS9gIUmaLpKi6PG4BILEbEyHzHqapqlJXZewE2BttpzGAXIIrC6P79ULCPo6VLl2buvoQQO7Xv4In85oI/8Pw1b3La5DPRVA3Lsnjttdc4++yzmTJlCk888QSBQMDpUoUQQoi8JwGgEClKdP95Cr1MPOsgh6tJn3Cn4R9ed+rdfzP/bO/9p2o6E046Ly215apYOMR7j9zJwtf/CUCZvx93nf0EB9ZM3enlFUguBTYtMGUzQJEhbp87+eZFr3UBlg1EVe3lx2vrt2f0voq8XgaVlgJQW1tLXYa7DoUQOzey32h+9rXf8NJ173Lx4d/A77H3u126dCk33XQTkydP5pZbbkkOgxNCCCFE+kkAKEQKtmxs4sO37W6SieccjNvvcbii9GlvtztyNFXFneLwj23Lt7L4tfkAjDz8RArL+6WtvlwTbNrOa7+8jnWz7UB0eOU+3Pu1p6ipGrfb62lqRxdgzJIuQJEZiqrgLrB/f5mmSSASyfh9appOadkAALYHAjQH2zN6f6P6VSV/ly1ZskS6aoVw0NDyYfzwlDt45wefcsupdzK8ogaA5uZmHnvsMY499limTZvGX/7yF5qampwtVgghhMgzEgAKkYLn/vF5sivrgIuOdLia9IlEosRi9jJAXw/2/pvxmzfAslB1F5NPuyRd5eWcho2refne71C/dhkABw4/hrvO+ivlhf27df1EF6BlgSFdgCJDdI8rORCkPRIh1gsBWXn5IFTV/hNk5ba6jE4Edukao/rZA0GCwSBr16zJ2H0JIbrH7ynkwsMu5YVr3+aR6X/l2H1OQIt3Bs+bN48f/vCHTJw4kauuuoq3336baLR3ppULIYQQ+UwCQCH2Ujgc5YV//Q+AmqPGUjEif7rbgkG7+09R7Om/qVj72SpWf7QcsCf/FlUOTFt9uWTjgs949effI9CwDYBTJl/MTSc/gNfd/UnImqqQ2ILRME0kAhSZoABef8dAkNZeGJahaS7KygcB0BgM0pDJvQCBQaUllPh8AKxavZo22W9MiKygqipHjj6G3170R96+6VNuPOlHDK8cAUAoFOK///0vF1xwARMnTuTmm2/m008/xZQuXiGEECIlEgAKsZfeemkBzY32i9UDLznK4WrSJxYziMSX/3ldrpSGmlimyYz7XwfA7fMz6dSL01pjLrAsiwWv/4u3fvsjoqEgiqLyzSm3culRNyf3PdsbiYnAFrIXoMgcVVOTS4EN0yTYC0uBy8sHoan2Gw2r6jLbBYiiMG5gf1RFwTRNFi5YINNHhcgylUVVfOOob/PitW/ztyue4awDzk3uFbh9+3Yef/xxTj/9dA444ADuuusu5s+fL8exEEIIsRckABRiL1iWxT8f+xiA0qHljJy6+33cckl7e8c+XKku/130yny2Lt4MwMRTLsJbWJKW2nJFLBrmwz/fyxfPPAKWhc9dyI9O/R0nTTw/5dtUv9wFKK91RIa4PO7kUuBgJEI0w1OBVVWnvGIwAM3tIera2jJ6f4VeL8MrKwBoam5m7bp1Gb0/IURqFEVhv2EH8pOz7mPGD2fx6/MeZtr4r+DW7anlmzZt4ne/+x3HH388RxxxBPfddx/Lli1zuGohhBAi+0kAKMRe+PT9FaxaZi/pPPgbx6Bq+XEImaZFKL7sz6PraOref12h5nbe/dWrAPjL+zH++HPSWmO2CzbV89ovrmfVzLcAGFhazT1fe4r9qnveJarFH2cWYMhAEJEhihJfChxPnFtDIcwMJ86l5QPRNfsNh1Xb6jPbBQgMr6igyGt3Oq5csUKWAguR5bwuLydOOIXfXPAHZvxwFj89+1ccMepoVCW+h+jKlfzqV7/iqKOOYsqUKfz6179m1apVDlcthBBCZKf8SC+E6CV/f/QjALylBUz62iEOV5M+7e3B5DIanzu17r8ZD7xBsMF+MX3oBdeiu/NnMvKe1K1ewot3f5v6NUsAmDzsCO752lMMLqtJy+2riv0B9jAQ6QIUmaJqKp4Cez9A07Iyvh+gqqiUVw4BoC0cZmtLS2bvT1UYP3AgiqJgmCbz5s2TqcBC5IgibzFn7H8Oj176JO/cPJNbTr2TA6oPSp6/ZMkSfv7zn3PYYYdx7LHH8sADD7B27VrnChZCCCGyjASAQnTT4nkbmT3Tnh554MVHJvfLynWmZREM2st/XZqGS9v7feo2zF7L3GdmATBs/6Oo3j9/9kbck1Wfvslrv7iW9ubtAJy233R+dOrD+D3Fab2fzt2m0gUoMsnl0dE99hsBUcPI+H6ApaX9cbniXXnb6jMeyBX5vIysqgSgtbWVpUuXZvT+hBDpV1lYxYWHXcoTlz/N2z/4lJtP/jGThu6fPH/hwoXcc889HHzwwZxwwgn87ne/Y8OGDQ5WLIQQQjhPAkAhuumpP9rdf7pHz6vhH+3B9mT3X4HHvdfXj4aivH7X8wDoHh+HXXBtOsvLWqYRY9bTj/DBn+/FiEXRVRdXH/9TLjnyppSGfeyJqkBiZbZ0AYpM8xR4UbWO/QDDsVjG7ktRVCqrqgEIRaOs396QsftKGF5RToXfD8CGDRvYsnVrxu9TCJEZ/YsHcMkR3+SpK5/lje9/yPdPuoV9B09Knj937lzuuusuDjjgAE4++WQeeeQRNm/e7GDFQgghhDMkABSiG9avrue91xcDMPGcQ/BXFDlcUXpYlpUc/uHSVNwpdP+996vX2L66DoADz7ocf3m/tNaYjUKtTbz5wM0sfONfAJQWVPJ/Z/2FY/Y5PaP323lvxpgsWxQZpCjgLfIlp4G3hkJEjcw95oqLK/H57N+ra7c3EI5mLnAEQFHYd/BAPLo9hXjhwoW0tLZm9j6FEBk3qHQIlx11Jf+66gVeveF9rjvhZvYZMD55/hdffMGPf/xjJk+ezGmnncZjjz1GbW2tgxULIYQQvUcCQCG64a8Pv49pWiiayqHfmup0OWnT3h7CjAdJBe697/5b/u5iZv/7MwAGjTuQccedldb6spG939+VbFkyG4CR/Sbws6//kzEDJmf8vhXF3sMM7KXbpnQBigxSVQVvkS/5/5ZQe0aX5/brNxywp12vqqvL2P0kuHWdCYMH2fsBGgazZ88mHA5n/H6FEL1jaPkwLp/yHZ7+7iu8dN07fO/4GxnVb2zy/M8++4xbbrmFiRMncuaZZ/LXv/6V+vp6BysWQgghMksCQCH2YMPa7bzxwnwAJpxxIGXVlQ5XlB6WZREMBgHQNRV3vBOmu1q2NvPqHc8C4Cks4ehv3YqSwvTgXGFZFsvef4lXf3EtgQZ7EvTx47/GnWc9Tnlh/16rQ9OU5GnDNHrtfkXfpOkaHr8dAlqWRVN7e8b2oPT6iigutn+/bmlqprU9swNIAMr8BewzwD5+Q6EQs+fMwTDkuBIi3wyvHMG3p17Dc9e8zvPXvMl3jr2OmsqRgP277eOPP+YHP/gBEyZM4Gtf+xp/+9vfaGjI/HYEQgghRG/K31frQqTJXx9+H8MwUVSFI66e5nQ5aRMMBpPdf/697P6Ltkd49vqnCDXby4eP/uYtFJRWpL3GbBGLhPn4iV/yyd9+jRmL4tLcXHXsXVx57B249d4dBqMAWrIL0O4EFCKTXB49ORnYsiyag5kLASv7VaMqKhawvLaW3tjscnBZKdUV5QA0NzczZ84cmQwsRB4b2W80Vx93PS9c+xbPfPdVrjjmuwwrHw6AYRi8//773Hjjjey7776cd955/POf/6S5udnZooUQQog0kABQiN3YtL6B15+bB8C+px9I+fAqhytKD8M0u0z+3ZvuP8s0eeXHz7J10SYAJpx0HkMnHZaROrNBa/0WXv35Naz46FUAqooG8ZOzn+TY8c4td1Y1hUQfoOwFKHqDy+tKTj43LYumYHtGHnsu3UNZxSAAGoPtbGluSft97MyoflX0KyoEoH77dubMmS0hoBB5TlEUxg4Yx7XTbuLl69/l3995iW8efRWDS4cAEIvFePfdd7n22msZN24cl1xyCa+88gqRDE9GF0IIITJFAkAhduPPv52Rn91/gWBy8q9/Lyf/fvSHd1n6xgIAhk46nAPPuTLt9WWL9XM/5sWfXMn29csBmDT0CH527r8Y0W/8Hq6ZWQp2CAh2g5QhmwGKXuD2upMhoN0JGCSSgeWy5RVDcLnsjsMVtduIZnACcYKiKEwYPJiqRAhYv53Zs2cT64X7FkI4T1EUxg+awA0n/pDXbvyAf3z7OS498nIGlNhvSESjUV5//XUuu+wyJk2axO23386iRYscrloIIYTYO4plyfqxviDVTY3LysrQNA3DMGhsbExzVTu3JfQawdi6Xrmv3Vm5dCuXnPJ7LMti3zMO5PRfX+R0SXugoKoKpmkBuz6sYzEjua+NR9cp9nm7fQ+z/v4J79z3CgClg2s47ZaHcXkLelR1NjJiUb545lEWv/1M8nNnHXgF5x5yNaq695OSd07pdDq1X8PRmIll2bfk0rUutyjSTSHVn1O+iYajhAMd+/MVuN0pDRHanUCgiY0b7Mnrg0pLGD9oYLeupypq8kdlprBM2TQt5m/cRH1bGwCFhYUcsP/+FBTk3++5bKAoCi63i2gkivw5mt1cbjeKYr/pFO1DHXCmaTJ/4xxeX/Ayr85/kcZg130BJ0+ezAUXXMDZZ59NWVmZQ1XuSNM0ysrKaGxslH1Ns5wTr7XyQWVlfuzJLkRvkwCwj5AAcO99/1t/5+N3l6G5NK586xZKh5Q7XdIedC8AbGxsIhqNomBvgK91c3DHnP98xht3vwhAQWklp/zoIYoqu/eiPJe01m1mxqN3Ub92GQBF3jK+O+2n7F99dJrvqecBoGlaxAz7urqqJvcGFJkgAWBnsahBqK09uUefW9Mo9HlR0xhDb968nNYW+7nrwOphlPn3HML1NAAE+7havGULW+PLj90uFxMnTqSqKj+2gMgmEgDmjr4aAHYWjUV4f9m7PD/naT5a8X6XQVxut5uTTz6ZCy64gKlTp6Jp6XqzMDUSAOYOCQBTIwGgEKmRALCPkABw78z9fC1XnfdnAA6+bArTbj/T0Xq6Z88BYCgUoqWlFbC7drq7/HfOfz7njbtfAMBXXMbJNz9IyYBhaak6m6z9YgYfPfFLou0BAPYZeADXnXhfhqb89jwAhC91AWoaimSAGSIB4JeZhkmoLYQZf3GpKApFXg9ube8miu9KLBZl7erZGKZBgdvNYSOGo+7hDYt0BIAAWBZrtzewcltd8lODBw1in3HjcO3lxHSxaxIA5g4JALuqa93Gy/Oe4/nZz7C6bmWX84YOHcpFF13ERRddxIABAxypTwLA3CEBYGokABQiNRIA9hESAHafZVlc+bU/sWD2Btx+D9957zYKygsdq6f7dh8AmqZFQ0MDpmmiqQplBQUoe0iLLMvi40fe46PfvwOAp7CYk3/wAGWDR2TiC3BMLBpm1r9/z9IZdsipoHDWQVfwtYOvQlMz9WI/PQGgaUEsZgcdmqqgd7OjU+wtCQB3xrIgHAwRC0eTn/PoOn6PBzUNaXRT01Zqt64GYHhFOaP699vt5dMWAMbVtbayZPPW5F6HHrebmhEjGDp0aLe7p8WuSQCYOyQA3DnLsliwcS7PzX6a1xe8TFu4NXmepml85StfYfr06UydOnWPb2CkkwSAuUMCwNRIAChEaiQA7CMkAOy+t16az4+vfRqAKTeczJHfPcGxWvbO7gPAltZWQu32vl0lPu8eJ/8aUYO3f/4yc/7zOQC+kgpOvOGXlA/Jr/CvYcMqPnjsHho32SFDia+C753wMyYNzfRk4/QEgGAHgIk5IG7pAswQCQB3JxaJEQ6GsOIPRAWFArcbn9vV49vesH4hwWALCnDg8GGU7mY/vnQHgACRWIxlW2upbel4Ye/1eBgydCiDBg2iwOdLy/30RRIA5g4JAPesPdLOW4te5ekv/snc9f/rcl51dTUXX3wxF154If367f6NjHSQADB3SACYGgkAhUiNBIB9hASA3RMMhDlv2m+p29pC0YBSrnzzh8mpl9lv1wFgOByhubkZ6N7gj8D2Np6/6V9s+GINAMX9h3LiDb/Iqz3/TNNg0ZtPM/v5P2PG7O6lCUMO5ZppP6PU3xt/VKQvAJQuwN4gAeCeWKZFOBgmFunoBlRVFb/bjacHy2aj0RBr18zFNE0K3C4OHVGzy+67TASACfWtbayqq6M1FO7y+bLSUsorKqgoL6eouFiWCO8FCQBzhwSAe2f51qU888U/eXnec7SGOt480HWdk08+mUsvvZSjjz46Y12BEgDmDgkAUyMBoBCpkQCwj5AAsHv+8Mu3eOL3HwBw5oPTGXfqfo7UkZqdB4CmadLQ0IhpmqiKQpm/YLdL87Ys2siz1/2D1lo7MOw3cgLHf++neItKM1x/72nbvpUP//wzti6fB4Cuujj/sGs4dfIlaZzyuyfpCwABYoaJGc87pAswEyQA7C4jZhAOhjFjHS86NVWloAdBYHNTLVu3rgJgcGkp4wbtfF+tTAaAAFgW21rb2NDQQGOwfacX8Xo8FPj9uN1uPB4Pbrcbt8uFy+VCd7lwx/91uVzout6np3dLAJg7JABMTTAS5I2Fr/DMrH8wf+PcLufV1NRwySWXcP7556d9yJAEgLlDAsDUSAAoRGokAOwjJADcsw1rt3PhSQ8RjRgMO3QkF/796j3ukZdddh4ANjU1E4n/sV7s8+7yBbhlWcz5z+e884tXMSIxAPaZegaHnP89NL3ny/iygWVZrJr5FjP/8WBy0MfQ8lFcc8LPqa4c08vVpDcAtIBo1A48VEXBpUkXYHpJALg3LCAWjhJpj2CZHUGcqqoUuFx4XK69Dr42bVxCW5v9PDRh8CAGlBTvcJmMB4CdBCMRtjY1sz0QpCUUSinAUhQFl67j9XrxFxZSWOinsLCIstJS3O7uDWnKZRIA5g4JAHtu2ZbFPP3FP3l53vMEwm3Jz7tcLk499VSmT5/OUUcdlZa/PSUAzB0SAKZGAkAhUiMBYB8hAeDuWZbF9Zc+yWcfrkTRVL754o30GzuoV2vouR0DwGAgSFvADrq8LhdF3p0vZw42BHj1/55l5YylAKi6i8Mvup4xR5/aK5X3hmDTdj596gHWz/kQsPcoO3W/Szjv0Gtw604s805vAAhgGBZGfA82l6amZQiDSJAAMBWWBbHIjkGgoih4XS58Lle3H6eGEWXtmnnEYhE0VeXQmmoKPF2P3d4MADuLGQYt7SHawmEC4TChaIyIESMSM4jEYik9cgoLC6msrGRA//6UlJbmZaegBIC5QwLA9AmGA7y24CWe/uKfLNo0v8t5I0aMSHYF9iTgkAAwd0gAmBoJAIVIjQSAfYQEgLv3yn/ncPdNzwJw0GVHc8LtZ/Xq/adH1wCw875/mqpSVuDb6bvKaz5Zycu3PU2g3n43uqhqEMdceQdVNfv0ZvEZY1kWKz9+nc//8zCRoP01VhQO4Orjf8qEIYc4WFn6A0ALiEVNLEBR7KXAIl0kAOyJRBAYDUUwja7BnFvX8bpc3Xq8tgdb2LB+ERYWhR4PB9dUd9kP0KkAcLcsi5hpEjVMYoZBNP4RMw2ihknUMAhGIgTCEdqjOw/CfF4vg4cMYciQIXg9ubIv7Z5JAJg7JADMjMWbF/LMF//klXkvEIwEkp93u93JrsAjjzxyr7sCJQDMHRIApkYCQCFSIwFgHyEB4K5tr2vlghMeoqW5nZIh5Vz+yg9w+3PxBVZHABiLRWlsbMKyLBRFoazAt8Om+bFIjPcffJNZT36c/NyoI77CYRdei8u76ymbuaS1fgufPPlrNi/+Ivm5Y8edxSVHfh+/Z8flg70r/QEggGFaGIZ9e7qqoqn52DfkBAkA0yUWNYiGIhjRWJfPq/GuQO8eugIbtm+irs5+juhXVMSkIYNIbHqZlQHgXjBNi9ZwiKZAkIZgkMZAELPTn2mKojCgf39GjBxJUWGhg5WmhwSAuUMCwMwKhNvsrsBZ/2Tx5gVdzhsxYgTTp0/n/PPPp6Kiolu3JwFg7pAAMDUSAAqRGgkA+wgJAHft1qv/xbuvLQLgvMe/zYijx/bafaeXHQBGozEamxqTXTYlBb4dOmvqV2/jxR/+h21LtwDg9vk5YvpN1Bx8bK9XnQmmEWPJO88x+4U/EwuHAKgqGsSVx97JpKGHOVxdQmYCQIBozMSy7HtwyUCQNJEAMN1MwyQajhIL7xj+uDUNj8uFexdDMjZtWkpbawMAwyvLGdWvH5D7AeCXxQyDutY2Njc10xgMdjlvQP/+jB4zBn9B7r5hIwFg7pAAsPcs2rSAZ774J6/Of3GHrsDTTjuN6dOnc8QRR+y2K1ACwNwhAWBqJAAUIjUSAPYREgDu3OvPz+POG54BYOI5B3PafRf0yv1mhoJlWTQ0NCT/2Cv0evC5OgZ4WJbF3Kdn8c4vXyUWigLQf/Qkplx+G4UV/R2pOt22Lp/PzKceoHHTasDe6+8rky7k/EOvwevOphfKmQsATcsiFrNvU1MVdFUGgvScBICZYi8PjhENR7pMDgY7IPLoOh5dx9XpjQzTNNiwfiGhkP3ieNzAAQwuK827ALCztlCYDQ2NbGluTnYFqqpCdXU1I0eORNdSm7DsJAkAc4cEgL0vEG7jlfkv8sysf7Bky6Iu540cOZLp06dz3nnn7bQrUALA3CEBYGokABQiNRIA9hESAO5o0/oGLjn19wTbwhT1L+Fbr9yEr9Sf8fvNFMMwaWpqxIh3/vk9bgo6TZEMNgZ47f+eY8V7SwBQVJX9T/8GE0+5EFXN/b3i2psbmPXMo6z69I3k54aWj+KKqXcwduB+zhW2S5kLAAFiMZP4PBDc0gWYBhIA9oZkV2AkimV2/X6rioLH5cKj6+iqSiwWYd3a+cRiERRg38EDGVRalp0BoGURNQzCsRhmvDvX/np09L3cqzMUjbK2fjubmpqToZnH7WbM2LEMHpRbw6skAMwdEgA6a9Gm+Twd7wpsj3R0A7vdbk466STOP/98jj32WFzxN30lAMwdEgCmRgJAIVIjAWAfIQFgV7GYwVXn/pmFczaAonDhk1dRffjojN5nJkWjUZqbWzDjUzYL3G78no7wb+3MVbx829O0bWsF7EEfUy6/jX4j93Wk3nQyYlGWvvc8c1/8K5F2uxvI5/Lz9UOu5qSJ56Nrrj3cglMyGwBalr0UGEBV6NI9JVIhAWBvsiwwYgaxcJRYNGZ/ohNNVfHoOhhhNm9YjGEaKMDEIYMZUFrieAAYikbZ3hagpb2dllCIQDjSZS+/znRVxe9xU+LzUVLgo8Lv71YoGAiFWVa7jYZAxxLBqspK9p2wL16PN21fSyZJAJg7JADMDm2hVl6d/yJPz/oHS7cu7nJeVVUV55xzDueddx6TJ0+WADBHSACYGgkAhUiNBIB9hASAXf3hl2/xxO8/AODwq45n6k2nZvT+Mqm9PURba2symujc+WdEY3zw0Nt89tePki+gRx5+EoddeC1uX+52O4K9nHntFzP437N/orVuc/LzR44+hUuO/D5l/ioHq+uOzAaAAIZhYZgyECQ9JAB0SmKCcCwS22FwCIAZDdFctwrTNFAUhfGDBjK4tLTXA8BQJMrmpia2tbbRFg6nfDuqolDuL6BfcTH9i4t2GODUhWVR19bG8q3baI/a2zrous4++4xlyOAhKdfQWyQAzB0SAGYXy7JYuGkez89+htcWvERrqKXL+RMmTOCb3/wmp5xySrcHhwhnSACYGgkAhUiNBIB9hASAHd59dSG3fvffAAycPIxL/nUNmiv3uqMM06S1pZVI/A9xBSjyee2uGKBhbT0v/vDfbF1sh2Mun5/DL76BkYdOc6rktKldMZ9ZT/+ButVLkp8bVjGay47+EfsOPtjByvZG5gNAgGjUxEIGgvScBIDZwDQtjEiMaCTaZb/AaCRIa91qrHjoN7islHED+pPpB7xpWtS1trK5qZmGQGCHR4iuufD6CvF4/bh0D5ruRo0H8aZpEotGiEZDhEIBQqHWZBd38vqqyoCSYoaVl1PQqav7ywzTZEXtNjY2NiU/V1lZyYQJE/B6sneqvQSAuUMCwOwVjoaZsextXpzzLB+vfB/D7PjdqGkaU6dO5ayzzuLkk0+muLjYwUrFzkgAmBoJAIVIjQSAfYQEgLaVS7dyxTl/oj0YwVfm5xvP30DJ4PKM3FemWBa0t7cTCAaSe2RpqkKx14uu6ViWyYLnZ/PWz14m2m7/kd5v5ASmXH4bRVUDnSy9x+rXLmXuS0+yYd4nyc+V+/tx3qHXMGXsaTm2l2HvBICmaREzZCBIz0kAmG1M00p2Bpoxg1ikndbtazGNeCecqjK0vIzBpaV43endCiAQCrO5qZktzc1EvrS8rqCgmMLCcvyFZbjdvm7fpoVFqL2NttbttLZuJxrt6CJUgH7FRQyvqKDIt+vlvY2BAIu3bKU9Yn8PXC4X48ePY+CA7PzdLwFg7pAAMDfUt9bxyvwXeGHOf1lRu7TLeR6Ph+OPP54zzzyTE088Eb8/t1eC5AsJAFMjAaAQqZEAsI+QABAatwe4/OxH2bS+EUVTueCJq6g+bFTa7ydTLAtC4RDBQCA56APA63JR6HGjKArhtjBv3P0Ci1+dB4CiqEw+7RImn3YJag5OiEyoW72EuS89wcYFM5Of87n8nHHANzll8sV4XN1/kZ09eicAhK4DQVyahqwEToUEgNksEQZGgkGaa1cTi7Z3Ob/U52NASTH9iotw66n9LowZBttaWtnU1Exze9fb13UXJSX9KCnpj8udnv33AoEmmptqaWtr6BKOVRT6GVFZSUnBzn/vGabJym11bGjoeM4eMGAA48ePx+3Krj1RJQDMHRIA5p6V9ct5btZ/eH3hK2xr2drlvIKCAk444QTOPPNMjjvuOAoKChyqUkgAmBoJAIVIjQSAfURfDwADbWG+d9HjLJm/CYAT7jiLg6Yfndb7yJRYLEYoFCYUCnVZHqarKn6vB3d8s/gtizbywg/+TdOGBgD85f055orb6D96kiN195RlWWxbuYB5L/+NTYtmJT/v0jycMOHrnHnAtygpyOV9bXovALSwlwKDvSLSpWlIBri3JADMDQpGNErDplUEW3Z83lOA8kI/A4qLqSoq3OOwDcuyaAgE2dLcTF1ra3JPTfu2FPyFpZSU9sdfWIaSoaMqGg3TsH0Tzc21XYNAv58RVbsOAhvaAizevIVQzN430ePxMGHCBKqy6EWTBIC5QwLA3NL52DIMgznrv+C1BS/x1qLXaAhs73JZn8/Hsccey8knn8yJJ55IeXlurYzJdRIApkYCQCFSIwFgH9GXA8BoJMb3v/V3Pv9oFQAHXHQkJ955NkqWboZmmhbRaIRIJEokEu7S7Qf2Ms4CtxuPy2VHEqbJrL99wowH3kzuiTVs/6M56rKb8fiLHPgKesaMxVj7v/dZ9NZ/qF+7LPl5t+7lxAnn8tX9LqPUnw9P+r0XAAIYpoUhS4F7QALA3NBxXAWb62nYvBojuvOwQlUU+hcXMai0lLICHygKpmkRCIdpCYVoCARoCASIful3sMvlpaS0HyUl/dD1Xe/Ll26GEaWhYTNNjVu6vBm0uyAwZhgs3VrL1uaOAQHDhg5lzNix3Zo0nGkSAOYOCQBzy66OrZgRY9bambyx4GXeWvw6Le3NXa6nqiqHH344J598MieffDLDhg3r7dL7HAkAUyMBoBCpkQCwj+irAWAsanDHdU/z7muLANjn5Mmc8cAlqJqz4YdpWZiGgWGYmKaJYcSIxQxisdgOm8AnuHUNn8uFS9eTL3GDDQFeuf0ZVn24HABNd3PweVezz9Qzsjbg3JX25gZWfPwaS957nmBjXfLzHt3HSRPP57T9pud4x9+X9W4ACF9eCqyi5thjxFkSAOaGrseVaRi01G+itX4LprHjBOEEVVFQFQXDsnYaRKmqRlFxBSXF/fAVOLuJfipBYG1LC0u31BKN71dYUFDAxIkTKSst7a2yd0oCwNwhAWBu6c6xFY1FmLV2Ju8ueYv3lrzFttbaHS4zfvx4jj/+eI477jgOOeQQ3O7ee9Ojr5AAMDUSAAqRGgkA+4i+GACGw1Fu++6/+egdu4us+vDRnPvYFeiezO2FZ1n2ZEfTNOLBnhn/f/zDMDBMs1svdBJLNd26jkfXdwhr1s1azUs/+g9t21oBKBkwlKnfvpPyoSMz8rVlgmkabF78Bcs/eIX18z7G6rSZfrm/H1+ZdCHHj/8ahd58nFrX+wFgl6XAyFTgvSMBYG7Y+XFlGgaBpm0EGusIB1u7dUu67sbvL8VfWIa/sAxVya6uWcOI0tiwmcadBIE1VRWUfmlPr0g0xuItW6hvCwB2QFBTU8OoUaMcezNAAsDcIQFgbtnbY8s0TRZtns97S97i3SVvsapuxQ6X8fv9TJkyheOOO47jjz+eoUOHZqL0PkcCwNRIAChEaiQA7CP6WgAYDIS55Tv/4rMPVwIw7NCRfP2Pl+P2e9JRor3hfCxGLBbDMIzkh2kYKUUEimLv6aepGrqqomsq+i72aYtFYnz08DvMfPxD+y9xYPRRp3DoBdfg8hSQ7SGFZVk0blzN6s/fYfVn7xBo6PqO86h+Ezhl8sUcOvIEdC27NqxPr94PAKHrVGBVUXA53A2bOyQAzA17Pq6MWJRwsJVoKEgsEsaIRTENEwUVVdPRXD40lxfd5cHncuF1ubK6W3ZXQWC538+ILweBlsWmpmaW127DiF+2qKiISZMmUVRY2NulSwCYQyQAzC09PbbW1q/mvaVv8dHy95m9/gti8enqnY0ePZopU6Zw1FFHccQRR8jegSmSADA1EgAKkRoJAPuIvhQAbt3UxA+ueIoVS+yJZzVHj+Wc338Dly+1ZQv2nnxRYtEoUcMO/Uxj58t0d0ZRQFXs5ZaaqsSXmqmoqoKmKKhq95di1i7dzMu3PEPdSjs00z0+jpj+fUYeOi1xb2RjSGFZFk2b17Juzoes+fxdmjav7XJ+gbuIo8acwvHjz2F41T7OFNnrnAkAAWKGhWnKfoB7JzuPLfFlqR9XhmESC0eJhXd8wezWdbwuV3LoUjayg8At8SCwo5u61OdjUFkp/YuL0OLHenskwqJNW2iKTzNWVZXRo0czfHh1xoaZ7IwEgLlDAsDcks5jKxBu47PVn/Dxig/4aMUMNjdt2un9jR8/nqOOOoqjjjqKww8/nJKSkh7db18hAWBqJAAUIjUSAPYRfSUAXDhnAzdf+Q8a6tsAGHvSJE6//+K9WvZrGCbRaIRoNGoHfzFjt5dPBHuaqqKqajLU0xQFJb6vVE+ZMYNP//wBHz/yLmbMDh/7jZrA0d+8heJ+gztdMntCilg0TO2yeWyY/ykb5n9KW/3WLucrisq+gw9mytjTOGzkiXhcO59kmb+cCwABojEz0UAa7z7N3g6n7JA9x5bYnZ4fV5Zld1pHw5HkYKUEVVHxuvSs7grcVRCoqyr9iouoKiqk3O9HVRTWbW9gdV09ZvyXQVlZGRMnTKDgS8uHM0UCwNwhAWBuydSxZVkWa+pX8/GK9/l45QfMXjeL9khwh8upqsqECRM45JBDOOSQQzj44IMZPHhwzu1P3RskAEyNBIBCpEYCwD4i3wNAwzD5+6Mf8sffvIsRD8iO+M40ptzwFZQ9dDdZlmVP3I1GiIYjxIydB34KoGmqvURX1ZKnM/0icNO89bzx0xfZtnQLAKru4oCzvsW+J3wdVf1yN4pzIYURi1K/dhm1y+exddlcalcuIBYO7XC50f0nceTokzl81El5Ms03Vc4GgBYQi5rJe5ahIHsiAWBuSO9xZRom0XCUaDia3HIhIdu7Ag0jRlPTVpqbaolGw13O0xSFMr+f0gIfLk1jQ0MDbWE71FFVleHV1YwYOTLjk4IlAMwdEgDmlt46tqJGlEWbFjBrzad8vuZT5q7/H6Hojn/7AQwcOJCDDz44+TFhwgQ8nvRszZPLJABMjQSAQqRGAsA+Ip8DwI3rGrj3R88ze+YaAHSPzld+ei4Tzzpol9eJxWJEIhEikSjRaOTLr+uA+B9PmopL03BpGrrauwMT2puCzHjgDeb994vk5yqGjeHob91C2eCaXVyrd0IKy7IINGxj+7rl1K9bRt3qxdStWkwssuMffS7Nw8Shh3JA9TEcMPxoKgoHZLy+3OBsAAhgWvZk4EQ1uqYhjYC7IgFgbsjMcWV3BdpB4A5dgaqKV8/ursBgsJnmpm20tTV06QpMULA7BKOd9hDUdZ1BgwYxYEB/3G4PLl1H0/W0hoISAOYOCQBzi1PHViQWZsHGeXy+ZiZz1s1i/sa5BMJtO72sy+Vin332YfLkyUyaNIlJkyYxfvx4fL6+tSJEAsDUSAAoRGr6VADY3NzMM888w+eff8727dvxeDyMHDmSU045hcMOOyzl243FYrz88su8//77bN68GYDBgwdzzDHHcOqpp6Lru19+unr1ap577jkWLFhAS0sLJSUlTJgwgbPPPpuaml0FPXsnHwPASDjG3x79kCce/oBIJAZAv30GcsZvLqFydNeQyTSteOBnf3TeKD1BAVy6hlvTcGk6mqb24k5IHaLtEf73j5nM/MsHhFrs/Zl0j5f9Tr+MfY//GupuH0/pDSksyyLU2kTz1vU0b91A89b1NG5aw/Z1ywm3Ne/yekPLRzF+8EHsN+wo9h18cB9c3tsdzgeAAKZlEYt13L90Au6KBIC5IfPHVWKvwF11BfpcLlxZ2hVoWRbt7c20tTYSDDQRjrTv9W0oioKu6x2BYPzDpevoLh1d03G5XHh9PnzxD49753vwSgCYOyQAzC3ZcmwZpsHKbcuZt342c9f/j7kbZrOhYdd/42uaxtixY5k4cSLjxo1jzJgx7LPPPgwePBg1T/cr7o3XWpZlYZomlmXt8AH2913X9Zxaoi0BoBCp6TMB4Pr167nttttobrZDC5/PRzgcTgZBX/3qV7niiiv2+nbb29v58Y9/zPLlywFwx//IjcT/ONpnn334yU9+gtfr3en133//fR588EFiMTvA8vv9BAIBwH73/YYbbuDoo4/e67q+LJ8CwFjU4NVn5/KXh2awdVMTAIqqcNClU5h60ynoHpf9B2o0mgz8Et/fL9NVNR766bg01dEnvlg4yvzn/sfHj75HoL7j3dLqA6dwyHnfo7C8XzduZe9CCtM0CLe1EGjYRqBxG4GGuuTptvotNG/dQCS483duEzRVp7piDPsMOoDxgw5in0EHUOQt7XYNfVd2BIDQdTIwyJ6AOycBYG7oveNqT12BPpcLj65ndaBumgahUBuh9jYikXaikRCRaIhYLL0Bj6Zp+P1+igoLKSwqoqiwkKKiIjxeL+4sCCnEnkkAmFuyJQDcmfq2Ouatn8PizQtYsmURizcvYHvb7l+nFBQUMHbsWMaMGcOYMWMYPnw41dXVDB8+POeHjezutZZpmrS0tNDY2EhTU1Pyo7GxcYfPNTc3EwqFCIVCtLe3J08nPrrjxRdf5PDDD8/El5l2EgAKkZo+EQBGo1G++93vsnXrVqqrq7nxxhupqakhHA7zwgsv8NRTT2FZFtdeey3Tpk3b8w128utf/5r3338fv9/Ptddem+wknDlzJr/97W8JBAIce+yx3HDDDTtcd/369Vx//fXEYjGOOuooLr/8csrLy2loaOBPf/oTH3/8MS6XiwcffJAhQ4b06HuQDwFgoDXEq8/O5d+Pf8rGdQ3Jzw+aPIwT7/oalWMHxAd32Et7d/bQVhUFl6bh1uNdflkQcrTVtTD7358z9+nPCTYEkp+vHD6WA8++gkHjd72U2TQNYqF2oqEg0VA70XDidJBYuOPz4UAL4bZmQm3N9r+tzYTamggHWnfoYNkdn8vPoLIaaqrGMaJqHDX9xjOsfDS65urR96Bvyp4AEHbsBNQUxbEu2OwkAWBucOa4MgyTWChKNLJjV6D9nKNnfRjYmYWFacQIhkMEQ+0YRgzLNLAsA8sy4xPtwbJMTCOGaRoYRsw+bcQwjJ2/6fZlXo+H0rIyiouLKSkpoaSkGF3r/tAu0XskAMwt2RwA7sy2llqWbFnI4s12ILhsy2K2NG/u1nXLysqorq6murqaIUOG0L9//x0+CgsLHXuT3+68bqe5ublLWJc4HQqFaGpqYvv27dTW1nYJ9Zqamnr15/fyv1/h0OMO6bX76wkJAIVITZ8IAF9++WX++Mc/4vF4+P3vf09VVVWX8x955BFeffVVysvLeeyxx/a4ZDdhzZo1XH/99ViWxY9+9COOOOKILud//PHH3HfffSiKwm9/+1uqq6u7nP+zn/2MTz/9lJqaGu6//360TkuGDMPgxhtvZM2aNRx55JH88Ic/TPGrt+VqAGgYJnM/X8ubLy7grZfmEwx0/NFZOqyCQ759LCNOGE/MiO30CTKxr5kd+GnomtZrgYYRNYgEw0QCYSLBiP3isD1KNBQh3Bpi0/wNbJy9jm3LtmCZHbW7CwopHzoab1EJRiRMLBomFgljRELEIhFikVDy80YkvJsKUuNzF1JR2J/KwoEMLK1mcFkNA0uHM6hsOGUFVTm1PCC7ZVcACPGOpljHYJDEvmBqFgTlzpMAMDc4PFxnN12BEO8613Tceu8+H/VUKBalPRLF+NL2GZqm4fV68Xg8aJqe/PZbpkk0GrLfiIqEiITbCYfaCLe3Ed3JXrEJCuAvLKSkpITSkhJKSkooLCrKmeA0n0kAmFtyLQDcmUC4jTV1q1i5bQWr61awctsKVm1bzpbmzXv9NRUUFFBWVhZ/o8H+KC4upri4GJ/Ph9vtxuPx4PF4kqd1Xe+ydLbzv5FIhPb29h0+gsEgwWCQ1tbWLmFfJAPHjKZqlPhKKfaVUOIrpdBbhM/lw6N78Lq8eFxePLoHj26fdiXfXFFQFAUl/i+AaZnEjCiX/OhChk4clPZaM0ECQCFS0yfeZp0xYwYAU6ZM2SH8AzjnnHN47bXXaGhoYMGCBey///7dut33338fy7IYOHDgTtuljzjiCAYOHMiWLVt4//33mT59evK8QCDArFmzADjzzDO7hH9g/1F95pln8pvf/IbPP/+cYDBIQUFBd7/knLa9voUP3p/H5x+t4rMPVlK/rbXL+WUjqphw/sGM+spEVF0lGot2OV9T1U5dflq3XzhYloURiRFus0O7cCAR3oWJJD4XjNif+9JHOBDpuFw89IuFu9cB8WWRYBtbl81J6bq74nMXUuwtpchbSpGvzP7XW0aRr5Ribynl8cCvomgABe7CtN63yB2KArpLxTBMTNOOT6KmiWqBpkgQKMSeKAq4PC5cHheGYWJEYsQiMcz4dPmYaRIzI7THn7YSb0y5NHu6fLYGXV7dhVd3ETUM2qNRIvFtNQzDIBAIEAgEUFUNt9uF2+3G5XLhdhfg9uz4d4tpxAi322Fge7CZUKCFSCiAhf07p62tjba2NjZt2gSAqioUFhYlX6yXFBdTWFSElqf7gQkhbH5PIROGTGbCkMldPh+OhtnctJENjevZ2LCejY0b2Niwng0N66lt2UJrqGWH20oEc4nfK9nE6/JSUlBKia+MYm9xp1DPDvaKC0qTpzuf5/ekv6uxvEr27BYi3+V9ANje3s6KFSsAOOCAA3Z6maqqKoYMGcKGDRuYN29etwPA+fPnA7D//vvv9Bewoijsv//+bNmyJXnZhMWLFyf3pdtVXYnPR6NRlixZwoEHHtitunKZZVmcedzNNDcGu3xec+sMO3o0+5y5PwMPGJb8fluWhRIzIWpCxMAKxWgPRGhKBnMhIm3hjlCvLUQkGCHSFiIc6Ph8JH56Zx0bvcWje3HrPtzxd+vc8Q9P/MOVOO3y4tY8uHUvXlcBPrcfr6sAr8vf6XQBPncBPpf9f1XNzg3pRfaxu2ZVTMXCMCws7GnBpmWimPaLcVVJvHsshNgVTVPRfG7cPjemYRKLxDBiMYxox/NM1DDsUC3+f1VR0FQVTVXje3HaH9kSDLo0+40107KIxGKEYzGi8XDT3k/QSO41pagqLt2Frmtomp78V9V0fIWl+ApLKWMIiqISi0UIBVtoD9iBYHuwmVg0Er9di5aWFlpaOl7UK4pCQUEBfr8fv78Af4GfAr+fAp8Pj8cjnepC5DGPy0NN1Uhqqkbu9PxQNER9Wx31rduoi3/Ut26jJdRCS3sLraGuH+FYmGgsQsSIYOxkSvquqIqK1+XD6/Lic/nwunz43D48Li9FniKKfSX2h7eEIl8xxd7iLp9LnC7yF0t3rRCi1+R9ALhx48Zkm/iXl+B2Vl1dzYYNG9iwYUO3bteyLDZu3LjH2x02bBjADreb+H9paekuN69NtKg3Nzezfv36PhEAKoqCu6wAGoOoLhVvqR9PsRdXgZvWTY3MvP9NYqFo/CNGNLTjfkuZ5tLcySd6j+7Fq3vxaF7cqgeP4sGFC7fqxaN58GhevFr8fM2NS3XjcRdQVFRJScVAioqr8Lh8uDR3ml6wyDJFkR6qqqCoCqZpYcaDQAswTAsj/hhTFVBQIP6v/RD+UjCoIEGh6PNUTcXtcwNuLAuMmIERjWHEjC5vPJmWhRkPBb9MUZRkJ66aXL5FRyAfD+UTzyWK0nE07vTY7MnXoyh4XS68LlcyDIzE6078zWWZJpFImC+/nlUUBVVVUVUNVVPRVA1FVVA0H4WlBRSVDQJFwYxF7E7BUCvhYCvh9rbkcBLLspKdhzt8nwC3x4PX68Xr8eD2eOITil1d/tV0HU1VURIhqxavSVVRVVXe5BAiR3ldXoaUDWVI2dC9vm7MiBExIkRjEaJmFFVRURU1/vvWfjNGVVQ0Vcetp+tvdyGE6D15HwA2NHQMiygvL9/l5RLndXefu8R0pe7ebmJvCJ/P1+V+dnfdxPnNzc17rOvvf/87//jHP3Z5/gUXXMCFF16429vYGTW+xEZVVcrKyvb6+qmIbrc7I82oSbCulWBd6x6usWeaotlhnO5LBnJezQ7wOod03vhl7PDOF/+cHeQlPrS97KbT3R7cPj8efzGeolLc3gIyG4nIHyO5Jzt/ZgqgqQqaatlBoGXReQswe+tKK545713wnJ1fsRC9RAHFraO77T/DLMPENEwsw8QyTXtf2C+9uWVZFjHLAHNnN5g7LMvCMAwMw4Doni6torhK8JaU4CkGy4wSi7RjRNsxomEMI4wRDWNZHd8UCwiHw4TDYZoz+YUIIUSe2bp6Nff96V6nyxBCZFDeB4Cdx557PJ5dXi5xXnt7+y4v01nny3XndhPXSQSAievv7rp7U1cgEGDbtm27PD8YDO6wz+DeUBSlR9ffG8UFxQRag/a7bsTfeVMUVEVDRel4Ny7+b+Iy9odmvzOnaKiKZndLxD+3M4YZI2i2EYy2pVyv2+2moLCAopJiyioqKKssp6yigop+lQwcOpgCv7/TpcPxDyFyUyQSZeu27WyprWdbXQONza20tgW7DLIRQvSUhWVYmDETYjFM08Q0LIgZdlBommDaXXZ9nWVZWKaBGYtgmlH7tNkxkRjLsENVy7ktPoQQIhccOGy/Xnu9J4RwRt4HgH2F3++nX79+uzy/oKDAfrd9LyWWwSSmXvWGW//vVpYuXZpc0gR0LG/qxc9pmobP58Pr9Sb/TXyUlJRQUVFBRUUFXq+3V74ve5JYVpWYUiaymxPHVqZEIhG2bdvGtm3bqKuro7GxkXA4nOyUDoVChMPhLlP0Eh+d/9/5dDZJ/E7IxtpEV33tZ2VZFpFIJNnxFovFMAxjl/8ml+d2OuYS/+98Oh3fv+5eP/HzSnQFmqbZ5XTnenb2u2Nn99Xl/wqg0eU6X77dzl/3Hm8vha9RCCFywRWHfSOl14tOkKBSiNTkfQDYOZwJh8O7nKQbDttdWYkOvT3pfLnEdXd3u1++TuL07q67N3VdfPHFXHzxxbs8v76+vtvLmzsrKytD0zRM00zp+qk455xzeuV+0iGxtDsbaJpGWVkZzc3NOfPk3Zc5cWxlkt/vp6amhpqaGqdLSbvEsdXY2CjHVpZLHFeGYeTFcZXv5NjKHXJs5RY5tnJHth1b2VBDd1RWVjpdghA5aefrIvNI5z32Ou8H+GWJ87q7z53P50uGct253c6X71zX7q6bSl1CCCGEEEIIIYQQQnSW9wHgkCFDkks8169fv8vLJc4bOrR7E6MURWHIkCEp327i/01NTbS0tOz0us3NzTQ321tYJ6YJCyGEEEIIIYQQQgixN/I+APT5fIwePRqA2bNn7/Qy9fX1bNiwAYDJkyd3+7YnTZoEwJw5c3Z5mblz53a5bML48ePRdX23dSVu1+VyMW7cuG7XJYQQQgghhBBCCCFEQt4HgABTp04F4IMPPqCurm6H85999lksy6K8vJyJEyd2+3anTJmCoihs3ryZTz/9dIfzP/nkEzZv3oyiKMkaEgoKCjj44IMBeOGFF3bYn8MwDF544QUADjnkkF3uXSiEEEIIIYQQQgghxO70iQDwpJNOYsCAAYRCIe6++27WrFkD2AM2nnnmGV555RXAHqSR6MpLuPzyyzn99NN54IEHdrjdmpoapkyZAsBDDz3EzJkzk1PkZs6cye9+9zvADiB3toT3oosuQtd1Vq1axf3335/cdLWxsZH777+fVatW4XK5uOiii9L2vRBCCCGEEEIIIYQQfUveTwEGewnt7bffzm233cbatWu57rrrKCgoIBQKYZomAKeddhrTpk3b69u++uqr2bJlC8uXL+fee+/F7XYDEIlEANhnn334zne+s9PrDhs2jOuuu44HH3yQDz/8kI8++oiCggICgQAAuq5z3XXXJfcaFEIIIYQQQgghhBBib/WJABDssO2hhx7iv//9L59//jn19fX4/X5GjBjBqaeeymGHHZbS7fp8Pn7+85/z8ssv8/7777N582YARo4cydSpUzn11FN36Crs7JhjjmHo0KE8++yzLFy4kJaWluRS5LPPPpuampqU6hJCCCGEEEIIIYQQAkCxLMtyugiRefX19Sldr6ysDE3TMAwjuURZZCdN0ygrK6OxsXGHPSVF9pFjK3fIsZU75LjKLXJs5Q45tnKLHFu5Q46t1FRWVjpdghA5qU/sASiEEEIIIYQQQgghRF8lAaAQQgghhBBCCCGEEHlMAkAhhBBCCCGEEEIIIfKYBIBCCCGEEEIIIYQQQuQxCQCFEEIIIYQQQgghhMhjEgAKIYQQQgghhBBCCJHHJAAUQgghhBBCCCGEECKPSQAohBBCCCGEEEIIIUQekwBQCCGEEEIIIYQQQog8JgGgEEIIIYQQQgghhBB5TAJAIYQQQgghhBBCCCHymASAQgghhBBCCCGEEELkMQkAhRBCCCGEEEIIIYTIYxIACiGEEEIIIYQQQgiRxyQAFEIIIYQQQgghhBAij0kAKIQQQgghhBBCCCFEHpMAUAghhBBCCCGEEEKIPCYBoBBCCCGEEEIIIYQQeUwCQCGEEEIIIYQQQggh8pgEgEIIIYQQQgghhBBC5DEJAIUQQgghhBBCCCGEyGMSAAohhBBCCCGEEEIIkcckABRCCCGEEEIIIYQQIo9JACiEEEIIIYQQQgghRB6TAFAIIYQQQgghhBBCiDwmAaAQQgghhBBCCCGEEHlMAkAhhBBCCCGEEEIIIfKYBIBCCCGEEEIIIYQQQuQxxbIsy+kiRPb6+9//TiAQwO/3c/HFFztdjhB5Q44tIdJPjishMkOOLSEyQ44tIURvkgBQ7NYpp5zCtm3b6NevH6+++qrT5QiRN+TYEiL95LgSIjPk2BIiM+TYEkL0JlkCLIQQQgghhBBCCCFEHpMAUAghhBBCCCGEEEKIPCYBoBBCCCGEEEIIIYQQeUwCQCGEEEIIIYQQQggh8pgEgEIIIYQQQgghhBBC5DEJAIUQQgghhBBCCCGEyGO60wWI7HbhhRcSCATw+/1OlyJEXpFjS4j0k+NKiMyQY0uIzJBjSwjRmxTLsiynixBCCCGEEEIIIYQQQmSGLAEWQgghhBBCCCGEECKPSQAohBBCCCGEEEIIIUQekwBQCCGEEEIIIYQQQog8JgGgEEIIIYQQQgghhBB5TKYAi51qbm7mmWee4fPPP2f79u14PB5GjhzJKaecwmGHHeZ0eUJknbq6Oj799FPmz5/P2rVraWhoQNd1qqqq2G+//fjqV7/KgAEDdnrdyy+/nG3btu329k855RSuuuqqTJQuRFZ75513ePDBB/d4ub///e8UFxfv9LxPP/2U1157jVWrVhEOh6msrOTggw/m61//+i6vI0Q+O/3007t92euuu47jjz++y+fkeUv0VW1tbSxcuJCVK1eyatUqVq5cSXNzMwD33HMPEydO3ONt9OQ5SV6jCSF6QgJAsYP169dz2223JZ/MfD4fgUCAuXPnMnfuXL761a9yxRVXOFylENmjrq6Oyy+/nM5D1QsKCohEImzYsIENGzbwxhtvcP3113PUUUft8nYKCgpwu927PE+IvkxV1d2+MFIUZaeff+SRR3j11VeTt+HxeNi8eTMvvPAC77//Pvfccw9Dhw7NSM1CZKvS0tLdnh8KhQiFQgCMGjVql5eT5y3R13z22WfdelNqV3rynCSv0YQQPSUBoOgiGo3y05/+lObmZqqrq7nxxhupqakhHA7zwgsv8NRTT/HSSy9RU1PDtGnTnC5XiKxgmiYABxxwAMcddxz77bcfxcXFGIbBkiVL+OMf/8jatWu5//77GTJkCMOHD9/p7VxxxRU7dFkIIWyVlZU89thje3WdN954g1dffRVFUbjooos444wz8Hg8rFmzhvvvv59169bx05/+lN/97ne4XK4MVS5E9nnyySd3e/4dd9zB3LlzGTVqFNXV1bu8nDxvib6orKyMkSNHMmrUKAYNGsT999/frev15DlJXqMJIdJB9gAUXbzxxhts3boVj8fDHXfcQU1NDQAej4dzzz2Xk08+GbCXWsViMSdLFSJrFBYW8pvf/IY777yTKVOmJLuUNE1jwoQJ3HXXXZSUlBCLxXjhhRccrlaIviEajfKPf/wDsJcinnvuuXg8HgBqamr48Y9/jMfjYcuWLbz11ltOlipEVqmvr2f+/PkAEu4J8SVTp07liSee4I477uDCCy/koIMO6tb1evqcJK/RhBDpIAGg6GLGjBkATJkyhaqqqh3OP+ecc1AUhYaGBhYsWNDL1QmRnfx+PyNGjNjl+WVlZRx44IEArFq1qrfKEqJPmz9/Po2NjSiKwtlnn73D+f369WPKlClAx3OfEALeffddTNPE5XJxzDHHOF2OEFlF07SUrtfT5yR5jSaESAcJAEVSe3s7K1asAOyljDtTVVXFkCFDAJg3b16v1SZErkt0BRqG4XAlQvQNiQ6moUOH7vTFEsD+++8PwLJly5L7nQnR17333nsAHHLIIRQWFjpcjRD5oSfPSfIaTQiRLrIHoEjauHFjcojB7vZ7qa6uTg42EEJ0z8KFC4HdH1vPPfccf/vb32hpaaGgoIDhw4dzxBFHMG3atF1usi5EX9Hc3Mz111/Ppk2bAKioqGDChAmcdtppO91XM/EctafnMwDLsti4ceNuhx0I0RcsWbIkeYx1Zx8xed4Sont68pwkr9GEEOkiHYAiqaGhIXm6vLx8l5dLnNfY2JjxmoTIBzNnzmTlypXA7vdTWr9+PW1tbXg8HlpaWpg/fz6PPPII3//+96mrq+utcoXISuFwmDVr1uByuTAMg82bN/Pmm29y/fXX89xzz+1w+cRzWneez0Ce04QAeOeddwD72Nhvv/32eHl53hKie3rynCSv0YQQ6SIdgCKpc6t5YlPanUmc197envGahMh1dXV1PPzwwwAceuihyb0AOzv00EPZd999mTBhQnKpcENDA2+99Rb//ve/WbduHXfddRe/+c1vZFKp6HPKy8u54IILOOKIIxg0aBAul4tYLMbixYt58sknWb58OY8//jjl5eVd9itLPKd15/kMIBgMZu6LECIHhMNhPvroIwCOPfbY3e51Js9bQuydnjwnyWs0IUS6SAegEEJkSFtbG3fffTfNzc0MGDCAa6+9dqeXu+KKKzjiiCOSL6LADj3OO+88fvjDHwJ2l0WiM0OIvmT//ffnggsuoLq6Ohkk6LrOpEmT+NnPfsbYsWMBeOKJJzBN08lShchpn376aTJ02NP0X3neEkIIIXKPBIAiyev1Jk+Hw+FdXi5xns/ny3hNQuSq9vZ27rrrLtauXUt5eTk/+clPKCoq2uvbOfTQQxk/fjwAs2bNSneZQuQ0l8vFxRdfDEB9fT2rV69Onpd4TuvO8xlAQUFBhqoUIjckwrqxY8cmhwmkQp63hNhRT56T5DWaECJdJAAUSZ33lOi818SXJc4rKyvLeE1C5KJwOMxPfvITli1bRklJCXfffTcDBgxI+fYSHU5bt25NV4lC5I3E8QFdj5HEc1p3ns9AntNE31ZXV8eCBQuAPXf/dYc8bwnRVU+ek+Q1mhAiXSQAFElDhgxBURTAXraxK4nzhg4d2it1CZFLwuEwd999N4sWLaKwsJCf/OQncqwI4YDEcded5zNFUXrU8SRErnvvvfcwTRO3283RRx/tdDlC5J2ePCfJazQhRLpIACiSfD4fo0ePBmD27Nk7vUx9fX1ytPzkyZN7rTYhckE0GuXee+9l/vz5FBQUcOedd1JTU9Pj2122bBkA/fv37/FtCZFvEscHdD1GJk2aBNgviOrr63d63Tlz5gB2t1LnJVZC9DWJ5b+HHXYYfr+/x7cnz1tCdNWT5yR5jSaESBcJAEUXU6dOBeCDDz6grq5uh/OfffZZLMuivLyciRMn9nJ1QmSvWCzGz3/+c+bMmYPX6+WOO+5gzJgxe7yeZVm7PX/WrFksXrwYgEMOOSQttQqRK/Z0fMRiMZ566ikAKioqGDlyZPK8SZMmUVZWhmVZPPfccztct66ujg8++ADoeO4Toi9avHgxW7ZsAbq3/Feet4TYez19TpLXaEKIdJAAUHRx0kknMWDAAEKhEHfffTdr1qwB7GWNzzzzDK+88goAF198MbquO1mqEFnDMAx+9atfMWvWLNxuN7fffntyA/Q9+eMf/8gf//hHFi5c2GVj58bGRp5++mnuu+8+AIYNG5aWfZmEyCXbtm3jpptu4o033qC2tjb5ecMwWLhwIbfeeitLly4F4NJLL0VVO/6scblcXHjhhQC8/PLLPPPMM8ljbM2aNdx9992EQiEGDhzICSec0ItflRDZJdH9V1lZ2a3OIXneEn1dS0tL8qOtrS35+UAg0OW8WCyWPK+nz0nyGk0IkQ6Ktae38USfs379em677Taam5sBewpVKBTCNE0ATjvtNK688konSxQiqySCCLD/wNvT8qknn3wyefqBBx7g3XffBew9XxJT3wKBQPIyI0aM4LbbbqOqqirdpQuR1Wpra7niiiuS/3e73Xi9XoLBYPKFla7rXHrppZxxxhk7vY1HHnmEV199FQBN0/B4PASDQQBKS0u55557ZL8k0WeFw2EuvfRSgsEg5557bnKq9u7I85bo604//fRuXe6ee+7ZoRuvJ89J8hpNCNFT8vaA2MGwYcN46KGH+O9//8vnn39OfX09fr+fESNGcOqpp3LYYYc5XaIQWaXz+yjRaPT/27u/0CrrPw7g7+MsFbWtiBXNVTAjm5oiIur802bBokKibiLBmwivgvIq6yIICQrECIpBN40gSC/qwkVERyubYLsRbGFGC1Si0OGawtZs53chO225/X5N+/Pj2esFg+d5vp/zPc85N4e9n++fnD9//k+/tr29PbW1tTlx4kR+/vnnDA4OZnR0NDfddFOamprS0tKSTZs2eZrLjFRXV5enn34633zzTfr6+jIwMJCLFy9mzpw5aWxszPLly/Pggw+moaFhyj527NiRFStWpKurK99//311hMWaNWvy+OOPp7a29h/8RPD/pbu7uxo+tLW1/anX+N2Cq3ctv0n+RwOulRGAAAAAAFBg1gAEAAAAgAITAAIAAABAgQkAAQAAAKDABIAAAAAAUGACQAAAAAAoMAEgAAAAABSYABAAAAAACkwACAAAAAAFJgAEAAAAgAITAAIAAABAgQkAAQAAAKDABIAAAAAAUGACQAAAAAAoMAEgAAAAABSYABAAAAAACkwACAAAAAAFJgAEAAAAgAITAAIAAABAgQkAAQAAAKDABIAAAAAAUGACQAAAAAAoMAEgAAAAABSYABAAAAAACkwACADMCIcOHUqpVEqpVMpLL72UJDl58mR27tyZpUuXpq6ubkLbmKGhoXR0dOThhx9OY2Nj5s6dm9ra2ixbtizPPPNMvv322ynf85577kmpVMqiRYumrHnhhReq97Vw4cKMjIxMWvfaa69V6w4cODDtzw8AwMwlAAQAZqR33303K1asyJ49e9Lb25uBgYEraj777LMsXrw4O3bsyIEDB3L69OkMDw/nl19+yddff5033ngjzc3NeeWVVyZ9j9bW1iTJmTNncuLEiUlryuVy9fjChQs5evTof62bPXt2Nm3aNK3PCgDAzDb7374BAIB/Wnd3d3bv3p1SqZTt27dn48aNmT9/fr777rvcfvvtSZKPPvooW7duzcjISGbNmpX29vbcf//9aWhoyNDQUHp6etLZ2ZmBgYHs2rUrSfL8889PeJ+2tra89dZbSS4HeHffffeE9sHBwfT09Ey4Vi6X09LSMuHayMhIDh8+nCRZvXp1Fi5c+Nd9GQAAFF6pUqlU/u2bAAD4ux06dKg6Ii9J6uvr88knn+Tee++9ovbHH3/MsmXL0t/fn/r6+nz44YdZu3btFXVnzpxJe3t7jh8/npqamhw/fjxLliyptp89ezb19fWpVCp57LHHsn///gmv7+rqykMPPZQkWb9+fbq7u3Pffffl4MGDE+q6u7uroeCuXbuye/fuq/8iAACYcUwBBgBmpI6OjknDv+Tyenv9/f1Jkv37908a/iVJQ0ND9u3bl5qamvz22295/fXXJ7TffPPNWb58eZLLAeQfn7uOTettamrK9u3bkyRHjhzJ0NDQpHXJ5VGFAAAwHQJAAGDGueOOO7J169ZJ2yqVSjo7O5Mk69aty8aNG/9rX0uWLMmaNWuSJB9//PEV7WOB3blz53Ls2LEJbWPBXltbW7VueHg4X3755aR1c+bMuWJ6MAAA/C/WAAQAZpyWlpaUSqVJ23p7e3Pu3LkkyY033pgPPvjgf/ZXU1OTJOnr68vQ0FDmzp1bbWttbc3evXuTJJ9++mlWrlyZJOnv768Gglu2bMnixYvT2NiYU6dOpVwuZ8uWLUku70J85MiRJJcDyfF9AwDAnyEABABmnEWLFk3Z9sMPP1SPu7q60tXVNa2++/v7c9ttt1XPN2/eXJ0iXC6Xs3PnziSXdxgeHR1NqVSqrk3Y2tqazs7OCVN+x08JNv0XAICrYQowADDjzJs3b8q28+fPX1Pfv/7664Tz2trarFq1KknyxRdf5NKlS0l+n9a7dOnS1NfXJ/k94Ovp6cng4OCEuvHtAAAwHQJAAIBxFixYUD1+7rnnUqlUpvV35513XtHn2Ai/wcHBHD16NMnE9f/GjB1funQpn3/++YS6+fPnV9caBACA6RAAAgCMM3568KlTp/6SPseHfOVyOT/99FN6e3uTpLrWX5I0NjamqampWnfhwoV89dVXSZINGzbkuuuu+0vuBwCAmUUACAAwzsqVK1NbW5skOXjwYIaHh6+5z/HhXblczsGDB5Nc3jxk8+bNE2rHwsJyuZzDhw9nZGRkwnUAAJguASAAwDg1NTV58sknkyRnz57Nnj17rrnP8dN3u7u7qxuLrFq1qho2jhkL+o4dO5b9+/dfcR0AAKZLAAgA8Ae7du1KXV1dkuTFF1/M3r17Mzo6OmX9xYsX8/bbb+e9996bsmYswBseHq7WjZ/+O2ZsvcBKpZJ33nknSVJXV1fdSAQAAKZr9r99AwAA/28aGhry/vvv55FHHsnw8HCeffbZvPnmm3n00UfT3NycBQsWZHBwMH19fenp6Um5XM7Q0FBefvnlKftsa2urto/tBDzZqL5bbrklzc3N6e3trdZt3rw5s2Z5bgsAwNURAAIATOKBBx7I4cOHs23btpw4cSInT57Mq6++OmV9TU1Nbr311inb161bl7lz52ZoaChJcv3112fDhg2T1ra1tVU3CRk7BwCAq+VRMgDAFFavXp3e3t7s27cv27Zty1133ZUbbrghNTU1qa2tzbJly/LEE0+ko6Mjp0+fzlNPPTVlX3PmzMn69eur52vXrs28efMmrf1j4CcABADgWpQqlUrl374JAAAAAODvYQQgAAAAABSYABAAAAAACkwACAAAAAAFJgAEAAAAgAITAAIAAABAgQkAAQAAAKDABIAAAAAAUGACQAAAAAAoMAEgAAAAABSYABAAAAAACkwACAAAAAAFJgAEAAAAgAITAAIAAABAgQkAAQAAAKDABIAAAAAAUGACQAAAAAAoMAEgAAAAABSYABAAAAAACuw/g90uHTeiTB4AAAAASUVORK5CYII=" 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}, "metadata": { "image/png": { @@ -316,30 +329,42 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 36, "id": "fee15370-568a-4fdc-8c16-a3db8e33256f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Check: True\n" - ] - } - ], + "outputs": [], "source": [ "reprod_env_3 = AsmEnv(\n", " config={\n", " 'reproducibility_mode': True,\n", " **CONFIG3\n", " }\n", - ")" + ")\n", + "_ =reprod_env_3.reset()\n", + "\n", + "reprod_escEnv_3 = AsmEnvEsc(\n", + " config={\n", + " 'reproducibility_mode': True,\n", + " 'r_devs': reprod_env_3.r_devs,\n", + " **CONFIG3\n", + " }\n", + ")\n", + "_ = reprod_escEnv_3.reset()" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "c8be4e61-5766-4402-bf1d-be7308751ce4", + "metadata": {}, + "outputs": [], + "source": [ + "# reprod_escEnv_3.r_devs - reprod_env_3.r_devs # check!" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 38, "id": "55d46a8d-1f8f-4f25-b58a-f036c64ce18b", "metadata": {}, "outputs": [], @@ -354,18 +379,22 @@ "\n", "ppo2_ep = pd.DataFrame(\n", " full_ep(policy=ppoAgent2, env=reprod_env_3)\n", + ")\n", + "\n", + "ppoEsc_ep = pd.DataFrame(\n", + " full_ep(policy=ppoAgentEsc, env=reprod_escEnv_3)\n", ")" ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 40, "id": "6866d87d-6193-45af-bf54-b8ef1e4db651", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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", + "image/png": 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0dGDTpk144403sH//fhQWFiq3HzVqFGbPno3rr78ebrcbjz76KAYOHBg2zQOwDrVffvklzjzzTAwdOhQNDQ345z//ifLycsyePRsAcO211+LJJ5/ElVdeie+++w7Dhg3DG2+8gZUrV+LRRx9VPDJnn302TjrpJNx2223Yv38/JkyYgLfeegstLS0hz/vYY49h9uzZmDRpEq655hqMGDEC9fX1WLVqFQ4ePKi8ZwAUZWf//v0RPqHwXHbZZXjttddw3XXXYcmSJTjppJPg9/uxfft2vPbaa/jkk0+UVF5mZiaOO+44rF69WukxAjBlpKOjAx0dHSHBSKyekYsvvhgZGRmYNWsWiouLsXXrVjz11FPIzMzEfffdF3DbjRs3Kr1Odu/ejZaWFuV7NGXKFJx99tkAgJqaGowfPx5XXHFFwCygBx54AOeccw5OP/10/PCHP8TmzZvxj3/8A1dffbXi/QGAhQsXory8HDNmzEBxcTGqqqrwzDPP4NChQwHBKEEknGSX8xBETxCuA2swZrpgSpIkNTQ0SLfccos0atQoyel0Svn5+dL8+fPDlvNeccUVYcs8jXQkbWtrk26//XZp1KhRksPhkAoLC6VZs2ZJDz74oNKRk5eWPvDAA9JDDz0kVVRUSE6nU5ozZ460YcOGgMcLLu39/PPPpXPPPVcqKyuTHA6HVFZWJl1yySUh5cT19fXSVVddJRUWFkoOh0OaNGmS7vY3NjZKl112mZSbmyvl5eVJl112mbRu3Trd17tnzx7p8ssvl0pLSyW73S4NHjxYOuuss6Q33ngj4HaFhYW65afBzJs3T5o4caLudR6PR7r//vuliRMnSk6nUxowYIB03HHHSX/605+klpaWgNv+5je/kQBI999/f8Dlo0aNkgBIe/bsibotRvjrX/8qTZ8+XSooKJBsNps0aNAg6dJLL5V27doVclv+fdb70ZaL8++CXgn522+/LU2dOlVyOp1SeXm59Pvf/175DnH+8Y9/SLNnz5YKCwslm80mFRUVSWeffbb05ZdfJuQ1E0Q4BEmSpN4NfwiCSCT79+/H8OHD8cADD+DXv/51sjcnoWzduhUTJ07E+++/jzPPPDPZm0MQRA9BnhGCIFKWJUuWYObMmRSIEEQfh4IRgiBSlkWLFuGrr75K9mYQBNHDUDBCEARBEERSIc8IQRAEQRBJhZQRgiAIgiCSCgUjBEEQBEEklbRoeiaKIg4dOoScnJyo7ZwJgiAIgkgNJHmMQFlZWcSuwmkRjBw6dChkwBNBEARBEOlBdXU1ysvLw16fFsEIbzddXV2dkCmWBEEQBEH0PK2traioqFDO4+FIi2CEp2Zyc3MpGCEIgiCINCOaxYIMrARBEARBJBUKRgiCIAiCSCoUjBAEQRAEkVTSwjNiBFEU4fF4kr0ZRAQcDkfE0i6CIAiif9InghGPx4N9+/ZBFMVkbwoRAYvFguHDh8PhcCR7UwiCIIgUIu2DEUmSUFtbC6vVioqKClp5pyi8cV1tbS2GDBlCzesIgiAIhbQPRnw+Hzo7O1FWVobMzMxkbw4RgaKiIhw6dAg+nw92uz3Zm0MQBEGkCGkvI/j9fgAg6T8N4J8R/8wIgiAIAugDwQiHZP/Uhz4jgiAIQo8+E4wQBEEQBJGeUDCSJCorK3HzzTeHvX7YsGF49NFHe217CIIgCCJZpL2Bta/y7bffIisrK9mbQRAEQRA9DgUjKUpRUVGyN4EgCILow3h8IiwCYLMmP0mS/C3ox/h8Ptx4443Iy8tDYWEh/vCHP0CSJAChaZqqqiqce+65yM7ORm5uLi666CLU19cr1//xj3/E1KlT8fTTT2PIkCHIzs7GDTfcAL/fj7/85S8oLS1FcXEx7rnnnoBtePjhhzFp0iRkZWWhoqICN9xwA9rb25XrDxw4gLPPPhsDBgxAVlYWJk6ciA8//BAA0NTUhB//+McoKipCRkYGRo8ejWeeeaYH3zGCIAgiEbS7fZh9/xf40b+/TvamAOiDyogkSejyJqd0NMNuNVUx8txzz+GnP/0pvvnmG6xZswbXXnsthgwZgmuuuSbgdqIoKoHIsmXL4PP5sGjRIlx88cVYunSpcrs9e/bgo48+wscff4w9e/bgggsuwN69ezFmzBgsW7YMX331FX7yk59g/vz5mDFjBgDWFfVvf/sbhg8fjr179+KGG27Arbfein/+858AgEWLFsHj8eDLL79EVlYWtm7diuzsbADAH/7wB2zduhUfffQRCgsLsXv3bnR1dcX5LhIEQRA9zbqqJjS0udHa7U32pgDog8FIl9ePCXd8kpTn3nrXAmQ6jL+lFRUVeOSRRyAIAsaOHYtNmzbhkUceCQlGPv/8c2zatAn79u1DRUUFAOD555/HxIkT8e233+KEE04AwIKWp59+Gjk5OZgwYQJOPvlk7NixAx9++CEsFgvGjh2L+++/H0uWLFGCEa2JdtiwYbj77rtx3XXXKcFIVVUVfvCDH2DSpEkAgBEjRii3r6qqwrRp03D88ccr9ycIgiBSn40HWwAAqTJFhdI0SeTEE08MUFJmzpyJXbt2hTQF27ZtGyoqKpRABAAmTJiA/Px8bNu2Tbls2LBhyMnJUf4vKSnBhAkTAlrkl5SUoKGhQfn/s88+w6mnnorBgwcjJycHl112GRobG9HZ2QkA+PnPf467774bJ510Eu68805s3LhRue/111+PV155BVOnTsWtt96Kr776KgHvCkEQBNHTbJKDEV+KRCN9ThnJsFux9a4FSXvuZBLcYl0QBN3L+EDB/fv346yzzsL111+Pe+65BwUFBVixYgV++tOfwuPxIDMzE1dffTUWLFiADz74AJ9++inuvfdePPTQQ7jpppuwcOFCHDhwAB9++CEWL16MU089FYsWLcKDDz7Ya6+ZIAiCMM+mGlkZkZi9IdlNKfucMiIIAjIdtqT8mP0wv/460Di0evVqjB49GlZrYFAzfvx4VFdXo7q6Wrls69ataG5uxoQJE2J+r7777juIooiHHnoIJ554IsaMGYNDhw6F3K6iogLXXXcd3nrrLfzqV7/Cv/71L+W6oqIiXHHFFXjxxRfx6KOP4qmnnop5ewiCIIiep7HdjZpm1d/nF6Ukbg2jzykj6URVVRVuueUW/OxnP8PatWvx97//HQ899FDI7ebPn49Jkybhxz/+MR599FH4fD7ccMMNmDdvnuLXiIVRo0bB6/Xi73//O84++2ysXLkSTzzxRMBtbr75ZixcuBBjxoxBU1MTlixZgvHjxwMA7rjjDhx33HGYOHEi3G433n//feU6giAIIjXhqgjHL0lJDwb6nDKSTlx++eXo6urC9OnTsWjRIvziF7/AtddeG3I7QRDw7rvvYsCAAZg7dy7mz5+PESNG4NVXX43r+adMmYKHH34Y999/P4455hi89NJLuPfeewNu4/f7sWjRIowfPx5nnHEGxowZo5hbHQ4Hbr/9dkyePBlz586F1WrFK6+8Etc2EQRBED0L94twUkEZESTe2CKFaW1tRV5eHlpaWpCbmxtwXXd3N/bt24fhw4fD5XIlaQsJI9BnRRAEkXyueX4NFm9V+1Rt+uPpyHHZI9wjdiKdv7WQMkIQBEEQ/YhUVEYoGCEIgiCIfkJDazfqWrth0dRbUDBCEARBEESvwc2rI4uywQtAKRghCIIgCKLX2N/IGlqOKcmBTZZH/ClgHaVghCAIgiD6CU0dHgDAwGwHLLI04vNTMEIQBEEQRC/RKAcjBVkORRkRSRkhCIIgCKK3ONrhBgAMzHLAwtM05BkhCIIgCKK3OCorIwM0yggFIwRBEARB9BraNI2VDKwEQRAEQfQ2ioE1y0kGVqLnGTZsGB599NFkbwZBEASRIvhFCc1dXgBkYCUIgiAIIgk0dXrA444BmXbFwOpLN8/IvffeixNOOAE5OTkoLi7Geeedhx07dkS8z7PPPgtBEAJ+aEgaUFlZiZtuugk333wzBgwYgJKSEvzrX/9CR0cHrrrqKuTk5GDUqFH46KOPAADHH388HnzwQeX+5513Hux2O9rb2wEABw8ehCAI2L17NyorK3HgwAH88pe/VN5zgiAIon/Dzat5GXbYrBZVGUm3YGTZsmVYtGgRVq9ejcWLF8Pr9eL0009HR0dHxPvl5uaitrZW+Tlw4EBcGx0RSQI8Hcn5MSl1PffccygsLMQ333yDm266Cddffz0uvPBCzJo1C2vXrsXpp5+Oyy67DJ2dnZg3bx6WLl0qv0QJy5cvR35+PlasWAGAfTaDBw/GqFGj8NZbb6G8vBx33XWX8p4TBEEQ/Zujil/EAQAppYzYzNz4448/Dvj/2WefRXFxMb777jvMnTs37P0EQUBpaWlsW2gWbyfw57Leea5gfnsIcGQZvvmUKVPw+9//HgBw++2347777kNhYSGuueYaAMAdd9yBxx9/HBs3bkRlZSX+85//wO/3Y/PmzXA4HLj44ouxdOlSnHHGGVi6dCnmzZsHACgoKIDVakVOTk7vve8EQRBESnNUU0kDIH2VkWBaWtjAnYKCgoi3a29vx9ChQ1FRUYFzzz0XW7Zsiedp+wyTJ09W/rZarRg4cCAmTZqkXFZSUgIAaGhowJw5c9DW1oZ169Zh2bJlmDdvHiorKxW1ZNmyZaisrOzNzScIgiDSiMagYESppkmBYMSUMqJFFEXcfPPNOOmkk3DMMceEvd3YsWPx9NNPY/LkyWhpacGDDz6IWbNmYcuWLSgvL9e9j9vthtvtVv5vbW01vmH2TKZQJAN7prmb2+0B/wuCEHAZ93qIooj8/HxMmTIFS5cuxapVq3Daaadh7ty5uPjii7Fz507s2rVLUUYIgiAIIpij7epcGgCwWVOnz0jMwciiRYuwefNmxbMQjpkzZ2LmzJnK/7NmzcL48ePx5JNP4v/+7/9073PvvffiT3/6U2wbJgimUiXpxLx587BkyRJ88803uOeee1BQUIDx48fjnnvuwaBBgzBmzBjltg6HA36/P4lbSxAEQaQSvBU8V0as8oLXn659Rm688Ua8//77WLJkSVh1Ixx2ux3Tpk3D7t27w97m9ttvR0tLi/JTXV0dy2b2OSorK/HJJ5/AZrNh3LhxymUvvfRSiCoybNgwfPnll6ipqcGRI0eSsbkEQRBECnG0k/UYGZApByPp2oFVkiTceOONePvtt/HFF19g+PDhpp/Q7/dj06ZNGDRoUNjbOJ1O5ObmBvwQwJw5cyCKYkDgUVlZCb/fH+IXueuuu7B//36MHDkSRUVFvbylBEEQRKqhDMnLDgpG0s0zsmjRIrz88st49913kZOTg7q6OgBAXl4eMjIyAACXX345Bg8ejHvvvRcAOymeeOKJGDVqFJqbm/HAAw/gwIEDuPrqqxP8UtILbjzVsn///pDLJE3EWlBQAFEUA64/77zzAm7DOfHEE7Fhw4a4t5MgCILoGzS2cwOrE0AaByOPP/44AISswp955hlceeWVAICqqipYLKrg0tTUhGuuuQZ1dXUYMGAAjjvuOHz11VeYMGFCfFtOEARBEIRhgvuMpG0worcCDyZ4xf/II4/gkUceMbVRBEEQBEEkDkmS0NQZWNprlYWDVAhGaDYNQRAEQfRx2tw+eOWqGbWahl1HwQhBJIkvttfjH1/sMqT2EQRBpDu8x0imwwqX3QpAo4ykwHEw5j4jBJGu+Pwibn5lPVq7fZg/oQTjSqlaiyCIvk1w91UAsMpyRCp0YCVlhOh3bKppQWu3DwDQ4abGcARB9H2CzasAYJOVkbSfTUMQ6cjK3WoTOI9PjHBLgiCIvkGTjjKSSlN7KRgh+h0rNMGI10/BCEEQfR+ephmgTdPIBlZSRgiil+n0+PDdgSblfwpGCILoDyjdVwM8I6ljYKVghOhXfLPvqFLeBlAwQhBE/0A1sDqVy7iBlUp7CaKX0fpFAMCTAtMqCYIgeprWLmbaz8uwK5dR0zMiBI/Hk+xN6Bes2N0IAJB9W/CSgZUgiH5Ah5sFI1lOq3IZlfYSqKysxI033oibb74ZhYWFWLBgATZv3oyFCxciOzsbJSUluOyyy3DkCFvJv//++8jPz4ffz0pR169fD0EQcNtttymPefXVV+PSSy9NyutJB452eLCtthUAMLk8HwDgoTQNQRD9gA4PC0aynWp7MSrt7UEkSUKntzMpP2a7eT733HNwOBxYuXIl7rvvPpxyyimYNm0a1qxZg48//hj19fW46KKLAABz5sxBW1sb1q1bBwBYtmwZCgsLA2YBLVu2LGSIIaFyoLEDADA4PwOD8lwAyDNCEET/QFVG1GDEIqROaW+f68Da5evCjJdnJOW5v/7R18i0Zxq+/ejRo/GXv/wFAHD33Xdj2rRp+POf/6xc//TTT6OiogI7d+7EmDFjMHXqVCxduhTHH388li5dil/+8pf405/+hPb2drS0tGD37t2YN29ewl9XX6G+tRsAUJLrhMPG4nDqM0IQRH+AN3gMUEbk2l6Rqmn6N8cdd5zy94YNG7BkyRJkZ2crP+PGjQMA7NmzBwAwb948LF26FJIkYfny5Tj//PMxfvx4rFixAsuWLUNZWRlGjx6dlNeSDtS3stK2klwX7HKy1EsGVoIg+gERlZEUOA72OWUkw5aBr3/0ddKe2wxZWVnK3+3t7Tj77LNx//33h9xu0KBBAJjP5Omnn8aGDRtgt9sxbtw4VFZWYunSpWhqaiJVJAqqMuKCW1ZEKE1DEERfR5IkxTOS5VANrDZL6igjfS4YEQTBVKokVTj22GPx5ptvYtiwYbDZ9D8W7ht55JFHlMCjsrIS9913H5qamvCrX/2qNzc57eDKSHGuE/UtLDChYIQgiL5Ol9cPbgsJUEaUdvDJPw5SmiZFWLRoEY4ePYpLLrkE3377Lfbs2YNPPvkEV111lVJBM2DAAEyePBkvvfSSYlSdO3cu1q5di507d5IyEoWGNlkZyVHTNOQZIQiir9Mup2gEAcjUUUZSYU1GwUiKUFZWhpUrV8Lv9+P000/HpEmTcPPNNyM/Px8Wi/oxzZs3D36/XwlGCgoKMGHCBJSWlmLs2LFJ2vr0oK5FTdPYuYE1FfZCgiCIHqRTNq9mOWwQZJ8IAFiVYCT5x8E+l6ZJF7QluZzRo0fjrbfeini/Rx99FI8++mjAZevXr0/chvVhuGekNM8Jh2JgTf5OSBAE0ZO06zQ8A7TBSK9vUgikjBD9gi6PH63dbIcsznUppb1eX/KNW0aRJAkNckBFEARhFL1KGgCwCqmjjFAwQvQLuF8kw25FjtMGu1xfn07KyDMr92P6nz/Hm98dTPamEASRRqiVNEHBCFdGUmBNRsEI0S9Qe4w4IQiCamBNo2Dki+0NAIBNNS1J3hKCINKJdu4ZCZumSf5xkIIRol/A/SLFuawNvD3NPCOiKGHDwWYAwJF2d3I3hiCItKLTHTqXBtAGI8mXRvpMMGJ2LgzR+yTzM9I2PAOgGFjTpbR375EOtMmel6MdNOGZIAjjtIfzjFAwkjisViY7eTx0gE51+GfEP7PeRAlGcpwAoBpYUyFZaoAN1c3K3xSMEARhhg4lTZO6wUjal/babDZkZmbi8OHDsNvtAT05iNRBFEUcPnwYmZmZYTvM9iTcM1KaF5imSRfPCE/RAEAjBSMEQZhArxU8oFbT0NTeBCAIAgYNGoR9+/bhwIEDyd4cIgIWiwVDhgwJaLrTW4R6RtKrmiZYGRFFSWnlTBAEEYloaRqaTZMgHA4HRo8eTamaFMfhcCRNuWpok6tp5DSN3ZY+Bla3z4+tta3K/35RQmu3F/mZjiRuFUEQ6UI6GFj7RDACsFW3y+VK9mYQKYgkSWENrOnQ9GxbbRu8fgkFWQ54fSLa3D40dngoGCEIwhDtaeAZIYMF0edpc/vQ6WE7Y3GurIykkWdkfVUTAGBKeR4KslkAQiZWgiCMErYDKwUjBNF78BbqOS4bMuUOhLyaJh1KezccZE3OplTkY2AWC0Ya2ykYIQjCGNzAmh3c9EygYIQgeg21+6qaxksnA+vWQ8wvMrk8DwVZTNlp7KDGZwRBGIMbWDOD28FbeTt4CkYIosdRpvVqgpF0mtpbL8/VqRiQqSgjR0kZIQjCIJ2yZyTEwMpLe1Og3xIFI0Sfh/srCrJUw6faDj75O2Ek3D4/mju9AICiHKfiGaFeIwRBGCWcZ8SWQqW9FIwQfZ7WLnYyz8uwK5fx0t5UN7Byb4jdKiAvw64qIxSMEARhAEmS1KZnQZ4R3qsoFZqeUTBC9Hla5ZkuuRnqqoB7Rjw+MaXnGvGheIXZbNrwQKqmIQjCBF1eP3isEZymUZQRCkYIoufhykiuS1VGnJr5OKmwKgjHYblZW5HcrI0bWGlyL0EQRuDmVUEAMuykjBBE0mjtloORgDSN2ko9lU2sPBgpzGZBCKVpCIIwgzIkz2ELGcVByghB9CJKmkajjHADK5DaXVgVZSSbKyMsGGnq9KR0eokgiNRANa+GTku3pNCgPApGiD6PkqbReEZsmiFzqWxi5ekYNU3DghGvX1KCLIIgiHCEq6QBAJuVqmkIotdok0/aORplRBCEtOg1cjgoGHHZrYoJrZF8IwRBREHtvhoajFhJGSGI3kM1sAbujOnQhTXYMwKo6gj5RgiCiEa7xjMSDM2mIYhewi9KaHPz0l57wHXpMJ8muJoGUIMRanxGEEQ0InlGKBghiF6iXeOryAlRRlK/8ZleMEIVNQRBGCWSZ4SCEYLoJXhZr8tugdMWuDJI9ZbwnR4fOjxMYtVTRigYIQgiGkppLwUjBJE8lB4jLnvIdTxNk6qekSNtLNhw2S3IcqiB1MBsanxGEIQxIhpYLTS1lyB6hdYuXkkTuiMqBtYU9YwcbmfTeotynAHNiihNQxCEUXgHVl0Dq3xckaTkNz6jYITo0+h1X+WkumckuOEZh9I0BEEYxYiBFUi+OkLBCNGn0ZtLw0n1aprD8sRerV8EUKcP89dGEAQRDiOeESD5vhEKRog+jTqxN7wykqoGVr0eI4DaNTFVt5sgiNTBSDUNQMEIQfQobd36Dc8ApHwHVr2yXkDdbp+YmttNEETqoBpYKU1DEEmDG1j1lRG2I6a8ZyQnWBmRgxFSRgiCiIIRAysA+JN8PDEVjNx777044YQTkJOTg+LiYpx33nnYsWNH1Pu9/vrrGDduHFwuFyZNmoQPP/ww5g0mCDNEKu21p7gyogzJC5emIWWEIIgoGE7TpJMysmzZMixatAirV6/G4sWL4fV6cfrpp6OjoyPsfb766itccskl+OlPf4p169bhvPPOw3nnnYfNmzfHvfEEEQ1u8tQt7eV9RlLVwMo9I0HKiN1CyghBEMbolBsnZjpC0zSCIIDHI8n2jIQeoSPw8ccfB/z/7LPPori4GN999x3mzp2re5+//vWvOOOMM/Cb3/wGAPB///d/WLx4Mf7xj3/giSeeiHGzCcIYkUp7nSlc2itJkjqxN6yBNfW2myCI1KLby4MR/dO9zWKBxy8mPRiJyzPS0tICACgoKAh7m1WrVmH+/PkBly1YsACrVq0Kex+3243W1taAn/6EJEl447uD2Hqof73unqCNV9PoNj1L3Wqa1m6fUnIc7BmxUzUNQRAG8PpF5TiRYQ9VRgBAFlrTNxgRRRE333wzTjrpJBxzzDFhb1dXV4eSkpKAy0pKSlBXVxf2Pvfeey/y8vKUn4qKilg3My15Z30Nfv36Btz+1sZkb0raE7HpmU02sKZgmqa5k/UYybBb4Qo6iNgsFsDSCZ/fp3dXgiAIAKoqAgAuh/7p3iZHI2kbjCxatAibN2/GK6+8ksjtAQDcfvvtaGlpUX6qq6sT/hypiiRJeHLZXgBATXN3krcm/VGqadLMwMoVHT2vS11XFbLH3A2p8I3e3iyCINKILjkYEQS1JUAw3DPiSyfPCOfGG2/E+++/jy+//BLl5eURb1taWor6+vqAy+rr61FaWhr2Pk6nE06nM+z1fZmlOw9je10bAKClywNJkgLmkhDGEUVJ7TOSkV59RriioxeM1HZUQRBEwFHb25tFEEQa4fayY1uG3Rr2PMJbBYjpVE0jSRJuvPFGvP322/jiiy8wfPjwqPeZOXMmPv/884DLFi9ejJkzZ5rb0n7CE0v3KH97/ZIyQp4wT4fHBx7sR1ZGUs97oSojodstWPj2SkkfbkUQROrClZFwfhEAsMhBSrKr80wFI4sWLcKLL76Il19+GTk5Oairq0NdXR26urqU21x++eW4/fbblf9/8Ytf4OOPP8ZDDz2E7du3449//CPWrFmDG2+8MXGvoo+wrqoJX+87CrtVgE3Wzrh3gDAPbwXvsFpCfBeAZjZNCiojkdI0giAfNASReo3IbD3UqqhJBEEwuuTFrN7xj8PPNWmljDz++ONoaWlBZWUlBg0apPy8+uqrym2qqqpQW6vKx7NmzcLLL7+Mp556ClOmTMEbb7yBd955J6Lptb/y4Sb2vp01uUyZzNrcSQfYWImUogE0U3tT0MDaFqFZmxKMQEz6aiYVWL7rML73t+X43dvUu4ggtCjKiE6PEQ5vfJZWnhHJQOS0dOnSkMsuvPBCXHjhhWaeql+yu6EdAHD8sAHYeqgVDW1uCkbiIJJ5FdCWyKZiMBJBGQFXRqSU3Pbe5u21NQCAtQeakrwlBJFa8GDEZQ+vO/BgJG2raYjEs/cI62Q7ojAbeZnsBNpEaZqYUbqv6pT1AmqaJhVP6G0RDKxcGREgpqTfpTfx+ER8to0Z5A+1dAWUMhJEf8dtwDNCwQgRgNvnR/XRTgDAyOIsDJCDkeYuUkZipTXCxF5Am6ZJvRN6JAOrpFFG+vvk3tV7GxVvkCQBB5s6k7xFBJE6qMoIBSOEQQ40dkKU2Eq4KNuJ/AzZM9JBykiscGVEr+EZkB59RvQCKb/EV//kGfl4S2DzxH1HKBghCE6XRy3tDQef3EvBCAEA2CP7RUYUZUMQBORn8TQNKSOx0hrhhA6kdppG7TOio4xImmqaFNz23sIvSvh0C0vRFMrzew40hh/aSRD9DSMGVgtXRtKpmoboObhfZGRRFgCoykgXKSOxEqkiBQAc1tRtBx/JwKoqI1LSHfDJZG1VE460u5HjsuEHxw4GAOw7QsEIQXC4h8pli17a609yypeCkRSBKyMji7IBQPWMkDISM0o1TVqmacIrI6Ikb28/V0a4cXX++BKMKmb7zYFGStMQBKfbjDKS5EMJBSMpwp7DPBiRlRElGCFlJFYitVQHNAbWFPRdRFJG1BJ7qV97RvYeZirIsUPyMbyQ7TekjBCEipmmZ+QZISBJknJgHSErI/mZ1PQsXtrd7ISe7YwcjKSiuqAaWEOVEZ6mEfq5MlLTxDo/lw/IxNCBLBg51NIFt4/KewkCMNYOngyshMLhNjfa3D5YBGDowEwAGmWESntjplNeFWQ6whlYU7PpmdcvKgcRXWUEagfW/txnhJfxDh6QgcJsB7KdNkgSUH20K8o9CaJ/oBpYDTQ9IwMrsUdWRYYUZMIpG40GKMqIh4ahxUiHrIxkOfVXBQ4ru9ybYgbWdlkVAYBsnWBE6xnpr31G2rq9SrXU4PwMCIKgBPL7KVVDEAA0BlZDfUbIwNrv4X4RnqIBgDzZdClKQJvbp3s/IjLRlBG7rIyk2qA8nqLJsFuVVJIWJRjpx56RmmamfgzItCNLTsMNk1M1+6m8lyAAAN1edqwwFoz0yiaFhYKRFID7Rbh5FWBfHp7nIxNrbHR6IisjqTooL5rxlqppgINyKmbwgAzlsmGFsjJCwQhBAFANrMbawZMy0u/RU0YAKu+Nlw432xGzwnlGFANraqkLkSppAOozAqjKyOB8NRjhJlYq7yUIhiEDKykjBOeQfGAdUpAZcHme7BuhYXnm8YuSsiNmhqmxT9Vqmkg9RgC1tFcQJHj6aeUIN6+WD1D3GSrvJYhADHlGBFJGCJkj7W4AQFGOM+Byroy0UEWNabo001uzwpb2sp3QJ0opZRKOpoyonhHA4++fwYiuMiIH84eau+BLsQCTIJKBoWoaK5X2EmCrcj5/hs/X4PDy3iYalmeaTtn0axEAp03/a+7QXO5NoaqUaG3sA4IRX/80N/MeI1rPCK88EiXAnWI+IIJIBkaannFlJNkpXwpGkkxjOws0rBYB+UFty5XGZ6SMmKbDo/pFBHlnC0ZbqZJKvpGoygg0wYjYP4ORg0rDMzUYcQR8nhSMEES3Ac8I78AqUp+R/g1P0RRmO5QZARwenJCB1Ty8x0hmmEoaIDAYSaWKGl7KbSRN4/X3v2Cky+NHo6wWluernhGb1QK+C6XS50kQyYKX9hqZTUPKSD/ncBsPRpwh1w0gA2vMdHoiV9IATI3iTvJUWklHM7AGBCP90MDK/SLZThtyMwI/Xx5gUpqG6O/4/KLSQ8nI1N5k++YoGEkyh9vDByN5VNobMx2e6MoIoJpYU2kl3WrGwNoP0zRqJU1GSAqO+4BSrZEdQfQ23ZpjGikjRFSORAhGtC3hCXN0uiN3X+WkYnmv6hkxoIz0w2oavUoaDjcrp9LnSRDJgJtXgfAmfoCUEULmSBsLNILLegFN0zMysJqGKyNZEVYEgPbklUoGVoMdWNFPgxGdShpOqnbVJYjeRmteDWfiBwALVdMQgDZN4wi5jkp7Y6dTMbCmszJCfUb00Kuk4ShpGgpGiH6OEoxEWZDZaGovAQBH2vQbngFqaW9rty/pDWnSDbW0N5pnJPUMj2b6jPTHaho1TZMZch0v7yXPCNHf4Q3PXBFSNICmHXyS1WEKRpKM0n1Vz8Cq6TtCXVjNwYfkRfeMpGI1jYnSXrH/KSN1Ld0AgEH5rpDrSBkhCIbS8CzKgsxCyggBaAysOsqI3WpRDq7a9uZEdJQheVGraVIrTePzi0pZctjZNFAPGv1RGeGl7gWZoalN8owQBMPIkDxAk6Yhz0j/JVIreI6TDq4xYVQZcaRY9UW7Ww0uok/tBXwp1Ma+N3D7/EqwNkAnGHGkoCGZIJKB0vAsSjBiESgY6fdEagXPcdq5p4GUETNwz0h2FAOr4jHwpcbJi6doXHZLQIdYLZJGTvX2sz4jvOeORdAP1pxKnxHaX4j+jVkDK7WD78dEagXP4SdLt7d/rYDjRammMWhgTRVlpDVK91UgSBnpZyddnqLJz9TfZyhNQxAMnqZxRui+CmianpGBtf8SqRU8xylLbFQdYA6lmiZaaW+KGR6jmVeB/m1gbepgwRovew9GraZJDaWLIJIFN7BSaS8RlUit4DlcdiZlxByqZyTyjuhIsWqaaN1XgeA0Tf8KRng3Yj2/CEDVNATBUQ2sBkt7yTPSf4nUCp7DD67kGTFHp9ugMpJiaRql+2qE7damafz9LBjhhu8BYZQRStMQBMNtsJqGghEiYit4jpNWejHRYVAZsaeYrK+ml8Jvt1YZ8fW7YET1jOhByghBMJSmZ1GOgRSMEBFbwXO4+SiVOoSmA4oyYrC0N1VOXtx4G2m7RfTf2TRqmiZM9VmKlWoTRLJQO7BSMEJEIVIreA6lacwjSZKqjERpeuZMsfeX99CItN1aA6s2ZdMf4GmaqMoIBSNEP6fLI/cZiaaMUJ8RIlIreA6laczj9ong+1U0ZcQl51O7U8QgbKRZmzYY8fW7PiORDay8vX88+4skSfjd25tw4RNfYUN1c8yPQxDJpNusZ4SqafovkVrBc9SVe2qcLNMBbRfTaDsif3+7U6TdvqKMRFjN9OcOrNEMrA5r/KXwq/Y04qWvq/Dt/ib84PGv8NiS3QE+HYJIB4y2g6c0TT/HSCt4QJum6V8nnXjgfpFMhzVsMzkOV0ZSLk0TIRjRnhj7XzVNzxpYJUnCw4t3AgAG5bngEyU88MkOLNnRENPjEUSy6CYDK2EE3tZaEBC2FTxABtZY6DA4lwZgbdeB1EnTdLhNpmn6mWeE7zcDssKV9saXplmx+wjWHGiCw2bBO4tOwmkTSgAAew93xPR4BJEsVAOrsT4jPgpG+ictXWyFl+uyR1y9p5rBMh3gvotoE3uB1FNG+AEk0rYHGFj7kTIiipLiGdGb2AvEV00jSRIekVWRH00fgpJcl6Ja8m6WBJEumO3AKlIw0j9p6Yrc1prjoA6spulQ0jQGlBFbahlYuTKSYTemjPj7kWekrdunGJN7Ik2z5VAr1lY1w2mz4IbKkQDUfHtXiniKCMIoRg2sfGovKSP9FC4350VI0QBqmoZKFY2jKCNRVgSAOhU51QysEZUR9M/SXu4XyXJYlaAjGLWJnfn9ZZ1cOTNjxEAU57oAABkO9ngUjBDphpKmiRKM2Kw0tbdfw5WRqMGInZQRsyjKSJRW8IC2tDc1TjaqgdWgMtIPg5FwqggQnzKyUQ5GppTnKZdlpNj3gyCMwtXeaGkaRRmhqb39E6PKCJ9CmiqehnTAlDJiSy0Dq5EBf/3VMxLNvApop/aa/zw3HGwGAEwuz1cu48EqeUaIdMOwMmJh+wwpI/0Uo54RroxQ0zPjdBhQFziKMpIiwV6HgTb2gcpI//leNEVpeAYA9hiVkQ63D7sb2gEEKSMO8owQ6YdflJR9IKpnRI4CyDPSTzGcpqHSXtMo813MVNOkgDIiipJy0qN28KFEawUPAM4Yp/ZurmmBKAGluS7FLwJoDazJ/34QhFG0acWoTc8Eqqbp1yjKSEb4AyuQeoPc0gFzykjqpMG0q2+jTc8AKenNinqLaEPyAHV/MVvau/FgCwBgskYVATTBiKd/td0n0hvtscQZpc8IN7CSMtJP4QfW6MpI6pws0wUznpFUKu3l5lVBiDxpM1ANEfvNhNqeNLByv8iUivyAyylNQ6QjSvdVuyVqF2oLDcrr3yhpmmieEWoHb5p0rabhQVSGPXIbe22aBoKU9BVNbxFtLg0Qe2mvEoxozKuAVhlJ/veDIIzSbdC8CpCBtd/TbNAzQmka88RSTeMTJfiSrDAYbdYmQXvQEJO+3b1FtIm9QGz7y9EOD6qPdgEAJgWnaRypo5wRhFG6POz7Gklh5ZCBtZ/TarSahgyspolFGQGA7iS/x11eY8bbgDSNIMKb5P4AvcXRjuj7TCylvRtlVWR4YVbI4oA6sBLpCK8OjNZjBNAoI+kWjHz55Zc4++yzUVZWBkEQ8M4770S8/dKlSyEIQshPXV1drNuc9kiSZKIDK3lGzBKLMgIkP1XDg6ho7vdgA6uvn7SE7yllZMuhVgDApMF5IddRnxEiHeHHsmjmVQCwpqsy0tHRgSlTpuCxxx4zdb8dO3agtrZW+SkuLjb71Ann169vwOmPLMN3B5p69Xk7PX7lg49WTeOkNI1pzFTTWCyCcgJLdjCiDviLvN1aZUQQRHh9/UMZMdJnhCsjomTckLf/CJvIO6o4O+Q6rYFVSnJOnSCMwtOKRjwj1hRRRqIfrYNYuHAhFi5caPqJiouLkZ+fb/p+PUlVYyd21rejrqW7V5+X+0UcVotSWhoOStOYx0yfEYCN2Pb4xKS/x2oreHPKiLcfKCPdXr9ygM2P0IF1T+s2WJyHILrL4PGJhmTq/Y0sGBk6MDPkOq1K5faJhg7uBJFstNU00bD2t0F5U6dOxaBBg3Daaadh5cqVEW/rdrvR2toa8NMTDMxmK6zGDnePPH44WjrVShpBiFx2pcymoWDEMGaUESB1Kmo6DAYjgdU0YtJnSvQGPK1ptQjICaMcuf1u3PDFNcgc+hQA0bCauL+xEwAwbGBWyHXa4INSNUS6YLQVPABY5T4j/r5eTTNo0CA88cQTePPNN/Hmm2+ioqIClZWVWLt2bdj73HvvvcjLy1N+KioqemTbeDBypN3TI48fjuYuYz1GAFV29qdAtUe6YGS+ixY1GEmygVXxuhhP0/SXPiOt3SwYyXXZwgbwXd4udPm6IFi7AcFvyMTa4fbhcBtbjOgFI1ZNGo9MrES64ObBiIFqGmuK9BkxnaYxy9ixYzF27Fjl/1mzZmHPnj145JFH8MILL+je5/bbb8ctt9yi/N/a2tojAcnALCcAoLG9d5URpZLGQDDi1MhsHr8Im5UKoCLh9avVJUaDEcUknGxlRKkCMpGm6Sd9Rtq6WaCW4wq/zwQHaUaCkQOyKjIg0x6250+G3QqPT6RghEgbVM+IEQOrGoxIkhRVre8pejwY0WP69OlYsWJF2OudTiecTmePb0chT9P0tjJisJIGUJURgM1PieDdI6D6LgBjZW1A6gzLUxUdc8pIf1DM2mRlJDuCuTe4GZyRNI3qFwlVRTgZditauryUpiHSBjNNz6yaBouiBFiTE4skp8/I+vXrMWjQoGQ8dQADs2VlpLc9Iwa7rwKAzWpRviyxjEXvb/AThtUiBARykeCrh2SnaWI2sPYDz0i7mysj4YOREGXERDAyvDBCMOJIDU8RQRiFL6zMBiPJTNWYVkba29uxe/du5f99+/Zh/fr1KCgowJAhQ3D77bejpqYGzz//PADg0UcfxfDhwzFx4kR0d3fj3//+N7744gt8+umniXsVMTIwK0nKiMHuqxynzYJOjz8lJsumOlq/iFG5UZncm3RlhD1/NM+ICPV7IAj+ftFnRE3TGFNGBMGYl+bAEZam0auk4fDvRycpI0SawBdWThNpGiDNgpE1a9bg5JNPVv7n3o4rrrgCzz77LGpra1FVVaVc7/F48Ktf/Qo1NTXIzMzE5MmT8dlnnwU8RrLgysiRXvaMGJ3Yy1GCEWp8FhWj6oIWZ4oMy+uQV//R0kvB6Yj+YGBtN+0ZkQxVoHFlRM+8ysmkYXlEmtFtwsBq0wYjSayoMR2MVFZWRmz+8+yzzwb8f+utt+LWW281vWG9AfeMtHb74PGJimu+p1FKezOMvf0OGpZnmE6TZb2ANk2T3JMNP9lF648SEIygf7SDN+8ZMZemiaSMZKRI6TdBGMVM0zOLRkH2J/FY0q9LM3JddiUqPNrRe6kaRRkx6EalxmfG0U6+NUrKKSP2KGma4Km9/SEYMeIZEQOVkWiKUafHh/pWpopG8oxQS3gi3VA9I9FP8amijPTrYMRiEVCQxXuN9F6qxkyfEYDm05ihK4Y0TaooI4pnxKQy0p88I9lGDawGlJGqo8wvkpdhj7gwyKA0DZFmuE1U01g0wUgyjyX9OhgBtBU1va+MGKmmAWIb/tVf4Sd0o2W9QCqV9hpLMQWnI/pDmsaIZyQ4SItWfcZn0gyLkKIBgAw7NT0j0gszfUYA1cSazHVNvw9G1F4jvaiMmOgzAmiVEQpGotHpjV0ZSXa1ktHOsQFVI+gfnXnb3GyfCdcKHtAZIBgtGGnklTThUzSAxjNCaRoiTTBjYAXUYISUkSTS2+W9flFSJGejwQgZWI3TZbBxmBaXLc1Ke4MNrP2gA2u7ydJeI9U0B3glTQS/CAC4KE1DpBlm+owAakt4UkaSiFLe20uNz3greMCMMsK+UJSmiU5caZokKiOiKKlpmmieEQQaWL394HuheEYMKiNGPCP7eY+RgmhpGgpGiPTCTJ8RQDWxkjKSRAp6WRnhfpEshxV2gx1CycBqnC5FXUgvA6v2RGdqam9/MbC6Y/CMRAlGqptYMDIkqmeEV9P0/feZ6BuYaQcPqCZWkappkkdve0aaTZb1Apo0DXVgjUoHL+01kaZRS3uTF4xwVUQQoud5Q5ue9f00De8zYri0N0ozOJ9fRG1LNwCgYkCUYITawRNphmJgNegZsSnD8npsk6LS74MRZXJvL1XTcGUk12CKBtCkafqBUTFeYurAmgKzaRTzqt0aUGoXTGjDQbHP9xnx+kXlszHuGYmsjNS2dMMvSnDYLCjOiTyU00VpGiLNUEt7jZ3iLZSmST4De3lyr1LWa7D7KqCeLEkZiU5sfUaSX9rb4eZeFzMTewEIfT9Nw82rAJAVwTPik9TbQZAiBu/Vco+R8vyMiMEfoE3TUDBCpAdmDaw2Ku1NPoWa+TSR2twnilaTQ/IAKNNnyTMSHcXAaqIDayoYWLu87EQareFZ8HdU6AdTe9vdalfdSD6rwJLnyH1GuF+kPIp5lT8voJaNE0Qq4xfVY4Jhz4iQfGXE9GyavgZXRtw+ER0ef0S3fiJolXPfuRGMeMFwZYSqaaLTFctsmhQwCCvKSJSDh64y0sfTd3yfidR9FTA3m6b6aBcAoGJARtTn5yob9Rkh0gGtt8lomqYw2wGPXwyY4Nvb9PtgJNNhQ4bdii6vH43t7p4PRrrYKi8Wzwj1GYlOp9dY4zAtfPWQzDQY94xESkMAwb4IAJDg6+N9Roz0GAGCZ9NECUZkZaTCgDJCfUaIdCIgGDFoYH33xtk9tTmG6fdpGkBVR470gm9EMbCaUUZSYOWeLsTXZyT51TTRgigJQYGHEL3tebrDe4xE6r4K6FUZRfeMRKukAajPCJFedMtBuMNqieqHSiUoGIFmPk0vlPcqaRozBlaaTWOYWAys/P1NZjDSYXC7Q9I06PtpmnYDPUaA4PcmmjIip2kKoqdpqB08kU7w45jRhmepQnptbQ9RyBuf9UJ5b2tcykjfPukkglhKe9VqmiQaWHmaJorXJcRkLUh9vrSX9xiJlkIN8YyECdK6vX4cbmMLD0PKCKVpiDTCbMOzVKHfe0YANU2zfNdhOG0WlOVnYPygXFMVL0ZpNTmXBqCpvWbojGU2jbyCYC500XBn3ETCDaxRW8EHeUaEfjCbRu2+arzsWYAEj0//fTko+0WynTbkG5iczQ/qviR+PwjCKGYn9qYKFIwAKM5xAQA+3FSHDzfVKZdPLs/DfedPxoSy3IQ9V1scTc9IGYmM1y8qJW2xKCMAW1Uk42RjNIgKrabp+1N7lbk0JoKRSMoIr6QpH5ABQYieU9dWOHUl6ftBEEZxm5zYmyrQXgXg4hMqcO7UMpw8tgizRxWiXC7323iwBec9thL/Xr43YT1I4vGMkIE1Mp2anL4ZAyt/f4HkBXyGDaw6HVj7fJ+RboOekYBqGgmeMPuLmUoaALBbBaXkkXwjRKrDG56ZOQamAqSMgB2U/vrDaQGXNbR247dvb8Jn2xpw9wfbAABXzxkR1/NIkqSW9prwjFCaxhjcvGq1CEqjOCMIggCnzQK3T0yaidVoMNIfO7Aqc2nMekbC7C9mKmkA9v3IsFvR7vaRb4RIeczOpUkVSBkJQ3GuC/+6/Hj8ZsFYAMBfPtmBnfVtcT2m26dKx5SmSTza+S5G5HctakVNspQRYwP+QpWRvm9gbY/BM4IInWmVhmcGKmk4NJ+GSBeomqYPIggCbqgciZPHFsHjE/HLV9fHpU7wHiMWwdyIe2U2DQUjEYmlxwgn2b1GFGUkigNeRNB3oB/0GWk1mKYxrIw0mVNGACDDwfZBmk9DpDqqgZWUkT6FIAi4/weTkZ9px5ZDrXhy2Z6YH6tVY141s3LnKQdK00SGr1rNmFc5ShfWJPlyug1uuyiGVtP0dQNrewwG1kizaZQ0jUHPCECNz4j0IV1LeykYMUBxrgt/PHsiAODfK/ahw+2Lcg99uHnVbMmwqozQgTASqjJi3grFy+CSl6YxpuqEKiN9vx18m1v2jCRgNk1ju1tRWsykaWhyL5EuKBN7bel1ek+vrU0iZ08pw7CBmWjp8uK1NdUxPUYs5tXa9loc7j4IILmzU9KBLo/5uTScZKdpugxOGw6dTdOPqmlMze2RdJWR3Q3tAFhZr5leNNT4jEgXKE3Tx7FaBKWa5t/L98UkjcdS1nvZR5fhlhVXAoIH7j4ux8eL0jgslmAkySbhToPThkOCkT4+tVeSJHU2jZl28GGUkV1yMDK6ONvUdpAyQqQLSp8RMrD2XS44rhwDsxyoae7CB5tqTd/fbCt4URJR31mPbn8XBGsXPD4xYf1O+iKdcXhGnEqaJlkGVl5NY1YZ6dtpGrdPVF5fVM9I0NRevUF5XBkZU5Jjajv455LM+UUEYQTyjPQDXHYrrpg1DADwzMr9pu/Pc9VGg5HAlR67L1XUhKcrhlbwHF4+nSzPCH/eqAZWHWUk0nTadIeriYKBCrTA/UUKo4yw8vxRJpURKu0l0gVK0/QTzp5SBgDYUWe+50hLl7k0jXalJwjs775exhkP8ZX2Jk8Z8fnVyg/TwQikPh2MKJU0TlvUCrTA94YpKmKQarSrXk7TmFVGlDRN332vib4BN7A6ycDatymUh+p1ef2KtG4Us2mawJUe+5tMrOHpMtirQw91cm/vByOdmgAo2momuJpGEMQ+3fSszYSaGFDaK7D3RBu8t3R60SBP6zWrjFBpL5EuUJqmn5DttCnt2RvbPabuqxpYjQUjPlENdhw2dlCl8t7wGG2prkcyS3t5EGURoq9mgvuMhPNG9BV499XsKJU0QKgyAgQGI7sPMzWzLM9l6PG0kGeESBcoTdNPEAQBA7OYOnK0w2QwIpf2Gu0zoj242m3ySo88I2GJq88Ir6ZJwslGW0kTNRXRz/qMKHNpophXgdBqGiBwf9kpp2hGmUzRABrPCFXTEClOF1XT9B8Gyqmaxg63qfuZLe3VHlx5MEIG1vB0eePvM5KM97fLhNeFV1PZLPw71D/SNFlGlBGNamS1hAbvil/EZIoGoDQNkT4opb00KK/vU5DlBAAcMZumMekZ0aZp7FaepqFgJBzxGFjVQXm9f7IxE0TxANVukb9DggRvH57aa3RIHhAYvPNgRJvC4pU0sQQjWU722cTafZkgegtK0/QjCmNN03AznsE0jfbgarOFys5EIDwYyYqpHXzyPAGdBruvAmrqTquMSBLg76Opmg4TnhHt/mLRUUZ4j5HRJeaDEb6A4OomQaQqSjt4StP0fQrkYKSx3XiaRpIk89U0mtJem5UMrNHojKsdfPIMrGYUHR6McGWEVY303fLethgNrPJsSUVJbOv2oralGwAwqsi8Z4QvILjviyBSFaqm6UcMzGZpmkYTykinx68YDY16RnySeuDjygiV9oYnrjRNEkt7u0xUAYUqIwAg9aqi8/HmOpz5t+V4YfWBHu8IzJURI54RPWWEB2nbalmKpjjHibxMc4MqAXUBwXsFEUSqoqZp0uv0nl5bmyIMVJQR48EIl3dtFsGQHA8EKiNWS2ipIhGImZN6MDy10+lOhmeEp2min3D5yV/xjAAAxF47SW482Iyfv7IOWw614g/vbMZl//kG9a3dPfZ8ypA8A56RQGUkME3zujzccubIgTFtB6+AozQNkerwhYmTDKx9H15NY8YzokzszbBHLd/kBHhGrOxvKi0MTzx9RrhalYyTjZntDjGwAoAgobmz57e7obUb1z7/HTw+EccMzoXLbsGK3Ufwu7c39dhztsvBoSFlRBO8WzRNz452ePDuhkMAgMtnDo1pO/j3o9Pj77MpMSL9kSRJSU1SmqYfoKRpTHhG+EnOaI8RIPDg6pTv1kYrs7B0xdFnRDEoJkGG7zLhdZEQXNoL9JYycttbm1DX2o1Rxdn47zUn4pkrpwMAvjvQ1GPpmnY3e11mPSMuBwv4n/tqP/77TZUSQB07ZEBM26GdGJyM7whBGEFbbUlpmn6Akqbp8Bg+CKvmVeMnSq1nxGFnz9NCBjpdAua7mFgRbG3cit8u/y3cOApArXjqTbgyYmQlo+sZESQ09/AJsqXTi6U7GgAA//zxschx2TG1Ih+CADR1ek2XuRulQ1ZGzFbTTC7PhcNmwWfbGvDI4p0AgCtmDjOsSgZjtQjIcXL1jPZBIjXpNjFaItWgYCQGeJrG7RPRYTBtYrYVPBCojPB28GSg00c738WMgfW1Ha/hf3v/h28PfwGA9bXw9bIMH3eapheUkRW7j0CU2EyXMXIH0wyHFUMKMgEAu+rND440gtIO3qRnJD/ThrvPPQYA4BMlFGQ5lCGXscL3XdoHiVSFm1etFgF2a3qd3tNra1OETIdNkcCMpmoUz4jBsl4gcKXHlREy0OljZr6Llm4/M1+KUD/Htl5e+fLVjKE0TUgHVjYsr6WzZ5QJDldFKscUBVzOA5OdPRyMGOkdo91f/JIfF51QgctOZB6RK2cNi3ulqJb30j5IpCZKWW+aTewFKBiJmYFZ5sp7+WrKaFkvENyBladp6ECoh5n5Llr4e+yXvEow0NsBn5mZOvyEaxEsEMBfp9Sj3wtJkrBs52EAQOXY4oDrxsgNxHbKDcUSjZlqGq2SyN+nu86diE9unosbTx4V97bwFCvtg0SqojY8S68UDUDBSMwo82kM5srNNjwDgqtpKE0TCd6PwmwlDQ9G3H63Yi7u7ffYTJqGKyNWwQqrIN9eEHu0mmZrbSsa2tzIsFtxwvBAA6iijNQlXhnxi5JS9mxoNo0mTcPn1AiCgLGlObBYYvOKaKHyXiLVSddW8AAFIzGjTu41lqZp7orPM2KVgxGSiPXpMpHq0MLfY6/o1VTU9G6axsxsGn7CFQQBFoHvvj2rjHBVZNbIgSG9C0YXq2maRFfUtGvmwPDZMJEITtMkGvKMEKmO0mMkzSppAApGYsbssLxmOac/INNh+Dm01TRWuc8IBSP6tJvo1KnFK7H30+13J63XiJlqGiVNAwusFq6M+Hu0mmbpDp6iKQq5bkRRFiwCqzBpaDM3xToaXO1yWC2GGjgFKCNS4k3IyQpWCcIo3Wk6sRegYCRmCk02PmuSZfQBJlpRBzRxslCaJhJm2oZr4e+xx+9JWprGTOdY3mfEYrEEKiM9lKZpd/uw9kATAGDemOKQ6112K4YNzAKQeBOrmUoaoOeVEUrTEKlOuraCBygYiRmzw/KaZGUk34Qyoj2gCgL7u4M6QOpiZrqrFu4Z8fg9SWt8ZibFxFf8FqjBiCD0XGnv9tpW+EQJpbkuDBmYqXsbtaImsSZWVe0ytsrrcWUkgwysRGrjJgNr/8PssDxuMORBjBG01TQ8GAF6v/Q0HTDTNlyLEoyIHrV0M1nVNAZm0yjBiGBRDayQ0NzVM6W9O2S1Y2xp+Em3vKIm0b1GeCVNttPglOveUkYoGCFSlHSd2AtQMBIzZqppRFHSeEZiq6bxSV5l1U8rs1BUZcSkgVV+j5lnJPXTNNpgREnTCCK6vWKPTO7lVTKRgpHRPdRrxOxn2nueEdr/iNSkX6VpvvzyS5x99tkoKyuDIAh45513ot5n6dKlOPbYY+F0OjFq1Cg8++yzMWxqaqG2hI+epmnt9kKUCw3MpGm0B1RW7UHBSDg6TDTH0sKVEa9ffX9706AoSRI65dk0RjrH6ikjFqHnKq146mV0cXbY2/A0za769oRW1LSZTL3p9RlJJKpyRsokkZr0KwNrR0cHpkyZgscee8zQ7fft24czzzwTJ598MtavX4+bb74ZV199NT755BPTG5tK8DTNUQPzabh5NcthhcNEZzxtmsYreqkDZARirabhFUsef3LSNB6/qASqZoMRroxkudj9eiJI3WkgTTOskHlJ2ty+hG6DWVOyNgDpCWUkWQZngjAK95+ZGYmRKpgeb7pw4UIsXLjQ8O2feOIJDB8+HA899BAAYPz48VixYgUeeeQRLFiwwOzTpwxcGfH6JbR2+yJO443FvAoEpWn8PjoYRiBeA6tbTE7Tsy7NbCMjA/70lJFspwUtQMLLe4+0u9HY4YEgsJk04XDarMh12dDa7cORdrfp73k4zHRfBQIDEK1KkiiU0u8uLyRJinnoHkH0FEowQp6RUFatWoX58+cHXLZgwQKsWrUq7H3cbjdaW1sDflINl92KLDn6jFZRo/hFsoz7RYDAA6pWGaFgJJR4DawsTdP7yhM3rzqsFtgMDLbSVtPwPiPZTna/RJf3cr/IkIJMZEZJfxXmMKXwcFvijLTtHnOpt94ysPpESfncCCKV6PKkrzLS48FIXV0dSkpKAi4rKSlBa2srurq6dO9z7733Ii8vT/mpqKjo6c2MiSLlABw5GGnq4D1GYldGvKKXlJEIdJgsA+XwgC+w6VnveQI6TR48lGDEoiojPE2TaGWEp2h4l9VIFGbzJoCJa3ymVNPEoIz0RJomw26FTW4rT71GiFSEgpEEc/vtt6OlpUX5qa6uTvYm6VKc6wIA1EcLRmLovgqEekao6VJ4Ojzx9xlJZprGaBt7pemZps9IFldGErzdO2Tz6tjS8CkaTlEPBCNmU289rYwIgqAp7yUTK5F6dKZxmsa0Z8QspaWlqK+vD7isvr4eubm5yMjI0L2P0+mE0+ns6U2LmxIejLR0R7xdUwxlvUCQMuL3IjebDKzhSKSB1eNjZbK9UatvNserndobEox0JrbXCFdGeLVMJMwOjjRCu8lgpKeVEYBV1DR2eEidJFKSbpOLm1Six5WRmTNn4vPPPw+4bPHixZg5c2ZPP3WPUyKnaepbowUj7MBl2sAqBqdpqLQ3HHF3YBU9yHbYwD2JvaU+mSnrBfQNrJlOttGJTNNIkmSoxwinR9I0Zqtperi0F4Cm/Jv2QSL16OpPTc/a29uxfv16rF+/HgAr3V2/fj2qqqoAsBTL5Zdfrtz+uuuuw969e3Hrrbdi+/bt+Oc//4nXXnsNv/zlLxPzCpJIaZ6xNE0sDc+AwEF5XtGLvEySiMPREaeB1e13QxB6v7GV2TSNXmlvpiPxaZq61m60uX2wWgQML8yKevueDEZimU0jij2njAC0ICBSk07leNLjSY+EYzoYWbNmDaZNm4Zp06YBAG655RZMmzYNd9xxBwCgtrZWCUwAYPjw4fjggw+wePFiTJkyBQ899BD+/e9/p3VZL0fxjERTRriB1UQreCBwpecTqbQ3HJIkKZ4R0wZWKfA9VueP9E7ApxpYzaUitMpIhkNWRhJYTbNDVkWGF2YZmpjLB0ceTmCahgeYqeIZAZC0kQEEYYTu/uQZqaysjNjkS6+7amVlJdatW2f2qVIenqZpiJqmib/PCOvASsGIHp0eP/hXMtY0DSBX1LjsALp6L03Dh+QZPHjwfc8iWGCxsLVEhj3xysjewx0AgFFF0c2rgFraeySKSmgGPoPJaGlvb3hGaEFApDJmq/NSifTTclIIxcDa6o7YBEkZktdPq2maOz344VOrcaCxE7kZNkwsy8NfLpisSPvxwv0iFsHcikCSpICAzyN6en0YWrfJgwffXgGCqoz0QDVNdVMnAISd1BtMYZaapklUQzD+ucbU9KzHPCOUKiVSF2p61k8pzmUH4C6vX5mjEYwkSTiqKCPxVdNoT5SimLgZID3NvR9ux/a6NnR5/ahvdeOL7Q245vk1CRvs1q6ZS2PmJKj15AByRU0ve0Zi7TNitVgVzwhP0yQ0GDnKgpGKAoPBSA4LtN0+ER0JaAjm84vKgTWWdvA9l6YhEzmRulCfkX5KpsOmrNrCpWq6vH54fOwEEo9nxCt6lecSJbU7Zarz9d5GvLqG9Yl56rLj8PLVM5CXYce6qmb86rUNCQmq4jWvclh5b+82Puv0sucxnKaR+4xolRGXXQ1GEjWorvooa0hYMUC//D6YTIdNMeEmIlWjDWiM+oC0ptWeMrCmqzpJ9H0kSVICeCrt7YeUyqmauhb9AzAv67VbBaV9vFG0qzsJEuw2KIP2Et36uydw+/z47dubAACXTB+C0yeWYtaoQjx52XGwWwV8sKkWT6/cF/fztMfZfZUTU+OzloPA5jeB9gZTz80xW03DvxNWQVVGeAzmFyXlvYgHSZJQJSsjQwwqI0BiK2r463BYLYYMtEAvKSNJGBlAEEbw+iX45cVdvyjtJQIpiVJR09ShmlfN5tGDV+7p5ht5d90h7DncgcJsJ247Y5xy+YkjBuLOsycCAP76+S4c7YivAiPeHiMct+g2d7I5sAp4Yg7wxk+AB8cA/1kAHN5hahvMVtNoDaxcGbFaAaccpCaioqaxw4Murx+CAAw2qIwAakVNIoKRDpNlvQAZWIn+TcDQTVJG+h/cN1Lfph+M8JOD2R4jQOjqjlXUpE/OeulOphZcduJQpUcK55LpQzB+UC7aun342+e74noetaw3tu6rHK/fa7x0c/ObwPPnAF1HgYwCABJQvRp4dxFgIlViVlZVDKyCoCgjftGv+JES8b3gfpGSHJdhVQIABsrKSCLKe5VKGhNqV2+W9rb14vwigjACP5bYLALsBoZuphrpt8UpBldGGlrDpWlim0sDhKYRgk2sqYxflLBydyMAYPbowpDrrRYBvz9zPADghdUHsLuhPebnirkVfLAy4ncbW/nu+gx482rA7wHGnQX8cgtw01rA6gQOfgsc+MrwNiiGM5OlvVbBqigjoiQmdMUeS4oGUNM00aZYG0FVu4wH8QFNz3pYGWlKcOt9Ir2pauzEdS98hz/9bws+3lynfH97E7PdnFMNCkbiJFpL+HiCkZCVuzZNk+KlhZtqWtDSxUy3U8rzdG9z0qhCnDquGH5RwiOf7Yz5uRKVpgkwsIZ7fw/vAN64CpBEYMolwEXPA45MYOBIYOqP2G1WPmp4G2JtBx+gjEh+5fuViBTJwSZmXi0vMJ6iAYCiBKZp1Lk0xoO03ijtLZb3906PH21pkColeh5JkvCbNzbg4y11eGblflz34nf40b+/7vXtSOeyXoCCkbiJ7hnh3VdjSNMEKyOaYCTV0zQrdh0GAMwaORC2CJLhLaePAQAs3lIfsym3Xammid0gDASV9uqdaDqPAi9fDLhbgSEzgbP/Clg0zznrJkCwALs+Beo2G9qGWA2sFsECq/zcfsmPsnwWONRGGdpohKrGGJURpfFZ/KpBPEPy9P5PFFlOm5IqrUvAe02kP+9tOISv9x2F02bBJdOHAAA2VDcrfsHewuyxJNWgYCROijWNz/SItfsqEHpA9YretJmNsXzXEQDA7NFFEW83sSwP40pz4PGL+GBTbUzP1ZGgNI226VnI+ytJwHs3AU37gPwhwMUvAragpm0DRwITzmN/r/yroW0w22ckoAOrrIyIkohB8pyk2uYuQ48TCd7wrGKAuWBkYJbBahpPJ1C7MaK3xuxnGryv9JQyAgCD8ljgd4iCkX5PW7cX93ywDQBw48mjcO/5kzBCnuW0/mBzr25LOg/JAygYiRs+LK+hrVu3x0OsQ/IAfYNlOigjHW4f1lY1AQDmjAr1iwTz/WmDAQBvrzsY8/MBQLbJ4VB6npHccI3l1vwH2P4+YLGz1ExWmNc1cxH7veNDwB89laYaWA2edCHPpoElwMA6SFZGaprjP0EqwYhpz4iBNE1zFfDkXODJOcC+L8PerL3bXPfV4OCjp5QRABiUz8v54w/8iPTm8aV70NDmxtCBmbhm7ggAwNQh+QCAdVXNvbot6dzwDKBgJG6KZNOe1y/plqjyPiOxKCPBaRqf6FMe52gKG+i+2XcUXr+E8gEZGGqgnfi5UwdDEIBv9zcplRxmiNnAqtOBtSDLAUFgjeUa+edZvxX4+Lfs7/l/BMqmhX/QsmmAMxfwtAMNW6JuQ2eMU3utlkAD62D5BFkb5wnS5xdxSA5oYk7ThKumqdsM/Ps0oFGunmoK32OGN/WLZS4N/z9RDeCCUVQoUkb6PVzN/c2CsYoiMW3IAADAOnlB1lukc8MzgIKRuHHYLBgod1bVS9XwNI3ZuTSAfmlvSa6x4XzJZMVulqKZM7rQUG+V0jwXZo0cCAB4Z12N6edLpIHVbrUo6Yb61m6mbrxzPeB3A6NOA068IfKDWqxA+fHs76roJrZY0xECAg2sPHUQ7wmytqUbflGCw2ZRzJpG4dU07W5faKv/5irgubOB9jr1Mm/4wIkrI0b7jOilZXoqVVOaK7/XCVChALDv2J4vgM/+BLz8Q6D628Q8rhEkCaj+Bti/EuihrrV9lUPNXTjQ2AmLAMwbo6ajp1XkAwDWVzf36tgOs5V5qQYFIwlA8Y3o9BrhrbELsmOoptFpesYNs3UpHIxslHOl04cXGL7P96eVAwDeXldjekUbazv4kA6sIgscecB3uM0NrP4nULsecOUB5/4DsBjYZSpOZL+rV0e8mc8vwi2PCjDanZcHI9qmZ6IkokwORo52eAKaH5mFl/WWD8iAxWKuSV+uywaHbFYOSNV4u4FXL2M9WQZNAcafLV8eXgUzG2DqpWV6KlXD0zS1idgH/V7gpQuAF74PrHgY2PkR8L9fmOpVEzNb3wWemgf85zTg2e8Bf5sKfPUPQOw5v01fYtUe1rpg0uA85LjUNPzY0hy47Ba0dfuw90jsLQvMYraBYqpBwUgC4Cev+qBVqdvnVw5YZs2AgI4y4vcq7ef5pOBUQ5Ik7KhrAwCMLck1fL8zjimF1SJg75GOsGbgcMTaDl5PGQHUCqmO2l3Akj+zK0+/B8gpNfbAQ2aw31GUER5EASY8I5pgRKuM5Gaos2HiSdUoA/Ji+L4KgoCBim9Ek6r58NcsoMsoYMbfnDJ2eQRlhM8GynUZ81oFf5ZAzykjPE2TEM/IR/8P2LsEsGeyUnFHNkvv7fwk/seOxLf/AV67HKjdANgyAGce0HwA+PR3wO7Pe/a5+wir9rJg5ERZ1eXYrRZMHpwPAFjbi74RtbQ3PU/r6bnVKQaXyGuCKhmqj3ZBktiqtzAGZUSvtJd3fPX4xIS0/k409a1utHb7YLUIGFGUZfh+2U4bRhdnAwA2mHSh8w6sptM0Op4RgAeXEiZtuAvwdQHD5wLTLjX+wIOPBwQr0HqQza6Jst0Oq0WZORSNcMqIIAgJKe+tUqb1musxwinK0ahKAOtUu+4FVvJ8wdOsEskuP3aEYIT38DBqYO1VZSRRnpFv/sWM0RCAH/wH+P4TwPE/Ydctf6jn1JFD64GPb2N/T/8Za9r3q+2qoqdNpaUiPg+w9H7gme8BB9ckbTO4MjJzxMCQ66bJJtb11c3qhaIop8RWsCDQ05HQ7VFLe0kZ6bdwk+aBxkDZueoo+7INGZhlei4NELqy84k+OG1WpTInXAv6ZLKjnqkiwwZmmi4xmyw3R9t0sMXU/RJW2isHI8U5Lsy3rMXQ5tWsq+pZjwJmPj9nNlA6if1dFT5V0xGDohMQjGj6jADqSfJQHOW9vOFZLMoIoA6OrG3pAjqOAB/+hl0x91Zg5Mnsb7v82BHSNLzpHK9uikavekbkxUdbty/2wYR7lzFVBABOvQMY9z3298xFciffb4ADKxOwtUF0NQOvX8G6B489E1h4P5A1kDXuy2c9MtDdmvjnTRQ1a1k11tI/s/fn2bOA7R/0+mZUH+1ETXMXbBYBJwwLTUdPC66oObQeeHqBnBI7k72GRyYCa55JWFqMSnsJDJWrDqqCKkF4cDLUZFUCR68DK6CmEZprdgK7PwO2f8h20hRI2+ySg5GxpTmm7zu5PB+AeWXEbIMsjl5pLwAMyrLg97YX2YUzF7H+IWYZIq8yIwUjMaxkwikjABTfyKE4jJVc3SuPMRjhg/VqmrpYINLZCJQcA8z5lXojA8oIbzpnNE3D3wObRX0vxR4yZGY7bYpiE1Oq5uheFhBIfmDSRcDsX6rX5ZQC037M/l7xaPwbq0WS2Oykpv0s8DjvscAg2yWnVbvNLQZ6jf0rmRpyeBuQWQgMPYkpl6/8GNj0Rq9uCldFJpfn6S6CeEXNjrpWuFf/G3iqkgWY9iygcAyQMQDoagLevxn496kJUXioAyuBIQOjBCMGylv14Gkap1UuH9YEI5dbP8H0/50GvPgD4JVLgH+dDDyzkAUnSTSgcb/I6OJYghFZGalpCfXDhAm0fH4R3V7ZBGrWwKpTrQQAx9W9gmGWejQKBcCcW0w9pkKF7BuJYGKNpQpIgtz0DIGeEQCaNE3sykiNrIyYmdarZbC8DQOrPwW2vMXSVef+A7Bp0pQ8GIkgU/PZS7w9fzT4e2C32EMu6wliTtV0NbGKma4mYPBxwDl/C1XdZt7Ifu/5gikZiWL146xXjtUBXPgcOyFqccljG9wpqIzUfMe6H/u6gJGnAou+AS5/D5h2GQAJ+PxPvXrc436RmSNDUzQAO0YX5ThRJB2F7bM/sG2ceD5w0xrgxm+BX+8CzriPtQE4tI4FJO8sAja/xVSUGF4LdWAlMHQg80Yc7fAEzKs40MjTNDEGI/LB1GVjBz6v6AVEEVd3/At32Z+DBSJQOBYoO5YdYKpWseDkgVHAGz8FDn4Xz8uKiZ1xKCNjS3PgsFrQ3OlF9VHNCfXQeuDRScDn/xdynw5N5Ui8Bla33w20H8aIbY8DAP5u+THgNP86AKjKSP0WwN2me5NY0jQ8QLVYNMqIrADwKo9YO4N6fKKS+iuTH8ssg/MzUIgWXFz3ILvgpF+E9mVR0jT6QZPPLyqfq2llRLAFdKbtKXiqxlR5b3cL8ML5wJEdQM4g4Icvq4GZloEj2X4t+Zm5NRFUfwss/gP7e8GfgcHHht7GmaLKyAH5uOZpA4bNAX74EkstWW3Awr+woKq5ijUa7CVW82BkRPimjkMKMnGb/b+w+jrZ4uSCp4Fc2bxttQMnXg/cuAaYIs+0Wv8im3v11DzgidnsuGcCHoy4KBjpv2Q7bUqvEa1v5ICslAwbaNzIqYWfLF1WORjxe4Fl92NO42sAgE9KfwYs+hq4dgnwiw3AjOuZK77rKLD5DeA/84HP/gj44h9cZgRRlLCznpWyjSkxfxJ32qwYN4jdb2NNM7uwrR545UdAS7Vubpif0B1Wi6lx90AYz8iXD8DqbcdGcThe6JwBnz/GE1puGauMkESg47DuTbiB1Yyio9uBlSsjygkyNmWkrqUbksR65xRmmesxwinLc+E++1PIk1qBkklA5W2hN4qSpmnrVj8Xsx1YLZbQ96UnKDOrjHS3shPqobWsqujSNyNXZ40+jf3etTjOLQWbqfT6lYDoAyZ+Hzjhav3bKWmaFFJG1r3E+tN0NQHlJwCX/DcwgHNkAsddyf5e/USvbNLRDo/yuXNviB5znLvxfetKSBCYN0fPd5ZTAnz/ceAnn7KgpHw64MgBGrYC/zoF+PIBw+n3Tt70jNI0/ZvgVI1flHBQXt2b7WTJ4QfTDBvb+bzN+4HlbMX5/7zX4PWMC9UveG4ZsPA+4Na9wFUfAcdcwE6EKx4BnjunVyTMmuYudHn9cFgtGBajGsRTNRsPtrAg6tVLgVa5EZqOrB+LusAJCUa6m4A1TwMA/uL/EfySRe3CGguyogWv/glLGfAXo2ckWAFQlJHmLjXN5fcByx5gDbWiwP0ig/PN9xjhjKh+E/Ot6+CWbPCe+0To/B4gqoGV+0WyHNaIQxa1cHXIKlhDvDQ9AR8DUddqIPBrrgaePgM4+C3gygcufxcomRj5PqNPZ793LY6vGZkoAm//jFV2FYwEztZJC3F4mqY3lBFRBHZ8DLx5DXD/MODxk4Cl97ERAQ3bgB0fsePWuzcAohcYfw573/SUyhOuZunAAyvYzKMeZs9htuAanJ8RcSFx0VEWHH1XcFbkrs0Aawfw/ceBqxcDv1jPZlxJfuCLu4GvnzS0Xd3UDp4AVJMqV0bqWrvh8YuwW9WSS7NwSV5J02x6HRB9aChfgFf9lfqNz6w2YOgs4IL/ABe/xKTX6tXA2udj2gYzcL/IiKIswyeRYHh9/sbqJuB/NzPTFzclekLTHbG2ggd0SnuP7GAHvpGnYnfWcQDCT2M2BF/B+fRPWJ3ytmcmqJqGKyMdHj/r09HVBLz0A2DJ3ayhVnNVxMfWBiMx0bgH2UvvAAA84LsYtc4R+rdzRE7TmK2kAQKnGWtn9vQUhj0jVV+zFW7DFiCrmJ1QB02O/gRDZjJlraMBqNsQ+4aufJRNkba5gIueU9UPPZzcM9LDwQgPkP57MbDpNfY9rd8MLL2XqSD/PBH47w+BfctYSfi8/8c8Lo4wCnNeOTDhXPa3wRN3POxpYMHISLkVgS61G1HWvgVuyYYXMi8z9wRZheyzmv9H9v8ntwM7P416t04v228oGOnPSBLG5LLVHC/n5X6R8gGZsMa4yuQHWMXA2l4PZA5EY+W9AITozcHGnwWcLM9U+eLuHl/x7IjDL8KZXMEOiMce+i+w4WW24jnrUXalrjLC3iOzlTRA6MnK3d7A/pj/R7WRnckGbAFwVSBMmiwmA2uYqb3we5HRug/TMhowTdgF72d3A0/MBfYuVe/cFrl/hGJejSUY8fuAt6+D4O3AOusx+I9/YUjfHQWDyohRvwgQGIxwZaRH0jSSBBzZjaEO9l0P6xnxdAKf/A545gwWUJQcA1zzBVA21djz2BzAiEr2d6ypmupv2H4PAN97QC03D4eijPRgmkaSWGO1Ta+xRcaM64ArPwTOe5yVGg8czTwgmYXArJtY+vnk30bvfHzi9ez3ptdZWqoH4crIyEh9lNa/BABYLB6Hra2x+a9w0s3MoCuJzEvSuCfizeNpB9+TKqJR0rM7SirRVge8eTVu2L8cX1v+Hw40Mnd1VZyVNIDGMwIWzHgFAfjeAygsKQewHUfa3fD6RdgjqRAnXM1SD0d2Asv+Aiy4J+btiQY3r8biF+GMKsrG6faN+BVeYBcs+DMLqt67kfVG8HkCKjPiUkbk9zfDloEuXxd7f4+5ABg0GcW5awC0xKeM2CJ7I2Ip7eUnWEEQ1HRE9Wpg+VigsxFvA4ATAPcu51UwWb65CuDBVhhqmtl3NqZKmpWPMBXLmYtnB/w/SB2WCMFI5PfFbCUNoBkgKFh7xsDq8wCr/g5seAU4shMzBAuetB+L/7WcCrSPA7KLmVH58A5gy9us1JQ3D5t8MXDmQ+bN0KNPZ9Uvuz4F5t1q7r7uNuCta+Xy4QvlqpMo9EZp71d/YyMWAODcfwJTLpavOAmY+qPYH7f8BBZs1W1in9HMKDOk4mA3V0aKwigjPg+wkfn63vDPxcEmljY13WtKEIAzH2ZBSNVXwOI7mHk3DLyqMJZqmnPeOQc17TV4ZsEzmFo81fT9EwEpI/GwbznwxBxg/3IAwGRhj5Km4ebVWHuMABrPSBOT1715g4GJ52NglgM2i8AWaZHGtQPMtb1Abmn+9ZPA4Z0xb0804jGvcmxb38Jj1gdhFSQcGPoDYMbPWG0+xxuojsTa8AzQvL9yOahHEJgkDChD4hraekMZMX7w4MqIVbDCIpd9+hu2sX4e9ky0W3JwWMpFVcmpbLV5/VdsVQ6wFXoEeH8S02nFxj2sIyYAfO8BOAuHyo8XYzCSisrIF/8HfH4XC+otdgiSiAXWNfgH7gceHA3cUwbcW85KNFf9gwUiuYOBH70GnP9UbFVZo+az3wfXAO36JuiwfHw7m4qcVwF870FjTft4NY27tWd6Fm3/EFh8J/v79Hs0gUgCEATguKvY32ue7tGeS3sOs2PQqHBpml2fAF1HIWWXYrk4GV1ev+5Ed0PYHMBZjzCFePv7rHtrGDplQ3wsyoinuwU+0QebFJuKnwgoGImVTW+w4VYdDSyvCaBAaENtSxc8PlFT1htbJQ2g8YzILcW9Q2cBggCLRVBOlnVG3PyjTwNGL2B+iA9u6ZEdVRQlRb4cHSmXGv4BWAvsN38KO3z42H8CXiu+mR1kbA5WugwA7sDBU2orePM7IO8rkikbTN2uXKBoDAC1sVxc05GjeEa4MhJLNY0gSbBufotdllnATnq3VeMvUz7GCe4n8OqIP7OVpisXyJInikY5ocXsGfnsTvbdGjUfmHyxEsyED0Z4mqZD97sYi2ekR5WRwzvU1fyCPzOT+A1f47/SAuwRB7FqCR4kZxQw/8LFLwE/XweMWRD78+YNZoMFIQE7THQZ3bWYteCHwFrMZ+Qbux9P00gi4EnwgLeGbcBb1wCQmFo768bEPj4ATL6I+Wwad0U8acdDt9eP6ia20AyrjKx/GQAgTLkYhbnsu847G8dE8Ti1YuiT34Y1NMfTgdXd3QwAcFT1QNdfg1AwEgurHwfe/Ck7AE88X/FlFFnbIUrsoB5v91VANVi65C+fN0ttsFOSpw7MM8T3/sLSBvuXMxkzHKLIVjAf/Ao4us/wtja0ueHxibBaBPMyf+Me4Lmz2MoTwLahP8YN3l9gc70mEODmtSDfiJKmiWEeA0/TZHazA69HY+5TPSPxpGmMKSNmtp0HqNZtH8AiB6n+oSexk57VplRu7TuieZ+yi+UnDK+MiKKk6b5q4vM7sArY9j8WkJ9+NyAISjATNU0jiSz1FoSqjMTwvrQchLWriV2WCGVEkoCPbmVlsWMWso68rlygeBxeKLgJp3oewuffX8uacN1WBfy/fcBFz7PUol4lkVm4MXPLO8Zu73Oz7QWAE28Ahs02/lz2DNUsnkjfiLcL+O8lLMAZNoc1++oJnDnApAvY39890yNPse9IByQJyMuw688b6zjC0moAMOVHSifjsPuCUU7+LVOuajewZoJBiKIUe5rmyG545cDdMWxOfNsZBxSMmGXDK+qQqRnXsQFXeRUAgEF21byaCM+IoozIi0e+kgeAkhwejBg8WQ4YpuadP/1dqH9AkoANrwL/OJ51dP323+zHILykuSzfFdnDoqW7lRnsHj+JzZmwZwFnPYLOU+6BCAu212kOiA5Z5g4KRo7K02EHZMUwiFA+WWXKq3MP1FV6ca7JYE8PpbRX/0AUi99F6cC69W3wQ45oUw1yPEW2vU5TeZRdIj9h+GDkSAcLJi2CWrYaFVFk3yUAOPZyoHg8ABgIRjT7hI6JlXtGckykaRRlxNcNqxzgJEQZ2fYeMwFbncAZfw64akIZC143NviAorGqspBIJpzHfu/70pgxc/U/Wbv57BL9Hi+REISe6cL6zb9Yyih3MKuKsRr/XE3DUzVb32M9ihKM1ryq6wHZ/j4LXAdNAYrHKYH9wabwc5gMkVWo+n6qQ6eBd/vUwNt0Nc2OD+CWX4szI3wTt56GghEzHFoP/O8X7O+TbmYRvsUCZDLFosjCvqjPfrUfbfKJpiJGZUSUROXE48ofBkBueiZTmmcyGAGYO71oPPMXPDaDjRFv2M4OdM+dDbx9LXBU49juOGL4oasUj4zBtNSuxcDfprGmPnwy7g1fAcf/BOPkapz6Vreaa1WUkUD5mHtmYpmK7JNTPpmy8uQR1VU6D/Ya4hlGyIOEMMoIz/GaKe1VDKySCEvRuIDLACjv3f4jHeiWZVs1TRM+GOF+kZJcE8Hkjg9Ym25HNlD5W+VirowF9DvRYrWrK3CdQK21m6dpzBt7LRL70V4WF8sfZr9P+jlQEFiqPFEORrYe6sHqk4EjWfM4yc9OdJFoPcR6ygDA/D9FLuMNR6K7sHa3srJyADj5d6xzak9SNpU1DhO9zLuTYLh5NaxfZNv/2G9Z0VKDkTiVEUB973T2mU5NJ2qXyeaP0vYP4JErPh1W88fRREHBiFE6jrAGXL5u5nI/9U7VFJbJpjbmga1Gl+5gufnzpw2OeYKi36NG0i65YY5WGSmW0wi6vUbCYbUDFz7DApKuo8w/8s8ZLBDZv5ylcU69A1hwL7u9nEc0QpXskTEUfO1dxoZbdR4BBo4CLn6RzZkYMAwAUwq4orStVj7Qhw1GWABRmG1eEvc3bGXP52AHFo8mZcDTNEfaPfDG2oXVzoORMJ6RGMqSJa4ASBKs5dMBBCoARTlO5GfaIUrqgdNImiamst6v/s5+z/gZ6yQpwwPlbq8Y3rjHTcl6wQivpjGjjMgreSsAqxzEx62M1G0CatcDFjvrbhzEhEE8GOnhvhwT5VTN1ncj327xncy7Uj6dVfDEQqK7sK56jPURKRwT+zaZZe6v2e9v/wN0NCb0obl5Vdcv0tXMjm0Aa9IGdeBkQoKRCNV5Sit4u8Vcw8L2w/BWf6P8S8FIquP3sXbKLdWsi+H5/wqse89k0laWrxmQD4Q/P2UUHrhwSuxPue095W9X0QQAgcFIaW4MygjApPTrVrCZDjllrKY/fwhrE73oazZdNa+c3VbOvRuBKyNRu80eXMPyx343MO4s4IbVwPizQ9z+40vZQTE0GAlM03BlZGAMwYi3YQsAIKNgFHtoTTAyINMBu5Vt0+FYK2qiKCPcM2ImxyvKao5gy4BF7uKpVQAEQcBYOVXDm9AhSw5GIhhYeVmv4Uqa6m+YXGx1ANN/FnCV02ZFkWywDjtBWKmo0UnTcM+ImaZnB5jxzgKNMhJv07O1cnn5uO/pruh5muZQSzea4unUG40J32e/9y4Nn6qpWs16d0Bg/rBofTnCkcgurB2Nqjpx8u9YQ8beYPTpLE3i7QBWP5bQh46ojOz6lCkyReOAwtEAkLg0DaAxxIfuU1wFNdMmAACw82O4NYde3tMqGVAwYoTFdzDlwJHNhlsFu9PlNI1NdOOaGaV49qoTcMvpY2NudgYA/nUvKH+75C+hXjBiqJomGKuNrWZ/tQ34f/uBmzcBFz4LDGAlmcrrS3Qw4u0CXrucHSRGVLLBUWHyx3xGzbZa+YTKSyPDKiMmI/pD6+HrZGmoTDnY80t+xdTKKpZ4y+8YUzVRPCOxND0Tu9jJyFJ+PKzy9yJYAeCpGt6EDtlymsbTFnZbTE/r5arIpIsCVBGO6hsJcxCOUN6rVNOYKe2VqyesWUWKMuIP01TNEN5uYOOr7O9pl+veJMdlVxS8LT2ZqikcBRRPZF4EPfO56Ac+lNWAYy+P3no8Ekp5bwKCkQ3/Zftr6SRFKegVBAGYK/vjvn5KP4BrrgYOfGXqYUVRwl7FM6ITjPAF5PizlYv4fsB7jcRFhAC+M9aGZzs+ZC0N+FNYetDPEwUKRqKx8TU1uj7vcVZmFYwjixncAPzu5GJUji2O7zmP7IavepXyrzKbRhOMlGlMgqKY4FJdPlrcxPjyKnkOT0TD7rf/ZnNmcstZ6WOEaoPxg6IrI35RwtEOpjoUmVVG1r0Avm7O0ASXWnWET66NWWJVlJHQYEYUJfNNz0QRorxitQybrZSwBre1HyurSoqJ1ZmrfD/D+UZqZAXDUJrm6F7VvxCmRFMNRsIpI+G7sKrKiMH3paUGYsM2AIAltwwW2Y/i1/qfzLLjA5amzC0HRp4c9mbcN7Klp1M10+XhdsvuC/VyffcsSym58liaNR5c+ex3ItI0/OQ87fLYlZpYGfs91l/H08YqH3nQK0lM8XpsOvDMQuaZM0hNcxfcPhEOqyW04szTCez6jP2tCUb4cbrT40dTpxdxoQQjofsUL+s1ZV71dAJ7lijBiMPiMN+YLYFQMBKJ2g3Aezexv+f8GpgQJroXBEUdQWcCcpRb3oYf6peCS2fawW7lAzJgtwro9oo41JKAfKQWJRhpMtSTpNPjU9IlYT0j3a2qGbDyNsAZuRcJT9Psbmhnng0ejGj6jDR1esDjsAIz1TR+H7D5TfjkHS/Tpm6zNhgZXsiec9/h0Db0hrCHD0b4wQMwoYxUrYIoB6SWwcepHViD+g6MLWXv7U4ejAiCxjein6pReowYUUa++Tcryx01X6mgCWZwNHmaH1g9OsGIWc/I9vfh51VGtgxY5UBHPLzD2P314CmaqT8CLOEP8IpvpLYHlREAOPYKpjB0t7AGbJz9K1jbeUA2iMZZDZGoLqyttWrVx/iz4nusWLBYWPdSeyaw5ws262bN08BLF7JuzjwIlsvjjcDL5YcOzAydvbXnc+YNyx8ClKqzh1x2q9ITKu5UjS28MhJTK/iqrwBfF9w5gwAkN0UDUDASno5G4BXZsDrqNHXGSzh4TjkRhqmt78AvxyJWwaqYirTVNDarBUPlhmp7Yz1ZhoOvjkRv2PkhWniKJi/Djrxwef5V/2Cm2cIxwJRLoj5m+YAMZDtt8PhF9vp0DKyNvKw3025uMN/Bb4GuJvhlZcZldSkqg7aiZnghO6nvOxJjA6gIU3t5isYiMNOZIba9Bx52WG2usM29eHlvXWs3WvhqjAcj7aHljpIk4aD8GZZHU0b8Pjb/Awg/ih5qILcn3HczjOTs84uKYmTYM7LrU4hyYGmz2GCRzbHikV3G7h9Ma60602fajyPedGIZ81j0aJoGYAHRQrlS5rvn2ODLLe8AL13EToKjTgOO/2n8z6PtwhoPXDkrn84miieDITOAH7/BzNJ7lwLv/xLYvZh1M+XeGBPN3SL24dn5Cfs97qwQ/1vCKmoMLG5MBSOy2dZTcQJ7+J4suTYABSN6eLuB168AWqpYOd8P/h1xdQQgccrIkd1A/Wb4ZanZKliVPF7wyHs+qInXvicMRxarIAAM+UZ4T5WwfpGuJuaqBwwb2SwWQRm4t622VbfPiFrWazKi3/kxAMCbUwqAncD4qsDtV82mijJyJMZgL0KaRum+6rAZl0Z3fwZRVswECGHbnue47EqaROnVophYQ9M0jR0etLl9EAQD1VD7lrGqnIwCtV25DtzgxyechqCkaQIP0Lz3CnsdBhQjTyewf4WScrMIFljl6ih/Y4zByJa3AUhAxQylwiscPE2z93C7sjrtMYbOZHNmIDHF9vUrZP/VyawiLREG0UQZWHnljyZlkRSGnQRc+iZQOJY1XKu8HbhuOZtlA+gO3wxHWF+VJDH1BQBGnRpyP75P7W+Mc9EYIbWpeEbMpGn2ycGIPLyRlJFUw+dhO3kkw6oeiQpGtrGd2FcxAwBgtajBiNYzAgAjZBNVwpURQQhM1URBMa+G84tsfpOtQIrGqx0lDTB+kDYYCfWMxB6MsFWMT24GFvAea9SnEXKwt/dIR2zmswjud9MzdZoOAI27FQUgZGpvEGPDmVh10jT75WCrLC8jeik6V0WOOT9i86pR8nezprlLea0BhDGwcvNqpsNqrN/J/hWArxuivP9ZBSssstlZ7GiITanc/Ab7fcwPot60ONeFwmwnRAnYVtfD6gjApu9Ov5YpDtmlbLDjD19WV83xkojS3o4jrIkhED613ZsMnQnc+A1w5fssRVwyMWx1XiTUcQlBx7nDO5gXzuYChp4Ucj++L+wOF5gbJYLSaloZ6TwK1G4EAHhK2eyqZJb1AhSMBNJSw0Y17/yYffCXvBI2Jx6CEowYbxSmi7yi8MurTptgCx+MFPKTZYKVEUBTUdMc9abV0Spp1v+X/Z52qbGBXTITBmkkcJ2DBy+5LcwxEYw0HQAObwMEK/xyfxitMqJN0wwpyIQgAG3dvtgGXUVSRnhZr9GGZ3s+BwCIcmop2kA4JRgJKe8NVUa48sOVoLB4OtWmTpMuinjTAVkODJR9PLrKHf88g1Z5pofkya23/XKZs0WwwCofVP0AcGidscfhHN3LGrkJFlbubgBe4rulpodNrABbJHzvAeDqxcCvdwAX/AdwxN7lOYREKCPbP2CeotLJUZWlpCGrZ8GDNyMRVhmR900MnaUG2RpGlyQoGIlQgdatmOENHk/2LwcgAUXj4HayfZGCkWSy7AHg7evZzwvnA48ew3KdVgcb1TzcRJ9+uddIXMrI0X3MNCtY4R8+F4C8arf2sjICxKaM6AUjh3cCNWtYnnZy5BNYMMcMVisVJCUYUducN8oBwkAz5lU+N2LIifDJDn+bYFN2RG2axmW3oiyPHQBiStVE8owoA/4MKiOyDCzKB6Roysi44GAkQuMzw8HIjg+ZwpU/FKiYHnWTRxZHOAiHVUZMVNJIkiYYYYsGq2CFVU6pioLAhqaZYfOb7Pfwuep7FoVjh+QDAFbuTmyDraSQCM8I90/0ZjmvWeJSRoICjt1yMDIyNEUDAKNlD9fuhvb4Kh8jDN7kaRqX0WCEN2cbPk8x7TstlKZJHrs+BTa8zH72fM6i+aGzgUvfipgP10VeZccVjPBSuGGz4XOxA7lVsMImsAOzNoUAqJ6R2pZufSk8HkwEIwciBSMb2ARLjD7N8MGdM6YkB1aLgKZOL4765B1Fm6aRlZEiM8qI7BfBmAVKUyybRQ1GPEGD27SpGtNEUEba3SZWMn4fsPdLAEHKiCW8MsKrPLYcamXVSBFawvNc9rBowQhP0Uy+yJDCNdpQMBKHMtK4G2g+AFgd8A9kjeu0QZqf38YMm+Rg5JgLDN/lZLmUf8XuI/D4EjQpOFnEm6YR/cABeWJuhJLopGMyGPH5RaXfUICB1dulpqR0/CIAG5Zqtwro9PjjG5jH9xnRBwSdC3iaJtNomkb2i2DEPEUNJmUkmUy/BjjtLvaz4F5g0bfAVR+YU0Q4SprGwDCrcOxazH6PO0udQhpBGcnPVKXwmE2W4VD6DTRHvJkoSjgo9xgJCUZEPxu+BxiqoAnZBLtVOaHtbZFXFLqeEYM7kacD2Lec/T3mDMUQbBWscFj0g5G4TKwR3O+dZhqe1axhTagyBkCUjc3aNI2eMjKyKBu5Lhu6vH5sr23TVNPoKSMsIBheGEHud7epJj0DXgpANbHqByP6Blal4ZmRShqucg09SXlfrBar+r4IAMxU1NRvZSk8q8OU8XLS4DwUZjvR7vbh2/1x7P+pQLxpmrpN7L6OHGDQ1IRtVsIJM14iHHWt3fCLEhxWS2BPowMr2f6dU8Y6r+pgs1owojABqRpbUBCkoUtWWg0ZWFtqWJAuWIChJylqMAUjyWTyRcBJv2A/M28AisbE/li8vt/EcLkAuluBKrnR2ej5ymo3kmcEUFfuCa+oMaiM1Ld1w+MXYbMIGBQ87XXfl0DbIRbYjF0Y02bw0sldTaHBCE/TGDawVq1ibejzhgCFY5T3M8AzEi4YiSUVFlEZMWFg5TLwiErFSBugAOgoIxaLgGOHss/wuwNH1cm9QQZWSZIUAysvZdZlzxLA7wEGDA970A0mcjASWRkxVEnDpeZR6v6ifV98EIBGE43PeAXIyFOMmdZlLBYBlWOZ8rRke/j5P2mBUw5GvB1MkTPLfjnYHzqr99q/xwL3jBhURrhfZFC+K3D2y25eRXNKRLVwlOwb2dXQFvY2UbE5Ad5/KjgY8fLZNAaCkX1MZUXZNCAjX1HcKRjpK8RbTbNvGZPfCkYCBSPUVXuEahpAbUuccN+IwWCkWlZFyvIzQnt98JTIhHMidluNBPeNbGuUT7hudWfmaRrDc2m4KjJ8LiAIasBnsSnqk1sMnCMTlzISwTPSaab76t4l7PfIUwNOuuGannGOGyIHI1XNaprG3RqwPfWtbnR5/bBaBP3+CRz+WY5daNiEzIORA0c7Q9MXYcoUDTc8E/1sHgsADJutqEMB7wsAtB7UbaymCw9GJpxn7PYaThnHlKcvdqR5MKKd9BuLb0TZx2JQl3sT/v0zGoyE84vwE/vIUyLef0wx843srI9j0SgIYX0jnWYMrNXyfiNX/nBlhEp7+wo8GOk6CoQ5OUSEp2hGnwZAXe1q+4wEe0aAOD0NkTBYTcMraSoKdE5kfEU/6rSYN4MrIxsOy8GIfPCQJMn8XBq+ahs2G4Dat0WrjAS/x1xe3d/YYd58ZqCaJjtaNY2nQ60IGT4XEu80isjKCAAcJysjaw80Mfmdr3w0JlZeiVUxICN8Ka3oV02JY86IvL0aSnNdyHba4Bel0B4L4Qys3TxNEyVIq9/CUleOHKB0khKM2ASb+r5wKd5IW/jDO1mKxmIHxhp/jZzZowthswjYe7gDB+LtJ5FMrHb1RG02VeP3qfNehqV4MGLSM6I71bqrCajfzP4eOjvi/UcrykiiKmoCjyndZkp7q+TOuHL7CK4GJ3MuDUDBSOLIkA2skhjVZxGCJAG75bkG8olba67UekaC+13wk2XY5lKxYlAZ4V0Fy4Nr75urWCWDYGVKRIzwXiP7W+XVuOgFfB60dvvg8bMTkKE0TXcrcGg9+1sORrSpMO4Z0VbTAGw+jd0qwO0TUWt2YF4EzwivpomqjBxcwxSz3MFA/pBAZcQS3jMCAFMq8mER2KqutrVbd3rvfsUvEsG8WvMdK1l35jH53SCCIISvqIlXGeGmwSEnAharvmLEe6sYMbHK/X0wYp763TdBrsuO44ex+32R9qmaGCtqajewajdXHmtdn8qYTdPojUuoWg1AAgaO0h0WqUUxc9e3xTcwL0xL+HalVUCU40lXMwu6ATUYkQ2spIz0FWwONd9qNlXTsE1tmjOMSWd8+JlWGZEghayCuTKy70gMK/dIGA5G5DbiIbX3cmqh/HhT+fdgclx2DC/MQic0O4qnHY2yeTXHaTOWJ61aDUh+1vcgvwIAAlJh4appbFaLYsw17Rvhyojfw9QFDR1yNU1UAytPRQyZCQhCQDoimjKS5bQpAwfXHmhWG59pWsIbqqTZ8RH7PerUiI3O9Ajb8CmcgVUZkmcwGJGDI/6+WC1W9X3JMhGMbJUr2Uw05QuGp2o+2xbacj+tiNXEul9OWQydHb1jdbIxq4zopWmU72Boo7NghhVmwWYR0OHx41Ask9Y5YRoptsjG77DjODgHv2W/C0YoxwMysPZFYi3v3S2naIbNUb5sAdU0Gvks2DdSIZeNdXn95lfukTBYTaMoI8FpGt4IKEou1QgTynLhgw0+Qd5ZPO1Kimag6RSNKh9r0zThghEgjhk1No2h1xeouLQbbXpWJcveQ04EgAADa6RqGs5xiom1STWxaoIR7jWKqIxo/SIm4b6REHk6SgfWiMqIJKnpAPlEwPeXgPeFp06PRAlGju4F6jYyFW/smZFvG4EzJrKBY6v2NKI+kftibxNreW+6+EWA2NM02kXXfuPBiN1qUfaxXfVxmFi52hpGUYwajPDhhRUnKhfxYx4FI32JWE2sPEUzWvVW6FXTAKHBiN1qwSjZHLXpYLO5542EooxEfsyDzVwZ0aRpRL86aCxMIyAzHCP7RrosfNJrh/lW8FGCEb0OrBzez8W0+SwgGAk8OXUaaXrm9wHV8kpGVgD490IQhKjKCKAJRqqaAHkWD9rqlOu5MhI2GGmuAhq2sjJAs713oMrTIQfgcGkaRRmJ8L4c2cn2MVsGqwhAoMdKSV/x4ZXRlBFuXB0+Rx14GQNDBmbiuKEDIErA/zYcivlxkk4syojfp57ohkX2T6QESpom+j4tSZI6JI+no91tLC0FKGp2NBLSiVXZb4KVEYPBCFdaNU0LlaZnlKbpQ8RS3uvtVg1FI9QmQcrB1WKFzaIemPVMrFMr8gEA66sT2I6aByPu1rAlfj6/iNpmtlNUaIORmrXsQObKU04W8cAratpEtfGZqWCku0Vz4FAPlDwVpg349JSRiYPZwXmT2XbfVhvAP7ugYERtehbhpFu3kZVYuvLYXB+oyohVsBpSRo6VK2q21LTAmykrI221AAC/KClDDocNDBOMcBNy+XRV+TPBRPmz29UQNEguWgfWSMoIl8crTmDpUUC3tNfPfVyNu5iaEg7e6CyGKppgzps2GADw9rqauB8racTiGanfzE7szjygeGLPbFciMaGMHGn3wO0TIQhAKW9fUP01S/vmDwHyyg095Siloiae8l6ujKj7jc8vKkprxGDE72P+L0DxiwAaZcRCykjfIRZl5OC3rPdFdglQOFq5WEnTCFYIgqAEJHrlvdOUYCR6t1TD8NUREHaFVN/mhk+UYLcKKNZ2QeXNsUZUJqTXwLFDBsBqEdDq58GIyTTNgVXMWFwwAsgbrFysNQmH6zMCsKZWABvY5/ObrJTSOXgAatOzrEhpGmUVcyJgCWz9Hq0dPKd8QAZKc13wiRL2e+TPVFZGapq64PGLcFgtKAsuWeTwdFuY7pLRKM11oTjHCb8oYfMhzfdIKa1UlRFJkpTeMfmZkYKRwBQNoPGMaIO0jHwAAvv+htsnD+8A6jexoDEOvwjnrEmDYLcK2HKoNb6TTjJR0jQmgm/tituSBqcVPs9HNsRHgqsiJTkuOGzya1O+g8ZVoPHyiIZNNXG02uf7jaa0l1egAUBupP489ZuYEunMC+gVlNaekcceewzDhg2Dy+XCjBkz8M0334S97bPPPgtBEAJ+XK4ETZhMNWLxjOyXWycPmx3Qv0ErOwOI2GtkihyMbDrYAn+iTKxWm7pCCmNiPSiX9Q7OzwhsBKS0Gk5MO+gspw2Ty/NUE6u73ZwyotTVB1aCBHRg5Z4RnTTN0IJM5DhtcPtE86V5SnlvoGekw0gH1iC/CADdfhqR0jSCIOCkUUyxW9csb0sbSyGs2ssUvAllubBqPz+O36tpLBZbMCIIgvL93FDdrF6h0/SsudMLt9yPpCQ3wjHigNwccMhMdVP1lBHBAuQxs3LYVM0meULvyFNjUn6CGZDlQKXcHj5t1RElTWPipMkbNmq+qymNXaMERhmWF9kvYry6bJqsUu6oa419fIc9dHHT3MmOWTlOW2ivJy3V8nm64oSAgDFt0zSvvvoqbrnlFtx5551Yu3YtpkyZggULFqChIXw5W25uLmpra5WfAwcOxLXRKUssLeF1vAxAYKUHoAYj/HIto4qzkeWwosPjj6/DXzBKr5EwwQg3r2pTNN5uVo4KJLTXwIkjBqJd0nhGzEzs5dtTHjjcTesZUZqeBZX2AqzDJk83mE7VhGlS1BGt6ZkkqatNzQFPhI4yEqWvzZzRLBhZXic/l6yMLN3BSnz5bJUQDq5hUn1GQVytvXkacZ1eMCJ6lTkbtXKVwcAsR/gKqbY61shMsACDj1Mu5u+BVhnxS35g4Eh2A71gRJKAzXIwMsn4LJpofF9O1by7riaxFW69BTevdxk8jmm/q5oAMaWxOdS+O1FSNTXN6qILAFtYHFrL/jYRjJTmuVCW54IoARti9ffpVKG1KMMljZpXZwRcnLazaR5++GFcc801uOqqqzBhwgQ88cQTyMzMxNNPPx32PoIgoLS0VPkpKYlck5228Mm9OpNRdfF2qaVWQb04zCgjVouAyeX5AID1Vc3mtjkSUSpq1GBEs2Ko+U5NO/ETQQI4ccRAdIKtCrxdbVhb1RT63HqIfuZhAYDyEwKuUjwjUdI0gJqq2XTQZDDCO89qlBFJkqIrI037WOt2q0MJBCRJUpQRAYIhZQQAZo1iQfJXDbzp2WF4PW4s38WUEd7KPARurB55SlylmlN1lRFtAMu+R7Ut7Hdp8FgBLfyzLBoHONX29VqPVYCxVx6gh/qtoY91aB2rpLFlAGO/Z/wFReGUccXIcdpwqKUb36TjrBql6srgcaxpP9BexxrGDT62xzYr4Rj0jRySfXFKKrNuMyvXzxzIUr8mmCYbytfFepzWSfsaNq/y5omaIB5I0zSNx+PBd999h/nzVVe9xWLB/PnzsWrVqrD3a29vx9ChQ1FRUYFzzz0XW7ZsiX2LU5kcVtqnrVaISPU37EudMyjkS60t7QUQdlgeZ6o8xny99oAfL1F6jej2GNH2fzDYNtwIxw8dgC45GFm1/QCOtHswKM+F2XIKIiwN25gM68gBisYGXBVQ2htmUB7nmFhNrLZQo6bbJ8Inr5jDlvbyA0fpJEWa5d1XARakWizRPSMAUJzjwtiSHByVsiEK7Hu0cfsOtLt9GJjlUAKtEOL0i3AmledBEFjwytNrsDmZugFoghF20B+UFyHA5Aa8oJNeQPpK2wyOVzps/1+oiZWnaMYuDAhs4sVlt+J7k9ix4J10TNXwoYpGF1VcFSmbpipe6YDBihoeJJfly4GA8h08zvQxjhvK1x6I0d+no7QaCka6W1jgDYQUFSizadLJwHrkyBH4/f4QZaOkpAR1dfon4LFjx+Lpp5/Gu+++ixdffBGiKGLWrFk4ePBg2Odxu91obW0N+EkLcuVgpNVgWZ82RRP0pdaW9gKI2BIe0FbUNBvf3mhECUaqlWBEs8rlHhgDtfdmyHLa4MpiqZL1e9h35/KZw8K3MOdw5WnwtJDVvXY2TaQ+I0AcJlZFGVGraTo1VSVZ4dI0XAHQHDi0QYcgGFdGAOCkUYWQYEGLjakkm7fvAADMG1sU6PfhdBxRO9bG2Ssm12VXZigp6ogghJT38oN+yMBFLdoTgQatkhigjIxewPwBzVXqewqwkvV1L7C/J18U2wuLwPePZamaDzbVKq2604YIE551STe/CMegMsKD5NLcoGCkzLwKdKy8aFxX3RxbJ1adKjRDPUZ4NWHekBBvVL+ZTTNz5kxcfvnlmDp1KubNm4e33noLRUVFePLJJ8Pe595770VeXp7yU1FR0dObmRi4MtJ1VHc4Wgha82oQ4Twj4ZQRXlGzs74tdnNUMFHm04SkaXwe1STVA70GBgxgO1GG1I0MuxU/mj4k+p1quF8kMEUjSmJABQYPRoIH5XGGDcxCdiwmVp2Oifzzcdkt+sZRQA0EwgQjRqtpOLNHsyCkxs+CqgP72byWynB+kT1LAEhAySS1P0kcTJHTiPom1iBlJD9MMCKKaq4+TDASMkDQkanOmtnylnqHb//F/DBF41jAkmCmDytAWZ4Lbd2+9GsPr53wLBoIpNLNL8IxGYwoaZow30EjTCjLhcNqwdEOD/Y3GhzgqEUnTdPcyc4JESvQlOPJlJCr0jJNU1hYCKvVivr6wHbH9fX1KC01dsCy2+2YNm0adu8O34jo9ttvR0tLi/JTXV1tZjOTR8YA9csi93IIi6dTNVbqdCw04xkBgOJcFwbJ5qiNZn0N4YigjPj8orKTKspI7XomH2YUAIVjQ+4TLyWFLBjJQjcuOK4ceZF2Ps5B/WBEawS2WWzItLHX0OnVP0BYLAImlsVgYuXKiCY45Y29sp1htl8U2XsJhA1GghWAaKus6cMHwmYRcMDLghF/yyFYBGDu6DBpLmVWUvxN6wA1jahrYpUPrHVKmiZMMHJ0L5ObbS6geELAVXqlvYpiNPF89nvL2+y9dbcDq/7JLpvza8OlqOG+G3pYLALOTdeeI5mFAARWDh/NjN95FDjCVLZgY2TKY2Byr8cnKqnF0jwX+/4d2cmujMEf47RZlb5JMaVqIhhYIyojPO2r0/eJn1PSKhhxOBw47rjj8PnnnyuXiaKIzz//HDNnGouK/X4/Nm3ahEGDBoW9jdPpRG5ubsBPWiAIGt9IlGCk+mtWSZBbDgwYHnK1tgeG9rdeNQ1nmnzA/2ZfgkxzEYKRutZu+EUJDqtF7TGipGhm9UivgbJiZrTMErpx1UnDot+hu4X1kQCAwccHXKV9H62CFXnyXKEWd/hAIyYTq87k3qNyL42BWWF2/sbdLI9tzwwI6sKlaYKv0yPbacOxQwegQWKfaYnQhGlDBiA/U2cbRFHtFRND11U9pmqUESVwUg6s7GSgyuFhfAdcHh80JWRGjrYdfIhiNGo+8wy11gAHvwHWPM3Uy4IRwMTvG9r+dQ3rMOu/s/D4hscN3R5Qq2qW7mhAU0fkXhYphdWmVga210e+La/QKBwTV/fapGBgWF59azckCXBYLWx/5Sf1/KFqk0uTcN/Iulj6QukM3zRUTcMXNzpVcWmbprnlllvwr3/9C8899xy2bduG66+/Hh0dHbjqqqsAAJdffjluv/125fZ33XUXPv30U+zduxdr167FpZdeigMHDuDqq69O3KtIJXLL2O9ovhHtOHsdE5R2UB4Q3TMCAHNGs5P10p0JkoUjVNMc1NTeK54DZXx4z7SDdmaypkFzhmZgRJEBw2HNWgASO3DwIXEy/P0F2Hub78wHADS7m8M+3KRyFoxsNFOWFyEYKQgXjHAZuHRyQNO4cMpI8HXh+OPZE1EymAW+47PacdMpo/RvWL+JmRcd2Qlb7Y4blAOnzYLWbp+a5tIoI5IkhRoFg4mQqw9QRixByojdBYyTq2VevghY/Af29+xbDDfl23h4I/ySH+vq1xm6PQCMKcnBhEG58PolvL8xzdrDGzWxpqtfBDCUplEC5DwXBEEI61kyw7FDuYm12fyddcYoRFVGIphXAdUnZzc5BDPRmA5GLr74Yjz44IO44447MHXqVKxfvx4ff/yxYmqtqqpCba2qCjQ1NeGaa67B+PHj8b3vfQ+tra346quvMGHChHBPkd4YVUaiDJUyW00DqP0i1lc3K1Nt4yKCMhLiF/H7dPtiJBR5JVNgM7jKDJOiAdT3F2DvMVdGWt2tYVMexw9jaaLNh1rR1h3+cwhAZyXTKHePLQjXPTaMpMp7jAChyogRE+uEslx8bxY7kZ9c5g/vF+Et4IfPVdqtx4vdasH04ez94yXF2gNrS5cX3d4oDc8inAj0mp4FBGiTZJMq7yo69kxgyg8Nbz9XzCIFq3qcLxtZ31ibZqkaoybWdPWLAAaDkSBTdU3sfhEOnxe1va7VvGKmeEbU40lztGAkgnkV0DQ9s6SZMgIAN954Iw4cOAC3242vv/4aM2aoq6elS5fi2WefVf5/5JFHlNvW1dXhgw8+wLRp8c8rSVmMVNS429XVb5jGYMGeES6hdQU1z9JSmufC+EG5kCTgy12HTW64DsqsndDHqjoaVNZbtxHwtLFWwyXHxP/cehiQVQPglTTlx4dcxdM0/OTFlRGf5EO7V9+gOjg/A0MKMuEXJazZb1Bi1Tl4NHVGSdMo/QCCylc1zc0sUEtYAWPBCADdYXkh8GAkAROXtfAy7JW7eTCiKiO8l0NBuIZnPg/7jgG6uXpFGbGEmdkzej5w0QvAxS8Bt+4DLnk5JNUTiVYPq+iLlMbT49ypg2G1CNhQ3RzfgLTeRmfCcwjeLvXknJbKSPTS3hDzqhKMxN5PpSTXhXGlORAlYNlOk8dpHWWEV9OENbAqi5upulenpYGVMECOgTRN9WpA9LFIdcBQ3Ztoe2AAMJRGAICT5QZWS7YnIBjRppyC1IJ9R4KmvSqzGmbG1SArImbGfktS2EoaQPP+yqXTLpsLLisLHCK9xzNHsLz4qr0GW/7rpGn4/JUBen4Nvw+olU+6EZQRi2CBy+pS0netRoeaRVPu3G1q+/wE+UU4s2Wz7Oq9jfD4xIADa11rlLLeernRlCtft9FU2NJeLRPOAcafFVPb91iVkaIcJyrHsH3yzbXh2xmkHFlyWjOSMnJoHfO9ZZfo+t5SHgPHkzpNmgath9goBcHCfEtxcPI4pjwt2WEypR7BMxJWGVEqaabqXp22HViJKOQaSNNwo2eYFA0QqowMcDFpr8kdeUV+ivwlX7bzcPxzanhg5esOmbez7whbTQwvlFcX2mZnPYVy8DCwwmzax7bZ6mCNw4JQPDmawMmIiXXmSDkY2RN7MHI00pC/w9tZRZIjBygI7GCr7b7K5zwNcBr7Xijw76e7lSl0wez7kgXKBSOAgsSeYMaX5mJglgOdHj/WVTUFVAbURqukidJoSndmj5GyVIPw70SnrzOib0uP849lU13fXluTuNlRPY2RLqxav0gCGxz2GnxYXoRg5JA8JK8sz6WqIsUT1GNRjMR8nI7FMxLBvCpKorIwSzsDKxEFRRmJEIzs05hXwxDsGVFOOt2RTzpTK/KRl2FHS5c3/im+NgeQJeeOW9RVnSRJ2HdYo4yIYkxTLE3jZAZWQ8EI94sMmqKW12oIVp4AVX0yEoxsOdSiHAQiorOSiWhg1UqqQRVJ2hOuss2yybg5TMv+EJw5qjytJ8HvWsx+J1gVAVi5Kx/at2L3kYA0TW1zlO6rUXL1hpSROGjxqN8Js+rIqeOLkeuyoa61G1/tOZKwbepRjKRptFOl0xG+H0QYlFfXypWRjLDdf2Nhmnycbu70ssDcKEFpX49PVJoo6gYjXc2GzKsAKSN9D60yojfAzN2mnnAiDJIL7sDKlZFoJx2b1YK5siyckGZLecyAh1bVgHe4zY0Ojx8WARhSkAk0bGUVN/asuOXLiGhl1WjdC3kwMjjULwKowR5PcwDGUmEluS6MKMyCKBksodbxjDR2sBxt5GAk9MChF4yYVkYANVUTnEoU/cD2D9jfPdAIDFBTNct3HQlY5WmrFnSJUsWgLe3V9YzEiTZANRuMuOxWnD2FLVJeX5MmqRpefabjFwPAjm1VcllvOvpFAENpmkPNGsUuAZU0HO1x2lSqJqg3j3ZBlOPSCUa4eTVf37yqHQxKwUhfI1s2CIrekNQGAKYgSH5gwDAgP3xn2eAOrGZOOqfKEuD7G2tjazmsJVcORlrUYGSv7BepKMiEw2ZRUzRDZhgulYwJfvAQfcw/EIkI5lUgtHQaUNM00U42J5pJ1UTsM6Iji0YIRvhnqauMmDlBhjOxVq1mpZyufGDEPOOPZwI+QXjjwWZ0C/Lr90TxjBhoNKU1sPaEMqL15JgNRgDg4hPYvv7x5rr06DkSTRk5vA1wt7AFSOnk3tuuRBIlGNE2PBuU69B4LxIzDPCUcXzRaMLfFzSbRukx4rLpd3OOkKIBVGVEgKAsfJMFBSOJRpvaaNMxsfLOliMqIz5MsGeEn3SipWkA4PSJJchyWHGgsRPfGq36CEcey3ejVV3RhZhXe2geTQiObADyDhemRT0ApkLUbWJ/65hXgdCmcoAxzwhg0sQaFIz4RUkpxQtRRnweZtQEdIMRbfkqh6s5Rr4XCuFMrFvfZb/HnWmq0sQMg/IyMLKIKUv7W2TlwtsROU1zaD0AiRm+eclpENr3hn+miVJGfKIPbd425X/DZmENkwbnYWJZLjx+MT2MrPwY1nkU0PPI8LRs+XE9uwDpSaJ40OrlFI3DZkFBdzULvmwZQPH4hDz9vDHFEAQ274p7U6LCgxHRB/i9ql8kbCXNevY7innVaXWyPipJhIKRnkAp7w062EsSsOtT9vfo0yM+hHaIG2DcwAoAmQ4bzpzMtuH1NXG20tdRRgKCEUnq8WZnCharejKKZBCu28iUqawiJk/qwPu1aJURoxVLJ8rByLbaVnUKbTiCZNWmTo+SYRoQfABp2MIUn4wBTDkLQk8ZKXAx6dVUMKJnshZFYNt77O8J5xp/rBiYP4Gtutc2sGBB6mqObGA1kKvXNj1LtDLS5mkL+D8WZUQQBPxQnqX0yrfV8SuWPU1mASBYAUhsaGIw+5ax38Pm9upmJZQorQK030mBt2LQ6f4bKwVZDhwv9xx5b4PBpng2TbDu7Yo+JC+KMpIqZb0ABSM9AzexBisjjXuApv2Axc4aSkVAMbAKgWmaNk9bxMZnnAuPZ7LwB5tq4xucp+MZ2SubV0cUZjH5vPMIUwB0VvMJx0iHWyVFc0JYl7+egdVomqYox6m0hv9iW5R8r6KMsJ2ep2jyM+2wBU8c1qZodLZbWf1DRxkx4xnhARpv5Q2w96ytFnDmRlXt4oW3SV9Rxw6g/pZadMmTbXU9IwZy9bqD8hKkjAQrZbEEIwBw7tQyZNit2N3Qju9iHSHfW1ismvLeoFSN6GdVVwAw8uTe3a5EEiVNE9DwLIF+ES0/kCut3vjuoLEA1eaEog57uyJX0kQxrwJqR28KRvoq4ZSR3XKlwtBZamVIGILTNLmOXAjyl9BI46Xjhw7A8MIsdHr8+GhzhAZX0cjlaRqtMqIp692zhF045ETdqpWEEy7Q06J0XtX3iwChyhNgrJqGc5q8uv90a5TZHUowwg5sSvdVk+ZVQO0zYtFU2SjGZjMnyPHnsoC45jtVxuUpmrELe/xzHFeai3GlOTjozwcAeJvZZzkwXMMzA10veeBhE2wJV0a0lTSA+cZnnFyXHWfJiuXL31TFvV09TjgT66H1zMfjzAu74k4LlEF5+gMQlYZnCa6k0XLm5EFw2S3Y3dCO9dohkuEQhADfSLPcQFE3GIliXgVSZy4NQMFIzxDuhMnLJkefFvUhgkt7rRarKX+AIAi44DgWSLwWT6pGUUZYdZDPLyrdV4cXZakD1RLcrTMshpSRyJU0QOTSXiMndh6MrNh9GF2eCCc9u74yUqDX8KwmcjCipGn0lBEzaZrsIjUVs+Y/TIbf+Cr7v4dTNJzvTxuMenlon72rAQJE5fsagMFGU7rt4PWq2WIgUcoIAFwyg6lS72+sjZ7iSzbhTKx75QXI8Dnp6xcBAjuw6qgStbzHSI5V9aAlWBnJcdmx8BgWoL7xnUEvkZL67UZLFzuO6Qcj69nvCAGjMpfG0jMeMTNQMNIT6Ckjnk7V6DkqejCiV+1hxsQKsLkYVouAb/YdNRZ165Fdyk4EohfoaEBNcxe8fglOmwWDsizqa+r1YCSMZ6T1ENBSxbY5wiomuHQaMG5gBYBxpTkYnJ+Bbq+I5ZFa7weV9h4NV9br7WIl0kBYtz7fZq3RLCZlBABO+Cn7vfF14M2rWaqtcGyP9BfR45ypZWgU8iBKAmzwY1qBH788bUzoDbkqUjQecIYfjsgDj7Dt4OMgkcHItIp8TKnIh8cn4sXVB+Lcsh4mbDCylP3u4XRej6M0LpMUT5cWroyMt1bLXq4CXS9XvFwoB+HvbTiEbq8BNY/7RuSZTgCQl6GntK5nv8OYVwHNXBpSRvooen0c9i8H/G5WEVA0Vv9+GoKVEcB8T4lBeRk4bypTNv762U5D9wnBalNfT0uNUtY7vDALlppvWcOgrCKgeGJsj28WJRgJM3iM+yBKJkZMhSkGVkuogdVIMCIIgqKOLI6UqgmqpuGt4EO6r9ZtZiXfWcXqawyCKyPaAJV/J5q7m82ZIofMZJ0kfV1spWt1Ahc83TupNrDv5vQRxTgCFgD+6eQC/RQN9/9EkccDlBE5jaWdzBwPfC4ND1xjTdMA7Htz9WzW2faFVQeMnXySheIZ0QTbnk51HxuRxn4RQE3TALq+kUOyZ2Skezu7YPCxPdJp9sQRAzE4PwNt3T58ssVASl1J03RH9oxESfsCZGDt+/CTSctBRZ7HptfZ79HzDX2h9VbuRhufabnxlFGwCMCSHYexIVZ1hFfUtB4M7LzKUzQjTg7pFtpjREvTVH/DfkfpChkpTdPubTdkEj5dDka+2N4QvqVzUDAStvtqFPMqoGkHr7meq2WRBvzpIgjA8T9R/19wD1DaQwMOw3DFrGGol/IBAJPywpQ28mCkYnrEx+oNA2t5TnnA/7Gy8JhSlOW50NjhwXvrDVZRJAM9ZaRqFVMJcsuBgSP175cuWCysTwqgW95bfVQ2sLbLimWCUzTqZgi4SC44eOrLvdEXFTz16+1ES1cYz0hXMxuJAURO06TIXBqAgpGeoWAkUxM8bcDXT7JV76Y32HXHXmHoIfRmp/CT5VG3gc6fMsMLsxR15G+f7zJ8vwC4b6SlJrCst7f9IkDgIEK9nVYZaR45GFH6jGiCvRxHjimT8AnDC5DrsqGxwxO+OsIeLhgJUiB46WCEVYy2fJXjtDqRaWMrPFO+EQCYcgmT2o//KXDC1ebumwAWTCzFuNFyakavVNvvVdM0FTNCr9fQk6W9/LswJJf5PeJJ0wCs++YVs4YBAP6zYl/qlvnyMnqtgZX7RUZUpuc8mmDCVNS0dqs9PHIaZSNoDwUjAHD5zKHIdFix5VBr9Em+Nq1nJIwyYsC8ClCapu9jcwCn/IH9/eWDwMe3AZCAid+PmL/TElzaC8SmjACqOvL59gZ8tClCf45wKMpIDXbWs54LY3O9ak6yN3PH3I/j7WDD3rR4OtUx81FW0jzY0yojVosVOQ6W2jESjNitFpw2gXUzfWd9mLQRV0b8HkD0a7qvhlFGDPTS0PYZAcz1oAnAmQ1c/i5w1sNJO7HY87nZW0eertvE0kiuPGDg6IiPo6uMJMrAKlfTDMlhwUiLuyXuAOKH04cgy2HFjvq2yGm+ZMKDkcbdLDD0dALr/8suM2DCTwvCBCPVskl/SKYPlkZ5EZegzqt6DMhy4EdyH5p/LtkT+caa3kXhg5H17HeUdgs8GHFYSBnpu0y5hLVJdrcwv4hgBU7+veG7K6W9cXhGOCOKspWV2C9eWY/VRjqHapG7sPqbq7FOTvXMwEYAEvMd8AChN3BksXblQKiJ9dBa1pkwpwzIC99qH9DvwAqYq6gBgB8cywK198OZz2yavhk+t36axt0OHN7B/o4gqSoGVgQGDso2mwxSU4Jw3WCBwH4xUdKAWmVEmdqbIGWEd1zlyohP8qEjwnA1I+Rl2JV98tHPdqWmOjL4OCCzkH02a59nP51HgPyhwLizkr11iYEHI97gYISlaObm1EDt/lvUo5ty9ZwRcFgt+Gb/0chzrzSlvTwYyQ9uoMgXN1FKr8kz0h+wWFgenjPtUqBwlOG766URlBWwWTkewO/PnIDTJ5TA4xdxzXNrzPlHZGWk83AVPD4RJblOlOx9i10XpZNsjxDOxKpMEZ0edaWv14EVMB+MnDhiIMryXGjt9uFzvQZoAcFIt2JgDQhG6uTALncwkFMS9rkkyAZWS9A28yors8pIghAlEdd8eg2uW3yd+ZOqEozoKCPc/1MeWeUCenZQHldGijOL4bKyzzPeVA0AXDNnBLKdNmytbcUnW1JQHXFkAfP+H/t76X3AV39jf8++Ob1LerWEUUYONjFl5Hi77LtIcH8RPUrzXPiBXFnz6Gc7w+9LcjAieTrDKyMGKmkAjTJCwUgfZ/hclo8vGgdU3m7qrrqlvSZPlFqsFgF/u2Qapg8rQJvbh4ufWoUPjaZsNGkaADinohvC7s8ACMBxV5relrgJZ2LlJy8DU0T1DKyAWt5rdP6IxSLgPLmj6Ft6M0esNkB+DsnbqQxJC6imMeB6BzQG1iBlpMDJcsLJUkYOdx7G6trVWHloJeo7TZ5UIyoj3IysP19Ii9L0zGJTqmkSrYzkOfJMlX9HY0CWA1cq6shOiOFM0MnkuCuBAcPZAMXWGlbqP/XHyd6qxBElTTPezwc09pxfRMsNlSPhsFnw1Z7G8AGq7BlpaWtDt1eEzSKgKEfj+TBoXgUCZ9MkGwpGepqzHgYWfW06laFX2hvTHBINLrsV/7nyeFSOLUK3V8QNL63Fw4t3hq8E4cgG1kzPEbjgxoXiR+zyMQuAguExbUtc8GAkeLYKLzmM4hcB9NNgQGwB3/lyS+elOw/rN7KS1ZH29g745Pd6gLbpWU108yoQ3jOSbGWktkP9HPa17DN3Zz5BODjl1lYPNFcBECI2r+P0RjVNnjPP8MgAo1w9ZzhynDZsr2vDB7H4uXoamwM49Q/q/7Nuilr+3e724cXVB3DTf9eh8oEluOLpb/DCqv1oaOuOeL+kEGZYXnUTS9OUd21jF/RSMFJRkImfzR0BALj7g636qV9ZGak7wlI5EwfnBZbFK+bVoRHNqwClaQgD6JX2apuexZpjznHZ8Z8rTsBPTmJBxN8+34VL//01GlojHCiyiiFmFcMKEf+xP4hRNXLr8OnXxLQNcZOjk6Y5sgPobmarBgMjzbkyEtx5MJaTzajibEypyIdflPDOOh0jqxyMNLexFXaWwxp48DCpjIQYWJ2xp+8SQV2HmmI50GqykRdXRjoOB06H5apI8XjAlRv1YbTjE5QOrAkIRkRJVNI0ec48U71ojJCf6cA18snnL59sh9uXgn1HJnyfdeYtnx5VCT3c5sYFj3+F37+zGf/bcAj7GzuxbOdh/OHdLah8YCmeXrEv+uKnNwkzLK/6aCeK0ISs7vqo3X8TzfWVI1GW58LBpi48uWxv6A3kYKShqRkAlGF7Cop5dWrU51Jm05CBlQgHP1nqGVg9ogddPoMjp3WwWgTccfYEPHrxVGQ5rFi1txELHv3y/7d33vFR1Pn/f81ustn03kMKEEIwIRQlBqSHJiKIX0VAwYanooKIcngigvcT7lAQEUXPE1DvLFjgKJYAIZSE0GsgEiAkhBSSkN6zn98fk5nsJptky+xOAu/n48Fjw+zszPuzn52Z9+ddse1Ujn4lR6HAqdg1qGR2GKI8D0VdOeDZE+huxZRebfRVYU3fxb+GDDaoq6a+3jSAcYXPtBGqKG5KzkRDY4uHYJMyUl7Br748tF001SVAcVP0/G1gGcksyzTuww6eTW4sBlRoxdyI8SIdu2gA3e9GygDWyvpK8dguKhfJLSMAbx3xdbFDdnE1vkruhFVZFQrg0a+AZxParYJ7o6Qa0z5LwcW8cng72+HV+F7Y9NQ9WDS+N+4KcEFVXSOW70jD1E8OiW4Q2RGUkZrm650xhuu3qhGjaFIEOqj+KzUOKhu8OTESALB+XwbS83S7RgvKSEkpv7gZ2FIZMTB4FSDLCGEALRvlAYC9jb3o25PiwTOlfyC2v3wf+vi74FZVPeZ9dwpzvjqGvNLWVpJfy7tjVt1fUaNoqlp4zxzrFTpriRjDohUzkvY//rXPgwYdoq0AVlMfNg8PCIKHowrXb1W3NrfbCm6aJmVEu8aIESZVfXVGAN0qrHKgo4yUZhr3YYWCj0MAdINYhQaMIYMNOow+y4jg6jQHQSlVK9VQ26glt4wA/MPntbF8VeZ1ey+JcUVdiboGDWZ9eQRXCisR6GaPLX+Jw7z4cIyI8MELI3pg+0v34b2HouGstsHp66WY9PFBHMoolFvs5vLuRRnipsKKOlTXN6KfommREGiFbuQtmBjtjxER3qhr0OCl/57Q7X/VtLipruLvJ62VkVP8qwGWEVJGiA7Rl3rKcZxpjdHaobu3E7a9NASvjekFWyWH3RcKMGZNEr4/miVaSTQahgOXCnGcRSB5xLfA+H809zaRA7H3T5NLpCSLN01yCiBiokGHaCuA1dQgYXuVUgxG3JDUoopiU8BZZSVvCtapMSIUOzMgWl9fBVZzZJYKsywjQHPciBADdOsakH+Wn08D+jgBzTVFpLaMCC4aFzveVWSp7/rhAUHo7eeMspoGrE4wsXWDjHx56CoyCirg5WSHLc/HIdTLUed9hYLDjNhg/PHqMMQEuaKkqh5P/DsVPxw1o4mnFHj35l9vNn/n2U2ZNINsmywjVooX0YbjOLz/SAy8ne1wqaACy3ecb36zqYy9GnUIcreHr4tWxp4RwatA86KMAliJNtFnGQHMD2LVh61SgZdHh2PHy0MRE+SK8poGLPrpLB79LAUpl4vwzOajuJhXDlslh6j+9wL3Pm+QK8RiCG6a6mK+Ad2F7fz/gwcbXAtAX1E5wLhmeS0RqiheyC3D/ktaq76mgL9r+fy2UE+tG7WB8SKAliuixWUr/iZkctNox4zcqLghrrYMpqUykt4UIB0cBzh6GnQIS8WMaAevar9KrYwIrlMA+Cb1Go5fM7zKstzkldaI1Z0XT+iNADf7Nvf1d7XH93+Jw8MDgqBhwBs/ncG3R7KsJWprvJsqAAuF3cDHi9iiATGsqfZPB9V/LYWXkx0+nNYPHAd8eyQb6/Y01aNpsrSqUacnXsRwSytAlhHCAPTFjABaLeMt8OCJ8HPGTy8Mxpv394baVoGjmbcw/V+HkZh+E3Y2Crz/SAx8nNUdH8jSqN2aSyKX32hWRiInGXyItgJYzTHDuzmo8Ng9fGGsj/dqFbJq8vGmX+eLzY3q7dP8IQMzaQAtZUShP2akrLZMHJc10VZGGBiyy4xc7basNZK+k3+NuN/gQ2h/N8I1I4VlRDutFzDv99ERg3t44ZGBQWAMWPTT2c4ZzKqH93ZdQFVdIwaGuOOhpjT39lDbKvH+I33x1JBQAMDin8/K18HYJYjvT6OpB4p5i8L1W9Xoz12CHWqbmoD2kUc2AEN6emFhkwvvg4Q/sXxHGjRN9z571Opx0Qj3k34GHZ/qjBAd0pZlRDujxhLYKBV4blgP7H1tBCbF8BaIIHd7/PTCYEzu1/GNxipwXLN15NiXzcXOIg2vCtlRAGtJbYlJK+s5w8JERW7Lsaa6I02WkYbaCjiqlBgU1rRiKckGSrP56rwGlJrWQL9lxEXlAg4cGJjYYdZaVNVXiVaCUJdQACa4aly0lJHqW0DmIf7/vQ1XRrSvFylTe1taRiztEvvbxEh4OamQUVCB9XszOv6AzJzLKcX/Tt8AxwHLHrwLCoVhbQU4jsPbD/QROxi/tfUcvk7JtKCkbaBQNFtHCnlLSHZxFQYrm9wiYcNk78Ezd2RPvP0ArxBtPJSJFQmZAAA7rh4DQ1pYP66l8K8GWnOoNw3RIW2VKxdM8paODwhws8e66f2R9PoIJLw6HFGBrhY9n9EIHUOT1wFgvF+3qWy9IYgBrC0sT14OXrDhbFCvqUdBlZ6Kqh3g72qPBWP4m9vfd6bxtRWa3BBB3E0M6+UNlU3TZZfVdOMI6GdQtH5b2TQ2ChsxpsHa6b15Vbw1w9nWGXd53QXABGVEu/DZpQSANfKrUY/uBh/CUo3ytNN6tV8tdf25OajwzoP89/hxYgaSO0OQZzt8eZC3JkzqG2D0PYLjOPxtYiSea0ptXrLtPDYeMrJOjRSIcSMXAfAxI3GKpk69YcOsL48enr4vDB9O6wcHlRKXbvG/ayeuDhF+zs07aTRAttAoNM6g44puGkrt7Xo0ahqxaP8i/OvMvyx7nrYsI0Ln3hrr+JRDPB1hr1J2vKO1mfgBcN8C/mbhGgzc96pRHxcDWDldZc9WYSv2ILlSoifH3wCeHhKGqEAXlNU0YNn/0sB8owEAfbhrGKntornWZAEwMGOkLWUEkK/WSF4Fr4z4Ovo2W0aMzagRYkZyjgFJ/+D/NsJFwxizWNEz0TLSwk1jTq2fjpgY7S/GVLz87Unklpqexm9JCspqsP0Mn9H29H2mFT/kOA6LJ/TG88P5xcWy7Wl4d0eadWuReDVZRpr6Q90suoX+XFNzPDOUkXpNvfHxU+0wpX8gDi0ahQl388pTsKocSm1LVEEan6KscjKo1hLQXIGV3DRdkAvFF7Dr6i6sO7nO+GqTRtBWhdAgZ371b/QN/3bDLRiIXwrM3g68etaoeBGg7e8XAMJc+RvrlVLTlBEbpQIrp/aFUsFh59lcfHqR9/FGKrIwMkJbGUnmX0OGGHRc4eGnTxkRLGamWHPMQcik8Xf0R6hrKAATLCNeEXzmTE1pc4qlES43baXDUgGsguXJ38kfHDhUNVRZLGCY4zj8fUoUIv1dUFRZhxe+OYGymvqOP2hlvjl8DfWNDAND3NGvm5vJx+E4DovGR+C1Jovivw9exTObj6K0ykpj1rKMNDRqEFh2CiquEQ3OQXwpfBN5cfeLGPvjWEnji9wdVZg2cTwADs71N/lKxQKCpTXoHoN7B1HMSBdGsEgwMHyd9rXFzqOvUR4A9HLnL9g/b7XTSInokLYCWAGguytvNjZH2YwKdMWyJnP7hiZlJIgrhLdNU7GniptA4Z8AOIN66QC6Jc9byezGy3y5tIP24xKjo4yYGjPiGgg8fwiY8ikweikw9V8GBfQKaCsdCoVWaq+EdUYE94yd0g5+jrwlJ6vMclkg9iolNjw+AC5qG5zKLsHUT5KRWWhep2ApqalvxDep/PifMdEqog3HcXh5dDjWzxgAta0C+9JvYuK6A8Y19DQVbz5AFIWXcDm/DLHcOQCAosdwk+NFSmtLcTj3MIprinE8/7hUkvLYOTXLLFRbBbQWN4ZZWgGKGenSaLtH/nf5fxZzl4iN8lqs3MNcwmCjsEFFfYVOfQfCONpK7QXMt4wIPH5vCFb9X19UcI7I1jSlHOc3BcZlNd04fO8C7N31H6AF7blperrxHaEzblk36FFURpz8EezMu7dKa0uNL8Dm2wfoNwMYugDo+6hRH9WODZHaMiJc34LlCYDoxjOppooRhHg64j/P3gs/FzUyCiow5ZND+Dols1Nk2fzv1A0UV9Yh0M0eY/u03WnaWCb29cePzw9GNw97XL9Vjf/bkIyNh65aduHlHgoo7YCGGly6dB6DFfw1qggbbvIhLxRfEP9OK0ozV8LWCMq6UBqAsWbLiIHxIgCl9nZptH3ytY21+P7i9xY5T1sPS1ulrbhy//NW1yuO1FkQlL2WAcKANJYRgUfu7oZ/zbobJS5NK5m8s/yrCauYtoqeAUC4WzgA4FLJJdOFNYH8St5M7OfoBwdbB9FqYOkHtTY6lhGuObVXmGNzKKrh07E91c31TgQLkCUtIwLRQa7430tDENPNDSVV9Viy7TxGrtqHD/5Ix9HMYtS3bD1gJf6TyqfiPn5vCGyU0j5GogJdsePloZgQ5Yf6RoZl29Pw/DfHUVptIbeNQgl48deP+9mNiOIy+e1mxItoKyAWUUaEgmaCMnIrkw8AV9gCQR03lhSg3jRdGEEZCXTi01y/S/8ONQ3SdqPUMA0Y+JWAvpW7tquGMA0hm0afMiJYRopqiiTx946O9EX0wKa4kDzeBGxs8CrQdjl4AOjpzltGrpdfR1W99fp+aLtpgGal6FzhOavJ0JZlBDDfOiJc7zqWkSYLkNFNAU3Ex0WNLX+Jw7uT74Kvix1ulNZg3d4MPLIhBVFLf8dDnxzC0m3n8OPx68goKLe4+/ZcTilOXy+FrZLDI3cbnsFmDK72tvhk5gAse/AuqJQK/H4+H/evPWC5YnBNbo8hhVug4BiyQ//P6E7r2rRURiSfE9Eycop/FTPz+ot1jQyhVsNbRshN0wURzLaTe06Gv6M/imuKsSdrj6Tn0PZ16wuwJGXEfNpz0zjYOsDXgTc9Sxak7Mdn1CD/LFBV3KyUBBuujAgKass6IwD/sPRQe4CBWTSwWhsN04gFzwRlZIAvXy/lRMEJq8ggyCGgnU0DmJfeW91QjaoGXrFzVze70kJcQgBYTxkBAJWNAk/EhSLp9ZH44JEYTIoJgLuDLWobNDiZVYLNKdewcMtpxK/ej+Gr9mHFrxeQUVDe8YFN4L9NFVPH3eUHLyfLPcQ4jsPswaH48YU4BHs4IKekGo9+dhhrd1+SPttGCGIFcFYTCptJq8w6nLYyUlRTJH1guV80H/Rdkcc3DM00fnEDNMeM2MpZUbsJUkaMRIig97b3xkM9HwIA/HLpF0nPoW1eJsuIZWirN42AlK4aAIBvFP9acBHY/z4Axt9QnA33t7cXwApY31VTXFOMOk0dOHDwduBjYgb48MrI8fzjVguwbmkZ0b5mzLGMCFYRW4UtnGyb68AIMSNZ5VlWDyJX2yrx8MAgrJveH8ffGoPEhSOw9rF+eOa+MAwK9YCdjQJZxVX4LOkK4lfvx5MbjyD1SpFk56+obcC2k3xPqBmxwZIdtz36Brlh5yv34aH+gWjUMKzZ/Semf34YOSUSpjw3LRZKmCOWqN6An4dhcVz6KKsrQ3Y5X4VYcFtK7qpROTQrUH/+Cpz7if+7h3Gd1CmAtQsj3KDc1e6Y3HMyOHBIzUsVf3xSoG0Z0fewFJSRa2XXJHcR3Sm0VYFVQHDVSKaMuIUAKmegsRY4/Am/bdQSow7RXmov0OyqsVYQq2AV8XbwFrOSoryioFKoUFxTbLW4Ee3AXo7jdL4fczJqtINXteN0gpyCoOSUqG6oxs3qmyYf31wUCg5hXo6Y3C8QSx7ogx+ej8OJJWOwfsYAjOnjC44D9qXfxLTPD+O5r47hqgTZONtP30BlXSO6ezkirrthfYOkwFltizXT+mHNtBg42dngSGYxJny4H7tadsg2lfBxSO61CNPqlsA7OEJvXJahXCzii6cFOgUi1o+vhJpWbMEg1j/eBhqqgaBBRsW5NGgaxPsgKSNdEG0fcoBTAO7159Myt2ZslewcLVd6LfGy94K7nTs0TGP1VM7bBUMtI+Zm1IgoFIBfk3UEDAgdCoSPNeoQ7QWwAs0ZNdayjLSMFwH4qPxob36VeSLfOq4aYS4FJUTbtWmOZURfJg3Am7QDnPh2BNZ01RiCo50NJvb1x79m3Y3E10ZgRmwwlAoOf6TlY8zqJCzfnoaSqjqTjq3RMLHi6vRBwWY9sE3lof5B2PnKfYjp5oaymga8+J8TWPTjGVTVmRmsrFDgvxiPdBZsVs0UoNkK0sezD/p49tHZJimCMlLX5I4b9ZZRqciCVQTQX+LA2pAyYiSCm0aoeDk1fCoAYFvGNknqGgDQaXambxXMcVyzq6aYXDWm0FYFVgHJLSNAs6sGAMa+a3QNg7aq8gpYO703t6K1MgLoumqsQcvAXh3LiBkxI20pI0Czq6azKSPahHo54r2HovHbvKEYGeGNBg3Dl4euYviqffj68DVojIy7+CMtD5cKKuCstsG0Qd0sJHXHhHg64sfn4zB3ZA9wHPD9sWw88NFBnMsxL9j89PUSAOg6yoiQUQPwFpHuxqUiaysjlNrbxahrrENlPW/qFALaRgWPgqudK/Kr8pGSmyLJeUQXAmfT5uoj3J2PD6C4EdNoq46LgFBE7HrFdelKOgv+3P5PGFXUS0Bw03RkGSmoLrBIV9mWCH1pWiojd/vyqYXWCmJtGUsjVcxIe8pIiDMfxGqN9F5zCfd1xsanBuHrZwaht58zSqvrsWTrOUz9NBlpNwxrrMgYw8eJvJL75OBQuKjlXUnbKhV4fVxv/LepDsuVwko89MkhrE/MQE298QpoUUUtsourwXF8OrU5CC6ZSI9IRHhEQMEpUFhdaIEg1qjm7uUj3zL648J9Tckp27QQWxNSRoxAuDnZcDZwUfHloVVKFUYEjQAAnLl5RpLziJkebTwogea4kUu3rFtX4nahIzeNp9oTzipnaJhGutVvxATgpePApLUmfbyjAFYnlRMCHHn3QUaJ5a0jQsyIEKQnEOMTAwWnQE5FjriPJbGUZURfWq+AkFFjzXoq5jI03Bs7XxmKdyb1gZMdX9l10scH8f92pqGytn03x74/b+JcThnsbZV4aoj5FVelIq6HJ36dNxRj+/iivpFh1e/pGP1BEn48ft2o4nDbT/M9drp7OZqlaJXXlYv3iz6efWBvYy+6fM8Xnjf5uHqxtQdmfAdM+w8QbFiXXm2ETDG1jVpauUyElBEjEG5Obmo3ndWp0JPjevl1Sc4jrtrbMMcDQG8PPpL6XNE5SZsx3Sm0VW5fgOM4RHpEAgBSc1OlOSnHAV49+SJLJiBYRtr7XVgziLUtN42jraP4+7SGq0afkiZFszxh8aGd1isgKCNdwTKijVLB4ckhYdi9YDgmRvujUcPwrwNXMWZ1Ev44r19xrGvQ4MME3gI7MzYYHo7ym/S1cXdU4bMnBmL1ozHwc1Ejp6QaC7ecRux7e7Bs+3ns//NmuzElGQUVWPkbH3T6+L0hZslyuYSP4fN18BV/NzHeMQAgmeVch+4jjOrjpE1OBZ8V1fL6lQtSRoxAO5NGG6F5nVQZNYZYRiI8IuDj4IPK+koczDkoyXnvJNqrwCowKph3q+y+ttsqMnWEBk0BrGg71kRI7z2Sd8Ti8ggBrC0tIwAw0HcgAFjlt6nRtC4GJygm5sRxCdVX24sZyS7PlixWzJr4uaqxfuYAbHzyHgS52+NGaQ2e+/o45nx1DFduVoj7NWoYXv3hFE5fL4WDSok5w7rLKHXbcByHqQOCkLhwBN4YHwF/VzVKquqx8VAmZn15BH3f+QNjVifhL18fw8pfL+KHo9lIzijEmeslmP/9SdTUazA03Auz40LNkkOwighVegFgdPBoAMAfmX90qt+K8Lzq5ixf/I82pIwYQXFt00rJTlcZESbzeoU0lhHtmJG2UHAKjA8dDwD47epvkpy3s3Cu8Bx+ufSLTiCv1HTkpgGabyInC07iZpV8KZwCojuiHSV1QtgEAMDurN2SWer0UdtYKz6s9a2sxoWO4+W4thtldYbFJZiKvg7MYrM8cwJYq/nr3dO+dQqrv6M/bBQ2qNPUibEzXZGRvX2Q8OpwvDiiB2wUHBLS8jFmzX4s3HIaXxy4gle+O4mdZ3Jhq+Sw4fGB8HXpHCb9trBXKfHiiJ44uGgUNj55Dx4eEIRAN3s0aBguFVTg9/P52JB0GW/8dAYzvkjFgx8fwrmcMrg72OL9R2KgUJiXISQoI4LlDADuDbgXrnauKKopwrH8Y2YdX0oEZUSoKCw3pIwYQZuWESfeMlJYXShJKW7hQdneQweAqIwkXU+yaglwS1Gvqce6k+swc9dMvJ38Nl5Pel3snSA1wvfVXhS5n6Mf+nr3BQOTvMquKYipve1YRiI8IjA4YDA0TIOv0r6ymCxCTxp7G3uxo602fb36oqdbT9Q01uDXK79aTA5AfwNBKZrlCZlz+iwjNgob9HDtAcB6WUOWwl6lxBvje2PXvKGIj/RBo4bhx+PX8fedF7DzTC44DlgzrR+G9fKWW1SDUSo4jOztgw8ejcHBRSNx6K+jsPnpQXhnUh/MjgvB0HAv9PRxgr+rGr4udlj9aD9JFC1BGREsZwCfNhsfHA8A+C2z8ywcs8vIMtJlEZWRFpYRVztXMaBV8MOZQ0cpnAJRXlEIdApEdUM19ufsN/u8ctKoacQLu1/A52c+h4ZpoOAU2J21G/MS50le2K2wuhC3am+BA9fhqmBM8BgAncNV01EAq8BTUU8B4CsDazd2lBJtF42+7B6O48QKxT9n/GwRGQT09ewRFHlTLSOMMdEyoi9mBGh24/2e+btJ5+hs9PJ1xhez78HPLw7G9EHBeKh/IKb2D8QXs+7GA30D5BbPZDiOQ6CbPYb38saTQ8KwbHIUvn4mFrsXDEfK4tFIfTMeI3v7SHKurHI+hkjbMgLoWgqFvlhyQ26aLkx7qX5C3IgUpnExuLKDdCuO48Qf+e9Xu/YN8WzhWaTmpkKtVGPVsFX4NP5TqJVqHMg5gJVHVkp6LiEdOsQlBA62Du3uGx/Cr2iO5R8T518uOqrAKhDrF4tIj0jUNNbg24vfWkSWlj1p9DGpxyTYKGyQVpSG9OJ0i8gBNMf/SBnAWllfiToNX4eh5eJDYGwIX7Qu+UayxV1R1mRAsDtWTI3Gmmn9sHpaP4yONLxlwZ0MY0yvZQQA7vG7Bx5qD5TUluBIruXjuTpCwzRiWEE3F1JGuhxtuWmAZu1SiiBWQy0jQLOrZv/1/RZbBVuD/dd5y86IbiMwPmw8BgcMxtpRfArsT5d+QsoN6SLRhUJxQq2W9ghyDkKkRyQaWSP+yPxDMhlMQZ87Qh8cx4nWkS/OfmGRm5++6qstcVe7Y2S3kQD4ObQU+iwjYgCriZYRQfG0t7FvU2Ht6d4TPVx7oEHTgH3Z+0w6D3H7UFhdiOqGaig4Bbo56T7gbRQ2GBPCW1kteS0YSkFVAWoba2HD2VA2TVdErL6qRxkR4kakCGI1NGYE4FN8I9wjUKepw3up75l9brk4kHMAADAsqLm3wuCAwXgs4jEAwLKUZZLFxQiWkQj3CIP2n9RjEgDgk1OfyKrwGaqMALxZOD44HvWaeryS+IrkFSAFy4ivY/ur5ofDHwYA/PTnT7hSIlFp/RYIlkQpLSPtWUG1GRvKW0fkVlQJ+RGsIv6O/nq74D4c/jAUnAIJ1xKQlJ1kbfF0EBbN/k7+naLgGUDKiFG0VwRJSsuIkKWgVnYcUMVxHJYNXgYlp8Rvmb91ycya/Mp8XCy+CA4chgQO0Xlv/sD5CHAMQE5FDtadXCfJ+dJv8S6DCA/DlJHHIh5DuHs4btXewj+O/kMSGUzBGGVEwSmwcthKDPIbhMr6Sry4+0VJg5wNsYwAvEI5JHAI6jR1WHJoiUVSGy1pGelQGdFy1ZQLPUKIO5K24kUEIj0jMavPLADA8pTlsrr2hHCCzpJJA5AyYhQt+9JoI2XMiOCyuMfvHoP2v8vrLjzX9zkAwN9T/y4Wo+oqCLUoor2iW938HW0d8bd7/wYA+CXjF7MLvNU31ovN7wy1jNgqbbF88HIoOAV2Xtkp26pGqDOiMPCytVPaYe3ItQhwDEBRTZGkQc6GKiMcx+GduHfgZOuEM4Vn8HXa15LJICAG9ir0WEY0lrWM9HTvie6u3VGvqcem85vEuB7izkOMF2nnAT+331yEuoSioLoA76W+J9vvRVCchOdWZ4CUEQNp0DSI/T7aixnJqcgxa/XXqGnEgeu8y2JEtxEGf25O3zno49kHpbWleHzX47hQdMFkGayN4KK5L+g+ve/fF3gf/Bz9UFlfieScZLPOdaX0Cho0DXBWOest1tUWUV5ReCLyCQDAwqSF2HVll1lymILwYNV+6HaEk8oJ48P4uKKEzARJ5GCMGRTAKuDn6IeFdy8EAKw9uRbbL2+XRA4BS1hG2rOCtmRaxDQAwOdnPseylGUWS0cnOjdCNd62LCMAX3p9+ZDl4MBh55WdWHJoiUXrKbVFZ8ukAUgZMZiS2hIAfI0HNzu3Vu/7OvjChrNBvaYeN6tNL5B1pvAMbtXegovKBf18+hn8OVuFLT4c8SF6uvVEQXUBZv82G9svb+/0K7W6xjoxOFU7XkQbBacQg79+v2Ze1pAQL9LLvZfRLdBf6v8S7gu8DzWNNVh0YBH+fvjvkqRyG4qxlhEBwZVwIOcAqhuqzZajtLZUPE5HMSMCU8OnYkLoBDRoGvDmwTex9sRas2qAaKMv4FuItzI3ZqSttF5tpveejjfueQMcOPx06SfEfRuH6TumY97eeZifOB9vHngT36R9g9M3T0s2ZqLzIfQpaplJ05L+Pv3x7pB3oeSU2HZ5G+Ynzpe+iV4HdLaCZ4CJysj69esRGhoKtVqN2NhYHDnSfrT+li1b0Lt3b6jVakRHR2PXLuuvKs1FWCm52rnqDSxVKpQIcOJz8c2JG0nMTgTAWwNsFcY1bPJ38sdXE75CnH8cqhuq8ebBN/H0709braW8KSRmJ6KqoQpe9l5iLxh9CCnMiVmJZtUdEVJMDXXRaKO2UePjUR/j2ehnAQDfp3+PCT9NwEt7XsK5wnMmy2QoJTUlAAyLGdGmj2cfBDgGoLqh2mzLEtDsovFUe8JOaWfQZziOw8phKzEneg4APstn47mNZssCWMYy0l4p+JZwHIcn+jyBdaPWwUPtgdrGWpwrOoe92XuxJ2sPtl/Zjn8c/Qce3/U47v/5fnxx9gtcK7vW6RcKhOFomEa872uXgm+LyT0nY82INVApVEi6noT7f74fq4+ttoqLnTHW6QqeASYoI99//z0WLFiApUuX4sSJE4iJicG4ceNQUKBfs0tOTsb06dPxzDPP4OTJk5gyZQqmTJmCc+csf/OWkvbSegXEsvBmxI0I8QhCSqSxOKucsT5+PV7u/zLUSjWO5R/DjF0zcCyv85QhFsityMW7h98FADzY48F2H7J9vfrC39EfVQ1VOHTjkMnn1LaMmIJSocS8AfPwWfxniPOPAwND0vUkTN85Ha/sfcViSsmhnEPYcWUHAH5lZQwcx2F0CF/aPiHLfFeNMS4abRScAq8MeAWLBy0GAHx86mNJ3IntZdNYOoBVm+HdhiPx0UTseGgH3h/+PpbcuwRL7l2Cuf3mYkTQCDjbOiOnIgdrT6zFA788gGHfD8PcPXPx+ZnPkZqbeltUUb5T0U6VFRalHTEyeCQ2T9iMft79UNtYi43nN2LcT+Pw7O/P4of0H3Cj4oZFZC2tLUV5PR9s3ZliRozO6Vm9ejXmzJmDp57i6xhs2LABO3fuxJdffom//vWvrfZfu3Ytxo8fj9dffx0A8O677yIhIQEff/wxNmzYYKb45lFYXYi6xjqD9r1aehVA2wWQgOaJvVh80aQfUkFVAa6UXoENZ9Mqq8QYbBW2eK7vc3ig+wN469BbOJp3FC/sfgGrhq8y+SEsNRqmwaIDi1BaW4q7PO/C3H5z292f4ziMDRmLzWmbsePyjnatKO1hbCZNWwwOHIzBgYORWZqJL85+ge1XtiMxOxGJ2Yno590PcQFxcLR1hJudGwKdAuHr6GtQ3Rh9lNWVYfGBxWBgeLTXoxgaNNToY4wNGYuv075GUnYSssuyDUobbwvhOzQm5kab6b2nIzU3FXuz9+KvB/6Kj0d9bLI8Z26ewaqjqwAAdjbNVhrhu75ZddOka1HoReSpbt2Xpj0UnAIhLiF64waqG6rxR+Yf+CXjF5y9eRYltSXYf32/GLBuw9kg0jMS/o7+cLNzQzfnboj0jESQc1C7LQC6Grdqb+Fi0UXeOgQGJaeEv6M/enn0go+DT5cc65mbZwAAgc6BRqXKRnlF4asJX+FAzgFsOr8JR/OOIjUvFal5fKfwcPdwPND9AYzoNsKg7EpDEBZkPg4+UNt0nl5DHDPCVlhXVwcHBwf8+OOPmDJlirh99uzZKCkpwbZt21p9Jjg4GAsWLMD8+fPFbUuXLsXWrVtx+vRpveepra1FbW1z1kRZWRm6deuG0tJSuLi4GCpuhzy+63GcvqlfhrYYHTwaH478UO97m89vxvvH3jdbrli/WHwx7guzjwMANQ01mL9vPg7lmG5NsCTOKmf88MAPBmnoZ2+exYxdM8w+p4JT4PCMw7C3sTf7WAJXSq7gi7Nf4NfMXy0WkBbpEYmv7//aYNeINhqmwZgtY1BQLZ1v+vHIx7Fo0CKTPltcU4yp26aK7hBz6ebcDSuGrhDbtT+6/VFcKDbf6vLDAz8g0tM0xbc96hrrkF6cjjOFZ3C64DROFJxAflW+5OchrMvQwKH4JP4Tkz+fU5GDX6/+igPXD+D0zdNmNXrsiIG+A7Fp/CaLHV+grKwMrq6uHT6/jbKMFBYWorGxEb6+ukFrvr6+uHjxot7P5OXl6d0/L6/tTpcrVqzAsmXLjBHNJGwVtkbd2FVKlRi7oI9hQcPwzYVvzCqMZae0w8zImSZ/viVqGzU+GvkRlqUswx+Zf4Ch8/ip3ezc8M7gdww2FUZ5RWFY0DCk5qaadd6J3SdKqogAQHe37nhv6Ht4deCr2HZ5G25U3EBlfSWKaoqQU56DwupCs777MNcwfDD8A5MUEYBXwJ6OfhofnfhIkhuco62j2NXYFDzUHlgxdAXe2P+GWUG1ahs1ZvSegaejntZZ5Y0LHYfMskyzAkYj3CPQw62HyZ9vD5VShWjvaER7R2Nm5EwwxnCj8gbOFp5FcXUximuKcaX0CtKK0lBYXWgRGeTCwcYBvTx6IdwtHDYKPuj/Wtk1/HnrTzFjsSuiUqjwQPcHzDpGoFMgno1+Fs9GP4vS2lIkXEvA9svbkVaUJum921Zhiwd7PCjZ8aTAKMvIjRs3EBgYiOTkZMTFxYnb33jjDSQlJSE1tfVDQqVSYfPmzZg+fbq47ZNPPsGyZcuQn69/JWAtywhBEARBEJbDIpYRLy8vKJXKVkpEfn4+/Pz0+4/9/PyM2h8A7OzsYGdn2gqQIAiCIIiuhVHZNCqVCgMHDsSePXvEbRqNBnv27NGxlGgTFxensz8AJCQktLk/QRAEQRB3FkZn0yxYsACzZ8/G3XffjUGDBuHDDz9EZWWlmF0za9YsBAYGYsWKFQCAefPmYfjw4fjggw8wceJEfPfddzh27Bg+//xzaUdCEARBEESXxGhlZNq0abh58ybefvtt5OXloV+/fvjtt9/EINWsrCydctWDBw/Gf//7X7z11lt48803ER4ejq1btyIqKkq6URAEQRAE0WUxKoBVLgwNgCEIgiAIovNg6PObetMQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErRpeDlwOhSGxZWZnMkhAEQRAEYSjCc7ujYu9dQhkpLy8HAHTr1k1mSQiCIAiCMJby8nK4urq2+X6X6E2j0Whw48YNODs7g+M4yY5bVlaGbt26ITs7+7bteUNj7Prc7uMDaIy3A7f7+IDbf4yWGB9jDOXl5QgICNBpotuSLmEZUSgUCAoKstjxXVxcbssfljY0xq7P7T4+gMZ4O3C7jw+4/cco9fjas4gIUAArQRAEQRCyQsoIQRAEQRCyckcrI3Z2dli6dCns7OzkFsVi0Bi7Prf7+AAa4+3A7T4+4PYfo5zj6xIBrARBEARB3L7c0ZYRgiAIgiDkh5QRgiAIgiBkhZQRgiAIgiBkhZQRgiAIgiBk5Y5WRtavX4/Q0FCo1WrExsbiyJEjcotkEitWrMA999wDZ2dn+Pj4YMqUKUhPT9fZZ8SIEeA4Tuff888/L5PExvPOO++0kr93797i+zU1NZg7dy48PT3h5OSEhx9+GPn5+TJKbDyhoaGtxshxHObOnQug683h/v37MWnSJAQEBIDjOGzdulXnfcYY3n77bfj7+8Pe3h7x8fG4dOmSzj7FxcWYOXMmXFxc4ObmhmeeeQYVFRVWHEX7tDfG+vp6LFq0CNHR0XB0dERAQABmzZqFGzdu6BxD37yvXLnSyiNpm47m8cknn2wl//jx43X26czz2NH49F2THMdh1apV4j6deQ4NeT4Ycv/MysrCxIkT4eDgAB8fH7z++utoaGiQTM47Vhn5/vvvsWDBAixduhQnTpxATEwMxo0bh4KCArlFM5qkpCTMnTsXhw8fRkJCAurr6zF27FhUVlbq7Ddnzhzk5uaK//75z3/KJLFp3HXXXTryHzx4UHzv1Vdfxfbt27FlyxYkJSXhxo0bmDp1qozSGs/Ro0d1xpeQkAAAeOSRR8R9utIcVlZWIiYmBuvXr9f7/j//+U989NFH2LBhA1JTU+Ho6Ihx48ahpqZG3GfmzJk4f/48EhISsGPHDuzfvx/PPfectYbQIe2NsaqqCidOnMCSJUtw4sQJ/Pzzz0hPT8eDDz7Yat/ly5frzOvLL79sDfENoqN5BIDx48fryP/tt9/qvN+Z57Gj8WmPKzc3F19++SU4jsPDDz+ss19nnUNDng8d3T8bGxsxceJE1NXVITk5GZs3b8amTZvw9ttvSycou0MZNGgQmzt3rvj/xsZGFhAQwFasWCGjVNJQUFDAALCkpCRx2/Dhw9m8efPkE8pMli5dymJiYvS+V1JSwmxtbdmWLVvEbRcuXGAAWEpKipUklJ558+axHj16MI1Gwxjr2nMIgP3yyy/i/zUaDfPz82OrVq0St5WUlDA7Ozv27bffMsYYS0tLYwDY0aNHxX1+/fVXxnEcy8nJsZrshtJyjPo4cuQIA8CuXbsmbgsJCWFr1qyxrHASoW+Ms2fPZpMnT27zM11pHg2Zw8mTJ7NRo0bpbOtKc9jy+WDI/XPXrl1MoVCwvLw8cZ9PP/2Uubi4sNraWknkuiMtI3V1dTh+/Dji4+PFbQqFAvHx8UhJSZFRMmkoLS0FAHh4eOhs/89//gMvLy9ERUVh8eLFqKqqkkM8k7l06RICAgLQvXt3zJw5E1lZWQCA48ePo76+Xmc+e/fujeDg4C47n3V1dfjmm2/w9NNP6zSH7OpzKHD16lXk5eXpzJmrqytiY2PFOUtJSYGbmxvuvvtucZ/4+HgoFAqkpqZaXWYpKC0tBcdxcHNz09m+cuVKeHp6on///li1apWk5m9rsG/fPvj4+CAiIgIvvPACioqKxPdup3nMz8/Hzp078cwzz7R6r6vMYcvngyH3z5SUFERHR8PX11fcZ9y4cSgrK8P58+clkatLNMqTmsLCQjQ2Nup8sQDg6+uLixcvyiSVNGg0GsyfPx9DhgxBVFSUuH3GjBkICQlBQEAAzpw5g0WLFiE9PR0///yzjNIaTmxsLDZt2oSIiAjk5uZi2bJlGDp0KM6dO4e8vDyoVKpWN3hfX1/k5eXJI7CZbN26FSUlJXjyySfFbV19DrUR5kXfNSi8l5eXBx8fH533bWxs4OHh0SXntaamBosWLcL06dN1mpC98sorGDBgADw8PJCcnIzFixcjNzcXq1evllFawxk/fjymTp2KsLAwXL58GW+++SYmTJiAlJQUKJXK22oeN2/eDGdn51Yu4K4yh/qeD4bcP/Py8vReq8J7UnBHKiO3M3PnzsW5c+d04ikA6Phno6Oj4e/vj9GjR+Py5cvo0aOHtcU0mgkTJoh/9+3bF7GxsQgJCcEPP/wAe3t7GSWzDP/+978xYcIEBAQEiNu6+hzeydTX1+PRRx8FYwyffvqpznsLFiwQ/+7bty9UKhX+8pe/YMWKFV2i7Phjjz0m/h0dHY2+ffuiR48e2LdvH0aPHi2jZNLz5ZdfYubMmVCr1Trbu8octvV86AzckW4aLy8vKJXKVtHC+fn58PPzk0kq83nppZewY8cOJCYmIigoqN19Y2NjAQAZGRnWEE1y3Nzc0KtXL2RkZMDPzw91dXUoKSnR2aerzue1a9ewe/duPPvss+3u15XnUJiX9q5BPz+/VgHlDQ0NKC4u7lLzKigi165dQ0JCQoet2WNjY9HQ0IDMzEzrCCgx3bt3h5eXl/i7vF3m8cCBA0hPT+/wugQ65xy29Xww5P7p5+en91oV3pOCO1IZUalUGDhwIPbs2SNu02g02LNnD+Li4mSUzDQYY3jppZfwyy+/YO/evQgLC+vwM6dOnQIA+Pv7W1g6y1BRUYHLly/D398fAwcOhK2trc58pqenIysrq0vO58aNG+Hj44OJEye2u19XnsOwsDD4+fnpzFlZWRlSU1PFOYuLi0NJSQmOHz8u7rN3715oNBpREevsCIrIpUuXsHv3bnh6enb4mVOnTkGhULRybXQVrl+/jqKiIvF3eTvMI8BbKwcOHIiYmJgO9+1Mc9jR88GQ+2dcXBzOnj2ro1QKinWfPn0kE/SO5LvvvmN2dnZs06ZNLC0tjT333HPMzc1NJ1q4q/DCCy8wV1dXtm/fPpabmyv+q6qqYowxlpGRwZYvX86OHTvGrl69yrZt28a6d+/Ohg0bJrPkhvPaa6+xffv2satXr7JDhw6x+Ph45uXlxQoKChhjjD3//PMsODiY7d27lx07dozFxcWxuLg4maU2nsbGRhYcHMwWLVqks70rzmF5eTk7efIkO3nyJAPAVq9ezU6ePClmkqxcuZK5ubmxbdu2sTNnzrDJkyezsLAwVl1dLR5j/PjxrH///iw1NZUdPHiQhYeHs+nTp8s1pFa0N8a6ujr24IMPsqCgIHbq1Cmda1PIQEhOTmZr1qxhp06dYpcvX2bffPMN8/b2ZrNmzZJ5ZM20N8by8nK2cOFClpKSwq5evcp2797NBgwYwMLDw1lNTY14jM48jx39ThljrLS0lDk4OLBPP/201ec7+xx29HxgrOP7Z0NDA4uKimJjx45lp06dYr/99hvz9vZmixcvlkzOO1YZYYyxdevWseDgYKZSqdigQYPY4cOH5RbJJADo/bdx40bGGGNZWVls2LBhzMPDg9nZ2bGePXuy119/nZWWlsoruBFMmzaN+fv7M5VKxQIDA9m0adNYRkaG+H51dTV78cUXmbu7O3NwcGAPPfQQy83NlVFi0/j9998ZAJaenq6zvSvOYWJiot7f5ezZsxljfHrvkiVLmK+vL7Ozs2OjR49uNe6ioiI2ffp05uTkxFxcXNhTTz3FysvLZRiNftob49WrV9u8NhMTExljjB0/fpzFxsYyV1dXplarWWRkJHvvvfd0HuRy094Yq6qq2NixY5m3tzeztbVlISEhbM6cOa0WdZ15Hjv6nTLG2Geffcbs7e1ZSUlJq8939jns6PnAmGH3z8zMTDZhwgRmb2/PvLy82Guvvcbq6+slk5NrEpYgCIIgCEIW7siYEYIgCIIgOg+kjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEIRsjRozA/Pnz5RaDIAiZIWWEIAiCIAhZoXLwBEHIwpNPPonNmzfrbLt69SpCQ0PlEYggCNkgZYQgCFkoLS3FhAkTEBUVheXLlwMAvL29oVQqZZaMIAhrYyO3AARB3Jm4urpCpVLBwcEBfn5+cotDEISMUMwIQRAEQRCyQsoIQRAEQRCyQsoIQRCyoVKp0NjYKLcYBEHIDCkjBEHIRmhoKFJTU5GZmYnCwkJoNBq5RSIIQgZIGSEIQjYWLlwIpVKJPn36wNvbG1lZWXKLRBCEDFBqL0EQBEEQskKWEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZOX/A//A4qlarP5NAAAAAElFTkSuQmCC", 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", 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", 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YjUY8//zzSE1NRd++fQEwkbJu3TqsWLHCISoC2D0jSm7uPCOnT5/Gb7/9hiuvvNKh4Z8/mM1m7Nu3z+G8vvPOO/j2228dbvfddx8A4KWXXsInn3wi7dvQ0IBLL70UxcXFWLRokdvUH0H4giIjxFmHyWTCV199hXHjxuH888936MC6cOFCbNmyBY888gj+9Kc/qX7umpoafPzxx27vu+mmm1BXV4fs7Gxcc801GDhwIOLj4/Hbb79h48aNePnllwGwqMObb76JyZMnY9CgQbj11lvRqVMn7Nu3D7t373YrNEQeffRR/PDDD5g0aRJuueUWDB06FA0NDdi5cye++uorHDt2zKHcMj8/H+effz7uuecetLS0YN68eejQoYPHNA/AOuGuXLkSl112Gbp27Yry8nK88cYbyM7Oxvnnnw8AuOuuu/D222/jlltuwebNm5Gbm4uvvvoKf/zxB+bNmyeF8CdPnozzzjsPjz/+OI4dO4Y+ffrgm2++cRFsAPMMnX/++ejfvz/uvPNOdOvWDWVlZVi7di1OnjyJ7du3S/uKkR0xxaCWm2++GV988QVmzJiBZcuW4bzzzoPVasW+ffvwxRdfYPHixVLKMDY2FkOHDsW6deukHiMAi4w0NDSgoaHBRYwE6hn5/PPPYbFYvKZoduzYIfU6OXToEGpqavDPf/4TADPFTp48GQBQXFyM3r17Y/r06dJaQBdffLHL84nCeOzYsQ7p0htvvBEbNmzAbbfdhr179zr0FomPj8eUKVP8/j+Js4hwl/MQhC+UlhR66sDqifLycv7hhx/m8/Pz+aioKD45OZkfP368qnJeOd5Ke8WvWktLC//oo4/yAwcO5BMSEvi4uDh+4MCBbkszV69ezV900UXSfgMGDOBfe+01n8dRV1fHz549m8/Pz+dNJhOflpbGjxo1in/ppZekjpxiaemLL77Iv/zyy3xOTg4fFRXFjx49mt++fbvD8zmX9i5dupS/4oor+M6dO/Mmk4nv3Lkzf/3117uUE5eVlfG33norn5aWxptMJr5///5uO6pWVFTwN998M5+YmMgnJSXxN998M79161a3HVgPHz7MT5s2jc/MzOSNRiOflZXFT5o0if/qq68c9ktLS+NHjBjh81x565rb2trKP//883zfvn35qKgoPiUlhR86dCj/1FNP8TU1NQ77PvroozwA/vnnn3fYnp+fzwPgDx8+7PNY1DBixAg+PT2dt1gsHvcRvzfubtOnT5f2Ez8L8m3ens/5e9i1a1ePr+Nv11fi7IPjeR9xX4Ig2h3Hjh1DXl4eXnzxRfz5z38O9+EElT179qBv37748ccfcdlll4X7cAiCUAB5RgiCaFcsW7YMI0eOJCFCEBqCPCME4YPTp0/DarV6vN9kMiE1NbUNj4jwxsyZMzFz5sxwHwZBECogMUIQPjjnnHOkJl3uGDt2LJYvX952B0QQBNHOIM8IQfjgjz/+QFNTk8f7U1JSMHTo0DY8IoIgiPYFiRGCIAiCIMIKGVgJgiAIgggrmvCM2Gw2nDp1CgkJCT5bMxMEQRAEERnwPI+6ujp07tzZ66KLmhAjp06dcliYiiAIgiAI7XDixAlkZ2d7vF8TYkRsHX3ixAkkJiaG+WgIgiAIglBCbW0tcnJyfK7irAkxIqZmEhMTSYwQBEEQhMbwZbEgAytBEARBEGGFxAhBEARBEGGFxAhBEARBEGFFE54RgiAI4uzEarXCbDaH+zAIDxiNRuj1+oCfh8QIQRAEEXHwPI/S0lJUV1eH+1AIHyQnJyMzMzOgPmAkRgiCIIiIQxQi6enpiI2NpYaXEQjP82hsbER5eTkAoFOnTn4/F4kRgiAIIqKwWq2SEOnQoUO4D4fwQkxMDACgvLwc6enpfqdsyMBKEARBRBSiRyQ2NjbMR0IoQXyfAvH2kBghCIIgIhJKzWiDYLxPJEYIgiAIgggrJEYIgiAIIkgUFhbiwQcf9Hh/bm4u5s2b12bHoxVUiZE333wTAwYMkNaIGTlyJH7++WeP+8+fPx8cxzncoqOjAz5ogiAIgtAiGzduxF133RXuw4g4VFXTZGdn47nnnkOPHj3A8zwWLFiAK664Alu3bkXfvn3dPiYxMRH79++X/qYcIBGpNFmaEGOICfdhEATRjunYsWO4DyEiURUZmTx5Mi699FL06NEDPXv2xLPPPov4+HisW7fO42M4jkNmZqZ0y8jICPigCSLY7K/cj/M/PR+vbnk13IdCEITGsVgsmDVrFpKSkpCWloa//e1v4HkegGuapqioCFdccQXi4+ORmJiIqVOnoqysTLr/H//4BwYNGoT3338fXbp0QXx8PO69915YrVa88MILyMzMRHp6Op599lmHY3jllVfQv39/xMXFIScnB/feey/q6+ul+48fP47JkycjJSUFcXFx6Nu3LxYtWgQAqKqqwo033oiOHTsiJiYGPXr0wAcffBDCMxZAnxGr1Yovv/wSDQ0NGDlypMf96uvr0bVrV9hsNgwZMgT/+te/PEZRRFpaWtDS0iL9XVtb6+9hEoQiDlQdQKutFTvP7Az3oRAE4Qae59Fktrb568YY9aoj+gsWLMDtt9+ODRs2YNOmTbjrrrvQpUsX3HnnnQ772Ww2SYisWLECFosFM2fOxHXXXYfly5dL+x0+fBg///wzfvnlFxw+fBjXXHMNjhw5gp49e2LFihVYs2YNbrvtNowfPx7Dhw8HAOh0Ovz73/9GXl4ejhw5gnvvvRePPfYY3njjDQDAzJkz0draipUrVyIuLg579uxBfHw8AOBvf/sb9uzZg59//hlpaWk4dOgQmpqaAjiLvlEtRnbu3ImRI0eiubkZ8fHx+Pbbb9GnTx+3+xYUFOD999/HgAEDUFNTg5deegmjRo3C7t27kZ2d7fE15syZg6eeekrtobVrSupLsKlsEy7JuwRGnTHch9N+4cN9AARBuKPJbEWfvy9u89fd8/QExJrUDZU5OTmYO3cuOI5DQUEBdu7ciblz57qIkaVLl2Lnzp04evQocnJyAAAffvgh+vbti40bN+Kcc84BwETL+++/j4SEBPTp0wcXXHAB9u/fj0WLFkGn06GgoADPP/88li1bJokRuYk2NzcX//znPzFjxgxJjBQVFeHqq69G//79AQDdunWT9i8qKsLgwYMxbNgw6fGhRnU1TUFBAbZt24b169fjnnvuwfTp07Fnzx63+44cORLTpk3DoEGDMHbsWHzzzTfo2LEj3n77ba+vMXv2bNTU1Ei3EydOqD3MdsfLm1/G/63+P6wpXhPuQ2mX2Hgb+wlbmI+EIAitM2LECIdoysiRI3Hw4EFYrY6Rnb179yInJ0cSIgDQp08fJCcnY+/evdK23NxcJCQkSH9nZGSgT58+0Ol0DtvEtuwA8Ntvv2HcuHHIyspCQkICbr75ZlRUVKCxsREAcP/99+Of//wnzjvvPDz55JPYsWOH9Nh77rkHn332GQYNGoTHHnsMa9aEftxRHRkxmUzIz88HAAwdOhQbN27Eq6++6lNgAGx1v8GDB+PQoUNe94uKikJUVJTaQ2vX1LTUAABqWyllFQokMcKTGCGISCTGqMeepyeE5XXDjdHoGA3nOM7tNpuNXb+OHTuGSZMm4Z577sGzzz6L1NRUrF69GrfffjtaW1sRGxuLO+64AxMmTMBPP/2EX3/9FXPmzMHLL7+M++67DxMnTsTx48exaNEiLFmyBOPGjcPMmTPx0ksvhex/DLjPiM1mc/B3eMNqtWLnzp0BLaZztiKan2iwDA28kJ8RzzNBEJEFx3GINRna/OZPBej69esd/l63bh169Ojhsm5L7969ceLECYfo/549e1BdXe3R/qCEzZs3w2az4eWXX8aIESPQs2dPnDp1ymW/nJwczJgxA9988w0eeeQRvPvuu9J9HTt2xPTp0/Hxxx9j3rx5eOedd/w+HiWoiozMnj0bEydORJcuXVBXV4eFCxdi+fLlWLyY5fGmTZuGrKwszJkzBwDw9NNPY8SIEcjPz0d1dTVefPFFHD9+HHfccUfw/5N2jpg+IDESGkQRwpNphCCIACkqKsLDDz+Mu+++G1u2bMFrr72Gl19+2WW/8ePHo3///rjxxhsxb948WCwW3HvvvRg7dqzk1/CH/Px8mM1mvPbaa5g8eTL++OMPvPXWWw77PPjgg5g4cSJ69uyJqqoqLFu2DL179wYA/P3vf8fQoUPRt29ftLS04Mcff5TuCxWqxEh5eTmmTZuGkpISJCUlYcCAAVi8eDEuuugiAOwNkOewqqqqcOedd6K0tBQpKSkYOnQo1qxZE5DiO1uhGXtoIbFHEESwmDZtGpqamnDuuedCr9fjgQcecNvojOM4fP/997jvvvswZswY6HQ6XHLJJXjttdcCev2BAwfilVdewfPPP4/Zs2djzJgxmDNnDqZNmybtY7VaMXPmTJw8eRKJiYm45JJLMHfuXADMjjF79mwcO3YMMTExGD16ND777LOAjskXHK+BUa62thZJSUmoqalBYmJiuA8nLEz/eTq2lG/BP0b+A1f3vDrch9Pu+GL/F3hm3TMYkDYAn1z2SbgPhyDOapqbm3H06FHk5eVR124N4O39Ujp+09o0GkFMH1C1R2igNA1BEET4IDGiEcT0gQYCWZqE0jQEQRDhg8SIRqBqj9BCpb0EQRDhg8SIRpBKeylNExIoTUMQBBE+SIxoBJq5hxaKPBEEQYQPEiMagTwjoYXawRMEQYQPEiMag9IIoUFK05DYIwiCaHNIjGgEStOEFqqmIQiCCB8kRjSCOFjSzD00kIGVIAgifJAY0QhUTRNayMBKEAQRPkiMaATyNIQWSoMRBKEFcnNzMW/evHAfRtAhMaIRpDQNpRFCAqVpCIIgwgeJEY0gpWlo5h4SyMBKEEQwKCwsxH333YcHH3wQKSkpyMjIwLvvvouGhgbceuutSEhIQH5+Pn7++WcAwLBhw/DSSy9Jj58yZQqMRiPq6+sBACdPngTHcTh06BAKCwtx/PhxPPTQQ+A4DhzHheV/DAUkRjQCpRFCC6XBCCLC4XmgtaHtb35cExYsWIC0tDRs2LAB9913H+655x5ce+21GDVqFLZs2YKLL74YN998MxobGzF27FgsX75c+Bd5rFq1CsnJyVi9ejUAYMWKFcjKykJ+fj6++eYbZGdn4+mnn0ZJSQlKSkqCeYbDiiHcB0AoQzJYUhohJFDTM4KIcMyNwL86t/3r/t8pwBSn6iEDBw7EE088AQCYPXs2nnvuOaSlpeHOO+8EAPz973/Hm2++iR07dqCwsBD//e9/YbVasWvXLphMJlx33XVYvnw5LrnkEixfvhxjx44FAKSmpkKv1yMhIQGZmZnB/T/DDEVGNAJ1YA0tVE1DEESwGDBggPS7Xq9Hhw4d0L9/f2lbRkYGAKC8vByjR49GXV0dtm7dihUrVmDs2LEoLCyUoiUrVqxAYWFhWx5+WKDIiEYgz0hooTQNQUQ4xlgWpQjH66p9iNHo8DfHcQ7bRK+HzWZDcnIyBg4ciOXLl2Pt2rW46KKLMGbMGFx33XU4cOAADh48KEVG2jMkRjQCGSxDC6VpCCLC4TjV6RKtMHbsWCxbtgwbNmzAs88+i9TUVPTu3RvPPvssOnXqhJ49e0r7mkwmWK3WMB5taKA0jUagGXtoIbFHEES4KCwsxOLFi2EwGNCrVy9p2yeffOISFcnNzcXKlStRXFyMM2fOhONwQwKJEY1AaZoQQ1qPIIgwMXr0aNhsNgfhUVhYCKvV6uIXefrpp3Hs2DF0794dHTt2bOMjDR2UptEI0syd0gghgUqnCYIIBqLxVM6xY8dctsmj3ampqbDZHK89U6ZMcRsRHzFiBLZv3x7wcUYaFBnRCGSwDC2UpiEIgggfJEY0ApWehhZqB08QBBE+SIxoBKr2CC0k9giCIMIHiRGNQE3PQgt5RgiCIMIHiRGNIM7cabAMDZLYozQNQRBEm0NiRCOQp6FtoMgTQRBE20NiRCNQGiG00PklCIIIHyRGNAIZLEMLGYQJgiDCB4kRjSB1YKXBMiRI6S/SegRBEG0OiRGNQNU0oYXEHkEQRPggMaIRxEGSDKyhgTwjBEEQ4YPEiEaghfJCi1zkUfSJIIhg0draGu5D0AQkRjQCGVhDi1zkUfSJIAh/KSwsxKxZs/Dggw8iLS0NEyZMwK5duzBx4kTEx8cjIyMDN998M86cOQMA+PHHH5GcnAyr1QoA2LZtGziOw+OPPy495x133IGbbropLP9PW0FiRCNQU67QIj+vFH0iiMiD53k0mhvb/ObPBHDBggUwmUz4448/8Nxzz+HCCy/E4MGDsWnTJvzyyy8oKyvD1KlTAQCjR49GXV0dtm7dCgBYsWIF0tLSHFb/XbFiBQoLC4NxGiMWQ7gPgPCN/MtAA2VocIiMUPSJICKOJksThi8c3uavu/6G9Yg1xqp6TI8ePfDCCy8AAP75z39i8ODB+Ne//iXd//777yMnJwcHDhxAz549MWjQICxfvhzDhg3D8uXL8dBDD+Gpp55CfX09ampqcOjQIYwdOzao/1ekoSoy8uabb2LAgAFITExEYmIiRo4ciZ9//tnrY7788kv06tUL0dHR6N+/PxYtWhTQAZ+NyAdKEiOhwUHwUUWNZimuL0ZpQ2m4D4M4yxk6dKj0+/bt27Fs2TLEx8dLt169egEADh8+DAAYO3Ysli9fDp7nsWrVKlx11VXo3bs3Vq9ejRUrVqBz587o0aNHWP6XtkJVZCQ7OxvPPfccevToAZ7nsWDBAlxxxRXYunUr+vbt67L/mjVrcP3112POnDmYNGkSFi5ciClTpmDLli3o169f0P6J9o6DuZLSNCGBDKzax2w1Y+r/psKoM+L3qb9Dx1EWuj0RY4jB+hvWh+V11RIXFyf9Xl9fj8mTJ+P555932a9Tp04AmM/k/fffx/bt22E0GtGrVy8UFhZi+fLlqKqqavdREUClGJk8ebLD388++yzefPNNrFu3zq0YefXVV3HJJZfg0UcfBQA888wzWLJkCV5//XW89dZbARz22YV8cKSBMjRQ9En7NFoaUdtaCwCw2Cww6U1hPiIimHAcpzpdEgkMGTIEX3/9NXJzc2EwuB9yRd/I3LlzJeFRWFiI5557DlVVVXjkkUfa8pDDgt9TB6vVis8++wwNDQ0YOXKk233Wrl2L8ePHO2ybMGEC1q5d6+/LnpXI0wY0UIYGB8FH0SdNQt4qIhKZOXMmKisrcf3112Pjxo04fPgwFi9ejFtvvVWqoElJScGAAQPwySefSEbVMWPGYMuWLThw4MBZERlRLUZ27tyJ+Ph4REVFYcaMGfj222/Rp08ft/uWlpYiIyPDYVtGRgZKS73ndFtaWlBbW+twO5uhstPQQwZW7UOinYhEOnfujD/++ANWqxUXX3wx+vfvjwcffBDJycnQ6exD8NixY2G1WiUxkpqaij59+iAzMxMFBQVhOvq2Q3U1TUFBAbZt24aamhp89dVXmD59OlasWOFRkPjDnDlz8NRTTwXt+bQOpWlCj0NpLxlYNQmJdiISkJfkivTo0QPffPON18fNmzcP8+bNc9i2bdu24B1YhKM6MmIymZCfn4+hQ4dizpw5GDhwIF599VW3+2ZmZqKsrMxhW1lZGTIzM72+xuzZs1FTUyPdTpw4ofYw2xXUAyP0kODTPpSmIQjtErDd3GazoaWlxe19I0eOxNKlSx22LVmyxKPHRCQqKkoqHxZvZzMO5kqatYcECvFrHzIhE4R2UZWmmT17NiZOnIguXbqgrq4OCxcuxPLly7F48WIAwLRp05CVlYU5c+YAAB544AGMHTsWL7/8Mi677DJ89tln2LRpE955553g/yftGCo7DT0U4tc+9D0hCO2iSoyUl5dj2rRpKCkpQVJSEgYMGIDFixfjoosuAgAUFRU5GHJGjRqFhQsX4oknnsD//d//oUePHvjuu++ox4hKqNIj9FAqTPtQBJEgtIsqMfLf//7X6/3ujDvXXnstrr32WlUHRThC4efQQ54R7UPfk/YHfRe1QTDeJ2pRqAGo7DT00ECmfUhQth+MRiMAoLGxMcxHQihBfJ/E980faKE8DUAphNBDLfe1D5mQ2w96vR7JyckoLy8HAMTGxoLjuDAfFeEMz/NobGxEeXk5kpOTodfr/X4uEiMagDwjoYdm1dqHTMjtC7EFhChIiMglOTnZZ8sOX5AY0QCUpgk9ZH7UPtRnpH3BcRw6deqE9PR0mM3mcB8O4QGj0RhQRESExIgGoO6goYcEn/Yh30/7RK/XB2WwIyIbMrBqAJrxtS0kRrSJXKjTe0gQ2oLEiAagi2zooTSN9nEQ7fQeEoSmIDGiAciYF3qoEkP7UJqGILQLiRENQGma0EMVS9qHIogEoV1IjGgAWnMj9FBpr/Yh0U4Q2oXEiAagNE3ooTSN9iHfD0FoFxIjGoBmfKGHzrH2ofJsgtAuJEY0ABnzQg9FnLQPLZtAENqFxIgGoHVTQg8JPu1DaRqC0C4kRjQAhZ9DDw1k2oe+JwShXUiMaABqBx96HAYvGsc0Cfl+CEK7kBjRADTjCz3kN9A+VBFFENqFxIgGoD4joYfSNNqHSuAJQruQGNEAtOZG6CHBp30oTUMQ2oXEiAagNE3ooVm19qGKKILQLiRGNAD5GUIPzaq1D0W3CEK7kBjRALSIW+ghwad9yPdDENqFxIgGoPBz6KFUmPah7wlBaBcSIxqABsrQQ11utQ+tvEwQ2oXEiAagpmehh2bV2of6jBCEdiExogFoxhd66BxrH6qIIgjtQmJEA8hnfDRQhgYayLQPVUQRhHYhMaIBqEog9FA1jfahVBtBaBcSI1pANlGni2xooPJp7UMRRILQLiRGNABFQ0IPmR+1Dy2bQBDahcSIBqDwc+ih8mntQ98TgtAuJEY0ABnz2gB5Koxm1ZqEBCVBaBcSIxqA1twIPeQ30D5kQiYI7UJiRANQ2WnooXOsfajqjCC0C4kRDUBpmraFzrE2oTQNQWgXEiMawCGFQLP2kEADmfYh0U4Q2oXEiAagi2zooUoM7UPl2QShXVSJkTlz5uCcc85BQkIC0tPTMWXKFOzfv9/rY+bPnw+O4xxu0dHRAR302QaZK0MPNT3TPuT7IQjtokqMrFixAjNnzsS6deuwZMkSmM1mXHzxxWhoaPD6uMTERJSUlEi348ePB3TQZxvUzCn0UCWG9qEIIkFoF4OanX/55ReHv+fPn4/09HRs3rwZY8aM8fg4juOQmZnp3xES5GdoA2hWrX0o1UYQ2iUgz0hNTQ0AIDU11et+9fX16Nq1K3JycnDFFVdg9+7dgbzsWQfN2kMLz/N0jtsB1I+HILSL32LEZrPhwQcfxHnnnYd+/fp53K+goADvv/8+vv/+e3z88cew2WwYNWoUTp486fExLS0tqK2tdbidzZCfIbQ4n1MayLQJ9RkhCO2iKk0jZ+bMmdi1axdWr17tdb+RI0di5MiR0t+jRo1C79698fbbb+OZZ55x+5g5c+bgqaee8vfQ2h3OM3We58FxXJiOpv3hLD5I8GkTStMQhHbxKzIya9Ys/Pjjj1i2bBmys7NVPdZoNGLw4ME4dOiQx31mz56Nmpoa6XbixAl/DrPd4Dw40oU2uDjPoun8ahNK0xCEdlElRniex6xZs/Dtt9/i999/R15enuoXtFqt2LlzJzp16uRxn6ioKCQmJjrczmacL6wUgg4uFBlpH1BkhCC0i6o0zcyZM7Fw4UJ8//33SEhIQGlpKQAgKSkJMTExAIBp06YhKysLc+bMAQA8/fTTGDFiBPLz81FdXY0XX3wRx48fxx133BHkf6X94nJhpbEyqLhLgxHagyqiCEK7qBIjb775JgCgsLDQYfsHH3yAW265BQBQVFQEnc4ecKmqqsKdd96J0tJSpKSkYOjQoVizZg369OkT2JGfRbikESgyElQoDdY+oD4jBKFdVIkRJTPG5cuXO/w9d+5czJ07V9VBEY64pGnoQhtU6Py2D6gdPEFoF1qbRgO4eBoojRBUXNI0FOLXJJSmIQjtQmJEAzinZehCG1yoz0j7gNI0BKFdSIxoAOcLK11ogwud3/YBVdMQhHYhMaJB6EIbXKi0t31Aq1sThHYhMaIBSHyEFpc0GA1kmoRWtyYI7UJiRANQGiG0UFO59gGlaQhCu5AY0QBUehpaqM9I+8ChmoaiWwShKUiMaACXag/yNAQVEh/tA/n3gt5TgtAWJEY0ALUrDy2UBmsfOKRpKNVGEJqCxIgGoDRC20LnV5tQmoYgtAuJEQ1AHUJDC0We2gfU9IwgtAuJEQ1ABtbQQmKvfUBr0xCEdiExogGoHXxooTRY+0Au2uk7QhDagsSIBqDISGih89s+oD4jBKFdSIxoAPI0hBZK07QPSIwQhHYhMaIBKI0QWqgdfPtA/j2h95AgtAWJEQ1AC7mFGKfTST0qtAn1GSEI7UJiRANQmia00PltH1CfEYLQLiRGNIDzLI/SNMGF0jTtA+ozQhDahcSIFqA0QkihVXvbB9RnhCC0C4kRDUBphNDishAhnV9N4pCmIV8VQWgKEiMagJqehRZaKK99QGkagtAuJEY0ADXlCi1UrdQ+oD4jBKFdSIxoAEojhBbq49I+kEcQ6TtCENqCxIgGoA6hoYU8Oe0DhzQNmZAJQlOQGNEA5GkILS7nlwYyTUJpGoLQLiRGNAhdaIMLpcHaB5SmIQjtQmJEA1CaJrSQgbV9QNU0BKFdSIxoAPI0hBZKg7UPaG0agtAuJEY0AFV7hBZK07QP5O8bvYcEoS1IjGgASiOEFkqDtQ+oHTxBaBcSIxqA0gihhSJP7QNK0xCEdiExogFc0gg0cw8qJPbaB5SmIQjtQmJEA9BgGVooDdY+oD4jBKFdSIxoADJYhhY6v+0D6jNCENqFxIgGIINlaKHIU/uA2sEThHYhMaIBaNXe0EJpmvYBpWkIQruoEiNz5szBOeecg4SEBKSnp2PKlCnYv3+/z8d9+eWX6NWrF6Kjo9G/f38sWrTI7wM+G6GmZ6GFzm/7QP4+0ntIENpClRhZsWIFZs6ciXXr1mHJkiUwm824+OKL0dDQ4PExa9aswfXXX4/bb78dW7duxZQpUzBlyhTs2rUr4IM/W6DS09BC57d9IH8f6T0kCG1hULPzL7/84vD3/PnzkZ6ejs2bN2PMmDFuH/Pqq6/ikksuwaOPPgoAeOaZZ7BkyRK8/vrreOutt/w87LMLSiOEFpc0GPkNNAn1GSEI7RKQZ6SmpgYAkJqa6nGftWvXYvz48Q7bJkyYgLVr13p8TEtLC2prax1uZzOURggtLgMXnV5NQmkagtAufosRm82GBx98EOeddx769evncb/S0lJkZGQ4bMvIyEBpaanHx8yZMwdJSUnSLScnx9/DbBc4D5Y06wsuLtU0dH41Ca3aSxDaxW8xMnPmTOzatQufffZZMI8HADB79mzU1NRItxMnTgT9NTSF0ySPLrTBhTwj7QNam4YgtIsqz4jIrFmz8OOPP2LlypXIzs72um9mZibKysoctpWVlSEzM9PjY6KiohAVFeXPobVLnGfq5BkJLi6eHArxaxKHdvD0HSEITaEqMsLzPGbNmoVvv/0Wv//+O/Ly8nw+ZuTIkVi6dKnDtiVLlmDkyJHqjvQshjwjoYWayrUPqM8IQWgXVZGRmTNnYuHChfj++++RkJAg+T6SkpIQExMDAJg2bRqysrIwZ84cAMADDzyAsWPH4uWXX8Zll12Gzz77DJs2bcI777wT5H+l/UJphNBC57d9QGKEILSLqsjIm2++iZqaGhQWFqJTp07S7fPPP5f2KSoqQklJifT3qFGjsHDhQrzzzjsYOHAgvvrqK3z33XdeTa+EI9SBNbRQmqZ9IBeV9B4ShLZQFRlR8gVfvny5y7Zrr70W1157rZqXImSQ+AgtlKZpH1CfEYLQLrQ2jQagyEhooYXy2gfUZ4QgtAuJEQ1Anoa2hc6vNqE+IwShXUiMaABKI4QWOr/tA+ozQhDahcSIBqDS3tDi0seFzq8mcUjTkKAkCE1BYkQDuKRpyJwXVETxoef0AOj8ahVK0xCEdiExogHEi6yO0zn8TQQHOr/tA0rTEIR2ITGiAcSLrDhY0oU2uIjn16Bjle50frUJVdMQhHYhMaIBnNMIlA8PLuIgJkVG6PxqEoc0DaXaiDCzsXQjvj34bbgPQzP4tVAe0baIg6XkaaCZe0igNI22oXbwRCTxxOoncKrhFM7tdC6y4rPCfTgRD0VGNIA4U9frhMgIDZZBRRy4DBylabQMtYMnIok6cx0AoL61PsxHog1IjGgAl2oPGiyDihR50lEaTMtQO3gikrDarOwnbw3zkWgDEiMagDwNocW5mobEnjahNA0RSYifQfosKoPEiAaQqj2ENAKFoIOLlAbjKA2mZeTvG72HRLgRIyIUGVEGiRENIM3cdcLMnULQQcXFIEznV5NQnxEikqDIiDqomkYDkGck+Mz77QBWHjiNCwrS0RTbDMDeZ4Rm1dqE2sETkQLP81JExGKzhPlotAGJkQjll12l2HisEvtL61BqagJgFyNEYJyqbsK/lx6EjQe2FFUjKu0ITB3Jk6NlnAUkCXYinJB/ST0kRiKQtYcrMOPjzdLfcd1aoYuyV3vQhzswPtt4AjYeKMhIQHy0ATvrycCqdZzfM3oPiXAi//yRZ0QZ5BmJQH7ccQoAMKxrCi4f2FnargMNloFisdrw+cYiAMCsC/Px9s1DIVhxYLZwAOj8ahFaeZmIJCy8PTUjlvgS3iExEmFYbTwW7y4DANw3rgf+eWU/6HTswtrYyn5SGsF/lu4rR1ltCzrEmTChbybS4qPQIz0OAFDdSLldreKSpiETMhFGKE2jHhIjEcaWoiqcqW9BQrQBI7t1QGK0EfHRLD1zps4MgGZ9gbBwPYuKXDMsGyYD+/j3z04EYBcjdPHQHpSmISIJeWqG0jTKIDESYfy8sxQAcFHvDGmwTIhi1p5mpkXoQusn5bXNWHnwNADg+nO6SNs7JUUDAGw2SoNpFXfvGYl2IlzYbBQZUQuJkQiC53ks3s3EyCX9Mu13cMJFlSdPQyDsPlULngd6ZsQjNy1O2i6mvXieqmm0irv3jL4nRLiQe0bkvxOeITESQewsrkFxdRNiTXqM6dlR2i5eVHl6uwLiQBlbuKpHRoLDdvugxcQezai1hzvhQb4RIlw4eEZs9DlUAo1uEcTv+8oBAIUFHRFttPcUkQZHntIIgXCgjK2e2TPdUYxIs2o6v5qF0jREJEGlveohMRJBHCxng+WQLikO210GS5rx+cXBchYZ6ZkR77DdPmhRmkaruBMeJCqJcCHvukpiRBkkRiKII6cbAAB5Mj8DIL+oCoMlzfhUY7PxOChERjymaXg6v1rFnUAnMUKECyrtVQ+JkQjBZuNx7AwTI906Os3cpZk6eRr8pbi6CU1mK0x6HXI7xDrcJw5kvHB+KfKkPdymaSjCRYQJKu1VD4mRCKG0thlNZisMOg7ZKTEO90kGVkrT+I1oXu3WMQ4GvePHnjw52qbZbMW/lx5w2U7vIxEuyMCqHhIjEYKYounSIRZG58HSyTNCkRH1HPCQogHkM2hmGqbzqy0+WV+Ej9Ydc9lOYoQIF3LPCJX2KoPESIRw9AwbLLs5+UUAV88IXWTVc1CIjBQ4mVcBuWdESINReF8z8DyPLzedAJx6xYj3EUQ4IM+IekiMRAiHT7v3iwCuaQQaLNVzoNx9jxGAxJ6W2VVci32ldTAamJCETIxQOpMIFyRG1ENiJEI4KppXKTISdGw2HoeEsumebsSIBKXBNMeXm08AAMb0TBO2yMQIfU+IMEEGVvWQGIkQjghpGueyXkDuGaFqGn84UdWIZrMNUQYduqTGutzvbBCmyJM2aDZb8d3WYgDAxH7pbCPPgafvCRFmHMSIjcSIEkiMRAAtFitOVjUB8J6mEdvBU/hZHaJ5tXvHeOh1nMv9FHnSJkv2lKG22YLOSdEY3CVZ2MpBLIGn95EIF3IBQpERZZAYiQCOVzSC59nqvGnxJpf7qSlXYByvYCmw7umuQs8BmlFrimX72fIJVwzOAsfJevGQEZkIM+QZUQ+JkQjgiGRejQPHuZm5w0mM0EVWFaU1zQCATknRbu93iYxQ5EkTiD6ggdnJkoDkKDJCRAAOq/baqLRXCSRGIgBvfhEAsGsPSiP4Q2ktEyMZiT7ECEWeNIPclJyfHu8kKEmMEOGFIiPqUS1GVq5cicmTJ6Nz587gOA7fffed1/2XL18OjuNcbqWlpf4ec7vjiJeyXkAeGaGLrD+U17YAADISo9zeb4802SNPJEgim1M1TWhstcKo59C1Q6wsmsVRuo0IOyRG1KNajDQ0NGDgwIH4z3/+o+px+/fvR0lJiXRLT09X+9LtFnFNGk+REfuHWd9GR9S+ECMjmR4iI5JBWN4wi1JhEY24wnVeWhyMep37NA2l24gwQQZW9RjUPmDixImYOHGi6hdKT09HcnKy6sedDYiDZefkGJf75LM7ntZOUQ3P8yjzlaaBo2cEYOdYx1EWM1I5JLb3T2d9Y+zfCfKMEOGH+oyop82utoMGDUKnTp1w0UUX4Y8//vC6b0tLC2prax1u7RWe53G6jqUR0hNc0wiOM3S6yKqlpsmMFgs7X+ke0jTO7eABioxEOnK/CGAXlBx05P0hwg71GVFPyMVIp06d8NZbb+Hrr7/G119/jZycHBQWFmLLli0eHzNnzhwkJSVJt5ycnFAfZtiobbZIg2VHN2LEQXjQRVY1YtQpJdaIKIP7NJf9fNK6JlrhoNTen4kReZqGJ9FOhBnyjKhHdZpGLQUFBSgoKJD+HjVqFA4fPoy5c+fio48+cvuY2bNn4+GHH5b+rq2tbbeC5HQdGywTow2INroOlo6DIpX2qqVMMq+6T9EArqsiA3QBiWR4npc8I1JkxF2ahjwjRJiQl/NSmkYZIRcj7jj33HOxevVqj/dHRUUhKsp9SL29US6kaNxFRQAn4UGeEdWUCT1GMj30GAFc28EDJPgimfK6FtQ1W6Dj7KZv8T3kOF3IqmlO1J1A57jO0OvISE54R36NJjGijLA49LZt24ZOnTqF46UjDrtfxFdDLlDTMz+QzKsezi9AaRqtcVAwr+Z2iJNSb+J3gpOV9gZTtK85tQaXfnMpXtn8StCek2i/UJpGPaojI/X19Th06JD099GjR7Ft2zakpqaiS5cumD17NoqLi/Hhhx8CAObNm4e8vDz07dsXzc3NeO+99/D777/j119/Dd5/oWHEHhg+zZUA5cL9QGp45iUy4rwQIUDnOJIR/SL5svb+UmQkRGma47XHAQBFtUVBe06i/ULVNOpRLUY2bdqECy64QPpb9HZMnz4d8+fPR0lJCYqK7F/Y1tZWPPLIIyguLkZsbCwGDBiA3377zeE5zmbKBc9Ix3jlaRqatSvHXtbrOe3nro8L+Q0iF7GSRjSvAk5pGgQ/TSNWRMjbfBOEJxz6jFA1jSJUi5HCwkKvX/L58+c7/P3YY4/hscceU31gZwtSmsZTd1CHc80GSxoolSMaWD01PAPk55hzs42INETzqthjBHCspglFmkac3dLAQiiBIiPqoa5OYabcl2dELjyozbVqfK1LA9jPsY48I5qgqKIRAJAr61js0GckBOlMsTqCBhZCCeQZUQ+JkTDjs5rGTWkvfbiVYbHacKZeQWmvcI51HKVpIh2rjcdp4T2Vr8JsT9PYPSPBNHqLIoRWYCWUQE3P1ENiJMx4674KOBlYqZpGFafrW8DzgEHHoUOcyeN+FBnRDhX1LbDaeOg4OLynkqCELjRpGmFAocgIoQRK06iHxEgYaTZbUdNkBuA5TeOuHTwNlMooFXqMpCdEQafjPO4nDWQ6HXg++LNqIniIHqCOCVEw6F2b1HFcaDqwisZVmuUSSqA0jXpIjIQRMSpiMuiQGOPeS+yuzwh9uJUhdV/1UtYL2M+nThbip3McmXha9NDeZ4SqaYjwQ6v2qofESBgRc98d46OEXLcr9ioB2UWWZu2KUNLwDLCfTx0XGvMjETzK6sRol+N76iAo+eD3GRG9IuQZIZRAaRr1kBgJI74angEejHmUplGEKEa8tYIH5AZW+0BGRCb2tYYcvzPu+oyEpLSXBhZCAWRgVQ+JkTByus7uafCENGuHDmJAhCo9lCGW9XoTe4BsVg1XDwIRWZR7StPIDawhEO1SaS8NLIQCyDOiHhIjYeS0j7JewLkhF6UQ1HCmvhWAZ3OwiCT4dJSmiXQ8ddSV+oxwXEi8VRQZIdRAnhH1kBgJI74angGyslNK06imsoGdX29lvYD9fOpDuOIrERxKpdSmJ89IaLxV1GeEUAN5RtRDYiSMlPvoMQJ4WHODDKyKqGpgZdMpPsSIu2oaOseRiZimcW7v7+D7oQ6sRJihNI16SIyEESVpGnFM1IVozY32TGUDS9OkxvoQI3CdVdM5jjxaLTZUCO+ps2fEvmpviJqeUWSEUAFFRtRDYiSMlHsoU5Qjz4XzlKZRTFOrFU1mdhFIiTN631kUfHIxQibhiEMshTfqOaTEOr6n4vulD9GqvWRgJdRAq/aqh8RImLDaeLvBUklpL/UZUUVlIzu3Rj2H+Cjvi1OL51gv68BKpzjyEM2r6QnRLn15pH48nM7egTWIgpKanhFqkEdDKMqqDO9XaSJk1DSZYbWxC2iqF0+Dux4Y9OH2TZWYookzeWwoJ+LOJEznOPIo91BJAzgZWIP4PWlosWDz8Sq0UmSEUIH8s0dpGmWQGAkTVcLMPSHaAKPec4BKanNNfgZViH6RFB9+EcCpmobSNBGLveGZa1pTim4Fseqs1WLDzf9djy1F1UjJKweiaWAhlEFNz9RzVqdpKhtasaWoCnXN5jZ/7SqFg6U9TUOVHmoQxZ63qJOIuz4j5MuJPDytSwOERrT/a9FebCmqBgA0W9g1wspb6bNB+IQMrOo5q8XItW+twVVvrMG2E9Vt/tpVjULZaax3c6XbslO6GPqkQvDj+CrrBWSzalklBgm+yMNbR117ZESWpgkguvW/7acwf80xAMDrNwxGRpL9c0SDC+ELm41Ke9VyVouRrh3iAADHKxrb/LXFmXuygjQC4JQLpxSCT8Tz66vhGSAbyPSUCotkxLWcnHuMADLRHoTolsVqw5M/7AYA3FvYHZMGdEZCtP1SSWKE8AVFRtRzVouRLqmxAICiyrYXI9WNYppGaWREtm6KjQZKX6jxjIjI16ah6FPk4TVNIxm9AxeU209Wo7KhFYnRBjx0UU/2/LAPKNRrhPAFiRH1nNVipGsHQYyEJTKisDsoXD0jNhoofaLGMyIv7aWKpcjF07o0gLzPSOAVUcv3nwYAjO7ZUTKXkxgh1OBQ2kuTR0WQGAFwPKyREWXrpshLe8nP4Bt/PCPMlyMOPnSOI4mmVitqm5kIcF6XBpC/h/qAvyeiGCns2VH+CtJvNNMlfEGlveo5q8WIlKapaAgoLN9saca28m2qZmLSuik+0jSO4efgr0baXlHjGREHLb1OlgqjcxxRiEsnRBt1SHDTxM5enm3vVOzPe3i6rgU7i2sAAGML7GJEHhmhUk3CF7Rqr3rOajGSnRILjgMaWq3Smhf+8PrW13Hzzzfj1+O/Kn6MUgOr47opwjYaKH1SKYk9//qMUGQksqiUxGWU2yZ27gys/nxPVh5gUZG+nRMdlmmwUWSEUAF5RtRzVouRaKNecuYHUlFzquEUAKC0vlTxY6oblQ2W9jbXgc34ziZ4ng/YM0IG1shC6svjYZ0hKbrFBfYeLhfESGFBR4ft5Bkh1ECr9qrnrBYjgD1VcyIA34h4cVKzboU9MqK8moaTShb9Ocqzh9omi9Rq39f5BeRpGhJ8kYqv6iiHPiNiOlNlCbzVxmPVQVGMpDs9P810CeU4r01DkxvfnPViRDKxBhAZEcWI2aask6t85u7LYCl1lgQnpWpooPSOGNKPM+kRbdT73N+h6RmlaSISXx4gh+iWn4Jyb0ktqhvNSIg2YHBOstPz2weXFkvbd2wmtIWzr4gErG/OejEiRkaOVzb4/RxSZERh+Lah1QqzlQ12avqM6DlqeqYEcRadGq+sx4gUGdHrqbQ3Qqlo8C7epZb+AaRp9pbUAgD6ZyXB4LRelHwwaTT77y8jzg6crx90PfENiRGhC2sgvUbEiIjSyIiY/zYZdIjxMXOXPCMUGVGMtGKvwoZnblvuU2QkovD1ngYjMnKwvB4A0DMjwc3z28VIs5kiI4R3nCMhFBnxzVkvRrqmBt5rRG1kpFq2Lo3S5e05jpNKTyn/6J1KH7NoZ8TzaaCVkSMWX++p3TOih7+Ccn9pHQD3YkTuB2skMUL4wEWMUDm4T0iMCJ6R03UtaGr17wOjVoxUKWx4Bjj2GdFz1JBLCaJnRGlkxG5gtUepSPBFFr6qo6Ty7AC66B4oY2KkIDPe5T75YNJEaRrCBxQZUc9ZL0aSY01IjGZNlPxdo0acNakVI4oqPWRiRKejWbsSpJC+wsiIPcTPATylwiIRn9U0QgTR3+hWTZMZJTWs3XwPN5ERq0Oahkp7Ce84t4Cn64lvznoxAgBdpIoa/0ys/qZpFPXAkK1No5c8IzRr94a/aRoWGSHPSCRS5eM7I296xvvxHh4UoiKdk6KRGO06SZBHRpotFBkhvEOREfW49lU+C+maGoddxbX4dEMR9pbUITXOiM7JMejdKRGdk2N8Pt7fNI2v7quA/SLLcXYDKw2U3qlUGxmBLDIiQGmayMFq4+1rOXlqeib6fvxM0+wXxEjPTNeoCM/zDp6RJvKMED4gz4h6SIwA6J7OcsTL9p/GMmGRLADgOODiPhm4c3Q3DMtN9fh4sYrGHwOrUnTQyQysFPLzRqUKTw4gH8jskREKq0YOtU1mCD3sfDc9k72HVhWrpR7wYl51/iw0U58RwgdU2qseEiMApo/sCrPVhvpmCyw2HhX1LThR1YS9JbVYvLsMi3eX4d7C7nh0QoHb6hdJjCjswKrGwOrYZ4TSNEoQPSMdlPYZka9NQysjRxyiuEyINsCod59ZlqJbMs+IRcVsVIqM+KikAYBmC3lGCO9QmkY9JEYAdIiPwl8u6eWy/VB5Hd5ZeQRfbDqJN5YfRnldC+Zc1d/lgqi2A6uY/1aTpgEnXyyPBkpv2M2OyiJPkvlR7jcgwRcxKDEku0vTWBXORnmel8p6C9yZV51ETStFRggfUAdW9ag2sK5cuRKTJ09G586dwXEcvvvuO5+PWb58OYYMGYKoqCjk5+dj/vz5fhxq25OfnoAXrhmI56/uD72Ow1ebT+Lxr3e6DFSqxYiKwVKqpoFOSCNQyM8bFqsNtc3s/VCapnHbMIu63EYMvippAPfvocWq7D08U9+KqkYzOA7IT3ct63WNjJAYIbxDkRH1qBYjDQ0NGDhwIP7zn/8o2v/o0aO47LLLcMEFF2Dbtm148MEHcccdd2Dx4sWqDzZcXHdOF7x901DoOODrLSfxxaYTDveH0sAqb3MtlvZSCsEzNU32gSIpRrknBxDKQqkdfMShZAVm8f0yyMSIUtOgWEnTNTUWMSbXjsgukRErpWkI77h4RlT4l85WVKdpJk6ciIkTJyre/6233kJeXh5efvllAEDv3r2xevVqzJ07FxMmTFD78mFjfJ8M/HlCAV74ZT/+/v1uDMhORu9OiQAC68DqC3k1jYEjA6svxBRYQrTBZX0RT7ibVZPgixwqFERG5KJdXN1aaZpG9Iu46y/CnsdRjNBCeYQvKDKinpD3GVm7di3Gjx/vsG3ChAlYu3atx8e0tLSgtrbW4RYJzBjTHRcUdESLxYb7Pt2KVgu72KlpetZqsaG+RXkaQd5nRKej0l5fVKuspAE8iBHyjEQMSgzJcqM3J4h2i8LZqLhid7e0OLf3O3+vW6wkRgjvkGdEPSEXI6WlpcjIyHDYlpGRgdraWjQ1Nbl9zJw5c5CUlCTdcnJyQn2YitDpOLwydRDS4k04VF6P+WuOwmqzShdCJWKkuoldWDkOSFSSRhDGRB0nK+0lMeIRf8qmxfNpCGCRNSJ0VDaI76kyMSJWnSkt7T0hdF7OEdapcsZ5IKE0DeELKu1VT0R2YJ09ezZqamqk24kTJ3w/qI1IiTNJlTev/nYQp2rqpfsUiRFhsEyKMTo02fKEPE2jB6VpfCH6C5JUREYc+oyQZyTisHtGPAtMaXVrjpPSNBaF7+GJKu9ixPl73UqlvYQPRAFr0Bkc/iY8E3IxkpmZibKyModtZWVlSExMREyM++6mUVFRSExMdLhFElcPycbgLsloaLXihcV7pO1KxEiVgvy3HId28BQZ8Yk/kRGHtWngWyASbYuiahrhe6KDTiqBVxIZ4XkeJypZhDYnxf31iAyshFpE8WHUsesQdWD1TcjFyMiRI7F06VKHbUuWLMHIkSND/dIhQ6fj8NTlfcFxwP92nJS2K2l6Zu8xomywdFi1l8SIT8Q0mBrPiJSm0dsrKSgyEjkoqaZxXFBSFCO+B4CKhlY0ma3gOCDLgxhx/l6bFRrVibMTnuel64dJzz6zFBnxjWoxUl9fj23btmHbtm0AWOnutm3bUFRUBIClWKZNmybtP2PGDBw5cgSPPfYY9u3bhzfeeANffPEFHnrooeD8B2FiQHYyrhjYGRxn/5CZFRjbalQOluJAyXH2yAhABktPVMnSYEqQn0fyjEQmShY+dFjDSbisKammEVfqzkyMRpTBtawXcBU1ZoqMEF6QXztMOpPLNsI9qkt7N23ahAsuuED6++GHHwYATJ8+HfPnz0dJSYkkTAAgLy8PP/30Ex566CG8+uqryM7Oxnvvvaepsl5P3D22O77ftVf6W0maRuyDoXSwlIx50AmDpX27nnN/8TybsVfTqDu/gFBNw1OaJpIwW22oE5rYpSo0sNojI74HAMm8muLeLwK4zmopMkI4s7WoCv/37S6kJ0ShX5b9sySlaSgy4hPVYqSwsNDrrNxdd9XCwkJs3bpV7UtFPL07JWJE9yTsEv5Wkqap9nPmznGcVCUAsBy5HiRGnJE8IypX7AVY0zOeIiMRhZii0fmoPpP6jEAHvYqF8k5WMb9Idqrn1bmdJxkkRgg5VQ2tuPeTLSipacbeEmDFwVYkCKuLSGka8oz4JCKrabTEn87Jkn5vVZCmqW5S5xnxFBkh24h7AkvTyFbtpXbwEUFVg30dJ2/VZw5pGiFiqCRN409kxEJpGkKA53k88uV2lNQ0o1taHJ6+oi96Ztj71YiREZrc+IYWyguQ3p1jgc3sdyWdGdWmaeSeEZ1OB3GMpMHSPWqbnsnNwEaDbNVe8uREBEoXPXRM0yjvwCqW9XbxUNYLuM5q1awGTLRvFqw5ht/3lcNk0OH1G4agT+dEDM2Lxp+E1U6qGthnkNI0viExEiDyD5lVQZqmRmU1jfwi6+wZIVyxl/aqWyQPcFx+nsSIZ/67+ihe+/0gunaIw6DsJNw4oit6emilHihKKmkAp2oaITKiZD2QIh8NzwDXNI3SZR+I9g3P8/hgzTEAwOyJvdCnM2tB0Tk5StqnrNYMfQyJESWQGAkQ+YXJBt8fONWREdEzAvvaNPLthJ1msxVNZvYeJKksnQYAI6VpfPL67wfx0q8HAADVjdXYfqIa32wtxmd3jUDfzklBfz0xMuJrUUmHfjycssiIxWrDqepmAECON8+I0yTDQgMLAeBAWT2OVzTCZNBh6jB7l3C58OBtepdthHvIMxIgjhcq3qdRSeyDkRSjsumZc2kvmUZcEKMieh2HxGhlOtshMqKn0l5vvLn8sCRE7rswH6/+aRAGd0lGXbMF0/67AYdP1/t4BvWIaTdvlTSAU5qGU1baW1LTDKuNh0mvQ0ZCtMf9XNYZocgIAWDx7lIAwOj8NMRF2a830rWD10EcYmnVXt+QGAkQlxCuj1RNdRCangE0WLpDDOknxxjBccpKdB08I7J28IQj1Y2tmPcbEyJ/uaQXHrm4AFcMysKC285Fv6xEVDS0Ytp/N0iLQHqF54FmZYtfKv2+uPue+BoARL9IdkqM5DNxh4uBlWa5BIBf9zAxcnFfx7XX7NdmnSBIKDKiBBIjAWK2OZpWvTU+s9p4qWeCWgOruz4jhCNS2bQfreABx3bwdH4d+WrzSbRYbOjdKREzxnaTtidGG7Hg1nORkxqD4uomzFtywPsTHfoNePM84IU8oHizz9e1dyxWFhlh1TTKIiNiJU22F78I4DrBsCnwhhHtm+LqJuwqroWOA8b1dhQj4gSVrZEkpgxJjPiCxEiAqDG31TbZhYrapmfgRE8DgzwjrqitpAGcPCN6mWeExIiEzcbjo3XHAQDTRnZ1iTp1iI/C01f0AwB8sOYY9pW6iXqYm4HPbgQ+vhoo3w3YLEDZHtf9nBDfU1+REfnaNKJo9/Ue+lqTRsQ1TWMN7vfPZgUOLwMW/xX44FLg0FLfjwkGPA+U7gSW/Qv47SmgaB07FsInS4QUzbCuqUiLj3K4z/6500uREbqe+IYMrAGiJk0jmlfjTHoY9cp0oLvOkgB5RtxR5cciea5pGmE7iT2JlQdP43hFIxKiDbhiUGe3+1xQkI4JfTOweHcZ/v7dbnx+9wi7aLG0AJ/fyKIiOiMQkww0nAYszT5fW+zL4+s9daym0QE8YPXxHiop6wXczGo5G1osNkQbg9B00NwELJwKHF1p31a2G7hnDZCU5flxgXJ6P/DlLUC5TBCufgVIygFu/RlIzvH4UAL4dQ9b/NU5RQPYPy8cdOBBaRqlUGQkQJzTNN4iI/aGZ8pn7iI66BwEDCltV0RzsJrz69IOXiztJbEn8dFaFhW5Zmg2Yk2e5y9/n9wXMUY9NhyrxLojlWyj1Qx8MY0JEUMMMO07oJuwnISlxedriz4gX4ZveZpG7FRs8zHLl7qveml4Brj5TnM2tJiD8P2ztACf38SEiDEOGHQTkNkfaK4Gvr07dFGK0l0sAlO+B9BHAb0mAf2vZcdQcwI4tjo0rxssmqqA5c8Dn0wFTmxo85dvNlux4Sj7fI/v7SpGpM8i7H2LyMDqGxIjAeLaKtqzZ6RaurCq9zSwpmcceJ4GS09IZkcV51dqKgcOBj15Rpwpr2vG7/vLAQA3jejqdd+s5Bicl58GAPbKml8eBw78AhiigRs+B3LPB4xC5Yqlyefr10jt/RWmaeQGVh+RkWJBjHharVfEdYJhQ4slQKFgNQNf3WYXaTd9BUz5D3DtAsAYCxxbBax5LbDXcMeprcCCSUDjGSBzAPDQbuBPnwBXvwcUTGT7NFYE/3WDgc0KrHgRmNsfWP4v4OBi4P0JwK9PsDRgG7GvtA4WG48OcSZ07eAqZO2eER0gLNmhZKmQsx0SIwGixjOitscIIFfZHAxksPRKlYLVXZ1xLAnlpLVpSOwx1hyqAM8DfTsnonvHeJ/7ZwsD+8mqJmDzAmDjewA44JoPgG5j2U4GUYx4j4zwPG+PJvqIjMj78UiRES/fEbPVhrI6NoBlJfvwjDiF2DnOhuZAIiOiENn3I6A3AdcvBLqOYvd16A5MfJ79vvJFoKXO/9dx5sQGYMHlLLKQNQyY/j8gvqP9/tgO7GckipHGSuCTa4Bl/wRa64D0vkCfKQBvY6Ltxwfb7FB2FdcAAPpmJbmt2rNPIGWREbpe+4TESID4I0aUlvUCsmoaTic0c6IOoZ5Qu+4P4LgQoUHH0cXDiTWHzwCAFPHwhShGTKfWAz89wjZe8Feg16X2nQyC4c+HZ6SuxQKrjb0/Pg2svLvIiOf3sLSmGTwPmAw6dPAhXl16B3E2NPsbGbFagK/vAPb+wITIdZ8A3S903GfwzUCHHkBrPbD9M/9ex5ljq4EPpwAttUCXUSxdFpPsuE+kipFDS4G3xwKHf2dRpClvATNWA1MXANd9DIADtn8KnNzUJoez+xQzaPcTOq46I19PTOozQtcTn5AYCRA1YkTtir2Am/4JosGSZu4uSJUXChvKAY5pGnlpL4k9dg7+OMQGplHdOyh6THZKDHpwJ3Hnyf8DbGag9+XAmD877mQQIhE+IiPVwiJ50UadT7Oo2z4jXgYA0S+Sley9xwggNySK+1n984xYLcA3dwJ7vmNG3qkfAT0vdt2P44Bz7mC/b3yPVb0EwqGlwMfXAOYGIG8sSwlFuWnfHxcGMcLzwJmDQF2Z6/aSHUy4fXwVUFMEpOQBd/wGDLoeEM38vScDg25gv/8yO/BzpYDdp1hkpF+W+47DYkpGHhmhJQR8Q9U0AeLSKlpJmsaPPhgcR54GX/hTTeM4o5adX2oHjxOVTSiuboJBx+HcvFRFj8k1VGOB6Tkk8PVA9rnAlW+zwVWOGBkxe/eMiIZkJaXaDp2KxbVpvLyHp6rtYsQX4nc62hCNJkuTf5ERqwX49i5g9zdMiFz3EVBwief9B10PLH0KOL2PRTXyRqt7PZH9vwBf3AxYW4EeFwNTPwSMHv7ntoyM1J4C/ngV2PsjUHuSbYtLB1K6sjRe7Smg8jDbzumAc+8GLvyrexF14d+A3d8BJzcAu74G+l8TssM2W23YV8JSZ/08LH8gXlMSLbUYptuO1aDrtRIoMhIg6gysyvLfcuRrbug4EiPeqFbYIEuOPaQKpH11FXLBZmgUGQH+EFI0g7ske62ikTA3I//3O9CZq8RBWxaap34KmNxUqij0jFSpiCTKQ+NSnxGb5/ewWBAjnZM9t4EXESMjJr3wueJsaDarECPmJuDL6Wyg1BlYekE0i3oiOgkYMJX9vvFd5a8l58BiVq1jbWUVM9d97FmIAG0nRkp2AO9eCKx/iwkRfRQTHA3lwMmNzLxbeZh9TnpfDtyxFJj4nHshAgCJnYDzH2S///aUoiotfzlYVo9Wqw0J0QaP6xmJab1YawMyUc22RWhp76nqJhw90+D1u9JWUGQkQMytDQ5/B9vAKmZjdKW7cNP+SXgjI0bYHP4PTyTB87ziBlkOjxPPo9UM08k1KEjthlMgsQcAaw6LKRplfhH8+gQM5btQwSdieutf8HFLNLq520+hZ0RNEzuXPiPw/h7aIyPey3oB++ASpWPHzUFFaW9DBfDpn9isXW9iRt5elyl77Dl3Apvns+hBTbG6viOHfwc+v5mlyvpMYdUyeh/fi7YQI4d+A76YzvwwHXsB4/8BdCtk6ZWy3UB9GftcGKKZ4dmTAHFm5Cxg0/ssnbN5PjD87pAc/i4xRdPZvXkVsH/u9OChd9oWSaw/UoGb39+AVosNCVEG9OmciMcn9sLgLilhOR6KjARCfTnMWxY4bPIuRtQPllJkpHgTEppPQS98qGnm7kh9iwUWQd3704FVJ7xvJiHtZm0vfQGaqljn0w+nqOpbwfM81gqREUV+kT0/SDP4l+MewimkSb4MF8TZuU8xoqysF3BOZ7LLGu8lTaMmMiJGOx0iI0rSNEXrgXcKmRCJTgJu/g7oPcn340Qy+wFdzwN4K7DhbeWPO7kJ+PQGwNrCIiJKhAgAxAqis6kqND1O9v4PWPgnJkTyxgC3LWYRImMMi6DlnMPOT/9r2E+lQgRgjx/zKPt95YtAS/AXbQSA3cWiX8S9eRUALOV7AQB6nt2AyPOMHCyrw50fbkKrxQaOA6JbzmDz0XKYDOGTBCRG/OX0fuC9cbDUlThs9lZP7k8fDCn8bLOnE+Tbzwrqy1njrB1feNxFPLdRBh1iTMo7Y0rnV7homCCIEbXn19LC8tY1xeoeF0pqioH3J7IS0iPLgIpDih+6v6wOZ+pbEWPU+54p1RQDP8xiv4+6H6XpzN8gDvguSGka72JEacMzwKkdvOgZ8SLYlfYYAewh9ii9ENHhrN5Le1vqgWVzgA8mCsbLXOC2X4Hc83y+lguj7mM/N32gbHHB2lPAZzewHi7544Fr3lcmRAAgVvAF8TagqVr9sXpj1zcsImIzA32vBG782rWaJ1CGTGMm14bTwPo3g/vcAruESpq+HvwiAGDbya5TegA6IfIaSdfrM/UtuOWDjahttmBo1xTs/McELOvxBXYmPYKC+o1hOy4SI/5wdCXw34uA6iJYnL5Q3jwjYpomUU01TWMVAEg+fvHnWZOmsVpYT4Y93wOr53ncTe1qyCK8sFgbJ5xPE8cGHlWREZ5nHTO/nA7M6w98eStQcVjVcQQVqxnY8hHw3jjg9F779tpTip9io9BhclhuivfZks0GfHcP0FwDdB4CjPu7ZAo9KbRbd0FK0/ioplFhSJYiXCU7kN50hB2ahwGA53lJKGWrSdPUMz+RDlb3npG6MmDVK8CrA4AVz7GIRr9rgLtXAem9fL6OW3pMYGW+LbXA1o+872tuYlGw+jKgY2/g2vn2c60EvRGIEgbZYKZqTm1jVUS8FRjwJ+Cq9wCD+i7UPtEbWRk5APzxGtBwJqhPb7Xx2COW9XqKjJTvha2YlRjznCEi0zQL1hxDcXUTuqXF4b1pwxDfWIz4EysQ03IahjS3idU2gTwjatn+GfD9LKbwc4bD0vt84OCX0t3K2sGrECMn1gGwD5aSGDlb0jTLnmWGNoBdkD1Q0cAGttQ4FRdfAPzG9wAAnDB7jOItAKJ8du90YON7wO5vAXDsgrv7G+DUFuC+LYBOeZTGL05uBorWsAtvwxnWWbNsN2vrDQBpPdmAVLpTlRjZcZKFowflJHvfccM7wNEVrFz3qncBvVHqNVLsKU2jMDKixgMkpWmWz8EQvQmfd0zyWE1T0dCKFiE8nZmk3MAa3XAGiI5GV10Jhu38B8APY6mEyqPs/T66kkUVACC1GxsY+13tWk2kBp0OGDUL+N8DwLo3WVWJ3s1lm+eBH+5nxxGTAlz/qbo0h0hcB6ClJnhixNIKfHcvWxix1yRgyhuh/U70uxpY8yr7vC/+K3CVivSWD46eqUeT2YoYox55aR4aAG54Fxbh/eZ1UdDxLF0UKR1YbTYe32xh0duHLurJGkSu/wgAz7w7qSRGIh+eB1Y8Dyyfw/7uMwW48i1Ytsxz2M1sdR8ZaTZb0WphFyrFBtaak7CV7wGSEqBLygEqq6V0QiQp7ZCx/xe2eJeIlzB1RT0buNLiVcy4SnfCdnIjkN0JOmMcAMAEITKi9PwWbwEW/x/7/eJ/slz4h5cDVcdYfwd3fSSCAc8D695gF1x3UbK4jsB5DwDDbgcWPcouznXKxchOITfe30MvBQCsP8RvT7LfL34GSMsHYF/rxaNnRBQjPlp4q1nLyV5Nw8NoY58FT4JdNK+mJ0QpypFbGk4DAEzC8/GcDb1OfgMUf+O6c/Y5wLDbgP5T3YsGfxjwJ+D3fzKBufkD4Nw7XfdZ829g5xcAp2ct5VPz/Hut2A5A5REmaoPByhfYKs2xacDkV0MvznU6YNI84L3xwI7PgIHXuTaV85MDZUxY9MxMENoAONFcC+z4HDbhbddDB0OEpWk2HqtEcXUTEqIMuKhPBos8bxEibkNvCeuxkRhRgqUV+N/9rMsfAJz3IDDuSUCnc4mEtHgQI2LIWa/jEB+l8LRveMcefk7KAbDTnoMMdR8MS2toQqlKqTrG+jIAQJ8rWJqmpZYNwm5mmmJkxFc3TQfWvC6dRTEyIrW1UpqmWfRne+nkyJns2AbeAKz7Dxs4QiFGbDbg50eFVusAuo9jEZC4NHaLz2SiSCyrTRRW2lUYGWk2W3GwnF14+2d7ECM8z0SOpZld7MUmXbD7MHyKEZ+eEeUeK15Ij9p7XgK8hwFAjNh0VtBjBACsQtg9Ki4dsNWhDElYl30JRiRWsnbtKXlAWg+g5yX+iwBvGKOB0X8GfvkLE77Zw4DOg+337/8FWCKIwkues7fd94dgVtSU7WZpKwC47GX22WwLsoexapr1bwE/PgTcs9a1xNzczN47eTt8Hxw9wyonu6fFud9hx+dAaz2sqd0BmKHj9NLk0aWLb5gQoyKX9u/EGgnu+wmoL2VisUBhlVeIIDHii6ZqVqt/bBWbdVz2MjDsVuluZ49Ik7nV7dNIK8rGGD2WhDnQUg9sng9bLNuXE5z89gttiNI0NSfZwlN7fgCueiekDYQ8YmlhZrfmGiBrKJtR7fkeAM+c+G7CzxXCujSK0zS1p4BdX4HXs/Or43SA3iSlwxSJkZIdQPFm1sRq0jy7SBp6CxMjB35hryOKgWCxRbbmy8XPsLJGb5+pxE7sp0IxsqekFlYbj7R4EzITPaQx9v7ATLH6KPadkL2+mKYpq2tGq8XmGn1Q6BmpEUt7FQhMWwMbPDmel75fNg++qmIVDc9QvAXW6uNAQjxM6X2B0nVohgHLOt+NEZf29v34YDH8bpYG2v8TM3NP/5F9rla+xKpHwDMDp7uoiRqCKUbWvM7Slr0mAX2nBP58arjwCVa9U3UMWDCZNXtLymKTrM0fACteYNeX+zazRmsKOHKaiZE8d2KE54ENrJrM1v0C4NSvrJFiBEVGms1WLNrJCi6uGiKUiW+ez34OvjG8k0+QgdU7taeYI/7YKsAUD9zwhYMQAVw9Is0W95GRGrWt4Ld/CjTXgBcMZaIYEQfLkBhYt3wIvH4O8z/w1vAsJW6zsvx4yTaW+752PhCdzIQg4HHhMDFN00Fpmmb924DNAr7zIABCq++oBHXVSls+ZD97XeY4w+rYUyjJtNlDoMGitcGeKrzoKVZt4UvcJgoXHoViZJcsReNWOLc2AL8IqanzHnDJM3eIMyHaqGMdvWvcREeCHRmxtMDWxAZPnd4kzUY9RkZEMaKgkgarXob4DY8SS1/VNj0LBhzH/BbJXYHqImaS/VeW3Sjb/1rg0pcD86cAMjFSGdjzNFSwJm8AiyS3NVEJrKQ5Ogko3gS8PYZVlr3UA/j5MZaGspmBMwcUP+XRMyxa2M3dgpHHVgNn9gPGOFhyhgMAdJxeKu2NhKZnS/aUoa7FguyUGJyTm8qq4A4uYXcOmR7egwOJEc9UHGbLU5fvYWHv234Beox32c0lTeNBjFSraQVvszGzGgBbpwEAAJ2gWkOmtPf9xAxw5kYmAgCgKcALklrMzWzWt/1T1pHxqneB5C7sAhstuNc9+EYq6tksW5FnxNwszQhsA64DwPpTwBRvT9P4Or+tjfZS46FuvshDBdG65cPg9mxY+warlkjuCgyfoewxKtM0onnVo19kzWusc2ZSF+D8h1zu5jhOijq4NbEafYsRq41HbbNCz8ieH8AL30Ndl1GyVKaHyEiVwshITTGwf5FkSJRKexHgqr3+EpMM/GkhkDmAfT+sLWywvfq/bOANxsxWFCOBVqJs/ZAdX6dBLG0SDrqOAu5aAWT2Z+KjaA3QXA3EZwAJQrSwuUbx0x054yUysu0T9rP/NbAJkT+dTi8NsJEgRsSoyJWDs9h6THu+A8ADXUay1aLDDKVp3HFkOSvPbKpks76bv2W9Atzg7JL2JEZURUaO/M7aIUclge9YAFRtBydcCO2zviBGRkq2swWpwLNBNPd84OvbA58duaNsD3DgZ/bcrQ1Aem8gvQ87hu2fAWU7WafKq/8L9LjI/rioBNaMyUNkpFJI03RQkqbZ/xO7KCVmg+8yHNglpGmiEsC1VAMAbL7SNHt/YFUHyV2BvELX+/tcDnwfxQbt6qLgeAkazrD1PAC2HofSss0EQYw0nmGpER+P2yU1dnIjRlrqJaGMi/7hvt07mIn18OkG974ReWTEgweotsksrXnm8zuz43PYBBnJxXaQVZz5iIz4EiNbFgC8Dda4jgAapaZnHGdDi7+r9gZKZj9gxiomqCuPAEnZdqEeDIKRprFZgY3vs9/PvSvwaE0gpOYBty9h0V6dkUUtO/YGvrxFuA4oEyNVDa2S7y83zekz39rA0toAMOhG2FqY6Ndx+ohJ0/A8j43HWJuIMT2FKO4uwYDd96owHZUjJEbkNFaylsLLnmUh9k6DgBu/BOLTPT7E2TPS6sHAKvYYUdTwbNtC9nPAVNgE97mYpmEfbi54aZraU6wrorkR6HYBcOmL9lLaYIuRHV8A389khk9PRCWy2Z/zwmBi/4MW9xePM0KaJlVJZERMnQy6AbzQOlxK0wg2BqsvsbdZ6Lw75Gb7CqJyDFFsJltfxnwuwWDNv4HWOqDTQFbCqJTYVObtsLYAdSUehTUANLXazasDspNdd9j6ERNyqd1YRZkHxBTIsYoG1zvlYsja6lYciZHE+CiD94qX+nLg8O/gO7PvqC4mxe6r8vAdOSV1X/UiRqxm6T22pnQFqvciWi+IKF9Nz9oCYzSQ0Sf4zyuaTAMRIwcWs2ZvMSlAvwgY6Iwx9pV9RUQB56VdgBwxKtIpKdp1naZ9i9iKyCm5QM65sBz8CgCg1xmkyWO4O7CeqGzCmfoWGPUci3hWHWfpK3CsQCACOLvFyOK/svJEgCnkkxtZ/hUABt3IjHneFpaC/UNmsvFo1XFe0jRizwQfg2VTNVuLAmCD5YmfAQA6MfQniJGgKO2WemDhdazkM60n82fojcFfo4LngeXPsfw2AOSOZtUAeiMrOS3bA3Toxtzcfa6wGy7liKZVT54RoZomzVdkpLqIRb4AYPCNsFnYxUjH6QBTvLKOiVXHWciX07HPiSdMQji31c2ArBZzs11Ejf2LewHkCY5jqZqqo0x8ehEjdvNqFDISnc6l1Qys/Q/7fdR9Xss0B+UkY+H6Inyx6SRmXpCPOHkFmUFmijU3uRUjVUp7jOz6GuCtsBmjAVihi0kB58UzUt9ikbwoXj0jB35hVQZxHWGJTweq9yLKIEvThCsyEmqk734AaRqxOdvgm31eP8NGtDC5UdLVFvZKmm4d3aRodnzGfg64DuA4Kaqq5wwRU9q7uYhNLPtlJbEqmj3fsTtyzwcSMsJ3YDLObjFyYgNbN0JOeh+Wix8yTVF4UVpenLehFXq0eOjAKob4fHZf3f0Nm8F27A10Hgz+xCIAgE5I0wQt7GezslRM6Q5W1nXjl/b2zDFCW+jGCo9hdFXs+8kuRGRl0arw4hlpbLVIM1WfBtZtCwHwrPQ1JRe28m0A7JERRaW9e4WQbNfzvFfKmASjWzDWydjzHUsbJmazElK1yMWIF+zm1URX8+qub1ivi7iOwMDrvT7PlEFZeP33QyiqbMQHfxzFrAt72O/Um8CKqHmPFTWKG57t+BwAYDPFAeZacLEpkqB0Fxk5LkRqOsSZkBjt5bk3/pf9HHwzrDzrvGpvB29Dc2t7FyN+RkWba1l/HQAY+KfgHFMoiBKvJ8rSNEdOs++wi19EiMwBYGIEdn+IThYZCbdnZJOQohkqLu0gpWiuDNMRuXJ2i5HRj7B1DAC2tHeXEapz+6IYieF51MJzmkac6aX6uriKKZpBNzCVLXaWNIhixAYmSQJM0yz+Pzb7M0QD13/mOFsWL0g2s8dSWsW01DH3OsAqLy56yr/n8RIZEStpoo06xHpbl8ZmA7YKRrPB0xzuYp4Ru4HVax+X3d+xn77Cm6IYaXUfzVGFODgOvcW/xlEKTawem53xPLD2Nfb78Bk+Z7wmgw6PXNwTD3y2DW+vOIIbh3e1l+hyHPvcWZo8mljtreC9iMvTB4BTWwFOD94YC5hroYtJ9ZqmOV7BWtR36eClDXxNsT16NnQ6rJtY9ZJJJ3pGeDRbIqOjZtAR16dprWfROGO09/2dOfALm0x16MEmdpGKGBlRmKY5KplXnSppdn7FUvpZwyQTqLRqrz4E7eD97P+0+bggRrqmMK9RyTZWoRghKRrgbK+mKbiE5fyH3AwMut4vk6HoGYkRVoxt9ZCmEQ2WqfFe0ginD7BUEacHBkwFIGtzHUwD67q3WEMgALjybbZaphxTrD2UHmiqZvlzQG0xM3qOfdz/54nynOM9Uy82PIvy3sPlxDqWy45KklZPla/2iqhEe4dbm4fzW33CnmvtfbmPYxbFSIBpmtKdLIKnM7CInT+I1QM+xIi49kZfZzFSsp0dh97EOowqYPKAzujTKRF1LRa8sdxpkT4fvUaqlBi+dwrLMOSPh01433Ux3g2sooclt4OHxlWAUJLKA11GASm50oTDXk2Dti/tbSvkZfT+VNOJQr3vlPAaV30RrS4yIqVpnCMjYvmyEBUB7FEQg94IPS/2LQrC52Xdm8CcLCaAVFDXbMb+MjYhGto1hfVfAZgvr60a0Sng7BYjQUAeGQEAs4eZXlUDu7imepvpCSFn5I8HEjId7tIZTOBh/3L7rbT3fA8sns1+v+hpz82IgtFvoGy3vfLislc8Vl4oQkFkxGeKRnS897pUmtlLYgQKS3vFL3LXUb5zrcFK02wSKhN6TfI/vyv2GvHSEr7VYsPBcnZ++3RyqtDY+rH9GMTZsw90Og6PTigAAHyx6STMVtk5FSMrFvddWqWGZ96+L/t+Yj/7XWV/H2NSJEGpg+sAcPwMi4x09RYZEVZdxYBr2SGKvjC9/VhaPDQ31Dwc5395b3MtcOg39rsXc3NEoMIzYrPx7j0jtadkJlD7xEQUI3qdMXilvYd+A36ZzQzfx/9Q9dCtRdXgeSAnNQbpidHAgV/ZHWHuuOoMiZEAkXtGAMBidS9GKqVukl5mevsE46qs66l95q6DzRjns1LAK9s/YyXLvI01uRl1v+d9Jd9IAGJk43v2DoxuerSowotnxF7W62Xg4nm7kOg92b5ZOI/2NI0PT45o/FIS3pQMrAGIEUurffbl1HBPFQrSNIdP18Ns5ZEQZZC6qAJg4XpxgB58k6qXHdOzIzrEmVDTZMaGo7LPksLIiEfPSHURW/OE0wE9LrYvm2AwgRdEIAfXVIrPyEj5PhYB0hmkAVVaKE9mvG2xttM0DeC/gf3AYiFFkw9k9A3+cQUTL5FWZ0pqm9FiscGo5xzLwUUxnH2Ow+RRvHYY9MbgpGkqj7CVy8VrvgcTvyekFE2XFNYeoWgtuyNU62b5CYmRAJFCuGIJl8V1xsTzPKqkduUeBswzh4DT+9hFsIf9QyKfuduMscqqPdyx6QO2zD1vFSqFXvEeRhVnv/42PrO02AfRQFtUA7KLh2tY9YySFXuLt7CeH8Y4h4WzpEFM6DNin8m4Ob+1p4AT69nvMkHj+ZiFaE4gYuTYShZKjktnVUj+okCM7C1hF+benZzMq/t+ZMeQmM1W9lSBXsdhfG8Wzfl1d6n9Dh9dWEWPlcc0zYHF7GfOcCA2VfL4cOBgM7FZr7vISFGlD8+IlPq5SPoOiCF2eWSk2c33vN3gb3mvJNSnRHaKBlCVphHNq11SY2HQy4ZMaXIzyWF/cUzQ603QCdeXgEp7f7ifHaeYJlRYASSypUjmFzn8OxsDOvbyWlUXDkiMBIjY9MzEsy+f1eo606tttsAieBA8hp33iXm8MfaqFjjO3G3GOHs+XE1kpGQHW9ANAIbfA1z+uu8VRUUx4q9n5MAvwgCWFdggKiKJEc9pGq/dV/d+z372vNjBfOlgVDXFe/fk7GeVTcgZrmy9mWCU9oqppd6TAlvxVDzeulKPHWFFv0ifzh5SNINu8OsYLu4riJE9Zfbz6iMyIka70jx5rPazknexskhatZfTgY9KBgBwTmKk2WxFSQ0TP24jIzxvFyNCigawR0bknpGqxha8t+qI+2PTOrF+REVbG+1VNBFkivRIdDL7qWBgd2tebay0L5fRy1GMiJ9Fo8EkVYhY/E3TlO+zr4s27m9sm4rICM/z2FZUDQAY0jXFLuJ7RFZUBCAxEjD2yAg7lVab68VVjIrEmfSsxtsdYm8Rpw+2fObOG+OkHgqKIyOWFuDbGYDNwmbzl8xRVlYbqGdku1B73//a4CwbriRN40mM8LxsUHc0ncoHMUQleveMiF/kgonKjjlQz4jVYk/d+TLL+iI+g13QeCsrR3TD3lJBjMj9IvLKEufGUQo5Lz8NsSY9SmqapWodGARBaHbvGan0Fklsqbc35hPeC4cIlzDQ6JwqosSoSEK0ASnu0j/Fm4Hq4yx61tP+HosTDoPOAL1o7uRs+OdPe/Hcz/tCt2hluPCn18iR5cz/k9SFtV+PdMTJTWudz+Ua7GJEFk07sJh9l9L7uLRStxtY5ZERP8WIuP5Vz0vs1UkqxEhxdRPqWiww6Dj0SIu1r0XjT3uAEOOXGPnPf/6D3NxcREdHY/jw4diwYYPHfefPnw+O4xxu0dEqy8UiGLGaxiSIEYub7qKVvlYflRuhejmaiuThZ17uGVF6AVz+HMutx6YBl81VHj6NCSAy0lABHBRMUsHqNeDFwCqvpnFL2S7WY8MQ7TIjcEzTyEp7ncVIawNwZAX7XekXOVDPSNEadv5jUlhzokDQ6ZkgAdymanielyIjveViZPc3kCpL/GxpH23Uo7CAtaD+dTfr2eErMnLGmyn5yDJm5EvJZc36IPuecBy4aNZLwTkycuyM3S/itupKFH49JziYrcU0jZ7TS2JkRmEuAOCtFYfx2Fc7YLEqnBxoAcnAelr5Y8SoYa9LIz9FAzi20PfhGymqEE3PsmjaPveTR0AeGYmSPCN+VdOYm4HtQquHodNV+VxE9pey62X3jvEwlW1laffoJBbdjTBUi5HPP/8cDz/8MJ588kls2bIFAwcOxIQJE1Be7n62BQCJiYkoKSmRbsePHw/ooCMJyWkvfOxsvGtpb2W9D7+IByMUez77RZY3xXkeLN1RdRz4Yx77fdJcx5VlfSFekPzxjOz6mkViOg1ia88EAy9fxApfreD3/8J+dr/QXm4rIKa77Kv2ip4cJ7F3ZAUz5yV3YflWRcccoGdEjOYUXMa61QaK5BspdrmrrLYFVY1m6HUcemTIzpFYRthfRft5N1zch32uf90j+Ea8eEZsNl7yjLgVmOL72XOiNPBJES7ooIsRxYjjd8Rnj5F94oDqOCGQZro6A/RClO+G4dl44eoB0HHAl5tPYsbHm9HUXhqhqVxYETYrS8sCyqOG4cYQZf8M+kjVHK90qsAyN9tTUr1dxYgoPAyGKGnVXrPVj8/Gvh+Z4TQxi1VYShMy5WJknyBGCjIT7O9R/njfafowoFqMvPLKK7jzzjtx6623ok+fPnjrrbcQGxuL999/3+NjOI5DZmamdMvIiIz2s8FAjIwYheyg1U0HVjEy4lOMuPlgi9YQKU3jpbukC1s/ZpUzeWMdSs8UEYhnZLfQ3U9Wex8w3kp7fbWCFzskyhfeE3DoM2KKt6fBnPuMHBA9ChOVz/zEyIg/aRqbzW6QU/veeSIpm/2sOeFy154Slj7p3jHOnkqsOCxrjjQloJe+oFc6dBxwoKwe5bXNssiIqxipaTLDKpx/l+8Mz9vLR3tOkG2WRbhiOohbHR56vFKMjLgRI2cOsiXgdUaXz4lkSOT0MHDi99yKqefk4O2bhyHKoMNve8tx83/XSwtiapqkHPaz5qSy/Ys3syhKVBLrSqwVpPJezyZWm42X0nuSz6hoLUtJxWeyFZSdkDqw6o3S5Mbqj4FVWFkcg29mkU35NVBhZPxAmUyMHF7GNua7XgcjAVVipLW1FZs3b8b48fYyTZ1Oh/Hjx2Pt2rUeH1dfX4+uXbsiJycHV1xxBXbv3u31dVpaWlBbW+twi1SkyAjHZq7uxIhUSePOvNraCBxfw37v6TqrkKdpEBWvPE1js9qNh+6WuPeFJEaq1D2u4Yy6ihOliBcOcyNbI0WA53nvnpHmWnvLf1kVjfzxAJtRy6tpbHLDmc1mr82XDYA+kTqw+mFgLdnG1kYxJaiuYPGImGapPOpy194SN/1FxKhI9wsCbo6UFGNEpyTmEzlR1STrM+IqRiqE9zMh2s0ieWcOsPNiiGZLnwvIRaVe+OxysDl8T467C7eLiBOCvNH2z5qAJEZ0ehh0ghgRPh8X9cnAR7cPR2K0AZuOV+Hat9egtMZ9hZBmEMVItatodYuYoulxUXAieG2FgrRHaW0zWi02GHQcOiUJkRRxctP9QrcTE3sHVnmaRqUYqSkWfFGcvZxeTC3ZLB6r0JwR0zR9UsCuKQArkohAVImRM2fOwGq1ukQ2MjIyUFpa6vYxBQUFeP/99/H999/j448/hs1mw6hRo3DypGfVPWfOHCQlJUm3nJwcNYfZpriIEd71Q+fVM1K0hoX/k3KAtB4ud8sNlpwpzt4h1Fea5tBS1uAqJsVtXtMn/npGDixm0ZjM/kByEN83eUt6WXSkttkCs9XDLBpgjnebBUjJc1vK5thnxL42DS8XlaXb2QBojFPn3ZDSNH60gxfDwN3Gul1Izi9SBDFS5SpGXPwiPA/sEsRIv2tc9veHzsnsYn6quslrZKRC8AC5raQRfTs5wx1alcvfR32cEBnheCnCAvjoMSIOqAWXutwlpWk4e5pGXqp5bl4qvpgxEhmJUThQVo+r31yDQ+VBWqk5HIgRtJYaZR1KxfSWVlI0IgrKe0UBm50SYy/rFSMMbiY3gP2zodObpEiru0mqVw6Kpevn2q+jxjhAvEIpMLGarTYcFsqS+1l2setyh3wgKUvdsbQRIa+mGTlyJKZNm4ZBgwZh7Nix+Oabb9CxY0e8/fbbHh8ze/Zs1NTUSLcTJxQq9DAgfvCMHBsIbe7EiDfPyCFRZV/gVmWLMzsOHHiTF4OlM1sFF/aAP/k3mMk9I2qqBaSLepC7++mN9goM2UxGHLjiowzuK5Xksxg3SOeRA2CIAi98JTj5xUOsoul+gbpzGUhpr5iKyB+n/rGekCIjriWpYo8Rqay3dCeLQhiiXTwU/tJZaBhVUtMk84y4Gli9VtIcFcSI0+zOwTMSZ0/TWKRlGmwormKVOy7dV+vL2aKZgHsx4sbAanH6nvfKTMTX94xCt7Q4FFc34dq31mDbiWrX49cCUfFsEgP4TtVUHBbSWwa3adCIRkEX1iIhtddFFLB1ZUDZTvZ79wvcPkZqeqYzgJfS9yojI+I1Rx6J1el8rl4u58jpBpitPOKjDEg7vY5tDEabhRChSoykpaVBr9ejrKzMYXtZWRkyMzM9PMoRo9GIwYMH49ChQx73iYqKQmJiosMtErHarNKMTFxEy+amnrzKm2fEx2ApGSw5DjoHA6sXgVBfbu/DMORmH/+FB8Q0jaWZpUaUYG62/z+hmCW5+SL6LOv1dX7laRoAFkFUOkRGxCiF2tp8f0t7m6rZGkUA0D2IYkSMjFQXsbJhgerGVhwRKk36dhYu0GJUpMfFjpUHASCKkVPVMs+Im9LeCk8ddW1We28Hp9SVPE1jFIzaPABLMzv3xdVNsPFsMcX0BCdBuf9ntnfnwW5njfLSXilN46Y6IjslFl/OGImB2UmoajTj+nfWYcUBFRUpkYRS34h4nck93yW9FfEoSNOIkRHJZySWuXca6DF1KXlGOB2sPIuY29RU07Q22l/HuXJPvAYqiFiJ69H0zIgHJ35vIjRFA6gUIyaTCUOHDsXSpUulbTabDUuXLsXIkSO9PNKO1WrFzp070alTJ3VHGoHIZ0dROjbTs7lpQS0OmC4Nz2pPAaf3AuCYydQNjn0w4iVDlMXbEvc7v2Kpiayh/rdlNsULS71Dea+RoyuZcEnozL6swcZNrxGpBNSd0Ks6BlQeZgbMPPczAtGTo+OEPjGCGIEoRpqqhLJreBQ0HhEjI9YWB5+LT46uYD0M0noCKV3VvaY3ErNYF0ebhXWjFdgqzODz0uKYYLbZ7EuM9w9Oigawi5Hi6iZ7lMtNZMTjWkOlO4DmajaIdBrkcJfcwGoUKqZ4DrDVsYmTmDt3W9Yr+kU8RICkyIjOHhnxtNZIh/goLLxzBEb3SEOT2Yrb52/Ed1tdq5ciHsk3UuR9Py/prYhHgYFVqsBKFcSIj8kNIPOM6PSwco4eI0UcW8UmgUk5risfq4iM7Bf6Bg1Os9qjOe0lMgIADz/8MN59910sWLAAe/fuxT333IOGhgbceitbN2PatGmYPXu2tP/TTz+NX3/9FUeOHMGWLVtw00034fjx47jjjjuC91+ECbNsgDHqRTHiKhLEdTZcIiNi7jFriMfFx+QXWV2UvemZ1yY6u79lPwOpZuE49b6R/cJFvUBFxYka3HwRK7y1ghfPb/Y5HmdtzkZge2REEJVHV7Jca1pP9R4YMTICqCvvFVM0wYyKACzMK4obmYl1q9ChcXCXZLbh5AZWcWNKCGqnxiyFnpHKBg99Y46uZD+7nudSmigXlUbhPhsAax2LTGw6xgT1kK4pjs/ZUm+fhXrwVvnyjDgTF2XAf6efg8sHdobFxuPBz7fh840+BvVII1lBZKSx0r7Oidb8IoAyz4iQpunaIY6lqxWIEWmhPE4PHkaHbYoQS3B7TnC9jnrpRO2MKMDPN+xnG9L7qGvv0MaoLja+7rrrcPr0afz9739HaWkpBg0ahF9++UUytRYVFUEn6/BZVVWFO++8E6WlpUhJScHQoUOxZs0a9OnTx9NLaAb5BSlKHwPwgNXNehiiryHVeZE8JSpbVk3DyappPK4qW3NSqB5RsMS9L2I7MOOmkl4jNpu9/0OvEM2S3IRVT9exc9sxwUNzLEDR+XWMjDQDYtRLeo/8EAYGE4suWVuZbyQmxfdjeN7uI8oPcHFBd6TkMS9I1VEALOe9VVi7YnAX4fjEKprekxxa5weKPU3j3TNyxpNnRBQjbkLN8jWcxOsPD0g9VTYKi4Wdm+sk+g8vZZGrlDyP/WPk1TS+IiMiJoMO864bhJRYIxasPY7Hv9kJvU6Ha4Zme31cxOClDFzi4K9MqGf0Z/13tEaU98gIz/OyCqxY1jyxoRwwxnptGiZP0/CcEQDvNn3v4UVlfhE3zRXVREaENE3v5m1sQwRHRQA/xAgAzJo1C7NmzXJ73/Llyx3+njt3LubOnevPy0Q88jSN0RALmF0jI2arDbXNbD+H2bvNpmiwlAysHAedrEOo1erBM7JHWIOly0ggMcBUmJo1Kkq2CqWo8aH70LvJl4oXi5xUJ1OizWqf8So4v5IY0UUBaGapDLkwUJuiETHFMzGn1Ddyej9LoRiigdwQ9GxwMrHabLK1K7okMy+JuOBZkKpoREQxUtVoRitngglg/RqcqHSXprG0AseFWbiTGJFHt3ScTvL/2ADoKg6gsdWC3UIb+mG5ToJQnqLxYCCXz3SNOrGE3/fgotNx+MflfcED+HDtcTz61XaYDDpcPlDBukbhRolnZJ8sEqpFxGipB89IdaMZdcK1u0tqLLBBuBbknu/VyG4TUuh6Tg8bZwLQonz5jtKdTEAbY91fRxU2PqtvseBEJftudTwjtFqIYL8IQGvTBIQ4YzLoDNAbxDSNo0ioFlI0HOe0Amn5Hpb+MMaxNIIH5DN3nayaxmOaZvd37GffK9X9M+5QI0bE8r78ccErRXVGunjYZwUeyzVPbWWiJTqJGRM94ND0DICVE46dt7BKgZoiFt3wVxhIvUYUihExEtNlZFCjEhKp3dhPIU1zsLwedS0WxJr0KMhIYH6VhtMsKtbNvY/JXxKjjUiIYvOfqlah8smdZ8RdmubUVsDcwI7LKY8uv9DrOJ30Xto4DvqKg9haVA2LjUfnpGhkp8hEq9Vsn4X6SNEAjmvTKA27cxyHpy7vixuGdwHPA498sQ2rDmrA1Oqr14i8C2moIqGhxst6V4C982pmYjSr1FMQyQbsk1QdpxPEiPvCBreIE6jc0Q6l6xIKxchBISrSK74R+sqDALjQTG6CCImRAJC6r+qMMBrZYGh1ioyIlTTJMUbodbKZl+hu7jrSa6MgeWmvLlpmYHX34a4+YU/RBKNrpxrPiOiqD3ZJrxw3X0T5eiMOiBeOvLFeWx87tIMHYBWqosBbWAgfALqMsJtRVR+zSjEipiKC1ejMGanXyDEA9hTNwOxk1kdBTNH0mRKSBlZidKSyRfguuPWMuImMHP+D/ew6ymWhR3k0kuM4KcrFAzBWHcRGwS8yzDlFc3wNM8TGprF+Dm6Qiw49p5c8I2YVfSM4jsM/r+iHywZ0gtnKY8ZHm7HzpIL+HeFE9IzUlbg3Xx9bxcRhQmcXM7Fm8GFgPV4hlvXGCs0phcicDzHiUNoriRGFkRHxc+7BcK/UM3JQ6HMzKeEg29BpgLI0cRghMRIA8siIUZjFWjnHyIhYGeDS8ExcddRHEy3nduVi0zOru2oaMUXTdZTLGjd+oXR9mqpjbDE+Th/aXgNOX8SaRrNkDnbpHSHNYtz3AhBxSdNwwmzEZlU8E/KKmvJeq8V+MfIQleB5HlUNrdhzqha1zX60Hpd3YeV5bJH8IsnsoiymaIK1wKETYuOzM82CGDE7ihGbTdZRV/6dEbsUu2k37pCmgU56L20AjNWHsekoW332nDwnMSJVglzicWVpeTrGITKicuEznY7DK1MHYlT3DmhoteK2BRtZv5VIJTaNVV6Bd7uWkWSS18rCeO7wUdor+UVSY+3NKROzpMUZPeHgGdGz6J67wgYXbFa74PHUVj9amRg5LIiRkbo9bEOEp2gAPz0jBENqeKYzwiBFRhzFiNRjRF7Wa7PJZnrexYjUWRI6h+oMt2Jkx+fsZzBSNIDy9WlE42qXkR6rgoKC5BlhFw8xRZOeEIW4KNlHubnW3sRK4SxGStMIJdocbwaOCoIxkKoWNY3PSraxC2N0ssuaF1Ybj7dWHMbbKw5LHiSjnsOIbh1wxaAsTBnU2d4h0hvJXQBOx2a19eXYIvlFUtgCh+ZGIK3Aa+owEFhkxIqDjXUYDbhERqqbzBCbpkoC3moBioSmTW4u0i5pGtjTNDpLM0pPHALQwdG8arPZFyL00qFY7gtz1w5eDVEGPd6+eSiueXMt9pfV4a4PN+OLu0cixuReCIUVnY6ZWCsPM9+IvHuxucl+7oLsK2pTfEZGZOZVqeuq++aUcqTSXk4PiJERJWuJle1iXW9NCW7XvAGg2MAqdgDu2biVbciNfDFCkZEAEEO1Bs4AY5QgRpw+p267SZbvYf0rjHFA50FeX8Nh5m6Ks6+d4hzeLt3J+jDoTUC/wFZYlRAjI748I/vbyMjmNCvw6Bc5tor16Ujt5rYFvBwHsQfAKsxkTJZaNmDHdQQy+vl/zFKaRkFLeClffL7DTL28thnT3l+PFxfvl4RIYrQBZiuPVQfP4M9fbsclr67Cb3vKfK9ZZIgCElmlRH3JQemiNbhLMrDlI7bPkGkhm+12To5BVOb3mNvyLjZHRbl4RsTKs6QYI4yiuCrbyc5fVJLbvjlyMSJP0wAsVZNtOYGkGCN6pMtKrU+sZ8slRCV6L9O0OaVpxA6s/ix8BiAh2oj3pg9DapwJO4tr8OhX232/Z+FCrKhx9o0c/JW9H0k5EbkUvWJ8eUakNE2cqiipvC8NrxMiI0rSNGLqvssIz6llpwmZJw6W1yMLp5HQdJJFrLsq6wMWTkiMBIA8TRMtRC2c50tV7sSIw4fOe17eYeZujLWX9jqFt7H1E/azYGLwohOiGGk443mfpmp7CD3URjansOqxM05Le4uouHDIq5UAwCZERnS2Vvtz6AL4mqhZLM+NX6TZbMUN763HH4cqEGPU44WrB2DfM5dgxz8mYOkjY/HohAIkxxpxqLwed3y4Cbcv2IQTlT465qbmAgB27toGAMhPj0eH+gPAqS1s1doQpWgAICs5Bob4AwCAQyajS2Skwq1fRPh8dRnhNp0iX8Fax+kcxIgNQHeuGMO6pkAn92yJK0v3usyr4VoectdxOskz4k9kRCQnNRZv3jgEBh2HH3eU4PXfPXejDiueeo3s/JL97Hd1YN+NcCNeT6wtLulCAFJX4p4xdWwCCQ7IK/T5tPLPDPTuCxvcckyIlnszmiqIjDSbrThR1YiReiFFkzXUcW2vCEXDn6TwIxcjJlnXR/lsSry4OnhGFPpFAMf+CdDpYOPZBZWXX8QtrcDOL9jvg27y639xi2h2rDjEwtruOPgrK4Pt2MteqREqnMSIOHPJTXM2r/oumRaRr2kCADbh4sGL41YgfhFAuWfE3Gxf7ViW33351/04VF6P9IQo/Hj/+Zh6To60Bk/3jvGYeUE+Vjx6AWaM7Q6jnsPv+8px8dyVeGvFYZitHt4z4X09emAXAOC6YTn2qEivSwNeodcbCXEt0BmrAQB1Op2rGHHXUVcUIx4u0g5pGugcOqzaAORzpzBpoKzM3Wa1+6v6XuX1eKUeI0JExFs7eDUM79YBz0xhEbeXlxzAL7vcLzQaVqTyXlnDtuYa+wrWQezOGxaiEmFfeM4x0lDZ0IrKhlZwHNCtVliaofMgQFr3yDPyNA2nUyhGbDbmSwG8t0ZQYGA9croBPA+MNe5lGzyZYSMMEiMBIBcjUdF25SnPM7t4RuR+ERX9OOymPHZRtMmV/IFfmK8jPjPwwVNOah4zsVmagOpj7vfZK+SOe08O3ut6wimsetRdmkbeAl7B+ZWayomREX2MsF24SHXzboD1iVLPyMkNbGCOz5QMcpuOVeK91awEd85V/dG9Y7zbhybFGPH4xF74+YHRGJ6XiiazFc/9vA+TX1uNzcfdpNg65AMABjf+gTiDFdd2awG2fszuGzxN/f+ognr+mPR7rRsx4tJ91cFf5VuMcBwnCUuApWlGJVdiyiDZmjPH1wD1Zcyb46NqSf4dB1hKFggsMiJy/bldcMuoXADAQ59vw75S76H3Nsddr5G9P7JIQsdegaUvIwH5wnNOaQ8xfZmVHAPT8eVso8Jrq7RqL6cDb7BPbrym4+Spe29LaShYT+dgeR0AXlPmVYDESEA4pGnkYkSWT3bxjKjwiwCuBkteFCPyi/g2IUUz8E9ey1hVo9MDHQvY7+V7Xe9vbQQOCq3L20KMOIUopUWs0mRpGjEqknOuogXe5KXTAGAVIyMA6yyZkBHgMSv0jByRrUbLcWi12PDoVzvA88A1Q7Mxrrfv48hPT8Bnd43Ai9cMQEqsEftK63D1m2sx+5udqGmUVd4MuA4N+iT01hXhjfQfkLzoHuaPyR0dXDHrhpJme0qiTse5eEbEtYZSxTTN6X3C9yXW40XapemZPE3DcehiPeG4Ho1YCdJ7EuuS6wV5wzMAfpX2euOJy3rj/Hy2js09H2/xr0IqVIhpmpIdLCJiaQXWvs629btGka/IaotQP4yIBxOrKEby02JVRVoBWWkvZ4BOlgL0KmBFwd1luPfUvYI0zeHyeuRypUiznWEeQo34ekiMBIAYATHqjIiSDXxNZvsF1mXFXulD59svAsiankldJYUeCqIYOb3f3rhp0I3+/SPeEBtMle9xve/wUhY1Se7i2f0dTGSzgprGVknodZVHRlSW4zqX9vJCZIQHfJYFK0KpZ+SoIEaEkt4fd5zC0TMNSIuPwt8mKV86geM4XDssB0sfKcTUYcyA+OmGIox7ZTm+21oMnudRwSXjz613AgDGVn7JGopFJwNXvh1yD8CBqn3S71KaRiYmxPc0zfn7knOux++LQ58RcA7CwwoOXFOl3ffU2mgvX/aRogEczYgA/C7t9YRBr8O/rx+MzknROHqmAY99uSNyDK3Z57KUXuMZ4NcngD9eZdeB2A7AsNs8Pmz3qRo8/MU2XPTKCvT46yKMeWEZHv96B5bvL4+c/01EuqY4ipHDp5kYOS+hhP3/xjh2PhQgX9xUp4912e4WMXXvqaRXOl5ZryUP5/LQ6Xp7VCT73NA0TwwBVNobAFI1jc6AmNgEcDwPnuPQ1NIECJ/BslomTNLiBYWswi8CuDFYQg/ACt4qCJ6VLwLgWXliR+/1736R3pv9dBcZ2fs/9rP35T5nSQ0tFuwrrcXBsnpUNLQixqhHXJQemUkx6JwUjc7JMY7lue4Qv4g2C4rKWfohLT4K8eLjrBb7oK50FuOUphHFiI0D6yYbKEo8I821QPEW9nveGPA8j/8K6Zlbz8t17NyrkNQ4E164ZiCuHpKNv363C4fK6/Hg59vw6tKDOFnVCLN1CH6MmYhJrUKzusv/DSRleX/SILCnwi5q60ThY2mRuk3aFz50EiNeSuDlvirnahokZbOVZ0/vZ16YDW+zlGZSF0Xha3HCIaZnAint9URqnAlv3DQU1761Br/sLsV7q47izjEh9l8pwRgNXPEfYP6lwJYPAeF/x8QXPHonvth4Ak98vwutFvvAW1TZiKLKRny28QTOzU3F45f2YqXkkYAUGXGfpjnHuo1tyBvtM4omIkXTdHpYDNGA2XG7Czwv80X5SC3LroGwNLsVGofK63Gfbrf9uDUCiZEAcPCMxMTBAPa5a2xmIbRms1VayC0nNYblv4+p84s4z9wlMWJpAc4cZL0hAGDsY0H5n1yQIiNOYsTSKlsYz3OfhvoWC95ZeQTvrTqCxlbvF/CkGCM6JUUjKzkGXTrEYlBOMoZ0SbGvO2OKZ+F6cyNOn2Th/jx5ikZhC3g58lkMAJiN7MtugR7IGaHoObyipAPr8TWsFDklD0jugvVHKrD7VC2ijTrccG5gC5AN79YBi+4fjXdXHcG/lx7EUaljbSw6X/UysD2ReVT6XBHQ6yihurkaxfX2Blp2MdJsFyPSujRRjhfprqM8Pq/zd0TuGbF1yGdi5Mx+IKMPsFpYJ+uC/1MUmfQYGQmiGAGAQTnJ+Pvkvvjbd7vw3C/7MCA7CcO7+TZLhpzc84DhM4D1b7EBsMfFHlsHPPvTHry7ionoCwo64qYRXdEzIwGHTtdj+b5yfLbxBDYcq8RVb6zBLaNy8ZdLeoW/x4qHlXtFMZJXo6xfkRyHCixDjF2MeIqmnd7HBLIhxvd1yxQPZrrlWarGSYxYrDYcPVOPEQZt+UUAEiMBIY+MGEyxMPA8zByH5iamsk9WMU9DfJSBzW7L97Bupgr9IoDjqr2A3TPCW5qBlS+xVTN7TvRuegoEMTJy5gATIOLs4NgqFtqMS/fYSnvz8Urc/dFmyQeQnhCFgswEZCZGo9liQ12zGaU1zSiubkJdswU1TWbUNJmxr9QxH9ovKxFXD8nGtcNyEJ/eByjehJaT2wHkuk/R5I312FHTE+L5hZGJm/KoLu7XhlCLkrVpnFajFaMiVw3Jdu3c688hGHSYeUE+Lh/YGVtPVGNAVpK9Aqn7OwE/v1L2VDqm+mrlkRGBCnn31cojzGiqj2LliR5w9lU5VNOkF7DPxW9PsYXdmmuYwB4wVdExiwOLGBkRRYm/fUa8cdPwLth8rBLfbTuFWZ9uxU/3n4/0hCB8BgNl3N/ZZ7S+HLjsFbdR0J92lODdVUfBccBD43ti1gX5Uil1TmosLihIx4zC7nj51wP4avNJzF9zDCsPnMa/rx+MfllJbf0f2XFjCG1qtaK4ugkxaEbi6U1so4rGh3Kfkd4YCzQ5bndBbPWQc67v6Itoum2pZWIkPt3h7uOVjci1nURHrha8IQZc1jDFxx1uSIwEgIPTXqeDQUjhNTezgedEFfsUZqfEsAukiv4iIi6REeGiaKo7BhRtZjsV/iXQf8UzSdmsI2BrHatSEcXJVqEUtPcktwP/ruIa3PL+RtS1WJCXFodHJxRgYr9MRyOhjLpmM0oEYXKqugkHy+qx9UQ1dhfXYFdxLXYV78Gvu8uwMLMfuOJNMJ7eDSAXeWn++0UA14FML0ZIuCCty6IkTSPzixyvaMBve8sAALedlxucYxDISY11Xd24DRFTNCmGbFRZTqJObGomW7n3jND0rEN8lP37kj3MqzB0blzn0PRs2O3A8XUsanZIMFuPe1KxWJVKe4X9g1lN4wzHcfjXVf2xp6QWB8rqcc/HW/Dx7cPDHz0wxQF3LWcl0SbXz8+p6ibM/mYHAODewu64f1wPt0/TKSkGL107EJMGdMJfvt6BI2cacNUba/C3Sb1x04iuHq8NIUXsyVRnL60W/SLjYw6Cs7aylF6H7oqfUr5qr162ppVHz4j4OVeYupfEiJvOsYfK6zFKSNFwXUYoTi1FAmRgDQCpHbwwcImXjOZmFgo/KTSfklYKVekXAVwXchNLe2Or9rGoSN8rFack/ILjZL4RYWZbe8reDtqNke3w6XpMf38D6losODc3FYvuH41L+3fyerFJiDaiZ0YCLihIx43Du+Ifl/fF9zPPw4a/jsc/JveByaDD2iMVKDKxXHqsMMvu3lH4sjfXAieFfgAqjKfOaRq9tMiawoWtfOGrtLfhDGsDDQC5Y/D15pPgeWB0jzTkp0d+oyJnalpqsPP0Trf3iWIkP4F9Xut0wrKPQmSkttksrXKdlRKjKEUDuL6HUpQLgC2uA3D7EmDMY6wNfo+LgZ4TFP8/oeoz4olYkwFv3TQUCdEGbD5ehVkLt3juF9OWGKLcChGbjcdDn29DbbMFA3OS8eB43761woJ0LH5wDC7qk4FWqw1/+3437vt0K+rCUUkkdvQt2S5tEsXIJTHC9U5BC3g58jSNXnbO3ApYnpe1elAhRgC3FTUHy+o0V9IrQmIkAJx7EOiFyIhZmAWfFCIjrn4R5WLEtbTXIPwEq2KZNC+A/0AhzibWTe8zj0OXUUBmf4ddLVYb7lu4FRUNreiXlYj3bhkW0MwuNc6EW87Lw9VDmLny0yIW0u1mO4as5Bhc0EsIUx5YzI6pQ77PFvDuEGfVeiF1EDTXvy/PiJiiSe8LPi4NP2w/BYCV82qRJ/54AjcsugG7zuxyuU8UIwPTWOjYzHFo4Tip10iRUKqdFm9ipmSVYkSeppHEO29jUcgL/wo8XgT8aaFfA4v0HQ+wHbwSunWMx/u3nIMogw5L95Xj0S+3R4YgccP/dpzC+qOViDXp8ep1g+wt/H2QHGvCOzcPxROX9ZY60V7++h/Yc6qNe62I6b9T21jkB6JfhMcIi5iiUVfuLv/M6IzRMAjXErcC9sxBoOE0YIj2mop0wIsY2XeqGiNIjJx9yBfKAwC9cAFsNbNZ8AnBM5KTEguc3iv4RWJVRTKcZ3020UCn0wPXzgdikgP+P3wiN7FaWoDN89nfw+9y2XX+mmPYU1KL5FgjPrjlXCRGByfdcfv5LCLy8VE2uGdyVXh0dBqiDILQ2fUV+6mgXFOOS5pGFCNK2jcrQV7a666LrdQCfix2FtfgWEUjoo06jFfQVyQSOVx9GABwqNqxxXmLtUUyr57TaQh4ocWtvNeIuNZQ1w5xzHRaU8QqOHz0SXBOZcp/dxCVUQmK06MikoHVqc+IvLFhKDgnNxVv3jQEeh2H77adwrT/bpDKniMFs9WGV5aw1v73FnZ37YTsA47jcMfobvj87pFSafOVb/yBTzcUtV0JcFoBuya31jFhABYZ6ccdRYfWYmYqzR+v6ikdSnujYqWV1t2maY6LqchzvC5L4ICXLqytxTuQzDXAYogDOg1SddzhhsRIALhGRgQx0iKkaWSeEX/8IoDrhbZSzyIBJVkXK1fSgSJGRkq2AyteYEo+obNLFU1xdRNe/pVdnGZP7IWOCQq/XArIT4/H+N7pqOdjcNzGzsHkDGE14cZKux9AZYtqh3b7AAzCYBN0MQKerYjrjLg4Xt4Y/LCNRUXG9c7wXeYcoVQ0VTj8FClvKAcAROuj0S01A7CyKoA6nY6tAgunJdvFqEinQfZUlwece/EAslJ4JQuUeUEq7XWKjIQqTSPnwl4ZeOumoYgz6bH2SAUuf301ft+nYDHENuLzjSdwvKIRafEm3Hpent/PM7RrCn66fzQu7JWOFosNs7/ZKaR+2iBtozfYB+1TrLz+UHk9JumFpRl6XmyPbirE2cCqF64lbtM0YrTcV38ROR4iIw0tFuTVsVS1rcuo4DbAbANIjASA84VKJ0VG2EVVXLAsJzXW3mFTRYoGcB0UG3RMFVcn9fbvoP1BjIzUnABWvcR+P+c2F1H1jx92o8lsxbm5qbh2aE7QD+OuMcxEtpfvCgDQlwu19Hu+Y2WHmf3tHWMVIpkfJc+IkA4LcBCTMMYwrwLg6hs5cwioOgrojLB1OQ8/7igBAFw+sHNwXruNabI0odHCPvMVzY5ipLSRGQQz4zLRIT4KvI0ZUllLeBYZEdM0XTrE2sW7jxQN4BrdAuzCJFBR6VzaG4o+I964qE8Gvp15Hrp2iMXJqibcNn8Tpr69Fj/vLEGTj1L5UNJstuLfS1kkYdYF+QGL55Q4E96bNgyPT+wlRYMufmUllu0rD8bheidrCPtZvBlmqw3HzjTgMt06tk1lpBWwf2Z0nA76qBj74qbOnxmel/kI/REjjgbWfaV1KOSY98VUcJHaww47JEYCwGy1l/YCgJ5np9NibkJ9iwVVghkvO1Fvr5gIIOQn/2kN1mCphPiOrP1zQiegy0jgnDuB4fc47LKlqApL9pRBr+Pw7JX9HFdIDRLn5KbgrjHdYMwSur2Kxs+dQoqm/7Wqn9O5qVzQ0zQc57m894DQpyX3PGwsMaO0thkJ0QYUFnQMzmu3MfJoiHNkpLSBiZGMuAwY9Troha6A8sXyxDRNbmqsQ8TIF97SNIFGRpxLe8Xveig9I870zEjAD7POx91juyHKoMPGY1W455MtGPLMEtyxYCPeW3UEu4prYGvD1usfrzuO8roWZCXH4PrhgfXCEdHpOMwY2x2f3zUCuR1iUVrbjFvnb8TDX2xDdWMIU1SSGNmCHSdr0Md2EDm60+CNcczwrBJ50zO9KQZ6T56Rst2sdN0Yq65lu4c0zcGiYgzT7Wd/+HHc4UZbcZwIQ95nBBBnY1ZYLE1Sj5HkWCMSyrewgSiuI1vvRAXOM3ddkMLPqrnmv17vfvU3Nku6anAWemSEpgqE4zj836W9gX3jgM/+C5TuZIt4iSF9D82YvOGcpgm6GAFYmkHsCyDnoNDGv8cE/G8HS9Fc0jfT7oPRGPJoiHNkpKyRlStnxDIvjImLRQtEMSJERoRIYg9jKYvC6aMUha+dBTsQ/DRNqJue+SIpxojZE3vj1lF5+OCPo/hpZwlOVjXht73l+G1vubTP8LxUTOibiYv6ZgTNr+VMs9mKt1ceAQDcd2F+0D+vw3JT8fMDY/DKkv347+qj+GZLMVYeOINnruiLS7y0B/AbMd1duhPrDpzCZXoWFeEKLnFbQeQL+aq9hqhoqcrS5pymPbyU/cw9X7lfBPCYprEeXAojZ0VFdC46pPqfNgsXJEYCwCWfLASaLJYmnKgUKmlSYoFDS9gDuo9TvfaH82DJQYyMREbeGAC2najGigOnoddxmHVhfuhfUFwt9PR+4NsZAHg2aCWpr0CR/AZimibYnhHA/fo0zbWSiLLmX4xflh4DAFw2oBO0ipLISGZcJgAgWh8vEyNNaDZbUVLDIiS5VUKIvOtIRYOBc2NAwIOB1Q/aurTXF5lJ0Zh9aW88PrEXdp+qxR+HzmDtkQpsPFqJmiYzft1Thl/3lMH0jQ4T+mXi1vNyg956/ctNJ3C6rgWdk6Jx1ZDQVH3FmPT462V9MLF/Jzz21Q4cKq/HPZ9swYW90vHU5X2D2y8nuSsQkwo0VaJm7++4Tb+WbfcjRQM4pmmM0XYDq9VFjKjviwTA3jXWSYx0KmNm+OrsCxABvXtVQ2IkAJwNrJJQsDRLkZHslBjgkKCAVaZoANc0ghQZcVeZESZe/Y2ZVq8cnOXYETVUJHcBopJYzvTYKtbRtvBxv57KOcQvekYQzMiTu/Lew78zn0uHfGxpSMWZ+v1IiDZgVPe04L1uGyOPhlQ2Vzrc5yxG4ozxqLHaIyOivyohyoDYE0KFkZ+LHQLyhSUDTNN4aAfflmkad3Ach35ZSeiXlYS7x3aHxWrDrlO1WL6/HD/uKMGh8nr8b/sp/G/7KQztmoKHL+qJ8/ID/2yZrTa8tYJFRe4e2x0mQ2gz/UO6pOCn+8/Hf34/hDdXHMbv+8qx9nAFHhjfA7efn6e4lNgrHMeiI4eW4KGKpxHDtcISmwGDH9drwDG1pzdGSZERq6y5H1obgeOC6FHR3RWA28iI1WrFgOaNAAdE953o13GHG/KMBIBzaa9O+NhZrM1SZKR3fANQthMA59cqsM7dJUVR0qaeES/sPFmDZfuFqMgFbRAVAYSLh1AendEfuHuF3zX1zhEQezVNEHHnGTn4K/vZYwJ+3skG6ot6Z4T84h5K5NGQquYqhwFb8owIaZpEE5vd1QqeEbGSpluqEZxo6lN4kXZnYA1WmsZjO/gQl/aqxaDXYZDQdOy3h8fix/vOxzVDs2HS67D5eBVufG89rn9nHTYfrwrodb7dWozi6iakxUfhunOCb1J3R5RBj4cvLsDPD4zG8LxUNJmteO7nfZj82mpsPl7p+wmUIPhGYrhWVCAZ+unf+r0chJQ21OlgNHDgxNJes0yMHF8DWFuAxGwgzX3HWo+IYkS2uN+pPWuQxtWgno9BZr9Cv4473Gj3yhcBOEdGdGI+2doi9RgZatnKdu48mK0aqhJPBtagVXsEyJsrWD+Jywd2Vt1nICAmzWMrit7xm/ovswzn82uQPCNBPL9iL5gzQu8Nm00SI3yPi7F4NxuoJ/TLDN5rhgG5GOHBo6rZPvCJnhExMpIcLRMj5mbJvHpB7FFWAh2fYe+O6QPnVJv892CnadqytDcQ+mUl4aVrB2L14xfgllG5MOlZB+Or31yD2+ZvxN4S9c3FmlqtmCv0FblzdB6ijW3rbcpPT8Bnd43AS9cOREqsEftK63D1m2sx+5udgRtchclMMd8B7+b/B5zCz5475KW9Jr294NzSKhMjYoom/0JVTfgA2A2sdadYRQ6Axt2LAAA7ooZAbwxeS4W2hMRIALg0PRNmTzZrq9RjJL9WqFf3czl6aWYnfF7DUk3jgSOn6/HzLjaQzhirfO2GoJCaBwy+KeDF7FzSNJKnJ4ixEbEfy5YFgNXChEjDacCUgF2GPiiubkKsSY+xPbVZRSPibFoV/26yNKG6pRqAXYykxSYDEJueNUvm1RH8Nvbg7sov0tJ7CFcxErTIiM6xmqatDaz+kp4QjX9c3hfLHi3En87JgV7H4fd95bj036vw6JfbUSr4dJTw1orDKKlpRlZyDKaPyg3dQXuB4zhcMzQbvz9SiKnDmF/l0w1FGPfyCny79aT/4jP3fPwl6UVc2jIHBX0HBXSM8nbwJoNO8jK1tMo8I6J5Va1fBGApJWMcUHWMVWlaWpF55FsAwKmMsYEcelghMRIAUjWNIEI4aRGtVpysbEQiGtDx1DK2c75/dd+ui4CJ4efwG1jfXnEEPA+M752OgkztraMCtFE1TZ8pQGwaUFsM7P8JWPZPtv2c27BoLwszX1CQ3uYzzWDjbFoV/y5rYFGRGEMMEozsc9JRFCN6xzRNQZ0g3gNY7BCQr+UUXM+IVNobYWkaX2Qlx+C5qwfgt4fH4rIBncDzwJebT6LwpWV4afF+n+vCnKxqxFsrWHfdv17WO+yf1ZQ4E164ZiA+v2sE8tPjUdHQioc+345r31qL5fvLVYuSmkYzvijPQg3iA/Jt8TzvUE1jMujACc0wzaIYqTwKnN7H+g/l+SEeYpKBwTey39e+AWz9EEmtJSjjk9Haa4rfxx5uSIwEgEsHVkGMtJqbUddiwVT9cugsjaxpWM65fr2G88ydE2d8YTawltY045utJwEA9xS2kVckBEgLEXJiB9YQREaM0cCQaez3Hx9mJcmmBPCjHsDPO1mjM62naAC7aTVKz8LEYmREnqIRz3OnBFbhIRpYj1c0oD93BCl1+wGd0S8xEoo0jYtnRCNpGk/kpcXhPzcMwbf3jsI5uSloNtvw+rJDKHxxOT5ae8ztGjhWG4+n/rcHLRYbhuelYmIEfVaHd+uARfePxqMTChBl0GHT8Src8sFGTHx1Fd5YfkhqpOeLeUsPgOdZp+eMRP+jrfJInJ7Tw6izR0bMZiEKteVD9jNvrH3VYLUMnwGAAw4uBv/7vwAA/7FcgXN7ZPl76GGHxEgAuIgRHVuumWuuQBRacYdJKOkdPkN9XlDAedYndnm1BtPT4Af/WXYIZiuPc/NSMbRrcEsH2xLnEL8hFJERgK1uzOmAxjPs75EzseWMDscqGhFj1ONCccE/DSNGQrond3f4W6qkibUPYllJdjFiaarGyaom3GIQmsD1u0qVv8q5Fw8QPAOrGP2Uqml04ekzEmwGd0nBF3ePxNs3D0W3tDhUNLTib9/vxoS5K/HFphNotbDz1my24p6PN0sNDZ+c3Df4fT4CxGTQYeYF+Vjx6AW44/w8xBj12Fdahxd+2Y8xLy7DqDlLMXPhFrz620F8u/UkNh+vwpn6Fum7/96qI/jgj2MAgIcv8r3qsDfknzedTgedjpMiI63mJsBqBrZ+zHYYdqv/L9ShO1DAqma4pgqc4lOxNmmSfRVzDUKlvQHgLEaaTRlA61GkclX4wvQ0MvlyVr8+YKrfryHN3J3SCOGMjBw+XY+FG4oABP7lDTfOs2pxsAlyPQ2QnAMUXArs+xH4//buPCqKK98D+Le66W7WBlkbUBYVd8QlQojP5SmKxCQaTcYY56lZzGZmdDDGmIk6mncGE09MMonRzHlucxyjMZPoiSZxcI8BUVHGvaMExAgNAgEaEHq774+mS3ph7YKi4fc5hyNWVXfdy62u+vVd3f2AxNfw1Xfmv2FKrMq8Sq0LqzfWQ6s3DzUc2GsgrpVdswtGQrweLP6n8n4QjEiuHUAC+uNxScNQx4SX23Ru26Y2oFGfEaGaaSzzjHCdPwNrR+E4DslDVZg0KBh7zhbgoyM38UtpDd786hI2HFYj0t8TpdX1yC+rhdxNgo/njMCQMKXYyW6Sytcd7zw2BK9P6o/vLmtw8FIhzvxShsLKOhReKsIhFFkdL5dK4O3uxi9A+Pajg/BorHPz/DRuvuOb78EBYOYOrOrvgZoSwCvYfD9wxsOvAWpzx9VPDU9i/JDeXS5QbAvXvgOKTM/M35osHViZTAnoAB04xEnMY/ExeqF5fZJ2smumgfh9Rt77/gaMJoakwcF4uK8rTq/zAF8D0vAZduOnse+Av+/Et8wrg45bhjqpNw7+xzzr6lOjO2biqM5Uft/cRCOTyBCpNK8dZGmmabwujYWyYURApUQKzqTDdtn7kHNG8+qlbVwA0mEzDQRuphFhobzOIpNK8D+JUZg5Mhy7swqw9XQeSrT1uKc1z4yrdHfD/y0Yg/jodjYpdDI/TzmeTYjAswkRqK434NKdCuT8WoH80hrcLqvFnfJaFFXVQWc08YHIc2OjsGhcX6fPbVUzwt+zJQBMMOjrgOzt5p0jf9/mFaTtRP0XTCN+jxM5P2OfcQJ2Dnbt2lUKRpxgWzMia1gl8Uc2FK8hw7z8+ZgXnToHP7skP+mZZZSAOMHI2bxy/LuhyvatlEGipEFI/IOMb6bpgBlYLVSxwOtnAQCHc+5CW29AuJ8HHo527YAOeBB4+Lv7I9DD3MRi24G1cTONZZ4RIwcUwgfhXMMETgmvtPncjiY9E2w6eNuhvV10nhEh+LjL8PKEflg4Ngpn88pRU2+AwcQQH+WPYCf6UYjJW+GGR/oH4hGbCd/q9EaUVtejpt4IuZsE0QJNS9C4+c5yzaBhzTLva7uA6oYh1ZY+ZM7gOFwc+S6eP5MJH3c3jIlyjWCxKRSMOMEuGGmoIclm/XB15BQMHRAD+DrXocj2YSnUkMX2uKetx5tfmVeFnDOmD/oHu+YImsbsVu3lO7B27N/3XxfuAgBmjwrvkEUFO5sl8AjwCECAhzm4sq0ZadxM4+HmATR8Y/yzcR52SLeAKcPBDX6izee2DdiBDhzaaxkx141qRmwp3KQYF+Paw8xb4i6ToncvAaeUb9D4urBcg1WcL4B7MDX0P0L/KeapCQRgWZdo4sBgYWajFREFI06wXSjPUjPiIQdipi8FBJhNs8np4Ds5GKmq02Ph9rPIL6tF714eWObifUUsbDsIP/hAd1zNU15pDU7fvAcAmN0NmmiAB4FHgHsAAtwbgpFmOrByHAcZ5wk9q8YpbiAOP/wPJMcPB9zkbT63bcAONBpN42Q5NjW019U7sJKO0fi6sFyD1RJzMJI3ZhUQFNq+4bwO6I0mfsLEJBdvogEoGHGK7aRnkf5KnCkDRkUqBZvW23aeEamTzTSMMdTojCjV1qOsRod6vRF6E4PBaILBxMAYoHCTmH9kEnAch7N55fj6wq/4ubgagd5y7HohAQHerjnLny0+2LN0EOY69tsFYwyrD1yBiQH/PTCoc9by6QSOakZ+q/8N1bpqaHXmJpjGfUYAwF3iDb2xGr5eBkyY/BjQzrkrHDbTQJigvcnp4LtBB1YivMZzjDwYAWm+LmsUgeaRYkKcx8Tw5leX8Mu9GnjJpZg4gIKRHo1vpmm4UQV4mjuqRgcJ175qN7RX0rrqZ5OJ4da9apzLL8f1oircKqnGnfL7KK2uR72hfTdoH3c37HguvnOnfQdQUVeBd356B+PCx2HOoDmCvrdtM40bP5qmY2qevr+iwY83SyGXSrD68fZPOd3VNK4Z6eVuHiljYiaof1MDALxkXvC2rNHTINDTF1qtBk/HBzo1iZajSc+Eaqbh+4zYLJRHNSPEEUedqbmGa0bnZABbpzeiuKoOxVX12J9zF99cvAuphMMnz46Er6eTnWG7AApGnMDXjDT0iuZnZxTwW5Ptt77mqp9rdQac+vke/n2tGMdvlOC32qZnVfSUS+HvJYenXAo3iQRuUg5uEg4cx0FnMKHeYES9wQSdwYT+wd6YOlSFaUNVCPLp/BqRbVe24eSvJ5FZmIlJEZMQ5Clce7Z9M03HdWCtqNVh3bfXAACvTOwnWKe5rqBxzYhMIoOfwg8V9RU49MshAEBvb/vmqGBvP+RpgbhI564p29pDQMC1aZh1B9aO+IyT7sO2HyHw4NrRGVp3zRiMJlwrqsLZvHJca/giebusFpX37e/nG54ajkmDQhy8i+tpVzCyadMmbNiwARqNBnFxcfjkk08QH9/0DKP79u3DqlWrkJ+fj5iYGLz33nt49FEnx1h3AbYXXocEIzbzjEhsqp/vlNfix5ulOHq9GKdvlVrVenjIpBgZ4Yfhvf0wIMQbkQFeCPZRIMBbDk+5a8ShlfWV2KveCwDQmXT4x7V/YNlDywR7f/vp4B0P7a2q00NTWYeiyjpU1xlQpzfivt6IOr0ROqMJcqkEsoYfuZsEMinHb5O7SXD5biU+P5mLqjoDIvw98drETl7Lp4M1rhmx/FtRX4Gvfv4KAPDUgKfsXmMZUWNpxmkvx99GhZ0OvjsP7SXCaW42YH0z10x1vQEn1CU4fLUYJ26UQFvv+BniLpNApXRHsNIdz8ZHYOZI151x1Vabn0h79+5FamoqtmzZgoSEBHz00UdITk6GWq1GcLB9u1VGRgbmzp2LtLQ0PPbYY9i9ezdmzpyJCxcuYNiwYYJkQiy2zTSWviNCBiO239wtoz2KKu9j4objyLeZ7riPvwemDlFhypAQjI7s5fI9rHdf341aQy2UciWqdFXYq96LF2NfhK/CV9DzWG4YMkszDQf878FrUBdrodZoUdIw54KzBoR444OnR4i+tofQGteMWP7NrcwFA4PKS4VZMfZt5T5y82gsoYIRq2YaCDuapicM7SXOa7xIngUfjBitr5nfanRIv16Mw1c0+PFWKT/rLWCe2yU+2h9xvf0QE+KN6EBvqHzdoXR3c+mJzZrT5mBk48aNWLRoEZ57zjyV7ZYtW3Do0CFs27YNb731lt3xH3/8MaZNm4bly5cDAN59912kp6fj008/xZYtW5xMvnNK75dCZ2z70tMmZsId7R1+xknbmhGtXovC6kJB0tjUEve1hhr8VnkXbnIOw8KViI/yx7gBQegb6NVwsdbj3n2NIGkQi86ow67r5qmTVz28CluvbMWN8hvYemUrnhn4jCDnqNZXA3jw95VLH/QZ2XrmAn8c5wYoPdwQ5KOAj0IGhczcydddZm7mMphMMBgZ9EYT9A2/G4wMOqMJeoMJCpkEs0aFI2mwClJJDQqrawRJf1dRet88zX3jmhGLRbGLIJfaj5Kx1IwU1RQ59Xmx1Mo4egCU3i916r0tgZLtDKx6o16wzzjpPiwjx/g5Rhr9frNUg89On0PevRr8XKzF1cIqGE0PamAjgj0xfkAgxg8IwmCV0qaWVosaoxY1HXzbCPQIdPhZ7QxtCkZ0Oh2ys7OxcuVKfptEIkFSUhIyMzMdviYzMxOpqalW25KTk7F///4mz1NfX4/6+gffRKuqqtqSzFZbenwp/nPvP06/j+UbniUYOX33NJL/lez0+zZmaUYYHOqLjN8AmfIyZMrLAIBcALka4AvXjj2aFKWMwpTIKeA4Dm+cfAPbr2zH9ivbO+Rc/g2jhDiOwTvmPat9JgDFDT8AzPcIR7GspOHHpk/Zxhvmn+6scc0IYB5BM7P/TIfHWj43+37eh30/73P63I2ng7d8e/zz6T87/b6A/dBerV4r+GecdB+NA2OpRAqYALVuH9S5Dde5B+Bh01L7G4ADZcABx4/STrHr0V2IC4oT5dxtCkZKS0thNBoREmLdYSYkJAQ3bji+y2o0GofHazRNPznT0tKwdu3atiStXWQSGb/CaFsFewZjSMAQjAsfh94+5s55Y1RjEOoVyq9eKpQRQSP4m/vUvuPwbd6XqNRVCnqOrkohVSB1dCqkEimSIpIwNnwszmvOC3oOpVyJxNBEAOYZRB8OfRgXSy4Keo6eIDE0EX4KPwDAlMgpOPXrKSwfs7zJb1pjw8diz409qNI5/2VDykkxNWoq///kqGTkVeYJMh+Pn8IPCaoEAECYdxhGBI3A9fLrTr8v6Z44cHg0+kGfyMf6TcHOny+DwdxMI+HMwbKE49q7fmqHaRzQd/q5WRu6mxcWFiI8PBwZGRlITEzkt7/55ps4efIksrKy7F4jl8uxc+dOzJ07l9/22WefYe3atSguLrY7HnBcM9KnTx9UVlZCqey6CzURQggh5IGqqir4+vq2+PxuU81IYGAgpFKpXRBRXFwMlUrl8DUqlapNxwOAQqGAQtE9JtUihBBCSPPaNNRCLpdj9OjROHr0KL/NZDLh6NGjVjUljSUmJlodDwDp6elNHk8IIYSQnqXNo2lSU1OxYMECPPTQQ4iPj8dHH32EmpoafnTN/PnzER4ejrS0NADAkiVLMGHCBHzwwQeYPn069uzZg/Pnz+Pvf/+7sDkhhBBCiEtqczAyZ84c3Lt3D6tXr4ZGo8GIESPwww8/8J1UCwoK+CnLAeCRRx7B7t278c477+Dtt99GTEwM9u/f7/JzjBBCCCFEGG3qwCqW1naAIYQQQkjX0drnt2tPz0kIIYQQl0fBCCGEEEJERcEIIYQQQkRFwQghhBBCREXBCCGEEEJERcEIIYQQQkRFwQghhBBCREXBCCGEEEJERcEIIYQQQkTV5ungxWCZJLaqqkrklBBCCCGktSzP7ZYme3eJYESr1QIA+vTpI3JKCCGEENJWWq0Wvr6+Te53ibVpTCYTCgsL4ePjA47jBHvfqqoq9OnTB3fu3Om2a95QHl1fd88fQHnsDrp7/oDun8eOyB9jDFqtFmFhYVaL6NpyiZoRiUSC3r17d9j7K5XKbnlhNUZ5dH3dPX8A5bE76O75A7p/HoXOX3M1IhbUgZUQQgghoqJghBBCCCGi6tHBiEKhwJo1a6BQKMROSoehPLq+7p4/gPLYHXT3/AHdP49i5s8lOrASQgghpPvq0TUjhBBCCBEfBSOEEEIIERUFI4QQQggRFQUjhBBCCBFVjw5GNm3ahKioKLi7uyMhIQFnz54VO0ntkpaWhjFjxsDHxwfBwcGYOXMm1Gq11TETJ04Ex3FWP6+88opIKW67v/zlL3bpHzRoEL+/rq4OixcvRkBAALy9vTF79mwUFxeLmOK2i4qKsssjx3FYvHgxANcrw1OnTuHxxx9HWFgYOI7D/v37rfYzxrB69WqEhobCw8MDSUlJuHnzptUx5eXlmDdvHpRKJfz8/PDCCy+gurq6E3PRvObyqNfrsWLFCsTGxsLLywthYWGYP38+CgsLrd7DUbmvX7++k3PStJbKceHChXbpnzZtmtUxXbkcW8qfo88kx3HYsGEDf0xXLsPWPB9ac/8sKCjA9OnT4enpieDgYCxfvhwGg0GwdPbYYGTv3r1ITU3FmjVrcOHCBcTFxSE5ORklJSViJ63NTp48icWLF+PMmTNIT0+HXq/H1KlTUVNTY3XcokWLUFRUxP+8//77IqW4fYYOHWqV/tOnT/P7/vSnP+Hbb7/Fvn37cPLkSRQWFmLWrFkiprbtzp07Z5W/9PR0AMDTTz/NH+NKZVhTU4O4uDhs2rTJ4f73338ff/vb37BlyxZkZWXBy8sLycnJqKur44+ZN28erl69ivT0dBw8eBCnTp3CSy+91FlZaFFzeaytrcWFCxewatUqXLhwAV9//TXUajWeeOIJu2PXrVtnVa5/+MMfOiP5rdJSOQLAtGnTrNL/xRdfWO3vyuXYUv4a56uoqAjbtm0Dx3GYPXu21XFdtQxb83xo6f5pNBoxffp06HQ6ZGRkYOfOndixYwdWr14tXEJZDxUfH88WL17M/99oNLKwsDCWlpYmYqqEUVJSwgCwkydP8tsmTJjAlixZIl6inLRmzRoWFxfncF9FRQWTyWRs3759/Lbr168zACwzM7OTUii8JUuWsH79+jGTycQYc+0yBMC++eYb/v8mk4mpVCq2YcMGfltFRQVTKBTsiy++YIwxdu3aNQaAnTt3jj/m+++/ZxzHsbt373Za2lvLNo+OnD17lgFgt2/f5rdFRkayDz/8sGMTJxBHeVywYAGbMWNGk69xpXJsTRnOmDGDTZo0yWqbK5Wh7fOhNffP7777jkkkEqbRaPhjNm/ezJRKJauvrxckXT2yZkSn0yE7OxtJSUn8NolEgqSkJGRmZoqYMmFUVlYCAPz9/a22//Of/0RgYCCGDRuGlStXora2VozktdvNmzcRFhaGvn37Yt68eSgoKAAAZGdnQ6/XW5XnoEGDEBER4bLlqdPpsGvXLjz//PNWi0O6ehla5OXlQaPRWJWZr68vEhIS+DLLzMyEn58fHnroIf6YpKQkSCQSZGVldXqahVBZWQmO4+Dn52e1ff369QgICMDIkSOxYcMGQau/O8OJEycQHByMgQMH4tVXX0VZWRm/rzuVY3FxMQ4dOoQXXnjBbp+rlKHt86E198/MzEzExsYiJCSEPyY5ORlVVVW4evWqIOlyiYXyhFZaWgqj0Wj1hwWAkJAQ3LhxQ6RUCcNkMmHp0qUYO3Yshg0bxm9/9tlnERkZibCwMFy6dAkrVqyAWq3G119/LWJqWy8hIQE7duzAwIEDUVRUhLVr12LcuHG4cuUKNBoN5HK53Q0+JCQEGo1GnAQ7af/+/aioqMDChQv5ba5eho1ZysXRZ9CyT6PRIDg42Gq/m5sb/P39XbJc6+rqsGLFCsydO9dqEbI//vGPGDVqFPz9/ZGRkYGVK1eiqKgIGzduFDG1rTdt2jTMmjUL0dHRyM3Nxdtvv42UlBRkZmZCKpV2q3LcuXMnfHx87JqAXaUMHT0fWnP/1Gg0Dj+rln1C6JHBSHe2ePFiXLlyxao/BQCr9tnY2FiEhoZi8uTJyM3NRb9+/To7mW2WkpLC/z58+HAkJCQgMjISX375JTw8PERMWcfYunUrUlJSEBYWxm9z9TLsyfR6PX73u9+BMYbNmzdb7UtNTeV/Hz58OORyOV5++WWkpaW5xLTjzzzzDP97bGwshg8fjn79+uHEiROYPHmyiCkT3rZt2zBv3jy4u7tbbXeVMmzq+dAV9MhmmsDAQEilUrvewsXFxVCpVCKlynmvv/46Dh48iOPHj6N3797NHpuQkAAAuHXrVmckTXB+fn4YMGAAbt26BZVKBZ1Oh4qKCqtjXLU8b9++jSNHjuDFF19s9jhXLkNLuTT3GVSpVHYdyg0GA8rLy12qXC2ByO3bt5Gent7i0uwJCQkwGAzIz8/vnAQKrG/fvggMDOSvy+5Sjj/++CPUanWLn0uga5ZhU8+H1tw/VSqVw8+qZZ8QemQwIpfLMXr0aBw9epTfZjKZcPToUSQmJoqYsvZhjOH111/HN998g2PHjiE6OrrF1+Tk5AAAQkNDOzh1HaO6uhq5ubkIDQ3F6NGjIZPJrMpTrVajoKDAJctz+/btCA4OxvTp05s9zpXLMDo6GiqVyqrMqqqqkJWVxZdZYmIiKioqkJ2dzR9z7NgxmEwmPhDr6iyByM2bN3HkyBEEBAS0+JqcnBxIJBK7pg1X8euvv6KsrIy/LrtDOQLm2srRo0cjLi6uxWO7Uhm29Hxozf0zMTERly9ftgoqLYH1kCFDBEtoj7Rnzx6mUCjYjh072LVr19hLL73E/Pz8rHoLu4pXX32V+fr6shMnTrCioiL+p7a2ljHG2K1bt9i6devY+fPnWV5eHjtw4ADr27cvGz9+vMgpb71ly5axEydOsLy8PPbTTz+xpKQkFhgYyEpKShhjjL3yyissIiKCHTt2jJ0/f54lJiayxMREkVPddkajkUVERLAVK1ZYbXfFMtRqtezixYvs4sWLDADbuHEju3jxIj+SZP369czPz48dOHCAXbp0ic2YMYNFR0ez+/fv8+8xbdo0NnLkSJaVlcVOnz7NYmJi2Ny5c8XKkp3m8qjT6dgTTzzBevfuzXJycqw+m5YRCBkZGezDDz9kOTk5LDc3l+3atYsFBQWx+fPni5yzB5rLo1arZW+88QbLzMxkeXl57MiRI2zUqFEsJiaG1dXV8e/RlcuxpeuUMcYqKyuZp6cn27x5s93ru3oZtvR8YKzl+6fBYGDDhg1jU6dOZTk5OeyHH35gQUFBbOXKlYKls8cGI4wx9sknn7CIiAgml8tZfHw8O3PmjNhJahcADn+2b9/OGGOsoKCAjR8/nvn7+zOFQsH69+/Pli9fziorK8VNeBvMmTOHhYaGMrlczsLDw9mcOXPYrVu3+P33799nr732GuvVqxfz9PRkTz75JCsqKhIxxe1z+PBhBoCp1Wqr7a5YhsePH3d4XS5YsIAxZh7eu2rVKhYSEsIUCgWbPHmyXb7LysrY3Llzmbe3N1Mqley5555jWq1WhNw41lwe8/LymvxsHj9+nDHGWHZ2NktISGC+vr7M3d2dDR48mP31r3+1epCLrbk81tbWsqlTp7KgoCAmk8lYZGQkW7Rokd2Xuq5cji1dp4wx9vnnnzMPDw9WUVFh9/quXoYtPR8Ya939Mz8/n6WkpDAPDw8WGBjIli1bxvR6vWDp5BoSSwghhBAiih7ZZ4QQQgghXQcFI4QQQggRFQUjhBBCCBEVBSOEEEIIERUFI4QQQggRFQUjhBBCCBEVBSOEEEIIERUFI4QQQggRFQUjhBDRTJw4EUuXLhU7GYQQkVEwQgghhBBR0XTwhBBRLFy4EDt37rTalpeXh6ioKHESRAgRDQUjhBBRVFZWIiUlBcOGDcO6desAAEFBQZBKpSKnjBDS2dzETgAhpGfy9fWFXC6Hp6cnVCqV2MkhhIiI+owQQgghRFQUjBBCCCFEVBSMEEJEI5fLYTQaxU4GIURkFIwQQkQTFRWFrKws5Ofno7S0FCaTSewkEUJEQMEIIUQ0b7zxBqRSKYYMGYKgoCAUFBSInSRCiAhoaC8hhBBCREU1I4QQQggRFQUjhBBCCBEVBSOEEEIIERUFI4QQQggRFQUjhBBCCBEVBSOEEEIIERUFI4QQQggRFQUjhBBCCBEVBSOEEEIIERUFI4QQQggRFQUjhBBCCBEVBSOEEEIIEdX/Azwf27UKXvXVAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -396,10 +435,12 @@ ], "source": [ "import matplotlib.pyplot as plt\n", + "n_timesteps = 200\n", "(\n", - " cr_ep[cr_ep.t < 400].plot(x='t', title=f'CR episode, rew={sum(cr_ep.rew):.2f}'),\n", - " ppo1_ep[ppo1_ep.t < 400].plot(x='t', title=f'PPO1 episode, rew={sum(ppo1_ep.rew):.2f}'),\n", - " ppo2_ep[ppo2_ep.t < 400].plot(x='t', title=f'PPO2 episode, rew={sum(ppo2_ep.rew):.2f}'),\n", + " cr_ep[cr_ep.t < n_timesteps].plot(x='t', title=f'CR episode, rew={sum(cr_ep.rew):.2f}'),\n", + " ppo1_ep[ppo1_ep.t < n_timesteps].plot(x='t', title=f'PPO1 episode, rew={sum(ppo1_ep.rew):.2f}'),\n", + " ppo2_ep[ppo2_ep.t < n_timesteps].plot(x='t', title=f'PPO2 episode, rew={sum(ppo2_ep.rew):.2f}'),\n", + " ppoEsc_ep[ppoEsc_ep.t < n_timesteps].plot(x='t', title=f'PPO_Esc episode, rew={sum(ppoEsc_ep.rew):.2f}'),\n", ")\n", "plt.show()" ] @@ -414,7 +455,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 58, "id": "a20d7ed0-8a57-42aa-84f1-ecc148e7988d", "metadata": {}, "outputs": [], @@ -432,33 +473,35 @@ " for obs in obs_list\n", " ]\n", " }\n", + " )\n", + "\n", + "def get_esc_policy_df(policy_obj, mwt, minx=-1, maxx=1, nx=500):\n", + " env=AsmEnvEsc(config=CONFIG3)\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'mwt': [mwt for _ in obs_list],\n", + " 'biomass': env.bound * (obs_list + 1)/2,\n", + " 'fishing_escapement': [\n", + " # env.get_mortality(\n", + " # policy_obj.predict(np.float32([obs, mwt]))[0]\n", + " # )[0] \n", + " env.bound * (\n", + " 1+policy_obj.predict(np.float32([obs, mwt]))[0][0]\n", + " ) / 2\n", + " for obs in obs_list\n", + " ]\n", + " }\n", " )" ] }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 59, "id": "245547ba-b2ba-4e61-8409-4e98c79d47fc", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n", - "Check: False\n" - ] - } - ], + "outputs": [], "source": [ "cr_df = get_policy_df(cr3, mwt=0.5, maxx=-1+0.14)\n", "\n", @@ -472,12 +515,18 @@ "ppo2_df_mwt2 = get_policy_df(ppoAgent2, mwt=0.4, maxx=-1+0.14)\n", "ppo2_df_mwt3 = get_policy_df(ppoAgent2, mwt=0.5, maxx=-1+0.14)\n", "ppo2_df_mwt4 = get_policy_df(ppoAgent2, mwt=0.6, maxx=-1+0.14)\n", - "ppo2_df_mwt5 = get_policy_df(ppoAgent1, mwt=0.8, maxx=-1+0.14)" + "ppo2_df_mwt5 = get_policy_df(ppoAgent2, mwt=0.8, maxx=-1+0.14)\n", + "\n", + "ppoEsc_df_mwt1 = get_esc_policy_df(ppoAgentEsc, mwt=0.3, maxx=-1+0.14)\n", + "ppoEsc_df_mwt2 = get_esc_policy_df(ppoAgentEsc, mwt=0.4, maxx=-1+0.14)\n", + "ppoEsc_df_mwt3 = get_esc_policy_df(ppoAgentEsc, mwt=0.5, maxx=-1+0.14)\n", + "ppoEsc_df_mwt4 = get_esc_policy_df(ppoAgentEsc, mwt=0.6, maxx=-1+0.14)\n", + "ppoEsc_df_mwt5 = get_esc_policy_df(ppoAgentEsc, mwt=0.8, maxx=-1+0.14)" ] }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 60, "id": "7473b83a-64db-45c2-aec7-c6055d881a7f", "metadata": {}, "outputs": [], @@ -498,18 +547,27 @@ " ppo2_df_mwt4,\n", " ppo2_df_mwt5,\n", " ]\n", + ")\n", + "\n", + "ppoEsc_df = pd.concat(\n", + " [ppoEsc_df_mwt1,\n", + " ppoEsc_df_mwt2,\n", + " ppoEsc_df_mwt3,\n", + " ppoEsc_df_mwt4,\n", + " ppoEsc_df_mwt5,\n", + " ]\n", ")" ] }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 61, "id": "339e8de2-9152-4cd5-be35-2234ca5dac5a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -529,13 +587,13 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 62, "id": "a4f825c2-8935-4152-8feb-daee36c7bf3a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -555,7 +613,38 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 69, + "id": "95150d6b-558d-4a1b-be4d-c627b507d629", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "ppoEsc_where_it_matters = (\n", + " ppoEsc_df[ppoEsc_df.fishing_escapement < ppoEsc_df.biomass]\n", + ")\n", + "\n", + "ggplot(\n", + " ppoEsc_where_it_matters,\n", + " aes(x='biomass', y='fishing_escapement', color='mwt')\n", + ")+geom_point()" + ] + }, + { + "cell_type": "code", + "execution_count": 50, "id": "e9d562ac-f0d7-4601-9404-bf8d1992ed8f", "metadata": {}, "outputs": [ diff --git a/src/rl4fisheries/envs/asm_esc.py b/src/rl4fisheries/envs/asm_esc.py index 3617349..6de10fd 100644 --- a/src/rl4fisheries/envs/asm_esc.py +++ b/src/rl4fisheries/envs/asm_esc.py @@ -16,13 +16,14 @@ def step(self, action): self.update_vuls() self.update_ssb() # - escapement = self.escapement_units(action) - current_pop = self.population_units() - if current_pop <= 0: - mortality = np.float32([0]) - else: - mortality = (current_pop - escapement) / current_pop - mortality = np.clip(mortality, 0, np.inf) + # escapement = self.escapement_units(action) + # current_pop = self.population_units() + # if current_pop <= 0: + # mortality = np.float32([0]) + # else: + # mortality = (current_pop - escapement) / current_pop + # mortality = np.clip(mortality, 0, np.inf) + mortality = self.get_mortality(action) self.state, reward = self.harvest(mortality) # self.update_vuls() @@ -37,4 +38,14 @@ def step(self, action): return observation, reward, terminated, False, {} def escapement_units(self, action): - return self.bound * (action + 1) / 2 \ No newline at end of file + return self.bound * (action + 1) / 2 + + def get_mortality(self, action): + escapement = self.escapement_units(action) + current_pop = self.population_units() + if current_pop <= 0: + mortality = np.float32([0]) + else: + mortality = (current_pop - escapement) / current_pop + mortality = np.clip(mortality, 0, np.inf) + return mortality \ No newline at end of file From 3b11b125cd72fb8b2b23ccb83a80ed77c4412bf7 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 24 May 2024 17:39:49 +0000 Subject: [PATCH 49/64] results notebook update --- notebooks/result_plots.ipynb | 171 ++++++++++++++++++++++++++--------- 1 file changed, 130 insertions(+), 41 deletions(-) diff --git a/notebooks/result_plots.ipynb b/notebooks/result_plots.ipynb index ec96ef8..4d394e4 100644 --- a/notebooks/result_plots.ipynb +++ b/notebooks/result_plots.ipynb @@ -19,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "id": "2119a088-27b1-490f-9114-23c4e3f69ca6", "metadata": {}, "outputs": [], @@ -106,7 +106,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "id": "9fc5702e-71b1-4af9-abd3-20e0ed6d0915", "metadata": {}, "outputs": [], @@ -124,7 +124,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "id": "81938413-d860-4195-b5dc-12bc110e39ba", "metadata": {}, "outputs": [], @@ -154,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "id": "99ed7e7d-8a48-4a4f-89eb-5e01718a8fec", "metadata": {}, "outputs": [], @@ -329,7 +329,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 7, "id": "fee15370-568a-4fdc-8c16-a3db8e33256f", "metadata": {}, "outputs": [], @@ -354,7 +354,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 8, "id": "c8be4e61-5766-4402-bf1d-be7308751ce4", "metadata": {}, "outputs": [], @@ -364,7 +364,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 11, "id": "55d46a8d-1f8f-4f25-b58a-f036c64ce18b", "metadata": {}, "outputs": [], @@ -388,13 +388,13 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 12, "id": "6866d87d-6193-45af-bf54-b8ef1e4db651", "metadata": {}, "outputs": [ { "data": { - "image/png": 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+85/5xx9/nL/jjjv4kSNH8n/5y18Ctr3zzjt5AHxBQQHv9XrF60ePHs0D4K+99lrZ/YiHSP/D5MmTRZHtP//5z4AfKgam1NbW8rW1teLfR44c4QsLC/mbb76Zf/TRR/lHH32U/853vsMD4BcuXBjwP+7bt4+3WCx8bm4uv3z5cn716tX8VVddxQPgzz333IT93wyGUljAwmCo4MCBA/wNN9zA19XV8Uajkc/Ly+PPPPNM/q9//Svf19cnbicXsDzzzDM8AP4f//hH1Od74okn+GnTpvHZ2dl8Xl4eP3HiRP6OO+4IcNulz/XBBx/wkyZN4k0mEz9mzJiQduVwXUI/+tGP+OHDh/Nms5kvLi7mzznnHP7jjz8OuJ/b7ebvuecefujQoXxWVhZfU1PDL1++POD/5XnSGnzPPffwVVVVfHZ2Nj9v3jx+165dYZ1ue3t7+eXLl/MjRozgjUYjX1pays+ePZt/8MEHAwK5Sy+9lM/Ozg5oIw5HtA6b1157jT/rrLN4i8XCWywWfsyYMfwtt9zC79+/P2C7d955RwwS/bn++ut5APzTTz8tux/xEOl/gEyr9Ny5cwO2DQ5YOjs7+auvvpofMWIEn5OTw5tMJn78+PH8Aw88EDZg3rdvH//973+fr6mp4bOysvja2lr+l7/8ZcQuMgYjmXA8H5QnZTAYGUVdXR0mTJiAt99+O9W7ojkVFRVYvHgx/vKXv6R6VxgMRophGhYGg5GW7N69Gw6HQzMbfAaDkdmwLiEGg5GWjB8/Xnb2DYPBGFiwDAuDwWAwGIy0h2lYGAwGg8FgpD2qMyyffvopLrzwQlRXV4PjOLz55puy21977bXgOC7kZ/z48eI2dDS8/w+bDMpgMBgMBoOiOmCx2WyYPHkyVq1apWj7Rx99FI2NjeJPQ0MDiouLcdlllwVsN378+IDt/Me8MxgMBoPBGNioFt0uWrQIixYtUrx9QUGBOEgNAN588010dnZi6dKlgTtiMER05IyGz+fDqVOnkJeXp+nMEwaDwWAwGImD53n09vaiuroaOp18DiXpXUJPP/005s+fL84eodTX16O6uhpmsxmzZs3CihUrMGTIEEWPeerUKdTU1CRidxkMBoPBYCSYhoaGgIGr4UhqwHLq1Cm89957IQO/Zs6ciWeeeQajR49GY2Mj7rnnHsyZMwe7du1CXl5eyOM4nU5x1gkAcUZIQ0MD8vPzE/tPMBgMBoPB0ISenh7U1NSEPdcHk9SA5dlnn0VhYSEuvvjigOv9S0yTJk3CzJkzUVtbi1dffRXXXXddyOOsWLEC99xzT8j1+fn5LGBhMBgMBiPDUCLnSJoPC8/zWLNmDa655hoYjUbZbQsLCzFq1CgcPHgw7O3Lly9Hd3e3+NPQ0JCIXWYwGAwGg5EmJC1gWb9+PQ4ePBg2YxKM1WrFoUOHQsa4U0wmk5hNYVkVBoPBYDD6P6oDFqvVih07dmDHjh0AgCNHjmDHjh04fvw4AJL9WLx4ccj9nn76acycORMTJkwIue2Xv/wl1q9fj6NHj2LTpk245JJLoNfrcdVVV6ndPQaDwWAwGP0Q1RqWrVu34pxzzhH/XrZsGQBgyZIleOaZZ9DY2CgGL5Tu7m689tprePTRR8M+5okTJ3DVVVehvb0dZWVlOOuss/D555+jrKxM7e7J4vV64Xa7NX1MhnZkZWVBr9enejcYDAaDkYb0C2v+np4eFBQUoLu7O2x5iOd5NDU1oaurK/k7x1BFYWEhKisrmZ8Og8FgDACinb/9GRDTmmmwUl5ejpycHHYyTEN4nofdbkdLSwsARNQvMRgMBmNg0u8DFq/XKwYrJSUlqd4dhgzZ2dkAgJaWFpSXl7PyEIPBYDBEktYllCqoZiUnJyfFe8JQAn2fmNaIwWAwGP70+4CFwspAmQF7nxgMBoMRjgETsDAYDAaDwchcWMCSxsybNw+33357xNvr6uqwcuXKpO0Pg8FgMBipot+LbvszX375JSwWS6p3g8FgMBiMhMMClgxGa2M9Rubi9HiRpdNBp2MaIAaD0T9hJaE0x+Px4NZbb0VBQQFKS0vxu9/9DtTrL7gkdPz4cVx00UXIzc1Ffn4+Lr/8cjQ3N4u3//73v8eUKVOwZs0aDBkyBLm5ufjJT34Cr9eLP//5z6isrER5eTnuv//+gH14+OGHMXHiRFgsFtTU1OAnP/kJrFarePuxY8dw4YUXoqioCBaLBePHj8e7774LAOjs7MQPf/hDlJWVITs7GyNHjsQ//vGPBL5iA49uuxvnPvwpvrtqI/qBDySDwWCEZUBmWHieh8PtTclzZ2fpVXXCPPvss7juuuuwZcsWbN26FTfeeCOGDBmCG264IWA7n88nBivr16+Hx+PBLbfcgiuuuALr1q0Ttzt06BDee+89vP/++zh06BC+//3v4/Dhwxg1ahTWr1+PTZs24Uc/+hHmz5+PmTNnAgB0Oh0ee+wxDB06FIcPH8ZPfvIT3HHHHfj73/8OALjlllvgcrnw6aefwmKxYM+ePcjNzQUA/O53v8OePXvw3nvvobS0FAcPHoTD4YjzVWT4s/rTQzjeYQcANPX0oaogO8V7xGAwMhme59Fld6PIYkz1rgQwIAMWh9uLcXd9kJLn3nPvAuQYlb/sNTU1eOSRR8BxHEaPHo2dO3fikUceCQlY1q5di507d+LIkSOoqakBADz33HMYP348vvzyS5x++ukASGCzZs0a5OXlYdy4cTjnnHOwf/9+vPvuu9DpdBg9ejT+9Kc/4ZNPPhEDFn/hb11dHe677z78+Mc/FgOW48eP49JLL8XEiRMBAMOGDRO3P378OKZOnYrp06eL92doR0tPH/7x2RHx74MtVhawMBiMmOF5Hne+thOvbG3Asz+agbmj0kd6wEpCac4ZZ5wRkJGZNWsW6uvr4fUGZoj27t2LmpoaMVgBgHHjxqGwsBB79+4Vr6urq0NeXp74d0VFBcaNGwedThdwHbXIB4CPP/4Y3/72tzFo0CDk5eXhmmuuQXt7O+x2sqr/2c9+hvvuuw9nnnkm7r77bnzzzTfifW+++Wa8/PLLmDJlCu644w5s2rRJg1eFQXnsf/Xoc/vEv+ubrTJbMxgMhjzPf3Ecr2xtAABsOtiW4r0JZEBmWLKz9Nhz74KUPXcqycrKCvib47iw1/l85CR49OhRXHDBBbj55ptx//33o7i4GBs3bsR1110Hl8uFnJwcXH/99ViwYAHeeecdfPjhh1ixYgUeeugh/PSnP8WiRYtw7NgxvPvuu/joo4/w7W9/G7fccgsefPDBpP3P/ZWGDjte3kIOLDOGFmPLkQ4cbGUBC4PBiI0dDV34w3/3iH8fabOlcG9CGZAZFo7jkGM0pORHrZPrF198EfD3559/jpEjR4bM2Rk7diwaGhrQ0NAgXrdnzx50dXVh3LhxMb9W27Ztg8/nw0MPPYQzzjgDo0aNwqlTp0K2q6mpwY9//GO8/vrr+MUvfoEnn3xSvK2srAxLlizB888/j5UrV+KJJ56IeX8YEpsPt8Pj4zGttghXzSCZtYMsw8JgMGLkN6/vhMvrQ00xKSsfbWcBC0MFx48fx7Jly7B//3689NJL+Otf/4rbbrstZLv58+dj4sSJ+OEPf4jt27djy5YtWLx4MebOnSvqR2JhxIgRcLvd+Otf/4rDhw/jn//8J1avXh2wze23344PPvgAR44cwfbt2/HJJ59g7NixAIC77roLb731Fg4ePIjdu3fj7bffFm9jxEeHzQUAqC3OwchyUuZjGRYGgxELPM+jvqUXALDikkkAgGPtdvh86dN5yAKWNGfx4sVwOByYMWMGbrnlFtx222248cYbQ7bjOA5vvfUWioqKcPbZZ2P+/PkYNmwYXnnllbief/LkyXj44Yfxpz/9CRMmTMALL7yAFStWBGzj9Xpxyy23YOzYsVi4cCFGjRolCnKNRiOWL1+OSZMm4eyzz4Zer8fLL78c1z4xCJ1CwFJkMWJYGTEQ7LC50G51pnK3GAxGBtLr9MDtJcHJlCGFMOg4OD0+NPb0pXjPJDi+Hxg39PT0oKCgAN3d3cjPzw+4ra+vD0eOHMHQoUNhNptTtIcMpbD3Szm//NfX+Pe2E/jVgtG45ZwROOtP/8OJTgdeufEMzBxWkurdYzAYGcTRNhvmPbgOOUY99ty7EN96cB0Ot9nw4vUzMXtEacKeV+78HQzLsDAYGQrNsBQLXgkjy4n3DSsLMRgMtbQHHU/qSknW9kga6VhYwMJgZCjBB5gRQsDCWpsZDIZaqCauhAYsJSRgOZpGnUIsYGEwMpROe3CGhQhvD7EMC4PBUEmHjWjfpAxLDgDgSJs9ZfsUDAtYGIwMpcMaGLAMZxkWBoMRI1LG1gTAL8PCSkIMBiMeXB4fep0eAEBxTmBJqKmnD7197pTtG4PByDzoAqg0lxxPhgoaluPtdnjTpLWZBSwMRgZCy0E6DijIJk7FBdlZqMgnq6ODLSzLwmAwlNMRpImrLsyGUa+Dy+vDqa70GFjLAhYGIwOhB5eiHCN0Osk9eXARqTs3p5F3AoPBSH+CRfx6HZd2jrcsYGEwMpDg1RCFpnNbhfQug8FgKEHsEsqVjim0LJQunUIsYGEwMpAOP5dbf0pySUmorZe53TIYDOV0BIluAUl4my6dQixgYTAykGDPBEqpELC021jAwmAwlEOPGf7HFGoed7yDZVgYKaaurg4rV65M9W4wYiBShoWWhNp6WUmIwWAow+7yoM/tAxBYZi7LEzK2aVJiZgELg5GB0C4hlmFhMBjx0i4EJCaDDjlGvXg9Pb7QBVKqYQFLGjNv3jz89Kc/xe23346ioiJUVFTgySefhM1mw9KlS5GXl4cRI0bgvffeAwBMnz4dDz74oHj/iy++GFlZWbBaSYvriRMnwHEcDh48iHnz5uHYsWP4+c9/Do7jwHFc2H1gpCftfl1C/tCAJV1WRAwGI/3xLzH7nwuKWcCSBvA84LKl5kflcOxnn30WpaWl2LJlC37605/i5ptvxmWXXYbZs2dj+/btOO+883DNNdfAbrdj7ty5WLdunfAv8tiwYQMKCwuxceNGAMD69esxaNAgjBgxAq+//joGDx6Me++9F42NjWhsbNT6VWYkkM4win7/v5nolsFgKEUU3AYfTwQBrtXpgdPjTfp+BWNI9Q6kBLcdeKA6Nc/9m1OA0aJ488mTJ+O3v/0tAGD58uX44x//iNLSUtxwww0AgLvuuguPP/44vvnmG8ybNw9PP/00vF4vdu3aBaPRiCuuuALr1q3DwoULsW7dOsydOxcAUFxcDL1ej7y8PFRWVmr/fzISSkeUDEuv04M+txfmLH3IfRkMBsOfNiudI2QKuD4/2wCDjoPHx6PD5kJVQXYqdk9kYGZYMohJkyaJv+v1epSUlGDixInidRUVFQCAlpYWzJkzB729vfjqq6+wfv16zJ07F/PmzROzLuvXr8e8efOSufuMBBHJhyXfbIBRT77W7WmSxmUwGOlNpK5DjuPEY0x7GpSZB2aGJSuHZDpS9dxqNs/KCvib47iA62i90efzobCwEJMnT8a6deuwefNmnHvuuTj77LNxxRVX4MCBA6ivrxczLIzMhef5kEnNFI7jUJJrRGN3H9qtTgwqTO2KiMFgpD+RFkD0upZeZ1osgAZmwMJxqsoymcTcuXPxySefYMuWLbj//vtRXFyMsWPH4v7770dVVRVGjRolbms0GuH1pr4uyVBHr9MDt5doocIdYEpzTWjs7hPTvAwGgyFHsC2/P1QX15EGnYesJNTPmDdvHj744AMYDAaMGTNGvO6FF14Iya7U1dXh008/xcmTJ9HW1paK3WXEAJ2qmmPUh9WolDAvFgaDoYJIJSFA0rWkQ0mIBSz9jDlz5sDn8wUEJ/PmzYPX6w3Rr9x77704evQohg8fjrKysiTvKSNWOiKUgyhia3MarIgYDEb6I5thSaPW5oFZEsoQqFjWn6NHj4Zcx/u1ShcXF8Pn8wXcfvHFFwdsQznjjDPw9ddfx72fjORCMyyRAhaWYWEwGGqg5Z5gmwQgvbxYWIaFwcgwomVYypjbLYPBUIG0CDKF3CZ2CWViwPLpp5/iwgsvRHV1NTiOw5tvvim7/bp160QnVf+fpqamgO1WrVqFuro6mM1mzJw5E1u2bFG7awzGgEBU9OdEKQkx0S2DwYhCn9sLm4s0X6R7SUh1wGKz2TB58mSsWrVK1f32798vOqo2NjaivLxcvO2VV17BsmXLcPfdd2P79u2YPHkyFixYgJaWFrW7x2D0ezpl6s0AKwkxGAzl0EAkS88h3xyqEkmnkpBqDcuiRYuwaNEi1U9UXl6OwsLCsLc9/PDDuOGGG7B06VIAwOrVq/HOO+9gzZo1uPPOO1U/F4PRn6EeLMGTmilsACKDwVBKl90NACjINoadKUcXQO1pkLFNmoZlypQpqKqqwrnnnovPPvtMvN7lcmHbtm2YP3++tFM6HebPn4/Nmzcna/cYjIyBpm8txvC2+5Jvggten7rZVQwGY2DhcHsAABZT+OMJ1bX09Hng9vrCbpMsEh6wVFVVYfXq1Xjttdfw2muvoaamBvPmzcP27dsBAG1tbfB6vaLFPKWioiJE50JxOp3o6ekJ+GEwBgp9QsCSHSFgKc4xguMAHy9lYxgMBiMcdno8iTB3rDA7Czoh8dKZ4rJQwtuaR48ejdGjR4t/z549G4cOHcIjjzyCf/7znzE95ooVK3DPPfdotYsMRkYhHmCM4b++Br0OxTlGtNtcaLM6xRIRg8FgBOOIsgDS6TgUCceTdpsL5fnmZO5e4L6k4klnzJiBgwcPAgBKS0uh1+vR3NwcsE1zc3PEKcLLly9Hd3e3+NPQ0JDwfWYw0gWHW35FBDDhLYPBUAY9nuRECFiA9BHepiRg2bFjB6qqqgCQeTbTpk3D2rVrxdt9Ph/Wrl2LWbNmhb2/yWRCfn5+wA+DMVCgKyK5AwwT3jIYDCU4opSEAClgSbVVguqSkNVqFbMjAHDkyBHs2LEDxcXFGDJkCJYvX46TJ0/iueeeAwCsXLkSQ4cOxfjx49HX14ennnoK//vf//Dhhx+Kj7Fs2TIsWbIE06dPx4wZM7By5UrYbDaxa4jBYEjQFVG4OUKUEiFgae1lAQuDwYhMtBIzECjkTyWqA5atW7finHPOEf9etmwZAGDJkiV45pln0NjYiOPHj4u3u1wu/OIXv8DJkyeRk5ODSZMm4eOPPw54jCuuuAKtra2466670NTUhClTpuD9998PEeIyGAzpACOfYUkfd0oGg5G+SCXmyAWXdCkJqQ5Y5s2bF3YuDeWZZ54J+PuOO+7AHXfcEfVxb731Vtx6661qd2dA4XK5YDSG995gDBz6FNSciwQXXOqxwGAwGOGQSsyRwwFxYvNA1LAwlDFv3jzceuutuP3221FaWooFCxZg165dWLRoEXJzc1FRUYFrrrkGbW1tAIC3334bhYWF8HrJB3DHjh3gOC7AfO/666/H1VdfnZL/hxE/PM/D7iK+CXI158KcLABAF2trZjAYMigqMdMMi5UFLEmH53nY3faU/Mhlp8Lx7LPPwmg04rPPPsMf//hHfOtb38LUqVOxdetWvP/++2hubsbll18OAJgzZw56e3vx1VdfAQDWr1+P0tLSgKnP69evx7x587R6KRlJxunxgXrBRWpDBIBClmFhMBgKUFJiztiSUH/A4XFg5oszU/LcX/zgC+Rk5SjefuTIkfjzn/8MALjvvvswdepUPPDAA+Lta9asQU1NDQ4cOIBRo0ZhypQpWLduHaZPn45169bh5z//Oe655x5YrVZ0d3fj4MGDmDt3rub/FyM50HIQECXDki1kWBwsYGEwGJHpU2KTIE5sTq2If0BmWDKJadOmib9//fXX+OSTT5Cbmyv+jBkzBgBw6NAhAMDcuXOxbt068DyPDRs24Hvf+x7Gjh2LjRs3Yv369aiursbIkSNT8r8w4oeuhox6HQz6yF9fVhJiMBhKEEvMMhkW2nXIMiwpINuQjS9+8EXKnlsNFotF/N1qteLCCy/En/70p5DtqK/NvHnzsGbNGnz99dfIysrCmDFjMG/ePKxbtw6dnZ0su5LhSPVm+bVGYTYrCTEYjOg43GQ+kJKSUJfDDa+Ph14XOiQxGQzIgIXjOFVlmXThtNNOw2uvvYa6ujoYDOHfOqpjeeSRR8TgZN68efjjH/+Izs5O/OIXv0jmLjM0RomiHwAKLSTD4nB70ef2ygrqGAzGwMWhQMRfbDHi7Z+ehZJcI1IUqwBgJaGM4pZbbkFHRweuuuoqfPnllzh06BA++OADLF26VOwMKioqwqRJk/DCCy+I4tqzzz4b27dvx4EDB1iGJcMRPRNkVkMAkGcyiKugHqZjYTAYEbBHmSUEAHodhwmDClBVkA2OS13EwgKWDKK6uhqfffYZvF4vzjvvPEycOBG33347CgsLodNJb+XcuXPh9XrFgKW4uBjjxo1DZWVlwCBKRuYRbbIqheM4FAjC205WFmIwGBFQMpssXRiQJaFMwb8dmTJy5Ei8/vrrsvdbuXIlVq5cGXDdjh07tNsxRsqINlnVn8LsLHTYXEx4y2AwIqK0zJwOsAwLg5FBONyk3iwnkKOInUKsJMRgMCIglZnTPxxI/z1kMBgiDhdR9CsR0VLzuG5WEmIwGBFQMvwwXWABC4ORQVDPBEUZFlHDwkpCDAYjFK+Ph8tDFkGZoGFhAQuDkUEocaWkiPb8rCTEYDDC4PBzzlayCEo1AyZgUTvDh5Ea2Pskj5IWRIrkdssCFgaDEQoV3HIcYDKkfziQ/nsYJ1lZ5KBtt9tTvCcMJdD3ib5vjECUtjUDzJ6fwWDI4/A7nqTSX0Up6a+yiRO9Xo/CwkK0tLQAAHJycjLijRlo8DwPu92OlpYWFBYWQq9P//RkKqAlISXpW+rDwjIsDAYjHJnkwQIMgIAFACorKwFADFoY6UthYaH4fjFCUaPoL2IaFgaDIYOSwYfpxIAIWDiOQ1VVFcrLy+F2s4N3upKVlcUyK1FQsyKiJaFuVhJiMBhhYBmWNEav17MTIiOjkVwplbQ1kwwLs+ZnMBjhUHM8SQf6veiWwehP0BWREuO4gpzAic0MBoPhj5rjSTrAAhYGI4Owq1gR5ZvZxGYGgxEZNceTdIAFLAxGBiEaxyk4wPhPbGbCWwaDEYya40k6wAIWBiODEFX9ClO4oj2/jQlvGQxGIJKvU2bIWVnAwmD4sftUNx79uB6HW62p3pWwOFQ43QKSjoVlWBgMRjCSTUJmhAKZEVYxGAnmUKsVv//PbmyobwMA7DzZhaeWnJ7ivQrFocI4DpC8WNjEZgaDEYxkRJkZoUBmhFUMRoJ5+KMDYrACALtO9qRwb8Lj9vrg9pJZS6pLQsyLhcFgBEFLzKxLiMHIIBo6yAyjBy6ZCABo6ulLO92H/2RVVhJiMBjx4nD5ALAuIQYjozjV1QcAmDS4ADXF2QCAfU29qdylEKh+RccBRr2yry41j2PzhBgMRjAON8mwsICFwcgQnB4v2qxOAEB1YTbGVOYDAPY1pVdZSHKlNCge4FlkEez5HemVLWIwGKmHHlNYSYjByBCaukl2xWTQoSgnC2Mr8wAA+xrTK8Nij+HgUiC2NbMMC4PBCIQZxzEYGQYtB1UXZoPjOIypStMMi8oOIQAoZBObGQxGBPoybPghC1gYA57GbgcAoLrQDAAYI2RY9jf3wuvjU7ZfwYgeLCoOLkVsYjODwYiAXaWvU6phAQtjwHOqiwQsVQVEbFtbYoE5S4c+tw/Hhe6hdMARg422KLplGRYGgxGEg2VYGIzM4pSgYakuIBkWvY7D6AqqY0mfshD1TFBTEqJtzXaXF04Pm9jMYDAk/IX8mQALWBgDnkaaYSnMFq+jnUJ706i1OZZ6c57JAGFgM3O7ZTAYAbAMC4ORYTR2S6JbypiqdMywqC8J6XQcE94yGIwQeJ6PqcycSljAwhjwnBQyLLQkBPhnWNInYIl1NcQmNjMYjGCcHh94oacgUwKWzChcMRgJwur0oLePaEP8S0LDyywAgJOdDni8PhgUOssmEkeMngkD0Z7f4/Xh473NeOGL43C6fXj62unIM2elercYjLSBZmyBzCkJsYCFMaCh+pU8swG5JunrUJprgkHHwePj0Wp1ih1EqUR0pVQZsNAMy0DRsLg8Ppz/2AbUt1jF6zbUt+E7E6tSuFcMRnpBM7ZGgw56nTLn7FST+mVjGuP2+vDfr0/h1S8b0sqPg6EdtBw0qDAwINHpOFTkkxIR1bikGjs1jstSt84oEjUsA6MkdKTNhvoWK4x6HYYJmbJ00iIxGOmAI4auw1SjOmD59NNPceGFF6K6uhocx+HNN9+U3f7111/Hueeei7KyMuTn52PWrFn44IMPArb5/e9/D47jAn7GjBmjdtc0x+vj8dOXvsIdr30TMCmX0X+gwUiVn36FUilc15QmAUufKLpV97WlJaHOAZJhob46w8tzcc0ZtQDSq9uLwUgH7DEYUaYa1QGLzWbD5MmTsWrVKkXbf/rppzj33HPx7rvvYtu2bTjnnHNw4YUX4quvvgrYbvz48WhsbBR/Nm7cqHbXNMdk0IHOmKMeGIz+RbiWZkq6BSxSl5C6DMtAm9jsnzVL10GWDEaqcWSYyy0Qg4Zl0aJFWLRokeLtV65cGfD3Aw88gLfeegv//e9/MXXqVGlHDAZUVlaq3Z2EwnEccrL0sLm84pvL6F9Q07jgkhAAVAkloaaeNAlYYu0SyhlYE5ulgMUsjllo6HCgt8/NhLcMhkCsx5NUknQNi8/nQ29vL4qLiwOur6+vR3V1NYYNG4Yf/vCHOH78eMTHcDqd6OnpCfhJFHQ1a2cBS79EsuWPXBJKFw1LX4xdQjRgGSgZFvqeVhdmo8hiRKUQeB5oZmUhBoMS6/EklSQ9YHnwwQdhtVpx+eWXi9fNnDkTzzzzDN5//308/vjjOHLkCObMmYPe3vAHmBUrVqCgoED8qampSdj+WkzkzWQBS/9E0rDIlYQcSd2nSNjdpCypPsNCSkIDTcNCjQCpCeDeRhawMBgUek4zswxLeF588UXcc889ePXVV1FeXi5ev2jRIlx22WWYNGkSFixYgHfffRddXV149dVXwz7O8uXL0d3dLf40NDQkbJ/pyYFpWPonLUK5pyLfFHJbVZplWGKtOUttzQOjJHSqK9C5mOlYGIxQaCNJJmVYkubD8vLLL+P666/Hv/71L8yfP19228LCQowaNQoHDx4Me7vJZILJFHqCSQT0zWQZlv6H18fDJryv+dmh2oZKIevS0uOEz8dDl2Kvgj63D4D6DEvRALLm93h9ouaI6pLGimMWWIaFwaDEMpss1SQlw/LSSy9h6dKleOmll3D++edH3d5qteLQoUOoqkq90ROdYslEt/0Pm1/WzN80jlKeZwLHAS6vDx1pkJ2g05ZNWbG1NQ+Eic0tvU54fTyy9BzK88iiRsqw9ILnmZ8SgwEQa34AMBn6ccBitVqxY8cO7NixAwBw5MgR7NixQxTJLl++HIsXLxa3f/HFF7F48WI89NBDmDlzJpqamtDU1ITu7m5xm1/+8pdYv349jh49ik2bNuGSSy6BXq/HVVddFee/Fz/ZLMPSb7EKlvxZeg4mQ+hXIUuvQ2kuOemlQ2uz0x3bAWYgTWym+pXKArOYERtWZoFRr4PV6cGJzvTQIzEYqcbpjm0BlEpU7+nWrVsxdepUsSV52bJlmDp1Ku666y4AQGNjY0CHzxNPPAGPx4NbbrkFVVVV4s9tt90mbnPixAlcddVVGD16NC6//HKUlJTg888/R1lZWbz/X9xIJSGmYelvWJ3kPc01GcBx4cs96aRjkVZE6r62Oh2HguyBMU9IGmQpiaiz9DqMKM8FAOxljrcMBgDA6SXHE2MazElTimoNy7x582TTqs8880zA3+vWrYv6mC+//LLa3UgaNGBhJaH+Bx16KOfNUZlvxjfoTnmnEM/zcNEDjMqABSA6lk67u9+3NkcatTCmMg97GntwoLkX541PL78nBiMViBnb/pxhGWhkC3Nb7Cm25m/tdeJEpz2l+9Df8M+wRIJmWFJtHkezK4D6DAvgb8+fei1OIgluaaYMKckBAJzsSn2mjMFIB8QFkD5zNCxsWnMUxJKQM3UlIafHiwv/uhFNPX2YM7IUN8wZhrNHpb5clulQDUuuOfLXoCJNSkL04ALEJpIbKBObg1uaKVVp5qnDYKQalmHph+SkgXHc4VabuMLfUN+GxWu24IvD7Snbn/5Cbx85eecpybCkOGChBxeAiITVUjhAJjZLGZZA52Laop7qwJPBSBdcGahhyZw9TRE51DguhSWh+hYrAFKHn1ZbBADYeqwzZfvTXxBLQjIZlsp8cqJLecBCW5oNuogCYTkKB8jEZqphGVwUPsPCAhYGgzAguoQGGungw1IvzECZUlOI88ZVAAB2n+qWuwtDAVR0q1TDkkoPD5cndsEtMDAmNvf0ucX3NHjUAh2z0O1ws44/BgMsw9IvyU6Dtub6ZpJhGVmRhwmDCgAAu06y9sx4UZRhEU50dpcXPX2p1DHFZ/I0ECY2Nwr6lcKcLFiCgtA8kwEW4buc6mwZg5EOSBqWzBHdsoAlCunQ1nyghWRYRlXkYnw1ce083mFHdz/31Eg0VHQrp2ExZ+nFk31jCgWbsXqwUAbCxOaTXaSLrjrMIEuO4/yGWbKAhcHwLzNnCpmzpyki1U63To8Xx9rJgXhkeR4Kc4yix8SeUyzLEg80wyLnwwIAFXnkRNfa60z4PkXCFXfA0v8nNrf0kPeHBibBVDHhLYMhEo+vU6rInD1NEVTDkqqA5UibDV4fjzyzQZwoTLMsTMcSH70KfFgAoDSPnOzbrKkLWOhqKHYNS/+f2Ez1K/kRSnyVaeKpw2CkA9Koj8wJAzJnT1NEqq35Dwj6lVEVeWJ3CNWxsAxLfFiFtmY5DQsAcZ5QW2/qTvbx1pvFklA/LiP2Rnk/pU4h5sXCYNAMCwtY+hE5KS4JHRQ6hEYKs1AAKcOyi2VY4kIsCUXLsAgBS2sKMyziwSVGRT8tCfXnic29UUp8TMPCYEjEOkw1lbCAJQq0JOT0+OD1Jb+t9YBfhxCFZlgOtljZjKM46FXgdAv4Z1hSXxKK1TNhIExslmZDRcuwsICFwWAaln4IzbAAgCMF5nG0Q8g/w1KeZ0JprhE+HtjXxMpCsWJV4MMCAKW5JDuR0gyLJz7PhIEwsTla11e6mAAyGOmAaBzHApb+A3EWJb8nW8fi3yE0yi/DwnEcxleTLMtupmOJCZ+Ph9WlLMNSlidkWKwp1LB44p/7Idrz99cMi1MYtRChJETt+tttLvSleJgpg5FqWIalH8JxnGjPn+zyS7gOIco4QcfCMiyxYXd7QY1r80zybc1iSSiVXUIa1JsL+/nE5mgloYLsLJiFgI+2QDMYAxGfj4fbSw6ATMPSz8hOUWszza4MK8sNmR9TW5wDADjRyToeYoGWDww6TjyJRYJmWDpsrpTomABtbLT7+8TmaCU+juP8vFjY94YxcPGf/s4yLP2MVHUKddrISrjUYgy5bXARC1jiweqUWmCjDRMsFl5/r49PWXZCi0Fl/X1ic09fdCPAynwmvGUw/Ke/Mw1LPyNVXizUlbQobMBCVoonOx0pHcqXqSgZfEjJ0utQJJRTUlUWiteaH4Akuu2nGRbqwxKpJASwTiEGAwCcXrIA4jiSZc4UWMCigFTZ89PVPD1Z+lMlCAgdbi86bP1zxZxIrApdbimi8DZF5nHOOKc1A0BRP7bnd3l84mskF7BIXiwsM8kYuPi73EbLMKcTLGBRgEXQsCRbdEtLQjSV74/JoBeFuKwspJ5oAs1gUi28jXdaM9C/JzbTABSQD0JZhoXB0EYTlwoya29TROoyLEJJKEzAAkg6lpNdLGBRi1IPFkqqA5Z4hx8C/XtiM30/s7P0MMgchCvy2TwhBiPeUR+pggUsCkiVhqVLKAkVW8KLCOnU5hOd9qTtU39BHHwYZVIzJdX2/PEOPwT6t4alR4F+BQDKhYAlla7FDEaqEZ2zM0hwC7CARRE0YEl2SajDHrkkBEjCW1YSUo/qDIswsbk1RSc6LUpCRaJxXP8rCSkt8VEtUqvVycTqjAGLSwNNXCrIrL1NEdlZgg9Lkt0xu5SWhFjAohqrU9mKnCKVhFJzstfiANOfJzZbFWbM6JgFt5fvl5kmBkMJWiyAUgELWBSQigyLz8eLK+FwXUIAMIhlWGJG6aRmitQllNqSUFwaluz+O7GZtjTnRwlATQa9GLilcjYUg5FKWIalH0NFtzZn8jQsvX0eUFPV6CUhO0tvq0TppGZKWdp0CcX+lc0z99+JzWq6vuh7maryHoORarQ4nqQCZUfrAY4ouk1iSYjqV3JNhohRMBXd2lxedNndYQ3mGOFR68NCS0LtNhd8Ph66JJstabEiohObO+1udDncogC1P6Dm/SzLM6G+xYqWXuWdQg0ddrz9TSM4DrAY9Th/UrXogMxgZBoub2aKblnAooBU+LB0ioLbyDV5c5YepbkmtFmdONnlYAGLCqwqfVhKciV7/i6HO+knK61qzoU5RhKw9LMMi9QlFL3rSxTeqsiw/PbNXVh/oFX8+5sT3fjLZZNV7iWDkR74G8dlEpm1tykiOwVtzZJ+Rf7E6F8WYihHsuZX1tacpddJ2ocUlBJEDUscs4QA/9bm/tUppCYALVcZsLi9Pnx5tAMAMGdkKQBg/YFWVoZlZCyicRwLWPofqRDddtrIilEuwwKw1uZYkbpKlCcZU6ljEUtCcTpTFvVT8zg1s6HUZlj2NvbA7vIi32zAE9dMh9GgQ0uvE4fbbLHvMIORQqQMC+sS6nekwum2UzSNk8+wsE6h2KBdJUo1LEBq3W5pScgcZ4alv05slrqElJeEWhQGLFuPdgIAptUWIduox/TaIgDApkPtsewqg5FymDV/PyZH0LCkImCJXhIiXiwsYFEOz/NSW7OKDEtpDNoHrXBppGHpr263at7PslwiNlb6Pm49RspB0+uKAQCzh5cAADYfalO9nwxGOuB0a1NiTjaZtbcpIhXW/HSOkPKSENOwKMXh9oot46oCFkF4256C6dhaTGsG+q95nJo2dX+322jwPI8vhQzL6ULAMksMWNrh8zEdCyPzcLIMS/8lOyv5JSGlols6fbaZDXNTDBVo6jjpvVWC2Nqc5JKQx+uDVzgxxqvq76/2/JIPS/SSEBXddtndUQ30jnfY0drrhFGvw6TBBQCASYMLkWPUo9Puxr6m3jj3nMFIPtLww8wKATJrb1MEzbA4PdKJI9F0CKv4aK3KlYKXRqfdjb4kjw7IVHr9PDs4TrmfSonwXrQn2Z6f1psBDTMs/awk1Ktw+CFAymJZevK+Rxu1QLMrEwcXwCwEt1l6HWYMJdmWTawsxMhAJA0LE932O6iGBSDlhGQgzRGSXzEWZGeJq+6WHubcqQS1gw8pJSkS3dLVEBB/Crc/algCNEkK3lOdjpOmb0fRsWw9SvUrRQHXz/YrCzEYmQbLsPRjzFk60IV4snQsSkW3HMehQsiyNKtw7hzI0KCTdn8phWpYkj0AkepXDDoOhjgDlsJ+WBKyu/w1Scp8dZS2NlP/ldNriwOuP2MYCVi2He9Us6sMRlpAMyzMOK4fwnEccrKS58XC87xiHxZAKgs1dbOARQmxByzUnt+ZVNMwLQeVFfVD0S3Vrxh0nOK2byXmcX1uLw61Eq+VKUMKA24bUZ4LgGSqOlIgwmYw4oF2CTHjuH5KdhJbm+0urxgBK7GAr2DCW1X0Ce+hGsEtINnz97l9SRVgazGpmdIfJzaLnjpm5ZokyYsl8nemoYN03uWZDaJ+iZJjNKBa+N4dabOq3mcGI5VoNeoj2ag+An766ae48MILUV1dDY7j8Oabb0a9z7p163DaaafBZDJhxIgReOaZZ0K2WbVqFerq6mA2mzFz5kxs2bJF7a4llJwkmsfRcpDRoFN0Uq0QDr4sYFEGzbCYVQYsOUaD+H4kU3ir5cElz2wQy5vd/STL0huDp46Sic1H20nAUluSEzYQGlZGsiw0C8NgZApaZm2Tieq9tdlsmDx5MlatWqVo+yNHjuD888/HOeecgx07duD222/H9ddfjw8++EDc5pVXXsGyZctw9913Y/v27Zg8eTIWLFiAlpYWtbuXMJLpxeIvuFWyYqwUVnpNTHSrCLEkpDJgAaQsS5stea+1Vh4sgDSxGeg/wluxpVnhXChAmYblWDsJRGqLLWFvH1pKrj/CLPoZGYaWWdtkonpa86JFi7Bo0SLF269evRpDhw7FQw89BAAYO3YsNm7ciEceeQQLFiwAADz88MO44YYbsHTpUvE+77zzDtasWYM777xT7S4mBBqw2JyJz7CILc1RBLcUUXTLNCyKoDoktRoWgHQKneh0JDnDou3BpSjHiK5+NLHZqsI0jlKWJ7jdynR8He+QMizhGFZGApbDrawkxMgs2PDDCGzevBnz588PuG7BggXYvHkzAMDlcmHbtm0B2+h0OsyfP1/cJhin04menp6An0RTVZA8R1mlHUIU1iWkjr44MiylFtoplLwMi2jLr1ELIs2wdPaTTiFpjpCagEXQsMhkJf1LQuFgGRZGpiINP2QBSwBNTU2oqKgIuK6iogI9PT1wOBxoa2uD1+sNu01TU1PYx1yxYgUKCgrEn5qamoTtP2W4sJpKRr1aLAlZlKW4/buE2Mj76MSqYQGkklAy3W6dGk1qplAhd2c/6W5R43JLKfez54/0nTkulISGRCgJDRc0LEfb7UkzlGQwtIC1NSeR5cuXo7u7W/xpaGhI+HNKArvEp3/pyrdQYYalPJ8cfJ0eX78RUiYSh4t8WWMpCUkTmzNTdAtImbuO/pJhcao3AqQZFpfHF7Y05vH6xIGikTIs1YXZMBp0cHl8ONXFho8yMgcpw9LPu4TUUllZiebm5oDrmpubkZ+fj+zsbJSWlkKv14fdprKyMuxjmkwm5OfnB/wkGrqaSka9mh5AC7OVrRjNWXrRr6WZCW+jEp/olnqxJO9kr7Win2aJOpJsgJco1NjyU8xZetEI8GSYYKOxuw8eHw+jQSdmMIPR6zjUCcFMMhYyDIZWMA1LBGbNmoW1a9cGXPfRRx9h1qxZAACj0Yhp06YFbOPz+bB27Vpxm3SACuzarK6Eu4TGkuIWy0KstTkqcWlYUlIS0lZ0S0tC/cXwTM2kZn8GFZFgI5wu7ahYDsqBThe5U4/pWBiZCDWO6/clIavVih07dmDHjh0ASNvyjh07cPz4cQCkXLN48WJx+x//+Mc4fPgw7rjjDuzbtw9///vf8eqrr+LnP/+5uM2yZcvw5JNP4tlnn8XevXtx8803w2aziV1D6YDFZBAnIydax2Jzqj8As04h5dAuIXMsXUIWOrE5iSUhce6HNulbGrAkM0uUSKjVgNrZUIOLqJA+NMNyjApui8OXgyjDxMwrC1gYmUOmZlhUtzVv3boV55xzjvj3smXLAABLlizBM888g8bGRjF4AYChQ4finXfewc9//nM8+uijGDx4MJ566imxpRkArrjiCrS2tuKuu+5CU1MTpkyZgvfffz9EiJtqhpflorG7D4darZhWWxT9DjFiFWvyyk9QFfnMPE4pWviwtCfRh0WarKpRSaifZVjEAFTl+ykXsNCW5iER9CsUlmFhZBo+Hw+3l4jEM03DojpgmTdvnmwnSjgX23nz5uGrr76Sfdxbb70Vt956q9rdSSrDyyzYeLAt4fVqKWBhJaFEoEXA0mFzwevjoZcpF2iF1pNVi/pZwELdp3NUZswGF0YOWI62UdM4+YBlOPNiYWQYdAEEZF6GJbP2NsUMFwaeHWpJ7GqKBiwWFRmW8nw2T0gpoobFqP7jX5xjBMcBPj55PiYur7b15v6WYaHvp+qARdCwhBPdSqZx4VuaKcNKyTHhVHdfUgajMhjxQhdAwADQsAxk6MEp0aspqmFRYzVeKQYsrEsoGrGWEADAoNeJbcHJ0rHQA4xWqyGqYXG4vf3iJGuPuyQUKLrleT6qyy2lyGIUO/SOdbCyECP9cQoLII4jE84zCRawqGB4OVltHeuwi62miYBajavJsEjzhFiGJRrxlIQAKUORrE4hrX1Yck0GUQ+TTC1OonCIGRa1XUIkYOnt8wT4F7VanbC7vNBxUhZGDjHw6WBeLIz0x9/lVul083SBBSwqqMw3I8eoh9cnrcC0hud52Fzqu4SoeVyb1Qm3N3HBVH9AKgnFGLCIAxCTVBLyaOtKyXFcv2ptFmdDxTB9m74OJ/10LEfbyHe7qiBbUVZrkKCFCVdaYjDSDa0XQMmEBSwq4DhONJBLlPDW4faCunyradMstZhg0HHgefkJtIzYT3AU0TwuaRkW7T0T+pPw1hGjhgUIXxba10Rmk42uzFP0GIMKI2thGIx0Q2sjymSSeXucYqSZQokJWGg5SMepO6HqdJw00I0FLBHheT7uklCpJckaFo0zLED/Ed76v5+xaJIGhekU2n2SBCzjqpQ5aNPS0skw3UYMRrqRiAVQssi8PU4xNMNysDlBAYvYIWRQXV8sFyfQMh1LJJwen5jBir0kRO35kxMYJmJF1F9KQk6PD9RlIZ4Mi392ZE8jCVjGVysMWGjQwzIsjAyAZVgGEKOENPH+5t6EPL41hkFuFLG1mWVYIkL1K0BsK3JA0rC09iY7w6Jdzbm/uN3aXfG9n4OD7PndXp/43R6nMGAZzDIsjAyCaVgGEKMrSMBS32JNyEj5eAIW6nbbyjIsEaHlgyw9h6wYnWNFe/4kZVgSkcKlJaFODQKWPrcXD3+4HztPdMf9WGpx+M1EicXEL1gwe6jVCpfHh1yTATUKOoT8H6PN6gwIiBmMdIRlWAYQNcU5MGeRkfLH2rX3XZBammPIsOQxL5ZoxOPBQinLS66GJREHmCINMyzPbDqKx/53ENes+SLpwlOH0FEXa3lvcHGghmXPKUm/Ijf00J/CnCyxHHWKlYUYaU4iNHHJIvP2OMXodRxGlpMsy4EElIVoS3OeysmzgJRhaellGZZIxCu4BfwHICoIDL1u4F/XAmsWAjv/DXg9qp8vESlcrUS3PM/j39tOAAC67G7c8sL2hHoUBeNwkefKifH9pNmRLrsbVqdHClgUloMA0j3IWpsZmYLWztnJJPP2OA0YJZSF9jdpL7wVMywqTbAAlmFRQrweLICkYbG5FDjFfvoXYPcbwPHNwGvXAX+fCVhbVD2f6MOi0SwhQDvR7TcnunGwxQqTQYd8swE7Grrwp/f3abGLiqCTmmOZvA0AeeYsFGQTp9qTnQ7sjiFgAVinECNz8DeOyzQyb4/TgNGVpFMoERkWq5OcAGMqCeWztuZo0BV5PBmWXJNBLM/I6lgavgQ+fZD8PulKILsYaD8IfPW8quejGRatpjUDflOn4/SSodmVhRMq8dDlUwCQEhHVYiWaeDxYKEOEAYcf7WkSO4SUtjRTWIaFkSmI099ZwDIwEDMsCQlYiEV4LCUhmmFptznhYW63YYnHs4PCcVx0LxaXDXj9BoD3AhMvA773f8C85eS2w5+oej5RdKtphoUEtz19npidkZ0eL/7z9SkAwPenDca54yowqDAbXh+Prxu6tNpVWeI1AQSAa86oBQA89NEBdDvcMOg4jKzIVfUYg4pC/VwYjHREyrCwLqEBwZhKsvo60mYTTyZaYRMzLOo/TCUWI/SC221bkgShmYYWGhZA8mJpi5Sh+GI10HkEyB8MfEfIsgw/h1we/xxwKR/tkIgMS0F2FqjNT6xTp9fubUG3w42qAjNmDy8FAEyrLQIAbD3aqcl+RkN8P2MooVIumz4Y351cLfq5jKzIU30wFzMsLGBhpDlihkXD40myyLw9TgMq8k3INxvg9fE43Kptp1BvH21rVj6pmaLTcSgTTqTNrLU5LH2u+DUsgH9JJczJvq8H+Owx8vv8u4HsQuFOI0gA43UBxzcpfi5RdBtnkOWPXseJU6dj1bF8vKcZAHDRlEFiS/H0OiFgOdahwV5Gxy5mWGI/lHEchwe+NxF1wmRmpYZx/oQzoGMw0hGnW/uMbbLIvD1OAziOE+eM7G/StixkE31YYjs5VTAdiyxaZVhKaYYlnIbl88eBvi6gdBQw4VLpeo4Dhs8jvx9SVhbieV7z4YcUUXgbYzbucBsJ1qfUFIjX0QzLV8e7EuJTFExfjJOag8k1GfDUktPx/WmDcdPZw1Tfn84TaurpY+VYRlrjZBmWgUeidCyxTGr2p0zsFGIZlnBooWEBZDIsjk5g8yry+7w7AV3Q8wz/FrlUGLC4/E5+Wovk4nW7PSr4ENWWWMTrRlfkwWLUw+r0JESUHoxdA18dyojyXDx42WSMrFA29NCf8jwTsvQcvD4eTey7x0hjRA0Ly7AMHGiG5YDGGZbeONqaAZZhiYYo0jTG99EvjeTF8sX/Ac5uoGwsMO6S0DsOnQeAA1p2A71NUZ/H6edponWGRXS7jUHD0mV3octOBOK1JZIjrEGvw9QhtCyUeB2LFl1CWqDTcahmOhZGBkAXQUx0O4BIWIbFGV+GhXYKsQGI4enTTHQbJjvh7gO2PEl+P/uXgC7M18tSAlRNIr8fXhf1efxN2LRO4RbHMXX6WDsRDZfnmULKMbQstO1o4nUsWnQJaQVrbWZkAjTDwtqaBxA0YDnR6dDUcyKeWUIAy7BEQ/suIb+T/c5/AfY2Iqwdd3HkOw8TuoWOfRb1eZx+tvxqp3dHIx7zOFoOqvMrB1HEgOV4EjIsGomotYBmWJg9PyOdScRssmSReXucJhRbjCjLIyeteg2zLDRgicU4DpDM45iGJTziLKF4u4QsQcZrPE/EtgAw80ZAL/P+VUwgl20Hoz6PqOhPgECuNFprtgw0w+JfDqJMHVIIHQc0dDgSnumzaxSAakF1Aclunupm3z1G+sKGHw5Q6ORmrcSFPM+LJaG8WAMWWhJiGZawaN0l1G5zwefjgSPriS4lywKctlj+ziVCF0rHoajPk4iWZgoNuGMJWMQMS2lohiXPnCVmIL+JdYJzzymgPfrrQwPQVGtYAKBKyLA0sgwLI41JhK9Tssi8PU4jpNZmbWYKOdxe0E7QeDMsbVbmdhsOrTQstJzi9fHodriBz1eTG6b8AMguinLn4eTS2gw45YPdRE5WpUFXawzB7dG2yCUhgHTcAMDB1hi+G71NwOOzgdVzor4+Dnd805q1pErIsDSyDAsjjaEZFi0665INC1jiQOsMCx18yHGxrxhLLCbmdiuDQ4PhhwBJp9KheV3NR4H6D8gNM2+KfufsQiCnhPzecVh200SaPJUKwuFYPidyJSHAL2BpiSFgee8O0h7utgH2dtlN7Wkkuq0qEDIsLGBhpDFMwzJAGVWpbaeQKLg1GmIWWOr93G5betmBMxiHhr4dtFNIv/MVgPcBQ2YDpSOV3ZlmWaKUPaQMS+JKQlanJ/rUaT96+txid5TmAcu+d4A9b0l/e92ym0slofiM47SgqpBkWLodbnGKdL/AZQM2/VVRVxsj/UlkmTnRsIAlDkYKB+XWXmfM9ub+WONsaaZIwlumYwnG4Y5/WjOFeLHwKDnwL3LF1KuV37lECFii6FgSWRLKNRnEx1WjYzkuZFdKc43IM4cfIUEDlkOtVvC8QsdbZy/wzi8Dr/PI75eUMUv9oSzfnCV2953qStBioWEL8PUrgC9J5d6WvcCT3wI+/C3w3EXA2z8nAQwjY2EalgGKxWRATTFJA2th0R9vhxBFEt6yDEswfRqVhACSYZnB7YPFdgww5gLjL1Z+ZzHDEqUk5KEZIe2/qhzHiVkWNSJtuZZmytBSC3QcMUJUrJHZ9izQewooqgMs5eQ6r/xCQPJhSX2GBfDXsWgsvD36GfD0ecDT5wJv3AjsfFXbxw/HkU+BJ84BWvcB5kJy3dY1JHBJVsDE0JxETH9PFpm3x2mGljoWOqk5Vg8WCsuwREZLo7GSXCOuMKwjf0z4HmCMfAIPvbOyTqFEj4KPpbWZCm5rZQIWk0GPIcWkXKSoLOR1S23hZy0DTLnS9TKkkw8L4NcppKWOpbcJeP57QMMX0nX739Xu8cPB88CHvwM8DmDYPODWrcA1bwLggBNfAraWxD4/I2FIx5TMO/1n3h6nGVo63lqd5OAcb8BSIWRYWlmGJQStZgkBQKXJg+/ohJPI1CitzMGo1rAk5qtKMyxqOoWOCiWhugj6FYqqTqHdbwI9JwBLGTDpCkBP9EFRMyxpYs1PqcoXMixaloQ+/zvg6QOqpwJXvkSuO/RJ1GAuLo5uABp3AAYzcOnTQG4ZMPwcIEt4z90Z0Lp9chtQ/3Gq9yLtSKQuLtGwgCVOtJwpZBUyLJYYJzVTWIYlMlp1CQHAZPtmZHMuNGUNBgZPV3dnqmGxtwF9kb1KpPRt+mRYjtGhh2E8WPwZrlR4y/PApsfI7zNuArLMgF7QxsgELC6PDx7BByBdWjSp8FazkpCjC/hyDfl97p3AqIWkw8zZQ/QsieIz4f2Y8kPAUipdn0X+P3jSfDG0713gqXOBFy4F9vwn1XuTVrAuoQHMaL9OIcXiwgjQtuZcU3gho1Ike/40P6gkGa+PFz0ItCgJjWr7EACwwTiH9KKrwZQn6TRksizpmGE53iG0NBdHybCUKQxYjnwKNH0DGLKB068j14kZlshZBBp8AumTYakWWps1c7v98inA1QuUjwNGLSDzqYZ/m9x28CNtniOY5j3CY3PArFsCbzOQ/w9ue2KeWwuObAD+dS3AC5+P/96maNDoQIDneb8uocw7/WfeHqcZw0pzYdBx6O3zxD1WXhx8GG+GRSgJsQxLIH1+J7i4AxZHF8qaNwIA3vXNju0xxE6hyMLbRNeby3KNyIIHpzesAQ79L+r2Xh8v+rZUCgLTSChubd76NLmc8gMgp5j8rqAkRPUrBh2HrDTpeBAzLFq43bodfrqen0tB8cjzyGV9ggKWTX8ll2MvlD6jlCwasKTpYqjzKPDSVYDXCYz+DlA1GXB0AG/+hGTy0h2eJ1m1BOHx8eLLwEpCAxCjQYehQmo83k4hrdua26nbbdMu4K1bgXd/BZzaEddjZzL+K/K4A4B970Dnc2O/bzC2Oipie4zi6AFLn5i+TVxJ6DbDa7i4Yw3w7h1Rt++wueD18eA4aZ5SJGhJqKXXiZ6+CJkSWztJ3wPA9KXS9QpKQlqW97SCmsc1aZFh2fIkKRkWDgHGf0+6fvi3AHBA8y4ywkBLek6RIZ4AcOZtobeLJaE01bB8+DuSkaqZCXz/H8D3niQ6nENrgb1pXBrieeDAh8CT5wB/qgXe+DH5bmiM02/6OysJDVCogVy8nUJatTWXWEzQcUAOb4f7X9cDq88CvvonsOUJ4Im5wN9nA5+sAJp3x/U8mYZkGqeDThfn5OPdrwMA3vaegd4+T0D2RjG0U0iuJORObPq2zrELN+uFA7mtNer2tHRUYjHCECWrkW/OEsuTEbMsO/8F+NxkJVw5UbpeQUmImrOlg8sthbY19zo96I0UpCnB0QVseIj8PvfXgcM0LSXAoGnk94Mai0o/f5y8H7VnhtdlpbPo9sgGEpRwOuCClSS4KhsNnH49uf3AByndPVnevBl48TLg1Ffk769fAv42HTi4VtOncWq5aEsBmbfHaQhtbd4Xb4alL77BhxS9jvhr/MbwArL3vQaAB8ZdDEz4PqA3kSF96/9I5rVsXhXXc2USWs0Rgr1DdP38AKQc1B6LcaCYYZHTsCRQIOe0YsRnv4SeE3LEzt6oafNWQZxLxbrRkC0L8TwJpAFg6jWBtykoCfWlWYcQQBYb+UKGNK7W5k1/Bfq6gNLRwKQrQ28fMZ9cHtkQ+3ME09cNbP0H+X32z8JvYxAyLOlWEvJ5gffvJL9P/xFQMU66bfi3yOXhdelZFmrdTwIUTgfM/ilw9WtEs+ToAF6/gRxvNMLpN6k5Vjf1VMICFg0YpZEXi82lTYYFAKZnN+MK/Tryxw9fAy5/Fvj+08Av9gEXPw6MXEBu++D/BVqh92OkFtg4X9997wA+D1AxEba8oQBiGyCIghpyKSMITFgLoscJ/HspsrqPopkvJNfx3qgupi2CTqs8X16/QqHC20PhWpsbvyZlDb0JmHBp4G0KSkJ2DccsaEm14MVyKlYdS28zaWUGgG//LjC7Qhl0GrnUMku67RlSTikdLelkgslKU9HtlifIZ8lcAMz7TeBttbPJZ6znJNB+MDX7J8f258jlqIXAefeRYPTG9SRosbcDH9+t2VOJx5M00XypJTP3Os2gnUL1zVZ4fbFH8L1il1D8AcuNrmeh53g0VHwbGDlfuiGnmIgbf/AKcPoNAHjg9RuBE9vifs50x78kFBf73yOXYy8UBwjGFLCIJ+XIpYOEdAl5XMCrS4D6DwFDNpb5fg43L5z0ZVqsASnDUqYww1In6LuOtYU5wX31PLkce4EktqUo6RJypV+GBdBgavPae0hAMGgaMOaC8NtUjCeXbfvJ+xkvHpc0cXz2T0k3UjhowJJObc1NO4GPhJP6t35HSmb+ZGUDQ2aS39NtHpLHCex4kfx+2hLpeoMROP9h8vv254Djn2vydJnscguwgEUThhTnwJylg9PjE1s+Y0HqEoozYDnyKSY7voCb1+PjQTeH34bjgIV/JCspTx/w0V3xPWcGoIlI0+2QumlGL4qpLViEnpR9MgGLhkZ3AEgA8O+lwIH3SHr/By+jIW8yeiGciJw9snen/yf9v6NBAxZq5y/isgPfCPbyU34YekclXUJpKLoF4nS7PbgW2PECAA5YsCJyu3z+IMBUQDJ9bQdi31nKrn+TsQi5lcCkyyNvl25tzS4b8K+lpCto1CJJrxLMsHnkMt0Clr3/JaWf/EFSmY9SO0sqlb51qyYi3EQ7ZyeamAKWVatWoa6uDmazGTNnzsSWLZENjObNmweO40J+zj//fHGba6+9NuT2hQsXxrJrKUGv4zCyXPBjiUPHImZY4uwSwqcPAgBe9H4LBzyVkbfTG4DzBWHf8U2ArS2+501zNLHlP7yedEjkDwYqJ8YZsNAMS+TJvppmWLxu4N8/Ava9TVLkV74IDJuH0lwjenjBBK5P44ClRApYAnyKdr8OOLvJ3KBh54TeUUH2Kd3mCFEkt1uVJSGnFXj7dvL7jBulrEA4OE7KssRbFuJ5qZV55k2AQea9TXZbs62NlK1XTiRZFP+WX3sHyRS21wN5VcBFqyIHeDRgObJB9vuWdLY/Sy6nXh2+9HfuveR/a68Hnr0w7qAl0b5OiUb1Xr/yyitYtmwZ7r77bmzfvh2TJ0/GggUL0NISfrbE66+/jsbGRvFn165d0Ov1uOyyywK2W7hwYcB2L730Umz/UYrQQsdCu4QiTcBVRM8pYsQF4EnvBaLmICKFQ0iHBu+TSh39FE1s+ekMl9GLAI4TSyOt1hgO4DrhACWTRdAshcvzxIti739I9uLKF4ARxICsLM8kZViilITokMRyhQHL4KJs6HUc+ty+QF8gKu48bUn48oOCDIs9zeYIUUQNi1q324/vBrqOE23TtxVkPGnA0hJnwHLwY6BlDxngOf1H8tuKJaEkdAl99TywchKw+W/kdflsJfDYFJJtWPcn4PEzicGd3kjal4NLQf5UTSEDHJ3dZORAOtDVIByruciT3nOKgSX/BXIryPv8xFzgn5cAr90QU6BKjyfGgRKwPPzww7jhhhuwdOlSjBs3DqtXr0ZOTg7WrFkTdvvi4mJUVlaKPx999BFycnJCAhaTyRSwXVFRUWz/UYoYXUnEhbHOFPL6eL+AJY4V485/A+DRVToNJ/gyZVN4aZ1839uxP28G4Ii3S8jnAw68T34fvQiAlGlo641BR6CkJKSV6Hb3G2TCry4LuPyfwMhzxZtKc03o5YV21SgloTaVGZYsvQ6Di8hJTiwLNX4DnNxKArZIB2oVJaGctBXdqghitz9HXG0B4MKV0vBHOWgnTLwZls8eJZfTrgWyC+W3FTMsCQ5YOg4Db/8ccNtIsLHoz0DZGMDRSTrL1j1ASlglI4HrPwaGzpF/PJ0eGHo2+f3wJ4ndd6UcJcaTGDydLBwjUToSuPYdErR0N5CS9M5XgacXqG5rl2wS0us7oxRVAYvL5cK2bdswf75Ua9PpdJg/fz42b96s6DGefvppXHnllbBYAueQrFu3DuXl5Rg9ejRuvvlmtLdHTn05nU709PQE/KQaMcMSY0mIdggBcWpYhLHzttHEaKpZifsuDVgOfUJaW/spcU/2PfUVYG0GjHlA3VkApPbeVhWzeERo2cPnidhuqYnTbV838P5y8vvZvwJGB5ZbS3NN6IFF2lYGtSUhwK8sJEx5xjYhuzLmAiC3PPyd1JSE0izDMkgIWE52OZSN6zj6GfD2MvL7vOWhWoZIVEwgl/EELKe+IoMOdQbgjAh6N3/EtuYEBywf/JYEq8POAW5cR0pVP/4MuOJ58hpNvJx8lm9aTzLEShg2l1weXp+w3VbFceGcOWRW9G1LRwI/+Ry47Fng4tVA3RzS0fXC5cA3/1L8lC7vACoJtbW1wev1oqIi0NmzoqICTU3RZzVs2bIFu3btwvXXBwqjFi5ciOeeew5r167Fn/70J6xfvx6LFi2C1xvejGvFihUoKCgQf2pqatT8GwmBdgodabOJaTc1UP2KUa+LvWTRso8o5nUGGCeRgKXN6ozeuVQ+FigeRoRrWhtRpRHUt8Mca7aCloNGfFus88elYdH5BaYRTsya+LD8737A2gSUjADOuj3k5rI8E3r56CUhh8uLXiELqLQkBEB0gj7SbiM6DXqA9Xe2DSaDRbeVBWZwHBnOGNWf58RW4JUfkizbuIuBs6O7DYuUjyWXvY2xaxu+eIJcjr8EKBgcfftkZFgOrgX2v0O+H4v+JOlS9AYyLmDencClTwLf+i1glB/AGUCdkGE58SXpzkk1tPNHScACkPLQ+IuBKVcBV79O/Hl4L9E99TQqeohMHnwIJLlL6Omnn8bEiRMxY8aMgOuvvPJKfPe738XEiRNx8cUX4+2338aXX36JdevWhX2c5cuXo7u7W/xpaGhIwt7LU5lvRp7ZAI+PxxG6klQBdcWMS3ArZFcw8jwUl1VBxwE+nlj0y8JxwBhBBL3vndifP82JW/NwSHCdHLVAvMo/YFE9/JKelIGIZSFpUFkcQeyXT5Lfz38orKCyNNeEXkQvCdGgzJylU5UFrC0hj32szU66UVy9JECmJ5BwqPBhSSenW4DoA2hAd7JT5sRe/zERUjo6gUHTiT9SpHbicJjyiGgZiE3HYmsHdr1Gfp/5Y2X3SXRbs9cjZQNn3EicarWidCQZOOrpA06m2MbB1k5a0gEyRkAtBiP5vAyeAbiswIe/VXS3AdUlVFpaCr1ej+bm5oDrm5ubUVkp040CwGaz4eWXX8Z1110X9XmGDRuG0tJSHDwY3uTHZDIhPz8/4CfVcBwnOt7G0ikkutzGGrDwvDQDZOJl0Os4sVyhTMdyIbk88IFsGj6TccTjjGrvkOYw0Y4DSCUhh9sLm0tlZo2elAGZDEucKdydrxJB9ahFAfvtT1meCT00YJHJsFBhcVmeSZVLZkBrMxXbTrtW/uSswIclHZ1uKYMimcfxPHByO/Dv64AXLyftwcO/DSx+CzDKT78OSzntFNqj/r5fPUeyqlVTJKv/aCS6rXnH8+REnlNCRhJoCceJpVxRP5IqGr4gl6Wj5cXCcuh0wPkPEofcXf8Wmy3kyORJzYDKgMVoNGLatGlYu1aab+Dz+bB27VrMmiWf1vrXv/4Fp9OJq6+OILLz48SJE2hvb0dVVZWa3Us5dKZQLAFLb7wBS8teoqQ3mIljIoCKfDq1WcFqaPDp5CDh7CEp00zD1kZKHzKp0biMxo6sB8AT4V9+tXi1xWSARXg81WUhBSUhelKOOWDZ+19yOfH7ETepyJdEt7xMW3NLD+0QUuZyS6EaFkv7TtKhoTeG917xR1GXEPnOpJvTLU5sxUM9v8B7xjsxYd2PgFcXA69cA/zjfODPQ8mAu13/Jun8KT8ErnpZmcg2HGJr8y519/N5gS+FKdkzbozcDhxMItua3Q7S/QMQfUo0AXAsiAGLhiMNYkHUr5wR3+NUTZY6u979FWkMkEEsCal1uvW6gUenAC9eGdX6IJGoPjsuW7YMS5YswfTp0zFjxgysXLkSNpsNS5eSevTixYsxaNAgrFixIuB+Tz/9NC6++GKUlARGk1arFffccw8uvfRSVFZW4tChQ7jjjjswYsQILFiwAJnE6Dham+k025gFtweFUfN1c8SVGk1LK8qw6HRk5sbOfxEdS+3s2PYjVby/XMgmeCO2hMZl5X5I6CwI4xlSmmeCrd2ONqtT1GsoguNI147PnZiSUMs+YiqmN0a2WgcJQGiGxW3rQqQZzGpdbim0tflSXviMjr0QsJTK30nRtGby2qRVhuXUDuCf38NQZzdZDrYfB4LlJbosYML3gFm3KBeMRiLWgOXA+6TjJLuY7ItSEtnWvOVJ0vlTUBO9vTpWaMDSsIXoWOQ8ZxKJWv2KHN/6LdGFte4Djm2UuqHCEPMw1dZ9QOcRkmk25cWzt3Gh+ux4xRVXoLW1FXfddReampowZcoUvP/++6IQ9/jx49AFpXr379+PjRs34sMPPwx5PL1ej2+++QbPPvssurq6UF1djfPOOw9/+MMfYDKl6MMUI1R4G0trc9weLPXCycCvXbVcTYYFIN0JNGBR4gORLtg7pHlI/sZSQcQ8S4jnpVbI4aEBS1muCcfa7bGbx/ncYTMsPM/DFU9JaK8whXnYOYA5ctnUaNABpnzAB3jsnZEDlhg6hADS2jyqkMdFtk3kCiUnI0XW/Gk2rbl1P/HIcHajueg03NF8Lr41yIslpwvlcmMuaUUuHU0mCWsBnXDdspe8VnqFx4/twtDJ066RghAlJEp029cNbBSs6OctT1wgUToKsJSRyeQnt6VmYeZ2SFOZ482wAEB2ETDhEjIL6uuX5QOWWG0SmnaSy8qJyrNxCSCm5fytt96KW2+9Next4YSyo0ePjihIzM7OxgcfpPHYbxXQ1uaGDgdsTo+qIYa98UxqdvZKEbtfSyTNsAQYdslBp5o2fk0GsOVVyG+fLuz8F6nFA9JlGGIuCXUcJuU2XRZQe2bIzfF1CkVu36UHFyDGgGWPELCM+27UTbMshUAv4JNJ97aqNI3z53LzFljsTvRY6pAf5jUMIRO7hD66i9isD5qGPTOexPqX9qHdl48lM6J4hMRD0VBi0e/sJkFL1aTo97F3SN2Ak3+g7vkMCQpYvn6ZiI9LRwOTw0yn1gqqY9n9BtGxpCJgObmdLFJyKyXRdLxMvooELHveAr7zl4jdUzF3CTV+Qy5pgJwiMlN5k6YUW4ziyau+JWg6Lc/L1hfjEt0eXk++AEVDgZLh4tWVwhC2qG63lNxyIsADpHk5kfB6SFCTange2Pas9LdMu2LMmgeaXamZEVZroIk9f5iSkH/AonqfOw4DzTsBTg+M/k7Uzc25ZPggJ9Ml1BJjhgUA5veR7OrWkguVrdBUdAmpyph1HAH+PAz4+B7l91FCXzdpxwWAix9HZXkZAJXmcbGg0wHVQlmJrtqjsfc/5PNWMREoH6Pu+WhmSOuAZfeb5HLaEmLylkhSLbylgtshZ2iXraiZSYIfl1W20zNmET/NsCgJiBMIC1g0ZnQ4AzmvB3jh+2QeRgRjNtrWHFNJ6GBoOQiQAhZVQ9hohkbOj6XrOPB/c4CHx5BVXSo5uS2wpVMmYIlZ8yCjXwEkTYfWE5vpakjHAQadygPbXsG1eOic0EnIYcgpINtkuSKXM2MtCaFlL2rse+Dm9XiPm6vsPgoyLH2xtDXveROwt5NLLdn/HgkCysYCZaNFt9sOm0vM7CWM6tPI5antyrbf+W9yOfFS9c+VJXQyadnW3NskiVDHXaTd40aiTsh4Hf+cDE9MNjSwVNqZpQSOI74sAPB15LE2MTnd8rxfSYgFLP0KWhYK0LFsfJgEAD0nIk5WjXnwIc8TPwcAGBEYsNAx901KMyyAFLAc+h/pJAjm1FfAU/PJ7BHeR8RYqWTbM+SSHkjlSghChkVVwOLzSSsxmbZggJj0qUauJOTnmaCmjRgAcEzQi8iIbf0pKCBieKPPHv59h39JSKX+4qvnAQD/803Fzm6FwY6SLqFYSkK0dNp1XNsheFRDJZxw880GUUB/Uu0QRLVUTyWXSjIsPaekz/OEGAIW0elWw7bmPf8BwJNORSXmdfFSOgoorCXlY7oYSSb0faLvm1ZMvoJcHl4XsVsyJqfbzqOk5Kg3auuLEwMsYNEYOlNI7BQ69RWw/k/SBhEi+t5Y5wi17ieBkN4kpToFKgXRbYfNJbbHRmXw6aQm7ugQxtz7cXI78MwFxJ6e4krhmHlHl2R8Nelycimz8oupS6jtANDXRWr31VPCbqKNPX/kkpBqRT/PS63pg2fIbytQWOzXvRemLOTz8WJApirD4nUTfQKAV71zQ6c2R0KBNb/dqVKT5PNJAYvPQ743WtDXI5WDhICF47jIXixaM0jIsDTvid5uvPsNADwpIcjNr4kEFd36PNoFfDTbNe5ibR4vGhwnlUmTPfDV2kq6s4D4O8SCKR5Gyny8L2K2LSYNC82ulI9VLupOECxg0ZhR/uZxbgfw+k3ky02JFLDEWhKifgK1s0KMpwqys2AWTnaKO4X0BmC2IKh+e5lkRtS6H3j+UlIjrT1LKo8kykBKCTteJM9fNlbaH4+CYXmqVuRCqnrw9IhfVk00LDIlIdX15s6jgL2NrIgU1pzLCvPg4IWsRhjzuE67Cx4fD44DSnIj9RGF4cAHgL0NfG4FNmBq6NTmSETJsLi9PnG1qPj9bN1Hgk9KxxFl94tG/YdktV4yUrLLB1BdSBYMCc+wFNQQDyWfO/pcIbEcdJn8dpHw7yjSorW5t0nKBiajHEQRhpfiwPsRM4oJgU6KLhkp27kXM9S7JkJpPCan26b0ENwCLGDRnJFCwNLS60TfB/cQ10ZLufRmRwhYxLZmtV1CNGAJyq4AZJVXVUAOME1qdCxzfgmM/x45AL58NfDcRcA/FpGsS/VpwA9eBvKEVs1U1IABslqm021n3CClqmUyLDENy6MCORn7bP+SkC/a3KZgdJHFpTG3IFLb8cpJittDKwvMkj1/mE4hGmQU5xiRpcZ0SnBf5iZfiaoikn0UpzbLESVgsfvpQhSLbmnwSenUKGDZ/Qa5HHdRgIhyUFGSMiwcp0zH0n6I3M7pY89mGPzKgVoIb/f+FwBPRhMUJnEmXO1skkm2tyXXpl/Ur5yWmMenZpTRnLPVZG1F/YrGGaEYYAGLxuSaDKgpzsYZuj0wbV1Nrrzob2QVBJAMRRhicrrleTLpFZCEZEHQspAqHYtOJ82pcHaTmqi9nbQc/vDfxDiIakZSlWE5/AnQcYj4h0y6gszWACKe4FweHzxCMJGTpeI1Fg2eIvsl0IyD28uj26FyrIH/xOYgYp7ULJaDpiu+S2W+GT2C263T1hVye2M3OTlVFarQr7j7JPH2uItDpzbLEcWHhQafBh1HfGSUQAMWTggAtciweN1SR93YCwNuqvab2pxwlOhYaPl02Fwgtyy25+E4bVubD68jl2MviP+x1KDPkpoU6FDTZJAo/QolSqBPs7ZGNYsO2tKc4g4hgAUsCWFymQ4PZq0GBx44bQkZlkf74iOWhGIQ3bbuJysEQ7a0wgqiKpZOIYC0Ly5+E/jeU8AlTwA/eJWMeadzL2j5KVUZFppdmXwVaTUWMyzhU6EOPw2P4gyLtUVYhXNE2xMBk0GPwhwSeKjWsci074olIbUaFjFgibzPwRRkZ8HKkfe0p7Mt5PZTwueHZuwUcXgdCdDzBwHVU1EnDEE82q4gyI2aYRFM42IR3FIhcudR5feNROM3JGg3F4Z0UFANi+wARK2IFrDwvFQOmhB5TIMitGxtpvO5FGqtNIWWhSLpWBq/AVrDN0nETMIDFnk7ANUZFlsbcR8GJ7kqpxAWsCSAG+1PYjDXhg5jFbDgfnJllIBF8mFRoWGh5aCaGVKGIQja2qyqJEQxWoBJlxH1+agFgRoZo+BHkooMy+H10kHm9OvJpV4ofUQKWIQVuV7HIUuvsOOGnuDKx0ada1Iaa2uzAuM4VSUhd5+0IlKRYeE4Di4DeU97uoO95IFGIUtQXaAiw7JPmGM05nyA46QhiKoyLPIlIYvSclBXAxE7cnpprpIWJaHjgv5iyBkhwxxF0W13EgOW1n2AM0wWt3kXKU/rTfFnM8TW5jj/L2urIHzmUrN6H/FtUkJp3Rca6NV/BDwxF3hWw8xPTyPQ20iGFSZKDxIlM6law0L1K8XDUmrJT2EBi9bseweTWt+Gj+fwSO4y6U2mJ/gwAUuf2ysKCFWVhGh7YoRyEODvxaLxQTMrCRmWvm6S5fCntxl47XoAPDD1GqBsFLleLAmFDxjoijwnS0WLsL/BUxQq8qmrsMrAUKYkFNPgw6adRHtkKSOtmyrwZBERoL2nM+Q2mqGrKlSYYfF5paByDDnoiyUhRRoW+S4hu1rXYvpeVk0CKiaQ3zuOksxDPByjQ+xCZ8JQDUtjVx88XvmhdHGTX0W6fnif5MvkD53kPuo8wFwQ33OJrc1xerFQAWrpyNScDLOLJKHvf2+Xup5aDwD//hF5La3N2nVD0aCobExEJ9q4UVgSUnxMoVPAKyfEu2eawAIWLbG2Av/5GQDgCe8FeKujVmrhlDnBU8EtoGLFyPPAMapfCRXcUkQNSywZFjkSWRJq2gW8+RPgwVHAgyOBfy0lBnUntgKvXQfYWoDyccCiP0v3UVgSiqmEUKMgYMmjc5u0LAnFoGGh5aBB01W7aPImErA4rR0ht1EdRpXSDMvxz4nuyVwo2p/TDMuxdnv01matS0Ji8DkLKBICOVcv2cdY8fkkXUwYi/eKPDOMeh08Pl59STYWaOfPjhcDr/f5gF2vk9/jLQcB2unXaDmIumunggUPEPFt4w7gi9XAiW3AS1cGtvZrZZKX6HIQoLwkpDTDQn22ylQ6IicIFrBoBc8D/70NsLfBVz4Oj/ouQ0+fRzqByZSERP2KyQC9UkfTtgNkgJfBLKs4p5oDzQ+YWcL/o3VJqPMoMabb8YJ0oNj9OvD3M4Cnvk3KYFkW4LJnA0tU9AQXpSSk+ATndpCZSgAwJHKHEEX1oEmKgpKQKt+YGAS34q5kk5W3W0Z0W600w7JPcNodvUg8iNKpzQ63N3pgR99PnyfsSAvVJSHRWnwKac3NqyZ/xyO8bTtAOucM2WFPujodh8HF5PVq6EhC6ZTOBTr4MWkXpux+nZTDTPmktBsvVMMS74k8GSfwaORVAufdS37/8LfAU98iYn7aJAHImheqgmaUEhmgRSsJqdWwUKPT0lHx7pkmsIBFK75+Cdj/DqDLgu57T2BQaSEAP8dbMWAJrS9TD5ZcNS3NAfqVyK2rtCTUanXCrWVaWsywaHwg3ryK1MarJgPXfQTctAEY/m1ym6WMDGi86iWpFEShr4HXGTbNb1dr4y6WVsoVlVYqE1AScsZSEorD9jsrp5DsiiOwrdnn48UMneKA5YAw0HTM+dLj63UYLJRJopaF/D1vwpjq2dUEoDwv+ZPQ1HbxUHIZj46F6lcGT4+oIRtSTL4nx5IRsJSOIO33vA/45hVynbtPmps0+6fqJjNHQiwJxVlmFgOWKfE9TrxMXUy8pcCTE/7kq4Br35a6yWTGfahC/Awm0M9EDPQjaVhUHFN4njR2AGmTYYlpWjMjiK7jwHu/Jr+f8xugciJGV2zHwRYrDjT1Yu6oMlkNS0yDDxuElXSY2rk/JRYjsvQc3F4erb1O5SecaIgZlthKQp/sa8FbO07ieIcdTo8PK6+YgpF5btHGHefeS4IxALjmdXLgzZIpR9CAhfeRk3+QyZtq0ziaXamarKi0UhFrhkVRSUjhPjutUudLDAdFc14RAEDnDDSOa7M54fby0HFAhRKXW2sLWaWCCylX1pVYcKzdjqNtNpwxrCT8/QHpwAuQ1yYoKKdjFiwmBa9N1zGS4tcbpZVi0VBSUo0nwyKjX6HUCgHL8WQELAAw5Qek/LXjRWD2z0iZo/s4ySjNulWb5xBLQnEELL3NUvdJiufTQKcDrnyBmMgNO0eaUm8wkQyyFiUhRyfQc5L8XjEu/seLRJSSkGTNr+B7Y20hRoucDigZodEOxgfLsMSLz0f0Fs4esro58zYAwOhKIiLb1xScYQk9wffEErBQs6NB8ql/nY4TT6aaloXiyLA4PV789KWv8OaOU9h+vAu7T/Xgb58cJK3Kbjs52Q4NGpInF6wAUpcQEHZFpLok5B+wKEAqCSWgS0hp+rZ1HwCeZIUsper2A0BOPhmAaHAHDkBsFCYOl+eZYVDi3xDQXVUUcJPi1mb/gDPMa2MTM2YKvjNNu8hl2WjpcYvryGU8rc30/6yNHLDUJDtgGX8JyYC07iMDVz99kFz/7d+FOGHHjBZtzaLgdlTYCehJJ7sQmHylFKwAiuZZKYYOiS2oiV/0LIdMScjr4+H2kuyzogxLm5BdKayNfvxNEixgiZcvVku6iktWi6PRqUX/gZCSUGTRba7Slua+bqC9nvyuIPVfFU9rcyTiEN5tPdoJq9OD0lwj7rqArDb+t/M4fF/8H9lg9m3qx677r8DDHGDsak5wgNTOp7DdkpbeWnr71Lndys4SUqvoF1LOMa7g8oQBiCavNUAUS51aFZvGyXRXKW5t1umllLzM+6koY9YsBCwVflmnojhLQt0nSOaC08v63dCS0HEl3jNaYC6QhLUHPybC4spJ0iRfLdCirZkKblOpX4lGFCG/Kuh3szyB2RVANshyeSRJgKJFUJqVgwBWEoqPln3Ax78nvy+4j/SqC9AMS31LL7w+HnqxJBRZw6I4w0Jrv0V1kpGbDFKGRcPWZjEAU38g/mQfaVU+Z3Q5fnTWULzx1UkMb3wHOnsbWYGMv1j9/uj0xFPB5wmbwlVVEvK4pBWRwnR1meDD4vby6LS7UJKrdCqxsmnNimgRWhDLYzN4KiginyULb0eX3Y0iCzn4UdO4aqWmcccjl0rUtTYbyUkxzMFXnLytpCQkWov7tWZSDUusJSH6HSwfJ9uSWyv8v0nLsADA+Q8S193eRrK4GX9JiEdMXGjR1pwu+hU5qC5Jy4Al0eZrCowoAYVOt2LAkh6CW4AFLNFp2klGngeltuFxAm/cRESeI+YD05YG3DykOAcmgw59bh8aOuyoM0buqhFt+ZWKbsVykDJhZWIzLOo1LOsOtAIA5o0uBwD8YOYQGP9LTir8xMvAxToRVG8SApZwJSGhDVaJ6LZ1H/nCmwpIUKgAo0GHEosR7TYXmnucygMWRcZxycmwGC3kM57P2XG4zYZpQsDSqKal2WWXymlh5i8FtzbLeuKIAUvkkpCiMQtihsUvYKEZFmsTKW2oFaPS/7FavmRYI3QJdTvc6La7UZCThGm3WdnA6IWJfXwgvg5BMYM5Je7dSRg0MIvg7aQKuphIeMASuSREjyd6HaestEtbmktHa7V3ccNKQnI4e4GXfgCsOgPY/750vccFvLqY1GGzi4Dv/i2khKHXcRhZQbIq+5t7FZWEFGdYTgoDzhQGLJW0tVmtIFQO+v/4PLITkoNp6LDjYIsVeh2Hs0YSncV3J1XhTB052e4xTYl9n8ROIZmSkJIMi385SEVpKibhrZKSkJL0Lc/Hf1AUpsfmw459TVKnUKOaDqGT28hnIq+aGJkF4d/a3BLNFVhmtehQWhLq6wkvRM4ukoJFW+gogqiIGqcpspvlGA2iC3JSsyyJhAYssYpRnb2SALU8fcoNIURxz1YMz0sGbEkLWMJkWNTOJqMtzWlUEmIBixy9zeQkaG0CXroCeHUJsPnvwKvXEEW5wUz8QPKrwt5d1LE0BQUsQb4SUklI4eorHTIs/k6NEQY6hoNmV6YNKUJBNvl/LdZjqOQ64OQNeKahQu7u8tCAJd6SELW2V9m9EJPbrVxJSE2XkLWFmKBxutgPMIJxnIlzo/6kZKhGTeOqlWhY/IdFhgn2/Fubj0TTscgcfO1KS0I0iMurBnKKpes5DsgRyqn2eAKW6KLs2pIkC28TjSHODEuboL+zlIdmrtMJDUpCXXYX3tnwBdES6bIS320jezxRoYlzdBKXX4A4EacJLGCRo3QE8OMNxL8AHLDnTeCD5SRY0ZuAK18kk08jMFoIWAIyLOBDxGr+xnFR6TklzKPQKz6hivb8Wk6N1WdJK1QVB651gn5l3hi/abFH1gMAtvtG4ZPD1uguqBH3iR5gIq/IFZWExJOR2oAlhk4huZKQmhVRi1AOKh4Wu9eGKR88SJDR0CgZj4mTmpVoWBqiT7dWPLVZ5uCrWHQbTr9CoZ1UNpVut71N5GDO6RStmCUvlhQNCtUasSQU4wKIBixpYkYWkThKQn1uL25+fhum3/cx3nj/QwCAo3BEiN2C5shlWNQsgOjQx/xBYuY1HWAalmhkZQPn3QeMu0RwjDxBat6zbpENVgBgVKVfp5AhGwAHgCdZFr8MRa+atmaaXakYp7hNkQ5ha+51wuP1KatfKsGYQ0R9CoW3fW4vNh0iJ4dzBP0KADFg+QIT0GZ14lCrDSPKY2h1FFX9oQdSxSUhn0/SPChsaabQgKUpFSUhmnKOpwtBp4PPmAu9qxfNrc3geR4eHy+WbqJ2Cfm8QMMW8rtswJKD9VDS2iyXYVHY9RVOv0KJNcNCA9rSUYpmwtDW5qS43SYDsa051gwLdU9Nn5V7WKK4Z8uxbn8r3ttFgv5JJlL+2uurQWRPco2QDVhUHE9oS3OaBZUsYFHK4GnkRwU0w3K41QaXDzAaLaR84rICkE7YqkpCKstBAOlgMep1cHl9aOrpw+AirfwYLCRgUSi83dPYA4fbi9JcE8YIwRx8PuAIce3tqDgDOAF8frg9xoAl8gBEqSQU5SPfcZi8PwYzUKLugEoDlhatSkJquoQ06kLQmfMBVy84pxWnuvvA8zx4HsjScyi1RBESt9UTP6Isi2ynkuLWZgUBS1TjOOrBIpthURmwqJyBk3TzuEQjtjXHmmFJL7v3iBhi17B8cYQszK6aMQQ/7LECR4H/dZRiRJ8b+UpL/7Gg6HiipkMofQS3ACsJJZSqAjPyzAZ4fDyp10cQ3qoS3dKApVp5rK7TcaL+4ESnlq3N6szj6AlqZHmu1B3SvIvMY8myoGwUGSD3+eEYB9KJIjmZkpAxyke+SVg9V4wH9OrieVHD0qviQC7bJUT22axkRURLQnH6PHCCjiWXc2BfY48ouK0sMEMXbc6Vf/lF5rVT3NosWxISNCxyGTOel8oPZWNDb88RApZYMywKM3BDBA3LsWR5sSSaeNuaM6YkFFnEH40vDpMBorOHl6DYSv7fXZ7BeGP7Sc12Lyxybc1qXG7bD5LLNMuCsYAlgXAcJ2ZZ9jX1RAxYFJeE/GeiqCxX0KyKpgGLSvM4WgKoK/XL8Bz5lFzWzsbMkURw+/nhjth0LLIlIdrWHOU1bhFa+WI48YsloW4VKzLZkpDCA4zPK62I4u1CCOgU6hVN4xR5sNBgL8pYAMVTm+MtCdlaAWc3AC7AI0mEZljUTmxWGbDQDMupLoe287xSRTxtzV5P2p4MQ9BHFvHL0W13Y6/QZTezNhec8P/u89Xg+c+Pxa7RU4JWXUIdh8ll8XCt9kwTWMCSYAJ0LFEClqii24BOEHWpOtqZcVLTDEvkVu1wHBNW1NRMC4BkMjZ0DibXFMBk0Ak6FuWdRyKGyF9Wh/BljSrSFFv51KdCacDSblMxaFJRl1CUr2nXMXJQNZgV+8ZERDBBy4UDext78O7ORgDAcCUlOjHDIi9WVtzaLHPwdSgpCdETY2FNeGtxqmFRI7q1tQE9J8jvCuc1leWZYDLo4OMl1+CMJp625q5jJDg3ZAdORE5HYuwS+vJoB3geGFZqQbm7EeC94I0WdGeVob7Fiq3HOhOwswJKuoSiZWx9XskKIFygn0JYwJJgxE6hJmvYAYg+H+9XEopS26QtmjF0glDh7YlODdPSsWZY/AMWv4yRyaDHtFrS5rhZSKmqQsY3QTSOixqw0HS1+oClxGKEXseRSoRV4UFOtkuItiFG2ef2Q+SyeLg4GiJmhJJQHmfHhvo2fLC7GRwHLJ1dJ38/nvdrB5c/kStubaYH36ASH8/zsCl5P2nAEkmLZImhJESzK8XDFXdPcBwntjYfjqbbyQTiaWsW9SsjtHXfTQRil5C6khDVr8wYWiweT7iSkVg4gdhfrN/fqt0+BqOgSyiqy233CXJ/vZGYpqYRaf6JyXwCZgrRE7xfwGIVDryAgpKQaL0eph4fhcHFNGBJhIZF2UGYaljEkpDLJkXygkhzljDBNyYdi4xIzq6krdnnjStdrdNxKBemGSv2vJEZB694+KF4YtYgfeuXYel2kH367uRqjKyIbD8PgLTbOzpIu72Ccpqi1uYIB1+nxweaVZcVUYuvSwTvi5wYRLcqy0GU4WVksXK4tR8ELPG0NWeK4BaIuSS05QhZbM0cVhzw/84cSnyAvjwaw2JMKVq0NdNyUFFd/AsgjWEBS4IZJbjdHu+ww2OgJ2qp3NFtJycFo0EXPfUvtq6q1ylQDctJLVPSWZHHDQTTZXeJJ0DqSyFNFy4DcokvyxnDScDyxeF29bVeUSQn1yUk8wXsOk7uqzeFdWlVgmovFipOjackFO3ErAYha1CWRQ7SOg647dsKgjfqDlw2RtFkV0VTmyMICGnwCUQJQGnmKdLrEk+GRWXAMqyMfFcOx1LqTDfEgCWGY0kmBSxiSUh5hsXq9GDXKUG/MrQkYAE0vY4ELDsaugIGEWqKbJeQwpKQqF9Jr3IQwAKWhFOSaxKtuXt8wgnVLyNBuzCqCszyc1WA+DIsQgr+VJcDXjXThOVQoWGhJ6aKfJO0Kg7jHTJpcAGMBh3arC71XRVyTrdKfFjowbRkRMwrC9op1KK0U0hBl1D0kpCGAYtQEhqUQzJ/l0wdjGFlavQrynQdilqbI8xFsQklVHOWDnq5zqVomSeaYenrDvv6hyXODEtM2qx0Q9SwxBCwUEOydBfcAjEZx2092gGvj0dNcTYZZeHnOTO8zIJiixFOjw87T3YnYIehMMPCAhaGDKMrycGq3SWcnAICFvKlr8yPZsrlk4ZRxdAJUp5nhkHHwePj1VnHy6GiJBRWcBtm9o3JoMekQQUAoF6cFqGt2eXxwSMEabLD8jQwtJI6heIrCXl9PNxess/RMyxRMglqEAKWqeV6fH/aYNy5SKHNv0p3YEWtzREOvoo8dXxe6cAb6XXJLiICdkBZp5CjC+gUpjvHHLD0g5IQ1bB4XeR1VgrPZ1aGJQbjuK+OdwEATq8rDmyrLxkJjuMwXdDobU1UWUjB8MPoJSHhM84CloHJ6ApyEmhxCgdYvxP8qS6Fg+U6j5DSi94kTZpVgV7Hic+hWVlIRUmIiiuHhhPcBmWMqPB2m9qAJUJJiJ7gAIUZljjMkqh9faPigCV8Scg/ZSybwnU7gO4G8rsmAQvRqpQYnHjwsskoy1M4dTrGDItsa3OUklD08p6LfF8idaPodEC2MF9IiY6F/o8FQwLnEimAloRae53o6VOYzUlX/Et+aspCtjagrwukzTy92mXDItokKA9YqEZweFlu4P8rZPlOr0uwjkWLWUJihkX9eSbRsIAlCdAMS6NdeLn9NCxN4pyWKBmWlr3ksmy0akMzCi0LadYppMI4jpZ3av09WFrCa3KkgEXllzqC6JaWg/Q6Dll6mRKCBoZW1KBPcVAYoSREDy5AFFU/PbiYC1WfRMNCO1+cPfLb+ePoIu2qgOKARVFrc4TVot2pwDROzDoNl+9GUaNjiXHGFEA6AKkgO+OFtwa/xZUaQSot0RXUKB4rklJknLMjcbKLHOcGFWYD7cLxpLBGLKOdLghvtx7rhE+r0rw/SnxY5BZAPp+URWQZloEJ7RRqsAkvt19G4pSfhkWWMOUTtYitzR1aZVhoW7MSDYvQIUQzLNZWYuwFLmTE/GlCwHKg2SoKdRURoa1ZdEXN0svrhDQoCdHXWLHfRoSSEE3fGnSc/Ownf/1KNA2UEoQMC5y9yu/jn3lQOH1XUWtzhIOvNBdKSYdQlJW8mk4hMWCZEn3bMIhloZYM17HodNJ3TU1rcwcNItPvRBgWGZuESNCFyqCi7LDlr/HV+TBn6dBldydGz0S/M7w3pFznUuJ029tIglCdgXyf0wwWsCQB2hLa1BdaElI8CTcOwS1F804hUXSrIsMidIeI/09RXcgAudJcE4YKJYOvjqsoC0UwjqMlIdlykK1d0jHEUVqhZbfmnj5l4uYIJSG6GjJHmy6tpeAWEDUs6FORYaGlPYXZFQrVMx2LpGOJUBKiHiwWRR4sUV4XCx2AqEDDEqPgliJ2CrVleMACxNba7O8XlAmoLAl5fTwa/Uv8fvoVSpZeh6k1JKjfkoiykP806AjHFNmSEM3YFtbGnMlPJCxgSQK5JgNqirNh52mXkH9JSMiwRJuEG0dLM0UqCWmdYZEPWLodbnTYyElHFN1GyRidNiQGHUsEa35VHUIFNYom8EaiPM8EvY6D28srM4+LUBLqU1pv1lJwC0gBi5oMi/heqhtnMFQIXo+0Rfj8iJqkwNfGoUTDQtPx0V4XcZ5QlIDFZZM+IzEGLFKGJcNLQkBs9vwdfmW6TECl021Lbx88Ph56HYeKPJNfiTkwY3t6nXBsO5oAx1uaYQHC+BcpOKakcYcQwAKWpDG+qgB2BLY1Oz1etFnJh0p2VovHKa0Y48qwaK1hUdbWTFfQZXkmafyAKLgNf5KLSXgbQdWvyDROo+4Fg14ndnwpymRFKgkpnfuhpWkcEKhh8Sn0iqD6KpWfzaitzXGVhOjJMUp5T+nE5qZdAHggrwrIq5DfNgJ0vEG/aG2WmdsVkfb0nE8TEX14EX8kaBm4Mt9MyrgRjimTawoBALtOJaC1WSeTYaFOt3IlIRawMABSu7RD+JILJ3iaXTEZdCjMkbHl7zhCapLGXCC/OuZ9GCR6sfRpI/hSmGGRLPnDCG4jrMqnC6uQHQ1d8CidyxNhuqoi0zgN2y2p8FaRjiWCql+a+5HskhB1tOUVaZPA834Bi7oMS9TW5givjT1aSUhN55TSic1xloMAYHiZ1Bml+DOdrojffYXZWp5P+5NhCKKIX5lxHM1cDyrKJosmKkQPyrCMrya2DYdabehzB+pM4kanI/oTIKxDNMAyLAwFTBhUABsfGLDQ1tfqwmx5MahGwsrKfDP0Og4ur09+6JxSFPqwNHSQgKWGOtzyvDRdOMJJbkRZLvLMBthdXuxrUlieiKckJDpSxn/ip3okRQGLLoKGRcnBxd4hlTK0OsAYzNIqTYmOpfsE4Ool91G5co7a2hw1wxLh/ewUThSmguidU/T2aAMQNQhYqguyYc7SweX1aTsiIxXQ1malAUtvEwmAOV38AzqThYwRZThoRnVwYTY58fM+UmLNDczIVeSbUGIxwuvjlR/b1BBppIUSp9s09mABYgxYVq1ahbq6OpjNZsycORNbtmyJuO0zzzwDjuMCfszmQL0Gz/O46667UFVVhezsbMyfPx/19fWx7FraMr46HzYhw8ILGpZGpS3NSuvxUTDodeLq/3iHBmUhcZij/GNRozrx/+xtJDoeTh/RU0an49TrWMSSUIQTnJxpHJ1pFIPHTTDVhVImKyoRu4RU1JvzqgGTAjdaJXCcX6eQgoCFZldKR0o1f4VEbW2OErBEzJjRlW3RkOgBvtK2Zg0CFp2Ow9DSflIWUjn4VNSvFNSo/pykDH34jG0kTgpBaHVhtt+Jf2jIZ5DjOIyrJqXX3YkoC0XM2kbpEuJ5v5bm9PNgAWIIWF555RUsW7YMd999N7Zv347JkydjwYIFaGlpiXif/Px8NDY2ij/Hjh0LuP3Pf/4zHnvsMaxevRpffPEFLBYLFixYgL4+jRxZ04DyfDOyLeRDyjsDMyyVUQOW2AfyBaNo6JxSFLY104CFusCKYrSiOtmDl+gKqTRgiZRhiVYS8vn8xqnH/0UdpMaLhR5cfB7AL8sgaVgUeo1oiVmF8DaO7rWorc1RSkIRnW67jpPLwtroO6GkrdndB7QKgVkcAQsglYUOZnprs9r290R9VhOJzDDVcAS0NEdZANGy0K6TKrrxlCIzNBSQWQQ5OqWGkEhmiylGdcDy8MMP44YbbsDSpUsxbtw4rF69Gjk5OVizZk3E+3Ach8rKSvGnokJKkfE8j5UrV+K3v/0tLrroIkyaNAnPPfccTp06hTfffDOmfypdGVJJBvzpfC7A65Za4KK1NGvYCTKslLZWahCw0JKQzyNb56WDAMvzhICiPbx6PhgqvN2uOGCJ0NYsnOAiim6tzSTI4fSafFGr1Xix6PxOun4nZkWTmsVMgoITsxroyUhJSShGwS1FtrU51gwLPVkoCVhohsXREVlk3LKHfMZzSoD8QdEfU4aR5XR6e38JWBSecGmGJVMEt4DqgIV+3wcV+gcs4T+DEwaRRcGeRApv1XYJ0UA/t0LRANNUoCpgcblc2LZtG+bPny89gE6H+fPnY/PmzRHvZ7VaUVtbi5qaGlx00UXYvXu3eNuRI0fQ1NQU8JgFBQWYOXOm7GNmIiMG+dUyXTapJBStpblNm5IQoHDonFKy/Np/ZbIsLT1BmaQ2ZULRyTWF0Os4nOxyiK+VLBGN46JpHo6Sy4LBgT4GMUIDFkX2/P5tiD7/gEVBSYhqNQrr1O6iPKYCYSeUBCyhAyzVINvaHGmWkOKSkJIMi+DDwvvICjMc/uWgOM35RleSE/3+5gSsrJOJ2vb3TMywiJ+/6AELz/NiSWhQUbbfZ7Au7PY0w7KvqVd7AXakkpDodBvhe0OF6mmaXQFUBixtbW3wer0BGRIAqKioQFNTU9j7jB49GmvWrMFbb72F559/Hj6fD7Nnz8aJEycAQLyfmsd0Op3o6ekJ+MkExtWUwMlL5nGNSlxuHZ1SfV2DL7sYsMgNnVOKwShlCCLoWHw+XtQn0EnGSjMsFpMBY6vIAV6RjiWSNX804zhat9VIDEgDlg6bSzy5RiTA6Ek6MfcpKQnRg2Khxo6USlfPPq+feDoRGZbwB16b4pKQgtdFnwWYhQAtko6lcQe5jLMcBEgBS32zVbup6amAlg2VGgyKmo4MClj8jeMizbsS6Ha4YRO+64EZlrqw29cW5yDXZIDT49N+IGaEQF9yuo2SYdH6eKIhCe8SmjVrFhYvXowpU6Zg7ty5eP3111FWVob/+7//i/kxV6xYgYKCAvGnpiZ9I0J/xlcXwCF4sbgcvX4Bi0xJiK5M8qr8Wk5jh5aEjrTZNGptlh+A2GF3wePjwXHEwRZAWAfISExTI7yNNPyQrsgjrSyiHFzUkm82iH4zp6JlhgJKQh7xV6swL8diUhCwaF0SUqph6ThCXmtDdsxZnqF+n8cQYs2wiJknha9LNB2LBoJbypDiHJizdHB6fNosGlKFmGFRELD4fH6TszMpYKHZTz7sMEF/aNdXicUIs0EX9TOo03HiYkxz4W20LqGBErCUlpZCr9ejubk54Prm5mZUVlYqeoysrCxMnToVBw+SsgC9n5rHXL58Obq7u8WfhoYGNf9GyhhclA0HR6L2QyebRfdXWQ2Lxj4bgwqzYdBxcHp8aOrRQNQcpbWZCm5LLCZk6XVEwEi/GApExNOE6aaKAhaxJKS2DfYoudRIGc9xnHIvFo6Tas5+JSGbGLBEyCJ4PUD3SfJ7ojIs0VbPYjlojPyAQRlkW5ujTGsO+372dQsTcqH8dckTjjM9p0Jv87olk0MNAha9jhNni+1PREtrslCTYeltBDwOohFL45NhCPR4AkQtCwUIbq0twv+rky2v0LLQ7lMaVwiidAkZIwYswnm0MH0TAKqOMkajEdOmTcPatWvF63w+H9auXYtZs2Ypegyv14udO3eiqqoKADB06FBUVlYGPGZPTw+++OKLiI9pMpmQn58f8JMJcBwHr4EcoN/8ghiVZWfpkZ+tZIibNgGLQa/DEMEPRdtOofAZFqlDSPjydxwGwBOdhKUs6sNT4e3uUz1id0hEIvgmRC0JdWhbEgJUCm/DnJhpwJIbKWDpOUnMBPVGIFfZYkExSvUJMRrG+SPb2hxpWrMQsFjClYRoMJxTorzVm5oF0k4gf1r3kffFVKBJyzsAjBYCloR4cCQLNRkWKrgtqtVEI5Y0DH4BSxTzuLCC2/zBsl2Q4xPV2hwmw+L18WLAokl3XYpQvSxatmwZnnzySTz77LPYu3cvbr75ZthsNixduhQAsHjxYixfvlzc/t5778WHH36Iw4cPY/v27bj66qtx7NgxXH/99QDISfz222/Hfffdh//85z/YuXMnFi9ejOrqalx88cXa/JdpRE4u+ZDWnyD6nKpCc5QJwtoJbiliGl6LlLSYYYkUsFD9SnCHkDITvOoCMyrzzfD6eHxzIsoX278k5Ldal9pgo5WEtPMeoAHLSSVeLKKqXwrIbGLZI8rBpaAm5uxGRJRqWDQYyCnb2hyxS0jm/YwlrU0DrpZ9obeJ5aBJ2kzDhp/wtikztHdhUROwZNrQQ4pOL5Vso5jHiYJbBR1CFP8MS1jjxFgJ873xX+xFPA52+x1T0hTV4xivuOIKtLa24q677kJTUxOmTJmC999/XxTNHj9+HDq/A2hnZyduuOEGNDU1oaioCNOmTcOmTZswbpy0Krvjjjtgs9lw4403oqurC2eddRbef//9EIO5/kBxYRHQBZSbPIADqCnKkb8D/bJr4MFCoWn4I1qIvaiGxRW+TTMkw6JCvwKQgHZaXRHe+aYRW4924IxhJZE3Dh78JQQw3Q6yQi/IDrO6c1oBm+AhpGGGZVAsGZYwJaHcSBqWROlXgMB5QnLE2dJMqS2x4Fi7HcfabYHvb0QfFpmMmVr9CkBKWoAUgPmjoX6FMqaSvL4DpiQktjSnp3uqLAYzObapKQkp/G6OKM9Flp5Db58HJ7scGBztXKCUMN8b+p3R67jwGhZHFymnAmldEoppfvStt96KW2+9Next69atC/j7kUcewSOPPCL7eBzH4d5778W9994by+5kFoI77G/mD0GpdQQWTpBJ5/t82s+KgcadQsZoJaHgDIt6C/wzhhbjnW8asflwO279lkygY/ALcD1OMWDptJEvbmFOmPQsPbiYC4HsQsX7FA2qYVHWjh1aErJG07AkMn1rUnAyChjIGXtJCCCtzZ8iTGtzlNS2bElITYalTAi4Oo+STKHR78SRgICFZliOddjhcHnlR0akK6oyLBkouKVEcM8OJqCB4uBRcmWUBZDRoMPwslzsa+rF3sZeDQOW0O8NPZ7kGPXhM/q0pTmnNK5p9YmGzRJKNsKHIV/nxC8XjMaEQQWRt+09RcRbOoOmJ6ahJTKdGWqJMrG5JcTlVhgyqDDDAgCzhpMujq1HO+WHhUUYrd5lJ78XhQtYNBbcUgYVkoNPQ4cS87gwJaFoAUtnglqaAWUalrZ6oqExF5AOtjigJcoQu/ooqe2wJ/pYMk+5ZUKnEA+07Zeu97iApp3kdw0DlrI8MkuG54H6lgzNsvhnWKKVMzLRNI6icJ5Qu40szMryjH7GhXVRH55a9O9t1LA8GCZja3eS42ZETVwGCG4BFrAkHzUOkXQFWzQU0MeUDAvLUMEe/HiHBlNjo7Q1N/f6lYR4XjKNUzEVeXiZBeV5Jjg9Pmw/LtMtpNNJJ3/hAOPy+EQ9SFG4idgJENwCEIXNJ7sc0V/jMBkWWWEpkPqSkL/gNk5txwjB/fVQsF19mNeFtjTruAjtmbFmnmhZy1/H0vAF+VxbylQF2EqgWZaMFd7S45jPLX8y9/mk71hJJpaElM0T6rCS20ssJmkxoeCYMq6KOt5qGbCEitVt0XR8GdDSDLCAJfnQsoOjK/q2Glry+1OVb4bJoIPbyysb0CeHQtFteZ4ZsLUCzm4AnKp6NsdxmD2caBs2H4oyVdff7AlSdkXHAfnmMAGLxh4slPI8E4wGHbw+Ba9xmBVRVB+WhJaEFMyJ0UBwSxlZQcqkxzrsosMvgLAZFptfIBeS2ub52DQsgF/A4qdjOfgxuRz+bc2FzRnf2mzMAyC8/nKfk54TRP+hMwAF6X0yDIs+eobF4fKKn8tiM086+ABFx5SxQsCyV0sBdrjvTbSMbQa43AIsYEk+5kJy2aeglY2aLWksVtPpONRSS/R4dSwyAxA9Xh/arH4aFiq4LRyielbFbKEstClqwBL4Ze20S4JbnS5MJiABHUIAeY1pluVYR5TXWBcqkpNta/Y4Jc+QVGlYNGhpppTnmZBnMsDr43HUX8fif+AVyg69feQ1CnvgdXQCLuHkqTa1XSYIb1v9MiwHBauFEfNDt4+TMWKGJUM7hXQ6ZX49dNFVVKdpljhpGKJrWGg5yKjXIa+vCQBPjot0TpUMNGA51m4XFylxE84mQWnGNo1bmgEWsCQfagNOza3kEAMW7Ud9U93A4XjH3Muc3NqsLvA8UaaXWIyKLfnDMXsEybB83dAl/8UOmtjcKWRYwgpuAc1t+f2pFQKW4x3hs08iYVT9YltzuBNz9wmoOSiqhp6IPI7IDp8aZlg4jsPwcpJlCZhi7O/Z4SPvebtgtlhskRFQ51YAWVEGigYjtjYLgVhPI9C8EwAHDD9H3WMpYJzowaFxS2syEbVOMouvTNavANLxRKZLqMPvM8l1HSVXFtUpKpUWW4xiB6Vmbe5hSkJ2xRlblmFh+KOmJJRAO2vNpsZmE2O3cIPjqJNueZ6JZDdUtjT7M7goB0OKc+Dx8fjySEfkDYNU/V122iEUphzk80lf1AQELDU0YGlXGLAIJSG31weX0AmTG7YTxk9wq5E3SAD0RASET/c7e6V9KIs/YAGAkWEDllARtagVyA0XsMRRh6etzd0NJPg+9D/yd/XUhASFoyvzYNBx6LK7xZbYjENJa7OoX8nQgEVBSajd/zMZQ4mZZln2NGpUHpTtEoomuk3vsh0LWJKNWBLqkt/OX6yWAP+CUZU0YInzS5JDrPPDBSzNwR1CMbQ0+0N1LJsORZj5AoSo+mU7hKzN5EvN6YH8QTHtkxy07HYsWsASVBKy+WWQwq6IEi2Q0xukUl844S0deJhbAVhkfHFUMEIIWAK6ZsIFLHIZllj1KwAJvGm3U+t+Sb+SgHIQQIZaUh3LrpMZWhZS0tosmsZloOAWUFQSomXvklxTTJ9BUceiVaeQnIg/XMbWaQUcwiKQaVgYAdAMSzQNS89JQayWRSyeNYbW0A809caXkpbJGLXEaRoXzCwhYNlQryBgCdKwhM2w0CxBwaCE1NdpwKK2JERXQyaDDgZ9mK9oPCdmpcjpWDQsB1FGhMuwBAyGJK+NopJQrIEc1bF884qUYUlQwAIAEwYlyJo9WSgRZ9OSUKZmWFSUhEos8WVYtAtYIncJWcJ1CVHBrblQypqlKSxgSTZUwxKtJETLQQkSq9WVWIjLotODU91xdAqJJaHQMk2AaZzHJX2ZY3TtPXtkGTiOtIJGdJAVU7iBXUJhMywJnp0xxE/DIhsUBpWEZFdDQHJaEOVORhoKbik0YDncZoOXThHnuJD0docgcCwJG7DQ8l6M72fFeHL55ZMkA2ouAAZNi+2xFEA9mHaezNCAJVpJyOf18znK0IBFLDFHDlja4wxYaGvz/qZe6bMfDzKzycJq4jKkpRlgAUvyoSUht01+ZHmCOoQoRoMOw0rJSeJAPK2V2QpLQp1HidGYMTdmo7EiixFTawoBAOv2t4bfKKgk1CkGLDIZlgR9UQcX5YDjSMaEZnrCogufYYkskEugBwtFzoslARmWwUU5MBl0cHl8aOiI0CkE/5KQKfgh4s88nX49MP4SoG4OMHgGcO4fEtrZQmfJ7DrZnZnC22gloe4G8r7pjUCB9lnipGAIXACFI6AkFMN3c2ipBeYsHewuL45p4T4eriQkGseloMSsISxgSTY0wwLIl4USHLAAko4lLvMqmmFx2wF3YKbGX3QrdgiVDI9LKPqtMeUAgP/tawm/QcSSkMYiTQWYs/SoFPQ7sgcifXgNS8QWxKSUhCJkWHgeaN5Nftcww6LXcRhWJtMpFK0kxPPxv5/FQ4HLngGufRu4/iNg2pLYHkch46ryoeNIN13IpOpMIFqGxb+lWZeB4weAwIGqEaBBdKXR4TePR/l3U6/jxAnee7UQ3soax7EMC0MNOr20MpErCyUhYBmjhfDWlA9wwscoKMvS5D9fI079CuUcIWD57GBbeJv+CCWh8BqWxI9Tr1HS2hxUEpI1eXI7pGGNiTzAWMjrLNa3Kd0NxABQZ5BKKBoh6lhaw3QKBWVYQrqEbK2kDRtc2gsHKdlGvfg/78rEslC0tmbxGJah5SAg5HgSDtolNIhvJlfkVgTOo1KApjqWsCMtaJmZZVgYalHSKSS2NCcww6KF26ZOF7G1WRwIVmiOy4PFn3FV+ajIN8Hh9mJLuPZmQ2DNmbY1y2tYEvdFrVXS2hzSJSSjYaH7bMqXXvdEIE4w3ht4/clt5LJivHqvkyiMCJthCQpYrBEyLPR1ya+WPgMZwITqDNaxRJs51Z7hgltAUUmoXSgJlXmbyBUxLIC0DVhCfZ1k25ozxOUWYAFLasiOIrxNcEszhaYhD7Za45spFCZg6elzi1+SqgKzNEMozjEDHMfhnNEyZaEgVX/ELiGfNyneA2Jrs5IMCw1YXNTlNspqKBEeLJRyIXvSvCfw+hNbyeWg6Zo/JbXor49QEnJ6vOgVPlMholtx4Fx6O3UGM34Q1bFkYGtz1JKQ8J3P1JZmIOosIZ7nxTJlkVNwn47B0ynhGRa54Ycsw8KQJVqGpbdRmtKcwPkbg4uykWPUw+Xx4Wg0rxA5ROGtlPGg5aCC7CwS1WuUYQGkstAn+1tCxYp+xnE8z0fuEuptIiUYnSHuacNyKDKPCyoJWeU0LMk6MVNBbduBQHH4ye3kMgHdM6NowNLcCx/tlvA7+HbayH7odVzoXKgMOuj6M0F0vM3kDEuEkyz166Ht4plIFOM4m8sLp2DyaLGfIFfGELCMqSKLx1PdfeIxK2bCzuCKMPzQZSflVCDtXW4BFrCkhmj2/LQcVFib0C4FnY7DyAoNdCxhMiy07biqwAzYOwC7MANIg0GOZ40oRZaew7F2O460BYlZ/az5rU4PPMKJLyRgEUsIifFgodSWSJOxIxLBOE62JJToE3PhENLR5XNLK2WvB2jcQX4frH2Gpa7EAqOBdEs0dAqvl9/Bl85sKcoxhs6FSkbnVAIYP6gAHEfKp9S3KGOQy7C4bEC38FnN5IBFLAmFDyJoOSg7S4+sntjb6vPNWagpJiXWuIW34UZ9RDqmdAtBlilfWkinMSxgSQXR7PmTILiljBZWtZp0CvkFLFS/Ul2YLZ3w8gcBRkvszyNgMRkwcygxkQspC4nDD52ifsVk0CE7eGWRpBM/1bA09fSFFwkDIW2IkoYlXEkoSSdmjpOyLLQrqHUv6QYz5cctng6HQa8TLfrFz6Nfx0OAQVcwGZphyTUZMEoYk/FVQ1dqd0YtchmWtgPkMqdUMzfklGCQz7AEdK3FOfl9bCW16I+zLCQ35Tw4YElWiVkjWMCSCqJNbBYHhmk/9DAYKrzdF8+XhNrz26WSEA1YKgv8pjRrkF2h+JeFAvBT9Xcq6RBK8Im/MCcLBdnk+UOyQRSxJERWQWmRYQFCBwJSwW31VCK2TgBjhIP2vsbggMWVOFv+FDN1SCEA4KvjXSndD9XImQv2h3IQEPbk7w/tECq36CVNXKwBi1Y6lqB99p9NFuJ0S7NgGSC4BVjAkhqiaVhEgar2q9hg/M2rYiZchkUoCVUXmIHWfeTK0lGxP0cQ1I9ly5GOwOnNYknIKQpuw3cIHSWXCT7BcRwX3nben+CSkEtOw5LEE7MYsAjCW1Fwmzj3V9pqv79ZOGj7pbfpyaE4uKXZ55M6HTIswwL4Byyh5otpDS1tu+2hJpj0O182Orn7pDV+x5Nw0JLQ8OxeQROXFbMmTruAJfB4QgW3QJguoQzLTLKAJRVEKwm10dWJdif4SEwcTGrop7r70BqreZVMSaiqIFtaoVdoZzQ2tNSCupIcuL08NvrPFjJIqwtlHiyJ/6KGbdf1J6gkZI3U1uzslYTNyTjAVAQFLAkU3FKo+DAkw+JxRi4JWZsSOsQy0Zw2hHx/vjnRHV+3XrKhGRYgNMvSXzIsCktCww3CMahwSMwmedSiv77ZCnc8n4Mg4zi6ADLqdTAagk75Yqcky7AwIiGXYfG4pJZmDTMSkcg1GTBcOKF+cyLM/ighnOi22090K662tLNyB/zKQv46Fj9Vf6o9WChhDdH8CSoJ2Z0R2prpPmcXJWdIGc2wdB4Fek4RDQuQEMEthZaEjrTb4HB5ARN57eDsiexyS1+XBA2xTDTDy3KRZzbA4fbGpyVLNvosaap3cHlb/M4n/hiWUBSWhGp0QqdNHCXmwUXZyDUZ4PL6cLg1Dov+oH220w6hDDeNA1jAkhrELqEwZZiOw8LMnbyEttv6M2kw2Z+vT8RYFgoKWHieF9uaq3M8Urq+XNvV1rfCtTf7qfolDUtwCcErqeOTGLAcUlgSskbSsCRbp2EplRxvX7wc4H2kTJlXmbCnLMszocRiBM8D9S29fp+trsiDDzNYvwKQbr0pwoysfiG8dfdJAtSMz7BEKQkJn8lqn2AaF6N+BSCfA1oSjassFDLqQ8jYytnyMw0LIyJyJSFaDiodmTTV9uTBZH9izrBQ0a0QsPQ4PKIVdJVTyBblVWvuzDpjaDFyjHq09Dqx+5TwBfeb/SFlWIJKQr2NJJsRR71ZDWEnEfsT3CUUae5HKlZDtCzUtJN41lz894Q/ZUBZyC8Yjjj4sCuzAxYAmCqUhTJOxxJOeNt+kAS35gJiU5/JBDlnB0M/k6XuRnJFHAELAIwXfHnicj4OyrCIk5qDBbceJymnAhnz3WEBSyqQKwnRdsAkitVohuWbEzFOjaUnFaFLiJaDinKyYOoQAjANJ/tSTAY9zhxRCsCvLOSneeiMZBpHV+QFg5IylG1QYTbMWWEmEVNCSkIRXClT4TXiP+DwvPuAmhkJf0paFtrb1BPwXYlcEkrs1O1kkLGdQuG8WMRy0JiMaJWVRS8tgMLRJpSECqjLbZwn/slCpu3reDJtIRqWCJo4mmXOskiLzjSHBSypgGZY+npIh4M/rULAooEjrFLGVuXDoOPQYXPhRKdD/QPQgMXjANyOwKGHVHCbgIAF8JveTNubw3QJFQRnWES/hMS3jQMk1TusVEZ4G7EkFMk7JokBy/Bvk8uJlwMzf5yUpxxNO4WawmdYQgYf0gA0ztVtKpkqnKiOtNnQaYvT6TSZhCsJiYLbDO8QAhQbx+XYYne59YcGLLtOdccuvA3K2FINS+TjSU3GBJYsYEkFVMMCPtR0iWZYSpP3ZTdn6cWWum9i0bGY8kmHBgA4usQMS3WhWeow8V+pawidK7SjoYscPAz+ottIGZaj5DKJJzhZ4a1fCtfj9UlW38EloVRoNUbOB36xH/jeE0k7qFEDrb2NPeCF7wrv6BRLfCEZFvp+JsG3KFEU5hgxrIyYKm7PpLJQtAxLpiPTJcTzPDpsLpjhRJaDim7r4nq6oSUW5JkN6HP7YncfDyoJRRx8mGGCW4AFLKnBYAIMwqRb/7KQzyeZrCWhQ8gfSXjbJb9hODjObyXcgcYuP9M4McOSmINXZYEZ46vzwfPAuv2tkpOuy+pXEoqUYalLyD6FQ9aLhXa2+DyiQA6I4kqZTPIqk7oCG1mRCx1HBld28OR189rISZzjggJQj0tKbWdwhgUATq8lafmwU8jTFTHD4rfQ6U8ZFrEkFJph6XGQ0R81nBCsmAuk7HmM6HScqCn8uiFGHQvN2PJewOeVKTFnluAWYAFL6ggnvO09BbhtRNyY5NWi9CXpkt0uIn6pe5phGZrdJw3WSuBqK6AslCPYgNvaxRV5SJdQCgKW4XJeLH4loYieCY5O6aSQQSuiWDBn6UUH5r2dwmsgBPaF2VnQ+88R6m4AwJP2WktZcndUY2YOIwHLF5kUsNBsMRXd2jukQad04ncmY5Ccs4NpEzqERhkFDxaNjieTa4TFY6zHYr3fAs3vmBIius1As0UWsKSKcK3NdGVSPCzwQ5cEJtVIjrcxmVf5dQpRDcsonZ9VtQYzhCJB/Vg+PdAKt1nYD2c3HH1kP8pyg7pKUphhOdRijTxh2uvys+WPUG+2lAHGnETualpAu2Z2tJHgRNfXBYAPUw4SutCK6jKmDh+JmcNIsL3zZLf4OUh7aIbFJgw3PfQ/0iFUNhbIT44tQ0Lx6zpE0PeWaqpGm4QAU6uARVg87og5YPH7jgQcU9IkYxsHLGBJFeE6hVJUDgKAkeV5KMjOgs3lja2lzq9TiLrcDnYJmosE6VcokwcXothiRG+fB9taAHDkY12EXgwrswSKbl02wCYIdJMYsNSV5kDHAb1OD1qCHYX9SkIR680Z7jWiFto180UjCZ51vAc5cKIkuKU5BcFnohhUmI1Bhdnw+nhsO5YhOpbqKeSy/kMyzfvgx+TvkeembJc0xeD3eQsqC1HB7TC9kEXW6LtJPXkOtPQGjh1RSkiGJYIPSxfLsDCUEq4kJHqwJD9g0es4nCGkpDcdalf/AELAwjs60SiUhEodwhDHBHUIUfQ6DvNGkXLAx3tbgWzyf5RwveJUZxF64jcXxl1vVoPJoEdtCckyhZSF/EtC6dTSnEJOEwKWL085wAsrxkJYQzMs1BU6SR1fiUYqC8XwHUwFw79Fvm+2FuDwOqD+I3J9fwlY9H4BS5DwlrY0D+a0XQCV55tRVWAGz8c4402nl5ogvC7ROTsga+txEQkCwAIWhgLkMiwpEqvNHk48TTYdaouyZRiEIMHa1Yo+tw9Zeg65LcJ034rE17LPG08Mqt7b1QTeQv6PYq5HDMJEUrgiH1VBykIhLpb+JaGoLYiZc3CJh2GluUK3BA+PkZQrCzgbpgiBjEg/yrAAwBlCgP3F4QzRseizgAnfI79/fDdgbyMu3TVnpHa/tEIfJPD2g5aEKr3N5AoNP4NxawoDjilkERSQte05SUp3BnNGab9YwJIqgjUsXjdw6ivye4JLKJE4cwQ5WG492ok+tzfK1kEIGZbeTrLamFlsA9eyh5Rnhp2j6X6GY97ocuQY9TjZ5UAPR17bEvTgjGHBGZaj5DIFJ7gJwmRs0ZWXEtAllCa2/CnG366+myeZqULOioumVAdu2A88WPyZMZQE2F+f6FL/HUwVk64gl827yOWwuZJDbKaj0/md/ANLuaQkxKPYLWQqNPwMTonXSNDPPC6sLo4Kbgsyx4MFYAFL6gguCZ34EnBZSZdLxYSU7NLwslyU5Zng9PjUf1FySMDi7CHZmQvN35Dra85IiouiOUsvim+/6SRfzBG5TlTkmwM3TGXAMkgSNgcQUBISDi79wDMhXqjw9pidHHxnVOmIGSGF5/tdhqW2JAcV+Sa4vXzm+LEMPj3w9R95Xsp2JSHow3cKtdlcKEUPjL4+AJym7cHTasln/8ujHbG5j/uZx4XVsGTo8YQFLKkiuCR0eB25HDqXRPUpgOM4zB5OMhKb1ZaFhAyLz04OsjPdW8j1oxdqtn/ROH8i6Uo45iAntfGF7tCNUniCGz+IdFQcarWK7pMAAtK3VmcYG22e99Ow1CVhT9MDKrztFDIsZw8KCuLsHYCrFwCXcQfeSHAcJ+quPs+UshDHESdkyoj5qduXRBBhnlCH1YUaql8pGKxpVmnS4AKYs3Rot7lQH2loqhx+xxSqYQmY1iwKbjPHgwVgAUvqoH4hrfvJCenQJ+Tv4Ykvn8hxpqBj+Uyt8Fb4f4odR1GOTtT0CPqVUckLWOaNLiNfcpDAYFhOmDEDKQxYyvPMKM8zwccDexv9XCz9ZgnRQCbX/+BibwfcdpBV3ODk7XCKmSLU8btBApaJJUErTfpe5lcDWUGZtAxmlrBo2HQwBi1ZqpjyA6JdGTqXzOjqT9BxH8ElIZtTClg0LtWaDHpMF4wEPz8cgwBbHyVryzIsDFWMmE/cbpt3AfvfBU4KJ/gk6D3koAfLrxu61LXUDZ4BvrAWRb5OvGS8D3qfm3RuJLHjKcdowDmjy9HBk4ClKssWuIHPl/JMBZ3GuvuUX1lIJxxIvG6prdk/w0J1GnlVgW2W/ZwiixHDSi3oFtxuje6gUpq/B0s/4ixhoOdXDV3o6QuTJUxHiocCt38D/OCVVO+J9ugjZFhsLsnlNgGfQdowEFvAEiq6Dcjaii63LGBhKMFSAky5ivz+n58RG+Xi4SlP0dUU56CuJAceH4/fvrETPp/C+qkxBx0LVsHLcxiuE0atj1qYdEHX+ZOq0METl9RsV1fgjdZm0prI6VOWqQirYwljHBfQ1twPphHHyqXTBsOuIwFLgAUA0O/0KxT6HfT6eHwei8VAqsgpBrKyo2+XadD/yS1NWvf6yByhIRq3NPtDF4+fH+5Qfhym+JeEwnUedrMMC0MtZ9wCgCOtgEDKy0GUey+aAIOOw5s7TuEvH+5XfL89hjH4m/cS6Yok6lco35lQhUVnTCR/2IMO9vQEVzA46U7ClPHVNGDx6xTSS7M/bH00fetfbx5YHiz+3HLOCNzyndPJH44gEWo/zbAAwFkjSZZlYyaVhfortO3X2ipe1WV3wcfDL2DR/rs5cVAhsrP06IhFxyIcU9xuJ9xeEuyIbc1eD9B9kvyuMGCxu+1Y/fVqPLv72dhEwBoRU8CyatUq1NXVwWw2Y+bMmdiyZUvEbZ988knMmTMHRUVFKCoqwvz580O2v/baa8FxXMDPwoXJP9klndIRwOhF0t8pLgdRzh5VhhXfIyf9x9cdwur1hxTdr77Zisc8l2Cb5Wxg+LeB2jMTuZth0ek4fGeG4PtiDzrYp8GKfIIgvK1v6YXTI7St6qRsyqkOEsgEdDd1qs+wHO46jN9s+A2O9RyLb4fTAI52mfl7FgH9rqXZnzkjyUlyY33/Dlhaevrw6YHW2Bxdk0WeMGKAGq1B8mAZok9cScho0GF6HWlmUN0EIWRYnH1SGUtcBPU2koy+3gjkVih6uG5nN1btWIVHtz8KLoVt0KoDlldeeQXLli3D3Xffje3bt2Py5MlYsGABWlpawm6/bt06XHXVVfjkk0+wefNm1NTU4LzzzsPJkycDtlu4cCEaGxvFn5deeim2/yjTmHUrueT0QN1Zqd0XPy6bXoNfnkf0J398bx9WfnwgamRd32KFF3p8MulB4JrXU5bFQA5ZncLeQXQrlPaD5DLJgyX9GVSYjcKcLLi9POqbhVWTnznVkZYuAMDYqnzpTqJATvkq7rX61/Dfw//Fc7ufi3eXUw/tqAvOsHT03wzLrOEl0Os4HG6z4USnPfodMoytRzuwZM0WnLFiLRav2YIzHliL3/9nt+iSnVbkVZLL3ibxqjarC1nwoBJCFjdB/kjUR0p1xxgNWFzEnddk0MGgF073on5lsOKOVIeHvC/ZhtSW/FQHLA8//DBuuOEGLF26FOPGjcPq1auRk5ODNWvWhN3+hRdewE9+8hNMmTIFY8aMwVNPPQWfz4e1a9cGbGcymVBZWSn+FBUVxfYfZRq1s4HzHwYufSqpVvFKuPVbI/GrBcR1d+XH9bjnv3tkByMebCGdLyMFR9eUQTuweG/gqrx5N7lM4RRZjuNEAzlRx+IX2Pk8LuQY9RhS7DfgMIaSkNVNgqFd7bvi2+F0wG8SuIijC+g5QX5PwSiLRJNvzsLkweRz0t+yLIdarbjm6S1Yf6AVPh4ozTXC6vTgmU1HceFfPwsUpKcDYoalUbyq3eZEHdcEPXykOyq3PCFPTQOWTYfa1AmwhWOKUxgAG15wq1wvmZEBi8vlwrZt2zB/vtRnr9PpMH/+fGzevFnRY9jtdrjdbhQXB5qJrVu3DuXl5Rg9ejRuvvlmtLdnkNgsHjgOOP06yd46zbjlnBG46wLivPvMpqNYvGaLmA71h+d5HBAyBnQyccow/P/2zjs8inL745/ZZDe9QHogJAFC7wFCECnSBRFBBEQBkYsiFkSQi15A0fsDFbGiiBcEOzZQQUB6772XkAQCKSQhlfSd3x+TXTawKZtssrvx/TxPHmB3duYMb3bmzDnfc44GHIo7CWcbXOx1DksNjAooC10/loPRxU9NBikhNUU09XdDpSoOu2q1lRpSllOgXGAupl4k765yTJtD32TR4EamW0uPBlbn6JuLbsVpoZ2Xbpazpe2QX6jlpR+PkVNQROfQumyb3pODr/Xhm6c708zfjeSsPEZ+sd+6Srp1U6cNIiyp2fk0loqzBD5Nqq24oG19D0K9XcjILWTR3xcr/sHiCEt+vs5hMdLl1oTrye1CJcrnrLbspHiTHJbk5GSKiorw8yuZ9/Lz8yMhIaGUT5Vk5syZBAYGlnB6BgwYwNdff82WLVt455132LFjBwMHDqSoyHhr6ry8PDIyMkr8CKqPCd1CWfJEB5w1duyNSmHIp7s5e1d7+eSsfNJzCpAkpWOuxXEpjrLohLe56XeU8X6WGX2go29z5fuz7lQ86bcLlItdcbdbNYU08zdIB2UlKv0fJDtwr3hlk+4CUygXcj71vPmMtwS6CEteOmiLrwkJp5Q//S3TFbomeKC4c/PGM4lcTMwsZ2vb4P2/L3D6egZ1nNV8PKo9od4uqFQS94f58NOzkXRpWJesvEKeWnHIejr9GomwJGcZOCze1Tf7zd5OxbyHlQesr/fFVHwYYnGEJStbuQ7UNZxyXomqQ5uMsFSVBQsW8OOPP7J69WocHe+ICkeNGsWQIUNo3bo1Q4cOZe3atRw6dIjt27cb3c/8+fPx8PDQ/wQF2Va3PltkQKsAVj93H8FezsTdymHY53v448QdEdqvR5XwfIiXC45qu9J2U3Po0kI64W3iWeVP9/p3boAWIjy4Ds383cgr1PLzkeKnneILjFoqpHmA252NU4sFz55Bd2YOVQDdBQbgdLKNp4V0c7fgzuytRJ3D0rrm7akh2gV50reFH0VamTf+OGPR6gxzcDkpky92XgHgneFt8Pco2ezP3VHNiqc606upD3mFWiauPExsSraxXdUshhqW4jVIycqjsar4+udTvSnJ+8N8GNwmAK0Mr685TVFFSpyLrycp6UrUu5GPy533KiHi1z0A2ZTD4u3tjZ2dHYmJiSVeT0xMxN/fv8zPLly4kAULFvD333/Tpk2bMrdt2LAh3t7eXL582ej7s2bNIj09Xf9z7do1U05DUEma+rvxx5Ru9GjiQ26Blhd/OMb8v85xOCaVhRuV8ud/3d/QwlYWoxPe6lJCusFsFk4HgaJjeTJS0aN8d+Cq0mOheNq1F5klBbfJxWFgE3UatcphsVMrOgG4o2NJ0K1n7Y2wAMwZ3AKNvYq9USmsP12xKLa18t0BJcLZp7kv/Voav184qu349PEOtKrnTmp2PuO/OkTa7XtT0DWKrpKmKF8R8nNXSqgaIyw6Zg9ugauDPSeupbFs95XyP1CcErqVqTh8JdL0KcUPQV6NK3x8XYrZphwWjUZDeHh4CcGsTkAbGRlZ6ufeffdd3nrrLTZs2EDHjh3LPU5cXBwpKSkEBAQYfd/BwQF3d/cSP4KawcNZzfLxnZjcsxEAX+y8wsil+ynUygxuE8DozlYS7XK5O8JiHfoVHUPb1cPVwZ7o5Gz2RCVT6Kr8rgdIKTT1N4iwJF9S/jTRYblt0OTK5h0WKDkstKgQks4p/67FKSFQmshN7qF8195ee5acfBuZ4HwXOflF/HpEicI+0aVs8biLgz3Lx3einqcT0cnZvPDDsYpFFaoLe4c7EdvitFBqZi4NpeIUkU/1Oyx+7o78Z1BzAN7beKF8YXJxhCUtq9hh0aXp87LulGd7Narw8W02JTRt2jS+/PJLVq5cyblz55g8eTLZ2dk89dRTAIwdO5ZZs2bpt3/nnXeYPXs2y5cvJyQkhISEBBISEsjKUkJVWVlZzJgxg/379xMTE8OWLVt4+OGHady4Mf379zfTaQrMiZ1KYuaAZnz6eHuc1HYUaWWCvZyZP6y1RWv0S6CPsBRrWKzMYXFxsGd4B2Xmyld7YkhXK3qF5s4ZuDsalIPrIyxhJu3fMMISkxFDRr6N67z0DsstSLmk6Ho0buAZYkmraoTJPRtRz9OJG+m5LN1ZgadrK2TtyRtk5BZSv44T3YvFxGXh6+bI/8Z1xEltx65Lyby3seINLKsFt0Dlz2LhrV1WHE5SPlqVptpKmu9mZKcg+rbwo6BIZuqPx8ktKMN5LY6wZBZrWBrpIiy6FLOzt0mpcZt1WEaOHMnChQuZM2cO7dq14/jx42zYsEEvxL169Srx8XfESZ9//jn5+fk8+uijBAQE6H8WLlwIgJ2dHSdPnmTIkCE0adKEp59+mvDwcHbt2oWDwz9nbootMrhNIKundGXCfaF8Nb4Tbo4W6rtiDBddL5YUpdImqVjDYkUphCcjQ1BJsPV8EvtTlHx+M+e7xJVVTAnZSYqe6EzymaoZa2kMp5snGKT3LDTZvCZxVNvx74HNAFiyI4qE9FwLW2Q6unTQ4xEN7lTAlUPzAHfefVSRDyzZEcXakzfK+UQ1otexKPe2ureVHkAFnqEmacuqgiRJLBjWGh83By4lZfHmn2V8p4sdFklbgNpOIljXJkHXi8qEdBDYsMMC8PzzzxMbG0teXh4HDhwgIiJC/9727dtZsWKF/t8xMTHIsnzPzxtvvAGAk5MTGzduJCkpifz8fGJiYli6dOk9lUgC66SZvztzHmpBQ2uoDDJE3zwuWVHF52cpX2ITv6gA8VnxHE08amYDlbyyLrV2+JZyQQlWG1RGFOTcKWk2NSVULJJr6a1ElM6k2LjDYtiLJeGk8vdang4yZHCbAMKD65BTUGT5aIOJnLmRzvFraajtJEaEm5YyfqhtIM90V3RxM34+yfkEC0UKDRyWgiIt/vnFFYc1oF8xxMvVgfdHtEWS4IeD1/jpUCn6Tbs7VYchXi53msYlV81hcba3obJmgcBm0OWcs5PvpIN8mlXqaWjq9qmM2zCOC6nmv1G81LsJzfzduCEr9vrKBv0nUqIAWblZ686nAhRpi/S9Vzr7dwbg5M2TZrPZIhhqWHQC6lpcIXQ3kiQxu7gf0q9H4zgVZ2XN1crgzxNKVKJvCz983EyPmr86oBn3h3mTU1DEpK+PWEaEa1DafMtAcKv2b1bjpnRv4sPLfZQHmP/8ftp4qXNxhEVD4V2C22KHxfsfFGERCKwewz4sev1K5Z7I47OUC+6u67vMYVkJNPYqFj3WjpsqJSLklmcw4kKXDvIKM6kxlaF+pUtAFwCOJh2lSGubgk3gToQl47pBSuif47CAUub8SHtF9/TW2rM2U+a85ZxSVdq/lMqg8rBTSXw8qj1BdZ24mnrbMiJcg9LmlOx8fUmzqgYEt8Z4vldjejfzJb9Qy7++PnxvmtBF0cT5SbdK9sWqZErIJhvHCQQ2gy4llJUIR4vn6VRScKtrc78/fr85LLuHFoHuvD5KaaRofztRqYKBSlcI6RwWCYkOfh1wVbuSnpfOudRzZrO5xtE5LEe+guwkkFTg29zk3SRmJ9Lrp158fPRjMxtYM7w6oCmOahUHY1Jtosz5asptLiVlYaeS6Nmk8u3r67ho+OKJjjiqVey6lMxCE6bImwV3neg2npTMPIMut5ZxWFQqiUUj29HIx4X49FwmrDhUcoBk8by0ECnxToRFliuvYbHFsmaBwGbQiW61hcrMGac60MT0qrP8onwKtMoMj2OJx8gtrB7BY3iLpkq3W1l7p6NmFSuEnNXOqFVqIgIUjdme63vMZm+NE9ZfGXJYLCKmyUDQmP60dzTpKMk5yXx//nsKikyYzWIlBHg4Mam7onuav/5c2ZUiVsDm4uhKp5A6eDhXTZTfItCddx9tCyhT5NedjC/nE2bEMMKSeA1PKRstUqU0cebCw0lptOftquFsfAbPfXf0zgT4uorup4GUSGNd07jsm5CXAUhQx7QBsCIlJBBUJxoXCL4PXP2hz5vw0kmTb/xwJ7oCkK/N5/jN42Y00gCV6s7MkoziaohKVgjd3ZWya2BXAPbe2Ft1Oy2FXwt46QTMSYHXbsCo7yq1m8x8pQoruyCbI0lHzGlhjfFsj4b4uTtwLTWHZbujLW1OmWw5rzgsfZqbp4hiSNtAJhWLcKf/fIIjsTXUvl+nYclKJD9OEeCnaQJAbdkbeFBdZ5aN64ST2o6dF2/yr6+PkFtQRKraH60s4Srl0tC5uCeTLrri2QDUjqXv1AjCYREIqpvx62D6Beg2FRwr11wwO79ka/D9N6onLQTcmRWUEaeUYusFcpVLCd3tsJy4eYKs/KxSP2cTSJLijFay34+hA7ozbqe5rKpRnDX2+jLnjzZfslzlTDlk5BZw4IrSGba3mRwWgFf7N6VHEx9yCoqYsOIQFxJqYM6Si4+ShpS1RMQsASDRu/RmqTVJ2yBPlhX3rNl58Sbjlh9k3blUbqDo+JyziiuJdCnmSkSFhMMiMAu3C24zbv04lpxYYmlTrA8zNLEzvMEBHIg/UOV9loqHIqgk/brSjbLgtpImqmNaYypdvllXgljfrT7B7sEUyUUcSKhG+20AQ4fNVh0WUDol92nuS36RlpdXnSC/UGtpk+5h18VkCrUyDX1cCPV2Kf8DFcTeTsXnT3SgQwNP0nMKeHLZAa6l3i7/g1VBZadv0d8g7xJFskRq22eq95gm0LWxN18/3RlXB3sORKcye81pYrXFTmJqcbPBSupXQDgsAjNx/OZxjiYd5cuTX5Zoxy4wDzqHxV2jRGjOpJwhPa+aSkrdix2WjOt30kF1G+p7KlQUY4PKdFGWfTf2Vd1OG8bQAY3NiCU2I9aC1lQeSZKYP6wNdV00nIvP4P1N1tebxdzpIEOcNUr7/qZ+biRl5vHEsgPczMwz+3FKoEsLAeu1EfiEWHbq+910CqnLz89GMrhNABo7FbHy3Q6L6TOEdAiHRWAWdC3X87X57Llhw6JKK0X3RB7sHkyoRygyMocSDlXPwXQOS3ocXC/WV1RCd2MoutWhc1hsWnhrBu5OidlylMXHzYH/DlVK9b/YcYX/7bKetv1arczOi0pPoZ5Ny2/FXxk8nTV8/XRnguo6EZtym7HLD5KeU41CagOH5fPCITSoa9kSX2M0D3Dn08c7cPD13nTt1El58VaxzilFV3UoHBaBhcjIu5O/3n5tu8XsqK3onshd1C5EBig56+roxwLcSQllXIfTvyl/r0Rlky7SZnhx6ezfGXuVPXFZcVxJt54bW02jW89QD6VKYkfcDkuaU2UGtg5gah/FqX173TlW7Im2iv4s5xMySc7Kw1ljR8fgutV2HD93R76ZEIG3qwPn4jN4esUhbucXlv/BylD8/dxe1JYUt2Y4qu2q5zhmwNNZQ0hYcd+p1CuQl3kn0uJl2kOQLMtGo7aWQDgsNo7hULsdcTso1FbTl/UfSnaBIrp1VbvSq0EvQHEMq6UJmy7CknBamX1kp4HmD5m8G2NPQ85qZ31589arW6tuq42ic1geDH0QgCOJR/SVQ7bKS73DeK54xMMbf55lwopDRCdnl/Op6mXnpZsARDb0QmNfvbeZEG8Xvp7QGXdHew7H3uKZb45UT7l3xLPEBD/KfwqfooGX9UVX7qG4tJnUaLiyXWnxUCcUPOqbtJt8bT5aWdFIicZxgiphGGFJz0vnWNIxC1pT+zCMsIT7heOmcSM1N5UTN0+Y/2C6C0lx3xca9zVpoqqO0uZ+PBD0AADbrm6rvI02ji4l1MKrBQ09GlKoLbT5KIskSczo35RX+jZBbSex7cJN+i7awail+/h8exT7olJIyapmfcdd7Cp2WO4P866R47UIdGfFhM44a5Tpzs9/f4yCIjMLkb0a8XvQv4mTfe8ME7Rm6oQof+akwsmflL83GWByMYJOxA8iwiKoIun5igBUQvklFGkh86KPsGhcUavU9KjfA6imKIWzF9gb9EdoPbxSuyktfPtAgweQkDiZfJKk20nGPlrr0Tmgbho3+gb3BWBTzCZLmmQWJEnihd5hbJzanZ5NfSjUyuy/kso7G84z+sv9hL+9ma7zt/DiD8f44eBVMnKrT+txO7+QQ9FKf5TuTapHv2KMDg3q8L9xHXGwV7H5XCKv/HTC7C38Y1OV60GIGaueqg0HV31lE+fXKn826WfybnQPQGqVGntVzUymLg3hsNg4ughL5wBlyN22a9usIoddW9A9kbuqlfbWDzRQohRbr201//+zJN1pAa52Ubq5VgJ9SuiuplbeTt608WkD/HMdW8P11Dkse27sqTUVdg19XFnxVGd2zOjJvIdb0q+Fn14ceiM9lz9O3GDWb6fo/N/NTP/5BDHVkDo6EJ1KfpGWep5OZi1nrghdG3nz+RMdsFdJ/HHiBq+vPmXW72lsivJ7Yo2CW6PoOtrKWtC4Ks00TcRaBLcgHBabR6dhGRgyEI1Kw7XMa5xPPW9hq2oPhhoWgPsC79P/P19Ou2z+A+p0LM0GVar1PJQ9Cl7ncG25uqVy9tkwsiyTWaDoVVzVrjSp04QGbg3IK8pj53XbrRYyRrCXC2MjQ1g6tiM7X+3FmTf78/3ECKb2CaOJnyu5BVp+ORJH3w92MH/9OTLNGHHZeVFJB3Vv4oNkhl5IpvJAMz8+GtUelQQ/HrrG2+vOmc1p0TkswbagYYE7OhaARr3A3vRp2cJhEZgNXU8Qfxd/egb1BOCPqD8saFHtQq9h0ShPis5qZyIDlWqhakkLtRyqdNWMfK7SuzBWJaRDp2M5GH+whGD7n0BeUZ5elO6qcUWSJPoEK0MnN8durvL+/4z6k/6/9OfkzZNV3pe5cXGwp2tjb6b2acLGqd35dXIkPZr4UFAk88WOKwz8aBdHYlPNciy9w1JD+hVjDGoTwDvDlWjist3RfLD5UpX3mZ1XSHKxFii4rg2khEA/BBFQ9CuVwFoqhEA4LDaP7qbjrnHn4cYPA/BX9F/6gX2CqnF3hAXuRCk2xGwwf1qo00SYcRkC21d6F8b6sOgI8QhRxKZyIRuiN1T6GBXl5u2bLD25tPqa7ZmAYdM4F7Vyw9GlhXbG7azyYMv10eu5kX2DD458UKX9VDeSJBEeXJcVT3Vi+fiO1K/jRNytHEYs2cdHmy+hrYLu43JSFlE3s1HbSXRtbDmHBWBExyDeHKJMaP94yyWW7oyq0v500RVPZ3WVBznWGIYRlsZ9K7ULEWERmA3djcDDwYPIwEjqOtYlNTf1H9/R1FwYVgnp6BPcB0c7Ry6nXa6eaqEqUt4T0YgmIwBYcWZFtZfBrzyzkk+OfcI7B9+p1uNUBJ1+xUXtgkpSLn0tvVoS4BJATmFOlXU9OiHz4cTDVvl7cTeSJPFAMz/Wv3Q/j7Svh1aGDzZf5Jlvj5CVV7nfi/WnlAnK3Rp74+Fk+Zv6uK4hvDqgKQD/99d5vtlf+c7GV4sFt8FeNhJdAajfSRHyh/UDt8p1HBYOi8AsFGgL9Dcnd407apVa31/i98u/W9K0WoOxCIu7xp1+IYra/tdLv1rErrIo7wIzLGwYdRzqcC3zGn/H/F2ttlzPug7A+pj1JOckV+uxykPnfBqupSRJPNRI6XXz08WfqrT/mzk39X9ffmp5lfZVk7g5qvlgZDvee7QNGnsVm84mMuyzPcSmmC7I/et0AqA0tLMWnuvZmCm9lD41s9ec5rsDlXNa9PoVWxHcgjKH7OUzMGJlpXehTzFbeDI1CIfFpjFseOWmcQNgSKMhgFIFYg1heFvH8KnckOFhSsnxxpiNVjcBuSzRLSipoidaPAHAl6e+1DeFqg50TkqhtpCfLlTNIagqhiXNhoxoMgKVpOJQwiGi0iqXNsgvyic1944GZOu1rVxJs62OwiM6BrFqUhd83Ry4mJjFw4v3sOdyxZ3M6ORszsVnYK+S6NfC/PODqsL0fk0Z3zUEgNdXn2b2mtMmD4zcdkGJoIX5upazpZXh4l1pAT+Ufz2pSYTDYsPoHBI3tRt2KqVNdLO6zQirE0a+Np9fLv5iSfNqBYZ9WAxp79uehh4NySnM4a/ovyxhWqmUJbrVMarZKFzULlxOu8yOa9XXOM0w6vDThZ/IL8qvtmOVR2nOp7+Lv76/TmWdKt15alQaegUpHZH/d+p/lTXVYrRvUIc/X+hG2yBP0m4XMHb5Qb7ZF1Ohz64/raSDIht54emsqUYrTUeSJOY+1ILp/ZogSfDN/lhGLNnL0au3KvT549fS2H8lFXuVxPBw0zrF2joiJWRDXM+6XmUxXnWhF9w6uOtfkySJsS3GAsoF0/CpT2AaBdoCcouUtTdMI4Dy/6yLsvxy8Rer6n1TkQuMu8adUU1HAUqUpTrsl2VZH2FxsnciJTeFjTEbzX6ciqKLSN7tfAL6/4s/ov6oVE8WnX7Fx9mHZ9o8A8DaK2u5dKvq1Sk1jZ+7I6smdWFYh3oUaWVm/36GeX+eLbcJ2/pTSjroQStKBxkiSRLPPxDG/8Z2xM3BnhNx6Qz7bC9TvjvKrks3yzw/nWB3SLtAAj0tf+OuSYTDYiPkFuYyZfMURq4daZW9TXRN49w17iVeH9JoCM3rNierIIvPjn9mCdNqBYY3LmMVNw81eggHOwfOpZ6zmknZhoPKypv78USLJ3Cwc+BU8ikOJhw0uy2ZBZnkFSlloE+2eBJQhL7VmYIqC120zE3tds97XQK7EOQWRFZBFmuvrDV534m3EwHwc/ajpXdL+gb3RUbm46MfV81oC+GotuP9EW2Z0V8RrC7fE80z3xwmuxQx7oWETE5dT8dOJdG/pX9NmmoyvZv7sfmVHowIr48kwbpT8Ty57CBd5m9h8rdHWLIjir1RyfreNDHJ2awv1uZM6t6wrF3XSkRKyEa4lnmN9Px0rqRfYfS60aw4bbmLrTF0bfkNIywAKknF9I7TAeXp39Zy6dcyr1lcoAl3nsgd7RxRq+6teKjjWIfHmj4GwKfHPrWKKIvhoLLynoi8nbz1UaIvT31pdluSbytr6KZ2Y2yLsbioXbh466LFmtbpm8YZibCoJJU+yrLs1DKTU1c3byspIV9nXwBeaP8CdpId2+O22+x8L0mSmNKrMZ8+3h6NvYrN55J47It9JKSXjDhrtTL/WXMKgH4t/KjrYl3pIGP4uTvy3oi2rH2hG090aYCns5qbmXmsP53AgvXnefzLA7R58286/3czjy7ZiyxDr6Y+NPN3L3/n5XAl7QpD1wytlGNsCUSExUYIqxPGb0N+o1dQLwq1hbx/5H0mbZpEYnaipU0DSo+wgNKqv2dQT4rkIt4/8n5Nm1Zp0vPSGf7HcEb8OcLiomHdE/ndmgdDnm71NE72TpxJOWMV7e5NHVQ2vuV47CV7DsQfMHvDM52uw9vZGw8HD32U5bPjn1XPtOtyuHvMwt2MaDoCbydvbmTfMLn6yzAlBBDqEcrQxkMB+ODIB1bhzFaWwW0C+XFSF7xcNJy5kcGQT3ez10CM+/ORaxyKuYWzxo7/DG5hQUtNp2WgB28Pbc3B1/rw/b8i+PfAZjzY2p96nk7IMiRl5pGclY8kwXO9GpvlmBtjNxKVHsV/9/+XW7kV09BYEuGw2BB1HOvwUa+PmBs5Fyd7Jw7EH2DYH8P4I+oPi1+EDJvGGWNa+DTsJXt2xu20mb4sUWlR5BTmkJyTzJITSyxqi74M1sgTuQ4vJy8eb/Y4AIuPL7Z4BE6XDtKoNBUaVBbgGsDgRoMB+OLkF2a1Reew+DgpN/EnWzyJm8aNy2mXLaJlMVaiboiTvZNef7L05FL9hboiGKaEdExuOxlHO0eOJR3j79jqLR+vbjo0qMOaKfcR5utKUmYeY5YdYM7vp/ls+2X+7y8lXT6tbxPq2ai+Q2Ovomsjb57t0YjPxoSz598PcOQ/fVj3Yjd++FcX1r1wP51C6prlWPFZijg5qyCLpSeXmmWf1YlwWGwMSZJ4tMmjrBq8ihZeLcjIz+D13a8zfsN4LqResJhdhk3jjBHqEapPWSw8vNAiT7WmEpcVp//7D+d/qHSZqTmoSIQFlCiFi9qFC7cuWLwyq7TBh2XxdKun9Y7tlljzpWt0KSFvJ6XjqbvGnXEtxgHw2YnPTHIIzEFZolsdw8OGU8+1Hsk5yfxw/ocK71sXYdGlhAD8XPyY0GoCAO8fft9qxfsVJaiuM78/fx+jOwchy/D1vlje3XCB9JwCWgS468uGawterg60DPQgspEXLQKrngrSEZ8dr//7jxd+5FrGNbPtuzoQfVhslFCPUL4d+C0vdXgJJ3snjiYdZeTakSw4uKBET5SaorwICyhPeW4aNy7eumgTM4biMu84LEVyEe8cfMdikazyUgg6PB09ea6tMvtn4eGFFr0AVUYgF+IRwlOtngLgvwf+a7YZQ3dHWEAR+tZ1rEtsRixz986t0bU11jjubtR2aia3nQwoURbd03B5GHNYAMa3Go+/iz/x2fGsOLOiElZbF84ae+YPa8PSJ8N5pH09Hg2vz/iuISwe0wF7O3E7qQg6h8XHyYdCbSEfHLXuUQ4iwmLDqO3UTGw9kT+G/kHf4L4UyUV8d+47Bq8ezNdnvq7Rpyi9hsWhdIfF09FTH+ZeeHihRSMWFeFapnKzHx42HLVKzb74ffxyyTJRi4rc4HQ80eIJOvp1JKcwh9d2v2axaFZFerAY45m2zxDiHsLNnJssOrzILLboHRbnOw6Li9qFhT0WYi/Zsz56fY3exPUOaBkRFoDBDQfT1qct2QXZvLn/zXKdKlmW7xHd6nCyd2Ja+DRAEfNGp0dX1nyrol9Lfz4Y2Y6FI9ryxpCWhHrbULt6C6KVtXoneHaX2agkFZtiN1V7x+mqIKqEagH+Lv4s6rmIL/p+QYh7CKm5qbx3+D0G/TaIr05/VSOTcHXH8NAYTwnpeLzZ47TxaUNGfgbPbHqGhOyEaretsugiLF0Cu/B8++cBmH9gPqdunqpxW0prGmcMlaTi7W5v46J24fjN43xy7JPqNs8olX0acrBzYE7kHEAZN7D60uoq25KSkwLcSQnp6OTfiVc7vwrAh0c/NGsaqiz0nW6NlDUbYqeyY95989CoNOy5voffo8oec5GRn6Hv12MYTdIxIGQAnfw7kVuUy3ObnxO9kf7BpOamkq/NR0KiW71uTGw9EYB5++fpnV5rQ0RYahFdA7vy28O/8UbkG/i7+JOUk8SiI4vo+3Nf3tj7BocSDlWbENNY4zhjqO3ULH5gMaEeoSTeTuSZTc9YRdmwMXQaliDXIJ5q+RS9G/SmQFvAy9tfrvEvtLHBh2VRz7Uer0e8DsCy08v47tx31WZbaVS0B4sxOvl30l9A39j3BtuubquSLcZSQjpGNR3Fo00eRStrmbFzBvvj91fpWBVB3+lWU/56NvRoyHPtlDTfuwffJSY9ptRtdekgDwcPHO0d73lfkiTe6/4e9VzrEZcVx0tbX9L3pxH8s7iRdQNQoo5qOzXPtnmW5nWbk56Xzpy9cyxeyGEM4bDUMtQqNcObDGfdI+uY13UejT0bc7vwNr9e+pUJGyfwwE8P8Pru11l7ZS2xGbFmc2B0otuyNCw6PB09+aLPF/g6+3Il/Qrj1o/Tf3msBV11EEB9t/pIksTb972td7RGrxvN6eTTNWZPeVUlxnio0UNMaTcFgAUHF5glUmEKVb24vNj+RYY2HopW1jJ9x3T2XK98Q7y7RbeGSJLE6xGv6x3SF7e+yPGk45U+VkXQ9WEpL8KiY1zLcbT1aUtmQSbPb32+1DL70vQrhng5efFZ789wU7tx/OZxpm+fTkFRgYlnILB1dPqVQJdAQHmYnH//fDQqDbuv77ZYZLYshMNSS9HYaXgk7BF+G/Iby/svZ1jYMFzVrqTkpvBH1B/M2jWLwasH0+2HbkzcOJFFRxZVSaCpTwmVUiV0NwGuAazov4J6rvW4mnmVsevHciblTKWPb26uZyqTfd3UbnonzFXjyuIHFhPiHkLi7UTGrR/HmstrasSe0mbPlMczbZ7RNyGbs3cOM3bMIC03zdzmGaWq+WZJkpgbOZeeQT3J1+bz/Nbn+euK6bOScgtz9Q6Ct/O9DguAvcqed7q/Q0RABDmFOUzaNKlKDlJZFGmL9P83FUnx6ez7sNeHBLgEEJsRy8vbX9Y7sYZUxGEBaOjZkI8e+AgHOwe2x21nxs4ZFGiF0/JPQqdfCXC9M76gkWcj/tPlP4DSwPHXi9YzAV6WZeGw1HYkSaKTfyfe7PomO0bu4Mt+XzKuxTjaeLfBwc6BzIJMDiQc4KvTX/H4X49zNuWsycfILczVh5UrEmHREeQexMoBK2no0ZDE24k8se4JlpxYQqHWeMvtmkSXDtJFV3QEuQfxw6Af9DfR2Xtm89/9/632J9TKRFhAWf9ZEbOY3HYydpIdG2I2MPzP4Vy8dbE6zCxBZUW3htir7FnUYxEDQgZQqC1k5q6ZLDu1zKRwtS4d5GDnUGZEw8HOgY97fUzXwK7kFObw/NbnWXN5jdlD47r0Hpi2nt5O3nza+1Oc7Z05lHCIgb8OZOWZlSVSOnqHxalshwWUtNtHvT5CrVKz5eoWXtj6gtC0/IO4ka1EtQNcSs5beiTsEX1xxFv732L1pdVWkR4q0BZQJCsFBKKs+R+Axk5Dl4AuTO80ne8Gfce+x/fxy0O/8GbXN2nh1YK0vDSe3vi0ye27ddEVlaQyOQLg5+LH1wO/pl9wPwrlQhYfX8yEjRMsLsbVCW7ru907DdVV48pHvT7S6wp+vPAjE/+eqL9ZVAd6DUsFNA93o5JUPNfuOb578DtC3ENIup3E+PXjOZJ4xNxmlsBcT0NqOzXvdH+H0c1GA4o49sVtL5KQnVChCihdas/bybuE82kMZ7Uznz7wqd5Bmr1nNpO3TC5R4l5VdGupUWnQ2JnWOr5JnSZ82vtTgt2DuZV3i4WHF/LUhqf0mqqKRlh03FfvPj7s9aFe1DvijxEciD9gkk0C20QXYdGlhAyZ0m4KQxoNoUguYs7eOby2+7VKDeI0J4a9kkSE5R+IWqWmad2mDAsbxrJ+y+jg24GsgiwmbJjAJ8c+qbAYz7Atv0oyfRk9HDxY2GMh8++fj6valWNJx3jsz8dqRPxYGoYRFmOoJBWT207mkwc+wVXtytGkozz252McSjhULfZUNsJiSEvvlnz74Le0921PZkEmk/6eVK2l5fqUUCVEt3ejklTM6jyL2V1mo1ap2X5tO31/6Uv7b9ozdM3QMkcR6G7mxgS3xlDbqVlw/wKeb/c8apWaPdf3MOavMWbrb1TRkubS6OTfiTUPr2Fe13l4OHhwKvmUXlNlqsMC0L1+d74f9L3izOYkMfHviby641WLPzQIqhedhsUwJaRDkiTeuu8tXurwEipJxdora5l/cH5Nm1gCncNkr7I3Ok+tphEOiwVx1biypO8S+gb3pVAuZOnJpfT/pT+Pr3ucF7a8wNora0vNcesHH5qQDrobSZIY3HAwPw3+ieZ1m3Mr7xbTtk2zWEdOfYTF1bjDoqNnUE9+GPQDYXXCSMlNYeLfE1l4aKHZO6eaWiVUGh4OHiztu5QOvh3I1+az7so6c5hnFF2VkLmehiRJ4rGmj/HNg98QVicMABmZqPQoXtj6AlO2TDGqwzLWg6U87FR2PNP2GX4d8iv+Lv6k5qbqR0rcyr3F2/vfZt2VdZUSretLmjUVE9waw15lzyNhj/D9g9/rNVWj143WT+o2bMtfEZrWbcqqwat4rMljSEisj1nPkDVDWHlmpVWkaAXmR5cSMhZhAeUhYWLriXzQU2kmtyV2i0V/F6ypBwsIh8XiONk7sajnIj7o+QHeTt6k5KZwKvkU2+O2M2vXLB787UFWnll5j9ivrMGHphLkHsQ3D36Dn7Ofoq+xUHi6rJTQ3YR4hPDdg9/xcKOH0cpaVp5dyfA/hnMlXZlMLcsyr+9+nbHrx7IhZgMF2gJO3TzFTxd+0m9THtn5VY+w6HC0d+TRJo8CsOv6rirvrzR0ww/NfYFp6dWS34b8xtEnj7L50c1MaDUBe5XSzn/o70P59NinJRxGw5SQqYR6hNI3uC+A3hn48tSXrLqwin/v+jdj1o0xOapWWQG1MRq4N+DbB79lYOhAVJJK/1Dh52KawwJKJGx25GxWDV5FB98O5BTmsPDwQsb8NabCXXYFtkFWfpY+YmgswmJIj/o98HDwILMgk1PJNd+DSoc1CW5BOCxWQ5/gPqx7ZB0rBqzg414f81zb56jrWJeE7AQWHl5I35/78t/9/2XL1S2k56WbXCFUHg52DvQK6gXAtmtV67+x+PhiRq8dzSO/P8LItSP55uw3+htGaciyXKIHS0Vwsnfi7W5v8+kDn+Lr7Mu1zGt8cFh5Mjlx8wR/RP3BsaRjzNgxg4jvInj8r8d5a/9bDF0zlFd3vFruHChdlYs5HBZQevYAnE89X209ZcwdYbkbtUqNn4sfL4e/zK9DfqVLQBfytfl8cfILBvw6gKUnl5Kel653WCqaErqbboHdANh9fTdF2iI2RivDEu0le06nnGbCxgmMWz+OPdf3VCjiUtGmcRXFw8GDd7u/y9pH1vJE8ycY0WQETeo0qfT+mns1Z8WAFczrOg83jRtnU87y3uH3zGKrwDrQRVfcNe7lOs52KjsiAyIBqq1yriJU9/XEVITDYkU4q50J9wunV4NeTG43mb8f/Zu5kXMJcQ8hsyCTHy/8yNRtU7n/x/tZdERpn26OCIuOBxo8ACgOS2Vby5+4eYIlJ5ZwOuU0l9MuczblLO8eepc+v/Rhzp457Luxz2iaKzknmbyiPFSSCn9Xf5OO2SOoB1/2+xKAndd3Ep8Vz6+XlNLAsDphuGncKNAW4Kp2pY1PG2Rk1ses59E/H2X02tGsOr/qHgfCsAy2MqJbY3g5edHSqyWg3IjLIjM/k8XHF/Nn1J+l9v8wRk0+ETX0aMjSvktZ1HMR9VzrkZqbyifHPqH3z73ZenUrULkIC0C4fziOdo4k3U7i54s/k5SThJvajb+G/cWopqNQq9QcTTrKs5uf5cHfHmTJiSVcSbtSamVFVTUspRHkFsTMzjOZEzmnUloyQyRJ4pGwR1jefzkAW69urVZRuaBm0emTAl2Np4PuRveAs/fGXrMc/0LqBf6M+pO9N/ZyJb3074oh1hZhKX/+vBEWL17Me++9R0JCAm3btuWTTz6hc+fOpW7/888/M3v2bGJiYggLC+Odd97hwQcf1L8vyzJz587lyy+/JC0tjfvuu4/PP/+csLCwyphXa3Cwc+DRJo8yLGwYu6/vZmfcTg4mHCQ6PVpfCmmKRqA8Ovp3xE3tRmpuKqeST9HOt53J+9CNS+/ToA8jm43kasZVvjv3HVfSr7D68mpWX16NvWRPkHsQjT0bE+4XTkuvlnohaoBLQKXEXQ09GtLZvzMHEw7y9dmv2RijPJHP7jKbJnWaEJcZR0PPhqhVas6nnud/p/7HlqtbOJ1ymtMpp3n7wNu08mpF54DOhPuFl3AEzRVhAbi//v2cSTnDruu7eCTskVK3e2v/W6yPXg8oUYV2vu3o7N+Zdr7tCHYPxs/Zj7yiPG4X3ia7IJus/CwupV0iJiMGMI/otiJIkkTf4L70CurFhpgNfHX6Ky7euqgXj5siRDXEwc6Bjv4d2X19Nx8d/QiA3sG9CXAN4PUurzOx9URWnFnBmstruJ51ncXHF7P4+GKC3YPpEtCFjn4daVa3Gb7OvjirnfXRMnOkhKqbZnWb0cG3A0eTjvLrxV+Z3G6ypU0SlIEsy+VWwsGdLrd3lzSXhs5hOZ18mlu5t6jjWKfSNsakx/Dk+idLpG19nHy4r959hPuF09anLVpZS1RaFAXaAlp4tSDILUjvZNmsw7Jq1SqmTZvGkiVLiIiI4MMPP6R///5cuHABX997L0579+5l9OjRzJ8/n8GDB/P9998zdOhQjh49SqtWrQB49913+fjjj1m5ciWhoaHMnj2b/v37c/bsWRwd7211/U9DJanoXr873et3B5QKjEMJh7iaeZVhYcPMdhy1Sk23+t1YH72erde2muywnE05y864nagkFS+Hv0wD9wZ0CejCiCYjOJx4mPXR69kUu4m0vDSi06OJTo9mU+ymEvsoT3BbFiOajuBgwkG+PfctoGgh2vm0Q5IkmtZtqt+uWd1mLOyxkJScFNZeWcvfMX9zMvmk3nlZfnp5if8TU8tgy6JbvW4sObGE/Tf2U6AtMOqcbbu6jfXR61FJKkLdQ4lKj+Jw4mEOJx6u8HEqelE0F/YqewY3HMyg0EGcTTnL71G/k1+UT+eA0h9kyqNbvW7svr5bn84ZGDJQ/56fix8zO8/kxQ4vsjl2M+ui13Ew/iCxGbHEZsSy6sIq/baeDp7Yq5RLXVVEtzXJyKYjOZp0lF8u/sLENhOtokJDUJLYjFhe3fkq51PP46J2wU3thqvGFTeNG4EugdR3q099t/oEuQXh7ejN5bTLQMUjLH4ufjT2bMzltMvsj9/PwNCB5X/ICIXaQl7b/Ro5hTkEugTirHYmLjOOmzk3WXN5TamNOCUkZJQojLU4+pJsYneaiIgIOnXqxKeffgqAVqslKCiIF154gX//+9/3bD9y5Eiys7NZu3at/rUuXbrQrl07lixZgizLBAYG8sorrzB9+nQA0tPT8fPzY8WKFYwaNapcmzIyMvDw8CA9PR13d/OlSP6JbIjZwIwdMwh2D2Zp36UmfXb+wflsv7adQQ0HseD+BUa30cpaErMTiU6P5kzKGY4kHSEqLQq1So2r2pUp7abQI6hHpWwvKCqg7y99SclVhu5N7zidcS3HVeizSbeT2HtjL0cSj3Di5gnS89K5XXCbAaEDeOu+typljzGKtEX0/KknaXlpfNDzA1p4tSjxfl5RHhM3TiQpJ4mnWj3FtPBpXM24yv74/RxMOMj51PNcz7qurxyQkHBRu+Csdqaeaz3a+7anW71udPLvZDabLUVsRiyDVw8GoI5DHbY+tlXveBgjuyCbfTf2cTjxMEcSjxCbEXtP5di08Gk81eqparXbHOQX5dP3l76k5qYyr+s8IgIiLG2SwIDLaZeZtWtWpYbcmnJdev/w+6w4s4IBIQN4Ofxlk48FyjDTpSeX4qZ247eHf8PfxZ+8ojyOJB5h/439HL95nDPJZ7BX2dPIsxF2kh3nUs+RV5SHRqWhkWcjpnaYStd6XSt1/PIw5f5tksOSn5+Ps7Mzv/zyC0OHDtW/Pm7cONLS0vj993unmjZo0IBp06YxdepU/Wtz585lzZo1nDhxgitXrtCoUSOOHTtGu3bt9Nv06NGDdu3a8dFHH92zz7y8PPLy7vQrycjIICgoSDgsZiArP4v7V91f6VI6CYnVD6+mkWcjM1tWMT4++jFfnvoSe8mezSM24+XkZRE7ymLmzpn8FV12u/tg92B+eegXo8P0irRFpOWl4WTvhKO9Y5W1E9aKLMs8+NuDxGXFMbLpSH37clM+n1WQRVxmHJfTLpORn8GQRkNsJsqi+10WWC9tvNsoDzSScu3Mys8iPT+d61nXicuMIy4zjmuZ17iVd4tCbSHuGneW9V9W4evjvhv7mLRpkllsnX//fAY3HGz0vSJtESpJpU9tFWgLSMlJwcfJBzuVnVmOXxqmOCwmpYSSk5MpKirCz69k+Z6fnx/nz583+pmEhASj2yckJOjf171W2jZ3M3/+fN58801TTBdUEFeNK2OajWHVhVX6cGBFkZB4tMmjFnNWAEY3G83OuJ10r9/dKp0VgMeaKg36jM2lASX8+vZ9bxt1VkCpILDWczMnkiQxofUEvjn7DWOaj6nU5900bjT3ak5zr+bVYGH1MqrZKDbGbCTxdqKlTRHchUpSMSBkAK9FvFbq99QcdPTrSAffDlWa+SYhMbiRkq4tjbudErVKjb+LacUPNUGlRLeWZtasWUybNk3/b12ERWAepneazvRO0y1tRqXwcfbhlyG/WNqMMgn3C2fHyB2WNsMmGNFkBCOajLC0GRbB19mXdcOqr8mgwPpR26lZOXClpc2wGkyKJXt7e2NnZ0diYkmPPzExEX9/496Yv79/mdvr/jRlnw4ODri7u5f4EQgEAoFAUHsxyWHRaDSEh4ezZcsW/WtarZYtW7YQGRlp9DORkZEltgfYtGmTfvvQ0FD8/f1LbJORkcGBAwdK3adAIBAIBIJ/FianhKZNm8a4cePo2LEjnTt35sMPPyQ7O5unnlKU92PHjqVevXrMn68MbXrppZfo0aMH77//PoMGDeLHH3/k8OHDLF2qVKBIksTUqVN5++23CQsL05c1BwYGlhD2CgQCgUAg+OdissMycuRIbt68yZw5c0hISKBdu3Zs2LBBL5q9evUqKtWdwE3Xrl35/vvv+c9//sNrr71GWFgYa9as0fdgAXj11VfJzs5m0qRJpKWl0a1bNzZs2CB6sAgEAoFAIAAq0YfFGhF9WAQCgUAgsD1MuX/XzgYOAoFAIBAIahXCYREIBAKBQGD1CIdFIBAIBAKB1SMcFoFAIBAIBFaPcFgEAoFAIBBYPcJhEQgEAoFAYPUIh0UgEAgEAoHVIxwWgUAgEAgEVo9wWAQCgUAgEFg9Jrfmt0Z0zXozMjIsbIlAIBAIBIKKortvV6Tpfq1wWDIzMwEICgqysCUCgUAgEAhMJTMzEw8PjzK3qRWzhLRaLTdu3MDNzQ1Jksy674yMDIKCgrh27VqtnVNU28+xtp8fiHOsDdT28wNxjrUBc5+fLMtkZmYSGBhYYnCyMWpFhEWlUlG/fv1qPYa7u3ut/OUzpLafY20/PxDnWBuo7ecH4hxrA+Y8v/IiKzqE6FYgEAgEAoHVIxwWgUAgEAgEVo9wWMrBwcGBuXPn4uDgYGlTqo3afo61/fxAnGNtoLafH4hzrA1Y8vxqhehWIBAIBAJB7UZEWAQCgUAgEFg9wmERCAQCgUBg9QiHRSAQCAQCgdUjHBaBQCAQCARWj3BYymHx4sWEhITg6OhIREQEBw8etLRJlWL+/Pl06tQJNzc3fH19GTp0KBcuXCixTc+ePZEkqcTPs88+ayGLTeeNN964x/5mzZrp38/NzWXKlCl4eXnh6urK8OHDSUxMtKDFphESEnLP+UmSxJQpUwDbXL+dO3fy0EMPERgYiCRJrFmzpsT7siwzZ84cAgICcHJyok+fPly6dKnENqmpqYwZMwZ3d3c8PT15+umnycrKqsGzKJuyzrGgoICZM2fSunVrXFxcCAwMZOzYsdy4caPEPoyt/YIFC2r4TIxT3hqOHz/+HtsHDBhQYhtbXkPA6PdSkiTee+89/TbWvIYVuT9U5Pp59epVBg0ahLOzM76+vsyYMYPCwkKz2SkcljJYtWoV06ZNY+7cuRw9epS2bdvSv39/kpKSLG2ayezYsYMpU6awf/9+Nm3aREFBAf369SM7O7vEdv/617+Ij4/X/7z77rsWsrhytGzZsoT9u3fv1r/38ssv8+eff/Lzzz+zY8cObty4wbBhwyxorWkcOnSoxLlt2rQJgBEjRui3sbX1y87Opm3btixevNjo+++++y4ff/wxS5Ys4cCBA7i4uNC/f39yc3P124wZM4YzZ86wadMm1q5dy86dO5k0aVJNnUK5lHWOt2/f5ujRo8yePZujR4/y22+/ceHCBYYMGXLPtvPmzSuxti+88EJNmF8u5a0hwIABA0rY/sMPP5R435bXEChxbvHx8SxfvhxJkhg+fHiJ7ax1DStyfyjv+llUVMSgQYPIz89n7969rFy5khUrVjBnzhzzGSoLSqVz587ylClT9P8uKiqSAwMD5fnz51vQKvOQlJQkA/KOHTv0r/Xo0UN+6aWXLGdUFZk7d67ctm1bo++lpaXJarVa/vnnn/WvnTt3Tgbkffv21ZCF5uWll16SGzVqJGu1WlmWbX/9AHn16tX6f2u1Wtnf319+77339K+lpaXJDg4O8g8//CDLsiyfPXtWBuRDhw7pt1m/fr0sSZJ8/fr1GrO9otx9jsY4ePCgDMixsbH614KDg+UPPvigeo0zA8bOb9y4cfLDDz9c6mdq4xo+/PDD8gMPPFDiNVtZQ1m+9/5QkevnX3/9JatUKjkhIUG/zeeffy67u7vLeXl5ZrFLRFhKIT8/nyNHjtCnTx/9ayqVij59+rBv3z4LWmYe0tPTAahbt26J17/77ju8vb1p1aoVs2bN4vbt25Ywr9JcunSJwMBAGjZsyJgxY7h69SoAR44coaCgoMR6NmvWjAYNGtjkeubn5/Ptt98yYcKEEgM/bX39DImOjiYhIaHEmnl4eBAREaFfs3379uHp6UnHjh312/Tp0weVSsWBAwdq3GZzkJ6ejiRJeHp6lnh9wYIFeHl50b59e9577z2zhtqrm+3bt+Pr60vTpk2ZPHkyKSkp+vdq2xomJiaybt06nn766Xves5U1vPv+UJHr5759+2jdujV+fn76bfr3709GRgZnzpwxi121YvhhdZCcnExRUVGJ/3wAPz8/zp8/byGrzINWq2Xq1Kncd999tGrVSv/6448/TnBwMIGBgZw8eZKZM2dy4cIFfvvtNwtaW3EiIiJYsWIFTZs2JT4+njfffJP777+f06dPk5CQgEajuecm4OfnR0JCgmUMrgJr1qwhLS2N8ePH61+z9fW7G926GPsO6t5LSEjA19e3xPv29vbUrVvXJtc1NzeXmTNnMnr06BKD5V588UU6dOhA3bp12bt3L7NmzSI+Pp5FixZZ0NqKMWDAAIYNG0ZoaChRUVG89tprDBw4kH379mFnZ1fr1nDlypW4ubndk262lTU0dn+oyPUzISHB6HdV9545EA7LP5ApU6Zw+vTpEvoOoETOuHXr1gQEBNC7d2+ioqJo1KhRTZtpMgMHDtT/vU2bNkRERBAcHMxPP/2Ek5OTBS0zP8uWLWPgwIEEBgbqX7P19funU1BQwGOPPYYsy3z++ecl3ps2bZr+723atEGj0fDMM88wf/58q28BP2rUKP3fW7duTZs2bWjUqBHbt2+nd+/eFrSseli+fDljxozB0dGxxOu2soal3R+sAZESKgVvb2/s7OzuUUEnJibi7+9vIauqzvPPP8/atWvZtm0b9evXL3PbiIgIAC5fvlwTppkdT09PmjRpwuXLl/H39yc/P5+0tLQS29jiesbGxrJ582YmTpxY5na2vn66dSnrO+jv73+PCL6wsJDU1FSbWledsxIbG8umTZtKRFeMERERQWFhITExMTVjoBlp2LAh3t7e+t/L2rKGALt27eLChQvlfjfBOtewtPtDRa6f/v7+Rr+ruvfMgXBYSkGj0RAeHs6WLVv0r2m1WrZs2UJkZKQFLascsizz/PPPs3r1arZu3UpoaGi5nzl+/DgAAQEB1Wxd9ZCVlUVUVBQBAQGEh4ejVqtLrOeFCxe4evWqza3nV199ha+vL4MGDSpzO1tfv9DQUPz9/UusWUZGBgcOHNCvWWRkJGlpaRw5ckS/zdatW9FqtXqHzdrROSuXLl1i8+bNeHl5lfuZ48ePo1Kp7kml2AJxcXGkpKTofy9rwxrqWLZsGeHh4bRt27bcba1pDcu7P1Tk+hkZGcmpU6dKOJ8657tFixZmM1RQCj/++KPs4OAgr1ixQj579qw8adIk2dPTs4QK2laYPHmy7OHhIW/fvl2Oj4/X/9y+fVuWZVm+fPmyPG/ePPnw4cNydHS0/Pvvv8sNGzaUu3fvbmHLK84rr7wib9++XY6Ojpb37Nkj9+nTR/b29paTkpJkWZblZ599Vm7QoIG8detW+fDhw3JkZKQcGRlpYatNo6ioSG7QoIE8c+bMEq/b6vplZmbKx44dk48dOyYD8qJFi+Rjx47pK2QWLFgge3p6yr///rt88uRJ+eGHH5ZDQ0PlnJwc/T4GDBggt2/fXj5w4IC8e/duOSwsTB49erSlTukeyjrH/Px8eciQIXL9+vXl48ePl/hu6ior9u7dK3/wwQfy8ePH5aioKPnbb7+VfXx85LFjx1r4zBTKOr/MzEx5+vTp8r59++To6Gh58+bNcocOHeSwsDA5NzdXvw9bXkMd6enpsrOzs/z555/f83lrX8Py7g+yXP71s7CwUG7VqpXcr18/+fjx4/KGDRtkHx8fedasWWazUzgs5fDJJ5/IDRo0kDUajdy5c2d5//79ljapUgBGf7766itZlmX56tWrcvfu3eW6devKDg4OcuPGjeUZM2bI6enpljXcBEaOHCkHBATIGo1Grlevnjxy5Ej58uXL+vdzcnLk5557Tq5Tp47s7OwsP/LII3J8fLwFLTadjRs3yoB84cKFEq/b6vpt27bN6O/luHHjZFlWSptnz54t+/n5yQ4ODnLv3r3vOfeUlBR59OjRsqurq+zu7i4/9dRTcmZmpgXOxjhlnWN0dHSp381t27bJsizLR44ckSMiImQPDw/Z0dFRbt68ufx///d/JW74lqSs87t9+7bcr18/2cfHR1ar1XJwcLD8r3/9656HPlteQx1ffPGF7OTkJKelpd3zeWtfw/LuD7JcsetnTEyMPHDgQNnJyUn29vaWX3nlFbmgoMBsdkrFxgoEAoFAIBBYLULDIhAIBAKBwOoRDotAIBAIBAKrRzgsAoFAIBAIrB7hsAgEAoFAILB6hMMiEAgEAoHA6hEOi0AgEAgEAqtHOCwCgUAgEAisHuGwCAQCgUAgsHqEwyIQCKyanj17MnXqVEubIRAILIxwWAQCgUAgEFg9ojW/QCCwWsaPH8/KlStLvBYdHU1ISIhlDBIIBBZDOCwCgcBqSU9PZ+DAgbRq1Yp58+YB4OPjg52dnYUtEwgENY29pQ0QCASC0vDw8ECj0eDs7Iy/v7+lzREIBBZEaFgEAoFAIBBYPcJhEQgEAoFAYPUIh0UgEFg1Go2GoqIiS5shEAgsjHBYBAKBVRMSEsKBAweIiYkhOTkZrVZraZMEAoEFEA6LQCCwaqZPn46dnR0tWrTAx8eHq1evWtokgUBgAURZs0AgEAgEAqtHRFgEAoFAIBBYPcJhEQgEAoFAYPUIh0UgEAgEAoHVIxwWgUAgEAgEVo9wWAQCgUAgEFg9wmERCAQCgUBg9QiHRSAQCAQCgdUjHBaBQCAQCARWj3BYBAKBQCAQWD3CYREIBAKBQGD1CIdFIBAIBAKB1SMcFoFAIBAIBFbP/wMm+h/YcJk5/wAAAABJRU5ErkJggg==", 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", 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0dGDTpk144403sH//fhQWFiq3HzVqFGbPno3rr78ebrcbjz76KAYOHBg2zQOwDrVffvklzjzzTAwdOhQNDQ345z//ifLycsyePRsAcO211+LJJ5/ElVdeie+++w7Dhg3DG2+8gZUrV+LRRx9VPDJnn302TjrpJNx2223Yv38/JkyYgLfeegstLS0hz/vYY49h9uzZmDRpEq655hqMGDEC9fX1WLVqFQ4ePKi8ZwAUZWf//v0RPqHwXHbZZXjttddw3XXXYcmSJTjppJPg9/uxfft2vPbaa/jkk0+UVF5mZiaOO+44rF69WukxAjBlpKOjAx0dHSHBSKyekYsvvhgZGRmYNWsWiouLsXXrVjz11FPIzMzEfffdF3DbjRs3Kr1Odu/ejZaWFuV7NGXKFJx99tkAgJqaGowfPx5XXHFFwCygBx54AOeccw5OP/10/PCHP8TmzZvxj3/8A1dffbXi/QGAhQsXory8HDNmzEBxcTGqqqrwzDPP4NChQwHBKEEknGSX8xBETxCuA2swZrpgSpIkNTQ0SLfccos0atQoyel0Svn5+dL8+fPDlvNeccUVYcs8jXQkbWtrk26//XZp1KhRksPhkAoLC6VZs2ZJDz74oNKRk5eWPvDAA9JDDz0kVVRUSE6nU5ozZ460YcOGgMcLLu39/PPPpXPPPVcqKyuTHA6HVFZWJl1yySUh5cT19fXSVVddJRUWFkoOh0OaNGmS7vY3NjZKl112mZSbmyvl5eVJl112mbRu3Trd17tnzx7p8ssvl0pLSyW73S4NHjxYOuuss6Q33ngj4HaFhYW65afBzJs3T5o4caLudR6PR7r//vuliRMnSk6nUxowYIB03HHHSX/605+klpaWgNv+5je/kQBI999/f8Dlo0aNkgBIe/bsibotRvjrX/8qTZ8+XSooKJBsNps0aNAg6dJLL5V27doVclv+fdb70ZaL8++CXgn522+/LU2dOlVyOp1SeXm59Pvf/175DnH+8Y9/SLNnz5YKCwslm80mFRUVSWeffbb05ZdfJuQ1E0Q4BEmSpN4NfwiCSCT79+/H8OHD8cADD+DXv/51sjcnoWzduhUTJ07E+++/jzPPPDPZm0MQRA9BnhGCIFKWJUuWYObMmRSIEEQfh4IRgiBSlkWLFuGrr75K9mYQBNHDUDBCEARBEERSIc8IQRAEQRBJhZQRgiAIgiCSCgUjBEEQBEEklbRoeiaKIg4dOoScnJyo7ZwJgiAIgkgNJHmMQFlZWcSuwmkRjBw6dChkwBNBEARBEOlBdXU1ysvLw16fFsEIbzddXV2dkCmWBEEQBEH0PK2traioqFDO4+FIi2CEp2Zyc3MpGCEIgiCINCOaxYIMrARBEARBJBUKRgiCIAiCSCoUjBAEQRAEkVTSwjNiBFEU4fF4kr0ZRAQcDkfE0i6CIAiif9InghGPx4N9+/ZBFMVkbwoRAYvFguHDh8PhcCR7UwiCIIgUIu2DEUmSUFtbC6vVioqKClp5pyi8cV1tbS2GDBlCzesIgiAIhbQPRnw+Hzo7O1FWVobMzMxkbw4RgaKiIhw6dAg+nw92uz3Zm0MQBEGkCGkvI/j9fgAg6T8N4J8R/8wIgiAIAugDwQiHZP/Uhz4jgiAIQo8+E4wQBEEQBJGeUDCSJCorK3HzzTeHvX7YsGF49NFHe217CIIgCCJZpL2Bta/y7bffIisrK9mbQRAEQRA9DgUjKUpRUVGyN4EgCILow3h8IiwCYLMmP0mS/C3ox/h8Ptx4443Iy8tDYWEh/vCHP0CSJAChaZqqqiqce+65yM7ORm5uLi666CLU19cr1//xj3/E1KlT8fTTT2PIkCHIzs7GDTfcAL/fj7/85S8oLS1FcXEx7rnnnoBtePjhhzFp0iRkZWWhoqICN9xwA9rb25XrDxw4gLPPPhsDBgxAVlYWJk6ciA8//BAA0NTUhB//+McoKipCRkYGRo8ejWeeeaYH3zGCIAgiEbS7fZh9/xf40b+/TvamAOiDyogkSejyJqd0NMNuNVUx8txzz+GnP/0pvvnmG6xZswbXXnsthgwZgmuuuSbgdqIoKoHIsmXL4PP5sGjRIlx88cVYunSpcrs9e/bgo48+wscff4w9e/bgggsuwN69ezFmzBgsW7YMX331FX7yk59g/vz5mDFjBgDWFfVvf/sbhg8fjr179+KGG27Arbfein/+858AgEWLFsHj8eDLL79EVlYWtm7diuzsbADAH/7wB2zduhUfffQRCgsLsXv3bnR1dcX5LhIEQRA9zbqqJjS0udHa7U32pgDog8FIl9ePCXd8kpTn3nrXAmQ6jL+lFRUVeOSRRyAIAsaOHYtNmzbhkUceCQlGPv/8c2zatAn79u1DRUUFAOD555/HxIkT8e233+KEE04AwIKWp59+Gjk5OZgwYQJOPvlk7NixAx9++CEsFgvGjh2L+++/H0uWLFGCEa2JdtiwYbj77rtx3XXXKcFIVVUVfvCDH2DSpEkAgBEjRii3r6qqwrRp03D88ccr9ycIgiBSn40HWwAAqTJFhdI0SeTEE08MUFJmzpyJXbt2hTQF27ZtGyoqKpRABAAmTJiA/Px8bNu2Tbls2LBhyMnJUf4vKSnBhAkTAlrkl5SUoKGhQfn/s88+w6mnnorBgwcjJycHl112GRobG9HZ2QkA+PnPf467774bJ510Eu68805s3LhRue/111+PV155BVOnTsWtt96Kr776KgHvCkEQBNHTbJKDEV+KRCN9ThnJsFux9a4FSXvuZBLcYl0QBN3L+EDB/fv346yzzsL111+Pe+65BwUFBVixYgV++tOfwuPxIDMzE1dffTUWLFiADz74AJ9++inuvfdePPTQQ7jpppuwcOFCHDhwAB9++CEWL16MU089FYsWLcKDDz7Ya6+ZIAiCMM+mGlkZkZi9IdlNKfucMiIIAjIdtqT8mP0wv/460Di0evVqjB49GlZrYFAzfvx4VFdXo7q6Wrls69ataG5uxoQJE2J+r7777juIooiHHnoIJ554IsaMGYNDhw6F3K6iogLXXXcd3nrrLfzqV7/Cv/71L+W6oqIiXHHFFXjxxRfx6KOP4qmnnop5ewiCIIiep7HdjZpm1d/nF6Ukbg2jzykj6URVVRVuueUW/OxnP8PatWvx97//HQ899FDI7ebPn49Jkybhxz/+MR599FH4fD7ccMMNmDdvnuLXiIVRo0bB6/Xi73//O84++2ysXLkSTzzxRMBtbr75ZixcuBBjxoxBU1MTlixZgvHjxwMA7rjjDhx33HGYOHEi3G433n//feU6giAIIjXhqgjHL0lJDwb6nDKSTlx++eXo6urC9OnTsWjRIvziF7/AtddeG3I7QRDw7rvvYsCAAZg7dy7mz5+PESNG4NVXX43r+adMmYKHH34Y999/P4455hi89NJLuPfeewNu4/f7sWjRIowfPx5nnHEGxowZo5hbHQ4Hbr/9dkyePBlz586F1WrFK6+8Etc2EQRBED0L94twUkEZESTe2CKFaW1tRV5eHlpaWpCbmxtwXXd3N/bt24fhw4fD5XIlaQsJI9BnRRAEkXyueX4NFm9V+1Rt+uPpyHHZI9wjdiKdv7WQMkIQBEEQ/YhUVEYoGCEIgiCIfkJDazfqWrth0dRbUDBCEARBEESvwc2rI4uywQtAKRghCIIgCKLX2N/IGlqOKcmBTZZH/ClgHaVghCAIgiD6CU0dHgDAwGwHLLI04vNTMEIQBEEQRC/RKAcjBVkORRkRSRkhCIIgCKK3ONrhBgAMzHLAwtM05BkhCIIgCKK3OCorIwM0yggFIwRBEARB9BraNI2VDKwEQRAEQfQ2ioE1y0kGVqLnGTZsGB599NFkbwZBEASRIvhFCc1dXgBkYCUIgiAIIgk0dXrA444BmXbFwOpLN8/IvffeixNOOAE5OTkoLi7Geeedhx07dkS8z7PPPgtBEAJ+aEgaUFlZiZtuugk333wzBgwYgJKSEvzrX/9CR0cHrrrqKuTk5GDUqFH46KOPAADHH388HnzwQeX+5513Hux2O9rb2wEABw8ehCAI2L17NyorK3HgwAH88pe/VN5zgiAIon/Dzat5GXbYrBZVGUm3YGTZsmVYtGgRVq9ejcWLF8Pr9eL0009HR0dHxPvl5uaitrZW+Tlw4EBcGx0RSQI8Hcn5MSl1PffccygsLMQ333yDm266Cddffz0uvPBCzJo1C2vXrsXpp5+Oyy67DJ2dnZg3bx6WLl0qv0QJy5cvR35+PlasWAGAfTaDBw/GqFGj8NZbb6G8vBx33XWX8p4TBEEQ/Zujil/EAQAppYzYzNz4448/Dvj/2WefRXFxMb777jvMnTs37P0EQUBpaWlsW2gWbyfw57Leea5gfnsIcGQZvvmUKVPw+9//HgBw++2347777kNhYSGuueYaAMAdd9yBxx9/HBs3bkRlZSX+85//wO/3Y/PmzXA4HLj44ouxdOlSnHHGGVi6dCnmzZsHACgoKIDVakVOTk7vve8EQRBESnNUU0kDIH2VkWBaWtjAnYKCgoi3a29vx9ChQ1FRUYFzzz0XW7Zsiedp+wyTJ09W/rZarRg4cCAmTZqkXFZSUgIAaGhowJw5c9DW1oZ169Zh2bJlmDdvHiorKxW1ZNmyZaisrOzNzScIgiDSiMagYESppkmBYMSUMqJFFEXcfPPNOOmkk3DMMceEvd3YsWPx9NNPY/LkyWhpacGDDz6IWbNmYcuWLSgvL9e9j9vthtvtVv5vbW01vmH2TKZQJAN7prmb2+0B/wuCEHAZ93qIooj8/HxMmTIFS5cuxapVq3Daaadh7ty5uPjii7Fz507s2rVLUUYIgiAIIpij7epcGgCwWVOnz0jMwciiRYuwefNmxbMQjpkzZ2LmzJnK/7NmzcL48ePx5JNP4v/+7/9073PvvffiT3/6U2wbJgimUiXpxLx587BkyRJ88803uOeee1BQUIDx48fjnnvuwaBBgzBmzBjltg6HA36/P4lbSxAEQaQSvBU8V0as8oLXn659Rm688Ua8//77WLJkSVh1Ixx2ux3Tpk3D7t27w97m9ttvR0tLi/JTXV0dy2b2OSorK/HJJ5/AZrNh3LhxymUvvfRSiCoybNgwfPnll6ipqcGRI0eSsbkEQRBECnG0k/UYGZApByPp2oFVkiTceOONePvtt/HFF19g+PDhpp/Q7/dj06ZNGDRoUNjbOJ1O5ObmBvwQwJw5cyCKYkDgUVlZCb/fH+IXueuuu7B//36MHDkSRUVFvbylBEEQRKqhDMnLDgpG0s0zsmjRIrz88st49913kZOTg7q6OgBAXl4eMjIyAACXX345Bg8ejHvvvRcAOymeeOKJGDVqFJqbm/HAAw/gwIEDuPrqqxP8UtILbjzVsn///pDLJE3EWlBQAFEUA64/77zzAm7DOfHEE7Fhw4a4t5MgCILoGzS2cwOrE0AaByOPP/44AISswp955hlceeWVAICqqipYLKrg0tTUhGuuuQZ1dXUYMGAAjjvuOHz11VeYMGFCfFtOEARBEIRhgvuMpG0worcCDyZ4xf/II4/gkUceMbVRBEEQBEEkDkmS0NQZWNprlYWDVAhGaDYNQRAEQfRx2tw+eOWqGbWahl1HwQhBJIkvttfjH1/sMqT2EQRBpDu8x0imwwqX3QpAo4ykwHEw5j4jBJGu+Pwibn5lPVq7fZg/oQTjSqlaiyCIvk1w91UAsMpyRCp0YCVlhOh3bKppQWu3DwDQ4abGcARB9H2CzasAYJOVkbSfTUMQ6cjK3WoTOI9PjHBLgiCIvkGTjjKSSlN7KRgh+h0rNMGI10/BCEEQfR+ephmgTdPIBlZSRgiil+n0+PDdgSblfwpGCILoDyjdVwM8I6ljYKVghOhXfLPvqFLeBlAwQhBE/0A1sDqVy7iBlUp7CaKX0fpFAMCTAtMqCYIgeprWLmbaz8uwK5dR0zMiBI/Hk+xN6Bes2N0IAJB9W/CSgZUgiH5Ah5sFI1lOq3IZlfYSqKysxI033oibb74ZhYWFWLBgATZv3oyFCxciOzsbJSUluOyyy3DkCFvJv//++8jPz4ffz0pR169fD0EQcNtttymPefXVV+PSSy9NyutJB452eLCtthUAMLk8HwDgoTQNQRD9gA4PC0aynWp7MSrt7UEkSUKntzMpP2a7eT733HNwOBxYuXIl7rvvPpxyyimYNm0a1qxZg48//hj19fW46KKLAABz5sxBW1sb1q1bBwBYtmwZCgsLA2YBLVu2LGSIIaFyoLEDADA4PwOD8lwAyDNCEET/QFVG1GDEIqROaW+f68Da5evCjJdnJOW5v/7R18i0Zxq+/ejRo/GXv/wFAHD33Xdj2rRp+POf/6xc//TTT6OiogI7d+7EmDFjMHXqVCxduhTHH388li5dil/+8pf405/+hPb2drS0tGD37t2YN29ewl9XX6G+tRsAUJLrhMPG4nDqM0IQRH+AN3gMUEbk2l6Rqmn6N8cdd5zy94YNG7BkyRJkZ2crP+PGjQMA7NmzBwAwb948LF26FJIkYfny5Tj//PMxfvx4rFixAsuWLUNZWRlGjx6dlNeSDtS3stK2klwX7HKy1EsGVoIg+gERlZEUOA72OWUkw5aBr3/0ddKe2wxZWVnK3+3t7Tj77LNx//33h9xu0KBBAJjP5Omnn8aGDRtgt9sxbtw4VFZWYunSpWhqaiJVJAqqMuKCW1ZEKE1DEERfR5IkxTOS5VANrDZL6igjfS4YEQTBVKokVTj22GPx5ptvYtiwYbDZ9D8W7ht55JFHlMCjsrIS9913H5qamvCrX/2qNzc57eDKSHGuE/UtLDChYIQgiL5Ol9cPbgsJUEaUdvDJPw5SmiZFWLRoEY4ePYpLLrkE3377Lfbs2YNPPvkEV111lVJBM2DAAEyePBkvvfSSYlSdO3cu1q5di507d5IyEoWGNlkZyVHTNOQZIQiir9Mup2gEAcjUUUZSYU1GwUiKUFZWhpUrV8Lv9+P000/HpEmTcPPNNyM/Px8Wi/oxzZs3D36/XwlGCgoKMGHCBJSWlmLs2LFJ2vr0oK5FTdPYuYE1FfZCgiCIHqRTNq9mOWwQZJ8IAFiVYCT5x8E+l6ZJF7QluZzRo0fjrbfeini/Rx99FI8++mjAZevXr0/chvVhuGekNM8Jh2JgTf5OSBAE0ZO06zQ8A7TBSK9vUgikjBD9gi6PH63dbIcsznUppb1eX/KNW0aRJAkNckBFEARhFL1KGgCwCqmjjFAwQvQLuF8kw25FjtMGu1xfn07KyDMr92P6nz/Hm98dTPamEASRRqiVNEHBCFdGUmBNRsEI0S9Qe4w4IQiCamBNo2Dki+0NAIBNNS1J3hKCINKJdu4ZCZumSf5xkIIRol/A/SLFuawNvD3NPCOiKGHDwWYAwJF2d3I3hiCItKLTHTqXBtAGI8mXRvpMMGJ2LgzR+yTzM9I2PAOgGFjTpbR375EOtMmel6MdNOGZIAjjtIfzjFAwkjisViY7eTx0gE51+GfEP7PeRAlGcpwAoBpYUyFZaoAN1c3K3xSMEARhhg4lTZO6wUjal/babDZkZmbi8OHDsNvtAT05iNRBFEUcPnwYmZmZYTvM9iTcM1KaF5imSRfPCE/RAEAjBSMEQZhArxU8oFbT0NTeBCAIAgYNGoR9+/bhwIEDyd4cIgIWiwVDhgwJaLrTW4R6RtKrmiZYGRFFSWnlTBAEEYloaRqaTZMgHA4HRo8eTamaFMfhcCRNuWpok6tp5DSN3ZY+Bla3z4+tta3K/35RQmu3F/mZjiRuFUEQ6UI6GFj7RDACsFW3y+VK9mYQKYgkSWENrOnQ9GxbbRu8fgkFWQ54fSLa3D40dngoGCEIwhDtaeAZIYMF0edpc/vQ6WE7Y3GurIykkWdkfVUTAGBKeR4KslkAQiZWgiCMErYDKwUjBNF78BbqOS4bMuUOhLyaJh1KezccZE3OplTkY2AWC0Ya2ykYIQjCGNzAmh3c9EygYIQgeg21+6qaxksnA+vWQ8wvMrk8DwVZTNlp7KDGZwRBGIMbWDOD28FbeTt4CkYIosdRpvVqgpF0mtpbL8/VqRiQqSgjR0kZIQjCIJ2yZyTEwMpLe1Og3xIFI0Sfh/srCrJUw6faDj75O2Ek3D4/mju9AICiHKfiGaFeIwRBGCWcZ8SWQqW9FIwQfZ7WLnYyz8uwK5fx0t5UN7Byb4jdKiAvw64qIxSMEARhAEmS1KZnQZ4R3qsoFZqeUTBC9Hla5ZkuuRnqqoB7Rjw+MaXnGvGheIXZbNrwQKqmIQjCBF1eP3isEZymUZQRCkYIoufhykiuS1VGnJr5OKmwKgjHYblZW5HcrI0bWGlyL0EQRuDmVUEAMuykjBBE0mjtloORgDSN2ko9lU2sPBgpzGZBCKVpCIIwgzIkz2ELGcVByghB9CJKmkajjHADK5DaXVgVZSSbKyMsGGnq9KR0eokgiNRANa+GTku3pNCgPApGiD6PkqbReEZsmiFzqWxi5ekYNU3DghGvX1KCLIIgiHCEq6QBAJuVqmkIotdok0/aORplRBCEtOg1cjgoGHHZrYoJrZF8IwRBREHtvhoajFhJGSGI3kM1sAbujOnQhTXYMwKo6gj5RgiCiEa7xjMSDM2mIYhewi9KaHPz0l57wHXpMJ8muJoGUIMRanxGEEQ0InlGKBghiF6iXeOryAlRRlK/8ZleMEIVNQRBGCWSZ4SCEYLoJXhZr8tugdMWuDJI9ZbwnR4fOjxMYtVTRigYIQgiGkppLwUjBJE8lB4jLnvIdTxNk6qekSNtLNhw2S3IcqiB1MBsanxGEIQxIhpYLTS1lyB6hdYuXkkTuiMqBtYU9YwcbmfTeotynAHNiihNQxCEUXgHVl0Dq3xckaTkNz6jYITo0+h1X+WkumckuOEZh9I0BEEYxYiBFUi+OkLBCNGn0ZtLw0n1aprD8sRerV8EUKcP89dGEAQRDiOeESD5vhEKRog+jTqxN7wykqoGVr0eI4DaNTFVt5sgiNTBSDUNQMEIQfQobd36Dc8ApHwHVr2yXkDdbp+YmttNEETqoBpYKU1DEEmDG1j1lRG2I6a8ZyQnWBmRgxFSRgiCiIIRAysA+JN8PDEVjNx777044YQTkJOTg+LiYpx33nnYsWNH1Pu9/vrrGDduHFwuFyZNmoQPP/ww5g0mCDNEKu21p7gyogzJC5emIWWEIIgoGE7TpJMysmzZMixatAirV6/G4sWL4fV6cfrpp6OjoyPsfb766itccskl+OlPf4p169bhvPPOw3nnnYfNmzfHvfEEEQ1u8tQt7eV9RlLVwMo9I0HKiN1CyghBEMbolBsnZjpC0zSCIIDHI8n2jIQeoSPw8ccfB/z/7LPPori4GN999x3mzp2re5+//vWvOOOMM/Cb3/wGAPB///d/WLx4Mf7xj3/giSeeiHGzCcIYkUp7nSlc2itJkjqxN6yBNfW2myCI1KLby4MR/dO9zWKBxy8mPRiJyzPS0tICACgoKAh7m1WrVmH+/PkBly1YsACrVq0Kex+3243W1taAn/6EJEl447uD2Hqof73unqCNV9PoNj1L3Wqa1m6fUnIc7BmxUzUNQRAG8PpF5TiRYQ9VRgBAFlrTNxgRRRE333wzTjrpJBxzzDFhb1dXV4eSkpKAy0pKSlBXVxf2Pvfeey/y8vKUn4qKilg3My15Z30Nfv36Btz+1sZkb0raE7HpmU02sKZgmqa5k/UYybBb4Qo6iNgsFsDSCZ/fp3dXgiAIAKoqAgAuh/7p3iZHI2kbjCxatAibN2/GK6+8ksjtAQDcfvvtaGlpUX6qq6sT/hypiiRJeHLZXgBATXN3krcm/VGqadLMwMoVHT2vS11XFbLH3A2p8I3e3iyCINKILjkYEQS1JUAw3DPiSyfPCOfGG2/E+++/jy+//BLl5eURb1taWor6+vqAy+rr61FaWhr2Pk6nE06nM+z1fZmlOw9je10bAKClywNJkgLmkhDGEUVJ7TOSkV59RriioxeM1HZUQRBEwFHb25tFEEQa4fayY1uG3Rr2PMJbBYjpVE0jSRJuvPFGvP322/jiiy8wfPjwqPeZOXMmPv/884DLFi9ejJkzZ5rb0n7CE0v3KH97/ZIyQp4wT4fHBx7sR1ZGUs97oSojodstWPj2SkkfbkUQROrClZFwfhEAsMhBSrKr80wFI4sWLcKLL76Il19+GTk5Oairq0NdXR26urqU21x++eW4/fbblf9/8Ytf4OOPP8ZDDz2E7du3449//CPWrFmDG2+8MXGvoo+wrqoJX+87CrtVgE3Wzrh3gDAPbwXvsFpCfBeAZjZNCiojkdI0giAfNASReo3IbD3UqqhJBEEwuuTFrN7xj8PPNWmljDz++ONoaWlBZWUlBg0apPy8+uqrym2qqqpQW6vKx7NmzcLLL7+Mp556ClOmTMEbb7yBd955J6Lptb/y4Sb2vp01uUyZzNrcSQfYWImUogE0U3tT0MDaFqFZmxKMQEz6aiYVWL7rML73t+X43dvUu4ggtCjKiE6PEQ5vfJZWnhHJQOS0dOnSkMsuvPBCXHjhhWaeql+yu6EdAHD8sAHYeqgVDW1uCkbiIJJ5FdCWyKZiMBJBGQFXRqSU3Pbe5u21NQCAtQeakrwlBJFa8GDEZQ+vO/BgJG2raYjEs/cI62Q7ojAbeZnsBNpEaZqYUbqv6pT1AmqaJhVP6G0RDKxcGREgpqTfpTfx+ER8to0Z5A+1dAWUMhJEf8dtwDNCwQgRgNvnR/XRTgDAyOIsDJCDkeYuUkZipTXCxF5Am6ZJvRN6JAOrpFFG+vvk3tV7GxVvkCQBB5s6k7xFBJE6qMoIBSOEQQ40dkKU2Eq4KNuJ/AzZM9JBykiscGVEr+EZkB59RvQCKb/EV//kGfl4S2DzxH1HKBghCE6XRy3tDQef3EvBCAEA2CP7RUYUZUMQBORn8TQNKSOx0hrhhA6kdppG7TOio4xImmqaFNz23sIvSvh0C0vRFMrzew40hh/aSRD9DSMGVgtXRtKpmoboObhfZGRRFgCoykgXKSOxEqkiBQAc1tRtBx/JwKoqI1LSHfDJZG1VE460u5HjsuEHxw4GAOw7QsEIQXC4h8pli17a609yypeCkRSBKyMji7IBQPWMkDISM0o1TVqmacIrI6Ikb28/V0a4cXX++BKMKmb7zYFGStMQBKfbjDKS5EMJBSMpwp7DPBiRlRElGCFlJFYitVQHNAbWFPRdRFJG1BJ7qV97RvYeZirIsUPyMbyQ7TekjBCEipmmZ+QZISBJknJgHSErI/mZ1PQsXtrd7ISe7YwcjKSiuqAaWEOVEZ6mEfq5MlLTxDo/lw/IxNCBLBg51NIFt4/KewkCMNYOngyshMLhNjfa3D5YBGDowEwAGmWESntjplNeFWQ6whlYU7PpmdcvKgcRXWUEagfW/txnhJfxDh6QgcJsB7KdNkgSUH20K8o9CaJ/oBpYDTQ9IwMrsUdWRYYUZMIpG40GKMqIh4ahxUiHrIxkOfVXBQ4ru9ybYgbWdlkVAYBsnWBE6xnpr31G2rq9SrXU4PwMCIKgBPL7KVVDEAA0BlZDfUbIwNrv4X4RnqIBgDzZdClKQJvbp3s/IjLRlBG7rIyk2qA8nqLJsFuVVJIWJRjpx56RmmamfgzItCNLTsMNk1M1+6m8lyAAAN1edqwwFoz0yiaFhYKRFID7Rbh5FWBfHp7nIxNrbHR6IisjqTooL5rxlqppgINyKmbwgAzlsmGFsjJCwQhBAFANrMbawZMy0u/RU0YAKu+Nlw432xGzwnlGFANraqkLkSppAOozAqjKyOB8NRjhJlYq7yUIhiEDKykjBOeQfGAdUpAZcHme7BuhYXnm8YuSsiNmhqmxT9Vqmkg9RgC1tFcQJHj6aeUIN6+WD1D3GSrvJYhADHlGBFJGCJkj7W4AQFGOM+Byroy0UEWNabo001uzwpb2sp3QJ0opZRKOpoyonhHA4++fwYiuMiIH84eau+BLsQCTIJKBoWoaK5X2EmCrcj5/hs/X4PDy3iYalmeaTtn0axEAp03/a+7QXO5NoaqUaG3sA4IRX/80N/MeI1rPCK88EiXAnWI+IIJIBkaannFlJNkpXwpGkkxjOws0rBYB+UFty5XGZ6SMmKbDo/pFBHlnC0ZbqZJKvpGoygg0wYjYP4ORg0rDMzUYcQR8nhSMEES3Ac8I78AqUp+R/g1P0RRmO5QZARwenJCB1Ty8x0hmmEoaIDAYSaWKGl7KbSRN4/X3v2Cky+NHo6wWluernhGb1QK+C6XS50kQyYKX9hqZTUPKSD/ncBsPRpwh1w0gA2vMdHoiV9IATI3iTvJUWklHM7AGBCP90MDK/SLZThtyMwI/Xx5gUpqG6O/4/KLSQ8nI1N5k++YoGEkyh9vDByN5VNobMx2e6MoIoJpYU2kl3WrGwNoP0zRqJU1GSAqO+4BSrZEdQfQ23ZpjGikjRFSORAhGtC3hCXN0uiN3X+WkYnmv6hkxoIz0w2oavUoaDjcrp9LnSRDJgJtXgfAmfoCUEULmSBsLNILLegFN0zMysJqGKyNZEVYEgPbklUoGVoMdWNFPgxGdShpOqnbVJYjeRmteDWfiBwALVdMQgDZN4wi5jkp7Y6dTMbCmszJCfUb00Kuk4ShpGgpGiH6OEoxEWZDZaGovAQBH2vQbngFqaW9rty/pDWnSDbW0N5pnJPUMj2b6jPTHaho1TZMZch0v7yXPCNHf4Q3PXBFSNICmHXyS1WEKRpKM0n1Vz8Cq6TtCXVjNwYfkRfeMpGI1jYnSXrH/KSN1Ld0AgEH5rpDrSBkhCIbS8CzKgsxCyggBaAysOsqI3WpRDq7a9uZEdJQheVGraVIrTePzi0pZctjZNFAPGv1RGeGl7gWZoalN8owQBMPIkDxAk6Yhz0j/JVIreI6TDq4xYVQZcaRY9UW7Ww0uok/tBXwp1Ma+N3D7/EqwNkAnGHGkoCGZIJKB0vAsSjBiESgY6fdEagXPcdq5p4GUETNwz0h2FAOr4jHwpcbJi6doXHZLQIdYLZJGTvX2sz4jvOeORdAP1pxKnxHaX4j+jVkDK7WD78dEagXP4SdLt7d/rYDjRammMWhgTRVlpDVK91UgSBnpZyddnqLJz9TfZyhNQxAMnqZxRui+CmianpGBtf8SqRU8xylLbFQdYA6lmiZaaW+KGR6jmVeB/m1gbepgwRovew9GraZJDaWLIJIFN7BSaS8RlUit4DlcdiZlxByqZyTyjuhIsWqaaN1XgeA0Tf8KRng3Yj2/CEDVNATBUQ2sBkt7yTPSf4nUCp7DD67kGTFHp9ugMpJiaRql+2qE7damafz9LBjhhu8BYZQRStMQBMNtsJqGghEiYit4jpNWejHRYVAZsaeYrK+ml8Jvt1YZ8fW7YET1jOhByghBMJSmZ1GOgRSMEBFbwXO4+SiVOoSmA4oyYrC0N1VOXtx4G2m7RfTf2TRqmiZM9VmKlWoTRLJQO7BSMEJEIVIreA6lacwjSZKqjERpeuZMsfeX99CItN1aA6s2ZdMf4GmaqMoIBSNEP6fLI/cZiaaMUJ8RIlIreA6laczj9ong+1U0ZcQl51O7U8QgbKRZmzYY8fW7PiORDay8vX88+4skSfjd25tw4RNfYUN1c8yPQxDJpNusZ4SqafovkVrBc9SVe2qcLNMBbRfTaDsif3+7U6TdvqKMRFjN9OcOrNEMrA5r/KXwq/Y04qWvq/Dt/ib84PGv8NiS3QE+HYJIB4y2g6c0TT/HSCt4QJum6V8nnXjgfpFMhzVsMzkOV0ZSLk0TIRjRnhj7XzVNzxpYJUnCw4t3AgAG5bngEyU88MkOLNnRENPjEUSy6CYDK2EE3tZaEBC2FTxABtZY6DA4lwZgbdeB1EnTdLhNpmn6mWeE7zcDssKV9saXplmx+wjWHGiCw2bBO4tOwmkTSgAAew93xPR4BJEsVAOrsT4jPgpG+ictXWyFl+uyR1y9p5rBMh3gvotoE3uB1FNG+AEk0rYHGFj7kTIiipLiGdGb2AvEV00jSRIekVWRH00fgpJcl6Ja8m6WBJEumO3AKlIw0j9p6Yrc1prjoA6spulQ0jQGlBFbahlYuTKSYTemjPj7kWekrdunGJN7Ik2z5VAr1lY1w2mz4IbKkQDUfHtXiniKCMIoRg2sfGovKSP9FC4350VI0QBqmoZKFY2jKCNRVgSAOhU51QysEZUR9M/SXu4XyXJYlaAjGLWJnfn9ZZ1cOTNjxEAU57oAABkO9ngUjBDphpKmiRKM2Kw0tbdfw5WRqMGInZQRsyjKSJRW8IC2tDc1TjaqgdWgMtIPg5FwqggQnzKyUQ5GppTnKZdlpNj3gyCMwtXeaGkaRRmhqb39E6PKCJ9CmiqehnTAlDJiSy0Dq5EBf/3VMxLNvApop/aa/zw3HGwGAEwuz1cu48EqeUaIdMOwMmJh+wwpI/0Uo54RroxQ0zPjdBhQFziKMpIiwV6HgTb2gcpI//leNEVpeAYA9hiVkQ63D7sb2gEEKSMO8owQ6YdflJR9IKpnRI4CyDPSTzGcpqHSXtMo813MVNOkgDIiipJy0qN28KFEawUPAM4Yp/ZurmmBKAGluS7FLwJoDazJ/34QhFG0acWoTc8Eqqbp1yjKSEb4AyuQeoPc0gFzykjqpMG0q2+jTc8AKenNinqLaEPyAHV/MVvau/FgCwBgskYVATTBiKd/td0n0hvtscQZpc8IN7CSMtJP4QfW6MpI6pws0wUznpFUKu3l5lVBiDxpM1ANEfvNhNqeNLByv8iUivyAyylNQ6QjSvdVuyVqF2oLDcrr3yhpmmieEWoHb5p0rabhQVSGPXIbe22aBoKU9BVNbxFtLg0Qe2mvEoxozKuAVhlJ/veDIIzSbdC8CpCBtd/TbNAzQmka88RSTeMTJfiSrDAYbdYmQXvQEJO+3b1FtIm9QGz7y9EOD6qPdgEAJgWnaRypo5wRhFG6POz7Gklh5ZCBtZ/TarSahgyspolFGQGA7iS/x11eY8bbgDSNIMKb5P4AvcXRjuj7TCylvRtlVWR4YVbI4oA6sBLpCK8OjNZjBNAoI+kWjHz55Zc4++yzUVZWBkEQ8M4770S8/dKlSyEIQshPXV1drNuc9kiSZKIDK3lGzBKLMgIkP1XDg6ho7vdgA6uvn7SE7yllZMuhVgDApMF5IddRnxEiHeHHsmjmVQCwpqsy0tHRgSlTpuCxxx4zdb8dO3agtrZW+SkuLjb71Ann169vwOmPLMN3B5p69Xk7PX7lg49WTeOkNI1pzFTTWCyCcgJLdjCiDviLvN1aZUQQRHh9/UMZMdJnhCsjomTckLf/CJvIO6o4O+Q6rYFVSnJOnSCMwtOKRjwj1hRRRqIfrYNYuHAhFi5caPqJiouLkZ+fb/p+PUlVYyd21rejrqW7V5+X+0UcVotSWhoOStOYx0yfEYCN2Pb4xKS/x2oreHPKiLcfKCPdXr9ygM2P0IF1T+s2WJyHILrL4PGJhmTq/Y0sGBk6MDPkOq1K5faJhg7uBJFstNU00bD2t0F5U6dOxaBBg3Daaadh5cqVEW/rdrvR2toa8NMTDMxmK6zGDnePPH44WjrVShpBiFx2pcymoWDEMGaUESB1Kmo6DAYjgdU0YtJnSvQGPK1ptQjICaMcuf1u3PDFNcgc+hQA0bCauL+xEwAwbGBWyHXa4INSNUS6YLQVPABY5T4j/r5eTTNo0CA88cQTePPNN/Hmm2+ioqIClZWVWLt2bdj73HvvvcjLy1N+KioqemTbeDBypN3TI48fjuYuYz1GAFV29qdAtUe6YGS+ixY1GEmygVXxuhhP0/SXPiOt3SwYyXXZwgbwXd4udPm6IFi7AcFvyMTa4fbhcBtbjOgFI1ZNGo9MrES64ObBiIFqGmuK9BkxnaYxy9ixYzF27Fjl/1mzZmHPnj145JFH8MILL+je5/bbb8ctt9yi/N/a2tojAcnALCcAoLG9d5URpZLGQDDi1MhsHr8Im5UKoCLh9avVJUaDEcUknGxlRKkCMpGm6Sd9Rtq6WaCW4wq/zwQHaUaCkQOyKjIg0x6250+G3QqPT6RghEgbVM+IEQOrGoxIkhRVre8pejwY0WP69OlYsWJF2OudTiecTmePb0chT9P0tjJisJIGUJURgM1PieDdI6D6LgBjZW1A6gzLUxUdc8pIf1DM2mRlJDuCuTe4GZyRNI3qFwlVRTgZditauryUpiHSBjNNz6yaBouiBFiTE4skp8/I+vXrMWjQoGQ8dQADs2VlpLc9Iwa7rwKAzWpRviyxjEXvb/AThtUiBARykeCrh2SnaWI2sPYDz0i7mysj4YOREGXERDAyvDBCMOJIDU8RQRiFL6zMBiPJTNWYVkba29uxe/du5f99+/Zh/fr1KCgowJAhQ3D77bejpqYGzz//PADg0UcfxfDhwzFx4kR0d3fj3//+N7744gt8+umniXsVMTIwK0nKiMHuqxynzYJOjz8lJsumOlq/iFG5UZncm3RlhD1/NM+ICPV7IAj+ftFnRE3TGFNGBMGYl+bAEZam0auk4fDvRycpI0SawBdWThNpGiDNgpE1a9bg5JNPVv7n3o4rrrgCzz77LGpra1FVVaVc7/F48Ktf/Qo1NTXIzMzE5MmT8dlnnwU8RrLgysiRXvaMGJ3Yy1GCEWp8FhWj6oIWZ4oMy+uQV//R0kvB6Yj+YGBtN+0ZkQxVoHFlRM+8ysmkYXlEmtFtwsBq0wYjSayoMR2MVFZWRmz+8+yzzwb8f+utt+LWW281vWG9AfeMtHb74PGJimu+p1FKezOMvf0OGpZnmE6TZb2ANk2T3JMNP9lF648SEIygf7SDN+8ZMZemiaSMZKRI6TdBGMVM0zOLRkH2J/FY0q9LM3JddiUqPNrRe6kaRRkx6EalxmfG0U6+NUrKKSP2KGma4Km9/SEYMeIZEQOVkWiKUafHh/pWpopG8oxQS3gi3VA9I9FP8amijPTrYMRiEVCQxXuN9F6qxkyfEYDm05ihK4Y0TaooI4pnxKQy0p88I9lGDawGlJGqo8wvkpdhj7gwyKA0DZFmuE1U01g0wUgyjyX9OhgBtBU1va+MGKmmAWIb/tVf4Sd0o2W9QCqV9hpLMQWnI/pDmsaIZyQ4SItWfcZn0gyLkKIBgAw7NT0j0gszfUYA1cSazHVNvw9G1F4jvaiMmOgzAmiVEQpGotHpjV0ZSXa1ktHOsQFVI+gfnXnb3GyfCdcKHtAZIBgtGGnklTThUzSAxjNCaRoiTTBjYAXUYISUkSTS2+W9flFSJGejwQgZWI3TZbBxmBaXLc1Ke4MNrP2gA2u7ydJeI9U0B3glTQS/CAC4KE1DpBlm+owAakt4UkaSiFLe20uNz3greMCMMsK+UJSmiU5caZokKiOiKKlpmmieEQQaWL394HuheEYMKiNGPCP7eY+RgmhpGgpGiPTCTJ8RQDWxkjKSRAp6WRnhfpEshxV2gx1CycBqnC5FXUgvA6v2RGdqam9/MbC6Y/CMRAlGqptYMDIkqmeEV9P0/feZ6BuYaQcPqCZWkappkkdve0aaTZb1Apo0DXVgjUoHL+01kaZRS3uTF4xwVUQQoud5Q5ue9f00De8zYri0N0ozOJ9fRG1LNwCgYkCUYITawRNphmJgNegZsSnD8npsk6LS74MRZXJvL1XTcGUk12CKBtCkafqBUTFeYurAmgKzaRTzqt0aUGoXTGjDQbHP9xnx+kXlszHuGYmsjNS2dMMvSnDYLCjOiTyU00VpGiLNUEt7jZ3iLZSmST4De3lyr1LWa7D7KqCeLEkZiU5sfUaSX9rb4eZeFzMTewEIfT9Nw82rAJAVwTPik9TbQZAiBu/Vco+R8vyMiMEfoE3TUDBCpAdmDaw2Ku1NPoWa+TSR2twnilaTQ/IAKNNnyTMSHcXAaqIDayoYWLu87EQareFZ8HdU6AdTe9vdalfdSD6rwJLnyH1GuF+kPIp5lT8voJaNE0Qq4xfVY4Jhz4iQfGXE9GyavgZXRtw+ER0ef0S3fiJolXPfuRGMeMFwZYSqaaLTFctsmhQwCCvKSJSDh64y0sfTd3yfidR9FTA3m6b6aBcAoGJARtTn5yob9Rkh0gGtt8lomqYw2wGPXwyY4Nvb9PtgJNNhQ4bdii6vH43t7p4PRrrYKi8Wzwj1GYlOp9dY4zAtfPWQzDQY94xESkMAwb4IAJDg6+N9Roz0GAGCZ9NECUZkZaTCgDJCfUaIdCIgGDFoYH33xtk9tTmG6fdpGkBVR470gm9EMbCaUUZSYOWeLsTXZyT51TTRgigJQYGHEL3tebrDe4xE6r4K6FUZRfeMRKukAajPCJFedMtBuMNqieqHSiUoGIFmPk0vlPcqaRozBlaaTWOYWAys/P1NZjDSYXC7Q9I06PtpmnYDPUaA4PcmmjIip2kKoqdpqB08kU7w45jRhmepQnptbQ9RyBuf9UJ5b2tcykjfPukkglhKe9VqmiQaWHmaJorXJcRkLUh9vrSX9xiJlkIN8YyECdK6vX4cbmMLD0PKCKVpiDTCbMOzVKHfe0YANU2zfNdhOG0WlOVnYPygXFMVL0ZpNTmXBqCpvWbojGU2jbyCYC500XBn3ETCDaxRW8EHeUaEfjCbRu2+arzsWYAEj0//fTko+0WynTbkG5iczQ/qviR+PwjCKGYn9qYKFIwAKM5xAQA+3FSHDzfVKZdPLs/DfedPxoSy3IQ9V1scTc9IGYmM1y8qJW2xKCMAW1Uk42RjNIgKrabp+1N7lbk0JoKRSMoIr6QpH5ABQYieU9dWOHUl6ftBEEZxm5zYmyrQXgXg4hMqcO7UMpw8tgizRxWiXC7323iwBec9thL/Xr43YT1I4vGMkIE1Mp2anL4ZAyt/f4HkBXyGDaw6HVj7fJ+RboOekYBqGgmeMPuLmUoaALBbBaXkkXwjRKrDG56ZOQamAqSMgB2U/vrDaQGXNbR247dvb8Jn2xpw9wfbAABXzxkR1/NIkqSW9prwjFCaxhjcvGq1CEqjOCMIggCnzQK3T0yaidVoMNIfO7Aqc2nMekbC7C9mKmkA9v3IsFvR7vaRb4RIeczOpUkVSBkJQ3GuC/+6/Hj8ZsFYAMBfPtmBnfVtcT2m26dKx5SmSTza+S5G5HctakVNspQRYwP+QpWRvm9gbY/BM4IInWmVhmcGKmk4NJ+GSBeomqYPIggCbqgciZPHFsHjE/HLV9fHpU7wHiMWwdyIe2U2DQUjEYmlxwgn2b1GFGUkigNeRNB3oB/0GWk1mKYxrIw0mVNGACDDwfZBmk9DpDqqgZWUkT6FIAi4/weTkZ9px5ZDrXhy2Z6YH6tVY141s3LnKQdK00SGr1rNmFc5ShfWJPlyug1uuyiGVtP0dQNrewwG1kizaZQ0jUHPCECNz4j0IV1LeykYMUBxrgt/PHsiAODfK/ahw+2Lcg99uHnVbMmwqozQgTASqjJi3grFy+CSl6YxpuqEKiN9vx18m1v2jCRgNk1ju1tRWsykaWhyL5EuKBN7bel1ek+vrU0iZ08pw7CBmWjp8uK1NdUxPUYs5tXa9loc7j4IILmzU9KBLo/5uTScZKdpugxOGw6dTdOPqmlMze2RdJWR3Q3tAFhZr5leNNT4jEgXKE3Tx7FaBKWa5t/L98UkjcdS1nvZR5fhlhVXAoIH7j4ux8eL0jgslmAkySbhToPThkOCkT4+tVeSJHU2jZl28GGUkV1yMDK6ONvUdpAyQqQLSp8RMrD2XS44rhwDsxyoae7CB5tqTd/fbCt4URJR31mPbn8XBGsXPD4xYf1O+iKdcXhGnEqaJlkGVl5NY1YZ6dtpGrdPVF5fVM9I0NRevUF5XBkZU5Jjajv455LM+UUEYQTyjPQDXHYrrpg1DADwzMr9pu/Pc9VGg5HAlR67L1XUhKcrhlbwHF4+nSzPCH/eqAZWHWUk0nTadIeriYKBCrTA/UUKo4yw8vxRJpURKu0l0gVK0/QTzp5SBgDYUWe+50hLl7k0jXalJwjs775exhkP8ZX2Jk8Z8fnVyg/TwQikPh2MKJU0TlvUCrTA94YpKmKQarSrXk7TmFVGlDRN332vib4BN7A6ycDatymUh+p1ef2KtG4Us2mawJUe+5tMrOHpMtirQw91cm/vByOdmgAo2momuJpGEMQ+3fSszYSaGFDaK7D3RBu8t3R60SBP6zWrjFBpL5EuUJqmn5DttCnt2RvbPabuqxpYjQUjPlENdhw2dlCl8t7wGG2prkcyS3t5EGURoq9mgvuMhPNG9BV499XsKJU0QKgyAgQGI7sPMzWzLM9l6PG0kGeESBcoTdNPEAQBA7OYOnK0w2QwIpf2Gu0zoj242m3ySo88I2GJq88Ir6ZJwslGW0kTNRXRz/qMKHNpophXgdBqGiBwf9kpp2hGmUzRABrPCFXTEClOF1XT9B8Gyqmaxg63qfuZLe3VHlx5MEIG1vB0eePvM5KM97fLhNeFV1PZLPw71D/SNFlGlBGNamS1hAbvil/EZIoGoDQNkT4opb00KK/vU5DlBAAcMZumMekZ0aZp7FaepqFgJBzxGFjVQXm9f7IxE0TxANVukb9DggRvH57aa3RIHhAYvPNgRJvC4pU0sQQjWU722cTafZkgegtK0/QjCmNN03AznsE0jfbgarOFys5EIDwYyYqpHXzyPAGdBruvAmrqTquMSBLg76Opmg4TnhHt/mLRUUZ4j5HRJeaDEb6A4OomQaQqSjt4StP0fQrkYKSx3XiaRpIk89U0mtJem5UMrNHojKsdfPIMrGYUHR6McGWEVY303fLethgNrPJsSUVJbOv2oralGwAwqsi8Z4QvILjviyBSFaqm6UcMzGZpmkYTykinx68YDY16RnySeuDjygiV9oYnrjRNEkt7u0xUAYUqIwAg9aqi8/HmOpz5t+V4YfWBHu8IzJURI54RPWWEB2nbalmKpjjHibxMc4MqAXUBwXsFEUSqoqZp0uv0nl5bmyIMVJQR48EIl3dtFsGQHA8EKiNWS2ipIhGImZN6MDy10+lOhmeEp2min3D5yV/xjAAAxF47SW482Iyfv7IOWw614g/vbMZl//kG9a3dPfZ8ypA8A56RQGUkME3zujzccubIgTFtB6+AozQNkerwhYmTDKx9H15NY8YzokzszbBHLd/kBHhGrOxvKi0MTzx9RrhalYyTjZntDjGwAoAgobmz57e7obUb1z7/HTw+EccMzoXLbsGK3Ufwu7c39dhztsvBoSFlRBO8WzRNz452ePDuhkMAgMtnDo1pO/j3o9Pj77MpMSL9kSRJSU1SmqYfoKRpTHhG+EnOaI8RIPDg6pTv1kYrs7B0xdFnRDEoJkGG7zLhdZEQXNoL9JYycttbm1DX2o1Rxdn47zUn4pkrpwMAvjvQ1GPpmnY3e11mPSMuBwv4n/tqP/77TZUSQB07ZEBM26GdGJyM7whBGEFbbUlpmn6Akqbp8Bg+CKvmVeMnSq1nxGFnz9NCBjpdAua7mFgRbG3cit8u/y3cOApArXjqTbgyYmQlo+sZESQ09/AJsqXTi6U7GgAA//zxschx2TG1Ih+CADR1ek2XuRulQ1ZGzFbTTC7PhcNmwWfbGvDI4p0AgCtmDjOsSgZjtQjIcXL1jPZBIjXpNjFaItWgYCQGeJrG7RPRYTBtYrYVPBCojPB28GSg00c738WMgfW1Ha/hf3v/h28PfwGA9bXw9bIMH3eapheUkRW7j0CU2EyXMXIH0wyHFUMKMgEAu+rND440gtIO3qRnJD/ThrvPPQYA4BMlFGQ5lCGXscL3XdoHiVSFm1etFgF2a3qd3tNra1OETIdNkcCMpmoUz4jBsl4gcKXHlREy0OljZr6Llm4/M1+KUD/Htl5e+fLVjKE0TUgHVjYsr6WzZ5QJDldFKscUBVzOA5OdPRyMGOkdo91f/JIfF51QgctOZB6RK2cNi3ulqJb30j5IpCZKWW+aTewFKBiJmYFZ5sp7+WrKaFkvENyBladp6ECoh5n5Llr4e+yXvEow0NsBn5mZOvyEaxEsEMBfp9Sj3wtJkrBs52EAQOXY4oDrxsgNxHbKDcUSjZlqGq2SyN+nu86diE9unosbTx4V97bwFCvtg0SqojY8S68UDUDBSMwo82kM5srNNjwDgqtpKE0TCd6PwmwlDQ9G3H63Yi7u7ffYTJqGKyNWwQqrIN9eEHu0mmZrbSsa2tzIsFtxwvBAA6iijNQlXhnxi5JS9mxoNo0mTcPn1AiCgLGlObBYYvOKaKHyXiLVSddW8AAFIzGjTu41lqZp7orPM2KVgxGSiPXpMpHq0MLfY6/o1VTU9G6axsxsGn7CFQQBFoHvvj2rjHBVZNbIgSG9C0YXq2maRFfUtGvmwPDZMJEITtMkGvKMEKmO0mMkzSppAApGYsbssLxmOac/INNh+Dm01TRWuc8IBSP6tJvo1KnFK7H30+13J63XiJlqGiVNAwusFq6M+Hu0mmbpDp6iKQq5bkRRFiwCqzBpaDM3xToaXO1yWC2GGjgFKCNS4k3IyQpWCcIo3Wk6sRegYCRmCk02PmuSZfQBJlpRBzRxslCaJhJm2oZr4e+xx+9JWprGTOdY3mfEYrEEKiM9lKZpd/uw9kATAGDemOKQ6112K4YNzAKQeBOrmUoaoOeVEUrTEKlOuraCBygYiRmzw/KaZGUk34Qyoj2gCgL7u4M6QOpiZrqrFu4Z8fg9SWt8ZibFxFf8FqjBiCD0XGnv9tpW+EQJpbkuDBmYqXsbtaImsSZWVe0ytsrrcWUkgwysRGrjJgNr/8PssDxuMORBjBG01TQ8GAF6v/Q0HTDTNlyLEoyIHrV0M1nVNAZm0yjBiGBRDayQ0NzVM6W9O2S1Y2xp+Em3vKIm0b1GeCVNttPglOveUkYoGCFSlHSd2AtQMBIzZqppRFHSeEZiq6bxSV5l1U8rs1BUZcSkgVV+j5lnJPXTNNpgREnTCCK6vWKPTO7lVTKRgpHRPdRrxOxn2nueEdr/iNSkX6VpvvzyS5x99tkoKyuDIAh45513ot5n6dKlOPbYY+F0OjFq1Cg8++yzMWxqaqG2hI+epmnt9kKUCw3MpGm0B1RW7UHBSDg6TDTH0sKVEa9ffX9706AoSRI65dk0RjrH6ikjFqHnKq146mV0cXbY2/A0za769oRW1LSZTL3p9RlJJKpyRsokkZr0KwNrR0cHpkyZgscee8zQ7fft24czzzwTJ598MtavX4+bb74ZV199NT755BPTG5tK8DTNUQPzabh5NcthhcNEZzxtmsYreqkDZARirabhFUsef3LSNB6/qASqZoMRroxkudj9eiJI3WkgTTOskHlJ2ty+hG6DWVOyNgDpCWUkWQZngjAK95+ZGYmRKpgeb7pw4UIsXLjQ8O2feOIJDB8+HA899BAAYPz48VixYgUeeeQRLFiwwOzTpwxcGfH6JbR2+yJO443FvAoEpWn8PjoYRiBeA6tbTE7Tsy7NbCMjA/70lJFspwUtQMLLe4+0u9HY4YEgsJk04XDarMh12dDa7cORdrfp73k4zHRfBQIDEK1KkiiU0u8uLyRJinnoHkH0FEowQp6RUFatWoX58+cHXLZgwQKsWrUq7H3cbjdaW1sDflINl92KLDn6jFZRo/hFsoz7RYDAA6pWGaFgJJR4DawsTdP7yhM3rzqsFtgMDLbSVtPwPiPZTna/RJf3cr/IkIJMZEZJfxXmMKXwcFvijLTtHnOpt94ysPpESfncCCKV6PKkrzLS48FIXV0dSkpKAi4rKSlBa2srurq6dO9z7733Ii8vT/mpqKjo6c2MiSLlABw5GGnq4D1GYldGvKKXlJEIdJgsA+XwgC+w6VnveQI6TR48lGDEoiojPE2TaGWEp2h4l9VIFGbzJoCJa3ymVNPEoIz0RJomw26FTW4rT71GiFSEgpEEc/vtt6OlpUX5qa6uTvYm6VKc6wIA1EcLRmLovgqEekao6VJ4Ojzx9xlJZprGaBt7pemZps9IFldGErzdO2Tz6tjS8CkaTlEPBCNmU289rYwIgqAp7yUTK5F6dKZxmsa0Z8QspaWlqK+vD7isvr4eubm5yMjI0L2P0+mE0+ns6U2LmxIejLR0R7xdUwxlvUCQMuL3IjebDKzhSKSB1eNjZbK9UatvNserndobEox0JrbXCFdGeLVMJMwOjjRCu8lgpKeVEYBV1DR2eEidJFKSbpOLm1Six5WRmTNn4vPPPw+4bPHixZg5c2ZPP3WPUyKnaepbowUj7MBl2sAqBqdpqLQ3HHF3YBU9yHbYwD2JvaU+mSnrBfQNrJlOttGJTNNIkmSoxwinR9I0Zqtperi0F4Cm/Jv2QSL16OpPTc/a29uxfv16rF+/HgAr3V2/fj2qqqoAsBTL5Zdfrtz+uuuuw969e3Hrrbdi+/bt+Oc//4nXXnsNv/zlLxPzCpJIaZ6xNE0sDc+AwEF5XtGLvEySiMPREaeB1e13QxB6v7GV2TSNXmlvpiPxaZq61m60uX2wWgQML8yKevueDEZimU0jij2njAC0ICBSk07leNLjSY+EYzoYWbNmDaZNm4Zp06YBAG655RZMmzYNd9xxBwCgtrZWCUwAYPjw4fjggw+wePFiTJkyBQ899BD+/e9/p3VZL0fxjERTRriB1UQreCBwpecTqbQ3HJIkKZ4R0wZWKfA9VueP9E7ApxpYzaUitMpIhkNWRhJYTbNDVkWGF2YZmpjLB0ceTmCahgeYqeIZAZC0kQEEYYTu/uQZqaysjNjkS6+7amVlJdatW2f2qVIenqZpiJqmib/PCOvASsGIHp0eP/hXMtY0DSBX1LjsALp6L03Dh+QZPHjwfc8iWGCxsLVEhj3xysjewx0AgFFF0c2rgFraeySKSmgGPoPJaGlvb3hGaEFApDJmq/NSifTTclIIxcDa6o7YBEkZktdPq2maOz344VOrcaCxE7kZNkwsy8NfLpisSPvxwv0iFsHcikCSpICAzyN6en0YWrfJgwffXgGCqoz0QDVNdVMnAISd1BtMYZaapklUQzD+ucbU9KzHPCOUKiVSF2p61k8pzmUH4C6vX5mjEYwkSTiqKCPxVdNoT5SimLgZID3NvR9ux/a6NnR5/ahvdeOL7Q245vk1CRvs1q6ZS2PmJKj15AByRU0ve0Zi7TNitVgVzwhP0yQ0GDnKgpGKAoPBSA4LtN0+ER0JaAjm84vKgTWWdvA9l6YhEzmRulCfkX5KpsOmrNrCpWq6vH54fOwEEo9nxCt6lecSJbU7Zarz9d5GvLqG9Yl56rLj8PLVM5CXYce6qmb86rUNCQmq4jWvclh5b+82Puv0sucxnKaR+4xolRGXXQ1GEjWorvooa0hYMUC//D6YTIdNMeEmIlWjDWiM+oC0ptWeMrCmqzpJ9H0kSVICeCrt7YeUyqmauhb9AzAv67VbBaV9vFG0qzsJEuw2KIP2Et36uydw+/z47dubAACXTB+C0yeWYtaoQjx52XGwWwV8sKkWT6/cF/fztMfZfZUTU+OzloPA5jeB9gZTz80xW03DvxNWQVVGeAzmFyXlvYgHSZJQJSsjQwwqI0BiK2r463BYLYYMtEAvKSNJGBlAEEbw+iX45cVdvyjtJQIpiVJR09ShmlfN5tGDV+7p5ht5d90h7DncgcJsJ247Y5xy+YkjBuLOsycCAP76+S4c7YivAiPeHiMct+g2d7I5sAp4Yg7wxk+AB8cA/1kAHN5hahvMVtNoDaxcGbFaAaccpCaioqaxw4Murx+CAAw2qIwAakVNIoKRDpNlvQAZWIn+TcDQTVJG+h/cN1Lfph+M8JOD2R4jQOjqjlXUpE/OeulOphZcduJQpUcK55LpQzB+UC7aun342+e74noetaw3tu6rHK/fa7x0c/ObwPPnAF1HgYwCABJQvRp4dxFgIlViVlZVDKyCoCgjftGv+JES8b3gfpGSHJdhVQIABsrKSCLKe5VKGhNqV2+W9rb14vwigjACP5bYLALsBoZuphrpt8UpBldGGlrDpWlim0sDhKYRgk2sqYxflLBydyMAYPbowpDrrRYBvz9zPADghdUHsLuhPebnirkVfLAy4ncbW/nu+gx482rA7wHGnQX8cgtw01rA6gQOfgsc+MrwNiiGM5OlvVbBqigjoiQmdMUeS4oGUNM00aZYG0FVu4wH8QFNz3pYGWlKcOt9Ir2pauzEdS98hz/9bws+3lynfH97E7PdnFMNCkbiJFpL+HiCkZCVuzZNk+KlhZtqWtDSxUy3U8rzdG9z0qhCnDquGH5RwiOf7Yz5uRKVpgkwsIZ7fw/vAN64CpBEYMolwEXPA45MYOBIYOqP2G1WPmp4G2JtBx+gjEh+5fuViBTJwSZmXi0vMJ6iAYCiBKZp1Lk0xoO03ijtLZb3906PH21pkColeh5JkvCbNzbg4y11eGblflz34nf40b+/7vXtSOeyXoCCkbiJ7hnh3VdjSNMEKyOaYCTV0zQrdh0GAMwaORC2CJLhLaePAQAs3lIfsym3Xammid0gDASV9uqdaDqPAi9fDLhbgSEzgbP/Clg0zznrJkCwALs+Beo2G9qGWA2sFsECq/zcfsmPsnwWONRGGdpohKrGGJURpfFZ/KpBPEPy9P5PFFlOm5IqrUvAe02kP+9tOISv9x2F02bBJdOHAAA2VDcrfsHewuyxJNWgYCROijWNz/SItfsqEHpA9YretJmNsXzXEQDA7NFFEW83sSwP40pz4PGL+GBTbUzP1ZGgNI226VnI+ytJwHs3AU37gPwhwMUvAragpm0DRwITzmN/r/yroW0w22ckoAOrrIyIkohB8pyk2uYuQ48TCd7wrGKAuWBkYJbBahpPJ1C7MaK3xuxnGryv9JQyAgCD8ljgd4iCkX5PW7cX93ywDQBw48mjcO/5kzBCnuW0/mBzr25LOg/JAygYiRs+LK+hrVu3x0OsQ/IAfYNlOigjHW4f1lY1AQDmjAr1iwTz/WmDAQBvrzsY8/MBQLbJ4VB6npHccI3l1vwH2P4+YLGz1ExWmNc1cxH7veNDwB89laYaWA2edCHPpoElwMA6SFZGaprjP0EqwYhpz4iBNE1zFfDkXODJOcC+L8PerL3bXPfV4OCjp5QRABiUz8v54w/8iPTm8aV70NDmxtCBmbhm7ggAwNQh+QCAdVXNvbot6dzwDKBgJG6KZNOe1y/plqjyPiOxKCPBaRqf6FMe52gKG+i+2XcUXr+E8gEZGGqgnfi5UwdDEIBv9zcplRxmiNnAqtOBtSDLAUFgjeUa+edZvxX4+Lfs7/l/BMqmhX/QsmmAMxfwtAMNW6JuQ2eMU3utlkAD62D5BFkb5wnS5xdxSA5oYk7ThKumqdsM/Ps0oFGunmoK32OGN/WLZS4N/z9RDeCCUVQoUkb6PVzN/c2CsYoiMW3IAADAOnlB1lukc8MzgIKRuHHYLBgod1bVS9XwNI3ZuTSAfmlvSa6x4XzJZMVulqKZM7rQUG+V0jwXZo0cCAB4Z12N6edLpIHVbrUo6Yb61m6mbrxzPeB3A6NOA068IfKDWqxA+fHs76roJrZY0xECAg2sPHUQ7wmytqUbflGCw2ZRzJpG4dU07W5faKv/5irgubOB9jr1Mm/4wIkrI0b7jOilZXoqVVOaK7/XCVChALDv2J4vgM/+BLz8Q6D628Q8rhEkCaj+Bti/EuihrrV9lUPNXTjQ2AmLAMwbo6ajp1XkAwDWVzf36tgOs5V5qQYFIwlA8Y3o9BrhrbELsmOoptFpesYNs3UpHIxslHOl04cXGL7P96eVAwDeXldjekUbazv4kA6sIgscecB3uM0NrP4nULsecOUB5/4DsBjYZSpOZL+rV0e8mc8vwi2PCjDanZcHI9qmZ6IkokwORo52eAKaH5mFl/WWD8iAxWKuSV+uywaHbFYOSNV4u4FXL2M9WQZNAcafLV8eXgUzG2DqpWV6KlXD0zS1idgH/V7gpQuAF74PrHgY2PkR8L9fmOpVEzNb3wWemgf85zTg2e8Bf5sKfPUPQOw5v01fYtUe1rpg0uA85LjUNPzY0hy47Ba0dfuw90jsLQvMYraBYqpBwUgC4Cev+qBVqdvnVw5YZs2AgI4y4vcq7ef5pOBUQ5Ik7KhrAwCMLck1fL8zjimF1SJg75GOsGbgcMTaDl5PGQHUCqmO2l3Akj+zK0+/B8gpNfbAQ2aw31GUER5EASY8I5pgRKuM5Gaos2HiSdUoA/Ji+L4KgoCBim9Ek6r58NcsoMsoYMbfnDJ2eQRlhM8GynUZ81oFf5ZAzykjPE2TEM/IR/8P2LsEsGeyUnFHNkvv7fwk/seOxLf/AV67HKjdANgyAGce0HwA+PR3wO7Pe/a5+wir9rJg5ERZ1eXYrRZMHpwPAFjbi74RtbQ3PU/r6bnVKQaXyGuCKhmqj3ZBktiqtzAGZUSvtJd3fPX4xIS0/k409a1utHb7YLUIGFGUZfh+2U4bRhdnAwA2mHSh8w6sptM0Op4RgAeXEiZtuAvwdQHD5wLTLjX+wIOPBwQr0HqQza6Jst0Oq0WZORSNcMqIIAgJKe+tUqb1musxwinK0ahKAOtUu+4FVvJ8wdOsEskuP3aEYIT38DBqYO1VZSRRnpFv/sWM0RCAH/wH+P4TwPE/Ydctf6jn1JFD64GPb2N/T/8Za9r3q+2qoqdNpaUiPg+w9H7gme8BB9ckbTO4MjJzxMCQ66bJJtb11c3qhaIop8RWsCDQ05HQ7VFLe0kZ6bdwk+aBxkDZueoo+7INGZhlei4NELqy84k+OG1WpTInXAv6ZLKjnqkiwwZmmi4xmyw3R9t0sMXU/RJW2isHI8U5Lsy3rMXQ5tWsq+pZjwJmPj9nNlA6if1dFT5V0xGDohMQjGj6jADqSfJQHOW9vOFZLMoIoA6OrG3pAjqOAB/+hl0x91Zg5Mnsb7v82BHSNLzpHK9uikavekbkxUdbty/2wYR7lzFVBABOvQMY9z3298xFciffb4ADKxOwtUF0NQOvX8G6B489E1h4P5A1kDXuy2c9MtDdmvjnTRQ1a1k11tI/s/fn2bOA7R/0+mZUH+1ETXMXbBYBJwwLTUdPC66oObQeeHqBnBI7k72GRyYCa55JWFqMSnsJDJWrDqqCKkF4cDLUZFUCR68DK6CmEZprdgK7PwO2f8h20hRI2+ySg5GxpTmm7zu5PB+AeWXEbIMsjl5pLwAMyrLg97YX2YUzF7H+IWYZIq8yIwUjMaxkwikjABTfyKE4jJVc3SuPMRjhg/VqmrpYINLZCJQcA8z5lXojA8oIbzpnNE3D3wObRX0vxR4yZGY7bYpiE1Oq5uheFhBIfmDSRcDsX6rX5ZQC037M/l7xaPwbq0WS2Oykpv0s8DjvscAg2yWnVbvNLQZ6jf0rmRpyeBuQWQgMPYkpl6/8GNj0Rq9uCldFJpfn6S6CeEXNjrpWuFf/G3iqkgWY9iygcAyQMQDoagLevxn496kJUXioAyuBIQOjBCMGylv14Gkap1UuH9YEI5dbP8H0/50GvPgD4JVLgH+dDDyzkAUnSTSgcb/I6OJYghFZGalpCfXDhAm0fH4R3V7ZBGrWwKpTrQQAx9W9gmGWejQKBcCcW0w9pkKF7BuJYGKNpQpIgtz0DIGeEQCaNE3sykiNrIyYmdarZbC8DQOrPwW2vMXSVef+A7Bp0pQ8GIkgU/PZS7w9fzT4e2C32EMu6wliTtV0NbGKma4mYPBxwDl/C1XdZt7Ifu/5gikZiWL146xXjtUBXPgcOyFqccljG9wpqIzUfMe6H/u6gJGnAou+AS5/D5h2GQAJ+PxPvXrc436RmSNDUzQAO0YX5ThRJB2F7bM/sG2ceD5w0xrgxm+BX+8CzriPtQE4tI4FJO8sAja/xVSUGF4LdWAlMHQg80Yc7fAEzKs40MjTNDEGI/LB1GVjBz6v6AVEEVd3/At32Z+DBSJQOBYoO5YdYKpWseDkgVHAGz8FDn4Xz8uKiZ1xKCNjS3PgsFrQ3OlF9VHNCfXQeuDRScDn/xdynw5N5Ui8Bla33w20H8aIbY8DAP5u+THgNP86AKjKSP0WwN2me5NY0jQ8QLVYNMqIrADwKo9YO4N6fKKS+iuTH8ssg/MzUIgWXFz3ILvgpF+E9mVR0jT6QZPPLyqfq2llRLAFdKbtKXiqxlR5b3cL8ML5wJEdQM4g4Icvq4GZloEj2X4t+Zm5NRFUfwss/gP7e8GfgcHHht7GmaLKyAH5uOZpA4bNAX74EkstWW3Awr+woKq5ijUa7CVW82BkRPimjkMKMnGb/b+w+jrZ4uSCp4Fc2bxttQMnXg/cuAaYIs+0Wv8im3v11DzgidnsuGcCHoy4KBjpv2Q7bUqvEa1v5ICslAwbaNzIqYWfLF1WORjxe4Fl92NO42sAgE9KfwYs+hq4dgnwiw3AjOuZK77rKLD5DeA/84HP/gj44h9cZgRRlLCznpWyjSkxfxJ32qwYN4jdb2NNM7uwrR545UdAS7Vubpif0B1Wi6lx90AYz8iXD8DqbcdGcThe6JwBnz/GE1puGauMkESg47DuTbiB1Yyio9uBlSsjygkyNmWkrqUbksR65xRmmesxwinLc+E++1PIk1qBkklA5W2hN4qSpmnrVj8Xsx1YLZbQ96UnKDOrjHS3shPqobWsqujSNyNXZ40+jf3etTjOLQWbqfT6lYDoAyZ+Hzjhav3bKWmaFFJG1r3E+tN0NQHlJwCX/DcwgHNkAsddyf5e/USvbNLRDo/yuXNviB5znLvxfetKSBCYN0fPd5ZTAnz/ceAnn7KgpHw64MgBGrYC/zoF+PIBw+n3Tt70jNI0/ZvgVI1flHBQXt2b7WTJ4QfTDBvb+bzN+4HlbMX5/7zX4PWMC9UveG4ZsPA+4Na9wFUfAcdcwE6EKx4BnjunVyTMmuYudHn9cFgtGBajGsRTNRsPtrAg6tVLgVa5EZqOrB+LusAJCUa6m4A1TwMA/uL/EfySRe3CGguyogWv/glLGfAXo2ckWAFQlJHmLjXN5fcByx5gDbWiwP0ig/PN9xjhjKh+E/Ot6+CWbPCe+0To/B4gqoGV+0WyHNaIQxa1cHXIKlhDvDQ9AR8DUddqIPBrrgaePgM4+C3gygcufxcomRj5PqNPZ793LY6vGZkoAm//jFV2FYwEztZJC3F4mqY3lBFRBHZ8DLx5DXD/MODxk4Cl97ERAQ3bgB0fsePWuzcAohcYfw573/SUyhOuZunAAyvYzKMeZs9htuAanJ8RcSFx0VEWHH1XcFbkrs0Aawfw/ceBqxcDv1jPZlxJfuCLu4GvnzS0Xd3UDp4AVJMqV0bqWrvh8YuwW9WSS7NwSV5J02x6HRB9aChfgFf9lfqNz6w2YOgs4IL/ABe/xKTX6tXA2udj2gYzcL/IiKIswyeRYHh9/sbqJuB/NzPTFzclekLTHbG2ggd0SnuP7GAHvpGnYnfWcQDCT2M2BF/B+fRPWJ3ytmcmqJqGKyMdHj/r09HVBLz0A2DJ3ayhVnNVxMfWBiMx0bgH2UvvAAA84LsYtc4R+rdzRE7TmK2kAQKnGWtn9vQUhj0jVV+zFW7DFiCrmJ1QB02O/gRDZjJlraMBqNsQ+4aufJRNkba5gIueU9UPPZzcM9LDwQgPkP57MbDpNfY9rd8MLL2XqSD/PBH47w+BfctYSfi8/8c8Lo4wCnNeOTDhXPa3wRN3POxpYMHISLkVgS61G1HWvgVuyYYXMi8z9wRZheyzmv9H9v8ntwM7P416t04v228oGOnPSBLG5LLVHC/n5X6R8gGZsMa4yuQHWMXA2l4PZA5EY+W9AITozcHGnwWcLM9U+eLuHl/x7IjDL8KZXMEOiMce+i+w4WW24jnrUXalrjLC3iOzlTRA6MnK3d7A/pj/R7WRnckGbAFwVSBMmiwmA2uYqb3we5HRug/TMhowTdgF72d3A0/MBfYuVe/cFrl/hGJejSUY8fuAt6+D4O3AOusx+I9/YUjfHQWDyohRvwgQGIxwZaRH0jSSBBzZjaEO9l0P6xnxdAKf/A545gwWUJQcA1zzBVA21djz2BzAiEr2d6ypmupv2H4PAN97QC03D4eijPRgmkaSWGO1Ta+xRcaM64ArPwTOe5yVGg8czTwgmYXArJtY+vnk30bvfHzi9ez3ptdZWqoH4crIyEh9lNa/BABYLB6Hra2x+a9w0s3MoCuJzEvSuCfizeNpB9+TKqJR0rM7SirRVge8eTVu2L8cX1v+Hw40Mnd1VZyVNIDGMwIWzHgFAfjeAygsKQewHUfa3fD6RdgjqRAnXM1SD0d2Asv+Aiy4J+btiQY3r8biF+GMKsrG6faN+BVeYBcs+DMLqt67kfVG8HkCKjPiUkbk9zfDloEuXxd7f4+5ABg0GcW5awC0xKeM2CJ7I2Ip7eUnWEEQ1HRE9Wpg+VigsxFvA4ATAPcu51UwWb65CuDBVhhqmtl3NqZKmpWPMBXLmYtnB/w/SB2WCMFI5PfFbCUNoBkgKFh7xsDq8wCr/g5seAU4shMzBAuetB+L/7WcCrSPA7KLmVH58A5gy9us1JQ3D5t8MXDmQ+bN0KNPZ9Uvuz4F5t1q7r7uNuCta+Xy4QvlqpMo9EZp71d/YyMWAODcfwJTLpavOAmY+qPYH7f8BBZs1W1in9HMKDOk4mA3V0aKwigjPg+wkfn63vDPxcEmljY13WtKEIAzH2ZBSNVXwOI7mHk3DLyqMJZqmnPeOQc17TV4ZsEzmFo81fT9EwEpI/GwbznwxBxg/3IAwGRhj5Km4ebVWHuMABrPSBOT1715g4GJ52NglgM2i8AWaZHGtQPMtb1Abmn+9ZPA4Z0xb0804jGvcmxb38Jj1gdhFSQcGPoDYMbPWG0+xxuojsTa8AzQvL9yOahHEJgkDChD4hraekMZMX7w4MqIVbDCIpd9+hu2sX4e9ky0W3JwWMpFVcmpbLV5/VdsVQ6wFXoEeH8S02nFxj2sIyYAfO8BOAuHyo8XYzCSisrIF/8HfH4XC+otdgiSiAXWNfgH7gceHA3cUwbcW85KNFf9gwUiuYOBH70GnP9UbFVZo+az3wfXAO36JuiwfHw7m4qcVwF870FjTft4NY27tWd6Fm3/EFh8J/v79Hs0gUgCEATguKvY32ue7tGeS3sOs2PQqHBpml2fAF1HIWWXYrk4GV1ev+5Ed0PYHMBZjzCFePv7rHtrGDplQ3wsyoinuwU+0QebFJuKnwgoGImVTW+w4VYdDSyvCaBAaENtSxc8PlFT1htbJQ2g8YzILcW9Q2cBggCLRVBOlnVG3PyjTwNGL2B+iA9u6ZEdVRQlRb4cHSmXGv4BWAvsN38KO3z42H8CXiu+mR1kbA5WugwA7sDBU2orePM7IO8rkikbTN2uXKBoDAC1sVxc05GjeEa4MhJLNY0gSbBufotdllnATnq3VeMvUz7GCe4n8OqIP7OVpisXyJInikY5ocXsGfnsTvbdGjUfmHyxEsyED0Z4mqZD97sYi2ekR5WRwzvU1fyCPzOT+A1f47/SAuwRB7FqCR4kZxQw/8LFLwE/XweMWRD78+YNZoMFIQE7THQZ3bWYteCHwFrMZ+Qbux9P00gi4EnwgLeGbcBb1wCQmFo768bEPj4ATL6I+Wwad0U8acdDt9eP6ia20AyrjKx/GQAgTLkYhbnsu847G8dE8Ti1YuiT34Y1NMfTgdXd3QwAcFT1QNdfg1AwEgurHwfe/Ck7AE88X/FlFFnbIUrsoB5v91VANVi65C+fN0ttsFOSpw7MM8T3/sLSBvuXMxkzHKLIVjAf/Ao4us/wtja0ueHxibBaBPMyf+Me4Lmz2MoTwLahP8YN3l9gc70mEODmtSDfiJKmiWEeA0/TZHazA69HY+5TPSPxpGmMKSNmtp0HqNZtH8AiB6n+oSexk57VplRu7TuieZ+yi+UnDK+MiKKk6b5q4vM7sArY9j8WkJ9+NyAISjATNU0jiSz1FoSqjMTwvrQchLWriV2WCGVEkoCPbmVlsWMWso68rlygeBxeKLgJp3oewuffX8uacN1WBfy/fcBFz7PUol4lkVm4MXPLO8Zu73Oz7QWAE28Ahs02/lz2DNUsnkjfiLcL+O8lLMAZNoc1++oJnDnApAvY39890yNPse9IByQJyMuw688b6zjC0moAMOVHSifjsPuCUU7+LVOuajewZoJBiKIUe5rmyG545cDdMWxOfNsZBxSMmGXDK+qQqRnXsQFXeRUAgEF21byaCM+IoozIi0e+kgeAkhwejBg8WQ4YpuadP/1dqH9AkoANrwL/OJ51dP323+zHILykuSzfFdnDoqW7lRnsHj+JzZmwZwFnPYLOU+6BCAu212kOiA5Z5g4KRo7K02EHZMUwiFA+WWXKq3MP1FV6ca7JYE8PpbRX/0AUi99F6cC69W3wQ45oUw1yPEW2vU5TeZRdIj9h+GDkSAcLJi2CWrYaFVFk3yUAOPZyoHg8ABgIRjT7hI6JlXtGckykaRRlxNcNqxzgJEQZ2fYeMwFbncAZfw64akIZC143NviAorGqspBIJpzHfu/70pgxc/U/Wbv57BL9Hi+REISe6cL6zb9Yyih3MKuKsRr/XE3DUzVb32M9ihKM1ryq6wHZ/j4LXAdNAYrHKYH9wabwc5gMkVWo+n6qQ6eBd/vUwNt0Nc2OD+CWX4szI3wTt56GghEzHFoP/O8X7O+TbmYRvsUCZDLFosjCvqjPfrUfbfKJpiJGZUSUROXE48ofBkBueiZTmmcyGAGYO71oPPMXPDaDjRFv2M4OdM+dDbx9LXBU49juOGL4oasUj4zBtNSuxcDfprGmPnwy7g1fAcf/BOPkapz6Vreaa1WUkUD5mHtmYpmK7JNTPpmy8uQR1VU6D/Ya4hlGyIOEMMoIz/GaKe1VDKySCEvRuIDLACjv3f4jHeiWZVs1TRM+GOF+kZJcE8Hkjg9Ym25HNlD5W+VirowF9DvRYrWrK3CdQK21m6dpzBt7LRL70V4WF8sfZr9P+jlQEFiqPFEORrYe6sHqk4EjWfM4yc9OdJFoPcR6ygDA/D9FLuMNR6K7sHa3srJyADj5d6xzak9SNpU1DhO9zLuTYLh5NaxfZNv/2G9Z0VKDkTiVEUB973T2mU5NJ2qXyeaP0vYP4JErPh1W88fRREHBiFE6jrAGXL5u5nI/9U7VFJbJpjbmga1Gl+5gufnzpw2OeYKi36NG0i65YY5WGSmW0wi6vUbCYbUDFz7DApKuo8w/8s8ZLBDZv5ylcU69A1hwL7u9nEc0QpXskTEUfO1dxoZbdR4BBo4CLn6RzZkYMAwAUwq4orStVj7Qhw1GWABRmG1eEvc3bGXP52AHFo8mZcDTNEfaPfDG2oXVzoORMJ6RGMqSJa4ASBKs5dMBBCoARTlO5GfaIUrqgdNImiamst6v/s5+z/gZ6yQpwwPlbq8Y3rjHTcl6wQivpjGjjMgreSsAqxzEx62M1G0CatcDFjvrbhzEhEE8GOnhvhwT5VTN1ncj327xncy7Uj6dVfDEQqK7sK56jPURKRwT+zaZZe6v2e9v/wN0NCb0obl5Vdcv0tXMjm0Aa9IGdeBkQoKRCNV5Sit4u8Vcw8L2w/BWf6P8S8FIquP3sXbKLdWsi+H5/wqse89k0laWrxmQD4Q/P2UUHrhwSuxPue095W9X0QQAgcFIaW4MygjApPTrVrCZDjllrKY/fwhrE73oazZdNa+c3VbOvRuBKyNRu80eXMPyx343MO4s4IbVwPizQ9z+40vZQTE0GAlM03BlZGAMwYi3YQsAIKNgFHtoTTAyINMBu5Vt0+FYK2qiKCPcM2ImxyvKao5gy4BF7uKpVQAEQcBYOVXDm9AhSw5GIhhYeVmv4Uqa6m+YXGx1ANN/FnCV02ZFkWywDjtBWKmo0UnTcM+ImaZnB5jxzgKNMhJv07O1cnn5uO/pruh5muZQSzea4unUG40J32e/9y4Nn6qpWs16d0Bg/rBofTnCkcgurB2Nqjpx8u9YQ8beYPTpLE3i7QBWP5bQh46ojOz6lCkyReOAwtEAkLg0DaAxxIfuU1wFNdMmAACw82O4NYde3tMqGVAwYoTFdzDlwJHNhlsFu9PlNI1NdOOaGaV49qoTcMvpY2NudgYA/nUvKH+75C+hXjBiqJomGKuNrWZ/tQ34f/uBmzcBFz4LDGAlmcrrS3Qw4u0CXrucHSRGVLLBUWHyx3xGzbZa+YTKSyPDKiMmI/pD6+HrZGmoTDnY80t+xdTKKpZ4y+8YUzVRPCOxND0Tu9jJyFJ+PKzy9yJYAeCpGt6EDtlymsbTFnZbTE/r5arIpIsCVBGO6hsJcxCOUN6rVNOYKe2VqyesWUWKMuIP01TNEN5uYOOr7O9pl+veJMdlVxS8LT2ZqikcBRRPZF4EPfO56Ac+lNWAYy+P3no8Ekp5bwKCkQ3/Zftr6SRFKegVBAGYK/vjvn5KP4BrrgYOfGXqYUVRwl7FM6ITjPAF5PizlYv4fsB7jcRFhAC+M9aGZzs+ZC0N+FNYetDPEwUKRqKx8TU1uj7vcVZmFYwjixncAPzu5GJUji2O7zmP7IavepXyrzKbRhOMlGlMgqKY4FJdPlrcxPjyKnkOT0TD7rf/ZnNmcstZ6WOEaoPxg6IrI35RwtEOpjoUmVVG1r0Avm7O0ASXWnWET66NWWJVlJHQYEYUJfNNz0QRorxitQybrZSwBre1HyurSoqJ1ZmrfD/D+UZqZAXDUJrm6F7VvxCmRFMNRsIpI+G7sKrKiMH3paUGYsM2AIAltwwW2Y/i1/qfzLLjA5amzC0HRp4c9mbcN7Klp1M10+XhdsvuC/VyffcsSym58liaNR5c+ex3ItI0/OQ87fLYlZpYGfs91l/H08YqH3nQK0lM8XpsOvDMQuaZM0hNcxfcPhEOqyW04szTCez6jP2tCUb4cbrT40dTpxdxoQQjofsUL+s1ZV71dAJ7lijBiMPiMN+YLYFQMBKJ2g3Aezexv+f8GpgQJroXBEUdQWcCcpRb3oYf6peCS2fawW7lAzJgtwro9oo41JKAfKQWJRhpMtSTpNPjU9IlYT0j3a2qGbDyNsAZuRcJT9Psbmhnng0ejGj6jDR1esDjsAIz1TR+H7D5TfjkHS/Tpm6zNhgZXsiec9/h0Db0hrCHD0b4wQMwoYxUrYIoB6SWwcepHViD+g6MLWXv7U4ejAiCxjein6pReowYUUa++Tcryx01X6mgCWZwNHmaH1g9OsGIWc/I9vfh51VGtgxY5UBHPLzD2P314CmaqT8CLOEP8IpvpLYHlREAOPYKpjB0t7AGbJz9K1jbeUA2iMZZDZGoLqyttWrVx/iz4nusWLBYWPdSeyaw5ws262bN08BLF7JuzjwIlsvjjcDL5YcOzAydvbXnc+YNyx8ClKqzh1x2q9ITKu5UjS28MhJTK/iqrwBfF9w5gwAkN0UDUDASno5G4BXZsDrqNHXGSzh4TjkRhqmt78AvxyJWwaqYirTVNDarBUPlhmp7Yz1ZhoOvjkRv2PkhWniKJi/Djrxwef5V/2Cm2cIxwJRLoj5m+YAMZDtt8PhF9vp0DKyNvKw3025uMN/Bb4GuJvhlZcZldSkqg7aiZnghO6nvOxJjA6gIU3t5isYiMNOZIba9Bx52WG2usM29eHlvXWs3WvhqjAcj7aHljpIk4aD8GZZHU0b8Pjb/Awg/ih5qILcn3HczjOTs84uKYmTYM7LrU4hyYGmz2GCRzbHikV3G7h9Ma60602fajyPedGIZ81j0aJoGYAHRQrlS5rvn2ODLLe8AL13EToKjTgOO/2n8z6PtwhoPXDkrn84miieDITOAH7/BzNJ7lwLv/xLYvZh1M+XeGBPN3SL24dn5Cfs97qwQ/1vCKmoMLG5MBSOy2dZTcQJ7+J4suTYABSN6eLuB168AWqpYOd8P/h1xdQQgccrIkd1A/Wb4ZanZKliVPF7wyHs+qInXvicMRxarIAAM+UZ4T5WwfpGuJuaqBwwb2SwWQRm4t622VbfPiFrWazKi3/kxAMCbUwqAncD4qsDtV82mijJyJMZgL0KaRum+6rAZl0Z3fwZRVswECGHbnue47EqaROnVophYQ9M0jR0etLl9EAQD1VD7lrGqnIwCtV25DtzgxyechqCkaQIP0Lz3CnsdBhQjTyewf4WScrMIFljl6ih/Y4zByJa3AUhAxQylwiscPE2z93C7sjrtMYbOZHNmIDHF9vUrZP/VyawiLREG0UQZWHnljyZlkRSGnQRc+iZQOJY1XKu8HbhuOZtlA+gO3wxHWF+VJDH1BQBGnRpyP75P7W+Mc9EYIbWpeEbMpGn2ycGIPLyRlJFUw+dhO3kkw6oeiQpGtrGd2FcxAwBgtajBiNYzAgAjZBNVwpURQQhM1URBMa+G84tsfpOtQIrGqx0lDTB+kDYYCfWMxB6MsFWMT24GFvAea9SnEXKwt/dIR2zmswjud9MzdZoOAI27FQUgZGpvEGPDmVh10jT75WCrLC8jeik6V0WOOT9i86pR8nezprlLea0BhDGwcvNqpsNqrN/J/hWArxuivP9ZBSssstlZ7GiITanc/Ab7fcwPot60ONeFwmwnRAnYVtfD6gjApu9Ov5YpDtmlbLDjD19WV83xkojS3o4jrIkhED613ZsMnQnc+A1w5fssRVwyMWx1XiTUcQlBx7nDO5gXzuYChp4Ucj++L+wOF5gbJYLSaloZ6TwK1G4EAHhK2eyqZJb1AhSMBNJSw0Y17/yYffCXvBI2Jx6CEowYbxSmi7yi8MurTptgCx+MFPKTZYKVEUBTUdMc9abV0Spp1v+X/Z52qbGBXTITBmkkcJ2DBy+5LcwxEYw0HQAObwMEK/xyfxitMqJN0wwpyIQgAG3dvtgGXUVSRnhZr9GGZ3s+BwCIcmop2kA4JRgJKe8NVUa48sOVoLB4OtWmTpMuinjTAVkODJR9PLrKHf88g1Z5pofkya23/XKZs0WwwCofVP0AcGidscfhHN3LGrkJFlbubgBe4rulpodNrABbJHzvAeDqxcCvdwAX/AdwxN7lOYREKCPbP2CeotLJUZWlpCGrZ8GDNyMRVhmR900MnaUG2RpGlyQoGIlQgdatmOENHk/2LwcgAUXj4HayfZGCkWSy7AHg7evZzwvnA48ew3KdVgcb1TzcRJ9+uddIXMrI0X3MNCtY4R8+F4C8arf2sjICxKaM6AUjh3cCNWtYnnZy5BNYMMcMVisVJCUYUducN8oBwkAz5lU+N2LIifDJDn+bYFN2RG2axmW3oiyPHQBiStVE8owoA/4MKiOyDCzKB6Roysi44GAkQuMzw8HIjg+ZwpU/FKiYHnWTRxZHOAiHVUZMVNJIkiYYYYsGq2CFVU6pioLAhqaZYfOb7Pfwuep7FoVjh+QDAFbuTmyDraSQCM8I90/0ZjmvWeJSRoICjt1yMDIyNEUDAKNlD9fuhvb4Kh8jDN7kaRqX0WCEN2cbPk8x7TstlKZJHrs+BTa8zH72fM6i+aGzgUvfipgP10VeZccVjPBSuGGz4XOxA7lVsMImsAOzNoUAqJ6R2pZufSk8HkwEIwciBSMb2ARLjD7N8MGdM6YkB1aLgKZOL4765B1Fm6aRlZEiM8qI7BfBmAVKUyybRQ1GPEGD27SpGtNEUEba3SZWMn4fsPdLAEHKiCW8MsKrPLYcamXVSBFawvNc9rBowQhP0Uy+yJDCNdpQMBKHMtK4G2g+AFgd8A9kjeu0QZqf38YMm+Rg5JgLDN/lZLmUf8XuI/D4EjQpOFnEm6YR/cABeWJuhJLopGMyGPH5RaXfUICB1dulpqR0/CIAG5Zqtwro9PjjG5jH9xnRBwSdC3iaJtNomkb2i2DEPEUNJmUkmUy/BjjtLvaz4F5g0bfAVR+YU0Q4SprGwDCrcOxazH6PO0udQhpBGcnPVKXwmE2W4VD6DTRHvJkoSjgo9xgJCUZEPxu+BxiqoAnZBLtVOaHtbZFXFLqeEYM7kacD2Lec/T3mDMUQbBWscFj0g5G4TKwR3O+dZhqe1axhTagyBkCUjc3aNI2eMjKyKBu5Lhu6vH5sr23TVNPoKSMsIBheGEHud7epJj0DXgpANbHqByP6Blal4ZmRShqucg09SXlfrBar+r4IAMxU1NRvZSk8q8OU8XLS4DwUZjvR7vbh2/1x7P+pQLxpmrpN7L6OHGDQ1IRtVsIJM14iHHWt3fCLEhxWS2BPowMr2f6dU8Y6r+pgs1owojABqRpbUBCkoUtWWg0ZWFtqWJAuWIChJylqMAUjyWTyRcBJv2A/M28AisbE/li8vt/EcLkAuluBKrnR2ej5ymo3kmcEUFfuCa+oMaiM1Ld1w+MXYbMIGBQ87XXfl0DbIRbYjF0Y02bw0sldTaHBCE/TGDawVq1ibejzhgCFY5T3M8AzEi4YiSUVFlEZMWFg5TLwiErFSBugAOgoIxaLgGOHss/wuwNH1cm9QQZWSZIUAysvZdZlzxLA7wEGDA970A0mcjASWRkxVEnDpeZR6v6ifV98EIBGE43PeAXIyFOMmdZlLBYBlWOZ8rRke/j5P2mBUw5GvB1MkTPLfjnYHzqr99q/xwL3jBhURrhfZFC+K3D2y25eRXNKRLVwlOwb2dXQFvY2UbE5Ad5/KjgY8fLZNAaCkX1MZUXZNCAjX1HcKRjpK8RbTbNvGZPfCkYCBSPUVXuEahpAbUuccN+IwWCkWlZFyvIzQnt98JTIhHMidluNBPeNbGuUT7hudWfmaRrDc2m4KjJ8LiAIasBnsSnqk1sMnCMTlzISwTPSaab76t4l7PfIUwNOuuGannGOGyIHI1XNaprG3RqwPfWtbnR5/bBaBP3+CRz+WY5daNiEzIORA0c7Q9MXYcoUDTc8E/1sHgsADJutqEMB7wsAtB7UbaymCw9GJpxn7PYaThnHlKcvdqR5MKKd9BuLb0TZx2JQl3sT/v0zGoyE84vwE/vIUyLef0wx843srI9j0SgIYX0jnWYMrNXyfiNX/nBlhEp7+wo8GOk6CoQ5OUSEp2hGnwZAXe1q+4wEe0aAOD0NkTBYTcMraSoKdE5kfEU/6rSYN4MrIxsOy8GIfPCQJMn8XBq+ahs2G4Dat0WrjAS/x1xe3d/YYd58ZqCaJjtaNY2nQ60IGT4XEu80isjKCAAcJysjaw80Mfmdr3w0JlZeiVUxICN8Ka3oV02JY86IvL0aSnNdyHba4Bel0B4L4Qys3TxNEyVIq9/CUleOHKB0khKM2ASb+r5wKd5IW/jDO1mKxmIHxhp/jZzZowthswjYe7gDB+LtJ5FMrHb1RG02VeP3qfNehqV4MGLSM6I71bqrCajfzP4eOjvi/UcrykiiKmoCjyndZkp7q+TOuHL7CK4GJ3MuDUDBSOLIkA2skhjVZxGCJAG75bkG8olba67UekaC+13wk2XY5lKxYlAZ4V0Fy4Nr75urWCWDYGVKRIzwXiP7W+XVuOgFfB60dvvg8bMTkKE0TXcrcGg9+1sORrSpMO4Z0VbTAGw+jd0qwO0TUWt2YF4EzwivpomqjBxcwxSz3MFA/pBAZcQS3jMCAFMq8mER2KqutrVbd3rvfsUvEsG8WvMdK1l35jH53SCCIISvqIlXGeGmwSEnAharvmLEe6sYMbHK/X0wYp763TdBrsuO44ex+32R9qmaGCtqajewajdXHmtdn8qYTdPojUuoWg1AAgaO0h0WqUUxc9e3xTcwL0xL+HalVUCU40lXMwu6ATUYkQ2spIz0FWwONd9qNlXTsE1tmjOMSWd8+JlWGZEghayCuTKy70gMK/dIGA5G5DbiIbX3cmqh/HhT+fdgclx2DC/MQic0O4qnHY2yeTXHaTOWJ61aDUh+1vcgvwIAAlJh4appbFaLYsw17Rvhyojfw9QFDR1yNU1UAytPRQyZCQhCQDoimjKS5bQpAwfXHmhWG59pWsIbqqTZ8RH7PerUiI3O9Ajb8CmcgVUZkmcwGJGDI/6+WC1W9X3JMhGMbJUr2Uw05QuGp2o+2xbacj+tiNXEul9OWQydHb1jdbIxq4zopWmU72Boo7NghhVmwWYR0OHx41Ask9Y5YRoptsjG77DjODgHv2W/C0YoxwMysPZFYi3v3S2naIbNUb5sAdU0Gvks2DdSIZeNdXn95lfukTBYTaMoI8FpGt4IKEou1QgTynLhgw0+Qd5ZPO1Kimag6RSNKh9r0zThghEgjhk1No2h1xeouLQbbXpWJcveQ04EgAADa6RqGs5xiom1STWxaoIR7jWKqIxo/SIm4b6REHk6SgfWiMqIJKnpAPlEwPeXgPeFp06PRAlGju4F6jYyFW/smZFvG4EzJrKBY6v2NKI+kftibxNreW+6+EWA2NM02kXXfuPBiN1qUfaxXfVxmFi52hpGUYwajPDhhRUnKhfxYx4FI32JWE2sPEUzWvVW6FXTAKHBiN1qwSjZHLXpYLO5542EooxEfsyDzVwZ0aRpRL86aCxMIyAzHCP7RrosfNJrh/lW8FGCEb0OrBzez8W0+SwgGAk8OXUaaXrm9wHV8kpGVgD490IQhKjKCKAJRqqaAHkWD9rqlOu5MhI2GGmuAhq2sjJAs713oMrTIQfgcGkaRRmJ8L4c2cn2MVsGqwhAoMdKSV/x4ZXRlBFuXB0+Rx14GQNDBmbiuKEDIErA/zYcivlxkk4syojfp57ohkX2T6QESpom+j4tSZI6JI+no91tLC0FKGp2NBLSiVXZb4KVEYPBCFdaNU0LlaZnlKbpQ8RS3uvtVg1FI9QmQcrB1WKFzaIemPVMrFMr8gEA66sT2I6aByPu1rAlfj6/iNpmtlNUaIORmrXsQObKU04W8cAratpEtfGZqWCku0Vz4FAPlDwVpg349JSRiYPZwXmT2XbfVhvAP7ugYERtehbhpFu3kZVYuvLYXB+oyohVsBpSRo6VK2q21LTAmykrI221AAC/KClDDocNDBOMcBNy+XRV+TPBRPmz29UQNEguWgfWSMoIl8crTmDpUUC3tNfPfVyNu5iaEg7e6CyGKppgzps2GADw9rqauB8racTiGanfzE7szjygeGLPbFciMaGMHGn3wO0TIQhAKW9fUP01S/vmDwHyyg095Siloiae8l6ujKj7jc8vKkprxGDE72P+L0DxiwAaZcRCykjfIRZl5OC3rPdFdglQOFq5WEnTCFYIgqAEJHrlvdOUYCR6t1TD8NUREHaFVN/mhk+UYLcKKNZ2QeXNsUZUJqTXwLFDBsBqEdDq58GIyTTNgVXMWFwwAsgbrFysNQmH6zMCsKZWABvY5/ObrJTSOXgAatOzrEhpGmUVcyJgCWz9Hq0dPKd8QAZKc13wiRL2e+TPVFZGapq64PGLcFgtKAsuWeTwdFuY7pLRKM11oTjHCb8oYfMhzfdIKa1UlRFJkpTeMfmZkYKRwBQNoPGMaIO0jHwAAvv+htsnD+8A6jexoDEOvwjnrEmDYLcK2HKoNb6TTjJR0jQmgm/tituSBqcVPs9HNsRHgqsiJTkuOGzya1O+g8ZVoPHyiIZNNXG02uf7jaa0l1egAUBupP489ZuYEunMC+gVlNaekcceewzDhg2Dy+XCjBkz8M0334S97bPPPgtBEAJ+XK4ETZhMNWLxjOyXWycPmx3Qv0ErOwOI2GtkihyMbDrYAn+iTKxWm7pCCmNiPSiX9Q7OzwhsBKS0Gk5MO+gspw2Ty/NUE6u73ZwyotTVB1aCBHRg5Z4RnTTN0IJM5DhtcPtE86V5SnlvoGekw0gH1iC/CADdfhqR0jSCIOCkUUyxW9csb0sbSyGs2ssUvAllubBqPz+O36tpLBZbMCIIgvL93FDdrF6h0/SsudMLt9yPpCQ3wjHigNwccMhMdVP1lBHBAuQxs3LYVM0meULvyFNjUn6CGZDlQKXcHj5t1RElTWPipMkbNmq+qymNXaMERhmWF9kvYry6bJqsUu6oa419fIc9dHHT3MmOWTlOW2ivJy3V8nm64oSAgDFt0zSvvvoqbrnlFtx5551Yu3YtpkyZggULFqChIXw5W25uLmpra5WfAwcOxLXRKUssLeF1vAxAYKUHoAYj/HIto4qzkeWwosPjj6/DXzBKr5EwwQg3r2pTNN5uVo4KJLTXwIkjBqJd0nhGzEzs5dtTHjjcTesZUZqeBZX2AqzDJk83mE7VhGlS1BGt6ZkkqatNzQFPhI4yEqWvzZzRLBhZXic/l6yMLN3BSnz5bJUQDq5hUn1GQVytvXkacZ1eMCJ6lTkbtXKVwcAsR/gKqbY61shMsACDj1Mu5u+BVhnxS35g4Eh2A71gRJKAzXIwMsn4LJpofF9O1by7riaxFW69BTevdxk8jmm/q5oAMaWxOdS+O1FSNTXN6qILAFtYHFrL/jYRjJTmuVCW54IoARti9ffpVKG1KMMljZpXZwRcnLazaR5++GFcc801uOqqqzBhwgQ88cQTyMzMxNNPPx32PoIgoLS0VPkpKYlck5228Mm9OpNRdfF2qaVWQb04zCgjVouAyeX5AID1Vc3mtjkSUSpq1GBEs2Ko+U5NO/ETQQI4ccRAdIKtCrxdbVhb1RT63HqIfuZhAYDyEwKuUjwjUdI0gJqq2XTQZDDCO89qlBFJkqIrI037WOt2q0MJBCRJUpQRAYIhZQQAZo1iQfJXDbzp2WF4PW4s38WUEd7KPARurB55SlylmlN1lRFtAMu+R7Ut7Hdp8FgBLfyzLBoHONX29VqPVYCxVx6gh/qtoY91aB2rpLFlAGO/Z/wFReGUccXIcdpwqKUb36TjrBql6srgcaxpP9BexxrGDT62xzYr4Rj0jRySfXFKKrNuMyvXzxzIUr8mmCYbytfFepzWSfsaNq/y5omaIB5I0zSNx+PBd999h/nzVVe9xWLB/PnzsWrVqrD3a29vx9ChQ1FRUYFzzz0XW7ZsiX2LU5kcVtqnrVaISPU37EudMyjkS60t7QUQdlgeZ6o8xny99oAfL1F6jej2GNH2fzDYNtwIxw8dgC45GFm1/QCOtHswKM+F2XIKIiwN25gM68gBisYGXBVQ2htmUB7nmFhNrLZQo6bbJ8Inr5jDlvbyA0fpJEWa5d1XARakWizRPSMAUJzjwtiSHByVsiEK7Hu0cfsOtLt9GJjlUAKtEOL0i3AmledBEFjwytNrsDmZugFoghF20B+UFyHA5Aa8oJNeQPpK2wyOVzps/1+oiZWnaMYuDAhs4sVlt+J7k9ix4J10TNXwoYpGF1VcFSmbpipe6YDBihoeJJfly4GA8h08zvQxjhvK1x6I0d+no7QaCka6W1jgDYQUFSizadLJwHrkyBH4/f4QZaOkpAR1dfon4LFjx+Lpp5/Gu+++ixdffBGiKGLWrFk4ePBg2Odxu91obW0N+EkLcuVgpNVgWZ82RRP0pdaW9gKI2BIe0FbUNBvf3mhECUaqlWBEs8rlHhgDtfdmyHLa4MpiqZL1e9h35/KZw8K3MOdw5WnwtJDVvXY2TaQ+I0AcJlZFGVGraTo1VSVZ4dI0XAHQHDi0QYcgGFdGAOCkUYWQYEGLjakkm7fvAADMG1sU6PfhdBxRO9bG2Ssm12VXZigp6ogghJT38oN+yMBFLdoTgQatkhigjIxewPwBzVXqewqwkvV1L7C/J18U2wuLwPePZamaDzbVKq2604YIE551STe/CMegMsKD5NLcoGCkzLwKdKy8aFxX3RxbJ1adKjRDPUZ4NWHekBBvVL+ZTTNz5kxcfvnlmDp1KubNm4e33noLRUVFePLJJ8Pe595770VeXp7yU1FR0dObmRi4MtJ1VHc4Wgha82oQ4Twj4ZQRXlGzs74tdnNUMFHm04SkaXwe1STVA70GBgxgO1GG1I0MuxU/mj4k+p1quF8kMEUjSmJABQYPRoIH5XGGDcxCdiwmVp2Oifzzcdkt+sZRQA0EwgQjRqtpOLNHsyCkxs+CqgP72byWynB+kT1LAEhAySS1P0kcTJHTiPom1iBlJD9MMCKKaq4+TDASMkDQkanOmtnylnqHb//F/DBF41jAkmCmDytAWZ4Lbd2+9GsPr53wLBoIpNLNL8IxGYwoaZow30EjTCjLhcNqwdEOD/Y3GhzgqEUnTdPcyc4JESvQlOPJlJCr0jJNU1hYCKvVivr6wHbH9fX1KC01dsCy2+2YNm0adu8O34jo9ttvR0tLi/JTXV1tZjOTR8YA9csi93IIi6dTNVbqdCw04xkBgOJcFwbJ5qiNZn0N4YigjPj8orKTKspI7XomH2YUAIVjQ+4TLyWFLBjJQjcuOK4ceZF2Ps5B/WBEawS2WWzItLHX0OnVP0BYLAImlsVgYuXKiCY45Y29sp1htl8U2XsJhA1GghWAaKus6cMHwmYRcMDLghF/yyFYBGDu6DBpLmVWUvxN6wA1jahrYpUPrHVKmiZMMHJ0L5ObbS6geELAVXqlvYpiNPF89nvL2+y9dbcDq/7JLpvza8OlqOG+G3pYLALOTdeeI5mFAARWDh/NjN95FDjCVLZgY2TKY2Byr8cnKqnF0jwX+/4d2cmujMEf47RZlb5JMaVqIhhYIyojPO2r0/eJn1PSKhhxOBw47rjj8PnnnyuXiaKIzz//HDNnGouK/X4/Nm3ahEGDBoW9jdPpRG5ubsBPWiAIGt9IlGCk+mtWSZBbDgwYHnK1tgeG9rdeNQ1nmnzA/2ZfgkxzEYKRutZu+EUJDqtF7TGipGhm9UivgbJiZrTMErpx1UnDot+hu4X1kQCAwccHXKV9H62CFXnyXKEWd/hAIyYTq87k3qNyL42BWWF2/sbdLI9tzwwI6sKlaYKv0yPbacOxQwegQWKfaYnQhGlDBiA/U2cbRFHtFRND11U9pmqUESVwUg6s7GSgyuFhfAdcHh80JWRGjrYdfIhiNGo+8wy11gAHvwHWPM3Uy4IRwMTvG9r+dQ3rMOu/s/D4hscN3R5Qq2qW7mhAU0fkXhYphdWmVga210e+La/QKBwTV/fapGBgWF59azckCXBYLWx/5Sf1/KFqk0uTcN/Iulj6QukM3zRUTcMXNzpVcWmbprnlllvwr3/9C8899xy2bduG66+/Hh0dHbjqqqsAAJdffjluv/125fZ33XUXPv30U+zduxdr167FpZdeigMHDuDqq69O3KtIJXLL2O9ovhHtOHsdE5R2UB4Q3TMCAHNGs5P10p0JkoUjVNMc1NTeK54DZXx4z7SDdmaypkFzhmZgRJEBw2HNWgASO3DwIXEy/P0F2Hub78wHADS7m8M+3KRyFoxsNFOWFyEYKQgXjHAZuHRyQNO4cMpI8HXh+OPZE1EymAW+47PacdMpo/RvWL+JmRcd2Qlb7Y4blAOnzYLWbp+a5tIoI5IkhRoFg4mQqw9QRixByojdBYyTq2VevghY/Af29+xbDDfl23h4I/ySH+vq1xm6PQCMKcnBhEG58PolvL8xzdrDGzWxpqtfBDCUplEC5DwXBEEI61kyw7FDuYm12fyddcYoRFVGIphXAdUnZzc5BDPRmA5GLr74Yjz44IO44447MHXqVKxfvx4ff/yxYmqtqqpCba2qCjQ1NeGaa67B+PHj8b3vfQ+tra346quvMGHChHBPkd4YVUaiDJUyW00DqP0i1lc3K1Nt4yKCMhLiF/H7dPtiJBR5JVNgM7jKDJOiAdT3F2DvMVdGWt2tYVMexw9jaaLNh1rR1h3+cwhAZyXTKHePLQjXPTaMpMp7jAChyogRE+uEslx8bxY7kZ9c5g/vF+Et4IfPVdqtx4vdasH04ez94yXF2gNrS5cX3d4oDc8inAj0mp4FBGiTZJMq7yo69kxgyg8Nbz9XzCIFq3qcLxtZ31ibZqkaoybWdPWLAAaDkSBTdU3sfhEOnxe1va7VvGKmeEbU40lztGAkgnkV0DQ9s6SZMgIAN954Iw4cOAC3242vv/4aM2aoq6elS5fi2WefVf5/5JFHlNvW1dXhgw8+wLRp8c8rSVmMVNS429XVb5jGYMGeES6hdQU1z9JSmufC+EG5kCTgy12HTW64DsqsndDHqjoaVNZbtxHwtLFWwyXHxP/cehiQVQPglTTlx4dcxdM0/OTFlRGf5EO7V9+gOjg/A0MKMuEXJazZb1Bi1Tl4NHVGSdMo/QCCylc1zc0sUEtYAWPBCADdYXkh8GAkAROXtfAy7JW7eTCiKiO8l0NBuIZnPg/7jgG6uXpFGbGEmdkzej5w0QvAxS8Bt+4DLnk5JNUTiVYPq+iLlMbT49ypg2G1CNhQ3RzfgLTeRmfCcwjeLvXknJbKSPTS3hDzqhKMxN5PpSTXhXGlORAlYNlOk8dpHWWEV9OENbAqi5upulenpYGVMECOgTRN9WpA9LFIdcBQ3Ztoe2AAMJRGAICT5QZWS7YnIBjRppyC1IJ9R4KmvSqzGmbG1SArImbGfktS2EoaQPP+yqXTLpsLLisLHCK9xzNHsLz4qr0GW/7rpGn4/JUBen4Nvw+olU+6EZQRi2CBy+pS0netRoeaRVPu3G1q+/wE+UU4s2Wz7Oq9jfD4xIADa11rlLLeernRlCtft9FU2NJeLRPOAcafFVPb91iVkaIcJyrHsH3yzbXh2xmkHFlyWjOSMnJoHfO9ZZfo+t5SHgPHkzpNmgath9goBcHCfEtxcPI4pjwt2WEypR7BMxJWGVEqaabqXp22HViJKOQaSNNwo2eYFA0QqowMcDFpr8kdeUV+ivwlX7bzcPxzanhg5esOmbez7whbTQwvlFcX2mZnPYVy8DCwwmzax7bZ6mCNw4JQPDmawMmIiXXmSDkY2RN7MHI00pC/w9tZRZIjBygI7GCr7b7K5zwNcBr7Xijw76e7lSl0wez7kgXKBSOAgsSeYMaX5mJglgOdHj/WVTUFVAbURqukidJoSndmj5GyVIPw70SnrzOib0uP849lU13fXluTuNlRPY2RLqxav0gCGxz2GnxYXoRg5JA8JK8sz6WqIsUT1GNRjMR8nI7FMxLBvCpKorIwSzsDKxEFRRmJEIzs05hXwxDsGVFOOt2RTzpTK/KRl2FHS5c3/im+NgeQJeeOW9RVnSRJ2HdYo4yIYkxTLE3jZAZWQ8EI94sMmqKW12oIVp4AVX0yEoxsOdSiHAQiorOSiWhg1UqqQRVJ2hOuss2yybg5TMv+EJw5qjytJ8HvWsx+J1gVAVi5Kx/at2L3kYA0TW1zlO6rUXL1hpSROGjxqN8Js+rIqeOLkeuyoa61G1/tOZKwbepRjKRptFOl0xG+H0QYlFfXypWRjLDdf2Nhmnycbu70ssDcKEFpX49PVJoo6gYjXc2GzKsAKSN9D60yojfAzN2mnnAiDJIL7sDKlZFoJx2b1YK5siyckGZLecyAh1bVgHe4zY0Ojx8WARhSkAk0bGUVN/asuOXLiGhl1WjdC3kwMjjULwKowR5PcwDGUmEluS6MKMyCKBksodbxjDR2sBxt5GAk9MChF4yYVkYANVUTnEoU/cD2D9jfPdAIDFBTNct3HQlY5WmrFnSJUsWgLe3V9YzEiTZANRuMuOxWnD2FLVJeX5MmqRpefabjFwPAjm1VcllvOvpFAENpmkPNGsUuAZU0HO1x2lSqJqg3j3ZBlOPSCUa4eTVf37yqHQxKwUhfI1s2CIrekNQGAKYgSH5gwDAgP3xn2eAOrGZOOqfKEuD7G2tjazmsJVcORlrUYGSv7BepKMiEw2ZRUzRDZhgulYwJfvAQfcw/EIkI5lUgtHQaUNM00U42J5pJ1UTsM6Iji0YIRvhnqauMmDlBhjOxVq1mpZyufGDEPOOPZwI+QXjjwWZ0C/Lr90TxjBhoNKU1sPaEMqL15JgNRgDg4hPYvv7x5rr06DkSTRk5vA1wt7AFSOnk3tuuRBIlGNE2PBuU69B4LxIzDPCUcXzRaMLfFzSbRukx4rLpd3OOkKIBVGVEgKAsfJMFBSOJRpvaaNMxsfLOliMqIz5MsGeEn3SipWkA4PSJJchyWHGgsRPfGq36CEcey3ejVV3RhZhXe2geTQiObADyDhemRT0ApkLUbWJ/65hXgdCmcoAxzwhg0sQaFIz4RUkpxQtRRnweZtQEdIMRbfkqh6s5Rr4XCuFMrFvfZb/HnWmq0sQMg/IyMLKIKUv7W2TlwtsROU1zaD0AiRm+eclpENr3hn+miVJGfKIPbd425X/DZmENkwbnYWJZLjx+MT2MrPwY1nkU0PPI8LRs+XE9uwDpSaJ40OrlFI3DZkFBdzULvmwZQPH4hDz9vDHFEAQ274p7U6LCgxHRB/i9ql8kbCXNevY7innVaXWyPipJhIKRnkAp7w062EsSsOtT9vfo0yM+hHaIG2DcwAoAmQ4bzpzMtuH1NXG20tdRRgKCEUnq8WZnCharejKKZBCu28iUqawiJk/qwPu1aJURoxVLJ8rByLbaVnUKbTiCZNWmTo+SYRoQfABp2MIUn4wBTDkLQk8ZKXAx6dVUMKJnshZFYNt77O8J5xp/rBiYP4Gtutc2sGBB6mqObGA1kKvXNj1LtDLS5mkL+D8WZUQQBPxQnqX0yrfV8SuWPU1mASBYAUhsaGIw+5ax38Pm9upmJZQorQK030mBt2LQ6f4bKwVZDhwv9xx5b4PBpng2TbDu7Yo+JC+KMpIqZb0ABSM9AzexBisjjXuApv2Axc4aSkVAMbAKgWmaNk9bxMZnnAuPZ7LwB5tq4xucp+MZ2SubV0cUZjH5vPMIUwB0VvMJx0iHWyVFc0JYl7+egdVomqYox6m0hv9iW5R8r6KMsJ2ep2jyM+2wBU8c1qZodLZbWf1DRxkx4xnhARpv5Q2w96ytFnDmRlXt4oW3SV9Rxw6g/pZadMmTbXU9IwZy9bqD8hKkjAQrZbEEIwBw7tQyZNit2N3Qju9iHSHfW1ismvLeoFSN6GdVVwAw8uTe3a5EEiVNE9DwLIF+ES0/kCut3vjuoLEA1eaEog57uyJX0kQxrwJqR28KRvoq4ZSR3XKlwtBZamVIGILTNLmOXAjyl9BI46Xjhw7A8MIsdHr8+GhzhAZX0cjlaRqtMqIp692zhF045ETdqpWEEy7Q06J0XtX3iwChyhNgrJqGc5q8uv90a5TZHUowwg5sSvdVk+ZVQO0zYtFU2SjGZjMnyPHnsoC45jtVxuUpmrELe/xzHFeai3GlOTjozwcAeJvZZzkwXMMzA10veeBhE2wJV0a0lTSA+cZnnFyXHWfJiuXL31TFvV09TjgT66H1zMfjzAu74k4LlEF5+gMQlYZnCa6k0XLm5EFw2S3Y3dCO9dohkuEQhADfSLPcQFE3GIliXgVSZy4NQMFIzxDuhMnLJkefFvUhgkt7rRarKX+AIAi44DgWSLwWT6pGUUZYdZDPLyrdV4cXZakD1RLcrTMshpSRyJU0QOTSXiMndh6MrNh9GF2eCCc9u74yUqDX8KwmcjCipGn0lBEzaZrsIjUVs+Y/TIbf+Cr7v4dTNJzvTxuMenlon72rAQJE5fsagMFGU7rt4PWq2WIgUcoIAFwyg6lS72+sjZ7iSzbhTKx75QXI8Dnp6xcBAjuw6qgStbzHSI5V9aAlWBnJcdmx8BgWoL7xnUEvkZL67UZLFzuO6Qcj69nvCAGjMpfG0jMeMTNQMNIT6Ckjnk7V6DkqejCiV+1hxsQKsLkYVouAb/YdNRZ165Fdyk4EohfoaEBNcxe8fglOmwWDsizqa+r1YCSMZ6T1ENBSxbY5wiomuHQaMG5gBYBxpTkYnJ+Bbq+I5ZFa7weV9h4NV9br7WIl0kBYtz7fZq3RLCZlBABO+Cn7vfF14M2rWaqtcGyP9BfR45ypZWgU8iBKAmzwY1qBH788bUzoDbkqUjQecIYfjsgDj7Dt4OMgkcHItIp8TKnIh8cn4sXVB+Lcsh4mbDCylP3u4XRej6M0LpMUT5cWroyMt1bLXq4CXS9XvFwoB+HvbTiEbq8BNY/7RuSZTgCQl6GntK5nv8OYVwHNXBpSRvooen0c9i8H/G5WEVA0Vv9+GoKVEcB8T4lBeRk4bypTNv762U5D9wnBalNfT0uNUtY7vDALlppvWcOgrCKgeGJsj28WJRgJM3iM+yBKJkZMhSkGVkuogdVIMCIIgqKOLI6UqgmqpuGt4EO6r9ZtZiXfWcXqawyCKyPaAJV/J5q7m82ZIofMZJ0kfV1spWt1Ahc83TupNrDv5vQRxTgCFgD+6eQC/RQN9/9EkccDlBE5jaWdzBwPfC4ND1xjTdMA7Htz9WzW2faFVQeMnXySheIZ0QTbnk51HxuRxn4RQE3TALq+kUOyZ2Skezu7YPCxPdJp9sQRAzE4PwNt3T58ssVASl1J03RH9oxESfsCZGDt+/CTSctBRZ7HptfZ79HzDX2h9VbuRhufabnxlFGwCMCSHYexIVZ1hFfUtB4M7LzKUzQjTg7pFtpjREvTVH/DfkfpChkpTdPubTdkEj5dDka+2N4QvqVzUDAStvtqFPMqoGkHr7meq2WRBvzpIgjA8T9R/19wD1DaQwMOw3DFrGGol/IBAJPywpQ28mCkYnrEx+oNA2t5TnnA/7Gy8JhSlOW50NjhwXvrDVZRJAM9ZaRqFVMJcsuBgSP175cuWCysTwqgW95bfVQ2sLbLimWCUzTqZgi4SC44eOrLvdEXFTz16+1ES1cYz0hXMxuJAURO06TIXBqAgpGeoWAkUxM8bcDXT7JV76Y32HXHXmHoIfRmp/CT5VG3gc6fMsMLsxR15G+f7zJ8vwC4b6SlJrCst7f9IkDgIEK9nVYZaR45GFH6jGiCvRxHjimT8AnDC5DrsqGxwxO+OsIeLhgJUiB46WCEVYy2fJXjtDqRaWMrPFO+EQCYcgmT2o//KXDC1ebumwAWTCzFuNFyakavVNvvVdM0FTNCr9fQk6W9/LswJJf5PeJJ0wCs++YVs4YBAP6zYl/qlvnyMnqtgZX7RUZUpuc8mmDCVNS0dqs9PHIaZSNoDwUjAHD5zKHIdFix5VBr9Em+Nq1nJIwyYsC8ClCapu9jcwCn/IH9/eWDwMe3AZCAid+PmL/TElzaC8SmjACqOvL59gZ8tClCf45wKMpIDXbWs54LY3O9ak6yN3PH3I/j7WDD3rR4OtUx81FW0jzY0yojVosVOQ6W2jESjNitFpw2gXUzfWd9mLQRV0b8HkD0a7qvhlFGDPTS0PYZAcz1oAnAmQ1c/i5w1sNJO7HY87nZW0eertvE0kiuPGDg6IiPo6uMJMrAKlfTDMlhwUiLuyXuAOKH04cgy2HFjvq2yGm+ZMKDkcbdLDD0dALr/8suM2DCTwvCBCPVskl/SKYPlkZ5EZegzqt6DMhy4EdyH5p/LtkT+caa3kXhg5H17HeUdgs8GHFYSBnpu0y5hLVJdrcwv4hgBU7+veG7K6W9cXhGOCOKspWV2C9eWY/VRjqHapG7sPqbq7FOTvXMwEYAEvMd8AChN3BksXblQKiJ9dBa1pkwpwzIC99qH9DvwAqYq6gBgB8cywK198OZz2yavhk+t36axt0OHN7B/o4gqSoGVgQGDso2mwxSU4Jw3WCBwH4xUdKAWmVEmdqbIGWEd1zlyohP8qEjwnA1I+Rl2JV98tHPdqWmOjL4OCCzkH02a59nP51HgPyhwLizkr11iYEHI97gYISlaObm1EDt/lvUo5ty9ZwRcFgt+Gb/0chzrzSlvTwYyQ9uoMgXN1FKr8kz0h+wWFgenjPtUqBwlOG766URlBWwWTkewO/PnIDTJ5TA4xdxzXNrzPlHZGWk83AVPD4RJblOlOx9i10XpZNsjxDOxKpMEZ0edaWv14EVMB+MnDhiIMryXGjt9uFzvQZoAcFIt2JgDQhG6uTALncwkFMS9rkkyAZWS9A28yors8pIghAlEdd8eg2uW3yd+ZOqEozoKCPc/1MeWeUCenZQHldGijOL4bKyzzPeVA0AXDNnBLKdNmytbcUnW1JQHXFkAfP+H/t76X3AV39jf8++Ob1LerWEUUYONjFl5Hi77LtIcH8RPUrzXPiBXFnz6Gc7w+9LcjAieTrDKyMGKmkAjTJCwUgfZ/hclo8vGgdU3m7qrrqlvSZPlFqsFgF/u2Qapg8rQJvbh4ufWoUPjaZsNGkaADinohvC7s8ACMBxV5relrgJZ2LlJy8DU0T1DKyAWt5rdP6IxSLgPLmj6Ft6M0esNkB+DsnbqQxJC6imMeB6BzQG1iBlpMDJcsLJUkYOdx7G6trVWHloJeo7TZ5UIyoj3IysP19Ii9L0zGJTqmkSrYzkOfJMlX9HY0CWA1cq6shOiOFM0MnkuCuBAcPZAMXWGlbqP/XHyd6qxBElTTPezwc09pxfRMsNlSPhsFnw1Z7G8AGq7BlpaWtDt1eEzSKgKEfj+TBoXgUCZ9MkGwpGepqzHgYWfW06laFX2hvTHBINLrsV/7nyeFSOLUK3V8QNL63Fw4t3hq8E4cgG1kzPEbjgxoXiR+zyMQuAguExbUtc8GAkeLYKLzmM4hcB9NNgQGwB3/lyS+elOw/rN7KS1ZH29g745Pd6gLbpWU108yoQ3jOSbGWktkP9HPa17DN3Zz5BODjl1lYPNFcBECI2r+P0RjVNnjPP8MgAo1w9ZzhynDZsr2vDB7H4uXoamwM49Q/q/7Nuilr+3e724cXVB3DTf9eh8oEluOLpb/DCqv1oaOuOeL+kEGZYXnUTS9OUd21jF/RSMFJRkImfzR0BALj7g636qV9ZGak7wlI5EwfnBZbFK+bVoRHNqwClaQgD6JX2apuexZpjznHZ8Z8rTsBPTmJBxN8+34VL//01GlojHCiyiiFmFcMKEf+xP4hRNXLr8OnXxLQNcZOjk6Y5sgPobmarBgMjzbkyEtx5MJaTzajibEypyIdflPDOOh0jqxyMNLexFXaWwxp48DCpjIQYWJ2xp+8SQV2HmmI50GqykRdXRjoOB06H5apI8XjAlRv1YbTjE5QOrAkIRkRJVNI0ec48U71ojJCf6cA18snnL59sh9uXgn1HJnyfdeYtnx5VCT3c5sYFj3+F37+zGf/bcAj7GzuxbOdh/OHdLah8YCmeXrEv+uKnNwkzLK/6aCeK0ISs7vqo3X8TzfWVI1GW58LBpi48uWxv6A3kYKShqRkAlGF7Cop5dWrU51Jm05CBlQgHP1nqGVg9ogddPoMjp3WwWgTccfYEPHrxVGQ5rFi1txELHv3y/7d33vFR1Pn/f81ustn03kMKEEIwIRQlBqSHJiKIX0VAwYanooKIcngigvcT7lAQEUXPE1DvLFjgKJYAIZSE0GsgEiAkhBSSkN6zn98fk5nsJptky+xOAu/n48Fjw+zszPuzn52Z9+ddse1Ujn4lR6HAqdg1qGR2GKI8D0VdOeDZE+huxZRebfRVYU3fxb+GDDaoq6a+3jSAcYXPtBGqKG5KzkRDY4uHYJMyUl7Br748tF001SVAcVP0/G1gGcksyzTuww6eTW4sBlRoxdyI8SIdu2gA3e9GygDWyvpK8dguKhfJLSMAbx3xdbFDdnE1vkruhFVZFQrg0a+AZxParYJ7o6Qa0z5LwcW8cng72+HV+F7Y9NQ9WDS+N+4KcEFVXSOW70jD1E8OiW4Q2RGUkZrm650xhuu3qhGjaFIEOqj+KzUOKhu8OTESALB+XwbS83S7RgvKSEkpv7gZ2FIZMTB4FSDLCGEALRvlAYC9jb3o25PiwTOlfyC2v3wf+vi74FZVPeZ9dwpzvjqGvNLWVpJfy7tjVt1fUaNoqlp4zxzrFTpriRjDohUzkvY//rXPgwYdoq0AVlMfNg8PCIKHowrXb1W3NrfbCm6aJmVEu8aIESZVfXVGAN0qrHKgo4yUZhr3YYWCj0MAdINYhQaMIYMNOow+y4jg6jQHQSlVK9VQ26glt4wA/MPntbF8VeZ1ey+JcUVdiboGDWZ9eQRXCisR6GaPLX+Jw7z4cIyI8MELI3pg+0v34b2HouGstsHp66WY9PFBHMoolFvs5vLuRRnipsKKOlTXN6KfommREGiFbuQtmBjtjxER3qhr0OCl/57Q7X/VtLipruLvJ62VkVP8qwGWEVJGiA7Rl3rKcZxpjdHaobu3E7a9NASvjekFWyWH3RcKMGZNEr4/miVaSTQahgOXCnGcRSB5xLfA+H809zaRA7H3T5NLpCSLN01yCiBiokGHaCuA1dQgYXuVUgxG3JDUoopiU8BZZSVvCtapMSIUOzMgWl9fBVZzZJYKsywjQHPciBADdOsakH+Wn08D+jgBzTVFpLaMCC4aFzveVWSp7/rhAUHo7eeMspoGrE4wsXWDjHx56CoyCirg5WSHLc/HIdTLUed9hYLDjNhg/PHqMMQEuaKkqh5P/DsVPxw1o4mnFHj35l9vNn/n2U2ZNINsmywjVooX0YbjOLz/SAy8ne1wqaACy3ecb36zqYy9GnUIcreHr4tWxp4RwatA86KMAliJNtFnGQHMD2LVh61SgZdHh2PHy0MRE+SK8poGLPrpLB79LAUpl4vwzOajuJhXDlslh6j+9wL3Pm+QK8RiCG6a6mK+Ad2F7fz/gwcbXAtAX1E5wLhmeS0RqiheyC3D/ktaq76mgL9r+fy2UE+tG7WB8SKAliuixWUr/iZkctNox4zcqLghrrYMpqUykt4UIB0cBzh6GnQIS8WMaAevar9KrYwIrlMA+Cb1Go5fM7zKstzkldaI1Z0XT+iNADf7Nvf1d7XH93+Jw8MDgqBhwBs/ncG3R7KsJWprvJsqAAuF3cDHi9iiATGsqfZPB9V/LYWXkx0+nNYPHAd8eyQb6/Y01aNpsrSqUacnXsRwSytAlhHCAPTFjABaLeMt8OCJ8HPGTy8Mxpv394baVoGjmbcw/V+HkZh+E3Y2Crz/SAx8nNUdH8jSqN2aSyKX32hWRiInGXyItgJYzTHDuzmo8Ng9fGGsj/dqFbJq8vGmX+eLzY3q7dP8IQMzaQAtZUShP2akrLZMHJc10VZGGBiyy4xc7basNZK+k3+NuN/gQ2h/N8I1I4VlRDutFzDv99ERg3t44ZGBQWAMWPTT2c4ZzKqH93ZdQFVdIwaGuOOhpjT39lDbKvH+I33x1JBQAMDin8/K18HYJYjvT6OpB4p5i8L1W9Xoz12CHWqbmoD2kUc2AEN6emFhkwvvg4Q/sXxHGjRN9z571Opx0Qj3k34GHZ/qjBAd0pZlRDujxhLYKBV4blgP7H1tBCbF8BaIIHd7/PTCYEzu1/GNxipwXLN15NiXzcXOIg2vCtlRAGtJbYlJK+s5w8JERW7Lsaa6I02WkYbaCjiqlBgU1rRiKckGSrP56rwGlJrWQL9lxEXlAg4cGJjYYdZaVNVXiVaCUJdQACa4aly0lJHqW0DmIf7/vQ1XRrSvFylTe1taRiztEvvbxEh4OamQUVCB9XszOv6AzJzLKcX/Tt8AxwHLHrwLCoVhbQU4jsPbD/QROxi/tfUcvk7JtKCkbaBQNFtHCnlLSHZxFQYrm9wiYcNk78Ezd2RPvP0ArxBtPJSJFQmZAAA7rh4DQ1pYP66l8K8GWnOoNw3RIW2VKxdM8paODwhws8e66f2R9PoIJLw6HFGBrhY9n9EIHUOT1wFgvF+3qWy9IYgBrC0sT14OXrDhbFCvqUdBlZ6Kqh3g72qPBWP4m9vfd6bxtRWa3BBB3E0M6+UNlU3TZZfVdOMI6GdQtH5b2TQ2ChsxpsHa6b15Vbw1w9nWGXd53QXABGVEu/DZpQSANfKrUY/uBh/CUo3ytNN6tV8tdf25OajwzoP89/hxYgaSO0OQZzt8eZC3JkzqG2D0PYLjOPxtYiSea0ptXrLtPDYeMrJOjRSIcSMXAfAxI3GKpk69YcOsL48enr4vDB9O6wcHlRKXbvG/ayeuDhF+zs07aTRAttAoNM6g44puGkrt7Xo0ahqxaP8i/OvMvyx7nrYsI0Ln3hrr+JRDPB1hr1J2vKO1mfgBcN8C/mbhGgzc96pRHxcDWDldZc9WYSv2ILlSoifH3wCeHhKGqEAXlNU0YNn/0sB8owEAfbhrGKntornWZAEwMGOkLWUEkK/WSF4Fr4z4Ovo2W0aMzagRYkZyjgFJ/+D/NsJFwxizWNEz0TLSwk1jTq2fjpgY7S/GVLz87Unklpqexm9JCspqsP0Mn9H29H2mFT/kOA6LJ/TG88P5xcWy7Wl4d0eadWuReDVZRpr6Q90suoX+XFNzPDOUkXpNvfHxU+0wpX8gDi0ahQl388pTsKocSm1LVEEan6KscjKo1hLQXIGV3DRdkAvFF7Dr6i6sO7nO+GqTRtBWhdAgZ371b/QN/3bDLRiIXwrM3g68etaoeBGg7e8XAMJc+RvrlVLTlBEbpQIrp/aFUsFh59lcfHqR9/FGKrIwMkJbGUnmX0OGGHRc4eGnTxkRLGamWHPMQcik8Xf0R6hrKAATLCNeEXzmTE1pc4qlES43baXDUgGsguXJ38kfHDhUNVRZLGCY4zj8fUoUIv1dUFRZhxe+OYGymvqOP2hlvjl8DfWNDAND3NGvm5vJx+E4DovGR+C1Jovivw9exTObj6K0ykpj1rKMNDRqEFh2CiquEQ3OQXwpfBN5cfeLGPvjWEnji9wdVZg2cTwADs71N/lKxQKCpTXoHoN7B1HMSBdGsEgwMHyd9rXFzqOvUR4A9HLnL9g/b7XTSInokLYCWAGguytvNjZH2YwKdMWyJnP7hiZlJIgrhLdNU7GniptA4Z8AOIN66QC6Jc9byezGy3y5tIP24xKjo4yYGjPiGgg8fwiY8ikweikw9V8GBfQKaCsdCoVWaq+EdUYE94yd0g5+jrwlJ6vMclkg9iolNjw+AC5qG5zKLsHUT5KRWWhep2ApqalvxDep/PifMdEqog3HcXh5dDjWzxgAta0C+9JvYuK6A8Y19DQVbz5AFIWXcDm/DLHcOQCAosdwk+NFSmtLcTj3MIprinE8/7hUkvLYOTXLLFRbBbQWN4ZZWgGKGenSaLtH/nf5fxZzl4iN8lqs3MNcwmCjsEFFfYVOfQfCONpK7QXMt4wIPH5vCFb9X19UcI7I1jSlHOc3BcZlNd04fO8C7N31H6AF7blperrxHaEzblk36FFURpz8EezMu7dKa0uNL8Dm2wfoNwMYugDo+6hRH9WODZHaMiJc34LlCYDoxjOppooRhHg64j/P3gs/FzUyCiow5ZND+Dols1Nk2fzv1A0UV9Yh0M0eY/u03WnaWCb29cePzw9GNw97XL9Vjf/bkIyNh65aduHlHgoo7YCGGly6dB6DFfw1qggbbvIhLxRfEP9OK0ozV8LWCMq6UBqAsWbLiIHxIgCl9nZptH3ytY21+P7i9xY5T1sPS1ulrbhy//NW1yuO1FkQlL2WAcKANJYRgUfu7oZ/zbobJS5NK5m8s/yrCauYtoqeAUC4WzgA4FLJJdOFNYH8St5M7OfoBwdbB9FqYOkHtTY6lhGuObVXmGNzKKrh07E91c31TgQLkCUtIwLRQa7430tDENPNDSVV9Viy7TxGrtqHD/5Ix9HMYtS3bD1gJf6TyqfiPn5vCGyU0j5GogJdsePloZgQ5Yf6RoZl29Pw/DfHUVptIbeNQgl48deP+9mNiOIy+e1mxItoKyAWUUaEgmaCMnIrkw8AV9gCQR03lhSg3jRdGEEZCXTi01y/S/8ONQ3SdqPUMA0Y+JWAvpW7tquGMA0hm0afMiJYRopqiiTx946O9EX0wKa4kDzeBGxs8CrQdjl4AOjpzltGrpdfR1W99fp+aLtpgGal6FzhOavJ0JZlBDDfOiJc7zqWkSYLkNFNAU3Ex0WNLX+Jw7uT74Kvix1ulNZg3d4MPLIhBVFLf8dDnxzC0m3n8OPx68goKLe4+/ZcTilOXy+FrZLDI3cbnsFmDK72tvhk5gAse/AuqJQK/H4+H/evPWC5YnBNbo8hhVug4BiyQ//P6E7r2rRURiSfE9Eycop/FTPz+ot1jQyhVsNbRshN0wURzLaTe06Gv6M/imuKsSdrj6Tn0PZ16wuwJGXEfNpz0zjYOsDXgTc9Sxak7Mdn1CD/LFBV3KyUBBuujAgKass6IwD/sPRQe4CBWTSwWhsN04gFzwRlZIAvXy/lRMEJq8ggyCGgnU0DmJfeW91QjaoGXrFzVze70kJcQgBYTxkBAJWNAk/EhSLp9ZH44JEYTIoJgLuDLWobNDiZVYLNKdewcMtpxK/ej+Gr9mHFrxeQUVDe8YFN4L9NFVPH3eUHLyfLPcQ4jsPswaH48YU4BHs4IKekGo9+dhhrd1+SPttGCGIFcFYTCptJq8w6nLYyUlRTJH1guV80H/Rdkcc3DM00fnEDNMeM2MpZUbsJUkaMRIig97b3xkM9HwIA/HLpF0nPoW1eJsuIZWirN42AlK4aAIBvFP9acBHY/z4Axt9QnA33t7cXwApY31VTXFOMOk0dOHDwduBjYgb48MrI8fzjVguwbmkZ0b5mzLGMCFYRW4UtnGyb68AIMSNZ5VlWDyJX2yrx8MAgrJveH8ffGoPEhSOw9rF+eOa+MAwK9YCdjQJZxVX4LOkK4lfvx5MbjyD1SpFk56+obcC2k3xPqBmxwZIdtz36Brlh5yv34aH+gWjUMKzZ/Semf34YOSUSpjw3LRZKmCOWqN6An4dhcVz6KKsrQ3Y5X4VYcFtK7qpROTQrUH/+Cpz7if+7h3Gd1CmAtQsj3KDc1e6Y3HMyOHBIzUsVf3xSoG0Z0fewFJSRa2XXJHcR3Sm0VYFVQHDVSKaMuIUAKmegsRY4/Am/bdQSow7RXmov0OyqsVYQq2AV8XbwFrOSoryioFKoUFxTbLW4Ee3AXo7jdL4fczJqtINXteN0gpyCoOSUqG6oxs3qmyYf31wUCg5hXo6Y3C8QSx7ogx+ej8OJJWOwfsYAjOnjC44D9qXfxLTPD+O5r47hqgTZONtP30BlXSO6ezkirrthfYOkwFltizXT+mHNtBg42dngSGYxJny4H7tadsg2lfBxSO61CNPqlsA7OEJvXJahXCzii6cFOgUi1o+vhJpWbMEg1j/eBhqqgaBBRsW5NGgaxPsgKSNdEG0fcoBTAO7159Myt2ZslewcLVd6LfGy94K7nTs0TGP1VM7bBUMtI+Zm1IgoFIBfk3UEDAgdCoSPNeoQ7QWwAs0ZNdayjLSMFwH4qPxob36VeSLfOq4aYS4FJUTbtWmOZURfJg3Am7QDnPh2BNZ01RiCo50NJvb1x79m3Y3E10ZgRmwwlAoOf6TlY8zqJCzfnoaSqjqTjq3RMLHi6vRBwWY9sE3lof5B2PnKfYjp5oaymga8+J8TWPTjGVTVmRmsrFDgvxiPdBZsVs0UoNkK0sezD/p49tHZJimCMlLX5I4b9ZZRqciCVQTQX+LA2pAyYiSCm0aoeDk1fCoAYFvGNknqGgDQaXambxXMcVyzq6aYXDWm0FYFVgHJLSNAs6sGAMa+a3QNg7aq8gpYO703t6K1MgLoumqsQcvAXh3LiBkxI20pI0Czq6azKSPahHo54r2HovHbvKEYGeGNBg3Dl4euYviqffj68DVojIy7+CMtD5cKKuCstsG0Qd0sJHXHhHg64sfn4zB3ZA9wHPD9sWw88NFBnMsxL9j89PUSAOg6yoiQUQPwFpHuxqUiaysjlNrbxahrrENlPW/qFALaRgWPgqudK/Kr8pGSmyLJeUQXAmfT5uoj3J2PD6C4EdNoq46LgFBE7HrFdelKOgv+3P5PGFXUS0Bw03RkGSmoLrBIV9mWCH1pWiojd/vyqYXWCmJtGUsjVcxIe8pIiDMfxGqN9F5zCfd1xsanBuHrZwaht58zSqvrsWTrOUz9NBlpNwxrrMgYw8eJvJL75OBQuKjlXUnbKhV4fVxv/LepDsuVwko89MkhrE/MQE298QpoUUUtsourwXF8OrU5CC6ZSI9IRHhEQMEpUFhdaIEg1qjm7uUj3zL648J9Tckp27QQWxNSRoxAuDnZcDZwUfHloVVKFUYEjQAAnLl5RpLziJkebTwogea4kUu3rFtX4nahIzeNp9oTzipnaJhGutVvxATgpePApLUmfbyjAFYnlRMCHHn3QUaJ5a0jQsyIEKQnEOMTAwWnQE5FjriPJbGUZURfWq+AkFFjzXoq5jI03Bs7XxmKdyb1gZMdX9l10scH8f92pqGytn03x74/b+JcThnsbZV4aoj5FVelIq6HJ36dNxRj+/iivpFh1e/pGP1BEn48ft2o4nDbT/M9drp7OZqlaJXXlYv3iz6efWBvYy+6fM8Xnjf5uHqxtQdmfAdM+w8QbFiXXm2ETDG1jVpauUyElBEjEG5Obmo3ndWp0JPjevl1Sc4jrtrbMMcDQG8PPpL6XNE5SZsx3Sm0VW5fgOM4RHpEAgBSc1OlOSnHAV49+SJLJiBYRtr7XVgziLUtN42jraP4+7SGq0afkiZFszxh8aGd1isgKCNdwTKijVLB4ckhYdi9YDgmRvujUcPwrwNXMWZ1Ev44r19xrGvQ4MME3gI7MzYYHo7ym/S1cXdU4bMnBmL1ozHwc1Ejp6QaC7ecRux7e7Bs+3ns//NmuzElGQUVWPkbH3T6+L0hZslyuYSP4fN18BV/NzHeMQAgmeVch+4jjOrjpE1OBZ8V1fL6lQtSRoxAO5NGG6F5nVQZNYZYRiI8IuDj4IPK+koczDkoyXnvJNqrwCowKph3q+y+ttsqMnWEBk0BrGg71kRI7z2Sd8Ti8ggBrC0tIwAw0HcgAFjlt6nRtC4GJygm5sRxCdVX24sZyS7PlixWzJr4uaqxfuYAbHzyHgS52+NGaQ2e+/o45nx1DFduVoj7NWoYXv3hFE5fL4WDSok5w7rLKHXbcByHqQOCkLhwBN4YHwF/VzVKquqx8VAmZn15BH3f+QNjVifhL18fw8pfL+KHo9lIzijEmeslmP/9SdTUazA03Auz40LNkkOwighVegFgdPBoAMAfmX90qt+K8Lzq5ixf/I82pIwYQXFt00rJTlcZESbzeoU0lhHtmJG2UHAKjA8dDwD47epvkpy3s3Cu8Bx+ufSLTiCv1HTkpgGabyInC07iZpV8KZwCojuiHSV1QtgEAMDurN2SWer0UdtYKz6s9a2sxoWO4+W4thtldYbFJZiKvg7MYrM8cwJYq/nr3dO+dQqrv6M/bBQ2qNPUibEzXZGRvX2Q8OpwvDiiB2wUHBLS8jFmzX4s3HIaXxy4gle+O4mdZ3Jhq+Sw4fGB8HXpHCb9trBXKfHiiJ44uGgUNj55Dx4eEIRAN3s0aBguFVTg9/P52JB0GW/8dAYzvkjFgx8fwrmcMrg72OL9R2KgUJiXISQoI4LlDADuDbgXrnauKKopwrH8Y2YdX0oEZUSoKCw3pIwYQZuWESfeMlJYXShJKW7hQdneQweAqIwkXU+yaglwS1Gvqce6k+swc9dMvJ38Nl5Pel3snSA1wvfVXhS5n6Mf+nr3BQOTvMquKYipve1YRiI8IjA4YDA0TIOv0r6ymCxCTxp7G3uxo602fb36oqdbT9Q01uDXK79aTA5AfwNBKZrlCZlz+iwjNgob9HDtAcB6WUOWwl6lxBvje2PXvKGIj/RBo4bhx+PX8fedF7DzTC44DlgzrR+G9fKWW1SDUSo4jOztgw8ejcHBRSNx6K+jsPnpQXhnUh/MjgvB0HAv9PRxgr+rGr4udlj9aD9JFC1BGREsZwCfNhsfHA8A+C2z8ywcs8vIMtJlEZWRFpYRVztXMaBV8MOZQ0cpnAJRXlEIdApEdUM19ufsN/u8ctKoacQLu1/A52c+h4ZpoOAU2J21G/MS50le2K2wuhC3am+BA9fhqmBM8BgAncNV01EAq8BTUU8B4CsDazd2lBJtF42+7B6O48QKxT9n/GwRGQT09ewRFHlTLSOMMdEyoi9mBGh24/2e+btJ5+hs9PJ1xhez78HPLw7G9EHBeKh/IKb2D8QXs+7GA30D5BbPZDiOQ6CbPYb38saTQ8KwbHIUvn4mFrsXDEfK4tFIfTMeI3v7SHKurHI+hkjbMgLoWgqFvlhyQ26aLkx7qX5C3IgUpnExuLKDdCuO48Qf+e9Xu/YN8WzhWaTmpkKtVGPVsFX4NP5TqJVqHMg5gJVHVkp6LiEdOsQlBA62Du3uGx/Cr2iO5R8T518uOqrAKhDrF4tIj0jUNNbg24vfWkSWlj1p9DGpxyTYKGyQVpSG9OJ0i8gBNMf/SBnAWllfiToNX4eh5eJDYGwIX7Qu+UayxV1R1mRAsDtWTI3Gmmn9sHpaP4yONLxlwZ0MY0yvZQQA7vG7Bx5qD5TUluBIruXjuTpCwzRiWEE3F1JGuhxtuWmAZu1SiiBWQy0jQLOrZv/1/RZbBVuD/dd5y86IbiMwPmw8BgcMxtpRfArsT5d+QsoN6SLRhUJxQq2W9ghyDkKkRyQaWSP+yPxDMhlMQZ87Qh8cx4nWkS/OfmGRm5++6qstcVe7Y2S3kQD4ObQU+iwjYgCriZYRQfG0t7FvU2Ht6d4TPVx7oEHTgH3Z+0w6D3H7UFhdiOqGaig4Bbo56T7gbRQ2GBPCW1kteS0YSkFVAWoba2HD2VA2TVdErL6qRxkR4kakCGI1NGYE4FN8I9wjUKepw3up75l9brk4kHMAADAsqLm3wuCAwXgs4jEAwLKUZZLFxQiWkQj3CIP2n9RjEgDgk1OfyKrwGaqMALxZOD44HvWaeryS+IrkFSAFy4ivY/ur5ofDHwYA/PTnT7hSIlFp/RYIlkQpLSPtWUG1GRvKW0fkVlQJ+RGsIv6O/nq74D4c/jAUnAIJ1xKQlJ1kbfF0EBbN/k7+naLgGUDKiFG0VwRJSsuIkKWgVnYcUMVxHJYNXgYlp8Rvmb91ycya/Mp8XCy+CA4chgQO0Xlv/sD5CHAMQE5FDtadXCfJ+dJv8S6DCA/DlJHHIh5DuHs4btXewj+O/kMSGUzBGGVEwSmwcthKDPIbhMr6Sry4+0VJg5wNsYwAvEI5JHAI6jR1WHJoiUVSGy1pGelQGdFy1ZQLPUKIO5K24kUEIj0jMavPLADA8pTlsrr2hHCCzpJJA5AyYhQt+9JoI2XMiOCyuMfvHoP2v8vrLjzX9zkAwN9T/y4Wo+oqCLUoor2iW938HW0d8bd7/wYA+CXjF7MLvNU31ovN7wy1jNgqbbF88HIoOAV2Xtkp26pGqDOiMPCytVPaYe3ItQhwDEBRTZGkQc6GKiMcx+GduHfgZOuEM4Vn8HXa15LJICAG9ir0WEY0lrWM9HTvie6u3VGvqcem85vEuB7izkOMF2nnAT+331yEuoSioLoA76W+J9vvRVCchOdWZ4CUEQNp0DSI/T7aixnJqcgxa/XXqGnEgeu8y2JEtxEGf25O3zno49kHpbWleHzX47hQdMFkGayN4KK5L+g+ve/fF3gf/Bz9UFlfieScZLPOdaX0Cho0DXBWOest1tUWUV5ReCLyCQDAwqSF2HVll1lymILwYNV+6HaEk8oJ48P4uKKEzARJ5GCMGRTAKuDn6IeFdy8EAKw9uRbbL2+XRA4BS1hG2rOCtmRaxDQAwOdnPseylGUWS0cnOjdCNd62LCMAX3p9+ZDl4MBh55WdWHJoiUXrKbVFZ8ukAUgZMZiS2hIAfI0HNzu3Vu/7OvjChrNBvaYeN6tNL5B1pvAMbtXegovKBf18+hn8OVuFLT4c8SF6uvVEQXUBZv82G9svb+/0K7W6xjoxOFU7XkQbBacQg79+v2Ze1pAQL9LLvZfRLdBf6v8S7gu8DzWNNVh0YBH+fvjvkqRyG4qxlhEBwZVwIOcAqhuqzZajtLZUPE5HMSMCU8OnYkLoBDRoGvDmwTex9sRas2qAaKMv4FuItzI3ZqSttF5tpveejjfueQMcOPx06SfEfRuH6TumY97eeZifOB9vHngT36R9g9M3T0s2ZqLzIfQpaplJ05L+Pv3x7pB3oeSU2HZ5G+Ynzpe+iV4HdLaCZ4CJysj69esRGhoKtVqN2NhYHDnSfrT+li1b0Lt3b6jVakRHR2PXLuuvKs1FWCm52rnqDSxVKpQIcOJz8c2JG0nMTgTAWwNsFcY1bPJ38sdXE75CnH8cqhuq8ebBN/H0709braW8KSRmJ6KqoQpe9l5iLxh9CCnMiVmJZtUdEVJMDXXRaKO2UePjUR/j2ehnAQDfp3+PCT9NwEt7XsK5wnMmy2QoJTUlAAyLGdGmj2cfBDgGoLqh2mzLEtDsovFUe8JOaWfQZziOw8phKzEneg4APstn47mNZssCWMYy0l4p+JZwHIcn+jyBdaPWwUPtgdrGWpwrOoe92XuxJ2sPtl/Zjn8c/Qce3/U47v/5fnxx9gtcK7vW6RcKhOFomEa872uXgm+LyT0nY82INVApVEi6noT7f74fq4+ttoqLnTHW6QqeASYoI99//z0WLFiApUuX4sSJE4iJicG4ceNQUKBfs0tOTsb06dPxzDPP4OTJk5gyZQqmTJmCc+csf/OWkvbSegXEsvBmxI0I8QhCSqSxOKucsT5+PV7u/zLUSjWO5R/DjF0zcCyv85QhFsityMW7h98FADzY48F2H7J9vfrC39EfVQ1VOHTjkMnn1LaMmIJSocS8AfPwWfxniPOPAwND0vUkTN85Ha/sfcViSsmhnEPYcWUHAH5lZQwcx2F0CF/aPiHLfFeNMS4abRScAq8MeAWLBy0GAHx86mNJ3IntZdNYOoBVm+HdhiPx0UTseGgH3h/+PpbcuwRL7l2Cuf3mYkTQCDjbOiOnIgdrT6zFA788gGHfD8PcPXPx+ZnPkZqbeltUUb5T0U6VFRalHTEyeCQ2T9iMft79UNtYi43nN2LcT+Pw7O/P4of0H3Cj4oZFZC2tLUV5PR9s3ZliRozO6Vm9ejXmzJmDp57i6xhs2LABO3fuxJdffom//vWvrfZfu3Ytxo8fj9dffx0A8O677yIhIQEff/wxNmzYYKb45lFYXYi6xjqD9r1aehVA2wWQgOaJvVh80aQfUkFVAa6UXoENZ9Mqq8QYbBW2eK7vc3ig+wN469BbOJp3FC/sfgGrhq8y+SEsNRqmwaIDi1BaW4q7PO/C3H5z292f4ziMDRmLzWmbsePyjnatKO1hbCZNWwwOHIzBgYORWZqJL85+ge1XtiMxOxGJ2Yno590PcQFxcLR1hJudGwKdAuHr6GtQ3Rh9lNWVYfGBxWBgeLTXoxgaNNToY4wNGYuv075GUnYSssuyDUobbwvhOzQm5kab6b2nIzU3FXuz9+KvB/6Kj0d9bLI8Z26ewaqjqwAAdjbNVhrhu75ZddOka1HoReSpbt2Xpj0UnAIhLiF64waqG6rxR+Yf+CXjF5y9eRYltSXYf32/GLBuw9kg0jMS/o7+cLNzQzfnboj0jESQc1C7LQC6Grdqb+Fi0UXeOgQGJaeEv6M/enn0go+DT5cc65mbZwAAgc6BRqXKRnlF4asJX+FAzgFsOr8JR/OOIjUvFal5fKfwcPdwPND9AYzoNsKg7EpDEBZkPg4+UNt0nl5DHDPCVlhXVwcHBwf8+OOPmDJlirh99uzZKCkpwbZt21p9Jjg4GAsWLMD8+fPFbUuXLsXWrVtx+vRpveepra1FbW1z1kRZWRm6deuG0tJSuLi4GCpuhzy+63GcvqlfhrYYHTwaH478UO97m89vxvvH3jdbrli/WHwx7guzjwMANQ01mL9vPg7lmG5NsCTOKmf88MAPBmnoZ2+exYxdM8w+p4JT4PCMw7C3sTf7WAJXSq7gi7Nf4NfMXy0WkBbpEYmv7//aYNeINhqmwZgtY1BQLZ1v+vHIx7Fo0CKTPltcU4yp26aK7hBz6ebcDSuGrhDbtT+6/VFcKDbf6vLDAz8g0tM0xbc96hrrkF6cjjOFZ3C64DROFJxAflW+5OchrMvQwKH4JP4Tkz+fU5GDX6/+igPXD+D0zdNmNXrsiIG+A7Fp/CaLHV+grKwMrq6uHT6/jbKMFBYWorGxEb6+ukFrvr6+uHjxot7P5OXl6d0/L6/tTpcrVqzAsmXLjBHNJGwVtkbd2FVKlRi7oI9hQcPwzYVvzCqMZae0w8zImSZ/viVqGzU+GvkRlqUswx+Zf4Ch8/ip3ezc8M7gdww2FUZ5RWFY0DCk5qaadd6J3SdKqogAQHe37nhv6Ht4deCr2HZ5G25U3EBlfSWKaoqQU56DwupCs777MNcwfDD8A5MUEYBXwJ6OfhofnfhIkhuco62j2NXYFDzUHlgxdAXe2P+GWUG1ahs1ZvSegaejntZZ5Y0LHYfMskyzAkYj3CPQw62HyZ9vD5VShWjvaER7R2Nm5EwwxnCj8gbOFp5FcXUximuKcaX0CtKK0lBYXWgRGeTCwcYBvTx6IdwtHDYKPuj/Wtk1/HnrTzFjsSuiUqjwQPcHzDpGoFMgno1+Fs9GP4vS2lIkXEvA9svbkVaUJum921Zhiwd7PCjZ8aTAKMvIjRs3EBgYiOTkZMTFxYnb33jjDSQlJSE1tfVDQqVSYfPmzZg+fbq47ZNPPsGyZcuQn69/JWAtywhBEARBEJbDIpYRLy8vKJXKVkpEfn4+/Pz0+4/9/PyM2h8A7OzsYGdn2gqQIAiCIIiuhVHZNCqVCgMHDsSePXvEbRqNBnv27NGxlGgTFxensz8AJCQktLk/QRAEQRB3FkZn0yxYsACzZ8/G3XffjUGDBuHDDz9EZWWlmF0za9YsBAYGYsWKFQCAefPmYfjw4fjggw8wceJEfPfddzh27Bg+//xzaUdCEARBEESXxGhlZNq0abh58ybefvtt5OXloV+/fvjtt9/EINWsrCydctWDBw/Gf//7X7z11lt48803ER4ejq1btyIqKkq6URAEQRAE0WUxKoBVLgwNgCEIgiAIovNg6PObetMQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErpIwQBEEQBCErRpeDlwOhSGxZWZnMkhAEQRAEYSjCc7ujYu9dQhkpLy8HAHTr1k1mSQiCIAiCMJby8nK4urq2+X6X6E2j0Whw48YNODs7g+M4yY5bVlaGbt26ITs7+7bteUNj7Prc7uMDaIy3A7f7+IDbf4yWGB9jDOXl5QgICNBpotuSLmEZUSgUCAoKstjxXVxcbssfljY0xq7P7T4+gMZ4O3C7jw+4/cco9fjas4gIUAArQRAEQRCyQsoIQRAEQRCyckcrI3Z2dli6dCns7OzkFsVi0Bi7Prf7+AAa4+3A7T4+4PYfo5zj6xIBrARBEARB3L7c0ZYRgiAIgiDkh5QRgiAIgiBkhZQRgiAIgiBkhZQRgiAIgiBk5Y5WRtavX4/Q0FCo1WrExsbiyJEjcotkEitWrMA999wDZ2dn+Pj4YMqUKUhPT9fZZ8SIEeA4Tuff888/L5PExvPOO++0kr93797i+zU1NZg7dy48PT3h5OSEhx9+GPn5+TJKbDyhoaGtxshxHObOnQug683h/v37MWnSJAQEBIDjOGzdulXnfcYY3n77bfj7+8Pe3h7x8fG4dOmSzj7FxcWYOXMmXFxc4ObmhmeeeQYVFRVWHEX7tDfG+vp6LFq0CNHR0XB0dERAQABmzZqFGzdu6BxD37yvXLnSyiNpm47m8cknn2wl//jx43X26czz2NH49F2THMdh1apV4j6deQ4NeT4Ycv/MysrCxIkT4eDgAB8fH7z++utoaGiQTM47Vhn5/vvvsWDBAixduhQnTpxATEwMxo0bh4KCArlFM5qkpCTMnTsXhw8fRkJCAurr6zF27FhUVlbq7Ddnzhzk5uaK//75z3/KJLFp3HXXXTryHzx4UHzv1Vdfxfbt27FlyxYkJSXhxo0bmDp1qozSGs/Ro0d1xpeQkAAAeOSRR8R9utIcVlZWIiYmBuvXr9f7/j//+U989NFH2LBhA1JTU+Ho6Ihx48ahpqZG3GfmzJk4f/48EhISsGPHDuzfvx/PPfectYbQIe2NsaqqCidOnMCSJUtw4sQJ/Pzzz0hPT8eDDz7Yat/ly5frzOvLL79sDfENoqN5BIDx48fryP/tt9/qvN+Z57Gj8WmPKzc3F19++SU4jsPDDz+ss19nnUNDng8d3T8bGxsxceJE1NXVITk5GZs3b8amTZvw9ttvSycou0MZNGgQmzt3rvj/xsZGFhAQwFasWCGjVNJQUFDAALCkpCRx2/Dhw9m8efPkE8pMli5dymJiYvS+V1JSwmxtbdmWLVvEbRcuXGAAWEpKipUklJ558+axHj16MI1Gwxjr2nMIgP3yyy/i/zUaDfPz82OrVq0St5WUlDA7Ozv27bffMsYYS0tLYwDY0aNHxX1+/fVXxnEcy8nJsZrshtJyjPo4cuQIA8CuXbsmbgsJCWFr1qyxrHASoW+Ms2fPZpMnT27zM11pHg2Zw8mTJ7NRo0bpbOtKc9jy+WDI/XPXrl1MoVCwvLw8cZ9PP/2Uubi4sNraWknkuiMtI3V1dTh+/Dji4+PFbQqFAvHx8UhJSZFRMmkoLS0FAHh4eOhs/89//gMvLy9ERUVh8eLFqKqqkkM8k7l06RICAgLQvXt3zJw5E1lZWQCA48ePo76+Xmc+e/fujeDg4C47n3V1dfjmm2/w9NNP6zSH7OpzKHD16lXk5eXpzJmrqytiY2PFOUtJSYGbmxvuvvtucZ/4+HgoFAqkpqZaXWYpKC0tBcdxcHNz09m+cuVKeHp6on///li1apWk5m9rsG/fPvj4+CAiIgIvvPACioqKxPdup3nMz8/Hzp078cwzz7R6r6vMYcvngyH3z5SUFERHR8PX11fcZ9y4cSgrK8P58+clkatLNMqTmsLCQjQ2Nup8sQDg6+uLixcvyiSVNGg0GsyfPx9DhgxBVFSUuH3GjBkICQlBQEAAzpw5g0WLFiE9PR0///yzjNIaTmxsLDZt2oSIiAjk5uZi2bJlGDp0KM6dO4e8vDyoVKpWN3hfX1/k5eXJI7CZbN26FSUlJXjyySfFbV19DrUR5kXfNSi8l5eXBx8fH533bWxs4OHh0SXntaamBosWLcL06dN1mpC98sorGDBgADw8PJCcnIzFixcjNzcXq1evllFawxk/fjymTp2KsLAwXL58GW+++SYmTJiAlJQUKJXK22oeN2/eDGdn51Yu4K4yh/qeD4bcP/Py8vReq8J7UnBHKiO3M3PnzsW5c+d04ikA6Phno6Oj4e/vj9GjR+Py5cvo0aOHtcU0mgkTJoh/9+3bF7GxsQgJCcEPP/wAe3t7GSWzDP/+978xYcIEBAQEiNu6+hzeydTX1+PRRx8FYwyffvqpznsLFiwQ/+7bty9UKhX+8pe/YMWKFV2i7Phjjz0m/h0dHY2+ffuiR48e2LdvH0aPHi2jZNLz5ZdfYubMmVCr1Trbu8octvV86AzckW4aLy8vKJXKVtHC+fn58PPzk0kq83nppZewY8cOJCYmIigoqN19Y2NjAQAZGRnWEE1y3Nzc0KtXL2RkZMDPzw91dXUoKSnR2aerzue1a9ewe/duPPvss+3u15XnUJiX9q5BPz+/VgHlDQ0NKC4u7lLzKigi165dQ0JCQoet2WNjY9HQ0IDMzEzrCCgx3bt3h5eXl/i7vF3m8cCBA0hPT+/wugQ65xy29Xww5P7p5+en91oV3pOCO1IZUalUGDhwIPbs2SNu02g02LNnD+Li4mSUzDQYY3jppZfwyy+/YO/evQgLC+vwM6dOnQIA+Pv7W1g6y1BRUYHLly/D398fAwcOhK2trc58pqenIysrq0vO58aNG+Hj44OJEye2u19XnsOwsDD4+fnpzFlZWRlSU1PFOYuLi0NJSQmOHz8u7rN3715oNBpREevsCIrIpUuXsHv3bnh6enb4mVOnTkGhULRybXQVrl+/jqKiIvF3eTvMI8BbKwcOHIiYmJgO9+1Mc9jR88GQ+2dcXBzOnj2ro1QKinWfPn0kE/SO5LvvvmN2dnZs06ZNLC0tjT333HPMzc1NJ1q4q/DCCy8wV1dXtm/fPpabmyv+q6qqYowxlpGRwZYvX86OHTvGrl69yrZt28a6d+/Ohg0bJrPkhvPaa6+xffv2satXr7JDhw6x+Ph45uXlxQoKChhjjD3//PMsODiY7d27lx07dozFxcWxuLg4maU2nsbGRhYcHMwWLVqks70rzmF5eTk7efIkO3nyJAPAVq9ezU6ePClmkqxcuZK5ubmxbdu2sTNnzrDJkyezsLAwVl1dLR5j/PjxrH///iw1NZUdPHiQhYeHs+nTp8s1pFa0N8a6ujr24IMPsqCgIHbq1Cmda1PIQEhOTmZr1qxhp06dYpcvX2bffPMN8/b2ZrNmzZJ5ZM20N8by8nK2cOFClpKSwq5evcp2797NBgwYwMLDw1lNTY14jM48jx39ThljrLS0lDk4OLBPP/201ec7+xx29HxgrOP7Z0NDA4uKimJjx45lp06dYr/99hvz9vZmixcvlkzOO1YZYYyxdevWseDgYKZSqdigQYPY4cOH5RbJJADo/bdx40bGGGNZWVls2LBhzMPDg9nZ2bGePXuy119/nZWWlsoruBFMmzaN+fv7M5VKxQIDA9m0adNYRkaG+H51dTV78cUXmbu7O3NwcGAPPfQQy83NlVFi0/j9998ZAJaenq6zvSvOYWJiot7f5ezZsxljfHrvkiVLmK+vL7Ozs2OjR49uNe6ioiI2ffp05uTkxFxcXNhTTz3FysvLZRiNftob49WrV9u8NhMTExljjB0/fpzFxsYyV1dXplarWWRkJHvvvfd0HuRy094Yq6qq2NixY5m3tzeztbVlISEhbM6cOa0WdZ15Hjv6nTLG2Geffcbs7e1ZSUlJq8939jns6PnAmGH3z8zMTDZhwgRmb2/PvLy82Guvvcbq6+slk5NrEpYgCIIgCEIW7siYEYIgCIIgOg+kjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEQRAEISukjBAEIRsjRozA/Pnz5RaDIAiZIWWEIAiCIAhZoXLwBEHIwpNPPonNmzfrbLt69SpCQ0PlEYggCNkgZYQgCFkoLS3FhAkTEBUVheXLlwMAvL29oVQqZZaMIAhrYyO3AARB3Jm4urpCpVLBwcEBfn5+cotDEISMUMwIQRAEQRCyQsoIQRAEQRCyQsoIQRCyoVKp0NjYKLcYBEHIDCkjBEHIRmhoKFJTU5GZmYnCwkJoNBq5RSIIQgZIGSEIQjYWLlwIpVKJPn36wNvbG1lZWXKLRBCEDFBqL0EQBEEQskKWEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZIWUEYIgCIIgZOX/A//A4qlarP5NAAAAAElFTkSuQmCC", + "image/png": 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", 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", + "image/png": 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", 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", + "image/png": 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/vNPv22w2V3rDiIiIICYmxrYCol+/frRr145Zs2ZVWuKqaVqNt3/jjTeyfv36KptaZWZmUlpaanfeggULOH36tO3nTZs2sXHjxhozNFWtAunTpw9Qvorj6quvJiUlhW+++cZ2TGlpKe+88w4BAQGMGDHCdlxpaSmzZ8+2HWc2m3nnnXfsbj8iIoKRI0fy4Ycf2moRKqprlqGubrzxRk6fPl1l/U9BQYFdF9NBgwbh6enJa6+9RmhoKD169ABUkLJhwwZWrlxplxWB8pqRupwq1oxcOM0GUFJSwueff46vr2+NmTyLxcJTTz2Fn58fDz74oN31Dxw4UOXvtb6++eYbNm/ezOOPP16n5cFCSGZEXHS8vLz4/vvvGTVqFJdddpldB9Z58+axbds2/vrXv1bq0VAXWVlZfPnll1Vedtttt5GTk0NsbCzXX3898fHxBAQEsHTpUjZv3sybb74JqKzD7NmzmTBhAn369OGuu+4iOjqaAwcO1No988knn+Tnn39m/Pjx3HnnnfTv35+8vDx2797N999/z4kTJwgPD7cd37FjRy677DKmTJlCUVERs2bNIiwsrNppHlCdcFetWsU111xDmzZtSEtL4/333yc2Ntb2yfj+++/nww8/5M4772Tr1q20bduW77//nrVr1zJr1ixbLc6ECRMYOnQozzzzDCdOnKB79+78+OOPVX7Cf++997jsssvo1asX9913H+3btyc1NZX169dz6tQpdu7caTvWmtk5ceJEtY+jJrfffjvffvstDz74ICtWrGDo0KGYzWYOHDjAt99+y+LFi21Thn5+fvTv358NGzbYeoyAyozk5eWRl5dXKRipb83IAw88QHZ2NsOHD6dVq1akpKTw1VdfceDAAd5880277NJjjz1GYWEhffr0oaSkhHnz5rFp0ybmzp1rNz15+vRpunXrxh133GG3F9CqVatYtWoVoIK9vLw8Xn75ZdtjGz58uO24F198kauuuoqwsDA2bNjAZ599xtixY2tchi6EHVcv5xGiNtV1YL1QdR1Yq5OWlqZNmzZN69ixo+bt7a2FhIRoo0ePdmg5b0U1Le21/qsVFRVpTz75pBYfH68FBgZq/v7+Wnx8vPb+++9Xur01a9ZoV155pe243r17a++8806t48jJydGmT5+udezYUfPy8tLCw8O1IUOGaP/+97+14uJiTdPKl5a+8cYb2ptvvqnFxcVp3t7e2rBhw7SdO3fa3d6FS3uXLVumTZw4UYuJidG8vLy0mJgY7ZZbbqm0nDg1NVW76667tPDwcM3Ly0vr1atXlR1Vz507p91+++1aUFCQFhwcrN1+++3a9u3bq+zAevToUW3y5MlaVFSU5unpqbVq1UobP358peWj4eHh2qWXXlrr76qmrrnFxcXaa6+9pvXo0UPz9vbWWrRoofXv31974YUXtKysLLtjn3zySQ3QXnvtNbvzO3bsqAHa0aNHax1LXXz99dfa6NGjtcjISM3Dw0Nr0aKFNnr0aG3hwoWVjv3ss8+0+Ph4zd/fXwsMDNRGjRqlLV++vNJx1r+FO+64w+586/Ne1en555+3HXfkyBHtqquu0sLDwzVvb2+ta9eu2owZM7SioiKnPGZxcTBoWi15XyFEs3PixAnatWvHG2+8wRNPPOHq4TjVvn376NGjB7/88gvXXHONq4cjhKgDmcwTQjQrK1asYPDgwRKICOFGpGZEiFqkp6djNpurvdzLy4vQ0NAmHJGoydSpU5k6daqrhyGEcIAEI0LUYuDAgbYmXVUZMWIECQkJTTcgIYRoZqRmRIharF27tsaW1i1atKB///5NOCIhhGheJBgRQgghhEtJAasQQgghXMotakYsFgtnzpwhMDCw1tbMQgghhNAHTdPIyckhJiamxm68bhGMnDlzxm5jKiGEEEK4j5MnTxIbG1vt5W4RjFhbR588eZKgoCAXj0YIIYQQdZGdnU1cXJztfbw6bhGMWKdmgoKCJBgRQggh3ExtJRZSwCqEEEIIl5JgRAghhBAuJcGIEEIIIVzKLWpGhBBCXJzMZjMlJSWuHoaohqenJyaTqcG3I8GIEEII3dE0jZSUFDIzM109FFGLkJAQoqKiGtQHTIIRIYQQumMNRCIiIvDz85OGlzqkaRr5+fmkpaUBEB0dXe/bkmBECCGErpjNZlsgEhYW5urhiBr4+voCkJaWRkRERL2nbKSAVQghhK5Ya0T8/PxcPBJRF9bnqSG1PRKMCCGE0CWZmnEPznieJBgRQgghhEtJMCKEEEI4yciRI3n88cervbxt27bMmjWrycbjLqSAVQghhGgimzdvxt/f39XD0B0JRpoRTdMwWzQ8TFUnvEotpXgY5SkXQghXadmypauHoEsyTdOM/Hf1MTr+/Tfu+mwTG4+dQ9M022V/X/N3Rn03iszCTNcNUAghLgKlpaU8/PDDBAcHEx4ezrPPPmt7Pb5wmiYpKYmJEycSEBBAUFAQN954I6mpqbbL//nPf9KnTx8+/fRTWrduTUBAAA899BBms5nXX3+dqKgoIiIieOWVV+zG8NZbb9GrVy/8/f2Ji4vjoYceIjc313Z5YmIiEyZMoEWLFvj7+9OjRw8WLVoEwPnz57n11ltp2bIlvr6+dOrUic8++6wRf2OSGWlWftmVDMCKg+msOJjOP67pxr3D2gOw5vQaMgozOJF9gj4+fVw4SiGEcJymaRSUmJv8fn09TQ6vFpk7dy733HMPmzZtYsuWLdx///20bt2a++67z+44i8ViC0RWrlxJaWkpU6dO5aabbiIhIcF23NGjR/ntt9/4/fffOXr0KNdffz3Hjh2jc+fOrFy5knXr1nH33XczevRoBg0aBIDRaOQ///kP7dq149ixYzz00EM89dRTvP/++wBMnTqV4uJiVq1ahb+/P/v27SMgIACAZ599ln379vHbb78RHh7OkSNHKCgoaMBvsXYSjDQTJWYLB5JzALi8S0tWHEzn+62nuHdYeyyahayiLAA0tJpuRgghdKmgxEz35xY3+f3ue3EMfl6OvVXGxcUxc+ZMDAYDXbp0Yffu3cycObNSMLJs2TJ2797N8ePHiYuLA+Dzzz+nR48ebN68mYEDBwIqaPn0008JDAyke/fuXH755Rw8eJBFixZhNBrp0qULr732GitWrLAFIxWLaNu2bcvLL7/Mgw8+aAtGkpKS+POf/0yvXr0AaN++ve34pKQk+vbty4ABA2zXb2wyTdNMHE7NpdhsIdDHg39dp/64DqflUlBsJqc4B7OmPlFYNIsrhymEEM3epZdeapdNGTx4MIcPH8Zsts/s7N+/n7i4OFsgAtC9e3dCQkLYv3+/7by2bdsSGBho+zkyMpLu3btjNBrtzrO2ZQdYunQpo0aNolWrVgQGBnL77bdz7tw58vPzAXj00Ud5+eWXGTp0KM8//zy7du2yXXfKlCnMnz+fPn368NRTT7Fu3Ton/FZqJpmRZmLPGZX56BkTTHSwLxGB3qTlFLH3TBZhLbJsx0kwIoRwR76eJva9OMYl9+tqnp6edj8bDIYqz7NY1Ov7iRMnGD9+PFOmTOGVV14hNDSUNWvWcM8991BcXIyfnx/33nsvY8aM4ddff+WPP/5gxowZvPnmmzzyyCOMGzeOxMREFi1axJIlSxg1ahRTp07l3//+d6M9RsmMNBN7TpcFI62CAOgdGwzArlNZZBZlumpYQgjhFAaDAT8vjyY/1ae76MaNG+1+3rBhA506daq0b0u3bt04efIkJ0+etJ23b98+MjMz6d69e/1+UcDWrVuxWCy8+eabXHrppXTu3JkzZ85UOi4uLo4HH3yQH3/8kb/+9a/897//tV3WsmVL7rjjDr788ktmzZrFRx99VO/x1IUEI81EeTCigpDesSEA7DqVSUZhhu04yYwIIUTjSkpKYtq0aRw8eJCvv/6ad955h8cee6zScaNHj6ZXr17ceuutbNu2jU2bNjF58mRGjBhhq9eoj44dO1JSUsI777zDsWPH+OKLL/jggw/sjnn88cdZvHgxx48fZ9u2baxYsYJu3boB8Nxzz7Fw4UKOHDnC3r17+eWXX2yXNRYJRpoBs0VjX3I2AD1irMFIhcxIheW8EowIIUTjmjx5MgUFBVxyySVMnTqVxx57jPvvv7/ScQaDgYULF9KiRQuGDx/O6NGjad++Pd98802D7j8+Pp633nqL1157jZ49e/LVV18xY8YMu2PMZjNTp06lW7dujB07ls6dO9uKW728vJg+fTq9e/dm+PDhmEwm5s+f36Ax1cagVWxGoVPZ2dkEBweTlZVFUFCQq4ejO4dTc7hy5ir8vEzs/ucYTEYDGXnF9HtpCQBP3HiKD3e/C8CHoz9kSKshrhyuEELUqLCwkOPHj9OuXTt8fHxcPRxRi5qer7q+f0tmpBmwFq92jw7CZFTzm6H+XsS28AXg6LnyBjqytFcIIYTeSDDSDOw5raZorPUiVvFldSMns87azpNpGiGEEHojwUgzYC1e7RFjnwLrVVY3kpZ/znaeZEaEEELojQQjzcDBVNV5tfsFwYi1iDWrwtJeyYwIIYTQGwlG3FxRqZnM/BIAYoJ97S5rHeoHgNmQYzvPDeqVhRBCXGQcCkZmz55N7969CQoKIigoiMGDB/Pbb79Ve/ycOXMwGAx2J6mMdq5zucUAeBgNBPvad+TzsLYKNuXZzrMgmREhhBD64lA7+NjYWF599VU6deqEpmnMnTuXiRMnsn37dnr06FHldYKCgjh48KDt5/p0sxPVswYjYQFeGI32v1ujETCUYDAW286TzIgQQgi9cSgYmTBhgt3Pr7zyCrNnz2bDhg3VBiMGg4GoqKj6j1DU6GxuEQDhAd6VLvMwGjGY8u3OkwJWIYQQelPvmhGz2cz8+fPJy8tj8ODB1R6Xm5tLmzZtiIuLY+LEiezdu7e+dymqkF5DMGIyGjCYcu3OkwJWIYQQeuPwrr27d+9m8ODBFBYWEhAQwE8//VTthj5dunTh008/pXfv3mRlZfHvf/+bIUOGsHfvXmJjY6u9j6KiIoqKimw/Z2dnOzrMi0bNmREDBo8LMiMyTSOEEEJnHM6MdOnShR07drBx40amTJnCHXfcwb59+6o8dvDgwUyePJk+ffowYsQIfvzxR1q2bMmHH35Y433MmDGD4OBg2ykuLs7RYV40zuaoepDwQK9Kl6nMSJ7deZIZEUII99W2bVtmzZrl6mE4ncPBiJeXFx07dqR///7MmDGD+Ph43n777Tpd19PTk759+3LkyJEaj5s+fTpZWVm2U8XtlYU9W2bEv7ppGvtgRGpGhBBC6E2D+4xYLBa7KZWamM1mdu/eTXR0dI3HeXt725YPW0+iarZgpKrMiEEyI0II0ZRGjhzJI488wuOPP06LFi2IjIzkv//9L3l5edx1110EBgbSsWNHW1uMAQMG8O9//9t2/UmTJuHp6Ulurqr3O3XqFAaDgSNHjjBy5EgSExP5y1/+YmuX0Vw4FIxMnz6dVatWceLECXbv3s306dNJSEjg1ltvBdS2ydOnT7cd/+KLL/LHH39w7Ngxtm3bxm233UZiYiL33nuvcx/FRaymmhGj0YDRQzIjQohmQNOgOK/pT/Wos5s7dy7h4eFs2rSJRx55hClTpnDDDTcwZMgQtm3bxlVXXcXtt99Ofn4+I0aMICEhoewhaqxevZqQkBDWrFkDwMqVK2nVqhUdO3bkxx9/JDY2lhdffJHk5GSSk5Od+Rt2KYcKWNPS0pg8eTLJyckEBwfTu3dvFi9ezJVXXglAUlISRmN5fHP+/Hnuu+8+UlJSaNGiBf3792fdunXVFrwKx50t6zNSVTACYLyggFUyI0IIt1SSD/+Kafr7/dsZ8PJ36Crx8fH84x//ANSH+FdffZXw8HDuu+8+AJ577jlmz57Nrl27GDlyJJ988glms5k9e/bg5eXFTTfdREJCAmPHjiUhIYERI0YAEBoaislkIjAwsNm1zHAoGPnkk09qvNwa3VnNnDmTmTNnOjwoUTelZgvn82sLRi7IjMhqGiGEaFS9e/e2fW8ymQgLC6NXr1628yIjIwH1AX/48OHk5OSwfft21q1bx4gRIxg5ciSvvvoqoDIjTz75ZNM+ABdweGmv0I+M/GI0DYwGCPWvXDMC2FrBexm9KbYUyTSNEMI9efqpLIUr7tfRq3jab81hMBjszrPWelgsFkJCQoiPjychIYH169dz5ZVXMnz4cG666SYOHTrE4cOHbZmR5kyCETdmXdYb6u+FyVh1IZO1gDXEO5S0gmSZphFCuCeDweHpEncxYsQIVqxYwaZNm3jllVcIDQ2lW7duvPLKK0RHR9O5c2fbsV5eXpjNZheOtnHIrr1urKbiVSirDzGqmpEgrxaAFLAKIYTejBw5ksWLF+Ph4UHXrl1t53311VeVsiJt27Zl1apVnD59mrNnz7piuI1CghE3VlswklOcAwaVCQn0DAGkZkQIIfRm2LBhWCwWu8Bj5MiRmM1mRo4caXfsiy++yIkTJ+jQoQMtW7Zs4pE2HpmmcWPWYCQsoOp6kZziHAA0iyeeBnWMTNMIIUTjuXAhB8CJEycqnVfxg2FoaCgWi/1r86RJk6r88HjppZeyc+fOBo9TbyQz4sZqW9Zr+0PWjEBZwZQEI0IIIXRGghE3djanlpoRrIGHAWswIjUjQggh9EaCETeWbqsZqXqapmIWxBqCSM2IEEIIvZFgxI2ds07TBNZhmkaTaRohhBD6JMGIG7MWsLasrmakLB+iyTSNEEIIHZNgxE1ZLBrn8mouYC3PglQIRmSaRgghhM5IMOKmMgtKMFtUYFFdK3i7YMQ6TYNM0wghhNAXCUbclHWKJtjXEy+Pqp9G25SMVp4ZkZoRIYQQeiPBiJvKKigBoIWfZ7XHVMyMaFS9d40QQgjhahKMuKnssmAkyLf6YKS8PsSA9VvJjAghhNAbCUbcVE5hKQCBPtV39LcFHjJNI4QQQsckGHFT2YVlmRGfGqZpqFzAKqtphBCi6RQXF7t6CG5BghE3Zc2M1BSM2E3TSJ8RIYRodCNHjuThhx/m8ccfJzw8nDFjxrBnzx7GjRtHQEAAkZGR3H777Zw9exaAX375hZCQEMxmMwA7duzAYDDwzDPP2G7z3nvv5bbbbnPJ42kqEoy4KWvNSE3TNBVX00jNiBDCnWmaRn5JfpOf6pNNnjt3Ll5eXqxdu5ZXX32VK664gr59+7JlyxZ+//13UlNTufHGGwEYNmwYOTk5bN++HYCVK1cSHh5ut/vvypUrGTlypDN+jbpV/TuZ0LVsa2akhgJWa+ChVewzIsGIEMINFZQWMGjeoCa/343/txE/Tz+HrtOpUydef/11AF5++WX69u3Lv/71L9vln376KXFxcRw6dIjOnTvTp08fEhISGDBgAAkJCfzlL3/hhRdeIDc3l6ysLI4cOcKIESOc+rj0RjIjbspaM1KnAlaZphFCiCbTv39/2/c7d+5kxYoVBAQE2E5du3YF4OjRowCMGDGChIQENE1j9erVXHfddXTr1o01a9awcuVKYmJi6NSpk0seS1ORzIibsi3trUvNiGawbdsrBaxCCHfk6+HLxv/b6JL7dZS/v7/t+9zcXCZMmMBrr71W6bjo6GhA1Zl8+umn7Ny5E09PT7p27crIkSNJSEjg/PnzzT4rAhKMuK06Le2tsJpGk3bwQgg3ZjAYHJ4u0YN+/frxww8/0LZtWzw8qn69ttaNzJw50xZ4jBw5kldffZXz58/z17/+tSmH7BIyTeOmbEt761AzUjEYkcyIEEI0nalTp5KRkcEtt9zC5s2bOXr0KIsXL+auu+6yraBp0aIFvXv35quvvrIVqg4fPpxt27Zx6NChiyIzIsGIm6pLZqRi4KHJrr1CCNHkYmJiWLt2LWazmauuuopevXrx+OOPExISgtFY/hY8YsQIzGazLRgJDQ2le/fuREVF0aVLFxeNvunINI2bqkvNSHkHVmP50l6ZphFCiEZTcUmuVadOnfjxxx9rvN6sWbOYNWuW3Xk7duxw3sB0TjIjbqio1ExRqQoqatybhop700hmRAghhD5JMOKGrFM0AAHedZmmkb1phBBC6JcEI27IVi/i7YHJaKj2uIob5Vks0mdECCGEPkkw4obq0goeLtgoz3qeZEaEEELojAQjbiinDq3goXyaRsOARZqeCSHcjLxeuQdnPE8SjLihurSCB/tpGlsBq0zTCCF0ztNTfdDKz8938UhEXVifJ+vzVh+ytNcN5RTWvqwXLuzAWnaeTNMIIXTOZDIREhJCWloaAH5+fhgM1dfHCdfQNI38/HzS0tIICQnBZDLV+7YkGHFD2QW1NzyDC5qeSWZECOFGoqKiAGwBidCvkJAQ2/NVXxKMuKG6tIKHilkQo61mRDIjQgh3YDAYiI6OJiIigpKSElcPR1TD09OzQRkRK4eCkdmzZzN79mxOnDgBQI8ePXjuuecYN25ctdf57rvvePbZZzlx4gSdOnXitdde4+qrr27QoC92tgLW2qZpqqoZkYIwIYQbMZlMTnmzE/rmUAFrbGwsr776Klu3bmXLli1cccUVTJw4kb1791Z5/Lp167jlllu455572L59O5MmTWLSpEns2bPHKYO/WNV1aW+5CqtpZJpGCCGEzjgUjEyYMIGrr76aTp060blzZ1555RUCAgLYsGFDlce//fbbjB07lieffJJu3brx0ksv0a9fP959912nDP5ilV3Hpb1V7dor0zRCCCH0pt5Le81mM/PnzycvL4/BgwdXecz69esZPXq03Xljxoxh/fr1Nd52UVER2dnZdidRriFLeyUYEUIIoTcOByO7d+8mICAAb29vHnzwQX766Se6d+9e5bEpKSlERkbanRcZGUlKSkqN9zFjxgyCg4Ntp7i4OEeH2azVtWak4kZ5Mk0jhBBCrxwORrp06cKOHTvYuHEjU6ZM4Y477mDfvn1OHdT06dPJysqynU6ePOnU23d3dW4HX5YF0Sr0GZECViGEEHrj8NJeLy8vOnbsCED//v3ZvHkzb7/9Nh9++GGlY6OiokhNTbU7LzU1tdb1yN7e3nh7ezs6tItGjqNLezUDFgtgkmkaIYQQ+tPgdvAWi4WioqIqLxs8eDDLli2zO2/JkiXV1piI2lksGjlFjjc9s0jTMyGEEDrlUGZk+vTpjBs3jtatW5OTk8O8efNISEhg8eLFAEyePJlWrVoxY8YMAB577DFGjBjBm2++yTXXXMP8+fPZsmULH330kfMfyUUir7jUNuVS93bwRukzIoQQQrccCkbS0tKYPHkyycnJBAcH07t3bxYvXsyVV14JQFJSEkZjebJlyJAhzJs3j3/84x/87W9/o1OnTixYsICePXs691FcRKzLer08jPh41twIqOLSXunAKoQQQq8cCkY++eSTGi9PSEiodN4NN9zADTfc4NCgRPXKN8lz4Kmz1oxQMVsihBBC6EODa0ZE07JuklfbFA1ckBmxlO14KbM0QgghdEaCETfjSCt4+2kaFYVIZkQIIYTeSDDiZnKK6rasFyoUq0oHViGEEDomwYibsU7T1CkzQuUCVllNI4QQQm8kGHEzudYeI951rxnRKtSMSJ8RIYQQeiPBiJux7kvj7117ZqRiFsRsXU0j0zRCCCF0RoIRN5NXlhkJcKSAVTPKNI0QQgjdkmDEzdiCEe+aG55BNTUjMk0jhBBCZyQYcTPWfWnqMk1THncY0CyymkYIIYQ+STDiZsozIw6sptEMUjMihBBCtyQYcTMOBSNV7E0j0zRCCCH0RoIRN+PINE15sWp5ZkQKWIUQQuiNBCNupl6ZEc2ANQaRdvBCCCH0RoIRN5NXZAYcrBlBNT4DyYwIIYTQHwlG3IjFotk6sDo2TWPE+lRLAasQQgi9kWDEjeSXmG3fOzJNo2kG0KQdvBBCCH2SYMSNWOtFTEYDPp61P3UVV9NYyTSNEEIIvZFgxI3Y9qXxMmEwGGo5uiID1oBEpmmEEELojQQjbsSRlTRQHngYkGkaIYQQ+iXBiBtxZJM8KA9GjAbJjAghhNAvCUbciEP70lAxC2IEWdorhBBCpyQYcSP1naaxy4xI0zMhhBA6I8GIG6l/MGIsrxmRzIgQQgidkWDEjeSWdV91dJrGaKgwTSMFrEIIIXRGghE3kltUAtRvmkaTAlYhhBA6JcGIG8mzZUZMdTq+fGlv+TSNBCNCCCH0RoIRN5JrqxnxdOh6FadphBBCCL2RYMSN5BZagxHHMiPGCt1aJTMihBBCbyQYcSN5xY71GbFbTSM1I0IIIXRKghE3kuvg0l7rMl5TxaW9sppGCCGEzkgw4kbKp2nqmBkpa3BmqND0TPqMCCGE0BsJRtxInoPt4K1TMiaZphFCCKFjEoy4kVwHN8qzZkGk6ZkQQgg9k2DETWia5nDNiK2A1Sjt4IUQQuiXQ8HIjBkzGDhwIIGBgURERDBp0iQOHjxY43XmzJmDwWCwO/n4+DRo0BejwhILlrI4os7TNFSxmkY2yhNCCKEzDgUjK1euZOrUqWzYsIElS5ZQUlLCVVddRV5eXo3XCwoKIjk52XZKTExs0KAvRtasCICfZ936jFhnZIxIO3ghhBD6VbeP2GV+//13u5/nzJlDREQEW7duZfjw4dVez2AwEBUVVb8RCsB+Wa/RWLduqtYsiEmmaYQQQuhYg2pGsrKyAAgNDa3xuNzcXNq0aUNcXBwTJ05k7969Dbnbi1L5Spo6ZkWoejWNFLAKIYTQm3oHIxaLhccff5yhQ4fSs2fPao/r0qULn376KQsXLuTLL7/EYrEwZMgQTp06Ve11ioqKyM7Otjtd7HIdXNYLFVbTGMufZpmmEUIIoTcOTdNUNHXqVPbs2cOaNWtqPG7w4MEMHjzY9vOQIUPo1q0bH374IS+99FKV15kxYwYvvPBCfYfWLFkbngU6EIyUZ0ak6ZkQQgj9qldm5OGHH+aXX35hxYoVxMbGOnRdT09P+vbty5EjR6o9Zvr06WRlZdlOJ0+erM8wmxVH96WBC1bTaOqplmkaIYQQeuNQZkTTNB555BF++uknEhISaNeuncN3aDab2b17N1dffXW1x3h7e+Pt7e3wbTdnDZqmMZiQDqxCCCH0yqFgZOrUqcybN4+FCxcSGBhISkoKAMHBwfj6+gIwefJkWrVqxYwZMwB48cUXufTSS+nYsSOZmZm88cYbJCYmcu+99zr5oTRvDZmm8ahQMyLTNEIIIfTGoWBk9uzZAIwcOdLu/M8++4w777wTgKSkJLuCyfPnz3PfffeRkpJCixYt6N+/P+vWraN79+4NG/lFxtF9aaBCB1ZpeiaEEELHHJ6mqU1CQoLdzzNnzmTmzJkODUpUlltkBhwLRqykz4gQQgg9k71p3ERuUQkAAfXoM2KsuJoGTQISIYQQuiLBiJvIK8uM1HWTPCifklE1I+VdW2VFjRBCCD2RYMRNNGw1jRFNM1Q6XwghhNADCUbchDUYCfSp72qa8mBEiliFEELoiQQjbsK6tDfA27PO1ymvGSnvMwKSGRFCCKEvEoy4ifpkRqy1ISZjeQErSOMzIYQQ+iLBiJvILixbTVOPaRqTwWRb2gtSwCqEEEJfJBhxA5qmlWdG6t2BVaZphBBC6JMEI24gv9iMNX5wJDNiZTLaP80yTSOEEEJPHH9nE03OmhUxGQ34ejre9MzDaKTizIysphFCCKEnkhlxAzm2lTQeGAyGWo4uV14zItM0Qggh9EuCETdgzYw40n0VKq6mkWBECCGEfkkw4gZyylbSOLKsF6TpmRBCCPcgwYgbyC2sX2bENk1jlKZnQggh9EuCETeQY52mcTAzYg06PKyrabTynXuFEEIIvZBgxA1YMyOBPnVvBQ/l0zHlS3tVMCJLe4UQQuiJBCNuoL4FrLaaEYN6mg0SjAghhNAhCUbcQH0LWK2zMapmBCrWjQghhBB6IcGIG6h3ZqRsmsZTpmmEEELomAQjbiCnoatpTBKMCCGE0C8JRtyAbZO8eq+msZ+mkaW9Qggh9ESCETdQvpqmftM0JqO1VkSW9gohhNAfCUbcQHnNiINLe20dWMsyI5pM0wghhNAfCUbcgK1mxEnTNNIOXgghhJ5IMOIGrEt761vA6nlBAavM0gghhNATCUZ0TtM02zRNkKOZEeuuvQZZTSOEEEK/JBjRuYISM5ayTEZ9p2k8bTUj6otM0wghhNATCUZ0zrqSxmgAX09TLUfbsxWw2qZp1FdZ2iuEEEJPJBjRuewKDc8MBsfauVszIB4mFcRosmuvEEIIHZJgROfKG545tqwXKk7T2AcxUjMihBBCTyQY0bn6NjyDCu3gpQOrEEIIHZNgROdyi+q3rFfTNNt0jLWAVZOmZ0IIIXRIghGdq3fDswp1IdaaEWkHL4QQQo8kGNG58lbw9Wt4BuVNz6yzM5IZEUIIoScSjOhcTj1rRirWhXheWDMimREhhBA64lAwMmPGDAYOHEhgYCARERFMmjSJgwcP1nq97777jq5du+Lj40OvXr1YtGhRvQd8sanvahq7aRpj2dOsSQGrEEII/XEoGFm5ciVTp05lw4YNLFmyhJKSEq666iry8vKqvc66deu45ZZbuOeee9i+fTuTJk1i0qRJ7Nmzp8GDvxjkFDZ8msbWZ0TawQshhNAhh97hfv/9d7uf58yZQ0REBFu3bmX48OFVXuftt99m7NixPPnkkwC89NJLLFmyhHfffZcPPvignsO+eDijZsTrgo3yZJpGCCGEnjSoZiQrKwuA0NDQao9Zv349o0ePtjtvzJgxrF+/vtrrFBUVkZ2dbXe6WOVad+xtwGoa0wXTNJIZEUIIoSf1DkYsFguPP/44Q4cOpWfPntUel5KSQmRkpN15kZGRpKSkVHudGTNmEBwcbDvFxcXVd5huz1bA2qDMiPW6khkRQgihP/UORqZOncqePXuYP3++M8cDwPTp08nKyrKdTp486fT7cBf1LWCtGIyYbO3gJTMihBBCfxzvMQ48/PDD/PLLL6xatYrY2Ngaj42KiiI1NdXuvNTUVKKioqq9jre3N97e3vUZWrNT76ZnFVbMmAymCgGJrKYRQgihLw5lRjRN4+GHH+ann35i+fLltGvXrtbrDB48mGXLltmdt2TJEgYPHuzYSC9S9S5gpTz7YTQYVTCiqadbMiNCCCH0xKF3uKlTpzJv3jwWLlxIYGCgre4jODgYX19fACZPnkyrVq2YMWMGAI899hgjRozgzTff5JprrmH+/Pls2bKFjz76yMkPpfnRNK3CNE39a0YMBgMeRgNSMyKEEEKPHMqMzJ49m6ysLEaOHEl0dLTt9M0339iOSUpKIjk52fbzkCFDmDdvHh999BHx8fF8//33LFiwoMaiV6FkF5ZitqjAIdjXsZoRK6NBPcUyTSOEEEKvHPq4XZc3sYSEhErn3XDDDdxwww2O3JUAMvOLAfDzMuHjaarlaHvWzIiR8mDELAWsQgghdEj2ptGxjDwVjLTw83L4utaAw2BQAYiH0VDeDl6maYQQQuiIBCM6dr4sM9LC3/EpGmsWy1CWDTEZDbZ28DJNI4QQQk8kGNGx83mq+2q9MiNlq2msNSNqszyD3WVCCCGEHkgwomPWzEiof8OnaUwVpmmkZkQIIYSeSDCiY7ZpmnpkRqxTMfaraaRmRAghhP5IMKJjGQ2ZprlgNY1a2Ss1I0IIIfRHghEdO59X/wJWa11I+WqaCjUjMk0jhBBCRyQY0bGGTNNYZ2Ks0zRGqRkRQgihUxKM6FhDghHbNI1tNU15zYgQQgihJxKM6Nj5/LKakYZM05QFIMYK7eAlMyKEEEJPJBjRKU3TbDUj9Vnaa2t6Zl3aW6GAVYIRIYQQeiLBiE7lFpVSWrZJnjNW03gYjbaaESGEEEJPJBjRKWv3VV9PxzfJg8qraYxGbO3gJTMihBBCTyQY0akMW/Gq4/UiULnpmbSDF0IIoVcSjOhU+SZ59VjWS+XVNBWX9krTMyGEEHoiwYhO2Rqe1afHCBX2psHa9KxCO3gJRoQQQuiIBCM6Vb6st37BiJUtM2IoD0ZkmkYIIYSeSDCiU+WZkfrVjFw4TWMygiztFUIIoUcSjOhUg1rBUzngkKW9Qggh9EqCEZ2yBiP1aXgGoGG/msZYoWZEMiNCCCH0RIIRncoom6YJcdI0jYcEI0IIIXRKghGdyiwrYK1vZsS2msba9MxgsO3kK6tphBBC6IkEIzqV0cClvbamZ1QuYLVO4QghhBB6IMGIDmmaZsuM1LvpGReupqnQgVWmaYQQQuiIBCM6lFdsptisAoaGtoO37dpbYW8ayYwIIYTQEwlGdMjaY8Tbw4hvPTbJgwqraarYtVcyI0IIIfREghEdqris15rZcFSlvWkM0g5eCCGEPkkwokPpOUVA/VfSQIXsR1ksY9eBVdrBCyGE0BEJRnTo1PkCAGJb+Nb7NiqvpikvYJXMiBBCCD2RYESHTp3PByC2hV+9b6PyahpsNSNSwCqEEEJPJBjRIWdkRi5seiZLe4UQQuiVBCM6ZA1G4hqQGbFN01gzI1LAKoQQQqckGNGhk9ZpmtCGZ0ZsS3tN5e3gJTMihBBCTyQY0ZmcwhJb99VWIQ0oYMW+6Znd0l6pGRFCCKEjDgcjq1atYsKECcTExGAwGFiwYEGNxyckJGAwGCqdUlJS6jvmZu10ppqiCfHzJNCnft1XoXKfEbW0V30v0zRCCCH0xOFgJC8vj/j4eN577z2Hrnfw4EGSk5Ntp4iICEfv+qJwKqPhxatQOTOiClgVmaYRQgihJx6OXmHcuHGMGzfO4TuKiIggJCTE4etdbGzLekPqX7wKFVbTlE3NmAygadL0TAghhP40Wc1Inz59iI6O5sorr2Tt2rVNdbduxxnLeqGK1TQmaXomhBBCnxzOjDgqOjqaDz74gAEDBlBUVMTHH3/MyJEj2bhxI/369avyOkVFRRQVFdl+zs7Obuxh6oazgpELV9OYpIBVCCGETjV6MNKlSxe6dOli+3nIkCEcPXqUmTNn8sUXX1R5nRkzZvDCCy809tB0ybqsNy60gdM0XNj0DKTpmRBCCD1yydLeSy65hCNHjlR7+fTp08nKyrKdTp482YSjc63yzEjDgpFK0zRGY3k7eJmmEUIIoSONnhmpyo4dO4iOjq72cm9vb7y9vZtwRPqQXVhCVkFZjxFnTdPYLe2VaRohhBD643Awkpuba5fVOH78ODt27CA0NJTWrVszffp0Tp8+zeeffw7ArFmzaNeuHT169KCwsJCPP/6Y5cuX88cffzjvUTQTp8uyIi38PAnwblicaFvai+xNI4QQQt8cfsfbsmULl19+ue3nadOmAXDHHXcwZ84ckpOTSUpKsl1eXFzMX//6V06fPo2fnx+9e/dm6dKldrchFGdN0UAVmRGDtIMXQgihTw4HIyNHjqyx5mDOnDl2Pz/11FM89dRTDg/sYmTrMdLAKRoorwspL2A1IN3/hRBC6JG8O+lIUobzgpFKTc+M5Ut7JTMihBBCTyQY0ZHEcyoYaRvu3+DbstaM2BewKhKMCCGE0BMJRnTkxLk8ANqGNTwYqbyaxmhrBy+raYQQQuiJBCM6YbZonCybpmkT5rwC1vK9aSp0YJU+I0IIIXREghGdOJNZQIlZw8tkJDrYCQWslaZpKtSMyEZ5QgghdESCEZ2w1ovEhfqWBQ4NU3maxmDrwCo1I0IIIfREghGdcGa9CFS1tBesmREpGRFCCKEnEozoxImzZcGIE1bSQPlUjG3X3oodWGWaRgghhI5IMKITJ6zLep1QvApVZEYM0mdECCGEPkkwohOJZdM0bZw0TVNl0zPZtVcIIYQOSTCiAxaLRmKGNTPi3GCkqtU00mdECCGEnkgwogMp2YUUl1rwMBqICfFxym3WuLRXpmmEEELoiAQjOmBdSRMX6oeHyTlPiW2axm6jPEWmaYQQQuiJBCM6kOjk4lUoDzhsq2kMBls7eFlNI4QQQk8kGNGBE04uXoUqakZM0g5eCCGEPkkwogO2HiPOzIxQw9JeyYwIIYTQEQlGdCApowBo5MyILO0VQgihUxKM6MCZTBWMxIQ0fIM8K1tmpGKfEdtqGglGhBBC6IcEIy6WX1xKVkEJgNOW9UIVq2mkA6sQQgidkmDExc5kFgIQ6O1BoI+n0263ygJW2bVXCCGEDkkw4mKNMUUDVS/ttWZGzBYJRoQQQuiHBCMulpylgpFoJ07RQPmKGfumZ9IOXgghhP5IMOJip8umaRotM1JVO3jJjAghhNARCUZcLNk6TRPs5MzIBTUjFbrBY5Y+I0IIIXREghEXO5PVSDUjFyztNRgMtsDEYpFpGiGEEPohwYiLJZdN00QHOzcYuTAzAuXFrFIzIoQQQk8kGHEhTdM4bVtN49xpGmvNiDUzAuWBiSztFUIIoScSjLjQ+fwSikpVYBDl7JqRC1bTABgN0mdECCGE/kgw4kLWHiPhAd54e5icettVTtMYrZkRmaYRQgihHxKMuJA1GGnl5CkaqLy0t+L3mmRGhBBC6IgEIy5kDUacXbwKFfamqVgzIhvlCSGE0CEJRlwoOatxGp5B+YqZipkRk1EKWIUQQuiPBCMu1FgraaCamhGDLO0VQgihPx6uHsDFrFEzI9alvbKaxu3tOZ3FpuMZxMeF0KtVMF4e8hlCCNG8SDDiQuU1I42QGSlb2mukqmkayYy4i12nMrn5ow3kF5sB8Pcy8eaN8YztGe3ikQkhhPM4/BFr1apVTJgwgZiYGAwGAwsWLKj1OgkJCfTr1w9vb286duzInDlz6jHU5qXUbCE1W2VGWjVZZkSmadxJ4rk87p6zmfxiM23D/Aj19yKv2MxfvtnJgZRsVw9PCCGcxuFgJC8vj/j4eN577706HX/8+HGuueYaLr/8cnbs2MHjjz/Ovffey+LFix0ebHOSllOERQMPo4HwAG+n335Vq2lM0oHVbRSWmLnzs82czS2me3QQ/3vkMjb/fTTDOoVTUGLmgS+2klVQ4uphCiGEUzg8TTNu3DjGjRtX5+M/+OAD2rVrx5tvvglAt27dWLNmDTNnzmTMmDGO3n2zYa0XiQzywVhxS10nsU3TVChgNUifEbexZF8qx8/mER7gzZy7BxLo4wnAf27uy/h31pB4Lp+//7Sbd/+vn4tHKoQQDdfolXDr169n9OjRdueNGTOG9evXV3udoqIisrOz7U7NTUqWdYM859eLQNVNzzzKgh6LTNPo3rdbTgJwyyVxRASW/4208Pdi9m39MBjgl13J7DvT/P43hBAXn0YPRlJSUoiMjLQ7LzIykuzsbAoKCqq8zowZMwgODrad4uLiGnuYTS45Sz12Z+9JY2WbpqlQM1KeGZFgRM9OZxaw5shZAK7vH1vp8t6xIYzvHQPAf5YdbtKxCSFEY9DlGsHp06eTlZVlO508edLVQ3K6JsuMVHiKPWwFrDJNo2c/bD2FpsGl7UNpE+Zf5TGPXtERgwF+35si2REhhNtr9GAkKiqK1NRUu/NSU1MJCgrC17fqVSTe3t4EBQXZnZqb5LKVNFGN0Aoeqq4ZKS9glcyIXlksGt9tVcH3jQOqzwh2igyU7IgQotlo9GBk8ODBLFu2zO68JUuWMHjw4Ma+a11rqsyI3TRNWc2IFLDq16YTGZzMKCDA24NxtfQSefSKjoDKjpzPK26K4QkhRKNwOBjJzc1lx44d7NixA1BLd3fs2EFSUhKgplgmT55sO/7BBx/k2LFjPPXUUxw4cID333+fb7/9lr/85S/OeQRuyhqMNHrNSIWlvR7SZ0T3Eg6mA3BVj0h8vUw1HtspMpD2LdU0zo5TmY09NCGEaDQOByNbtmyhb9++9O3bF4Bp06bRt29fnnvuOQCSk5NtgQlAu3bt+PXXX1myZAnx8fG8+eabfPzxxxf1sl6zRbM1PGu0zEgVG+UZjVLAqnfrj6rC1aEdwut0fJ/YEAB2nsxspBEJIUTjc7jPyMiRI2t8M6uqu+rIkSPZvn27o3fVbJ3LLaLUomE0QMtGaHgGVa+m8TBKAaueZReWsPt0FgCDO4TV6TrxcSH8uP20BCNCCLemy9U0zZ214VlEoA8epsZ5CqpaTVPeDl7o0aZjGVg0aBfuX+fNE/vEhQCw42SmZLyEEG5LghEXSG7kehEoz4xUtZpGClj1ad3Rc0DdsyIAXaMD8TIZOZ9fwsmMqvv2CCGE3kkw4gIpWY23W6+VdWlv1dM08glaj9aV1YsMbl/3YMTbw0T3GLX0ffvJ840yLiGEaGwSjLhASnYR0LiZkarawRuMkhnRq4y8Yg6k5ABwqQPBCJRP1ew8meXsYQkhRJNwuIBVNFyTZEas0zRVdmCVzIjebDimpmi6RAbSMtCxoubyupEKmRFNg/0/w/FVcGYHBEbBuNcguHJ7eSGEcDUJRlygvGakcbqvQnnAUXGaxiTBiG6tr0e9iFV8WTCy50w2JWYLnlop/O8x2DnP/sCkDXDjXGh7WUOHK4QQTiXTNC6Q0sg9RqC2pb06D0YsFji9FTZ/DCtmQMZxV4+o0W1NVFmNS9qFOnzdtmF+BPt6Ulxq4VDiafjqzyoQMZjgkvth0gcQ1Qvyz8Lca+FYgpNHL4QQDSOZkSamaVp5ZiSoCWpGqKrpmY5rRorzYd6NcGJ1+XmbPoJbvobWl7puXI0or6iUAylqs7t+rVs4fH2DwUDXqEB2HE8h8tc74dwW8AqAG+ZApyvVQd0nwk8PqKmbhY/AQ+vBO8B5D0KIplBaDEYPMMrn6OZGntEmdj6/hOJSFQxENmIwUtVqGpPRUN3h+mAuge/uUIGIpx90HA2RvaAgQ32i3/ezq0fYKHaeysSiqUxZfYuaowI9meX5HuHntoB3ENz5S3kgAuDlB5NmQ0hryEqCZS84afQXEXMJpOyGHfPgyFKwmF09oubPYoGDv8OXf4Y3u8HLEfBOX0jb7+qRCSeTzEgTSy4rXg0P8MbLo/FiwapW03gY1V4nuuzAqmmw8GE4/Ad4+MLtC6D1IJUp+fE+OPCL+hraTk05NCPbkzKB+mVFrG7LnM1A02ZKDZ543DwPYvpWPsg7ACb8B76YpLJN3SdB26H1vs+LyvYv4ffpUJRdfl5QK+h3B1z6IPgEu25szdXpbbBgCqQfsD///AmYOwHu/BVadnHJ0ITzSWakiSVnWotXG6cNvFWlpmelRQSUqhdSXdaM7P4eds1XKdgbP1eBCKhP9Dd+Dh2vhNJC+HYyFDavJazbk1S9SN/WIfW7gW1fMDDteyyagS9j/gHthlV/bIfLoV/ZRpYLHoTC7OqPFVBapIqBF05VgYh3ELQZCr4tIPs0JPwL3o6Hde9KpsSZTm2BzyeqQMQ7CIY+Bvcug0e2qQ8jeekqIMk86eqRuicddmuWYKSJnc5UmZFWdWz3XV92u/YWnIcPR/DA/jvLLtXZH2LeOfj9afX9iGeg81X2lxtNcN1HEBwHGcdUBkWH/0z1oWka28oyI33rkxk5tRV+nQbAzNI/s9QwuPbrXPUKhLSBzCRY9ITj93mxyD4Dn10NW+cABrj8H/B0Ity1CKYdgOs+hvAu6v/rj7/Din+5esTNw8nN8PkkFfy1HgKP74IrX4TYARDWAW5fCBE9IDcVEma4erTuwVwCS/8Jr7WFF8PhpXAVYBfnu3pkNhKMNLFT59WTH9vCr1Hvx7Zrr2aB7+6E9P14aiXll+vpzXzx3yD/nHqBGfpY1cf4hcINc8HoqYowN8yu++2f3AQfXQ5v9YA3u6p/wpJC54y9gZIy8snIK8bLZKRnqyDHrpyfAd/eDuZizsWO5l3zJNJy6vC4fILguv+CwQi7voFd39Vv8M1Z4nr4cASc3gI+IXDr9zDiyfLCSU8f6H0DTFmngjuAde+oKQRRf+cTVQF7cQ60HQa3fa+yUBX5h8G1/1Hf75yvPqCI6mWfUVmkNTNV4GwpAUupmnr8eBScPezqEQISjDS5U+dVZiS2RdNkRozr37Ut5TRWcbnLHV+lpmcwwLXvgIdX9cfG9ocxZZ8+lzyrgozanNwMX1wHZ7ZB9inISVb/hPNvgRLX7+WyrWyKpkerILw9THW/oqbBL39RUwWhHci46h00jKTnFNXt+q0HwfCn1PcLp8KBXx0ceTOlabDpvzB3POSlqQD5/gToNLrq400eMHgqtBsB5iL449kmHW69FeWo/4Nf/wqfjoNvblM1Gi4dUy7M/z9VsB7dB/7vG/Dyr/rY2AHQYRRoZlj9ZpMOE4CcFP1PERVkwvKX4d2BkLReTXf9+ROYtl/V5AVEQto++OQqOHvE1aOVAtamVh6MNE1mxLDvZ8CgPl0UlXfotGDBhANvfo1B02DJc+r7gfeqYKM2l9yn/rH2/qgyPvctV91Fq5K0Eb66vvxT1ugXVEDy0xQ4uhy+ukHVo/g53tvDWbYlZgLQN87BKZqdX8O+BarG5s8fEx4SDpSv1qpTcfTwJyF1jyoO/uZ2GP8W9J188S6bNJeoAG/7F+rnHn+Cie9V/4ZoZTDA2Ffhg6FlXW9X11y340o5KerNe8fX6v+iov3/U0XNE99r+mXfmqaKVVP3gH8E3Dyv9t/7yGfg6DKVHRn+JLRo2/jjTFwHG96HA4vUz4MfUlPLrlwmX5QDR1dAyi5V41Scp1Z9Je9UATJAqwHw5/9CaHv1c1AMPLAK5t0EyTvgy+vgniUQGOmyh3GRvuq4Tvk0TVPVjKDewFv1x1hxZkYPszT7FsCZ7aonxoin63Ydg0GlaMM6qazAnGtUGrIiTYP176vLrPPO//eNCna6T4TbfgCvQLWE+IPLVEreRayb2/VrE1L3K51PhEVlWY2R06FVP4J9PfE0qaXbZ3PrmB0xeaiprz63qk+Y/3sM/hMPCa9B+kEHHkUzUJyvPpVv/0JNX41+Aa7/rPY3RKvI7jDgbvW9XpdNH/gV3h+sVlIV56j/oSGPqqZ4vW8GDOp/8uiyph/bqjdUIGf0hJu+gOBWtV8n7hJof7maclj3TuOPccfX8Nk4FbRpZnVa9w68N6jsvCZ+Uc1Ohm/vgNfaqenaVW/Auv/Alk/g1CYViLTsCjd+AfcuLQ9ErAKj1PRji3aQmQjzblCBjYtIZqQJ5RaVcj5f1W00djCilaigx+jpr97of51mP03j6uW95hJY9qL6fsgjENCy7tf1DoRbv1PzoOeOqCLDq9+A2IFwciOsf1dN/wB0u1b116j4ptJmMNz9m8qsnDuiXmBC26t/XJOHemPyDy97sRtZ+Z/YSXKLStl3Rq1m6d+mjpkR6/RMcQ60HgyX/QUAo9FAeIA3yVmFpOcUEVPXAmmTB1z7ripoXf+eKmpN+Jc6hXVUwU6v6+vz8NxHQSZ8fbPKuHn4qpb5ncc4fjvDn4Ktc+HUZjXl0aqf04daL+ZSVZe16UP1c1QvuPIl9bdt7UPU5xZVT3B4sfp9NKX9v8CKsrqb8W851txw6KNwbIVajTdmRs3TvA1xfDX8/Ij6vtcNMOyv5QXgmUlqmqvTGLXMO25Q3YPY+tA0lQ36/enylYWhHdQ2D96B4OGtXsta9VevXRV6TVUS0FJ9OPvkKpVJ2fcz9L218cZeAwlGmtDpsimaED9PAn08G++OSouwFOWCEQx9b1VvrJ7+VPyTdHnNyPYvVOGZX7iac3dUaDvVZ2DuBDh/XE3HVGTyUvUlA++t+p8xqpeqBfj1CVWzknFUnSra+bVqqT51E4R3dHyMtdiaeB6LpgLT6LruU7TrW/XJ1eStgghj+VRbRKAKRtLqWjdiZTTCyKdVULj/f7D7WxXMnTsCP9yjnqfhT9b8ouauctNUijplN3gHqwxamzqsSKpKYKSa2tn9rco+/OkD5461PgqzVNB9dLn6ecijcMU/1BvWhbwD1dfi3CYbHim7VWdgUFsXWJed11W7ERAQBbkpcGQJdL3G+WNMP6iCDUuJmsb600fqfyaim5r+Xf0mrH1bBXKHF6upU99QQIPAaPW4et9Y9e/cUeYSWPQkbP1M/RzTDya8DdG963+bYR3g/75VdXUuCkRAgpEmdTKjaaZo2P4lmmYGTBh736zO8/KzC0ZcuprGYlb/vADDnyh/EXRUizZw9++Q8CocX6lWMviEQN/bVBAS2q7m63sHwnUfwlUvqUKu9EPqfE9f9Wlnyydqlc/ZQ40SjGw+ngE4sB9N3jlYPF19P+LJSmOy7vZb5yLWC3n5QfxN6lSYDateV2noFa+oNO6E/9gFP7qRnQxr3lIpZp9gldHqcV3twdP5RNUALuMY+LeE239qeEO9QQ+oYGTPDyr74EjGz9kKs1Rxatpe1dH4zx/X/GZt/T9sqlR9ZhJ8eb0KftoOKy9Od4TRpDJ3699Vgbqzg5H0gzBnPBRmqszrnz6wr6ny8oNRz0Lvm9Rr2vGVkHVSFT+D6ofy88Pqf2j8LOgytv5jyc9QHaqPr0ItNf+7yoyanPA2Htu/bjV7jUiCkYbQNIc+LdrqRUIasXjVYoEN72MpyxIarelCTz+MFQpFXNr4bP/PKnDwDVUdLBsiKKZ8mV/e2fI0pSMCItSp/Uj7809tVingRmqytqksGBlU12Bk2T/Ll0APqbwE2hqM1Gl5b218guCql1VR4KIn1cqLkgL404dgasSsnqNOblafWnNTys/b+IFarnztO9UHA2kH4Is/Qc4ZCG4NkxeoT4gNFTtAfVo9sw22zVEZJVewWOCH+1QgEhClMj4xfWq+jrUIsymCkfwMFYjkpkDLbqpOpL5/V71vVMHIwd/U/6qzuuGm7oPPr1UBRWRPuOUb9UGlKi07w6T31HtC1sny14xjCap+LecMfH2Tal1wxbOOP9azh9WS54xjqsbuz580LLDRISlgdVRhFqx8Xe2V8lpbtWyqOK9OV22SZb2HF8O5I1jKgiTb3jRe/nYFrC6bptE0WFsWPFxyn/pk4Sz+4c5JhVpZX9QaIRgpLDGz41QmAAPb1iEYSd2rAgJQ8+pVzI23DFT72tQ7M1KVgfeW93fZ8wPMvxWSNuij2+i2L2DO1eVvaKNfgEseUFN0h36D9y9V+8hYLvhbP7VF1QnlnFFz6/csdk4gYjWobNph8yeu62eT8C/1WuDhA/83v/ZABNTST2j8YCQzSf3+zx5ULfVv+6FyLxFHRPVWz6O5yHn7V+39SdVR5KWrbNkd/1P9TWpjMKj9n6J6qdOQR+CxHTDoQXX52rdVz6MTa+s2jpJCVTj731EqEAlpDff80ewCEZDMSN2VFMKOr1SXxfyz5ecXZqrCnzZDar2JJglG1r8HgGbyBq2kfNdeT/s3fZcFI4nr1KdGDx8YeJ9rxlBX1mCk4n4kTrLrVBbFpRbCA7xpF16HYrclz4FmUQW51RT4NXiapjrdr4WbvlQV+9Z5cb8w9WIb3kV9Mo0d4Nz7rIm5pKwg8yP1c9fxKn1unWboN1ntY5S2Ty0X3fyJSt8Hx8K+hWU9VTSVwbjtB+cv7e7xJ1j6ggp2tnxSv5qohjj4u1pZAaqeoKp9iqrSFNM0p7fC17eo7qmB0er3X5eVMzUxGNTf4LIXVRO/frfX/7ZKCmHp8yq7Bqr1/01fNuxvxMMbxr2mCs7/9yik7lZBdOvBEB2vppbPHlJToQaTOt7DW30AOLlBFRYDxF2qxuLKqb9GJMFIbdIOqHXlexdAUdkn5PDOcOlDqogoeadqftOm9ps6ldnI3VfP7FDLVY0eWEyeUFpSvjeNp68+0mDWJXjxt+j/n8qn7JNiI2RGNp8on6Ix1DbVd3S52iXW6AGj/1ntYRG2aRonByOgPond9Zt6kT70h5ouOpagTps+UkV6o56rud9C5klVHxDepf69TLJOww/3QtI69fPIv6mpkIq3F9UT7l+p/m9XvaG6qJ7eYn873SeW9dOoZ71STTy84fK/qVqBVW+oGqam2kgvJwUWPqS+v+QBiL+57tf1KnvuGqOAtbQYVv9bFXtaStVU463fqgDRGXrdAMteUq9/547WL9OVvAt+vB/Sy3YEvuwvagsAZ9RkAPSYpGpjVrysthhIWq9OtQmKhf53qpVDzsz86owEI9UpyoWVr6kXNEupOi84TqXdBtyt5vxObS4LRpLqdJO2zEhoI2VGNpYt3etxHVrhLqBsbxpQ0zQVDnVJZiTrlPpUDU3/abE+GnGaZmNZvcjAtrWkpzVNfcoGlUmq4UW20TIjVrEDIPZjlZk4s0NtYnYsAfZ8r5aNHlykivQqdistzofd36mVSdYXXt9QtQyx63gV5NTljdpcopqz/TJNdej0Kis+rq5g0cMLLntcFRbu+EoVIp4/DhHd1d9eY+/2Gn+LqmNIP6BS86Oeq/t1i3Jh2+dqWWbnMXWvS7NY4KcHVaAY2UsVZjuisTIjmUmqh0vKbvVztwkqEHRmgBbSGjpdpV5ftnwKY15x7PqHl6gxmotV07WJ71XeI8sZ/MNg/EwY/LBqQ5C6V72+hHcuL7gvLVLjKC1US+7bj9Rn4biTSTBSldPb1HK4zET1c5erVSakzVD7T2AhrdXXrNqDkZzCEjLLeow0yiZ5hVlqnhPgkvvRVqk3e9unbk8/1y/t3TFPTTW0uQzCOzX9/TvKJ0R9dXIwUmq2sC1RpV4vaVfLPPTxlapDoodvrcWQLQPKgxFN02rPuNSXyRPiBqpTv9vVcsD/PabedL76swoyIntAST5s/0oFDwAYVAFgQYYqYt7/s6rvaH+5mgpqe5n6FGgwqv+p9IPqlLJLvVkUZqqbiY5XDcnq8uk3KFqt2GpqJg8Y9bzadmD9+9DzetUYrSYWi1pmvvSF8oLcTlfBuNdrXxkGKvNwbIX6W7n+E8c/RdsKWJ2YGUnaoOqM8s+qIPSaN9U0VmP8bQ68RwUj279Uy5erKza90MlNqgOxuVj1Cpn0vqo/a0xhHZxbp9QMSDBSUWGWevFc+rz6wwxurZppVVcsFBynvtZhjwLrbr2N1mNkz49QWqAKuWIHlO9NY52mKVtVY9BAM7hgNY3FUt5muyFzuk3Ju3GmaXaczCS3qJQgHw+6RNUyTWCd1up7W60FdNbMSLHZQnZBKcF+TbTqpcMV8NAGtQ/Ghtkqg3Hgl/LLQ9qobGLvG9US2jM71JvGvp9VEaO1DgXUPLnRQ/0tX8gvXP0eLv+be6Sru4xTgXfiGvhsLNz8NbQdWvWxSRvh92dUPRWooCw3FQ7/oeqs7vhZNbGqzuaPyxuHjXu1fpkfWwGrk2qkTm5SfYDMxaq+6Jb5zpuWqUrH0eoDYmaSej2sS8+MtANqW4jSAhX43fyVvlaLXUQu7mBk8d/L214XZaviKuuUTNfxKlXnG1L99a2ZkTpM05zKaOTiVetKi763gcFQORgpK2A1oKFhaPo+IydWqd+Td5AqwnQHjVTA+suuZABGd4/EZKzhE2LqXlUrYjDWaVrLx9NEkI8H2YWlpOUUNl0wAirYHTtDzd0fXKSWbpYUqEC+63j7NLM1q3LFP9Sbwf6fVbO19APqjctSojImYR3Vm2p4F2g3XBXuulO62mBQS1a/vlml5L/4k6rh6DxGFQAXZqlp3iPLVKEiqLqN4U/CpVPU/8uCh1Rr769uhHuXVO4GrGlqSufXsuzP8CdVfUF9OHOaxlyismXmYvUmf8Ocxu1KCupvY8DdsPSfKjirLRgpLYLv7y7vIXLDHAlEXOjiDkZOblL/6BWFd1bFeNV17qwopCwzknVKffKvoSivUXuMpO1XBXpGj7I9JsqbmpXXjKj7NQIWXDBNs60sK9Lreucu521MjVAzYrZo/LpbBSMTesfUfLA1K9Lt2rql6VHZkezCUtJziugU2QjFmbVp1c+xNugRXdVpxFNquXD2GfUGFtLGeYWDruQXCpMXwvf3wMFfYdtcdarEoN48r3iufLOy8E5w+49qu4OUXWr36fEzVddRg0GtFlr8dzU1A+p16/K/13+szixg3TBbjc83VPWmaexAxKrv7WrF45ltcHhp9bstg2qWmLZXZdxu/rrpxiiq1Az+2xtg+JPly3SNHio6ruOLPqDWyBuMan17XnqNOx6ebMxlvdasSOexthUq1r1nyjMj6h/NqAFNPU1TcF598gXH2z27UiOsptl0PIP0nCKCfT0Z2rGGeemcFFX4CaqFdx1FBPpwND2P9LpulqcnRlN5gN+cePqqJZnHlsOhxaro11yi/r5CWqtpLusUw4W8A9VmZp+MVgW4X0xSTcxKCspX95m81V4pDW3Zb82MmItV1qC+U2FZp9QbPcCVLzbtrtj+4eqD5Ib31R5OD62veoXXyU2wdpb6fvxM/a/suwhc3MFIQ6ulTZ4QGKO2pc9MqjEYOZKmPm20a+nk6NtcojZNAvWpoIxt115bAasKggwXXN4kDv5WtoNkN4ju03T321C2zEi2w912q/O/XWqH4bE9ovDyqGF567Yv1JRh3CCH2jTburBmu2Ew0pwZjSrg6FjDJ/XqBEaqZdWr31IbwlmLW42e6vbGvOKcYkivCm/aRbn1D0ZWvgYleaovRh8X7HVy+d/Vh5+sJJUlGXtBm/ms02p6RrOo1Vbd3WTauJnTResJt2abqqm5buRwqpqH7ezs1PnRFSq74xdue6GrWA9yYQGrtSV8nTIjuemq0+zGjxo2xr0L1NfGqqJvLNZgxFKiPok2UKnZwu971BvJ+Pjo6g+0mFUfAoAB9zh0H9ZgxFowLZqJ4FjVefeJg3D7AnhwDfztjOqu6qxVGSaP8uaI9a2TKs6HPWWr+kY9W/9+Mg3hHaCyHQAbZ5dnZUHt7/TFJNWyPayjakYmdEGCkYaqw4qanMISzmSpttCdI5wcjOz+Vn3tdb1tjr1i1uPCDqwOZUbWvKWWllprF+qjMKt8x9DuE+t/O67gFaCm4cApUzVrjpwlI6+YMH8vBrevYWXM4T9Uts031OHfWb/Wqm/Jgh2nySsqbchwhR55+kKHy9XqlCq2BGiwhhaxHlwExTlqyql17V2pG02nK1XWQ7OovYt+flRNHX16lep2GtRKbYzYkDb0wqkkGGmoOqyoOVw2RRMR6O3cFQ5FObC/bAllrxttZ1fMetimaTy80QxGWzBS62qa3HTYUrZNdfYpNR1UHwd/U5mFlmWFiu7EYHDackdN03hn+REAJsTH4GGq4V9vy6fqa99bwdPHofsZ2zOKtmF+ZOaXMG9j3ZrxCWHT0CLWXd+or71vck1WpKJr31FNKkEVDSfMgHNH1Eqm23+qukZHuIwEIw1lm6apPjPSaFM0B35V6+NDO9itYKgYaNiCEYMBs4efbbO8Wqdp1r9T3utBs9T4+Gq0b6H66m5ZESsnFbH+sS+VrYnn8fE0MmVkDWn18ydUgy+A/nc5fD8mo8F2+x+tPkZhiQ42tBPuoyGZkdw0tUwZbKv6XMrDW+08Pfln1cW0x5/UXj0PbWz8DrzCYfUKRt577z3atm2Lj48PgwYNYtOmTdUeO2fOHAwGg93Jx8exT3u6VodpmkOp6lNGp8ga9u2oj4qfQirUYlhX0kCFaRrA4uGLoSwIqXGaJu8cbPq47AbKMjnnTzg+vsLs8hen7pMcv74eOGF5b6nZwuu/HwDgnsvaERlUw9//1rmAprqS1rMW4E99Y4kJ9iE9p4jvtp6q122Ii1RDgpHd34NmVs3Zwjs6d1wN0X6EWl59wxzVg0VWzuiSw8HIN998w7Rp03j++efZtm0b8fHxjBkzhrS0tGqvExQURHJysu2UmJjYoEHrSkjZDnmZSWrFRRUONUZmJCdVLREE6H2D3UV2NSOGisGIn+0Jr3GaZtNHqho+qreanwY4X4/n7NBitYomrBNEdHP8+nrQkJbw5hIozuO7rac4mp5HCz9PHhhRQ4BRWlzepXbA3Y7fXxkvDyP3D1fNsT5IOEqJ2UU7NAv305BgxPrhKP4W541HXDQcDkbeeust7rvvPu666y66d+/OBx98gJ+fH59++mm11zEYDERFRdlOkZHVL4F1O9b2xiV55Vs9X+BwWWakszMzI3t+UNMnsQMrdWWscpoG0CrsT1NtZqS0WO1GDDD0MWhR1nelPpmRfQvU1x6T3GsVTUX1bQmvafDfK9De6s7SxT8D8PAVnQiqaSuAA/9T/WoColQr8Qa4+ZLWhAd4cTqzgJ93nGnQbYmLSH2DkexktYcSBvfNggqXcigYKS4uZuvWrYweXb5W3mg0Mnr0aNavr34r5NzcXNq0aUNcXBwTJ05k7969Nd5PUVER2dnZdifd8vRRuzxClUWsWQUlpGSrlTQdnbmSpuIUzQWqy4xoHr7lBazV1Ywc+EXtieEfoTp/tmirznc0GCnKKa99cNd6Eaj/NE3KLkjZhaEwk/+Uvsj4oKPcdmktBXObywL6/nc0uC21j6eJey5TQer7CUewWJq4/b9wT/UtYLWumIvpI9Mgol4cCkbOnj2L2WyulNmIjIwkJSWlyut06dKFTz/9lIULF/Lll19isVgYMmQIp05VP5c9Y8YMgoODbae4OJ13ZaxhRc2RNPUJIyrIh2BfJ62kST+kPoUYPVRR1gWqrRnxLC9grTYzsvkT9bX/nWrpYH2DEesUTWgHiOzp2HX1pL770xxYBECpZsTfUMQs8yt4n91f/fHpB9WGagaj07rU3nZpa4J8PDiansfve6v+/xTCTn0zI0eWqq8dr3TueMRFo9FX0wwePJjJkyfTp08fRowYwY8//kjLli358MMPq73O9OnTycrKsp1OnqznSo6mYg1GqnjDbpTiVWtvkQ6jqtzquqZpmhqbnqXuK3tDNJVvtlXfYKTiKhp3naKB+q+mOaiCkedL72SHR288zIWqAVN1Nv1Xfe08zmk7mwb6eHLnUDXN9u7yI02/OaJwP7ZgxIHg22Iuz4zUp8OsEDgYjISHh2MymUhNTbU7PzU1laioqDrdhqenJ3379uXIkSPVHuPt7U1QUJDdSdfCO6uv1h2AK7AWr3apqXj1WAIseQ6K82q/L02rMEVzY5WHVDdNY+uuSDWZkS1lWZGuV0NwK/W9NdAqzKy2JqaS4rzyKZoek+p2Hb2qzzRN1ilI2YVZM/Cb+RIYOV2dv3dB1c9x9hm18yrAoPsbNNwL3TWkLX5eJvYlZ7NkX2rtVxAXN1sw4sA0zelt6vXBJ1itpBGiHhwKRry8vOjfvz/Lli2znWexWFi2bBmDBw+u022YzWZ2795NdHQN7bDdjbWZV3rlNHytK2ksFrVN+Nq31dbXtTm5UU0HeQVAl6urPMSu6RkVshKeFVbTXJgZMZeooliwX8nhHQD+ZXPAdV1Rc/gP1aOkRVu1IsedVdyfpq4O/gbAVq0zoRExxA8Zq4qMi3PLM0YVrZmlprRaD1Y7sjpRC38v7hzSFoC3lhyS2hFRs/pM01inaNpf3jx2WhYu4fA0zbRp0/jvf//L3Llz2b9/P1OmTCEvL4+77lINmiZPnsz06dNtx7/44ov88ccfHDt2jG3btnHbbbeRmJjIvffe67xH4Woty5atph+0W95rsWjsPaPexLpEVROMJK2D7NPq+03/haSNNd/XtrKln92uBS+/Kg+pmPWoOE2DV4WmZxem7BPXqsyHXxi0HW5/mXWqJrOOwYh1L5ruk9x7igbqt5qmLBhZau7HpD4xGIzG8g3Dtn9lf2z2mfJ9aEY+0yi/r/uHtyfQ24MDKTn8tkdqR0QN6lPAaqsXkSkaUX8OByM33XQT//73v3nuuefo06cPO3bs4Pfff7cVtSYlJZGcnGw7/vz589x3331069aNq6++muzsbNatW0f37t2d9yhcLayDKiYtzlUp+jJH0nPJzC/B19NE95hqppqs28R7+AAa/PyI2r67KgXny7MX1pqOKlgDDbspGgBP/+qX9u5Ty0/pek3lTzeO1I0U56vMCLj3KhorRwtYC7PRjq8CYKmlP9fGl013xd+iilMT10DGsfLjV7/ZaFkRqxA/L+6+TNWOzFx6CLNkR0R1HM2M5GfA6a3q+46jGmdM4qJQrwLWhx9+mMTERIqKiti4cSODBg2yXZaQkMCcOXNsP8+cOdN2bEpKCr/++it9+/Zt8MB1xeSpdoAESD9gO3vT8QwA+rYOwbOqvUhKi8uzCH/6QC2nPXsQNrxf9f3s+FpNf0T2hLhLqh2ONdAwXvj0epZ3YLWbprFY1JJeUBmXCzkSjBxZCiX5qtYkphk8z47WjBxdhsFSwlFLNCFx3WkdVpa9Cm6l0tgAS19QQdv692BzWafbRsqKWN0zrB3Bvp4cScvlp+2nG+1+hJuz7cVUx2Dk6HJAg4geEBTTaMMSzZ/sTeMsLcvqRtLK60aswcjAtqFVX+foclX4FRCpgoBRz6nzt85RAUJFmla+gdqAu2t847IGGoYLjjF4+VfdgfXUJtVbxDu46k/njgQj1kZn7r6KxsrR1TRlUzRLLP2Z1LeV/WWDH1Jf9y2Ad/rB4r+pn4c9ofbOaERBPp48VLZnzWu/HyBXdvQVVfEum6apazBim6KRrIhoGAlGnMXa7rwsM6JpGptPqGBkULtqghHrFE3PP4PRpL56Bao3/cQ19sceXwXnDqvLq1lFY2XLjFwwTWPw8rfVjJRaKmygtv9/6muXsVVvS25teV9bMFJSoPqLAHSv3P/ELVnbwZfk175zsbkU80H1+Jdr/bmm1wVF2h1Hq91CA6Mhp2wqc/hTcMU/nDvmatw5tC1tw/xIzynineWHm+Q+hZupOE1T21Jwi6V87ympFxENJKXPznJBZuTU+QKSswrxMBro27pF5eMLs229KOh1vfrq5Qe9/qwyI9u/hHZlhaSaBmtnqe/jbyp/wahGtcGId3nBa6l1vxJNg/1l9SLdJlR9g7YC1iTVU8Boqvq4I8tU3UxQrN0uwm7Nu0KtT2E2+IdVf+zJDZiKMsnQAvBqO4iwAO/Kx3S4AqasU7Uioe1rzXI5k7eHiWfHd+eeuVv4dM1xbh7Ymnbh/k1y38JNWAtYNTOUFoKnb/XHpu6GvDTw9Fc1TxfIKijhp22nOJNVSGZ+MYE+nvSICaJPXAjtWzp501Dh9iQYcZaICitqLBZbVqRnq2B8vap48975tfq0Hd4FYiq8cfedrIKRfQvh6jdUzcLO+WpKx+QFg6bUOhTrFIzdsl7sp2nM1gLW9AMqyPDwUU3UqhIUoy4vLYSM49XvyNlcGp1VZPJQL7YleWpKraZgpKzr6nJLP4Z3qaHvjl8ojHnFqcNMzE5ke9p2ru1wbeXC5Qqu6BrByC4tSTiYzvQfd/HVvZdiMjaT50o0nFeFIKEop+ZgxLakd4RdRrW41MIXGxJ5Z/lhMvOrziZ2jQpkQnwMNw6Io2VgFUG7uOhctNM0mqax+nA6D36xlcISc+1XqE1oezB6qjetrJO2epFLqpqi0bTyjpuX3Gf/xt2qn1oqXFqoClZzUuD3p9VlI5+p09bc1nbwF74pGb38bR1YzdaaFOvOv22GVLtUGKMJInuo75N3VH1Mcb6tXqJZrKKpqC4rajQNS1mma4m5HyM6RzTBwMq9vOFlnl37LBuTa14abjAY+OeEHvh5mdhwLIOPVh2r8XhxkTEa1VQw1F43YpuiKf8Qo2kaj83fzku/7CMzv4SOEQHcN6wdT1zVmTuHtGVg2xZ4mgwcSMnhjcUHuey15fzz572kZBU20gMS7uKizYyUWjSe/n4XZ7IK+W7LSW4f3LZhN2jyhPBOkLYP0g+w6YSK9i+pqnj1WEJ5/Uf8zfaXGQzQ73ZV3Pj706ozq7kIovvAkMfqNJTqMiNG7/KlvSXWmhFrMGJd6VGdmL5qCd+Z7eXTShUdXATFOWoVTezAOo3TbfgEQ86ZmotY0w9iPH+cIs2TQ/4DnbtDcx2czFFbJqTk1d5HpG24P89P6M7TP+zmzT8OclnHcHrFBjf2EIW78A5Q/8s1BSOFWaoBI9hlVN9bcYTf9qTgZTLy/LXduWlAHB4XrCTMyi9h8b4UvtqYxM6TmcxZd4Lvt57iias6c/vgtpKpu0hdtJkRT5ORB8tWF3yw8hjFpdVsHOeIsrqR7KRdHEtXbb8HtK2iXsSaFelzS9X1H31uhTaXqd4l5iI1PTPxvTp3N7RmRi5cTWP08sNg3SjPoqmCzBNlhbK1reaI7qO+Ju+s+vKKuwgbm9mfVV1W1JRlRdZaejCgc1yl331j0jSNjEKVicsurls/lBsHxDGuZxSlFo2H5m0lLUc+mYoydek1cnwVWEpVS4NQ1cNm+YFU3lxyCIAXJ/bg1kFtKgUiAMF+ntw4II4FDw3hq3sH0ScuhNyiUv75v33c8ME6zmQWOP0hCf1rZu8ajrHOV57OLGCBM3ovlAUj5/YsxYCFS9uHEuJ3weqUjONwqGw6Y2A1XWh9Q+CuX2H6Kbj7D3hwLUTVfefb6pqeGb3La0ZKLBY4tUUVnPqF176zbkwf9TV5Z+Vlx7lp5Snb3hdkepqDurSEt3ZdtfRneOem3UI9vzSfglL1Al7XYMRgMDDjul7EhfpyMqOAOz/dTHZhLauFxMWhLl1YL+i6WlBs5qnvd6FpcOug1tx8Seta78ZgMDC0Yzg/ThnCSxN7EOjtwbakTMa/s4Y1h8829FEIN3NRByM+niYeGN4egPcTjpSvMKmvjqPRMNAucwNveH7E5Evj7C+3WFSHVc2ipkVadqn59jx9ofUgaNnZoWHUtLTX+nndbDFXmKIZUXs2o2VXMHmruonzx+0v2/ODqr5v1b9ONS1up7bGZ7lpaKc2A7DC0pfLOlbeSbkxnS0of+HOdmC31RA/L764exDhAV7sS87mvrlbyJP+I6K2zIimVVrS+9XGRM7mFhMX6svzE3o4dHdGo4HbB7dl0WPD6NkqiIy8YiZ/upEv1p+o5wMQ7uiiDkYA/m9Qa1r4eXLiXD6j3lrJ2FmrmPDOGia9t5bbP9nI9B93MTvhKOuPniO/uJYX6tj+bB3wOqWaketNqxi7e5p9b47178CJ1Wp1xjVvNtpjsgYjF9aMqI3yygpYSwvh2Ap1fl0abpk8y7MzZ7bbX7bza/W1OWZFoML+NJlVX37odwxo7LS0JzK2PS38q+jV0ojsgpE6Zkas2ob7M+euSwjw9mDj8Qxu+GC9FBNe7GzBSDV/S+kHIeuk+nDSZiiFJWY+LCuEnjqyI14e9XtbiQv14/sHh3BD/1gsGjy7cC+v/36g8j5aolm6aAtYrfy8PJgysgP/WnSAxHP5NR7rYTTQv00LRneL5KoekbQJq9yj4dWTPQkreZT3vd/FdHgxvLMcekxSWY4dZW/aY2eo/WwaibUDa6UlnhUyI1r+eTVNA3Xv/hndRxWxJu8oL2JN3qlORg/VtK05alHW9O1sNY3CrF1Xzf0Z3qlpsyJgH4zkFDuw22qZnq2C+fLeQdw7dzP7krP50/tr+e/kAfRsJUWtFyVbMFLNNI11iqbtUPDyY/7a46TnFNEqxJfr+sU26K59PE28fn1v4kL9eGvJId5POMrZ3CJmXNdbClubuYs+GAG497L2DG4fTm5RKaUWC6VmjRKzhcyCEk6fL+BIWi5bE8+Tkl3IxuMZbDyewSuL9tMnLoRr42MYHx9NCz8vvt6UxJbE83gYB5F127WErntZ9QexdloF6Doe+k1u1Mdjy4xcWERpNIGmzvNI3a6mVkI7qBUwdWGtGzmzo/y85S+rr90n1dyDw51F9VZfqyreLc5HO7oCA6pe5J9NPEUDDcuMWPWJC+Gnh4Zy52ebOJqex3Wz1/HypJ7cOCCu9iuL5qW2aRpbvciVFJWa+WClyopMGdmh3lmRigwGA4+O6kRkkDfTf9zNt1tOkVdkZuZNfZxy+0KfJBhBzVnWZWlj0rl8lh9IZen+NNYdPcuOk5nsOJnJy7/uI9Tfi7O5xQD8qW8rQjvEQ4efVNV54nq1Y6uXH/S9vdEbglW7ay9AWW7EI2Wb+tGRPVFsK2p2qXnjpA1qh16DCS7/W73Hq3vR8err+eOqbsSnwt/K8ZUYSgs4pYVz3NSGvq1Dmnx45wrO2b6vbzACKk3+40NDmfbNDpYdSOOp73ex6XgGz03oTpCPpzOGKtyBVw370xTnQeJa9X3H0Szdl0ZKdiERgd7cMKBhWZEL3TSwNUE+njw6fzu/7k4mr7iU2bf2r7qJpHB7Eow4oHWYH3cObcedQ9uRnlPEr7vO8PPOM2xLyuRsbjHhAd5MGdmB2y6tkGloN7y8rXsTqbZmBLCUlQl5ZhxUZzgSjER0KytizVJBVsKr6vy+t9U67aRpGvuTc1i0O5kT5/II9vWkZaA3V3WPontMUI3XdTm/UNXiPvsUpOxR6WmrA78CaopmYNswvD2a/oWyvgWsVQn29eS/kwfw3oojvLX0EN9vPcXaI2f51596cXnXpm3kJlwkuGyDx3NHKl92Yi2YiyG4NYR34vtfVOH2DQNiG+Vvf1yvaD729uCBL7aQcDCdOz7bxCd3DCBQguNmR4KRemoZ6G0LTJLO5XM0PZdL24fpImqvtmZEnVt2kFlla9oNq/sNW4tYT2+Fz68tO88bRjxd49WOpefy6Pzt7Dld+Y1y1tLD9GoVzIMjOnB1r6gm7c/hkOjeZcHIrvJgpKTQtq/PH5YBXNbBNdNUF07TaJrWoN+j0WjgkVGdGNwhjCe+28mJc/ncNWczwzu35G9Xd6VrlM6DR9Ewrfqrr6e3qgxoxb+lI0vU146jSMspYuWhdAD+3MBakZqM6NySL+4ZxN2fbWbT8Qxu/Xgjc+66hNAmLhQXjUsm4JygdZgfl3eN0EUgAjVnRrSy8yyguqr6VtGUrSaj/6kasllTuUMfK/8kVYUVB9OY+N5a9pzOxsvDyJgekfz96m48OqoTY3tE4WkysPt0FlPnbWPyp5s4ll5DbwNXstWN7Co/79BvUJhFMmFstHRjiA6CkRJLCYVm56yGGdA2lN8eG879w9vjaTKw6lA6Y2etZvKnm1i6L5WShi6FF/oU0UN9yCjMhIwK2wVYzOU7fHcew0/bT2PRoH+bFo2+8d3AtqF8ff+lhPp7setUFjd9uJ7UbFn11ZxIZqQZqjEzopkAMxaDwbEpGivrtJPFAnnpEFB96v633ck8NG8bmgYD2rTg/dv6ERHoY3fMudwi5q47wQerjrH68Fmu/s9qXprYkxv0VjhprRtJqRCM7JgHwPelw/Dz9qKXi1afnCs8Z/dzdlE2vh41bHDmAF8vE3+7uhu3DmrN678fZNGeZFYdSmfVoXSCfDy4omsEV/WIYkTnlvh7y8tJs+DhpTKBpzbD6W3lU7CJayEnGXyC0dpfzve/qnbw1/dvvKxIRT1bBfPtA5dy28ebOJyWyw0frOezuwbSQXYAbhYkM9IMVdf0DMBS8bza9qOpidEIgZHVFuMeScvhie92omkqhTvvvksrBSIAYQHeTLuqC0v+MpzLOoZTWGLhye938eR3OykodsIGhs4SXZYZST+gpmdyUmyNn340D2NQu9AqW183NotmIaNAtYK3ZsLqs7y3Nm3C/Hnv1n6sfOJy7hvWjjB/L7ILS1mw4wwPfbWNvi8t4baPN/LWkkMsP5DK0fRc52xAKVyj4lSN1e7v1dfuE9mVUsjhtFy8PYxc0zu6yYbVMSKQ7x4cTJswP5Iy8pn47loW7619Pyahf/JRphmqdmkvYI0/S42eEHdJo9x/blEpD3yxlbxiM5e2D+W1P/eq9Y26TZg/n999Ce8nHOGtJYf4buspdp3K4r1b+9ExQgeffIJagW8oFGSozRBPrAHNzGGv7hwvjOZWF03RZBVlUaqpZnzR/tGcyTvToBU1tWkd5sffr+nOM+O6sS3pPEv2pfLH3hROnMtnzZGzrDlSPmVkMEBkoA+tQ/1oHeZHu3B/2ob506bse8mk6NiFwUhpEexbqL7veT0LdqjtM8b0iGrylVbW5mhT521j0/EMHvhiK3cOacuTY7rU628qv7iUwhILJWYLwb6e+HjqY7r9YiOvBs2QbWlvFYkvrey8/OAO4OHdKPf/ws97OZqeR2SQN+/c0q/OGQOj0cDDV3SiX5sWPPr1Dg6m5nDtu2uYcV0vJvapvi6lSRgMKjtyLEEtZ971LQCfFwwBYFinpt2PxspaLxLiHUKoT2ijByNWJqOBgW1DGdg2lOnjunI0PZcNxzLYlnievWeyOXk+n/xiMynZhaRkF7LpREal22gZ6E3bMD/ahPnTLtyfmBAfIgJ9iAj0JiLIhyAfD/0WNDd31mAkeafaUPPIMlVDEhCFufVQfvk6AYCJfWJcMryWgd58de8gZiw6wKdrjzNn3QmW7Evl79d048rukXhW85pTXGphX3I225POsz0pk+0nz3Myw35jvvAAL9qG+dMrNpg+cSEM6RBOy8DGea0U5SQYaYaq27UXoBgfoIDs0LpvvOeIrYkZfLf1FADv/l+/ev0TD+kQzqLHLuPRr7ez4VgGj83fweYTGTw7vrtLls7aRJUFIwkzACjxCmZh9iBiW/jSOdI12RtrMBLuG05QWdv6pghGKjIYDHSMCKRjRCC3Xaq61WqaRkZeMUkZ+Zw8X0Di2TyOn8vjxNk8TpzLJyOvmPScItJzith84nyVt+vtYSQiyLs8QCkLUloGehMZpM6LCvJp8vb7F4XQ9uATogKQ1D2wp2yKpud1bEzMJD2niGBfT5cF4aB2Xn9uQneGdw7n7z/t4XRmAQ99tY3wAC+u7B5FmzA/Qv28OJ9fTHJWIbtPZ7H7dFa1O7QbDWDR4GxuMWdzi9mSWP532T06iDE9ohgfHy01Ko1EgpFmqKaakRRTFHCe8xHOn6IxWzSeXbAXgBsHxDKwbWi9bysi0Iev7r2UWUsP8c7yI3y5IYktJ87z5o3x9IhxUZtyaxErQKv+vOv3KNm7PbmuW6TLPsFbg5Ew3zCCvMqCkQb2GnEGg8FAWIA3YQHe9G1decVWVkEJiedUYKIClDxSsgpJyykiLbuQ7MJSikotnMwoqPTJ9UKxLXzp36YFg9uHMaJLS6KDnVO8e1EzGFR25OgyWPYiHC3bx6rn9fxvUzIA43pG6aIj6sguEfzxl+HMTjjK/M0nOZtbxNebkqo9PsTPk75xIfRt3YK+rUPo1SqYIB9PDAb1d3nqfAGHUnPYdSqLTccz2JecbTvNXHqI+NhgbrmkNRPiY2Sq0YnkN9kMWadpqlraa0BlFsyNsPnUvE1J7EvOJsjHg6fHdm3w7ZmMBv56VRf6tWnBX7/dyYGUHCa+u5aHLu/IlBEdmn4pdZerVYO3qN5Y+t/DvNcSgCKucGEzMGv31XDfcPw91F5JTZ0ZqY9gX096x4bQOzakyssLS8ykZReRllMeoKTlFJWfsgtJzyniXF4xp84XcOp8AQt3nAGgS2QgI7u0ZETnlvRv28K12TR3Zg1Gji5XPw+4h5KoPvy2RxVuT4h3zRRNVfy9PXhiTBceG92JVYfS2ZZ0njOZhWTkFRPq70XLQG+6RgXSt3UL2ob5VfvhIcTPixA/L3q2Crbts3M2t4gVB9L4dXcyaw6fZeepLHae2s1Lv+xjYt9W/N8lrWUfJyeQYKQZqmlpr/Wf0Gxxbo+IjLxi/r1YdXX961VdCAtw3hzr5V0iWPz4cP6xYDeL96byn2WH+WZzEtOu7Myf+sY23aczLz+Y+B4Ae06pVLW/l4lB7eufAWoo2zSNTzieJlVI6A7BSG18PE20DlOFrzXJKSxh58ksNp3IYPXhdHaczORgag4HU3P4cNUx/LxMDOkQRv82ofSJC6FXbDAB8mm2bqx1IwCDpsDYGaw5mE5mfgnhAd5c2l5/e1F5moyM6hbJqG6RTrvN8ABvbhgQxw0D4jibW8QPW0/x9aYkTpzLZ97GJOZtTKJXq2D+b5DKlsjfV/3Ib60Zqmk1jTVbUqo5Nxh5Y/EBsgpK6BYdxK2D6rjxngNaBnrzwW39+XV3Mq/+doBT5wt4+ofdvPnHIW67tA1/7h9Lq5CmS88v3Z8GwPDOLV36yftsYXnNiLVWqDGW9upVoI8nl3UK57JO4Uy7sjPn84pZfeQsKw+ms/JQOmdzi1i6P832fBkM0CkigPjYEOLjQugTF0KXqMBqCx4vah2ugN43QWRPGPIIGAwsLFtFM7539EW5i254gDcPjOjA/cPbs/7YOb7edJLf9ySz+3QW03/czcu/7OPaPq24rl8r+saFuGS5v7uSYKQZqmk1jTVAsThxmmbnyUzmbz4JwIsTezTaP6DBYGB87xiu7B7J5+sS+Wj1MdJyinhrySHeWnKIvq1DGNsjilHdIujQMqBR6ziWH0gFcOkUDdjXjBSZiwB91Iy4Sgt/L66Nj+Ha+BgsFo39KdmsPXKWnSez2HEyk9OZBRxKzeVQaq6t0Nrbw0iPmCBbcHJp+zAigyr3xLnoeHjBdR/ZfszML2bRHtXTY1JfF69uczGDwcCQDuEM6RDOudzu/LDtFF9vOsnxs3l8vSmJrzclEezryfDOLbm8bMrQmdni5kiCkWaopgJWa4DirGkai0XjuYV70DS4rm+rBhWt1pW3h4n7hrfnjiFt+W1PMl9tTGLziQy1VC8pkxm/HSAu1JdRXSO5vGsEg9qFOrV3wO5TWew5nY3RgMs3j6tYM2LNiDSHaRpnMBoN9IgJtit4TsspZNfJLHaeUjtu7zyZSXZhKduSMtmWlAmo7Em/1i0Y1zOKMT2iiAutearoYvHjttMUl1roFh1EfB12Ob9YhAV4c//wDtw3rD0bjmXw7ZaTLD+QRlZBCf/beYb/7VS1TB0jAujfugX927SgX5sWdGjpL0vXK5BgpBmqaWmvoSxAsThpmuazdSfYeSqLAG8PnhnX8KJVR3h5GJnYpxUT+7QiLbuQ3/aksOxAGhuOnuNkRgFz1p1gzroT+HmZGNoxnNHdIriia2SDewa8vewQAJP6tCLcxZ92KgYj1udbgpHqRQT6MLq7D6O7q5oCTdM4cS6fnSdVcLIt6Ty7TmWxNfE8WxPP8/Kv++nVKphrekczvnc0sS0uzsBE0zTbCpX/G9Ra3kSrYDAYGNwhjMEdwig1W9h5KpMVB9JZcTCNvWeyOZKWy5G0XL7ZorLIfl4m2oX7075lAO3D/Wnf0p82Yf60CfUjxM/zovsdSzDSDNmmaaosYFVfzZaGT9McTc/l9d8PAPDMuK5EuDC1HRHkwx1D2nLHkLbkFZWy9shZlh9IY/mBNNJyiliyL5Ul+1IxGHbTNy6EK7tHcWV3x6dzdp/KYun+NIwGePiKjo34iGpXbC7mfJHqhRDmG0aJpQS4uKdpHGUwGGgXrpquWaceUrIKWbw3hd/2JLPpeIatP8Wrvx2gX+sQxveO4Zre0RfVVM7WxPMcTsvF19PkskZn7sTDZKR/m1D6twnliTFdyMgrZlviebYknmdb4nl2nsokv9jM3jPZ7D1T+f810MeDNmF+tAn1p3WYH23Kuhi3CfMnOsgHYzOs15FgpBmqaddeA87JjJgtGk98t5OiUgvDOoU3StFqffl7e3BVjyiu6hGFpmnsPZPNsv1pLN2fyu7TWbaU/Gu/H6BduD+jukYwoK1abREVXPMbjDUrMrFPq0bfqbQ2+zP2A9DCuwUtvFuQX5IPSGakoaKCywPbs7lFLN6bwi87k9lw/Jztb+elX/cxqF0oE+JjGNczutlvZz+vLCsyIT66ydu/Nweh/l6M7h5py8iVmC0knsvnWHoux87mcSw9l+Nn80g8l09aThE5haXsOZ3NntOV/5e9TEZiQ33pEhlIz1bB9Co7uXvzPwlGmiHrNE2VNSNl55kbEIyUmi38/ac9bE/KJNDbg9f+3Fu3KUWDwUDPVsH0bBXMY6M7kZxVoFZX7Etl/dFzHD+bx8drjvPxmuMARAX5EB8XTO/YELpFB9IpIpDoYB+yCkp4Z/kR3WRFAHam7QQgPiIeg8Fg68BaaC6k2FyMl8m9X5z0IDzAm1sHteHWQW1Iyy7k193J/LIrma2J59lwLIMNxzJ4buFehnQI44quEQzr1LLZ1QLsT8621T3ccol+PnS4M0+TkY4RAVXuu1VQbCYpI5/Ec3llX/NJzMgn6Vwep84XUGy2cCw9j2Ppefy2p3yTwFYhvvSODba93vWMCXKrolkJRpohW9OzGpb21reAtbDEzKNfb+ePfakYDfCv63oR04RLahsqOtiX2y9tw+2XtiGnsITVh8+y+nA625MyOZSao/ZS2VvI4r2ptuuYjAZMRoOtjfTdQ9vpoiX0jvQdAMS3VJ1hAzwDMGBAQyO7OJtw33AXjq75iQjy4a6h7bhraDtOnc/n113J/G/XGfaczi77Oypb2eTvRd/WIXSPCaZtmB8xIb4EeHvg52XCv+yrh9GIwaCmTQ0YMBjAaFD/nep8fQQzJWYLT3y3kxKzxpXdI6vspiucy9fLRJeoQLpEBVa6rNRsITmrkONn89ifnM2u01nsOZ1F4rl8TmcWcDqzwC5AiQ72oUdMED1irEFKEFFBPrr5+6pIgpFmqKalvUaDAbS6TdOYLRqnzxdwKjOf5MxC1h87x5J9qWQVlODlYeSdW/oypkeU08ffVAJ9PLm6VzRX91JboOcXl7L7lFppsfdMNvuTszl+No8Ss4bZotEjJojp47pxWSfXv8lrmlaeGSkLRowGIwFeAeQU50gw0shiW/jxwIgOPDCiA8fP5rF4bwprDp9l04kMzuUV2/U2qS8PowFPkxFPk/WrEU8PA55GIxpqeb7ZomGxaFg01VVZKztPA/y9PAj19yLEz5NQfy/CA7yJbeFLXAtVfxDbwhc/r5rfAmYnHGXvmWxC/Dx55U+Ns5+VqDsPk5G4UD/iQv0Y3rl8X6CsghL2ltU27T6dxb4z2Rw7m0dyViHJWYV2f4th/l50jwkqy54E0zU6kDahfi7viSLBSDNU62qaaoKR7MIS1h05y4ZjGWxJzOBwai5FVWwqFRnkzds399VlB8aG8PPyYFD7MAZVeFwWi0Z6bhE5hSW0Dw/QTeFYSl4KaQVpmAwmeoT1sJ0f5BWkghEpYm0y7cL9eXBEBx4c0YHCEnPZrrCZHEnLJbFsz538YjN5xaXkF5vrXDxeatEotZgpKKnfuDLzSzidWfO+PuEBXsSF+tEqxJeYEF+ig32IDvbF02Tgx22n+W2P2ofmhWt7EBF48RTsuptgX0+GdAxnSMfyDyA5hSXsT85hz+msskLZLA6n5XIur9gukwdqZWL7cH9e+VNP+rdxTUdpCUaaoZpW0xgvmKYpMVv4Y28qC3acZuXBdIrN9sGHl4eR2BbqRapzZCBjekQxsG3oRdN90Wg0EBnko7uVEzvTVVakS2gX/DzLl5sGeQVxmtNSxOoiPp4m+rVuQb9qpjM0TaOo1GLLXmiaymqgqW0cLFr5eWaLRonZUnZS3xebLZSUWjAYDJiMKtNpNKhpRINBTSlap3tyiko5n1fM+fwSzucVk5ZTqDYePJ9PUkY+OYWlth1qt5f1WKnKjQNiuVZH+9CIugn08eSSdqFc0q48uCgsMXMwJYc9Z1SvpL1nsjicmktBiZkDKTm1ZsoaU73u+b333uONN94gJSWF+Ph43nnnHS65pPpdYL/77jueffZZTpw4QadOnXjttde4+uqr6z1oUbMa28Fbe1EUljBzySG+3pREWk6R7fL2Lf25rGM4g9qF0T0miNahfhdN4OFOrMGIdYrGylrEKsGIPhkMBqc24GuIrPwSW2ByJrOAM5mFpGSrr5n5xQztGM5tl7ahW3SQq4cqnMTH00R8nNoKwcpi0co6E+fQvqW/y8bmcDDyzTffMG3aND744AMGDRrErFmzGDNmDAcPHiQionI3ynXr1nHLLbcwY8YMxo8fz7x585g0aRLbtm2jZ0+Zg2wMtg6sVdaMqPO2JGawbtthQK0YuHFALNf2iaFLZKAui5uEvR1pO4AqghGvsmBEpmlELYL9PAn2C5YdZy9yRqPBVofiSg4HI2+99Rb33Xcfd911FwAffPABv/76K59++inPPPNMpePffvttxo4dy5NPPgnASy+9xJIlS3j33Xf54IMPGjj8hjlbcJZic7FLx9AYrI2wqpqm8TSZoBQMpnz6tLPwp36xjOzUEk8PI5BLcl5uE49WOKrEUsKBDNVsrk9EH7vLrMHImdwznMk909RDE0K4sXDfcJe1BHAoGCkuLmbr1q1Mnz7ddp7RaGT06NGsX7++yuusX7+eadOm2Z03ZswYFixYUO39FBUVUVRUPnWQnd04n/IeX/G4Ld3dHFXV9Kx7dDDHT4BX2CqOsop/74N/72v6sYmGC/cNJ8bffi7fOk0zd99c5u6b64phCSHc1JdXf1kp29pUHApGzp49i9lsJjIy0u78yMhIDhw4UOV1UlJSqjw+JSWlyuMBZsyYwQsvvODI0OrF0+iJt8l9msI4wtPoyag2oyqdP7b9FaxJXk5haaELRiWcxWgwckvXWypNqY2IHcHCIwvJK8lz0ciEEO6qqg+wTUWXq2mmT59ul03Jzs4mLi7O6ffz2djPnH6bejcybiRrbl7j6mGIRtI/sj8rb1rp6mEIIYRDHApGwsPDMZlMpKam2p2fmppKVFTVza+ioqIcOh7A29sbb+/mmbEQQgghhD2HWq55eXnRv39/li1bZjvPYrGwbNkyBg8eXOV1Bg8ebHc8wJIlS6o9XgghhBAXF4enaaZNm8Ydd9zBgAEDuOSSS5g1axZ5eXm21TWTJ0+mVatWzJgxA4DHHnuMESNG8Oabb3LNNdcwf/58tmzZwkcffeTcRyKEEEIIt+RwMHLTTTeRnp7Oc889R0pKCn369OH333+3FakmJSVhNJYnXIYMGcK8efP4xz/+wd/+9jc6derEggULpMeIEEIIIQAwaNbe4TqWnZ1NcHAwWVlZBAVJN0AhhBDCHdT1/du12/QJIYQQ4qInwYgQQgghXEqCESGEEEK4lAQjQgghhHApCUaEEEII4VISjAghhBDCpSQYEUIIIYRLSTAihBBCCJeSYEQIIYQQLuVwO3hXsDaJzc7OdvFIhBBCCFFX1vft2pq9u0UwkpOTA0BcXJyLRyKEEEIIR+Xk5BAcHFzt5W6xN43FYuHMmTMEBgZiMBicdrvZ2dnExcVx8uTJZrvnjTxG99fcHx/IY2wOmvvjg+b/GBvj8WmaRk5ODjExMXab6F7ILTIjRqOR2NjYRrv9oKCgZvmHVZE8RvfX3B8fyGNsDpr744Pm/xid/fhqyohYSQGrEEIIIVxKghEhhBBCuNRFHYx4e3vz/PPP4+3t7eqhNBp5jO6vuT8+kMfYHDT3xwfN/zG68vG5RQGrEEIIIZqvizozIoQQQgjXk2BECCGEEC4lwYgQQgghXEqCESGEEEK41EUdjLz33nu0bdsWHx8fBg0axKZNm1w9pHqZMWMGAwcOJDAwkIiICCZNmsTBgwftjhk5ciQGg8Hu9OCDD7poxI775z//WWn8Xbt2tV1eWFjI1KlTCQsLIyAggD//+c+kpqa6cMSOa9u2baXHaDAYmDp1KuB+z+GqVauYMGECMTExGAwGFixYYHe5pmk899xzREdH4+vry+jRozl8+LDdMRkZGdx6660EBQUREhLCPffcQ25ubhM+iprV9BhLSkp4+umn6dWrF/7+/sTExDB58mTOnDljdxtVPe+vvvpqEz+S6tX2PN55552Vxj927Fi7Y/T8PNb2+Kr6nzQYDLzxxhu2Y/T8HNbl/aEur59JSUlcc801+Pn5ERERwZNPPklpaanTxnnRBiPffPMN06ZN4/nnn2fbtm3Ex8czZswY0tLSXD00h61cuZKpU6eyYcMGlixZQklJCVdddRV5eXl2x913330kJyfbTq+//rqLRlw/PXr0sBv/mjVrbJf95S9/4X//+x/fffcdK1eu5MyZM1x33XUuHK3jNm/ebPf4lixZAsANN9xgO8adnsO8vDzi4+N57733qrz89ddf5z//+Q8ffPABGzduxN/fnzFjxlBYWGg75tZbb2Xv3r0sWbKEX375hVWrVnH//fc31UOoVU2PMT8/n23btvHss8+ybds2fvzxRw4ePMi1115b6dgXX3zR7nl95JFHmmL4dVLb8wgwduxYu/F//fXXdpfr+Xms7fFVfFzJycl8+umnGAwG/vznP9sdp9fnsC7vD7W9fprNZq655hqKi4tZt24dc+fOZc6cOTz33HPOG6h2kbrkkku0qVOn2n42m81aTEyMNmPGDBeOyjnS0tI0QFu5cqXtvBEjRmiPPfaY6wbVQM8//7wWHx9f5WWZmZmap6en9t1339nO279/vwZo69evb6IROt9jjz2mdejQQbNYLJqmufdzCGg//fST7WeLxaJFRUVpb7zxhu28zMxMzdvbW/v66681TdO0ffv2aYC2efNm2zG//fabZjAYtNOnTzfZ2OvqwsdYlU2bNmmAlpiYaDuvTZs22syZMxt3cE5S1WO84447tIkTJ1Z7HXd6HuvyHE6cOFG74oor7M5zp+fwwveHurx+Llq0SDMajVpKSortmNmzZ2tBQUFaUVGRU8Z1UWZGiouL2bp1K6NHj7adZzQaGT16NOvXr3fhyJwjKysLgNDQULvzv/rqK8LDw+nZsyfTp08nPz/fFcOrt8OHDxMTE0P79u259dZbSUpKAmDr1q2UlJTYPZ9du3aldevWbvt8FhcX8+WXX3L33XfbbQ7p7s+h1fHjx0lJSbF7zoKDgxk0aJDtOVu/fj0hISEMGDDAdszo0aMxGo1s3LixycfsDFlZWRgMBkJCQuzOf/XVVwkLC6Nv37688cYbTk1/N4WEhAQiIiLo0qULU6ZM4dy5c7bLmtPzmJqayq+//so999xT6TJ3eQ4vfH+oy+vn+vXr6dWrF5GRkbZjxowZQ3Z2Nnv37nXKuNxiozxnO3v2LGaz2e4XCxAZGcmBAwdcNCrnsFgsPP744wwdOpSePXvazv+///s/2rRpQ0xMDLt27eLpp5/m4MGD/Pjjjy4cbd0NGjSIOXPm0KVLF5KTk3nhhRcYNmwYe/bsISUlBS8vr0ov8JGRkaSkpLhmwA20YMECMjMzufPOO23nuftzWJH1eanqf9B6WUpKChEREXaXe3h4EBoa6pbPa2FhIU8//TS33HKL3SZkjz76KP369SM0NJR169Yxffp0kpOTeeutt1w42robO3Ys1113He3atePo0aP87W9/Y9y4caxfvx6TydSsnse5c+cSGBhYaQrYXZ7Dqt4f6vL6mZKSUuX/qvUyZ7gog5HmbOrUqezZs8eungKwm5/t1asX0dHRjBo1iqNHj9KhQ4emHqbDxo0bZ/u+d+/eDBo0iDZt2vDtt9/i6+vrwpE1jk8++YRx48YRExNjO8/dn8OLWUlJCTfeeCOapjF79my7y6ZNm2b7vnfv3nh5efHAAw8wY8YMt2g7fvPNN9u+79WrF71796ZDhw4kJCQwatQoF47M+T799FNuvfVWfHx87M53l+ewuvcHPbgop2nCw8MxmUyVqoVTU1OJiopy0aga7uGHH+aXX35hxYoVxMbG1njsoEGDADhy5EhTDM3pQkJC6Ny5M0eOHCEqKori4mIyMzPtjnHX5zMxMZGlS5dy77331nicOz+H1uelpv/BqKioSgXlpaWlZGRkuNXzag1EEhMTWbJkSa1bsw8aNIjS0lJOnDjRNAN0svbt2xMeHm77u2wuz+Pq1as5ePBgrf+XoM/nsLr3h7q8fkZFRVX5v2q9zBkuymDEy8uL/v37s2zZMtt5FouFZcuWMXjwYBeOrH40TePhhx/mp59+Yvny5bRr167W6+zYsQOA6OjoRh5d48jNzeXo0aNER0fTv39/PD097Z7PgwcPkpSU5JbP52effUZERATXXHNNjce583PYrl07oqKi7J6z7OxsNm7caHvOBg8eTGZmJlu3brUds3z5ciwWiy0Q0ztrIHL48GGWLl1KWFhYrdfZsWMHRqOx0tSGuzh16hTnzp2z/V02h+cRVLayf//+xMfH13qsnp7D2t4f6vL6OXjwYHbv3m0XVFoD6+7duzttoBel+fPna97e3tqcOXO0ffv2affff78WEhJiVy3sLqZMmaIFBwdrCQkJWnJysu2Un5+vaZqmHTlyRHvxxRe1LVu2aMePH9cWLlyotW/fXhs+fLiLR153f/3rX7WEhATt+PHj2tq1a7XRo0dr4eHhWlpamqZpmvbggw9qrVu31pYvX65t2bJFGzx4sDZ48GAXj9pxZrNZa926tfb000/bne+Oz2FOTo62fft2bfv27RqgvfXWW9r27dttK0leffVVLSQkRFu4cKG2a9cubeLEiVq7du20goIC222MHTtW69u3r7Zx40ZtzZo1WqdOnbRbbrnFVQ+pkpoeY3FxsXbttddqsbGx2o4dO+z+N60rENatW6fNnDlT27Fjh3b06FHtyy+/1Fq2bKlNnjzZxY+sXE2PMScnR3viiSe09evXa8ePH9eWLl2q9evXT+vUqZNWWFhouw09P4+1/Z1qmqZlZWVpfn5+2uzZ/9/O3bM0EoVRHH+WrBMTxKBkiCJoChsltXYSCARSpgqp1MLGSlCLFDYWfgGLxUr8Flql1UKwDQQS0qSJYAjEwpezxS4LEtfsiuyTxf8PppkwcC53Zu5JmMm3geNHfQ6HrQ/S8Pvn4+OjMpmM8vm8bm5udH5+rjAMValUPiznpy0jknR8fKz5+XkFQaCVlRVdXl56R3oXM3t1Oz09lSS1Wi2tra1penpa0WhUi4uL2t/fV7fb9Q3+F0qlkmZnZxUEgebm5lQqlVSv1399fn9/r+3tbU1NTSkej6tYLKrdbjsmfp+LiwuZmWq12ov9/+McVqvVV8/L9fV1ST9e7z04OFAqlVI0GlUulxsY9+3trcrlsiYmJjQ5OanNzU31ej2H0bzurTE2Go3fXpvValWSdH19rdXVVSUSCY2Pj2tpaUlHR0cvFnJvb42x3+8rn88rDEONjY1pYWFBW1tbA1/qRnkeh52nknRycqJYLKa7u7uB40d9DoetD9Kf3T+bzaYKhYJisZiSyaR2d3f18PDwYTm//AwLAADg4lM+MwIAAEYHZQQAALiijAAAAFeUEQAA4IoyAgAAXFFGAACAK8oIAABwRRkBAACuKCMA3GSzWdvZ2fGOAcAZZQQAALji7+ABuNjY2LCzs7MX+xqNhqXTaZ9AANxQRgC46Ha7VigULJPJ2OHhoZmZhWFokUjEORmAf+2rdwAAn1MikbAgCCwej9vMzIx3HACOeGYEAAC4oowAAABXlBEAboIgsKenJ+8YAJxRRgC4SafTdnV1Zc1m0zqdjj0/P3tHAuCAMgLAzd7enkUiEVteXrYwDK3VanlHAuCAV3sBAIArfhkBAACuKCMAAMAVZQQAALiijAAAAFeUEQAA4IoyAgAAXFFGAACAK8oIAABwRRkBAACuKCMAAMAVZQQAALiijAAAAFffAdScfF0SRbvFAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -455,11 +455,14 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 13, "id": "a20d7ed0-8a57-42aa-84f1-ecc148e7988d", "metadata": {}, "outputs": [], "source": [ + "def mwt_obs(mwt):\n", + " return 2 * (mwt - MINWT) / (MAXWT - MINWT) - 1 \n", + "\n", "def get_policy_df(policy_obj, mwt, minx=-1, maxx=1, nx=500):\n", " env=AsmEnv(config=CONFIG3)\n", " obs_list = np.linspace(minx, maxx, nx)\n", @@ -469,7 +472,7 @@ " 'mwt': [mwt for _ in obs_list],\n", " 'biomass': env.bound * (obs_list + 1)/2,\n", " 'fishing_mortality': [\n", - " (1 + policy_obj.predict(np.float32([obs, mwt]))[0][0]) / 2 \n", + " (1 + policy_obj.predict(np.float32([obs, mwt_obs(mwt)]))[0][0]) / 2 \n", " for obs in obs_list\n", " ]\n", " }\n", @@ -488,45 +491,66 @@ " # policy_obj.predict(np.float32([obs, mwt]))[0]\n", " # )[0] \n", " env.bound * (\n", - " 1+policy_obj.predict(np.float32([obs, mwt]))[0][0]\n", + " 1+policy_obj.predict(np.float32([obs, mwt_obs(mwt)]))[0][0]\n", + " ) / 2\n", + " for obs in obs_list\n", + " ]\n", + " }\n", + " )\n", + "\n", + "def get_esc_mwt_policy_df(policy_obj, biomass, minx=-1, maxx=1, nx=500):\n", + " env=AsmEnvEsc(config=CONFIG3)\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'mwt': MINWT + (MAXWT - MINWT) * (obs_list+1)/2,\n", + " 'biomass': [biomass for _ in obs_list],\n", + " 'fishing_escapement': [\n", + " # env.get_mortality(\n", + " # policy_obj.predict(np.float32([obs, mwt]))[0]\n", + " # )[0] \n", + " env.bound * (\n", + " 1+policy_obj.predict(np.float32([2 * biomass/env.bound - 1, obs]))[0][0]\n", " ) / 2\n", " for obs in obs_list\n", " ]\n", " }\n", - " )" + " )\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 30, "id": "245547ba-b2ba-4e61-8409-4e98c79d47fc", "metadata": {}, "outputs": [], "source": [ "cr_df = get_policy_df(cr3, mwt=0.5, maxx=-1+0.14)\n", "\n", - "ppo1_df_mwt1 = get_policy_df(ppoAgent1, mwt=0.3, maxx=-1+0.14)\n", - "ppo1_df_mwt2 = get_policy_df(ppoAgent1, mwt=0.4, maxx=-1+0.14)\n", - "ppo1_df_mwt3 = get_policy_df(ppoAgent1, mwt=0.5, maxx=-1+0.14)\n", - "ppo1_df_mwt4 = get_policy_df(ppoAgent1, mwt=0.6, maxx=-1+0.14)\n", - "ppo1_df_mwt5 = get_policy_df(ppoAgent1, mwt=0.8, maxx=-1+0.14)\n", - "\n", - "ppo2_df_mwt1 = get_policy_df(ppoAgent2, mwt=0.3, maxx=-1+0.14)\n", - "ppo2_df_mwt2 = get_policy_df(ppoAgent2, mwt=0.4, maxx=-1+0.14)\n", - "ppo2_df_mwt3 = get_policy_df(ppoAgent2, mwt=0.5, maxx=-1+0.14)\n", - "ppo2_df_mwt4 = get_policy_df(ppoAgent2, mwt=0.6, maxx=-1+0.14)\n", - "ppo2_df_mwt5 = get_policy_df(ppoAgent2, mwt=0.8, maxx=-1+0.14)\n", - "\n", - "ppoEsc_df_mwt1 = get_esc_policy_df(ppoAgentEsc, mwt=0.3, maxx=-1+0.14)\n", - "ppoEsc_df_mwt2 = get_esc_policy_df(ppoAgentEsc, mwt=0.4, maxx=-1+0.14)\n", - "ppoEsc_df_mwt3 = get_esc_policy_df(ppoAgentEsc, mwt=0.5, maxx=-1+0.14)\n", - "ppoEsc_df_mwt4 = get_esc_policy_df(ppoAgentEsc, mwt=0.6, maxx=-1+0.14)\n", - "ppoEsc_df_mwt5 = get_esc_policy_df(ppoAgentEsc, mwt=0.8, maxx=-1+0.14)" + "ppo1_df_mwt1 = get_policy_df(ppoAgent1, mwt=0.6, maxx=-1+0.14)\n", + "ppo1_df_mwt2 = get_policy_df(ppoAgent1, mwt=0.7, maxx=-1+0.14)\n", + "ppo1_df_mwt3 = get_policy_df(ppoAgent1, mwt=0.8, maxx=-1+0.14)\n", + "ppo1_df_mwt4 = get_policy_df(ppoAgent1, mwt=0.9, maxx=-1+0.14)\n", + "ppo1_df_mwt5 = get_policy_df(ppoAgent1, mwt=0.95, maxx=-1+0.14)\n", + "\n", + "ppo2_df_mwt1 = get_policy_df(ppoAgent2, mwt=0.6, maxx=-1+0.14)\n", + "ppo2_df_mwt2 = get_policy_df(ppoAgent2, mwt=0.7, maxx=-1+0.14)\n", + "ppo2_df_mwt3 = get_policy_df(ppoAgent2, mwt=0.8, maxx=-1+0.14)\n", + "ppo2_df_mwt4 = get_policy_df(ppoAgent2, mwt=0.9, maxx=-1+0.14)\n", + "ppo2_df_mwt5 = get_policy_df(ppoAgent2, mwt=0.95, maxx=-1+0.14)\n", + "\n", + "ppoEsc_df_mwt1 = get_esc_policy_df(ppoAgentEsc, mwt=0.6, maxx=-1+0.14)\n", + "ppoEsc_df_mwt2 = get_esc_policy_df(ppoAgentEsc, mwt=0.7, maxx=-1+0.14)\n", + "ppoEsc_df_mwt3 = get_esc_policy_df(ppoAgentEsc, mwt=0.8, maxx=-1+0.14)\n", + "ppoEsc_df_mwt4 = get_esc_policy_df(ppoAgentEsc, mwt=0.9, maxx=-1+0.14)\n", + "ppoEsc_df_mwt5 = get_esc_policy_df(ppoAgentEsc, mwt=0.95, maxx=-1+0.14)" ] }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 31, "id": "7473b83a-64db-45c2-aec7-c6055d881a7f", "metadata": {}, "outputs": [], @@ -561,13 +585,13 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 32, "id": "339e8de2-9152-4cd5-be35-2234ca5dac5a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -587,13 +611,13 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 33, "id": "a4f825c2-8935-4152-8feb-daee36c7bf3a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -642,6 +666,71 @@ ")+geom_point()" ] }, + { + "cell_type": "code", + "execution_count": 43, + "id": "1c395e68-8cf0-43eb-97cd-73bc8920ea89", + "metadata": {}, + "outputs": [], + "source": [ + "ppo_esc_mwt_df1 = get_esc_mwt_policy_df(ppoAgentEsc, biomass=0.2)\n", + "ppo_esc_mwt_df2 = get_esc_mwt_policy_df(ppoAgentEsc, biomass=0.5)\n", + "ppo_esc_mwt_df3 = get_esc_mwt_policy_df(ppoAgentEsc, biomass=1.5)\n", + "ppo_esc_mwt_df4 = get_esc_mwt_policy_df(ppoAgentEsc, biomass=2.5)\n", + "ppo_esc_mwt_df5 = get_esc_mwt_policy_df(ppoAgentEsc, biomass=3.5)\n", + "\n", + "ppo_esc_mwt_df = pd.concat(\n", + " [ppo_esc_mwt_df1,\n", + " ppo_esc_mwt_df2,\n", + " ppo_esc_mwt_df3,\n", + " ppo_esc_mwt_df4,\n", + " ppo_esc_mwt_df5,\n", + " ]\n", + ")\n", + "\n", + "def mortality_from_esc(esc, biomass):\n", + " if biomass <= esc or biomass <= 0:\n", + " return 0\n", + " else:\n", + " return (biomass - esc)/biomass\n", + "\n", + "ppo_esc_mwt_df['fishing_mortality'] = ppo_esc_mwt_df.apply(\n", + " lambda row: mortality_from_esc(row.fishing_escapement, row.biomass),\n", + " axis=1,\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "8208a3c4-edda-476f-b72f-7280925ffffb", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "# ggplot(\n", + "# ppo_esc_mwt_df,\n", + "# aes(x='mwt', y='fishing_mortality', color='biomass')\n", + "# )+geom_point()\n", + "\n", + "ggplot(\n", + " ppo_esc_mwt_df,\n", + " aes(x='mwt', y='fishing_escapement', color='biomass')\n", + ")+geom_point()" + ] + }, { "cell_type": "code", "execution_count": 50, From 5ec60e8596be9b259f5a51f5426952b550868834 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:02:48 +0000 Subject: [PATCH 50/64] added constant action agent --- src/rl4fisheries/__init__.py | 1 + src/rl4fisheries/agents/const_act.py | 14 ++++++++++++++ 2 files changed, 15 insertions(+) create mode 100644 src/rl4fisheries/agents/const_act.py diff --git a/src/rl4fisheries/__init__.py b/src/rl4fisheries/__init__.py index 6c71b1b..aaab717 100644 --- a/src/rl4fisheries/__init__.py +++ b/src/rl4fisheries/__init__.py @@ -9,6 +9,7 @@ from rl4fisheries.agents.cautionary_rule import CautionaryRule from rl4fisheries.agents.const_esc import ConstEsc from rl4fisheries.agents.msy import Msy +from rl4fisheries.agents.const_act import ConstAct from gymnasium.envs.registration import register diff --git a/src/rl4fisheries/agents/const_act.py b/src/rl4fisheries/agents/const_act.py new file mode 100644 index 0000000..54b23d9 --- /dev/null +++ b/src/rl4fisheries/agents/const_act.py @@ -0,0 +1,14 @@ +import numpy as np + +class ConstAct: + def __init__(self, env, action): + self.env = env + self.action=action + + def predict(self, observation): + return self.action, {} + # + def action_to_mortality(self, action): + return (self.action + 1 ) / 2 + def action_to_escapement(self, action): + return self.env.bound * (self.action + 1 ) / 2 \ No newline at end of file From d01696226f7ac9504bb053c57d01dc01d6ef4be0 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:03:25 +0000 Subject: [PATCH 51/64] hyperpars --- hyperpars/ppo-asm.yml | 23 ++++++++++++----------- 1 file changed, 12 insertions(+), 11 deletions(-) diff --git a/hyperpars/ppo-asm.yml b/hyperpars/ppo-asm.yml index 918b25e..be40808 100644 --- a/hyperpars/ppo-asm.yml +++ b/hyperpars/ppo-asm.yml @@ -1,21 +1,22 @@ # algo algo: "PPO" -total_timesteps: 10000000 +total_timesteps: 4000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - # batch_size: 512 - # gamma: 0.9999 - # learning_rate: !!float 7.77e-05 - # ent_coef: 0.00429 - # clip_range: 0.1 - # gae_lambda: 0.9 - # max_grad_norm: 5 - # vf_coef: 0.19 + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[300, 200])" use_sde: True - # clip_range: 0.1 + clip_range: 0.1 # env env_id: "AsmEnv" @@ -34,6 +35,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "results-trophy-nage-10-1obs" +id: "results-trophy-nage-10-1obs-hyperpars-larger-net" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file From 912b973a89b3b13b6e1559bfef1519e456ce3889 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:04:05 +0000 Subject: [PATCH 52/64] require scikit-learn specific version for skopt to work currently --- pyproject.toml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 8ab01c6..7272908 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,7 +7,10 @@ dependencies = ["gymnasium", "matplotlib", "typing", "polars", - "tqdm"] + "tqdm", + "scikit-optimize", + "scikit-learn==1.4.2", + ] [project.optional-dependencies] tests = ["pytest", "pytest-cov", "stable_baselines3", "sb3-contrib", "ray"] From 9c8455d2575deeb5906f51144e3ab51723ce1e1e Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:05:11 +0000 Subject: [PATCH 53/64] fixed policy scripts update --- scripts/fixed_policy_opt.py | 2 + scripts/tune.py | 160 +++++++++++++++++++++++++++++++++ scripts/tune_fixed_policies.sh | 11 +-- 3 files changed, 165 insertions(+), 8 deletions(-) create mode 100644 scripts/tune.py diff --git a/scripts/fixed_policy_opt.py b/scripts/fixed_policy_opt.py index 5bda2c2..f9e3438 100644 --- a/scripts/fixed_policy_opt.py +++ b/scripts/fixed_policy_opt.py @@ -21,6 +21,8 @@ from rl4fisheries import AsmEnv from rl4fisheries.utils import evaluate_agent +login() + # optimization algo if args.opt_algo == "gp": from skopt import gp_minimize diff --git a/scripts/tune.py b/scripts/tune.py new file mode 100644 index 0000000..a894bde --- /dev/null +++ b/scripts/tune.py @@ -0,0 +1,160 @@ +#!/opt/venv/bin/python +import argparse +parser = argparse.ArgumentParser() +parser.add_argument("-f", "--input-file", help="input yaml file") +parser.add_argument("-hf-login", "--do-huggingface-login", default=False, type=bool, help="Whether to log in to hugging face from tune.py script.") +args = parser.parse_args() + +import numpy as np +import yaml + +from huggingface_hub import hf_hub_download, HfApi, login +from skopt import gp_minimize, dump +from skopt.space import Real +from skopt.utils import use_named_args + +from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule +from rl4fisheries.utils import evaluate_agent + +with open(args.input_file, "r") as stream: + OPTIONS = yaml.safe_load(stream) + +""" +OPTIONS = { + 'config': {...} + 'n_eval_episodes': ... + 'n_calls': ... + 'id': ... + 'repo_id': +} +""" + +# +# +### HF + +if args.do_huggingface_login: + login() +api = HfApi() + +# +# +### OPTIMIZATION OBJECTIVE FNS + +msy_space = [Real(0.0001, 0.5, name='mortality')] +esc_space = [Real(0.0001, 10, name='escapement')] +cr_space = [ + Real(0.00001, 10, name='radius'), + Real(0.00001, np.pi/4.00001, name='theta'), + Real(0, 0.8, name='y2') +] + +@use_named_args(msy_space) +def msy_fn(**params): + agent = Msy( + AsmEnv(config=OPTIONS['config']), + mortality=params['mortality'], + ) + m_reward = evaluate_agent(agent=agent, ray_remote=True).evaluate( + n_eval_episodes=OPTIONS['n_eval_episodes'] + ) + return -m_reward + +@use_named_args(esc_space) +def esc_fn(**params): + agent = ConstEsc( + AsmEnv(config=OPTIONS['config']), + escapement=params['escapement'], + ) + m_reward = evaluate_agent(agent=agent, ray_remote=True).evaluate( + n_eval_episodes=OPTIONS['n_eval_episodes'] + ) + return -m_reward + +@use_named_args(cr_space) +def cr_fn(**params): + theta = params["theta"] + radius = params["radius"] + x1 = np.sin(theta) * radius + x2 = np.cos(theta) * radius + # + agent = CautionaryRule( + AsmEnv(config=OPTIONS['config']), + x1 = x1, + x2 = x2, + y2 = params["y2"], + ) + m_reward = evaluate_agent(agent=agent, ray_remote=True).evaluate( + n_eval_episodes=OPTIONS['n_eval_episodes'] + ) + return -m_reward + +# +# +### OPTIMIZE + +msy_results = gp_minimize(msy_fn, msy_space, n_calls=OPTIONS['n_calls'], verbose=True) + +print( + "\n\n" + f"gp-msy results: " + f"opt args = {[eval(f'{r:.4f}') for r in msy_results.x]}, " + f"rew={msy_results.fun:.4f}" + "\n\n" +) + +esc_results = gp_minimize(esc_fn, esc_space, n_calls=OPTIONS['n_calls'], verbose=True) + +print( + "\n\n" + f"gp-esc results: " + f"opt args = {[eval(f'{r:.4f}') for r in esc_results.x]}, " + f"rew={esc_results.fun:.4f}" + "\n\n" +) + +cr_results = gp_minimize(cr_fn, cr_space, n_calls=OPTIONS['n_calls'], verbose=True) + +print( + "\n\n" + f"gp-cr results: " + f"opt args = {[eval(f'{r:.4f}') for r in cr_results.x]}, " + f"rew={cr_results.fun:.4f}" + "\n\n" +) + +# +# +### SAVE + +path = "../saved_agents/results/" +msy_fname = f"msy-{OPTIONS['id']}.pkl" +esc_fname = f"esc-{OPTIONS['id']}.pkl" +cr_fname = f"cr-{OPTIONS['id']}.pkl" + +dump(msy_results, path+msy_fname) +dump(esc_results, path+esc_fname) +dump(cr_results, path+cr_fname) + +# HF + +api.upload_file( + path_or_fileobj=path+msy_fname, + path_in_repo="sb3/rl4fisheries/results/"+msy_fname, + repo_id=OPTIONS["repo_id"], + repo_type="model", +) + +api.upload_file( + path_or_fileobj=path+esc_fname, + path_in_repo="sb3/rl4fisheries/results/"+esc_fname, + repo_id=OPTIONS["repo_id"], + repo_type="model", +) + +api.upload_file( + path_or_fileobj=path+cr_fname, + path_in_repo="sb3/rl4fisheries/results/"+cr_fname, + repo_id=OPTIONS["repo_id"], + repo_type="model", +) diff --git a/scripts/tune_fixed_policies.sh b/scripts/tune_fixed_policies.sh index cb6eba4..dbcd252 100644 --- a/scripts/tune_fixed_policies.sh +++ b/scripts/tune_fixed_policies.sh @@ -8,11 +8,6 @@ cd "$scriptdir" python hf_login.py # gp -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gp -nc 100 -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gp -nc 100 -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gp -nc 100 - -# gbrt -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p msy -v True -o gbrt -nc 100 -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p esc -v True -o gbrt -nc 100 -python fixed_policy_opt.py -f ../hyperpars/tqc-asm.yml -p cr -v True -o gbrt -nc 100 \ No newline at end of file +python tune.py -f ../hyperpars/for_results/fixed_policy_UM1.yml +python tune.py -f ../hyperpars/for_results/fixed_policy_UM2.yml +python tune.py -f ../hyperpars/for_results/fixed_policy_UM3.yml From cdf32004a3c405b591932d053cdd094c2a0efb76 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:06:25 +0000 Subject: [PATCH 54/64] mwt obs in AsmEnv --- src/rl4fisheries/envs/asm_env.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/rl4fisheries/envs/asm_env.py b/src/rl4fisheries/envs/asm_env.py index 50d48e0..82d0bb3 100644 --- a/src/rl4fisheries/envs/asm_env.py +++ b/src/rl4fisheries/envs/asm_env.py @@ -12,6 +12,7 @@ render_asm, get_r_devs, get_r_devs_v2, + observe_mwt, ) # equilibrium dist will in general depend on parameters, need a more robust way @@ -125,6 +126,7 @@ def __init__(self, render_mode: Optional[str] = 'rgb_array', config={}): "observe_total": observe_total, "observe_total_2o": observe_total_2o, "observe_total_2o_v2": observe_total_2o_v2, + "observe_mwt": observe_mwt, } self._observation_fn = obs_fn_choices[ config.get("observation_fn_id", "observe_2o") From 926c30a51d0a4ebf4f254fc78c8989cab9ce53f6 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:06:47 +0000 Subject: [PATCH 55/64] small denominator safety in AsmEnvEsc --- src/rl4fisheries/envs/asm_esc.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/src/rl4fisheries/envs/asm_esc.py b/src/rl4fisheries/envs/asm_esc.py index 6de10fd..3515146 100644 --- a/src/rl4fisheries/envs/asm_esc.py +++ b/src/rl4fisheries/envs/asm_esc.py @@ -42,10 +42,13 @@ def escapement_units(self, action): def get_mortality(self, action): escapement = self.escapement_units(action) - current_pop = self.population_units() - if current_pop <= 0: + current_observed_pop = self.surv_vul_b + if ( + (current_observed_pop <= escapement) + or (current_observed_pop<=1e-10) + ): mortality = np.float32([0]) else: - mortality = (current_pop - escapement) / current_pop + mortality = (current_observed_pop - escapement) / current_observed_pop mortality = np.clip(mortality, 0, np.inf) return mortality \ No newline at end of file From af28fb1d30bcb65ef46dd6b6c4f627391131150e Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:10:14 +0000 Subject: [PATCH 56/64] input files galore --- hyperpars/for_results/fixed_policy_UM1.yml | 7 ++++ hyperpars/for_results/fixed_policy_UM2.yml | 7 ++++ hyperpars/for_results/fixed_policy_UM3.yml | 8 +++++ hyperpars/for_results/ppo_biomass_UM1.yml | 38 ++++++++++++++++++++ hyperpars/for_results/ppo_biomass_UM2.yml | 38 ++++++++++++++++++++ hyperpars/for_results/ppo_biomass_UM3.yml | 39 +++++++++++++++++++++ hyperpars/for_results/ppo_both_UM1.yml | 38 ++++++++++++++++++++ hyperpars/for_results/ppo_both_UM2.yml | 38 ++++++++++++++++++++ hyperpars/for_results/ppo_both_UM3.yml | 39 +++++++++++++++++++++ hyperpars/for_results/ppo_mwt_UM1.yml | 38 ++++++++++++++++++++ hyperpars/for_results/ppo_mwt_UM2.yml | 38 ++++++++++++++++++++ hyperpars/for_results/ppo_mwt_UM3.yml | 39 +++++++++++++++++++++ hyperpars/ppo-asm-esc.yml | 40 ++++++++++++++++++++++ 13 files changed, 407 insertions(+) create mode 100644 hyperpars/for_results/fixed_policy_UM1.yml create mode 100644 hyperpars/for_results/fixed_policy_UM2.yml create mode 100644 hyperpars/for_results/fixed_policy_UM3.yml create mode 100644 hyperpars/for_results/ppo_biomass_UM1.yml create mode 100644 hyperpars/for_results/ppo_biomass_UM2.yml create mode 100644 hyperpars/for_results/ppo_biomass_UM3.yml create mode 100644 hyperpars/for_results/ppo_both_UM1.yml create mode 100644 hyperpars/for_results/ppo_both_UM2.yml create mode 100644 hyperpars/for_results/ppo_both_UM3.yml create mode 100644 hyperpars/for_results/ppo_mwt_UM1.yml create mode 100644 hyperpars/for_results/ppo_mwt_UM2.yml create mode 100644 hyperpars/for_results/ppo_mwt_UM3.yml create mode 100644 hyperpars/ppo-asm-esc.yml diff --git a/hyperpars/for_results/fixed_policy_UM1.yml b/hyperpars/for_results/fixed_policy_UM1.yml new file mode 100644 index 0000000..87ca70e --- /dev/null +++ b/hyperpars/for_results/fixed_policy_UM1.yml @@ -0,0 +1,7 @@ +config: + upow: 1 + harvest_fn_name: "default" +n_eval_episodes: 250 +n_calls: 40 +id: "UM1" +repo_id: "boettiger-lab/rl4eco" \ No newline at end of file diff --git a/hyperpars/for_results/fixed_policy_UM2.yml b/hyperpars/for_results/fixed_policy_UM2.yml new file mode 100644 index 0000000..4b8ff19 --- /dev/null +++ b/hyperpars/for_results/fixed_policy_UM2.yml @@ -0,0 +1,7 @@ +config: + upow: 0.6 + harvest_fn_name: "default" +n_eval_episodes: 250 +n_calls: 40 +id: "UM2" +repo_id: "boettiger-lab/rl4eco" \ No newline at end of file diff --git a/hyperpars/for_results/fixed_policy_UM3.yml b/hyperpars/for_results/fixed_policy_UM3.yml new file mode 100644 index 0000000..e566562 --- /dev/null +++ b/hyperpars/for_results/fixed_policy_UM3.yml @@ -0,0 +1,8 @@ +config: + upow: 1 + harvest_fn_name: "trophy" + n_trophy_ages: 10 +n_eval_episodes: 250 +n_calls: 40 +id: "UM3" +repo_id: "boettiger-lab/rl4eco" \ No newline at end of file diff --git a/hyperpars/for_results/ppo_biomass_UM1.yml b/hyperpars/for_results/ppo_biomass_UM1.yml new file mode 100644 index 0000000..f30755a --- /dev/null +++ b/hyperpars/for_results/ppo_biomass_UM1.yml @@ -0,0 +1,38 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_1o' + n_observs: 1 + # + harvest_fn_name: "default" + upow: 1 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "biomass-UM1" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_biomass_UM2.yml b/hyperpars/for_results/ppo_biomass_UM2.yml new file mode 100644 index 0000000..f0847f2 --- /dev/null +++ b/hyperpars/for_results/ppo_biomass_UM2.yml @@ -0,0 +1,38 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_1o' + n_observs: 1 + # + harvest_fn_name: "default" + upow: 0.6 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "biomass-UM2" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_biomass_UM3.yml b/hyperpars/for_results/ppo_biomass_UM3.yml new file mode 100644 index 0000000..932e1e2 --- /dev/null +++ b/hyperpars/for_results/ppo_biomass_UM3.yml @@ -0,0 +1,39 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_1o' + n_observs: 1 + # + harvest_fn_name: "trophy" + n_trophy_ages: 10 + upow: 1 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "biomass-UM3" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_both_UM1.yml b/hyperpars/for_results/ppo_both_UM1.yml new file mode 100644 index 0000000..5ef91f2 --- /dev/null +++ b/hyperpars/for_results/ppo_both_UM1.yml @@ -0,0 +1,38 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_2o' + n_observs: 2 + # + harvest_fn_name: "default" + upow: 1 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "2obs-UM1" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_both_UM2.yml b/hyperpars/for_results/ppo_both_UM2.yml new file mode 100644 index 0000000..d7ab1a6 --- /dev/null +++ b/hyperpars/for_results/ppo_both_UM2.yml @@ -0,0 +1,38 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_2o' + n_observs: 2 + # + harvest_fn_name: "default" + upow: 0.6 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "2obs-UM2" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_both_UM3.yml b/hyperpars/for_results/ppo_both_UM3.yml new file mode 100644 index 0000000..4f46ed2 --- /dev/null +++ b/hyperpars/for_results/ppo_both_UM3.yml @@ -0,0 +1,39 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_2o' + n_observs: 2 + # + harvest_fn_name: "trophy" + n_trophy_ages: 10 + upow: 1 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "2obs-UM1" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_mwt_UM1.yml b/hyperpars/for_results/ppo_mwt_UM1.yml new file mode 100644 index 0000000..1279b3b --- /dev/null +++ b/hyperpars/for_results/ppo_mwt_UM1.yml @@ -0,0 +1,38 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_mwt' + n_observs: 1 + # + harvest_fn_name: "default" + upow: 1 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "mwt-UM1" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_mwt_UM2.yml b/hyperpars/for_results/ppo_mwt_UM2.yml new file mode 100644 index 0000000..8c2f501 --- /dev/null +++ b/hyperpars/for_results/ppo_mwt_UM2.yml @@ -0,0 +1,38 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_mwt' + n_observs: 1 + # + harvest_fn_name: "default" + upow: 0.6 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "mwt-UM2" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_mwt_UM3.yml b/hyperpars/for_results/ppo_mwt_UM3.yml new file mode 100644 index 0000000..840c266 --- /dev/null +++ b/hyperpars/for_results/ppo_mwt_UM3.yml @@ -0,0 +1,39 @@ +# algo +algo: "PPO" +total_timesteps: 4000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + gamma: 0.9999 + learning_rate: !!float 7.77e-05 + ent_coef: 0.00429 + clip_range: 0.1 + gae_lambda: 0.9 + max_grad_norm: 5 + vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + clip_range: 0.1 + +# env +env_id: "AsmEnv" +config: + observation_fn_id: 'observe_mwt' + n_observs: 1 + # + harvest_fn_name: "trophy" + n_trophy_ages: 10 + upow: 1 +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "mwt-UM3" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/ppo-asm-esc.yml b/hyperpars/ppo-asm-esc.yml new file mode 100644 index 0000000..bc82e5d --- /dev/null +++ b/hyperpars/ppo-asm-esc.yml @@ -0,0 +1,40 @@ +# algo +algo: "PPO" +total_timesteps: 10000000 +algo_config: + tensorboard_log: "../../../logs" + # + policy: 'MlpPolicy' + batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 + # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" + policy_kwargs: "dict(net_arch=[256, 128])" + use_sde: True + # clip_range: 0.1 + +# env +env_id: "AsmEnvEsc" +config: + observation_fn_id: 'observe_1o' + n_observs: 1 + harvest_fn_name: "trophy" + n_trophy_ages: 10 + # upow: 0.6 + # use_custom_harv_vul: True + # use_custom_surv_vul: True +n_envs: 12 + +# io +repo: "cboettig/rl-ecology" +save_path: "../saved_agents/results/" + +# misc +id: "results-trophy-nage-10-1obs-hyperpars1" +# id: "short-test" +additional_imports: ["torch"] \ No newline at end of file From f5fa42fb284aa280cb3a6d1f4555def1f706f1e8 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Wed, 29 May 2024 22:10:36 +0000 Subject: [PATCH 57/64] notebooks --- .../optimal-fixed-policy-cases-results.ipynb | 14919 ++++------------ notebooks/result_plots.ipynb | 279 +- 2 files changed, 3236 insertions(+), 11962 deletions(-) diff --git a/notebooks/optimal-fixed-policy-cases-results.ipynb b/notebooks/optimal-fixed-policy-cases-results.ipynb index 1d1e40f..eaea30c 100644 --- a/notebooks/optimal-fixed-policy-cases-results.ipynb +++ b/notebooks/optimal-fixed-policy-cases-results.ipynb @@ -1,15 +1,5 @@ { "cells": [ - { - "cell_type": "markdown", - "id": "7ff29091-615f-4d91-8198-20d8ae2fb197", - "metadata": {}, - "source": [ - "# Finding optimal fixed policies for several cases to explore in the paper\n", - "---\n", - "## Setup" - ] - }, { "cell_type": "code", "execution_count": 1, @@ -30,10 +20,20 @@ "from stable_baselines3.common.evaluation import evaluate_policy\n", "from stable_baselines3.common.monitor import Monitor\n", "\n", - "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, ConstAct, CautionaryRule\n", "from rl4fisheries.envs.asm_fns import get_r_devs, observe_total" ] }, + { + "cell_type": "markdown", + "id": "7ff29091-615f-4d91-8198-20d8ae2fb197", + "metadata": {}, + "source": [ + "# Finding optimal fixed policies for several cases to explore in the paper\n", + "---\n", + "## Setup" + ] + }, { "cell_type": "code", "execution_count": 2, @@ -83,7 +83,7 @@ "outputs": [], "source": [ "msy_space = [Real(0.001, 0.25, name='mortality')]\n", - "log_esc_space = [Real(-6, 2, name='log_escapement')]\n", + "esc_space = [Real(0, AsmEnv().bound / 5, name='escapement')]\n", "cr_space = [\n", " Real(-5, 2, name='log_radius'),\n", " Real(- np.pi/4.00001, np.pi/4.00001, name='theta'),\n", @@ -103,11 +103,10 @@ " return msy_obj\n", "\n", "def esc_obj_generator(config):\n", - " @use_named_args(log_esc_space)\n", + " @use_named_args(esc_space)\n", " def esc_obj(**x):\n", " eval_env = AsmEnv(config=config)\n", - " escapement = 10 ** x['log_escapement']\n", - " agent = ConstEsc(env=eval_env, escapement = escapement)\n", + " agent = ConstEsc(env=eval_env, escapement = x['escapement'])\n", " rews = eval_pol(\n", " policy=agent, \n", " env_cls=AsmEnv, config=config, \n", @@ -137,34 +136,45 @@ " return cr_obj" ] }, + { + "cell_type": "code", + "execution_count": 4, + "id": "240f1608-98aa-486c-b27e-6f018acfe896", + "metadata": {}, + "outputs": [], + "source": [ + "NCALLS = 40" + ] + }, { "cell_type": "markdown", - "id": "8226ea99-2cf1-494f-8335-365c036f43ac", + "id": "14cd665f-e859-41f7-b6f7-d14b16566bab", "metadata": {}, "source": [ - "## upow=0.6, non-trophy fishing" + "## upow=1, trophy fishing 10 age classes" ] }, { "cell_type": "code", - "execution_count": 4, - "id": "800575c8-7adf-4afb-9d1e-095148727fa0", + "execution_count": 5, + "id": "6e5b88dd-3725-48ea-b227-f6ca5357f189", "metadata": {}, "outputs": [], "source": [ - "CONFIG1 = {\n", - " \"upow\": 0.6\n", + "CONFIG3 = {\n", + " \"upow\": 1,\n", + " \"harvest_fn_name\": \"trophy\"\n", "}\n", "\n", - "cr_obj1 = cr_obj_generator(CONFIG1)\n", - "esc_obj1 = esc_obj_generator(CONFIG1)\n", - "msy_obj1 = msy_obj_generator(CONFIG1)" + "cr_obj3 = cr_obj_generator(CONFIG3)\n", + "esc_obj3 = esc_obj_generator(CONFIG3)\n", + "msy_obj3 = msy_obj_generator(CONFIG3)" ] }, { "cell_type": "code", - "execution_count": 5, - "id": "a9cc0d3d-66de-49fa-910a-7731bba0a8aa", + "execution_count": 9, + "id": "1b4333db-83ce-46c2-87cf-943da18b3370", "metadata": { "collapsed": true, "jupyter": { @@ -184,7 +194,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:06,448\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:11:25,183\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -192,9 +202,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 7.1426\n", - "Function value obtained: -50.2248\n", - "Current minimum: -50.2248\n", + "Time taken: 8.4516\n", + "Function value obtained: -3.1997\n", + "Current minimum: -3.1997\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -202,7 +212,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:13,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:11:33,630\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -210,9 +220,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 7.2930\n", - "Function value obtained: -100.0810\n", - "Current minimum: -100.0810\n", + "Time taken: 7.7052\n", + "Function value obtained: -6.5283\n", + "Current minimum: -6.5283\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -220,7 +230,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:20,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:11:41,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -228,9 +238,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 6.9121\n", - "Function value obtained: -40.3280\n", - "Current minimum: -100.0810\n", + "Time taken: 8.4599\n", + "Function value obtained: -22.9527\n", + "Current minimum: -22.9527\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -238,7 +248,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:27,708\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:11:49,814\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -246,9 +256,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 7.0030\n", - "Function value obtained: -75.6427\n", - "Current minimum: -100.0810\n", + "Time taken: 7.7430\n", + "Function value obtained: -26.7393\n", + "Current minimum: -26.7393\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -256,7 +266,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:34,746\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:11:57,583\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -264,9 +274,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 7.0246\n", - "Function value obtained: -13.8655\n", - "Current minimum: -100.0810\n", + "Time taken: 7.7411\n", + "Function value obtained: -6.7580\n", + "Current minimum: -26.7393\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -274,7 +284,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:41,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:12:05,291\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -282,9 +292,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 7.1452\n", - "Function value obtained: -23.8341\n", - "Current minimum: -100.0810\n", + "Time taken: 8.4607\n", + "Function value obtained: -0.0109\n", + "Current minimum: -26.7393\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -292,7 +302,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:48,925\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:12:13,770\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -300,9 +310,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 6.9714\n", - "Function value obtained: -133.4123\n", - "Current minimum: -133.4123\n", + "Time taken: 8.1181\n", + "Function value obtained: -4.8319\n", + "Current minimum: -26.7393\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -310,7 +320,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:55:55,992\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:12:21,893\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -318,9 +328,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 7.2094\n", - "Function value obtained: -44.7161\n", - "Current minimum: -133.4123\n", + "Time taken: 8.6239\n", + "Function value obtained: -1.9565\n", + "Current minimum: -26.7393\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -328,7 +338,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:03,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:12:30,602\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -336,9 +346,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 7.0324\n", - "Function value obtained: -10.0156\n", - "Current minimum: -133.4123\n", + "Time taken: 8.5311\n", + "Function value obtained: -0.5830\n", + "Current minimum: -26.7393\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -346,7 +356,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:10,134\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:12:39,051\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -354,9 +364,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 7.4595\n", - "Function value obtained: -0.0036\n", - "Current minimum: -133.4123\n", + "Time taken: 8.9081\n", + "Function value obtained: -16.4910\n", + "Current minimum: -26.7393\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -364,7 +374,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:17,575\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:12:47,965\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -372,9 +382,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 7.3179\n", - "Function value obtained: -0.0000\n", - "Current minimum: -133.4123\n", + "Time taken: 8.8131\n", + "Function value obtained: -27.9997\n", + "Current minimum: -27.9997\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -382,7 +392,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:24,887\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:12:56,768\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -390,9 +400,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 7.2691\n", - "Function value obtained: -131.0600\n", - "Current minimum: -133.4123\n", + "Time taken: 8.7463\n", + "Function value obtained: -28.4467\n", + "Current minimum: -28.4467\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -400,7 +410,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:33,250\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:13:05,517\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -408,9 +418,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7377\n", - "Function value obtained: -61.4294\n", - "Current minimum: -133.4123\n", + "Time taken: 8.7956\n", + "Function value obtained: -27.3375\n", + "Current minimum: -28.4467\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -418,7 +428,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:40,944\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:13:14,292\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -426,9 +436,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 7.4950\n", - "Function value obtained: -131.3133\n", - "Current minimum: -133.4123\n", + "Time taken: 8.7755\n", + "Function value obtained: -14.2261\n", + "Current minimum: -28.4467\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -436,7 +446,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:48,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:13:23,065\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -444,9 +454,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5838\n", - "Function value obtained: -135.3706\n", - "Current minimum: -135.3706\n", + "Time taken: 8.8205\n", + "Function value obtained: -28.2476\n", + "Current minimum: -28.4467\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -454,7 +464,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:56:56,022\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:13:31,916\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -462,9 +472,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6447\n", - "Function value obtained: -137.0071\n", - "Current minimum: -137.0071\n", + "Time taken: 9.0165\n", + "Function value obtained: -26.4324\n", + "Current minimum: -28.4467\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -472,7 +482,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:03,674\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:13:40,921\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -480,9 +490,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5230\n", - "Function value obtained: -138.9258\n", - "Current minimum: -138.9258\n", + "Time taken: 8.7226\n", + "Function value obtained: -0.0000\n", + "Current minimum: -28.4467\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -490,7 +500,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:11,201\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:13:49,679\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -498,9 +508,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5191\n", - "Function value obtained: -135.8094\n", - "Current minimum: -138.9258\n", + "Time taken: 8.7945\n", + "Function value obtained: -0.0000\n", + "Current minimum: -28.4467\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -508,7 +518,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:18,725\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:13:58,484\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -516,9 +526,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5404\n", - "Function value obtained: -132.4386\n", - "Current minimum: -138.9258\n", + "Time taken: 8.7617\n", + "Function value obtained: -29.7365\n", + "Current minimum: -29.7365\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -526,7 +536,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:26,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:14:07,223\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -534,9 +544,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7329\n", - "Function value obtained: -136.2971\n", - "Current minimum: -138.9258\n", + "Time taken: 8.8635\n", + "Function value obtained: -28.8264\n", + "Current minimum: -29.7365\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -544,7 +554,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:34,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:14:16,093\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -552,9 +562,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6322\n", - "Function value obtained: -140.0636\n", - "Current minimum: -140.0636\n", + "Time taken: 8.8558\n", + "Function value obtained: -30.5688\n", + "Current minimum: -30.5688\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -562,7 +572,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:41,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:14:24,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -570,9 +580,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 7.5808\n", - "Function value obtained: -141.1176\n", - "Current minimum: -141.1176\n", + "Time taken: 8.3566\n", + "Function value obtained: -31.3171\n", + "Current minimum: -31.3171\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -580,7 +590,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:49,269\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:14:33,327\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -588,9 +598,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6479\n", - "Function value obtained: -142.4183\n", - "Current minimum: -142.4183\n", + "Time taken: 8.0471\n", + "Function value obtained: -30.8064\n", + "Current minimum: -31.3171\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -598,7 +608,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:57:56,915\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:14:41,383\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -606,9 +616,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8256\n", - "Function value obtained: -138.9429\n", - "Current minimum: -142.4183\n", + "Time taken: 8.1063\n", + "Function value obtained: -21.6612\n", + "Current minimum: -31.3171\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -616,7 +626,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:04,712\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:14:49,515\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -624,9 +634,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8529\n", - "Function value obtained: -138.5246\n", - "Current minimum: -142.4183\n", + "Time taken: 8.9988\n", + "Function value obtained: -29.9731\n", + "Current minimum: -31.3171\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -634,7 +644,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:12,597\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:14:58,523\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -642,9 +652,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8736\n", - "Function value obtained: -131.4659\n", - "Current minimum: -142.4183\n", + "Time taken: 8.9511\n", + "Function value obtained: -29.6215\n", + "Current minimum: -31.3171\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -652,7 +662,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:20,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:15:07,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -660,9 +670,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7868\n", - "Function value obtained: -146.7316\n", - "Current minimum: -146.7316\n", + "Time taken: 9.1322\n", + "Function value obtained: -31.4150\n", + "Current minimum: -31.4150\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -670,7 +680,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:28,233\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:15:16,590\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -678,9 +688,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9675\n", - "Function value obtained: -149.3556\n", - "Current minimum: -149.3556\n", + "Time taken: 8.9694\n", + "Function value obtained: -31.1333\n", + "Current minimum: -31.4150\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -688,7 +698,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:36,231\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:15:25,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -696,9 +706,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7273\n", - "Function value obtained: -149.8641\n", - "Current minimum: -149.8641\n", + "Time taken: 8.9227\n", + "Function value obtained: -6.5397\n", + "Current minimum: -31.4150\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -706,7 +716,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:43,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:15:34,515\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -714,9 +724,9 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9885\n", - "Function value obtained: -148.2691\n", - "Current minimum: -149.8641\n", + "Time taken: 8.8802\n", + "Function value obtained: -31.7101\n", + "Current minimum: -31.7101\n", "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, @@ -724,7 +734,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:51,942\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:15:43,379\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -732,9 +742,9 @@ "output_type": "stream", "text": [ "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7775\n", - "Function value obtained: -145.5978\n", - "Current minimum: -149.8641\n", + "Time taken: 8.9249\n", + "Function value obtained: -31.6148\n", + "Current minimum: -31.7101\n", "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, @@ -742,7 +752,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:58:59,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:15:53,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -750,9 +760,9 @@ "output_type": "stream", "text": [ "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7742\n", - "Function value obtained: -145.9430\n", - "Current minimum: -149.8641\n", + "Time taken: 9.9819\n", + "Function value obtained: -31.3555\n", + "Current minimum: -31.7101\n", "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, @@ -760,7 +770,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:59:07,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:16:02,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -768,9 +778,9 @@ "output_type": "stream", "text": [ "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 7.6758\n", - "Function value obtained: -145.8356\n", - "Current minimum: -149.8641\n", + "Time taken: 8.7532\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.7101\n", "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, @@ -778,7 +788,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:59:15,208\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:16:11,055\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -786,9 +796,9 @@ "output_type": "stream", "text": [ "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0398\n", - "Function value obtained: -0.0000\n", - "Current minimum: -149.8641\n", + "Time taken: 8.9633\n", + "Function value obtained: -30.7369\n", + "Current minimum: -31.7101\n", "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, @@ -796,7 +806,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:59:23,245\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:16:20,017\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -804,9 +814,9 @@ "output_type": "stream", "text": [ "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8355\n", - "Function value obtained: -123.7036\n", - "Current minimum: -149.8641\n", + "Time taken: 8.9807\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.7101\n", "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, @@ -814,7 +824,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:59:31,113\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:16:28,992\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -822,9 +832,9 @@ "output_type": "stream", "text": [ "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9280\n", - "Function value obtained: -146.8933\n", - "Current minimum: -149.8641\n", + "Time taken: 8.9359\n", + "Function value obtained: -0.0000\n", + "Current minimum: -31.7101\n", "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, @@ -832,7 +842,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:59:40,058\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:16:37,929\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -840,9 +850,9 @@ "output_type": "stream", "text": [ "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6553\n", - "Function value obtained: -96.2864\n", - "Current minimum: -149.8641\n", + "Time taken: 9.0881\n", + "Function value obtained: -31.3828\n", + "Current minimum: -31.7101\n", "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, @@ -850,7 +860,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:59:47,710\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:16:47,050\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -858,9 +868,9 @@ "output_type": "stream", "text": [ "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9087\n", - "Function value obtained: -18.2684\n", - "Current minimum: -149.8641\n", + "Time taken: 9.0722\n", + "Function value obtained: -1.1221\n", + "Current minimum: -31.7101\n", "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, @@ -868,7 +878,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 17:59:55,578\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:16:56,131\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -876,9 +886,9 @@ "output_type": "stream", "text": [ "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8215\n", - "Function value obtained: -143.3425\n", - "Current minimum: -149.8641\n", + "Time taken: 10.1829\n", + "Function value obtained: -31.1595\n", + "Current minimum: -31.7101\n", "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, @@ -886,7 +896,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:00:03,438\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:17:06,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -894,2892 +904,2978 @@ "output_type": "stream", "text": [ "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9729\n", - "Function value obtained: -144.0208\n", - "Current minimum: -149.8641\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" + "Time taken: 9.1643\n", + "Function value obtained: -31.2598\n", + "Current minimum: -31.7101\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:00:11,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:17:15,484\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9140\n", - "Function value obtained: -59.0199\n", - "Current minimum: -149.8641\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 8.7507\n", + "Function value obtained: -2.5989\n", + "Current minimum: -2.5989\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:00:19,314\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:17:24,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 7.7575\n", - "Function value obtained: -0.0000\n", - "Current minimum: -149.8641\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 8.7705\n", + "Function value obtained: -13.7095\n", + "Current minimum: -13.7095\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:00:27,090\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:17:33,095\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1577\n", - "Function value obtained: -102.7227\n", - "Current minimum: -149.8641\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 8.8140\n", + "Function value obtained: -11.9370\n", + "Current minimum: -13.7095\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:00:36,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:17:41,861\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9665\n", - "Function value obtained: -146.7394\n", - "Current minimum: -149.8641\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 8.3590\n", + "Function value obtained: -6.7621\n", + "Current minimum: -13.7095\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:00:44,188\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:17:50,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9532\n", - "Function value obtained: -146.6516\n", - "Current minimum: -149.8641\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 8.8122\n", + "Function value obtained: -9.9579\n", + "Current minimum: -13.7095\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:00:53,184\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:17:59,042\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2294\n", - "Function value obtained: -148.3380\n", - "Current minimum: -149.8641\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 8.6047\n", + "Function value obtained: -0.0816\n", + "Current minimum: -13.7095\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:01,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:18:07,689\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0417\n", - "Function value obtained: -141.8872\n", - "Current minimum: -149.8641\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 8.8067\n", + "Function value obtained: -1.1403\n", + "Current minimum: -13.7095\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:09,451\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:18:16,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2552\n", - "Function value obtained: -148.2297\n", - "Current minimum: -149.8641\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 8.7715\n", + "Function value obtained: -12.6753\n", + "Current minimum: -13.7095\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:17,766\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:18:25,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0794\n", - "Function value obtained: -146.6327\n", - "Current minimum: -149.8641\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 8.7691\n", + "Function value obtained: -0.7091\n", + "Current minimum: -13.7095\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:25,818\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:18:34,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4322\n", - "Function value obtained: -145.1000\n", - "Current minimum: -149.8641\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 9.2388\n", + "Function value obtained: -1.5970\n", + "Current minimum: -13.7095\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:34,245\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:18:43,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8712\n", - "Function value obtained: -147.2085\n", - "Current minimum: -149.8641\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0674\n", + "Function value obtained: -13.7622\n", + "Current minimum: -13.7622\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:42,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:18:52,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 8.4857\n", - "Function value obtained: -146.0308\n", - "Current minimum: -149.8641\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6153\n", + "Function value obtained: -13.2632\n", + "Current minimum: -13.7622\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:50,642\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:19:01,000\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1465\n", - "Function value obtained: -143.2042\n", - "Current minimum: -149.8641\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0366\n", + "Function value obtained: -13.0581\n", + "Current minimum: -13.7622\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:01:58,789\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:19:10,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3069\n", - "Function value obtained: -147.6975\n", - "Current minimum: -149.8641\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6125\n", + "Function value obtained: -0.0604\n", + "Current minimum: -13.7622\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:02:07,078\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:19:19,610\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1248\n", - "Function value obtained: -146.0510\n", - "Current minimum: -149.8641\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3962\n", + "Function value obtained: -13.8986\n", + "Current minimum: -13.8986\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:02:15,255\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:19:29,061\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 7.8741\n", - "Function value obtained: -146.7015\n", - "Current minimum: -149.8641\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3479\n", + "Function value obtained: -13.3746\n", + "Current minimum: -13.8986\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:02:23,104\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:19:38,356\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 7.9997\n", - "Function value obtained: -147.0754\n", - "Current minimum: -149.8641\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6922\n", + "Function value obtained: -12.8879\n", + "Current minimum: -13.8986\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:02:31,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:19:47,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1482\n", - "Function value obtained: -142.8745\n", - "Current minimum: -149.8641\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1179\n", + "Function value obtained: -13.4850\n", + "Current minimum: -13.8986\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:02:39,233\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:19:56,195\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9888\n", - "Function value obtained: -151.0266\n", - "Current minimum: -151.0266\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0332\n", + "Function value obtained: -13.4547\n", + "Current minimum: -13.8986\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:02:48,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:20:05,227\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0642\n", - "Function value obtained: -149.0134\n", - "Current minimum: -151.0266\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0526\n", + "Function value obtained: -13.3495\n", + "Current minimum: -13.8986\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:02:56,321\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:20:14,258\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0512\n", - "Function value obtained: -149.8404\n", - "Current minimum: -151.0266\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0562\n", + "Function value obtained: -0.2710\n", + "Current minimum: -13.8986\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:03:04,355\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:20:23,357\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2602\n", - "Function value obtained: -147.3890\n", - "Current minimum: -151.0266\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2721\n", + "Function value obtained: -13.5180\n", + "Current minimum: -13.8986\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:03:12,642\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:20:32,636\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5360\n", - "Function value obtained: -144.6945\n", - "Current minimum: -151.0266\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2449\n", + "Function value obtained: -13.4055\n", + "Current minimum: -13.8986\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:03:21,182\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:20:41,911\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2329\n", - "Function value obtained: -146.6455\n", - "Current minimum: -151.0266\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0993\n", + "Function value obtained: -13.9822\n", + "Current minimum: -13.9822\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:03:29,392\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:20:50,937\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0400\n", - "Function value obtained: -146.3620\n", - "Current minimum: -151.0266\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0729\n", + "Function value obtained: -13.2498\n", + "Current minimum: -13.9822\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:03:38,446\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:21:00,020\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 8.0667\n", - "Function value obtained: -147.1161\n", - "Current minimum: -151.0266\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2779\n", + "Function value obtained: -13.4668\n", + "Current minimum: -13.9822\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:03:46,598\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:21:10,320\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2680\n", - "Function value obtained: -147.8922\n", - "Current minimum: -151.0266\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4320\n", + "Function value obtained: -13.4532\n", + "Current minimum: -13.9822\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:03:54,797\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:21:19,748\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0775\n", - "Function value obtained: -149.2322\n", - "Current minimum: -151.0266\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5455\n", + "Function value obtained: -13.1296\n", + "Current minimum: -13.9822\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:04:03,866\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:21:29,312\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1962\n", - "Function value obtained: -145.0572\n", - "Current minimum: -151.0266\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2624\n", + "Function value obtained: -13.3584\n", + "Current minimum: -13.9822\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:04:13,070\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:21:38,625\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 8.1596\n", - "Function value obtained: -143.8009\n", - "Current minimum: -151.0266\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1221\n", + "Function value obtained: -12.4933\n", + "Current minimum: -13.9822\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:04:21,253\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:21:48,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1386\n", - "Function value obtained: -146.0845\n", - "Current minimum: -151.0266\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1819\n", + "Function value obtained: -13.2568\n", + "Current minimum: -13.9822\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:04:30,346\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:21:57,916\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3585\n", - "Function value obtained: -145.9828\n", - "Current minimum: -151.0266\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7738\n", + "Function value obtained: -13.2592\n", + "Current minimum: -13.9822\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:04:38,749\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:22:06,642\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1646\n", - "Function value obtained: -146.7597\n", - "Current minimum: -151.0266\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4649\n", + "Function value obtained: -13.5029\n", + "Current minimum: -13.9822\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:04:47,936\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:22:16,166\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2258\n", - "Function value obtained: -147.4701\n", - "Current minimum: -151.0266\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1748\n", + "Function value obtained: -13.6450\n", + "Current minimum: -13.9822\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:04:56,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:22:25,332\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5693\n", - "Function value obtained: -145.4419\n", - "Current minimum: -151.0266\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2320\n", + "Function value obtained: -12.8053\n", + "Current minimum: -13.9822\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:05:04,728\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:22:34,628\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5831\n", - "Function value obtained: -147.1113\n", - "Current minimum: -151.0266\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 9.2320\n", + "Function value obtained: -12.8431\n", + "Current minimum: -13.9822\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:05:13,313\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:22:43,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5982\n", - "Function value obtained: -142.1284\n", - "Current minimum: -151.0266\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8065\n", + "Function value obtained: -13.9130\n", + "Current minimum: -13.9822\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:05:21,932\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:22:53,601\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2327\n", - "Function value obtained: -145.6544\n", - "Current minimum: -151.0266\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1979\n", + "Function value obtained: -13.3716\n", + "Current minimum: -13.9822\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:05:31,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:23:03,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3888\n", - "Function value obtained: -148.4968\n", - "Current minimum: -151.0266\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1941\n", + "Function value obtained: -13.5835\n", + "Current minimum: -13.9822\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:05:39,547\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:23:12,961\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3289\n", - "Function value obtained: -146.2288\n", - "Current minimum: -151.0266\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3120\n", + "Function value obtained: -12.9922\n", + "Current minimum: -13.9822\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:05:48,908\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:23:22,354\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2651\n", - "Function value obtained: -147.4892\n", - "Current minimum: -151.0266\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 9.2445\n", + "Function value obtained: -2.8234\n", + "Current minimum: -2.8234\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:05:58,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:23:31,648\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7033\n", - "Function value obtained: -144.5124\n", - "Current minimum: -151.0266\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 9.5994\n", + "Function value obtained: -3.8033\n", + "Current minimum: -3.8033\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:06:06,856\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:23:41,195\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5694\n", - "Function value obtained: -147.1889\n", - "Current minimum: -151.0266\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 9.6936\n", + "Function value obtained: -1.7693\n", + "Current minimum: -3.8033\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:06:15,440\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:23:50,848\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2216\n", - "Function value obtained: -145.0250\n", - "Current minimum: -151.0266\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 9.0173\n", + "Function value obtained: -10.7400\n", + "Current minimum: -10.7400\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:06:24,727\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:23:59,928\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 8.7992\n", - "Function value obtained: -146.3057\n", - "Current minimum: -151.0266\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 9.5029\n", + "Function value obtained: -4.5722\n", + "Current minimum: -10.7400\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:06:33,451\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:24:09,962\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2868\n", - "Function value obtained: -147.3213\n", - "Current minimum: -151.0266\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 9.8481\n", + "Function value obtained: -24.1916\n", + "Current minimum: -24.1916\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:06:42,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:24:19,279\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 8.6152\n", - "Function value obtained: -147.7221\n", - "Current minimum: -151.0266\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.0514\n", + "Function value obtained: -2.3565\n", + "Current minimum: -24.1916\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:06:51,381\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:24:28,437\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4433\n", - "Function value obtained: -145.4214\n", - "Current minimum: -151.0266\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 10.0270\n", + "Function value obtained: -6.1845\n", + "Current minimum: -24.1916\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:07:00,830\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:24:38,375\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3968\n", - "Function value obtained: -147.6219\n", - "Current minimum: -151.0266\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 9.3369\n", + "Function value obtained: -19.4562\n", + "Current minimum: -24.1916\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:07:10,196\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:24:47,634\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8338\n", - "Function value obtained: -147.6337\n", - "Current minimum: -151.0266\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 9.2591\n", + "Function value obtained: -23.4271\n", + "Current minimum: -24.1916\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:07:19,058\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:24:56,952\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9760\n", - "Function value obtained: -146.3274\n", - "Current minimum: -151.0266\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0426\n", + "Function value obtained: -1.3370\n", + "Current minimum: -24.1916\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:07:28,031\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:25:06,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3455\n", - "Function value obtained: -144.4779\n", - "Current minimum: -151.0266\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9825\n", + "Function value obtained: -24.1701\n", + "Current minimum: -24.1916\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:07:37,416\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:25:17,010\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4949\n", - "Function value obtained: -145.8979\n", - "Current minimum: -151.0266\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7463\n", + "Function value obtained: -23.5009\n", + "Current minimum: -24.1916\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:07:46,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:25:26,729\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3499\n", - "Function value obtained: -144.4805\n", - "Current minimum: -151.0266\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3757\n", + "Function value obtained: -24.3974\n", + "Current minimum: -24.3974\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:07:56,276\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:25:36,163\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6696\n", - "Function value obtained: -144.4206\n", - "Current minimum: -151.0266\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3587\n", + "Function value obtained: -23.9335\n", + "Current minimum: -24.3974\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:08:05,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:25:45,524\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4384\n", - "Function value obtained: -148.4113\n", - "Current minimum: -151.0266\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1368\n", + "Function value obtained: -24.2812\n", + "Current minimum: -24.3974\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:08:15,344\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:25:54,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3791\n", - "Function value obtained: -147.8722\n", - "Current minimum: -151.0266\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3667\n", + "Function value obtained: -23.7564\n", + "Current minimum: -24.3974\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:08:24,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:26:05,077\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5231\n", - "Function value obtained: -143.9188\n", - "Current minimum: -151.0266\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 9.3228\n", + "Function value obtained: -24.0885\n", + "Current minimum: -24.3974\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:08:34,269\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:26:14,409\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7191\n", - "Function value obtained: -146.1422\n", - "Current minimum: -151.0266\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4847\n", + "Function value obtained: -1.4339\n", + "Current minimum: -24.3974\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:08:44,000\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:26:23,892\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4630\n", - "Function value obtained: -146.4104\n", - "Current minimum: -151.0266\n", - "\n", - "--------------------\n", - "--------------------\n", - "Iteration No: 1 started. Evaluating function at random point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4311\n", + "Function value obtained: -22.5492\n", + "Current minimum: -24.3974\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:08:53,464\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:26:33,288\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 8.5263\n", - "Function value obtained: -3.1148\n", - "Current minimum: -3.1148\n", - "Iteration No: 2 started. Evaluating function at random point.\n" + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4446\n", + "Function value obtained: -24.1125\n", + "Current minimum: -24.3974\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:02,040\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:26:42,735\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 7.9127\n", - "Function value obtained: -100.4878\n", - "Current minimum: -100.4878\n", - "Iteration No: 3 started. Evaluating function at random point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8582\n", + "Function value obtained: -24.9897\n", + "Current minimum: -24.9897\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:09,954\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:26:52,597\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 7.9788\n", - "Function value obtained: -5.2865\n", - "Current minimum: -100.4878\n", - "Iteration No: 4 started. Evaluating function at random point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5239\n", + "Function value obtained: -24.3544\n", + "Current minimum: -24.9897\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:17,946\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:27:02,131\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 8.6109\n", - "Function value obtained: -43.6996\n", - "Current minimum: -100.4878\n", - "Iteration No: 5 started. Evaluating function at random point.\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5923\n", + "Function value obtained: -24.7287\n", + "Current minimum: -24.9897\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:26,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:27:11,732\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 8.5982\n", - "Function value obtained: -98.7542\n", - "Current minimum: -100.4878\n", - "Iteration No: 6 started. Evaluating function at random point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7160\n", + "Function value obtained: -25.5449\n", + "Current minimum: -25.5449\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:35,160\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:27:21,440\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 8.8102\n", - "Function value obtained: -7.9154\n", - "Current minimum: -100.4878\n", - "Iteration No: 7 started. Evaluating function at random point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0578\n", + "Function value obtained: -24.2661\n", + "Current minimum: -25.5449\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:43,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:27:31,518\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 7.8920\n", - "Function value obtained: -8.4514\n", - "Current minimum: -100.4878\n", - "Iteration No: 8 started. Evaluating function at random point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0957\n", + "Function value obtained: -23.8934\n", + "Current minimum: -25.5449\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:51,869\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:27:42,609\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 8.0056\n", - "Function value obtained: -32.3352\n", - "Current minimum: -100.4878\n", - "Iteration No: 9 started. Evaluating function at random point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4367\n", + "Function value obtained: -24.8825\n", + "Current minimum: -25.5449\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:09:59,867\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:27:53,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 8.5909\n", - "Function value obtained: -6.4695\n", - "Current minimum: -100.4878\n", - "Iteration No: 10 started. Evaluating function at random point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5060\n", + "Function value obtained: -25.2361\n", + "Current minimum: -25.5449\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:10:08,470\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:28:02,591\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 8.2068\n", - "Function value obtained: -81.0671\n", - "Current minimum: -100.4878\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4736\n", + "Function value obtained: -24.0366\n", + "Current minimum: -25.5449\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:10:16,686\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:28:12,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0693\n", - "Function value obtained: -109.5436\n", - "Current minimum: -109.5436\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4649\n", + "Function value obtained: -25.2479\n", + "Current minimum: -25.5449\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:10:25,768\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:28:22,539\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1009\n", - "Function value obtained: -110.8605\n", - "Current minimum: -110.8605\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1297\n", + "Function value obtained: -24.3826\n", + "Current minimum: -25.5449\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:10:34,908\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:28:32,723\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3745\n", - "Function value obtained: -110.1220\n", - "Current minimum: -110.8605\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4881\n", + "Function value obtained: -25.3757\n", + "Current minimum: -25.5449\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:10:44,216\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:28:42,184\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3563\n", - "Function value obtained: -2.7774\n", - "Current minimum: -110.8605\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4984\n", + "Function value obtained: -24.6935\n", + "Current minimum: -25.5449\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:10:53,620\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:28:51,719\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1550\n", - "Function value obtained: -109.1802\n", - "Current minimum: -110.8605\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5176\n", + "Function value obtained: -24.6567\n", + "Current minimum: -25.5449\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:11:02,813\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:29:01,227\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2128\n", - "Function value obtained: -110.1629\n", - "Current minimum: -110.8605\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9622\n", + "Function value obtained: -24.5985\n", + "Current minimum: -25.5449\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:11:11,965\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:29:11,197\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9456\n", - "Function value obtained: -108.1219\n", - "Current minimum: -110.8605\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6649\n", + "Function value obtained: -23.9832\n", + "Current minimum: -25.5449\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:11:20,930\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:29:20,844\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9004\n", - "Function value obtained: -109.3257\n", - "Current minimum: -110.8605\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2147\n", + "Function value obtained: -24.7094\n", + "Current minimum: -25.5449\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:11:29,817\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:29:31,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0523\n", - "Function value obtained: -110.5202\n", - "Current minimum: -110.8605\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0227\n", + "Function value obtained: -24.4611\n", + "Current minimum: -25.5449\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:11:38,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:29:41,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0686\n", - "Function value obtained: -108.1390\n", - "Current minimum: -110.8605\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7620\n", + "Function value obtained: -24.3058\n", + "Current minimum: -25.5449\n", + "CPU times: user 14min 51s, sys: 19min 45s, total: 34min 37s\n", + "Wall time: 18min 25s\n" ] - }, + } + ], + "source": [ + "%%time\n", + "\n", + "cr_gp3 = gp_minimize(cr_obj3, cr_space, n_calls = NCALLS, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "esc_gp3 = gp_minimize(esc_obj3, esc_space, n_calls = NCALLS, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "msy_gp3 = gp_minimize(msy_obj3, msy_space, n_calls = NCALLS, verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "bcd28c02-a8ff-4bd8-9df6-4b8981bdc8a2", + "metadata": {}, + "outputs": [], + "source": [ + "# plot_objective(esc_gp3) # looks good!" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "fb84909e-3816-493a-b888-cb394c6beed6", + "metadata": { + "scrolled": true + }, + "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "2024-05-22 18:11:47,961\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "\n", + "cr.: -31.71, [-0.2958516511636784, 0.4446492829229163, 0.08970008331564934] \n", + "esc: -13.98, [1.136737379993107]\n", + "msy: -25.54, [0.04672528295535901]\n", + "\n" ] + } + ], + "source": [ + "print(f\"\"\"\n", + "cr.: {cr_gp3.fun:.2f}, {cr_gp3.x} \n", + "esc: {esc_gp3.fun:.2f}, {esc_gp3.x}\n", + "msy: {msy_gp3.fun:.2f}, {msy_gp3.x}\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "8226ea99-2cf1-494f-8335-365c036f43ac", + "metadata": {}, + "source": [ + "## upow=0.6, non-trophy fishing" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "800575c8-7adf-4afb-9d1e-095148727fa0", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG1 = {\n", + " \"upow\": 0.6\n", + "}\n", + "\n", + "cr_obj1 = cr_obj_generator(CONFIG1)\n", + "esc_obj1 = esc_obj_generator(CONFIG1)\n", + "msy_obj1 = msy_obj_generator(CONFIG1)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "a9cc0d3d-66de-49fa-910a-7731bba0a8aa", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true }, + "scrolled": true + }, + "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 8.2281\n", - "Function value obtained: -111.1747\n", - "Current minimum: -111.1747\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" + "Iteration No: 1 started. Evaluating function at random point.\n", + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 2.5186\n", + "Function value obtained: -10.2335\n", + "Current minimum: -10.2335\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:11:56,224\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:31:13,215\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1119\n", - "Function value obtained: -110.5373\n", - "Current minimum: -111.1747\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 13.1620\n", + "Function value obtained: -24.2906\n", + "Current minimum: -24.2906\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:12:05,328\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:31:22,540\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0879\n", - "Function value obtained: -106.8115\n", - "Current minimum: -111.1747\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 9.4016\n", + "Function value obtained: -9.4887\n", + "Current minimum: -24.2906\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:12:14,407\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:31:32,044\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5319\n", - "Function value obtained: -108.8923\n", - "Current minimum: -111.1747\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 9.6123\n", + "Function value obtained: -136.8509\n", + "Current minimum: -136.8509\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:12:22,925\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:31:41,557\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 8.3492\n", - "Function value obtained: -110.6728\n", - "Current minimum: -111.1747\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.2846\n", + "Function value obtained: -8.0572\n", + "Current minimum: -136.8509\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:12:31,303\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:31:51,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 8.8975\n", - "Function value obtained: -106.7525\n", - "Current minimum: -111.1747\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 10.2745\n", + "Function value obtained: -133.5202\n", + "Current minimum: -136.8509\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:12:40,175\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:32:02,095\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1815\n", - "Function value obtained: -111.4289\n", - "Current minimum: -111.4289\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 9.7550\n", + "Function value obtained: -61.5989\n", + "Current minimum: -136.8509\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:12:49,393\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:32:11,799\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 8.5026\n", - "Function value obtained: -109.1199\n", - "Current minimum: -111.4289\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 9.1711\n", + "Function value obtained: -34.3222\n", + "Current minimum: -136.8509\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:12:57,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:32:21,037\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1353\n", - "Function value obtained: -107.6682\n", - "Current minimum: -111.4289\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 9.8201\n", + "Function value obtained: -110.6454\n", + "Current minimum: -136.8509\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:13:07,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:32:30,843\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 8.9578\n", - "Function value obtained: -112.1221\n", - "Current minimum: -112.1221\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.1430\n", + "Function value obtained: -100.4184\n", + "Current minimum: -136.8509\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:13:15,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:32:41,005\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1668\n", - "Function value obtained: -109.1704\n", - "Current minimum: -112.1221\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4935\n", + "Function value obtained: -0.0000\n", + "Current minimum: -136.8509\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:13:25,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:32:51,656\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4409\n", - "Function value obtained: -106.2691\n", - "Current minimum: -112.1221\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0505\n", + "Function value obtained: -128.8594\n", + "Current minimum: -136.8509\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:13:34,634\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:33:01,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1184\n", - "Function value obtained: -113.3081\n", - "Current minimum: -113.3081\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4755\n", + "Function value obtained: -139.4282\n", + "Current minimum: -139.4282\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:13:43,751\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:33:11,073\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2273\n", - "Function value obtained: -108.3703\n", - "Current minimum: -113.3081\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7018\n", + "Function value obtained: -138.0903\n", + "Current minimum: -139.4282\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:13:52,955\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:33:22,622\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1702\n", - "Function value obtained: -109.6190\n", - "Current minimum: -113.3081\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 13.6099\n", + "Function value obtained: -146.0186\n", + "Current minimum: -146.0186\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:14:02,106\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:33:33,336\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2777\n", - "Function value obtained: -109.8952\n", - "Current minimum: -113.3081\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9004\n", + "Function value obtained: -149.7063\n", + "Current minimum: -149.7063\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:14:11,452\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:33:44,268\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2352\n", - "Function value obtained: -111.6577\n", - "Current minimum: -113.3081\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6152\n", + "Function value obtained: -148.2921\n", + "Current minimum: -149.7063\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:14:20,673\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:33:53,845\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1924\n", - "Function value obtained: -109.6728\n", - "Current minimum: -113.3081\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.3368\n", + "Function value obtained: -0.0000\n", + "Current minimum: -149.7063\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:14:29,878\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:34:04,182\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1180\n", - "Function value obtained: -110.6084\n", - "Current minimum: -113.3081\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5271\n", + "Function value obtained: -149.1930\n", + "Current minimum: -149.7063\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:14:39,025\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:34:13,860\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3525\n", - "Function value obtained: -106.4812\n", - "Current minimum: -113.3081\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0119\n", + "Function value obtained: -150.1250\n", + "Current minimum: -150.1250\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:14:48,378\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:34:23,785\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1724\n", - "Function value obtained: -111.7625\n", - "Current minimum: -113.3081\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9642\n", + "Function value obtained: -150.0871\n", + "Current minimum: -150.1250\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:14:57,599\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:34:33,704\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4404\n", - "Function value obtained: -109.5424\n", - "Current minimum: -113.3081\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6005\n", + "Function value obtained: -146.4708\n", + "Current minimum: -150.1250\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:15:06,980\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:34:43,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2450\n", - "Function value obtained: -109.6388\n", - "Current minimum: -113.3081\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0960\n", + "Function value obtained: -146.3879\n", + "Current minimum: -150.1250\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:15:16,266\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:34:53,444\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3724\n", - "Function value obtained: -111.0515\n", - "Current minimum: -113.3081\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6909\n", + "Function value obtained: -145.2411\n", + "Current minimum: -150.1250\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:15:25,644\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:35:03,123\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3912\n", - "Function value obtained: -106.5638\n", - "Current minimum: -113.3081\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8158\n", + "Function value obtained: -126.8413\n", + "Current minimum: -150.1250\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:15:35,007\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:35:12,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3482\n", - "Function value obtained: -109.9455\n", - "Current minimum: -113.3081\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 9.9763\n", + "Function value obtained: -119.4992\n", + "Current minimum: -150.1250\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:15:44,332\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:35:22,948\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3430\n", - "Function value obtained: -110.1465\n", - "Current minimum: -113.3081\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0881\n", + "Function value obtained: -146.5926\n", + "Current minimum: -150.1250\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:15:53,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:35:33,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5137\n", - "Function value obtained: -108.0023\n", - "Current minimum: -113.3081\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4038\n", + "Function value obtained: -146.1494\n", + "Current minimum: -150.1250\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:16:03,240\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:35:43,507\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4510\n", - "Function value obtained: -109.0760\n", - "Current minimum: -113.3081\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6138\n", + "Function value obtained: -0.0000\n", + "Current minimum: -150.1250\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:16:13,660\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:35:54,054\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3444\n", - "Function value obtained: -109.7235\n", - "Current minimum: -113.3081\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2692\n", + "Function value obtained: -145.8938\n", + "Current minimum: -150.1250\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:16:23,019\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:36:04,369\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4180\n", - "Function value obtained: -108.2542\n", - "Current minimum: -113.3081\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0923\n", + "Function value obtained: -0.0000\n", + "Current minimum: -150.1250\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:16:32,429\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:36:14,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7001\n", - "Function value obtained: -112.5849\n", - "Current minimum: -113.3081\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8600\n", + "Function value obtained: -128.3500\n", + "Current minimum: -150.1250\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:16:42,145\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:36:24,311\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 9.0735\n", - "Function value obtained: -105.9648\n", - "Current minimum: -113.3081\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2425\n", + "Function value obtained: -143.7077\n", + "Current minimum: -150.1250\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:16:51,223\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:36:34,594\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3049\n", - "Function value obtained: -104.6931\n", - "Current minimum: -113.3081\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2733\n", + "Function value obtained: -0.0000\n", + "Current minimum: -150.1250\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:17:00,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:36:44,811\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1241\n", - "Function value obtained: -109.6909\n", - "Current minimum: -113.3081\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 10.4232\n", + "Function value obtained: -144.4944\n", + "Current minimum: -150.1250\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:17:10,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:36:55,236\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4527\n", - "Function value obtained: -107.6980\n", - "Current minimum: -113.3081\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0153\n", + "Function value obtained: -123.5602\n", + "Current minimum: -150.1250\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:17:20,127\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:37:05,332\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3407\n", - "Function value obtained: -109.3408\n", - "Current minimum: -113.3081\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9372\n", + "Function value obtained: -97.4335\n", + "Current minimum: -150.1250\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:17:29,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:37:17,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 9.1528\n", - "Function value obtained: -110.0202\n", - "Current minimum: -113.3081\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0363\n", + "Function value obtained: -132.8630\n", + "Current minimum: -150.1250\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:17:38,635\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:37:28,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 9.2478\n", - "Function value obtained: -108.3832\n", - "Current minimum: -113.3081\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8358\n", + "Function value obtained: -22.1397\n", + "Current minimum: -150.1250\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:17:47,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:37:41,194\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8375\n", - "Function value obtained: -108.9196\n", - "Current minimum: -113.3081\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2494\n", + "Function value obtained: -135.8170\n", + "Current minimum: -150.1250\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:17:57,733\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:37:51,412\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4495\n", - "Function value obtained: -109.2279\n", - "Current minimum: -113.3081\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 8.1063\n", + "Function value obtained: -2.3129\n", + "Current minimum: -2.3129\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:18:07,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:38:02,628\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5630\n", - "Function value obtained: -110.3166\n", - "Current minimum: -113.3081\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 12.9156\n", + "Function value obtained: -0.1582\n", + "Current minimum: -2.3129\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:18:17,760\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:38:12,422\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3607\n", - "Function value obtained: -112.1051\n", - "Current minimum: -113.3081\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 9.6119\n", + "Function value obtained: -0.1828\n", + "Current minimum: -2.3129\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:18:27,112\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:38:22,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5396\n", - "Function value obtained: -110.6268\n", - "Current minimum: -113.3081\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 9.5967\n", + "Function value obtained: -1.0969\n", + "Current minimum: -2.3129\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:18:36,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:38:31,740\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 9.3452\n", - "Function value obtained: -108.8991\n", - "Current minimum: -113.3081\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.6148\n", + "Function value obtained: -0.4385\n", + "Current minimum: -2.3129\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:18:45,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:38:42,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6449\n", - "Function value obtained: -107.6218\n", - "Current minimum: -113.3081\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 9.8437\n", + "Function value obtained: -0.4405\n", + "Current minimum: -2.3129\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:18:55,686\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:38:52,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5317\n", - "Function value obtained: -109.5969\n", - "Current minimum: -113.3081\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 10.9900\n", + "Function value obtained: -95.7194\n", + "Current minimum: -95.7194\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:19:05,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:39:03,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0276\n", - "Function value obtained: -107.6892\n", - "Current minimum: -113.3081\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 10.1492\n", + "Function value obtained: -33.4026\n", + "Current minimum: -95.7194\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:19:15,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:39:13,368\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6048\n", - "Function value obtained: -106.5261\n", - "Current minimum: -113.3081\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 10.2079\n", + "Function value obtained: -0.1904\n", + "Current minimum: -95.7194\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:19:24,860\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:39:23,486\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8810\n", - "Function value obtained: -105.0934\n", - "Current minimum: -113.3081\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.2832\n", + "Function value obtained: -0.0817\n", + "Current minimum: -95.7194\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:19:34,742\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:39:33,761\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5930\n", - "Function value obtained: -109.4023\n", - "Current minimum: -113.3081\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6636\n", + "Function value obtained: -107.4204\n", + "Current minimum: -107.4204\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:19:44,353\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:39:44,504\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 9.4152\n", - "Function value obtained: -111.5302\n", - "Current minimum: -113.3081\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 9.8027\n", + "Function value obtained: -2.6271\n", + "Current minimum: -107.4204\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:19:54,797\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:39:54,398\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8567\n", - "Function value obtained: -111.2069\n", - "Current minimum: -113.3081\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7279\n", + "Function value obtained: -106.1368\n", + "Current minimum: -107.4204\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:20:04,581\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:40:07,348\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8912\n", - "Function value obtained: -109.4680\n", - "Current minimum: -113.3081\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6205\n", + "Function value obtained: -103.0969\n", + "Current minimum: -107.4204\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:20:15,529\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:40:17,666\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8526\n", - "Function value obtained: -109.8335\n", - "Current minimum: -113.3081\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2602\n", + "Function value obtained: -109.3642\n", + "Current minimum: -109.3642\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:20:25,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:40:27,913\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7092\n", - "Function value obtained: -109.6025\n", - "Current minimum: -113.3081\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1735\n", + "Function value obtained: -109.4980\n", + "Current minimum: -109.4980\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:20:35,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:40:40,849\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6532\n", - "Function value obtained: -106.9613\n", - "Current minimum: -113.3081\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5517\n", + "Function value obtained: -104.1693\n", + "Current minimum: -109.4980\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:20:44,752\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:40:54,005\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9265\n", - "Function value obtained: -110.8921\n", - "Current minimum: -113.3081\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 14.4668\n", + "Function value obtained: -76.1099\n", + "Current minimum: -109.4980\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:20:54,637\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:41:04,130\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9273\n", - "Function value obtained: -106.4988\n", - "Current minimum: -113.3081\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8885\n", + "Function value obtained: -8.9258\n", + "Current minimum: -109.4980\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:21:05,626\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:41:15,020\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5533\n", - "Function value obtained: -106.9844\n", - "Current minimum: -113.3081\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5906\n", + "Function value obtained: -57.0804\n", + "Current minimum: -109.4980\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:21:15,137\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:41:25,603\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8004\n", - "Function value obtained: -112.6856\n", - "Current minimum: -113.3081\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" - ] + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5209\n", + "Function value obtained: -4.0593\n", + "Current minimum: -109.4980\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" + ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:21:24,993\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:41:36,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8939\n", - "Function value obtained: -106.2492\n", - "Current minimum: -113.3081\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9820\n", + "Function value obtained: -110.5932\n", + "Current minimum: -110.5932\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:21:34,909\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:41:49,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1197\n", - "Function value obtained: -110.9822\n", - "Current minimum: -113.3081\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 15.2155\n", + "Function value obtained: -108.4352\n", + "Current minimum: -110.5932\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:21:45,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:42:00,386\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9651\n", - "Function value obtained: -110.7704\n", - "Current minimum: -113.3081\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0849\n", + "Function value obtained: -18.3594\n", + "Current minimum: -110.5932\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:21:54,974\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:42:10,464\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1038\n", - "Function value obtained: -108.1396\n", - "Current minimum: -113.3081\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6497\n", + "Function value obtained: -107.9916\n", + "Current minimum: -110.5932\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:22:05,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:42:21,107\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6300\n", - "Function value obtained: -108.5247\n", - "Current minimum: -113.3081\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.1949\n", + "Function value obtained: -109.1506\n", + "Current minimum: -110.5932\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:22:14,775\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:42:31,331\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3881\n", - "Function value obtained: -108.0111\n", - "Current minimum: -113.3081\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 9.4586\n", + "Function value obtained: -106.9728\n", + "Current minimum: -110.5932\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:22:25,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:42:45,778\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0992\n", - "Function value obtained: -109.6469\n", - "Current minimum: -113.3081\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 15.8136\n", + "Function value obtained: -90.5518\n", + "Current minimum: -110.5932\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:22:35,200\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:42:56,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2008\n", - "Function value obtained: -110.2677\n", - "Current minimum: -113.3081\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9237\n", + "Function value obtained: -110.2055\n", + "Current minimum: -110.5932\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:22:45,367\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:43:07,587\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6477\n", - "Function value obtained: -110.3927\n", - "Current minimum: -113.3081\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0950\n", + "Function value obtained: -105.5405\n", + "Current minimum: -110.5932\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:22:55,052\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:43:18,655\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9332\n", - "Function value obtained: -110.6995\n", - "Current minimum: -113.3081\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8020\n", + "Function value obtained: -110.0656\n", + "Current minimum: -110.5932\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:23:05,017\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:43:29,440\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2438\n", - "Function value obtained: -108.0380\n", - "Current minimum: -113.3081\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5400\n", + "Function value obtained: -111.6948\n", + "Current minimum: -111.6948\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:23:15,240\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:43:41,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1308\n", - "Function value obtained: -109.5009\n", - "Current minimum: -113.3081\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0360\n", + "Function value obtained: -108.2348\n", + "Current minimum: -111.6948\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:23:25,355\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:43:52,051\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1166\n", - "Function value obtained: -109.2512\n", - "Current minimum: -113.3081\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 10.5317\n", + "Function value obtained: -45.0164\n", + "Current minimum: -111.6948\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:23:35,505\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:44:02,574\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0187\n", - "Function value obtained: -109.6719\n", - "Current minimum: -113.3081\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5652\n", + "Function value obtained: -111.1728\n", + "Current minimum: -111.6948\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:23:45,544\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:44:14,094\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2409\n", - "Function value obtained: -106.2462\n", - "Current minimum: -113.3081\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6510\n", + "Function value obtained: -107.1987\n", + "Current minimum: -111.6948\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:23:56,743\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:44:25,830\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2279\n", - "Function value obtained: -107.9563\n", - "Current minimum: -113.3081\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 14.5112\n", + "Function value obtained: -106.5132\n", + "Current minimum: -111.6948\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:24:06,960\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:44:40,315\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4646\n", - "Function value obtained: -110.8636\n", - "Current minimum: -113.3081\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 10.2311\n", + "Function value obtained: -107.8871\n", + "Current minimum: -111.6948\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:24:17,441\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:44:50,602\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4714\n", - "Function value obtained: -108.2392\n", - "Current minimum: -113.3081\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 9.6303\n", + "Function value obtained: -109.5860\n", + "Current minimum: -111.6948\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:24:27,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:45:00,900\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1199\n", - "Function value obtained: -108.1512\n", - "Current minimum: -113.3081\n", + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3379\n", + "Function value obtained: -108.2855\n", + "Current minimum: -111.6948\n", "\n", "--------------------\n", "--------------------\n", @@ -3790,7 +3886,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:24:38,053\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:45:12,488\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3798,9 +3894,9 @@ "output_type": "stream", "text": [ "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 10.0648\n", - "Function value obtained: -17.6242\n", - "Current minimum: -17.6242\n", + "Time taken: 9.9504\n", + "Function value obtained: -12.7125\n", + "Current minimum: -12.7125\n", "Iteration No: 2 started. Evaluating function at random point.\n" ] }, @@ -3808,7 +3904,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:24:48,179\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:45:22,516\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3816,9 +3912,9 @@ "output_type": "stream", "text": [ "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 9.2865\n", - "Function value obtained: -17.5461\n", - "Current minimum: -17.6242\n", + "Time taken: 10.1196\n", + "Function value obtained: -11.5940\n", + "Current minimum: -12.7125\n", "Iteration No: 3 started. Evaluating function at random point.\n" ] }, @@ -3826,7 +3922,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:24:57,430\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:45:32,658\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3834,9 +3930,9 @@ "output_type": "stream", "text": [ "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 9.5097\n", - "Function value obtained: -37.2531\n", - "Current minimum: -37.2531\n", + "Time taken: 11.3079\n", + "Function value obtained: -32.8462\n", + "Current minimum: -32.8462\n", "Iteration No: 4 started. Evaluating function at random point.\n" ] }, @@ -3844,7 +3940,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:25:06,971\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:45:43,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3852,9 +3948,9 @@ "output_type": "stream", "text": [ "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 9.5651\n", - "Function value obtained: -121.9332\n", - "Current minimum: -121.9332\n", + "Time taken: 10.5472\n", + "Function value obtained: -105.7970\n", + "Current minimum: -105.7970\n", "Iteration No: 5 started. Evaluating function at random point.\n" ] }, @@ -3862,7 +3958,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:25:16,650\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:45:54,508\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3870,9 +3966,9 @@ "output_type": "stream", "text": [ "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 9.6386\n", - "Function value obtained: -27.4291\n", - "Current minimum: -121.9332\n", + "Time taken: 10.7245\n", + "Function value obtained: -34.5301\n", + "Current minimum: -105.7970\n", "Iteration No: 6 started. Evaluating function at random point.\n" ] }, @@ -3880,7 +3976,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:25:26,197\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:46:06,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3888,9 +3984,9 @@ "output_type": "stream", "text": [ "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 9.8095\n", - "Function value obtained: -109.6144\n", - "Current minimum: -121.9332\n", + "Time taken: 11.1340\n", + "Function value obtained: -114.0690\n", + "Current minimum: -114.0690\n", "Iteration No: 7 started. Evaluating function at random point.\n" ] }, @@ -3898,7 +3994,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:25:36,047\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:46:18,214\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3906,9 +4002,9 @@ "output_type": "stream", "text": [ "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 9.4082\n", - "Function value obtained: -62.5131\n", - "Current minimum: -121.9332\n", + "Time taken: 12.7205\n", + "Function value obtained: -65.3205\n", + "Current minimum: -114.0690\n", "Iteration No: 8 started. Evaluating function at random point.\n" ] }, @@ -3916,7 +4012,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:25:45,425\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:46:29,106\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3924,9 +4020,9 @@ "output_type": "stream", "text": [ "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 9.6892\n", - "Function value obtained: -25.3334\n", - "Current minimum: -121.9332\n", + "Time taken: 10.3345\n", + "Function value obtained: -8.5293\n", + "Current minimum: -114.0690\n", "Iteration No: 9 started. Evaluating function at random point.\n" ] }, @@ -3934,7 +4030,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:25:55,097\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:46:39,441\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3942,9 +4038,9 @@ "output_type": "stream", "text": [ "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 9.8643\n", - "Function value obtained: -73.6274\n", - "Current minimum: -121.9332\n", + "Time taken: 11.5117\n", + "Function value obtained: -46.7897\n", + "Current minimum: -114.0690\n", "Iteration No: 10 started. Evaluating function at random point.\n" ] }, @@ -3952,7 +4048,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:26:04,977\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:46:51,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3960,9 +4056,9 @@ "output_type": "stream", "text": [ "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 9.6215\n", - "Function value obtained: -11.9736\n", - "Current minimum: -121.9332\n", + "Time taken: 12.3599\n", + "Function value obtained: -9.6972\n", + "Current minimum: -114.0690\n", "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, @@ -3970,7 +4066,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:26:14,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:47:03,272\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3978,9 +4074,9 @@ "output_type": "stream", "text": [ "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9584\n", - "Function value obtained: -120.6884\n", - "Current minimum: -121.9332\n", + "Time taken: 11.9172\n", + "Function value obtained: -124.8926\n", + "Current minimum: -124.8926\n", "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, @@ -3988,7 +4084,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:26:24,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:47:15,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -3996,9 +4092,9 @@ "output_type": "stream", "text": [ "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7566\n", - "Function value obtained: -121.4256\n", - "Current minimum: -121.9332\n", + "Time taken: 11.1081\n", + "Function value obtained: -121.5150\n", + "Current minimum: -124.8926\n", "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, @@ -4006,7 +4102,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:26:34,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:47:26,340\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4014,9 +4110,9 @@ "output_type": "stream", "text": [ "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7532\n", - "Function value obtained: -123.2711\n", - "Current minimum: -123.2711\n", + "Time taken: 11.3430\n", + "Function value obtained: -124.2937\n", + "Current minimum: -124.8926\n", "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, @@ -4024,7 +4120,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:26:44,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:47:37,695\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4032,9 +4128,9 @@ "output_type": "stream", "text": [ "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9136\n", - "Function value obtained: -119.5122\n", - "Current minimum: -123.2711\n", + "Time taken: 10.3123\n", + "Function value obtained: -122.6365\n", + "Current minimum: -124.8926\n", "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, @@ -4042,7 +4138,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:26:53,972\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:47:48,015\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4050,9 +4146,9 @@ "output_type": "stream", "text": [ "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8257\n", - "Function value obtained: -122.9657\n", - "Current minimum: -123.2711\n", + "Time taken: 9.0860\n", + "Function value obtained: -122.9173\n", + "Current minimum: -124.8926\n", "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, @@ -4060,7 +4156,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:27:03,845\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:48:01,378\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4068,9 +4164,9 @@ "output_type": "stream", "text": [ "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7340\n", - "Function value obtained: -125.2013\n", - "Current minimum: -125.2013\n", + "Time taken: 14.9621\n", + "Function value obtained: -122.6017\n", + "Current minimum: -124.8926\n", "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, @@ -4078,7 +4174,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:27:13,622\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:48:12,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4086,9 +4182,9 @@ "output_type": "stream", "text": [ "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8894\n", - "Function value obtained: -123.6988\n", - "Current minimum: -125.2013\n", + "Time taken: 9.1725\n", + "Function value obtained: -122.9132\n", + "Current minimum: -124.8926\n", "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, @@ -4096,7 +4192,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:27:23,424\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:48:25,745\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4104,9 +4200,9 @@ "output_type": "stream", "text": [ "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7726\n", - "Function value obtained: -124.8692\n", - "Current minimum: -125.2013\n", + "Time taken: 15.3665\n", + "Function value obtained: -122.0319\n", + "Current minimum: -124.8926\n", "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, @@ -4114,7 +4210,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:27:33,187\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:48:36,655\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4122,9 +4218,9 @@ "output_type": "stream", "text": [ "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6934\n", - "Function value obtained: -122.4800\n", - "Current minimum: -125.2013\n", + "Time taken: 10.3742\n", + "Function value obtained: -124.4707\n", + "Current minimum: -124.8926\n", "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, @@ -4132,7 +4228,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:27:42,968\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:48:47,009\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4140,9 +4236,9 @@ "output_type": "stream", "text": [ "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9766\n", - "Function value obtained: -124.7319\n", - "Current minimum: -125.2013\n", + "Time taken: 10.8190\n", + "Function value obtained: -127.3040\n", + "Current minimum: -127.3040\n", "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, @@ -4150,7 +4246,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:27:52,952\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:48:57,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4158,9 +4254,9 @@ "output_type": "stream", "text": [ "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1488\n", - "Function value obtained: -122.1076\n", - "Current minimum: -125.2013\n", + "Time taken: 11.0690\n", + "Function value obtained: -125.3524\n", + "Current minimum: -127.3040\n", "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, @@ -4168,7 +4264,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:28:03,055\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:49:08,958\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4176,9 +4272,9 @@ "output_type": "stream", "text": [ "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5009\n", - "Function value obtained: -8.8643\n", - "Current minimum: -125.2013\n", + "Time taken: 11.4150\n", + "Function value obtained: -122.2632\n", + "Current minimum: -127.3040\n", "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, @@ -4186,7 +4282,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:28:13,579\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:49:20,367\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4194,9 +4290,9 @@ "output_type": "stream", "text": [ "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7307\n", - "Function value obtained: -125.2242\n", - "Current minimum: -125.2242\n", + "Time taken: 9.2634\n", + "Function value obtained: -118.9392\n", + "Current minimum: -127.3040\n", "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, @@ -4204,7 +4300,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:28:23,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:49:35,237\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4212,9 +4308,9 @@ "output_type": "stream", "text": [ "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0418\n", - "Function value obtained: -123.6909\n", - "Current minimum: -125.2242\n", + "Time taken: 16.3303\n", + "Function value obtained: -120.4615\n", + "Current minimum: -127.3040\n", "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, @@ -4222,7 +4318,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:28:33,382\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:49:45,932\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4230,9 +4326,9 @@ "output_type": "stream", "text": [ "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9569\n", - "Function value obtained: -123.1854\n", - "Current minimum: -125.2242\n", + "Time taken: 9.2637\n", + "Function value obtained: -125.3327\n", + "Current minimum: -127.3040\n", "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, @@ -4240,7 +4336,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:28:43,348\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:50:00,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4248,9 +4344,9 @@ "output_type": "stream", "text": [ "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3169\n", - "Function value obtained: -124.0511\n", - "Current minimum: -125.2242\n", + "Time taken: 16.1308\n", + "Function value obtained: -122.4334\n", + "Current minimum: -127.3040\n", "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, @@ -4258,7 +4354,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:28:53,632\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:50:11,380\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4266,9 +4362,9 @@ "output_type": "stream", "text": [ "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8593\n", - "Function value obtained: -128.2024\n", - "Current minimum: -128.2024\n", + "Time taken: 10.9672\n", + "Function value obtained: -124.4445\n", + "Current minimum: -127.3040\n", "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, @@ -4276,7 +4372,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:29:03,496\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:50:22,281\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4284,9 +4380,9 @@ "output_type": "stream", "text": [ "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0411\n", - "Function value obtained: -125.8631\n", - "Current minimum: -128.2024\n", + "Time taken: 10.8215\n", + "Function value obtained: -125.8148\n", + "Current minimum: -127.3040\n", "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, @@ -4294,7 +4390,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:29:13,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:50:33,156\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4302,9 +4398,9 @@ "output_type": "stream", "text": [ "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6858\n", - "Function value obtained: -122.9178\n", - "Current minimum: -128.2024\n", + "Time taken: 10.2420\n", + "Function value obtained: -126.8922\n", + "Current minimum: -127.3040\n", "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, @@ -4312,7 +4408,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:29:23,342\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:50:44,559\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4320,9 +4416,9 @@ "output_type": "stream", "text": [ "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2887\n", - "Function value obtained: -119.8288\n", - "Current minimum: -128.2024\n", + "Time taken: 12.9081\n", + "Function value obtained: -122.7065\n", + "Current minimum: -127.3040\n", "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, @@ -4330,7 +4426,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:29:33,529\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:50:56,297\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4338,9 +4434,9 @@ "output_type": "stream", "text": [ "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8899\n", - "Function value obtained: -121.8036\n", - "Current minimum: -128.2024\n", + "Time taken: 10.7134\n", + "Function value obtained: -121.7051\n", + "Current minimum: -127.3040\n", "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, @@ -4348,7 +4444,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:29:43,426\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:51:07,071\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4356,9 +4452,9 @@ "output_type": "stream", "text": [ "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7102\n", - "Function value obtained: -124.2616\n", - "Current minimum: -128.2024\n", + "Time taken: 12.6497\n", + "Function value obtained: -123.0796\n", + "Current minimum: -127.3040\n", "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, @@ -4366,7 +4462,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:29:53,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:51:19,709\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4374,9 +4470,9 @@ "output_type": "stream", "text": [ "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 9.8853\n", - "Function value obtained: -122.2972\n", - "Current minimum: -128.2024\n", + "Time taken: 10.9608\n", + "Function value obtained: -121.6733\n", + "Current minimum: -127.3040\n", "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, @@ -4384,7 +4480,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:30:03,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:51:30,650\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4392,9 +4488,9 @@ "output_type": "stream", "text": [ "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 9.5582\n", - "Function value obtained: -125.4430\n", - "Current minimum: -128.2024\n", + "Time taken: 11.5136\n", + "Function value obtained: -125.8669\n", + "Current minimum: -127.3040\n", "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, @@ -4402,7 +4498,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:30:12,580\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:51:42,172\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4410,9 +4506,9 @@ "output_type": "stream", "text": [ "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9967\n", - "Function value obtained: -122.9375\n", - "Current minimum: -128.2024\n", + "Time taken: 12.1153\n", + "Function value obtained: -125.0135\n", + "Current minimum: -127.3040\n", "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, @@ -4420,7 +4516,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:30:22,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:51:54,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4428,9 +4524,9 @@ "output_type": "stream", "text": [ "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1173\n", - "Function value obtained: -122.7530\n", - "Current minimum: -128.2024\n", + "Time taken: 10.7594\n", + "Function value obtained: -122.2269\n", + "Current minimum: -127.3040\n", "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, @@ -4438,7 +4534,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:30:32,659\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:52:05,072\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4446,9 +4542,9 @@ "output_type": "stream", "text": [ "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1666\n", - "Function value obtained: -122.6971\n", - "Current minimum: -128.2024\n", + "Time taken: 11.0589\n", + "Function value obtained: -121.1210\n", + "Current minimum: -127.3040\n", "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, @@ -4456,7 +4552,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:30:42,879\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:52:16,158\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4464,9 +4560,9 @@ "output_type": "stream", "text": [ "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9232\n", - "Function value obtained: -124.7774\n", - "Current minimum: -128.2024\n", + "Time taken: 10.9067\n", + "Function value obtained: -124.1935\n", + "Current minimum: -127.3040\n", "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, @@ -4474,7 +4570,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:30:52,821\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:52:27,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4482,9 +4578,9 @@ "output_type": "stream", "text": [ "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8226\n", - "Function value obtained: -127.6329\n", - "Current minimum: -128.2024\n", + "Time taken: 12.0283\n", + "Function value obtained: -124.4234\n", + "Current minimum: -127.3040\n", "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, @@ -4492,7 +4588,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:31:03,602\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:52:39,144\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { @@ -4500,12573 +4596,3582 @@ "output_type": "stream", "text": [ "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7612\n", - "Function value obtained: -123.4035\n", - "Current minimum: -128.2024\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" + "Time taken: 16.1896\n", + "Function value obtained: -120.8218\n", + "Current minimum: -127.3040\n", + "CPU times: user 15min 14s, sys: 19min 8s, total: 34min 22s\n", + "Wall time: 21min 47s\n" ] - }, + } + ], + "source": [ + "%%time\n", + "\n", + "cr_gp1 = gp_minimize(cr_obj1, cr_space, n_calls = NCALLS, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "esc_gp1 = gp_minimize(esc_obj1, esc_space, n_calls = NCALLS, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "msy_gp1 = gp_minimize(msy_obj1, msy_space, n_calls = NCALLS, verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "7793ff2e-dc78-4900-ac38-431b5f5b201d", + "metadata": { + "scrolled": true + }, + "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "2024-05-22 18:31:13,377\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "\n", + "cr.: -150.13, [0.04342366137026321, -0.01139629999817482, 0.15086166706789647] \n", + "esc: -111.69, [0.46970553887262595]\n", + "msy: -127.30, [0.044227386748548404]\n", + "\n" ] + } + ], + "source": [ + "print(f\"\"\"\n", + "cr.: {cr_gp1.fun:.2f}, {cr_gp1.x} \n", + "esc: {esc_gp1.fun:.2f}, {esc_gp1.x}\n", + "msy: {msy_gp1.fun:.2f}, {msy_gp1.x}\n", + "\"\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "0b5f1e9f-d896-4e6c-835a-fd227adfec08", + "metadata": {}, + "outputs": [], + "source": [ + "# plot_objective(esc_gp3) # looks good too!" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "3ea1e603-3c5d-4fbd-aefb-f3531b99a8c3", + "metadata": {}, + "outputs": [], + "source": [ + "import ray\n", + "ray.shutdown()" + ] + }, + { + "cell_type": "markdown", + "id": "acc1d2fc-e50e-40bf-bbdb-35cff1a151b4", + "metadata": {}, + "source": [ + "## upow=1, non-trophy fishing" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "8983ccaa-ee40-4161-b691-d095b51a8d57", + "metadata": {}, + "outputs": [], + "source": [ + "CONFIG2 = {\n", + " \"upow\": 1\n", + "}\n", + "\n", + "cr_obj2 = cr_obj_generator(CONFIG2)\n", + "esc_obj2 = esc_obj_generator(CONFIG2)\n", + "msy_obj2 = msy_obj_generator(CONFIG2)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "883f8c50-0897-4c2f-92d2-0a6b683d638c", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true }, + "scrolled": true + }, + "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 9.7890\n", - "Function value obtained: -121.5322\n", - "Current minimum: -128.2024\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" + "Iteration No: 1 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:31:23,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:54:02,633\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0559\n", - "Function value obtained: -121.3806\n", - "Current minimum: -128.2024\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 10.9315\n", + "Function value obtained: -46.1007\n", + "Current minimum: -46.1007\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:31:33,229\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:54:13,534\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1698\n", - "Function value obtained: -119.6925\n", - "Current minimum: -128.2024\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 12.4076\n", + "Function value obtained: -55.6889\n", + "Current minimum: -55.6889\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:31:43,436\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:54:25,958\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5240\n", - "Function value obtained: -124.7613\n", - "Current minimum: -128.2024\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 11.9817\n", + "Function value obtained: -7.2042\n", + "Current minimum: -55.6889\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:31:54,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:54:37,865\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9256\n", - "Function value obtained: -123.7052\n", - "Current minimum: -128.2024\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 10.9808\n", + "Function value obtained: -68.2717\n", + "Current minimum: -68.2717\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:32:03,916\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:54:48,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3407\n", - "Function value obtained: -124.0130\n", - "Current minimum: -128.2024\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 11.5361\n", + "Function value obtained: -23.6040\n", + "Current minimum: -68.2717\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:32:14,256\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:55:00,456\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9008\n", - "Function value obtained: -122.6460\n", - "Current minimum: -128.2024\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 11.2388\n", + "Function value obtained: -44.7199\n", + "Current minimum: -68.2717\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:32:24,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:55:11,664\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0070\n", - "Function value obtained: -126.5892\n", - "Current minimum: -128.2024\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 10.6266\n", + "Function value obtained: -27.0222\n", + "Current minimum: -68.2717\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:32:34,182\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:55:22,236\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4073\n", - "Function value obtained: -123.4009\n", - "Current minimum: -128.2024\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 9.1898\n", + "Function value obtained: -56.4855\n", + "Current minimum: -68.2717\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:32:44,569\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:55:36,709\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3187\n", - "Function value obtained: -121.8074\n", - "Current minimum: -128.2024\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 15.8840\n", + "Function value obtained: -22.9363\n", + "Current minimum: -68.2717\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:32:54,921\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:55:47,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1348\n", - "Function value obtained: -124.6643\n", - "Current minimum: -128.2024\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 10.7103\n", + "Function value obtained: -37.8728\n", + "Current minimum: -68.2717\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:33:05,067\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:55:58,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7630\n", - "Function value obtained: -121.6280\n", - "Current minimum: -128.2024\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8545\n", + "Function value obtained: -63.3852\n", + "Current minimum: -68.2717\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:33:15,790\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:56:09,937\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4211\n", - "Function value obtained: -118.4107\n", - "Current minimum: -128.2024\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0440\n", + "Function value obtained: -63.8500\n", + "Current minimum: -68.2717\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:33:26,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:56:20,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4146\n", - "Function value obtained: -119.7914\n", - "Current minimum: -128.2024\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9483\n", + "Function value obtained: -0.0000\n", + "Current minimum: -68.2717\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:33:36,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:56:32,965\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0937\n", - "Function value obtained: -124.2212\n", - "Current minimum: -128.2024\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5362\n", + "Function value obtained: -68.2444\n", + "Current minimum: -68.2717\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:33:46,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:56:45,517\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6871\n", - "Function value obtained: -119.5058\n", - "Current minimum: -128.2024\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7372\n", + "Function value obtained: -53.1859\n", + "Current minimum: -68.2717\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:33:57,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:57:01,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1315\n", - "Function value obtained: -122.0702\n", - "Current minimum: -128.2024\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 18.1602\n", + "Function value obtained: -68.4843\n", + "Current minimum: -68.4843\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:34:07,583\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:57:13,385\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8392\n", - "Function value obtained: -123.9594\n", - "Current minimum: -128.2024\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6575\n", + "Function value obtained: -67.7700\n", + "Current minimum: -68.4843\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:34:18,473\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:57:25,037\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4072\n", - "Function value obtained: -122.4237\n", - "Current minimum: -128.2024\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6207\n", + "Function value obtained: -72.4312\n", + "Current minimum: -72.4312\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:34:28,876\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:57:39,417\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9652\n", - "Function value obtained: -122.4054\n", - "Current minimum: -128.2024\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1011\n", + "Function value obtained: -75.0044\n", + "Current minimum: -75.0044\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:34:38,793\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:57:50,811\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2593\n", - "Function value obtained: -122.6365\n", - "Current minimum: -128.2024\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2990\n", + "Function value obtained: -76.9663\n", + "Current minimum: -76.9663\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:34:49,065\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:58:03,117\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4918\n", - "Function value obtained: -124.1046\n", - "Current minimum: -128.2024\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7030\n", + "Function value obtained: -80.9614\n", + "Current minimum: -80.9614\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:34:59,572\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:58:15,829\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4629\n", - "Function value obtained: -122.7987\n", - "Current minimum: -128.2024\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5174\n", + "Function value obtained: -79.0889\n", + "Current minimum: -80.9614\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:35:10,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:58:27,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1056\n", - "Function value obtained: -125.7414\n", - "Current minimum: -128.2024\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2068\n", + "Function value obtained: -83.4642\n", + "Current minimum: -83.4642\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:35:20,151\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:58:38,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 10.0253\n", - "Function value obtained: -121.5002\n", - "Current minimum: -128.2024\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 11.0475\n", + "Function value obtained: -81.2126\n", + "Current minimum: -83.4642\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:35:30,192\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:58:49,576\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3737\n", - "Function value obtained: -125.4692\n", - "Current minimum: -128.2024\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 10.8559\n", + "Function value obtained: -80.0164\n", + "Current minimum: -83.4642\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:35:40,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:59:00,380\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2547\n", - "Function value obtained: -123.6835\n", - "Current minimum: -128.2024\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 10.0461\n", + "Function value obtained: -84.9349\n", + "Current minimum: -84.9349\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:35:50,806\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:59:15,995\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 9.9426\n", - "Function value obtained: -123.3200\n", - "Current minimum: -128.2024\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 18.1204\n", + "Function value obtained: -84.4203\n", + "Current minimum: -84.9349\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:36:00,780\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:59:28,617\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1437\n", - "Function value obtained: -121.6043\n", - "Current minimum: -128.2024\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3726\n", + "Function value obtained: -84.1797\n", + "Current minimum: -84.9349\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:36:10,949\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:59:41,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 9.6519\n", - "Function value obtained: -122.7514\n", - "Current minimum: -128.2024\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9805\n", + "Function value obtained: -82.1850\n", + "Current minimum: -84.9349\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:36:20,917\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 19:59:52,945\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1888\n", - "Function value obtained: -123.8053\n", - "Current minimum: -128.2024\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 11.4122\n", + "Function value obtained: -87.0540\n", + "Current minimum: -87.0540\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:36:31,791\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:00:04,400\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1231\n", - "Function value obtained: -125.6889\n", - "Current minimum: -128.2024\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 11.3546\n", + "Function value obtained: -86.0763\n", + "Current minimum: -87.0540\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:36:41,934\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:00:15,824\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8388\n", - "Function value obtained: -127.7351\n", - "Current minimum: -128.2024\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5947\n", + "Function value obtained: -88.0330\n", + "Current minimum: -88.0330\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:36:52,737\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:00:28,379\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6161\n", - "Function value obtained: -126.6123\n", - "Current minimum: -128.2024\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 11.9900\n", + "Function value obtained: -86.4731\n", + "Current minimum: -88.0330\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:37:03,475\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:00:40,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9526\n", - "Function value obtained: -122.3208\n", - "Current minimum: -128.2024\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1745\n", + "Function value obtained: -81.9750\n", + "Current minimum: -88.0330\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:37:14,356\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:00:52,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1861\n", - "Function value obtained: -125.1156\n", - "Current minimum: -128.2024\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8411\n", + "Function value obtained: -84.5548\n", + "Current minimum: -88.0330\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:37:25,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:01:04,433\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7912\n", - "Function value obtained: -123.1862\n", - "Current minimum: -128.2024\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0906\n", + "Function value obtained: -85.3201\n", + "Current minimum: -88.0330\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:37:35,349\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:01:16,577\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3672\n", - "Function value obtained: -124.2510\n", - "Current minimum: -128.2024\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5605\n", + "Function value obtained: -82.3599\n", + "Current minimum: -88.0330\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:37:45,683\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:01:28,016\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5638\n", - "Function value obtained: -125.1671\n", - "Current minimum: -128.2024\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 11.8971\n", + "Function value obtained: -8.3631\n", + "Current minimum: -88.0330\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:37:56,314\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:01:39,891\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8461\n", - "Function value obtained: -122.6942\n", - "Current minimum: -128.2024\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2061\n", + "Function value obtained: -89.8726\n", + "Current minimum: -89.8726\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:38:07,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:01:51,182\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7002\n", - "Function value obtained: -124.6567\n", - "Current minimum: -128.2024\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7599\n", + "Function value obtained: -83.7336\n", + "Current minimum: -89.8726\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:38:17,878\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:02:02,968\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9417\n", - "Function value obtained: -121.7817\n", - "Current minimum: -128.2024\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 10.4022\n", + "Function value obtained: -0.6225\n", + "Current minimum: -0.6225\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:38:28,778\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:02:15,208\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1075\n", - "Function value obtained: -120.5220\n", - "Current minimum: -128.2024\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 13.6815\n", + "Function value obtained: -56.1893\n", + "Current minimum: -56.1893\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:38:39,884\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:02:27,095\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1988\n", - "Function value obtained: -124.6843\n", - "Current minimum: -128.2024\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 11.0478\n", + "Function value obtained: -6.4770\n", + "Current minimum: -56.1893\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:38:51,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:02:38,165\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8785\n", - "Function value obtained: -120.8858\n", - "Current minimum: -128.2024\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 11.4460\n", + "Function value obtained: -9.1928\n", + "Current minimum: -56.1893\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:39:01,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:02:49,533\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6365\n", - "Function value obtained: -122.1166\n", - "Current minimum: -128.2024\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 10.4646\n", + "Function value obtained: -0.0905\n", + "Current minimum: -56.1893\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:39:12,602\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:02:59,971\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5517\n", - "Function value obtained: -123.6217\n", - "Current minimum: -128.2024\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 11.3627\n", + "Function value obtained: -1.4677\n", + "Current minimum: -56.1893\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:39:23,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:03:11,435\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5972\n", - "Function value obtained: -123.3492\n", - "Current minimum: -128.2024\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 10.7663\n", + "Function value obtained: -3.9063\n", + "Current minimum: -56.1893\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:39:33,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:03:22,212\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6335\n", - "Function value obtained: -126.9866\n", - "Current minimum: -128.2024\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 11.3977\n", + "Function value obtained: -4.3400\n", + "Current minimum: -56.1893\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:39:44,455\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:03:33,597\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4923\n", - "Function value obtained: -121.4247\n", - "Current minimum: -128.2024\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 14.0482\n", + "Function value obtained: -3.4998\n", + "Current minimum: -56.1893\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:39:54,864\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:03:47,676\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4419\n", - "Function value obtained: -123.7017\n", - "Current minimum: -128.2024\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 12.7551\n", + "Function value obtained: -0.1903\n", + "Current minimum: -56.1893\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:40:05,342\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:04:00,457\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5760\n", - "Function value obtained: -124.2262\n", - "Current minimum: -128.2024\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 10.9471\n", + "Function value obtained: -2.0055\n", + "Current minimum: -56.1893\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:40:15,925\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:04:12,562\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8301\n", - "Function value obtained: -125.8693\n", - "Current minimum: -128.2024\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 13.3978\n", + "Function value obtained: -56.1504\n", + "Current minimum: -56.1893\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:40:26,808\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:04:24,716\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9323\n", - "Function value obtained: -124.1342\n", - "Current minimum: -128.2024\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5740\n", + "Function value obtained: -53.6866\n", + "Current minimum: -56.1893\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:40:37,671\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:04:37,278\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8595\n", - "Function value obtained: -123.5373\n", - "Current minimum: -128.2024\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 9.5907\n", + "Function value obtained: -52.6332\n", + "Current minimum: -56.1893\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:40:48,569\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:04:52,580\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3228\n", - "Function value obtained: -120.4915\n", - "Current minimum: -128.2024\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 17.0366\n", + "Function value obtained: -61.1456\n", + "Current minimum: -61.1456\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:40:59,894\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:05:03,942\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4824\n", - "Function value obtained: -122.1312\n", - "Current minimum: -128.2024\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2087\n", + "Function value obtained: -61.5286\n", + "Current minimum: -61.5286\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:41:11,438\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:05:16,219\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7418\n", - "Function value obtained: -124.1009\n", - "Current minimum: -128.2024\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2079\n", + "Function value obtained: -68.9736\n", + "Current minimum: -68.9736\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:41:22,147\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:05:28,431\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5864\n", - "Function value obtained: -124.0157\n", - "Current minimum: -128.2024\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 9.7108\n", + "Function value obtained: -72.3998\n", + "Current minimum: -72.3998\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:41:33,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:05:44,973\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3634\n", - "Function value obtained: -121.5518\n", - "Current minimum: -128.2024\n", - "CPU times: user 1h 7min 7s, sys: 1h 8min 14s, total: 2h 15min 22s\n", - "Wall time: 46min 37s\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 19.3513\n", + "Function value obtained: -77.6997\n", + "Current minimum: -77.6997\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] - } - ], - "source": [ - "%%time\n", - "\n", - "cr_gp1 = gp_minimize(cr_obj1, cr_space, n_calls = 100, verbose=True)\n", - "print(\"\\n--------------------\"*2)\n", - "esc_gp1 = gp_minimize(esc_obj1, log_esc_space, n_calls = 100, verbose=True)\n", - "print(\"\\n--------------------\"*2)\n", - "msy_gp1 = gp_minimize(msy_obj1, msy_space, n_calls = 100, verbose=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "7793ff2e-dc78-4900-ac38-431b5f5b201d", - "metadata": { - "scrolled": true - }, - "outputs": [ + }, { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "\n", - "cr.: -151.03, [-0.32011410817668384, 0.03317549293764699, 0.09032157726866336] \n", - "esc: -113.31, [-0.39913963226889937]\n", - "msy: -128.20, [0.04076301400384111]\n", - "\n" + "2024-05-24 20:05:57,466\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] - } - ], - "source": [ - "print(f\"\"\"\n", - "cr.: {cr_gp1.fun:.2f}, {cr_gp1.x} \n", - "esc: {esc_gp1.fun:.2f}, {esc_gp1.x}\n", - "msy: {msy_gp1.fun:.2f}, {msy_gp1.x}\n", - "\"\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "3ea1e603-3c5d-4fbd-aefb-f3531b99a8c3", - "metadata": {}, - "outputs": [], - "source": [ - "import ray\n", - "ray.shutdown()" - ] - }, - { - "cell_type": "markdown", - "id": "acc1d2fc-e50e-40bf-bbdb-35cff1a151b4", - "metadata": {}, - "source": [ - "## upow=1, non-trophy fishing" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "8983ccaa-ee40-4161-b691-d095b51a8d57", - "metadata": {}, - "outputs": [], - "source": [ - "CONFIG2 = {\n", - " \"upow\": 1\n", - "}\n", - "\n", - "cr_obj2 = cr_obj_generator(CONFIG2)\n", - "esc_obj2 = esc_obj_generator(CONFIG2)\n", - "msy_obj2 = msy_obj_generator(CONFIG2)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "883f8c50-0897-4c2f-92d2-0a6b683d638c", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true }, - "scrolled": true - }, - "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5576\n", + "Function value obtained: -79.4983\n", + "Current minimum: -79.4983\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:41:45,178\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:06:09,070\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 10.0248\n", - "Function value obtained: -5.9724\n", - "Current minimum: -5.9724\n", - "Iteration No: 2 started. Evaluating function at random point.\n" + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 10.7931\n", + "Function value obtained: -79.8282\n", + "Current minimum: -79.8282\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:41:55,275\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:06:21,020\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 9.8660\n", - "Function value obtained: -15.9630\n", - "Current minimum: -15.9630\n", - "Iteration No: 3 started. Evaluating function at random point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 13.9501\n", + "Function value obtained: -79.5679\n", + "Current minimum: -79.8282\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:42:05,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:06:33,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 11.0314\n", - "Function value obtained: -47.8077\n", - "Current minimum: -47.8077\n", - "Iteration No: 4 started. Evaluating function at random point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1967\n", + "Function value obtained: -77.8531\n", + "Current minimum: -79.8282\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:42:16,166\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:06:45,016\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 9.9788\n", - "Function value obtained: -14.5273\n", - "Current minimum: -47.8077\n", - "Iteration No: 5 started. Evaluating function at random point.\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3307\n", + "Function value obtained: -79.1936\n", + "Current minimum: -79.8282\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:42:26,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:06:57,346\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 10.0417\n", - "Function value obtained: -24.0273\n", - "Current minimum: -47.8077\n", - "Iteration No: 6 started. Evaluating function at random point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6949\n", + "Function value obtained: -81.2194\n", + "Current minimum: -81.2194\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:42:37,146\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:07:09,979\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 11.2892\n", - "Function value obtained: -30.1455\n", - "Current minimum: -47.8077\n", - "Iteration No: 7 started. Evaluating function at random point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7577\n", + "Function value obtained: -81.1917\n", + "Current minimum: -81.2194\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:42:47,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:07:21,802\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 10.8662\n", - "Function value obtained: -48.4105\n", - "Current minimum: -48.4105\n", - "Iteration No: 8 started. Evaluating function at random point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5382\n", + "Function value obtained: -82.9986\n", + "Current minimum: -82.9986\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:42:58,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:07:33,398\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 10.1717\n", - "Function value obtained: -6.2904\n", - "Current minimum: -48.4105\n", - "Iteration No: 9 started. Evaluating function at random point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 12.3809\n", + "Function value obtained: -27.2346\n", + "Current minimum: -82.9986\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:43:08,532\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:07:45,744\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 10.5277\n", - "Function value obtained: -83.9195\n", - "Current minimum: -83.9195\n", - "Iteration No: 10 started. Evaluating function at random point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6984\n", + "Function value obtained: -81.5665\n", + "Current minimum: -82.9986\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:43:19,109\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:07:58,464\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 11.4224\n", - "Function value obtained: -50.3316\n", - "Current minimum: -83.9195\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8719\n", + "Function value obtained: -85.0717\n", + "Current minimum: -85.0717\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:43:30,426\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:08:11,321\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7138\n", - "Function value obtained: -36.0910\n", - "Current minimum: -83.9195\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7921\n", + "Function value obtained: -84.7287\n", + "Current minimum: -85.0717\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:43:41,191\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:08:25,161\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 10.1741\n", - "Function value obtained: -85.0784\n", - "Current minimum: -85.0784\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4475\n", + "Function value obtained: -81.3886\n", + "Current minimum: -85.0717\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:43:51,369\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:08:37,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6964\n", - "Function value obtained: -87.0753\n", - "Current minimum: -87.0753\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8823\n", + "Function value obtained: -82.8944\n", + "Current minimum: -85.0717\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:44:03,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:08:51,431\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6453\n", - "Function value obtained: -88.6745\n", - "Current minimum: -88.6745\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8321\n", + "Function value obtained: -81.4263\n", + "Current minimum: -85.0717\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:44:13,714\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:09:04,351\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2225\n", - "Function value obtained: -84.4254\n", - "Current minimum: -88.6745\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1246\n", + "Function value obtained: -85.4385\n", + "Current minimum: -85.4385\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:44:24,887\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:09:15,855\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2571\n", - "Function value obtained: -85.4937\n", - "Current minimum: -88.6745\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 16.1497\n", + "Function value obtained: -85.9286\n", + "Current minimum: -85.9286\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:44:36,131\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:09:31,603\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6072\n", - "Function value obtained: -83.8924\n", - "Current minimum: -88.6745\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 12.6213\n", + "Function value obtained: -83.1319\n", + "Current minimum: -85.9286\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:44:46,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:09:44,243\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5894\n", - "Function value obtained: -83.9604\n", - "Current minimum: -88.6745\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1807\n", + "Function value obtained: -83.0476\n", + "Current minimum: -85.9286\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:44:57,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:09:55,450\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7857\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2951\n", + "Function value obtained: -85.7664\n", + "Current minimum: -85.9286\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:45:08,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:10:07,703\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6423\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 11.1823\n", + "Function value obtained: -87.1824\n", + "Current minimum: -87.1824\n", + "\n", + "--------------------\n", + "--------------------\n", + "Iteration No: 1 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:45:19,863\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:10:19,304\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0857\n", - "Function value obtained: -82.2186\n", - "Current minimum: -88.6745\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 14.9840\n", + "Function value obtained: -4.0178\n", + "Current minimum: -4.0178\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:45:30,927\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:10:34,106\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6316\n", - "Function value obtained: -84.6019\n", - "Current minimum: -88.6745\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 14.4173\n", + "Function value obtained: -31.5501\n", + "Current minimum: -31.5501\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:45:41,622\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:10:48,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7340\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 10.2892\n", + "Function value obtained: -10.5194\n", + "Current minimum: -31.5501\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:45:52,222\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:10:59,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2421\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 15.6113\n", + "Function value obtained: -46.6685\n", + "Current minimum: -46.6685\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:46:02,519\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:11:14,522\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7104\n", - "Function value obtained: -84.9129\n", - "Current minimum: -88.6745\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 11.1985\n", + "Function value obtained: -5.0326\n", + "Current minimum: -46.6685\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:46:13,275\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:11:25,884\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 10.3763\n", - "Function value obtained: -26.1337\n", - "Current minimum: -88.6745\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 13.4766\n", + "Function value obtained: -10.7524\n", + "Current minimum: -46.6685\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:46:23,691\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:11:39,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4086\n", - "Function value obtained: -84.0755\n", - "Current minimum: -88.6745\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 13.7367\n", + "Function value obtained: -11.1720\n", + "Current minimum: -46.6685\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:46:34,090\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:11:52,717\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 10.4468\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 12.2371\n", + "Function value obtained: -14.1001\n", + "Current minimum: -46.6685\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:46:44,546\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:12:04,997\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9374\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 11.0415\n", + "Function value obtained: -10.1015\n", + "Current minimum: -46.6685\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:46:55,480\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:12:16,070\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0186\n", - "Function value obtained: -81.5174\n", - "Current minimum: -88.6745\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 12.5963\n", + "Function value obtained: -37.8382\n", + "Current minimum: -46.6685\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:47:07,522\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:12:28,540\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5568\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 11.7697\n", + "Function value obtained: -46.3341\n", + "Current minimum: -46.6685\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:47:18,142\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:12:40,375\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7516\n", - "Function value obtained: -77.7110\n", - "Current minimum: -88.6745\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4146\n", + "Function value obtained: -46.3095\n", + "Current minimum: -46.6685\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:47:28,809\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:12:52,699\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6104\n", - "Function value obtained: -83.2199\n", - "Current minimum: -88.6745\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 12.1300\n", + "Function value obtained: -48.3464\n", + "Current minimum: -48.3464\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:47:39,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:13:04,925\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8024\n", - "Function value obtained: -79.7576\n", - "Current minimum: -88.6745\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5492\n", + "Function value obtained: -18.2297\n", + "Current minimum: -48.3464\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:47:50,236\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:13:17,366\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5249\n", - "Function value obtained: -84.3443\n", - "Current minimum: -88.6745\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5743\n", + "Function value obtained: -47.2293\n", + "Current minimum: -48.3464\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:48:00,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:13:30,087\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 10.2010\n", - "Function value obtained: -77.2008\n", - "Current minimum: -88.6745\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2751\n", + "Function value obtained: -47.1796\n", + "Current minimum: -48.3464\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:48:11,990\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:13:41,685\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1662\n", - "Function value obtained: -80.2271\n", - "Current minimum: -88.6745\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 13.7624\n", + "Function value obtained: -46.5643\n", + "Current minimum: -48.3464\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:48:23,175\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:13:55,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6192\n", - "Function value obtained: -8.5063\n", - "Current minimum: -88.6745\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 18.5540\n", + "Function value obtained: -47.8431\n", + "Current minimum: -48.3464\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:48:34,800\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:14:13,694\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8566\n", - "Function value obtained: -3.7862\n", - "Current minimum: -88.6745\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 12.7725\n", + "Function value obtained: -49.1088\n", + "Current minimum: -49.1088\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:48:45,653\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:14:26,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4481\n", - "Function value obtained: -3.2344\n", - "Current minimum: -88.6745\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 12.9839\n", + "Function value obtained: -46.8100\n", + "Current minimum: -49.1088\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:48:57,103\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:14:39,553\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2688\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2575\n", + "Function value obtained: -46.5567\n", + "Current minimum: -49.1088\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:49:08,384\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:14:51,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7288\n", - "Function value obtained: -84.4595\n", - "Current minimum: -88.6745\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 18.1203\n", + "Function value obtained: -45.8535\n", + "Current minimum: -49.1088\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:49:19,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:15:08,816\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7063\n", - "Function value obtained: -78.4889\n", - "Current minimum: -88.6745\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 12.0476\n", + "Function value obtained: -45.2057\n", + "Current minimum: -49.1088\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:49:30,338\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:15:20,829\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0449\n", - "Function value obtained: -59.8454\n", - "Current minimum: -88.6745\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" - ] + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 12.2335\n", + "Function value obtained: -47.0513\n", + "Current minimum: -49.1088\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" + ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:49:41,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:15:33,165\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 10.6049\n", - "Function value obtained: -73.6175\n", - "Current minimum: -88.6745\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 11.2428\n", + "Function value obtained: -44.2587\n", + "Current minimum: -49.1088\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:49:53,728\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:15:47,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9459\n", - "Function value obtained: -84.3413\n", - "Current minimum: -88.6745\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 14.7874\n", + "Function value obtained: -47.1422\n", + "Current minimum: -49.1088\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:50:05,445\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:16:01,981\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2590\n", - "Function value obtained: -84.9368\n", - "Current minimum: -88.6745\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 13.8157\n", + "Function value obtained: -43.6144\n", + "Current minimum: -49.1088\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:50:16,757\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:16:13,383\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7428\n", - "Function value obtained: -0.0000\n", - "Current minimum: -88.6745\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 16.9669\n", + "Function value obtained: -45.1806\n", + "Current minimum: -49.1088\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:50:28,479\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:16:29,963\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9108\n", - "Function value obtained: -81.6157\n", - "Current minimum: -88.6745\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 10.6304\n", + "Function value obtained: -48.0437\n", + "Current minimum: -49.1088\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:50:39,385\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:16:41,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 10.5106\n", - "Function value obtained: -83.9244\n", - "Current minimum: -88.6745\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 16.3949\n", + "Function value obtained: -46.0012\n", + "Current minimum: -49.1088\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:50:51,558\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:16:57,018\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3788\n", - "Function value obtained: -89.3415\n", - "Current minimum: -89.3415\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 12.4767\n", + "Function value obtained: -46.8942\n", + "Current minimum: -49.1088\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:51:03,265\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:17:09,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 10.8804\n", - "Function value obtained: -86.8953\n", - "Current minimum: -89.3415\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 12.8090\n", + "Function value obtained: -46.1682\n", + "Current minimum: -49.1088\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:51:16,589\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:17:22,298\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2644\n", - "Function value obtained: -85.1525\n", - "Current minimum: -89.3415\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 13.1923\n", + "Function value obtained: -44.1171\n", + "Current minimum: -49.1088\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:51:29,555\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:17:35,447\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8981\n", - "Function value obtained: -86.7892\n", - "Current minimum: -89.3415\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 11.6060\n", + "Function value obtained: -45.3269\n", + "Current minimum: -49.1088\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:51:40,348\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:17:49,986\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1355\n", - "Function value obtained: -82.2920\n", - "Current minimum: -89.3415\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 14.6667\n", + "Function value obtained: -5.7484\n", + "Current minimum: -49.1088\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:51:51,494\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:18:01,705\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1931\n", - "Function value obtained: -86.9512\n", - "Current minimum: -89.3415\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 13.0461\n", + "Function value obtained: -44.9505\n", + "Current minimum: -49.1088\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:52:02,616\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:18:14,750\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2295\n", - "Function value obtained: -83.3199\n", - "Current minimum: -89.3415\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 12.5551\n", + "Function value obtained: -46.0894\n", + "Current minimum: -49.1088\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:52:13,891\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:18:27,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2705\n", - "Function value obtained: -83.8452\n", - "Current minimum: -89.3415\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 11.5106\n", + "Function value obtained: -46.7230\n", + "Current minimum: -49.1088\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:52:25,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:18:39,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1241\n", - "Function value obtained: -84.1858\n", - "Current minimum: -89.3415\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 15.1281\n", + "Function value obtained: -48.9271\n", + "Current minimum: -49.1088\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 18:52:36,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 20:18:55,034\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5172\n", - "Function value obtained: -90.2582\n", - "Current minimum: -90.2582\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:52:47,878\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 16.7738\n", + "Function value obtained: -45.6091\n", + "Current minimum: -49.1088\n", + "CPU times: user 15min 39s, sys: 21min 59s, total: 37min 38s\n", + "Wall time: 25min 7s\n" ] - }, + } + ], + "source": [ + "%%time\n", + "\n", + "cr_gp2 = gp_minimize(cr_obj2, cr_space, n_calls = NCALLS, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "esc_gp2 = gp_minimize(esc_obj2, esc_space, n_calls = NCALLS, verbose=True)\n", + "print(\"\\n--------------------\"*2)\n", + "msy_gp2 = gp_minimize(msy_obj2, msy_space, n_calls = NCALLS, verbose=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "8104f281-815e-4d55-86c3-9e22c4634149", + "metadata": {}, + "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5751\n", - "Function value obtained: -84.5137\n", - "Current minimum: -90.2582\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" + "\n", + "cr.: -89.87, [-0.011692399581430202, 0.5402896544155231, 0.22268980190474855] \n", + "esc: -87.18, [0.647851461853063]\n", + "msy: -49.11, [0.05164405247952578]\n", + "\n" ] - }, + } + ], + "source": [ + "print(f\"\"\"\n", + "cr.: {cr_gp2.fun:.2f}, {cr_gp2.x} \n", + "esc: {esc_gp2.fun:.2f}, {esc_gp2.x}\n", + "msy: {msy_gp2.fun:.2f}, {msy_gp2.x}\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "624c8d13-95cd-402c-a61f-18e497194db6", + "metadata": {}, + "source": [ + "## Saving models" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "9196be9f-11aa-4a9e-8e41-718bcec76091", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "path = \"../saved_agents/results/\"\n", + "\n", + "def to_cr(log_polar_params):\n", + " theta = log_polar_params[1]\n", + " radius = 10 ** log_polar_params[0]\n", + " x1 = np.sin(theta) * radius\n", + " x2 = np.cos(theta) * radius\n", + " y2 = log_polar_params[2]\n", + " return {'x1': x1, 'x2': x2, 'y2': y2}\n", + "\n", + "def to_esc(params):\n", + " return {'escapement': params[0]}\n", + "\n", + "def to_msy(params):\n", + " return {'msy': params[0]}\n", + "\n", + "#\n", + "eval_env1 = AsmEnv(config=CONFIG1)\n", + "eval_env2 = AsmEnv(config=CONFIG2)\n", + "eval_env3 = AsmEnv(config=CONFIG3)\n", + "\n", + "# \n", + "cr1_fname = \"cr_case_1.pkl\"\n", + "cr1 = CautionaryRule(env=eval_env1, **to_cr(cr_gp1.x))\n", + "dump(cr1, path+cr1_fname)\n", + "\n", + "esc1_fname = \"esc_case_1.pkl\"\n", + "esc1 = ConstEsc(env=eval_env1, **to_esc(esc_gp1.x))\n", + "dump(esc1, path+esc1_fname)\n", + "\n", + "msy1_fname = \"msy_case_1.pkl\"\n", + "msy1 = Msy(env=eval_env1, **to_msy(msy_gp1.x))\n", + "dump(msy1, path+msy1_fname)\n", + "\n", + "# \n", + "cr2_fname = \"cr_case_2.pkl\"\n", + "cr2 = CautionaryRule(env=eval_env2, **to_cr(cr_gp2.x))\n", + "dump(cr2, path+cr2_fname)\n", + "\n", + "esc2_fname = \"esc_case_2.pkl\"\n", + "esc2 = ConstEsc(env=eval_env2, **to_esc(esc_gp2.x))\n", + "dump(esc2, path+esc2_fname)\n", + "\n", + "msy2_fname = \"msy_case_2.pkl\"\n", + "msy2 = Msy(env=eval_env2, **to_msy(msy_gp2.x))\n", + "dump(msy2, path+msy2_fname)\n", + "\n", + "# \n", + "cr3_fname = \"cr_case_3.pkl\"\n", + "cr3 = CautionaryRule(env=eval_env3, **to_cr(cr_gp3.x))\n", + "dump(cr3, path+cr3_fname)\n", + "\n", + "esc3_fname = \"esc_case_3.pkl\"\n", + "esc3 = ConstEsc(env=eval_env3, **to_esc(esc_gp3.x))\n", + "dump(esc3, path+esc3_fname)\n", + "\n", + "msy3_fname = \"msy_case_3.pkl\"\n", + "msy3 = Msy(env=eval_env3, **to_msy(msy_gp3.x))\n", + "dump(msy3, path+msy3_fname)\n", + "\n", + "\n", + "## Didn't work for the gp objects since I used a fn generator :(\n", + "\n", + "# cr1_fname = \"cr_case_1.pkl\"\n", + "# dump(cr_gp1, path+cr1_fname)\n", + "\n", + "# esc1_fname = \"esc_case_1.pkl\"\n", + "# dump(esc_gp1, path+esc1_fname)\n", + "\n", + "# msy1_fname = \"msy_case_1.pkl\"\n", + "# dump(msy_gp1, path+msy1_fname)\n", + "\n", + "# #\n", + "\n", + "# cr2_fname = \"cr_case_2.pkl\"\n", + "# dump(cr_gp2, path+cr2_fname)\n", + "\n", + "# esc2_fname = \"esc_case_2.pkl\"\n", + "# dump(esc_gp2, path+esc2_fname)\n", + "\n", + "# msy2_fname = \"msy_case_2.pkl\"\n", + "# dump(msy_gp2, path+msy2_fname)\n", + "\n", + "# #\n", + "\n", + "# cr3_fname = \"cr_case_3.pkl\"\n", + "# dump(cr_gp3, path+cr3_fname)\n", + "\n", + "# esc3_fname = \"esc_case_3.pkl\"\n", + "# dump(esc_gp3, path+esc3_fname)\n", + "\n", + "# msy3_fname = \"msy_case_3.pkl\"\n", + "# dump(msy_gp3, path+msy3_fname)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4df50600-c069-4974-a7fc-6630e13e8057", + "metadata": {}, + "outputs": [], + "source": [ + "esc3" + ] + }, + { + "cell_type": "markdown", + "id": "a5f554a4-dd95-4bff-bf24-d60ef1215cf5", + "metadata": {}, + "source": [ + "## Objective plots" + ] + }, + { + "cell_type": "markdown", + "id": "491ddf8b-9039-49d8-b027-7b7e89046f4a", + "metadata": {}, + "source": [ + "### 1" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "aa3f2db6-75b0-47aa-8c08-8511faf6290b", + "metadata": {}, + "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:52:59,421\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0454\n", - "Function value obtained: -87.1609\n", - "Current minimum: -90.2582\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" - ] - }, + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(cr_gp1)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "80a9ca9b-2a4a-425f-b644-5559a096f825", + "metadata": {}, + "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:53:11,472\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2004\n", - "Function value obtained: -85.9424\n", - "Current minimum: -90.2582\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:53:22,894\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1849\n", - "Function value obtained: -86.5487\n", - "Current minimum: -90.2582\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:53:34,892\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2276\n", - "Function value obtained: -86.7229\n", - "Current minimum: -90.2582\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:53:47,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1792\n", - "Function value obtained: -85.0491\n", - "Current minimum: -90.2582\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:53:58,296\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5159\n", - "Function value obtained: -87.3644\n", - "Current minimum: -90.2582\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:54:09,842\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7261\n", - "Function value obtained: -85.6815\n", - "Current minimum: -90.2582\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:54:21,503\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6967\n", - "Function value obtained: -88.1699\n", - "Current minimum: -90.2582\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:54:33,364\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0597\n", - "Function value obtained: -86.3618\n", - "Current minimum: -90.2582\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:54:45,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8961\n", - "Function value obtained: -88.4223\n", - "Current minimum: -90.2582\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:54:57,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1781\n", - "Function value obtained: -83.5344\n", - "Current minimum: -90.2582\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:55:09,464\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4290\n", - "Function value obtained: -85.1680\n", - "Current minimum: -90.2582\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:55:20,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6026\n", - "Function value obtained: -84.1598\n", - "Current minimum: -90.2582\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:55:32,496\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6667\n", - "Function value obtained: -87.6237\n", - "Current minimum: -90.2582\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:55:44,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1505\n", - "Function value obtained: -88.6482\n", - "Current minimum: -90.2582\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:55:55,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0393\n", - "Function value obtained: -84.7632\n", - "Current minimum: -90.2582\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:56:07,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4367\n", - "Function value obtained: -86.1388\n", - "Current minimum: -90.2582\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:56:18,781\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3000\n", - "Function value obtained: -89.3813\n", - "Current minimum: -90.2582\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:56:31,117\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5670\n", - "Function value obtained: -88.2972\n", - "Current minimum: -90.2582\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:56:43,688\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5073\n", - "Function value obtained: -84.9865\n", - "Current minimum: -90.2582\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:56:56,137\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3699\n", - "Function value obtained: -86.3100\n", - "Current minimum: -90.2582\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:57:08,504\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7616\n", - "Function value obtained: -86.2788\n", - "Current minimum: -90.2582\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:57:20,255\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8280\n", - "Function value obtained: -88.0902\n", - "Current minimum: -90.2582\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:57:32,105\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1601\n", - "Function value obtained: -87.5204\n", - "Current minimum: -90.2582\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:57:43,326\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0240\n", - "Function value obtained: -88.1710\n", - "Current minimum: -90.2582\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:57:55,334\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7394\n", - "Function value obtained: -87.2143\n", - "Current minimum: -90.2582\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:58:07,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6356\n", - "Function value obtained: -84.6836\n", - "Current minimum: -90.2582\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:58:19,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6862\n", - "Function value obtained: -85.0274\n", - "Current minimum: -90.2582\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:58:32,391\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 11.2858\n", - "Function value obtained: -85.5836\n", - "Current minimum: -90.2582\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:58:45,944\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1340\n", - "Function value obtained: -88.2977\n", - "Current minimum: -90.2582\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:58:57,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0673\n", - "Function value obtained: -82.4661\n", - "Current minimum: -90.2582\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:59:09,963\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9388\n", - "Function value obtained: -84.0442\n", - "Current minimum: -90.2582\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:59:21,924\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0997\n", - "Function value obtained: -86.7391\n", - "Current minimum: -90.2582\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:59:33,991\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4722\n", - "Function value obtained: -85.9318\n", - "Current minimum: -90.2582\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:59:46,448\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4782\n", - "Function value obtained: -85.0170\n", - "Current minimum: -90.2582\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 18:59:58,931\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8382\n", - "Function value obtained: -86.4555\n", - "Current minimum: -90.2582\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:00:10,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5420\n", - "Function value obtained: -83.6674\n", - "Current minimum: -90.2582\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:00:23,435\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3492\n", - "Function value obtained: -85.2587\n", - "Current minimum: -90.2582\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:00:35,743\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4814\n", - "Function value obtained: -85.7160\n", - "Current minimum: -90.2582\n", - "\n", - "--------------------\n", - "--------------------\n", - "Iteration No: 1 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:00:48,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 12.0917\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 2 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:01:00,304\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 10.5236\n", - "Function value obtained: -21.3872\n", - "Current minimum: -21.3872\n", - "Iteration No: 3 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:01:10,838\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 11.3990\n", - "Function value obtained: -61.4340\n", - "Current minimum: -61.4340\n", - "Iteration No: 4 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:01:23,183\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 11.6861\n", - "Function value obtained: -30.5749\n", - "Current minimum: -61.4340\n", - "Iteration No: 5 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:01:35,561\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 12.9329\n", - "Function value obtained: -3.9297\n", - "Current minimum: -61.4340\n", - "Iteration No: 6 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:01:46,889\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 11.7872\n", - "Function value obtained: -10.5661\n", - "Current minimum: -61.4340\n", - "Iteration No: 7 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:01:58,647\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 10.6260\n", - "Function value obtained: -1.9804\n", - "Current minimum: -61.4340\n", - "Iteration No: 8 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:02:11,346\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 12.8230\n", - "Function value obtained: -5.2969\n", - "Current minimum: -61.4340\n", - "Iteration No: 9 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:02:22,286\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 12.5219\n", - "Function value obtained: -1.9594\n", - "Current minimum: -61.4340\n", - "Iteration No: 10 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:02:34,675\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 11.8681\n", - "Function value obtained: -79.6325\n", - "Current minimum: -79.6325\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:02:46,579\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1325\n", - "Function value obtained: -82.9123\n", - "Current minimum: -82.9123\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:02:57,657\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0311\n", - "Function value obtained: -84.5376\n", - "Current minimum: -84.5376\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:03:08,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7218\n", - "Function value obtained: -84.4892\n", - "Current minimum: -84.5376\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:03:20,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4979\n", - "Function value obtained: -1.9761\n", - "Current minimum: -84.5376\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:03:31,971\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0924\n", - "Function value obtained: -83.5743\n", - "Current minimum: -84.5376\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:03:44,020\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8763\n", - "Function value obtained: -84.5529\n", - "Current minimum: -84.5529\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:03:55,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3417\n", - "Function value obtained: -81.7204\n", - "Current minimum: -84.5529\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:04:07,197\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 10.9443\n", - "Function value obtained: -85.3490\n", - "Current minimum: -85.3490\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:04:18,234\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9346\n", - "Function value obtained: -84.3531\n", - "Current minimum: -85.3490\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:04:30,141\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0929\n", - "Function value obtained: -85.9082\n", - "Current minimum: -85.9082\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:04:42,457\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5980\n", - "Function value obtained: -86.7586\n", - "Current minimum: -86.7586\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:04:54,888\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2158\n", - "Function value obtained: -83.0358\n", - "Current minimum: -86.7586\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:05:07,119\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7629\n", - "Function value obtained: -84.8722\n", - "Current minimum: -86.7586\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:05:18,868\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3968\n", - "Function value obtained: -85.8878\n", - "Current minimum: -86.7586\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:05:30,356\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9633\n", - "Function value obtained: -84.8926\n", - "Current minimum: -86.7586\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:05:42,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4213\n", - "Function value obtained: -86.3130\n", - "Current minimum: -86.7586\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:05:53,606\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4698\n", - "Function value obtained: -87.6020\n", - "Current minimum: -87.6020\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:06:05,189\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1861\n", - "Function value obtained: -83.4369\n", - "Current minimum: -87.6020\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:06:17,374\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0788\n", - "Function value obtained: -85.9242\n", - "Current minimum: -87.6020\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:06:30,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8591\n", - "Function value obtained: -85.3490\n", - "Current minimum: -87.6020\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:06:42,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8357\n", - "Function value obtained: -84.9675\n", - "Current minimum: -87.6020\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:06:55,145\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 11.7458\n", - "Function value obtained: -87.6662\n", - "Current minimum: -87.6662\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:07:06,847\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4007\n", - "Function value obtained: -84.6370\n", - "Current minimum: -87.6662\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:07:19,287\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1146\n", - "Function value obtained: -86.4096\n", - "Current minimum: -87.6662\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:07:32,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 11.0060\n", - "Function value obtained: -85.3912\n", - "Current minimum: -87.6662\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:07:44,521\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9291\n", - "Function value obtained: -85.0626\n", - "Current minimum: -87.6662\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:07:57,219\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 10.7253\n", - "Function value obtained: -86.2307\n", - "Current minimum: -87.6662\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:08:11,201\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4998\n", - "Function value obtained: -86.3373\n", - "Current minimum: -87.6662\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:08:23,513\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4992\n", - "Function value obtained: -87.0573\n", - "Current minimum: -87.6662\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:08:36,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6326\n", - "Function value obtained: -85.6411\n", - "Current minimum: -87.6662\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:08:48,911\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5245\n", - "Function value obtained: -82.7747\n", - "Current minimum: -87.6662\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:09:01,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1244\n", - "Function value obtained: -88.5028\n", - "Current minimum: -88.5028\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:09:14,326\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 11.6625\n", - "Function value obtained: -86.1438\n", - "Current minimum: -88.5028\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:09:26,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1965\n", - "Function value obtained: -84.6050\n", - "Current minimum: -88.5028\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:09:38,313\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1221\n", - "Function value obtained: -84.3418\n", - "Current minimum: -88.5028\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:09:51,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0093\n", - "Function value obtained: -84.4929\n", - "Current minimum: -88.5028\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:10:04,357\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 11.9171\n", - "Function value obtained: -85.1945\n", - "Current minimum: -88.5028\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:10:16,226\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3140\n", - "Function value obtained: -81.8894\n", - "Current minimum: -88.5028\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:10:30,569\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4836\n", - "Function value obtained: -86.0075\n", - "Current minimum: -88.5028\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:10:43,112\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4976\n", - "Function value obtained: -85.6050\n", - "Current minimum: -88.5028\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:10:55,651\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8227\n", - "Function value obtained: -86.3416\n", - "Current minimum: -88.5028\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:11:08,439\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3011\n", - "Function value obtained: -86.3921\n", - "Current minimum: -88.5028\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:11:20,770\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 11.3639\n", - "Function value obtained: -86.7170\n", - "Current minimum: -88.5028\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:11:32,038\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2249\n", - "Function value obtained: -87.9136\n", - "Current minimum: -88.5028\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:11:44,400\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0663\n", - "Function value obtained: -83.7074\n", - "Current minimum: -88.5028\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:11:57,419\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1646\n", - "Function value obtained: -83.9611\n", - "Current minimum: -88.5028\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:12:09,545\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2143\n", - "Function value obtained: -86.3481\n", - "Current minimum: -88.5028\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:12:23,844\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5183\n", - "Function value obtained: -87.8012\n", - "Current minimum: -88.5028\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:12:38,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8534\n", - "Function value obtained: -86.6255\n", - "Current minimum: -88.5028\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:12:52,214\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5267\n", - "Function value obtained: -85.6845\n", - "Current minimum: -88.5028\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:13:07,135\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4344\n", - "Function value obtained: -86.8237\n", - "Current minimum: -88.5028\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:13:19,260\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8941\n", - "Function value obtained: -83.2762\n", - "Current minimum: -88.5028\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:13:32,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5444\n", - "Function value obtained: -84.9381\n", - "Current minimum: -88.5028\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:13:44,694\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4875\n", - "Function value obtained: -84.4635\n", - "Current minimum: -88.5028\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:13:58,249\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3168\n", - "Function value obtained: -86.0736\n", - "Current minimum: -88.5028\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:14:11,501\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2999\n", - "Function value obtained: -86.1583\n", - "Current minimum: -88.5028\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:14:23,715\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5058\n", - "Function value obtained: -85.1833\n", - "Current minimum: -88.5028\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:14:38,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6764\n", - "Function value obtained: -88.9795\n", - "Current minimum: -88.9795\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:14:50,942\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2883\n", - "Function value obtained: -85.7122\n", - "Current minimum: -88.9795\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:15:04,292\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7493\n", - "Function value obtained: -83.0249\n", - "Current minimum: -88.9795\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:15:16,964\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9523\n", - "Function value obtained: -84.1864\n", - "Current minimum: -88.9795\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:15:31,018\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9677\n", - "Function value obtained: -85.4601\n", - "Current minimum: -88.9795\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:15:42,980\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5693\n", - "Function value obtained: -86.4198\n", - "Current minimum: -88.9795\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:15:55,522\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2483\n", - "Function value obtained: -83.5641\n", - "Current minimum: -88.9795\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:16:07,763\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7245\n", - "Function value obtained: -83.6426\n", - "Current minimum: -88.9795\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:16:20,526\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 11.1246\n", - "Function value obtained: -85.6648\n", - "Current minimum: -88.9795\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:16:34,656\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8312\n", - "Function value obtained: -83.9867\n", - "Current minimum: -88.9795\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:16:48,080\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4259\n", - "Function value obtained: -82.5118\n", - "Current minimum: -88.9795\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:17:02,821\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2356\n", - "Function value obtained: -86.3403\n", - "Current minimum: -88.9795\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:17:15,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 13.1240\n", - "Function value obtained: -83.6473\n", - "Current minimum: -88.9795\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:17:28,295\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2001\n", - "Function value obtained: -83.6651\n", - "Current minimum: -88.9795\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:17:41,491\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4735\n", - "Function value obtained: -88.4078\n", - "Current minimum: -88.9795\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:17:55,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2596\n", - "Function value obtained: -84.0268\n", - "Current minimum: -88.9795\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:18:07,199\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9511\n", - "Function value obtained: -83.4724\n", - "Current minimum: -88.9795\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:18:20,170\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0713\n", - "Function value obtained: -84.1173\n", - "Current minimum: -88.9795\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:18:33,271\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4891\n", - "Function value obtained: -83.2998\n", - "Current minimum: -88.9795\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:18:46,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1511\n", - "Function value obtained: -85.3088\n", - "Current minimum: -88.9795\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:18:59,004\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9693\n", - "Function value obtained: -84.9342\n", - "Current minimum: -88.9795\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:19:12,964\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7960\n", - "Function value obtained: -85.0579\n", - "Current minimum: -88.9795\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:19:25,709\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2893\n", - "Function value obtained: -85.8128\n", - "Current minimum: -88.9795\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:19:38,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5893\n", - "Function value obtained: -87.8402\n", - "Current minimum: -88.9795\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:19:51,619\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2243\n", - "Function value obtained: -88.0271\n", - "Current minimum: -88.9795\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:20:07,431\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5916\n", - "Function value obtained: -83.6923\n", - "Current minimum: -88.9795\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:20:22,527\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5075\n", - "Function value obtained: -86.1168\n", - "Current minimum: -88.9795\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:20:35,911\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5386\n", - "Function value obtained: -85.5532\n", - "Current minimum: -88.9795\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:20:49,534\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3971\n", - "Function value obtained: -85.4601\n", - "Current minimum: -88.9795\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:21:03,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7992\n", - "Function value obtained: -83.5207\n", - "Current minimum: -88.9795\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:21:17,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4445\n", - "Function value obtained: -84.3831\n", - "Current minimum: -88.9795\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:21:31,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1385\n", - "Function value obtained: -82.4670\n", - "Current minimum: -88.9795\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:21:43,676\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 17.0420\n", - "Function value obtained: -85.7595\n", - "Current minimum: -88.9795\n", - "\n", - "--------------------\n", - "--------------------\n", - "Iteration No: 1 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:22:00,403\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 13.3441\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 2 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:22:13,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 12.1430\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 3 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:22:25,855\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 11.3214\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 4 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:22:40,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 16.0620\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 5 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:22:53,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 12.6246\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 6 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:23:05,830\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 12.3825\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 7 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:23:18,327\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 12.4799\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 8 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:23:30,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 12.8842\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 9 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:23:43,630\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 12.1856\n", - "Function value obtained: -1.8994\n", - "Current minimum: -1.8994\n", - "Iteration No: 10 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:23:55,883\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 12.3818\n", - "Function value obtained: -2.5139\n", - "Current minimum: -2.5139\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:24:08,156\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 11.4094\n", - "Function value obtained: -2.0813\n", - "Current minimum: -2.5139\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:24:22,304\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0544\n", - "Function value obtained: -2.2911\n", - "Current minimum: -2.5139\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:24:35,762\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3254\n", - "Function value obtained: -1.9797\n", - "Current minimum: -2.5139\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:24:47,968\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8745\n", - "Function value obtained: -2.4750\n", - "Current minimum: -2.5139\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:25:00,985\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8067\n", - "Function value obtained: -2.2776\n", - "Current minimum: -2.5139\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:25:14,733\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9730\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.5139\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:25:27,773\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9588\n", - "Function value obtained: -0.0000\n", - "Current minimum: -2.5139\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:25:40,671\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7669\n", - "Function value obtained: -2.5372\n", - "Current minimum: -2.5372\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:25:54,474\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8422\n", - "Function value obtained: -2.8429\n", - "Current minimum: -2.8429\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:26:09,317\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3344\n", - "Function value obtained: -1.8454\n", - "Current minimum: -2.8429\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:26:22,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4106\n", - "Function value obtained: -3.0755\n", - "Current minimum: -3.0755\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:26:36,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5436\n", - "Function value obtained: -3.5748\n", - "Current minimum: -3.5748\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:26:49,655\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9905\n", - "Function value obtained: -5.5441\n", - "Current minimum: -5.5441\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:27:03,700\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8164\n", - "Function value obtained: -8.0095\n", - "Current minimum: -8.0095\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:27:15,447\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 12.3010\n", - "Function value obtained: -35.1492\n", - "Current minimum: -35.1492\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:27:27,688\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 11.5499\n", - "Function value obtained: -39.1156\n", - "Current minimum: -39.1156\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:27:39,920\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 18.0375\n", - "Function value obtained: -45.9205\n", - "Current minimum: -45.9205\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:27:57,365\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1468\n", - "Function value obtained: -26.0641\n", - "Current minimum: -45.9205\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:28:11,474\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8943\n", - "Function value obtained: -45.2668\n", - "Current minimum: -45.9205\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:28:25,868\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9876\n", - "Function value obtained: -47.7713\n", - "Current minimum: -47.7713\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:28:38,348\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4895\n", - "Function value obtained: -46.4605\n", - "Current minimum: -47.7713\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:28:50,989\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4254\n", - "Function value obtained: -47.5786\n", - "Current minimum: -47.7713\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:29:05,253\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2774\n", - "Function value obtained: -46.2635\n", - "Current minimum: -47.7713\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:29:19,573\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7253\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:29:32,377\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4799\n", - "Function value obtained: -46.7317\n", - "Current minimum: -47.7713\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:29:45,771\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 12.1492\n", - "Function value obtained: -45.8123\n", - "Current minimum: -47.7713\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:29:58,249\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9250\n", - "Function value obtained: -46.8353\n", - "Current minimum: -47.7713\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:30:14,294\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8402\n", - "Function value obtained: -45.9584\n", - "Current minimum: -47.7713\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:30:28,747\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8060\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:30:42,514\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 12.8741\n", - "Function value obtained: -46.1857\n", - "Current minimum: -47.7713\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:30:55,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3373\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:31:08,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 12.4183\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:31:21,941\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4462\n", - "Function value obtained: -46.1164\n", - "Current minimum: -47.7713\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:31:37,625\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 11.8656\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:31:50,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 18.9770\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:32:08,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9229\n", - "Function value obtained: -45.8909\n", - "Current minimum: -47.7713\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:32:21,456\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8126\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:32:35,356\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0452\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:32:49,418\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6907\n", - "Function value obtained: -46.4117\n", - "Current minimum: -47.7713\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:33:03,022\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0216\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:33:17,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6671\n", - "Function value obtained: -44.7488\n", - "Current minimum: -47.7713\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:33:30,701\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6474\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:33:44,328\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2026\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:33:58,127\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3246\n", - "Function value obtained: -46.0245\n", - "Current minimum: -47.7713\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:34:12,950\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7276\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:34:26,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 12.0483\n", - "Function value obtained: -47.2695\n", - "Current minimum: -47.7713\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:34:39,133\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 17.9769\n", - "Function value obtained: -0.0000\n", - "Current minimum: -47.7713\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:34:56,634\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9255\n", - "Function value obtained: -49.3547\n", - "Current minimum: -49.3547\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:35:09,666\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6407\n", - "Function value obtained: -1.9186\n", - "Current minimum: -49.3547\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:35:23,286\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5259\n", - "Function value obtained: -47.3805\n", - "Current minimum: -49.3547\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:35:37,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0457\n", - "Function value obtained: -2.0854\n", - "Current minimum: -49.3547\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:35:50,810\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9219\n", - "Function value obtained: -43.3179\n", - "Current minimum: -49.3547\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:36:04,767\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9386\n", - "Function value obtained: -1.9662\n", - "Current minimum: -49.3547\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:36:18,677\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 17.2462\n", - "Function value obtained: -44.9149\n", - "Current minimum: -49.3547\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:36:35,914\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2240\n", - "Function value obtained: -0.0000\n", - "Current minimum: -49.3547\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:36:48,733\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 17.8964\n", - "Function value obtained: -48.2577\n", - "Current minimum: -49.3547\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:37:06,059\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4908\n", - "Function value obtained: -48.0746\n", - "Current minimum: -49.3547\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:37:19,440\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2178\n", - "Function value obtained: -0.0000\n", - "Current minimum: -49.3547\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:37:33,858\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2289\n", - "Function value obtained: -47.3106\n", - "Current minimum: -49.3547\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:37:47,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1989\n", - "Function value obtained: -48.8041\n", - "Current minimum: -49.3547\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:38:01,250\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7207\n", - "Function value obtained: -46.2191\n", - "Current minimum: -49.3547\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:38:14,959\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1385\n", - "Function value obtained: -47.1541\n", - "Current minimum: -49.3547\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:38:28,982\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5416\n", - "Function value obtained: -46.1420\n", - "Current minimum: -49.3547\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:38:41,689\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8685\n", - "Function value obtained: -48.2708\n", - "Current minimum: -49.3547\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:38:55,388\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6398\n", - "Function value obtained: -48.8198\n", - "Current minimum: -49.3547\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:39:08,120\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4267\n", - "Function value obtained: -47.6542\n", - "Current minimum: -49.3547\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:39:22,659\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7383\n", - "Function value obtained: -47.0740\n", - "Current minimum: -49.3547\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:39:37,391\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4720\n", - "Function value obtained: -46.1323\n", - "Current minimum: -49.3547\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:39:51,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 12.2977\n", - "Function value obtained: -0.0000\n", - "Current minimum: -49.3547\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:40:04,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 19.8883\n", - "Function value obtained: -46.6693\n", - "Current minimum: -49.3547\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:40:24,006\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3358\n", - "Function value obtained: -49.0673\n", - "Current minimum: -49.3547\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:40:37,336\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9920\n", - "Function value obtained: -0.0000\n", - "Current minimum: -49.3547\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:40:51,239\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0761\n", - "Function value obtained: -46.7308\n", - "Current minimum: -49.3547\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:41:04,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2108\n", - "Function value obtained: -47.5447\n", - "Current minimum: -49.3547\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:41:17,663\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5748\n", - "Function value obtained: -0.0000\n", - "Current minimum: -49.3547\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:41:31,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8805\n", - "Function value obtained: -47.6168\n", - "Current minimum: -49.3547\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:41:45,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3012\n", - "Function value obtained: -48.1308\n", - "Current minimum: -49.3547\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:42:00,414\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0945\n", - "Function value obtained: -0.0000\n", - "Current minimum: -49.3547\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:42:15,554\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8922\n", - "Function value obtained: -45.4751\n", - "Current minimum: -49.3547\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:42:30,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 13.3004\n", - "Function value obtained: -46.3762\n", - "Current minimum: -49.3547\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:42:44,784\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5564\n", - "Function value obtained: -46.1720\n", - "Current minimum: -49.3547\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:42:59,490\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4438\n", - "Function value obtained: -47.1809\n", - "Current minimum: -49.3547\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:43:13,776\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5516\n", - "Function value obtained: -48.3087\n", - "Current minimum: -49.3547\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:43:28,398\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3101\n", - "Function value obtained: -48.2784\n", - "Current minimum: -49.3547\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:43:43,548\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9981\n", - "Function value obtained: -47.1562\n", - "Current minimum: -49.3547\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:43:58,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7765\n", - "Function value obtained: -47.6764\n", - "Current minimum: -49.3547\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:44:15,704\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 18.8005\n", - "Function value obtained: -47.3652\n", - "Current minimum: -49.3547\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:44:30,190\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4907\n", - "Function value obtained: -45.5958\n", - "Current minimum: -49.3547\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:44:44,714\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9495\n", - "Function value obtained: -47.5417\n", - "Current minimum: -49.3547\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:44:58,662\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5283\n", - "Function value obtained: -46.9092\n", - "Current minimum: -49.3547\n", - "CPU times: user 1h 14min 6s, sys: 1h 14min 6s, total: 2h 28min 12s\n", - "Wall time: 1h 3min 26s\n" - ] - } - ], - "source": [ - "%%time\n", - "\n", - "cr_gp2 = gp_minimize(cr_obj2, cr_space, n_calls = 100, verbose=True)\n", - "print(\"\\n--------------------\"*2)\n", - "esc_gp2 = gp_minimize(esc_obj2, log_esc_space, n_calls = 100, verbose=True)\n", - "print(\"\\n--------------------\"*2)\n", - "msy_gp2 = gp_minimize(msy_obj2, log_esc_space, n_calls = 100, verbose=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "8104f281-815e-4d55-86c3-9e22c4634149", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "cr.: -90.26, [-0.03355168327278335, 0.7853961999069485, 0.2463992248494044] \n", - "esc: -88.98, [-0.28034215083975056]\n", - "msy: -49.35, [0.05773712246669316]\n", - "\n" - ] - } - ], - "source": [ - "print(f\"\"\"\n", - "cr.: {cr_gp2.fun:.2f}, {cr_gp2.x} \n", - "esc: {esc_gp2.fun:.2f}, {esc_gp2.x}\n", - "msy: {msy_gp2.fun:.2f}, {msy_gp2.x}\n", - "\"\"\")" - ] - }, - { - "cell_type": "markdown", - "id": "14cd665f-e859-41f7-b6f7-d14b16566bab", - "metadata": {}, - "source": [ - "## upow=1, trophy fishing 10 age classes" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "6e5b88dd-3725-48ea-b227-f6ca5357f189", - "metadata": {}, - "outputs": [], - "source": [ - "CONFIG3 = {\n", - " \"upow\": 1,\n", - " \"harvest_fn_name\": \"trophy\"\n", - "}\n", - "\n", - "cr_obj3 = cr_obj_generator(CONFIG3)\n", - "esc_obj3 = esc_obj_generator(CONFIG3)\n", - "msy_obj3 = msy_obj_generator(CONFIG3)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "1b4333db-83ce-46c2-87cf-943da18b3370", - "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:45:13,273\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 12.7166\n", - "Function value obtained: -3.3422\n", - "Current minimum: -3.3422\n", - "Iteration No: 2 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:45:26,282\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 12.8683\n", - "Function value obtained: -2.2590\n", - "Current minimum: -3.3422\n", - "Iteration No: 3 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:45:40,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 15.2559\n", - "Function value obtained: -3.6202\n", - "Current minimum: -3.6202\n", - "Iteration No: 4 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:45:54,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 13.0518\n", - "Function value obtained: -1.2145\n", - "Current minimum: -3.6202\n", - "Iteration No: 5 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:46:07,121\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 12.8836\n", - "Function value obtained: -6.0471\n", - "Current minimum: -6.0471\n", - "Iteration No: 6 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:46:20,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 12.0856\n", - "Function value obtained: -21.7106\n", - "Current minimum: -21.7106\n", - "Iteration No: 7 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:46:38,999\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 18.7035\n", - "Function value obtained: -12.7459\n", - "Current minimum: -21.7106\n", - "Iteration No: 8 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:46:51,415\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 18.5711\n", - "Function value obtained: -15.7186\n", - "Current minimum: -21.7106\n", - "Iteration No: 9 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:47:09,354\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 13.6057\n", - "Function value obtained: -18.5392\n", - "Current minimum: -21.7106\n", - "Iteration No: 10 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:47:23,029\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 13.3696\n", - "Function value obtained: -19.8398\n", - "Current minimum: -21.7106\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:47:36,331\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8086\n", - "Function value obtained: -0.2499\n", - "Current minimum: -21.7106\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:47:50,212\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2382\n", - "Function value obtained: -20.6884\n", - "Current minimum: -21.7106\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:48:04,438\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2872\n", - "Function value obtained: -24.0880\n", - "Current minimum: -24.0880\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:48:18,896\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8952\n", - "Function value obtained: -23.9823\n", - "Current minimum: -24.0880\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:48:32,592\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 12.7013\n", - "Function value obtained: -24.5750\n", - "Current minimum: -24.5750\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:48:45,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5461\n", - "Function value obtained: -24.1093\n", - "Current minimum: -24.5750\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:48:59,854\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 12.9551\n", - "Function value obtained: -24.0773\n", - "Current minimum: -24.5750\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:49:13,565\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8085\n", - "Function value obtained: -24.3747\n", - "Current minimum: -24.5750\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:49:26,694\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2552\n", - "Function value obtained: -24.6860\n", - "Current minimum: -24.6860\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:49:40,915\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2444\n", - "Function value obtained: -25.1980\n", - "Current minimum: -25.1980\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:49:56,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 12.5093\n", - "Function value obtained: -22.1760\n", - "Current minimum: -25.1980\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:50:08,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5840\n", - "Function value obtained: -2.8943\n", - "Current minimum: -25.1980\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:50:22,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4374\n", - "Function value obtained: -24.1276\n", - "Current minimum: -25.1980\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:50:36,040\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5980\n", - "Function value obtained: -25.1970\n", - "Current minimum: -25.1980\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:50:50,394\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5959\n", - "Function value obtained: -25.4101\n", - "Current minimum: -25.4101\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:51:04,983\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 13.4430\n", - "Function value obtained: -24.6311\n", - "Current minimum: -25.4101\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:51:18,345\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2002\n", - "Function value obtained: -24.6536\n", - "Current minimum: -25.4101\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:51:33,629\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6360\n", - "Function value obtained: -24.3260\n", - "Current minimum: -25.4101\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:51:49,198\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7697\n", - "Function value obtained: -24.1331\n", - "Current minimum: -25.4101\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:52:04,458\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9642\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.4101\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:52:17,684\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 20.1782\n", - "Function value obtained: -25.8992\n", - "Current minimum: -25.8992\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:52:40,983\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 17.5726\n", - "Function value obtained: -24.7605\n", - "Current minimum: -25.8992\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:52:58,741\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 19.3697\n", - "Function value obtained: -10.2977\n", - "Current minimum: -25.8992\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:53:15,139\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1188\n", - "Function value obtained: -27.2983\n", - "Current minimum: -27.2983\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:53:29,265\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9095\n", - "Function value obtained: -25.3650\n", - "Current minimum: -27.2983\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:53:44,217\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6142\n", - "Function value obtained: -25.1707\n", - "Current minimum: -27.2983\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:53:57,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 18.8586\n", - "Function value obtained: -17.8434\n", - "Current minimum: -27.2983\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:54:15,637\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5371\n", - "Function value obtained: -28.1856\n", - "Current minimum: -28.1856\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:54:31,609\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2483\n", - "Function value obtained: -27.6668\n", - "Current minimum: -28.1856\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:54:48,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 16.9095\n", - "Function value obtained: -24.7152\n", - "Current minimum: -28.1856\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:55:02,315\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8592\n", - "Function value obtained: -21.1227\n", - "Current minimum: -28.1856\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:55:16,213\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8794\n", - "Function value obtained: -12.3416\n", - "Current minimum: -28.1856\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:55:31,469\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5303\n", - "Function value obtained: -25.8644\n", - "Current minimum: -28.1856\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:55:46,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9911\n", - "Function value obtained: -30.2845\n", - "Current minimum: -30.2845\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:56:01,140\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8762\n", - "Function value obtained: -28.9319\n", - "Current minimum: -30.2845\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:56:15,582\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1724\n", - "Function value obtained: -31.5466\n", - "Current minimum: -31.5466\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:56:30,652\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7560\n", - "Function value obtained: -29.8928\n", - "Current minimum: -31.5466\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:56:45,654\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5281\n", - "Function value obtained: -28.7802\n", - "Current minimum: -31.5466\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:57:00,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1077\n", - "Function value obtained: -31.4449\n", - "Current minimum: -31.5466\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:57:15,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3850\n", - "Function value obtained: -30.1364\n", - "Current minimum: -31.5466\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:57:30,679\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6837\n", - "Function value obtained: -30.5866\n", - "Current minimum: -31.5466\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:57:45,198\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7768\n", - "Function value obtained: -3.2644\n", - "Current minimum: -31.5466\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:58:00,092\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2291\n", - "Function value obtained: -0.0000\n", - "Current minimum: -31.5466\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:58:15,318\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7794\n", - "Function value obtained: -19.3080\n", - "Current minimum: -31.5466\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:58:30,069\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3003\n", - "Function value obtained: -27.0818\n", - "Current minimum: -31.5466\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:58:45,381\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 17.2853\n", - "Function value obtained: -29.7998\n", - "Current minimum: -31.5466\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:59:02,564\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5723\n", - "Function value obtained: -29.8916\n", - "Current minimum: -31.5466\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:59:17,300\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 14.0231\n", - "Function value obtained: -30.5911\n", - "Current minimum: -31.5466\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:59:31,324\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7449\n", - "Function value obtained: -22.9761\n", - "Current minimum: -31.5466\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 19:59:47,028\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5489\n", - "Function value obtained: -27.8065\n", - "Current minimum: -31.5466\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:00:01,576\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 15.3040\n", - "Function value obtained: -29.3063\n", - "Current minimum: -31.5466\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:00:16,976\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6854\n", - "Function value obtained: -25.4359\n", - "Current minimum: -31.5466\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:00:32,551\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 14.7504\n", - "Function value obtained: -26.8313\n", - "Current minimum: -31.5466\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:00:47,301\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9350\n", - "Function value obtained: -18.2366\n", - "Current minimum: -31.5466\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:01:02,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5534\n", - "Function value obtained: -30.1370\n", - "Current minimum: -31.5466\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:01:16,981\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 18.7948\n", - "Function value obtained: -23.5834\n", - "Current minimum: -31.5466\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:01:36,027\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 18.2109\n", - "Function value obtained: -29.5153\n", - "Current minimum: -31.5466\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:01:53,935\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8581\n", - "Function value obtained: -6.6769\n", - "Current minimum: -31.5466\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:02:08,720\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2246\n", - "Function value obtained: -31.2148\n", - "Current minimum: -31.5466\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:02:23,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4528\n", - "Function value obtained: -31.8623\n", - "Current minimum: -31.8623\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:02:38,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8004\n", - "Function value obtained: -30.5065\n", - "Current minimum: -31.8623\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:02:54,213\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8590\n", - "Function value obtained: -1.2338\n", - "Current minimum: -31.8623\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:03:10,144\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 18.5292\n", - "Function value obtained: -30.6296\n", - "Current minimum: -31.8623\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:03:28,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6776\n", - "Function value obtained: -28.7260\n", - "Current minimum: -31.8623\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:03:43,257\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7452\n", - "Function value obtained: -31.6708\n", - "Current minimum: -31.8623\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:03:58,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 12.6056\n", - "Function value obtained: -31.9045\n", - "Current minimum: -31.9045\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:04:12,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 24.4298\n", - "Function value obtained: -30.3985\n", - "Current minimum: -31.9045\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:04:36,118\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2909\n", - "Function value obtained: -30.8683\n", - "Current minimum: -31.9045\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:04:50,143\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 20.7625\n", - "Function value obtained: -30.5748\n", - "Current minimum: -31.9045\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:05:11,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 19.2616\n", - "Function value obtained: -30.0262\n", - "Current minimum: -31.9045\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:05:30,461\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 20.4224\n", - "Function value obtained: -32.0205\n", - "Current minimum: -32.0205\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:05:49,903\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0436\n", - "Function value obtained: -31.4876\n", - "Current minimum: -32.0205\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:06:04,931\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2155\n", - "Function value obtained: -30.6195\n", - "Current minimum: -32.0205\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:06:21,089\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3091\n", - "Function value obtained: -1.9054\n", - "Current minimum: -32.0205\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:06:37,406\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4208\n", - "Function value obtained: -24.7538\n", - "Current minimum: -32.0205\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:06:52,913\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2272\n", - "Function value obtained: -26.3072\n", - "Current minimum: -32.0205\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:07:09,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0176\n", - "Function value obtained: -31.3672\n", - "Current minimum: -32.0205\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:07:25,091\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2073\n", - "Function value obtained: -0.0000\n", - "Current minimum: -32.0205\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:07:40,362\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0951\n", - "Function value obtained: -31.2598\n", - "Current minimum: -32.0205\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:07:56,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0373\n", - "Function value obtained: -30.7222\n", - "Current minimum: -32.0205\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:08:12,497\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5148\n", - "Function value obtained: -0.0000\n", - "Current minimum: -32.0205\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:08:29,082\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1886\n", - "Function value obtained: -26.7533\n", - "Current minimum: -32.0205\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:08:45,214\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8299\n", - "Function value obtained: -23.7794\n", - "Current minimum: -32.0205\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:09:02,064\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8097\n", - "Function value obtained: -1.5413\n", - "Current minimum: -32.0205\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:09:17,905\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 17.8100\n", - "Function value obtained: -31.2005\n", - "Current minimum: -32.0205\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:09:34,698\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7735\n", - "Function value obtained: -30.6715\n", - "Current minimum: -32.0205\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:09:50,424\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4205\n", - "Function value obtained: -29.5495\n", - "Current minimum: -32.0205\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:10:06,978\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9746\n", - "Function value obtained: -24.1894\n", - "Current minimum: -32.0205\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:10:21,854\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8627\n", - "Function value obtained: -30.7302\n", - "Current minimum: -32.0205\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:10:38,650\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4924\n", - "Function value obtained: -28.2524\n", - "Current minimum: -32.0205\n", - "\n", - "--------------------\n", - "--------------------\n", - "Iteration No: 1 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:10:54,267\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 14.3592\n", - "Function value obtained: -13.7919\n", - "Current minimum: -13.7919\n", - "Iteration No: 2 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:11:08,657\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 15.3803\n", - "Function value obtained: -0.8608\n", - "Current minimum: -13.7919\n", - "Iteration No: 3 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:11:24,057\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 14.4865\n", - "Function value obtained: -0.8770\n", - "Current minimum: -13.7919\n", - "Iteration No: 4 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:11:38,474\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 12.5861\n", - "Function value obtained: -0.9897\n", - "Current minimum: -13.7919\n", - "Iteration No: 5 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:11:51,804\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 20.9790\n", - "Function value obtained: -0.0000\n", - "Current minimum: -13.7919\n", - "Iteration No: 6 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:12:12,939\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 23.4379\n", - "Function value obtained: -0.8367\n", - "Current minimum: -13.7919\n", - "Iteration No: 7 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:12:35,572\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 14.2344\n", - "Function value obtained: -0.8237\n", - "Current minimum: -13.7919\n", - "Iteration No: 8 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:12:49,725\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 14.7844\n", - "Function value obtained: -0.8734\n", - "Current minimum: -13.7919\n", - "Iteration No: 9 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:13:04,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 15.3880\n", - "Function value obtained: -0.9060\n", - "Current minimum: -13.7919\n", - "Iteration No: 10 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:13:19,994\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 13.7719\n", - "Function value obtained: -0.8580\n", - "Current minimum: -13.7919\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:13:34,159\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 18.7448\n", - "Function value obtained: -9.9804\n", - "Current minimum: -13.7919\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:13:52,743\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0185\n", - "Function value obtained: -14.1624\n", - "Current minimum: -14.1624\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:14:08,467\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2708\n", - "Function value obtained: -13.4188\n", - "Current minimum: -14.1624\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:14:23,883\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4794\n", - "Function value obtained: -13.0523\n", - "Current minimum: -14.1624\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:14:39,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6075\n", - "Function value obtained: -13.6092\n", - "Current minimum: -14.1624\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:14:53,788\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 14.5097\n", - "Function value obtained: -2.2971\n", - "Current minimum: -14.1624\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:15:08,349\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8102\n", - "Function value obtained: -13.3907\n", - "Current minimum: -14.1624\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:15:24,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8886\n", - "Function value obtained: -7.8471\n", - "Current minimum: -14.1624\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:15:39,116\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8942\n", - "Function value obtained: -13.8512\n", - "Current minimum: -14.1624\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:15:54,191\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8543\n", - "Function value obtained: -13.2317\n", - "Current minimum: -14.1624\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:16:10,538\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 16.7105\n", - "Function value obtained: -13.4035\n", - "Current minimum: -14.1624\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:16:25,607\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9611\n", - "Function value obtained: -13.6324\n", - "Current minimum: -14.1624\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:16:39,781\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9912\n", - "Function value obtained: -13.4511\n", - "Current minimum: -14.1624\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:16:55,509\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4858\n", - "Function value obtained: -13.7319\n", - "Current minimum: -14.1624\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:17:10,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9089\n", - "Function value obtained: -13.3498\n", - "Current minimum: -14.1624\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:17:25,081\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 13.2782\n", - "Function value obtained: -13.3748\n", - "Current minimum: -14.1624\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:17:41,756\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 18.6530\n", - "Function value obtained: -13.4548\n", - "Current minimum: -14.1624\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:17:56,816\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0746\n", - "Function value obtained: -13.9134\n", - "Current minimum: -14.1624\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:18:12,003\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1300\n", - "Function value obtained: -13.5699\n", - "Current minimum: -14.1624\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:18:28,153\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 15.2037\n", - "Function value obtained: -13.9893\n", - "Current minimum: -14.1624\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:18:43,248\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8263\n", - "Function value obtained: -13.2808\n", - "Current minimum: -14.1624\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:18:57,392\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5138\n", - "Function value obtained: -13.3273\n", - "Current minimum: -14.1624\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:19:11,314\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 20.4689\n", - "Function value obtained: -13.1557\n", - "Current minimum: -14.1624\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:19:31,667\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 20.5685\n", - "Function value obtained: -13.7990\n", - "Current minimum: -14.1624\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:19:52,270\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 23.6767\n", - "Function value obtained: -13.4255\n", - "Current minimum: -14.1624\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:20:18,638\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 17.6619\n", - "Function value obtained: -13.0218\n", - "Current minimum: -14.1624\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:20:33,352\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 17.5666\n", - "Function value obtained: -13.4393\n", - "Current minimum: -14.1624\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:20:51,685\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 17.3208\n", - "Function value obtained: -13.3430\n", - "Current minimum: -14.1624\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:21:08,025\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9746\n", - "Function value obtained: -13.6745\n", - "Current minimum: -14.1624\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:21:23,796\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6023\n", - "Function value obtained: -13.2590\n", - "Current minimum: -14.1624\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:21:38,113\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 21.0679\n", - "Function value obtained: -13.3283\n", - "Current minimum: -14.1624\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:21:59,711\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8964\n", - "Function value obtained: -13.7560\n", - "Current minimum: -14.1624\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:22:15,656\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7662\n", - "Function value obtained: -13.2686\n", - "Current minimum: -14.1624\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:22:31,371\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8372\n", - "Function value obtained: -13.4258\n", - "Current minimum: -14.1624\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:22:48,176\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 13.7827\n", - "Function value obtained: -13.1792\n", - "Current minimum: -14.1624\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:23:04,620\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 17.8800\n", - "Function value obtained: -13.5241\n", - "Current minimum: -14.1624\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:23:19,924\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1300\n", - "Function value obtained: -13.3398\n", - "Current minimum: -14.1624\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:23:35,946\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 16.7410\n", - "Function value obtained: -13.5360\n", - "Current minimum: -14.1624\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:23:52,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 16.1024\n", - "Function value obtained: -13.0472\n", - "Current minimum: -14.1624\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:24:08,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2336\n", - "Function value obtained: -13.3045\n", - "Current minimum: -14.1624\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:24:24,966\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 13.6231\n", - "Function value obtained: -12.9234\n", - "Current minimum: -14.1624\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:24:39,591\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 21.3430\n", - "Function value obtained: -13.7088\n", - "Current minimum: -14.1624\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:25:00,769\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 24.7311\n", - "Function value obtained: -13.6131\n", - "Current minimum: -14.1624\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:25:25,328\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 22.7744\n", - "Function value obtained: -12.8286\n", - "Current minimum: -14.1624\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:25:47,609\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8792\n", - "Function value obtained: -12.7727\n", - "Current minimum: -14.1624\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:26:03,462\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 16.6997\n", - "Function value obtained: -13.8037\n", - "Current minimum: -14.1624\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:26:20,169\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0160\n", - "Function value obtained: -13.8822\n", - "Current minimum: -14.1624\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:26:36,175\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8208\n", - "Function value obtained: -13.9756\n", - "Current minimum: -14.1624\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:26:53,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 13.9429\n", - "Function value obtained: -13.6753\n", - "Current minimum: -14.1624\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:27:07,497\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 19.8395\n", - "Function value obtained: -13.2046\n", - "Current minimum: -14.1624\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:27:26,782\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0558\n", - "Function value obtained: -13.3153\n", - "Current minimum: -14.1624\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:27:43,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1606\n", - "Function value obtained: -13.6479\n", - "Current minimum: -14.1624\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:27:58,757\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 19.3947\n", - "Function value obtained: -13.7278\n", - "Current minimum: -14.1624\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:28:17,517\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9217\n", - "Function value obtained: -13.8681\n", - "Current minimum: -14.1624\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:28:32,736\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 20.9789\n", - "Function value obtained: -13.1946\n", - "Current minimum: -14.1624\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:28:53,342\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 13.0279\n", - "Function value obtained: -13.1855\n", - "Current minimum: -14.1624\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:29:07,150\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 26.8780\n", - "Function value obtained: -13.0255\n", - "Current minimum: -14.1624\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:29:33,337\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 15.4052\n", - "Function value obtained: -13.6944\n", - "Current minimum: -14.1624\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:29:48,667\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 14.1011\n", - "Function value obtained: -13.3326\n", - "Current minimum: -14.1624\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:30:03,465\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 23.8231\n", - "Function value obtained: -13.4103\n", - "Current minimum: -14.1624\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:30:26,579\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 16.7662\n", - "Function value obtained: -13.1638\n", - "Current minimum: -14.1624\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:30:43,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 22.4772\n", - "Function value obtained: -13.2211\n", - "Current minimum: -14.1624\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:31:05,978\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5034\n", - "Function value obtained: -13.8004\n", - "Current minimum: -14.1624\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:31:22,454\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8258\n", - "Function value obtained: -13.0706\n", - "Current minimum: -14.1624\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:31:39,041\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 17.5066\n", - "Function value obtained: -13.2345\n", - "Current minimum: -14.1624\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:31:56,757\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 17.2684\n", - "Function value obtained: -13.7316\n", - "Current minimum: -14.1624\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:32:14,021\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 18.6246\n", - "Function value obtained: -13.2624\n", - "Current minimum: -14.1624\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:32:32,746\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4163\n", - "Function value obtained: -13.3726\n", - "Current minimum: -14.1624\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:32:49,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 13.8531\n", - "Function value obtained: -13.5893\n", - "Current minimum: -14.1624\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:33:03,820\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 24.8330\n", - "Function value obtained: -13.6783\n", - "Current minimum: -14.1624\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:33:27,834\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5875\n", - "Function value obtained: -13.4919\n", - "Current minimum: -14.1624\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:33:45,244\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 19.0128\n", - "Function value obtained: -13.7669\n", - "Current minimum: -14.1624\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:34:02,511\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 14.2241\n", - "Function value obtained: -12.9329\n", - "Current minimum: -14.1624\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:34:17,050\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 23.9931\n", - "Function value obtained: -13.1596\n", - "Current minimum: -14.1624\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:34:40,693\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 14.9950\n", - "Function value obtained: -13.3585\n", - "Current minimum: -14.1624\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:34:55,945\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 21.4343\n", - "Function value obtained: -13.8398\n", - "Current minimum: -14.1624\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:35:17,074\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 14.3189\n", - "Function value obtained: -13.5490\n", - "Current minimum: -14.1624\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:35:31,951\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 24.0823\n", - "Function value obtained: -13.3595\n", - "Current minimum: -14.1624\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:35:55,489\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9351\n", - "Function value obtained: -12.9894\n", - "Current minimum: -14.1624\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:36:11,302\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 16.9627\n", - "Function value obtained: -13.4997\n", - "Current minimum: -14.1624\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:36:28,352\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 15.5490\n", - "Function value obtained: -12.7742\n", - "Current minimum: -14.1624\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:36:44,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7321\n", - "Function value obtained: -13.8610\n", - "Current minimum: -14.1624\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:36:59,632\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 18.0026\n", - "Function value obtained: -13.2046\n", - "Current minimum: -14.1624\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:37:17,816\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6302\n", - "Function value obtained: -13.6597\n", - "Current minimum: -14.1624\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:37:32,933\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 24.7897\n", - "Function value obtained: -13.3522\n", - "Current minimum: -14.1624\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:37:57,110\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6996\n", - "Function value obtained: -13.4632\n", - "Current minimum: -14.1624\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:38:12,396\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 23.6777\n", - "Function value obtained: -13.3483\n", - "Current minimum: -14.1624\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:38:35,559\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 17.5413\n", - "Function value obtained: -13.8656\n", - "Current minimum: -14.1624\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:38:53,086\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5719\n", - "Function value obtained: -13.1648\n", - "Current minimum: -14.1624\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:39:09,681\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 17.1363\n", - "Function value obtained: -14.3016\n", - "Current minimum: -14.3016\n", - "\n", - "--------------------\n", - "--------------------\n", - "Iteration No: 1 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:39:26,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 1 ended. Evaluation done at random point.\n", - "Time taken: 15.8634\n", - "Function value obtained: -0.0000\n", - "Current minimum: -0.0000\n", - "Iteration No: 2 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:39:42,690\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 2 ended. Evaluation done at random point.\n", - "Time taken: 16.2954\n", - "Function value obtained: -25.1807\n", - "Current minimum: -25.1807\n", - "Iteration No: 3 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:39:59,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 3 ended. Evaluation done at random point.\n", - "Time taken: 16.1448\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 4 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:40:15,099\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 4 ended. Evaluation done at random point.\n", - "Time taken: 16.5112\n", - "Function value obtained: -0.9482\n", - "Current minimum: -25.1807\n", - "Iteration No: 5 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:40:31,890\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 5 ended. Evaluation done at random point.\n", - "Time taken: 15.6452\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 6 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:40:47,648\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 6 ended. Evaluation done at random point.\n", - "Time taken: 17.2778\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 7 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:41:05,428\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 7 ended. Evaluation done at random point.\n", - "Time taken: 24.3452\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 8 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:41:29,313\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 8 ended. Evaluation done at random point.\n", - "Time taken: 21.3204\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 9 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:41:50,357\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 9 ended. Evaluation done at random point.\n", - "Time taken: 15.3876\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 10 started. Evaluating function at random point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:42:08,224\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 10 ended. Evaluation done at random point.\n", - "Time taken: 18.3777\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 11 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:42:24,148\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 11 ended. Search finished for the next optimal point.\n", - "Time taken: 16.9908\n", - "Function value obtained: -23.9636\n", - "Current minimum: -25.1807\n", - "Iteration No: 12 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:42:41,162\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 12 ended. Search finished for the next optimal point.\n", - "Time taken: 15.9118\n", - "Function value obtained: -15.5843\n", - "Current minimum: -25.1807\n", - "Iteration No: 13 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:42:57,068\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 13 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7454\n", - "Function value obtained: -17.2209\n", - "Current minimum: -25.1807\n", - "Iteration No: 14 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:43:12,913\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 14 ended. Search finished for the next optimal point.\n", - "Time taken: 20.4829\n", - "Function value obtained: -4.9900\n", - "Current minimum: -25.1807\n", - "Iteration No: 15 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:43:33,368\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 15 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8254\n", - "Function value obtained: -22.7081\n", - "Current minimum: -25.1807\n", - "Iteration No: 16 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:43:50,079\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 16 ended. Search finished for the next optimal point.\n", - "Time taken: 16.9089\n", - "Function value obtained: -0.8624\n", - "Current minimum: -25.1807\n", - "Iteration No: 17 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:44:06,950\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 17 ended. Search finished for the next optimal point.\n", - "Time taken: 13.5610\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 18 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:44:22,300\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 18 ended. Search finished for the next optimal point.\n", - "Time taken: 25.9277\n", - "Function value obtained: -0.9049\n", - "Current minimum: -25.1807\n", - "Iteration No: 19 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:44:47,387\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 19 ended. Search finished for the next optimal point.\n", - "Time taken: 28.4779\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 20 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:45:15,988\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 20 ended. Search finished for the next optimal point.\n", - "Time taken: 19.1985\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 21 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:45:34,126\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 21 ended. Search finished for the next optimal point.\n", - "Time taken: 17.4535\n", - "Function value obtained: -23.4528\n", - "Current minimum: -25.1807\n", - "Iteration No: 22 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:45:51,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 22 ended. Search finished for the next optimal point.\n", - "Time taken: 17.3519\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 23 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:46:08,881\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 23 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8159\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 24 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:46:24,885\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 24 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0803\n", - "Function value obtained: -0.9133\n", - "Current minimum: -25.1807\n", - "Iteration No: 25 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:46:40,914\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 25 ended. Search finished for the next optimal point.\n", - "Time taken: 15.1441\n", - "Function value obtained: -0.8762\n", - "Current minimum: -25.1807\n", - "Iteration No: 26 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:46:56,632\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 26 ended. Search finished for the next optimal point.\n", - "Time taken: 18.0000\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 27 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:47:14,125\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 27 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0803\n", - "Function value obtained: -24.8374\n", - "Current minimum: -25.1807\n", - "Iteration No: 28 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:47:30,485\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 28 ended. Search finished for the next optimal point.\n", - "Time taken: 17.5908\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 29 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:47:47,766\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 29 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0137\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 30 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:48:03,631\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 30 ended. Search finished for the next optimal point.\n", - "Time taken: 16.9997\n", - "Function value obtained: -23.7273\n", - "Current minimum: -25.1807\n", - "Iteration No: 31 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:48:19,750\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 31 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0223\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 32 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:48:35,306\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 32 ended. Search finished for the next optimal point.\n", - "Time taken: 15.8198\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 33 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:48:51,957\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 33 ended. Search finished for the next optimal point.\n", - "Time taken: 16.2813\n", - "Function value obtained: -24.7542\n", - "Current minimum: -25.1807\n", - "Iteration No: 34 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:49:07,518\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 34 ended. Search finished for the next optimal point.\n", - "Time taken: 25.7638\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.1807\n", - "Iteration No: 35 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:49:32,713\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 35 ended. Search finished for the next optimal point.\n", - "Time taken: 16.8646\n", - "Function value obtained: -24.7489\n", - "Current minimum: -25.1807\n", - "Iteration No: 36 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:49:50,121\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 36 ended. Search finished for the next optimal point.\n", - "Time taken: 17.2418\n", - "Function value obtained: -0.8548\n", - "Current minimum: -25.1807\n", - "Iteration No: 37 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:50:06,689\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 37 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4862\n", - "Function value obtained: -0.8529\n", - "Current minimum: -25.1807\n", - "Iteration No: 38 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:50:23,363\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 38 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6256\n", - "Function value obtained: -25.7620\n", - "Current minimum: -25.7620\n", - "Iteration No: 39 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:50:38,230\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 39 ended. Search finished for the next optimal point.\n", - "Time taken: 22.1361\n", - "Function value obtained: -0.8844\n", - "Current minimum: -25.7620\n", - "Iteration No: 40 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:51:00,109\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 40 ended. Search finished for the next optimal point.\n", - "Time taken: 15.0743\n", - "Function value obtained: -0.8696\n", - "Current minimum: -25.7620\n", - "Iteration No: 41 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:51:17,563\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 41 ended. Search finished for the next optimal point.\n", - "Time taken: 18.4293\n", - "Function value obtained: -24.9961\n", - "Current minimum: -25.7620\n", - "Iteration No: 42 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:51:33,697\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 42 ended. Search finished for the next optimal point.\n", - "Time taken: 18.6820\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 43 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:51:52,283\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 43 ended. Search finished for the next optimal point.\n", - "Time taken: 14.8649\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 44 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:52:08,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 44 ended. Search finished for the next optimal point.\n", - "Time taken: 19.6056\n", - "Function value obtained: -24.9433\n", - "Current minimum: -25.7620\n", - "Iteration No: 45 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:52:26,862\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 45 ended. Search finished for the next optimal point.\n", - "Time taken: 14.6143\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 46 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:52:42,117\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 46 ended. Search finished for the next optimal point.\n", - "Time taken: 25.0543\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 47 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:53:06,415\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 47 ended. Search finished for the next optimal point.\n", - "Time taken: 17.6200\n", - "Function value obtained: -25.0296\n", - "Current minimum: -25.7620\n", - "Iteration No: 48 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:53:24,147\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 48 ended. Search finished for the next optimal point.\n", - "Time taken: 17.6422\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 49 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:53:41,794\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 49 ended. Search finished for the next optimal point.\n", - "Time taken: 15.7354\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 50 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:53:57,618\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 50 ended. Search finished for the next optimal point.\n", - "Time taken: 20.0075\n", - "Function value obtained: -24.6033\n", - "Current minimum: -25.7620\n", - "Iteration No: 51 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:54:22,610\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 51 ended. Search finished for the next optimal point.\n", - "Time taken: 22.2062\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 52 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:54:39,777\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 52 ended. Search finished for the next optimal point.\n", - "Time taken: 16.0193\n", - "Function value obtained: -24.7025\n", - "Current minimum: -25.7620\n", - "Iteration No: 53 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:54:55,755\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 53 ended. Search finished for the next optimal point.\n", - "Time taken: 27.5433\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 54 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:55:23,246\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 54 ended. Search finished for the next optimal point.\n", - "Time taken: 16.5501\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 55 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:55:39,981\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 55 ended. Search finished for the next optimal point.\n", - "Time taken: 17.6153\n", - "Function value obtained: -23.3715\n", - "Current minimum: -25.7620\n", - "Iteration No: 56 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:55:57,271\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 56 ended. Search finished for the next optimal point.\n", - "Time taken: 17.1656\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 57 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:56:14,653\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(esc_gp1)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "ad28edfe-c997-49c9-af07-9aec73462d50", + "metadata": {}, + "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 57 ended. Search finished for the next optimal point.\n", - "Time taken: 18.4854\n", - "Function value obtained: -25.1107\n", - "Current minimum: -25.7620\n", - "Iteration No: 58 started. Searching for the next optimal point.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:56:33,181\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(msy_gp1)" + ] + }, + { + "cell_type": "markdown", + "id": "5fbd99bb-d5c0-4cc7-a8d8-57ae7410623d", + "metadata": {}, + "source": [ + "### 2" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "7c5d3b9c-d627-4851-89cf-f8769818e184", + "metadata": {}, + "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 58 ended. Search finished for the next optimal point.\n", - "Time taken: 16.3453\n", - "Function value obtained: -24.7787\n", - "Current minimum: -25.7620\n", - "Iteration No: 59 started. Searching for the next optimal point.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:56:49,851\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(cr_gp2)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "8f177fb6-d527-4367-bc55-080f4116bbc1", + "metadata": {}, + "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 59 ended. Search finished for the next optimal point.\n", - "Time taken: 16.9631\n", - "Function value obtained: -0.8623\n", - "Current minimum: -25.7620\n", - "Iteration No: 60 started. Searching for the next optimal point.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:57:06,450\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(esc_gp2)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "20647c64-7ab3-47c4-a0e8-5b7f4b7a9e2c", + "metadata": {}, + "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 60 ended. Search finished for the next optimal point.\n", - "Time taken: 20.3394\n", - "Function value obtained: -25.7061\n", - "Current minimum: -25.7620\n", - "Iteration No: 61 started. Searching for the next optimal point.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:57:26,696\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(msy_gp2)" + ] + }, + { + "cell_type": "markdown", + "id": "41607833-e11a-4ca1-8a8c-b478cc811894", + "metadata": {}, + "source": [ + "### 3" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "1636f3ff-2f3c-4563-a4b1-139e67a28cbf", + "metadata": {}, + "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 61 ended. Search finished for the next optimal point.\n", - "Time taken: 16.4044\n", - "Function value obtained: -24.9317\n", - "Current minimum: -25.7620\n", - "Iteration No: 62 started. Searching for the next optimal point.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:57:43,405\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(cr_gp3)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "4bfa1c5a-45f1-43dd-a2fa-16231a9a5079", + "metadata": {}, + "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 62 ended. Search finished for the next optimal point.\n", - "Time taken: 19.7760\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 63 started. Searching for the next optimal point.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:58:03,046\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(esc_gp3)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "f9415caa-168f-4177-8ba8-970ebb57322f", + "metadata": {}, + "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 63 ended. Search finished for the next optimal point.\n", - "Time taken: 18.0187\n", - "Function value obtained: -24.1865\n", - "Current minimum: -25.7620\n", - "Iteration No: 64 started. Searching for the next optimal point.\n" - ] + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 20:58:21,210\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_objective(msy_gp3)" + ] + }, + { + "cell_type": "markdown", + "id": "b1c7400b-a8fc-4d28-8493-3cad80babb53", + "metadata": {}, + "source": [ + "## Constant action on escapement env \n", + "(Should be equivalent to simply constant escapement)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "21893d39-3aa1-48b5-8677-6ac836cabc42", + "metadata": {}, + "outputs": [], + "source": [ + "from rl4fisheries import AsmEnvEsc\n", + "\n", + "# do this for CONFIG3\n", + "CONFIG = CONFIG3\n", + "\n", + "def const_act_esc_obj(x):\n", + " eval_env = AsmEnvEsc(config=CONFIG)\n", + " agent = ConstAct(env=eval_env, action=np.float32([x[0]]))\n", + " rews = eval_pol(\n", + " policy=agent, \n", + " env_cls=AsmEnvEsc, config=CONFIG, \n", + " n_batches=1, batch_size=200\n", + " )\n", + " return -np.mean(rews)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "b041ad87-48c7-4c85-80f1-86f33891f3c2", + "metadata": { + "scrolled": true + }, + "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 64 ended. Search finished for the next optimal point.\n", - "Time taken: 18.5912\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 65 started. Searching for the next optimal point.\n" + "Iteration No: 1 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 20:58:39,550\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:49:09,759\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 65 ended. Search finished for the next optimal point.\n", - "Time taken: 14.4120\n", - "Function value obtained: -23.8400\n", - "Current minimum: -25.7620\n", - "Iteration No: 66 started. Searching for the next optimal point.\n" + "Iteration No: 1 ended. Evaluation done at random point.\n", + "Time taken: 7.7871\n", + "Function value obtained: -0.0000\n", + "Current minimum: -0.0000\n", + "Iteration No: 2 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 20:58:54,829\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:49:17,359\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 66 ended. Search finished for the next optimal point.\n", - "Time taken: 30.0197\n", + "Iteration No: 2 ended. Evaluation done at random point.\n", + "Time taken: 7.5012\n", "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 67 started. Searching for the next optimal point.\n" + "Current minimum: -0.0000\n", + "Iteration No: 3 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 20:59:24,147\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:49:24,880\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 67 ended. Search finished for the next optimal point.\n", - "Time taken: 19.0750\n", - "Function value obtained: -24.2439\n", - "Current minimum: -25.7620\n", - "Iteration No: 68 started. Searching for the next optimal point.\n" + "Iteration No: 3 ended. Evaluation done at random point.\n", + "Time taken: 7.7451\n", + "Function value obtained: -0.2427\n", + "Current minimum: -0.2427\n", + "Iteration No: 4 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 20:59:43,121\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:49:32,646\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 68 ended. Search finished for the next optimal point.\n", - "Time taken: 17.1814\n", + "Iteration No: 4 ended. Evaluation done at random point.\n", + "Time taken: 8.3741\n", "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 69 started. Searching for the next optimal point.\n" + "Current minimum: -0.2427\n", + "Iteration No: 5 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:00:01,063\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:49:41,032\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 69 ended. Search finished for the next optimal point.\n", - "Time taken: 19.5890\n", - "Function value obtained: -23.9463\n", - "Current minimum: -25.7620\n", - "Iteration No: 70 started. Searching for the next optimal point.\n" + "Iteration No: 5 ended. Evaluation done at random point.\n", + "Time taken: 7.5954\n", + "Function value obtained: -14.2442\n", + "Current minimum: -14.2442\n", + "Iteration No: 6 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:00:19,922\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:49:48,614\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 70 ended. Search finished for the next optimal point.\n", - "Time taken: 17.2594\n", + "Iteration No: 6 ended. Evaluation done at random point.\n", + "Time taken: 7.7939\n", "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 71 started. Searching for the next optimal point.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2024-05-22 21:00:37,149\tINFO worker.py:1749 -- Started a local Ray instance.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration No: 71 ended. Search finished for the next optimal point.\n", - "Time taken: 18.3128\n", - "Function value obtained: -24.4614\n", - "Current minimum: -25.7620\n", - "Iteration No: 72 started. Searching for the next optimal point.\n" + "Current minimum: -14.2442\n", + "Iteration No: 7 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:00:55,520\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:49:56,376\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 72 ended. Search finished for the next optimal point.\n", - "Time taken: 17.1803\n", - "Function value obtained: -24.9506\n", - "Current minimum: -25.7620\n", - "Iteration No: 73 started. Searching for the next optimal point.\n" + "Iteration No: 7 ended. Evaluation done at random point.\n", + "Time taken: 7.8183\n", + "Function value obtained: -0.0000\n", + "Current minimum: -14.2442\n", + "Iteration No: 8 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:01:12,583\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:50:04,221\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 73 ended. Search finished for the next optimal point.\n", - "Time taken: 25.0919\n", - "Function value obtained: -24.0691\n", - "Current minimum: -25.7620\n", - "Iteration No: 74 started. Searching for the next optimal point.\n" + "Iteration No: 8 ended. Evaluation done at random point.\n", + "Time taken: 8.2861\n", + "Function value obtained: -13.5701\n", + "Current minimum: -14.2442\n", + "Iteration No: 9 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:01:37,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:50:12,548\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 74 ended. Search finished for the next optimal point.\n", - "Time taken: 17.7718\n", + "Iteration No: 9 ended. Evaluation done at random point.\n", + "Time taken: 7.7770\n", "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 75 started. Searching for the next optimal point.\n" + "Current minimum: -14.2442\n", + "Iteration No: 10 started. Evaluating function at random point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:01:55,568\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:50:20,324\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 75 ended. Search finished for the next optimal point.\n", - "Time taken: 18.1646\n", + "Iteration No: 10 ended. Evaluation done at random point.\n", + "Time taken: 7.7843\n", "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 76 started. Searching for the next optimal point.\n" + "Current minimum: -14.2442\n", + "Iteration No: 11 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:02:13,760\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:50:28,088\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 76 ended. Search finished for the next optimal point.\n", - "Time taken: 17.6818\n", - "Function value obtained: -24.4948\n", - "Current minimum: -25.7620\n", - "Iteration No: 77 started. Searching for the next optimal point.\n" + "Iteration No: 11 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0924\n", + "Function value obtained: -0.8730\n", + "Current minimum: -14.2442\n", + "Iteration No: 12 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:02:31,537\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:50:36,165\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 77 ended. Search finished for the next optimal point.\n", - "Time taken: 21.9875\n", - "Function value obtained: -24.4039\n", - "Current minimum: -25.7620\n", - "Iteration No: 78 started. Searching for the next optimal point.\n" + "Iteration No: 12 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9161\n", + "Function value obtained: -13.7361\n", + "Current minimum: -14.2442\n", + "Iteration No: 13 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:02:53,520\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:50:44,129\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 78 ended. Search finished for the next optimal point.\n", - "Time taken: 17.7110\n", - "Function value obtained: -25.4551\n", - "Current minimum: -25.7620\n", - "Iteration No: 79 started. Searching for the next optimal point.\n" + "Iteration No: 13 ended. Search finished for the next optimal point.\n", + "Time taken: 9.0523\n", + "Function value obtained: -13.9624\n", + "Current minimum: -14.2442\n", + "Iteration No: 14 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:03:11,225\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:50:53,204\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 79 ended. Search finished for the next optimal point.\n", - "Time taken: 17.7361\n", - "Function value obtained: -24.0056\n", - "Current minimum: -25.7620\n", - "Iteration No: 80 started. Searching for the next optimal point.\n" + "Iteration No: 14 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6467\n", + "Function value obtained: -14.4321\n", + "Current minimum: -14.4321\n", + "Iteration No: 15 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:03:28,984\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:51:01,902\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 80 ended. Search finished for the next optimal point.\n", - "Time taken: 19.8734\n", - "Function value obtained: -24.5530\n", - "Current minimum: -25.7620\n", - "Iteration No: 81 started. Searching for the next optimal point.\n" + "Iteration No: 15 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7355\n", + "Function value obtained: -9.5334\n", + "Current minimum: -14.4321\n", + "Iteration No: 16 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:03:48,772\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:51:10,570\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 81 ended. Search finished for the next optimal point.\n", - "Time taken: 17.3307\n", - "Function value obtained: -23.9856\n", - "Current minimum: -25.7620\n", - "Iteration No: 82 started. Searching for the next optimal point.\n" + "Iteration No: 16 ended. Search finished for the next optimal point.\n", + "Time taken: 7.9293\n", + "Function value obtained: -3.9556\n", + "Current minimum: -14.4321\n", + "Iteration No: 17 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:04:05,967\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:51:18,507\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 82 ended. Search finished for the next optimal point.\n", - "Time taken: 17.2184\n", - "Function value obtained: -25.0607\n", - "Current minimum: -25.7620\n", - "Iteration No: 83 started. Searching for the next optimal point.\n" + "Iteration No: 17 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0527\n", + "Function value obtained: -0.0000\n", + "Current minimum: -14.4321\n", + "Iteration No: 18 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:04:23,417\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:51:26,652\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 83 ended. Search finished for the next optimal point.\n", - "Time taken: 16.7710\n", - "Function value obtained: -1.3204\n", - "Current minimum: -25.7620\n", - "Iteration No: 84 started. Searching for the next optimal point.\n" + "Iteration No: 18 ended. Search finished for the next optimal point.\n", + "Time taken: 8.0973\n", + "Function value obtained: -0.0135\n", + "Current minimum: -14.4321\n", + "Iteration No: 19 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:04:40,159\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:51:34,749\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 84 ended. Search finished for the next optimal point.\n", - "Time taken: 19.7425\n", - "Function value obtained: -24.2707\n", - "Current minimum: -25.7620\n", - "Iteration No: 85 started. Searching for the next optimal point.\n" + "Iteration No: 19 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8475\n", + "Function value obtained: -0.0000\n", + "Current minimum: -14.4321\n", + "Iteration No: 20 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:05:00,460\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:51:43,493\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 85 ended. Search finished for the next optimal point.\n", - "Time taken: 22.5330\n", - "Function value obtained: -24.3694\n", - "Current minimum: -25.7620\n", - "Iteration No: 86 started. Searching for the next optimal point.\n" + "Iteration No: 20 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6437\n", + "Function value obtained: -13.9815\n", + "Current minimum: -14.4321\n", + "Iteration No: 21 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:05:22,969\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:51:52,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 86 ended. Search finished for the next optimal point.\n", - "Time taken: 25.0221\n", - "Function value obtained: -24.8173\n", - "Current minimum: -25.7620\n", - "Iteration No: 87 started. Searching for the next optimal point.\n" + "Iteration No: 21 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1441\n", + "Function value obtained: -0.0000\n", + "Current minimum: -14.4321\n", + "Iteration No: 22 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:05:48,384\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:52:00,312\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 87 ended. Search finished for the next optimal point.\n", - "Time taken: 19.2994\n", - "Function value obtained: -25.0125\n", - "Current minimum: -25.7620\n", - "Iteration No: 88 started. Searching for the next optimal point.\n" + "Iteration No: 22 ended. Search finished for the next optimal point.\n", + "Time taken: 8.5943\n", + "Function value obtained: -0.0000\n", + "Current minimum: -14.4321\n", + "Iteration No: 23 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:06:06,718\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:52:08,915\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 88 ended. Search finished for the next optimal point.\n", - "Time taken: 18.0873\n", - "Function value obtained: -24.0236\n", - "Current minimum: -25.7620\n", - "Iteration No: 89 started. Searching for the next optimal point.\n" + "Iteration No: 23 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1905\n", + "Function value obtained: -13.9271\n", + "Current minimum: -14.4321\n", + "Iteration No: 24 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:06:24,846\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:52:17,098\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 89 ended. Search finished for the next optimal point.\n", - "Time taken: 18.2515\n", - "Function value obtained: -24.9301\n", - "Current minimum: -25.7620\n", - "Iteration No: 90 started. Searching for the next optimal point.\n" + "Iteration No: 24 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8385\n", + "Function value obtained: -13.3206\n", + "Current minimum: -14.4321\n", + "Iteration No: 25 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:06:43,088\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:52:25,965\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 90 ended. Search finished for the next optimal point.\n", - "Time taken: 18.4844\n", - "Function value obtained: -24.4818\n", - "Current minimum: -25.7620\n", - "Iteration No: 91 started. Searching for the next optimal point.\n" + "Iteration No: 25 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7661\n", + "Function value obtained: -13.6458\n", + "Current minimum: -14.4321\n", + "Iteration No: 26 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:07:01,680\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:52:34,730\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 91 ended. Search finished for the next optimal point.\n", - "Time taken: 17.5678\n", - "Function value obtained: -24.8025\n", - "Current minimum: -25.7620\n", - "Iteration No: 92 started. Searching for the next optimal point.\n" + "Iteration No: 26 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7579\n", + "Function value obtained: -13.8530\n", + "Current minimum: -14.4321\n", + "Iteration No: 27 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:07:19,155\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:52:43,478\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 92 ended. Search finished for the next optimal point.\n", - "Time taken: 19.2867\n", - "Function value obtained: -24.6682\n", - "Current minimum: -25.7620\n", - "Iteration No: 93 started. Searching for the next optimal point.\n" + "Iteration No: 27 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6986\n", + "Function value obtained: -14.1390\n", + "Current minimum: -14.4321\n", + "Iteration No: 28 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:07:38,449\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:52:52,188\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 93 ended. Search finished for the next optimal point.\n", - "Time taken: 17.9912\n", - "Function value obtained: -24.4891\n", - "Current minimum: -25.7620\n", - "Iteration No: 94 started. Searching for the next optimal point.\n" + "Iteration No: 28 ended. Search finished for the next optimal point.\n", + "Time taken: 8.7337\n", + "Function value obtained: -14.7883\n", + "Current minimum: -14.7883\n", + "Iteration No: 29 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:07:57,432\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:53:00,945\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 94 ended. Search finished for the next optimal point.\n", - "Time taken: 20.2703\n", - "Function value obtained: -24.1971\n", - "Current minimum: -25.7620\n", - "Iteration No: 95 started. Searching for the next optimal point.\n" + "Iteration No: 29 ended. Search finished for the next optimal point.\n", + "Time taken: 8.4861\n", + "Function value obtained: -13.6805\n", + "Current minimum: -14.7883\n", + "Iteration No: 30 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:08:16,715\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:53:09,425\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 95 ended. Search finished for the next optimal point.\n", - "Time taken: 18.3892\n", - "Function value obtained: -23.2317\n", - "Current minimum: -25.7620\n", - "Iteration No: 96 started. Searching for the next optimal point.\n" + "Iteration No: 30 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1717\n", + "Function value obtained: -14.0910\n", + "Current minimum: -14.7883\n", + "Iteration No: 31 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:08:35,174\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:53:18,584\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 96 ended. Search finished for the next optimal point.\n", - "Time taken: 18.0607\n", - "Function value obtained: -0.0000\n", - "Current minimum: -25.7620\n", - "Iteration No: 97 started. Searching for the next optimal point.\n" + "Iteration No: 31 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6759\n", + "Function value obtained: -13.8217\n", + "Current minimum: -14.7883\n", + "Iteration No: 32 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:08:53,207\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:53:27,310\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 97 ended. Search finished for the next optimal point.\n", - "Time taken: 17.9907\n", - "Function value obtained: -24.7574\n", - "Current minimum: -25.7620\n", - "Iteration No: 98 started. Searching for the next optimal point.\n" + "Iteration No: 32 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8683\n", + "Function value obtained: -13.4420\n", + "Current minimum: -14.7883\n", + "Iteration No: 33 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:09:11,114\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:53:36,166\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 98 ended. Search finished for the next optimal point.\n", - "Time taken: 19.4152\n", - "Function value obtained: -25.0136\n", - "Current minimum: -25.7620\n", - "Iteration No: 99 started. Searching for the next optimal point.\n" + "Iteration No: 33 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6232\n", + "Function value obtained: -14.0526\n", + "Current minimum: -14.7883\n", + "Iteration No: 34 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:09:30,517\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:53:44,792\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 99 ended. Search finished for the next optimal point.\n", - "Time taken: 23.5589\n", - "Function value obtained: -24.5597\n", - "Current minimum: -25.7620\n", - "Iteration No: 100 started. Searching for the next optimal point.\n" + "Iteration No: 34 ended. Search finished for the next optimal point.\n", + "Time taken: 8.6967\n", + "Function value obtained: -14.3145\n", + "Current minimum: -14.7883\n", + "Iteration No: 35 started. Searching for the next optimal point.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-22 21:09:54,195\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-24 22:53:53,525\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Iteration No: 100 ended. Search finished for the next optimal point.\n", - "Time taken: 15.6735\n", - "Function value obtained: -24.6703\n", - "Current minimum: -25.7620\n", - "CPU times: user 1h 39min 42s, sys: 1h 20min 34s, total: 3h 17s\n", - "Wall time: 1h 24min 54s\n" - ] - } - ], - "source": [ - "%%time\n", - "\n", - "cr_gp3 = gp_minimize(cr_obj3, cr_space, n_calls = 100, verbose=True)\n", - "print(\"\\n--------------------\"*2)\n", - "esc_gp3 = gp_minimize(esc_obj3, log_esc_space, n_calls = 100, verbose=True)\n", - "print(\"\\n--------------------\"*2)\n", - "msy_gp3 = gp_minimize(msy_obj3, log_esc_space, n_calls = 100, verbose=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "fb84909e-3816-493a-b888-cb394c6beed6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "cr.: -32.02, [-0.383730004464649, 0.7853961999069485, 0.08034226735043051] \n", - "esc: -14.30, [0.06615357610240746]\n", - "msy: -25.76, [0.045615795667256265]\n", - "\n" + "Iteration No: 35 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8980\n", + "Function value obtained: -14.2506\n", + "Current minimum: -14.7883\n", + "Iteration No: 36 started. Searching for the next optimal point.\n" ] - } - ], - "source": [ - "print(f\"\"\"\n", - "cr.: {cr_gp3.fun:.2f}, {cr_gp3.x} \n", - "esc: {esc_gp3.fun:.2f}, {esc_gp3.x}\n", - "msy: {msy_gp3.fun:.2f}, {msy_gp3.x}\n", - "\"\"\")" - ] - }, - { - "cell_type": "markdown", - "id": "624c8d13-95cd-402c-a61f-18e497194db6", - "metadata": {}, - "source": [ - "## Saving models" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "9196be9f-11aa-4a9e-8e41-718bcec76091", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "path = \"../saved_agents/results/\"\n", - "\n", - "def to_cr(log_polar_params):\n", - " theta = log_polar_params[1]\n", - " radius = 10 ** log_polar_params[0]\n", - " x1 = np.sin(theta) * radius\n", - " x2 = np.cos(theta) * radius\n", - " y2 = log_polar_params[2]\n", - " return {'x1': x1, 'x2': x2, 'y2': y2}\n", - "\n", - "def to_esc(log_params):\n", - " return {'escapement': 10 ** log_params[0]}\n", - "\n", - "def to_msy(params):\n", - " return {'msy': params[0]}\n", - "\n", - "#\n", - "eval_env1 = AsmEnv(config=CONFIG1)\n", - "eval_env2 = AsmEnv(config=CONFIG2)\n", - "eval_env3 = AsmEnv(config=CONFIG3)\n", - "\n", - "# \n", - "cr1_fname = \"cr_case_1.pkl\"\n", - "cr1 = CautionaryRule(env=eval_env1, **to_cr(cr_gp1.x))\n", - "dump(cr1, path+cr1_fname)\n", - "\n", - "esc1_fname = \"esc_case_1.pkl\"\n", - "esc1 = ConstEsc(env=eval_env1, **to_esc(esc_gp1.x))\n", - "dump(esc1, path+esc1_fname)\n", - "\n", - "msy1_fname = \"msy_case_1.pkl\"\n", - "msy1 = Msy(env=eval_env1, **to_msy(msy_gp1.x))\n", - "dump(msy1, path+msy1_fname)\n", - "\n", - "# \n", - "cr2_fname = \"cr_case_2.pkl\"\n", - "cr2 = CautionaryRule(env=eval_env2, **to_cr(cr_gp2.x))\n", - "dump(cr2, path+cr2_fname)\n", - "\n", - "esc2_fname = \"esc_case_2.pkl\"\n", - "esc2 = ConstEsc(env=eval_env2, **to_esc(esc_gp2.x))\n", - "dump(esc2, path+esc2_fname)\n", - "\n", - "msy2_fname = \"msy_case_2.pkl\"\n", - "msy2 = Msy(env=eval_env2, **to_msy(msy_gp2.x))\n", - "dump(msy2, path+msy2_fname)\n", - "\n", - "# \n", - "cr3_fname = \"cr_case_3.pkl\"\n", - "cr3 = CautionaryRule(env=eval_env3, **to_cr(cr_gp3.x))\n", - "dump(cr3, path+cr3_fname)\n", - "\n", - "esc3_fname = \"esc_case_3.pkl\"\n", - "esc3 = ConstEsc(env=eval_env3, **to_esc(esc_gp3.x))\n", - "dump(esc3, path+esc3_fname)\n", - "\n", - "msy3_fname = \"msy_case_3.pkl\"\n", - "msy3 = Msy(env=eval_env3, **to_msy(msy_gp3.x))\n", - "dump(msy3, path+msy3_fname)\n", - "\n", - "\n", - "## Didn't work for the gp objects since I used a fn generator :(\n", - "\n", - "# cr1_fname = \"cr_case_1.pkl\"\n", - "# dump(cr_gp1, path+cr1_fname)\n", - "\n", - "# esc1_fname = \"esc_case_1.pkl\"\n", - "# dump(esc_gp1, path+esc1_fname)\n", - "\n", - "# msy1_fname = \"msy_case_1.pkl\"\n", - "# dump(msy_gp1, path+msy1_fname)\n", - "\n", - "# #\n", - "\n", - "# cr2_fname = \"cr_case_2.pkl\"\n", - "# dump(cr_gp2, path+cr2_fname)\n", - "\n", - "# esc2_fname = \"esc_case_2.pkl\"\n", - "# dump(esc_gp2, path+esc2_fname)\n", - "\n", - "# msy2_fname = \"msy_case_2.pkl\"\n", - "# dump(msy_gp2, path+msy2_fname)\n", - "\n", - "# #\n", - "\n", - "# cr3_fname = \"cr_case_3.pkl\"\n", - "# dump(cr_gp3, path+cr3_fname)\n", - "\n", - "# esc3_fname = \"esc_case_3.pkl\"\n", - "# dump(esc_gp3, path+esc3_fname)\n", - "\n", - "# msy3_fname = \"msy_case_3.pkl\"\n", - "# dump(msy_gp3, path+msy3_fname)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4df50600-c069-4974-a7fc-6630e13e8057", - "metadata": {}, - "outputs": [], - "source": [ - "esc3" - ] - }, - { - "cell_type": "markdown", - "id": "a5f554a4-dd95-4bff-bf24-d60ef1215cf5", - "metadata": {}, - "source": [ - "## Objective plots" - ] - }, - { - "cell_type": "markdown", - "id": "491ddf8b-9039-49d8-b027-7b7e89046f4a", - "metadata": {}, - "source": [ - "### 1" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "aa3f2db6-75b0-47aa-8c08-8511faf6290b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(esc_gp1)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "ad28edfe-c997-49c9-af07-9aec73462d50", - "metadata": {}, - "outputs": [ + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-24 22:54:02,380\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 36 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8348\n", + "Function value obtained: -13.8238\n", + "Current minimum: -14.7883\n", + "Iteration No: 37 started. Searching for the next optimal point.\n" + ] }, { - "data": { - "image/png": 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OpSO7rBYA4GZtiqVB3TGhr1OHvezW9ckZCwoKEBwcDEII7t+/jwEDBuD+/fuwsbHBpUuXYGdnxyguu8/cVKvVipuw+cwdHEjMBQDY8YywJKg73hjgAkN9OviPzVxcXJCWloaffvoJaWlpqKmpwdy5cxEWFgYTExPGcWly64CrD8qx4uc0Ra+xqQNd8eH4nvTyuwMxMDBAWFgYwsLC1BdTbZGodkcIwd7L2fjsdAZkBHC2MEHkZF8M62ar7apRbbBp0ybY29tjzpw5Svv37duH0tJSrFq1ilFcer3WQTVIpFj6Uyo+/U2e2K/5OePs0pdpYndAu3fvRo8ePZ7a7+Pjw7gDC8D2M7e/P9CxFkRpF4VV9Vjw/V+4VSiCvh4Ha8f3RPhgd3pbq4MqLi6GYwtjJ2xtbVFUVMQ4LruTm3rK/ZJqhH13DY+qxbAy42LnNH8EdrV+8Rsp1nJ1dUVCQgI8PDyU9ickJMDJyYlxXHYn9927QHg4EB0NeHtruzZad6tQiJn7klBR24ju9ubYFz4QLpa0m2hHN3/+fCxZsgQSiQSjRo0CAMTFxWHlypVYvnw547jsTu7aWuDqVfm2k0vOrUD4vuuoFjehj4sAB2YPgiWDcdIU+3zwwQcoLy/HO++8g8ZGeacjY2NjrFq1CmvWrGEcl93JTQEArmSWYe6Bv1AvkWKQuxX2hg8Aj97m0hkcDgdRUVFYt24dMjIyYGJigm7dusHIyEiluDS5We5WoRDzD8oTe1g3G+yZMQAmXDohgi4yNzfHwIED1RaPJjeL5VfUYXb0ddQ2SjHEyxrfzRoAIwOa2LqmtrYWkZGRiIuLw6NHjyCTKc968+DBA0Zx2Z3c7u7A99/Lt51MVV0jZu1PQmm1GD0ceNg1vT9NbB01b948/PHHH5gxYwYcHR3VdkuT3cltZQVMn67tWrS7BokU8w78hQeltXAUGGP/7IG0K6kO+/333/Hbb79hyJAhao3L7h5qpaXAzp3ybSdBCMGamJv4K7cSPGMDRM8eBEcB88EDFPtZWlrCyspK7XHZndz5+cDixfJtJxFzoxD/SymEvh4Hu6f3h7cDXbZW123YsAHr169HXZ16F19g92V5J5NTVov1J24BAJa80g2DvWy0XCOqPWzZsgVZWVmwt7eHu7s7DA2Vf4LduHGDUVya3CzR2CTD+0dSUNsoRYCHFd4ZSZdQ6ixeffVVjcSlyc0SX8TeQ1qBEAITQ2yd0q/DzppCtV1ERIRG4rL7NzePB4wZI9/qsCuZZdh9KQsAEDXZF04WtAGts6mqqsJ3332HNWvWoKKiAoD8clx3Zz/t1g04e1bbtdCoBokUq2NughDgP4O6IKQ3XTaps0lPT0dQUBAEAgFycnIwf/58WFlZISYmBnl5eTh48CCjuOw+c0ulgEgk3+qoby89QF5FHRz4xlg7vqe2q0NpwbJlyxAeHo779+/D+LFZfseNG4dLly4xjsvu5E5LAwQC+VYHPayqx874TADAmnE9YGbE7gspSjOuX7+OBQsWPLXf2dkZxcXFjOOyO7l13MbTGWiQyDDI3QqhfZkPyqc6NiMjI4hEoqf237t3D7a2zKfNosmtJYlZ5fgtvQh6HCAitBedIqkTCw0NxSeffAKJRAJAPgQ0Ly8Pq1atwuTJkxnHpcmtBU1SGT4+dRsAMC2gi2KReapz2rJlC2pqamBnZ4f6+noMHz4cXl5e4PF42LhxI+O49EeeFhy6loc7xdWwMDXE8tF0+qjOTiAQIDY2FpcvX0Z6ejpqamrg7++PoKAgleKyO7l9fYFHjwALC23XRG3qG6XYcUHeiLZ8dHc6VRKlMHToUAwdOlRt8did3IaGgAoNCmz0Y1IeymrEcLYwwdRBXbRdHUpLtm/f3upj33vvPUZlsDu5s7KApUuBrVuBrl21XRuVNUik+OYPeU+0RSO96BpendjWrVuVnpeWlqKurg4W/1ylVlVVwdTUFHZ2doyTm93fLqEQOHVKvtUBP13PR2m1GE4CY7ze30Xb1aG0KDs7W/HYuHEj+vXrh4yMDFRUVKCiogIZGRnw9/fHhg0bGJfB7uTWIeImKXbFy8/ab4/0AteA/ukpuXXr1mHHjh3wfmxufm9vb2zduhVr165lHJd+w9rJ0b8KUCxqgAPfGG8OoGdt6l9FRUVoamp6ar9UKkVJSQnjuDS524G4SYpdF+Ut5G+P6EonOqSUvPLKK1iwYIHSpAzJycl4++23Vbodxu7kdnYGtmyRbzuwY8mFeChsgB3PCFMGumq7OhTL7Nu3Dw4ODhgwYACMjIxgZGSEQYMGwd7eHt999x3juOxuLbe3B5Yt03YtVCKTEXz7p3ze6QXDu8LYkJ61KWW2trY4ffo07t27hzt37gAAevToge7du6sUl91n7spK4Oef5dsOKv7eI2SX1YJnbICp9KzNOu7u8qWPH39ERkYqHZOeno5hw4bB2NgYrq6u2Lx5s0bq0r17d4SGhiI0NFTlxAbYfubOzgbefBNITgYsLbVdG0b2Xc4BIJ+IgQ7pZKdPPvkE8+fPVzznPTbzj0gkwpgxYxAUFIRvvvkGN2/exJw5c2BhYYG33npLLeVLpVJER0c/c8WRCxcuMIpLv20adLe4Gpczy6DHAWYGumm7OtQz8Hg8ODg4tPjaoUOH0NjYiH379oHL5cLHxwepqan44osv1Jbc77//PqKjozF+/Hj07t27k6w40sHtT8gGAIT0dqDraLNYZGQkNmzYgC5dumDatGlYunQpDAzkqZGYmIiXX34ZXO6/YwCCg4MRFRWFyspKWKrhivLIkSM4evQoxo0bp3Ksx7U6ucViMcRiseJ5S4PLqX+V14gRkyKf3G7OEA8t10Y3PPmda25ZVsV7770Hf39/WFlZ4cqVK1izZg2KiorwxRdfAACKi4vh4aH8/8/e3l7xmjqSm8vlwstL/VNZt7pBbdOmTRAIBIqHq2s7NA6ZmAB+fvJtB3M4KQ+NTTL0cRGgv1vHbC9gG1dXV6Xv4KZNm1o8bvXq1U81kj35aG6VXrZsGUaMGIE+ffpg4cKF2LJlC3bs2KF0ItO05cuX48svvwQhRK1xOaSVEVs6c7u6ukIoFILP56u1Uh1dY5MMQ6Mu4FG1GNum9MOrfh37Pr22iUQiCAQC5OfnK33XnnXmLi0tRXl5+XNjenp6Kl1qN7t9+zZ69+6NO3fuwNvbGzNnzoRIJMLx48cVx1y8eBGjRo1CRUWFWs7ckyZNwsWLF2FlZQUfH5+nVhyJiYlhFLfVl+XquATqLE7fLMKjajHseEYY50unKlYXPp/fqhOJra0t47nHUlNToaenBzs7OwBAYGAg/u///g8SiUSRdLGxsfD29lZLYgOAhYUFJk2apJZYSghDQqGQACBCoZBpiBe7cYMQLle+7UAmfnWZuK36lWw/f0/bVdEJmvquXblyhWzdupWkpqaSrKws8sMPPxBbW1syc+ZMxTFVVVXE3t6ezJgxg9y6dYscOXKEmJqakt27d6u1LprA7tZyQoDGRvm2g7hVKERqfhUM9Tl0MgaWMzIywpEjR/DRRx9BLBbDw8MDS5cuxbLHekUKBAKcO3cOixYtQv/+/WFjY4P169er7TZYs6amJsTHxyMrKwvTpk0Dj8fDw4cPwefzYW5uzigmu5O7Azp0LQ8AEOzjAFse/RnDZv7+/rh69eoLj+vTpw/+/PNPjdUjNzcXISEhyMvLg1gsxujRo8Hj8RAVFQWxWIxvvvmGUVx2dz/tYKobJDiRKr/9Nf0l2mmFap33338fAwYMQGVlJUweuzM0adIkxMXFMY5Lz9xqdDylEHWNUnjZmSPAw0rb1aE6iD///BNXrlx5qvXe3d1dhxcC7NkTuHUL8PTUdk1eiBCCH67KL8nDArrQRQaoVpPJZJC2sB5eQUGBUj/3tmL3ZbmJCeDj0yE6sSTnVuJuSTVMDPXxmj+daYVqvTFjxmDbtm2K5xwOBzU1NYiIiFCpSyq7kzs3F5g3T75luR+uyusY2tcJAhPDFxxNUf/asmULEhIS0KtXLzQ0NGDatGmKS/KoqCjGcdl9WV5eDuzdC7zzDuDG3gaqitpGnL4pX40x7CV6+4tqGxcXF6SlpeHIkSOKFUfmzp2LsLAwpQa2tmJ3cncQP/+Vj0apvB95HxcLbVeH6oAMDAwwffp09cZUa7ROiBCCw0n/NqRRFBN3797Fjh07kJGRAQDo2bMnFi9ejB49ejCOye7f3B1A4oNy5JTXwdzIABPoGtsUA8eOHUPv3r2RnJyMvn37om/fvrhx4wZ8fX1x7NgxxnHZfea2twdWr5ZvWepwUj4A4FU/J5hy2f3npNhp5cqVWLNmDT755BOl/REREVi5ciXjNbrZfeZ2dgY2bWLt1MblNWKcvSVvSPsP7UdOMVRUVISZM2c+tX/69OkoKipiHJfdyV1dDcTHy7csFHOjEI1SGfq6CODjJNB2dagOasSIES32Xb98+TKGDRvGOC67ryPv3wdGjpTPfurvr+3aKHm8IY2etSlVhIaGYtWqVUhOTsZLL70EALh69Sp+/vlnfPzxxzh58qTSsa3V6plYntQ8O4ZGZ2K5cQPo35+VyX31QTmm7rkKM64+kv4viE5brEHt8l3TIj291l1AczicFrupPgv9RjLUfNae6OdME5tSyZPzlKsLu39zs1RlbSN+/6dH2jR6SU6pUUNDg9pisTu5DQ3lLeWG7OqrfexGARqlMvR25qO3M21Io1QjlUqxYcMGODs7w9zcHA8eyNeWW7duHfbu3cs4LruT29cXKCiQb1mCEIIfaUMapUYbN25EdHQ0Nm/erDSmu3fv3iqt8snu5Gaha9kVeFBaC1OuPib2Y+f9d6pjOXjwIPbs2YOwsDDo6/+7Cmzfvn0V86szwe7kvnkTcHGRb1lC0ZDWzwnmtCGNUoPCwsIWVxyRyWSQSCSM47I7uSUSoLBQvmWBCqWGNPYOQaU6ll69erXYieWXX36Bn58f47j01NMGMY81pPm60IY0Sj3Wr1+PWbNmobCwEDKZDDExMbh79y4OHjyIX3/9lXFcdp+5WeTxhjR61qbUaeLEiTh16hTOnz8PMzMzrF+/HhkZGTh16hRGjx7NOC49c7dSc0OaGVcfof3o0E5KvYYNG4bY2Fi1xmT3mbtbN+DiRflWy378Z7GB0H7OtCGN6hDY/S3l8YARI7RdC1TUNuLMLdojjVIfS0vLVk9/XVFRwagMdid3YSHw1VfA4sVaHdN9LFnekObrLKANaZRaPD6VcXl5OT799FMEBwcjMDAQAJCYmIizZ89i3bp1jMugo8JeQCYjGLUlHjnldfhski+m0XnS2p2ujwqbPHkyRo4cicWLFyvt/+qrr3D+/HmltcHbgt2/uVkgIatMMUfaRNqQRmnA2bNnERIS8tT+kJAQnD9/nnFcmtwv0LzYwGv+dGgnpRnW1tY4ceLEU/tPnDgBa2trxnHpt/U5ioUNOJ/xCABdtZPSnI8//hjz5s1DfHw8AgICAADXrl3DmTNn8O233zKOy+7ktrYG5s6Vb7XgcFIepDKCQR5W6G7PfEE2inqe8PBw9OzZE9u3b0dMTAwA+bzlly9fViQ7E+xuUNMiiVSGoVEXUCISY/t//BBK5yTXGl3/rmkKu39z19cDt2/Lt+0sLqMEJSIxbMy5CPFxaPfyKUpV7E7ujAygd2/5tp01r7X95gBXcA3Y/WeiqJbQb20LsstqcTmzDBwOnW2F6rhocreg+fbXSG87uFqZark2FMUMTe4n1IqbcPQv+fpfMwLp7S+q42L3rTAOB+By5dt2EpNSiOqGJnjYmGF4N9t2K5fqXF577bVWH9t8e6ytVE7uUlGD5m5P+PkBYrFmYreAEIIDV3IAADMD3aCn137/qFCdi0Cg+QFIKif3T9fz8aGLnTrqonUJmeXIfFQDM64+Xu/vou3qUDps//79Gi9D5d/cP/2VjwZJ69cvapOMDPlosHa6FRb9z1n79f4u4BmzayEEimorlc/clXUSHE8pxFRN3DKqrwdSUtqlE0teeR3i7pQAAGYOdtd4eRT1uF9++QVHjx5FXl4eGhsblV67ceMGo5hqaS3fl5ANhr1YWeNgYg4IAV7ubouutubarg7ViWzfvh2zZ8+Gvb09UlJSMGjQIFhbW+PBgwcYO3Ys47gqJ7cpVw/3SmpwObNM1VBaUytuwk//3P6aTc/aVDv7+uuvsWfPHuzYsQNcLhcrV65EbGws3nvvPQiFQsZxVU7uSX7yhqe9l7NVDaU1//vn9pe7tSmGd6e3v6j2lZeXh8GDBwMATExMUF1dDQCYMWMGDh8+zDiuyskd9lIXcDhA/N1SZD6qVjWcMg8P4OhR+VZDZDKi+Idp1mB3evuLancODg6KSRC7dOmCq1evAgCys1X7uatycnexMsPonvYAgH0JOaqGU2ZpCbzxhnyrIbEZJcguqwXf2ABvDnDVWDkU9SyjRo3CyZMnAQCzZ8/G0qVLMXr0aEyZMgWTJk1iHFctPdTmDPXAub9LEHOjACuDvWFhyn3xm1qjpAQ4dAgICwPs7dUT8wnfXpKvhTz9JTc6jRKlFXv27IFMJgMALFq0CNbW1rhy5QpCQ0OxYMECxnHV8m0O8LCCjxMftx+KcDgpH2+P6KqOsPKpjZcvl89droHkTs6txF+5lTDU5yCcNqRRWqKnpwc9vX8voqdOnYqpU6eqHlflCAA4HA5mD5H/Lj6YmAOJVKaOsBr33Z/ys/ar/ZxhxzfWcm0obdi4cSMGDx4MU1NTWFhYtHhMXl4exo8fD1NTU9jZ2eGDDz5AU1OT0jHx8fHw9/eHkZERvLy8EB0d/dxy09PTFWfr9PT05z6YUtt16IS+joj8PQNFwgacuVWMCSyflii3vBZnbstXEZn/sqeWa0NpS2NjI9544w0EBgZi7969T70ulUoxfvx4ODg44MqVKygqKsLMmTNhaGiIzz77DIC84Wv8+PFYuHAhDh06hLi4OMybNw+Ojo4IDg5usdx+/fqhuLgYdnZ26NevHzgcTouNZxwOB1Ipwx6ghCGhUEgAEKFQqNi3NfYucVv1K3l152WmYZUlJxMCyLdqtu74TeK26lcSvu+a2mNT6tXSd03d9u/fTwQCwVP7T58+TfT09EhxcbFi365duwifzydisZgQQsjKlSuJj4+P0vumTJlCgoODn1leTk4Okclkiv9+3oMptY7nDgtwA1dfDyl5VUjJq1Q9oEAATJgg36pRZW2jYsw2PWtTz5OYmAhfX1/YP9bmExwcDJFIhNu3byuOCQoKUnpfcHAwEhMTnxnXzc1NsVZYbm4unJ2d4ebmpvRwdnZGbm4u47q3OrnFYjFEIpHS40m2PCPF5fh+ddwW69oVOHlSvlWjA4k5aJDI0NuZj0BP7UybTLXdk98/cTsMBy4uLlZKbACK58XFxc89RiQSob4V4yJGjhzZ4mJ/QqEQI0eOZFr11if3pk2bIBAIFA9X15bvCc8e4g4AOH2zCEVCFQd8SCRAaal8qyaiBgn2/dNpZeHwrq1eaZHSPldXV6Xv4KZNm1o8bvXq1eBwOM993Llzp51r/2yEkBa/h+Xl5TAzM2Mct9UNamvWrMGyZcsUz0UiUYsJ3ttZgAAPK1zLrsD3iblYGdKDceVw86baFwI8eCUHooYmeNmZY2xvR7XEpNpHfn6+0sQgRkZGLR63fPlyhIeHPzeWp2frfo45ODggKSlJaV9JSYniteZt877Hj+Hz+TAxMXlm7ObZWDgcDsLDw5U+j1QqRXp6uqJbKhOtTm4jI6Nn/jGfNGeoB65lV+DQtTwsHuUFUy47OofUiJvw3T9n7XdHeUGfdjXtUPh8fqtm/bG1tYWtrXrGCAQGBmLjxo149OgR7Ozkk5LExsaCz+ejV69eimNOnz6t9L7Y2FjFcrzP0jwbCyEEPB5P6R8CLpeLl156CfPnz2dcd41kXVBPe7hbmyKnvA5Hr+cjfIjm+oa3xfeJuaiqk8DTxgz/rw+7b9VR7SMvLw8VFRXIy8uDVCpFamoqAMDLywvm5uYYM2YMevXqhRkzZmDz5s0oLi7G2rVrsWjRIsXJbuHChfjqq6+wcuVKzJkzBxcuXMDRo0fx22+/Pbfs/fv3K25/7dixA+bmah5qzLSZ/UW3Jw4m5hC3Vb+SIZFxRNIkZVaIGm+F1YolxO+Tc8Rt1a/kl7/yVY5HtR9N3gqbNWsWAfDU4+LFi4pjcnJyyNixY4mJiQmxsbEhy5cvJxKJRCnOxYsXSb9+/QiXyyWenp5k//79rSpfKpUSQ0NDcu/ePTV+KjmNXS+/0d8FW2PvoaCyHr+zoFPLoat5qKhthJu1KV1nm1KIjo5+YW8yNze3py67nzRixAikpKS0uXw9PT1069YN5eXl6NatW5vf/9zYao32GGNDfcz8Z97vPZceMBu61rcvIBTKtyqob5Ri9z8DRBaN9IKBPp2unWKPyMhIfPDBB7h165Za42r0Wz4z0B1GBnq4WShE4oPytgfQ1wf4fPlWBT9czUVZjRguliaY5OesUiyKUreZM2ciKSkJffv2hYmJCaysrJQeTGm0GdvKjIs3Brjgh6t52HPpAQZ3tWlbgPv3gcWLga++AhheslTVNWLHhfsAgPdGdYMhPWtTLLNt2zaNxNX4Pap5Qz1x6Foe4u+W4m5xNbwd2rCIfXU1cO6cfMvQVxcyIWpoQg8HHibTucgpFpo1a5ZG4mr8NOZuY6ZY33r3pSxNF6ckr7wOBxJzAABrxvWk97Up1mtoaHhhN+/Wapdr1AXD5X3DT6Q+RHZZbXsUCQDYfPYOJFKCYd1s6MSHFGvV1tZi8eLFsLOzg5mZGSwtLZUeTLVLcvdztcCoHnaQygi2xt5rjyKRkleJX9OLwOEAa8b2bJcyKYqJlStX4sKFC9i1axeMjIzw3Xff4eOPP4aTkxMOHjzIOG67tS4tH9MdAHAq/SHuFLfyUsPVVd6Y9oxBKs9CCMFnp+VLEE32d0EvJw0tVEhRanDq1Cl8/fXXmDx5MgwMDDBs2DCsXbsWn332GQ4dOsQ4brslt4+TAON9HUEIsOVcK8/etrbAokXybRucvlmM6zmVMDbUU/yjQlFsVVFRoRjIwufzFcM/hw4dikuXLjGO2673hZaO7g49DhD7dwnS8qte/IaKCuCHH+TbVqqsbUTESfkg+rde7gpHwbNH5VAUG3h6eiI7Wz6gqUePHjh69CgA+Rn9WfO6tUa7JreXnblihZLPz9198RtycoAZM+TbVtrw698oqxHDy84ci0aqd5IHitKE2bNnIy0tDYB8LPrOnTthbGyMpUuX4oMPPmAct93HYi4J6oaTaYX4834Zrj0oR4AaZ0K5cKcEMSmF0OMA/329D4wMVOvZRlHtYenSpYr/DgoKwp07d5CcnAwvLy/06dOHcdx2767lamWKKQPlDWQbT2egSU3TIAvrJVgTcxMAMHeoB/y6aG6VEopSB5lMhqioKAwZMgQDBw7E6tWrUV9fDzc3N7z22msqJTagheQG5N1AecYGSC8QYle8ejq2bDqdgRKRGB42Zlg+xlstMSlKkzZu3IgPP/wQ5ubmcHZ2xpdffolFixapLb5WktuOb4xPJvoAAL6Mu49bhc9YptTMDHjpJfn2Oc7dLsaR6/LZTKMm94GxIb0cp9jv4MGD+Prrr3H27FkcP34cp06dwqFDhxSLFahKa6MoXu3njLG9HdAkI1h2NBUNkhYmXvf2BhIT5dtnSM2vwntH5ONoZw9xxyAP5qNoKKo95eXlYdy4cYrnQUFB4HA4ePjwoVriay25ORwOPn21N2zMjXCvpAZfMOi5lltei7nR19EgkWF4d1t8OI72RKM6jqamJhgbKy9jZWhoCImaZvvV6syF1uZGiHzNF/MO/oVv/3yAUT3s8NLjrec3bjxz9tPyGjFm7UtCeW0jejvz8XWYPx3OSXUohJCnZj1taGjAwoULlaY0jomJYRRf69kQ1MseUwa4ghBgbvR1nLlV/ML3COslmHfwL+SU18HZwgT7wgfS5XepDmfWrFmws7NTmot9+vTpcHJyUtrHFCsyYt2EXsitqMXVBxVY+EMy3h3lhaVB3Z/6l4cQgpNpD7Hh1wyU1YghMDHEgTkDYcejK3RSHc/+/fs1Gp8VyW1uZIAf5gbgs9N3sC8hGzsuZOJWoRAr7erQE0BpdQMqiqux4de/cTmzDADgaWuGrW/2g5ddGyZ/oKhOhBXJDQAG+npYP6EXfF34WH3sJi7eLcWjPzLxG4Dw/ddx20G+sKCRgR7eHeWF+S970h5oFPUcHMJoWlL5ckICgQBCobBVq0C0xa1CobyPeJkQZo+KkGlkiTo9Q4zwtsXHoT5ws2a+fhLV8Wjyu6bLWHPmflxvZwF+WvDvUiyEEDTJCG0Np6g2YHe2ZGcD06eDk5NDE5ui2ojdGVNZCRw6JN9SFNUm7E5uiqIYo8lNUTqKcYNacyO7KvMqv1BNzb9bTZZDsVrzd4zhjZ1Oi3FyV/+zCohrG2cmZWT4cM2XQbFedXW1St0xOxvG97llMhkePnwIHo8HDoeu5EFpDiEE1dXVcHJygp4e/SXZWoyTm6IodqP/DFKUjqLJTVE6iiY3RekomtwUpaNoclOUjqLJTVE6iiY3Remo/w+CfS5gj8FxQAAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(msy_gp1)" - ] - }, - { - "cell_type": "markdown", - "id": "5fbd99bb-d5c0-4cc7-a8d8-57ae7410623d", - "metadata": {}, - "source": [ - "### 2" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "7c5d3b9c-d627-4851-89cf-f8769818e184", - "metadata": {}, - "outputs": [ + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-24 22:54:11,253\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 37 ended. Search finished for the next optimal point.\n", + "Time taken: 8.9657\n", + "Function value obtained: -14.5724\n", + "Current minimum: -14.7883\n", + "Iteration No: 38 started. Searching for the next optimal point.\n" + ] }, { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(cr_gp2)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "8f177fb6-d527-4367-bc55-080f4116bbc1", - "metadata": {}, - "outputs": [ + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-24 22:54:20,220\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 38 ended. Search finished for the next optimal point.\n", + "Time taken: 9.1209\n", + "Function value obtained: -13.9084\n", + "Current minimum: -14.7883\n", + "Iteration No: 39 started. Searching for the next optimal point.\n" + ] }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_objective(esc_gp2)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "20647c64-7ab3-47c4-a0e8-5b7f4b7a9e2c", - "metadata": {}, - "outputs": [ + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-24 22:54:29,333\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 39 ended. Search finished for the next optimal point.\n", + "Time taken: 8.8265\n", + "Function value obtained: -14.1652\n", + "Current minimum: -14.7883\n", + "Iteration No: 40 started. Searching for the next optimal point.\n" + ] }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-24 22:54:38,131\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Iteration No: 40 ended. Search finished for the next optimal point.\n", + "Time taken: 8.1129\n", + "Function value obtained: -14.0068\n", + "Current minimum: -14.7883\n" + ] } ], "source": [ - "plot_objective(msy_gp2)" - ] - }, - { - "cell_type": "markdown", - "id": "41607833-e11a-4ca1-8a8c-b478cc811894", - "metadata": {}, - "source": [ - "### 3" + "esc_gp2 = gp_minimize(const_act_esc_obj, [(-1.,1.)], n_calls = NCALLS, verbose=True)" ] }, { "cell_type": "code", - "execution_count": 22, - "id": "1636f3ff-2f3c-4563-a4b1-139e67a28cbf", - "metadata": {}, + "execution_count": 8, + "id": "68d8ba12-c8fe-468d-b831-66d954006dba", + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { "text/plain": [ - "" + "([-0.9388866114029923], -14.788338827246875)" ] }, - "execution_count": 22, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "plot_objective(esc_gp3)" + "ca_agent = ConstAct(env=AsmEnvEsc(config=CONFIG), action=esc_gp2.x[0])" ] }, { "cell_type": "code", - "execution_count": 24, - "id": "f9415caa-168f-4177-8ba8-970ebb57322f", + "execution_count": 10, + "id": "f28c880a-5c90-4343-b8a1-15ebd3aaaace", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "1.5278347149251914" ] }, - "execution_count": 24, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ - "plot_objective(msy_gp3)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "78583c73-cb01-47a9-a338-bb28fb813dc4", - "metadata": {}, - "outputs": [], - "source": [ - "cr_gp1" + "ca_agent.action_to_escapement(ca_agent.action)" ] }, { "cell_type": "code", "execution_count": null, - "id": "21893d39-3aa1-48b5-8677-6ac836cabc42", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b041ad87-48c7-4c85-80f1-86f33891f3c2", + "id": "960ca82c-bf56-4e6a-929d-9dec1fae50e5", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/result_plots.ipynb b/notebooks/result_plots.ipynb index 4d394e4..50bd6fb 100644 --- a/notebooks/result_plots.ipynb +++ b/notebooks/result_plots.ipynb @@ -13,20 +13,30 @@ "\n", "from plotnine import ggplot, aes, geom_density, geom_line, geom_point\n", "\n", - "from rl4fisheries import AsmEnv, AsmEnvEsc, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries import AsmEnv, AsmEnvEsc, Msy, ConstEsc, ConstAct, CautionaryRule\n", "from rl4fisheries.envs.asm_fns import get_r_devs, observe_total" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 33, "id": "2119a088-27b1-490f-9114-23c4e3f69ca6", "metadata": {}, "outputs": [], "source": [ "def nat_units(obs, env):\n", - " biomass = env.bound * (obs[0] + 1) / 2\n", - " mwt = MINWT + (MAXWT - MINWT) * (obs[1]+1)/2\n", + " if len(obs) == 2:\n", + " biomass = env.bound * (obs[0] + 1) / 2\n", + " mwt = MINWT + (MAXWT - MINWT) * (obs[1]+1)/2\n", + " elif (len(obs)==1) and (env.observation == 'mwt'):\n", + " biomass = 0 \n", + " mwt = MINWT + (MAXWT - MINWT) * (obs[0]+1)/2\n", + " \n", + " else:\n", + " biomass = 0\n", + " mwt = 0\n", + " # placeholder\n", + " \n", " return biomass, mwt\n", "\n", "#\n", @@ -77,7 +87,7 @@ " ray.shutdown()\n", " return rews\n", "\n", - "def eval_pol(policy, env_cls, config, n_batches=1, batch_size=300, pb=False):\n", + "def eval_pol(policy, env_cls, config, n_batches=1, batch_size=400, pb=False):\n", " batch_iter = range(n_batches)\n", " if pb:\n", " from tqdm import tqdm\n", @@ -124,7 +134,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 100, "id": "81938413-d860-4195-b5dc-12bc110e39ba", "metadata": {}, "outputs": [], @@ -133,12 +143,14 @@ "\n", "ppoAgent1 = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10.zip', device='cpu')\n", "ppoAgent2 = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10-run2.zip', device='cpu')\n", - "ppoAgentEsc = PPO.load('../saved_agents/results/PPO-AsmEnvEsc-results-trophy-nage-10.zip', device='cpu')" + "ppoAgentEsc = PPO.load('../saved_agents/results/PPO-AsmEnvEsc-results-trophy-nage-10.zip', device='cpu')\n", + "ppoAgent1obs_mwt = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10-mwt_obs-hyperpars-run2.zip', device='cpu')\n", + "ppoAgent1obs = PPO.load('../saved_agents/results/PPO-AsmEnv-results-trophy-nage-10-1obs-hyperpars.zip', device='cpu')" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 5, "id": "9142ccb9-82fb-4d68-84fb-2ea76215e200", "metadata": {}, "outputs": [], @@ -154,7 +166,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 6, "id": "99ed7e7d-8a48-4a4f-89eb-5e01718a8fec", "metadata": {}, "outputs": [], @@ -186,20 +198,23 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 103, "id": "52f366c2-1879-4954-9800-ec97f85f364e", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "2024-05-24 02:11:00,452\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-24 02:11:14,730\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-24 02:11:22,206\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-24 02:11:29,520\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-24 02:11:37,095\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-05-24 02:11:51,035\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-05-28 23:37:17,887\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-28 23:37:25,861\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-28 23:37:33,877\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-28 23:37:41,544\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-28 23:37:56,622\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-28 23:38:11,482\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-05-28 23:38:26,744\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], @@ -222,12 +237,26 @@ ")\n", "ppoAgent2_rews = eval_pol(\n", " policy=ppoAgent2, env_cls=AsmEnv, config=CONFIG3\n", + ")\n", + "ppoAgent1obs_mwt_rews = eval_pol(\n", + " policy=ppoAgent1obs_mwt, env_cls=AsmEnv, config={\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " **CONFIG3\n", + " }\n", + ")\n", + "ppoAgent1obs_rews = eval_pol(\n", + " policy=ppoAgent1obs, env_cls=AsmEnv, config={\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " **CONFIG3\n", + " }\n", ")" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 104, "id": "7b5b2627-ca46-419c-86a2-60d8911dee99", "metadata": {}, "outputs": [], @@ -262,29 +291,41 @@ " 'agent': 'ppo_esc',\n", "})\n", "\n", + "ppo_mwt_rews_df = pd.DataFrame({\n", + " 'rew': ppoAgent1obs_mwt_rews,\n", + " 'agent': 'ppo_mwt',\n", + "})\n", + "\n", + "ppo_1obs_rews_df = pd.DataFrame({\n", + " 'rew': ppoAgent1obs_rews,\n", + " 'agent': 'ppo_1obs',\n", + "})\n", + "\n", "rews_df_case3 = pd.concat(\n", - " [cr_rews_df, esc_rews_df, msy_rews_df, ppo1_rews_df, ppo2_rews_df, ppoEsc_rews_df]\n", + " [cr_rews_df, esc_rews_df, msy_rews_df, ppo1_rews_df, ppo2_rews_df, ppoEsc_rews_df, ppo_mwt_rews_df, ppo_1obs_rews_df]\n", ")" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 105, "id": "44484162-7774-425d-9447-82f178faf9b2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(32.120517542052035,\n", - " 13.716304965534043,\n", - " 23.867732405070303,\n", - " 38.70609230040449,\n", - " 51.815898659947536,\n", - " 56.49522702267767)" + "(31.08607231085893,\n", + " 13.141327710588053,\n", + " 24.952381511804543,\n", + " 34.11284129268802,\n", + " 50.61623440882353,\n", + " 53.00837814723987,\n", + " 36.304620193349116,\n", + " 12.963944229322747)" ] }, - "execution_count": 10, + "execution_count": 105, "metadata": {}, "output_type": "execute_result" } @@ -298,18 +339,20 @@ " np.mean(ppo1_rews_df.rew),\n", " np.mean(ppo2_rews_df.rew),\n", " np.mean(ppoEsc_rews_df.rew),\n", + " np.mean(ppo_mwt_rews_df.rew),\n", + " np.mean(ppo_1obs_rews_df.rew),\n", ")" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 106, "id": "495142e1-2607-4168-986e-aee3163f96ad", "metadata": {}, "outputs": [ { "data": { - "image/png": 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QIsztv3FxkerRs02T1khvnyRJ2rlzp8fqAgAAAAAA3kUACISIJUuWSJJOH5Ch8HBbk9ZoTwAIAAAAAEDAIQAEQsDhw4e1ceNGSU3b/msyOwB//vlnOZ1OT5QGAAAAAAC8jAAQCAFVz/8bdGZWk9cxA8Bjx44pLy+v2XUBAAAAAADvIwAEQoB5/l90dIR69W7b5HXMAFBydQECAAAAAAD/RwAIhAAzAOw/oL0iI8ObvE56eqL7MQEgAAAAAACBgQAQCHL5+fnasGGDJGnQoA7NWqtdeqIMw5DEIBAAAAAAAAIFASAQ5JYtW+Ye2HFGMwPAqKgItWwVL4kAEAAAAACAQEEACAS5JUuWSJIiI8PVt396s9dLTz8xCRgAAAAAAPg/AkAgyJnn//Xtl66oqIhmr5fePlESASAAAAAAAIGCABAIYkePHtXatWslSYPO7OCRNc1JwLt371ZFRYVH1gQAAAAAAN5DAAgEseXLl7tDujM8FAC2z0iWJDkcDu3bt88jawIAAAAAAO8hAASCmLn9Nzw8TP1Pb++RNdPbJbof79q1yyNrAgAAAAAA7yEABILYokWLJEm9+7RTTEykR9Zs1drufrx3716PrAkAAAAAALyHABAIUkVFRVq9erUkz23/laoHgGwBBgAAAADA/xEAAkFq6dKlcjgckqRBZ2Z5bN3o6AglJsZIogMQAAAAAIBAQAAIBKmvv/5akmSzhen0ARkeXbtVK1cXIAEgAAAAAAD+jwAQCFJmANi7Tzu1aBHl0bVbHt8GnJOT49F1AQAAAACA5xEAAkGosLBQy5cvlyQNGtzB4+u3Ph4AcgYgAAAAAAD+jwAQCELLly93n/83eHBHj6/fqkoAWFlZ6fH1AQAAAACA5xAAAkFo0aJFkqTw8DD1H9De4+ubZwCWlZUpNzfX4+sDAAAAAADPIQAEgtDChQslSX36pisuzrPn/0lS6zZ292MGgQAAAAAA4N8IAIEgc+zYMa1evVqSdObgLK+8h9kBKHEOIAAAAAAA/o4AEAgyy5cvV3l5uSTpzCFeCgBbnwgAmQQMAAAAAIB/IwAEgsy3334rSYqIsOn0ARleeY/ExBhFRoZLYgswAAAAAAD+jgAQCDLmAJB+/dsrJibSK+9hGIb7HEACQAAAAAAA/BsBIBBEDh8+7D7/b+hZnb36XuY5gASAAAAAAAD4NwJAIIhkZ2fL6XRKkkaM7ObV92rVOl4SASAAAAAAAP6OABAIIl999ZUkKSEhRn37tffqe7Vs6eoA3L9/v1ffBwAAAAAANA8BIBAknE6nvv76a0nSWWd3ls3m3ds7La2FJOnIkSMqLS316nsBAAAAAICmIwAEgsTGjRvd3XhnDffu+X+SlJLawv340KFDXn8/AAAAAADQNASAQJAwt/9K0tkjunj9/cwOQEk6ePCg198PAAAAAAA0DQEgECTM7b/durVyT+j1ptQqAeCBAwe8/n4AAAAAAKBpCACBIHDs2DEtXbpUkm+6/yQpNZUAEAAAAACAQEAACASBb7/9Vg6HQ5LvAsDEpFj3oBECQAAAAAAA/BcBIBAEPv/8c0lSXIsoDRiQ4ZP3tNnClJwcK4kAEAAAAAAAf0YACAS48vJyzZkzR5I08pyuiowK99l7m+cAMgQEAAAAAAD/RQAIBLhly5YpNzdXkjR6zGk+fW/zHEA6AAEAAAAA8F8EgECAM7f/RkTaNNxH5/+ZUtPiJdEBCAAAAACAPyMABAKY0+nUZ599JkkaOqyTWsRH+/T9U1PjJNEBCAAAAACAPyMABALYqlWrtGvXLkm+3/4rnegAPHr0qIqLi33+/gAAAAAA4NQIAIEA9sEHH0iSIiJsGjO2h8/fP+34EBCJbcAAAAAAAPgrAkAgQJWXl+ujjz6SJA0f0UWJibE+ryEl9UQAyDZgAAAAAAD8EwEgEKC+/fZbd9fdxZf0saQGOgABAAAAAPB/BIBAgJoxY4YkKS4uUuec182SGugABAAAAADA/xEAAgGooKBAs2fPliSNPr+HYmIiLakjISFaERE2SXQAAgAAAADgrwgAgQA0Y8YM99Tdq3450LI6wsLClJwSJ4kOQAAAAAAA/BUBIBBgnE6n3nzzTUlSp85pGjAww9J6kpNdw0dyc3MtrQMAAAAAANSOABAIMGvXrtWGDRskSVdePUCGYVhaT3KyqwOQABAAAAAAAP9EAAgEmFdeeUWSFBFp06W/6GdtMZJ7CzABIAAAAAAA/okAEAgg+/bt08yZMyVJF4/v4+6+sxIdgAAAAAAA+DcCQCCAvP7663I4HJKkX904xOJqXMwzAA8fPqzKykqLqwEAAAAAACcjAAQCRFFRkd544w1J0uAhWTqtRxuLK3JJOt4BWFFRoSNHjlhbDAAAAAAAqIEAEAgQU6dOdW+zvfGmYRZXc4J5BqDENmAAAAAAAPwRASAQAEpKSvT8889Lkrqf1lojz+1qcUUnVD2H8NChQxZWAgAAAAAAakMACASAd955R/v27ZMk3f7bETIMw+KKTjDPAJToAAQAAAAAwB8RAAJ+zuFw6L///a8kqVPnNJ1/QQ+LK6ouKZktwAAAAAAA+DMCQMDPvffee9q9e7ck6bY7hisszL9u24SEaNlsrprYAgwAAAAAgP/xryQBQDXl5eV69tlnJUkZmckad3FviyuqKSwsTImJMZLoAAQAAAAAwB8RAAJ+bNasWdq+fbsk6dbbhys83GZxRbUzJwETAAIAAAAA4H8IAAE/5XQ63Wf/tWmboEsu62txRXUzJwETAAIAAAAA4H8IAAE/9eWXX2rjxo2SpJtuHqbIyHCLK6qbOQmYMwABAAAAAPA/BICAnzK7/xKTYnXF1QMsrqZ+SXQAAgAAAADgtwgAAT+0fPlyLV26VJJ0/a/OVGxspMUV1a/qGYBOp9PiagAAAAAAQFUEgIAfmjRpkiQpJiZCE24YbHE1p2aeAehwOHT06FGLqwEAAAAAAFURAAJ+ZseOHfriiy8kSVf9cqCSkmItrujUzDMAJc4BBAAAAADA3xAAAn5m2rRp7sfX/8r/u/+kE1uAJc4BBAAAAADA3xAAAn7E4XDo7bffliQNHdZJGZnJFlfUMFW7FA8fPmxhJQAAAAAA4GQEgIAf+eKLL3Tw4EFJ0i+vHWhxNQ2XSAAIAAAAAIDfIgAE/IjZ/ZeSEqdzR3W3uJqGS0o8EQAeOXLEukIAAAAAAEAN4VYXAN+w2WwBsWYoO3LkiBYsWCBJuviSvoqKimjyWoZhVPt/b4uKjlBsbKSKisp05MgRfm80AV8z/2V+b/geBRa+X/6Leyrw8L3yX9xPgYnvFwArEACGiKSkJI+uZ7PZPL5mqPvoo49UXl4uSRp/aX9FREQ2e83w8KaHiI2VlBSroqIyFRYW8nujkbifAoPdbre6BDQQ91Rg4J4KDNxPgYH7KXBwTwGwCgFgiMjLy/PIOna7XTabTRUVFSooKPDImnAxt/+2aZugXr1by+Eoa/JahmEoPDxC5eUOOZ1OT5VYr4TEGO3Zc0R79+712O+3YMf9FBhsNpvsdrsKCgpUUVFhdTmoB/dUYOCeCgzcT4GB+ylwcE95DgEq0DQEgCHCG/9BwH9keE5eXp57++/YC3pKkkeCO6fT6bMAMPH4OYCHDx/m90YT8DXzfxUVFXyfAgjfK//HPRU4+D75P+6nwML3CoAVGAIC+IG5c+e6t/9eMK6XxdU0TWJSjCTPdZsCAAAAAADPIAAE/MDXX38tSUpNbaE+fdtZXE3TVO0ABAAAAAAA/oMAELBYZWWlvvnmG0nS0LM6KSwsMG/LxEQ6AAEAAAAA8EeBmTQAQeT777/XwYMHJUnDzupkcTVNl5jk6gAsKSlRUVGRxdUAAAAAAAATASBgMXP4hyQNO7uzdYU0k7kFWKILEAAAAAAAf0IACFgsOztbktStWyu1bBlvcTVNZ3YASpwDCAAAAACAPyEABCxUXFyspUuXSnKd/xfIko6fAShJR44csa4QAAAAAABQDQEgYKF169aptLRUkjR4aEeLq2keOgABAAAAAPBPBICAhVauXOl+3K9/ewsrab6qASBnAAIAAAAA4D8IAAELrVixQpLUoUOKkqoEaIEoPj5KYWGGJDoAAQAAAADwJwSAgIXMDsC+/dMtrqT5wsLClHD8HEA6AAEAAAAA8B8EgIBFcnJylJOTIynwt/+aEhNdXYx0AAIAAAAA4D8IAAGLmNt/Jan/6cERAJrbmOkABAAAAADAfxAAAhYxt/9GR0eoa7dWFlfjGQkJbAEGAAAAAMDfEAACFjEDwF692yo83GZxNZ5hTgJmCzAAAAAAAP6DABCwgNPp1MaNGyW5AsBgkcgQEAAAAAAA/A4BIGCB3bt36+jRo5Kkbt1bW1yN55gdgEeOHFFFRYXF1QAAAAAAAIkAELCE2f0nKWjO/5NODAFxOp0qKCiwuBoAAAAAACARAAKWMAPAsDBDnbukWVyN55hbgCXOAQQAAAAAwF8QAAIWMAPAzA4piomJtLgazzG3AEucAwgAAAAAgL8gAAQsYAaA3YJo+68kJSaeCADpAAQAAAAAwD8QAAI+VlJSom3btkmSunUPsgCQDkAAAAAAAPwOASDgY5s3b3ZPyA2mCcCSlJR04gxAAkAAAAAAAPwDASDgY1UnAHc7LbgCwKioCMXEREhiCzAAAAAAAP6CABDwsc2bN0uSYmIi1K5dgsXVeJ65DZgOQAAAAAAA/AMBIOBjP/30kyTXBOCwsOC7BRMTXduA6QAEAAAAAMA/BF/6APg5cwBIVlaKxZV4R0IiHYAAAAAAAPgTAkDAhyorK7V9+3ZJUoesVIur8Y4kOgABAAAAAPArBICAD+3Zs0elpaWSpMwg7wDMz8+3uBIAAAAAACARAAI+ZW7/lYJ3C7A9IVqSdOTIEWsLAQAAAAAAkggAAZ8yB4BIwbsFODHB1QF47NgxORwOi6sBAAAAAAAEgIAPmR2AiYkxSkqKtbga7zA7ACW2AQMAAAAA4A8IAAEfMgPAzA7Buf1XkhKODwGRCAABAAAAAPAHBICAD5lbgDsE6fl/kpSQcCIAzMvLs7ASAAAAAAAgEQACPlNWVqadO3dKkrKC9Pw/SbJXCQAZBAIAAAAAgPUIAAEf2bVrlyoqKiRJmUHcAZhIAAgAAAAAgF8hAAR8xOz+k6T09CQLK/EuOgABAAAAAPAvBICAj+zatcv9OD090bpCvCwuLlLh4a4/WhgCAgAAAACA9QgAAR8xA8Do6Aglp8RZXI33GIbh7gJkCAgAAAAAANYjAAR8xAwA26UnyjAMi6vxLnMSMFuAAQAAAACwHgEg4CPmGYBt2yVaW4gPEAACAAAAAOA/CAABH9m9e7ek4D7/z5SQSAAIAAAAAIC/IAAEfKC0tFT79u2T5NoCHOwS7NGSCAABAAAAAPAHBICAD+zZs0dOp1NSaGwBtrMFGAAAAAAAv0EACPiAuf1XktLTkyysxDfMLcD5+fkWVwIAAAAAAAgAAR8wB4BIIbIF+HgHYElJiYqLiy2uBgAAAACA0EYACPjArl27JEmRkeFKSYmzuBrvMwNAiS5AAAAAAACsRgAI+IC5BbhduwSFhQX/bVc1AMzLy7OwEgAAAAAAEPxJBOAHzC3A7ULg/D/pxBmAEoNAAAAAAACwGgEg4AN79uyRJLVpm2BxJb5RtQOQABAAAAAAAGsRAAJeVllZqX379kmSWrexW1yNb9gJAAEAAAAA8BsEgICXHTp0SA6HQ5LUqlVoBIAJCdHuxwwBAQAAAADAWgSAgJft3bvX/bhV69AIAKOiIhQdHSGJISAAAAAAAFiNABDwMnP7ryS1DpEAUDoxCIQtwAAAAAAAWIsAEPCyUOwAlE5sAyYABAAAAADAWgSAgJfl5ORIkqKiwqtNxw12CQmxkggAAQAAAACwGgEg4GVmB2Cr1nYZhmFxNb5jpwMQAAAAAAC/QAAIeJl5BmAonf8nSYmJdAACAAAAAOAPCAABL6vaARhK7HZXB2B+fr7FlQAAAAAAENoIAAEvcweArUIrADTPOzxy5IicTqfF1QAAAAAAELoIAAEvOnbsmAoKCiSFXgdgQqIrAKyoqNCxY8csrgYAAAAAgNBFAAh4kXn+nxR6ZwBWnXicl5dnYSUAAAAAAIQ2AkDAi8ztv1IIdgBWCQAZBAIAAAAAgHUIAAEvqhYAhtgZgHYCQAAAAAAA/AIBIOBFOTk5kiTDMJSa1sLianwrMZEAEAAAAAAAf0AACHjR/v37JUkpKXGKiLBZXI1vVe0AzM/Pt7ASAAAAAABCGwEg4EUHDhyQJKW1DK3uP0my26PdjxkCAgAAAACAdQgAAS8yA8DUtHiLK/E9my1M8fGuEJAtwAAAAAAAWIcAEPCigwcPSpJSU0OvA1CSEhIIAAEAAAAAsBoBIOBFJzoAQzQATIyVRAAIAAAAAICVCAABLykqKtLRo0clSWkhGgDa6QAEAAAAAMByBICAl5jbf6XQ7QBMPD4JmAAQAAAAAADrEAACXmJu/5VC9wxA+/EAMD8/3+JKAAAAAAAIXQSAgJfQAXgiAMzLy7O4EgAAAAAAQhcBIOAlVTsA09LiLazEOuYW4KNHj6q8vNziagAAAAAACE0EgICXmAFgRKRNdnu0xdVYw+wAlNgGDAAAAACAVQgAAS8xA8C01BYyDMPiaqyRmHgiAGQQCAAAAAAA1iAABLzEDABTQnQAiFS9A5AAEAAAAAAAaxAAAl5iDgFJC9EBIJKUkHBi6zMBIAAAAAAA1iAABLzE7ABMDdEBIBJnAAIAAAAA4A8IAAEvcDqdJ84ADOEOwES2AAMAAAAAYDkCQMALjh49qpKSEkmhfQZgXIso2WyuP2YIAAEAAAAAsAYBIOAFZvefFNodgIZhKN7uOgeQABAAAAAAAGsQAAJeUDUADOUOQOnEIBACQAAAAAAArEEACHhBbm6u+3FKSpyFlVjPbnedA8gQEAAAAAAArEEACHjBoUOH3I+TQzwATDg+CIQOQAAAAAAArBFudQG+lJ+frxkzZmj58uXKzc1VVFSUOnXqpAsvvFCDBw9u8rrl5eX65JNPlJ2drZycHElSu3btNGLECI0bN07h4af+Mv/000/6/PPPtW7dOuXm5ioiIkLJycnq1q2bzj33XPXq1avJ9cH3zA7A8PAw2Y+fgReqEhLpAAQAAAAAwEohEwDu3LlTDz/8sDuEiImJUWFhodasWaM1a9bo4osv1i233NLodYuLi/Xoo49q8+bNkqTIyEhJ0tatW7V161YtWrRIjz/+uKKj6w6B3n77bb333nuqrKyUJMXGxqqsrEy7du3Srl27ZBgGAWCAMTsAk5PjZBiGxdVYiw5AAAAAAACsFRIBoMPh0BNPPKH8/HxlZmbqvvvuU1ZWlkpLSzVr1iy99dZb+vjjj5WVlaVRo0Y1au0XXnhBmzdvVlxcnO6++253J+HSpUv13//+V5s2bdKLL76oe++9t9bXT58+XdOnT1dERISuueYajR49WsnJyXI6ncrLy9OaNWtUXl7e7K8BfMsMAJOSYy2uxHpmB2ReXp7FlQAAAAAAEJpC4gzAOXPmaN++fYqKitJjjz2mrKwsSVJUVJSuuuoqXXDBBZKkadOmNSps2759u7755htJ0l133aUhQ4bIMAwZhqEhQ4bozjvvlCQtWLBAP//8c43Xb926VdOnT5dhGHrooYd09dVXKzk5WZJkGIaSk5N17rnnasyYMc36/OF75hbglJTQngAsnegALCoqksPhsLgaAAAAAABCT0gEgAsWLJAkDR8+XGlpaTWev/zyy2UYhg4fPqz169c3eN3s7Gw5nU61adNGQ4YMqfH80KFD1aZNGzmdTmVnZ9d4fsaMGaqsrNTQoUM1cODAhn9C8HtmAJicQgeg/XgAKLENGAAAAAAAKwR9AFhcXKwtW7ZIkk4//fRar0lLS1N6erokae3atQ1ee926dZKk/v3713rOm2EY6t+/f7VrTUVFRVq2bJkkacSIEQ1+TwSGqmcAhjpzCIjEIBAAAAAAAKwQ9GcA7t69W06nU5KUmZlZ53WZmZnuoRsN4XQ6tXv37lOum5GRIUk11t2yZYsqKiokSZ06ddKqVas0c+ZMbd26VQ6HQ61atdKgQYN02WWXyW63N6gm+IfKykodPnxYkpSSQgCYQAcgAAAAAACWCvoA0AxiJLnP16uN+VxDBxUUFxerpKSkwesWFxeruLhYMTGuMGTv3r3ua77++mtNmzZNkmsCsCR3GLlgwQI9/vjjat++fb31TJs2TW+//Xadz19zzTW69tprG/CZ1S8sLMz9/0lJSc1eLxjl5ua6w93UlgmKOD4Z2grhERGWvbcpOSXe/djhcPD7pgrup8BgdngnJCS4/0IJ/ol7KjBwTwUG7qfAwP0UOLinAFgt6ANAM6STXEM/6mI+V1xc3KB1q17XkHXN15gB4LFjx9wff/vtt9WtWzf99re/VYcOHVRRUaGVK1dq0qRJys3N1ZNPPqlJkybJZrPV+T6FhYU6cOBAnc8XFRXV+/rGMgzDo+sFk6qhc0pKCxmquT3cV6x8b1Ni4olzEAsKCvh9Uwvup8Bg/oc7/B/3VGDgngoM3E+BgfspcHBPAbBK0AeA/qqystL9ODo6Wo8++qh7q6/NZtOgQYN011136YknntDu3bu1ZMkSnXXWWXWuFxcXp5YtW9b5fGxsrLsrrTnCwsJkGIacTme1zwEnVO3uTEmNk1PW/G2sIcOy966q6hCQqt2R4H4KFIZhKCwsTJWVlXRX+DnuqcDAPRUYuJ8CA/dT4OCe8hwCVKBpgj4AjI6Odj8uLS11b7E9WWlpqSS5O/ROpep15mvrW/fk11StY+TIkbWe8zdo0CC1bdtWOTk5Wrt2bb0B4IQJEzRhwoQ6nz906FCDtzfXJykpSTabTZWVlR5ZLxjt2LHD/dgeHylHWZnPazAMQxERkSp3OCz/j8HICMlmC1NFRaX27t3L75squJ8Cg81mU1JSkvLz8wmw/Rz3VGDgngoM3E+BgfspcHBPeU5qaqrVJQABKeh7xauez1d1a+bJzOcaeh5DTEyMO9BryLpVrz+5LnMCcW3M58ypsvB/ubm57sfJDAGRYRjuScAMAQEAAAAAwPeCPgBMT093H467c+fOOq8znzvVsA2TYRjucK4p65rTgRvK/Bzg/8ywNjw8THZ79CmuDg0Jx78OBIAAAAAAAPhe0AeAMTEx6tKliyRp1apVtV5z6NAh7dq1S5LUt2/fBq/dp08fSdLq1avrvGbNmjXVrjW1a9dOaWlpkqTdu3fX+XrzufrO94N/MQPA5OQ4gtvjzHMACQABAAAAAPC9oA8AJdcZe5L0zTff6ODBgzWe//DDD+V0OpWcnKzevXs3eN3hw4fLMAzl5ORoyZIlNZ5fvHixcnJyZBiGuwaTYRg655xzJEkLFixQQUFBjdcvW7ZMOTk5kqSBAwc2uC5Yy9wCnJRc+3mToYgAEAAAAAAA64REAHj++eerdevWKikp0V//+ldt375dkmtAx4wZM/Tpp59Kcg3SCA+vPhfl5ptv1vjx4/XMM8/UWDcrK0vDhw+XJE2aNElLly6V0+mU0+nU0qVL9dxzz0lyBZC1bfm97LLLlJSUpKKiIj3xxBP6+eefJbkmBH/33Xfu13fv3l0DBgzwzBcDXmcGgCkpLSyuxH8kJLi2AOfn51tcCQAAAAAAoSfopwBLUkREhB555BE9/PDD2rFjh+655x7FxsaqpKTEPYL9oosu0qhRoxq99h133KG9e/dq8+bN+vvf/67IyEhJUtnxya/du3fX7bffXutr4+Li9Oijj+pPf/qTNm3apLvuuktxcXFyOBzu12dmZuoPf/gDW0kDiHsLcAodgCa7nQ5AAAAAAACsEhIBoOQaujFp0iR98MEHWr58uQ4dOqS4uDh17NhR48aN0+DBg5u0bkxMjP7xj3/ok08+UXZ2tnvLbqdOnTRy5EiNGzeuRldhVZ07d9Zzzz2nDz/8UCtWrNDBgwdls9nUpUsXnXXWWbrwwgsVFRXVpNpgjapnAMIl8fgUYDoAAQAAAADwvZAJACUpMTFRN910k2666aYGv+bVV1895TXh4eG69NJLdemllzaprqSkpEbXBf/kdDqVl5cnSUpKogPQZJ4BWFRUpNLSUkJtAAAAAAB8KCTOAAR85dixYyovL5ckJRIAuiUcDwAltgEDAAAAAOBrBICAB5kDQCQCwKrsx4eASGwDBgAAAADA1wgAAQ8yt/9KUmIiAaApwU4HIAAAAAAAViEABDzo8OHD7sdJSTH1XBlaEhIJAAEAAAAAsAoBIOBBdADWruoZgGwBBgAAAADAtwgAAQ+q2gHIGYAn2KsEgFVDUgAAAAAA4H0EgIAHmeFWVFS4YmIiLK7Gf8TERCgiwiaJDkAAAAAAAHyNABDwILMDMDEpVoZhWFyN/zAMQ3a7axIwZwACAAAAAOBbBICAB5kdgImJDAA5mbkNmAAQAAAAAADfIgAEPMgMAJM4/68GMxRlCzAAAAAAAL5FAAh4kHsLMBOAazA7ABkCAgAAAACAbxEAAh7k3gJMB2ANCcfPAKQDEAAAAAAA3yIABDwoNzdXEmcA1oYzAAEAAAAAsAYBIOAhpaWlKioqkkQHYG0SEjgDEAAAAAAAKxAAAh5S9Ww7AsCaEo53RZaUlKikpMTiagAAAAAACB0EgICHmANAJCmJISA1mFuAJbYBAwAAAADgSwSAgIdU7QBMSiYAPJk5BEQiAAQAAAAAwJcIAAEPqdoBmEgHYA10AAIAAAAAYA0CQMBDqp8ByBTgkyVUCQAZBAIAAAAAgO8QAAIeYnYAhoUZslfZ7goXOgABAAAAALAGASDgIWYHoD0hRmFh3FonS0wkAAQAAAAAwAqkFICHmB2ASYls/61NdHSEIiPDJREAAgAAAADgSwSAgIeYHYCJSQwAqUtCgmtrNAEgAAAAAAC+E251AUCwMDsAmQBcN3tCjA4ePMYQEAAAAABADX/+858lSR06dNDEiRMtrSXYEAACHuIOAOkArJM5CZgOQAAAAADAyf7yl79IkkaMGEEA6GFsAQY8xL0FmDMA60QACAAAAACA7xEAAh5QWVnpDrWSkukArIv9+BmAbAEGAAAAAMB3CAABD8jPz1dlZaUkzgCsj9kBaHZLAgAAAAAA7yMABDzAPP9PkpI4A7BO9uMBYH5+vpxOp8XVAAAAAID3lZSUaNasWbr77rs1dOhQpaWlKSIiQvHx8erSpYuuv/56zZs3r0FrORwOPffccxo2bJiSk5MVGxurrl276s4779SPP/4oyTVIwzAMGYahBQsWnLK2l19+WRdddJHat2+v6OhoJSQkqFevXrr77ru1efPmel9f23utXLlSN954ozp27Kjo6GilpKTonHPO0ZQpU9yNMycz1zBlZ2e7P1b115QpUxr0dUJNDAEBPKBqRxtDQOpmdgCWlZWpuLhYsbF8rQAAAAAEtx49emj79u01Pn7s2DFt3bpVW7du1bRp03TJJZdo2rRpatGiRa3r7Nu3T2PHjtXatWurfXzLli3asmWLXn/9db3++usNris7O1vXXXed9uzZU+3jpaWl+v777/X999/rhRde0F//+lc99NBDDVrzn//8px5++GFVVFRUW2/BggVasGCBZs2apffff1/h4cRRvsZXHPCAqh2ADAGpm90e7X6cn59PAAgAAAAg6BUVFSkxMVHnnnuu+vfvr8zMTMXGxqqgoEDr1q3Tu+++q71792rWrFn69a9/rffee6/GGiUlJRo9erQ2bNggSUpNTdVNN92kPn36qKysTAsXLtSbb76pG264QWPHjj1lTZ9//rkuueQSORwOhYWFaezYsRo1apTatWunkpISrVixQlOnTlV+fr7++Mc/StIpQ8BXXnlFb7/9ttLS0jRx4kT16dNHYWFhWrx4sV599VWVlpbqo48+0lNPPeVe0zRz5kxJ0mWXXSZJ6tmzp5544oka73H66aef8nND7QgAAQ+gA7Bhqp6PeOTIEbVp08bCagAAAADA+15//XWNGjVKERERtT7/t7/9Tdddd50++ugjvf/++/r222911llnVbvmySefdId/vXr10vz589WyZUv38xMnTtTtt9+uUaNGadasWfXWs3fvXk2YMEEOh0MtW7bUrFmzNHjw4GrX3HDDDfrDH/6gsWPHasOGDXr00Ud12WWXqXv37nWu+/bbb2vEiBGaNWuWEhIS3B+/9tprdeWVV+q8885TRUWFnn76aT3wwAOKjIx0X3PppZdWWys1NbXGx9A8nAEIeEDVADCJISB1MqcAS3JPTQYAAACAYHbBBRfUGf5JUmxsrN544w3FxcVJkt54441qz5eVlemFF16QJIWHh+vdd9+tFv6ZBg4cqH//+9+nrOdf//qXexfbjBkzaoR/pnbt2un999+XzWZTRUWFnn322XrXTU5O1gcffFAt/DONGDFCV1xxhSTp0KFD+u67705ZJzyLABDwADPMiomJUGQUjbV1Mc8AlAgAAQAAAMBkt9vVu3dvSdLSpUurPfftt9/q0KFDkqQxY8aoR48eda5zww03KCUlpc7nnU6npk6dKkkaMmSIzj777Hrr6t69uwYNGiRJmjNnTr3Xnuq9R48e7X5sdjPCd0gqAA8wwyx7Auf/1cdOAAgAAAAgBOXl5emtt97SF198oQ0bNig3N1eFhYVyOp01rt29e3e1f67aLXfOOefU+z4REREaNmyYZs+eXevzGzduVG5uriQpKSlJH3300Slrt9lskqTt27erpKRE0dHRtV43ZMiQetdJT093P666iw6+QQAIeEB+fr6k6kMuUFNCQvUhIAAAAAAQ7GbNmqWbbrrJHbydSkFBQbV/zsnJcT/u1KnTKV/fsWPHOp/bsWOH+/Fnn32mzz77rEE1mQ4fPqy2bdvW+lxqamq9r42KinI/LikpadT7ovkIAAEPcHcA2ukArE9UVISiosJVWlpOByAAAACAoLdkyRJdccUVKi8vlyT16dNHo0aNUufOnZWUlKSoqCgZhiFJeuSRR/T999+rsrKy2hqFhYXux7Gxpz5z3jxLsDbN/TmsrKyszufCwjhlzp8RAAIeYHazVe1wQ+0SEmN0YP9RAkAAAAAAQe+xxx5zh3/PP/+87rjjjjqv/dvf/lbrx6sGekVFRad8z6qB4clatGjhfnzfffc1aGgIggPxLOABnAHYcOYgEAJAAAAAAMHM4XBowYIFkqQBAwbUG/5J1bfnVlV1y+22bdtO+b4//fRTnc9VPYdv165dp1wLwYMAEPAAM8xKIAA8JXObNAEgAAAAgGB26NAhd/df586d6732u+++c0/6PdkZZ5zhfvz111/Xu47D4dCiRYvqfL5fv35KSEhwr1VaWlrver5mboeubTgKmocAEGgmp9N5YggIW4BPydwmzRAQAAAAAMGs6tbdrVu31nvtn/70pzqfGzZsmFJSUiRJc+fO1caNG+u8durUqfUOG7HZbLruuuskuQLK//znP/XW5WvmFuX6tjGjaQgAgWYqLi52H4SawBCQU7KzBRgAAABACLDb7erataskaeXKlZoxY0aNayoqKnTvvffq888/r3OdqKgo/fa3v5UklZeX6+qrr9aBAwdqXLdixQrdf//9p6zrj3/8oxITEyW5Bo8888wzNQaPVFVYWKhXX31V77zzzinXbq6srCxJ0qZNm1RcXOz19wslDAEBmqlqJxtnAJ5aYqLra0QHIAAAAIBg97vf/c599t9VV12lq6++WiNGjFBSUpK2bt2qt956Sz/88IN69eqlqKgorVy5stZ1HnroIX344YfasGGDNmzYoJ49e+qmm25S3759VVZWpm+++UZvvvmmwsLCNH78eM2ePVtS7ZN527Vrp/fee08XX3yxSktLde+99+qFF17QZZddph49eqhFixY6evSotm/frhUrVuirr75SSUmJ/vrXv3rvC3XcqFGjtG7dOhUWFuriiy/WDTfcoLS0NPfW4N69e6tdu3ZeryMYEQACzVQ1yOIMwFOr2gHodDrdf5ADAAAAQLC57bbbtGLFCr322mtyOp2aPn26pk+fXu2a3r17a9asWbrxxhvrXCc6Olpz587V2LFjtW7dOh06dEj//Oc/q10TGxur119/XevWrXMHgPHx8bWuN3r0aH377beaMGGCfvzxR23ZskVPPfVUne9vs9nUunXrhn7aTXb//ffrrbfe0v79+zV//nzNnz+/2vOvv/66Jk6c6PU6ghFbgIFmqrqVlTMAT80cAuJwODjXAQAAAEBQMwxDkydP1gcffKDzzz9fKSkpioiIUOvWrTVixAg999xzWr58uXvra33atGmjFStWaNKkSRoyZIgSExMVExOjzp0764477tCqVat01VVXVTsDMDk5uc71Bg4cqI0bN+r999/XhAkT1KVLF9ntdtlsNiUkJKhXr1665ppr9PLLL2v37t26+eabPfI1qU/btm21atUq3XffferTp4/i4+NpGvEQw8lolZBQ1zShxkpKSpLNZlNFRYXy8vI8smagmzNnjiZMmCBJ+nTOnerStZXFFbn+JRMRESmHo8zvpifNmrlGv7/vA0nSmjVrQrp9m/spMNhsNiUlJSkvL08VFRVWl4N6cE8FBu6pwMD9FBi4nwIH95TnpKamWl2C3xswYIBWrVqlxMREHT58mAANkugABJqtegcgW4BPperXiEEgAAAAAOA5S5Ys0apVqyRJI0eOJPyDGwEg0ExVQyzOADy1BAJAAAAAAGi0VatW6ejRo3U+v3HjRl1zzTXuf7799tt9URYCBENAgGYyh4BERoYrOjrC4mr8X0LiiQCQScAAAAAA0DCvvfaapkyZojFjxujMM89URkaGwsPDtW/fPn3zzTf66KOPVF5eLkn65S9/qTFjxlhcMfwJASDQTGYXWwIDQBokwX4iAOT8EwAAAABouMLCQs2cOVMzZ86s85rrrrtOkydP9mFVCAQEgEAzmV1snP/XMFUnJdMBCAAAAAAN83//93/KyMhQdna2tm3bptzcXB05ckRxcXFq166dhg0bpokTJ2ro0KFWlwo/RAAINNOJDkACwIaIjAxXTEyEiosdnAEIAAAAAA2UkZGh//u//9P//d//WV0KAhBDQIBmMkMsO1uAG8zsliQABAAAAADA+wgAgWZybwG20wHYUInHA0C2AAMAAAAA4H0EgEAznQgA6QBsKDoAAQAAAADwHQJAoJnMAJAzABvO3C5NAAgAAAAAgPcRAALNUFpaquLiYklMAW6MBDoAAQAAAADwGaYAA81QNcBKYAhIg9k5AxAAAABAEJs3b57VJTRYjx491K5dO6vLgJcRAALNUDXAYghIwyXYT2wBdjqdMgzD4ooAAAAAwHPGjBljdQkNNnfuXALAEMAWYKAZqncAEgA2VEJirCSpoqJChYWFFlcDAAAAAEBwowMQaIaqAaCdLcANVnW7dF5enlq0aGFhNQAAAADgHU9cNl7d27SxuowaNu3dq0dmzra6DPgQASDQDFW3ANMB2HCJxzsAJVcA2L59ewurAQAAAADv6N6mjc7IyrS6DIAtwEBzVO8AJABsqITEE1+rvLw8CysBAAAAACD4EQACzWB2AEZE2BQTE2FxNYHj5A5AAAAAAADgPQSAQDOYAWC8PZpJto2QmHSiA7BqFyUAAAAAAPA8AkCgGczwKsHOAJDGaNEiSmFhrsD08OHDFlcDAAAAAEBwIwAEmsHsAOT8v8YJCwtznwNIByAAAAAAAN5FAAg0gxleEQA2XuLxrxkdgAAAAAAAeBcBINAMZgdgQgJbgBsr4fggEDoAAQAAACBwlJaW6rXXXtPll1+urKwstWjRQjExMUpPT9e4ceP03HPP1Wj0mDhxogzDqPErLi5OnTp10nXXXafs7GyLPqPQQAAINIO7A9BOB2BjmYNA6AAEAAAAgMAwb948denSRTfddJM+/PBD7dixQ5WVlYqKitKePXv02Wef6a677lKHDh00efLkGq+PiIhQq1at3L/Kysr0008/6e2339bIkSP14IMPWvBZhQYCQKAZ3ENA2ALcaObXjA5AAAAAAPB/77zzji688ELt2rVLnTp10uTJk7Vv3z4VFRXpyJEjKiws1GeffaYrr7xSx44d08cff1xjjaFDh2rfvn3uXyUlJVqxYoXOPvtsSdI///lPzZkzx9efWkggAASayOFwqKioSBJnADZFUhJbgAEAAAAgEHz//fe66aabVF5ervPPP19r167Vr3/9a7Vq1cp9TWxsrC644AK99957WrRokTIyMk65rs1m04ABAzRr1iylpqZKkqZMmeKtTyOkEQACTVQ1uOIMwMYzOwDz8vLkdDotrgYAAAAAUJdHHnlExcXFatu2raZPn664uLh6rx8yZIieeeaZBq+flJSkQYMGSXKFjfA8AkCgicwBIJIUbycAbKzE4x2A5eXlOnbsmMXVAAAAAABqk5OTo1mzZkmS7r77biUmJjbodWFhjYuczMaQysrKRr0ODUMACDRR1QCQMwAbLyHxxNeMQSAAAAAA4J8WLFjgDufGjx/vlfc4fPiwli9fLknq2LGjV94j1BEAAk1UdQswZwA2XmJCrPsx5wACAAAAgH/auHGjJCkqKkrdu3f36NoVFRVauXKlLr30UuXm5kqSbrjhBo++B1zCrS4ACFTVOgDtBICNlZh04muWl5dnSQ2VlZWaPXu23nnnHfc5E71799Y111yjiy66qNEt6wAAAAAQbMxgLikpSYZhNGutxYsXq3Xr1tXWLi8vd//zrbfeqssvv7xZ74HaEQACTcQQkOZJSDzRAWhFAHjw4EHdeuutWrhwYbWP79+/X19++aXOPPNMvfzyy2rXrp3PawMAAACAYORwOLR///4aH7fZbJoyZYomTJhgQVWhgfYWoInMANBmC1NciyhriwlASYnWdQDu27dP48aNc4d/8a3sOuPaMzXwmkGKbxkvSVq2bJnGjRunHTt2+LQ2AAAAAPAnKSkpklw/t5lnATbViBEj5HQ65XQ6VVZWpk2bNum3v/2tKioqdM8992jdunWeKBm1oAMQaCJzC3C8PbrZbdChKK5FlGy2MFVUVPo0ACwuLta1116r7du3S5LOuPZMXfDoxYqIjpAkOUoc+vL/zdHiyQu1Z88eXXbZZZo9e7bat2/vsxoBAAAAwF/06NFDklRaWqpNmzbptNNO88i6ERER6tatm5577jnZbDb997//1RVXXKE1a9YoNjb21AugUegABJrI7ABk+2/TGIbhngTsywDw0Ucf1fr16yVJQ286Wxc/cZk7/JOkiOgIXfDIRRr1+7GSpN27d+umm25SWVmZz2oEAAAAAH8xcuRId9PL7NmzvfIef//739WyZUtt2bJF//73v73yHqGOABBoIrMD0M4AkCZL9HEAuGzZMr3xxhuSpM5nd9H5f7ywzu7NEXeco7NvGylJWr16tf7617/6pEYAAAAA8Cdt27bV+PHjJUmTJk2qdh5+fSorKxv8HnFxcXrggQckSf/61790+PDhRteJ+hEAAk10ogOQALCpEo8PAvFFAFheXq4//OEPkqTIuEhd9tSVp5zye979Y5R5RpYk6aWXXtKiRYu8XicAAAAA+JsnnnhC0dHR2rNnj375y1+qqKio3uuXLFmi3/3ud416j9tuu02JiYk6evSonn766WZUi9oQAAJNZAaA8Xa2ADeV2QHY0L9Bao4333xT33//vSTpnLtHyd464ZSvsYXbdOWzv1R0vOt7/H//939sBQYAAAAQcnr16qVXXnlFNptNc+bMUd++ffX666/rwIED7muKior0xRdf6Oqrr9awYcO0c+fORr1HfHy87rzzTknSf//7X58Piwx2BIBAExUUFEiiA7A5Eo53AHq7vbusrEzPPPOMJCm1U5qG3HhWg1+b0CZRox44X5K0efNmvfjii94oEQAAAAD82oQJE/TJJ5+oXbt22rp1q37961+rVatWiouLU2JiouLi4nTBBRfovffeU0JCgn7xi180+j3uuecexcbGqqCgwP0zHDyDABBoIrNrzc4QkCZL8FEH4IwZM5STkyPJ1f1ni7A16vVnXDdYbXu1kyQ9/fTTOnTokMdrBAAAAAB/N3bsWG3btk2vvPKKLr30UmVkZMjpdKqkpETp6ekaN26cXnzxRe3YsUM33HBDo9dPTU3VzTffLEl69tlnfbJbLFSEW10AfMNma1zgYdWagaKiokJHjx6VJCUkxNY5SMIqZj3+VtfJkpJOnAFoGMYpz+RrioqKCj333HOu98tIVq9xfRr9dbGF2zTuz5folSteUGFhoSZNmqQnnnjCo3WGyv3kdDr19ddfa8qUKVq9erUqKyvVo0cPXXfddbrkkkv88ves+b0Jle9RsOD75b+4pwIP3yv/xf0UmPh+IdBFRUXp5ptvdgd1DTFlyhRNmTKlQdc+++yzevbZZ5tYHepCABgikpKSPLqezWbz+JqBJDc31/04ObmFIiIiLaymbuHhEVaXUK/k5HhJrulQNptNiYmJHn+P2bNna8uWLZKkc+44TzExTevY7DKki7qfe5o2ffWDJk+erIceekjp6ekeqTFU7qeCggLddNNNmjFjRrWP7927V/Pnz9eIESM0ffp0tW7d2qIK62e3260uAQ0UKvdUoOOeCgzcT4GB+ylwcE8BsAoBYIjw1OGZdrtdNptNFRUV7jPwQtGOHTvcj+NaRMjh8K/BEIZhKDw8QuXlDjmdTqvLqZPdfiI43b59uzp06ODx93jhhRckSbFJsep9aT+VORxNXuvc+8Zo01c/qLS0VH/+85/1r3/9q1m1hdL9dOTIEV122WVau3atJCkhJkaje3ZXhM2m+Rt/1IGjR5Wdna0hQ4Zo9uzZHgtXPcFms8lut6ugoEAVFRVWl4N6hNI9Fci4pwID91Ng4H4KHNxTnkOACjQNAWCI8MZ/EITyf2RUHVpht0f7bcjmdDr9tjZJslcZoHLo0CG1b9/eo+vv3btX8+bNkyT1+8XpCo8Kb9bXo03Ptuoxtpc2frFBb731lu6//36lpaV5pNZgvp8cDocmTJjgDv/G9uqhf15xqewxru9/ycUO/e3TLzRtyXLt2LFD1157rT777DPFxPjXgJ2Kioqg/j4FG75X/o97KnDwffJ/3E+Bhe8VACswBARogqoHkTIFuOkSE0987bwx4v3tt99WZWWlJGnA1YM8subZt42UJJWUlOjVV1/1yJrB7j//+Y8WL14sSfrF6f30/HVXu8M/SYqOiNDjl1yk20aeLUnasGGD/vCHP/h1eA0AAAAAgYQAEGiCqgGgnQCwyRITY92PPR0AOp1OvfPOO5KkjAGZatmllUfWTe/bXllDOkmSXnvtNR07dswj6warZcuW6T//+Y8kqU96O/3jiktrHfZiGIYeOH+UhnftLEl65513NHv2bJ/WCgAAAADBigAQaIL8/Hz3Y7u9aUMlICV4sQNwxYoV+vnnnyVJp1850KNrn33rCEmuIPj999/36NrBxOFw6N5771VlZaViIyP1zDVXKqKeqXe2sDA988sr1cruGg7z2GOPqbCw0FflAgAAAEDQIgAEmsDsADQMQ/HxUdYWE8Di4iIVEeEKhKp2VXrCrFmzJEm2CJt6jO3l0bU7D++qtM4tJbm6ANmqWrs333zTPYH5DxeMUVZqyilfkxQXq4fHjZUk5eTk6JlnnvFmiQAAAAAQEggAgSYwOwDj46Nq3c6IhjEMw32GYtXBKs1VWVnp3j7a6ewuikmIPcUrGscwDA2aMESStGnTJvf5djihoKBATz31lCSpS8s0XXtmw7swL+rbW2d27CDJNcV579693igRAAAAAEIGyQXQBGYAyPl/zZeY5PoaenIL8HfffecOjXqP6+uxdavq94vTFRkbKcnVBYjqXnrpJeXm5kqSHho3VuH1bP09mWEYeuziCyVJZWVlev75571SIwAAAACECgJAoAnM7apMAG4+cxCIJzsA3dt/I23qPuo0j61bVXR8tPpedrok6bPPPtO+ffu88j6B6NixY+4JyYOyOmhkty6NXqNH2zYa1aO7JGnq1Kk6ePCgR2sEAAAAgFBCAAg0wYkOQAaANFdSsmcDQKfTqS+++EKS1Pnsroq2ey+kPfN61zbg8vJyvfnmm157n0Azbdo0d0fnHecMl2EYTVrnznNdw1aKi4v14osveqw+AAAAAAg14VYXAAQidwegF8OlUJGUFCfJcwHgpk2btGvXLklS9/O80/1natWttToMytKO5dv15ptv6r777pOtEVtdg5HD4dBLL70kSTqtTWsN79q5yWv1bZ+us7t01sItWzVt2jT9/ve/V0wM9xwAAAACxyY/Pc/aX+uC9xAAAk3AGYCeY3YAmufFNdecOXPcj7ue690AUJIG/HKQdizfrr179yo7O1vnnnuu19/Tn3322Wfas2ePJOnWEWc1ufvPdONZQ7Rwy1bl5eXpo48+0jXXXOOJMgEAAACfeGTmbKtLACSxBRhokhNnALIFuLmSklwBYGFhoUpKSpq93ty5cyVJbXu3k72VvdnrnUqPsb0UFR8lSXrnnXe8/n7+burUqZKktPgWurBPr2avN7xrZ7VPTpIkvf76681eDwAAAABCEQEg0EiVlZUqKCiQRAegJ5gBoNT8ScC5ublasWKFJKmbD7r/JCkyJlK9L3JNGv788889Os040Gzbtk3ffPONJOmqMwYowgPboW1hYbr2zDMkSatXr9bq1aubvSYAAADgbU6nM2B+jR492uovF3yAABBopIKCAjmdTkmS3U4HYHMlJce5Hzd3G/BXX33l/t74KgCUpNOvHChJKi0t1Ycffuiz9/U3ZvefYRj65aCBHlv3qjNOV+TxMJEuSwAAAABoPAJAoJHM7b8SHYCeULUDsLmDQLKzsyVJsclxatOrbbPWaoz0fhlK69xSUugGVA6HQ++++64kaWS3LkpPSvTY2slxcTr3tG6SpI8++khlZWUeWxsAAAAAQgEBINBI5gAQiSnAnmAOAZGaFwA6nU4tXLhQktRxSCeFhfnujzfDMHT6Fa6Ot7Vr12rjxo0+e29/sWDBAncH55UDT/f4+ped3k+Sa5v4l19+6fH1AQAAACCYEQACjVQ1ALQzBKTZkj3UAbht2zbl5ORIkjoO7dzsuhqr7y9OV5jN9Ufq+++/7/P3t9qMGTMkSfHR0Tq3e1ePrz+yWxclxbp+r7z33nseXx8AAAAAghkBINBIVbcAJ7AFuNniWkQpIsJ1vltzAkBz+IQkdRrm+wAwPi1eHY+/74cffqjKykqf12CVY8eO6YsvvpAkXdCrh6IiIjz+HpHh4RrX1zVVeO7cudXuQwAAAABA/QgAgUaq3gFIANhchmG4zwFszhAQMwBMbJekpIxkj9TWWH3G95Mk5eTkaMmSJZbUYIXPP/9cRUVFkqRL+vf12vtc2s+1tsPhcAeOAAAAgD8yDCNgfs2bN8/qLxd8gAAQaKRqQ0CYAuwRZgDY1A7AiooKLVq0SJKr+88wDI/V1hg9zu+liGhX99sHH3xgSQ1WMLc8t7bbdWbHDl57n/4Z6Wptt0uSPv74Y6+9DwAAAAAEm3CrCwACjRkAtoiPks1Ghu4J5iCQpgaAGzZscH9fOlqw/dcU1SJK3Uadpg2frNPs2bP15JNPKioqyrJ6fOHAgQPu6csX9+stmxeHr4SFhWls7x6asmipFixYoIKCAtmPB4IAAACAP/rLE+PVvXsbq8uoYdOmvfrTI7OtLgM+RAAINJK5BZgJwJ6TmNi8LcBmACW5JgBbqe8l/bXhk3XKz8/X/PnzdeGFF1paj7d9/PHH7vMOL/Xi9l/Thb17acqipSorK9PcuXN1xRVXeP09AQAAgKbq3r2NBpyRaXUZAFuAgcYyO82YAOw5ze0AXLhwoSSpZbfWapEW77G6mqLz8K6KOR5ompNxg9mnn34qSeqQmqLT2rT2+vsNyGyvlvGu7/Hs2fyNJQAAAAA0BAEg0EhmB6CdDkCPac4ZgA6HQ8uXL5ckdRpqbfefJIVHhqvXuD6SXNNqCwoKLK7Ie3Jzc7V48WJJrum/vjh7MSwsTGN6nibJ1flZXFzs9fcEAAAAgEBHAAg0Eh2AnpeUHCdJKi4udk+Tbaj169e7X5M5qKPHa2uKvpf0kySVlpbqk08+sbYYL5ozZ44qKiokSWN69fDZ+553WjdJUlFRkXv4CwAAAACgbgSAQCOZAWBCAh2AnmJ2AEqN7wJctmyZ+3HmAP84W6P9gEwltE2UFNzTgD/77DNJUpsEu/q0a+uz9x3cKUvREa5py/PmzfPZ+wIAAABAoCIABBrJ3NLJFmDP8UQAmNIh1fLz/0xhYWHqc7wLcOHChdq3b5+1BXnBsWPHtGDBAknSmJ49FObF6b8ni46I0LDOrm7PefPmyel0+uy9AQAAACAQEQACjeB0Ok9MAWYLsMeYQ0CkxgWATqfTff5f5hkdPF1Ws/S9pL8kV40zZ860uBrP+/LLL1VaWipJGuvD7b+mc49vA961a5c2bdrk8/cHAAAAgEBCAAg0wrFjx9xnntnZAuwxSUlx7seNCQB/+uknHTx4UJKUMbCDp8tqllbdWqtV9zaSpA8//NDiajzPnP6bFBurgR0yfP7+53Tr6n7MNmAAAAAAqB8BINAI5vl/EmcAelLVDsDc3NwGv67q+X8ZAzp4siSPMLcBr1mzRtu2bbO2GA8qKyvTl19+KUka1aO7wm02n9fQJjFBPdq2luSatgwAAADAeyZOnCjDMBr0a+LEiVaXi1oQAAKNUDUApAPQc2JiIhQVFS6pcR2AZgAYmxyn1I6pXqmtOfpc1Nf9OJi6AJcuXapjx45JcgWAVjm3u2sb8HfffdfosyMBAAAANF5ERIRatWpV76+EhASry0QtCACBRjDP/5OkBDtnAHqKYRjuLsCmdABmDuwgwzC8UltzJKYnKfP41uQPPvggaIZVmFtuI2029zAOK5gBYGVlpXsgCQAAAADvGTp0qPbt21fvr2effdbqMlELAkCgEap2AMYTAHqUOQm4oZ1chw4dcm+rzfSz8/+qMrcBb9u2TevWrbO2GA8xA8AzO2YpLirKsjr6tG+nhBhXJy4BIAAAAADUjQAQaATOAPQecxBIQwNAc/qv5H8DQKrqeWEfhYW7/qj94IMPLK6m+bZt2+YOXs1JvFaxhYVp6PEOxG+++SZoOiwBAACAYLJ+/XrdeOON6tixo6KjoxUXF6esrCydd955+uc//1nnLrD8/Hz9/e9/1+DBg5WcnKzo6Gh17NhRF110kd544w2VlJT4+DMJbASAQCNU3QLMGYCeZW4BbmgA+N1330mSwqPC1aZnW6/V1VxxyXHqfLZrYu3MmTPdU6QDVdWJu+d271rPlb5xVudOkqQ9e/YE1aAVAAAAIBh88cUXGjhwoKZMmaLt27dLcp0juGPHDn311Vd68MEHtXr16hqvW7Zsmbp166aHH35Yy5Yt09GjRxUXF6ddu3bp008/1cSJE7Vp0yZffzoBjQAQaASzAzA2NlIREb6ffBrMzC3ADT0DcOXKlZKktr3aKTwy3Gt1eUKf8f0kSfv27dOSJUusLaaZzOm/ndJSlZGSbHE10lldOrkfZ2dnW1gJAAAAgJP99re/VVlZmS688EL98MMPKikp0ZEjR3T06FEtW7ZMd999t+x2e7XX7NixQxdccIH279+v7t2769NPP1VRUZFyc3NVVFSkRYsW6dZbb1VkZKRFn1Vg8u+fmgE/Y3YA2hM4/8/TEqucAeh0Ousd6lFeXq61a9dKktL7tfdJfc3RfXQPRURHyFHi0AcffKCzzjrL6pKa5NixY1q8eLEk6Zzu1m7/NWWkJCsjOUk7D+cpOztbN910k9UlAQAAAEFr8eLFat26db3XfPjhhxo6dKgOHDign376SZI0efLkaq9r0aKFBg0apEGDBtV4/UMPPaS8vDxlZmZq0aJFSk4+0XgQERGhoUOHaujQoR76jEIHHYBAI5gBYIKd7b+eZnYAlpWVqbCwsN5rN23apKKiIklSer8Mr9fWXFFxUeo+uock6eOPP1ZpaanFFTVNdna2HA6HJOk8i8//q2rY8W3A3377rcrLyy2uBgAAAAheDodD+/fvr/dXWVmZJFfIFxbmip327dvXoPULCws1Y8YMSdKf/vSnauEfmocAEGgEcwsw5/95nnkGoHTqbcCrVq1yPw6EDkDpxDbg/Px8ffXVV9YW00Rz586VJMVHR2tAB/8JXs1twEePHq31/BAAAAAAnjFixAg5nc56f40cOVKSFBsbqxEjRkiSzj//fD3++ONauXJlveeif/fdd+6/1B83bpzXP59QQgAINAJbgL0nOTnO/fhUg0DM8//iUloosV2SV+vylM7DuyrmeHAciNOAKysr3ef/nd2lkyJs/nMG5pBOHd1bxjkHEAAAAPAfr776qnr06KEDBw7oT3/6kwYOHCi73a7zzz9fr7zySo3dUfv375ckRUdHq2XLllaUHLQIAIFGMDsAE+gA9LiUlBMB4MGDB+u91uwATO/Xvt6zAv1JeGS4el7YW5I0Z84cHTt2zOKKGmf9+vU6cOCAJOlcP9r+K0lJcbHq3c41CXrBggXWFgMAAADArWPHjlq3bp1mz56t22+/Xb1791ZxcbHmzp2r3/zmN+rVq5dycnKsLjMkEAACjXCiA5AA0NNSUlq4Hx86dKjO644ePaoff/xRUmCc/1dVn/H9JUklJSX67LPPLK6mcebNmydJMgxDI7p1sbiamoZ27ijJFQ6b50MCAAAAsJ7NZtPFF1+sF154QevWrdOBAwf03HPPyW63a+vWrfrd737nvtYcFFJSUuJuQIBnEAACDeR0Ok+cAWhnC7CnJSbFuLv56gsA165dK6fTKUlqHyDn/5kyB3WQvbVrxH2gbQM2A8C+6e2U2qLFKa72vcEdsyS5DiU2t4gDAAAA8D+pqan67W9/q8cee0xS9V08AwcOVEREhCTp008/taK8oEUACDRQYWGh+zBSO1OAPS483KbEJNfXtb4A0Ax3DMNQuz7pPqnNU8LCwtT7or6SXGfVBcrfaB08eNC97fqc7l0trqZ2AzpkyHZ8wtiiRYssrgYAAACAOQ24LjExrp//qp4DGBcXpyuuuEKS9Je//EV5eXneKzDEeDQAvPbaa/XNN994cknAb5jbfyUpgSEgXmGeA1hfAGgGUamd0hQdgEFsn0tc24ArKirc4+39XdWpxf52/p+pRVSUerZtI0lavHixxdUAAAAAWLx4sfr166dJkyZpy5Yt7p1c5eXl+uyzz/T4449Lki644IJqr/vb3/6mxMRE/fzzzxo2bJg+//xzORwOSa4dPwsXLtT111+vjRs3+vYTCnAeDQCnT5+uc845R6eddpqeeeaZU07yBAKJuf1X4gxAbzEnAdc1BMTpdLo7ANMDbPuvqU3PtkrtmCZJeueddyyupmHM6b9p8S3Uo01ri6up25kdO0hyhcQlJSXWFgMAAAAEocWLF6t169b1/ho1apT7+rVr1+ruu+9W165dFR0drZSUFEVFRWncuHHav3+/unbtqv/85z/V3iMrK0uffPKJUlNT9cMPP+jCCy9UXFycUlNTFRcXp+HDh2vatGmn7DBEdR7fAux0OrV582bdf//9Sk9P1w033KBvv/3W028D+Fz1DkACQG84VQfg/v373WPh0/sGZgBoGIb6XNJPkrRkyRLt2LHD0npOpby8XF9//bUkaWS3rgoL89+TI8xzAEtLSzkHEAAAAPACh8Ph/rmsrl/mz3NnnHGG3n33Xf3mN79R//79lZSUpIKCAtntdg0ZMkRPPfWUVq9erbZt29Z4n2HDhunHH3/UY489pv79+ys6OlqFhYVq3769Lr74Yk2dOlWnnXaarz/9gObRn+QWLFigX/7yl4qMjJTT6VRJSYneeustjRgxQj179tSkSZOqdVEBgaRqAGhnC7BXJB+fBFxXALh27Vr347a9Auv8v6r6XNzP/Xj69OnWFdIAK1ascP/eH+mH03+rGtghU2HHB8ksWbLE4moAAACA4DFlyhQ5nc4G/VqzZo0k13l+V111lV5++WWtWrVK+/btk8PhUF5enhYvXqzf//73io2NrfM9k5OT9Ze//EWrVq1SQUGBiouLtW3bNs2ePVvXX3+9oqKifPTZBwePBoDDhw/X22+/rd27d+tf//qXunbt6v4NsGnTJv3ud79Tu3btdOONN/LDGQJO1fCaDkDvSEk90QFong9R1bp16yRJYbYwtTrNf7einkpKVqp7gMnbb79tcTX1M7f/2sLCdFaXzhZXUz97TLR6cA4gAAAAANTglb1cKSkpuv/++7Vp0yZ9/fXXuvrqq91dgcXFxZo6darOOuss9enTRy+88IIKCgq8UQbgUdW2AAfg8IlAYG4BLi8vr/b1NpkdgGldWikiKsKntXmauQ14/fr11Tob/Y0ZAA7skCF7jP93vp6Z1UGSq3ORM0EAAAAAwMXrhzmNGDFC77zzjnbv3q2nnnqqWlfg999/r7vuuktt27bVzTffrOXLl3u7HKDJzA7A6OgIRUaFW1tMkEo+HgBKtW8DNjsA2/Vu57OavKX3xf0UZnP9EfzGG29YXE3t9u7dq++//16S6/y/QDDo+CCQ4uJirV692tpiAAAAAMBP+Ow095SUFD3wwAPatGmT5s+fr6uvvloRERFyOp0qKirS66+/riFDhqh///565ZVXVFxc7KvSgAYxA0C73f+7oAJVyvEzAKWak4APHDigvXv3SpLa9Az8ADA+LV7dzukuybUN2B+71czuP0k6p3uABIBZmTKOnwPINmAAAAAAcLFknOM555yjf/zjH5o4caIkuX9YczqdWrdunW677TZlZGTo6aefVmVlpRUlAjWYW1IZAOI9KfV0AJrdf5LUNgg6ACVp4NWDJLk+13nz5llcTU3z58+XJLVNSFDXVi0trqZhEmNj1b11K0kEgAAAAABg8mkAWFlZqY8++kgXXHCBOnXqpFdeeUWSK/hr0aKFRo8e7e4KzM3N1QMPPKBzzz2XbkD4BXcHIANAvMYcAiJJubm51Z4zz8kzwgy1Pq2NT+vylu6jeigu2fU5v/POOxZXU11ZWZkWLFggSRrZvav7L2oCwZnHtwEvX75cDofD2mIAAAAAwA/4JAD8+eef9cgjj6h9+/a6/PLLNXfuXFVWVsrpdKp379564YUXtGfPHs2ZM0e7du3S3/72N6WlpcnpdGrhwoX6z3/+44sygXqZHYAMAPGe+PhoRUTYJNXsAFy/fr0kKa1zS0XGRPq8Nm8IjwxX/8sGSHJtt92/f7/FFZ2wbNkyFRYWSpJGdOticTWNYwaARUVFfj1gBQAAAAB8xWsBYEVFhWbOnKmxY8eqU6dOevLJJ7V37145nU5FRETo2muv1cKFC7V27VrddtttatHCdfZXWlqaHnroIf3www/q2bOnnE6n33XGIDSd6ABkC7C3GIbhHgRy8hmAZpATDOf/VWVuA66oqNCMGTMsruYE8/y/CJtNwzp3tLiaxjmjQwf3Y4ZLAQAAAIAXAsAdO3bo4YcfVkZGhq644grNmzfP3e3XoUMHPfnkk9q9e7emTZumYcOG1blOcnKy7rnnHknS9u3bPV0m0GhmAJjAFmCvMs8BrNoBmJubq927d0sKjgnAVbXt2U7teqdLcg0DcTqdFlfkYp7/Nyirg+KioiyupnFSWsSpQ2qKJAJAAAAAAJCkcE8udv7552v+/PlyOp3uH2LDwsJ04YUX6o477tDYsWMbdY5Uerrrh+KSkhJPlgk0SUFBgSTOAPS25OSaAWDVASDB1gEoSQOvPkN71u/W5s2btWrVKg0YMMDSenbu3Kkff/xRUuBM/z3ZwMwM7TiUq+XLl8vpdAbUGYYAAAAA4Gke7QCs2u3XsmVLPfTQQ9q2bZs+/vhjXXDBBY3+ASw2NlYZGRnKzMz0ZJlAoxUXF6u0tFQSHYDellxLB6AZABqGoTY92lpSlzf1u/R02SJdZx++9dZbFldzovtPkkZ2D6zz/0wDOmRIcm0l37Fjh7XFAAAAAIDFPNoBKElnn322br/9dl1++eWKiIho1lrDhw/nBzf4BXMAiCTZ7ZwB6E21bQE2z/9LyUpVVIvA2o7aELFJcepxfi+t/3itPvjgA/35z3+W3W63rB7z/L+M5CR1TE21rI7mGJiZ4X68fPlyZWVlWVgNAAAAQtWmTXutLqFW/loXvMejAeD69evVs2dPTy4J+AXz/D+JDkBvS0l1BYCHDx9WeXm5wsPD3ROA2wbZ+X9VDbpusNZ/vFZFRUV69913dcstt1hSR0lJiRYuXChJGtm9a8Bune2YlqrE2BgdKSrW8uXLdfXVV1tdEgAAAELQnx6ZbXUJgCQPbwEm/EOwqhoAxtMB6FUpKS3cj3Nzc3XkyBF3J3DbIDz/z5Q5KEstu7aSJE2ZMsWyYSDffvutiouLJUkjuwXm+X+S6/zZ0zPaS2IQCAAAAAB4NAAMCwtTeHi4Zs9uXMI9Z84c2Ww2hYd7fEcy4BFVtwDTAehd5hmAkmsbsNn9JwV3B6BhGBp03WBJ0ubNm7V48WJL6vjiiy8kSTERERrSKbC3zZrnAG7atKlaiA8AAAB4mzkcNRB+jR492uovF3zAowGgpCZ3rVSdHAz4m6rhAVOAvSvlpADQPP9PUlAOAKmq72WnKzI2UpL0+uuv+/z9Kysr3QHg8K6dFd3Mc1ytNqDKAKnvvvvOwkoAAAAAwFoeDwCBYFT9DEC2AHtT1S3Ahw4dck8ATu6Qomh7cIev0fHR6ntpf0nSp59+qv379/v0/desWeN+z9E9T/Ppe3tD3/btFGFzTVcmAAQAAAAQyvwiACwqKpIkRUcTrMA/mVuAIyJtio4O7K4of5ecEut+fPDgQXcHYDCf/1fVGce3AZeXl2vatGk+fW+z+y/MMHRO98A9/88UHRGhnm3bSOIcQAAAAAChzS8CwKVLl0qSWrZsaXElQO3MDsAEe0zATkUNFDExkYqLc22D3bNnj3766SdJUtteoREAtunRVu1Pd51dN3XqVDkcDp+9txkADuyQqeS4uFNcHRjMcwBXrVrl068lAAAAAPiTJk/dWLdundasWVPrc1999dUpD1x3Op0qLCzUqlWrNG3aNBmGoTPOOKOp5QBeZXYA2tn+6xPJKXEqLCzT1q1b3R8LlQBQks68Yah2rdqpnJwcffzxx/rFL37h9ffcsWOHfvjhB0nS6B7dvf5+vjIgM0OTFy5WcXGxNmzYoP79+1tdEgAAAELAvHnzrC6hwXr06KF27ULn561Q1eQAcObMmXr88cdrfNzpdGrSpEmNWsvpdMowDN12221NLQfwKjMAZAKwb6SktNCunXnatWuX+2NtQigA7HVhH8395+cq2Juv559/XpdddpnXO0/N7j8pOM7/Mw083gEoScuWLSMABAAAgE+MGTPG6hIabO7cuQSAIaBZW4BPHh1d18dP9atVq1Z65ZVXdO655zb7EwK8wexoZQKwb6SkurafHjhwQJKUmJ6k2MTY+l4SVGwRNg2ZOEySq9t68eLFXn/Pzz//XJLUtVVLZaYke/39fCUtPl4ZyUmSOAcQAAAAQOhqcgfgpZdeqg4dOlT72I033ijDMHTnnXfq9NNPr/f1YWFhatGihbKystS7d2/Zjk9qBPyRewuwnS3AvtCyZbwk6ejRo5JCa/uvaeAvB2nBpPkqPVaq559/XsOGDfPaex0+fFjLli2TJI0Kou2/pgEdMrTzcJ6WL1/u7jgHAAAAfGH8E5epTfc2VpdRw95NezX7kZlWlwEfanIA2LdvX/Xt27fax2688UZJ0nnnnafx48c3rzLAj7g7AO10APpCaloLSa5JuFJoBoDR9hgN/OUgLXp1oebNm6fNmzera1fvTOb98ssvVVFRISm4tv+aBmZmauaqtdq/f7927dqljIyMU78IAAAA8IA23dso84wsq8sAPDsF+PXXX9drr712yu4/INCYHYCJiQSAvpCWFl/tn0MxAJSkwROHKczm+mP6xRdf9Nr7fPrpp5KklvHx6tOurdfexyoDqpwDyDZgAAAAAKHIowHgr371K/3qV79Senq6J5cFLFVSUqLi4mJJnAHoK2nHOwBNoRoAJrZLUq+L+kiS3nvvPfeZiJ509OhRzZ8/X5J0fq8eCgvz6L8W/EKXlmmKj3Zt3//uu+8srgYAAAAAfC/4ftIDPMzc/itJCXQA+kRayxMdgPGt4hWX0qKeq4PbsJuHS5LKysr00ksveXz9L774QqWlpZKki/r28vj6/iAsLEz92rv+YmrFihUWVwMAAAAAvkcACJxCtQCQISA+UXULcErXNAsrsV7bXu3Uebjr7L/JkycrNzfXo+t/9NFHkqRW9ngNzAzes/H6Z7gCwO+//15FRUUWVwMAAAAAvtWkISAdO3aUJBmGoW3bttX4eFOdvB7gD6p3AMZaV0gIiY2LdD9O7pxiYSX+4Zy7z9PWbzarqKhIL730kh5++GGPrJufn6+vv/5aknRh715Buf3X1D+jvSSpoqJCa9eu1ZAhQyyuCAAAAAB8p0kB4I4dOyS5AruTP24YhpxOZ5OKOXk9wB+YA0AkKSGBDkBf2P7TIfdje4cECyvxDxkDOqjjsM76adFWvfrqq7rjjjuUlJTU7HU/++wzORwOSdK4PsG5/dfUL+PE2bQrV64kAAQAAAAQUprU7pGRkaHMzExlZGTU+Lj5XFN+nbwe4A/y8vLcj+kA9I0N63Pcj+Mz7RZW4j/Oues8SdKxY8f0v//9zyNrzpo1S5LUJsHu3iIbrBJjY9UxLVUS5wACAAAAjTVx4kQZhiHDMBQWFuZuDKvLrl27ZLPZ3K+ZOHFijWsqKir05ptvaty4cWrbtq2ioqKUmJiobt26acyYMXr88ceVnZ3tbjJbvny5wsPDZRiGpkyZcsqa//znP8swDNntdv38889N+KyDS7M6ABv6cSCQVdsCTAegT2z83hUARiZEyogN3m2pjdHhzI7qcGZH7Vj2k/73v//p9ttvl93e9HD08OHDys7OliRd2Ce4t/+a+me0108HD2nFihVyOp10nQMAAABN4HQ6NXXqVD322GN1XvPGG2+osrKyzudzc3M1btw4LVu2zP2x6OhoGYahLVu2aPPmzZo3b54kV1NOYmKiBg0apAceeED//Oc/de+992rMmDFq27ZtreuvW7dOf//73yVJ//rXv5SZmdmUTzWoBP9PfEAzmQFgdHSEoqIirC0mRJgdgHEZ8e4JtXCdBShJBQUFeuWVV5q11ocffqjy8nJJ0sV9eze7tkBgdjnu379fe/bssbgaAAAAIPCYQdrUqVPrPf7tjTfeqHb9ya677jotW7ZMcXFxevLJJ7Vnzx4VFxcrLy9Px44dU3Z2tu6//361bNmy2uv+8pe/6LTTTtORI0d066231rp2eXm5brzxRjkcDp133nl1XhdqCACBUzADQDvdfz5RWurQ1i0HJEktCACryRrSSRkDO0iSXnzxxWrnUzbWO++8I0nq0jJNfdLbeaI8v2cOApHYBgwAAAA0Rb9+/dSrVy9t27ZN3377ba3XLFq0SFu3blXv3r3Vr1+/Gs9v2rRJc+bMkSS99tprevDBB6t18sXGxmr48OH6f//v/2nXrl3Vdj5FRUVpypQpstls+uSTT/Tmm2/WWP+pp57SqlWrFB8fr8mTJzfzMw4eBIDAKZgBYEJCjLWFhIgfN+1XebmrVbxFRrzKy8tVWVlhcVX+wTAMnXvPKEmu4TQvv/xyk9b5/vvvtW7dOknS5QNPD5mtsF1btVRspGvC9MqVKy2uBgAAAAhMv/rVrySd6PI7mXk+n3ndydavX+9+fPHFF9f7XpGRkTWOKzK3AkvS7373O+3bt8/93MaNG/X4449LYuvvyXweABYXF+vpp5/WL37xC40fP16PPfaY9u7d6+sygAYjAPStjd+f+POgRUa8JKm0tMyqcvxOx2GdlXlGliTppZdeqnZGZUNNnz5dkmQLC9Nl/ft6sjy/Fm6zubsdCQABAACAprnuuutks9n0/vvvq6ioqNpzxcXFeu+992Sz2XTdddedcq2cnJxTXlMbcyvw4cOHdfvtt0tyDRX59a9/rdLSUrb+1sKjAeDq1avVp08f9e3bV0uWLKnxfEFBgQYPHqwHHnhAs2bN0qeffqq//e1v6tOnj1avXu3JUgCPIQD0LfP8v5jkaEUmRkkS24CrMAxD5903WpJ09OhRvfjii416vcPh0IwZMyRJI7p2Vkt7vMdr9GfmOYBr167l9xUAAADQBG3atNGYMWNUUFCgmTNnVntu5syZKigo0Pnnn6/WrVvX+vqBAwe6dyH99re/1YEDBxpdQ9WtwB999JHefvttPf3001q2bBlbf+vg0QBwxowZ2rBhgw4cOKDBgwfXeP7hhx/W+vXr5XQ6q/3Kzc3V5Zdfzg9j8EvuADCRANAXzAnArU5Ldf9LoayMPxuqyhrcSVlDOkmSXn75ZR0+fLjBr50/f74OHTokSbp8QH+v1OfP+h0/B7CsrEwbNmywuBoAAAAgMNW1DfhU238lKSsry/38nDlzlJ6ernPPPVd//OMf9eGHHzZ4l2jVrcB33XWXeyoxW39r59EAcNmyZTIMQ6NHj65xptTRo0c1efJkGYahjIwMzZw5U2vWrNFvfvMbSdLPP/+sadOmebIcwCPMQQt2OgC9rqysXD/+uF+S1LZXmvvj/OVATef+ztUFWFhYqOeff77BrzP/nE2MjdF5Pbp7pTZ/xiAQAAAAoPkuueQSJSYmav78+dq9e7ckaffu3Zo/f76SkpJ0ySWX1Pv6l19+Wb///e8VFRUlh8Ohr7/+Wk8++aQuv/xytW3bVn379tVLL72k8vLyetepuhW4uLiYrb/18GgAuGfPHklS//41u0o+//xzlZSUSJImT56sSy65RH369NFLL72kPn36SJI++ugjT5ZTQ35+viZPnqxbb71VV1xxha677jo99thjWrp0abPWLS8v10cffaR7771XV199ta6++mrdd999mjVr1il/s56sqKhIv/71rzV+/HiNHz9e8+fPb1ZtaB6n06m8vDxJUiIBoNdt3XJAjjLXwI92vVsqLMz1FwmcAVhTh0FZ6nRWF0nSq6++qoMHD57yNTt37tTcuXMlSZf176eo8HCv1uiP0uJbqH1ykiTOAQQAAACaKjo6WldffbUqKyvdk3jffPNNVVZW6uqrr1ZUVFS9r4+MjNRTTz2lPXv26JVXXtH111+v0047zT3wY926dbr99ts1evRoFRcX17lOVFSUnnzySfc///vf//bAZxecPBoAmtvK2rRpU+O57Oxs93PnnXdeteeuvPJKOZ1O91RKb9i5c6fuvPNOzZo1S3v37pXNZlNhYaHWrFmjv//973rllVeatG5xcbEefPBBvfbaa9q2bZsqKipUUVGhrVu3avLkyfrjH//oDj4bYurUqe6vI6xXWFioigpXIEUHoPeZ5/9JUpveaYqKtEmiA7Au597r6gIsKipqUBfglClT5HQ6JUkThgzyam3+zDwHkAAQAAAAaLqTtwGb/1/f9t+TpaSk6Oabb9bUqVO1ceNG5eXl6b333lO/fv0kSQsWLNDDDz9c7xoJCQm1PkZ1Hg0Aza2SJ49olqQlS5a4Dq8/KfyTpIyMDElqUAdLUzgcDj3xxBPKz89XZmamnn32Wb377rt69913NWHCBBmGoY8//lhffvllo9d+4YUXtHnzZsXFxemhhx7S+++/r/fff18PPfSQ4uLitGnTpgYf0r9p0yZ98cUX6tatW6PrgHeY3X+SlMgZgF5nTgCOSYxSQtsWioxydagRANYu4/RMdRnp+vPitdde0/79++u8tri4WG+99ZYkaXjXzuqYluqTGv2ReQ7gzp076/2aAQAAAKjbkCFD1LVrV/344496+umn9eOPP6pr1661zoRoKLvdriuvvFKLFy9Wjx49JLkaGSorKz1VdsjyaAAYGxsrqWaQl5+f7+7uGzp0aI3XRUdHS5K708rT5syZo3379ikqKkqPPfaYsrKyJLlaRa+66ipdcMEFklxnYzVmy+727dv1zTffSHIdODlkyBAZhiHDMDRkyBDdeeedklyJ9c8//1zvWuXl5Xr++edlGIbuuOOOpnya8AJzAIhEB6AvmB2AbXqmyTAMAsAGMM8CLC4u1qRJk+q87oMPPnAPC7lhaNP/hRwMqp4DSBcgAAAA0HQ33HCDJOkPf/iDpMZ1/9UnJiZGEyZMkORqzPFWw1go8WgA2KFDB0nSt99+W+3jn3zyiTutHTZsWI3X5ebmSvJeq+aCBQskScOHD1daWlqN5y+//HIZhqHDhw9r/fr1DV43OztbTqdTbdq00ZAhQ2o8P3ToULVp00ZOp9O9BbouH374oX7++WdddNFF7oAS1qsaACYQAHqVw1GhTT/skyS17um6TyMjXQEgU4Drlt63vbqdd5ok19+M7du3r8Y1lZWV7i3CHVKSNbJbF5/W6G96tGmtyOPnHzIIBAAAAGi666+/XoZhyOFwKCwsTNdff73H1o6Li3M/joyM9Ni6ocqjAeDZZ58tp9Op2bNna+3atZKkgoICPfXUU5Kktm3bqlevXjVet2HDBknySvBVXFysLVu2SJJOP/30Wq9JS0tTerrrTCiz7oYwuxr79+9fY+qxJBmG4R6IUt/5hjk5OXrvvfeUmpqqa6+9tsHvD+8jAPSdbVsPqqzM1YFrTgCOijQ7AMskOa0qze+ZZwGWlpbqmWeeqfH8559/rq1bt0qSbhlxlmy1HNMQSiLDw9W7XVtJdAACAAAAzZGRkaF//etfuv/++/Wvf/1L7du3P+Vrtm3bpm3bttV7TUVFhaZPny5JyszMVFJSkkfqDWUe/SnwlltuUVhYmEpKSjRo0CANHjxYnTp10oYNG2QYhm655ZZaX/fVV1/JMAz3NGBP2r17t/vQ+8zMzDqvM5/btWtXg9Z1Op3uUdf1rWueb1jfus8//7zKysp0yy23KCaGkMmfVAsAOQPQq77fcGIASOuervPpzC3ATqdTZWUOS+oKBG17ttNp5/eU5Jq8ZU5kl1xfu//+97+SpNQWLXT56f2sKNHv9Ds+CGTNmjWNntYOAAAA4IT7779f/+///T/dd999Dbp+/fr16tatmy699FJNnz692s8vJSUlmj9/vkaNGqUlS5ZIku655x6v1B1qwj25WJ8+ffSnP/1Jf/rTn+RwOPTdd9+5w7c+ffro97//fY3XrF+/Xps2bZJhGDrrrLM8WY4kuc+8kqTk5OQ6rzOfqzr0oT7FxcXu6b4NWbe4uFjFxcU1Ar558+Zp/fr1OuOMM2rdRtxQ06ZN09tvv13n89dcc41HugvNAS9hYWEhkcBXPXsuJdUumy2wOqfCIyKsLqHBNm50bV2NtkcppUOiDMNQVPSJ+isrKxQZGTifT8MY7v9v7ud2/gMX6Ic536usrEwvvviie8vv559/rlWrVklydf/Fx8bVt0zIOCMrS5MXLlZRUZF2797t7taujdnhnZCQ4P53GvxTqP07KlBxTwUG7qfAwP0UOLingBMiIiJUUVGhWbNmadasWZJcsyGio6OrNeFIrnkLv/vd73xfZBDyaAAoSY8++qj69u2rV155RVu3blVcXJzGjBmjBx98sNbuNvPQeqfTqfPPP9/T5bhDOsk19KMu5nPFxcUNWrfqdQ1Z13xN1a/BkSNH9PrrrysqKkq33nprg963LoWFhTpw4ECdzxcVFclmszXrPaoyDMOj6/krc7J1fHy0wgPw8zVUc2u6v1q/1vW3Pm16pckwXP+BFBV14o+o0tLSgPp8GsOo8r9N1bZHO/W5qK/WfbJWr732mh588EFlZGTosccekyQlx8Vp4llDpVqOKwhFp3c40bn93XffaeDAgad8TW0T7uGfQuXfUYGOeyowcD8FBu6nwME9BUjjxo3Tjz/+qE8//VQLFy7Uhg0blJOTo6NHj8put6tDhw4aOnSobrzxRg0aNMjqcoOGxwNASRo/frzGjx/foGv/97//6X//+583yvB7r7zyio4dO6Zf/epXatmyZbPWiouLq3eN2NhYj0xZDgsLk2EYcjqdITGG2z2gJjFGzgA7g86QETA1l5dX6IcfXFuA2/ZuKfO8v6oBYHFxccB8Pg3nijRdn1XzP7fz7jtf6z9dJ4fDoSeeeEKjR4/W6tWrJUm/PW+kWkRFSXQHSJLaJtjV2m7XvoICLVmyRL/5zW/qvNYwDIWFhamyspLuCj8Xav+OClTcU4GB+ykwcD8FDu4pzyFAtcaUKVM0ZcqURr/uo48+qvXjXbt2VdeuXXXvvfc2rzBJI0eO5M/ABvBKAOhPoqOj3Y9LS0sVGxtb63XmVs+GnsFX9bqq20TrWvfk16xcuVILFy5UZmamLrnkkga9Z30mTJjgHpFdm0OHDjV4e3N9kpKSZLPZVFlZ6ZH1/N3+/fslSXZ7tBxlZRZX03CGYSgiIlLlDkdA/EG46Yd9Ki1xncPWpmeq+z+KIsLDZBiuzKqwsCjozgF0bft1RYCe+NySs1LU6+K+Wj97jaZMmaIvvvhCktTKHq9rBw1QmSNwfg/7Qr+MdH2xYaMWL15c759nNptNSUlJys/P98hfpMB7Qu3fUYGKeyowcD8FBu6nwME95TmpqalWlwAEpKDvFa96Pl/V8wBPZj7X0PMYYmJi3IFeQ9ater0kvfjii5KkiRMnyuFwuM8INH+ZzOeqbmWG75jnDzAAxLs2rD9x6Gub3mknnjBOdAGWlnIPNMQ5d58nI8xQRUWF+zDd+8acp+gAOg/SV/pnuCaUbdu2rd4/xwEAAAAg0AV9B2B6erq71Xrnzp1KT0+v9bqdO3dKUoNGVkuuDqv09HRt2bLF/drGrGue1/eXv/yl3vd54YUX9MILLyguLk7vvPNOg2qD57gDQDsBoDdtWO/a/hudEKXE9Phqz0VFhaukpJwQvIHSOrVUr4v6aP3stZKk7q1b6YoBdQ+4CGVmAChJK1as0JgxYyysBgAAAAC8x2sB4Jo1a/T5559rw4YNysvLa9AP74ZhaP78+R6tIyYmRl26dNHmzZu1atUqDR06tMY1hw4d0q5duyRJffv2bfDaffr00ZYtW9xnbNVmzZo17msReOgA9A0zAHQNAKk+pCIqKkJSiUpK6t5qj+pajWqj9Z+skyqdapVg52DwOvROb6vwsDCVV1Zq1apVBIAAAAAAgpbHA8C9e/fqxhtv1Lx58xr1OqfTWeMHf08ZOXKkNm/erG+++UZXX3210tLSqj3/4Ycfyul0Kjk5Wb17927wusOHD9eHH36onJwcLVmyREOGDKn2/OLFi5WTkyPDMDRy5Mhqz82ePbvetc0hKvfcc4/OO++8BtcEzzIDQHsCAaC3OBwV2vTDPklS215pNZ6PimYLcGPs2rVLJZFlanlmKx1Ysk/fbtmmnCP5apuYYHVpfic6IkKntWmt9XtytHLlSqvLAQAAAACv8WhbyLFjx3TOOedo3rx5cjqdjfrlTeeff75at26tkpIS/fWvf9X27dsluQZ0zJgxQ59++qkk1yCN8PDqmejNN9+s8ePH65lnnqmxblZWloYPHy5JmjRpkpYuXer+fJYuXarnnntOkiuAzMjI8OJnCG+oqKhQQUGBJCmRANBrtm45oLKy4wNAagsAj58BWFbmYGLaKRQWHtOPP/4oSep8YSdJUkVlpaYuXmplWX6t3/FtwCtXruT3FwAAAICg5dEOwKefflqbN292n4/38MMPa/To0UpPT1dkZKQn36pRIiIi9Mgjj+jhhx/Wjh07dM899yg2NlYlJSXuH/guuugijRo1qtFr33HHHdq7d682b96sv//97+7Ps+z4xNju3bvr9ttv99wnA5/Jz893P6YD0HvM7b+S1LZ33QGg5OoCjImpfZJ3qKsoL9fq1atVUVEhw5AGndFF+wft1Lblu/TO8hW667yRiouKsrpMv3N6Znu9uWSZjh49qi1btqhbt25WlwQAAAAAHufRAHDmzJmSpNatW+u7775Tq1atPLl8s2RkZGjSpEn64IMPtHz5ch06dEhxcXHq2LGjxo0bp8GDBzdp3ZiYGP3jH//QJ598ouzsbOXkuMKMTp06aeTIkRo3blyNrkIEBnP7ryQlcgag13y/wXXPxCRGKaFdfI3nXWcAupSUEADWxul0au26dSosLJIkdW7ZUomxMRpyVR9tW75LBcUl+mDlGt0w9EyLK/U/Jw8CIQAEAAAAEIw8mkxt27ZNhmHojjvu8Kvwz5SYmKibbrpJN910U4Nf8+qrr57ymvDwcF166aW69NJLm1Fddac6IxDeVzUApAPQe9av2yNJatOz5gAQ6cQZgJJUyiCQWn3//fc6ePCgJKmlPV6ZyUmSpE5ntFdahyQd3JGn1xct0YTBZzAQ5CQZyUlKjovV4cIirVy5Utddd53VJQEAAACAx3n0J0FzOy0dFAgGVQNApgB7R1lZuX7ctF+S1KaW7b9S9S3AJaUEgNU59cPGjdqzxxWiJsbEqGfbNtLxHNUwDA2+0jWBfMehXH394xarCvVbhmG4zwFcsWKFxdUAAAAAgHd4NADMzMyUJB09etSTywKWqBYA2gkAvaHqAJDaJgBLUliYoYgImyTXFmC4VFZWat269dq5a5ckqUVUpPpmpMsWVr2Lss+Yroqxu87+e2fZdz6vMxD0z0iXJG3atIl/fwEAAAAISh7dAjx+/Hht3LhRixYt0o033ujJpQGfowPQ+6oOAGnTu2Wd10VFhcvhqCAAPK6kpFhr1qxRfr5rSnV8dLT6Z6Qrwlbz73QiosLVd2w3LX1vnb7etFl7j+SrTWKCr0v2a+Y5gE6nU6tXr3ZPdwcAAACaa++mvVaXUCt/rQve49EA8K677tLLL7+st956Sw888IC6d+/uyeUBn8rLy5Mk2Wxhiouzbop1MHMPAEmKVkLbFnVeFxUdrmPHSlXKFmAdPHhQG9avV5nDIUlKjotVn/R2Cq8l/DMNuKiHlr63TpVOp95fsUp3jzrHV+UGhD7p7WQYhpxOp1asWEEACAAAAI+Z/chMq0sAJHl4C3CbNm00ffp0hYeHa/To0frmm288uTzgU/n5+ZIke0J0rcMp0Hzrj3cAtu1V+wAQU/TxcwBDuQPQ4XBo/fp1WrVqlTv865CarP4Z7esN/yQprUOSMvq0liS9u3ylKo6f1wqX+OhodW3l2oK+cuVKi6sBAAAAAM/zaAfg448/LkkaNWqUZs2apXPOOUf9+vXTkCFDlJqa2qDpk4899pgnSwKazOwATGQCsFe4BoDskyS1qeP8P1NkVIQkHe8AdMo95SJE5OTk6Mcff1RZWZkkKdJm02ltWystvu6uyZMNuLiHdq7bp5z8fC3cvFUju3f1VrkBqX9Ghn7cd0ArV66U0+kk9AcAAECzOJ1Oq0sAqvFoAPjnP//Z/UOTuZ1qzZo1WrNmTYPXIACEvzjRAUgA6A1bNh+Qo6xC0qkDQHMSsNPpVGlpmaKiorxenz84evSofvhho/Lyjrg/1soer26tWyky3NaotXqM7KTPn/1WJcfK9Pay7wgAT9I/I13Tl69Qbm6uduzYoaysLKtLAgAAAACP8egWYMn1A7r56+R/PtUvwJ+YHYAMAPGOqgNA2vauPwCMjj7xdxWlpcG/Dbi8vFybNm3SkiVL3OFfTES4+rZvp97pbRsd/kmuYSB9zu8mSfp602YdLiz0ZMkBzxwE8v/Zu+/oqArsgePfN72kFwi9SG/SRIoKgqiIqFjAil3BtvzQ1dVVwa5rr2BZ26qo2AEVUASV3kGR3ksgIckkUzKZ9vvjZYYgAVJm8pLM/ZzDOUNm3nt30nPnFpA2YCGEEEIIIUT9E9UKwF9++SWapxNCU+EKwGSpAIyJdWv3AmBLtZDU6PitrOEKQIDiYi9JSTENTVM5OTn8+ecfeL1qu69OUWiRnkbLjHT0uuq1pZ58TjuWfrkOfzDI92v/5Op+faIRcr1wUmYGiWYzRV4vy5Yt49JLL9U6JCGEEEIIIYSImqgmAAcOHBjN0wmhqYKCAkASgLGyZvVuAJp0b3jCeWvm0hmAUH8rAAOBABs3bmT37t2Rt2Uk2GmX1RCbyXicIyuucftM0pslc2i3g29Xr5EEYBk6nY6Tmzfl981bpQJQCCGEEEIIUe9ENQEoRH0iCcDYcbtL2LzpIACNuzU44eMNBh16vUIgEKqXm4BdLjdLly7B6VTbco16PR0aNaRhYmJU950oikLXoe2Y9+4ylu/YxZ68fJqmpUbvAnVcj+bN+H3zVv744w8+++wzQqEQZrOZRo0a0a9fvwotshJCCCGEEEKI2kgSgEKUo7i4GI/HA8gMwFj4c90+gkF17meTk0+cAERR24Ddbh/Fxd4YR1ezDuXlsXTpUnw+H6BW/XVsnIXZEJtvz13Pasu8d5cB8O3qtdw+WCq3t+Xk8sXylUxfsw5QqzHvuOOOox7XunVrzjnnHEaOHEmPHj1qOkwhhBBCCFGHnKjLqTaZPXs2Q4cO1ToMEWMxTwDu2bOH9evXk5eXR0lJCWPGjIn1JYWotnD1H8gW4FhYs3pP5HaTClQAgtoG7Hb78NajCsCcnByWLVtGIBAE4KQGGbRKT49q1d/fpTdNpknHBuz96yDfrlrDbWeeUad+OYmmtXv28vysn/h105YKPX7btm1MnjyZyZMn07t3b/7xj39wzjnnxO37TwghhBBCCFF3xCwB+O677/L888+zYcOGI97+9wTgE088wfz582nWrBn//e9/YxWOEJUSXgACkCIJwKhbu0ZNAKa1TMaaYqnQMebSTcCeepIAzM/LY/mK5QSDIXSKQucmjWiYlFgj1+46tC17/zrI5oM5/LU/m06NG9XIdWuLPJeLx2f8wNcr10TepqDQqnF3TNaTsFib0qxJe7qd3BOfz4OjMJvsA+vZsHE+m7cuIBj0s3z5cq655hpOPfVUnnnmGTp37qzhMxJCCCGEELXVBY88TqMOHbQO4yj7N2zgu4kPah2GqEFRTwB6PB4uvfRSfvzxRwBCoVDkvvKqJHr37s1DDz2Eoijcc889dOzYMdohCVFp+fn5kdtSARh9a0oTgE1ObljhYyyli0DqwwxAp7OIlatWRZJ/3Zs3Jc1uq7HrdxnchlmvLSQUDDFjzbq4SgDO37iZCZ99QZ7LDYBRb6Zv55Gc2vkiUhOzWL93P/sdDvwBC0mJanVqRnpLOrQ/nQF9b8DpPMTS5Z/y+6J3cboOsWTJEoYOHcrdd9/NXXfdhdEYnYUtQgghhBCifmjUoQMtep2idRhCEPWJ5mPGjOGHH34gFArRokUL7r//fsaOHXvMxw8dOpTMzEwAZsyYEe1whKiSsi3AyckVq1ATFXPwYBH796kVlhWa/1fKYlUTK8FgkJKSkpjEVhN8Ph8rV6zE7/ejAN2aNSEjIaFGY0hIs9HiZDXpN+vPv2r02loJBoO88tMvXP/e/yLJv24nDWbC5R9zbt+xpCZmAZBkVb/evcXFFJezcdpuT+PMgbdx7//NZ8igu9DrTfh8Pp5++mnOO+889uzZc9QxQgghhBBCCKG1qCYAf/75Z7788ksUReGKK65g48aNPPHEE5xzzjnHDkCnY+jQoYRCIX7//fdohiNElZWtAExJrbnKrHiwZvXuyO1KJQAthwuWi0sXtNQ9IdatWxtpY27fKIsGiUmaRNLh9FaAugBjy4GDmsRQU7w+H+M++pQX58wlFAphMdm56uzHGD3kYZLsGUc8Ntl6uOK3IL/gmOc0m+2cPeT/uGvcdJo07grA6tWrGTp0KAsWLIjJ8xBCCCGEEEKIqopqAvD9998H1E2J77//foVboU4++WQA/vorPipRRO1XNgGYLC3AUbV2zV4A9EYdDTtknODRh5kth7+f1NU5gDt27CQnJxeAxsnJNE9L1SyWcAIQ6ncVoMvr5Yb3PmJ26XNsmNaa20a+SaeWp5f7+ASLGZ1OHVdRdhbosWQ1bMftt3zFmWfcBkBubi6XXnop//vf/6L0DIQQQgghhBCi+qKaAFywYAGKojBmzJhKzUFq3LgxANnZ2dEMR4gqy8vLA8CeYMZkivmy7LgS3gDcsFMGBrO+wsdZyiQAi4vrXgWg2+1i8+bNACSYTbRvVPH5h7GQ0jCRRu3V8Quz62kCsNDjYcw7H7Bw6zYA2jbrw9gLXyc9uekxj1EUhSSLmvQvOwrgePR6A+cO/SdXjX4No9GK3+9nwoQJvPjii0fMwRVCCCGEEEIIrUQ1AXjgwAEA2rdvX6njLBZ15lJ9GO4v6odwBWBqilT/RVMgEGTdWrUCsGklFoAA6PUKRqOaMPR46tr3ihB//PEnwWAQRYFOjRuj1x29FKmmdSytAly7Zy/7Ck5c7VaXFPt83Pj+x6zcpbacd2k1kKvPfgKT8cRf08mlcwALCwsJViKB163LcG67+QsSE9TE6pNPPslDDz0kSUAhhBBCCCGE5qKaANTr1T/Og8FgpY4LV1ulpKREMxwhqiycAExOkfl/0bR9Wy4upxeo3Py/sPAcwLpWAbh3777I51SLtDSSrGaNI1J1PKN15HZ9qgL0BwLc8fFnLN+xE4DubYYyashDGPQVq0wPzwEMBoMUFRVW6tqNG3Vi3M1fkJbaHIA333yTf//735IEFEIIIYQQQmgqqgnAhg3Vip4tW7ZU6rgVK1YA0KxZs2iGI0SVhZM1KVIBGFXh9l+AxlVKAKoJnLpUARgI+COtv1ajkdaZFZ97GGuZLVNJb54CwOw/12sbTJSEQiEe+Oo7fv5rIwDtm/fj4kH3oddVvJX/iEUgVaiMTE9rzm03f0FWA7Ua/u2332bSpEmSBBRCCCGEEEJoJqoJwP79+xMKhfjmm28qfIzL5WLatGkoisJpp50WzXCEqLJIAlA2AEdVOAFoTTGT1iK50seHE4B1qQJwx44deL1q1WPbhpmRBRO1RbgNeOn2nTjcdef9eizv/LaQactXAtAiqyuXnzWxUsk/AJPRgKV0jq2jgnMA/y4xMZObr/+IBpltAHjjjTd48sknJQkohBBCCCGE0ERUE4CXXXYZAKtWreLdd9+t0DHjxo2LJFuuuuqqaIYjRJUdbkuXBGA0rV2jJgAbd2uAolQ+ERbeBFxS4iMQCEQ1tlgoKSlh+/YdAKTYrDRITNQ2oHK0698CgEAwyO9btmocTfXM37iZp7+fBUBGcjOuOedJTAZLlc4VngNYUIFNwMeSkJDBzdd/TEZ6SwBeeuklXnrppSqfTwghhBBCCCGqKqoJwPPPP5++ffsSCoUYO3YsTz31FE6ns9zHrlq1iuHDh/Pxxx+jKArDhg2jT58+0QxHiCqTFuDoc7m8bNygLgpq0q3y7b9weAYggLcOLA3asWNHJFHZtkEDqF3FfwA06dgQS4IJUBNoddX23EPc+cnnBEMhzEY7V5/zOFZz1ROu4TZgj9tNSUlJlc+TlNiAm6//JDIT8Mknn+STTz6p8vmEEEIIIYQQoiqimgAE+Oyzz8jKysLv9/Pggw/SoEEDxo8fH7n/lFNOoVGjRvTu3Zsff/yRUChEs2bNeP/996MdihBV4vF4IhuppQU4etau2UsgoC4IatarUZXOEW4BBvDU8jZgn8/Hrl27AEi320m2Va0SLdb0Bh2tT1Hnr87fuLlOtqh6fT5u/+hTioqLUVAYNeRBMlNaVOucR84BLKjWuVKSG3HTdf8jIUGd/zhhwgRmz55drXMKIYQQQghRkwYNGoSiKEyaNIni4mIeeeQROnbsiNVqJTMzk1GjRrF+/dFzxefNm4eiKJEOsIULFzJixAgyMzOxWq1069aNF1988YQdXt9//z0XXHABWVlZmEwmsrKyuPDCC/nxxx+j/lz379/PP//5T7p06UJiYiI2m41OnTpxzz33kJ2dfczjZsyYwYgRI2jUqBFGo5HU1FTatWvHJZdcwttvv33Mv7W2bt3KXXfdRadOnUhMTCQhIYGOHTty7bXXRvX5RT0B2KxZM5YsWRKpBCwuLmbXrl2RD/bKlSs5cOAAoVCIUCjEqaeeysKFC8nIqD2D8UV8C1f/gVQARtPK5epGVkWn0LR7wyqd44gEYC1fBLJz587ID7FWmekaR3N8bU9Vq9MOFhXx1/5j/0CrrR6f+WMk7sG9r6dD837VPmeCxRL5uVXdBCCoi0FuuOZ9TCY7gUCAm266KbIASwghhBBCiLrC6/UyePBgJk2axLZt2zCZTOTm5jJt2jR69ux53Be6v/rqKwYOHMiMGTPw+/34/X7WrVvHhAkTGD58eLmdN+EO0+HDhzN9+nRycnKw2+3k5OTw3XffMWzYMO64446oFTLMnDmTdu3a8dxzz/Hnn3/i8/kIhUL89ddfPP/883Tt2pWlS5ceddzDDz/MiBEjmDFjBtnZ2ZjNZkpKSti8eTNfffUVt9xyS7lJzrfffpuOHTvy6quv8tdff+H3+zGZTGzcuJEPP/yQyy+/PCrPC2KQAAQ1Cbhw4UK+/fZbLr74YtLT0yMJv1AoREJCAsOHD+fzzz9n0aJFNG7cOBZhCFEl4fl/IBWA0bRyhVoN16B9GuZEU5XOYTLpI0s0imtxC3AwGGB3afVfqs1Kiq12J5Lb9Dm8gX3exk0aRlJ536/9g48WqT+AT2rSi0HdozNLVqdTSLSYAShwFETlnE0ad+aaKyaj1xvxeDxceeWVbNmyJSrnFkIIIYQQoiZMnjyZNWvW8MEHH+B0OnE4HKxZs4bevXvj9XoZPXr0MavkbrjhBs466yy2bdtGfn4+DoeD559/Hr1ez6xZs5g4ceJRx7z44ou8+eabANx3333k5uaSn59PTk4Od999NwCvv/46r776arWf2+rVq7nkkktwu93cc889bN++HY/Hg8vlYs2aNZx99tnk5uZy0UUXUVhYGDlux44dPPHEE5EYDxw4gNPpxOVykZuby8yZMxk9evRRc/C/+eYbbrnlFnw+H+eddx4rV67E4/GQl5eHw+GIJDijJSYJwLARI0bwxRdfcPDgQZxOJ3v27KGgoIDCwkKmT5/OpZdeGsvLC1ElR1YASgIwGgKBIKtW7QagWc+sqp9IAXPpHECPp/a2AO/fn02JzwdA8/Q0jaM5scQMO1lt1SrseXVoDuC+Agf/+vJbAOzWVC478wF0On3Uzh9uA3YUOIhWZ3S7Nqdz2chnAfXFhtGjR3PgwIHonFwIIYQQQogYczgcvPXWW4wZMwajUe3Q6tatG7NmzSIzM5OCggJeeOGFco9t2rQp33zzDa1atQLAZrMxYcIEJk2aBKhL88oW5Ljdbh577DEA7rzzTp5++mlSU1MBSEtL47nnnuOWW24B4JFHHqn234jjx4/H6/Xy3HPP8eyzz9KyZUsURUGn09GtWzemT59Ot27d2L9/P++8807kuKVLlxIMBmnfvj1PP/00DRocnnmfnp7Oeeedx6effopef/hvFZ/Pxz/+8Q8ALrzwQqZPn06PHj0i9ycmJjJixAimTp1aredUVkwTgGXZbDYaN25MUlJSTV1SiCqRFuDo27zpIM4iLwDNelUjAcjhNuDaXAG4c6fa7mw1GslISNA4moppc6paBbhy524Ka3l7NUAwGOTeaV9TVPp5MOrMf5Noi26rdTgBGAgEKCoqPMGjK67HyRcy/Nx/A7Br1y6uvPLKYy7MEkIIIYQQojZp0aIFV1555VFvT0tLY9y4cQBMmzat3GPvvvtuzGbzUW8fP348NpuN4uJipk+fHnn77NmzKSgoQK/X88ADD5R7zocffhidTkdeXh5z5sypylMCYNu2bcyfPx+73c5tt91W7mNMJlOkkK1sq3M4z1VYWIjb7a7Q9ebOnRsZl/fCCy+g08U+PVdjCUAh6oojEoDSAhwVq1buityu6gKQsMMJwNpZAZifn0dRUREAzdJSUWrh5t/yhOcABoJBFmzZqnE0J/bxkmWROPt1uYQ2TXtH/RrJZVq3y35fiIYzBtzEaf1uAGDt2rXceOON+EqrRoUQQgghhKitBg4ceFQra9n7QG2JLVvJFzZo0KByj0tISKBXr16AujciLDwzu1OnTmRllV9I0qRJEzp27HjE46ti4cKFgDrjsEWLFmRlZZX777nnngOILHwEOPXUU0lLS2P//v3069ePKVOmsHXr8f+mWrRoEQAdOnSgdevWVY67MgxVOejRRx+NdhwRDz/8cMzOLURFhL9R6XQKiYlHvzohKm/FcvWbY2JDO8mNq1cRZyltAS72FAMhoHZl2Pbs2QuAXlFonJKscTQV17RzFuYEE15nCb9u2sKwrp21DumYduQe4qmZswDISG7G2X1ujsl1LAYDJoOBEr+f/Px8GjeK7rza4ef+G0fhftb9+QNz587ln//8Jy+++OIxf6ESQgghhBBCa02aNKnQfTk5OaSlpR3z/mMde/DgwSPOcaLjQG0t/vPPP484trL2798PgN/vr9CInrKVfqmpqXz00UdcffXVrF27NlIJmZmZyZAhQ7jmmms477zzjjg+fI0WLVpUOebKqlICcNKkSTH7A0USgEJr4Uqf5BRrjZThxoPwApBmPbOq/b0jXAEYDIXwekvKLSHXivrDQh142zApCYO+7nz+6A06WnZvzMbfd7Bo6zatwzmmQDDIP6d9hcfnQ1F0XDLoX5gMlthcTFFItlrIKXJGvQIQQKfTMfqSFyly5rBj53I+/vhjmjZtyj333BP1awkhhBBCCCGOLbyht3379mzYsKHSxw8bNozt27fzxRdf8NNPP7FgwQJ27drFp59+yqeffsr555/Pt99+q2mOocpXLrvV91j/TvS4v98vRG0QrgBMSZb5f9Fw8GARe3aryZPqzv+DwwlAqH1twNnZ2QQCQQAa1aHqv7DWvZoCsPNQHnvyC7QN5hjeX7CY5TvUhPIZJ19B84axrVQMzwF0Fjnx+aPfoms0mrn2yrfJzDgJgGeeeSaqg36FEEIIIYSIpn379lXovszMzCodW3aBRvgce/fuPW5Me/bsOerYymrYsGHkWuFkYGUlJSVxww038Mknn7Bz5042bdrEhAkTAJgxYwZTpkyJPDbc0hyeH18TqlQB+Msvvxz3/ldffZWvvvoKnU7H2WefzZAhQ2jTpg12ux2Xy8WWLVv4+eefmT17NsFgkIsvvpg77rijSk9AiGgrKCgAZP5ftKxaUXb+X3QTgB6Ph+TklGqfM1r27lV/8NhMRlJtdS+B3Krn4dL6RVu2cdkpPTWM5mh78wt4YfbPADRMbcXgXtfG/JpJ1sMfR0eBg/T06C4aAbDZUrhhzPu88dbFFDlzmDBhAg0bNmTw4MFRv5YQQgghhBDVMX/+/BPe17Jly6Paf8P3t2zZ8qi3u1wuli9fDkDPnof/BundW53zvX79erKzs8udA7hv3z7++usvgMgcwaro378/AE6nk/nz50fld/G2bdvy/PPPs2nTJmbMmMG8efMiC0b69esHwIYNG9i2bVuNzAGsUgXgwIEDj/nvm2++4euvv6Zjx46sXLmSmTNnMmHCBC644AKGDBnCBRdcwIQJE5g5cyarVq2iQ4cOfPXVV3z33XeRgZFCaClSAZgiCcBoWFGaADRaDTTsUP3kidly+HULt7v2VAC63S4KChxAafVfHRzjltkyFXuamvBaWMvagEOhEA9/OwN3SQkKChedcQ8GvSnm102yHm4vDr84EAtpqU25/pp3MZls+P1+brjhBtauXRuz6wkhhBBCCFEVO3bsKLdjJT8/P1Lhdtlll5V77PPPP09JSclRb3/llVdwu91YLBZGjBgRefvQoUNJTU0lEAjw5JNPlnvORx55hGAwSHp6OkOHDq3KUwLU1t9wEvDee+/F4zn235qhUAiHwxH5f3nPqSxraVGB1+uNvG3w4ME0b96cUCjEhAkTCAaDVY69oqLafDxnzhxefvll0tLSmDt3Ll27dj3u47t06cLcuXNJTU3lpZde4qeffopmOEJUSXjWl1QARsfK0gUgjbs1QG/UV/t8Op0SSQIe75tyTcvenx25nVW6Br6uURQlUgW4cMu2WjWa4Yd1fzL3r40A9Ol0Ycxbf8P0Oh0JFjUJGMsEIECTxl24avTr6HR6XC4XV1xxBbt3747pNYUQQgghhKiM5ORkbr75Zj766CN8PnVEzrp16zj33HM5cOAAKSkpkbbXv9u1axcjR45kx44dgPr33EsvvcRDDz0EwPjx44+oHLTZbJH7Xn31Ve6///7I3+t5eXn885//5K233gJg4sSJkURbVb322mtYrVZWrFjB6aefzk8//YTf74/cv3XrVl577TW6devG9OnTI29/+umnOf/885k6dSrZ2Yf/LiwqKop0yII6JzDMYDDw0ksvAfDtt99ywQUXsHr16sj9TqeTadOmMXLkyGo9p7KimgCcMmUKiqJw4403RvqnT6Rhw4bceOONhEIh3nzzzWiGI0SVRBKAKXWvhbO28XhKWP+nOsshGu2/YdbSNuDalADcX/qNPtlqwWoynuDRtVfrnuocwINFRWzLydU4GlWhp5hHvvsegERbOmf3ualGr59SWgVY4HAQ65Roh3aDGHnBE4C6Ae3yyy+PyQISIYQQQgghqmLcuHF07dqVa665hsTERFJSUujWrRtLly7FbDbz6aefltuqC/Duu+8ye/ZsWrVqRWpqKklJSfzf//0fgUCAc845h0mTJh11zPjx47n11lsBNdGWkZFBWloamZmZPPfccwDcdtttURkr16NHD6ZPn056ejorVqxg6NCh2Gw2MjIysFgstGnThjvvvJM//vjjiOWWwWCQmTNncuWVV9KoUSMSEhIiz++uu+4iEAhw4YUXcvPNNx9xvZEjR/L666+j1+uZOXMmPXr0wGazkZ6eTlJSEqNGjTrhCL7KiGoCMNyz3b1790od16NHDwCWLl0azXCEqLRgMCgJwChat2Yvfr9ayhzNBKDFGk4Auk/wyJrhdDpxOp2Auv23Lis7B3DBltrRBvzsrDkcLCoC4Pz+d2ExJdTo9ZNK5zn6fT7cblfMr9en12jOOvMfAGzatIkxY8ZQXFwc8+sKIYQQQghxImazmV9++YVJkybRsmVLvF4vGRkZXHbZZaxYsYJzzjnnmMdefPHFzJ8/n/PPPx+9Xo/BYKBr16688MILzJw5E7PZfNQxiqIwZcoUZsyYwfnnn096ejpFRUWkp6czYsQIvv/+e15//fUjEnLVMWTIEDZv3szjjz9O3759SUhIoKCgAIvFQs+ePbntttuYNWsWV1xxReSYW265hSlTpnDZZZfRsWNHjEYjTqeThg0bMmzYMKZOncrXX3+NXn90R9xtt93GH3/8wa233kqbNm0IhUL4/X46dOjA9ddfzxdffBGV5wVVXAJyLAcPHgSO7GuuiPDjw8cLoZWioqJI7720AFff0qU7AFB0Cs16RLECsDQBWOwphlAIovTNvqqys/dHbjdMStQwkupLbZxESqNECvYXsWjrNsb0P1XTeFbu3MXHi5cB0L55Pzq3OqPGY0gu00pQUODAbrPH/JpnnfkPChz7WL5yGosXL+b222/n7bffRqeL6ut2QgghhBBCVJrFYmHixIlMnDix0sf279//iPbZiho+fDjDhw+v9HFVkZqayr///W/+/e9/V+jxjRs35tZbb41UKlZWhw4djtgQHCtR/UsiNTUVOP5WmPKEH5+SkhLNcISotPACEJAlINGwdPF2ALI6ZWBJOvrVnKqyWtTlD8FQiOJKvuAQC9nZBwBItVkxG6P6uoomwlWAi7ZuJ1ADw2iPJRAM8tA30wmFQpgMFi44bXzUXtmrDJvJhKH01TpHjOcAhimKwsUXPEG7NmrC87vvvuPBBx+sVXMZhRBCCCGEEHVHVBOAffv2JRQK8dFHH7Fo0aIKHbN48WI++ugjFEWhb9++0QxHiEorO2tLKgCrp8TrZ9VKdYFBi1MbR/Xc4RZgAI9b2zZgl8uFy6W2hTao49V/YeEEoMPjYWNpclMLny5dzvp96mzFwb2uIyWhYrNlo00BUkrbgGO9CKQsvd7I1Ze/TuNG6sKTt99+m8cff1ySgEIIIYQQQohKi2oCMFzuGB7gOGXKlMhWmL/z+Xy8+eabnHvuuZGtKuPGjYtmOEJUWtkKwGSZAVgta9bswetVv7Zb9IluAtBaJgHo1ngRSNnRBRkJ9SMB2OLkwx+vZTt2ahJDgdvNc7PUzfAZyc3o1+USTeIIC7cBFzmd+AOBGruu2ZzADWPeIzOjNQCvvPJKZNixEEIIIYQQQlRUVHvVzjnnHG688Ub++9//4nK5uP3223nggQcYMGAAbdq0wWaz4Xa72bJlCwsWLMDhcEQqGW688UbOPvvsaIYjRKWVre5JlRbgagm3/6JAi1MaRfXcZrMBnU4hGAxpvgk4nABMtJixmup++y9AcoMEUrISKcguYum2HVzbv+ars1+YPZcCt/qxHd7/Dgx6bTcrR+YAhkIUFjpIS02rsWsnJmRy8/UfM+Wd0eTl7+I///kPJpOJf/zjHzUWgxBCCCGEEHXBwoULufjiiyt1zMsvv8zo0aNjFFHtEfW/Vt966y1sNhuvvfYaoVCIgoICvv/++6MeF078KYrCnXfeyYsvvhjtUISotCNmAKZKBWB1LFmyA4BGUZ7/B4ACFosBt9unaQKwpMQbSRpnJtbsZtpYa3FyIwqyi1i2YyehUKhGZ+/9tT+bjxerW+E7tBhAu2baLiIBSLaVWQSSX1CjCUCA5KQsbrlBTQIWOPbx+OOPYzabGTt2bI3GIYQQQggh4tO8efOqdNygQYNqdIRNSUkJBw5UboyR1kUlNSXq6wQVReHll1/m119/5aKLLsJkMhEKhY76ZzabGTlyJL/99hsvvfSSJoPdhfi78AxAs9mA1WrSOJq6q8TrZ3Vk/l+TmFzDUroIxOPRbgbgwYM5kduZifWj/Tes+clq1WZOkZMdh/JO8OjoCYVCPPLdTIKhEAa9keH9bq+xax+PQa/HblYT2TU5B7Cs1JSm3HLDJyQlqRu1H3roIV566SVNYhFCCCGEEKI2CiccK/Pvuuuu0zrsGhGzfrUBAwYwYMAASkpKWLNmDfv27cPpdJKQkECTJk3o1q0bJpMkWETtEq4AlPl/1bN27V6Ki9X5n9FeABIWngOo5as1ubm5AFiMBhLNUa5y1NgRcwC376BVRnqNXHfm2j9Ysm0HAKd1G01aUmw+f6oixWbF5VWrPkOoy0FqWnpaC2657iPeeu8qCosO8MQTT1BUVMSDDz4oL6QJIYQQQgghjinmA6tMJhOnnHJKrC8jRFSEKwBl/l/1xHL+X1h4E3BxsZdgMIhOF/WC5uMKhUIcOnQIgDS7XZtsUAylN03GnmrFle9h6fadjDqlV8yv6S4p4cmZPwKQZM9gYPerYn7Nyki2WtmbX4DP58PtcmG32zWJIzPzJMbe9DnvvH81efm7eeWVV3C5XDz55JM1/nUghBBCCCGEqBvkLwUhyggnAFNSJQFYHUuWqAnArI4xmP9Xquwm4OLimq8CdDgckQ3m6QnaJIJiSVEUmndTk7fLtu+okWtO/uVX9jsKARh26jhMxtpViZtSZg5gfkG+hpFAelpzxt70OZkZJwHw3//+l7vuuivyOSmEEEIIIYQQZUkCUIgyIglAaQGuspISP6tWhOf/xa5902I5nAB0u2s+AXjokNr+qwBp9vqZMG5ROgdwV14+2aWJuVjZV+Dg7V8XANAyqxtdTxoc0+tVhdVkwqjXA+oiEK0lJ2Ux9qbPaJzVCYDPPvuMq6++GqfTqXFkQgghhBBCiNpGEoBClBGeAZiaVv8qumrKujLz/1rGMAFotR1OAGoxBzA8/y/JaokkheqbFt0Ot2/Hugrw2R/n4PX7UVA4r/8dtXKencLhKkCtFoH8XYI9nVtumErL5r0B+Pnnn7nwwgsrvflMCCGEEEIIUb9JAlCIMsIz3VKlBbjKys7/a35K7BKARoMevUH9FlbTCUC/34fD4QBK5//VUw1PSsdsV5c1Ld2xM2bXWbdnL9+sWgNA97Zn0ySjXcyuVV3JNvV7g8vlosTn0zgaldWaxE3X/Y+unYcBsHbtWoYNG8amTZs0jkwIIYQQQghRW8R8CYgQdYXH48HtdgOQmiYJwKpatKh0/l+HDKzJMdyMq4DVYsTp9EY+bjXl0KFDhELq7fo4/y9Mp9fRtHNDti7dzaqdu2NyjVAoxBOliz+MejNDT7kxJteJlhTr4fEABQUFNMjM1DCaw4xGC1eOeo2Zs57k94X/Zffu3QwfPpwPP/yQfv36aR2eEEIIIUTc2r9hg9YhlKu2xiViRxKAQpQKz/8DqQCsKo+nhBXL1UqxVgOaxPx6FquaAKzpCsDcXLVS1KDTkWyt3/Mim5UmAP/an43L68Vujm5Sd876DSzZtgOAAd1GkZzQIKrnj7ZEixlFUQiFQhTk59eaBCCATqdjxLAHSU1pwowfHqOgoIBLL72U1157jZEjR2odnhBCCCFEXPpu4oNahyAEIC3AQkSE239BZgBW1fKlO/GVBABoPaBZzK8X3gTs8dRwBWDp/L80u41aOKouqpp2zgIgGAqxds/eqJ7bFwjw9PezAEiwpnLGyVdE9fyxoNPpSLJYgNozB/DvTut3PVeNfh2DwUxJSQm33HILr776KqFw2aoQQgghhBAi7kgFoBClyiYA06QFuEoW/L4VAL1JT/NTGp3g0dVns6rz6Xw+Pz6fD6PReIIjqs/tduMpLgYgrR63/4Y17dRA3X4RgpU7d9PvpNZRO/fHi5exvbSackjvGzCb6sbXXbLNisPjweFwEAyF0NXCLHDXzsNITGzABx/fjNudz6OPPsru3bt58sknMRjkR78QQgghRKzJi6+itpEKQCFKhTcAA6Sm1v/ETiws+H0LAM17Z2G0xD7JcMQm4BqaA5ifX+bzxFY3ElbVYUkwk9kyFYCVu6I3B7DQ4+GVn34BoEFqS3q1Hxa1c8daeA5gMBikqLBQ42iOrWXzXtx+y5ekp7UA4L333uPaa6/F5XJpHJkQQgghhBCipkkCUIhSR7YA1//ETrTl5jjZuOEAUDPtvwDW0gpAoMYWgeTlqbMiTQY9dpPpBI+uH5qVtgGv3rU7aq9kvjZ3PvmlH7Nhfceh19WdqrRk2+G5j/m1tA04LCO9Fbfd8iXNm/UAYPbs2Vx44YUcOHBA48iEEEIIIYQQNUkSgEKUClcAms2GyGw5UXELF2yN3G49oGmNXNNiNUZm8NVUAjC8LCbVZlNbY+NA084NAchzudlxKO8Ejz6x3Xn5fLBgMQBtmp5Cu2anVvucNclkMGA1qd8jCsosD6qtEuzp3HL9J3TpdC4Aa9asYdiwYWzatEnjyIQQQgghhBA1RRKAQpQKVwCmptlQauFMr9ouPP/Plmohq1NGjVxTUcBiURMxNZEALC4ujmwcTomD9t+wZl2yIrdX7txV7fM9++McSgIBFEXHsL7jqn0+LaRY1Y9/bV0E8ndGo4WrRr/Gaf1vBGD37t0MHz6cVatWaRyZEEIIIYQQoiZIAlCIUuEEYJpsAK60UCgUmf/Xqn9TFF3NJVBtNrUN11UDCcAj5kSWaQOt79KbpWBJNAOwqppzANft2cv0NesA6NnuXLLSordUpCaF24C9Xm8kKVzb6XR6Rgx7kAvOexhFUSgoKOCSSy5hyZIlWocmhBBCCCGEiDFJAApRKpzcSU2Nn8quaNm6JYeDB4qAmmv/DbNYa64CMLwAxKjXYzebY3692kKnU2jaSW0DXrmzegnA//w4BwCD3sSQ3tdXOzathBeBQN2pAgwb0O96Rl/yAjqdnqKiIkaNGsVvv/2mdVhCCCGEEPWKoih15t+cOXO0fneJGiAJQCFKRRKAsgCk0sLtvwCtT6vZBGC4ArCkpIRAwB/Ta4UXgKTarJHZg/GiWRc1Abgx+wBOr7dK51iwZSu/b1Y/V/p1uYRke2bU4qtpdrMJg079EZpfUPvnAP5dj5Mv4spRr6LTGXC73VxxxRXMmzdP67CEEEIIIYQQMVJ31i4KEWORGYCp0gJcWeH23/RWySQ3TqzRa5dd2OJ2e0hMjM31vV5vpMownub/hTUt3QQcDIVYs3sPA9qcVKnjQ6EQ//lBfWXRYkpgYPcrox5jjVIUkm1WDjldFOQXaB1NlXTtPIwxV77JR5+Ow+v1cu211zJt2jT69OmjdWhCCCGEEPXGyAsep1GjDlqHcZT9+zfw9XcPah2GqEGSABQCNTkhFYBVU1LiZ+niHQC0HtCsxq9vtZoit91ud8wSgPlHzP+Lv8+RJh0bqFuPQ2obcGUTgN+v+5O1e/YCMLD7VVjNNZsojoVkq5oALHI68Qf8GPR170dqx/aDueaKN/nwk1silYBff/013bp10zo0IYQQQoh6oVGjDrRqcYrWYQghLcBCABQVFeHz+QBZAlJZy5buxO0uAWq+/RfAaitbARi7OYD5+Wqbp0GnI8ESP/P/wix2Ew1apQGVXwTiCwR4btZPACTZM+jX5eKox6eF8CIQQiEcBQ5tg6mGDu0GcfmlL6IoOgoLC7n88svZtav6256FEEIIIYQQtYckAIXgcPsvyBKQypo3dyMABrO+xheAgLqgwmxRK69imgAsXfSQHIfz/8KalbYBr9q1m1AoVOHjPl+2gh256tfY4F7XYTTUjwRqcplFIPl1bBHI33XrMpxLLnwKgJycHK666ioKCws1jkoIIYQQQggRLZIAFILDC0BAWoArIxQKMffnDQC07NcEY5l5fDXJVtoG7IlRAjAQ8ON0qluOyyZ94k3T0kUgBW4POw/lneDRKndJCS//9AsAmSnN6dnu3JjFV9P0Oh2JFgsABXVwEcjfndJrFGed+Q8ANmzYwE033YTfH9vFOkIIIYQQQoiaIQlAIZAKwKrati2X3bvUxEe7M1toFkd4EUisKgAdjkLCBW/xnABs0rFB5Paa3XsqdMx7vy8ip8gJwNBTbkKvq3tz8o4n3AZcUOAgRMWrImurs878B927XgDAL7/8wqOPPqpxREIIIYQQQohokASgEPwtASgzACts3s8bI7fbapkAtJVWABYXEwwGo37+gjLtnclWS9TPX1dkNEvBVJpsXbN77wkfn+9y8+a83wBo1qAjnVqeHtP4tJBSmhAO+P04SxOddZmiKFw68j80b9YDgMmTJzNz5kyNoxJCCCGEEEJUlyQAheBvLcBSAVhhv5TO/2vYIZ3kxtptdbWWaT32eDxRP384AZhgNmHQx++3TZ1eR+MOmQCRjb7H88Yvv1Lk9QJwTp9bUerh8MTIIhCOTBTXZUajmatGv47dpi59ufPOO9m+fbvGUQkhhBBCCCGqI37/khWijHAFYGKiBaNRr3E0dYPD4WHFcnVTqJbVfwC20gpAiE0bsMNRAMR3+29Ykw5qG/Afe/fhCwSO+bi9+QV8uGgJAO2anUqrxt1rIrwaZzEYMBvUtua6vgikrJTkRlx+2UsoikJRURE33ngj3tJkrhBCCCGEEKLqsrOz+fzzz7n33nsZMmQIqampKIqCoijs2LEjZteVBKAQHK4AlAUgFffbr5sJBNR2W60TgGUrAN1uV1TP7Xa7KCnxAZIAhMNzAL1+P5uyDxzzca/8PI8Svx8FhbP73FxT4dU8RTk8BzC/7i8CKatdm9MZMuguANatW8ezzz6rcURCCCGEEELUfVOmTGH06NE8++yzzJ07t8Y6iSQBKARlEoDS/lth4fl/tlQLTU5ucIJHx5beoMNkUis33e7otgAXFDgit8u2e8arJh0bRm4faw7gjtxDfLliFQBdTxpMo/Q2NRKbVsJzAD0eT72rkhsy6E5aNO8FwKuvvsry5cs1jkgIIYQQQoi6TVEUmjdvzsiRI3n88cd5+eWXa+S6kgAUAsjNzQWkArCi/P4Av87fDECbQc3R1YK5eLHaBBx+Ncao12EzmY7/4DiQ1MBOQunXybE2Ab/80y8EgkEURceQXtfVYHTaSLYd/r6RX8+qAHU6PaMufg6j0UowGOSOO+6I2bZtIYQQQggh4sGDDz7Izp07+eqrr/j3v//NGWecUSPX1f6vdiFqgXAFYJpsAK6Q1av2UFCgVtq1O7OltsGUCm8CjlUCMNlqpR7usKg0RVEibcBr9hydANx84CDfrl4LQI+255CR0qxG49NCosWMXqf+OK1PcwDDMtJbct45/wJg69atPP300xpHJIQQQgghatqgQYNQFIVJkyZRXFzMI488QseOHbFarWRmZjJq1CjWr19/1HHz5s2LzLcDWLhwISNGjCAzMxOr1Uq3bt148cUXCRxnvjjA999/zwUXXEBWVhYmk4msrCwuvPBCfvzxx6g9x+uuuw5FUbjuuusA+OSTTxgwYABJSUkkJibSv39/vvjii2MeH36e8+bNY+/evdx22220bt0as9lM9+7dI4/T67XZOyAJQCGQFuDKCm//1Rl0tD69qcbRqMIVgB6Ph1AoFJVzBgJ+nM4iAJJk/l9EOAG46UAOzr+1vL40Zy6hUAidoufMnmO0CK/GKYoSmQ9Z3yoAw/qecjVtWg8A4K233uKPP/7QOCIhhBBCCKEFr9fL4MGDmTRpEtu2bcNkMpGbm8u0adPo2bMns2fPPuaxX331FQMHDmTGjBn4/X78fj/r1q1jwoQJDB8+nJKSkqOOCYVCjB07luHDhzN9+nRycnKw2+3k5OTw3XffMWzYMO64446o/Q0YNnbsWK666iqWLFmCoig4nU4WLVrEZZddxmuvvXbcYzdt2kT37t2ZPHkyBw4cwGg0HvfxNUUSgCLu+f3+SJWXtABXzLzSBGDzUxphSTRrHI3KZlUrAEOhEMXF0ZkDWFhYRPjniCwAOaxx6SbgUCjEH3v3Rd6+ft9+vl/3JwC9OwwnLamRJvFpIaV0PmRRURH+gF/jaKJPp9Mx8oLHMBhMBAIB7r33XoLBoNZhCSGEEEKIGjZ58mTWrFnDBx98gNPpxOFwsGbNGnr37o3X62X06NFkZ2eXe+wNN9zAWWedxbZt28jPz8fhcPD888+j1+uZNWsWEydOPOqYF198kTfffBOA++67j9zcXPLz88nJyeHuu+8G4PXXX+fVV1+N2nP87rvv+OCDD5g8eTKFhYU4HA62bdsWadW99957I0VE5bn77rtp1KgRCxYswOVy4XQ6j1s5WFMkASjiXkFBQeTVgtRUaQE+kd2789m86SAA7TTe/ltWuAUYwOWKThtwYeHhBSBJltqR6KwNGnfIjNxeW2YRyAuzfwbAoDcyqMfVNR6XlsIJQEIhCvILNI0lVjLSWzHo9HEALFu2jE8++UTjiIQQQgghRE1zOBy89dZbjBkzJlLZ1q1bN2bNmkVmZiYFBQW88MIL5R7btGlTvvnmG1q1agWAzWZjwoQJTJo0CYCXXnrpiMSa2+3mscceA+DOO+/k6aefJjU1FYC0tDSee+45brnlFgAeeeQRPJ7oFILk5+fzzjvvMHbsWGyl875btWrF1KlTMZlMeDweZsyYcczjDQYDc+bMoX///pG3tWmj/WJESQCKuHfo0KHIbWkBPrFw9R9A28G1KQF4uKw6WnMAHY5C9dxGI0aDNnMaaiNbkoW0psnA4UUgq3fv4ee/1M+NPh0vIDlB283QNU2dEanONamvbcAAg04fR3qa+nX/6KOP1uvnKoQQQgghjtaiRQuuvPLKo96elpbGuHHqi8XTpk0r99i7774bs/noworx48djs9koLi5m+vTpkbfPnj2bgoIC9Ho9DzzwQLnnfPjhh9HpdOTl5TFnzpyqPKWjNG/evNzn2LhxY/r06QNw3JE4Y8aMoWHDhlGJJZokASjiXtkEYFq6VACeSDgBmN4qmfSWKdoGU4bRqMdoVJN0LpcrKucMVwAmWS1ROV99cngRiFoB+MIstfrPaLBwRvejf1jWdzqdjiSL+nlSn5NiRqOZC89/BFCf54svvqhxREIIIYQQoiYNHDgw8sJ3efcB7Nixo9wW2UGDBpV7XEJCAr169QJg5cqVkbevWLECgE6dOpGVlVXusU2aNKFjx45HPL66evfufczn2KRJE+D4v/P369cvKnFEmyQARdwr+41JKgCPz+XysnjxdgDa1pLtv2XZIpuAq58A9Pv9kVbiRIskAP8unADcm1/A7D//4rfNWwDo13kkibZ0LUPTTHJpG7DD4ajX8/Hatx1I+7aDAHjnnXfYsWOHpvEIIYQQQoiaE06Anei+nJycKh178ODBo85xvONAbS3++7HVkZiYeMz7LKV/G/p8vmM+JjMz85j3aUkSgCLuHdECLEtAjmvB71vxlajr2dvWovl/YeEEYDRmABYWFkZuSwXg0cIJQIDnZ/0EgNlo4/STL9cqJM2F5wAGg8EjPn/qo/PO+ReKosPn8/HEE09oHY4QQgghhBC1hl5fO8dHSQJQxL3c3FwADAYdSUmS6DmecPuvOcFE897ll2BrKTwH0OPxVLsC68gFIPJ58XdZbTLQ6dUfIZsOqK+09e96GTZLspZhaSrFevgFhPrcBgyQ1bA9vXteCsA333xzRKuGEEIIIYSov/bt21eh+8qrgqvIsQ0aHC40CJ9j79695R4TtmfPnqOOFUeTBKCIe+Gy4rQ0OzqdfEkcSzAYZN7cTQCcdEYz9Mba96qGrcwmYI+nelWA4QUgNpMRg14+L/7OaDbQoHVq5P8WUwIDul6qYUTaMxr02EuHGtf3BCDA2YMnYDSqVY/h7WxCCCGEEKJ+mz9//gnva9myJWlpaRU+1uVysXz5cgB69uwZeXvv3r0BWL9+PdnZ2eUeu2/fPv766y+AyBxBUT75q1bEvXALsCwAOb4/1u0jN9cJQLta2P4LRyYAq9sGHK4AlPl/x5bUICFyu3+XS7Gajz0rI16E24DzCwoIaRxLrCUlNeT0/jcA8Pvvv7NgwQKNIxJCCCGEELG2Y8cOpk6detTb8/PzmTJlCgCXXXZZucc+//zzlJSUHPX2V155BbfbjcViYcSIEZG3Dx06lNTUVAKBAE8++WS553zkkUcIBoOkp6czdOjQqjyluGHQOgBRM2LRg15b+9orq2wC8Fibfuqa8POI5vMJV/+hQNuBLVCofe+rsglAt9td5efv8/lwuz0AJFmtUCPPtfa9P08kb4+aJNXrLfRoP6IOPoPKO9FzTLFZ2ZtfgN/nw+VykZiQcIIj6rYzBtzMgsUf4PU6ef755znjjDO0DimivvyMqo/CHxv5GNUd8rGqveTrqW6Sj5eoy5KTk7n55psJBAKMHj0ao9HIunXruOmmmzhw4AApKSlMmDCh3GN37drFyJEjef3112nZsiUej4c333yThx56CIDx48cfUTlos9l46KGHmDBhAq+++ip2u517772X1NRU8vLyeOqpp3jrrbcAmDhxIlarNfbvgCgIBoNHLCMtKCiI3M7PzyehzN8QaWlpUetUlARgnEhNTT3xgypBr9dH/ZxaCX/hZWYmYjSaTvDousVgMEbtXPN+UROAzXpmYc+ondWSBp0Oi8VAcbEfj8eDyVi15+9wFERuJ1ut6JRYF0sr6OpY8nnn2n3k7iwAoFnjwfhDJpR63kJfkeeXZj/8w7rQ4SAtrX58nzyWZFMmZ5x2I3N+fpnffvuNtWvXMnDgQK3Dqlc/o+qzpKQkrUMQFSBfT3WDfD3VHfI1Jeq6cePGMW/ePK655hpuuukmLBYLDodaGGA2m/n000/Jyip/Xvy7777L6NGjadWqFSkpKTidTvx+PwDnnHMOkyZNOuqY8ePHs3HjRt58802efvpp/vOf/5CcnIzD4YjMfb/tttu44447YvOEY2DXrl20atWq3PvKtkADbN++nZYtW0blupIAjBPRmkeVlJSEXq8nEAjUmy2X4VXhqak2fL6jy5HrIkVRMBiM+P0+QqHqNyJmZxfyxzp18GrbQS0IVXPBRizZbCaKi/04nUWUHGc1+/EcOnT41ZgEs4lgKDbPV036KUCIYBQ+TjVp3vvLANDrzTRrPBiHx0PDpPrbAqzodBX6vDcb9FiMRop9PnJzc2nSpEkNRKetAadez2+/v0uxt4iHHnqIb7/9VrNY6uPPqPpIr9eTlJREYWEhgUBA63DEMcjXU90gX091h3xNRY8kULVlNpv55ZdfeOaZZ5g6dSo7d+4kIyODM888k4kTJ9K5c+djHnvxxRczf/58nnrqKRYtWoTBYKBjx45cf/313HXXXeVWxyqKwpQpUxgxYgRTpkxhyZIl5Ofnk56eTt++fRk3bhzDhg2L5VOuNyQBGCdi8QtBffglIxAIRFqAU9NsUUmW1SahUCgqzym8/Reg7eAWhGrxdDOrzQR5blwuV5Wfe/gVLLvJVLoAJFbPt2zVX+19n/7dnvUH2LpsNwAtWwzBaEzA4fHUoWdQOZX9KKXYrGQ7fOTl59e77ynlsVqTGdDvOn6e9yq//fYbv//+O/369dM6rHrxM6q+CwQC8nGqI+TjVPvJ11PdIh8rUddZLBYmTpzIxIkTK31s//79mT59eqWPGz58OMOHD6/0cZXx/vvv8/7771f5MRX93b9ly5aa/J1Qv/u1hDiB/Pz8SNlwuiwBOaZwAjC5cQIN2h29zak2Cc8B9HpLCJSWk1dWZAGIVRaAlGf+BysAMBjNdOiqDuktKi6Oi2RXRYQXgXiLi/F4PBpHUzNO63cDJpMNgNdff13jaIQQQgghhBB/JwlAEddyc3MjtyUBWL7iYh8LF2wFoO2ZLWr9opQjNgG7K78JuKSkBI+nGIAk2QB8lH0bc9i8aCcAnbsPJyWjAQDBYAiX16tlaLVGitUWuR2t8Qu1nc2WQp/eVwAwa9YsNm7ceIIjhBBCCCGEEDVJEoAiroXbfwHSM+r3ts6qWrJ4Ox6POkuv7eAWGkdzYkdsAna5Kn182ZksSVIBeJT5HywHQG8wcXKfS7AkmCP3FZYmTuOd3WzCUDq/JF4SgACn9bsenU6dLPLGG29oHI0QQgghhBCiLEkAiriWk5MTuZ2WJhWA5fnlZ7WSx2g10Kpv7V9oYLEYCRcputxVSQCq7b8KkCgVgEfI3pLLxt93ANDp5GHYE9IxWgzojOqPksJiSQACoCiRNuD8ggJtY6lBqSlNOLnr+QBMmzaN7OxsjSMSQgghhBDxZuHChWRlZVXq32effaZ12DVCloCIuFa2BThNWoCPEgqFIvP/Wg9oisFc+79lKDqwWo243T7crsq3ABcWFgFgM5vQ62p3u3NN+/3jVQDo9Ea6n3oZoCZKrQlmXPkeqQAsI8VmI7fIicvppMTnw2Q0ah1SjRh42i2sWvMNPp+Pt956i4cffljrkIQQQgghRBTMmzevSscNGjSoRmeFl5SUcODAgUodEy9zu6UCUMS1cALQbDZgt5tO8Oj4s2njAfbtUyvi2p5Z+9t/w8JtwFWZAVhUpCYAEy3mEzwyvuTtdfDnL+osyPZdziIhMSNynzlBfX87vd7IUp14l2q1Rm4XxFEbcKOsjrRrcwYAH374Ia4qtOELIYQQQghRVeGEY2X+XXfddVqHXSMkASjiWngGYFq6vdYvt9DCL3MPD/JvO6gOJgArmXwIBPy4S5OGCWZp/y1r4WdrCAVDgEL3PpcecZ+1dA5gKBTCWSyLQEBtH9eVVpDG0xxAgNP63wCAw+Hgyy+/1DgaIYQQQgghBEgCUMS58AxA2QBcvnlzNwHQqEsmiQ3rzvsonAD0+/2UlJRU+Lhw9R/I/L+ynHluVn2/AYDW7QeQknbkLMiyi0AcMgcQAEWnkGwpnQMYZwnAtiedTkZ6SwDeeeedGm35EEIIIYQQQpRPEoAiroVbgGX+39Hy8lysWrkbqFvtvwDWMpuAK1MFGJ7/B5AgLcARS75cR6AkAECPU0cddb/BpI/MhyyMk/kZFRFeBFJYWIg/ENA4mpqj0+nof+oYAP766y8WLlyocURCCCGEEEIISQCKuBZuAU5PT9A4ktrn13mbI5U77QbXrQSgrUwC0F2JTcDhCkCzwYDZoI96XHVRsauEpV//AUCTFt1p0KhduY+zlM4BlEUgh6XYbIDaGu2Io23AAL16XIrJpL6w8vbbb2scjRBCCCGEEEISgCKuRSoA02waR1L7hOf/JWTaaNQ5U+NoKsdsNqDXq/PXXJXYBFxUVAjIApCyVny3Hq9TbaPu2ffo6r+wcBuwu6QkrqrdjifZZo3MFs3Ly9M4mpplsSTSu8clAPzwww/s3r1b44iEEEIIIYSIbwatAxBCKyUlJRSUVuVIBeCRSkr8/PbrZgDaDmqOoqtjC1IUtQqwqMiLu4ItwKFQiKIiJyDtv2H+kgCLp60FIKNhG5q06HHMx1oSD1ddFhUXk2qXtnq9TkeSxYLD44m7BCBA/1PHsHDJhwSDQT7++GP+9a9/aR2SEEIIIUSN279/g9YhlKu2xiViRxKAIm6V/YM8LUOSFWWtWL4LZ5G6zbXt4JbaBlNF4QSgs4IJQJfLRTAYBCBRNgADsHb2Jopy1fdfz76jjrsp22I/nDQt9EgCMCzVbsXh8eAodBAIBNDr46e1PDPzJFq36su27Yv55JNPuOeeezAY5NcOIYQQQsSXr797UOsQhACkBVjEsXD7L0BamiQrygq3/+qNOlr3b6pxNFVjK01Iud1uQqHgCR9fdgOwVABCMBBkwaerAUhObUyrdgOO+3i9QYfRagRkDmBZKTb1e0soGMLhcGgcTc3r0+tyAPbv38/cuXM1jkYIIYQQQoj4JS/Fi7hVNgGYLluAjzDvZzUB2LJvE0x2o8bRVI3drrakhkIh3G43dvvx27yLCtX5f3qdgs1kOu5j48GG33dwaFcBAN37XIpOd+LKNWuCGZ/HR2GxJADDUkrnAIZCIfLy8khLS9M6pBrVpdO52KwpuD0FfPjhh5x99tlahySEEEIIUSNmz56tdQgV1qlTJ61DEDVAEoAibkkCsHw7th9ixw51O3LbM+vW9t+ybPbDSTyn03XCBGBhaQVggtnMcTpd48aiz9YAYLWn0q7LWRU6xpJgojAHin0+Svx+TNLuiV6nI9FiptBTTF5+vtbh1Dij0UyP7iNZsOg95syZw/79+2nUqJHWYQkhhBBCxNzQoUO1DkGII0gLsIhbR7QASwIwYv68TZHbbQfV4QSgzRRJ5LkqMAfw8AZgmf+3Z/0Bdv+RDUDXniMwGCpWEWlJPHIOoFCl2tQt446CgsicyXgSbgMOBoN88sknGkcjhBBCCCFEfJIEoIhb4QSg3W7CYqmbba6xMP8XNQGY3jqF1OZJGkdTdTqdEvm4ulzO4z7W6y2mpMQHyPw/ILL5V28w0an78AofZ7abCGddCz2emMRWF6WUJgCDwSAFjgJtg9FAVsN2tGjeC4BPPvkkLpOgQgghhBBCaE0SgCJuhROAUv13mMvlZcmS7UDdrv4LC88BPFEFYGHh4QUg8V4B6Djg5M95WwFo13kIVltyhY/V6RTMttJFIDIHMCLFZo3czs+LvzZgOFwFuGvXLubPn69xNEIIIYQQQsQfSQCKuBVOAKanH382XDxZvHAbvpIAAG0GNdc4muoLbwJ2Oo+fAAy3/yqoMwDj2dKv1hEKhADo1vuiSh9vSVDff4WeYgiFohlanWXQ6yOJ5bz8PI2j0Ua3LudhNicC8NFHH2kcjRBCCCGEEPFHEoAibh06pC66kAUgh80rbf812Y206F33B/WHKwADgQDe41SkhSsAbWYTel38bgAp8fhYMX09AM1a9SIto/JVoJZE9X3uCwQo9vmjGl9dlmpX24ALChxx2QJrMtno3m0EALNmzaKgoEDbgIQQQgghYkxRlDrzb86cOVq/u0QNkASgiFvhCsDUNEkAAoRCocgCkNYDmqI36TWOqPpstjKbgI/TBlxUZgNwPFv940aKnSUAdOs9skrnCFcAAjhkDmBEuA04GAjgcDg0jkYbvbpfAoDX6+Xbb7/VOBohhBBCCCHii0HrAITQysGDBwFIz5AEIMDGDQfI3q+2wtaH+X8ANnuZBKDTSXp6+lGPCQQCuN1uIL7n/wWDocjyj9T05jRr1atK5zHbjCg6hVAwRGFxMQ2T6+4imWgKbwIGyMvPJzU1VcNotNG8WQ/S01pyKG8Hn332Gddee63WIQkhhBBCxNzjFzxCh0YdtA7jKBv2b+DB7yZqHYaoQZIAFHHJ6XRGkj6ZGTIDEIhU/wG0GVj35/8BGI16TCY9JSUB3MeoAHQ6D28IjucKwM2Ld5K3R61M69Z7JIpStVZoRVEw200UF3nVOYACUOcAJljMOIu95OfnAa21DqnGKYpCz+4jmTP3RZYtW8a2bdto3Tr+3g9CCCGEiC8dGnXglBZVe3FdiGiSFmARl3JyciK30zMlAQgwb66aAMzqlEFiw/pTFRmuAjxWC3C4/RcgwRK/CcDFn6vVfxZrMu06D67WuSyJ6vuxqLiYkCwCiQhXARbkF8Tt+6Vn94sjt6dNm6ZhJEIIIYQQQsQXSQCKuFQ2AZghFYA4HB5WrdwFQNsz60f7b5jdpiajXC5nufc7nWoC0KDTYTHEZ1F09pZctq/cC0Dn7udhMFYvEWpNKF2+Egzi9pZUO776IpwADAQCOAoLNY5GG2mpTWnd8lQAPv/887hciCKEEEIIIYQWJAEo4tIRCUCpAOS3XzcTDKoVSfWl/TcsXAHo9Zbg9/uOur+oSE0MJljMEKcLgJd8sQ4Anc5A557nV/t8ZReBFB5n+3K8CS8CAcjLy9MwEm2FqwB37drF4sWLNY5GCCGEEEKI+CAJQBGXpALwSPN/Udt/rakWmpzcQONoostuP5yMcpXTBuyM8w3Abkcx637aDMBJHU7HnnD0opTKMlqN6Azqj5dC2QQcYTQYsJd+nuXHcQKwa+dhGAzq++Hzzz/XOBohhBBCCCHiQ3z2u4m4F94AbDTpSUqK382vAIFAkF/nqwmgNqc3Q6evX68LHLkJ2EVyckrk/16vlxKfWhUYr/P/Vn2/AX9JAIAuPS+IyjkVwJJgwl1QLBWAf5Nqs+HyesnPzycUClV52YoWPMWFHDq0k0N5O3EUZuPxOPAUOyguVpPoCgqKTofJaMVmS8NuSyEhIZP0tOakp7XEalU3QlssiXTpeA6r133Ht99+y1NPPYXVaj3epYUQQgghhBDVJAlAEZfCFYDp6fY69Qd4LPz5xz7y89SNyG0G1a/2XwCL2YBerxAIhI6qAAzP/4P4rAAMBkMs//ZPADIatqFh4w5RO7clwYy7oJiiYi/BYAidLr6/zsJS7Vb25OcTCAQoLCokOSlZ65DK5fN52bVnFbt2rWTn7pXs3rsGpzO3Wue029JolNWRpk26kZrWDFC3cM+ZM4cLLohO8lkIIYQQQghRPkkAirgUTgBmZCZqHIn2Fvy2Rb2hwEmnNdM2mFhQwGYzU1RUfNQikPD8P4jPBOCWJbvI36cuo+jSc0RUk+HhOYChUAint5gkqfACIKV0EQhAfl5+rUoAOl2H+GvjXP7a8BObtvyGz3f89m2LwUqiKQmbyY5O0REKhQiGQnh8LhzefEoCRy6Acbnz2LJtAVu2LTji7Y8//jh2u53TTjsNcxx+HQohhBBCCFETJAEo4lK4BTgjw65xJNr77Vc1Adiocya2tPqZpLHbTRQVFeN0HlkBWFQ6/89iNGCoZ63PFbHsG7X6z2xJoE3HgVE9tyXxcOt1oUcSgGEmgwG72YTLW0JeXh4tW7bUNJ5AwM+mLb+ybMXn/LXxZ4JB/xH3Kyi0TD2JTpkn0zqtHU2Tm9M0qQUN7I0wG46drAuFQhT7PeS6D7KncCd7HbvY5djOxtw/2XJoA77g4YU827dv5/LLLycpKYlzzz2XCy+8kEGDBmEymY55fiGEEEIIIeqqjRs38vXXXzNv3jzWrVtHTk4OFouFNm3aMGzYMO666y4aNmwY9etKAlDEpUgFYJwvAHEWFbN61W4AWp/WVONoYic8B9DjcRMMBtHp1GRfURwvAMnfV8jmxTsB6ND1bIzG6M7CNJoM6E16AiUBmQP4Nyk2Gy5viToHkBCKBuunvV4ni5d9zO+L3qewMPuI+zJtDRnQ4kz6NR9IlwY9SDQnVfr8iqJgNdpoltySZsktoUxxsS9Qwpa8jSzZOZ+FO35mi2Mr/pCfwsJCPv/8cz7//HPS09MZNWoU11xzDW3btq3msxVCCCGEEKJ2WLBgAaeddtoRb0tOTqaoqIhVq1axatUqpkyZwtdff80ZZ5wR1WtLAlDEpcMVgPGdAFyyeDt+fxCAk06vf/P/wsKbgEMhcLmcJCYmEQodngkYjwtAln37J4TU2517nB+Ta1gSzLjy3BR6JAFYVqrNxt78Avx+P4WFRSQnVT7BVlVudwELFr/PgsXv4/E4Im9PMCVxdpvzObftRbTP6BzT2ahGvYmOmV3pkNGVASndcXkL2Rvcz8bizfy8YS5FXieHDh1i8uTJTJ48mb59+zJu3DjOPffcSPJeCCGEEEKIusjn82EwGBg5ciRXX301gwYNIikpCa/Xy+zZs7nzzjvZuXMnF1xwARs3boxqJaAkAEXccTqduN3q0ot4TwD+/ttWAIw2A816RL/EuLZISDic4CsqUhOAbreLYFBNfsZbBaDP62fVzL8AaNaqN8mpjWNyHUuCCVeeG5fXSyAYRC/JGwBS7YfnAOYdOlQjCUC/v4RFS//HT7+8HNnaC9A+ozOXdb6Gga3Oxmyo2Y3oigKJSQ3x5RXT2tCSG86+ntBFMG/TPD5bMY35m38jGAqyePFiFi9eTOvWrbntttsYPXo0Fkt8b28XQgghhBB1U5s2bdiwYQMnnXTSEW83m82MGDGCNm3a0LNnTxwOB2+++SYPP/xw1K4tf42JuBNu/wVIz4z3BOBmAFqe2gS9Sa9xNLFjtRojW2idTnXxR7j9FyAxzpIJf8zdgqfQC6jLP2LFmng4sSpVgIepcwDV982hvLyYX++vjT/z4mvnMuOHxyPJv+5Zp/DcuW/z1oWfc3bbC2o8+ReWnKS+8BAKhThw4ABmg4lzOp3Nu9e8zW93/8I/zryDdHs6ANu2beOee+6hT58+fPDBB/h8vuOdWgghhBBCRNGgQYNQFIVJkyZRXFzMI488QseOHbFarWRmZjJq1CjWr19/1HHz5s1DUZRIh8nChQsZMWIEmZmZWK1WunXrxosvvkggEDju9b///nsuuOACsrKyMJlMZGVlceGFF/Ljjz9G7Tled911KIrCddddB8Ann3zCgAEDSEpKIjExkf79+/PFF18c8/jw85w3bx579+7ltttuo3Xr1pjNZrp37w5A06ZNj0r+ldWxY0dOPfVUAFasWBG15waSABRxqGwCMJ4rAHftymPnDjX5cNLp9XD7b1kK2EurAJ1ONQES3gCsUxSscbZsYNnXfwCQmNyQ5q17x+w65oQyi0BkDuAR0kqrAAvy8wmGQjG5htOZy0ef3s77H91E7qHtAJyU1p4Xz3uXV87/gD5NB8S01bciLJYkTCb1fbF///4j7muc3Ijxg+9iwd3zePLCx2id0SryuHvuuYf+/fszbdq0E/6yKIQQQgghosfr9TJ48GAmTZrEtm3bMJlM5ObmMm3aNHr27Mns2bOPeexXX33FwIEDmTFjBn6/H7/fz7p165gwYQLDhw+npKTkqGNCoRBjx45l+PDhTJ8+nZycHOx2Ozk5OXz33XcMGzaMO+64g1CUf6ceO3YsV111FUuWLEFRFJxOJ4sWLeKyyy7jtddeO+6xmzZtonv37kyePJkDBw5gNBorde2MjAwA/H7/CR5ZOZIAFHHniARgHFcALvx9a+R2fV4AEpZQOgcwnPgLVwLazSZ02uZAatSe9QfYt0H9Gujc43x0uthVfhoMeowWddJEoccTs+vUReE24EAggKOgIKrnDoVCrFk3gxdePYd1f34PQIoljX+e9gjvXPQFvRr3jer1qkMBkpKyAMjPz6fYe3Si2Gw0c0Xv0cy58wdeHfUirdLVROCOHTu47bbbGDJkCAsWLKjJsIUQQggh4tbkyZNZs2YNH3zwAU6nE4fDwZo1a+jduzder5fRo0eTnZ1d7rE33HADZ511Ftu2bSM/Px+Hw8Hzzz+PXq9n1qxZTJw48ahjXnzxRd58800A7rvvPnJzc8nPzycnJ4e7774bgNdff51XX301as/xu+++44MPPmDy5MkUFhbicDjYtm1bZCnHvffeS95xOnnuvvtuGjVqxIIFC3C5XDidzuNWDpbl9/sjv9t26dKl+k+mDEkAirgjFYCq33/bAkByk0TSW6VoG0wNCM8BLC4uxu/3x+0G4GXf/AmAXm+kQ9ezY349S+n7XSoAj5RqKzMHMIptwF6vk0+njeeTz+/E5VbPe27bi/j4spmM6HAZ+hgmfKsqOTE8fzRE9v7yf1kE0Ol0nN91OLPvnMl/Rj5Fk5QmAPz5559cdNFF3HLLLezZs6cGIhZCCCGEiF8Oh4O33nqLMWPGRCrbunXrxqxZs8jMzKSgoIAXXnih3GObNm3KN998Q6tW6gu6NpuNCRMmMGnSJABeeumlI343drvdPPbYYwDceeedPP3006SmpgKQlpbGc889xy233ALAI488gidKRQf5+fm88847jB07Flvp7+2tWrVi6tSpmEwmPB4PM2bMOObxBoOBOXPm0L9//8jb2rRpU6Frv/baa2RnZ6PT6bj22mur90T+RhKAIu6ENwAbTXqSkuJr9luY3x9g0YJtAJx0WlPN2wBrgr3MIhCHwxH54RBPCUBPkZc/56qJ35M6nIHVlhzza1pK5wAWl/jwRbmEvS4z6PUkWdXvP9FKAO7P3sArky9g9brvAMiwNeCZsyfzwMAnSTTH/mNdVWazHYs5EYDs7P0neDQY9AYu63kJc/8xiweH3U+iWX0h5+uvv6ZTp048/fTTMh9QCCGEECJGWrRowZVXXnnU29PS0hg3bhwA06ZNK/fYu+++G3M5f3+NHz8em81GcXEx06dPj7x99uzZFBQUoNfreeCBB8o958MPP4xOpyMvL485c+ZU5SkdpXnz5uU+x8aNG9OnTx8A/vjjj2MeP2bMmCpt7125cmXked5555106tSp0uc4HkkAirgTrgDMyEiIi8RXedau2UtRkVqR1fq0ej7/r5S9zDy6Q4dyI7cTLPGTAFw7exP+EnVeWqfu59XINS0yB/CYwlWA+QUFBEo3UlfV8pVf8NqbF0Vm/Z3e4iw+uORb+jUfWO04a0JS6TIQh8OB2+2q0DEmg4kb+1/Pz+Nnc1nPSwD1VeL777+ffv36sW7dupjFK4QQQggRrwYOHHjMv6MHDlR/99yxY0e5L3IPGjSo3OMSEhLo1asXoCbBwsJLMDp16kRWVla5xzZp0oSOHTse8fjq6t279zGfY5MmahdKfn7+MY/v169fpa+5a9cuLrzwQjweD3369OGZZ56p9DlORBKAIu6EE4Dpcdz+u+B3tQpM0Sm06tdE42hqhtlkwGhUv+U5HIWRt8dLBWAoFGLFdHUrV2p6c7KaRPfVpGOx2E3qoDdkE/DfpdrtAISCQQqqOAcwGAww44fHmfb1P/H7vegVA3f0/RePn/Vyra76+7vwHEDgmDNjjiUzIYP/jHyKr26ZRrcmXQFYvXo1Z599Nk899RRerzeqsQohhBBCxLNwAuxE95UdvVWZY8Mde2XPcbzjQG0t/vux1ZGYmHjM+ywWtYvneB0nmZmZlbre/v37Oeuss9izZw+dO3fm+++/L7dSsrokASjiTvibQkaGXeNItLN4oVol1KhLJtaUOGmDVsBeugjE5VIrjIx6HWaDQcuoaszevw5ycJv6Klyn7ufVWPWrTq/DZFVng0gF4JFSbNbIxyHv0KFKH19S4uZ/U8fx28L/ApBpa8hrI/7HqC5j6lx1s8lowWJJAiA7+0CVztGj2clMv/0r/n3evzAbTPj9fl544QWGDBnC2rVroxmuEEIIIYQQx6TXV3zu9sGDBxkyZAibN2+mTZs2/PTTT6Snp8ckLkkAirhTtgU4Hnk8JaxetRuAln3jo/ovLDwHMLxePsFsiVSn1XcrvlOr//R6I+06D6nRa1tL5wAWeoohFKrRa9dmep0uMgfwUCXnABYWHWTyO6NYv0Gdc9I+ozNvXvgZnRucHPU4a0q4DbioqLDCbcB/Z9AbuG3QWGb/43t6NusBwMaNGzn33HN54403CFaz1VoIIYQQIt7t27evQveVVwVXkWMbNGhw1Dn27t173JjCi+DKHlsXHDp0iLPOOou//vqLFi1a8PPPPx+z1TkaJAEo4s7hCsD4TACuXL4Ln0+dAxcv7b9h4U3AodIkVLzM/yt2evkjsvzjdCzWY5e0x4I5nHj1+ymWRSBHSCudA1jocOAPVOx9k5e/m8lvX8a+/epG59NbDOGV4R+QYa9bv/D8XVLi4firWgUY1qbBSXx+0yc8OOx+THojPp+PiRMnMnr06Eq3GAshhBBCiMPmz59/wvtatmxJWlpahY91uVwsX74cgJ49e0be3rt3bwDWr19/zN/h9u3bx19//QUQmSNYF+Tn5zN06FDWrVtH48aNmTt3Ls2bN4/pNSUBKOKK0+nE7XYD8ZsAXLRI3f6rM+po1it2ry7URgkJRyb84mX+37qfNuMrVpNLHU+umeUfZVnLLgIp3b4sVJE5gKEQ+XnHHiQcdjBnK5PfGUVe/i4ARnW5lsfOehmr0RbTOGuCyWiNtAEfOFD9JJ1ep+fG/tfz9a1f0DazDQDz5s1j0KBB/PTTT9U+vxBCCCFEPNqxYwdTp0496u35+flMmTIFgMsuu6zcY59//vlIN1ZZr7zyCm63G4vFwogRIyJvHzp0KKmpqQQCAZ588slyz/nII48QDAZJT09n6NChVXlKNa6wsJBzzjmHVatW0bBhQ+bOnUvr1q1jft34GH4lRKmyg0jTM+MzARie/9e0e0NMNqPG0dSs8AzAsHhIAKrLP9RXxFLSmtGoaecaj8FsN6HoFELBEA5PMQ2Skmo8htoq2WpBpygEQyHy8vKOOzB4774/+e8HY3C51Xbhm3rdxTXdb61z8/6OJymxIcXFhRQWFuLxuLFaq5/Y7NSoI9+N+4onfnyaj5Z+wqFDh7jyyiu5++67ueeeeyo1o+XvgsEgDoeDnJwccnJyyM3NpbCwEJ/PF/kXDAaxWCzYbDbsdjs2m40GDRrQqFEjMjMzq3V9IYQQQoialpyczM0330wgEGD06NEYjUbWrVvHTTfdxIEDB0hJSWHChAnlHrtr1y5GjhzJ66+/TsuWLfF4PLz55ps89NBDAIwfP/6IykGbzcZDDz3EhAkTePXVV7Hb7dx7772kpqaSl5fHU089xVtvvQXAxIkTsVqtsX8HVJPL5WL48OEsW7aMjIwMfvrpJ9q3b18j15YEoIgrZROAmXFYAVhUWMwf69T5CfE2/w/AYNRhMusp8aot0Haz6QRH1H37NuaQvTkXgE4nn6tJskhRFCwJZjyFxTjcUgFYlk6nI8VmJc/lPu4cwH371/P2+1fh8TgAuKvv/Vza5ZqaCrPGJCU24GDOZkDdBtyqVXReCbUYLTw2YhJntDmde766j8LiQp577jlWrFjBlClTym1RKSsQCLBlyxZWr17N5s2b2bp1K9u2bWPbtm0UV2O5jV6vp0GDBrRs2ZIOHTrQoUMH2rdvT+fOnUlJSanyeYUQQgghYmXcuHHMmzePa665hptuugmLxYLDof6Oajab+fTTT485x+7dd99l9OjRtGrVipSUFJxOJ/7SEUHnnHMOkyZNOuqY8ePHs3HjRt58802efvpp/vOf/5CcnIzD4YjMd77tttu44447YvOEo+zLL7/k999/B8DtdnPWWWcd87HNmjVj2bJlUbu2JABFXIn3CsBlS3cQDKrz7+Jt/l+YzWqkxBtApygY9PV/CsKK6eryD53eSLsux/7hEmvWRDUBWFhcTDAYQqerP1Vr1ZVqt5PnclNUWjlmNB5ZmZt9YBPvvH8NHo8DBYX7zniM89pdrFG0sWUyqW3AxcWFZGcfiFoCMGxoxyFMH/cV46beyfrsv/jll18YMmQI7777Lj169Ig8zu12s2jRIhYsWMCqVatYvXo1TqczqrGAmljcv38/+/fvZ9GiRUfc1759e/r06UOfPn3o27cvLVu2jPr1hRBCCCEqy2w288svv/DMM88wdepUdu7cSUZGBmeeeSYTJ06kc+djdxxdfPHFzJ8/n6eeeopFixZhMBjo2LEj119/PXfddVe5nRGKojBlyhRGjBjBlClTWLJkCfn5+aSnp9O3b1/GjRvHsGHDYvmUo6rsUjq32x0ZUVYei8US1WtLAlDElbIJwHicAbi4dP6fwWKgyckNNY5GGxarHgogGArV+0SU113Cup/UaqrW7QZgtSVrFosl8fACFmdxMUm22l+eX1PSbDa2lt7Oy8ujYcPDX5s5udt4+/2rIm2/957+aL1N/oUlJTYobQN2RK0NuKzmac358pbPeHjGI0xb+SV79uzh/PPPZ/z48ZhMJubPn8+SJUvKnU8DYDCbSW/ZkoxWrUlv2YqUxk2wp2eQkJ6OPT0dS2ISBpMJvcmIzmBEURR8xcX4PB58HjfFTifOnIMUHjhA4YFsCrOzydm2lYObN+POP1wFunHjRjZu3Mj//vc/AFq1asVZZ53FWWedRf/+/aP+C6EQQgghREVZLBYmTpzIxIkTK31s//79mT59eqWPGz58OMOHD6/0cZXx/vvv8/7771f5MeFlk8dz3XXXcd1111U+uCiQBKCIK+ENwEaTnqSk+PvjadFCNQHYvFcWBnMczp0Kgdl8uOrP6fWSZK2/nwfrftqCz6OW1Hfqru2rYtakw/MWCzweSQCWkWi1oNfpCASDHCqTAMwv2MPb712N06m2cE/o/zDD21+iZag1IimxIQdz1K3VBw4coGXLVlG/hsVo4ZmLnqBjZgeemvMMJSUl/Oc//znqcXqjicadO9Ok28k0Pbk7Tbt2I7V5C3S6ylUPm6xWTFYrUNpq3L5DuY9zHsrl4KZN7Fm7hl0rl7Nr1Uo8BQUAbN++nbfffpu3334bq9XK0KFDGTlyJEOGDKkT826EEEIIIYS2JAEo4kq4AjAjI6FeDc6viLxDLjZuOABAyzht//UHAlithxOfhcXF9ToBuHKGuvwjObUJjZt10zQWg1GP0WLAV+zHIZuAj6AoCqk2G7lOJ3mlcwDd7gL++8F1OAr3A3DHqfdxUafLtQyzxqhtwIkUFxeRnZ0d9QSg1+tl37697N27l8auhtzTdTyT/3qbghJ1do3JbqfHxZfS4czBtOjdB2MNVtolpGeQ0C+D1v36A2qLSO62bWxbtIBN8+exfcki/F4vHo+H7777ju+++46EhATOO+88LrvsMs4444xKJyeFEEIIIUR8kASgiCvhBGB6HLb/Llm8PXI7Xuf/Bfx+DEYdBoOC3x+iqNirdUgxc3B7Hvs2qBWvHbudUysS3pZEsyQAjyHVriYAXU4nTlch/5t6Mzm5amPwdT3GMarrtRpHWLPUbcBFOBwOPB5PtSvcQoTIOZjDnj17yM3NOaI9o0VSCx4d+DivrHqNLbkbKXG52LZwAf2vvb5Gk3/l0el0NGjThgZt2tD3mmsp8XjYsWQxf/00mz9n/4inoACn08nnn3/O559/TosWLbjqqqu44oorjjl8WwghhBBCxCd5mVjElXALcEaGXeNIal54/p85wUSjzpkaR6ON8IYpq1V97aPIU/XtnbXd6h83AqAoOtp1HqJxNCpr6RxAr89Psc+ncTS1S5pdnXMXCgWZ+vk/2LFzOQDD213C9T3rxkazaEpKbBC5feBAdpXP4/f72bFzB7/9+hurVq0kJ+dgJPlnSUqmYfsOtBlwOt36DeH1m6cyuPN5AORs3cKUSy9i+9LF1XsiUWayWmk36EwufPwp7luwlGvefo/uF12Mya7+TNu5cydPPvkk3bt357rrrmPx4sUVmkUjhBBCCFFfLFy4kKysrEr9++yzz7QOu0ZIBaCIK4dbgBM1jqTmLS6d/9eiTyN0hvjM/fsDAQBsNgNFRT6cXi/BENS3PSABf5C1szYB0KxVL+yJ6RpHpAonAAEcbg+WZONxHh1fEsxmDHod6zd9xp798wDo2+wM7j5tYq2o3qxpJpMNizmRYm8R2VWYA+h2u9m8eQt79+4lEPBH3q43mkjOyiK5cWPM9iMrwc1GCw9d/CwtM9vw7rxX8BQU8P5113DBo0/Q69JRUXle0aQ3Gmk3cBDtBg7ifNej/PHDTFZ8/im7V68iEAgwc+ZMZs6cSc+ePRk7diwjRozAYJBf+4QQQghRNfPmzavScYMGDarRFyRLSko4cOBApY7xxEmHkvwmKOJKvFYA5uQUsX37IQBa9GmscTTaCVcAJthNHMBDMBTC7fWSYDGf4Mi6Zeuy3Tjz1HXy7bsM1Tiaw8x2E4peIRQI4fB4aJicpHVItYeikHPwV/bs/wWADhldmDT4eQy6+P0xnZTYgGJvEY6CAoqLPVgsJ24DdrlcbN6yhT279xAKBSNvtyQmktqsOUkNGqIcZ0aeoiiMOWMsLTJb89Q391Ps8/DNA/fh2LePM+/8R61NxprtdnpdOopel44ie+MGln/6Cau+/pISt5uVK1dyyy230LRpU2699VbGjBmDzRbdzcpCCCGEELVFTScc65L4LAMSccnpdOJ2q0mRjDibAbh86c7I7RanxmcCMBSCQGkFYGKCKfL2+jgHMNz+azIn0LJtX42jOUxRFCwJarJV5gAeafPupaze8AkADW2NeWLIa9iM8fVCxd8lJjWM3M4+wau4LreLdevW8ssvv7B7167S5J9CQmYDmvfsTYtTTiU5q9Fxk39lDex4Nq9c9z/SEjIA+OW1l/nmgfsI1IHW9az2HTh/4qPcM38hQ+++l8QG6vtxz549PPTQQ/Tu3Zs33ngDl8ulcaRCCCGEEKImSQJQxI1w+y9AemZ8JQCXLd0BgMluJKtjhrbBaCRc/QdgtxoxGNRKnsLi+jUH0F1YzMbf1YUvbTsNwmAwneCImhVuAy4q9hIMBk/w6PiQW7CbT39+lFAoiNVg4/5Tn8Kuj78xBX9nNtkwm9Xv1Qeyy58D6PV6Wb/+Txb8/jv79u1TX+1VFJIbNaZV33407doNW0oKVanba9eoE6/fMJUWGa0BWPnlND669UaKnUVVfUo1ypqczBm3jmPC3F+55D/P07B9B0D9WThx4kR69+7N66+/LolAIYQQQog4IQlAETfKJgAz46wCMJwAbNYzK27n/wXKJAANOj0JdjUxVlTPEoB//LyFgE9NrNWm9t+wcAIwFArVu/d9VRSXOPnfrAcoLnGioDCh90SaJrakpKRE69BqhaREtXqtoKCA4jKfL4GAny1bNvPbb7+ye/duQqEQiqKQ0rgJbfoNoEnnLpij0ObaKKUJr13/MSc37w3Alt9/479XjqawknNltGQwmeh+0cXc/t33XPnGmzTq1BmA3NxcJk2aRO/evXnnnXfkc04IIYQQop6Lz0yAiEvh+X8QXxWABQVuNm1Un3vzUxppHI12whWAOgV0OoXEMgnA+jQiYvUPGwBITW9Og0btNI7maJYyi0AK6vEW5ooIBgN89vNj5Dp2A3Bz9zvo3/R0AHy+knr1eVlV4QQgqNuAQ4TYvXsXv/76K1u3bj3c1t+gIa369qNxp86YojzfLtGazLNXv8OZnYcBkL3hL94adTEHNm+K6nViTVEUOp51NuO+ns5VU96mcecugJoIvP/++xkwYADffPONzMwRQgghhKinJAEo4kbZTUANMuOnvW7l8l2RP+jiegFI6SZQvU4PHJ4DGAiGcNeTypcD2w6xb4Na6dq+69BaubDAYNRjtKrbfx2lMznj1Zzl/2XT7iUAnNXyXK7odC1Gvfr5GQqBz1/7583Fmtl8uA147969LFq4iPXr10eq1WwpqbTofQpNunTFZI3dYguTwcRDFz/L5f1uAMCxfx/vXH4p25csjtk1Y0VRFDoMPouxX33HlZPfokFb9YWCHTt2cPPNN3POOeewYMECjaMUQgghhBDRFr/rBUXcCScALRYjCYn1a+vr8YTbf/UmPY27NtA2GA35/WqlkKF0CUBSmUUgDrcHu7l2zcqrijWlyz8URUe7ToM1jubYrIlmfB4fDk+xmumqhYnKWPtrxwJ+Xa0u/WiX1pF/nvoQiqKoCUAFCEFJSQkmo1HbQGuBxIQGeL1OiooOz94z2ew0aNsWe3pGleb7VYVO0TF26D00TGnMKz88QXFRER/cMIaLn3mebuePqKEookdRFDoOGUr7QYNZ9fWXzH35RQoPZLNq1Souuugihg4dymOPPcZJJ52kdahCCCFEnbZh/watQyhXbY1LxI4kAEXcCCcAMxsk1MrKqFhZVroBuGn3hhjMeo2j0UYwGIwsnAgnAK1WI0ajDp8viMPjoXFqspYhVlvAH2TNbLUlsVmrXtgT0zWO6NisiWYKDzop8fsp9vmxmOIryZVXuJ8v5j0FQJIpmcfOeBazwQKoSRmjTocvEMRXUgL2+N0EHAI8Hg/BwOHkvKLTkdn6JFKbNqvwRt9oG3nKlWQmNeSxL/+J11fMtAl3UXhgPwNuuLlO/mzR6fX0unQUXYePYNEH7/HbW1PwOouYM2cO8+bNY+zYsUyYMIGEhPgZnSGEEEJE04PfTdQ6BCEAaQEWcSQ8AzCzQfy0/7pcXv78Yx8AzfvE8/y/QOS2Xn/4215yoppYcNSDWXRbl+3GlecBaufyj7KsR8wBjK82YJ/fy9SfJlJc4gTg3/0fo6H9yK9No8FQ+lg/wTidx+YPBCjIz8dZ5ESnM6HXqwlSc0Iiac1baJb8Czut/RBeGPMeSdYUAGY98xTfP/EowUDg+AfWYiarlYFjb+P/fppH3zHXodPr8fl8vPrqq/Tt25dp06bJfEAhhBBCiDpMEoAiboQrAONp/t+qlbsJBNTKtxanxO/8vyM3AB/+tpeYoCainF4v/tL3U10VXv5hMifQsm1fjaM5PpPNiK40Eetw1/3ka2V8v/gN9uWqlZrXdLmRU5sMOOoxptI5gIRQqwDjSAhwud3k5eXh85Uu7jEYsCeq4wuKCwvx15L3SeemJ/P6DZ/QKKUpAIs/fJ/Pxt+Bz+vVOLLqsaelMfzBidz23fe07tsfUH9+3nbbbQwfPpw1a9ZoHKEQQghRN4RCoTrzb+jQ2l1AIKJDEoAiboQTgBlxtAE4PP9PZ9DRtEfD4z+4HgtvANbrlCNa9JLLVKIVFtfdRJTbUczGBTsAaNtpEAZD7Z5nqChKZBtwPFUArtnyE0vXfwtAz4ancF3XW8t9nEGvi4xFLKklya6a4PP7yc/Lx+V0qZlABUw2G7aUVBKSw1WSIYpyDh7vNDWqWXpLXr/hE9o3Vjfqrp/1Ix9cdzXuggJtA4uChm3bcd0HH3H5q2+Q3Fh9AWnZsmUMHTqUf/7znzgcDo0jFEIIIYQQlSEJQBEXAoEAubm5QHy1AC9bsgOARp0zMNnia85aWeENwIa/tQ0mJpZZBOLx1GhM0fTHz1sI+NQKxg5d68ard7ak0urLYi/+Otw2WVEH83fyza/PAZBuzeDBAU9ENlIfTYlsAy4pqf+bgEOAy+UmPz8/kqzXGQzYUlIw2dTNviZzAkaTervoYO1JAAKkJWTw4pj3OLXN6QDsXLGcd664jIK9ezSOrPoURaHzOcO464efOPOOf2AwmwmFQrz//vv069ePr7/+WtqChRBCCCHqCEkAiriQk5MTWQLRIE4SgMXFPtasVv8Abd4nftt/CR2eAaj/WwLQoNdhL02MOtx1NwG4+ke1/Tc1vTmZWe00jqZirMmWyO2COvy+rwif38unP02ixF+MTtEz8bSnSbMef0mLqXQOYCAQIFCPE6ThWX8uV5mqP7sdW0oKOv2Re8psCWobsLsgH7+vdlVG2kx2nhj9Gud1vxiAnK1beGv0Jexfv17jyKLDZLUy+K7x3PXDT3QYchag/ly95ZZbuOKKK9i5c6fGEQohhBBCiBORBKCIC+H2X4ifCsC1a/ZQUqJW07Q4JX4XgASCgUiFyt8rAOFwG3CBx0NdLGQ5sO0Q+zbkANC+69A6s4XUkmBG0amxFrjrdxvwj0umcCB/OwA3nXwb3Rr0OOEx4QpAqL9VgB5PMfl/m/VnS0nFZLWW+3hb6RxAQiGcOTk1FWaFGfRG/jniMa4beDugVir+96rRbFnwm8aRRU9q06ZcNfltrnhtCkkNswD4+eefOf3003n11Vfx+ern56oQQgghRH0gCUARF45IAMbJDMAVy3dEbjfrmaVdIBo7YgNwOS2XKclqAtAfCOKsg8P71/y4EQBF0dGu82CNo6k4nU7BUrqEpT5XAG7YuZDFf34NQK+sU7m805gKHafXKehKE6T1bQ5gMBiiwOGgqKhITborYLJZS6v+jtUWDWZzIgajmhysbW3AYYqicN3A2/nniMfQKXq8Lif/u/kGVn/zldahRVWns8/hzh9m03fMdSiKgsfj4dFHH2Xo0KGsWLFC6/CEEEIIIUQ5JAEo4kLZBGC8tACvWK62ZGWclIo1xXKCR9df4Q3ACke3AAOklGlFzXfVrUq0gD/AmtnqRtlmrXphTzh+W2ltYy2dA1hYXBxp0a9PCt2H+HL+MwAkmZO5v98j6JSK/thVItuAS3wl1MHi1HKV+Hzk5edR4lWTmjq9DmtyMiabvULHh7cBu/PzCNTiarPhPS7hyctfw2K0EvT7+fLeu5k/5Y16NS/PkpDI8Acncsu0r8nq2AmAP//8k2HDhvHvf/9bbesWQgghhBC1hiQARVw4WFototfrSE2zaRxN7IVCIVaWJgCb9Yzf7b9QdgPw4c2qZZlNeqwWddZYXWtF3bJ0N648tXquriz/KMuapCZfQ6FQnV7CUp5gKMiX857GXaxuSr2v70QybJmVOofRoCYAQ8EQ/tI22boqBLjcbgoKCggG1GSv0WLGmpKK3lDxBUXhOYChUIii3NrXBlxW37YDeWnM+6TY0gD46YVnmfHIwwTr2UzHpt1OZuyX33LufQ9gtFoJhUK89dZbDBo0iAULFmgdnhBCCCGEKCUJQBEXwhWA6Rl2dOVUgdU3O7YfIi9Prb5oGsftv3BkAvBYUkor0fLddWsO4Oof1PZfsyWBFm36ahxN5VmTzGppJvWvDXjhui/YsmcZABe2vZQBTQdW+hymMkswSmrZ0ovKCAaDOAocuJyHF31YEhMxJyRWemal2ZKEwagmjmtrG3BZHZp05fUbPqFpWgsAln7yEVPvGEdJPUt46w0GBtx4M3fOnM1J/QcAsGPHDi666CLuu+8+nE6nxhEKIYQQQoj6nwkRgsMVgPHS/rtyxa7I7Wa94jcBGAoR2aBq0B8nAVjaBuwLBHDVkTmAbkcxGxfsAKBNx0EYDCZtA6oCvV6H2a7GXdeqL49nX+5mZi99C4CWya0Z13N8lc6jKErk87akjnxe/l2Jz0deXn5kjqHOoMeWkorBbK7yOSPbgPPyIi3+tVmTtOa8dv3HdGzSDYANP8/h/WuvwpWXp3Fk0ZfatCnXvvc/Lnz8Kcx2dd7uu+++y8CBA/n11181jk4IIYQQIr5JAlDEhXAFYGZmfCQAV61UE4DWFDPprVK0DUZDAb8/MjutvA3AYeFFIAD5dSQRte6nzQT9aitlXWz/DbOVtgGrW5jrUPnlMZT4PHz286MEgn6MOhMPDXgSi6H8rbYVEZ4D6PP7Cdax94873PIbDLf8Wk646KMiwnMAQ6FgrdwGXJ4UexovjnmPAe3OBGD36lW8ffklHNq5Q9vAYkBRFHqPupw7v59F29PVytddu3ZxySWXcM8991BUVKRxhEIIIYQQ8UkSgCIuRBKAcVYB2KxHVqVb7OoTf6DsBuBjf7uzmA2ROYCHnHVjcP3q0u2/qenNycxqp3E0VReeAxgMhigqLtY4mur7fvEb5Dp2A3Brjzs5KbVttc5nMpS2AYfqzjbgUChEYWEhzqNafhOI9HxXg9mSjN5Q2gacc+AEj649LEYrj4x6mRG9RgFwaMcO3rxsJNsWL9I4sthIbtSYa955j5FPP4slUf3Z+8EHH3D66aczd+5cjaMTQgghhIg/kgAU9V4oFCqTAEzQOJrYKyz0sHmT2vIs8/9KNwArx08AAqSVbkrOd7sJBmt3pdWBrYfYv1GtfGrfdWidTvKGNwGDOoOxLtu4awnL/poOQJ9G/bmk/RXVPqdBf3h5TV1IAAYCAfLzCyguVluWdfrqt/yWJ1wF6KojbcBhBp2BCedN5ObB/weAp6CAD24Yw7JPP9E4sthQFIWeF1/KnTNn0/7MwQDs3buXSy+9lDvuuAN3Ham4FkIIIYSoDyQBKOq9goKCyB/O8dACvGrl7sjt5r0aaRiJ9sKJAYPuxC2Haalqm2YgWPs30oar/xRFR7vOgzWOpnoMRj0mq7oFti7PAXQXF/L1r/8BIMmUzH39Ho5SYlaJVAGWeGt3ArCkpIS8/PzDi3dMJqxRaPktjy1B3agcCgZx5uZG/fyxpCgKV512M4+NegWL0UrQ7+e7h//NzMcm1alkZmUkZWVx1ZR3uOTZF7AkJQHw+uuvM2jQIFatWqVxdEIIIYQQ8UESgKLeC1f/QXxUAK4qbf/VGXQ07pqpcTTa8gfCCcATf6tLTTZHKq1ya3EbcMAfYO2cTQA0a9ULe0K6xhFVX7gKsMDtoU6tYS5jxsJXKHIfAmD8Kf8i3Rq9r73wHMBgMBhJrtU2brebAoeDUGn1rMlmw5qUFLPqVIs1Bb1B/bwpOlh32oDLOr3DWbx6/Uc0SFIrtRf/7wP+d/P1eBwOjSOLDUVR6H7hSO6cMYuTBpwOwJYtWxg2bBjPPfdcrf3cFkIIIYSoLyQBKOq9sgnABnFQAbiytAIwq1MGxtLKqngUCoUIBNTlAydq/wV1I21yaSIqz1V7E4Bblu7GladWKNbl5R9l2Uq3MPsDAYqK69622z+2zWPNlp8AOLPF2QxueXZUz28MzwGk9rUBh0IcMe9P0SlYkpIw2Wwxv3Z4G7Ar7xDBMvM+65K2WR2ZctPndG7aHYCtC37nzVEjObhli7aBxVBSVhbXvvsBF056DIPZTCAQ4JlnnmH48OFs3bpV6/CEEEIIIeotSQCKeu/gwYOR2/V9CYjfH2Dt6j0ANOsZ3+2/ZatJDPqKfatLT1HbgIuKvXh9tbMaZfUPavuv2ZJAyzZ9NY4mOmzJh7fk1pUtzGFOdx7f/vYCAGmWdMafcl/Ur6FTlMjnsLcWJQCDwRAFBUfO+7Mmp2AwmWrk+pFtwHWwDbistIQMXhjzHmd3uwCAQ9u38+ZlF/HHDzM1jix2dDodA667gdu/nUnjLl0BWLlyJWeeeSbvvfdevdgILoQQQghR20gCUNR7ZSsAMzLrdwvwxg0HcLvVBEGzXvG+AKRiG4DLSk89nIjKKXJGPabqcjuK2bhgBwBtO52J3lAziZZYM5gOzwHMc9WdBGAoFOLr357H7S0E4J99HyLZnBKTaxlL24B9Ph/BWpAc8QcC5Ofn4fP5ANCbjDGb93csZmsyer36NVBX24DDzAYz91/4FGPPuhudoqPE5eKzf9zBD089TqD0fVwfZZ7Uhls++5JBt9+FTq/H4/Fw7733cvnllx/xs1sIIYQQQlSfJABFvRf+IyIl1YbJZDjBo+u2laXz/0AqAMPD9HWKgq6Cc8jsdiNWi/o5crCoKGaxVdW6nzYT9Kttze271I/23zBb6RbmAre7zlT/rNr0Ixt2LgDgvJMupF+T02N2LZOhNLEWAp/GVYAlJSXk5+dHWuyNVgvWpOQa30atoGArrQJ0Hqq7bcBhiqJwef8bef7q/5JqV2d7Lnzvv7x37VUU5eRoHF3s6I1Ghvzj/7hp6jTSWrQEYO7cuQwaNIiffvpJ2+CEEEIIIeoRSQCKei+cAMys59V/AKtWqgnA5MYJJDeq/8/3ePz+ii8AKSszXa0CzHe78ZUmOGqL1T9sACA1owWZWW01jia6wm3AgWCQQk+xxtGcWIHzADMWvgZAQ3sjbu81IabXM+r0kSU1Ws4BdHs8h5d9KGBOsGO2a/e9JjwHMBQM4DxUd9uAy+rR6lTeuvmLyFzAncuX8cZFw9m2eJG2gcVYs+49uP3bmZxy+ZUA5ObmcsUVV/DQQw/h9da92aBCCCGEELWNJABFvXc4AVi/5/8BrFqhLgBp1jO+23+hTAKwgvP/wjLS1OUFoRDk1qI24Oyth9i/SU1wdOgytMarrWItvAkYIN9de5ewAARDQb6a/wxenxrnv/pOxG6McRJMUSJtwFokAENAkdOJs8ipLvtQFKxJSRgt1hMeG0sWWwq6SBvwwRM8uu7ITGrIS9e+z8V9rgLAmZPD+9dexZznn63XLcEmm40LHn2CK16bgjU5GYApU6YwbNgwWRAihBBCCFFNkgAU9V4kAdigflfEZWcXsndvAQBN4zwBGAwEI3PSKjr/Lywp0YzJqB6TU4vagNeULv9QFB1tO5+pcTTRZzDqMdvVRE5tnwO45M9v2Lp3JQCXtL+CHlmn1Mh1TaXbgAOBIP4abHcNhaDQUYjHrW6fVvQ6rCkp6I3az6BUULAlZALg4uxjywAAzZRJREFUPJRb59uAyzLqTdx17r956OLnsJsTCIVC/PrmG7x9+aXk7dqpdXgx1ensc7j9u+9p0Vv92lq3bh2DBw9m6tSpdWZEgBBCCCFEbVO/B6L9jcPh4IsvvmDp0qUcOnQIs9nMSSedxHnnnUffvlXfpun3+5kxYwbz589n3759ADRp0oSBAwcyfPhwDIby381bt25lyZIl/Pnnn+zatQun04nFYqFp06aceuqpnHfeedhstirHJVThBGCDer4BeFWZ+X/N43z+3xEbgCuZAFQUyEy3sTfbSa7ThT8QrHQVYbQF/AHWztkEQPPWvbEnpGsaT6zYUix4XSUUuD0Eg0F0lfzY1YTcgt3MWvImAM0SW3Bz99tr7NqmMgs2SrwlGGyxr74LBkM4HI7Isg+dwYA1OQlFqT0fG3tiA5yOvYQCahtwUoOGWocUVUO6nEenJt147Kt/sn7vGvauW8vrFw5nxMRH6X7RxVqHFzPJjRpzw/+mMn/y6/zy2su43W7uuusu5s2bx7PPPktSUpLWIQohhBBC1Cm15zf4GNu1axd33HEH3377Lfv370ev1+NyuVi9ejVPPvkkb7/9dpXO6/F4+Ne//sW7777L1q1bCQQCBAIBtmzZwn//+18eeOABiouPnmc1b948/u///o9PP/2UdevWUVhYiMViwe12s3HjRj788EPuvPNOdu3aVc5VRUW5XC6cTrWNM7O+JwBXqe2/RquBhh3qZ4KoovwBNQGoUPkKQIAGGWriPRgK1YptwFuW7MaVr1Zf1bflH2XZktVFIKFQCIfHo3E0RwsGA3wx7yl8AS86Rcf9/R/BYqi5FlidTodep7Z+10QbcCAQJL8g/8hNv8nJtSr5B2CxpqLTq1uk61MbcFmNUpvyynUfcs3pY1FQKHG5+PLeu5l65zicufV3QYhOr+fMO+7ixo8+JblRYwC++uorhgwZwpo1azSOTgghhBCibqldv8XHiM/n4/HHH8fhcNCiRQtefvllPvvsMz777DOuvvpqFEVh+vTpVdo298Ybb7Bp0ybsdjv3338/06ZNY9q0adx///3Y7XY2bNjA5MmTjzouEAhgMpk466yzePTRR/n888+ZOnUqn332GePHjycpKYmcnBwee+wxGX5dDQfL/DFY3xOAa1fvAaBRl0x0hrj40j4mv19tA9TpdFWalZecZMFsVqut9jscUY2tKsLLP8yWBFq2OVXjaGLHmmQhvOmiNrYB/7b2U3YfXA/AlZ2up1NG1xqPIdwG7POVEMtOSL/fr276Lf1aMlrMmmz6rQhFOdwGXJSTQzBYu5b3RItBb+TGM+/ixTHvk5mkjnlYP+tHXj3vHNZM/7Zet8a26H0Kt3/3PZ3OOReAHTt2MHz4cD788MN6/byFEEIIIaIpLrIEs2bNIjs7G7PZzMMPP0yrVq0AMJvNjBo1imHDhgHw0UcfHdE6eCLbt2/n119/BeDOO++kX79+KIqCoij069ePO+64A1Cr/XbuPHJeT/v27Xn77be566676N69O2azOgDfYrEwePBg7r33XkBtX12wYEH13gFxLNz+C5CZUX9nAPp8Af78o7T9/OQGGkejvapuAA5TFGiYYQcg3+XGW4nvC9HmKvCwcaH6/aNtpzPRG7SfuxYrer0OS4L6/PJrWQJw/6Gt/LT8PQBOSm3HtV1v1iSOcBtwKAQlvthUAZaU+MgvKIgk0kw2G+aE2v0CSngbcDDgx3XokMbRxFb3lqfw7q1fc+7JFwHgLsjni7vH88ltt9TbCkgAa3Iyl7/yBudPfBS90YTX6+Xuu+/m9ttvx+Wq3YuDhBBCCCFqg7hIAM6bNw+AM844g8zMzKPuv+SSS1AUhby8PNatW1fh886fP59QKESjRo3o16/fUff379+fRo0aEQqFmD9//hH3NW3alNTU1GOeu1u3bjRooP5BI5vvqu6IBGA9rgDctPEAXq+apGpycv2af1VpIQhUcQNwWQ0zbeHTccCh3TKQP37eQtCvJmLqc/tvmC1FbQMuLC4mUEsqufwBH9PmPkEg6MegM/BAv0cxlrac1jSjXh8ukqTEG/0EYLHXS4GjgFAwBAqYExIw1YFZtFZbKjqdWh1ZeDBb42hiL9GazL8ufJJnrpgSqQbc8PNPvHLeUJZ/NrXeVkEqisKpV13DzZ9OI6VJEwCmTZvGueeey6ZNmzSOTgghhBCidqv3CUCPx8PmzZsB6NmzZ7mPyczMpGnTpgCVmimzdu1aAHr06FFuW5SiKPTo0eOIx1ZGeMB1oB5tNaxp8ZIAXFPa/guSAPQH/IQbwqpaAQiQYDeRYFOTPPsKCkCjLrNw+29qRgsys9pqE0QNsierM/VCoRAF7tpRBTh35QfsP7QFgOu7jeWkVA0/DoqCsbQKsKQkuuMhPB4PhY5C9XNdAUtiEkaLJarXiBVF0cVFG/Dfndr2DN4b+y3De1wKQHFhId8+9ABvj7qYvesq/3tHXdGkazfGfT2D9mcOBmDDhg0MHTqUr776SuPIhBBCCCFqr3qfANyzZ09kPkyLFi2O+bjwfbt3767QeUOhEHv27DnheZs3b16p84YVFRVF2obD5xCVF04A2mwmEhLMGkcTO+EEYEIDG0mN7BpHo63w/D+o2gKQsho1VNvGnd4SHJ6jl/nEWvbWQ+zflAtAhy5Da+X8tWizJJpRShddHHJq39a3++B65q/+BIBOGV0Z3fEajSM6PAcwEAge8fleHS63m6LShTeKTsGanILBVLfazW2JpW3A/vrfBlxWgiWRf454lOeueocmaervC3vWruHNSy/iu4kP4i4o0DbAGLGlpHDl5LcZes99KDodbrebW2+9lXvvvVdmJwshhBBClMOgdQCxlpeXF7mdlpZ2zMeF78vPz6/QeT0eT2S7b0XO6/F48Hg8WK0V2xj56aef4vP5sFqtDBgw4ISP/+ijj/jkk0+Oef8VV1zBlVdeWaFrH4+uNKGi0+mO28JcWxSU/uHToEEixjr2x2xlrF2jJgCbdm+IvrQ6CNQ/5BXqf9KorHD7r05RE4DVef5ZDexs3VlAMBhin8NBqj12rZC6cjarrvlhI6BWN7XtfGbMrl2b6HQKtmQLrnwPh1yuct8vNaXEV8wXvzxFKBTErDfzQP9HMOq0/7FpNhhwoiY4SnwlGE3VSPqHwOkswlU6c1HR6bAmJ6MzaP88K8tmT0enMxIM+nBk7yexnJEf9VmftqfxQasZfLrwXf736xS8/mKWTf2YP3/8nrP/7x76XH4VeqM2revHYjRUP56zbr+L1r1O4ZO7bqMo5yDvvfcef/75J1988QWNGzeOQpTxq679zhevwi8OJicny1KcWk6+poQQWqt7v+FXUjhJB0QWbZQnfJ/H46nQecs+riLnDR9TkQTgsmXLmDlzJgBXXnklycnJJzzG5XIdsfH279xu9xGJoepSFCWq54uV7Gx1FlSDhkn1NhFWWOhh65YcAJqcnAVHPM/6+ZyPJ7wARK/TV/tjbjToyUy3ciDHTbbDQfushhh0sfi8PzrOgD/A2tnqTKvmrXtjT8iIwXVrJ3uKFVe+B7e3hGKfD4tJm6TFrGVvketQq7dv7XEXzZKOXe1dk3SKgkGvwx8I4vV6sdurngAsLCyM/DzT6XVYk1PQ1YHv7eVSdNgSM3E69lGUm0MwEKi7z6WKTAYTY84Yy9ndRvDqj0/z24Y5uPPz+ebhf/P7e+8w7N776XLuebWmmjhaYZzUrx/jZ87ik3/cztZFC1m6dCl9+vThq6++KndGs6icuvI7X7zTVbPrQdQc+ZoSQmil3icA65pt27bx/PPPEwwG6du3LxdccEGFjrPb7ZGlIeWx2WxRmSWo0+lQFIVQKFQnZizt3bsXgIZZSYS0GuIWY2tWH24vVzcAh5+ngmaD67QSAl8UFoCU1bhhAgdy3ASCIQ44CmmSmhKV8x5W/sdp8+KduArUxEz7rmeX+5j6yp5qhe3q7Vynk6YavEq+de9KFq77AoCeWacwsv0o9Y5a8mEwGQz4AyX4fD5CwSBKJf/wC4VCFDocFBerlYQ6gx5rcjKKTl9bnmKVJCRm4XTsIxQIUJSTQ3JWltYhaSIrpQlPXP4qizf/yuuznmFn7lZyt2/nf+NuoXmPnpx3/0O0OqWPpjEqirrNOloSMhtw44dT+eGZJ/ntnTfJzs5m4MCBvPbaa9x4443Ru1AcqWu/88UrRVHQ6XQEg0GpAKzl5GsqeiSBKkTV1PsEoKXMAHOv14vtGNsMw/NiKtqiW/Zxx5s1U/a+E5179+7dTJw4EbfbTdeuXbnnnnsq/Cr91VdfzdVXX33M+3Nzcyvc3nw8qamp6PV6gsFgVM4Xa+EEYEaGHV9J9Ddm1gYrl5dmShRo1DmDYDCIgoKiUwgFQ/U28VmeYDAY+YXKoNNF5bknJ1mwWgx4iv3syc+nUUpStc8ZVra9NRg68hfBld//BYDZkkjLk7T9Q72mGa1GDGYDfq+fQ0VOGqecuAo6mrwlbr6Y9xQANoOdf/WdqH6sQrUm/4dJr8cNEFI391qOU4n+d6FQCIfDQUmJDwCd0YA1KVn9eVPH/3i02FLR600EAiVqG/BxXhiLB31OOo2eY/vy4+qveW/eaxxy5rBr1UqmjBpJu4FncuYdd9H05O41HpeiKJiMRnx+X9QTFmff+y8atG/Ptw/ej8/r/X/27js+inr7//hrZrZks+kJBEKvIlIs2BVEsYKiotjF3r22+7X3rlfvtZerXnvvFcWODRVp0pv0DumbbTPz/WN2N6FJSHZ3tpzn43d/5kuSnUMaO++c8zmcf/75TJgwgTvvvBNXBh8Fkgjp9pwvW2maRnFxMdXV1bI4MMXJ91T8lJVlz2SMEPGU8b3iTc/na3oe4Kair2vueQwejycW6DXncZu+/ZasWLGCm266ierqanbYYQduvPFGeaLaSg0NDbEzAMvbxS+0STXRBSBtehbjzs/ur5no+C+0bgNwU4oC7cutEcvqBj91/sQfLl9f1cDcn60lQL36DkVzZNfnVQG8RdYvbzbU1ye9o+GzCY9TVWctELp00D8p97ZP6vWbw6GpRHalENyOhQeGaVJVVRUL/zSnszH8ywSKgjff2oRev2E9eihkc0H2c6gORux6PK9cMpazh/6D3MiZkXO//5anjz+GF88ew5LJk2yuMr52HnkM57z+NoXtrTMAn3/+eUaNGvW3R6UIIYQQQmS6jA8AO3bsGLuxWbJkyVbfLvq6Tp06NetxFUWhY8eOcXncVatWceONN7Jhwwa6d+/OLbfc0uxORLF10fP/ANqW59tYSeKYphkLADsMLLe5GvtFA0CF1m8Abqp927zYWVXLq6rj9rhb8+dX8zB0qyOwT/+DE369VOQttrq1w4ZBdTPPZo2HOUsmMHG2dQbrPh0Gc1j3I5N27e2jxLYBB4LBZnUmGoYV/oVCkTF5t8sa+82U8C/CW2CN/ZqGQe1aCXyiPK5cTtv/Al699HNG73UGbocVss//YTzPnDCKF848jcV/TLS5yvjp0K8/F7z3IV0jo84TJkzg4IMPZurUqTZXJoQQQghhj4wPAD0eD7169QJg0qQt/4Z73bp1LF1qnaM2cODAZj/2gAEDAJg8efJW32bKlCkbve2m1qxZww033MC6devo0qULt99+O3l5ec2uQWzdypUrYy+Xl2dmB+CK5dWsX18PQIedJQCMBoDRM1bixeXSKC22QvmV1dXoRmI70qZEtv+WlHWlrLxnQq+VqnILc2K7UdbX1Sflmj5/De+P/xcABe5CrtrzhpQOx1wO6/wb0zAJbaPTzTAMqqqqCEfDvxw3OfmZ+XPR7SnE4bS+X2tWr7a5mtRT7C3lokOu5o3LvuTEvc8iJ/KxWvDTjzx70vE8e/JoZn/zVUacT5VXWsYZL7zCnqecBljTFkcddRRjx461uTIhhBBCiOTL+AAQ4IADDgBg/PjxrF27drPXv/fee5imSUlJCf3792/24w4ePBhFUVixYgW//PLLZq//+eefWbFiBYqixGpoav369dx4442sXbuWDh06cPvtt1NQkJk3ZHZY3eTGL1MDwM0XgGS3cNg6+yZe479NVbSzgvmwbrCmpjbujx+1av46Vs1bB8AO/Q9O6QAqkTSHSk6+da7dhvrkBIAf//Qwtb71AFy5+3WUelL7fBmn5oiFpMHA1s841Q2DyqqqWEDuzHGTk5eZXdEQGSGPjAH7KisJBxM/tp+Oir2lXHDwP3njH19y0j7nxILAxRN/59ULzuXRIw5h4ltvENqOEfNUpDmdjLjldkbeeQ+qw4HP52PMmDE8+eSTsjBBCCGEEFklKwLAQw89lHbt2uH3+7njjjv46y9raUIgEOCdd97h00+tca9TTz0Vh2PjvSjnnHMORx11FA899NBmj9utWzcGDx4MwKOPPsqECRMwTRPTNJkwYQKPPfYYYAWQnTt33uh9q6qquPHGG1m1ahXt2rXjzjvvbPb5g6J5mnYAZuoIcHT81+lx0LZXyTbeOrOZJuhx3gDcVElRDm631XG1PHK2ZCJM+dzq/lMUld59hybsOunAWxTp4mrwx7Y7J8qfC79j2oKvATiwy6Ec0CX1R68VRcEZ2YIX3ErIpRsGVZVV6JFw3OnJwZ3B4V9UXkF0+69JzWoZA/47Rd4Szh92JW9c9hVnDLmYwlzruci6hQv48Mbr+PfQ/fjuycfwJfDnXjIMGn0iY557kZyCAkzT5Oabb+b//u//ttk9K4QQQgiRKTJ+CzCA0+nkxhtv5IYbbmDRokVcdtll5Obm4vf7YyMuI0aMYNiwYdv92BdddBErV65k7ty53H333bHFHcHIxtk+ffpw4YUXbvZ+n3/+eWxDbXV1NVdcccVWr9GnTx+uv/767a4t20XPACws9JCT47S5msSYOtUKANv3a4PqyIo8f6v0cDh2DloiOgAVRaF92zwWLa2mytdAfSCI1x3f5Rx6WGfauLkAdO6+O7l52R3qeos8rF9SBcCGeh/lhYnp5K31reejH/4NQElOKZfvfk1CrpMILk0jFNYJh3V0XUeLBIIAuq5TVVWFHjlP0unx4PZ67So1qZzuPJyuPELBOmpWr6Kkmef7ZrOi3GLOGHIxJ+5zFl9M/ZC3JrzA8g1LqFu3jq//8yDjn3qCXUcdzz5nnEVJ5y52l9si3ffeh/PefI9Xzj+bDUsW8+KLL7J48WKeffZZCguTu21cCCGEECLZsiYx6Ny5M48++igjR46kffv2hEIhvF4vAwcO5Prrr+e8885r0eN6PB7uvfdezjrrLHr06IGmaWiaRo8ePTj77LO5++67ycnJ2ez9mp6tE91Wu7X/1dXVtfjvnc2iAWB5u8zsdgmFdGb8uQKQ8V+AsN50A7D2N2/ZctFtwADLK+O/DGTeL0vwVfkB2KHf9v9CItPk5LlQndY/U4k6B9A0TT4Y/yC+QA0AV+91MwXu9AkCXE261gPBxjFgXdepbBL+uXKzJ/yL8hZYY8D+mmqCSVwkk+5ynB5GDjqRly76lNuPf5i+HayzkUMNDfz6yks8dPBQXrv4AhZP/D0tR2jb9OjBeW+9R5fdBgHw3XffccQRR7B48WKbKxNCCCGESCzFTMdnb2K7rVu3Li6PU1xcjKZp1s1lZWVcHjNRjjzySCZMmMB++/fkfy+NsbucuJs5YwVHj3gSgOMePYS+h/eIvU5BQVFVTMPAbNZ+0PRXV1eHz9eAqkBpAhfpTJu5hvWVflyaxn69eqCqLT+jT1VUrBPLTAzT4PXrxzLnx0W4c/IZc/GraI74dhimoxVz11K7th6nprF/755xPxNx0pyxvPv9fQAM73E0/7fXTZu9jRL9/0xS8LvJpLLeh26YuFwuiooKCes6VZVVsV80uby5uDy5NteZJIoS/VQRCvpY/tfPALTp3pPSrl3trCyt/blkEm9NeIEfZ3+90b8pHQcMZJ8zz6HvoYehOZo/VKIoCi6nk2AoZFuIGA4G+OD6a5n60QcAlJWV8dprr7HLLrvYUk8qSqfnfNlM0zSKi4uprKxE13W7yxF/Q76n4qesLLXPaRYiVWVNB6DIPo0dgJm6AGRZ7OUOA2UDcHTBgZag7r+o9uVWuBjUddbWxq87t67Sx7xflgDQe6ehEv5F5EW2L4d0ndoGf1wfu6puNZ/8bJ3VWu5tz0W7bf0ohtSlxLoAQ6EgoVCYqsrKJuGfN3vCv004nR7cOVY3Z82aVTZXk976d96VO0Y/wiuXjOWY3U+OLQxZNm0qb11xKf8ZNoSf/vcs/toamyttPofLzah//ZsDL7O+79etW8fRRx/N119/bXNlQgghhBCJIQGgyEimacYCwLZtM3MEOBoA5rXNpaB9do32bUk4gQtAmior8eCKjKWurI7fGPC0cfMwIuOaO/Q/JG6Pm+5yiz2xTbdr43gcgmEavPvdfQRC1mjxtXvfiteZuM7RRHJFzv0zTaiqrsIwrI4qd54Xl8djZ2m2i24DDtTV4ZfjNFqtQ0lnLjv8Rt6+/BvOO+hKyvKt4yeqV6zg83vv4oHB+zL2njupWr5sG4+UGhRFYejF/2DUv/4d2xB86qmn8uabb9pdmhBCCCFE3EkAKDJSdXU1fr/VLZTpG4A7DGgb97HIdGPoRiz0SMQCkKYURaFtmRW4rq+vJxhu/biNaZpM+Ww2AKVtu9OmvGerHzNTOBwannzrHNV4dlz+/Oc7LFwxCYBRO5zELuWD4vbYyebUNKI/AsxY+JeHMye7wz+IBoDWB6dm1cq/f2PRbPmeQk7e9xxe/8c4rj/6Xnq26wNAoL6On59/jv8MO4A3L7uEZVOn2FtoM+088hhO++9zuHJzCYfDXHLJJTzyyCNpecahEEIIIcTWSAAoMtLKlY03euXlmTcCXFvjZ+EC61xHGf9t7P6DxAeAAOVtrADQNGFNTW2rH2/FnLWs+WsDAH2k+28zeSVWkFUfCOAPhVr9eCvXz2fcb88A0LWwO+ftfEmrH9NOumlsdDahFf5tvnwqG2kOFx6vtU27ZvUqCXTizKm5OGTAUTxz7rv857Tn2bvXAQAYus70sZ/y9PHH8OxJxzNz3BcYKX42Wc/9BnPWy6/jLSkF4I477uCGG27YaGmbEEIIIUQ6kwBQZKTo+C9kZgfgn38uj93IdthZNgBHA0AF0JIQABbku/DkWOeurapp/ZlXkz+bBYCqOujVd2irHy/TeEsaz7Bb18ouwFA4wFvf3IluhHCoDm7Y507cjvQNy3RDp9rXENtOonly0Nxue4tKMd6C9gCEAwF8lRtsriYzKYrCLt325J6TnuDFiz7hyN1G43JYX4eL/5jI65dcwMOHHsQfb7+JHocQP1E69B/AuW++Q0nnLgA888wznHfeeQSbbNgWQgghhEhXEgCKjNQ0AMzEJSCxBSAKVPSTALBxAYiatHHodm2tLsAqXwMNwfA23nrrQoEw076cB0CXnnviyS2MS32ZxO1x4vQ4gdafAzjut2dYU7kIgHMGXkyvkh1aW55touGf0ST8U50uTOlY2khuXhsU1Qrsq1fKGHCidSnrzlXDb+Wty7/hrAMupdhrddRtWLKYD264locOPZCJb72RskFgaZeunPvG21T06w/Ahx9+yGmnnYbP57O5MiGEEEKI1pEAUGSk6AiwqiqUlmbegoxpkQCwTc9i3PmyLbZpAJgsbcsau9LW1rZ8DHj2j3/hrwsAMv77d6LbgCvrfegtDLjmLfudn6e/A8Au5YMYveOpcasv2TYN/9zeXBwuV+x1opGqqHgjyypq165F11se2IvmK8ot5vTBF/LGZV9x9ZF30LHE6qqrWraMD264lvuH7s/vb76ekkFgXlkbznrpNbrvvS8A33zzDSeccAK1rfhZL4QQQghhNwkARUaKdgCWtcnD4dBsria+TNNsXAAi5/9hmqBHzpZK9AbgpnI9Try5VlfRmlbcFEbHf3O9xXTunr6LKBItLzIGbJomG+rqt/v9ff5q3v3uXuuxXPlct/dtqEp6/hO4pfDP6XbH/j6miZx1t4m8yBiwaejUrl5jczXZxe1wc8Quo3jhoo+5/uh7Y0Fg5bKlfHjjdTw64lBmjvsi5b5m3Xl5nPrf5+hz0MEATJgwgWOPPZYNG2SMXAghhBDpKT3vfoTYhmgA2DYDF4CsWF7NunXWGGSHgTL+Gw6HYgsQHGpyw942pVYoVeVrINCCbcDVa+pY8PsSAHrvdBBqkutPJ54CN6rD+idre8eATdPkg/EPUutbD8BVe1xPW2+7uNeYDFsL/wDUJuPvsrhgYzmeIhxOq4u0etUKm6vJTg7VwSEDjrKCwGPupVNpVwDW//UXr19yAc+eNJolkyfZW+QmnG43Jz7yOAOOHAnAlClTGDly5EbHjAghhBBCpAsJAEVGij45L8/ABSBTpyyNvSwdgJtsAE5iByBAWSuXU0z5fDbRphcZ//17iqLgLbICnHV1dbAd3UKT5n7OjEXjATik23CGdknPj7VuGFsN/wAUBdRIBigB4OaiXYANVVUEGxpsriZ7RYPAFy/6hH8eeTuleW0AWDJpIs+cMIrXL72QDUuW2FxlI83pZNS//s3uJ54MwOzZsznyyCNZkkI1CiGEEEI0hwSAIiNFzwAsz8AOwGlTlwPg9Dho27vE5mrsFw5Fzv9TlI06oJIhP89Fjtvq2tvecwBN02Ty2NkAtG3fh+KyznGvL9PklVgBYCisU93MAGd9zXI++fkRANp5K7hs96sTVl8iWeGfb6vhX1T0e8AwTVJroNJ+3oLGrs+aVbIMxG4OzcGIXY/jlUvGcuaQS8iJdGjO/OJzHh1+CN8+9gihQMDmKi2qqnLkbXey79nnArBo0SJGjBjBvHnzbK5MCCGEEKL5JAAUGUfXddassc54yswOQOv8v/b92sRGIrNZKNIB6NDsGZ+NdgFuqPehG82PXJb8uYoNy6oB6DPg4ITUlmm8xblWmxuwphkdl2E9xFtf30kw1ICqqFy/z+14nXmJLjPumhv+ARudayhdgBtzOj24PUUAVK9aJQFpivC4chkz5CJeu/QLjtrtBFRFJRwI8M0j/+Gx4Ycyb/z3dpcIWF3Ih159HQddfiVg/aJx5MiRzJ492+bKhBBCCCGaR9IDkXHWrl0bu/HNtDMAQyGdGdOt86vk/L/IApBYAGjPj7PSyHZawzSp8vma/X5TPrNuGjWHi547HpCI0jKO5lDxFuUAsKamdptjwF/9/hzL1lpLVk7Z6UwGtN0l4TXG22bhX+7Wwz+w8tFoH6wh24A3Ex0DDjX4aKiqsrcYsZGSvDKuHH4LT53zFn07DARgw5LFvHTOGbxx2cXUrV9nc4VWCHjARZdyxA03A9bzjWOOOUZCQCGEEEKkBQkARcZpejh327aZ1QE4b+5q/P4QAB0GyPl/ejjcZAGIPT/OigrdqJGD19Y3czttsCHEjG8XANC997643d6E1Zdp8iKLV/yhELX+rY8Hzl36Kz9MewOAfm0GMqb/eUmpL550w6C6YZPwL2fr4V9UbAx4OzpSs4U3vy2KYnULV6+UZSCpqHf7vjx21qv835F3UBDp2Jwx9jMePeJQ/vz0k5TYFrz3mDMZccvtAKxbt45jjjmGWbNm2VyVEEIIIcTfkwBQZJymAWB5u8zqAIyO/wJ02Fk6AENNF4DYtEFXVRWKCq1QZl0zA8CZ3y0g2GAFubL8Y/vkleTGWtzWbOXcxZr6dbzz7T0A5LsKuGnfu3CojmSVGBex8C8yxdvc8A+IBdIgY8CbUlUH3nxr6UTNmtXoengb7yHsoCoqw3cZxcsXf8ZhA48GwFe5gbeuuJTXL7mQ2rVr7S0Q2POU0zjy1juAxhBw5syZNlclhBBCCLF1EgCKjBNdAALQNsPOAIwuAMlrk0tB+/Q7yyzeohuAVUXZKPRIttLIdlpfMEhDMLTNt588dg4AeQVt6dBl50SWlnEcTg1PQZMx4E0Yhs7b395Nvb8KgKv3uolyb/tklthqVvjX0KLwD6zvh8YxYAkAN5VX2AEAU9epafILI5F6CnOLuHbk3dx70pOU5Vtd77O+/ILHhh/K7G++srk62OPkUznq9rsAWL9+PcceeywzZsywuSohhBBCiC2TAFBknGgHoNvtoLDQY3M18TV1ylLAOv9PSfLG21QUDlthm13n/0WVFOfEXt7WGPCGFTUsnmKNHu7QbxiKIj+Gt1d+ZAzYFwxSv8mW0O+nvMbCFZMAOLr3aPbvdGDS62uNxvDPGnPc3vAvqnEMWALATeV4inC6rK+h6hUyBpwO9uo1hOcv/JAjdj4WAF9VJa9ecC6f3nGr7ZuCdz/x5M1CwOnTp9takxBCCCHElsidp8g40Q7AtuX5GRWS1dX6WTDfOgS9w0A5/w+zsQPQrvHfqFyPkxy3VUPlNhaBTBnbeFh8n/6y/bcl8iKbl2HjLsBFq6bxzR/PA9CjqBcX7np5sktrlXiFf9AYAJqAYUoIuKloF6C/tgb/VkbJRWrJzyng6qPu5O4THo+dDTjh5Rd5+rijWTN/vq217X7iyYy8424ANmzYwLHHHsuff/5pa01CCCGEEJuSAFBknGgHYHmGbQCeNm157PBzOf8Pwno4tgTW7g5AgKJCqwuw0ueDrZxRb+gGUyLjvxWd+lNQlF6jqanC6XaQk28FY9FzAH3+Gt76+k4M0yBHy+Hm/e7BrbUsPLNDPMM/2OQcQF0CwE3lFbSLdd9WrVhuczVie+yzw1CeO/99dum6JwCr58zmqVFHMe2Tj2yta9AJJ3H0XfeiKAqVlZUcf/zxsh1YCCGEECnF/rtmIeIsGgBm2vl/sQUgClT0kwAwvNECEPt/lBUVWGFNMKxTHwxu8W0WTFxGzZo6APoMODRptWWi6DbgOn8AX8DPu9/dS3X9GgAu2/0auhR2s7O87WJsEv65cj2tCv+itOgYsHQAbkbTXHjyygCoWb0KQ9dtrkhsjzYF5Txw6rOcM/QyVEUj1NDA21dexth77kQP27fYZbfjT2DkXfcC1jjwqFGjWLBggW31CCGEEEI0Zf9dsxBxlrEdgFOtALBNj2Lc+S6bq7FfOBRdAAJaKgSAhY3nAG5tDHjSx9aGSJfbS48d9k9KXZkqeg4gwJd/vMLsJT8DMKzr4RzW/Ui7ytpuhmFQtUn458rJ2cZ7NU/0CATTlBBwS/IjY8BGOEztmjU2VyO2l6ZqnLr/+Tw05gWKvaUA/Pz8c7x41unUb1hvW127HTeaEbfcDsCaNWs49thjWbx4sW31CCGEEEJE2X/XLEQc+f1+KisrAWibQQGgaZpMi3QAdthZzv+D1Dn/L8qT48AdPQewfvMAsG6Djzk/WTeBvXc6EIczfcZTU5Erx4nb66Kyag6/TX8VgK6F3blyj+vT5uzPRIZ/sMkYsCwD2YwntwSH01oUJWPA6WtA593477nv0LfDQAD+mvALTx5zFCtm2reNd89TTuOwa28AYMWKFYwaNYoVsnBGCCGEEDaTAFBklKZPsNu1z5wAcOWKatautUZHOwyU8V9MCEUDwBQ4/y+qqGDr5wBO/WJO7Cy2HQccluzSMpLDG2TGnOcAkxyHh9v2v59cZ+423y8VbBb+eeIb/gEoyDbgbckrrACgoboKf50sA0lXbQrKeWjMixy522gAqleu4LmTRzPn229sq2nfs87hoCuuAmDx4sUce+yxrF692rZ6hBBCCCFS585ZiDiIbgAGaNcucwLA2Pl/yAZgAF3XYwtRUqUDEKC4cMvnAJqmyaRPZgHQpl0vysp72FJfJjEMnd9/fYxgqAaAy3a7Lm3O/TPMLYR/nviGf1FqkzHg6PeMaJRfWBFbBlK5bNk23lqkMpfDxVXDb+WfI25DUx0EfT5evfBcfn31ZdtqOuDCSxhy4cUALFiwgOOOO4716+0bTxZCCCFEdpMAUGSUph2A7dsX2lhJfEUDQKfHQdveJTZXY79Q0wUgKdQBWFjQONZb0+CPvbx46krWL60GYMeB0v0XD7/98CKrlk8H4LCux7BX+wPY6vrlFGKYBlW+puFfTsLCP2gMAEG6ALdE01zk5lld1TWrVtm6QELEx4hdj+e+k5/C687DNAw+ue1mxt5zp22LXg66/Cr2OeNsAGbPns1xxx1HVVWVLbUIIYQQIrulzp2zEHEQDQAVRaFN28zZAhwNANv3a4PqkG/bcDgEpM4CkKhcjxNH5PNT1dAQ+/NJn1rdfw6nm147HmBHaRll0fwJTJ7wFgC9S/syZqeL0A0TPcUDLsM0qN4s/PMk9JqKYn2fAOiGbLrdkoLijgCYhk71SjmnLRMM6r4Pj575Km0L2gHWcpC3rriUcDCQ9FoUReGw625gj5NPBWD69OmccMIJ1NXVJb0WIYQQQmS31LlzFiIOli+3DnJv0yYPpzN1RkNbIxTSmTHduimV8/8soVBqLQBpqjCyobkmEgA21AaY+e0CAHrsMBiX22tbbZmgpmoVX3/yAAD57gKuH3I3Tof1MQ+EUrd7yzBNqn0N6JHwz5mE8C9KjYy4yhjwlrlzCnG5rV8YVS5blgZ9pKI5urftxZNnv0nv9jsBMOPzsbx6wbkEt7KlPZEURWH4zbex66jjAZg0aRKnnnoqDU1+USSEEEIIkWgSAIqMEj0DsDyDzv+bN3c1fr/V8Sbn/wFmYwdgKo3/RhXkW2PAdf4AYd3gzy/nEQ5anVd9Bx5uZ2lpLxTy8/n7txMMWJ0zV+9/O+0KKtAiXZeBcJhUHAM2TZNqn2+j8M+dpPAPZAy4OfKLrC7AUIOPejmjLWOU5rfhoTEvsFu3vQGY/+MPvHDmaTRUVye9FlVVGXnnPfQ7YgQAP/30E+eeey6hUCjptQghhBAiO6Xe3bMQrRAdAW5fkXnn/4EEgADhcJhoE5NDS70OwGgAaGJ1Af7xyUwAiks7U95hRxsrS2+mafLd2IdYv2YhACcPPJvdO+4DgMNlfR3ohklYT62AyzRNqpqGfznJDf9AxoCbw1vQDlV1AlC1bKnN1Yh4ynV5ueekJxnc52AAlk6exHOnnkDt2rVJr0XVNEbd/yC9hwwF4IsvvuCyyy6TYF4IIYQQSSEBoMgo0QAwkzYAT5lsBYB5bXMpaC/jo00XgDhTcAS4IM8Ve3nhjBWsnm91E+044FCUJp1YYvtM+/095s/6DoA9O+7HqTufG3udw6VB5EMbSKElDpuHf27cuckN/6JkDPjvqYpKXmF7AOrWryfYkPwxUZE4LoeLm497kMN3PgaA1XPm8OzJo6lZtSrptThcLk545HG6DNodgLfffpvrrrtOvi+FEEIIkXASAIqM4ff7WbduHQDt2mVSB6DVjdJhYLkESDRdAKKgqqn38XA4VLy5VifR9LHzAFBVB737DbOzrLS2bNFkfvnuOQA6FHTm6sG3xwItsM7XSrUxYCv8a9gk/Mu1rR4ZA962gqKOWEmySeVS6QLMNA7VwdVH3snovcYAsGHxIp477SRbQkCXx8OpTz9LxU79APjf//7HPffck/Q6hBBCCJFdJAAUGWNVkyfx7SoyowOwpqaBhQusUFMWgFiiC0CcKTj+G1WQ70IP6Cz92ere7NZ7Hzy5mRNKJ1NN9Sq+/OgeTNPA48jl5gPvx+vK2+ztnG4HAIZhEgrbO+baGP5ZQZvd4R9sPAYsAeCWOZwecvPaAFC1cgW6nM2WcRRF4cKDr+aUfa0OYjtDwJz8Ak5/7gXKuvcA4D//+Q9PPPFE0usQQgghRPaQAFBkjOj4L2ROB+CfU5fHXpbz/6zxRT0y4pmKC0Ci8vPcrPtjDbrfCqJ2HHCYzRWlp1DIzxfv3YG/oQaAf+5/C12Kum/xbTWXRrTJzW/jGLBpmlQ3pFb4FxXtmjRMU8YNt6KguDMApq5TtWL5Nt5apCNFUTjnwMtTIgT0lpRyxvMvUVhRAcAtt9zCyy+/nPQ6hBBCCJEdUvcOWojttFEA2D4zOgBjC0AUqOjfxt5iUkA4HIoNdzpS8Py/qHyvi1U/WuFBXkE5HbvubG9Bacg0Tb7//GHWrVkAwEkDzmLfLkO3+vYKjctAguGwLQFXNPyLLiJxulMn/AMZA26OHE8h7hzrF0iVS5diyscpI0VDwJP3PQdoDAFr16xJei2F7Ss484VX8JaWAnDVVVfx4YcfJr0OIYQQQmQ+CQBFxogGgIqi0LZtvs3VxEc0AGzbuwR3k+US2SocarIAJIU7AOuX1VK70Opa69nvYBQldWtNVdMmfsC8md8CsHvHfTltl/O2+T6OyBiwaSZ/GcgWwz9v6oR/IGPAzVVQYnUBhoMBalavtrkakSiKonDugVdsFAK+cNbp+Kqqkl5LaddujPnfS+Tk52OaJhdeeCFff/110usQQgghRGaTu1KRMaIBYFmZF5fLYXM1rWeaJlOnWgGgjP9aQpEzuTRVTemFKJPfmQuAomp02/FAm6tJP8sWTeKXb58BoENBJ67Zf+OlH1ujOVQUzfq6CISSFwBuHv65Ui78i5Ix4G3LzWuDw2lta96wdHEKrJQRiRINAaOLQdbMncPL555JoL4+6bW037Evp/73fzg9HkKhEGeeeSYTJkxIeh1CCCGEyFwSAIqMsXLlSgDK22fG+X/LllWxYb11EyILQCyhSFeXU03dH12B+hB/fmKNrXbotgfOnMz4ekyWqg3L+OKDu5ss/fgXee7md/Q6I2PAIV1PSpfbpuGfw+3C7fUm/LotJWPA26agxM4CDNTV4duw3uaKRCJFF4McscsoAJZNncJrF51PKBBIei1ddhvESY89ieZ00tDQwCmnnMKff/6Z9DqEEEIIkZlS9y5aiO20fLl15lq7dply/t/S2MsddpYOQMMw0XVrqYYjhTcAT/90IUGfFVR23+kQDNNEN6SHqDkC/lo+e/cWgoE6FBSuGXLHVpd+bE10DBgSvwzENE1qNgn/cnJTN/yDjceAdcPebcmpLK+wParqBGD94sU2VyMSTVEUrhp+Kwf0PRSAhb/8xFuXXxpbOpVMvfYfwnEPPoSiqtTU1DB69GgWLFiQ9DqEEEIIkXkkABQZIzoC3D5DOgCnRc7/c3mdtOlZbHM19guHQ7GXU3UDsGma/PHWbAAKSzrQpkM/AMLSabVNuh7miw/uonqDFeSfNegS9uq0/3Y/jqoqqE7r6yMQCkGCBjij4V8oGv65IuFf6k6mx0THgE0TGQPeClXRyC/uCICvcgMN1dU2VyQSTVM1bjjmPvbosR8As7/+ko9vudGW75F+hx3ByDvvAWDdunWMGjWKZcuWJb0OIYQQQmSW1LyLFmI7BYNB1q5dC2RSB6D1ZL99vzaoKRp4JVN0AYgCOFJ0BHj5tLWsnlMJQN/dDkeJtFqFpdNqm376+imWL54CwLAewzlup1Nb/FjRMWDdMGPdefG0xfDPmx7hH8gYcHMVFHVCiWwbX7foL5urEcng1FzcPvph+nXaFYA/3n6T75541JZadjtuNIdfdyNgTTiMGjWKNTZsKRZCCCFE5kjNu2ghtlP0/D+Adu3TPwAMBsPMmG79nWQBiCUU6QDUtNRdAPLHW3MA0BwudhgwLBZU6gkIoTLJ9EkfM2PyJwD0bTuQf+xzXas+xw6XIxbG+UOhv3/j7WSFf/60Df9AxoCbS9Oc5BdaXYD169fhr62xuSKRDDlOD3ef+BidSrsB8M3D/2HSe+/YUss+Z57NARdfCsDChQsZPXo0VTZsKRZCCCFEZpAAUGSE6PgvQLsMGAGeM3s1waDV8dZxZ1kAAo0bgJ1qap7/11AdYOYXiwDo0Xd/cjz5aI5oB6AEgFuzbNEkfvzqSQDaettz89D7cGmuVj2mooAj0gUYCIfjNsJnmiY1fj+h6FmULmfahX9RMgbcPIUlnVGUaBfgInuLEUlT4Cni/pOfpthbCsCHN17HvB++t6WWA/9xBXudfgYAM2bM4KSTTqKurs6WWoQQQgiR3iQAFBlh4w7A9A8Ao+O/IB2AAHpYx4gs0kjV8/+mfjifcMAKhnba9QigsVbdMDAkZNnMpht/bxv2IEWekrg8tjOyDMQ0rRCwtUwTqv1+QuGm4V9eWoZ/sPEYsHQBbp2mucgvrACgbu0aAvUSvGSL9sUdufekp8hxejDCYd74x8WsmDkj6XUoisLh19/ELsceB8DEiRMZM2YMfr8/6bUIIYQQIr2l5p20ENupaQdgedt8GyuJj+gG4IJ2XvLLU3uraDKEmiwAcabgBmDTNPnjbWv8t7S8G2077ACApjUNWaQLsKktbfztVtwzbo+vOVTUyMff38plIKZpUt3QEAv/NJcTdxqHfxAdA7b+AnIO4N8rKOmMEumYXC9dgFllh4qduPW4f6MqGsH6el4+90yqlid/GYeqqoy88x76HnoYAOPHj+f8888nbMOWYiGEEEKkLwkARUZYvtzaHFpa6sUV6fxJZ9ENwNL9Z4mO/6qKgpaCC0AW/baKDYus88F22nV47Pw6rUm3oowBN9L1MOM+uLvVG3+3xRH5WRDWjZYvAzHNjTr/NKfV+Zeix1Bul2gAaJpgmPL1uTUORw7egvYA1KxeTaC+3uaKRDLt1WsIVw6/BYC6tWt55YJzCNgwgqs5HBz/4EP03H8wAJ999hmXXXaZBPhCCCGEaLbUu5MWogWiAWD7DkX2FhIHVVU+/vprPQAd5Pw/AEKRDcCp2P0Hjcs/nC4PPfsNif25piqxMFA6ABv9/M3TLFs8GWj9xt+/43RrrVsGEj3zr2n4l5cZ4R+AqjbZBiyLav5WUUnXSBegybqFC+wuRyTZiF2P49T9zgdg9Zw5vPN/V9gSvDlcbk567Cm67DYIgLfeeotrr71WzvEUQgghRLNIACgywtKl1shsh4r0P/9v8qSlsZc77trOxkpSg2masTEnZwqe/1e3zsecbxYD0KvfUFzu3I1e74guApGABbA2/k6f9DEQn42/f0dRFBzOFi4DiYR/wQwN/8DKRjUZA24WhzOHvMhZgLVr18hG4Cx01tBLGbzjIQDM/vorvnrwX7bU4fJ4OPW/z1GxUz8Ann/+ee666y5bahFCCCFEekm9u2khWiCTOgCnRAJA1alS0a+NzdXYL9Skc8uRgh2Ak9+bhxG2gqW+ux2+2eujY8AyApyYjb/b4sxpyTKQTcM/B54MC/+iol2AJhICbktRSbfYRuC10gWYdVRF5bqRd9O7fV8AfnjmKSa/964tteTkF3D6cy9Q1r0HAA8//DCPPPKILbUIIYQQIn1IACjSXl1dHZWVlQB0yIAAcPKkJQC071sWO8Msm0XHfxXAkWLn/xlhg0mR8d/yjn0oK+++2ds4tOg5aya6kb1jWptu/L31oAfitvH372z/MhCTWn9go/AvJy+fjEz/sM4BjP7NJAD8e5rDRUFxRwDq16/HV1Vpc0Ui2TyuXO484TFK86xfzn140/Us/mOiLbV4S0o584VXKOpofU3ecccdPP/887bUIoQQQoj0kFp300K0QLT7D6B9mo8Ah8M6UyMLQGT81xLtAHRoWsJGRVtqzrdLqFntA6DfoCO3+DayCGTLG3+7l/RK2vWbvwzECv8CkdA5Gv6l2Jdd3KlyTmWzFRR3QVWtr6e1Cxa0Yre0SFdtC9px5wmP4nK40UNBXr/4AiqXJX8zMEBBu3ac+cIr5Le1zgu+5pprePvtt22pRQghhBCpTwJAkfai5/9B+ncAzpm9moYGK/DqJAEgmBCOBICpeP7f76/NAsDjLaL7jvtu8W0cTerWDT0pdaWSzTb+7nZxQjb+/h2n2xFbBtKw1WUgJnVNwj/V4ci4M/+2RlWbfo1KCPh3NM1JQUlnABqqq6hfv87mioQdduwwgGtH3g1A/Yb1vHbx+QQbGmyppaRzF8Y8/zKeoiJM0+TSSy/lo48+sqUWIYQQQqS21LujFmI7ZVIH4KQ/lsRelgAQwuEwRmRxg0NNrfP/Vs+tZPHE1QD03fVwNM25xbdTFNAiI6jZ2AG42cbffqclvQZFiYSAWOcAGpstAzGp9wfxx8I/DU9+Xsp1nCaKqjROOBt69oXU26ugqDNq5OzKNfPnyQbWLHXgTodz+v4XArBq1kw+vPE6274Wynv15vRnX8DtzUPXdc4//3zGjh1rSy1CCCGESF0SAIq0F+0A9HicFBfnbuOtU1v0/L/CDvnkl3ttrsZ+TReAOFNsAcjE163uP1XV6Lvr5ss/moqOAetZtgk4mRt/t8Xpjnz9mOAPBpu8xqQ+EIx1BqqahicvP2vCv6jYNmDTlEBrG1RVo6jMOu8zWF9P1Yrl23gPkanOOOBi9u51AADTPv6QX174n221dBwwkNOefR5Xbi7hcJizzz6bcePG2VaPEEIIIVKPBIAi7cU2AFcUpv1N++Q/rDCz4y7lNleSGoKRUEZT1di20lTQUB3gz08XAtCtz75480v/9u2jY8Bh0yBbshU7Nv7+HVVT0ZzW58EfDhH9RPgCQRqCodjbePLzUVLoay1ZVKXx6YAsA9m2/MIKnC7rlzTrFi5Eb/aGaZFJVEXl+mPupWNJFwC+uP8eFv7ys231dNltEKc98z+cHg+hUIgzzzyTr7/+2rZ6hBBCCJFaJAAUaS/aAVhRUWRvIa20enUNy5dXATL+GxVK0fP/pn4wn1CDdcPfb/ctL/9oKjoCjAm6mfnhSuX6pRtt/L1t2INJ2fi7LdExYMOAgB7GFwzi2yj8K8jK8A+sEeDoXz0bz6rcXgoKxW2sRTZ6KMj6xYvsLUjYJj+ngDtPeBSPKxdD13nz8kupWm7PUhCArrvvyalPPYvD7SYYDDJmzBi+++472+oRQgghROpIrbtqIVog2gFYkeYLQKZMalxmIhuAQQ/rsU6kVBr/NXSDiW/MBqCsXQ/addxxm+/TdBNwpo8B+xtqGfvurRtt/O1W3NPusgBwuLRYwFcfCOILWKPAiqqSk6Wdf01FuwBNExkDboZcbyk5uVawXbl0CSGblkAI+3Vt05PrRt4DgK9yA69fciEhv9+2errvvQ+nPPUMDpeLQCDAaaedxo8//mhbPUIIIYRIDRIAirQWDodZuXIlABUZsgDE6XFQvoP93VJ2C6bo+X8LflpO5bJaAPoNGtGssXNNU2JbaMMZ3AGo62HGfXgX1ZVWKH/2oEuTvvF3W5w50S5AK+BSVGvst+km3GylNvla1mUZSLOUtOkFKJiGwZoF8+0uR9ho8I4Hc+p+5wOwYsZ0Prr5BluD9J777s9Jjz+N5nTh9/s55ZRT+Pln+8aThRBCCGE/ueMRaW3VqlWxG9V07wCcHOkArBjQFs2ZOoGXXaLjv5qioKVQOPP7a9byjxxPAT13GtKs91EALdJdpmfo+WqmafLjV0+yfPEUAA7peSSjdjrF3qK2oGlcq6iKFf6l2Ii5XRSlyTKQDP06jTeXO4+8wgoAatespn7DBpsrEnY684BL2LOn9UuPKR+8x6+vvGRrPb2HHMCJjz6O5nTi8/k46aSTpBNQCCGEyGJy1yPSWvT8P0jvDsBAIMSM6SsAWQASFQpZ45lOR+qEoesXVbPgJ+vz1GeXQ3A43c1+30zfBDx90sfMnPIpADu1Hcgle1+Tckt5wkGdgC/SWaoqOHJzUVIoXE4F0WU7JhICNldxWXdU1QnA6rlzMOXjlrU0VePGY+6norgTAJ/fexdLp0y2taY+Bw5j9EOPbRQCfvPNN7bWJIQQQgh7yJ2PSGvR8/8AKjoW2VdIK03/cwWhkNXJKAtArHP2okFZKo3/Rs/+UxSVnXYdvl3vG10EEjYNMu10taV//cFPXz8FQHlee2468H5bN/5uSTik46+3QmVUcObmgqplbEdmS6mKEuuSlDHg5tE0F0VtegAQ9NWzYekSmysSdsr3FHL78Q/jcrjRQyHevOwS2ztD+x58CCc99mRsHPi0005j3LhxttYkhBBCiOSTAFCktWgHoKoqlJcX2FxNy02a2HjD2HFn6QBMxfP//LVBprw/D4Auvfckv6jtdr2/IzpmambWGHDl+qWM+7DJxt+D/k1RTrHdZW1EDxv464JWW5sC7vx8VId1FqBumsi+i41Fx9UN05RlIM2UX1iBK8f6N2jdor9sXQAh7NezXR+uOOImAKpXruCd/7sCw+ZAfYehB3HKU/+NbQc+44wz+OSTT2ytSQghhBDJJQGgSGvRDsC25fk40/jcvN9/XwRAm57F5JZ47C0mBUTHf9UUOv9v8ntzCfrCAAzY4+jtfv9oByBkTgDob6jhs3duJhioR0Hh2iF30rW4h91lbUTXDfy1gSbhXx6qw4GagZ+PeIluAwYZA24uBYXStjsACqaus2b+XLtLEjY7fOdjOWKXUQDM/2E83z/5uM0VQa/9h3DaM8/j9HgIhUKcc845vP/++3aXJYQQQogkSY07ayFaKNoBWFFRZG8hraDrBn/8bnUAdt6jvc3VpIZg0OoATJXuPyNs8Pur1vKPsnY9aN95p+1+jKZBZiYETroe4osP7qSmytrCfc7u/2DPTvvZXNXGDN3EXxuwOvwUcOV5UZ3OyGsVIo1ukU43u6pMPYpC7GOjGzIG3FzunIImC0HWUL9hvc0VCbtddtgN9GzXB4BvH32I+T+Ot7ki6L7X3ox57kXc3jx0XeeCCy7g9ddft7ssIYQQQiSBBIAirS1btgyAig7puwBkzpzV1NZa42Jddq+wuRr7Wef/WaFDqgSAs75aTPXKegAG7HlMi5ZbKEqTcwAzIAD88asnWbFkGgCH9DqSY/uebHNFGzMMk4ZaP2bkQ+305qK5Nj6XUImMZZuAYab/5ySeol2Apikfm+1RXNYDVbNC5lVz5kgHZZZzO3O47biH8LrzMU2Tt6+8nOqVK+wuiy6DdmfMCy+Rk5+PYRj84x//4IknnrC7LCGEEEIkmASAIm2ZphkLANuncQfgxF8XxV7uPEg6AIPBYOxlV4psAP715RkA5OaX0qNvy7vcomerpXsH4IzJnzJzymcA9C/fhUv3ujalNv6aRqTzLxb+eXC4N9/YrCgKSqzTTboAm9LUxmUgRoZurk4ETXNSXGaNwYcafKz/6y+bKxJ261DSmWtH3gWAr6qSNy+7hHCTf+fs0mngLpz50mt4S0oBuOWWW7j99tvl3E8hhBAig0kAKNJWZWUlPp8PgA4diuwtphV+/20RAMWdCihon2dvMSkgGDn/T0uR8/+WTVnD8mnrAOg3aASa5tzGe2ydFuk4S+cAcMXS6fz4ldUp0tbbnhuG3ouzFR+TeDNNaKgLYOjWTawzNwdHTs5W316VLsCtUpXMCKyTLb+wAzmeIgA2LFmEv67W3oKE7fbvM4wT9z4LgKVTJjPuX/faXJGlYqd+nPP6WxR16ADAo48+yuWXX044HLa5MiGEEEIkgv1310K0UPT8P4CKNA0ATdNk4u+LATn/LyoUPf8vRbr/Jrw8EwCH003fXQ9v1WNFR4BN0+o4Szd1NWsZ98GdGIaOW3Nzy4H/SqmNvybgrwtghK2PrcPjxuH5+6U60gW4dRudW2nzBtN0U1q+I4qiYpomq2bNkq4qwTkHXc6AzrsB8MuLz/PnZ6mxgbesW3fOff0d2vbqDcBrr73G2WefjV82WQshhBAZRwJAkbYWLVoUe7lT59QJIbbHXwvXsX69dbacnP8HeliPdRulwvl/Vctrmf2VFdD2HnAQOZ78Vj1etAMQ0q+rKhwK8Pn7t9PgqwLgyv1upkdpb3uL2kSgLogesj6umtuFM7d5G7WbdgGm2+clkWQZSMs5XbkUlnYDwF9bQ+XSJTZXJOzmUB3cMurfFHutkdsPbriWtQsX2FyVpaBdO85+9U0672oFlJ999hknnHAC1dXVNlcmhBBCiHiSAFCkrSVLGm+oOnYssq+QVvj9t8Wxl+X8v03O/9McNlZi+f212ZiRTr0Be4xs9eM1DQDTaRGIaZp8/8XDrF01D4DR/U5nSLeDba5qYwFfiHDQCqlUlwNXXi7QvHMJN+oClI3AG5FlIC1XWNwFl9v6pcHahQsJNjTYXJGwW2l+G24e9SCqohKsr+eNSy8iGDnKxG65RUWMef5leg0+AICff/6ZAw44YKNpCyGEEEKkNwkARdpavNgKz9qW5+N2p84ZZNsjev5fXttcirsU2FtMCgiGrPFfTVVRVXuXSgTqgkx6dy4AXXrtQVFpx1Y/pqoQ+3ulU6fZtInvM3fGNwAM6rA3Y3a90OaKNhZsCBHyW2dWqQ4Nd14ezQ3/otQ07s5MpKbLQGQMePsoikJp+Y6AgmnorJo9C8mWxS5d9+DsoZcBsGbeXD665caUGRF3eTyc8uR/GXjU0QD8+eef7Lnnnvzxxx/2FiaEEEKIuJAAUKStaADYqVOJzZW03MRIANhl94qU2qJqCxNCkQ5AVwqM/055fx7BeiuQHLDH0XF73Og5gOkSMi1bNIlfvn0WgIr8Tlwz+A401f7PT1QoECbYYIV/iqbiKsiDFnwvKYrSGM5KF+BGoh8XwzBTJqhIF+6cfAqKOwHgq9xA9YrlNlckUsFJ+57N3r0OAGDqh+/zx1tv2FtQE5rTybH3P8iQCy8GYOXKlQwdOpTPP//c5sqEEEII0VoSAIq0FQ0AO3YqsreQFlq+rIoVK6zzdTrvLuO/oXAYIxIu2L0ARA8Z/PqKtfyjtLwbFV0HxO2xo2PA6TACXFO1knEf3oNpGngcudxy0L/Id6dOp2o4pBPwWSGtoiq4C/JQlJb/s6ZqjcFhWM68i9GafEyNNPi6TTVFZT1wunIBWDNvHiFZrpD1VEXluqPvprzQOvv30ztuZcXMGTZX1UhVVYZd8U+Ou//fqA4HPp+P008/nf/+9792lyaEEEKIVpAAUKQlXddZtmwZAJ06p2cH4MTfF8Ve7iIbgGPdfwr2dwDOHLeI6hXWcpaBex4b1+7Mxk3AZizwTEWhYANj37uNgL8WgKsH30aXou42V9VIDxv464LW5g4FXPl5KK3uTGzsAjRMUvrzk0wbLQORMeDtpipqbBTY0MOsnDVTRoEFBZ4ibjv+IZyak3AwyBuXXkRDTY3dZW1k9+NP4OwXXyEnvwDTNLnhhhu4+uqrCUWO6xBCCCFEepEAUKSllStXxp6AduqUnhuAowtAPEVu2vRMzxAzngKRANChabaOQ5umyS/P/wlAXkEbeuw0OK6P70iDs+ZM0+S7sQ+xYe0iAE7d+Vz27jzE3qKaMHQTf10gFv658/NQHfFZGqNqjWfehfXU/PzYQVNlU3Jr5HiKNhoFror8Aktktz4V/bj4kGsBqFy6hPev/b+UG7Pvte/+XPTuhxR16ADA888/z/HHH8+6detsrkwIIYQQ20sCQJGWouO/AB3TNAD8dcJCwNr+q9i88MJupmESjgS6dnf/LfhpOavnVAIwYK9j0OK8jVjbaMw0NYOUP//4kPmzvwdg706DOXng2TZX1Mg0TRpqA0QX0rryvKjOeC4BUmKjwBJ2NVKVxmDUkC7AFiku64HT5QVgzYJ5shVYADBy0Ikc1G84ALO+GsfP/3vW5oo2V96rN+e//T6ddx0EwE8//cQhhxzCn3/+aXNlQgghhNgeEgCKtNQ0AEzHEeAVy6tYvGgDAF337mBzNfYLBoOxkTiXzef//fy/6QC4c/LYcedD4v74qqLEOhxTMVxauWwGv3z7DAAdCjrxz/1vRW3FuXrxZAINtUFMI3JWpNeD5nLF/TqKqsb2iIQNWQgSFe0CNEwTw0y9r91UpygqZe0iW4F1nZWzZsgosEBRFK4acStdyqwjFsY9cB+LJ/5uc1Wbyytrw5kvvcqgE04CYOnSpYwYMYIPPvjA3sKEEEII0WypcVcnxHaKBoAul4O2bfNsrmb7/fLzwtjL3SQAJBgZ/1UVBYeNHYDL/1zL4t9XAdBv0AicLk9CrqM5UjMA9NVtYNyHd2EYOm7NzY1D78PrSp3vr0BdECNsfcwcHjeOnJyEXUtrMqotC0EsqtrYBajLeHSLuHMKKSzpDEBDVRWVS5fYXJFIBbkuL7cd/xA5Tg+GrvPm5ZdStz71RmwdLhcj77ibI2+7M7Yc5Nxzz+X2228nHA7bXZ4QQgghtkECQJGWliyxbpo6dCxCVdPvy/iXnxYA4C3z0KZX+nUwxls0AHTaPP778/NW95/mcNFv96MSdh1HZOQ7lUaADUPny4/uwVdndaZets8NdCvuaXNVjQINIcJBK4jTXE6cuYkJZ2OUjReCpFpYawcFK6QHaxtwqp1Vli6KSrvHRoHXLlhAwOezuSKRCrq26clVI24FoHbNat6+8vKUHbff46RTOPPFV/CWlALw6KOPcuyxx7Jq1SqbKxNCCCHE30m/5EQIGjsAO3VOv/P/TNNkwi9/AVb3n50LL1JBOByOhSt2jv+uX1TN7K+sr6s+Aw/G4y1M2LWi3WWGYWKmyBDghO//x4ql1nlOR/Y5ngN7HGZzRY1CgTChBqu7RHVouPK8QOK/b1RNiY0C64Yho8A0jgGDbARuKWsUeCdAwTR0Vs2aIWGqAODg/kdy1G4nALDwl5/49rFHbK5o67ruvicXvPchHQcMBOCXX37hwAMP5IcffrC5MiGEEEJsjQSAIi1FA8COHdMvAFywYC1r1tQC0G3vjjZXY79o9x+AK84LN7bHhBdngGndnA/c65iEXqvpIpBU6CxbMOdHpv72LgB92vTjvN0vt7egJsIhnYDPWhCjqAqu/DxIWmiuoGqN229lFNj60GspfIZlunDn5FNY2hWAhupqNiyRUWBhufjQa+ndvi8A3z/xKPPGf29zRVtXVNGBs197i71OPwOAtWvXctxxx/Hggw9iyM8HIYQQIuVIACjSjs/nY82aNUB6LgD55acm5//tI+f/BQNWAOjQ1NjIZbLVrfMx9aP5APTYcT8Kitsn9HobnS9n81lqleuX8u1n/wagMKeYGw64B6cWz626LafrBv66oJW+KeAqyEdJ8si/stkosHRqqdIFGBdFJV1xufMBWPfXAvx1dTZXJFKB2+HmtuMeIi+nANM0eeefV1C9coXdZW2Vw+Vi+I23cMIjj+P25mEYBvfeey8nnngi69al3jmGQgghRDaTAFCknaVLl8Ze7tipyL5CWii6AKS4UwFFHQtsrsZepmESClndXXZ2//36yiz0oBXE7bzPcQm/nqoqsQlWO7uoQkE/X7x/B6GgD1VRuW7InbTxlttWT1OGYeKvDTSGf/l5qDadEalqTbcCyyiwqlj/AwkAW8MaBe6LoqiYhmFtBZauKQG0L+7IdSPvBsBXVcmbl11CuEm3fCrqd9gRXPj+R7TrsyMA3377LUOGDOHbb7+1uTIhhBBCREkAKNJOdPwX0q8DUNcNfpsQOf9Puv8IBIOxE/DcNp3/568J8MebswHo2G0Xytr1SPg1FayOR7A3APzxqyeoXG+NHo7Z5UJ2br+7bbU0ZZrgrwtgRj40Tm8umtPerkS1SddmSNdT5ORG+0TPAjQBXUajW8zlzqOotBsAgdpa1i1eZG9BImXsu8OBnLTP2QAsnTKZcf+61+aKtq20azfOe+s9djveOsdwzZo1jB49mptuugm/329zdUIIIYSQAFCknUWLFsVe7pRmZwDOmL6CmhrrSXC3feT8v2AgAFibRR02dXf99tpsAnVWF+Iu+x6ftOtqNm8CnjfzO2b/OQ6APTruy/H9T7Olji0J1AcxwlbE5vC4cbjdNldkjQJHz240scL8bKYqinQBxklBSRfcOdbSoQ2L/qKhpsbmikSqOPvAyxjYeRAAv7z4PNPHfmpzRdvmzMnh6LvuZfRDj5JTYE05PPXUUxx22GHMnj3b5uqEEEKI7CYBoEg7SyKHpRcVecgvyLG5mu3z4/j5sZe77pXlHYBm4wIQt8Oe8d9AfYjfXpkJQLuOfanoMiBp146eA6ibyQ+SaqpWMf4La7tkiaeMK/e7GVVJjX8Ogg0hwkErUNJcTpy5HpsraqSoamPoZZpZfx6gFvmaMU1ZCNIaCkpkFFjDNE1WzpohCxQEAA7Vwc2jHqTYWwrAB9dfy7q/Fm7jvVJD/yNGcMnHY+m6x54AzJgxg4MPPphnn31Wtl4LIYQQNkmNOz4htkO0A7Bjmo3/Aoz/fh4AFf3b4C1NnWDDDsFQCCNyE+Cyafx34huzaai2uhB32/9ElKRtl22yCdhMbhegrof58qN7CQZ9KChcPfg2inJSo5M2HNQJNoQBUB0arjwvscMSU4Tq2Pg8QCOLQ0BVbdoFGLa3mDTndOVS3MY6fiBYX8+6hQtsrkikitL8Ntx87AOoikqgvo43/nERwYYGu8tqlsL2FZz54qscfNXVqA4Hfr+f6667jtGjR7N8+XK7yxNCCCGyjn2n7ouk0hIwXpmIx2yOhQut335361aa1MCmtaqrG5gy2Vpg0nNIF5QkBRvJus72io7/KoDThq+loC/EhJdmANCmojcdu++a1Os33QSsGyaOJP065vcfX2LNSmsM64QBY1Lm3D9dN/DXWx2hiqrgyvdCSn5/K2gOlXDICm3DhoFT0VKz1CTQFBXDNGJdgE2/rm2XZp+TgqJO+OrW4vdVsmHJEvLK2pBbXGR3WQmiNP5Xyd4Qvbl26b4nZw29lGe/eZjVc+bw6e23cOy9/0pqDS19vqU5HAy54CJ67rsfb115GesX/cV3333H/vvvz913383JJ5+cVs/lUlH0+bhdz8tFy8jnSwhhBwkAs0RxcXw7fDRNi/tjNkc4HOavv6wlGj16luN0upJeQ0tN+HlWrFuo55AuKGrib5STcY2WMQlExn9dDoct46eT352Hb4N1HuNu+yW3+w8iHYAKYEaXKCT+x/GyRZOYPOFtAHZs059Tdz6fVEhJTNPEXxdssvHXi6Km8hNjKwTUwwYm1lIQp6Zl5U2sqioo0QBQD6Np7hT4iop+VadCJdtBgTbt+rJs0a+YRpiVs2bSY6+9bdt+nQyqopB2nyebnLrf+UxfOoUJ875n0rtv02PPvdh99IlJubaigKuVi5i67bobV3w2jrH338NPL/yP2tpaLr30UsaOHct///tfOnTI8mNR4qAgcuaiSH123UcJIYQEgFmisrIyLo9TUFCApmnouk6NDQeVL1y4kHDYGjXr1LmIUCiY9Bpa6ttvZgGQU+imQ/82mAke+1RUNeHXaKlQOBRbHOByaJhJ3qkaDoT5+fk/ASgt70aXXnsk9fpg3fJqqoKum4QNExL8MfDVV/H1J/cDJl5nHtcMvgOHqiX8us3hrwtg6lYdzlwPqsPejb/NEV0KouvmJiGg3ZUln6aohGMhoG5zF6ASzdVJha/t7aU5cyhp04v1q2cRavCxau4c2vXpY3dZCaCgKkrkGIj0+zzZQoHrjr6H8/47itXVK3n/putp03sHKnbql7BLOh1OFMU65zMUDsXhAZ0cfsPN7DDsYN679v+oWraMzz77jL59+3LPPfdw4onJ/2VcJtA0jYKCAmpqamQpU4qz+z4qk0iAKkTLSACYJRLxhMCOJxnz5s2Lvdy1a2naHCRtmiY/RM7/675vRxSHktDQq+nYb7LDteYI+BvHf102LACZ8v586tZaZyjtakP3X5Smqei6HukATBzTNPj2swfx1Vu/CLhs3+tpl1+R0Gs2V8AXQo+M02o5Lhw56bPYR1FVVAyMaAho6DjV7AsBNVVBN2nsAlRt7Mxu+rFPvR99zZJfWIGvbi0N9euoWr6M/DZt8JaU2l1WfCmRdl/MtP082aHQU8Stx/2HS58/lXAgwKsXnceF732UlK+PeD7f6rbHXlzy8eeM+9e9/PbaK9TU1HDxxRfz4Ycf8uCDD9KuXbu4XSub6LouAWAakc+VEMIOqTofKMQWLVjQeDB6167pc0M0e9Yq1qypBaDnkM42V2O/QOT8P6emRUbAkkcP6fz8P6v7r7isM9377JPU6zelRTYo6IaR0HvgaRM/YMnC3wE4rNdIBncdlsCrNV8oECbkjyz9cDpweXNtrmj7qaqKGvk8miaEDZ00+b1EXDmabgSWm5pWKyvvg6panbArZ81CD8uSFWHZscMALj/iJgCqV6zgzcsuQQ/FoTsvydxeL0feegdnvPAKhRXWL6TGjRvH/vvvz2uvvZY2v+AVQggh0okEgCKtRAPAsrI88gvSp1Poh/GNnYs99u9kYyX2C4d1wrHx3+R3/037eAHVK+sB2HW/E1BsOH8wKjoqaZokbJvs2lXzmPDd/wDoXNiNC/a8KiHX2V562CDgs25aY0s/0vQsMFVrDAGNLA0BN94ILAFga2kON6XlOwAQDvhZM3eOzRWJVDJi1+M5arcTAPjr1wl8ft/dNlfUcj322ZdLPvmcQSecBEBVVRWXXXYZxx13HIsWLbK3OCGEECLDSAAo0kp0A3DXbunT/Qcw/jsrAGy3Yxn5bb02V2OvQJPtv+4kB4B6yOCnZ6zuv4LiCnr03T+p19+UpjUGXnoCzmsMBnx8+dE9GEYYp+ri2iF3kuOwPzg3DBN/XaDJ0o88W4PYeJAQELTI0iETYiG/aDlvfjm5+W0BqF61ktq1a22uSKSSSw+7jn6drO31E156gcnvvWtzRS2Xk5fPyDvuZszzL1HUsSMA48ePZ/DgwTzxxBOxs5+FEEII0Trpfcclsk60AzCdAsDKSh8Tf18MQI8h2d39BxDwW5t3HZoWC0ySZdpH86lcZo1i77rfaFSbN802XZYQTkAA+MNXT1BduQKAc3e/jO4lveJ+je1lEln6EfnruvK8qDZ0gibCpiFgKMtCQFVRYiP9uq7LCF8clLbdAU2zzlRcNWcW4TRafCUSy6m5uO34/1AWCYk/uvl6lk2banNVrdNz3/259JMv2OfMs1FUlYaGBm655RYOO+ww/vzzT7vLE0IIIdKeBIAibTQ0NLB8+XIgvQLA776ZExvv7HNwN5ursZfeZPw32d1/4aDO+Kesm6PCkg707n9gUq+/JapCLDCKdwfg3BlfM3f6VwDs3WkwR/Y5Lq6P31KBuiBG2Pp+cHhy0Fw2LoxIgKYhoGla24GzKQdzqI1PK2QUuPU0zUVpux0B0INBVs+eLTszRExpXhtuP/5hnJqTcDDI65dcSN269O4UdeXmcvh1N3Lem+9SvoM1Bj916lQOPvhg7rzzThoaGmyuUAghhEhfEgCKtLFo0aJYR0nXbmU2V9N8X305C4D8ci8V/dvaXI29/JHxX0h+ADj5nbnUrLLO/hs0+GTbu/+iomPA8QwAqytXMP6LxwAoy23LFfveaNum46aC/hDhoBUKaS4nzlz7x5ETYaMQkOwKARUFNKXxa9ow49/Zmm1yvWXkFbQHoHbtGmpWr7K5IpFK+nYcyJXDbwGgZtVK3vjHxYSD6d8p2nHgzlz43sccdMVVaE4Xuq7z8MMPc8ABB/DTTz/ZXZ4QQgiRliQAFGmj6QbgbmnSAej3h/hx/HwAeh/UBSXJI6+pZqPtv0n8WIQawvz4zDQAStp0oedOg5N27W2JjgHHKwDU9RBffnQPoVADqqJy9eDbKcgpistjt0Y4pBP0Wec4KZqKKy99l340RzaHgJqqxj6zeli6AOOhpG1vtMj5navnzCHc5JcpQhy+87EcvfvJACye+Dtj777D5oriQ3M6OeDCS7j4o8/oMmh3wDoL+uijj+aqq66ipqbG5gqFEEKI9CIBoEgb0QBQURQ6dymxuZrm+fnHBTQ0WJtOdxiW3eO/4XA4dpB3srv/Jr45m7p11tjQ7kNOTamFE9EOQMM0MeKQEP06/gXWrrKWzpw04CwGtNu11Y/ZWoZu4K+LdKSoCu6CPKtVLMOpmoqqZV8IqCiNC0EM00Q3JARsLVV1UBYZBTbCIVbOniWjwGIjlxxyDQM7DwLgt9deYcLLL9pcUfy06dGDs155gyNvuxO3Nw+Al156iX322YfPPvvM5uqEEEKI9JE6d8FCbEM0AKyoKMTtdtpcTfNEx3/deS667dXB5mrs5fc32f7rTF4AGKgP8dNz1uHhZe160HWHvZN27ebQmp6Z1souwCULJzL1N2sT5E5tB3LywLNa9XjxYJqmFf5FNv6687woKTJ+nQyqmp0hoKYqRJt89bAuYVUceHJLyC+yNqTWr19H9YrlNlckUolDc3Lr8f+hXZH1XOOzu25n7nff2lxV/Kiqyh4nncKlY8fR56BhAKxevZoxY8Zw9tlns2bNGpsrFEIIIVKfBIAibSxcuBBInwUgum7wzddzAOg5pDOaK3tCj82Yjdt/XQ4ttik0GX57dSYNVVb4uPsBp6XEWXhNObTGelqzCdhXt4FvPn0AgDxXPtcMvgNNtX+7rr8uiKFb8Y8z14PqTI/wPp6yNwS0nmKYgB7p/hWtU9ymJw5nLgBr5s0jJAsRRBPF3lLuOfEJvO48TMPgrSv+wao5s+0uK64K27Xn5Cf+ywkPP4a31Ho++NFHH7Hvvvvy5ptvyvZxIYQQ4m9IACjSRmMAmB4LQCZPWsqG9dbSiR0O7mpvMTYLhUKx7ja3I3kBUEN1gF9emA5Aecc+dO4xKGnXbi5VVWLTsC3tADRNg28+fYAGXxUAl+97I23z2sWpwpYL+ELoIevvpLldOHIyc+lHc6iqGhv3zpYQUFUUWQgSZ6qiRUaBFQw9zMpZM6W7UmykW9te3DLq36iKRqC+jlfOP5vatem9GXhTiqLQ7/Dh/GPsV+xyzCgAqqqquOSSSxg9ejRLliyxuUIhhBAiNUkAKNJCdXU1ayNPYNOlA3Dsp1bwpDlVeg7pbHM19vJHuv8UxeoATJYJL80gUGudwbjHkNNTrvsvqrWLQKb89i5LF00CYPgOx7Jfl6Fxq62lQkGdkN/q+lIdGq68XJsrsp+yaQhoZH4I2HQhSFi6AOMix1NEQbH1b4qvqpLKpUttrkikmj167sc/DrsegOoVK3jtovMIRf4dziS5RUUce98DnP7cCxR1sEafv/vuO/bff3+eeeYZjDgt1xJCCCEyhQSAIi003QCcDgFgOKzHAsCeQzqTk++2uSL7mGbj9l+3w5G0EK5+fQO/vTITgIouA+jQbWBSrtsS0VBIN7Y/DVq9Yg6/jX8BgC5F3Tlv98vjWFnL6GGDQL219ENRFVz5eWTyxt/toahNtgObEDYy+3y8pgtBTBPCuiwEiYfisu44XV4A1i6YT8Dns7kikWqO3v0kRu1xKgDLpk7hvWv+mbGBWK/9h3DJJ1+w1+lnoCgKPp+P66+/nhEjRjB37ly7yxNCCCFShgSAIi3MmTMn9nLPnm1trKR5fvt1EevW1QGw04ieNldjr2AgENtum8zx3/FPTSXoszqO9jjgtKRdtyUcTToAt6cjLBio56uP78UwdFyam+uG3IXbYe+YrWGY+OsCsaUfrvw8FFX+qWlK1RpDQCMLQrGNFoLoupzRFQeKolLWbidAwTR0Vs6cIR9XsZmLDrmGvXoOBmD62E/5+qEHba4ocdxeL8NvvIVzXn+bsu49APj9998ZOnQo//73vwmFQjZXKIQQQthP7spEWoj+Bjc310X7igKbq9m2Tz+2ts46PQ56H9jV3mJsFh3/VRUlaeO/6xfXMOkdKzTuusPetOvUNynXbSlNbeyO05t5Tpppmowf9xg1VSsBOH+PK+ha3CMh9TWXCfjrAkT/Ci6vF9Vh/yKSVGSFgNbLVgiYmZ05UQ5Vi/WAhsJyIx4P7px8ikq7AeCvqWb94kX2FiRSjqZq3DzqQbq37Q3A+Kee4LfXXrG5qsTqvOtuXPThpwy56BJUh4NgMMg999zDwQcfzNSpU+0uTwghhLCVBIAiLcyebW2x696zDWqKdxMFg2HGfW6NnvY+qCuu3Ozbehpl6AbBoDUKmuNMXhD07SOTMMImiqKy59AxSbtuS0XPAITmB0Fzpn/FvJnfArBflwM5ovcxCaltewTqgxhhqwvJ4XGjuV02V5TaVE1rXABjmi0aAU8Xm44C6xne9ZgshSVdcbnzAVi/6C/8dbU2VyRSTa7by70nPUlZfjkAn9x2MzO++NzmqhLL6XYz7PKruODdD6no1x+AGTNmcMghh3DbbbfRINuzhRBCZKnUTlKEiIh2APbqlfrjvz/9sIDqauvJZb/h2T3+6/f7Y+eb5TiTE4Qun7aWWeMWAdBn50MoLuuUlOu2hqopsSPymtMBWLVhGT98+TgAbbzlXLbP9bYvOAn6w4QDVqijuhw4cz221pMuNIcaCwHDhkEGZ4AbjQKHdV22AseBoiiUtd8JRVExDYOVM2diZug5b6Ll2ha25/5T/kteTgGmafLOVZfx128T7C4r4drv2Jfz3nqPQ6++FofbjWEYPPbYYwwdOpSJEyfaXZ4QQgiRdBIAipRXX1/PkiVLAOjZs43N1WzbJx9PA8Cd76LH4Oze/tsQGf91alqs+yeRTNPkq39bT+odTjeDBp+S8GvGg0LjGPC2NgHr4SBffnQP4ZAfVVG5ZvAd5LvtHYsPhwyCDdZYp6KpuPO8yNKP5lJQN+oAzezNwE1HgWUrcHy4XF6KSrsDEKirZd2iv2yuSKSi7m17cfcJj+HUXISDQV678DxWzZltd1kJpzkc7HfO+Vzyyed03WNPwFosN3z4cG6//fbYkjIhhBAiG0gAKFLe/PnzYy/3TPEOwLpaP1+NmwVAn0O64XAn58y7VBQKhmJjfska/503fhlL/lgNwIA9j8GbX5KU68ZDdAxY38YI8ITvn2fdamsr9ik7n0u/8p0TXdrfMnSTQH3j0g93fh4o8k/L9lAUJbYJ2sTqBMxUm20FlhAwLgpKOuP2FAKwYfEiGmpqbK5IpKIBXQZx86gHUBUVf20tL519BlXLl9ldVlKUdunKmS+9xohbbsfp8WAYBo8++ijDhg2TswGFEEJkDblLEykvev4fQI9eqd0B+Okn02mIdEINPGYHm6uxV4PfGoNWFXAnYRGEoRt889AfAOTkFrDz3qMSfs14igZAYdNgaw1gixf8yrSJ7wPQv3xXTux/RnKK2wrT3GTpR74XRcve0Ls1FLXpZuDMPg9QUxU0pbHjdVtdr2LbFBTK2u2EomiYpsnKmTMw5OMqtmD/PsO4/IibAKhds5oXzjqdunVrba4qOVRVZc9TTuPijz6jy26DAOs55qGHHsp9990XO7NYCCGEyFQSAIqUN2eOtc01J8dJx45F9hazDe+8ZQVQxZ0L6LJnhc3V2McwzNhYjdvhTMr5dFPen8/a+VUA7Lb/SbjcuQm/Zjw5omOg5pbHgOtr1/PNp/8GIN9dwNWDb0NT7Q3b/HUBDN0Kqpy5HjSnLP1oDVVTNjoPMJNHgTVVjY0C6+EwZib/ZZPE6fRQ3MY6dzboq2fdwvnbeA+RrY7a7QTGDL4IgPV//cXzZ5yGr7LS5qqSp7RLV8565Q0Ou/YGHC4Xuq7zwAMPcOihhzJz5ky7yxNCCCESRgJAkfKiC0B6pPgG4HlzVzN1ijVKs/NxfWxfymAnv98fCy+SMf7rrw3y7aOTACgsqaDvrocn/JrxFu0ABDbr/jIMna8//Rf+hmoArtz3Jtp4y5Na36YCDSH0kBVUam4XDk+OrfVkBmXjjdBG5m7KVZTG0NtERoHjpaCoIzm5xQBsWLIUX1WVvQWJlHXGkIs5bs/TAVgzdw4vnnV6Vo2Oq5rGvmedw0UffkbHAQMBmD59OsOGDeM///mP/EwSQgiRkVI3TREiItoB2CPFF4C8/ZYVQCmqwsBjs3z8t8Ea/3VqKo4kjIT++Mw0fBushSN7DzsHTUvOxuF4arokRd8k+Jny69ssXzwFgKP6HM/enYcks7TNhII6oQbr5kh1aLjy0qvbMqUpirUVGjC20g2aKVRFwRH5ujdMU26446SsvC+K6gBMVs6aiaFnbpAsWk5RFC4+5BqO3G00ACtmTOflc88kUF9vc2XJ1aZHD8554x2GXfl/aE4noVCIu+++m+HDh7NgwQK7yxNCCCHiSgJAkdLq6upYtGgRADvsYG/H098JBsN8+P4UAHoO6UxBuzx7C7JRMBhssvwj8UHchiU1/PqyNbLTodvOdOm1R8KvmQiK0uQcwCahz6rls/jth5cA6Fbck3MG/cOW+qL0sEGg3jonSVEVXPmy8TfeVFVtMgpsksHHAaKpCqqcBxhXDmcOJW16ARBq8LFm/jybKxKpSlEUrjjiZg4dMBKApZMn8eoF5xCM/BIvW2gOB0MuuIgL3vuI9n13AmDSpEkceOCBvPTSS3JEgRBCiIwhAaBIaU3PYtlhx3Y2VvL3vv5yNpUbfADscnwfm6uxV7T7T1WUpCz/+OrfEzHCBoqisu/B56b16HVsE3AkBAn46/jq43sxTQO35ua6IXfhcrhtq88wTPx1jRt/Xfl5KDafQ5ipNMfWO0IzjaPJeYBhOQ8wLvILK/B4ywCoWr6M+g3rba5IpCpVUfm/o+5gaN/DAPjr1wm8fvH5hPx+mytLvnY79OH8t9/ngIsvRVFVfD4fV111Faeeeipr12bHohQhhBCZTQJAkdKaBoB9UjgAfPnFCQB4yzz0GtrF5mrsY+gGwYDVHZbjdCQ8jFv020rmfL0EgB13PYyStl0Ter1Ei56JFjYMDNNk/BePUlu9GoAL9ryKzkXdbKvNZOONv05vLmoSAt7stekocOaGYtZ5gI1BcigcsrGazFFW3gdVtbqwV86ahS4j1mIrHKqDG465j317DwVg/o8/8Mp5ZxP0+WyuLPk0p5ODLruSc15/m+JOnQEYN24cQ4YMYdy4cTZXJ4QQQrSOBIAipc2YMQOAklIvbdqk5ljt9D+XM/H3xQAMOqUfmjN7O6J8DQ1EY4pEj/8ausG4+38DwOX2svvgUxN6vWSILQIxYebUz5k/+3sABncdxmG9RtpYGQTqghhh67Pr8LhxuO3rRMwWTUeB9QzfCqwqxM4DNE0JAeNBc7gpKbfOow0H/KyZN9fmikQqc2hObjnuP+zd6wAAFk74mefGnIK/ttbewmzSeZddufjDT9ntOOuMxLVr13LKKafwz3/+k/osOydRCCFE5pAAUKS0aAC4Q5/ylB3tfPH5XwDQnCqDTu5rczX2MU3wR8Z/3Q5to6UWiTD53XmsnlMJwG6DT8LjLUzo9ZIh2gFYs2EZP3/9FABtve35x97X2fr1H/SHCQetMVTV5cCZ67GtlmyjNt2Um+Hn42mqghb5OjcMM3aWqGi5vPxycvPbAlC9cgW162SMUWydy+Hi9tEPMbjPwQAsmvgbz5x6Er7qKnsLs4k7L4+j776Pkx5/mtwia7v2iy++yIEHHsikSZNsrk4IIYTYfhIAipRlGEZsBLhPn9Qc/127tpbPPpkOQP+RvfGWZu82VH9DA0akRcnjdCX0Wr5KP98+Yj35LizpQL9BIxJ6vWRRNQVdD/Lrl/9BDwdQFY1rh9xBnjvftprCIZ2gz+rGUjQVd14esvQjeRRFQVWjo8Bm7HssUzk0FTW6AEXXMTI89EyG0rY7oGrWz+TVs2cRDkl3pdg6p+bi5uMe5KB+wwFYOnUyz5xyAr7KSpsrs0/fgw/hkk8+p9f+QwBYuHAhRxxxBA888IBsLxdCCJFWJAAUKWvx4sWxMYtUXQDy2iu/EQpZXSp7jOlvczU2Mq3xX7Bu4J2OxI5Bf/PwHzRUBwDY79AL0LTEbxtOBgWY/svLVK+3RspP3+U8+rYdYFs9hm7gr7POdERVcBfkQYp24may6FmAkPldgAAOVZOlIHGkaS7Kyq3lVOFgkNVzZttckUh1DtXB9Uffy+E7HwPAihnTee60k6hZtcrmyuyT37Ytpz37PCNuuR2H242u69x3330ceeSR/PXXX3aXJ4QQQjSLBIAiZaX6ApCGhiCvv/o7AF32rKDdjmU2V2SfQCAQG9fzJPjsv2VT1zD53XkAdN9xXzr12DWh10umhbN/Yt60sQAMaLcbx/c73bZaTNOkoS4Y2/jrzvPKxl/bKLHzIc0MXwgC0aUgjaPPch5g6+XmtSGvwPp3tHbNamrWrLa5IpHqNFXjmqPu4qjdTgBgzdw5/PeEUayZP9/myuyjKAp7nnIaF33wKRU79QNg4sSJHHDAAbz66qvyywohhBApTwJAkbKi5/85HCo9e7SxuZrNvf7q72xYb3Uo7nXWQJursVe0+09TFNyOxAWAhm4w9q5fAXA4c9jn4PMSdq1kq6lazXefPAxAobuYK/a5FdWmwM3a+BvE1K2bGWeuBzXBwa74e0oWLQQBUBVFloLEWUnbHdAc1vKe1XNmEwoEbK5IpDpVVblqxK2cvO+5gHWO5LMnHceSSX/YXJm92vTowblvvsvgCy5CUVV8Ph+XX345Z555Jhs2bLC7PCGEEGKrJAAUKWvatGkA9OjRBpfbYXM1G2toCPLs0z8C0K5vGb0P7GJzRfYJhcKEImdK5bicCZ0QnfT2XFbNWg/AbvufRF5BZnRd6nqYr9+/n6DfCpQv3/dmSnLLbOsmCNQH0UPWqKmW48KRk2NLHWJjTReC6FkwCixLQeJLVR2Ule8IgB4KsXLmDOlYEtukKAoXHHwVlx56HQoKDdXVPD/mFGZ9Nc7u0mzlcLk4+Mr/46yXX6eoQwcAPv30UwYPHsx3331nb3FCCCHEVkgAKFLWlClTAOg/sIO9hWzBm69PZN26OgAGXzooZTcUJ4PP5wOs8+sSOf5bv74htvijuKwTA/YcmbBrJdvv37/M6uXWuVzH9z+dXSv2AqygJ9mCDSHCgcjGX6cDlzd7F9ukGkVRYgsydNPM+C5AkKUg8ebxllJQ3BkAX+UGNixZbHNFIl2M2vM0bh71AE7NSTgQ4PVLLuT3N16zuyzbdd19Dy7+6DMGjrTOS1y9ejXHH388N954I36/3+bqhBBCiI1JAChS0qpVq1i92jqjaKd+FTZXszG/P8QzT/0AQPmOpewwrKu9BdlID+sEI2NkVvdf4oLQr/49EX+ttZBiv8MuzJjFH0sX/MGUn98BYMe2/Rmz2/mxLspkd+eEgjrBBmujoeJQcefLxt9Uozoa/9nOhoUgsPFSkJAsBWm14rIeuCKbxdctXEhDTY3NFYl0MXSnw7n/lGfwuvMwDYOPbr6BsffciZHl3bk5+QUc969/M/o/j5JTUADA008/zSGHHBI7zkYIIYRIBRIAipQ0derU2Mv9+qdWB+Abr/3O2rWR7r+Ld8vq7r96ny+6I4Jcpyth11n48wqmfbQAgJ47DaFD18w4c7G+dgNff/ggAHmufK494A4cqqNJAJi8WvSwQaDeClgVVbHCvyz+2k5dCmqkJc4wTYwsCMOspSCN52GGQiFMW/pjM4OiqJS13wlF0TBNg5Uzp2d9gCOab5eue/DIGS9Tll8OwM/PP8cr55+Dv1aC5P7DR3DJx2PpttfeAMyaNYtDDjmEJ598UrqXhRBCpAQJAEVKio7/OhwqfXYst7eYJqqqfDz+yHcAlPcppc8h3e0tyEa6rhOIjLfkOJ2xUCLeQg1hPr39ZwDcOXnsc/C5CblOshmGzjcfPoDfVw3A5fvdQHlee4BYqJyskMPQTfx1gdjGX1d+nmz8TWGq1vi9lg1nAQKoCo1LQYBwKGxvQWnO5fJS3KYnAEGfj9Xz5tpckUgnPcp34Klz3qRPRX8A5o3/jv+OHsX6xYvsLSwFFLav4IwXXuHQa65DczoJBoPcfPPNHH/88axcudLu8oQQQmQ5CQBFSop2APbq3Ra3O3VGPR9/5Duqq62Ntwdftw9KgkKvdOCrb+z+87gS9zn6/onJVC23Oi73HnYOuXnFCbtWMk3+6W2WL7K+zo/c8Tj26zo09rqmHYCJjgBN0wr/zEiO5MrzojpSa+mO2JQSCwEN01qQkQ00VcHRpPsxFJYQsDUKijriybMWKVWvWE7NmtU2VyTSSVl+Wx4e8yIH9RsOwNoF83n6+GNYOOEXmyuzn6qq7Hf2eZz/9ge06dkLgPHjxzN48GA++ugjm6sTQgiRzSQAFCnHNM1YB2Aqjf/+tXAdr778KwC9hnah+74dba7IPoZuxA63djsdaGpifpSsnLmeCS/NBKBD14HsMHBYQq6TbMsXTWPi+FcB6FHSm3N3/8dGr286Vp7IEU8TaKgNYujWNZxeD5orcaPcIn5UVYmdi5ctZwECaKraZDOwIZuBW6msfEc0hxuAVbNnEWxosLkikU7czhxuPOZ+zhl6GQANVVW8eOZp/PTcM3JWJ9C+b18ufO8j9jptDABVVVWcffbZXHrppdTW1tpcnRBCiGwkAaBIOatWrWLt2rUA9OufOgtA7r/nC8JhA0VTOPjave0ux1a+pmf/JSgwMsIGn9z6E6ZhojlcDD7ikow4b7G+dj1fvX8fpmngceRy7dA7cUVuwKMUhaQsAvHXBTDCVnjkyHHhyMlJ2LVEvDV2AZqAniVdgLD5ZuBsGYNOBE1zUdauL6BghMOsmP4npnw8xXZQFIVT9z+fO0Y/Qo7Tg6HrfH7f3bx+8QWyYAZw5uQw/KZbOf3ZF8hr0waAN954g6FDh/Lbb7/ZXJ0QQohsIwGgSDmTJk2KvZwqHYBffzmLr7+aDcCgk3eirEdmjKG2hGEYNPitLhGXI3HdfxNensmqWRsAGDT4ZApLUicMbildD/Plu/fSUF8FwBX730inwi6bvZ0CCV8EEqgPogetG33N5cTpzU3MhUTCKKoa+zrRDSOr1mI03QwcDoezYhlKonhySygs7QqAv7ZGzgMULbJ/n2E8efYbdC6zzkae9dU4njzmSFbMlC24AL0GD+GSj8fS56CDAVi8eDFHHnkk9957L6FQyObqhBBCZAsJAEXK+f333wHIyXHSZ8d2NlcDdbV+br35EwC8pR4OuGx3myuyV329LxZKJar7b93CKr5/fDIApeXdGLDnMQm5TrL9+s0LrFpmjTQfs9OJDO520FbfNpGLQAINIUIBa3RSdTpw5XuB9O+uzEaq1rgYI5u2TG66GTgcCsnIYSsUlXYjJ9f6xVbV8mXUrJbzAMX269a2F0+d8yYH7nQEAJVLl/DM6GOZ+Obr8v0JeEtKOfmJpxl55z04PR4Mw+DBBx9kxIgRLFiwwO7yhBBCZAEJAEXKiQaA/Qd0wOm0fxPpA/d/yepV1hjLYTfvh6coe8ckdV3HHzkjyu1w4NDi/yPECBt8eOOPhAM6iqJywIjL0LT0X0qxYNaPTPv1fQD6th3A2btf+rdvn6hFIKFAmFCDtTxB0VTcEv6lNUVRmnQBmgnrGE1FqgLOJpuBQ+FQ4lpmM5yCQpv2/TY6DzDg89lclUhHuS4vNx37Ly4//CYcqoNwMMiHN13Pm5ddjK+qyu7ybKcoCoNGn8jFH35KxwEDAWvy5cADD+Tll1+WoFQIIURCSQAoUkogEIhtAN551042VwMTf1/Ma69YZ7T0GtqFvkf0sLkie9U32fzrdSem++/nF6az4s91AOy63wm0ad8rIddJpqr1y/ju44cAKMwp5vqhd+FQ/z7UTMQikHBQJ1BvjRopqoK7IA8U+Wcg3TXtAsy28/DUJpuBTRNCoVBWjULHk6a5aNN+J0DB0MOsmD4NQ5asiBZQFIWjdz+Jx858lfJC6/iOGZ+P5bERh7Hgpx9tri41lHbtxjmvv80BF1+Koqr4fD6uvPJKzjjjDNavX293eUIIITKU3PmJlPLnn38SCAQA2NXmALCmpoH/u+IdAFxeJ8NvH5wRSyhaKhzWCUQ2/+YkaPPv6rmVfP/4FABKy7uz634nxP0ayRYK+vninbsJBRtQFZXrDriTMm/bbb5fvBeBhEM6/vqg9X+o4CrIR1Ht77AVracoCtFvR93Mri5A2GQzsGkSlvO0WizHU0xx5Ay3QF0dK2fNlEBVtFifDv159vz3GNZ/BAC1a1bzwpmnMfaeOwlFnutlM83p5KDLruSc196iuKP1nPezzz5j8ODBfP311zZXJ4QQIhNJAChSysSJE2Mv77JrZ9vqME2Tm2/4iOXLqwA49IZ9KWifZ1s9qaC+vr7J5l/3tt58u+khnQ9v+AEjbKCqDg4ceRWa5oz7dZLJNE3Gf/YolWsXA3D6ruezc8WgZr1vPBeB6GEDf12Q6CfQnZ+Pqkn4l0nUJuP44SzrAoSNNwPrhoEeDttbUBorLOlKbp61rbR2zWrWL/rL5opEOsvPKeDGY+7npmP/hdedD8DPzz/H08eNZMWM6TZXlxo677obF330KbscexwAa9as4cQTT+S6666jIXLsihBCCBEPEgCKlPLbb9a4bZeuJZSUem2r4923J/HZJ9YT052G92Tn4/vYVksqCIXCsc5Mj8uJqsa/E/KH/05j9ezI1t8hp1Datmvcr5Fs0359n3nTvwNgz077MXrA6dv1/tGO09bsd9XDBg21gSbhXx6qI/3PVBSbUmLfl4ZpZuVWXIemxULAsK5n3Th0PJW12wmny/ql17qFC6hdu9bmikS6O6jfcP53wfsM7GItUls9Zw5PH3c04x64n1BkuiCb5eTlc+y9/+KERx7HU1gIwLPPPstBBx3EH3/8YXN1QgghMoUEgCKlFBQUUFSUZ2v336yZK7nj1k8BKOyQz/A7snv0F6C+rg6wOtI8Cdj8u2zqGn58ZhoAbSt6s/Peo+J+jWRbuuAPJnz9PAAVBR355+BbULfzvL3Yl53ZsnMAdd3AX9cY/rnyvKjO9O6qFFunao0/p7Ix/FIAh6rFVtqEw2EMM/s+DvGgqhptOwxAjXRhr5w5g0B9nc1ViXRXXljBv0/7HxcM+ycuhxtD1/nhv0/y+MgjWDzxd7vLSwn9DjuCSz7+nO577wvAvHnzOOKII7jtttvwS1AqhBCilRRT1k1lhXXr1sXlcYqLi9E0DV3XqaysjMtjbqrG9wnVNQvIy4v/mOm2rF9Xx6iRT7FiRTWqQ2XMayPptGu7pNfRWgoKiqpiGgZmK09wCgQCVFdbW5C9Lhe5cV7+EagL8t/jPqJqeR0Oh5tR5zxMcZn9C2Bao2r9ct773xUEA/XkOnN56Mj/0bmo23Y/jmlCMGQFGA5VRduOzktDN2mo9RPNP1x5XrQELW4RqcMwDAzd+p53qmpCunVTm4JpmoR0PXZkgdPpzPpf4rRUg6+S1csmAyZOj4cug/bAEY9fIiigKqoV0Mqz0JSlNjnr14jzLxWWrl/Evz6+iWlLGrvb9jzlNIZd+U9y8gvieq10ZBgGv736MuMeuI9QZAy4V69ePPLIIwwatPFRIpqmUVxcTGVlJbos7klpybiPyhZlZWV2lyBEWpIOQJFyFEWxJfwLBsNcetEbrFhRDcBhN++XluFfXJlQV1cPgKYoeFzx7x777M4JVC23Okv2OeTctA//Av56Pn/rdoKBehQUrjngjhaFf7DJIpDtuEs2dGOj8M+ZlyvhX5ZQVaWxAy4LuwDB+jfE0WQzcigUissinWzkyS2mpG1vAEINDSyfNhXDkIBBtF6n0q48NOZFrjjiZjyuXAB+ffVlHj70IKZ88F7Wf8+qqspep43hko/H0nWPPQGrG3D48OHcdtttcjagEEKIFpEAUAisZQ233PgxE3+3ljXsdnJfBp28k81V2c/X0BD7bXKu2xX3LpppHy9g+qcLAejWZx923OWwuD5+shmGztcf3E/V+mUAnDnoIvbstF+rHlNtst20WTXo1pl/sfDP68HhTn6gLuyixEaBTUA3svMmWlVUHGqTEDAsIWBLFRR1JL+oAwAN1VWsmDFDPpYiLlRFZeSgE3nhwo/Yq+dgAOrWrePdq6/iuZNHs3LWTJsrtF9J5y6c+dJrDL/pVpweD4Zh8Nhjj3HggQdutDhPCCGEaA4JAIUAHrj/S959exIAXfao4LAbWxfaZALDMPHVW91/Tk0lJ85nx21YUsPYO38BwJtfxpDh/0j7Mb3fvnuJJfOtJ+RDux/K8f1Pa/VjRo8NNM1tT8rpWwr/cnJaXYNIL4qqxjpHdaM1K2TSm6YqjSGgGQkBba4pXZW03QGP1xq3qlu7htVz58jHUsRNeWEF95z0JHeMfoTywgoAFv8xkSePOZJP77gVX1WVvQXabEvdgPPnz2f48OHceuut+Hw+mysUQgiRLiQAFFnvuWd+4pmnfgCgbe8SRj95GJpLs7kq+/nq62NdZ944d5DpIYP3rxlP0BcGFA46+p/kePLjeo1kmzX5C6b8/A4AvUr7cPl+18cl0Gz6GH/XBajrBv6m4V9eroR/WUxtMgIb77O70okVAkY6Ik0Ih0I2V5SeFBTaVPTDnWOdzVa1fBkbFi+ytyiRURRFYf8+w3jxoo85ff8LcWouTMNgwssv8tDBB/DTc88QCgTsLtNW0W7AETffFusGfPzxx9lvv/348ssv7S5PCCFEGpAAUGS1l16YwH13fw5YG39PeX4EnkIZlwyHw7HzZdwOB04tvoHo1/+ZyIrp1mKaXfc7gYou/eP6+Mm2dMEkxn/2GAAlnjJuHnY/bkd8wreNzgHcSgC4xfBPxn6zmqIosa+bsGGSzRObmqqiNRmlD0kI2CKqotG2w0AcTuu8trUL5rNh2VKbqxKZJsfp4ayhl/L8hR+yV68hADRUV/P5fXfzyGEHMfWjD7L6lxqqqrLnqadzycef023PvQBYtGgRhxxyCBdccEHclv4JIYTITBIAiqz1v2d/4s7bPgXAW+rh1BdGkF/utbmq1FBbWxfboOmN8/KImV8s4teXrXN92nXsy6DBJ8f18ZNt3eqFjHv3bkzTIMfh4fZD/k0bb3ncHl+hsQtwSx2AetigoUbCP7E5TWv8Jz6c5YsbHJqEgPGgaS7KO+6M5rB+xqyZO4eqFcttrkpkoo4lXbj3pCd54NRn6dVuRwCqli/nnX9ewdOjRjL3+++y+izKks6dOfOl1zj67vvwFBYC8NZbb7HPPvvw+uuvZ/XHRgghxNZJACiy0tNPjufeu6zOv7w2uZz+6khKuxXZW1SK8Pv9sZvjXLcLTY3fj4l1C6v4+OYfAfB4ixh27DWoavqOW9fVrGPsG7cSCjagKhrXD72LnqU7xP066lbOAQwHdRpqA0TTWgn/xEYUBVWNhl7WuZ7ZTELA+HA6PbTruAuqZv1yaNXs2VSvWmlzVSJTDeq+D0+f+zY3HHMf5YXtAVgxYzovn3sm/z3+mKwOAhVFYbfjRnPZF1+z88hjAKisrOQf//gHxx57LAsWLLC5QiGEEKlGAkCRVUzT5N//+pIH77fOSskv9zLmtZG06Vlsc2WpwTBM6uqsxR+aquKJ4+KPoC/E21d+R9AXRlFUhh1zNXkFZXF7/GQLBnyMffNW6mvXA3Dx3v9kj077JuRa6hbOAQwFwvjrgrHwz5XvlfBPbEbVFKJfPeEsHpuL2lIImJ3RQes4Xd5ICOgETFbOmknVihV2lyUylKqoHNz/SF66+DMuGPZPCjxFACybNpWXzz2Tp487mrnffZu1QWBeaRknP/wYY/73IsUdOwHw448/MnjwYO666y7qIwvdhBBCCMXM1n8ts0y8zgQpLi5G0zR0XaeysjIuj7mp2oZPCevxP1coGAxz/dXv89GH0wAoaJ/H6a8cRUmXwrhfy24KCoqqYhoG5nbc3tbW1sXO/iv05OByOOJSj2mavH/NeGaM/QuAPQ88g132OT4uj22HcCjAp6/fwsolfwIwuv/pnLX7xQm9ZjBkYJqgKQpGUCfYELZeoSq4872ojvhuaRaZwzQMdN36OeBQlbh29aaepot3tv6zL6wb6JGnP4oCTocz7beQ2yHgr2X1sskYhtVN2bZXb0o6dd72OypWqGOYxrbXmwvbqE1+VqTSuXu+QD3v//4ab/7yPDUNVbE/b9dnR/Y96xz6HTEChyu+x5ekMkVRcDmdBEMhAj4f3z72MD//71kM3Tr6oaKigttuu42RI0fKzzmbJeM+KluUlaVvE4EQdpIAMEtkewBYU9PAJRe8zoRfrACqTa9iTn5uOIUV6b15dmtaEgCGQmGqKisxsRZ/FHjit0H2t1dn8sW9vwHQtfdeHHr8jWn7JFTXw4x75y4Wz7P+PkO7H8r/DbkVVUlsqBIOm+iGgd6gY4SsGzFFVXAV5KPGeUmLyDx6WI8tAnFpGmn67dcMzQsAQULAeAkG6li9bDK6HgSgtFt3yrp1528/khIApoVUDQCjthYEFpS3Y+8xZzDohJPIyS+wr8AkaRoARm/rVs2Zzad33Mqi336Nvd1+++3H3XffzY477mhXqVlPAsD4kQBQiJaRADBLZHMAuHDBWi6+4HUWzF8LQNe9OzD68UPJKcjcccntDgBN2FBZSTgcRgFKvN7Y2WGtNf/HZbxx8deYhklBcXtGnf0Q7py8uDx2spmmwbcf/Ye5f34DwB6d9uXmg+7HocanU/Lv6GETf10QMxwJLDQVd0EeShqfoSiSyDQJh60beFUh7pu9U0fzA0AA3TBjo9EK4HA6Eh7mZ6JQyMfqZZMJh/wAFFZ0oF3vHVC21m0qAWBaSPUAMMoXqOfTye/wzq8vsbq68TxKl9fLziOPYfcTT6Zdn8wNvbYUAII1ffHnp5/w+b13UbtmNQCapnH22Wdz9dVXU1iYeRMwqU4CwPiRAFCIlpEAMEtkawD49Zez+L+r3qWuNgDAgKN7c+TdB6C5MvXm17K9AWB9vS92Rkye243HFZ9x0rULqnj+1E8J1IVwujwcc+aDlLTpEpfHTjbTNPlp3NNM//1jAPqV78ydhz5MjiN+nZJbY+gm/pogRmSMU3U6cOd7QYIKsR0Mw4h9DTlUFS1OIX9q2b4AEDYOAQEcDg1NgvXtFg77Wb1sCqGg9W9JblExHfoPQNvSWbISAKaFdAkAo8JGmO9njuPNX55n7soZG72u0867MOjEk+l3+HBcHo9NFSbG1gLAqEB9Pd8/+Tg/P/8semT5UWlpKVdddRVjxozBlUXj0naTADB+JAAUomUkAMwS2RYAGobBow9/y+OPfAdYo5JDr9yDfc/fJStGvLYnAAyHwlRGRn+dmkZRbnyeGPsq/fzv5E+pXFaLoqgcfsItdO45KC6PnWymafLbty8x+ee3AOhR0pv7j3gSryvxnYzhoEGgLogZuffS3C4cXo90KYkWyfxR4O0PAMFaCBLWjdh7aKqKI05noGYTXQ+xdsWf+Bus5wdOTy4dBwzE7fVu/IYSAKaFdAsAo0zTZOriibz3+6v8NOcbdCMce11OQQH9jxjBgCOPovNuu2/0d0xX2woAo9b9tZDP7rydeT98H/uzbt26cdNNNzFixIiseH5sNwkA40cCQCFaRgLALJFNAWBlpY9r/vku330zF4CcQjejHjqYHvt3ileJKa/ZAaAJlZWVhCKjv8Xe3LgsCNBDOq+cO44lf1gjJ/scfC4D9jy61Y9rByv8e5HJP78NQIeCTjw4/L8UeUoSe10g5AsT9DXeuDhyc9ByrNF1azOwPFkX28c0TfSMHgVuWQAIYJoQ0vXYe6mKgsPhkJvi7WSaBuvXzKWuejkAqqZRvkMfCtu1b3wjCQDTQroGgE2tr13L2Cnv8cnkd1hVtXyj1xW0a8+AEUcyYMRI2u24Y9p+rzc3AATr34B533/HF/+6lzXz5sb+fPfdd+fWW29ljz32SHS5WU0CwPiRAFCIlpEAMEtkSwD464S/+OcV77B6VQ0A5TuWMvrxwyjunPmHQDfV3ADQV++jLjb668IThzEQ0zT5+KafmPrhfAB23OUwBh9xSVo+sTZNk1+/fYEpP78DQEVBR+4//EnKvG0TfF3w1wbRg5EbLhVceV40lxPDiC4tUFAkABQt0HQUWFMUHFr6d8A0ankACNb3XtjQiXybWecCOhwZ0SWUbDWVS9iwdj7Rz0NBu/a026GPtbRIAsC0kAkBYJRhGkxc8DOfTXmXn+d+RzAc2Oj1JZ27sMOBB9HnwGF02W3QlkfXU9T2BIBRejjM5Pfe4ZtH/kPtmjWxPz/88MO5+uqr6devX6LKzWoSAMaPBIBCtIwEgFki0wPAcFjnsYe/5cnHx8ee/Aw4pjfDbx+M05M+T+LipTkB4MajvypFublxufY3D//BT8/+CUBFl/4MP/lONC39RulM02TCN88z9Zd3Aavz777Dn0h4+KeHTQK1Tc77c6i48vNQIiGNaVq1KShpGaqK1NB0FNipqnFb+mO/1gWAUbphEDYa319GglvG31DF2pUz0MPWchCnJ5f2O+5IbnGxBIBpIJMCwKbqA3X8OPtrvpr+KX8s/AXD1Dd6fU5+Pr0GH0Cv/YfQba+9KKroYFOlzdOSADAq6PPx0/PP8uMzTxP0+WJ/fuSRR/J///d/sjE4ziQAjB8JAIVoGQkAs0QmB4DLl1Vx1eVvM+mPJQC4vE6G3z6Y/iN7J6S+dLCtANA0YcOGDei6bo3+5uaixaEL6NdXZjLuvt8AKG7ThaNPvw+3J7/Vj5tspmnwy1fPMe3XD4DkhH8mEPKHCdaHYzfEmtuJK8+7UaYRDQBBxoBFa5joIevMOwVwaBqZkQHGJwCEzc8FVBRwaNINuL10PcT61bPw1a2N/Zm1Jbg3iqZJAJjCMjUAbGpD3Tp+mP0VP835hsmLfiWkhzZ7m+JOnem+51503XMvuuy2O0UdOqTUL+BaEwBG1a1by/dPPs7vb7yOHgrGHvfoo4/mn//8J717Z+9z6niSADB+JAAUomUkAMwSmRoAfv7ZdG687kNqaqzugooBbTn2P8Mo6VKYkNrSxbYCwNqaWhr81scs3+0mJw5bf6ePXcj7V48HIK+gDUef8QB5Ben3j7Ouh/nu44eYN/1bADoUdOb+I56gNLdNwq5pGuCvazLyq4Az14PD497i28sYsIiHpucBKljnAabQPW0LxS8ABCtw1w0D3dy4G1BzaPK9t51qq5ezYe18zMhCBofLTZsePSlo1y6lwhTRKBsCwKZ8gXomLvyZn+d+y4R546nybdji2+UWl9ChX38q+venQ/8BtO+zIwXtK2z75UA8AsCo6lUrGf/UE/zx9puxjcGKonDUUUdx6aWXMnDgwHiUnLUkAIwfCQCFaBkJALNEpgWA1dUN3HHLJ3z04bTYn+1z3s4MvXwPNFemHWq//f4uAAwEAlRXW2ckuh0OCjw5rb7e3O+X8vbl32KEDdyefI4ecz/FZZ1b/bjJFgr6GffuPSxdMBGAbsU9ufPQhynNTdyTjE23/Cqaiivfi+rY+tfxxl2A0o0kWs40DPTouLkCDjXdQ8D4BoBRhmESNpp0AwKapqFl3BKVxAqHA2xYMxdfXeOZY25vHm169MBb1kYi1RSTbQFgU4ZpsGjtAqYs+pUpi35nyuLfqGmo3urbu3JzKevegzbde9CmR09Ku3WjqH0FhRUd8JaWJjQcjGcAGFW1fBnfP/UEk959GyPcuIxsyJAhXHLJJQwZMkSC+xaQADB+JAAUomUkAMwSmRQAjv9+Htdf8z5rVtcCkNcml5H3H5hVW363ZWsBoKEbbKjcgGGYqIpCsTc3MkbacvN/WMZbl32DHjJwONwceerdlHfs09q/QtL5fTWMffM2Vi+fDUD/drtw67AH8LryEnI904RAfYiwv/HsIS3Hhcubu+2pXtMaTwTpAhStZ+hGrKs0/UPAxASAsOVuQBkLbhlf/Vo2rJlHONQQ+zNPYSElnbuQV9ZGgoUUkc0B4KYM0+CvNfOYvWI6s1f8yZwVM1i4eg5hI7zN93W4XBS0r6CofQX5bduSW1KCt7iE3OJivCWlsf+68/Jwe704c3O362dKIgLAqA1LlvDjs08z+b13CAeDsT/v378/F154IUcddRRu95anFcTmJACMHwkAhWgZCQCzRCYEgHV1Ae6/5wveeO332J/1PaIHR9w2mNzi1nexZZItBYCmCVWVlYQiv8kt9Hhw/U2XWXMs+Hk5b176NXrQQHO4OOKEW+nQLf3GQ6o3rGDsm7dRtX4ZAPt0HsK1B9yBy5GYJ7Wbdf2pCk5vLpq7+aPYjV2ASqtDXCFSNQRs+gylefUkLgCMMkzQm2wKBgkCt5sCmCY1VcupWv8Xht4YLDg9uRR36kRhebu02sSaiSQA/HuBcIC/Vs/lr7XzWbx2AYvXLWTxugWsrFy21QVszeXyenHl5uL2enF783B5vVY46MnFnZsbe73TY71Nbn4BWo4bZ44HlzcXV671epcnF5fXejutFYuM6tat5ZeXXuC3117BX1MT+/OysjJOPfVUzjjjDDp0SO1lKalAAsD4kQBQiJaRADBLpHsA+Puvi7jm/95j2VLrmp4iN0fcNpidhvdMSA3pbksBYNNz/3JdLrxuV6uusfDnFbz5j68JB3Q0zclhJ9xCp+67tLr2ZFu+aBrj3r2bQIPVUXp475Fcss/VaGr8N34ahkmwPkw40KTrz+3E6c1F2d4NDNIFKOKsaQhoLQZRkxYuG6aJaZpWsE30v5tTiAaBCqrS+LXfWGbiA8BYzZuMBROpTdMcaBIE/j3F+nfKxMTQdWqqllJbuRS9SRCoqCp5ZWUUtGtPXkkpinxMk04CwJYJhAOsrlrBmuqVrKq2/ru6egWrq1dSWb+Oal8VNQ1V1hbsJHK43eTk55NbUoq3JNKBWFyCN/p/l5RQUN6OwvbtyW9bvsXAMFBXx8S33uCXF5+neuWK2J+rqsrhhx/O6aefzpAhQ+R4hK2QADB+JAAUomUkAMwS6RoA+v0h/v3AV7z4v19iYw29hnZhxF1DyG/rTcj1M8GmAWBDg5/aWivgcjk0Cj2eVj3+zHGLeP+a8RhhA1VzcNjxN9G556B4lJ5UMyd9zo+fP4FhWIHcGbtdyAkDxsR9/Mw0rQ2/oYZwq7r+tvS40gUo4skwDAy9ycILRcERhw3hTUVDvmjoZ8ThWYiqWOdhqorS5Ps3OU9vdMNE3zQIxDojUNVUCee3pEkAGP3AmaZBfe1qqiuXEArUbfTmqubAW1pCXmkbvKWlOFyt+wWWaB4JABNHN3Tq/LVU+TZQ7auk2leJL1CPL1iPL1BPQ9B6uSHoi/y5j4ZAPQ0hHw1BH/5Qg/XfYEOruw23RFFV8tuWU1RRQUG79hRVVFDapSul3bpR1q0HnqIi5n73Lb++8hILf/lpo/dt3749o0eP5sQTT6RnT/lFfVMSAMaPBIBCtIwEgFkiHQPAaVOXcc0/32PB/LUAuLxODr1xX3Y+ro+cD7QNTQPAYChEVWUlJqCpCsW5ua36+E1+dy6f3v4LpmHicLg55Ljr0y78C4eD/PTF08ya/DkAbkcOVw++jX27HhD3a+khg0B9CCPcJFRxu3B6Pdvf9bcp6QIUCWAaJrreeLOvENl828Kv12hQbZhmJPjb+tsqSmOHX+T/bfZYRDsEt/I4qqKgqckPxXXDRDeNzepSVRVNVWU8uKktBIBNBfzV1NWsor5mNYYR2uz1rtxcPEXF5BYWklNYhCs3V376JYAEgKnPNE0Cup9A0E99sI6GgBUKNgR9sbCw6f/q/DVURQLHKt8GquorqfZtIKRv/n32d9zePEq7daO0azc8hUVULl3C4t9/I9jg2+jtBg0axHHHHcfw4cNp165dPP/qaUkCwPiRAFCIlpEAMEukUwC4vvpDHn34FZ56YnzsJrTLnhWMvG8oRR0LEnLNTBMNAMOhEBsqKzEMAwUoys1tcTePaZr8/NyffPPwJABcbi+Hn3AL7TvvFMfKE6+mciXj3r2HdasWAFDmbcutwx6gZ+kOcb2OoZsE6kPowcabJtWh4vTmojrjN17cdCOwhIAifkz08MZhloIVrqnqpmO3Td4rkueY0e6+SFi3NUp0jFdVGoO/7ajRNK3AMjo+vOlja0rLg8uWMkyrI3DToFMBVE1FUzX5JdY2AsAo0zRo8G3AV7eOhvp16OHAlh9O03B788jJz8Ptzcedn4fbm9eqM8+EBIBpI9IBbZhGixqfTdOkIehjQ/061tasZm3NKlZXr2BNzSrWVq9idc1KVlUtpyHo2+ZjOdxuNJeLQGTqJFaiorDHHnswYsQIjjzyyKw9L1ACwPiRAFCIlpEAMEukSwC4ZMkSTh9zLDOmLwbA4dY46Oq92OO0/q3vlsoi1o0VbFi/nrBujbcW5OTgbmHwFA7qfHbHL0z9YD4AHm8Rw0++g7Ly7vEqOSkWzv6J7z5+mGCgHoBdK/bg6iG3U+Qpjts1DMMk1BAm5Ncbn4gr4Mz14Mhxb1++0exrQvRiEgKKeDJNE0PfvKsNtvylvK0nFIpCJOxT4h+CmSaGYVqBYNNr0roOxlaUEwkCNx/QUxRQVQ1VTd45iymlmQHgpgKBWgK+SvwN1fgbqjZaHrIlDrcbV643tl3VFVmoIMFg80gAmCZaGQA2h2mabKhbx7INi1m6fhHL1i9i6YZFLF2/iOUblqA3YxtyU/3792fYsGEceOCBDBo0CEeWfE9KABg/EgAK0TISAGaJdAkAa2tr2Xv/3Vi9vJIOA9sy8l8HUtY9fuFM1jChqrqaYNC6OfK6XeS28Myk+g1+3r7iG5ZOWgNAYUkFR5x4G4UlFXErN9GCAR8/ffE0c6Z9BVg3nifvfDYn73wWmhqfg6oNg0jwF94o+HPkuHF4chIbYDcZBYZoCBgpYEtvzJbvEbb+PiLbmaaJqW/e1fZ3Ygs7EhX4/Q3TsBaabNrBaEcQCNYvBvTIGPSmFKygRVVVFFXNju/AFgaAmwqFfAQaaggF6ggG6ggGajdaJLI1Egw2jwSAaSIJAeDfCYaDLFm3kIVr5jJ/1WwWrpnLgtVzqKxf36z3z8nJYY899mD48OHss88+9O7dO2OPTJAAMH4kABSiZSQAzBLpEgAC3DPuKib/MZt9z9sF1ZGZTwASyoTqmmoCAesmyON0kpfjbtFDrZixjnev+o7/b+/Oo+MoD3zv/6qrN60tyZK8SbblhcV4YYsxBmxjyMaawAxzAN/h3Hsgl5l7JySQc/MOJByC4ywz8zowZBKSyZw5MJC5MzgwvgHzejgYTMAmNpfFNt7AC16xJUtuSa1eq+r9o9Wtbqkla7XUre/nnHYvVfX0021VV9evn+XMseSA7FNnLNQXb/9r+YvKhqu2I+7E4Y+1cd3/q7bgSUlShb9S31n6mC6vWzws5ecM/iSZXk9ynL9hnkChV446w5nstk/Z0yH07+O+7wAR453TOQBfzlaBnanfwLvzjoxcLRhdRjIIHI2Wd05nWG/3EgZKyW7WhsuQy3Cd8+D0nBmmADAXy4opFm1XPBZSPBpSrPM611iC3bl9vs5AMBkM+kpL5S8tG7czEBMA5olRDgB709zepP0n92rfiY+15/hO7Tm+U42tn591O6/Xq/POO0/XXHONvvSlL2nhwoUqK8uf7519IQAcPgSAwOAQAI4T+RQAvtT2cx21T41I2QXPkYKtrYpGk+Mk+dxulRf5B16M7eiP/7JLrz/xf2Unkl/65152g6760n+XaeZHC4loJKStbzyjj//veqW+EV85bakeuOrhYenya1tOcmbfzK6+klwetzzF/mEd528gMscE7B9DvZ8xJIMcuhQj3+VqEWgahkyXK+dYhuekTp1hYNcEKbkZnSf3XWMlFkA3/xEMAHtjJWKKxQYeDBouU0Xl5SoKVKioIqCiQMW4aSlIAJgnxmgAmMvp9kbtPbZTe0/s1O5jO7Tn2A61RoJn3S4QCGjOnDm68sortXjxYs2ZM0fTpk2TaQ5PL45zhQBw+BAAAoNDADhOEACOA47U2tqqSGf45zVNlRcVDfjkNnQ6rP/z/Xf06R+OSpJM06OrvvTfNfeyrw53jUeE4zg6tHeL/rDhaXW0Jbuf+N1Fun/xg/rynJuH1JrGkWTHbcXCiazJPSTJ5XXLUzR6wV+Ws5xT99o4Kz2BQ+ed9Ppjp0UXMBS2bcu2Mv+2R69bcHddrQPt9GQqvUk2tOzqWm2kJ2YZ/dfRL6MQAPZmwMGgYchfVq6SCRNUUlWlovJA/rzvA0QAmCfyKADsznEcfR48rj3Hd2j34Q+168hH2t+4T+FE+KzbmqapiRMn6sILL9TcuXPV0NCgKVOmaOrUqZo6deqYbDVIADh8CACBwSEAHCcIAAub40itGd1+PaapiuKiAZbhaPvv9+u1v92m8JlkiFhZXa/rb/t/NKF2xnBXeUQ0N36mLa/9RkcOvJ9+bFH9VfqfV/4v1ZZOGnS5jiMlopbikYTsRPagYqbXI7ffL5cnv36FPpvOXp7KCgILoeURIEe2lZwwJMWQ5DbH1oQcWS0EzzKbcqb0zMqZl7EWDo6hALA3ViKqaLRV0Y6gIpEzikXa5Dg9QzCX262SyiqVVteotLpapsczCrUdGQSAeSKPA8BcbMfWkaaD2nXkI3382Qfae2KnDjUfULwf3fgzlZWVqa6uThMnTtSECRPSl+rqalVXV6fvBwIBBQIBeQc5VvZAEAAOHwJAYHAIAMcJAsDC5TiOgsGgYrHkF6Nkyz+/XIZLvXcqy9ZypE3rV23RgS3H049dsPCLuurL98vjHXgX4nMtHArqvbee1673X02foFUWVekvFn9H18xYMagTX0eSnXCUiCQUj2Z3801P7uH3nbsx/kZJ9y7FhIAoFL2ND+h2maPWLfhs7M790XEcOZ2h4IA6/I+VcDAPAsDuHMdWNNKqSEeLwh2nFQ23qkflDUPFgQqV1tSorLpGnqKB/RA31hAA5okCCwBziVsxHTz1qXYf/Ui7jnyovcc/1uGWQ8nXPEyKiopUXl6u8vJyBQKB9HUgEFBZWVn6dmpZRUWFKioqVFVVpfLy8n51RyYAHD4EgMDgEACOEwSAhcmyLAXPBJWwLEnJMf/K/L70Sd3ZAsCOMxG985sd2vavu9NdWksDtVr61f+habMvH/H6D1Uk3Kbt776kHdv+j+KxZHcRt8utW+feoTsX/jeV+gbe/cO2HSWilhJRK7u1nyTDdMnt98n0e8dWa5qR1mOCEUMuugSjQDid3YIz93bT1Tk+4KjVamBSQX2yC/8QwkEZPQPCkfisy8MAsDvbTiTDwNBpdYSaZCWiPdbxlZaprKZWZbW18paU5M3fUwoBYJ4YBwFgLpF4WJ9+vkd7ju/Up5/v1oGT+3Socb9iVs99caQZhpEVCFZUVKiysjJ9qa6u1sSJEzV79mzV1dWppqZGoVDonNezkBAAAoNDADhOEAAWnngsrmBra/pLud/jVqnPn2650lcAGA3F9d7/3qN3/mm7om3JloOG4dL8RbfoC8tWyuMd260WwqGgdr73snZs/Q/Foh3px5dMW6Z7F/2VppTXD6g823ZkxWzFo5bseLeTnHQ3X9/YGN9vFNEaEIUrd7fgsTI+4GClcvthCQcNQ0Z6ZuLkMWPQ70wBBIDdRSOt6mhvVEd7o+Kxnif23uISldXWqqymVr6ysrz45CQAzBPjNADMxbItHWs+rAOn9ungqX06cOoTHTi1Tydajsl2rH6XY3o8nd35DTmOLTuRkBUfWBfks6mqqtLEiRPTl/r6+qzLlClTzkm35HxFAAgMDgHgOEEAWEAcKdTRoY5QKP09r8TnVXG3Lwm5AsDgiXZt++1uvb92n6LtXV9k6mddritW3KPqiTNHuvZD0tJ0WNv/uE77dmyUlYilH7948uX6L5d+QxdNXNjvsmzLUSJmyYrZshI9vzS73KZMn1emzysjjwOA4UYIiILmOLJydAs2XaYK8WNgqC0He0xG0t9WgwUYAGaKx8PJMLDtlKI5Zjj1FBUlWwbW1MofCIzZT1ACwDxBAHhWCSuuE2eO6ejpz3S0+ZCONn+mo6c/07GWw2psPSnLTgypfJfbLdPrlcs0ZRguSY4c25aVSMiKxeQMYv8xDEOTJ09WXV2dpk2bpunTp2vWrFmaOXOmZs6cqcrKyiHVOd8RAAKDQwA4ThAAFgbLstXW1poe789lSKV+v3zuni3TUidXiWhCn7x1VDtePqB9m47IyZgBs2byHC2+7r9q6oz+B2fnmmUldPjTbdr1/v+nI/vfy1o2f9IlWnnJfVo4+bKzluM4kp2wlYjZsmJW1kygKYbpkunzyu3zFvzYfkPSrUswswSj0OQeH9CQ2+Uas+MDDrchh4MZXYplGFlhodIhYWEGgJkSiWg6DIyEz6j7C3b7fCqrqVVpTa2KKyrG1PASBIB5ggBwSCzbUkvotE4GT6ix9YROBk/oVPCEGttOKRhqVktHs86ETqs13DPMH03FxcWaNGmSpk6dqmnTpmnmzJk677zztGDBAk2ePHlMfZaMBAJAYHAIAMcJAsA850jhcFjtoVC69ZXbdKnc75fp6hlUdZyJ6OCWE/r07aPa+8bhdDfflGmzL9eCK76uqTMWjtkvCM2Nn2nPh6/pk51vKBw6k37cZZha2nCdvn7RnTq/Zm6v26cm8bDilqy4LSue+4uxy+2Sy+OR6fPK5S6smXxHWvfWgMkZVMfm3xMwcMkuwd1/LDCNzvEBx+mfejIEdHJeD1R2SJi8rVQX47E2c/EwsKxYZxjYqEi4pceswqbHq9KaGpXX1Kq4slJGjuP7uUQAmCcIAM+JhBVXMHxGZ0LNagmdVnukVe2RdrVHWhWKtisUbVOo8357xv2OWEgd0ZDiVuzsTzKMvF6vysrKVFVVpSlTpmjGjBmqq6tLz4JcU1OjSZMmqba2Vp48nL2cABAYnHEVAAaDQa1du1Zbt27V6dOn5fP5NGvWLN1www1avHjxoMtNJBJ6+eWXtWnTJh0/npxFderUqVq2bJluvPFGuXO0zsp04MABvfTSS9qxY4daW1sVCAQ0b9483XbbbWpoaBh0vTIRAOavWCyu9vZ2JRLJ7gmGpCKvR8VenwxDsi1bpz9r1YmPT+vEx006+lGjjn/c1ONLoL84oNlzr9FFl9+oyupp5/6FnIXjOGpu/EwHdr+jg3s3q/nUoazl5b6AvjjnJt069w7Vlk7KsX2yhZ+VSIZ9dsJWzsnhjFRXDY9Mr4eWfkNEl2AUvp7jA0rJwNt0uQqya/BgZYWCTmoQioGPOZgp1bg4c4ISdQsI8zEotO2EOtobFWo/pUiouUcY6HJ7VFpdrbLaWpVUTcgK484VAsA8QQCYF+JWTJF4WKFoSOFoSO2RNnVEkwFhKBpSuDMoDEXbFe58rCOWXDcUa1dHNJRcPxpSbJjDxKqqKk2ePFn/9E//pFmzZg1r2SOFABAYnHETAB4+fFiPPPKIgsFk8+2ioiJFo9H0F5qbb75Z991334DLDYfD+v73v699+/ZJUnqw1lgs+cF8wQUX6PHHH5ff78+5/aZNm/Tkk0+mw52SkpL0rFBut1vf/va3dc011wy4Xt0RAI59juPIjtvJGWhjliKhiNqDIYXbI0pELYXPRBU9E5MVjCvcElXL0XY1f9aqM0fbkq3bcvD5S1U/63LNmb9cdQ2XyDTH1iQW8XhEJw7v1NEDH+rQvj+qteV41nKX4dJlUxfry+fdrEX1V8trJvcvx0mO4WcnbNlWZ+Bn9X6GmWrl5/K4ZXrcGrdNd0YKXYIxLvQWBCY/q1yu/Iy+U6Fdqjdu5rh8Tsa/SV2vMXMfN9JdfPv3XKlvnqmvoIOZmKS7VBfjrHAwozVhuoXhOZD9Hna9mU72ja71HUvhULPCoUaFO07LsbMnK3CZpkomdIaBlVWdkxOMPALAPEEAmDeGa59KWPF0y8KOaEihSJta28+ore20Wlqb1NzWpJb2Jp3paFFbrFVt8Xa1xdvUHg/1OkGgJL34v3+na65bOuh6nUsEgMDgjK00YITE43H98Ic/VDAY1PTp0/Xggw+qoaFB0WhU69at0/PPP6/f//73amho0PXXXz+gsn/xi19o3759Kikp0Te/+c10S8J3331Xf//3f689e/bol7/8pb797W/32Pbw4cPp8O/qq6/Wvffeq6qqKjU3N+sf//Ef9c477+iJJ55QQ0OD6urqhuW9wNAlopYirVGFz0QUDkYVbum8PhNRLJxQPJxQIpJQPBxXPJJQPGIpHk4oHonLitlKRBOyYlY66EtErfT9ofL6ilU9abamTJ+v+lmXqmbyHLlcY6dbayzaoVPH9urksT06dmi7Pj+6S7aVPfCyIUMX1s7XVdOXa9msL6nKXy3HcmTFHUXC8c7Qr+8zRcPtSrby83jk8pij3o2q4BnJEMRxjIyxwgwZhkNrQBQQQy7TkMvMDgJtR7IdW4adbBXochmd3eHHlq5WeV3ddu0BhwVOt5s5xlI1JJeyu/GmZ6fPCOOS//TcPh0E9mhB6GQvz1Ezp2vjXl9BZovCrFCwc0H3/7lUXXq/7+TK9AbMW1Qlb1GVAralSKRFkdBpRcLNcuyEbMtS26mTajt1UpIhX2mpiquqVFpVpaKKijF1nAcw8tymR+VFFSovquhzPUeSFYsp1hFSNBRSpL1NzWdO6XTwpJrbGxWMtepMLKhgrFXBWFBTp844F9UHMIrGRQC4YcMGff755/L5fHr00UdVU1MjSfL5fLrjjjvU3Nys9evX67nnntPy5cvP2mU35eDBg3rrrbckSX/1V3+lK6+8Mr3syiuvlG3b+ulPf6o333xTt912m6ZPn561/fPPP69EIqGGhgY99NBDMs3kF7iqqip95zvf0fHjx3Xw4EE9//zz+u53vzscbwX6YMUstTV2qO1kSO2nQmo9GVLbyQ61nwqp7VRIbZ33o+3ndgyPngz5i8tVFqhRoGqqAlVTVDGhTjWT5yhQNblz9rHRF4t2qKXxsE6fOqTGE/t08ugeNTceVq7TJK/p07zai7W4fqkWTblaFd4JyQH4I446OqJ9P1Fnl16Xxy2X25TL487L7mCFINUiKNmqp6tFj4vWgCgoGUGg7cixu/7WLceRZTkylAwDDcPovD53tese9NmDGJ+vP/XtrUzHkSz1DOJc3QLB3loMGul8MN3WsNfnGUxrwlS1nBx1PJdSr6rHs7tM+Yur5S+ulhxb0ciZZBjYcVq2HZfkKNrepmh7m1oOfyYZhjzFJfKXlakoEFBxoEK+klIaugOQIcnt9crt9aq4Ijlr8GRdKEmyLaszGOxQrCOkeDis6imTR7G2AM6FcREAvvnmm5KkpUuXpsO/TLfffrteffVVNTc3a8eOHbrkkkv6Ve6mTZvkOI4mT56cFf6lLFmyRJMnT9aJEye0adMm/fmf/3l6WSgU0rZt2yRJX/va19LhX4ppmvra176mn/3sZ9q6das6OjpUXFzc35ec115YvUG7PzjUeVLV+ct6+iTLSd+WIxmmIZfpkss0ZJguudyGXK7Oa9MlwzRkJJsmybGT4+XZcVuJuKVExFKsI568tMcU60icvXJn4TI9cnt8XRe3V26Pv/O+V6a782K6ZZpeuUx38uLyyHR7ZJqeznU88ri9nWUkH/cXl6uopFJFJYEx82u/ZSXUHmxU25nP1Xrmc7W2nFBL0xE1n/pMbcGTvW7nMlyaHpilhTWXa0HNZTq/coF8pi+50JYSkdytIQ2XIcNtJgM/05TLbTKG3xiTauGTbo2T0crIMHK1rwHyVbK1n1ydgZttK9WjKxUGptKpzECwq2Xc4J85O/xK7mNdY+71o+ZGV2BvdCZxg++231kPp6s+GS89LT1MQOaYoVKPloKp7sT9eg3p1oS5654OB3MEhanHM9fr+wmznyGrlullRuZDOVsV9vb/3lXXzpo5kuSSWTxBRcUT5Di2YpE2RSNnFI2cUTzalhw30HEUD7UrHmpX2+cnks/hdstTVCRPcYm8xSXyl5XKX1ouj9eb/JsFMO65TFP+snL5y8rTj/EDOlD4Cj4ADIfD+uSTTyRJl156ac51ampqVFdXpyNHjuijjz7qdwC4fft2SdIll1yS8wPTMAxdcsklOnHiRHrdlF27dqXH/eutXqnH4/G4du/ercsuu6xf9cp3n+1r1dH3Px/takiSTNMvnzcgr7dCPm9F8ranTB5vqbzeEnl9pfJ6y+Tzl8rjK5Hb402Gka7OUNJlpENIw5AMlySXIcPVGWa5jKz1TNMl03TJ7TbT25xrjuMoEY8qGmlXNNymUHuzOtpa0tcdbc3qCLWovbVRHe2N6s8wouXegM6rvEhzKufqvMqLNLvyAhW5ew+0DdOVDHRNU4Zpdoa5yfcEeSDjZDgVCGR240sP3J/xL5DPDMPo/Kzq/Du3s8cK7B4IprdTVyDUW+zV1a5NA+5qmg76OifnMTKfcNhkhIg9liV/fHM6X3tnTpixVF2fEX0Fg+oqfyDVz3pv+wgKx4Kuunb+26O+LnlLK1VSUpnsvm1bioSDikaCikVaFYu1pccOdBIJxdraFGtrU6jrGZIz3nu9Mv1+efx+efxFndc+eX1FchMQAgBQ0Ao+ADx69Gg6oOjeBTfT9OnTdeTIER05cqRf5TqOo6NHj5613GnTkrOtdi83db+iokKBQCDntoFAQIFAQMFgUIcPHx43AaD85SqfMVWOZcu2LDkJK+vaTliyY3E5Qxg81zDMZKDnS4Z6Pm9FZ8gXSD/u9QTkdueevKWHuBSP24orctZVuwKzHGMfZQ4W7liS4UiGLcOVvHYMR4ZhS7KTgz3LliNbsi3ZsuU4thzHkm3HZFlx2XZcCSsmOxGTZcWSt62orERclh1TPB5WPN6hRLxD8c5LIhFOPvcg+M0iTS6t07SymZpWPlPTyhs0rWymqvzVWSF5MvxMhnxZ165k6DdGz88wQKnwwXGS/6HpLnrprnrJf7NPzrv/9/PHgHzS+WOPachlqrNVXOrSs6VZdiA2+K6oWUHfkFrzDbfOH7yy6pLdYjDd0j9rjdzBYFepPYPTrElJMv7p7V3I14YuqWDUZbpVWjpBpaUTJCXfx1isQ9FIUNFIm+KxkOLxUMaEIo7seEx2PKZ4qD3ntxXD5ZLhdsvl9qRb2ptud/K2O9ljwfS45XKZ6R/p0rddplyuzh/rjGRvjK6/RyMdQitPJ8sBAKAQFHwA2NzcnL5dVVXV63qpZf2d2TYcDisSifS73HA4rHA4rKKioqzn6Wvb1PJgMHjWej333HP67W9/2+vyO++8U3fddVefZfRHavYql8ulysrKIZeXy5FtuxQ+0zq0QgxX1iyASt1OX0sJu0OJcIfaw8eS23T1D0oXkxnIZd3PWi871Mg2OmMLjQRDhsq8AVX6J6jCV6Uqf7UmlUzVxOLJqi2ZokmlU1Xuq0i21jNcnS0dXZ0tGV1doZ/LNTbOS3HOZJ6oZ53Yd3K6nf1n7zX97JsHjFXp8EPJPaB7V9TuoaDTRziV2peymotlr5xrHxuTMmbslbrem66JPPoYZzBrWeb7OMZf80gz/fKV+OUrmdj5gCMrEVUilvyhL5EIy4pHlEhEZCWi6vFpa9tyYjHZsXMw1nH6O5nU52d4vz7e+7FSr6tw/ABSDs+aoLvuvm20qwFgBBV8AJgK6aTkpB+9SS0Lh8P9Kjdzvf6Um9omFQCmtu9r24HUKxQK6dSpU70u7+jo6DHO4FAYhjGs5WVyYkMfi0+O3aOrESTT5U5eTLfcLrc8bp98Hp+8Hp98niL5fclLkb9YRUUlKi4qUaC8UoHyKpWVBuQv8snr88pX5JPX75PP75PX75Wnc+INR5YsDX02YxS+cCSqxtNn1BJsU2tru1rbQ4pEYrKH0LIXQAFyJMeyZVmS7ORYi8kG8N1uc7wfEMdly4pFZSWisq2YrHhMViImOxHt7DWQkGPHZVuJzpmIh+G7GYAx7QH7oRE7vwMwNhR8ADhelJSUqLa2ttflxcXFsqyhBzMulysZ9DjOiJ2o3/a1r2nPnj2Sulo55Lru67G+7ve3LJfLJdM05fF45Ha75Xa7e9wvKipKX1LvTebz5bru77LM58l1MU2z12VFRUUqKSmRz+eT3+9XcXGxfD4fg/uOMedif8ontm3r9OnTOn78uE6fPq1QKJR1CYfDsm1blmXJtu2s25ZlDctnXC6pz4hUV06ptxa/I+NcPle+y/V/hbFnJP6fHMeRZVmKxWJZl0QikfUZ0dvnRua+3WO4gl4eyzd91tnTecmQ+Z3BsQ3Ztq14PK5EIqFEItHjszh1LEu9X6nb3Z/7bJ+lw/3e5uP/FTAaZs+ZOWLfpYYbQSUwOAUfAPr9XWO4RaPRXmfSjUajkpRuoXc2meultu2r3O7bpG73te1A6rVy5UqtXLmy1+VNTU397t7cl8rKSpmmKdu2h6W8XJ588skRKXc8MU1TlZWVamlpkWVZ6S7oGFvOxf6Ub9xut6ZNm5YeP3Us6L4/YexK7VOWZbFPjWHsU/mB/Sk/sD/lj3zYp8Zqvbqrrq4e7SoAeck12hUYaZlj7GWOB9hdall/x7VLtfrqb7mZ62fWq69tB1MvAAAAAAAAIFPBB4B1dXXpLgyHDx/udb3Usvr6+n6VaxiG6urqBl1u6v6ZM2fU2pp7wotgMKhgMChJY6o1DAAAAAAAAPJHwQeARUVFmjNnjiTp/fffz7lOU1OTjhw5IklauHBhv8tesGCBJOmDDz7odZ0PP/wwa92UuXPnyu1291mvVLkej0cXXnhhv+sFAAAAAAAApBR8AChJy5cvlyS99dZbamxs7LH8xRdflOM4qqqq0vz58/td7tKlS2UYho4fP64tW7b0WL5582YdP35chmGk65BSXFysL3zhC5KkdevW9Rizw7IsrVu3TpK0aNGiXscuBAAAAAAAAPoyLgLAL3/5y5o0aZIikYhWrVqlgwcPSkpOsLF27Vq98sorkpITaaRa5aXce++9uuWWW/T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}, "metadata": { "image/png": { @@ -323,13 +366,18 @@ "source": [ "# plot\n", "(\n", - " ggplot(rews_df_case3, aes(x='rew', fill='agent'))+geom_density(alpha=0.7)\n", + " ggplot(\n", + " rews_df_case3[\n", + " ~(rews_df_case3.agent=='ppo_nr1')\n", + " ], \n", + " aes(x='rew', fill='agent'))\n", + " +geom_density(alpha=0.7)\n", ")" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 39, "id": "fee15370-568a-4fdc-8c16-a3db8e33256f", "metadata": {}, "outputs": [], @@ -349,12 +397,25 @@ " **CONFIG3\n", " }\n", ")\n", - "_ = reprod_escEnv_3.reset()" + "_ = reprod_escEnv_3.reset()\n", + "\n", + "\n", + "reprod_mwt_env_3 = AsmEnv(\n", + " config={\n", + " 'reproducibility_mode': True,\n", + " 'r_devs': reprod_env_3.r_devs,\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " **CONFIG3\n", + " }\n", + ")\n", + "reprod_mwt_env_3.observation = 'mwt'\n", + "_ = reprod_mwt_env_3.reset()" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 40, "id": "c8be4e61-5766-4402-bf1d-be7308751ce4", "metadata": {}, "outputs": [], @@ -364,7 +425,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 41, "id": "55d46a8d-1f8f-4f25-b58a-f036c64ce18b", "metadata": {}, "outputs": [], @@ -383,18 +444,22 @@ "\n", "ppoEsc_ep = pd.DataFrame(\n", " full_ep(policy=ppoAgentEsc, env=reprod_escEnv_3)\n", + ")\n", + "\n", + "ppo_mwt_ep = pd.DataFrame(\n", + " full_ep(policy=ppoAgent1obs_mwt, env=reprod_mwt_env_3)\n", ")" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 42, "id": "6866d87d-6193-45af-bf54-b8ef1e4db651", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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2NTWJEyZMEG02m3jdddeJzzzzjPjII4+IV111lZicnCxWVlaGbHvfvn2GfyuewKp+LmfBggUiAHHKlCniv/71L/GZZ54R77jjDnHw4MHiww8/HPDYO++8UwQgpqeniz6fT75/6NChIgDxN7/5jeF+mGXRokXi0KFDxb/85S/if/7zH/GRRx4RTzvtNBGAePbZZ4d9vt7xVVxcLBYXFwfcV1ZWJhYUFIipqanivffeKy5cuFAcMmSImJiYKG7YsCFgnwCIkydPFl977bWQr67YRI7oXpAYIQiJnTt3itdff73Yr18/0eFwiKmpqeLUqVPFJ598Ui67FEVjMfLyyy+LAMT//ve/Ybf33HPPiRMnThQTExPF1NRUcfTo0eIdd9wR0AWWb+uLL74Qx4wZIzqdTnHYsGEhJbta1TTXXHONOHDgQDEhIUHMysoSTz75ZPGrr74KeJ7H4xHvu+8+sX///qLdbheLiorE+fPnB7xfUWTlsffdd59YUFAgJiYmiiUlJeLmzZs1O7A2NDSI8+fPFwcNGiQ6HA4xOztbnDJlivjII48EiLQLL7xQTExMDCil1cJIjIiiKL7//vviSSedJCYnJ4vJycnisGHDxHnz5ok7duwIeNynn34qC0A11113nQhAfPHFFw33wyw//fSTePHFF4t9+/YVnU6nmJycLE6YMEFcuHCh6PF4wj4/EjEiiqK4Z88e8fzzzxfT0tLExMRE8ZRTThHXrFkT8Bgu/PS+wglCgmhrBFHU8BMJgugU9OvXD6NGjcInn3zS0bsSd/Ly8jB37lw8/PDDHb0rBEF0MJQzQhBEu7Nlyxa0tLS0Wet1giC6FlRNQxBEuzNy5EjU19d39G4QBNFJIGeEIAiCIIgOhXJGCIIgCILoUMgZIQiCIAiiQyExQhAEQRBEh9IlElj9fj+OHDmC1NTUuM7RIAiCIAii7RBFEQ0NDSgsLAzoCBxMlxAjR44cQVFRUUfvBkEQBEEQUXDw4MGAAZ3BdAkxwoc9HTx4UHeCJUEQBEEQnYv6+noUFRUFDG3UokuIER6aSUtLIzFCEARBEF2McCkWlMBKEARBEESHEpEYWbBgAY4//nikpqYiNzcX5513Hnbs2GH4nJdffhmCIAR8JSQkxLTTBEEQBEF0HyISIytWrMC8efPwww8/YOnSpfB4PJg1axaampoMn5eWloajR4/KXwcOHIhppwmCIAiC6D5ElDOyZMmSgJ9ffvll5Obm4ueff8b06dN1nycIAvLz86PbQ4IgCKLH4vP54PF4Ono3CB3sdjusVmvMrxNTAmtdXR0AICsry/BxjY2NKC4uht/vx4QJE/Dggw9i5MiRsWyaIAiC6MaIooiysjLU1tZ29K4QYcjIyEB+fn5MfcCiFiN+vx+33norpk6dilGjRuk+bujQoXjppZcwZswY1NXV4ZFHHsGUKVOwZcsW3Zpjl8sFl8sl/0zTPQmCIHoWXIjk5uYiKSmJGl52QkRRRHNzMyoqKgAABQUFUb9W1GJk3rx52Lx5M1atWmX4uMmTJ2Py5Mnyz1OmTMHw4cPxn//8B//4xz80n7NgwQLcd9990e4aQRAE0YXx+XyyEOnVq1dH7w5hQGJiIgCgoqICubm5UYdsoirtvemmm/DJJ5/gm2++MeyopoXdbsf48eOxe/du3cfMnz8fdXV18tfBgwej2U2CIAiiC8JzRJKSkjp4Twgz8P9TLLk9ETkjoiji5ptvxocffojly5ejf//+EW/Q5/Nh06ZNOOOMM3Qf43Q64XQ6I35tgiAIovtAoZmuQTz+TxGJkXnz5uHNN9/E4sWLkZqairKyMgBAenq6bNXMnTsXvXv3xoIFCwAAf//733HiiSdi0KBBqK2txcMPP4wDBw7guuuui3nnCYIgCILo+kQUpnnmmWdQV1eHkpISFBQUyF9vv/22/JjS0lIcPXpU/rmmpgbXX389hg8fjjPOOAP19fX4/vvvMWLEiPi9C4IgCILoBJSUlODWW2/V/X2/fv3w2GOPtdv+dBUiDtOEY/ny5QE/L1q0CIsWLYpopwiCIAiiO/LTTz8hOTm5o3ej09ElBuURBEF0BURRhMvrR4I99iZQRPckJyeno3ehU0KD8giCIOLEDa/9jJMe+gYHq5s7eleIDsTr9eKmm25Ceno6srOzcffdd8uRheAwTWlpKc4991ykpKQgLS0Nl1xyCcrLy+Xf/+1vf8O4cePw0ksvoW/fvkhJScHvf/97+Hw+/Otf/0J+fj5yc3PxwAMPBOzDwoULMXr0aCQnJ6OoqAi///3v0djYKP/+wIEDOPvss5GZmYnk5GSMHDkSn332GQCWXvHrX/8aOTk5SExMxODBg/Hf//63Df9i5IwQBEHEjaVb2UVk3pvr8H83ndTBe9O9EEURLR5fu2830W6NuFrklVdewbXXXos1a9Zg7dq1uOGGG9C3b19cf/31AY/z+/2yEFmxYgW8Xi/mzZuHSy+9NCDlYc+ePfj888+xZMkS7NmzBxdddBH27t2LIUOGYMWKFfj+++9xzTXXYObMmTjhhBMAABaLBU888QT69++PvXv34ve//z3uuOMOPP300wBYQYrb7ca3336L5ORkbN26FSkpKQCAu+++G1u3bsXnn3+O7Oxs7N69Gy0tLTH8FcNDYoQgCCIO+P1KTt3GQ3XYWd6AIXmpHbhH3YsWjw8j7vmi3be79e+zkeSI7FJZVFSERYsWQRAEDB06FJs2bcKiRYtCxMiyZcuwadMm7Nu3D0VFRQCAV199FSNHjsRPP/2E448/HgATLS+99BJSU1MxYsQInHzyydixYwc+++wzWCwWDB06FA899BC++eYbWYyok2j79euH+++/H7/97W9lMVJaWooLL7wQo0ePBgAMGDBAfnxpaSnGjx+P4447Tn5+W0NhGoIgiDjQ5PYG/LztKI2x6KmceOKJAW7K5MmTsWvXLvh8gc7Otm3bUFRUJAsRABgxYgQyMjKwbds2+b5+/fohNVURtnl5eRgxYgQsFkvAfbwtOwB89dVXOPXUU9G7d2+kpqbiyiuvxLFjx9DczEKIf/jDH3D//fdj6tSpuPfee7Fx40b5ub/73e/w1ltvYdy4cbjjjjvw/fffx+GvYgw5IwRBEHGgoTVQjNQH/UzERqLdiq1/n90h2+1o7HZ7wM+CIGje5/f7AQD79+/HWWedhd/97nd44IEHkJWVhVWrVuHaa6+F2+1GUlISrrvuOsyePRuffvopvvzySyxYsACPPvoobr75ZsyZMwcHDhzAZ599hqVLl+LUU0/FvHnz8Mgjj7TZeyRnhCAIIg6EiJEWGnsfTwRBQJLD1u5f0XQX/fHHHwN+/uGHHzB48OCQuS3Dhw/HwYMHA0aebN26FbW1tTH14vr555/h9/vx6KOP4sQTT8SQIUNw5MiRkMcVFRXht7/9LT744APcfvvteP755+Xf5eTk4KqrrsLrr7+Oxx57DM8991zU+2MGckYIgiDiQENroPiobyUx0lMpLS3FbbfdhhtvvBHr1q3Dk08+iUcffTTkcTNnzsTo0aPx61//Go899hi8Xi9+//vfY8aMGXK+RjQMGjQIHo8HTz75JM4++2x89913ePbZZwMec+utt2LOnDkYMmQIampq8M0332D48OEAgHvuuQcTJ07EyJEj4XK58Mknn8i/ayvIGSEIgogDoc4IhWl6KnPnzkVLSwsmTZqEefPm4ZZbbsENN9wQ8jhBELB48WJkZmZi+vTpmDlzJgYMGBDQ1Twaxo4di4ULF+Khhx7CqFGj8MYbb8gjWjg+nw/z5s3D8OHDcfrpp2PIkCFycqvD4cD8+fMxZswYTJ8+HVarFW+99VZM+xQOQTTTVrWDqa+vR3p6Ourq6pCWltbRu0MQBBHC//1yBH/433r55zPHFOCpX03owD3qurS2tmLfvn3o378/EhISOnp3iDAY/b/MXr/JGSEIgogDIWEayhkhCNOQGCEIgogDPEyTnsiqHKiahiDMQ2KEIAgiDnBnpHdGIvuZnBGCMA2JEYIgiDjAnZHemUyMUDUNQZiHxAhBEEQckMWI5IzUt3jRBeoDCKJTQGKEIAgiDvAwTR/JGXH7/HB5/R25SwTRZSAxQhAEEQe4M5KblgCL1LSTKmoIwhwkRgiCIOIAFyNpCTakyRU1JEYIwgwkRgiCIOJAg4sJj9QEO9ISmBipoy6sBGEKEiMEQRBxINAZYWO/yBkhCHOQGCEIgogRURRlMaJ2RihnhIg3/fr1w2OPPdbRuxF3SIwQBEHEiMvrh8/PyniTnValCyuJEYIwBYkRgiCIGFGX8DptViQ7WZimye3rqF0iOoiSkhLcfPPNuPXWW5GZmYm8vDw8//zzaGpqwtVXX43U1FQMGjQIn3/+OQDguOOOwyOPPCI//7zzzoPdbkdjYyMA4NChQxAEAbt370ZJSQkOHDiAP/7xjxAEAYIgdMh7bAtIjBAEQcSIWyVG7FYBiXYrAKCZxEj8EEXA3dT+X1E0rnvllVeQnZ2NNWvW4Oabb8bvfvc7XHzxxZgyZQrWrVuHWbNm4corr0RzczNmzJiB5cuXS29RxMqVK5GRkYFVq1YBAFasWIHevXtj0KBB+OCDD9CnTx/8/e9/x9GjR3H06NF4/oU7FFtH7wBBEERXx+NjYsRhtUAQBCQ5mBhp9ZAYiRueZuDBwvbf7l1HAEdyRE8ZO3Ys/vrXvwIA5s+fj3/+85/Izs7G9ddfDwC455578Mwzz2Djxo0oKSnBiy++CJ/Ph82bN8PhcODSSy/F8uXLcfrpp2P58uWYMWMGACArKwtWqxWpqanIz8+P7/vsYMgZIQiCiBHujDhs7JSaIDkjLeSM9EjGjBkjf2+1WtGrVy+MHj1avi8vLw8AUFFRgWnTpqGhoQHr16/HihUrMGPGDJSUlMhuyYoVK1BSUtKeu98hkDNCEAQRI9wZsVtZDD/RQWGauGNPYi5FR2w30qfY7QE/C4IQcB/P9fD7/cjIyMDYsWOxfPlyrF69GqeddhqmT5+OSy+9FDt37sSuXbtkZ6Q7Q2KEIAgiRlxBzgjPGaEwTRwRhIjDJV2FGTNm4JtvvsGaNWvwwAMPICsrC8OHD8cDDzyAgoICDBkyRH6sw+GAz9f9jisK0xAEQcSI4oxIYkRyRlpIjBAmKCkpwRdffAGbzYZhw4bJ973xxhshrki/fv3w7bff4vDhw6iqquqI3W0TSIwQBEHESHDOiFJNQ+3gifBMmzYNfr8/QHiUlJTA5/OF5Iv8/e9/x/79+zFw4EDk5OS08562HRSmIQiCiBGPj5V/OqyBYqTF49d9DtE94Ymnavbv3x9yn6gqGc7KyoLfH3isnHfeeQGP4Zx44on45ZdfYt7PzgY5IwRBEDHilmL43BmRS3spgZUgTEFihCAIIkbcXraC5TkjCZQzQhARQWKEIAgiRtyqpmcAqAMrQUQIiRGCIIgY8UgJrHYq7SWIqCAxQhAEESPBzkiSKkyjlYRIEEQgJEYIgiBihJf2Om2BOSM+vygLFYIg9CExQhAEESMh7eClMA0AtLpJjBBEOEiMEARBxEhwO3i71SILE6qoIYjwkBghCIKIkeB28IAyuZe6sBJEeEiMEARBxEhwO3hA3YWVnBGCCAeJEYIgiBjxBFXTAMqwPCrvJYjwkBghCIKIESNnhBqf9WzcbndH70KXgMQIQRBEjLh9ge3gAcUZaSEx0qMoKSnBTTfdhFtvvRXZ2dmYPXs2Nm/ejDlz5iAlJQV5eXm48sorUVVVBQD45JNPkJGRAZ8032jDhg0QBAF33nmn/JrXXXcdrrjiig55P+0FiRGCIIgYoZyRtkcURTR7mtv9K5qmda+88gocDge+++47/POf/8Qpp5yC8ePHY+3atViyZAnKy8txySWXAACmTZuGhoYGrF+/HgCwYsUKZGdnB0z/XbFiBUpKSuLxZ+y02Dp6BwiCILo6WtU01BI+vrR4W3DCmye0+3Z//NWPSLInRfScwYMH41//+hcA4P7778f48ePx4IMPyr9/6aWXUFRUhJ07d2LIkCEYN24cli9fjuOOOw7Lly/HH//4R9x3331obGxEXV0ddu/ejRkzZsT1fXU2yBkhCIKIEU1nxEE5Iz2ViRMnyt//8ssv+Oabb5CSkiJ/DRs2DACwZ88eAMCMGTOwfPlyiKKIlStX4oILLsDw4cOxatUqrFixAoWFhRg8eHCHvJf2gpwRgiCIGOHOiFPDGaEwTXxItCXix1/92CHbjZTk5GT5+8bGRpx99tl46KGHQh5XUFAAgOWZvPTSS/jll19gt9sxbNgwlJSUYPny5aipqen2rghAYoQgCCJm+PwZu02Q75NLe8kZiQuCIEQcLukMTJgwAe+//z769esHm037ksvzRhYtWiQLj5KSEvzzn/9ETU0Nbr/99vbc5Q6BwjQEQRAxIreDtyozaShMQwDAvHnzUF1djcsvvxw//fQT9uzZgy+++AJXX321XEGTmZmJMWPG4I033pATVadPn45169Zh586dPcIZITFCEAQRI8GD8gAgwUZhGgIoLCzEd999B5/Ph1mzZmH06NG49dZbkZGRAYtFuQTPmDEDPp9PFiNZWVkYMWIE8vPzMXTo0A7a+/aDwjQEQRAxopXAymfTcNeE6BmoS3I5gwcPxgcffGD4vMceewyPPfZYwH0bNmyI3451csgZIQiCiBGtdvAJdvY9lfYSRHhIjBAEQcSIljPitPE+I+SMEEQ4SIwQBEHEiEejHTx3RlxeckYIIhwkRgiCIGLEZZAzQmEagggPiRGCIIgY0WoHrzgjFKaJlmjmwhDtTzz+TyRGCIIgYoTnjDjVzoiNnJFosdvtAIDm5uYO3hPCDPz/xP9v0RBRae+CBQvwwQcfYPv27UhMTMSUKVPw0EMPha2Bfvfdd3H33Xdj//79GDx4MB566CGcccYZUe80QRBEZ0LLGXHK1TTkjESK1WpFRkYGKioqAABJSUkQBCHMs4j2RhRFNDc3o6KiAhkZGbCqmv5FSkRiZMWKFZg3bx6OP/54eL1e3HXXXZg1axa2bt0a0Itfzffff4/LL78cCxYswFlnnYU333wT5513HtatW4dRo0ZFveMEQRCdAb9fhNfPbGrtahpyRqIhPz8fAGRBQnReMjIy5P9XtAhiDMGeyspK5ObmYsWKFZg+fbrmYy699FI0NTXhk08+ke878cQTMW7cODz77LOmtlNfX4/09HTU1dUhLS0t2t0lCIKIO60eH4bdvQQAsPm+2UhxsjXe7opGzFy4AumJdvxy76yO3MUujc/ng8fj6ejdIHSw2+2GjojZ63dMHVjr6uoAsLa1eqxevRq33XZbwH2zZ8/GRx99FMumCYIgOgV8SB4Q1A6emp7FBavVGpP9T3QNohYjfr8ft956K6ZOnWoYbikrK0NeXl7AfXl5eSgrK9N9jsvlgsvlkn+ur6+PdjcJgiDaFI+qWiawA6vSDl4URcp5IAgDoq6mmTdvHjZv3oy33nornvsDgCXKpqeny19FRUVx3wZBEEQ8cKuG5KkFh7qyhsp7CcKYqMTITTfdhE8++QTffPMN+vTpY/jY/Px8lJeXB9xXXl5umOwyf/581NXVyV8HDx6MZjcJgiDaHLkVvDXwdMqdEYBCNQQRjojEiCiKuOmmm/Dhhx/i66+/Rv/+/cM+Z/LkyVi2bFnAfUuXLsXkyZN1n+N0OpGWlhbwRRAE0RmRy3ptgadTu9UCq4U5JeSMEIQxEeWMzJs3D2+++SYWL16M1NRUOe8jPT0diYmJAIC5c+eid+/eWLBgAQDglltuwYwZM/Doo4/izDPPxFtvvYW1a9fiueeei/NbIQiCaH/4XBqbJXRtl2CzoMntI2eEIMIQkTPyzDPPoK6uDiUlJSgoKJC/3n77bfkxpaWlOHr0qPzzlClT8Oabb+K5557D2LFj8d577+Gjjz6iHiMEQXQLvPKQvNAEVWU+DTkjBGFERM6ImZYky5cvD7nv4osvxsUXXxzJpgiCILoEXj8TGjYNMcKTWMkZIQhjaDYNQRBEDPDuq5phGprcSxCmIDFCEAQRAzyB1WbRcEZUvUYIgtCHxAhBEEQM8JwRm1XLGaEwDUGYgcQIQRBEDPjkMI1Bzgg5IwRhCIkRgiCIGJDDNIbVNOSMEIQRJEYIgiBigCew2jX7jEg5IyRGCMIQEiMEQRAxwMWIVSNMw3NGKIGVIIwhMUIQBBEDXgrTEETMkBghCIKIAaUDa+jpVGl6Rs4IQRhBYoQgCCIGjMM05IwQhBlIjBAEQcQAbwevNZuGmp4RhDlIjBAEQcSA4dReanpGEKYgMUIQBBEDPr9+O3he2ktNzwjCGBIjBEEQMSA7I5phGnJGCMIMJEYIgiBiwHA2jY0SWAnCDCRGCIIgYsAwTEMJrARhChIjBEEQMeDxh09gpXbwBGEMiRGCIIgY4B1YtUp7lT4j5IwQhBEkRgiCIGKAJ7BqNT2TO7B6yRkhCCNIjBAEQcSAz2+QwEodWAnCFCRGCIIgYkDuwEpTewkiakiMEARBxIAcptHqM0KlvQRhChIjBEEQMcDDNHaNahql6Zkfoii2634RRFeCxAhBEEQMeKRqGq0OrDxnBKBQDUEYQWKEIAgiBsx0YAVIjBCEESRGCIIgYsArNz0LdUbsVgH8bmp8RhD6kBghCIKIAa9BO3hBEKjxGUGYgMQIQRBEDPAwjV0jTANQ4zOCMAOJEYIgiBjgzohWB1aAGp8RhBlIjBAEQcSA4owYixFKYCViYX1pDY5/4Cu8u/ZgR+9Km0BihCAIIgaMpvYCqjANOSNEDLz+QykqG1z483sbUd3k7ujdiTskRgiCIGKAT+3V6sAK0OReIj6oE6SfXbGnA/ekbSAxQhAEEQNGHVgBckaI+FDdrLghP+6r7sA9aRtIjBAEQcSAUQdWgBJYifhQ1eiSv69uchk8smtCYoQgCCIGjJqeATS5l4gPxxoVZ6S6kXJGCIIgCBVG7eABckaI+KB2RprcPrS4u9fxRGKEIAgiBow6sAJKzgg5I0S0NLu9aA4SH8e6WaiGxAhBEEQMKM4I5YwQbQMP0STYLchPSwCAblfeS2KEIAgiBrxh+oyQGCFipVIK0fRKdqJXigNAYA5Jd8DW0TtAEATRleF9RnQ7sFKYhogRLjyyU51IT7QDCMwh6Q6QGCEIgogB3oFVbzaNk5wRIka48MhOdshipLuFaUiMEARBxIDc9Czc1F7qwEpEyTEuRlKcSE1gl+1jJEYIgiAIABBFURYj+n1GyBkhYqNKCtP0SnEgNYHCNARBEIQKj1RJA4RPYKWcESJaGl1eAEBaoh1ZySyBtbuFaaiahiAIIkq4KwIYlfbSbBoiNlqkYyfRbkV2N62mITFCEAQRJR6/4nboihGbFKYhZ4SIkla3Ikaykp0AyBkhCIIgJLyqMI3u1F4+m4acESJKuDOS4LDKCawNrZ6O3KW4Q2KEIAgiSniPEUEALJTASrQRshixWZDqZGKk0eWFKIpGT+tSkBghCIKIEt59Vc8VAZQwDSWwEtHCh+IlOqxIkZwRv6iIlO4AiRGCIIgoCTeXBqAEViJ2WlUJrIl2q9xgr6HV25G7FVdIjBAEQUQJT2DV674KqMM05IwQ0cGPnQS7FYIgIMXJ80ZIjBAEQfR4wnVfBVQdWL2+bhXjJ9oPubTXwYRtiipvpLtAYoQgCCJKPFICq173VUCZTSOKgNtH7ggROeo+IwDkippGckYIgiAIOWfEMEyjnGYpiZWIFJ9fhNurhGkAtTPSfcp7SYwQBEFECa+msRmEaRxWCwRJq1ASKxEp6mOGOyMpCZQzQhAEQUjwPiNG1TSCIMh5Iy5KYiUiRF2+y48jPiyPxAhBEAShOCMGYRqAGp8R0cN7jCTYLXJjPUpgJQiCIGQUMWJ8KpXn05AzQkSIyxuYvAqoElh7shj59ttvcfbZZ6OwsBCCIOCjjz4yfPzy5cshCELIV1lZWbT7TBAE0SngYRq7QZgGUJJY+YWFIMzS4mbHmFqMUJ8RAE1NTRg7diyeeuqpiJ63Y8cOHD16VP7Kzc2NdNMEQRCdCo9UTWPU9AygxmdE9KiH5HG6Y5jGFukT5syZgzlz5kS8odzcXGRkZET8PIIgiM6K188TWI3XdXLjM8oZISJEGZIXGqbpTpN72y1nZNy4cSgoKMBpp52G7777zvCxLpcL9fX1AV8EQRCdDaUDq7EzwhuftVKYhogQ9ZA8DjU9i4KCggI8++yzeP/99/H++++jqKgIJSUlWLdune5zFixYgPT0dPmrqKiorXeTIAgiYpQwTZgEVkmMUGkvESmtntAE1hQnK+3t0WGaSBk6dCiGDh0q/zxlyhTs2bMHixYtwmuvvab5nPnz5+O2226Tf66vrydBQhBEp0NOYA2XM6KaT0MQkSCHadRipBs2PWtzMaLFpEmTsGrVKt3fO51OOJ3OdtwjgiCIyFE6sFICK9E2aIVpumMCa4f0GdmwYQMKCgo6YtMEQRBxQ+7AGiZMQwmsRLS0yn1GlGMsTdVnpLtMgo7YGWlsbMTu3bvln/ft24cNGzYgKysLffv2xfz583H48GG8+uqrAIDHHnsM/fv3x8iRI9Ha2ooXXngBX3/9Nb788sv4vQuCIIgOIFJnxEVihIiQVndomCZZckZ8fhGtHn+Aa9JViViMrF27FieffLL8M8/tuOqqq/Dyyy/j6NGjKC0tlX/vdrtx++234/Dhw0hKSsKYMWPw1VdfBbwGQRBEV8R0B1a56RmFaYjIaNFIYFV/3+T29kwxUlJSYmgLvfzyywE/33HHHbjjjjsi3jGCIIjOjvkOrDSbhogOrQRWi0VAssOKJrcPTS4vslO6fo4lzaYhCIKIEurASrQ1cjv4IPcjSQrVNLm6h8AlMdKGiKIor5wIguh+KE3PTCawUmkvESFafUYApaKmyd09KmpIjLQRPr+IOY+vxJlPrCJrliC6KR7eDj6MM+KkMA0RJVo5IwCQ7GQ/d5fyXhIjbcSR2hZsL2vAjvIGLNlME4oJojvi5WGacDkjNkpgJaKDC1inPfByneRgzkgzhWkIIw7Xtsjfv/VTqcEjCYLoqshhGpPt4MM5IwermwPOHQThlgQsD/Vx5DANOSOEEYdqlBPKD3urcYROMATR7fDwpmfhBuXJTc/0nZGGVg9mLlyBkoe/gYtySwgJt3SMOWzBzggTuJQzQhhyuCZQfBw41txBe0IQRFvBwzThckbMOCObD9fD5fXD4xOxdn9N/HaS6NJwZ8Rh1UlgJWeEMOJQTaD4qGx0ddCeEATRVsgJrGGqaeQOrAY5I9vL6uXvv91VGYe9I7oD/JgJdkaS5fk03cNFIzHSRgTHfSvqWztoTwiCaCt8frPOiJTAauCMbDuqEiM7q+Kwd0R3wK0nRqQwTTOFaQgjeM7ImD7pAIDKBnJGCKK7EXGYxsAZ2Xa0QfV9PY6Rm0pA5YxY9ZwREiOEDj6/KCesji/KAEBihCC6I0oCa2xTe70+P3aUNwTcd6iGkt4JwO3VKe11UmkvEYaKhlZ4/SJsFgEje6dL95EYIYjuhtKB1XwCq9Zsr/3HmuD2+pHssMpuKp0zCEBVTWMNLu2lahoiDMca3QCA7BQnCtITADCBQhBE98Lj57NpwiSw2tiFwy8qk37VcOFRmJGI3FQ6ZxAKen1Gkh0UpiHCwA+OZKdVdWKhVQ5BdDfMTu1VW+xaoZr6FnbOSEu0IzeNTWCtqKdzRk/H6/ODa1e9ahoK0xC68LrvFKcNuansxFLb7KFGRgTRzfDK1TTmckYA7cZn9a0eAEBqgnLOIGeEcKsGreqX9pIzQujAD44khw0ZSXY51lclhW8IgugecGfEGqaaRhAEwyTWhlbJGUmwK24qOSM9HpdKuIZU01BpLxGOZjc72SQ7bRAEATl8pUO9RgiiW+E1mcAKqBufaYVpmDOSlqh2RkiM9HS4M2IRQiu2kuUOrN3DcScx0gYoYRp28smWTi7kjBBE90LuMxKmtBdQGp8ZhWnSElQ5IxSm6fHoNTwDFDHi9vnlx3VlSIy0AUoCKztYMhLtAIDaZhIjBNGd8PJ28GHCNEA4Z0SVwCqFaaoa3XLpMNEzccmVNNaQ3/EwDdA9QjUkRtqApiAxki6JkTrJiiUIontgtgMroJT3hnNGslMcEATWw6S6iRYwPRkjZ8Rmtch5SN0hiZXESBvQxHNGpDrwjCQmRupJjBBEt8LsoDxAKe/VTmBVqmlsVgt6JTsAAOWUZ9aj0Wt4xpHLe91dP2+ExEgb0KTqMwIozkgtiRGC6Fb44uWMqMI0AGuYCABVNJ+mR6PX8IzDrzHkjBCaUJiGIHoGvAOrzUQ1DXdGNHNG5DANO2dkJjFnhM4ZPRujMA2guO/dofEZiZE2IDiBNY3ECEF0S5QOrGaqaYycEV7ay84VPLRL54yeDReuumKkGzU+IzHSBvD4HS/tVapp6MRCEN0JpQOrCWdEp+mZ3y+iwaU0PQMUMULnjJ6N7IyEyRlpIjFCaCE7I47AMA0lsBJE90KpponAGQkK0zS5veCDfFMT+DmDhWlIjPRs5ARW3TBN9+nCSmKkDQjJGSHLlSC6JXKfEVMdWLWbntVLreAdNossWGRnpIVKe3syrrAJrDxMQzkjhAa8Pa/S9ExJRhNFamJEEN0FbwQJrLyaJjiBVc4XkUI0gBLarSNnpEcTPoGVnBFCB1EU0eTWLu31+kW5BwlBEF0bn1+UwyuRhGlcwc6Iai4NhzsjNdS1uUejiJHQDqwAJbASBrR4fPIJKkU6UBLsFjkBiUI1BNE98KjGu5sq7dVJYK1vDUxeBVQ5I3S+6NGYbXpGCaxECFyhCgKQKK2EBEFQynvJdiWIboF6bow9kgTWIDHS6GLnBL54AVSlvXS+6NGYDdN0B8edxEickfNFHDYIgrJaooQ0guhe8EoaALCaGpTHm54Fhmla3OznRNXgM+V8QXlmPRmeXxQugZWcESKE4FbwHCrvJYjuBZ9LAwB2Ux1YtZ0RnnyYpBYjUpjG5xe7RT4AER1hnREndWAldGgK6jHCoZbwBNG94GEaq0UIcEH10OvA2iJZ7GoxkmC3yBcg6jXSczHb9Kw7CFYSI3FGqaQhMUIQ3RmewGomRAOoEliDSnubJack0a6cMwRBUMp76ZzRY+EJrHphGt7lu4lKe4lg5PivPTBMwzsrNrR2/YOGIAglZ8RuUoyEc0YSHYGnY2oJT7jChGmSHDxnhMI0RBA8HswndHJ42R6JEYLoHijdV82dRhNs2lN7lTBNoJuaIZf3UtJ7TyVczkgKJbASenALNkHHGaEEVoLoHkQyJA/Qb3qmhGmCkt7JGenxhBMjPM+oxeMLKDXvipAYiTPcgg0VI1I1DTkjBNEtkIfkmaikARS3NLiapkWK96tLewFyUwlVmCZMAivQ9VvCkxiJM/xEkxCkZHmr54ZWWuUQRHeAJ7CaaQUPKLNpQsSIJ7SaBlDOGfV0zuixhHNGnDaL7Mw1d/HGZyRG4ozLoxemIWeEILoTvgiG5AGqBNagpmf8IhIcpuHOCIV2ey7hqmkEQZBFbFcv7yUxEmf4iSYhKIFVqaahEwtBdAc8vkhzRtg5wecX4VXNtdFLYOUjJGgB03MJ54wA3SeJlcRInGnVcUYo/ksQ3QteTWM3W02jOieo3ZFmndJeSnonuBhx6kztBYAkZ/co7yUxEmf0xYjijNCsCYLo+nhVHVjNoE5CVOeNtGg0PQNUYRpyU3ss8tReA2eku8yn6dFi5GB1M7YcqYvrh51X0wTH+HjOiF/sHhMWCaKno1TTmDuNWiyCHKppUZ0DtNrBA+qk9659kSGiJ1w7eEA9ubdrHyc9WozMe3MdznxiFdbur47ba+o5Iwl2izxMi/JGCKLrw/M+zHZgBZS8EB6aEUVRc1AeQAmsRPgOrIDaGenai9weLUZ4qR1v4R4PlATWwBOLIAhKRU1L11awBEGomp6ZrKYBlIoZLkBcXj94r6oEh86kb1q89Fh4t15KYO3m6DUhigXFGQn901JFDUF0H+R28Cb7jACqjpmSM6IO1yTpJL23evwhLeSJnoGZME0ShWm6Pkrdf/w+6HKfEY3sZ6qoIYjugyfCDqyAcuHgYRqevOqwWkJyT1ISlIRWOmf0PERRDNtnBCBnpFuQqDNFMxb02sEDqlI9ckYIossjJ7BG5IxIOSOSCFHKekPPF1aLgFQnlff2VLx+Ebzw0rC0l0/u7eKFET1ajCS0RZjGGz5MQ02MCKLr45PDNFE4I9IqtkWn+yqHGp/1XNyqXjTGCaxSmIacka6LHKZpk5wRozANrXIIoqvDKx3sBheKYBKDwjR6lTQcyjPruZgVIxSm6QaYFSOiKGJ/VZOpZmVKmEbLGaFqGoLoLnAxkqjxWddDPfJdfasVpgHU5b10zuhp8HwRq0UwbKxHHVi7AXyyrlHOiN8v4qb/rUfJI8vx4frDYV+TCxutGB+tcgii+2Dkguqh9BkxG6ahPLOeiplKGgBIcVI1TZfHacIZeWbFHny68SgA4LNNRw1fTxRFebWkGaZJpGoaguguRCNGQsM0Zp0REiM9DTM9RgBVAiuFabouiTojvdV8saVM/n7b0QbD13OpXsc4gZVOLATR1ZFDshHkjPBeItwR4VU1ejkjadT4rMdipvsqoM4ZoTBNl8VMzkhpdbP8/eHaFlQ0tOo+Vv062gmsNGuCILoLckg2kjCNM7AMs1WeS2PTfHyaPLmXzhk9DbNhGhqU1w0IV9pb1+JBbTNbkfTJTAQAbCit1X09vlKyWgTNseJUTUMQ3Qe90Q9GKB1Y2YWDx/l1wzTkjPRYuBhxhkmQVg/K68oT4SMWI99++y3OPvtsFBYWQhAEfPTRR2Gfs3z5ckyYMAFOpxODBg3Cyy+/HMWuxp9wzshByRXJTnHgpEHZAID1B2t1X0+OIevYalRNQxDdB6PRD3oEd2Dlq1lutQdDXZt7Lryaxqwz4hfj28CzvYlYjDQ1NWHs2LF46qmnTD1+3759OPPMM3HyySdjw4YNuPXWW3Hdddfhiy++iHhn443ijGj/A7kY6ZOZhGH5qQCAfZVNuq+nNDyjngEE0d1pNRj9oIcyKI89t1GK8yfrhGnkPDNKYO1xyM5ImJwRdSVWV66o0f4EGDBnzhzMmTPH9OOfffZZ9O/fH48++igAYPjw4Vi1ahUWLVqE2bNnR7r5uMJPIrrOSA0TI32zktA7MwkAcKSuRff1jFrBA4rl2uT2wevzh8yiIAii6+AK83nXgueGtAQ5I7yLZjAUpum5uE0msFosApIdVjS5fWhyeZGd4myP3Ys7bX41XL16NWbOnBlw3+zZs7F69Wrd57hcLtTX1wd8tQV8ZLfeoDyevNo3KwmFGQkAgCO1RmKEJ7TphWkU7dfYxZONCKKnYzT6QQ+5tNcj5YyYDNNQaLfnIYdpTFRrJXeDipo2FyNlZWXIy8sLuC8vLw/19fVoadG+sC9YsADp6enyV1FRUZvsm+KMaIdpSqvZ/hVlJaJPBnNGqhrduk5KONvWbrXIJy6KARNE1ya6pmd8Ng0P03BnREeMUNOzHgt33sLljAAqMdKFwzSdMk4wf/581NXVyV8HDx5sk+3IOSM60w4PSc5IUWYS0hJtctaynjti1AqeI6906ORCEF0aM5/3YJLlDqxSmMYdJkwjnS+a3T54fF03OZGIHFdEzgg7frqy497mYiQ/Px/l5eUB95WXlyMtLQ2JiYmaz3E6nUhLSwv4agvkahqdME1lowsAkJuWAEEQUJjB9vdIrXavEVeYBFZAnZDWdQ8agiCMRz/okaiaTeP3i7JDEi6BFSA3taeh5IyEP77kMQMUptFn8uTJWLZsWcB9S5cuxeTJk9t602HhosHjE+HzB9Znu71++cOflewAAJUY0XNGzIgR6jVCEN2B1jBD7rRQd1pt9frChmlsVovsyFJFTc/CbDUN0D0m90YsRhobG7FhwwZs2LABACvd3bBhA0pLSwGwEMvcuXPlx//2t7/F3r17cccdd2D79u14+umn8c477+CPf/xjfN5BDKjt1eA8kJpmNwDAIgAZUkY7FyOHYwnT0HwagugWRNP0TF2G2SxVPwD6CawAnTN6KmaraQDl+GnoSWJk7dq1GD9+PMaPHw8AuO222zB+/Hjcc889AICjR4/KwgQA+vfvj08//RRLly7F2LFj8eijj+KFF17o8LJeIDDRNFiMHGtkYiQzyQGLNL65d5iKGjN9B2g+DUF0PVo9Pny0/jCWbGbDMn1+Ub5YRDKbxmIR5MVKs8snt4XXc0YAyjPrqbh90qA8Ewms3aGHVcR9RkpKSgxbzmp1Vy0pKcH69esj3VSbY7EIcNgscHv9aNFxRniIBlCFaXR6jXBnxGhWBc2nIYiuhdfnxxlPrMReqeHh8j+VIDdN6eUQiTMCsPh+q8ct56QBxs4INT7rmUQUpukG15VOWU3TnvBVTXB577GmUDGSl8ackfJ6F7Qw03eA5tMQRNficG2LLEQAYPORuoDzReRihD2+Uhq6aRHMhXbJGelZmJ3aC3SP6wqJEZ35NNXSqqVXiiJGclPZaqiiXruaxlwCK1XTEERXIjhHbGdZg/xZt1sFWKUwrlnSJXFxqIa9brLTBkHQfw2a3NszMTu1F1CHabruMUJiRBIOrqDy3moNZyQ3lTkj9a1ezcZncgKrYc6IpGBdXVfBEkRP4mhQKf92lRiJZC4Nh59TZDGiU9bLIWekZxJJAiuJkW6A3rA8OUyTpIiRtESbfGBUNoSGalwmpnjyjopd+aAhiJ4ET1jvLeWM7ShvMJUfpkdGEhcjrKmiXsMzjtISnsRITyKSpmepTr7I7brXlR4vRhJ1wjRaCayCICBPSlyraAgN1YSb2gsoBw2dWAiia3Ckjn3WTx6WA4DNrKqVzg+RdF/lZCUFhmmMklcBWsD0VJQE1vCCtztU0/R4McJXNsHVNLy0NytoAiIP1VRoJLGa6TPSHew0guhJcGdkdO90ZKc4IIrApsN1ACJPXgWAzOAwTTgx0hNKe7d8CLx/PfDp7YBHOyevpxFRn5FucF2JuLS3u6EksAaGaXjOSC+VMwKoklg1wjRmEliV+G/XPWgIorMgiiJe/n4/KhpcuGP2UMNE0Gg5KpXyF6QnYkB2Cqoaq7GzvBFAdM5IphSmCdd9lSOfM7prAut3jwNL71F+LhgLTJir//geQiRihKppugFKaW/4BFZALUY0wjQmZlVQ0zOCiB//+mIH7vt4K55ZvgfrD9a2yTb4LKrCjEQUSI0P91ZJYiSKBNbMoHNKuDBNtz5nlG0KFCIAsP2zjtmXTobbF3k1TavH32UHKvZ4McJXJepph36/KOeMhDgjabGGaZiCdXv9IRU8BEGYp7bZjWdX7JF/XnegJu7bqG/1yOeGwowEufHhvirWdySqMI2UM8Lp0Qms3zzIbkecB/zue/b93m8Ad5PuU3oK/PoQyWwaoOuGanq8GClIZ+LicI3SS6C2xQM+Ny94FZNjFKYxlcBqA3eSu+pBQxCdgdLqZqibQa/dH38xwst60xPtSHLYUCidL2qbmTCITowEnlPMl/Z2s/NF+RZgx2eAYAFO/n9A7gggoxjwtgJ7vunovetwIgnT2KwWuZleYxc9Tnq8GCnKSgIAHJTK7AAlRJOaYIM9yCIzyhlxecIPzrJYBKQ4qL0zQcTKoZrAZmRrD9QYjqqIhtogh5Q7I5yoqmmCFjhcbOjBm541urzwdlELXpP1r7PboWcAOUMAQQAGnszuO7Ku4/arkxCJGAG6fjiPxEimJEaqQ8VIcIgGUFfT6OeMhDtBaVbUHFwDfHAj8O5vgNVPAR7t+TcEQTC4mzlrRB7sVgFVjS6Uqj7H8YCHaPhntiA9WIxE6Iwsfwg5PzwQcNfIwjTDp/DQrnp/ujxeN/DLW+x7dbJq7gh2W7G9/fepg6hscOG1Hw6E5C1G0oEVUE3u7aLOSI+vpinKYieXQzUtEEURgiCguom5HsErGADygKxjTW54fP4A58RsV8a0RDuO1LUqB82R9cCr5wIe6US65UMmTi55Jab3RhDdGd40bGBuCsrqW7HxUB22Ha1Hca/kuG2DX/x56WTvWJyRwz8Dyx+EHUAOhqMSGQCA8X0zDZ/msFmQaLeixeNDQ6tXbprWpdm9FGipBlILgIGnKvfnDGO3FVs7Zr/aGZ9fxHlPfYfDtS1odftw/fQB8u94AqvT5DGW2sUranq8M1KYkQiLwIYS8SmaypA8Z8jjs5IcsEmzKKoaA0M1rd7wYRogyE5zNwPvzGVCJG80cMpfWQx160dA6Y8xvTeC6M7wME2fzET0lcKtwaGbWOF5GnzVmZZok2PzQITVNKuflr9NEhRnNT1MmIZvFwDquktod9sn7HbEeYBVtSbOHc5ua/azc2M357XV++XZR4t/ORzwO1eEzkhX72HV48WI3WqRrdeD1eygqG7UD9NYLAKyU/jAPEWMeHx++KSs1/BhGpWCXfkIUFsKpBcBV38KTP8zMP4K9sCVj8Twzgiie8NP4n0yk9Ans23ESKMsRthnVhAEWFS9TIYVGIdYlBeqZI6nRALYOSbYadEjbOOzpmPAsn8ARzea25+OxOcFdi5h3w87I/B3yTlAYhYAEaja2e671t58uF4RILvKGwNCNZHmjIT0Gjm2B2iujtOetj09XowAQO9MHqphSlx2RlK07dDctNAkVvVBFM4Z4QlplmO7gO+eYHee/k8gIZ19f8Lv2O2+lYA3NFGWIHo6oijKwqN3RiL6BH2G40WjNNCSrzoBJYkdAM4f39vcC+1cAojKOaI4jQmaX53Q19TTDRuf1R8BXjyNLV7evw7wd/KWAQd/ZCGahAyg75TA3wmC4o5Udv+8EfVEaJfXj/WltQBYewk5TGPSfUtVJTpj30rg38cDT4wHDneNZGASIwhNYtXrMcLRanym7uAari6cOSMiTtj2IOD3AINnA8POVG1gOJCcC3hbWO5IV8LnYSsfgmhD6lu8cj5Hn0xFjHB3M15wZ0QtRu4+ewRKhubgmz+VwGox2fGVOwESfz9zEB44fxRuVOUIGBEQ2q05AOz4HNj/HbDuVeDZaUC11G+lagewdbG5fYqGY3uAr++PzYHZ9SW7HTI7METDkfNGtkW/jS6Ay+tDleTCTx/C5h6t3lMFAGj2+OSydfWxZwR/nKuxBvjwRiZ+W2uBNy7qEiGvHp/ACkCONx84xv5hvJomuB8AJ0djPo3SfdUStiV1aoIN51hWo2/dWsCWAMx5CFA/RxCAASXApneAvcuB/tOieVvtj6sReP4UtlKbMBc48bdAhrmVH0FEAl9R9kp2IMFuVYVpmuVE9HjAp6Cqm0qdPDQXJw/NNf8inlZgz9cBd+UnAr8eU2z6JbgFn3Xgc+Czu9giJuAFR7Ocs1/eZNV4oy4wv39m2bUU+N9lgN8L/PgfYO5ioPeEyF9nr9RDRJ24qiZ7MLut3hvdfnYRyqQBjE6bBSVDcvDtzkrsqmCdfXmoxWYRTDU9A5Tco+MPvAjUHwZS8gCfG2g+xgTgyPPi/ybiCDkjAPrnsOz7/cdY1z9lSJ62GMnTCNO4TDQ84/Syu/BXu1RjP+1PQFb/0AcNKGG3e5aFfb1Ow8pH2crM3QD88BTwxISAODlBxIvaFmnBILmX3BlpcvvkhmSoLQWeO5l98Z4WESLnjJhcnWpSupolqKcWAn0msfs8ka1U0xJtGCqU4pRNdzIhkjUQ6DUIyB0JnPZ34NqlwKlSW/Uj64CW2uj3V49vHmBCBABc9cAHNwCR9nVpqlJcFX6OCyZLcouq90W1m+2OKDLhFGF4jI8Z6J2RiOJegQti9XFnVlinJ9pRJJRj8rH32R3nPq2UTW/5IKJ96whIjAAYkM3ECG/xbNRnBFB6jVRqhGnMlPqNq1yMXKEW5bbewNQ/aD9o0ExAsLKy38o4JnLVHQL2fRv5SSQcjRXA6n+z72fcCRRPZSfN964FSn+I77a6C55WYMldwE8vUGgrQnjFAM+/SrBb5e7Ih2paWELny2eyC/ORdcDieWw1HyGNGs5IxBxay26LJwN2KWHVG9lk2rQEO/5iewsW+IAhpwM3/QTc/DPw+++Bqbew100rAHoNBkQ/cOD76PdXi8Pr2LnI6gBuXgc4UoFju4D9KyN7nb3LAYhA3iggNU/7MVyM1OyL/3kq3rgaWW+oJ8az8FUEyAMYMxJkMcK6CouyI2c2RAMAaQlW/NP2AuzwAANOBgbPBEZKDtnOL9m+dmJIjADoJ4mRqkY36lo8ukPyOFpdWM1M7AUA+LwYfuBNAMBHyRcBttDyYQDsgzp4Fvt+Q3SruhBWPgo8PhZ45Ww2qtsfx26Oe75mlmD+aKDkTuCqj4GhZ7K45ca347ed7sSGN5iD9OntwAfXd/TedCl492J199KAJNbvn2DOSFIvYPTF7AGf/wUoj6x/RYNGzkjEHP6Z3fY+ThEjETY1HOLajFOsG+CDFZj9IGDROc/wkO6+b6PcWR3WvshuR5wH9BoIjJH+pmtfiux1eIhGzxUBWGhXsADuRqCpMtI9bV8++h1rwwAw9y0C8XSkVpkGzcOMjS4vqpvc8nHHq7jMMLL0TUy1bkErnMCZj7I7C8YycedtCclb6myQGAFb9XCBsflwnZzF3EujzwigqqYJyBmRnJFwmc+7vkBSy1EcE1PxuTDd+LG8xHfD/1hiaCzUHQa+Vtmsa18E1r8a22uq4THxQaexnBeLFRj/a3bf/lXx2053YtvHyvdbF7OulIQp6mVnRDlZ81btVZVlzG0CgHP+DVzwPGs5DhFY81xE21E6sJq/KAQgisBhyRnpc1zUzshxh18DAHyXejoTA3r0k8RIpI6FES01wCbJ+j/+WnY78TfsdvtnzOEzgygCe5az73nbdy1sTiCtD/u+M+eNbH4f2PZ/ys9NFcDRX0w//YiUM1KYnoAEuxX50hDWA9XNmonThuxbiYEbHgIAPG2bqxwjgqC4I5s7d6iGxIhEf8kd+V7KZk52WJHo0BYWPExT1eiCX+otYrYVPHZ8DgD4yHcSqlxhHjtkNqu7b6pgyWOx8PN/mUvRbxpQche7b+O7sb0mRxSVwVYDT1Hu7zsZgMD6BTSUx2db3YXm6sALhuhjtjRhCu6MaJXc5h74hK2qc0eykIYgAJPnsQdtfJtdXE3S0BpjmKa2lK3uLXYgfwxgi8IZqdqFPhXL4RcFvJ9wnvFj+09nrkL55vhdyH95i62sc0cCRSew+/LHsHOTzwUc3WDudY7tBuoPsVBPcElvMDyPrrOKkX0rgY9+z76ffgcw7Cz2/Y7PTL/EUe6MSCK6Lw/VHGuWE1hTzRx3taXAu1dBEH34yDcF//XMDPw9T2bevRRorTO9f+0NiRGJAVIS68e/HAUADDdoZpSd4oAgAF6/iGqpDJhP7HUahWlEUXYQlvvHoq45jNthtQNjL2PfR5mAB4D1Kvn5Zfb98dcpr1n6PWvGFCvlW5hgsicBRZOU+5OygPxR7PsD5I4EsHMJc6lyRwKF49l9bdHkKVZHrZMi54yowjQ8ZySvRnIiRp0PWKRTXPFUNvfE0wxseNP0dnifkajFCA/R5I8C7AnsC4jMGZH2d5l/PHZ48o0fm5ythEDisdjw+xQ36fhrlKo/QQD6nsi+L11t7rX4gqXvZMCRZPzYzpzEenAN8Oal7H84ZA4w4w7JeQOw+yvTL3NUckb45PhiVVVn8BgCQz76PdB8DN7c0bjTcz0aXD65AScAdtxnD2FhdGkx3BkhMSLBnRE+aGtU73Tdx9qsFjm5tVwamNdqYmIvKrcD9Ych2hKwxj8MDS5v4EGjxTgpVLNzCdBQZuathLJ1MVudpRayfiaZxUDBOJbotv2T6F5TDQ/R9DspNAem+CR2G++EumhpKOscSXEb32G3I85lJwog/mJkw5vA/XkszNfN4J1I1WEa5liK6NcoVWuoV9+CAEy6gX2/5nlT+VIen1/+XEedM1K+hd3mj2G3sjMSQTWNdAH52DfZXDv40Zew203vxH6sb/s/5k4kZgJjLgv8Xd/J7NZsgjo/TxiFaDiyGNlj7rXbGp+HudPfPQG8eh7gaWJJohe/zBaNXJiVbTIdbq2Ucg7zpPCMXFFT3SSHIcMed0d/YQ6rxQbxktdYvgiCJsJ3kVANiRGJicWBw6pGG4gRQNVrRDqglCF5Bn9S6cMoFk+FC0zM1Ic7ueQOYx960Qes/a/xY/VY8zy7Pe4a9sEBgOFns9sIlLwuezVCNJw+x7HbIxti304siCJLFH10KLBqUftss+4ws1CDS/7qjwL7VrDvx1yi9FWo2hXf7X/1N3bcfPTbLtUW2gxKAqtyss5JdaJYKEeGv5qFAnpPDHzSmEsAZzoLh63+N/DxLcB/zwQW3wS8dw37WXXxblJNyE2O1hnhjbvyRrJb7oyYzbOo3gtUboMoWLHcP1YpWzZi+FlM9BzbHXsl23ePs9tJNwLOlMDfyc7ID+HFnc+j5I4NMCFG5M9EJ2gJX72PVcu8cRGw9G5JiJQAl72h/D+zBrCOsj43ULEl7EuKoqgIasndK+LzlapbQsYQ6MJdqxHnwp7dX56bFCJaeahmz9cRhSnbExIjEhP6ZqJQsssAYHQfYzHC49OV9UFixMgZkbqpWvpPk23fWjMrnUlSpcXalyJPcjywGji0hsWsJ16l3M+t3P2rYquq8bQorofWSaZgHLst39xx5aueVtaRkCc1tnWpcdUu4OkpwKIRwGOjgcfGBLoTG99irlTRiSw23hbOiNcVKED4RaUzUHeIneBjaFuuVLmowjQpTkyySC3ECycoFwqOIxmYdB37fundLHR5YBWw/jWWjPjzy0CjktvEt5FotwZM546ISkmM8K6i3BnxmswZ2cEqIHxFk1GPFLR4fCGj5kNwpgKjL2Lf82M+Go5sUMp5uaukJn8MC8221rL+QkYcWsv6DyX1UlwiI3KGstuqXR3f3v67x4C6gyxHZvAsYObfgF+/z44njiAo4VYT7dddXj88PiZ8ufvBq8EO17ZojiEIwetWnA7p/8Mbn4WIkZyhLCTs97Ck404IiREJQRAwsV+W/PPAnBSDR4e2hHfJE3sN/qRHpIO0cIL+QaPF8HPYqO2mCqWMzAyiCCy7j30//gogRdU1smAs4EhhJ5LyzeZfM5jS1Sx2mlqonEDUZA1gPQm8reFPWG3FJ38MLC/mFQ1txed/YasjwcpO5PWHmDux5UOgtR74/kn2uAlXsltZjOyKXwjp8M+BXTo7y1iBPV8zcfbEOFZmvvalqPofKGEaVQJrmhNjBWbr+/pM0nweSu4CxlzKvu99HHDes2zVz1HNgmqIteGZu1nJecgdwW7l0l6TzojkJliHzJJbz4d1UwGWGwawEG20eWHrpGq74WcDyb1Cf2+1K85nuLwR7p72n6Hk8RiRUQxYney8UXvA/D7HG1cDsOk99v1F/wV+/S5w0h+129jzbrRHwosRfvwKApDiYK/Fq8HK6ltlB8xQjBz+mYX7krLlxGLD6wofSsj/F50MEiMqbj9tCFITbDh/fO+wMyeCh+WFdUaaqphlDwCF42RrzpQYsdpZiAWIrHHT7q/YScKWwJKsgl+T26yxlN6qq2i0OgVaLECBtBLqiFBN3WFFiPCM97ZM6jz8M+uaK1hZY6o7Dyqryg9/C7x9BWvP3GuQEoPn8XFXffzCKfx/yl87UiHYGFmZoilaaoGP5ikD4+oOMqH42Chg5xcRvVSwxQ2w8Q1DLGwKamO6hjAG2EXk/P8A834CrvkCGHc5cMa/AKeUsO5X3Du5rDfaEE3VDgAiu1iksNkjSgKrCWdEFJmrCUDoe6J8oakxE6opHMfaw/s9SkgwErxu5SLMu3hqYTZvRM4X0QjlamGxKiI9nk0fI2XLh6wyq9cglhNnRKEkRg79HPZl1VVaFulak5uaAJtFgM8vYk9lo/x7XXg1Xr+T5HOv4XWl/wx22xZNL+MAiREV/bKTsfavM7HwkrFhH5sbNJ8mrBg5sp7d9hoMJKQjQzpoaptNhl0m/oatsg+vNXWww+8Hlv2dfT/peiCtMPQxvCfBrsguBAHIYsQgDsxDNcEXtz3fsCmjvENlW7D2JXbxKz5JGUboa8NJyCsXstsxl7Baf3sCm8g87Cy2yuMXhln3K6srm5NdsACg4Uh89uPQT+x24m8ACEwANVWZe271XuCZKcBzJSwhL16sf529v6yBwB37WPOurAEshv3mpRGFz/j0WnUCq1UAhloOAQAqEjRGLHAEAcgZEri65U3EAsSIVEkTrTPC80X4FFpAlcBqwhmp2a+UBReMjfycwRugRZM8fngt4KpjoYl+Bv2QzFTUNFYon/FBOvNotOBOa0dO790rfV5HX6y92FLTdzJbhFRuYwMFAXbRb6wIeWiDRp8cq0VAvpQqsKeSdQM37G/DG9upZpcZOiNFk9jCtLEcqOwgl9oAEiNBOG1WU7MAgsM0jS4mRpJ0epPIcUQprpgujwQ3uUpPyVUyoteo3JH6o6zV9f/9IdCO3fgWULaRhUim/lH7NUecy3oS7F3OMsUbyiNTzI0VQLl0sTLqqMjtS/VJ0edl+73pXeCFU1m74rZgk1S1Mul6JuaAACveFGWb5Ni9IeVbpOokATjpNuV+ixW45FXg5L+ymPPVS4ChcwKfy8VifZzEyLHd7LZwApBRxL43cwLy+4H/Xc4ugqIfWP9GfPYHUOYsHX8dK/uePA/4/Q+SYyUCPzxt6mVEUZT7MKjDNGiqRDoa4RcFHLb1jmzfLNJJX+Wa8c90siNKMcIvojxfBFAlsJpwRnhorWAsYE9AepIkRsyeM4qlaqJoxIh8oZtuHFbpczy7ANeWslwgLXZ+AUBkixKtRZEe/O/WkUms/H/ARZcRyb2AAZL7wGfBfHgj8MhgNmFZhdxHJEjo8lANR9cZ8bqUfVOJRfm60qpxjNicyvuIxi1rY0iMREluWmA1TR0f3KUz6Vd2BYLEiKnseM4Jkt2/+QMmBOoOsRXs+teBda8AT5/ATjyVO4DPpLDM9Nu1470AS54cJSW6vXER8OgQ4KlJ5lXz3uXstmAs62+gx4ASAAITLvxiu+MzNlmS88NT5rYZCQ3lUmhMYCsyLkYiCdO4GoCXzwL+d2n4k/pKqQXzyPPYyluNxQrM+DOLORdPDn1uPMWIz6OEBLMGKCd1MyvMym2Bj9v0bnzCWupEZ7VVb3MCJfPZ99s/NVW+3uT2gVfEq8M0fL9LxVyUt0R4auNVZipnpNUdZoERDr46zlYdC5EksEohGp4PwJ2RsP2JODyEUrkt8vCfWowY4UxVEjf1KvN4bwvei8Ms/DPEB+u1N/VHgLpStmALrszSgy8YN77L3CAeIg7qiMudvWAx0idIjOjmjFTuYA5vQoZSeYQwzgighJL4YqUTQWIkStTzaURRRE0T++dnJOnYarzcS2oCxh9nKmeE03siS7rze9iF76u/AS3V7GKTN4pZ8f+dwwSKu4FVa0zRGcTHmf5nwJ7MPnCCha1CXpwFlJlIauVx4HClesnZyod55xfMfeGrYP7h3fdt/Lu08jbcuSPYSZP3QIkkTLP2JZbkCwA/Pqv/uKpdSmb7tD9FvKtILWC3DUcjf24wtaXsompLZK8bSbXOPumk2X86s+ibq+Iz58Qo0Tl/FLvg+r2mGpJxN9FhtQSOV69gYmSX2Efu4WAajTBNs5t9nxC1GJFO+L0GKPdFUtrLFzCSs5ghLXT4xOKwJGcD2dLf2mxjMoAl3vJVdzgxAgBDT2e3Wg21mqsVRyzYDQxH8VTmupRvUoRde8L/Bnkj2fnDDMPPYufTqh3M8eUkBFZnKs5I4PUi2BnRFSNyCHBEQPgorONul5rN+Trf6AkSI1HCuz26vX7Ut3hl6zRDyxlxNbL4LyBn1UeUwKqGryJ/fJatWiGwhLxrlwKjLmS/83uZG3HJK/oDteQ3MgS4fRtLtPzTLma7ttYCb1xsLA70WsDrMWQ2u932MfviibWz7mdCRfSzZLF4wvMm+khCyBpqxRvi8wKrVY7Ntk9YQqwWqxYBENnqj3edjYQ0KaxQr/P6kcArOLL6M4s9EmeEC4+BpygJb/FIZOUiRy/Redyv2K2JY0BJXg0ar17JxUjvgCGWptAI07RIDc+Swg2/1MLvU1qZ9xqk3M8vBuGcEb9fGeqXPxpAlG4qd+EiCdUc3cAWPKmFQKZB7g1nqJSLtXc54G4K/N3615gIzRstvw/TqLvJ/vgsOzaiGYvRVBWdu8fFiF5llhaJmdJ5N2hRqhK5gP4Axt6ZJsM0FdKxoc5HgoljJNJzYDtCYiRKEuxWnJG4GedaVkmlWExpZiRqOCM87JGcK4cz5IMmUjEyeCZwvGrC69RbWOa8Iwm46CXgz3uAeWuAKz8CUsO0jpbfTDpraJSczcII2UNYouHPBk3WKrYBjWVs9W0mnjr8bAACWyW9I5W0TrkZSO+tVJWsWsgqLuIFT5rrczy7tUrOiNmckfJNLNnLmc5OSKKPhRKCcTcprshJOvk54UiTnJH6ODgjvGslr6SREwHDhN/8PqVtf7/prOEeEJ8EQr7tAp3k8OHnABYby3MKswrW6jECQHZ+dvsLI3dGNMI0LZIzojejypC6Q2z1aXUA6UXK/TaTzkjtftZcy+pkCb9Q3NSIzhnFU9ltJGKEJy0XjguftAmwC2JGMRMdb18JfHADC1O01AJrpD4nJ9xg7rWC4f1S1jwHvPsbFk7mJcfhaKkB3rgEeHggm64bKXzmDi9fNsvg04Brv2B5YnxidNDFXy9npE+wGNEN00ifySAxkil1Bq/RS3KWQ9XkjHQftnyEp8UH8bjjaVSVHZCVqGbOCA/R5I2Q74oqTMM5/Z/AJa8BN68DTrsv8HfJ2eziE80HH2DKnidfbn5fP6FVbgE/NbQFvBa5w1mzIE7eaGDqrez7iVexKqPGcuCbB6Lb72D8PqWCqbd0Mon0g8hP4H1PVCpx+PtWs/srttLNKFaET6TEM0zDV+RcjPAwTcNR40FZFVvZ7x2pTDTkSCc6bgnHAg8RZQ/S/n1SlrIKDtOoS+6+GnyilkTMXjEKMWKRXsuvdkZYzkhUYoSHaLIGBLqT8tTeMM4IbyOfO0yu+ok4ZwRQ8kaO/mK+n0uZlKNh1skQBODUe9jfcM8ylifxwXXAQ8Us5yI5R7koR8rws5mbnJCuhJw+/ZO5ct8VDyuVgpvejaxEWBQVUWamSVswvSeyAgHuhAU1btOaOg0Ak/tnYVxRBgAmVJx6U+BlZ2REwN2ZSWadERIj3YMfngHev1b+sbzsqHziStfKGeF2a+5I+a6Iq2nUWG3AiHOMR4nHwrAz2IqsaqdyUgwm0r4BAHNxzn4cOOdJ4IZvlPbSNifr9QCw6o0ommCFULmd9QdwpCjOgC1KMVI8RXmf+1eGdsHd9jG7HX529CIwnmEa7izw4yMxQxE7Ridk7iT1nsCOMb7qqtoZWxdMn0eZSKxO5gyG99L54WngxdnA1v/TfBjv/xHQot3VKJdF7xPzUdkYpRhRdQmWxUg0YRr5fxAkvmRnxKQYyVNCfhHnjACskiq9L3P1eEJsOOSLcARhldEXAdd8CZw4D5h8E5AoNZBMzGRua7SNBp2pwO9XA3eWssqrASUs54sP/tTD5wU2vxd4XyRJ8jX7Wd8fq0O7maNZZJGrF6ZRXS8qtsG2aCjen7ARD54/Go9fNk77NV0NSoJ6sDMiHSPVTeGcEQrTdH12LQWW3BlwcJVWsEx1q0UIXa0BmvG9qOK/7UVCOrMaAeVCq8bTatwCXg9BYH0vJsxVFDpnwMlsFelpYsO5tBBFFibh+TdGqC+sfGUaSZjG7wcOSOV4xVPZRSE5hwkc9Und51Eado04N/zr6sHDNK11oXH3SOEXfnW8X05iNQjV8AmzPNk4s198umDW7GefF3sSy0PQY9iZSpjr4A/AO3NZnk4QzXKVi+qzJrlBvoQs1CEFFfUssdw0GmEavp0AMdJSqywujJCTV4MWDLIz0mpcRs+7IucpC5iMcKtePXiJL++ZYYTPozhhkeZ49JkInP4gMPsB4PYdwJUfAjeuVKptYsViUbrlbn7PeLzEvuXMaU3MAq6QQqhbF5tvXcAFWe7w0HNVJGg4boBOmOa9a4GmSli/uBO/OqEvThmWp/2afEGRksccRRXqY0Tz+Ndxhxcu3Ym//d8WHDgW47knBkiMRILfr7RXP/461CYWAwCOSGIkI9Gu3aOEn5hUCjsjMYpVTnvCnYBSjVjzwR+YzZySH6LMo0YQlCRGvYqKbx8B3voVm5oZbkYPT17trYr3RpK8VbmdxZztSSx2brEowksdqjm0lq2gErMCtxUpzjSWhQ/Eljfi9wO1B9n3mcXK/WaSWLkY4TFydRfMihjyRniIpteg8K3AT70XuOpjafKsyAbYBSUtNsnOiEok8M+YFAZq8fjQ5I7AzdG4aPBGhgGlvc+eBDwzOfz8ES1BCCjOCMAEiR78762y4WVnJFIxMmgmuzXT5bZqJ7tQOdNY2DFabA52DskoCv/YSBg0k33WGsuNe2X8IpXUjrpQqcppqTEfBo00VKWHhsgFdBJYTQzYA6AcWzwMqyJLyhlx+/yymNbcnyAx8sG6Q3j5+/36jko7QGIkEvYsY4rZkcpmXDhYPLC8mk1B1AzRuJsV6z1LWSVlJrPHtnr8aInkpNle8KTUQz+HrkDUIZpowxJa8JkhB74L7YtwcA3wzf3s+5p9rOTWCPnCqsrhiKS0l7siRZOUDzAXaGoxwuc8DCgxN3NDD0FQeo3E0oW1qZK9P8GihH4ApWeDXpjG1aCsiNU9FeQk1hjyRvg0YqMQDUcQWDnpec+wZmg+F/Du1QFuUYtW/w8pLGLNHixXIESUNyKHaZQLPT+ZB3RVrpOE3u5lxq9XIzlJmf0C71eHK/RCNT6vZlgrQ24HH+EFY/BMpTMor7TSg7s+eSPj+9mOFzaHMoFWPW9KjatRaj4IYOxlrJyah8vMuFqAKlQVvhu3IXLJeHDOCM97isJ14S6lhlhMtFvhkMrdNYWFTpiGC3zD9vNtDImRSOBNvkZdACT3gtXJxEgCDBqe8ZNKQnqApZbitMFuZR/2iE8u7UHOcFZF4mlSuqxy+InYqAV8NGT0ZSt40a/8rTlbFwf+/NW9wLrXtHMZWuuVC6s6E15tUYaza+V8kanKffz9HtkANB1j3/P9NOpAa5Z4VNTwi2VqQaC9HM4ZObIBgAik9QmswuLPi8kZ4WJksPHj1FhtwMUvszCRuyGglX2TVpjmmLSNXgPlsvuoxIjqeGoJ3o46fMZnzWghikpMPzPogmG1K9vSc0ZqD6jCWgXy3Vkp7PhtdpuY3KsmMVMJ1ewM00lYTjQ2IRw7Cl59t+1j7fyy7Z+wAXJZAxVhzYsHzLoPalEWCxoiF9BwRtSLL9X/XBNZ6IaKEUEQjJNYdcI0TbzbMImRLgJvHCRdoOxOZqsngJ30NMt6eSJb1sCAlQY7aMIkG3UkFgtzBYDAmSE1+1k8W7Aq9m884a8ZvPLkOSDnPMl6eXhbgf+7CXiwEFg0KrAc9OCPAES2KlVPKraqxKJRqEYUA5NXOan5UhKyyGLSLbXKfsVDmMUjiVVeNfUNvJ9XItSWMrcuGN4grs/EwPt5GC6W8l6e46NhKxtitSthDXX/D6nkNtAZ4Tkag5CTEjiqwfS2AJ1qGuk0ycNfgJJ/pEVjBQtjChYm7oKR59PoOCNyJc7AALct1WmDTRqqFvE5g8+hCjeh+1gELlZH0ec4Kb+sOTS/TBSBn15k34+5VDnnclGhl5CvxtXAqoCA2MPQFr0wTVDTM/UMqHA5KrU6rpsEv65oLnL5a6vC3G6vH24f66lDYqQr4G5Smj9JIQxHAnNGEgWpx4iWM8J7PmhUvvD4XqdMYgWUUI1aGGz/jN0WTwlJnooLshj5SnEvvG6lTLfvFODS11kpYWIWEyV1B4Gv/6G8Bm/cFTxlM0CMGJzMq/eyHipWR2gbaC46tv4fmz8h+piLFHzxj4Z4lPfyC6a6twXASr4TswCIygVHjZzwG/R+1fNB1C5UQznL53h2mnG5MGBoK4dFI8at6YyoBE9OWjTOiEbTs+AwDXc7AOPSXP5+UwuVCi414ebT6CS/CoIg95GIWIzwyrVwydvRuFjtjSAAY6X8siV3ss6vXGDv/IIlmNsSA6cN80pGM2Ea3hMnJT/2c5xGNQ2brRTkjPAcFSB8D5oa48+TsRgJdUZ4iAYAkqPtNhwHerYYEUVm6Zvh8M/sgErrLV94LI7gME0YZyQInvlc3RnDNIBSHbLna6UbK4/FDjurbbZZPIXZ041lyiqubBPLHUjMZCdoixWYdjtw2zYmTABgy0fKqme/qnGXGnU/FCMxwp2gwgmhJYljJYt4+ydS11UoibexEo/5NDxME5w4KAiq5mcaeSM8ITM4CTezH3MnvK3KBX/Lh2wO0ub32Un0yAb9/fF5FKcnGsGmcfIMyRlprWejEAAgo1h2RiITI6Ht4Fs8QaKnTi1GDF7bwEYHoJpPo3PRUbk8wfSKVozwY98oadbvVyUCd2IxAgBTbmIjBFrrgP9dBiwaCbx/vdLc7IQblLAnoIRpKreHL1PX6W4aFRrHlcvrh1cariQ3NVOPajAq+/b7lM+4zvHF8xFrDHNGlN/xUvkEuwU2a8dJgp4tRr57DPjPNKVJlBHq6Y3c+pMa2iRKYkRz3LPcElrfGdE8aDoD2YNZAqjoY9NvD//MEjsFi9IELN7YnMo8DD54i5fS9jk+MKnOnsB6eww/B4AozZGpVzon9lPlewDsxCBIh7yRGJFDFhrVMfmj2X74vWylLFiVxNtYiYcY4at3rQu/3kj2+iMsaVawsMohNRarcmGq3M4Smt+9mlUmcPwGzl7dIZYDZHWyUsRI0aiAagoO03AnIqkXkJAm54xE1BJeswNrUGmv2hkxumCEc4JMOyOhYsRw1WsED3cZiai6g0ysWB2xVdK0B/ZE4PK3gAlXsQViSzU7R7VUsxBTcCfkJGlYqN8Tvs+QPPclDmLEoGQcUE2EPqa6Bhm5bvWH2WtZ7Lq5JcoxojW5NzSBtbETJK8CPVmMuJuAn19hq70XZ7NufUZ2M1euqiZE/KSSIIVp0hI1/pnB3TBVdOqcEc7Yy9ntl39lrZUBdvGNd8memuC8EX6r13Z+4lXsdsuH7Ev0s793uka83kyvkeA28sGcqGotPfUWIDWKi6wWbRmmAVQhl6BeI/z95o4AHMkaz5NOyuVbgc9uByACI85jI+EB4/wbWRwVRVdtpLGSC+kzwitEpDLa3KgSWLVm0wQ5MAFhGgOHoTaMM2IP54zoNEyDksQauTPCxYjBfvMQTdbA8DOtOgNJWcA5TwC3bAQufoVNIB93BZvTlZgZ+Fj1rJhwpf3xFCMaYRo+gNFhs8Aq5QDJ4Xz+WL19rFHlhOn8j6IN03RkvggAdOzWOxJHMnDNEuD1C1k44Jv7WULUzHu1H8/jiOrELumkcuHoLOzxF+K8cb0Dn+N1KRcWjZVGVrg5Ap2Bcb9ifT8Or2UTXC02YMYdbbtNLkZKV7MLAK9YGXa29uP7l7CGZE2VwMfSlGJ1vFiNzcFWHnqrI3ezEu7Rm0kx6kIpOTafzdaJF9wZaSxn5Z1W1cfT72d2tLeVzR3Su7DLYRoNZ4Qfu8EzaniyLk9YDqZgDFt1fvcYa/rmTAPm/At472r2eyNhJ4uRKFfammJEckZ4nxEePpIS+qJyRoIuGqIoymJEyRlRJbAaOSNhYvqGCayeVlUrgNAhdVnRLmBsJkR4UK+WLoPVBow8j33pYVF/lgyapQGBE3FjRaOaJiTM6G4KXYB4WrQTWY0+3xI8/K/pjBiEacgZ6UhS84Frv1Q6BOp19hRF7V4JUpimTwrwxOXj5eQyGW632xLkAXlquoQzYk8EfvUOMOg0Np3zyo8ir4qIlKz+LOHM7wX+9ytmrWYPVXplBGO1Bc6+cKQAE6/WeWyYlvBHf2FhqZT8wD4dwfSeGF8hAjBBZbExZ6cxaGLynmVszsa+FUBThfbzXQ1MLADaFi53Rqr3Bl4I90sTdXnFRTDjr2Cl6fy1S+5kbpCZJnJ61T1m0diG7IzYtcVIbipzASojqqYJFCMur1/On07UdEYMLupyjoyOe2g3cCn4NhypSmhBRdQJrGackTBVGl0atYtgJEaaq1m+GhBbG3h5u6El4yHHL3f2EjIASE6JntjlU8MNzj1KYYRBNY067NkJynqBni5GAOaQnDiPfd9Uqf2Y+sOs34bFFrhaCTeBs+4Qu03vo9lAqEs4IwCQ3Au44j3g8jeB/joXrHgzWfqf8B4nw8MkzJ7yV+C4a1kFQ8l8No9Fi3BhGp5v0nti+zd9sliZCAJCV0prnlO+19v3Bukk6khVqifUpBUygeX3Km5I0zElUVhPjCRmAtP+xL7PGQZMuoF9b2bwoF6/DbNoOSPBJ89gMSJV0xxrcsMrlSyGJShMo47rJ9qt7H71+UEvri+KSp8YvX4RsjOiUWKtDvFoHH+xJ7CacLHS41AZ1tkQBM1QXAg8nyq9L5uLEyuaYZqgAYzqiks+WE/v+KqXrilaJeMSXLAea4wsTEPOSGeANzDSEyM8XyRrQKB1xg8crZMKEChGNJDHPTd10tLejmT0xYozkT0UOCHMCHBHMnDWQuD2bSzTXo9wq3nugMVjVRQN/FhRu3S1BwNboutd/LkYUTctUyMISmky7yJ7QKo8yh1h3Mhr8k3ABS+wOR/8b2hGjNTE6oxI2/CrnRF28pRP5kFiJCvJAZtFYIam1glZi6CLBg/RyHH9pkoAqkZ5eguQ1jq2cAGUsFswdoNFTNB7CSZ6ZyRMngpgKgTQpdEZWhdAPCtpArapzkXiCdg8eVVVcRkuudmEM5KdzISnYQdWv0dunaA5eLIDIDECAMlSY6xGHfubl0IGNwIKe+AYi5GsaDPjewI2B3DF+8BZjwE3LDe+UEb0umFawlfrJw+2C7w5E+9pA0iNnVQXQr0LSjgxAgADT2W3PCl4y4fsllcw6WGxAGMuDjwJmgnTyJ+B+Idpkh02lksTVOposQjIjrTxmTXwohES1+d/W47u/0ByRRIz9SfVGq1+uRjRyTfpFa2bGokz0pbJ6R2JzpyYAOKZvKqzzVBnRFXkIC9w9ZwRKfSvJ3QB9JKSnI81aQyLVC+mpc+UkjPSsUnLPTeBVQ3v0tlSzf5BwYlDcovkoNr7cJYa70ugVdkAVZ+RJjdEUdQesteTyR0ev5MCR2dQlAwvsdMoxW4XCsawW3UTpOBW+HpDAhtNiJEBJayEt3Iba9y2VepgOf7KyPc1nDPi9ykX52jza4K24Vb1aEh0WFn+jM/N3pNqInBumhNl9a2oqDeZxCpb+JIzElzWG7xQ0RMjPF/EKN/IKLwbzhmJOoE1TM6Iq0Ep19Y5X3V5dFqzByAPKIyXMxI6m6Y5WOiqxbQtzALXRJiGh/89PhH1Ld7AmWnBjR9tDqWaxkHOSMeTmMX6RQABMzBk9NpZ2w2y4gHVqlD7w80PGpdXZ8IiEX/knBGNk7mnVTkxdJQzki+JkaMbpfyDI1J7eyhTfWNxRpKylGZ271zJknUHlAD5o/Sfo0c4YddQxl7fYouux4jGNniIBpBO5rzCJbUwoPpIaQlvVoxoh2kUMRLkjOheLMLkiwCq0l6N1whTFqzkmXng94eZr6QmnDPC/44JGUBCmvnX7UqEC9OIYtuFaYyqaeTQSx/jY8PVqLSfMBD3CXYrUqWQS1VT0P9bows1hWk6ExaLUu2ilTeil2VulIgGhA3TJDmscBpNWCTij1GYpmYfAJENCNSoZGgXckdI486r2Sp7m9TxtugEJXlaL8TExUiKgRgBgDMXKgLZngyc/Nfo9lVnAqgMdwlSC6LvW2HVTix1WC2wWy2KeAz6jPEkVvNhmsDZNCF5KbwDcZJ0ntC7qJuw0XWdEVHUn/YrwcWIzy+iriWCXDO1M6I1JFKvc293QmP+UADN1exzB8RvNo/GbBo5TGO3sf+F+jphtMDlnydnetjkWjlUE5wzpdH4kTsjcmv6DoLECCeZJ7EG2bF+v36vBPnA0TjhBR9kGgiCEtuubIygJwIRPUZ5DuqZIB0VMrMnKCW4R39RBoENP0e5+OuFacw4IwBzR65ZAlzyKnDbVqBIp7lbOLjLpOeM8OPfKGQRdhuBYZoQkcC3EXQRzZHKeyN2RqQwTWuIMyKJEe5Y6IVmG0yIETnXLGgR01IDuKTxFDpJpA6bBenSQM6qSM4ZXISLfm1nINZ+MF0BLoh9Os4Id8BTC/XzfSLeZqgbEzDosaVGOZbSepsTI0bHlkQv6bpyTOsYCfpMNVJpbyeDi5HGIGek4agUk7aGnlSNDpyWGuVkY3AyzpYaNFVF0qCJiB6j0t5jqhK7joSLg28fYe33AWDEOeHj/jw/I5wYAZhAHnGufgm0GWRhp+cShM/8N78NLkZ48mpQvD3YGeGNz0znjOiEaRxBYoRfrPWqaUw5IzqVLVxYJecYXgyzpVVvRB1m+bGjtV1AVdbbjZ0RnQm6MjW8k2+/OG4zdDZNQM4IP36Tc5lgNGqIZ6KShsMTnasM59OwBVln6cBKYoTDk1iDnRG5aVNRYEdMwDi+x1epiVnKSkiDHOnEYroEkYgNozwHORwX2vmyXZnyB3ZxPLKOrWQLx7OVsi1Mwii/YBrlK8STcGEadSw8TtvgDZpCnBEdMWK68VlImEbPGenHbnXDNFwQGjkjOhccM8mvUDrMRuSmqodEau17rInGXYFwYRrefEyj823s21SJEbXQDRYYhs6ICaErwRe5ZpwRPuupo6tpSIxwZGckSIwYtXY2OnDM2LWAHKaJyHIlosdmEFrgAjKtnS7mevQayBq4ASzx8/SH2Peyq6NxgVV3X402WTRSwlXTmMj8j3QbvEeDvIqTZ/EEhjVy03gX1kjDNIGlvSE5I+HCNGasdL3ZNGHCupyc1AjfG8DCjkbHjxzi6+Bjvy0JV00jOyNxFCOaYRq1MxL0Pzdc4JoQuhLZETQ+a2ztwtU0Tz31FPr164eEhASccMIJWLNmje5jX375ZQiCEPCVkKDvFHQYsjMSFKYxym5XJ7AGJ4WZjN+TGGlnjC6g8oe9E5yQZz8I/Po94KafgL4nsPuMKiL4xVKv+2pbEK6aJgJb2ew2ZGfEbi5MU9mo0WtBi6C23QEXDFFUqmmMwjSeViUB0kjQ6iWwmhQjcpgm0nOG0eTeSEJ8XRWN1uwBhCmrjmmbPnWYhuc92UIFu+EC12ROGFQ5I8HVNEBI3lyXraZ5++23cdttt+Hee+/FunXrMHbsWMyePRsVFToNwwCkpaXh6NGj8teBAwdi2uk2QU5gDRIjRk2I1HHd4A94vbkPdy85TENipF0wSgI1+T9rF6w2YPBpbCYMx9DV4fveTq4IYL6aJi4JrIGORbLTJpU61rLfBwkeLvI9PlF7YFjIdgIt/IAhea21yt9cdka03AXJDbUnSXNGdNBb/UYYpqlqiLbxmUYVj5mS5K5OR4RpDNrBJ9k1nBGjPiP8+DLxP5KvK1rHSHCYpqu2g1+4cCGuv/56XH311RgxYgSeffZZJCUl4aWXXtJ9jiAIyM/Pl7/y8trxhGkWXrLXfCzwfqNSO7UYCc6MN2mpyc5IpCcWIjrkD2KQ+PN5lXwhEzZoh6B3MQHaP18EMHaZfF4l5Gkixm12G03qahp5Fk9KoGgDqzrJlJo9mSrv1ZlNk+SwKq5TQoYiMvye0BW2+oJuVI2ld8GRL0zGYiTqCjy9BGhXg9LCvjMI8bbCqM+Ip0W52LdrmCY4Z8SgA2sEYeReUkv4kD4jQMBnyu8X0STtT0pXKu11u934+eefMXPmTOUFLBbMnDkTq1ev1n1eY2MjiouLUVRUhHPPPRdbtmwx3I7L5UJ9fX3AV5vD+0o0VwfebzTJ0mpXDrbgg4fCNJ0TPXehqZIliwpWzQnLnQKjhm1c/LZXvghgXCbdVAFAZH/PpBj+nkbVNGFCC3x6r6mKmqCqh4DSXh6iSckLTAQNSUA1mWCoZ8XLFybjipacaCvw9MJ80rlKdKaxGU/dFaOcEZ575Ehhpe/x3mbAbCVVPlLwIkKe6Bx0bKjFvYkFR04qd0aMwzQ8mRboYs5IVVUVfD5fiLORl5eHsrIyzecMHToUL730EhYvXozXX38dfr8fU6ZMwaFDh3S3s2DBAqSnp8tfRUXtUG7GD0C1M+J1KScYvfp7uSV80GrDpKXGDxrqM9JO6IVp1BfzaBt0tTVGzkgE8eS4749RMnBKHmsqGC1BYZpmuUeDTTmR6zR5UxqfmfhsBVU9BIRp5ItAnpInBmhc1CMUI+r/o9+nen6YME28nRHp2N/dkoo/v/uLvHLvdhjNpqlXVX7Fs8eQvE3lb8qPrSS7SozwnEU9ZyRCcc+TnOtbvbKwVvZJcUZ4iMZqEeQGnB1Fm2998uTJmDt3LsaNG4cZM2bggw8+QE5ODv7zn//oPmf+/Pmoq6uTvw4ePNjWu6k4I55mwC2FXGoPAhBZl0q91bK8ygkO05iz1Lgz0qB10BDxRy+00BUS+Mxc/Ntz/2Vhp5UQGaf9CWl6pg6fGP/PuIMQW5jGFtjZ1mJRve8onRGtXhKN5ewiKVjD/s1yVGWbvni0hJfeX7mYgXd/PoR/fr7N/Gt2JYzCNG2VvK7ZZ0TK0RBalesGdzT1kpvVx7oJcZ+WYJPFRYgzqPrcysmrDmuHz0aLSIxkZ2fDarWivLw84P7y8nLk55s76djtdowfPx67d+/WfYzT6URaWlrAV5vjTFX+Sdwdqd3PbjOL9dWy1sHj95mO4acn2mG3stc+Ri3h2x6bTs4I/7DHkt/Q1hg1bOuQnBGDMI2ZoX1RbKPZpRYjxtuILEwTeKGSwzQOS+jqVe+CwcVIuJwju4ZDUacqCQ7jzGUlOyAIgF+McHqvjjNSdZQlbpYjEwDw6aayyObedBUsBsdrBN1NI9tmaGiIC90Ur3SdcaQq4THZGdFZ3Jr8PAmCgLw03oU46DhVfaZ4WW9Hh2iACMWIw+HAxIkTsWzZMvk+v9+PZcuWYfLkyaZew+fzYdOmTSgo6GRZ24KgyhuRDhKjHiMc+eBpUu5rrFDlH+SE2aygJBtRF9a2R68CpCOchUgxLO3tAGfHsEy6jZwRj4ZjoStGeOMzM2GaQDESMD9EFnrSduSLeozOiLeVjZsAlBJlE5VHdqsFWdL0XtMdZgHd4+fgATap2pHZBylOG6oaXdh0uM7863YVNFwKmbaqJtLo+ipXhLmloaxc5ALaQhVQCV3z+8eP/3I9Z0QVpunosl4gijDNbbfdhueffx6vvPIKtm3bht/97ndoamrC1VdfDQCYO3cu5s+fLz/+73//O7788kvs3bsX69atwxVXXIEDBw7guuuui9+7iBfBYiTMBE0AiqJ1q8RIhPkHeWn8oDHZLZKIHj13oTOV9ephNOTP7JC8eGLUZyRetnewGHGp5nqEec8RDcsLWjUHND0L3o58wdBz18K8Z3VHZn7RUecsmICveiM6Z+g4I64adqHr3acfpg9h4ehl2wLd726BUc5IWzmj3BmBCPj9cHv98EquU6JLus6ok871hq9GIe51jxHV57az9BgBgIj34NJLL0VlZSXuuecelJWVYdy4cViyZImc1FpaWgqLKqZVU1OD66+/HmVlZcjMzMTEiRPx/fffY8SIEfF7F/FCTmKVKmrMNMHRFCORHTisW2QdyskZaXv0QgudqeGZHnKsV6M0k3df7Sx9Rng5bKzVPTpTe5OctrChIJ7oaSqBVW82jVaSoVZprt+n+tybdEYA9r90JEXcIK4gPQFbj9ajLCIxoi3Ek1wsQTc9rxinpOThs01lWLGrCrfNGmr+tbsChmEa863WI0I9QsTvQYtbuTY6WiVnRP2Z1au0ikKMKDlTes6IRy6V7+iJvUAUYgQAbrrpJtx0002av1u+fHnAz4sWLcKiRYui2Uz7Izsj0kFiJkzDRzm7GpT7ImhOAwD5XMHWkTPS5ui5C12hHba8sg1OvuXdV1PCjhaPK+3RzVavmsYePmdEvTIURdE4QS+46Zk6UVY3TKP6vDZVAqKPhWbVtrvmtmzswuj3KBcdOUxj0hlJZ/twNJJzhsZ+t3p8yPRXAwLQq6AvJvViC7JtR+rh9vrh6OAKi7iiUWYr02YJrGox4kWzh/09bRYBtmapSkst2LUWtwH7Z14syTkjwYJVlQgvT+zt4FbwAM2mCUTd+EwUlSmuWQP0n+OQWm9rOSMmZ5zkSyeWiFY5RHToVYB0BWdET0jFK1k0UgwTWPkFPFZnRLuaJsXSonKDtN83/1y1evzhu7AGte2WnRHBDbRK+RP8oqFVmhtpaXjwa0QYpimQLjRldTozcrTQcEYOVTchFzVs0zlFKMpKRHqiHW6fHzvKGrRepesi5wUFVS36PPFp0KdFkBhp0eoxohav8uK2MfB1onBGcnWdESVM06VzRro16pyRukOAu4GtYIxGystKVnXwRJhMqCQakRhpc7Tq+NUzRbpCzohOaWa75osASv5NsDMSYYMm421oh2nSvdL/y8ANSrBb5dL5I7VhLtrBYRouejzSdqxOpcurVjVNpBeL4FBPhGEaZQETSQJrqDNy5OhhOAX2noXUAgiCgDF92PvceLjW/Gt3BfTCNA1lAET2+1ga9BltEwB83sDSdK0+OerriXqmUoRuO2CUM6K4jUo1Tcf3ViIxokYtRiq3s+97DVJOiFrwoWRqJRthZjY/sZAYaQe0bFDuLFidQGJm+++TWfSSbzuqEkivtX5TJeLSfTVgG9wZkWLcHl6JYOy89M5gn63D4cSIKkzj9fnh9rEql0SXKq7Pwzxa1TSRVjOpqya8LmUUgckwTUE6c1ZidUaqjpYCABqsGXLZuyxGDnazihq9PiNqVzSWBn2a27QAEOTttqirwWQxog7TSNcT0aeIRk8r0FIj7WMEzoheYYTqM9WZElhJjKjhCaxNx4AKqfFPTpgkLjlMo3ZGIss/UBQsJbC2OUZhtdT8+HZfjDe2cCGmThKmCQhZxHiKCZlNI9ncLmmgZZjPWGEGu2ibdkZ8ygUDABL4dgIuGBruWsTOiKpqgodobImmW5Hnp7MLTaw5I01VLFel2am0IBjdOwMA8MuhWvOv3RWw6uSMtPXnRyWClJJx1cwjdZhG3Y6fn6OiXCzlqbqwBnTVpTBNF4D3BKk/rDgjucONn6MpRiKz1LgYqWvxUBfWtsYorNaZG54BysUkJGckKMGyvdBLYI1XvggQIHi8PlYaCQCJWpUIGvSOVIyoVq+CANhbtMSIdAwFJK1HmHPEnRFPa+CAPJNiOF9yRhpavfIFJSwa4wTctexc5UtW3t9oyRnZXdEIl7cbnY/kME3Q34uHFMMlHkeLynVr4d1X7VAKJdTHlsWqhJL58RXlYikt0cbCQQCOqh00dZ8Rvj8kRjoZ+aPZbc0+YN9K9n3OMOPnOINW2mpLzWQCa1qCjSllAGVUUdO2aIVpukKPEUB/UF6H5YyoxEhAfDuOycAWZRWnHurlaDHXcVZxRsJ8rlQXjFa3JHjsVghaQs8h5ahouqFmwzR8plWLMqTNZPIqwC4eqdIFxHTiu+yMKGLWIv2vLOmKEC9MT0Bagg1ev4g9FUFVHV0ZvTBNkyQ4wzSojH27PtkZybU1So0xLaGjRoLd2yg/T4IgyMd/QJgyIEwj5UaRGOlkJGUBuSPZ93UslhreGeGrJOnExC01W4IybjwMrHUvJbG2C/z/5XMp4YWuUEkD6A/K67CcEVUulfoErx6SF/M2lGQ7bjVbLQKsWmWRGmiejLVQdcpsdrPjIrCxmmo7WnlikR5D/DhsrWeLH8C4ak8Dnmt2NJzQ4mgcP8ludiG2q8SIIAgYVsBGcGw72g4T09uLoPJtmbZ2RlSdX7kYybNI+TjJOaHVV8HuLV8smVzcqtF0BlVuI4VpOjPFqrb2GX1ZAqsR8ipJstTUq+wILDUeqqHy3jaGrzoA5cPeFVrBAyZ6pHSQMwIEhmri2bNFI76dZLdCMLkN82Ea5YLQ4mLvJWBir1aSYQyNDuW273WHgGrWjh2Z/c09V0IRWs1hHikR5Iy4vX5k+li1UEJWoCszPJ+d17aXdSMxwv/HwWGaNndGlIs/F9S5Qi27T0sAOYNC/zEslnpnSsdIjU6YxkVhms5LX5UYmXxz+J4BwWEaOV8ksvyD3mZXcERs2BzKhzHEBu3kOSNaPVJcjYoQ7nRiJJ7OiFvVfdVqehuFUjVNRYPLOP9B5fK4Wtnfl3Vf1RAZ8spV+rv7PMoFTXXB+KXyF5y/+HysPrI6dHsZRexWLUYidEaKstg542C1yXOGnKfCHl/d5EauwELKiVmBJcXDJWdke3fqNaIxJwZAOzgjoQmsvVArbVPj+HUEOW8xLDaU64pqkav6TDW0cmeESns7H/2nA/ZkdpCM/3X4xweHaeRkNPPxX0BRsIdqSIy0OcF5I7IYacdW6tGgXtnyHA2e09De3VcBVp0gSKcQdUVNYzydEenEKfrQ3MoET+CQPONtZCU75CS+w0afLVU/iFa3S9qOTsVDcGMq/j+w2IFEpRrmTyv+hN21u3HD0htCt5fOxUgpcCxKMZLJ8k4O1ph0RnifFKmJW1WjCwUCc0Ys6YF/xx4VpuFl1cltLUZ8aPawi3+WX8or1MrzilPOCKAWI6pjhP8dvJTA2rlJyQV+uxK4YUVgmZUewQdOlGKkj5adRrQN6gooUVTNpTDXcKrD4KW9EJXVnbqMtiPQqqiRhMLOpmRc9txqnPzIchw4FmUipMqxaHWx1V2W3a24EmHetyAI6JvFLtoHqg0u2qpOma0uyRmxQXE8AhpTBdvoqpWrqpTZpTVdmcPFyNGNgEvKHzCagaVBkfS+Dhq9LzXOIDFS14BsSNsO6m8yJC8FggBUNbrNTT3uCsjl28FiRGN6bjxRlRTzME2GLEY0thmcM8KvKVGcnzQTuPnx62mSwzS9DnwKbH4faKyMeBvxgsSIFr0Gmk8WCr6wReuMZLATC4Vp2gG1M9Jaq0zI7CqlvYCShNjRM3WCQ0c+r3wBv+njI/hhbzX2VTXhn59vj+31AbS2svdcaJUuoPZkU25QcS9JjFQZCCJVONYlOSN5tibWfApCYD5BSGhWuxorwyiBnYdpWmul5xYo/UtMojgjJs8ZQc5I87EjsAgiPLCHVHQkOWzo34t9TrpN3ojKoZBxNysX/TavplHCNGm8g7CWmFbnjPj9EY8KUMMd96N1LfBL04L5Z8bfWg+Pj92XvvqfwHvXAFU7I95GvCAxEiv8wIHITk4xhmkO17RAVJdJEvFHHVrjCceJmcq8kM4KL+0FlPLeeOZnRENw47OmSkD0QxSs2N2s/D0/31yG9aU10b8+FDFSwCsR1F1RDegnXVQNnRFBkEM1Hjf72+ZZatnvkrMDp6+ajOlnOg0aVKUWKCEuIOIQDaDkjFQ2uAKbWunBxYirno2zr2YlxXX2HM2/47ACdtHqNqEarTAND9HYEtouzKnuYSOPGTjG7tP63KqPr+YqyXUUolos5aU6YbUI8PhEVDZKCwYnC8GJrfz/KsIS4Ty1toDESKzYkyC3+41BjBRIZXotHl/4oV5EbKidka4SogFYCICf2LgzEs/8jGgIDtNI+9Noy4IfFlwwoTfOH8/+tos3HIn89S1W1lYegMvFHIA8gbfGNvee+3Jn5FiYcIb0t3VJ1TTZcpJhUFxfdkN5UyrtmH5mgiJG3MGN4az2wITpcFV7GqQn2uVeI4fM5I1wMSL6AXcj/NI8nOYEbSE7LF9KYj3aTZJYtfqM8LBEcm7bdV9Wdffl4wySuRgxSmBVX09S843Hkuhgs1rka4t8/HPRJYmRfHsrBD7aoAPbG5AYiRVBUA6epgpl4FqEYiTBbkWONDCP8kbaGHXTKm6BdvYQDSe4C2s8e3pEQ7AzIu3PYR+78J06LA9zRrGL+bLt5dG5fpLgcUu5HNlGlQgayM5IuLwV6b24pTBNtshFT9B2gvuM6DgjiTbFGaps0YjFqy9+E+Ya75sGgiCgT1YESaz2BMVda62DtZGJKFeSdpXGMKm8d1t3qajRyhnhzkhKG4Vo1NtVt4PXGjPAUeeMxJAvwumfzV5vPw9TSmJEkMT04ETp/9vB7jCJkXjAT06VO6Sf05RVSATwzGdTqxwiejSdkS4iRoJzNDpLzghf+UsuwUEPW1VPG5KNqYOy4bBZcLC6BXsqG7VexdQ2uDPSy88tbpPOiJzo2QKf30AMSRcNj4e9l0w5yTDogsEXH34PC5fpOCNe1Qq8gjdpU5OYoXzf5zjjN6FDXylUUxrO9eEksP8LXPVwNrP99qdo/x15ee/uiga5DX+XRg7TqJ2RNq6kAUJGDSShFTav9P/S7DOisViKIl+EM0ASI3u5GJGOAYvPBTu8GODkScwd6w6TGIkH/OLG59lEeeBQeW87oRYjUfaF6TCCW3p3eM5IsBhhZa4VYiZ6JTuQlmBHstOGEwewidjLtmlclMNug+dysPec4ZfcR5N9FwozEmG3CnD7/IEzOoKRLhpuKWckw6eTZBjcOE/HGfGochM0xcgZjwADSoDfafQhMUk/6UKzzyg5V40qiTXZxfbJkqF9vuqTmYgUpw0en4i9VVGIyM6GVphGrpZqQ2dElavS7PYhWwiTgK3OaYsy7K+mv3yMSP9Dh7LNFDSjyM5zsDq2AzWJkXjAT0580m+UB06xXILYjeZBdEbUTau6mjPCbVR5oqe5GS1thqpdOwDZJagQM+SuwgAwfTCr1vhxX3XU23BJpb3pXu6MmBMjVotS3ru30uCzJV00Wvh29MSI1aaIQleDrjOiFiOVzRphmr4nAnMXA3kjTL0PLQZms3PP3ijESLqX7ZMjU/t8JQiCHKrpFnkjlqCQIhDijHh9/vgPK5XbwfvQ4vYhRw4z6rgx6grNeIiRHPZ6smC12pgQApAqtKC3RTrOOzB5FSAxEh+4ui39gd32GhzVy/STY3sUpmlT1AliXU2M8BHirbVs5eSSMuI7S58RSRyVI1OenQIAk/qzZmBr91crJYamtyGJBKkzamqEYgQABueyz+iuCoMVvrRy5lU7qbz80qjioblKGYwZ7IyoLnoVLVE4QiYYmMvOGXuM3pcaSYz4W2qR42f9NVJy++o+nIdqtnWH8l7VjBgZOWckFyt2VmLyP79GycPLowsn6m5XnTPiVbWC1/nMqkvH5Zy26EMoPEyz/1izEqaUrlmpaEEu+PHbsedAEiPxQCqVkkdC954Q1csMiNRyJaIjwAbtYgmsPM+gpVZxRUz222gTZDHCw0bazsiIgjQkO6yob/ViZ0WEq2xpJo+7hV0gkuXkP/NiZEgeO8HvNto2304rC+UkuXkzLI3t8AsG756qMRgzrDMSBwZIzsiRula5UsMQSYy01ByVL0JpefozcZTy3m7gjGjmjLD/S501A9e/uhaVDS6U1bfiihd+RF28qhpVjkyz24ccLkb0QqtyaW8DcGw3+z6zOOrNF2YkwmG1wO31KzOapLyRFLSglyRKO/ocSGIkHvQ9MfDnwvFRvQx3Ro7UtcTfKiQU+IWkZh/rfilYIu5+2WFwZ6SlJjBXoa3KEsMRUk0jOSNipjyJGmAlhhOK2b7/FGmohl/kW+uQiFbYvdKqNQJnZFAeu6juLDdY8cohjHoAIhJauejR6pLJxcguZV+C/gdqMXK06ajpfY2EzGQHMpPY/8DUIkZ6j77DG2AVRDQgEfY0fVdNKe/tDs6IRphGckZ2NSbB7fWjuFcSinsl4WhdK17/8UCctsucEb/PC5fXjxyeM6LnjPBjq/YA+5xb7EDOsKg3b7UIcuO/vUEVNalCM9I9JEa6D0NmK99bHVE1MAKAXskOpDptEEWg1GyLZyJy+If98M/sNrNf5294xgkQI9qdP9sVnjvhaWadLaWTe4WYiXyVMwIAxxWzUM0XWyIs8ZXes9VVq1jc9qSI3KDBuex/vqu8QX/b0oXa4q5HMlph9fHeCwbzQ8o2s1ve3l2FuprmcONh0/saKQOlnADDfBiO5OI6ytYDAI5YehsKWZ4zUtHgwjHeNKurIodL1DkjTHDubGLH6tg+GbjlVBZmf/n7/cZOmuntsvCQW6rSyg2XM8Irnji5w5WJ3VEyWHIGd/Iybemzk4IWOZGZEli7A9lDlO997qhXqYIgoH8OhWraHB6mEaVyxZzhHbcvkaIWI3LyageKEfX+SN1XfbDgGNKQlx4oRs4dVwi7VcCq3VVYurU84m043HXKiTxCN6h/djIsAlDf6tWftSKJEYenXhE9jlTtGVXcXTv0E7vNGRryELUzUt5UHtr4LE4MkM4Zu83kjUjvMaGxFABQ4QwVUWqSnTZ5Vf3Lodrod7IzIM+IkVxnT6s8F2hzHTtWh+Sl4KwxhchPS0BlgwszF36LJ5btinG7UjWYhx13OeFyRtJ6A5mq0FnhuNi2D8XhknN/JFGaJ9TA4ZZyRtKptLfrIwjAOGnC77Q/xfRSvEHTfhIjbUfwxUXjQtJpUV/8a1k77w61V5OkKbXN1bJTcwzp8MMS4oz0y07G9dOYa3j/p9vM966Q3nOiv0HpvhpBvgjAmgoWS5+trXohB+lCnSw2hl+9qhsdApo2ulqMiBDbLFQzuk8GAGDV7qrwDw7qf1SXFD4XYcYQVvb61pqDEe9bpyI4TMPLeq0O/FLJ3LLBealw2Cz4z5UTMXUQK0dfuHQn3vyxNIbtSv1r3Gy7eXycgd4xLAjAiHOUnwvGRr9tCTkRmef+SGJkjGUP+zkpWzm3dBAkRuLFmQuBS14DZvwlppfhNeHdZh5EZ8QZZIPGEI9tdwLEiBTT7sh8FzmhVslhKfOz+4LFCADcdMog5KQ6UVrdjDfNxuSlbWSgCXkWna6oJpjUjwmn//tFpy29dKFOQzPy+DA+PddJ3WsEYFZ6EJ6g6bCHG9omVDNrBPtb/HygBmV1rcYPDkqybUkNH1KeO5kJlq+2lXfthozBfUYkISkm52C3FOIaIuUWjS3KwBvXnYg/zmSu94OfbTPuUWNiu14vOx6UnBGDRmsjzlW+z9cWIzuqd2Bf3T5Tu8DDbbsrGuDx+eGTwjTjuBhRu/sdBImReGFPYGpWHvMeHVMHsX4M3+yohNfXDboedkbyRwd++LqqM1Kzn32f0a+j9gZIlJyRlhq5J8IRkXVczUgKnaWR5LDh1pksJv/E17vR0GqiYkF6z+lCIwbYpLLeDP1yVD0uncRCEp9uPKpdKcHFiNCMIjsvmTYZ19cI9XFnJDeRvcahxkMR77MZ8tIScJyUHLxkcxj3JcgZ8ZnIbxuUm4qpg3rBLwKv/RCnpM6OILiaRsoXcTt7weX1w2mzyP1oODefMgjj+2ag0eXF/Z9ui267XIx43LDAjywz4wwKJwCDZgK9j9N0Rpo9zbjo44twzkfnBDhwegQ0sKtsQqvA3mdvQfo8ZUfXjiKekBjpZEwszkRWsgN1LR6s2R9FgygiPFY7cPoC5edOsCowjSxGqoGaTuCMqMM0klNzWMxGfloCBJ2cjkuOK8KA7GRUN7nx/Ld7w29Des8ZaER/q2StR/GexxdlYGheKlxeP95bpyEMZGekCf2s0klar9nU4NMCf07uFfIQfpEoTmfOQlsmsc4ZzZIPP9tcZvzApMD9tJm8CF01uR8A4O2fDnbdSr/g2TSSM9JgY8fXgJwUWC2Bx6zFIuCB80ZDEJiI/eVgbdTb9Xo8yEQDbPADEIBkg66vggBc8T5w/TLNBW69W3HOzThu6gZ2mw/XoUkIClWTGCGCsVoEzBzOVlJfbokgyY+IjEEzgQtfBC5/C3AkhX98Z4Hb7LWlgKcJgABkGCchtimyM1It57AcksSIHnarBXecztyo51fuQ0V9mNCC7Iw0oQ+kHI0oxIggCJg7hQmDF1fuhSfYeZT+tmlCM4osUv5Fhk5OxYCTle9t2pVYXIz0S2P7eqihbZwRADhdGkb40/5qVDQY/D0LxwNTb8UG+zg85LkM6Rnm8gROHZ6H3hmJqG324P+imb7cGQgO00jdV2uEDABKB+xgRhSmyZOn//n59siHPapmHsmJ0cnZSkJtFKiToc2Gao6XGg+++/NBHPMGCZxOsCAjMdIJmTWCnVi+3FIW3ZRTwhyjLwKGzunovYiM4CSz1IKYy/5iIsAZYUl+h8XskEqaYGaPzMf4vhlo8fjweLhqBUkkZAqNyPdLK389kRCGCyf0QXaKE0fqWvHR+qAVpSpnJF+sMN6OIAA3rGD5Ruc8qfkQXtori5E2CtMAbMjm2KIMiCIrndbFYgFOuw/zrPfiGd85yE4xF1a2WgRcKeWOvPz9/q55XlLNiIEoymKkws9Cbn0y9cv7bzttCBxWC1bvPYZvd5lIFNbYrsfdinyBt16PLem81acIzn315sTIlScWw2YR8MPeavzftqDKK3JGCC1OGpyNRLsVR+paseUIJbISKtSTXoGOb9amDhtJYuSQmIP8NGOBJAgC5s9heRZv/XQQ243ajUvb6CNUwSG6WZM6jb4eZkiwW3H9NFY2+dhXuwJDDrIz0oRcHxc9BrkpheOAeT8CYy7W/DV3RgZlDgIAHKg/0KYX8TmSO/LZRuO8EVEUUSn1DMlOMS9kLz2uCE6bBVuP1uPnAzXR72hHYVE5EX6fXP1V6s0AABTpOCMA0CczSRZj//x8e2QjDfhnpLkaBbIYia2M1uVVytPNOiOFGYk4ZywTQZvVGQC2xKjFfTwhMdKOuHzmmgYl2K1yOd2XW8LEgImehdUeMHUzljbRcYGHafxeeRzCITE7oBW8HpP6Z+H0kfnw+UXc8d5G/YTtYDcorU9MieJzJ/dDQXoCDte24JXv9yu/kJyRPkIVkvxSaX2UITBRFGVnZGD6QFgFK5o8TShvbrvQ65lS3sgP+44pbb81aHB55bLqSMRIZrID541jF9GX1X+3rkKAGPHKYmRPC/s8GTkjADDv5EFIddqw7Wg9Pt4YQahKyg2xtVYjnyeMxtEZ2VtnIu9K4rZZLBzzk38olvvGwt9vOnP2+NyeDoTESDvxypZXcMIbJ+DHoz+aevzsUSzT+rPNFKohglC7I+rmSB2BI0npwgqgSUhCPZIDhuQZcd+5I5GWYMPGQ3V4cZXOCi+oAiRWAZbosOL2WSxn5d/f7EZ1k1t7O8k52g3PTKDuvppkT0LfNOaw7K01f+GIlKKsJJzQPwuiCHwYHIJScbiGCZWMJDsSHZFdhHjOzZLNZSgPl+vT2bCqqrv8HrkUfVsT+x8bOSMAkJXswG9LBgIAHv5iB1xek4m8yaxC0uk6hgLEJ0yjXtjuq9tn+hrRJzMJT1w+Hm7BiRWTnoHlNx/rOnvtDYmRduKRtY/AJ/pw89c3m3r8qcPzkGC3YHdFI9aV1rbtzhFdizpV86nOcCLh7giAo8gBIBgmsKrJS0vA3WeNAMCaS2l2EbXa0GxRiYI4hKbOH98bIwrS0NDqVTpsBpfrRlE+zFGXW9otdgxMZxexPXV7TL/Gkn1LcOknl+JgvflmYxdNZNU/7649qBtKOHCM9QrhTeAiYWRhOo7vlwmvX8QbsTQC6wjUzojXLTsje1vZ/713RviREFdP7YecVCcO1bSYb4SWxMRIgqdWlTMSvzBNg7sBx1qPmX7uOWML8dP/m4m/njkipn2INyRG2pkWr7nGOWkJdpw5mqnnt9Z0sQ890baMPJ/dnvTHqOcgxZUkRYwc8LETr5kwDeeiiX0wfUgOXF4/bnxtLeo1eo80CqomY3FoUme1CPh/Z7Kcldd/OMDGL9iccAmqsEWcxIjNYsOADPZ/isRS//O3f8bWY1tx56o7TT/njNEFSE2wYf+xZny9vULzMQeOsRCUXvVIOK6a0g8A8OaPpea76HYG1GKksRzweyFCQCXSkZXsQLIzfHWLuk/Ok2b75EjOSIqvVpUzEj9nBAB21uyM6Pm9UpwhZcwdDYmRdsJuCW0AFY7LpSZNH288oljJBHHGI8DcxcCp93b0njBUOR0/+5gDEIkYEQQBj1w8BgXpCdhT2YTfvLQmoCmZx+dHrk+VazH28tj3GazBYMnQHHj9Ih6SSjbrRdUFOoakPi5GBAiwClbZGYkmTLOxcqPpxyY7bfjVCUxEPafTw+VANXdGohMjs0fmIy/NiapGFz4P12StMyEIiiCR3EW3sxe8sKEoTL6IGnWfnMe/MjG3RhIjiWIL+glSDmCszkiQGNlRvSOm1+sMkBhpJ3qnKAdfVYu50rCJxZkY3TsdrR4/XtKLpxM9j+RsYEBJ1AMZ4069ksz3rm8GeiU74LBFdmrJTU3A83OPQ3qiHetKa3HWv1fi5wNsFbntaD0Oi6xZl1g0WbPBWLTMnzMcFgFYsqUML323HxBVeQADT4n6dXkreLvFDkEQMDCDiZHdtbvbPAfs6in9YbcKWLO/Gqs0ylBLYwjTAKxPzK9PYELtpe+6WJkvFyNS5VeDgwmFPpnmhZndasE9Z7MQx3+/348dZWEm+zrT5Lk4NkFykmKckKtOYAWAHTUkRogoMGupCYKAeSezssBXvt+PGnJHiM6IVHHitaegEpkRuSJqRvVOx9s3nojeGYk4WN2Ci59djYVf7sAPe4/hFvc8fJ1yNoRf/S+ee46h+am4ZipLAv7HJ1uRI6hKjPtPj/p1eQKrXUqa7J/eHzaLDfXuetOdWDOcGfL3TR7zgzPz0xNksXD/p1vhC8odOVAthWmidEYA4PJJfeG0WfDLwVrdcFCnhDvUkjNyTGDCtk+WeWcEAEqG5mL2yDz4/CLuWbzZWJAJgd1WfQmZMTda5Dkj6U6WdE3OCGGaZq8yYGpntfn43qwReRiWn4oGlxcLl0YWFySIdmHOw8D4K/DxlPcAAIUZ0YkRgI06//zWabhgfG/4RTa/5sHPtmOtOAzbJv6tTSaL/vG0ISiSLkZveiU35NynYnKeeJiGh2cdVgeGZrIKns3HNpt6jQRVldKumsjG2N9y6mCkJdiwvawhIFzj9vrlappoc0YAICfViaslEffQku2h3Ww7K04p96iCzZkpEzMAROaMcO4+awQS7Bb8uK9af/iihF/dhj819inb3BkZm8Pm1uyr24dWbxerbgqCxEg7oU5c3XJsi+nnWSwC7j17JADgjR8PYEM0sxEIoi3JGQKc+xR2uZhQMFOVYERagh0LLx2HJy8fj7QEJalwysD4hWfUJDtteOmq4+G0WfAP7xXYfsFSYPwVMb1msBgBgFHZowAAW6rMff7V54xt1ZENactMdsjVEguX7sD6Utak7FBNM/wikGi3Iic1ts69v5sxEBlJduwsb8R/VpivEupQeCXWgdXsxiP1lokgZ4TTJzMJN0nO9f2fbjNMZvUkKMeupff4iLcVDM8ZKUotQqYzEz7Rh921u2N+3Y6ExEg7oT6xbKjcENFzJw/shXPHFcIvAre+tR6NLm/4JxFEO8MbbRXGKEY4Z48txLd3nIxnr5iAF686DuP7xt8V4QzOS8WXf5yOZ66ehmFjJhk+ttHdiO8Pfw+/qO8GaImRkb3YomJT1SZT+9TsUdzUXyp/MfUcNRcf1wezR+bB4xNxzcs/YcuROrkF/qjeabqDDM2SnmTHvVLuxOPLdsmCp1PD+/K4WZ7HzhYmRoqicEYA4PrpA9CvVxIqG1x4zCCZtdWhHLvCgBlRbUsNFyNOqxOjc0YDANaUrYn5dTsSEiPtgMfvCWiCVNZUhrKmyDqr/v2cUShMT8D+Y834w//W63erJIgO4kgts4njJUYAICPJgdNHFeDU4Qbj1uNEca9klAzNDfu4e7+/Fzd+dSNe3fKq7mNkMWINdUa2HtsKn9+4YZbX7w0oD/6p7KeIE0UFQcDCS8ZhTJ901DR7cOYTq/DE12z1zPNkYuW8cb0xZ1Q+PD4RN772Mw5WN4d/UkeSFfi+N7hZYUE0zggAOG1W/O0cJjJfNkhmdflVl9p+06LaVsDrSTkjCdYETCmcAgD47vB3Mb9uR0JiJAo2VGzA0UbzJW3qWN6gDGbrReqOpCfZ8dSvJ8Bps+Dr7RW49e0NXavGn+j2HI6zMxIpu2p24bGfH4so2TMavjzwJQDg0Z8f1X0Mr6axCUqYaUD6AKTYU9DibQnrjgT3I6porkBpQ+T9hpKdNrx6zSSUDFUSKPv1SsKskfkRv5YWgiDg4YvHYkheCioaXDj/6e/xw17zDbjaHVXHYlGwYpfYBzmpTiTYo2+HXjI0Vx5rMP8D7bEGQqMqyTcttkoaQMkZcdqcOKn3SQCAdRXrAty0rgaJkQjZW7cXV35+JWa9P8v0SoWfWCyCBcfnHw+ACZpIGd83E09ePh52q4BPNh7Fr57/Qb4AEERH4vOLKJPag8eaMxItt3xzC17c/CL+9v3f2m2beucALWfEarFiWh+2Kl5WuszwddXnjIl5EwEwdyQaMpIceOmq4/HqNZNw8ymD8NSvJ8S14VWK04bXrj0Bw/JTUdXowmXP/YD7Pt6CFrfJduntiapJYGNKf7jgiNoVUXPP2SOQ6rRhXWktnvomNH/ml+Kr4RMFLM6Yq/saBxsOYvZ7s/HW9rfCbk8dpumb2hd9UvrA6/d26VANiZEIUZflHqg/YOo53BlJtCXKJ5ZoLbVZI/Px/NzjkOq0Ye2BGsx57Fss6UqNh4huSXl9K3x+EXargNwYEyOj5WADK9dcsn9Jm25H3TNIr6OqVs4IAMzsOxMA8NWBrwwXM1yMJNmSMCmf5bCYnWulhcUiYPqQHNw+ayhGFqaHf0KE5KUl4L3fTZEbNf73u/2Y9dgKfNPZyn5VYZoqJ9vXaCppginMSMR957JwzaKvdmLxhsDy7W9cQzDG9QJ+Gfg73dd4fevrONJ0BA/8+EDYhS4P0zitTgiCgKm9pwLo2qEaEiMR4vYpvT6+O2LuH89PLIm2REwtnAqbxYb99ftNj34OpmRoLj79wzSMLcpAfasXv319Hf7fh5sCx6ETRDvCk1fz0xNg6aA208l2pYlXW9rVPAQDAD8c/UHzMXKfkSAxclLvk+C0OnGo8ZBhvyG+/4m2RCUn4Mh3AblnnY0Upw0LLhiD/159PArSE3CwugVXv/wTfvvaz4ZThNsVVWl4nY+J5ki6rxpx/vje+I3UKv+Pb2/AS6uUAXY/7D2GJiTixAFZus9PcyqzkcJVT8lhGit7D1MLJTFi8prUGSExEiE1rUrG+KrDq0w9h4uRBGsCUhwp8krnm4PfRL0ffXsl4d0bJ+PGGcx2fOPHUpz95CpsL6sP80yCiD9yvkh6x4RogMAmYW1pVzd4lCRFvc+wnjOSZE+SLxxflX6luw31AmZ09mhkOjPR4G6IKrzb3pw8NBdf3TYD10/rD6tFwJItZZi5cAWe/3Zvx/cjEQR5cN3X1skAgH5RdqINfWkB95w1ApceVwS/CPz9k62Y+9Ia/HKwFnsqmyAIwKT++mJEvdBdcXCF4bb4Y3kvmkkFk2ATbDjYcBCl9V1zlhmJkQhRi5Gfyn5Cnasu7HN4w7NEOztRn1x0MoDwceNwOGwWzJ8zHK9eMwnZKU7sqmjEOU9+h4VLd5JLQrQrfBJs7zitMqOhwR1eJMSKz+8LSC5dW7Y24JzA4WLEZg0dvjazWAnV6KEWI1aLVU5S/PbQt9HvfDuS7LTh/505Ap/cfBImFmei2e3DA59tw9lPrsKeSo3JzO3J9V8Dl72JD5tYSWy/7PiIEYCFw/554Wjcc9YIOG0WrNxVhXOfYm7FsPw0ZCQ5dJ+rPn7DXRuCnZFkezLG57H+JWYXyZ2NHi9GIu1aV+uqlb93+Vx4d+e7preRaGMn6lP7ngqLYMHGyo1ynDsWpg/JwZJbp+GUYblw+/x4YtkuzFr0LZZuLe9acyOILsuWI0yUjyhIC/PItkEURTR6lIvc0v1LQ4aJxYMmr1KpMyB9AHyiT1P4qGfTBDO9z3TYBBt21+7G/rr9mttRixEAmF7EWtMvPbC0S32mhxek4d0bJ+NfF45BZpId28sacOEz38tzhzqEzGK4B83BYakUvV8MbfG1EAQB15zUH5/dMg0Ti5Ww0NQwTfvUYmRHzQ7sqdVvJKcu7eXM6MP6l7R1zlRb0aPFyOtbX8dln1xmelYEAFS3sg8Rb8P7v23/C7DXtJBPLFZ2YslJypFDNZ/t/Szi/dYiO8WJF686Dv/+1XjkpTlRWt2M619di7kvrcGu8jCDnAgiRrYcYeHBtkiONEOzt1luQpbpzESDpwHLDy6P+3aa3EyMOCwOnDngTADAp3s/DXmcXpgGYPNETig4gT13X+hzAVUCq51dKKf3no5kezIONR7Cuop1Mb6L9sViEXDJ8UX48o8zMLYoA7XNHvzq+R/x5ZbIei3Fk3h2otVjYE4K3r1xMt68/gTcdcYw3HzqYMPHq8UIoH1ccbgz4rAqTsvp/U6HAAHrK9bHZZHb3vRYMdLsacYrW1/Bnro9+PWnv8bmKnPzIrgz8qthv0JuYi4qWirw/q73DZ8TvMoBgLMGnAUA+Hjvx4adHCNBEAScNaYQy24vwe9KBsJhZTbh6Y+vxD8+2Ypmd+dNfiPih88voqHV024r6LpmDw5J805GFHaMM8JP5DaLDRcMvgAA8M6Od+K+He6+pDhScNaAsyBAwJqyNSEOhxymsYSGaQDgvEHnAQA+2PWBZlKqOoEVYKJkVvEsAMDi3Ytjfh8dQU6qE/+7/gTMHJ4Ll9eP372xLuxMl7bigDy5OCnmTrRGWCwCpgzMxg3TByI9MVSYquG5SHP6zQHAxIheczzu+qnnF+Ul58ki95M9n8S87+1NjxUjSfYkvDbnNQzJHIJjrcdw9ZKrTbkUPD6ck5SDG8bcAAD4zy//Mcze1xIjM4tnItmejAP1B+IeB05x2vCX04dh6W3TMWsEmyz54qp9mPP4SvzYmRsSETHR5PLinsWbMeEfSzH6b19i/D+W4q8fbWrzrpg8RFOUlRj2hNtW1LuZM5PmSMOlQy+F3WLHmrI1Uffm0IM3VEu2J6MwpVDuG/LezvcCHmfkjADAKX1PQaYzExXNFVh5aGXI77XOGecOOhcA8Nm+z3Co4VCM78SYj/d8jJ/Lf4776yY5bHj2iom4YEJv+PwibnlrPd5Z2/6r+P3H2P8xXsmr8YAL6rMHno0MZwaONB3RTXJWl/aq4SL3rR1vdbnBeT1WjABAfnI+Xp3zKqb2nopWXyv+svIvuPu7uw2FRY2LiZFMZyYuGHwB+qT0wbHWY3hz+5u6z5FzRuzKiSXZnoxLhl4CAHhx04ttsoot7pWM5+Yeh5elUrsDx5px6XM/4N7Fm9FE8226FTVNbpz71Hd4dfUB1LWwC2Ftswev/1CKUx9dgfs/2YpjjaE5FIdrW/Dez4cw/4NNuO6VtbjpzXVYuHQnfth7LGT0vB6bJTEyqoNCNIByIk91pKIgpQAXDr4QAPDv9f+O62eLbyfFzqa/XjKEfYbf2/VeQDK7Uc4IwOz18wafBwB4YfMLIfuoJUYm5E7ACfknwOVz4Z9r/tlmztee2j24a9Vd+M2S36CqpSrur2+zWvDIRWPxqxP6QhSBO97biNdW74/7doyQnZHs+OaLxAI/tnKTcnH5sMsBAC9tfknz/yw7I9bACdmz+s1C75TeqG6tDuvYdzZ6tBgBmCj49yn/xm/H/hYWwYKPdn+E8xafhy/3fxlyEHj9XtS72AosMyETdqsdvx/3ewDsoNGrrFGX9qq5cviVcFgc2FC5ASsPh66O4kXJ0Fx8+cfpuHxSXwDAK6sPYNaibztfQyIiKjw+P377+s/YXdGIvDQn/nv18dh832y8cd0JOGlQNtw+P15YtQ+TF3yNq15ag7s+3ITrX12LEx78ClP/+TX+9O4v+N+aUny1rRyfbDyKJ5btwmXP/YATFyzDvYs3Y82+avh1hEmL24dXV7PmfxPacJBdOBrdLHySak8FAFw3+jo4LA6sq1iH1UdWx207amcEAKb1mYahmUPR5GnCy1telh/nFbX7jKiZO2IuEqwJ2Fi5MaQCQkuMCIKAu064CzbBhhWHVphKno+G/fX75e9f2PRCm2zDYhHwwHmj5Bk5dy/egue+bb/Jv7wFwsDslHbbZjjUgvryYZcj0ZaIrce2hix0/aIfbj/LU3TaAp0Ru8WOq0deDYD979p6NEI86fFiBGBx3Xnj5uGFWS+gILkAR5uO4vYVt+OqJVfh072fyiq0zlUHEeyknO5kq8Az+p+BQRmD0OBuwL/X/1vz9bVOLAAL9fx6xK8BAA//9LB8Qm0LUhPsWHDBaLx27ST0yUzE4VrWkOjal3/Cmn3VXSpDnwjkle/348d91XJb7pOH5iLFacPUQdl4/boT8Mo1kzC2TzrcPj9W7KzEmz+WYunWcpTXu2C1CBhXlIHfzhiIB84fhb+eORznjitEWoINlQ0uvLL6AC75z2qcsGAZznvqO5z15Eqc+uhyTFmwDMfdvxTHP/AVDtW0oDA9Ab86oa/uPq46vAqnvnNqm5Wm8jBNioNdXPKS82TnccGaBbpVK5GizhkBWLt2viB5betrco8H2Rmx6ouR7MRseR8fXvtwQCI8bwfAE1g5AzIG4JYJtwAAHlrzELYdM26OFQ3quVvv7HjHsKojFgRBwN1nDce8kwcCAB78bDvmf7ARLm/btiXw+Pz45SBbOI7vm9Gm2zKL2+eWrzMpjhRkJmTi1gm3AgAeXfsoNlUqs4zUVWLBC1wAuGDwBeib2hdVLVV4buNzbbvjcYTEiIr/396dRzV15v8Df98kJOxB1oCyKYhFFlcwbd0KI2pbtXZB60y109FvrVqtS6tOq9ZOv9jT6erY+pv2W+s504q1rcu06hRBtI6IYsFdEAoElbBDFpZA8vz+SLkSdihwAT+vc3KO3vuQPB+eS/LJs92Jiok4PO8wlocvh0wsQ3pxOjb+vBHT90/HqsRV2Jm+E4B5XLpxYppYJMbGiI0AgP2Z+1vdrKatZAQAloUug7O1M/I0eVj448Iu3823qyYHuuGnV6bwGxIl3izGM/8vBVPePYkdx27iv9mltEfJAKKuqsUHCeadPN947AGM9HBoUWbqSDccXvkwjq2ejLfmjsYr0SPxxmPBOPCiEle2zcChFQ9h46xRWBTpi79MHo6PFoxF2ut/wJ4lE/HkuGFw+C0xySioxNU7GuSU6HG3qhalOgN0dQ3gOGD73BDYyVqfrAkAx3OPo7imGP/J+0+v/B6afqts9ELoC/zf1rNHn0WB5vfPTWj8ptk4TAOY9w2K9DQPn2w9uxX1pvoO54w0Wha2DC7WLsitysXuS7v54+29ZywevRjThk2DwWTA+lPre/xLTNPVhfWmemw5u6XHJtk3x3EcNsSMwubZo8BxwL7zBVjwz3O9Os/pZqEWNfVGOFpLMMKtf/SMNF6/HDj+2lo4aiGme09Hvakeq0+uRpG+CMC9+SKA5WqaRlZiK6yfsB4AsOfqHvw7598D4ssmJSPN2Ehs8NKYl/DDEz/gpfCXoLBTmJcJ3k7mx+DEnOUdHiM9IzE/cD4YGFYlrcKak2uQmJ/Iz4Ru743FXmqPXVG7oLBTIE+Th5eTXm5xx86eZis1b0iU8MoUxE7whr1MgoLyGuw+lYNFn6dizPaf8MfPU/HO8Zv496W7SP21DNfvapBTokNuqR75ZXoUlFejWFPbZvc96Rtv/XgdeoMR43yc8PR473bLPuDpiD8p/bA6OhAvPOyPiX7OsJW2nkBIJSJMH+WO954JR9rr0di/bBL++afx2LNkIuKXTcKRlQ/h+JrJOLF2KlI3RyE62KPd127s+u+tJYeNb+aO0nureVxtXLH/sf0IcQmB1qDFulPr+CShuxp7RppuPc9xHLYqt8JGYoO0ojRs+nkTP0+so2RELpNjU+QmAOZu9ZMq854l7b1ncByHvz38N3jaeUKlVWHr2a09+mFzV2de4fKX0L/ARmKDyyWXcbP8Zo89f2uWTRmBPUsmwtFagnRVJWI+PI2PTtxCVfXva6/WpP22x8k43yGC3bqguaZzkUSc+WOZ4zj878P/iwCnAJTUlGD1ydWorq/ml/VKOEmbq7WmeU9DbFAsGBg2n9mMxccX89tS9Fdtf5W5zynsFFg+ZjmWhS3D9bLrSCtKw/sX3wcAOFk7tSi/OXIzOHD47tZ3SFQlIlGVCJlYhoe8HkKVwdwl2HQZVlMhriHYO3MvFvywADfKb+BA5gE8N7rtuzv2lOFu9njnqTBsmzMaCTeKkJxZjDO3SlGsrcOZ7FKcye548pq1lQi+znYIHSZHhJ8zlCNc4O3cfyaFdYWhwTyMkZJT9ts+BAxSiQhyG/OdPc0PW3g728DNXtarSwI743RWCX68XAgRB7w1L6TX3lhlEjEih7e/YVN7GGP8fZg6e3PJrmpMEpr2jADmv+MPpn+A+Ufm40b5DWQUZ/B3zu7W6/zWC9G0ZwQAvB288fepf8fqk6sten86SkYAIMYvBhfUF7A/cz/WJK/BCyEv8MNOrSUjgDmJeXfqu1hybAl+yv8JiapEfmfX36tQbx6mGes+FpdLLuO8+jyyKrIQ7BLcI8/flmlB7vhh1WSs//YSzueW44MTWfgkORuRw10wzscJoUPl8HWxxbAhtrC2Enf8hG1IyzMvQhgv4Byn5lrr2QPMX1Y/fuRjPPvjs7hWdg3zj8znJ7c2ny/SVOP8IhuJDfbd3If04nS8mPAi9s7a2+Y1JTRKRjogFokR6haKULdQTB46GTsu7OBn6jclE8uw7cFtiA2KxbG8Y/j+1veoqqtCUkESX6a9i8DL3gtLQpbgg4sfIL04vU+SEb5eUjHmhHthTrgXGGO4VazD+dxyXLurQVaRFhXVBmhqGlBvNMHEGEwmBhMD6hqMqK03IbNIi8wiLb69aF5u6Otii8mBrng4wA3KES6CLffsLJOJYX9aAT48kYUiTed27ZRKRLCTiiGViMwPsQgO1lbwdbGFn4sd/FxtMcLNHsPd7GHfzvBFd2lr67Hpe/M48nNKP8E2G+uMiroK/sO1vLYcOoOOn3PRU9p6MwfMCUmkIhInVCdwvez670tGms0ZaWrKsCl4b+p7WJe8jp/A2tY31+Zem/gaahpqcCTnCD678hl/vL33jHC3cMSOisVXN77CmTtneiwZaRym8bTzRIBTAM6rzyO7IrtHnrsjPi62iF86CT9eKcSuk9m4qdbidFYJTmeV8GU4DlA4WsPb2RaO1hJYW4lhYyWGzEoEqfje36Tst4eznRRuDjK4O1jjplqDY7/d5VzZwY6ofYnvGWnluvJ28MbOR3Ziw+kNuKO7g7+n/R0AIOpgYEPEibBuwjrMD5yPJceX4Eb5DSTkJ2DOiDk9H0AP6Na75K5du/Duu+9CrVYjPDwcO3fuRERERJvlDxw4gDfeeAN5eXkIDAzEO++8g9mzZ3e70kIJGBKAz2e0P7v8AZcH8IDLA3h57Mu4VnYN65LXoajaPNZnK2m/xyDMNQwAcLn0cs9UuBs4jsNID4dW5x4012A04U5lDbKLdUjLr8D53HJcKqhEflk18stU+Nc5FTjOvBNh6FA5fJxtoZBbQ+FoDVd7GeQ2VnC0kcDB2gpigbpLr9/V4K+HriBdVQnAvDFTzGgPBHk4wEosgsFoQpnOgNsVNSioqMadihoUVtXA0GCCoaHlOHpGQWWLYwpHawx3s8MIN3v4udrBS24Nj99+D+4OMkjEXRstrTY0YNW+dNyprIG3sw02xAR1J/Q+03zyaL42H6NdRnfrua6XXUeBtgAhriEYaj+UP85PYLVqPckJdgnGCdUJXCu91uFr5Gvy8a/r/4LSS4mpw6ZCLLr3Lby1OSNNPeLzCN6f9j5ePvkyAMs7sbbHSmyFtx9+G1OGTcFb597iV+Z19C12omIivrrxFS6VXOrU63REZ9Dxv0svey8EDjHvGppd2TfJCGBeafN4uBceC/PEjUItLuSV4xdVBbKKdFCV6aE3GFFYVYvCqu7vozF3jBcm+LV907q+1rjhWWvJNACMcR+Dw3MP47Mrn/ErnFx/u+FfR/zl/pgXMA9fXP0CF9QXLJKR5IJk3NXdRYOpAb9W/YpXxr/CL87oa11ORvbv34+1a9di9+7diIyMxIcffoiYmBhkZmbC3d29RfmzZ89i4cKFiIuLw2OPPYavv/4a8+bNwy+//IKQkJAeCaI/kogkCHcLx4HHD+Dj9I+RVZ7F38ioLcEuwRBzYhRXF6NIXwQPu/bH4YUmEYvg62IHXxc7RD1grquurgHncsrw860S/HyrFL+W6pFdrEN2cfuT7BxkEjjaWMHRxgpyGwnkNlawlUrAwZwgcRwg4swTvEQiAODM/+cAEcdZlOOanJNKzD0W9jIJHKwlsJeZH9UGI07cKEL8hQIYTQz2Mgle+cNI/HGSD2SS9ruA640mqKtqUVtvRF2DCQajCXX1JlRWG5BfXo38Mj1+LdHj11I9SrR1UGtqodbU4mxOyw3nRJx5K//GJE0ht8YQWylMjMFgNKG6zghdXQN0dQ3Q//bIKdFDV9cAaysR3n9mTLsTR/uDxiGaRgWagm4lI59e+hSfZHzC/z/cLRxBQ4Ig4kRIyE8A0PabeePrXSvrOBnZnrId59XnEZ8ZDy87L8wePhuedp6Qy+T8F4umc0aam+4zHUfmHcHp26cx279rX7pi/GIw1n0s/nbub8iuzEaIa/vvkY23pcipzIHWoG0z/uYYY9hydgsyyzMR5hYGfb0etQ21MDLzPDcnmRPsrOwQ4BQAALhVcatLcfQEjuMQ7OWIYC9HLH7Qj693ud78d3anogbVhgbUGIyorjeirt78t2hoMKGuwQhDgwm19SaU6w0o1taiWFsHo5FhrO8QbJ8rzGdPg6kBuzJ2oc5YhwhFBMa6j4VcJm+3Z6+RrZUtVo9bjUUPLMJ/8v7TpWGziYqJfDLS6HLJZaxKWmVRbm7AXIx1b/9zqrdwrIsznyIjIzFx4kT84x/mZawmkwne3t5YtWoVNm7c2KJ8bGws9Ho9fvjh3va0kyZNwpgxY7B79+4W5Vuj0Wggl8tRVVUFR0dhtpvuK08deQqZFZnYptwGpZdS6Or8bmX6OmSqtbhVpIVaU4dSXR1KNHWorKmHtrahX6zceWSUO16OCuyVe1Roa+uhKq829xaVV+NORTVKtHUo1RlQqq1DQzcnAHs4yrBtzmiEDXPq2Qr3gOr6auzP3I/r5ddhNBlRVVeF27p7O4Y+P/p5LBi1oEvPWVFbgT8d+xPqTfVQ2ClQpC/il9k3tStqF6YMm9LieGVtJSbvN++WenDOwRZLZhvla/KxLGEZxJwYDlIHixtjNvXx9I8x3Wd6l2LoLbO+m4XbutvYMXlHpz9IkguSEXc+rs3zIS4h2PfYPugMOij3md+HvpvzXZs9QgOd0WREVkUWymrLYDAaYC+1xxi3Ma2uVvk9vsn8Bv939f8sjjlYOfA9I3NGzMHbD7/do68JmHv0Htr3EIzMiK9nfw0XGxe8nfo2v9T+D75/gL/cH3NHzIWPY9tL9Lujs5/fXfpKZTAYcPHiRWzatIk/JhKJEB0djZSU1jcWSklJwdq1ay2OxcTE4NChQ22+Tl1dHerq7o3dazSarlRzQAt1CzUnIynbhK5K7+AAyM0PCYD+8NZ23gj88ac+fEFb88O6ZUdip+kBbEgFkNpDdeoDfo5+yNPkYc+1PdhzbU+3niNCEYHPZ3yO0ppSJKmSUF5bDiMzQqVRwciM/L05mnOydsJQ+6G4o7uDJ4480eHrzPCbge0PbkeSKgln7pyBvl6PQn0hblXcglgkxijnUd2qf28Idw/Hbd1tbPy55ZfBjgQOCcTUYVPhKHWElcgK2ZXZqGmowVMjnwJgnsPgZeeFu/q7ePJIy7lypHuifaKRVZEFlVbFJyIALIYee5KdlR2CXYJxpfQKnj36LH+cA4fD8w7DX+7fK6/bFV1KRkpLS2E0GuHhYTl84OHhgZs3W1/6pVarWy2vVre9n0ZcXBzefPPNrlRt0JgzYg6SVEkDauc8QpoLdwvH00FPw0Zsg4q6Cog5MQKcArAyaWWbOxV3RC6V49WJr4LjOLjZuiF2VGyXfv6ZoGew+9LuDvfMkEvl+J+w/4G1xBqzh8/G7OH3hlpqG2rBwPrVioR5AfNw9s5ZfqO0zprgMQH/iPpHh5Nsnxr5FD678lmv7TXSX/g6+mKY/TBIxVLc1d1FVkVWq71vvwcHDk+NfAqvRbwGwNyLWKgvxB3dHejr9a326vWUBaMWIC81j9+9lQOHp4Oe7heJCNDFYZq7d+9i6NChOHv2LJTKe0MIr776Kk6dOoXU1JZf06RSKfbu3YuFCxfyxz755BO8+eabKCoqavV1WusZ8fb2vi+GaQghhJDBoleGaVxdXSEWi1skEUVFRVAoFK3+jEKh6FJ5AJDJZJDJen78nhBCCCH9T5fWFEqlUowfPx6JiYn8MZPJhMTERIuekqaUSqVFeQBISEhoszwhhBBC7i9dXhO4du1aLF68GBMmTEBERAQ+/PBD6PV6PP+8+U6Bzz33HIYOHYq4OPNM7dWrV2Pq1Kl477338OijjyI+Ph5paWn45z8Hzg18CCGEENJ7upyMxMbGoqSkBFu2bIFarcaYMWNw/PhxfpKqSqWCSHSvw+XBBx/E119/jddffx2bN29GYGAgDh06NKj3GCGEEEJI53V5nxEh3E/7jBBCCCGDRWc/v+muvYQQQggRFCUjhBBCCBEUJSOEEEIIERQlI4QQQggRFCUjhBBCCBEUJSOEEEIIERQlI4QQQggRFCUjhBBCCBEUJSOEEEIIEVSXt4MXQuMmsRqNRuCaEEIIIaSzGj+3O9rsfUAkI1qtFgDg7e0tcE0IIYQQ0lVarRZyubzN8wPi3jQmkwl3796Fg4MDOI7rsefVaDTw9vZGQUHBoL3nzWCPcbDHBwz+GAd7fMDgj3GwxwcM/hh7Kz7GGLRaLby8vCxuotvcgOgZEYlEGDZsWK89v6Oj46C8uJoa7DEO9viAwR/jYI8PGPwxDvb4gMEfY2/E116PSCOawEoIIYQQQVEyQgghhBBB3dfJiEwmw9atWyGTyYSuSq8Z7DEO9viAwR/jYI8PGPwxDvb4gMEfo9DxDYgJrIQQQggZvO7rnhFCCCGECI+SEUIIIYQIipIRQgghhAiKkhFCCCGECOq+TkZ27doFPz8/WFtbIzIyEufPnxe6St2ybds2cBxn8Rg1ahR/vra2FitWrICLiwvs7e3x5JNPoqioSMAad+z06dN4/PHH4eXlBY7jcOjQIYvzjDFs2bIFnp6esLGxQXR0NG7dumVRpry8HIsWLYKjoyOcnJzwwgsvQKfT9WEUbesoviVLlrRo05kzZ1qU6c/xxcXFYeLEiXBwcIC7uzvmzZuHzMxMizKduS5VKhUeffRR2Nrawt3dHRs2bEBDQ0NfhtKmzsQ4bdq0Fu344osvWpTprzF++umnCAsL4zfBUiqVOHbsGH9+oLcf0HGMA7n9WrNjxw5wHIc1a9bwx/pNO7L7VHx8PJNKpeyLL75g165dY0uXLmVOTk6sqKhI6Kp12datW9no0aNZYWEh/ygpKeHPv/jii8zb25slJiaytLQ0NmnSJPbggw8KWOOOHT16lP31r39l33//PQPADh48aHF+x44dTC6Xs0OHDrFLly6xOXPmMH9/f1ZTU8OXmTlzJgsPD2fnzp1jP//8MwsICGALFy7s40ha11F8ixcvZjNnzrRo0/Lycosy/Tm+mJgYtmfPHnb16lWWkZHBZs+ezXx8fJhOp+PLdHRdNjQ0sJCQEBYdHc3S09PZ0aNHmaurK9u0aZMQIbXQmRinTp3Kli5datGOVVVV/Pn+HOORI0fYjz/+yLKyslhmZibbvHkzs7KyYlevXmWMDfz2Y6zjGAdy+zV3/vx55ufnx8LCwtjq1av54/2lHe/bZCQiIoKtWLGC/7/RaGReXl4sLi5OwFp1z9atW1l4eHir5yorK5mVlRU7cOAAf+zGjRsMAEtJSemjGv4+zT+sTSYTUygU7N133+WPVVZWMplMxvbt28cYY+z69esMALtw4QJf5tixY4zjOHbnzp0+q3tntJWMzJ07t82fGUjxMcZYcXExA8BOnTrFGOvcdXn06FEmEomYWq3my3z66afM0dGR1dXV9W0AndA8RsbMH2ZN3/ibG2gxDhkyhH3++eeDsv0aNcbI2OBpP61WywIDA1lCQoJFTP2pHe/LYRqDwYCLFy8iOjqaPyYSiRAdHY2UlBQBa9Z9t27dgpeXF4YPH45FixZBpVIBAC5evIj6+nqLWEeNGgUfH58BG2tubi7UarVFTHK5HJGRkXxMKSkpcHJywoQJE/gy0dHREIlESE1N7fM6d0dycjLc3d0RFBSE5cuXo6ysjD830OKrqqoCADg7OwPo3HWZkpKC0NBQeHh48GViYmKg0Whw7dq1Pqx95zSPsdFXX30FV1dXhISEYNOmTaiurubPDZQYjUYj4uPjodfroVQqB2X7NY+x0WBovxUrVuDRRx+1aC+gf/0dDogb5fW00tJSGI1Gi18uAHh4eODmzZsC1ar7IiMj8eWXXyIoKAiFhYV48803MXnyZFy9ehVqtRpSqRROTk4WP+Ph4QG1Wi1MhX+nxnq31n6N59RqNdzd3S3OSyQSODs7D4i4Z86cifnz58Pf3x85OTnYvHkzZs2ahZSUFIjF4gEVn8lkwpo1a/DQQw8hJCQEADp1XarV6lbbuPFcf9JajADw7LPPwtfXF15eXrh8+TJee+01ZGZm4vvvvwfQ/2O8cuUKlEolamtrYW9vj4MHDyI4OBgZGRmDpv3aihEY+O0HAPHx8fjll19w4cKFFuf609/hfZmMDDazZs3i/x0WFobIyEj4+vrim2++gY2NjYA1I921YMEC/t+hoaEICwvDiBEjkJycjKioKAFr1nUrVqzA1atXcebMGaGr0mvainHZsmX8v0NDQ+Hp6YmoqCjk5ORgxIgRfV3NLgsKCkJGRgaqqqrw7bffYvHixTh16pTQ1epRbcUYHBw84NuvoKAAq1evRkJCAqytrYWuTrvuy2EaV1dXiMXiFjOGi4qKoFAoBKpVz3FycsLIkSORnZ0NhUIBg8GAyspKizIDOdbGerfXfgqFAsXFxRbnGxoaUF5ePiDjHj58OFxdXZGdnQ1g4MS3cuVK/PDDDzh58iSGDRvGH+/MdalQKFpt48Zz/UVbMbYmMjISACzasT/HKJVKERAQgPHjxyMuLg7h4eH46KOPBlX7tRVjawZa+128eBHFxcUYN24cJBIJJBIJTp06hY8//hgSiQQeHh79ph3vy2REKpVi/PjxSExM5I+ZTCYkJiZajBUOVDqdDjk5OfD09MT48eNhZWVlEWtmZiZUKtWAjdXf3x8KhcIiJo1Gg9TUVD4mpVKJyspKXLx4kS+TlJQEk8nEv6EMJLdv30ZZWRk8PT0B9P/4GGNYuXIlDh48iKSkJPj7+1uc78x1qVQqceXKFYukKyEhAY6Ojnw3upA6irE1GRkZAGDRjv05xuZMJhPq6uoGRfu1pTHG1gy09ouKisKVK1eQkZHBPyZMmIBFixbx/+437dhjU2EHmPj4eCaTydiXX37Jrl+/zpYtW8acnJwsZgwPFOvWrWPJycksNzeX/fe//2XR0dHM1dWVFRcXM8bMS7d8fHxYUlISS0tLY0qlkimVSoFr3T6tVsvS09NZeno6A8Def/99lp6ezvLz8xlj5qW9Tk5O7PDhw+zy5cts7ty5rS7tHTt2LEtNTWVnzpxhgYGB/Wbpa3vxabVatn79epaSksJyc3PZiRMn2Lhx41hgYCCrra3ln6M/x7d8+XIml8tZcnKyxbLI6upqvkxH12XjksIZM2awjIwMdvz4cebm5tZvlk12FGN2djbbvn07S0tLY7m5uezw4cNs+PDhbMqUKfxz9OcYN27cyE6dOsVyc3PZ5cuX2caNGxnHceynn35ijA389mOs/RgHevu1pfkKof7SjvdtMsIYYzt37mQ+Pj5MKpWyiIgIdu7cOaGr1C2xsbHM09OTSaVSNnToUBYbG8uys7P58zU1Neyll15iQ4YMYba2tuyJJ55ghYWFAta4YydPnmQAWjwWL17MGDMv733jjTeYh4cHk8lkLCoqimVmZlo8R1lZGVu4cCGzt7dnjo6O7Pnnn2darVaAaFpqL77q6mo2Y8YM5ubmxqysrJivry9bunRpi0S5P8fXWmwA2J49e/gynbku8/Ly2KxZs5iNjQ1zdXVl69atY/X19X0cTes6ilGlUrEpU6YwZ2dnJpPJWEBAANuwYYPFPhWM9d8Y//znPzNfX18mlUqZm5sbi4qK4hMRxgZ++zHWfowDvf3a0jwZ6S/tyDHGWM/1sxBCCCGEdM19OWeEEEIIIf0HJSOEEEIIERQlI4QQQggRFCUjhBBCCBEUJSOEEEIIERQlI4QQQggRFCUjhBBCCBEUJSOEEEIIERQlI4QQwUybNg1r1qwRuhqEEIFRMkIIIYQQQdF28IQQQSxZsgR79+61OJabmws/Pz9hKkQIEQwlI4QQQVRVVWHWrFkICQnB9u3bAQBubm4Qi8UC14wQ0tckQleAEHJ/ksvlkEqlsLW1hUKhELo6hBAB0ZwRQgghhAiKkhFCCCGECIqSEUKIYKRSKYxGo9DVIIQIjJIRQohg/Pz8kJqairy8PJSWlsJkMgldJUKIACgZIYQIZv369RCLxQgODoabmxtUKpXQVSKECICW9hJCCCFEUNQzQgghhBBBUTJCCCGEEEFRMkIIIYQQQVEyQgghhBBBUTJCCCGEEEFRMkIIIYQQQVEyQgghhBBBUTJCCCGEEEFRMkIIIYQQQVEyQgghhBBBUTJCCCGEEEFRMkIIIYQQQf1/obADNXM4nNYAAAAASUVORK5CYII=", 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", 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", 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", 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", 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/vNPv22w2V3rDiIiIICYmxrYCol+/frRr145Zs2ZVWuKqaVqNt3/jjTeyfv36KptaZWZmUlpaanfeggULOH36tO3nTZs2sXHjxhozNFWtAunTpw9Qvorj6quvJiUlhW+++cZ2TGlpKe+88w4BAQGMGDHCdlxpaSmzZ8+2HWc2m3nnnXfsbj8iIoKRI0fy4Ycf2moRKqprlqGubrzxRk6fPl1l/U9BQYFdF9NBgwbh6enJa6+9RmhoKD169ABUkLJhwwZWrlxplxWB8pqRupwq1oxcOM0GUFJSwueff46vr2+NmTyLxcJTTz2Fn58fDz74oN31Dxw4UOXvtb6++eYbNm/ezOOPP16n5cFCSGZEXHS8vLz4/vvvGTVqFJdddpldB9Z58+axbds2/vrXv1bq0VAXWVlZfPnll1Vedtttt5GTk0NsbCzXX3898fHxBAQEsHTpUjZv3sybb74JqKzD7NmzmTBhAn369OGuu+4iOjqaAwcO1No988knn+Tnn39m/Pjx3HnnnfTv35+8vDx2797N999/z4kTJwgPD7cd37FjRy677DKmTJlCUVERs2bNIiwsrNppHlCdcFetWsU111xDmzZtSEtL4/333yc2Ntb2yfj+++/nww8/5M4772Tr1q20bduW77//nrVr1zJr1ixbLc6ECRMYOnQozzzzDCdOnKB79+78+OOPVX7Cf++997jsssvo1asX9913H+3btyc1NZX169dz6tQpdu7caTvWmtk5ceJEtY+jJrfffjvffvstDz74ICtWrGDo0KGYzWYOHDjAt99+y+LFi21Thn5+fvTv358NGzbYeoyAyozk5eWRl5dXKRipb83IAw88QHZ2NsOHD6dVq1akpKTw1VdfceDAAd5880277NJjjz1GYWEhffr0oaSkhHnz5rFp0ybmzp1rNz15+vRpunXrxh133GG3F9CqVatYtWoVoIK9vLw8Xn75ZdtjGz58uO24F198kauuuoqwsDA2bNjAZ599xtixY2tchi6EHVcv5xGiNtV1YL1QdR1Yq5OWlqZNmzZN69ixo+bt7a2FhIRoo0ePdmg5b0U1Le21/qsVFRVpTz75pBYfH68FBgZq/v7+Wnx8vPb+++9Xur01a9ZoV155pe243r17a++8806t48jJydGmT5+udezYUfPy8tLCw8O1IUOGaP/+97+14uJiTdPKl5a+8cYb2ptvvqnFxcVp3t7e2rBhw7SdO3fa3d6FS3uXLVumTZw4UYuJidG8vLy0mJgY7ZZbbqm0nDg1NVW76667tPDwcM3Ly0vr1atXlR1Vz507p91+++1aUFCQFhwcrN1+++3a9u3bq+zAevToUW3y5MlaVFSU5unpqbVq1UobP358peWj4eHh2qWXXlrr76qmrrnFxcXaa6+9pvXo0UPz9vbWWrRoofXv31974YUXtKysLLtjn3zySQ3QXnvtNbvzO3bsqAHa0aNHax1LXXz99dfa6NGjtcjISM3Dw0Nr0aKFNnr0aG3hwoWVjv3ss8+0+Ph4zd/fXwsMDNRGjRqlLV++vNJx1r+FO+64w+586/Ne1en555+3HXfkyBHtqquu0sLDwzVvb2+ta9eu2owZM7SioiKnPGZxcTBoWi15XyFEs3PixAnatWvHG2+8wRNPPOHq4TjVvn376NGjB7/88gvXXHONq4cjhKgDmcwTQjQrK1asYPDgwRKICOFGpGZEiFqkp6djNpurvdzLy4vQ0NAmHJGoydSpU5k6daqrhyGEcIAEI0LUYuDAgbYmXVUZMWIECQkJTTcgIYRoZqRmRIharF27tsaW1i1atKB///5NOCIhhGheJBgRQgghhEtJAasQQgghXMotakYsFgtnzpwhMDCw1tbMQgghhNAHTdPIyckhJiamxm68bhGMnDlzxm5jKiGEEEK4j5MnTxIbG1vt5W4RjFhbR588eZKgoCAXj0YIIYQQdZGdnU1cXJztfbw6bhGMWKdmgoKCJBgRQggh3ExtJRZSwCqEEEIIl5JgRAghhBAuJcGIEEIIIVzKLWpGhBBCXJzMZjMlJSWuHoaohqenJyaTqcG3I8GIEEII3dE0jZSUFDIzM109FFGLkJAQoqKiGtQHTIIRIYQQumMNRCIiIvDz85OGlzqkaRr5+fmkpaUBEB0dXe/bkmBECCGErpjNZlsgEhYW5urhiBr4+voCkJaWRkRERL2nbKSAVQghhK5Ya0T8/PxcPBJRF9bnqSG1PRKMCCGE0CWZmnEPznieJBgRQgghhEtJMCKEEEI4yciRI3n88cervbxt27bMmjWrycbjLqSAVQghhGgimzdvxt/f39XD0B0JRpoRTdMwWzQ8TFUnvEotpXgY5SkXQghXadmypauHoEsyTdOM/Hf1MTr+/Tfu+mwTG4+dQ9M022V/X/N3Rn03iszCTNcNUAghLgKlpaU8/PDDBAcHEx4ezrPPPmt7Pb5wmiYpKYmJEycSEBBAUFAQN954I6mpqbbL//nPf9KnTx8+/fRTWrduTUBAAA899BBms5nXX3+dqKgoIiIieOWVV+zG8NZbb9GrVy/8/f2Ji4vjoYceIjc313Z5YmIiEyZMoEWLFvj7+9OjRw8WLVoEwPnz57n11ltp2bIlvr6+dOrUic8++6wRf2OSGWlWftmVDMCKg+msOJjOP67pxr3D2gOw5vQaMgozOJF9gj4+fVw4SiGEcJymaRSUmJv8fn09TQ6vFpk7dy733HMPmzZtYsuWLdx///20bt2a++67z+44i8ViC0RWrlxJaWkpU6dO5aabbiIhIcF23NGjR/ntt9/4/fffOXr0KNdffz3Hjh2jc+fOrFy5knXr1nH33XczevRoBg0aBIDRaOQ///kP7dq149ixYzz00EM89dRTvP/++wBMnTqV4uJiVq1ahb+/P/v27SMgIACAZ599ln379vHbb78RHh7OkSNHKCgoaMBvsXYSjDQTJWYLB5JzALi8S0tWHEzn+62nuHdYeyyahayiLAA0tJpuRgghdKmgxEz35xY3+f3ue3EMfl6OvVXGxcUxc+ZMDAYDXbp0Yffu3cycObNSMLJs2TJ2797N8ePHiYuLA+Dzzz+nR48ebN68mYEDBwIqaPn0008JDAyke/fuXH755Rw8eJBFixZhNBrp0qULr732GitWrLAFIxWLaNu2bcvLL7/Mgw8+aAtGkpKS+POf/0yvXr0AaN++ve34pKQk+vbty4ABA2zXb2wyTdNMHE7NpdhsIdDHg39dp/64DqflUlBsJqc4B7OmPlFYNIsrhymEEM3epZdeapdNGTx4MIcPH8Zsts/s7N+/n7i4OFsgAtC9e3dCQkLYv3+/7by2bdsSGBho+zkyMpLu3btjNBrtzrO2ZQdYunQpo0aNolWrVgQGBnL77bdz7tw58vPzAXj00Ud5+eWXGTp0KM8//zy7du2yXXfKlCnMnz+fPn368NRTT7Fu3Ton/FZqJpmRZmLPGZX56BkTTHSwLxGB3qTlFLH3TBZhLbJsx0kwIoRwR76eJva9OMYl9+tqnp6edj8bDIYqz7NY1Ov7iRMnGD9+PFOmTOGVV14hNDSUNWvWcM8991BcXIyfnx/33nsvY8aM4ddff+WPP/5gxowZvPnmmzzyyCOMGzeOxMREFi1axJIlSxg1ahRTp07l3//+d6M9RsmMNBN7TpcFI62CAOgdGwzArlNZZBZlumpYQgjhFAaDAT8vjyY/1ae76MaNG+1+3rBhA506daq0b0u3bt04efIkJ0+etJ23b98+MjMz6d69e/1+UcDWrVuxWCy8+eabXHrppXTu3JkzZ85UOi4uLo4HH3yQH3/8kb/+9a/897//tV3WsmVL7rjjDr788ktmzZrFRx99VO/x1IUEI81EeTCigpDesSEA7DqVSUZhhu04yYwIIUTjSkpKYtq0aRw8eJCvv/6ad955h8cee6zScaNHj6ZXr17ceuutbNu2jU2bNjF58mRGjBhhq9eoj44dO1JSUsI777zDsWPH+OKLL/jggw/sjnn88cdZvHgxx48fZ9u2baxYsYJu3boB8Nxzz7Fw4UKOHDnC3r17+eWXX2yXNRYJRpoBs0VjX3I2AD1irMFIhcxIheW8EowIIUTjmjx5MgUFBVxyySVMnTqVxx57jPvvv7/ScQaDgYULF9KiRQuGDx/O6NGjad++Pd98802D7j8+Pp633nqL1157jZ49e/LVV18xY8YMu2PMZjNTp06lW7dujB07ls6dO9uKW728vJg+fTq9e/dm+PDhmEwm5s+f36Ax1cagVWxGoVPZ2dkEBweTlZVFUFCQq4ejO4dTc7hy5ir8vEzs/ucYTEYDGXnF9HtpCQBP3HiKD3e/C8CHoz9kSKshrhyuEELUqLCwkOPHj9OuXTt8fHxcPRxRi5qer7q+f0tmpBmwFq92jw7CZFTzm6H+XsS28AXg6LnyBjqytFcIIYTeSDDSDOw5raZorPUiVvFldSMns87azpNpGiGEEHojwUgzYC1e7RFjnwLrVVY3kpZ/znaeZEaEEELojQQjzcDBVNV5tfsFwYi1iDWrwtJeyYwIIYTQGwlG3FxRqZnM/BIAYoJ97S5rHeoHgNmQYzvPDeqVhRBCXGQcCkZmz55N7969CQoKIigoiMGDB/Pbb79Ve/ycOXMwGAx2J6mMdq5zucUAeBgNBPvad+TzsLYKNuXZzrMgmREhhBD64lA7+NjYWF599VU6deqEpmnMnTuXiRMnsn37dnr06FHldYKCgjh48KDt5/p0sxPVswYjYQFeGI32v1ujETCUYDAW286TzIgQQgi9cSgYmTBhgt3Pr7zyCrNnz2bDhg3VBiMGg4GoqKj6j1DU6GxuEQDhAd6VLvMwGjGY8u3OkwJWIYQQelPvmhGz2cz8+fPJy8tj8ODB1R6Xm5tLmzZtiIuLY+LEiezdu7e+dymqkF5DMGIyGjCYcu3OkwJWIYQQeuPwrr27d+9m8ODBFBYWEhAQwE8//VTthj5dunTh008/pXfv3mRlZfHvf/+bIUOGsHfvXmJjY6u9j6KiIoqKimw/Z2dnOzrMi0bNmREDBo8LMiMyTSOEEEJnHM6MdOnShR07drBx40amTJnCHXfcwb59+6o8dvDgwUyePJk+ffowYsQIfvzxR1q2bMmHH35Y433MmDGD4OBg2ykuLs7RYV40zuaoepDwQK9Kl6nMSJ7deZIZEUII99W2bVtmzZrl6mE4ncPBiJeXFx07dqR///7MmDGD+Ph43n777Tpd19PTk759+3LkyJEaj5s+fTpZWVm2U8XtlYU9W2bEv7ppGvtgRGpGhBBC6E2D+4xYLBa7KZWamM1mdu/eTXR0dI3HeXt725YPW0+iarZgpKrMiEEyI0II0ZRGjhzJI488wuOPP06LFi2IjIzkv//9L3l5edx1110EBgbSsWNHW1uMAQMG8O9//9t2/UmTJuHp6Ulurqr3O3XqFAaDgSNHjjBy5EgSExP5y1/+YmuX0Vw4FIxMnz6dVatWceLECXbv3s306dNJSEjg1ltvBdS2ydOnT7cd/+KLL/LHH39w7Ngxtm3bxm233UZiYiL33nuvcx/FRaymmhGj0YDRQzIjQohmQNOgOK/pT/Wos5s7dy7h4eFs2rSJRx55hClTpnDDDTcwZMgQtm3bxlVXXcXtt99Ofn4+I0aMICEhoewhaqxevZqQkBDWrFkDwMqVK2nVqhUdO3bkxx9/JDY2lhdffJHk5GSSk5Od+Rt2KYcKWNPS0pg8eTLJyckEBwfTu3dvFi9ezJVXXglAUlISRmN5fHP+/Hnuu+8+UlJSaNGiBf3792fdunXVFrwKx50t6zNSVTACYLyggFUyI0IIt1SSD/+Kafr7/dsZ8PJ36Crx8fH84x//ANSH+FdffZXw8HDuu+8+AJ577jlmz57Nrl27GDlyJJ988glms5k9e/bg5eXFTTfdREJCAmPHjiUhIYERI0YAEBoaislkIjAwsNm1zHAoGPnkk09qvNwa3VnNnDmTmTNnOjwoUTelZgvn82sLRi7IjMhqGiGEaFS9e/e2fW8ymQgLC6NXr1628yIjIwH1AX/48OHk5OSwfft21q1bx4gRIxg5ciSvvvoqoDIjTz75ZNM+ABdweGmv0I+M/GI0DYwGCPWvXDMC2FrBexm9KbYUyTSNEMI9efqpLIUr7tfRq3jab81hMBjszrPWelgsFkJCQoiPjychIYH169dz5ZVXMnz4cG666SYOHTrE4cOHbZmR5kyCETdmXdYb6u+FyVh1IZO1gDXEO5S0gmSZphFCuCeDweHpEncxYsQIVqxYwaZNm3jllVcIDQ2lW7duvPLKK0RHR9O5c2fbsV5eXpjNZheOtnHIrr1urKbiVSirDzGqmpEgrxaAFLAKIYTejBw5ksWLF+Ph4UHXrl1t53311VeVsiJt27Zl1apVnD59mrNnz7piuI1CghE3VlswklOcAwaVCQn0DAGkZkQIIfRm2LBhWCwWu8Bj5MiRmM1mRo4caXfsiy++yIkTJ+jQoQMtW7Zs4pE2HpmmcWPWYCQsoOp6kZziHAA0iyeeBnWMTNMIIUTjuXAhB8CJEycqnVfxg2FoaCgWi/1r86RJk6r88HjppZeyc+fOBo9TbyQz4sZqW9Zr+0PWjEBZwZQEI0IIIXRGghE3djanlpoRrIGHAWswIjUjQggh9EaCETeWbqsZqXqapmIWxBqCSM2IEEIIvZFgxI2ds07TBNZhmkaTaRohhBD6JMGIG7MWsLasrmakLB+iyTSNEEIIHZNgxE1ZLBrn8mouYC3PglQIRmSaRgghhM5IMOKmMgtKMFtUYFFdK3i7YMQ6TYNM0wghhNAXCUbclHWKJtjXEy+Pqp9G25SMVp4ZkZoRIYQQeiPBiJvKKigBoIWfZ7XHVMyMaFS9d40QQgjhahKMuKnssmAkyLf6YKS8PsSA9VvJjAghhNAbCUbcVE5hKQCBPtV39LcFHjJNI4QQQsckGHFT2YVlmRGfGqZpqFzAKqtphBCi6RQXF7t6CG5BghE3Zc2M1BSM2E3TSJ8RIYRodCNHjuThhx/m8ccfJzw8nDFjxrBnzx7GjRtHQEAAkZGR3H777Zw9exaAX375hZCQEMxmMwA7duzAYDDwzDPP2G7z3nvv5bbbbnPJ42kqEoy4KWvNSE3TNBVX00jNiBDCnWmaRn5JfpOf6pNNnjt3Ll5eXqxdu5ZXX32VK664gr59+7JlyxZ+//13UlNTufHGGwEYNmwYOTk5bN++HYCVK1cSHh5ut/vvypUrGTlypDN+jbpV/TuZ0LVsa2akhgJWa+ChVewzIsGIEMINFZQWMGjeoCa/343/txE/Tz+HrtOpUydef/11AF5++WX69u3Lv/71L9vln376KXFxcRw6dIjOnTvTp08fEhISGDBgAAkJCfzlL3/hhRdeIDc3l6ysLI4cOcKIESOc+rj0RjIjbspaM1KnAlaZphFCiCbTv39/2/c7d+5kxYoVBAQE2E5du3YF4OjRowCMGDGChIQENE1j9erVXHfddXTr1o01a9awcuVKYmJi6NSpk0seS1ORzIibsi3trUvNiGawbdsrBaxCCHfk6+HLxv/b6JL7dZS/v7/t+9zcXCZMmMBrr71W6bjo6GhA1Zl8+umn7Ny5E09PT7p27crIkSNJSEjg/PnzzT4rAhKMuK06Le2tsJpGk3bwQgg3ZjAYHJ4u0YN+/frxww8/0LZtWzw8qn69ttaNzJw50xZ4jBw5kldffZXz58/z17/+tSmH7BIyTeOmbEt761AzUjEYkcyIEEI0nalTp5KRkcEtt9zC5s2bOXr0KIsXL+auu+6yraBp0aIFvXv35quvvrIVqg4fPpxt27Zx6NChiyIzIsGIm6pLZqRi4KHJrr1CCNHkYmJiWLt2LWazmauuuopevXrx+OOPExISgtFY/hY8YsQIzGazLRgJDQ2le/fuREVF0aVLFxeNvunINI2bqkvNSHkHVmP50l6ZphFCiEZTcUmuVadOnfjxxx9rvN6sWbOYNWuW3Xk7duxw3sB0TjIjbqio1ExRqQoqatybhop700hmRAghhD5JMOKGrFM0AAHedZmmkb1phBBC6JcEI27IVi/i7YHJaKj2uIob5Vks0mdECCGEPkkw4obq0goeLtgoz3qeZEaEEELojAQjbiinDq3goXyaRsOARZqeCSHcjLxeuQdnPE8SjLihurSCB/tpGlsBq0zTCCF0ztNTfdDKz8938UhEXVifJ+vzVh+ytNcN5RTWvqwXLuzAWnaeTNMIIXTOZDIREhJCWloaAH5+fhgM1dfHCdfQNI38/HzS0tIICQnBZDLV+7YkGHFD2QW1NzyDC5qeSWZECOFGoqKiAGwBidCvkJAQ2/NVXxKMuKG6tIKHilkQo61mRDIjQgh3YDAYiI6OJiIigpKSElcPR1TD09OzQRkRK4eCkdmzZzN79mxOnDgBQI8ePXjuuecYN25ctdf57rvvePbZZzlx4gSdOnXitdde4+qrr27QoC92tgLW2qZpqqoZkYIwIYQbMZlMTnmzE/rmUAFrbGwsr776Klu3bmXLli1cccUVTJw4kb1791Z5/Lp167jlllu455572L59O5MmTWLSpEns2bPHKYO/WNV1aW+5CqtpZJpGCCGEzjgUjEyYMIGrr76aTp060blzZ1555RUCAgLYsGFDlce//fbbjB07lieffJJu3brx0ksv0a9fP959912nDP5ilV3Hpb1V7dor0zRCCCH0pt5Le81mM/PnzycvL4/BgwdXecz69esZPXq03Xljxoxh/fr1Nd52UVER2dnZdidRriFLeyUYEUIIoTcOByO7d+8mICAAb29vHnzwQX766Se6d+9e5bEpKSlERkbanRcZGUlKSkqN9zFjxgyCg4Ntp7i4OEeH2azVtWak4kZ5Mk0jhBBCrxwORrp06cKOHTvYuHEjU6ZM4Y477mDfvn1OHdT06dPJysqynU6ePOnU23d3dW4HX5YF0Sr0GZECViGEEHrj8NJeLy8vOnbsCED//v3ZvHkzb7/9Nh9++GGlY6OiokhNTbU7LzU1tdb1yN7e3nh7ezs6tItGjqNLezUDFgtgkmkaIYQQ+tPgdvAWi4WioqIqLxs8eDDLli2zO2/JkiXV1piI2lksGjlFjjc9s0jTMyGEEDrlUGZk+vTpjBs3jtatW5OTk8O8efNISEhg8eLFAEyePJlWrVoxY8YMAB577DFGjBjBm2++yTXXXMP8+fPZsmULH330kfMfyUUir7jUNuVS93bwRukzIoQQQrccCkbS0tKYPHkyycnJBAcH07t3bxYvXsyVV14JQFJSEkZjebJlyJAhzJs3j3/84x/87W9/o1OnTixYsICePXs691FcRKzLer08jPh41twIqOLSXunAKoQQQq8cCkY++eSTGi9PSEiodN4NN9zADTfc4NCgRPXKN8lz4Kmz1oxQMVsihBBC6EODa0ZE07JuklfbFA1ckBmxlO14KbM0QgghdEaCETfjSCt4+2kaFYVIZkQIIYTeSDDiZnKK6rasFyoUq0oHViGEEDomwYibsU7T1CkzQuUCVllNI4QQQm8kGHEzudYeI951rxnRKtSMSJ8RIYQQeiPBiJux7kvj7117ZqRiFsRsXU0j0zRCCCF0RoIRN5NXlhkJcKSAVTPKNI0QQgjdkmDEzdiCEe+aG55BNTUjMk0jhBBCZyQYcTPWfWnqMk1THncY0CyymkYIIYQ+STDiZsozIw6sptEMUjMihBBCtyQYcTMOBSNV7E0j0zRCCCH0RoIRN+PINE15sWp5ZkQKWIUQQuiNBCNupl6ZEc2ANQaRdvBCCCH0RoIRN5NXZAYcrBlBNT4DyYwIIYTQHwlG3IjFotk6sDo2TWPE+lRLAasQQgi9kWDEjeSXmG3fOzJNo2kG0KQdvBBCCH2SYMSNWOtFTEYDPp61P3UVV9NYyTSNEEIIvZFgxI3Y9qXxMmEwGGo5uiID1oBEpmmEEELojQQjbsSRlTRQHngYkGkaIYQQ+iXBiBtxZJM8KA9GjAbJjAghhNAvCUbciEP70lAxC2IEWdorhBBCpyQYcSP1naaxy4xI0zMhhBA6I8GIG6l/MGIsrxmRzIgQQgidkWDEjeSWdV91dJrGaKgwTSMFrEIIIXRGghE3kltUAtRvmkaTAlYhhBA6JcGIG8mzZUZMdTq+fGlv+TSNBCNCCCH0RoIRN5JrqxnxdOh6FadphBBCCL2RYMSN5BZagxHHMiPGCt1aJTMihBBCbyQYcSN5xY71GbFbTSM1I0IIIXRKghE3kuvg0l7rMl5TxaW9sppGCCGEzkgw4kbKp2nqmBkpa3BmqND0TPqMCCGE0BsJRtxInoPt4K1TMiaZphFCCKFjEoy4kVwHN8qzZkGk6ZkQQgg9k2DETWia5nDNiK2A1Sjt4IUQQuiXQ8HIjBkzGDhwIIGBgURERDBp0iQOHjxY43XmzJmDwWCwO/n4+DRo0BejwhILlrI4os7TNFSxmkY2yhNCCKEzDgUjK1euZOrUqWzYsIElS5ZQUlLCVVddRV5eXo3XCwoKIjk52XZKTExs0KAvRtasCICfZ936jFhnZIxIO3ghhBD6VbeP2GV+//13u5/nzJlDREQEW7duZfjw4dVez2AwEBUVVb8RCsB+Wa/RWLduqtYsiEmmaYQQQuhYg2pGsrKyAAgNDa3xuNzcXNq0aUNcXBwTJ05k7969Dbnbi1L5Spo6ZkWoejWNFLAKIYTQm3oHIxaLhccff5yhQ4fSs2fPao/r0qULn376KQsXLuTLL7/EYrEwZMgQTp06Ve11ioqKyM7Otjtd7HIdXNYLFVbTGMufZpmmEUIIoTcOTdNUNHXqVPbs2cOaNWtqPG7w4MEMHjzY9vOQIUPo1q0bH374IS+99FKV15kxYwYvvPBCfYfWLFkbngU6EIyUZ0ak6ZkQQgj9qldm5OGHH+aXX35hxYoVxMbGOnRdT09P+vbty5EjR6o9Zvr06WRlZdlOJ0+erM8wmxVH96WBC1bTaOqplmkaIYQQeuNQZkTTNB555BF++uknEhISaNeuncN3aDab2b17N1dffXW1x3h7e+Pt7e3wbTdnDZqmMZiQDqxCCCH0yqFgZOrUqcybN4+FCxcSGBhISkoKAMHBwfj6+gIwefJkWrVqxYwZMwB48cUXufTSS+nYsSOZmZm88cYbJCYmcu+99zr5oTRvDZmm8ahQMyLTNEIIIfTGoWBk9uzZAIwcOdLu/M8++4w777wTgKSkJLuCyfPnz3PfffeRkpJCixYt6N+/P+vWraN79+4NG/lFxtF9aaBCB1ZpeiaEEELHHJ6mqU1CQoLdzzNnzmTmzJkODUpUlltkBhwLRqykz4gQQgg9k71p3ERuUQkAAfXoM2KsuJoGTQISIYQQuiLBiJvIK8uM1HWTPCifklE1I+VdW2VFjRBCCD2RYMRNNGw1jRFNM1Q6XwghhNADCUbchDUYCfSp72qa8mBEiliFEELoiQQjbsK6tDfA27PO1ymvGSnvMwKSGRFCCKEvEoy4ifpkRqy1ISZjeQErSOMzIYQQ+iLBiJvILixbTVOPaRqTwWRb2gtSwCqEEEJfJBhxA5qmlWdG6t2BVaZphBBC6JMEI24gv9iMNX5wJDNiZTLaP80yTSOEEEJPHH9nE03OmhUxGQ34ejre9MzDaKTizIysphFCCKEnkhlxAzm2lTQeGAyGWo4uV14zItM0Qggh9EuCETdgzYw40n0VKq6mkWBECCGEfkkw4gZyylbSOLKsF6TpmRBCCPcgwYgbyC2sX2bENk1jlKZnQggh9EuCETeQY52mcTAzYg06PKyrabTynXuFEEIIvZBgxA1YMyOBPnVvBQ/l0zHlS3tVMCJLe4UQQuiJBCNuoL4FrLaaEYN6mg0SjAghhNAhCUbcQH0LWK2zMapmBCrWjQghhBB6IcGIG6h3ZqRsmsZTpmmEEELomAQjbiCnoatpTBKMCCGE0C8JRtyAbZO8eq+msZ+mkaW9Qggh9ESCETdQvpqmftM0JqO1VkSW9gohhNAfCUbcQHnNiINLe20dWMsyI5pM0wghhNAfCUbcgK1mxEnTNNIOXgghhJ5IMOIGrEt761vA6nlBAavM0gghhNATCUZ0TtM02zRNkKOZEeuuvQZZTSOEEEK/JBjRuYISM5ayTEZ9p2k8bTUj6otM0wghhNATCUZ0zrqSxmgAX09TLUfbsxWw2qZp1FdZ2iuEEEJPJBjRuewKDc8MBsfauVszIB4mFcRosmuvEEIIHZJgROfKG545tqwXKk7T2AcxUjMihBBCTyQY0bn6NjyDCu3gpQOrEEIIHZNgROdyi+q3rFfTNNt0jLWAVZOmZ0IIIXRIghGdq3fDswp1IdaaEWkHL4QQQo8kGNG58lbw9Wt4BuVNz6yzM5IZEUIIoScSjOhcTj1rRirWhXheWDMimREhhBA64lAwMmPGDAYOHEhgYCARERFMmjSJgwcP1nq97777jq5du+Lj40OvXr1YtGhRvQd8sanvahq7aRpj2dOsSQGrEEII/XEoGFm5ciVTp05lw4YNLFmyhJKSEq666iry8vKqvc66deu45ZZbuOeee9i+fTuTJk1i0qRJ7Nmzp8GDvxjkFDZ8msbWZ0TawQshhNAhh97hfv/9d7uf58yZQ0REBFu3bmX48OFVXuftt99m7NixPPnkkwC89NJLLFmyhHfffZcPPvignsO+eDijZsTrgo3yZJpGCCGEnjSoZiQrKwuA0NDQao9Zv349o0ePtjtvzJgxrF+/vtrrFBUVkZ2dbXe6WOVad+xtwGoa0wXTNJIZEUIIoSf1DkYsFguPP/44Q4cOpWfPntUel5KSQmRkpN15kZGRpKSkVHudGTNmEBwcbDvFxcXVd5huz1bA2qDMiPW6khkRQgihP/UORqZOncqePXuYP3++M8cDwPTp08nKyrKdTp486fT7cBf1LWCtGIyYbO3gJTMihBBCfxzvMQ48/PDD/PLLL6xatYrY2Ngaj42KiiI1NdXuvNTUVKKioqq9jre3N97e3vUZWrNT76ZnFVbMmAymCgGJrKYRQgihLw5lRjRN4+GHH+ann35i+fLltGvXrtbrDB48mGXLltmdt2TJEgYPHuzYSC9S9S5gpTz7YTQYVTCiqadbMiNCCCH0xKF3uKlTpzJv3jwWLlxIYGCgre4jODgYX19fACZPnkyrVq2YMWMGAI899hgjRozgzTff5JprrmH+/Pls2bKFjz76yMkPpfnRNK3CNE39a0YMBgMeRgNSMyKEEEKPHMqMzJ49m6ysLEaOHEl0dLTt9M0339iOSUpKIjk52fbzkCFDmDdvHh999BHx8fF8//33LFiwoMaiV6FkF5ZitqjAIdjXsZoRK6NBPcUyTSOEEEKvHPq4XZc3sYSEhErn3XDDDdxwww2O3JUAMvOLAfDzMuHjaarlaHvWzIiR8mDELAWsQgghdEj2ptGxjDwVjLTw83L4utaAw2BQAYiH0VDeDl6maYQQQuiIBCM6dr4sM9LC3/EpGmsWy1CWDTEZDbZ28DJNI4QQQk8kGNGx83mq+2q9MiNlq2msNSNqszyD3WVCCCGEHkgwomPWzEiof8OnaUwVpmmkZkQIIYSeSDCiY7ZpmnpkRqxTMfaraaRmRAghhP5IMKJjGQ2ZprlgNY1a2Ss1I0IIIfRHghEdO59X/wJWa11I+WqaCjUjMk0jhBBCRyQY0bGGTNNYZ2Ks0zRGqRkRQgihUxKM6FhDghHbNI1tNU15zYgQQgihJxKM6Nj5/LKakYZM05QFIMYK7eAlMyKEEEJPJBjRKU3TbDUj9Vnaa2t6Zl3aW6GAVYIRIYQQeiLBiE7lFpVSWrZJnjNW03gYjbaaESGEEEJPJBjRKWv3VV9PxzfJg8qraYxGbO3gJTMihBBCTyQY0akMW/Gq4/UiULnpmbSDF0IIoVcSjOhU+SZ59VjWS+XVNBWX9krTMyGEEHoiwYhO2Rqe1afHCBX2psHa9KxCO3gJRoQQQuiIBCM6Vb6st37BiJUtM2IoD0ZkmkYIIYSeSDCiU+WZkfrVjFw4TWMygiztFUIIoUcSjOhUg1rBUzngkKW9Qggh9EqCEZ2yBiP1aXgGoGG/msZYoWZEMiNCCCH0RIIRncoom6YJcdI0jYcEI0IIIXRKghGdyiwrYK1vZsS2msba9MxgsO3kK6tphBBC6IkEIzqV0cClvbamZ1QuYLVO4QghhBB6IMGIDmmaZsuM1LvpGReupqnQgVWmaYQQQuiIBCM6lFdsptisAoaGtoO37dpbYW8ayYwIIYTQEwlGdMjaY8Tbw4hvPTbJgwqraarYtVcyI0IIIfREghEdqris15rZcFSlvWkM0g5eCCGEPkkwokPpOUVA/VfSQIXsR1ksY9eBVdrBCyGE0BEJRnTo1PkCAGJb+Nb7NiqvpikvYJXMiBBCCD2RYESHTp3PByC2hV+9b6PyahpsNSNSwCqEEEJPJBjRIWdkRi5seiZLe4UQQuiVBCM6ZA1G4hqQGbFN01gzI1LAKoQQQqckGNGhk9ZpmtCGZ0ZsS3tN5e3gJTMihBBCTyQY0ZmcwhJb99VWIQ0oYMW+6Znd0l6pGRFCCKEjDgcjq1atYsKECcTExGAwGFiwYEGNxyckJGAwGCqdUlJS6jvmZu10ppqiCfHzJNCnft1XoXKfEbW0V30v0zRCCCH0xOFgJC8vj/j4eN577z2Hrnfw4EGSk5Ntp4iICEfv+qJwKqPhxatQOTOiClgVmaYRQgihJx6OXmHcuHGMGzfO4TuKiIggJCTE4etdbGzLekPqX7wKFVbTlE3NmAygadL0TAghhP40Wc1Inz59iI6O5sorr2Tt2rVNdbduxxnLeqGK1TQmaXomhBBCnxzOjDgqOjqaDz74gAEDBlBUVMTHH3/MyJEj2bhxI/369avyOkVFRRQVFdl+zs7Obuxh6oazgpELV9OYpIBVCCGETjV6MNKlSxe6dOli+3nIkCEcPXqUmTNn8sUXX1R5nRkzZvDCCy809tB0ybqsNy60gdM0XNj0DKTpmRBCCD1yydLeSy65hCNHjlR7+fTp08nKyrKdTp482YSjc63yzEjDgpFK0zRGY3k7eJmmEUIIoSONnhmpyo4dO4iOjq72cm9vb7y9vZtwRPqQXVhCVkFZjxFnTdPYLe2VaRohhBD643Awkpuba5fVOH78ODt27CA0NJTWrVszffp0Tp8+zeeffw7ArFmzaNeuHT169KCwsJCPP/6Y5cuX88cffzjvUTQTp8uyIi38PAnwblicaFvai+xNI4QQQt8cfsfbsmULl19+ue3nadOmAXDHHXcwZ84ckpOTSUpKsl1eXFzMX//6V06fPo2fnx+9e/dm6dKldrchFGdN0UAVmRGDtIMXQgihTw4HIyNHjqyx5mDOnDl2Pz/11FM89dRTDg/sYmTrMdLAKRoorwspL2A1IN3/hRBC6JG8O+lIUobzgpFKTc+M5Ut7JTMihBBCTyQY0ZHEcyoYaRvu3+DbstaM2BewKhKMCCGE0BMJRnTkxLk8ANqGNTwYqbyaxmhrBy+raYQQQuiJBCM6YbZonCybpmkT5rwC1vK9aSp0YJU+I0IIIXREghGdOJNZQIlZw8tkJDrYCQWslaZpKtSMyEZ5QgghdESCEZ2w1ovEhfqWBQ4NU3maxmDrwCo1I0IIIfREghGdcGa9CFS1tBesmREpGRFCCKEnEozoxImzZcGIE1bSQPlUjG3X3oodWGWaRgghhI5IMKITJ6zLep1QvApVZEYM0mdECCGEPkkwohOJZdM0bZw0TVNl0zPZtVcIIYQOSTCiAxaLRmKGNTPi3GCkqtU00mdECCGEnkgwogMp2YUUl1rwMBqICfFxym3WuLRXpmmEEELoiAQjOmBdSRMX6oeHyTlPiW2axm6jPEWmaYQQQuiJBCM6kOjk4lUoDzhsq2kMBls7eFlNI4QQQk8kGNGBE04uXoUqakZM0g5eCCGEPkkwogO2HiPOzIxQw9JeyYwIIYTQEQlGdCApowBo5MyILO0VQgihUxKM6MCZTBWMxIQ0fIM8K1tmpGKfEdtqGglGhBBC6IcEIy6WX1xKVkEJgNOW9UIVq2mkA6sQQgidkmDExc5kFgIQ6O1BoI+n0263ygJW2bVXCCGEDkkw4mKNMUUDVS/ttWZGzBYJRoQQQuiHBCMulpylgpFoJ07RQPmKGfumZ9IOXgghhP5IMOJip8umaRotM1JVO3jJjAghhNARCUZcLNk6TRPs5MzIBTUjFbrBY5Y+I0IIIXREghEXO5PVSDUjFyztNRgMtsDEYpFpGiGEEPohwYiLJZdN00QHOzcYuTAzAuXFrFIzIoQQQk8kGHEhTdM4bVtN49xpGmvNiDUzAuWBiSztFUIIoScSjLjQ+fwSikpVYBDl7JqRC1bTABgN0mdECCGE/kgw4kLWHiPhAd54e5icettVTtMYrZkRmaYRQgihHxKMuJA1GGnl5CkaqLy0t+L3mmRGhBBC6IgEIy5kDUacXbwKFfamqVgzIhvlCSGE0CEJRlwoOatxGp5B+YqZipkRk1EKWIUQQuiPBCMu1FgraaCamhGDLO0VQgihPx6uHsDFrFEzI9alvbKaxu3tOZ3FpuMZxMeF0KtVMF4e8hlCCNG8SDDiQuU1I42QGSlb2mukqmkayYy4i12nMrn5ow3kF5sB8Pcy8eaN8YztGe3ikQkhhPM4/BFr1apVTJgwgZiYGAwGAwsWLKj1OgkJCfTr1w9vb286duzInDlz6jHU5qXUbCE1W2VGWjVZZkSmadxJ4rk87p6zmfxiM23D/Aj19yKv2MxfvtnJgZRsVw9PCCGcxuFgJC8vj/j4eN577706HX/8+HGuueYaLr/8cnbs2MHjjz/Ovffey+LFix0ebHOSllOERQMPo4HwAG+n335Vq2lM0oHVbRSWmLnzs82czS2me3QQ/3vkMjb/fTTDOoVTUGLmgS+2klVQ4uphCiGEUzg8TTNu3DjGjRtX5+M/+OAD2rVrx5tvvglAt27dWLNmDTNnzmTMmDGO3n2zYa0XiQzywVhxS10nsU3TVChgNUifEbexZF8qx8/mER7gzZy7BxLo4wnAf27uy/h31pB4Lp+//7Sbd/+vn4tHKoQQDdfolXDr169n9OjRdueNGTOG9evXV3udoqIisrOz7U7NTUqWdYM859eLQNVNzzzKgh6LTNPo3rdbTgJwyyVxRASW/4208Pdi9m39MBjgl13J7DvT/P43hBAXn0YPRlJSUoiMjLQ7LzIykuzsbAoKCqq8zowZMwgODrad4uLiGnuYTS45Sz12Z+9JY2WbpqlQM1KeGZFgRM9OZxaw5shZAK7vH1vp8t6xIYzvHQPAf5YdbtKxCSFEY9DlGsHp06eTlZVlO508edLVQ3K6JsuMVHiKPWwFrDJNo2c/bD2FpsGl7UNpE+Zf5TGPXtERgwF+35si2REhhNtr9GAkKiqK1NRUu/NSU1MJCgrC17fqVSTe3t4EBQXZnZqb5LKVNFGN0Aoeqq4ZKS9glcyIXlksGt9tVcH3jQOqzwh2igyU7IgQotlo9GBk8ODBLFu2zO68JUuWMHjw4Ma+a11rqsyI3TRNWc2IFLDq16YTGZzMKCDA24NxtfQSefSKjoDKjpzPK26K4QkhRKNwOBjJzc1lx44d7NixA1BLd3fs2EFSUhKgplgmT55sO/7BBx/k2LFjPPXUUxw4cID333+fb7/9lr/85S/OeQRuyhqMNHrNSIWlvR7SZ0T3Eg6mA3BVj0h8vUw1HtspMpD2LdU0zo5TmY09NCGEaDQOByNbtmyhb9++9O3bF4Bp06bRt29fnnvuOQCSk5NtgQlAu3bt+PXXX1myZAnx8fG8+eabfPzxxxf1sl6zRbM1PGu0zEgVG+UZjVLAqnfrj6rC1aEdwut0fJ/YEAB2nsxspBEJIUTjc7jPyMiRI2t8M6uqu+rIkSPZvn27o3fVbJ3LLaLUomE0QMtGaHgGVa+m8TBKAaueZReWsPt0FgCDO4TV6TrxcSH8uP20BCNCCLemy9U0zZ214VlEoA8epsZ5CqpaTVPeDl7o0aZjGVg0aBfuX+fNE/vEhQCw42SmZLyEEG5LghEXSG7kehEoz4xUtZpGClj1ad3Rc0DdsyIAXaMD8TIZOZ9fwsmMqvv2CCGE3kkw4gIpWY23W6+VdWlv1dM08glaj9aV1YsMbl/3YMTbw0T3GLX0ffvJ840yLiGEaGwSjLhASnYR0LiZkarawRuMkhnRq4y8Yg6k5ABwqQPBCJRP1ew8meXsYQkhRJNwuIBVNFyTZEas0zRVdmCVzIjebDimpmi6RAbSMtCxoubyupEKmRFNg/0/w/FVcGYHBEbBuNcguHJ7eSGEcDUJRlygvGakcbqvQnnAUXGaxiTBiG6tr0e9iFV8WTCy50w2JWYLnlop/O8x2DnP/sCkDXDjXGh7WUOHK4QQTiXTNC6Q0sg9RqC2pb06D0YsFji9FTZ/DCtmQMZxV4+o0W1NVFmNS9qFOnzdtmF+BPt6Ulxq4VDiafjqzyoQMZjgkvth0gcQ1Qvyz8Lca+FYgpNHL4QQDSOZkSamaVp5ZiSoCWpGqKrpmY5rRorzYd6NcGJ1+XmbPoJbvobWl7puXI0or6iUAylqs7t+rVs4fH2DwUDXqEB2HE8h8tc74dwW8AqAG+ZApyvVQd0nwk8PqKmbhY/AQ+vBO8B5D0KIplBaDEYPMMrn6OZGntEmdj6/hOJSFQxENmIwUtVqGpPRUN3h+mAuge/uUIGIpx90HA2RvaAgQ32i3/ezq0fYKHaeysSiqUxZfYuaowI9meX5HuHntoB3ENz5S3kgAuDlB5NmQ0hryEqCZS84afQXEXMJpOyGHfPgyFKwmF09oubPYoGDv8OXf4Y3u8HLEfBOX0jb7+qRCSeTzEgTSy4rXg0P8MbLo/FiwapW03gY1V4nuuzAqmmw8GE4/Ad4+MLtC6D1IJUp+fE+OPCL+hraTk05NCPbkzKB+mVFrG7LnM1A02ZKDZ543DwPYvpWPsg7ACb8B76YpLJN3SdB26H1vs+LyvYv4ffpUJRdfl5QK+h3B1z6IPgEu25szdXpbbBgCqQfsD///AmYOwHu/BVadnHJ0ITzSWakiSVnWotXG6cNvFWlpmelRQSUqhdSXdaM7P4eds1XKdgbP1eBCKhP9Dd+Dh2vhNJC+HYyFDavJazbk1S9SN/WIfW7gW1fMDDteyyagS9j/gHthlV/bIfLoV/ZRpYLHoTC7OqPFVBapIqBF05VgYh3ELQZCr4tIPs0JPwL3o6Hde9KpsSZTm2BzyeqQMQ7CIY+Bvcug0e2qQ8jeekqIMk86eqRuicddmuWYKSJnc5UmZFWdWz3XV92u/YWnIcPR/DA/jvLLtXZH2LeOfj9afX9iGeg81X2lxtNcN1HEBwHGcdUBkWH/0z1oWka28oyI33rkxk5tRV+nQbAzNI/s9QwuPbrXPUKhLSBzCRY9ITj93mxyD4Dn10NW+cABrj8H/B0Ity1CKYdgOs+hvAu6v/rj7/Din+5esTNw8nN8PkkFfy1HgKP74IrX4TYARDWAW5fCBE9IDcVEma4erTuwVwCS/8Jr7WFF8PhpXAVYBfnu3pkNhKMNLFT59WTH9vCr1Hvx7Zrr2aB7+6E9P14aiXll+vpzXzx3yD/nHqBGfpY1cf4hcINc8HoqYowN8yu++2f3AQfXQ5v9YA3u6p/wpJC54y9gZIy8snIK8bLZKRnqyDHrpyfAd/eDuZizsWO5l3zJNJy6vC4fILguv+CwQi7voFd39Vv8M1Z4nr4cASc3gI+IXDr9zDiyfLCSU8f6H0DTFmngjuAde+oKQRRf+cTVQF7cQ60HQa3fa+yUBX5h8G1/1Hf75yvPqCI6mWfUVmkNTNV4GwpAUupmnr8eBScPezqEQISjDS5U+dVZiS2RdNkRozr37Ut5TRWcbnLHV+lpmcwwLXvgIdX9cfG9ocxZZ8+lzyrgozanNwMX1wHZ7ZB9inISVb/hPNvgRLX7+WyrWyKpkerILw9THW/oqbBL39RUwWhHci46h00jKTnFNXt+q0HwfCn1PcLp8KBXx0ceTOlabDpvzB3POSlqQD5/gToNLrq400eMHgqtBsB5iL449kmHW69FeWo/4Nf/wqfjoNvblM1Gi4dUy7M/z9VsB7dB/7vG/Dyr/rY2AHQYRRoZlj9ZpMOE4CcFP1PERVkwvKX4d2BkLReTXf9+ROYtl/V5AVEQto++OQqOHvE1aOVAtamVh6MNE1mxLDvZ8CgPl0UlXfotGDBhANvfo1B02DJc+r7gfeqYKM2l9yn/rH2/qgyPvctV91Fq5K0Eb66vvxT1ugXVEDy0xQ4uhy+ukHVo/g53tvDWbYlZgLQN87BKZqdX8O+BarG5s8fEx4SDpSv1qpTcfTwJyF1jyoO/uZ2GP8W9J188S6bNJeoAG/7F+rnHn+Cie9V/4ZoZTDA2Ffhg6FlXW9X11y340o5KerNe8fX6v+iov3/U0XNE99r+mXfmqaKVVP3gH8E3Dyv9t/7yGfg6DKVHRn+JLRo2/jjTFwHG96HA4vUz4MfUlPLrlwmX5QDR1dAyi5V41Scp1Z9Je9UATJAqwHw5/9CaHv1c1AMPLAK5t0EyTvgy+vgniUQGOmyh3GRvuq4Tvk0TVPVjKDewFv1x1hxZkYPszT7FsCZ7aonxoin63Ydg0GlaMM6qazAnGtUGrIiTYP176vLrPPO//eNCna6T4TbfgCvQLWE+IPLVEreRayb2/VrE1L3K51PhEVlWY2R06FVP4J9PfE0qaXbZ3PrmB0xeaiprz63qk+Y/3sM/hMPCa9B+kEHHkUzUJyvPpVv/0JNX41+Aa7/rPY3RKvI7jDgbvW9XpdNH/gV3h+sVlIV56j/oSGPqqZ4vW8GDOp/8uiyph/bqjdUIGf0hJu+gOBWtV8n7hJof7maclj3TuOPccfX8Nk4FbRpZnVa9w68N6jsvCZ+Uc1Ohm/vgNfaqenaVW/Auv/Alk/g1CYViLTsCjd+AfcuLQ9ErAKj1PRji3aQmQjzblCBjYtIZqQJ5RaVcj5f1W00djCilaigx+jpr97of51mP03j6uW95hJY9qL6fsgjENCy7tf1DoRbv1PzoOeOqCLDq9+A2IFwciOsf1dN/wB0u1b116j4ptJmMNz9m8qsnDuiXmBC26t/XJOHemPyDy97sRtZ+Z/YSXKLStl3Rq1m6d+mjpkR6/RMcQ60HgyX/QUAo9FAeIA3yVmFpOcUEVPXAmmTB1z7ripoXf+eKmpN+Jc6hXVUwU6v6+vz8NxHQSZ8fbPKuHn4qpb5ncc4fjvDn4Ktc+HUZjXl0aqf04daL+ZSVZe16UP1c1QvuPIl9bdt7UPU5xZVT3B4sfp9NKX9v8CKsrqb8W851txw6KNwbIVajTdmRs3TvA1xfDX8/Ij6vtcNMOyv5QXgmUlqmqvTGLXMO25Q3YPY+tA0lQ36/enylYWhHdQ2D96B4OGtXsta9VevXRV6TVUS0FJ9OPvkKpVJ2fcz9L218cZeAwlGmtDpsimaED9PAn08G++OSouwFOWCEQx9b1VvrJ7+VPyTdHnNyPYvVOGZX7iac3dUaDvVZ2DuBDh/XE3HVGTyUvUlA++t+p8xqpeqBfj1CVWzknFUnSra+bVqqT51E4R3dHyMtdiaeB6LpgLT6LruU7TrW/XJ1eStgghj+VRbRKAKRtLqWjdiZTTCyKdVULj/f7D7WxXMnTsCP9yjnqfhT9b8ouauctNUijplN3gHqwxamzqsSKpKYKSa2tn9rco+/OkD5461PgqzVNB9dLn6ecijcMU/1BvWhbwD1dfi3CYbHim7VWdgUFsXWJed11W7ERAQBbkpcGQJdL3G+WNMP6iCDUuJmsb600fqfyaim5r+Xf0mrH1bBXKHF6upU99QQIPAaPW4et9Y9e/cUeYSWPQkbP1M/RzTDya8DdG963+bYR3g/75VdXUuCkRAgpEmdTKjaaZo2P4lmmYGTBh736zO8/KzC0ZcuprGYlb/vADDnyh/EXRUizZw9++Q8CocX6lWMviEQN/bVBAS2q7m63sHwnUfwlUvqUKu9EPqfE9f9Wlnyydqlc/ZQ40SjGw+ngE4sB9N3jlYPF19P+LJSmOy7vZb5yLWC3n5QfxN6lSYDateV2noFa+oNO6E/9gFP7qRnQxr3lIpZp9gldHqcV3twdP5RNUALuMY+LeE239qeEO9QQ+oYGTPDyr74EjGz9kKs1Rxatpe1dH4zx/X/GZt/T9sqlR9ZhJ8eb0KftoOKy9Od4TRpDJ3699Vgbqzg5H0gzBnPBRmqszrnz6wr6ny8oNRz0Lvm9Rr2vGVkHVSFT+D6ofy88Pqf2j8LOgytv5jyc9QHaqPr0ItNf+7yoyanPA2Htu/bjV7jUiCkYbQNIc+LdrqRUIasXjVYoEN72MpyxIarelCTz+MFQpFXNr4bP/PKnDwDVUdLBsiKKZ8mV/e2fI0pSMCItSp/Uj7809tVingRmqytqksGBlU12Bk2T/Ll0APqbwE2hqM1Gl5b218guCql1VR4KIn1cqLkgL404dgasSsnqNOblafWnNTys/b+IFarnztO9UHA2kH4Is/Qc4ZCG4NkxeoT4gNFTtAfVo9sw22zVEZJVewWOCH+1QgEhClMj4xfWq+jrUIsymCkfwMFYjkpkDLbqpOpL5/V71vVMHIwd/U/6qzuuGm7oPPr1UBRWRPuOUb9UGlKi07w6T31HtC1sny14xjCap+LecMfH2Tal1wxbOOP9azh9WS54xjqsbuz580LLDRISlgdVRhFqx8Xe2V8lpbtWyqOK9OV22SZb2HF8O5I1jKgiTb3jRe/nYFrC6bptE0WFsWPFxyn/pk4Sz+4c5JhVpZX9QaIRgpLDGz41QmAAPb1iEYSd2rAgJQ8+pVzI23DFT72tQ7M1KVgfeW93fZ8wPMvxWSNuij2+i2L2DO1eVvaKNfgEseUFN0h36D9y9V+8hYLvhbP7VF1QnlnFFz6/csdk4gYjWobNph8yeu62eT8C/1WuDhA/83v/ZABNTST2j8YCQzSf3+zx5ULfVv+6FyLxFHRPVWz6O5yHn7V+39SdVR5KWrbNkd/1P9TWpjMKj9n6J6qdOQR+CxHTDoQXX52rdVz6MTa+s2jpJCVTj731EqEAlpDff80ewCEZDMSN2VFMKOr1SXxfyz5ecXZqrCnzZDar2JJglG1r8HgGbyBq2kfNdeT/s3fZcFI4nr1KdGDx8YeJ9rxlBX1mCk4n4kTrLrVBbFpRbCA7xpF16HYrclz4FmUQW51RT4NXiapjrdr4WbvlQV+9Z5cb8w9WIb3kV9Mo0d4Nz7rIm5pKwg8yP1c9fxKn1unWboN1ntY5S2Ty0X3fyJSt8Hx8K+hWU9VTSVwbjtB+cv7e7xJ1j6ggp2tnxSv5qohjj4u1pZAaqeoKp9iqrSFNM0p7fC17eo7qmB0er3X5eVMzUxGNTf4LIXVRO/frfX/7ZKCmHp8yq7Bqr1/01fNuxvxMMbxr2mCs7/9yik7lZBdOvBEB2vppbPHlJToQaTOt7DW30AOLlBFRYDxF2qxuLKqb9GJMFIbdIOqHXlexdAUdkn5PDOcOlDqogoeadqftOm9ps6ldnI3VfP7FDLVY0eWEyeUFpSvjeNp68+0mDWJXjxt+j/n8qn7JNiI2RGNp8on6Ix1DbVd3S52iXW6AGj/1ntYRG2aRonByOgPond9Zt6kT70h5ouOpagTps+UkV6o56rud9C5klVHxDepf69TLJOww/3QtI69fPIv6mpkIq3F9UT7l+p/m9XvaG6qJ7eYn873SeW9dOoZ71STTy84fK/qVqBVW+oGqam2kgvJwUWPqS+v+QBiL+57tf1KnvuGqOAtbQYVv9bFXtaStVU463fqgDRGXrdAMteUq9/547WL9OVvAt+vB/Sy3YEvuwvagsAZ9RkAPSYpGpjVrysthhIWq9OtQmKhf53qpVDzsz86owEI9UpyoWVr6kXNEupOi84TqXdBtyt5vxObS4LRpLqdJO2zEhoI2VGNpYt3etxHVrhLqBsbxpQ0zQVDnVJZiTrlPpUDU3/abE+GnGaZmNZvcjAtrWkpzVNfcoGlUmq4UW20TIjVrEDIPZjlZk4s0NtYnYsAfZ8r5aNHlykivQqdistzofd36mVSdYXXt9QtQyx63gV5NTljdpcopqz/TJNdej0Kis+rq5g0cMLLntcFRbu+EoVIp4/DhHd1d9eY+/2Gn+LqmNIP6BS86Oeq/t1i3Jh2+dqWWbnMXWvS7NY4KcHVaAY2UsVZjuisTIjmUmqh0vKbvVztwkqEHRmgBbSGjpdpV5ftnwKY15x7PqHl6gxmotV07WJ71XeI8sZ/MNg/EwY/LBqQ5C6V72+hHcuL7gvLVLjKC1US+7bj9Rn4biTSTBSldPb1HK4zET1c5erVSakzVD7T2AhrdXXrNqDkZzCEjLLeow0yiZ5hVlqnhPgkvvRVqk3e9unbk8/1y/t3TFPTTW0uQzCOzX9/TvKJ0R9dXIwUmq2sC1RpV4vaVfLPPTxlapDoodvrcWQLQPKgxFN02rPuNSXyRPiBqpTv9vVcsD/PabedL76swoyIntAST5s/0oFDwAYVAFgQYYqYt7/s6rvaH+5mgpqe5n6FGgwqv+p9IPqlLJLvVkUZqqbiY5XDcnq8uk3KFqt2GpqJg8Y9bzadmD9+9DzetUYrSYWi1pmvvSF8oLcTlfBuNdrXxkGKvNwbIX6W7n+E8c/RdsKWJ2YGUnaoOqM8s+qIPSaN9U0VmP8bQ68RwUj279Uy5erKza90MlNqgOxuVj1Cpn0vqo/a0xhHZxbp9QMSDBSUWGWevFc+rz6wwxurZppVVcsFBynvtZhjwLrbr2N1mNkz49QWqAKuWIHlO9NY52mKVtVY9BAM7hgNY3FUt5muyFzuk3Ju3GmaXaczCS3qJQgHw+6RNUyTWCd1up7W60FdNbMSLHZQnZBKcF+TbTqpcMV8NAGtQ/Ghtkqg3Hgl/LLQ9qobGLvG9US2jM71JvGvp9VEaO1DgXUPLnRQ/0tX8gvXP0eLv+be6Sru4xTgXfiGvhsLNz8NbQdWvWxSRvh92dUPRWooCw3FQ7/oeqs7vhZNbGqzuaPyxuHjXu1fpkfWwGrk2qkTm5SfYDMxaq+6Jb5zpuWqUrH0eoDYmaSej2sS8+MtANqW4jSAhX43fyVvlaLXUQu7mBk8d/L214XZaviKuuUTNfxKlXnG1L99a2ZkTpM05zKaOTiVetKi763gcFQORgpK2A1oKFhaPo+IydWqd+Td5AqwnQHjVTA+suuZABGd4/EZKzhE2LqXlUrYjDWaVrLx9NEkI8H2YWlpOUUNl0wAirYHTtDzd0fXKSWbpYUqEC+63j7NLM1q3LFP9Sbwf6fVbO19APqjctSojImYR3Vm2p4F2g3XBXuulO62mBQS1a/vlml5L/4k6rh6DxGFQAXZqlp3iPLVKEiqLqN4U/CpVPU/8uCh1Rr769uhHuXVO4GrGlqSufXsuzP8CdVfUF9OHOaxlyismXmYvUmf8Ocxu1KCupvY8DdsPSfKjirLRgpLYLv7y7vIXLDHAlEXOjiDkZOblL/6BWFd1bFeNV17qwopCwzknVKffKvoSivUXuMpO1XBXpGj7I9JsqbmpXXjKj7NQIWXDBNs60sK9Lreucu521MjVAzYrZo/LpbBSMTesfUfLA1K9Lt2rql6VHZkezCUtJziugU2QjFmbVp1c+xNugRXdVpxFNquXD2GfUGFtLGeYWDruQXCpMXwvf3wMFfYdtcdarEoN48r3iufLOy8E5w+49qu4OUXWr36fEzVddRg0GtFlr8dzU1A+p16/K/13+szixg3TBbjc83VPWmaexAxKrv7WrF45ltcHhp9bstg2qWmLZXZdxu/rrpxiiq1Az+2xtg+JPly3SNHio6ruOLPqDWyBuMan17XnqNOx6ebMxlvdasSOexthUq1r1nyjMj6h/NqAFNPU1TcF598gXH2z27UiOsptl0PIP0nCKCfT0Z2rGGeemcFFX4CaqFdx1FBPpwND2P9LpulqcnRlN5gN+cePqqJZnHlsOhxaro11yi/r5CWqtpLusUw4W8A9VmZp+MVgW4X0xSTcxKCspX95m81V4pDW3Zb82MmItV1qC+U2FZp9QbPcCVLzbtrtj+4eqD5Ib31R5OD62veoXXyU2wdpb6fvxM/a/suwhc3MFIQ6ulTZ4QGKO2pc9MqjEYOZKmPm20a+nk6NtcojZNAvWpoIxt115bAasKggwXXN4kDv5WtoNkN4ju03T321C2zEi2w912q/O/XWqH4bE9ovDyqGF567Yv1JRh3CCH2jTburBmu2Ew0pwZjSrg6FjDJ/XqBEaqZdWr31IbwlmLW42e6vbGvOKcYkivCm/aRbn1D0ZWvgYleaovRh8X7HVy+d/Vh5+sJJUlGXtBm/ms02p6RrOo1Vbd3WTauJnTResJt2abqqm5buRwqpqH7ezs1PnRFSq74xdue6GrWA9yYQGrtSV8nTIjuemq0+zGjxo2xr0L1NfGqqJvLNZgxFKiPok2UKnZwu971BvJ+Pjo6g+0mFUfAoAB9zh0H9ZgxFowLZqJ4FjVefeJg3D7AnhwDfztjOqu6qxVGSaP8uaI9a2TKs6HPWWr+kY9W/9+Mg3hHaCyHQAbZ5dnZUHt7/TFJNWyPayjakYmdEGCkYaqw4qanMISzmSpttCdI5wcjOz+Vn3tdb1tjr1i1uPCDqwOZUbWvKWWllprF+qjMKt8x9DuE+t/O67gFaCm4cApUzVrjpwlI6+YMH8vBrevYWXM4T9Uts031OHfWb/Wqm/Jgh2nySsqbchwhR55+kKHy9XqlCq2BGiwhhaxHlwExTlqyql17V2pG02nK1XWQ7OovYt+flRNHX16lep2GtRKbYzYkDb0wqkkGGmoOqyoOVw2RRMR6O3cFQ5FObC/bAllrxttZ1fMetimaTy80QxGWzBS62qa3HTYUrZNdfYpNR1UHwd/U5mFlmWFiu7EYHDackdN03hn+REAJsTH4GGq4V9vy6fqa99bwdPHofsZ2zOKtmF+ZOaXMG9j3ZrxCWHT0CLWXd+or71vck1WpKJr31FNKkEVDSfMgHNH1Eqm23+qukZHuIwEIw1lm6apPjPSaFM0B35V6+NDO9itYKgYaNiCEYMBs4efbbO8Wqdp1r9T3utBs9T4+Gq0b6H66m5ZESsnFbH+sS+VrYnn8fE0MmVkDWn18ydUgy+A/nc5fD8mo8F2+x+tPkZhiQ42tBPuoyGZkdw0tUwZbKv6XMrDW+08Pfln1cW0x5/UXj0PbWz8DrzCYfUKRt577z3atm2Lj48PgwYNYtOmTdUeO2fOHAwGg93Jx8exT3u6VodpmkOp6lNGp8ga9u2oj4qfQirUYlhX0kCFaRrA4uGLoSwIqXGaJu8cbPq47AbKMjnnTzg+vsLs8hen7pMcv74eOGF5b6nZwuu/HwDgnsvaERlUw9//1rmAprqS1rMW4E99Y4kJ9iE9p4jvtp6q122Ii1RDgpHd34NmVs3Zwjs6d1wN0X6EWl59wxzVg0VWzuiSw8HIN998w7Rp03j++efZtm0b8fHxjBkzhrS0tGqvExQURHJysu2UmJjYoEHrSkjZDnmZSWrFRRUONUZmJCdVLREE6H2D3UV2NSOGisGIn+0Jr3GaZtNHqho+qreanwY4X4/n7NBitYomrBNEdHP8+nrQkJbw5hIozuO7rac4mp5HCz9PHhhRQ4BRWlzepXbA3Y7fXxkvDyP3D1fNsT5IOEqJ2UU7NAv305BgxPrhKP4W541HXDQcDkbeeust7rvvPu666y66d+/OBx98gJ+fH59++mm11zEYDERFRdlOkZHVL4F1O9b2xiV55Vs9X+BwWWakszMzI3t+UNMnsQMrdWWscpoG0CrsT1NtZqS0WO1GDDD0MWhR1nelPpmRfQvU1x6T3GsVTUX1bQmvafDfK9De6s7SxT8D8PAVnQiqaSuAA/9T/WoColQr8Qa4+ZLWhAd4cTqzgJ93nGnQbYmLSH2DkexktYcSBvfNggqXcigYKS4uZuvWrYweXb5W3mg0Mnr0aNavr34r5NzcXNq0aUNcXBwTJ05k7969Nd5PUVER2dnZdifd8vRRuzxClUWsWQUlpGSrlTQdnbmSpuIUzQWqy4xoHr7lBazV1Ywc+EXtieEfoTp/tmirznc0GCnKKa99cNd6Eaj/NE3KLkjZhaEwk/+Uvsj4oKPcdmktBXObywL6/nc0uC21j6eJey5TQer7CUewWJq4/b9wT/UtYLWumIvpI9Mgol4cCkbOnj2L2WyulNmIjIwkJSWlyut06dKFTz/9lIULF/Lll19isVgYMmQIp05VP5c9Y8YMgoODbae4OJ13ZaxhRc2RNPUJIyrIh2BfJ62kST+kPoUYPVRR1gWqrRnxLC9grTYzsvkT9bX/nWrpYH2DEesUTWgHiOzp2HX1pL770xxYBECpZsTfUMQs8yt4n91f/fHpB9WGagaj07rU3nZpa4J8PDiansfve6v+/xTCTn0zI0eWqq8dr3TueMRFo9FX0wwePJjJkyfTp08fRowYwY8//kjLli358MMPq73O9OnTycrKsp1OnqznSo6mYg1GqnjDbpTiVWtvkQ6jqtzquqZpmhqbnqXuK3tDNJVvtlXfYKTiKhp3naKB+q+mOaiCkedL72SHR288zIWqAVN1Nv1Xfe08zmk7mwb6eHLnUDXN9u7yI02/OaJwP7ZgxIHg22Iuz4zUp8OsEDgYjISHh2MymUhNTbU7PzU1laioqDrdhqenJ3379uXIkSPVHuPt7U1QUJDdSdfCO6uv1h2AK7AWr3apqXj1WAIseQ6K82q/L02rMEVzY5WHVDdNY+uuSDWZkS1lWZGuV0NwK/W9NdAqzKy2JqaS4rzyKZoek+p2Hb2qzzRN1ilI2YVZM/Cb+RIYOV2dv3dB1c9x9hm18yrAoPsbNNwL3TWkLX5eJvYlZ7NkX2rtVxAXN1sw4sA0zelt6vXBJ1itpBGiHhwKRry8vOjfvz/Lli2znWexWFi2bBmDBw+u022YzWZ2795NdHQN7bDdjbWZV3rlNHytK2ksFrVN+Nq31dbXtTm5UU0HeQVAl6urPMSu6RkVshKeFVbTXJgZMZeooliwX8nhHQD+ZXPAdV1Rc/gP1aOkRVu1IsedVdyfpq4O/gbAVq0zoRExxA8Zq4qMi3PLM0YVrZmlprRaD1Y7sjpRC38v7hzSFoC3lhyS2hFRs/pM01inaNpf3jx2WhYu4fA0zbRp0/jvf//L3Llz2b9/P1OmTCEvL4+77lINmiZPnsz06dNtx7/44ov88ccfHDt2jG3btnHbbbeRmJjIvffe67xH4Woty5atph+0W95rsWjsPaPexLpEVROMJK2D7NPq+03/haSNNd/XtrKln92uBS+/Kg+pmPWoOE2DV4WmZxem7BPXqsyHXxi0HW5/mXWqJrOOwYh1L5ruk9x7igbqt5qmLBhZau7HpD4xGIzG8g3Dtn9lf2z2mfJ9aEY+0yi/r/uHtyfQ24MDKTn8tkdqR0QN6lPAaqsXkSkaUX8OByM33XQT//73v3nuuefo06cPO3bs4Pfff7cVtSYlJZGcnGw7/vz589x3331069aNq6++muzsbNatW0f37t2d9yhcLayDKiYtzlUp+jJH0nPJzC/B19NE95hqppqs28R7+AAa/PyI2r67KgXny7MX1pqOKlgDDbspGgBP/+qX9u5Ty0/pek3lTzeO1I0U56vMCLj3KhorRwtYC7PRjq8CYKmlP9fGl013xd+iilMT10DGsfLjV7/ZaFkRqxA/L+6+TNWOzFx6CLNkR0R1HM2M5GfA6a3q+46jGmdM4qJQrwLWhx9+mMTERIqKiti4cSODBg2yXZaQkMCcOXNsP8+cOdN2bEpKCr/++it9+/Zt8MB1xeSpdoAESD9gO3vT8QwA+rYOwbOqvUhKi8uzCH/6QC2nPXsQNrxf9f3s+FpNf0T2hLhLqh2ONdAwXvj0epZ3YLWbprFY1JJeUBmXCzkSjBxZCiX5qtYkphk8z47WjBxdhsFSwlFLNCFx3WkdVpa9Cm6l0tgAS19QQdv692BzWafbRsqKWN0zrB3Bvp4cScvlp+2nG+1+hJuz7cVUx2Dk6HJAg4geEBTTaMMSzZ/sTeMsLcvqRtLK60aswcjAtqFVX+foclX4FRCpgoBRz6nzt85RAUJFmla+gdqAu2t847IGGoYLjjF4+VfdgfXUJtVbxDu46k/njgQj1kZn7r6KxsrR1TRlUzRLLP2Z1LeV/WWDH1Jf9y2Ad/rB4r+pn4c9ofbOaERBPp48VLZnzWu/HyBXdvQVVfEum6apazBim6KRrIhoGAlGnMXa7rwsM6JpGptPqGBkULtqghHrFE3PP4PRpL56Bao3/cQ19sceXwXnDqvLq1lFY2XLjFwwTWPw8rfVjJRaKmygtv9/6muXsVVvS25teV9bMFJSoPqLAHSv3P/ELVnbwZfk175zsbkU80H1+Jdr/bmm1wVF2h1Hq91CA6Mhp2wqc/hTcMU/nDvmatw5tC1tw/xIzynineWHm+Q+hZupOE1T21Jwi6V87ympFxENJKXPznJBZuTU+QKSswrxMBro27pF5eMLs229KOh1vfrq5Qe9/qwyI9u/hHZlhaSaBmtnqe/jbyp/wahGtcGId3nBa6l1vxJNg/1l9SLdJlR9g7YC1iTVU8Boqvq4I8tU3UxQrN0uwm7Nu0KtT2E2+IdVf+zJDZiKMsnQAvBqO4iwAO/Kx3S4AqasU7Uioe1rzXI5k7eHiWfHd+eeuVv4dM1xbh7Ymnbh/k1y38JNWAtYNTOUFoKnb/XHpu6GvDTw9Fc1TxfIKijhp22nOJNVSGZ+MYE+nvSICaJPXAjtWzp501Dh9iQYcZaICitqLBZbVqRnq2B8vap48975tfq0Hd4FYiq8cfedrIKRfQvh6jdUzcLO+WpKx+QFg6bUOhTrFIzdsl7sp2nM1gLW9AMqyPDwUU3UqhIUoy4vLYSM49XvyNlcGp1VZPJQL7YleWpKraZgpKzr6nJLP4Z3qaHvjl8ojHnFqcNMzE5ke9p2ru1wbeXC5Qqu6BrByC4tSTiYzvQfd/HVvZdiMjaT50o0nFeFIKEop+ZgxLakd4RdRrW41MIXGxJ5Z/lhMvOrziZ2jQpkQnwMNw6Io2VgFUG7uOhctNM0mqax+nA6D36xlcISc+1XqE1oezB6qjetrJO2epFLqpqi0bTyjpuX3Gf/xt2qn1oqXFqoClZzUuD3p9VlI5+p09bc1nbwF74pGb38bR1YzdaaFOvOv22GVLtUGKMJInuo75N3VH1Mcb6tXqJZrKKpqC4rajQNS1mma4m5HyM6RzTBwMq9vOFlnl37LBuTa14abjAY+OeEHvh5mdhwLIOPVh2r8XhxkTEa1VQw1F43YpuiKf8Qo2kaj83fzku/7CMzv4SOEQHcN6wdT1zVmTuHtGVg2xZ4mgwcSMnhjcUHuey15fzz572kZBU20gMS7uKizYyUWjSe/n4XZ7IK+W7LSW4f3LZhN2jyhPBOkLYP0g+w6YSK9i+pqnj1WEJ5/Uf8zfaXGQzQ73ZV3Pj706ozq7kIovvAkMfqNJTqMiNG7/KlvSXWmhFrMGJd6VGdmL5qCd+Z7eXTShUdXATFOWoVTezAOo3TbfgEQ86ZmotY0w9iPH+cIs2TQ/4DnbtDcx2czFFbJqTk1d5HpG24P89P6M7TP+zmzT8OclnHcHrFBjf2EIW78A5Q/8s1BSOFWaoBI9hlVN9bcYTf9qTgZTLy/LXduWlAHB4XrCTMyi9h8b4UvtqYxM6TmcxZd4Lvt57iias6c/vgtpKpu0hdtJkRT5ORB8tWF3yw8hjFpdVsHOeIsrqR7KRdHEtXbb8HtK2iXsSaFelzS9X1H31uhTaXqd4l5iI1PTPxvTp3N7RmRi5cTWP08sNg3SjPoqmCzBNlhbK1reaI7qO+Ju+s+vKKuwgbm9mfVV1W1JRlRdZaejCgc1yl331j0jSNjEKVicsurls/lBsHxDGuZxSlFo2H5m0lLUc+mYoydek1cnwVWEpVS4NQ1cNm+YFU3lxyCIAXJ/bg1kFtKgUiAMF+ntw4II4FDw3hq3sH0ScuhNyiUv75v33c8ME6zmQWOP0hCf1rZu8ajrHOV57OLGCBM3ovlAUj5/YsxYCFS9uHEuJ3weqUjONwqGw6Y2A1XWh9Q+CuX2H6Kbj7D3hwLUTVfefb6pqeGb3La0ZKLBY4tUUVnPqF176zbkwf9TV5Z+Vlx7lp5Snb3hdkepqDurSEt3ZdtfRneOem3UI9vzSfglL1Al7XYMRgMDDjul7EhfpyMqOAOz/dTHZhLauFxMWhLl1YL+i6WlBs5qnvd6FpcOug1tx8Seta78ZgMDC0Yzg/ThnCSxN7EOjtwbakTMa/s4Y1h8829FEIN3NRByM+niYeGN4egPcTjpSvMKmvjqPRMNAucwNveH7E5Evj7C+3WFSHVc2ipkVadqn59jx9ofUgaNnZoWHUtLTX+nndbDFXmKIZUXs2o2VXMHmruonzx+0v2/ODqr5v1b9ONS1up7bGZ7lpaKc2A7DC0pfLOlbeSbkxnS0of+HOdmC31RA/L764exDhAV7sS87mvrlbyJP+I6K2zIimVVrS+9XGRM7mFhMX6svzE3o4dHdGo4HbB7dl0WPD6NkqiIy8YiZ/upEv1p+o5wMQ7uiiDkYA/m9Qa1r4eXLiXD6j3lrJ2FmrmPDOGia9t5bbP9nI9B93MTvhKOuPniO/uJYX6tj+bB3wOqWaketNqxi7e5p9b47178CJ1Wp1xjVvNtpjsgYjF9aMqI3yygpYSwvh2Ap1fl0abpk8y7MzZ7bbX7bza/W1OWZFoML+NJlVX37odwxo7LS0JzK2PS38q+jV0ojsgpE6Zkas2ob7M+euSwjw9mDj8Qxu+GC9FBNe7GzBSDV/S+kHIeuk+nDSZiiFJWY+LCuEnjqyI14e9XtbiQv14/sHh3BD/1gsGjy7cC+v/36g8j5aolm6aAtYrfy8PJgysgP/WnSAxHP5NR7rYTTQv00LRneL5KoekbQJq9yj4dWTPQkreZT3vd/FdHgxvLMcekxSWY4dZW/aY2eo/WwaibUDa6UlnhUyI1r+eTVNA3Xv/hndRxWxJu8oL2JN3qlORg/VtK05alHW9O1sNY3CrF1Xzf0Z3qlpsyJgH4zkFDuw22qZnq2C+fLeQdw7dzP7krP50/tr+e/kAfRsJUWtFyVbMFLNNI11iqbtUPDyY/7a46TnFNEqxJfr+sU26K59PE28fn1v4kL9eGvJId5POMrZ3CJmXNdbClubuYs+GAG497L2DG4fTm5RKaUWC6VmjRKzhcyCEk6fL+BIWi5bE8+Tkl3IxuMZbDyewSuL9tMnLoRr42MYHx9NCz8vvt6UxJbE83gYB5F127WErntZ9QexdloF6Doe+k1u1Mdjy4xcWERpNIGmzvNI3a6mVkI7qBUwdWGtGzmzo/y85S+rr90n1dyDw51F9VZfqyreLc5HO7oCA6pe5J9NPEUDDcuMWPWJC+Gnh4Zy52ebOJqex3Wz1/HypJ7cOCCu9iuL5qW2aRpbvciVFJWa+WClyopMGdmh3lmRigwGA4+O6kRkkDfTf9zNt1tOkVdkZuZNfZxy+0KfJBhBzVnWZWlj0rl8lh9IZen+NNYdPcuOk5nsOJnJy7/uI9Tfi7O5xQD8qW8rQjvEQ4efVNV54nq1Y6uXH/S9vdEbglW7ay9AWW7EI2Wb+tGRPVFsK2p2qXnjpA1qh16DCS7/W73Hq3vR8err+eOqbsSnwt/K8ZUYSgs4pYVz3NSGvq1Dmnx45wrO2b6vbzACKk3+40NDmfbNDpYdSOOp73ex6XgGz03oTpCPpzOGKtyBVw370xTnQeJa9X3H0Szdl0ZKdiERgd7cMKBhWZEL3TSwNUE+njw6fzu/7k4mr7iU2bf2r7qJpHB7Eow4oHWYH3cObcedQ9uRnlPEr7vO8PPOM2xLyuRsbjHhAd5MGdmB2y6tkGloN7y8rXsTqbZmBLCUlQl5ZhxUZzgSjER0KytizVJBVsKr6vy+t9U67aRpGvuTc1i0O5kT5/II9vWkZaA3V3WPontMUI3XdTm/UNXiPvsUpOxR6WmrA78CaopmYNswvD2a/oWyvgWsVQn29eS/kwfw3oojvLX0EN9vPcXaI2f51596cXnXpm3kJlwkuGyDx3NHKl92Yi2YiyG4NYR34vtfVOH2DQNiG+Vvf1yvaD729uCBL7aQcDCdOz7bxCd3DCBQguNmR4KRemoZ6G0LTJLO5XM0PZdL24fpImqvtmZEnVt2kFlla9oNq/sNW4tYT2+Fz68tO88bRjxd49WOpefy6Pzt7Dld+Y1y1tLD9GoVzIMjOnB1r6gm7c/hkOjeZcHIrvJgpKTQtq/PH5YBXNbBNdNUF07TaJrWoN+j0WjgkVGdGNwhjCe+28mJc/ncNWczwzu35G9Xd6VrlM6DR9Ewrfqrr6e3qgxoxb+lI0vU146jSMspYuWhdAD+3MBakZqM6NySL+4ZxN2fbWbT8Qxu/Xgjc+66hNAmLhQXjUsm4JygdZgfl3eN0EUgAjVnRrSy8yyguqr6VtGUrSaj/6kasllTuUMfK/8kVYUVB9OY+N5a9pzOxsvDyJgekfz96m48OqoTY3tE4WkysPt0FlPnbWPyp5s4ll5DbwNXstWN7Co/79BvUJhFMmFstHRjiA6CkRJLCYVm56yGGdA2lN8eG879w9vjaTKw6lA6Y2etZvKnm1i6L5WShi6FF/oU0UN9yCjMhIwK2wVYzOU7fHcew0/bT2PRoH+bFo2+8d3AtqF8ff+lhPp7setUFjd9uJ7UbFn11ZxIZqQZqjEzopkAMxaDwbEpGivrtJPFAnnpEFB96v633ck8NG8bmgYD2rTg/dv6ERHoY3fMudwi5q47wQerjrH68Fmu/s9qXprYkxv0VjhprRtJqRCM7JgHwPelw/Dz9qKXi1afnCs8Z/dzdlE2vh41bHDmAF8vE3+7uhu3DmrN678fZNGeZFYdSmfVoXSCfDy4omsEV/WIYkTnlvh7y8tJs+DhpTKBpzbD6W3lU7CJayEnGXyC0dpfzve/qnbw1/dvvKxIRT1bBfPtA5dy28ebOJyWyw0frOezuwbSQXYAbhYkM9IMVdf0DMBS8bza9qOpidEIgZHVFuMeScvhie92omkqhTvvvksrBSIAYQHeTLuqC0v+MpzLOoZTWGLhye938eR3OykodsIGhs4SXZYZST+gpmdyUmyNn340D2NQu9AqW183NotmIaNAtYK3ZsLqs7y3Nm3C/Hnv1n6sfOJy7hvWjjB/L7ILS1mw4wwPfbWNvi8t4baPN/LWkkMsP5DK0fRc52xAKVyj4lSN1e7v1dfuE9mVUsjhtFy8PYxc0zu6yYbVMSKQ7x4cTJswP5Iy8pn47loW7619Pyahf/JRphmqdmkvYI0/S42eEHdJo9x/blEpD3yxlbxiM5e2D+W1P/eq9Y26TZg/n999Ce8nHOGtJYf4buspdp3K4r1b+9ExQgeffIJagW8oFGSozRBPrAHNzGGv7hwvjOZWF03RZBVlUaqpZnzR/tGcyTvToBU1tWkd5sffr+nOM+O6sS3pPEv2pfLH3hROnMtnzZGzrDlSPmVkMEBkoA+tQ/1oHeZHu3B/2ob506bse8mk6NiFwUhpEexbqL7veT0LdqjtM8b0iGrylVbW5mhT521j0/EMHvhiK3cOacuTY7rU628qv7iUwhILJWYLwb6e+HjqY7r9YiOvBs2QbWlvFYkvrey8/OAO4OHdKPf/ws97OZqeR2SQN+/c0q/OGQOj0cDDV3SiX5sWPPr1Dg6m5nDtu2uYcV0vJvapvi6lSRgMKjtyLEEtZ971LQCfFwwBYFinpt2PxspaLxLiHUKoT2ijByNWJqOBgW1DGdg2lOnjunI0PZcNxzLYlnievWeyOXk+n/xiMynZhaRkF7LpREal22gZ6E3bMD/ahPnTLtyfmBAfIgJ9iAj0JiLIhyAfD/0WNDd31mAkeafaUPPIMlVDEhCFufVQfvk6AYCJfWJcMryWgd58de8gZiw6wKdrjzNn3QmW7Evl79d048rukXhW85pTXGphX3I225POsz0pk+0nz3Myw35jvvAAL9qG+dMrNpg+cSEM6RBOy8DGea0U5SQYaYaq27UXoBgfoIDs0LpvvOeIrYkZfLf1FADv/l+/ev0TD+kQzqLHLuPRr7ez4VgGj83fweYTGTw7vrtLls7aRJUFIwkzACjxCmZh9iBiW/jSOdI12RtrMBLuG05QWdv6pghGKjIYDHSMCKRjRCC3Xaq61WqaRkZeMUkZ+Zw8X0Di2TyOn8vjxNk8TpzLJyOvmPScItJzith84nyVt+vtYSQiyLs8QCkLUloGehMZpM6LCvJp8vb7F4XQ9uATogKQ1D2wp2yKpud1bEzMJD2niGBfT5cF4aB2Xn9uQneGdw7n7z/t4XRmAQ99tY3wAC+u7B5FmzA/Qv28OJ9fTHJWIbtPZ7H7dFa1O7QbDWDR4GxuMWdzi9mSWP532T06iDE9ohgfHy01Ko1EgpFmqKaakRRTFHCe8xHOn6IxWzSeXbAXgBsHxDKwbWi9bysi0Iev7r2UWUsP8c7yI3y5IYktJ87z5o3x9IhxUZtyaxErQKv+vOv3KNm7PbmuW6TLPsFbg5Ew3zCCvMqCkQb2GnEGg8FAWIA3YQHe9G1decVWVkEJiedUYKIClDxSsgpJyykiLbuQ7MJSikotnMwoqPTJ9UKxLXzp36YFg9uHMaJLS6KDnVO8e1EzGFR25OgyWPYiHC3bx6rn9fxvUzIA43pG6aIj6sguEfzxl+HMTjjK/M0nOZtbxNebkqo9PsTPk75xIfRt3YK+rUPo1SqYIB9PDAb1d3nqfAGHUnPYdSqLTccz2JecbTvNXHqI+NhgbrmkNRPiY2Sq0YnkN9kMWadpqlraa0BlFsyNsPnUvE1J7EvOJsjHg6fHdm3w7ZmMBv56VRf6tWnBX7/dyYGUHCa+u5aHLu/IlBEdmn4pdZerVYO3qN5Y+t/DvNcSgCKucGEzMGv31XDfcPw91F5JTZ0ZqY9gX096x4bQOzakyssLS8ykZReRllMeoKTlFJWfsgtJzyniXF4xp84XcOp8AQt3nAGgS2QgI7u0ZETnlvRv28K12TR3Zg1Gji5XPw+4h5KoPvy2RxVuT4h3zRRNVfy9PXhiTBceG92JVYfS2ZZ0njOZhWTkFRPq70XLQG+6RgXSt3UL2ob5VfvhIcTPixA/L3q2Crbts3M2t4gVB9L4dXcyaw6fZeepLHae2s1Lv+xjYt9W/N8lrWUfJyeQYKQZqmlpr/Wf0Gxxbo+IjLxi/r1YdXX961VdCAtw3hzr5V0iWPz4cP6xYDeL96byn2WH+WZzEtOu7Myf+sY23aczLz+Y+B4Ae06pVLW/l4lB7eufAWoo2zSNTzieJlVI6A7BSG18PE20DlOFrzXJKSxh58ksNp3IYPXhdHaczORgag4HU3P4cNUx/LxMDOkQRv82ofSJC6FXbDAB8mm2bqx1IwCDpsDYGaw5mE5mfgnhAd5c2l5/e1F5moyM6hbJqG6RTrvN8ABvbhgQxw0D4jibW8QPW0/x9aYkTpzLZ97GJOZtTKJXq2D+b5DKlsjfV/3Ib60Zqmk1jTVbUqo5Nxh5Y/EBsgpK6BYdxK2D6rjxngNaBnrzwW39+XV3Mq/+doBT5wt4+ofdvPnHIW67tA1/7h9Lq5CmS88v3Z8GwPDOLV36yftsYXnNiLVWqDGW9upVoI8nl3UK57JO4Uy7sjPn84pZfeQsKw+ms/JQOmdzi1i6P832fBkM0CkigPjYEOLjQugTF0KXqMBqCx4vah2ugN43QWRPGPIIGAwsLFtFM7539EW5i254gDcPjOjA/cPbs/7YOb7edJLf9ySz+3QW03/czcu/7OPaPq24rl8r+saFuGS5v7uSYKQZqmk1jTVAsThxmmbnyUzmbz4JwIsTezTaP6DBYGB87xiu7B7J5+sS+Wj1MdJyinhrySHeWnKIvq1DGNsjilHdIujQMqBR6ziWH0gFcOkUDdjXjBSZiwB91Iy4Sgt/L66Nj+Ha+BgsFo39KdmsPXKWnSez2HEyk9OZBRxKzeVQaq6t0Nrbw0iPmCBbcHJp+zAigyr3xLnoeHjBdR/ZfszML2bRHtXTY1JfF69uczGDwcCQDuEM6RDOudzu/LDtFF9vOsnxs3l8vSmJrzclEezryfDOLbm8bMrQmdni5kiCkWaopgJWa4DirGkai0XjuYV70DS4rm+rBhWt1pW3h4n7hrfnjiFt+W1PMl9tTGLziQy1VC8pkxm/HSAu1JdRXSO5vGsEg9qFOrV3wO5TWew5nY3RgMs3j6tYM2LNiDSHaRpnMBoN9IgJtit4TsspZNfJLHaeUjtu7zyZSXZhKduSMtmWlAmo7Em/1i0Y1zOKMT2iiAutearoYvHjttMUl1roFh1EfB12Ob9YhAV4c//wDtw3rD0bjmXw7ZaTLD+QRlZBCf/beYb/7VS1TB0jAujfugX927SgX5sWdGjpL0vXK5BgpBmqaWmvoSxAsThpmuazdSfYeSqLAG8PnhnX8KJVR3h5GJnYpxUT+7QiLbuQ3/aksOxAGhuOnuNkRgFz1p1gzroT+HmZGNoxnNHdIriia2SDewa8vewQAJP6tCLcxZ92KgYj1udbgpHqRQT6MLq7D6O7q5oCTdM4cS6fnSdVcLIt6Ty7TmWxNfE8WxPP8/Kv++nVKphrekczvnc0sS0uzsBE0zTbCpX/G9Ra3kSrYDAYGNwhjMEdwig1W9h5KpMVB9JZcTCNvWeyOZKWy5G0XL7ZorLIfl4m2oX7075lAO3D/Wnf0p82Yf60CfUjxM/zovsdSzDSDNmmaaosYFVfzZaGT9McTc/l9d8PAPDMuK5EuDC1HRHkwx1D2nLHkLbkFZWy9shZlh9IY/mBNNJyiliyL5Ul+1IxGHbTNy6EK7tHcWV3x6dzdp/KYun+NIwGePiKjo34iGpXbC7mfJHqhRDmG0aJpQS4uKdpHGUwGGgXrpquWaceUrIKWbw3hd/2JLPpeIatP8Wrvx2gX+sQxveO4Zre0RfVVM7WxPMcTsvF19PkskZn7sTDZKR/m1D6twnliTFdyMgrZlviebYknmdb4nl2nsokv9jM3jPZ7D1T+f810MeDNmF+tAn1p3WYH23Kuhi3CfMnOsgHYzOs15FgpBmqaddeA87JjJgtGk98t5OiUgvDOoU3StFqffl7e3BVjyiu6hGFpmnsPZPNsv1pLN2fyu7TWbaU/Gu/H6BduD+jukYwoK1abREVXPMbjDUrMrFPq0bfqbQ2+zP2A9DCuwUtvFuQX5IPSGakoaKCywPbs7lFLN6bwi87k9lw/Jztb+elX/cxqF0oE+JjGNczutlvZz+vLCsyIT66ydu/Nweh/l6M7h5py8iVmC0knsvnWHoux87mcSw9l+Nn80g8l09aThE5haXsOZ3NntOV/5e9TEZiQ33pEhlIz1bB9Co7uXvzPwlGmiHrNE2VNSNl55kbEIyUmi38/ac9bE/KJNDbg9f+3Fu3KUWDwUDPVsH0bBXMY6M7kZxVoFZX7Etl/dFzHD+bx8drjvPxmuMARAX5EB8XTO/YELpFB9IpIpDoYB+yCkp4Z/kR3WRFAHam7QQgPiIeg8Fg68BaaC6k2FyMl8m9X5z0IDzAm1sHteHWQW1Iyy7k193J/LIrma2J59lwLIMNxzJ4buFehnQI44quEQzr1LLZ1QLsT8621T3ccol+PnS4M0+TkY4RAVXuu1VQbCYpI5/Ec3llX/NJzMgn6Vwep84XUGy2cCw9j2Ppefy2p3yTwFYhvvSODba93vWMCXKrolkJRpohW9OzGpb21reAtbDEzKNfb+ePfakYDfCv63oR04RLahsqOtiX2y9tw+2XtiGnsITVh8+y+nA625MyOZSao/ZS2VvI4r2ptuuYjAZMRoOtjfTdQ9vpoiX0jvQdAMS3VJ1hAzwDMGBAQyO7OJtw33AXjq75iQjy4a6h7bhraDtOnc/n113J/G/XGfaczi77Oypb2eTvRd/WIXSPCaZtmB8xIb4EeHvg52XCv+yrh9GIwaCmTQ0YMBjAaFD/nep8fQQzJWYLT3y3kxKzxpXdI6vspiucy9fLRJeoQLpEBVa6rNRsITmrkONn89ifnM2u01nsOZ1F4rl8TmcWcDqzwC5AiQ72oUdMED1irEFKEFFBPrr5+6pIgpFmqKalvUaDAbS6TdOYLRqnzxdwKjOf5MxC1h87x5J9qWQVlODlYeSdW/oypkeU08ffVAJ9PLm6VzRX91JboOcXl7L7lFppsfdMNvuTszl+No8Ss4bZotEjJojp47pxWSfXv8lrmlaeGSkLRowGIwFeAeQU50gw0shiW/jxwIgOPDCiA8fP5rF4bwprDp9l04kMzuUV2/U2qS8PowFPkxFPk/WrEU8PA55GIxpqeb7ZomGxaFg01VVZKztPA/y9PAj19yLEz5NQfy/CA7yJbeFLXAtVfxDbwhc/r5rfAmYnHGXvmWxC/Dx55U+Ns5+VqDsPk5G4UD/iQv0Y3rl8X6CsghL2ltU27T6dxb4z2Rw7m0dyViHJWYV2f4th/l50jwkqy54E0zU6kDahfi7viSLBSDNU62qaaoKR7MIS1h05y4ZjGWxJzOBwai5FVWwqFRnkzds399VlB8aG8PPyYFD7MAZVeFwWi0Z6bhE5hSW0Dw/QTeFYSl4KaQVpmAwmeoT1sJ0f5BWkghEpYm0y7cL9eXBEBx4c0YHCEnPZrrCZHEnLJbFsz538YjN5xaXkF5vrXDxeatEotZgpKKnfuDLzSzidWfO+PuEBXsSF+tEqxJeYEF+ig32IDvbF02Tgx22n+W2P2ofmhWt7EBF48RTsuptgX0+GdAxnSMfyDyA5hSXsT85hz+msskLZLA6n5XIur9gukwdqZWL7cH9e+VNP+rdxTUdpCUaaoZpW0xgvmKYpMVv4Y28qC3acZuXBdIrN9sGHl4eR2BbqRapzZCBjekQxsG3oRdN90Wg0EBnko7uVEzvTVVakS2gX/DzLl5sGeQVxmtNSxOoiPp4m+rVuQb9qpjM0TaOo1GLLXmiaymqgqW0cLFr5eWaLRonZUnZS3xebLZSUWjAYDJiMKtNpNKhpRINBTSlap3tyiko5n1fM+fwSzucVk5ZTqDYePJ9PUkY+OYWlth1qt5f1WKnKjQNiuVZH+9CIugn08eSSdqFc0q48uCgsMXMwJYc9Z1SvpL1nsjicmktBiZkDKTm1ZsoaU73u+b333uONN94gJSWF+Ph43nnnHS65pPpdYL/77jueffZZTpw4QadOnXjttde4+uqr6z1oUbMa28Fbe1EUljBzySG+3pREWk6R7fL2Lf25rGM4g9qF0T0miNahfhdN4OFOrMGIdYrGylrEKsGIPhkMBqc24GuIrPwSW2ByJrOAM5mFpGSrr5n5xQztGM5tl7ahW3SQq4cqnMTH00R8nNoKwcpi0co6E+fQvqW/y8bmcDDyzTffMG3aND744AMGDRrErFmzGDNmDAcPHiQionI3ynXr1nHLLbcwY8YMxo8fz7x585g0aRLbtm2jZ0+Zg2wMtg6sVdaMqPO2JGawbtthQK0YuHFALNf2iaFLZKAui5uEvR1pO4AqghGvsmBEpmlELYL9PAn2C5YdZy9yRqPBVofiSg4HI2+99Rb33Xcfd911FwAffPABv/76K59++inPPPNMpePffvttxo4dy5NPPgnASy+9xJIlS3j33Xf54IMPGjj8hjlbcJZic7FLx9AYrI2wqpqm8TSZoBQMpnz6tLPwp36xjOzUEk8PI5BLcl5uE49WOKrEUsKBDNVsrk9EH7vLrMHImdwznMk909RDE0K4sXDfcJe1BHAoGCkuLmbr1q1Mnz7ddp7RaGT06NGsX7++yuusX7+eadOm2Z03ZswYFixYUO39FBUVUVRUPnWQnd04n/IeX/G4Ld3dHFXV9Kx7dDDHT4BX2CqOsop/74N/72v6sYmGC/cNJ8bffi7fOk0zd99c5u6b64phCSHc1JdXf1kp29pUHApGzp49i9lsJjIy0u78yMhIDhw4UOV1UlJSqjw+JSWlyuMBZsyYwQsvvODI0OrF0+iJt8l9msI4wtPoyag2oyqdP7b9FaxJXk5haaELRiWcxWgwckvXWypNqY2IHcHCIwvJK8lz0ciEEO6qqg+wTUWXq2mmT59ul03Jzs4mLi7O6ffz2djPnH6bejcybiRrbl7j6mGIRtI/sj8rb1rp6mEIIYRDHApGwsPDMZlMpKam2p2fmppKVFTVza+ioqIcOh7A29sbb+/mmbEQQgghhD2HWq55eXnRv39/li1bZjvPYrGwbNkyBg8eXOV1Bg8ebHc8wJIlS6o9XgghhBAXF4enaaZNm8Ydd9zBgAEDuOSSS5g1axZ5eXm21TWTJ0+mVatWzJgxA4DHHnuMESNG8Oabb3LNNdcwf/58tmzZwkcffeTcRyKEEEIIt+RwMHLTTTeRnp7Oc889R0pKCn369OH333+3FakmJSVhNJYnXIYMGcK8efP4xz/+wd/+9jc6derEggULpMeIEEIIIQAwaNbe4TqWnZ1NcHAwWVlZBAVJN0AhhBDCHdT1/du12/QJIYQQ4qInwYgQQgghXEqCESGEEEK4lAQjQgghhHApCUaEEEII4VISjAghhBDCpSQYEUIIIYRLSTAihBBCCJeSYEQIIYQQLuVwO3hXsDaJzc7OdvFIhBBCCFFX1vft2pq9u0UwkpOTA0BcXJyLRyKEEEIIR+Xk5BAcHFzt5W6xN43FYuHMmTMEBgZiMBicdrvZ2dnExcVx8uTJZrvnjTxG99fcHx/IY2wOmvvjg+b/GBvj8WmaRk5ODjExMXab6F7ILTIjRqOR2NjYRrv9oKCgZvmHVZE8RvfX3B8fyGNsDpr744Pm/xid/fhqyohYSQGrEEIIIVxKghEhhBBCuNRFHYx4e3vz/PPP4+3t7eqhNBp5jO6vuT8+kMfYHDT3xwfN/zG68vG5RQGrEEIIIZqvizozIoQQQgjXk2BECCGEEC4lwYgQQgghXEqCESGEEEK41EUdjLz33nu0bdsWHx8fBg0axKZNm1w9pHqZMWMGAwcOJDAwkIiICCZNmsTBgwftjhk5ciQGg8Hu9OCDD7poxI775z//WWn8Xbt2tV1eWFjI1KlTCQsLIyAggD//+c+kpqa6cMSOa9u2baXHaDAYmDp1KuB+z+GqVauYMGECMTExGAwGFixYYHe5pmk899xzREdH4+vry+jRozl8+LDdMRkZGdx6660EBQUREhLCPffcQ25ubhM+iprV9BhLSkp4+umn6dWrF/7+/sTExDB58mTOnDljdxtVPe+vvvpqEz+S6tX2PN55552Vxj927Fi7Y/T8PNb2+Kr6nzQYDLzxxhu2Y/T8HNbl/aEur59JSUlcc801+Pn5ERERwZNPPklpaanTxnnRBiPffPMN06ZN4/nnn2fbtm3Ex8czZswY0tLSXD00h61cuZKpU6eyYcMGlixZQklJCVdddRV5eXl2x913330kJyfbTq+//rqLRlw/PXr0sBv/mjVrbJf95S9/4X//+x/fffcdK1eu5MyZM1x33XUuHK3jNm/ebPf4lixZAsANN9xgO8adnsO8vDzi4+N57733qrz89ddf5z//+Q8ffPABGzduxN/fnzFjxlBYWGg75tZbb2Xv3r0sWbKEX375hVWrVnH//fc31UOoVU2PMT8/n23btvHss8+ybds2fvzxRw4ePMi1115b6dgXX3zR7nl95JFHmmL4dVLb8wgwduxYu/F//fXXdpfr+Xms7fFVfFzJycl8+umnGAwG/vznP9sdp9fnsC7vD7W9fprNZq655hqKi4tZt24dc+fOZc6cOTz33HPOG6h2kbrkkku0qVOn2n42m81aTEyMNmPGDBeOyjnS0tI0QFu5cqXtvBEjRmiPPfaY6wbVQM8//7wWHx9f5WWZmZmap6en9t1339nO279/vwZo69evb6IROt9jjz2mdejQQbNYLJqmufdzCGg//fST7WeLxaJFRUVpb7zxhu28zMxMzdvbW/v66681TdO0ffv2aYC2efNm2zG//fabZjAYtNOnTzfZ2OvqwsdYlU2bNmmAlpiYaDuvTZs22syZMxt3cE5S1WO84447tIkTJ1Z7HXd6HuvyHE6cOFG74oor7M5zp+fwwveHurx+Llq0SDMajVpKSortmNmzZ2tBQUFaUVGRU8Z1UWZGiouL2bp1K6NHj7adZzQaGT16NOvXr3fhyJwjKysLgNDQULvzv/rqK8LDw+nZsyfTp08nPz/fFcOrt8OHDxMTE0P79u259dZbSUpKAmDr1q2UlJTYPZ9du3aldevWbvt8FhcX8+WXX3L33XfbbQ7p7s+h1fHjx0lJSbF7zoKDgxk0aJDtOVu/fj0hISEMGDDAdszo0aMxGo1s3LixycfsDFlZWRgMBkJCQuzOf/XVVwkLC6Nv37688cYbTk1/N4WEhAQiIiLo0qULU6ZM4dy5c7bLmtPzmJqayq+//so999xT6TJ3eQ4vfH+oy+vn+vXr6dWrF5GRkbZjxowZQ3Z2Nnv37nXKuNxiozxnO3v2LGaz2e4XCxAZGcmBAwdcNCrnsFgsPP744wwdOpSePXvazv+///s/2rRpQ0xMDLt27eLpp5/m4MGD/Pjjjy4cbd0NGjSIOXPm0KVLF5KTk3nhhRcYNmwYe/bsISUlBS8vr0ov8JGRkaSkpLhmwA20YMECMjMzufPOO23nuftzWJH1eanqf9B6WUpKChEREXaXe3h4EBoa6pbPa2FhIU8//TS33HKL3SZkjz76KP369SM0NJR169Yxffp0kpOTeeutt1w42robO3Ys1113He3atePo0aP87W9/Y9y4caxfvx6TydSsnse5c+cSGBhYaQrYXZ7Dqt4f6vL6mZKSUuX/qvUyZ7gog5HmbOrUqezZs8eungKwm5/t1asX0dHRjBo1iqNHj9KhQ4emHqbDxo0bZ/u+d+/eDBo0iDZt2vDtt9/i6+vrwpE1jk8++YRx48YRExNjO8/dn8OLWUlJCTfeeCOapjF79my7y6ZNm2b7vnfv3nh5efHAAw8wY8YMt2g7fvPNN9u+79WrF71796ZDhw4kJCQwatQoF47M+T799FNuvfVWfHx87M53l+ewuvcHPbgop2nCw8MxmUyVqoVTU1OJiopy0aga7uGHH+aXX35hxYoVxMbG1njsoEGDADhy5EhTDM3pQkJC6Ny5M0eOHCEqKori4mIyMzPtjnHX5zMxMZGlS5dy77331nicOz+H1uelpv/BqKioSgXlpaWlZGRkuNXzag1EEhMTWbJkSa1bsw8aNIjS0lJOnDjRNAN0svbt2xMeHm77u2wuz+Pq1as5ePBgrf+XoM/nsLr3h7q8fkZFRVX5v2q9zBkuymDEy8uL/v37s2zZMtt5FouFZcuWMXjwYBeOrH40TePhhx/mp59+Yvny5bRr167W6+zYsQOA6OjoRh5d48jNzeXo0aNER0fTv39/PD097Z7PgwcPkpSU5JbP52effUZERATXXHNNjce583PYrl07oqKi7J6z7OxsNm7caHvOBg8eTGZmJlu3brUds3z5ciwWiy0Q0ztrIHL48GGWLl1KWFhYrdfZsWMHRqOx0tSGuzh16hTnzp2z/V02h+cRVLayf//+xMfH13qsnp7D2t4f6vL6OXjwYHbv3m0XVFoD6+7duzttoBel+fPna97e3tqcOXO0ffv2affff78WEhJiVy3sLqZMmaIFBwdrCQkJWnJysu2Un5+vaZqmHTlyRHvxxRe1LVu2aMePH9cWLlyotW/fXhs+fLiLR153f/3rX7WEhATt+PHj2tq1a7XRo0dr4eHhWlpamqZpmvbggw9qrVu31pYvX65t2bJFGzx4sDZ48GAXj9pxZrNZa926tfb000/bne+Oz2FOTo62fft2bfv27RqgvfXWW9r27dttK0leffVVLSQkRFu4cKG2a9cubeLEiVq7du20goIC222MHTtW69u3r7Zx40ZtzZo1WqdOnbRbbrnFVQ+pkpoeY3FxsXbttddqsbGx2o4dO+z+N60rENatW6fNnDlT27Fjh3b06FHtyy+/1Fq2bKlNnjzZxY+sXE2PMScnR3viiSe09evXa8ePH9eWLl2q9evXT+vUqZNWWFhouw09P4+1/Z1qmqZlZWVpfn5+2uzZ/9/O3bM0EoVRHH+WrBMTxKBkiCJoChsltXYSCARSpgqp1MLGSlCLFDYWfgGLxUr8Flql1UKwDQQS0qSJYAjEwpezxS4LEtfsiuyTxf8PppkwcC53Zu5JmMm3geNHfQ6HrQ/S8Pvn4+OjMpmM8vm8bm5udH5+rjAMValUPiznpy0jknR8fKz5+XkFQaCVlRVdXl56R3oXM3t1Oz09lSS1Wi2tra1penpa0WhUi4uL2t/fV7fb9Q3+F0qlkmZnZxUEgebm5lQqlVSv1399fn9/r+3tbU1NTSkej6tYLKrdbjsmfp+LiwuZmWq12ov9/+McVqvVV8/L9fV1ST9e7z04OFAqlVI0GlUulxsY9+3trcrlsiYmJjQ5OanNzU31ej2H0bzurTE2Go3fXpvValWSdH19rdXVVSUSCY2Pj2tpaUlHR0cvFnJvb42x3+8rn88rDEONjY1pYWFBW1tbA1/qRnkeh52nknRycqJYLKa7u7uB40d9DoetD9Kf3T+bzaYKhYJisZiSyaR2d3f18PDwYTm//AwLAADg4lM+MwIAAEYHZQQAALiijAAAAFeUEQAA4IoyAgAAXFFGAACAK8oIAABwRRkBAACuKCMA3GSzWdvZ2fGOAcAZZQQAALji7+ABuNjY2LCzs7MX+xqNhqXTaZ9AANxQRgC46Ha7VigULJPJ2OHhoZmZhWFokUjEORmAf+2rdwAAn1MikbAgCCwej9vMzIx3HACOeGYEAAC4oowAAABXlBEAboIgsKenJ+8YAJxRRgC4SafTdnV1Zc1m0zqdjj0/P3tHAuCAMgLAzd7enkUiEVteXrYwDK3VanlHAuCAV3sBAIArfhkBAACuKCMAAMAVZQQAALiijAAAAFeUEQAA4IoyAgAAXFFGAACAK8oIAABwRRkBAACuKCMAAMAVZQQAALiijAAAAFffAdScfF0SRbvFAAAAAElFTkSuQmCC", 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", 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", "text/plain": [ "
" ] @@ -435,12 +510,13 @@ ], "source": [ "import matplotlib.pyplot as plt\n", - "n_timesteps = 200\n", + "n_timesteps = 400\n", "(\n", " cr_ep[cr_ep.t < n_timesteps].plot(x='t', title=f'CR episode, rew={sum(cr_ep.rew):.2f}'),\n", " ppo1_ep[ppo1_ep.t < n_timesteps].plot(x='t', title=f'PPO1 episode, rew={sum(ppo1_ep.rew):.2f}'),\n", " ppo2_ep[ppo2_ep.t < n_timesteps].plot(x='t', title=f'PPO2 episode, rew={sum(ppo2_ep.rew):.2f}'),\n", " ppoEsc_ep[ppoEsc_ep.t < n_timesteps].plot(x='t', title=f'PPO_Esc episode, rew={sum(ppoEsc_ep.rew):.2f}'),\n", + " ppo_mwt_ep[ppo_mwt_ep.t < n_timesteps].plot(x='t', title=f'PPO mwt episode, rew={sum(ppo_mwt_ep.rew):.2f}'),\n", ")\n", "plt.show()" ] @@ -455,7 +531,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 93, "id": "a20d7ed0-8a57-42aa-84f1-ecc148e7988d", "metadata": {}, "outputs": [], @@ -463,6 +539,9 @@ "def mwt_obs(mwt):\n", " return 2 * (mwt - MINWT) / (MAXWT - MINWT) - 1 \n", "\n", + "def obs_to_mwt(obs):\n", + " return MINWT + (MAXWT - MINWT) * (obs+1)/2\n", + "\n", "def get_policy_df(policy_obj, mwt, minx=-1, maxx=1, nx=500):\n", " env=AsmEnv(config=CONFIG3)\n", " obs_list = np.linspace(minx, maxx, nx)\n", @@ -470,7 +549,7 @@ " {\n", " 'obs': obs_list,\n", " 'mwt': [mwt for _ in obs_list],\n", - " 'biomass': env.bound * (obs_list + 1)/2,\n", + " 'biomass': env.bound * (obs_list + 1) / 2,\n", " 'fishing_mortality': [\n", " (1 + policy_obj.predict(np.float32([obs, mwt_obs(mwt)]))[0][0]) / 2 \n", " for obs in obs_list\n", @@ -478,6 +557,36 @@ " }\n", " )\n", "\n", + "def get_biomass_policy_df(policy_obj, minx=-1, maxx=1, nx=500):\n", + " env=AsmEnv(config=CONFIG3)\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'mwt': 0.5,\n", + " 'biomass': env.bound * (obs_list + 1) / 2,\n", + " 'fishing_mortality': [\n", + " (1 + policy_obj.predict(np.float32([obs]))[0][0]) / 2 \n", + " for obs in obs_list\n", + " ]\n", + " }\n", + " )\n", + "\n", + "def get_mwt_policy_df(policy_obj, minx=-1, maxx=1, nx=500):\n", + " env=AsmEnv(config=CONFIG3)\n", + " obs_list = np.linspace(minx, maxx, nx)\n", + " return pd.DataFrame(\n", + " {\n", + " 'obs': obs_list,\n", + " 'mwt': [obs_to_mwt(mwt_obs) for mwt_obs in obs_list],\n", + " 'biomass': 0,\n", + " 'fishing_mortality': [\n", + " (1 + policy_obj.predict(np.float32([obs]))[0][0]) / 2 \n", + " for obs in obs_list\n", + " ]\n", + " }\n", + " )\n", + "\n", "def get_esc_policy_df(policy_obj, mwt, minx=-1, maxx=1, nx=500):\n", " env=AsmEnvEsc(config=CONFIG3)\n", " obs_list = np.linspace(minx, maxx, nx)\n", @@ -522,13 +631,19 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 97, "id": "245547ba-b2ba-4e61-8409-4e98c79d47fc", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "cr_df = get_policy_df(cr3, mwt=0.5, maxx=-1+0.14)\n", "\n", + "ppo_mwt_df = get_mwt_policy_df(ppoAgent1obs_mwt)\n", + "\n", + "ppo_biomass_df = get_biomass_policy_df(ppoAgent1obs, maxx=-1+0.14)\n", + "\n", "ppo1_df_mwt1 = get_policy_df(ppoAgent1, mwt=0.6, maxx=-1+0.14)\n", "ppo1_df_mwt2 = get_policy_df(ppoAgent1, mwt=0.7, maxx=-1+0.14)\n", "ppo1_df_mwt3 = get_policy_df(ppoAgent1, mwt=0.8, maxx=-1+0.14)\n", @@ -550,9 +665,11 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 84, "id": "7473b83a-64db-45c2-aec7-c6055d881a7f", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [], "source": [ "ppo1_df = pd.concat(\n", @@ -585,13 +702,13 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 85, "id": "339e8de2-9152-4cd5-be35-2234ca5dac5a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -611,13 +728,13 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 86, "id": "a4f825c2-8935-4152-8feb-daee36c7bf3a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -637,13 +754,13 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 87, "id": "95150d6b-558d-4a1b-be4d-c627b507d629", "metadata": {}, "outputs": [ { "data": { - "image/png": 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I6HFlV8u1dZrVVNOOjbyYJrDt335QW1ftsFy/YOIyL6YBAMC7aAACAAAAIWLAqF6Kiom0VHvRrf1lGIaXEwWuw3tSbdWn7EmV213+48IAAAQqGoAAAABAiKhWN0l3/vcmOctZ2EKSel19ri4Y08tHqQJTRJTTVr0z0hnWDVMAQHCjAQgAAACEkK4Xd9Qj39ytFl2anLKvSs0EXf/YMN3+xig5HOH9o0Cjs+srspK10ZKS1OKcpjQAAQBBK8LfAQAAAAB4VpvzW+rpGQ9p5/o92r56lwoLClWjQTV16NdGEVH8CCBJcYmxOn/YOVow3trcfhfe2NvLiQAA8B7+9QcAAABCyMGdh/XTZ4u0ZcV2FeQVqFrdqup1zbnqOOBsOSPsPfYa6q64b4h++XGdMtOyyq1r0aWJul7cyUepAADwPBqAAAAAQAhwu9z68qlvNePduTJNs/j1nev2aNWPa1W7aU098Nntqteyjh9TBpaajarr71+N1Ysj/qv0Qxll1u3bekDzvlisgTf28WE6AAA8J7wn/gAAAABCxGePfa3p78wp0fw70YEdh/T05f/R4T+O+DhZYGvaoZGemf1/qlq3Spk12Rk5+ujhCZr6xizfBQMAwINoAAIAAABBbuf6PZr5wfwK6zJSjmnCc995PU+wmfn+fKUmp1dYN+GZ77Rv6wHvBwIAwMNoAAIAAABBbvbHCyzXLp/2a7mPu4ab/Jx8zftyiaVa0zT10ycLvZwIAADPowEIAAAABLmNC3+zXOsqcOn35du8mCa4/LZ8e4WLgJxo1Yy1XkwDAIB30AAEAAAAglxudr69+qw8LyUJPlnp1pt/x+uzvZQEAADvoQEIAAAABLkqNRNs1id6KUnwiUuMtVdfxV49AACBgAYgAAAAEOTOv6Kr5drEGgk6u2dLL6YJLq3ObW6rqdflovZeTAMAgHfQAAQAAACCXL/h5ys6NtpS7cAbeysiKsLLiYJHdGyU+g0/31KtYRgaOKa3lxMBAOB5NAABAACAIJdQvbLGvnuTnBHlf3vfvl8bXXbXIB+lCh5XPHCxGrWtX2HdlQ9drHot6/ggEQAAnkUDEAAAAAgBXQa11yNf360m7Rucsi8mvpKG/m2gHvz8r4z+K0VMfCU9+u09OueiDuXWzfxgvhZ9tdxHqQAA8Jyw+dc/MzNTGzZs0LZt27R9+3Zt27ZNR48elSQ9++yzateu3Rmdv7CwUN9//70WLFig5ORkSVK9evXUp08fXXzxxYqIKP9DvWPHDk2ePFnr169XRkaGEhMT1bZtW11xxRVq0qTJGWUDAABAeGjTo6Wenf13bf91t35fvk0F+YWqVjdJXQd3UKX4Sv6OF9Diq8Tpttdu0B8X7tOh3Sml1hw7kqn/3vmJ8nLydcHoXj5OCADA6QubBuDy5cv12muveeXcOTk5euyxx7RlyxZJUlRUlCRp27Zt2rZtm5YsWaKnn35alSqV/k3XggUL9Nprr6mwsFCSFBcXpyNHjmjBggVasmSJ7r33XvXqxTcYAAAAqJhhGGreubGad27s7yhBZ8Iz35XZ/DvRJ49MVKcLzla1elV9kAoAgDMXNg1ASUpKSlKzZs3UvHlz1a1bV6+88opHzvvf//5XW7ZsUVxcnO666y6dd955kqSff/5Zr7/+un777Te9/fbbuvfee0859o8//ihu/vXs2VO33HKLqlatqtTUVL3//vtasmSJXn31VTVp0kT161c8LwkAAADCj2ma+n35Ns36eKE2L92q/Jx8JdWpop5XdlXf4T1UpWaCvyMGvKyj2Vr0jbXHe10FLs39fImu/r9LvJwKAADPCJsGYN++fTVgwIDiP2dmZnrkvDt37tTChQslSWPHjlX37t2L93Xv3l1ut1svvPCC5s+fryuuuEKNGjUqcfyXX36pwsJCNWnSRPfff7+cTqckqWrVqnrggQeUnJysnTt36ssvv9TDDz/skcwAAAAIHYX5hXr3ns+1+JsVJV7PzsjRxOemasprM3XX+7eo0wVt/ZQwOGxY+Jvycwos16+csZYGIAAgaITNIiBFjTVPW7BggUzTVJ06dUo0/4qcf/75qlOnjkzT1IIFC0rsy8rK0sqVKyVJl19++SkZnU6nLr/8cknSihUrlJ2d7ZX3AAAAgOD1wYPjTmn+nSg3K0+vjHlXW1Zs92Gq4JOZlmWrPuso35sDAIJH2DQAvWXdunWSpE6dOskwjFP2G4ahTp06lagtsmnTpuJ5/zp37lzq+YteLygo0ObNmz2WGwAAAMFv1/o9WjB+WYV1hfmFGvfPyT5IFLziqsTaq0+0Vw8AgD/RADwDpmlq7969knTKo70natiwoSRpz549JV4v+nOVKlWUmJhY6rGJiYnF+/74448zzgwAAIDQ8dMnCy3X/r58u/7YtM+LaYJb296tFRUTabm+y0XtvJgGAADPogF4BnJycpSbmyvp+Jx9ZSnal5OTo5ycnOLX09LSKjz2xP1F9QAAAIAkbVm10179yh1eShL84qvEqceV3SzVOiMcGnBDLy8nAgDAc8JmERBvOLGZFx0dXWbdiftycnIUExNT4vjyjj1x/4nXK80XX3yhcePGlbn/+uuv1/Dhw8s9B3yn6JHxxMREmabp5zQIZA6Ho/h/k5KS/JwGgYp7CqzgfhJ63C63rfqoiChLn/twvaf89aUx2rJih/Zt2V9u3W0vj1aLds18lCpwcU+BFeF6PwECDQ3AEJKVlaVDhw6VuT87O9tri6Hg9BV94wRUxDAM/g6jQtxTYAX3k9BRq1GNCptVJ6rdpKatz3243VOSalbRfxY8rX+NekOrZ68rtcYZ4dDvK7cpZW9X1WpUw8cJAxP3FFgRbvcTINDQADwDRSP5JCkvL6/MuhP3nXhM0X+Xd+yJ+088tjRxcXGqWbNmmftjY2PlcrnKPQd8xzAMORwOud1ufhOGcjkcDhmGIdM05XbbG+mB8ME9BVZwPwk9F4zsXWaj6mRVaiaq88D2lr4fDOd7SkL1yvrn1If1yJDntHbexlP2uwrdmvPFIv0ya51emP2YGrWp74eUgYF7CqwI1vsJTW2EGhqAZyAmJkYxMTHKyclRampqmXVF+4rqixTN7VfesSfur2hY/ciRIzVy5Mgy96ekpDCPYABxOp1KSkrS0aNHacyiXElJSXI6nXK73fwdRpm4p8AK7iehp23/lqrRsJoO/3GkwtpBt/RRZtYxKavi84b7PeXrF6aV2vw7Ufqho3r8shf00pInFBEZno0C7imwIljvJ9WrV/d3BMCjGIN7BgzDUP36x3/jV94KvUX7GjRoUOL1oj+np6crIyOj1GOPHj2qo0ePSvpzNWEAAABAkiKjI/XAZ39VQvX4cuvOu6yLLh07yEepglt+Tr5mfjjfUu3BXYe1asYar+YBAMATaACeofbt20uSfv311zJr1qxZU6K2SJs2bRQRcXwQ5urVq0s9tui8kZGROuuss840LgAAAEJMwzb19M8ZD6vHFV0VEVXyAZ/qDarqhqev0th3bpLDybf+Vvz60wZlpWdbrl848WcvpgEAwDN4BPgM9e7dW99++62Sk5O1bNkyde/evcT+pUuXKjk5WYZhqG/fviX2xcbGqmvXrlq2bJmmTJmiXr16lZhnwOVyacqUKZKkbt26KTY21uvvBwAAAMGnZqPquvOdmzQq5Zi2rNqh/Jx8Va1TRS27NqPxZ9PhPeVPz3OylL326gEA8Iew+m4gIyOjeMvMzCx+PSsrq8S+wsLCEsfdcsstuvTSS/Xqq6+ecs4mTZqod+/ekqQ33nhDP//8s0zTlGma+vnnn/Xmm29Kkvr27VvqI7wjRoxQRESEtm/frldeeaV47oy0tDS98sor2r59uyIjIzVixAhPfRgAAAAQohKqV9Y5F3XQ+cO6qvV5LWj+nYbIaHtjJE4edQkAQCAKq3+tylog47nnnivx52effVbt2rWzfN477rhD+/fv15YtW/Tcc88pKipKkpSfny9Jat26tf7617+WemzDhg11991367XXXtOiRYu0ePFixcbGKivr+OzMERERuvvuu4vnGgQAAABOVpBXoN0b9ykvO0+JNRJUr2VtGYbh71hBqWXXpl6tBwDAH8KqAegtMTEx+te//qXvv/9eCxYsUHJysiSpWbNm6tu3ry6++OLiuf5K06dPHzVo0EDffvutNmzYoIyMDFWtWlXt2rXTFVdcoSZNmvjqrQAAACCIZKZnadobszRv3FIdO/LnEy4N29TTRX/pr77Xd6cRaFOT9g3VrFMjbf91t6X6C0b39nIiAADOnGGapunvEPCNlJQUf0fACZxOp5KSkpSWliaXy+XvOAhgSUlJcjqdcrlcxdMEACfjngIruJ+EltQD6Xr2yteUvPVAmTW9rjlXt78+Sg6HvUeBw/2esnnZVj171WtyFZT/3geM6qVbXhruo1SBh3sKrAjW+0n16tX9HQHwKCYFAQAAAIKMaZr6z43vltv8k6RFXy3XlNdm+ihV6Direwvd+9FfFB0bXWZNkw4NdcUDQ3yYCgCA00cDEAAAAAgyGxf/rm2/7LJUO/2dOcrPyfduoBDUZVB7vbriafUb2aPUxVR2rv1Dd5/zmH78YJ4f0gEAYA8NQAAAACDIzB+3zHJtZlqWfpm5zotpQteR5DQtmbRCbpe71P2F+YX69JGvNOvD+b4NBgCATTQAAQAAgCBzcNchW/UHdh72UpLQ9vH/TVB+TkGFdV889a2OpWZWWAcAgL/QAAQAAACCjP1FPfi2364da3dr++pdlmoLcgs0f9xS7wYCAOAM8J0AAAAAEGSadGjo1XpI6xf8Zqt+w0J79QAA+BINQAAAACDIDBjVy3Jt7SY1dHavVl5ME5rysvNs1edm2asHAMCXaAACAAAAQaZB67rqdc25lmqve/Ry248MQ0qskWCrvkpNe/UAAPgS3wkAAAAAQejWl0eo29BOZe43HIZueuE6nXtJZx+mCh1dL+4oZ4T1H5fOv6KrF9MAAHBmaAACAAAAQSgyOlL3fHirHvj8r+rQv42ckU5JUlxijC4Y3UsvzPuHBt7Yx88pg1fV2lV03qVdLNVWr19VXS7q4OVEAACcvgh/BwAAAABwegzDUJdB7dVlUHuZpqnC/EJFRkf6O1bIGPP8tdq9aa/2/ra/zJqY+Eq658NbFfG/BiwAAIGIEYAAAABACDAMg+afh8UnxemJqfer1zXnFo+wPJEzwqmzerTwQzIAAOyhAQgAAAAAZYivEqc73hyjK+6/WIZhlNjnKnRp9cz1enTQC/r88W/kdrv9lBIAgPLxCDAAAAAQhHIzc7Xk25VaM2ejcjJzlVAtXude0lldLurA46getmDCMn39r6nl1kx/Z44qxUXr6ocv8VEqAACsowEIAAAABJmlk1fqwwfHKzsjp8Try777RdXrV9Vd792sFuc09VO60FKYX6gJz3xnqXbqG7N04U19lFgjwbuhAACwiUeAAQAAgCCydPJKvXHbR6c0/4qk7E3Vs1e9ph1rd/s4WWj6ZeY6pR/KsFRbmF+oBeOXeTkRAAD20QAEAAAAgkRuZq4+fHB8hXV52fn64IFxMk3TB6lC29ZVO23Vb1u9yztBAAA4AzQAAQAAgCCx5NuVZY78O9nOtX9oO82oM+YqdNmqLywo9FISAABOHw1AAAAAIEisnbvJVv2auRu9lCR81GhYzWZ9dS8lAQDg9NEABAAAAIJEzjFro/+K5GbmeSlJ+Dh/WFc5bayq3Pf67l5MAwDA6aEBCAAAAASJytUr26uvFu+lJOGjSs0E9b3OWlOvba9WatK+oZcTAQBgHw1AAAAAIEicd0lnW/XnDu3kpSThZdQzV6tNz5bl1tRrVUdj373ZR4kAALCHBiAAAAAQJLpc1F7VG1S1VNvxgraq3bSmlxOFh6iYKP3f+Dt1zd8vVdU6VUruNKS4xFi17dlKOcdy/ZIPAICK0AAEAAAAgoQzwqm737tF0bHR5dZVr19Vt748wkepwkNkdKSG3TtYQ/82UIbD+HOHKWUdzdbMD+fr3u5PaPq7c/wXEgCAMtAABAAAAIJI8y5N9MTU+9S0Y6NS93e8oK2e+uHBU0eq4YzNH79Unz36tUy3Wep+023q88e+0ZzPF/s4GQAA5YvwdwAAAAAA9jRp31DPzvo/bVu9S2vnblTOsVwlVItXt6GdeOzXS/JzC/TlU99aqh3/9LfqeWU3RcdGeTkVAADW0AAEAAAAglTzzo3VvHNjf8cIC8unrlZmapal2qyjOVr63Sr1G36+l1MBAGANjwADAAAAQAV+X77Nq/UAAHgTDUAAAAAAqEB+XoGt+sK8Qi8lAQDAPh4BBgAAAIJMZnqWNi76XdkZOYpPilPb3q0VE1/J37FCWvX6VW3VV6uX5KUkAADYRwMQAAAACBIZKcc04bkpWjJphfJz/hyRVikuWr2v665r/36pYhNi/JgwdPW8qpsmvzLDcn2va87zYhoAAOzhEWAAAAAgCKQdPKonLn5R875YUqL5J0m5WXma9eF8PXXpy8pMs7ZQBeyp27y2Og9qZ6m244CzVb9VHS8nAgDAOhqAAAAAQBB4868f6cDOw+XW/LFpn96/7wsfJQo/t782Sg3OqltuTb2WtfXXN0b7KBEAANbQAAQAAAAC3M51f2jT4i2WaldOX6uDFTQKcXoqV43XE1Pv16Bb+p4y56IzwqHG7Rpo9HPXKKF6ZT8lBACgdDQAAQAAgAC36OvllmtN09TiSSu8mCa8xSXGasxz1+r+z28vsdCHq9CtXev36LmrXtejF72gfVsP+DElAAAl0QAEAAAAAtyRfWn26pPt1cOerat26N/D3yrz87J99S49OfQlmoAAgIBBAxAAAAAIcJHRkV6th3Vul1tv3v7RKQuxnCwzLUvv3vWZj1IBAFA+GoAAAABAgGt9XnN79ec281ISrJ69Xof+OGKpdusvO7V9zW4vJwIAoGI0AAEAAIAA1+PKrqcsOlGWxBoJ6jqko3cDhbFV09farF/jnSAAANhAAxAAAAAIcDHxlXT9Y5dbqr3hn1cpIirCu4HCWGZ6lr36NHv1AAB4Aw1AAAAAIAgMvLGPRjx5pQyHUep+Z6RTt7w8Qj2u6OrjZOEltnKMvfoEe/UAAHgDvxoEAAAAgsTQOy5Q1yEdNOezxVo9a52yjuYoPilW3YZ0Uv8beqhavar+jhjyOg9qp0VfL7def2F7L6YBAMAaGoAAAABAEKnVuIaGPz5Mwx8f5u8oYemcwR2VVDtRaQeOVljb6Oz6atmtqQ9SAQBQPh4BBgAAAACLIiKd+usbo+WMKP9HqUpx0brttRtkGKU/sg0AgC/RAAQAAAAAG9r1OUsPj79TVetUKXV/rSY19Ojke9WkfUPfBgMAoAw0AAEAAADApnZ9ztJrq57R3e/fojbnt1TlqvHF+1L2puqH/87W78u3+zEhAAB/ogEIAAAABAnTNHUkOU27N+5Vyt5Umabp70hhzXS7tWTSSm1aukXHUjOLX3cVuLTsu1/05CUv6ZsXv/djQgAAjmMREAAAACDAud1uLfpquWZ+OF871/5R/HrDNvV04c191ff67nJGOP2YMDx9+OB4rfpxbbk1k178QVVqJuqC0b18lAoAgFMxAhAAAAAIYIUFLr1+64d6567PSjT/JOmPTfv0wf1f6qVR7yg/t8BPCcPT/u0HtWDCMku1k178XoX5hV5OBABA2WgAAgAAAAFs3NPfavm01eXWrPlpgz7+vwk+SgRJmvv5Ysu16Ycy9MvMdV5MAwBA+WgAAgAAAAEqI+WYZn+80FLtggnLlLI31cuJUGTXhr226ndvtFcPAIAn0QAEAAAAAtTib1ZYfnTUdJuaP36plxOhiNvttlVvulmwBQDgPzQAAQAAgAC1b+sBW/XJ2w56KQlOVrd5bVv1dZrV8lISAAAqRgMQAAAACFCG3Xq7B+C09R/Zw3JtbEKMug3t5MU0AACUjwYgAAAAEKAatqlnq77BWfbqcfqatG+ojhe0tVQ75PYBqhQX7eVEAACUjQYgAAAAEKB6XNVNUTGRlmqdEQ71va67lxPhRHe+faOadW5cbk2f67pr2H2DfRMIAIAy0AAEAAAAAlRcYqyG3jHQUu2FN/dVlVqJXk6EE8Ulxurxyfdq+OPDVLNhtRL7ajWpoWH3DtYtLw+Xw8GPXQAA/+JfIgAAACCAXfngxep/Q89ya3pc0VUjnrjCR4lwoqiYKF1y54V69Lt71XVIR0VERUiSDu48rMn/maF7uj2uaW/OkqvQ5eekAIBwFuHvAAAAAADK5nA4dMtLw9Xlovaa9eF8rZu3WaZpSpLa9mqlC2/qq3OGdJDBCiB+s3/HIT192StKP3j0lH1H9qVp3NOTtWXFDt394a2KiHT6ISEAINzRAAQAAAACnGEY6jywnToPbKfcrDxlH8tRbHwlVYqv5O9oYc9V6NJLN7xdavPvRKt+XKtJL32va/9+mY+SAQDwJx4BBgAAAIJIpbhoVa1dheZfgPh19gYlbz1gqXb2RwuUl53v5UQAAJyKEYAAAAAAcJoWTFhmuTbraI5+mblW5w/r6sVEABA65s+fr/nz50uSxowZo8aNG/s1TzCjAQgAAAAApyllb6qt+sN77NUDQDibP3++nnrqKUlS3759aQCeAR4BBgAAAIDTFBFlb1GPyCjGYAAAfI8GIAAAABAEcjJzdfiPI8pMy/J3FJygxTlNbdY38VISAADKxq+fAAAAgABlmqbWzt2oH9+fp3XzNss0TUlSs86NdeGNfdTzqm5yOPmdvj9dMLqXZrw711Jto7b11bwLDUAAgO/x3QIAAAAQgEzT1GePfq0Xrn9La+duKm7+SdL21bv09thP9eINbys/t8CPKVG3eW0NvLF3hXUOp0MjnrhChmH4IBWAcDN//nwZhiHDMPTkk09KkrZt26a7775brVq1UlxcnGrXrq0LL7xQs2bNOuX4pUuXavjw4WrWrJkqVaqkWrVq6eqrr9batWtPqS0sLFTlypVlGIZ69OhRZqYRI0YUZ2rVqlWZdX/729+K6zZu3ChJevLJJ2UYRvH8f5LUr1+/4rqijTkBraMBCAAAAASgaW/O1o/vzyu3Zs1PG/TB/V/6KBHKMvrZa9RvxPll7o+KidRd792sdn3O8mEqAOFs8uTJ6tSpk15//XVt2bJF2dnZOnjwoGbPnq1Bgwbp2WeflXT8l01PPPGEevToofHjx2vHjh3Ky8vToUOH9M0336hr166aNm1aiXNHRESoV69ekqSVK1cqMzOz1Azz5v35b9iWLVu0b9++Uuvmzj0+irpWrVo6++yzz/i9o3Q8AgwAAAAEmLzsfE19/UdLtYu+Xq5h9w9RnaY1vZwKZXFGOPWX/9ygvsN7aNZHC7Rx8e/KOZajSvHRatqhkc67rIs6X9jO3zEBhInVq1frhRdekNPp1J133qlu3brJ6XRq/vz5+vjjj1VYWKhHH31UPXr00OrVq/X000+rUaNGGjNmjFq3bq2srCx99dVXmjVrlgoKCjRmzBj9/vvvql69evE1+vfvrxkzZqigoECLFi3S4MGDS2TYvHmz9u/fX+K1uXPn6oYbbijx2v79+/Xbb79JOj7Cr8h1112njh07asKECZo4caIk6Z///Kfatm1b4vjY2Ngz/4CFCRqAYcTptLdCGbyr6PPB5wV28PWCsnBPgV18rQS2lT+sUdbRHMv1879cqpFPXumx63NPOT1nnddCcYmxys7I1pqfNiovO1+/zt6gX2dv0LinvtWgW/pp2D2D5YwIvY8rXysoC/cT35s2bZoaN26suXPnqkmTP+cdHT58uHr27KnRo0dLksaOHautW7fq4osv1tdff62YmJji2ptvvlmjR4/WZ599ptTUVH388cd68MEHi/ef2KybM2fOKQ3AotF/MTExatWqldasWVNqA/DEUYL9+/cv/u/WrVurdevWWrNmTfFrPXv2VN++fU/jIwKJBmBYSUpK8ncElCIhIcHfERAknE4nf49RIe4psIL7SeA7vPOIrfr92w555XPKPcWeTT9v0eOD/63sY6c2b48ePqavnp+qPRuT9cQ3D4RUE5B7CqzgfuJbX375ZYnmX5FRo0bpmWee0datW7VhwwbVrFlT48aNK9H8K/LMM8/o888/l2ma+vHHH0s0ADt16qSkpCSlpaUVP8J7oqLXzj//fHXr1k1r1qwp0ew7uU4q2QCE59EADCNpaWn+joATOJ1OJSQkKCMjQy6Xy99xEMASEhLkdDrlcrmUkZHh7zgIUNxTYAX3k+CRk5trq76woMCj3+txT7EvNytPj1/+QqnNvxMtm7pKHz72pa5+6BIfJfMe7imwIljvJ8Hc1O7cubPOP7/seUl79OihrVu3SjreECyrOdugQQM1atRIu3bt0qZNm0rsczgc6tOnj7777jutXbtWqampqlq1qqTj8wrOnz9f0vGmXrdu3fT8889r9+7d2r59u5o1a1Z8nqIGYMOGDUu8Ds+jARhGgulmG05cLhefG1jG1woqwj0FVvF1Etjqtaxtq75ui9pe+ZxyT7Fu4dc/6+gha02wmR/O0yV3DlRkdKSXU/kOXyeoCPcT3znvvPPK3V+79p//xnTr1q3C2l27dpX6S6Z+/frpu+++k9vt1rx583Tllcenoli7dq2OHDk+kn3AgAFq3769oqKilJ+fr7lz5xY3+nbv3q2dO3dKYvSfL7AKMAAAABBgzr2ks2IqV7Jc329kDy+mgRWLv15uuTYjJVPr5m/2YhoA4axatWrl7o+OjrZdm5eXd8q+E5t2Jz7KW/Sob0JCgs455xzFxMQUNyVPrOPxX9+iAQgAAAAEmEpx0Rp6x0BLtd0v76J6LeyNGITnpSbbewTbbj0AWOVwWG/12Kk9Wdu2bVWz5vEV6Etr7PXu3bt48ZeiBt+J8wDSAPQtGoAAAABAALr83os04Iae5da07dVKt706ykeJUJ7ImChb9VE26wEgEBWtyvvbb78pOTlZLpdLCxculFSyqVf03wcPHtTGjRsl/dkMbNGiherVq+fD1OGJBiAAAAAQgBwOh25+abju/egvOuv8FiX2NTirnm5+cbgenjBW0bE0kgLBWec1t1XfqhuT3QMIfic/Brxq1ariRYEGDBhQvO/cc89VbGxscd3vv/+uffv2nXIOeA+LgAAAAAAByjAMdRvaSd2GdlJGyjEdS8tSTHwlJdVOlGEY/o6HE1wwprd++nSRpdp2fc5S7aY1vZwIALzv5Abg3r17JUk1atRQu3btivdFRUWpR48emj17tubOnavIyMhSz3GyEx9RNk3Tk9HDDiMAAQAAgCCQUL2y6rWorap1qtD8C0CNzq6vC0b3qrAuOjZaI564wgeJAMD7WrRoofr160s63gAsmtevb9++p/xbVdToW7BggX766SdJx3/R1a9fvzLPHx8fX/zfWVlZHs0ebmgAAgAAAIAHjHn+Wg0YVXYTsHK1eP3fhDvVqG19H6YCAO8qauDt3r27eF6/Ex//LVLUAExLS9OUKVMkHV9IpEaNGmWeu0mTJsX/vXr1ao9lDkc8AgwAAAAAHuCMcOqWl4brgtG99NMnC7V52VblZucrtnIlnd2rlfpc111N2jf0d0wA8Kj+/fvr888/lyQVFhYWv3ayLl26KCEhQRkZGeXWnah3796KiopSfn6+XnzxRUlShw4dFB0dLUmKiYlRnz59PPZeQhkNQAAAAADwoMbtGujyewfLlLRk0gqlJqdp7+/7NfOD+WrRpYkuvuMCnXtJZ3/HBACPOPkR3gYNGqhFixan1DmdTvXu3Vvff/998WsVNQCrVaumhx56SM8884wyMzP1xBNPlNjfqFEj7dq16/TDhxEeAQYAAAAAD9q9ca/+ceHzmvv5YuVl55fYt/WXnXr15vc18bkpfkoHAJ7VqFEjNW3atPjP5c3pd2LDz+l0Whq9989//lNff/21hgwZorp16yoqKurMAocpw2QZlbCRkpLi7wg4gdPpVFJSktLS0uRyufwdBwEsKSlJTqdTLpdLaWlp/o6DAMU9BVZwPwlOR/al6mjKMUXHRqtO05pyOL3/O3zuKacvNzNX9/d8WqnJFf8d+9t/b1TPq7r5IJV3cE+BFcF6P6levbq/IwAexSPAAAAAQIAxTVM/T12tH9+bqy0rdxS/Xr1+VQ0Y3UsX3dJPleKi/ZgQZVny7UpLzT9JmvrGTPW4siurOgMAvI5HgAEAAIAAYpqmPnpovF6/9YMSzT9JStmbqonPTtFTl76sjCOZfkqI8swfv9Ry7Z7Nydr+624vpgEA4DgagAAAAEAA+f6t2frp00Xl1uxav0ev3fK+mM0n8BzcZW/anYO7DnspCQAAf6IBCAAAAASIgrwCTXtrtqXaTUu2aOtJIwThf06bczQ6I/iRDADgffxrAwAAAASIX2au0zEbj/bO/WKJF9PgdDTt2MhWfZP2Db2UBACAP9EABAAAAAJE8taD9uq32auH9w0Y3ctybYf+bVSrcQ0vpgEA4DgagAAAAECAcDjtrQbrcLB6bKDpOOBstenZssK6yOgIXfXQJT5IBAAADUAAAAAgYDQ8u76t+kZt7dXD+xwOh+77+Da17t6izJro2Cjd+/Ftat65se+CAQDCWoS/AwAAAAA4rmP/s1W9flWl7E21VN//hp5eToTTEZcYq0cn3a0VP6zR7I8XaMvKHXIVuFS1bpJ6X3uuLhjdW9XqJvk7JgAgjHh0BODChQu1cOFCpaZa+4alSHp6evGxAAAAQLhyOB266qGhlmrPu6yLGtkcMQjfcUY41f2yLvrHN3frzrdv1Nm9WiknI0c//PcnPX/N65r25iwdS7W+4AsAAGfCoyMA+/btK8MwNHnyZF166aWWj1u+fLkGDx4sh8OhwsJCT0YCAAAAgkqf67rr6KEMjX/muzJrOvRvo9tfG+W7UDgtmWlZeumGt/X7iu0lXt+35YDGPT1ZU9+cpQc/v0Mtuzb1U0IAwcztzpVhOP0dwy9MU3I4Iv0dI6gE1CPApmn6OwIAAADgd5feNUhterTUjx/M14rvV6sg7/gvyVt1a6aBN/VR98u6yOFkOu9A5ip0ldr8O1Fmapb+dd0bembmw6rbvLYP0wEIdu6MZ6XsTxW+XRRDZrWpMiJb+TtI0AiIBmBR488wWMUMAAAAkKTmXZrozi5NVPj6KGVn5Cg6JkrRsVH+jgWLVvywptzmX5GcY7n69uUZuvPtG32QCkDIyP/F3wn8ypQpuf6gAWhDQPzaMD09XZIUGxvr3yAAAABAgImIdCqhWjzNvyDz0yfW5zdfPm21MlKOeTENgFDjdrtllvN/7hD5v/Leo0y3vz8NQSUgRgB+++23kqSGDRv6OQkAAAAAnLltq3dari3ML9TujXvVrs9ZXkwEIJS4TdlqgJk2Hxb21POZdq5q95o8Q2rPaTcAp0yZoilTppS67/XXX9d3331X7vGmaSorK0tr1qzR9u3bZRiGevfufbpxAAAAACBguApctuoLbdYDCG9uuSWd/gi4UJg70BES78J3TrsBuGbNGn3yySenzNtnmqbmzZtn61ymaSouLk733Xff6cYBAAAAgIBRo2F1HdhxyHJ9zYbVvJgGQKgxDdP2qL5yz+eDZpphccyeL7KEozOeA9A0zeKttNcq2hISEnTFFVdo6dKlat68+ZnGAQAAAAC/63PdeZZrm3dprHot63gxDYBQ4zYll+n22OY2Ta9v3sgC6057BOA999yjMWPGFP/ZNE01bdpUhmHo3Xff1cCBA8s93uFwKD4+XklJSacbAQAAAAACUv+RPfX9f39SVnp2hbWX/O1CHyQCEErcBuPkmAXQntNuACYmJioxMfGU103TVM2aNdWoUaMzCgYAwSQzPUuLv16uXRv2yu1yq27zWup9bXdVrVPF39EAAEEoPydfa+dtUtqBo4qOjVLr85qrVuMa/o4FGxKqV9b9n96ufw9/S7lZeWXWXfngxeo2tJMPkwEIBcUr4frt+gHQfvN7gODi0VWAd+48vtJVzZo1PXlaAAhYbrdbk178Qd//d7bycwpK7Pv6he/Vb/j5Gv3cNYqMjvRTQgBAMCnML9Skl3/QT58sUmZaVvHrhmGoQ/82Gv7EFWrQuq4fE8KOs7q30NMzHtK3L0/Xyh9+lavwzwn7m3VqpEvuvFDnXtLZjwkBBCtThtx+HgPo7xGI/r5+sPFoA5BRfwDCiWma+vjhCfrp00Wl7ne73Jrz+WIdSU7TA5//Vc4Ip48TAgCCSWF+oV4c+V+tm7/5lH2maWrNnI36fcV2PfL13WreubHvA+K0NGhdV3e/f4vSD2Vox7rd2v7LLmWlZym+arwK8wuVn5OvqJgof8cEEGTcMhXua4ebzAFoi0cbgAAQTtbP31xm8+9Ea+Zs1NzPF2vgjX18kAoAEKy+efH7Upt/J8o5lquXR7+j11Y8TdMoyGxY+JsmPj9FKXtSS7weVyVWQ24boMvvvUgOxxmv0QggTLglv48A9DsjzN+/TV5tAO7fv18bNmxQWlqacnNzLR0zatQob0YCAI+Z+dF8y7WzPl6gC8b0lmEwUQUA4FR52fn66ZOFlmrTDx7Vsim/qM913b2cCp4y/Z05+vzxb0rdl5Wera9fmKaDuw7r9tdH8b0CAEvcpluuMB8BF97v3j6vNAAnTJigf/3rX1q/fr2t4wzDoAEIICgU5hdqzU8bLdfv/W2/Duw8rDpNmSMVAHCqNXM2KOtojuX6xV8vpwEYJHau36MvnphUYd3CiT+rTY+WfF4BWOI2AmEEoKd/YWHv/YR5/9M2jzcA77rrLr311luSeB4bQOjKycyV2+WuuPAEWenZXkoDAAh2R5LTbNWn7k/3ThB43KwP51v+uejH9+ep97XnMQoQQIVM05S9n0a8ksK/l+dWaYtHG4BTp07Vm2++Wfznc889VwMHDlT9+vUVHR3tyUsBgF/FxFeSw+mw1QSMqxLrxUQAgGAWVcnefH6RlVhdPhiYpqll3/1iuX7X+j08MQDAElOm30fA+fp3Fae8X5MOoB0ebQC+++67kiSn06lPPvlEI0aM8OTpASBgRERFqOOAs7V6lrWpDuq1qqPaTWp4ORUAIFid1b25vfrzW3gpCTwpLztfedl5to45eiiDBiCACpknbH4N4c/L0/+zxaPLTK1atUqGYWjkyJE0/wCEvAtv6mu99sY+PM4DAChTvZZ11KZnS8v1F4zu7cU08JSoSpEyHPb+/a8Ux5NTACrmlkNulWwEukN4M3Xqe2XaOXs82gA8evSoJGnAgAGePC0ABKT2/c7SgBt6Wqhro/4W6gAA4W3kk1cqOrbiR4EH39Zf9VrU9kEinCmH06G2vVpbrq9SK1H1W9f1YiIAoaLQ7ZZLKrGV1jg7uSZYt8KTNpf8PgAx6Hi0AVirVi1JUmQkc5IACH2GYeimF6/X5fdeVOpcTA6nQ/1GnK/7P71dEZFOPyQEAASTJu0b6uHxdyq+alyZNRf9pZ9GPnmlD1PhTA280fpozQE39OR7BgCWmKZDblMVbIbMkzZ30GwVvTd/fwaCj0fnADz33HO1d+9ebd682ZOnBYCA5XA4dO3fL9PFt1+ghV/9rN0b9sp0m6rTvJZ6X3ueqtVN8ndEAEAQOat7C72+6hkt/maFlkxaobT96YqKjVKbHq00cExv1W9Vx98RYVOXi9qr65COWjl9Tbl1Dc6qpyF/5UkqANa4ZcoVpMvgmrKygG/FFfQA7TFMDz40PW/ePA0YMEBNmzbV5s2bGQkYYFJSUvwdASdwOp1KSkpSWlqaXC6Xv+MggCUlJcnpdMrlciktLc3fcRCguKfACu4nsIp7imcV5BXogwfGaeHEn0vd37p7C93zwS1KrJHg42RnhnsKrAjW+0n16tX9HaFcW5OHKM+15gzP4s8G4pm3ohpU+1CJsYM9kCU8eHQEYL9+/XTnnXfqzTff1JgxY/TJJ5/QBAQAAAAQ1iKjI/XXN0br0rEXas7ni7Vz3R6ZLrdqN62pfiN6qGW3piwWBsAeQzI93sDz5n3o5IbfmV+LNUDs8WgD8I8//tD999+v1NRUjRs3TqtXr9Ydd9yh7t27q3r16nI4Kp5ysGHDhp6MBAAAAAABoV7LOhr55JVaM3ej5n6+WJuWbtHGJb+rXova6j+yp7pc1F7OCOYABFAxUw6Zpu9/cVBWz80Tj/Tava7h2WUtQp5HG4CNGzcu/s2VYRjasmWL7rnnHsvHG4ahwsJCT0YCAAAAgICQkXJML416R1tX7SjxesqeVK2du0mNzq6vB7+8gzmEAVTINCV3AM0B6I/BeKbBEEA7PN4uNU3zjDYAAAAACDX5Ofn613VvnNL8O9HujXv17JWvKutotg+TAQhGLhlhv9FCssejIwBHjx7tydMBAAAAQEiYP26pdq7bU2Hd/u2H9OP783TlAxf7IBWAYOUyFLSrAHuKydyptni0Afjxxx978nQAAAAAEPRM09SsTxZarp/7+WINu3ewHE7mtwJQOtN0yG2G9z3C9MuDx8HLow1AAAAAAEBJWenZ2vf7fsv1qfvTdWh3imo3renFVACCmft/j8GGM38sghLMaAACAAAAAcDtdmv9/N+06OvlOrIvVZHRkWp1bjP1G9lDVWtX8Xc8nIH8vAL7x+TaPwZA+HCbkjvcG2AMALSFBiAAAADgZwd3HtbLY97Vns37Sry+fsFmTX5lui6/Z7CufPBiGcx3FJQqJ8UpMjpCBXmFluoNw1BS7UQvpwIQ3Bwy/TwC0FdXL7PPZ4T3I9B2ea0BmJ6ervfff18zZ87Upk2blJqaqsLCQhUWlvxHb+7cuTpw4ICqV6+uCy+80FtxAAAAgIB0JDlNT132stIOHC11v6vQrUkv/aCC/EJd/+jlvg0Hj4iMjtR5l3XRoq+WW6rvNLCtKleN93IqAMHMlCl3mDQAT2b+79oMALTHKw3AiRMn6rbbbtOxY8ckHZ/0VlKpv7Fcu3at7r//fsXExGj//v1KSEjwRiQAAAAgIE145rsym38nmvr6TPW6+lzVb1XHB6ngaYP/0l+Lv1kh013xj6yDb+vvg0QAgplbDpk6PgIu3BphhiS3wu99nymPj5f87LPPNHz4cGVkZMg0TdWuXVstW7Yss37MmDGKiIhQbm6upk2b5uk4AAAAQMDKSDmmn6eutlw/++MFXkwDb2rSvqFu/vf1FdZd/+jlaturtQ8SAQhmLhlymZLLLJoP8M/N5aXt5Ov467pFr9MAtMejDcDk5GTdfvvtMk1TdevW1axZs7Rv3z698MILZR6TlJSk3r17Szr+ODAAAAAQLjYv26rCfGvzwknSunmbvJgG3jZgVC89+MUdatK+wSn76reuo7vev0WX3jXID8kABBu325BbpW/m/0YHFm1uD22uCjZPXefU6xqnbG4ZMukA2uLRR4DffPNN5ebmKiYmRnPmzFGrVq0sHdetWzfNnTtXa9eu9WQcAAAAIKDlZObaqs/NyvNSEvhK5wvbqdPAttq57g/t2ZyswkKXEqrGq0mHhkqqxcIfAKxxy5DrNMd0ldU38/acfqVd19o1y6hiYSxbPNoAnDVrlgzD0PDhwy03/ySpefPmkqRdu3Z5Mg4AAAAQ0BKqV7ZVX7mavXoEJsMwVLlqvP7YuE8LJixV1tEcSVJ81Tj1G95DF93aT1XrVPFvSAABzS1DLvN0G2CB1jg7vaF8jAC0x6MNwJ07d0qSevbsaeu4xMTjv+kqWjQEAAAACAdte7VWfFKcMtOyLNWfP6yLlxPBFzYv26oXR/5XOcdKjgDNTM3StDdnad64JXp43J1q3rmxfwICCHhFj/d6hq8bgid37kKlkRnYPDoHYFbW8W9c4uPtLVmfk3P8N16VKlXyZBwAAAAgoEVVitSAUdZ+eR4VE6m+w3t4ORG87eCuw6U2/06UmZqlF4a/qdT96b4LBiDIGDI9tqnczW1jq+hcx7czy/vnXIeww6MNwGrVqkmSDh48aOu4rVu3SpJq1KjhyTgAAABAwLvi/ovV+rzm5dYYDkN/fWO0qtRM8FEqeMv0d+aU2/wrkpmapZkfzvd+IABByS2HXKbhk81tOixvLtP7udz/20zToy2tkOfRj1abNm0kSQsXLrR13LRp02QYhrp04ZEGAAAAhJeoSpH6vwljdcHoXoqMPnWGnrrNa+nhcXfqvEv5XjnY5ecWaNFXyy3Xz/tyidwutxcTAQhWx0fceW/l3ZJb2SsOl775JhdPANvj0TkABw8erDlz5mjKlCnaunWrWrRoUeExEyZM0Jo1a2QYhoYMGeLJOAAAAEBQiI6N0s0vDtc1f79UP09drdTkNEVGR6rVuc3UpkdLGax0GBKO7Eu1tfLzsSOZSj+coaq1q3gvFICgVDQCMJyxCIg9Hm0A3nLLLXruueeUlpamSy+9VNOnT1eTJk3KrJ84caJuvfVWGYahunXravjw4Z6MAwAAAASVylXjNXBMb3/HgJeY/LQKwEPc5vGRduHMNLin2uHRBmBCQoLefvttXXfdddqyZYvatm2rYcOGKTo6urjmrbfe0p49e/Tjjz9q/fr1Mk1TTqdTH330kSIjIz0ZBwAAAAACRvV6VRUdG6287DxL9fFJcUqsXtnLqQAEI7ckV7g3AHkG2BaPNgAl6eqrr1Z6errGjh2rnJwcjR8/XpKKH1u46667imtN01RUVJTeffddDRw40NNRAAAAACBgRMVEqdfV3fTTp4ss1fcdfr6cEU4vpwIQjIoW3QhnDKq2xytfLbfeeqtWrlypyy+/XIZhyDTNUzZJGjJkiJYvX67Ro0d7IwYAAAAABJQhf71AleKiK6yLS4zRRbf09X4gAEHL9PPm7/fG/Lj2eHwEYJF27drp22+/1dGjR7VkyRLt2rVL6enpio+PV/369dWrVy/VqFHDW5cHAAAAgIBTp2lN3f/p7Xp59DvKzSr9UeC4xBg9+MXfVK1eVR+nAxAs3MbxFXf9yZdXP7nhaEgyw3wEpF1eawAWSUxMDKjVfY8ePapvvvlGK1as0JEjRxQdHa1mzZppyJAhOu+882yf75FHHtGGDRss1Q4YMEB33313iddeffVVzZ07t9zjGjZsqDfffNN2NgAAAACBp23v1np+ziOa/u4cLfpqeXEjMDYhRr2vO09DbhugGg2q+TklgEDmNsUjwF4fhxhavN4ADCR//PGH/vGPf+jo0aOSpJiYGGVlZWnNmjVas2aNLrnkEt166622zhkfH68qVaqUub+wsFCZmZmSpGbNmpVZFxUVpdjY2FL3JSQk2MoEAAAAILDVblpTN71wvUY+dZVSk9OUmZql/Lx8RVWKUlxi6T8XAEARUw6ZJ83qFurtsBNHHJqnvIKKhE0DsKCgQM8884yOHj2qRo0a6b777lOTJk2Ul5enKVOm6Msvv9S0adPUpEkTXXDBBZbP+8gjj5S7/6uvvtIXX3yhyMhI9enTp8y6nj176p577rF8XQAAAADBb9e6PzT1zVlaPWu9TPfxH2kjK0Xq/MvP0aV3Xai6zWv7OSGAQFToMuSqoOPnqYagnTabJ5uQFV3X7cFrhQOvNgDdbre2b9+utLQ05ebmWjqmd+/eXskyc+ZMHThwQNHR0Xr88ceL5x+Mjo7WNddco9TUVE2fPl1ffPGF+vbtq4gIz3xo5s2bJ0nq2rWrKleu7JFzAgAAIPSkHkjXkb2pckY6Va9FHUXHRvk7Erxs4cSf9e49n8vtKvljbEFugRZMWKYV3/+qB7+8Q2d1b+GnhAAClSmHXOW2yE7dZ7U558lxdXYagqVft7wzMALQDq80AOfPn6+XX35Zc+bMUV5e6RPblsYwDBUWFnojkubPny/peIOxtMVHrrzySs2YMUOpqalav369OnXqdMbX3Lx5s/bt2ydJtkYVAgAAIHxsWPibpr01W+vmbSp+LaZyJfW+9jxdcueFqlY3yY/p4C1bVu4otfl3opzMXL10w9t6cdHjqlqniu/CAQh4phw25wA8/Yag75SWqOwmn9sMvHcQyDw+Y+Q//vEPDRgwQNOnT1dubq5M07S1eUNOTo62bt0qSercuXOpNTVq1FD9+vUlSWvXrvXIdefMmSNJqlq1qkcaigAAAAgt09+Zo2eveq1E80+Sco7lauYH8/WPgf/SH5v2+SkdvGnam7PKbf4Vyc7I0exPFvggEYBgYsosngfQ2macsingNoetzWAEoC0eHQE4efJkPf/888V/bt68uXr27KnatWsrOjrak5eyZe/evcXNxUaNGpVZ16hRI+3Zs0d79uw542vm5eVpyZIlkqS+ffvK6XSWW79u3TrddtttOnz4sKKiolSnTh116dJFF198sZKS+K0vAABAqFk9e70+f/ybcmuOHs7QC8Pf0kuLH1dMfCUfJYO3ZaQc0y8z11mun//lUl3zf5fKMPhhF8BxpuEI+znwwv392+XRBuAbb7xx/KQREXrvvfc0ZswYT57+tKWmphb/d9WqVcusK9qXlpZ2xtf8+eeflZWVJUkaMGBAhfUpKSlyOp2KiYlRdna2tm/fru3bt2vGjBl66KGH1KFDhzPOBAAAgMAx5dUfLdWlJqdp0VfLdeFNZS8oh+ByaHdK8YIfVqQfylBeVp4q0QQG8D9uGXKb3vylgP1Hhr39kPHJZ3MwAtAWjzYAf/31VxmGoZtuuilgmn+SSixAUt5IxKJ9OTk5Z3zNn376SZLUsmVLNWjQoMy6Zs2aqWXLluratauqVasmh8Oh7OxsrVixQp988olSU1P13HPP6ZVXXlG9evXKveYXX3yhcePGlbn/+uuv1/Dhw0/vDcHjin6Dm5iY6LXH3xEaHA5H8f8yIhhl4Z4CK7ifBI4/Nu/TlpU7LNcvnPCzrr3/cu8FOgn3FO9KrJJacdFJqlavpuiYwFoYhnsKrOB+4h2macjt+VndKvBnw83UqQ0/85QWnXcbdC6vnj30eLQBWLSAR9++fT152qBz+PBhrV+/XlLFo/8uueSSU16LjY1V37591aZNG91zzz3KzMzU+PHj9cADD5R7rqysLB06dKjM/dnZ2RU+igzfK/rGCaiIYRj8HUaFuKfACu4n/rd/+0Fb9fu27vfL54x7inc0atNAlWKjlZttbcHEBq3qKjY+xsupTh/3FFjB/cSz3HLI5fMGYEV8PSIv0N5/YPNoA7BRo0bavHmzXK7A6sNWqvTnUPm8vDzFxsaWWle0YnFMzJn94zpv3jy53W5FRUWpV69ep32emjVr6uKLL9bEiRO1atUqud3ucm+acXFxqlmzZpn7Y2NjA+5zE84Mw5DD4ZDb7eY3YSiXw+GQYRgyTVNuNzNdoHTcU2AF95MAYtj7e+pwOnz6fRz3FO+Kjo1S3+t66MeP5lqqH3LrBQH5fTz3FFgRrPeTQG9quyUvPwIc+E4dcYjyeLQBOGjQIG3evFkrV67UiBEjPHnqM3LivH+pqallNgCL5go80+Hrc+ce/4f83HPPVXx8/Bmdq2XLlpKOj947duyYEhMTy6wdOXKkRo4cWeb+lJQUj8xvCM9wOp1KSkrS0aNHA/IbOgSOpKQkOZ1Oud1u/g6jTNxTYAX3k8BRtWGV4saJFY3a1vfp54x7ivcN+ksfLfxmmbIzyp9+qFbjGuo2rGNA/p3lngIrgvV+Ur16dX9HKJfbNAJwBKBv0f6zx6NfLWPHjlVsbKw+/vhjj6yk6yn169cvnnfgjz/+KLOuaF95c/ZVZNOmTUpOTpYkXXDBBad9HgAAAISu6vWrquMFZ1uuv2D06T9VgsBUu2lNPTzub4qrUvrgBEmq3aSG/v7VWMVWDtzHfwH4h1uGTDO8N4X5CEi7PNoAbNy4scaNG6ecnBz1799fK1eu9OTpT1tMTIxatGghSVq9enWpNSkpKcVNyzNZcXfOnDmSjv+2wBMr927ZskXS8fdQuXLlMz4fAAAAAsOVD1ysiKiKH8hp0r6Bul3cyQeJ4GstuzXTS4se15UPXqyqdf98Cqley9oa/ezVem7OI6rVuIYfEwIIXIZMP2/ywmbr+gYNQDs8+giwdHxRiyVLlmjEiBE677zzdM4556hbt27FK9xW5PHHH/d0JEnHFybZsmWLFi5cqGuvvVY1apT8h/Tbb7+VaZqqWrWq2rVrd1rXyMvL05IlSyRJ/fr1q/D9mqZZPDKxNIcPH9b06dMlSeeccw6TpgIAAISQZp0a654Pb9Xrf/lA+TkFpdY0Oru+Hvryb5YahQhOVWol6qoHh+qqB4cqPydfGUeOKf1ghhwRjnJ/VgAQ3tym4bU5AK08WsvdKfh4/DuJwsJCzZgxQ4cPH5Zpmlq1apVWrVpl+XhvNQAHDRqkqVOn6sCBA/rnP/+pe++9V02aNFFeXp6mTZumH374QdLxefQiIkp+WG655RYdOnRI/fv31z333FPmNZYuXars7GxJFa/+K0nz58/Xzz//rH79+qlNmzZKSEiQJOXk5GjFihX69NNPdezYMcXExOj6668/zXcOAACAQNVlUHu9uPBxzfpogRZMXKbM1CxJx+f8Gzimt3pdfa6iYqL8nBK+sHnZVn3/1mz9OntD8dyQMfGV1PPqbrp07CBVr1+1gjMACCdu+X8OQH80AYuak4YkN5MA2uLRBmBhYaGGDRtWPGpNkq1Vfrz5G67IyEg9+uij+sc//qFdu3bp7rvvVmxsrHJzc4tXrBo6dOgZzdtXtPjHWWedpbp161ZY73a7tWzZMi1btkzS8cd8IyIilJWVVZwpMTFRDz74oOrXr3/auQAAABC4ajaqrpFPXakRT16h3Kw8OSOciqoU6e9Y8KHZnyzUxw9POOVnp5zMXM3+eKF+nrpaf584Vk3aN/RTQgCBxm3q+Fx4/g7iV4xDtMOjDcCPP/64eCRdTEyMRowYoZ49e6p27dqKjo725KVOS8OGDfXGG29o0qRJWrFihVJSUhQXF6emTZvq4osv1nnnnXfa5z58+LDWr18vydroP0lq166dRo4cqc2bN2vfvn3KyMhQdna24uLi1KBBA51zzjkaNGgQc/8BAACEAcMwFBNfyd8x4GMbFv5WavPvRMeOZOqF69/SS4sfV3xSnA/TAQhUpuko9RHgUG0Ilt7qowFoh0cbgO+//74kqVq1alq8eLFatWrlydN7RJUqVXTzzTfr5ptvtnzMBx98UGFNjRo19N1339nKUrNmTV1zzTW2jgEAAAAQOqa89qOlp6aOHs7Q/PHLNPSO039iCUDoKHRLLgsNsDNtCJ5ui80X1w3VZqe3eLQBuHXrVhmGoTvvvDMgm38AAAAAECgO/3FEGxb9brl+3pdLaAAC+B+ri4CUrAmeplnFSW3MOAd5uAFYNIdfmzZtPHlaAAAAAAg5+7cftFV/YMchmabJ6sAAZBoOmX5eBMS7Kr7PuYOonRkIPPrV0rRpU0lSRkaGJ08LAAAAACHH4bT345jhoPEH4DjTS5vbC5u3rm0wB6AtHm0AXnnllTJNU7Nnz/bkaQEAAAAg5NRvXddWE7Bx2/qM/gMgSXLLkMv0/OY2HR7fXKbD4rXtbaalR6BRxKMNwDvvvFNNmzbVN998QxMQAAAAAMpRpWaCug7paLl+wOje3gsDILh4oVHn/t/KwhVtp9e483xWGaH8CLTnefSjVblyZf3www9q2rSpLrvsMr3wwgs8DgwAAAAAZRh272BFxURWWFe/dR31GHaODxIBCAYuGXL7aTNP2vyWg1VAbPHoIiD9+/eXJMXHxys3N1ePPPKIHnvsMbVq1UrVqlWTw1F+v9EwDM2ZM8eTkQAAAAAgYDVqW1/3fXy7/nPTe8rLziu1pl7L2vq/8XcqKibKx+kABCrTlMVVgEOXySIgtni0ATh//vziOSmK/rewsFCbNm2q8FhWswIAAEA4cbvd2rDwd80fv1QHdx6W0+lQkw4NNWBULzVsU8/f8eBDHfq30YuLHtPsjxdqwYSlykjJlCQ1OKuuLhjVS72v665KcdF+TgkgkLhNh1whvQqwFfSQ7PBoA1BSqUMwGZYJAAAA/Cl1f7peHv2OdqzZXeL1rb/s1KyPFqjnVd30l/+MVGR0xY+GIjTUaFBNwx8fpusfu1y5WXky3abyc/IVERWh6FhG/gEoyS2F/SIYbn8HCDIebQC63Xz4AQAAgPJkpmXpn8P+owM7DpVZs/ibFcrPydc9H/2Fp2TCzN7f92vGe3O19NuVysvOlyTVaVZTF4zprf4jezISEEAxfw+18tS/Tqf7PvjX0R6PjwAEAAAAULYpr88st/lXZMUPa/Tr7A3qfGE7H6RCIFgyaYXeHvupXIUlB1bs335Inz/2jeZ9uUR//+ouVa1dxT8BAQQMU4bf5wD01tWtNgRNM9wfgbaHjxYAAADgI/m5BZo/fqnl+lkfzfdeGASUTUu26L93ntr8O9He3/br38PfUmF+oQ+TAQhEbjlCdjNP2sqqYQigPYwABAAAAHzkj417lZmaZbl+w6LfWSwvTEx66Qe5XRVPqbR7w16tnL5G3S8/xwepAAQqt2n6fQSgv7HchD1ebQDu379fc+bM0aZNm5SamqqCggJ9+OGH3rwkAAAAELBys/Ns1bsKXHIVuBQRxe/tQ9n+HYe0ackWy/U/fbaIBiAQ5tymo3gRkHDqgxW1PE2F1/v2BK98J3HkyBHde++9mjBhglwulyQV/+by5Abg7bffro8++kgNGjTQ9u3bvREHAAAACAhVaibaqo+rEkvzLwz8sXGvvfpN+7yUBECwcLlU7gjAUGmOnfwOzXL3ojwenwNw586d6tSpk7788ksVFhbKNE2Z5YzL/Otf/6rCwkLt2rVLCxcu9HQcAAAAIGDUa1lbDc6qZ7n+/GGM8kIpQuUnewBnwCG3jDI386StvNpA3lzlbNwK7fFoA9DlcunSSy/V3r17ZZqmhg8frpkzZ+rNN98s85gOHTqoZcuWkqSZM2d6Mg4AAAAQUAzD0ODb+luqdTgdGnRzX+8GQkCo26K2vfrmtbyUBEDQcOiUJl95m0JwowFoj0cbgJ999pk2btwowzD02muv6YsvvtDAgQNVr175v+Xs16+fTNPU8uXLPRkHAAAACDh9r++uXtecW2HdTS9cp3ot6/ggEfytQeu6atGlieX6/jf09GIaAEHBNGSa8tjm9tHmyevCHo82ACdNmiRJ6tmzp8aOHWv5uLZt20qStmyxPvEtAAAAEIwMw9Dtr4/StY9cqviqcafsr9Ospu796C8aMKqXH9LBXy6/b7ClutpNa6r7ZV28nAZAoHObhkc386TNV+c9eb+dHArzVZDt8uiMwr/++qsMw9AVV1xh67jq1atLOr54CAAAABDqHA6HLr9nsIbcfoFWz1qnAzsPy+l0qGnHRmrTo6UMgx9qwk3nge005vlr9ekjX5U5h3r1BlX18Li/KSomysfpAAQaU0a5i4CcuZLntjrg7tRFOzw7VI9FQE6fRxuARQ28+vXr2zrO4Tg+ENHtdnsyDgAAABDQoipF6rxLGc2F4wbd3FeNzq6v6e/M0aof18r83zNuiTUS1G/k+Rr8lwFKqBbv55QAAsHxRTI8vq6rZUWNuPJX6S2twvMZYI1HG4BxcXFKT09Xdna2reP2798vSapataon4wAAAABAUGl9XnO1Pq+5MtOylLo/XRFRTtVsVEMRkU5/RwMQQEwdbwL6G0244OHRBmCDBg2Unp6udevW2Tpu0aJFkqQWLVp4Mg4AAAAABCVHhEO//bxNi79eriP70xVVKVJndW+uC8b0VtMOjfwdD4CfuV2S2+3/BqA/ucuYLgGl82gDsG/fvlq3bp0mTJigZ599VlFRFc9NsXPnTk2dOlWGYahfv36ejAMAAAAAQee3n7fplRvf1bEjmSVeP7DjkOZ9uVR9h5+vm18czqhAIIyZhkNmAIwA9K9wf//2ePSB8RtvvFGGYSg5OVl33313hfWpqam6+uqrVVBQoIiICN10002ejAMAAAAAQWX3xr3613VvntL8O9H8cUv10UPjfJgKQCAyw3yDPR5tAHbo0EFjxoyRaZp67733dNFFF+mnn37SsWPHimuys7P122+/6T//+Y86dOhQvHLw3XffrQYNGngyDgAAAAAElfH/nKy87LwK6+Z9uVQ71/3hg0QAApH7f6sA+3MzPbzZvT4jAO3x6CPAkvT2229rx44dWrBggWbPnq3Zs2dLkgzj+CemcuXKxbVFy9sPGjRIzz//vKejAIBf5Gbm6tAfx1dFr9GwmmLiK/k5EQAACAYHdx3W2rmbLNfP/mSh/vLKSC8mAhCo3G79rwnmP96+enmj/AxJTAFoj8cbgFFRUfrpp5/06KOP6rXXXlNubm7xPsMwipt+khQdHa277rpLzz33nJxO5q8AENyStx3Q9//9SUsmrVB+ToEkKSomUucP66qhfxuoei1q+zkhAAAIZL8v326r/rdlW72UBECgMw3D76sA+/rqJ/b7DB3/GMA6jzcAJcnpdOr555/Xfffdp4kTJ2rhwoXatWuX0tPTFR8fr/r166tPnz667rrrVK9ePW9EAACf2rDwN7006p1THtnJzynQ/HFLtey7Vbr3o9vUoX8bPyUEAACBriCvwGZ9oZeSAAh0Lrdk+nkEoD8H4DEPoH0enQPwZDVq1NCdd96pr776SitWrNCWLVu0evVqTZ06Vffffz/NPwAh4eCuw3p59KnNvxPlZefrPze9q/3bD/owGQAACCZV6ybZq69TxTtBAAQBxxnPoRds28nv17DRAD18+LDuv/9+tWjRQjExMapevbouvPBCfffdd2f0WVi5cqWGDx+uBg0aKDo6WjVr1tRFF12kyZMnWzp+zZo1GjFihOrVq6fo6GjVr19fI0eO1Nq1a88oV2m82gAEgHAw4725ys2qeLLuvOx8TX93rg8SAQACXUFegX6e+ou+fWW6Jv9nhlbPXi+3y+3vWPCzdr1bq0rNBMv1va45z4tpAAQyt9uU21SJzTxpO3l/sG0VvR/T4hjAjRs3qm3btnrllVe0bds2RUZGKj09XbNnz9awYcN09913n9bn4OWXX9Z5552n8ePHa9++fYqLi1NaWppmzpypK664QjfffHOJafBONm7cOHXr1k3jxo1TcnKyYmJitG/fPn355Zfq1q2bJk6ceFq5ykIDEADOQGF+oRZO/Nly/eKvlys/197jPQCA0GGapqa9OUt/6/iIXrvlA339r2n66vmpenHEf3V318e0YMIyf0eEH0VERWjQLX0t1SZUr6yeV3b1biAAAcyQWcGmIN8qen9W2n95eXm69NJLdejQIbVt21Zr1qxRRkaGMjIy9Mwzz8gwDL3++uv6+OOPbX30v//+ez3wwANyu90aOXKk9u3bp9TUVGVkZOj1119XZGSkPvroI7344oulHr9x40bdeOONKigo0DXXXKPk5GSlp6crOTlZV199tfLz8zV69Gj99ttvtnKVx6sNwA0bNujJJ5/UkCFD1LFjRzVr1kwdO3bUkCFD9NRTT2njxo3evDwAeF36oQzlHMutuPB/crPylLY/3XuBAAAByzRNffTwBI17erKOHck8ZX/K3lS9c9dnmvL6TD+kQ6C45M4L1e3ijuXWxMRX0v2f3q5K8ZV8EwpAADJOGSFnd/P3CD9PjBCsyHvvvacdO3YoNjZWP/zwgzp06CBJio2N1T/+8Q/dcccdkqRHH31UBQXWB2o8/vjjkqSuXbvqs88+U506dSRJMTExGjt2rB555BFJ0jPPPKO0tLRSj8/Pz1fHjh315ZdfFh9fp04djRs3Th07dlReXl7xdTzBKw3APXv2aMiQIerQoYP++c9/aubMmVq/fr127dql9evXa+bMmXr66afVvn17DR06VHv27PFGDADwutNaeIrFqgAgLC2ftlo/fbKwwroJz3ynrat2+CARApEzwqm7P7hV1/7jMlWplVhin2EY6jSwrZ764QG17NrUTwkBBAK35PE59YJts/KD1RdffCFJuv7669WwYcNT9j/00EMyDEPJycmaN2+epY/9gQMH9Ouvv0qS7rvvPhml/FBY9PqxY8dOmQ/w6NGj+v777yVJ999/vyIiSq7PGxERofvvv1+SNHXqVB07dsxSrop4fBXgNWvWaODAgUpNTS33WeciM2bMUJcuXTR79uziTiwABIsqtRJVuVp8qSM5ShOfFKdqNif4BgCEhh/fs/aDhSTN/GC+WpxDgydcOZwOXX73RRp6x0BtWPSbUpPTFFUpSq26NVONhtX8HQ9AADDNosd8vXiNMzjWE8nO5PqSlJmZqZUrV0qSLrroolJrGjZsqLPOOkubNm3SnDlzdOGFF1Z43t27dxf/d+vWrUutSUhIUN26dbVv3z7Nnj1bN910U/G+xYsXKz8/X5I0aNCgUo8vej0vL0+LFy/W4MGDK8xVEY+OADx27JiGDh2qI0eOyDRNNWjQQM8//7xWrlyp9PR0FRQUKD09XatWrdK//vUvNWzYUKZpKiUlRUOHDvVYVxMAfMUZ4VS/4edbru97fXdFRHn8dy8AgAB3JDlNv6/Ybrl++fe/qrDA5cVECAYRkU517H+22pzfUof+SNG0t2bpy6e+1Zo5G+R2s2gMEM5MOc54BODpjBC0WuuN65+8v6I24+bNm4sHprVt27bMuqJ9mzZtsvSxP3HEn8tV9r/VhYWFknTK9HdF16lVq5Zq1KhR6rE1atRQzZo1beWqiEd/Cn311VeVnJwswzA0bNgwffbZZ4qNjS1Rk5CQoM6dO6tz584aO3asRo0apUmTJik5OVmvvfaaHn30UU9GAgCvG3RrP80fv1QZKeWPAoyvGqeL/tLfR6kAAIHk6OEMW/WF+YXKPpqthOqVvZQIweDo4Qy9d+8XWj1rfYnXv39rtmo2qq6b/3292vdr46d0APzJNOT1EYB2nOloPW9cdP/+/cX/Xbdu3TLrivadWF+eEx8l3rhxo7p06XJKzZEjR3Tw4EFJUnJycqm5ystUtP/QoUOWc1XEoyMAi55rbt68ucaNG3dK8+9kMTEx+vLLL9WiRQuZpqlJkyZ5Mg4A+ETV2lX08Pg7lVA9vsyaytXi9fC4O3n8FwDCVKW4aNvHRMfaPwahI+NIpp669OVTmn9FDu1O0QvD39KqGWt9nAxAIDDdZz4HYLBvFTUdMzP/HKBRXn+qaJ/Vp1Jr165dPIXdv//971JHAT7//PPF/33yeYtyVdQzs5urIh5tAG7fvl2GYWj06NGKioqydExUVJTGjBkjSdqxg8mOAQSnph0a6YX5j+mK+4eUmLC7Ss0EDbtvsF6Y/6iad27sv4AAAL+q3aSmqjeoarm+Vbdmio619v00QtMXj3+j/dsPlVvjdrn13zs/UXZGjo9SAQgU/l6AIzA2/338n3jiCUnHRwBeeumlWrt2rQoKCrRv3z49/vjj+s9//qPIyEhJksPhlfV3bfPKRFQtWrSwVd+8eXNvxAAAn6pSM0FXP3yJrnzwYmWlZ8s0pfik2IC54QMA/MfhdGjAqF6a+OwUS/UDb+zt5UQIZEcPZ2jpd6ss1eYcy9Xir5frwpv7ejcUgMBiGOpfqYX6VWpp67B5uVs0N3erl0KdvtN5L5GZheXuj4//8wmt7OxsJSQklFqXnZ0tSapc2fq0G8OGDdOzzz6rRx99VNOnT9f06dNL7D/nnHPUpUsXvfvuu6pSpUqpuYquW5bTyVUej/5UWvQcdHp6uq3jiupLW5IZAIKNw+FQ5arxSqgWT/MPAFDsolv6qUn7BhXWdejfRt0vP8cHiRCoVs9aL5eNRWCWf/+rF9MACESmKUUbUUpyxtraoo0ory4SYncrOtfpvBejgrWQTpxj7+R5+E5UtK9OnTq2PgePPPKIli9frptuuklt27ZVw4YN1b17d7300ktasmSJcnKOj85u2bJkY7MoV3mZziRXWTw6AnDo0KHauHGjfvjhB916662Wj/vhhx9kGIYuueQST8YBAAAAAkaluGj9/au79NqtH2jjot9LrTnvsi66/bVRcjj5BVI4O5aaZbO+/IXIAIQet2kox12oNFf5o8hOluMulGl6ZvEQTz6BezrvJcYofURfkdatW8swDJmmqY0bN6p169al1hWt0tumjf1Flbp27aquXbuWum/16tWSpO7du5d4veg6Bw8eVEpKiqpXr37KsYcPH9ahQ4dOO1dpPNoAHDt2rN5//31NmzZNX331la655poKj/n66681depUVa9eXWPHjvVkHAAAACCgVK4ar398c7e2rtyhuV8sUfK2g3I4DDVqW1/9b+ipRmfX93dEBIDYhBh79ZXt1QMIfqYpzc7eqtnZ/nuc15NrEP+UvVU/lfJeymoyGpL+3XBEueeMj49Xt27dtHz5cv3444+68sorT6nZu3evNm3aJEkaMGCA3dhlWr9+vTZs2CBJGjlyZIl9PXv2VFRUlPLz8zVz5kyNGHHq+5g1a5YkKTo6Wj179vRIJo/+arFu3bqaNGmSkpKSNHLkSD300EM6cOBAqbUHDhzQww8/rBEjRqhatWqaNGmSx4Y1AgAAAIHKMAy17NZMt78+Sk9Pf1BPfv+AbvzXdTT/UKxD/zYyDOs/Wncc2NaLaQAEIrckU4ZfN7cPtvKubUVRc238+PHas2fPKfv//e9/yzRN1a1bV/369fPI5yYvL0933HGHJOnSSy9V27Yl79EJCQkaOnSoJOmVV145ZRXhwsJCvfLKK8XHe2oOQMM0Pbduyk033SRJ2r17t+bNmyfDMORwONSmTRu1aNFCcXFxysrK0rZt27Rx40a53ccf2O7bt68aNWpUdkjD0IcffuipmGErJSXF3xFwAqfTqaSkJKWlpZW6bDhQJCkpSU6nUy6XS2lpaf6OgwDFPQVWcD+BVdxT/O+lUW/rlx/XVVgXGR2hN1Y/q8Qa5T8K5w3cU2BFsN5PSnssM5AMX/xf/ZZR/hxyoe6lzsPVv3b5j8fm5eWpTZs22rFjh9q3b6/PP/9c7du3V05Ojl577TU98sgjMk1TH330kW688cYSxzZu3Fi7d+/W6NGj9cknn5TYd/DgQb3yyiu66qqr1K5dO1WqVEkul0sLFy7U3//+dy1fvly1a9fWL7/8UmIuwiIbN25U586dlZ+fr2uvvVavvvqqateurQMHDuiee+7RxIkTFR0drTVr1pT56LJdHn0E+JNPPin+TVXR/7pcLm3YsKF46GMR0zSLa+bPn1/huWkAAgAAAAgXo5+5Rtt+2aWjhzPKr3v2Gr80/wD4l2EaKm04lyfn5QsUZY71s/Bmo6OjNXXqVPXv31/r1q1Thw4dlJCQoKysrOKG9NixY09p/lUkJydH//73v/Xvf/9b0vFfiBw7dkyFhcdXJm7RooWmTZtWavNPks4++2x9/PHHGjNmjCZOnKivvvpKiYmJxYvkRkVF6ZNPPvFY80/y8CPA0vHG3olbaa+V93pZtQAAAAAQLmo0rKYnpt1f5qPhMZUr6fbXR2nAqF4+TgYgEJhus9RHYxWCW9mPIVtz9tlna/369br33nvVvHlz5eXlKTExURdccIEmT56s119/3eqHvViNGjX01FNPqW/fvqpbt66ysrJUpUoV9erVS6+//rrWr1+vVq1alXuO4cOHa8WKFbr++utVp04dZWdnq27dusWvX3fddbZzlcejjwDv3r3bU6c6RXmPCMMaHgEOLME6FB6+x+M1sIJ7CqzgfgKruKcEDtM0tXnpVi35dqXSDx5VdGyUzu7ZSj2u6KpK8ZX8mo17CqwI1vtJoD8CfP2Ct7XpWHg/AvxKl+s0oM7Z/o4RNDz6CDBNOgAAAADwHMMw1KZHS7Xp0VKSdHjPEWWkHNOR/emq07SmHE6PP9QFIAiYUqmPAIcXT65DHPo82gAEAAAAAHiWaZpaMmmlfvxgnrav3lX8evUGVXXB6N666JZ+io6N8l9AAH5gyDTDuwEW9v1Pm2gAAgAAAECAcrvdev++LzV/3NJT9qXsSdWEZ77T8mmr9chXdyk+Kc4PCQH4g2n6rgFot9Hm7VRFeUy3ly8UYhgvDgAAAAABasprM0tt/p1o59o/9PpfPvRRIgCBwJQht+mbzbS5+SqPwSPAtnh1BKDL5dK6deu0d+9eZWRkWJrwc9SoUd6MBAAAAABBIS87Xz+8/ZOl2vULNmv7r7vUrFNj74YCEBAMnn+VyQfBFq80APft26ennnpK48ePV3Z2tuXjDMOgAQgAAAAAklZOX6OsdOs/T837YgkNQCBMmMwBKIX7+7fJ4w3AlStXasiQIUpNTZXJkjQAAABACYd2p2jf1gOSpPot66hGw2p+ToRAtX/bQVv1ydvt1QMIXnRbYJdHG4BZWVkaNmyYjhw5IofDoREjRqhnz566/fbbZRiG7rzzTrVq1Uo7d+7Ujz/+qI0bN8owDI0cOVL9+/f3ZBQAAAAgoGxetlWTX5mh9Qs2l3i9XZ+zdMX9g9X6vBZ+SoZAZTjsjW4xDEbDAOHCdCvsRwDSBLXHo4uAfPjhh0pOTpZhGPr000/12Wef6S9/+Uvx/gEDBuiOO+7Qiy++qPXr12v8+PGqXLmyxo8fr8jISI0ePdqTcQAAAICAsPibFXrmildPaf5Jx+du++ewV7X4mxV+SIZA1qhtfVv1jds28FISAIHGNI43wMJ9g3UebQD+8MMPkqQePXpoxIgRFdZfe+21mjx5slwul2677TZt377dk3EAAAAAv9u1fo/euetTuV3uMmvcLrfeuetT7Vq/x4fJEOg6DWynpNqJluv7j+rpxTQAAspprM4bahurANvj0Qbg+vXrZRiGhg4dWur+0lYB7tevny699FJlZ2fr3Xff9WQcAAAAwO+mvztHrsKym39FXIVuzXhvrg8SIVhERDp19cOXWKrtdfW5qteitpcTAQgYDAGETR5tAKampkqSGjduXOL1iIjjUw3m5OSUetxFF10k0zQ1Y8YMT8YBAAAA/CovO18/T/nFcv2y71YpLzvfi4kQbPqN6KFrH7m03JouF7XXLS9X/AQWgNDhMk2/j8Dz98YIQHs8ugiI0+lUQUGBnE5nidcrV66s9PR0HThwoNTjkpKSJEn79u3zZBwAAADAr9IPHlVBXqHl+oK8QqUfOqpajWt4MRWCzeX3DNbZPVtp5gfztfz7X1WYf/xr6qzzW+jCm/qo29BOcjg8OrYDQIAzZMgM81FwZrh/AGzyaAOwVq1a2r17t9LT00u83qBBA6Wnp2v9+vWlHrd7925JZY8QBAAAAIJRRJSz4qKTj4m0fwxCX4tzmqrFOU3110KXsjNyFB0brahKkf6OBcBP3O6Kp5YIdbT/7PFoA7BNmzbavXu3tmzZUuL1Ll26aN26dZo2bZqysrIUFxdXvM/tduuzzz6TJNWrV8+TcQAAAAC/SqpdRVXrVFHq/nRL9VXrVFFSnSpezYTg5ip0a81PG7Xi+191LDVTMQkx6nRBW/W8uptiK8f4Ox4AHzHkCPsRgLDHo+PEe/ToIdM0tXTp0hKvX3XVVZKktLQ0XXHFFdq8ebPy8/O1adMmXXnlldq4caMMw9DAgQM9GQcAAADwK4fTof43WF+ZdcCoXjzKiTJtWPSbxnb+h/575yda9eNa/b5iu9b8tEEf/98E3dnhES2dvNLfEQH4jPG/hUDCd6MBao9Hv7sYPHiwJGn58uUl5vsbPHiwzj//fJmmqZ9++klt27ZVTEyM2rVrp6lTp0qSYmNj9eCDD3oyDgAAAOB3g27uqxoNq1VYV7NhNV14Ux8fJEIw+u3nbXrh+reUkXKs1P05mbl647aPtMzGojMAgpdpyu+LcPh7YwkQezzaAOzYsaOeeuop3X///acs6DFp0iS1b99epmmeslWuXFlff/21mjZt6sk4AAAAgN/FJ8XpH1/frdpNyl7Yo3aTGnrk67sVnxRXZg3Cl2ma+uCBL4sX/yjPhw+OYyVpIAwY0vFJ8MJ4YxEQezw6B6AkPfbYY6W+XqtWLf3yyy+aOHGiZs2apQMHDiguLk5du3bVzTffrBo1WOkMAAAAoalWkxr617xHtXjSCs39fLH2/p4sSarfqq7639BTPa/spujYKD+nRKDatGSL9m05UHGhpKz0bC2bskp9rz/fy6kA+JPJI7AyPDumLeR5vAFYHqfTqeHDh2v48OG+vCwAAADgd9GxURpwQ08NsDEnICBJ6+Zvtl1PAxAIbab7f3PhARbRLgUAAACAAJabmevVegDBx2GE+fA/iTkAbfLpCED4l9Pp9HcEnKDo88HnBXbw9YKycE+BXXytoDzcUwJLlZqJtuoTayT4/HPH1wrKwv3EO2j/SW4+CLZ4tAFYUFCgd955R6Zpqnfv3urYsWOFx6xZs0YLFy6Uw+HQHXfcIYeDQYnekpSU5O8IKEVCQoK/IyBIOJ1O/h6jQtxTYAX3E1jFPSUwDBrVX1/9a6rl+gtv6OfTv+PcU2AF9xPPKloJF7DKow3AqVOn6u6775bT6dS2bdssHVO1alXdf//9crvdaty4sYYOHerJSDhBWlqavyPgBE6nUwkJCcrIyJDL5fJ3HASwhITjv8V3uVzKyMjwdxwEKO4psIL7CazinhJYKteKVYd+bbR23qYKa+s2r6Wm5zTwyff+3FNgRbDeTwK+qV20Gm44o/9pi0cbgN9//70kqWfPnmrUqJGlYxo2bKjevXtr3rx5mjJlCg1ALwqmm204cblcfG5gGV8rqAj3FFjF1wms4J4SOG79z0g9OfQlpexNLbMmLjFGd71/i0zT9Pnnja8TVIT7iacZCvsOWLg3QG3y6PO2q1atkmEY6tu3r63jiupXrFjhyTgAAAAAEBKq1U3SUz88qM6D2skwTv2hv3X3Fnry+wfV6Oz6fkgHwNfMov8Xzlu4N0Bt8ugIwN27d0uSmjdvbuu4pk2bljgeAAAAAFBS1TpV9ODnd+jQ7hStmrFWx1IzFVM5Rh0HnK2Gber5Ox4AX+IRYNp/Nnm0AZiXlydJio6OtnVcVFSUJCk7O9uTcQAAAAAg5NRsVF1Dbh8gt8ut3Zv2KSPlmHau+0ONzq4vh5NFFYFwYLolhf0iIOH+/u3xaAMwKSlJhw8fVnJysq3j9u/fL0lKTLS3vD0AAAAAhJuCvALNeG+eZn+yQCl7/pwTsHr9qho4prcu+kt/RVWK9GNCAN7mKGUqgHBjyu3vCEHFo78eatasmSRp9uzZto4rqm/cuLEn4wAAAABASMnNytPz176h8f+cXKL5J0kpe1M1/pnv9Pw1rys3K89PCQH4gtvtlmkqrDdGQNrj0QZg//79ZZqmZsyYoZUrV1o6Zvny5Zo+fboMw9CAAQM8GQcAAAAAQspHD43X5qVby6357edt+uCBcT5KBMAvTMP/i3D4eTNN0wMfyPDh0QbgLbfcov9n767Do7rTNo7fZyaekJDgFtwp7u4thRYKNaSl7g6Vre3Wdqu01LauUCoUa2mhULR4cXf3kJAQlznvH2zyEmJzwkiS+X6ua3bpnOecuSeEk+TJT/z9/WWapoYOHVpkE3D16tW65pprZJqm7Ha77rjjDlfGAQAAAEqM5HMp2rfxoPauP6BzsYnejoNS6PThM/rr59VO1S6ftkanD51xcyIAXmPI6w04rz9YA9ASl64BWLt2bT322GN67bXXdPLkSXXr1k1Dhw7V0KFD1axZM4WFhSkxMVHbtm3TzJkzNXPmTGVmZsowDD388MOWdw8GAAAASrpje07ol/fnafn0NUpPyZAk2f1san9la131wEDVb13bywlRWiz9cZVMh3MjXkzT1OIfVujax4e4ORUAbzAchnx9Cqxvv3vrXNoAlKRXXnlFe/fu1dSpU5WZmalp06Zp2rRp+dZmD9e89tpr9frrr7s6CgAAAOBV25bt0htjPsyzHltWpkOrZq3T379v1P0f3qouQ9t5KSFKkxP7T1mqP7n/tJuSACgRXDwD1p0NNSbrep/L94i32Wz68ccf9eabb6pChQoyTbPAR8WKFfX222/rhx9+kMEONgAAAChDzhyN1Zs3/7fQzRiyMrL0wX1fav+mQx5MhtLK7md3az2A0sMwDRmmXPpw53RdV2fNyQynuXwEYLbHHntM99xzj37//XctXbpUR44cUUJCgsLDw1WzZk317NlTgwYNUnBwsLsiAAAAAF4z9/PFSjmXWmRdVkaWfv1wnh786HYPpEJpVrdltBZ9t9zp+nqtot2YBoA3GRf8r+/y9fdvjdsagJIUEhKiESNGaMSIEe58GQAAAKBEcTgcWjTF+UbNql/W67bXkhUaEeLGVCjtul/bUd+9OF1pyQWPKs0WGBKg7td18kAqAN5gMqlWJkMALXH5FGAAAADA1yWdTda5M87v9JuVkcWOrShSSHiwhj16hVO1wx65QiHhzLYCyizT8P4uvF5+GD6+CYpVbh0BWJiEhARlZmYqKirKWxEAAAAAt7DZrf+e3bDxgwyKNvShy5V0Nlm/fjCvwJrB9/bX0IedaxQCKMV8fACcw9c/ABa5dARgZmam1q1bp3Xr1unMmfx/g7lgwQK1atVKkZGRqlSpkmrXrq1PPvnElTEAAAAArwoJD1al6ApO1weFBqpq3cpuTISywjAMjf7ncL3w63h1G95BgSEBks5P+e06vL1e+HW8xrwwgk0WgbKuBIzA8/aDGcDWuHQE4IwZM3T99dfLMAxt3bpVFSrk/qZn9erVGjRokDIzM2Wa5/+mDh8+rHvvvVexsbF66qmnXBkHAAAA8ArDMNTv5h76/uUZTtX3uL5TTiMHcEajjvXVqGN9maaprIws2f3tNP0AH2JmN8IAJ7m0AThnzhxJUqtWrdSkSZM8x8eNG6eMjAxJUqVKlVSjRg1t2rRJDodD//rXv3Tdddepfv36rowEAAAAeEW/m7tr/ldLFHMkttC60IhgDblvgIdSoazJSMvUyplrtX7+FiUnpKhcZKg6Dmmjdle0lN3P7u14ANzEZho+vwaewbYWlrj0o7Vp0yYZhqE+ffrkObZr1y4tW7ZMhmHo+uuv19GjR7Vu3TotXrxY/v7+ysjI0Oeff+7KOAAAAIDXhJUP1T9+fFAVaxa85nVYZKie+O4BVa5d0YPJUFasnbtJD7R5Wv998GutnLlWmxZu07Jpa/T2bZ/okY7Pa9fqvd6OCMBNTNP0+hRcrz8YAmmJSxuAp0+fliQ1bdo0z7Hs0YGGYejNN9+Un9/5wYfdunXT1VdfLdM0tWjRIlfGAQAAALyqeoOqenXhMxr9z+GqWrdSzvORVSM0fNyVemPJc2rUoZ4XE6K0WvfHZr019qMCd5uOORKrV66bqD1r93s4GQBPoPUFq1w6BTh744/IyMg8x5YuXSpJatu2rWrWrJnrWK9evfTzzz9r9+7drowDAAAAeF1oRIiG3D9Ag+/rr7TkdJmmqaDQQNZrQ7FlpGXo40e+lekovAWQnpKhTx6bpNcWPcvnG1DG2MS/aVjj0hGAaWlpkqSkpKQ8x5YvXy7DMNSrV688x6pUqSJJSkhIcGUcAAAAoMQwDENBoYEKDguiGYNLsuqX9UqIOedU7eHtx7R9BQMtgDKHKcAMg7TIpQ3A7JF/R48ezfX8zp07dfz4cUlSly5d8pyXnp4uSTnTggEAAAAA+dvw51ZL9Rst1gMoBUxDhimffsAalzYAmzVrJtM0NX369FzPT5kyJefPPXr0yHNedsOwUqVKeY4BAAAAAP5fSmKKpfrkc6luSgLAq0zDpx8Oky6gFS5tAA4ePFiStHbtWj3xxBPasWOHJk+erLfeekuGYahr1675NvnWrVsnSWrUqJEr4wAAAABAmVMuKsxSfbjFegAlnyHD+9NvvfywsZyGJS5tAN5111056/m99dZbat68uW6++eacNQGfeuqpPOdkZGRo7ty5MgxD7du3d2UcAAAAAChzOg5pY63+Kmv1AEoBBr/BIpc2AMuVK6dff/1V1atXl2maOQ/DMPTss8/mjBC80MyZMxUfHy9J6tOnjyvjAAAAAECZ07pvc1Wt69zySU26NFTt5jXdnAiApxmS10fgefvBOoDWuHzXjXbt2mnXrl367bfftGfPHoWGhqp///5q0qRJvvXHjx/X2LFjC9whGAAAAADw/2x2mx785Ha9NOxtpSalFVgXUSlc90y8yYPJAHgSE2BhhVu23Q0ODtaIESOcqn3wwQfdEQEAAAAAyqx6rWrrn7PG6dNxk7Vvw8E8x5v3aKw73xqtKnXYaBEoi0zTZBowLHFLAxAAAAAA4F51Lqull+c+qb3rD2r9H5uVfC5F5aLC1GFwa9VqUt3b8QC4leHzDUCHj79/qzzSAExPT1dsbKzS09MVHR3tiZcEAAAAgDLPMAw1aFtHDdrWkWmaSog5p9TENCUnpCgkPNjb8QC4i8P0+TXwmAJtjdsagLt27dLEiRM1d+5c7d+/X9L5L06ZmZm56r7//nvt27dPVatW1W233eauOAAAAABQJmVmZGnx9ys074vFOrj1SM7zLfs00xV39lGb/i28mA6AOxiySaaPt8B8vAFqlVsagK+99pqee+45ZWVlnZ+XXoikpCQ9++yz8vPz05AhQ1S5cmV3RAIAAACAMic1MVVvjv1IW5fuzHNs08Jt2rRwm668u5/GvDhChuHjzQKgLGENQBmMAbTE5uoLvvrqq3r66aeVmZkpm82mLl26qHv37gXWjxw5UkFBQcrKytKsWbNcHQcAAADwquRzKdqzdr92rd6ruJPx3o6DMua/D32Tb/PvQr99/Kd+/2SBhxIB8Agfb/5JYg6wRS4dAbh7924999xzkqQWLVrop59+UuPGjTVz5kz99ddf+Z4TEhKivn376vfff9eiRYt0xx13uDISAAAA4BUn95/WzPfmatnPq5WekiHp/JI4rfs311UPDFTTLg29nBCl3aFtR7X61/VO1c6cOEcDbukp/0B/N6cC4AmmKZ9fA5AmqDUuHQH4/vvvKysrSxEREZo7d64aN27s1Hnt27eXaZravHmzK+MAAAAAXrH77316ZuB/tHDSspzmnySZpqn187bopWFv689vlnoxIcqCBZPyH2SRn4SYRP39+0Y3pgHgSYZ0vgHmyw9Y4tIG4IIFC2QYhm6++WZVq1bN6fPq1q0rSTp8+LAr4wAAAAAelxBzTq+P+VBJ8SkF1pimqc8fn6Jty3Z5MBnKmiM7j1uqP7zjmJuSAPA4h+n9Bpy3H3QBLXFpAzC7gde+fXtL55UrV06SlJiY6Mo4AAAAgMf9+e1fSoxNKrLONE3Nem+uBxKhrCpqw0UAZZdNhgxTPv+A81zaAExLS5MkBQUFWTovu/EXGhrqyjgA4FUOh0MJZxJ1LjaRb9ABwIcsmrzM6dqNC7bpzLE4N6ZBWVarSXVL9TUbOz9LC0Ap4O0ReF5+OFzwIfQlLt0EpFKlSjp69KiOHj1q6bxt27ZJkqpUqeLKOADgFWeOxemPzxdp0ZTlSog5/wuOqOqR6ndTd/W/pafCK4R5OSEAwF2yMrN06tAZS+ec3H9aFapHuikRyrI+o7tp7meLnKotVyFM7Qe1dmseAJ5jZjfCfBgjAK1x6QjAVq1ayTRNzZ8/3+lzTNPU9OnTZRiGOnXq5Mo4AOBxO1bu1hM9X9Ks9/7Iaf5JUuyxOP302i96qs/LOrTN2i9JAAClh2EzZBiGpXNsdmv1QLbazWuq4+DWTtUOfehyBQSxAzBQVhjm+Y1AfPkBa1zaALzqqqskSXPmzNGaNWucOue9997T7t27JUlDhw51ZRwA8KiTB07r9dEfKjmh4EXf407E69Ub31PCGdY8BYCyyGazKbp5Dafr/QL8VLOxtWmcwIXufW+smnVvVGjNoLv76sp7+nkoEQBPsPi7pjLJRhvQEpc2AMeOHavq1avL4XDo6quv1vLlywuszcjI0GuvvaZx48bJMAw1btxYw4cPd2UcAPCoXz+Yp5RzqUXWxZ2I1/yvl3ggEQDAG/qP7el0beer2yosknWwUXxBYUH6x/cP6vY3Rim6We7mc8veTfX45Pt080vXWR6ZCgCFKgHTb82SEKIUcekagIGBgZo8ebIGDhyoU6dOqUePHurSpYsiI/9/TZPHH39chw8f1sKFCxUTEyPTNBUUFKRJkya5MgoAeFRqUpqW/rTa6fo/v/lL1zw6iG/GAaAM6nFdJ835dIGO7jpRaF1QaKCGPXKFh1KhLPML8FP/sT3U7+buij+VoJSkNJWLClVYeZrLQFllmIb3m3Befn1+lLLGpQ1ASerVq5dmzJihm266SbGxsVqxYoUk5fyQO2HCBEn/v2V9+fLl9eOPP6pt27aujgIAHnPqYIzSktOcro89Fqeks8mM+gCAMigwJED/+OFB/eeG9wpsAoaEB2vc1/eoRiN2ZYXrGIahiMrhOvX3fq2cuVZpyWkqXyVCna5qq8gqEd6OB8CFTNP0+U0wTB9//1a5vAEoSYMGDdKWLVv0+uuv69tvv9WZM3l3QouIiNDo0aP19NNPq3p11j0BULqZxfjq43DwFQsAyqoKNaL08tyntOSHlZr/9VId3n5+A6jyVSLUZ3RX9b+lp6KqlvduSJQ5u1bv1RdPfa+DW47ken7S81PV+ep2uuXVGxgVCJQV7AJMA9AitzQAJalq1aqaMGGCJkyYoG3btunAgQM6e/aswsLCVLNmTbVu3Vo2m0uXIAQAr6kUXUH+gX7KSMt0qj68YpjCIkPcnAoA4E1BoYEaeFsvDbytlzLTM+XIciggOMDbsVBGbVmyQ6+P/iDf70WyMh1aNm2NDm0/pn/OekyhEXwPApQJNMBggdsagBdq1qyZmjVrVqxzY2NjtWXLFklSz57OL6gMAJ4UUi5Yna9up6U/rXKqvveobvwSBAB8iF+AR77tho9KTUrTxLs+K/IXkYe3H9Wkf/6su9+5yUPJALiLYcrnpwCzBKA1Jf6nz6VLl6p3797q27evt6MAQKGG3D9A/oFF/4AXGhGsgbf18kAiAADgC5ZPX6PE2CSnapf9vFoJZxLdnAgA3I8GoDUlvgGYrTjrawGAJ0U3q6GHPrmj0CZgSHiwxn97nypUjyywBgAAwIoVM9Y6XZuRlqm1cze5MQ0ATzCz1wD04QddImuYiwAALtR+UCu9PPcp/frhPK2cuTZnKk5QaKC6X9dJQ+7tryp1K3k5JQAAKEsSYs5Zqj9nsR5ACcQUYDqAFtEABAAXi25WQ/e9f4tu+c8NOn3ojGw2Q5VrV1JgCAu/AwAA1wsOC7JUHxQa6KYkADzFJsPnG2AGk4AtoQEIAG4SUi5YtZvX9HYMAABQxrXs00w7V+91uv6y3k3dmAaAJ5hZDp9vAMKaUrMGIAAAAAAgrz5jusnub3eqtmXvpqpWv4qbEwFwN8MwvL4Gn7cf7BVhDQ1AAAAAACjFIqtEaNTz1xRZFxoRrJtfud4DiQC4m+k4vwagLz9o/1nDFGAAAAAAKOWuvLufbHabvnthWs4mZBeqXLuiHvvybtVoWNUL6QC4msHyd4xos4gGIAAAAACUAVfc0UfdhnfQ4ikrtGXpDqUlp6t8lQh1G95BbQa0kN3PuWnCAEo+I3sqLOAkGoAAAAAAUEaUiwrTkPsHaMj9A7wdBYAbGZLPNwANhkFaQgMQAAAAAMqYvesPaN6XS7R9xW6lp2aoQvXy6n5tR/W4vrNCI0K8HQ/AJTJlyOfbXw4f74BaRAMQAAAAAMqIzIwsfTZ+shZPWZHr+bMn47V3/UH9/OZvevTLu9SsayMvJQTgEia7YPj8+7eINRMBAAAANzh9+IxW/bJOy6at0a41+2Sa/KQC9/v88e/yNP8ulBiXpNdHfaD9mw97MBUAV7OVgF14vf1gJxRrGAEIAAAAuNDBLUf046uztH7ellxNv+oNqmjIAwPVe2QX1i2CW+zfdEiLvlteZF1acrqmvDhdT//0kAdSAXAHU4bPj4DjF2vW0AAEAAAAXGTL0h1686b/Ki05Pc+xY3tO6pNHvtWhrUd088vX0QSEy83/eqnTtZsXb9eJfadUtV5lNyYC4DYOpgDDmhLfAIyOjtbYsWO9HQMAAAAoVELMOb196yf5Nv8uNOfThapzWS31urGLh5LBV+xYucdS/c7Ve2kAAii1+D2aNSW+AdimTRt9+eWX3o4BAAAAFGrhd8uVnJDiVO3s//6pnjd0ZhQgXCojLcNifaabkgBwN8NgF2BGQFrDJiAAAACACyz5YaXTtYe3H9UBNmGAi1WoHmmtvoa1egAlh5k9BdiXHxacPn1a48aNU8OGDRUcHKyKFStq4MCBmjFjhrULXWTZsmUaNWqU6tSpo6CgIAUHB6t+/foaO3as1qxZU+B5vXv3Pt/ELeQxZMiQS8p2MZeOAKxXr16xzrPZbCpXrpyioqLUqlUr9enTR4MHD5bNRn8SAAAApcOZo7GW6mOOxKpuy2g3pYEv6nF9J6enAZevHK7LejZxcyIA7pKzE64vc/L9b926VX379tWpU6ckSeXKldPZs2c1b948zZs3Tw899JAmTpxo+eX/+c9/6sUXX8z575CQEDkcDu3bt0/79u3Tt99+q1dffVVPPPFEgdcIDQ1VWFhYvsciI137SxqXdtgOHDiggwcP6sCBAzmPgwcP5jzy++8DBw5o37592rRpkxYtWqSJEydq2LBhql+/vubNm+fKeAAAAIDb+PnbLdX7B5b41XhQynS9poPKVw53qvbyO3rLL4DPQaC0Mh0O74/A8/LDmWU00tLSdPXVV+vUqVNq0aKFNmzYoISEBCUkJOjll1+WYRh69913LS89N3/+/Jzm37XXXqvdu3crKSlJycnJ2rJliy6//HKZpqmnnnqq0JGA48eP14kTJ/J9fPvtt5YyFcWlDcDo6GhFR0erRo0aOX8RpmnKNE1FRESoRo0aioiIyHlOOv8XVqNGDVWvXl1BQUE5xw4ePKhBgwZp6tSprowIAAAAuEWjjvWdrrX721WvVW03poEvCgoN1Lhv7lVIeHChdR2HtNHVD17uoVQA3MGQ4fUGnLcf2X2lwnzyySfat2+fQkJCNHv2bLVq1UrS+dF6zzzzjO677z5J0rPPPquMDOfXUZ08ebIkqUGDBpoyZYoaNGgg6XyPq3nz5po+fbqqVKki0zQ1bdo0p6/rTi4fAbhs2TLVqVNHpmmqe/fu+vnnnxUbG6vY2FgdPnw4589Tp05V9+7dZZqm6tSpo9WrVyspKUmbNm3SnXfeKUlyOBy67bbbdObMGVfGBAAAAFyu/y09na7tfFVbhVcs58Y08FUN2tbRi789rvZXtJJhyz06JrJqhEY+O0wPf3qHbHaWWwJKM8OgAehE/0+TJk2SJI0cOVLR0XmX3XjiiSdkGIaOHTumhQsXFn3B/zl+/LgkqVWrVvLzyzuaOjg4WM2bN5ckJSYmOn1dd3LpmO+0tDQNGTJEGzdu1HPPPacXXngh37ry5ctr+PDhGj58uJ577jm98sorGjJkiFasWKEWLVro448/VsuWLfXggw8qKSlJH3/8sZ5++mmXZIyPj9fUqVO1evVqnTlzRoGBgapfv76uvPJKde7c2fL1Tp48mdOwLMyTTz6pbt26FXh83759mj59ujZv3qyEhARFRESoRYsWGj58uOrWrWs5FwAAADyrdb/matW3mTYu2FZoXWhEsEY84dqFvYEL1WhUTeO+uUcxR2K1a81epadmKKpqeTXr3tjyVHUAJZev7wJc1PtPTEzMmX57xRVX5FsTHR2tpk2batu2bfrzzz81cOBAp147u0+zceNGZWZm5mkCpqSkaOvWrZKktm3bOnVNd3Ppr30+/vhjbdiwQZ07dy6w+Xexl156SZ07d9aGDRv08ccf5zx///33q3Xr1pLksrUADx06pAceeEAzZ87U8ePHZbfblZSUpA0bNujf//63Pv3000u6fnh4uMqXL5/vIyAgoMDzFi9erPHjx2vx4sWKjY1VYGCgzpw5o8WLF2vcuHFaunTpJeUCAACA+9lsNj3y2Z1q3a95gTURlcL1jx8fUrV6lT2YDL6qYs0odb2mgzoObqOAYH9tX75Lx/ed8nYsAC5gOOT1EXjefhS1BuD27dtzpgm3aNGiwLrsY9u2Ff4LvAvdeeedMgxDe/bs0ciRI7Vnz/kNmEzT1LZt2zR8+HCdPHlSbdu21ZgxYwq8zuTJk1W7dm0FBAQoKipK3bp10+uvv66EhASnszjLpSMAp0yZIsMwdOONN1o678Ybb9TKlSs1ZcoUPfjggznPDxs2TBs2bNCOHTsuOVtGRoZefvllxcfHq3bt2nrsscdUt25dpaWlaebMmZo8ebJ++eUX1a1bV/379y/Wa7z11luqUqWKpXMOHTqkiRMnKjMzU927d9cdd9yhqKgoxcbG6tNPP9WyZcv0zjvvqG7duqpZs2axcgEAAMAzgsKC9Pjk+7RlyU7N/2qJdq/dr8yMTFWOrqheN3ZR9+s6KqRc4euzAa5y+vAZzXhnjpb9vFppyek5zzdsX09X3T9AHQa39l44AJfG0PlGmC8r4v1nT9OVpOrVqxdYl33swvqitG3bVt9++63uuusuTZ06VVOnTs3ZBTg1NVUVK1bUY489phdeeEH+/v4FXmfPnj0KCAhQaGiozp49q+XLl2v58uX64IMPNGvWrJw1C13BpQ3A7I5ntWrVLJ2XXb979+5cz2cvohgXF3fJ2ebOnasTJ04oMDBQzz//vCpVqiRJCgwM1PXXX6/Y2Fj99ttvmjRpknr37p3vHG53mDx5sjIzM1W3bl2NGzdOdvv5IflRUVEaP368jh07pv3792vy5Ml68sknPZIJAAAAxWez2dSyd1O17N3U21Hgww5uPaJ/XzdRCTF5157a/fc+Tbj1Y13z2CBd/9TVXkgH4FIZ5vkHCnbh2nshISEF1mUfO3funKXrjx49WtWrV9dNN92ko0ePKjk5OedYWlqakpKSlJ6enu+5vXv31m233aaBAweqSpUqMgxDsbGxmjJlip5++mkdOnRIgwYN0ubNm1WhQgVLuQri0inASUlJkqRjx45ZOi+7y3rhB0s635yTpKCgoEvOtmjRIklSz549c5p/FxoxYkTOB3zz5s2X/HrOSEpKypmPPmzYsJzmXza73a5hw4ZJklavXp3n4wMAAAAAF0tNTNXroz/Mt/l3oekTfteyn1d7KBUAlzJ9fQVAyfDiEMjMzEzde++96tu3r2rUqKH58+crNjZWJ06c0MyZM1W9enV9/PHH6t69e76D2v71r3/p5ptvVtWqVXOmMkdFRen+++/XggUL5O/vr+PHj+utt95yWWaXDnOrVauW9uzZoylTpuihhx5y+rwpU6ZIUp4prjExMZJ0yd3OlJSUnNGFBS2+WKlSJdWsWVOHDx/Wxo0b1aZNm0t6TWds27ZNmZmZhebKfj4jI0Pbt29Xu3bt3J4LAAAAQOm1dOpqxR5zbhbVrPf+UNfhHYpcSwtACWOaGti8hgZcZm2psHmbj2jelqNuClV8A1pYfy/+jrRCj4eFheX8OTk5WeHh4fnWZQ+2KleunNOv/eabb+qjjz5SkyZNtHjx4lwD166++mp16dJFzZs31/bt2/Xqq6/qtddec/ra7dq104033qhvv/1Wv/zyi/797387fW5hXDoC8PLLL5dpmlq9erWeeeYZp855+umntWrVKhmGkWdXlk2bNkmyPqX4YkeOHMlZ+LF27doF1mUfO3z4cLFe5/XXX9fIkSM1fPhw3XrrrfrPf/6TM8IvP9mvU758eUVERORbExERkXPs0KFDxcoFAAAAwHcsnrLc6dpD245q30Z+zgBKH0NB/n6KDA209Ajy9/P65h35PYrzXgyz8BGAF677V9hM1exjVnpPb7/9tqTzG9jmN2u1UqVKuummmyRJM2fOdPq62Tp16iRJ2rdvn+VzC+LSEYDjx4/Xl19+qeTkZL366qtaunSpHnnkEfXu3VtRUVE5dbGxsVq4cKHeeecdLV9+/otTSEiIxo0bl+t6v//+uwzDUMeOHS8pV2xsbM6fL8xxsexjxV1zcPfu3QoJCZHNZtOZM2e0YsUKrVixQt26ddNjjz2WZ+HH7NcpLFP28fj4+CJzTZo0Sd99912Bx0eOHKlRo0Y5+W7gbtm/ZY2IiMhpUAP5sdlsOf8fGRnp5TQoqbinwBncT+As7iml26mDZyzVJ51OLtY9gXsKnMH9xD0MU0pNz1RcYuGj4C6Wmp5ZIjcPKc57CSpX+HJxTZo0kWEYMk1TW7duVZMmTfKt27p1qySpWbNmTr3umTNndOrU+R3V69WrV2Bd9rEDBw44dV13c2kDMDo6Wl9++aVGjRqlrKwsLVu2TMuWLZMkhYeHKyQkRMnJybm2MzZNU35+fvrqq68UHR2d8/ySJUt06tQphYSEaOjQoZeUKzU1NefP2esK5if7WEpKitPXDggI0JVXXqkePXqobt26OYtHHjp0SD///LMWLlyoZcuWKTQ0VA888ECuc7Nfp7BMVnIlJSXlfBLmJzk5Oc86g/C+7G+cgKIYhsG/YRSJewqcwf0EzuKeUjrZ/az9+/YP8L+kewL3FDiD+4lrmZLmbT6qeZtL3nTe4ijOe3nznqsKPR4WFqaOHTtq1apVmjNnjkaMGJGn5siRI9q2bZskqV+/fk697oWfy4XN1Mw+VtDU48KsWrVKklS3bl3L5xbE5VvdXnvttapYsaLuuOOOXEMV4+PjlZCQkKfjX79+fX322Wfq1atXrud79uyZa8eWkioyMlL33HNPnuejo6P16KOPKjw8XDNnztS8efM0bNiwPOsculJoaKgqV65c4PGQkBBlZWW57fVhjWEYstlscjgc/CYMhbLZbDm/uXI4HN6OgxKKewqcwf0EzuKeUro1bFdPa35f71StYRiq16p2sX5O4J4CZ5TW+0mJb2qbJrsAO/H+R48erVWrVmnKlCl6/vnnVatWrVzHX3/9dZmmqerVq6tPnz5OvWxkZKRq166tgwcP6rPPPtOdd96Z5/MlISEhZ7+L7Om8ObFNs9B1V9evX6/vv/9eknTVVYU3Oa1weQNQOr+d8c6dOzVr1izNmDFDa9as0bFjx5SUlKTQ0FBVr15dHTp00NChQzV06FC3/8O6cD52Wlpagds/p6WdH24aHBzsstcePXq0fv/9d6Wnp2vNmjW5GoDZr5P9ugVxNteYMWM0ZsyYAo/HxMQUe3ozXM9utysyMlLx8fE0ZlGoyMhI2e12ORwO/g2jQNxT4AzuJ3AW95TSrdeozk43AFv1babA8v7FuidwT4EzSuv9pGLFit6OUCgje/08FOquu+7SO++8o3379mnIkCH69ttv1bJlS6WkpGjixIl6//33JUkvv/xynmXb6tSpo4MHD2rs2LH66quvch2799579dRTT2nt2rUaOnSoXn/9dTVp0kQOh0Pr1q3TI488krPvw8MPP5zr3FdffVW7du3SjTfeqM6dO+fs+xAXF6cffvhB//jHP5SRkaGqVatq/PjxLvtYuKUBKJ3/R37NNdfommuucddLOO3i9QcLagBmrxXoyvUrgoKCFB0drT179ujkyZP55rpwjUJP5QIAAABQNrXp30JNuzbU9uW7C63zD/TTtU8M8VAqAK5kOswiN8Eo6wwnOqCBgYGaNWuW+vbtq02bNqlVq1YKDw9XUlJSTkP6wQcf1K233mrptcePH6/169frhx9+0OzZszV79mwFBQUpKytLGRkZks6Pkv73v/+t/v375zo3LS1NX331VU5TMTw8XHa7XWfPns0ZJVuvXj1Nnz5dFSpUsJSrMD4xCb9mzZo5wyudmZ998ZBQd8l+nbNnz+ZaF/FC8fHxio+Pl6RcayQCAAAAQH5sdpse++puNe5Uv8CawJBAPfrl3arfpo7nggFwGcMwvL5zr9cfTmrevLk2b96sRx99VA0aNFBaWpoiIiLUv39/TZ8+Xe+++67zF/sfu92u77//XjNmzNCwYcNUo0YNORwO2e121atXTzfffLNWrFihJ598Ms+51113nZ599ln17dtXtWvXlsPhUGJioipXrqz+/fvr/fff16ZNm9SyZUvLuQrjthGAJUlwcLAaNmyoXbt2ad26deratWuempiYmJzhma1atXLZa6empuY0FqtUqZLrWLNmzeTn56fMzEytW7dOvXv3znP++vXnh+77+/uradOmLssFAAAAoOwKKx+qZ6c9qtW/rtO8r5Zq95q9ysp0KKpaefW8sbP6j+2pCtWZYQSUWg4HU4AtvP/KlStrwoQJmjBhgtPnOLN7b/bSdlY0b95cL730kqVzXMEnGoDS+XUJd+3apSVLluiGG25QpUqVch2fNm2aTNNUVFSULrvsMqevW9TijVOmTFF6eroMw1CHDh1yHQsJCVGHDh20YsUKzZw5Uz169Mi1HmJWVpZmzpwpSerYsWOBU5cBAAAA4GJ+/nZ1vaaDul7TQaZpynSYstl9YhIYUOYZMtgEBJa4rQG4YcMG/f7779qyZYvi4uKUmppa5DmGYejPP/90S57LL79cs2bN0okTJ/TSSy/p0UcfVd26dZWWlqZffvlFs2fPlnR+Iw0/v9wfljvuuEOnTp1S37599cgjj+Q69vTTT6tNmzbq0KGDoqOjcxp4hw4d0vTp03Pez4ABA/LdAXj06NFas2aN9u7dqwkTJuiOO+5QZGSk4uLi9Nlnn2nv3r3y9/fX6NGj3fBRAQAAAOALUhJTteznNdq7/oAcmQ5Vrl1RPa7vpCp1KhV9MgCUQKVpV+mSwOUNwOPHj+vWW2/VvHnzLJ1X1Ei6S+Xv769nn31WzzzzjA4cOKCHH35YISEhSk1NzdmyfsiQIXkWZyzK6dOnNWnSJE2aNEl2u10hISFKT0/PtbNvr169dPfdd+d7fnR0tB5++GFNnDhRS5cu1V9//aWQkBAlJSVJkvz8/PTwww/n2zwEAAAAgMKYpqnZH87Xz2/OVmpSWq5j0976TZ2HttWdE8YoOCzISwkBFIfhMHx+CrAh9/WQyiKXNgATExPVp08f7d69u0R2YqOjo/Xee+/p559/1urVqxUTE6PQ0FDVq1dPgwcPVufOnS1f85ZbbtHGjRu1e/duxcXF6dy5c7Lb7apWrZqaNGmifv36FblwY69evVSrVi1NmzZNW7ZsUUJCQs5U5OHDh6tu3brFfcsAAAAAfNhPr/2i6RN+z/eYaZpaMWOtYg7H6pmfH1FgSICH0wEoPtPnpwDT/rPGpQ3At99+W7t27ZJhGKpZs6aeeeaZnKmvAQEl44tJ+fLldfvtt+v22293+pzPPvuswGPdu3dX9+7dLzlXvXr1NH78+Eu+DgAAALwnKzNL6+dt0c7Ve5WRlqEK1SPVdXgHNluAV+zdcLDA5t+Fdq/dr18/nKcR4wd7IBUAVzAMMQLQjbNIyyKXNgCnT58uSapatarWrFmTZ9dbAAAAoKxa/et6ffPcTzpzNC7X89+/MlNdhrXXba/fqJBywV5KB18074vFTtfO/3qphj58hfz87UUXA/A6w2QCrErgzNOSzKVbQO3du1eGYei+++6j+QcAAACfsfj7FXr7tk/yNP8kyZHl0LKfV+uVEROVmlj0xniAq6ydu8np2rMn47Vvw0E3pgHgSqbM8yMAffhB+88alzYAszfTaNy4sSsvCwAAAJRYscfP6rPx3xVZt2/DQU19Y7YHEgHn1/dLOpts6ZykeGv1ALzHcEiG6duPkrj3REnm0gZg7dq1JUnnzp1z5WUBAACAEuvPb5YqMz3TqdqFk5fl2YkVcAfDMBRaPsTSOaER1uoBeJlp+vTDMH1+ErQlLm0AXn311TJNU8uWLXPlZQEAAIASa/Xs9U7XJiekaOtfO92YBvh/7S5v6XRt+SoRqte6thvTAHAlWl/ig2CRSxuADz74oCIjIzV58mTt2LHDlZcGAAAASqRzZ5Ks1ccmuikJkNuA23o5Xdt/bA82AAFKEbMETMH19oNFAK1xaQOwWrVq+v777+Xn56cBAwZoyZIlrrw8AAAAUOIElwuyVM9OwPCU+q1r65rHBhVZ17BdXQ25b4AHEgFwFcOU5PDyw/TAo7DXhiV+rrzYiy++KEnq37+/Zs6cqT59+qh169bq0qWLKlasKJut6H7j888/78pIAAAAgFu1GdBCv3+8wKla/yB/NevWyM2JgP933ZNXKSQ8RD+/8Wue9ScNw1DnoW1154QxCgwJ8FJCAMVhZv2vCejVEN59ba+//1LGpQ3Af/3rXzKM85OwDcOQaZrasGGDNmzY4PQ1aAACAACgNBlwS0/N+WShU7sRdh/RQWGRoR5IBZxnGIaG3Ndf/W7urmU/r9He9QeUlZGlyrUrqucNnVW5dkVvRwRQHKbJKDiDRQCtcGkDUMq7DbOVbZkN/vIAAABQylSrX0XXPjlEP736S6F1laMr6Pp/DPVQKiC34LAg9R/bQ/3H9pAkObIcln5WA1Cy2AyDBqDp8HaCUsWlDcCFCxe68nIAAABAqXDNo4MUEBSgn16bpfSUjDzHG7arq4c/v1PlK4d7IR1wXmpSmpb+tEp/frNUh7YelWmaqhxdQb1Hd1O/m7orvGI5b0cE4CTT4ZDh6018H3/7Vrm0Adirl/O7TAEAAABlRfY0y96jumjJDyu1c+UeZaRnqkL1SPW4vrMatq/LbBd4VcyRWP3nhvd0bPeJXM+fOnRGP/5nln77+E89Mek+NWxfz0sJAVjClxSZfAwscfkUYAAAAMBXhZUP1ZV399OVd/fzdhQgR2piqv5z/bs6tudkgTWJsUl6beT7emXeP1SlTiUPpgNQHEb2Lrk+jE1ArCl6W14AAAAAQKm1+IeVhTb/siXFp+iX9/7wQCIAl8qQTcb/dsL11QesoQEIAAAAAGXY/K+XOF3718+rlZKY6sY0AFzByN4F2JcfsKRYU4APHTqU8+fo6Oh8ny+uC68HAAAAACi+9NQMHdlx3On6tOR0Hdt9QvXb1HFfKACXzpTPbwLCKEBritUArFu3rqTzix1nZmbmPF+nTp1LWtz44usBAAAAAIrPkeWwfE5WpvVzAAAlW7EagGYhXebCjgEAAAAAPCcwJEDlK4fr7KkEp+oNw1Dl6ApuTgXgUtlkMgIOlhSrATh27FhLzwMAAAAAPM8wDPUe1VUz3pnjVH2bgS1UvkqEm1MBuFQOh8E6eLCkWA3AL7/80tLzAAAAAADvGHBrL839fJFSzhW+uYdhM3TV/QM8lArApTDo/vERsIhdgAEAAACgDIuqVl7jvr5HQaGBBdYYNkN3vDlKTTo39GAyAMVmSobDyw/TRY9ivj4dQGuKNQIQAAAAAFB6NO/eWC/NeVIzJ87RylnrlJl+fvNFwzDUqm8zXfXgQDXr2sjLKQE4yzAleXsPBi+/PGsgWkMDEAAAAAB8QM3G1XT/h7dq7CvX68jO43I4HKpSp5IqVI/0djQAVpnyegPO6wxvByhdaAACAAAAgA8JiwxV4071tWv1Pq37Y7NkmqrRuJqadG4gm41VooDSwHSwC7BBB9AStzQAs7Ky9Msvv+j333/Xli1bFBcXp9TUwheclc4PP9+7d687IgEAAAAAJK36ZZ2mvvGrjuw4nuv5qvUqa/hjV6rH9Z28lAyAswyZ3p8C7HW+/v6tcXkDcNu2bbrhhhu0bdu2XM+bTnxiGgbdWwAAAABwlzmfLtDXz/yU77ET+07pwwe+0unDZzR83JUeTgbACtNh0v9yeDtA6eLSBuDp06fVr18/nTp1Kqfh5+fnp4oVKyowsOAdpwAAAAAA7rVn3QF98+zUIut+eu0XNWhXVy17N/VAKgDFYTOYAGv6fAfUGpc2AN944w2dPHlShmGodevW+s9//qM+ffooICDAlS8DAAAAALDo90/+dGpm1vnaBTQAgRLMNA1GAMISlzYAZ8+eLUlq0KCB/vrrL4WEhLjy8gAAAECJtH/TIc37crG2LduttJR0RVaNUPcRHdXzxs4KKx/q7XiA0lMztOqX9U7Xb/xzq87FJqpcVJgbUwEoLsNkDUBfHwFplUsbgAcPHpRhGLrrrrto/gEAAKDMy8rM0pdP/aA/v1ma6/mzJ+O1f+Mh/fzmbD3y+Z26rBcjqeBd52ITlZWR5XS9aZo6eyqBBiBQQhmSe3cBdsW1XdGhKySHj/c/LXPpHu/+/v6SpDp16rjysgAAAECJ9NXTP+Zp/l0oOSFFb9z0X+1Zd8BzoYB8BAZbX5YpIMjfDUkAuIRpSg43PkwXPNycw8YQQEtc2gCsV6+eJCk2NtaVlwUAAABKnMM7jmn+V0uKrMtIzdDkF6Z5IBFQsNDyIarVtLrT9RVrRqlSrQpuTATgUhimIcOUTz8YAWiNSxuAI0aMkGmamj9/visvCwAAAJQ4878ueOTfxXas2K3DO465MQ1QOMMw1H9sT6fr+93cXTa7S39cBOBKbp3/WzoYjAC0xKV39Pvvv1+1atXStGnTtGzZMldeGgBKJdM0tX/TIa2Y8bdW/bJOJw+c9nYkAICL7Fy5x1r9qr1uSgI4p/eorqrftk6RdbWaVtfld/RxfyAAxeeqabql+OHsruY4z6WbgERERGjGjBm68sorNXjwYL377rsaM2aMbDZ+cwTA96yY8bdmTpyrg1uP5Hq+Ze+muvaJIWrYvp6XkgEAXCEjLcOt9YCrBQT566kpD2jCrR9r+/Ld+dbUb1Nb47+5V8FhQR5OB8Aahr8xCNKaYjUAb7vttkKPN2/eXAsWLNCtt96qxx9/XB06dFDFihWLbAQahqHPP/+8OJEAoESZ+sav+vmN2fke27Rou7Yt361HPr9T7S5v6eFkAABXiaoeqWN7TjpdX6F6pBvTAM4JiwzVc9Mf1dalOzX/m6U6vP2YZJqq3rCq+t3cXS37NGMAB1AamCYNMFhSrAbgV199JaOIydbZx2NiYvT77787fW0agABKu7/nbCyw+ZctMz1T7971md78658ssA0ApVTP6ztry5IdTtWGRYaqdf8Wbk4EOMcwDLXo2UQtejbxdhQAxWaenwbsTa4ehGjx7TAD2JpiTwF2x1zropqKAFAazP7QuY2Q0lMyNO/LJRr1/DVuTgQAcIdOV7fV9/+eqdhjcUXWDrytlwKC/D2QCnCew+HQpoXbtODbZTq667hkGIpuVkP9buqu5j0a8/MZUIIZWSVgCmwZ6z+WdcVqAO7fv9/VOQCgTDh1MEY7LCwKv+SHlTQAAaCUCgjy1/hv7tEr105U0tnkAuvaXn6ZrnnsSg8mA4p29mS83rrlI+1ZeyDX88d2n9DKmWvVtGtDPfbl3QqLDPVOQABFYwgcLChWA7B27dquzgEAZULM0VhL9fGnE5SRliH/QEaFAEBpVLdltF76/QlNeWmG1s7dJEeWI+dY+crhGnBbLw196HLZ/exeTAnklpKYqn9f/+759f8KsH35br068n09P+MxRq8CJZDDYXp9BJ63GYwBtMSluwADgK/zD7B2WzUMQ3Z/figEgNKsWv0qeuyru3XmWJx2rtqjtJQMRVUtr+bdG8nP4tcFwBP++GJxoc2/bHvXHdDiKcs14NZeHkgFwAq75PMjAE3TUXQRcvAdCQC4UK0m1RUUGqjUpDSn6hu0q8tOewBQRlSoHqmu13TwdgygUA6HQ/O/XuJ0/byvlqj/LT1ZDxAoYUzTwfg3PgKWeKUBOH36dC1dulSZmZlq3bq1brzxRoWEhHgjCgC4VFBYkLpf10nzv3LuG+sBt/R0cyIAAID/F3M4VjGHnV+y5PD2Y0qMS1K5qDA3pgJgmSGfHwHo83OgLXJpA3D37t0aN26cJOm5555Thw65fwOanp6uwYMHa8GCBbmef/XVVzV37lzVrVvXlXEAwCuGPXKF1szeoPjTCYXWNWxXV12GtfNQKgAAACktJd3yOempGW5IAuBSGKbhmv6Xt3poFw/eK04O+n+WuHTe2Q8//KBff/1Vf/31l1q1apXn+CuvvKI///xTpmnmeuzZs0fXXHONHA7mbwMo/SpUj9QzUx9ShRqRBdY07lhfj0++j7WhAACAR0VWibA0ndfub2f0H1ASZUlymJf+ML30cEEOJgBb49IG4LJlyyRJ/fv3V0BAQK5jaWlpmjhxogzDUEREhN5++23NmDFDV155pSRp8+bN+umnn1wZBwC8plbTGnrzr3/qjrdGq0G7OgqLClV4xXJq3a+5xn1zj56f+RjfTAMAAI8LiwxVq37Nna7vdFUbdgEGSiLDIcM0ffphMgTQEpcOPTl06JAMw1D79u3zHPvjjz+UkJAgwzD0+eefa/jw4ZKkwYMHq0mTJtq3b5+mTp2qG264wZWRAMBrgkID1e+m7up3U3dvRwEAAMhx5d19tWH+liLrDMPQoDv7eiARAKtspuHzawAyAtAal44AjImJkSTVrFkzz7FFixZJkqKionTNNdfkPG+32zVy5EiZpqn169e7Mg5Q4h1LjtMXh5bojs1f6Pr1H+jWTZ/pw4N/6mBKjLejAQAAoIy6rFdTXfvEkCLrbnrpWjVoxzrtQElkyjy/Bp5PP2gBWuHSEYBxcXGSlGf6ryQtX75chmGoX79+edacqFevniTpxIkTrowDlGi/ndqo9w/MV5b5/2tfJmal6dfTG/Xr6Y0aVa2zRlfvYmmNFgAAAMAZI8YPVuXoipo24Ted2Hcq17EajavpuieGqNNVbb2UDkCRsptgPs3nPwCWuLQBGBQUpKSkJJ0+fTrX8ykpKVq3bp0kqWvXrnnOCws7vw5Werr1HamA0mjRmR2auP+PQmu+O75SQXZ/XVu1Q6F1AAAAQHH0uL6Tul3bQTtW7NHRXcclw1B00xpq1LEev4QGSjp6X3wMLHLpFODsqb9r167N9fzcuXOVkXF+6/j8GoDZIwfLlSvnyjhAiZTpyNJnRxY7VTvp6HKdy0x1cyIAAAD4KpvNpmbdGmnArb3UpFN9xZ9O0No5m3T68BlvRwNQmBKwCYe3H3QArXHpCMAuXbpox44dmjp1qv71r3+pZs2ayszM1IQJEySdX/+vbdu8w8i3b98uSYqOjnZlHKBEWhm/V7EZSU7VpptZ+vPMNg2rwvQLAAAAuMffv2/UjIlztHfdgZznDMNQyz5Nde3jQ1gHECiBDNP0+U1AYI1LRwDeeuutkqRz586pdevWuvHGG9WqVSv99ddfMgxDN998s2y2vC+5dOnS819gWrZ0ZRygRNqeeNxS/bbEo25KAgAAAF/36wfz9NbYj3I1/yTJNE1tXLBNLwydoL/nbPROOAAFOr8JiK8/WKrACpc2ALt376677rpLpmkqNjZWP/30k3bs2CHp/PTgZ555Js85+/bty5kynN/0YKCsyXBkWqzPclMSAAAA+LJNi7Zr8gvTCq3JTM/Ue3d/rlMHYzyUCoAzDFOSw/Tuw1ONvgJem6VKrXFpA1CS/vvf/+qdd95R8+bNFRAQoMjISN14443666+/FBUVlaf+ww8/zPnz5Zdf7uo4QIlTKSDcUn3lQGv1AAAAgDN+/WCeU3XpKRn64wvn1rAG4Blmlvn/OwF76+Hw0KOA1zZd8HH0JS5vABqGoYceekibN29WSkqKYmJi9N1336lWrVr51o8fP1779+/X/v37VadOHVfHAUqcPhWayCbnf1XRr0IzN6YBAACAL4o9flabF293un7xDytkst4YUGIY8v4mHN5+yOHw9l9DqeLSTUCKo2rVqt6OAHhUxYBy6hXVRAtji/6Gq0VYDTUK5d8IAAAAXCvmSKyl+sTYJKUlpSkoLMhNiQBYwvxXycLAGpSABiDgi+6v3U/H085qR1LBG4JUDyyvp+oN9mAqAABQHMkJKdr19z6lJaUpolI5NWxfT3Y/u7djAYXyC7D+OWr35/MaKClMh0M+vwuwj799q2gAAl4QYg/Qa02v189n1mv64dU6l5macyzI5q9+FZppTPWuivAP9mJKAABQmLMn4zX19V/118+rlZacnvN8hRqRGnhbbw2+tx+NQJRYNRpWU3C5IKWcSy26WFKdy2rJP9DfzakAOMswVfwGYFlpnBll5Y14RrEagN98803On2+++eZ8ny+uC68HlGVB9gA90PgKXVuxrTacPahzmakKsQfqsnI1FGIP9HY8AABQiFMHY/TisAk6czQuz7EzR+M05aXp2rlqjx798m75MWoKJVBgSIB63tBZcz9b5FT9gFt7ujcQAEvM7N1xfZjp4+/fqmI1AG+55RYZhiHDMHI17LKfL66Lrwf4gkCbv9pH1PV2DAAA4CSHw6G3xn6Ub/PvQuv+2Kwf/zNLo56/xkPJAGuufvByrZy5TvGnEwqtq3NZLXW/tpOHUgFwjunzU4BtrINoSbF3ATZNM99doLKfL+4DAAAAKMk2LdquQ9uOOlU7/6slSk10bool4GlR1crrmakPqUKNyAJr6rWurSenPKCAIKb/AiWJLXsKsK8/4LRijQD88ssvLT0PAAAAlBVLvl/hdG1KYqpWz96gnjd0dmMioPhqNa2hN5c+r6VTV2vh5GU6se+UbHab6lxWS/1u7qEOV7ZmGjtQApmSdxtg2S/tzUF4DAC0pFgNwOxpvn379s31/NixYy89EQAAAFCCnT58xq31gKcFhQVpwC09NeAW1vkDSgtDZsnYzKMkZIBTLmkNwOnTp6tmzZo5z992222SpIceekitW7d2SUAAAACgJPHzt/YttH9Asb7lBjwuMyNLa+ds1OLvV+jUwRjZ7HY1aFtb/cb2VP3Wtb0dD8AFzi+h5tvdN99+99a59LuRr776SoZhaNiwYTQAAQAAUCY1aFdXO1bucb6+PZt9oeQ7se+U3hjzoY7tOZnr+cPbj2rh5OXqMqyd7nl3LGsBAiWFQ6yBxy7AlhRrExA/v/N9w7S0NJeGAQAAAEq6/jf3cLq2RqOqatqloRvTAJcu7mS8Xhr+Tp7m34VWzFir9+7+nI0bgZLCdJxvgPnygzGAlhSrARgVFSVJ2rFjh0vDAAAAACVdlbqVdMWdfYqsM2yGRv9rRM762UBJNX3Cb4o9Fldk3d+/b9SGP7d6IBGAIpnyfgPOlbv5Fuv1vf2XULoUawpwmzZtNHfuXL333ntq1KiR2rRpo6CgoJzjp06d0qFDh4oVKDo6uljnoWh2O7t3lSTZfx/8vcAKPl9QEO4psIrPlUtzyys3KCMtU39+szTf434BfrrvvbFqf3krDydzDe4pviPlXKqW/rjK6fr5Xy/N9/OazxUUhPuJm2Q3zsoqJ96awTbAlhhmMcZw//jjj7rxxhvz/DYz+1LF/S2nYRjKzMws1rkAAACAp21bsVOzPpyrdfM3KSUxVZFVyqvPjd00+K7+qhxdydvxgCJtXLRV4/v+y+n6oNBA/XJuktvyAHDOQ1e+od2bDns7hlc999nt6npF6fxFmzcUawTg9ddfryVLlujDDz/M9zjrQpRMcXFFD+uH59jtdoWHhyshIUFZWVnejoMSLDw8XHa7XVlZWUpISPB2HJRQ3FPgDO4nrletSWXd/e5N+R4rzd97cU/xHWdOn7FUn5aSrtjYWBmGwT0FTimt95PIyEhvRyiUWdZHADrBx9++ZcXeBfj999/XHXfcodmzZ+vw4cNKS0vT119/LcMw1Lt3b6bylkCl6WbrS7Kysvi7gdP4XEFRuKfAWXyewBncU8q+iErhluojq0TI4XDkeZ7PExSF+4lrMflVMugAWlLsBqAktW7dWq1bt87576+//lqS9PDDD+vqq6++pGAAAAAAAPeKbl5DNZtU05Edx52q735tRzcnAuAMh+koeghcaW+QFbG8XCl/dx5XrF2AAQAAAACln2EYuvLufk7V+gf6qf/Ynm5OBMAZNklyOAp/uHKXXm88inh/jIK05pJGAF5s4cKFkqQWLVq48rIAAAAAADfpPaqrdq3Zp0XfLS+wxma36d73xqpSdAUPJgNQINYAZP8Ji1zaAOzVq5crLwcAAAAAcDPDMHTnhNGq0aiaZv93vs6ejM91vG6raI18dpgu69XUSwkBXMx0uKEB6O5+mrND9pzMQf/PGpc2AAEAAAAApY/NZtOQ+/rrijv7aNPCbTp18LTsfnbVa1NH9VvX9nY8ABcxzP81Ad3qUq9/UcfP8uUKP8Ew6ABaQQMQAAAAACBJ8vO3q+3Ay5SZnqlNi7dr77oDOrT1iBq2r6eajat5Ox6A/zHPdwA9/KJFHM8zws+9IxRZA9AaGoAAAAAAAEmSI8uhXz6Yp98/XqD40wm5jjXp0lCjnhumhu3reSkdgBwOs+Rtg+vhPEwBtoZdgAEAAAAAcjgcev++L/X9yzPyNP8kaceK3Xrpmre1YcFWL6QDcCFDOt9w8+GHYTAG0AoagAAAAAAAzfl0oVZM/7vQmoy0TL17x2dKiDnnoVQA8mM6HOenAPvww/T0FOhSjgYgAAAAAPg4R5ZDv3+ywKnalMRULfpuuZsTASiUKck0ffpB/88aGoAAAAAA4ON2rt6rmMOxTtcvnbrKjWkAFMk0JYfDu49LbeK54vWddPr0aY0bN04NGzZUcHCwKlasqIEDB2rGjBmX9NewbNkyjRo1SnXq1FFQUJCCg4NVv359jR07VmvWrCny/EWLFmnYsGGqWrWqgoKCVKdOHd19993av3//JeXKDw1AAAAAAPBxscfPWqqPs1gPwLVM0/T+w+G4tMclvr6zawBu3bpVLVq00IQJE7Rnzx75+/vr7Nmzmjdvnq655ho9/PDDxfo7+Oc//6nu3btrypQpOnjwoOx2uyRp3759+uabb9SpUye9/vrrBZ7/+uuvq2/fvpo5c6ZOnTqlwMBAHTx4UJ988olatWqlxYsXFytXQWgAAgAAAICPCwwOsFTvH2StHoBrGaZ5fidgbz48MdW3sNd2YtvhtLQ0XX311Tp16pRatGihDRs2KCEhQQkJCXr55ZdlGIbeffddffnll5Y+/vPnz9eLL74oSbr22mu1e/duJSUlKTk5WVu2bNHll18u0zT11FNP5TsS8I8//tBTTz0l0zT14IMPKjY2VvHx8dqzZ4969+6tc+fOafjw4Tpz5oylXIWhAQgAAAAAPq5Bu7qy+9udrm/WraEb0wAoiumpBlxxmnOeaDI6TGf6f/rkk0+0b98+hYSEaPbs2WrVqpUkKSQkRM8884zuu+8+SdKzzz6rjIwMpz/+kydPliQ1aNBAU6ZMUYMGDSSd35m4efPmmj59uqpUqSLTNDVt2rQ85//jH/+QaZoaMmSI3n33XZUvX16SVL9+fc2cOVPVq1dXbGysXnvtNaczFYUGIAAAAAD4uPKVw9VxSBun6wfc0tONaQAUxbSw/p0vmzRpkiRp5MiRio6OznP8iSeekGEYOnbsmBYuXOj0dY8fPy5JatWqlfz8/PIcDw4OVvPmzSVJiYmJuY5t375d69atkyQ9+eSTec4NDw/XvffeK0n67rvvXPZ3TQMQAAAAAKAbnrpaYVGhRdZ1G95BjTs18EAiAAWxGSpgdJyjjD4KGAlYiMTExJzpt1dccUW+NdHR0WratKkk6c8//3T641+3bl1J0saNG5WZmZnneEpKirZu3SpJatu2ba5jCxac33E9PDxcXbt2zff6l19+uSTp6NGj2rFjh9O5CkMDEAAAALDo9OEz+v6VGXqq7yt6uMNzem7Qa/r1g3k6F5tY9MlACVWlbiU9O/URVagRWWBNj+s76Z53b3Z68X0A7uFwZMk0Hfk8Lt6oo6w88tlEpIjb0Pbt23NGz7Vo0aLAuuxj27Ztc/rjf+edd8owDO3Zs0cjR47Unj17JJ0fmblt2zYNHz5cJ0+eVNu2bTVmzJhc52a/TtOmTWWz5d+Wyx49aDVXYfKOUwQAAACQL9M09esH8/T9KzPlyHLkPH/qYIz2rD2gqW/M1v0f3KIOg1t7LyRwCWq3qKkJy/+llbPWacmPKxVzOFZ+gX5q1KGe+o/toXqtans7IgBJMo3z6+BZP9HlUbymiPefPU1XkqpXr15gXfaxC+uL0rZtW3377be66667NHXqVE2dOlUhISFyOBxKTU1VxYoV9dhjj+mFF16Qv79/vrkKyxQSEqLy5cvr7NmzlnIVhgYgAAAA4KQ5ny7Udy9OL/B4WnKa3rnjUz0x+X616tvMg8kA1wkIDlDPGzqr5w2dJZ1vfKcmpck/0L+IMwF4zP9G/F36dS79EpblN3KvGDmKWhvvwrX3QkJCCqzLPnbu3DlLrz969GhVr15dN910k44ePark5OScY2lpaUpKSlJ6enqBuQrLlH387NmzlnMVhCnAAAAAgBMS45I05eUZRdY5shz66ukf5HC44AczwIuO7jquL56cojsajtNt9R7VTTUe0PNXvqGlP65SZkaWt+MBPs101S68HllD0Indg4vx2t5ciSAzM1P33nuv+vbtqxo1amj+/PmKjY3ViRMncnbx/fjjj9W9e3fFxcV5L+gFGAEIAAAAOGHx9yuUkZrhVO2Jfae0ZclOtezd1M2pAPdY+uMqffzIN8rKzN3I3v33Pu3+e58WTF6mV375h8KjynkpIeDbylcKV/dR7dVjVAdL5y39bo3++m6Nm1IVpOjhfd1HdbD8XoLCCh+VHBYWlvPn5ORkhYeH51uXPXKvXDnn72dvvvmmPvroIzVp0kSLFy9WUFBQzrGrr75aXbp0UfPmzbV9+3a9+uqreu211/LkunDEoKtyFYYGIAAAAOCEHSv2WKrfvmIXDUCUSpsWbtN/H/paZiHra+1YsVuv3Pi2Xp37nAeTAch2x39GafXCtYqokn9TqyDtBrRUjZo1ZLPbZLMZstltMv73/zbb/z+X83wBm1QUxZHlOP9wmHL8b9MOR5b5v+f+9+fs5x2mqjaraPm9VKlSudDjF66xd+zYsQIbgMeOHZMkVatWzenXfvvttyVJ999/f67mX7ZKlSrppptu0oQJEzRz5sxcDcDsXNmvm5/k5GSdPXvWcq7C0AAEAAAAnJCWkncdn8Kkpzg3WhAoaX58dVahzb9s6+Zv1sZFW3VZTxrdgKfVa1lHoVWCdfLkSUvndbiijaqMreKmVMV38uRJy+/l4s01LtakSRMZhiHTNLV161Y1adIk37qtW7dKkpo1c27t3jNnzujUqVOSpHr16hVYl33swIEDuZ7Pfp3t27fL4XDk22S9cOdfZ3MVhQYgAAAA4ISoauUt1UdWtVYPlAT7Nx/W3vUHna7/9eM/aAACXlKlShVVqVLymnnF4Y73EhYWpo4dO2rVqlWaM2eORowYkafmyJEjOc22fv36OXXdCxt2hw4dKrAu+9jFIw/79u0rSUpISNCKFSvUrVu3POfOnTtXklSjRo0CG5dWsQkIAAAA4IRuI5xfm8hmt6nLsHZuTAO4x4FNBf8wm5896w+4JwgAuMDo0aMlSVOmTNHhw4fzHH/99ddlmqaqV6+uPn36OHXNyMhI1a5dW5L02WefKSsr76ZICQkJmjJliiSpU6dOuY41adJEbdu2zXn9i507d07//e9/JUmjRo2S4aLdTmgAAgAAAE5o3qOxopvVcKq289C2qlA90s2JANdzZFnbvdpqPQB40l133aV69eopKSlJQ4YM0aZNmyRJKSkpevXVV/X+++9Lkl5++eU8U4rr1KkjwzB0yy235LnuvffeK0lau3athg4dqm3btsnhcCgzM1OrV6/WFVdckdNwfPjhh/Oc/5///EeSNGvWLD3yyCOKj4+XJO3bt09Dhw7V0aNHFRUVpSeeeMI1HwjRAAQAAACcYrPZ9OgXd6l85cIXKa/doqZue22kh1IBrlWtvrUpeDUaVnVTEgC4dIGBgZo1a5YqV66sTZs2qVWrVoqIiFC5cuX0j3/8Q6Zp6sEHH9Stt95q6brjx4/XDTfcIEmaPXu2mjdvrtDQUIWEhKhTp05asWKFbDabXn31VfXv3z/P+QMHDtRrr70mwzA0ceJERUVFqXz58qpfv74WLlyocuXKadq0aapYsaJLPg4SDUAAAADAaVXrVdZLc55Up6vaymbP/a10YEig+t/SU8/PfEyhESFeSghcmiZdGqhKnUpO1w+63bk1swDAW5o3b67Nmzfr0UcfVYMGDZSWlqaIiAj1799f06dP17vvvmv5mna7Xd9//71mzJihYcOGqUaNGnI4HLLb7apXr55uvvlmrVixQk8++WSB13jiiSe0YMECDR06VBUrVlRKSopq166tO++8Uxs3blSvXr0u5W3nYZimWfT2TigTYmJivB0BF7Db7YqMjFRcXFy+awYA2SIjI2W325WVlaW4uDhvx0EJxT0FzuB+4lqxx89qy5IdSklMVbmoULXu10Ih4cHejuUS3FN828LJy/TJo5OKrItuWkMfb3hThs3gnoICldb7iStHXgElAbsAAwAAAMUQVa28et7Q2dsxAJfrPaqrTuw7pVnv/VFgTaXoCnphxhPy8/crVU0dAPBVNAABAAAAADkMw9DI565Rg7Z19dvHf2rHyj05x8IiQ9V7VFdddf8AVatnbb1AAID30AAEAAAAAOTRYXBrdRjcWqcPn1Hc8bPyDw5QjYZVFRDkX/TJAIAShQYgAAAAAKBAUdXK68Cmw1o2fY3OnoxXYEigmndvrGH3DVJUlUhvxwMAOIEGIAAAAAAgXwc2H9bbt36sU4fO5Hp+08Jtmvr6r7rj1dEa+sAVXkoHAHAWDUAAAAAAQB5Hdx3Xy8PfVlJ8Sr7HM9Iy9N9Hv1JWZpb6jO3q4XQAACts3g4AAAAAACh5vn7mpwKbfxf6/B/fKe5kvAcSAQCKiwYgAAAAACCX43tPavPi7U7VZmVmacG3f7k5EQDgUtAABAAAAADksnnxDmv1i5xrFgIAvIMGIAAAAAAgl9TEVEv1KRbrAQCeRQMQAAAAAJBLeKVy1uorWqsHAHgWDUAAAAAAQC5tB7aUf6Cf0/VdhrVzYxoAwKWiAQgAAAAAyCW8Qpi6jejoZG05db2mg5sTAQAuBQ1AAAAAAEAeN714raKb1Si0xj/QX09PeVhBoYEeSgUAKA4agAAAAACAPELCg/X8zMfU/dqOsvvl/dGxfus6euPPf6p1nxZeSAcAsML5RR0AAAAAAD4lNCJE9394q0b/c7hW/bpeZ0/GKzAkQM27N1aH/m3l5+enrKwsb8cEABSBBiAAuFnCmUQtnLxMS75foVOHzsjP364Gbeuo/y091X5QK9n97N6OCAAAUKjyVSJ0+e29dXL/aa36db1W/bJeu1buV4fLW6tRh/rejgcAKAINQABwox0r9+jNm/+rpLPJOc9lpmdqy9Kd2rJ0pxp3qq/x396rsPKhXkwJAABQuLiT8fps/GSt/2OLTNPMeX7Si1NVv3Ud3fLqDWrQto73AgIACsUagADgJkd2Htfroz7I1fy72M5Ve/XWzR8pK5OpMwBQWhzfd0q/ffynfnrtF835dIFOHzrj7UiAW8WdjNe/Br+hdXM352r+Zdu74YBeumaCdqzc44V0AABnMAIQANzk5zdnKyUxtci6HSv3aO2cTeo4pI0HUgEAiuvk/tP68h/fa+OCbbme/+bZqWp7+WW69dUbVaF6pJfSAe7zxRNTdKqIRnd6Sobeveszvfv3y/IL4MdMAChpGAEIAG5w9lSC1sxe73T9vK+WuDENAOBSHd97Us8Pfj1P80+STNPU2jmb9PyVbyjmSKwX0gHuc/rQGa2ds8mp2rgT8Vpt4fsfAIDn0AAEADc4sOWwsjIdTtfvXXfAfWEAAJfENE29d/fnSohJLLQu9licPnzgK8+EAjxk9ez1+U77LciqWevcmAYAUFw0AAHADTLTM63VswYgAJRYO1ft1f5Nh52q3b58tw5uPeLmRIDnJJwpvPF9qfUAAM+gAQgAblCldkVL9ZWjK7gpCQDgUq2Y8bdb64GSLLhckFvrAQCeQQMQANygZpPqqtsq2un6Xjd2cWMaAMCliD99zq31QEnWum9zS/WtLNYDADyDBiAAuIFhGLrqgYFO1YZFhqr3qK5uTgQAKK6g0EC31gMlWZ3Laqlh+3pO1QaFBqrH9Z3cnAgAUBw0AAHATboMbafhj11ZaE1wuSCN/+ZelYsK81AqAIBVl/VqYrG+qZuSAN5x++sjFRxW9NTe214bqZBywR5IBACwigYgALjRdU9dpYc/uyPPdGC7v11drmmvl35/Qo071fdSOgCAMzoOaaPwiuWcqq0UXUGt+zEFEmVL7RY19cy0R1SpgDWLQ8oF674PbmH0HwCUYH7eDgAAZV3nq9up89XtdHj7UZ0+HCu7n111LqupiErh3o4GAHCCf6C/bn99pN65/VOZpllgnc1u0x1vjJLNzu/YUfbUb11bb698QevnbdGKmX8r4fQ5hUeFq/3AVuo9spvSMlO9HREAUAjDLOy7GJQpMTEx3o6AC9jtdkVGRiouLk5ZWVnejoMSLDIyUna7XVlZWYqLi/N2HJRQ3FPgDO4nl2bFzLX69NFJSknM2+gILR+i+96/RW0HXuaFZK7HPQVFSTybpD2rDioxNknB4UGq3z5a5atEeDsWSqDSej+pWLGityMALsUIQAAAAMAJXYa2U6u+zfTXj6u09o/NSk5IVlj5ULW/srW6De/A5h/wCYlnkzTlpRn6a+oqpadk5Dxv97Op41VtNfqfw1WheqQXEwIA8kMDEAAAAHBSSLlgDby9twbe3tvbUQCPOxebqBeHTdCRHcfzHMvKdGjF9L+1c9Ve/WvWuALXCwQAeAcLlAAAAAAAivTZuMn5Nv8uFHssThPvLHy9TACA59EABAAAAAAU6tTBGK35baNTtXvXH9Su1fvcnAgAYAUNQAAAAABAoZZPX2NpVN9fU1e5MQ0AwCoagAAAAACAQsUeP2ut/oS1egCAe9EABAAAAAAUKjA4wFJ9QJC1egCAe9EABEqIwymx+un4Gn15ZKl+Or5GR1JjvR0JAAAAkCQ16dLQUn1Ti/UAAPfy83YAwNcdS43TxH1/aMO5Q7me//LoUrUuF60Ha/dXtaDy3gkHAAAASGrTv4Uq1opSzOGif0kdFBqoHtd38kAqAICzGAEIeNGhpBg9svW7PM2/bBvOHdK4Hd/raGqch5MBAAAA/89mt+mWf98gwzCKrB39rxEKDgvyQCoAgLN8bgRgfHy8pk6dqtWrV+vMmTMKDAxU/fr1deWVV6pz586Wr5ecnKxVq1Zpw4YN2rNnj06dOiWHw6HIyEg1adJEgwYNUvPmzQs8/5133tGCBQsKfY3o6Gi9//77lrOVWmam7DogQ8lyqLwcqiU58Y1GaWOapp7f9KPiM5MLrTubmaw39v2mt5uOcuobLgAAAMAd2l3eUg9+fJs+evgbpadk5Dlu97Np9L9GqP/YHl5IBwAojE81AA8dOqRnnnlG8fHxkqTg4GAlJSVpw4YN2rBhg6666irdeeedlq756KOP6vjx4zn/HRAQIJvNplOnTunUqVNasmSJrrnmGt16662FXicgIEAhISH5HgsPD7eUqdQykxVk/qAgxwzZdDrn6Uw1VKrtOqUbV0pG2Rm0uiPxuLbFH3GqdlfySe1MOqEmYdXcnAoAAAAoWJdh7dW8RxMt+m651s3ZpHOxiQoJD1HLPk3V9+buqlA90tsRAQD58JkGYEZGhl5++WXFx8erdu3aeuyxx1S3bl2lpaVp5syZmjx5sn755RfVrVtX/fv3d/q6WVlZqlOnjgYOHKh27dqpWrVqMk1Tx44d0zfffKMVK1Zo+vTpqlq1qgYNGlTgdbp3765HHnnEBe+0dDLMeJXLelh+2pXnmJ92K8zxb6UZa5Rke14y7F5I6HpLYndYq4/bSQMQAAAAXhdeIUxXPzhQY5+/QSnnUrV23kadOHJKe9buV1BooEIj8h/YAADwHp9pAM6dO1cnTpxQYGCgnn/+eVWqVEmSFBgYqOuvv16xsbH67bffNGnSJPXu3Vt+fs59aB555BG1aNEi13OGYahGjRp68skn9dxzz2nz5s2aPn16oQ1AXxfmeD7f5t+FAs15cjhqKsVubZRmSXU2o/CpvxeLt1gPAAAAuEtiXJK+feZnLZi8VKnJaTnPB4YEqPu1nXTjM0MVFhnqxYQAgAuVnfmURVi0aJEkqWfPnjnNvwuNGDFChmEoNjZWmzdvdvq6Fzf/LmSz2dS3b19J0okTJ5SYmGgttI+wm9vkb65xqjbQ/FEyy0YjLNge4NZ6AAAAwB3iTyfon0Pe1G+fzs/V/JOktOR0/fnNUv1zyJuKP53gpYQAgIv5RAMwJSVFu3fvliS1bds235pKlSqpZs2akqSNGze67LUvXL8vKyvLZdctSwIds52utSlJAeZCN6bxnHYRdSzVtw2v7Z4gAAAAgAUfPvC1ju0+UWjNsd0n9NFD33goEQCgKD4xBfjIkSMyTVOSVLt2wU2U2rVr6/Dhwzp8+LDLXnvLli2SpPLlyxe6mcemTZt099136/Tp0woICFC1atXUrl07DR48WJGRZXshXbsOWas3Xff3402dIxuoclCETqXGF1lb0T9MncrX90AqAAAAoGCHdxzTpoXbnKrd8OdWHdl5XDUbs441AHibT4wAjI2NzflzVFRUgXXZx+Li4lzyujExMZozZ44kqV+/fjIMo9DaU6dOKSgoSKmpqdq7d69+/PFHPfDAAy4dkVgyWf00LBuftnbDpmeaXyObCv68kCSbDD1cZ6DsZWgHZAAAAJROf01dbal+6U+r3JQEAGCFT4wATE1NzflzYGBggXXZx1JSUi75NTMzM/Xmm28qJSVFlStX1rXXXptvXf369dWoUSN16NBBFSpUkM1mU3JyslavXq2vvvpKsbGx+ve//60JEyaoRo0ahb7mpEmT9N133xV4fOTIkRo1atQlvS+3SGwlpTi3BqAkBZVrq6DA0j8q0jAMdbFF6o02Y/Tilp/z3eQjwj9EzzUfrm6VGnshIUoKm82W8/9lfUQwii/7l0wRERE5o96Bi3E/gbO4p6Ag504nWapPjEnifuPjuJ8AJYNPNAA9zTRNvf/++9q2bZsCAgI0fvx4hYbmvwPWVVddlee5kJAQ9e7dW82aNdMjjzyixMRETZkyRePHjy/0dZOSknTq1KkCjycnJ8tut1t7Mx5ght4oM+Uz54ptlWUL7ifDKHnvo7h6VGmqXyo+oT+Ob9KSU9uVkJGicP9g9arcTAOqXaYgNv/A/xiGUSL/DaNkyW7wAIXhfgJncU/BxQKDrX1vGhgcyP0GkrifAN7mEw3AoKCgnD+npaUpJCQk37q0tPM7WAUHB1/S633yySdasGCB7Ha7nnjiCTVp0qRY16lcubIGDx6sH374QX///bccDkehN83Q0FBVrly5wOMhISElcyMSo4YUdJ2M1J+KLDVDHpTpsEkqge/DIsMwZLPZ5HA45C+7Bldro8HV2uSpK5F/Z/Aom80mwzBkmqYcDoe346CEuvCewm/XURDuJ5fG4XDo4NYjSog9p7CIUNW5LFp2e9n8gZZ7CgrSonsTzfligdP1zbs15vtZH1da7yc0rlHW+EQD8MJ1/2JjYwtsAGavFXgpQ9S/+OILzZ49WzabTY899pg6duxY7GtJUqNGjSSdH7137tw5RUREFFg7ZswYjRkzpsDjMTExLlvf0OXMBxRqxCrQ/LPAkmTbPUpN7SelltD3YJHdbldkZKTi4+P5pgiFioyMlN1ul8PhKLn/huF13FPgDO4nxZOZkaU/vlikeV8s1on9p3Oer1grSv3H9tSgu/oqIMjfiwldj3sKCnJZv8YKiwxVYlzRU4HDokJ1Wf8m3G98XGm9n1SsWNHbEQCXKpu/srxIzZo1c9YdOHSo4B1ns4/VqlWrWK/zzTffaMaMGTIMQw8++KB69OhRrOv4JMNfSbYXdc72mjKMjjL/96lpKlBpxiDF2z9Tqu1mL4cEAAC+Jj01Q2+M/kDfPjc1V/NPkmIOx+r7l2fo39dOVEpiagFXAMqWgOAAjXlhhFO1Y/41osw1xwGgtPKJBmBwcLAaNmwoSVq3bl2+NTExMTp8+LAkqVWrVpZf47vvvtPUqVMlSffcc4/69etXzLS57dq1S9L591CuXDmXXLPEMgxl2HronP0dxdkXKdY+T3H2P5Vkf05ZRjNvpwMAAD7om2d/0qZF2wut2bl6rz55dJKHEgHe1+vGLrr11Rtl98t/iqTdz6ZbX71RvW7s4uFkAICC+EQDUJJ69+4tSVqyZIlOnz6d5/i0adNkmqaioqJ02WWXWbr21KlT9f3330uSbr/9dg0aNMip84pa/+D06dP67bffJEnt27f3rUVTDT/JCJUMH3rPAACgRIk7Ga9F3y1zqnblzLU6sa/gzdiAsmbgbb305c6JGvX0cNVpXktR1cqrVtPqGvboFXpn9UsaeFsvb0cEAFzAZ7orl19+uapWrarU1FS99NJL2r9/v6TzG39MnTpVs2fPlnR+HT0/v9xLI95xxx26+uqr9c477+S57qxZs/TNN99IksaOHauhQ4c6nWnRokX6z3/+o5UrVyohISHn+ZSUFC1evFhPPvmkzp07p+DgYI0cOdLqWwYAAMAl+OunVcrKdH6zlMXfr3BjGqDkqRxdUbe+PFIfbXhD//plvAbc2kvBYcHavHi7zp5KKPoCAACP8YlNQCTJ399fzz77rJ555hkdOHBADz/8sEJCQpSampqzC96QIUPUv39/S9f9/PPPJZ3f2WjmzJmaOXNmgbX/+Mc/1LRp05z/djgcWrFihVasOP/NYnBwsPz8/JSUlJSTKSIiQo8//rhq1qxpKRcAAAAuzcn9eWeNFOY4IwDhg04cOKUPHv5Cq35dl2uGk93frq7D2mvMi9cqvEKYFxMCACQfagBKUnR0tN577z39/PPPWr16tWJiYhQaGqp69epp8ODB6ty5s+VrZn+RM01TZ8+eLbQ2MzMz139fdtllGjNmjLZv366jR48qISFBycnJCg0NVa1atdS+fXtdfvnlZX/tPwAAgBLIsFubLGOzWA+Udkd2HdPjfV9Q3Mn4PMeyMrK09KdV2rNuv/45a5wiKoV7ISEAIJtPNQAlqXz58rr99tt1++23O33OZ599VuCxWbNmFTtL5cqVdf311xf7fAAAALhP3Za1LNXXa1XbTUmAksc0Tf175MR8m38XOr73lD4dN1njv7nXQ8kAAPnh15QAAABAProOa6/gckFO1foH+qnnDdZnkwCl1bZlu7Rv00GnatfO2WR5Sj0AwLVoAAIAAAD5CAoL0vBxg52qHXxff9Y5g09ZPv1va/UzrNUDAFyLBiAAAABQgMH39tPQhy8vtGbArT113ZNXeSgRUDKcLWLq76XWAwBcy+fWAAQAAACcZRiGbnxmmNoObKk/Pl+kNb9vUHpKhvwC/NR24GW6/PbeatatkbdjAh4XEBzg1noAgGvRAAQAAACK0KhDPTXqUE+maSojNUP+Qf4yDMPbsQCvad69sVbOXOt0fYseTdyYBgBQFKYAAwAAAE4yDEMBwQE0/+Dzuo/ooJDwYKdqq9SppMt60wAEAG+iAQgAAAAAsCQoLEj3TBhbZJ3NbtNtr90om40fPQHAm7gLAwAAAAAsGzi2tx756C75B/rnezy4XJAe/fIutezTzMPJAAAXYw1AAAAAAECxDL5rgDpf1U7TP/xNG+ZtUfK5FJWLClOnIW3U/fpOCinn3DRhAIB70QAEAAAAABRb+coRGvbwFbrq/gFa98dmbVq0XbvX7tfJgzHqMrSd6retw7qZAOBlNAABAAAAAJdkw4Kt+mzcZJ05Gpfr+d8++lMN2tXR/R/cqqr1KnspHQCANQABAAAAAMW2avZavTH6wzzNv2x71h7QP4e8qZMHTns4GQAgGw1AAAAAAECxpCan6c3b/itHlqPQuoSYc/riiSkeSgUAuBgNQAAAAABAsSyc8pfOxSY6Vbtp0XYd33vSzYkAAPmhAQgAAAAAKJbls9ZYqv/7941uSgIAKAwNQAAAAABAsTg7+i9bUnyym5IAAApDAxAAAAAAUCzlIsMs1YdGhLgpCQCgMDQAAQAAAADF0uXqDpbq213R0k1JAACFoQEIAAAAACiWPiO7qVyUc6MAL+vVVNUbVHVzIgBAfmgAAgAAAACKJTg0SOM+v1c2e+E/WoZXLKfbXx/poVQAgIvRAAQAAAAAFFvnIe30+KR7FVWtfL7H67eprRd+Ha8qdSt5NhgAIIeftwMAAAAAAEq31v1a6N21L2vtnE3atGi7UhNTFV6pnLoMbacG7erKMAxvRwQAn0YDEAAAAABwyex+dnUc0kaRVSM078slWvXLei35YaXKV4lQ12vaq+/obipfJcLbMQHAJ9EABAAAAABcsqzMLH3+xBQtnLQs1/NJZ5P106u/aNa7c/XAf29T+0GtvJQQAHwXawACAAAARUhLTteZY3FKPpfi7ShAifX1Mz/maf5dKC05Xe/c/om2Ld/lwVQAAIkRgAAAAECBNi/erjmfLdT6eVtkOkxJUqMO9TTg1l7qek37Inc+BXzF0V3HNe/LJUXWZWU69N0L0/Ty3Kc8kAoAkI0GIAAAAHAR0zT13QvT9OuH8/Mc27Vmn3at2acVM//Ww5/eqYAgfy8kBEqW+d8sdbp27/qD2rvhoOq3ru3GRACAC/ErSwAAAOAiv3+8IN/m34XWzd2szx//zkOJgJJt95p9Fuv3uikJACA/NAABAACAC6SnpGv62787Vbvkh5U6se+UmxMBJV9GWqZb6wEAl4YGIAAAAHCBNb9tUGJcktP1CwrZ9ADwFRVrRVmsr+CmJACA/NAABAAAAC5waNtRi/VH3JQEKD16Xt/Z6drQ8iFqO+AyN6YBAFyMBiAAAABwAdN0bz1QFrW7opWq1q3kVO2AW3sqMCTAzYkAABeiAQgAAABcoEajqm6tB8oiP3+7xn97ryIqhRda1+6KlhoxfoiHUgEAstEABAAAAC7Q6aq2Ci4X5HR93zHd3ZgGKD1qNKqml+Y8oe7XdpRfgF+uY1HVIzXy2WF69Iu75Odv91JCAPBdfkWXAAAAAL4jKDRQg+/tr6mv/1pkbcchbVSzcTUPpAJKh0q1Kuj+D2/VTS9eq11r9in2eJzOxSapUnQFVawZJcMwvB0RAHwSDUAAAADgItc8NkgxR2K16LvlBdY06dJQ9757swdTAaVHUnyy/pq6Wmt+2yBHliPn+Yq1ojTorr664s4+stmYkAYAnkIDEAAAALiIzWbTXW+PUcs+zTT3s4XauWpvzrEajapqwK291HdMN/kH+nsxJVAy7dt4UP++dqKS4lPyHIs5HKtvn5uqfesP6r4Pb6EJCAAeQgMQAAAAyIdhGOoytJ26DG2nuJPxOncmUcHlgpjGCBQiLTldb97033ybfxdaNm2NareoqaseGOihZADg2/h1CwAAAFCEyCoRim5WQ5VqVaD5BxRi+fQ1ijsR71Tt758sUGZGlpsTAQAkGoAAAAAAABdZ8sNKp2vjTsRr69KdbkwDAMjGFGAA8JDYE2e14Ju/tPTHlTpzLE5+Af5q3Km++o/toXaXt5TNzu9kAABA6RZzNNZa/ZEzbkoCALgQDUAA8IANC7Zq4u2fKjUpLee5rMw0bVq4TZsWbtNlvZrq0S/vUnBYkBdTAgAAXBr/AGs/YvpZrAcAFA/DTQDAzfauP6AJYz/K1fy72ObF2zXxjk9lmqYHkwEAALhWow71rdV3tFYPACgeGoAA4GY//meWMtIyi6zbuGCbtizZ4YFEAAAA7tH/lp5O17bo2UTV6lV2YxoAQDYagADgRif3n9amRdudrp//1RI3pgEAAHCv+m1qq9uIjkXWBQT7a+Rzw9wfCAAgiQYgALjVvo0HLdXvWW+tHgAAoCQxDEN3vzNGXYe3L7AmJDxYj397n+q1qu3BZADg21hxFQDcKDM9y1J9Voa1egAAgJLGP9BfD/z3Ng24pZfmf7VE21fuUXpquipUi1T36zqp98guCosM9XZMAPApNAABwI0q167o1noAAICSyDAMNencQI071deOlXs076sl2v33Ps3+cJ5W/bJWPa/vrO7XdVJwWJC3owKAT6ABCABu1LBDXVWrX1nH955yqr7XyC5uTgQAAOAZ6Snp+uC+L7V69oZcz589laA9aw/o5zd/0/hv71WDtnW8kg8AfAlrAAKAG9lsNl31wECnaqOqlVe34R3cnAgAAMD9TNPUe/d8kaf5d6H40wn6z/Xv6tieE54LBgA+igYgALhZ71FdNejuvoXWlKsQpscn3aeg0EAPpQIAAHCfrUt36u/fNxZZl5yQoh//84sHEgGAb6MBCABuZhiGbnrxWt33wS2q3bxmrmP+Qf7qdWMXvTznSdW5rJaXEgIAALjWvK+WOF379+8bFHcy3o1pAACsAQgAHmAYhnpc10ndr+2ow9uPKeZorAIC/VWnZS2FlWcXPAAAULbsXLXX6dqsTIf2rjug9oNauTERAPg2GoAA4EGGYSi6WQ1FN6vh7SgAAABuk5GW4dZ6AIA1TAEGAAAAALhUhRpR1uqrR7opCQBAogEIAAAAAHCxHtd1dLq2at1KatC+rhvTAABoAAIAAAAAXKr3qK4KjQh2qvbKe/rJZuNHUwBwJ+6yAAAAAACXKhcVpke/vFuBIQGF1vUZ3VX9b+npoVQA4LtoAAIAAAAFyMrM0rnYRKWnpHs7ClDqNO/eWP/6Zbxa928hwzByHascXUG3/OcG3TlhTJ5jAADXYxdgAAAA4CJ71h3QnE8XavWv65SRlilJatyxvgbc2lNdhrWXzc7v0QFn1Lmslp787n6dOhijHat2a+eqfUqMTVR4xXLKSMtU/KkEla8S4e2YAFDm0QAEAAAALvDL+3/ouxen53l+5+q92rl6r5b+tEqPflH01EYA/2/jwm368dVZSoxNyvX89y9PV6+RXTX25esUEMy/KQBwF351CQAAAPzP0h9X5dv8u9DGBdv00cPfeCgRUPrNmDhHXzwxJU/zT5KyMh1a8O1femPMh8pMz/RCOgDwDTQAAQAAAEmOLId+fG2WU7UrZ67VwS1H3JwIKP0ObD6sH16ZWWTdlqU79dtHf3ogEQD4JhqAAAAAgKRNi7Yp5nCs0/Xzv1nqxjRA2fDHl4udrp331RI5shxuTAMAvosGIAAAACDpgMURfYwABIq25rcNTtfGHInVvo2H3BcGAHwYDUAAAABAkukwLZ5gsR7wMaZp5rvuX2ES4xLdlAYAfBsNQAAAAEBS9QZVLNVXrV/ZTUmAssEwDIWEB1s6J6SctXoAgHNoAKLEspv7FOj4UUGObxTg+FWGmeDtSAAAoAxrO/AyhVcMc7q+75jubkwDlA1t+rdwujaiUrjqta7txjQA4LtoAKLEsZu7VC7zPkVkjVGo4x2FOD5SmOPfKp81VCFZb0hmsrcjAgCAMsg/0F9X3T/QqdqmXRuqcaf6bk4ElH4Db+vldG2/m7rLL8DPjWkAwHdxd/Uhdrvd2xGKZHdsVmjmQzKUt8lnKE1B5nT5OXYqyf8DyQjxQkLXyf77yO/vxTRNpZuZCjD8ZBiGp6OhBCsN/47hHYXdU4D88LmSv6sfvFynD50pdOfS2i1qatxX98jPr+x+K809BVYV9LnStEsjXXl3P/328Z+Fnl+3VbSGPXwFn3NlEPcToGQwTJPVi1EymGaazNP9JMepoouDb5Qt4kX3h/Ig0zS15sxe/XhohZaf3qVMM0tBdn/1qdJc10d3UfPytbwdEQAAn2CappZMXalpE2dr2/KdOc9XqlVBQ+4eqGseGqTgMNYpA5zlcDj07Qs/6YfXZyojLSPP8c5D2umJrx9QuUjnp+ADAKyhAehD4uLivB2hUP5Zvykk8wWnak0FKiHgV8kId3Mq97Hb7QoPD1dCQoLSMzP07v55mnN6U4H1Y2p01ZgaXRkR6IPCw8Nlt9uVlZWlhATWwkT+LrynZGVleTsOSijuJ9bFHDmjs6fOKSg0UNUbVJHN7hsr6HBPgTOs3lMSzpzToikrtHvtPp07kyi7n10N29dVs66N1KJHE5/59+VrSuv9JDIy0tsRAJcqu/MWkEdJv9kGZ/3hdK2hNNkzFyrdNsSNiTwjKytLnx9cVGjzT5ImHV2ucvZAXVW5jYeSoSQq6f+O4X1ZWVl8nsApfJ44J7JaeUVWKy9JMmX63MeNewqc5cznSWj5EFVvWEVLf1qpg1uOSJI2L96uaW/9pkrRFTT0ocvV96bu/MK7jOJ+AngXv2JBiWEzz1irV6ybknjWmfREzTi13qnaSUdXKM2Rd9oEAAAAUNIt/G653hj9YU7z70KnD53RZ+O/03cvTvdCMgAo+2gAosQwFeTW+pJq7unNyjIdTtWey0rVsrjdbk4EAAAAuNbhHcf02bjJKmoFql8/mKc1szd4JhQA+BAagCgxMo32bq0vqfYknbRY78QmKQAAAEAJMvezRXJkOfdL76J2DAYAWEcDECVGqm2oTDm3NXyGWivLqOfmRJ6RZXEfHoec+8YJAAAAKAkcDoeWT1vjdP2OlXt0+rC15YEAAIWjAYgSwzQqKcV2Z9F1Clay/RH3B/KQGkHlLdVXC7RWDwAAAHhTalKaUhJTLZ0TdyLeTWkAwDfRAESJkmrcpGTbPQWOBHSoos7Z31GW0cjDydxnYKXLnK71N+zqHdXUjWkAAAAA1woI9Ld+TpD1cwAABfPzdgAgF8NQqnGz0oxBCnLMlJ/5twylyGFUULoxQOlGX8kI9HZKl6oTUlGdy9fXyrN7i6wdVKmlIvyDPZAKAAAAcA2/AD816lBPu9bsc6o+vGKYajSq6uZUAOBbGAGIEsk0KinFfofO+X2kBL+vlWifoHTboDLX/Ms2rs4VahRa+Dc5HSPq6faaPT2UCAAAAHCd/rc4/31s71Hd5F+MUYMAgILRAARKgFC/QL3a6DqNrdFNlQLK5TpWMyhS90b30XMNrpa/zblNUgAAAICSpOs17dW0a8Mi66rUqaQh9/X3QCIA8C1MAQZKiCC7v26o1knXVu2gAykxSspMU7h/sGoHVZBhGN6OBwAAABSb3c+u8d/eq/fu+lwb/tyab02tpjX0xOT7VC4qzMPpAKDsowEIlDB2w6b6IZW9HQMAAABwqZBywXriu/u1c9Uezf9qqfZvPqS05HSFRoSocaf66jK0nSrUiPR2TAAok2gAAgAAAAA8wjAMNencUOdik3R4xzEdO3pSZ47G6dC2o5r35RLVaFRVw8ddqa7XdPB2VAAoU2gAAgAAAAA8Zu7ni/TVP37I99jRXSf03t1f6PThWA196HIPJwOAsotNQAAAAAAAHrF3/QF9/fSPRdZ9//IMbf1rpwcSAYBvoAEIAAAAAPCI3z9eINM0nav9ZIGb0wCA76ABCAAAAABwu/SUdK36db3T9ev+2KzEs0luTAQAvoMGIAAAAADA7c7FJiozPdPpetNh6uzJBDcmAgDfQQMQAAAAAOB2/kEBls8JCPJ3QxIA8D00AAEAAAAAblcuKlQ1GlV1ur5irShVrBXlxkQA4DtoAAIAAAAA3M4wDA24tZfT9f1u7iGbjR9ZAcAVuJsCAAAAF0k4k6jD24/q5P7TcmQ5vB0HKDP6jOqqui1rFVlXo3E1DbzN+WYhAKBwft4OAAAAAJQUmxZu0++fLNDGBdtkmqak89MQ+93cQ5ff3lvBYUFeTgiUbgHBAXrqh4c0YexH2rl6b741dVtF6/FJ9ymkXLCH0wFA2UUDEAAAAJA09fVf9fObs/M8H3M4Vj+8MlPLp63R0z8+pPJVIryQDig7wiuE6flZj2nTou368+ulOrTtqFIT0xRcLlC1W9RS+0GtFBoR4u2YAFCmMAUYAAAAPm/x9yvybf5d6PD2Y3rrlo/kcDAlGLhUNptNLXs3VZ3LaulcbKISzpzTyQMxWv3ren14/1e6v/U/9NtHf+aMxAUAXBoagAAAAPBpDodD0yf87lTtnrUHtGnRdjcnAso+0zT12bjJmvr6r0o5l5rneGJskr59fqq+e2GaF9IBQNlDAxAAAAA+bduyXTp54LTT9Qu//cuNaQDfsOqXdVo4eXmRdb9+OF+bF9N0B4BLRQMQAAAAPu3YrhOW6o/utlYPIK85nyx0unbu54vcFwQAfAQNQAAAAPg2w3BvPYBc4k7GF7gDcH7W/bFZacnpbkwEAGUfDUAAAAD4tOhmNazVN63upiSAb0iIOWep3nSYSopPdlMaAPANNAABAADg0xp3qq8ajao6Xd/v5h5uTAOUfSHlgi2fExQW6IYkAOA7aAACAADApxmGoeuevMqp2uY9GqtZt0ZuTgSUbRVrRal6Q+eb7o061CtW0xAA8P9oAAIAAMDndbqqrW5++bpCaxq2q6tHPr9TBmsAApfEMAwNvK2X0/VWagEA+aMBCAAAAEgadFdfvTTnSXUb0VF+AX45z0c3q6HbXh+p52Y8qrDyoV5MCJQdfcd0U9OuDYusazvwMnUZ1t4DiQCgbDNM0zS9HQKeERMT4+0IuIDdbldkZKTi4uKUlZXl7TgowSIjI2W325WVlaW4uDhvx0EJxT0FzuB+4rz01AwlxiUpINjfJ5t+3FPgjEu9p6Qmpuq/D32j1b+uz/d4zxs66/Y3RikgyP9So8KLSuv9pGLFit6OALiUX9ElAAAAgG8JCPJXVLXy3o4BlGlBYUF69Iu7dHjHMf357VLtWLFHcSfOKivTobDIUDmyHNq34aAad6rP1HsAuEQ0AAEAAAAAXhMUGqhtf+3W4e1Hc55LOpusk/tP66+pq9VmQAs9+PHtCg4L8mJKACjdWAMQAAAAAOAV52IT9fLwd3I1/y62ft4WTRj7kbIyS8/0UQAoaWgAAgAAAAC84pf35+nUwaLXKt+ydKdWzlrngUQAUDbRAAQAAAAAeFxGWoYWfrfM6fr5Xy1xYxoAKNtoAAIAAAAAPO7IzuNKjE1yun7nqr1MAwaAYqIBCAAAAADwuLTkdEv1pmkqIzXDTWkAoGyjAQgAAAAA8LioauUt1QeXC1JgaKB7wgBAGUcDEAAAAADgcZVrV1TD9vWcru9+bUcZhuHGRABQdtEABAAAAAB4xZX39HWqzma3aeBtvd0bBgDKMBqAAAAAAACv6HRVWw26u/AmoGEYunPCaNVsXM1DqQCg7PHzdgAAAAAAgG8yDEM3vXitqtWrrFnv/aGYI7G5jleuXUEjHh+intd39lJCACgbGAEIAAAAAPAawzA04NZemrjmJQ175ApVqB6Zc+zUwTP6+OFv9fatH+vQtqNeTAkApRsNQAAAAACA1/385mzNeGeOzhyLy/W8I8uh1bM36Pkr39C2Zbu8lA4ASjcagAAAAAAAr1r1yzpNe+u3QmvSktP01tiPFH86wUOpAKDsoAEIAF6QmZ6pDQu2auHkZVo2bY3OHI0t+iQAAIAy6pcP5jlVl5yQooWTl7k5DQCUPWwCAgAelJWZpZnvztUfny/O9dtrw2ao3cCWuvG5YarRsKoXEwIAAHjW0V3HtXfdAafrF09ZoWGPDHJfIAAog2gAAoCHZGZk6Z3bP9HaOZvyHDMdpv6es1HbV+zS01MfVr1Wtb2QEAAAwPNOHTrj1noAAFOAAcBjZrz9e77NvwslxafozZv+q/SUdA+lAgAA8C4/f7u1+gBr9QAAGoAA4BHpqRma+8Uip2rjTsRrxcy17g0EAABQQtRuUUt+Ac5PTmvQrq4b0wBA2UQDEAA8YOOCrUqMTXK6fulPq9yYBgAAoOQIrxCmTle1dbp+wC093ZgGAMomGoAA4AFnjsVZqo+1WA8AAFCajRh/pULCg4usa9ypvjpcGCyQwwAAKJlJREFU2dr9gQCgjKEBCAAe4B/ob6neL8BaPQDg0mVmZGnDn1v05zdLtfj7FTqx75S3IwE+o1r9Knrq+wdUrkJYgTVNOjfQ+G/uld2PNQABwCp2AQYAD2jSqb61+s7W6gEAxefIcujXD+bp908X6uzJ+FzHWvZuqhufu0Z1L6vlpXSA72jYvp4mrPiXFk9ZoQWT/tLJAzFyZDkkSQFB/goKC9Suv/epdb/mstkYywIAVnDXBAAPqNGompp1a+R0PWvbAIBnOLIcev/eLzTl5Rl5mn+StGnRdr1w1ZvatnyXF9IBviesfKjqXFZLZ08mKCsjS6bDlOkwlZacrg3zt+qN0R/qtZEfKCUx1dtRAaBUoQEIAB4y6p/DFRBc9NTe/rf0VK2mNTyQCADw20d/asWMwndeT0tO14RbPlbiWec3cwJQPAc2H9YbYz5UckJKgTWbFm7Tu3d+JofD4cFkAFC60QAEAA+p37q2nph8v0LLhxRY0+/mHrrl39d7MBUA+K6szCz9/ulCp2qTziZr6Y/s0A6420+v/aK05PQi6zb8uVVbFu/wQCIAKBtYAxAAPKh598aauOYlLf1xpf6aulpxJ+IVEOSvpt0aacAtPVW3ZbS3IwKAz9i+fLelXdeX/rRKg+7q68ZEgG+LORKr9fO2OF0/76slatmnmRsTAUDZQQMQADwsNCJEV9zZV1fcyQ+RAOBNZyw0/yQp9thZ9wQBIEnau/6ATNN0un7P2v1uTAMAZQtTgAEAAOCTAoIDLNYXvY4rgOLLzMhyaz0A+DIagAAAAPBJjTrUk2EznK5v0qmBG9MAqBxdwVJ9JYv1AODLaAACAADAJ1WoHql2l7d0ur7/LT3dmAZAg3Z1Vb1BFafre93YxY1pAKBsoQEIAAAAn3XjM0MVEh5cZF2P6zqpYfu6HkgE+C7DMDTk/gFO1UZUCleP6zq5OREAlB00AAEAAOCzajSqpqd/ekjlK4cXWNPzhs666+0xMgznpwsDKJ7eo7rqijv7FFoTGhGsxyfd61TzHgBwHrsAAwAAwKfVb1NHb696Ucunr9HSH1cp5misAgL91ahjffW/pafqt67t7YiAzzAMQze/fJ3qXFZLs/87X4e3H7vgoBReoZw6XdVG5atEeC8kAJRChmlln/UyID4+XlOnTtXq1at15swZBQYGqn79+rryyivVuXPnYl83MzNTv/76qxYvXqxjx85/kapRo4Z69eqlwYMHy8+v8F7rvn37NH36dG3evFkJCQmKiIhQixYtNHz4cNWt65rpJjExMS65DlzDbrcrMjJScXFxyspiBzMULDIyUna7XVlZWYqLi/N2HJRQ3FPgDO4ncBb3FDjD3feUQ9uO6rVR7yv22Nk8x2x2m4Y9coWufWIIo3NLuNJ6P6lYsaK3IwAu5VMjAA8dOqRnnnlG8fHxkqTg4GAlJSVpw4YN2rBhg6666irdeeedlq+bkpKi5557Trt27ZIkBQQESJL27NmjPXv2aNmyZXrxxRcVFBSU7/mLFy/WxIkTlZmZKUkKDQ3VmTNntHjxYi1btkyPPvqoevToUZy3DAAAAAClzol9p/TS8LeVGJuU73FHlkPT3vpNjiyHbnh6qIfTAUDp4zMjADMyMnT//ffrxIkTql27th577DHVrVtXaWlpmjlzpiZPnizTNPXQQw+pf//+lq791ltvafHixQoNDdVDDz2UM5Jw5cqVevfdd5WUlKQ+ffro0UcfzXPuoUOH9MgjjygzM1Pdu3fXHXfcoaioKMXGxurTTz/VsmXL5O/vr4kTJ6pmzZqX9DEojSMAbeZRBTpmyN9cJZtOS0q/4KgpySjw/w2ZMvM9np/s4xcqrN41GWwy5MjzupJpmsoyHcoyzx81Lzrv/69k/q9euvAXn+b/Xju7MjvDhckkU6ZpSMb/12UnvjB73vdw8UfFzPk/07gwX/4Z/v89XPx8/hl0wRlmARlM05QueCsXX62wDKby/t1d+O6VT4YLr5r95s3/PZFfhvw/L3J/+PL9FLzwUJ7jF13ngizng+R8cP4/mHnBRy3Pf1+U56JYhWbI87zVDBfX558h7384kUH/+8dhJUM+fw+F/PX8//EiM1z8mh7OoPxes4AMBbxiURlyK+j+ePHxwlh7xQIz5PzDdE2G3P+2XZXB2tcoj2XIeQlnXyvvfVP/+0qW732hoKyFXbKolyzwBGfvTReWXvx1Mbuk6K8Tud9L/l8nsq+V39dq5Zx98deq3Ofl9zH//wwXVph5PxVyvc6FXzdzfcSczpD7+4bct/ULMxgXnJb7K7uZK0P+n/W5s1xqhvN/9Xm/XygsQ34f8/zOLyhD9udDQRny+z4o508Xfe924f8X9r3bxelzZci5fsEZcn9pyZ3B2e8fc2f433UvyKALrpaTwVSea1xYfX5J+0u7PxoyZHrk/nixi++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}, "metadata": { "image/png": { @@ -668,7 +785,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 88, "id": "1c395e68-8cf0-43eb-97cd-73bc8920ea89", "metadata": {}, "outputs": [], @@ -702,13 +819,13 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 89, "id": "8208a3c4-edda-476f-b72f-7280925ffffb", "metadata": {}, "outputs": [ { "data": { - "image/png": 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}, "metadata": { "image/png": { @@ -731,6 +848,58 @@ ")+geom_point()" ] }, + { + "cell_type": "code", + "execution_count": 91, + "id": "fa840b8a-3638-4772-9431-d8f0bf97233d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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oAgAAAKCnisViXnnllbS2tmbUqFEZNmzYQJcEUPEcAQgAAEDFW716db773e9m0qRJ2XvvvXPwwQfnHe94R04//fTMmTNnoMsDqGiOAAQAAKCiLV26NKeddlruv//+9R4vFou57bbbctttt2X69On5whe+kEKhMEBVAlQuRwACAABQsYrFYv7u7/5uo/BvQ//6r/+a//zP/9xKVQEMLgJAAAAAKtZvfvObzJ49u0dj/+Vf/iVtbW39XBHA4CMABAAAoGL15qi+BQsW5Pbbb+/HagAGJwEgAAAAFesPf/hDr8Y/8cQT/VQJwOAlAAQAAACAKiYABAAAoGLtsccevRq/55579lMlAIOXABAAAICK9cEPfrDHY9/61rfm6KOP7sdqAAYnASAAAAAVa//99+9xqPfZz342dXV1/VwRwOAjAAQAAKBiFQqFXHXVVTnwwAM3Oe7cc8/Nhz70oa1UFcDgIgAEAACgog0bNiwzZ87MJZdckokTJ5YfLxQKee9735sZM2bkC1/4wgBWCFDZHBsNAABAxRsyZEg+/OEP52//9m+zcOHCtLa2ZtSoUdl+++0HujSAiicABAAAYNAoFArZaaedBroMgEHFKcAAAAAAUMUEgAAAAABQxQSAAAAAAFDFBIAAAAAAUMUEgAAAAABQxQSAAAAAAFDFBIAAAAAAUMUEgAAAAABQxQSAAAAAAFDFBIAAAAAAUMUEgAAAAABQxQSAAAAAAFDFBIAAAAAAUMUEgAAAAABQxQSAAAAAAFDF6ga6gK1t6dKlmTFjRu6777689tprGTJkSMaPH58TTjghhxxyyBbP29bWlptvvjlz587NggULkiS77rprjjrqqEyZMiV1dZt+qf/4xz9m5syZeeSRR7Js2bIMHz48e+21V0455ZS0tLRscV0AAAAAbNu2qQDwueeeywUXXJClS5cmSRobG7NixYo89NBDeeihh3LSSSflox/9aK/nXblyZb74xS9m3rx5SZKGhoYkyVNPPZWnnnoqd955Z7761a9m6NChXa4/d+7cXH755Wlra0uSNDc357XXXsvcuXNz5513Zvr06Zk0adKWPGUAAAAAtnHbTAC4du3afO1rX8vSpUszbty4nHvuuWlpacnq1asza9asXHvttbnpppvS0tKSY489tldzf/vb3868efPS3NycT3/60+UjCe+5555861vfyhNPPJF///d/z/Tp0zda97nnniuHf0cccUTOPvvsjBw5MosXL85VV12VO++8M5dddllaWloyZsyYPnktBquOjo7Mnj07s2bNypNPPplFixalpqYmHR0dqa2tTXt7e2pqalIsFlMoFFIsFpOk/PWG/5bWLRQK683R+d+2trbU1dWV/y1to729vfx95/Gl+Ta37U1ts7SNjo6O8rY2XF5XV7de7Z3H9+T5b/iadX4+G26z8/Pf8HXoapsbbruk87a7en7d1VTaZmn9zjVs+Jp3/rez7n7+bW1t5Tk6v5c2fL6lcRu+9hs+p65q6Oq172pbXb3nuvq5d/Xad34v9+R5b7itTb3nNvy5b/iad7Xtzj//DV+b7p53d5+5zj+jDT/ntbW15W22t7dv9vPe1fPubpub23Zf9Ziunv+GP+9tscds+NnsTY8pFovlOQqFQpc9ZnM/977qMZv6OfdVj+nqM1atPaarn393z3/Dz9CG74vefM57+nnvTY/p7nPeHz1mU6/9QPaYDccNVI+pra0tz73he62r93tP9mO6+7x39fy7e303tS+xpT2mVOOb6TGb+//51ugxxWIxO+20U/bYY4984AMfyMEHH7zRugBsbJsJAG+99da8/PLLGTJkSL70pS9l9OjRSZIhQ4bk1FNPzeLFi/Ozn/0s11xzTSZPnrzZU3ZL5s+fnzvuuCNJcs455+TQQw8tLzv00EPT0dGRSy65JHPmzMkpp5yScePGrbf+tddem7a2trS0tOSzn/1s+RfakSNH5nOf+1wWLFiQ+fPn59prr815553XFy/FoPS73/0uf/d3f5enn356oEsBAAAG0Pz583PPPffkBz/4Qfbbb79cddVV2W233Qa6LICKts3cBGTOnDlJkiOPPLIc/nX2/ve/P4VCIYsXL84jjzzS43nnzp2bYrGYXXbZZb3wr+Swww7LLrvskmKxmLlz5663bMWKFbn//vuTJCeffPJ6R7MkSW1tbU4++eQkyX333ZfW1tYe11VNHnvssZx88snCPwAAYD0PPvhgTjrppLz00ksDXQpARdsmAsCVK1fmySefTJLst99+XY4ZPXp0+RTbhx9+uMdz/+53v0uS7Lvvvl0eel4oFLLvvvuuN7bkscceK1/3r7u6So+vXbs2jz/+eI/rqiaf/exns3z58oEuAwAAqEALFizIV77ylYEuA6CibRMB4AsvvFC+jsiGp+B2Vlr2/PPP92jeYrGYF154YbPzlg5H33De0vc77LBDhg8f3uW6w4cPLy977rnnelRXNXn44YfzwAMPDHQZAABABbvxxhuzcOHCgS4DoGJtE9cAXLx4cfnrkSNHdjuutGzJkiU9mnflypVZtWpVj+dduXJlVq5cmcbGxvW2s6l1S8uXLl262bquueaaXHfddd0uP+2003L66advco6BVlNTU/53xIgR+fWvfz3AFQEAAJVu7dq1eeCBB3LGGWe86bk2/J0Ekj/dfGz48OHlA4xgMPWLbSIALIV0ybqbfnSntGzlypU9mrfzuJ7MW1qnFACW1t/Uur2pa8WKFZv8q1dra+tG1xmsVIVCIbW1tU79BQAAemT58uV9+vtO6XcS6KwU+EBng6FfbBMB4Laiubk5O+64Y7fLm5qa0t7evhUr6r2ampoUCoUUi8V0dHRUfIIOAABUhhEjRvTJ7zsb/k4CybqAp6amJh0dHY4ApKyv+0V/hojbRAA4dOjQ8terV69OU1NTl+NWr16dJOUj9Dan87jSupuad8N1Sl9vat3e1DV16tRMnTq12+WLFi3q8enNA2XEiBGpra1NR0dHlixZkmOOOSYXXnjhQJcFAABUsKamphx88MF98vvOhr+TQLIumBkxYkSWLl1a8QfWsPX0db8YNWpUH1TVtW3i2NXO19jrfD3ADZWW9fSos8bGxnIo15N5O4/vXNem1t2SuqrJO97xjkyePHmgywAAACrYqaee2u2NFQHYRgLAMWPGlC/Yuak76ZaWjR07tkfzFgqFjBkzZovnLX3/+uuvZ9myZV2uu3Tp0ixdujTJn+4mvK3513/91+y8884DXQYAAFCB9txzT2cNAWzGNhEANjY2ZsKECUmSBx98sMsxixYtyvPPP58k2WeffXo897vf/e4kyW9/+9tuxzz00EPrjS155zvfmbq6uk3WVZq3vr4+e+65Z4/rqiZjxozJLbfckiOOOGKgSwEAACpEoVDIiSeemFmzZjn6D2AztolrACbJ5MmTM2/evNxxxx3567/+64wePXq95TfccEOKxWJGjhyZvffeu8fzHnnkkbnhhhuyYMGC3H333Tn00EPXW37XXXdlwYIFKRQKG53K2tTUlAMPPDB33313Zs2alUmTJq13wcf29vbMmjUrSXLQQQd1e+3CbcFuu+2WmTNn5vHHH8+NN96YP/7xj3nxxRczdOjQrF69Og0NDVmzZk2GDBmSNWvWpL6+Pm1tbampqSlfoLV0Yc6ampq0tbWlvr4+a9euTX19fdasWZOGhoasXr06Q4cOzapVq9LY2Fi+a3Pp39bW1jQ1NWXlypXlcZ1rKM3Xedulo09LX3d0dKSurq7bba9cubK8jdK2m5qayttubW0tb7Pz8+287dra2rS3t5drKD3vjo6O1NbWpq2trVzDkCFDys+ju+e94b+rVq0qv+YbPu/Nbbu9vT11dXXln1fpeWyuhlLNq1atKq9XqqG+vr68zY6Oji63XVNTk/b29o1+7pvbdufHO2+79NrX1dWVn3fnbZfecz3Z9obvre5e++5+7nV1deu95pt6vzc0NGz0fFtbW9Pc3JzW1tZNbrv0/Dv/3LvadkmhUOjVa156f3f3vDf8nA8dOrT8+q5evbp8R7Yt+Zx33nZXn/PSNrvrMZ0/52+mx3T1mnfVY9auXZva2trytjd8z22uxzQ2Nm7Uc/qyx7S3t6e2trbcYzp/zrdGjyn9HEvPu6d9rvPz7vyad36fb2mP6cnz3lQNekzPe0xXn7W1a9emubk5K1asSH19fY96TGnbpde+rz7nldhjNvycd9VjutqXGKj9mN70mK5ej849ZujQoWlvb0+hUOiT/ZgNe21X/bynPaa3n/NK7jFd7UNtaY9ZvXp1xo0bl/Hjx+f973//NnuWFEBvbTMB4HHHHZcbb7wxL7/8ci666KJMnz49LS0tWb16dW666abccsstSdbdSKN0VF7J2WefnYULF+boo4/OZz7zmfWWtbS05Mgjj8zcuXNzxRVXpFAo5OCDD06S3HvvvbnyyiuTrAsgu/qf0xlnnJH7778/Tz/9dC699NKcffbZGTFiRJYsWZLvfOc7efrpp1NfX58zzjijH16VwWfPPffcZo+E3JaVLri7ZMkSF9ylrHTB3fb2dhfopky/oCv6Bd3RMwDYVmwzAWB9fX0uvPDCXHDBBXnmmWcybdq0NDU1ZdWqVeVbNZ944ok59thjez333//93+ell17KvHnzcvHFF6ehoSFJsmbNmiTJxIkT84lPfKLLdXfbbbdMmzYtl19+eX71q1/l17/+dZqamrJixYokSV1dXaZNm1a+1iAAAAAA9MY2EwAm68K2K664Ij/5yU9y3333ZdGiRWlubs7b3/72TJkyJYcccsgWzdvY2Jh/+qd/ys0335y5c+dmwYIFSZLx48dn8uTJmTJlykZHFXZ21FFHZezYsbnhhhvy6KOPZtmyZeVTkU855ZS0tLRsUV0AAAAAUChueEEVqtaiRYsGuoTNcooOXXF6Dl3RL+iKfkFX9Au6o2fQFT2DrugXdKWv+8WoUaP6oKqubRN3AQYAAACAbZUAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqpgAEAAAAACqmAAQAAAAAKqYABAAAAAAqlihWCwWB7oIKLnmmmuyYsWKNDc3Z+rUqQNdDlDB9Augp/QLoDf0DKCnBlO/EABSUU444YQsXLgwO+64Y372s58NdDlABdMvgJ7SL4De0DOAnhpM/cIpwAAAAABQxQSAAAAAAFDFBIAAAAAAUMUEgAAAAABQxQSAAAAAAFDFBIAAAAAAUMXqBroA6Oz000/PihUr0tzcPNClABVOvwB6Sr8AekPPAHpqMPWLQrFYLA50EQAAAABA/3AKMAAAAABUMQEgAAAAAFQxASAAAAAAVDEBIAAAAABUMXcBZostXbo0M2bMyH333ZfXXnstQ4YMyfjx43PCCSfkkEMO2eJ529racvPNN2fu3LlZsGBBkmTXXXfNUUcdlSlTpqSubtNv2z/+8Y+ZOXNmHnnkkSxbtizDhw/PXnvtlVNOOSUtLS1bXBew5fq6X7S2tubee+/NQw89lKeeeioLFy5MR0dHRowYkYkTJ+b444/Pu971rm7Xv+yyyzJ79uxNbmO33XbLlVde2evagDenr/vFK6+8ko9+9KObHXfeeefl8MMP73a5/QuoPH3dL84///w8+uijPRp7zDHHZNq0aes9Zv8CKs8bb7yRRx99NE899VSefvrpPPXUU1m6dGmS5Otf/3r23nvvNzX/YMovBIBskeeeey4XXHBB+YPT2NiYFStW5KGHHspDDz2Uk046qUc72xtauXJlvvjFL2bevHlJkoaGhiTJU089laeeeip33nlnvvrVr2bo0KFdrj937txcfvnlaWtrS5I0Nzfntddey9y5c3PnnXdm+vTpmTRp0pY8ZWAL9Ue/mD59el566aXy9w0NDampqcnChQuzcOHC3HHHHfnLv/zL/O3f/u0m52loaEhTU1OXy4YNG9armoA3r7/2L0qGDRuWmpquT4Ap7XN0xf4FVJ7+6Bfbbbdddthhh26Xt7W15Y033kiSjB8/vttx9i+gctx77725/PLL+2XuwZZfCADptbVr1+ZrX/tali5dmnHjxuXcc89NS0tLVq9enVmzZuXaa6/NTTfdlJaWlhx77LG9mvvb3/525s2bl+bm5nz6058u/+Xunnvuybe+9a088cQT+fd///dMnz59o3Wfe+658ofniCOOyNlnn52RI0dm8eLFueqqq3LnnXfmsssuS0tLS8aMGdMnrwWwaf3VL9rb2/O2t70t733ve7P//vtnl112SbFYzIIFC3L11Vfn7rvvzsyZM7Pzzjvn+OOP73aeI444Ip/5zGf64JkCb1Z/7l+U/Mu//Et22mmnXq1j/wIqT3/1i/PPP3+Ty6+//vpcc801qa+vz1FHHdXtOPsXUFlGjBiR8ePH5x3veEfe+ta35tJLL+2TeQdbfuEagPTarbfempdffjlDhgzJl770pfJhqUOGDMmpp55a/mX7mmuuKSfZPTF//vzccccdSZJzzjknhx56aAqFQgqFQg499NB86lOfSpLMmTMnzz777EbrX3vttWlra0tLS0s++9nPZuTIkUmSkSNH5nOf+1xaWlqydu3aXHvttW/q+QM911/94jOf+Uy+9a1v5cQTT8wuu+ySJCkUCtl1111z3nnnlQ/lnzlzZh8/I6C/9Fe/eLPsX0DlGah+8ctf/jJJcuCBB2b77bfvs3mB/jN58uT84Ac/yJe+9KWcfvrpOeCAA/pk3sGYXwgA6bU5c+YkSY488siMHj16o+Xvf//7UygUsnjx4jzyyCM9nnfu3LkpFovZZZddcuihh260/LDDDisf5TN37tz1lq1YsSL3339/kuTkk09ObW3testra2tz8sknJ0nuu+++tLa29rguYMv1V7/Ya6+9ul1WU1OTo48+Okny8ssvl0/VASpbf/WLN8P+BVSmgegXjz/+eF588cUk2eKjkIGtb8P/d/eVwZhfCADplZUrV+bJJ59Mkuy3335djhk9enT5ENWHH364x3P/7ne/S5Lsu+++KRQKGy0vFArZd9991xtb8thjj5X/utddXaXH165dm8cff7zHdQFbpj/7xeZ0vr5Oe3t7n80L9I+B7BebYv8CKs9A9Yvbb789ybqjc0q/kwDbrsGYX7gGIL3ywgsvpFgsJknGjRvX7bhx48bl+eefz/PPP9+jeYvFYl544YXNzrvbbrslyUbzlr7fYYcdMnz48C7XHT58eIYPH56lS5fmueeey/7779+j2oAt01/9oidKd/DbYYcdNnmx7d/97nf52Mc+lldffTUNDQ3ZZZddsv/++2fKlCkZMWJEn9UDbNrW6hf//M//nAULFmT16tUZPnx4dt999xx77LE58MADuxxv/wIqz0DsX6xevTp33nlnknWnE27uiCL7F1DdBmt+4QhAemXx4sXlr0vnqHeltGzJkiU9mnflypVZtWpVj+dduXJlVq5cWX68tJ1NrbsldQFbrr/6xeYsWrQoP//5z5MkxxxzTJd/kes8duHChRk6dGhWrVqVp59+Otdff30+9alPbbUjjICt1y+efPLJFIvF1NTU5LXXXsvdd9+diy66KJdccknWrl270Xj7F1B5BmL/4p577smKFSuSrNu32Bz7F1DdBmt+4QhAeqX0Jk/WXWS3O6Vlnd/km9J5XE/mLa3T2Ni43vqbWndL6gK2XH/1i01pa2vLN7/5zaxcuTI77rhjPvCBD3Q5bvz48dl9991z4IEH5i1veUtqamrS2tqa++67L9///vezePHiXHzxxbn00kuz6667vum6gE3rz37R0NCQE044IZMmTUpLS0uampqSrLv73k9+8pP88pe/zJ133pnm5ubyBbtL7F9A5RmI/Yv/+Z//SZLsvvvuGTt2bLfj7F/AtmGw5heOAASgKhSLxVx55ZV57LHH0tDQkM997nNpbm7ucuxJJ52UE044IaNHj05Nzbr/FTY1NWXy5Mn553/+52y33XZZuXJlfvjDH27NpwD0gxEjRuTjH/943vWud5XDv2TdaTnTp0/PX/zFXyRJbrvttvLpPAAlr776avlGIps7+s/+BVDJBID0ytChQ8tfr169uttxpWWlhHtzOo/rybwbrlP6elPrbkldwJbrr37Rnf/3//5fZs+endra2vzDP/xDJk6cuEXz7LjjjpkyZUqS5IEHHkhHR8ebqgvYvK3dLzo744wz0tDQkGKxWL4jX4n9C6g8W7tf/PKXv0xHR0caGhoyadKkLZ7H/gVUj8GaXwgA6ZXO56h3vv7GhkrLenqR28bGxvKbuifzdh7fua5NrbsldQFbrr/6RVe+973v5ZZbbklNTU3OPffcHHTQQVs8V7LuFJ8kaW1tzfLly9/UXMDmbc1+saGhQ4eWL9L9yiuvdFmX/QuoHFu7X8yePTtJcvDBB2e77bZ7U3PZv4DqMFjzCwEgvTJmzJjyBfWfe+65bseVlm3qGhmdFQqFjBkzZovnLX3/+uuvZ9myZV2uu3Tp0ixdujTJn+7GA/Sf/uoXG7r66qvz05/+NIVCIeecc86b+us8MDC2Vr/oLfsXUHm2Zr947LHHsmDBgiTJscceu8XzANVlsOYXAkB6pbGxMRMmTEiSPPjgg12OWbRoUfm21vvss0+P5373u9+dJPntb3/b7ZiHHnpovbEl73znO1NXV7fJukrz1tfXZ8899+xxXcCW6c9+UXLddddlxowZSZKPf/zjPbozX0/MmzcvybrnsP322/fJnED3tka/6M6qVavKO+g77bTTesvsX0Dl2Zr94vbbb0+SjBo1qk/6jv0LqB6DMb8QANJrkydPTpLccccdefXVVzdafsMNN6RYLGbkyJHZe++9ezzvkUcemUKhkAULFuTuu+/eaPldd92VBQsWpFAolGsoaWpqyoEHHpgkmTVrVtrb29db3t7enlmzZiVJDjrooPUuAg70n/7qF0kyY8aM/OhHP0qSfOQjH8nxxx/fo/WKxeIml7/66qv52c9+liQ54IADyhfxBvpXf/WLzX3mf/jDH2bNmjUpFArlfYkS+xdQmfpz/6Jk9erVufPOO5Mk73nPeza7P2D/ArYtgzG/0HXoteOOOy4777xzVq1alYsuuijz589Psu5/kjNmzMgtt9ySJJk6dWo51S45++yz8773vS+XXXbZRvO2tLTkyCOPTJJcccUVueeee1IsFlMsFnPPPffkyiuvTLLuf/hdHQJ7xhlnpK6uLk8//XQuvfTSLFmyJEmyZMmSXHrppXn66adTX1+fM844o89eC2DT+qtf3Hjjjbn66quTJGeeeWb5Lp49MWfOnHzjG9/IPffcs94h9ytXrszcuXNz3nnnZfny5WlsbMxpp53W26cMbKH+6hfnn39+rr/++syfP3+9Heznnnsul19+eWbOnJkk+V//63+VT+fpzP4FVJ7+6hed3XXXXWltbU2y+bv/JvYvoJItW7as/N8bb7xRfnzFihXrLWtra1tvvWrLL+o2PwTWV19fnwsvvDAXXHBBnnnmmUybNi1NTU1ZtWpV+W5WJ5544hZdJ+Pv//7v89JLL2XevHm5+OKL09DQkCRZs2ZNkmTixIn5xCc+0eW6u+22W6ZNm5bLL788v/rVr/LrX/86TU1NWbFiRZKkrq4u06ZN63LnHugf/dUvvvvd7yZZd/2NWbNmlf9C1pUvfOEL6x0239HRkbvvvrv8l7rGxsbU1dVlxYoV5ZqGDx+ez3/+8/oFbEX91S9effXVXHPNNbnmmmtSW1ubpqamrFmzZr077x111FH52Mc+1uX69i+g8vTn7yMlpZt/7LnnnnnrW9+62fH2L6ByTZ06tcvHL7744vW+//rXv96ro4YHW34hAGSL7Lbbbrniiivyk5/8JPfdd18WLVqU5ubmvP3tb8+UKVNyyCGHbNG8jY2N+ad/+qfcfPPNmTt3bvmiu+PHj8/kyZMzZcqUjf6K19lRRx2VsWPH5oYbbsijjz6aZcuWlQ/9P+WUU9LS0rJFdQFbrj/6Rek0m2KxmNdff32TYzf8S97ee++dqVOn5vHHH8+LL76YZcuWpbW1Nc3NzRk7dmwOOOCAHHfcca7NAwOgP/rFWWedlYcffjhPPvlklixZkuXLl6e2tja77LJLJk6cmGOOOWaja/NsyP4FVJ7++n0kWfeHg0ceeSRJz47+S+xfwLZosOUXheLmLlYAAAAAAAxargEIAAAAAFVMAAgAAAAAVUwACAAAAABVTAAIAAAAAFVMAAgAAAAAVUwACAAAAABVTAAIAAAAAFVMAAgAAAAAVUwACAAAAABVTAAIAAAAAFVMAAgAAAAAVUwACAAAAABVTAAIAAAAAFVMAAgAAAAAVUwACAAAAABVTAAIAAAAAFVMAAgAAAAAVUwACAAAAABVrG6gCwAAgEo0Z86czJkzJ0ly1lln5W1ve9uA1gMAsKUEgAAA0IU5c+bkK1/5SpJk8uTJAkAAYNByCjAAAAAAVDEBIAAAAABUMQEgAAAAAFQxASAAAG/KnDlzUigUUigU8uUvfzlJ8tRTT2XatGnZY4890tzcnJ133jnvfe9784tf/GKj9e+6666cfvrpGT9+fIYOHZqddtopf/VXf5WHH354o7FtbW3ZfvvtUygUcvjhh3db0xlnnFGuaY899uh23Cc/+cnyuN///vdJki9/+cspFArl6/8lyXve857yuNJ/rgkIAAwWAkAAAPrUzJkzs+++++Zb3/pW5s2bl9bW1rzyyiu57bbbctxxx+XrX/96kqRYLOYf//Efc/jhh+eHP/xh/vjHP2b16tVZuHBhZsyYkQMPPDA33XTTenPX1dVl0qRJSZL7778/b7zxRpc1/PKXvyx/PW/evLz44otdjps9e3aSZKeddsq73vWuN/3cAQAqkbsAAwDQZx588MFccsklqa2tzac+9akcdNBBqa2tzZw5c/If//EfaWtry4UXXpjDDz88Dz74YL761a9m3LhxOeusszJx4sSsWLEi119/fX7xi19k7dq1Oeuss/KHP/who0aNKm/j6KOPzn//939n7dq1+dWvfpXjjz9+vRoef/zxvPTSS+s9Nnv27Hzwgx9c77GXXnopTzzxRJJ1R/iV/M3f/E3+7M/+LD/60Y/yX//1X0mSiy66KHvttdd66zc1Nb35FwwAYCsQAAIA0GduuummvO1tb8vs2bPT0tJSfvz000/PEUcckTPPPDNJcs455+TJJ5/MlClT8uMf/ziNjY3lsR/5yEdy5pln5uqrr87ixYvzH//xH/n85z9fXt45rLv99ts3CgBLR/81NjZmjz32yEMPPdRlANj5KMGjjz66/PXEiRMzceLEPPTQQ+XHjjjiiEyePHkLXhEAgIHnFGAAAPrUtddeu174V/KhD30oEyZMSJI8+uijGT58eK677rr1wr+Sr33taykUCkmSn//85+st23fffTNixIgkfzqFt7PSY4cddlg5HOwc9m04Llk/AAQAqDYCQAAA+sx+++2Xww47rNvlnW/c8aEPfSjDhg3rctzYsWMzbty4JMljjz223rKampocddRRSZKHH344ixcvLi8rFouZM2dOknWhXinYe/bZZ/P000+vN08pANxtt90yfvz4njw9AIBBSQAIAECfOeSQQza5fOeddy5/fdBBB/Vo7JIlSzZaVjoNuKOjY72j+x5++OG89tprSZJjjjkmhx9+eBoaGpKsf8Tfs88+m/nz5ydx9B8AUP0EgAAA9Jm3vOUtm1w+ZMiQXo9dvXr1Rss6h3adg71SGDhs2LAccMABaWxsLIeSncc5/RcA2JYIAAEA6DM1NT3fvezN2A3ttdde2XHHHZN0HewdeeSRqa2tTfKngK/zkYICQABgWyIABABgUCrdlfeJJ57IggUL0t7enjvuuCPJ+qFe6etXXnklv//975P8KQycMGFCdt11161YNQDA1icABABgUNrwNOAHHnggy5YtS7Lu+n8lBx98cJqamsrj/vCHP+TFF1/caA4AgGpVN9AFAADAltgwAHzhhReSJKNHj87ee+9dXtbQ0JDDDz88t912W2bPnp36+vou59hQ51OUi8ViX5YOALBVCQABABiUJkyYkDFjxuSFF15YLwCcPHlyCoXCemOPPvro3HbbbZk7d2752oCFQqF8N+GubLfdduWvV6xY0Q/PAABg63AKMAAAg1YpwHv22WfL1/XrfPpvSelIvyVLlmTWrFlJ1t1IZPTo0d3O3dLSUv76wQcf7LOaAQC2NkcAAgAwaB199NH5z//8zyRJW1tb+bEN7b///hk2bFiWLVu2yXGdHXnkkWloaMiaNWvyf/7P/0mS7LPPPhkyZEiSpLGxMUcddVSfPRcAgP4iAAQAYNDa8BTesWPHZsKECRuNq62tzZFHHpmbb765/NjmAsC3vOUt+Yd/+Id87WtfyxtvvJF//Md/XG/5uHHj8swzz2x58QAAW4lTgAEAGLTGjRuXt7/97eXvN3VNv86BX21tbY+O3rvooovy4x//OCeccELe+ta3pqGh4c0VDAAwAApFtzQDAAAAgKrlCEAAAAAAqGICQAAAAACoYgJAAAAAAKhiAkAAAAAAqGICQAAAAACoYgJAAAAAAKhiAkAAAAAAqGICQAAAAACoYgJAAAAAAKhiAkAAAAAAqGICQAAAAACoYgJAAAAAAKhiAkAAAAAAqGICQAAAAACoYgJAAAAAAKhiAkAAAAAAqGICQAAAAACoYgJAAAAAAKhi/x+SoSzdH1zHSAAAAABJRU5ErkJggg==" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "ggplot(\n", + " ppo_mwt_df,\n", + " aes(x='mwt', y='fishing_mortality')\n", + ")+geom_point()" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "id": "cc475799-be54-47ee-bfc0-29a28e440de2", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "ggplot(\n", + " ppo_biomass_df,\n", + " aes(x='biomass', y='fishing_mortality')\n", + ")+geom_point()" + ] + }, { "cell_type": "code", "execution_count": 50, From 814b164f4581faeaa446884e3713e7a918fb51b5 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 30 May 2024 17:52:21 +0000 Subject: [PATCH 58/64] longer tuning, do not store obj fun (unserializable) --- hyperpars/for_results/fixed_policy_UM1.yml | 2 +- hyperpars/for_results/fixed_policy_UM2.yml | 2 +- hyperpars/for_results/fixed_policy_UM3.yml | 2 +- scripts/tune.py | 12 +++++++++--- 4 files changed, 12 insertions(+), 6 deletions(-) diff --git a/hyperpars/for_results/fixed_policy_UM1.yml b/hyperpars/for_results/fixed_policy_UM1.yml index 87ca70e..d5ba727 100644 --- a/hyperpars/for_results/fixed_policy_UM1.yml +++ b/hyperpars/for_results/fixed_policy_UM1.yml @@ -2,6 +2,6 @@ config: upow: 1 harvest_fn_name: "default" n_eval_episodes: 250 -n_calls: 40 +n_calls: 70 id: "UM1" repo_id: "boettiger-lab/rl4eco" \ No newline at end of file diff --git a/hyperpars/for_results/fixed_policy_UM2.yml b/hyperpars/for_results/fixed_policy_UM2.yml index 4b8ff19..30c1faf 100644 --- a/hyperpars/for_results/fixed_policy_UM2.yml +++ b/hyperpars/for_results/fixed_policy_UM2.yml @@ -2,6 +2,6 @@ config: upow: 0.6 harvest_fn_name: "default" n_eval_episodes: 250 -n_calls: 40 +n_calls: 70 id: "UM2" repo_id: "boettiger-lab/rl4eco" \ No newline at end of file diff --git a/hyperpars/for_results/fixed_policy_UM3.yml b/hyperpars/for_results/fixed_policy_UM3.yml index e566562..c9d8b37 100644 --- a/hyperpars/for_results/fixed_policy_UM3.yml +++ b/hyperpars/for_results/fixed_policy_UM3.yml @@ -3,6 +3,6 @@ config: harvest_fn_name: "trophy" n_trophy_ages: 10 n_eval_episodes: 250 -n_calls: 40 +n_calls: 70 id: "UM3" repo_id: "boettiger-lab/rl4eco" \ No newline at end of file diff --git a/scripts/tune.py b/scripts/tune.py index a894bde..16f0a84 100644 --- a/scripts/tune.py +++ b/scripts/tune.py @@ -16,6 +16,12 @@ from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule from rl4fisheries.utils import evaluate_agent +print(f""" + +Working with the input {args.input_file} now... + +""") + with open(args.input_file, "r") as stream: OPTIONS = yaml.safe_load(stream) @@ -132,9 +138,9 @@ def cr_fn(**params): esc_fname = f"esc-{OPTIONS['id']}.pkl" cr_fname = f"cr-{OPTIONS['id']}.pkl" -dump(msy_results, path+msy_fname) -dump(esc_results, path+esc_fname) -dump(cr_results, path+cr_fname) +dump(res=msy_results, filename=path+msy_fname, store_objective=False) +dump(res=esc_results, filename=path+esc_fname, store_objective=False) +dump(res=cr_results, filename=path+cr_fname, store_objective=False) # HF From 1df123da429b67e47c8631a6bb662f5d03175351 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 31 May 2024 19:40:34 +0000 Subject: [PATCH 59/64] New train scripts --- scripts/train.py | 7 ++++++- scripts/train_rl_algos.sh | 16 ++++++++++++---- 2 files changed, 18 insertions(+), 5 deletions(-) diff --git a/scripts/train.py b/scripts/train.py index 9708894..fe04732 100644 --- a/scripts/train.py +++ b/scripts/train.py @@ -13,7 +13,7 @@ # hf login from huggingface_hub import hf_hub_download, HfApi, login -login() +# login() import os @@ -41,3 +41,8 @@ except Exception as ex: print("Couldn't upload to hf :(.") print(ex) + +print(f""" +Finished training on input file {args.file}. + +""") diff --git a/scripts/train_rl_algos.sh b/scripts/train_rl_algos.sh index 85e9c37..fbb2a2f 100644 --- a/scripts/train_rl_algos.sh +++ b/scripts/train_rl_algos.sh @@ -5,12 +5,20 @@ scriptdir="$(dirname "$0")" cd "$scriptdir" # just for good measure, install -pip install -e .. +# pip install -e .. # hf python hf_login.py # train -python train.py -f ../hyperpars/ppo-asm.yml & -python train.py -f ../hyperpars/tqc-asm.yml & -python train.py -f ../hyperpars/rppo-asm.yml & \ No newline at end of file +python train.py -f ../hyperpars/for_results/ppo_both_UM1.yml +python train.py -f ../hyperpars/for_results/ppo_both_UM2.yml +python train.py -f ../hyperpars/for_results/ppo_both_UM3.yml + +python train.py -f ../hyperpars/for_results/ppo_mwt_UM1.yml +python train.py -f ../hyperpars/for_results/ppo_mwt_UM2.yml +python train.py -f ../hyperpars/for_results/ppo_mwt_UM3.yml + +python train.py -f ../hyperpars/for_results/ppo_biomass_UM1.yml +python train.py -f ../hyperpars/for_results/ppo_biomass_UM2.yml +python train.py -f ../hyperpars/for_results/ppo_biomass_UM3.yml From d471608322086bcf93e97697a621d6522cf4ebfc Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 31 May 2024 19:41:08 +0000 Subject: [PATCH 60/64] hyperpars for results --- hyperpars/for_results/ppo_biomass_UM1.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_biomass_UM2.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_biomass_UM3.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_both_UM1.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_both_UM2.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_both_UM3.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_mwt_UM1.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_mwt_UM2.yml | 22 +++++++++++----------- hyperpars/for_results/ppo_mwt_UM3.yml | 22 +++++++++++----------- 9 files changed, 99 insertions(+), 99 deletions(-) diff --git a/hyperpars/for_results/ppo_biomass_UM1.yml b/hyperpars/for_results/ppo_biomass_UM1.yml index f30755a..1eff5ea 100644 --- a/hyperpars/for_results/ppo_biomass_UM1.yml +++ b/hyperpars/for_results/ppo_biomass_UM1.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_biomass_UM2.yml b/hyperpars/for_results/ppo_biomass_UM2.yml index f0847f2..c12e903 100644 --- a/hyperpars/for_results/ppo_biomass_UM2.yml +++ b/hyperpars/for_results/ppo_biomass_UM2.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_biomass_UM3.yml b/hyperpars/for_results/ppo_biomass_UM3.yml index 932e1e2..69b138c 100644 --- a/hyperpars/for_results/ppo_biomass_UM3.yml +++ b/hyperpars/for_results/ppo_biomass_UM3.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_both_UM1.yml b/hyperpars/for_results/ppo_both_UM1.yml index 5ef91f2..4804c19 100644 --- a/hyperpars/for_results/ppo_both_UM1.yml +++ b/hyperpars/for_results/ppo_both_UM1.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_both_UM2.yml b/hyperpars/for_results/ppo_both_UM2.yml index d7ab1a6..4e30968 100644 --- a/hyperpars/for_results/ppo_both_UM2.yml +++ b/hyperpars/for_results/ppo_both_UM2.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_both_UM3.yml b/hyperpars/for_results/ppo_both_UM3.yml index 4f46ed2..3a6ce1e 100644 --- a/hyperpars/for_results/ppo_both_UM3.yml +++ b/hyperpars/for_results/ppo_both_UM3.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_mwt_UM1.yml b/hyperpars/for_results/ppo_mwt_UM1.yml index 1279b3b..0aa6b72 100644 --- a/hyperpars/for_results/ppo_mwt_UM1.yml +++ b/hyperpars/for_results/ppo_mwt_UM1.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_mwt_UM2.yml b/hyperpars/for_results/ppo_mwt_UM2.yml index 8c2f501..e748b0b 100644 --- a/hyperpars/for_results/ppo_mwt_UM2.yml +++ b/hyperpars/for_results/ppo_mwt_UM2.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" diff --git a/hyperpars/for_results/ppo_mwt_UM3.yml b/hyperpars/for_results/ppo_mwt_UM3.yml index 840c266..58cc0da 100644 --- a/hyperpars/for_results/ppo_mwt_UM3.yml +++ b/hyperpars/for_results/ppo_mwt_UM3.yml @@ -1,22 +1,22 @@ # algo algo: "PPO" -total_timesteps: 4000000 +total_timesteps: 8000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' - batch_size: 512 - gamma: 0.9999 - learning_rate: !!float 7.77e-05 - ent_coef: 0.00429 - clip_range: 0.1 - gae_lambda: 0.9 - max_grad_norm: 5 - vf_coef: 0.19 + # batch_size: 512 + # gamma: 0.9999 + # learning_rate: !!float 7.77e-05 + # ent_coef: 0.00429 + # clip_range: 0.1 + # gae_lambda: 0.9 + # max_grad_norm: 5 + # vf_coef: 0.19 # policy_kwargs: "dict(log_std_init=-3.29, ortho_init=False, net_arch=[256, 128])" - policy_kwargs: "dict(net_arch=[256, 128])" + # policy_kwargs: "dict(net_arch=[256, 128])" use_sde: True - clip_range: 0.1 + # clip_range: 0.1 # env env_id: "AsmEnv" From 3a54646d1b579205363b5d4519277b4db97336ff Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Fri, 31 May 2024 19:41:58 +0000 Subject: [PATCH 61/64] New sb3 train util with checkpoint saving --- src/rl4fisheries/utils/sb3.py | 83 ++++++++++++++++++++++++++++++++++- 1 file changed, 82 insertions(+), 1 deletion(-) diff --git a/src/rl4fisheries/utils/sb3.py b/src/rl4fisheries/utils/sb3.py index be59ed1..9ff7bd9 100644 --- a/src/rl4fisheries/utils/sb3.py +++ b/src/rl4fisheries/utils/sb3.py @@ -118,4 +118,85 @@ def sb3_train(config_file, **kwargs): model.save(save_id) print(f"Saved {options['algo']} model at {save_id}") - return save_id, options \ No newline at end of file + return save_id, options + + +def sb3_train_save_checkpoints(config_file, checkpoint_freq=500_000, checkpoint_start=4_000_000): + with open(config_file, "r") as stream: + options = yaml.safe_load(stream) + options = {**options, **kwargs} + + if 'additional_imports' in options: + import importlib + for module in options['additional_imports']: + print(f"importing {module}") + module = importlib.import_module(module) + globals()[module.__name__] = module + + if "n_envs" in options: + env = make_vec_env( + options["env_id"], options["n_envs"], env_kwargs={"config": options["config"]} + ) + else: + env = gym.make(options["env_id"]) + + if ( + 'policy_kwargs' in options['algo_config'] and + isinstance(options['algo_config']['policy_kwargs'], str) + ): + options['algo_config']['policy_kwargs'] = eval(options['algo_config']['policy_kwargs']) + + ALGO = algorithm(options["algo"]) + if "id" in options: + options["id"] = "-" + options["id"] + model_id = options["algo"] + "-" + options["env_id"] + options.get("id", "") + save_id = os.path.join(options["save_path"], model_id) + + model = ALGO( + env=env, + **options['algo_config'] + ) + + progress_bar = options.get("progress_bar", False) + + # + ## TRAINING + model.learn( + total_timesteps=min(options["total_timesteps"], checkpoint_start), + tb_log_name=model_id, + progress_bar=progress_bar, + ) + model.save(save_id+"chkpnt1.zip") + print(f"Saved {options['algo']} checkpoint at {save_id+'-chkpnt1.zip'}") + if options["total_timesteps"]<=checkpoint_start: + return save_id+'-chkpnt1.zip', options + # + timesteps_now = checkpoint_start + i = 1 + while True: + i+=1 + model.learn( + total_timesteps=checkpoint_freq, + tb_log_name=model_id, + progress_bar=progress_bar, + ) + model.save(save_id+f"-chkpnt{i}.zip") + print(f"now ...-chkpnt{i}.zip") + timesteps_now += checkpoint_freq + if timesteps_now >= options["total_timesteps"]: + return save_id + f"-chkpnt{i}.zip", options + + + + + + + + + + + + + + + \ No newline at end of file From 9a6b2878b4b43b32c4e19edf8a235bb5384e9066 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 6 Jun 2024 00:21:45 +0000 Subject: [PATCH 62/64] added results/figures notebooks --- hyperpars/for_results/ppo_biomass_UM1.yml | 7 +- hyperpars/for_results/ppo_biomass_UM2.yml | 7 +- hyperpars/for_results/ppo_biomass_UM3.yml | 7 +- hyperpars/for_results/ppo_both_UM1.yml | 7 +- hyperpars/for_results/ppo_both_UM2.yml | 7 +- hyperpars/for_results/ppo_both_UM3.yml | 7 +- hyperpars/for_results/ppo_mwt_UM1.yml | 7 +- hyperpars/for_results/ppo_mwt_UM2.yml | 7 +- hyperpars/for_results/ppo_mwt_UM3.yml | 7 +- notebooks/for_results/0_tests.ipynb | 115 ++ notebooks/for_results/1_fp_skopt.ipynb | 436 ++++++++ notebooks/for_results/2_reward_distr.ipynb | 964 +++++++++++++++++ notebooks/for_results/3_policy_plots.ipynb | 1048 +++++++++++++++++++ notebooks/for_results/4_episode_plots.ipynb | 842 +++++++++++++++ scripts/train.py | 4 +- scripts/train_rl_algos.sh | 12 +- src/rl4fisheries/utils/__init__.py | 2 +- src/rl4fisheries/utils/sb3.py | 4 +- src/rl4fisheries/utils/simulation.py | 2 +- 19 files changed, 3462 insertions(+), 30 deletions(-) create mode 100644 notebooks/for_results/0_tests.ipynb create mode 100644 notebooks/for_results/1_fp_skopt.ipynb create mode 100644 notebooks/for_results/2_reward_distr.ipynb create mode 100644 notebooks/for_results/3_policy_plots.ipynb create mode 100644 notebooks/for_results/4_episode_plots.ipynb diff --git a/hyperpars/for_results/ppo_biomass_UM1.yml b/hyperpars/for_results/ppo_biomass_UM1.yml index 1eff5ea..b80fc3e 100644 --- a/hyperpars/for_results/ppo_biomass_UM1.yml +++ b/hyperpars/for_results/ppo_biomass_UM1.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -33,6 +36,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "biomass-UM1" +id: "biomass-UM1-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_biomass_UM2.yml b/hyperpars/for_results/ppo_biomass_UM2.yml index c12e903..5fdb7ad 100644 --- a/hyperpars/for_results/ppo_biomass_UM2.yml +++ b/hyperpars/for_results/ppo_biomass_UM2.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -33,6 +36,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "biomass-UM2" +id: "biomass-UM2-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_biomass_UM3.yml b/hyperpars/for_results/ppo_biomass_UM3.yml index 69b138c..af1dd26 100644 --- a/hyperpars/for_results/ppo_biomass_UM3.yml +++ b/hyperpars/for_results/ppo_biomass_UM3.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -34,6 +37,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "biomass-UM3" +id: "biomass-UM3-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_both_UM1.yml b/hyperpars/for_results/ppo_both_UM1.yml index 4804c19..7c14abc 100644 --- a/hyperpars/for_results/ppo_both_UM1.yml +++ b/hyperpars/for_results/ppo_both_UM1.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -33,6 +36,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "2obs-UM1" +id: "2obs-UM1-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_both_UM2.yml b/hyperpars/for_results/ppo_both_UM2.yml index 4e30968..ed0f97b 100644 --- a/hyperpars/for_results/ppo_both_UM2.yml +++ b/hyperpars/for_results/ppo_both_UM2.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -33,6 +36,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "2obs-UM2" +id: "2obs-UM2-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_both_UM3.yml b/hyperpars/for_results/ppo_both_UM3.yml index 3a6ce1e..df35a06 100644 --- a/hyperpars/for_results/ppo_both_UM3.yml +++ b/hyperpars/for_results/ppo_both_UM3.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -34,6 +37,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "2obs-UM1" +id: "2obs-UM3-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_mwt_UM1.yml b/hyperpars/for_results/ppo_mwt_UM1.yml index 0aa6b72..8d73c8e 100644 --- a/hyperpars/for_results/ppo_mwt_UM1.yml +++ b/hyperpars/for_results/ppo_mwt_UM1.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -33,6 +36,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "mwt-UM1" +id: "mwt-UM1-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_mwt_UM2.yml b/hyperpars/for_results/ppo_mwt_UM2.yml index e748b0b..4ba5383 100644 --- a/hyperpars/for_results/ppo_mwt_UM2.yml +++ b/hyperpars/for_results/ppo_mwt_UM2.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -33,6 +36,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "mwt-UM2" +id: "mwt-UM2-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/hyperpars/for_results/ppo_mwt_UM3.yml b/hyperpars/for_results/ppo_mwt_UM3.yml index 58cc0da..078bdb4 100644 --- a/hyperpars/for_results/ppo_mwt_UM3.yml +++ b/hyperpars/for_results/ppo_mwt_UM3.yml @@ -1,10 +1,13 @@ # algo algo: "PPO" -total_timesteps: 8000000 +total_timesteps: 6000000 algo_config: tensorboard_log: "../../../logs" # policy: 'MlpPolicy' + # learning_rate: 0.00015 + policy_kwargs: "dict(net_arch=[64, 32, 16])" + # # batch_size: 512 # gamma: 0.9999 # learning_rate: !!float 7.77e-05 @@ -34,6 +37,6 @@ repo: "cboettig/rl-ecology" save_path: "../saved_agents/results/" # misc -id: "mwt-UM3" +id: "mwt-UM3-64-32-16" # id: "short-test" additional_imports: ["torch"] \ No newline at end of file diff --git a/notebooks/for_results/0_tests.ipynb b/notebooks/for_results/0_tests.ipynb new file mode 100644 index 0000000..5724ca2 --- /dev/null +++ b/notebooks/for_results/0_tests.ipynb @@ -0,0 +1,115 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "24dc16ef-5d68-4a20-be9f-7ed9f97f3c0b", + "metadata": {}, + "source": [ + "# Testing several parts of our algos\n", + "---\n", + "## 1. default network architectures\n", + "\n", + "For each problem shape, what is the default network architecture used by PPO?" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "86470282-d84b-49ff-a7e9-5647580b3d65", + "metadata": {}, + "outputs": [], + "source": [ + "from rl4fisheries import AsmEnv\n", + "import yaml\n", + "from stable_baselines3 import PPO" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "2c293e58-45b2-41e1-881b-a85d9230aba0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "ActorCriticPolicy(\n", + " (features_extractor): FlattenExtractor(\n", + " (flatten): Flatten(start_dim=1, end_dim=-1)\n", + " )\n", + " (pi_features_extractor): FlattenExtractor(\n", + " (flatten): Flatten(start_dim=1, end_dim=-1)\n", + " )\n", + " (vf_features_extractor): FlattenExtractor(\n", + " (flatten): Flatten(start_dim=1, end_dim=-1)\n", + " )\n", + " (mlp_extractor): MlpExtractor(\n", + " (policy_net): Sequential(\n", + " (0): Linear(in_features=2, out_features=64, bias=True)\n", + " (1): Tanh()\n", + " (2): Linear(in_features=64, out_features=64, bias=True)\n", + " (3): Tanh()\n", + " )\n", + " (value_net): Sequential(\n", + " (0): Linear(in_features=2, out_features=64, bias=True)\n", + " (1): Tanh()\n", + " (2): Linear(in_features=64, out_features=64, bias=True)\n", + " (3): Tanh()\n", + " )\n", + " )\n", + " (action_net): Linear(in_features=64, out_features=1, bias=True)\n", + " (value_net): Linear(in_features=64, out_features=1, bias=True)\n", + ")" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "with open('../../hyperpars/for_results/ppo_both_UM2.yml') as stream:\n", + " options = yaml.safe_load(stream)\n", + "\n", + "PPO(env=AsmEnv(config=options['config']),**options['algo_config']).policy" + ] + }, + { + "cell_type": "markdown", + "id": "79d44b0b-25bf-4fe7-8ad1-c9e2ba181e54", + "metadata": {}, + "source": [ + "They all seem to be of the form $\\{in\\}\\rightarrow 64\\rightarrow 64 \\rightarrow\\{out\\}$ by default." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8fc31253-c12b-4777-abcb-2344477475ef", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/for_results/1_fp_skopt.ipynb b/notebooks/for_results/1_fp_skopt.ipynb new file mode 100644 index 0000000..e215346 --- /dev/null +++ b/notebooks/for_results/1_fp_skopt.ipynb @@ -0,0 +1,436 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "841b7cca-025c-4896-8922-8c36168b28e3", + "metadata": {}, + "source": [ + "# Fixed policy optimization visuals" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "f3f87a78-110b-4ea5-92f6-fb3416477b11", + "metadata": {}, + "outputs": [], + "source": [ + "from skopt import load\n", + "from huggingface_hub import hf_hub_download\n" + ] + }, + { + "cell_type": "markdown", + "id": "a29b54e8-e386-4895-bf3f-efde3f30ade4", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Load" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2a558950-0a18-4143-8fa9-0096a577af0b", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e85cb195fee9419db65ca164379104fb", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "cr-UM2.pkl: 0%| | 0.00/2.20M [00:00, , )" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " plot_objective(cr_UM1),\n", + " plot_objective(cr_UM2),\n", + " plot_objective(cr_UM3),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "2cbb305f-91be-424f-8ed8-acf69531aa96", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(, , )" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(\n", + " plot_objective(msy_UM1),\n", + " plot_objective(msy_UM2),\n", + " plot_objective(msy_UM3),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "91243b31-a1a9-4c65-820d-0f96d8fea4cc", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/for_results/2_reward_distr.ipynb b/notebooks/for_results/2_reward_distr.ipynb new file mode 100644 index 0000000..b71230d --- /dev/null +++ b/notebooks/for_results/2_reward_distr.ipynb @@ -0,0 +1,964 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "79c85ba8-af0c-4e50-8576-f6e4867b7b32", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "id": "2b1fef36-1981-4209-a418-85b7672be424", + "metadata": {}, + "source": [ + "# Reward distributions" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0e5ee484-d06a-44ef-b263-6488207bc9b0", + "metadata": {}, + "outputs": [], + "source": [ + "from huggingface_hub import hf_hub_download, HfApi\n", + "from plotnine import ggplot, aes, geom_density\n", + "from skopt import load\n", + "from stable_baselines3 import PPO\n", + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.utils import evaluate_agent\n", + "from rl4fisheries.envs.asm_fns import get_r_devs\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import ray" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3f64a2e-c60f-4c55-9b95-f7071b24f82b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "7fc4fa4a-95d8-452c-beb9-d01b9578e764", + "metadata": { + "jupyter": { + "source_hidden": true + } + }, + "outputs": [], + "source": [ + "## UM1\n", + "\n", + "CFG_UM1_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "CFG_UM1_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "CFG_UM1_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "\n", + "## UM2\n", + "\n", + "CFG_UM2_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "CFG_UM2_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "CFG_UM2_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "\n", + "## UM3\n", + "\n", + "CFG_UM3_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}\n", + "CFG_UM3_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}\n", + "CFG_UM3_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "e47f7d71-7186-45fd-a019-8ab3019fbae2", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Load" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "b2ad8d67-5113-4747-bd0f-28111e1ee572", + "metadata": {}, + "outputs": [], + "source": [ + "cr_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM1.pkl\")\n", + "cr_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM2.pkl\")\n", + "cr_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM3.pkl\")\n", + "\n", + "esc_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM1.pkl\")\n", + "esc_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM2.pkl\")\n", + "esc_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM3.pkl\")\n", + "\n", + "msy_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM1.pkl\")\n", + "msy_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM2.pkl\")\n", + "msy_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM3.pkl\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "89f24e34-7302-4d8f-afca-4671d55355b7", + "metadata": {}, + "outputs": [], + "source": [ + "cr_UM1 = load(cr_UM1_file)\n", + "cr_UM2 = load(cr_UM2_file)\n", + "cr_UM3 = load(cr_UM3_file)\n", + "\n", + "esc_UM1 = load(esc_UM1_file)\n", + "esc_UM2 = load(esc_UM2_file)\n", + "esc_UM3 = load(esc_UM3_file)\n", + "\n", + "msy_UM1 = load(msy_UM1_file)\n", + "msy_UM2 = load(msy_UM2_file)\n", + "msy_UM3 = load(msy_UM3_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2146eba9-ad8e-4e4b-90fc-84bc650f3477", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2017439f0195413e8026e831d4b9b334", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "(…)PPO-AsmEnv-2obs-UM1-64-32-16-chkpnt3.zip: 0%| | 0.00/106k [00:00,
)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(fixed_pol_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + " ggplot(ppo_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "74d6f109-7365-4731-8f8b-e001662461e9", + "metadata": {}, + "source": [ + "### UM2" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "17233ba3-9669-4f49-8fdc-66ce612e75c1", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-06-05 20:47:42,007\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:47:57,485\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:48:13,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + } + ], + "source": [ + "PPO_2o_rews = get_rews(\n", + " agent=PPO_2o_UM2,\n", + " env=AsmEnv(config=CFG_UM2_2o),\n", + " agent_name='PPO_2o',\n", + ")\n", + "\n", + "PPO_mw_rews = get_rews(\n", + " agent=PPO_mw_UM2,\n", + " env=AsmEnv(config=CFG_UM2_mw),\n", + " agent_name='PPO_mw',\n", + ")\n", + "\n", + "PPO_bm_rews = get_rews(\n", + " agent=PPO_bm_UM2,\n", + " env=AsmEnv(config=CFG_UM2_bm),\n", + " agent_name='PPO_bm',\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "28b79920-2de2-4a7b-ac9f-a4dcf5c86b09", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-06-05 20:48:34,047\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:48:41,952\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:48:49,682\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + } + ], + "source": [ + "CR_rews = get_rews(\n", + " agent=CautionaryRule(\n", + " env=AsmEnv(config=CFG_UM2_bm),\n", + " **(from_radius_theta(*cr_UM2.x)),\n", + " ),\n", + " env=AsmEnv(config=CFG_UM2_bm),\n", + " agent_name='CR',\n", + ")\n", + "\n", + "Esc_rews = get_rews(\n", + " agent=ConstEsc(\n", + " escapement=esc_UM2.x[0],\n", + " env=AsmEnv(config=CFG_UM2_bm),\n", + " ),\n", + " agent_name='Esc',\n", + " env=AsmEnv(config=CFG_UM2_bm),\n", + ")\n", + "\n", + "Msy_rews = get_rews(\n", + " agent=Msy(\n", + " mortality=msy_UM2.x[0],\n", + " env=AsmEnv(config=CFG_UM2_bm),\n", + " ),\n", + " agent_name='Msy',\n", + " env=AsmEnv(config=CFG_UM2_bm),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "d66f1288-cb48-4a4f-971e-3b47226cbf32", + "metadata": {}, + "outputs": [], + "source": [ + "fixed_pol_df = pd.concat(\n", + " [\n", + " pd.DataFrame(CR_rews),\n", + " pd.DataFrame(Esc_rews),\n", + " pd.DataFrame(Msy_rews),\n", + " ]\n", + ")\n", + "ppo_df = pd.concat(\n", + " [\n", + " pd.DataFrame(PPO_2o_rews),\n", + " pd.DataFrame(PPO_mw_rews),\n", + " pd.DataFrame(PPO_bm_rews),\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "467b094f-1948-4a0e-af8b-dd437adc8fe4", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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gAATgt7Zv3+56nJLSxFyQ89CgQbLS01tKogAEAAAAAHgHBSAAv7Vt2zbX49SGWeaCnCfrHMAlS5aotLTUcBoAAAAAQKCjAATgt6wC0GazKTk503Ca2rO2ARcXF+uHH34wnAYAAAAAEOgoAAH4LasATIhPU2houOE0tdeqZS/Z7UGSpLlz5xpOAwAAAAAIdBSAAPyWVQCmpGSZDXKeIiKildO0kyRp/vz5ZsMAAAAAAAIeBSAAv+UqABv6xwCQ6tq1dZ4DuHz5ch09etRwGgAAAABAIKMABOCXiouLtWfPHkn+twJQktqeGARSVVWlRYsWGU4DAAAAAAhkFIAA/NLOnTtdj1P8aAKwpVlOZ4WFRkjiHEAAAAAAgGdRAALwS9b2X8k/VwAGB4eqZcuekjgHEAAAAADgWRSAAPxS9QKwoR+eAShJ7U5sA96wYYPy8vIMpwEAAAAABCoKQAB+ySoA4+IaKjws0nCaC9O2TV/XY1YBAgAAAAA8hQIQgF86OQE4y2yQOsjIaK2YmARJnAMIAAAAAPAcCkAAfskqAP11+68k2e12tWndR5JzBaDD4TCcCAAAAAAQiCgAAfidsrIy7dq1S5KU6scrAKWT5wDu3btXW7ZsMZwGAAAAABCIKAAB+J1du3apqqpKkpSS4r8rAKVTzwGcN2+ewSQAAAAAgEBFAQjA72zdutX12J+3AEvO/MnJGZIoAAEAAAAAnkEBCMDv7Nixw/U4xc8LQElq29q5CnDBggWqrKw0nAYAAAAAEGgoAAH4Hev8v8iIWEVFxZkN4wbt2jrPASwoKNBPP/1kOA0AAAAAINBQAALwO9YKQGvrrL9r0/rkOYBz5841mAQAAAAAEIgoAAH4nZ07d0qSkpLSDSdxj9jYRGVmtJEkzZ8/33AaAAAAAECgoQAE4HesAjBQVgBKJ6cBL1myRCUlJYbTAAAAAAACCQUgAL9SUFCggoICSVLDpMApAK1zAEtKSrR06VLDaQAAAAAAgYQCEIBfsVb/SYG1ArBlix4KCgqWxDmAAAAAAAD3ogAE4FcCtQAMD49Ss5wukjgHEAAAAADgXhSAAPxK9QIwKTEwhoBYrHMAV6xY4drmDAAAAABAXVEAAvArO3bskCTFxiQqPDzKcBr3ss4BrKqq0sKFCw2nAQAAAAAECgpAAH5l165dkgJr+6+laXYnV6nJOYAAAAAAAHehAATgV6wtwMkBNAHYEhwcolYte0riHEAAAAAAgPtQAALwGw6H42QBGIArACWpbRvnNuBNmzYpNzfXcBoAAAAAQCCgAATgN/Lz81VUVCQpcAvAdicKQEmaN2+ewSQAAAAAgEBBAQjAb1jn/0mBuQVYktLTWyo2NkkSBSAAAAAAwD0oAAH4DWsCsBS4BaDNZlPbNn0lOQtAh8NhOBEAAAAAwN9RAALwG9b5fzabTYmJjQyn8Zy2rZ0FYF5enjZt2mQ4DQAAAADA31EAAvAbVgEYH5+qkJAww2k8x1oBKElz5swxFwQAAAAAEBAoAAH4DdcE4ADd/mtJTs5QampTSdLMmTMNpwEAAAAA+DsKQAB+42QBmG44ied1bD9QkrRo0SIVFxebDQMAAAAA8GsUgAD8QlVVlXbv3i3JuUIu0HXsMEiSVFJSooULFxpOAwAAAADwZxSAAPxCXl6eysrKJEnJSZmG03heq5Y9FRoaLoltwAAAAACAuqEABOAXduzY4XpcH1YAhoaGq3WrPpIoAAEAAAAAdUMBCMAv7Nq1y/W4PhSAktSxw0BJ0rZt27RlyxazYQAAAAAAfosCEIBfsAaABAUFKyE+1XAa7+h04hxAiVWAAAAAAIALRwEIwC9YBWBiQiPZ7UGG03hHw4ZNlJraVBIFIAAAAADgwlEAAvAL1gTgpKR0w0m8q2P7gZKkRYsWqbi42GwYAAAAAIBfogAE4BesAjAxsbHhJN7V8cQ24JKSEi1cuNBwGgAAAACAP6IABODzqqqqtGfPHklSUmIjw2m8q1XLngoNDZckffvtt4bTAAAAAAD8EQUgAJ934MABlZWVSZKSEuvXFuDQ0HC1ad1HkrMAdDgchhMBAAAAAPwNBSAAn2dt/5WkxHq2AlCSOncaKknasWOH1q9fbzgNAAAAAMDfUAAC8HnVC8D6tgJQOlkAStJ///tfg0kAAAAAAP6IAhCAz6teACYkpBlMYkZCfKqys9pLkmbMmGE4DQAAAADA31AAAvB5VgEYG5vkGohR33TpPEyStGzZMu3fv99wGgAAAACAP6EABODzrAIwKbGx4STmdOnkLAAdDoe++eYbw2kAAAAAAP6EAhCAz7MKwPo4AMSSmdlGiQnOP//XX39tOA0AAAAAwJ9QAALweSdXANa/ASAWm83mGgYyZ84cFRcXG04EAAAAAPAXFIAAfNrx48d15MgRSfV7BaB08hzA4uJizZ8/33AaAAAAAIC/oAAE4NOqTwCuzysAJal1q14KD4+SxDZgAAAAAEDtUQAC8GnVC8D6vgIwJCRM7dv1l+QsAKuqqgwnAgAAAAD4AwpAAD5tz549rsdJSfV7BaB0chvwvn37tHz5csNpAAAAAAD+gAIQgE/btWuXJCksNELRUXFmw/iAzh2HKigoWJL0xRdfGE4DAAAAAPAHFIAAfJq1AjAxsbFsNpvhNOZFR8epdavekqTp06fL4XAYTgQAAAAA8HUUgAB8mrUCMDGxseEkvqN7t1GSpO3bt2vNmjWG0wAAAAAAfB0FIACfZq0ATKrnA0Cq69p5uGs1JNuAAQAAAADnQgEIwGdVVFQoNzdXkpSUyAAQS1xcQzVv3k0SBSAAAAAA4NwoAAH4rLy8PFVWVkqSElkBeIoeXZ3bgNetW6ctW7YYTgMAAAAA8GUUgAB8lnX+nyQlJbECsLpuXUe6Hk+fPt1gEgAAAACAr6MABOCzrPP/JCkxgRWA1SUlpSs7q70ktgEDAAAAAM6OAhCAz7JWANpsdsXHpxpO43u6ndgG/OOPP2r37t2G0wAAAAAAfBUFIACfZa0AjI9PUXBwiOE0vqd7t1Gux6wCBAAAAADUhAIQgM+yVrUlJTY2nMQ3NUrLUeNGzSVxDiAAAAAAoGYUgAB8llUAJlIA1sjaBrxkyRLt37/fcBoAAAAAgC+iAATgkxwOx8kCkAEgNerezTkN2OFw6KuvvjKcBgAAAADgiygAAfikY8eOqbCwUBIF4Nk0yWyr5OQMSWwDBgAAAACcGQUgAJ9kDQCRpISENINJfJvNZlOPbhdLkubPn69Dhw4ZTgQAAAAA8DUUgAB80t69e12PKQDPrvuJArCyslL//e9/DacBAAAAAPgaCkAAPokCsPaaZnd0fY7YBgwAAAAA+DkKQAA+ySoAg4NDFRuTaDiNb7Pb7erW1TkMZO7cuTp27JjhRAAAAAAAX0IBCMAnWWcAJsSnymazGU7j+6xzAMvKyjRjxgzDaQAAAAAAvoQCEIBPys3NlSQlMAG4Vlo076bY2CRJ0ueff244DQAAAADAl1AAAvBJrhWAnP9XK3Z7kLp1GSFJmjVrlgoLCw0nAgAAAAD4CgpAAD7H4XC4CsBECsBa69HduQ24uLhYs2bNMpwGAAAAAOArKAAB+JyjR4+qqKhIkpQQTwFYW61a9lJ0VJwktgEDAAAAAE4KNh3AmwoKCjR58mR9//33OnjwoMLCwpSTk6OLL75YvXr1uuDrVlRUaPr06Zo7d65rcmnjxo01YMAAXXLJJQoOPvOned++fVq7dq02b96sLVu2aOvWrSopKZEkffbZZ2d9z3379unOO+88Z7Y///nP6tu373n+iQCzrP+OJCkhkQKwtoKDQ9Sly3DNmz9JM2bMUElJicLDw03HAgAAAAAYVm8KwJ07d+qRRx5RQUGBJCkiIkKFhYVasWKFVqxYocsuu6xWhdrPFRcX67HHHtPGjRslSaGhoZKkzZs3a/PmzVq4cKGeeuqpM/4l/IMPPnDLNr3Y2FjZ7WdezGnlAfyJtf1XYgXg+eredZTmzZ+kwsJCzZ07VyNGjDAdCQAAAABgWL0oAMvLy/XMM8+ooKBATZo00QMPPKDs7GyVlpZq2rRpeu+99/T5558rOztbQ4cOPa9rv/LKK9q4caOioqL0+9//3rWScPHixfr3v/+t9evX69VXX9X9999/2mttNpvS0tLUrFkz5eTkqLi4WB999NF5//lefPFFpaSknPfrAF9lTQCWpESmAJ+Xdm37KSIiRsXFx/T5559TAAIAAAAA6kcB+PXXXysvL09hYWF6/PHHlZycLEkKCwvTtddeq0OHDunLL7/UxIkTNXDgwBq37P7ctm3bNG/ePEnS7373O/Xu3dv1sd69e6uqqkrPP/+85syZo9GjR6tJkyanvP7ee+9VUFCQ658XL15c1z8qEBCsFYAhwWGKiUkwnMa/hISEqXPHIVq0eKq+/vprlZeXKyQkxHQsAAAAAIBB9WIIyJw5cyRJ/fv3d5V/1V199dWy2Ww6dOiQfvrpp1pfd+7cuXI4HEpLSzul/LP06dNHaWlpcjgcmjt37mkfr17+ATjJOgMwPiFVNpvNcBr/073bKEnSkSNHtGDBAsNpAAAAAACmBXwBWFxcrE2bNkmSunTpcsbnJCcnKz09XZK0cuXKWl971apVkqTOnTufsaSw2Wzq3LnzKc8FcG5WAcj5fxemQ/uBCguNkCRNnz7dcBoAAAAAgGkBvwV49+7dcjgcknTaFtzqmjRpol27dmnXrl21uq7D4dDu3bvPed3MzExJqvV1L8QLL7ygvXv3qrS0VA0aNFCLFi00dOhQde/e3WPvCXiSVQAmJlAAXoiwsAh17DBI3//wpb788ku98MILrDgGAAAAgHos4AvAQ4cOuR4nJNR8lpj1scOHD9fqusXFxSopKan1dYuLi1VcXKyIiIhaXf98bNq0SZGRkbLb7Tp48KC+++47fffdd+rbt68eeOCBWp3/NXHiRL3//vs1fvyGG27QjTfe6M7YdWJNPbbb7YqPjzecxv9ZK1gbNGjgKsxNcTgcrgKwYcMMj/w342nW59NmsxnL37fPlfr+hy+Vn5+v1atXa+DAgUZyuIMv3Z+BgK+f7sX96V7cn+7F/ele3J/uxf3pXtyfAM4l4AtAq6STnEM/amJ9rLi4uFbXrf682lzXeo27yoDQ0FBdfPHFuuiii5Sdna3IyEhJ0s6dOzVlyhTNnj1bCxcuVFRUlO69995zXq+wsFD79++v8eNFRUU+uYLIZrP5ZC5/ZX3jYNKRI0dUWFgoSUpKSvf7MwBN5e/WdZhCQsJUXl6qqVOnasiQIUZyuJMv3J+BhK+f7sX96V7cn+7F/ele3J/uxf3pXtyfAGoS8AVgoIqPj9fdd9992u9nZmbq/vvvV2xsrKZNm6ZvvvlGV155peuMw5pERUWpYcOGNX48MjJSlZWVdc7tLna7XTabTQ6HQ1VVVabj+D2bzSa73a6qqirjP4Hdvn2763FiQprxPBeieulnKn94eLQ6dhioH5Z9rU8++UT/+Mc//PYbbF+6PwMBXz/di/vTvbg/3Yv70724P92L+9O9AvX+pMwE3CfgC8Dw8HDX49LSUtdKuZ8rLS2VpFqv0Kv+POu1Z7vu+VzbHW666SZ99dVXKisr09KlS89ZAN588826+eaba/x4fn5+rbdHe0N8fLyCgoJUVVXlU7n8VVBQkOLj41VQUGC86F2/fr3rcXR0Yq1X5fqSiIgI1zdgJvN36TxcPyz7Wnv37tW3337rt+eC+tL9GQj4+ule3J/uxf3pXtyf7sX96V7cn+4VqPdnUlKS6QhAwPDP5SDnofr5fNXPA/w562O1PS8hIiLCVejV5rrVn+8N4eHhrgEk+/bt89r7AnVlnf8nMQW4rrp2HqagIOfPeZgGDAAAAAD1V8AXgOnpJ88Q27lzZ43Psz6WkZFRq+vabDbXqjp3Xheo76wCMCQ4TDExNQ/YwblFRcWpdavekqQZM2YYTgMAAAAAMCXgC8CIiAg1b95ckrR8+fIzPic/P1+7du2SJHXs2LHW1+7QoYMk6ccff6zxOStWrDjlud5SUlLiKh9TUlK8+t5AXezZs0eSFJ+Q6vcDQHxB507O4R+bN2/Wli1bDKcBAAAAAJgQ8AWgJA0cOFCSNG/ePB04cOC0j3/yySdyOBxKSEhQ+/bta33d/v37y2azae/evfruu+9O+/iiRYu0d+9e2Ww2VwZ3OddBuR988IHKyspks9n89twv1E+5ubmSpMSERoaTBIbOHU9O//3mm28MJgEAAAAAmFIvCsARI0YoNTVVJSUlevrpp7Vt2zZJzgEdkydP1hdffCHJOQgjOPjUuShjxozR5Zdfrn/+85+nXTc7O1v9+/eXJL300ktavHixHA6HHA6HFi9erJdfflmSs4C0zuOrrqKiQkePHnX9qj4soPrvHz169LTX/uUvf9GkSZO0bdu2Uw7N3blzp/71r3/p008/lSQNGzbsnANAAF9irQBMiE81nCQwNGzYRI0bOVdBsw0YAAAAAOqngJ8CLEkhISF69NFH9cgjj2j79u36wx/+oMjISJWUlLhGpF966aUaOnToeV/7N7/5jXJzc7Vx40b97//+r0JDQyVJZWVlkqRWrVrpnnvuOeNr161bp0ceeeSMH/v5RN7PPvvslH8+cOCAJk6cqIkTJyooKEiRkZEqKys7ZerwgAEDdNddd533nwkwxeFwuM4ATEhkBaC7dO40RHv2btJ3332no0ePKjY21nQkAAAAAIAX1YsCUJIyMzP10ksvacqUKfr++++Vn5+vqKgoNW3aVJdccol69ep1QdeNiIjQc889p+nTp2vu3Lmu8iInJ0cDBw7UJZdcctqqQne49dZbtXLlSm3atEmHDx/WsWPHFBQUpLS0NLVq1UpDhgzx+rmDQF0VFBSoqKhIEhOA3alzp6Ga/uVYVVRUaNasWbryyitNRwIAAAAAeFG9KQAlKS4uTnfccYfuuOOOWr/mjTfeOOdzgoODdeWVV573X6rbt29/2sq+2urXr5/69et3Qa8FfJVVoEtSYgIFoLs0y+mi6Kg4HS88om+++YYCEAAAAADqmXpxBiAA/2Cd/ydJCRSAbhMUFKwOHQZJkr799ttTzg0FAAAAAAQ+CkAAPsOaACwxBdjdrGnAhw4d0o8//mg4DQAAAADAmygAAfgMawVgSEiYoqPjDacJLO3aXSSbzSZJmjNnjtkwAAAAAACvogAE4DNcE4AT0lxlFdwjJjpe2VnOwUCzZs0ynAYAAAAA4E0UgAB8hqsAZAKwR7RvN0CStHz5chUUFBhOAwAAAADwFgpAAD7DKgCZAOwZHdr3lyRVVlZq/vz5htMAAAAAALyFAhCAT3A4HK4CMJ4C0CNymnZWRESMJGn27NmG0wAAAAAAvIUCEIBPKCgoUFFRkSQmAHtKcHCI2rTuI8lZADocDsOJAAAAAADeQAEIwCdYE4AlKSE+1WCSwNahnXMb8K5du7RlyxbDaQAAAAAA3kABCMAnWNt/JVYAelL79gNcj5kGDAAAAAD1AwUgAJ9QvQBM4AxAj2mYnKmUlCxJ0oIFC8yGAQAAAAB4BQUgAJ9gFYAhIWGKjo43nCawtWnVW5K0aNEiVVZWGk4DAAAAAPA0CkAAPsE6AzAhIU02m81wmsDW+sQgkIKCAq1evdpwGgAAAACAp1EAAvAJubm5kjj/zxtat+rlerxw4UKDSQAAAAAA3kABCMAnuFYAMgHY4+LjUtQorZkkCkAAAAAAqA8oAAEY53A4XCsAE1gB6BWtWzvPAfzuu+9UUVFhOA0AAAAAwJMoAAEYd+TIERUVFUliArC3WINAjh07pp9++slwGgAAAACAJ1EAAjDOmgAsSYkUgF7Rqto5gAsWLDCYBAAAAADgaRSAAIyzzv+TpIR4CkBvaBCbpPTGLSRRAAIAAABAoKMABGCcdf6fJCUkcgagt7Ru1UeStHjxYpWXlxtOAwAAAADwFApAAMZZKwBDQsIUHRVnNkw90vrENuCioiKtWbPGcBoAAAAAgKdQAAIwzjoDMCEhTTabzXCa+qNF826ux0uWLDGYBAAAAADgSRSAAIyzCsDEBLb/elNcXEM1TM6UJH3//feG0wAAAAAAPIUCEIBxrhWA8amGk9Q/1irAJUuWyOFwGE4DAAAAAPAECkAARjkcjmpbgFkB6G3NTxSA+/bt086dOw2nAQAAAAB4AgUgAKOOHDmi4uJiSc4zAOFdLVt0dz1mGzAAAAAABCYKQABGWROAJSmRAtDrGqU1V2RkrCQGgQAAAABAoKIABGCUtf1XkhLiKQC9zW63q3kz5zZgVgACAAAAQGCiAARg1CkFYCJnAJpgDQJZv369jhw5YjYMAAAAAMDtKAABGGUVgCEhYYqOijMbpp6yzgF0OBxaunSp4TQAAAAAAHejAARglHUGYGJCI9lsNsNp6qem2R0VFBQiiW3AAAAAABCIgk0HAFC/5ebmSmICsEmhoeHKzGytbdtW6ccffzQdB8B5KCkp0Zw5c7RkyRKtW7dOhw4dUmlpqaKiopSSkqI2bdqobdu26tWrlxISEkzHBQAAgCEUgACMslYAUgCa1axpZ23btkrLly9XVVWV7HYWiAO+LC8vTy+//LImTpyowsLCGp83ffp0Sc6BP127dtWoUaP0i1/8Qqmpqd6KCgAAAB/A3/AAGONwOE6uAGQCsFE5TTtJko4dO6YtW7aYDQOgRlVVVRo3bpx69OihcePGucq/0IgwNe2Uo66juqvXFb3VcUhnpbdMlz3I7nrd0qVL9dRTT6ljx4666aab9OWXX6qiosLkHwcAAABewgpAAMYcPnxYxcXFkqREVgAa1fREAShJy5YtU/Pmzc2FAXBGBQUFGjNmjObMmeP6vY5DOmvILUPVpm9bBYee/m1dWUmZdq7ZoVVzVmrFtz9q55odqqqq0owZMzRjxgw1adJE99xzj2644QZFRkZ68U8DAAAAb2IFIABjrAnAEluATUtNyVZkZKwkafny5YbTAPi5vXv36rLLLnOVf42aNdKjU5/Q/eMfVIdBHc9Y/klSaHiomnVtrtEPXqOnvvqbnvnmWQ2/Y6Si46MlSTt27ND//M//qHPnznrxxRd1/Phxb/2RAAAA4EUUgACMObUAbGQwCex2u2sbMAUg4Fvy8/M1evRorVu3TpLU+6q+euLLZ9SsS7PzvlZ6ywzd+Neb9X/fv6QxL/5ajVukS5IOHTqk5557Tt27d9fYsWNVUlLi1j8DAAAAzKIABGAMKwB9S9PsTpKkNWvW8Jd/wEcUFhbqhhtucJ3NefHdl+rX/7xboeGhdbpuSFiI+v2iv56e8b+6b/yDatbVue0/Pz9fjz32mHr27KmJEyeqsrKyzn8GAAAAmEcBCMAYawJwaGi4oqPizIaBmuV0kiRVVFTop59+MhsGgBwOh/70pz9pxYoVkqTBvxyiXzx8nWw2m9vew263q9OQznrkk8d13/gHldEmU5LzBzT333+/RowYoaVLl7rt/QAAAGAGBSAAY6wVgAnxaW79Cy0uTPVBIGwDhqcdP35c69at09y5c/XNN99o4cKF2rhxo8rKykxH8xnvvfeeJk2aJEnqOLiTbn7qVx77Wmmz2dRpSGc9+eUz+s1/7lVKVookaeXKlbr44ov129/+VgcPHvTIewMAAMDzmAIMwBhXAcj2X5/QIDZJyUkZOpC/iwIQbudwOLR06VJNmzZNCxYs0Lp16+RwOE57XkhIiNq2bashQ4bosssuU9u2bQ2kNW/Hjh165JFHJEmJjRN15z/vlj3I8z+3tdvt6nFZL3Ue3lUz3vyvPvv3VJUWlWrSpEmaPXu2/v73v+viiy/2eA4AAAC4FysAARhDAeh7GAQCdysrK9O7776rvn376pJLLtFrr72mtWvXnrH8k6Ty8nKtWLFCL774ogYOHKiRI0dq2rRpqqqq8nJycxwOhx566CEVFRXJZrfpnpfvVXRctFczhISF6JLfXKbn5vw/9by8lyTpwIED+tWvfqW7775bhw8f9moeAAAA1A0rAAEY4XA4XAVgIhOAfUbTpp20+PvPtX37dh0+fFjx8fGmI8GPffXVV/rrX/+qbdu2uX4vNDhYvVu3Uo9WLdSicWOlJiQoLCRYRaWlyj10WGt37NR369Zr+abNqnI4tGzZMo0ZM0Zt2rTRs88+qz59+hj8E3nHxx9/rDlz5kiSht8+wjWgw4T41ATd8/K96nFpT739l/E6mn9UU6ZM0dKlS/Xmm2+qU6dOxrIBAACg9igAARhx+PBh16TZhPhUw2lgyc5q73r8008/qX///gbTwF8VFBTof/7nfzR58mTX72WlpGjMyOG6ok8vNYiKqvG1l/ToLknaf+SIPp63QBO++Vb7Dh/R2rVrdcUVV+iXv/ylHn/8ccXFxXn6j2FEYWGhnnrqKUlSUkayRj90jeFETl1HdleLHq307mNv6/vPF2vnzp265JJL9Oyzz+qWW24xHQ8AAADnwBZgAEZYE4AlKYEVgD6jSWYb1+NVq1YZTAJ/tXjxYvXv399V/iU3iNXzd9ym2f/vWd0ybMhZy7/qGsbF6beXX6r5L76gx2+6QdHh4ZKkd999V4MGDdKPP/7osT+DSa+++qr27dsnSbrukRsUFhluONFJMQkxuufl3+rWZ29XcGiwysrK9OCDD+rxxx+vV1u0AQAA/BEFIAAjcnNzXY85A9B3REbGKiUlSxIFIM7fpEmTNHr0aNf2/kt6dNe3z/2vbhg0QEH2C/uWIzw0VGNGjdCsF57VyG5dJUm7d+/WpZdeqrfffrvGswT90f79+/XSSy9Jkpp1ba5uo7obTnQ6m82mgTcN1qOf/FWJjRMlOUvLMWPGuFZ1AwAAwPdQAAIwovoKQM4A9C1ZTdpJogBE7TkcDj333HP67W9/q/LycoWFhOj/7r5Tr/zuN4qPcc/witSEeL123+/0wpjbFBbiXH320EMP6a9//WvArD77z3/+o6KiIknS9Y/eKJvNZjhRzbI6ZOuxqU+oSbsmkqTPP/9cN998s4qLiw0nAwAAwJlQAAIwwlohFBoarqioBobToDrrHMAtW7bo2LFjhtPA1zkcDj3xxBN68cUXJTm3/H786MO6ul9fjxRY1w8coCmPP6r0pJOrz373u9+pvLzc7e/lTfn5+ZowYYIkqcPgjkYHf9RWXEq8Hv74MbUf2EGSNHfuXN1yyy2sBAQAAPBBFIAAjLAKwISERj69yqU+slYASs5BIEBNHA6Hnn76ab3yyiuSpJy0VE178nF1ymnq0fftkJ2lT//6mNpkZkhybj2+7bbbVFZW5tH39aRx48a5Vv9d/rsrzYY5D+FR4fr96/er45DOkqQ5c+boV7/6ld8XsgAAAIGGAhCAEa4CkAnAPqdJtQKQbcA4mxdffNF1Zl3T1FR9+Jf/UXpSklfeOyU+TpMefVg9W7WUJH399de6++67VVFR4ZX3d6fjx4/rzTfflCS16dvWL1b/VRcSFqJ7x/5eHQZ3lCTNmjVLDz30UECdzwgAAODvKAABGGGdAcj5f74nJjpeSYnpklgBiJp99NFHev755yVJ2akp+vCRPyslPs6rGWIjI/Xunx5UnzatJTnPofv973+vyspKr+aoqw8//NC13f6S31xmOM2FcZaAf1DLXq0kSe+//77+9a9/GU4FAAAACwUgAK9zOByuKcBMAPZNWVkMAkHNFi5cqPvvv1+S88y/iX9+SKnx8UayhIeG6s0H/qCuzZtJkj7++GM9+eSTRrJciKqqKr3++uuSpMYt0tWmX1vDiS5caHiofvfafUpt6lzZ/be//U2fffaZ4VQAAACQKAABGHDo0CHXIfEUgL7JOgdw48aNrnPJAEnasWOHbr31VpWXl58o3+5TRnKy0UxR4eF6+48PqF0T50TaV199VW+99ZbRTLU1c+ZMbd26VZI07Lbhfn8manRctB6Y8EfFJMRIkv7whz+4/nwAAAAwhwIQgNdZ5/9JUkI8BaAvsiYBV1VVac2aNYbTwFeUlpZqzJgxOnLkiCTpX/f82uMDP2orNjJS4x+6X40SEyRJDz/8sGbMmGE41blZk3+jGkSp9+i+ZsO4ScOsFN3zn3tls9l0/PhxjRkzhsnAAAAAhlEAAvC66gVgYiJnAPqiLAaB4Awee+wxrVixQpL0uysu06ju3cwG+pmU+Di9/dADiomIUFVVle6++25t2bLFdKwa5eXlaebMmZKkvtdcpLCIMMOJ3KdN37a64r6rJDnPEn388ccNJwIAAKjfKAABeB0rAH1fgwbJio9LkUQBCKepU6dq/PjxkqQ+bVrrgauvMpzozFpmpOvV3/9WdptNx44d069+9SsdP37cdKwz+vjjj10DSy66boDhNO53+e+vVOs+bSRJ48eP16xZswwnAgAAqL8oAAF4nTUBOCw0QlFRDQynQU2sVYAUgMjLy9Mf//hHSVJygwb692/uUpDdd7+F6N++nR76xdWSpA0bNui+++6Tw+EwnOpUDodD77//viQpq322MlplGE7kfvYgu+761z2KiouWJD3wwAOuaccAAADwLt/97h1AwLImAMcnpPn9gfeBzJoEvH79epWWlhpOA1McDof+8Ic/uM79+7+771TDuDijmWrjt5ddohFdu0iSpk2bprFjxxpOdKoffvhBmzdvliRddF1/w2k8Jy4lXjc9cbMk5w9/nn76acOJAAAA6icKQABeZ60ATGQCsE/LauIcBFJRUaF169YZTgNT3nnnHdfWzV8OGaz+7dud4xW+wWaz6R933ammqamSpCeffFI//PCD4VQnWav/gsNC1OvyPobTeFbvq/qq4+BOkpxbgRcuXGg2EAAAQD1EAQjA66wzADn/z7dVHwTy008/GUwCU3bv3u0a3tCkYUM9csN1hhOdn5jICL12/+8UERaqyspK3X333T6xBbWoqEhTp06VJHUd0VVRcVFmA3mYzWbTr569TRExEZKk//mf/1FFRYXhVAAAAPULBSAAr3I4HK4twAkJTAD2ZQkJaa4zGtesWWM4DUz4y1/+oqKiIudqurvvVGS4/02pbdG4sf56842SpB07dujPf/6z4UTSzJkzXYNJ+l5zkeE03pGQlqjRD/1CkvNYgQkTJpgNBAAAUM9QAALwqkOHDqmkpESSlJCQajgNzsZmsykzwznBkwKw/vnqq6/01VdfSZJuGjxQ3Vs0N5zowt0wcIBGde8qyTl59+OPPzaaZ9q0aZKkqLhotenb1mgWbxp082A1at5YkvT888/r0KFDhhMBAADUHxSAALzKOv9PkhJZAejzMjJaSZLWrl3rc1NU4TnHjx/Xww8/LElKio3Vn669xnCiurHZbHr+jtuUGh8vSfrTn/6k7du3G8lSVFSkb775RpLUdWQ3BYcEG8lhQnBIsG564peSpCNHjui5554znAgAAKD+oAAE4FXW9l/JucUUvq3JiRWAR48e1e7duw2ngbe8+OKLrrL+sZuuV1yU/59RFxcdrX/d82vZbDYdP35c9913n6qqqrye49tvv1VRUZEkqcelPb3+/qa1vaiduoxwrsZ8++23tWnTJsOJAAAA6gcKQABedeoKQApAX5eZ2dr1mG3A9cPatWv16quvSpL6tm2jK/v0NpzIfXq3aa1fXzxSkrRw4UKNHz/e6xms7b/R8dFq3aeN19/fF1z3yA0KCg5SVVWVnn/+edNxAAAA6gUKQABeZU0ADguNUGRkA8NpcC6NG7WQzeb8XwUFYOBzOBx6/PHHVVlZqdDgYP3t1ltks9lMx3KrB6++Ss0aOX/48NRTT3l1K3BhYaG+/fZbSVLXkd0VFBzktff2JSlZqbro2v6SnIUoU8YBAAA8jwIQgFdZBWBCQqOAKxYCUWhouNLSmkqiAKwPvv32W82dO1eSdPvI4WqaFniDesJDQ/X3X98hu82moqIir24Fru/bf6u7/A9XKjgsRJI4CxAAAMALKAABeJW1BZgJwP6DScD1Q0VFhZ544glJUkJMjO69/FKzgTyoS7NmunPUCEnOrcATJkzwyvt+8cUXkqSYhBi16t36HM8ObAlpiRp88xBJ0owZM7R06VLDiQAAAAIbBSAAr6q+AhD+ITPDWVRs27ZNhYWFhtPAUyZOnKiNGzdKkh4YfaViIyMNJ/KsB68ZrZwTKxyffPJJ7dixw6PvV15erpkzZ0qSOg7pVG+3/1Z36W8vU1hkmCTpH//4h+E0AAAAgY0CEIDXOBwO1xTgRApAv9Ek07kC0OFwaN26dYbTwBOOHTvmGsbQrFGabhw80GwgL3BuBR4j24mtwA899JAcDofH3u/777/X0aNHJUkdh3T22Pv4k9ikBhr0S+cqwG+//VarV682nAgAACBwUQAC8Jr8/HyVlpZKYguwP8nIOLlVce3atQaTwFP+9a9/KT8/X5L0lxuuU3BQ/Vid1rV5M90+Ypgkac6cOfr000899l5ff/21JCk4NFjt+rf32Pv4mxF3jFJwaLAk6aWXXjKcBgAAIHBRAALwGmv7r8QKQH8SH5ei6Oh4SWKFTgDat2+fXnvtNUlSnzatNaRTR8OJvOuha0YrLSFBkvToo4+qoKDAI+9jFYCterVWRHSER97DH8Wnxqvv1RdJkqZOnaotW7YYTgQAABCYKAABeE31ApAzAP2HzWZznQPIIJDA869//UvFxcWSpP+57hf1bjp3VHi4nrrlJknSgQMH9Mwzz7j9PTZv3qytW7dKkjoNZfvvz426+xLZ7DZVVVXpxRdfNB0HAAAgIFEAAvAaawKwJCXEswXYn1gF4Nq1a1VVVWU4Ddxlz549evvttyVJw7t2VqecpoYTmTGiW1cN6+Is5t5++2398MMPbr3+jBkzXI85/+90qdmp6n5xD0nOz//+/fsNJwIAAAg8FIAAvMZaARgeHqXIyFjDaXA+MjOcg0COHz+uXbt2GU4Dd3nxxRdVVlYmm82mB68ebTqOUU/dcrMiw8LkcDj00EMPqby83G3Xtrb/prdMV3JGstuuG0hG3XWJJKm0tNS1JR0AAADuQwEIwGusAjAhIa3ebTP0d5mZJweBsA04MGzevFnvv/++JOmynj3UOjPDcCKzGicl6sGrr5LkvMfHjRvnlusWFBRoyZIlktj+ezbZHZuqWdfmkqRXXnnFrQUsAAAAKAABeJG1BZgBIP6ncaPmstudk2EpAAPDM888o8rKStltNt0/+krTcXzCbSOGqW2TTEnS3//+d+Xl5dX5mgsWLFBlZaUkqf3A+jVg5XwNu22EJCk3N1dTpkwxnAYAACCwUAAC8BrXCsD4NMNJcL5CQsLUKC1HEgVgINi4caNr9d/V/foqpxH/TUpScFCQnvrVLyVJhYWFevrpp+t8zTlz5kiSwqPDldOlWZ2vF8i6juqmhDTnROaXXnrJcBoAAIDAQgEIwCuqqqqUm5srybkFGP7HOgdw7dq1hpOgrp577jlVVVUpyG7X76+63HQcn9K9RXNd1ae3JGnSpEl1GgjicDg0e/ZsSVLrPm0VHBLsloyBKjgkWMNvGylJWrJkiZYvX244EQAAQOCgAATgFQcOHHCd6cQWYP+Unt5SkrR9+3YVFhYaToMLtX37dr377ruSpCv69FKThg0NJ/I9D19/rSLDwiRJf/nLXy548vW2bdu0Y8cOSVK7/u3cli+QDbllmELCQyVJb731luE0AAAAgYMCEIBXWNt/JVYA+qvMDOcgEIfDoQ0bNhhOgwv197//XRUVFbLZbPrtZZeajuOTUhPide8Vl0mSfvzxR3344YcXdB1r+68ktevf3h3RAl5sYqx6X+5cgfnZZ5+poKDAcCIAAIDAQAEIwCuqF4CJFIB+KSODScD+Li8vz7Wq6rJePdW8MatxazJm5HBlNkyW5ByYcvTo0fO+hlUAJmckq2GTFHfGC2hDbxkuSSouLtbkyZMNpwEAAAgMFIAAvMKaACxJCWwB9ksJ8amKjIyVxDmA/uo///mPysrKJEn3X3OV4TS+LTw0VI/fdIMk5xEGL7744nm9vry8XPPnz5ckte3fXjabze0ZA1XLnq3UuEW6JOndd9+Vw+EwnAgAAMD/UQAC8AprBWBkRKwiIqINp8GFsNlsrm3AFID+Jz8/X++8844kaXi3LmqXlWU2kB8Y1qWz+rd3nt33+uuvu87zq41ly5bp+PHjktj+e75sNpuG/HKoJOdq4x9//NFwIgAAAP9HAQjAK6wVgAkJqYaToC4y0p0F4Lp161iV42fGjRunoqIiSdIDV482nMY/2Gw2PXbj9bLbbCovL9ezzz5b69fOnTvXeQ27Ta37tPFUxIDV/9qBCg51Tk22imsAAABcOApAAF5hrQBk+69/y8xoJUk6fPiw8vLyDKdBbRUUFOjNN9+UJA3o0F7dWrYwnMh/tMxI1zUX9ZMkTZkyRStXrqzV6xYsWCBJyu7QVFENojyWL1DFJMSo26jukqRPP/1Ux44dM5wIAADAv1EAAvAKqwBkAIh/y0hv5XrMIBD/MXHiRFeBct/oK82G8UMPXn2VwkJCJElPPfXUOVe/FhUVafny5ZKkVr1bn/W5qNmAGwdJcn4+P/nkE8NpAAAA/BsFIACPq6ysVG5uriQpgQLQr6Wnt3Q95hxA/1BeXq7XX39dktQ+O0t927U1nMj/pCUm6I6Rzsm08+bN0+zZs8/6/GXLlrmGrVAAXrhWvVorJdt5bMTEiRMNpwEAAPBvFIAAPO7AgQOqrKyUxBZgfxceHqWGDZtIcp4DCN83ffp01xmcd44awTTaC3TPpRcrLtq5lfepp55yfU07k4ULF0qS7EF2Ne/GdusLZbPZ1P+6AZKkFStWaMOGDYYTAQAA+C8KQAAeZ5UPEluAAwGTgP2Hw+HQK6+8IklKjY/XJT26G07kvxpERen3V14uybn9ffLkyTU+1yoAszpkKyI6wiv5AlWf0X1dpfVHH31kOA0AAID/ogAE4HHVC0BWAPq/jBPbgDdu3Oja5gjftGTJEq1YsUKSdNuIYQoJDjYbyM/9cshgZSQnSZKeffZZlZaWnvacoqIiLVu2TJLUujfTf+sqPjVBbfo5t61Pnjz5rCsvAQAAUDMKQAAeZw0AkTgDMBBkpDtXAFZUVGjTpk2G0+Bsxo4dK0mKDAvTDYMGGE7j/8JCQvTHX1wtyfmDjffee++05/zwww8qLy+XxPl/7tL3aucU5tzcXNd0ZQAAAJwflgKgVoKCgkxHqJEvZ/MX1ufQU59LawBIVFQDRUZEe+Q9fJXdHng/Z2nS5OSqpg0bNqhDhw4efT9P35+BauvWrfryyy8lSdcN7K+EmJjTnhOI96enXdGnt16a9rk27dmrf/7zn7r11lslnbw/Fy1a5Pzn4CC17NGKz3EdWJ+77hf30DuPTFBJYYk+/vhjDR482HAy/8HXT8/hc1p33J+ew+cUwJlQAKJW4uPjTUc4o6CgIJ/N5o9iY2M9ct0DBw5IkpKS0hUeHu6R9/BFNpstIP+8mZktFRYWqdLSIm3ZssVr/w166v4MVBMmTJDD4ZDNZtNvrrjstHsxUO9Pb/jTddfqzn/8U7m5uZo0aZLuvfde1/25ZMkSSVJO52aKS4wzmNK/Vb8/w8PD1evy3przwWx9/vnneuONNxQdXb9+mFRXfP10L77/dC/uT/fi/gRQEwpA1Mrhw4dNRzhFbGysgoKCVFlZqaNHj5qO4/eCgoIUGxuro0ePeuR8pW3btkmS4uNSVFJS4vbr+5qwsDDZbDY5HI4znhEWCBo3bq6tW1dq2bJlHv/64On7MxAdOXJEb731liRpZLeuSouLc/23Vx/uT08b0aWTWqY31obde/S///u/uuOOO1ReXq5jx465CsCWPVvWi6937lbT/dnryj6a88FsFRUV6d1339X1119vMKX/4Oune/H9p3txf7pXoN6flJmA+1AAolZ8+X/KvpzN31RWVnrk82mdAZgQn6aqqiq3X9+XBeqfNyO9tbZuXak1a9Z47b9BT92fgWj8+PEqKiqSJI0ZNaLG+zBQ709vuG/0lbrn3/9Rbm6uXnvtNd1yyy1avHix6/y/lr1a8/mto+qfvxY9WyqhUaIO7T2oDz74QL/4xS8MJvM/fP10Pz6f7sP96X58PgGcCQfTAPCoiooK5eXlSZISmQAcMDIzWkmS8vLydOjQIcNpUF1ZWZlef/11SVKnnKbq1ryZ4USBaVS3rmqdmSFJeu6551RcXKyFCxdKcp7/16xrc5PxAo7dblef0X0lSQsWLDhluBQAAADOjQIQgEft27fPtYojIZEJwIHCmgQsSevWrTOYBD/32WefuUr3MaNGyGazGU4UmOx2u+676gpJziJ84sSJrgIwu2NThUdxvqK79RntnAbscDg0depUs2EAAAD8DAUgAI+qvkojIZ4CMFBknFgBKElr1qwxmATVORwOvfrqq5KkxomJurh7N8OJAtuIrl3UMiNdkvTyyy9rxYoVkqSWPVud5VW4UI2aNVJm2yaSpE8++cRwGgAAAP9CAQjAo/bs2eN6zBbgwBETHa/4uBRJ0tq1aw2ngWXRokVatWqVJOm2EUMVHBRkOFFgs9vtuueSiyVJu3btUllZmSSpefcWJmMFtJ6X9ZIkrVy5Ulu2bDGcBgAAwH9QAALwqFNWACawAjCQZGQ4twGzBdh3jB07VpIUFR6u6wcOMJymfriiTy81Tko85fead6UA9JSel/d2Pf70008NJgEAAPAvFIAAPMoqAKOj4xUayplYgSQjvaUkaf369Uyb8wFbtmzR119/LUm6fmB/xUZGGk5UP4QEB+ueyy51/XNydkNFxUUZTBTYktKTXANWPvnkEzkcDsOJAAAA/AMFIACPsrYAs/038FgrAIuKirR9+3azYaBx48bJ4XDIbrPptuHDTMepV24cPEjWqJXwlAijWeqDXlc4VwFu2rSJM0gBAABqiQIQgEdZKwDZ/ht4MjNOTgLmHECzDh8+rA8//FCSNLJ7V2U2TDacqH7JPXRI1jq0qpgq5eblGs0T6Lpf0lM2u7NyZRgIAABA7VAAAvAoVgAGrkZpOQoKCpbEOYCmvf322youLpYk3TlqpOE09c/idetdjyPTorT0+6UG0wS+BskN1KZPW0nS1KlT2QYMAABQCxSAADymvLxc+/fvlyQlJKQaTgN3Cw4OVVpajiRWAJpUVlamN954Q5LUpVmOujZvZjhR/fP9emcBGBEbrpDYUG3atEnHjh8znCqw9TyxDXjXrl1aupTCFQAA4FwoAAF4TF5enmtlRgIrAANSZrpzGzDncJkzdepU7du3T5I0ZtQIw2nqpyXrNkiSmrXPkM1mU1VVlVb8uMJsqADXdWQ3BYc6VyCzDRgAAODcKAABeIy1/VdiC3CgyshoJUnavn27jh8/bjhN/eNwOPTqq69KkjKSkzSyW1fDieqffYePaPuJArZtp6au8xdXrVqliooKk9ECWlSDKLUf2FGS9Nlnn/G5BgAAOAcKQAAek5t78iB8tgAHpuqDQDZs2GAwSf20YMECrV69WpJ024hhCg4KMpyo/lm6caPrcbP2meqU01SSczr2+vXra3oZ3KDn5b0kSQcOHNDChQsNpwEAAPBtFIAAPKb6CsCEeKYAB6L09Faux5wD6H3W6r+YiAhd17+/4TT109INzgIwLDxEGc1SlZ2aqgZRUZKkZcuWmYwW8DoP7azQ8FBJzlWAAAAAqBkFIACPsQrA2NgkhYSEGU4DT0iIT1VUVANJnAPobZs2bdI333wjSbph0ADFREYYTlQ//bBxkySpaZt0BQXZZbfZ1LFptiRp//792pu712S8gBYWGa4OgztJkr744gu2AQMAAJwFBSAAj7G2ACcmsPovUNlsNmWcGATCCkDvGjdunCQpyG7XrcOHGk5TPxWWlGj19h2SnNt/LW2bZCo4yPkt1qqVq4xkqy96XNJDknTw4EG2AQMAAJwFBSAAj7FWALL9N7BlnhgEsm7dOtfUZ3jWwYMH9dFHH0mSLu7RTelJSYYT1U+rtm5TZVWVJKlZuwzX74eHhqp5o8aSpPXr16usrMxIvvqg45BObAMGAACoBQpAAB7jKgCZABzQMk6cA3jkyJFTBr/AcyZMmKCSkhJJ0p2jRhpOU38t37xFknMlbNPW6ad8rF12E0lSeXm51q5jdaynsA0YAACgdigAAXhEaWmpDhw4IElKTGQFYCDLqDYJmHMAPa+0tFRvvvmmJKlbi+auqbPwvh+3OAvAtCbJiowOP+VjjZMSlRATLYltwJ5WfRvwokWLDKcBAADwTRSAADwiLy/P9ZgtwIEtvXEL2Ww2SZwD6A2ffPKJq1y/c9QIw2nqL4fDoR9PrABs1jb9tI/bZFO7rCxJ0r59+7Rv3z5vxqtXqm8DnjZtmuE0AAAAvokCEIBHWNt/JSmBISABLTw8Sg0bOrc7rlu3znCawOZwODR27FhJUkZysoZ37WI4Uf21Oz9fBwqOSpJy2mac8TmtMzMUZD8xDGQVqwA9JSwyXB0GdZTENmAAAICaUAAC8Ii9e/e6HidyBmDAs84BZAWgZ82bN8/1Ob5j5HBXuQTvs1b/SVLTNmcuACPDwtQ0LVWScxhIZWWlV7LVRz0u7SmJbcAAAAA14W8OADzCKgBtNpvi41MMp4GnWQXgpk2bVFpaajhN4Hr11VclSbGREbq2fz/Daeo3awBIWHiI0rMb1vi81pnOcrCkpERbtm6p8XmoG6YBAwAAnB0FIACP2L17tySpQYNkBQeHGk4DT8s8MQikoqJCmzZtMpwmMG3YsEEzZ86UJN0waKCiIyLMBqrnrBWA2a0byx5U87dTWSkpiggLkyStXcMKWU+pvg14+vTpbAMGAAD4GQpAAB5hnQGYmNDYcBJ4Q/VJwJwD6Bnjxo2TJAUHBem24UMNp6nfSsvLtWbHTklS0zanDwCpLshuV8t053O2bNmi4uJij+err7pfwjZgAACAmlAAAvAIVwGYyPl/9UHD5EyFhTpXpHEOoPvl5+dr0qRJkqRLe3ZXo8REw4nqtzU7dqjsxAqznHMUgJLUOtP5nKqqKq1fv96j2eoztgEDAADUjAIQgEdYW4CTElkBWB/Y7Xalp7eUJK1Zs8ZwmsAzYcIE19mKd4wcYTgNllcbAJLd+twFYEp8nBJiYiTx34cnhUcxDRgAAKAmFIAA3O7YsWMqKCiQxArA+oRJwJ5RUlKit956S5LUs1VLdWyabTgRrPP/ktLi1CAh+pzPt8nmGgaSm5urw4cPezRffWZtA87Pz2cbMAAAQDUUgADcztr+K3EGYH2SkeEsAPft26eDBw8aThM4Jk+erAMHDkiS7hzF6j9fsGLLVklS01qs/rO0zDj5tXDDhg1uzwSnjkM6KSQsRBLbgAEAAKqjAATgdtb2X4kVgPVJRjqDQNzN4XBo7NixkpzTZId07mQ2ELT/yBHtOpAv6dwDQKprEBml1IR4SRSAnhQeFa6OgztJYhswAABAdRSAANxu7969rsecAVh/WCsAJc45c5fZs2e7yqI7Rg5TkJ3/bZtmrf6Tzq8AlKQWjZ1fD/fv369Dhw+5NRdOqr4N+LvvvjOcBgAAwDfwNwkAbmetAAwNDVd0dLzhNPCWmOh4xcenSuIcQHd59dVXJUkNoqL0i4suMpwG0skBIMEhQcpslnper23e+OSK6A3rWQXoKdW3AU+bNs1wGgAAAN9AAQjA7awzABMTGstmsxlOA2+yBoGwBbju1q1bpzlz5kiSbho8UJHhYWYDQdLJASBNWqQpOCTovF4bGxmpRokJktgG7EnhUeHqwDZgAACAU1AAAnA7awUg5//VP5kntgGvX79elZWVhtP4N+vsv+CgIN06bKjhNJCkispKrdy6TZKU3frCjjdofmIb8IEDBxiW40E92AYMAABwCgpAAG7nWgHI+X/1jjUIpLi4WNu3bzcbxo/t379fkydPliRd1quHa3gEzNq4e4+KSkslnd8E4OqqbwNev2G9W3LhdEwDBgAAOBUFIAC3qqysdA0BSWIFYL2TmXFyEjCDQC7c+PHjVVZWJkkaM3KE4TSwWOf/SVLOeQ4AscRERLi2AW/etNktuXC66tuAp0+fzjZgAABQ71EAAnCrAwcOqLy8XJKUkEABWN+kpTVVUFCwJM4BvFDFxcUaP368JKl361Zqn51lNhBcrPP/GiREKyGlwQVfp2lamiTnSs+CowVuyYbTdb+khyS2AQMAAEgUgADczDr/T+IMwPooODhUjdKaSWIS8IWaPHmy62y4MaNY/edLftziLACbtkmv04CjnLST04M3b2YVoKd0GtKZacAAAAAnUAACcKvqBWBSAmcA1kcZJ7YBUwCev6qqKtfwj6apqRrSqaPhRLAcKSzU5r25kqSmber2tS0hJkYJMTGS2AbsSeFR4erINmAAAHzWE088oSeeeEITJkwwHaVeoAAE4FbWABBJSkhIM5gEpliTgLdv367jx48bTuNfZs2apY0bN0qS7hg1XHY7/5v2FatOTP+VpOxWdf/hRtMTqwB3796tkpKSOl8PZ9bjsl6SpIMHD2r+/PmG0wAAgOqefPJJPfnkkxSAXsLfLAC4lbUCMDY2SaGh4YbTwISM9Faux+vXM+X0fFir/+Kio3RNv76G06A6qwC02aSslnU/3qBZI+cPSKqqqrRl65ZzPBsXquOQTgqLDJMkTZ061WwYAAAAgygAAbiVtQKQ8//qr4xqk4DZBlx7a9as0dy5cyVJvxwyWBFhYYYTobqVJwrA1MwkhUfW/d9Nany8osKdPyRhG7DnhEWEqdPQzpKkL774wjVdGwAAoL6hAATgVtYKQM7/q7/i41IUHRUnyVlqoXas1X8hQUG6ZegQw2nwcyu2bpUkZbV0z9c2m83m2ga8bds2zqfzIGsbcEFBgebMmWM2DAAAgCEUgADcihWAsNlsDAI5T3l5eZoyZYok6Yo+vZQSH2c2EE6Rd/iw9h0+IknKbuW+r21WAVheXq7de3af49m4UO0HdFBETIQkpgEDADyvpKRE06ZN0+9//3v16dNHycnJCgkJUUxMjJo3b65f/vKX+uabb2p1rfLycr388svq27evEhISFBkZqRYtWujee+/Vhg0bJDkHadhsNtlstnP+oKukpETjxo3TpZdeqoyMDIWHh6tBgwZq166dfv/737vOoq7Jmd5r2bJluu2229S0aVOFh4crMTFRgwYN0oQJE1RVVXXG61jXsMydO9f1e9V/cTagewWbDgAgcBQVFenQoUOSpMREVgDWZxnpLbVu/Xdat26dHA7HKf+Dx+kmTJig8vJySdKYkSMMp8HPVR8AkuWGASCWjKQkBQfZVVFZpW1btymrSZbbro2TQsND1WV4Vy2cskBffvmlSkpKFB7OGbUAAM9o06aNtm3bdtrvHz9+XJs3b9bmzZs1ceJEXXHFFZo4caKio6PPeJ28vDyNHDlSK1euPOX3N23apE2bNmn8+PEaP358rXPNnTtXN9100ylDGyWptLRUa9as0Zo1a/TKK6/o6aef1sMPP1yraz7//PN65JFHVFlZecr15syZozlz5mjatGn6+OOPFRxM9eQL+LcAwG327t3repyYwArA+sxaAVhQUKA9e/YoPT3dcCLfVVJS4vrpZp82rdWmSabZQDiNdf5fULBdGTkpbrtuSHCwGiclace+/dq2bZsGDRrktmvjVD0u66WFUxbo+PHjmjlzpi655BLTkQAAAaqoqEhxcXEaPHiwOnfurCZNmigyMlJHjx7VqlWr9NFHHyk3N1fTpk3T7bffrkmTJp12jZKSEg0bNkyrV6+WJCUlJemOO+5Qhw4dVFZWpvnz5+vdd9/VLbfcopEjR54z01dffaUrrrhC5eXlstvtGjlypIYOHarGjRurpKREP/zwg9555x0VFBToL3/5iySdswR8/fXX9f777ys5OVm33nqrOnToILvdrkWLFumNN95QaWmppk6dqhdeeMF1Tcunn34qSbrqqqskSW3bttUzzzxz2nt06dLlnH821B4FIAC3sc7/k1gBWN9lZrRxPV69ejUF4FlMmTJFBw8elCTdPmK44TQ4kxVbnOf/ZeSkKiTUvd86ZaWkaMe+/Tp48KAKCgrUoEEDt14fTm37tVNUgygVFhRq6tSpFIAAAI8ZP368hg4dqpCQkDN+/G9/+5tuuukmTZ06VR9//LEWLFigfv36nfKcZ5991lX+tWvXTjNnzlTDhg1dH7/11lt1zz33aOjQoec83iI3N1c333yzysvL1bBhQ02bNk29evU65Tm33HKL/vznP2vkyJFavXq1HnvsMV111VVq1apVjdd9//33NWDAAE2bNu2U719uvPFG/eIXv9CQIUNUWVmp//u//9NDDz2k0NBQ13OuvPLKU66VlJR02u/B/TgDEIDbVC8AkzgDsF7LSG+poCBnUfLzbQs4yeFw6LXXXpMkNWnYUEM6dzScCD/ncDi0att2SVJWS/d/XctOPbmicOu2rW6/PpyCQ4PVdVQ3SdKMGTNUWFhoOBEAIFCNGjWqxvJPkiIjI/X2228rKipKkvT222+f8vGysjK98sorkqTg4GB99NFHp5R/lm7duunFF188Z57/9//+n+uYpsmTJ59W/lkaN26sjz/+WEFBQaqsrNS//vWvs143ISFBU6ZMOeMPLwcMGKBrrrlGkpSfn6+lS5eeMyc8jwIQgNtY50mEBIcpJibRcBqYFBoarsaNWkiiADybBQsWuAal3DZimILs/G/Z1+zYt18FJ8qiLDcOALHERUepwYm/AGzbevp5QXCfHpc6/8JTVFRU68PXAQDwhNjYWLVv316StHjx4lM+tmDBAuXn50uShg8frjZt2pz2esstt9yixMSa/97lcDj0zjvvSJJ69+6tiy666Ky5WrVqpR49ekiSvv7667M+91zvPWzYMNdjazUjzGILMAC3sVYAxiekyk6RUe9lZ7XXzl1rKQDPYty4cZKkmIgIXdu/3zmeDRNWVivlst04AMRik03ZqSlasWWrdu7cqYqKCg7K9pDWfdooJjFWxw4e1dSpU9lqBADwmMOHD+u9997Tf//7X61evVoHDx5UYWGhHA7Hac+tvotK0imr5c51PnBISIj69u2rzz777IwfX7t2reuomfj4eE2dOvWc2YOCgiRJ27ZtO+vgrN69e5/1OtWPADp8+PA53xeex3eYANzGWgGYxPl/kJSV1V5z53+k/fv3Ky8vT6mpqaYj+ZQtW7ZoxowZkqTrBvRXdESE4UQ4kxVbndtyw8JDlJaZ5JH3yEppqBVbtqq8vFy7d+9WVlaWR96nvgsKDlK3Ud01e+JMzZw5U8ePH69x8iIAABdq2rRpuuOOO1zF27kcPXr0lH+uPlgxJyfnnK9v2rRpjR/bvn276/GXX36pL7/8slaZLIcOHVKjRmfeAZGUdPbvi8LCwlyPS0pKzut94RkUgADcxvrpFROAITlXAFpWrlxJAfgzr7/+uhwOh+w2m24dPtR0HNTAWgHYpEUj2YM8s7I5PTlJwUFBqqis1LZt2ygAPajHZT01e+JMlZSU6L///a/rfCIAANzhu+++0zXXXKOKigpJUocOHTR06FA1a9ZM8fHxCgsLk81mkyQ9+uijWrNmjaqqqk65RvVzaiMjI8/5ntZZgmdy5MiRC/hTnFRWVlbjx9jx5X8oAAG4RVVVleunVUwAhiRlZrSW3R6kqqpKrVy5UiNGjDAdyWcUFBTogw8+kCQN79pFmQ2TDSfCmVRUVmr19h2SPHP+nyUkKFiNEhO1c/9+7dy502PvA6llj1aKaxinI/uPaOrUqRSAAAC3evzxx13l33/+8x/95je/qfG5f/vb3874+9ULvaKionO+59kGW1Vf6f7AAw/UamgIAheVLQC3yM/PV2lpqSQpkQnAkHMQSHpjBoGcyXvvvef6hu6OkcMNp0FNNu3Zq5ITP/n2xATg6qwSeP/+/SosYkKtp9iD7Op+ifNw81mzZtV5ZQQAAJby8nLNmTNHktS1a9ezln/Sqdtzq6u+5XbLli3nfN+tJ44rOZPq5/Dt2rXrnNdCYKMABOAW1vl/EmcA4qSsE9uAKQBPqqio0BtvvCFJapfVRD1atjCcCDVZseXkN9TZrT37da36KlBWAXpWj8uc04DLy8s1ffp0w2kAAIEiPz/ftfqvWbNmZ33u0qVLXZN+f6579+6ux7Nnzz7rdcrLy7Vw4cIaP96pUyc1aNDAdS1rwYavsLZDn2k4CtyPAhCAW1SfXsUZgLBkN3EWgPv27VNeXp7hNL7hq6++cv0E9o6Rw13f+MD3WOf/RcdGKCk1zqPvldyggcJDQyVJO05sO4Zn5HRppqQMZ+E6ZcoUw2kAAIGi+tbdzZs3n/W5f/3rX2v8WN++fZWYmChJmjFjhtauXVvjc995552zDhsJCgrSTTfdJMlZUP7jH/84ay5vs7Yon20bM9yHAhCAW1RfAZjAFmCcUH0QyKpVqwwm8R1jx46V5Cx8Lu3Zw3AanM2qEwVgVqvGHi9q7TabMpKd0/R27KAA9CS73a7eV/aRJC1cuPCUaYsAAFyo2NhYtWjh3NmxbNkyTZ48+bTnVFZW6v7779dXX31V43XCwsL029/+VpJz58h1112n/fv3n/a8H374QQ8++OA5c/3lL39RXFycJOfgkX/+85+nDR6prrCwUG+88YbrvGpPys7OliStX79excXFHn+/+o4hIADcwloBGB0dr/Cwc0+rQv2QmdnGNQhk1apVGj68fp939+OPP+r777+XJN0ydLDCQkIMJ0JNSsrKtP7E1zVPn/9nyWzYUJv27NXRo0d1+PBhxcfHe+V966PeV/bR5y9Nk8Ph0CeffKJ7773XdCQAQAC47777XGf/XXvttbruuus0YMAAxcfHa/PmzXrvvfe0bt06tWvXTmFhYVq2bNkZr/Pwww/rk08+0erVq7V69Wq1bdtWd9xxhzp27KiysjLNmzdP7777rux2uy6//HJ99tlnks48mbdx48aaNGmSLrvsMpWWlur+++/XK6+8oquuukpt2rRRdHS0jh07pm3btumHH37QrFmzVFJSoqefftpzn6gThg4dqlWrVqmwsFCXXXaZbrnlFiUnJ7t+8Nq+fXs1bszxUu5CAQjALawCkAnAqC40NFyNGzXXrt3rtWLFCtNxjHvttdckSWEhwbpp8CDDaXA2a3fuVEVlpSTPn/9nqX4O4I6dOygAPahR88Zq0i5LO1Zv1+TJkykAAQBucffdd+uHH37QW2+9JYfDoQ8//FAffvjhKc9p3769pk2bpttuu63G64SHh2vGjBkaOXKkVq1apfz8fD3//POnPCcyMlLjx4/XqlWrXAVgTEzMGa83bNgwLViwQDfffLM2bNigTZs26YUXXqjx/YOCgpSamlrbP/YFe/DBB/Xee+9p3759mjlzpmbOnHnKx8ePH69bb73V4znqC7YAA3ALawtVEuf/4WeaNu0kSVq+fHm9PuB3//79mjZtmiTpit69ldQg1nAinM2KLdtcj721ArBBVKQaRDlXUHMOoOf1Gd1XkrRmzRqtWbPGcBoAQCCw2Wx68803NWXKFI0YMUKJiYkKCQlRamqqBgwYoJdfflnff/+9a+vr2aSlpemHH37QSy+9pN69eysuLk4RERFq1qyZfvOb32j58uW69tprTzkDMCEhocbrdevWTWvXrtXHH3+sm2++Wc2bN1dsbKyCgoLUoEEDtWvXTjfccIPGjRun3bt3a8yYMW75nJxNo0aNtHz5cj3wwAPq0KGDYmJiOB/bg1gBCMAtTq4ApADEqZo17aS58z7UgQMHtGvXLmVmZpqOZMTEiRNVXl4uSfrVsCGG0+BcVm51TgBOaBirBgnRXnlPm2zKSE5WQeEO7dy5Uw6Hg2+CPajnZb304TPvy1Hl0JQpU9S2bVvTkQAAAWL06NEaPXr0WZ8zZ86cc14nJCRE995771lXqlvHy8TFxZ3z+2y73a5rrrlG11xzzTnf+0yeeOIJPfHEE7V67sCBA2v1w/9GjRrpxRdfvKA8OD+sAARQZyUlJTpw4IAkKYEVgPiZnJzOrsc1nXMS6CoqKvT2229Lkro2b6b22VlmA+GcXANAWnr3WIOMZOc24OpfV+EZcSnxatuvnSRp8uTJZz0QHQAAX/Tdd99p+fLlkpyFGz84xNlQAAKos+oTFJNYAYifSW/cQmEnBsNY36DUN//9739d/53cMnSw4TQ4l6NFRdqSmydJym7t3a9p6cmJrse7du3y6nvXR72vcm4Dzs3N1aJFiwynAQDgpOXLl+vYsWM1fnzt2rW64YYbXP98zz33eCMW/BhbgAHU2Z49e1yPGQKCn7Pbg5Sd1UHrNyyutysA33rrLUlSYmyMLu7R3XAanMuqrdtdj729AjA6PEJx0dE6cvy4du3apa5du3r1/eubriO76e2/hKmsuFQff/yx+vXrZzoSAACSnN8/TpgwQcOHD1fPnj2VmZmp4OBg5eXlad68eZo6daoqKiokSddff72GDx9uODF8HQUggDqzzv+TKABxZs1yOmn9hsVatWqVysrKFBoaajqS12zYsEHz58+XJN04aKDCQkLMBsI5Wef/SVKTFmlef//0pEQdOX5cu3fv5hxADwuPCleXEV21eOoiff7553r++ecVHh5uOhYAAJKkwsJCffrpp/r0009rfM5NN92kN99804up4K/YAgygzqwCMCgoWHENkg2ngS/Kaeo8B7C0tFRr1641nMa7rNV/dptNNw0eaDYMamXVNuf5f6mZSYqM9n4ZlJ6UJEkqLi5W/sF8r79/fdP7yj6SpGPHjunrr782nAYAAKc//elPev7553XxxRerZcuWSkpKUnBwsBo0aKA2bdrozjvv1MKFCzVx4kSFhYWZjgs/wApAAHW2c+dOSVJiQiPZ7UGG08AX/XwQSKdOncyF8aLjx49r0qRJkqQR3bqoUWLiOV4BX7DyxACQ7JZmzjT9+TmAyUn8YMWT2l7UTrFJsTqaf1QffvihrrjiCtORAABQZmam/vSnP+lPf/qT6SgIEKwABFBn1grApKR0w0ngqxLiUxUfnyqpfg0CmTRpko4fPy5JumXoEMNpUBv7jxzR3oOHJElZrcwUgDERkWoQFSVJ2rWTQSCeFhwSrD6jnWf/zZo1S7m5uYYTAQAAuB8FIIA6syZVUgDibJqd2AZcXwaBOBwO1/bfZo0aqU+b1oYToTas1X+SlNXK3Jmm6UnOVYDVz1iF51z0i/6SpKqqKn300UeG0wAAALgfBSCAOqmsrHRNAU6mAMRZ5OR0kiRt2bJFhw8fNhvGC77//ntt2LBBkvTLoYMY5OAnVp0oAIOC7MpslmosR+MTBWBRUZEOHjxoLEd90bhlupp2zpEkffDBB3I4HIYTAQAAuBcFIIA6ycvLc42fZwIwzqZZThfX46VLlxpM4h3vvvuuJCksJERX9e1jOA1qy1oB2LhpikJCzR2VnJ6c5HpsrbKGZ/W/doAkaevWrVqyZInhNAAAAO5FAQigTqr/xTQ5KcNgEvi6ptkdFRwcKkkB/5frgoICffbZZ5KkS3p2V9yJ89zg2xwOh1Zs3SpJyjZ0/p+lQWSUYiIjJMm1yhqe1eOyXgoNd36Nev/99w2nAQAAcC8KQAB1Ur0ATGIFIM4iNDRc2VntJUmLFy82nMazpkyZouLiYknSDQMHGE6D2tp54ICOHC+UJGUZmgBcXaOEBEkUgN4SGRuprqO6S5KmTZvmGuADAAAQCCgAAdSJVQDa7UFKSEgznAa+rmWLHpKkFStWqKSkxHAaz3A4HK7tv80apalHyxaGE6G2qg8AyW5t/gcaaYnOcwALCgp0vJAyyhv6X+cs7IuKijRt2jTDaQAA/sJms/nNr2+++cb0pwuGuLUAvPHGGzVv3jx3XhKAj7MKwPj4VAUFmTsvC/7BKgDLysr0448/Gk7jGStXrtTq1aslSdcP7M/wDz9iDQAJDQ9RWpNkw2mkRokJrsd7drMK0Bta9mql5Aznv/sPPvjAcBoAAAD3cevf1j/88EN99NFHatGihe666y7dcsstSkhIOPcLAfit3bt3S2ICMGqnRfOustlscjgcWrJkiXr37m06kttZq/9CgoJ0db++htPgfKzY4jz/r0nzNAUFmd8kkdwgViHBwSqvqNCevXvUsmVL05ECnt1uV79r++vTF6doyZIl2rJli3JyckzHAgD4iWdvv1Wtm2SajnGadTt26uG3JpiOAcPcvlzH4XBo48aNevDBB/WXv/xF11xzjX7961+rX79+7n4rAD5g586dkjj/D7UTFRWn9MYttWv3+oA8B/D48eOaMmWKJGlEt65KjI01nAi1VVlVpdXbd0jyjfP/JMlusys1Pl67DhzQ3j17TcepN/pdc5Gm/uMTORwOvffee3r88cdNRwIA+InWTTI5/gU+y60/3p4zZ46uv/56hYaGyuFwqKSkRO+9954GDBigtm3b6qWXXtKRI0fc+ZYADKqqqnIdTp/EBGDUUosWzkP2ly5dqsrKSsNp3Gvq1KkqLHQOkbhhEMM//MnmPXtVVFoqyTfO/7NY24D37dun8vJyw2nqh8TGSWrbv50k5zbg0hP3BQAAgD9zawHYv39/vf/++9q9e7f+3//7f2rRooUcDoccDofWr1+v++67T40bN9Ztt92m7777zp1vDcCA/fv3u/5ixApA1JZ1DuDRo0e1bt06w2nca+LEiZKkjORk9W3T2nAanI/qA0B8ZQWgdLIArKqqUl5enuE09cegm4dIkvLz8/XFF18YTgMAAFB3HjngJjExUQ8++KDWr1+v2bNn67rrrnOtCiwuLtY777yjfv36qUOHDnrllVd09OhRT8QA4GHWABBJSkrmDEDUjlUASgqobcAbNmzQsmXLJEk3DOwvu938GXKoPasAjIqNUHKjeMNpTkpNiHcNkrFWXMPzOg3prPhU530wYcIEs2EAAADcwON/OxkwYIA++OAD7d69Wy+88MIpqwLXrFmj3/3ud2rUqJHGjBmj77//3tNxALiRNQBEkpISKQBRO4kJaa77JZBWg0+aNEmSZLPZdM1FnHvrb6wCMKtFI5+a3BweEqrEmBhJ0t69nAPoLUHBQRpwwyBJzq9T69evN5wIAACgbry2PCExMVEPPfSQ1q9fr5kzZ+q6665TSEiIHA6HioqKNH78ePXu3VudO3fW66+/ruLiYm9FA3CBrAEgNptNiQlphtPAn7Ru7Zz+u2DBAlVVVRlOU3eVlZX6+OOPJUn92rZRaoLvrCDDuZWWl2vdia9nWa18Z/uvJe3ENuA9e/bI4XAYTlN/DLhhoOwnpkG//fbbhtMAAADUjZH9SYMGDdJzzz2nW2+9VZJcP2l3OBxatWqV7r77bmVmZur//u//AuIvhkCgslYAxjVoqJCQMMNp4E/atXGukDt06JBWr15tOE3dLViwQLm5uZKkq/v1NZwG52vdzl0qPzGQxpfO/7NY5wCWlJTo0KFDhtPUH/GpCeo8rIsk6aOPPnIN+AEAAPBHXi0Aq6qqNHXqVI0aNUo5OTl6/fXXJTmLv+joaA0bNsy1KvDgwYN66KGHNHjwYFYDAj7KWgGYlMT2X5yfNm36uB7Pnz/fYBL3sLb/RoWHa2S3robT4Hyt3LrV9Ti7le8NNGqUmOh6zDmA3mUNAzl27Jg++eQTw2kAAPCOW2+9VTab7bRf0dHRatWqle68806tXLnytNdlZWWd9hq73a64uDh169ZNjz76aK2Gms2ePVtjxoxRy5YtFRsbq8jISGVnZ+uGG27Qp59+6vY/7/Lly/XXv/5VgwYNUkpKikJCQhQXF6fevXvrueeeC5i5FV4pAHfs2KFHH31UGRkZuvrqqzVjxgxVVVXJ4XCoffv2euWVV7Rnzx59/fXX2rVrl/72t78pOTlZDodD8+fP1z/+8Q9vxARwnqwVgBSAOF/xcSlKb9xCkjR37lzDaerm+PHjmj59uiTp4u7dFBnOalh/Y53/F5cUo7ikGMNpTtcgKlJRJ+4rCkDvatOvrRo2aSiJbcAAgPonJCREKSkprl8lJSXasGGD3njjDXXr1k1jx4494+uioqJcr0lMTFRBQYGWLVumv/3tb2rXrl2NgwCPHDmiyy+/XIMHD9abb76pjRs3qqKiQkFBQdq+fbs+/PBDjR49Wr179z7lPPq6eO+999S1a1c99dRTmjNnjg4cOKDo6GgdPXpUixcv1sMPP6z27dtr7dq1bnk/kzxWAFZWVurTTz/VyJEjlZOTo2effVa5ublyOBwKCQnRjTfeqPnz52vlypW6++67FR0dLUlKTk7Www8/rHXr1qlt27ZyOBz64IMPPBUTwAVyOByuKcAUgLgQbdo4t8ouWbJEpaWlhtNcuOnTp6uoqEiSdPVFbP/1R64BID64/VeSbLK5VgEyCMS77Ha7Bt40WJK0cuVK/fjjj4YTAQDgPX369FFeXp7rV1FRkWbMmKFmzZqpoqJCv/3tb8+4EvChhx5yvebAgQM6evSoxo4dq5iYGB08eFDXXHONSkpKTnlNQUGBLrroIn3++ecKDQ3Vn//8Z23evFlFRUU6duyY9u7dqxdeeEExMTFavHixevfu7dqRVhfl5eWKiIjQ7bffrm+++UaFhYU6fPiwjh07prfffltJSUnauXOnLr30Ur/fner2AnD79u165JFHlJmZqWuuuUbffPONa7VfVlaWnn32We3evVsTJ05U3741/0UpISFBf/jDHyRJ27Ztc3dMAHV08OBB1xfApETf2zIH32edA1hUVKQffvjBcJoLZ23/bZyYqF6tWhpOg/N1vLhYm/c6z2/0xQEglpR452CZQ4cO+XVh7o8uunaAgkODJUnjx483nAYAAHNCQ0M1bNgwTZs2TSEhIaqqqqpxFWB1MTExuuuuu1y7O/fs2aNp06ad8py77rpLq1evVnh4uL766is999xzysnJcX08LS1Nf/zjH7Vw4UIlJiZq9+7duuGGG+o8N6J3797aunWr3nzzTQ0dOlQRERGSnKsYb7nlFtf3+tu2bXMN/fNXbi0AR4wYoWbNmum5555zrfaz2Wy65JJL9MUXX2jLli3685//rKSkpFpdLz3duaro580wAPOs1X+SlJyUYTAJ/FWrVr1ktwdJ8t9zAPfs2aMFCxZIkkb36yO73chsLdTB6u07XJN1s1v67g8zUuPjXI9z83LNBamHYhJi1P2SnpKkTz75RPn5+YYTAQBgVps2bdStWzdJOq8f5N98882u75erv27ZsmX66KOPJElPPvmkBg8eXOM12rdvr//85z+SpEWLFmnq1KnnG/8ULVu2VGpqao0fHzRokJo0aeLKWZO1a9fq9ttvV1ZWlsLDwxUfH69+/fpp7NixqqioqFNGd3Hr31Sqr/Zr2LChHn74YW3ZskWff/65Ro0a5Zr2W1uRkZHKzMx0fbIB+I7qBSArAHEhIiNilNO0kyRp3rx5ZsNcoE8++cRVHo3u2+ccz4Yvsrb/SlITH90CLDlXAFrfR1kTp+E9w28fIUkqLS3lLEAAAHRywVZBQUGtXxMeHq7EE8eaVH/duHHjJEkNGjTQvffee87rXHfddWrevPkpr/UkaxFbTUXeO++8o44dO2r8+PHasWOHwsPDVVhYqIULF+qee+7RgAEDdOTIEY/nPBe3L1W46KKL9P7777uGedSlvOvfv7+2b9+urdWm8wHwDacUgJwBiAvUprXzKIjly5f75XQtawpZ++ws5TRKM5wGF8IqAJMbxSs6NsJwmpqFBgcrMcY5oCQv99zT8+Be2R2bqllX5180xo8fr7KyMsOJAAAwa8eOHZKk+BPHlNRGYWGhayV99dfNnj1bkjR8+HBFRkbW6lpXXHGFJGnhwoUeXWF36NAhrV69WpLUrl270z7+/fff64477lBFRYVGjRqlzZs368iRIzp+/LjeeustRUZGatGiRbr99ts9lrG23FoA/vTTT5o7d66uv/56hYSEuPPSAHyMVQDGxiYpNDTccBr4q/btLpLkHBw1Z84cs2HO0+bNm/XTTz9Jki7v1dNwGlwoqwDMbuX7K5lTE5zfKLMC0Izhd4yUJO3bt0+fffaZ4TQAAJizdOlS1xbeXr161fp1Y8eOde2esV5XXl6uzZs3S5I6depU62t17NhRkrNUtMpIT3jqqadUWlqqmJgYXXPNNad9/NFHH1VFRYW6dOmiadOmuc4tDA0N1W233aY33nhDknPhwJIlSzyWszbcWgC2bdvWnZcD4MOsAjCZ1X+og+bNuioqqoEkacaMGYbTnJ/q541c2rOHuSC4YIeOHdOuAwck+fYAEIs1CKSwsNAvV8z6u64juymhkXPb0rhx41x/gQEAoL7Yu3ev3n33XV1++eWqqqpSaGiofvvb3571NZWVldq8ebOefPJJPfLII5KkZs2a6dJLL5XkXGFnsbYH10b12RIHDx48nz9GrX3xxRd66aWXJDmLwOTk5FM+fvjwYX377beSpIcffviMC+FuuOEGtWzpHBRonXNoSrA7L2a322W32/XJJ5/o8ssvr/Xrvv76a1188cWy2WweXbpZUFCgyZMn6/vvv9fBgwcVFhamnJwcXXzxxefVWv9cRUWFpk+frrlz52rv3r2SpMaNG2vAgAG65JJLFBx85k/zvn37tHbtWm3evFlbtmzR1q1bXQNPavuT5Qt9b6Cudu/eLUlK5Pw/1EFQULA6th+kRYunaubMmaqsrFRQUJDpWOfkcDhc23+7Nm+mxkm1/2YFvmNVtfP//GEFYFrCya0yubm5io2NNZim/gkKDtLQXw3TpGc/1IoVK7R06VL16EH5DwAIXHPnzq1xlkNkZKQmTJigFi1anPaxJ598Uk8++eQZX9ekSRPXFGFftmLFCt14442qqqrSlVdeqT/84Q+nPWf58uWuHwiebXDJ0KFDtWHDhrMOEfEGt7dDF/rTUE//FHXnzp165JFHXAdNRkREqLCwUCtWrNCKFSt02WWX6c477zzv6xYXF+uxxx7Txo0bJTmXeUrOrWGbN2/WwoUL9dRTTyk8/PQtkh988IFmzZp1wX+murw3UBcOh0M7d+6UxApA1F2nTkO0aPFU5efn68cff3RNFPNl69atc33tvbw323/9lbX912a3KbNZzdPffEVibIxCgoNUXlGp3Nxc10+T4T39bxioqf/3icpKyvTaa69RAAIAAlpISIgSEhIkSTabTZGRkUpPT9dFF12kX//618rMzDzj66KiohQdHS3JuVAsJiZGzZo108iRI3Xrrbcq5sS5xpJc15fObyWfdZbgz6/hDuvWrdPw4cN19OhRDRw4UB988MEZi9ADJ3aShIeHnzWDNTBl//79bs15vurF8rDy8nI988wzKigoUJMmTfTAAw8oOztbpaWlmjZtmt577z19/vnnys7O1tChQ8/r2q+88oo2btyoqKgo/f73v3etJFy8eLH+/e9/a/369Xr11Vd1//33n/Zam82mtLQ0NWvWTDk5OSouLj6vJaF1eW+gLgoKCnT8+HFJUlIiBSDqpkO7AbLbg1RVVamvv/7aLwpAa/Wf3WbTJT26G06DC2UVgI2ykhUWEWo4zbnZbXY1jIvTnvyDnANoSHRctPpec5FmT5yp6dOna8+ePWrc2PdXjwIAcCH69OlzQed0P/TQQ3riiSdq9dyQkBDl5ORoy5YtWrFiRa3fY+XKlZKcKxHrMnz25zZt2qQhQ4bowIED6tWrlz7//POAWVTl9inAF6KoqEiSPPZJ/frrr5WXl6ewsDA9/vjjys7OliSFhYXp2muv1ahRoyRJEydOPK8tyNu2bdO8efMkSb/73e/Uu3dv2Ww22Ww29e7d2zW+es6cOWc8lPLee+/VuHHj9Mc//lGjR492HRbpjfcG6sJa/ScxARh1Fx0dpxbNnaXfN998YzjNuTkcDtf5f71at1LDuDijeXBhHA7HyQEgLX3//D9L6olzAPft26eqqirDaeqnYbcNl+Q80+jNN980nAYAAP9nbZ+dMWOGqx86l2nTpkmS+vbt67btxFu3btXgwYOVm5urzp0766uvvnKtZDwT60zAkpKSU84y/Dnr+KyGDRu6JeeF8okCcPHixZI898mwGuv+/fufdmijJF199dWy2Ww6dOiQa6JjbcydO1cOh0NpaWnq3bv3aR/v06eP0tLS5HA4NHfu3NM+Xpdzrur63kBdWF/AJApAuEenjkMkSWvWrDnl/vJFK1as0Pbt2yVJlzH912/lHTqsAyeOBcnyg/P/LNYk4PLycuUfzD/Hs+EJjZo3VrsB7SVJ77zzjmtFPAAAuDC//vWvJTl3mr388svnfP5HH32kTZs2SZLuuusut2TYsWOHBg0apN27d6tdu3aaMWOG4s7xg/4uXbq4tgbPnDmzxudZH+vatatbsl6oC94CvGrVqhqXZ86aNUtHjhw56+sdDocKCwu1fPlyTZw4UTabTd27u38bVXFxsevG6NKlyxmfk5ycrPT0dO3atUsrV65U586da3XtVatWSZI6d+58xv3gNptNnTt3Vm5uruu57mLyvYFTVgAyBARu0LnTEH046X8lOX/yd/vttxtOVDNr+29wUJBGdTf7P3FcuJXVBoBk+eEKQMk5CKRhstmfJNdXI++8WKvn/qSCggJNnDhRd999t+lIAAD4rW7duumaa67R5MmT9de//lXdunWrcajGTz/95Jo83Lt3b1111VV1fv89e/Zo8ODB2rlzp1q2bKlvv/32lCnDNYmPj9ewYcM0Y8YMPffcc7ryyitPW434wQcfaP369ZKk66+/vs5Z6+KCC8BPP/1UTz311Gm/73A4XGOSa8vhcMhms3nkm6fdu3e7BoycbV94kyZNtGvXLu3atatW13U4HK5VKme7rnUoZm2v6+vvDUgn76noqDhFRNS8JBqorUZpzdSwYRPt379DX331lc8WgA6HQ9OnT5ck9W3TWgnVDjCGf7EKwOCQIKU3TTGcpvZiIiMUFR6mwpJS5ebmqWOHjqYj1UttL2qnjDaZ2rV2p8aNG6c77rjD56cZAgDgy15//XWtXbtWa9eu1ahRo/TAAw/ozjvvVNOmTSVJeXl5evfdd/XMM8/o6NGjSktL0wcffCC7vW4bW/fv368hQ4Zo69atysnJ0cyZM5WSUvvvDZ9++mnNmjVLy5cv15VXXql///vfysnJUVlZmd577z3X8WyjR482PjysTp8ph8Nxyq+afv9cv1JSUvT666+fdWzyhaq+D/tsU1msjx0+fLhW1y0uLlZJSUmtr1tcXKzi4uJaXduX3xuQTq4ATE7OMJwEgcJms6lHN+d5rPPnzz9lqpcv+emnn1wF+Mjuvj+sBDVbuc1ZAGbkpCo45MKP5PA2m2xKObEKMI9BIMbYbDaNuusSSc4fNlvnEAEAgAsTFxenBQsW6OKLL1ZZWZmee+455eTkKCoqSrGxsUpLS9Of/vQnHT16VD169NDixYvdMvxj7Nix2rBhgyRnGdi1a1elpqae8dfo0aNPe32PHj305ptvKjg4WF9++aWaNWum+Ph4RUdH6/bbb1dRUZH69OnjE+cGX/AKwCuvvFJZWVmn/N5tt90mm82me++9t8bttha73a7o6GhlZ2erffv2dToP72ysokxyDv2oifWx2hZl1Z9Xm+tar4mIiKjV9b393hMnTtT7779f48dvuOEG3XjjjeeZ1HOslt9utyu+2nYoXBhrG3mDBg1OKfNrsmfPHklSakqWW+7pQGN9Pm02G5+f89D/oms0/cuxqqys1Jw5c3TnnXdKOv/705NmzZolyZnp8r69/fLfL/en8weVP23bLklq2iZdwSEX/O2QS1Cw90rERklJ2pqbp/z8fAUFBSk01PcnGNeWP92fA34xUFNe+FgH9+Rr7NixGjNmzBmPZTHJl75+BgK+/3Qv7k/34v5EIIiPj9cXX3yhmTNn6r333tP8+fOVm5uriooKNWnSRD179tS1116r0aNHu+3/udWHqh07dkzHjh2r8bk1Dfq45ZZb1LVrV/3973/XrFmzlJeXp8jISLVt21Y333yzxowZ4xM7BS74O96OHTuqY8dTt53cdtttkqQhQ4bo8ssvr1syeFVhYaH2799f48eLioo8VtLWhc1m88lc/qo2y6cdDoe2bt0qSUpJyfK5v+z4Gj4/tZfTtKNSUrK0b992TZ48+bRjIeq6vN8drOm/PVu1dK3C8mf19f7cmpungsJCSVLT1o1lU90/D+64Rm2lnRgE4nA4tG/fPteRH4HG1+/PkNAQXXrPZXr70fFauXKlZs+erWHDhpmOdUa+8PUzkPD9p3txf7oX9yfcYcKECZowYcJ5v84alFdXQ4YM0ZAhQ9xyrXN54okn9MQTT9T5Om3bttX48ePrHsiD6v4j72qsP+y5Vv95U3h4uOtxaWmpIiMjz/i80tJSSar1T5urP8967dmuez7XNvHeUVFRZ53CHBkZqcrKyvNI6Vl2u102m00Oh+OUxh4XxmazyW63q6qq6pw/gT1w4IAKT/zFuWHDTH5iewbV/9LK5+f89Ol1uT6d9m/Nnj3bOeCgYcPzuj89aePGjVqzZo0k6ZKePfz23y33p/Tj5s2ux1mtGsuhun0ebLLV+Rrno3r5vGfvHmVkBM5xDP52fw6+aYgm/79JKiwo1PPPP++R42zqwle+fgYKvv90L+5P9wrU+5MyE3AftxaAv/rVr9x5ObeofkbeoUOHaiwAraWctV0uHRERoYiICBUXF9e4DLT6da3nu4Mn3vvmm2/WzTffXOPH8/Pza30+ojfEx8crKChIVVVVPpXLXwUFBSk+Pl4FBQXnLHpXrlzpehwfl8b5kmcQERHh+gaMz8/56dplpD6d9m9VVVXpvffe06233npe96cnffDBB67Hgzu299t/t9yf0tL1znNewiJClZwWp4ryigu+ls1mU3BwsCorKr32F9gQu12xkZE6WlSkPbv3qLhD4Px79Lv7M0ga9Mshmv7yZ5o5c6bmzp2rDh06mE7l4itfPwMF33+6F/enewXq/VmbSawAaifg11unp6e7fppsDS44E+tjtf0pus1mU3p6utuv6+vvDVS/55KTuLfgXk0y2yolJUuS9Nlnn5kN8zNffvmlJKldkybKSE42nAZ1YU0AbtIiTfYg//xWKCU+TpJzIh7MGnrrcAWHOn+m/p///MdwGgAAgDPzz+96z0NERISaN28uSVq+fPkZn5Ofn++a6vjzcw3PxvoJ748//ljjc1asWHHKc93F5HujftuxY4ckZxGdmNjIcBoEGpvNpp7dL5UkLVy40GfKjdzcXC1btkySNKKb7xxzgfNXUVmp1dudX8eyW/nv17CGcXGSnKv9y8rKzIap5+IaxqnP6H6SpGnTprm+pwQAAN7zhz/8ocbpvTX9qm8uqABs2rSpmjZtqpycnDP+/oX++vn13GXgwIGSpHnz5unAgQOnffyTTz6Rw+FQQkKC2rdvX+vr9u/fXzabTXv37tV333132scXLVqkvXv3ymazuTK4i8n3Rv1mFYAJ8WkKCal5CjVwoXr3ukKScyLXxx9/bDiNk7X6T5JGdu9mMAnqatOevSo5UZhltWxsOM2FaxjXQJLznLz9B2oe4gXvGHXXxbLZbKqsrNSrr75qOg4AAPVOQUGB9u3bd16/6psLKgC3b9/u+vXz39+xY8cpHz/fX54wYsQIpaamqqSkRE8//bS2bXNu/SktLdXkyZP1xRdfSHKegxccfOqxiGPGjNHll1+uf/7zn6ddNzs7W/3795ckvfTSS1q8eLEcDoccDocWL16sl19+WdL/Z+++w+O8y7Tvf+8Z9d57r+691ySO0xNCgPBk4YGwAQILbJaFhWVhKcsuy8O+y8ISEkNICJAeUpw4ceISl9iO7bjIvUiy5aZiWZIlq5eZ94/RPZbjpjLSPTM6P8fhg0HTTsuKNLrmd12XqwB5pQ193d3dNDU1uf/0nXXT9+NNTU0ef26RwTJbgBMT1f4rwyMzo5jcXNfJ5eeff94rBoObPydyU5IpSvfdU2MCe3q3mAPk+PAJQLMFGKCmevS9gPU2qflpTFnqOh387LPPXnNGs4iIiHje008/7a6J9PfPaDOoJSBZWVmXbGm73setFhgYyA9+8AO+//3vU1FRwSOPPEJYWBjt7e3uDUl33XUXN99884Af++/+7u+oqqri6NGj/OxnPyMoKAjA3Y4zZswYvvrVr17xvocOHeL73//+Fa/76EKOK83CGspziwzWxQKgCssyfBYtuJ/jx/dSWlrKzp07Wbp0qWVZGhsb2bJlCwC3zpjulT/npP/M+X8RUaEkpMRYG2YIQoOC3YtARuM72N7ojq/cye5VO2ltbeWPf/wj3/rWt6yOJCIiIuI2qALg1U7qDdcJPk/IysriN7/5Da+88grbt2/n3LlzhIeHk5eXx5133smcOXMG9bihoaH8/Oc/Z8WKFWzYsIHKykoA8vPzueGGG7jzzjsvO1XoKVY+t4xO3d3d7tlGSToBKMNo7ux7ePb5f6O7u5PnnnvO0gLge++9595OuHTaVMtyiGeYBcCcMek+X8xNiolRAdCLFM4oomhmEUc/PMoTTzzB3/3d3xEaGmp1LBERERFgkAVAXxUTE8NDDz3EQw891O/7/OEPf7jubQICArj33nu59957B5Rn4sSJQ95yOdjnFhmMyspKdyFEG4BlOEVExDB92i1s276CV199lccee8yyLKtXrwYgJiKcaQXDM6tWRkZ7ZyeHT50GIKfYd9t/TUmx0ZRVVlJXV0dnZ6e7E0Csc/tX7uLoh7+krq6O559/nr/927+1OpKIiIgIMAq2AIuI55gLQACSktQCLMNr0YL7AddM1Ndee82SDD09PaxduxaAGydNwm7Tj01fdujkKbp738TIHeu7C0BMyb2bgLUIxHtMXjKFtELX19bjjz9Od3e3xYlEREREXPSbjIj0W98CoE4AynCbOGEhsbEpAPzud7+zJMPOnTvdw/yXTJ1sSQbxnJK+C0D84QRgbwEQtAjEW9hsNm7/yp2AazTOm2++aXEiEREREZcRbwFua2tj2bJlvP/++3R3dzNlyhS++tWvkpqaOtJRRGSAzAUggYHBREcnWZxG/J3NZueGRf+H15b/io0bN3Lw4EGKi4tHNMOqVasAsNtsLJo0cUSfWzzPnP8XlxRFdFyExWmGLiw4mMiwUC60tmkOoBeZ+7F5vPpfL9NQ3cCjjz7Kvffe6/PzJkVEpH8OnThpdYQr8tZcMrI8WgDcvXs3n//85zEMg2XLljF37txLrm9qamLhwoXs37/f/bG33nqLxx9/nFWrVjF1qoari3gz8wRgYkImNrVCygi46Ya/4Y0Vj9LT082TTz7JL37xixF9/jVr1gAwo6iQmPDwEX1u8by95gKQYt9v/zUlx8SqAOhlAoICuOWLt/Pivz/H3r17ef/991m0aJHVsUREZAR876mnrY4gclUe/Q3+r3/9K/v37+fs2bNX3Kr7/e9/n3379uF0Oi/5U1dXxyc+8Qk6Ojo8GUdEPMw8AZioDcAyQmJjU5g5/XYAXnrpJZqamkbsuU+fPs2BAwcAuGmK2n993YXWNsqrqgHIGeP77b+mpNhoAOrq6ujq6rI4jZhueOAGQqPCAPjNb35jcRoRERERD58A3LZtG4ZhsHTp0staHS5cuMCTTz6JYRhkZmby61//mtzcXB577DF+//vfc+LECZ555pkBbegVkZFlngBMStQCEBk5S2/+PFu3v0lLSwsvvPACX/7yl0fkec3Tf6D5f/5gX0UFTqcTgFw/mP9numQRyNmzpKf7z+lGXxYaGcaS/7uEFb99k/Xr17N3714mTZpkdSwRERkm5tgYXzBu3DirI4hFPFoAPHPmDMAVW3lXrlxJe3s7hmHw5JNPsmTJEgCWLVvG1q1b2bdvH6+//roKgCJeqqWlhdraWkALQGRkjSmeTVbmWE6eOsRTTz3FF7/4xRFpQTdfyGUmJlKY5j8Fo9HKnP8HkO1HBcC+i0Cqa6pVAPQiN3/hVt75wzt0d3Tx6KOP8vvf/97qSCIiMkyWLl1qdQSR6/Lob1Dnzp0DuOJCjw0bNrivM4t/pk996lM4nU727t3ryTgi4kGnTp1yX05M0glAGTmGYXD7rX8LQHl5+SUn84ZLa2sr77//PgBLpkzSAH8/sKd3A3ByZjxhESEWp/EccxEIaBOwt4lJimHBJxYAsHz5cvcpehEREREreLQA2NjY6HrQK5zM+OCDDzAM47LiH0BWlquYYJ4uEhHv0/cXlySdAJQRdsPiTxMREQvAb3/722F/vs2bN9Pe3g5o/p+/uLgAxH9O/5nMNmAtAvE+t335DgzDwOFw8Nhjj1kdR0REREYxjxYAw8Jcw44/WshrbGx0n+6bN2/eZfcLCXG9E9/T0+PJOCLiQX0LgFoCIiMtODiMW27+PABbtmxh9+7dw/p869evdz1vYCBzxo4Z1ueS4VfX1MTpc3WAf83/M5ltwFoE4n1S8lKZftsMAJ5//nl3t4yIiIjISPNoATAnJweATZs2XfLxFStW4HA4AJg/f/5l96urc70oj46O9mQcEfEgswAYER5DWFiUxWlkNFp684MEBgYDw38KcN26dQDMGVNMSFDQsD6XDL++8/9yxvjfjLyk2BigdxFI7Vlrw8hlbv/KnQC0tbXx1FNPWZxGRERERiuPFgAXLlyI0+nkjTfeYM+ePQA0NTXxi1/8AoC0tDQmTJhw2f32798PQG5urifjiIgHnTx5EtDpP7FOdFQCC+d/EoA333xz2OZpnT59mtLSUgAWTbz8Z5b4HrMAaLMZZBakWJzG85JiLr6BevasCoDeJn9qAcVzXCeJ//CHP9DS0mJxIhER8TTDMHzmz+rVq63+dIlFPFoA/NKXvoTNZqO9vZ1Zs2YxZ84c8vPz2b9/P4Zh8KUvfemK93vvvfcwDINJkyZ5Mo6IeNDFAqAWgIh17rjty+55WsuWLRuW5zDbfwEWTZo4LM8hI8ssAKbnJhEcEmhxGs8LDw4hvHecytkaFQC90Z1fvRuAhoYGnnvuOYvTiIiIyGgU4MkHmzRpEj/60Y/40Y9+RFdXFx9++CFOp9N93T/90z9ddp99+/Zx+PBhDMNgwYIFnowjIh7idDqpqKgAIEknAMVCKSm5TJ92Kzt2vsNzzz3Hd77zHWJjYz36HGYBMDk2hqJ0/5sXN9o4nc6LC0DG+O+/Z1JMNMer23UC0EtNvGESGWMyOX34FI8//jgPPvgggYH+V4wWERntHvzPvyVrbLbVMS5z8tAJnv6exlCMdh4tAAL867/+K5MnT+aJJ56grKyM8PBwbrnlFv75n/+Z0NDQy27/m9/8BnC9QL/11ls9HUdEPKCuro7W1lYAErUBWCx2x21fZsfOd2htbeWpp57iW9/6lsceu6enhw0bNgCwaMIEDMPw2GOLNSrr6jnX1ARATrH/zf8zJURHc7y6hnPnzuFwOLDZPNrkIUNkGAZ3fOVOfv8Pyzh16hRvvPEGn/jEJ6yOJSIiHpY1NpuiWcVWxxC5omF5dXjPPffw5ptvcujQIXbs2MHPfvYzoqKuvDTg97//PQ6HA4fDQUqK/83lEfEHZvsvQFKS972jJaNLUeEMigpdWzX/8Ic/0NbW5rHH3rNnD+fPnwdg8STN//MHe44dc1/O9fMTgADd3d3U19dbnEauZNbdc4hPjwdcb4CbXTIiIiIiI0FvD4vIdfVdtqATgOIN7rzjKwCcO3eOF154wWOPa27/NQyDBRPGe+xxxTolve2/QcEBpOUmWZxm+CRGX1wEUnO2xsIkcjUBgQHc+sXbAThw4ID7+42IiIjISFABUESuyywAGoZBQoL/ttCJ75g6+WbS0woBeOyxx+ju7vbI45q/kE/IySYuMtIjjynWKikrByCrMJWAALvFaYZPTHg4QQGuyS6aA+i9Fv2fGwiPDgcujsERERERGQkqAIrIdZkFwLjYVAICgixOIwI2m407b3edAqyoqODNN98c8mNeuHCBHTt2ALB4otp//UGPw8He4xUA5I7x7zcvDMMgofcUoDYBe6+Q8BCWPLgUgE2bNrF7926LE4mIiMho4fElIKaSkhJWrlzJ/v37aWhooL29/br3MQyDtWvXDlckERkkswCYqA3A4kXmzf0YL7/6XzQ0VPPoo49y7733Dmlpx6ZNm+jp6QFgkQqAfqHsTCWtHR0A5I717wIguOYAVtbV6QSgl7v580tZuewtujq6eOyxx3jiiSesjiQiIiKjgMcLgFVVVXzhC19g9erVA7qf0+nUtkURL1VRUQFAclKOpTlE+goICOL2W77Icy/+O3v37mXjxo0sXrx40I9ntv+Gh4QwrbDAUzHFQrvLy92XR0MBMDHatXCtvb2dpqamqy5gE2tFJUQz/xMLWP/cOlasWEFVVRWpqalWxxIRERE/59EW4ObmZm688UZWr16N0+kc0B8R8U4dHR2cPn0agORkbQAW73LjDX9DWJiryDHUeVqbNm0CYHZxkXuWmvi2knLXApCI6DASUmKsDTMCEmNi3Je1CMS7Lf3CrYBra/Mf//hHi9OIiIiMboZhYBgG69evtzrKsPJoAfB//ud/OHr0KAAZGRk8/vjjlJWV0d7ejsPhuO4fs/VKRLzHqVOn3EX6pCQVAMW7hIZGcPNNnwNgw4YN7NmzZ1CPU11dTWlpKQDzx4/zWD6xVknvCcC8semjossgPioSm8310k5twN4tvTiDcfNdm8b//Oc/92tUjoiIyEh58MEH3UWxvn8iIiIYM2YMX/rSl674ujsnJ+ey+9hsNmJiYpgxYwY/+MEPqK6uvu7zr1u3ji9+8YsUFxcTFRVFWFgYubm5PPDAA7z22mvD8VceFTxaADT/IVJSUvjwww95+OGHycvLIyhISwNEfNWxY8fcl9UCLN7o1qVfIDAgGIBHH310UI+xefNm9+V548d6JJdYq7W9gyOnzwD+vwDEFGCzE9+7vVqLQLzf0i/cAkBdXR2vvvqqxWlEREQuFxgYSHJysvtPe3s7R44c4Q9/+AMzZsxg2bJlV7xfeHi4+z7x8fE0Njayc+dO/uM//oMJEyawdevWK97v/Pnz3HPPPdx00008+eSTHD16lO7ubux2OxUVFbzwwgvcd999zJ07192lJv3n0QJgeXk5hmHwd3/3dyQnJ3vyoUXEIsePH3dfTtYJQPFC0dGJLFzwSQDeeOONS75m++v9998HICYinLGZWnbjD/afOEGPwwGMjvl/psSY3k3AOgHo9SYvmUpiVhIATzzxhEbiiIiI15k3bx7V1dXuP62traxatYqCggK6u7v52te+dsWTgN/+9rfd96mtraWpqYlly5YRGRlJXV0dn/zkJy87/d7Y2MjChQt58803CQoK4rvf/S5lZWW0trZy4cIFKisr+cUvfkFkZCRbt25l7ty5nDx5cqQ+FX7BowVAR+8L7eLiYk8+rIhYyFwAEhkZ5561JuJt7rj9YQzDhsPh4PHHHx/w/c35f3PHjnG3UIpvK+mzACRnlJwABEiMdhUAm5qaaGtvsziNXIvNbuPmB5cCsH///quehhAREfEWQUFBLF26lOXLlxMYGIjD4bjqKcC+IiMjefjhh/nlL38JwJkzZ1i+fPklt3n44YfZv38/ISEhrFy5kp///Ofk5+e7r09NTeWf/umf2Lx5M/Hx8Zw+fZoHHnjAXYeS6/PobznZ2a7TQRcuXPDkw4qIhczTVGr/FW+WkpzDzBm3A/D8889TW1vb7/ueOHGCEydOADBvnNp//YW5ACQpPY6IqFCL04ycpN4TgAC1Z/v/34FYY+H9iwkOc40w+P3vf29xGhERkf4ZN24cM2bMAGDHjh39vt9nP/tZ95vtfe+3c+dOXnzxRQB+8pOfcNNNN131MSZOnMhvf/tbALZs2cLrr78+0PjXdPr0ab785S+TmZlJcHAwOTk5/MM//AP19fVXvP2Pf/xjDMPghhtuAODll19m4cKFxMTEEBcXx+23337J37WpqYkf/vCHFBcXExoaSmpqKl/72tc4f/68R/8eV+LRAuA999yD0+m8ZJaSiPg28wSgFoCIt7vrjq8A0N7ezh/+8Id+3888/Qcwb5wWgPiLPb3zS0fL/D9TQvTFk9raBOz9wqLCWPCpRQC8/fbbmmckIiI+IyMjA3C17vZXSEgI8fHxl93vd7/7HQDR0dF8/etfv+7jfPrTn6awsPCS+3pCeXk506ZN44knnuD8+fPY7XZOnDjBr3/9a6ZNm3bdluPvf//73H///WzduhWHw0FDQwPvvPMOixcvZuvWrdTW1rJgwQJ++tOfcubMGRwOB9XV1Tz22GMsXbqUrq4uj/1drsSjBcBvfOMbxMbG8uyzz3L48GFPPrSIWKCnp8f9TU7z/8Tb5eVOZtzYeQA89dRTtLa29ut+5ptWidHRFKSlDls+GTnnGps4VXsOGF3z/wBCAoOIDg8HdALQV5htwA6Hg6eeesriNCIiIv1jdtDExsb2+z4tLS2cO3fusvutW7cOgFtuuYWwsLB+PdbHPvYxwPVavru7u98ZruVb3/oW0dHRvP/++1y4cIHm5mbeeOMNEhMTOXHiBA888MBVZ/aWlJTwX//1X/zqV7+isbGRpqYm9u7dS3FxMa2trXzzm9/kS1/6Ep2dne7Hv3DhAn/4wx8ICAhgx44dPPnkkx75e1yNRwuAqampvPDCCwQEBLB06VI2btzoyYcXkRF25swZ97sQKgCKL7jz9ocB1wax/mzVdDqd7gUg88ePxTCMYc0nI6Okz/by0VYAhItzAGtqdALQF6TmpzFh8UQAnn32WTo6OixOJCIicm0ffvihu611zpw5/b7fsmXL3AU0835dXV2UlZUBMGXKlH4/1uTJkwFXUdEsRg5VR0cHK1euZMGCBQDYbDbuvvtuXnnlFcDVcrxy5cor3rexsZHvf//7PPLII+4i5sSJE3niiScA2Lp1K2+//TYrVqxgwYIFGIZBUFAQDz30EJ/73OcAV/vwcArw5IP927/9GwA333wzy5cv58Ybb2TKlCnMnTuXhISEfg1W/+EPf+jJSCIyBJdsAE7OsS6ISD9NnLCY5OQcamoqePLJJ/nMZz5zzaJeeXk51dXVgOb/+ZM95a4CoD3ARlZBisVpRl5iTDRllZXU19fT3d1NQIBHX+7JMFjyf29m/4Z91NfXs2LFCj7xiU9YHUlEROQylZWVrF27lu985zs4HA6CgoL42te+ds379PT0cPz4cZ599ln+8z//E4CCggLuuusugEtm65ntwf2RkJDgvlxXV3fJwpDBuv/++ykoKLjs4wsXLmTRokVs3LiRl19+mTvuuOOy2wQFBfGP//iPl318/vz5hISE0N7ezqc+9akrPv6SJUt46qmn2Ldv35D/Dtfi0VeE5vBDAMMwcDqdlJSUUFJS0u/HUAFQxHuY8/9AMwDFN9hsNm6+6XM8+/y/sX//frZv387s2bOvenvz9B9o/p8/2d1bAMzMTyEwaPQVvxJ75wA6HA7OnTtHSsroK4L6mkk3TSEuNY76qnr+9Kc/qQAoIiJeYcOGDVd9Mz0sLIynn36aoqKiy677yU9+wk9+8pMr3i87O9u9RdjbmIs8rmTx4sVs3LiRXbt2XfH6nJwcIiMjL/u4zWYjISGB06dPM2HChCveNzk5GYCGhoaBhx4Aj78q/mg/9NX6o69ErVci3sU8ARgSEkFUZP/fjRGx0qIFn+Svr/wXHZ1tPPnkk/0qAGYkxJOVlDhSEWUYOZ1OSsrNBSBpFqexRlJMjPvy2bNnVQD0AfYAO4v+zw28/j+v8sEHH3DkyBGKi4utjiUiIqNcYGAgcXFxgKteExYWRkZGBgsXLuTLX/4yWVlZV7xfeHg4ERERgKsAFhkZSUFBAbfddhsPPvjgJYUy8/HBdZKvv8xZgh99jKFIT7/66BjzurNnz17x+tTUq88St9vt17yNeb2nZhlejUcLgObgRhHxD2YBMDk5RwV68Rnh4THMm/dx1q1/jjfffJPq6uorFkCcTidbtmwBYO5Ytf/6i+PVNTT1LoDJGWUbgE0RoSGEBgXR1tmpTcA+ZPEDN/DG/76Oo8fBn/70J372s59ZHUlEREa5efPmsX79+gHf79vf/jY//vGP+3XbwMBA8vPzKS8vH1D36J49ewDXScTsbHWr9YdHC4CLFy/25MOJiMXMFuDkxCu/syPirZYu+Tzr1j9Hd3c3zz77LN/61rcuu01paan7XcY5Y8eMdEQZJubpP4C8cRkWJrGOgUFiTAwnz57lbM2V36UW7xObEseUm6ey692dvPjii/zgBz/o9yZEERERX3bTTTdRXl7OqlWraG1t7dfPv+XLlwOuGXueaieurKy87nVJSUkeeS4reHQLsIj4D6fTebEAqAUg4mOyMsdSWDAdgOeffx6Hw3HZbT744AP35dlj1GrnL8wNwKHhwSRnjN7RBeYcwNra2gGNYxFr3fjZJQA0NTXx+uuvWxtGRERkhHz5y18GXJt0H3300eve/sUXX6S0tBSAhx9+2GM5NmzYcN3rpk2b5rHnG2kqAIrIFdXU1NDa20anBSDii25Y9H8AOHHihLvVty+zAJgaF0dmYsJl14tvMk8A5hSnYbON3tEFSTHRAHR1dQ37QGnxnPELJ5CY6ZpH+qc//cniNCIiIiNjxowZfPKTnwTgRz/6Ee+9995Vb7tv3z735uG5c+fy8Y9/3GM5XnzxRY4dO3bZx7ds2cLGjRsB+NSnPuWx5xtpw14APH36NKtWreKFF17gz3/+83A/nYh4iDn/DyA5Kce6ICKDNGvmnQQHu9oHnn322Uuuczqd7gLgrOIizbj0Ex1dXRw8cRKA3LGjc/6fKbG3AAhXH1Yt3sdms7H4b24EYNeuXRw4cMDiRCIiIiPjiSeeYNy4cbS3t3P77bfzve9975JiXHV1Nf/1X//FggULqKurIzU1leeffx6bzXNlraCgIG677TY2b94MgMPh4K233uK+++7D6XQyb948br/9do8930gbtgLgU089xfjx48nOzub222/nM5/5DF/4whcuu91//Md/cMstt/DQQw8NVxQRGQSz/RfUAiy+KTQ0gjmz7gZgxYoVNDY2uq87deqUe47HrDFFluQTzzt88hSdvdvTckfpAhBTbEQkAb0b5bQIxLcs+ORCbHbXS/Tnn3/e4jQiIiIjIyYmhk2bNnHHHXfQ2dnJz3/+c/Lz8wkPDycqKorU1FS+853v0NTUxKxZs9i6davHl3/8f//f/8f58+dZsGABkZGRREREcNddd1FTU0N2djbPP/+8Tx8c8HgBsK2tjTvvvJMvfelLHD58GKfT6f5zJTNmzGDNmjU8/fTTHDp0yNNxRGSQzBOAgQHBxMYkW5xGZHAWL7ofgPb2dl599VX3xzX/zz/t7rMAZLSfALQZBgnmHMCztRankYGISY5l0o2TAXj55Zfp7Oy0OJGIiMjIiI2N5a233mLNmjV84QtfoKCgAMMw6O7uJjs7m/vvv5+//vWvbN26lawszy+qLCgoYNeuXXzxi18kJiaGnp4esrKyeOSRR9i1a9ewPOdI8ugWYIDPfe5zrFy5EoCcnBweeOABGhoaWLZs2RVvv3TpUhITEzl37hwrVqxg7Nixno4kIoNgFgCTkrI8eqxaZCQVFswgNSWfqupynnvuOfdJdLMAGBcZSWFampURxYPMBSBxSVHExEdanMZ6idHRVNc3qAXYBy389GJK1uymvr6ed999l7vvvtvqSCIiMoo8/fTTPP300wO+X98usqFYsmQJS5Ys8chj9cdHD6w98cQT/b7vj3/8Y3784x9f8zbX+7zccMMNI7K0zaO/1a9du5ZXXnkFwzB44IEHOHLkCP/xH//BrbfeevUANhtLly7F6XSyadMmT8YRkSEwv0lpAYj4MsMw3KcAS0pKKCsrAy4WAGcWFfr0MX651J7eE4Cjvf3XlBjtmgPY0tJCS0uLxWlkICbfNIWoBNcJzueee87iNCIiIuIPPFoANCvEeXl5PP300wQGBvbrfpMnu9oc1AIs4j3ME4Ca/ye+bs7se9yXX331VWpqatwDhdX+6z/Ot7RQXlUNQI4KgIAWgfiygMAA5t23AID33nuPqqoqixOJiIiIr/NoAXDz5s0YhsHnPve5fhf/ANJ626+qq6s9GUdEBqm+vt69MCE5UScAxbclxKdTVDQTcBUA+87/m6UCoN/Ye+zi5vK8UT7/z5QQFeU+4aoCoO9ZeP9iwLWB8IUXXrA4jYiIiPg6jxYAa2pcW+aKiwf2C1VISAjgGtIuItYrLy93X05NzbMwiYhnzJtzL+D62l6xYgUA4SEhjMvKtDCVeFJJb/uvYTPILtZcR4CggABiwsMBFQB9UXpROvnTCgBXG/BIzAYSERHxVY888ggpKSkD+jPaeHQJiN1uB1zvVA5EfX094Fr7LCLW61sATElRAVB836wZd/DnZ36Iw9Hjnjc7o7CAgN6fW+L7zAJgWnYiIaFBFqfxHokx0TQ0N6sA6KMW3r+Y8l1lVFRU8MEHHzBv3jyrI4mIiHilxsZG96E0uTKPngBMTk4GcA9Z76+dO3cCkJmpkxgi3sAsAAYGBhMXm2pxGpGhi4qKZ8L4hQDU1dUBmv/nT5xOJ3t65zrmqv33EuYikIaGBrq6uixOIwM1++7ZBAa7xuq8/PLLFqcRERHxXk8//TROp3NAf0YbjxYA582bh9Pp5PXXX+/3fVpaWnj55ZcxDIMFCxZ4Mo6IDJJZAExOzsFm8+i3CRHLzJ1zzyX/X/P//MeZujpqG5sAbQD+KHMRiNPppLa21uI0MlChkWFMvWU6AG+88YbG5YiIiMigefQ3+0996lMA7N69m6eeeqpf9/nqV79KQ0MDAJ/5zGc8GUdEBsnckJqarPZf8R/Tp92K3e46SWO3GUzOy7U4kXiK2f4LOgH4UeYJQNAcQF817775ADQ1NbFq1SqL04iIiIiv8mgB8K677mLOnDk4nU6+8pWv8J//+Z80Nzdf8ba7d+/mzjvv5Nlnn8UwDG6//XZmzZrlyTgiMggOh8NdAExJUYFE/EdYaCRxsfkA2G12ggI8OgZXLLSntwAYFBxAem6SxWm8S0RICOEhwYAKgL5qwqKJRMZHAfDXv/7V4jQiIiLiqzze2/fiiy+SkpJCd3c3P/jBD0hKSuIf/uEf3NfPnDmT1NRUZsyYwTvvvIPT6SQzM5Onn37a01FEZBCqq6tpa2sDtABE/EtXVxehwRkAdHZ3s/d4hbWBxGN29xYAs4vSsNs1tuCjzFOAKgD6poDAAGbfPQeANWvWuJfniYiIiAyEx18lZ2Zmsm3bNvdJwPb2dk6ePIlhGADs2rWLmpoa99DF2bNns2XLFhISEjwdRUQGoe8G4FSdABQ/Ul1dTWREDuD6efTujp2W5hHP6OpTzM0bp/bfK0noLQDW1tbicDgsTiODYbYBd3V1sXz5covTiIiIiC8alv6nzMxMtmzZwptvvsmf/vQnNm7cyLlz59zXR0REsHjxYj7/+c/zyU9+cjgiiMgg9S0ApmgGoPiRM2cqCQgIJTwsjZbWM7y7cxffuV8/g3zd4VOnae/sBCBvbIbFabxTUu8ikO7ubhrONxAfF29xIhmo3Ml5pOSlUH2smpdffpkvfOELVkcSEZErOHnohNURrshbc8nIGtYBSHfffTd33303AK2trZw/f56IiAiioqKG82lFZAjMAmBYWBSRkXEWpxHxnMrKMwCkJY2jtOIMpWcqOVZVTV5qisXJZCh2l1180yJvnAqAV/LRRSAqAPoewzCY+/H5vPbfr/Dhhx9y7Ngx8vL0Jp2IiLd5+nv9W4YqYoURG5QTFhZGWlqain8iXs4sAKam5Llb90V8ndPppLKyEoDxeRcXTr2jNmCft6v3e1ZsYhSxiXqNcSUxEREE2O2A5gD6snkfn+++rGUgIiIiMlCalC0ilzALgMnJmv8n/qOhocG93KYwo4DslAJAcwD9gXkCUKf/rs5mGCRGu4qjZ2tUAPRViVlJFM4oAuC1117D6XRanEhEREzmjgNf+LN06VKrP11ikUG1AP/bv/2bp3O4/fCHPxy2xxaRa+vq6uLECdd8CC0AEX9y5swZ9+W0+DimFs3nRHUZJceOU9fURLxOp/ukhgvNHK+uAbQA5HoSoqOpqm/QCUAfN/ueOZTuOEpZWRkHDhxgwoQJVkcSERERHzGoAuCPf/zjYWsNVAFQxDonT56kp6cH0AIQ8S+VZ1ztv6HBwcSERzC5cDavb/wTTqeTDXv3c9+CeRYnlMHY3WdpkRaAXFti7yKQ1tZWmluaiQiPsDiRDMaMO2bx7I//gtPh5PXXX1cBUERERPpt0C3A/Tlaer3bffR6EbHWJRuAdQJQ/MgZcwFIXByGAdmphUSFxwCwbs9eC5PJUJjtv3a7jeyiVIvTeLekvotA1Abss2KSYhgzZywAy5cv1+tnERER6bdBnQBct27dNa//zW9+w6uvvorNZuOWW25hyZIlFBQUEB4eTktLC2VlZaxdu5ZVq1bhcDi47777+PrXvz6ov4CIeE5ZWZn7copmAIqfaG9vp66uDoDUeNdma5thY0LeTLbsW82GffvocTiw2zQW19fs6i0AZhakEBQcaHEa75YQFYVhGDidTs6ePasNsj5s1l2zObTlIBUVFezZs4cpU6ZYHUlERER8wKAKgIsXL77qdd/85jd57bXXGDt2LC+88AITJ0684u3+8R//kf379/PpT3+aV199laysLP77v/97MHFExEPME4AxMUmEhqo9TPyDuf0XXCcATZMKZrFl32rON7dQUn6M6YUFVsSTQXI4HJSUHwM0/68/AgMCiI2IoP7CBc0B9HEz7pjFX/71Tzh6HLz++usqAIqIiEi/ePS4w+rVq/n1r39NXFwc77333lWLf6YJEybw3nvvERsby69+9SvWrFnjyTgiMkBmAVDz/8SfnOmd/2e32UiOjXF/fEL+DAzD9WNwvdqAfU5ZVRUXejc7a/5f/yT2tgGrAOjbIuMiGTd/PKA2YBERb2EYhs/8Wb16tdWfLrGIRwuAy5YtwzAMHnroIZKTk/t1n+TkZB566CGcTie/+93vPBlHRAbIbAHWBmDxJ5W98/+SYqIJsNvdH48IjSI/3TVLa92efZZkk8Ez5/8B5I1TAbA/zEUg58+fp7Oz0+I0MhSz7p4DwOnTp9mxY4fFaURERMQXDKoF+GrMFyADbUWYOnUqANu3b/dkHBEZgJaWFnerZLLm/4mfcDgcVFVVAZAaF3/Z9ZMKZlF2+gB7jx+ntrHRfUJKvJ85/y8iOozEtFiL0/iGxOgowLWArfZcLelpap32VdNvncGf/uUperp6eP3115k5c6bVkUREBPjbB/+T7KyxVse4zImTh3jq6e9ZHUMs5tECoNlS0tHRMaD7mbdXS4qIdfouAElNUQuw+Ifa2lq6urqAiwtA+ppUMItX1/8RgA179/PJhfNHNJ8MnnkCMG9cBoZhWJzGN5gnAMH1mksFQN8VHhPOhEWT2LN2N2+88QY//elPsWmRkYiI5bKzxlJcNMvqGCJX5NFXCrGxrnfgN2zYMKD7mbePiYnxZBwRGYCjR4+6L6eoBVj8hDn/Dy5dAGLKSikgMiwGgM0HDo5ULBmi5rY2jpx2tXZrAUj/hQeHEB4SAsDZs7UWp5Ghmn33bACqq6vZunWrxWlERETE23m0ADhnzhycTifPPPMMH3zwQb/us3XrVp555hkMw2DOnDmejCMiA3Do0CEAbDY7yUnZFqcR8Qxz/l9UWBgRoSGXXW8zbIzNmQLApgMHNEzfR+w5dtz9b5WvBSAD4l4EUlNjcRIZqqlLpxEQHAjA66+/bm0YERER8XoeLQA+/PDDAPT09HDrrbeybNkyd+vVR3V1dfG73/2O2267je7ubgC++tWvejKOiAyAWQBMTsohICDI4jQinmHOtUy7QvuvaXzeNABqGs5T3jsvULyb2f5rGJAzRicAB8JsAz537hwOh8PiNDIUoZFhTL5xMgArVqygp6fH4kQiIiLizTw6A/DWW2/loYce4sknn6SlpYWvfe1r/Mu//Avz58+noKCAsLAwWltbKSsrY/PmzTQ2NrrfwX/ooYe45ZZbPBlHRAbg8OHDAKSl5lucRMQzmpubaWxsBCD1Cu2/pnE509yXN+0/SEFa2rBnk6ExF4Ck5SQRGh5scRrfYi4C6e7upr6hnoT4BIsTyVDMuGMWO9/ZQW1tLTt27GD27NlWRxIREREv5dECIMDvf/97wsLCePTRR3E6nZw/f5633377stuZhT/DMPjGN77B//zP/3g6ioj0k8Ph4MiRIwCkpRVYnEbEM/rO/7tWATAxNpXE2FRqG6rYfOAgD95y80jEk0FyOp3sLjcXgOj030D13XR99uxZFQB93OSbpmAPtNPT1cOKFStUABQREZGr8vi6MMMw+PWvf83GjRu59957CQoKwul0XvYnODiYj3/847z//vv86le/0gY/EQudOnWKtrY2QAVA8R9nzrjm/wUGBFxS9LgS8xTgB4cO0a02Oq92sraWuqYLAORp/t+AxUREEBjgev/37NmzFqeRoQqLCmP8ggkAvPXWW5pjKiIiIlfl8QKgaf78+bz66qs0NTWxbds2XnvtNf7yl7/w2muvsX37dhobG3nllVeYN2/ecEUQkX7quwE4LVUFQPEP5gKQlNhYbLZrv8k0PtdVAGxqbWN/xYlhzyaDZ87/A8gbpwLgQNkMw90GXKtNwH5h+m0zANebeXv37rU4jYiI+IMHH3wQwzAu+xMREcGYMWP40pe+xJ49ey67X05OzmX3sdlsxMTEMGPGDH7wgx9QXV193edft24dX/ziFykuLiYqKoqwsDByc3N54IEHeO2114bjrzwqeLwF+KOCgoKYOXPmcD+NiAxB3wJgqmYAih/o7u52n25KvcYCENOY3k3AAJv2H2BKft5wRZMhMuf/hYYHk5qdaHEa35QQHU1lXb1OAPqJqbdM5+nvPYXT4WTFihVMnjzZ6kgiIuInAgMDieszSufcuXMcOXKEI0eO8PTTT/Ob3/yGr3zlK5fdLzw8nIiICMC1JPbcuXPs3LmTnTt3smzZMlasWMGcOXMuu9/58+f53Oc+x5tvvun+WGhoKHa7nYqKCioqKnjhhReYM2cOL7/8MhkZejN4IIbtBKCI+A6zABgXm0JYaKTFaUSG7uzZs+6NmKmxsde9fVR4DFnJrtOvmw4cHNZsMjTmCcCcMenXPdkpV2a2xLe2ttLc3GxxGhmqqPgoimePAVxtwCIiIp4yb948qqur3X9aW1tZtWoVBQUFdHd387Wvfe2KJwG//e1vu+9TW1tLU1MTy5YtIzIykrq6Oj75yU/S3t5+yX0aGxtZuHAhb775JkFBQXz3u9+lrKyM1tZWLly4QGVlJb/4xS+IjIxk69atzJ07l5MnT47Up8IvqAAoIpSWlgKQqvZf8ROVlVXuyylx1y8AAozLnQrAztIyOrq6hiWXDE17ZycHTrhe6OVrAcigJcVcnIlZc7bGwiTiKdNvc3XblJaWXnKqX0RExJOCgoJYunQpy5cvJzAwEIfDwbJly657v8jISB5++GF++ctfAq5Z3cuXL7/kNg8//DD79+8nJCSElStX8vOf/5z8/IvdaampqfzTP/0TmzdvJj4+ntOnT/PAAw/gcDg8+5f0YyoAioj7l4V0LQARP1Fd7SoARoeHExYc3K/7FGdNAqCjq4u9xyuGK5oMwf6KE+4lLVoAMnjxUZHu5WtqA/YP02+b7r68YsUKC5OIiMhoMG7cOGbMcM2g3bFjR7/v99nPfhabzXbZ/Xbu3MmLL74IwE9+8hNuuummqz7GxIkT+e1vfwvAli1beP311wca/zLmvML169dz9uxZvv71r5OTk0NoaCiFhYX89Kc/pbOz0337devWcfvtt5OYmEhYWBhz5sy54s/frVu3YhgGkZGRdHd3X3b9hAkTMAyD4OBgWltbL7t+zpw5GIbRryJrf6gAKDLKnTt3jvr6egDS0wotTiPiGVVVrgJgSj/af01FWRMxcBVFth0+Miy5ZGj6LgDJ1QKQQQu0BxDbO5fnbI0KgP4gLjWevKmuUxIqAIqIyEgw5+81Njb2+z4hISHEx8dfdr/f/e53AERHR/P1r3/9uo/z6U9/msLCwkvu6wknTpxg6tSp/Pa3v6WhoYGuri7Kysr44Q9/yAMPPADA448/zs0338yqVavo7Oykra2Nbdu2cc899/Dqq69e8ngzZswgPDyc5ubmywqltbW1HDzoGj3U2dnJli1bLrm+ubmZnTt3AnDDDTd45O+nAqDIKGe2/wKk6QSg+IHW1jbOnz8P9L/9FyA8NJKMpFwAtqsA6JXMBSBJ6XFERodZnMa3mW3AOgHoP2b0tgHv27ePEye0zVxERIaX+bMmdgBvuLe0tHDu3LnL7rdu3ToAbrnlFsLC+vca72Mf+xgAmzdvvuLpusH4h3/4B7Kzs9mzZw+NjY00NTXx05/+FIBXX32Vf//3f+eRRx7hu9/9LnV1dTQ2NlJRUcHcuXNxOp38/d//vXsOOUBAQADz588HYP369Zc814YNG3A6nURFRV3x+k2bNtHd3U1KSgpjxozxyN9PBUCRUU4FQPE35uk/GNgJQICibFcb8I6jpe5WU/Eeu8tdBcA8nf4bsoTeRSDnz5+/pKVFfNf022e4L7/99tsWJhEREX/34Ycfuk+0XWmb79UsW7YMp9N5yf3MU3YAU6ZM6fdjmVvvW1paPPbGl2EYvP3220ya5PqdICwsjB/84AfuluR//dd/5bOf/Sw/+9nPiImJASA7O5vnn38ewzA4c+bMZSf5zNN7VyoAAvz93//9Na9fvHixR/5uoAKgyKhnzv8LC4siJjrJ4jQiQ1dVVQmA3Wa7ZNlBf5hzAJvb2zl48pTHs8ngVdc3UFnnGleQN1YLQIaq738bZ2t1CtAfJOekkDk2C4A333zT4jQiIuKPKisr+ctf/sI999yDw+EgKCiIr33ta9e8T09PD2VlZfzkJz/h+9//PgAFBQXcddddAO5xVIC7Pbg/EhIS3Jfr6uoG8te4qq985Svuwl5fN998s/vy9773vcuuz87OpqDAdZhm3759l1xnFvA+elLRLPh99atfJSkpiQ8//PCSOYDm9SoAiojHmCcA09ML3UPhRXyZeQIwITqaALt9QPctyprovqw2YO9inv4DnQD0hMToPgVAtQH7jWm3upaB7NixQ/+uIiIyZBs2bHAvyDAMg/T0dD73uc9RXV1NWFgYzzzzDEVFRZfd7yc/+Yn7PgEBARQWFvLjH/+Yjo4OsrOz3VuEvc3EiROv+PGkJNdBmZCQEHeh76OSk5MBaGhouOTjM2fOvGwO4Llz5zhw4ABFRUWkpaWxePHiS+YAtrS0uG/rqfl/oAKgyKhnFgAz0i//xi3ia5xOp7sAmDqA+X+mmIg4UuJcxSUtAvEuO0tdrSFBwQFk5CdbnMb3hQUHExEaAsDZs7UWpxFPmXaLqwDodDpZtWqVxWlERMTXBQYGkpycTHJyMikpKeTl5bFo0SK+//3vc+jQIT71qU9d8X7h4eHu+6WmplJUVMQdd9zB//7v/7Jv3z7GjRvnvm1cXJz78kBO8pmzBD/6GEORmpp6xY/bew8VJCcnX/XQjHmbrq6uSz4eGBjIvHnzgIun+sz5f2Zx76Ntwub8v+TkZMaOHTvYv85lAjz2SCLic1paWjh1ytXmmJGuDcDi+xoaGujo6AAgeYDz/0xF2ZOorj/N9iNHcTgc2Gx6r8wbmAXAnDHpBAQM7GSnXFlidDTNbe3U6qSY38gan01cWjz1lXW8++67fP7zn7c6koiI+LB58+ZdNpuuP7797W/z4x//uF+3DQwMJD8/n/LyckpKSvr9HHv27AFcc/qys7MHnHEk3XDDDaxevZr169fzz//8z+75flcrAJrXL1q0yKM59FuNyChW3qelLl0FQPEDlZUXF4CkDrIAaM4BbGhuprTP44l12js72Xe8AoCC8ZnWhvEjZhvwuXPncDgcFqcRTzAMg6lLpwGuXx76zhISERHxVuaSjVWrVvX7Z9fy5csBmD9/vle2E/f10TmAZqHPLPyNGzeO5ORk9xzAj17vKSoAioxifTcAqwVY/IHZ/hsSFERMRMSgHsMsAILmAHqL/RUn6Owdmpw/QQVAT0nsXQTS3d19yQBu8W1mAbCtrc19gkBERMSbffnLXwagsbGRRx999Lq3f/HFF92/yz788MPDms0TZs2aRVhYGM3Nzbz77rvs37+f4uLiS1qOzTmAq1evHpb5f6ACoMioZm4ADggIIjnJu49Ni/SHuQE4JTaGwe60SYhJJr53I7bmAHoHs/0XtADEk/ouAqk5W2NhEvGkMXPGEhoZCsDbb79tcRoREZHrmzFjBp/85CcB+NGPfsR777131dvu27fPvXl47ty5fPzjHx+RjEPRdw7gv/3bv10y/89k/v+f/exndHV1kZSUdMmsRE9QAVBkFDMLgCnJudjtGgkqvq27u5vaWtcyg+QhDgIu6j0FuO3IEZxO55CzydCYBcCUzHgio8MsTuM/YsLDCQxwfe/Xxlj/ERAUwMQbJgPw7rvv0tPTY3EiERGR63viiScYN24c7e3t3H777Xzve9/j2LFj7uurq6v5r//6LxYsWEBdXR2pqak8//zzPjOv22wD3r59O3D56T7z/5vXe3r+H6gAKDKqHT58GICMjGKLk4gMXU1NjXuO2WDn/5nGZLsKgDUN5zmhDamWcjqd7Oxt8cjX/D+PMgyDxOgoAGr1de5XzDbgc+fOsW3bNovTiIiIXF9MTAybNm3ijjvuoLOzk5///Ofk5+cTHh5OVFQUqampfOc736GpqYlZs2axdetWr1/+0dfVCn6msWPHkpycfNXrPUEFQJFRqr293f2OSqYKgOIHzPl/AClDLAAWZk50X97ZZ1amjLyTtbXUNjYBmv83HMw2YJ0A9C+TbpiMvXdb9htvvGFxGhERkf6JjY3lrbfeYs2aNXzhC1+goKAAwzDo7u4mOzub+++/n7/+9a9s3bqVrKwsq+MOiDkHEKC4uJiUlJTLbtO36DccBUD1/ImMUqWlpe7TUjoBKP7ALADGhIcTGhw0pMdKic8gPCSSlvYL7Cwt4xML5nsiogzCzqMX5/9pA7DnmYtA2trauHDhApGRkRYnEk8IjwmnaFYxh7YcZPny5Xz3u9+1OpKIiPiQp59+mqeffnrA96uoqPDI8y9ZsoQlS5Z45LH643ojfx588EEefPDBa97G3Nx7NUFBQbS0tFzzNi+88AIvvPDCNW8zFDoBKDJKHTlycbmBTgCKPzALgClxQzv9B2AzbORnuIbu9l1AISNvR+8JzLCIEFKyEixO43/6LgLRKUD/Mu2W6YBr3EdZmb6PiYiIjHYqAIqMUocOHQIgKCiEpETfOj4t8lEtLa00NjYCkBI7tAUgpoKM8QAcOXWaC61tHnlMGTizAJs3PgObbZCrneWqEqKisPWuzFYB0L9M6Z0DCLBy5UoLk4iIiIg3UAuw9Ivdbrc6wlV5czZvZp4ATE8rcm8ANgzDZ7Yo+Qp9PofO6C1OXOvrs7q62n05NT7OfZ+hKMx0nQB0OJ3sPX6chRMnDPkxvY23f31eaG3j8KnTgKv91xP/rh5nXPxfAy/Mdx2BAQHERUZyrqmJs2fPetXXhDdl8UXJ2clkjs3i1KGTvPvuu3zjG9+wOpJf0evPoTM/h/pcep4+pyJyJSoASr/EDnGg/nCx2+1em83bmQXA7KyxBAcHA7j/VzzDMAxCQkKsjuE3rvX1WVvrOrlkt9lIjY8nwD70wkFR1gQMw4bT6WDP8QqWzpwx5Mf0Jr7w9bn18FH3TJYxU3IJCPDely0Bdu/Ndj1JsTGca2qitrbWa74mfOHr0xfMvGMWpw6dZOvWrfT09JCQoDZ6T9DrT8+KioqyOoJf0denjFaPPPIIL7744oDu0/cQwWjgu69WZUQ1NDRYHeESUVFR2O12enp6aGpqsjqOz2lubnYPaE1NLaCjo4Pg4GA6OjquOwBVri84OBjDMHA6nXR0dFgdx+cZhnHdr89Tp04BvQsNnA66ux1Dft4AexCZyXmcrC5j66HDtLe3D/kxvYEvfX1uOXAAAJvNILMgme7ubosTXYHhKv5193SDj377TOj95buhoYHz589bWnjzpa9PXzB5yRRe/e+/4nA4eOmll3jggQesjuTT9PrTs+x2O1FRUTQ1NdHT02N1HJ/nr1+fKmZKfzU2NlJTU2N1DK+mAqD0izf/UPbmbN7KnP8HkJFe5C6qOJ1O92Zg8Qx9PofObAO82ten0+m8uAAkNtajReyCjHGcrC5jV2kp3d3dfteS6O1fnzuOuhaAZOSnEBwa5JVvULjbfp3X3yDnrZJiLi4CqaquIjsr28I0F3n716cvyJ6QQ2xKHA3V9bz99tvcf//9VkfyG3r96Tk9PT36fHqYPp8yGg12c/Fo4l+/yYhIv1xaANQGYPFt9fX17pNCKR5+l9hcBNLU2kZZb5FRRkaPw8HusnIACiZkWJzGvyXFxLgvj7ZWGH9ns9mYcdtMANatW6dTlSIiIqOYCoAio9Dhw4cBCA2NJC4u1eI0IkNTWXmxMJca55kNwKaCjHHuyzuPlnn0seXaSs+c4UKba/ty/vhMi9P4t+DAQGIjIgCoqVbrjL+Zfst0AFpbW9myZYvFaURERMQqKgCKjEJmATAjvcg7t2qKDEB178m80KAgosPDPfrYiTGpRIW7ThXuKlMBcCTt6FNwLVABcNglx8YAaHaOH5qwcCJBIUEArFq1yuI0IiIiYhUVAEVGIbMFOCO9yOIkIkNXWVUJQEpcLJ6uZxuG4T4FuLNUBcCRZH6+YxIiiUuOvs6tZajMNuDz58/7zcIbcQkKDWbsfNc4g9WrV/vsrEoREREZGhUARUaZhoYG9wmPjAzN/xPf1tXVxblz5wBIHqYtceYcwLLKKs43Nw/Lc8jlzAUg+eMzdVJ5BJgnAAGqazQH0N9MvXkqACdOnKC0tNTiNCIiImIFFQBFRhmz/Re0AER8X01NjXtTaOowFQALM8e7L+/qXUohw6u2sZETZ88CkD9eC0BGQlJMtLvQqjmA/mfSTVPcl9UGLCIiMjoFWB1AREbWJQVAnQAUH1fVZzNvStzwFACzU4uw2wLocXSzs7SMm6ZMHpbnkYt2lWr+30gLCnAtAqm/cEGbgP1QQnoCmWOzOHXoJKtXr+brX/+61ZFERPzSiZOHrI5wRd6aS0aWCoAio4w5/y8qMp7oqASL04gMjVkAjI2IICQoaFieIyggiKzkfI5XHaGk/NiwPIdcavuRowAEBQeQVahN5SMlOSaG+gsXtAjET01eMoVTh06ybds2zp8/T0zv3EcREfGcp57+ntURRK5KLcAio4x5AjBdC0DED5gFwOE6/WfKSx8DwJ5jx90txzJ8Puyd/5c7NoOAQLvFaUaPpN45gI2NjbS1t1kbRjxucm8bcE9PD+vWrbM2jIiIiIw4FQBFRhGn0+kuAGoDsPi65uYWmpqaAEgZpvl/prw0VwGwqbWV45qPNqxa2zvYX3ECgMKJWRanGV2SYi5uW9YcQP+TP7WAiNgIwLUNWEREPMfpdPrMn6VLl1r96RKLqAAoMopUVVXR0NAAQFbmWIvTiAzNJfP/hrsAmH7xv5eSY2oDHk67y8vp7ukBVAAcaUkxMe5FIJoD6H9sdhuTbpwCwNq1a+np/e9MRERERgcVAEVGkf3797svZ2WNszCJyNBVVVUCEGC3kdjn5NJwSI5PJzQ4HEBzAIeZOf/PsBnaADzCggICiIt0nRDTHED/ZLYB19fXs3PnTmvDiIiIyIhSAVBkFDELgIZhIyNdG4DFt5knABOjY7DbhvfHmc2wuecA7i5TAXA4mQXAzPwUQsKCLU4z+iT1LobQCUD/NGHxRGx21/fLVatWWZxGRERERpIKgCKjyIEDBwBITckjODjU4jQig+d0Ot0FiuFeAGIy5wAeOnmS9s7OEXnO0aaru5vdZeUAFE1S+68Vknvb6Zuammhta7U4jXhaeHQ4hTNdM4DXrFljcRoREREZSSoAiowiZgFQ8//E19XV1dHZW4Qb7vl/JvMEYFdPDwdPnhyR5xxtDp44SWtHB6D5f1bRIhD/N2XJVMD1muD06dMWpxEREZGRogKgyCjR0tLCsd7lBVlZKgCKb6usHLkFICbzBCBASfnxEXnO0ebDo6XuywUqAFoiKTr64iKQGrUB+6PJvQVA0DZgERGR0UQFQJFR4tChQzidTgCyMrUARHxbde/8v9DgYKLDw0fkOaMj4oiPTgagpLx8RJ5ztDHn/yVnxBEdF2FxmtEpMCCAuMhIQCcA/VVqfiqJWUmACoAiIiKjiQqAIqOE2f4LkK0NwOLjqqpdBcCU2Bh6DyuNCPMUoE4Aep7T6eTDo64CYMEEnf6zUnJsDKBNwP7KMAymLJkCwPvvv09rq2Y9ioiIjAYqAIqMEmYBMDIyjpiYZIvTiAxeZ2cntbW1AKTExY3oc5tzACtqami40Dyiz+3vjlVVU9d0AYBCLQCxlLkJuKmpiZbWFmvDyLAw24Db29vZtGmTxWlERERkJKgAKDJK7N+/H3AtADFG8siUiIfV1NS429lHav6fKT/94vzMPb0zNcUzzPZfgMJJ2RYmkZTeE4AAVVVVV7+h+Kzi2WMIDgsG1AYsIiIyWqgAKDIKOByOPhuA1f4rvq1vQWKkC4DZqYXYDNePzt3lKgB6ktn+GxUbTlLayP67yqUSY6Kx21xf51WVKgD6o8DgQCYsmgjAqlWr3G+qiIiIiP9SAVBkFKioqHDP+NH8P/F1ZgEwNiKCkKDAEX3u4MAQMpLyAChRAdCjzBOAhZOydUrZYgE2O0kx0YBOAPqzSTdNAaCyspKDBw9aG0ZERESGnQqAIqNA3wUgWSoAio8zCxIpcdacEstLLwZcBUCdmvGM6oYGTp51zXUsnJBpcRoBSI51zdesqqrS17mfmnzjZPflVatWWZhERERERoIKgCKjgDn/z24PJC013+I0IoPX3NzMhQuuRREj3f5ryuudA9jQ3MyJ3qKVDM2HR0rdlzX/zzukxsUArqU7dfV11oaRYRGTHEvupFxAcwBFRERGAxUARUYB8wRgelohAQFBFqcRGbzKPvPIRnoDsCkvbYz78h61AXvE9iNHAAgJCyIjX1vKvUHf/740B9B/mW3AO3bsoK5OhV4RERF/pgKgyChgFgA1/098ndn+G2C3kRgdZUmGtIQsQoJCAdhdXm5JBn/zwaHDABROzMZu10sTbxAdHkZosGtLbKXmAPqtKUumAuB0Olm7dq3FaURERGQ46VW2iJ87f/48p0+fBjT/T3xfVVUlAEkxMe4tpSPNZrOTk1oEwJ5jxy3J4E/ONTZx9PQZAIqnqP3XWxgY7jb7ahUA/Vb2xByiEl0LX9QGLCIi4t9UABTxc5csAMkca2ESkaFxOBxUV1cDkGzR/D+T2Qa8v+IEXd3dlmbxddt6238BiibnWBdELpPau2intraWzs5Oi9PIcLDZbEzubQN+77336OrqsjaQiIiIDBsVAEX83J49e9yXc7LHW5hEZGjOnatz/3KaanEBMDfNtQm4o6uLI72n12RwtvW2/waHBpFdlGpxGunL3LTtdDqpqamxOI0MlylLpgDQ1NTE9u3brQ0jIiIiw0YFQBE/ZxYAkxKzCA+PsTaMyBBUVla6L1u1AMSUl35xEUiJFoEMyQeHXCcACydlaf6fl0mOjXFfrqyqvPoNxaeNWzABe6AdUBuwiIiIP9MrbRE/ZxYAc7InWJxEZGjM+X9hwcFEhYVZmiUuKomocNfpqL2aAzhodU1NHOmdUVqs9l+vExIYRFxkJADVVdUWp5HhEhoRypg5rhEhq1atsjiNiIiIDBcVAEX82IULFyjv3VKakzPR4jQiQ2NuAE6Ji8UwrM1iGIZ7DmDJMZ0AHKxthy/O/yuekmNdELkqcw5g3xO44n/MOYClpaUcP643NURERPyRCoAifmzv3r3uy7kqAIoP6+zs5Ny5c8DFuWRWM+cAHj19hpb2dovT+Katmv/n9ZJ7/3trbm7mwoULFqeR4TJlyVT3ZbUBi4iI+CcVAEX8WN8CoE4Aii+rrKzE6XQCkBJr7fw/kzkH0OF0sr/ihMVpfNPW3hOAhRM1/89b9V24o1OA/ispJ5nUgjRABUARERF/pVfbIn7MLAAmJmQSGeEdp6ZEBuN076ZdwzBI6bOYwErmCUCAPWoDHrD6Cxc4fKp3/t+UbIvTyNUkREcRGBAAwJlKbbz2Z2Yb8JYtW2hubrY2jIiIiHicCoAifsy9ACRHC0DEt5054yoUxUZEEBwYaHEal4jQKJJiXSdmSso1M2ugLpn/pwUgXstm2NxzAM+cVgHQn01eMgVwjVzYsGGDtWFERETE41QAFPFTzc3NlJWVAZr/J77N6XRyundTbKqXzP8zmYtAdAJw4D7oM/8vS/P/vFpafDwAZ8+epbOz0+I0MlwKZxQRGuXasK5twCIiIv5HBUARP7Vv3z73zLTcnEkWpxEZvAsXLrjb0ZJjvasAmNs7B/BU7TnqmposTuNbzAUghROzCAiwW5xGriUt3jV30+FwUFVdZXEaGS4BgQFMXOR6w3DNmjU4HA6LE4mIiIgnqQAo4qfM9l/QAhDxbX0XD6TGeccCEJN5AhBgzzG1AfdXw4Vm9/y/osma/+ftUuNisRkGoDZgfze5dxvw2bNnL1kkJiIiIr5PBUARP2W+cE+Iz9ACEPFplZWuE0eBAXYSoqIsTnOprJR8bIbrR2lJudqA++uS+X9TcqwLIv0SFBBIYkw0AGfOqADozybeMAmjt9irNmARERH/ogKgiJ/SAhDxF1VVrhOAyTGx2GyGxWkuFRwYQkZSHqATgAOx5dAhAIJDAsnW/D+fYM4BPHPmjFpD/VhUfBT50woAWL16tcVpRERExJNUABTxQ83NzZSWlgKQm632X/FdDoeDmpoaAJK9bAGIKS+9GHAVAM25m3Jtmw8cBKBwUrbm//kIcw5gV1cXtbW1FqeR4TTppikAlJSUUF1dbW0YERER8RgVAEX80IEDB9yFCM3/E19WW3uOrq4uAFK9bAGIKTfNVQCsv3CBU7XnLE7j/aobGig94zrVOXZ6rsVppL/ME4CAeyu3+KcpS6a4L69du9a6ICIiIuJRKgCK+KG+C0ByVQAUH1ZVdXHjqLctADH1XQRSckxzAK9ny4FD7stjp+VZmEQGIiIkhJjwcEBzAP1d5tgs4lJd32/VBiwiIuI/VAAU8UMlJSUAxMelERUVf+0bi3gxc/5fRGgoEaGhFqe5srTEHIICQwDYqzmA17XpwAEAIqLDyMhLtjiNDERaguvniU4A+jfDMNxtwOvWraOjo8PaQCIiIuIRKgCK+KFdu3YBkJ83xdogIkNkngBMjYvD8K79H252m52c1EJAm4Cvx+l0srn3BODYablet9RFrs2cA9jS0sL58+etDSPDasqSqQC0trbywQcfWJxGREREPEEFQBE/c/78ecrLywHIUwFQfFhHRwd1dXUApMZ7Z/uvyZwDuK+igu6eHovTeK9jVdVU1dcDrgKg+Jb0vnMAz+gUoD8bO38cgcGBAKxatcriNCIiIuIJKgCK+Jndu3e7L+sEoPiyqqqL2yf7LiDwRuYcwLaOTveCC7mc2f4LMHa65v/5mtjICEKDggA4fVpzAP1ZcGgwY+ePA1xzALXhXERExPepACjiZ8z2X8OwaQGI+DRz/p9hGKR46QZgU99FIHu0COSqzPbfhNQYElO9+99ULmdgkG7OATx1yuI0Mtwm984BrKiooKyszNowIiIiMmQqAIr4GbMAmJFeREhIuMVpRAbPnP8XHxVFUGCAxWmuLSEmhciwaABKyrUI5Ep6HA62HDwIwDht//VZ6QkJADQ0NHDhwgWL08hwmnzTVPdltQGLiIj4PhUARfyI0+l0twBr/p/4uosLQLz/pJhhGO45gDoBeGX7jlfQ1NoGqP3Xl2UlJbgvnzx50sIkMtwSMhLIGJMJuNqARURExLepACjiR06fPk1tbS0ABSoAig9rbGyktbUVwOvbf025vW3Ah0+dpq2jw+I03mfTgYPuy2Om5lgXRIYkPjKK0OBgQAXA0cBsA966dSuNjY3WhhEREZEhUQFQxI/s3LnTfVknAMWXmaf/AFLivHsDsMmcA9jjcHDghAojH7Vpv2sBSGZBCpExGk/gqwzDIKN3DqAKgP5vyhJXG3BPTw/vvfeexWlERERkKFQAFPEjZvtvcFAoGelFFqcRGbzKSlcBMCgggPioSIvT9I/ZAgxQojbgS7S2d7DjaCkAY6flWpxGhiozMRGApqYmzjeetzaMDKv8aQWEx0QAsGbNGovTiIiIyFCoACjiR8wFIDk5E7HbvXtpgsi1VFe7CoDJsTHYDMPiNP0TFR5DQkwKAHu0COQSHxw6RGd3NwATZhVYnEaGKjNRcwBHC5vdxqQbJwGuAmBPT4/FiURERGSwVAAU8RPd3d3s3bsXgHy1/4oP6+npoaamBoBkH5n/ZzLbgPccUwGwrw179wEQFBJI4cQsi9PIUMVGRhAeEgLAqZOnLE4jw82cA1hfX+9+o1FERER8jwqAIn7i8OHD7qUJeXmTLU4jMni1tbV0954WS/WR+X8msw24oqaG883NFqfxHuv37gdgzJQcAoN0OtnXGRjuU4A6Aej/JiyehM3u+pVh1apVFqcRERGRwVIBUMRP9H1XviBvqoVJRIbGnP8HvrMB2GSeAASdAjRV1JylovdEp9p//UdGbwGwubmZ+vp6i9PIcIqIiaBwhmuu8OrVqy1OIyIiIoOlAqCInzALgFFRCcTHp1ucRmTwKivPABAVFkZEaIjFaQYmO7UQw3D9aC0p1yIQgI297b8A41UA9BtZvYtAAI5XqNjt78w24AMHDnD69Glrw4iIiMigqAAo4ifMAmB+7mQMH1maIHIllZWVgO+1/wKEBIWSnpgN6ASgaX1vATAxLZbkdN/7N5Uriw4PJzbCtR224niFtWFk2E1ecrGzQG3AIiIivkkFQBE/0NTUxOHDhwEoyJ9mcRqRwWtubqGxsRGA1HjfLBaZcwD3HDuG0+m0OI21Orq62HLwEKD2X3+UnZwEwKlTp7Qd1s+lFaaRlO369165cqXFaURERGQwVAAU8QO7du1yFxoKC6dbnEZk8MzTf+CbJwDh4hzA2sYmKutG92y0HUdLae3oAFQA9EdmAbCrq4vTZ9QW6s8Mw2DqLa7XF5s3b6apqcniRCIiIjJQKgCK+IEPP/wQAMOwkZerDcDiu8z5fwF2O4nRURanGZxLF4GM7jmAZvuvPcBG8ZQca8OIx2UkJGC3uV5Kqg3Y/03rLQB2dXWxdu1ai9OIiIjIQKkAKOIHtm/fDkBW1jhCQsItTiMyeOYJwJTYWHdhwdekJ+USGBAEQMkonwO4obcAWDgxm5DQIIvTiKcFBQSQFh8PQEVFhbVhZNgVTC8kItY19/Gdd96xOI2IiIgMlG/+diUibg6Hg507dwJQVKD2X/FdPT09VFdXA747/w8gwB5Adoqr3XXPKN4EXF3fwOFTrrbQCbPyLU4jw8VsAz579iwtLS0Wp5HhZA+wu5eBrFmzhq6uLosTiYiIyECoACji444cOcKFCxcALQAR31ZTc9a9SCA11ncLgAC5vW3Ae49X0ONwWJzGGmtL9rgva/6f/8pOTnRf1ilA/zftFtfrjKamJj744AOL04iIiMhAqAAo4uN27NjhvqwFIOLLLl0AEmthkqEz5wC2tLdTXlVlcRprrNm9G4D45GjSc5MsTiPDJTEqmrDgYACOHx/dLe+jwfiFEwkIDgS0DVhERMTXqAAo4uPM+X/R0YkkJmRanEZk8MwFIDEREYSFBFucZmjy0vssAhmFbcBtHR1s2n8QgMnzijEMw+JEMlwMwyAnJRlwFQAdo/TE62gREh7C+PnjAdccQKfTaXEiERER6S8VAEV8nLkBuLBgun7JFp925oyrAOjrp/8AkmLTCA+JBKCkfPSdinp//0E6eueDTZ5XZHEaGW55qSkAtLe3c/rMaYvTyHCb2rsN+PTp0+zfv9/iNCIiItJfKgCK+LC6ujrKy8sBVwFQxFc1NV2gubkZgNQ4357/B65TUblpxQCUHBt9JwDN9t+QsCCKJ+dYG0aGXXZSkntrd1lZmcVpZLhNuXmq+w3Hd9991+I0IiIi0l8qAIr4MHP7L6gAKL7NbP8FSPODAiBcXARy+OQp2js7LU4zchwOB2t3uxaAjJ9ZQECg3eJEMtyCAgLISnItAykvK7c4jQy3mKQY8qa6NntrDqCIiIjvUAFQxIeZ8//s9kBysidYnEZk8M6ccS0ACQoIID46yuI0npHXewKwq6eHQydPWZxm5Ow7XkFtYyMAk+eq/Xe0yE1xtQGfP3+euro6i9PIcJu61LUNeO/eve7xDSIiIuLdVAAU8WHmBuDcnIkEBYVYnEZk8KqqXAXAlLhYbH4yy9JsAYbR1Qa8eper/dewGUycU2hxGhkp5hxAUBvwaDDtlotdB++8846FSURERKS/VAAU8VHd3d3s7p2zVVAwzeI0IoPX3d1NTU0N4B/z/0wxkfHERSUBsOfY6FkEsmZ3CQAF4zOJjA6zNoyMmMjQUJJiYgDcs2nFf6UWpJGc49r+rAKgiIiIb1ABUMRHHThwgNbWVgCKNP9PfFh1dTUOhwPwrwIgXGwD3lM+Ok4AnjlXx8HedudJav8ddcxTgJWVlbS0tlicRoaTYRjubcCbN2+mqanJ4kQiIiJyPSoAivioDz/80H1ZC0DEl5nz/8D/CoBmG3B5VTWNLf5fEFnbe/oPYPI8FQBHm/w0VwHQ6XRSerTU4jQy3Mw5gF1dXaxdu9biNCIiInI9KgCK+CizABgfn05sbMp1bi3ivcz5f3GRkYQEBVqcxrPy0se4L+89XmFdkBGycodrM3lSehypWQkWp5GRlhgdTWxEBABHjhyxOI0Mt8IZRUTGRQJqAxYREfEFKgCK+ChzAYhO/4mvMzdIpsX71+k/gJzUIgxcS038fQ5g/YULbD10GIBpi8Zi+MkyF+k/A4PCjHQATp06RcsoOPU6mtnsNiYvmQLAmjVr6OzstDaQiIiIXJMKgCI+qKqqipMnTwJQqAUg4sPOnz/vnmXpb+2/AKHB4aQmZAL+Pwdw1c5d9PTOcpyxeJzFacQqRelpgKsN+GjpUYvTyHCbdusMAJqamti0aZPFaURERORaVAAU8UFbt251Xy4ummVhEpGh8ef5f6bcNFcbcMkx/y4Avr3ddSo5Pjma7KJUi9OIVRKioy62AR9WG7C/m7BoIsFhwQCsWLHC4jQiIiJyLSoAivggswAYEhJBVuZYi9OIDN6Z06cBCAkKIi4ywuI0w8OcA1jTcJ7q+gaL0wyP8y0tbD5wEFD772hnYFDU2wZ8+vRpmluaLU4kwykoJIhJN04GYOXKlfT09FicSERERK5GBUARH7Rt2zbANf/PZrNbnEZk8E6fcRUA0+Pj/bZolJd2cRHIHj89BbhmVwldvb/4T1+k9t/RriijTxvwUbUB+7sZt7s6Ec6dO3dJh4KIiIh4FxUARXxMY2MjBw+6TtqMUfuv+LC2tjbq6uoA/1wAYspMziPA7tpuXFLun4tAVn7oav+NSYgkb1yGxWnEavFRUcRFurbDHjp4yOI0Mtwm3TSZgGDX9zi1AYuIiHgvFQBFfMz27dtxOp0AFBerACi+y9z+C5CeEG9hkuEVYA8kKzkf8M85gM1tbWzctw+AaQvHYLP550lO6T8DgzFZrkJwZWUl9Q31FieS4RQaEcqEhRMAeOutt3D0LgMSERER76ICoIiPMdt/7fZA8nInW5xGZPBO987/C7DbSYqJsTbMMMvtnQO47/hxv/vl+L2SPXR0dQMwTe2/0mtsZqa7rX///v0Wp5HhNuP2mQBUVVWxa9cui9OIiIjIlagAKOJjzPk6ebmTCAoKsTiNyOCZJwBT42Kx2/z7x1FeajEATa1tHK+usTiNZ73d2/4bGRNG0cQsi9OIt4gKCyMzMQGAgwcOuk+ui3+asnQa9gDXTOK33nrL4jQiIiJyJf79G5eIn2lvb2f37t0AFBfNtDiNyOB1dXVRXV0NQFq8/7b/mswTgOBfbcAXWttYu3sPAFMXjMFm18sKuWhsViYAFy5c4MTJExankeEUERPBmLljAdccQBV8RUREvI9eqYv4kJKSEjo7OwEo1gIQ8WFVVVXuVtj0UVAATInPIDQ4HIA95f5TAHx35y46uroAmL1kosVpxNsUpqURFBAAwIH9ByxOI8PNbAOuqKhQ27eIiIgXUgFQxIeY7b8AhQUzLEwiMjSnT7vafw3DICXOfzcAm2yGjdw0VxtwyTH/2QT8+pYPAIhNjKJwUrbFacTbBAYEUJieDkBpaSkdHR0WJ5LhNO3WGe65j9oGLCIi4n1UABTxIeYCkIyMYiIiYqwNIzIEZ864FoAkRkcTHBhgcZqRkZfmagM+UHGC9t6TvL6strGRTb2numbdNEHbf+WKxmW72oC7urrYf0CnwvxZdGI0RbNcb3RoDqCIiIj3UQFQxEf09PSwfft2QO2/4tscDod7AchomP9nKsgcD0BXTw97j1dYG8YD3ty6HUfvnK85N6v9V64sPSGehKgoAEp2l1gbRobd9Ntc3QlHjhyhtLTU4jQiIiLSlwqAIj7i8OHDNDU1AVBcqAUg4rvOnq2lq3duXHrCKCoApo91X95ZWmZhEs9Y3tv+m5adSEZ+ssVpxFsZGEzKzwWgvr5ey0D83PTbL74+efPNNy1MIiIiIh+lAqCIj+g7/08nAMWXnT592n05Pd7/5/+ZIsKiSY3PAmCnj5+Mqag5y+7eZSazb57onvslciVjMzPcy0B0CtC/xafFkzclH9AcQBEREW8zOgYv9WpsbOSvf/0r27dvp66ujuDgYPLz87njjjuYM2fOoB+3u7ubFStWsGHDBiorKwFIT09n8eLF3HnnnQQEXPvTfOzYMV577TX27dtHU1MT0dHRTJgwgfvuu4/c3Nwr3qempoYvfelL18323e9+l/nz5w/8LyVexywAxsenEx+fZnEakcEz5//FREQQHhJicZqRVZA5jqq6k+wsLcPpdPps4cw8/Qcwa8kEC5OILwgKCGRcdhYl5ccoLS3lQvMFIiMirY4lw2TG7TM5VlLOvn37OHbsGHl5eVZHEhEREUbRCcCTJ0/y9a9/neXLl1NVVYXdbqelpYWSkhJ+9rOf8cQTTwzqcdva2vjnf/5nnnrqKcrLy+np6aGnp4eysjKefPJJ/uVf/oX29var3n/Dhg18+9vfZsOGDdTX1xMcHExdXR0bNmzgW9/6Fu+///51M0RFRRETE3PFP0FBQYP6e4l3cTqd7gKgTv+JrzPn/42m03+mggzXHMC6pgucqDlrcZrBcTqd7u2/+eMzSUyNtTiR+IJJea43NJ1Op04B+rmZd158nbJ8+XILk4iIiEhfo+IEYFdXF//+7/9OY2Mj2dnZ/OM//iO5ubl0dHSwfPlynn32Wd58801yc3O5+eabB/TYjz32GEePHiU8PJy///u/d58k3Lp1K//7v//L4cOHefzxx/nmN7952X1PnjzJr3/9a7q7u1mwYAFf/OIXiYuLo76+nieeeILNmzfzq1/9itzcXDIyMq6a4b//+79JTtb8JX928uRJqqurASgu0vw/8V0NDQ20tLQAo2sBiKkw8+JpuR2lZeSk+N737r3HjlNe5fp+NFun/6Sf4iMjyUpK5OTZWkpKSpg9e7bepPRTiVlJ5E3J51hJOa+//voVXwOLiIjIyBsVJwDfffddqqurCQ4O5oc//KG7rTY4OJj777+f22+/HYBnnnmG7u7ufj/u8ePH2bhxIwDf+MY3mDt3LoZhYBgGc+fO5etf/zoA69ev58SJy4deP/vss3R3d5Obm8u3vvUt4uJcp2Hi4uL49re/TW5uLl1dXTz77LND+vuL79u2bZv7sgqA4ssunf83+gqAKfEZhIe6Wh93HPXNOYAvbnSdTA8ItDPrJhUApf9mFBUC0N7ezt69ey1OI8Np9j2uN8QPHjzIkSNHLE4jIiIiMEoKgOvXrwdg0aJFJCYmXnb9Jz7xCQzDoL6+nn379vX7cTds2IDT6SQ1NZW5c+dedv28efNITU3F6XSyYcOGS65raWnhww8/BODee+/Fbrdfcr3dbufee+8FYPv27bS2tvY7l/gfs/03IjyGtNRCi9OIDN6pU6cACA8JJiYiwuI0I89m2CjIGAf45ibgto4Olm9xfT+aMq+YiOgwixOJL8lKSiQpJgaAHTt20NPTY20gGTZ924Bff/1164KIiIiIm98XANva2ijt3bY4bdq0K94mMTHR3WK7Z8+efj+2+e711KlTrzjI3TAMpk6desltTQcPHnSfNrxaLvPjXV1dHDp0qN+5xP+YJwALC2dgs/n9f7bix8wCYEZCAj66/2LIzDmAR8+cobG3HdpXvLNjJxfa2gBYcMdUi9OIrzEwmFFUAMCFCxc4eOigxYlkuMSlxlM0qxhwFQCdTqfFiURERMTvKwmnT592v+jIzs6+6u3M68xfTq/H6XS6W9mu9bhZWVlXfFzz/8fExBAdHX3F+0ZHR7uvO3ny5FWf4xe/+AUPPPAA9913H1/4whf4z//8T/fpQvF9dXV1HD16FNACEPFt58830tTUBEB6QoLFaaxjFgCdTicl5ccsTjMwL25wtf/GJkYxbro2e8rAFaanER0eDsCH2z9UYciPzbrb1QZcVlbG/v37LU4jIiIifr8EpL6+3n3ZnLF3JeZ1DQ0N/XrctrY293bf/jxuW1sbbW1thIaGXvI817qveX1jY+M1c5WWlhIWFobNZqOuro4PPviADz74gPnz5/OP//iPBAYGXvfv88wzz/Dcc89d9foHHniAv/mbv7nu44wU8xSczWYjNta/N1CacyYBJk1c4P4aGg7BwcHD9tijiXki2DCMYf338jWHDx92X85NTSUg4Prfm/qy2/3jR1Zh1gRsNjsORw97jldw2+yRLewP9uuzorqGLQddp9EX3DGVoBAtcOjLHmC//o0EgFljilm9cxd1dXWUl5czceJE93X6/jk8rPj5vvC+RTz7o7/gdDh45513WLRo0Yhn8LTR9PpzJJj/vUdHR+vNAA/Q16eIXI9//DZ1DWaRDq794se8rq23tel6+t6uP49r3sd8MWve/3ovyK6WKygoiDvuuIOFCxeSm5tLWJhrDtPJkyd55ZVXWLduHZs3byY8PNy9jORaWlpaOHv27FWvb21tvWxOoTcwDMMrc3nSli1bAAgKCiU/f8oV2809ZTgfe7TS5/QicxlSeEgIcZGRA24B9pdPZWhwKDkphRyrPMyHR45a+jUykOd+Yf3FWbaL7piOgZ/8g3iIPh/9NzEvh22HDtPU2sqGDRuYMGHCFcdb6Pun51jxuYxNjmXCggns27iXl19+mZ///Od+8286Gl5/jiSNt/EsfX2KyNX4fQHQX8XGxvKVr3zlso9nZWXxzW9+k6ioKJYvX87q1au599573TMOryY8PJykpKSrXh8WFuZVw7ptNhuGYeB0OnE4HFbHGVbmCcDCgmkE2AOH7R1S8/MpQ9f3Fxx9Tl2cTicVFRWAaxGA62P9v79hDOz23q4gczzHKg+z42gpXd3dBIzgC/XBfH329Dh4/r31AIydlktieixO/OgfZIgMDH0+BsBuszFvwjje2b6D+vp6du3exfRp0wF9/xwOVv58n3vvPPZt3Mvx48fZunUrs2b59iiT0fT6cyQYhoHNZsPhcOi/dw/w169PFTNFPMfvC4AhISHuyx0dHe6Tch/V0dEB0O92k763M+97rcf96H3My9e672BymT7zmc+wcuVKOjs7+fDDD69bAPzsZz/LZz/72atef+7cuX63R4+E2NhY7HY7DofDq3J5WktLC7t37wagIH96v0+oDpTNZiMkJISOjg6/esFgldDQUPcLsOH6N/M158+fd8//S4uPp7u7q9/3NQyDgIAAenq6/eYXhPz0sQC0tLdTUlrK+GvMkvW0wXx9bti7j8q6OgDm3TaF7q7u4YzoU9xfn909fvP1ORKK09PYHhlB/YVmNm7YSFFhEQEBAfr+6WFW/3yftGQy9gA7Pd09/OUvf6GwsHDEM3jSaHn9OVLsdjuxsbE0NjZ61UEDX+WvX58Jo3hutIin+f15674z9vrOA/wo87r+zksIDQ11F+X687h9b98317XuO5hcppCQEPcCkpqamgHdV7zHrl273NuixxT79rvmMrr1XWSUqRdy7kUgADuPllmYpH/+svY9AELDg5m2cKzFacQf2Awbc8a6vpYuXLjgfrNL/EtEbCTjF04AXNuA9SajiIiIdfy+AJiRkeFuJ7nWJl3zuszMzH49rmEY7lN1g3lc8//3PRXzUY2NjTQ2NgIXtwnL6LJ161YADMNGfv5Ui9OIDJ65+Tw8JISYiAiL01gvPjqJuChXK/TOUu8uAJ45V8eaXSUAzLt1MsEhA1veInI1RelpJMXEAPDBBx/Q0tpibSAZFrPumg1AVVUV27dvtziNiIjI6OX3BcDQ0FB3u8GuXbuueJtz5865fzmdPHlyvx970qRJANd817qkpOSS25rGjRtHQEDANXOZjxsYGMjYsQM7cdHe3u4uPiYnJw/ovuI9zAJgdtY4wkIjLU4jMnjm99jMxAS/WeYxVOYpwB2lpRYnubZn31uHo7e19caPzbQ4jfgTwzBYPMl1Oqyjo4NN72+yOJEMh2m3ziAgyPWa9/XXX7c2jIiIyCjm9wVAgBtuuAFwLVOora297PpXX30Vp9NJXFwcEydO7PfjLlq0CMMwqKys5IMPPrjs+i1btlBZWYlhGO4MprCwMGbOdP0itXz58svmXvT09LB8+XIAZs2addnswuvNGXr++efp7OzEMAz384hv6erqYseOHQCMKZ5tcRqRwWtoaODChQsAZKj9160w01UAPFV7jup675zV09HVxQvrXYuIxk7PIyVL/37iWRkJCRRlpAOwb98+KqsqLU4knhYWFcbEG1xvsL/xxhvu0SYiIiIyskZFAfDWW28lJSWF9vZ2fvrTn3L8+HHA9W7zX//6V9566y3AtQjDPJVn+uIXv8g999zDr371q8seNzc3l0WLFgHwm9/8hq1bt+J0OnE6nWzdupVHH30UcBUgr9TC+5nPfIaAgADKy8v55S9/6R7W2tDQwC9/+UvKy8sJDAzkM5/5zGX3/Zd/+Rdeeukljh8/fknx8OTJk/z617/mtddeA2Dp0qXXXQAi3mnv3r20trYCUKwCoPgw8/QfQEaiCkimosyLbzhtP3LEwiRXt/LDHZzrHVNx48dmWJxG/NXCCeMJsNtxOp28+867Wqbih+bcMxeA2tpaNm7caHEaERGR0cnvtwCDq4X2Bz/4Ad///vepqKjgkUceISwsjPb2dvcw4rvuuoubb755wI/9d3/3d1RVVXH06FF+9rOfERQUBEBnZycAY8aM4atf/eoV75uVlcUjjzzCr3/9a95//302bdpEWFgYLS2uGTgBAQE88sgjVyzg1dbW8swzz/DMM89gt9sJCwujs7Pzkq3Cixcv5uGHHx7w30m8Q99TpcWFOsUpvsssAEaEhhATrvl/pszkPEKDw2nraGHb4aPcM3eO1ZEu8+c1ruUfsYlRTJ5XbHEa8VdRYWHMKCpk66HDnDp1il27dzFt6jSrY4kHTVk6lZCIENqb23n55Ze56aabrI4kIiIy6oyKAiC4im2/+c1veOWVV9i+fTvnzp0jPDycvLw87rzzTubMGdwvXqGhofz85z9nxYoVbNiwgcpKV+tKfn4+N9xwA3feeedlpwr7Wrx4MZmZmbz66qvs37+fpqYmdyvyfffdR25u7hXv9+CDD7Jnzx5KS0vd7XV2u53U1FTGjBnDkiVLLps7KL7FLACmpRUQFRVvcRqRwXMvQ0pI1Py/Pmw2O4WZE9hbto1tXngC8OCJk+w46ppPuPju6djto6JpQCwys6iQI6dO09DczOpVqyksKLzm6yfxLcGhwcy4fSabXn6ft99+m+bmZiK0EEpERGREjapXVjExMTz00EM89NBD/b7PH/7wh+veJiAggHvvvZd77713ULny8vL49re/PaD7LFiwgAULFgzq+cT7ORwOtm3bBsCYIrX/iu9qaGigubkZgHTN/7tMcdZE9pZt4+jpM9RfuEBcpPcs+/nTmrUA2ANsLLxTp7FkeAXY7dw8bQovb9xER0cHK1eu5O6777Y6lnjQvPsWsOnl92ltbWXlypV86lOfsjqSiIjIqKK380W80KFDh2hsbASguGiWxWlEBu/kyYvz/zI1/+8yxdkXT2p/eOSohUkuVdfUxKubtgAwfdE4ouN0UkeGX0ZCApPy8gA4fPgwR45638lYGbwxc8YSmxILwEsvvWRxGhERkdFHBUARL9R3/p82AIsvO3nyBAARoaFEh4dbnMb75KQWERQQDMC2w95TAPzL2nV0dHUBsPRT3jebUPzXDZMnEhEaCsDqVatpbmm2OJF4is1uY+698wHYuHEj1dXVFicSEREZXVQAFPFCW7duBSAxIZP4+DSL04gMjtPpdM//y0rS/L8rCbAHkp8xFoDtXnICsL2zkz+vdrX/Fk7KIndMusWJZDQJDgrktpnTAWhra2Pl2yu1FdiPzL3PVQB0OBy8/vrr1oYREREZZVQAFPEyTqfTfQKwuFjtv+K7zp6tpbW1FYCsxESL03ivoixXG/D+igqa29osTgOvb/mAc01NANzyqbkWp5HRKC81lSkF+QBUVFSwe/duixOJp2SOySRzbBagNmAREZGRpgKgiJc5duwYZ8+eBTT/T3zbiRMn3JezklQAvJri3gKgw+lkZ2mZpVmcTidPrHwXgKT0OCbPLbI0j4xeN0yeRFyka/bkhg0bOFd3zuJE4inzek8B7tu3j8OHD1ucRkREZPRQAVDEy5jtv6D5f+LbTpyoACAhKorwkBBrw3ix/Iyx2G12ALYdtnbpwYa9+yg9UwnAzZ+Yjc2ulwlijcAAO7fNnIHNZqO7u5sVb66gu7vb6ljiAXM+NhejdybEyy+/bHEaERGR0UOv7EW8jNn+Gx2VSEpyrsVpRAanu7ub06dPA5Cp03/XFBwYQm5aMWD9IpDf957+C4sMYf5tUyzNIpIcE8PcsWMAqK2tZc2aNRYnEk+ITYlj7LxxALzyyis4HA6LE4mIiIwOKgCKeBnzBGBx0Uz3O+QivqaystJ9Wic7KcniNN7PnAO459gx2js7Lcmw93gFm/YfAOCGe2YQHBpkSQ6RvmYWFZKTnAy4Wkb3799vcSLxBLMN+MyZM2zevNniNCIiIqODCoAiXqSystI9N03tv+LLKioqALDbbKQnxFsbxgcUZU0EoLO7m91l5ZZk+O0bbwIQEGhnyX36/iPewTAMbps5jcjQUADWrFlD7blai1PJUM24YxbBYcEAPPfccxanERERGR1UABTxIn3n/xWrACg+zCxkp8bFERQQYHEa71eUOQHDcP1I/uDQyA/FP3rmDCs/3AnAwjunER0XMeIZRK4mNCiYO2bPxGaz0dXVxRvL36DTopOy4hkh4SHMusv1OmfFihU09W4eFxERkeGjAqCIFzHn/4WFRZGZUWxxGpHBaW9vp6amBtD8v/4KC4kgJ7UQgC0HD4348z/25lsA2O02bvv0vBF/fpHrSYuLY+GE8QDU19fz7rvvWpxIhmrBpxYBrp8Zr7/+urVhRERERgEVAEW8iFkALCqcga13K6iIrzlx4iROpxOAbBUA+21szlQAdpeV09reMWLPe+LsWZZvcZ0+nr10EvEpMSP23CIDMbUgj4K0NAAOHz7Mrt27LE4kQ1E0q5jkHNd8x+eff97iNCIiIv5PBUARL1FXV8eRI0cAzf8T33ayt/03ODCQ5JhYi9P4jnG9BcCunh52lJaO2PMuW/E2PQ4HhgF3PDB/xJ5XZKAMDJZOn0JMeDgA69etp7Kq0uJUMliGYTC/9xTgjh07OHrU2i3oIiIi/k4FQBEvsW3bNvflMUUqAIrvqjhRAUBmYgI2mzZZ91dh5njsNte8xJFqA66ub+DljZsAmL54PClZCSPyvCKDFRIYxF1zZhFgt9PT08Mby9+gta3V6lgySPM/sQDDcP2c0ClAERGR4aUCoIiXMNt/g4JCyMmZYHEakcFpaGjg/PnzAGQlJlkbxscEB4WSnzEWGLkC4O/ffofO7m4A7vzMghF5TpGhSoyO5qYpkwC4cOECb614yz12QHxLfFo84xe5XvO89NJLdPd+PxIRERHPUwFQxEuYG4AL8qcREBBkcRqRwTl27Jj7ck5KsoVJfJM5B3DvseM0tQ7vqaZzjU08u24dAJPmFJJZkDKszyfiSeOzs5mQkw1ARUUFW7ZssTiRDNbCTy0G4OzZs7z33nsWpxEREfFfKgCKeIHm5mb27t0LaP6f+Lbjx48DEBcZQXR4mMVpfI85B9DhdLLt8JFhfa7fLn+Dto5OAO787MJhfS6R4XDj5EkkxcQArlP05vcf8S1Tb5lGWJTr58Vzzz1ncRoRERH/pQKgiBfYvn07DocDgOKiWRanERmc7u5uTp06BUB2sk7/DUZe+hiCAoKB4W0Drmk4z5Mr3wVg/Mx88sdnDttziQyXALudO2fPJDgwEKfTyVtvvUVTU5PVsWSAgkKCmHPvPADeffddzp07Z3EiERER/6QCoIgXMOf/2e0BFORPsziNyOCcPHnKPb8pRwXAQQkMCKIwyzUPazgLgP/76uu0dbpO/33sCzcO2/OIDLeY8HBuneH6udnW1sYbb7xBT0+PxalkoBbd72oD7u7u5qWXXrI4jYiIiH9SAVDEC5jz//JyJxMcHGpxGpHBOX7cNf8vwG4nIyHe4jS+y5wDeOjkKeqG4TRTZV0dT69aDcDkeUXkjU33+HOIjKT81FRmFhcBUFVVxXvrNEfO12RPzCF7gmum45///GctdRERERkGKgCKWKy9vZ1du3YBav8V32bO38pMTCDAbrc4je8y5wACfHDosMcf/1evvEZHVxeg03/iP+aNG0NmYiIAJbtLOHjooMWJZCAMw2DxAzcBUF5erqUuIiIiw0AFQBGL7dq1i87eVjwVAMVXNTScp6GhAVD771BlpxYSGhwOwOYDni1inD53jmfWuk5HzbhhHFna/Ct+wmbYuH3WdMJDQgBY9e4q6uvrLU4lAzH33rkEh7lmoP75z3+2OI2IiIj/UQFQxGJm+69hGBQVzrA4jcjgmO2/oALgUNltdsZkTwZg474DHm2F+9/X3qCruwfDMPj4397ksccV8QbhwSHcOXsmNsOgq6uLFStWaB6gDwmNDGP2PXMBWLFiBXV1dRYnEhER8S8qAIpYzFwAkpU5jvDwaIvTiAyO2f4bExFBTES4xWl834R815sBp2prOVFz1iOPWVFzlpff3wTA7CUTSc9ToVb8T3p8PHPGjgGgpqaGTZs2WZxIBuKGz7jGEnR2dmoZiIiIiIepAChioe7ubj788EMAiotmWpxGZHC6u7s5efIkADnJSRan8Q8T8i6eBt6wb59HHvPXry2nx+HAsBnc+7ea/Sf+a2ZxEenxrkVE27dv58TJExYnkv7KnZRH1ngtAxERERkOKgCKWGj//v20tLQAMKZ4tsVpRAbn5MlTdHd3A2r/9ZTkuHQSY1MBVxvwUJWeqeS1za6h+vNumUxqVuKQH1PEW9kMg9tmTic4MBCAt996m7b2NotTSX8YhsENf+N6g6KsrMzdJSEiIiJDpwKgiIX6vrDVAhDxVeXlZQAEBtjJTEywOI3/ME8Bbjl4iM7eAutg/eKlv+JwOrHbbdr8K6NCVFgYS6a6Zmk2Nzez6t1VFieS/pp77zyCQrUMRERExNNUABSxkFkATE3JJzpaJ3LEN5WVuQqA2UnJBNjtFqfxH2YBsKW9nd1l5YN+nB1HS3l35y4AFt8znaT0OI/kE/F2xRkZjM3KBODo0aPs37/f4kTSH6GRYcz52BwA3nzzTW1zFhER8RAVAEUs4nA43BuANf9PfFVNTQ3Nzc0A5KWkWJzGv4zLnYrNcP2Y3rB3cHMAnU4nP3vBNUg/ODSIu/7vYo/lE/EFN06eRHR4GADvvfee+/uVeLcb/sa1pbyzs5Pnn3/e4jQiIiL+QQVAEYscPXqUhoYGQPP/xHeV9Z5MMwyD3BTN//Ok0OBwCjLGAbBh3+BOLq3eVcKOo6UA3PbpeUTFakOzjC7BgYHcPG0qAB0dHaxapVZgX5A7OY/sCTkAPP300/T09FgbSERExA+oAChikb7z/1QAFF9lzv9LjYslLCTY4jT+Z0K+63Tw/ooT1DU1Dei+3T09/L+XXgYgMjacpffP9Xg+EV+QlZjIxNwcAMrLyzl48KC1geS6DMPg5geXAlBRUcHatWstTiQiIuL7VAAUsYhZAIyPSyMhIcPiNCIDd+HCBWpqagDIS021OI1/MucAOp1ONu0fWNHilU2bKT1TCcA9n1tMSGiQx/OJ+IqFE8YTFeZqBV67di0tLS0WJ5LrmX3PXMJjIgB48sknLU4jIiLi+1QAFLGA0+m8OP9Pp//ER5X1WUyh+X/DIye1kPDQSAA2DqANuL2zk//+62sAJKXHsfCuacOST8RXuFqBpwDQ3t7O6tWrrQ0k1xUUEsSiT7vmlr733nscO3bM4kQiIiK+TQVAEQucOHGCqqoqAMYUz7I4jcjgmO2/MRERxEVGWpzGP9lsdsbnTgdccwCdTme/7vfHVWuo7p0x+vGHbiIgQNuZRbKTkpiQkw1AaWkphw8ftjiRXM9N/3cJhmEA8Mc//tHiNCIiIr5NBUARC1wy/69IJwDF93R2dnLy5EkA8lJT6P39TIbBxALXHMCz58+zv+LEdW9/vrmZ376xAoCc4jSmLx43rPlEfMmiiROICA0FXKfKOjo6LE4k15KYlcTkJVMAeO6559S6LSIiMgQqAIpYwCwARkXGk5qab3EakYGrqKhwb2XMV/vvsJpcMBsDV4V1bcme697+t2++RVNrKwCf+PLN2GyqzoqYggMDuXHyRABaWlp4f9P7FieS67n5wVsAaGpq4pVXXrE4jYiIiO9SAVDEAu75f0Wz3K0tIr6ktLQUgJCgINLi4y1O49+iwmPJSx8DwJpdJde87ZlzdTy9yjXbbPzMfMZOyx3ueCI+Jz8tldzeNy5KdpdQXVNtcSK5lnELxpOc6/r3evLJJ/s9CkFEREQupQKgyAirrq7m+PHjABRr/p/4oJ6eHsrLXQtA8lJTdMJsBEwunAvA3uPHqWk4f9Xb/fKV1+jo6sYwXKf/RORyBgY3Tp5IgN2O0+lk1burVFTyYjabjSWfc30/O3jw4CVjVERERKT/VAAUGWF9X7gWF6kAKL6nouKEe25WYVqaxWlGhymFc9yX1+25chvw4VOn+OumzQDMvnkSWQVqzRa5mujwcGaPKQagpqaG3bt3W5xIrmX+JxcSHBYMwFNPPWVxGhEREd+kAqDICDPbf0NCIsjO0nB+8T1Hjx4BICgggKykJIvTjA6ZyXnERSUCsHb3lQuA/++lv+J0OgkItHPv3944kvFEfNL0wgLio1wbzN9//32aW5otTiRXEx4dzrz7FgCwYsUKqqqqLE4kIiLie1QAFBlhF+f/zcRms1ucRmRgHA4HZWVlgKv9N8CuHyMjwTAMJveeAnx//wHaOzsvuX7b4SPuwuANH5tBQkrMSEcU8Tl2m42bpkwGXJvN169bb20guaYln3e1Aff09OgUoIiIyCDoNzeREdTQ0MDBgwcBVwFQxNecPHmS9vZ2AArU/juizAJga0cH2w4fcX/c6XTyny+8BEBIWBB3fnaRJflEfFFGQgLjsrMAOHToEKfPnLY4kVxNRnEm4+aPB+BPf/oTrb3bzkVERKR/VAAUGUHbt293Xx5TPNvCJCKDc/ToUQACA+zkJCdbnGZ0GZczlaAA1wystbtL3B9/d8cudpW5lrLc9sB8IqPDrIgn4rMWjB9HUEAAAO+tfU8LQbzYLV+8DXC9ofrSSy9ZnEZERMS3qAAoMoLMBSCBgcHk5kyyOI3IwDidTkpLSwHISU4mMEAt7CMpKDCYcbnTAFizuwSn00l3Tw//76WXAYiOi2DpJ+Zc6yFE5ArCQ0KY1WchyL59+yxOJFcz6cbJpOSnAvC73/0Oh8NhcSIRERHfoQKgyAgyC4AF+dMIDAy2OI3IwJw+fdrdclWYnm5xmtFpSpGrwHf6XB1HTp/mxQ3vU15VDcA9n19McGiQlfFEfNbUgjxiIiIA10IQc9O5eBebzcYtf+s6BVhWVsaaNWssTiQiIuI7VAAUGSHNzc3s2eMa0l9cNMviNCIDd+SIq/03wG4jV+2/ljDnAAK88cE2/ufV1wFIzoxn/h1TLUol4vsCbHYWT5oAQGtrK1u2bLE4kVzN/E8uIDzGVaz93e9+Z3EaERER36ECoMgI2blzJz09PQCMKVYBUHyL0+nk6FHX4onspGSCAgMsTjQ6xUYmUJAxMLBCWwAAcHBJREFUDoAXN7zP2fPnAbjvi0sIUEu2yJDkpiS7Z5vu2rWLuvo6ixPJlQSHBnPjZ28CYOPGjRw4cMDiRCIiIr5BBUCREWK2/9rtARQUTLc4jcjAnDx5ipaWFgCKMtT+a6XpYxYCUNvYCEDe2HSmLRxjZSQRv2BgsHjSBGw2Gw6Hg3XvrbM6klzFks8txR7oetNj2bJlFqcRERHxDSoAiowQswCYkz2BkGBt6RTfcvjQIcC1/Tc/NdXiNKPbjN4CoOkTX74ZwzAsSiPiX+IiI5mSnwfA8ePHKS8vtziRXElsSiyz754LwKuvvkpNTY3FiURERLyfCoAiI6Cjo4Ndu3YBUFw02+I0IgPT09PDkd723/zUVG3/tVhQUDShIYkAhIYHUzwlx9pAIn5mzphiwoJdi7rWrVvnHt8h3uXWL7qWgXR2dvLHP/7R4jQiIiLeTwVAkRFQUlJCe3s7oPl/4nuOHz/u3ohZlJFhcRr54NAhoqPyAWhr6aD+bKPFiUT8S3BgIPPGjwWgoaGB3SW7LU4kV5I9IYcxc13/Tk8//TRtbW0WJxIREfFuKgCKjACz/dcwDIqLZlqcRmRgDvW2/4YEBZGTnGRxmtGt9nwjh0+ddhcAAXZtPGRhIhH/ND47m8ToaAC2bN6i4pKXuvWLtwNQV1fHiy++aHEaERER76YCoMgI2Lp1KwAZ6cWEh8dYG0ZkADo7O90zsArT07Db9GPDSpsOHMTpdBIWlkBcQhoAu94/bHEqEf9jM1wLQcA1xmPT5k0WJ5IrmbxkCqkFru+Fjz32mNq1RURErkG/yYkMs56eHrZt2wbAmGLN/xPfUlZWRldXFwDFav+11MmztVT0DrrPHZPOuMnzACjdd4LG+mYro4n4pczERArSXMWlPSV7OHfunMWJ5KNsNhu3P3wn4BpXsWLFCosTiYiIeC8VAEWG2f79+2ludv1yXqz5f+JjzPbfiNAQ0hPiLU4zejmdrtN/AIFBARROzGLsxDnu60o26RSgyHBYOHE8dpsNp9PJunXrrI4jVzD33nnEJMcC8Jvf/Aan02lxIhEREe+kAqDIMDPn/wEUF6kAKL6jtbWNiooKwLX8w2YY1gYaxUrPnKGmoQGAwolZBAUHkpyaQ2x8CgDb1x2wMp6I34oJD2dKgWvmZkVFBeXHyi1OJB8VGBzILQ/dCsCePXt4//33LU4kIiLinVQAFBlm5vy/5OQcYmOSLU4j0n+HDh3E4XAAMEbtv5bpcTjYfNB1EjM0LJjcsemAa6nQ+CkLADi6p4L62ibLMor4s9nFRYQFBwOwft169/dF8R43fuYmQqPCANcpQBEREbmcCoAiw8jpdLoLgGOKNP9PfMv+/fsBSIiOIikmxtowo9j+ihOcN8cITMnBbre7r5swZSHgagP+8L39luQT8XfBgYHMHTcWgPr6enbv3m1xIvmo0MgwbvrsEgDWr1/Pnj17LE4kIiLifVQAFBlGpaWl1NXVAWr/Fd9y9uxZzp49C8C4rCzU/WuNzu5uth12zfeLjAkjoyDlkusTkzNIScsFYOuafSOeT2S0mJCTTWJ0NABbtmyhrb3N4kTyUUv/9lYCggMBePTRRy1OIyIi4n1UABQZRn3n/43RAhDxIfv3u2bK2QyDMZmZFqcZvXaVldPS3gHAmKl5V5zDOGGq6xTgqbJqKitqRzSfyGhhMwwWTZoAQHt7O5s3b7Y4kXxUTFIMCz7hGovwxhtvcPz4cYsTiYiIeBcVAEWGkfkLQlxcKomJWRanEemfnp4eDh1ybZzNSUkmPCTY4kSjU2t7BzuPlgIQlxRNStaVtzCPn7wA84jmtrU6BSgyXLISE8lPSwVgT8ke9wl/8R63PXwnhmHgcDh4/PHHrY4jIiLiVVQAFBkmTqeTLVu2ADCmeA6GeijFRxw/fpzW1lbA1f4r1th25Aid3d0AjJ2eh8GVv4dExcSTnTvOdZ+1+3A6nSOWUWS0WThhPHabDYfDwbp166yOIx+RkpvC9NtnAvD8889TW6tT0SIiIiYVAEWGybFjx6ipqQFgbLEWgIjvMJd/hAYFkZeacp1by3A439zCvuMVAKRkJhCfFH3N25ttwOeqznPs0JnhjicyasVGRDAlPw9wvVly7NgxixPJR9351bsAV6v2smXLLE4jIiLiPVQAFBkm5uk/gLFj5lqYRKT/WlvbKC8vB6A4MwO7TT8mrPDBoUP0OBwYhsHYabnXvf3YiXOx2QMA2LZm73DHExnVZo0pIjTYNRph3bp1OBwOixNJX7mT85iwaCIATz75JA0NDRYnEhER8Q76zU5kmJgFwJiYJJKTc6wNI9JPBw8edP8yq/Zfa9Q0nOfwqdMAZBakEBkTft37hIZFUDBmKgDb1+6nu6tnWDOKjGYhgUHMHTcGgPr6enaX7LY4kXzU3d/4GAAtLS088cQTFqcRERHxDioAigwDzf8TX7V37x4AEqOjSYqJsTbMKLX5gGsBi91uo3hKTr/vN3n6jQA0N7WxZ8uR4YgmIr0m5mSTEBUFwJbNW2hrb7M4kfRVPHsMxXNcRdrf//73XLhwweJEIiIi1lMBUGQYnDhxgsrKSgDGjpljcRqR/jl16rR7q+XEnBxUtx55J2rOcuLsWQByx2YQGtb/DcyFY6cTHuGaFfj+Sp1IEhlONsPGokkTANesuS2bt1znHjLS7vnGvQA0Njby1FNPWRtGRETEC6gAKDIMNm/e7L48tlgFQPEN5um/wAA7Y7IyLE4z+jidTjb1nv4LDA6gYGLmgO5vtwcwcdpiAA58WE59bZPHM4rIRdlJSe5FSSUlJdTV11mcSPoat2A8eVPzAXj88cdpaWmxOJGIiIi1VAAUGQZm+290VCKpqfkWpxG5vra2do4ePQpAcUYGwYGBFicafY6cPsPZ8+cBKJqYTVDQwP8NpsxcAoDT4WTLuyUeTCciV7Jo4gRsNhsOh4P169ZbHUf6MAyDe/7+XgDq6ur4y1/+Ym0gERERi6kAKDIMPvjgAwCKi2dp/p/4hAMH9tPd3Q242n9lZPU4HGw5eAiA0PBgcsakD+pxEpMzyMguBmDzyhIcDqfHMorI5WIjIpiSlwfAsWPHOHb8mMWJpK/JN00ha3w2AI8++ijt7e0WJxIREbGOCoAiHnby5ElOnToFwNgxcy1OI9I/e/a42n+TYqJJjo21OM3os/dYBY297WnFU3Kx2wf/43nKjJsAqK1s4EhJhSfiicg1zB5bRGhQEADr1613b1IX6xmG4d4IXFNTw/PPP29xIhEREeuoACjiYWb7L8DYMbMtTCLSP6dOnaK+vh6ACVr+MeLaO7vYdvgwAFGx4WTmJw/p8cZNnk9QUAgA69/YMeR8InJtIYFBzB03FnC1mpbsKbE2kFxi+m0zSCt0nar+3//9Xzo7Oy1OJCIiYg0VAEU8zCwARkbGkZ5WZHEakeszT/8FBgQwJnNgiydk6HaUltLW+wvpuOn5Qx4bEBwSyqTpNwCw+/1DNGgZiMiwm5ibTXxUJABbNm9Rq6kXsdls7lOAp0+f5sUXX7Q4kYiIiDVUABTxMHP+35ii2Zr/J16vubmFI0eOADAmM4PgwACLE40uF1rb2F1WDkBiaiyJ6Z5pv54+91YAHA4nG1fs9MhjisjV2QwbiydNBKCtre2SbgCx3uy755CSnwrAL3/5Szo6OixOJCIiMvJUABTxoDNnzlBRUQHA2DFzrA0j0g979uxxz6ua3DvIXkbOB4cO0d3TA8DY6XkYeOZNg6SULLLzxgOwccUuurt6PPK4InJ12UlJ5KakALB79273aAWxns1u495/+DjgOgX43HPPWZxIRERk5KkAKOJBfd/xH6MCoHi5np4e9vTOqspISCAxOsraQKNMbWMTB0+6FgZl5CUTEx/p0cefMe82ABrrm9n1/iGPPraIXNmiieOx2Ww4HA7WrFljdRzpY9Zdc9yzAP/nf/5HbdoiIjLqqAAo4kFmATAiPIaM9GKL04hc25EjR2np3Tw7JV+n/0bapv0HcDqd2Ow2xkzN9fjjF4+fRUSkq6X4vde2e/zxReRycZGRTC3IB+DEiRMcPHjQ4kRistlt3PvN+wCoqqriz3/+s8WJRERERpYKgCIeZBYAi4tmYbPpPy/xbrt37wIgMiyU/NRUi9OMLifO1lJRUwNA3th0wiJCPP4c9v+/vTuPj6q+9z/+OrNksu8JCSSEsO/7DrKIVgVcUet2tbdX7XrValtbt9u61Pbeq63aa6v2Z6uCVgURFSyi7JuAbLLvEJaQhJCELJNkZs7vjyEjSIBAJjnJzPv5eOSRyZwzZ94M35zMfM53sTsYNPw7AOzalMeeLQeD/hwicqYR3bsRHx0NwIIFC9TTrAUZPHEIWd39i1298MILVFZWWpxIRESk+ahCIRIk+fn57NmzB9D8f9Ly5efnc/jwYQD65uZis2nBmuZimiZLN20CwOly0LlP+yZ7rsEjr8ThjABg7nsrmux5ROQbToeD8f37AlBZWcmiRYssTiR1bDYb1z/o7wVYUFDAG2+8YXEiERGR5qMCoEiQLFu2LHBb8/9JS7d2rb/3n8Nuo0+HDtaGCTPb8g5SUFIKQNc+OUREOJvsuaJj4uk/+FIA1i7ZSsEhLUog0hw6ZmTQpV1bADZu3MjBQ+qB21IMvGIwOb1zAHjxxRcDU2GIiIiEOhUARYJkyZIlAMTEJNA+u6fFaUTOrry8gm3btgHQLSubKFeExYnCh8frZfkW/4Ic0bGRdOjersmfc9glk8EwMH0m86avbPLnExG/sX37EOFwADDvs3l4vVqNuyUwDIPrfjYFgKKiIl5//XWLE4mIiDQPFQBFgqSuANiz+0jN/yct2rp1awMfRLX4R/Nav3svZSfnnOo+IBe7venPFcmpmXTvNRSAZZ+u40SJeruINIe4qChG9vJfECwqKmLVai3G01L0v2wAuX39iy/9+c9/5sSJExYnEhERaXqqUogEwf79+zlw4AAAPXuMtDiNyNnV1NSwfv16ANqnp5OemGBtoDDirqlh1fbtACSkxNIuN73ZnnvE2OsAqKn28JnmAhRpNv065tImKRGAFctXUHSsyNpAAvh7AV7/0I0AFBcX85e//MXiRCIiIk1PBUCRIFi8eHHgdq+eoyxMInJuX3+9KbAi5aAunS1OE16+3L6D6tpaAHoO6oRhNN/CK1k5XenQuQ8A86avpLxUK1+KNAebYXD5wAHYbTa8Xi//+vRf+Hw+q2MJ0GdcX7oO7QbAyy+/TGFhocWJREREmpYKgCJBsHTpUgASE9PJzOxkcRqR+vl8Pr76ag0AqQnx5KQ3Xw+0cFdaUcmG3f5VwtOzkknLTGr2DGMuuwkAd2U1/3p32Xn2FpFgSUtIYGh3f6HpyJEjrF692uJEAv5egDf/+hYAKioqeP755y1OJCIi0rRUABRpJNM0A/P/9eoxqll79YhciB07dlJa6l99dlDnLqipNp/lW7bg9fkwDOg50Jp5F3M69lIvQBGLDOnaJTDlwrJlyzh27JjFiQSg86AuDPjOIADeeOMN9u3bZ20gERGRJqQCoEgjbd++PTBspKeG/0oLtvrkBPSxUZF0y2761WfFL/94CdvyDgKQ3SmD+KRYy7Kc1gvwn+oFKNJc7DYb3xk0ENvJocBz5szRUOAW4sZf3oxhM6itreUPf/iD1XFERESajAqAIo1U1/sPoJcWAJEWKi8vj/z8fAD6d+qEXStVNwvThMVffw2A3WGj24BcS/PkdOxF7slegJ+9v4KSIq18KdJc0hISGNqtKwD5+fksW64ifEvQrms7Rt94CQAzZsxg06ZNFicSERFpGvoEKNJIdQXA9PQcUlOzLE4jUr+6OaciHA765nawNkwY2XX4MIeK/EP9OvXMJiraZXEimDDpDgBq3LXM+scCi9OIhJeh3bqSmeyfA/TLlV+SdzDP4kQCcN2DU3C4nJimydNPP211HBERkSahAqBII3i9XpYt81/BV+8/aamKio6xe/duAHrndsDldFqcKDx4vD6WbNoMQGR0BJ37tLc4kV+79l3p1X80AEs/Xc+hvQUWJxIJH3abjSuHDCbC4cA0TebMnoO72m11rLCX0jaFy+66HIAvvvgi8N5OREQklKgAKNIIGzdupKysDIBemv9PWqgvv1wJgM1mY0AnrVLdXDbs2UNpRQUA3Qfk4nDYLU70jQkTb8dmd2D6TN5/ZZ7VcUTCSmJMDOP69QWgrKyMeZ/pd7AlmPyTq4mKiwLgqaeewjRNixOJiIgElwqAIo1w6vx/PdQDUFqgkpIStm7dCkDP9tnER0dZnCg8VFXX8OW27QAkJMeS3SnD4kSnS0rJYOioqwDY9OUuvv5yp8WJRMJLz5xsumX5F2Patm0bGzZusDiRxCbFMfFHkwH46quvmDVrlsWJREREgsthdQBpHez2ltNz5duszFZXAMzO7k5SYrplORrLMIzAd5sWhwgqq1/PVatWYZomhmEwpGvXwP9162IEvreW+Cu3baO6thaAXkM6Y9haXvAxl9/EhjULqao8wdsvfsqTf88lwqXh4Rfsm+aJQcv7f27NWuf5qmEMDCYM7E/+8eOUVlTyxedfkJGRQWZGZnCfR3/fL8iV90xk/ptfcDy/mKeeeopJkyYRGRlZ774t+b1xa1H3Guq1DD69piJSH8NU/3aRi1JdXU1SUhJVVVVMmvgD/uN7z1gdSeQ0ZWVlvPjii3i9Xnq0z+bqEcOtjhQWjpWV8fd/fYbPNMnMSWPYhD5WRzqrtV9+zsfv/R8A1/77eG74jwkWJxIJL0eKi3n7iwV4fT4SExO59957iYpST20rLX5vIX/+8YsAPPvss/zqV7+yOJGIiEhwqAegNMjx48etjnCa+Ph47HY7Xq83MAdfc1u2bBlVVVUAdO82HLe79U7ibRgGLpeL6upqzXkTBC6XC8MwME2T6upqy3IsXrwEr9cLwOCuXfF4PJZlaRwDh8OOx+MFWn77XLB+Az7TxGYz6DEwF5/PZ3Wk05zaC6jfoHGs+/JzDu7fzuypixl6aS8yslMtTNcKGeCwO/B4Pa2hebZ4docdAwMTE6/Ha3WcJpcWH8/4/n35fO16SkpKmDFjBlOmTAla70f9fb9wgycPJfeVjuzdsIdnnnmG66+/nvR0/yiPlvD+M5TY7Xbi4+MpKysLvF+Rixeq7TMpKcnqCCIhQwVAaZCW/EfZqmwLFiwAwDBsdOsypMV9yL8QdQUB0zRb9b+jJbLq9aysrGTjyTmlOrXNJDU+rtV++Pvmc7DZ4v8N+48WsOdIPgAdurcjNj66RReFDMPGxBvu5bUXfoGn1subz33CQ8/dia0FDlluqQLDfk1afPtsbcLl9ezdIYfDRcVsOXCA3bt3s3TpUkaNCs7CYvr7fnFueew2nr3pacrLy3nmmWd4/vnnz9inJb83bm28Xq9ezyDT6yki9dFkICIXqa4A2LnTAKKj4y1OI3K6NWvWUHtyDrqhXbtanCY8+EyTxZs2AeB0OejaN8fiRA3TJrMDw0f7J77fvn4f82eusjiRSHgxMLh0QF/SEhIAWL58Odu2bbM4VXjrNqw7gycOBWDatGls3rzZ4kQiIiKNpwKgyEU4duwY69evB6Bvn7HWhhH5lurqatatWwdATno6GckaOtEcNu/bT1Gpf8hNt74dWtWCGmOvuIWUdP+KpDNe/Zz8A0UWJxIJL067g6tHDCXa5QLg008/5Uj+EYtThbebf30LjggHPp+PJ554Imx6pIqISOhSAVDkIixevDjwRrBPrzEWpxE53Zo1X1FTUwPA0G7q/dccamo9LN+yFYDYhGg6dG9rcaIL43S6uO6792HYbNTWeHj9D7PwejVcUKQ5JUTHMHn4UOw2Gx6Ph5kfzORE+QmrY4Wt9Jx0vvP9KwH/+75PP/3U4kQiIiKNowKgyEWoG/4bE5NAx479LE4j8g23u5qvvloDQFZqKu1StaBDc1i1YweVJxd86Tmo42kLbbQWbbM7M3r8DQDs2XKQWX9fYHEikfDTLiWFCQP6A1BRUcEHMz6wdDGpcDf5p9cQn+Yfmv3YY49RWVlpcSIREZGL1/o+oYhYzDTNQAGwV8/R2Gx2ixOJfGPNmjWBD4vDe3QnSAtJyjmUlFewducuAFIzk2iTnWJxoot3yYQbaZvdGYA505ayadUuixOJhJ9eOe0Z3LULAAUFBcycObMVr+LeukXHR/PdR24FIC8vj2effdbiRCIiIhdPBUCRC7Rt2zby8/2rfPbtrfn/pOVwu92B3n/Zaalkp6n3X3NY/PUmvD4fhmHQe0inb1aFbYXsDidTbn+IyKgYAP72zAcUF5ZZnEok/Izu1ZMe7bMBf+Fp9uzZmoPOIiNvGEXXIf7pNJ577jl27NhhcSIREZGLowKgyAWq6/0H0Ke35v+TlmP16tWBuf+G9+hhcZrwsC//KLuP+Cfq79C9LfFJsRYnarzE5HSuufmnAJSXVfHyE+9SU11rcSqR8GIYBpcPHECHNm0A2LFjB/PmzbM4VXgyDIN/e+bfsdlt1NTU8J//+Z8qxoqISKukAqDIBaorALZt25mUlNY10b+ErqqqKtauXQtA+/Q0slJb7zDU1sLr87Ho668BiHA56davg7WBgqhbr6GMGHMNAPu2Hebvf5ilD7wizcxuszF52BAyT67kvmHDBubPn29xqvCU3T2by//9OwB89tlnfPjhh9YGEhERuQgqAIpcgKqqKlauXAlo+K+0LOr91/zW795D8YlyALoPyCXC5bQ4UXBdOvEOOncfCMDqBZv5+M1FFicSCT9Oh4NrR44gJT4egK+++oqFCxdaGypMXfezG0hMTwTgwQcfpKKiwtpAIiIiF0gFQJELsGLFCtxuNwB9VACUFqKy8pvefznp6bRLSbY4UeircLtZuXUbAAnJseR0zbQ4UfDZbHZuuO1npGW0B+Cjfyxi1fxNFqcSCT9RERFMuWQkyXFxgP+Cz6LFKsg3t6i4aP7tye8B/nkZ//CHP1gbSERE5AKpAChyAeqG/zodLrp3G2ZxGhG/1atXU1vrn6NteI/uFqcJD8s2b6Xm5KqcvYd2xgjR5ZZdkdHc8r1fEx3j7330+u8/ZNu6vRanEgk/Ma5IplwyiqRY/zyjq75cpZ6AFhh1w2h6X9IHgFdeeYV169ZZnEhERKThVAAUuQBffPEFAN26DcHlirI4jQhUVlaybp2/91+HNum0Ve+/JpdffJzN+/cD0C43nZQ2idYGamKJyencfNfDOBwReGq9vPToP9m3/bDVsUTCTmxkJDdeMorEk0XA1atX86+5czU/ZzMyDIN7n/8REVER+Hw+HnjggcD0GyIiIi2dCoAiDbRnzx527twJQP9+EyxOI+K3cuVK9f5rRqZpsnDjRgDsDjs9B3W0OFHzyO7QnSl3PIhhs1FdVcOfHp7GkQNFVscSCTuxUVHcNGY0qSfnBPx640Y+/vhjvF6vxcnCR0ZuBjf/6lYAtmzZwksvvWRxIhERkYZRAVCkgT777LPA7QH9VQAU65WVlbF+/XoAOmZmkJms3n9NbcuBPI4UHwegS5/2RMVEWpyo+XTtOYRrbvoJAOWllTz/87c4drTU4lQi4Sc2MpKbxowOrA68fft2Zs6cGbgYJE1v4r2TyO3nvwD03HPPsX37dosTiYiInJ8KgCINVFcAbNu2M23SO1gbRgRYvmw5Xq8XwzAY2bOn1XFCXnWth2WbNwMQHRdJp17ZFidqfn0HjeM71/w7AMcLy/jjL96i7LhWwhRpbpEREdwwehTZaWkA7N27l3fffZeKSv0+Nge7w873//tu7A47tbW1/OxnP1MvTBERafFUABRpgLKyMlasWAHAwP6XWZxGBI4dK2bTZv+KrN2y2pGWEG9xotC3YutWKtzVAPQa3Bm7PTz/hA4bPZlLJtwIQH7eMf74y6lUlrstTiUSfiIcDq4bOZzObf2rkB85coRpU6dx7Ngxi5OFh+we7Zn0k6sB/3yMr732msWJREREzi08P72IXKD58+fjObnip+b/k5Zg2bKlmKaJzWZjRI8eVscJeYUlpazfvQeA9LbJZLRPsTiRtcZ+5xaGjLwKgLxd+bzwq7eprtJE+CLNzWG3M2nYUPp38g9HLS0tZdq0aRw4cMDiZOHh6p9eS9su7QB4+umn2bZtm8WJREREzk4FQJEGmDdvHgCxMYl06TzI4jQS7o4ePRqYb6h3hxwSY2MsThTaTNNk/oYN/oKr3Ubv4V0wMKyOZSnDMLjimu/Td9A4AHZvzuPPj79LbY3H2mAiYchmGIzv15exfftgGAbV1dW8//77gV7i0nScLif3/vGH2B12qqur+dGPfqRVgUVEpMVSAVDkPLxeL59//jkAffuOx253WJxIwt3ixYsBf8+PYd26WZwm9G3ef4DDx4oB6NK7PbFxURYnahkMm42rb/wx3fsMB2DrV3t49akZeL0+i5OJhKeBnTtx9fChOOx2fD4fn875lEWLFmGaptXRQlqHvrlc+7MbANi0aRP//d//bXEiERGR+qkAKHIea9asobjY/+F/oFb/FYvl5eWxb98+APp36khsVPisQmuFquoalm7yL/wRExdF5z7ht/DHudjsdq6/9QE6de0PwLql2/j7H2bh86ngIGKFTpmZ3DRmNDGRLgBWrlzJO++8Q3V1tcXJQtukH02m86AuALz00kusXLnS4kQiIiJnUgFQ5Dzmzp0LgN3uoE/vsRankXBX1/vP5XQypGsXi9OEvmVbtlB1cjhX72GdsdvtFidqeRwOJzfd+UuyO/jnolw5byNvvzBHvY5ELJKRlMQt48aSnpgIwM6dO3nzzTcDFzMl+OwOO/f+8Ye4ol34fD5+/OMfU1JSYnUsERGR06gAKHIen332GQDdug4lJibB4jQSznbt2s3hw4cBGNSlM5ERERYnCm1HiovZtG8/AG1z0mjTLrwX/jgXZ4SLW/7912S08y9EsPCjNXz4+gKLU4mEr/joaG4eO5ru2VkAFBcXM3XqVHbv2W1xstCV3qENt/3m3wB/b/37779fF0JERKRFUQFQ5Bz27NkTWGxBq/+KlUzTZOnSJQBEu1wM6NzJ4kShzeczmb9+I6Zp4nDY6TVEr/f5REbFcPvdj5Oa7i84zJ66hKVz1lmcSiR8Oe0Orho6mLH9+gYWB5n5wUwNT21CY747luHXjgBgzpw5vPbaaxYnEhER+YYKgCLn8MknnwRuDx50hYVJJNxt3bqNwsJCAIZ260aEQ4vRNKUNe/dScHL4Vtd+OUTFaK7FhoiOiee2ux8nLj4ZgLee/4QtX+2xOJVI+DIwGNa9G9ePGoHL6cQ0TZYsWcLHH39MbW2t1fFCjmEY3PXs92mTmwHAb37zG9at04UQERFpGVQAFDmHjz/+GIAOOb1JT2tvcRoJV16vl2XLlgL+YV19cjtYGyjElVe5WbFlKwBxiTF07JllcaLWJSExle9+79c4IyLxen385b/e49DeAqtjiYS1Dm3acOv4sSTHxQGwbds2pk2bRklpibXBQlBUbBQ/fvk/cbic1NbWcs8992g+QBERaRFUABQ5i7y8PNavXw/AkMETrQ0jYW3duvWBDw/De3THYdepuykt3LiR6pM9Y/oO74LNptf7QmVmdeSG236GYdioqqjmpUfeoby00upYImEtKTaWW8aNoVPbTAAKCwt568232Ld/n7XBQlBOrxxue+IOAPbv38+9996L1+u1OJWIiIQ7faoROYvZs2cHbg8dogKgWKO6upqVK1cAkJaQQI/22RYnCm27Dh9h5yH/Qis5XTNJaZNobaBWrGvPwXznmn8HoCi/hL/9biY+nybEF7GSy+nk6mFDGd6jOwBut5vp709n1epVFicLPePvuJRRU0YDsGDBAp555hmLE4mISLhTAVDkLOqG/2ZldSMzo6PFaSRcrVz5JVVVVQCM7t0Lm2FYnCh0Vdd6WLBhAwCuqAh6DNLvfWMNGXkV/QaPB2DTql188tYiixOJiGEYjOjRnWtGDCPC4cA0TRYtXMQnn3yieQGDqG4+wNy+uQC89NJLzJw50+JUIiISzlQAFKlHfn4+q1b5r4YPGXSVxWkkXJWVnWDt2q8AaJ+eTk56usWJQtuyzZspr3ID0HtoZyIinBYnav0Mw+Cq6++hTVv/B+CP31jEplW7LE4lIgCdMjNPzgsYC8DWrVt5++23KS0ttThZ6IiIjOCnrz5AfGo8APfffz8bN260OJWIiIQrFQBF6nHa8F/N/ycWWbp0CR6PB8MwuKR3L9T5r+kcPlbMxr37AGiTnULbDmnWBgohTqeLm/7t50RGxWCa8NozH3DsqAoMIi1Bclwct4wbS8dM/6q1BQUFvPXWW+zfv9/iZKEjpW0KP/nLfdgddqqqqrj99ts5fPiw1bFERCQMqQAoUo8PPvgAgIyMjmRldbM4jYSjgoICtmzZAkD37CzSExMsThS6PF4fn69bh2maOJx2+g7rgoGqrcGUlJLBtd+9D4CKsir+37Mz8Xl9FqcSEfDPC3jN8GGBeQGrqqp4//33Wb16tcXJQke3Yd35t6e/B/hHmdx2222Ul5dbG0pERMKOCoAi33LgwIHA8N9RI67DULcrscCiRYv8BSm7jZE9e1gdJ6St2bmTY2UnAOgxIJeomEiLE4Wmrj0HM3zMNQDs2LCfue8ttziRiNSpb17AhQsXal7AIBp323gm/fhqADZv3sx//Md/4PF4LE4lIiLhRAVAkW+p6/0HMGLYtRYmkXC1b98+9u3bB0D/Tp2Ij462NlAIKz5xglXbtgOQlBZPh+7tLE4U2sZfeRvpmTkAfPj6AvbvOGJxIhE5VafMTG4ZP5akWM0L2BSm/PImhl49HID58+fzi1/8AtPU6ugiItI8VAAU+Za6AmDH3H5kZORanEbCjWmaLFrkXyk1MiKCIV27WpwodJmmyedr1+P1+bDZDPqN6Koev03M4XBy/a0PYHc48Xp8/O13H1Bbox4wIi1JSlwct46vZ17AA5oXsLFsNht3P3cvXQb7/7ZPnTqVJ598UkVAERFpFioAipxiy5YtbN26FYCRI66zNoyEpc2bt1BQUADAsO7diNRKtE1m3e49HDp2DIBOvbKJT4q1OFF4SM9oz4Sr7gDgyP4i5kxbYnEiEfm2unkBh3X3z4NcVVXF+++9z5o1ayxO1vpFREZw/+sP0q5rFgB//vOfeeGFFyxOJSIi4UAFQJFTTJ8+HQDDsDFs6GSL00i48Xg8LF3qL4YkxMTQN1c9UJvK8fJylm32L7ISlxhD134drA0UZoaMuop27f09YOa8vZRDewssTiQi32YYBiN79uDq4UMD8wIuWLCA2bNna17ARopNjOXnUx8mrX06AM888wyvv/66xalERCTUqQAocpLP52PmzJkA9Oo5kqTENhYnknCzZs1XnDjhX4xiVM8eOOw6RTcFn2ny2Vfr8Hi9GIZB/1HdsOu1blY2m53JN/4Im92B1+Pjjf/5SKsCi7RQndu25ZbxYwLzAm7ZssU/L2CZ5gVsjKSMJH759q9IbJMEwMMPP8z7779vcSoREQll+sQjctKSJUs4ePAgACOHX29xGgk35eUVfPnlSgAykpLomqXFKJrK+l17OHxy6G/n3tkkpcZbnCg8pWe0Z/SlUwDYs/UQX8xcZXEiETmblLh4bhk/htyMb+YFnPrWVA4dOmRxstYtrX06v5j6MDGJ/uLqT3/608BoFBERkWBTAVDkpGnTpgEQGRnL0CETLU4j4Wbp0iXU1NQAMLZvHy1G0USKT5SzbIt/6G98kob+Wm30+OtJa5MNwMz/N59jR9WjSKSlinRGcO2Ib+YFrKys5N1332Xzls0WJ2vd2nXL4qG3fkFUfDQ+n4+f/OQnvPfee1bHEhGREKQCoAhQXFzM7NmzARgx7GoiI2MsTiTh5OjRo2zatAmAbllZtE1JtjhRaPKZJvPWrj1l6G93Df21mN3hZPKNPwbDoMZdy/t/+czqSCJyDnXzAk4cOhiH3YbX62XO7DksXrJYK9k2Qsd+nfjFtIeJPlkE/OlPf8o///lPq2OJiEiI0ScfEfyLfwR6X425xeI0Em7mz5+PaZo47HZG9+5pdZyQtXbnbg4fKwagS5/2JKbEWZxIALJyujJgyAQA1izawtav9licSETOp1tWFjdeMpqYSBcAX678ko8++kiLgzRCx36d+OXbvyYmIQbTNLnvvvsCo1NERESCQQVACXumafL2228DkNWuK5069rc2kISV7dt3BOaeHNSlM/HR0RYnCk2FpWUsP2Xob5e+ORYnklONv/I2IqP8Pa/ffulTPB6vxYlE5Hwyk5O5dfxY0hISANixYwdvv/12YDEruXAd+ubyi7d/FSgCPvDAA7zyyitWxxIRkRChAqCEvQ0bNrB5s3/+mrFjbtHca9JsPB4PixYtBCA2KpLBXbtYGyhEebxe/rV6DV6fD5vNYMBoDf1taWJiExj3HX/v6yP7i5j/gRYEEWkN4qKiuXnsJXRumwn4Fwd56623OJJ/xOJkrVeHPrn88p+PEJfs76X+2GOP8fvf/15DrEVEpNH0CUjC3j/+8Q8A7HYno0Zo9V9pPl999RWlpf5FD0b17EWEw2FxotC0dPMWisrKAOg+IJeEZA39bYkGDb+C9Ex/z8yP3lhIyTH1IhJpDSIcDiYPG8qQbl0BqKio4J/v/JNt27ZZnKz1yumVw6+nP05y2xQAnnvuOX71q1/h8/ksTiYiIq2ZCoAS1oqLi5kxYwYAw4ZMIj4+xeJEEi7KyytYuXIlABlJSfRon2VxotC0/2gB63btBiA1I5FOvbItTiRnY7Pbueq6uwFwV9bw4esLLE4kIg1lGAaje/XkisEDsdtseDwePv74Y5YtX2Z1tFarbee2PDrjcTI6+XtXvv766/z4xz/WPIsiInLRVACUsDZ16lTcbjcA37n83y1OI+Fk8eJF3yw807ePhp43garqGuZ+tRYAZ4SDAaO763Vu4drn9qRnv1EALPt0HXm7j1qcSEQuRM/27ZlyySiiXf7FQZYvW87HH3+Mx+OxOFnrlNIulUemP05O7w4AzJgxgzvvvJOKigprg4mISKukAqCELY/Hw9///ncAOub2o3OnARYnknBx8OChwLyT3bOzaJuSbHGi0GOa8Pm69VScLPD3Hd6VqJhIi1NJQ1x61e3Y7Q5ME6b/dZ7VcUTkArVLSeGW8WNIiY8HYNu2bfzzn/+kvKLc4mStU3xKPL969xG6De8OwOeff851111HQUGBxclERKS1UQFQwta//vWvwOqr6v0nzcXn8/HFF58D/nmTLund2+JEoWnDnj3sOnwYgKxObWiXm25xImmopOQ2DB01EYDNa3azadUuixOJyIVKiI7hu2MvITcjA4AjR44w9a2pHC1Qr96LERUXzUNv/pJBVw0BYP369UycOJHdu3dbnExERFoTFQAlbL322msAJMSnMWzIJIvTSLhYt2594Kr98B7diY1Sr7RgO3q8hMVfbwIgJi6KPsO0unJrM3rCjURFxwLw/l/n4fNq4nuR1sbldHLNiGEM7NwZgBMnTvDO2++wc9dOi5O1ThGREfzk5f/k8u9fAcD+/fuZOHEiq1Zp1XQREWkYFQAlLK1du5bly5cDcOn423A6XRYnknBQUVHJsmVLAUiJj6d/p44WJwo91bW1zFm1Gq/Ph81uY/C4njidWl25tYmMimHMZTcDcGhvAUv/td7aQCJyUWyGwdi+vZkwoD82m43a2lpmfThLRauLZLPbuP03/8atT9wO+BezmzJlCp988onFyUREpDVQAVDC0gsvvABAREQkl0/4nrVhJGwsWrSQ6upqAC7t1xe7TafgYDJN+HztekpOTo7ee3AnEpLjLE4lF2vQ8O+QnOIfPjjr9QW4q2osTiQiF6tvbgeuHzWCyIgITNNk0aJFfPrpp3i9XqujtUpX3H0VP/6/n+KIcOB2u/n+97/Pq6++anUsERFp4fTpU8LOtm3bmDNnDgDjxt5KfHyKxYkkHHx74Y+stFSLE4WejXv2suPQIQDadkgjp3tbixNJY9gdTiZMuhOA0uJy5v5zmcWJRKQx2qelccu4MSTF+of3b9q0iffee4+qqiqLk7VOQ68ezi+m/YqYhBhM0+TRRx/lv/7rv/D5NGWCiIjUTwVACTsvvvgiAHa7g0lX/sDiNBIOvF4v8+Z9Bmjhj6ZypPg4i77+GvDP+9dvRDcMDItTSWN16zWU7A49AJj73gpKjp2wOJGINEZSbCy3jBtDdloaAAcPHmTq1KkcO3bM4mStU7dh3Xn0gydIyfJfVHz55Ze59957cbvdFicTEZGWSAVACSv79+/ngw8+AGD0yCmkpKiHkDS9L79cRVFREQAjevbQwh9BVuF288mXXwbm/Rs0tifOCM37FwoMw+Dyyf5egDXuWj76x0JrA4lIo0VGRHD9qBH0ye0AQElJCdOmTWPvvr3WBmul2nZpx+Mz/4uc3jkAzJo1iylTpqioKiIiZ1ABUMLKc889h9frxTAMJk38odVxJAwcO1bMypUrAMhITtLCH0Hm9fn45MtVlFf5ezv0G9GVxBTN+xdK2rXvSo++IwBYMmcdh/cXWpxIRBrLbrMxYUA/xvbtg2EYVFdXM2P6DNauW2t1tFYpsU0Sv3rvMfqM6wvAqlWruOqqq9i9e7fFyUREpCVRAVDCxo4dO3j33XcBGDH8OtpmdrI4kYQ60zT57LO5eL1ebDYblw0YgM3QsNRgWrhhI4ePFQPQsUc7sjtlWJxImsKlV96Oze7A9JnMePVzq+OISBAYGAzs3IlrRwwjwuHANE2++PwL5n0+T/PYXYSo2CgeeP0hxt8xAYC9e/dy1VVXsXLlSouTiYhIS6ECoISN3/3ud/h8Pux2Bzde/6DVcSQMfPXVWg4ePAjA4C6dSUuItzhRaNm4Zx8b9+4DIDUjkZ6DVdQPVcmpmQwe/h0ANizfwfb1+6wNJCJBk5uRwXfHjSE+OhqA9evWM2PGDKqrqy1O1vrYHXbufOZ7fPfRWwE4fvw4U6ZMCUx/IyIi4U0FQAkLa9euZfbs2QCMH3sb6ek5FieSUHfixAm++MLfUykpNpZh3btZnCi0HCwsYuHGjQBExUYyaGxPbDb9SQtloyfciCvSXyB4/5V5mKZpcSIRCZbU+HhuHT+WtinJAOzbt49p06ZRUlJibbBWyDAMrvrBJH7yl/twupzU1NTwgx/8gOeff17nTRGRMKdPSxLyTNPk6aefBsAVEcW11/ynxYkk1JmmyezZswO9Fy4b0B+H3W5xqtBxrOwEH630L/phd9gYMq4XrsgIq2NJE4uJTWDkuOsB2LftMGsWbrE4kYgEU7TLxZTRo+jRPhuAY8eOMXXqVPIO5lmcrHUaMmkoD7/7KHEp/tEHzz77LA888AC1tbUWJxMREauoACghb/bs2SxZsgSA73zn+yQltrE4kYS6DRs2sn37dgB6d8ghKy3V4kSho8JdzawVK6iurcUwYOAlPbToRxgZNnoScQn+HkIf/O0LPLVeixOJSDA57HauGDyQUb16AlBVVcX7773P15u+tjhZ69R5YGce//A3ZHTKBODtt9/mlltuobS01OJkIiJiBRUAJaRVVlbyxBNPAJCYmM41k35icSIJdWVlZcyd+y8AEmJiGNOnj8WJQketx8tHK1ZSWlEJQK/Bnclsn2ZxKmlOzggX46/wz21VePg4C2ettjiRiASbgcHQbl2ZPGwIDrsdr9fLvz79F4sWLdIQ1ouQnpPOYzP/i27DuwOwePFiJk+eTF6eelaKiIQbFQAlpP35z38OvMG55eZHiIqKtTiRhDLTNPn0008DQ3+vGjIYl9NhcarQ4PX6+OTLVeQfPw5Abo925PZsZ3EqsUKfgWNJz2gPwCdvLaay3G1xIhFpCl3atePmsZcQGxUJwKpVq/jwww+pqamxOFnrE5sYy8/fepiRN4wGYNu2bVx55ZWsX7/e2mAiItKsVACUkLV//35eeuklALp0HsSoEddbnEhC3dq16zhw4AAAg7p2ITs93eJEocFnmsxZtYq9+fkAZGSn0ntIZwwMi5OJFWw2OxMm3QlAeVkVn76z1OJEItJU2iQmcuu4saQnJgKwa9cu3nnnHU6cOGFtsFbI6XJyzx9/wLUP+N8PFxQUcO211/Lpp59anExERJqLCoASkkzT5Oc//zlutxvDMLjzjicxDBULpOkUFhayePEiAFLi4zT0N0hMExas38DWA/6evCkZiQwa20O/z2GuU9f+5Hb2/459Pv1Ligs0n5VIqIqNiuLmMaPp0q4t4C9cvfXWWxw5csTiZK2PYRhc/+AU7n7uXuxOO5WVldx111288sorVkcTEZFmoAKghKR33nmHhQsXAnD5Zd8jt4OKMdJ0ampq+Pjjj/F4PNhsNiYOHYrToVV/G8s0YenmzWzYsxeAxNQ4hl7aG7tWVA57hmEEegHW1nj48PUFFicSkabkdDiYNHQIQ7t1BaCiooJ//vOfbN682eJkrdPom8bw87ceJjo+GtM0eeyxx/j1r3+N16uFlUREQpkKgBJy8vPzefzxxwFIS8vm5hsftjiRhLrPP/+cY8eOATC6V08ykpMtTtT61RX/1uzYCUBcYgzDL+uLU3MqykmZ7TrSZ+AYAFZ8toG8XfkWJxKRpmQYBqN69eSKwQOx22x4PB7mzJnDggUL8Pl8VsdrdXqM7MljM/+L1Gz/Ylp/+9vfuOuuu6ioqLA4mYiINBUVACWk1A39LSsrA+A//v0PRLqiLU4loWzTps2BHggdMzMY2LmzxYlaP9OExZs2BYp/sfFRjLyiPxGRTouTSUsz7opbsTucmCZMf/Vzq+OISDPo2b49N40ZTUykf3GQNWvWMGPGDNxuLQh0odp2acfjH/6Gjv07ATB37lyuueYa8vN1QUVEJBSpACgh5R//+Adz584FYNyYW+jdc7TFiSSUFRUV8fnn8wCIi47iikED0dR0jWOaJgs3fs3anbsAiE2IZuSV/YmKcVmcTFqixKR0ho6aCMDm1bvZvGa3xYlEpDlkJidz26VjyUxOAmDfvn289dZbFB0rsjhZ65OQlsDD7z7CoKuGALBx40auvPJKtmzZYnEyEREJNhUAJWRs27aNJ554AoD09Bxuv/UJixNJKKuqcjNz5kxqa2uxGQYThwwhMiLC6litmtfnY+5Xa1m/21/EiUuMZuQV/YmMVvFPzm7U+BuIjIoF4L2XP8Pr1VBAkXAQGxnFjZeMpldOewBKSkqYNnUaO3fttDhZ6+OKcvGTv/wnV97rv6By6NAhJk+ezIIFml9VRCSUqAAoIaGmpoYf/OAHuN1u7HYHP/nhS0Sd/EAoEmw+n4+PPppFSUkJAGP69qFtiub9a4yaWg+zVqwMrPYbnxTLiO/0JzJKRVU5t6joWMZcfhMAh/YWsGDmKosTiUhzcdjtXD5oAOP69cVmGNTU1PDhzA9ZvmI5pmlaHa9Vsdls3PLYbdz5zPcwbAYnTpzg1ltv5a233rI6moiIBIkKgBISnE4n//Ef9+JyRTHl+ofo1LG/1ZEkhH3xxXwOHDgAQJ/cDvTv2NHiRK1bhdvN9KVL2X+0AIDUjERGXaninzTckBFXkZbh7wU06x8LKS0utziRiDQXA4MBnTpy/eiRgZ74y5Yu46OPPqKmpsbidK3Ppf92GQ+8/hCuaBder5cHH3yQp59+WgutiIiEABUAJSQYhsGUG27l2afnMXnij6yOIyFs3bp1rF+/DoB2qSmM79dX8/41wtHjJbyzYBFHj5cA0LZDGsMu64szQqv9SsPZ7HauuvZuAKoqqpnx2hcWJxKR5tY+LY1bx48lNSEegB07djBt2rRAb31puH6X9ueRGU+Q2MY/x+ILL7wQGGkjIiKtlwqAElLS09pjs6lZS9PYvn07X3zhLyzER0czedhQ7GpvF21b3kHeW7yEE1VVAHTsmcWgMT2x2/WayoXL6dSLXv39Cz8t/9d6dm/OsziRiDS3xJgYvjt2DF3atQX8i3W99dZb7N6jBYIuVE6vHJ746Ddk9/D3rv7www+54YYbKCwstDaYiIhcNH3KEhFpgP37DzB79mxM08TldHLtiOFEu7Q4xcXw+nws/noTn65eg8frxWYz6D+yG72HdMZQd0pphMsm3UlERCQA016YowVBRMJQhMPBpKFDGNGzB4Zh4Ha7+WDGByxZskTzAl6g5MwUHpn+GH3G9QVg9erVXHbZZaxbt87iZCIicjFUABQROY+DBw/x4Ycz8Xq9OOx2rh05IjDESC5MaUUl7y9ewlc7dwHgiopgxBX9ad8l0+JkEgriE1K45DL/giAHdubz2XvLLU4kIlYwDIPh3btx7cjhgXkBV65cyfvvv09lZaXF6VqXqLhoHnj9IS698zIADh8+zNVXX83bb79tcTIREblQKgCKiJxDXt5Bpk9/n5qaGmyGwaShQ2inFX8vyo5Dh5k2fwFHio8DkJyewJhJA0lJT7A4mYSSYZdMpk3bXABm/X0h+QeKLE4kIlbJbdOG2y4dS5sk/1x2+/fv58033+TQ4UMWJ2td7A47dz79Pb7/P/fgiHBQXV3N/fffzy9/+UsttCIi0oqoACgichb79+9nxozp1NbWYrPZmDh0CB0zM6yO1epUVdcwZ9UaZn+5iuraWgwDuvRpz8gr+hEVE2l1PAkxdruDq2/6MYbNhqfWyxv/+zE+n4b9iYSrhOgYbh47mr4d/RcGTpw4wT/f+SdfffWVxclanzHfHcsj0x8nOdN/IfTvf/871113HYcPH7Y4mYiINIQKgCIi9di8eTPTp/uLf3abjclDhwQmFZeG23noMG9+/gXbDx4E/EN+h13Wlx4DO2rBHmkyme06MnLcdQDs/PoAC2ettjaQiFjKYbMzoX8/rhg8EIfdjs/nY/78+Xz44YdUuausjteqdOzfid/Mfopuw7sD/nkBx48fz2effWZxMhEROR99+hIROYVpmqxYsYI5c+bg8/lwOuxMHjaUTm01R92FKCmv4MPlK/nky1VUVlcDkNWxDeOvHUJ6Ww2hlqY3ZsJNpKS3A2DGq59TePi4xYlExGo927fn1vFjSIqNBWDnzp288Y83yMvTquEXIj41gV9M+xVX3HMVAMXFxdx+++08+uijVJ/8my8iIi2PCoAiIie53dV8+OGHLF26FIBol4sbR4/WsN8LUOvxsnzrNt764gv25ucD/l5/Q8b3ZuAlPYhwOS1OKOHC4Yzgmpt+AoZBtbuW156egcfjtTqWiFgsNT6BW8ePpUf7bMA/JPjdd99lydIl+HxaObyhHE4Htz5+Ow+8/hCxSf6C6quvvspVV13Fjh07LE4nIiL1UQFQRAT/qnZvvvkGu3b5V6dNiY/ju+PGkJGcZHGy1sHr87Fx7z7+MW8eX27dhsfrwzAMcnu0Y/x1Q8hsn2p1RAlDWTndGDX+egD2bD3ER39faG0gEWkRXE4nVw4exJWDBxHhcGCaJitXrOSdd97heIl6C1+I/pcN4Km5vwsMCf7666+59NJLeemll/B4PBanExGRUxmmaWpmbDmvoqKWtYpiUlISdrsdr9fL8eP+N2oV5T6WLtKwg4ths9mIjIzE7XaH3dXv2tpalixZwtq1a6k7HfZon82E/v1xOuwXdUyHw4lhgGmCx1MbzLgtjmma7Dh0mBVbtnK8vDxwf3J6An2GdSEhObbxT2L426jP5wP9xWo0m/2ba38+b+j/vnu9Ht74y+McOrADw4AH/+ff6DGoY9CObxgGDocDj8eD3lI1nsPpwMDAxMRTq+JBY6l9nl9JRQWfrl5D/skV6p1OJ5dccgkDBw7EMIzT9o2KisIwDEzTpKpKcweeyuf18fGfZ/HRCx/iPdnbeuDAgbz44ot069at3sfY7XaSkpI4fvw4Xq96aDdWfZ+PQkFqqi4iiwSLCoDSICoAhrZwLACapsmWLVtZunQJZWVlADgdDsb06U2fDh341nv+CxIOBUCfz2THoUOs3rGDotKywP2xCdF0H5BLZk4qBo14EU+lAmBQhVsBEOB48VFe+9PPqXZXEpcYzWN/vZeUNglBObYKLMGlAmBwqX02jNfnY8XWbazZsTPwOmVnZ3PllVeSmJgY2E8FwPPbv3k/f3voFfK2HAAgIiKCBx54gJ/+9KdERUWdtq8KgMGlAqCInI8KgNIgKgCGtnAqAPp8Pnbu3MnKlSspKCgI3J+Tns6EAf1JiIlu9HOEcgHQ4/Wyed8Bvtq1k9KKysD9UdEuuvbvQHbnDGyNqZ7WRwXAoArHAiDAlo0rmDH1fwFo3yWTh1/8d1yRjZ+TUgWW4FIBMLjUPi/MkeJiPvtqHcUnTgD+3oCjRo1i0KBB2Gw2FQAbyFPj4ZP/+4iPX5oV6A3Yvn17nn76aa688spAz0oVAINLBUAROR8VAKVBVAAMbeFQACwtLWXr1m1s3LiB0tLSwP3x0dGM6tWTbllZjer1d6pQLACWlFewce9eNu8/gLumJnB/VIyLTj2zyemWid1+cUOmz0sFwKAK1wIgwPxPp7FswQcADJvQh7sfvf6MIX4XSgWW4FIBMLjUPi+cx+tlxdZtfLVzV+A1S01N5fLLL6dLly4qAF6AA1v28+aj/2DXVzsD940dO5ZHH32UAQMGqAAYZCoAisj5qAAoDaICYGgLRgHQ4/FQVnaCEyfKqKpyU11dTXW1//u3TzNOp5OIiAgiIly4XP7vkZGRREZGEhUVSURERKM/lNfU1HDkSD4HDhxg//59HDly5LTtMZGRDOrSmX4dO+KwB3c9pFApAPp8Jnvy89m4dy/7jxacti0uMYbOvbNpl5uOzdbE60mpABhU4VwA9Pm8vPuP37Nr21oAJt4+mhvuntCoY6rAElwqAAaX2ufFO1JczBfrNlB4ykXDfv36cfnllxMdHa0CYAP5fD5WfLCMd5/9J2WF37yWkyZN4pFHHmHkyJEqAAaJCoAicj4qAEqDqAAY2i6kAOj1eikqKuLo0aMcPVpAUVEhpaWllJeXB+3DhWEYpxQEowK3/V/+n51O/6p9Pp8Pr9dLRUUllZUVVFRUUFxcfFovv1NlJCfRv2NHuma1w95EhavWXAA0TSgsLWVrXh7b8w5S4XYHthkGpLdLoUO3tqS3S250kbbBVAAMqnAuAAK4qyr4+8uPUHT0IAA3/+g7fOfmERd9PBVYgksFwOBS+2wcn+lj/e69rNiylZqTK9pGREQwbPgwBg4YSEREhMUJW4/Ksko++b+P+Pzvn1Hj/mYkwTXXXMO9997L0KFDm+99RYhSAVBEzkcFQGkQFQBD27kKgDU1NRw8eJC8vDzy8vI4evToBfUSdDocZ8wJV+v1NttQY5vNRkZSIh0y2tCtXRaJsTFN/pytsQBYVlnF9oMH2XYgj6KystO2uSKdtO+SSfuumcTERp3lCE1IBcCgCvcCIEBZyTH+8fIjlJb4/7Z97xfXMHrigIs6lgoswaUCYHCpfQZHubuKJV9vZlvewcB90dHRDB8+nP79+zfdFBghqOTocT56aRaL3l4QmB8QYMCAAdx5551cd911xMbGWpiw9VIBUETORwVAaRAVAEPbtwuARUXH2LVrF7t37+LIkSNn/dAQFRFBWmICiTExxMfEkBAdTXx0NJGuCCKdTiIcTmy2M6/mmiZ4fV5qaj3UeDxU19ZSXVtLVU0N7poaqmtrcdfU4K6pxV1b883tk9u99RQPXU4nUS4X0S4XibExpMTFk5YQT2ZKMhEOR9Bfs3NpLQXA4+Xl7Dp8hF2HDpP/rTeKhmGQ3i6ZrI5tyGifij3Iw6QviAqAQaUCoN+xwsP84+VHqazwF7xv+emVXDZl2AUfRwWW4FIBMLjUPoOroLSUxRs3kVdYGLgvLi6OQYMH0a9vP/UIvABFB4uY9/pcFr6zgOqKb0YbREdHM3nyZG644QZGjx6Ny+WyMGXrogKgiJyPCoDSICoAhr6CgkI2b97Mrl07KSkpOWO73WYjMzmZdqkptElMJD0xkdioqKAtnNFQpumfoNvj9WIYBjabgc2wBX0ev8ZoqQVA0zQpKCllT34+uw4fpqi07Ix9ElPiyOrYhra56URGtZAPMioABpUKgN/IP7yXaa89GSgCXvu9cUy+c8wFDUNTgSW4VAAMLrXP4HI4/RcU9xzOZ9HGjaf9HY2MjKRf/37069ePhPgEqyK2KjabDY/bw7/+3xzmT/2CorzC07bHxMRw6aWXMmHCBIYPH07Hjh0tHSZcW1vL8ePHKS4uPu3r+PHjVFZWUllZSVVVFVVVVVRWVlJdXR0Y8WKaZuB30G6343K5TpvmJioqiqioKOLi4khKSiIpKYnExESSkpJISEggMTHxvAVmFQBF5HxUAJQGUQEw9NTU1LBnz152797Fnj17cJ8y11udNkmJdGjThuy0NDKTk3BoiEuDtKQCoLumlgMFBew7epR9RwtOm9OvTmJKHJntU8nMSSM2IdqClOehAmBQqQB4uqKCg0x97becKC0G/KsD3/nzq3FFOhv0eBVYgksFwOBS+wyuU9tnTU0tOw8dYs2OXRSccuHUMAw6dOhAv3796Nixo4YHn8OpI1A8Hg/bv9zG0vcWs3rOamqqznxPn5aWxuDBg+nRowfdu3ena9euZGdnExcXd9GFwaqqKgoLCyksLKSgoOC026f+XFRURFnZmRdOm1NcXBzp6em0adOm3q+uXbvSoUMHoqKiVAAUkXqpACgNogJgaDhx4gS7du1i165d5OXlnbHimt1mIzstjY6ZGXTMyCAu2oL53kKAlQVAn8/kaMlx8gqL2H+0gMPHjuH71mneMCApLSFQ9IuOjWzWjBdMBcCgUgHwTCXFBUz721MUFx0GILtzBj/+7c2ktU0672NVYAkuFQCDS+0zuOprnyYmBwoK+WrHLvYXFJy2v8vlonPnznTr3o2c9jk4mnlKkpbubHNQ17hr2LJ0M+vmrWX952spLax/Ybc60dHRtGnThqSkJKKjo4mKiiI6Ohqn04nH46G2thav14vb7ebEiROUlpZSVlbGiRMngraasyvaRUSUi4ioCFxRLlxREThdTgybDU7WJg3DwDAMvB4vte4aaty11LhrTt72f3lqGn/eS0lJoV27dmRnZ5OdnU1WVlbge/v27UlMTGz0czQnFQBFgiesCoClpaVMnz6dVatWcezYMVwuF506dWLixIkMHz78oo/r8Xj45JNPWLRoEYcP+z88tGvXjrFjxzJp0qTz/rHfs2cPM2fO5Ouvv6asrIyEhAR69+7NDTfcQG5ubpM+d0OpANg6maZJfv5Rdu/exe7duyn41htTgMiICDpmZtClXTuyU1NxOnSlurGaswDoM00KS0rJKyziYFEhh4qOBVYqPJXT5SC9bTLp7fxfrsgWMry3IVQADCoVAOvnrqrgw3deYOe2rwD/4jc3/uByxl4zuN65TOuowBJcKgAGl9pncJ2vfR4vL+frffvZsv8AVdWnvyd1OBxkZWWR0yGH9tntSUtLC/vegedahK6OaZrk7znCjtU72LVmB3s37OHIniN4a7317h8MdoeduJR4EtLiSUhLJD41nviUBGKTY4lNiiMuyf89NjmWuOQ4ouNjTvvb2hg17hoqSiqoKC2noqSC8pJyKksrKC+p4ERRGaWFJZQUlFBa4P9efrz8gp8jISGBDh068MYbb9CuXbug5G5KKgCKBE/YFAAPHDjAo48+Smmp/wpSVFTUafMyXH311dxzzz0XfNyqqioef/xxduzYARCYm6Gmxr+8fffu3XnyySeJjKy/h82iRYt44YUX8Jz8wB4TE0NFRQXgf6Pws5/9jEsuuaRJnvtCqADYetTU1LB//4HA0N669nSqxNhYOmVm0DEzk7bJydjtNn1ACKKmLADWerwcLSkhv7iYw8eKOVhURHVt/c+RkBxLm6wU0tolk5QWf8ZqzK2GCoBBpQLg2Zk+H4vmvcuS+TP8v8BA13453PKTK2jfJbPex6jAElwqAAaX2mdwNbR9enxe9h8tYOehw+w5kl/v32m73R4YzpmU7J/zLTkpmYSEBGy2ljOvcVNqSAGwPl6Pl4L9Rzmy+wjH84spOVrC8fxiKssqqamqoaaqmuqqary1XuxOOza7HbvDjiPCQVRcNNHx0UTHRREVH01MQiwJafHEpyaQkJpAQnoC0Qkxreb/wFPjCRQFK49XUnSwkMK8Qo7uz6foYCFFB49RUVJ/kXDP3j3ExcY1c+ILpwKgSPCERQGwtraWn/zkJ+Tn55OTk8ODDz5Ibm4u1dXVzJo1i2nTpmGaJvfddx+XXXbZBR37ueeeY9GiRcTExHDfffcFehKuXLmSF198kYqKCsaPH8/PfvazMx574MABHnjgATweD6NHj+buu+8mOTmZ4uJiXnvtNZYtW4bT6eSFF14gKysrqM99oVQAbLm8Xi9Hjhxh//4DHDiwn8OHD5/xJsowDNomJ5N7cmhvclzcaYt36ANCcAWrAGiaJqUVlRwpLib/+HGOFBdTWFp21jfJcYkxpGYkknLyy+Vq2BxmLZ4KgEGlAuD55e3bxkfv/V9gSLBhwPDL+jL5zjG0yUo5bV+dP4NLBcDgUvsMrotpnx6vl7zCQvYXFHKgoJBj55lHzjCMwBDWui+H04nDYcfpdOJwOHDYHYFhpWcwCfxfm5j+n7/93TQDtzHAYXf4C2QOR+D4DocDp9MZWKTCFeki0hUZ1F6LF1sAlPpFRUVhGAamaZ42tLmqvIpjh4ooOuj/KjxQQHnxCWb8ZTp2o+X3QlUBUCR4wqIA+Mknn/Dqq6/icrl4+eWXSUtLO237X//6V+bMmUNycjJ/+9vfGjxsdu/evTzwwAOYpsmvfvUrRo4cedr2ZcuW8Yc//AHDMHjxxRfJyck5bfuzzz7LihUryM3N5fnnnz/tD6rX6+XBBx9k7969jBo1iocffjioz32hVABsOaqq3Bw5cpjDh49w5MhhDh06RG09V5ZdTic5bdLpmJFBhzZtiHKdfcinPiAE18UUAD1eL8fKTlBYWur/KvF/r284b53YhGhS2iSQmpFESkZiy1m1N9hUAAwqFQAbpra2msWfv8+XSz7Be/L32DCg34huTLhhKN36d8Bmt+n8GWQqAAaX2mdwBaN9Vrjd5B8/Tn7xcY4eL6GorJQKd+t5/1pXFIyOjiYmJsb/Fev/HhsTe9rt832mUgEwuM5WADybKyMvUwFQJMyExUy0CxcuBGDMmDFnFP8ApkyZwqeffkpxcTFff/01AwYMaNBxFy1ahGmaZGZmMmLEiDO2jxw5kszMTI4cOcKiRYu48847A9sqKipYvXo1ANddd90ZV9PsdjvXXXcdf/zjH1m1ahWVlZVER3+zOmdjnltaB9M0KSsro7CwiKIi/+pj+fn5Z13VyzAM2iQlkp2WRvu0NNqlpmBvJcMXwoVp+t/4l5SXc/yUr5LyckrKK85YrONUzggHialxJKXGk5QeT1JqPBGh0sNPpAVyOl1MuOoOBg+/ggVz32HTuiWYpo/1y7ezfvl2klLjGDy+F/1GdKVbv1xs9lY6xF5EmlVMZCSdMjPplPnNtALVtbWUVFRQUl5OaUUlVdU1VFVXU1ldTVVNNbUeLx6v/6vW68V7nmKZAWAYgU6CdSvk+r/57z911Vyvz4fH27A59Wpra6mtreXEiRPn3TcyMpLY2FhiY2P9RcFYf4Gw7r74uHicTr2XERFpLiFfAKyqqmLnzp0ADBw4sN590tLSyMrKIi8vjw0bNjS4ALhx40YABgwYUO/S84ZhMGDAAI4cORLYt86WLVsC8/6dLVfd/bW1tWzdupVBgwYF5bmlZTBNE7fbTUVF5ckVyUooLS2lpMT/vbi4uN6efXVsNhtpCQlkJiedLPilEhmhN1FW8flM3DU1VNbUUF1by4nKKsqqKiktL6e8qooTVVWcqKw6Z4++Ok6Xg4SkWOKTY4lPiiUxNY64hOh6f9dFpGklJKVx3S33Mfbym1m1bA7rV31BTY2b40UnmPf+Sua9vxJnhIMufdrTsWcW2Z3akNU5g7TMpHMuHiIiUsfldNImMZE2Fq7OapqmvxDo8+Lx+vB6vdR4PFTX1uI++d7GXVOL++TPVdXVVLjdVLj93+srILrdbtxu93lHEkVFRZ21SBgTE0NUZFRgKHJrmZtPRKQlCvkC4MGDBwNDHs41DDYnJ4e8vDzy8vIadFzTNDl48OB5j9u+fXuAM45b93NiYiIJCQn1PjYhIYGEhARKS0s5cOBAoADY2OeWswvMmWKa9d72en14vR68Xi9erxePx3vytue0n2tra6iurqa62v+9pqaampqakwW/CioqKqisrGzwcAfDMEiMiSE1IZ7M5GQykpNpk5iAI8RXjzuzQ9yZPeTq7TNXz50mJj6f/82tz+fDZ35z23vy69T7PF4vtR4PNZ6T370eajwePB7/95paD1U11f6r9DU1uE8uvnMhHE47sQnRxMZHExsf5S/4JccSFePCOOvkPiJihaSUDK645vuMv+JWtm9ezab1S9izYwM+n5faGg9bvtrDlq/2BPZ3OO2ktEkgOT2BlDYJJKbGEx0XSUxcFNGx/u+RMS6cEQ4cTvvJ7w6cEQ6cTnvQVpQUEWkIwzBw2O3+95YXeD3ZxKSm1kOF203lKYXB8qqqU4qEVZRXueu9EFpVVUVVVRWFhYXnfa6IiIhAMTAqKgqXy0VERAQOp4OIiAicTmfgK8L5zc92u/+8arfbsdlO/263ndxm899nGEbgq+61EREJBSFfACwuLg7cTk5OPut+ddvONrzy26qqqnC73Q0+bt0ftqioqNOe51yPrdteWlp6Wq7GPnd9pk6dyttvv33W7bfeeiu33XbbObM2p7qrfzabjaSkJABWrljI//7vR/Xu35rmvTGMb4ZmnPrGo9ztptztZt/RgjMfVM+/r6H/4oa+NmfW4pr+OVs7m80gMtpFVEwkUTEuomJcxJws9sUmROOKitCbygugq/7BpyLThYuMjqHfkHH0GzKOmuoq9u/Zwp4dG9i3axMF+Qfw+fy9YDy1Xo4eLOboweLzHPHsDMPAsBmB7zbD8M+Jeer9gdtw9lUBrNEiT28tMlTTMtD0qcFyauvRa3qRTBOTby6w+05+N08uUnLqhffWxTjtWzM+40Xbv+cAqclJQckiIq1DyBcA6wplAC6X66z71W1ryISp396vIcete0xdEa7u8ed67NlyNfa561NRUUFBQT2FpZMqKyuDuupXsBiGEchls3vYe2COxYkkVNntNqKjooiKjiI6Ooqo6Eji4+OJT4gjMSGOhIR44hPiSYiPIyklkbTUFBKTElrk742IBFMPYAoANTU17Nu7l507t5OXl0d+/hGO5ueTn5/PsWNFVFdf2ET/pmlielvjB2EREWnpIuxOvU8VCTMhXwCUhomJiSE9Pf2s26Ojo/E2cHLg5lDXPd80zcAw2vbt29Gpc/xpvea+3YvufNu+3dW/rsdR3c92ux2Hw+EfLnDyq+5nh8MRuB0REREYkvBtZ5uz0cr76v7tZ7vianW+YN0XERERGB5y6u26n0+93+VyERcXR1xcHLGxsect1p+qvvYpF88wjMAqwK2zV0DLovYZXN9unyOGDTrrvm63m+PHjwe+Tpw4EZgewj9tRHXgttfrDRzTVzd1wcmvb9/XEv8vL/Z39dS/R8H+fQ/H80dTvp7hSK9ncDXV6+nz+QKLldTW1uLxfDN9j8/nC3w/9fap9317GqD6fj7XPg3VlG2oIceOiIhoUZ/vzkZFSpHgCfkCYGRkZOB2dXX1aSvpnqruqvy5esmd6tT9znVF/9Rtpz6m7vb5egPUl6uxz12fO+64gzvuuOOs24uKiho8PLo5JCUlYbfb8fl8gVwZGRnMnTvX4mStk91uJykpiePHj7eKNwLNrbKyksrKygbvX1/7lItX1z5LS0vVPoNA7TO4LrR9RkZGkpmZSeYpK4DKN+rap9frVfsMAv19Dy61z+BS+wyuC22fdReeWrrU1FSrI4iEjJCf/OfUOfJOnQ/w2+q21c0ndz5RUVGBolpDjnvq/qfmOtdjz5arsc8tIiIiIiIiIiLhI+QLgFlZWYGhgAcOHDjrfnXbsrOzG3RcwzDIysq66OPW/VxSUkJZWVm9jy0tLaW0tBT4ZkXfYDy3iIiIiIiIiIiEj5AvAEZFRdGlSxcA1q5dW+8+RUVF5OXlAdCvX78GH7tv374ArFu37qz7rF+//rR96/Ts2ROHw3HOXHXHdTqd9OjRI2jPLSIiIiIiIiIi4SPkC4AA48aNA2Dx4sUUFhaesf2DDz7ANE2Sk5Pp06dPg487ZswYDMPg8OHDrFix4ozty5cv5/DhwxiGEchQJzo6miFDhgAwa9asM+a98Hq9zJo1C4ChQ4eeMXdhY55bRERERERERETCR1gUAK+44goyMjJwu9089dRT7N27F/BPfDp9+nRmz54N+BfCqOuVV+fuu+/mmmuu4U9/+tMZx83NzWXMmDEAvPTSS6xcuTKwCtTKlSv585//DPgLkKcO4a1z++2343A42L17N88//3xgstbjx4/z/PPPs3v3bpxOJ7fffnvQn1tERERERERERMJDyK8CDP4htI899hiPPvoo+/bt4/777yc6Ohq3243P5wNg8uTJXHbZZRd87B//+MccOXKEHTt28Lvf/Y6IiAgAampqAOjevTs/+tGP6n1s+/btuf/++3nhhRdYsmQJS5cuJTo6moqKCgAcDgf3339/YL6/YD63iIiIiIiIiIiEh7AoAIK/2PbSSy8xY8YMVq1aRVFRETExMXTs2JFJkyYxfPjwizpuVFQUv//97/nkk09YtGgRhw8fBqBTp06MGzeOSZMmndGr8FRjx44lOzubDz74gE2bNlFWVhYYinzDDTeQm5vbZM8tIiIiIiIiIiKhzzBN07Q6hLR8RUVFVkc4TVJSEna7Ha/XGxg6LRfPbreTlJTE8ePHz5iPUi6c2mdwqX0Gl9pncKl9BpfaZ3CpfQaX2mdwqX0GV6i2z9TUVKsjiISMsJgDUEREREREREREJFypACgiIiIiIiIiIhLCVAAUEREREREREREJYSoAioiIiIiIiIiIhDAVAEVEREREREREREKYCoAiIiIiIiIiIiIhTAVAERERERERERGREKYCoIiIiIiIiIiISAhTAVBERERERERERCSEqQAoIiIiIiIiIiISwlQAFBERERERERERCWEqAIqIiIiIiIiIiIQwFQBFRERERERERERCmAqAIiIiIiIiIiIiIUwFQBERERERERERkRCmAqCIiIiIiIiIiEgIUwFQREREREREREQkhKkAKCIiIiIiIiIiEsJUABQREREREREREQlhKgCKiIiIiIiIiIiEMBUARUREREREREREQpgKgCIiIiIiIiIiIiFMBUAREREREREREZEQpgKgiIiIiIiIiIhICFMBUEREREREREREJISpACgiIiIiIiIiIhLCVAAUEREREREREREJYSoAioiIiIiIiIiIhDDDNE3T6hAiF2rq1KlUVFQQExPDHXfcYXUckdOofUpLpvYpLZnap7Rkap/Skql9isj5qAAordLEiRMpKCggPT2dOXPmWB1H5DRqn9KSqX1KS6b2KS2Z2qe0ZGqfInI+GgIsIiIiIiIiIiISwlQAFBERERERERERCWEqAIqIiIiIiIiIiIQwFQBFRERERERERERCmAqAIiIiIiIiIiIiIUwFQBERERERERERkRDmsDqAyMW47bbbqKioICYmxuooImdQ+5SWTO1TWjK1T2nJ1D6lJVP7FJHzMUzTNK0OISIiIiIiIiIiIk1DQ4BFRERERERERERCmAqAIiIiIiIiIiIiIUwFQBERERERERERkRCmAqCIiIiIiIiIiEgI0yrA0qqUlpYyffp0Vq1axbFjx3C5XHTq1ImJEycyfPhwq+NJCPviiy944YUXzrvf1KlTiY+Pr3fbihUr+PTTT9m9ezfV1dWkpqYyZMgQbrrpprM+RgSgvLycTZs2sWvXLnbv3s2uXbsoLS0F4JlnnqFPnz7nPUZj2p/OvXIujWmfd999NwUFBec8/sSJE/nhD3941u1qn3IuhYWFrFixgo0bN7Jv3z6Ki4txOBykpaXRv39/rr76ajIyMs55DJ0/pak0pn3q/CkiF0oFQGk1Dhw4wKOPPhr4UBEVFUVFRQXr169n/fr1XH311dxzzz0Wp5RQZ7PZzvlm3zCMeu//61//ypw5cwLHcLlcHD58mFmzZrFo0SKeeeYZsrOzmySztH5ffvllgwrQZ9OY9qdzr5xPY9snQHR0NBEREWfddjZqn3IuhYWF3H333ZimGbgvOjqampoa8vLyyMvLY+7cuTzwwAOMHj263mPo/ClNJRjts+4xOn+KSEOoACitQm1tLU8//TSlpaXk5OTw4IMPkpubS3V1NbNmzWLatGl8/PHH5Obmctlll1kdV0JYamoqf/vb3y7oMXPnzmXOnDkYhsHtt9/Otddei8vlYu/evTz//PPs37+fp59+mj//+c84nc4mSi6tXVJSEp06daJz5860bduW559/vkGPa0z707lXGupi22ede+65hwkTJlzQY9Q+5Xx8Ph8AAwcO5NJLL6V///7Ex8fj9XrZunUrr776Kvv27eP5558nKyuLDh06nPZ4nT+lKTW2fdbR+VNEGkpzAEqrMHfuXPLz83G5XDzxxBPk5uYC4HK5uPnmm7nqqqsA//BLj8djZVSR09TW1vL2228D/mEYN998My6XC4Dc3Fwef/xxXC4XR44cYd68eVZGlRZs3LhxvPHGGzzxxBPcdtttDB48uEGPa2z707lXGuJi22djqX3K+cTGxvLHP/6R3/zmN4wZMybQg99ut9O7d29++9vfkpCQgMfjYdasWac9VudPaWqNaZ+NpfYpEp5UAJRWYeHChQCMGTOGtLS0M7ZPmTIFwzAoLi7m66+/buZ0Ime3ceNGjh8/jmEY3HDDDWdsT09PZ8yYMcA37Vzk2+x2+0U9rrHtT+deaYiLbZ+NpfYp5xMTE0PHjh3Puj0pKYlBgwYBsHv37tO26fwpTa0x7bOx1D5FwpMKgNLiVVVVsXPnTsDfRb4+aWlpZGVlAbBhw4ZmyyZyPhs3bgQgOzu73jdYAAMGDABg+/btuN3uZssmoa8x7U/nXmnJ1D4lWOp6XXm93tPu1/lTWoKztc/GUPsUCV+aA1BavIMHDwYmx83JyTnrfjk5OYEJc0WaSmlpKQ888ACHDh0CICUlhd69ezN58uR652apa4/na7sApmly8OBBOnfuHPzgEpYa0/507pXmNHPmTN566y3KysqIjo6mQ4cOjBw5kssuu6zeye3VPiVYNm3aBJzZjnT+lJbgbO3zVDp/ikhDqQegtHjFxcWB28nJyWfdr27b8ePHmzyThK/q6mr27t2L0+nE6/Vy+PBhPvvsMx544AFmzpx5xv517bchbRfUfiW4GtP+dO6V5nTgwAHKy8txuVyUlZWxceNG/vrXv/LQQw9RWFh4xv5qnxIMK1euZNeuXQBnLKKg86dY7Vzt81Q6f4pIQ6kHoLR4pw6pqJt8uT5126qqqpo8k4Sf5ORkbr31VkaOHEnbtm1xOp14PB62bNnCm2++yY4dO/j73/9OcnIyY8eODTyurv02pO0CVFZWNt0/QsJOY9qfzr3SHIYNG0avXr3o3bt3YKhbcXEx8+bN491332X//v389re/5Y9//ONpq6yqfUpjFRYW8n//93+Avx3WzbVWR+dPsdL52mfd/Tp/isiFUA9AEZEGGDBgALfeeis5OTmBN1EOh4O+ffvy7LPP0q1bNwDeeOMNfD6flVFFRFqNe+65h5EjRwY+vIL/gst3v/tdHn74YcDfu+WLL76wKqKEoPLycp566ilKS0vJyMjgvvvuszqSSEBD26fOnyJyoVQAlBYvMjIycLu6uvqs+9Vti4qKavJMIqdyOp3ccccdABQVFbFnz57Atrr225C2CxAdHd1EKSUcNab96dwrVhs2bBg9e/YEYPXq1adtU/uUi1VVVcVvf/tb9u3bR3JyMk8++SRxcXFn7Kfzp1ihoe3zfHT+FJH6qAAoLd6pc1OcOmfFt9VtS0pKavJMIt9W1wMQID8/P3C7rv02pO2C2q8EV2Pan8690hLUnVtPPa+C2qdcnOrqap588km2b99OQkICTz31FBkZGfXuq/OnNLcLaZ8NofOniHybCoDS4mVlZWEYBuDvxn42dduys7ObJZdIQ9S1x4a0XcMwyMrKapZcEh4a0/507pWWTO1TLlR1dTVPPfUUmzdvJjY2lieffPKc7ULnT2lOF9o+G0PtUyR8qQAoLV5UVBRdunQBYO3atfXuU1RUFFiivl+/fs2WTaTO9u3bA7fbtGkTuN23b1/A/yaqqKio3seuW7cO8F+pPXVYhkhjNab96dwrLUHdufXU8yqofcqFqa2t5Xe/+x0bN24kOjqa3/zmN+Tm5p7zMTp/SnO5mPbZEDp/isi3qQAorcK4ceMAWLx4cb3L2X/wwQeYpklycjJ9+vRp5nQS6kzTPOd2j8fDtGnTAEhJSaFTp06BbX379iUpKQnTNJk5c+YZjy0sLGTx4sXAN+1cJFga2/507pWmdL5z6+rVq9myZQsAQ4cOPWO72qc0hMfj4fe//z3r1q0jMjKSJ554gq5du573cTp/SnO42Pap86eIXAwVAKVVuOKKK8jIyMDtdvPUU0+xd+9ewN9dfvr06cyePRuAO+64A4fDYWVUCUEFBQX8/Oc/Z+7cuRw9ejRwv9frZdOmTTzyyCNs27YNgLvuugub7ZtTq9Pp5LbbbgPgk08+Yfr06YFJlffu3ctTTz2F2+0mMzOTyy+/vBn/VdLalJWVBb7Ky8sD91dUVJy2zePxBLY1tv3p3CsNdTHt89VXX+XVV19l06ZNp01Ef/z4cd5//33+8Ic/ANC+fXsmTJhwxnOqfcr5eL1e/vd//5fVq1cTERHBY489FlgY4Xx0/pSm1pj2qfOniFwMwzzf5QORFuLAgQM8+uijlJaWAv7V1txuNz6fD4DJkydz7733WhlRQtTRo0e55557Aj9HREQQGRlJZWVl4MOsw+Hgrrvu4tprr633GH/961+ZM2cOAHa7HZfLRWVlJQCJiYk888wzmmNFzumaa65p0H7PPPPMGVfrG9P+dO6VhriY9vmnP/2J+fPnA/451OpWUa2oqAjs37FjRx599FHS0tLqPZ7ap5xL3UU68Bf0YmJizrn/m2++ecZ9On9KU2lM+9T5U0QuhgqA0qqUlJQwY8YMVq1aRVFREZGRkXTs2JFJkyYxfPhwq+NJiKqurmbevHls3bqVvXv3UlpaSmVlJS6XizZt2tCnTx+uuuoq2rVrd87jrFixgjlz5rBnzx7cbjepqakMHTqUG2+8kYSEhGb610hr1ZgCIDSu/encK+dzMe1z27ZtrFixgu3bt1NQUMCJEyfw+XzExcXRqVMnRo0axZgxY87b+0TtU87m66+/5tFHH23w/h999FG99+v8KU2hMe1T508RuRgqAIqIiIiIiIiIiIQwzQEoIiIiIiIiIiISwlQAFBERERERERERCWEqAIqIiIiIiIiIiIQwFQBFRERERERERERCmAqAIiIiIiIiIiIiIUwFQBERERERERERkRCmAqCIiIiIiIiIiEgIUwFQREREREREREQkhKkAKCIiIiIiIiIiEsJUABQREREREREREQlhKgCKiIiIiIiIiIiEMBUARUREREREREREQpgKgCIiIiIiIiIiIiFMBUAREREREREREZEQpgKgiIiIiIiIiIhICFMBUEREREREREREJISpACgiIiIiIiIiIhLCVAAUEREREREREREJYSoAioiIiIiIiIiIhDAVAEVEREREREREREKYCoAiIiIiIiIiIiIhTAVAERERERERERGREKYCoIiIiIiIiIiISAhTAVBERETC1sKFCzEMA8Mw+M1vfgPAzp07eeihh+jVqxeJiYmnbavjdrt55ZVXmDx5MtnZ2URGRpKQkEDv3r2577772LFjx1mfs0ePHhiGQVZW1ln3efTRRwO54uLiqK2trXe///mf/wnsN3v27Av+94uIiIhIeFABUEREROSkqVOn0q9fP55//nm2bNlCaWnpGfssWrSIzp0788Mf/pDZs2dz8OBBqqurKSsrY/Pmzbz00kv07NmTZ599tt7nGD9+PACHDh1i+/bt9e4zf/78wO3y8nJWrVp1zv0cDgdjxoy5oH+riIiIiIQPh9UBRERERFqC5cuX88wzz2AYBnfddReXXHIJMTEx7Nq1i/bt2wPw6aefcu2111JbW4vNZuPKK6/ksssuo127drjdbtasWcObb75JaWkpjzzyCAC//vWvT3ueSy+9lL/85S+Av4DXrVu307afOHGCNWvWnHbf/PnzGTVq1Gn31dbWsnTpUgAGDx5MXFxc8F4MEREREQkphmmaptUhRERERKywcOHCQI88gPT0dObNm0ffvn3P2PfIkSP07t2b4uJi0tPTmTVrFsOHDz9jv0OHDnHllVeyadMm7HY7mzZtonv37oHtRUVFpKenY5omU6ZMYfr06ac9fs6cOUyaNAmAkSNHsnz5csaNG8eCBQtO22/58uWBouAjjzzCM888c/EvhIiIiIiENA0BFhERETnplVdeqbf4B/759oqLiwGYPn16vcU/gHbt2vH+++9jt9vxer288MILp21PTU2lT58+gL8A+e1rsXXDejt16sRdd90FwIoVK3C73fXuB/5ehSIiIiIiZ6MCoIiIiAiQk5PDtddeW+820zR58803ARgxYgSXXHLJOY/VvXt3hg4dCsDcuXPP2F5XsDt27BgbNmw4bVtdYe/SSy8N7FddXc2yZcvq3c/lcp0xPFhERERE5FSaA1BEREQEGDVqFIZh1Ltty5YtHDt2DICkpCQ+/PDD8x7PbrcDsHfvXtxuN5GRkYFt48eP509/+hMAX3zxBf379weguLg4UBCcMGECnTt3Jjs7m7y8PObPn8+ECRMA/yrEK1asAPwFyVOPLSIiIiLybSoAioiIiABZWVln3bZv377A7Tlz5jBnzpwLOnZxcTFt27YN/Dx27NjAEOH58+fz0EMPAf4Vhn0+H4ZhBOYmHD9+PG+++eZpQ35PHRKs4b8iIiIicj4aAiwiIiICREVFnXVbSUlJo45dU1Nz2s8JCQkMHDgQgCVLluDxeIBvhvX26tWL9PR04JsC35o1azhx4sRp+526XURERETkbFQAFBERETmP2NjYwO0HH3wQ0zQv6KtDhw5nHLOuh9+JEydYtWoVcPr8f3Xqbns8HhYvXnzafjExMYG5BkVEREREzkYFQBEREZHzOHV4cF5eXlCOeWqRb/78+Rw9epQtW7YABOb6A8jOzqZTp06B/crLy1m9ejUAo0ePxul0BiWPiIiIiIQuFQBFREREzqN///4kJCQAsGDBAqqrqxt9zFOLd/Pnz2fBggWAf/GQsWPHnrZvXbFw/vz5LF26lNra2tPuFxERERE5FxUARURERM7Dbrdz++23A1BUVMTzzz/f6GOeOnx3+fLlgYVFBg4cGCg21qkr9G3YsIHp06efcb+IiIiIyLmoACgiIiLSAI888giJiYkAPPbYY/zpT3/C5/Oddf+Kigr+9re/8c4775x1n7oCXnV1dWC/U4f/1qmbL9A0Td544w0AEhMTAwuJiIiIiIici8PqACIiIiKtQbt27Xjvvfe4+uqrqa6u5mc/+xkvv/wy119/PT179iQ2NpYTJ06wd+9e1qxZw/z583G73Tz11FNnPeall14a2F63EnB9vfratGlDz5492bJlS2C/sWPHYrPpWq6IiIiInJ8KgCIiIiINdPnll7N06VLuuOMOtm/fzs6dO/nv//7vs+5vt9vJyMg46/YRI0YQGRmJ2+0GICIigtGjR9e776WXXhpYJKTuZxERERGRhtBlYxEREZELMHjwYLZs2cL777/PHXfcQZcuXYiPj8dut5OQkEDv3r259dZbeeWVVzh48CB33333WY/lcrkYOXJk4Ofhw4cTFRVV777fLvipACgiIiIiDWWYpmlaHUJERERERERERESahnoAioiIiIiIiIiIhDAVAEVEREREREREREKYCoAiIiIiIiIiIiIhTAVAERERERERERGREKYCoIiIiIiIiIiISAhTAVBERERERERERCSEqQAoIiIiIiIiIiISwlQAFBERERERERERCWEqAIqIiIiIiIiIiIQwFQBFRERERERERERCmAqAIiIiIiIiIiIiIUwFQBERERERERERkRCmAqCIiIiIiIiIiEgIUwFQREREREREREQkhKkAKCIiIiIiIiIiEsJUABQREREREREREQlhKgCKiIiIiIiIiIiEMBUARUREREREREREQtj/B16Nc9gyR63dAAAAAElFTkSuQmCC" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,
)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(fixed_pol_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + " ggplot(ppo_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "fa4acb62-93d3-4fdc-87e0-472a99eea4a0", + "metadata": {}, + "source": [ + "### UM3" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "d0fd387d-f999-48bd-a79c-142c9f3c0d51", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-06-05 20:50:03,511\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:50:19,287\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:50:35,191\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + } + ], + "source": [ + "PPO_2o_rews = get_rews(\n", + " agent=PPO_2o_UM3,\n", + " env=AsmEnv(config=CFG_UM3_2o),\n", + " agent_name='PPO_2o',\n", + ")\n", + "\n", + "PPO_mw_rews = get_rews(\n", + " agent=PPO_mw_UM3,\n", + " env=AsmEnv(config=CFG_UM3_mw),\n", + " agent_name='PPO_mw',\n", + ")\n", + "\n", + "PPO_bm_rews = get_rews(\n", + " agent=PPO_bm_UM3,\n", + " env=AsmEnv(config=CFG_UM3_bm),\n", + " agent_name='PPO_bm',\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "495838f3-cb9e-448f-9a04-c5241cb935c9", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-06-05 20:51:32,538\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:51:40,525\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-05 20:51:48,198\tINFO worker.py:1749 -- Started a local Ray instance.\n" + ] + } + ], + "source": [ + "CR_rews = get_rews(\n", + " agent=CautionaryRule(\n", + " env=AsmEnv(config=CFG_UM3_bm),\n", + " **(from_radius_theta(*cr_UM3.x)),\n", + " ),\n", + " env=AsmEnv(config=CFG_UM3_bm),\n", + " agent_name='CR',\n", + ")\n", + "\n", + "Esc_rews = get_rews(\n", + " agent=ConstEsc(\n", + " escapement=esc_UM3.x[0],\n", + " env=AsmEnv(config=CFG_UM3_bm),\n", + " ),\n", + " agent_name='Esc',\n", + " env=AsmEnv(config=CFG_UM3_bm),\n", + ")\n", + "\n", + "Msy_rews = get_rews(\n", + " agent=Msy(\n", + " mortality=msy_UM3.x[0],\n", + " env=AsmEnv(config=CFG_UM3_bm),\n", + " ),\n", + " agent_name='Msy',\n", + " env=AsmEnv(config=CFG_UM3_bm),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "1b6d4958-6956-41ca-8368-32942f1e2226", + "metadata": {}, + "outputs": [], + "source": [ + "fixed_pol_df = pd.concat(\n", + " [\n", + " pd.DataFrame(CR_rews),\n", + " pd.DataFrame(Esc_rews),\n", + " pd.DataFrame(Msy_rews),\n", + " ]\n", + ")\n", + "ppo_df = pd.concat(\n", + " [\n", + " pd.DataFrame(PPO_2o_rews),\n", + " pd.DataFrame(PPO_mw_rews),\n", + " pd.DataFrame(PPO_bm_rews),\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "c6673202-3c37-4779-b648-2c2636b6c7fa", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,
)" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(fixed_pol_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + " ggplot(ppo_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1ac02e72-2b26-4277-8fe0-631b49c3b763", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/for_results/3_policy_plots.ipynb b/notebooks/for_results/3_policy_plots.ipynb new file mode 100644 index 0000000..99d1b48 --- /dev/null +++ b/notebooks/for_results/3_policy_plots.ipynb @@ -0,0 +1,1048 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "5960f976-0f72-4c76-b45c-0f5d793fe8ae", + "metadata": {}, + "source": [ + "# Policy plots" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "7c22bd9a-3777-496b-88ba-f19e6471638b", + "metadata": {}, + "outputs": [], + "source": [ + "from huggingface_hub import hf_hub_download, HfApi\n", + "from plotnine import ggplot, aes, geom_point, geom_line\n", + "from skopt import load\n", + "from stable_baselines3 import PPO\n", + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.utils import evaluate_agent\n", + "from rl4fisheries.envs.asm_fns import get_r_devs\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import ray" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e2f2306a-3721-41c8-95ec-0c9f0652176b", + "metadata": {}, + "outputs": [], + "source": [ + "## UM1\n", + "\n", + "CFG_UM1_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "CFG_UM1_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "CFG_UM1_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "\n", + "## UM2\n", + "\n", + "CFG_UM2_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "CFG_UM2_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "CFG_UM2_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "\n", + "## UM3\n", + "\n", + "CFG_UM3_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}\n", + "CFG_UM3_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}\n", + "CFG_UM3_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "56316506-65dc-4b94-a4e1-cae92979c53c", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Load" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "bc1803a6-fa08-45c1-9ae7-b60837c13f0e", + "metadata": {}, + "outputs": [], + "source": [ + "cr_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM1.pkl\")\n", + "cr_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM2.pkl\")\n", + "cr_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM3.pkl\")\n", + "\n", + "esc_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM1.pkl\")\n", + "esc_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM2.pkl\")\n", + "esc_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM3.pkl\")\n", + "\n", + "msy_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM1.pkl\")\n", + "msy_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM2.pkl\")\n", + "msy_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM3.pkl\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c3c0c3ae-0a36-4652-b992-73e8638be29c", + "metadata": {}, + "outputs": [], + "source": [ + "cr_UM1 = load(cr_UM1_file)\n", + "cr_UM2 = load(cr_UM2_file)\n", + "cr_UM3 = load(cr_UM3_file)\n", + "\n", + "esc_UM1 = load(esc_UM1_file)\n", + "esc_UM2 = load(esc_UM2_file)\n", + "esc_UM3 = load(esc_UM3_file)\n", + "\n", + "msy_UM1 = load(msy_UM1_file)\n", + "msy_UM2 = load(msy_UM2_file)\n", + "msy_UM3 = load(msy_UM3_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "bd93cc8e-6553-47f6-b170-1fc7ed4c132e", + "metadata": {}, + "outputs": [], + "source": [ + "base_fname = \"sb3/rl4fisheries/results/PPO-AsmEnv-\"\n", + "repo = \"boettiger-lab/rl4eco\"\n", + "\n", + "PPO_2o_UM1_file = hf_hub_download(repo_id=repo, filename=base_fname+\"2obs-UM1-64-32-16-chkpnt3.zip\")\n", + "PPO_mw_UM1_file = hf_hub_download(repo_id=repo, filename=base_fname+\"mwt-UM1-64-32-16-chkpnt3.zip\")\n", + "PPO_bm_UM1_file = hf_hub_download(repo_id=repo, filename=base_fname+\"biomass-UM1-64-32-16-chkpnt1.zip\")\n", + "\n", + "PPO_2o_UM2_file = hf_hub_download(repo_id=repo, filename=base_fname+\"2obs-UM2-64-32-16-chkpnt1.zip\")\n", + "PPO_mw_UM2_file = hf_hub_download(repo_id=repo, filename=base_fname+\"mwt-UM2-64-32-16-chkpnt4.zip\")\n", + "PPO_bm_UM2_file = hf_hub_download(repo_id=repo, filename=base_fname+\"biomass-UM2-64-32-16-chkpnt3.zip\")\n", + "\n", + "PPO_2o_UM3_file = hf_hub_download(repo_id=repo, filename=base_fname+\"2obs-UM3-64-32-16-chkpnt5.zip\")\n", + "PPO_mw_UM3_file = hf_hub_download(repo_id=repo, filename=base_fname+\"mwt-UM3-64-32-16-chkpnt2.zip\")\n", + "PPO_bm_UM3_file = hf_hub_download(repo_id=repo, filename=base_fname+\"biomass-UM3-64-32-16-chkpnt4.zip\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "bf9d03e3-0169-49cb-8dd5-72ab9033b2ae", + "metadata": {}, + "outputs": [], + "source": [ + "PPO_2o_UM1 = PPO.load(PPO_2o_UM1_file, device='cpu')\n", + "PPO_mw_UM1 = PPO.load(PPO_mw_UM1_file, device='cpu')\n", + "PPO_bm_UM1 = PPO.load(PPO_bm_UM1_file, device='cpu')\n", + "\n", + "PPO_2o_UM2 = PPO.load(PPO_2o_UM2_file, device='cpu')\n", + "PPO_mw_UM2 = PPO.load(PPO_mw_UM2_file, device='cpu')\n", + "PPO_bm_UM2 = PPO.load(PPO_bm_UM2_file, device='cpu')\n", + "\n", + "PPO_2o_UM3 = PPO.load(PPO_2o_UM3_file, device='cpu')\n", + "PPO_mw_UM3 = PPO.load(PPO_mw_UM3_file, device='cpu')\n", + "PPO_bm_UM3 = PPO.load(PPO_bm_UM3_file, device='cpu')" + ] + }, + { + "cell_type": "markdown", + "id": "5d668ef2-bbdc-46d2-bc31-e20e910ba76d", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Policy plot utilities" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "9a9b5e0d-e334-4544-a5ca-a8623004be5b", + "metadata": {}, + "outputs": [], + "source": [ + "from itertools import product\n", + "\n", + "def obs_to_mwt(obs, asm_env):\n", + " return asm_env.parameters['min_wt'] + (\n", + " asm_env.parameters['max_wt'] - asm_env.parameters['min_wt']\n", + " ) * (obs + 1) / 2\n", + "\n", + "def obs_to_bms(obs, asm_env):\n", + " return asm_env.bound * (obs + 1) / 2\n", + "\n", + "def get_mwt_policy(mwt_obs_list, *, agent, asm_env):\n", + " mwt_list = [obs_to_mwt(mwt, asm_env) for mwt in mwt_obs_list]\n", + " return {\n", + " 'mwt': mwt_list, \n", + " 'fishing_intensity': [ \n", + " 0.5 * (1 + agent.predict(np.float32([mwt]))[0][0]) \n", + " for mwt in mwt_obs_list\n", + " ],\n", + " }\n", + "\n", + "def get_bms_policy(bms_obs_list, *, agent, asm_env):\n", + " bms_list = [obs_to_bms(bms, asm_env) for bms in bms_obs_list]\n", + " return {\n", + " 'bms': bms_list, \n", + " 'fishing_intensity': [ \n", + " 0.5 * (1 + agent.predict(np.float32([bms]))[0][0]) \n", + " for bms in bms_obs_list\n", + " ],\n", + " }\n", + "\n", + "def get_2obs_policy(bms_obs_list, mwt_obs_list, *, agent, asm_env):\n", + " mwt_list = [obs_to_mwt(mwt, asm_env) for mwt in mwt_obs_list]\n", + " bms_list = [obs_to_bms(bms, asm_env) for bms in bms_obs_list]\n", + "\n", + " predictors = list(product(bms_list, mwt_list))\n", + " bms_list_long = [pred[0] for pred in predictors]\n", + " mwt_list_long = [pred[1] for pred in predictors]\n", + " \n", + " return {\n", + " 'bms': bms_list_long, \n", + " 'mwt': mwt_list_long,\n", + " 'fishing_intensity': [ \n", + " 0.5 * (1 + agent.predict(np.float32([bms, mwt]))[0][0]) \n", + " for (bms, mwt) in product(bms_obs_list, mwt_obs_list)\n", + " ],\n", + " }\n", + "\n", + "def from_radius_theta(radius, theta, y2):\n", + " x1 = radius * np.sin(theta)\n", + " x2 = radius * np.cos(theta)\n", + " return {'x1': x1, 'x2': x2, 'y2': y2}" + ] + }, + { + "cell_type": "markdown", + "id": "8d6fca5f-f81e-4c3a-af2a-e61ef41ce518", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## UM1" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "0cf1da75-6bcb-4083-a07b-3bd8729213d3", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "bms_obs_list = np.linspace(-1, -1+0.14, 500)\n", + "mwt_obs_list_short = [-0.5, 0, 0.3, 0.5, 0.7, 0.9]\n", + "mwt_obs_list = np.linspace(-1,1,500)\n", + "\n", + "\n", + "UM1_2o_pol = pd.DataFrame(get_2obs_policy(\n", + " bms_obs_list, mwt_obs_list_short, \n", + " agent = PPO_2o_UM1, \n", + " asm_env = AsmEnv(config=CFG_UM1_2o),\n", + ")) \n", + "\n", + "UM1_mw_pol = pd.DataFrame(get_mwt_policy(\n", + " mwt_obs_list, \n", + " agent = PPO_mw_UM1, \n", + " asm_env = AsmEnv(config=CFG_UM1_mw),\n", + ")) \n", + "\n", + "UM1_bm_pol = pd.DataFrame(get_bms_policy(\n", + " bms_obs_list, \n", + " agent = PPO_bm_UM1, \n", + " asm_env = AsmEnv(config=CFG_UM1_bm),\n", + ")) " + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "id": "722c952e-374f-4edb-a4f8-ad28e018bb06", + "metadata": {}, + "outputs": [], + "source": [ + "UM1_cr_pol = pd.DataFrame(\n", + " get_bms_policy(\n", + " bms_obs_list,\n", + " agent = CautionaryRule(\n", + " env = AsmEnv(config=CFG_UM1_bm),\n", + " **(from_radius_theta(*cr_UM1.x)), \n", + " ),\n", + " asm_env = AsmEnv(config=CFG_UM1_bm),\n", + " )\n", + ")\n", + "\n", + "UM1_esc_pol = pd.DataFrame(\n", + " get_bms_policy(\n", + " bms_obs_list, \n", + " agent = ConstEsc(\n", + " env = AsmEnv(config=CFG_UM1_bm), escapement=esc_UM1.x[0]\n", + " ),\n", + " asm_env = AsmEnv(config=CFG_UM1_bm),\n", + " )\n", + ") \n", + "\n", + "UM1_msy_pol = pd.DataFrame(get_bms_policy(\n", + " bms_obs_list, \n", + " agent = Msy(\n", + " env = AsmEnv(config=CFG_UM1_bm), mortality=msy_UM1.x[0]\n", + " ), \n", + " asm_env = AsmEnv(config=CFG_UM1_bm),\n", + ")) " + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "id": "5408ae79-40aa-4ca6-b7dd-5cf7b4d4d635", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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TrFgxTZ48WRUqVHDrPABgGgEgAAAAACBLOn/+vF599VUtWLDArRt85M6dW+PHj1ft2rXdNgcAuBMBIAAAAAAgS0lJSdG0adM0bNgwJSQkuG2e8PBwDR8+XC1btpRlWW6bBwDcjQAQAAAAAJAl2LatVatWqVevXoqOjnbbPEFBQXrllVfUvXt3BQUFuW0eAPAUAkAAAAAAQKb322+/qUOHDtq/f7/b5nA4HOrSpYtefvll5ciRw23zAICnEQACAAAAADKtuLg4de7cWRs2bHDrPFFRUXr99ddVoEABt84DAN5AAAgAAAAAyHRSU1P16quvasaMGW7d4OORRx7RyJEjddttt7ltDgDwNgJAAAAAAECmMmvWLA0ePFjnzp1z2xylS5fWyJEjVblyZbfNAQCZBQEgAAAAACBT2LFjh1588UW3PucvV65cGjp0qJo3b+62OQAgsyEABAAAAAB41dGjR/XKK69o1apVbpsjODhYL774ovr27SvLstw2DwBkRgSAAAAAAACvuHDhgkaOHKlJkya57Tl/lmWpWbNmGjVqlIKDg90yBwBkdgSAAAAAAACPsm1bixcvVp8+fZSQkOC2eSpXrqwPPvhA+fLlc9scAJAVEAACAAAAADzmp59+Ups2bXT06FG3zXHHHXdo8uTJuuuuu9w2BwBkJQSAAAAAAAC3i4uLU+fOnbVhwwa3zZE/f36NGjVKtWvX5jl/APAPBIAAAAAAALdJSUnR6NGjNXr0aCUnJ7tljtDQUL388svq3r27AgIC3DIHAGRlBIAAAAAAAONs29batWvVs2dPnTp1yi1zWJalpk2basyYMQoNDXXLHADgCwgAAQAAAABGHT16VB06dNCuXbvcNkf58uU1e/ZsFSxY0G1zAICvIAAEAAAAABiRkpKivn37au7cuW6bI1++fJo5c6YqVKjgtjkAwNc4vN0AAAAAACDrmzNnjkqVKuW28C80NFRjxozRTz/9RPgHABnEFYAAAAAAAKft3r1bPXr00M8//+yW+g6HQ926ddNLL72k7Nmzu2UOAPB1BIAAAAAAgAyLiYnR4MGDtWDBArfN8dhjj+ntt99WsWLF3DYHAPgDAkAAAAAAwE1LTU3VnDlzNGDAACUlJblljhIlSmjs2LF6+OGH3VIfAPwNASAAAAAA4Kb88ssvatmypY4dO+aW+mFhYXrttdfUtWtXt9QHAH9FAAgAAAAAuKGEhAR17NhRa9euddsczZo105gxYxQUFOS2OQDAXxEAAgAAAACuybZtTZkyRUOGDHHb7b7ly5fXrFmzVKhQIbfUBwAQAAIAAAAAruGHH37Qc889p3379rmlfr58+TRx4kRVr17dLfUBAP8fASAAAAAAIF1cXJxefvllffLJJ26pHxwcrFdeeUXPPPMMt/sCgIcQAAIAAAAAJElz587VSy+9pIsXL7ql/mOPPaaJEycqMjLSLfUBANdGAAgAAAAAfu7gwYNq0aKF/vjjD7fUL1SokGbPnq177rnHLfUBADdGAOhHAgICvN2CW/jq7wXPuvw+4v0E03hPwQTWKLgL7ykkJCTo1Vdf1axZs2TbtvH6wcHBGjFihNq1ayfLsozXh+9jnYKr+Bx1iWW7Y5UHAAAAAGRatm3rk08+UZcuXXTmzBm3zNGhQweNHTtWOXLkcEt9AMDNIwD0I7Gxsd5uwZicOXMqICBAqampio+P93Y78AEBAQHKmTOn4uPjlZqa6u12kMWxRsE01iiYxBqFv//+W61atdIPP/zglvr33HOPJk2apLJly7qlPnwf6xRM8sXPUc48R5VbgP2Ir7zR/81Xfy94R2pqKu8pGMX7CSaxRsE03k/+xbZtDRkyRBMmTHDL7b45cuTQ8OHD1bx5c0m8v2AG7yOY4u+fowgAAQAAAMDHffPNN+rcubNOnjxpvLZlWWrdurVGjRrFc/4AIJNyeLsBAAAAAIB7REdHq3PnzmrYsKFbwr/SpUtr165dmj17tgIDub4EADIrAkAAAAAA8DFpaWmaO3eu7r33Xi1btsx4/fDwcE2ZMkXffPONihYtarw+AMAsvqIBAAAAAB9y7NgxPfXUU9q/f7/x2pZlqX379ho4cKBy5sxpvD4AwD0IAAEAAADAB9i2rQEDBmjq1Klu2eTjrrvu0vvvv68777zTeG0AgHsRAAIAAABAFrd161b16NFDx48fN147JCREw4YNU/v27Y3XBgB4BgEgAAAAAGRRsbGxeumll/Tpp5+6pX79+vU1ZcoUBQcHu6U+AMAzCAABAAAAIAv65JNP1LNnTyUlJRmvXbRoUc2aNUvlypUzXhsA4HkEgAAAAACQhURHR+vJJ5/UTz/9ZLx2cHCwXnvtNXXp0kWBgfznIgD4Coe3GwAAAAAA/Le0tDSNHTtW99xzj1vCvypVqujHH39U9+7dCf8AwMewqgMAAABAJvfTTz+pY8eOOnTokPHaOXLk0EcffaRq1aoZrw0AyBy4AhAAAAAAMqnU1FS98sorqlatmlvCv27dumnfvn2EfwDg47gCEAAAAAAyoe3bt6tNmzY6c+aM8drlypXTlClTdNtttxmvDQDIfLgCEAAAAAAykfj4eHXv3l0NGjQwHv6FhYXpvffe07p16wj/AMCPcAUgAAAAAGQCtm1r1apVevbZZxUfH2+8ftWqVTVz5kxly5bNeG0AQOZGAAgAAAAAXnbhwgW1adNGmzdvNl47IiJCc+bMUaVKlYzXBgBkDdwCDAAAAABetHDhQt12223Gwz/LstSjRw/t2bOH8A8A/BxXAAIAAACAFxw9elTPPvusvv76a+O177rrLk2cOFF33XWX8doAgKyHKwABAAAAwIPS0tI0ffp0VaxY0Xj4FxgYqDfeeEMbNmwg/AMApOMKQAAAAADwkFOnTqlp06b69ddfjdd+4IEHtHDhQkVERBivDQDI2rgCEAAAAADczLZtjR8/Xvfcc4/x8C979uyaPn26Vq5cSfgHALgmrgAEAAAAADfav3+/unXrpj179hivHRUVpeHDhysyMtJ4bQCA7yAABAAAAAA3uHzV37Bhw5SWlma0dp48efTRRx/p4YcfNloXAOCbCAABAAAAwLBjx46pUaNG+vPPP43Xfvrpp/XOO+/IsizjtQEAvokAEAAAAAAMSUtL05gxY/TOO+8oNTXVaO1ixYpp3rx5KlOmjNG6AADfRwAIAAAAAAYcOnRI7dq102+//Wa0bkBAgPr06aNevXopMJD/hAMAZBz/9gAAAAAAF40bN05Dhw6VbdtG6956661atGiRihYtarQuAMC/EAACAAAAgJOOHDmiZs2a6cCBA0brOhwODRkyRF27djVaFwDgnxzebgAAAAAAsprU1FSNHz9eFStWNB7+PfDAA9q1axfhHwDAGK4ABAAAAIAMOHXqlJ588kn9/PPPRuuGhoZq6NChateuHTv8AgCMIgAEAAAAgJv00UcfqX///kpLSzNa9/7779eiRYsUERFhtC4AABIBIAAAAAD8p2PHjqlbt27avn270brBwcEaP368mjZtarQuAAD/xDMAAQAAAOA6bNvWggULVLFiRePhX40aNbRz507CPwCA23EFIAAAAABcQ0JCgpo1a6Zt27YZrRseHq7Ro0cT/AEAPIYAEAAAAAD+ZeXKlXrmmWd04cIFo3UfeughLViwQOHh4UbrAgBwIwSAAAAAAPB/zpw5oz59+uizzz4zWjcsLEwTJ07UE088YbQuAAA3gwAQAAAAACR9++23atGiheLj443WrVGjhsaNG6dbbrnFaF0AAG4WASAAAAAAv5aSkqJ+/fppzpw5RuuGhIRo7NixioqKMloXAICMIgAEAAAA4Ld27dqlDh066OjRo0brPvjgg1q4cKGyZctmtC4AAM5weLsBAAAAAPA027b13nvvqXbt2kbDv9DQUI0bN07Lly8n/AMAZBpcAQgAAADAr5w4cUKNGjXSoUOHjNatWLGipk2bpgIFChitCwCAq7gCEAAAAIBfsG1bM2bM0AMPPGA0/AsICNDIkSO1YsUKwj8AQKbEFYAAAAAAfN7Zs2fVoUMHbdy40Wjdu+66SwsXLmSHXwBApsYVgAAAAAB82ubNm1W2bFmj4V9gYKAGDBigdevWEf4BADI9rgAEAAAA4JMSExP10ksvaf78+UbrFilSRMuWLVOxYsWM1gUAwF24AhAAAACAz9m3b58qVapkPPx78cUXtXPnTsI/AECWwhWAAAAAAHzKhAkT9MYbbxitWahQIU2fPl3333+/0boAAHgCASAAAAAAn/DXX3+pQ4cO+v77743WbdGihUaNGqWgoCCjdQEA8BQCQAAAAABZ3hdffKFnnnlGCQkJxmpmy5ZNCxYsUKVKlYzVBADAG3gGIAAAAIAsKy0tTd26dVP79u2Nhn+PP/64du3aRfgHAPAJXAEIAAAAIEv68ccf1bZtW/3111/GaoaEhGjs2LGKiooyVhMAAG8jAAQAAACQpaSlpWnixIkaMmSIbNs2Vveuu+7SsmXLFBERYawmAACZAQEgAAAAgCzj7Nmzatq0qXbt2mWspsPh0MCBA9WjRw85HDwlCQDgewgAAQAAAGQJq1atUrdu3XT+/HljNYsXL66ZM2fqrrvuMlYTAIDMhq+3AAAAAGRqFy9eVN++fdWmTRuj4V+7du20Y8cOwj8AgM/jCkAAAAAAmdbx48dVr149HTt2zFjNnDlzavbs2Xr44YeN1QQAIDPjCkAAAAAAmdKMGTP0v//9z2j4V6NGDe3YsYPwDwDgV7gCEAAAAECmcuHCBXXt2lWrVq0yVtPhcGjUqFFq3bq1sZoAAGQVBIAAAAAAMo2ff/5ZjRo10pkzZ4zVLF26tD799FMVKFDAWE0AALISbgEGAAAA4HVpaWkaOXKkqlevbiz8syxLXbp00aZNmwj/AAB+jSsAAQAAAHjVuXPn1Lx5c+3YscNYzfDwcC1evFgVKlQwVhMAgKyKKwABAAAAeM327dtVtmxZo+FftWrV9NtvvxH+AQDwfwgAAQAAAHhcSkqKBg8erAYNGighIcFIzaCgIA0fPlyLFi1SaGiokZoAAPgCbgEGAAAA4FHx8fFq1KiR9u7da6xmwYIF9fnnn6tYsWLGagIA4Cu4AhAAAACAx6xfv15ly5Y1Gv61b99eu3btIvwDAOA6uAIQAAAAgNtdvHhRgwYN0rRp04zVzJ49uyZNmqS6desaqwkAgC8iAAQAAADgVnFxcapfv75+++03YzXLlSunpUuXKleuXMZqAgDgq7gFGAAAAIDbrF69WuXKlTMW/lmWpf79+2vdunWEfwAA3CSuAAQAAABgnDtu+c2bN69mzJihBx980FhNAAD8AQEgAAAAAKPi4uLUoEED/frrr8ZqVq1aVbNnz1ZYWJixmgAA+AtuAQYAAABgzJo1a3TPPfcYC/8CAgI0cuRIffzxx4R/AAA4iSsAAQAAALgsNTVVb775piZNmmSsZqFChTR37lyVK1fOWE0AAPwRASAAAAAAl5w5c0aNGjXSzz//bKxmgwYN9OGHHyowkP9kAQDAVdwCDAAAAMBpmzZt0v33328s/AsKCtKECRM0ffp0wj8AAAwhAAQAAADglFGjRikqKkpnz541Uq948eLauHGjmjdvbqQeAAC4hK/UAAAAAGRIfHy8WrZsqR07dhir+dRTT2nixImyLMtYTQAAcAkBIAAAAICb9v3336t169Y6ffq0kXrBwcEaO3asnnzySSP1AADA1bgFGAAAAMBNmT59uurWrWss/CtevLi2bNlC+AcAgJtxBSAAAACAGzp//ry6du2q1atXG6vZvHlzjR8/nlt+AQDwAAJAAAAAANf1559/qnHjxjp69KiResHBwRo1ahQbfQAA4EF+FwDGxcVp8eLF2rFjh06fPq2QkBCVLl1a9erVU6VKlTJcLzU1VXv37tWBAwd04MABHTx4UCdOnJAktWjRQq1atbrh+DFjxmjdunU3fE2xYsU0YcKEDPcGAAAAuGLFihXq1KmTUlNTjdQrVKiQli1bphIlShipBwAAbo5fBYCHDx/WgAEDFBcXJ0kKCwvT+fPntWvXLu3atUtPPPGEunTpkqGa0dHRGjhwoMu9BQcHKzw8/JrncubM6XJ9AAAA4GZdvHhRL7/8subMmWOsZlRUlCZNmiSHg8eQAwDgaX4TACYnJ2vo0KGKi4tT8eLF1bt3b5UsWVJJSUlatmyZ5s6dq+XLl6tkyZKqVatWhmqHhYWpVKlSuvXWW1W6dGnNnz9ff/31V4ZqPProo3rxxRczNAYAAAAw7fz582rQoIH27t1rpF5QUJCGDx+u9u3bG6kHAAAyzm8CwFWrVunEiRMKCQnRoEGDlC9fPklSSEiImjVrppiYGH3xxReaM2eOqlWrpsDAm/tHky9fPi1YsOCKhxcvXbrULb8DAAAA4E7btm1TixYtdP78eSP18ubNqxUrVqhUqVJG6gEAAOf4zfX3GzZskCRVqVIlPfz7p6ioKFmWpZiYGO3Zs+em6zocDnYuAwAAQJZm27bGjRunhg0bGgv/Hn/8cf3www+EfwAAZAJ+EQAmJCRo//79kqT777//mq/Jly+fihQpIkn68ccfPdYbAAAA4E0pKSlq27athgwZItu2Xa7ncDj05ptvatasWQoNDTXQIQAAcJVf3AJ89OjR9A8zxYsXv+7rihcvriNHjujIkSOeai3d7t271a1bN506dUrBwcEqWLCgHnjgAdWvX1+RkZEe7wcAAAC+78CBA2rWrJmxz78RERFasWKFypQpY6QeAAAwwy+uAIyJiUn/OXfu3Nd93eVzsbGxbu/p36Kjo3Xy5EmFhoYqMTFRBw8e1KJFi/Tcc89xRSIAAACMW7VqlapWrWos/HvooYf07bffEv4BAJAJ+cUVgImJiek/h4SEXPd1l88lJCS4vafLSpcurdtvv10VKlRQnjx55HA4dOHCBe3YsUMzZsxQTEyM3nrrLY0aNUqFCxe+Ya05c+Zo3rx51z3fsmVLtWrVyvSv4BUOhyP9f7lCEiZcfpZnRESEkduf4N9Yo2AaaxRMsixLAwYM0FtvvWWs5sCBAzVo0CCeje2nWKNgGp+lYBJr1CV+EQBmZk888cRVx8LDw1WtWjWVLVtWL774os6dO6f58+erb9++N6x1/vx5nTx58rrnL1y4oICAAJd7zkwsy/K53wnedfnDBmACaxRMY42Cq2JjY9W4cWNt2rTJSL3w8HB9+eWXqly5spF6yNpYo2Aan6Vgkr+vUX4RAP7z4cNJSUkKDw+/5uuSkpIkSWFhYR7p67/kz59f9evX18KFC/Xdd98pLS3thm/YbNmyKX/+/Nc9Hx4ertTUVHe06nGXd1+2bVtpaWnebgc+wLIsORwOpaWl+fW3QjCDNQqmsUbBhEOHDumRRx7RqVOnjNQrW7asli9fruLFi/vMZ0w4hzUKpvFZCib54hrlTDDuFwHgP5/7FxMTc90A8PKzAjPTJca33367pEtX7509e1YRERHXfW2bNm3Upk2b656Pjo72yvMN3SEyMlIBAQFKS0vzmd8J3hUQEKDIyEjFxcXxHzFwGWsUTGONgqs+/vhj9ezZU8nJyUbqtWrVSqNGjVJAQADrHFijYByfpWCSL65RefPmzfAYvwgAixQpkv7tweHDh1WkSJFrvu7w4cOSpKJFi3qyPQAAAMAtbNvWa6+9pilTphipFxgYqLFjx6pZs2ZG6gEAAM/wixugw8LCdNttt0mSdu7cec3XREdHp++AVr58eY/19l/27dsn6dLvkCNHDi93AwAAgKwiLi5OderUMRb+5cuXT2vWrCH8AwAgC/KLAFCSqlWrJknatGnTNZ97smTJEtm2rdy5c+vuu+/2SE//de/5qVOn9MUXX0iS/ve///n9AysBAABwc/bu3atKlSrphx9+MFLv0Ucf1Y8//qhy5coZqQcAADzLbxKlOnXqqECBAkpMTNSQIUP0+++/S7q08cfixYu1YsUKSZeeoxcYeOWd0Z07d1bDhg01ZsyYa9Y+f/684uPj0/9cfkhpUlLSFccvbzJy2YYNGzR8+HBt27ZN8fHx6ccTEhK0ceNGvfzyyzp79qzCwsLUsmVLU/8oAAAA4MOWL1+umjVrKjo62uValmXpxRdf1OLFixUUFGSgOwAA4A1+8QxASQoKCtJrr72mAQMG6I8//lDPnj0VHh6uxMTE9MCuQYMGqlWrVoZrDxs2THv37r3q+NKlS7V06dL0v7do0UKtWrVK/3taWpq++eYbffPNN5Iu3eYbGBio8+fPp/cUERGhfv36Xfe5hQAAAIAkpaam6pVXXtGMGTOM1AsODtacOXNUvXp1I/UAAID3+E0AKEnFihXT+PHj9cknn2jHjh2Kjo5WtmzZVKpUKdWvX1+VKlXyaD9333232rRpo19++UXHjh1TfHy8Lly4oGzZsqlo0aL63//+pzp16vDsPwAAANxQUlKSmjZtqh07dhipV6JECa1cudKpXQYBAEDmY9n/9SA6+AwTt4FkFpe3hU9NTWVbeBhxeWv42NhYn9kaHt7DGgXTWKNwI/v27dMTTzyhmJgYI/Xq1q2ryZMnKzw83Eg9+D7WKJjGZymY5ItrlDNf0PnNMwABAAAAX/PZZ5+pevXqxsK/ESNGaNasWYR/AAD4GL+6BRgAAADwFe+8845GjhxppFaOHDk0Z84cPfzww0bqAQCAzIUAEAAAAMhCzp07p/bt22vTpk1G6pUuXVqffvqpChQoYKQeAADIfLgFGAAAAMgioqOjVaVKFWPh31NPPaVvvvmG8A8AAB9HAAgAAABkAVu2bNF9992nI0eOuFwrICBA7733niZNmiTLsgx0BwAAMjNuAQYAAAAyMdu2NWXKFA0cOFC2bbtcL3v27Nq4caPKly/P7poAAPgJAkAAAAAgk0pNTVWvXr00f/58I/XKlCmjr776SoULF1ZqaqqRmgAAIPPjFmAAAAAgEzp16pQee+wxY+FfVFSU1q1bx/P+AADwQ1wBCAAAAGQyf/75p+rUqaPTp0+7XMuyLL399tvq2LGjgc4AAEBWxBWAAAAAQCayYsUKPfTQQ0bCv2zZsmnp0qWEfwAA+DkCQAAAACCTGD16tJ5++mklJye7XKtEiRL67rvv9MgjjxjoDAAAZGXcAgwAAAB4WVJSkrp166YVK1YYqVenTh1NmTJF4eHhRuoBAICsjQAQAAAA8KLo6Gg1adJEv/76q5F6AwYMUM+ePWVZlpF6AAAg6yMABAAAALxk3759qlu3ruLj412uFRwcrNmzZ6tGjRoGOgMAAL6EZwACAAAAXvDpp5+qWrVqRsK//Pnza926dYR/AADgmggAAQAAAA8bN26cunTpYmSzj4oVK2rnzp0qU6aMgc4AAIAv4hZgAAAAwENMb/bRunVrjRw5UkFBQUbqAQAA30QACAAAAHjAuXPn9MQTT2jv3r1G6o0dO1atWrUyUgsAAPg2AkAAAADAzfbt26cGDRooNjbW5VrZs2fXokWLVKFCBQOdAQAAf8AzAAEAAAA3Wrt2rWrUqGEk/CtatKg2bdpE+AcAADKEABAAAABwkxkzZqhly5ZKSkpyuVa1atX07bffqmjRogY6AwAA/oQAEAAAADAsJSVFL7zwgvr162ekXqdOnbRw4UIFBAQYqQcAAPwLzwAEAAAADEpJSVGzZs20efNml2s5HA5NnjxZTZo0MdAZAADwVwSAAAAAgCFHjx5Vo0aNdPjwYZdr5ciRQwsXLuR5fwAAwGUEgAAAAIABv/76q+rVq6ezZ8+6XKtIkSJasWKFChUqZKAzAADg73gGIAAAAOCiFStWqFq1akbCvypVqmj79u2EfwAAwBgCQAAAAMAF48aN09NPP63U1FSXa3Xq1Ekff/yxgoODDXQGAABwidEAcPXq1SbLAQAAAJlWWlqaevfurSFDhrhcy7IsTZw4UW+//bYcDr6jBwAAZhn9dPH444/r1ltv1YgRI3Ty5EmTpQEAAIBM49y5c2rUqJFmz57tcq3w8HAtWbJEzZo1M9AZAADA1Yx/vfj777/r1VdfVdGiRdW8eXN99dVXpqcAAAAAvObUqVOqXr26tm3b5nKtAgUK6Ouvv9ajjz5qoDMAAIBrMxoAtm/fXqGhobJtW8nJyVq8eLFq166t22+/Xe+++66io6NNTgcAAAB41N69e/XQQw/pjz/+cLnWfffdpy1btqhw4cKuNwYAAHADRgPA6dOn6/jx4xo7dqzKlSsn27Zl27YOHjyol19+WUWKFFGrVq20YcMGk9MCAAAAbrd582bVrl1bcXFxLtd66qmn9MUXXygiIsJAZwAAADdm/BbgiIgIPf/889q9e7e2bt2qdu3apV8VePHiRS1cuFA1a9bUHXfcodGjRysmJsZ0CwAAAIBRU6dOVVRUlJKTk12u9eqrr2rSpEkKDAw00BkAAMB/c+sWYw899JBmzJhxzasC9+/fr759+6pw4cJq27atNm/e7M5WAAAAAKe8/vrr6t+/v2zbdqlOQECApk2bpl69ehnqDAAA4Oa4NQC87N9XBbZt2zb9qsCkpCTNmzdP1apV01133aVx48bpzJkznmgLAAAAuK7ExES1bdtWEydOdLlWjhw5tGHDBjVs2NBAZwAAABnjkQDwnx566CHNnDlTx48f13PPPZd+3LZt/frrr+rVq5eKFCmiZ599VseOHfN0ewAAAIAuXLig+vXr68svv3S5VtGiRbVx40bdcccdBjoDAADIOI8HgCkpKVq4cKGaNm2qiRMnyrKs9NspLt8efOHCBU2ePFllypTRhx9+6OkWAQAA4McOHz6sBx98ULt373a5VqVKlfTNN9+oaNGiBjoDAABwjscCwAMHDuill15S4cKF03cCvhz4VaxYUdOnT9exY8c0atQolSlTJj0IfOaZZ7Rq1SpPtQkAAAA/tmvXLlWrVk0nTpxwuVZUVJSWLFmikJAQA50BAAA4z60BYHJyshYsWKAaNWqoTJkyeu+993Tq1CnZtq2wsDB16tRJ33//vbZt26b27durYMGCevHFF/XLL79o5syZCg8Pl23bevvtt93ZJgAAAKCvvvpKdevW1dmzZ12uNWjQIE2ePFlBQUEGOgMAAHBNoDuK7t+/X1OmTNHMmTN1+vRpSUq/zfeOO+5Q9+7d1a5dO0VERFy3Rtu2bbVv3z4NGzZMP/30kzvaBAAAACRJU6ZM0YABA1yuExgYqIkTJ6pp06YGugIAADDDaAA4f/58TZkyRZs2bZL0/0O/oKAgNW7cWN27d1e1atVuul7FihUlKT1EBAAAAEwbPny4Ro0a5XKd0NBQLVmyRBUqVDDQFQAAgDlGA8DWrVtfsalHkSJF1LVrV3Xu3FkFChTIcL3g4GCT7QEAAADpLl68qK5du2rFihUu1ypQoIBWr16tggULGugMAADALLfcAly7dm11795dTzzxhBwO5x8zWLFiRa1fv95gZwAAAMClZ1VHRUVp27ZtLtcqW7asli5dqty5cxvoDAAAwDyjAWDfvn3VrVs3lS5d2ki9yMhIVa1a1UgtAAAAQJJOnDihJ554Qn/88YfLterWrauZM2fKsizXGwMAAHATowHgO++8Y7IcAAAAYNTx48dVo0YNI8+Y7tixo4YPH074BwAAMj3n78+9ho4dO6pjx47atWtXhsbt3btXHTt2VKdOnUy2AwAAAKTbsWOHKlWqZCT8GzlypEaMGOHS424AAAA8xegnlhkzZmjmzJk6fPhwhsYdO3ZMM2bM0IwZM0y2AwAAAEiS1qxZo0aNGikhIcGlOkFBQZo+fbqefvppM40BAAB4gFs2AQEAAAAyi5kzZ6pv374u18mWLZuWLVum8uXLG+gKAADAczJFAJiamipJCgzMFO0AAADAB9i2rWHDhmns2LEu1ypQoIC++OILFS1a1EBnAAAAnpUpErfff/9dkpQzZ04vdwIAAABfkJqaqt69e2vevHku17rzzjv16aefKnfu3AY6AwAA8Dy3BIA3uxPahQsXtHPnTo0dO1aWZenOO+90RzsAAADwI0lJSWrdurU2btzocq2qVatq/vz5CgoKMtAZAACAdzgdAL7xxht68803rzpu27YaN27sVM0mTZo42w4AAACg+Ph4NWnSRLt373a5Vtu2bTVy5EgFBAQY6AwAAMB7XLoC0LbtDB2/kWrVqum5555zpR0AAAD4sRMnTqhevXo6cuSIy7UGDBigF1980fWmAAAAMgGnA8ASJUqoatWqVxzbuHGjLMtS2bJllTdv3huOdzgcyp49u0qWLKlatWqpXr16cjgczrYDAAAAP3bw4EHVrVtXsbGxLtVxOBwaP368mjVrZqgzAAAA73M6AGzfvr3at29/xbHLAd6wYcPUsGFD1zoDAAAAbsJ3332nqKgoXbhwwaU6QUFBWrJkiSpVqmSoMwAAgMzB6CYgVapUkWVZ/3n1HwAAAGDCxo0b1bx5c6WmprpUJ0eOHFq2bJnuvvtuQ50BAABkHkYDwA0bNpgsBwAAAFzXvHnz1KtXL6WlpblUp2DBglq7dq3y589vqDMAAIDMhYfuAQAAIMv54IMP1LNnT5fDvzJlymj9+vWEfwAAwKcZvQIQAAAAcCfbtvXaa69pypQpLteqWrWq5s2bp+DgYAOdAQAAZF5OBYBvvvlm+s+DBg265nFn/bMeAAAAcJlt23rhhRe0YMECl2s1atRIkydPVmAg34cDAADfZ9m2bWd0kMPhkGVZknTFA5f/edxZrj7AGdcXHR3t7RaMiYyMVEBAgFJTUxUbG+vtduADAgICFBkZqdjYWNYhuIw1CqaxRkkJCQlq27atNm7c6HKtnj17asCAAS5/bs2qWKNgGmsUTGOdgkm+uEY5s/mu01952rZ9zQ9NTuSJ6fz1QxgAAACuLzk5WU2aNNH333/vcq3BgwfrueeeM9AVAABA1uFUALh+/foMHQcAAACccerUKTVo0ECHDh1yqY5lWfrggw/UpEkTQ50BAABkHU4FgFWrVs3QcQAAACCjTp8+rVq1aun48eMu1QkJCdHcuXP5rAoAAPwWTz0GAABApvPbb7+pfv36iouLc6lOeHi4li1bpnvvvddMYwAAAFkQASAAAAAylV9++UWPP/64Lly44FKdvHnzas2aNSpSpIihzgAAALImrwSAJ0+e1LZt25SSkqLy5curdOnS3mgDAAAAmczmzZvVvHlzJScnu1SnSJEiWrlypQoUKGCoMwAAgKzLaAAYExOjGTNmSJLq16+vMmXKXPWaIUOGaNiwYVd8qGvevLk++ugjhYaGmmwHAAAAWciqVavUvn17paamulTn7rvv1sqVKxUSEmKoMwAAgKzNaAC4cOFC9e3bV8HBwWrfvv1V5+fOnavBgwfLsizZtn3FuLS0NC1YsMBkOwAAAMgiFi5cqOeff/6Kz4jOeOSRRzRv3jzCPwAAgH9wmCy2fv16SVLlypWVJ0+eq84PGjRIkmTbtho1aqQXX3xRRYsWlW3b+vjjj7V582aT7QAAACALmDx5sp577jmXw78mTZpo6dKlCg8PN9QZAACAbzAaAO7bt0+WZemhhx666tzXX3+t33//XZZlaejQoVq6dKlGjRqlb7/9VpGRkZKk2bNnm2wHAAAAmZht2xo5cqQGDhzocq2OHTtq8uTJsizLQGcAAAC+xWgAGB0dLUm67bbbrjq3du1aSVJISIh69uyZfjx//vxq2bKlbNvWtm3bTLYDAACATMq2bfXv31/vvPOOy7Vee+01jRgxQg6H0Y+2AAAAPsPoMwBPnz4tScqWLdtV57Zu3Srp0u3B/z5/zz33SJIOHz5ssh0AAABkQqmpqerZs6cWLlzoUh3LsvT222+rY8eOhjoDAADwTUYDwMu3XMTGxl5xPC0tTdu3b5dlWapcufJV4y4/L/DChQsm2wEAAEAmk5aWpnbt2mn16tUu1XE4HJo+fbrq1atnqDMAAADfZfQ+ifz580uS9u/ff8Xxbdu2KT4+XpJUqVKlq8adO3dOkhQWFmayHQAAAGQiFy5c0JNPPuly+BcUFKSFCxcS/gEAANwkowHgfffdJ9u2tWDBAl28eDH9+IcffihJCg4O1iOPPHLVuEOHDkmSChUqZLIdAAAAZBJJSUlq2LChNm/e7FKd0NBQrVy5UtWqVTPTGAAAgB8wGgA+9dRTkqQjR46oZs2amjx5srp06aKZM2fKsiw1bNjwmlf5bdu2TZZl6c477zTZDgAAADKBmJgY1axZUz/++KNLdSIiIvTVV1+pfPnyhjoDAADwD0afAdiyZUuNHz9e27dv19dff62vv/46/VxISIgGDx581ZgzZ85ow4YNkqQHH3zQZDsAAADwsri4OD322GMub/aWP39+rV69WoULFzbUGQAAgP8wegWgZVlasWKFGjduLMuyZNu2bNtW4cKF9cknn6hs2bJXjZkxY4aSk5MlSbVq1TLZDgAAALzoyJEjevTRR10O/4oWLar169cT/gEAADjJ6BWAkpQ7d24tWbJEp06d0qFDh5QtWzaVLVtWDse1s8ayZctq+vTpsixLDzzwgOl2AAAA4AVHjx5VrVq1FBMT41KdO++8U59//rly5sxpqDMAAAD/YzwAvCxfvnzKly/ff76udu3a7moB/xIQEODtFtzCV38veNbl9xHvJ5jGewomZLU16ueff1a9evUUHx/vUp377rtPn332mbJly2aoM/xbVnlPIXPLamsUshbeV3AVa9Qllm3btrebAAAAgG/YvXu3HnnkEZ07d86lOnXq1NFnn32m4OBgQ50BAAD4LwJAPxIbG+vtFozJmTOnAgIClJqa6vLVBYB06dugnDlzKj4+Xqmpqd5uB1kcaxRMyypr1LZt29SkSRMlJSW5VOfxxx/XrFmzFBjotptV/BprFEzLKmsUsg7WKZjki2tUZGRkhse49VPVX3/9pb179yo2NlaJiYk3NaZdu3bubMmv+cob/d989feCd6SmpvKeglG8n2BSZl6jtmzZombNmqVv7uastm3b6r333pNlWZn2d/Ul/DOGSZl5jULWxXsKpvj7GuWWAHDBggV6++23tWfPngyNsyyLABAAACCLWbNmjdq2bevyh+pOnTpp+PDhsizLUGcAAACQ3BAAvvDCC5o4caIkibuLAQAAfNvnn3+uTp06KS0tzaU6r7zyivr06WOoKwAAAPyT0QDws88+04QJE9L//uCDD+qxxx5TkSJFFBISYnIqAAAAeNmSJUv0zDPPuPyl78CBA/XCCy8Y6goAAAD/ZjQA/OCDDyRdesDijBkz1Lp1a5PlAQAAkEnMnj1bvXv3drnO6NGj1aZNGwMdAQAA4HqMBoDfffedLMtSmzZtCP8AAAB81IwZM9SvXz+XajgcDo0fP17NmjUz1BUAAACux2gAGBcXJ0mqWbOmybIAAADIJCZMmKA33njDpRoOh0MzZsxQ3bp1DXUFAACAG3GYLHbLLbdIkoKCgkyWBQAAQCYwbtw4l8O/oKAgLViwgPAPAADAg4wGgA8++KAk6ZdffjFZFgAAAF721ltvaciQIS7VCA4O1uLFi1W9enVDXQEAAOBmGA0Au3fvLtu2NWfOHCUnJ5ssDQAAAC+wbVvDhg3T6NGjXaoTFhamL774Qg8//LChzgAAAHCzjAaA1atX13PPPadDhw7p6aefJgQEAADI4l577TWNGTPGpRrZsmXTihUrVL58eTNNAQAAIEOMbgJy+PBh9enTRzExMZo3b5527typHj166KGHHlLevHnlcPx33lisWDGTLQEAAMAJtm3r1Vdf1dSpU12qExERodWrV6tUqVKGOgMAAEBGGQ0AS5QoIcuyJEmWZWnfvn168cUXb3q8ZVlKSUkx2RIAAACc0KtXL82dO9elGnny5NGKFSsI/wAAALzMaAAoXfq2GAAAAFlTamqqevfurXnz5rlUJ1++fNqwYYPy589vqDMAAAA4y2gA2L59e5PlAAAA4GHPPvusPvnkE5dqFC5cWCtXriT8AwAAyCSMBoDTp083WQ4AAAAekpKSoh49emjp0qUu1SlatKjWrVunXLlymWkMAAAALjO6CzAAAACypi5durgc/t16661as2YN4R8AAEAmQwAIAADgxy5evKj27dvr888/d6lOmTJltGbNGuXJk8dQZwAAADCFABAAAMBP2batTp066YsvvnCpzj333KOVK1cqe/bshjoDAACAScZ3Ab7szJkz+vDDD7Vq1Sr9/PPPiomJUUpKilJSUq543bp163TixAnlzZtXtWvXdlc7AAAA+IekpCQ9/fTTWrt2rUt1ypcvr+XLlyssLMxQZwAAADDNLQHgwoUL1a1bN509e1bSpW+XJcmyrKte++OPP6pPnz4KCwvTX3/9pZw5c7qjJQAAAPwf27aNhH8PPvigFi1aRPgHAACQyRm/BXjWrFlq1aqV4uPjZdu2ChQooNtvv/26r3/66acVGBioxMRELV++3HQ7AAAA+IekpCQ1b97c5fCvYsWK+uSTTxQeHm6oMwAAALiL0QDw+PHjeuaZZ2TbtgoVKqTVq1fr2LFjGjFixHXHREZGqkqVKpIu3Q4MAAAA90hLS1P79u21fv16l+pUrVpVS5cuVUhIiKHOAAAA4E5GA8AJEyYoMTFRYWFh+uqrr1SrVq2bGlexYkXZtq0ff/zRZDsAAAD4P0lJSWrWrJm++uorl+pUqVJF8+fPV3BwsKHOAAAA4G5GA8DVq1fLsiy1atVKZcqUuelxt956qyTpjz/+MNkOAAAAJKWmpqpdu3bauHGjS3Vq166thQsXKigoyFBnAAAA8ASjm4D8/vvvkqRHH300Q+MiIiIkKX3TEAAAAJhx8eJFtWzZUps2bXKpTq1atTRz5kwFBrplDzkAAAC4kdErAM+fPy9Jyp49e4bGJSQkSJJCQ0NNtgMAAODXUlJS1K5dO5fDvwYNGmjOnDmEfwAAAFmU0QAwT548kqS///47Q+P2798vScqXL5/JdgAAAPxWcnKyWrZs6fIz/+rWraupU6cqICDAUGcAAADwNKMBYNmyZSUpw98yL1++XJZl6YEHHjDZDgAAgF+6fOXfhg0bXKrTpEkTzZgxg/APAAAgizMaANatW1e2bWvZsmXpV/X9lwULFmjXrl2SpHr16plsBwAAwO+kpKSodevWWrt2rUt1nnjiCb3//vtyOIx+XAQAAIAXGP1E17lzZ+XOnVsXL15Uw4YN0zcFuZ6FCxeqS5cusixLhQoVUqtWrUy2AwAA4FdSUlLUoUMHrVu3zqU6TZs21bRp07jyDwAAwEcYfZJzzpw59f7776tFixbat2+fypUrpyZNmigkJCT9NRMnTtSRI0f05Zdfas+ePbJtWwEBAfroo48UFBRksh0AAAC/kZaWpvbt22v16tUu1WncuLEmTZoky7IMdQYAAABvM76V21NPPaUzZ87o+eefV0JCgubPny9J6R8iX3jhhfTX2rat4OBgffDBB3rsscdMtwIAAOAXUlJS1KVLF5fDvyeffJLwDwAAwAe55aEuXbp00bfffqvGjRvLsizZtn3VH+nSM/+2b9+u9u3bu6MNAAAAn2fbtjp37qzPP//cpTpNmjTRhAkTCP8AAAB8kPErAC+7++67tWTJEsXFxWnr1q36448/dObMGWXPnl1FihRR5cqVlS9fPndNDwAA4PNSU1PVo0cPrVixwqU6XPkHAADg29wWAF4WERHB7r4AAACG2batZ599VkuWLHGpTtOmTbnyDwAAwMcZDQAPHz4sScqfP79CQ0NvelxSUpL+/vtvSVKxYsVMtgQAAOBz0tLS1KtXL33yyScu1YmKitLkyZMNdQUAAIDMyugzAEuUKKFSpUpl+AHUGzZsSB8LAACAG+vXr5/mzZvnUo3GjRtrwoQJhjoCAABAZmb8FuDLG3x4eiwAAICvs21b/fv316xZs1yq06hRI3344YeGugIAAEBm55ZdgAEAAGDewIEDNXXqVJdqNGzYUO+//76hjgAAAJAVuH0TkJtx9uxZSVJ4eLiXOwEAAMh8bNvWgAEDNGnSJJfq1KtXT9OmTTPUFQAAALKKTBEArl27VpJUsGBBL3cCAACQ+bzzzjsaMWKESzXq1q3r8tWDAAAAyJqcDgA3btyojRs3XvPcggULtGvXrhuOt21b58+f186dO7V+/XpZlqWHH37Y2XYAAAB80tixY10O/2rWrKmZM2fKsixDXQEAACArcToA3LBhg958882rjtu2rYULF2aolm3bCgoK0gsvvOBsOwAAAD5n8uTJGjp0qEs1atasqVmzZhH+AQAA+DGXNgGxbfuKP9c7/l9/7r//fi1fvlz333+/y78QAACAL5g5c6YGDhzoUo3KlStr7ty5Cg4ONtQVAAAAsiKnrwB8+umnVa1atfS/27atGjVqyLIsDRkyRI888sgNxzscDmXPnl0lS5ZUrly5nG0DAADA58yZM0d9+/Z1qUblypU1f/58BQQEGOoKAAAAWZXTAWDx4sVVvHjxa54rV66cqlat6nRTAAAA/uqTTz5R7969XapRsWJFLVy4UEFBQYa6AgAAQFZmdBfg9evXS7oUAAIAACBjli1bpu7du1/xaJWMqlChghYvXkz4BwAAgHRGA0Cu+gMAAHDO2rVr1bVrV5fCv3vuuUdLlixRaGiowc4AAACQ1bm0CQgAAABct379erVt21ZpaWlO1yhXrpyWLVtG+AcAAICrGL0C8N/S0tJ08OBBxcbGKjEx8abGVKlSxZ0tAQAAZCrfffedWrVqpZSUFKdr3H777Vq+fLmyZ89usDMAAAD4CrcEgF9//bXeeecdrVmz5qaDP0myLMulD78AAABZyc6dO9W4cWOXPv+UKlVKX3zxBeEfAAAArst4APjee+/p5Zdflm3bLj3DBgAAwJft379fjRs3VlJSktM1ihcvri+++EIREREGOwMAAICvMRoAbt68Wf369ZNlWbJtW4ULF1b16tVVpEgRhYSEmJwKAAAgyzp48KDq1KmjhIQEp2sUKlRIq1evVu7cuQ12BgAAAF9kNAAcO3Zs+s9DhgxR//795XCwzwgAAMBlx44dU7169XT27Fmna+TLl09ffPEF4R8AAABuitEA8JtvvpFlWWrcuLEGDBhgsjQAAECWd/LkST3++OOKiYlxukbu3Lm1fv163XLLLQY7AwAAgC8zenne6dOnJUlPPPGEybIAAABZXnR0tB5//HGdOHHC6RoRERH6/PPPCf8AAACQIUYDwLx580qSsmXLZrIsAABAlnbu3Dk1bNhQR44ccbpG9uzZtW7dOt12220GOwMAAIA/MBoA3nvvvZIuPdgaAAAA/z/8279/v9M1wsLCtH79epUsWdJgZwAAAPAXRgPATp06ybZtLViwwGRZAACALCk1NVXNmzfXnj17nK4RHBysL774Qv/73/8MdgYAAAB/YjQAbNKkiaKiorR792699NJLJksDAABkKRcvXlTLli21Y8cOp2sEBgZqwYIFKl++vMHOAAAA4G+M7gIsSXPmzFFISIjee+89ff/993rxxRf10EMPpT8fEAAAwB9069ZN69evd3q8w+HQokWLVLlyZYNdAQAAwB8ZDQADAgLSf7ZtWxs2bNCGDRtuerxlWUpJSTHZEgAAgEelpaWpd+/e+vzzz12qM23aNMI/AAAAGGE0ALRt+4Z/BwAA8HWDBw/W3LlznR5vWZamTp2qBg0aGOwKAAAA/sxoAFilShVZlmWyJAAAQJYxatQoTZ482aUa7777rho2bGioIwAAAMBwAJiR230BAAB8yZQpUzR8+HCXarz11ltq166doY4AAACAS4zuAgwAAOCPlixZogEDBrhU4+WXX1aXLl0MdQQAAAD8fwSAAAAALvjss8/0zDPPuFTj+eefV58+fQx1BAAAAFzJ6C3AAAAA/mT79u3q2rWrSxuftW3bVoMGDTLYFQAAAHAlrgAEAABwwvbt29W0aVOlpqY6XaNJkyYaOXKkwa4AAACAqzl1BWDHjh0lSZZladq0aVcdd9a/6wEAAGRGf/zxh5566ildvHjR6Ro1a9bUBx98IMuyDHYGAAAAXM2ynbhnxeFwpH9Y/ee33v887ixXvkXHjUVHR3u7BWMiIyMVEBCg1NRUxcbGersd+ICAgABFRkYqNjaWdQguY43ybQcPHtTjjz+uM2fOOF2jUqVK+vjjjxUaGnpTr2eNgkmsUTCNNQqmsU7BJF9co/LmzZvhMU4/A9C27WuGfa48A4dvwAEAQGZ29uxZNWzY0KXw75577tEnn3yi4OBgc40BAAAAN+BUAPj7779n6DgAAEBWFxsbq9q1a+vkyZNO1yhdujThHwAAADzOqQCwePHiGToOAACQlSUmJurJJ5/UH3/84XSNokWL6ssvv1SuXLmM9QUAAADcDKdvAfaUmJgY7d27V5JUpUoVL3cDAAD8TXJyslq2bKndu3c7XSNv3rxavnw54R8AAAC8ItMHgJs3b1aTJk3kcDiUkpLi7XYAAIAfSU1NVZcuXbRlyxana+TMmVMrV65U4cKFDXYGAAAA3DyHtxu4Wa5sLgIAAOCMfv36acWKFU6PDw0N1eeff64SJUqYawoAAADIoCwTAAIAAHjSsGHDNHv2bKfHBwUF6eOPP9add95psCsAAAAg4wgAAQAA/uWDDz7QmDFjnB7vcDg0d+5cVapUyVxTAAAAgJMIAAEAAP7hk08+0cCBA50eb1mWJk2apOrVqxvsCgAAAHBept8ExLS4uDgtXrxYO3bs0OnTpxUSEqLSpUurXr16Tn1Ln5qaqr179+rAgQM6cOCADh48qBMnTkiSWrRooVatWt1UnUOHDmnp0qXas2eP4uPjFRERoXLlyqlp06YqWbJkhvsCAAAZt27dOnXv3t2lZw+PGDFCUVFRBrsCAAAAXONXAeDhw4c1YMAAxcXFSZLCwsJ0/vx57dq1S7t27dITTzyhLl26ZKhmdHS0S1cJSNLGjRs1duzY9F2Os2XLptOnT2vjxo3aunWrevXqpcqVK7s0BwAAuLFdu3apbdu2LoV/r7zyijp06GCwKwAAAMB1fhMAJicna+jQoYqLi1Px4sXVu3dvlSxZUklJSVq2bJnmzp2r5cuXq2TJkqpVq1aGaoeFhalUqVK69dZbVbp0ac2fP19//fXXTY09fPhwevj36KOPqnPnzsqdO7diYmL04YcfauvWrRozZoxKliypIkWKOPOrAwCA//Drr7+qUaNGunjxotM1unXrpj59+hjsCgAAADDDbwLAVatW6cSJEwoJCdGgQYOUL18+SVJISIiaNWummJgYffHFF5ozZ46qVaumwMCb+0eTL18+LViwQJZlpR9bunTpTfc1d+5cpaSkqGTJkurTp48CAgIkSblz51bfvn11/Phx/f7775o7d65efvnlDPzGAADgZpw6dUpNmjTRhQsXnK4RFRWlIUOGGOwKAAAAMMdvNgHZsGGDJKlKlSrp4d8/RUVFybIsxcTEaM+ePTdd1+FwXBH+ZcT58+f17bffSpIaN26cHv5dFhAQoMaNG0uSduzY4dJ/mAAAgKudPHlStWvXVnR0tNM1atWqpQkTJjj9eQAAAABwN78IABMSErR//35J0v3333/N1+TLly/9Ftsff/zRI339/PPP6c/9u15fl48nJyfrl19+8UhfAAD4g+TkZD311FM6evSo0zUeeOABzZ49+6bvHAAAAAC8wS8CwKNHj6Y/0Lt48eLXfd3lc0eOHPFIX5fnyZUrlyIiIq75moiIiPRzhw8f9khfAAD4usTEREVFRennn392usZtt92mhQsXEv4BAAAg0/OLADAmJib959y5c1/3dZfPxcbGur2nf85zo57+ed5TfQEA4Ot69Oihb775xunxt9xyi9asWXPdL/AAAACAzMQvvrJOTExM/zkkJOS6r7t8LiEhwe09/XOeG/X0z/P/1decOXM0b968655v2bKlWrVqlcEuMyeHw5H+v5GRkV7uBr7g8rO7IiIi0q8YBpzFGpV52batPn36aPny5U7XyJMnjzZu3Jj+6BBPYI2CSaxRMI01CqaxTsEk1qhL/CIA9Bfnz5/XyZMnr3v+woULV200ktVZluVzvxO86/KHDcAE1qjM56233tK4ceOcHh8WFqbvvvtOJUqUMNdUBrBGwSTWKJjGGgXTWKdgkr+vUZk+ACxWrJjat2/vUo3Q0ND0n5OSkhQeHn7N1yUlJUm69OHeEy7Pc3ne67nZvrJly6b8+fNf93x4eLhSU1Mz2GXmdHn3Zdu2lZaW5u124AMsy5LD4VBaWppffysEM1ijMqf58+drwIABTo8PDAzUihUrVLRoUY//+5Q1CiaxRsE01iiYxjoFk3xxjXImGM/0AeB9992n6dOnu1Tjn8/Yi4mJuW4AePlZgZ66xPhyX/98RuG13Gxfbdq0UZs2ba57Pjo62meeIxgZGamAgAClpaX5zO8E7woICFBkZKTi4uJ8JiiH97BGZT4rVqxQhw4dnB7vcDi0ePFi3X333V75vylrFExijYJprFEwjXUKJvniGpU3b94Mj/GL6x+LFCmSfs/3jXbSvXyuaNGiHunr8jxnzpxRfHz8NV8TFxenuLg4SZeuhgQAABnzyy+/qEuXLi594ztmzBg98sgjBrsCAAAAPMfoFYClSpVyapzD4VCOHDmUO3dulS9fXtWrV1f9+vWN3Z8dFham2267Tfv27dPOnTv18MMPX/Wa6OhoHTlyRJJUvnx5I/P+l7JlyyowMFApKSnauXOnqlWrdtVrfvjhB0lSUFCQ7rzzTo/0BQCAr/j5559Vr149JScnO13jrbfeUsuWLQ12BQAAAHiW0QDwjz/+SL9P/7LLV95Jl3be+/ff//26DRs2aOzYsSpWrJimTJmixx57zEhv1apV0759+7Rp0yY1b95c+fLlu+L8kiVLZNu2cufOrbvvvtvInP8lPDxcFSpU0DfffKNly5apcuXKV9zHnZqaqmXLlkmSKlaseN1blwEAwNXOnj2rJk2a6Pz5807X6N69u7p06WKwKwAAAMDzjN4CXKxYMRUrVkyFCxdOD/Rs25Zt24qIiFDhwoXTt12+HP5ZlqXChQurUKFCCg0NTT/3559/qm7dulq8eLGR3urUqaMCBQooMTFRQ4YM0e+//y7p0gYbixcv1ooVKyRdeo5eYOCVuWjnzp3VsGFDjRkz5pq1z58/r/j4+PQ/lx9SmpSUdMXxa2320bp1awUGBurgwYMaNWpU+vMNYmNjNWrUKB08eFBBQUFq3bq1kX8OAAD4g9jYWNWsWfM/n7N7I82aNdPrr79urikAAADAS4xfAXj8+HE1b95cx44d06OPPqpevXqpevXqypUrV/rrzpw5o3Xr1mnMmDHasmWLSpQooUWLFqlgwYLau3evxo8frw8//FBpaWnq2LGjqlevrjx58rjUW1BQkF577TUNGDBAf/zxh3r27Knw8HAlJiamB3YNGjRQrVq1Mlx72LBh2rt371XHly5dqqVLl6b/vUWLFmrVqtUVrylWrJh69uypsWPHavPmzdqyZYvCw8PTr1YIDAxUz549VaRIkQz3BQCAP0pJSVGLFi3Sv+xzRtWqVTVhwoQr7lwAAAAAsiqjVwAmJSWpQYMG+vrrrzVw4EBt2rRJTZo0uSL8k6RcuXKpadOm2rRpkwYMGKCtW7eqQYMGunjxosqVK6cPPvhA48ePl3Tp6roPPvjASH/FihXT+PHj1ahRIxUsWFDJycnKli2bypcvr1dffVVdu3Y1Mk9GVa1aVe+++66qVKmiyMhIJSUlKXfu3Kpataree+89ValSxSt9AQCQ1aSlpalz587auXOn0zXuuecezZgxg/APAAAAPsOyXdkS71/GjRunF198UQ899JC2bt160+Mefvhhbd++XWPGjNHzzz+ffvz+++/Xjz/+qCpVqmj9+vWm2vRb0dHR3m7BmMvbwqemprItPIy4vDV8bGysz2wND+9hjfIO27bVr18/zZw50+kaJUuW1IYNGzLdc3dZo2ASaxRMY42CaaxTMMkX16i8efNmeIzRKwDnz58vy7LUokWLDI1r0aKFbNvW/PnzrzjeuHFj2batX3/91WSbAADAB02YMMGl8C937tz65JNPMl34BwAAALjKaAB44MABSVLBggUzNO7y6/fv33/F8VtvvVWSSPwBAMANzZs3T2+++abT47Nnz65Vq1apaNGiBrsCAAAAMgejAeDljSuOHz+eoXF//fWXJOnChQtXHA8JCZEkhYaGGugOAAD4oq1bt6pnz55Ojw8ICNCCBQtUokQJc00BAAAAmYjRAPDyt+b/vpX3v1x+/b93ur38zDpXdwAGAAC+6ccff8zwo0f+yeFwaNasWXrwwQcNdgUAAABkLkYDwDp16si2be3YsUMDBgy4qTGvvvqqtm/fLsuy9Pjjj19xbvfu3ZIyfksxAADwfUePHlVUVJQSExOdrjFy5EjVrl3bYFcAAABA5mM0AOzbt6+yZcsmSXr77bdVpUoVLVmyRDExMVe8LiYmRp988okqV66sESNGSJLCw8PVp0+fK163cuVKWZalihUrmmwTAABkcfHx8WrcuLHi4uKcrtGvXz+1a9fOYFcAAABA5hRoslixYsU0ffp0tWrVSqmpqdq6dau2bt0qScqZM6fCw8N14cIFxcfHp4+xbVuBgYGaMWOGihUrln5806ZNOnnypMLDw9WoUSOTbQIAgCzs/PnzatKkif7880+na7Ru3VovvfSSwa4AAACAzMtoAChJTz75pPLmzavOnTvr0KFD6cfj4uIUHx8v27aveH3p0qU1depUVa1a9YrjVapU0blz50y3BwAAsjDbttWtW7f0x4Q4o0aNGho5cqTBrgAAAIDMzXgAKEnVqlXTb7/9ps8++0yffvqpvv32Wx0/flznz59XtmzZVKhQIVWoUEGNGjVSo0aNFBAQ4I42AACAD7FtW/369dOqVaucrnHfffdp1qxZCgoKMtgZAAAAkLm5JQCUpICAADVp0kRNmjRx1xQAAMCPjB8/XjNnznR6fNGiRbVo0SKFhIQY7AoAAADI/IxuAgIAAOAOn332mYYOHer0+MjISH366afKlSuXuaYAAACALIIAEAAAZGqbN29Wly5drnqO8M0KDg7WypUrr9hsDAAAAPAnBIAAACDTOnz4sNq2bau0tDSnxgcEBGj27NkqXbq04c4AAACArMNtzwDctWuXVq5cqb179yo2NlaJiYn/OcayLH311VfuagkAAGQhR44c0WOPPabz5887XWPy5MmqUaOGwa4AAACArMd4APjXX3+pQ4cOWrNmTYbG2bYty7JMtwMAALKglJQUtWjRQjExMU7XePnll9W4cWNzTQEAAABZlNEA8Ny5c6pevbr279/v9HN6AACAf0tKSlLz5s21b98+p2t07txZffr0MdgVAAAAkHUZfQbg6NGj0z+sFylSRO+//74OHDigxMREpaWl/eef1NRUk+0AAIAsqHfv3tq6davT42vWrKm33nqLOwsAAACA/2P0CsClS5dKkgoUKKBvv/1Wt9xyi8nyAADAx40dO1aLFi1yevw999yjadOmEf4BAAAA/2A0ADx48KAsy1KPHj0I/wAAQIbMnj1bQ4cOdXp8gQIFtHLlSgUHBxvsCgAAAMj6jN4CnJaWJkkqU6aMybIAAMDH7dq1S/369XN6fM6cObV06VLCPwAAAOAajAaAxYsXlySdPXvWZFkAAODDdu/erSeeeMLpZwEHBQVp1apVuvXWWw13BgAAAPgGowFgw4YNZdu2Sw/uBgAA/uPChQtq1qyZEhMTna4xZcoUwj8AAADgBowGgM8//7wiIyM1d+5c/frrryZLAwAAH3P27Fk99thjOn36tNM1xo8frwYNGhjsCgAAAPA9RgPAggULasGCBQoMDNRjjz2mTZs2mSwPAAB8hG3bat++vfbt2+d0jWeffVYtWrQw2BUAAADgm4zuAvzmm29KkmrVqqVly5apevXquvfee/XQQw8pb968cjj+O28cNGiQyZYAAEAmY9u2+vfvr82bNztdo1GjRnxmAAAAAG6S0QDw9ddfl2VZkiTLsmTbtnbt2qVdu3bddA0+zAMA4NtGjx6tadOmOT2+QoUK+vDDD9M/cwAAAAC4MaMBoHTpW/0b/f1G+CAPAIBvW716tYYPH+70+GLFimn27Nl8ZgAAAAAywGgAuH79epPlAACAD9m+fbuefvppp8fnyZNHa9asUe7cuc01BQAAAPgBowFg1apVTZYDAAA+4sSJE2rRooWSk5OdGh8UFKS5c+cS/gEAAABOMLoLMAAAwL/Fx8friSee0Llz55wa73A4NH/+fD3wwAOGOwMAAAD8AwEgAABwm6SkJDVv3lx//PGH0zXeeust7jIAAAAAXEAACAAA3KZv37767rvvnB7fvXt3dezY0WBHAAAAgP9x6hmAhw8fTv+5WLFi1zzurH/WAwAAWdfIkSO1YMECp8fXr19fb775psGOAAAAAP/kVABYsmRJSZJlWUpJSUk/XqJECVmW5XQz/64HAACypmXLlumdd95xeny5cuU0YcIEgx0BAAAA/supANC2bafOAQAA37dz5051797d6fFFihTRp59+quzZsxvsCgAAAPBfTgWA7du3z9BxAADgHw4ePKimTZsqOTnZqfHh4eFavHixIiIiDHcGAAAA+C+nAsDp06dn6DgAAPB9CQkJatWqlc6fP+/U+MDAQM2fP1+lS5c23BkAAADg39gFGAAAuCwhIUFNmzbVoUOHnK4xYcIEPfzwwwa7AgAAACARAAIAAANeeuklfffdd06P79Wrl6Kiogx2BAAAAOAyAkAAAOCSSZMmacGCBU6Pb9asmfr372+wIwAAAAD/RAAIAACc9umnn2rw4MFOj3/ggQc0evRoWZZlsCsAAAAA/+TUJiD/JTU1VcuXL9fKlSu1d+9excbGKjEx8T/HWZalgwcPuqMlAABg2IEDB/Tcc885Pb5o0aKaN2+egoODDXYFAAAA4N+MB4A///yzmjdvrp9//vmK47Zt/+dYvv0HACBr+P333/X4448rKSnJqfFhYWFauXKlcufObbgzAAAAAP9mNAA8deqUatasqZMnT6YHfoGBgcqbN69CQkJMTgUAALwkLS1Nbdq0UVxcnFPjAwMDNW/ePN1yyy2GOwMAAABwLUYDwJEjR+rvv/+WZVm69957NXz4cFWvXp1bewAA8BHJyclq3bq19u3b53SNqVOn6tFHHzXYFQAAAIAbMRoArlixQpJ06623asuWLQoPDzdZHgAAeNnAgQO1fv16p8e/8MILql+/vsGOAAAAAPwXo7sA//nnn7IsS127diX8AwDAxyxevFjTpk1zevxTTz2l1157zWBHAAAAAG6G0QAwKChIklSiRAmTZQEAgJetXr1aPXr0cHp8+fLlNXHiRDb8AgAAALzAaABYqlQpSVJMTIzJsgAAwIuio6PVuXPn9A2+MqpgwYKaO3cu4R8AAADgJUYDwKioKNm2rbVr15osCwAAvOTUqVOqWbOmEhISnBofHh6utWvXsuMvAAAA4EVGA8Bnn31WRYsW1ZIlS7R161aTpQEAgIfZtq3WrVvr+PHjTo23LEtTp05V/vz5DXcGAAAAICOMBoARERH69NNPlTdvXtWvX1+zZs1SWlqaySkAAIAH2Latvn376ocffnC6xvvvv6/HHnvMYFcAAAAAnBHozKCOHTve8Pxdd92ldevWqUOHDurXr58qVKigvHnzyuG4cd5oWZZLuwsCAAAzRo0apVmzZjk9vmvXroqKijLYEQAAAABnORUAzpgx4z8f5H35fHR0tFauXHnTtQkAAQDwrq1bt+rtt992enytWrX0xhtvGOwIAAAAgCucCgAlOb0T4I2wOyAAAN61e/dutWjRwunxd9xxh+bOnfufV/0DAAAA8BynAsDff//ddB8AAMDL4uLi1KxZMyUmJjo1PiIiQrNnzyb8AwAAADIZpwLA4sWLm+4DAAB40cWLF9W8eXOdPn3aqfEhISFavXq1SpQoYbYxAAAAAC7jK3oAAPxcWlqannnmGX3//fdO1xg3bpxKlSplsCsAAAAAphAAAgDg5yZPnqzly5c7PX7gwIFq2rSpwY4AAAAAmOT0JiCuWLp0qTZv3qyUlBTde++9atGihcLDw73RCgAAfm3lypV6/fXXnR4fFRWlF154wVxDAAAAAIwzGgDu379fffr0kXTpaoAKFSpccf7ixYuqX7++1q1bd8Xxt99+W6tWrVLJkiVNtgMAAG7gt99+U8eOHWXbtlPjy5Urp/fee89wVwAAAABMM3oL8MKFC/X5559ry5YtKl++/FXnhw0bpq+++kq2bV/x58CBA2rSpInS0tJMtgMAAK7jzJkzatasmVJSUpwaX7hwYS1fvlzZsmUz3BkAAAAA04wGgFu3bpUk1apVS8HBwVecS0pK0tixY2VZliIiIjR69Gh9+umnqlevniRpz549+vjjj022AwAAruHChQuKiorS8ePHnRofHBys2bNnK3v27IY7AwAAAOAORgPAw4cPy7Is/e9//7vq3OrVqxUfHy9JmjZtmnr27KmGDRtq2bJlKl26tCRp8eLFJtsBAADX8Oqrr2r37t1OjXU4HJo1a5buvvtuw10BAAAAcBejAWB0dLQkqUiRIled27BhgyQpd+7catKkSfrxgIAAtWzZUrZt64cffjDZDgAA+Jf3339fc+fOdXr84MGDVbNmTYMdAQAAAHA3owFgbGysJF11+68kff3117IsSzVr1pRlWVecK1WqlCTpxIkTJtsBAAD/sGbNGg0aNMjp8VFRUXrmmWcMdgQAAADAE4wGgKGhoZKkU6dOXXE8ISFBO3fulCQ9/PDDV427/AyhixcvmmwHAAD8n+PHj6tr165Oj69UqZImTpwoh8PoRwcAAAAAHmD0U/zlW3+///77K46vWrVKycnJkq4dAF6+cjBHjhwm2wEAAJL+/vtvPf744zp37pxT4/Pnz6+PPvpIAQEBhjsDAAAA4AlGA8CHHnpItm1r8eLFOnr0qCQpJSVFo0aNknTp+X/333//VeN++eUXSVKxYsVMtgMAACR1795df/31l1Njw8LCtHjxYuXLl89wVwAAAAA8xWgA2KFDB0nS2bNnde+996pFixYqX768tmzZIsuy1K5du2veOrR582ZZlqV77rnHZDsAAPg127bVv39/bd682ekas2bN0p133mmwKwAAAACeZjQAfPTRR9W1a1fZtq2YmBh9/PHH+vXXXyVduj14wIABV405dOhQ+i3D17o9GAAAOGfatGmaOnWq0+NffvllVatWzVxDAAAAALzC+JO833//fY0ZM0Z33XWXgoODFRkZqRYtWmjLli3KnTv3Va+fNGlS+s916tQx3Q4AAH7pl19+0cCBA50e36pVK/Xt29dgRwAAAAC8xbJt2/ZmAydOnFBSUpIsy+IZgG4WHR3t7RaMiYyMVEBAgFJTU9M3kQFcERAQoMjISMXGxio1NdXb7SCL8/YadeDAAT322GNOb/pRtmxZrVmzRsHBwYY7g7NYo2CSt9co+B7WKJjGOgWTfHGNyps3b4bHBLqhjwwpUKCAt1sAAMBn2Lat9u3bOx3+5cuXTwsXLiT8AwAAAHyI8VuAAQCAd6Smpqp9+/bat2+fU+MDAwO1YsUKvpwDAAAAfAwBIAAAPmLYsGFauXKl0+PHjBmjkiVLGuwIAAAAQGbg1C3As2bNSv+5Xbt21zzurH/WAwAAN2fLli2aMGGC0+MHDRqk5s2bG+wIAAAAQGbh1CYgDodDlmXJsiylpKRcddzpZv5VD2axCQhwfb74YFh4j6fXqB9++EENGjTQxYsXnRpfq1YtzZ8/33BXMIk1CibxOQqmsUbBNNYpmOSLa5RHNwG5Xm7o5U2FAQDwKxcvXlTr1q2dDv9uu+02TZkyxXBXAAAAADITpwLA6dOnZ+g4AAAw7+LFi4qKitKpU6ecGp8jRw6tXr1a2bNnN9wZAAAAgMzEqQDw8m2+NWrUuOJ4+/btXe8IbhMQEODtFtzCV38veNbl9xHvJ5jmzvdUv379tG3bNqfGWpalGTNmKCIiwnBXcAfWKLgL7ymYwBoFd+J9BVexRl3i0jMAly5dqoYNG6Yf79ixoyTphRde0L333musSQAAcKWFCxeqRYsWTo9ftGiRnnrqKYMdAQAAAMisnH4G4LXMmDFDlmWpcePGBICZkC89PDVnzpzpD4WNj4/3djvwAQEBAcqZM6fi4+N95sGw8B53r1FbtmxRmzZtnB7foUMH1apVy6f+veDrWKNgEp+jYBprFExjnYJJvrhGRUZGZniMUwFgYGCgUlNTlZSU5MxweImvvNH/zVd/L3hHamoq7ykYZfr9dObMGbVu3VopKSlOjX/wwQc1dOhQ3udZFGsUTOP9BJNYo+AOvKdgir+vUQ5nBuXOnVuS9OuvvxptBgAAXF9iYqKioqJ09uxZp8YXLlxYS5cuVXBwsOHOAAAAAGRmTl0BeN9992nVqlUaP368br/9dt13330KDQ1NP3/y5EkdPnzYqYaKFSvm1DgAAHyZbdvq3r27du/e7dT4oKAgzZgxQ0FBQYY7AwAAAJDZORUAdujQQatWrdLp06fVqlWrK87Ztq1u3bo51YxlWU7f0gQAgC+bMWOGPv/8c6fGOhwOLVq0iOfzAgAAAH7KqVuAmzVrph49esi27Sv+XPbv4xn5AwAArrRhwwa98sorTo/v06ePHn30UYMdAQAAAMhKnN4FeMKECercubNWrFihI0eOKCkpSTNnzpRlWapWrRq38gIAYMDhw4fVrl07paWlOTX+8ccfV58+fQx3BQAAACArcToAlKR77733ituJZs6cKUnq2bOnGjZs6FJjAAD4u6SkJLVt21YJCQlOjS9btqxmzpwph8OpC/4BAAAA+Aj+iwAAgEwoJSVFHTp00M8//+zU+PDwcE2dOpXwDwAAAIBrVwD+2/r16yVJ5cqVM1kWAAC/8/7772vNmjVOjQ0ICNCSJUt02223Ge4KAAAAQFZkNACsWrWqyXIAAPilDRs2aOjQoU6PHzp0qB544AGDHQEAAADIyrgvCACATOTXX39V27Ztnd7048knn1SnTp0MdwUAAAAgKyMABAAgk0hOTlbnzp2VmJjo1PgKFSpo4sSJsizLcGcAAAAAsjICQAAAMoGUlBS1adNGv/32m1Pjc+XKpSlTprDpBwAAAICr8F8JAABkAmPGjNG6deucGhsUFKSPP/5YRYoUMdwVAAAAAF9AAAgAgJdt2bJFI0eOdHr82LFjde+995prCAAAAIBPIQAEAMCL9uzZoxYtWji96Ufr1q31/9q77/io6vz742cy6QFCIqFIiYHFgiIqouAiREVRAjYUpVlBwRUEBAsoSBVhQTpYQNalWAAXEQu4u0REECwsIigkUo0IITF10mbm9we/5AuSQOZyJ5O583o+Hj6c5N73nTMxfkgOd+695557TE4FAAAAwEooAAEA8BGXy6XHH39chYWFhub/+te/avr06dz0AwAAAMAZUQACAOADTqdTvXv31t69ew3Nx8bGauHChdz0AwAAAMBZ8VsDAAA+MHXqVH3++eeGZkNDQ/XOO+/ovPPOMzkVAAAAACuiAAQAoIpt27ZNr776quH51157TVdeeaWJiQAAAABYGQUgAABVaNeuXbr77rsN3/SjT58+6tq1q8mpAAAAAFgZBSAAAFXE7XbrkUceUUFBgaH59u3ba+rUqSanAgAAAGB1FIAAAFQBl8ulfv36KTU11dB8TEyMlixZouDgYJOTAQAAALA6CkAAAKrA1KlT9eGHHxqaDQkJ0bJlyxQVFWVyKgAAAACBgAIQAAAv27lzp6ZPn254fvHixbr66qtNTAQAAAAgkFAAAgDgRampqerWrds53fTjlltuMTkVAAAAgEBCAQgAgJe4XC716dNHubm5huavvfZavfLKKyanAgAAABBouJI4AABe4Ha7NXDgQKWkpBiaP++88/TBBx8oJCTE5GQAAAAAAg1nAAIA4AVTpkzRwoULDc3a7XYtWrSI8g8AAACAKSgAAQAw2e7duzVy5EjD82+99Zauu+46ExMBAAAACGQUgAAAmOjIkSO64YYbzummH7fddpvJqQAAAAAEMgpAAABMUlxcrF69eik9Pd3QfKtWrTRp0iSTUwEAAAAIdNwEBAAAk7z88sv64YcfDM3WqVNHa9euVVhYmMmpAAAAAAQ6zgAEAMAEy5cv1+zZsw3N2mw2zZ8/n/IPAAAAgFdQAAIAcI5SU1M1dOhQw/Nz5sxRYmKieYEAAAAA4CQUgAAAnIPc3Fzdd999cjqdhuZ79uypHj16mJwKAAAAAP4PBSAAAAYVFxerb9++OnDggKH55s2bc9MPAAAAAF5HAQgAgEHz58/Xl19+aWg2NjZWn376qWrUqGFyKgAAAAA4FQUgAAAGJCcna+LEiYbnZ8+erVq1apmYCAAAAADKRwEIAICHUlNT1bdvX7lcLkPzY8eO1S233GJyKgAAAAAoHwUgAAAecLlcGjBggBwOh6H5O++8U0888YTJqQAAAACgYhSAAABUktvt1hNPPKHt27cbmm/UqJFefvllc0MBAAAAwFlQAAIAUElLlizRypUrDc1GRUXpww8/VJ06dUxOBQAAAABnRgEIAEAlpKSk6LnnnjM8P2/ePDVu3NjERAAAAABQORSAAACcRVpamrp27aqioiJD848//ri6dOlicioAAAAAqBwKQAAAzuLpp5/W8ePHDc3ecMMNGj9+vMmJAAAAAKDyKAABADiDadOm6fPPPzc0e95552nWrFmy2WwmpwIAAACAyqMABACgAv/61780efJkQ7MhISH66KOPVL9+fZNTAQAAAIBnKAABAChHTk6Ohg8fbnj+9ddfV5s2bUxMBAAAAADGUAACAPAnubm56ty5s7KysgzN33XXXXrwwQdNTgUAAAAAxlAAAgDwJ88995z27t1raPbSSy/VP//5T677BwAAAKDaoAAEAOAka9eu1bvvvmtoNiwsTO+8847Cw8NNTgUAAAAAxlEAAgDw/23ZskX9+vUzNGuz2TR//nxu+gEAAACg2qEABABAktPp1OOPP66SkhJD86NGjVK3bt1MTgUAAAAA544CEAAQ8JxOp/r27au0tDRD861bt9agQYNMTgUAAAAA5qAABAAEvEmTJmn9+vWGZuvWrau3335bQUH8kQoAAACgeuK3FQBAQNu1a5fmzJljaDYoKEhr165V3bp1TU4FAAAAAOahAAQABKxDhw7p9ttvl8vlMjQ/atQoXXDBBeaGAgAAAACTUQACAAKSy+XSAw88oKysLEPzPXv25Lp/AAAAAPwCBSAAICBNmTJFO3fuNDSbkJCgmTNnymazmZwKAAAAAMxHAQgACDjvv/++pk2bZmg2PDxcixcvpvwDAAAA4DcoAAEAAeXo0aMaMmSIoVmbzaZ3331XLVq0MDcUAAAAAHgRBSAAIGAUFBTonnvuUVFRkaH5hx56SNddd53JqQAAAADAuygAAQABwe12a8CAAdq9e7eh+auuukrjx483ORUAAAAAeF+wrwMAAFAVVq9erbVr1xqarVOnjtasWaPQ0FCTUwEAAACA93EGIADA8nbu3Km//e1vhudnzJhB+QcAAADAb1EAAgAs7Y8//tD9999v+Lp/L7/8sjp37mxyKgAAAACoOhSAAABLe/755/X7778bmr3tttvUr18/kxMBAAAAQNWiAAQAWNb8+fO1YsUKQ7N169bV1KlTTU4EAAAAAFWPAhAAYEnffPONRo8ebWg2LCxMn332merVq2dyKgAAAACoehSAAADLycvLO6e37o4bN06NGjUyMREAAAAA+A4FIADAUoqKitSzZ0/9+uuvhubvvvtuPfzwwyanAgAAAADfoQAEAFjKggULtHnzZkOzl112mebPny+bzWZyKgAAAADwHQpAAIBlfP/995o0aZKh2ZCQEM2aNUtBQfzRCAAAAMBa+C0HAGAJ+/btU/fu3eV0Oj2etdlsWrRokVq2bOmFZAAAAADgWxSAAABLeOaZZ5STk2NoduDAgbr11ltNTgQAAAAA1QMFIADA702ePFkbNmwwNHvJJZdoxIgR5gYCAAAAgGqEAhAA4Nc+/PBDTZs2zdBs7dq1tWLFCtWoUcPkVAAAAABQfVAAAgD8Vn5+/jmdvffGG2+obt26JiYCAAAAgOqHAhAA4JccDoeSkpKUkZFhaH7AgAFKTEw0NxQAAAAAVEMUgAAAvzRhwgTt3LnT0GxiYqLGjRtnciIAAAAAqJ6CfR2gqmVlZWnFihXaunWrjh8/rrCwMDVr1kxdunRR27ZtDR+3pKREH330kZKTk5WWliZJatiwoTp27KikpCQFB5f/pZ4xY4b+85//nPHYTZo00Zw5cwxnAwCr2bp1q9544w1DszVq1NCcOXNks9lMTgUAAAAA1VNAFYAHDx7UqFGjlJWVJUmKiIhQXl6etm/fru3bt6tbt27q37+/x8d1OBx68cUXtWfPHklSaGioJCklJUUpKSnatGmTxo0bp/Dw8AqPERoaqsjIyHK31apVy+NMAGBVP/30k+655x653W6PZ4OCgvSPf/xD9erV80IyAAAAAKieAqYALC4u1oQJE5SVlaX4+HgNGzZMCQkJKiws1OrVq7V06VKtWbNGCQkJ6tSpk0fHnjdvnvbs2aOoqCgNHjy47EzCLVu2aNasWfrpp580f/58DR06tMJjtG/fXkOGDDmXlwgAAeHJJ5+Uw+EwNDtu3Dh16NDB5EQAAAAAUL0FzDUAP/vsMx05ckRhYWEaPXq0EhISJElhYWHq0aOHbrvtNknSkiVLVFJSUunj7tu3T1988YUkadCgQWrXrp1sNptsNpvatWunJ598UpK0YcMGHThwwORXBQCBZezYsfrf//5naPbqq6/Wo48+anIiAAAAAKj+AqYA3LBhgySpQ4cOiouLO2179+7dZbPZlJGRoR9++KHSx01OTpbb7VaDBg3Url2707Zfd911atCggdxut5KTkw3nB4BAt2zZMsPXQ61bt67++c9/Vng9VgAAAACwsoAoAB0Oh/bu3StJuuqqq8rdJy4uTo0aNZIkj84u2bFjhyTpyiuvLPeC8jabTVdeeeUp+wIAPJObm6uRI0canl+1apXq1KljYiIAAAAA8B8BcSrE4cOHyy4WHx8fX+F+8fHxOnTokA4dOlSp47rdbh0+fPisx23SpIkknfG4O3bs0OOPP65jx44pNDRUDRo0UOvWrZWUlKSYmJhK5QEAK3I4HEpKSlJeXp6h+aFDh+qiiy4yORUAAAAA+I+AKAAzMjLKHsfGxla4X+m2zMzMSh3X4XCooKCg0sd1OBxyOByKiIg4bZ/09HTZ7XZFREQoPz9fqampSk1N1SeffKJnnnlGrVq1OmueJUuWaNmyZRVu79mzp3r16nXW4/iDoKCgsn9TkMIMpWfwRkdHG7q7LLxn2LBh2rVrl6HZO+64Q1OmTCn3DG1vYo2C2VijYCbWKJiNNQpmY52CmVijTgiIArC0pJNO3PSjIqXbKnt3yZP3q8xxS2dOLgCbNWumCy+8UG3atNF5552noKAg5efna+vWrVq8eLEyMjI0adIkTZ8+XQ0bNjxjnry8PB09erTC7fn5+bLb7ZV5aX7DZrNZ7jXBt0p/2ED18MUXX+if//ynodk6dero3Xff9el1/1ijYDbWKJiJNQpmY42C2VinYKZAX6MCogCszrp163ba5yIjI5WYmKgWLVpoyJAhys3N1fLlyzV8+PAzHisqKkp169atcHtkZKScTuc5Z64OgoKCZLPZ5Ha75XK5fB0HFmCz2RQUFCSXyxXQfytUnfz8889ld2j3lN1u1/LlyxUcHOyTdY81CmZjjYKZWKNgNtYomI11Cmay4hplpBgPiAIwPDy87HFhYaEiIyPL3a+wsFCSyn2LbnlO3q909kzH9eTY0om7ViYlJendd9/VN998I5fLdcbGuk+fPurTp0+F29PT0yv99ubqLiYmRna7XS6XyzKvCb5lt9sVExOjrKwsyxTl/szpdOr2229Xfn6+ofmZM2fqiiuu8Nn6wBoFs7FGwUysUTAbaxTMxjoFM1lxjTJyg8OAOP/x5OvznXw9wD8r3VbZawxERESUFXqVOe7J+1fWhRdeKOnE23dzcnI8mgUAf/Xyyy8rNTXV0GxiYqLuu+8+kxMBAAAAgP8KiAKwUaNGZRd9PHjwYIX7lW5r3LhxpY5rs9nUqFEj048LAIFsxYoVmjlzpqHZevXqaf78+SYnAgAAAAD/FhAFYEREhJo3by5J+u6778rdJz09XYcOHZKkSt1xt9Tll18uSfr+++8r3Gf79u2n7OuJPXv2SDrxGmrWrOnxPAD4k6NHj2rIkCGGZkNCQrRu3TpDp8MDAAAAgJUFRAEonXhLmHTijpLHjh07bfuqVavkdrsVGxurli1bVvq4HTp0kM1mU1pamjZv3nza9q+++kppaWmy2WxlGUqd7eKTx44d08cffyxJuvrqqwP+jjUArK2kpER9+/Y94zVVz+Tpp5/W+eefb3IqAAAAAPB/AdMode7cWfXr11dBQYHGjx+vffv2STpxg44VK1Zo7dq1kk7cSCM4+NR7o/Tr10+33367ZsyYcdpxExIS1KFDB0nS7NmztWXLFrndbrndbm3ZskVz5syRdKKAbNKkySmzGzZs0Msvv6wtW7YoOzu77PMOh0PJycl69tlnlZOTo4iICPXs2dO0rwUAVEdPP/10hWdpn02XLl00dOhQkxMBAAAAgDUExF2ApRNvDXvhhRc0atQo7d+/X0899ZQiIyNVUFBQdlvxrl27qlOnTh4f+4knntBvv/2mPXv2aNKkSQoNDZUkFRUVSZIuvvhiDRw48LQ5l8ulzZs3l505GBERoeDgYOXl5ZVlio6O1ogRI8quNQgAVpScnKxly5YZmm3SpIneeustzpIGAAAAgAoETAEonfglcfbs2Vq5cqW2bt2q9PR0RUVFqWnTpkpKSlLbtm0NHTciIkKTJ0/WRx99pOTkZKWlpUmSmjVrpsTERCUlJZ12VqEktWzZUn369NHu3bv166+/Kjs7W/n5+YqKilLjxo119dVXq3Pnzlz7D4Cl/fbbb3rkkUcMzQYFBWnGjBmUfwAAAABwBjb32S5EB8tIT0/3dQTTxMTEyG63y+l0KjMz09dxYAF2u10xMTHKzMyU0+n0dZyAkZ+fr1tvvVW7d+82ND9r1qxqeYkE1iiYjTUKZmKNgtlYo2A21imYyYprlJEbH3LKBADAZ2bPnm24/OvWrVu1LP8AAAAAoLqhAAQA+MSGDRs0bdo0Q7NxcXGaNGmSyYkAAAAAwJooAAEAVW7fvn164IEHZOQqFKGhofrkk09Uv359LyQDAAAAAOuhAAQAVLkRI0bI4XAYmh05cqTi4+NNTgQAAAAA1kUBCACoUpMmTVJycrKh2RtvvFEDBgwwOREAAAAAWBsFIACgyqxfv16vvvqqodn4+HgtXbpUdrvd5FQAAAAAYG0UgACAKuFwODRs2DDD8zNmzFBwcLCJiQAAAAAgMFAAAgC8rrCwUN27d9eRI0cMzU+cOFHt27c3ORUAAAAABAYKQACA182dO1fbtm0zNNutWzc99thjJicCAAAAgMBBAQgA8Kqff/5ZU6dONTQbGxurCRMmmJwIAAAAAAILBSAAwGt+/fVXdevWTSUlJR7PBgcH691339X555/vhWQAAAAAEDgoAAEAXjNy5EhlZmYamh0zZoyuuOIKcwMBAAAAQACiAAQAeMWyZcv08ccfG5pt06aNHnnkEZMTAQAAAEBgogAEAJhu48aNGjp0qKHZuLg4LVu2TKGhoSanAgAAAIDARAEIADCVy+XSsGHD5HK5DM0vXrxYtWvXNjcUAAAAAAQwCkAAgGncbrcGDBig/fv3G5ofMGCArrnmGnNDAQAAAECAowAEAJhm3rx5+uCDDwzNXn/99Ro3bpzJiQAAAAAAFIAAAFNkZmZq8uTJhmYjIiL02muvyWazmZwKAAAAAEABCAA4Z7m5ubr11ltVUFDg8azNZtO8efMUFxfnhWQAAAAAAApAAMA5Gz58uH755RfDs127djU5EQAAAACgFAUgAOCcbN68WStXrjQ027RpUw0bNszkRAAAAACAk1EAAgAMS0lJ0f33329oNjIyUsuWLVNwcLDJqQAAAAAAJ6MABAAY4na79cgjjyg/P9/Q/JIlS9SsWTOTUwEAAAAA/owCEABgyKxZs7R7925Ds7fffruuv/56kxMBAAAAAMpDAQgA8Ninn36qiRMnGppt2rSpZs6caXIiAAAAAEBFKAABAB7Jzc3VE088Ibfb7fFsSEiI1q5dqxo1anghGQAAAACgPBSAAIBKc7vdevzxx5WTk2No/vnnn1edOnVMTgUAAAAAOBMKQABApU2ZMkXr1q0zNHvXXXfpySefNDkRAAAAAOBsKAABAJWSkpKiadOmGZpt2LChFixYIJvNZnIqAAAAAMDZUAACAM4qLy9P999/v6Hr/gUFBWnGjBkKCuKPHAAAAADwBX4bAwCckcvlUv/+/XXgwAFD81OnTlViYqK5oQAAAAAAlUYBCAA4o7Vr12r9+vWGZm+44QY98MADJicCAAAAAHiCAhAAUKEDBw4YvnFHdHS0pk6danIiAAAAAICnKAABAOXKzc1Vjx49lJ+f7/FsUFCQPvzwQ8XHx3shGQAAAADAExSAAIByzZo1S7/88ouh2QEDBqhFixYmJwIAAAAAGEEBCAA4zRdffKEZM2YYmm3RooWeffZZcwMBAAAAAAyjAAQAnGL//v3q27ev3G63x7PR0dFau3atIiMjvZAMAAAAAGAEBSAA4BQvvPCCoev+SdLYsWNVo0YNkxMBAAAAAM4FBSAAoMy8efP02WefGZq9//771atXL5MTAQAAAADOFQUgAECS9OWXX2rMmDGGZi+99FLNmjVLNpvN5FQAAAAAgHNFAQgAkMvl0ogRIwzN2mw2TZkyhfIPAAAAAKopCkAACHAul0v9+vVTSkqKofnp06frmmuuMTkVAAAAAMAsFIAAEODefvttrVmzxtDsXXfdpT59+picCAAAAABgJgpAAAhgOTk5GjdunKHZ2rVrG75mIAAAAACg6lAAAkCAysvL02233aacnByPZ+12u9555x01bNjQC8kAAAAAAGaiAASAAPXyyy/r559/NjT7/PPPq3Xr1iYnAgAAAAB4AwUgAASgXbt26Y033jA026JFC/Xv39/kRAAAAAAAb6EABIAAc+jQId1+++1yuVwez9asWVPvvvuuIiMjvZAMAAAAAOANFIAAEGCeffZZZWVlGZpdsGCB6tevb3IiAAAAAIA3UQACQABZsWKF1q9fb2i2W7duuvnmm01OBAAAAADwNgpAAAgQX3/9tQYNGmRo9i9/+YvmzZsnm81mcioAAAAAgLdRAAJAAHC73XrqqadUUlJiaH7JkiUKDw83ORUAAAAAoCpQAAJAABg9erRSU1MNzT733HNq1qyZyYkAAAAAAFWFAhAALO6dd97RggULDM3edtttGjZsmMmJAAAAAABViQIQACzM4XBo5MiRhmZr1KihuXPnct0/AAAAAPBzFIAAYFEul0u9evVSTk6Ox7M2m01z5sxRzZo1vZAMAAAAAFCVKAABwKImTJigL7/80tDs8OHDlZSUZHIiAAAAAIAvUAACgAUdPnxYc+fONTTbtGlTDR8+3OREAAAAAABfoQAEAIvJzc3VnXfeKZfL5fFsWFiYFi1apKAg/ngAAAAAAKvgNzwAsJiBAwfqwIEDhmYXLlyoSy+91OREAAAAAABfogAEAAvZuHGjPv30U0OzN954ozp37mxyIgAAAACAr1EAAoBF/Prrr3rwwQcNzcbFxWnOnDkmJwIAAAAAVAcUgABgAcXFxerVq5dycnI8nrXb7froo48UFxfnhWQAAAAAAF+jAAQAC/jHP/6hXbt2GZp9+OGH1bRpU5MTAQAAAACqCwpAAPBz3333nV588UVDs5dffrleeuklcwMBAAAAAKoVCkAA8GOZmZnq3bu3SkpKPJ6tWbOm1qxZo7CwMC8kAwAAAABUFxSAAODHJk+erPT0dEOzzz//vCIjI01OBAAAAACobigAAcBPffjhh1q0aJGh2e7du6tfv34mJwIAAAAAVEcUgADgh1JTUzVw4EBDs02bNtX8+fNls9lMTgUAAAAAqI4oAAHADz3//PMqKiryeM5ms2nixImUfwAAAAAQQCgAAcDPzJgxQ//9738NzY4ZM0adOnUyOREAAAAAoDqjAAQAP7Jp0yZNnDjR0GzHjh31t7/9zeREAAAAAIDqjgIQAPyEy+XSM888Y2g2PDxc48aNMzkRAAAAAMAfUAACgB9wu90aOHCg9uzZY2h+8eLFatGihcmpAAAAAAD+gAIQAPzAe++9p1WrVhmaffDBB3XTTTeZnAgAAAAA4C8oAAGgmsvPz9fo0aMNzdarV08jRowwOREAAAAAwJ9QAAJANVZYWKi77rpLGRkZHs8GBwdr1apVqlevnheSAQAAAAD8BQUgAFRjc+bM0XfffWdoduTIkbrwwgtNTgQAAAAA8DcUgABQTaWlpWn69OmGZi+//HI9+uijJicCAAAAAPgjCkAAqIYyMjLUpUsXFRUVeTxbq1Ytvffee4qMjPRCMgAAAACAvwn2dQBUHbvd7usIXmHV14WqVfp9VF2+nyZOnKhff/3V0OysWbNUt25dkxPBqOryPQX/Vt3WKFgH31MwA2sUvInvK5wr1qgTbG632+3rEACA//P111+rXbt2MrI833HHHVq1apWCgjjBGwAAAABwAgVgAMnMzPR1BNPUqlVLdrtdTqdT2dnZvo4DC7Db7apVq5ays7PldDp9luOXX35RYmKicnNzPZ694IIL9NVXXyk8PNwLyeAJ1iiYrbqsUbAG1iiYjTUKZmOdgpmsuEbFxMR4PMNbgAOIVb7R/8yqrwu+4XQ6ffo9NXz4cEPlnyS98cYbCgkJ4f+Jaob/HjCTr9coWA/fTzATaxS8ge8pmCXQ1yjeIwYA1cSKFSu0YcMGQ7MDBw7UFVdcYWoeAAAAAIA1UAACQDWwbds2DRo0yNBsu3btNHbsWJMTAQAAAACsggIQAHzM7XZryJAhKikp8Xg2ODhYCxYskM1m80IyAAAAAIAVUAACgI+98sor2rNnj6HZSZMm6fzzzzc5EQAAAADASigAAcCH1qxZo2nTphma7dmzpx5++GGTEwEAAAAArIYCEAB8pLCwUMOHDzc0Gx0drZdfftnkRAAAAAAAK6IABAAfcLvdGjx4sDIyMjyetdlsmj9/vqKioryQDAAAAABgNRSAAOADr732mlatWmVoduTIkbr55ptNTgQAAAAAsCoKQACoYsePH9e4ceMMzSYkJGjw4MEmJwIAAAAAWBkFIABUIafTqQceeEDFxcUez4aGhmrhwoUKCmLpBgAAAABUHr9FAkAVGj16tLZu3WpodsGCBWrZsqXJiQAAAAAAVkcBCABVJCUlRa+//rqh2b/+9a/q1q2byYkAAAAAAIGAAhAAqoDD4VCvXr0MzUZHR2vu3LkmJwIAAAAABAoKQADwMrfbrYEDB2rfvn0ez9psNq1cuVINGzb0QjIAAAAAQCCgAAQAL9u4caPWrl1raLZ79+5q1aqVyYkAAAAAAIGEAhAAvCgjI0P9+/c3NNu4cWO98sorJicCAAAAAAQaCkAA8JLi4mL16dNHGRkZHs+GhITok08+Ua1atbyQDAAAAAAQSCgAAcBLVq5cqW3bthmaHThwoOrVq2dyIgAAAABAIKIABAAvOHTokJ555hlDs1dddZWeffZZkxMBAAAAAAIVBSAAmCw3N1f33HOPHA6Hx7PR0dFavXq1QkNDvZAMAAAAABCIKAABwGSvv/66fvnlF0Ozzz33nMLDw01OBAAAAAAIZBSAAGCiH374QVOmTDE0261bNz366KMmJwIAAAAABDoKQAAwyZEjR3TvvffK6XR6PBsfH6+FCxfKZrN5IRkAAAAAIJBRAAKASaZNm6bjx48bmh07dizlHwAAAADAKygAAcAEGzZs0OLFiw3NDho0SElJSeYGAgAAAADg/6MABIBztHfvXj3wwAOGZq+66iqNHj3a5EQAAAAAAPwfCkAAOEfjx4+Xw+HweC4oKEgTJkzwQiIAAAAAAP4PBSAAnINly5bpk08+MTQ7depUtWnTxuREAAAAAACcigIQAAz6+uuvNWzYMEOzt912m+G3DQMAAAAA4AkKQAAwaMyYMXI6nR7PhYeHa8yYMV5IBAAAAADA6SgAAcCAqVOn6ttvv/V4zmazaeHChWrWrJkXUgEAAAAAcDoKQADw0CeffKIpU6YYmn3ooYd0yy23mJwIAAAAAICKUQACgAfcbrdefPFFQ7OxsbEaMWKEyYkAAAAAADgzCkAA8MDQoUN14MABj+fsdruWLl2quLg4L6QCAAAAAKBiFIAAUElvv/22li5damj2ueee09VXX21yIgAAAAAAzo4CEAAqoaioSBMmTDA0Gx8fr8cee8zkRAAAAAAAVA4FIACchcvlUt++fZWZmenxbFhYmJYvX67IyEgvJAMAAAAA4OwoAAHgLKZPn67//Oc/hmanTZum5s2bm5wIAAAAAIDKowAEgDPIzs7WjBkzDM1efvnluueee8wNBAAAAACAhygAAaACxcXFuuuuu1RYWOjxbHR0tJYsWSK73e6FZAAAAAAAVB4FIABU4IUXXtCOHTsMzS5evFgNGjQwOREAAAAAAJ6jAASAchw8eFCLFy82NHvDDTeoffv25gYCAAAAAMAgCkAA+JO8vDzdfffdcrlcHs82aNBAb7zxhhdSAQAAAABgDAUgAPzJ4MGDdeDAAUOz7733nqKjo01OBAAAAACAcRSAAHCS77//Xh9++KGh2fvuu08XX3yxyYkAAAAAADg3FIAA8P8dP35c999/v6HZ5s2b6+9//7vJiQAAAAAAOHcUgAAgye12q3v37jp27JjHs8HBwVq9erXCw8O9kAwAAAAAgHNDAQgAktatW6fk5GRDswMGDFBcXJzJiQAAAAAAMAcFIICA99tvv+mxxx4zNHvNNddo1KhRJicCAAAAAMA8FIAAAlpRUZF69uypnJwcj2dr1Kih999/X8HBwV5IBgAAAACAOSgAAQS09957Tz/++KOh2REjRigyMtLkRAAAAAAAmIsCEEDASk1N1XPPPWdoNikpSQMHDjQ5EQAAAAAA5qMABBCQcnNzdd9996mwsNDj2bp162rhwoWy2WxeSAYAAAAAgLkoAAEEpDfeeEMHDhwwNDt69GjZ7XaTEwEAAAAA4B0UgAACzg8//KBXXnnF0Oyjjz6q++67z+REAAAAAAB4DwUggIBy7Ngx9ejRQ06n0+PZCy+8UJMnT/ZCKgAAAAAAvIcCEEBAmTVrltLT0w3NvvTSS+aGAQAAAACgClAAAggYX331lV577TVDs6NGjdLNN99sciIAAAAAALyPAhBAQDhw4IB69+4tt9vt8ey1116rIUOGmB8KAAAAAIAqQAEIICC88sorys3N9XjObrdrzJgxXkgEAAAAAEDVoAAEYHmffPKJ3n//fUOz06dPV5s2bUxOBAAAAABA1aEABGBpP/74o/r3729o9tZbb1WvXr1MTgQAAAAAQNWiAARgaRMmTFBhYaHHc+Hh4Ro1apQXEgEAAAAAULUoAAFY1tKlS/X5558bmn3zzTd18cUXm5wIAAAAAICqRwEIwJK2bNmip59+2tBs79691blzZ5MTAQAAAADgGxSAACxp7NixcjqdHs/VqlVLI0aM8EIiAAAAAAB8gwIQgOXMnDlT33zzjcdzQUFBWr58uRo2bOiFVAAAAAAA+AYFIABLWb9+vSZMmGBodvjw4WrXrp3JiQAAAAAA8C0KQACW4Xa7NXr0aEOzdevW1TPPPGNyIgAAAAAAfI8CEIBljB49WikpKR7PBQcH691339V5553nhVQAAAAAAPgWBSAAS1i5cqUWLFhgaHbUqFFq1aqVyYkAAAAAAKgeKAAB+D2n06kxY8YYmo2Pj9cjjzxiciIAAAAAAKoPCkAAfm/w4MH6/fffPZ4LCwvT8uXLFRkZ6YVUAAAAAABUDxSAAPzaW2+9pffee8/Q7N///nc1b97c5EQAAAAAAFQvFIAA/JbD4dD48eMNzbZo0UL33nuvyYkAAAAAAKh+KAAB+CW3261+/fopJyfH49kaNWpoyZIlstvtXkgGAAAAAED1QgEIwC/NnDlT69atMzS7YMECNW7c2OREAAAAAABUTxSAAPxOZmampk6damj22muv1S233GJyIgAAAAAAqi8KQAB+xeVy6cEHH1RRUZHHs7GxsVq0aJFsNpsXkgEAAAAAUD1RAALwKxMmTNDmzZsNzS5btkx169Y1OREAAAAAANVbsK8DVLWsrCytWLFCW7du1fHjxxUWFqZmzZqpS5cuatu2reHjlpSU6KOPPlJycrLS0tIkSQ0bNlTHjh2VlJSk4OAzf6l/+eUXffDBB/rhhx+UnZ2t6OhoXXbZZbr77ruVkJBgOBdgJYcPH9bcuXMNzXbu3FmtW7c2OREAAAAAANVfQBWABw8e1KhRo5SVlSVJioiIUF5enrZv367t27erW7du6t+/v8fHdTgcevHFF7Vnzx5JUmhoqCQpJSVFKSkp2rRpk8aNG6fw8PBy55OTkzVz5kyVlJRIkqKionT8+HElJydr06ZNGjp0qK6//nojLxmwjJKSEj3wwANyuVwez9avX19z5szxQioAAAAAAKq/gCkAi4uLNWHCBGVlZSk+Pl7Dhg1TQkKCCgsLtXr1ai1dulRr1qxRQkKCOnXq5NGx582bpz179igqKkqDBw8uO5Nwy5YtmjVrln766SfNnz9fQ4cOPW324MGDZeVf+/bt1a9fP8XGxiojI0NvvPGGNm3apBkzZighIUGNGjUy5Wvhr9xut7799lu9/fb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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(UM1_2o_pol, aes(x='bms', y='fishing_intensity', color='mwt')) + geom_point(),\n", + " ggplot(UM1_mw_pol, aes(x='mwt', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM1_bm_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "id": "b10bdde3-d136-42e1-be73-aaf61f9998ce", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(UM1_cr_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM1_esc_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM1_msy_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "5990c1bd-4fd9-4e30-ae9a-24811753da52", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## UM2" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "32491ab0-994a-430a-89ce-abb35f8a7c81", + "metadata": {}, + "outputs": [], + "source": [ + "bms_obs_list = np.linspace(-1, -1+0.14, 500)\n", + "mwt_obs_list_short = [-0.5, 0, 0.3, 0.5, 0.7, 0.9]\n", + "mwt_obs_list = np.linspace(-1,1,500)\n", + "\n", + "\n", + "UM2_2o_pol = pd.DataFrame(get_2obs_policy(\n", + " bms_obs_list, mwt_obs_list_short, \n", + " agent = PPO_2o_UM2, \n", + " asm_env = AsmEnv(config=CFG_UM2_2o),\n", + ")) \n", + "\n", + "UM2_mw_pol = pd.DataFrame(get_mwt_policy(\n", + " mwt_obs_list, \n", + " agent = PPO_mw_UM2, \n", + " asm_env = AsmEnv(config=CFG_UM2_mw),\n", + ")) \n", + "\n", + "UM2_bm_pol = pd.DataFrame(get_bms_policy(\n", + " bms_obs_list, \n", + " agent = PPO_bm_UM2, \n", + " asm_env = AsmEnv(config=CFG_UM2_bm),\n", + ")) " + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "2ae07d61-e26e-43b5-9f90-c4d48e9764d0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(UM2_2o_pol, aes(x='bms', y='fishing_intensity', color='mwt')) + geom_point(),\n", + " ggplot(UM2_mw_pol, aes(x='mwt', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM2_bm_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "301de3bb-95d1-4cc1-a53b-90bc49ebd970", + "metadata": {}, + "outputs": [], + "source": [ + "UM2_cr_pol = pd.DataFrame(\n", + " get_bms_policy(\n", + " bms_obs_list,\n", + " agent = CautionaryRule(\n", + " env = AsmEnv(config=CFG_UM2_bm),\n", + " **(from_radius_theta(*cr_UM2.x)), \n", + " ),\n", + " asm_env = AsmEnv(config=CFG_UM2_bm),\n", + " )\n", + ")\n", + "\n", + "UM2_esc_pol = pd.DataFrame(\n", + " get_bms_policy(\n", + " bms_obs_list, \n", + " agent = ConstEsc(\n", + " env = AsmEnv(config=CFG_UM2_bm), escapement=esc_UM2.x[0]\n", + " ),\n", + " asm_env = AsmEnv(config=CFG_UM2_bm),\n", + " )\n", + ") \n", + "\n", + "UM2_msy_pol = pd.DataFrame(get_bms_policy(\n", + " bms_obs_list, \n", + " agent = Msy(\n", + " env = AsmEnv(config=CFG_UM2_bm), mortality=msy_UM2.x[0]\n", + " ), \n", + " asm_env = AsmEnv(config=CFG_UM2_bm),\n", + ")) " + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "202d8c08-0fbf-461b-a3c0-2562bbad8d1d", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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uWAAKAApAAAAAAIDHyc7O1rp16zR//nytWLFC+/fvV1pamrtj5Qs/Pz+FhYWpZs2aatasmVq0aKE6deqoSJEi7o4GoICiAAQAAAAAuFVGRoZiY2P1448/6rffftOWLVt85r59DodDlSpVUtWqVdWmTRs1btxYNWvWlJ+fn7ujAfAiFIAAAAAAgHx17NgxrVu3Tt9//722bt2qgwcP+sQTecPDw1WmTBm1aNFCrVu3VvPmzRUaGuruWAB8AAUgAAAAAMA2WVlZ2rJlixYvXqyff/5Zhw4dUlJSkrtj2cowDEVGRqpWrVq6/vrrddNNN6lGjRo8gReA21AAAgAAAAAsc+bMGS1evFgLFy7UqlWrFBcXp8zMTHfHso3D4VDx4sVVp04dtW3bVu3atePBHAA8DgUgAAAAAMBle/bs0cKFC/X9999r586dSk1NdXck2/j5+alixYo5T+G94YYbVKlSJTkcDndHA4ArogAEAAAAAORKdna2li9fru+++07Lly/XkSNHlJ2d7e5YtggODlbx4sXVrFkztW3bVh06dOASXgAFFgUgAAAAAOCSkpOT9d1332nBggVau3atEhIS3B3JFv7+/qpcubJq1aqljh07qlGjRipfvry7YwGAZSgAAQAAAAAyTVNHjhzRzJkztWTJEv3+++9KT093dyzL+fv7q2zZsmrSpInatWun1q1bq2jRojIMw93RAMA2FIAAAAAA4IOys7O1Y8cOTZ8+XStWrNCePXu87nJef39/lShRQg0aNFCHDh3Upk0blSlTxt2xACDfUQACAAAAgA/IzMzUqlWrNHPmTK1atUp//fWXuyNZrkyZMqpRo4Y6dOigli1bKjo6mgd0AIAoAAEAAADAK6Wnp2vx4sX69ttvtWbNGp06dcrdkSwVEhKievXqqWXLlurcubOqVKmigIAAd8cCAI9EAQgAAAAAXiAtLU3ff/+9vvvuO61Zs0aJiYnujmSZQoUKqVy5cmrbtq1uuukmtWjRgjP7AMAJFIAAAAAAUAClpqZq7ty5mj9/vtauXavk5GR3R7KEn5+fypYtqzp16qhz58668cYbVa5cOXfHAoACjQIQAAAAAAqA5ORkzZ49Wz/99JPWrFmj1NRUd0eyROHChVWjRg21adNGHTt2VLVq1RQYGOjuWADgVSgAAQAAAMADJSUlad68efrxxx+1evVqpaSkuDtSnvn5+alSpUpq0qSJunbtqiZNmqhw4cLujgUAXo8CEAAAAAA8QFJSkhYtWqR58+YpJibGK+7hFxISovr166tdu3bq2bOnypYt6+5IAOCTKAABAAAAwA1SUlK0atUqffPNN4qJidGpU6dkmqa7Y7nM399fxYsXV6tWrdShQwfdfPPNCgoKcncsAIAoAAEAAAAgX6Snp2v79u2aNm2ali1bpsOHDxfowi8kJESVKlVSx44d1bt3b0VHRys7O9vdsQAAl0ABCAAAAAA2OXbsmCZPnqwFCxZo9+7dBbYgMwxDRYoU0XXXXacuXbqoXbt2ioqKkiQ5HA5FRkYqPj7ezSkBAJdDAQgAAAAAFklOTtb06dM1f/58bdy4URkZGe6O5BKHw6FSpUqpefPm6ty5s5o3b87DOgCgAKMABAAAAAAXpaWl6eeff9a8efO0bNkyJSUluTuSSwIDAxUVFaVbbrlFHTt2VIMGDRQYGOjuWAAAi1AAAgAAAEAuZWdna9u2bZozZ46+//57HT16tEBe1hsSEqLKlSurW7du6tChg2rWrCnDMNwdCwBgEwpAAAAAALiC1NRUzZ07V1OnTtW2bduUlpbm7khOCw8PV7Vq1dSjRw+1b99eVapUcXckAEA+ogAEAAAAgH8xTVOrV6/WlClTtGzZMsXFxbk7ktOKFCmimjVrqmfPnmrXrp3KlSvn7kgAADeiAAQAAADg82JjYzVnzhzNmjVL+/btU2ZmprsjOSUiIkL16tXLOcOvVKlS7o4EAPAgFIAAAAAAfE5GRoY2btyoCRMmaNWqVQXuLL/ChQurYcOG6tatm26++WYVL17c3ZEAAB6MAhAAAACATzhz5oy+/PJL/fjjj9q+fbtM03R3pFwLCQlRkyZN1KlTJ3Xr1k2RkZHujgQAKEAoAAEAAAB4paysLMXExOjbb7/VggULlJCQ4O5IuRYUFKRGjRqpY8eOuuOOO1SkSBF3RwIAFGAUgAAAAAC8Rnp6uubPn6/PPvtMO3bsKDBP7PX391e9evV0yy23aMCAAZzhBwCwFAUgAAAAgAJt//79+uyzz7Ro0SIdPnzY3XFyxc/PTzVq1FCHDh00cOBAlStXToZhuDsWAMBLUQACAAAAKFAyMjK0atUqTZw4UStWrFBSUpK7I12VYRiKiopSq1at1L9/f9WpU0eBgYHujgUA8BEUgAAAAAA8XlpammbOnKnp06dry5YtysrKcnekq4qIiFDTpk3Vu3dvtW7dWoULF3Z3JACAj6IABAAAAOCRDh48qJkzZ+rrr7/WkSNHPP6pvQEBAapbt666dOmiXr16qUSJEu6OBACAJApAAAAAAB4kNjZWY8eO1a+//qoTJ064O85VVa5cWW3bttW9996rypUruzsOAACXRAEIAAAAwG2ysrK0ZMkSTZ8+XUuWLNG5c+fcHemKIiMj1bBhQ91777264YYbFBAQ4O5IAABcFQUgAAAAgHxlmqaWL1+uMWPGaMuWLUpPT3d3pMvy9/dXpUqVdOedd6pLly6qWLGiuyMBAOA0CkAAAAAAtktOTtbXX3+tr7/+Wlu3bvXo+/lFRESoffv26tWrl9q2bSvDMNwdCQCAPKEABAAAAGCLtLQ0TZ8+XZ9//rn27t3rsaWfw+FQnTp1dPvtt6t///4KDQ11dyQAACxFAQgAAADAMidOnND//vc/zZgxQ4cOHXJ3nMuKjIxU69atNWDAADVu3FiBgYHujgQAgG0oAAEAAADkSVJSkj7++GN9++23Hlv6GYahatWqqXPnzrr77rtVunRpd0cCACDfUAACAAAAcNqRI0c0Y8YMTZkyRceOHXN3nEsKCwtTw4YNNWrUKDVr1ox7+QEAfBYFIAAAAIBcOXPmjD744APNmzdPsbGx7o5zSSVKlFDPnj3Vq1cv1alTh9IPAABRAAIAAAC4gjNnzmjGjBmaMGGCjhw54u44FzEMQ9ddd526deumQYMGKSwszN2RAADwOBSAAAAAAC6QlJSkCRMmaPbs2dq7d6+741wkJCREjRo10oMPPqjmzZsrICDA3ZEAAPBoFIAAAAAAlJmZqblz5+rdd9/Vvn37ZJqmuyNdoEiRIurUqZPuuusuNWzY0N1xAAAoUCgAAQAAAB+Vnp6u77//Xp9//rk2b97sUaWfYRiqUKGCevfurXvuuUcRERHujgQAQIFFAQgAAAD4ENM0tWDBAo0ZM0YrV65UZmamuyPlMAxDNWrU0B133KF+/fqpaNGi7o4EAIBXoAAEAAAAfMChQ4c0evRoLVy4UKmpqe6OkyMgIEB16tTRqFGj1KFDB/n5+bk7EgAAXocCEAAAAPBSBw4c0MSJEzV9+nQlJia6O06OgIAAtWrVSn379lWnTp3k78+PJQAA2Il/aQEAAAAvkpqaqo8//lgzZ87UwYMH3R0nR1hYmJo1a6ZnnnlGtWvXdnccAAB8CgUgAAAAUMCZpqmVK1fqxRdf1I4dO5Sdne3uSJKkQoUK5Ty594YbbpBhGO6OBACAT6IABAAAAAqoTZs26ZNPPtEPP/zgMQ/ziIiIUPv27fX000+rYsWK7o4DAABEAQgAAAAUKHFxcRo7dqzmzp2r06dPuzuOJCk0NFSdOnXSkCFDdP3117s7DgAA+A8KQAAAAMDDZWdna968eRo7dqz27Nnj7jiS/rmnX6dOnTRq1Chdc8017o4DAACugAIQAAAA8FD79u3TG2+8oZ9++kkZGRnujqOQkBC1adNGI0aMUP369d0dBwAA5BIFIAAAAOBBzpw5owkTJmjy5Mk6deqUu+MoMDBQ7du313333aemTZvyIA8AAAogCkAAAADAzUzT1I8//qjx48dr06ZNMk3TrXkCAgJ0/fXX67nnnlPjxo0p/QAAKOAoAAEAAAA3OX36tF577TV99913Sk5OdnccNWrUSP3799cdd9whf39+VAAAwFv43L/qCQkJmjVrltatW6fTp08rKChI0dHR6tSpk5o2ber0es8884y2b9+eq23btWunESNGXPDa+++/r19//fWKcxUqVND48eOdzgYAAADPY5qmli5dqueee87tD/QwDEOVK1fW448/rm7duikgIMCteQAAgD18qgCMjY3Vs88+q4SEBElSoUKFlJKSoi1btmjLli3q0qWLhg0b5tSaYWFhKlKkyGXfz8zMzPltbnR09GW3CwwMVEhIyCXfCw8PdyoTAAAAPM/+/fs1fvx4ff31125/oEf58uXVu3dvPfDAAypcuLBbswAAAPv5TAGYkZGh1157TQkJCapYsaIeeeQRVa5cWWlpaZo3b56mTZum+fPnq3Llymrfvn2u133mmWeu+P4333yjqVOnKiAgQK1atbrsds2bN9fIkSNzvV8AAAB4vqysLH311Vf68ssv9ccff7g1S2hoqHr27KnHHntMderUUVZWluLj492aCQAA5A+fKQAXLlyoY8eOKSgoSC+88IJKlCghSQoKCtIdd9yhuLg4/fTTT5o6dapat25t2T1Pli5dKumf+6nw21UAAADfcPToUT3//PNatGiRzp0757YcgYGBatmypV544QVde+21kqTIyEi35QEAAO7h5+4A+WXZsmWSpJYtW+aUf//Ws2dPGYahuLg4bdu2zZJ97tq1S0eOHJEkp84qBAAAQMFjmqZ++uknNW3aVHXr1tX333/vtvKvVq1a+uijj3T48GHNmDEjp/wDAAC+ySfOADx79mzODZYbNGhwyW1KlCihqKgoHT58WL///rvq16+f5/0uWbJEklS0aFFL1gMAAIDnSUhI0LvvvqtJkybp7NmzbstRokQJ9evXTw888ICKFi3qthwAAMDz+EQB+Ndff8k0TUlSxYoVL7tdxYoVdfjwYR0+fDjP+0xLS1NMTIwkqXXr1nI4HFfcfuvWrbr33nt18uRJBQYGqkyZMrr++ut16623cpkGAACAB9q4caNeeOEFrVu3zm0ZAgMD1b17dz366KOqUqWK23IAAADP5hMFYFxcXM7fr/Tb0PPvWXEz5DVr1iglJUWS1K5du6tuf+rUKTkcDhUqVEipqanat2+f9u3bpwULFuiJJ55Q3bp1r7rG1KlTNX369Mu+37dvX/Xr1y/3X4QH8/Pzy/m/FKSwgmEYkqSIiIicXxgAruIYBatxjPIcqampGj9+vN59912dOnXKLRkMw1Dt2rX15ptvqkOHDjmfj9ziGAWrcYyC1ThOwUoco/7hEwXgv++9EhQUdNntzr9nxaUbixcvliRVq1ZN5cuXv+x20dHRqlatmho1aqRixYrJz89PqampWrdunSZPnqy4uDi9/vrrevfdd1WuXLkr7jMlJUUnTpy47PupqalXPROxoDEMw+u+JrjX+W82ACtwjILVOEa5z/bt2/Xiiy9q3rx5ysrKckuG0qVLq2/fvnrppZcUHh6e5/U4RsFqHKNgNY5TsJKvH6N8ogDMbydPnsx5kMjVzv7r0qXLRa+FhISodevWqlmzpkaOHKnk5GTNmDFDjz322BXXCg0NVcmSJS/7fkhIiNu+YbWan5+fDMOQaZrKzs52dxx4AcMw5Ofnp+zsbJ/+rRCswTEKVuMY5R6maWrq1KkaM2aMdu3a5ZYMDodDXbp00aOPPqpmzZrlvJ6X7+k4RsFqHKNgNY5TsJI3HqNcKcZ9ogAMDg7O+XtaWppCQkIuuV1aWpokqVChQnna39KlS5Wdna3AwEC1aNHC5XVKliypW2+9VTNnztSGDRuUnZ19xca6f//+6t+//2XfP3XqlCWXN3uCyMhIORwOZWdne83XBPdyOByKjIxUQkKC1xTlcB+OUbAax6j8dfbsWY0ePVozZsxQYmKiWzKUL19eL774ojp37pzzTb5VxxOOUbAaxyhYjeMUrOSNx6jixYs7PeMTBeC/7/sXFxd32QLw/L0C83qPgV9//VWS1KRJE4WFheVprWrVqkn65/LdpKQkRURE5Gk9AAAAXNpff/2lUaNGacWKFW75AaFQoUK65ZZb9Morr6h06dL5vn8AAOC9fKIAjIqKyjl9ODY2VlFRUZfcLjY2VpKueM++q9m5c6eOHj0qSWrfvr3L6wAAAMB+pmkqJiZGjz76qPbv3++WDDVq1NADDzyg3r17+/z9iQAAgD184juMQoUKqWrVqpKkTZs2XXKbU6dO6fDhw5KUqyfuXs6SJUsk/XM6Zl7WOe/PP/+U9M/XULhw4TyvBwAAACk9PV0TJ05U1apV1aNHj3wv/4KDgzVgwABt2rRJK1asUN++fSn/AACAbXziDEBJat26tf78808tX75cvXv3VokSJS54f86cOTJNU0WLFlWdOnVc2kdaWppiYmIkSW3atLnqN3GmaeY8jvpSTp48qZ9++kmS1LBhQ74pBAAAyKP4+Hi9/fbbmjhxojIzM/N9/9dee62eeuop3XLLLXxvBwAA8o3PfNdx8803q3Tp0jp37pxeffVVHThwQNI/pd2sWbP0448/SvrnQRr+/hf2okOHDlXXrl31/vvvX3Efq1atUmpqqqSrP/1XkpYtW6Y33nhDa9asueAG02fPntVvv/2mJ598UklJSSpUqJD69u3rzJcLAACAf9m3b5/69++vatWq6bPPPsvX8i8oKEiDBg3Srl27tHz5cnXq1InyDwAA5CufOQMwICBAzz33nJ599lkdPHhQI0aMUEhIiM6dO5fzWPHOnTvn6b595x/+ce2116ps2bJX3T47O1urV6/W6tWrJf1zma+/v79SUlJyMkVEROjxxx+/7H0LAQAAcHmrV6/W008/rR07duT7vitUqKBnn31W3bt3p/ADAABu5TMFoPTPN2EffvihZs+erXXr1unUqVMKDQ1VlSpVdOutt6pp06Yur33y5Elt27ZNUu7O/pOkOnXqqH///tq1a5eOHDmixMREpaamKjQ0VOXLl1fDhg118803c+8/AAAAJ2RnZ+ubb77Rq6++qhMnTuTrvv39/dWqVSu98cYbqly5cr7uGwAA4HIM0zRNd4dA/jh16pS7I1gmMjJSDodDWVlZio+Pd3cceAGHw6HIyEjFx8crKyvL3XFQwHGMgtU4RuVOamqqPvnkE3344YdKSUnJ132XKlVKAwYM0MiRIxUYGJiv+3YWxyhYjWMUrMZxClbyxmNU8eLFnZ7xqTMAAQAA4H1OnDihMWPGaNq0afn+YI9mzZrp0UcfVatWrfJ1vwAAAM6gAAQAAECBtGfPHo0ePTrnYW75JSgoSIMHD9ZDDz2kkiVL5uu+AQAAXEEBCAAAgAJl06ZNeuWVVxQTE5Ov+y1TpozeeOMN3XLLLXI4HPm6bwAAgLygAAQAAECBsGzZMr366qvaunVrvu3TMAw1bNhQ7733nqpXr55v+wUAALASBSAAAAA82vz58zV69Gjt27cv3/YZGBionj176pVXXlGRIkXybb8AAAB2oAAEAACAR/rmm2/0xhtv6K+//sq3fRYrVkzDhw/XvffeK39/vlUGAADege9qAAAA4DFM09RXX32lMWPG6MSJE/m23+rVq+vFF1/UTTfdlG/7BAAAyC8UgAAAAHA70zT15ZdfasyYMYqPj8+Xffr5+al58+Z68803VbVq1XzZJwAAgDtQAAIAAMBtsrKyNGnSJL355ptKSEjIl30GBQXptttu06uvvqqIiIh82ScAAIA7UQACAAAg32VmZmrKlCl6/fXXlZiYmC/7jIyM1NChQ/XII49wfz8AAOBT+M4HAAAA+SYjI0PTpk3TK6+8oqSkpHzZZ8WKFfXoo4+qb9+++bI/AAAAT0MBCAAAANtlZGRo5syZeuGFF/Kt+Ktfv76eeeYZtW7dOl/2BwAA4KkoAAEAAGCbzMxMzZo1S88880y+FX/t27fXc889p1q1auXL/gAAADwdBSAAAAAsl5WVpXnz5umJJ57Il4d7GIahXr166emnn1ZUVJTt+wMAAChIKAABAABgGdM0tWDBAo0aNUpxcXG278/f3z/nwR6RkZG27w8AAKAgogAEAACAJZYvX677779fJ06csH1fwcHBGjFihO6//36Fhobavj8AAICCjAIQAAAAebJp0yYNHTpUhw8ftn1foaGhevrppzVo0CAFBgbavj8AAABvQAEIAAAAl/z5558aMmSIdu/ebfu+wsPD9eKLL6pfv37y9+dbWAAAAGfw3RMAAACccuzYMQ0dOlRr1661fV/FihXTSy+9pDvuuEN+fn627w8AAMAbUQACAAAgVxITEzVixAj9+OOPMk3T1n2VKFFCL7/8sm6//XYZhmHrvgAAALwdBSAAAACu6Ny5c3rjjTf0+eefKyMjw9Z9lSxZUi+++KJ69epF8QcAAGARCkAAAABcUlZWlv73v//p5ZdfVnJysq37KlWqlJ5//nn17t3b1v0AAAD4IgpAAAAAXMA0Tf3yyy8aNWqUTpw4Yeu+SpQooWeeeUb9+/e3dT8AAAC+jAIQAAAAOXbt2qXBgwdr7969tu6naNGieuKJJzRkyBBb9wMAAAAKQAAAAEiKi4vT4MGDFRMTY+t+wsPDNWrUKD300EO27gcAAAD/hwIQAADAh2VmZuqxxx7T9OnTbX2yb0hIiB544AE98cQTPNwDAAAgn1EAAgAA+KhPP/1Ur7/+us6ePWvbPgIDAzV48GC9/PLL8vPzs20/AAAAuDwKQAAAAB+zfPlyPfLIIzp06JBt+3A4HOrTp4/Gjh2rgIAA2/YDAACAq6MABAAA8BEHDx7UE088oaVLl9q2D8MwdOutt+rDDz9UWFiYbfsBAABA7lEAAgAAeLnk5GS9+eab+uyzz2y9z1+LFi00YcIElShRwrZ9AAAAwHkUgAAAAF7KNE3NmjVLjzzyiM6dO2fbfq677jp9/vnnqlKlim37AAAAgOsoAAEAALzQH3/8oX79+ik2Nta2fVSqVEkfffSRGjdubNs+AAAAkHcUgAAAAF4kJSVFDz74oH788Ufb9lGsWDGNHTtWnTt3lmEYtu0HAAAA1vBzdwAAAADkXXZ2tiZOnKhrr73WtvIvKChIzz33nHbs2KEuXbpQ/gEAABQQnAEIAABQwG3ZskXDhg3TwYMHbVnfz89Pt99+u9555x0FBwfbsg8AAADYhwIQAACggDp79qweeOAB/fDDD7bto1GjRpoyZQpP9gUAACjAKAABAAAKoClTpujpp59WRkaGLeuXLVtWX331lerWrWvL+gAAAMg/FIAAAAAFyB9//KEhQ4bojz/+sGX9kJAQvffee+rRowf3+AMAAPASFIAAAAAFQFJSkp588kl9/vnntqzvcDj08MMPa+TIkQoJCbFlHwAAAHAPCkAAAAAPt2TJEg0bNkxnzpyxZf1bb71Vo0ePVrly5WxZHwAAAO5FAQgAAOChkpKS1LdvX61du9aW9aOjo/XBBx+ocePGtqwPAAAAz+Dn7gAAAAC42CeffKLq1avbUv4FBwfr9ddf15o1ayj/AAAAfABnAAIAAHiQXbt26YEHHtD27dttWb9Hjx766KOPFBAQYMv6AAAA8DwUgAAAAB4gPT1dY8aM0QcffCDTNC1fv1q1apo2bZoqVapk+doAAADwbBSAAAAAbrZt2zb16tVLp0+ftnztsLAwvf3227rttttkGIbl6wMAAMDzcQ9AAAAAN0lPT9eDDz6otm3b2lL+DRo0SNu2bVPPnj0p/wAAAHwYZwACAAC4wbJly3T//ffr1KlTlq9dtWpVffXVV7rmmmssXxsAAAAFDwUgAABAPjp37pwefvhhzZ071/K1AwMDNXbsWPXr18/ytQEAAFBwUQACAADkk+XLl+uuu+5Samqq5Wt369ZN48aNU2hoqOVrAwAAoGCjAAQAALBZcnKyRo4cqXnz5lm+dvny5TVhwgQ1atTI8rUBAADgHXgICAAAgI2WLVum+vXrW17+ORwOPfbYY9qwYQPlHwAAAK6IMwABAABskJWVpfvuu0/fffed5WvXrFlT3377rUqWLGn52gAAAPA+FIAAAAAWW7Nmje666y6dOXPG0nWDgoI0btw49ezZ09J1AQAA4N24BBgAAMAiKSkpeuyxx9SlSxfLy7+ePXtq+/btlH8AAABwGmcAAgAAWGDPnj3q0aOHjh8/bum6xYoV04QJE9SzZ0/Fx8crKyvL0vUBAADg/TgDEAAAIA9M09Qbb7yhG2+80fLyr1evXtqxY4fatm1r6boAAADwLZwBCAAA4KJ9+/Zp6NCh2r59u6XrlihRQjNnzlSdOnUsXRcAAAC+iTMAAQAAXDBz5ky1aNHC0vLPMAzdf//92rhxI+UfAAAALMMZgAAAAE5ITU1V//79tWLFCkvXLV++vCZNmqS6detaui4AAADAGYAAAAC59Ntvv6lu3bqWl3/33nuvNm7cSPkHAAAAW3AGIAAAwFVkZWXppZde0qeffmrpumXLltU333yj6tWrW7ouAAAA8G8UgAAAAFfw999/q0uXLjp06JBlaxqGoWHDhun5559XcHCwZesCAAAAl0IBCAAAcBnTpk3Tk08+qbS0NMvWLFasmGbMmKH69etbtiYAAABwJRSAAAAA/5GZmal7771X33//vaXr9u3bV+PGjZNhGJauCwAAAFwJBSAAAMC//Pnnn+rWrZtOnTpl2ZpFihTRF198oVatWlm2JgAAAJBbPAUYAABAkmma+uSTT9SqVStLy78OHTpo8+bNlH8AAABwG84ABAAAPi8rK0t33nmnlixZYtmaAQEBmjBhgrp06WLZmgAAAIArKAABAIBP2759u26//XadPn3asjXr16+vqVOnqmTJkpatCQAAALiKS4ABAIBPMk1Tn332mdq1a2dZ+edwOPT0009r4cKFlH8AAADwGJwBCAAAfE5WVpYGDRqkBQsWWLZm8eLF9cMPPyg6OtqyNQEAAAArcAYgAADwKbt371aDBg0sLf969eqlzZs3U/4BAADAI3EGIAAA8Bnfffed7r//fmVmZlqyXqFChfThhx+qW7dulqwHAAAA2IECEAAAeL3s7Gw98cQTmjJlimVrVq9eXfPnz1dkZKRlawIAAAB24BJgAADg1Y4ePaq2bdtaWv6NGDFCv/32G+UfAAAACgTOAAQAAF7r999/V/fu3ZWcnGzJeuHh4ZoyZYqaN29uyXoAAABAfuAMQAAA4HVM09Qnn3yim266ybLyr2HDhtq6dSvlHwAAAAoczgAEAABeJT09Xffdd5/mz59vyXqGYejJJ5/UqFGj5OfH704BAABQ8FAAAgAAr3Hs2DF17dpVBw4csGS98PBwTZ8+XU2aNLFkPQAAAMAd+DU2AADwCsuXL1ezZs0sK/8aNWqknTt3Uv4BAACgwKMABAAABd6UKVN0++23W3K/P8MwNGLECM2fP19BQUEWpAMAAADci0uAAQBAgZWenq7hw4drzpw5lqwXHBys6dOnq0WLFpasBwAAAHgCCkAAAFAgJScnq0uXLtq+fbsl61177bX64YcfFB4ebsl6AAAAgKfgEmAAAFDg7Nq1S/Xr17es/OvTp48WL15M+QcAAACvxBmAAACgQPn+++913333KSMjI89r+fn56bPPPlO3bt0sSAYAAAB4Js4ABAAABcb48eM1ZMgQS8q/kiVLavny5ZR/AAAA8HqcAQgAADxeWlqa7rvvPv3www+WrNekSRNNnz6dS34BAADgEzgDEAAAeLSzZ8+qU6dOlpV/I0eO5GEfAAAA8CmcAQgAADzWnj171K1bN508eTLPawUGBurDDz/UbbfdZkEyAAAAoOCgAAQAAB5p/fr16tmzp86ePZvntYoWLaqffvpJ0dHRFiQDAAAAChYuAQYAAB7nm2++0a233mpJ+dewYUNt3LiR8g8AAAA+iwIQAAB4DNM0NXr0aD344IMyTTPP6w0cOFA//PCDwsLCLEgHAAAAFExcAgwAADxCZmamhg8frlmzZuV5LT8/P40fP169evWyIBkAAABQsFEAAgAAt0tOTlavXr20YcOGPK8VFhamGTNmqGnTphYkAwAAAAo+CkAAAOBWJ0+e1K233qoDBw7kea0KFSrop59+UqlSpSxIBgAAAHgH7gEIAADcZu/evWrevLkl5d+NN96o5cuXU/4BAAAA/0EBCAAA3GLz5s1q06aN4uLi8rzWsGHDNGfOHIWGhlqQDAAAAPAuXAIMAADy3fz58zVs2DBlZWXlaR3DMDR27FgNHDjQomQAAACA96EABAAA+Wrq1KkaNWpUntcJDAzUtGnT1Lp167yHAgAAALwYBSAAAMgXpmnqjTfe0HvvvZfntYoVK6ZffvlF5cuXtyAZAAAA4N0oAAEAQL548sknNWnSpDyvc8011+i7777jYR8AAABALlEAAgAAW6Wnp2vIkCH6+eef87xW27ZtNXXqVAUEBFiQDAAAAPANFIA+xOFwuDuCLbz160L+Ov854vMEq/n6ZyorK0t33HGHYmJi8rxWv379NG7cOJ/835RjFOzCZwpW4BgFO/G5Ql5xjPqHYZqm6e4QAADA+8THx6tVq1batm1bntcaO3asHnvsMQtSAQAAAL6HAtCHxMfHuzuCZcLDw+VwOJSVlaXExER3x4EXcDgcCg8PV2JiorKystwdBwUcxygpOTlZbdq00b59+/K0jp+fnz766CP17t3bomQFE8coWIljFKzGMQpW4zgFK3njMSoyMtLpGS4B9iHe8kH/L2/9uuAeWVlZfKZgKV/8PB0+fFgdO3bU8ePH87ROQECAZs6cqRYtWvjk/46XwjEKVuPzBCtxjIId+EzBKr5+jKIABAAAlvn7779100036fTp03laJyIiQj/99JOqVatmUTIAAADAd/m5OwAAAPAOO3fu1I033pjn8q9UqVJasmQJ5R8AAABgEc4ABAAAebZ792517NhRqampeVqnevXqWrRokUJCQixKBgAAAIAzAAEAQJ6sX79e7du3z3P517BhQ/3888+UfwAAAIDFKAABAIDLNm7cqG7duiktLS1P63Tq1Ek//fSTwsLCLEoGAAAA4DwKQAAA4JIVK1aoS5cuysjIyNM6vXv31sSJE2UYhkXJAAAAAPwbBSAAAHDaypUr1atXrzyXfyNHjtT48ePlcDgsSgYAAADgv3gICAAAcMqvv/6qfv36KSsrK0/rPPPMMxo1apRFqQAAAABcDgUgAADItV9//VV9+/ZVdnZ2ntYZN26c+vXrZ1EqAAAAAFdCAQgAAHJlyZIluvPOO/NU/vn5+enjjz9Wz549LUwGAAAA4EooAAEAwFUtWbJE/fr1y3P5N23aNLVv397CZAAAAACuhgIQAABc0dKlS/N85p+/v79mzpypli1bWpgMAAAAQG5QAAIAgMuy4sy/gIAAzZs3T40aNbIwGQAAAIDcogAEAACXFBMTk+cz/4KDg/Xjjz/quuuuszAZAAAAAGf4uTsAAADwPMuXL9ftt9+urKwsl9coVKiQfv75Z8o/AAAAwM04AxAAAFxg8+bN6tOnjzIzM11eIzQ0VAsXLlT16tUtTAYAAADAFZwBCAAAcqxfv15dunRRRkaGy2uEhYXpl19+ofwDAAAAPAQFIAAAkCTt2bNHPXv2VFpamstrhIeHa/HixapataqFyQAAAADkBQUgAADQrl271KFDB509e9blNQoXLqxFixYpOjrawmQAAAAA8ooCEAAAH3f8+HF17dpVycnJLq8RHh6uX375hfIPAAAA8EAUgAAA+LCjR4+qbdu2OnPmjMtrhIWFceYfAAAA4MEoAAEA8FGJiYnq0qWLTpw44fIaYWFh+vnnnyn/AAAAAA/m7+4AAAAg/yUnJ6tz586KjY11eY2QkBAtWrSIB34AAAAAHo4zAAEA8DHnzp1Tr169tGvXLpfXCA4O1vfff0/5BwAAABQAnAEIAIAPyc7O1t13360NGza4vEZgYKB+/PFHXXfddRYmAwAAAGAXzgAEAMBHZGdn68EHH9SSJUtcXiMgIEDffvst5R8AAABQgFAAAgDgI1588UXNmjXL5XmHw6GZM2fqhhtusDAVAAAAALtRAAIA4AM+/vhjffrppy7P+/n5adKkSWrRooWFqQAAAADkBwpAAAC83LfffqsXX3wxT2t8+umn6tixo0WJAAAAAOQnCkAAALzYypUrNXz48Dyt8fbbb6tHjx4WJQIAAACQ3ygAAQDwUhs3btQdd9yhrKwsl9d46aWXNHDgQAtTAQAAAMhvFIAAAHihEydOqE+fPsrIyHB5jeHDh+vBBx+0MBUAAAAAd6AABADAyxw7dkzt27fXmTNnXF5j4MCBev75560LBQAAAMBtKAABAPAi2dnZ6tevn/7++2+X1+jUqZPGjh0rwzAsTAYAAADAXSgAAQDwEhkZGbrzzju1bds2l9e44YYb9Nlnn1H+AQAAAF7E390BAACANZ577jktXrzY5fkaNWpozpw5cjgcFqYCAAAA4G6cAQgAgBeYMmWKJk6c6PJ8VFSUZs+eTfkHAAAAeCHOAAQAoICbO3euHnvsMZfnIyIitHTpUhUpUsS6UAAAAAA8BmcAAgBQgB04cEAPPvigy/NBQUGaPXs25R8AAADgxSgAAQAooA4ePKgOHTooIyPDpXmHw6EffvhBdevWtTgZAAAAAE9CAQgAQAGUmZmpO+64Q2fOnHF5jQ8//FD16tWzLBMAAAAAz0QBCABAAZOZman+/fvrwIEDLq/x+uuvq1evXhamAgAAAOCpKAABAChgnnrqKS1ZssTl+UGDBmnYsGEWJgIAAADgySgAAQAoQL799ltNmTLF5fn27dvr9ddftzARAAAAAE/n7+4AAAAgd5YtW6bhw4e7PF+7dm1NmzZNfn78/g8AAADwJfwEAABAAXDs2DENHDhQWVlZLs2XLFlS06dPp/wDAAAAfBA/BQAA4OGSk5PVo0cPpaamujQfFhamRYsWqUyZMhYnAwAAAFAQWFoALlq0yMrlAADweZmZmRo4cKD27t3r8hoTJ05UuXLlLEwFAAAAoCCxtAC85ZZbdM011+itt97SiRMnrFwaAACf9N5772n58uUuz48fP15t2rSxMBEAAACAgsbyS4APHDigZ555RuXLl1fv3r21ZMkSq3cBAIBPmDdvnsaOHevy/P3336/evXtbmAgAAABAQWRpAThw4EAFBwfLNE1lZGRo1qxZ6tChg6pVq6a3335bp06dsnJ3AAB4re3bt+vee++VaZouzbdt21YvvPCCxakAAAAAFESWFoCTJk3S0aNHNW7cONWuXVumaco0Te3bt09PPvmkoqKi1K9fPy1btszK3QIA4FWSk5M1YMAAl5/4W6tWLU2dOlX+/v4WJwMAAABQEFl+CXBERISGDx+urVu3KiYmRgMGDMg5KzA9PV0zZ85Uu3btVKNGDb333nuKi4uzOgIAAAXWuXPndMcdd+jw4cMuzYeHh2vy5MkKCAiwOBkAAACAgsryAvDfmjVrpsmTJ1/yrMA9e/boscceU7ly5XTXXXdpxYoVdkYBAKBAGDt2rNavX+/SbEBAgObMmaNKlSpZGwoAAABAgWZrAXjef88KvOuuu3LOCkxLS9P06dPVunVr1apVSx988IHOnDmTH7EAAPAoP//8sz788EOX5z/44APVrVvXwkQAAAAAvEG+FID/1qxZM02ZMkVHjx7VQw89lPO6aZravXu3Ro0apaioKD344IM6cuRIfscDAMAtNm3apEGDBrn80I9hw4apZ8+eFqcCAAAA4A3yvQDMzMzUzJkzddttt+mjjz6SYRg5P+ycvzw4NTVVn376qapXr67PP/88vyMCAJCvsrKy9OCDDyozM9Ol+fbt22v06NEyDMPiZAAAAAC8Qb4VgHv37tUTTzyhcuXK5TwJ+Hzh17hxY02aNElHjhzRu+++q+rVq+cUgffdd58WLlyYXzEBAMhXmZmZ6tu3r/bu3evSfLly5XJ+oQYAAAAAl2JrAZiRkaGvv/5abdu2VfXq1fXOO+/o5MmTMk1ThQoV0pAhQ7Rx40atWbNGAwcOVJkyZTRy5Ejt2rVLU6ZMUUhIiEzT1JtvvmlnTAAA3GbcuHFaunSpS7MhISH69ttvVbRoUYtTAQAAAPAm/nYsumfPHn322WeaMmWKTp8+LUk5l/nWqFFD999/vwYMGKCIiIjLrnHXXXfpzz//1OjRo7Vjxw47YgIA4FY7d+7U2LFjXZ6fPHmyqlatamEiAAAAAN7I0gJwxowZ+uyzz7R8+XJJ/1f6BQQEqHv37rr//vvVunXrXK/XuHFjScopEQEA8Bb79+9X586dlZWV5dL88OHD1aZNG4tTAQAAAPBGlhaAd9555wUP9YiKitI999yjoUOHqnTp0k6vFxgYaGU8AAA8xsMPP6ykpCSXZjt16qTnn3/e4kQAAAAAvJUtlwB36NBB999/v7p06SI/P9dvM9i4cWOX74sEAICneuutt7R27VqXZkuXLs1DPwAAAAA4xdIC8LHHHtO9996r6OhoS9aLjIxUq1atLFkLAABP8M033+jtt992aTY4OFhff/21wsLCLE4FAAAAwJtZWgCOGTPGyuUAAPAqqampeuqpp1yenzx5smrVqmVhIgAAAAC+wPXrcy9h8ODBGjx4sLZs2eLU3Pbt2zV48GANGTLEyjgAAHiMc+fOqXPnzi7f9+/OO+9Uu3btLE4FAAAAwBdYWgBOnjxZU6ZMUWxsrFNzR44c0eTJkzV58mQr4wAA4DGeeuopbdu2zaXZxo0ba+zYsRYnAgAAAOArLC0AAQDAxTZt2qTp06e7NFu4cGF9++23CggIsDgVAAAAAF/hEQVgVlaWJMnf35aHEgMA4DaHDh3S7bffLtM0nZ41DEMTJkxQSEiIDckAAAAA+AqPKAAPHDggSQoPD3dzEgAArJOdna2BAwe6fN+/N998UzfddJPFqQAAAAD4GltOuTMMI1fbpaamatOmTRo3bpwMw9C1115rRxwAANzigw8+0I4dO1yabd68uQYPHmxxIgAAAAC+yOUC8OWXX9Yrr7xy0eumaap79+4urdmjRw9X4wAA4FEWLVqkJ554wqXZEiVKaMKECRYnAgAAAOCr8nQG4OXuZ+TKfY5at26thx56KC9xAADwCImJierdu7eys7OdnvX399fPP/+skiVL2pAMAAAAgC9yuQCsVKmSWrVqdcFrv/32mwzDUM2aNVW8ePErzvv5+SksLEyVK1dW+/bt1alTJ/n5ecQtCQEAyJMHH3xQZ86ccWl25MiRqlChgrWBAAAAAPg0lwvAgQMHauDAgRe8dr7AGz16tLp27Zq3ZAAAFEATJkzQjBkzXJpt3769Hn/8cYsTAQAAAPB1lj4EpGXLljIM46pn/wEA4I3279+vF154waXZMmXKaNq0aZwNDwAAAMBylhaAy5Yts3I5AAAKjOzsbN13330u3ffPMAy98847lH8AAAAAbMFPGgAAWOCpp57S5s2bXZp97bXXdNNNN1mcCAAAAAD+QQEIAEAerVq1SpMmTXJptkWLFrrnnnssTgQAAAAA/8elS4BfeeWVnL//+15H/37dVa7eOwkAAHdIS0vT8OHDXZoNCwvT2LFjLU4EAAAAABcyTNM0nR3y8/OTYRiSpKysrEu+7qp/rwdrnTp1yt0RLBMZGSmHw6GsrCzFx8e7Ow68gMPhUGRkpOLj4zkOIdeys7N19913a8GCBU7PGoahBQsW6Prrr7chGbwNxyhYie+jYDWOUbAaxylYyRuPUa48fNflh4CYpnnJss+FPjFHXstDAADy07x581wq/yRp8ODBlH8AAAAA8oVLBeDSpUudeh0AAG+TkpKip556yqXZSpUq6emnn7Y4EQAAAABcmksFYKtWrZx6HQAAb5Kenq4+ffooLi7O6dlChQrpp59+UkREhA3JAAAAAOBiPAUYAAAnffXVV1qzZo1Ls08//bRKlChhcSIAAAAAuDwKQAAAnJCUlKTRo0e7NHvDDTdo6NChFicCAAAAgCtz+SEgeXHixAmtWbNGmZmZqlu3rqKjo90RAwAAp5w9e1bdu3dXcnKy07MlSpTQN998o4CAABuSAQAAAMDlWVoAxsXFafLkyZKkW2+9VdWrV79om1dffVWjR49WRkZGzmu9e/fWxIkTFRwcbGUcAAAs9cknn2jr1q0uzb722msKCgqyOBEAAAAAXJ2lBeDMmTP12GOPKTAwUAMHDrzo/WnTpunFF1+UYRgyTfOCuezsbH399ddWxgEAwDIJCQl6//33XZrt1auXevToYW0gAAAAAMglS+8BuHTpUklSixYtVKxYsYvef+GFFyRJpmmqW7duGjlypMqXLy/TNPXtt99qxYoVVsYBAMASZ8+eVdeuXXX27FmnZ6OjozV+/HgZhmFDMgAAAAC4OksLwD///FOGYahZs2YXvbdq1SodOHBAhmHotdde09y5c/Xuu+9q/fr1ioyMlCT973//szIOAACWeO+997Rz506XZt966y35+fHMLQAAAADuY+lPJKdOnZIkVa1a9aL3Fi9eLEkKCgrSiBEjcl4vWbKk+vbtK9M0tWbNGivjAACQZ4mJifr0009dmh05cqRatWplcSIAAAAAcI6lBeDp06clSaGhoRe9FxMTI+mfy4P/+/51110nSYqNjbUyDgAAeZKWlqYePXq4dOnv9ddfr7Fjx9qQCgAAAACcY2kBeP7+RvHx8Re8np2drbVr18owDLVo0eKiufP3C0xNTbUyDgAAeTJmzBiXn/r78ccfc98/AAAAAB7B0gKwZMmSkqQ9e/Zc8PqaNWuUmJgoSWratOlFc8nJyZKkQoUKWRkHAACXJScn6/PPP3dp9umnn1bjxo0tTgQAAAAArrG0AKxfv75M09TXX3+t9PT0nNfP/wAVGBioG2+88aK5/fv3S5LKli1rZRwAAFySlZWlfv36uXTpb6NGjfTKK6/YkAoAAAAAXGNpAdirVy9J0uHDh9WuXTt9+umnGjZsmKZMmSLDMNS1a9dLnuW3Zs0aGYaha6+91so4AAC45J133tHq1atdmn377be59BcAAACAR/G3crG+ffvqww8/1Nq1a7Vq1SqtWrUq572goCC9+OKLF82cOXNGy5YtkyQ1adLEyjgAADgtJSVFH3/8sUuzI0eOVM2aNS1OBAAAAAB5Y/lDQH788Ud1795dhmHINE2Zpqly5cpp9uzZl/yhaPLkycrIyJAktW/f3so4AAA4xTRNPfTQQ0pJSXF6tlGjRnrmmWdsSAUAAAAAeWPpGYCSVLRoUc2ZM0cnT57U/v37FRoaqpo1a8rP79JdY82aNTVp0iQZhqHrr7/e6jgAAOTaxIkT9cMPP7g0+8EHH3DpLwAAAACPZHkBeF6JEiVUokSJq27XoUMHuyIAAJBrZ8+e1RtvvOHS7P33369rrrnG4kQAAAAAYA3bCkBPlZCQoFmzZmndunU6ffq0goKCFB0drU6dOqlp06ZOr3f8+HENGzbsqts9+eSTl3wC8nn79+/X3LlztW3bNiUmJioiIkK1a9fWbbfdpsqVKzudCwDgnNdff10JCQlOz1133XV66aWXrA8EAAAAABbxqQIwNjZWzz77bM4PeIUKFVJKSoq2bNmiLVu2qEuXLrkq8y4nPDz8spc6BwYGXnbut99+07hx45SZmSlJCg0N1enTp/Xbb78pJiZGo0aNUosWLVzOBQC4sl9++UUTJkxwafazzz677LEfAAAAADyBrQXg33//re3btys+Pl7nzp3L1cyAAQNsyZKRkaHXXntNCQkJqlixoh555BFVrlxZaWlpmjdvnqZNm6b58+ercuXKLj+M5J133lGpUqWcmomNjc0p/5o3b66hQ4eqaNGiiouL0+eff66YmBi9//77qly5sqKiolzKBQC4vPT0dI0YMUKmaTo927dvX0VHR9uQCgAAAACsY0sB+PXXX+vNN9/Utm3bnJozDMO2AnDhwoU6duyYgoKC9MILL+TcnzAoKEh33HGH4uLi9NNPP2nq1Klq3bq1/P3z5+TIadOmKTMzU5UrV9ajjz4qh8Mh6Z+HqTz22GM6evSoDhw4oGnTpunJJ5/Ml0wA4Eu++uornTx50um56Ohovf322zYkAgAAAABrWX7N0sMPP6w777xT27Ztk2maTv+xy7JlyyRJLVu2vOTDSXr27CnDMBQXF+d0cemqlJQUrV+/XpLUvXv3nPLvPIfDoe7du0uS1q1bp9TU1HzJBQC+Yt++fXr55Zddmv3qq6+ueHsHAAAAAPAUlp7m9v3332v8+PE5/92kSRPddNNNioqKUlBQkJW7csrZs2e1Z88eSVKDBg0uuU2JEiUUFRWlw4cP6/fff1f9+vVtz7Vz586c+/5dLtf51zMyMrRr1y5df/31tucCAF+QlZWlgQMH5voWFf/WsWNHVatWzYZUAAAAAGA9SwvA8zdQdzgcmjx5su68804rl3fZX3/9lXN2YcWKFS+7XcWKFXX48GEdPnzYpf2MGTNGR48eVVpamiIiIlStWjW1b99ejRo1uuT25/dTpEgRRUREXHKbiIgIRUREKCEhQbGxsRSAAGCRxYsX648//nB6rlSpUvrwww9tSAQAAAAA9rC0ANywYYMMw1D//v09pvyTpLi4uJy/Fy1a9LLbnX8vPj7epf3s2bNHISEh8vPz0+nTp7V69WqtXr1aN954ox555BEFBARcsP35/Vwp0/n3ExISrppr6tSpmj59+mXf79u3r/r165fLr8aznX/ipp+fnyIjI92cBt7AMAxJ/5Tudt6OAJ4hNTVVTzzxhEuzs2bNUqVKla64DccoWI1jFKzEMQpW4xgFq3GcgpU4Rv3D0gIwISFBktSuXTsrl82zf1/edaVLkc+/d/bs2VyvHRgYqE6dOqlFixaqXLmyQkJCJP3zdN/Zs2dr6dKliomJUWhoqB566KELZs/v52qXR+c2V0pKik6cOHHZ91NTUy+6z2BBZxiG131NcK/z32zAe5mmqUGDBuno0aNOz954441q3rx5rrfnGAWrcYyClThGwWoco2A1jlOwkq8foywtAEuVKqW//vrrojPdvFlkZKTuu+++i16vUKGCRo0apfDwcM2bN0+//PKLunfvrqioKNuyhIaGqmTJkpd9PyQkRFlZWbbtPz/5+fnJMAyZpqns7Gx3x4EXMAxDfn5+ys7O9unfCvmCtWvXavbs2U7PhYaGauLEibk6jnKMgtU4RsFKHKNgNY5RsBrHKVjJG49RrhTjlhaATZo00V9//aVdu3ZZuWyeBQcH5/w9LS0t5yy9/0pLS5MkFSpUyLJ933nnnVqwYIHS09O1fv36CwrA8/s5v9/LyW2u/v37q3///pd9/9SpUy5f3uxpIiMj5XA4lJ2d7TVfE9zL4XAoMjJSCQkJXlOU49Ief/xxl+beffddFS1aNFfHHI5RsBrHKFiJYxSsxjEKVuM4BSt54zGqePHiTs9Yev7j/fffL9M0NXXqVGVkZFi5dJ78+x57/74f4H+df8/KewwEBwerQoUKkqTjx49fMteVMtmVCwB80f/+9z+tWrXK6bkaNWqoR48eNiQCAAAAAPtZWgC2adNGDz30kPbv36+7777bY0rAqKionJs+xsbGXna78++VL18+X3Kd38+ZM2eUmJh4yW0SEhJy7q14vkgEADjv0KFDLj34w8/PT6+99lrOvyMAAAAAUNBYeglwbGysHn30UcXFxWn69OnatGmTHnjgATVr1kzFixfP1Q0X7Si5ChUqpKpVq+rPP//Upk2bdMMNN1y0zalTp3T48GFJUt26dS3b97lz53KKxVKlSl3wXs2aNeXv76/MzExt2rRJrVu3vmh+8+bNkqSAgABde+21luUCAF/z2WefKTMz0+m5kSNHqlWrVjYkAgAAAID8YWkBWKlSpZwzJAzD0J9//qmRI0fmet4wDJd+OMuN1q1b688//9Ty5cvVu3dvlShR4oL358yZI9M0VbRoUdWpUyfX65qmecWzQmbMmKH09HQZhqFGjRpd8F5ISIgaNWqk1atXa968eWrRosUFN3LMysrSvHnzJEmNGze+7L0LAQBXdvDgQU2cONHpuVKlSrl8z0AAAAAA8BSWPwPZNM08/bHLzTffrNKlS+vcuXN69dVXdeDAAUn/PGBj1qxZ+vHHHyX98yANf/8Le9GhQ4eqa9euev/99y9a95lnntE333yjAwcOXHAzydjYWI0bN05z586VJN10002XfALwnXfeKX9/f+3bt0/vvvtuzg1O4+Pj9e6772rfvn0KCAjQnXfeacn/DgDga5KTk3XHHXe49Aum4cOHX/RvAgAAAAAUNJb+VDNw4EArl7NUQECAnnvuOT377LM6ePCgRowYoZCQEJ07dy7nseKdO3dW+/btnVr35MmTmjp1qqZOnSqHw6GQkBClp6df8GTfVq1a6d57773kfIUKFTRixAiNGzdOK1as0MqVKxUSEqKUlBRJkr+/v0aMGHHJ8hAAcHUzZ87M+aWPM9q1a6d77rnHhkQAAAAAkL8sLQAnTZpk5XKWq1Chgj788EPNnj1b69at06lTpxQaGqoqVaro1ltvVdOmTZ1e8+6779bvv/+uPXv2KD4+XklJSXI4HCpTpoxq1Kihdu3a6brrrrviGq1atVL58uU1Z84cbd++XYmJiTmXIt92222qXLmyq18yAPg00zT13nvvOT0XGBiozz//nAd/AAAAAPAKhmnndbfwKKdOnXJ3BMtERkbK4XAoKysr57JpIC8cDociIyMVHx9/weX8KNheeuklffTRR07PDRo0SGPGjHF5vxyjYDWOUbASxyhYjWMUrMZxClbyxmNU8eLFnZ6x/B6AAAB4gt9++82l8q9s2bJ68sknbUgEAAAAAO5BAQgA8EqffvqpS3NTp05VsWLFLE4DAAAAAO5j26MNz5w5o88//1wLFy7Uzp07FRcXp8zMzIuewvjrr7/q2LFjKl68uDp06GBXHACAD9mxY4cWL17s9FyHDh1Up04dGxIBAAAAgPvYUgDOnDlT9957r5KSkiT9cxN2SZe8mfrvv/+uRx99VIUKFdLff/+t8PBwOyIBAHzEyZMn1adPH6fnHA6HHn74YRsSAQAAAIB7WX4J8FdffaV+/fopMTFRpmmqdOnSqlat2mW3v/vuu+Xv769z585p/vz5VscBAPiYTz75RMeOHXN67sUXX1STJk1sSAQAAAAA7mVpAXj06FHdd999Mk1TZcuW1aJFi3TkyBG99dZbl52JjIxUy5YtJf1zOTAAAK5KT0/XpEmTnJ4rX7687rvvPhsSAQAAAID7WVoAjh8/XufOnVOhQoW0ZMkStW/fPldzjRs3lmma+v33362MAwDwMa+88oqSk5OdnnvggQcueZsKAAAAAPAGlhaAixYtkmEY6tevn6pXr57ruWuuuUaSdPDgQSvjAAB8yKJFizRhwgSn5xo2bKi77rrLhkQAAAAA4BksLQAPHDggSWrevLlTcxEREZKU89AQAACc9cEHHzg943A4NGPGDAUFBdmQCAAAAAA8g6UFYEpKiiQpLCzMqbmzZ89KkoKDg62MAwDwEdu2bdPatWudnhswYICKFClifSAAAAAA8CCWFoDFihWTJB0/ftypuT179kiSSpQoYWUcAIAPSE5O1rBhw5yeCwgI0NChQ21IBAAAAACexdICsGbNmpKk5cuXOzU3f/58GYah66+/3so4AAAf8M4772jfvn1Oz3300UeqVq2aDYkAAAAAwLNYWgB27NhRpmlq3rx5OWf1Xc3XX3+tLVu2SJI6depkZRwAgJdLTU3V//73P6fnrr32WvXo0cOGRAAAAADgeSwtAIcOHaqiRYsqPT1dXbt2zXkoyOXMnDlTw4YNk2EYKlu2rPr162dlHACAl/vqq6+UkJDg9NzDDz9sQxoAAAAA8Ez+Vi4WHh6uTz75RH369NGff/6p2rVrq0ePHhc8XfGjjz7S4cOH9fPPP2vbtm0yTVMOh0MTJ05UQECAlXEAAF5s586deu2115yeq1+/vrp27WpDIgAAAADwTJYWgJLUq1cvnTlzRsOHD9fZs2c1Y8YMSZJhGJIuPOvCNE0FBgZqwoQJuummm6yOAgDwYs8//7zS0tKcmgkMDNT06dMVGBhoUyoAAAAA8DyWXgJ83rBhw7R+/Xp1795dhmHINM2L/kj/3PNv7dq1GjhwoB0xAABeau/evU4/cEqS+vfvr+LFi9uQCAAAAAA8l+VnAJ5Xp04dzZkzRwkJCYqJidHBgwd15swZhYWFKSoqSi1atFCJEiXs2j0AwIuNGTPG6RnDMDR06FAb0gAAAACAZ7OtADwvIiKCp/sCACwzd+5czZ071+m5J554QlWrVrUhEQAAAAB4NksLwNjYWElSyZIlFRwcnOu5tLQ0HT9+XJJUoUIFKyMBALxIVlaWXnnlFafnKleurEcffdSGRAAAAADg+Sy9B2ClSpVUpUoVLVq0yKm5ZcuW5cwCAHA5S5Ys0V9//eX03IgRI3IeRgUAAAAAvsbyh4Ccf8BHfs8CALxbdna23nrrLafnSpQooR49etiQCAAAAAAKBlueAgwAgNXGjBmjrVu3OjXj5+eniRMnKiQkxKZUAAAAAOD5PKIATEpKkiR+QAMAXFJCQoI+/vhjp+duvvlmNW3a1IZEAAAAAFBweEQBuHjxYklSmTJl3JwEAOCJvvnmG509e9bpuQcffNCGNAAAAABQsLj8FODffvtNv/322yXf+/rrr7Vly5YrzpumqZSUFG3atElLly6VYRi64YYbXI0DAPBS586d00cffeT0XJMmTdS4cWMbEgEAAABAweJyAbhs2TK98sorF71umqZmzpzp1FqmaSogIEAPP/ywq3EAAF7q8ccf15EjR5yaCQsL05dffsmTfwEAAABAebwE2DTNC/5c7vWr/WnQoIHmz5+vBg0a5PkLAgB4j4MHDzr9SyVJGjJkiEqVKmVDIgAAAAAoeFw+A/Duu+9W69atc/7bNE21bdtWhmHo1Vdf1Y033njFeT8/P4WFhaly5coqUqSIqzEAAF7sq6++uuAXTLnh5+enQYMG2ZQIAAAAAAoelwvAihUrqmLFipd8r3bt2mrVqpXLoQAASEpK0tSpU52e69u3r8qVK2dDIgAAAAAomFwuAC9l6dKlkv4pAAEAyIv7779f8fHxTs2UL19eb775pk2JAAAAAKBgsrQA5Kw/AIAVtmzZooULFzo99/DDDys4ONiGRAAAAABQcOXpISAAANhhypQpTs+EhYXp9ttvtyENAAAAABRslp4B+F/Z2dnat2+f4uPjde7cuVzNtGzZ0s5IAAAPl5SUpHnz5jk99+CDDyosLMyGRAAAAABQsNlSAK5atUpjxozRL7/8kuviT5IMw1BmZqYdkQAABYBpmhoyZIiSkpKcmqtXr54eeeQRm1IBAAAAQMFmeQH4zjvv6Mknn5RpmjJN0+rlAQBebNWqVTkPlHLGiBEj5OfHXS0AAAAA4FIsLQBXrFihxx9/XIZhyDRNlStXTm3atFFUVJSCgoKs3BUAwAtNnjzZ6ZlSpUrp5ptvtj4MAAAAAHgJSwvAcePG5fz91Vdf1dNPP80ZGQCAXDl79qx++eUXp+dGjRqlgIAAGxIBAAAAgHewtABcvXq1DMNQ9+7d9eyzz1q5NADAi5mmqfvuu08pKSlOzbVu3VqDBw+2KRUAAAAAeAdLT887ffq0JKlLly5WLgsA8HLLli3TTz/95PTciBEjZBiGDYkAAAAAwHtYWgAWL15ckhQaGmrlsgAALzdlyhSnZypVqqQbbrjBhjQAAAAA4F0sLQDr1asnSdq3b5+VywIAvFh2draWLFni9NzDDz/MfWYBAAAAIBcs/clpyJAhMk1TX3/9tZXLAgC8lGmaevLJJ3Xu3Dmn5jp27Kj+/fvblAoAAAAAvIulBWCPHj3Us2dPbd26VU888YSVSwMAvNCKFSs0efJkp+dGjhzJvf8AAAAAIJcsfQqwJE2dOlVBQUF65513tHHjRo0cOVLNmjXLuT8gAADnTZw40emZa665RvXr17chDQAAAAB4J0sLQIfDkfN30zS1bNkyLVu2LNfzhmEoMzPTykgAAA+VnZ2thQsXOj13//33c/YfAAAAADjB0gLQNM0r/jcAAOd98cUXTv/S56abbtJdd91lUyIAAAAA8E6WFoAtW7bkrAwAwFVt2bJFzz33nNNzzz33HP/OAAAAAICTLC0AnbncFwDguyZMmOD0WeLR0dGqUaOGTYkAAAAAwHtZ+hRgAACu5uzZs5o3b57Tc4MHD5afH/9sAQAAAICz+EkKAJCvli9froyMDKdmmjRpokGDBtmUCAAAAAC8GwUgACDf/PXXXxo+fLjTc++9954CAgJsSAQAAAAA3o8CEACQb8aPH6/4+HinZqKiohQdHW1TIgAAAADwfi49BGTw4MGSJMMw9OWXX170uqv+ux4AwHukpqZq5syZTs8NGDCAe/8BAAAAQB64VABOnjxZhmFI0gWF3b9fdxUFIAB4p127dik5OdmpmSpVqmjIkCE2JQIAAAAA3+BSAShJpmlesuwzTdPlMHktDwEAnik9PV3PPPOM03OTJ09WeHi4DYkAAAAAwHe4VAAeOHDAqdcBAL7t008/1aZNm5yaiYyMVPXq1W1KBAAAAAC+w6UCsGLFik69DgDwXVlZWZo4caLTc/369ePefwAAAABgAZcvAc4vcXFx2r59uySpZcuWbk4DAHDWli1bdOTIEadmQkJCuPcfAAAAAFjE4wvAFStWqEePHvLz81NmZqa74wAAnPTDDz84PTNp0iSVL1/ehjQAAAAA4HsKzLVVeXm4CADAPWJiYvTxxx87NVO4cGG1bdvWpkQAAAAA4HsKTAEIACh43nzzTWVnZzs106FDB5vSAAAAAIBvogAEANjijz/+0Jo1a5yeGzx4sA1pAAAAAMB3UQACAGyxYcMGp2eGDh2qxo0b25AGAAAAAHwXBSAAwHKpqakaN26cUzOhoaEaPXq0TYkAAAAAwHdRAAIALPfKK6/owIEDTs3Uq1dPfn78swQAAAAAVuMnLQCApRITEzVjxgyn5/r3729DGgAAAAAABSAAwFILFy5UamqqUzNVqlRRly5dbEoEAAAAAL6NAhAAYClnn/zr7++v6dOnKygoyKZEAAAAAODbKAABAJbZsGGDpk+f7tRMrVq1FB0dbVMiAAAAAAAFIADAEqZp6vHHH1dmZqZTc61bt7YnEAAAAABAEgUgAMAi69ev1/bt252a8fPz08CBA21KBAAAAACQKAABABZZtmyZ0zOPPvqoypcvb30YAAAAAEAOCkAAQJ6ZpqklS5Y4NVOhQgU9/vjjNiUCAAAAAJzn7+4AV1OhQgUuDwMAD/fxxx9r06ZNTs00atRIhmHYlAgAAAAAcJ7HF4D169fXpEmT3B0DAHAZycnJGjt2rNNz3bt3tz4MAAAAAOAiXAIMAMiT2bNnKyUlxamZSpUq6aabbrIpEQAAAADg3yw9A7BKlSouzfn5+alw4cIqWrSo6tatqzZt2ujWW2+Vnx/9JAB4uo0bNzq1fUBAgL744gs5HA6bEgEAAAAA/s3SAvDgwYMyDEOmaea89u/7O5mmedF//3e7ZcuWady4capQoYI+++wzzhABAA+WmpqqX3/91amZ1q1bq27dujYlAgAAAAD8l6Wn2FWoUEEVKlRQuXLlcgo90zRlmqYiIiJUrlw5RURE5Lwm/VP8lStXTmXLllVwcHDOe4cOHVLHjh01a9YsKyMCACw0atQoHT9+3KmZ6667zqY0AAAAAIBLsbQAPHjwoGJiYlSpUiWZpqnmzZtr9uzZiouLU1xcnA4fPpzz91mzZql58+YyTVOVKlXSunXrlJKSoq1bt2rYsGGSpOzsbA0ePFinT5+2MiYAwAL79u3TnDlznJoxDEN9+vSxKREAAAAA4FIsLQDT0tLUuXNnrVq1Ss8//7yWL1+uHj16qEiRIhdsV6RIEd12221avny5nn32WcXExKhz585KT09X7dq1NWHCBH344YeSpJSUFE2YMMHKmAAAC0ybNs3pme7du6tSpUrWhwEAAAAAXJalBeCECRO0ZcsWNW3aVC+//HKuZl599VU1bdpUW7ZsuaDoe/DBB1WvXj1J0i+//GJlTACABbZv3+7U9qVLl9a7775rUxoAAAAAwOVYWgDOmDHDpcu7+vTpI9M0NWPGjAte7969u0zT1O7du62MCQDIoxMnTmjdunVOzXTp0kVhYWE2JQIAAAAAXI6lBeDevXslSWXKlHFq7vz2e/bsueD1a665RpIUHx9vQToAgBVM09Tdd9+tlJQUp+bq1KljUyIAAAAAwJVYWgCe/2Hw6NGjTs39/fffkqTU1NQLXg8KCpIkBQcHW5AOAGCFmJgYrV+/3qmZ8PBwde3a1aZEAAAAAIArsbQALF++vCRddCnv1ZzfPioq6oLXT506JUkqVqyYBekAAFZw5eEfw4cPV2hoqA1pAAAAAABXY2kBePPNN8s0Ta1bt07PPvtsrmaeeeYZrV27VoZh6JZbbrngva1bt0py/pJiAIB9/vzzT6e2b9iwoUaMGGFTGgAAAADA1VhaAD722GM5Z3i8+eabatmypebMmaO4uLgLtouLi9Ps2bPVokULvfXWW5KkkJAQPfrooxdst2DBAhmGocaNG1sZEwDgor/++kt//PGHUzMdO3aUYRg2JQIAAAAAXI2/lYtVqFBBkyZNUr9+/ZSVlaWYmBjFxMRI+uf+TyEhIUpNTVViYmLOjGma8vf31+TJk1WhQoWc15cvX64TJ04oJCRE3bp1szImAMAFGRkZ6tevn9LS0pyau+6662xKBAAAAADIDUsLQEm6/fbbVbx4cQ0dOlT79+/PeT0hIUGJiYkyTfOC7aOjo/XFF1+oVatWF7zesmVLJScnWx0PAOCin3/+Wbt27XJqplKlSmrZsqVNiQAAAAAAuWF5AShJrVu31h9//KHvv/9e3333ndavX6+jR48qJSVFoaGhKlu2rBo1aqRu3bqpW7ducjgcdsQAAFho6tSpTs8888wz8vOz9G4TAAAAAAAn2VIASpLD4VCPHj3Uo0cPu3YBAMhHzj78o3v37vwbAAAAAAAegNMyAABX9ffff+v48eNOzbRp08amNAAAAAAAZ1AAAgCuKC0tTX379lVGRoZTc7Vq1bIpEQAAAADAGRSAAIArmjdvnnbs2OHUTL169VS3bl2bEgEAAAAAnGHbPQC3bNmiBQsWaPv27YqPj9e5c+euOmMYhpYsWWJXJACAC7766iuntjcMQ08++aRNaQAAAAAAzrK8APz77781aNAg/fLLL07NmaYpwzCsjgMAyKPt27c7tf3QoUPVvn17m9IAAAAAAJxlaQGYnJysNm3aaM+ePTJN08qlAQBukJSUpLNnzzo106pVK5vSAAAAAABcYek9AN977z39+eefkqSoqCh98skn2rt3r86dO6fs7Oyr/snKyrIyDgAgDzIzMzVgwABlZ2c7NRcdHW1TIgAAAACAKyw9A3Du3LmSpNKlS2v9+vUqVaqUlcsjjxwOh7sj2MJbvy7kr/OfIz5P/2fu3LlauXKlUzPNmjVT9erVbUpUMPGZghU4RsEufKZgBY5RsBOfK+QVx6h/GKaF1+pGREQoOTlZr7zyip599lmrlgUAuEHz5s0VExPj1MyCBQt0yy232JQIAAAAAOAKS88APH+ZGGd/eKb4+Hh3R7BMeHi4HA6HsrKylJiY6O448AIOh0Ph4eFKTEzkdgSS0tPTnS7/RowYoSZNmnjVscZVHKNgNY5RsBLHKFiNYxSsxnEKVvLGY1RkZKTTM5YWgBUrVtSuXbuUlJRk5bKwiLd80P/LW78uuEdWVhafKUmpqalOz3To0IH/7S6B/01gJY5RsBqfJ1iJYxTswGcKVvH1Y5SlDwHp2rWrTNN0+qwRAIDnME1To0ePdnquTJkyNqQBAAAAAOSVpQXg8OHDFRkZqWnTpmn37t1WLg0AyCe//PKLvvzyS6dmmjRpovLly9uUCAAAAACQF5YWgGXKlNHXX38tf39/3XTTTVq+fLmVywMA8sHnn3/u9Mx9991nQxIAAAAAgBUsvQfgK6+8Iklq37695s2bpzZt2qhevXpq1qyZihcvLj+/q/eNL7zwgpWRAABOSEhI0LJly5yaGTJkiDp37mxPIAAAAABAnllaAL700ksyDEOSZBiGTNPUli1btGXLllyvQQEIAO4TFxfn9MzQoUNtSAIAAAAAsIqlBaD0z83jr/TfV3K+PAQAuMfmzZudngkPD7chCQAAAADAKpYWgEuXLrVyOQBAPtq9e7dGjBjh1EytWrVUokQJmxIBAAAAAKxgaQHYqlUrK5cDAOSjDz74QOfOnXNqZsiQIZy9DQAAAAAeztKnAAMACqaEhATNmzfPqZmWLVuqT58+NiUCAAAAAFiFAhAAoP379ys9Pd2pmU8//VQBAQE2JQIAAAAAWIUCEACg1NRUp2dCQkJsSAIAAAAAsJpL9wCMjY3N+XuFChUu+bqr/r0eAMB+Z8+e1auvvurUTFRUFAUgAAAAABQQLhWAlStXliQZhqHMzMyc1ytVqpSnm8H/dz0AgP3Gjx+vjRs3OjVz11138fAPAAAAACggXCoATdN06T0AgGfJyMjQ5MmTnZopUaKEBgwYYE8gAAAAAIDlXCoABw4c6NTrAADPtGHDBp04cSLX2xuGoRkzZqh48eI2pgIAAAAAWMmlAnDSpElOvQ4A8Exnzpxxant/f3/VrVvXnjAAAAAAAFvwFGAA8GF//vmnU9tHRETYlAQAAAAAYBcKQADwURs2bNBbb73l1EyHDh1sSgMAAAAAsAsFIAD4qNGjRysjI8OpmcGDB9uUBgAAAABgFwpAAPBBe/fu1cqVK52aefjhh7n/HwAAAAAUQC49BORqsrKyNH/+fC1YsEDbt29XfHy8zp07d9U5wzC0b98+OyIBAP5l06ZNTm1fpEgRPffcczalAQAAAADYyfICcOfOnerdu7d27tx5weumaV511jAMq+MAAC4hPT3dqe1DQ0M5RgMAAABAAWVpAXjy5Em1a9dOJ06cyCn8/P39Vbx4cQUFBVm5KwCAi7Kzs/Xjjz86NVOhQgWb0gAAAAAA7GZpATh27FgdP35chmGoXr16euONN9SmTRsFBgZauRsAQB58/PHHWrx4sVMzffv2tSkNAAAAAMBulhaA588oueaaa7Ry5UqFhIRYuTwAII/S0tL00UcfOTUTFRWl7t272xMIAAAAAGA7S58CfOjQIRmGoXvuuYfyDwA80KJFi3Tq1Klcbx8YGKhp06apUKFCNqYCAAAAANjJ0gIwICBAklSpUiUrlwUAWOTAgQNObR8dHa2aNWvalAYAAAAAkB8sLQCrVKkiSYqLi7NyWQCARbKyspzanjP/AAAAAKDgs7QA7Nmzp0zTdPrm8gAA+yUlJembb75xaqZu3bo2pQEAAAAA5BdLC8AHH3xQ5cuX15w5cxQTE2Pl0gCAPHrqqae0d+9ep2YGDBhgUxoAAAAAQH6xtACMiIjQd999p+LFi+vWW2/VV199pezsbCt3AQBwwbFjxzR79mynZnr06KHatWvblAgAAAAAkF/8XRkaPHjwFd+vVauWfv31Vw0aNEiPP/64GjVqpOLFi8vP78p9o2EY+vLLL12JBAC4grlz5zp1/79y5cpp3LhxNiYCAAAAAOQXlwrAyZMnyzCMK25z/v1Tp05pwYIFuV6bAhAArHfkyBGntq9atSoPAAEAAAAAL+FSAShJpmlamUOSrloqAgBcw9N/AQAAAMB3uVQAHjhwwOocAACbHDt2TN9//71TM02bNrUpDQAAAAAgv7lUAFasWNHqHAAAmzzwwAM6ceJErrcPDg5Wnz59bEwEAAAAAMhPlj4FGADgWbZv364VK1Y4NfPUU0+paNGiNiUCAAAAAOQ3CkAA8GKzZ892avumTZvqgQcesCkNAAAAAMAdXH4ISF7MnTtXK1asUGZmpurVq6c+ffooJCTEHVEAwKv9/fffTm1foUIFHsgEAAAAAF7G0gJwz549evTRRyVJzz//vBo1anTB++np6br11lv166+/XvD6m2++qYULF6py5cpWxgEAn+fn59yJ3sHBwTYlAQAAAAC4i6WXAM+cOVM//PCDVq5cqbp16170/ujRo7VkyRKZpnnBn71796pHjx7Kzs62Mg4A+LRjx45p2bJlTs3ccMMN9oQBAAAAALiNpQVgTEyMJKl9+/YKDAy84L20tDSNGzdOhmEoIiJC7733nr777jt16tRJkrRt2zZ9++23VsYBAJ9lmqaGDBmikydP5nqmePHi6ty5s42pAAAAAADuYGkBGBsbK8Mw1LBhw4veW7RokRITEyVJX375pUaMGKGuXbtq3rx5io6OliTNmjXLyjgA4LM2bNigdevWOTXz2muvKSgoyKZEAAAAAAB3sbQAPHXqlCQpKirqovfOX4ZWtGhR9ejRI+d1h8Ohvn37yjRNbd682co4AOCzvv76a6e2v+2229SzZ0+b0gAAAAAA3MnSAjA+Pl6SLrr8V5JWrVolwzDUrl27i54wWaVKFUn/3K8KAJB3sbGxTm1funRpm5IAAAAAANzN0gLw/NMj/3vPqbNnz2rTpk2SLn2D+bCwMEn/PCUYAJB3/v7OPeQ9ICDApiQAAAAAAHeztAA8f+nvxo0bL3h94cKFysjIkHTpAvD8mYOFCxe2Mg4A+KTExETt3r3bqZlGjRrZlAYAAAAA4G6WFoDNmjWTaZqaNWuW/vrrL0lSZmam3n33XUn/3P+vQYMGF83t2rVLklShQgUr4wCAzzFNU/fcc0/OMTg3oqKi1L59extTAQAAAADcydICcNCgQZKkpKQk1atXT3369FHdunW1cuVKGYahAQMGyM/v4l2uWLFChmHouuuuszIOAPicDRs2aMmSJU7NvPjii3I4HDYlAgAAAAC4m6UFYPPmzXXPPffINE3FxcXp22+/zbkMLSoqSs8+++xFM/v378+5ZPhSlwcDAHLvq6++cmr7YcOGqXv37vaEAQAAAAB4BEsLQEn65JNP9P7776tWrVoKDAxUZGSk+vTpo5UrV6po0aIXbf/xxx/n/P3mm2+2Og4A+JTzt1TIrfP3bgUAAAAAeC/nHhOZC4Zh6OGHH9bDDz+cq+0fe+wxDR8+XIZhcA9AAMgj0zRt3R4AAAAAUPBYXgA6q3Tp0u6OAABewTTNnCeu51bVqlVtSgMAAAAA8BSWXwIMAHCPV1991alLgMuWLau2bdvamAgAAAAA4AkoAAHAC+zevVsffvihUzOjRo2Sv7/bTwQHAAAAANjMpZ/8/v2UyQEDBlzydVf9ez0AQO5MmjTJqe2HDh2qgQMH2pQGAAAAAOBJXCoA7777bhmGIcMwLijszr/uqv+uBwDInWXLljm1fZMmTfJ0vAYAAAAAFBwuX/t1uSdH8kRJAMh/KSkptm4PAAAAACi4XCoAL3epmbOXoAEArBEeHq7jx4/nevsSJUrYmAYAAAAA4ElcKgDPXzb236dHcj8pAMh/a9as0aFDh3K9fWRkpFq2bGljIgAAAACAJ8nTPQDnzp2rqKionNcHDx4sSXr44YdVr149SwICAC7v9OnTGjBggNLT03M9M2DAAAUHB9uYCgAAAADgSfysXGzy5MmaMmWKYmNjrVwWAHAZ06ZNU3x8fK63b9asmR577DEbEwEAAAAAPI1LBaC//z8nDqalpVkaBgDgnBkzZji1/WuvvcbZfwAAAADgY1wqAIsWLSpJ2r17t6VhAADOcebef5KcelAIAAAAAMA7uHQPwPr162vhwoX68MMPVa1aNdWvX/+CM0pOnDjh8mXAFSpUcGkOAHxRQECAMjIynNoeAAAAAOBbXCoABw0apIULF+r06dPq16/fBe+Zpql7773XpTCGYSgzM9OlWQDwNZmZmSpSpIhSU1NztX1AQIBq1aplcyoAAAAAgKdx6RLgO+64Qw888IBM07zgz3n/fd2ZPwCAqzNNUyNGjNDRo0dzPdOlSxeVKFHCxlQAAAAAAE/k0hmAkjR+/HgNHTpUP/74ow4fPqy0tDRNmTJFhmGodevWXMoLADb65Zdf9M033+R6+7CwMD366KM2JgIAAAAAeCqXC0BJqlevnurVq5fz31OmTJEkjRgxQl27ds1TMADA5X355Ze53tbPz08zZsxQtWrVbEwEAAAAAPBULl0CDABwn/T0dC1btizX22dnZ6tYsWL2BQIAAAAAeLQ8nQH4X0uXLpUk1a5d28plAQD/kpKSouzsbKdmEhMTbUoDAAAAAPB0lhaArVq1snI5AMAlFC5cWP7+/k49NT0yMtLGRAAAAAAAT8YlwABQwBw9elTBwcG53r5mzZqqXLmyjYkAAAAAAJ6MAhAACpCEhAT17NlTycnJuZ4ZMmSIDMOwMRUAAAAAwJNRAAJAAfLFF1/o4MGDud6+U6dOuvPOO+0LBAAAAADweBSAAFBAZGVl6auvvsr19oULF9bnn38uh8NhYyoAAAAAgKejAASAAuLo0aM6evRorrdPSkpSXFycjYkAAAAAAAUBBSAAFBDp6en5MgMAAAAA8C4UgABQQJQqVUr+/v653j4oKEglSpSwMREAAAAAoCCgAASAAmLHjh1OPc23W7duKlSokI2JAAAAAAAFAQUgABQA+/btU9++fZWRkZGr7R0Oh+655x6bUwEAAAAACgIKQAAoAD744AMlJSXlalvDMPTuu++qbt26NqcCAAAAABQEFIAA4OESExM1d+7cXG8fFRWlfv362ZgIAAAAAFCQUAACgIfbs2ePzp49m+vtDx8+zNN/AQAAAAA5KAABwMNlZWXlywwAAAAAwDtRAAKAh6tYsaJTT/8tU6YMT/8FAAAAAOSgAAQAD7dnzx45HI5cb3/nnXfamAYAAAAAUNBQAAKAB9uxY4fuvPNOZWZm5mr7iIgIDRw40OZUAAAAAICChAIQADzY2LFjlZqamqttCxUqpP/9738qXbq0zakAAAAAAAUJBSAAeKhjx45pwYIFud6+Tp06atasmY2JAAAAAAAFEQUgAHiorVu3Kjs7O9fb//HHHzamAQAAAAAUVBSAAOChcnvfv/MyMjJsSgIAAAAAKMgoAAHAQ1WsWNGp7StVqmRPEAAAAABAgUYBCAAeyjAMBQYG5nr7vn372pgGAAAAAFBQUQACgAc6cOCAevToofT09FxtX6JECQpAAAAAAMAlUQACgAd6+eWXFRcXl6ttCxcurKlTpyoiIsLmVAAAAACAgogCEAA8zNGjR7VgwYJcb9+xY0c1aNDAxkQAAAAAgIKMAhAAPExMTIyys7Nzvf3vv/9uYxoAAAAAQEFHAQgAHiY1NdXW7QEAAAAAvoUCEAA8TIkSJWzdHgAAAADgWygAAcDDNG7cWEFBQbnevkePHjamAQAAAAAUdP7uDpDfEhISNGvWLK1bt06nT59WUFCQoqOj1alTJzVt2tTp9VJTU7V27Vpt2bJFe/fu1YkTJ5Sdna3IyEjVqFFDHTt2VK1atS47//777+vXX3+94j4qVKig8ePHO50NQMGTkpKiAQMGKC0tLVfbFy5cWH369LE5FQAAAPD/2rvz6Crrc1/gz84ESZgCoigooteqiEVFLdaJCqceBac6Mqko3N7TOqBtta3WWrFWTz22HsfVoxa54FTEgeq1TlVbL4gz4lBHChQVwhAghECSff/gkgOVwA7sAfb+fNbqMsnv2e/+7jT8Vvjy7vcFtmcFVQDOmTMnrrjiiqipqYmIiPLy8qitrY233nor3nrrrTjhhBNizJgxrTrmJZdcEp9//nnz52VlZVFUVBQLFiyIBQsWxEsvvRSnnHJKjBo1apPHKSsri4qKio2udejQoVWZgO3X1VdfHa+++mpKs2VlZfFf//Vf0alTp8yGAgAAYLtWMAXgmjVr4tprr42ampro2bNnXHrppdGrV6+or6+Pxx57LCZNmhRTp06NXr16xaBBg1I+bmNjY+y+++7x7W9/O/r16xc777xzJJPJmD9/fkyYMCGmTZsWjzzySHTr1i2OO+64Fo9zxBFHxNixY9PwSoHt1ZIlS+KBBx5Ief6SSy6JgQMHZjARAAAA+aBgrgH4pz/9Kb744oto06ZNXHXVVdGrV6+IiGjTpk2cccYZzeXcxIkTo6GhIeXjjh07Nv7zP/8zhgwZEjvvvHNERCQSiejevXtcfvnlsf/++0dExCOPPJLmVwTkmyeffDJWrVqV8vzMmTMzmAYAAIB8UTAF4AsvvBAREUcdddRG75h56qmnRiKRiMWLF8c777yT8nH79OnT4lpRUVEcc8wxERHxxRdfxIoVK1oXGigoX3zxRavm17/8AAAAALSkIArAurq6+OijjyIi4qCDDtroTNeuXaNHjx4REfH222+n7bnXv35fY2Nj2o4L5J/y8vKMzgMAAFCYCuIagPPmzYtkMhkRET179mxxrmfPnjF37tyYO3du2p571qxZERHRqVOnTd7MY+bMmfHd7343Fi5cGGVlZbHzzjtHv379YvDgwVFVVZW2PMC26/DDD8/oPAAAAIWpIM4AXLx4cfPHnTt3bnFu3dqSJUvS8rzV1dXx1FNPRUTEwIEDI5FIbHJ2wYIF0bZt21i1alV88skn8dBDD8UFF1yQ1jMSgW3Xe++9t8l9Yn3FxcUxcuTIDCcCAAAgHxTEGYDrX1S/TZs2Lc6tW6urq9vq52xoaIgbb7wx6urqYscdd4zTTjtto3N77rlnfO1rX4tDDjkkunTpEkVFRbFy5cqYMWNGjB8/PhYvXhzXXXdd3HTTTdG9e/dNPufEiRPjvvvua3F96NChMWzYsK16XduKoqKi5v86Q5J0WFe8dezYsfmM4WyaMmVKXHTRRSnP/+xnP4v99tsvg4nYGvYo0i3XexT5xR5FutmjSDf7FOlkj1qrIArAbEsmk3HrrbfGe++9F2VlZfHDH/4wKisrNzp7wgknfOVrFRUVMWDAgOjdu3eMHTs2VqxYEffff3/88Ic/3OTz1tbWxoIFC1pcX7lyZRQXF7fuxWzjEolE3r0mcmvdLxvZ1NDQED/4wQ9Snr/sssviqquuSvlsQXLHHkW65WKPIn/Zo0g3exTpZp8inQp9jyqIArBt27bNH9fX10dFRcVG5+rr6yNi6y+s/7vf/S6ef/75KC4ujssuuyz22WefLTrOjjvuGIMHD44HH3wwXnvttWhqatrkD2xlZWXsuOOOLa5XVFTkzY1IioqKIpFIRDKZjKamplzHIQ8kEokoKiqKpqamrP+r0NSpU1t17dEdd9zRz/02zh5FuuVyjyL/2KNIN3sU6WafIp3ycY/akmK8IArA9a/7t3jx4hYLwHXXCtyaU4zvueeeeOKJJ6KoqCguvfTSOPTQQ7f4WBERX/va1yJi7dl7y5cvj44dO7Y4O2LEiBgxYkSL69XV1Wm7vmGuVVVVRXFxcTQ1NeXNayK3iouLo6qqKmpqarJelD///POtmv/zn/8c55xzTobSkA72KNItl3sU+cceRbrZo0g3+xTplI971A477NDqxxTE+Y89evRofqvcnDlzWpxbt7brrrtu0fNMmDAhHn300UgkEnHhhRfGkUceuUXHAQrL+tcpTcXq1aszlAQAAIB8VBAFYHl5eey1114REfHGG29sdKa6urr5LXh9+/Zt9XPcd999MXny5IiI+F//63/FwIEDtzDthj788MOIWPsa2rdvn5ZjAtuWzd3gZ2vnAQAAKGwFUQBGRAwYMCAiIl566aVYuHDhV9anTJkSyWQyOnfuHPvvv3+rjj158uR44IEHIiLi/PPPj+OOOy6lx23uvecLFy6MJ598MiIiDj744IK/YCXkqxNOOKFVf77PPPPMDKYBAAAg3xRMo3TsscdGt27dYtWqVTFu3Lj47LPPImLtjT8mT54cTzzxRESsvY5eScmGl0YcPXp0nHjiifHb3/72K8d9/PHHY8KECRERcc4558RJJ52UcqYXXnghfvWrX8X06dNj2bJlzV+vq6uLF198MS6//PJYvnx5lJeXx9ChQ1v7koHtQF1dXfzwhz9M+eLGhxxySPTr1y/DqQAAAMgnBXETkIiI0tLSuPLKK+OKK66I2bNnx8UXXxwVFRWxatWq5r94DxkyJAYNGtSq4959990RsfauMo899lg89thjLc7+5Cc/iX333bf586amppg2bVpMmzYtIta+zbekpCRqa2ubM3Xs2DF+9KMfRY8ePVqVC9g+XHbZZfHCCy+kNNuzZ8+46667mq9pCgAAAKkomAIwImK33XaLW265JR5++OGYMWNGVFdXR2VlZeyxxx4xePDg6N+/f6uPue5tvMlkMpYuXbrJ2YaGhg0+33///WPEiBHx/vvvxz/+8Y9YtmxZrFy5MiorK2PXXXeNgw8+OI499ljX/oM8NXfu3HjooYdSmk0kEjFhwoTYZZddMpwKAACAfFNQBWBERKdOneL888+P888/P+XH3HXXXS2uPf7441ucZccdd4wzzjhjix8PbN8eeOCBlN/6m0wm47nnnovevXtnOBUAAAD5pmCuAQiwrfn4448zOg8AAAARCkCAnCkuLm7VvDuBAwAAsCX8bRIgR/r06ZPReQAAAIhQAALkzKBBg1I+q6+ioiJOP/30DCcCAAAgHykAAXJg/vz5MXz48JRvAnLRRRdFhw4dMpwKAACAfKQABMiyZDIZo0aNitmzZ6c0f95558Wll16a2VAAAADkLQUgQJZNmzYt3njjjZRmS0tL47LLLotEIpHhVAAAAOQrBSBAlj344IMpz65ZsyYef/zxDKYBAAAg3ykAAbJs7ty5GZ0HAACA9SkAAbKstLS0VfNlZWUZSgIAAEAhUAACZNkhhxzSqvmDDz44Q0kAAAAoBApAgCw77rjjUr6pR8+ePeNb3/pWhhMBAACQzxSAAFn097//PUaOHBnJZDKl+auvvjqKi4sznAoAAIB8pgAEyJLGxsYYOXJkSjf1KCoqiptvvjmGDBmShWQAAADkMwUgQJY8++yz8f7776c026lTpzjttNMynAgAAIBCoAAEyJL77rsv5dnFixfHs88+m8E0AAAAFAoFIECWzJ49u1Xzf//73zMTBAAAgIKiAATIktbezMPNPwAAAEgHBSBAlhx00EGtmj/wwAMzlAQAAIBCogAEyJLhw4enPLvffvvFwQcfnME0AAAAFAoFIEAWLF26NH72s5+lNFtUVBRXXnllJBKJDKcCAACgECgAATKsqakpzj333HjllVc2O1tSUhK33nprDBo0KAvJAAAAKAQKQIAMe/755+Pll19OabZv375x+umnZzgRAAAAhUQBCJBh9957b8qzr7/+enz88ccZTAMAAEChUQACZNjMmTMzOg8AAACbogAEyLCGhoZWzTc2NmYoCQAAAIVIAQiQYb169croPAAAAGyKAhAgw4YPH57y7N577x39+vXLYBoAAAAKjQIQIMNqa2ujqCi17fbiiy+ORCKR4UQAAAAUEgUgQAbdfPPN8ZOf/CSampo2O3vJJZfE6aefnoVUAAAAFBIFIECGzJo1K6699tqUZk8//fT46U9/muFEAAAAFCIFIECG3HPPPSnPTps2zd1/AQAAyAgFIECGPPHEEynPzps3L95+++0MpgEAAKBQKQABMiCZTMbixYtb9ZjWzgMAAEAqFIAAGZBIJKJDhw6tekxr5wEAACAVCkCADPmXf/mXlGe7du0aBxxwQObCAAAAULAUgAAZcs4556Q8O3LkyCgrK8tgGgAAAAqVAhAgA7788sv42c9+ltLs/vvvHxdeeGGGEwEAAFCoFIAAabZy5co488wzU7qr79FHHx1TpkyJdu3aZSEZAAAAhUgBCJBm999/f7z77rspzX7961+PTp06ZTYQAAAABU0BCJBm48ePT3l20qRJUV9fn7kwAAAAFDwFIEAarVixIj744IOU5xcvXhyffvppBhMBAABQ6BSAAGm0evXqrDwGAAAAUqUABEijjh07tuqGHolEInbZZZcMJgIAAKDQKQAB0qi4uDhOP/30lOcHDRoUXbt2zWAiAAAACp0CECDNTjnllCguLk5p9vvf/36G0wAAAFDoFIAAafT666/HueeeG42NjZudHTduXBx++OFZSAUAAEAhK8l1AIB8MW/evBg6dGgsWbJkk3MlJSXxm9/8Js4666wsJQMAAKCQOQMQIE3uvPPOzZZ/ERENDQ0xe/bszAcCAACAUAACpEV9fX3cf//9Kc9PmDAhmpqaMpgIAAAA1lIAAqTBvHnzYtmyZSnPL1y4MBYsWJDBRAAAALCWAhAgDZLJZFYeAwAAAK2lAARIg1122SXKy8tTnu/YsWN07do1g4kAAABgLQUgQBpUVFTEd77znZTnzzrrrCgpcSN2AAAAMk8BCJAmQ4cOTanUa9euXYwZMyYLiQAAAEABCJAWr732Wpx99tnR0NCwybnKysqYMGFC9OzZM0vJAAAAKHTefwawlT777LM466yzoqamZpNznTp1ikcffTT222+/LCUDAAAAZwACbLXf/va3my3/IiKWLl0ab7zxRhYSAQAAwH9TAAJshWXLlsWUKVNSnh8/fnzmwgAAAMBGKAABtsIHH3wQq1atSnl+5syZm71OIAAAAKSTAhBgK2xJmdfU1JSBJAAAALBxCkCArdDau/nusssuUVZWlqE0AAAA8FUKQICt0L179xgwYEDK88OGDctcGAAAANgIBSDAVrrwwgtTmuvQoUOcc845GU4DAAAAG1IAAmyFL7/8Mm666abNzlVWVsaECROiW7duWUgFAAAA/60k1wEAtldLliyJk08+OT7++ONNzu29995x9913x957752lZAAAAPDfnAEIsIV+/etfb7b8i4j429/+FmvWrMlCIgAAAPgqBSDAFlixYkU88MADKc/fc889GUwDAAAALVMAAmyBGTNmxPLly1Oef/bZZzOYBgAAAFqmAATYAsuWLcvoPAAAAKSLAhBgC3Tp0iWj8wAAAJAuCkCALXDooYdG165dU54fMmRIBtMAAABAyxSAAFugTZs2cfbZZ6c0W1xcHOeee25mAwEAAEALFIAAW+jggw+OTp06bXbuuuuui169emU+EAAAAGyEAhBgC9x0000xdOjQWLp0aYszXbt2jTvuuCPOO++87AUDAACAf6IABGilyZMnx69+9avNznXv3j1OOeWULCQCAACAlikAAVohmUzGjTfemNLsW2+9Fc8//3yGEwEAAMCmKQABWmHatGnxySefpDz/v//3/85gGgAAANg8BSBAK3z44YcZnQcAAIB0UwACtEIikcjoPAAAAKSbAhCgFfbdd99Wze+zzz4ZSgIAAACpUQACtMIhhxzSqlLvnHPOyWAaAAAA2DwFIEArJBKJuOyyy1Ka/cY3vhFHHXVUhhMBAADApikAAVph1apVMXPmzKioqNjk3AEHHBD33ntvFBXZZgEAAMitklwHANhe1NXVxdChQ+Pll19ucaa4uDjGjh0bY8eOjbZt22YxHQAAAGycU1MAUnTNNddssvyLiGhsbIzHH388SktLs5QKAAAANk0BCJCCmpqamDRpUkqzH330UTz33HMZTgQAAACpUQACpGDq1KlRV1eX8vxDDz2UwTQAAACQOgUgQArmz5+f0XkAAADIFAUgQAratGnTqvmysrIMJQEAAIDWUQACpKB///4ZnQcAAIBMUQACpODQQw+N3r17pzRbVFQUZ599doYTAQAAQGoUgAApSCQSce2110ZJSclmZy+++OLYZZddspAKAAAANk8BCJCClStXxosvvhht27bd5NwFF1wQP/7xj7OUCgAAADZv86eyABS4FStWxOmnnx6vvfZaizMdO3aMe++9Nw4//PAsJgMAAIDNcwYgwGZcdtllmyz/IiJqamrixhtvzFIiAAAASJ0CEGAT5s+fH1OmTElp9q9//Wu8/fbbGU4EAAAAraMABNiEhx9+OBobG1Oef+CBBzKYBgAAAFpPAQiwCXPnzm3V/Lx58zKUBAAAALaMAhBgE9q0adOq+bKysgwlAQAAgC2jAATYhIMPPrhV84ccckiGkgAAAMCWKcl1ALKnuLg41xEyIl9fF9m17ufon3+ehgwZEjvttFN8+eWXmz1GeXl5DB8+3M8kG/DzQDq0tEfB1vIzRTrYo8gkP1dsLXvUWolkMpnMdQiAbdmkSZNixIgRm5274YYb4rLLLstCIgAAAEidMwALyJIlS3IdIW06dOgQxcXF0djYGMuWLct1HPJAcXFxdOjQIZYtW7bBXX+TyWRUVFREnz59YtasWS0+/kc/+lGMHj06r/6cseXsUaRbS3sUbAl7FOlmjyLd7FOkUz7uUVVVVa1+jAKwgOTLD/o/y9fXRW40NjY2/0w1NTXF5ZdfHuPHj29xfv/9949bb701evfuHU1NTVlKyfbEHkU6rb9HQTr4eSKd7FFkgp8p0qXQ9yg3AQFowa9+9atNln8REe+88048//zz2QkEAAAAW0ABCLAR1dXVcfvtt6c0e9NNN8WKFSsynAgAAAC2jAIQYCMeeOCBWL16dUqzy5cvj0ceeSTDiQAAAGDLKAABNmLmzJmtmn/nnXcylAQAAAC2jgIQYCNae3HYQr6YLAAAANs2BSDARuyxxx4ZnQcAAIBsUQACbMTQoUNTni0tLY3TTjstg2kAAABgyykAATZijz32iFNOOSWl2WHDhsVOO+2U4UQAAACwZRSAAC246aab4oADDtjkzDHHHBO//OUvsxMIAAAAtoACEGAjPvrooxg1alS89dZbG13v1atXXHfddTFx4sRo06ZNdsMBAABAK5TkOgDAtmbWrFlx8sknR01NTYszbdu2jTPOOCNKS0uzmAwAAABazxmAAOtpaGiIUaNGbbL8i4h4//3348c//nGWUgEAAMCWUwACrOfpp5+O2bNnpzT76KOPxhdffJHZQAAAALCVFIAA65k8eXLKsw0NDfH4449nMA0AAABsPQUgwHoWLFiQ0XkAAADINgUgwHrKy8tbNV9RUZGhJAAAAJAeCkCA9Rx11FGtmj/yyCMzlAQAAADSQwEIsJ7hw4dH27ZtU5rt06dPHHzwwRlOBAAAAFtHAQiwns6dO8dVV1212bk2bdrEDTfcEIlEIgupAAAAYMspAAH+yahRo2LYsGFRVLTxLbJz585x3333xaGHHprlZAAAANB6JbkOALAtefLJJ+Oyyy6L+fPnf2Wtc+fOMXbs2Dj77LOjsrIyB+kAAACg9ZwBCPD/PfjggzFy5MiNln8REYsXL47x48dHXV1dlpMBAADAllMAAsTacu+8886LZDK5yblPP/00fv7zn2cpFQAAAGw9BSBAREyaNClWrlyZ0uyjjz4a1dXVGU4EAAAA6aEABIiIJ554IuXZ1atXx7PPPpvBNAAAAJA+CkCAiFiyZEmr5pcuXZqZIAAAAJBmCkCAiOjQoUNG5wEAACBXFIAAEfGv//qvKc+WlJTEMccck8E0AAAAkD4KQICIGDlyZJSVlaU0O3jw4OjWrVuGEwEAAEB6KAABImLHHXeMW2+9dbNzu+yyS1xzzTVZSAQAAADpoQAE+P/GjBkTP/nJT6K8vHyj6/369YupU6fGLrvskuVkAAAAsOVKch0AYFswffr0uOaaa2L69OkbfL20tDT69OkT48aNi0MPPTQSiUSOEgIAAMCWcQYgUPCeeeaZOPnkk79S/kVErFmzJt588824/fbbo7GxMQfpAAAAYOsoAIGCVl1dHWPGjInVq1dvcu7JJ5+MO+64I0upAAAAIH0UgEBBmzhxYtTW1qY0e9ddd0VDQ0OGEwEAAEB6KQCBgjZlypSUZ+fPn7/RtwkDAADAtkwBCBS0L7/8slXzX3zxRYaSAAAAQGYoAIGC1rZt21bNl5eXZygJAAAAZIYCEChoRxxxRMqzpaWlceihh2YwDQAAAKSfAhAoaKNGjUp59oQTToiuXbtmMA0AAACknwIQKGgHH3xwDBs2bLNzXbp0iZ/+9KdZSAQAAADppQAECt5//Md/xLnnntvi+m677RaPPPJI9OzZM3uhAAAAIE1Kch0AIJfWrFkTf/zjH+Pjjz+O8vLyWL16dZSUlESHDh2id+/eMXz48Bg8eHCUlZXlOioAAABsEQUgULAWLVoUI0aMiNdee22Drzc2NsbChQvj3XffjZ49eyr/AAAA2K55CzBQkFavXh3Dhg37Svm3vurq6jjjjDPi008/zWIyAAAASC8FIFCQHnvssXjjjTc2O1dTUxO//e1vMx8IAAAAMkQBCBSk8ePHpzz7yCOPxNKlSzOWBQAAADJJAQgUnGQymdLZf+usWrUq3n333QwmAgAAgMxRAAIFJ5lMRkNDQ6se09p5AAAA2FYoAIGCU1RUFLvuumurHtPaeQAAANhWKACBgnTWWWelPNu/f//YY489MpgGAAAAMkcBCBSks88+O9q3b5/S7AUXXJDhNAAAAJA5CkCgIHXr1i3uvffeqKio2OTcT3/60zj22GOzlAoAAADSTwEIFKwjjzwyHnnkkRgwYEAUFxdvsNavX78YP358XHLJJTlKBwAAAOlRkusAALkwe/bsuP322+MPf/hDrFixIiIiSktL47DDDovRo0fHcccdl+OEAAAAkB4KQKDgvPLKKzFs2LBYtmzZBl9fs2ZNvPTSSzFjxoy4++6749vf/naOEgIAAED6eAswUFDmz58fw4cP/0r5t75Vq1bF+eefHx988EEWkwEAAEBmKACBgnLXXXdFTU3NZudWrVoVt912WxYSAQAAQGYpAIGC0dTUFPfff3/K848++mjz9QEBAABge6UABArG4sWLo7q6OuX5VatWxdy5czOYCAAAADJPAQgUjEQikZXHAAAAwLZEAQgUjKqqqth5551Tnq+srIzddtstg4kAAAAg8xSAQMEoKiqKESNGpDx/+umnR0VFRQYTAQAAQOYpAIGCMmrUqNhxxx03O9e+ffv43ve+l4VEAAAAkFkKQKCgdO3aNR588MFNloAdOnSIiRMnRq9evbKYDAAAADJDAQgUnD59+sSf//znGDt2bOy0007NX+/SpUtceOGF8eKLL8Y3v/nNHCYEAACA9CnJdQCAbKquro577703Jk6cGPPmzYuIiN122y3OOOOM+PGPfxxFRUXR2NiY45QAAACQPs4ABArGW2+9FUceeWRcf/31zeVfRMScOXPixhtvjAMPPDD+9re/5TAhAAAApJ8CECgI//jHP+LMM8+M6urqFmfmzp0bp556aixevDiLyQAAACCzFIBAQbjjjjtSKvbmz58f48ePz3wgAAAAyBIFIJD36uvr44EHHkh5fsKECZFMJjOYCAAAALJHAQjkvTlz5kRNTU3K8//4xz9i0aJFGUwEAAAA2aMABPLeltzV152AAQAAyBcKQCDv9ejRI9q0aZPyfMeOHaNLly4ZTAQAAADZowAE8l67du3ipJNOSnl+6NChUVJSksFEAAAAkD0KQKAg/Nu//VuUlZVtdq6ysjJGjx6dhUQAAACQHQpAoCD06dMn7rjjjigtLW1xpqKiIu69997o2bNnFpMBAABAZikAgYJx4oknxv/5P/8nTjzxxA3e4ltWVhZnnnlmzJgxI4455pgcJgQAAID0c5EroGAsXrw4Xn311dh5551j5MiRsdNOO8Xhhx8e++yzT3Tp0iWqqqpiyZIluY4JAAAAaaUABPLe6tWr4+qrr44JEyZEfX39Bms77LBD/OQnP4lRo0blKB0AAABklgIQyGsNDQ1x7rnnxjPPPLPR9erq6vjBD34QS5cujWuuuSbL6QAAACDzXAMQyGt33313i+Xf+saNGxdvvPFGFhIBAABAdikAgbzV1NQUd999d8rzt912WwbTAAAAQG4oAIG89d5778Vnn32W8vzkyZMzmAYAAAByQwEI5K1Fixa1an7ZsmWxZs2aDKUBAACA3FAAAnmrQ4cOrZovLy+PkhL3RgIAACC/KACBvNWnT5/YaaedUp4/7rjjIpFIZDARAAAAZJ8CEMhbpaWlcfbZZ6c8//3vfz+DaQAAACA3FIBAXvve974XX//61zc7d/bZZ8e3vvWtLCQCAACA7FIAAnmtXbt2MXny5Bg4cOBG10tKSuL73/9+/Md//Ie3/wIAAJCXXO0eyHtVVVXxwAMPxKxZs+K+++6L2bNnR0lJSfTt2zeGDx8e3bp1i+Li4lzHBAAAgIxQAAJ5LZlMxquvvhoPPvhgzJs3L8rKyqJ///4xbNiw2GGHHXIdDwAAADJOAQjkrc8//zzOP//8ePXVVzf4+lNPPRU33HBDXHrppXHppZd66y8AAAB5TQEI5KVFixbFiSeeGLNnz97o+urVq+P666+Purq6uPLKK7MbDgAAALLITUCAvHTDDTe0WP6t7+abb453330384EAAAAgRxSAQN5Zvnx5PPjggynP//73v89gGgAAAMgtBSCQd6ZNmxYrV65Mef65557LYBoAAADILQUgkHdWrFjRqvnly5dnKAkAAADkngIQyDudO3fO6DwAAABsTxSAQN457LDDokuXLinPn3jiiRlMAwAAALmlAATyTps2beKcc85JabakpCTOPvvsDCcCAACA3CnJdYBsq6mpicmTJ8eMGTNi0aJF0aZNm9hzzz3j+OOPj/79+2/xcRsaGuKPf/xjvPjiizF//vyIiOjevXscffTRMXjw4Cgp2fS3+tNPP41HHnkk3nnnnVi2bFl07Ngx+vTpE9/5zneiV69eW5wLCtXYsWPj5ZdfjldeeWWTc7/+9a9jt912y1IqAAAAyL5EMplM5jpEtsyZMyeuuOKKqKmpiYiI8vLyqK+vj6ampoiIOOGEE2LMmDGtPm5dXV387Gc/iw8//DAiIsrKyiIiYvXq1RERsc8++8Q111wTbdu23ejjX3zxxbj55pujoaEhIiIqKyujtrY2ItaenXTJJZfEkUce2epc/6y6unqrj7GtqKqqiuLi4mhsbIwlS5bkOg7bqNra2rjiiivioYceijVr1myw1r179/jFL34RJ510UkREFBcXR1VVVSxZsiQaGxtzEZc8Yo8i3exRpJM9inSzR5Fu9inSKR/3qB122KHVjymYMwDXrFkT1157bdTU1ETPnj3j0ksvjV69ekV9fX089thjMWnSpJg6dWr06tUrBg0a1Kpj33777fHhhx9GZWVlXHTRRc1nEk6fPj3+8z//Mz744IO444474pJLLvnKY+fMmdNc/h1xxBExevTo6Ny5cyxevDj+67/+K15++eX47W9/G7169YoePXqk5XuxvUomk/H666/HhAkT4s0334zq6upYs2ZNJJPJSCaTkUgktvq/TU1NUVRU1Px866+tn2P92dY8R0RscKx/PmZrc7bU36fjOTZ27H9+Hen+vrf03Ftz7IiIDh06RFlZWey0005xwAEHxMCBA2PQoEGbPTMXAAAA8kHB/O33T3/6U3zxxRfRpk2buOqqq6Jr164RsfZaYWeccUYsXrw4nnzyyZg4cWIMGDAg5WLgs88+i5deeikiIi688MI47LDDmtcOO+ywaGpqihtuuCFeeOGF+M53vhM9e/bc4PGTJk2KhoaG6NWrV/zgBz+I4uLiiFh7V9If/vCHMX/+/Pjss89i0qRJcfnll6fjW7FdWrFiRXz3u9+Np59+OtdR2I59/vnn8fbbb0dVVVUce+yxuY4DAAAAWVEwNwF54YUXIiLiqKOOai7/1nfqqadGIpGIxYsXxzvvvJPycV988cVIJpOx8847b1D+rfPNb34zdt5550gmk/Hiiy9usFZbWxuvvvpqREScfPLJzeXfOsXFxXHyySdHRMSMGTNi5cqVKefKJ2vWrIkRI0Yo/0iLZDIZv/nNb+K6667LdRQAAADIioIoAOvq6uKjjz6KiIiDDjpoozNdu3Ztfovt22+/nfKxZ86cGRERBx544EbfdplIJOLAAw/cYHad9957r/m6fy3lWvf1NWvWxPvvv59yrnwyefLkePnll3Mdgzxz8803x6effprrGAAAAJBxBVEAzps3r/maYv/8Ftz1rVubO3duSsdNJpMxb968zR533R1G//m46z7v1KlTdOzYcaOP7dixY/PanDlzUsqVb37/+9/nOgJ5KJlMxvjx43MdAwAAADKuIK4BuHjx4uaPO3fu3OLcurVU7zJUV1cXq1atSvm4dXV1UVdXF+Xl5Rs8z6Yeu269pqZms7kmTpwY9913X4vrQ4cOjWHDhm3yGNua5cuXx5tvvpnrGOSpadOmRVVVVUT8941TOnbs2OLNVSBV624mVFRU1PwzBlvDHkU62aNIN3sU6WafIp3sUWsVRAG4rqSLWHvTj5asW6urq0vpuOvPpXLcdY9ZVwCue/ymHtuaXLW1tbFgwYIW11euXPmV6wxu6+rr63MdgTxWW1v7lT8T637ZgHRIJBLb3b7Lts0eRTrZo0g3exTpZp8inQp9jyqIArBQVFZWxo477tjiekVFRTQ2NmYx0dbr0KFDlJWVxerVq3MdhTzUrVu35j8TiUQiioqKoqmpqaD/VYj0KCoqikQiEclkMpqamnIdhzxgjyKd7FGkmz2KdLNPkU75uEdtSTFeEAVg27Ztmz+ur6+PioqKjc6tO9ts3Rl6m7P+3KbOVFt/bf3HrPt4c2e5pZprxIgRMWLEiBbXq6urU35787bkhBNOiIcffjjXMchDJ510UvOfieLi4qiqqoqamprtrihn21NVVRXFxcXR1NS0Xe67bHvsUaSTPYp0s0eRbvYp0ikf96gddtih1Y8piPMf17/G3vrXA/xn69ZSvcZAeXl5cymXynHXn18/16YeuyW58s2YMWNyHYE81KVLlzj11FNzHQMAAAAyriAKwB49ejRf9HFTd9Jdt7brrrumdNxEIhE9evTY4uOu+3zp0qWxbNmyjT62pqYmampqIuK/7yZcaPr16xe/+MUvch2DPFJeXh533313tGvXLtdRAAAAIOMKogAsLy+PvfbaKyIi3njjjY3OVFdXx9y5cyMiom/fvikf++tf/3pExCbvVPvWW29tMLtO7969o6SkZJO51h23tLQ09t1335Rz5Zvvfe97ceedd0avXr1yHYXt3KGHHhqPP/54HH744bmOAgAAAFlRENcAjIgYMGBAfPjhh/HSSy/FmWeeGV27dt1gfcqUKZFMJqNz586x//77p3zco446KqZMmRLz58+PadOmxWGHHbbB+v/9v/835s+fH4lEIgYMGLDBWkVFRRxyyCExbdq0eOyxx+LII4/c4EKOjY2N8dhjj0XE2tKipWsXFopTTz01TjnllPjrX/8an3zyScyePTtWrVoViUQiVq5cGZWVlbFixYpo3759LFu2LKqqqmLx4sXRuXPnDf5bVVUVS5cujU6dOkVNTU1UVlZGXV1dtG3bNlavXh3FxcWRTCYjmUxGSUlJrFmzJtq0aRMrV66Mdu3axfLly6NDhw5RU1PT/BxVVVWxZMmS6Ny5cyxZsiQ6duwYy5Ytiw4dOsTy5cujsrIyVq5cGW3atImGhobmuw81NjZGaWlprF69OsrLy6O2tnajz7Fo0aLo0qVL8+tY/znat28fK1asiIqKiqirq9voc5SVlcWqVauivLx8g9fRsWPH5u/F+sde/zlqamqiffv2UVtbGxUVFbFq1aooLS2NxsbG5oupNjQ0RFlZWdTX10d5eXmsWLHiK9+jzp07b/A61v3/sO57tP7rqK+vj5KSkuYL/hYXF8fq1aujTZs2sWrVqqioqNjgOTp16hRLlizZ4P+H9Z+jS5cu0aNHjzj88MOjd+/eOfsZBgAAgFwomALw2GOPjccffzy++OKLGDduXFxyySXRq1evqK+vj6lTp8YTTzwREWtvpLHurLx1Ro8eHQsWLIhjjjkmxo4du8Far1694qijjooXX3wxbrnllkgkEvGNb3wjIiJeeeWVuPXWWyNibQG5sbfwDh8+PF599dX45JNP4qabborRo0c3lxh33XVXfPLJJ1FaWhrDhw/PwHdl+1NUVBRHHXVUnHTSSVFcXByNjY0uCgsAAACwCQVTAJaWlsaVV14ZV1xxRcyePTsuvvji5rOZ1p1lNGTIkBg0aFCrj/29730vPv/88/jwww/juuuui7KysoiIWL16dURE7LPPPvFv//ZvG33sbrvtFhdffHHcfPPN8Ze//CX++te/RkVFRdTW1kZERElJSVx88cXN1xoEAAAAgNYomAIwYm3Zdsstt8TDDz8cM2bMiOrq6qisrIw99tgjBg8eHP3799+i45aXl8f1118ff/zjH+PFF1+M+fPnR0TEnnvuGQMGDIjBgwd/5azC9R199NGx6667xpQpU2LWrFmxbNmy5rcif+c733HdOwAAAAC2WCKZTCZzHYLsqK6uznWEtKmqqvIWYNKquLi4+e33jY2NuY7Dds4eRbrZo0gnexTpZo8i3exTpFM+7lE77LBDqx9TEHcBBgAAAIBCpQAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA8lkgmk8lch4DWmjhxYtTW1kZlZWWMGDEi13EANmCPArZl9ihgW2efgvRTALJdOv7442PBggWx4447xpNPPpnrOAAbsEcB2zJ7FLCts09B+nkLMAAAAADkMQUgAAAAAOQxBSAAAAAA5DEFIAAAAADkMQUgAAAAAOQxBSAAAAAA5LGSXAeALTFs2LCora2NysrKXEcB+Ap7FLAts0cB2zr7FKRfIplMJnMdAgAAAADIDG8BBgAAAIA8pgAEAAAAgDymAAQAAACAPKYABAAAAIA85i7AbFdqampi8uTJMWPGjFi0aFG0adMm9txzzzj++OOjf//+uY4HFKgVK1bErFmz4uOPP45PPvkkPv7446ipqYmIiF/+8pex//775zghUMgWLlwY06ZNi5kzZ8bs2bNj8eLFUVJSEl27do0DDjggTjjhhOjWrVuuYwIF7OOPP44ZM2bERx99FPPnz49ly5ZFfX19tG/fPvbYY4846qij4uijj46iIucwwZZyF2C2G3PmzIkrrrii+S/V5eXlUV9fH01NTRERccIJJ8SYMWNyGREoUM8991zcfPPNG11TAAK5tHDhwhg9enSs/yt/RUVFrF69OhoaGiIioqysLMaOHRtHHHFErmICBe7222+Pp556qvnztm3bRkTEqlWrmr/Wp0+fuPLKK6OioiLr+SAfOAOQ7cKaNWvi2muvjZqamujZs2dceuml0atXr6ivr4/HHnssJk2aFFOnTo1evXrFoEGDch0XKEBVVVWx5557xv/4H/8jdtlll7jppptyHQmg+R9KDzrooDjmmGPigAMOiA4dOkRjY2O8//778bvf/S5mz54dN910U/To0SN233333AYGCtLee+8d3bt3j969e0f37t2bS76lS5fGM888E5MmTYpZs2bFPffcExdccEGO08L2yRmAbBf++Mc/xu9+97to06ZN3H777dG1a9cN1u+888548skno3PnznHXXXdFSYluG8iexsbGKC4ubv58xYoVMWzYsIhwBiCQW7W1tfHll1/GHnvssdH1JUuWxEUXXRQ1NTUxcODAuPjii7OcEGDzJk6cGA899FCUlZXFAw884O97sAW8gZ7twgsvvBAREUcdddRXyr+IiFNPPTUSiUQsXrw43nnnnSynAwrd+uUfwLaksrKyxfIvYu3Zy/369YuIiE8++SRbsQBaZa+99oqIiNWrV8fy5ctznAa2TwpAtnl1dXXx0UcfRcTat69sTNeuXaNHjx4REfH2229nLRsAwPauQ4cOEbH2bGaAbdEHH3wQEWuvDdipU6fchoHtlPNm2ebNmzev+cLVPXv2bHGuZ8+eMXfu3Jg7d262ogEAbPdmzZoVEZv+PQsg2+rr62PhwoXx5z//OR555JGIiBg8eHAkEokcJ4PtkwKQbd7ixYubP+7cuXOLc+vWlixZkvFMAAD5YPr06fHxxx9HRMTAgQNznAYodOtfR3l9JSUlMWTIkBgxYkQOUkF+UACyzVv/1u9t2rRpcW7dWl1dXcYzAQBs7xYuXBi33XZbRER84xvfaL4WIECuFBUVNb/Fd+XKlbF69epIJBIxZMiQOOWUU1x3GbaCAhAAAArMihUrYty4cVFTUxPdunWLiy66KNeRAKKioiImTJgQERHJZDIWLFgQU6dOjalTp8Zzzz0XV1xxRfTu3TvHKWH75CYgbPPatm3b/HF9fX2Lc+vWysvLM54JAGB7VVdXF7/4xS9i9uzZ0blz57jmmmuiffv2uY4FsIFEIhE77bRTjB49OkaNGhXLly+PX//615v8OyHQMgUg27z1r/u3/vUA/9m6taqqqoxnAgDYHtXX18c111wTf/vb36Jjx44xbty46NatW65jAWzSv/7rv0ZpaWksWrQoXn/99VzHge2SApBtXo8ePZrv9DRnzpwW59at7brrrlnJBQCwPamvr49x48bFu+++G+3atYtrrrnG703AdqGsrKz5TOXPP/88x2lg+6QAZJtXXl4ee+21V0REvPHGGxudqa6ujrlz50ZERN++fbOWDQBge7BmzZq47rrrYubMmVFRURFXX3119OrVK9exAFJSV1cXy5YtiwiXfIItpQBkuzBgwICIiHjppZdi4cKFX1mfMmVKJJPJ6Ny5c+y///5ZTgcAsO1qaGiI66+/Pt58881o27ZtXHXVVfG1r30t17EAIiKisbExksnkJmcee+yxaGhoiIiI/fbbLxuxIO8oANkuHHvssdGtW7dYtWpVjBs3Lj777LOIWPtWlsmTJ8cTTzwREREjRoyIkhI3twayb9myZc3/W7FiRfPXa2trN1hb98srQDY0NjbGjTfeGK+++mqUlZXFlVde6Q6awDaluro6Lrnkknj66ac3ONkjmUzG3Llz484774z7778/IiIOO+yw6NmzZ66iwnYtkdxc1Q7biDlz5sQVV1wRNTU1EbH2FvGrVq2KpqamiIgYMmRI/M//+T9zGREoYCeeeGJKc7/85S+dqQxkzaxZs+KnP/1pRESUlpZGZWXlJucnTJiQjVgAzb788ssYM2ZM8+dlZWXRtm3bWLVqVaxevbr564ccckj86Ec/irZt2+YiJmz3nCrFdmO33XaLW265JR5++OGYMWNGVFdXR2VlZeyxxx4xePDg6N+/f64jAgBsU9b/t/41a9bE0qVLcxcGYCM6d+4cl112WcycOTM+/PDDWLJkSSxbtixKS0uje/fu8bWvfS2OPvroOOigg3IdFbZrzgAEAAAAgDzmGoAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAACk3QsvvBCJRCISiURcffXVuY4DAFDQFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAABkxd/+9re48MILY++9947KysqoqqqK/v37x29+85uor69v8XG77757JBKJ2H333SMiYvXq1XHrrbfGN7/5zejatWu0a9cu+vbtG//+7/8etbW1Gzz2yy+/jKuvvjr69u0bHTt2jPbt20f//v3jrrvuimQyucm8TU1Ncd9998XJJ58cPXv2jPLy8mjbtm107949+vbtG6effnrcfvvtsWjRoq3+3gAAZFIiubnffAAAoJVeeOGF+Na3vhURET//+c9j3333jfPOOy9Wrly50fl99tknnnrqqejZs+dX1nbffff4+9//Hj179ozp06fHkCFD4vXXX9/ocQ455JB4+umno1OnTjF9+vQ4+eST48svv9zo7NChQ2PSpEmRSCS+srZo0aIYMmRITJ8+fbOv9de//nX88Ic/3OwcAECulOQ6AAAA+e3111+P66+/PtasWRPDhg2LgQMHRnl5ebz77rtxzz33xOeffx4ffPBBfOtb34o333wzOnbsuNHjrFmzJk499dR4/fXX41/+5V/i5JNPjh122CE+/fTTuO2222LevHnx6quvxtixY+Pqq6+OY489Nurq6uLcc8+No446KsrLy+PVV1+NO+64I+rq6uL++++PQYMGxXnnnfeV5xozZkxz+bfrrrvGWWedFXvttVdUVVVFbW1tfPTRRzFt2rT4y1/+ktHvHQBAOjgDEACAtFv/DMCIiIqKinjiiSdiwIABG8wtXbo0jj/++Jg2bVpERHz3u9+NO++8c4OZdWcARkQkEom46667vlLaffnll3HAAQfEF198EcXFxbH//vvH3Llz45lnnokDDzxwg9nnn38+Bg4cGBER++23X8yaNWuD9QULFsTOO+8cTU1N8c1vfjOee+65aNu27UZf58KFC6O6ujr23XffFL8zAADZ5xqAAABk3PXXX/+V8i8iolOnTvGHP/wh2rVrFxER48ePj4ULF7Z4nNGjR2/0jL2ddtopLrjggoiIaGxsjLfeeituu+22r5R/ERHHHHNMcwH47rvvxty5czdY//TTT6OpqSkiIoYPH95i+RcR0bVrV+UfALDNUwACAJBRnTp1ijFjxrS43r179xg+fHhERNTX18fUqVNbnL3wwgtbXDviiCOaP95pp53i9NNPb3H2yCOPbP74vffe22CtsrKy+eOWrjUIALA9UQACAJBRRxxxxCbPoouIGDRoUPPHM2bM2OhMZWVl9OnTp8VjdOvWrfnjfv36RVFRy7/qrj+7ZMmSDdZ69+4d3bt3j4iIe+65J84999x4+eWXo7GxcZOvAQBgW6UABAAgo/baa69WzcyfP3+jM507d97oHXvXadOmTfPHXbp02eTzrT+7atWqDdaKi4vjd7/7XfPMvffeG0cccUR07tw5vv3tb8cvfvGLePnll8OltAGA7YUCEACAjFr/LbWpzCxfvnyjM5s6o29rZjfm+OOPj9deey1OO+20KCsri4iIZcuWxTPPPBNXX311HHHEEbHnnnvGxIkTt+p5AACyoSTXAQAAyG+1tbWtmmnfvn0m46SsT58+8Yc//CFqa2vj5ZdfjunTp8df/vKX+Mtf/hL19fXx2WefxciRI+OTTz6Jn//857mOCwDQImcAAgCQUR9//HGrZnbZZZdMxmm1ysrK+Pa3vx1XXXVVPPPMM7Fw4cIYN25c8/ovf/nL+OKLL3KYEABg0xSAAABk1Loz5jbl2Wefbf74G9/4RqYjbZX27dvHlVdeGSeddFJERKxZsyamT5+e41QAAC1TAAIAkFFLly6Nu+66q8X1zz//PCZNmhQRa2/OMWTIkGxF2yq9evVq/rihoSGHSQAANk0BCABAxl1++eXx0ksvfeXry5YtizPOOKP5xh+jRo2Krl27ZjveBv70pz/Fb37zm1iyZEmLMwsWLIiHH364+fO+fftmIxoAwBZxExAAADJqyJAh8cwzz8QxxxwTZ511VgwcODDKy8vjvffei7vvvjvmz58fEWvPqLvhhhtynHbtGYmXXnppXH755TFgwIDo379/7LHHHtGuXbtYtGhRzJw5M+6///7mgvCMM86IvfbaK8epAQBapgAEACCj+vXrFyNHjoxRo0bFpEmTmt/uu7699947nnrqqejQoUMOEm4okUhExNpr+z3zzDPxzDPPtDh72mmnxe9///tsRQMA2CIKQAAAMu6MM86Ivn37xi233BJPP/10/OMf/4jS0tLYe++948wzz4zvf//70aZNm1zHjIiIs88+O3r37h3PPvtsvPLKK/H+++/H/Pnzo66uLioqKmK33XaL/v37x8iRI+Poo4/OdVwAgM1KJJPJZK5DAAAAAACZ4SYgAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQxxSAAAAAAJDHFIAAAAAAkMcUgAAAAACQx/4fK00nqAf38UoAAAAASUVORK5CYII=" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(UM2_cr_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM2_esc_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM2_msy_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "2fbd46bf-f639-4fe2-bfb4-8e6ddd95bf6a", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## UM3" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "1b435467-a730-4c13-89da-779d307fbb6e", + "metadata": {}, + "outputs": [], + "source": [ + "bms_obs_list = np.linspace(-1, -1+0.14, 500)\n", + "mwt_obs_list_short = [-0.5, 0, 0.3, 0.5, 0.7, 0.9]\n", + "mwt_obs_list = np.linspace(-1,1,500)\n", + "\n", + "\n", + "UM3_2o_pol = pd.DataFrame(get_2obs_policy(\n", + " bms_obs_list, mwt_obs_list_short, \n", + " agent = PPO_2o_UM3, \n", + " asm_env = AsmEnv(config=CFG_UM3_2o),\n", + ")) \n", + "\n", + "UM3_mw_pol = pd.DataFrame(get_mwt_policy(\n", + " mwt_obs_list, \n", + " agent = PPO_mw_UM3, \n", + " asm_env = AsmEnv(config=CFG_UM3_mw),\n", + ")) \n", + "\n", + "UM3_bm_pol = pd.DataFrame(get_bms_policy(\n", + " bms_obs_list, \n", + " agent = PPO_bm_UM3, \n", + " asm_env = AsmEnv(config=CFG_UM3_bm),\n", + ")) " + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "54523015-78ea-4ad2-87ce-443bbed24566", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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HBJr36KOPZurUqTz//PO8+uqrvPrqqyQSCXzfJ5/PA8tuFT7xxBPZZpttwv62REREpADGX0KNfz6xHm/6gccmdDqnkDN7q9nXC3xnI1qdv+L6H1LtX4jLrND+DKTsQ8S8d2l1r8eaupBmFREREQlfxTQAAUaMGMF1113HP//5T1555RUaGxuprq5m44035rDDDmOXXXYJPKfrupx77rnsueeePP3000yZMoXm5mYcx2HIkCFsuummHHbYYbr9V0REpBcYv4Vq/+fEeanHGn8WsNTRab5CxnwJnJoeurKsi+eMp8W5i7j3JNX2ChzaQ5k3xnTqva/S4vwe3xkdypwiIiIiYTPW6r6FUrL8duJS0dDQgOu6eJ5HU1NTb8eRXuS6Lg0NDTQ1Na1xv0ypHHpdkOUifV2wGar8y0naxzGRHAexhkvikmN7Opwf4Tsb9cg1y0GvvCZYS9q7khQPhNYYtsRpcX6H5xS2l7SsTu8VZDm9VxAo7deEgQMH9nYEkdVUzB6AIiIiUgFsnrT3Rxq8/UnZxyJv/lnAp4EOczpNztO0xa5W868UGENn7DyWOvfhsWE4U5Kjzv8WCf+xUOYTERERCVNF3QIsIiIiZcpaEvbfVPm/xiEb/eWAPFvS7pyL74yN/HoSDetsQLPzT5L+HVT5v+92w9hgqfYvwtgmMu5XQ0opIiIi0n1qAIqIiEhJc/23qPX/D4fobxOzxMmYg+hwzgZTFfn1pGdknOPIsi91/pm4zOvWXAaostdivHa63FPDCSgiIiLSTWoAioiISGnyF1Pnn4PLR5Ef8OFTR5c5li7nRDDaQaUcWWdDms1dVPlXk7T3duvP1LIm4F9xvCV0uOeGFVFERESkaGoAioiISGnxvWUHfPBw5Hv8eWxIh/Ntcs4BkV5H+ggTo8P9IVlvT2rteZhu3k6esvdh83E63bPA9NQ51CIiIiKrUwNQRERESkbCf4Rq/0oMmciusWx/vzF0mB/juZtHdh3pu/Luziz1H6DO/xou87s1V5q7MX47He75IaUTERERCU4NQBEREenzHH82Nf65uMyI7HbfZY2/zWh3fobvDI/oKlIqrFNPs7mbau9nJHmmW3Ol7EPYfD86Y2eElE5EREQkGDUARUREpO+yWaq8X5PkwUgbfx6b0upcjHU2iugqUpJMjPbYpXjeX0jbG7v1ZzDN7eB5dLrfCy2eiIiISKHUABQREZE+Kea9SI39OQ6tkcy/rPE3llbnl1hnaCTXkPLQ5Z5G3t+SWv8cDH7R86TtnfjeBmTcr4SYTkRERGT91AAUERGRPsXYJVT7vyBhX4lk/mWNv+G0Ob/EdzaO5BpSfvLOzjRzA/X+GRi6ip6n2l4DfoqMc1SI6URERETWzentACIiIiIAWEvCv59+3lGRNf88BtHq/IGW2F1q/klgvrMpze7t+NR1a54q/0ri/qSQUomIiIisnxqAIiIi0vv8JdR5x1HjX4nBC396qml1fkFz7AHyzjahzy+Vwzcb0uzejccGRc9hsNT45+H4U0JMJiIiIrJ2agCKiIhIr0rkbqPBP5IYM0Kf2xKj3XyTpe7j5JwDQp9fKpM1dTQ7f8Oj+ENjDB51/hk4dm6IyURERETWTA1AERER6RXGzsdfdBhp/7puHaywJhbI8DmanKfJuKeAieoMYalYTg3N7i3kGVH8FLRR650Bfi7EYCIiIiKrUwNQREREepa1JL07qc0eA164t0BaIM9Ympx/0R67CByddyYRMtW0ODfjMbzoKVwWUOufBTYfYjARERGRVakBKCIiIj3G+Eup9U6j2l4b+l5/PjW0Or+jJXYrOANDnVtkrZwULe5f8Bha9BRxJpP2rg4vk4iIiMhnqAEoIiIiPSLuT6SffwRx3g91Xouhw5zKUvcx8s52oc4tUghraml2bsRjcNFzpLiXuP9UiKlEREREPqUGoIiIiETLZqnJ/4Aa/yehr/rLsQ1LnUfock/VPn/Su5xaWty/4lNfVLkBavyfEbNvh5tLREREBDUARUREJEKu/w79vKNJ8BJhtud8amhxrqY19gesUxfizCLFs2YALc4N+KSKqjf41Hj/B1aHgoiIiEi41AAUERGR8FmflHcDdf43cVga3rQYOs2XWOo+SN7ZKbR5RcLiO8Nodf6ExS2q3mEJtd6ZOhREREREQqUGoIiIiITLb6POO4Uqe1Ooq/48htPs/I1O9/tgkiHOLBIuzxlHm3Mptsj6OG+T8m8MNZOIiIhUNjUARUREJDQx7zUa/MOJ8XFoc1oc2jmVZvdOfGfj0OYViVLO2YsOc07RTcC0vQXXfyfUTCIiIlK51AAUERGR7rMeae9qau13MWRDm9ZjOEud+8jEdMiHlJ6M+wWy5rCiag2WWv9sjF0YcioRERGpRGoAioiISPf4HdR5p5G2d4d2y6/F0G7Opjl2F9YZFNKsIj2v3TmPHJsXVevQQbV3eciJREREpBKpASgiIiJFc/33afAPI8aHoc2ZZyRLnfvJuF8ObU6RXmNitDq/w6dfUeUJXiLp/T3cTCIiIlJx1AAUERGR4Kwl6d1MnX8qhkw4U2LoMN+gxb1Nq/6kvDhJWt1rsMSKKq+yv8Pxp4UcSkRERCqJGoAiIiISjM1R451Htf1zaLf8egym2fkbXe7XwLghzSrSd3hmHG3OhUXVGiw1/vlg8yGnEhERkUqhBqCIiIgUzPiN1HtfIMF/QpszYw6n2b1XJ/xK2cs5B9DFUUXVxphOlf/bkBOJiIhIpVADUERERAoS81+hn/8lXBpDmc+SgIbb6Er8FIzekkhl6HB/SJ5xRdWm7H04/ichJxIREZFKoHfbIiIisl4p/3Zq/bND2+8vx9a0xB/BSe4UynwiJcO4tLmXYokXVV7rnwO2K+RQIiIiUu7UABQREZG1sz5V+Z9T5f8+lP3+LA4d5pu0un8ApyaEGUVKj2+G0WouwxZR67KQav+q0DOJiIhIeVMDUERERNbI2BbqvBNJ8Xgo8/nU0OLcTJd7Cpiwjg8RKU15d3cy5vCiahP2ERx/RsiJREREpJypASgiIiKrcfxZ1HtfIca0UObLsh1LnYfwnLGhzCdSDjqd7+IxKHCdAWr9s3UrsIiIiBRMDUARERFZRcx/g3r/OByauz2XxdBuvk2bex04xe15JlKurKmlxbkeixu41mUBVf4fIkglIiIi5UgNQBEREVkh6d1JrX8GBq/bc/lU0eL8kYx7om75FVkL62xIlzmxqNqkvQ/jLwk5kYiIiJQjNQBFREQEgLT3B6rttaEc9pFnFM3u/XjOViHMJlLeOp2vk2dM4DqDR61/Fth8BKlERESknKgBKCIiUulsjpr8OaTtbaFM12WOocW9HWt0yq9IQUyMVuc6LLHApTE+IWXvjCCUiIiIlBM1AEVERCqZ30md9w0SvNjtqSwubc6P6XB/qFt+RQKyTj86na8VVZvybwVfqwBFRERk7dQAFBERqVDGLqHeP44YH3V7Lp8qmt1byTpHhpBMpDJ1mVPIs1ngOoc2qu0vIkgkIiIi5UINQBERkQrk+DOp947FZUG358ozhqXOv/DN6BCSiVQwY2hzL8EWsRNn0j5J3J8UQSgREREpB2oAioiIVBjHn0KdfzIOrd2eK2P2ocW9CZyq7gcTEXwzhC5T7K3Afw05jYiIiJSL4DsNi4iISMmKef+l1n4fg9+teSzQwRlk3OPDCVYhrLVkbTMd/gK6vMW0+NPI+x10+AvwbZac7cA3eayfBwPGGhwnjkOCmKkiYWpJOYOocjeg1hlOlTuUhKnGGP1Ot5x0OqcS9yYSY2qgujjvk/AfJescHFEyERERKVVqAIqIiFSIhP8o1fZiDLZb81hcWp0ryTu7hpSs/PjWoyn/AY35N1mSf5dObyEZ24RPtvBJlv9n8tY/1CVN0ulHg7spA+JbMzi+LQlTj9FhLKXJGDrc86jzTg9cWu1fTs5shzWDIwgmIiIipUoNQBERkQqQ8B6m2l5SxM5iq/KpocX5Hb6zSSi5ykHedtKU+5C5uedYmvuIdjsXS8+eyOrRSYffSYc/jzm5pwEwuNQ4wxkc35Fhyf2pdjZUQ7CE5M2WdHEoKR4OVGfIkvLupjN2ZkTJREREpBSpASgiIlLmUt5fSNsbu9388xhMi3sj1vQPJVep8myGBdmXmZV9hqX5D8nT1tuR1sji0epPpzUznU8y/8AhQf/YZoxNfZUB8eAnzUrP63B+TMKfhMPSQHUp7qbLHlfx/18VERGRT6kBKCIiUsZS3i1U2Ru7PU+OrWh1rgWTCCFVabHW0pT/gFmZJ5ife5l8CIen9AafLI35yTS2TQYcBsa2ZuPk5xmU2KaXk8laOTE6+SbV/pWBygx5arwf0+r+CbTqU0RERFADUEREpDxZS9r/FWl7X7enyrA37e4lYNwQgpUGz+ZYkH2FqZn7aPWm4ZPr7Ugh82nMv0Fj/g1i7dUMS+zLhKqTcU2yt4PJZ2TM4SS5lxgfB6qL8w4x+xp5s0NEyURERKSUqAEoIiJShqr835IKofnXwWl0xb4eQqK+z1qfOdnnmNZ1Py1+sNNXS1medqZn/8307EMMiG3FVlXfo8od1NuxZDkTo9X5Ff38YwKf3p32f0erc3M0uURERKSkqAEoIiJSTqxPtXcZyYAHB6w2DdBhvkvGPTacXH2UtT7zspOYmrmPZu9j6OYJyaXNsjj/Js+0nEq9O5atq75PbWx4b4cSwDqDydjDSNkHA9XF+YiE/yBZ54iIkomIiEipUANQRESkjFT5l5Dk0W7NYYE25wpyzp7hhOqDOrwFvNN+PY3emz1+Ym8paPY+5rnWM+jnjmebqh9QHduwtyNVvE7nVBLeUzh0BKqr8n9H1nwOTCqiZCIiIlIK1AAUEREpB9an2rs0hOZfjBbnOjxn65CC9R15v4sZmYf5uOufJXuQR09b6n3IxNbT2SC2C1tVf5eEU9vbkSqWNYPpcM6mxr8sUJ1DKwn/IbLuFyJKJiIiIqVADUAREZFSZy3V3s9J8mT3piFJs/NnfGdcSMH6hqbch3zQeStLvLd7O0rJWpB/iSeaX2GT1HGMTX0RY5zejlSRsuZQPG7BZU6guip7A1l7MJjqiJKJiIhIX6d3byIiIqXMWqq8y7vd/POpodm9vWyaf9b6zOh6hCeXnsKktnPV/AuFz0ddt/Fk80m05Kf1dpjKZBw6ndMDlzm0UOVfG0EgERERKRVaASgiIlLCqvxLSPFIt+bwaaDZuQlrBoeUqvfkbQcfdfyd6dmHSmhvPwdDDJcEDjEcE8fgYozBWh/f5vFNDt9m8clh8Xo1bda28HzrWQxN7MvWVd/DGLdX81SarHMAWf9BEvw3UF3SPkqn/TbW9IsmmIiIiPRpagCKiIiUImtJe7/rdvPPYxAt7k1Y0z+kYL2jzZvDex1/YVH+td6OsgaGBHWk3IE0uBOodUdQH9uEandD4qaqqBk9v4tWby7N3ocszr9LS/4TOuwiLNmQs6/dnOwzLMpOZsean9IvPrbHrivQ4X6fhHdcoBpDjpR/O53uGRGlEhERkb5MDUAREZESlPZ/S5p7ujVHnmG0ODeV9L5gi3Nv817HX2nxp/Z2lP8xpM1g6mNj2SixBwNiW0VycIbrpOjnbEy/+MaM5JAVX8/5bSzOv83MzGMszX9EjrbQr72yLE280HYO41JfZVzqK9obsIf4ZhRZsxsJOylQXcreTcYeim9GR5RMRERE+io1AEVEREpMyruNtO1e889jOC3ujSXb/FuQfYV3O/9Cpz+/V3MYHGrcEWwQ25nhyQNIO4MxxvRanrhTw5DErgxJ7ApAxm9hVuYxZmYeo9MujOiqlildf2dh7jV2qbmMmJOI6DqysnbnAuLeMRi6Cq4x5Ej7N9LuXhxhMhEREemL1AAUEREpIUnvVqrs9d2aI8c4Wt0/g0mGlKrnzMu+wLsdN5CxS3otQ8LUs2F8N0Ylj6QmNrTXchQi6dQxNv0lxqa/RMZvYWrnvczIPoJHZ+jXavY+4snmk9i19jLqYxuHPr+sypp+dJkvkbZ/C1SXsM/QYZeU/G3/IiIiEowagCIiIiUi4T/S7eZfno1Lsvk3L/Mi73T8kSxLe+X6tc4oRiQPZETyIBwT75UM3ZV06ti0+hQ2rT6Flvw0Jrf/llZ/eqjX8OjgP60/YKv0GQxPfS7UuWV1Xc6XSHl3YAIcDGPwSfs30+H+IMJkIiIi0teoASgiIlIC4v6TVPsX052bS3NMoNX9Y0k1/xbmXuPNtmt6pfFXbYYzLv1lhsR3w3VKs+m3NnWx0exVfy1d3hLeaL+KJd67Ic7u81bndbT7C5hQdUKI88pnWTOQTufbVPm/C1SXtP8kYw/GM5tFlExERET6GjUARURE+riY/yo1/s+71fxbtvLvT1Aiq9eW5N7n9baryNDYo9dNmYGMTBzKqNQRxJzSaZQWK+X2Z9e6X9LpNfJG+1U0ee+HNvcnmbtp9qawY80FJbtqshR0mWNJcQcOhd8Wb7Ck/Dtpd38RYTIRERHpS9QAFBER6cNcfwq1/vcx+EXPkWcsLSXS/Gvz5vBq66W029k9dk2XFBvF92bT6lOIl+ihKN2VdgeyW90VNOc/4fW2K+iw4Ryu0ph/gxdafsxutZeX3SrKPsMYupxjqfJ/H6gsYZ+m3Z5XsgcBiYiISDBObwcQERGRNXPsDGr9bwXa3+uzPEbQ4twAJh1isvBlvGYmNZ/Hsy3f7rHmX52zMdtV/x8HN9zNVjVnVGzzb2X1sTHs2+/PbJk+E4dwGnYt/hQmtnyLjN8cynyyuow5Ap/aQDXL9gL8S0SJREREpK9RA1BERKQv8lup807H6cZprR7DaHH/An34Vta818WrzVfxZMuJNPnh3X66NoYYIxOH8rn629iz/mo2TOwa+TVL0YjUgRxY/3cGuFuHMl+XXcTzLWeR8ZeGMp+sypo62p0LAtel7V24dkoEiURERKSvUQNQRESkjzG2lXr/azi0FD2HxxCanZuxpibEZOGx1vJR+13cMfVzzM1NjPx6SdPAVlVncUi/f7JF9bdIOHWRX7PUuU6CXeouZsfqCzEh7BqTsUt4tvm7dPqLQkgnn5Uze+AxKHBd0r83gjQiIiLS16gBKCIi0pdYn1rve7jMLXoKnwH/W/lXFWKw8CzMvsrjS4/lg85bsd24vbkQdc7G7Fp7OQf0u4Xhyf0xpjtHqVSmwYkd+Fz936h3Nun2XDma+U/z9+nylnY/mKzKGDLOFwKXJexjYG0EgURERKQvUQNQRESkr7A+1d75xPiw6Ck86mh2bsSa/iEGC0eHt5CJzd/hv+2/IE9HpNcaHNuBfequZ8/6q+kf2yzSa1WCuFPN7nVXMTb5pW7PlaWF51vOossv/NRaKUzGHIPHwEA1Dl2k7N8jSiQiIiJ9hRqAIiIifUSV/yuSPFt0vSVNq3sj1gl+G2CUfD/P661X8UzLabT7UR7wYRiW+Byfq7uNHWsvpNrdKMJrVR5jDOOrTmTn6l9iunlASJYm/tNyDnm/K6R0AmBNDR3O2YHr0v4fMVa3ZouIiJQzNQBFRET6gKR3L0l7f9H1lgTNzp/xTd9qes3sepzHmr/KvPzzEV7FYXTyKA7qdxdbV3+XhKv9/aI0MLE5+9f9lWQ3V5lm7GL+03IOOT/a1aCVJmf2wKdfoBqDR8p/IJpAIiIi0ieoASgiItLL4v5EquyvKHZ3OotLi/NHfGdMqLm6oy0/i2ebv8Pbnb/DJxvRVRxGJY/k4H53s1nVqcRMKqLryGcl3X7sU3c9/dzx3Zqn3c7iyXnfx2oPuvCYBBlzdOCyuH0s/CwiIiLSZ6gBKCIi0otc+yE1/oXdaP5Bq7kcz9k0zFhF82yGt9v/yLOtZ9AW2e2+DsMTB3Jwv3+wedVpuCYR0XVkXWJOit1qL2dIfLduzbM48x7Pzb8Qa/2Qkkmnc0LgE4FjzCHhPxFRIhEREeltagCKiIj0EuM3UuudgSFfVL0F2p2fkXd3DzdYkRZk/8uTS09hZvaRiK5gGBLfg4Pq72Kr6jNxTff2oZPuM8Zl+5ofMyb1xW7NM73tKV5f/MeQUgmmii5zcuCyKv+3YKNasSsiIiK9KdbbAURERCqS7aDO/zZON07D7TDfIuscFGKo4mS8Zt7ouIrF+bciu8aA2FZsV/1jEk5NZNeQ4k1InwTW8knmn0XP8X7LnSSrhjI0uXeIySpX1jmAKu9aTIBb8B2WkrDPkDW9/7oiIiIi4VIDUEREpKdZS613Hi5zip6i0xxDxjkxxFDFmdH1MO92/hlLNLdv1jgj2bHmAqrcDSKZX8IzoepkUmYQ73ZdX/Qckzt+Q9oZRP/4ZiEmq0zW1JExB5Oy/wpUF/ef6hO/WBAREZFw6RZgERGRHpb2ryHOa0XXZ9iDTuccMMXuHNh9nd5inmk+nXc6r4+k+Zc0/dil5nL2rr9Ozb8SMip9KJukju/GDJb/tl9Mxm8KLVMl63C+i0+wU7ETvIhrp0SUSERERHqLGoAiIiI9KOnfT9reXXR9nvG0u5f0WvPPWsuHHXfwdMvX6fDnhT6/Q4It09/lgH63MkCrwErSuPRXmJD6WtH1edvOiy3nk7ddIaaqUKaajDkkWAkeVd5vIwokIiIivUUNQBERkR7i+B9R5f+q6HqPwbQ4v4deOvW2zZvDsy3f4ePMnSw7giRMhhGJQzi4392MSH0u5Lmlp41Jf57RyaOLrm+3s3mnXYeChCHrHBa4Js5kXPtJBGlERESkt2gPQBERkR7g2NnU+d/GFHm7rE81re71YKpCTrZ+1npM6bqbKV1RNP6gX2w8O1b/lIQT7FZF6ds2TX+NnG1ndvaJourn5J6hoWtTRqYODjlZZfHMWHJmB+L21UB1Mf8/eO6YiFKJiIhIT9MKQBERkahZn1rvBzh0FleOS6tzLb4ZEnKw9evwFjKx+TtM6fo7YTf/4tRy8NDr2avfb9T8K0PGGLau/i4DY9sWPcc7nX+kLT87xFSVqc35KZZ4oJqUvRdsca9ZIiIi0veoASgiIhIl61PjnYdLcU0Mi6HNuRzP2TTkYOs3retfPNPyDTps2Hv9GcanTuLgAXewQdVWIc8tfc0ONT+h1hlZZLXl5bYLyasR1S3WDCLH1oFqXBaR9m+NKJGIiIj0NDUARUREIpTybyTBC0XXd5pTyTm7h5ho/bJ+C882f5f3Ov9C2Kv+BsS25oC6Wxmb/iLG6G1IJXBNkl1rLyce8DTa5bpsI5PbfxNyqsqTdYIdBgKQtA+AzUaQRkRERHqa3nmLiIhEJOa/StreVHR9xhxGl1P8aarFmJ2ZyJPNX6PNnxHqvHFTy041v2CX2otJuvWhzi19X9ypZre6y3Eo7gCbBbmXmZedFHKqypI1++EzIFCNw1Ji9p2IEomIiEhPUgNQREQkAo6dSa3/Q0yRK+jybEq78xMwJuRka7me7eTV1st4s+M3WHKhzj0qcQT719/EoPg2oc4rpaXGHca21ecWXT+5/de0edoPsGgmSZt7aeBXpIR9PJI4IiIi0rPUABQREQmbzVLjnYuhuFvnfPrT6v66x5p/zflPeGrp11iQfynUeavMRuxV+zs2r/4Grilu5ZeUlyGJnRmfOqGoWp8cr7ddibXhn0RdKfJmKyzBVuAm7YO4WgUoIiJS8mK9HUCCcV23tyMUrZSzS/ct/++vPweysrL882B9qnI/Jcas4spJ0Ba/FccJdqteUdeylg/ab2VK190hz+wwIX0Cm1R/ZZ2j9LpQmcbXHEuT9wELc68Grm31pzM9+wBjq74QQbLKkPP3I+nfV/B4gyVt76YzFuwQkWLoNUHWRH8eKpdeE0TCZax+jSoiIhIav+1GaLu86HrT70+Y1L4hJlqzjnwjT845h6bslFDnrY+P4uBhvycVawh1XikvXV4zD8w4gS5vcRHVDgcNu44h6W1Dz1UJbO4D7OIjA1a5mMH/xTg1kWQSERGR6KkBWGKampp6O0IgdXV1uK6L53m0tLT0dhzpRa7rUldXR0tLC57n9XYc6UXl/Lrg+m9QnfsOBr+o+k73e2Rjx4ecanXzsy/zasvl+EXeorxmDltVn8mo9EEFV+h1obJ1eAt5quk0LMH/29e4I9iv4Y8RpKoMydxvSfl3Bqppi/0Fz90yokTL6DVBlivn9wpSuFJ+TWho0C9Cpe/RLcAlptRe+FZWytklPJ7n6c+CrFBOfxaM30qt/4Oim38Z9qOTr0DE/07eafsTM3IPhTpnvTuOHat/StLtV9R/U70uVKYkA9g0/TXe6/xL4No2bybvt93GJuljI0hW/jo5lhTBGoCp/JW02L+Aif7jg14TZGX6syB6TRAJhw4BERER6S7rUeP/AIeOosrzjKbd/Wmkh35k/CaeaT491OafIcbm6dPZvfZXJN1+oc0rlWNU8giGVe1eVO2UrjtZnNPhFMWwZiAeGwWqifERCTsxmkAiIiISOTUARUREuqnK/x1x3i2q1idFq3MNmGTIqT41P/sKTzd/gw5/Xmhz1jij2Lf+z4xKHYbpodOKpfwYY9hrg0tIOv2KqLa833lT2JEqgzFknM8HLgtyeIiIiIj0LWoAioiIdIPrTyZp7yqq1uLQ5lyNdQaGnOp/81vL+x0381r7JSHu92fYJHUCe9dfSzqi3FJZHBNjrw0vKqq22ZvCtK4HQ05UGbrM0XhsEKgmhlZcioiIlCo1AEVERIrk2NnU+T+g2PVvHeZb5J2tQs20XN528Hzr2UzN3BvanAnTwL51f2Jc+suhzSkCsFHVjmzR76Siat/v/Cst+WkhJ6oAppoO55sBi3LE/NciiSMiIiLRUgNQRESkSDXeBRi6iqrNmr3IONGc+Ls09xFPNZ9GqxdeU2RE4hD2r/8rVe6Q0OYUWdlWDV8j7QRbkQZg8fmw844IEpU/z2waaLwBavyfgu2MJpCIiIhERg1AERGRIqS83xPjo6JqPYbT5lwayaEfM7oe4YW2c8nbtlDmi1HFTjUXsWX1t3F64PRPqVyOibFjzU8xuIFrF+ZfZmH29QhSlTffjCLP5oFqHJaStE9ElEhERESiogagiIhIQHH/Wars7UXVWuK0ub8EE7zJsc55rc/ktt/wTucfARvKnP2cTdiv340Mim8bynwi61PrjmCT1HFF1b7RfiVZvyXkROWv0zkhcE3CPhlBEhEREYmSGoAiIiJB+J1U+5cVVWqBVucqPLNxqJEy/lKea/kuc3ITQ5tzs9Q32L3+V8RNVWhzihRidOpI0ib4rcB5Opie0YEgQeWcvcmanQLVOHZqRGlEREQkKmoAioiIFMrmqPO/g0NrUeVdfIG8E+yD9vo05z9mYvPptPmzQpkvYerZq/Z3jE4fEcp8IkG5JslONT/HFPE29eOuf9LpN0aQqrzlzJ6BxrssIen/M6I0IiIiEgU1AEVERAqU8m8lxodF1ebZhE73rFDzzM38h/+0nkOecDbkHxzfgX3r/0xtbEQo84kUqyY2lNHJowPXWfK81nYZ1vrhhypjuYArAAHS/vVgOyJIIyIiIlFQA1BERKQArv8haXtTUbU+aVqcP0BIh2hY6/N2+x94o+NKwtnvz7BF+lvsWHMhMZMOYT6R7huTOoaEqQ9c1+x9TGPuzQgSlS/fDCdndgxU49Cuw0BERERKiBqAIiIi62HsUmr9szEEX1VkgXbnF+CEs5ee5+d4ue1CZmYfDWW+GNXsXfsHRqYODWU+kbAknDp2qD6/qNp3Ov+oVYABtTtnYwn2S4qY/1ZEaURERCRsagCKiIisR5V/NQ7NRdV2mq+Rc3YPJUfGb2Jiy+kszofzoXtAbGsO6HczNbGhocwnEraG+ASGxHcLXNfhz+ejrjsiSFS+fDOanNklUE2MN0GNVhERkZKgBqCIiMg6JLyHSdrHi6rNM4Eu5+uh5GjKfcjE5m/RZcM54GBs6qvsXPMLXJMMZT6RqIxPn4hDPHDdJ133kfPbIkhUvjw2CTTeZS4pe1tEaURERCRMagCKiIishbGLqLa/LKrWp5pW9yowbrdzzM++zKS280I57MMQZ7eaKxmfPg5jTLfnE4lajTuUTdPBG+mWHFO67o4gUfnKOAcFrkn5d4LNRJBGREREwqQGoIiIyJpYnxrvxxi8osrbnIuxZkC3Y3zceS+vtV8KRew/+FnVzlAOqL+ZhviEbs8l0pNGJg+hytkwcN30zIO0eNPDD1SmfDOcrNk7UI3DUhL2PxElEhERkbCoASgiIrIGaf964rxfVG2XOYa8E2wvrc+y1mdy+2/5sOvmbs2z3JD4ruxVdy0JpzaU+UR6kjEOm6ZPCVxn8Xiv4y/hBypj7c7/YUkFqnHsjIjSiIiISFjUABQREfkM488mZW8vqjbPWDqcc7p1fd96vNL6c+Zkn+nWPMttnjqd7Wv+D8cE30dNpK8YktiVDeI7B65bnH+L1vysCBKVJ2vqyLNxoJqEnajDQERERPo4NQBFRERWZjup88/EYIOX4tLu/gy6sbde1m/luZYzaPQmFz3Hcg4Jdq29glHpw7o9l0hfsHnV6RTz9vXtjj9gbfD/T1cqz2wWaHyMj0naeyJKIyIiImFQA1BERGQl1f5vcFkYuM4C7c6FeGZM0dfu9BfzXPOZtPtzi55juZQziL3r/kD/2Kbdnkukr0g7AxmeOCBwXZP3LnOyT0eQqDxlnKMC16T8u7UKUEREpA9TA1BEROR/HP8DEvahompz7E3W+VzR1271ZvJs87fI0FT0HMs1uJuxT90fqHIHd3sukb5m86rTiZu6wHWfdN2vVYAF8swYMubAQDUuc4nxbkSJREREpLvUABQREQGMXUKdfzbF3LzrU0e7e27R116UnczzLWfjkSl6juVGJ49it7rLcU2y23OJ9EWuiTM+dWLgujZ/Botzb0WQqDwtOwwk2EcF4wdfPS0iIiI9Qw1AERERoMq/BoeWwHUWQ4vze6zpX9R1F2Rf45X2n2HJF1X/KcPm6W+yWdWp3ZxHpO8bltyHhKkPXPdW5+/I264IEpUhk8QSbKVl0j4MWmUpIiLSJ6kBKCIiFS/mv0rCPlFUbYZj8J3i9v2b0fUIr7ZfBEUcOLIyQ4zdaq9gVOrwbs0jUipck2T76h8Hruv0FzAz81gEicpT3mwbaHyCF4nb5yJKIyIiIt2hBqCIiFQ0x86nxv9xUbf+eoygw/1uUded2nkf73T+sajalSVMPfvUXU9DbEK35xIpJf3jm9PgBv9zP73rQe0FWKAuc0zgmpT9RwRJREREpLvUABQRkYqW9v+AQ0fgOotLi/M7MIlgddbyQeffeL/rpsDX/KxqZyh767APqWBjUl8KXNNpF9KYnxx+mDKUN9uRYd9ANXH7OsZ2/zAjERERCZcagCIiUrFi3iQS9smiajud07DOwEA11lre7vgDn3R1f4XMQHcb9qq7joRT2+25RErV4Pj2NLhbBK6b3P4bcrY9gkRlxhg6ndODl9EcQRgRERHpDjUARUSkIhm7kBp7QVG3/ubYhi5zUqAaay1vt/+eWdnu7z82NLE/O9VehGNi3Z5LpJQZ47BdzQ8D12VtM7Mzz0SQqPxY0y9wTcJ/KvwgIiIi0i1qAIqISEWq8v+IQ/DTQC0x2txfgCm8dWitz6ttlzIr93jg633WuNSxbFN9FibA9UXKWcrpzwbxXQLXTc88GEGa8mNNHXk2C1STtjfi2qkRJRIREZFiqAEoIiIVJ+5NImGLW4nXbs7DmsJv/bXW5/W2K1mYf6Wo633KsE3VOWySPrab84iUn42TRwWu6fDnsTj3dgRpyk+XE+wwEIMl6d8bURoREREphhqAIiJSUYxtpsb+tKhbfzPsSdY9rODxvvV4ue2nzM9PKuJqnzK4bFf1Y4Ym9+7WPCLlqn98c4YlDghc93r7lXg2E0Gi8pI1B5Ij2F6LCft0RGlERESkGGoAiohIRUn7v8fQGbjOkqDT/X7h463Pf1svZnG+eyuMDHF2r72KDZO7dmsekXI3Pn08BGztZ20zc7P/iSZQOTExupzjgpWwFKyNJo+IiIgEpgagiIhUjLj/Ikn778B1FmhzLsI3Qwoa79scL7WeT6P3euBrrSxGFXvVXk19bGy35hGpBClnABvEdwpcNzPzaARpyk8xh4HE0C3WIiIifYUagCIiUhlshmr/4qJu/c2yLzmnsNtvrbW80noxS7x3i7jSp+Kmjr3qf0dNbHi35hGpJONSx2JwA9Us9T5iSf79iBKVjzyb4lNf8HgD1Hg/Ad1iLSIi0ieoASgiIhUh7f8Zh6WB6yxpOt0zChrr2zwvt13IYm9y4OusLG0GsU/tH0k7hR82IiJQH9uY4YnPBayyvNV+Ldb6kWQqGyZJxhweqMRhCQn7RESBREREJAg1AEVEpOzF/NdI2b8HrrNAq3MRvtmooPGvtl3K4vybga+zsipnQ/asv46EW9uteUQq1ahUsCYVQLs/h8Zu/n+3EnQ5J+MxKFBNUg1AERGRPkENQBERKW/WUu1fUeStv3uSd/Yo4BIer7ZexqL8a0Vc5VN1zmj2qruWuKnq1jwilazWHcGA2JaB62ZndGrt+lhTQ8YcEajG2EURpREREZEg1AAUEZGylvT/jsvswHWWFJ3u9woa+3r7r1iQfynwNVZW74xlt9pf4Zpkt+YREdi86vTAewHOz02i3ZsbUaLyYU1DoPEuC8C2R5RGRERECqUGoIiIlC3XfkiV/WNRtW3Oz/DN0HWOsdbydvsfmJ97oahrLNfP2ZRd6y7HdeLdmkdElql1RzAkvmugGp8c73bcEFGi8pEz2wcab+ikxr8sojQiIiJSKDUARUSkbFV512LwAtfl2LagU3/f6biemdlHi4m2Qn93K3at/SWuSXRrHhFZ1YjkQYFrFuVfp92bF0Ga8uGbUYGbgAn7DI4NvhJbREREwqMGoIiIlKW4P5E4bwSusyRod/9vveOmdP6DmdlHiom2woDYluxc+3McRz+ORcI2ILYVNc7wgFWWBbnu3c5fCTqcs7AEW7Gc9B+KKI2IiIgUQp84RESk7Dh2HtX+L4qqbTc/xDfD1jnmk85/8lHX34qaf7lBsR3YueZiHBPr1jwismbGGLapPgcCHgE0tesB8rYzmlBlwjNjyZmdAtU4zIkojYiIiBRCDUARESk7Kf9GHLoC1+UZRdY5dJ1j5mSe44OuW4qNBixb+bdjzfkYox/DIlGqj21MvTs2UE3GLuGTrn9GlKh8+AwMNN6xurVaRESkN+mTh4iIlBXH/5ikfThwncWlzb0M1tGUm599ickdv+pOPAa627NzzS8wJtgJpSJSnOHJAwLXzMw8hmdzEaQpH57ZNND4OO8S95+NKI2IiIisjxqAIiJSPmw7tf45GGzg0g5zGr4Ztdbnm/If8Hr7Fd0IB/3cCexUe4GafyI9aGhib+KmJlBN1jazNPdhRInKQ8YcgE91oJoq/w9g/YgSiYiIyLqoASgiImUj5d+Py6LAdT4DyDhfWevzbfnZvNh6PraIE4WXa3A3Y9faS9X8E+lhMVP1v70Ag5me1aEV62Sq6HRODVTiMouYfT2iQCIiIrIuagCKiEhZMH4LaXtD4DqLodW9Akxqjc93+ouY1PojLMXfDljrjGKX2ktxTLBTM0UkHIPj2xMzwVarzc+9wKJc8JPEK0nGfAWPwYFqYrwXURoRERFZFzUARUSk9FmfGv/HGLKBSzMciWc2W+Nznp/hheYfkaOt6GjVZji71V2Bo5V/Ir1qo/gegWumZ/4dQZIyYgyWQcFqdMKyiIhIr1ADUERESl7cvkycyYHrLEk63a+t8TnPZpnUeh4ZFhedK20GsUfdr4mZdNFziEg4RibXfcL3mizM/Zec7YggTfnwzNBA45P2cdC/UxERkR6nBqCIiJQ261HlXxW8DGhzfoo1a7597bW2X9LiTy06VoIGdq/7FTFnzbcWi0jPqouNZnTiyMB1TTndsrouGXNYoPEu80j7t0SURkRERNZGDUARESlpaf/3uMwPXJdnB3LOfmt87t32G1iUf63oTDGq2bP+tySdhqLnEJHwbZz+fOCatzp+R14r1tYqb7Ynz4RANUn7INhMRIlERERkTdQAFBGRkuXY+aTs3YHrLIYO95trfG5q5/1Mzz5YfCaS7F53FSmnf9FziEg0kqY/Nc7wQDUZu4TZmYnRBCoHxqHVvRxL4fucOiwlZt+OMJSIiIh8lhqAIiJSsqq8X2PwA9d1mZPxzBarfX1RdjLvd91YdB6Dyy61l1LjDit6DhGJjjGmqL0AZ2UfiyBN+Vi2lUIsUI2hJZowIiIiskZqAIqISElK+E+R4IXAdR5D6HS+sdrXl+Y+4b/tF3UjkWHnmotpiG3SjTlEJGrDkwdS7QRr0rd6M7HWRpSoPFjqAo137NyIkoiIiMiaqAEoIiKlx+ap8q8tqrTT+QYYs8rXsn4Lr7T/FItXdKStqs5iQHz1VYUi0re4Js4m6eMC1Vg8Pu66K6JE5SFr9gg0vsreiGNnRpRGREREPksNQBERKTlJew8OiwLXZdmFrHPIKl/L204mtfyInG0rOs/m6W8xPLnmA0VEpO9piI0HzHrHreyjrjvp9IO/7lSKjHNMoPGGLlK+mqoiIiI9RQ1AEREpKY6dSZX/x8B1ljjt7qq3+Fpreb3tCtq7cSvaiMQhjEoF31NMRHpP2hnE4PgOAat8ZmYejyRPOfDMGDrMqYFqkvZRnQYsIiLSQ9QAFBGRklLl/w5DLnBdxhyDNbWrfO2DzptZlH+96CxD4ruxRdXpRdeLSO8Zl/oqJuBb4cbc5GjClImMOSLQeEMnDgsiSiMiIiIrUwNQRERKhuNPJ27/E7jOYwM6nO+s8rXZmYlMzdxXdJY6dwzbVZ+HMfpRKlKK+sXGsWF8r0A1Ld40sn5rRInKgAl2WzUAOltFRESkR+hTi4iIlAabpcb/ccBdu5Zpcy4CE1/xz035D3mr45qio6SdQexSczGmmA+7ItJnDIxvFWi8T5a3Ooo7gKgSWPrj0y9QTdI+FE0YERERWYUagCIiUhJS9h/ECH5iZI6t8MyWn/6z38bLrRcWfeKvS4rdan9N3Kkpql5E+o4h8V1wSASqWZB7mXav+H1Dy5pxyZgjA5Wk7d9w7QcRBRIREZHl1AAUEZG+z3qk/NuDl5Ggzb14xW1pns3yYuv/4dFZZBCXXWovIeX0K7JeRPqSuFPDsOT+getmZ5+OIE156HK+iE99oJqUf29EaURERGQ5NQBFRKTPS/t/wGFp4LoO8zWsGbTin9/quI5Wf0bRObar+iH9YpsUXS8ifc+m6a8RN3WBaprzUyNKU/qsGUiHc0agmrh9NqI0IiIispwagCIi0qe59j3S9u+B63xqyDpfWPHPMzOPMzdb/IfM8amT2DC5e9H1ItI3xUyKwfHtA9U05ifT6gXfkqBSWPoHGu/QClangYiIiERJDUAREenTUv5tgWss0OZcjDXL9ulrzL3J2x2/LzrDhvE9GJv+YtH1ItK39Y9tHmi8Jc97HTdElKb0WVMbbDwxIBtNGBEREQHUABQRkT7M8T8mYScGrsuxA3lnZwDyfievtV/OsrZgcHXOxmxdfXZRtSJSGjZK7EXMVAeqacy/SZs3O6JEpS3PpvgMKHi8IU+1f1mEiUREREQNQBER6Ztshlr/XEwRpV3uqcCyQz8mtZ5H3rYXFSFh+rFr3WW4JtgpoSJSWmImxYT0SYHrGnNvRpCmDJgYXc7RgUqS9gkc/8No8oiIiIgagCIi0jcl/CdwWRC4rsscRt5sDcC7HTfQ6k8v6voGl51rLiJmqoqqF5HSMjJ5CEkTbO+6Jk8Nq7XpMseTZ3SgmqT3z4jSiIiIiBqAIiLS91iPKnt94DKfGjrMjwCYm53ErOxjRUfYofoC6mLBPryKSGmrdUcEGj8v+xxL8x9FlKbEmRQZc0igEtd+EFEYERERUQNQRET6nCr/dzgsCVzX5RwHTpyW/DQmt19V9PXHJL/A4ESwU0FFpPRtmNgj0HiLz5SuuyNKU/qMcYMV2Fw0QUREREQNQBER6VscO5+k/UfgOo/BdJkv4dscr7X/EotX1PUHxbZjfPrEompFpLQNTexNwtQFqlmY+y+dfmNEiUqbx9BA4x0WYv3miNKIiIhUNjUARUSkT0n5N2LwA9e1Ob/Akub1tivp8OcXd20zkB2qL8QY/XgUqUSuSbJd9XkBqyyt3oxI8pS6nNkVn8L3VTS0YZt/HGEiERGRyqVPOCIi0me49gOS9uHAdTm2xXO2YmbmcRbkXy7q2g4Jdq79BY6jH40ilWxAfEscYoFqFufeiihNiTNxupxjg9VknsIp8vAmERERWTt9yhERkb7BWqq9XwZe/Wdx6HRPpyU/jXc7/1T05Xeo+Qk17rCi60WkfNS4wwONn5Z5gJb8tIjSlLYucyx5NglUE/cfiiiNiIhI5VIDUERE+oSYfZMYUwLXZcxRZBjPy60/L3rfv42TxzAovl1RtSJSfoYnPhdovMVnWuZfEaUpccbBM8EagI6dG1EYERGRyqUGoIiI9D7rUeVfGbyMBJ3Ot3mz/TqyNBV16QGxLZmQPqmoWhEpT8OS+5FkQKCaudnn8WwmokSlzRIPWBB8H1gRERFZNzUARUSk16Xs7cSYHriuyxzDtMxzzMs9V9R149SwXfV5OvRDRFYRM1VsVXNmoBqfLBm/uF9ElLu82SzQ+JidjLFLowkjIiJSofSJR0REepfNkfLvClzmMYgmvsp7nTcUdVmDy841F5Nw6oqqF5HyVuuOCFzTmH87giSlL2v2x6e24PEOS6jyfxthIhERkcqjBqCIiPSqpP0nThG377ZyJi+2/bToff82TZ1CfXxMUbUiUv5Spj9J0z9Qzbsdf6LLXxxRohJmUnQ63wxUkrBPY2xjRIFEREQqjxqAIiLSaxw7h7Qf/ORejw2Z3PU+Hf68oq47OLYjo1JHFFUrIpXBGJcRyQMD1fhkmZl5LKJEpS3jfAGPwldVGjwS9tkIE4mIiFQWNQBFRKTXpPxbcQi2ab7FMMM/hVm5J4u6ZtpswA41P9G+fyKyXqOSh5M0DYFq5mQnRhOmDFhqAo03LI0miIiISAXSpx8REekdXitJ+0jgsiZ/J15q/1uRF3XYtuaHGOMWWS8ilSTh1DEu9ZVANZ2+bltdG2uqAhZEk0NERKQSqQEoIiK9o+3nGPKBy17OOHh0FXXJraq+R0NsfFG1IlKZqtwNA4235FmanxJRmtKWM7sEGp+0j2JsS0RpREREKosagCIi0uNs5kVM9uHAde/mtqOxyA/Wg2M7MTy5X1G1IlK5+rnjcEgEqnmt7TI8m4soUenKmMOwAf5duswh7d8UYSIREZHKoQagiIj0ONse/APdIi/N612zirpe0vRjm+qzi6oVkcoWd2rYKLFXoJouu5j5uUkRJSpd1tTT4ZwdqCZhHwLbGU0gERGRChLr7QA9rbm5mXvuuYdXXnmFxYsXk0wmGTNmDIceeii77BLstoTPyuVyPP7447zwwgvMmjWL9vZ26uvr2Wijjdhqq604+uijSSaTIX0nIiIlKj8DAm6Sby282DUEaC3igoZdan9J3Am2+byIyHKbpI9lfnYSeToKrpmbfZahib0jTFWaMs7RpP0/4hT4eu7QRsy+Rd7sHHEyERGR8lZRDcCZM2dy/vnn09zcDEA6naa9vZ3JkyczefJkjjjiCL7xjW8UNffcuXO5+OKLmTNnDgCu65JKpVi8eDGLFy/m7bffZv/991cDUEQqm81D8xmBy17N1NHsF9P8g3Gpr1DjDi2qVkQEIO0MYlhyf6ZnHiy4psNbFGGi0hZ0/1dDe0RJREREKkfFNABzuRyXXHIJzc3NjBw5kh/84AeMHj2aTCbDAw88wO23386DDz7I6NGjOeCAAwLNvWTJEn7yk5+wZMkSxo8fzwknnMAWW2yB67pkMhlmzJjBpEmTSCSC7R8jIlJuEvZZjP9JoJoF+Rgf5Ip7/ewf25xxqWOLqhURWVmVs0Gg8R3+PDJ+E0mnIaJEpcunHpfCb+u1tmI+soiIiESmYvYAfOyxx5g/fz7JZJILL7yQ0aNHA5BMJvnyl7/MIYccAsBtt91GPh/st5LXX389S5YsYbPNNuOyyy5j6623xnXdFfNvsskmnHLKKdTV1YX7TYmIlJiUf2ug8Z6FF7r6FXUthwTbV/8EY0xR9SIiKxsQ2zLQeJ8sb7ZfHU2YEpczwW6NrrK3gM1ElEZERKQyVEwDcOLEiQDstddeDBo0aLXnv/CFL2CMYcmSJbz99tsFzztjxgxeeuklAL7zne8Qj8dDySsiUm7i/vO4FH6Cr7XwYmcN7ba4621XfS4Jp7a4YhGRz6iLjabB3TRQzaL8G7R6MyNKVLq6nGOwAT6GxHifpL0/ukAiIiIVoCIagJ2dnUyZsuxD53bbbbfGMYMGDWLYsGEAvPnmmwXPvbyxOHr0aEaMGNG9oCIi5cp2Ue1fSpC1eAu8GNO8VFGXG5E4hA0S2jBeRMK1edU3MLiBauZkn4koTenyzXA6nLMC1aT8+5b9ZkhERESKUhEbasyePRv7vzcMI0eOXOu4kSNHMmvWLGbNmlXw3O+//z4AG2+8Me3t7dx99928+OKLNDY2Ul1dzbhx4zj00EPZYYcduvdNiIiUsIT/OA4tBY/PWcPzXcVtm5CggQlVJxVVKyKyLvWxsQyIbUljfnLBNZ1eY3SBSljWHEQ1vy14vMtMHObjs2GEqURERMpXRTQAlyxZsuLv+/fvv9Zxy59ramoqeO558+at+Pvvf//7zJ8/H9d1SafTtLS08Oqrr/Lqq69y1FFHceqppxaRXkSkxFmftL0pUMkLXTV02eCL1A0Ou9ReTNxUB64VESlE2ll9K5l1afamYK2PMRVx403BTIBDQD7VFXoOERGRSlERDcCurk/fLCSTybWOW/5cZ2fhb0ja2toAeOaZZzDGcNppp3HQQQeRTCZZsmQJt9xyC8888wwPPPAAY8aMYZ999lnnfLfddht33HHHWp8/9thjOe644wrO19scx1nxvw0NOgWvki0/iKG+vn7FilypEO3XYjoWFDx8QT7GrPzaX6vXZct+pzCi/9ZF1UrP0+uCQOm9VxgW25FZi54oeHy7P5d5zqNs3u/4CFOVIJvENroYvIJL6us3Arfv/xmR7iu11wWJht4niISrIhqAUVr+QuT7Pl/84hc58sgjVzzXv39/zj77bGbNmsXHH3/MP/7xj/U2ANvb21m4cOFan+/o6FhxwnApMcaUZG4J3/I3dFIZrN+K7byl4PEZa5jYWdytv/XxUWw54ERcR681pUavCwKl815h47rP8fri35HxC9/W4P3mO9m84au4TiLCZKWmFj+5H2QKb6aa9isw/a7R6e4VpFReFyRaep8gEo6KaACmUp9uIp/JZKiqqlrjuEwmA0A6nS547nQ6TWtrKwBHHXXUas8bYzjqqKP49a9/zaxZs1iyZMk6b0Ourq5m8ODBa32+qqoKzyv8N6W9zXEcjDFYa/F9v7fjSC8yxuA4Dr7v6zd4laTjLoztKHj4S101ZIs4n8olwec2ug5jYyX1Glnp9LogUHrvFQwxth/wXSYturTgmi5vKTNbn2dEzT7RBStFqRMwARqAZB7F75wIyb0iiyR9Q6m9Lkg0Svl9ghrX0hdVRANw5YbbkiVL1toAXL5XYJBl5v3796e1tZXa2lrq6+vXOGb56cIAjY2N62wAnnDCCZxwwglrfb6xsTHQHoW9raGhAdd18X2/pHJL+FzXpaGhgebmZjVoKoSxLdR7fyz45N/GvMvMfHGrY8alj6ezxdKJXmdKiV4XBErzvUIDO5MyA+myhR/wsbD1Y2pz2qJgVeNIcyJp/lZwRa71Vto6towwk/QFpfi6IOEr5fcJAwcO7O0IIqupiLW0w4YNW3GrwMyZM9c6bvlzw4cPL3juESNGBMqiWxZEpFKk/T/g0FrQ2C7f8FRnPRTcLvxUP3c8GyePXP9AEZEQpZy1/0J3Tdq9eesfVIFy7q6BxsftaxElERERKW8V0QBMp9OMGzcOgNdff32NYxobG5k1axYAW29d+G9nt9lmGwBaW1tpbm5e45jZs2ev+PtBg4KdHCciUoqMbSFpHy14/OuZ6iJv/U2xc83FGKPbLESkZ9XFxgQaPyf7DM35qRGlKV3GBjvZ19AFJXYroIiISF9QEQ1AYMXhG8899xyLFi1a7fl7770Xay39+/dnyy0Lv61g1113XbFn4P3337/a89ZaHnjgAQDGjRtHv379AmcXESk1Sf8fGLIFjW3yXD4p8tTf8ekTiDmp9Q8UEQnZyMTBgcb75Pi4666I0pQu3wwINp7C9+oWERGRT1VMA/Cggw5iyJAhdHV1cfHFFzNt2jRg2cEf99xzDw899BCwbA++WGzVrRFPO+00jjzySK6++urV5q2pqeHLX/4ysKwB+OCDD644TKSpqYmrr76ajz/+GGMMxx13XITfoYhI3+DYWaRsYfs5Zazhqc46irn1d2BsG0YljwhcJyIShrrYaDaKBzuMYkHuZbr8JRElKk0eY/EYVfB4h05S9ubI8oiIiJSrijgEBCAej3PBBRdw/vnnM336dM466yyqqqro6upacbLU4YcfzgEHHBB47mOOOYbZs2fz1FNPccMNN3DTTTeRTqdpa2vDWovjOHz9619n++23D/vbEhHpc9L+LTgFrv57J5Om0wa/fdchznY1P9a+qiLSq7aq/h7zlv4HS2GnlFp8WrxpgfcPLGvG0OV8mWr/yoJL0v5fyZqD8c2GEQYTEREpLxXTAIRlB3Zcd911/POf/+SVV16hsbGR6upqNt54Yw477DB22WWXouY1xnDWWWex44478thjj/HJJ5/Q0dFB//792XzzzTnqqKNW7EEoIlLOjG0lYR8vaGybZ3g/V9ytXJtVnUrcrPlEdxGRnuKaBIYYtsBfegDk/UyEiUpTxhxJnBdJ8HxB4w0+Sf8BOt1vRZxMRESkfFRUAxCgX79+nHrqqZx66qkF1/zlL38paNxuu+3GbrvtVmw0EZGSl/Rvw5Bf77i8hSc767FF3fq7LSOThxYTT0QkdFXOENr8mQWPn555gCGJnXBMxb0NXzvjkDM7k7CFNQAB4va/dKIGoIiISKEqZg9AERGJlms/Jm1vL2jsx7kUrbaYD78OW1d/r4g6EZFoDE9+LtD4Ju99ZmefjihN6TIm6MrIYKcHi4iIVDr96lFEREKR8u/GFLAPVtYa3shUF3WNLdLfIuUEOzFSRCRKwxP780nnP8mytOCaGZmHGZE8MLpQJcgn6L6IWscgIiLrNnHiRCZOnAjAKaecwqhRo3o1T2/TT04REek+P0fCPrLeYdbCMx215Iu49XeAuyUjUwcXk05EJDJxp4Ztqr8fqKbFm0rGXxpNoBKVM7tjKXxfWJepxP2XIkwkIiKlbuLEiVx00UVcdNFFTJ8+vbfj9Do1AEVEpNvS/nUYvPWOm5uPs9BPFHWNzau/WVSdiEjUqtwNAtfkbUcESUqXNTVkncMLHm+wVPuXgV3/vrMiIiKiBqCIiHSTaz8hzT3rHedZeDFTU9Q1JqROptYdWVStiEjUEqYucE2rV/jBIZWiK3YGuBsXPN6hkbh9LsJEIiIi5UMNQBER6Zak/8+Cxr2SqaHTuoHnr3PHMCb9hcB1IiI9Je7UMDC2daCaN9uv1m3An2XSkNglUEnC6jZgERGRQqgBKCIixbNZkvbR9Q5r8R0+zqWKusSm6VOKqhMR6UmjkoXfvgqQp4NZmccjSlPKgp0GbGiPKIeISOWYOHEixhiMMfz85z8H4OOPP+ass85i/PjxVFdXM2TIEA488EAef3z1n12TJk3iuOOOY8yYMaRSKTbYYAO+9KUv8eabb642Np/PU1tbizGG3Xfffa2Zjj/++BWZxo8fv9ZxZ5xxxopx7777LgA///nPMcZw0UUXrRi37777rhi3/FFph4KoASgiIkWr9n+FoWudY6yFFzpri5p/ZPIwBsaDraoREekNg+M7sWF8j0A1s7NPR5SmhDnBTgP2bXH7yoqIyNrdd999bLvttlx77bV89NFHdHR0sGDBAp544gkOOuggLr30UgCstfzsZz9j99135+9//ztTp04lk8mwcOFC7rnnHnbccUcefPDBVeaOxWLsueeeAPz3v/+lra1tjRmeeeaZFX//0UcfMWfOnDWOe/rpZT9LN9hgAzbffPNuf+/lLNbbAUREpDQ5diZJ++/1jns/l6LRjweeP2UGsHlaB3+ISGkwxrBRYm/m5f5TcE2nvyjCRKXJpA7Ctt9Q8PgEL9NpF2LN4AhTiYhUjtdff50rrrgC13U588wz2WmnnXBdl4kTJ3LTTTeRz+e54IIL2H333Xn99df5xS9+wciRIznllFOYMGEC7e3t3H333Tz++OPkcjlOOeUUPvzwQwYOHLjiGvvttx+PPPIIuVyO559/nkMOOWSVDO+//z7z5s1b5WtPP/00J5544ipfmzdvHh988AGwbIXfcl/96lfZZpttuPPOO7nrrrsAuPjii9liiy1Wqa+qqur+v7ASogagiIgUJenfu94xeQtvZYr7wTo+fSLGmKJqRUR6g2uC/bLDYrHWw5jg+6OWKxPfipzZnJh9t6DxDkup9n9Nm3tFxMlERCrDgw8+yKhRo3j66acZPXr0iq8fd9xx7LHHHpx88skAfPe732XKlCkcdthh/OMf/yCdTq8Ye+qpp3LyySdz6623smTJEm666SbOPffcFc+v3Kx76qmnVmsALl/9l06nGT9+PJMnT15jA3DlVYL77bffir+fMGECEyZMYPLkySu+tscee7DPPvsU8W+kfOgWYBERCc62k7QPrXfYa5lqckX8qBkU24Fhyf3WP1BEpA+pd8fiBPj9uiXP+503RxeoRHXGfo5Pev0D/ydu/4Nj561/oIiIFOT2229fpfm33EknncS4ceMAeOedd6ivr+eOO+5Ypfm33CWXXLLil/mPPrrqnuHbbrstDQ0NwKe38K5s+dd22223Fc3BlZt9nx0HqzYAZc3UABQRkcCq/V/hrGfj9Xn5OB8VcfCHQ4Ltas5d/0ARkT4m4dQxJLH2Dc3XZFrmAdq9uRElKk2+MwKPCQWPN1ji9rkIE4mIVI7tttuO3Xbbba3Pr3xwx0knnURdXd0axw0fPpyRI0cC8N57763ynOM47L333gC8+eabLFmyZMVz1lomTpwILGvqLW/szZgxg08++WSVeZY3AEeMGMGYMWMK+fYqmhqAIiISiLELSdgn1zvu9UwVEPwW3o1TnydmCl/5ISLSl2ySOhY3wOo1gJmZxyJKU7oM2UDjHdsaURIRkcqyyy67rPP5IUOGrPj7nXbaqaCxTU1Nqz23/DZg3/dXWd335ptvsnjxYgD2339/dt99dxKJZQc+rbzib8aMGUybNg3Q6r9CqQEoIiKBJP0HMHjrHDMjl2BJEQd/1DjD2ST11WKjiYj0ump3I0YkDwxUsyT/fkRpSpdvaoKNp7I2chcRicqAAQPW+XwymQw8NpPJrPbcyk27lRt7y5uBdXV17LDDDqTT6RVNyZXH6fbf4NQAFBGRghnbQsres84x7b7Di13BPrgtt131edoMX0RKXsKpDzQ+bzsjSlK6cmaPQOPj9r9g1/3LKRERWT/HKbxNFGTsZ22xxRYMHrzsBPc1Nfb22msvXHfZ54LlDb6VVwqqARicGoAiIlKwtP8HHNZ9m9U72XRRB38Mie9KbWxEsdFERPqMtBkYaHynv4CMv/rtUZUsYw7GBljVl+BlUvbuCBOJiEjYlp/K+8EHHzB37lw8z+O555bt6bpyU2/53y9YsIB33112SvzyZuC4ceMYOnRoD6YuXWoAiohIQYxtIWnXvU9Vhw9Tijj4I0Y1W1efVWw0EZE+ZYPEzsQC7APo0cXk9qujC1SKTDXtzo+xAUqS/j1aBSgiUkI+exvwq6++SktLC7Bs/7/ldt55Z6qqqlaM+/DDD5kzZ85qc8i6qQEoIiIFiftPYFh9/47lfAsTO+uxRRz8sUXV6cSM9m8SkfIQM2lGJA8OVNOYf4NWb2ZEiUpT1jkAn8JXU7rMI8Y7ESYSEZEwfbYBuHxV36BBg9hyyy1XPJdIJFacPrzyuM/O8Vkr36JsbZBfKZUnNQBFRGS9jG2hyv51nWOm55MsLuLgjypnIzZMBNvrSUSkrxufPoG02SBQzZzMM+sfVGEcOoKNt40RJRERkbCNGzeOYcOGAcsae8v39dtnn30wZtVFBcsbfc8++yxPPvkkAMaYFacJr0lNzaf7kre3t4eavRSpASgiIuuV8v+Gw9J1jnkzU8wKPsNONRfimFhRuURE+irHxGmIjQ9U06nm1WoswbaVCDpeRER61/IG3owZM1as7Fv59t/lljcAm5qaeOCBB4BlB4kMGjRorXOPHj16xd+//vrroWUuVfrEJSIi62YzJO2D6xzybiZFmw1+eu+IxCFUuxsVm0xEpE9zTbBmVN4PttqtEuTMdiTtkwWNtYBRE1VEpKTst99+/O1vfwMgn8+v+Npnbb/99tTV1dHS0rLOcSvba6+9SCQSZLNZrrrqKgC23nprkskkAOl0mr333ju076WvUwNQRETWKW5fxqFlrc+3+g6vZ6sDz+sQZ0zq892JJhGw1tKa72BWZgELc03M6JxHm9dFS74Nz/rkrUfMcYkZl3q3hupYilGpjdgg0cCI1BDSTnK1WzZEKlX/2GbMyj5e8PjG/BsszU+hX2xchKlKS8Y5hqRXWAPQANX213h2UzyzSbTBREQkFJ+9hXf48OGMG7f6z0HXddlrr73497//veJr62sADhgwgB/96EdccskltLW18bOf/WyV50eOHMn06dOLD19i1AAUEZG1s+1U+b9Z55B3s2ko4uCPnQaeQ5UXbH8sCV+H18XrrR/w35YPmNY5h1avEx8/4Cyvrfg7B0O/WC1j08PYqX5ztqoZQ9JJhBtapERsmNiD9zr/Ss62FjTeJ897HX9ht7orIk5WOvJsTcYcQtI+UtB4Q56Ufyft7oURJxMRkTCMHDmSjTfemKlTpwKrNwRXtt9++61oALquW9DqvYsvvpitt96am266icmTJ9PY2Eg2mw0nfIkxVkehlJTGxtK6raGhoQHXdfE8j6ampt6OI73IdV0aGhpoamrC87zejiMFSvl/p8q/bq3Pt/gO/2pvCHzyb0NiHIcNu1GvC73AWsvHnbN5esl/eaN1Cp127Sc7h6WfW8Ou9Vuwf/8dGZRoWPF1vS4IlP97hdmZp3mz4+pANXvWXkNdbPT6B5aZtb4m+F00+AdiyBc0jyVOk/swmOCr06VvKPfXBSlMKb9PGDiw8BPMRXqKVgCKiMiaWUvSv3ddTzOxsy5w8w9g6/6ndCOYFKMp18rfFzzOm21T6PJ79reeS702HlnyEo8seYl+sRp2r9+KowftTdoNvm+kSKkZltyPKV130uHPL7hmcf7timwAro0xrQU3/wAMORwW4aMGoIiIyHJqAIqIyBq5diouc9b6/Nx8nGY/+I+RoendGFGzD74f9DZTCcpayxttH3HbvEdZnG/u7TgALM238dDiSTy8+EXGV4/k3M1OIokagVLeYibYKeme7YooSakq5jVCrysiIiIrUwNQRERWZ3NU+xes/WkLr2RqAk9riLP74At1SETEcn6exxa/xAOLnidLrrfjrJHF8kH7dE797y8YmhzENzc6mlHpDXs7lkgkkqY/MLXg8a3e7OjClCBLPzw2wGVBgeMdrHWL2Z5WRESkbDm9HUBERPqehH2GGDPW+vyb2SrabPDVFSOSnyPh6pasqOStx78WPce3PriCfyx6us82/z5rTmYRP5t2A+d/cj2zuxb2dhyR0A1N7BVo/NzcRBblXo8oTQkyDhnnqMKH41Prnwc9sMepiIhIqVADUEREVpP071vrc1lreD+bDjxnwtQxPnVCd2LJWlhreb5pMmd8cBX/XDSRPKW1UfZyszMLOX/q9Vw14zba8h29HUckNEMSu5MyAwLVfNx1T0RpSlPGHIPHkILHx/iEhH0iwkQiIiKlRQ1AERFZhbGLifH2Wp9/J5MmX8R9VVtWnUncCX7bsKzb9M55/PiTP/CXef+iy/bs4R5Read9Kmd+9Gv+teh5rLW9HUek21wTZ/ua/yPIPalL8u/Q7s2NLlSJsaaONucXBHlFSPn3RxVHRESk5GgPQBER+ZS11HgXYFjzAR1LPZf3c8FX/9U4w9kgvnN308lKMn6Wm+c9xKTmtTdrS5nF8s9Fz/BU06v838iTGJIMtnpKpK/pF9sEhxh+gFvz27w5VLsbRZiqtBi6Av36yeXDZZvWat9ZERERrQAUEZFPxXibOG+u9fnXMtX4Raz+27zqGzr4I0Tvtk3lzA9/VbbNv5Utzbdy3ie/554Fz2g1oJQ8E/BkWhtovVslCHp6vP3fQ0RERNQAFBGRFZLruF2qxXOY6yUCzzkkvjsD49sUH0pWyFuP62bdzZUzbyNr870dp0c9uPh5fjr1zyzJtvR2FJGi1bmjAo1fmHtZje+V+GZYoPGWGnQUsIiIyDJqAIqICADGtpGwz67xOWvhha7aoubdNP217sSS/5nROY8ffHQNr7Z+0OPXjpsYVSZJvVtDP7eWereaKidFrId3EpmVWcC5n1zHe23TevS6ImEZkTw40PhZ2SdYmH81ojSlxzcbkTPbFzzeoYWUvSnCRCIiIqVDewCKiAgAVf6VGDrX+NzHuSSNfjzwnMMTn6PKHdzdaBXNWssTS17hjgWPRX4jm4vD0ORgJlSNYMe6TRmeGkLaTa63rt3rZHrnPF5peZeP2mcxL9cYWda89bhi5t84fMDufHHwfrq1XErKhok9mZq5j1ZvRsE107v+zQbxHSNMVVo6zYnE7WsFj0/7N5I1h+CbDSNMJSJSenw/V7FbpC5bXR/DcSprTZwagCIigmPnkbBPr/E5a+H9bPCDP+Kmhs2rvtXdaBXNtz6/m/0PXmv9MLJrVDspdqnbgsMG7saARL/i5nDTbF6zMZvXbLzia7O7FnLfwolMbptCHi+ktJ/69+IXmNY5l7NHfJWEE7w5LdIbXBNn2+pzea7lzIJrGvNvkPPbdIr6/+SdneiwX6OqwJV9Bp+k/wCdrn4eiYgsZ/1mWLgbNsDBVGUnvhMMuK23U/QoNQBFRISE/+haT/6dlY/TbIP/uNgkdQKuUWOmWE25Vi6dfhOLcktDn9vFYbva8Zy84WHUxqpCnx9gWGow3x3xZQCmtM/i5nkPMTu7MNRrvNsxjQs+uZ6fbfwNqt1UqHOLRMUh+Oti1rYQRw3A5awZFOhsj7h9hU7UABQRWc76rVhylb1Laj66X7D3VWoAiohUOpslae9f41NdvuHFruAfOuOmjmHJfbsZrHJN65zH5dNvoctmQ5037SQ5ZMCuHDFwT5wevOdjXPVwLh37LVrzHfxpzn283f5JaHMvyDXxwynX8rPRpzIkOSC0eUWiEjPBV1SbIpqG5a0r0GgTcLyISPmz6z1pvhxOojfraHFa61XcoRhqAIqIVLi0fyMui9b43Ee5FFncwHNuX/3joj7kCkxu/YirZ90V6puutJPky4MPYN+G7Xp1z7zaWBU/HHk8bflOfj/7H7zXMT2UeTv8Ln469U+cP+prjEprny/p2xKmnjp3NC1e4YfZfNh5K9tU/0B7Xv6PpX+g8T7RrHQWESlZFjzrB1oBGOS9aVg/rYK+Gw70/RhbcQ2xSmt4iojIymwXSXvfmp+y8F4Re//1cycwIL5Fd5NVpH8veoHfzroztOafi8MXB+3LH8afy379t+8zzYOaWJrzRp3EFePOZKPUwFDmzNo8P5/2Fz5oL/xwBZHeYIxhZPLQQDVzc8+yOP92RIlKT9bsjqXwn08xpuLaqREmEhEpMQb8gH/Zz/zlr+PhhfRY1zW6e13flv4Kx6DUABQRqWBx+yIOrWt87s1MmlwRPybGpr7U3VgV6f6Fz/GPRU+FNt92NeO5bvw5HDFoTxzTN3/cD00N4oadLuTUjY7ADeEticVyxYxbmdzyUQjpRKIzLLE//d3NA9XMyDwcUZoSZKrJmMMKGmpZdgtwtXfhst9siYgIy28BDtpgW/mxekMw+r9Wv+qa/yp0tkpTaSseRURkOWtJ+bev8akW3+HtXPBbpgbEtmZwfIfuJqso1lr+OvdfPN/8Zijz1Thpvjvsy0yoGRnKfD1h3wE7sFPtZlw6/RZmZuZ3ay4fy9Wz7+SHI45ni5oxISUUCZdjYmyc+jxL2t8tuKYxH85rRLnocL5NzHudGOte2bd83XOMqcTs6+TN9tGHExHp4yzLbgEuPSE27UzlNQD75pIAERGJXMI+RJz31vjcB9k0wXfvMGxb/cM+c5tpqQiz+bdj7QSuHX9OSTX/lku5SS4e801O2ODgbs9lgV/PvIO3Wj/ufjCRyAT74JG3OshiFSZNzuwcqCRhn44ojIhIqXGwUNmPyuv/qQEoIlKRrCXl373Gp7LWMCWXCjzlsMS+JJ367iarGL61/H72PaE0/1wczh1+PGcO/zJuH73dt1CfG7ATF4/+JrVO9zbt97H8dtbfmdIxK6RkIuFKOg2Bxjs4eDYTUZrSZGgLNN6hKaIkIiKlp9DbaaP6q/AbeqP7q9KU9qcEEREpisN0Yqx5ddR/OmsJdiYYGFw2Tn0+jGgV44Y59/NKy5pXYAYxNDGIa8efwxa15XO764j0EH61yfcYndqoW/P4WC6ffiszuxaElEwkPPXuWKqcIQWP98nxZvs1ESYqRcF+UWCtTqcXEVmuO/v/hfGwvXhtvyLbf2oAiohUpJR/5xq/vthzmeMlAs83NvVFat3Su+20N1hruXHug0xq6f6JnrvXb8XFY06nxi2/D7UpJ8HPRp/K5xp26tY8eTwum34zC7Na+SN9izEOo5JHBqqZl/sPzXmdZrtc0FuAHWaD9SJKIyJSOiw+HlT2Q3sAiohIuYvZt0nZB9f43DvZ4I0klzRjUl/sbqyKceeCJ3h26RvdnufUDY/gm0OPLvlbftfFGMMJGx7MVwcf0K15Ov0Ml0y7iYyXDSmZSDhGJQ+hv7tFoJqZmUcjSlN6cmYnPIYWPD7O26T9myJMJCJSKkyvrwDsC49KU76fGkREZI2Sa9n7b4nnMiufDDzfiOSBuCZ4XSV6uHESjy55qVtzxIzLBaO+xl4N24aUqu87ZOBufG/YlzGBD6b5VLPXxiXTbyLr50JMJtI9xriBT05v9j6JKE0JMg7tzv9hcQsuSdq7wXZGGEpEpDR41lb8o9KoASgiUklsloSduPqXLUzqqsUGbLAkTD/GpY8NKVx5e67pDe5a+GS35qh201w8+nTGVQ0PKVXp2L5uAj8ZdTJuN966zMws4Po594aYSiQEAW9B8nUL6yryznbk2K7g8Q5tJOyzESYSESkNPr2/D6C/IkdYj2DXrjRqAIqIVJCE/ziG1T88LvJjNPmxwPNNSJ9C3HTvtNZK8EH7dG6c9+9uzdHg1nL5mO+wUWpgSKlKzyZVIzhv5IndagK+1voh/1r0fIipRLqn2gl22E3GLtZpwJ9hCPbvw2FORElEREqDtRBNAy7Khl3YDUWtABQRkTJl7GKq7a/X+NxbmeBNvKRpYGhiz+7GKnszO+dz1Yzb6c5ZYxslBnL52DOoi1WHmKw0ja8eyU9Hf51YgFv+Puufi57h5eZ3Q0wlUrzB8R1ImPqCx2dtM293/CHCRKUo6Eea4l8/RETKglnWBOztR0/rzWv3BWoAiohUiKT91xpXSczMJZhXxMm/49JfwTHxMKKVrbZ8B1fM/Bv5Nay6LNSw5GB+vvE3SLnB/xuVq9HpjTh35AndWgn457n3syTXEmIqkeI4Js7GqWMC1czJPkuHtzCiRKUnbzYNVmD1EUhEpPdX/4Fne/axyvUrsAuon34iIhUi6T+y2teshTezwVf/1TqjGJE4JIxYZavLz3Lp9Jto84rfbH50aiMu2vgbJB01Wj9rQvVIfjTyRJwiDwbJW4+Lpv2VtnxHyMlEgts4eTR17tgAFT5zsk9HlqfUZJyjAo1P25tw7YcRpRERKQ0+YD/z6O2GYJSP1b/X4g+XK1VqAIqIVADXfrLGPY8WeTGWFrH33/j08RhTeT80g7h+9n3MzS4uun5YchDnjzqFmNGtamszoXok3xx6dNH1S/Ot/HnuA+EFEimSMYZaJ9jhPu3+3IjSlB7fjKDLHFHweEOGtP/XCBOJiPRx1uLBao/VVuiV0SP/mYdOARYRkfJjPWq8n2A+swedtfBaJviecmlnMIPjO4SVrizdt3Aib7QVv7pko8RALhx9KnEneHO20uxavyVfH3J40fVvtk3h8cUvh5hIpDgmaLO/Aj+4rEuH80M8Cj8kKW4n4dgFESYSEem7LP87CGQ9D2vNKg+/pB7r+f4qsB0W6nf8+OOPhzmdiIiEIG5fxGXWal//OJek0Q9+a+k21T8I/kG1grzV+jH3Nz5XdH3/WC0/H30aSUd7/hVq7/7b8bmGnYquv33BY3zQPiPERCLB1btjAo1v8j7UacArM3EM+cKH4+PaDyIMJCLShxnwMAU81r9CsLdv7V37w6z7UYG/SAu1AXjwwQczduxYrrjiChYu1MbEIiJ9QcI+vNrXrIUPcunAczW4m9E/tlkYscrSguwSfjf7H0XX1zppfjb6NJI68COw44YcxLY144uuv37OveT8wpsHImEbmtwHl2TB4zv8+XzQeUuEiUpR0AOXij+gSUSklFnCua3WL6iJGNWju/krbzuj0Nc8Tps2jZ/85CcMHz6cr3zlKzz11FNhX0JERApkbCsJu/rtjY1F7v03Nv3FMGKVpZyf56rpt5GxuaLq4ybGzzb+Bv3itSEnqwyOMXxv2JfYMDGgqPqmfCtXz7qzIn8bLH1D3FQzNvWlQDWzMk+Qs+0RJSo9PhsGHF/c64WISMmzYDEhPD57uEYYc/bMtXQISDedfPLJpFIprLXkcjnuueceDjzwQDbZZBN+9atf0djYGOblRERkPar8KzGsegqtZ+GlTE3guerdMQyKbRtWtLJz09x/syi/tKhaB8OPR57IoES/UDNVGsdx+NHIE6lyUkXVv9M+lf8sfTPkVCKFG5P6ElXOkILHe2RYkH0pwkSlJeMcFmh8lf9XsFr5KyKVyFltf79wHqzzsfa9Bgt5FJ9rTXsEogZg99x0003MnTuXa665hi222AJrLdZaPvnkE8477zyGDRvGcccdx8SJE8O8rIiIrIFj55GwT6/29am5ZFGr/7avPl97/63FU0v+ywstbxVdf/rQoxlbFewEUFmz/vE6/m/kSUXX3zr/YRbnmkNMJFI4YwwxE+xwpi6/+NPGy03WHIJP/4LHx3mVpP1XhIlERPqu9e6RF8FjXavxevy6Vg3Abquvr+e73/0ub731Fi+88AInnXTSilWB2WyWu+66i/33358JEybw29/+liVLloQdQUREgIT/GJ89+RfgwyL2/hvgbkPaLfx0xUqyNNfK7fMfK7r+i4P2ZZf6LUNMJCPSQzh5yKFF1eZsnl/NvIO81d5g0jtcU/g+gP+riCRHKbKmhlb3KmyAfydJ/16dqCwiFcj24t59feRh1AAM1a677srNN9+8xlWBU6ZM4Yc//CFDhw7lxBNP5Pnnn48yiohIZbGWhF29KbXUc2gqYvXf6NQRYaQqOxk/y8XTb8TDL6p++9oJHDFoz5BTCcB+/XdgtyIbq3Mzi3hi8SshJxIpTP/Y5oHGz8+9gFfk3qPlyGMEy7aGL0yMqTgsiDCRiEjf1OsNuD7wqDSRNgCX++yqwBNPPHHFqsBMJsMdd9zBPvvsw+abb861117L0qVLeyKWiEjZStq7iDFjla95Fp7trAs814DY1gyO7xBWtLJy67xHaCzydtEN4wM4fejR4QaSVZyy4WEMjNcXVXv3wqeY2TU/5EQi6zcyeTBB3qI3ex8zteve6AKVGEPwQ1GKqRERKWUW8K1T8Y9K0+Pf8a677sott9zC3LlzOfPMM1d83VrLBx98wPe//32GDRvGGWecwZw5c3o6nohI6bN50v4dq315Zj5Biw2++m/rqu9iKnCJ/Pp80D6D/zQXd2BElZPkgo2/TtJJhJxKVpZ0Evx45MnETfA/9z4+1868G98Wt7pTpFhpZxBjU8FOXJ+ReQRfh1kAYKnFBlzV4VPcLwpEREqW0QpAnQLcA/L5PHfddRfHHHMMv//97zHGYP+378by24M7Ojq4/vrrGT9+PDfccENPRxQRKWlx+woOq5+6/kE2+N5/A2Nbk3YHhxGrrCzMNvGbmas3WQv13eFfpsYN/t9DghuU6MdJQw4pqnZRfimPLXk55EQi67dJ6nhcCj/NOmOXsDT/YYSJSohJkzO7FjzcAnH7enR5RET6oLWdjFtJD08rAKPz8ccf86Mf/YihQ4euOAl4ecNvp5124qabbmLOnDn85je/Yfz48Ssagd/61rd47LHiN1cXEak0CfvUal9r9lwai9j7b1TqyDAilZ1b5j1Mpsg9t47f4CA2qx4dciJZlz37bcO2NZsUVXv3gqeY3jkv5EQi62aMwRJsRV/WtkSUpvRkTOErKA1Q7V+CY2dHF0hEpI8xsNYTeXvyQQ881n7tyjsAKtIGYC6X484772S//fZj/Pjx/PrXv2bRokVYa0mn05x66qm89tprvPTSS5x88slsuOGGnH322bz//vvccsstVFVVYa3l8ssvjzKmiEjZiNm3SdhHV/mab+HZrloIuMx9g/jObBDfMcR05eH5pjd4p/2Tomq3rB7DgQN2DjmRrI8xhu8N/wr9Y8H3wPTx+cvcf624W0Gkp8RMdaDxDvGIkpSenNmZLoI0AfMk/fsiTCQi0rcsb4L5FfD4bOPv0+cqTyQNwClTpnDuuecydOhQjj/+eJ599tkVq/0mTJjANddcw5w5c7jhhhvYdttt1zjHiSeeyPe//30A3n333ShiioiUnZR/K+Yzv82a58VpLmL13yapE8KKVTZmds3npnn/Lqq2zq3mW8OOCTmRFMoxhq9tdHhRtbMyC3ih+a2QE4ms2+D49oHGT8v8C98WfvptWTOGjHNUoJKk1R1HIlJBDHg4WBz8Xnx4vfCwK33flSb4J8J1+Pvf/86f//xnnnvuOYAVvy2Px+McffTRfPvb32afffYpeL6ddtoJgMWLF4cZU0SkLBm7iLidtNrXi9n7r8GdQF1sZBixyspt8x/DK+J2AYPhglFf075/vWyrmrEcOmA3Hl68+v9P1ufmeQ8xNj2MIckBESQTWd3I5GHMzj5d8PjG/GTmZJ9hePKACFOVDrOGvXDXxWEJWA+MG1EiEZE+xFr8dbyljeK+h/XdixTVvRZru24l3tsRagPw+OOPX+VQj2HDhvHNb36T0047jSFDhgSeL5HQ6YgiIoWK2/+utvqvyXOZ5wW/LWxc+qthxSobTyx5hQ87ZhRV+4VB+7BBsn/IiaQYXx68P6+3fsj8bLBfLuZsnjvmP84PRh4bUTKRVfWLjWN08mimZe4vuGZ65iGGJfbXye0ApvBDVAAscXrhfEQRkV6x/FbYNVv966XdLFtLelt5v/AJtQG43IEHHsi3v/1tjjjiCByn+B+kO+20E88880yIyUREypOxLaT936/yNWthUlfN/za5Ldzg2M4Mim8XZrySN7trIXfML+72sM2qR3P4wD1CTiTFMsZw6kZHcNn0W7AB386+2T6FjztmMbZqeETpRFY1JvmFQA3AFu8TsnYpSdMQXagSkWcTfKpxaC9ovCWOoQmLflkjIpXB68YvPdb0DirqXz2t7V3b+q+7thGV90ufUBuAP/zhDzn99NMZM2ZMKPM1NDSw9957hzKXiEg5S9r7cGla5WuNfowlfvDVf2NSR4eUqnzcseBx/CJ+95kwMc4Y9kWtxuljNqkawdED9+K+xmcD114z625+OfY7up1bekSejsA1OdtBEjUAMWmy5hBS9p6Chjt0UOudR4v7JzCV96FQRCqLBTxb7PvTvva+tsj1iX3t2+gBof50u/LKK0Nr/omISIGsJenfv9qXP8oGu/0JoNYZSUNssxBClY/nmt7g3fapRdWeMeyLahT1UUcO2pMB8frAdS1eOw81vhBBIpHVJUxt4JoYwV/7y1WncwoegwseH+NdYvbVCBOJiPQVdsVhGMEfnz1Zt9h5evf62Mr7ZU+o3/HXv/51vv71rzN58uRAde+88w5f//rXOfXUU8OMIyJSEYxdhMuCVb621HOZnk8GnYnNqk7TarWVLMm1cPO8h4qq3bffdmxTu0nIiSQsjnH4ztBjivrl7+NLXqbDy4SeSeSz4k4NA2JbB6p5r/OvK/bjrnTW9KfTOT1QTco+EFEaEZG+w6zWROvOg/U+/ACP9c/Xvbz+Ovc/LG+hNgBvvvlmbrnlFmbOnBmobs6cOdx8883cfPPNYcYRESl/1lLtX7Xal1/LVAf+wTYgtiUD48E+aJa7uxY8gYcfuK7GSfPFDfaPIJGEaWzVcA4asGvgurz1uGbWnfhqskgPGJU8LND4ebn/0JifHE2YEmRoCzTesdOjCSIi0odYa/B68OFbp+BH9FmWPbqzB2KpqrzvWESkjMTsGyRY9XbEVt9hrhf8FPVRycPDilUWJrd+xEst7wauM8APRx6vW39LxNED9yJtgq6WhQ86ZvBq6/sRJBJZ1QbxnRkWPyBQzYzMIxGlKUVBV3lU5qoQEakwBnycHnyYAI+ey1Vp+sR37HkeALFYJIcSi4iUraS9b7WvfZIL3sxIO4MYHN8xjEhlIevnuGHuv4qq3a9hR0anNwo5kUQl7SY5c/gXi6q9f2HwQ0REgjLGsFFir0A1i/NvR5Sm9Hgm6P7kBrS6V0TKnMX26ArAPvmowF/49IkG4LRp0wCoq6vr5SQiIqUlbl9e5Z9bfYf3s8FXnm1d9X0c44YVq+Q93DiJNi/46Zt1bjXHDNLp9aVmi5oxbF87IXDdnOwiJja9HkEikVX5ZAON92xXRElKT55t8BhR8PgYn5C0d0WYSESkb+jZFYB972F1CEg4Ct1AvqOjg//85z9cc801GGPYdNNNo4gjIlKWEv4jOJ/Z2+idbBX5gC/tte4oBsS3CDNaSZvZNZ8HGp8rqvaHI4+nJlYVciLpCV8YvG9RdbfOf4QluZaQ04isKuX0DzTeIY5vvYjSlBhj6HS+Eaikyr8BY4PtHSgiUlL+twdeRT+MGoAFu+iii3Bdd5UHgLWWo48+erXn1vSora1l77335pNPPgHg85//fDjflYhImTO2jWr/V6t8LWsN04q4/Xdk8tCwYpU8ay03zv03PsFv/9qjfhtGpoZEkEp6wtDkIL40eL/AdZ71eGLxy+sfKNINde4Yqp2hBY/36OLdzj9HmKi0ZJ396TIHFTze0EnCPhZhIhGR3mWxgQ7mKM+HbgEOxFq7ymNtXy/ksffee3PmmWd2+xsSEakECfsIhs5VvjYrFw+8l0Xc1DI0oVtWl3u3fRrTuuYGrqt2UnxFp/6WvMMH7sEG8WArrQAeb3qFlnx7BIlEljHGMDp1RKCamZlHaPNmR5SoFNUGGh2z2kdRRMqX+d9nBtvLjyit99oBGoCLFi3inHPOYdy4caTTaQYOHMiBBx7I/fff362ML7zwAscddxyjRo0ilUqRTqcZM2YMJ598Mv/973+7NfeaFH3qxqhRo9h771U/ND777LMYY9hss80YOHDgOusdx6GmpobRo0dzwAEHcOihh+I4lbcEU0SkGAl/4ir/nLGG1zLVgefZtvpHxIxOqwXo8Lq4fs69RdV+d/iXqIsF//cvfc/Rg/fmT3NWP1xnXfLW43ez/8H/jTy54G1QRIIakTiY+dmXacy/UXDNjMwjbF4V7PbX8hVsH0UTcLyISCmxBnxM5E249enJd02f/V79Ai/+7rvvst9++7Fw4UIAamtrWbp0KU888QRPPPEE3/ve97jmmmsC5/nZz37GL37xixX/XFVVhe/7TJ06lalTp/K3v/2Nyy+/nB/96EeB516bohuAJ598MieffPIqX1vewLv00ks58sgju5dMRETWyLFziLHqyoQPsykyBDvEI0E9g+JbhxmtpN2z8Glaizj4Y9OqUWxaPTqCRNIbdq3bgmebXueDjhmB6j7smMknnbMZWzU8omRS6YxxGBTbNlADcGn+wwgTlRbfDAm03MS3qejCiIj0NgteBR6CsTKvgBWAmUyGI488koULF7LFFltw2223sfXWW9PR0cFvf/tbfvrTn3LttdeyzTbb8LWvfa3gaz/55JMrmn9f/OIX+eUvf8nYsWOx1vLee+9xzjnn8Nhjj/HjH/+Yfffdlx133LHo73Nlof4X32uvvdhrr73Wu/pPRESKV+1dgiG/4p+thSm54B9URqQK3w+p3LXnO3l2aeEfqpeLmxhf3yjYbXnStxljOHPYF3GLeIt098KnIkgk8ilrgh3s4VmtYlsuaw7CBlhrkuQ5HDstwkQiIr3JYHFWefT2qbw9cvLvZx7r8+c//5mpU6dSVVXFQw89xNZbL1s8UVVVxfnnn893vvMdAC644AJyuVzB//Zvv/12AMaOHcvf//53xo4du+y/ijFsvvnm3HfffWywwQZYa7n33uLuUFqTUBuAEydO5JlnnmG33XYLc1oREfkf135EnDdX+VqT79Jhg63+c0kyMnlImNFKlrWWP/0/e/cdJ1V1/g/8c+6dvn2BBZZl6UhTEBtWql1R7L0lmkS/RqOJKSb5mWgSk+83GI2JMYmiRiP2gthQQRSkKNJ777CwfXf6Pb8/VlaWbffM3rtT7uf9el1lZ85z55lluTvzzDnP2f0GYgnsmHlV9zNR5CmwIStKphxXFk7NV58du65+OxZXr7EhI6IGfq1IaXwM9ZDSsCmb9GKInogIcxv9SAAC9cgy/mxvUkRESSIFEJdND+OI48j7O3Icee62Djsf9/D7okb708Kff/55AMDVV1+N0tLSZvffd999EEJg9+7dmD17tunv/549ewAAI0eOhMvVfGGu3+/H8OHDAQC1tdbtSp/wEmBKjkO7LaejdM6dOu7Q3z9/DjrGG53T5Ou4BD4LqjU2B4DhWbciy632RtIOqfDzsLBqFZbVblSO6+LOw6SuJ0AXyX8O6SqVrwtX9JiIxdWrETTCSnEv7P0AJ+QP5c9FglLxZyGV9PSNwcr6bESluTcDQWM/NoanY0jW9TZnZg27rwkh7RdwRVZCx742xx2aJ+iWS+AW22Bo/W3Jh8zhdcG5Uvl1QtqTwsTmgU3vV+kXaGVvP7OP2/Jjth6tybbLYbW1tY0bcZxzzjktjiktLcXQoUOxevVqfPzxxzjrrLNM5dqvX0P7oGXLliEWizUrAgaDQaxatQoAMHr0aFPnNIMFwDRTUJCeM010XU/b3Mlaubm5yU4hbUkZhzzQdInh9pgH1e388jqSgAvDu18Ej57cTStS5brw7pb5yjECwE+H3YSueWx5YYVUvC4UoAC3xS/BoxteVIqriFVjTXwHTu92rE2ZZa5UuSakuqHyciwvn2Z6/KbQ6xjd8yZ49dT7d9Ya+64JBTDKBwCRtguATXLxLYXIOs6mfKg9vC4QkJqvEzKBodwDMPGCYOc5MqvWS5GudjZuW7NmDaRsON+IESNaHTdixAisXr0aq1evNp3lrbfeiieffBIbN27E1Vdf3aQH4Jo1a3Dvvfdi3759GD16NK677jrT521PQgXAw3cq+fWvf93i7Yk6/HzUXEVFRbJTUJKbmwtd1xGPx1FdXZ3sdCiJdF1Hbm4uqqurEY+rL7UkwBt7Br74jia3JdL7r5f3DNRVR1CXpB0OU+m68GXVGmyq3akcd2r+SBQbhWl3TU41qX5dGO0dhC7uXByMqv2cPrXxDQzRe8PFWYCmpNI1IR2UiinYos9GTXyrqfFxGcGKfa9hgP9iW/OyQmdcE7KiNUpvgIL1ZQhHeK3vbLwuEJD6rxPakvKFawFTPfDSj8Lcw3YqmIeW6QJAcXFxq+MO3Xf4+PaMHj0a//nPf3Dbbbfh1Vdfxauvvtq4C3AoFELXrl1xzz334De/+Q3cbrfp87YnoQLgAw88APFNtfTwgt3htyeKBcC2pduF73DpnDtZJx6P82chETIKT3x6k5siUmB/XO0XgoCOfp6LUubvIJl5VMVq8eTON5TjBIApXcemzPcwE6TydeGyool4cpfaz0lZtBKv752NS4vG25RV5krVn4NUk6cPMF0ABIDK6EbEPenzvbXzmmAgTy0XI8CfyyTj959S+XVC2pKA0zvEtlcAPbz3XiAQaHXcoftqamqUHv/aa69FcXExrr/+euzatQv19fWN94XDYdTV1SESsXbCRsIl30NTIVu6PdGDiIha5pYLoKHpDIR5oWylHQ0BoK/3QuS6+lmZWtr6pPxL5f5uAHBl0Zno6sm3PiFKSafkHY3B/t7KcR+VL0bEML8bHJEatdfN3AjkWxGhVpj3yLmA5L9lIso8hhQ2H1qzI97G0dJ4q3OKH35Y2qlQTSwWww9+8ANMmDABvXr1wkcffYTy8nLs3bsXb731FoqLi/Hkk0/itNNOs3TFUUIzAFvb3URl1xMiIjLPLT9v8nV5XMfOmFf5PL29E61KKa3FjTjeO/iFclyRuwDndj3ZhowolV3V/Uz8duvTSjH1RgifVy7HhEL2DiPrZWm9lMbXG3shpezwSp1MEBETYODxZh+qtcaN5fDJ/yAkbrE5MyKiTiQ0FEfPQEnsdKWwna7PsNP9efsDW37QJl/JI26RLX64Ze73Vkn0NOXnsse9qM37s7OzG/9cX1/fai/KQzP3cnLMb8z4f//3f/jHP/6BIUOG4NNPP4XP921bp8mTJ+Pkk0/G8OHDsWbNGjz88MP44x//aPrcbUmoADh27Fil24mIKHG6XAuvnNnktkR6/+XrQ5Cj97EqrbT27N6ZCCcwo4NLOp2pv78XBvpLsDGo1i/y1bJPcHzuEOS6krvhDmWeEu8ErA+9AGlyAVdlfB22hmein+8CmzNLA8KLWu03yDHuhjD5/fMZbyAkbgAE908koswgpYQm/fBKtbYImvQjblvvwMQ/pErkueiy7fdTh/f92717d6sFwN27dwMAevbsafqxH3nkEQDAHXfc0aT4d0i3bt1w/fXXY+rUqXjrrbcsKwBmYtdHIqKM4jeea/ImxZDA9qj67L9B/iutTCttbQvuwaeVS5Xj+vuKcULuMOsTopQnhMAdJZdBV3zZVBcPYuaBeTZlRU7m07qgxDNJKWZT6FUYMmZTRuklph0PA+Z3cddwEC651L6EiIg6mYREFGGEUKV0RBHuhKXD6kdiz6Xt/npDhgxpnDm/atWqVscdum/YMHPvEw4ePIj9+/cDAPr379/quEP3bd261dR5zeDHWEREKUzIcrjlZ01uWxYJIKRYiOjmOh5Fbi5FBIB3E1j6KyDww95XQBf83MypCt25OCXvaHxWtUwpbk7FElxaNB4ezbod3IgAYHjgNuyPfomwLDc1PizLsT/6JXp4xticWXoQqG9/0GHMLhkmIkoPAlvcX2CLW/11cSrOI0vkufi0tpfsZmdn48QTT8TChQvx/vvv49JLL202ZufOnVi9ejUAYOJEc62WNO3b79/27dtbHXfovtZmHiYiKX9z+/fvx9tvv43XX38dmzZtSkYKRERpwSVXQuDbXc8iUmBNxK98Hvb+a7A/UoFF1a1/gteaU/OOQYHbul++lJ7O6aLe/zEkI5hXqVY0JDJDFx74tC5KMbWG2jL2TCbR+o6OVownIkppEpBSOP5oz7XXXgsAePHFF7Fjx45m9//pT3+ClBLFxcUYP95cq6CCggL06dPQlunf//53iztcV1dX48UXXwQAnHTSSabOa4alBcDy8nJMnToVU6dOxbp161oc8+CDD6K0tBRTpkzB5ZdfjsGDB+Oaa65BKBSyMhUiovQnwwgYf2ty05aoV3nHKq/IR3f3iVZmlpaklPjrzldgKO6e6RI6zu96ik1ZUTop8RVhQr76TNrp+z9CebTahozI6YTi7wPV8ZksJtR+L+pyo02ZEBElgQAkRNIPWHyoP3bbbrvtNvTv3x91dXW44IILsHz5cgBAMBjEww8/jMcffxwA8NBDD8Htbrrao2/fvhBC4Kabbmp23h/84AcAgK+++goXXXQRVq9eDcMwEIvFsGjRIpxzzjmNBce77rrL5F9q+yxdAvzSSy/hxz/+MTweD2688cZm97/wwgv4f//v/0EIASllkzjDMDB9+nQr0yEiSmteORM6mn7StDXqUT7PQN8V0ASXH66u24Ltob3KcRd3G4tibzcbMqJ0dH3Pc/FZ1TJEFXqphYwIPi5fjMu7cyYuWStX74fK+HrT46tiXHlzSEi7BN74O6bHB+STiMljEBPH2pgVEVEnkRKGiRlwCZ/exJhkfyRlmEjS6/Xi7bffxoQJE7B8+XKMHDkSubm5qKura5y5d+edd+Lmm29Weuwf//jH+Prrr/HSSy9h5syZmDlzJnw+H+LxOKLRho0KNU3D73//e0yapNbzty2WzgCcPXs2AOD0009Hly7NlyT8+te/BtAwC+Oiiy7C3Xffjd69e0NKiVdeeQWfffZZsxgiIqfyGm80+Xp71IP9hloBMEvrhT7e861MK229dUD9d0yO5se5CSz7pMylCQ3jCkYrx31S8SUMaW7HUSKzenvPUhq/J/o5dkU+tSmb9BIXQxASVyjF+AxOViCizCAhYEBD3KbDMHGYHWflcWSeZgwfPhwrVqzAj370IwwcOBDhcBh5eXmYNGkS3njjDTz22GPK339d1zF9+nS8+eabuPjii9GrVy8YhgFd19G/f3/ccMMN+OKLL/DTn/5U+dxtsXQG4Pr16yGEwMknN3+zNH/+fGzZsgVCCDz44IP4xS9+AQD42c9+hqFDh6KyshL/+c9/cPrpp1uZEhFRWhKyGi58O1NDSmBpRL3/ULHnjMbdq5zs65p1WFe/TTnuzC4nwSV0GzKidDap4AR8XL5YaTl5vRHG4uo1OClvuI2ZkdPkuwahu/sk7IsuNB2zOfQ6it383QAA9eIH8MrXmvTabYtbzoOQ1ZCCPWGJKL1JARhSKDbGyRwCQFzhyRcVFTW2uzPLzO69F110ES666CLziXSQpTMADxw4AAAYNGhQs/s++ugjAA1TKA9fw1xUVISrr74aUkosWLDAynSIiNKW13i5yddlcReqDNXPbDT09lo3ZTxdGdLA83s/UI4rchfg/K6n2pARpbse3i6Y0m2cctzTe2agJqa28yhRe0Zl/Qg6vKbHV8e3oCa+1b6E0ogQ1aaLfwC+mS9TZmNGRESdRH5TADziMDL0aOl5xg3nfRBmaQHw4MGDAICsrKxm982bNw9Aw/LgI+8/5phjALS9BTIRkVNocjv8clqT27bH1Hv/lXrOhF9j77rltRtxIFqpHHddj7M5+49adXaXk+AWakX5kBHB3MqvbcqInMolApCKczjqjX02ZZNuzBdOD5FQ/31MRJSK4hDNDqOFo6VxZo+Wzmfm6MhjtvS4LY6xsQdiqrK0AHhoKUFFRUWT2w3DwMKFCyGEaHGJ76F+gfX1/FSciMhnvIHDJ+RXGxrWRX1K59Dhx/DAbVanlnaklHijTL3fVXdPIY7Obj6bnegQr+bBafkjleNmVyyxIRtyOtWNnjTF4nWmkshBHH0Uxgto8qCNGRERdRazs+c0yCMOQ+GIJ3ioPEbLjyvaPSSc90G/pQXAoqIiAMCGDRua3L5gwQJUV1cDAMaMGdMsrra2FgDg9/utTIeIKC255ZwmX68IB2AoXq67uI7hzr8A5lQuwdbQHuW4a7ufDY39sagd53Y5WXkWYFm0AmvqttqTEDlWvj5YafyB6HKbMkkzQiCkTTE/HBLZxs8hZEX7g4mIUpiEhIRm4hDNDqTFobV/OLABoqUFwGOPPRZSSkyfPh2RSKTx9n/9618AAI/Hg1NPbd5PafPmzQCA4uJiK9MhIko7mtwJDfsbvw5Lga0x9SVKfXznWJlWWjKkgZkH5inHDQ30w8gczv6j9nX3FGJyV/XNy57Y+RqiRsyGjMip+njPVRq/JfwmDkSX2ZRNegmLyYhhoOnxGqrglTNszIiIqDM0rDey4zBsOGx5bAd+2G9pAfDyyy8HAOzYsQMTJ07EP/7xD9x666149tlnIYTA5MmTW5zlt2DBAgghMHToUCvTISJKL9JAdvxnTZb/7o+5YEDtl1OePgjdXMdanV3aWVW3BWUJ9P6b0u0M65OhjDW24Fhoii+nquJ1WFyzxqaMyIm6u09AoetopZgt4bdtyibNCB/qtJ8phXgNFgCJKN21v0Q20aOjy3cTXdIbV94cxNJyWFqw9BlfffXVOOmkkyClxPz583HHHXfg6aefBtCw++//+3//r1lMZWUl5syZAwA46aSTrEyHiCituOUiuLC58euYBL4KN99UqT3HZf0MQjjvF9rhDGng5X0fK8f18xVjcKDUhowoU+W5snFCrvoHmHMruBkIWUcIHaMCP1KK2R/9ElGj1qaM0ouAWh9yDbsBaX73YCKiVCNgT6Gu4Wi78JZY4c76PB24Atj6TUBmzpyJiy++GEIISCkhpUSvXr3w2muvYdiwYc1innnmGUSjUQDApEmTrEyHiCiteOR7Tb7eFPWhRqr1F/OJrvDr3Pl3TsUSbA/vVYrRIHBHyWWNG1oRmXVp0XjlXoDr6rdhZ2h/+wOJTJJQXVYuEZaVdqSSfpR3fD/UX4qIKD1JyIR36O3o0VJfwWTl4jSWbwFWWFiI119/HWVlZdi8eTOysrIwbNgwaFrLvySHDRuGadOmQQiB4447zup0iIjSgzTglk13B12vuPMvAJR6z7Iqo7QlpcSsisXKcaOyB6ObJ9/6hCjjdfcUYlzBaMwqX2Q6xoDEv3e/jf/X7zssOpMldKH+O0ODeo/ZTBRHf0i4IEwXUd0QKIdEF1vzIiKykyGd/frDiUuALS8AHtKtWzd069b+LJSzzuKbVSIin3wWGg42fh0yBCoNtUu0CwGUes+2OrW0sz20F7vDZcpxZ3dpvks9kVln5B+rVAAEgC2h3dgc3IUBgRKbsiIn8Yg8ZGu9UWvsMB2zM/IRBvuvtjGr9CBFHiJiArzyQ1PjBcLIif8M1fqTgMNbbhBR+oo7fCaz4cDn77xnTESUamQd/MbzTW5aFmm+YVJ7hvm/C69WYFVWacmQBp7d+177A48wImsAjmLvP+qAUl/3hPpHzq9abkM25ERCCPTxnqcUsyH0Iqpim9sf6ABB7UZImP/d68IquKT6bHMiolQhpXD0YTiwCSALgERESeaVsyAQbPy6PK5jfTSgfJ7unhOtTCstLa5eg03Bncpxt/e6lMswqcNu6nk+dMWXVvOqVqA2prYBAVFrenvPRJ42SClmW/hdm7JJL4boh3rxXaUYn3zLpmyIiOwnU+BI5vNwYAtA+5YAA8CePXuwcuVKVFRUIBQKmYq54YYb7EyJiCjlHDmDIJHef0Xu4+HRcq1KKW19VK4+G2Nk1kBkudS/50RH6uXthmOyB+Lr2vWmY4JGGNP3f4TvFk+2MTNyCl14MNh/DRbX/cZ0zL7oAgD/Y19S6US4ld6RanKbfbkQEdlIym9mACY5D7tqcGael2E4rwJoSwFw+vTpePjhh7FixQqlOCEEC4BE5Cia3AKP/KzJbTtjHuXz9PNeZFVKaasuFsT64HbluEldOHOSrHNa/iilAiAALKhagauKJiHbpT7zl+hIEnGl8VFZa1Mm6Uj1zWCy3zoTESVICBjQkn4V66wSXEvP03BgD1fLC4A//OEP8be//Q1Aw06MRETUuoDxWJNdB/fHXAgq7kjV030aurpHWp1aWpGyYUdVVSOzB+LorAE2ZEROdWzOYBS6clEeqzYdE5VxfF2zAacXOPvfMVnDrWUrjdfghpSSbRAAxIXa7wOBWkBGAKH+wR0RUbIZKTADMJniDnzylhYA3377bTz++OONX5900kk488wzUVJSAq/Xa+VDERGlPU3uhEcubPw6LoG5oRyofhZW6uVu6huCO7Ckdp1y3HU9zuWbXrKULjR8r9fF+MO255TiPqpYhFPzj4HGn0fqoHx9ELwiH2FZaWp8HGFsCE3nbsAAYhiJOPpAh7mlvToOIGD8GfX6z23OjIjIYrKhAHjYl45x6FlLxUkXmcDSAuCTTz4JANB1Hc888wyuvfZaK09PRJRR3EbTfnXbY14Epa50Do/IQ4FruJVppaVPKr5SjhnoL0GRx9m7JpM9hmT1RQ9PF+yNHDQdszW0B3Mrv8a4gtE2ZkZOoAk3Sr3nYENouumYDaGXUOKZiIBeZGNmaUAI1Gu3Isf4pekQr5yJkLwZhuhhY2JERNaSomkBsNn9nZiL3Y58loeeW8yBUwAtLXl++eWXEELguuuuY/GPiKgtMg6vfKPJTVuj6kuISr3nQBduq7JKS4aU+LpGffbfmYXs/Uf2OTlvhHLMrPJFbJ9ClujvuwTZWqlChIHtkQ9syyedRLUJCItxpscLGPAa79iWDxGRLSRgQLR6yCOOtsam+hFv5ZDWlsPSgqXPuKqqCgAwceJEK09LRJRxvPJNuLCx8euoBPbG1Qp5PtENA32XW51a2nm9bDZCRkQpZkigD07K5cxJss+4/NHQFV9m7Qzvx65wmU0ZkZO4hA8lXrXX4wejy23KJv1IqM0O17DVnkSIiOwiZLMiX1sHMvAQcF7bFUsLgN27dwcAuN3Ono1CRNQmKeEzXmly08JQNmKKl+RS71nQHd54vCJag3cPzFeOm9z1dPb+I1vlu3NwTXf1/pxfVq+xIRtyJkNpdEwGbcrDAThzl4jSjJTWHkYnHZY+NguAHXPSSScBANas4YtXIqLW6NgIHdsbv64zNGyNqW+U1N3NJayfVi5BXPFNbhd3HoZm9bUnIaLDTCw8QXkW4IyDn2Nv2HzvQKLWeEWh0viYrIeUatfTTBUX/ZXGa9jLIiARpRUpBQwLD3nE0ZnnPXKM2VyceNm2tAD4gx/8AFJKPP/884hGo1aemogoY7iMhU2+3hL1fjO13rwC1zDkuvpZmVZaWpzAbKmzCk+CJpzX84M6nxACI7LVCgkxGces8kU2ZURO0t1zInSY/3ApJA9gfei/NmaUPiLiLEj4TI93Yw188gUbMyIispYQ1hYAmxfXtGaHYeJoOcamIiLUNl/MBJa+Axo/fjz+53/+B5s3b8ZNN93EIiAR0RE0uQcB+VST23bF1NomCOgYEfi+lWmlpS+r12BneL9STLGnG84qPMmmjIiam1BwvHLM55XLEOdMLOogt8hCiXeSUszm0JuIGNU2ZZQ+pMhBSFylFOMz/gvIsE0ZERFZz4Bm49F8M46WNhYxt9mItbnJbw4nvtJyWXmy7du3495770V5eTn++9//YsmSJbj99ttx8skno2vXrtC09uuNpaUqO5YREaUXn/EyBL59g7Aj6sF+Q62PXxfX0cjV+1qcWXqJSwMv7FXfsXJiwXHQ2PuPOtHI7EEYHuiHVfVbTMeEZAT7I+Xo6e1qY2bkBEP8N2J/5EsE5T5T4w1EsCsyG/18F9mcWeoLat+FO/4JXIe17GiLhkp45FxExJk2Z0ZEZAWZEj3wkrkKV3UFViawtADYt2/fxqbqQgisX78ed999t+l4IQRisZiVKRERpQ4Zg0e+++2XElgaCSifpsitPqMo0yyr3YDymNosFbdwYUzeCJsyImqZEAJXdj8Tv97yT6W4p3bPwC/63sjl6tQhLuFDoXs4dkXMFQABoCq+2caM0ojQIFEImCwAAoAut9mXDxGRhQxIGIbzCmCHMzTnPX9LC4AAIJ3YSZGIyAQhy6ChpvHrMsOFSkPtMqzBgxLPBKtTSztLqtcqx5yRPwrZLvWCK1FHFXu7Ikv3oy5ufpfVDcEdWF67EaNyBtuYGTmBUJzhYMi4TZmkI7XvneQMcyJKE0IKR86Aa0I67/lbWgC88cYbrTwdEVHmkBJZxv82uWlfTP0SPNh/NdxatlVZpaWySAUWVK9SisnW/biq+1k2ZUTUNrfmwtj8UXj34BdKcZ9UfMUCIHVYllasNL46vgmGjEETls8TSDtxMRBu+bXp8bqx2eIO60RENhHJXX6bCtgDsIOmTZtm5emIiDKGS34FDxY0fh2WAmujfqVzuJGD/t5LrE4t7Uzf9xGiUq1dxHE5Q+DR+GaWkufsLidjTsXXqDdCpmPW15tfekjUmhLvBKwPvQBp8q1OnbEL60MvYoj/epszS31hbTJ88VdMj/diNqLGB4hoZ9uYFRGRBQ7tipvkNKycg6f6XKQDZwDyMyoiok7gk683+Xpl2I+QVNt6vtA9rLHPqlOVR6uxpCax5b9EyZTvysaFXU9TigkaYSypWWdTRuQUPq0LSjxquwFvC7+LmDRfrM5UcTEAYTFRKcZnPN/Q5JeIKJUJwJAiow55xNFujAOXQLMASETUCVzyq8Y/xyWwMepTPkdvL5ewrqrbDEPx870B/l4Y4C+xKSMi84Zm9VWO+deutxA2ItYnQ44yPHAbvCLf9PiYrMO+yIL2BzpAnXY/DGSZHu/CJuhQ/6CKiKhTScCAyOhDHnG0dL/TsABIRGQzt7EA4rDNP8oNFyKKl99cvT+KXKOtTi2tGNLArIOLlGI0aLij5DLHz5yk1NDX1xMl3iKlmHojhC+qVtqUETmFLjzwaV2VYuoN8zsHZzThA6A2Y1+Xu+zJhYjIKt/MADxy1lxnH8mcIRhzYBNA2wqAlZWV+N///V9MmjQJxcXF8Pl8cLma91/65JNP8N///hcffvihXakQESWPDCHL+G2Tz5c2RrzKpzku6+cQQu0NSKb5tPJrbAvvVYop8XZDF3eeTRkRqRFC4IKupyrHJbLrNdGRNLiVxpvtGegMar9/peJ4IqLOlgoFuWQvEXbifDhbOqK/9NJL+N73voeamoYZL/KbPhgtzcBYtmwZ7r33Xvj9fuzZswe5ubl2pERElBQe+RE0VDZ+XRZ3YWNMbfMPF7IR0LtbnFl6kVJiVrna7D8AODV/pA3ZECXu5Lyj8VH5YmwM7jQdszG4CzEZh8vhHwJQx+S7jkJFfI3p8bsjc9HfdzFcQu13ViaKiaHwyPmmx7vlUkQx3saMiIg6zjDRVSedO5oeWX068rnEHTgF0PKS53PPPYdrrrkG1dXVkFKiR48eGDx4cKvjb7rpJrhcLoRCIcyYMcPqdIiIkspjzG7y9ZqI+hupXt4zrEonbe2JHMCucJlSjE/z4DQWACkFHZ87VGl8nRHE9H2zbMqGnKKP9xyl8XXGLmwMmd8BN5OFxRSl8T75CtwGeygSUWo7skdeSwfS+Gj3uTmwRZClBcDdu3fj+9//PqSUKC4uxocffohdu3bhj3/8Y6sxBQUFOOOMhje3n3zyiZXpEBEllwzBheWNX8YlsCPmUTyJQB/v+dbmlYZW1G5SjvlOz8nI1jlzhVLPsdmtfzDamtkVX6EmVm9DNuQUWXox+njPU4rZEf4QcRm1KaP0ERVjEBVqfXi98mWbsiEisoBs2LC8o4eRxgek85YAW/qMH3/8cYRCIfj9fnz88ceYNGmSqbgTTzwRUkosW7bMynSIiJIqy/gzNNQ1fl0R15W3mx/ouxw5em+rU0srB6NVeHW/2gdEGoTyLCuiztLD2wVHZw1QionJOOZXLW9/IFEbhvlvhQbzfWgjshoVMfPLhjOW0FErfqO0Y6RHLoCQFTYmRUSUOPnNJiBW99VLpyPOXYA75sMPP4QQAtdccw2OOuoo03EDBw4EAGzdutXKdIiIkkbIMnjk+41fxyUwL5SjfJ4Sz0Qr00pLH5UvRkTGlGKOzh4AzYHT+il93NjzfOWefpuDu23KhpxCEzpUOzpFZa09yaQb0bBoTIWGgzYlQ0TUQdLcEuCOHkYHDrsf24lLgC3dBGTLli0AgNNOO00pLi+vYYfGQ5uGEBGlO698HwLxxq+3x7yolmqXXL/WHQHN2Zt/GFLis8qlynETC06wPhkiC3Xz5GNYVj8sr91oOmZJzTocjFZxZ2vqELfIRliWmx4fk0Ebs0kn5mdOHiKlt3kXeiKiFCC+mQHY2dr6GKW9TTusfmzVlVmZwNIZgHV1DUvdsrOzleKCwYYXFj6fz8p0iIiSxmV81eTrDVH161sf7zkQwnm9KQ5XG69HTVyt79kxWQNxTPZAmzIiss7gQKnS+IiM4sW9H9qUDTlFd/eJSuPXB59H2KiyKZv0IUUOYhikFOOVb9iUDRFRx0h0zgxAlU1FOvuxpfM2Aba2ANilSxcAwL59+5TiNmzYAADo1q2blekQESWFS34NNxY3ua08rrbUz68VcfMPIKGdTy8pGgfhwCn9lH5Ozx8FXfGl2Fc1a1EerbYpI3KCPj61jUBC8iC2hmfYlE16CWtquwH75XS45AqbsiEi6oiO9/9L90MmYQZksllaABw2bBgAYO7cuUpxM2bMgBACxx13nJXpEBElRSD+NxzeJ2hDxIuo4uV2kO9KuISzZ0VvDu7CPMVND3yaB8VefphE6SHflY0zC9VmYxmQWFW32aaMyAly9b4Y5L1GKWZH+EMYMt7+wAwXFuchiuFKMV7jNZuyISJKnJQy6ZtwJP3gEuCOOffccyGlxFtvvdU4q68906dPx9KlSwEA552n9okkEVGq0eU6uLC68euwFFgcVmuLAAD5LvMbKWWqj8u/VI45NW8kvJrbhmyI7HFl90nwaR6lmPV1O2zKhpyit3eS0viwrETIKLMpmzQiPAhq31MK8cjPbUqGiIg6hgXADvnud7+LwsJCRCIRTJ48uXFTkNa89NJLuPXWWyGEQHFxMa65Ru3TSCKiVOMyljT5elPUq7zFfIE+BDm6Wm+wTLS6ru3fIUfyCjfO7XKyTdkQ2UMTGkq8RUoxn1ctwxbuCEwdIKHe+MgAZwA2UPveCdQDijvZExF1hmQvwT20DLejR+KPney/gc5n6S7Aubm5eOKJJ3DVVVdh/fr1GDFiBKZMmQKv99tds/72t79hx44deP/997FixQpIKaHrOp5++mm43Zy1QURpTIbhk02X+uyKqc3sAYCB/iutyihtlUUqURFT2xn+nC5j0M2Tb09CRDY6PncoNgZ3mh5vwMA7Bz7Hnb2vsDErymReLR86vIgjbDqmKrYJ2XovG7NKD1Lkqo2HDuv3siQi6rhU6IGXzKtjMnZBTjZLC4AAcPnll6OyshJ33nkngsEgXnzxRQBobMj+wx/+sHGslBIejwdPPvkkzjzzTKtTISLqVD45HTq+nZUTkQIH4mqX2W6u41DkdnY/VCkl/rrzFUjFlwSqO6oSpYrT80fhjf1zEJZR0zFLatahMlaLfJd6iwEiXXhQ7BmLHRHzu0ovr38Mhe6h8GvO7rMaxyDE0R06zG16KBBHlvFH1Om/tDkzIiI1Uib/44nOKMG19hydOAPQ0iXAh9x6661YvHgxLr74Ygghvmkw2fQAGnr+LVy4EDfeeKMdaRARdR4Zg9d4o8lNC0LZiCleZrs5vPgHAGvqt2JbaI9STL4rB0Oy+tqTEJHNsnU/vlt8kVKMAYk9YfZko8T1802GgPkd6g1EsD38gY0ZpQmhI6xdohTile9Cl+ttSoiISJ0EYKBhI4xkHkYnHG09ttNYPgPwkKOPPhqvv/46qqqqMG/ePGzduhWVlZXIzs5GSUkJTj/9dHTr5uxPEIkoc+hYDx37G7+uNTRsU1z+K6Chp4c97OZVqu38CwCTCk+AS5h/I0uUao7PHQrsUotZULUSQ7P62ZMQZbwcvRRH+a7H2tAzpmN2RWbjKP919iWVJkLiSrgxG26sNR3jNd5EvX6fjVkREZknkBpLgJPJcOAMQNsKgIfk5eVxd18iyngeY26TrzdHvVCd1N7DfQp8WhcLs0pPqrP/ursLcV6XU2zKhqhzaEKg2NMVuyMHTMfMqfwap+ePwsBAbxszo0yW7VL72QkZB23KJM0IDyLiHLil+QKgS66wMSEiIjVStr4ENhPrYi29K4vHM/GZts3SJcDbt2/H9u3bEQqFlOLC4XBjLBFRutHkFvjkC01u26/Y+0+HD8MD37MyrbS0qnYzdoT3tz/wMCfmDocubOloQdSpxhaMVo75sHyRDZmQU+hQ3ahKg5TqOwhnJKH2IZ9Q2HCFiMhuQrS+NBYZeLT0PIUDlwBb+o6pb9++6N+/Pz780HxDYQCYM2dOYywRUbrxGS9DIN749f6YC3viam+qurqPhVfLszq1tGJIiWf3vqscNySLm39QZjgjfxTydbVNPb6sXoOoEbMpI8p0ea6B0OE1PV4ihrXBZ23MKH0Y6KE0XsNBCFlpTzJERIokvp0F6NSjc7YgSS2WT5k4tMFHZ8cSESWFjMIrm37osSScBdVfKF1dIy1MKj2tqtuMfZFypZjunkIMy+KHR5QZAroP1/c4VykmDgPVsXqbMqJM5xZZKPaMVYrZHH4DdXG1Vg2ZKCrGwECB6fECQWQZv7UxIyIiBSlQgEv+4bwVRM57xkREFtLkLggEG78uj+soM9xK59DhQy/vOIszSz+r67Yox1zT/SxoisuwiFJZb3935ZiZBz+3IRNyikH+q+BGjlLM9vD7NmWTRoQbIe1KpRCPXABdbrIpISIiNVIKRx9OlBIFwJqaGgBAIBBIciZERApkHFnGH5rctD+uVvwDgKP818EteP1bX6/WB7bU2x2jcgbblA1RcnRzF6CbO18p5uOKL7EtyBlZlBi/1hWlvnOUYspjq2zKJr2ExLWIYaBSjMeYaVM2REQKROcVAA3Fo7NyklwCnBwfffQRAKBnz55JzoSIyDy3/AJufLurn5TApqj5XkoA4BF56Ou90OrU0s6CqpXYGNypFNPXX2xTNkTJowmB8QXHKcd9VPGlDdmQU7hFltL4qOSycwCA0BETw5VCdLBYT0QpIIHCXKKH3QXDRHMyHNiBTm2bysN8+umn+PTTT1u8b/r06Vi6dGmb8VJK1NXVYcmSJZg9ezaEEDjllFMSTYeIqNN55RtNvt4Q9aFccflvnt4fwuFLWKWUeKtsrnLcmFy1N11E6WJS4QmYXfEVyqKVpmNW1Gy0LyHKeD6ti9L4oFGGkFEOn1ZoU0bpRHHmv6yzJw0iIiUOrH4dyYHfgoQLgHPmzMFvf9u8ka2UEi+99JLSuaSUcLvd+OEPf5hoOkREnc4llzX+WUpgbdSnfI5e3glWppSWNgR3YHfkgFJMibcIw7L62ZQRUXJ5NQ/O73IqntlrfqlgdbwOcWlAFymxuIPSTHf3iXDBj9hhPW3bYiCMpXVTMSbnIZszS30xMQKQr5oe78Yy6HId4uIoG7MiImqbBBzbB+8QLgFWJKVscrR2e3vH6NGjMWPGDIwePbrDT4iIqDO4jU8g8O0SqEpDR5Wh9pmKX+uOnm7OfN4VKlMaLyBwR8lljp85SZmtyGN+d1GgYTfgF/d92P5Aoha4hB+lXrU+gAdjy1EV22xTRukjIsbCQL7p8QJRZMX/z76EiIhM4KtoZ0p4BuBNN92EcePGNX4tpcSECRMghMCDDz6IU089tc14TdOQnZ2Nfv36IT8/P9E0iIg6n6xDlvGHJr84D8Z15dMcn/VzaEJ905BMIqXEwmq1ZvKF7lwUe7valBFRajgqqw/y9CxUxc0vF/yofBHOLjwJ3RSLh0QAMNh/HfZE5iEo95uO2RWZgzxXfxuzSgPCi3rtB8g+YlOwtriwirMAiSippOQMQCmdt2oi4QJgnz590KdPnxbvGzFiBMaOHZtwUkREqcwr34eGb9+Uh6XA12G1BuoCbuQ6/U0TgIXVq7CmfqtSTF8fN4yizOcSOsYXHo83y1rut9wSCWB2xRJc0X2ifYlRxtKFGwWuYQhGzRcAw8ZBGzNKHxHtQsSNF6DD/G72brmQBUAiSh7hyBZ4TTjx+SdcAGzJ7NmzATQUAImIMpXbaLphxfqIDyGozQDs5j7WypTS1gcHFyjHjC9guwhyhgu6nIp5lcuUNgPZVK+2mzbR4VxCrZdt0FDr35rJDOQrFQCFUd/BZkxERB3DGYDOe/6W/toZO3Ysxo4diy5d1HYSIyJKF0LWwI0VjV9L2bD7r6o+3nOtTCst7Q6WYXNot1LMQH8JhmcNsCkjotTi1lw4SXG3692RMhjSsCkjynSFbrWft4r4GuyNqH+Qk4mkUNsR2YWVDS8iiIiSQEp8sxOIkw/nXYP5uRMRkYKA8UcIhBq/DkmBOqk4+881Gt1cnMV2MFypHHN7r0uhcfMPcpAeXrUPVavj9Xi9bI49yVDG6+E+BR6RpxSzNvhsk80AnSoi1Jbeu7EEHvmuTdkQEbVNoGEGnJMPw4G/uixdAnwkwzCwadMmVFRUIBQKtR8A4IwzzrAzJSKihGlyNzxydpPbtsW8yuc5yn+D43ewlVLi3b3zlOMK3Lk2ZEOUuo7PGYrntfcRMiKmYz44uADndjkFWbr67GRyNl24MSzwXSyt+7PpmDpjFw7GlqOre6SNmaW+iDgDcXSHjn2mY/zGC4iI8wCHvyYgouRw/Gc3DlwCbEsBcP78+fjTn/6EWbNmmS78AYAQArFYzI6UiIg6zCM/gDisXWydoeFL5c0/XAjoPaxOLe18XbEW8w4uU4oZEujD2X/kOH7diwkFx+Pdg/NNx0RkDPOrluPMwhNtzIwyVS/PWKwPvoB6Y6/pmKr4RscXACHcqNUfQm78tiavFdqiYyt0rEYcakuviYg6yum1P6BhwprTWF4A/POf/4yf/vSnkFJyOQARZRS3sajJ1+ujPkioFaR6ek6FWwSsTCstzdj9mXLMhILjbciEKPVdWjQe86uWozJWazpmZ8j8Tq5ER/KIXNTDfAEwatTZmE36iIvhkAhAwPz3Q5e7ERcsABJR53N6uUZwBmDHfPbZZ/jJT34CIQSklOjVqxfGjx+PkpISeL3qy+SIiFKF2/gcbjSdsbYtqnZdE9DQ33uxhVmlp6gRw5flq5RiBvt744TcoTZlRJTaXELHQH9vfFmzxnTMhuAOSCkd326AEhPQeqAyvt70+F3RTzFAXsYPuAAAPkChAAhZbVsmRERtcmABrCnnbYlhaQHw0Ucfbfzzgw8+iJ///OfQNOd9U4kow0gJv/Fkk5viEqiVate3Uu+5yHNxB9u6WBCG4sKDS4smQBP8fULO1dtXpFQA3BUuw6zyRTiry0k2ZkWZqsQ7Ebujc02PDxll2Bh8CUMDN9uYVXqIiaHwyM9Nj/fL/yAqJ0Eqbr5CRNQRDZvgOrsAqLqSKxNY+m7qiy++gBACF198Me6//34W/4goI7iwEi5sanLbonC28i+NIvdxVqaVtmbs+VQ5psCdY0MmROnj9PxREIrXnPcOfoG4dF5/G+q4rq6RyNMHKsXsiHyEuAzblFH6CIspSuN17IfPeMmmbIiIWiaAb6qADj4c2AnR0grdwYMHAQAXXnihlaclIkoql7GkydfVhoaNUbXdNXV4UeDiEtZd4TK8svNjpZhiT1cUuQtsyogoPXRx52FcwWilmPJYNVbWbmp/INERhNBwXPYvIBTeKkRlDSpia23MKj1ExUmIQq1nrVe+DUhuhEhEnUdAg5Rw9AHF1VyZwNJn3LVrVwBAVpbarphERKlKyFp45atNbtsQUSv+AUAvzzi4Ba+Nn5R/qRwzsfAE9jEjAnBdj3Pg0zxKMfujFTZlQ5nOr3WFUOwWFJXcDARCQ632C6UQDeXQsMumhIiIWiIBKRx9OHGRhKUFwFGjRgEANm3ip81ElBl8xn+g42CT2/bH3UrncCELg/3XWJlW2lpeu1FpfG9vd+VZT0SZyiV0dHXnK8Wsqt1sTzLkCB6RqzS+LPq1TZmkGaH2OgEAhIzYkAgRUWv44boQXALcId/5zncgpcT06dOtPC0RUXLICLxyRpOb6gwN5YbajIgS70R4NS5hBYDquNrskEmFJ8AldJuyIUo/fX09lcZ/XbseX9essykbynTdPWqbyOyIfICD0ZU2ZZM+JPIgobZawCNn2pQNEVFzUjqv+NWc84qglhYAp0yZgksvvRTLly/HfffdZ+WpiYg6nQvroKGyyW3zQ9kwFH9Z5Onc+RcA5lUuR8hQm+FQ4OLmH0SHm1CgvpnQuwe/sCETcoI+3vOg+gZpS/hte5JJJ8KFsDhTKcQvX4YuWTwlos4hBCClcPzhNJZ3PXz++edxzTXX4M9//jMmTpyIGTNm4MCBA1Y/DBGR7TxG00/jK+I69sbV+m+5RBZ6eE62Mq20FIyH8dzed5VisnQ/hmb1tSchojTV398Lo3OOUopZX78d+yLlNmVEmSxH743BvmuVYvZFFyFq1NqUUfoIa1dAKr7V8hmv2ZQNEVFTjZvgOv1wGLV1bO3Q9W+XaUkpMWfOHMyZM8d0vBACsZi9O2BVVVXh1VdfxaJFi3Dw4EF4vV4MGDAA5513HsaMGWPZ47z11lt46qmnAABFRUX497//bdm5ich+ulwJn2w6i2FrzKt8nr7eC+AS6puGZJp5Veqz/8bmHwuPpt5HiSiTCSFwW/FF+P66PynFHYhUorun0KasKJP18ozD+tDzChEGwrISbmTbllM6iIsBCIpbEJDm3wN45FxwGxUi6gwN7e+cNwOuKec9f0sLgEeuI0+1deXbt2/H/fffj6qqKgCA3+9HXV0dli5diqVLl+LCCy/Erbfe2uHH2b9/P1544YUOn4eIksdnvNzstoNxtUumT3TBYN9VVqWU1lYobv5R6MrFxd3G2pQNUXrzaV7o0BCH+e3r1tVvw/Ds/jZmRZlKT2BDi7r4XmTrJTZkk15i4milGSYCQUDGAGHpWzQiopalVrmm06VYuapTWPrb5YwzzoAQqVlFjUajeOihh1BVVYU+ffrgnnvuQb9+/RAOh/HWW2/hhRdewIwZM9CvXz9MmjSpQ4/1xBNPIBQK4aijjsK6dWy8TZR2ZBgeOafJTftjLuxR3P23i+sYCG5gAQCoiNUojT8hdyi8nP1H1CIhBPr7e2FDcIfpmHcOzMOJucNR4iuyMTPKRB6RjyytF+qMXaZjVtT/FYWuv8GtOXsWoBRqfWwlABfWIIaj7UmIiOgQAccXAJ34/C0tAKos9+1sH3zwAfbu3Quv14tf//rX6NatGwDA6/XiiiuuQHl5Od599108//zzGDduHFyuxL41n376Kb766iuccsopKC0tZQGQKA3pcgMEmrYj+CqcBdVp4l3do6xLKo1tCe7GjtA+pZgCd65N2RBlhgmFx2PDLvMFwDgMzCpfhJuLL7AxK8pEQgj08Z6L1UHzS1nDsgI7Ih+jv+8iGzNLfXEMRBzdocPc70ABIDv+c1TqrwDCb29yRORoUgrAgZtgHM6JMwAt3wQkVR0qTp5xxhmNxb/DXXrppRBCoLy8HCtWrEjoMWpqavDvf/8bfr/fkqXERJQEMoxs47dNbiqP6zhgqM1G84hc9PScamVmaUlKiad3z4Ch8BGbAHB8zlD7kiLKACfmDkMfbw+lmPlVKxCTcZsyokxW6j0b2Zrakt4d4Q9tyiaNCBfC2sVKIRrK4ZEf2ZMPEdE3nF36a6DyPSgrK8O9996LQYMGwe/3o2vXrjjrrLPw5ptvdjiPSCSCv/3tbxg3bhyKiorg9XpRUlKCCRMm4KGHHkIwGOzwYxziiAJgMBjEhg0bAACjR49ucUy3bt1QUtLwwmbZsmUJPc7TTz+NqqoqXHvttejSpUtiyRJRUnnkJ9Cxs8lt+xWX/gLA8MD3oQu1HYMz0YbgDmwPq83+OzbnKHTz5NuTEFGGcAkd1/Y4WykmIqOoidXblBFlMl14MVCxp22tsSvl+oEnQ0hchRj6KMV45Qc2ZUNE1EBCQko4+jDi5n5HrVq1CiNGjMDUqVOxceNGuN1uVFZWYtasWZgyZQruuuuuhP8eNmzYgGOOOQb/8z//g08//RQVFRUIBALYtWsXZs+ejV/96lc4ePBgwuc/kiMKgDt37mx8AdKnT+u/gA/dt2OH+SU1h6xYsQIff/wxBgwYgPPPPz+xRIko6bzG281u2x5VK+R5RSGKPadZlVJaW1azQWm8V/Pgxp68hhKZkedS76+2K1xmQybkBB5NrZ8dYCBq1NqSS1oRXoSF2tJ7Tap9cEZElBDp7MNMMSwcDmPy5MnYv38/RowYgaVLl6K6uhrV1dV46KGHIITAY489hmnTppk4W1N79uzBuHHjsG7dOowZMwYff/wxQqEQKioqUF9fj4ULF+K+++6Dz+dTPndrHFEALC8vb/xzYWFhq+MO3VdRUaF0/kNTNjVNw+233w5dZ9N/orQkJVxY0+SmrVEP9hlqBcBcva+FSaW3qnid0viBvl7IT6CoQeREXT35yNWzlGKe3PUGgvGwTRlRJsvR+0IovnX4uv7/OAsQABQ3A9FQBiEr7cmFiAgNM+CSXYBL9iFN/E775z//ic2bNyMQCGDmzJkYOXIkACAQCOD+++/H7bffDgD45S9/iWg02u75Dnf77bdj9+7dOP300zFnzhxMmDChsZbk9/tx4okn4o9//CO6du2qdN62JLTTxS233AKgoSnwU0891ez2RB15PquEQqHGP3u93lbHHbpPdY31Sy+9hN27d+O8887DoEGDEkvyG88//zz++9//tnr/1VdfjWuuuaZDj9GZNE1r/H9BQUGSs6FkOrRDeF5eXuq+Gaj7O0R9pMlNqyPqTbiPKpyMgmz+vNfHQlhRt0kppnt2V14rHCQtrgsp7uyeJ+OVneb7hVXH67AkugEXdD3dxqzU8LVCuihASfR07Kj/1HTEgdjXiAV2osh3jKnxGXtNiJ0BVDxserhABPna74H8f9mYVGrjdYGADL4mpAqHbwICEz9Szz//PICGOkxpaWmz+++77z78/e9/x+7duzF79mycddZZph565cqVjf0Dn3jiiTbrVFZKqAD4zDPPNP5jPLxgd/jtibKjAGinbdu24Y033kBBQQGuv/76Dp+vrq4O+/fvb/X++vr6tJxhKIRIy7zJeode0KUaGd8HWf/3JrdVxXUcVNz8I9tVjL6546EL/rz/Z/NMVEZrlGJO6zaK1woHStXrQjqYUjIes/YtVPq39vH+RbioZJx9SSWIrxVS38guN2FX/TwYiJmO2VgzAz2zjlV6nIy7JugDYXhOASLzTYeI6OcQxgYI9xAbE0t9vC4QkIHXhFRhQ03VzpKi1emKdk5YW1uLxYsXAwDOOeecFseUlpZi6NChWL16NT7++GPTBcBDhcWRI0di+PDh5pPuoIQKgAAgpWyx2NeRynxHi4etOXzNdDgcRiAQaHFcONywJMbvNzfjxzAMPP7444jFYrjllluQlaW2DKclWVlZKCoqavX+QCCAeDx9dvDTNA1CCEgpYRhGstOhJBJCQNM0GIaRmp/g1b0Egab/tqoM9RcbY7v/HjA0xJE+/07tUBcL4qN9i5RiunsLcWzekLS6xlHHpPx1IQ1k6wFcVjIR/97ypumYvcGDKfXvjK8V0ke+eyD655yHjTXN++W2pjy00fTPW0ZfE7LuAyKXQ8D8EjGj/jUg+2c2JpW6eF0gIL2vCaleuNaEaLcAlmqsrhaJdmZArlmzpvHnbsSIEa2OGzFiBFavXo3Vq1ebfuz58xs+EBo9ejSqqqrwu9/9Dq+99hp27tyJvLw8nHjiibj99ttx3nnnmT6nGQkVALds2aJ0e7Id3vevvLy81QLgoV6BZqeZz549G+vWrcPw4cNx4oknNls6HIs1fDoqpWy8z+12w+Vq/dt+3XXX4brrrmv1/gMHDij3KEymgoIC6LoOwzDSKm+ynq7rKCgoQFVVVUq98TwkJ/YJDp/rZ0hgeaTla0VrBFyQdQWoqOfP+sKqVQgbkfYHfkNA4LaeF6O6ssrGrCjVpPp1IV34FTcqCsZD2Fa2E7mujn9waQW+Vkgv7lg3pfF1sb0oLz8AYWJmfGZfE4qQLU6GR841HRENbkZt1Jn/JnhdICC9rwlW9m2zhQTsna+XDtp+/nv27Gn8c3FxcavjDt13+Pj2bNjw7UaJxx13HDZt2gSXy4WcnBwcOHAAM2fOxMyZM3HPPffgz3/+s+nztiehAmBrO+m2tcNuMpWUlDR+grR9+3aUlJS0OG779u0AgN69e5s67759DTt0rVq1CldeeWWr48rKyhrv/853voOLLrpIJX0ispkmt8CFtU1u2xzzokJx+W+ha5htM5nTTU28Xml8np6NgYGWr81E1LZ+/p4QML80xoDE33a+ip/1uYHXLFKWo5t7nXxIVNZibfA5DA3cbFNG6cNAd6XxOtYAMgoItdcjRETtkXas/007bX8Pamu/3cm+tUlkh99XU2O+HcuhDzaeffZZaJqGv/zlL7j11lsRCASwZ88e/PSnP8V//vMfTJ06FaNHj8a1115r+txtSfnF9OXl5Zg7dy7mzjX/admR/H5/4+YcS5YsaXHMgQMHsGPHDgBo3NmFiBxASmTHH4RA0+Ul6yLq26338bbcG8KJVtVuVhqf606NmUhE6aiLOw8jswcrxayt34aNwZ02ZUSZrKtrJPxa6+1qWrI1PANho9KehNJITKj1edJxAH7jSZuyISLHS4GdeJO7C3DyHGptYBgGfvKTn+Cuu+5qLCT27NkTzz77LI477jgAwO9//3vLHjfhHoCd5bPPPsOUKVOgaVrjktpEjBs3DuvXr8fcuXNx5ZVXolu3pssXXn/9dUgpUVhYiKOPPtrUOa+55po2d+T973//i+nTp6OoqAj//ve/E86diOyjY1Wz2X9hKVCuOPsvXz8KPdwnW5la2lpSsw5LatcpxRyTNcCmbIic4ZKicVhRuxFxmO+V9Wnl1xgUUJvNRSSEjoG+K7Ci/nHTMQZi2Bn5BAN8l9iYWeqLiHEwkA8NlaZjfPINBOXNgOAHZURkJYELu/fGhT3UVuDM2LsTM/busCmnxF3YQ/25fFTW9pLd7Ozsxj/X19cjNze3xXH19Q0rn3Jyckw/dk5OTmMLuh/96EfN7hdC4J577sG1116L1atXY8+ePejZs6fp87cm5WcAHtLRpp9nn302evTogVAohAcffLCxX2E4HMarr76KmTNnAmjowXdkj77vfve7mDx5Mv7yl790KAciSj0eY3az2yrj6pfGYYHvmupv5ATvHfxCabwGgfEFx9mUDZEz9PH1wEm5arOL9oYO2JQNZbrenjORq/dTiqmOp2av8E4lPKjXblcLQRAe+YlNCRGRU0kAfk1HF49P6fBretJn7rV0JPJcfHrb8+EO7/u3e/fuVscduk+lQHfo3IWFhc0mpx0yZMi3u8AfWq3aUSk/A9Aqbrcbv/zlL3H//fdj69atjVMsQ6FQ4/TLCy64AJMmTUpypkTUaWQcHjmnyU0xCcwLtvzpTlsCWg+LkkpvZZEKrK/frhRzedFEdPXk25MQkYP08HZRGr8/WgFDGtBE2nweTClCCIE8faBSUa8qtglSSsf3nYxoFyBuPAMdrb+ZPJJu7EqjaRtElA40AMFYHAfDIaW4YCye3LWzrUjkuYRibW8sM2TIkMa9JFatWtWkIHe4VatWAQCGDRtm+rFHjBiBlStXmh5v1e9OxxQAAaC0tBR//etf8dprr2HRokU4cOAAsrKy0L9/f5x//vkYM2ZMslMkok7kk89BR9Op31uiXtRBbSZfF9dIeLU8K1NLWwej6rv4nll4og2ZEDlPH5/aBxFV8Tq8XjYHlxVNsCkjymRZutpSqzpjJ7aF30Vf3/k2ZZQ+DFEMXZovALoxH0F5G8BiPRFZRQLv7NmJd/ao9wMWKbh7cCLPJc/rxZ/auD87OxsnnngiFi5ciPfffx+XXnppszE7d+7E6tWrAQATJ040/dhnnnkmpk+fjvLycpSVlbU4C3Dt2m/bVFm14a6jCoAAkJ+fj+985zv4zne+Yzom0f597fUIJKIkkmH4jFea3bwxqr75Rz/vhVZklBEqY+Z3vwIAAUDn0mkiSxyTPRBd3HlKhfgPDi7AuV1OQZaufu0jZyvxjMO64H8gYb5H98bQKyj1ng1NOO4tSBMxDIMbX5oe78JGeOWrCIsrbMyKiBxFICVn8nUqE8//2muvxcKFC/Hiiy/i17/+NXr3bto7+U9/+hOklCguLsb48eNNP/SUKVNw9913o6amBlOnTsUf/vCHpqlJialTpwIATjjhBBQVqW2+1Rp+jEREjuSWX7TYhLvSUHtTUuQ6Ad09nMEGALXxIKbv/UgpZoC/BJrDl4MRWUUTGi7tZv7FJwBEZAzzq5bblBFlMq9WgFLv2UoxYVmO/dHFNmWUPsLaRZCKM2h8xsuAbHu5GhERmWem/nnbbbehf//+qKurwwUXXIDlyxteMwWDQTz88MN4/PGGDbEeeughuN1NN5Hs27cvhBC46aabmp23oKAAv/zlLwEA//d//4fHHnsMwWAQALB3717cdNNN+OqrryCEwG9/+9vEn+QRWAAkIkdyywXNbtsdcyvMY2hQ4jE/1TvTzS7/EhVxtRmAEwqOtykbImc6Nf8Y9PZ2V4rZFS6zKRvKdMP8t8AtstsfeJiaeOrtHtnZDNFTeTafjt1wgcV6IiKryG/2gmiL1+vF22+/jaKiIixfvhwjR45EXl4ecnJy8POf/xxSStx55524+eablR//Jz/5CW6++WbEYjHcddddyMvLQ5cuXVBcXIznnnsOmqbhkUcewTnnnJPI02sRC4BE5Di6XAevnNnktpgEPg/lAIqfyOe6+lqXWBqTUmJ25RKlmKOy++CkPLVdS4mofT0VNwPZFym3KRPKdJpwI0vrpRRzIPq1Tdmkl3rtfyDhbn/gYTRjn03ZEJEjpcDuvck8NGnufd/w4cOxYsUK/OhHP8LAgQMRDoeRl5eHSZMm4Y033sBjjz1m6jxHEkLg6aefxmuvvYazzjoLeXl5qKmpQXFxMa6++mosXLgQd911V0Lnbo2zG3AQkSP5jWch0HQZzdaYF2Gp9plIV9dIZOnF7Q90gHojrLwByE19L4TLYP8/Iqv18jZvJN2WNXVbsKJ2I47OHmhTRpTJcvW+qIyvMz2+PL4KuyKfopdnrI1ZpQGhQyIfAuZn4HrlW4jIs7gZCBFZQji8B6CmMPGjqKgIU6dObezLZ8bWrVtNjbvkkktwySWXmD5vR/C3BxE5ipAH4ZafNbt9e9SreiYM8l1lTVIZwDDU+xL5uekAkS1Ozx+ltEOfBPDK/k8gpcPfCVBCVPsAAsCm0Gv8eQMQFSOVxruxDB75oU3ZEJGTSAlACkcfRgruZmw3FgCJyFFccmWz2X8AUKE4E62H+2QUurl89ZAPyxcpjXcJHUW+QpuyIXK2Lu48jM0/VilmW2gvNod225QRZbI810AUudU2w6qJb0V1fLNNGaWPsDZFOcZnvGpDJkTkOFImfQlusg8nzoBkAZCInEOGETD+0ezm9REf6qVaAbDANcSqrNLernAZ3j7YfFZlW07rdiyyXX6bMiKi63qcA5/mUYrZEmQBkBIzKuseqL6tqIvvtSeZNBLDKIQxTinGhdXQJHsBElHHCOG82W/NOHAmOguAROQYXjkTOrY1uS0mga/DAeVzFbm5e+0hH5d/qTTeJXRcUjLBpmyICADcmguFrlylmKporU3ZUKZziwDcQu136c7ILC4DFgL12p3qYZLFUyLqGAEkfQZesg8nFkFZACQiZ5ASXuP1Zjdvi3kRUbwUdnWNRLZeYlVmaW957Ual8Rf2PAMDsvn9I7JbkadAafzsyq9QGWMRkBKTrw9WGl8WW4K90S9syiZ9SJGvHBMw/gFI9d67RESHSNHQLdjZBwuAREQZSaAKLjTvN1QWU9sMXcCF4YHvW5VWRggaIaXxfbN62pQJER3udMU+gDXxeswoU1vOT3RIH++5yjFbwzNtyCTNCD+iUPu36sYyuOWnNiVERE5gGDLpM/CSfUhDWvCdTC8pXwAsLS3FjTfeiBtuuCHZqRBRGvMZLzW7zZDA7rhaj6wurqORrfeyKq20VxmrRTAeUYrJdWfblA0RHe7YnMEo9nRViplXtRwhQ+3fNBHQ0BqjUB+mFFMeW4GwUWVTRukjpF2qHOOTb9iQCRE5hQALgOAMwNRz7LHHYtq0aZg2bVqyUyGiNKXJrfDJZ5vdvjLiR53i5h+5ej+r0kp7Ukr8bccriLewq3JrsnQ/RuQOsDErIjpEFxru7n2VUkzQCGN7iP3FSJ0QOoYHvqccFzTKbMgmvUTFOEQxWinGJb+GExvYE5F1hHT2oTnwEpryBUAioo7yGa83+3wnLoG1UfVdaEu8E61JKgNsCO7A+uAOpZhx+cfCq6vNuiSixHVT7AMIAPXxsA2ZkBP4NLUZpwCwNjgNUho2ZJNGhIagdr1aCAxoUu13MBHRIQICkE4/kv230PnUml+1o3///gnFaZqGnJwcFBYWYuTIkRg/fjzOP/98aBrrk0TUcR45u9ltu2IehKXaNabIfQJy9N5WpZX2PqtcqjS+m7sAF3Uba08yRNQiTQjkubJRpbC5x0fli3BM9kBoDtwdjzrGo+UgXx+Myvh60zEHYyuwP7oY3T0n2ZhZ6jNED+WYbOPnqBbPAsLSt3RE5ACy8T8O5sDnb+lvi61bt0IIAXnYdPTDt1aWUjb7+shxc+bMwaOPPorS0lL885//xJlnnmllikTkMLrcBIGDzW6vNNSW/mpwY2Tgbouyygz7IxVK44/PHQKv5rYpGyJqzSl5R+O9g+Z3W11Rtwlf1azBCblq/dyIAKCP9zxU1psvAALAtvC7LACiFDEMgQtrTce4sAVuOQ9RwQ/XiIhUObD+Z+0S4NLSUpSWlqJXr16NBT0pJaSUyMvLQ69evZCXl9d4G9BQ+OvVqxeKi4vh8/ka79u2bRvOPfdcvPrqq1amSEROImPIjv+s2fLfqBTYEPUpnSpL6wWPlmNdbhkgaKgtE/QIFv+IkmFCwfHQFV/yfVS+2KZsKNMVe8YiTxukFHMwtsqmbNKIEAhpaj07AcArZ9iQDBFlOoHk9+BL9gEHdp+wtAC4detWzJs3D3379oWUEqeddhpee+01lJeXo7y8HDt27Gj886uvvorTTjsNUkr07dsXixYtQl1dHZYvX45bb70VAGAYBm655RYcPNh89g4RUXvcch507Gp2+6qIH/WKm38UujkT5nCr67YobxTQ319sUzZE1JYiTwGu6X6WUsza+m0IshcgJUATOgb6L1eKMRBBbWy3TRmlj4g4E1EcqxSjS7XZlkREAJK/A28KHE5sdGJpATAcDuOCCy7A/Pnz8atf/Qpz587FlClTkJ+f32Rcfn4+LrnkEsydOxf3338/5s2bhwsuuACRSAQjRozAk08+ib/+9a8AgLq6Ojz55JNWpklEDuE13mt2W1xCefYfAPTxnmtFShnBkBLP7JmpNG2+qzsPx2QPtC0nImrbUVl9lGNUZ/kSHRLQ1fvZfVX3OxjS/K7yGUkIRMQkpRANB+A25tqUEBFlKnnoPw4+ZNx5UwAtLQA++eSTWLp0KcaMGYPf/OY3pmIefPBBjBkzBkuXLm1S6LvjjjswatQoAMCsWbOsTJOInEBG4MKSZjeXGy6EFDf/6O05Czm6+pvnTLWqbjP2RcqVYi4vmghNcGMnomTJ1gPKMavrttiQCTlBjtYHOXpfpZhaYwf2RRbZk1AaiWlHKY0XALKMhwEZsSchIspIQiR/CW6yD82BcwAtfTf24osvQgiBq65S619x1VVXQUqJF198scntF198MaSUWLvWfDNcIiIACBiPQkPzXS/L42pLfwFguP97VqSUMVbXbVYa39fXE2PyRtiUDRGZUeDOQX+f2jL8Z/bMRHm02qaMKJMJIdDfe5Fy3PbwhzZkk17iGIoY1IqAGirhkZ/YlBERZSIBJH0GXrIPKVkA7JCNGzcCAHr27KkUd2j8hg0bmtw+cGDDcrGKigoLsiMipxDyALzy7Wa3hwyBZWG1WTAuZEPnzrVNhIyo0vh8FzdPIUoFkwpPVBoflTHMqWg+k5rIjF6eCcjXhyjFVEXVPmDKSEIgqH0PUjHMbZjf6ZuISB76j4MPzXn1P2sLgHV1dQCA3bvVmvju2bMHAFBfX9/kdq/XCwDw+dT7dRGRc3nl+xBo3kdoXdSHMNRmABZ7TrUqrYwgpcSO0D6lmDxXlk3ZEJGKk/OOxtBAX6WYBdUr7UmGMp4QAsWe05ViQvIAttSw9U9UG4MYRivFuLEYXAZMRCqEww/lT1oygKUFwN69ewNAs6W87Tk0vqSkpMntBw4cAAB06dLFguyIyCncxmfNbpMy0c0/zrMipYzxaeXX2BDcoRTD5b9EqUETAmML1IoKVdHmrRSIzCpwqS1lBYCF+6cizkIWYuIYpfEaKhEwnrApGyLKNMKB/e/I4gLg2WefDSklFi1ahPvvv99UzC9+8QssXLgQQgicc845Te5bvnw5APUlxUTkXG7jU7ixotntISkQlGqz//p5L0auq59VqaU9Q0q8c+BzpZgSb5HyjCMiso9f8yiNj8go+wBSwvL0QcjV+yvFhI0q7A6r/a7JRBFtvHKMV74FIWtsyIaIMo1IhfqfA2fgJZulBcAf//jHyMpqWOr18MMP44wzzsDrr7+O8vKmu0WWl5fjtddew+mnn44//vGPAIBAIIB77723ybj33nsPQgiceKJazxoicigpETCebPGuPXH1Pn6l3rM6mlFGWVO3BWXRStPjdWi4o+RSiJR4hUFEADAo0Bse4TI93oDEYztehpR8lU7qhBAY4r9ROW5/hL0n42IQojhWKUYgxM1AiMgUmQI9+BoSSd4hHPjSxvwrQBNKS0sxbdo0XHPNNYjH45g3bx7mzZsHAMjNzUUgEEB9fT2qq7/9JFlKCZfLhWeeeQalpaWNt8+dOxf79+9HIBDARRddZGWaRJShXFgGHVub3R40BBaGspXOpcEDn8b2A4fbGylvf9Bh8t05KPZ2sykbIkpElu7HmLwRmFu51HTMltBurK3fiqFZnBFN6rq5j0WhawTKY+b7Se6PfomYDMIl/DZmlvrq9PuRF78KAjHTMS5jEcIa3zsRUdskpCMLYE048PlbOgMQAC677DJ8+OGH6NevH6SUjUdVVRX27t2LqqqqJrcPGDAAs2bNwqWXXtrkPGeccQZqa2tRU1ODsWPHWp0mEWUgtzG/xds3Rn2IKV7uij2nO/6Nx5Gk4m9Jj+DuyUSp6JJu4xHQ1HqiqhQMiY5U4BqqND4qa7Cm/mmbskkfhihGDMOUYjz4FLrk5j1E1I5kz/5LlcNhLC8AAsC4ceOwbt06vPbaa7j++usxZMgQ5ObmQtM05ObmYsiQIbj++uvx6quvYu3atSzwEVGHaXIvvPK1Fu/bHPMqnUvAhf6+iy3IKnPEpYEFVc17K7alj6+HTdkQUUcUuHNwar7aBgP7wmozgIkO18tzhnLMzshsRAz2n4wJtY17BAwEjH/ZlA0RZZRkF99S4XAYS5cAH07XdUyZMgVTpkyx6yGIiBr5jGnQEGzxvlpDdfOPC5Gj97EirYzxcflibAjuVIoZX3CcTdkQUUfl6llK4w/GqmBICY09PSkBOXofdHGNxMHYMtMxBiLYG/0Cpd6zbcws9YW1yfDFn4OAYTrGLRdDkzthiBIbMyOidCbgzB54h3PiKxpbZgASEXUmIWvhlR+2eN+GiBeG4uW90D3CirQyhiElPqpYrBRzdNYAHBUobX8gESVFf3+x0vjKWC1mHPjMpmzICUZl3Q0BtdYQ+yJqv3sykSF6ICSuVo5zG1/ZkA0RZQru7QU4sQTIAiARpT1dLodAuNntYSmwOKy6+YcL+fpgq1LLCDvD+7FPYQMQAYEf9LqEu/8SpbBhWf1R5C5Qipl5YB6C8ebXWiIzfFoX5OkDlGL2xxahLPq1TRmlj6D2A0iotTPxyWmArLMpIyLKCMlefpvkQxrOq4KyAEhE6U3GEDD+0eJdm6I+xBU/2enhORVeLc+KzDJGbbxeabyEhEfjBiBEqUwTAld2n6QUE5ZRzFfsBUp0uCK3Wj87ANgYetmGTNKM0BDDIKUQHfvhk6/alBARZQIhnX2wB6CFli5divfeew8rV65ERUUFQqFQuzFCCHz88cd2pUREGcgj34cLG1u8b1dMrQilw4vBvmusSCuzKP5ydAsdLqHWd5GIOt/xuUPRz1eMLaHdpmN2hPfZmBFlut7es7Ah9BIk4qZjymOrUBvfiWzd2f3sItoFcBtqu/t6jTcREtcB/J1MRC1xYAGsCQfOALS8ALhnzx7cfPPNmDVrllKclJLLxYhImc94vcXbpQQqDbVLXC/POGTpPa1IK2NEjRhe3veRUszI7EG8nhOliSJPgVIBsDzCXVkpcT6tEIN9V2Nd6HmluAPRZY4vAIbFmfDhKegoMx2jYx80uQ2G6G9jZkSUtpxX/2rKgY0QLV0CXFtbi/Hjx2PWrFmQUiodRESqhFEFF9a2eN+KiB8hqXaJy9H7WpBVZvm8ahm2hPcoxUwsPMGmbIjIaj08XZTGr6zbhM3BXTZlQ04wwHc5NHiUYjaEpiNiOLz4LPyo0/6fclhA/sORb3KJyIQU6MOXzEPnJiAd88gjj2D9+vUAgJKSEjzxxBPYuHEjQqEQDMNo94jHzS8HICLyyedavD0iBVZGAkrnEtDRwzPGirQyyiflXyqNH5t/LIYG+tqTDBFZ7oz8UUovf+Mw8OI+tVUeRIcTQiDPNVApJiKrsCU8w6aM0kdMHA2puIDLIz+HS3I3ZSJqLtk9+JJ9SBYAO+aNN94AAPTo0QOLFy/G9773PfTv3x8ej9qnfERE7dHlJvjliy3etyXqVd78o6f7FPg0tZkwmS4YD2O7Yr+vswpP4vJfojTS1ZOPU/NGKsWsr9+OnaH9NmVETlDqOVs5ZnvofRjS4ZMFhBsRMUE5zCdfsyEZIqL0JmSyM+h8lhYAN23aBCEEbr/9dnTv3t3KUxMRNeFtpfcfAJTH1Zpd6/BjeOB7HU0p40RlTDkm7vQ3Z0Rp6Mae58GnqX1Yu75+u03ZkBP09JyKgChWiomgCrXxHTZllD5C2hXKMW45DzAMG7IhonQlgKQvwU2Jw2EsLQAa3/xiOeqoo6w8LRFRMx45u8Xb4xLYFVd7I9vVdQw8Wq4VaWWUsBFRnhhf4Ob3kSjdeDQ3Clxq/3Zr40GbsiEn0IUHI7PuVo5bGfwHpHR2ISsuhiEkLlaKETDgk2obrxBRZtOESH7xLdmHAxctWVoA7NOnDwCgpqbGytMSETXhMhZDoLLF+5aGAwhKtRmAua5+FmSVWWIyjsd2vqL0wdjRWQOQ68qyLScisk+hYvH+s8qlCBsRm7IhJ8hzDYAGr1JMRWw19kUX2ZRR+ghrlyrH+OW/oEm1Tb2IKHNJ2dABz9EHZwB2zOTJkyGlxLx586w8LRHRt2QI2cb/a/EDm6gENkR9iifUUOKZZEVmGeWr6rXYHtqrFHN2F26iQpSuTs07Rmn8/mgF3j0w36ZsyAl04UYvzxnKcdvD79mQTXqJoz/iKFWKEYjDa7xlU0ZElG4MIPkz8FLhcBhLC4B33nknCgoK8MILL2Dt2rVWnpqICADgkR9Ba2X2386YB1HFy1qJZzwCepEFmWWWTyuXKI2fVHACjs4eYFM2RGS3E3KHoVBxGfDsyiWIse8ndUA/32QAarP2y2LLIJ3+cycEQtplymEeyeIpETUQEEnfhTfZBwuAHdSzZ09Mnz4dLpcLZ555JubOnWvl6YmI4DU+aPW+akN18w8fRgS+39GUMpLqDp+DAr1tyoSIOoNHc+Gu3lcqxVTFarE1yCWFlLgcvQ/6ey9SjDKwOjjNlnzSSVhcjBj6K8XoKIPHmGFTRkSUXmTyZ98l+XDiEmCXlSf77W9/CwCYNGkS3nrrLYwfPx6jRo3CySefjK5du0LT2q83/vrXv7YyJSLKIJrcCxeWtXhfWAqsV1z+m6X1gi7U+g85heHEj8SIHK7U10M5JmiEbMiEnKTEOx6bw68rxWwNv40+3nOQrZfYlFUaEC6ExPXIlr9RCgsYjyEiJgIiYFNiRJQ2HP9y33m7gFhaAHzggQcgRMM3UQgBKSWWLl2KpUuXmj4HC4BE1Jqs+IMQiLV438qwHyHFzT+6uI+2Iq2MUxGtUW7uX+ztZlM2RNRZNCGQpflQp1DU+7J6LY7OHmhjVpTpsrVS5Or9UB3fohS3Pfw+hgW+a1NW6SGqnQoZ90HA/L9ZDXXwyg8RVtxJmIgo4ziwAGrpEmAAkFI2Hkd+3d5BRNQaXa6HG1+3eF9MAhuVN/8A+njP6WhaGUdKicd3voKIbLnQ2pL+vmKU+rrbmBURdZbjcocojZ9TuQRr67bZlA05gRAC/ZSXAQO7InMd//5BimyExXnKcV5DbcYlEWWepO/AmwqHA9cAWzoDcPbs2VaejoiokaeN3n/lcRciip9n9PdOQZZe3NG0Ms76+u3YGNypFHNRN/VdHIkoNU0qOAFzK5cqxcwqX4QhWX3sSYgcoZdnPLaH30dF3PwmghFZiU2hVzDQf4WNmaW+eu0H8MQ/hoYq0zEubITHeAcR7QIbMyOiVCYb/+Nc0kh2Bp3P0gLg2LFjrTwdEVEDGYZXvt/q3eWKm38AwFG+GzqSUcb6rKrlHoutGZM7AqNyBtuUDRF1tj7+nji/yymYeXC+6ZglNWsRNqLwam4bM6NMJoRAX++FqKg3XwAEgA2hl9HHex7cWrZNmaUBkYWwuBh++axSWMD4JyLiHEBY+naQiNKFQzfBOJwTn7/lS4CJiKwWMJ6AhooW7wsaAsvCWUrn84g8aJp60dAJyiItf59b082Tb08iRJQ0p+QdozTegERtvN6mbMgpuntOhEuo/T43EMGO8Cc2ZZQ+wtr5yjEaDsBtfG5DNkSUDgRE0nfhTfZhxJ03BZAFQCJKbbIOXvlOq3evjfqVl//29JzW0azoG7pgIZUo03g1j3LMnvABGzIhJ9GFF3196v3stkXedXwvQEOUICLUX9v45TTA4d87IqdqXALs4MN5ewCzAEhEKc5jfA6BlmeWGDKRzT809PGqv8FwgtpYPXaFy5Ri+vvYR5Eo03Rx56G7p1Ap5h+73kBd3PxOpEQtGRK4FgFdbVf5emM3NoffsCmj9FGn/RwSXqUYFzbAK1+zKSMiSmlSJr0Al+xDd2AJMKGmD9u3b2/8c2lpaYu3J+rw8xGRw0kJr3yl1btDUiAk1T7HGOS7Ajl6745mlpGe3vMOahSW8XVz5+Po7AE2ZkREyaAJgQkFx+HFfbNMx9TE6zGvchnO6nKSjZlRptOEG4PzLsLS8n8rxW0OvY6+3guhC+f2oZSiABExAV75nlKcz3gRYXEJIDgvhMhZpAPLX00ZDvwOJFQA7NevH4CGhr2xWKzx9r59+0KIxL+JR56PiJzNI2fCjdWt3r8nrv5Cv9jDHWtbsj9SgSU1as3Xr+g+CRrfMBBlpAkFx2NuxdfYFTG/tPezyqUsAFKHDcw9H0vLnwZgvjdTRFZjT2Q+Srxj7UssDYS0S+GNqxUAdeyBS85HLIElxESUvmTjf5zLeeW/BJcASykbj7buS+QgIgIASAmfMb3Vu4OGwMJQjtIpdXjh19SWFjnFgqqVSq8Bjgr0wYm5w2zLh4iSy6O5cW7XU5Ri9ituIkTUkix3d5R4xynHbQj9F4Z09kSCOIYiKk5QjssyHgEkl/ATOYkQ3ATEiT1QE5oBeOONNyrdTkSkSsdGuLC51fs3RH2IK35uU+wZC12o9cdxivJYtdL4LF219yIRpZss3a80PipjCMbD8Ou8zlLHHJN9B/aGv0AMQdMx9cYebA69gYH+y23MLMUJgVrtt8iPXwgB88VQHXvgk68iJK6zMTkiSiUCgHBe/asJIZ03BzChAuC0adOUbiciUuU12m5KvSWq9gZTgxv9fRd3IKPMpitOCHeLhH59EFEa6evrCQEBaXJ+cBwGntj1Ou4pvdrmzCjTuYQPxZ6x2B55Xylua2gm+vsugebgHeqlyENEnAavnKMU5zVeRkhcw16ARE7hwOIXcRdgIkpBLrkCPvl2m2NqpdqL+37ei5Gtl3QkrYwVMaJYXbdFKeaoQB+bsiGiVFHozsWxOYOVYpbVbsCW4G6bMiIn6eM9VzkmjHLsjXxhQzbpJaypz4LUcQAexQ1EiCh9SSkhJBx/OA0LgESUcrzGy23evy7iU961qdA9tCMpZbTXy+Zgt0Kjf5/mwSl5R9uYERGliku6jYMLah+4zKlYYlM25CS5rn7o6VbfmGJ18F+IGrU2ZJQ+YhiFCNR6eAJAlvFnCFlmQ0ZElJKS3oMvyYcDtwFhAZCIUosMwSNnt3p3yBD4MpyldEoNbuTrarNYnCJsRJTfrF/V/Uz2+CJyiN6+7jhZseC/K8wCAlljZNZd0OBWignLCmwNv2NTRmlCCNRqD0AqvrkVCMFnvGlLSkSUYoRMfgEu2YchO/59TDMsABJRSvEY70PAaPX+TVH12X89PafBo+V2NLWMtLx2I4JG2PT4bu58jC84zsaMiCjVdPPkK40/GK2CdODOemQ9XXjR032qctzW0DuQMm5DRmlEy0ZETFAO88kXAYfvpkzkBMKBs98owU1A2hOPxzFjxgy89957WLlyJSoqKhAKtb+1vBACmzZtsiMlIkoDQpYhS/6lzTG742ozAXT4MNh3TQeyymyVMbVlUhqbgxM5Ti9vkdL48lg1PixfiLO7jLEpI3KSPr7zsSs6RykmgmpsC7+Pvr7z7UkqTYS1K+CNf6wUIxBCwPgj6vX7bcqKiFKDcGQPvMM58flbXgBcvXo1rrzySqxevbrJ7WY+CRaCVWgiJ/MZb0Eg0ur9UgIVhtplq5dnPAJ6946mlrE8Qq2g6lUcT0Tpb1TOIOS5slGl8IHBm2WfYlzBaHg1j42ZkRMUuI5CsXscdisWAVcHn0KR+3hHvwaIiaMREhfBJ99SivPJmQjLyxEXbJ9ClLEEvumDR05iaQGwrKwMEydOxP79+xsLfi6XC127doXXy35RRNQ2j2y7Z8+ySABhqTYDLdfVpyMpZTQpJZbXblCKGZbVz6ZsiChVuYSOi7qejuf2mt8htN4IY0HVKowtONbGzMgpjg7cjj1VcyHbaBFyJIkYtoXew9Csm+xLLA0EtTvgjc+EgNqyXl/8KdS5/mhTVkSUbEJKCKe363BgD0BLC4D/+7//i3379kEIgVGjRuEPf/gDxo8fD4+Hn/4SUdtccgU07G/1/rAUWB3xK51TwIXu7pM7mlrG+qxyKb6sWasUw/5/RM40oeB4fFS+WGnH8C2h3RgLFgCp41yaD8WesdgVaX2TsJZsjczA4MDV0IVzJyJIkY2wOBc+OUMpzoPPEZbLEBMjbcqMiJJJNv7HuYR03gpUS5s5zZw5EwAwcOBAfP755zj77LNZ/COi9skIsuP3t9mKdkvUi7his9piz2nwaQUdyy1DSSnxYfkipZgLupyKHt4uNmVERKlMCIESn1ovwAORSnuSIUfq550MKL4OMBDFsrpH7UkojYS0G2BArQgqIJEV/w03BCHKZMnehTfJhzSct1mUpQXAbdu2QQiB2267DYFAwMpTE1EG88jZ0ND2rJLyuNqEZRcCGOa/tSNpZbTdkQPYEd5nerxbuHBZkfpugkSUOYrcah+orKrbgo31O23KhpwmzzUA/b0XK8ftiX6OqthG6xNKI4bohaCm/ppIx164jU9syIiIkk1IHk7cCdnSAqDb3dAcvm/fvlaelogynNd4u837YxLYFVebTdzVPQoeLacjaWU0lWb+ABCVMcQVei8RUeY5PX+U0ngDBl7c96E9yZAjDfJfCQ3qq4vWBV+wIZv0EhaXwUC+clyWnArIOusTIqKkcuDq1+YcuAmtpQXA/v37AwDKy8utPC0RZTBNboULy9oc83U4CyHVzT/0vh3IKvOp7uarQ4Nu7a8MIkozPbxdcHzOUKWYjcGd2B4yP9uYqC0uEUCJd6JyXFnsKxyILrU+oXQiPAhpVyiHaahGljHVhoSIKKlSYAlusg9hsADYIZdeeimklPjoo4+sPC0RZSopkR3/LUQbM8siUmBjVLVvjYYS76SOZpfRNgbVluUNy+oH4cBPyYioqe8WT4ZH8QOEDfXbbcqGnGiQ7wroUG81tKzuMRgO72cXEtchjlLlOI/8AMIwvwEQEaWHpC/BTfYBmey/gk5naQHwjjvuQO/evfH6669j3rx5Vp6aiDKQCyvhQtu70O6KeRBTvFSVeCbBr3XtSGoZbUtwt/KyvImFx9uUDRGlE7/uRRd3nlJMRazGpmzIiXxaFwzx36AcF5IHsCsy14aM0ohwoVb7hXoYDGQb9wPSeW+WiTKVgEj6DLxkH8KBlzRLC4B5eXl488030bVrV5x//vl47rnnYBjsGUVELfMY77Q7ptLQlc6pw4fhge8lmpIjzCpfpPR513E5QzAye7Bt+RBReumqWACcU7EE1TH2ECPrlHrPglfkK8etDv4LUUOtB26miYujEcNRynFurIBXvml9QkSUJBICcPRx6L9Oorat5jduueWWNu8fPnw4PvnkE9x88834yU9+ghNOOAFdu3aFprVdbxRC4KmnnkokJSJKM5rcC69sexZayBDYEPEpnTdb6w1dcXmak8RkHIuqVyvFXNP9LGhc/ktE3zgl/xisqNtkenxNvB5vH/gM1/U4x8asyEk04UJ/3xSsCU5TiovJOqwK/hOjsu6xKbM0IATq9F8gN35zmy1YWuIznkZYXAQI9gQmSn/fzAB0NOd9AxIqAD7zzDPt9oI6dP+BAwfw3nvvmT43C4BEzhAwHoVAuM0xKyIBhBUnKnd1H9ORtDJeXTyIqGIPpDojBC6oJqJDTsgZilfdn+BgtMp0zOeVy3B50QR4NfUdXIla0s97EXaGZ6PG2KoUtysyF0f5boJfL7QnsTQQF4MQEpfCL19RitNxEAHjUdTrP7IpMyLqLFJKRy6BPZxw4GLVhD++kVJafhCRM2hyH9zyszbHRCWwSXHzD0Cg1Ht24ok5gGrzfkB9x2AiymxuzYW7el+pFBM0wtgS3GNTRuREQmg4OnBHApEGltQ97Pj3HiHtJkioF+R98hW45Nc2ZEREnU5KZx+cAWjOli1brM6DiBzEY7zf7rKT8rgLUcXPKAb6LkdA79GR1DLe7nAZBASkyV94ha5cFHkKbM6KiNJNqbe7ckxtvN6GTMjJ8l2Dka8PRmV8vVJcZXwttkfeQx/veTZllvqkKEBQuw0B43HlWH/876hx/cuGrIiIOpPzWhwlVADs06eP1XkQkUMIWQ6f/G+74w7E1S9Pg7zXJJKSY9THQ3hkx3TTxT8AGFcwGhp7/RDREYQQyHNloypmfkOFdw7Mw6icwXAJtc2diFojhMDIrLsxt/pOSMSVYjcEX0ap5xwIB/+OC4mr4cG7cGGzUpwLq+CNv4awfqlNmRFRZ+ASYOd9A5z7G4+IksIbnwYNNW2OqTM0LI8E1M4rCtvdaMjp5lUtR43CDJxiT1ecVXiSjRkRUTo7OXeE0vgtod2YX7ncpmzIqbL1EvT1XqgcF5blWBN82oaM0ogQqNfU+/kJAAH5CDS53fqciKiTyIYVsEaSD9kJRyuP7cROEHy3TESdRhp18MRntjtubcSHmOLlqdhzeqJpOcbnlcuUxl9eNBF+XbUPIxE5xYTC46EpLp/5uOJLm7IhJxvouwwa1PvVbgm/jfLYahsySh8xMRoRjFGOEzAQiD9qQ0ZE1BkEGjbBEDLJh9EJRxuP7TRJKQC+8cYbuOeee/DDH/4QTz/9NOrr2ROGyAlkaDYE6tocY0hgY9SndF4BHX2853YkNUc4EK1UGh+WEXsSIaKM0N1TiCuLJinFbA3tQW08aFNG5FQeLRdD/DcnFLu2/lmLs0kzQqBW/x0MqK28AAAPvoDHeM+GpIjIbvLQf5x+OIylBcANGzZg8uTJmDx5MhYvXtzs/kgkgjPPPBOXXXYZHn30Ufztb3/DrbfeilGjRnFjEaJMJ2uB2j+0OywoNUQUL02DfdciSy9ONDPH0BX7brlEQm1iichBjs4ZqBwTjIdsyIScrp/vAuRofZXjKuJrsD30ofUJpRPhR1B8L6HQLONhCFlucUJEZDeR7MJbChwy7rwpgJYWAF966SW88847+PzzzzFy5Mhm9//ud7/Dxx9/DCllk2Pjxo2YMmUKDMN5fwFETuGNvwoYZe2O2xbzKJ+7p+eURFJylLp4CDEjZnq8gEB/P4uqRNS2HF191tA7B+bZkAkRMCzwnYTiVgSfQH18r8XZpJewdiFi6KUcJxBFlvGQDRkRka0EIKR09pHsv4MksLQAOG9ewwu6SZMmweNp+iY+HA7j0Ucfbdg1Li8PjzzyCN58802cd955AIAVK1bglVdesTIdIkoV0oAn/nq7w2oNDUvCWUqndiEAn9Y10cwc4x+7XkedYX7WzajsQejizrMxIyLKBLmuLAwL9FWKmVO5BJuCu+xJiByti+sYdHMdl0BkHGvqp1meT1oRPtRof4FM4O2hRy6A13jNhqSIiOwjHFgBtLQAuH37dgghcPzxxze778MPP0R1dTUA4KmnnsJdd92FyZMn46233sKAAQMAAK+++qqV6RBRitDlamjY1+649VEfVD+LKfFOgC7UZw06yZbgbiyv3Wh6vFe4cUnReBszIqJMcmYX9d3CPy5v3iqGqKOEEBid9VPoUOslDAB7Y19gT8TZs1Ol1gshcVlCsQHjMQij2uKMiMg+IulLcJN9CIX3nWVlZbj33nsxaNAg+P1+dO3aFWeddRbefPNN0+cw45FHHoEQAkII9O3b19JzAxYXAA8cOAAAKCkpaXbfnDlzAACFhYWYMmVK4+26ruPqq6+GlBJff/21lekQUSqQYWQbD5gaujWqtuOsDh/6eScnkJSzfFqpdm09u8sYlPq625QNEWWaY7MH49jso5RiVtZttikbcjqX5sNg37UJxS6t+wsiRo3FGaWXkHYjDOQrxwlEkWPcBci49UkRkfVkCuwAnOQDJjvQrVq1CiNGjMDUqVOxceNGuN1uVFZWYtasWZgyZQruuusuS/5Ktm3bhl/96leWnKs1lhYAKyoqAKDZ8l8AmD9/PoQQmDhxIsQRcy379+8PANi719m9N4gykUfOgo7d7Y6TEqiXapek/r5LENB7JJqaY+wJH1Aa78DZ8ETUAUIInJw3QimmLh6ElNKmjMjpSn1nwy/UP8gyEMaK+r/bkFH6kKIANdqfkci/ThfWwW88ZXlORGSTFJiFl9wZgO0Lh8OYPHky9u/fjxEjRmDp0qWorq5GdXU1HnroIQgh8Nhjj2HatGkmzta2H/zgB6irq8OYMWM6fK7WWLrFo8/nQ11dHcrKmjb6DwaDWLJkCQDglFOaN+vPzs4G0LBLMLVN19V28Uwl6Zw7Jc4XN9cTZmkkANXlv108Q/lzZYIm1AqrmqZ12veVf3/Odujvnz8H6a/Qm6s0Pibj+KBiIc7vdmqT2/mz4GxWXRN0ZOHk/IfwScVtgGIpa290HnZH56C3b2KHckhr+ghEo2fDY3ygHOqTzyEqLoTUmq8ISzgdXhcci68T7CO+2QTEyYSJp//Pf/4TmzdvRiAQwMyZM1FaWgoACAQCuP/++7Fnzx787W9/wy9/+Utcd911cLvdCeXy4osv4r333sNll12G4cOHY8GCBQmdpz2WFgBLSkqwbt06fPXVV01u/+CDDxCNRiGEaLEAeGjmYE5OjpXpZKSCgoJkp5AQXdfTNndKnIxthjywvt1xtYaGVRG/0rldIoB+XcfAo6ttGuJEUvE109CuAzvl3yuvC3RIbq5a8YhSz4n5ueiyMw8HI1WmY17Z9zHO63tGkzd4vCYQYM01oQAFOMqYgnVV7W9CdqQVdX/H0KLz4dbVXptkEhn/NeSBLwCp1tdPwEBu/HsQBTMhtI7/e+Z1gQC+TrCDs0t/Dcx8D55//nkAwNVXX91Y/Dvcfffdh7///e/YvXs3Zs+ejbPOOks5j/Lyctx9993IycnBo48+in/+85/K5zDL0gLgySefjLVr1+LVV1/FAw88gJKSEsRiMUydOhVAQ/+/0aNHN4tbs2YNALT4DaWmDhVL00Vubi50XUc8Hm/cBIYcQsaRHf0+dBOX1g0Jbf4xDnXVEdSBM4fb8tHBRVhTvcX0+HxXDgZrvWy91vC6QIfouo7c3FxUV1cjHmffqHQ3seB4vLzvY9PjYzKOt7d8gusHXshrAgGw/prQR5+CzeJDRGWtUlxMhvDhjntwcu7vmrUucg4XNNdUZEe/q94axDiAcNkvEPT8PuFH52sFAtL7dUKqF66llKZmwGUyrZ3nX1tbi8WLGzYtO+ecc1ocU1paiqFDh2L16tX4+OOPEyoA/vjHP8b+/fvxl7/8BcXFxcrxKiwtAN58882YNm0aampqMGrUKEyaNAkrVqzAmjVrIITADTfcAE1rvhTts88+gxACxxxzjJXpZKR0u/AdLp1zJ3Vu4zPocqupsftjalOl3SIbA71X8WeqHREjilf2faIUc1HX0yEMII7O+d7y75CAhp8D/iykv7MLx+CziqXYEzloOmZlTdPNQPhzQIB11wQ38nB81v34ovbnyrEHosuwsf419PdNaX9whopjGCJiArxS7bUEALjlx4hE30FEO7fjefC64Hh8nWA9AXAaYDvPf82aNY39ikeMaL3X8YgRI7B69WqsXr1aOYU5c+Zg2rRpGD16NP7nf/5HOV6VpZuAnHbaabjtttsgpUR5eTleeeUVrF27FkDD8uD777+/WczmzZsblwy3tDyYiNKTz3jV1LioBMoNtTWqJZ6J8Gr5CWTlLIur16AuHjQ9fnigHyYUHm9jRkSUyVxCxwm5w5RiyiLptbKB0k+hezh6uE9OKHZd8HmEDfPL2jNRvXZfgrsCA1nG76DL9lvBEFEyOHV287faq3/u2bOn8c9tzcw7dN/h480IhUK47bbboGka/vGPf3RKr0tLC4AA8MQTT+Avf/kLhg8fDo/Hg4KCAlx11VX4/PPPUVhY2Gz83//+7U5bZ599ttXpEFES6HITXPiq/YEAFoWyEVO8FOXofRJJy3G2hNrffflwWS7n9joiImsUutX6NB2IVWH2/sU2ZUPUYFjgu9DhU44zEMX8mvsQkyEbskoPUuSiRvtLQhOFBAxkx38GyLDleRFRB32zBFgYST6kRUdCj932la229tv2EYFAoNVxh+6rqalR+it48MEHsWHDBnz/+9/HCSecoBSbKMsLgEII/PCHP8SKFSsQDAZx4MAB/Pe//0Xv3r1bHP/jH/8YW7ZswZYtW9C3b1+r0yGiziYlsuK/hYDR7tA6Q8OWmFfp9Dp86OFJ7JN8p4nL9v8OOjKeiOhIx+UMgUuofYL99Na3ETWiNmVEBPi1bjguS30ZMADUG3uwJjjN4ozSS1wbjLC4KKFYHXu/KQLyNQZRShEADAnIJB+GRUdCj528b//KlSvxv//7v+jRowd+//vE+6WqsrQHYCJ69OiR7BSIyEIuLIULG0yN3Rz1Km/+0dt7JtyCO/+a4RFql/hu7nx7EiEix8h1ZeHkvKPxWeVS0zFV0VrMO7Acp3cZZVteRN08x6JbeDTKYkuUY7eH30MP98no5h5lfWJpol67B674UriwTTnWg4XwGc8hpN9kfWJElBgpMPbk3hh7itpGrJ/O345P5++wKanEjT1F/bks+Krt1VLZ2dmNf66vr291N+r6+noAQE5OjqnHNQwDt956K6LRKKZOnYq8vDyTGXdc0guARJRZvPGXTY8tN9QuQR6RhyH+G1VTcqR9kXLMVXgDDgCn54+yJRcicpZru5+NJdXrUGeY70G6qmoTC4Bku5FZd2FO1e2IoU459svahzA293EEdIdOXhBu1GpTkWdcBpHAgmC//CfixlGIalzFQZQqfF4X8vPU2iP4vK6U3D04kefidbf9XvTwvn+7d+9utQC4e3dDIbFnz56mHve5557DggULcMYZZ+DCCy9sstQYACKRCICGnZoP3ef1euF2q22c2RIWAInIMrpcCQ8+MzW2ztCwS3H3366ukdCFJ5HUHOfFvR+i3jDfs2hU9iCU+IpszIiInMKvezEkqw++qllrOmZL7S4bMyJq4NUKcFz2L7CwtvnGhO0xEMFXdX/EaTl/hhCWd1FKC4bWE/XyXmTJ/1OObdgU5GeowiuQGl9vEKWCUCiGyiq1HqehUKxh+WyKSeS5RMKxNu8fMmQIhBCQUmLVqlUYMmRIi+NWrVoFABg2zNxGaFu3bgUAzJ07t81Zg9u3b2+8/5FHHsHdd99t6vxtSagA+NxzzzX++YYbbmjx9kQdfj4iSi+B+GOmev8BwJfhLMQV25Dmu1q+6FJTB6NVWFprbhk2AOTpWbit18X2JUREjqPaUmBNzRYsOLgCR2kl9iRE9I2u7qPR030q9kTnKcdWxzdhZf0TODrrDhsySw9h/RK44kvglZ8ox2qIIte4DdXiOUihtmEQEVlNYu7n2zH38+3JTsQSiTyX7EDbk1Gys7Nx4oknYuHChXj//fdx6aWXNhuzc+dOrF69GgAwceJEpcdPhoQKgDfddBOEEBBCNCnYHbo9UUeej4jShy43wI2VpsbWGRp2xNRm8mnwoMQzLoHMnGdV7WZIheU5ua4sZOncAZiIrHNq/jF4v3yBUsx/ts3Eg31v69BrSSIzjsm6CxVV6xCSB5Rjt0c+QKFrBHp5x9qQWXqo1+6DK/41dFQox+rYj+z4vahx/cuGzIhIhdN/2wqt/e/Atddei4ULF+LFF1/Er3/962ab2/7pT3+ClBLFxcUYP368qcd94IEH8MADD7R5/29+8xv06dOncbagVRKevy6lhGxh6ueh2xM9iCg9+YznTY/dHXMrb/4x0HcF3Fp2+wMJISOiND4i257+TkSkqtTXA8Oz+ivF7Ajuw/r6zJiJQKnNJXw4PvtXCccvq38U1bEtFmaUXqTIRY32V8gEu0m5sQqB+O9TchkhkaNIZx/CxPvR2267Df3790ddXR0uuOACLF++HAAQDAbx8MMP4/HHHwcAPPTQQ8169PXt2xdCCNx0003tPk5nSeiqPW3aNKXbiSizuYwl8MiPTI8vi6tdetzIxUDf5appOVaOK6A0PlfnrspEZL3v9boY92x4FDEZNx2zLbQXR2X1sTErogZ5rn4Y6L0SG8MvKcdKxLCg9peYkPs0XJrXhuxSn6H1R728O6F+gADgk+/AMLohpN9qcWZEZIoEi/AmOld5vV68/fbbmDBhApYvX46RI0ciNzcXdXV1iMcbXt/ceeeduPnmm21O1hoJFQAPLc2YMGFCk9tvvJG7cxI5kV8+a3pHuPK4js0xtR2acly9uSTMJENKfFVtvvE+AJyUN9ymbIjIyfJc2ShyF2B3xPwyyzX1W3FWl5NszIroW4P916A8vgrlMXMtTA4XlTVYUPsLnJLzR2jCmfsqhrUp0ONL4YP5D4EP55fTEDf6I6qlft8sokxk+26+Vpy/o28B28zBXILDhw/HihUr8PDDD2PGjBnYsWMH8vLyMHr0aNxxxx24+OKLO5hk50loCfBNN92Em2++GUuWLGly+y233IJbbrkFS5cutSI3IkoDmrELbrnY9PjlkYDy8t8e7jGqaTnWp5VLsLhmjenxAc2LU/OOsTEjInKyYm83pfFLatZhee1Gm7IhakoIgVFZP4IOtQ8mD6mKb8Dy+r9anFUaEQL1+gOIQW25f2M4gGzj13AZX1ibFxG1SwgBGNLeQ1pw2JiDSgG0qKgIU6dOxYYNGxAKhXDw4EHMmjWrzeLf1q1bIaXEM888o/R388ADD0BKaXn/P6ADPQBb8swzz+DZZ5/F9u3s30LkFH7jCdNj6w2BnYqbf+jwocTDT4bNkFLiw/JFpscLCPyg5FIE9MTe+BARteeM/FHKMTMPqO/OSpQov9YNJ2T/GolOM9kVmY0toRnWJpVOhIZa/WEYSGwzMQGJHOM+6HKdxYkRUdsaCmBOP5wmoQKgy9UwzT0cDluaDBGlF5exCF58Ynp8peFSnv13TNYPufmHSbvCZdgdLjM93ivcOCZ7oI0ZEZHTHZ09EH18PZVi1tZvw75IuU0ZETXXxT0CA7yXJhy/Ovgv7Ak7dxabIUpQoz0OmeDcEoE4cuLfh2ZstjgzImod2ys5sQdiQlfpwsJCAMDatWp9pogos/iMl5XGb4qqNsrWUOw5TTHGuapitUrjQzKi1JyfiEiVJgTuKrlCOW5f+KAN2RC1brD/GhToQxKO/7r+T6hy8M7AcW0o6sWPEo7XEEaucRs0udPCrIioVVYsz037I9l/CZ0voY61xx57LD744AP89a9/xeDBg3HsscfC5/t2Cdn+/fsTXgZcWlqaUBwRdTKjAm7MNz18b8yNrYqbf2RrJapZOZpPU1te7RI6dGs7QRARNVPozoVL6EofOMyrWo5jcgbZmBVRU5pw4aSchzC76laEZYVyvEQc82vuwxk5jyHLpTbrNVOE9UuhxbfCL19LKF5DPXLj30GV9iyAAmuTIyKixAqAN998Mz744AMcPHgQ11xzTZP7pJT4FKYwwwAAriRJREFU3ve+l1AyQgjEYrGEYomoE0mJbOO3ShPH10TV+8yVes9UjnGykBFRGj88qz93VyYi2wkh0NfXExuD5mf2LKhehTNqj8Xw7MQ2FyBKhC48OC775/ii5meQMJTjDYQxv/YnOCP3cXi1fOsTTANB/V64YpvhxtcJxWuoQZ5xExB/E9D5QTCRnZzYA+9wTnz+CU39uOKKK3D77bdDStnkOOTI21UOIkp9LrkIHiw0PT4qgV2Km394RD43/1BwMFqFx3e+ohQzseB4m7IhImpqfMFxyjGzFDY1IrJKgWsIjs36ScLxEVmNedX3ImrUW5hVeqnR/4QYeiccr6EaqLgYRmyPhVkRURMC1uyymwo7BSe6a7AD608JzQAEgMcffxzf/e53MXPmTOzYsQPhcBjPPvsshBAYN24cl/ISZTDV3n+1hqa8+cfRgR9w8w8FH5UvRr1hfmOmE3OHcQMQIuo0J+UOx7sHv8Cu8H7TMUtrNyBkRJTbGxB1VE/PqegbvQBbI+8kFB+UZZhXcy9Oy50Kl0hsd9y0JrJQrf0b+cZl0FCT2ClkNXDgAqDgDQABa/MjIkACQn2is/WSWINz4gzAhAuAADBq1CiMGjWq8etnn30WAHDXXXdh8uTJHUqMiFKTkGVwK8z+kxL4MqReyMtzsfeTWYY08FnlUtPjBQRu6HEel/8SUadxay7c0OMc/GHbc6ZjJCQqozXo4e1iY2ZELRsW+A5qjO04GFueUHydsQtfVP8Mp+b8GZrWobdc6UnLQbX4B/Li34FAKMGT1AAVF0LTnoKh9bUyOyICHDkD7nDScN7zZ/d3IjJPGsiJ/xRCoS/O7rgbew212RtZWi/4BN/wmVUbD6Imbn6pkYRU3jGYiKijunnUm/q/uv8TtoihpBBCx4lZD8CvFSV8jmpjC+bV3Ie4ND9DP5MYoh+qtccgO/CWUyCIXONG6MYyCzMjIgE0zL5z8CFTYQZkJ7O0ADh79mx88sknOPXUU608LRGlCJf8Ei6sVYpZH1Hf/KOPl7PTVAjF5dVERMlQ6MpFT09XpZjFNWuwrn6bTRkRtU3TXBiT/Xu4RFbC56g2NmJ+9c9gSGdudBjXRqBW+78OFQE1RJFr3A53/AsLMyNyNglY338vzQ7dgWuALS0Ajh07FmPHjkWXLpy5Q5SJ/PJ55Zh9ca/S+CytF0q9Zyk/jpN5NQ88wm16vE/zJDQTh4ioI4QQmFiovvnQxxVf2pANkTkBvQinZD+MjrxtqjY2YX71Txw7EzCqjUGddn+HWn0JSGTLe+E11F+LElELZMMsQCcfhuG8KYBcAkxEprjkcrjkV0ox1YaGqOLjDPRdDl2oFQ2dTEqJZ/a8g4g0/50+NW8kvJr5giERkVXG5Y9GseIswNW1W2zKhsicHFcfnJD9K6ADM+6rjE34rPpuxGTQusTSSEQ7F3Xilx0sAgJZxt/hjz9mVVpEjiWR/Bl4yT6cuIaKBUAiap80kBX/HYTCyzZDArOD3ZQfKlvvrRzjZBuCOzCvynyD8oDmxTldxtiYERFR69yaCxd0PU0pps4IojpWZ1NGROYUuY/DiMDtHTpHnbELc6vuRNRw5s9zRD8P9dqdHd700y+nIzt2O+DQGZVEVhBSwJJeekaSDgtyEdJ5JUAWAImoXW65CDp2KMXsintQbcSVYrK13sjTByrFON0nFWqzMm/rdTGKuPyXiJJI9RokATy242VwMxBKtj7eszHEd1OHzhGU+/FJ1a2oj++zJqk0E9auRr34SYeLgB4sRV78amjGHkvyInIaCdkwY6OjR7Jm8FmVi8OwAEhE7fIb/1KO2RRVLzL1813EzT8Ura3bqjTecOAvOiJKLQP8JejmzleK2RDcgXX12+1JiEjBAP8l6OM9v0PniKEWc6vvREVsnUVZpZewPgX12g87XATUsRd5xtXQDbUPQ4mooa+mkM4+0OGrUPphAZCI2uQxZsCFNcpx5UaO0vg8fRB6e85UfhynixhqXRZVegUSEdlBEwJnFZ6kHPdp5dc2ZEOkbrj/NvRxn9ehc8QRwvya+7A/4sziVVi7CnXiFx1++y0QQa5xJ7yxaZbkReQUQoik9+BL/pHsv4XOxwIgEbVOxuE3nlYO2xobgjqjUimmh/sUzv5LQLYeUBpf4FIrzBIR2WFS4Yko8RYpxWwN7rYpGyI1QggMz/oeerhP6eCZJBbX/Qbrg9MtySvdRPQLUKv9xoIiIJCFfyEndiuErLEiNSJnkM4+BAuARETfcsvPoEOtR40hgcUh9abMhe6hyjFOtzW4B+WxKtPju7jzMDhQamNGRETmaELgpNzhSjF7IgexoV6tHy2RXYQQGJ31UxS7x3X4XBtC/8VXtX+AIWMdTyzNRLUzUSP+BGnB21I3ViEvfglcXBJM1C6ZpKJbyh0OwwIgEbVMhhEwHlMO2xYrQUjx09ccvQ8KdBYAVcSlgb/ufAVRaX6jlTMLT4QmeNknotTQz99TabyExFO732YvU0oZQgiMyvoRurvVl7QfaW/0C3xafQcihvNmsMX001Ct/QsG3B0+l4Y65Bh3wh//CyCNjidHlKGkE6tfR3Diywm+EySiFvnk89CxVylGQsMO41jFRxIY6r+Fy38VfV2zDgeilabHj8oejLMT6LlFRGSX4Vn9lTcD2RM5iDV1W+xJiCgBQggcl/Vz9HJP6PC56o09+LjqJhyMrLIgs/QS14aiWnsGBjreqkQA8MuXkR+/CMLY1fHkiDKQkEj6JhzJPjQHVgBZACSi5mQUPuM15bCIHIOymNobswL9KHRzqxYNaUHVSqXxw7L6cfYfEaUUTWi4tEi9aPJ1zXobsiFKnBAaRmbdhRLPpA6fy0AUC+p+jjX1z0I6bAabofVDlf4i4uhhyfk0HES+cQX8sb87c6oPUVsEkPxNOJJ8OHAWJN8NElEzXvk2NFQqx62I9UG9oTZrMN81WPlxCKiK1SqNr4nX2ZQJEVHiTs4bgX5ZvZRiVtZtguSbeUoxQggcE7gT/b1TLDnf5vBr+Lz6x45bEixFIaq0lyDdYyw5n4CEH88jL34JdGOjJeckygzcBRgOfC3BAiARNaHJPfAbf1OOC+E4bAovUo4r9oxVjiHAq3lsHU9E1FmG5PRVGr8nchCzytV/3xDZTQiBoYGbMdT3HUvOV21sxEdVN2BfZLEl50sbmhvIewrwX2nZ/Bwd+5Br3IBA7PeADFl0VqL0JQ7NADSSfHRGka+tx3cYFgCJqAmf8TI0qL0wktCxOX4xItL8jrQAkK8PQb5rkFIMAVJKhIyIUsywrH42ZUNE1DGndDlGOWbmwfmIKWyCRNSZ+vsvwjH+uyw5l0QcX9Y9iEU1v4Uho5acMy0IDVreg0DOVEhY0ydaAPDhHeTHL4A7/qEjZ/8QHSIlAANI+i68RiccrTy2w7osAGABkIgOZ0ThlW8oh4VxNqqMPUoxAjqOzbpH+bEImHlwHjYEd5ge389XjAF+tSV2RESd5Zi8Qegd6K4UUxmrwYpaLuej1NXbNxGnZP8JAi5LzlcW+xKzKq/H/sgSS86XNnznolp7FgZyLTulhnrkyAeQG78WmrHZsvMSpRMBbgIiHFgBZAGQiBoFjL9AQG1mGQDUiPOxPfyBUky2VoKAbk2TZycJxsOYceBz0+PdQsf1Pc6xMSMioo4RQuAnQ26EUJzls7F+p00ZEVmjwD0Ep+c+CjfyLDlfDPVYXPcAvqz5PaKGWi/gdBbXBqJKfxlRjLD0vC5sRZ5xHbJi90HIckvPTUSpzzBYACQih9LlOvigPvsvJC7BuvAS5eW/Ba6hyo9FwMLqVUrLf0/JPRoDAiU2ZkRE1HEDskvQy99NKeaTiq9QGXXWBgmUfnL03hif9wSytVLLzrkvtgAfVd2EHeGPHLMhjhS5qHH9E/W41dJ9OwUALz5HfvwCBGJ/gHDYpivkcMnegCPJh7Cmu0BaYQGQiAAAPuNF5RgDbtTgNuyIfKQcW+rlrLREbA/tUxpfL9VndBIRJcPQHLVepfVGCG8f+MymbIis49aycUbuX9HLPcGycxqIYHn9Y/i0+nbUxMy3BUl3IdfNqNL+DQPZlp63oT/gDOQb58If+xNg1Ft6fqKU1JECWrI3D7HgcGD9jwVAIgKE3A+PVC/iRcTFqDS2IybrlOKKPWOR5+qv/HgEGFCbqu6UmQFElP7O7nGycsy8quUIxsM2ZENkLSEERmXfjWG+7wIWvu2sM3Zhbs0d+Kr2YUQcMnvN0IahSn8NEaF+zWiPgAE/3kSBcRYCsd8CDlpqTc4i0cECWgrM4Ovo4cS9xFgAJHI6aSAn/jMI1cISfAhpV6Isqt6M+pjAncox1CBPV/vEu6e3i02ZEBFZa1B2KY7LGaIUEzIi2BLcbVNGRNbr55+M03KmwoWApefdG52PWVXXYW39c4g7YPa/FDmo1f+MGvErSLgtP7+AAR/eR4FxNrJj90AYByx/DKKkMpD0AlyyD2FpQ4H0wAIgkcO55GK4sFY5rl77PqqMODaH31CK8yAfuvAoPx4BlbFazK38Winm9PxR9iRDRGQxIQS+1+ti5biPKhZbnwyRjfJcAzAp7znk62oF7/ZJbAq/ig8qr8Lm4JswZMzi86eeqH4uKrSZiGKwLecXkPBgAfKNyciN3QDN2GDL4xB1OoGkF+BS4nAYFgCJHC5g/FM5xkA+wuISbA29DQm1udMlvrHKj0cNpu+bhfJYtenxJ+eOQHdPoY0ZERFZy6t5UODKUYr5qmYtVtRutCkjInvomgen5PwRR/muh5VLggFAIoY1oafxQeVV2Bh8FXEjwwuBWjZqXM+gRvsVJHRbHkIAcGEj8o0bkR87G574i4DB9gOUvkSyC4ApsZw42X8LnY8FQCIH8xgfwIU1ynEh7VLEIbErMkcpTkBDX//5yo9HQFWsFouqVpke382dj5uLL7QxIyIie5ySd7RyzKxyzgKk9COEwED/5Tgt+xF4hfUtOwxEsC70HD6suhL/n737jo/sLM/Gfz2nTVVvuyvtavu627sYY+NeABd6MYGYJARIo4T2gzch8BIgIXkpKZBGIBCKSai2MdgYG2xjg7HX9tpr7PX21Wp31eu0U5/fH3NGGo2k3TmzczQq15ePkS1d9zO3RtKcmXtOeTb9Fbje8j402FZuwJjyk1DODVhMwSSS8gto8q5F0nkPVC/4kTRENSdFfgBWq39m9FKbf3gIMBGtHNJE3PunwGUuViMnbkHOG4KLYO98nt/8h0iqnYFvk4DdqQNwA5ynManEEFGqf04cIqKwXd10IdSAT1GfSu3jxUBoyWrQN+Lahi9jjX5FKOt7sHHIuh0/HX8jHp/8O5he+UcTLDVSyZ8bcFz5Ijw0hXpbAh4M7ESD94dodF6KmPNFwBsL9TaJqkV6Hmo7Aaz9PyvwCGAOAIlWqoh3FxSMBa5Liw8AIoLns98KXLux/vrANZSXcXOB8tkVcAJwIlqe2oxG3Nx+beC636YPhtAN0cIQQsX25AdxSfLvoSIWym1IuOhzfoV7x2/BLyfei3HnUCi3sxi4yg6Mqbcjg3cgrMOCiylIIYZb0eTdiAbndYi6XwUk35SgRazWhwAvgn+EDHYRzOWAA0CiFUjIFGLy3wPXuVgHR7kEI86zOGE/GKjWEI1IaO2Bb5PyEmqwFwMJNRpSJ0RE4buo4ezANV89cSfSbjaEbogWTrN+Jl7S+E2sNa4L9XYm3IN4aPLPcffo7+D5zLdge+lQb68mhIac9laMKXfAxOULcrCfAKDiBOLyP9HkXo0G51WIuv8F4Y0uwK0TBVB6Hr6V+M8KxAEg0QoU9/4ZCoIf/pFR/hQQAkdyPwlc2x19KRShBa6jvKAvanfUbQupEyKi8DVpdeiMtAWqSblZ/HLsqZA6Ilo4qtBxXuI9uDT5eUQR7O8gKBcZ7Df/F/eMvwm/HH8vBqydkMvsuDipNCGt/T3Gla/DwbYFO+tXfhg4iLj8Mhq9m9Dg3IC487dQvOexIo89pEVGLI4hYFgXFinrH+4BSETLnJBjMOTdgessvAi2ciUAYNB5MlCtLuqwIfbKwLdJec+nj+DW/nvKzutCwxWN20PsiIgoXEIIXNt0YeC6B0eDbZ+IFrNGfTOuafwSzoj+AbAAh7FOeAfxWPoTuGvstXh08uMYsp9eVsNAT9mMCe2rmFT+CS4W9pzU+WHgOKK4E43eW9HkXoU65w9guD/k3oFUG8vxEODS8/ydsqamP4Ga4O44RCtM3PsCBJzAdVn1XQCAjNsHW04Gqt0SfSOiSrgnYl7O7hx+GDLAFuoPVt+Eei0RYkdEROG7smkH7hvZiWPWYNk1x60hpN0cT4NAy4YQKjbFXosu41o8lfknDDo7Q79NCReDzhMYTD0BAQPN2lnYGnkzmvStEGLp7z/iKC/EuPJd6O6DiMt/gIr+Be9BwIaOvdDlZyDlZyC9BFxsg6ncBFtcBinqFrwnWoEWw4C/li0shu9/gXEASLSCaN5OGPKuwHW2eCFcsQlSutiZ/pvA9Q3alsA1lDdiT2B3an/Z+QY1gcsazw+xIyKihaEJFa9uvxL/0vu9smskJP6193v44LrfhRAixO6IFlZEbcBFdR/DmLMfu1KfQ1oeW5DblbAw7OzCr51dABQ0KFvRHXkZOo0roShL+6WkrV6BcVwB3X0Ycfl5qDhRkz4EAIE0FDwB3XvC33cpChdbYOEKWMp1kKId4GMaVZPEihyAFZMr8BDgpf2oTUSBxLyvIehTBwkDKeVjAPKH/k66R4LdptKOJnVrwFulgn5rONAbYxNuGp70oCyDd+iJiLbG1kKBgBfgkfCZ9EEcyB7D5nhXiJ0R1UajthlXNf4bTlgP45nMf8CSYwt46x7GvT14OrsHT2f/CRHRhDZtO9ZHXol6bf2S3TvQVi/FOC6F6j6LhPw0VBwI/Hy5mvIDwRwU7IaO3Uh4/wIJAQ/tcLEJlnINbHERpGitYZdEy8AKHKpzAEi0QqjeM9DxROC6rLgZUrQAAHrN+wLXd0dughDhn7dmuRIVPQVdeRszIlqeGvU67Kg7AzsnnwtUd//o4xwA0rK22rgUq41LcSh7J/bmvgUHC38VX1OOotf+OXrtnwMQiItVaNHOxdrIS9GgbYAi9AXv6XS46lmYwDcgvH4kvE9Dx2MQi+QkYQISKvqhoh+G9yu/KwUSTXCwDo64ELZ4EVyxDeDzbirXqfYAXA57CJ5kyOe5wU+LtdRxAEi0EsgMkt7HgpdBhancPPXfY+6+QPUJpRMbIrz4x+lo15vy5+gtM7820gFlBb6bRUTL12varsSu1F440i27ZldqHzwp+XhIy96G2MuxPnoTDuZuw/7c/8JBpkadSGTkCWTsEzhq5y9cZqABjdpWrDYuQ4fxIugiXqPegpFKB1LKPwIyh5j3RUTkXVCQrXVbM+Qf2TwIDMPAMAz5JCD/03++qMFFKzx0wcYL4CpnwBVbIdG4Ivd4opNYCYfAnmSIuTT3WT49HAASrQBReRtU9AWuyyp/NnV4wTHrAWS9gUD1Xca1UPguZMU86eHrfXcFeu/56qYXhNYPEVEtdEXbcWnDeXhgrPwr/E66Gfxw8H68rv3qEDsjWhyEENgUew02Rl+Nntxd2GveCktO1LotWBjHgPMYBpzHgAwgoCAmOlCvrUeHfgla9HMQUxbxYawiiqz6QWTlB6DLexHzvl7zw4NPJd+bAw19APpgYCfgz3gkFEhE4KEdHlbBwdlwxXq4Yhs80QEIo3aN04ITwPLYw+80iBUw/yzFASDRciclot43A5e5WIWc8qb8v0sbz2a+HHiNZu3MwDU07dGJZ/Fkam/Z+Q6jGZc2nhdiR0REtbG9bmugASAA3D38a1zfcjESaiykrogWFyEEumM3ojt2I/qtx/Fs5j+QkcHfAA6LhDe1l2Cf/Wv/swI6koirq9CknoFW7QI06tsgZWMtW51JCNjiJbCVlwDeOKLeNxDFbVBqtrdlZQQ8CGSh4AiAIzDwG/9CEIUjTVRIxCBRBxed8NABV2yGJzrhYj080QaISE2/B6oeCVn9AWDY88Ryp+9l9hHk/MLLBQeARMtczPt3KBgLXJdV3jb17332r2DJ8UD1SWUdmrSzAt8uTbtv5LGysyoUfHDtmxFR+O4tES0/5yW3oEmrw6gzWXaNJR38anw3XtJ8UYidES1OHcYL0GF8CWmnD7uzX8SwsxvhvzqvhISNSYy7kxh39+Gw9aP8p8cBTSQQVZuQEF1IKuvQop+DOqUbEaWxdlf5VhqQU96FHN4FxXsOce8/oWMnBJb2ucTy96YLgRSA1PQVkf0BIaY+CAA6JKLwUA+JBnhYBQ/NcMV6SNEAF+sg0QopkoDguGGxEgCkF/ZjwumuX/J3XtFy8xeJFbgHJP8iiZYxVR5AVH4jcJ2LLljiuqn/HrafDrzGmfE/qN2Ts2Ug65rYmz1adt6Fx/ubiJYtVSh4dduV+OqJOwPVPTT2FAeAtKIltFW4uO5TcKWJPZlvoNe6ryYXDKmEI9NIOWmk0It+PIID5nemviagQ0MUUaUVUaUZ9epGxJQ2NKibEVfaoSt1oT8v8pQzkVI+D0gPmtyJmPdf0PAcBOxQb7dW8vemBGBBwIKCCQC9AH6LqS8VDQvz57AWyF+sxAAQgYcEgBg8NEEiAQ8dkCIKF2sgRAwuVkEiAYl6SCQBhXtwhyY/AVz42z3ZzG3Wn2wIA7riJTkAJKLlJOp9I/B5SiSASeXvpnbxd6WJfvvRQGs0qtvQrl8Y8JapWM6zAtdkK6ghIloqrmragZ+NPIpes/zz0R7OncBDY0/hssbzQ+yMaPFTRQRnJ96OsxNvx4C1E/tz38WoG+zq2ouJhJ3/nzeJSe8QBp3H50gpUGFAQxy6kkBUaYUh6pFQumAoSdQpa6ErDYgqTdDFaQwMhQJHXIRJ5SJASujyYRje92HgcQDOoj5nYFjE1EeJ/J6FWQDZuY9KkiUfi79kAV6fijo0whQvham8Bp7gFd6rQQix+HYKXuh+Qt8DcvHhAJBomVLkIRjyZ4HrbFwOT9k49d97sv8d+PDfZh76e9oSahQCIn9+jjLVqUvj6npERJW6qP4s9A4GuyDVbYMP4MUN5/GKwES+duNCtBsXwpMujubuwf7c95DDYK3bCoEHFzm4yMH0RpDyTn1khYAKARUqIlBgQFNiUwNEHUnoShK6qIcu4oiIZqiKhghaoCoRGEoSGuJwxUWwtcuQBqB4xxGVX4MuH4aC0RU5DDwdhUOTFQwjJr+NqPsdZJT3wlReV+POlj7pycU3AFxgK/Hb5wCQaDmSDurcD/vvugWTU3936t9tmcZR897Aa3QaVwWuoZkGrFGoQoEj3bLyW2Jr0aTXhdwVEVFtXd54AW4bfCDQibsH7TH8Nn0Q5yY3hdgZ0dKjCBXdsRvQHbsBpjuGA7kf4pj988Bv/C4nEi4kXHjIH1VhFo6QrPhISeH/fwQKOtCtWlhvpNGuWtAA8H2JYARcJLzPQSIBS7m+1u0saVLK2hwCvIiIFfj9cwBItAzp8gGo6A1clxOvgyOmryLbbz0KF7lAa7Ro56Fe2xD4tmma6Vn4/NFvlz38A8BzXBHRitCs1+Pyxu14YOyJQHX3jTzGASDRSUTURpyVeCvOwlvhyCwOZH+IY9YvkJX9tW5tiZP+/ztwARx0VRzM1gMAVHhoUFysUi20qi6aFRsJJX/sh+oPBqWcPSSc63MrTdz7F1jiWkDotW5lyRLAijwH3gwr8PvnAJBouZE2Et4/Bi7zEEdGefeMz404zwRaQ0DDBYn3B75tmunX489g2C7/3ffLG87HRfU87JqIVoa3rLoev5n4LXKeWXbNk6m9eGpyH86v2xJiZ0TLgyZi2BZ/M7bF3wzby6DP+hUOm3di0jsKuUwvcFELLhSMeApGPB35u1XCgAdFAG2qjXrhQRceNmgmJqWGVjV/30sABgBXTg8KCwrDweU+JFQwDEM+mB8CUkWkAOAtgj3gTvcX9XSGeCtv/scBINFyE/e+AAXDgetM8XpAGFP/PeEcQq/180Br1CndiCrNgW+bZnpw7MlA+WuaXsgrABPRiqErGi5IbsEjE8HepPrJ8K84ACQKSFfiWBu9Dmuj10FKiTF3H46aP8OAtRMmRrAiX0GHRsCCCkjgqKNOffZpKw4PAvXCzV9TV0hs1Ez0ugZ2GGkMuDpaVAdxxcOEq6JTtzHsqWhVXZhSQIOEKgDLEzAUCUsKGEKe9gAxyJAxjIGkJp+BBQ4AKyWkyB8GXGs17EHyIiBEtJQJOYyI/GHgOhetyCpvmfG5fbn/hUT5h6ACQJuxPfBt02x91kig/KA9io1YE1I3RESLz9VNOwIPAPdkjqDPHMaqSEtIXREtb0IINGlb0aRtBRKAKy2M2M/iqHUvRp1nkZPD4ECw+jwoAIAJ6b90l8DjVv7Q159lNTgQSAoPUub36up0LBx1DLwgmsYhO4oNWg5SCGQ8BZt0E/vtCM41sjjkRLBOM5HyVKiQSCoehl0N7ZqDQf/jhKegTnhTrwg0AWQ9gZgikZECCTE9UASmB32F4WJh6GhDwICcMQiclZWAEWBI6MrJaty9K1b+HICL4EIgYe/DcJLvT/IcgES0lMW9f4AIOLQDgJTyUUAkpv47542g334k4CoK1hkvC3zbNJsScEuoCCWkToiIFqdt8W6cEe/GnsyRQHU/Gvol3tH56nCaIlphVGGgzbgAbcYFAABPOph0e3DMvB/DzjNIeUfg8ZDhUDn+cDAl/T0GJbDPiQEAfp2rgweBITc/JNQgcdCOYFKqmPBUHHUimDRU9Dn5PQgjwsOQq+F8kcUTZhyXK5N4yozjTCOHYVeDKjy0KC56bAPnRLLYa8WwPZrBATuCjbqJYVeDITwkhYd+V0O3buOYo2ODYaHf0bBWtzHqqUgoLhQAk56KZtXFkKuhQ3Mw6n8s16ibRpzTjIpJAFgMe8DVsoXF8P0vMP7JEC0TuvcwDBnskF0AcLANrrhwxufGnYOQAS93tjn6BsTVjsC3T7M1aElMupmy893RVSF2Q0S0+Agh8O6uN+Bdez8b6LXDQ+NP4/LG7Tgj0R1ab0QrlSI0NGgb0aBtnPqcI3MYtp9Gn/UIRt3nkfX6p66wS+Hy/DeULX9IaEHAkvl/P+REAQDPWjF4EJjwVFgQiEDiFxkdOSh4KFuHAU+HCuCoY6BbN3HAjkGHh2esGI44BlbbFp6x4mhSHDxrxbBRN3HcU+BCwHCAHtfAas/GXjuGTs3Gc1YMZxpZDLo6DCHhQaDP1dGkujjqGGUPAD0J9Lpt2Fr9u23FEDXf9a/2FsUh0AuMA0Ci5UBKxLx/CbwHtYRARn3PjJNySOnhYO77AVcS2Bp9c8AamsuDY7vQaw6UnT8nsRHtRlOIHRERLU5JLY5NsS7szwa76v3PRh7lAJBogWgiig7jInQYF019zvNcTLgHMeQ8jUH7CWTcEzAxGvjUM3T6SoeEZtGriQEvf27wA04EgMBBOwoXAhF4OOYaiAiJB3L1sKDgcTOBEU+HConjroFuzcQjdhINioNHzCRSnoLnrSgOOxF0ahaetWI418hgtxlDs+rieSuKtMzvjbhKO/Veo4ecCGzUVf8OWWnmHIAt16HYHK+UF8NFUBYYB4BEy4Au74GGw4HrTHEjHDHzvH0n7Icx4v420DpJpYsXoaiCtJvDN07cVXZeEype03ZliB0RES1u1zRdGHgAuHPyOWRcE3E1ElJXRHQyiqKiUdmCRn0LNsdeN/V5TzqYcA5jxHkWWfUwxu3DSNn9cGSGw8Gayj/Hd/2PZmFYKAvP/WX+SsaQ6HXzj6uHnQgkBCxXwIKCuHDxuJVATHj4TS4JDwJ7rChGpQ4Jc2po+MtcHV4aG0eDOv/Pe9DV8GguiXPivKjT6Sr7HHjLYiY4+5sIesTbcsABINESJ+QgEt5nAtdJ6Mgq75z1+cPmjwOvtTby0sA1NNvDY0/BkuWfK+fm9uuwOb42xI6IiBa3i+rPwo+GHsIJayhQ3Tf6foI/7nxNSF0RUSUUoaFR34xGfTOampqgqipc18Xo6Cg86SLjnsCEewRjzh5kZD9Sbi9sbxI20pAo/9xxVG2i5GP+KCOgsGehRMY/R2HhIyAxKnUokDjmRqBA4rATgQBwd6YB50cy2KibUxcXAYCcJ7DPjmK3FYcqGrDKeHH439oydnrnAFwWE8HQrz+yGHEASLTExbyvQEH554sryImbIUXjjM9Z3iRGnWcDrWOIBqw1rg18+zTb06n9gfKO5JNdIlrZdEXDH695NT5++MuB6n41vhvXNb0Qm+JdIXVGRNWkCBVJrQtJrQtrIpfO+rqUEo5MI+MNIOsOYcI7ANMbQ8o9BsubgIVxuDIHDxb3Jlxwc41Z8p/zSj5K5M9V+JiZxJNmHO2qA0NImFKg39WncmfGboEqjIVoftkSkNW7Cm4t5oGlv1aV9LDydgDkAJBoKRPeECLyzsB1LlYhq/zJrM8PO88EXuuc+J9CV5KB62i2rGcGyuc8nkSbiGh9bDXa9SYM2KOB6u4ZeRR/ygEg0bIghIAukmhQkmjQNmIVLjpp3pU2HJlCzh1DWh6HK3NIu8fgyAxy3hBsmYUlJ+BKE67MwoMDDzY8uAAHiAvCgYLj7uwh37boW9Adub4GHS0vUiLEq+CGsW7JxG/emyj/tqVceX/LHAASLVXSQZ33/0FU8NZFRnwQEOqMz9leCrvTXwy8VrN2duAamludGg81T0S0HAkhcG3zhfh2/88C1T028Sx+370RcTUaUmdEtFipQocqmhBRmtCADRWt4UkXHmzYXhqOzMBBGo6Xg4UJeJ4NU44CEDDlCKSUsLwJQHhwCgNFz4QnXHjSyq8lHEjPgxROfs8s4cGTnn+eMg8SEoCc9TGv+KPAcjlEs0ATMazWL0d35MYZV5mmyqmaiqX1e1L9XhP1K++1FAeAREuUIe+ChucD1znYDFu5eNbnj1r3wcZkoLUa1TMQURoC90Cz2Z6DYXu87LwCgQvrzwyxIyKipePqpgtx78hjGLTHyq5x4eFfe7+PD6x7My9kRUSBKUKFAhWaGgXQUut2ypY/7FMgf/yjKBokCki4EFKBFC6EVOEJG0JqkMIBpIoZx0wKOZWFn1Gk5v+3CiEkpJQAFAgh8/XCnVpP+FkFKiQkxIw9vBQAHjTNQGNjA8bGxuG6K29vrTC1r23Fm/7ytTi+rw+KqkBRBYSS/6goChRFgVAEVFWBUBUoisjn/M8rijKjTlWLP5//WKirZBsrPQnP8+C5HjxPQnoeXNfLf97/nOd6kN70v3ueB+nOrCv8+1x11/3eyruYIgeAREuR5yHmBTvfEQBIqEipfw8IZdbXes17A6+3PnpT4Bqa27f770GP2V92/gV1Z6BZrw+xIyKipSOi6Lhl1fX4h6P/E6hud/oADmaP8VyARLRiiKnXAfmjgWaOZlT/ExogAMX/COgnO5Wf/9GYfT0QUZotrKdOf5zVQ1EvM/qlavvDT72p1i3QAuNfE9ESFJX/ChWDgetyeD08sXrW56V0kfKOBlqrST0Ta/TLA/dAs004adw/+kTZ+Ra9Ab+3+sYQOyIiWnrOTW5Gsxb8jZE7hx4KoRsiIiKixYUDQKIlRpX7EJe3Bq6T0GGqvzPn157Lfs0/v0j5NkZfy3fkquRX40/DDXD/70huRb2WCLEjIqKlRxUKrm2+MHDdk6l9OJI9EUJHRERERIsHX70TLTEx998rqksrH4YnOmZ/3j2BQ+btgdYSUNCoba6oD5qtzxoJlB9zUiF1QkS0tF3fcgk69OZANRISXzp+u3+uKiIiIqLliQNAoiVE9x6Gjl8HrnOwDZYy9yGjPebdgdfr0F+EqLJ0Tna82CnznPlk3jz3vCQimpMmVLyh/drAdb3mAPakD1e/ISIiIqJFgq8iiZYKmUbC++uAo6K8rPKH835tyNkVaC0BDVuicx9KTJVpCngxj+7oqpA6ISJa+nbUb0OTVhe47tb+n3EvQCKiRWTcSeFYZgCTTqbWrRAtC7wKMNESEfW+DQXBD/20xBWwxWVzfm3CPYwJ90ig9Tr1K1GvbQjcB81t2B7Hz4Z/U3ZehYLLGy8IryEioiVOFQpe1XYFvnbix4Hqesw+3Dv6GF7SfFFInRERkeU5mHBSGLTGcNTsx6A9hn5zGKPOJCbcNDKOCRsOJGa+IXNGvBvXNb8QF9adCSEq2SWCiDgAJFoCFHkYMfnfges8RJESnwDm2EhKKbEr/Xkg4MU/WvTzAvdB87u17x6Mu+my8y9ruZgXACEiOoWrGnfgF6OP40iuL1DdjwYfwtVNL4Am1JA6IyJavtJuFoPWGAatURzMHceQNYZ+awQTThppLwtburMGe+XakzmCPZkjuKLxArx19SugcAhIFBgHgESLnZRIuh+HgBu41BS/AyjGnF8bcX6LSfdwoPU0xLDKuDhwHzS3EXsCT0zuKTvfHVmFN7RfE2JHRETLgxACr2+/Bp/ruTVQ3bibwv2jj+M67gVIRDSD5TkYscdw3BzG/sxRDNnjOG4OYtLNIOVl4cjgr1Uq8eDYLjRpdXht+9ULcntEywkHgESLnCZ/BQ17A9e5WIWs8pZ5v95n/Srwmusi10MTscB1NLdnUgfgBXgXVEDwAiBERGU6J7EJHUYz+gNeaf27Az/H9rptaNEbQuqMiGjxyXkWhqwxHMwew3FzCIdzJzBiT2LcmYQl7UDPWcN29/AjuL7lEsTVaK1bIVpSVtwAcHx8HN/73vfw6KOPYnh4GJFIBJs2bcKNN96Iiy8OvmdTJpPBb37zG+zatQv79+/HwMAAPM9DU1MTzjjjDNxwww04++yzQ/hOaCUQchxJ7xOB6ySASeXvgXmGdVJ66HceC7RmRDRhW+yWwL3Q/LKeGSifk1ZInRARLT+KEPijNa/Cpw5/NdDL1pxn4bbBB/G2Na8IrTciooUmpcSQPY6eXB96cn04nDuBPnMEE24KWc+q+NDcWjCljUfGn8E1zRfWuhWiJWVFDQB7enrwkY98BOPj4wCAWCyGdDqNXbt2YdeuXXjFK16Bd7zjHYHWfN/73ocTJ05M/bdhGFAUBQMDAxgYGMCDDz6I17zmNXjrW99a1e+FVoa49w9QMBm4zhYvhqdsmffr+3PfQ9brD7Rmu34RFKEH7oXml1TjAfPc+5KIKIjN8bU4P7kFu1L7AtU9NLYLb2i/hudcJaIlxZEuhq1x7M/24miuHweyvRiyxjHhpRfsEN2FcswcrHULREvOihkA2raNT33qUxgfH0d3dzfe//73Y8OGDTBNE7fffju+9a1v4Uc/+hE2bNiA6667rux1XdfF+vXr8dKXvhQveMELsHr1akgpcfz4cXz961/Hr3/9a/zwhz/EqlWrcMMNN4T4HdJyI7zjMOTPAtdJGMgo75v36660cMi8PfC6q4wXBa6hk8t5wfboe2H9WSF1QkS0fL2y7YrAA0APEv/S+z18uPv3eKJ5IlpUpJRIu1kcyp7A85kj2J89igFrDBNOCnYF5wwnopVjxQwAf/rTn6Kvrw+RSAQf+9jH0NbWBgCIRCK4+eabMTIygp/85Cf45je/iauuugqaVt5d8973vhfnnHPOjM8JIdDZ2YkPf/jD+OhHP4rdu3fjhz/8IQeAVD5poc57P0QFu+KnxXvgic55vz5gPwZbBturMK6sQpu2PXAvNL+9mR58s++usvNRxcDljeeH2BER0fK0MboGO+q24YnJ5wPV7ckcwWMTz+JFDTyVCxEtPFd66DdHsCdzGAezx3Eoewwj9gSy0lxCB+uGpyvaXusWiJacFTMAvP/++wEAV1xxxdTwr9jrXvc63HXXXRgZGcHu3buxfXt5w47S4V8xRVFwzTXXYPfu3ejr60MqlUIymayof1pZovJb0NATuM7FKljKq06aGbKfCrzuefH3QAg1cB3N786hh8o+mbIA8I41r0aChwATEQUmhMAfd74G73r+s7ClE6j2tsH7OQAkotAdN4fwfPoIdqcO4IQ1hCF7HJa0a93WohVVDFxcP//rcCKa24oYAGazWezblz/0Y8eOHXNm2tra0NXVhaNHj+Kpp54qewB4KvX19VP/7rrcJZvK4OUQ874ZuEwCSCt/CZxkUDfp9uCodW+gdZNKF1p0bmCracSewNOp/WXnG7V6XFh/RogdEREtb1HFwPUtF+NHQw8FqjtuDeNnI4/iJc0XhdQZEa0kKSeDZzOHsWtyLw5nT2DIHoPJQV9g1zdfjJgaqXUbREvOihgA9vb2Qsr8njbd3d3z5rq7u3H06FEcPXq0arf9zDPPAAAaGxtnDAOJ5iQ9JL0PQSAbuNQUN8FRTn4lrH3Z/4FEsL0fWvTzAvdCJ9dnDQc6dGPMmYAnJc9DRUR0Gq5puhB3Dz0CO+B28Na+e3B+cgvajaaQOiOi5UZKiUPZ49idPoDdqQPot0Yw4aZr3daycGXjdryq7cpat0G0JK2IAeDIyMjUvzc3N8+bK3xtdHS0Krc7NDSEu+++GwBw7bXXQpTx4v2b3/wmbr311nm//qY3vQlvfvObq9LfQlAUZepjUxOfOJ9S7scQkzsDl0noiDT/JSLK/Pdx1hlB3+ivA699TtvNaKrCi57C739DQ8PUQH6lqhNDgfICAk1NjVCEElJHC4uPC1TAxwUCFu4xoQlNeKe8Gf+4f/7nWXPx4OGu8Ufw3q1L5/nXUsXHBCpYSs8Vsq6J5yYO4tfDu7F34giOm0MwA17ojU7trPqNeNWaK3Fx87llva4motlWxAAwl8tN/XskMv+uwoWvZbPB974q5TgOPvvZzyKbzaK9vR2vf/3ry6pLp9MYGBiY9+uZTAaquvTOxSaEWJJ9LyQpPcj0ZyuqVer/CkKffW7LYiPZPZABrwy2qe4GtMa2VtTTfApP6FaytclVEBCQZe4H2J1YA13TQ+5q4fFxgQr4uEDAwjwmvGTNxfjh8V/gSOZEoLpfDD6Gmzovwxn1G0LqjIrxMYEKFttzhUk7jecmDuFXQ0/h+YkeHM8OwOGVd0+boeiIKxEk9QTaIo1ojTShK96O1dFWdMba0BJpQp0er3WbREveihgALjQpJb74xS/i2WefhWEY+OAHP4hEIlFWbSKRQHv7/Fc0isfjS+pcgoqiQAgBKSU8z6t1O4vb5McgvL7AZVK7ADJyM3CS3wtPOnhq+CsBVxa4qPWDVft9E0JAURR4nrei39WXUuKrB28ve/gHAC/ruGRJ/d2fCh8XqICPCwQs/GPC67uuxef2BjvXrgTwN7/9Cv7zwo9CV/j0OSx8TKCCxfBcwfVc7J3swSMju/HYyG8xaI7yfH0BaVARVSOo15NoNurQGWvHmmgr1sXXYE2sBa1GE3R1/sfU4seEpfZceDENrokKVsQzmGg0OvXvpmkiHp/73QPTNAEAsdjpXWnzS1/6En7+859DVVV86EMfwhlnlH/y/ltuuQW33HLLvF8fGhqq2iHKC6GpqQmqqsLzvCXV90JT5TNocL9bUe2EfDfcU9y3R817MWLtDbRuQnRiYiwNoDrnK1FVFU1NTRgfH19yG/Bq2jmxB/cPPl52vsNoxnZj87L6++HjAhXwcYGAhX9MOEfdgDPi3diTORKobsSewHcP3oMbWi4JqTPiYwIVLPTjgpQSx81BPDH5PHal9uG4OYiMZ4Z+u0uZCgURxUCjlkSjVoe1kXZ0RJqxProa7UYz6rRT7LGXA1K5yZPfxhJ+TGhtba11C0SzrIgBYPF5/0ZGRuYdABbOFXg655n4r//6L/z4xz+Goih4//vfj4su4lXj6BSkRML9fxWV5sRr4YozT5k7Yv4k8Nproy+ppCU6hftGHys7qwkVH1j7JkQVI8SOiIhWFkUIvLvrZrxn7+fgItieRd8b+Dm2J7diVaQlpO6IaCG4nodn0gfw6Phv8UzmICacNLxAl2hb/jShIqnG0KAm0BVdhQ69CVsTa7HKaEWDluTF6YiWoBUxAOzq6prahbynpwddXV1z5np6egAAa9eureh2vv71r+O2226DEALvfve7cfnll1fcM60cUflVaNgfuM5FBzLKB06ZM70xjLvB1tdFEmuNawP3RCeX8yw8mz5Udt6RLjQeakZEVHVJLYarml4Q6E0ZIP+4/O+9P8D/3fh2noSeaImQUmLEnsBjk8/hyYk9OJzrQ07yIh0qVESEjlajAR1GMzbFutAZacPaaAcatSQf44iWoRXxyjIWi2HLli3Yu3cvnnjiCbz4xS+elRkaGsLRo0cBAOeff37g27j11lvxve99DwDwJ3/yJ7j2Wg5P6NQU2YeYF/TcfHlZ5c+AMjbMx6z7A699TuzPYCj1FXRFJ5Nxc6cOzVHTojeE0A0R0cr26rYr8Mj4M0h7wS7+dsg8gZ2Te/DC+lPvgU9EC09KiV5zAI+O/xY7J/dgwBqDA6fWbdWEJlTUKTG0GI3ojq7G5lgnuqOr0Wo0IqIsvwvMEdHJrYgBIABcddVV2Lt3Lx588EG88Y1vRFvbzCum/uAHP4CUEs3NzTj33HMDrf29730P//M//wMAeNvb3oYbbrihan3TMiYlEu4nICo43MAWL4AlTj1kzrj92JP978Drt+rBh+B0agk1CgEE+okn1NM7JykREc2tXkvgT7tei8/2fCtw7ZeO3Yb10VVoMyo/bQwRVU9Pth+/Gn8KOyf3YMSeCHx4/1KmQKBOTaBZr8Pm2Fqsi67C1sQ6tGj1vGgREc2wYh4RXvayl+GOO+5AX18fPvnJT+J973sfNmzYANM08aMf/Qg//vGPAeQvwqFpM++Wt7/97RgYGMA111yD9773vTO+dscdd+DrX/86AOD3f//38apXvWpBvh9a+iLyO9CxK3CdhzgmxWcAoZwy22PeDYlgJ8xt0c6HodQF7otOLeVmoQsdVplXkFsfXY0mjT8LIqKwnJvchK2xtdibPRqozpI2/vvET/DB7t8NqTMiOpkBcxQ/H9uJxyf2YNAeg1wB5++LCB0NWhLroh3YGF2DMxMb0BVth8E9+YioTCtmAKjrOv7qr/4KH/nIR3D48GH8+Z//OeLxOHK53NSl5V/+8pfjuuuuC7TuV76SP3xTCIHbb78dt99++7zZv/iLv8CZZ/JwEQIg04h7/1FRaU75PUCJnjqIyg7/XR+5KXANnZrtOfh8z7fLHv4BwEuaL+L5V4iIQnbLquvx8UNfgRdwj6Hd6QN4YuJ57KjfFlJnRFQw6aRx78hO7Jx4DsesgWU97osKA41aHTbHO7E13o1t8XVoNRqhCbXWrRHRErdiBoAAsG7dOnzhC1/A97//fTz66KMYGhpCIpHAxo0bcdNNN+Hiiy8OvKaUcurj2NjYSbOOszLPPUGzJbyPQyD4+eAcrEdOvKmsbM4bRk4OB1q/TduBDv1FgfuiU9s5+Rx6zYGy8xfWnYEXNwQ7HQEREQXXHVuN17Zdie8N/iJw7b8d+wE+Ff1jdBjNIXRGtHKZro0H+x/Bz/sfw/OTR+AEPKJlKdCEilatAWuibbgguRVnxrvRZjTxzV8iCs2KGgACQGNjI972trfhbW97W9k1X/7yl+f92h133FGNtmgFiXh3ICIfDlwnoWJS+QIgTr2bv5Qedqb+JvBtbIi8ik86QnL/6BOB8q9uuxJKGYd5ExHR6bux9VLcN7oTo85koDpL2vjGibvxwe43h9QZ0crxfLoHPxv5DX6bPoiMZ9a6naoRAJJKHB2RZpyd2Ihzk5uxKbaGz/OIaMGtuAEgUU1JBzHv3yoqNcWrIJWWsrJDzlMYd/cHWl9FDI06D2MKS5C9/wCgzxrG2mhHSN0QEVExVSh425pX4LM9twau3Z3ejwdHn8QVTdtD6Ixo+Uo5Gdw18ggeG38W/fZIrdupCgUCzXoDuow2vKD+TJyT3Ihmvb7WbRERAeAAkGhBJdyPQ8F44DoPbcgo7yw7f9S8N/BtdEaugi7igeuoPMv5XDVERMvBucnNuLpxB34xFmyPbQD46ok7sTHWia5oewidES0PnpR4avJ53Df6BPZkDsOWS/v0SCoUNGpJbI2vw/a6bTgvuRkxNVLrtoiI5sUBINECMbyfIYKfB66TACaUzwMiVl5eehh2ng50G5pIYEv0dwL3RuVr0uqQdrNl59dE2kLshoiI5nJzx3V4ZOK3yAY8/NCDxH8cuw1/vfEdUHgqDaIp43YK943uxK/Gn8agPVbrdiqmQEG9FscZsW6cm9yM85KbUafFeeocIlpSOAAkWgieh7j3hYpKbXE1PGVT2fn9ue/AksH2Mlxn3ICo0hS0NSrT06n9OGYOlp3fEluLTg4AiYgWXFyN4o86X41/Ovq/gWt7zD58q+9uvGX1DSF0RrQ0SCmxJ3MEvxjdiacm9yMnrVq3VJGEEsWaSBteWH8mzktuxupIa61bIiI6bRwAEoVNSiS8v4aCocClHhqQVv6i7LztpbA/973At9OmXxC4hspjejb+49gPIcs8CFgAeGXb5eE2RURE89pRtw2XNpyHh8eD7U0PAPeOPoYdddtwdnJjCJ0RLU6W5+DJiedx18ivcTTXv+Su2KtCQYvegPOTW/Ci+rOxKd7JC3QQ0bLEASBRyHT5MCL4WUW1KeWTkCJZdv6YdT88BHunNaF0okU7N2hrVKbfjD+DVIBDf1/XdjXOS24OsSMiIjqVN3Zch50Te2BWsPfSF3q/i09v+jM06XUhdEa0OFieg/tGHsODY0/iuBX8Te5aiokIVkVacEn9Odhetw3tER4FQ0QrAweARGGSDuLeZysqtcUL4YgXBKrptx8LfDvbYm/h+UtC9PjknkB5Q9FD6oSIiMrVoCXx7q7X47NHg18VOOuZ+FzPrfjExj/i+QBpWRm3U7hz6CH8ZuJZjLupWrdTtqQaw+ZoFy5pOBfnJjchoZV3Xm0iouWGA0CisEiJhPtJqBgIXOohgZTySSDAC4dRZw+GnF2BbqdR3YbVxosDdkdBBNn7D0CgC4UQEVF4zq3bjCsbt+OBsScD1x41+/E//ffgzateFkJnRAunJ9ePnw3/Bo9NPIesDHZxnFpJKjGcm9yMSxvOxdmJjVAUHs5LRARwAEgUGk0+UfGhv2nxfyBFfaCaZzNfBso8z1xBu35hoDwFF1eigfIxNVieiIjC8/r2a/DE5POYdDOBa3868husj63Bixt4mg1aWk6YQ/jBwP3YnT4Q+IrYtZBUYjg7sREvbjwP5yU38fx9RETz4ACQKAzSRML7eEWlNs6FrVwVqGbcOYAxd2+gGgEFXZFrA9VQMFJKmJ4dqOb85JaQuiEioqDqtQQ+3P0WfOzgl+AFfJMNAL587HZsja1Fq9FY/eaIquhItg93DD6Ip9P7YUmn1u2cVFyJYHNsLS5vvAAX1G3h6VOIiMrEASBRCBLep6BiOHCdhxhS6mcBoQaqG6jg3H+dxtWIKa2B66h8dwz9Es9nj5SdPzuxAWsi/JkQES0ma6MdeHnrZbhj6JeBa114+PjBL+NvN/8p6rVECN0RVW5f+ijuGvk1np7cB3sRX7nXgIY10XZc1bgdL6w/E0ktXuuWiIiWJA4AiapM9Z5ERN5XUW1GvAdSBLtqoO2lcNj8caAaFTGcE/+TQDUUTNY18ZPhX5WdTyhR/N6qG0PsiIiIKvXK1svx1OReHDH7A9dOehl8rudWfHzD23nRLaq5AXMU/ztwL3an9sOUwY5SWEjtkWZc1f4CXNV6IRIm9/AjIqoGDgCJqkjICdR5f1lRrY0zYSk3Ba7bn/suLDkeqKZZOwuqiAS+LSrfIxPPIOdZZecvbTwfqyItIXZERESV0hUNf7n+rXjvvn+o6Jxoh3Mn8J/H78A71rySQ0BacL25Adw59DB2TjwHG4vz8N6YEsG2+Dpc03Qhzk5uRFtzK1RVheu6GDVHa90eEdGywAEgURUlvL+BgmDDOADwEMWk8s+ACPYn6UoTR63gFxrhuf/C15MLtpfIuJMKqRMiIqqGqGrgbWteiS/2frei+ofHn0KTXoc3tF9T5c6IZhu2xnHH0C/x6MRvkVmEF/IQEGjTG3FF43Zc1ng+mvRgR8AQEVFwHAASVYnm7YQhg58fCACyyh8DSvBzA43ae2DLYIOjmNKOVfqLAt8WBSMDniy+kpPLExHRwnph/Zl4Rctl+NHwQxXV3zn0ENZG2nFxwzlV7owISDlZ3D70AH49/kxFV64OmyE0nJXYgKuaduD85FYo3BuWiGhBcQBIVAWK7Eed938qqrVxFkzxusB1UkocML8fuO7CxEegCJ5LJWzNWrB3stcYPPyXiGgpeH3HNXg2cwgHsscqqv/3Yz9AVDFwQd3WKndGK1HWzeEXo0/g7uFHMO4uvqMJGtUkLqo/C9e3XIIWo6HW7RARrWgcABJVQdz9ewgEf6dVIopJ5QuBD/0FgH77EQw5uwLV6GhAvbYh8G1RMCk3i4fGd5edFwAub7wgtH6IiKi63rP2jfjIgX9Dys0GrpUA/vnod/CRDW/Fplhn9ZujZc+THn45tgs/HfkNjpmDtW5nlu7oKlzVuANXNG2HJtRat0NERD4OAIlOk+7dCx2PVFSbVd4OKLGKag+bdwau6YxcUdFtUTD/2/8z9FvDZecvaTgPbUZTiB0REVE1NWpJfGT9H+AjB/69olM4uPDwt4e/hr/e8A50RdtD6JCWGyklnpzcizuHHsLB3LFFdeIQDQo2xbvwipbLcVZyA1Sh1LolIiKaAweARKdBlQeR9D6JSs5gYuMC5MSbKrpdy5vEsFP+HmZ5At2RGyq6PSpfysng1wH2/ltlNOOtq4Nf/ZmIiGprTaQNb139cnzlxI8qqneki08c+i98YuM7eBV4mtdxcwjf7vspnk0fhgO31u1MiQgd5yQ24mUtF2NrfB2vbk1EtARwAEh0GuLuZyBgB67LX/X3c0CFT5Z6rZ8HrtkceQOSaldFt0fleyq1H7Ys/wl6UonDUHhORiKipeiKpu3oNQfw05HfVFRvSgsfO/glfHLTH6PDaK5yd7RU9VujuGvoYTw89jQsOLVuZ0pURPDC+jNxfcsl6Iq21bodIiIKiANAogpF3W9Bw1MV1WaVd1Z86G/GHcCe7H8HrlsffUVFt0fBBL3qXtoLfv4oIiJaPH6n46U4lhvEM5mDFdWb0sZfHfgPfHLjH3FPwBXM8hzcNfQr/GLscYw6k7VuZ0q9msCFdWfgtW1XoU5P1LodIiI6DRwAElVAlc8iJv+1okN/LXEZTCX4VX8Leqy7IAO+G9ygbkZE4ZXXFkJMiYSaJyKixUURAu9ZdzM+dvA/0Rfg/K/FLGnjIwf+Df9349uxLrqqyh3SYuVKDw+OPomfjjyCExX+7oQhqcRxacN5eFnLi3jlXiKiZYQDQKKgpIeE+ymICk6/LBFFWvnYad18r/mLwDXdEZ5jbqEEvdrdeXVbQuqEiIgWSkQx8JHuP8BfHPhXpCrcs9uBh48f/DLev+5NOCe5qcod0mJyMHsMt564BwdyvRVdRCYMSSWGSxrOwctbL0OjXlfrdoiIKAQcABIFFHc/Aw2HA9dJACnlryBFsuLbnnR7YMqRQDUN6mZ0GldVfJtUvp5cH756ovyrM6tQcFXjjhA7IiKihVKvJ/DRDX+Ijx78EiwZ/PzAQP7qwJ/p+Rbe3fUGXFh/ZpU7pFo6nD2BO4cexhOTe+DCq3U7AIA6NY4X1Z+N17ZdhYRW2alpiIho6eAAkCgAzXsCUdxeUa0lboKtXFPxbXvSwc7UpwLXbY2+CUrAvdKoMncM/hK2LP/w7Deteima+C47EdGysSrSgv/T/Rb8zeGvndaQ5wu938XLWy7F69uv4dVVl7CMk8MPBu/HryZ2I+0ujnP+RoWOixvOxfUtF2N1pLXW7RAR0QLiAJCoTEJOIul9pKJaD3XIKO8+rdvvtx9FxusLVKMiiib97NO6XSrPuJPC45N7ys43a/V4SfNFIXZERES1sCnehQ+sezM+0/MtyNM4vPPO4YfRb43gz7peB0UoVeyQwpRzTdw19GvcP/YkxtzFcTGPiNBxfnIL3tBxLdqNplq3Q0RENcIBIFE5pETS+ysoGA9eCoGU8llIUX9aLfSa9wau6TSugi7ip3W7VJ7j5mCg8/iMOZOQUnLPDiKiZejs5Eb8aedr8a/Hvn9a6zw2+Rw+tP+L+PiGtyOpcXu+WLmeh0cnfovbBh9En704LuahQcWZifV4TftV2Bhdw+cbRETEASBROXT5U+jysYpqc+KNcJRzT+v2bZnGsLM7UI0m4tgSe9Np3S6Vz5PB9vKQ/n4hfDpORLQ8vaghvwf+6Q4BB+0xvG/vP+J9696Es5IbqtEaVYGUEo9OPIt7hn+D/bneWrcDABAQ2BJbixtbL8EFya0c+hER0QwcABKdgioPIul9uqJaFx3IKX942j08nf4CXJiBatYbNyGq8DCPhdJuNAfKrzJaoPCJORHRsvaihrPhSAdfOl7Z+YMLLDj4+55v4Prmi/HGjut4SHCNSCmxJ30Etw09gH2Zo4vmYh5rjFa8tu0q7Kg7A6rC3w0iIpobB4BEJyMlku5HIBD8an4SGiaVfzmtq/4CQNo9gT77V4HrOoyLT+t2qXxSStw1HOxndEXj9pC6ISKixeTSxvOhQsW/Hf/Baa9198gjeCq1Dx9a9xY0G6d3ahEq3+HsCXy//+d4NnMYDtxatwMgfy7hqxp34PqWixFRjVq3Q0RESwAHgEQnEfX+FSqOVFSbFW+Dp6w57R56zfsC1zSom9GobTnt26byPJ3aj/tGd5adb9CSuKKJA0AiopXi4sZzYCg6/rn3O6d1YRAAOGEN4/37/xFv7ngZXtryoip1SKWeTx/BXcOPYHdq/6IZ+iWUGC5vPB+vbL0CCS1a63aIiGiJ4QCQaB669wDi8lsV1TrYhpzyu6fdg5QejtsPBKwSODN2+ocdU/nuHS3//JAKFLx/7ZuQVGMhdkRERIvNjvpt+MC6N+PzPbcGumjUXCSAb/X/FHcPP4K/WP97aOOVXU+blBIHs8dw2+AD2JM5Aks6tW4JQP5iHjvqz8DLWy5Fd2xVrdshIqIljANAorl4NhIVnvfPQxwTyr8C4vT/vA7kvo+M1x+oplU7Hy36Oad921Qe07OwO7W/7LwHDw3a6R0WTkRES9O5yU346w3vwCcP/1dVBkzDzjg+uP8LuLj+HLxjzauh8fxvgUgp8Wz6EH409DD2Zo4smnP6KVCwOdqJN696GTbET/9oEiIiIoADQKLZpIs678+hYKKi8qzyHkA5/b27XGnhkBn8pOGrjUtP+7apfGk3F3g/jrSbRZNeF0o/RES0uK2LrcLfbPwTfOrwVzHupquy5iMTz2Dn5HN4XdvVuLH1xVVZc7myPQcPjj2JB0afxBGzr9btzLDGaMVLW16EKxq3Q+WFXoiIqMo4ACQqEfH+Bzp2VVRr4jqYyiur0seA/RgsGWwIqSGONcYVVbl9Kk9MiQSvUYPXEBHR8tEeacanN78Tnz78NRw1B6qypiNd/O/Avbhj6Jd4U8dLcEXjdghebR4A0G+O4P7RJ/Cr8acx5qZq3c4MTVodrmt+IV7WfDF0hS/NiIgoPNzKEBVRvB7E5b9XVOuiGWn1/1atl6PmvYFrtsbeBE3w3HILKePlYAit7EO5uiLtaNZ45UYiopUuoUbxyY1/jC8fvwMPjT9VtXWznon/OnEnbu2/B29ovxbXNF0IZYUNAi3PwVOTe3Hf6E4czB6HKa1atzRDROi4tOE83Nh6KdqMxlq3Q0REKwQHgEQ+ISdQ570LooIrvUkIpJW/BoRalV76rccw6DweqCYqWrA+Up29D6k8tufg8z3fDnQep+uaX8g9MoiICAAghMA7Ol+FtZF2/M/Az07z0iAz5TwL3+i7C7f2/RSXNpyH17ZfhSZ9eb4BJaXE/uwxPDS6C0+mnq/aodXVpAsVZyc24nc7rkd7hBdtISKihccBIJEv7n4eKoYqqs2IP4GjvKBqvRzIfTdwTYfxIg6WFthjk8+hN8ChW+cmNuHyxgvCa4iIiJak61svwVmJDfjbw19Dtsp7q7nw8OD4Ljw4vgsdejOub7kYVzXtgLLEzzF3OHscD489jZ2TezDmTJ72lZXDICCwOdaJm1ouxQV1W/k8jYiIaooDQCIAhnsXDNxTUa2DLTCV361aLym3F6PunsB16yLXV60HKs/9o8H20ry5/VpoVdpLlIiIlpd1sVX44rYP4rM9t+K5zOFQbqPfHsF/9/0E/933E6wxWnFV0w5c2bQDUcUI5faqZcyexLPpQ9g58Rz2ZY9hYpGdx6/U2kg7bmx5MS5uOHfFHX5NRESLFweAtOIpXi8S8m9QydMziRgm1c8AVXwX/Zj5i8A1ncZVqFfXV60HKk+vORgo32+PYl1sVUjdEBHRUqcpGj7c/RbcO/oYbu37aah7tR23hnBr/z24tf8exJQIzkpswCX15+CCuq01uxiFK10czwzg4aFd2JM6hL3Zoxh30nArOD3LQmvW6nFDyyW4vHE7YuriHqgSEdHKxAEgrWzSQtL7IAS8ispTyschRXvV2pl0j+KA+cOAVQrOjb+raj1QAHLxHW5ERERLmxACL2m+CBckt+Cfjn4HR83+0G8z65l4fHIPHp/MH4GgQkGz3oDuaAe2xbuxMboGq6KtSKqnf6GxnGdhxBpHT64fveYADuWOY9AaxYg9CRvln1N3MWjW6vHihnPxirbLF/1elERERBwA0oqW8P4OGnoqqjXFS2GLy6raz6Hc7ZABn/w2qWdCFXzSWQv1WhJpK1d2vjPSGmI3RES0nLQZTfjUpj/GXUO/xncG7oNX4ZuVlXDhYdAexaA9ip2TM09LokDAUAxEhAZD0RFRDGhChQYV0t9j0ZEubM+BKe2pj450l8SefKdSryZwZeN2vKzlYtRp8Vq3Q0REVDYOAGnF0r0HEZF3V1TrYi3Syl8BVTyviytNHLPuD1zXHeW5/2rhN+O/xQmr/IvGbI2txZpIW4gdERHRcnRD6yW4smk7PnvkWziQO1brduBBIueZyMHEMpjnlSWpxnFZw3m4vuUSNOl1tW6HiIioIhwA0oqkyMNIeh+rqFZCIKV+ChDV/fMZsJ+Ah2BX/ksq67Baf3FV+6BTy7om/uvEj8rOCwCvbLs8vIaIiGhZi6tRfGzj2/B8+gj++eh3kPKytW5p2WvR6nFxw7l4RetliKmRWrdDRER02jgApJVHStS5H4IIOGwDAAkgLT4EV2ypaku2l8Lu9BcD152feC8UoVe1Fzq1h8efRs4r//fn1W1X4tzk5hA7IiKilWBbohtf3PZB/GL0cdza91PYK2UXvAXSpjfimsYLcUXTdiS10z/fIRER0WLCASCtOHHv01DRW1GtjStgqa+qckfAUete2JgMVGOgAQ3qhqr3Qqe2a3JvoDxPDE5ERNUihMA1zfkh1Y+HHsYdgw/CWcDzAy4nKhSsjXbg6qYX4MUN58JQ+KYqEREtXxwA0opieHciKu+sqNZDI9Lqh6rcUV6PGfxchOuiL4MQagjd0KlkvPIv/AEAGdcMqRMiIlqpNKHiVW1X4OWtl+HOoYfx46GHYEq71m0telFh4Ly6zbi26YU4I9Fd63aIiIgWDAeAtGIIbxgJ77MV1UoomFD+DVI0V7krIOP2Ie0dD1SjiyTWR26qei9UnoQa7LCgZMA8ERFRuVSh4FVtl+OVrZfhwbEncfvggxh2Jmrd1qIhINAVacNF9WfjJc0X8Xx+RES0YnEASCuCkCnUe++o6Lx/AJAVb4OnVP9dYildPJb6VOC6bdG3IKI0Vb0fOjXLczBkjZWdFwC2120NrR8iIiIgf2jwlU07cGXTDhzOnsAPBx/AU6m9kLVurAYa1STOS27GS5tfhLWxjlq3Q0REtChwAEgrQtz7f1DRV1GtjR3IKb9f5Y7yBuzHkfJ6AlYJdBgXh9IPndo3++7GcWuo7PwFya1oMzisJSKihbM+thrvW/c78DwPu1L78P3BX+CYOQi5DMeBAkCdmsC5yU24vOECnJHohhCi1m0REREtOhwA0rJnuHfCkPdWVOuhAZPKPwBCqXJXeT3mTwPXrNIvQZR7/9XEmD2Jh8Z2lZ1vUJP4vdU3htcQERHRSSiKgh3127Cjfhsc6eLXY7vx4NguHMj2wl2iFw4xoKPFqMf25DZcWH8GNsY6OfAjIiIqAweAtKyp3vNIyE+jkqeFEkBK+SQQ0hXhTG8cQ86uQDUCGrZE3xhKP3RqD48/HegF0wvrz0SzXh9iR0REROXRhIrLmy7A5U0XAAAGzFE8OL4LT0w8h35rFA7c2jY4h4gw0GY0YGtsHc5LbsHWxNrA5+ElIiKiPA4AafmSGSS9/w+iwsNdMsp74CgXVrmpaU+l/xEegl2tb63xEtRrG0LqiE6l3xoNlJ9w0yF1QkREdHraI014ffvVeH371QCAMSeFvekePDn5PHpzAxiwR2FKK/SDhlUoSKgxNGpJbIx14qyWTehWOtCi1kNX+FKFiIioWrhVpeVJeqhzPwwV5Z+rrZiNHTBFeHvaTbo9GHQeD1zXGbmq+s1Q2dSAh4IrCOfQcSIiompr1JK4qOEsXNRw1ozPTzhpDFljOG4Oos8exZA1ikk3g5SbheXasODA9VxIISFl/px8CgQ0RYMOFVEtgriIolGvQ70WR2ekHS16PdqNZjRpdTMO31VVFU1NTRgdHYXrLr49EomIiJYyDgBpWYrKr0NH8AEbAHhoQkr9WyDE88kcNX8WuKZOXY8m9YwQuqFyxRQjUH59bHVInRARES2Mei2Bei2BjfHOWrdCREREp4G7p9Cyo3m/Qcz7z4pqJQQmlH+AFOGdt82RGfRaPw9cd0bs93mS6xo6kj2Be4YfLTuvCxWXNZwfYkdERERERERE5eEAkJYXbwJ13l9Uft4/8S54ytYqNzXTc5mvwpaTgWqa1XPRrr8gpI6oHN/u/xlsOGXnb2h5Meq0eIgdEREREREREZWHA0BaPqSFeu/PIJCrqNwUV8BU31TlpmayvAn0Wr8IXLc2cm0I3VC5jpuDeC5zuOz8ukgHXtN2VWj9EBEREREREQXBASAtG3Hv76HhYEW1HlqQUf6yyh3NdsJ6GB6sQDW6qMNq47KQOqJy7EkfCZRXhAKFh2sTERERERHRIsEBIC0LuvszRORdFdVK6JhQ/iXU8/4BgCstHDC/H7juzNgfQBXBLj5B1WXJ8g/9BQDLs0PqhIiIiIiIiCg4DgBpydPkbiTlX6PS/a3S4gPwlHVV7WkuB3M/QNYbCFQTV1ZhbeQlIXVE5WrQEoHyjXpdSJ0QERERERERBccBIC1t0kLS/T8Q8CoqN8WNsJRXVLmp2Tzp4Ih5d+C6TuOq6jdDgXhS4omJ5wPVvLjh3JC6ISIiIiIiIgqOA0BauqSNOvedUDBaUbmDjUgrHwEW4Fxtw85umHIkUI2AgnWRl4XUEZXrgbEn8Ojks2XnG7UkXlR/dogdEREREREREQXDASAtWXHvC9Dx24pqJSJIqX+7IMM/Tzp4LvO1wHVbo7+LqNJS/YaobFJK/HT4N2XnVSh4T9fNMBQ9xK6IiIiIiIiIguEAkJYk3b0fEfm9imolBCaUf4Inwj/vHwD0Wj/HpHcoUI2KCDZFXx9SR1Suo2Y/TlhDZeejSgSb4l0hdkREREREREQUHAeAtOSo3n4k5UcrvuhHDm+Bq5xX1Z7mI6XEEfPHgetWG5dBLMDeiXRy404qUD7tZeFJGVI3RERERERERJXhAJCWFCFTqPPeDwG3onoLFyKr/lGVu5pf1uvHhBts7z8AWB+5KYRuKKiIYgTKG0KHwsEtERERERERLTIcANLSIV0k3Q9CQfmHZBZz0YSU8jlALMyvvZQensr8c+C6tcZL0aBtDqEjCsr1gl1d+qzEhpA6ISIiIiIiIqqcVusGiMoV8/4VOp6uqFZCQ0r9B0As3MUZBpzHMeI8E7jujNgfVL8ZCmzEnsAXjn03UM21zReG1A0RERERERFR5bgHIC0Jhnc3YvLbFdenlP8LV2ytYkendiT3k8A1rdp2GEoyhG4oqHtHHkXazZadv6j+LJyb2BRiR0RERERERESV4QCQFj3F60HC+5uK63PitbCVa6vY0ak5Moch58nAdTz33+LgSQ8Pju0qO69A4A9Wv5wXbiEiIiIiIqJFiQNAWtSEHEG99ycVX/TDxrnIKO+vclentiv9eUgEO39cm3Yh2vUXhtQRBTHhpDHpZsrOe5CYCHjFYCIiIiIiIqKFwgEgLWp17gegYKyiWg/1SKmfXrCLfhSMOfvQbz8SuG5r9He5BxkRERERERERVR0HgLQ4SYm483fQ8Hxl5dAwqX4RUjRXubFTO2L+OHBNndqNBm1jCN1QJeJqFLoo/xpJUcVAs94QYkdEREREREREleMAkBaliPddRHFHxfVp8UG4YnMVOyqPIzM4Yf0qcN2GyKu4998iIaXE1078GLZ0yq55ccN5iCgLd4VpIiIiIiIioiA4AKRFR/WeRVz+c8X1OfEaWOorq9hR+Z5O/wtc5ALVNKrb0GUs7EVKaH57Mz14ePzpsvNRxcD1LReH2BERERERERHR6eEAkBYVRfaiznsXRMALaBTYOAsZ5YNV7qo8GbcPJ+yHAtdtiryOe/8tIveN7gyU/+M1r0aHsfCHmhMRERERERGViwNAWjykjTr3/VAC7kFXkL/ox98BNRqmHTHvBiAD1UREM9qNC8NpiCqyJ304UF5Z4IvMEBEREREREQXFV660OEgXSfdDUNFbWTk0jCtfhhStVW6sPLaXQo/108B1m6KvhRLgYhMUPlPawfJesDwRERERERHRQuMAkBaFmPdvMPCbiuvTyl9CKl1V7CiYZ7NfgSPTgWqSyjqsj7wipI6oUgklGijfpNeF1AkRERERERFRdXAASDVnuPcgKm+tuD4rfheWcn0VOwrG9MZw3HogcN36yE08998i81z6EEadybLzrXojNsdqN3gmIiIiIiIiKgcHgFRTqrcXCfnXqHQMZmEHsuo7q9pTUEet++DBCVSjIYbOyJUhdUSVsDwb/9r7A3gBzuP4kuYX8hyAREREREREtOjxlSvVjJADqPPeDRHwwhkFLjqQVj9d5a6CMb1xHMx9P3Dd5tjvQBPxEDqiSj068Swm3PIP4z4/uQUvbX5RiB0RERERERERVQcHgFQb0kW9+y4oKP9wyxnl0DGh/BukqO351/blvg1bpgLVREUbNkZeHU5DVLHHJp4NlD87sZF7/xEREREREdGSwMuPLjGqqta6hYpN9S49xO3/cxpX/AUy+mehKJ3Va64CjpdBr/mLwHXrY9dD01ben17h579Yf4cn3WygfFaai/Z7WUp4H65si/1xgRYefxdWNj4m0Fz4+7By8TGBqLpW3hRiiWtqaqp1CxVRVXWqd2/i/wHWwxWvJZL/H+qSN1SrtYo9P/YAXAQbGinQcF7HGxHTlubPsRrq6+tr3cKckpE4gvw4m5ONS/bvcbEoflyglW2xPi7QwuJjAhXwMYEK+LhAAB8TiKqFA8AlZnR0tNYtBFJfXw9VVeG6LiYmJqC59yLufLnyi34o1yNrvQ6o8f2Q80awc+RfAtedmXgrcpMCOSytn2M1qKqK+vp6TExMwHXdWrczQ9Y10ZvuD1SzRe1ccn+Pi0Xp4wKtXIv5cYEWDh8TqICPCVTAxwUClvZjAgfXtBhxALjELLUHvmLCeRJx96MVD/8cbENKfATwvKr2VYkDmdvgoPwLRgCALhJYb7xiSf8Mq8F13UV3H3yl9w4M2+Nl58+Mr8dqvWXRfR9LEe9DAhbn4wLVBn8PCOBjAs3E3wXiYwJRdfAM9rQw3GEk3fdDoLLhnYcGTKqfBUTtz//gSQdHrLsD1601XhZCN3S6Bq0x/GbimbLzUcXA762u/SHoREREREREROXiAJBCJ70JYOyNUJCprB46JpQvQYqWKndWmePWL+HIYHv/CajojlwfUkd0On41/jRkgPyFdWdiTaQttH6IiIiIiIiIqo2HAFO4pIQc+xMI71jFS6TEx+Epa6vYVOVMbxTPZP4tcN222O8hrq4KoSM6XUMBDv0FAFPaIXVCREREREREFA4OACk8UgKpTwD2zsrKAWTEn8FWr65uX6ehx7wHLnKBahToWB95eUgd0enSAh5WHjRPREREREREVGs8BJhCE5G3QuT+p+J6C1fDVG+pYken77D548A1Xca1UIUeQjdUDSkn2KHpm2KdIXVCREREREREFA4OACkUuvdrxL1/rbjewRak1Y9VsaPT12v+HJYcC1QjoGFD9JXhNESn7Vfju/Ho5LNl5w2h49KG80LsiIiIiIiIiKj6OACkqlO8Q0h6H4IIdGmFaR7qMaH8ByAiVe6scpY3gd2Z4APNLdGbkVS7QuiITpcnJW4bfCBQzWvarkRcjYbUEREREREREVE4eA5AqiohB1Hv/RkE3IrqJXRMql8ExOIashy17oUHK1CNgIbuyE0hdUSna0/mMPqtkbLznUYbbmi5JMSOiIiIiIiIiMLBPQCpeqSHOvfDUBDsqqpT5QAmlc/AFZur29dpklLicO5HgevWGJfDUOpC6IiqoTc3ECgvhIAQIqRuiIiIiIiIiMLDASBVjS5/Aw17Kq7PKH8OR7moih1Vx4Hcd5GTw4FqFBjYEn1jSB0REREREREREZWPA0CqmogMvpdcQU7cBFNZfAMz20thX+47ges2RF6FhLomhI6oagLuzdcZaQupESIiIiIiIqJwcQBIVaPIIxXV2TgfGeXDVe6mOo5a9wU+9x+gYH2U5/5bzPqtEfyg/xeBaq5q2hFSN0RERERERETh4gCQqij4r5OL1ZhUPw+IxXc9GldaOJD7fuC6NfqliCrNIXRE1XL74IPISrPs/NbYWpwZXx9eQ0REREREREQh4gCQqsYVWwLlPcT8K/7GQuro9Dyf/TosORaoRkUUZ8bfHk5DVBUpN4tHJ35bdj4idLxn7Rt5ARAiIiIiIiJasjgApKoxlVeXnZVQMan8GzyxOryGToMt0+gx7wlc1x25AVGlKYSOqFqO5vpgS7fsvCNdJNXFOaQmIiIiIiIiKgcHgFQ1Ds6FJS4pK5sSH4WrbA25o8r15H4KF7mAVQrWR18eSj9UPU6A4R8AePBC6oSIiIiIiIhoYXAASNUjBFLKJ2Bj+7wRCYG08gHY6ksXsLFgTG8U+83vBq7rNK5ETOGVYhe7eMC9+Vr1Rh7+S0REREREREva4rvyAi1tIoFJ9Z9gyJ8h6v0AGvLnWpOIwhLXIqe8Hq7YVuMmT25v9ttwZDpQjYY4zo3/WUgdUbVYnoNvnrgrUM3ljReE0wwRERERERHRAuEAkKpPaLDEDbCUG9DUGIOiWJBeHOmxyVp3dkq2zKDX+nngunWRl0EVkRA6omr65diTOJg7XnY+pkRwZdOOEDsiIiIiIiIiCh8HgBQuEYVQEkDA867VyuHcj+DBClgl0B25MZR+qHqklLhvdGegmnd1vQGNWjKkjoiIiIiIiIgWBs8BSORLub3Yl/vfwHWbIq9FXO0IoSOqppSbxTFzMFBNh8ErOhMREREREdHSxwEgke9g7jZIOIFqNMSwLfaWkDqiarKkHbjG9ILXEBERERERES02HAASAXC8XEXn/uuO3ggh+Ge0FCSUKATKv5qvANCo14XXEBEREREREdEC4eSCCMBz2a8G3vtPQMM644aQOqJq+5+BeyEhy86fl9yCpBoLsSMiIiIiIiKihcEBIK14485+9Fh3Ba47M/ZWxNX2EDqiatuf6cUvRh8PVPOy5heF1A0RERERERHRwuIAkFa8Q+adgWs0xLGeV/5dMoJe/fflLZfh7OTGkLohIiIiIiIiWlgcANKKZss0jlsPBK7rjt4EIdQQOqIw/DZ9MFB+a3xtSJ0QERERERERLTwOAGnFklLiydT/g4QbqE4TCayPvDykrigMpmcFy1dwxWAiIiIiIiKixYoDQFqxRt3nMOg8GbjurNjbEFWaQuiIwqILLVC+Xk2E1AkRERERERHRwuMAkFasA9nvB64x0IhO46rqN0OhuW9kJybdTNn5Zq0eW3gIMBERERERES0jHADSijTuHMCAE+zCEACwPnojlIB7k1HtTDoZfLv/p4Fqrmt+IVTBh0YiIiIiIiJaPvgql1YcKT08mf4cABmoLibasDH6mnCaolA8OPYkbFn+OR63xdfh+pZLQuyIiIiIiIiIaOFxAEgrzrDzNNJeb+C6M+NvgyoiIXREYXkm4NV/z0tu4d5/REREREREtOzwlS6tOHuyXw9cE1PasEp/UQjdUJhyrhkob3u8+i8REREREREtPxwA0orSY96DcXd/4LrN0TdACDWEjihMwQ7yBuo1Xv2XiIiIiIiIlh8OAGnF8KSLfdlvB65rUDdjrfGyEDqiMD2d2o/DueNl51UoeEH9mSF2RERERERERFQbHADSinHCegg5ORy47ozY70EIEUJHFBZPevjaiR8H2gPwooaz0aglQ+uJiIiIiIiIqFY4AKQVwZEZPJf9r8B1CaUTLdp5IXREYdqV2odhe7zsfJNWh1tWXR9iR0RERERERES1wwEgrQj7st+BKUcDVgmcn/hzCF4Vdsn5bSrY1X+3xbuRVGMhdUNERERERERUW5xs0LLnShM95t2B69q0F6BJOyOEjihspgx2NV8XXkidEBEREREREdUeB4C07B3M3QYHmcB1W2I3h9ANLQTbCzYA5Ln/iIiIiIiIaDnjAJCWtUm3B/ty/xu4rlW7AI3qthA6orAdzB7Dzok9gWpeVH92SN0QERERERER1R4HgLSsHcrdDgknUI2Ahh2JD/HKv0vUt/t/Bgdu2fkN0TXYHOsKsSMiIiIiIiKi2uIAkJYt20uh17ovcF2XcR10hYeELkW9uQHszfSUnTeEjj/tei2HvURERERERLSscQBIy5KUErvSn4cMfHEHgQ3Rl4fSE4Xv+cyRQPl2vQkdRnNI3RAREREREREtDhwA0rI05OzCgLMzcN2myOtQp64LoSNaCJYMdri3FDKkToiIiIiIiIgWDw4AaVk6kPtB4BoNMWyL3RJCN7RQcq4ZKN+k1YXUCREREREREdHiwQEgLTvjzn4MO08FrlsffSWE4J/EUnXcHMJdw78OVPPihvNC6oaIiIiIiIho8eC0g5YVV1p4bPJvAtfpIon1kRtD6IgWyu2DD8KUdtn5Zq0eL6w/K8SOiIiIiIiIiBYHDgBpWTlhPQwTw4Hrzon9KSJKUwgd0UKYcNJ4bOLZsvMKBN6z9mYYihZiV0RERERERESLAweAtGxI6eH57DcC18XFKqw2LguhI1ooR3P9cANc8VlAYH10dYgdERERERERES0eHADSsrE3dytycihw3cbYqyGECKEjWihegOEfAEjw6r9ERERERES0cnAASMuC5U3gYO6Hgevq1c1YZ1wfQke0kCacdKB8m9HEoS8RERERERGtGBwA0rJwIPd9eCj/AhAF58ffzSv/LnGD1hi+3ndXoJorGi8IpxkiIiIiIiKiRYiTD1ryUm4vDpk/ClzXpJ2Fem1DCB3RQrpn5DfIeVbZ+YQawxWN20PsiIiIiIiIiGhx4QCQlrxnMv8BCSdQjYCCs2JvC6kjWiiu9PDQ2FOBat7Z+XrUa4mQOiIiIiIiIiJafDgApCVt0jmKYSfYAAgAuozr0KhtCaEjWkjjTgoZLxeoplmvC6kbIiIiIiIiosWJA0BasqSUeCrzjxVUKtgae3O126EaEAh+IY9KaoiIiIiIiIiWMg4Aacnqse7GuLsvcN064yWIKs0hdEQL7WC2N1A+rkTQojeE1A0RERERERHR4sQBIC1JUno4kPtB4Dpd1OOs+DtC6IgW2piTwn8cuy1QzWWNF0BXtHAaIiIiIiIiIlqkOACkJanHugdZrz9w3RnRW6AKI4SOaKHdP/o4TGmXnU8oUVzfcnGIHREREREREREtThwA0pKTcfvxbOYrget0UYfOyNUhdES18OvxZwLlb26/lof/EhERERER0YrEASAtOYfM2+HBDFy3PfFBqCISQkdUC6P2RKB8QouF1AkRERERERHR4sYBIC0plpfCEfOuwHXN6llo07eH0BHVihDBruZrCD2kToiIiIiIiIgWNw4AacmQUuKJ9N9Dwg1cuyX2OyF0RLXywOiTyHlW2XldqNgU6wyxIyIiIiIiIqLFiwNAWjIGnJ0Ydp4KXNemvQAt2vkhdES1kHIy+GZfsL1AL6o/G0ktHlJHRERERERERIsbB4C0ZOzL/k/gGgEV2xP/X+DDRWnx+uX4U7CkU3Y+qcbw2rarwmuIiIiIiIiIaJHjAJCWhBPWwxh39wWu6zZugq5wz6/l5OnU/kD5Kxq3o9VoDKcZIiIiIiIioiWAA0Ba9GwvhV3pfwxcpyKCDdFXVr8hqqmsG+wK0IbCi38QERERERHRysYBIC16h80fw0OwoQ8AnBX7I8TV9hA6olrxpMSEkw5UU6dyD1AiIiIiIiJa2TgApEUt541if+67geviYjXWRq4LoSOqpduHHsSwM152XoHAjrptIXZEREREREREtPhxAEiL2q705+HBCly3KfY6XvhjmUm7Ofxk6FeBal5Yfxaa9fqQOiIiIiIiIiJaGjgApEVr3D6AYeepwHVN6plYa7wkhI6oln49vhuWtMvOJ9U4bll1fYgdERERERERES0NHADSoiSlxFPZf6qgUuCCxAe4998y1JPrD5Q/I96Nei0RUjdERERERERESwcHgLQoHTRvw6R7OHDdKv0SXvhjmXKkEyivCTWkToiIiIiIiIiWFg4AadFxpY0DFVz4Q0UEZ8XfFkJHVGtZ18Sz6UOBalZHWkLqhoiIiIiIiGhp4QCQFp29uVthy1Tgum2xtyCmtIXQEdXa/w7ci1Fnsuy8gMDljReE1xARERERERHREsIBIC0qY84+HMr9MHCdjnp0R24IoSOqtbSbxcNjwS4Gc1nj+WjRG0LqiIiIiIiIiGhp4QCQFpW92W9Bwgtcd3b87VCEHkJHVGu7JvfBCnD+v4QSxe+t4jCYiIiIiIiIqIADQFo0Rpw9GHSeCFzXrJ2DzshV1W+IFoVxJ9jh4A1aEobCYTARERERERFRAQeAtCjYMo0nUn9XUe3ZsXdUuRtaTCaddKB8TI2E1AkRERERERHR0sQBIC0Kh3N3wpQjgetW65ehXtsQQke0GPSZw/j56M5ANWcnNobUDREREREREdHSxAEg1ZzrmTiQ+17gOg1xnJ/48xA6osXitqEHkZN22XkFAlc3vSDEjoiIiIiIiIiWHg4AqaaklHgi8xm4MAPXbovdAlXwcM/latLJ4LGJZwPVvK79ajTr9SF1RERERERERLQ0cQBINTXk7MKA/WjguohoQlfkmhA6osWiJ9cHR7pl5xUouKnl0hA7IiIiIiIiIlqatFo3sNDGx8fxve99D48++iiGh4cRiUSwadMm3Hjjjbj44osrXtdxHNx555144IEHcPz4cQBAZ2cnrrzyStx0003QtBV3V5dlT/ZrFdVdmPwINBGvbjO0qAQZ/uXJUPogIiIiIiIiWupW1FSqp6cHH/nIRzA+Pg4AiMViSKfT2LVrF3bt2oVXvOIVeMc7gl9RNpvN4qMf/Sj27t0LADAMAwCwf/9+7N+/Hw8//DA+8YlPIBqNVu+bWQaOmHdhwj0UuK5DvwSN2tYQOqLF5PHJPYHybUYThBAhdUNERERERES0dAkp5YrYbca2bbzzne9EX18furu78f73vx8bNmyAaZq4/fbb8a1vfQtSSrznPe/BddddF2jtz33uc3jggQeQSCTwnve8Z2pPwkceeQT//M//jHQ6jauvvhrve9/7Tvv7GBoaOu01FsKPnrkPvxW3ITUCJFtyGB+Oo6V1EsMjdWhuTCGTi2DHhl4o88xrcjkFP9l5LnIJDZmJCGREwnNUKNKFNFQg7UEmAUwKKI0evHEVSr0LL6VCibonz46pUBrmyWZcyIQAJgVEowdZnI248FwVQrrAfNlCD3EXnp3PCkOFrCAr/Kw3pkKpd+ClNSgxF56lQsDPZl3I+Kmz0FUgd7KsA8/SprNZv98JQGmS09mUBiWezyrChdQqzBb9LNQGB+7kzKyaBJIdsy/+4aSBwSeTSMkIlKyAp0songIpPUhVQLEl3KgKLePAiavQMh7cuICaA9zTzUYUqFkX7oyshKtjZtaScKPFWRduXJmZhYRUcPKsIaA4gBTIZ2f14MKJqdBMbzoLQCoCiuNNZZ2ECj3twYkpM7MCkOIk2ZwHNyKguP66p8pGi3ooJ2vP3UPh/nXiCrSchBtBURZQnNk/i5NlPUOBYnpwY8p0Nutn/fsBqoAwXXgR9dRZRUBYfjbnwY0r/s9CgZZD2Vk1J+FGBVQb8ISEUBTAciFPlrUATynNFv8+lGRVCSEUCNvL3w9BsqYLN+bfvzH/dz0ioDp+D/Nl4wJq9hTZuAYt7c7M2iU9RAr9lpnNunATGrSUCychoGUlnJPeD/66hWzxulAgnELWy99naRdOnYCWLiObceEk/WxUgWrJ2VnT8+8zv4fMzKwCBSjJqhkX7nxZ14Onn07W/50PlM3fv9L/3uB68DQFihViNqrm//ZnZCU8DVDkSbJp//f4ZNmMCzfpZ+MCqnmKbJ0CLeVncxKe7mc9D55aRtZTAFmUnfp9KOphrqxZ9Hvm3w9uTEAJlMXU9nPOHuLK1HauOJvfzgXJ1mK7PEd21rZ2jm14JdvlObKztsun2tZyu7y0t8sVbsMr2i7niu7fFbRddlo1SE1AswXOcOvw0Zdei/WrW6v/4jUEra1Lo09aWVbMOQB/+tOfoq+vD5FIBB/72MewYcMGAEAkEsHNN9+MG264AQDwzW9+E47jlL3uoUOH8OCDDwIA3v3ud+OSSy6BEAJCCFxyySV417veBQC4//77ceTIkSp/V4uPbdv49DPvwUTyXxCLZdDVNIq2hgwa9CzWtKSgw8XGjlF01KdmDf9Gx/J7SD7+zFp8t++FGHHiQKsKDwLxNTaEBsRXW1BjEtEWG5FGCSPmINriQVVcJDpcCMiZ2ahErNVCpBGIJPysWpJV81klKhFrsaeysdJsZz6bmCvbLKGqHhKrXAghEV+dzyY789l429xZZVYW+WwDYCQcRKeyHhT4WS2fFREg3mrDKM5qJdmSdYuzmuYivsqDgERstTOz3/Z8NlJXkhXT2cSpspgnWw9E62xE/GysY3Y20jD78N+xXRHs7V2DTDYCa5UBqIDVacAzBKx2FbJOg9Mo4DWrcGMCTocOqQHWah2yONuhnTq7Zq6sBi9emhUz101qcJr87NS6AtYqHVLJZ6UhYHWoc2f1ouwaHTKiFGWVmT3oAnan30Mhu0qFrFNnZN32fL92Z9G6hgKzoyjbpMFLlGQL6+plZlcXZZMKnOZCVoHbpkPqJesac2eddj+7RodUMJ1dpUIm1ZnrzpXVp7N2iwK3WYNbuB90mc+qgNU5nfXiCuxWdUbWK6w7X7ZJg5ssZAWcTmNmds3Js1BFfn1dwFqjwYsrcFq16WzbHFljrqwynV1Tsu7qfNZuUU+dXaXDixVl/Z+bZ2A62zn9+zyVbSysq+Wzq/N/m8VZGfPvh0K2VZ2d1UuyDdNZOVd2tQ4ZLcrW+etG8lmp+j8/rSjb5vdQr8BtK8oqJevG8lmvUYNbL6bX7fDX7SxatzhbJ6a/t6ls/oWLtSaftdoUeA0l2VWzs94cWVnIKiXZqAKrVYHXoE71KyNiet01Jdl2dY5s/m/opNkWFTKC/OOPMn3/mhVkzQ4/25DPelE/6//coCKfjZRkW4uySiGb/1mcNKsWZdfo8CJi/qwG2KvnyNaXZNuLslpRtt3PNvrZWElWnSfbosIt7needZ0mAbd5ZtYqrNtplJnFzGydCqexJKvNzlqFrL+uN9+6Nd0uo4ztMvKPN+ppbpeby9gudyzj7XJH5dtlb7lslyvMlrVdXl2yXU6usO3yOgO5LQacJgVunYDZDDzVNonXP3Yb/u93fhL2S1qiZWvFDADvv/9+AMAVV1yBtra2WV9/3eteByEERkZGsHv37rLXfeCBByClxOrVq3HJJZfM+vqLX/xirF69GlJKPPDAAxX3v1R89vkP4KyOwxgT9WiSE4i3upjoN7B58zD27WvDC848iif3dWFt6xgAwPPydaNjEfxo5AL86KmzsadhNawjCpJbbKQO6GjcaiJ9PIq6rizMXBTRmAmZ1CAmHBhdElaPQHKLk89um87mclFE4ya8hA4xaUNfU5Td72ePRVG3Np+NzZNNz5GNJ/JZpZA9CiS32LOy2XQUsYQJNzZ3tmFWNgc3qkNJz87WbzWR7p3OxpP5rOpn7V4gsbkkuy6LbMrPRgpZwO4F4psdpA/oaNhqIjMja05nV4vp7H5tZnayKJudmc3s19CwzUTmqJ+diCJe5/eQs6GuEnDmyWYmI9Ai+QFgrk/B4GAdJp7VcayuBZFeE7nNEUR7bOQ26DAGPVjtChRPhad68OoMKGM2rK5IPrupOOvC6lCgusrMbGcEkd5cPnvEzw75WUeBq7r57IQNa01RtsdGbpMBY6CQFXC1omxnBEZxD5vzWbNDgWoLuIYHr06fmd1Ykl2lTmeTGpTJfA9T2cPWVA/mKhWqNU92k5/dbMDod2GuVqFZAk7Eg5fws6sjMI5VIWsKOFEJL65BSdmwVxswjhf1u9lApM+FuaYkm85nI/NlcyXZVXOse8KF2TmdlbF81lllQD9uIrchOn82OjNrbihZt8vPxvxs1obTMZ2NlGbTc2RPWH7WzGePuzC7NOhTWXU623eSbBxzZ48UZdeWZHOFrFmSdfws4CRnZrV+E+b64h5KshEVwrThtBvQ+q189kj+bzRybDprJwFpqBCWDaft5FmrNNtnITfVQ1F2UsKqA3CqddcVZTU/21qUPWwityWCSG/RuvX5LArZgaJs6brF2bY5skf97Hg+KzQNcBw4rQb0gZJ+i7ONJ8lu8bPdfrapkHXhtPjZbmN63d6SrFCnstpgUXbLPFnXhdNsQBu2YHZHZmfHJKwmkc96fnbIgrkugkjPzKzhZxWokNKF05TPWmv97OYIokdt5Nbr+WxzSXbYz/o9TGVHJayWebI9JdkRCatFgSKLsiMWrHVz9FCchedn7els4fF9rmyjn11blD3qb2OGJazWomxDUfZo0XZufVHWy2e9BgPqaMm6he3ckDedFX527CTZNj+rlGSPniJbn8+aayNLe7u8aZFul5NF29pqbMPD2i6XZgNsl+1qbJc7S7bLmUW4XS7OBt0upxZou3yKbNnb5RSqul2ed0qhAT9OHMff/fBnIb6iJVq+VsQAMJvNYt++fQCAHTt2zJlpa2tDV1cXAOCpp54qe+2nn34aALB9+/Y5zz8mhMD27dtnZJerH+6+B+euOYzH9nZjff0IDk12oCWSBhoUxFQb6zeOIDOpYvuWXuRMFQDwi11b4UngR89dgGjMwQCaoGsetE7AywLJzTayRxU0rMshtS+CZIuJdH8UsbgNW4tA1z1oawS8rERyU3E2irrirGpMZ3Pe9Lrd+XVPlk0UZdN+NtWXz1qKn109T7bVROpEIZvvV10tIC0/e2yObMKGJWZnc8cFGtbnkN5nzMwin1VWCcDyEC/NtpVmXSgd+Wxik43cCT+7388ez2fN4qztIbHZgTlP1vIKWQWwPcQ3+dkNfrbdROp4bCprlGb7prP1bdbU39KJA80YSNfhRK4FkBJmVwTqiIPcBgNGjwWrU0X0qAO3UUCbBLwYIGPa7OwRC1anhmiPDac0CwmzKwp11EFuY2FdP9skoE+IfDbqZzujUMf8dQ+bsLoKWWU6G9EAIWF3RvLZjUXZI352DPBiAijKKmM2chsNRKaylp+V+axRlJ3w1z1SlG0uyup+dk1RtseEtVZD9HA+a4xIePGidVdHICaL1l07ve7srDGd7SnKthRldQ2yNHvUhLlWQ/RQSVbLZ61CdoMB46g1MzvsZ1UVUpGwVpVk1/nfW/G6ftZeZUCk8lm9kC1eNxEwK1RIVcLuKMr2FmVb58i26xBpF7kNkXy2W0P0oAW73OwhPzvkzc5m/OyxebKykDVKsnq+hzYFkQEXXkJA+Fmn1QAK2eN+9lBRNinyA4zi7Hp/3fVzZF0VUpNwWw0g62ePz8xG58tuKMoetmC3q4gOuHCLsy0GYPrrnihat11FtN+FWzdHdoOf3TBH1inOejA3FK1b6KGvJNtclO3z1z1swe4oytoKpCbhFLLdfna9juhhM589PkfW8rP9+WzkkDUzayn5vTJOla0XUCwBaQBu43RWmy9rCsgI4Db42fURf9DpZ1epiB5z8tmcn200ANtft5A9bMFapSJ6PJ9Vs0XrOh7MdflsboMxnT1Wkq33s93T2ehhC9ZqFdHeebLrItAG7el1C9mG6axXV0Y2g3w2qQOunx0uPGbPl9VmZgvrrinJRouyayNQR/x1j9jT2UYBLQN4UUAmNMCT09kNc2TTfjY+V9bvobD9TM2VLdrWzpWda1vL7fLJt8vGSbbLxdva+bJHTrUNX2Hb5cMlWWWFbZePBdguHz/Jdlkt2S4fq3C77GersV0+JQH8wDsCK8BRe0SUtyIGgL29vSic6rC7u3veXOFrR48eLWtdKSV6e3tPue66desCrbtU7dXugBBA19oJODawbU0/jp1IYmPTEB5/tgut0TSe7etCVHUwZuWv4NsTa8WjQ+ugrAGsYSDRmsPkPg2xhI1UbwSa6sGCASEAtQNwHYn4WhvWCJBsK8lqc2S7ClkLqf1+9mg0n5WFrIDrSsTmyKZLsko7Zmbb/Wxyrqy/7lob1iiQbDeR2q8hnrQxeSSfNd05smNAot1E6kBpNuJnlZnZjqLs4Sh0zYPplGS7nJnZuqKs7WdbC+s6sMaBZFE2dSifzVn5rCjJJjpMpA9qiNdZ+aw+OxvtcmAXsodKsubMLADY40Cmw4B+PP9EN3rYgowA+riXf+SK5F+o2B06kHZhrtGgn8g/GYwe8bNjfjaav96R3ZF/0jIje7gkGynJdmrQ+4qyUUAf8bOGn203gKw3nW3NZ725sh35rOVn7aKsMSIBBZDF6+Y8WGt06P2FrJnPDvnr6rOzmp+NHLbgxYqyakm2U4c2MDMbGfSzWn5Ib7fNlxXTWbWM7ICfFep0D2ZJ9kjRuioAoUyva3qwuvxsm5rPxv11i7OtfnaNDm3Qht2mIlqSFcXrWn4PfrZ0XeFvJp3Wkmy7mv/eEkVZ6WdbirJDJdl+d2a2VQdsCatThzrsZ4/YM7LK1Lonyfb5Wc/PNvvZNX62w//eirNu0bqOhNlpQB12YLWrMHoseEmBaJ8LaIDiFK17qmxh3aaSbIcK44gFNykQPVGybnF2pChbJxA94czMNs6R7fGzx/ysVbSu62dHT5Ft9LNrDCijNqxVRdleG7Io6zbks1bndDbSY8GtF4ge87OmmJ0dd/LrHi3K6n5W+EMrV8JaU5Tt9bNH/Ww2n/Xq9amsmHBgrVZhHDHz2d5TZTUYPSbchul11VlZfTp7tCSb8bN1mv+9+dk1Wv57a5juQU372aSfXV28rgW3USDaY0MaResm84/vxT3ohexRP+uv6ybmyPaWZFPIrztP1jlZdrUOMenCWuNnmwSiR/zs5BzZVHFWmf7eTpY9NjOrTfjZmDqVRcrfdh0r3Sb6241CdlVRtrD9PFKa1aaz6ZJ1j8yzrS3OHi/ZfnK7fMrtsh5kuzxfVlNnZ7ldXrnbZTfAdnmube1w0TaxeLs81zZ8gbfL5fBiwP+7477ywkQ0ZUUMAEdGRqb+vbm5ed5c4Wujo6NlrZvNZpHL5cpeN5vNIpvNnnTNb37zm7jxxhvn/eeuu+5CU1PTovxnVeMwAGB1Yhz7jrShTjfRM9oCTUjIRP5XraU1DQDoMfP3SazexvOHVsEwXGQHI1AUwPWfDClN+fvEaMkfDhpvsGGdUPPZAWNGVi1km/PZWIOVz0YKWQlHFLJixrqxBgtWn4rIHFnRWJJttGH1KX42UpLF7HX7/Wz/zHUVPxsp6tf2s7k+A6oi4Ug/2zD7e7MH5smW9lvIRp1TZqONFuwhP3tCn5EVDbPvB3u4sG4+a7v+Frs022DDHhaIRh1kC1mndF1vOjukImvqmNwfATRAzeSXlUb+CarT6D9ZblEhUvl3D43B/BMGNe1ndT/bVJSdcPLZ/pJsYd2GObJ9fjZ1kh4m8nudGP22n80PMKV28qw8VXYyv/eN0ee/iJ4sZLXZ/aby2Yif1SYkIABohWHFdBYpF26D38NJsk6LNp0dKMmqfra+KJsuWXe8JFu8bnaeHpQ51s16cBuLehgvyU6tqwK5QtbJv4ge8wABSFFYV52d7fez415JDzOzTqOA3j9z3TmzppffQ6U0W+ihrihrefk9SfrzL/r1UT8LMSNrt6iALeE0FmVH5sk2+9nCupHidZXZ6zqlWRdQpl8IucmirFuSHZmZ9UqzzQr0gZnrKlLMzDYXZUvWncomtNnZgZKsNzPrFPc7YPsDgnmyzfnBydS6UcAYzr8wVtxCvzOzdrMCfdDOv+j3s6KwbryQ1WZnh/wenJJsk59tUaAP2f6Lfj9rl/Y7ndX8bGRwnnWLs8OFrDP/ugDs5kJWwCisa83Rr/+znp1FPhtTZ67bokIbceDF/awKKKafjc9+zNaGZ2bVwrrRObKFdYf8bG7+rDoaMJsQ+fusOOt/b27T9O+bOprfU8cYKMlG/Gzj9O/QrGy2NDv9OKGOuf5AoyQ7V7/j+T11IoX7rLD9jMzexkxlB/Iv+gvrzpVVxh24Sb+HU2yXlUlul+faLqsT/jUX59su1xdtEyeXy3ZZK9ou2zO3y/Nsa+fcLpduw1unt8sGt8unv132Ft92uVw7x/tr/vr3ZP8QLUbB/sqWqMKQDshf9GM+ha+dakhXUJwrZ91CTSwWmzebTqcxMDAw79czmQxU/129xUZXXDg2oOkeTNv/1fKv9KFp+QGPpuY/Hkq34dy6o1AUCddSAXjTC/nfnv+GZD7jSqgq4NmFrPC/OLNGUfNZRQE8pyRbuNtU6a8v/RYlPKuw0MysmDOrAnDhbwNn9SsUOdW3Z/rZwvemlGQL6yvS/96KsqX3Q3HWmi8rZ2aL+sV8WaXoezMVABKy0KgyMzvVi5CQpshn/ScZs+8zTK0vTQWANys762ehSHhZBaNqHBHHf7Xn389SLXwUU/+tmRIOAFFyzZCysoV1lZKsAmiWny25RvqsrAqotoQLQEz9Ck9/bb6sMk8W6vTvn2LNs65SklUAxZRwk5j+MxKFbOn6gJrx1526z+bOShX5q7sBEK6YkYU6O6tkPXgJdWoIUuhh7qyEF5vdA+boQeQ8yJgy/Sss5ssKiJwLGVUAfy/S2T2I2Vmn8EMuXbcoa+azYmrdmb3MykaKsgWFdbXirAdpAMKZJ1u6rq5CmZXF7O/RzF/Ne3YPM7MoZBNzZMUcWcsFYursfqf+RovuQ8sDYmJWVpZ8b1AFYHtAVEB4flaWZLWix2Vb5rOF34dCVsz+3YEjgYiAcEqyc/yewZGAIYDS7By/v3AB6ABKLlQ+Zw8e8s+0TtWDVpQtrOudpF+Zvz9EIXuy721WtuRvXinKuhJQxVRWlPSAGf36Wf97EyV/SjP+9j2J/NU35cxs4Xey9LFKAYRdki39nSw8g1XnyM76XZ/+/KzH1lm/60VZ/zF76rF1nn7zV2r38uue7H7wPyrOqbLTNcL2Tno/zJktnGC55G9z6vFHmc6i8Hc3tU2cva5qy/xdUHKfzbmds/JZbpdrv11WsxJuAuVtl9MevJha1nZZyXrwytou+9vw6MmyZWyXS3/XlentMrhdrvF2uSjrzpMtZ7tcsv0slwVv0b4uJlqsVsQAcClJJBJob2+f9+vxeByuO/sKqYtBxjHQEM8h6+pors+/jat4+V6tXP7BOWPqAICsaeCJ9AY4jgKtLp8RhWd1hXf5/cOnHEtBJCpgOwq0Omdm1p4/q9f7WaUkm8tnXUsBooDjKNAbXEgJKIVngP6LlMK6rjk7q4p5spYCxEqypT2UZF1HhVbv96CWkZ3qd+77zDX9HlwVWmM+K9SSfovvhzjgFK+r+r9jTun3JvysUtSvn/VfgMmpHoqypevOyipTWb3ZxdhwHO1G4ZvyX9j5NYrpwYUKxZRwkiogAc8oPCvys9Y8WQ/wIoVnRfOsaxVlS9edowc3UZKdb92irBuZe11hegBUCFPCTSgz+y1knZKsJeEm/Wx0Zg+K/wJPMQs1RdmSdefMTvWAkn5nZvMvdDS/hzKycXVmv+LUWRktvR8CZEvXzfk/CxeQ8TJ68LNerJDF/D3Myp6k30T+RZHn9yBPum4+6xayheH8jN8HJZ+tU2b0ML3uzKwwJVCnAA7yL+bKzcb9bGHo786RrRczs/P0W5x14yVvJszKAqjPv3CYuh9m9VC4zwCvUYGwT3afFWXj+eys721WVs6RFTN6UKwKsjk/awGev8d84QXWnOsm8lk3Mff9UPy7M5X17wdPw9zr5oqySX/vEb3k/p0j6xSyhddgXknWlPCS+Z+fU6fM6GHurJheV86fFTkJFLIJP1voobRfU8Ktyw82C1lZWLfwmG3lH1OnshbgJPxtjF7Sg+1nc9I//yKmt0el2eJ1kc/ahXVP1gMEFPMkPZwsW9gelWZzHtx6fzvnZ+V82eJtYl1J9iTbuamfW2mW2+X8bS/odrmwrS0nq6Hs7XKiCtvlk2w/Zen28yTbZcntcqjb5UIP82+XZdF2+VTbz5Nsl0u24eWqF8aifV0MgMNJWpRWxAAwGp3a8sE0TcTj8Tlzppk/FuVke+gVK84Vak+2bjlr33LLLbjlllvm/frQ0FDZhygvtL4T3Vi9aTcODLXinM4TOJZuwAWbjiLtGGiPjMGVApkhHWgHjAEbx+qakOnXUd9pIj1uILHRhG1riDbk8jsLpPIP6HafAOqBTL+Bhs7cVNYqzqYLWSWf7TPQ0OVnN5iwLA3RBhOeN0e2fzobL2QbrXw240xnG/x11+aQHjMQ35jPxprMkqw4STY3M9tfyOpoWOsiNTbdQ7zFz2ZL1/Wzo/66poZ4Ww6eJ6az/QJoBLJT2QjiG3J+1oTnCajmHNl101nT1BBvnZl1S7Mj+X7NOdZ1BwTQVJyNIL7RX7fdz1r5rDMAoCn/vTWucxHZ42KgrR5KWsJcpeWfNGn5JwXqhAO7XYXe78DcoEPvd2F36jOzxjzZPhf2mpNkO6azRp8Ly8/mSrOT+azRnz85+FQ2JZFbreWfNEXmyZ5wYa0uyc63rp9V51o37cBGSXaVDnVSIteVz7r+w42ScoBCdlPRupMSuc55sgP+useL1u3UZ2bT+azeb8PdVJSdyGfzTwj9bMbPDsyRXaPnnxAmysh2lmbt2dk1Rj7b5WeTACQgsv66gzbcegPGMRdWpwF1fHpdZ96sMztbV5IdsOFuLs0ac2cL6/Y6sLoMqGMSZum6Zsm6xdmu0qwLQMuv2zBH1gKcegFIQCnNHnfy53Eqzjbks8IqyR5zYK3VoY2eJDtkw20sznrT2cZTZ3N+1m7ys/6Lv+KsWVh3rTEz679I04ZsOI0GjD4/O+JnTT/rAcLJ96AN23CaDBgn8lcnnJnNv9iGW8g6c2T1GVk5X3Z4jmyhhxEHTrPfb2m2uWTdERtOcyS/brfuZw2IXFHWmz9rrTWg5AC7pSQ7asNpKWQ1aEOzsyhetyUC44QNs1uHPuTBWpfPWoV1Zcm6fUXZtQaULGC1+cMBUdqDDXO9Dn1wjiyKsq1zZ82OmeuqYzbskqy51oCSlTDbC9n874466mf7itbtKsn6bxaqYzbstgj0QnYg/5iiZGS+BxeQ/pt66rifPWHnt0cDbn7djL9ucbawbv/863ql6/bZU9tEa01JtnT72Te9/bRKt596Yd2TZDsCbJdXl6y7UrfLa7Q5t58VbZeL1y3NLpXtcmKO7ecmbpdPa7s8x7rzb2vlot4ul+sPzjl/0b4uBoDW1tZat0A0i3LqyNJXfH6+4vMBlip8rdxj9mOx2NRAr5x1i/PL0e+u/zPkXA2Y8OBJgZ4jTYhEgOd6V2F91zgOjLZh+9ajGMwlccM5T+f3DHMcSAk4JwBVF0j36Ii2A+nBKOKbLGTTOhJrzPyeYY4Nryib8bOpgSjiGwvZXD7rFrIinz2qI9oukRqMFK3rZz1r5rpF2botDrIpHcmufNZAPuv2AaqW7yHSBqQG8tlMSkeyy4R90mx0Ots5M+sVZY2WkmzJul6/nz2qw2gGUv1+D5N+1vazHuD1e9PrNgOT/REkN/vZtbl8VvjZgXw22zO9bj5rIFHIqn52UOazR0+WNf2sB1X1120CJvsiSG5ykJkwUNedg22riPjZZnUcECqMEzZknYrIMQd2lwFt2ENunQ6RA5x65J8sZB1AETBOWJBJP9s5nVVOlu0tyq43prMugNx0FqXZbv9FcYOYme3zs8cc2GsMaEN+NgvYDf4hMGbRugkVkWM27E4D+pDfwxxZva8ou8bPlqwrCtl+C4ipiPTasFcb0AcL68r80MEFYBWtO1+20c86xesqM7Mb8i8y7WY/a8/MGr027FVF62YkrGYx57pT2QF3dtZ1ACGgD/jZYzbsjkI2ks+25t8Fh+sCEvl1o/66HQb0QRfmegNKuijr+dnB6azjr1vImm2FrDc7216Sbc9nZSE7cJKsv66UfnZojmx3ybooykaKsv0nyQ762WM2nDYdRr+b/91J5bOiKKv560Z6ramsWZoVfnbYAgw/25p/YW6uN6Cm8kMH4fhDEglow/bc2Uk/axdlR6azbouf7c6/0DVX5bOeWrSuLhA5epJs8bq6QORYcTbfQ6503VE/22vBbdHyg4R1/ovXQlYrymrzZFf7Wd3Pjlmzs91zZL38AGgq21yybqeWzxol2WN+9oSfHfezFuBFirKqgHHMgtukwTjhzJ8d97O901mzkPVfDHpRCXiAMj69rtek51+8rs2/0M11lmQnirINmv9Cd2bWjfnZyTmy3ZF8dq2fjeezalFW1vvZdRFoY9P9FrLT69r57DE/O+qva54iuzaSf1Fcmk05+exxe7qHtcb0C2gTU4eFlmYjheyIv50z/SFJ4Y3LkqxdyK4tWTdTki1sP4uzdYVsYXtUsq0d8ZDrzm9rC9np7ef82+U5s8nZ2RW5XU6UbGu7T2O7bJ9ke78ot8vOzO3ysZLtcib87TJWwnZ5qGi73Haq7fI82/BFsl0uR3wYuP7Cs0/jlSvRyrQiBoBdXV0Q/rkFenp65s0VvrZ27dqy1hVCoKurq+rrLlUbWjtxbP/LcMamQTy6rxsXn3kYT5/oxDmrjuLIRDMa3RTG3TiGemOIJD20Hh9HdK2H8X0R1G+zMN4TRd26LFIjEUSMHGxTB0ZcIKIgc0BDdK2HiTmy0UhJ9qCf3RtB/TazJGvCMo0Z2UiX9LMWxgrZ4QiiURPZjA6MupCGguxBFUZnPltXyHZnMTkcQTSWzwo/m/Ozk4XskeJs7tTZ9flsLJZDNl3IqlPZqR4OF2XjfnbCzx72s/siqNtm57MbspgciiBenNU15A4VZbfOzMYShaw9nV3t91DIrp+d9XQNucMKjNXIf2/F6w5GEE/62ZQNV9WQOyymsk07TNT3ZJHboMM47sJsU6COSUi4UFwF+oAJt0FH9KAJqzuC6EELuQ3GnFltsCi7PoLogaJsuwKtkHXEdPaQv+5Js1Y+e9iEtc7Pbsy/e212KNBGJaTwoDj5J2VugzYzu8l/x7RDhTbqwRMeFDuf9Rq0fA8z1p2dVYuyZml2lZ9V/OywDa/e72FtBNH9fg+9fnbEg6d6UCw/W+dnu4rWLc2agDpiw0uWse7/3969B0dV3/8ff5295wYkEggECYEiivpD5esYHYoIFDoQWzqitd5GLfTqBR1bp4VRlOrQ2tHpF7EMP2qrA6VTpR0LOtRo62WsCKW2FG+IgkRDruQCIXs95/vH2d1skt1wC9nk8HzMOLPhvPLJezfr55O88znnxLNWvleB/UF73NTs6HjWa3XJ+veHFC5NqaE6qtAotzxNKdnmiKxcj/yfhRQu9XW+vtXxcVOzLWmy47tmYz5TrmC8WZLTM+uvjipUmjkbSamhSzZg2dnWNNnUcRtTsolxD4QUGZ2SPdCZjeb2kp3QmfU2mooksm2Zxw2O8fTMBuy7xvbInm3vkIrkWXIdjTdL/G47Oyol+1ma7JF4tjqRDSlY3kvWF8+WxLOJccd2Zt3ds4lxv+SX/7NI57j58Wx7RIbPvtNuctwJ8WxZSrbd3tWSzI70KbA3pOB4v/z749n6WNes1y3f5yFFRiTqDXTNFsjOdnTLfhpSqPu4qVmXW94vOsftkq2LKTLEzhrBeLYmpEhxyrj7UrOG3EfSZFPHTezoGhrPhiIyXC67huEp2X0RBcfFs8Pi2XA8W5OSLY9nyzNno8Pj9aZma2MKDzPkbrPsrBHPnpV473RmfSlZdc92G9dXG1O40JC71ZKiUTt7sJdsUSIbkyGXfAc7a+iSPdgz660NKVrkTWbttcvOhhLZWEwuK54ttNeu0Dhf1+zweNaMZ+t6yRYbcrekZGtDig6L1zDOnzlrxseNZzvXxDTrsmmvy9Fh3dfl9Gs46/IJrMsuJ6zLKa/v8a7hJ7MuH0+WdXlwrMvh3n/ndHdI/3v5nP75BRdwGMOyrBM72X6Quu+++7Rnzx7NmTNHd9xxR4/jjY2N+va3vy3LsvTQQw/p4osvPq5xn3nmGW3atEmjR4/WmjVr0ma+973vqaamRgsXLtQtt9xySs+jsbHxlD6/P/z/7evlHrNVn+4r0sRxtfr04EhNGFmr6tbhGu5pVbs7T1ZrTDnFpvbvKdT+oSMU/twl39kRhWp8CowOKdjklz8/qEjYL08kIjPPK6spJvcoQ5HPDXnPjiqcyDb65S8IKhIOyBMJd2ZLDEW+OHZWTTG54ln/OFPBak/PbDQkM9duHLpGpmQPuBUYE1aw3i//kEQ2LDPX23t2aFCRYEDeWFixZNZlZ8tiClafSNajwJhQPBtSOOiXLxZWLMduXtpZyV9mps+aYcUCvWcD8aw3kW2JyTXCpegXkq/MVPBAPNvQNRsNeGW0xOQqdila0y2bGDfklyc+bvds8z8Dai7Kl782qlCxW74WS9EcyR0zZEVjsnI8crdGFC32yVsbVmiUT/76iELDPfK1mHY2asiKpWSH++StS5PNldyRTFmv/HVRO9vaS7Y+rFBJPFucYdy2qKJneXvPmjFZgZRsag3FHvmaTUXzMmS7j9tsKpovucMnkfV75D4cUfSs+HMb6ZW/PqrQCI98h0xFCix5Qq5k1nUkolhRL9mgyz4t0O+xG79F3V7f3rKFPnkbUuod4ZHvUEyRfEOekGGfFuhLk62NKjjSI3+67OF4DSnjBkdkyGYatymm8BBD3qBhn27oSXlu9fHn1lu2/QTGTZeN1xseYsjbYchypWSH+eRtjH8v6qIKlnjkbzzB7FBD3qOdWVe7fQpP5qz9130jNdsUVmhESrbBbs6kZpM19JZ1mzJcbhlHoz3rHeWVvyFqZ9tTsh1RxYb2kj1i7+brNVsfVbgwnvWaMgw7aw71yZNabzwbGeaSp906+ewQnzyHTiQbUqjYJ399uqwlQy4ZoajMAq89biJbkngdXPKmyboPRRQu9h4jG5NZ4EnJRhQs8XVmj1gy/ZYM6xjZIpe8bemz0ZHx+b3EJ1+arMIxWXkeuZtTsqN88tdFFDrLbWd9dr0nnR0Rz47umo35LblSa2iJr0d1Xcf1tVmK+i25TJcUjcnK7YPscLd8rSnZiF2DpyWiSI81Mb5+Biy5TZesiD2up7WXbKa1ts7+XvjrIqzLx7sup8s6ZV2u755NWT8zreG1UYVGZljDnbYuZ8qeyrrcLevkdTlS7E5e31GSZEpDGw09MX2u/t/4MVn7Xfd4cQowBqIzpgG4ZcsWrV27VoFAQKtXr1ZxcXGX42vXrtWWLVtUVFSkdevWyeM5vusP7Nu3T0uWLJFlWfrJT36iyy+/vMvxf/zjH1q5cqUMw9CqVas0duzYU3oeg6EBmPDszue1z9qhtlZTvpygIiG/3O6wLMMrK2rKEzAUbjcUKDBVezBfh6xcme0eWX7JiLgkT0wy3ZJlSm5X/C5TLllHLVk5plxBlyy/lT4bvyuWOiyZgXg2YMkId8t6XPbdtnrLxlwyDEuWO5F1SR06gawlM2Clzdp74F2yQjEZOS7pqGTmmHIF3bICpoyQIXnNjFkrx5IRdHVmffGsfecRWWFTRo6RzCpoSAGra1aW5EqT7TCknJPNxm9/mZrtiGePHiMbMKSgfbqY0WFIOVLkoFeRqEfuiEuWYe++NWKWTI8hd9RSxG3IG5UiHskTsxRzG3KblsxM2Vg8G02XlUy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Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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ELpcr2PFgsUNvhU1KSlJMTIwaNGig2NhYNWnSRPHx8WrSpImSk5PVsGFD1a9fXw0aNFBycrIaNGigmJgYdtYBABCiKAABAAAi3MGDB7VmzRp9//33WrNmjbZs2aKsrCwO3KhlqnbfVT17Ljk5WYmJiUpJSVHDhg1Vp04dtW7dWsnJyWrXrp0SExMVGxur1NRU7yEUAAAgPFEAAgAARIj9+/dr7dq1WrRokf744w+tXbtWubm57OYLQVUHUsTFxal+/fpKTExURkaG4uLi1K5dO8XFxal169ZKSUlR48aNVadOHSUmJvq0dkpKipxOp9xut/Ly8mz+SgAAQCigAAQAAAgzBQUF2rJlixYtWqRffvlFq1evVl5eHjv6gsThcHgPrai6ZbZRo0Zq1qyZGjRooDZt2qh+/fpq3LixmjRpori4OBmGEezYAAAgjFAAAgAA1GL5+flasGCBFi9erB9//FH79u1TYWFhsGOFNcMwFBMTo4SEBKWkpCg5OVmZmZlKTk5Whw4dVL9+fbVu3VoNGjRQ48aNgx0XAACAAhAAAKA2qKys1Pr167Vw4UJ99913+v3337V7925O3LVQdHS095l4KSkpatKkidq2bavU1FR16NBBTZs2VWpqqurUqSOHwxHsuAAAAD6jAAQAAAhBGzdu1IIFC/TNN99o/fr1ys7OltvtDnasWqnqeXppaWlKTk5W27Zt1bhxY7Vv314tWrRQZmam6tatq5iYmGBHBQAAsAUFIAAAQBCZpqns7Gx9+eWX+vbbb7VixQrl5OSws89H0dHRSkxMVGpqqlq0aKFGjRrp1FNPVePGjdW2bVulpaX5fDgGAABAuKIABAAAqEF5eXlatWqVPvnkE61cuVKbN29mZ98/qFOnjpKSktSyZUtlZmaqdevW6tixo9q0aaPU1FTFxsYGOyIAAEDIowAEAACwicfj0aZNm/TNN9/oiy++0KZNm5SXlxfsWCGlTp06qlu3rtq2bav09HSdcsopOv7449WuXTslJSVxGi4AAIAFKAABAAAsUlZWplWrVunzzz/XggULtHPnTpWXlwc7VlBFR0erXr16atGihZo3b65u3bqpbdu2ateunerVqyen0xnsiAAAAGGPAhAAACBARUVFWr58uWbPnq3vv/9eWVlZEfnsvri4OCUnJ6tVq1bq2LGj2rVrp06dOqlVq1ZKSEgIdjwAAICIRwEIAADgo6KiIv3444+aPn26VqxYoaysrGBHqjEOh0MNGzZUWlqaOnfurNNOO02dO3dWenq6kpKSgh0PAAAA/4ACEAAA4CgqKiq0Zs0avf/++1q2bJl27twZ7Ei2i42NVbNmzZSRkaEzzzxTXbp0UefOnZWQkMDz+AAAAGopCkAAAIBDZGVl6a233tLXX3+tTZs2yTTNYEeyRXx8vJo1a6bjjjtOPXr0UJcuXXTiiSfyTD4AAIAwRAEIAAAiWn5+vqZPn67PP/9cv/zyiyorK4MdyVIxMTFq0KCBTjzxRJ1zzjk666yz1LZtW8XFxQU7GgAAAGoIBSAAAIgoLpdLP/30k6ZPn6758+crJycn2JEsYRiGEhIS1L59e5166qnq0aOHOnbsqIYNG3LrLgAAQISjAAQAAGGvsrJSs2bN0sSJE/Xbb7+poqIi2JGqxTAMNW7cWK1atdJ5552ns846S507d5bD4Qh2NAAAAIQgCkAAABCWNm7cqA8++ECffvpprT6t1+FwKDU1VWeeeaa6du2q8847T+np6YqOjg52NAAAANQSFIAAACAsmKapdevW6aWXXtKCBQuUl5cX7Eh+MwxD9evXV/v27XXRRRfp/PPPV5s2beR0OpWSkqK8vDy53e5gxwQAAEAtQwEIAABqLY/Hoy+++EJTp07V4sWLa90BHomJiWrVqpV69uypiy66SB07dlR8fHywYwEAACDMUAACAIBaxTRN/fDDDxo3bpxWrlxZq57n16xZM3Xu3FlXXHGFzjrrLKWlpQU7EgAAACIABSAAAAh5LpdLn376qaZMmaJly5bJ4/EEO9IxORwOtWvXTmeffbauvvpqdejQgef2AQAAICgoAAEAQEgyTVM//vijxo0bp59//jnkd/pFR0erY8eOuuCCC3T11VcrPT1dhmEEOxYAAABAAQgAAELL2rVr9dJLL+nzzz9XeXl5sOMcVUxMjDp27KiLL75YgwcPVlpaGoUfAAAAQhIFIAAACLqdO3fq5Zdf1uzZs3Xw4MFgxzmiqKgotWvXTpdeeqkGDhyo5s2bU/gBAACgVqAABAAAQVFRUaH33ntP7777rrZv3x7sOH/jcDjUtGlTXXTRRRo4cKBOOukkRUXxRycAAADUPvwpFgAA1Kg//vhDDz/8sL7//nu53e5gxzlMYmKizjnnHA0YMEAXXnihEhISgh0JAAAAqDYKQAAAYLv9+/frrbfe0nvvvafCwsJgxzlMu3btdMkll2jkyJFq2LBhsOMAAAAAlqMABAAAtjBNU3PmzNHrr7+ulStXBjuOV506dXTaaafptttu01lnnSWn0xnsSAAAAICtKAABAICl8vPz9dhjj+mTTz5RQUFBsONIkurXr6/+/ftr4MCB6tSpU7DjAAAAADWKAhAAAFhi5cqVuu+++/Trr7/KNM1gx1GbNm105ZVXavTo0UpKSgp2HAAAACBoKAABAEDAKisrNWXKFD3zzDPKyckJahaHw6F27drp+uuvV//+/VW3bt2g5gEAAABCBQUgAADwW3Z2tp555hlNmTJFLpcraDkcDodOOukk3Xjjjerfvz/P8wMAAACOgAIQAAD4bN26dXrwwQe1dOnSoGUwDEMnnXSShg0bpquuukrx8fFBywIAAADUBhSAAADgH5mmqQULFuiBBx7Q1q1bg5LBMAy1atVKY8eOVb9+/RQVxR9hAAAAAF/xp2cAAHBElZWVmjZtmp588knl5eUFJUOzZs3Ur18/3XXXXTzTDwAAAAgQBSAAADhMUVGR3njjDb300ksqLS2t8c+Pj4/X4MGDNWrUKB133HE1/vkAAABAuKEABAAAkqS8vDy98MILeuutt+R2u2v0s51Op0499VQ99dRTOvnkk2v0swEAAIBwRwEIAECEO3DggJ555hm9//77Mk2zRj+7efPmuuaaa3TbbbcpNja2Rj8bAAAAiBQUgAAARKi9e/fqmWee0dSpU2u0+IuKilLv3r01ZswYdvsBAAAANYACEACACLNv3z6NGzdO06ZNq9HiLz09Xffff78GDBig6OjoGvtcAAAAINJRAAIAECFycnL0xBNP1OiOP6fTqYsuukiPP/64MjIyauQzAQAAAByOAhAAgDBXVFSkJ598Uu+99548Hk+NfGa9evV0yy236JZbbuHZfgAAAECQUQACABCmKioq9Nxzz+mll16qsVN9jz/+eD366KPq1atXjXweAAAAgGOjAAQAIMyYpqm3335bjz/+uMrKymz/PKfTqXPPPVdPP/20WrRoYfvnAQAAAPAPBSAAAGHkiy++0F133aXc3FzbPyshIUGDBw/WI488ooSEBNs/DwAAAEBgKAABAAgDv/76q2699VatX7/e9s9q2LCh9/l+hmHY/nkAAAAAqocCEACAWmz//v26//779fnnn9v+Wa1bt9Z9992n/v372/5ZAAAAAKxDAQgAQC1UWlqql19+WePHj7f9gI+OHTvq4YcfVs+ePW39HAAAAAD2oAAEAKAWMU1TX375pcaMGaP8/HxbP6tLly76z3/+oy5dutj6OQAAAADsRQEIAEAtkZWVpYEDB9r+nL9u3brp8ccf18knn2zr5wAAAACoGRSAAACEOI/Ho7Fjx2rq1KkyTdO2zzn99NM1btw4dezY0bbPAAAAAFDzKAABAAhhc+fO1d13363c3FzbPqNTp07673//q86dO9v2GQAAAACChwIQAIAQtGvXLt1+++1aunSpbZ/Rpk0bjR8/Xl27drXtMwAAAAAEHwUgAAAhxDRNvfrqq3riiSdsO923cePGGj9+vC644AJb1gcAAAAQWigAAQAIEVu2bFH//v2VlZVly/pJSUkaN26cBg0aZMv6AAAAAEKTI9gBAACIdBUVFXrooYd05pln2lL+RUVF6V//+pe2bNlC+QcAAABEIHYAAgAQRD///LNGjBihPXv2WL62YRgaPHiwnnzySSUlJVm+PgAAAIDagQIQAIAgME1T9957ryZPnmzL+meeeaZefPFFtWzZ0pb1AQAAANQeFIAAANSwNWvWaNCgQcrOzrZ87WbNmumll15S9+7dLV8bAAAAQO3EMwABAKghZWVleuihh9SrVy/Ly7+YmBg98MADWrVqFeUfAAAAgMOwAxAAgBqwY8cO9e3bVzt37rR87R49emjy5MlKTEy0fG0AAAAAtR87AAEAsNlrr72m0047zfLyLy0tTV9//bVmzpxJ+QcAAADgqNgBCACATXbt2qWrr75aK1assHTdqKgo/etf/9LNN9+s6OhoS9cGAAAAEH4oAAEAsMH8+fPVv39/lZSUWLpu9+7dNWHCBDVv3tzSdQEAAACELwpAAAAs5Ha7NXr0aL333nuWrpuYmKgJEyaob9++lq4LAAAAIPxRAAIAYJFNmzbp2muv1datWy1d9+KLL9Z7773H7b4AAAAAAkIBCACABT799FPdeOONcrlclq2ZkpKiyZMnq1u3bpatCQAAACDycAowAADVUFFRoZtvvlk33HCDpeXfkCFDtHLlSso/AAAAANXGDkAAAAK0Y8cOXX311dqyZYtlayYnJ+v999/XmWeeadmaAAAAACIbOwABAAjAokWL1LVrV0vLvyuuuEIbNmyg/AMAAABgKXYAAgDgB7fbrX//+9968803LVuzTp06euONN3ThhRdatiYAAAAAVKEABADAR+Xl5bryyiu1fPlyy9Y855xz9O677yolJcWyNQEAAADgUBSAAAD4YMOGDerTp49yc3MtWc/hcGj8+PG65pprLFkPAAAAAI6GZwACAHAMn3zyic4991zLyr/MzEz9+OOPlH8AAAAAagQFIAAA/+C5557TqFGjVFlZacl6Q4cO1bJly9SyZUtL1gMAAACAY+EWYAAAjqC4uFgjRozQggULLFkvJiZGU6dOVc+ePS1ZDwAAAAB8RQEIAMBfFBYW6sILL9TmzZstWe+EE07QjBkz1KhRI0vWAwAAAAB/cAswAACHWLNmjTp16mRZ+Tdy5Eh9++23lH8AAAAAgoYdgAAA/P998803Gjp0qFwuV7XXiomJ0SeffKIuXbpYkAwAAAAAAscOQAAAJL355psaPHiwJeVf69attX79el144YUWJAMAAACA6mEHIAAgonk8Ht1///2aNGmSJetddtllmjFjhhISEuR2uy1ZEwAAAACqgwIQABCxysvLdcMNN2j+/PnVXsswDI0bN0433HCDYmNjLUgHAAAAANagAAQARKTCwkJdccUV+u2336q9VmJioqZNm6YzzzzTgmQAAAAAYC0KQABAxNm7d6969+6tHTt2VHutzMxMzZs3Tw0aNLAgGQAAAABYj0NAAAARZcuWLerRo4cl5V+vXr20aNEiyj8AAAAAIY0CEAAQMdasWaPzzjtPubm51V7rnnvu0bRp05SQkGBBMgAAAACwD7cAAwAiwpIlSzR48GBVVFRUax2n06m33npLffr0sSgZAAAAANiLAhAAEPbmz5+v6667Th6Pp1rrJCYm6uOPP9app55qUTIAAAAAsB+3AAMAwtqMGTM0dOjQapd/6enp+uWXXyj/AAAAANQ6FIAAgLD1wQcf6LbbbpNpmtVap1OnTlq4cCGHfQAAAAColSgAAQBh6ZVXXtHdd99d7XWuuOIKzZ8/X/Xq1at+KAAAAAAIAgpAAEDYefnll/Wf//yn2uvccMMNevvtt+Vw8D+XAAAAAGovDgEBAISVp59+Ws8//3y11xk3bpxGjhxpQSIAAAAACC4KQABA2HjuueeqXf45HA698soruuqqqyxKBQAAAADBRQEIAAgLTz31lF544YVqrREVFaUPP/xQPXv2tCYUAAAAAIQACkAAQK33/PPPV7v8S0hI0Jw5c9SpUydrQgEAAABAiKAABADUauPHj9fTTz9drTXq1KmjuXPnqn379halAgAAAIDQQQEIAKi1Xn/9dY0bN65aa6SmpmrBggVq0qSJRakAAAAAILQ4gh0AAIBATJw4UY888ki11mjcuLG+/vpryj8AAAAAYY0dgACAWmfGjBm67777qrVGRkaGFi5cqLp161qUCgAAAABCEzsAAQC1yueff67bbrutWmtkZmbqyy+/pPwDAAAAEBHYAQgAqDWWLl2qkSNHVmuN4447TgsWLFB8fLxFqQAAAAAgtLEDEABQKyxfvlxXX3213G53wGu0bdtWc+fOpfwDAAAAEFHYAQgACHnbtm3TwIED5XK5Al6jaudfbGyshckAAAAAIPSxAxAAENK2bNmiCy64QCUlJQGv0aZNG82dO5fyDwAAAEBEYgcgACBklZaWqm/fvsrPzw94jZYtW2rBggWKi4uzMBkAAAAA1B7sAAQAhKT8/Hz16tVLe/fuDXiNFi1aaO7cuZR/AAAAACIaOwABACHHNE0NHTpUGzduDHiNxo0ba+HChapTp46FyQAAAACg9mEHIAAgpHg8Ht1666364YcfAl4jNTVVX3zxBeUfAAAAAIgdgACAEPP444/ro48+Cnh+cnKyFi5cqMaNG1uYCgAAAABqL3YAAgBCxsyZM/XKK68EPD8+Pl5z5syh/AMAAACAQ1AAAgBCwldffaVbb7014PkxMTGaN2+eTjjhBAtTAQAAAEDtRwEIAAi6HTt26Prrr5fH4wlovmEYmjJlCuUfAAAAABwBBSAAIKj27t2rSy65RBUVFQHNNwxDEydO1LnnnmtxMgAAAAAIDxSAAICgKS0t1cCBA7V///6A13jiiSfUu3dvC1MBAAAAQHihAAQABIVpmrrzzju1du3agNe44447NHr0aAtTAQAAAED4oQAEAATFU089pVmzZgU8v1+/fnrooYcsTAQAAAAA4YkCEABQ47788ktNmDAh4PlnnHGGXn75ZesCAQAAAEAYowAEANSotWvXauTIkQHPb9u2rWbOnKnY2FgLUwEAAABA+KIABADUmL1792rAgAEqLy8PaH5KSoqmT5+uuLg4i5MBAAAAQPiiAAQA1AjTNHXzzTcrOzs7oPlxcXH69NNP1bx5c4uTAQAAAEB4owAEANjONE2NHTtW3333XcBrTJw4Ue3atbMwFQAAAABEBgpAAIDtpk+frg8++CDg+U888YR69eplYSIAAAAAiBwUgAAAW23ZskX33ntvwPOHDx+uG2+80cJEAAAAABBZKAABALbZvXu3Lr300oAP/ejSpYueeOIJi1MBAAAAQGShAAQA2Obuu+9Wbm5uQHMzMjI0ffp0xcbGWpwKAAAAACILBSAAwBbPPfecFixYENDcmJgYzZw5U3Xr1rU4FQAAAABEHgpAAIDlZs+erWeeeSaguYZh6L333lNmZqbFqQAAAAAgMlEAAgAsVVxcrPvuuy/g+Y8++qguuugiCxMBAAAAQGSjAAQAWKakpESXXHKJDh48GND8Xr166aabbrI2FAAAAABEOApAAIBlHnroIa1bty6guW3atNE777wjh4P/aQIAAAAAK/G3LACAJX788UdNmTIloLkxMTGaPXu2EhMTLU4FAAAAAKAABABU24YNG3TVVVfJNE2/5xqGoTfeeEONGjWyIRkAAAAAgAIQAFAtpmnqxhtvVGlpaUDzH374YV1++eUWpwIAAAAAVKEABABUy/PPP68//vgjoLmnnXaabrvtNosTAQAAAAAORQEIAAjYp59+qmeeeSaguQ0bNtT7778vwzAsTgUAAAAAOBQFIAAgICUlJbrrrrsCmutwOPT5558rLS3N4lQAAAAAgL+KCnaAmpafn6+ZM2dqxYoVysnJUWxsrFq3bq1LL71UXbt29Xs9t9ut33//XZs3b9bmzZu1ZcsW7d27V5I0aNAgDRkyxKd1tm7dqtmzZ+u3335TQUGBkpOTdeKJJ6p///7KzMz0OxcA2Mk0TY0ePVoFBQUBzb/nnnu4tgEAAABADYmoAnDHjh168MEHlZ+fL0mKj49XcXGxVq9erdWrV+vyyy/XqFGj/FozOztbDz/8cLVyLV68WC+++KJcLpckKTExUTk5OVq8eLGWLVumu+66S+ecc061PgMArPTcc89p/vz5Ac297LLLdM8991icCAAAAABwNBFTAFZWVuqJJ55Qfn6+WrRoobvvvluZmZkqLy/XnDlzNHXqVH322WfKzMxUr169/Fo7Pj5erVq10nHHHafWrVvrww8/1J49e3yau2PHDm/5d/bZZ2vkyJGqX7++cnNz9fbbb2vZsmWaMGGCMjMzlZ6eHsiXDgCW2r17t5577rmA5jZq1EjvvPMOz/0DAAAAgBoUMQXg/PnztXfvXsXGxuqRRx7xPncqNjZWV199tXJzc/XFF19oypQp6tmzp6KifPtPk5aWpunTpx/2l9nZs2f7nGvq1KlyuVzKzMzU2LFj5XQ6JUn169fXPffco6ysLG3btk1Tp07V/fff78dXDADWq6io0ODBg+XxePye63A49MYbb3ivcwAAAACAmhExh4AsWrRIktS9e/cjPnR+wIABMgxDubm5+u2333xe1+FwBLyTpbi4WD/99JMkqW/fvn/7S7HT6VTfvn0lSStWrFBJSUlAnwMAVrn77ru1bt26gOa+8MILOvvssy1OBAAAAAA4logoAEtLS7Vp0yZJ0imnnHLEMWlpad5bbNesWVMjudauXet97t/RclW9XllZGfBfugHACqtWrdKMGTMCmtu9e3efD0UCAAAAAFgrIgrAXbt2yTRNSVKLFi2OOq7qvZ07d9ZIrqrPqVevnpKTk484Jjk52fvejh07aiQXAPxVcXGxrr/++oDm1qtXTy+99JLFiQAAAAAAvoqIZwDm5uZ6f12/fv2jjqt6Ly8vz/ZMh37OP2Wqej8/P/+YuaZMmaJp06Yd9f3BgweHzQ4ch8Ph/TklJSXIaRAOqm7lT05O9v6DAf7k8Xh03XXXaffu3X7PdTgcWrJkiTp06GBDstDFNQpW4xoFK3GNgtW4RsFqXKdgJa5Rf4qIArCsrMz769jY2KOOq3qvtLTU9kyHfs4/ZTr0/WPlKi4u1v79+4/6fklJSdg9fN8wjLD7mhBcVX/YwP/z5Zdfat68eQHNvemmm3TSSSdZnKj24BoFq3GNgpW4RsFqXKNgNa5TsFKkX6MiogCMFImJiWrYsOFR309ISJDb7a7BRPapOnzFNM2ATiMF/sowDDkcDnk8noj+V6G/Kiws1IgRIwKa2759ez399NNhc93xB9coWI1rFKzENQpW4xoFq3GdgpXC8RoVSDEeEQVgXFyc99fl5eVKSEg44rjy8nJJUnx8fI3kqvqcqs89Gl9zXXvttbr22muP+n52dnaN3d5st5SUFDmdTnk8nrD5mhBcTqdTKSkpys/Pj8jC6khcLpcGDhz4jzuLjyYhIUGfffaZysvLj3mNC0dco2A1rlGwEtcoWI1rFKzGdQpWCsdrVGpqqt9zImL/46HP2Dv0eYB/VfVeTT1joCrXP2U69H2efQCgJn366adasmRJQHPHjh171MONAAAAAAA1KyIKwPT0dO9DH//pJN2q95o3b14juao+5+DBgyooKDjimPz8fOXn50uSMjIyaiQXAJSUlOiBBx4IaG6PHj106623WpwIAAAAABCoiCgA4+Pj1aZNG0nSypUrjzgmOztbO3fulCSdfPLJNZKrQ4cOioqK+sdcq1atkiRFR0erffv2NZILQGRzuVwaOnSocnJy/J6blpam6dOn87BmAAAAAAghEVEASlLPnj0lSUuWLNGBAwf+9v6sWbNkmqbq169fYydWJiQkqEuXLpKkOXPm/O1edLfbrTlz5kiSTj/99KM+uxAArDRjxoyAb/198MEHvf+wAQAAAAAIDRFTAF500UVq3LixysrK9Pjjj2vbtm2S/jxgY+bMmZo7d66kPw/S+OtfXkeOHKk+ffpowoQJR1y7uLhYBQUF3h9VpxSVl5cf9vqRHoR/zTXXKCoqSlu2bNH48eO9DzjNy8vT+PHjtWXLFkVHR+uaa66x6j8FAByVy+XSk08+GdDcq666SkOGDLE4EQAAAACguiJmm0Z0dLQeeughPfjgg9q+fbvuuOMOJSQkqKyszFvYXXbZZerVq5ffaz/55JP6/fff//b67NmzNXv2bO/vBw0a9Le/HGdkZOiOO+7Qiy++qKVLl+q7775TQkKCiouLJUlRUVG64447lJ6e7ncuAPCHx+PRiBEjjrhL+lhatGihV1991fu8VQAAAABA6IiYAlD6s2x7+eWX9fHHH2vFihXKzs5WYmKiWrVqpd69e6tr165BydWjRw81b95cs2bN0u+//66CggLvrcj9+/dXZmZmUHIBiCwffvih5s2bF9DcRx55hPIPAAAAAEKUYZqmGewQqBnZ2dnBjmCZlJQUOZ1Oud1u723TQHU4nU6lpKQoLy/vb8/jjASmaeqUU07Rrl27/J47fPhw/fe//6UAPATXKFgt0q9RsBbXKFiNaxSsxnUKVgrHa1RqaqrfcyLmGYAAgKO75557Air/2rRpQ/kHAAAAACGOAhAAItzs2bP1/vvvBzSXW38BAAAAIPRRAAJABDNNU88//3xAc4cNG6aLLrrI4kQAAAAAAKtRAAJABHvttde0YcMGv+e1atVKzz77LLv/AAAAAKAWoAAEgAi1bNkyPfbYYwHN/c9//kP5BwAAAAC1BAUgAESop556Sh6Px+95/fr149ZfAAAAAKhFKAABIAJ9/fXXWrFihd/zmjZtqldffZXdfwAAAABQi1AAAkCE2bFjh2688caA5j711FOKjo62OBEAAAAAwE4UgAAQYR544AEVFhb6Pe+ss87SxRdfbEMiAAAAAICdKAABIIJs3bpVX331ld/zkpOTNXnyZDmdThtSAQAAAADsRAEIABGisrJS119/vUzT9HvuU089peTkZBtSAQAAAADsRgEIABHiscce09q1a/2el5mZqSuuuMKGRAAAAACAmkABCAAR4ODBg5o4caLf82JiYvThhx8qNjbWhlQAAAAAgJpAAQgAEeDxxx9XeXm53/Puu+8+tW7d2oZEAAAAAICaQgEIAGHuq6++0vvvv+/3vDp16mjEiBE2JAIAAAAA1CQKQAAIY5WVlRo7dmxAc1955RXVqVPH4kQAAAAAgJpGAQgAYeyTTz7R3r17/Z535ZVX6tJLL7UhEQAAAACgplEAAkCYys/P18MPP+z3PIfDEdA8AAAAAEBoogAEgDB10003KScnx+95o0ePVtOmTW1IBAAAAAAIBgpAAAhDv/32m7755hu/57Vr106PPvqo9YEAAAAAAEFDAQgAYejpp58OaN5LL70kp9NpcRoAAAAAQDBRAAJAmPnss8/01Vdf+T3vtNNOU+fOnW1IBAAAAAAIJgpAAAgj+fn5GjNmjN/zEhIS9Prrr9uQCAAAAAAQbBSAABBGZsyYoeLiYr/nPfzww2rZsqX1gQAAAAAAQUcBCABhorS0VM8//7zf89LS0nTdddfZkAgAAAAAEAooAAEgDJimqVtvvVW5ubl+z73vvvsUExNjQyoAAAAAQCigAASAMPDjjz/qs88+83vehRdeqOHDh1sfCAAAAAAQMigAASAMBHKAh2EYeuaZZ2xIAwAAAAAIJRSAAFDLrVu3Tl9++aXf8y655BKlp6fbkAgAAAAAEEooAAGgFissLNSgQYPk8Xj8mpecnKwnn3zSplQAAAAAgFBCAQgAtdiMGTOUlZXl97ynn36a3X8AAAAAECEoAAGgFnvjjTf8npOenq5+/frZkAYAAAAAEIooAAGglvroo4/0v//9z+95N998s5xOpw2JAAAAAAChiAIQAGqhjRs36vbbb/d7Xs+ePTVq1CgbEgEAAAAAQhUFIADUQu+8845cLpdfcwzD0IQJE2QYhk2pAAAAAAChiAIQAGoZt9utadOm+T3voosuUrNmzWxIBAAAAAAIZRSAAFDLPPDAAyovL/drTnR0tO6++26bEgEAAAAAQhkFIADUIl9//bXee+89v+c9+uij6ty5sw2JAAAAAAChjgIQAGqRt99+2+859erV07Bhw2xIAwAAAACoDSgAAaCWyM7O1sKFC/2eN3ToUMXGxtqQCAAAAABQG1AAAkAt4Ha7dcstt/g9r2nTpgHNAwAAAACEDwpAAKgFpk6dGtDuv0mTJik1NdWGRAAAAACA2oICEABCnGmaeuedd/ye1759e3Xq1Mn6QAAAAACAWoUCEABC3Nq1a7Vu3Tq/540aNUqGYdiQCAAAAABQm1AAAkAIq6ys1F133eX3vDPOOEMDBw60IREAAAAAoLahAASAEPbaa69p1apVfs+bOnWqYmJibEgEAAAAAKhtKAABIES5XC699957fs87//zzlZycbEMiAAAAAEBtRAEIACFq+fLlysrK8nveiBEjbEgDAAAAAKitKAABIARVVlbqkUce8XvegAEDdMEFF9iQCAAAAABQW1EAAkAIGj9+vH777Te/5sTFxenll1/m5F8AAAAAwGEoAAEgxJSVlWnixIl+z+vTp4+io6NtSAQAAAAAqM0oAAEgxCxcuFA5OTl+z7v++uttSAMAAAAAqO0oAAEghLjdbk2YMMHveddff71OO+006wMBAAAAAGo9CkAACCETJkzQypUr/ZqTkpKicePG2ZQIAAAAAFDbUQACQIgoLS3VG2+84fe8vn37yul02pAIAAAAABAOKAABIER8+eWXOnjwoN/zhg8fbnkWAAAAAED4oAAEgBAxZcoUv+fccMMN6tChgw1pAAAAAADhggIQAELAxIkTtWTJEr/mNGzYUE8++aRNiQAAAAAA4YICEACCrKysTM8884zf83j2HwAAAADAFxSAABBkc+fOVU5Ojt/zhg0bZkMaAAAAAEC4oQAEgCD7/PPP/Z4zePBgtW3b1oY0AAAAAIBwQwEIAEG0ePFizZ071685jRo10nPPPWdTIgAAAABAuKEABIAgcblcuuOOO2Sapl/zrrjiCsXExNiUCgAAAAAQbigAASBIvvrqK+3evdvveddcc40NaQAAAAAA4YoCEACCxN9bfyXpwgsvVIcOHWxIAwAAAAAIVxSAABAEe/fu9bsATElJ0WuvvWZTIgAAAABAuKIABIAaZpqmRowYoeLiYr/mXXnllUpOTrYpFQAAAAAgXFEAAkAN+/HHH/XTTz/5Pa9///42pAEAAAAAhDsKQACoYdOnT/d7TqdOnXTqqafakAYAAAAAEO4oAAGgBnk8Hi1evNivOXFxcXrttddkGIZNqQAAAAAA4YwCEABq0FNPPaVdu3b5NWfQoEFq06aNTYkAAAAAAOGOAhAAasi2bdv00ksv+T3vggsusCENAAAAACBSUAACQA15//33ZZqmX3OaN2+u888/36ZEAAAAAIBIQAEIADVkwYIFfs/597//LafTaUMaAAAAAECkoAAEgBrw66+/asOGDX7Nufzyy3XFFVfYlAgAAAAAECkoAAHAZkVFRbrmmmvkdrv9mnfZZZfZlAgAAAAAEEkoAAHAZrNmzdLevXv9mpOUlKQLL7zQpkQAAAAAgEhCAQgANps+fbrfc4YOHaqkpCQb0gAAAAAAIg0FIADYyDRNrV271q85bdq00QMPPGBTIgAAAABApKEABAAb/fvf/1ZxcbFfc+68807FxcXZlAgAAAAAEGkoAAHAJj///LNef/11v+d16dLFhjQAAAAAgEhFAQgANnn33Xf9nnPuuecqMzPThjQAAAAAgEhFAQgANvnqq6/8Gh8TE6N//etfNqUBAAAAAEQqCkAAsMGuXbtUUFDg15y7775bnTt3tikRAAAAACBSUQACgMWKioo0cOBAv+f17NnT+jAAAAAAgIhHAQgAFps6dao2btzo15z09HR16tTJnkAAAAAAgIhGAQgAFjJNU5MnT/Z73vDhw+V0Om1IBAAAAACIdBSAAGChoqIibdq0ya85nTt31k033WRTIgAAAABApKMABAAL+XvyryQ9+eSTio2NtSENAAAAAAAUgABgmY0bN+rOO+/0a47D4VCrVq3sCQQAAAAAgCgAAcAyr7/+usrKyvyac/HFF6tBgwY2JQIAAAAAgAIQACxRUlKijz/+2K85hmHo5ptvtikRAAAAAAB/ogAEAAtkZWWptLTUrzkPPvigunbtalMiAAAAAAD+RAEIABaYPHmy33MGDhxoQxIAAAAAAA5naQEYyOmXAFDbffXVV3rjjTf8mpOWlqa0tDSbEgEAAAAA8P9YWgBefPHFOu644/TMM89o//79Vi4NACHr1Vdf9XvO0KFD5XQ6bUgDAAAAAMDhLL8FeNu2bXrggQfUvHlzDRw4UN9++63VHwEAIWPHjh36/vvv/ZqTlpamESNG2JQIAAAAAIDDWVoADhs2THFxcTJNU5WVlZo5c6YuvPBCtW3bVs8995yys7Ot/DgACLpdu3b5PWfKlClq1KiRDWkAAAAAAPg7SwvAiRMnKisrSy+++KJOPPFEmaYp0zS1ZcsW3X///UpPT9eQIUO0aNEiKz8WAILCNM2Abv89+eSTbUgDAAAAAMCRWX4LcHJyssaMGaNff/1Vy5Yt03XXXefdFVhRUaEZM2bo/PPPV7t27fTCCy8oNzfX6ggAUCMmT57s9+FHp512Gs/+AwAAAADUKMsLwEN169ZNkyZNOuKuwE2bNumee+5Rs2bNNHToUC1dutTOKABgKY/Ho9dff93vecOHD7c+DAAAAAAA/8DWArDKX3cFDh061LsrsLy8XNOmTVPPnj11wgkn6KWXXtLBgwdrIhYABGzlypXaunWrX3NOOeUU9evXz6ZEAAAAAAAcWY0UgIfq1q2bJk+erKysLN12223e103T1Pr163XXXXcpPT1dt956q3bv3l3T8QDAJzt37vRrvMPh0LRp0xQTE2NTIgAAAAAAjqzGC0CXy6UZM2aof//+evXVV2UYhkzTlCTv7cElJSV64403dPzxx+vtt9+u6YgA8I/cbrfeeecdv+akpKSoQYMGNiUCAAAAAODoaqwA3Lx5s+677z41a9bMexJwVeF3+umna+LEidq9e7fGjx+v448/3lsE3nTTTZo/f35NxQSAY3rxxRe1YsUKv+Z07drVpjQAAAAAAPwzWwvAyspKTZ8+Xeedd56OP/54Pf/88zpw4IBM01R8fLxuuOEG/fLLL1q+fLmGDRumJk2a6M4779S6des0efJkJSQkyDRNPf3003bGBACfVVRU+L37T5Kuv/56G9IAAAAAAHBsUXYsumnTJr311luaPHmycnJyJMl7m2+7du10880367rrrlNycvJR1xg6dKg2btyoJ598Un/88YcdMQHAb4sWLdKBAwf8mtO7d291797dpkQAAAAAAPwzSwvADz/8UG+99ZaWLFki6f+VftHR0erbt69uvvlm9ezZ0+f1Tj/9dEnylogAEGz+Hv6RkJCg119/XYZh2JQIAAAAAIB/ZmkBeM011xx2qEd6erpGjx6tkSNHqnHjxn6vx2mZAEKJ2+3WRx995Nec5s2bKz4+3qZEAAAAAAAcmy23AF944YW6+eabdfnll8vhCPwxg6effroWLlxoYTIACNz48eP1yy+/+DWnaiczAAAAAADBYmkBeM899+jGG29U69atLVkvJSVFPXr0sGQtAKiOkpISvfnmm37PGz58uPVhAAAAAADwg6UF4H//+18rlwOAkDFv3jzl5+f7NWfw4MHq2LGjTYkAAAAAAPBN4PfnHsGIESM0YsQIrV692q95v//+u0aMGKEbbrjByjgAYJlt27b5Nb5BgwZ67rnnbEoDAAAAAIDvLC0AJ02apMmTJ2vHjh1+zdu9e7cmTZqkSZMmWRkHACxhmqYWL17s15y2bdtykBEAAAAAICRYWgACQDh64403tHz5cr/mnHzyyTalAQAAAADAPyFRALrdbklSVJQthxIDQMCKi4sDupV32LBhNqQBAAAAAMB/IVEAVj1bq27dukFOAgCH+/TTT1VQUODXnMGDB+u4446zKREAAAAAAP6xZcudYRg+jSspKdHKlSv14osvyjAMtW/f3o44ABCw3377za/xTZo00bPPPmtTGgAAAAAA/BdwAfif//xHjz322N9eN01Tffv2DWjNfv36BRoHAGyxadMmv8Z36tRJsbGxNqUBAAAAAMB/1doBaJqmX6//k549e+q2226rThwAsNTnn3+uRYsW+TWHW38BAAAAAKEm4AKwZcuW6tGjx2GvLV68WIZhqEOHDkpNTf3H+Q6HQ0lJScrMzFSvXr106aWXyuEIiUcSAoDKy8t17733+j1vyJAhNqQBAAAAACBwAReAw4YN+9spl1UF3pNPPqk+ffpULxkABNFnn32m7Oxsv+Zcfvnl7AAEAAAAAIQcSw8B6d69uwzDOObuPwAIdf7e+tu4cWO99NJL9oQBAAAAAKAaLC0A/f0LMwCEqgMHDvg1vmfPnkpKSrIpDQAAAAAAgeOhewDwFxs3btT333/v15zGjRvblAYAAAAAgOqhAASAQ7jdbg0fPlxlZWV+zevXr59NiQAAAAAAqJ6AbgF+7LHHvL9+5JFHjvh6oA5dDwBq2oIFC7Rp0ya/5px11lnq0KGDTYkAAAAAAKgewzRN099JDodDhmFI+nO3zJFeD9Sh68Fa/p5oGspSUlLkdDrldruVl5cX7DgIA06nUykpKbryyiv18ccf+zwvOTlZixcvVrNmzWxMh9qGaxSsVnWNysvL489KqDauUbAa1yhYjesUrBSO16hADt8N+BAQ0zSPWPYF0Cd6Vbc8BIDq2rNnj1/jBwwYQPkHAAAAAAhpARWACxcu9Ot1AKgNysvLtXnzZr/mNGzY0KY0AAAAAABYI6ACsEePHn69DgC1wciRI7V//36/5nTr1s2mNAAAAAAAWINTgAFA0po1azRlyhS/5rRv354CEAAAAAAQ8igAAUDSpEmT/BrvdDr11FNP8exSAAAAAEDIC/gQkOrYv3+/li9fLpfLpZNPPlmtW7cORgwA8Prll1/8Gj906FCdffbZNqUBAAAAAMA6lhaAubm53l00vXv31vHHH/+3MY8//riefPJJVVZWel8bOHCg3nvvPcXFxVkZBwB8lp+f79f44447zqYkAAAAAABYy9ICcMaMGbrnnnsUExOjYcOG/e39qVOn6t///rcMw5BpmofN83g8mj59upVxAMAn33zzjXbt2uXXnBYtWtiUBgAAAAAAa1n6DMCFCxdKks455xw1aNDgb+8/8sgjkiTTNHXFFVfozjvvVPPmzWWapj766CMtXbrUyjgAcEzZ2dkaNWrUYf8ocSxpaWk677zzbEwFAAAAAIB1LC0AN27cKMMwjngq5vfff69t27bJMAw98cQTmj17tsaPH6+ffvpJKSkpkqQPPvjAyjgAcExTp05VUVGRX3NuvPFGxcTE2JQIAAAAAABrWVoAZmdnS5LatGnzt/e++eYbSVJsbKzuuOMO7+sNGzbU4MGDZZqmli9fbmUcADimjz/+2K/xPXr00JgxY2xKAwAAAACA9SwtAHNyciRJiYmJf3tv2bJlkv68Pfiv73fs2FGStGPHDivjAMAx7du3z6/xV199tRwOSy+dAAAAAADYytK/xRqGIUnKy8s77HWPx6Mff/xRhmHonHPO+du8qucFlpSUWBkHAP5RWVmZSktL/ZpzpH/gAAAAAAAglFlaADZs2FCStGnTpsNeX758uQoKCiRJXbt2/du8qudvxcfHWxkHAI7KNE3ddNNNfhWA0dHROv30021MBQAAAACA9aKsXKxz587asWOHpk+frscee8z7kPy3335bkhQTE6Ozzjrrb/O2bt0qSWratKmVcfAXTqcz2BFsEa5fF+w1f/58zZ071685ffr0UePGjW1KhHDFNQpWqPo+4vsJVuN7ClbgGgU78X2F6uIa9SdLC8CrrrpKc+bM0c6dO3X++efrmmuu0S+//KLJkyfLMAz16dPniLv8li9fLsMw1L59eyvj4C+qTlsOJ06nMyy/Ltjv/fff92t8amqqnn32Wb7f4BeuUbBa3bp1gx0BYYRrFKzGNQpW4zoFK0X6NcowTdO0ajHTNHXmmWd6n/d36OtxcXH6+eef1aFDh8PmHDx4UI0aNZLL5dJTTz2l+++/36o4+Iu/PpuxNqtbt66cTqfcbrf39nLAV6ZpqlmzZiorK/N5zquvvqrBgwfbmArhhGsUrOZ0OlW3bl0VFBTI7XYHOw5qOa5RsBrXKFiN6xSsFI7XqECKcUt3ABqGoblz52rkyJH69NNP5fF4JEnNmjXTW2+99bfyT5ImTZqkyspKGYahXr16WRkHfxEu3+h/Fa5fF+zjdrv9Kv8kKS0tje81BITvG1jJ7XbzPQVL8f0EK3GNgh34noJVIv0aZWkBKEn169fXrFmzdODAAW3dulWJiYnq0KGDHI4jnzfSoUMHTZw4UYZh6NRTT7U6DgD8zR9//CHDMOTPBuhGjRrZmAgAAAAAAPtYXgBWSUtLU1pa2jHHXXjhhXZFAIC/2b9/vwYNGuRX+de+fXueUQoAAAAAqLWOvC0PAMLUxIkTdeDAAb/mjB49+rDnmgIAAAAAUJtQAAKIGB6PRx988IFfc6688kpdc801NiUCAAAAAMB+tt0CLEl79uzR77//rry8PJ8fuH/dddfZGQlABMvLy9O+ffv8mjNmzBh2/wEAAAAAajVbCsDp06fr6aef1m+//ebXPMMwKAAB2Maf5/5VofwDAAAAANR2lheAt99+u1599VVJgf1lGwDs8tlnn/k1Pi4uTs2bN7cpDQAAAAAANcPSAvDTTz/VK6+84v39GWecoQsuuEDp6emKjY218qMAwC8//fST7r//fr/m9OvXT0lJSTYlAgAAAACgZlhaAL755puSJKfTqUmTJvHgfAAh47XXXvNrV3J8fLxuvfVWGxMBAAAAAFAzLD0F+Oeff5ZhGLr22msp/wCEjIMHD2revHl+zXnrrbd0/PHH25QIAAAAAICaY2kBmJ+fL0k6//zzrVwWAKplz549crvdfs3p1KmTPWEAAAAAAKhhlhaAjRo1kiRFR0dbuSwAVEtUlP9PO4iJibEhCQAAAAAANc/SAvCMM86QJK1bt87KZQEgYKZp6vXXX/drTmZmplJSUmxKBAAAAABAzbK0ALz55ptlmqamTJmiyspKK5cGgIB89NFH+uCDD/yac/3118swDJsSAQAAAABQsywtAM8991zddttt2rp1q4YPH04JCCCoAtn916ZNGw0dOtSmRAAAAAAA1Dz/H4z1D3bs2KGxY8cqNzdX06ZN08qVK3XLLbeoW7duSk1NlcNx7L4xIyPDykgAItimTZv0+++/+zze6XTq448/VlJSko2pAAAAAACoWZYWgC1btvTeNmcYhjZu3Kg777zT5/mGYcjlclkZCUAE27t3r1/j3W639zAjAAAAAADChaUFoPTnLXcAEAr8PZE8OjpaUVFR8ng8NiUCAAAAAKDmWVoADhs2zMrlACBgLpdLL730kl9zevbsyeEfAAAAAICwY2kBOHHiRCuXA4CAvfbaa/rmm2/8mnPzzTfblAYAAAAAgOCx9BRgAAgFLpdL77zzjl9zLrjgAl1xxRU2JQIAAAAAIHgoAAGEnR9//FF79uzxeXxSUpImTpzo00nlAAAAAADUNvxtF0DY2b9/v1/jnU6nEhISbEoDAAAAAEBwWX4KcJWDBw/q7bff1vz587V27Vrl5ubK5XLJ5XIdNm7BggXau3evUlNTdeGFF9oVB0AE8ff0X8o/AAAAAEA4s6UAnDFjhm688UYVFhZKkkzTlKQjnq65Zs0ajR07VvHx8dqzZ4/q1q1rRyQAEaKiokLvvfeeX3POOeccm9IAAAAAABB8lt8C/P7772vIkCEqKCiQaZpq3Lix2rZte9Txw4cPV1RUlMrKyvTZZ59ZHQdAhHn22We1dOlSv+aMGDHCpjQAAAAAAASfpQVgVlaWbrrpJpmmqaZNm+qrr77S7t279cwzzxx1TkpKirp37y7pz9uBASBQpaWlmjRpkl9zhg4dqlNPPdWeQAAAAAAAhABLC8BXXnlFZWVlio+P17fffqtevXr5NO/000+XaZpas2aNlXEARJhvvvlGBw8e9Hl8kyZN9N///te+QAAAAAAAhABLC8CvvvpKhmFoyJAhOv74432ed9xxx0mStm/fbmUcABFmz549fo1PSEhQVJRtZyEBAAAAABASLC0At23bJkk6++yz/ZqXnJwsSd5DQwAgELGxsX6Nj4uLsykJAAAAAAChw9ICsLi4WJKUlJTk17zS0lJJ/GUcQOBcLpe++OILv+Z069bNpjQAAAAAAIQOSwvABg0aSJL27dvn17xNmzZJktLS0qyMAyCC/Pe///X7ICFO/wUAAAAARAJLC8AOHTpIkpYsWeLXvM8++0yGYXASJ4CAFBUV6e233/ZrzujRo9WmTRubEgEAAAAAEDosLQAvueQSmaapOXPmeHf1Hcv06dO1evVqSdKll15qZRwAEeLzzz9XUVGRz+Pbtm2rxx57zMZEAAAAAACEDksLwJEjR6p+/fqqqKhQnz59vIeCHM2MGTM0atQoGYahpk2basiQIVbGARAh/D1BvH79+nI6nfaEAQAAAAAgxERZuVjdunX1+uuva9CgQdq4caNOPPFE9evX77CTOV999VXt3LlTX375pX777TeZpimn06n33ntP0dHRVsYBECGiovy7lPk7HgAAAACA2szyvwVfddVVOnjwoMaMGaPS0lJ9+OGHkiTDMCRJt99+u3esaZqKiYnRm2++qQsuuMDqKAAigGma2rBhg19zOnfubFMaAAAAAABCj6W3AFcZNWqUfvrpJ/Xt21eGYcg0zb/9kP585t+PP/6oYcOG2REDQAR488039cknn/g1Z+jQofaEAQAAAAAgBNl2H9xJJ52kWbNmKT8/X8uWLdP27dt18OBBJSUlKT09Xeecc47S0tLs+ngAEaC4uFjPPvusX3OGDx+uzMxMmxIBAAAAABB6bH8QVnJyMqf7ArDFnDlzVFBQ4PP4k046SU899ZSNiQAAAAAACD2WFoA7duyQJDVs2FBxcXE+zysvL9e+ffskSRkZGVZGAhDG1qxZ49f4zMxMDhsCAAAAAEQcS58B2LJlS7Vq1UpfffWVX/MWLVrknQsAvvJ4PLaOBwAAAAAgHFh+CEjVAR81PRdA5KmsrPRrPP/IAAAAAACIRLacAgwAdvvmm2/04Ycf+jVnyJAhNqUBAAAAACB0hUQBWFhYKElKSEgIchIAtUFFRYXuuOMOv27pvfzyy9W6dWsbUwEAAAAAEJpCogD85ptvJElNmjQJchIAtcHcuXO1f/9+n8e3a9dOL730ko2JAAAAAAAIXQGfArx48WItXrz4iO9Nnz5dq1ev/sf5pmmquLhYK1eu1MKFC2UYhs4888xA4wCIIFX/aOCrnj17KikpyaY0AAAAAACEtoALwEWLFumxxx772+umaWrGjBl+rWWapqKjo3X77bcHGgdABKl6bICvSkpKbEoCAAAAAEDoq9YtwKZpHvbjaK8f68cpp5yizz77TKecckq1vyAA4c/f3Xz169e3KQkAAAAAAKEv4B2Aw4cPV8+ePb2/N01T5513ngzD0OOPP66zzjrrH+c7HA4lJSUpMzNT9erVCzQGgAiTlZV11McPHM1ll11mUxoAAAAAAEJfwAVgixYt1KJFiyO+d+KJJ6pHjx4BhwKAIzFNU8OHD/frAJAuXbro5JNPtjEVAAAAAAChLeAC8EgWLlwo6c8CEACstmzZMq1atcrn8Q0aNNArr7xiYyIAAAAAAEKfpQUgu/4A2OnDDz/0a/wtt9yiVq1a2ZQGAAAAAIDaoVqHgABATdq+fbtf40tLS+0JAgAAAABALWLpDsC/8ng82rJli/Ly8lRWVubTnO7du9sZCUAtFhMT49f4qChbL3EAAAAAANQKtvzt+Pvvv9d///tfff311z4Xf5JkGIZcLpcdkQDUcqZpqqKiwq85p5xyik1pAAAAAACoPSwvAJ9//nndf//9Mk1TpmlavTyACDVu3DitWLHC5/EtW7bkuaQAAAAAAMjiAnDp0qW69957ZRiGTNNUs2bNdO655yo9PV2xsbFWfhSACLJ161ZNmDDBrzn//ve/5XDwmFMAAAAAACwtAF988UXvrx9//HH961//4i/gAKpt8uTJfu0ofuihh3TZZZfZmAgAAAAAgNrD0gLwhx9+kGEY6tu3rx588EErlwYQwZYsWeLX+NTUVJuSAAAAAABQ+1i6PS8nJ0eSdPnll1u5LIAIV1JSYut4AAAAAADCmaUFYNWum8TERCuXBRDhUlJS/BqflpZmUxIAAAAAAGofSwvATp06SZK2bNli5bIAItimTZu0adMmn8fXqVNHvXr1sjERAAAAAAC1i6UF4A033CDTNDV9+nQrlwUQoUpKSjR48GAVFBT4POfaa69VUlKSjakAAAAAAKhdLC0A+/XrpwEDBujXX3/VfffdZ+XSACLQxx9/rP/9738+jz/jjDP0r3/9y8ZEAAAAAADUPpaeAixJU6ZMUWxsrJ5//nn98ssvuvPOO9WtWzdO5QTgt2nTpvk1/tFHH1V8fLxNaQAAAAAAqJ0sLQCdTqf316ZpatGiRVq0aJHP8w3DkMvlsjISgFps8+bNfo3fvXu3TjvtNJvSAAAAAABQO1laAJqm+Y+/BwB/HPqPCr5wOCx9qgEAAAAAAGHB0gKwe/fuMgzDyiUBRLDU1FTl5OT4PP7EE0+0MQ0AAAAAALWTpQWgP7f7AsA/efXVV7Vhwwafx/fo0UOZmZk2JgIAAAAAoHbifjkAIee3337To48+6vP4qKgo3XvvvfYFAgAAAACgFqMABBBy3n33XZ/HGoahN998U2eccYaNiQAAAAAAqL0oAAGEnE8//dTnsaZp6rjjjrMxDQAAAAAAtRsFIICQUlFRocLCQr/m+HNQCAAAAAAAkSagQ0BGjBgh6c9b7w69Va/q9UD9dT0AkSc6OlqxsbEqLy/3eU5SUpKNiQAAAAAAqN0CKgAnTZokwzAkHf6srkNfDxQFIBDZSkpKVK9ePe3bt8+n8Q0bNtQJJ5xgcyoAAAAAAGqvgApA6c/nbh2p7DNNM+Aw1S0PAdRulZWVuu6663wu/yRp6NChiomJsTEVAAAAAAC1W0AF4LZt2/x6HQB8MXPmTC1ZssTn8SeccIJuu+02GxMBAAAAAFD7BVQAtmjRwq/XAcAXEydO9HlsXFycPvroI57/BwAAAADAMQR8C3BNyc3N1e+//y5J6t69e5DTALBLfn6+Vq1a5fP4srIylZSU2JgIAAAAAIDwEPIF4NKlS9WvXz85HA65XK5gxwFgk0DKvOLiYhuSAAAAAAAQXhzBDuCr6hwuAiD01atXT06n0685qampNqUBAAAAACB81JoCEEB427Nnj2JjY30ef/bZZ6thw4Y2JgIAAAAAIDxQAAIIuuzsbF155ZV+3QY8evRoGxMBAAAAABA+KAABBN0bb7yhnTt3+jx+9OjRuvjii21MBAAAAABA+KAABBBUFRUVmjp1qs/j09LS9MQTT8gwDBtTAQAAAAAQPigAAQTV9u3blZ2d7fP4AwcOqLCw0MZEAAAAAACEFwpAAEFVXl5eI3MAAAAAAIhUFIAAgqpp06Z+3c6bkJCglJQUGxMBAAAAABBeKAABBNWWLVsUFRXl8/irrrrKr/EAAAAAAEQ6CkAAQbNlyxYNGjRIlZWVPo2PiorSyJEjbU4FAAAAAEB4oQAEEDTjx4/3+UAPh8OhV155Re3atbM5FQAAAAAA4YUCEEBQ5OXl6ZNPPvF5fJs2bTRgwAD7AgEAAAAAEKYoAAEExdq1a1VRUeHz+K1bt8o0TRsTAQAAAAAQnigAAQSFr8/9q+JyuSgAAQAAAAAIQMgfpZmRkaFhw4YFOwYAi7Vo0cLv8Q4H/2YBAAAAAIC/Qr4A7Ny5syZOnBjsGAAstmPHDjmdTrndbp/GDx482OZEAAAAAACEJ7bTAKhxa9as0bXXXutz+VevXj0NHTrU5lQAAAAAAIQnS3cAtmrVKqB5DodDderUUf369XXyySfr3HPPVe/evbndDwhT48aNU1lZmU9j4+Pj9f777ystLc3mVAAAAAAAhCdLC8Dt27fLMIzDHtRvGIb316Zp/u33fx23aNEivfjii8rIyNBbb72lCy64wMqIAIJsx44dWrBggc/ju3Tpom7dutmYCAAAAACA8GbpFruMjAxlZGSoWbNm3kLPNE2Zpqnk5GQ1a9ZMycnJ3tekP4u/Zs2aqWnTpoqLi/O+97///U+XXHKJZs6caWVEAEG2atUqv07z3bhxo41pAAAAAAAIf5YWgNu3b9eyZcvUsmVLmaaps88+Wx9//LFyc3OVm5urnTt3en89c+ZMnX322TJNUy1bttSKFStUXFysX3/9VaNGjZIkeTwejRgxQjk5OVbGBBBElZWVfo13uVw2JQEAAAAAIDJYWgCWl5frsssu0/fff6+HH35YS5YsUb9+/VSvXr3DxtWrV0/9+/fXkiVL9OCDD2rZsmW67LLLVFFRoRNPPFFvvvmmXn75ZUlScXGx3nzzTStjAgiijIwMv8Y3b97cpiQAAAAAAEQGSwvAN998U6tXr1bXrl31n//8x6c5jz/+uLp27arVq1cfVvTdeuut6tSpkyTp66+/tjImgCAqLy/364CfwYMH25gGAAAAAIDwZ2kB+OGHH8owDA0aNMiveYMGDZJpmvrwww8Pe71v374yTVPr16+3MiaAIFmzZo2uueYaeTwen8Y3atRIV111lc2pAAAAAAAIb5YWgJs3b5YkNWnSxK95VeM3bdp02OvHHXecJCkvL8+CdACC7ZFHHlFpaalPY+vWraupU6cqKSnJ5lQAAAAAAIQ3SwvA4uJiSVJWVpZf8/bs2SNJKikpOez12NhYSVJcXJwF6QAE04YNG/T999/7PP6yyy7TySefbGMiAAAAAAAig6UFYNXD+v96K++xVI1PT08/7PXs7GxJUoMGDSxIByCYfvjhB7/G//HHHzYlAQAAAAAgslhaAF500UUyTVMrVqzQgw8+6NOcBx54QD/++KMMw9DFF1982Hu//vqrJP9vKQYQeny99bdKWVmZTUkAAAAAAIgslhaA99xzjxITEyVJTz/9tLp3765Zs2YpNzf3sHG5ubn6+OOPdc455+iZZ56RJCUkJGjs2LGHjZs3b54Mw9Dpp59uZUwAQdC4cWO/xlP8AwAAAABgjSgrF8vIyNDEiRM1ZMgQud1uLVu2TMuWLZP05wP9ExISVFJSooKCAu8c0zQVFRWlSZMmKSMjw/v6kiVLtH//fiUkJOiKK66wMiaAIGjZsqUcDofPJwBfeeWVNicCAAAAACAyWFoASn/+pT01NVUjR47U1q1bva/n5+eroKBApmkeNr5169Z655131KNHj8Ne7969u4qKiqyOByAINm/erIEDB/pc/jVu3Fh9+vSxORUAAAAAAJHB8gJQknr27KkNGzbo008/1SeffKKffvpJWVlZKi4uVmJiopo2baouXbroiiuu0BVXXCGn02lHDAAhYuzYscrLy/NpbJ06dfT+++8rPj7e5lQAAAAAAEQGWwpASXI6nerXr5/69etn10cAqAXWrVun77//3ufxN998szp37mxjIgAAAAAAIoulh4AAwF999dVXfo2vOv0bAAAAAABYgwIQgK3y8/P9Gn/oIUEAAAAAAKD6KAAB2ColJcWv8fXq1bMnCAAAAAAAEcq2ZwCuXr1a8+bN0++//668vDyVlZUdc45hGPr222/tigQgCM4++2y/xvfu3dumJAAAAAAARCbLC8A9e/bo+uuv19dff+3XPNM0ZRiG1XEABFFOTo7GjBnj8/i0tDT16dPHxkQAAAAAAEQeSwvAoqIinXvuudq0aZNM07RyaQC10B133KENGzb4NDY6Olqvvfaa4uLibE4FAAAAAEBksfQZgC+88II2btwoSUpPT9frr7+uzZs3q6ysTB6P55g/3G63lXEABNGWLVs0f/58n8ePGzdOPXv2tC8QAAAAAAARytIdgLNnz5YkNW7cWD/99JMaNWpk5fIAapGPP/7Yr/GbN2+2KQkAAAAAAJHN0h2AW7ZskWEYuuWWWyj/gAi3e/duv8ZnZWXZlAQAAAAAgMhmaQHo8XgkSccff7yVywKohfx9lh/P/gMAAAAAwB6WFoAtWrSQJBUWFlq5LIBaqGvXrraOBwAAAAAAvrG0AOzTp49M09SyZcusXBZALeN2u7VgwQKfx9etW1f9+/e3MREAAAAAAJHL0gJwzJgxSklJ0dSpU7V+/XorlwZQizz++OOaPn26z+MfffRRJSYm2pgIAAAAAIDIZWkB2KRJE02fPl1RUVG64IILtGTJEiuXB1AL7N27V2+++abP4x999FENHTrUxkQAAAAAAES2KCsXe+yxxyRJvXr10pw5c3TuueeqU6dO6tatm1JTU+VwHLtvfOSRR6yMBKCGTZs2TS6Xy+fxaWlpNqYBAAAAAACWFoCPPvqoDMOQJBmGIdM0tXr1aq1evdrnNSgAgdrt119/9Wv8mjVrdPXVV9uUBgAAAAAAWFoASpJpmv/4+39SVR4CqL08Ho9f491ut01JAAAAAACAZHEBuHDhQiuXA1ALZWZm+jW+VatWNiUBAAAAAACSxQVgjx49rFwOQC3Upk0bn8fGxsbqyiuvtDENAAAAAACw9BRgAJHt66+/1r333uvz+Ouuu07169e3MREAAAAAAKAABGCJ4uJi3XLLLT6fAHzRRRfp0UcftTcUAAAAAACgAARgjVmzZungwYM+jTUMQ48//rhiYmLsDQUAAAAAAAJ7BuCOHTu8v87IyDji64E6dD0AtcfcuXN9Hmuapr7++muNHj3axkQAAAAAAEAKsACsOuXTMIzDbvdr2bKlDMMIOMxf1wNQe+Tl5fk13tfdggAAAAAAoHoCKgBN0wzoPQDhq27duraOBwAAAAAAgQmoABw2bJhfrwMIf+eff74WLVrk8/gLLrjAvjAAAAAAAMAroAJw4sSJfr0OILwdPHhQs2bN8nn8ueeeq9atW9uYCAAAAAAAVOEUYADVYpqmRowYoVWrVvk0vkGDBnr66adtTgUAAAAAAKpQAAKolqVLl2rp0qU+jY2Li9Onn36qVq1a2ZwKAAAAAABUCegW4NosPz9fM2fO1IoVK5STk6PY2Fi1bt1al156qbp27Rrwui6XS59//rkWL16srKwsSVKzZs3Uo0cP9e7dW1FRR/5PPWHCBC1YsOAf187IyNArr7wScDbATpMnT/Z5bFlZmYqLi21MAwAAAAAA/iqiCsAdO3bowQcfVH5+viQpPj5excXFWr16tVavXq3LL79co0aN8nvd0tJSPfzww9q4caMkKSYmRpK0efNmbd68WcuWLdNjjz2muLi4o64RExOjhISEI77HaakIZX/88Ydf43///Xd17tzZpjQAAAAAAOCvbCkA3W63PvvsM82bN0+///678vLyVFZWdsx5hmFoy5YtdkRSZWWlnnjiCeXn56tFixa6++67lZmZqfLycs2ZM0dTp07VZ599pszMTPXq1cuvtV977TVt3LhRiYmJuv322707CZcvX66XXnpJ69ev1+uvv6677rrrqGucffbZuvPOO6vzJQJB4fF4bB0PAAAAAACqx/ICcO3atRo4cKDWrl172OumaR5zrmEYVsfxmj9/vvbu3avY2Fg98sgjSktLkyTFxsbq6quvVm5urr744gtNmTJFPXv2POotu3+1bds2LVmyRJI0ZswYdevWzftet27d5PF49Mwzz2jRokXq37+/WrRoYf0XBwTRcccdp23btvk1HgAAAAAA1BxLC8ADBw7o/PPP1/79+72FX1RUlFJTUxUbG2vlR/lt0aJFkqTu3bt7y79DDRgwQPPmzVNubq5+++03n29RXLx4sUzTVJMmTQ4r/6qceeaZatKkifbs2aPFixfruuuuq9bXAYSak08+WV9//bVPY1u1anXE/z8BAAAAAAD2sbQAfPbZZ7Vv3z4ZhqFOnTpp3LhxOvfcc73PxAuW0tJSbdq0SZJ0yimnHHFMWlqa0tPTtXPnTq1Zs8bnAvDXX3+VJHXu3PmIOxgNw1Dnzp21Z88e71ggXMyePVvPP/+8z+PvuusuORwcPg4AAAAAQE2ytACcO3eupD9v8fvuu++OeqhFTdu1a5d3R+I/3YLbokUL7dy5Uzt37vRpXdM0tWvXrmOum5GRIUn/uO6vv/6qG2+8UQcOHFBMTIyaNGmiU089Vb1791ZKSopPeYCalJWVpTFjxvh0e78kjR07VoMGDbI5FQAAAAAA+CtLC8D//e9/MgxDo0ePDpnyT5Jyc3O9v65fv/5Rx1W9l5eX59O6paWl3sNNfFm3tLRUpaWlio+P/9uY7OxsOZ1OxcfHq6SkRFu2bNGWLVs0b9483XfffTr55JOPmWfKlCmaNm3aUd8fPHiwhgwZcsx1aoOqXWQOh4OCNEheeOEFlZeX+zQ2LS1NTz31lJxOp82pAle1gzc5OdnnUhM4Gq5RsBrXKFiJaxSsxjUKVuM6BStxjfqTpQVgdHS0SktL1bJlSyuXrbZDTyD+p2cRVr1XWlrq07qHjvNl3ao5hxaArVu3Vtu2bdWlSxc1aNBADodDJSUlWrFihSZNmqTc3Fw99dRTGj9+vJo1a/aPeYqLi7V///6jvl9SUhLSBUwgDMMIu6+ptpgxY4bPYw8cOKAVK1bo7LPPtjGRNbhFGVbiGgWrcY2ClbhGwWpco2A1rlOwUqRfoywtAFu1aqXVq1cftuMO/+zyyy//22sJCQnq2bOnOnTooDvvvFNFRUX68MMPdc899/zjWomJiWrYsOFR309ISJDb7a525lDgcDhkGIZM05TH4wl2nIi0b98+v8ZnZWWF9PefYRhyOBzyeDwR/a9CsAbXKFiNaxSsxDUKVuMaBatxnYKVwvEaFUgxbmkBOGDAAK1atUrffPONRo0aZeXS1RIXF+f9dXl5+VFvT666nfFIt+geyaHj/ulWyEPf83VtSWrYsKF69+6tGTNm6Oeff5bH4/nHxvraa6/Vtddee9T3s7Ozfb69OdSlpKTI6XTK4/GEzddU28THx6uoqMjn8aH+fyun06mUlBTl5+eHdFGJ2oFrFKzGNQpW4hoFq3GNgtW4TsFK4XiNSk1N9XuOpfsfb731VjVv3lyzZs3SsmXLrFy6Wg59Pt8/7U6ses/XZwzEx8d7Cz1f1j10vK/atm0r6c/bdwsLC/2aC9ipe/fuPo+Nj49Xly5dbEwDAAAAAACOxtICMDk5WZ988olSU1PVu3dvvf/++yGxXTc9Pd370McdO3YcdVzVe82bN/dpXcMwlJ6ebvm6QKgrKytTdna2z+MHDBig5ORkGxMBAAAAAICjCegW4BEjRvzj+yeccIIWLFig66+/Xvfee6+6dOmi1NTUYz5w0TAMvfvuu4FE+kfx8fFq06aNNm7cqJUrV+rMM8/825js7Gzt3LlTknw6cbdKx44dtWnTJq1ateqoY1avXu0d66+NGzdK+vNrqFOnjt/zAat5PB6NGjVKixcv9ml806ZNdf/999ucCgAAAAAAHE1ABeCkSZO8O+qOpur97OxszZs3z+e17SgAJalnz57auHGjlixZooEDByotLe2w92fNmiXTNFW/fn2ddNJJPq/bvXt3zZo1S1lZWfrhhx/UrVu3w97//vvvlZWVJcMw1LNnz8PeM03zH/87HjhwQF988YUk6bTTTov4E2sQGubNm6cvv/zSp7H169fXJ598osaNG9ucCgAAAAAAHE3AjZJpmpb/sNNFF12kxo0bq6ysTI8//ri2bdsm6c8DOmbOnKm5c+dK+vMgjaiow3vRkSNHqk+fPpowYcLf1s3MzPQ+C+3ll1/W8uXLvV/P8uXL9corr0j6s4DMyMg4bO6iRYs0btw4LV++XAUFBd7XS0tLtXjxYt1///0qLCxUfHy8Bg8ebNl/C6A6Jk6c6PNYwzDUtGlTG9MAAAAAAIBjCWgHYFV5VptER0froYce0oMPPqjt27frjjvuUEJCgsrKyrzPKbzsssvUq1cvv9e+5ZZbtGfPHm3cuFFPPfWUYmJiJEkVFRWSpHbt2unmm2/+2zyPx6MffvhBP/zwg6Q/b/ONiopScXGxN1NycrLuvfde77MGgWDyeDz67rvvfB6fk5Oj9evX+3VbPQAAAAAAsFZABWCLFi2szlEjMjIy9PLLL+vjjz/WihUrlJ2drcTERLVq1Uq9e/dW165dA1o3Pj5eTz/9tD7//HMtXrxYWVlZkqTWrVurZ8+e6t279992FUrSSSedpGuvvVbr1q3T7t27VVBQoJKSEiUmJqp58+Y67bTTdNFFF/HsP4SM8vJyv49NLyoqsikNAAAAAADwhWHafe8tQoY/p7aGupSUFDmdTrndbuXl5QU7TsQwTVOtW7dWYWGhz3N++OEHHXfccTamsobT6VRKSory8vL8LjmBv+IaBatxjYKVuEbBalyjYDWuU7BSOF6jUlNT/Z7DqRIAfGYYhnr37u3z+I4dO6p169Y2JgIAAAAAAMcS0C3A1TV79mwtXbpULpdLnTp10qBBg5SQkBCMKAD8sH79en3zzTc+jx89evQxTwwHAAAAAAD2srQA3LRpk8aOHStJevjhh9WlS5fD3q+oqFDv3r21YMGCw15/+umnNX/+fGVmZloZB4CFsrOzddVVV/l8K/mQIUN09dVX25wKAAAAAAAci6W3AM+YMUOff/65vvvuuyOe+vnkk0/q22+/lWmah/3YvHmz+vXr5z35FkDoeffdd7V3716fxnbr1k0vvPACu/8AAAAAAAgBlhaAy5YtkyT16tVLMTExh71XXl6uF198UYZhKDk5WS+88II++eQTXXrppZKk3377TR999JGVcQBYxOPx6IMPPvB5/Pr16+VyuWxMBAAAAAAAfGVpAbhjxw4ZhqHTTjvtb+999dVXKigokPTnTqI77rhDffr00Zw5c7yHBMycOdPKOAAssn//fu3bt8/n8Xl5edq1a5eNiQAAAAAAgK8sLQCrng2Wnp7+t/cWLVokSapfv7769evnfd3pdGrw4MEyTVOrVq2yMg4AiwRyVDq39AMAAAAAEBosLQDz8vIk6W+3/0rS999/L8MwdP755//tuWCtWrWSJJ+fLwagZqWlpSkpKcnn8XFxcWrSpImNiQAAAAAAgK8sLQDj4uIkSQcOHDjs9dLSUq1cuVKSdOaZZ/5tXlWxUFFRYWUcABaJiYnReeed5/P4/v37KzEx0cZEAAAAAADAV5YWgFW3/v7yyy+HvT5//nxVVlZKOnIBWLVzsE6dOlbGAWCR2bNna+7cuT6NjY2N1U033WRzIgAAAAAA4CtLC8Bu3brJNE3NnDnTewCAy+XS+PHjJf35/L9TTjnlb/PWrVsnScrIyLAyDgALrF69WrfccotPzwGMjo7Wm2++qfbt29dAMgAAAAAA4AtLC8Drr79eklRYWKhOnTpp0KBBOvnkk/Xdd9/JMAxdd911cjj+/pFLly6VYRjq2LGjlXEAWOCVV16Ry+XyaeyAAQPUu3dvmxMBAAAAAAB/WFoAnn322Ro9erRM01Rubq4++ugjrV+/XtKftwc/+OCDf5uzdetW7y3DR7o9GEDw5OXl+XzrryR98803nP4LAAAAAECIsbQAlKTXX39dEyZM0AknnKCYmBilpKRo0KBB+u6771S/fv2/jX/ttde8v77ooousjgOgGnbs2OHz7j9Jys7OVkFBgY2JAAAAAACAv6KsXtAwDN1+++26/fbbfRp/zz33aMyYMTIMg2cAAiHG6XTWyBwAAAAAAGAfywtAfzVu3DjYEQAcRWZmphITE1VcXOzT+JYtWyopKcnmVAAAAAAAwB+W3wIMIHwkJibqtNNO83n8sGHDZBiGjYkAAAAAAIC/KAABHNW4ceO0ePFin8ZmZGRo6NChNicCAAAAAAD+CugW4Pfff9/76+uuu+6Irwfq0PUABM+nn36q8ePH+zS2WbNm+r//+z8lJyfbnAoAAAAAAPgroAJw+PDhMgxDhmEcVthVvR6ov64HIHheffVVn8deddVVat26tY1pAAAAAABAoAK+Bdg0TZmmedTXA/0BIPg2btyolStX+jz+k08+sS8MAAAAAAColoB2AE6cONGv1wHULjt27PBr/M6dO2WaJgeAAAAAAAAQggIqAKv+kn/eeecd9vqwYcOqnwhA0MXExPg1Pjo6mvIPAAAAAIAQVa1nAM6ePVvp6ene10eMGCFJuv3229WpUydLAgKoeSeeeKJiY2NVXl7u0/jTTjvN5kQAAAAAACBQAT8D8EgmTZqkyZMn+337IIDQkpKSog4dOvg8fvjw4faFAQAAAAAA1RJQARgV9efGQV93BwGoPTwej26//XatWrXKp/Fdu3ZV7969bU4FAAAAAAACFVABWL9+fUnS+vXrLQ0DIPjeffddTZ8+3aexp59+uj744APvPwoAAAAAAIDQE9Df2jt37qz58+fr5ZdfVtu2bdW5c2fFxcV539+/f3/AtwFnZGQENA9A9bndbr3xxhs+j+/fv7/q1atnXyAAAAAAAFBtARWA119/vebPn6+cnBwNGTLksPdM09SNN94YUBjDMORyuQKaC6D6li9f7ld5/3//93+64YYbbEwEAAAAAACqK6BbgK+++mrdcsstMk3zsB9V/vq6Pz8ABM+uXbtsHQ8AAAAAAGpewA/ueuWVVzRy5EjNnTtXO3fuVHl5uSZPnizDMNSzZ09u5QVqoZiYGL/Gx8bG2pQEAAAAAABYpVpP7u/UqZM6derk/f3kyZMlSXfccYf69OlTrWAAat6pp54qwzB83o3bpUsXmxMBAAAAAIDqCugWYADhKT09XW3btvV5/PXXX29jGgAAAAAAYIVq7QD8q4ULF0qSTjzxRCuXBVAD3G63brzxRm3YsMGn8X369NEZZ5xhcyoAAAAAAFBdlhaAPXr0sHI5ADVowoQJmjNnjk9jL7vsMr366qsyDMPmVAAAAAAAoLq4BRiAysrK9NZbb/k8/sorr1RcXJyNiQAAAAAAgFUoAAHo66+/Vm5urs/jp0+fbmMaAAAAAABgJQpAANqxY4et4wEAAAAAQPBQAAJQdHS0reMBAAAAAEDwUAAC0KmnnmrreAAAAAAAEDwUgADUqVMnpaen+zx++PDh9oUBAAAAAACWogAEIpzb7daYMWO0a9cun8YPGTJE7du3tzkVAAAAAACwCgUgEOGeffZZffTRRz6NHTBggJ599lmbEwEAAAAAACtRAAIRrKioSG+++abP42+55RbFxMTYmAgAAAAAAFiNAhCIYHPmzFFRUZHP46dNm2ZjGgAAAAAAYAcKQCCCbdmyxdbxAAAAAAAg+CgAgQjmcPh3CTAMw6YkAAAAAADALhSAQAQ78cQTbR0PAAAAAACCjwIQiGCXXHKJkpOTfRprGIaGDh1qcyIAAAAAAGA1CkAgQpmmqSeffFL5+fk+jb/mmmuUmZlpcyoAAAAAAGA1CkAgQk2YMEGvv/66T2Mvu+wyPfPMMzYnAgAAAAAAdqAABCJQYWGhJkyY4NPY6OhoPffcc4qJibE3FAAAAAAAsAUFIBCBZs6cqZKSEp/GVlZW6qOPPrI5EQAAAAAAsAsFIBCBfv31V7/G//bbbzYlAQAAAAAAdqMABCKQ2+22dTwAAAAAAAgdFIBABGrVqpWt4wEAAAAAQOigAAQi0MCBA+V0On0aaxiGBg0aZHMiAAAAAABgFwpAIAJ9/fXXMk3Tp7FXXnmlMjIybE4EAAAAAADsEhXsAABq1tSpUzV27Fifxp511ll69tlnbU4EAAAAAADsRAEIRJCioiI99NBDPo1t0KCBPvzwQ8XHx9ucCgAAAAAA2IlbgIEI8tFHH6moqMinsTk5OVqxYoXNiQAAAAAAgN0oAIEIsnTpUr/GL1myxKYkAAAAAACgplAAAhGkpKTE1vEAAAAAACD0UAACEaRRo0a2jgcAAAAAAKGHAhCIIP379/d5rGEY6tu3r31hAAAAAABAjaAABCJIfHy8YmNjfRp78cUXq2XLlvYGAgAAAAAAtqMABCLEsmXLNGDAAJWXlx9zbOvWrTV+/PgaSAUAAAAAAOwWFewAAOxXWlqqUaNGqays7JhjW7Rooblz56pBgwY1kAwAAAAAANiNHYBABPjkk0904MABn8ZmZWXJ7XbbnAgAAAAAANQUCkAgAsyZM8fnsZWVlZo3b56NaQAAAAAAQE2iAAQiQHZ2tq3jAQAAAABA6KIABCJAUlKSreMBAAAAAEDoogAEIkDPnj39Gn/uuefaEwQAAAAAANQ4CkAgAvTp00dOp9OnsWeffbbatm1rcyIAAAAAAFBTKACBMJeVlaUhQ4b4dLJv3bp1NW7cuBpIBQAAAAAAagoFIBDGXC6XhgwZoi1bthxzbGpqqmbNmqV27drVQDIAAAAAAFBTKACBMDZ//nz98ccfPo1NSUlRx44dbU4EAAAAAABqGgUgEMamTJni89hNmzZpxYoVNqYBAAAAAADBQAEIhLFNmzbZOh4AAAAAAIQ+CkAgjBmGYet4AAAAAAAQ+igAgTB2wgkn2DoeAAAAAACEPgpAIIwNHTrU57EdO3bUySefbGMaAAAAAAAQDBSAQJhyuVyaP3++T2MNw9D999/PLcAAAAAAAIShqGAHAGA90zQ1duxYTZs27ZhjHQ6Hnn32WV144YU1kAwAAAAAANQ0dgACYWj58uU+lX+SdNlll+m6666zOREAAAAAAAgWCkAgDE2cONHnsd9++60KCwttTAMAAAAAAIKJAhAIQ0uWLPF5bHFxsX755Rcb0wAAAAAAgGCiAATCUHFxsa3jAQAAAABA7UEBCIShtLQ0W8cDAAAAAIDagwIQCEN9+/b1eWxGRoZOPfVU+8IAAAAAAICgogAEwtCpp54qwzB8GnvDDTfI6XTanAgAAAAAAAQLBSAQZr744guNGjVKpmkec+wll1yi0aNH10AqAAAAAAAQLBSAQBjZvn27brzxRlVWVh5z7BVXXKF3331XUVFRNZAMAAAAAAAECwUgEEbee+89lZWV+TT24MGDio6OtjkRAAAAAAAINgpAIEyYpqkZM2b4PH7x4sXKysqyMREAAAAAAAgFFIBAmCgpKVFubq5fc3bt2mVTGgAAAAAAECooAIEwEcjtvDExMTYkAQAAAAAAoYQCEAgTMTEx6tSpk8/j69atq7Zt29oXCAAAAAAAhAQKQCCMXHfddT6PHThwoBISEmxMAwAAAAAAQgEFIBAmcnJyNH36dJ/GNmzYUGPGjLE5EQAAAAAACAVRwQ7w/2vvzqOrLOz0gX9vFiAJi0TZCopocUEpVusIVpGKlQ5LxVp3bNWRenTc247zK061YK1dxo61Wo/FtaKOCo5FrZXaikKlWFxxqYJYsMiOiYQQQri/PzhkYITkBvLm5t58Pud4DLzPvTzkhPeEh/e+F9h91dXVcfrpp8drr73WaLZ3797x0EMPRa9evVqgGQAAAJBtrgCEPPCb3/wmo/EvIuK8886Lgw46KOFGAAAAQGthAIQcl06n4+677844P2XKlEin0wk2AgAAAFoTAyDkuBUrVsSCBQsyzi9atCg++uijBBsBAAAArYkBEHJcdXV1izwGAAAAyE0GQMhxe+21VxQWFmacLygoiG7duiXYCAAAAGhNDICQ4zp27Bhf+cpXMs6PGDEiOnfunGAjAAAAoDUxAEIeOOKIIzLOXnjhhQk2AQAAAFobAyDkuDvuuCMmTpyYUfZ73/tefPGLX0y4EQAAANCaFGW7ALDrZs2aFRMmTGg0l0ql4rrrrouLL764BVoBAAAArYkrACGH/fKXv8wol06nY9myZQm3AQAAAFojAyDkqOXLl8cf//jHjPMPPfRQpNPpBBsBAAAArZEBEHLUhx9+2KRBb+3atbFu3boEGwEAAACtkQEQclRxcXGTH1NU5LafAAAA0NYYACFHffazn41OnTplnD/kkEOipKQkwUYAAABAa2QAhBxVWloaZ5xxRsb5c889N7kyAAAAQKtlAIQctXz58pg3b15G2QEDBsRpp52WcCMAAACgNXJDMMhBH3/8cYwdOzYWLFjQaPbQQw+NBx98MEpLS1ugGQAAANDauAIQctBNN92U0fgXEXH99ddHz549E24EAAAAtFYGQMgx69evjwceeCDj/G9+85sE2wAAAACtnQEQcswrr7wSFRUVGef/+Mc/JtgGAAAAaO0MgJBjPvnkkybl161bl1ATAAAAIBcYACHH7Lnnnk3Kl5eXJ9QEAAAAyAUGQMgxhx9+ePTp0yfj/EknnZRgGwAAAKC1MwBCjiksLIwRI0ZklC0oKIjzzz8/4UYAAABAa2YAhBxz5513xp133plR9kc/+lHsv//+CTcCAAAAWrOibBcAMvf000/Hv//7vzeaKy4ujptvvjlOPfXUFmgFAAAAtGauAIQckU6n4yc/+UlG2dra2ujUqVPCjQAAAIBcYACEHPH666/HG2+8kXH+3nvvTbANAAAAkCsMgJAj3n777Sbl33nnnYSaAAAAALnEAAg5Ip1OZ7sCAAAAkIMMgJAjDjrooCblDzjggISaAAAAALnEAAg54rDDDotDDjkk4/w3vvGNBNsAAAAAucIACDli3bp1seeee2aUHThwYIwYMSLhRgAAAEAuKMp2AaBx69ati5NPPjlee+21RrMHHHBATJkyJYqK/PEGAAAADICQE6699tqMxr+ysrJ47LHHonv37i3QCgAAAMgFXgIMrdyaNWvi4YcfzihbVVUVf/rTnxJuBAAAAOQSAyC0ck8//XRs2LAh4/zUqVMTbAMAAADkGgMgtHIrV65MNA8AAADkNwMgtHKlpaWJ5gEAAID8ZgCEVm7o0KFNyg8bNiyZIgAAAEBOMgBCK3fggQfG4MGDM8oWFRXFuHHjEm4EAAAA5JKibBeg5RQWFma7QiLy9fe11YwZM2L+/PkZZSdMmBB9+vRJuFF+2vp1lO9fT7Q8X1M0B+cokuJriubgHEWSfF2xu5yjtkil0+l0tksAO/anP/0pRowYEbW1tQ3mCgoK4kc/+lF897vfjVQq1ULtAAAAgFxgAGxD1q5dm+0KzaZz585RWFgYdXV1UVlZme06iUin0zFkyJB49913G82WlJTE22+/HZ07d26BZvmpsLAwOnfuHJWVlVFXV5ftOuS4tnCOomU5R9GcnKNobs5RNDfnKZpTPp6junbt2uTHeAlwG5IvX+j/V77+vmbNmpXR+BcRUV1dHQ888ECMHz8+4Vb5r66uLm+/psgOX080J+compuvJ5qTcxRJ8DVFc2nr5yhvAgKt1AsvvNCk/KxZsxJqAgAAAOQyAyC0UuvXr080DwAAALQNBkBopXr06NGkfPfu3RNqAgAAAOQyAyC0UieddFKT3tH3lFNOSbANAAAAkKsMgNBK9e7dOw4//PCMsgceeGAMGzYs2UIAAABATjIAQiu0adOmuPjii2PevHmNZsvLy+Ouu+6KggJ/nAEAAIBPsxhAKzRx4sSYOnVqo7l99tknfve738UBBxzQAq0AAACAXGQAhFZm5cqVceedd2aUXbZsWXTu3DnhRgAAAEAuMwBCK/Pwww/Hxo0bM8pu3LgxHn744YQbAQAAALnMAAitzNtvv92k/FtvvZVQEwAAACAfGAChlUmn09muAAAAAOQRAyC0MgcddFCT8gceeGBCTQAAAIB8YACEVua0006L4uLijLLFxcVx+umnJ9wIAAAAyGUGQGhlNm3aFHvvvXdG2W9+85vRvXv3hBsBAAAAuawo2wWA/7Vo0aIYM2ZMLF++vNHsmDFjYuLEiS3QCgAAAMhlBkBoJdLpdJx//vkZjX9HHnlkTJ48OQoKXMQLAAAANMx6AK3ErFmzYv78+RllX3755YyGQgAAAAADILQSjzzySMbZurq6eOyxxxJsAwAAAOQLAyC0Eh999FGieQAAAKBtMgBCK1FSUtKkfIcOHRJqAgAAAOQTAyC0EkcffXST8l/84hcTagIAAADkEwMgtBJnnHFGtG/fPqNsv379YujQoQk3AgAAAPKBARBaiRkzZkQqlWo0V1BQED/60Y+ioMAfXwAAAKBxFgRoBR544IG4+OKLY8OGDQ3mSkpK4s4774zhw4e3UDMAAAAg1xkAIctWr14dV199dUbZo446KkaPHp1wIwAAACCfGAAhyx588MFGr/zbaubMmfH3v/894UYAAABAPjEAQpbNmDEj42w6nY5nn302wTYAAABAvjEAQpZVVFQ0KV9ZWZlQEwAAACAfGQAhy/bcc88m5cvLyxNqAgAAAOQjAyBk2ahRozLOFhUVxYknnphgGwAAACDfGAAhy77+9a9HaWlpRtkxY8ZEz549E24EAAAA5BMDIGTR+vXr45JLLon169c3mt13333j+uuvb4FWAAAAQD4xAEKWpNPpuPjii+N3v/tdo9kjjzwynnjiiejevXsLNAMAAADyiQEQsmTOnDnx5JNPZpQtKyuLHj16JNwIAAAAyEcGQMiSe+65J+Psc889FwsXLkyuDAAAAJC3DICQJfPmzWtS/uWXX06oCQAAAJDPDICQJRs3bkw0DwAAABBhAISs2XvvvZuU32effRJqAgAAAOQzAyBkyRlnnJFxdp999omjjz46wTYAAABAvjIAQpYcffTRUVpamlH2oosuisLCwoQbAQAAAPnIAAhZMH/+/BgzZkysX7++0ew555wT//Iv/9ICrQAAAIB8ZACEFlZZWRlnnnlmrFy5stHs+PHj4z//8z8jlUq1QDMAAAAgHxkAoYU99NBDsWzZsoyy8+fPN/4BAAAAu8UACC1sypQpGWdffPHFWLhwYYJtAAAAgHxnAIQW1tRBzwAIAAAA7A4DILSwpr6br3f/BQAAAHaHARBa2CGHHJJxtqCgIAYMGJBgGwAAACDfGQChhZ177rkZZ0eMGBG9evVKrgwAAACQ9wyA0MLS6XQUFxc3mmvfvn18+9vfboFGAAAAQD4zAEILuv322+OSSy6J2traBnMlJSVx1113xaBBg1qoGQAAAJCvDIDQQl577bX4j//4j4yy11xzTZx44okJNwIAAADaAgMgtJBf//rXGWcfe+yxBJsAAAAAbYkBEFpAXV1d/Pa3v804/9e//jUWL16cYCMAAACgrTAAQgtYt25dVFdXN+kxK1asSKgNAAAA0JYYAKEFdOjQocmPKSsrS6AJAAAA0NYYAKEFtG/fPoYMGZJxvmfPntG/f/8EGwEAAABthQEQWsh5552Xcfab3/xmFBUVJdgGAAAAaCsMgNAC1q1bF48//nhG2YMPPjguvPDChBsBAAAAbYVLjCBhGzdujHHjxsXs2bMbzR555JFxzz33RKdOnVqgGQAAANAWuAIQEvbggw9mNP5FRJxxxhnRvXv3hBsBAAAAbYkBEBKUTqfjrrvuyjh/zz33JFcGAAAAaJMMgJCg5cuXx1tvvZVx/o033ohVq1Yl2AgAAABoawyAkKCqqqomP2bdunUJNAEAAADaKgMgJKi8vLxJ+VQq1eTHAAAAADTEAAgJ6tq1awwbNizj/PHHHx+dO3dOrhAAAADQ5hgAIWGnnnpqxtkLLrggwSYAAABAW2QAhATNnTs3JkyYkFH2oosuihNOOCHhRgAAAEBbU5TtApCv3n///TjzzDOjsrKywVxBQUF873vfi8suu6yFmgEAAABtiSsAISG33HJLo+NfRMTmzZujrKwsUqlUC7QCAAAA2hoDICTgk08+ialTp2acv/feexNsAwAAALRlBkBIwIIFC6K6ujrj/DvvvBM1NTUJNgIAAADaKgMgJGDTpk1NfkxdXV0CTQAAAIC2zgAICejbt28UFGT+x6tHjx5RUlKSYCMAAACgrTIAQgK6d+8eX/7ylzPOn3322d4EBAAAAEiEARASkE6nY8CAARllO3fuHOedd17CjQAAAIC2qijbBSDfpNPpuO666+K2225rNNuxY8e47777omfPni3QDAAAAGiLDIDQzB599NGMxr/i4uJ4+OGH48gjj2yBVgAAAEBb5SXA0IzS6XTceuutGWVra2tjzpw5CTcCAAAA2joDIDSj+fPnx5tvvplx/qGHHkqwDQAAAIABEJrVkiVLEs0DAAAANJUBEJpRcXFxk/Lt2rVLqAkAAADAFgZAaEaHHXZYFBVl/t46X/jCFxJsAwAAAGAAhGbVrVu3GD16dMb58847L8E2AAAAAAZAaFbLli3L+L5+xx13XJxwwgkJNwIAAADausxfqwg0aNWqVfHVr341Fi1a1Gj2uOOOi7vvvjsKCwtboBkAAADQlrkCEJrJpEmTMhr/CgoK4uc//3l06tSpBVoBAAAAbZ0BEJrB2rVrY9q0aRllN2/eHPfff3/CjQAAAAC2MABCM3juuediw4YNGeeffvrpBNsAAAAA/C8DIDSDysrKRPMAAAAAu8oACM1gjz32aFK+S5cuyRQBAAAA+D8MgNAMhg0bFiUlJRnnR44cmWAbAAAAgP9lAIRm0KVLlzjxxBMzyrZr1y7OOeechBsBAAAAbGEAhGbwm9/8JqZPn55R9sYbb4xevXol3AgAAABgi6JsF4Bc9+STT8ZVV13VaK59+/Zx8803xymnnNICrQAAAAC2cAUg7IbNmzfHxIkTM8rW1NTEoYcemnAjAAAAgO0ZAGE3zJ49O95///2M8/fee2+CbQAAAAA+zQAIu+HVV19NNA8AAACwuwyAsBs2bdqUaB4AAABgdxkAYTfsu+++ieYBAAAAdpcBEHbDV77ylejatWvG+bPPPjvBNgAAAACfZgCE3bBp06bYb7/9MsoOGjQojj322IQbAQAAAGyvKNsFIFdVVFTEySefHG+88Uaj2X79+sV9990XBQU2dwAAAKBlGQBhF333u9/NaPzr1q1b/O53v4s999yzBVoBAAAAbM/lSLAL/vGPf8Tjjz+eUXblypXx3nvvJdwIAAAAYMcMgLALpk2bFps3b844//DDDyfYBgAAAGDnDICwCz766KMm5ZcuXZpQEwAAAICGGQBhF3To0CHRPAAAAEBzMQDCLhg8eHCT8kOGDEmoCQAAAEDDDICwC4YPHx69e/fOKFtSUhJnnHFGwo0AAAAAdswACLvgkUceiRUrVmSUnTBhQnTp0iXhRgAAAAA7VpTtApBrHnvssbj00ksbzaVSqbjmmmviW9/6Vgu0AgAAANgxVwBCE2zYsCH+3//7fxll99xzz7jooosilUol3AoAAABg5wyA0ATTp0+P1atXZ5RdtWpVPPXUUwk3AgAAAGiYARCaYNasWU3Kz549O6EmAAAAAJkxAEITVFdXNylfVVWVUBMAAACAzBgAoQl69uyZaB4AAACguRkAoQlOOeWURPMAAAAAzc0ACE2w9957Z3xV39ChQ2PAgAEJNwIAAABomAEQMrRs2bL453/+51i2bFmj2b59+8att97aAq0AAAAAGmYAhAyk0+k4//zz4/333280u//++8eTTz7p/n8AAABAq2AAhAzMnTs3XnrppYyy//jHP6Jdu3YJNwIAAADIjAEQMvDQQw9lnN2wYUP8z//8T3JlAAAAAJrAAAgZWLx4caJ5AAAAgKQYACEDxcXFieYBAAAAkmIAhAwcccQRTcp/4QtfSKgJAAAAQNMYACED48aNi8LCwoyyffr0ieHDhyfcCAAAACAzBkBoxObNm2Py5MlRV1eXUf7aa6/NeCwEAAAASJoBEBpxww03xC9+8YtGcwUFBfGzn/0sxo4dm3wpAAAAgAwZAKEBH3zwQUbjX0TE5z73ufjmN7+ZcCMAAACApjEAQgPuu+++SKfTGWVfffXVePvttxNuBAAAANA0BkBowOzZs5uU//Of/5xQEwAAAIBdYwCEBmzYsKFJ+erq6oSaAAAAAOwaAyA0oEePHk3K9+rVK6EmAAAAALvGAAgNOPXUUzPOduzYMUaMGJFgGwAAAICmMwBCA3r16hXFxcUZZceNGxcdO3ZMuBEAAABA0xgAYSf+8Ic/xOmnnx61tbWNZr/4xS/GhAkTWqAVAAAAQNMYAGEHVq9eHePHj4+NGzc2mj3qqKPioYceig4dOrRAMwAAAICmMQDCDjz44IOxbt26jLKLFi2KwsLChBsBAAAA7BoDIOzAtGnTMs6uWLEiZs2alWAbAAAAgF1nAIQdWLZsWaJ5AAAAgJZiAIQdKCsra1K+tLQ0oSYAAAAAu8cACDtw9NFHZ5wtKiqKo446KsE2AAAAALvOAAg7cOqpp2acHTlyZPTs2TPBNgAAAAC7rijbBVpaRUVFPProozF37txYvXp1tG/fPvbff/8YOXJkDB48eJefd9OmTfHEE0/EzJkzY+nSpRER0bt37zjuuONi1KhRUVTU8Kf6/fffj8ceeyzeeOONqKysjC5dusShhx4aX/va16Jfv3673IumW7RoUVxxxRUZZcvLy+Oaa65JthAAAADAbmhTA+DixYtjwoQJUVFRERERJSUlUVVVFa+++mq8+uqrMWbMmBg/fnyTn7e6ujr+4z/+I959992IiGjXrl1ERCxYsCAWLFgQs2fPjokTJ0aHDh12+PiZM2fGzTffHJs2bYqILfefW716dcycOTNmz54dV155ZRx77LG78lumiaqqquL000+Pv//9741me/ToEf/93/9toAUAAABatTYzANbW1sb1118fFRUV0bdv37jqqquiX79+UVNTE48//nhMmTIlpk+fHv369YsTTjihSc992223xbvvvhtlZWVx2WWX1V9JOGfOnPjFL34R77zzTvzqV7+KK6+88lOPXbx4cf34d8wxx8QFF1wQ5eXlsWbNmvj1r38ds2fPjv/6r/+Kfv36RZ8+fZrlc5Gr0ul0zJs3L+6777545ZVXYtWqVVFbWxvpdDrS6XSkUqnd/n9NTU3U1NRk1GfgwIFxyCGHJPy7BgAAANg9bWYA/P3vfx/Lli2L9u3bx/e///3o1q1bRES0b98+TjvttFizZk089dRTcf/998ewYcMafcnuVosWLYrnn38+IiIuvfTSGDJkSP2xIUOGxObNm+PHP/5xPPfcc/G1r30t+vbtu93jp0yZEps2bYp+/frFt7/97SgsLIyILS8t/c53vhNLly6NRYsWxZQpU+Lqq69ujk9FTlq3bl1ceOGF8cwzz2S7Sr1nn302li5dGp/5zGeyXQUAAABgp9rMm4A899xzERExdOjQ+vFvW6ecckqkUqlYs2ZNvPHGGxk/78yZMyOdTkevXr22G/+2Ovroo6NXr16RTqdj5syZ2x2rqqqKl156KSIixo4dWz/+bVVYWBhjx46NiIi5c+fG+vXrM+6VT2pra2PcuHGtavyL2HJF4t/+9rds1wAAAABoUJsYAKurq+O9996LiIjDDz98h5lu3brVv8T2tddey/i5X3/99YiI+PznPx+pVOpTx1OpVHz+85/fLrvVW2+9VX/fv5312vrztbW18fbbb2fcK588+uijMXv27GzXAAAAAMhJbWIA/PDDDyOdTkdEfOoluNvaemzJkiUZPW86nY4PP/yw0efdZ599dvi8W3+8xx57RJcuXXb42C5dutQfW7x4cUa98s3dd9+d7Qo7lEqlon///tmuAQAAANCgNnEPwDVr1tR/XF5evtPc1mNr167N6Hmrq6tjw4YNGT9vdXV1VFdXR0lJyXa/TkOP3Xq8oqKi0V73339/PPDAAzs9fuaZZ8ZZZ53V4HO0Np988km88sor2a6xQyNGjIiBAwdmuwbNZOsVvF26dKn/BwPYVQUFBfX/79q1a5bbkA+co2hOzlE0N+compvzFM3JOWqLNjEAbh3pIra86cfObD1WXV2d0fNum8vkebc+ZusAuPXxDT22Kb2qqqpixYoVOz2+fv36T91nsLXL9B15W1phYWFMmDAh5z6fNG7rNxvQHFKplPMEzco5iubkHEVzc46iuTlP0Zza+jmqTQyAbUVZWVl07959p8dLS0ujrq6uBRvtvs6dO0e7du1i48aN2a6ynZ/97GcxZMiQnPt8snOpVCoKCgpi8+bNbfpfhWgeBQUFkUqlIp1Ox+bNm7NdhzzgHEVzco6iuTlH0dycp2hO+XiO2pVhvE0MgB06dKj/uKamJkpLS3eY23q12dYr9Bqzba6hK9W2PbbtY7Z+3NhVbpn2GjduXIwbN26nx1etWpXxy5tbkzFjxsTUqVOzXaPewIEDY9y4cTn5uWTnCgsLo2vXrlFRUWHYZbd17do1CgsLY/Pmzc4VNAvnKJqTcxTNzTmK5uY8RXPKx3PUXnvt1eTHtInrH7e9x9629wP8v7Yey/QeAyUlJfWjXCbPu21+214NPXZXeuWb8ePHZ7vCdq666qpsVwAAAADIWJsYAPv06VN/08eG3kl367G99947o+dNpVLRp0+fXX7erT/++OOPo7KycoePraioiIqKioj433cTbmuOOOKI+MEPfpDtGhERceGFF8aoUaOyXQMAAAAgY21iACwpKYn+/ftHRMTLL7+8w8yqVatiyZIlERExaNCgjJ/7c5/7XEREg+9U++qrr26X3WrAgAFRVFTUYK+tz1tcXBwHH3xwxr3yzcUXXxy333579OvXLyu/fs+ePeOGG26ISZMm1Y/JAAAAALmgTdwDMCJi2LBh8e6778bzzz8fp59+enTr1m2749OmTYt0Oh3l5eUxcODAjJ936NChMW3atFi6dGm8+OKLMWTIkO2O//nPf46lS5dGKpWKYcOGbXestLQ0jjzyyHjxxRfj8ccfj2OPPXa7GznW1dXF448/HhER//RP/7TTexe2FaecckqcfPLJMWvWrFi4cGF88MEHsWHDhkilUrF+/fooKyuLdevWRadOnaKysjK6du0aa9asifLy8u3+37Vr1/j4449jjz32iIqKiigrK4vq6uro0KFDbNy4MQoLC+tvDLrvvvvGAQccEMcff3wUFxdn+TMAAAAA0HRtZgAcMWJE/Pa3v41ly5bFpEmT4sorr4x+/fpFTU1NTJ8+PZ588smI2PJGGluvytvqggsuiBUrVsTxxx8fV1xxxXbH+vXrF0OHDo2ZM2fGLbfcEqlUKo466qiIiPjLX/4Sv/zlLyNiywC5o5fwnn322fHSSy/FwoUL46abbooLLrggunbtGmvXro3JkyfHwoULo7i4OM4+++wEPiu5p6CgIIYOHRonnXRSFBYWRl1dnZvCAgAAADSgzQyAxcXFcc0118SECRPigw8+iMsvvzxKS0tjw4YN9W8rPnr06DjhhBOa/NwXX3xxfPTRR/Huu+/GDTfcEO3atYuIiI0bN0ZExEEHHRQXXXTRDh+7zz77xOWXXx4333xzvPDCCzFr1qwoLS2NqqqqiIgoKiqKyy+/vP5egwAAAADQFG1mAIzYMrbdcsstMXXq1Jg7d26sWrUqysrKYr/99otRo0bF4MGDd+l5S0pK4sYbb4wnnngiZs6cGUuXLo2IiP333z+GDRsWo0aN+tRVhds67rjjYu+9945p06bF/Pnzo7Kysv6lyF/72teydt87AAAAAHJfKr31ZmfkvVWrVmW7QrPp2rWrlwDTrAoLC+tffl9XV5ftOuQ45yiam3MUzck5iubmHEVzc56iOeXjOWqvvfZq8mPaxLsAAwAAAEBbZQAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8lkqn0+lsl4Cmuv/++6OqqirKyspi3Lhx2a4DsB3nKKA1c44CWjvnKWh+BkBy0siRI2PFihXRvXv3eOqpp7JdB2A7zlFAa+YcBbR2zlPQ/LwEGAAAAADymAEQAAAAAPKYARAAAAAA8pgBEAAAAADymAEQAAAAAPKYARAAAAAA8lhRtgvArjjrrLOiqqoqysrKsl0F4FOco4DWzDkKaO2cp6D5pdLpdDrbJQAAAACAZHgJMAAAAADkMQMgAAAAAOQxAyAAAAAA5DEDIAAAAADkMe8CTE6pqKiIRx99NObOnRurV6+O9u3bx/777x8jR46MwYMHZ7se0EatW7cu5s+fHwsWLIiFCxfGggULoqKiIiIifvjDH8bAgQOz3BBoy1auXBkvvvhivP766/HBBx/EmjVroqioKLp16xaHHXZYjBkzJnr27JntmkAbtmDBgpg7d2689957sXTp0qisrIyampro1KlT7LfffjF06NA47rjjoqDANUywq7wLMDlj8eLFMWHChPq/VJeUlERNTU1s3rw5IiLGjBkT48ePz2ZFoI169tln4+abb97hMQMgkE0rV66MCy64ILb9lr+0tDQ2btwYmzZtioiIdu3axRVXXBHHHHNMtmoCbdxtt90WTz/9dP2PO3ToEBERGzZsqP+5Qw89NK655pooLS1t8X6QD1wBSE6ora2N66+/PioqKqJv375x1VVXRb9+/aKmpiYef/zxmDJlSkyfPj369esXJ5xwQrbrAm1Q165dY//994/Pfvaz8ZnPfCZuuummbFcCqP+H0sMPPzyOP/74OOyww6Jz585RV1cXb7/9dtxxxx3xwQcfxE033RR9+vSJfffdN7uFgTbpwAMPjN69e8eAAQOid+/e9SPfxx9/HDNmzIgpU6bE/Pnz46677opLLrkky20hN7kCkJzwxBNPxB133BHt27eP2267Lbp167bd8dtvvz2eeuqpKC8vj8mTJ0dRkW0baDl1dXVRWFhY/+N169bFWWedFRGuAASyq6qqKpYvXx777bffDo+vXbs2LrvssqioqIjhw4fH5Zdf3sINARp3//33x8MPPxzt2rWLhx56yN/3YBd4AT054bnnnouIiKFDh35q/IuIOOWUUyKVSsWaNWvijTfeaOF2QFu37fgH0JqUlZXtdPyL2HL18hFHHBEREQsXLmypWgBN0r9//4iI2LhxY3zyySdZbgO5yQBIq1ddXR3vvfdeRGx5+cqOdOvWLfr06RMREa+99lqLdQMAyHWdO3eOiC1XMwO0Ru+8805EbLk34B577JHdMpCjXDdLq/fhhx/W37i6b9++O8317ds3lixZEkuWLGmpagAAOW/+/PkR0fD3WQAtraamJlauXBl/+tOf4rHHHouIiFGjRkUqlcpyM8hNBkBavTVr1tR/XF5evtPc1mNr165NvBMAQD6YM2dOLFiwICIihg8fnuU2QFu37X2Ut1VUVBSjR4+OcePGZaEV5AcDIK3etm/93r59+53mth6rrq5OvBMAQK5buXJl3HrrrRERcdRRR9XfCxAgWwoKCupf4rt+/frYuHFjpFKpGD16dJx88snuuwy7wQAIAABtzLp162LSpElRUVERPXv2jMsuuyzblQCitLQ07rvvvoiISKfTsWLFipg+fXpMnz49nn322ZgwYUIMGDAgyy0hN3kTEFq9Dh061H9cU1Oz09zWYyUlJYl3AgDIVdXV1fGDH/wgPvjggygvL4+JEydGp06dsl0LYDupVCp69OgRF1xwQZx33nnxySefxE9/+tMG/04I7JwBkFZv2/v+bXs/wP9r67GuXbsm3gkAIBfV1NTExIkT429/+1t06dIlJk2aFD179sx2LYAGfeUrX4ni4uJYvXp1zJs3L9t1ICcZAGn1+vTpU/9OT4sXL95pbuuxvffeu0V6AQDkkpqampg0aVK8+eab0bFjx5g4caLvm4Cc0K5du/orlT/66KMst4HcZACk1SspKYn+/ftHRMTLL7+8w8yqVatiyZIlERExaNCgFusGAJALamtr44YbbojXX389SktL47rrrot+/fpluxZARqqrq6OysjIi3PIJdpUBkJwwbNiwiIh4/vnnY+XKlZ86Pm3atEin01FeXh4DBw5s4XYAAK3Xpk2b4sYbb4xXXnklOnToEN///vfjgAMOyHYtgIiIqKuri3Q63WDm8ccfj02bNkVExCGHHNIStSDvGADJCSNGjIiePXvGhg0bYtKkSbFo0aKI2PJSlkcffTSefPLJiIgYN25cFBV5c2ug5VVWVtb/t27duvqfr6qq2u7Y1m9eAVpCXV1d/OxnP4uXXnop2rVrF9dcc4130ARalVWrVsWVV14ZzzzzzHYXe6TT6ViyZEncfvvt8eCDD0ZExJAhQ6Jv377Zqgo5LZVubGqHVmLx4sUxYcKEqKioiIgtbxG/YcOG2Lx5c0REjB49Or71rW9lsyLQhn31q1/NKPfDH/7QlcpAi5k/f35873vfi4iI4uLiKCsrazB/3333tUQtgHrLly+P8ePH1/+4Xbt20aFDh9iwYUNs3Lix/uePPPLI+O53vxsdOnTIRk3IeS6VImfss88+ccstt8TUqVNj7ty5sWrVqigrK4v99tsvRo0aFYMHD852RQCAVmXbf+uvra2Njz/+OHtlAHagvLw8/u3f/i1ef/31ePfdd2Pt2rVRWVkZxcXF0bt37zjggAPiuOOOi8MPPzzbVSGnuQIQAAAAAPKYewACAAAAQB4zAAIAAABAHjMAAgAAAEAeMwACAAAAQB4zAAIAAABAHjMAAgAAAEAeMwACAAAAQB4zAAIAAABAHjMAAgAAAEAeMwACAAAAQB4zAAIAAABAHjMAAgAAAEAeMwACAAAAQB4zAAIAAABAHjMAAgAAAEAeMwACAAAAQB4zAAIAAABAHjMAAgDQ7J577rlIpVKRSqXiuuuuy3YdAIA2zQAIAAAAAHnMAAgAAAAAecwACAAAAAB5zAAIAAAAAHnMAAgAAAAAecwACABAi/jb3/4Wl156aRx44IFRVlYWXbt2jcGDB8fPf/7zqKmp2enj9t1330ilUrHvvvtGRMTGjRvjl7/8ZRx99NHRrVu36NixYwwaNCh+8pOfRFVV1XaPXb58eVx33XUxaNCg6NKlS3Tq1CkGDx4ckydPjnQ63WDfzZs3xwMPPBBjx46Nvn37RklJSXTo0CF69+4dgwYNilNPPTVuu+22WL169W5/bgAAkpRKN/adDwAANNFzzz0XX/rSlyIi4tprr42DDz44zj///Fi/fv0O8wcddFA8/fTT0bdv308d23fffePvf/979O3bN+bMmROjR4+OefPm7fB5jjzyyHjmmWdijz32iDlz5sTYsWNj+fLlO8yeeeaZMWXKlEilUp86tnr16hg9enTMmTOn0d/rT3/60/jOd77TaA4AIFuKsl0AAID8Nm/evLjxxhujtrY2zjrrrBg+fHiUlJTEm2++GXfddVd89NFH8c4778SXvvSleOWVV6JLly47fJ7a2to45ZRTYt68efHlL385xo4dG3vttVe8//77ceutt8aHH34YL730UlxxxRVx3XXXxYgRI6K6ujrOPffcGDp0aJSUlMRLL70Uv/rVr6K6ujoefPDBOOGEE+L888//1K81fvz4+vFv7733jjPOOCP69+8fXbt2jaqqqnjvvffixRdfjBdeeCHRzx0AQHNwBSAAAM1u2ysAIyJKS0vjySefjGHDhm2X+/jjj2PkyJHx4osvRkTEhRdeGLfffvt2ma1XAEZEpFKpmDx58qdGu+XLl8dhhx0Wy5Yti8LCwhg4cGAsWbIkZsyYEZ///Oe3y/7xj3+M4cOHR0TEIYccEvPnz9/u+IoVK6JXr16xefPmOProo+PZZ5+NDh067PD3uXLlyli1alUcfPDBGX5mAABannsAAgCQuBtvvPFT419ExB577BGPPPJIdOzYMSIi7rnnnli5cuVOn+eCCy7Y4RV7PXr0iEsuuSQiIurq6uLVV1+NW2+99VPjX0TE8ccfXz8Avvnmm7FkyZLtjr///vuxefPmiIg4++yzdzr+RUR069bN+AcAtHoGQAAAErXHHnvE+PHjd3q8d+/ecfbZZ0dERE1NTUyfPn2n2UsvvXSnx4455pj6j3v06BGnnnrqTrPHHnts/cdvvfXWdsfKysrqP97ZvQYBAHKJARAAgEQdc8wxDV5FFxFxwgkn1H88d+7cHWbKysri0EMP3elz9OzZs/7jI444IgoKdv6t7rbZtWvXbndswIAB0bt374iIuOuuu+Lcc8+N2bNnR11dXYO/BwCA1soACABAovr379+kzNKlS3eYKS8v3+E79m7Vvn37+o/33HPPBn+9bbMbNmzY7lhhYWHccccd9Zl77703jjnmmCgvL48TTzwxfvCDH8Ts2bPDrbQBgFxhAAQAIFHbvqQ2k8wnn3yyw0xDV/TtTnZHRo4cGX/961/j61//erRr1y4iIiorK2PGjBlx3XXXxTHHHBP7779/3H///bv16wAAtISibBcAACC/VVVVNSnTqVOnJOtk7NBDD41HHnkkqqqqYvbs2TFnzpx44YUX4oUXXoiamppYtGhRnHPOObFw4cK49tprs10XAGCnXAEIAECiFixY0KTMZz7zmSTrNFlZWVmceOKJ8f3vfz9mzJgRK1eujEmTJtUf/+EPfxjLli3LYkMAgIYZAAEASNTWK+Ya8oc//KH+46OOOirpSrulU6dOcc0118RJJ50UERG1tbUxZ86cLLcCANg5AyAAAIn6+OOPY/LkyTs9/tFHH8WUKVMiYsubc4wePbqlqu2Wfv361X+8adOmLDYBAGiYARAAgMRdffXV8fzzz3/q5ysrK+O0006rf+OP8847L7p169bS9bbz+9//Pn7+85/H2rVrd5pZsWJFTJ06tf7HgwYNaolqAAC7xJuAAACQqNGjR8eMGTPi+OOPjzPOOCOGDx8eJSUl8dZbb8Wdd94ZS5cujYgtV9T9+Mc/znLbLVckXnXVVXH11VfHsGHDYvDgwbHffvtFx44dY/Xq1fH666/Hgw8+WD8QnnbaadG/f/8stwYA2DkDIAAAiTriiCPinHPOifPOOy+mTJlS/3LfbR144IHx9NNPR+fOnbPQcHupVCoittzbb8aMGTFjxoydZr/+9a/H3Xff3VLVAAB2iQEQAIDEnXbaaTFo0KC45ZZb4plnnol//OMfUVxcHAceeGCcfvrp8a//+q/Rvn37bNeMiIhvfOMbMWDAgPjDH/4Qf/nLX+Ltt9+OpUuXRnV1dZSWlsY+++wTgwcPjnPOOSeOO+64bNcFAGhUKp1Op7NdAgAAAABIhjcBAQAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPGYABAAAAIA8ZgAEAAAAgDxmAAQAAACAPPb/AX3mwliJdRvdAAAAAElFTkSuQmCC" 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,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(UM3_2o_pol, aes(x='bms', y='fishing_intensity', color='mwt')) + geom_point(),\n", + " ggplot(UM3_mw_pol, aes(x='mwt', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM3_bm_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "351e7eef-799a-419f-9a5f-70362e3329ea", + "metadata": {}, + "outputs": [], + "source": [ + "UM3_cr_pol = pd.DataFrame(\n", + " get_bms_policy(\n", + " bms_obs_list,\n", + " agent = CautionaryRule(\n", + " env = AsmEnv(config=CFG_UM3_bm),\n", + " **(from_radius_theta(*cr_UM3.x)), \n", + " ),\n", + " asm_env = AsmEnv(config=CFG_UM3_bm),\n", + " )\n", + ")\n", + "\n", + "UM3_esc_pol = pd.DataFrame(\n", + " get_bms_policy(\n", + " bms_obs_list, \n", + " agent = ConstEsc(\n", + " env = AsmEnv(config=CFG_UM3_bm), escapement=esc_UM3.x[0]\n", + " ),\n", + " asm_env = AsmEnv(config=CFG_UM3_bm),\n", + " )\n", + ") \n", + "\n", + "UM3_msy_pol = pd.DataFrame(get_bms_policy(\n", + " bms_obs_list, \n", + " agent = Msy(\n", + " env = AsmEnv(config=CFG_UM3_bm), mortality=msy_UM3.x[0]\n", + " ), \n", + " asm_env = AsmEnv(config=CFG_UM3_bm),\n", + ")) " + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "8a4168aa-a415-434b-8ed7-5842a08a12bc", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(UM3_cr_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM3_esc_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + " ggplot(UM3_msy_pol, aes(x='bms', y='fishing_intensity')) + geom_point(),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "206a52bd-f522-42e9-b1f2-0616007debf5", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/for_results/4_episode_plots.ipynb b/notebooks/for_results/4_episode_plots.ipynb new file mode 100644 index 0000000..a97a078 --- /dev/null +++ b/notebooks/for_results/4_episode_plots.ipynb @@ -0,0 +1,842 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "997d7210-9871-46bf-afcd-9b7281f7f09d", + "metadata": {}, + "source": [ + "# Episode plots" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "2e5a5d9f-2dca-4e84-85e0-f638ebcd1713", + "metadata": {}, + "outputs": [], + "source": [ + "from huggingface_hub import hf_hub_download, HfApi\n", + "from plotnine import ggplot, aes, geom_point, geom_line\n", + "from skopt import load\n", + "from stable_baselines3 import PPO\n", + "\n", + "from rl4fisheries import AsmEnv, Msy, ConstEsc, CautionaryRule\n", + "from rl4fisheries.utils import evaluate_agent\n", + "from rl4fisheries.envs.asm_fns import get_r_devs\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import ray" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "197374ee-a5e9-4c1a-bc59-134ef128e869", + "metadata": { + "jupyter": { + "source_hidden": true + } + }, + "outputs": [], + "source": [ + "## UM1\n", + "\n", + "CFG_UM1_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "CFG_UM1_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "CFG_UM1_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 1,\n", + "}\n", + "\n", + "## UM2\n", + "\n", + "CFG_UM2_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "CFG_UM2_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "CFG_UM2_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"default\",\n", + " 'upow': 0.6,\n", + "}\n", + "\n", + "## UM3\n", + "\n", + "CFG_UM3_2o = {\n", + " 'observation_fn_id': 'observe_2o',\n", + " 'n_observs': 2,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}\n", + "CFG_UM3_mw = {\n", + " 'observation_fn_id': 'observe_mwt',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}\n", + "CFG_UM3_bm = {\n", + " 'observation_fn_id': 'observe_1o',\n", + " 'n_observs': 1,\n", + " #\n", + " 'harvest_fn_name': \"trophy\",\n", + " 'upow': 1,\n", + " 'n_trophy_ages': 10\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "22e758ef-6f8d-4356-9d17-05ea02212a1b", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Load" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "id": "3f3c8ad5-d4c9-41db-8361-f74f77ecb18b", + "metadata": {}, + "outputs": [], + "source": [ + "cr_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM1.pkl\")\n", + "cr_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM2.pkl\")\n", + "cr_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/cr-UM3.pkl\")\n", + "\n", + "esc_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM1.pkl\")\n", + "esc_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM2.pkl\")\n", + "esc_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/esc-UM3.pkl\")\n", + "\n", + "msy_UM1_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM1.pkl\")\n", + "msy_UM2_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM2.pkl\")\n", + "msy_UM3_file = hf_hub_download(repo_id=\"boettiger-lab/rl4eco\", filename=\"sb3/rl4fisheries/results/msy-UM3.pkl\")" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "id": "6013cb2d-7b22-44ee-a8b2-c70bb60bc444", + "metadata": {}, + "outputs": [], + "source": [ + "cr_UM1 = load(cr_UM1_file)\n", + "cr_UM2 = load(cr_UM2_file)\n", + "cr_UM3 = load(cr_UM3_file)\n", + "\n", + "esc_UM1 = load(esc_UM1_file)\n", + "esc_UM2 = load(esc_UM2_file)\n", + "esc_UM3 = load(esc_UM3_file)\n", + "\n", + "msy_UM1 = load(msy_UM1_file)\n", + "msy_UM2 = load(msy_UM2_file)\n", + "msy_UM3 = load(msy_UM3_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "id": "2c340620-3d64-421c-b7eb-5da488d4eebf", + "metadata": {}, + "outputs": [], + "source": [ + "base_fname = \"sb3/rl4fisheries/results/PPO-AsmEnv-\"\n", + "repo = \"boettiger-lab/rl4eco\"\n", + "\n", + "PPO_2o_UM1_file = hf_hub_download(repo_id=repo, filename=base_fname+\"2obs-UM1-64-32-16-chkpnt3.zip\")\n", + "PPO_mw_UM1_file = hf_hub_download(repo_id=repo, filename=base_fname+\"mwt-UM1-64-32-16-chkpnt3.zip\")\n", + "PPO_bm_UM1_file = hf_hub_download(repo_id=repo, filename=base_fname+\"biomass-UM1-64-32-16-chkpnt1.zip\")\n", + "\n", + "PPO_2o_UM2_file = hf_hub_download(repo_id=repo, filename=base_fname+\"2obs-UM2-64-32-16-chkpnt1.zip\")\n", + "PPO_mw_UM2_file = hf_hub_download(repo_id=repo, filename=base_fname+\"mwt-UM2-64-32-16-chkpnt4.zip\")\n", + "PPO_bm_UM2_file = hf_hub_download(repo_id=repo, filename=base_fname+\"biomass-UM2-64-32-16-chkpnt3.zip\")\n", + "\n", + "PPO_2o_UM3_file = hf_hub_download(repo_id=repo, filename=base_fname+\"2obs-UM3-64-32-16-chkpnt5.zip\")\n", + "PPO_mw_UM3_file = hf_hub_download(repo_id=repo, filename=base_fname+\"mwt-UM3-64-32-16-chkpnt2.zip\")\n", + "PPO_bm_UM3_file = hf_hub_download(repo_id=repo, filename=base_fname+\"biomass-UM3-64-32-16-chkpnt4.zip\")" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "id": "c875e183-dec5-48c3-b901-b9e01b3f99fb", + "metadata": {}, + "outputs": [], + "source": [ + "PPO_2o_UM1 = PPO.load(PPO_2o_UM1_file, device='cpu')\n", + "PPO_mw_UM1 = PPO.load(PPO_mw_UM1_file, device='cpu')\n", + "PPO_bm_UM1 = PPO.load(PPO_bm_UM1_file, device='cpu')\n", + "\n", + "PPO_2o_UM2 = PPO.load(PPO_2o_UM2_file, device='cpu')\n", + "PPO_mw_UM2 = PPO.load(PPO_mw_UM2_file, device='cpu')\n", + "PPO_bm_UM2 = PPO.load(PPO_bm_UM2_file, device='cpu')\n", + "\n", + "PPO_2o_UM3 = PPO.load(PPO_2o_UM3_file, device='cpu')\n", + "PPO_mw_UM3 = PPO.load(PPO_mw_UM3_file, device='cpu')\n", + "PPO_bm_UM3 = PPO.load(PPO_bm_UM3_file, device='cpu')" + ] + }, + { + "cell_type": "markdown", + "id": "f77e3ec2-dcbc-4a10-b4d4-b1d4c2ae1b9c", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Utilities\n", + "\n", + "Use 2 observations for all agents! (It's ok, they'll only use the first observation - biomass - but, the plots will also keep track of the mean weight (the second observation.)" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "57161153-9490-4588-bf1c-473bdcd6d28f", + "metadata": {}, + "outputs": [], + "source": [ + "def obs_to_mwt(obs, env):\n", + " return env.parameters['min_wt'] + (\n", + " env.parameters['max_wt'] - env.parameters['min_wt']\n", + " ) * (obs + 1) / 2\n", + "\n", + "def obs_to_bms(obs, env):\n", + " return env.bound * (obs + 1) / 2\n", + "\n", + "def safe_predict(agent, obs, observed_var):\n", + " if observed_var == '2o':\n", + " if len(obs) == 2:\n", + " return agent.predict(obs)\n", + " if observed_var == 'mw':\n", + " if len(obs) == 2:\n", + " return agent.predict(np.float32([obs[1]]))\n", + " if len(obs) == 1:\n", + " return agent.predict(obs)\n", + " if observed_var == 'bm':\n", + " if len(obs) == 2:\n", + " # print(obs[0], agent.predict(np.float32([obs[0]]))) ###########\n", + " return agent.predict(np.float32([obs[0]]))\n", + " if len(obs) == 1:\n", + " return agent.predict(obs)\n", + " print(f'problem in safe_predict. obs: {obs}, observed_var: {observed_var}')\n", + " return\n", + "\n", + "def simulate_episode(*, env, agent, observed_var: 'bm, mw or 2o'):\n", + " bms = []\n", + " mwt = []\n", + " ts = []\n", + " fishing = []\n", + " rews = []\n", + " obs, _ = env.reset()\n", + " #\n", + " for t in range(env.Tmax):\n", + " action, info = safe_predict(agent, obs, observed_var) # agent.predict(obs)\n", + " # print(obs, action, end=\"\\n\\n\")\n", + " new_obs, rew, term, trunc, info = env.step(action)\n", + " #\n", + " bms.append(obs_to_bms(obs=obs[0], env=env))\n", + " mwt.append(obs_to_mwt(obs=obs[1], env=env))\n", + " ts.append(t)\n", + " fishing.append(0.5 * (1 + action[0]))\n", + " rews.append(rew)\n", + " obs = new_obs\n", + " if term or trunc:\n", + " break\n", + " return {\n", + " 't': ts,\n", + " 'biomass': bms,\n", + " 'mean_wt': mwt,\n", + " 'fishing_intensity': fishing,\n", + " 'rew': rews,\n", + " }\n", + " \n", + "def from_radius_theta(radius, theta, y2):\n", + " x1 = radius * np.sin(theta)\n", + " x2 = radius * np.cos(theta)\n", + " return {'x1': x1, 'x2': x2, 'y2': y2} " + ] + }, + { + "cell_type": "markdown", + "id": "5d1ddd08-656b-4676-b819-979ff99219b6", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## Reproducible noise env" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "id": "381c0204-ff17-425a-a222-ce385f24d23d", + "metadata": {}, + "outputs": [], + "source": [ + "env_UM1 = AsmEnv(\n", + " config = {**CFG_UM1_2o, 'reproducibility_mode': True, 'r_devs': get_r_devs(n_year=AsmEnv().Tmax)}\n", + ")\n", + "\n", + "env_UM2 = AsmEnv(\n", + " config = {**CFG_UM2_2o, 'reproducibility_mode': True, 'r_devs': get_r_devs(n_year=AsmEnv().Tmax)}\n", + ")\n", + "\n", + "env_UM3 = AsmEnv(\n", + " config = {**CFG_UM3_2o, 'reproducibility_mode': True, 'r_devs': get_r_devs(n_year=AsmEnv().Tmax)}\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ff7b86b8-cf75-4889-ab7d-a8dc3f4abbaf", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "## UM1\n", + "\n", + "Caution: sometimes PPO_bm_UM1 seems to go out of wack and start predicting a constant action. This is not the behavior that it's supposed to have and the value of the constant action can be quite erratic (usually leading to near-zero rewards, inconsistent with notebook 2). If this happens, usually re-loading the model fixes the problem. Not really sure where the bug is coming from ATM." + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "id": "f7d75696-1bea-4bf0-b6a0-58a14f5561e4", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "ppo_bm_UM1_ep = pd.DataFrame(simulate_episode(env=env_UM1, agent=PPO_bm_UM1, observed_var='bm'))\n", + "ppo_2o_UM1_ep = pd.DataFrame(simulate_episode(env=env_UM1, agent=PPO_2o_UM1, observed_var='2o'))\n", + "ppo_mw_UM1_ep = pd.DataFrame(simulate_episode(env=env_UM1, agent=PPO_mw_UM1, observed_var='mw'))\n", + "\n", + "cr_UM1_ep = pd.DataFrame(simulate_episode(\n", + " env = env_UM1, \n", + " agent = CautionaryRule(\n", + " env = env_UM1,\n", + " **(from_radius_theta(*cr_UM1.x)), \n", + " ), \n", + " observed_var='bm',\n", + "))\n", + "\n", + "esc_UM1_ep = pd.DataFrame(simulate_episode(\n", + " env = env_UM1, \n", + " agent = ConstEsc(\n", + " env = env_UM1,\n", + " escapement=cr_UM1.x[0], \n", + " ), \n", + " observed_var='bm',\n", + "))\n", + "\n", + "msy_UM1_ep = pd.DataFrame(simulate_episode(\n", + " env = env_UM1, \n", + " agent = Msy(\n", + " env = env_UM1,\n", + " mortality=msy_UM1.x[0], \n", + " ), \n", + " observed_var='bm',\n", + "))" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "id": "22240bd9-936c-46f8-9f11-ac8063f0642a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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+jjnr93X1UAii0wmHw7jppptQUFCA0tJS3HXXXZBlGUBsSGjHjh0499xzkZubi/z8fFx44YXYu3ev+vi9996LsWPHYvr06ejbty9yc3Nxww03QJIk/P3vf0dlZSXKy8vx4IMPGsbw2GOPYdSoUcjJyUGfPn1www03oLW1VX18+/btOOecc1BUVIScnByMGDECn3zyCQCgoaEBl156KcrKypCdnY3BgwfjpZdeyuA7dvhjOyQ0adIk9aAxY8aMGTH3FRQUoL29Pe5z3nzzTbvDIIjDnse+2AAAuPqlxVj/wJnwODve2pro2ciyDF8XuHbZLoftKpGXX34Z11xzDb7//nssWbIEv/71r9G3b19cd911hu0ikYgqVr7++muEw2HceOONuOiiizB37lx1u82bN+PTTz/FrFmzsHnzZvz85z/Hli1bMGTIEHz99df49ttv8atf/QqTJ0/GhAkTAACiKOLJJ59E//79sWXLFtxwww2444478O9//xsAcOONNyIYDGLevHnIycnBmjVrkJubCwC46667sGbNGnz66acoLS3Fpk2b4PP5OvAuEtROliC6IcFwxPD320t24fJj+8XZmiCs4QtJGH73Z53+umvunwKv297lpk+fPnj88cchCAKGDh2KVatW4fHHH48RLLNnz8aqVauwdetWtcXFK6+8ghEjRmDx4sU4+uijATBhM336dOTl5WH48OE45ZRTsH79enzyyScQRRFDhw7Fww8/jDlz5qiCRZ/4W1NTgwceeAC//e1vVcGyY8cOXHDBBRg1ahQAYMCAAer2O3bswLhx4zB+/Hj1+UTHoNWaCaIbsnGfsQfRql2NXTMQgugijj32WIMrc9xxx2Hjxo2QJKNDtHbtWvTp08fQj2v48OEoLCzE2rVr1ftqamqQl5en/l1RUYHhw4dDFEXDfbyFPAB8+eWXOO2009CrVy/k5eXh8ssvR319vRoxuOWWW/DAAw/ghBNOwD333IMffvhBfe7111+PN998E2PHjsUdd9yBb7/9Ng3vSs+GHBaC6Ib8uMfYvXlPo7+LRkIcTmS7HFhz/5Qued2uxuVyGf4WBMH0vkiEuZvbtm3D2Wefjeuvvx4PPvggiouLsWDBAlxzzTUIBoPwer249tprMWXKFHz88cf4/PPP8dBDD+HRRx/FzTffjKlTp2L79u345JNP8MUXX+C0007DjTfeiEceeaTT/ufDDXJYCKIbskYRLMOrWI+h3Y0U+yY6jiAI8Lqdnf6TSpfTRYsWGf7+7rvvMHjw4Jh1aIYNG4adO3caGoiuWbMGjY2NGD58eGpvFIClS5ciEong0UcfxbHHHoshQ4Zgz549Mdv16dMHv/3tbzFz5kz8/ve/x/PPP68+VlZWhiuvvBL/+c9/8MQTT+C5555LeTwECRaC6JasrWWC5fThFQCYYEmU7E4Qhxs7duzAtGnTsH79erzxxhv43//9X/zud7+L2W7y5MkYNWoULr30Uixbtgzff/89rrjiCpx88slq/kgqDBo0CKFQCP/7v/+LLVu24NVXX8Uzzzxj2ObWW2/FZ599hq1bt2LZsmWYM2cOhg0bBgC4++678cEHH2DTpk348ccf8dFHH6mPEalBgoUguiF7mpijcuyAEggCS8Ktbwt28agIovO44oor4PP5cMwxx+DGG2/E7373O/z617+O2U4QBHzwwQcoKirCSSedhMmTJ2PAgAF46623OvT6Y8aMwWOPPYaHH34YI0eOxGuvvYaHHnrIsI0kSbjxxhsxbNgwnHnmmRgyZIiakOt2u3HnnXdi9OjROOmkk+BwOKgitoMI8mEwbWtubkZBQQGampqoTT9xWDDsrlnwhSR8/YdJuPDZhdjbHMAHN56AMX0Ku3poxCGC3+/H1q1b0b9/f2RlZXX1cIgeTrzj0c71mxwWguhmtAXCaq+M0lwPehVmAwD2UB4LQRA9GBIsBNHNONAaAMAqK3I8TlQrgoUSbwmC6MmQYCGIbgYXLKV5bFXzXkUkWAiCIEiwEEQ3Y38LS64tyfEAAKoLmGCpa6JeLARB9FxIsBBEN0N1WHKZYCnKYU5LY3uoy8ZEEATR1ZBgIYhuBhcsZUpIqDCbdeNsaKeyZoIgei4kWAiim1HfyoQJd1gKvUywNPnIYSEIoudCgoUguhnRIaHCbAoJEQRBkGAhiG5GtGApUBwWX0iCPyTFfR5BEMThDAkWguhmHFBCQiW5zFnJ8zghKmvHUViIIIieCgkWguhmRDssoiig0EthIYI4nBAEAe+//35XD+OQggQLQXQjQlIELf4wAKBYKWcGtEqhRqoUIgiih0KChSC6EdxBEQSgQBEpgJbH0kghIaIHMGnSJNx888249dZbUVRUhIqKCjz//PNoa2vD1Vdfjby8PAwaNAiffvqp+pzVq1dj6tSpyM3NRUVFBS6//HIcOHBAfXzWrFk48cQTUVhYiJKSEpx99tnYvHmz+vi2bdsgCAJmzpyJU045BV6vF2PGjMHChQuTjleWZZSVleHdd99V7xs7diyqqqrUvxcsWACPx4P29nbU1NQAAM4//3wIgqD+TSSGBAtBdCO4g5Kf5YKDJ65Ac1iaKCREdARZBoJtnf8jy7aH+vLLL6O0tBTff/89br75Zlx//fX4xS9+geOPPx7Lli3DGWecgcsvvxzt7e1obGzEqaeeinHjxmHJkiWYNWsW9u7diwsvvFDdX1tbG6ZNm4YlS5Zg9uzZEEUR559/PiKRiOF1//znP+P222/HihUrMGTIEFxyySUIh8MJxyoIAk466STMnTsXANDQ0IC1a9fC5/Nh3bp1AICvv/4aRx99NLxeLxYvXgwAeOmll1BbW6v+TSTG2dUDIAhCgzsoRV6X4X6ew0LN44gOEWoH/lrd+a/7//YA7hxbTxkzZgz+8pe/AADuvPNO/O1vf0NpaSmuu+46AMDdd9+Np59+Gj/88AO+/PJLjBs3Dn/961/V50+fPh19+vTBhg0bMGTIEFxwwQWG/U+fPh1lZWVYs2YNRo4cqd5/++2346yzzgIA3HfffRgxYgQ2bdqEI444IuF4J02ahGeffRYAMG/ePIwbNw6VlZWYO3cujjjiCMydOxcnn3wyAKCsrAwAUFhYiMrKSlvvS0+GHBaC6EY0tDFBwgUKh4eHKCRE9BRGjx6t/u5wOFBSUoJRo0ap91VUVAAA9u3bh5UrV2LOnDnIzc1Vf7jA4GGfjRs34pJLLsGAAQOQn5+vhmF27NgR93V5SGffvn1Jx3vyySdjzZo12L9/P77++mtMmjQJkyZNwty5cxEKhfDtt99i0qRJ9t8IQoUcFoLoRvAclsIoh6WIqoSIdODyMrejK17X7lNcxu+AIAiG+wSBhUwjkQhaW1txzjnn4OGHH47ZDxcd55xzDvr164fnn38e1dXViEQiGDlyJIJBo2sZ7zWSMWrUKBQXF+Prr7/G119/jQcffBCVlZV4+OGHsXjxYoRCIRx//PEW/3vCDBIsBNGN4CGfoiiHRWvPTyEhogMIgu3QzKHAkUceiffeew81NTVwOmMva/X19Vi/fj2ef/55TJw4EQBLgk0ngiBg4sSJ+OCDD/Djjz/ixBNPhNfrRSAQwLPPPovx48cjJ0d7710uFySJGkHagUJCBNGNaIjjsPC/G9rIYSGIaG688UYcPHgQl1xyCRYvXozNmzfjs88+w9VXXw1JklBUVISSkhI899xz2LRpE7766itMmzYt7eOYNGkS3njjDYwdOxa5ubkQRREnnXQSXnvtNTV/hVNTU4PZs2ejrq4ODQ0NaR/L4QgJFoLoRjTGcVjyeZUQ5bAQRAzV1dX45ptvIEkSzjjjDIwaNQq33norCgsLIYoiRFHEm2++iaVLl2LkyJG47bbb8I9//CPt4zj55JMhSZIhV2XSpEkx9wHAo48+ii+++AJ9+vTBuHHj0j6WwxFBllOoN+tmNDc3o6CgAE1NTcjPz+/q4RBEyvzm1SX47Me9+J9zR+Dy42rU+5duP4gLnl6IvsVezLvjlK4bIHHI4Pf7sXXrVvTv3x9ZWVldPRyihxPveLRz/SaHhSC6EVpIyOiw5HqYw9IaSNwPgiAI4nCFBAtBdCPihYRys1giYaufBAtBdAW8i67Zj77/C5E5qEqIILoR8ZJu8xTBEpQi8IckZLkcnT42gujJvPDCC/D5fKaPFRcXd/JoeiYkWAiimyDLstp6vyjH6LDkuLWvamsgTIKFIDqZXr16dfUQejwUEiKIbkJ7UEJQYg2qolvzO0QBOW4mUigsRBBET4QEC0F0E/a3BAAA2S4Hsk0cFDWPhRJvCYLogZBgIYhuwj5FsJTne9SW4Hryspjr0uynXiwEQfQ8SLAQRDdhX4sfAFCe5zF9PNdDlUIEQfRcSLAQRDdhX7PisOSZN/nKo5AQQRA9GBIsBNFFrK1txi1vLMfOg+0AtJBQWTKHhQQLcZgjyzJ+/etfo7i4GIIgoLCwELfeequl506aNCnptoIg4P333+/wOK1y7733YuzYsZ32eh2hs98bO9gWLPPmzcM555yD6upqS//Y3LlzIQhCzE9dXZ1hu6eeego1NTXIysrChAkT8P3339sdGkEcUkx7eyU+XLkHv3zhOwC6kFC+uWDhDksLhYSIw5xZs2ZhxowZ+Oijj1BbW4sNGzbgf/7nf9K2/9raWkydOjVt+0vG7bffjtmzZ9t6Tk1NDZ544onMDCgB+vdm27ZtEAQBK1as6PRxmGFbsLS1tWHMmDF46qmnbD1v/fr1qK2tVX/Ky8vVx9566y1MmzYN99xzD5YtW4YxY8ZgypQp2Ldvn93hEcQhw9raZgDAzoM+tAfDapVQvJAQb89PgoU43Nm8eTOqqqpw/PHHo7KyEuXl5cjLy0vb/isrK+HxmE8MMkFubi5KSko67fU6Qme/N3awLVimTp2KBx54AOeff76t55WXl6OyslL9EUXtpR977DFcd911uPrqqzF8+HA888wz8Hq9mD59ut3hEcQhgSzLqmMCAJ//uBd7m5Mk3ao5LFQlRBy+XHXVVbj55puxY8cOCIKAmpqamDDPv//9bwwePBhZWVmoqKjAz3/+c8M+IpEI7rjjDhQXF6OyshL33nuv4XF9dIC7CDNnzsQpp5wCr9eLMWPGYOHChYbnPP/88+jTpw+8Xi/OP/98PPbYYygsLLT0P0WHhK666iqcd955eOSRR1BVVYWSkhLceOONCIXYd3vSpEnYvn07brvtNjUqwVmwYAEmTpyI7Oxs9OnTB7fccgva2trUx2tqavDXv/4Vv/rVr5CXl4e+ffviueeeUx8PBoO46aabUFVVhaysLPTr1w8PPfSQ6XvTv39/AMC4ceMgCAImTZqEefPmweVyxURJbr31VkycONHS+5EqnZbDMnbsWFRVVeH000/HN998o94fDAaxdOlSTJ48WRuUKGLy5MkxBwwnEAigubnZ8EMQhxL1bUGDU/LFmr2GsmYz8qhKiOggsiyjPdTe6T+yLFse4z//+U/cf//96N27N2pra7F48WLD40uWLMEtt9yC+++/H+vXr8esWbNw0kknGbZ5+eWXkZOTg0WLFuHvf/877r//fnzxxRcJX/fPf/4zbr/9dqxYsQJDhgzBJZdcgnCYfde++eYb/Pa3v8Xvfvc7rFixAqeffjoefPBBy/+TGXPmzMHmzZsxZ84cvPzyy5gxYwZmzJgBAJg5cyZ69+6N+++/X41KAMx5OvPMM3HBBRfghx9+wFtvvYUFCxbgpptuMuz70Ucfxfjx47F8+XLccMMNuP7667F+/XoAwJNPPokPP/wQb7/9NtavX4/XXnsNNTU1pmPkqRlffvklamtrMXPmTJx00kkYMGAAXn31VXW7UCiE1157Db/61a869J4kI+Ot+auqqvDMM89g/PjxCAQCeOGFFzBp0iQsWrQIRx55JA4cOABJklBRUWF4XkVFBdatW2e6z4ceegj33XdfpodOEBljy/42w9+Ltx1Eo9KWvyJJlRCFhIhU8YV9mPD6hE5/3UW/XASvy2tp24KCAuTl5cHhcKCysjLm8R07diAnJwdnn3028vLy0K9fP4wbN86wzejRo3HPPfcAAAYPHox//etfmD17Nk4//fS4r3v77bfjrLPOAgDcd999GDFiBDZt2oQjjjgC//u//4upU6fi9ttvBwAMGTIE3377LT766CNL/5MZRUVF+Ne//gWHw4EjjjgCZ511FmbPno3rrrsOxcXFcDgcyMvLM7wHDz30EC699FLVbRo8eDCefPJJnHzyyXj66aeRlcXOHT/5yU9www03AAD++Mc/4vHHH8ecOXMwdOhQ7NixA4MHD8aJJ54IQRDQr1+/uGMsKysDAJSUlBjGcc011+Cll17CH/7wBwDAf//7X/j9flx44YUpvx9WyLjDMnToUPzmN7/BUUcdheOPPx7Tp0/H8ccfj8cffzzlfd55551oampSf3bu3JnGERNE5tmyvxUAMK5vIQRBqxByO8SYhQ85PCTUQlVCRA/m9NNPR79+/TBgwABcfvnleO2119De3m7YZvTo0Ya/q6qqkuZE6p9TVVUFAOpz1q9fj2OOOcawffTfdhkxYgQcDq2jtZUxrly5EjNmzDCsFD1lyhREIhFs3brV9H8RBAGVlZXqvq+66iqsWLECQ4cOxS233ILPP//c9tivuuoqbNq0Cd99xwoGZsyYgQsvvBA5OTm292WHLln88JhjjsGCBQsAAKWlpXA4HNi7d69hm71795qqawDweDzdNimIIKyw9QBzWMb0LkSzL4TNiuNSVZhl2uUWoMZxRMfJdmZj0S8Xdcnrpou8vDwsW7YMc+fOxeeff467774b9957LxYvXqzmlLhcRtEvCAIikUjC/eqfw7+DyZ7TEVIZY2trK37zm9/glltuiXmsb9++lvZ95JFHYuvWrfj000/x5Zdf4sILL8TkyZPx7rvvWh57eXk5zjnnHLz00kvo378/Pv30U8ydO9fy81OlSwTLihUrVAXrdrtx1FFHYfbs2TjvvPMAsINk9uzZMXE5gjhc4IKlf2kOmnSC5cLxfeI+h7fmpz4sRKoIgmA5NNOdcTqdmDx5MiZPnox77rkHhYWF+Oqrr/Czn/0sI683dOjQmFya6L/TjdvthiRJhvuOPPJIrFmzBoMGDerQvvPz83HRRRfhoosuws9//nOceeaZOHjwIIqLi2PGACBmHABw7bXX4pJLLkHv3r0xcOBAnHDCCR0akxVsC5bW1lZs2rRJ/Xvr1q1YsWIFiouL0bdvX9x5553YvXs3XnnlFQDAE088gf79+2PEiBHw+/144YUX8NVXXxlsqGnTpuHKK6/E+PHjccwxx+CJJ55AW1sbrr766jT8iwTR/WhoDwJgTeIGleeq9192bPx4spbDQlVCRM/lo48+wpYtW3DSSSehqKgIn3zyCSKRCIYOHZqx17z55ptx0kkn4bHHHsM555yDr776Cp9++mlcNzQd1NTUYN68ebj44ovh8XhQWlqKP/7xjzj22GNx00034dprr0VOTg7WrFmDL774Av/6178s7fexxx5DVVUVxo0bB1EU8c4776CystK04qm8vBzZ2dmYNWsWevfujaysLBQUFAAApkyZgvz8fDzwwAO4//770/mvx8V2DsuSJUswbtw4Nclp2rRpGDduHO6++24ArOnMjh071O2DwSB+//vfY9SoUTj55JOxcuVKfPnllzjttNPUbS666CI88sgjuPvuuzF27FisWLECs2bNiknEJYjDBZ44m+tx4tIJfXHykDI8ftEYFGSb568AgNfN4t1twdjZDkH0FAoLCzFz5kyceuqpGDZsGJ555hm88cYbGDFiRMZe84QTTsAzzzyDxx57DGPGjMGsWbNw2223qUmumeD+++/Htm3bMHDgQDX5dfTo0fj666+xYcMGTJw4Ub32VldXW95vXl4e/v73v2P8+PE4+uijsW3bNnzyySeGViMcp9OJJ598Es8++yyqq6tx7rnnqo+JooirrroKkiThiiuu6Pg/bAFBtlNv1k1pbm5GQUEBmpqakJ+f39XDIYikTPz7V9h50IeZNxyPI/sWWXpOY3sQY+9npZkbH5wKl4NW1iDi4/f7sXXrVvTv3z+jF9aeynXXXYd169Zh/vz5XT2ULuOaa67B/v378eGHHybdNt7xaOf63SU5LATR02nVOSxW8bq1bduDEgqySbAQRGfxyCOP4PTTT0dOTg4+/fRTvPzyy/j3v//d1cPqEpqamrBq1Sq8/vrrlsRKuqAzHkF0ATxx1o5gcTtFuBwsZt5GibcE0al8//33OP300zFq1Cg888wzePLJJ3HttdcCYCXK+lJj/c9rr73WxSNPP+eeey7OOOMM/Pa3v03Y2ybdkMNCEJ1MICwhJLFIbG6Wva9gjseJxvYQ2oMkWAiiM3n77bfjPvbJJ5+obfWjORxzMTujhNkMEiwE0cno+6jkuG0KFjcTLG0BSrwliO5Com6xRPqgkBBBdDI8HOR1O+AQ7ZVFqpVCFBIiCKKHQYKFIDqZVPJXOF7lOVTaTFglk91aCcIq6TgOKSREEJ2MWiFkM38FAHI9zGGhHBYiGW63G6IoYs+ePSgrK4Pb7c5oozOCMEOWZQSDQezfvx+iKKrdc1OBBAtBdDIdcliUnBfKYSGSIYoi+vfvj9raWuzZs6erh0P0cLxeL/r27WvaoM4qJFgIopPpiGDJoRwWwgZutxt9+/ZFOBw2XQ+GIDoDh8MBp9PZYYePBAtBdDIdEixqDgsJFsIagiDA5XLFrOBLEIcalHRLEJ1MKl1uOVywtFPSLUEQPQwSLATRyagOSwpJt7ysuZVCQgRB9DBIsBBEJ9OxHBbFYSHBQhBED4MEC0F0Mh0pa86hPiwEQfRQSLAQRCfTsaRb6sNCEETPhAQLQXQy6ejD0kp9WAiC6GGQYCGITiYtDgvlsBAE0cMgwUIQnUyHyprdVNZMEETPhAQLQXQyvhATG1lKibIduMNCjeMIguhpkGAhiE4mEGarlmY5UxEsfC0hEiwEQfQsSLAQRCcT4A6Ly/7XjyfdhiQZwXDHl2snCII4VCDBQhCdDHdYPC77Dku27jk8tEQQBNETIMFCEJ2ILMuaYHHa//q5HNpqp2GJHBaCIHoOJFgIohMJ6MI4qQgWQRDgEJloCUfktI2LIAiiu0OChSA6EaNgsR8SAgCnIlgoh4UgiJ4ECRaC6EQCYZZ3IgjG8I4d3A72tSWHhSCIngQJFoLoRAIhLX9FEFITLE5F6FAOC0EQPQkSLATRiWgJt6mFgwDAqTgsIYkcFoIgeg4kWAiiE+EhoVQSbjkuJYclRA4LQRA9CBIsBNGJaD1YOiBYnDyHhQQLQRA9BxIsBNGJaDksHQgJqQ4LhYQIgug5kGAhiE4kLSEhXiVEgoUgiB4ECRaC6EQ60uWWw6uEKIeFIIieBAkWguhE0lEl5FKrhEiwEATRcyDBQhCdCF+puUNJtyI1jiMIoudBgoUgOhHusGR1qA8LhYQIguh5kGAhiE4kHWXN1DiOIIieiO2z5rx583DOOeeguroagiDg/fffT7j9zJkzcfrpp6OsrAz5+fk47rjj8Nlnnxm2uffeeyEIguHniCOOsDs0guj2pKNKyE2t+QmC6IHYPmu2tbVhzJgxeOqppyxtP2/ePJx++un45JNPsHTpUpxyyik455xzsHz5csN2I0aMQG1trfqzYMECu0MjiG6PPy19WBSHhXJYCILoQTjtPmHq1KmYOnWq5e2feOIJw99//etf8cEHH+C///0vxo0bpw3E6URlZaXd4RDEIUU6HBZa/JAgiJ5Ip+ewRCIRtLS0oLi42HD/xo0bUV1djQEDBuDSSy/Fjh07OntoBJFx1E63HakSosZxBEH0QGw7LB3lkUceQWtrKy688EL1vgkTJmDGjBkYOnQoamtrcd9992HixIlYvXo18vLyYvYRCAQQCATUv5ubmztl7ATRUdLTh4U5LEFyWAiC6EF0qmB5/fXXcd999+GDDz5AeXm5er8+xDR69GhMmDAB/fr1w9tvv41rrrkmZj8PPfQQ7rvvvk4ZM0Gkk/SEhMhhIQii59FpIaE333wT1157Ld5++21Mnjw54baFhYUYMmQINm3aZPr4nXfeiaamJvVn586dmRgyQaSddLTmdymLH9JqzQRB9CQ6RbC88cYbuPrqq/HGG2/grLPOSrp9a2srNm/ejKqqKtPHPR4P8vPzDT8EcSig5bB0pHEc9WEhCKLnYTsk1NraanA+tm7dihUrVqC4uBh9+/bFnXfeid27d+OVV14BwMJAV155Jf75z39iwoQJqKurAwBkZ2ejoKAAAHD77bfjnHPOQb9+/bBnzx7cc889cDgcuOSSS9LxPxJEtyGdqzVTp1uCIHoSts+aS5Yswbhx49SS5GnTpmHcuHG4++67AQC1tbWGCp/nnnsO4XAYN954I6qqqtSf3/3ud+o2u3btwiWXXIKhQ4fiwgsvRElJCb777juUlZV19P8jiG5FOpNuqayZIIiehG2HZdKkSZDl+Fb0jBkzDH/PnTs36T7ffPNNu8MgiEOSdOSwUOM4giB6IrSWEEF0IulYrZkaxxEE0RMhwUIQnUgwDSEhNyXdEgTRAyHBQhCdSFpCQorDQkm3BEH0JEiwEEQnwquEstJQ1kyN4wiC6EmQYCGITkRbrZkaxxEEQdiBBAtBdCLcYXGnoQ9LkBwWgiB6ECRYCKKT8IckNVE2Lyv1ZbyoSoggiJ4ICRaC6CQa20MAAIcoINeTumBxUQ4LQRA9EBIsBNFJNPqCAIDCbBcEQUh5P04lhyVEOSwEQfQgSLAQRCfR0MYclkKvq0P7obWECILoiZBgIYhOook7LF53h/ZDISGCIHoiJFgIopPgOSyF2R1zWKhxHEEQPRESLATRSTT6mGAp6HBIiPdhIYeFIIieAwkWgugkNIelYyEhdbXmMDksBEH0HEiwEEQnoeWwpCnplhwWgiB6ECRYCKKTUB2WdIWEKIeFIIgeBAkWgugkuGAp6HDSLVUJEQTR8yDBQhCdBE+67WhZM28cFySHhSCIHgQJFoLoJJratU63HYEvnEhVQgRB9CRIsBBEJ9GghISK0uSwSBEZskyihSCIngEJFoLoBPwhCb6QBKDjfVh4DgsAdfVngiCIwx0SLATRCexrDgAARAHI68BKzYBWJQQAYVoAkSCIHgIJFoLoBN5duhMAcFS/Iohi6is1A1ofFgAIhclhIQiiZ0CChSAyTCAs4bVFOwAAVx3fv8P7c+oET4gcFoIgeggkWAgiwyze2oD6tiDK8zyYMqKiw/sTBEEVLdSLhSCIngIJFoLIMJv2tQAAxvYpNCTMdgRasZkgiJ4GCRaCyDCb9rcCAAaV56Ztn+p6QiRYCILoIZBgIYgMs2kfEywDy9IvWKh5HEEQPQUSLASRYTbtawOQXoeF57CQw0IQRE+BBAtBZJCm9hAOtLIeLAMzEBKipFuCIHoKJFgIIoPw/JXK/CzkdrBhnB4XJd0SBNHDIMFCEBlkez0LBw0oy0nrfp1q0i05LARB9AxIsBBEBmnxhwF0fMHDaNQ+LNQ4jiCIHgIJFoLIIG1BJli8bkda90s5LARB9DRIsBBEBmkPsBWac9KYvwJoOSxBymEhCKKHQIKFIDJIphwWJzksBEH0MEiwEEQGybTDQjksBEH0FEiwEEQGyZjDIlKVEEEQPQvbgmXevHk455xzUF1dDUEQ8P777yd9zty5c3HkkUfC4/Fg0KBBmDFjRsw2Tz31FGpqapCVlYUJEybg+++/tzs0guh2tAcVh8WdboeF1hIiCKJnYVuwtLW1YcyYMXjqqacsbb9161acddZZOOWUU7BixQrceuutuPbaa/HZZ5+p27z11luYNm0a7rnnHixbtgxjxozBlClTsG/fPrvDI4huRVtAcVg86a4SUkJCJFgIgugh2J72TZ06FVOnTrW8/TPPPIP+/fvj0UcfBQAMGzYMCxYswOOPP44pU6YAAB577DFcd911uPrqq9XnfPzxx5g+fTr+9Kc/2R0iQXQbMuWwUOM4giB6GhnPYVm4cCEmT55suG/KlClYuHAhACAYDGLp0qWGbURRxOTJk9VtCOJQJWN9WKhxHEEQPYz0TvtMqKurQ0VFheG+iooKNDc3w+fzoaGhAZIkmW6zbt06030GAgEEAgH17+bm5vQPnCDSQKaqhJzqWkLksBAE0TM4JKuEHnroIRQUFKg/ffr06eohEYQpme50S0m3BEH0FDIuWCorK7F3717DfXv37kV+fj6ys7NRWloKh8Nhuk1lZaXpPu+88040NTWpPzt37szY+AkiVWRZ1nJY0t6HhRrHEQTRs8i4YDnuuOMwe/Zsw31ffPEFjjvuOACA2+3GUUcdZdgmEolg9uzZ6jbReDwe5OfnG34IorsRCEcgRZigSH8fFiUkRDksBEH0EGwLltbWVqxYsQIrVqwAwMqWV6xYgR07dgBg7scVV1yhbv/b3/4WW7ZswR133IF169bh3//+N95++23cdttt6jbTpk3D888/j5dffhlr167F9ddfj7a2NrVqiCAORbi7AgDeTFUJhclhIQiiZ2D7LLpkyRKccsop6t/Tpk0DAFx55ZWYMWMGamtrVfECAP3798fHH3+M2267Df/85z/Ru3dvvPDCC2pJMwBcdNFF2L9/P+6++27U1dVh7NixmDVrVkwiLkEcSvAeLFkuEQ7FEUkXbmrNTxBED8O2YJk0aRJkOf6szqyL7aRJk7B8+fKE+73ppptw00032R0OQXRbuMOSm+b8FYD6sBAE0fM4JKuECOJQQKsQyoRgoU63BEH0LEiwEESG4D1Y0p1wCwAuZfHDcIQcFoIgegYkWAgiQ3CHJd0lzYC2llCQHBaCIHoIGe90SxA9jRZ/CNvr27WFDzPgsDjVPiwkWAiC6BmQYCGINHPxc9/hxz3NmDKCVbmle+FDQL9aM4WECILoGVBIiCDSzI972NpWn/3Iujd7PRlwWJQclhDlsBAE0UMgwUIQacSs5D8jDouTN46jkBBBED0DEiwEkUYa20Mx9xXnuNP+Oi6RGscRsWza14o3vt+BfS3+rh4KQaQdymEhiDRS2xR7oSjL86T9dahxHBHNzGW7MO3tlQCAs0ZV4alLj+ziERFEeiGHhSDSSF2zL+a+0txMCBZyWAgjs9fuU3+fv3G/uvAmQRwukGAhiDRi7rCkPyTkpsUPiSjW1jWrvzf7w/hxT1MXjoawzOz7gXevAWjykRQSLASRRmobTQRLblbaX8ep5LCE6CRHAPAFJWw70AYAGNOnEADw7eb6LhwRYYnNc4D5jwKr3wUObu7q0XR7SLAQRBoxc1hKM+CwaI3jyGEhgI37WhCRgZIcN84dUw2ABEu3JxIBPr9L93e468ZyiECChSDSSHQOi9ftyMjihy5a/JDQsa62BQBwRFUexvYtBABs3NvShSMikrJnObB3lfa3TN/lZJBgIYg0Eu2wZKJCCABcisMSJIeFgJa/ckRlPvqX5ABgx6I/JHXlsIhErPuv8W8SLEkhwUIQaaShLWj4OxMVQoDOYaEcFgJQ81cGleei0OtCfhZz9XYcbO/KYRGJWPex8W8SLEkhwUIQaaRVWfAwV1mhuTQ3/fkrgNaan3JYCACoV4RyWa4HgiCgppS5LFsVIUN0M+o3Awc2AKILcOex+0iwJIUEC0GkiUBYUhu59Sn2AshcSIj3YQlRDgsBoL6VCZZiRSD3U8JC2+tJsHRLts1nt30mANmF7HcSLEkhwUIQaaItoOUL9CnKBpC5kJDbIaIMDTg2shwwWb+I6DnIsoz6tgAAoDSHHW81JUwwb6unkFC3ZPu37Lbf8YCgXIYpvJsUEiwEkSbalHBQlkvET8dWo2+xF6cdUZGR13JK7XjL/T942f0wIouezchrEIcG7UEJ/hC72JWQw3JoYCZYyGFJCq0lRBBpQstfceHs0dU4e3R1xl4rd979KBbrAADCl/cCQ84Aigdk7PWI7stBJX/F4xThdTsAAP1LFYflADks3Y7GHUDTTkB0An2OIcFiA3JYMomvkez6HoQmWByZfaG2erhWvgoA2BKphBD2ASvfzOxrEt2WA61KOEhJuAWA3kVMsNQ1+2lNoe7GjkXstnI04M4hwWIDEiyZonYl8PcBwPQpQOu+5NsThzxcsOR4Mmxc/jgTQiSMVZEaTJemsvt2LcnsaxLdFu6wlOgq0kpzPXCIAqSIrAoaonNpD4ZxxfTvcd5T3xj74exeym77HMNuMyFYwoHDcrJMgiVTbPgMkCVg5yLgvWu7ejREJ9DWWYJFcVP+T5qIFZGB7L7dSw/LExSRHLVCKEcTLA5RQLlSoWa2XASRWWRZxi1vrMC8DfuxYmcj5qzTTVq5YOl1FLsVFUdWTkOTv8adwBu/BB4oBx6oAB4bATzUF5j1/zq+724ACZZMwQ9KAKhd0WXDIDqPtqgeLBmhZS+wewkAAZ/ieKyT+0J2ZAH+RtbbgehxHFAqhEpyjBVplQVs0c26RIJFCrPF9+b8lapU0siOg+34cu1e9e+Pfqhlv4SDzH0HNMGSLoclHARe+wWwXmlIJwWA5l1AoAn48f86tu9uAiXdZgJZNlr0/iZACgEOV9eNicg4rUpZc0YFyw6luqByJBp3FyMsSQiWj4KndjETMqWDMvfaRLfkoOKwRDcprMzngsUX8xwATKC8exWwVmkRXzwQGHNRpobZo9i8v9Xw9+x1e9EWCCOn/kcmJLIKtSR5Je+ow4JlwePA/rWAtxS44gMgK5+tBv3fW9Lj3nQDyGHJBI3bgfYDgKBLvvQ1dN14iE6h1d8JISFeDtn3eLV5nK98LLuP8lh6JLzLrT4kBGgOS21zHIdl7YeaWAGA2fcBoTjihrDFlv2snPysUVXoW+yFPxTB4m0HjeEgLlRUh6UDIV1fI/DNP9nvUx8GKkcChX2B3kez+yIkWIh48IOyagyQXcx+b6el3g932oKdUCWk69/gVhZAbC8bx+7bTYKlJ1KvJt0aQ0JViUJCkQgw7x/s9+NvAXIrgObdwM7vMzrWnsJmRbAMKMvBqF4FAIANe1uA2h/YBlVjtI3TERJa9goQagPKhwMjL9DuT2d+TDeABEsm2KVT0d4S9jsJlsOejFcJ+RqAvT+y3/tpDktLqXLyq1sNhCjBsqdxUM1hMTosFfkJBMuPM4G9qwF3LnDibazEFgAatmVyqD2GLUpIaEBZDoZUsLWCNuxtBepWsQ2qRmsbcyc+VRckHAB488hjb9CcG8O+D4/8JBIsmYDPdHuPJ8HSg8h40m3tDwBkoKgGyC1XF0D0eXsBOWVAJATU/ZCZ1ya6LS1KKDI/23jcVRWw5SHqokNCwTbgi7vZ78ffAniL2TEFkGBJE1uURScHlOZiSEUuAGBTXSOwbw3boFIvWOw5LOHo9cMWv8iSa/OqgFG/MD4m8n2nwWF5/wZg6YwuDRuSYEk3UsiYBU6CpceQccGyby27LR8BAHApDks4IgO9xrPHKI+lxxGvnJ6HhEY3z4X8+kXAW5cDi54DXv4pC/8U9gVOuIVtXNSP3ZJg6TAt/hD2tzDXa0BZDgYrDkt430Yg7AdcOUBRf+0JFgVLWyCMaW+twPB7PsP8jfvZnYEWLbR3yv8DXFnGJ3XUveHsXgqseA345A9M8HYRJFjSzd4f2UGZVcCy7r2HaQ5LsJ0lehEqLZlOuuWzs/JhAACXksMSlCJAb6VEcsfCzLw20W3hx120UC7P92C8sA7/FP8JYcMslmT76R+YA+zMBs5/DnAxF0Z1WBq3d+LID0/4cgiluR7kZblQU+KF2yFigLSFbVA5UnM+AMuC5e4PfsTM5bsRDEfw5uKd7M4lLwG+g0DJIGDML2OflK4clu9fYLcjzgdySju2rw5AgiXd8ITb6iPZQak6LAe7bkzpZtW7wOPDgX+OIdGiQ0u6zbTDwgSLUxEsYUkGBk1mj234jB1rq95ltv+6jzMzFqJbEJIiCITZhS76uPOIwGOe5yAKMnxlY4BT/gwMPJUdK5e9C/Q7TtuYQkJpg3cWrixgSdBOh4gBZTkYLipisHKU8QkWBcvCzQfU3+et34+g3wcsfIrdceJtgMPkvJMOh6X9ILD6Pfb70delvp80QH1Y0k10F8PDTbC07gf+77csXwIAtn8DHHFW146pm9DG+7BkZeBrJcs6wTIcgD4kFAGqxrITYd0q4O0rgG3ztef+ei5QPS79Y4omHGCJv9XjjDNIImPwcBBg4uzVrUJf1KFFzsYPk2bghBEJFscsVEJC7fUszODJS+9AZRmYeR2b4Fz8GuD0JH1KtyTYzvqd9J8I9D/JdJOGdla1VeTVkqAHludicP1u9ofy/VURNcESjoThFGPPH22BMPYoydMuh4CWQBibFn6I4a11Su7KhebjTYfDsmUu6x1TPpzlZXYhdFZJN7uXsVv+wR5uIaG6HzSxAmhltt2ZlW+xZLEMt65Xq4TcGRAsTbuAYAsgupj9C11IKCyzyoAjr2Tb6sUKAGz7Jv3jMeP964EXTgWWvNg5r9dR2g4A8x5h3YMPUXg4yOMU1eNBRTkOvo8cgVq/O/qpRrLytRYMDRkIC22ZA6x6B9j0BfsuHqq8dSkw7+/Ah7fE3aShnZ0fC3WCpXdRNgYLu9gfZUONT1Acllf3LsTxbxyP9ze9H7NP3telJMeN88f1AgA0r/uKPTj4DMAZ5/MVtGNCjkTwY/2PWLFvRdyxm8In4f2ON1YgdQEkWNJJoAXYv479Xn0kuz3ckm55WS1n+7doCbbgw80fYunepZC723o2P74P/N+vgf/+TktOyxAZTbrl7krJIPXkxB2WEK8aGHcZi2M7s9nxd/Kf2P07F6V/PGZw25iXWHZ3XjkX+Op/gM8ytM7KnIeAp08EFjyRsbJSLpLzzFy9rUywLIwMx954zeP0ZDIsxEMXAPsedmHiZsrsXAxsVkRCw1bcOPtGnPv+uXhvw3uG816j6rBonc375QvoLSghnbIjjPtVRMWnDavhC/tw1zd34ftaYz8c3jl3YHkujupXBACoPLiYPRjH6dHvGwBunXsrLv7oYlz+6eVYf3C9tf8ZiI0adCEkWNLJnhUAZCC/N5BXwe47XAXLUVex29qVeG3VS/jzgj/jqllX4ZkfnsnIy87ePhtT35uKk986GUvqLFbC+JtYW2rOnAeBfesyMr7WQBjtQWa75mSicVz9JnZbOli9y+1krxNUchjgygbOfxr4f7uB677STmS7Fmd+YUR9jDx6Btld2bua3WZC0C17Ffj6b8DeVcCX92TMdYq74KYUVt3PhZHhatVKQgr7sNvm3ekcIhPbm74EILC28W37ge2HYHL4qrfVX0OlQzBv1zxsadqCexfei61NW9XHeEioMFsTLEPEWoiCjCYhLzZpVREVhY5s9a6vd31t2GTTPkWwlOViUHkeCtCKviElibfmxPhjFrVz0SKdCKptq030n2pIIeW6Bq0SsQshwZJO9ijhoF5Havcdbjks+xTBMngKkN8LkCUcOLhRfXhL45aMvOx7G9/DrtZdOOg/iG/3WAxDbZrNREvxAKD/yey+jZ+nbUz1vnrc9c1dWLl/JV6Yz/7v/qU5MS3S08JBZWHDkoHqXW59lZAe0cGs2+pxgOgEWmqBpp3pH5NhfNoJG4V9M/tadmg/aC7WGndov/c9LvbxjtC6D/j0j8b7Vr2b3tdQaInn6u1bAwRbEHDmYq3cD/taLDgs+SzUkHbB8t2/2e2ws4EBk9jv3bVfUPtB4L3rgE//FBsq3PiF+qsUlRPSHGxWfzcNCUns+7cp0jvWhVYEi36fIX3YHZrDMqg8F4PKc3GMuA4iZEglg4G8yvj/j255GEnW8p0CkgUBCzCxGfYBngI1FN2VpCRYnnrqKdTU1CArKwsTJkzA99/Hb+c8adIkCIIQ83PWWVqi5lVXXRXz+JlnnpnK0LoWM+uM57AEW1hS4qGMFAL2K1ZixQi2gBcAKRJUN4n+oqUL/X7DkXCCLXVsns1uh/4EGKIcT1vmpG1MDy56EO9veh+XfXIZnp/HBMvtZwyFkIk4L1+JWXfS8Dh5DkuccIPbq1Uk6FcPzwR1K7XfrX4+meabfwJ/78/WyIlms+44cHvT+7rzH2Vt0quPBG5TBP7ORUBLXXpfBwnCkMr3tK1gKCIQsbfZwrknv5rdNqVRsLTuZzlkAHDcTdrxyDu+dicCLaxHzaq3gUVPA89NYhMegH3/GjRRLkVV3ejPT2pIKEdzWEp92wAA66UqNPuivh+KqAhZECwDy3JQkO3CUVl72GsVjUZCdA5LWLf/oBQ02zoW3gS1V/dIpLc9grfeegvTpk3DPffcg2XLlmHMmDGYMmUK9u3bZ7r9zJkzUVtbq/6sXr0aDocDv/iFsSPfmWeeadjujTfeSO0/6kp4wq1esHgKNJV7qLss9ZsAKQi489gsWjmA9V/eTAmWiK7kz9JryDJzWABg0GnAwFPY79u/TVv7+rX1a9Xf24ISirwu/GRUgtlOR+CCpVhzWHgOS1zBAgClSnhG74BkAv0FyOrJMJOseEPr5rrgcZa0rGfTl9rv6RRYLXuBJdPZ76fdDRT0Vqx02bjQYJpojdODBQeYYJFKWAjRmsOiCJbmPWkbH5a8yCpMeh0F9JnQvQXLitdZCI/Tsgf49n/Z7xs+Y7euHABAGMbvnP6c1NAW67A469nnsVHuhZ0N7cbXVRwWvaAIScZzHF9eoXcRE9ejPUz87nL2S/w/6R0W3XnassPSjfJXgBQEy2OPPYbrrrsOV199NYYPH45nnnkGXq8X06dPN92+uLgYlZWV6s8XX3wBr9cbI1g8Ho9hu6KiotT+o66idZ9iuwtA9VjtflE8fCqFeP5KxXAWclC+DFKCL1q60LsqlgTLvrUsFOLMBvoezxLd8qpYU7+d36U+kMad7OQlywhGjBfm/GxXZtyVkF8L6egcFrczTkhIDw/P6EMgmUB/AQp3sWDZuwb4+PfG++Y/qv0e8hkFi5RGwbL0JSbYeh+tieQhU9htBnJleNJtTCm9kvzvrGA9e/Y2B5InxOf3ZrfpCgmF/MD3z7Pfj7uRnTO4YKnfBARa0/M66YInjZ/5N+DCV9nvC59i3/nFyv8x/FwAQCQqiVp/fmo0KWvGgQ0AgE1yL+xqiGptL/D2BNp5NKwL34SlCJoVYcoTeQeAfUbrparE/5PisEQAyNA+f8sOi7ouXtfnrwA2BUswGMTSpUsxefJkbQeiiMmTJ2PhQmtJVC+++CIuvvhi5OTkGO6fO3cuysvLMXToUFx//fWor49/cQ8EAmhubjb8dDncXSkbGtvDoCsSb1e8Djw+Cnjq2PStwKoKFtYann8ZEsVebZHgQmf7NbiV2edo1q5aELT4Oc/0T4UnRgKvXwhsnh0TmvJmopwZUKxombl1uoQ9d7KQENB5gmWf5jZ1mcPSfhB491fA08exkEzNROCymeyxH9/XEoM3zQZCulluuhyWcFBzVyb8VrufrxsTXWGXBuIuuKmEhHJ6s+9qMByJDUVEo3dY0lHV9M0/gfYDQEEfYBi70CO3HMitBCBrnZu7A407FEEpsG6uw84Beh/DjpMnRgIHt7AQ+JFXAIjNYdFP1Bp97He1SigcVB3SjZFe2BXXYdG5yCb7EwSgINsFRCSUBtj3eWl7ReL/i+fHRN1tSbDoq14PRYflwIEDkCQJFRXGN6miogJ1dcnjs99//z1Wr16Na6+91nD/mWeeiVdeeQWzZ8/Gww8/jK+//hpTp06FJJk3u3nooYdQUFCg/vTp08fOv5EZEllnnS1YIhIw+3+Aph3A/rXpK+flJ1ze+Ig7LHbdDzPm/QN4sJJVV5hgCDtZcXH4jF+/yNjAU9nt5jTksexZHjMOrzsD1UGALn9lgKEPgtuhVAl1tcPiazTOyq3azekkHARe+ok2S+5/MvCz51illCeftS/n1Q5rP2S3onJBsSBYfGELC75t/wZo3csWohz2U+3+ypHs9sCGtOex8ZBQnl6w6C6Q7srhyFfcl6RhobxKAALrs9R+IPG2yVg/C5j7EPv91L8Yu7CqYaFulHi79iN2W3Miex8EATjnCZa0zjnm1+pkNBwtWJTzXiAsqdWChdmKw3JwCyBLCIhe1KEYexqjPgdFVMTLYeGOTX6Wi3W3btwOZySAgOzCypYkDf4EARBESFHOr6WQ0J7lAGQmOPOSCKNOolOzaF588UWMGjUKxxxzjOH+iy++GD/96U8xatQonHfeefjoo4+wePFizJ0713Q/d955J5qamtSfnTszXAFhBbUlv0lH0c4OCW2Zy+KvnE2z09Mci8+IKpQTcLocltqVrGeFLAEf3QbsiA3Z2H6NOqVkVS9Y9BUKbSmckPW5L7mVMSGhjAmWg0rlVbGxU6nLaSGHhQuWpp2ZK23mszBOhsKCCVkynYlzbykr6b7yQ+YYOFza577pCyau1iiCZdTP2W0SwbL6wGoc89ox+MfiJMJ/y1x2O+h0YyOv/F5sdh4Jx75XHYQvB2FwWJQLJNx5QH41KvLZgnhJE28dLiBXuTB1JCy08QvWYA2y0hvoYuPjVcp3Mh15LBGJTUA6ukTIDqXycJAWPUDFCOCsR9nxc9rdwMl36M555jksjUqFkCjoeuMon3lz7gAAAuqao8Svss9wnDy9g0pOjFp9uJ+FlzbL1djRGEwe6hMciD5DWBIsak7mkYm360RsCZbS0lI4HA7s3Wu8+O3duxeVlYmTDdva2vDmm2/immuuSfo6AwYMQGlpKTZt2mT6uMfjQX5+vuGnS4lI2iq5Zq2LucPia+ic8axUEpaPvpbZmrJk6CGQEr5GLY+iQnFYlNlHuKNJt7Pv106wkRAw42zWbGvnYnUTW4JFlrUeG3x2CzA7mouttf9llueiZw2vkxD9STwrP2YcGelwC2iNvPQrvALwOCyEhAp6sxlc2M9m/5kg2trv7Gq4kA/4+mH2+6l/iXU5+UVo/SfsuxH2MZeQlzMnWWfliWVPAABeWfNK4nFwwcIFEkefu8GFdJowXfiwXmkzUDoIEASU57M2+J2WeDv7fibORpwPnP1E7OP8vahNg8Py5b3Aq+cBj48E1n+a2j5kWZskRZe4H3UVcMUHwMTfM0FnkrcHaOcktQeL1w1RVFwNJX8lWMTyz3gCrQp3WGB+jtP2qTiCSkL1Jrka7UFJLaOOi+hAOCq1ztJ5mjvq+klfF2NLsLjdbhx11FGYPXu2el8kEsHs2bNx3HGJexm88847CAQCuOyyy5K+zq5du1BfX4+qqiQJRd2FvauBQBO74FaMin28s0NC2xaw2xE/02aRm2bH394K/KJU0IetRA3o+geYx14tEWxXO3Liyg/YRTkSYs22XjydVXjAZiVS43Yg0Aw43EDpEONjI85jtx/dCjzUG/j0DuDj26yNVS9YIpKhcgmQ4M1EwzhAW0G3yFgRwHNYQolCQg6X1l8jU2Ehnr9SoLg5ne2wbJ7DQj75vYFxl8c+PuRMwOFhTt4spfvv+F+x9wZI6rBEkixKB4Dlz9Qqpd0DTo59nAvlvekVLKZJt1ECtzyPOSz7rDSPK1COlVRLm/f+yBxM0QX85FHtPdbDL4D71nQs4bmlDvj+OfZ7sAX40qR83QoHt7Bmdg6PsWDCDNVhMboa/LynVQjp/m/uqikdbuMJlng5LA1tUUm8Srhvn4slScfkxEQjiJCQQkhov3Htsu6A7ZDQtGnT8Pzzz+Pll1/G2rVrcf3116OtrQ1XX301AOCKK67AnXfeGfO8F198Eeeddx5KSkoM97e2tuIPf/gDvvvuO2zbtg2zZ8/Gueeei0GDBmHKlCkp/ludDF+rpd9x5itmZndiSMjfxKpjAGZp8uzuulUdCwlwwaI/eNMREtr+Lct5KOjD+lb8/EUgr1opx5XZSajtgL1KJG41lx0Re8I84TYtl4Vj9UKuO4mHopPWxFDmQkL8AlRoLlgSOixA5vNYuGCpHsNuOzuHha9IPexs8+9fXgVw4q3a30U1LEzB8xOSHLPRPTdM2bEQgKxUo5m4zTwMsmd58n3ZwLQPC/+cFYHLHRZL7fn5MVZv7m4nhbu7Q6YAOSXm2xT1Z+XBYX/qrwOwCp6wn01KBAe7wPLwqR12KAUjvY5MviijySQN0Kp6TCuElBBOdjU7d+5rCUCK6M7FJjks+oR+7qCo+1T6wbTnsu/1zoNJ8qsEh/2k24ikjhvlRyTethOxLVguuugiPPLII7j77rsxduxYrFixArNmzVITcXfs2IHaWmPb3/Xr12PBggWm4SCHw4EffvgBP/3pTzFkyBBcc801OOqoozB//nx4PIfIip7c0eh3gvnjnemwHFDs4NwKILtQKUF2sCS6ltqET00IbxinP3iF2HiubcHCm7sNPJVZ572OAn6/Frjpe2VWKgObv7JX1myWcMtxOIGL/gP89F/A1L8r91k8znS9PJqDxpJMQQxkJiQUieguQDWGh/hid4FEDgugCZZMrBEjy5p1XDWW3XZmlVBEAjYooYBEq4afeBurGup3AnD1pyx5kjfVSiJILDksiu0f1z7vfTS73bM8rQ6UaUiIL16oiA9bDktH+6TwhHbu7JohilqotiN5LLwJ5Ml/BGqUc++6T+zvh1dR9pmQfFs+SYvuw6J8pvzz4InOkGVVROX3OgKiAIQjMupbdZ+FmcNi1oiOuzYHt7FdK59vUodFjE26TSpYDm5lEw9nNlBYk3jbTiSlM+xNN92Em266yfQxs0TZoUOHxk0Mys7OxmeffZbKMLoHEYlVBwDx13ToTMHChQVfz8WVzWYg+9eykwOPUdver9HWBGDqsFjuQsvhJcbRrgfAcg/2rgY2fmHPxVETbk3CcwDgzgGOvFwTd1YdgWZNsDSFYgVLRsqaW+uYABAcWmhHwbLDwnNf4jWP2/4tsOI1YPJ9seucJKNtPwvHQJen0Zl9WHYtYd+rrELWbycermzgqo+M91msEorOV4hmybaD2DtnPs4C4rcvLx7IxuhvZMe0Pjk/2AZsncc+38pRtlbENU26jQohlucpOSxWHBa9YIlE7HU3jUiaY1I1JvG2FSNZGfHeVQB+kXhbMwKtmlDuexxLot86j+UpHW9+bYoLD+VZSS4VeIKseQ5LzOfRuo+V2AsinCU1KMvbib3NAdQ1+1GuJEMnEywHeUgox82+W8p5yFU2ENjQFNvXxWTMUtQhlTQkxB31sqHdosMtp/uM5FBl12J2Esoq1GaY0XTmekJKQpba4RRIT5JbtBACOt44rmkXE0KCaB73H3w6u90826Zg4Q7LyMTbORSL1eoFVhcSaowSLBCDmVn0UA0H9YkJd/C1hBLmsADa+kN8PaJoXpoKLP8PsPgF++PjJ7bi/lpuU2eGhLYp+U/9TzIPByVCDQklFiyJRHhYiuCyFxehLMQuIlLRAPMNRVFLyNcneUck4I1LgDcuBp6daHul65hOt7KsOXLKDJxXCVlyWEqHMMcx2AI0brM1FjTuYCEahycmfBkDT9xPdTHSPcsBOcJEXkEv4IifsPt3LATabEwMpZB2DFtJLuWN2OJUCakLoPLJC2/nn98bcHpQWcAWOKzV57EkESyGkFDTTvZ/u7woKmftPJI7LI6YHJakDgufoHaj/BWABEvH4Znpg0+Pf8LszLJmHnfUCwu1jHBl7PZWaD+oVZjok1jFxF+0pHD7uNdRQLZJZ+M+E9hFpb0ekk4IJXwNXyPrPwNoiY7xcCoznLDfWn6PLum2STKeJAQxgOxM5LBE2ft6LDssvBy63kSw6KtBrIQ+ouH5K+XDtXyhzky6TeZuJsKiYEkUEnpn6S74QxH0F1gfqu+aCuPvqLfSzmGXTrDMfxTYqluZ10bZsyzLagfU/Gzlf2nbrzTFE1heGPQOi4Vutw4XUM6649oO13DHsmSQYQ0bU/iFUN9w0A67lDAOD7UV9mUFD3IE2GjDsd+/jjmYnoKYkKspfJIG4/uoOixKTpGagK+2JGAuZ6VZPpFaJRSncZw+JMRd0qIa9C5mbfotOSxRdyV1WFRHvXutvE6CpaNwwcIX1zODOyyhdlYVY4X2g6mtecMPNL2w4PbzzsWpJd7y+Hx+b2MXX+WEb3udH46av3Ka+eMOl5pfYmhOl+iCyKswCvqyHJ5EqL0yZGvdTpv1Dkub8TExmJkcFrXiI1awJF38kMMdlrZ9gD+qK7S+FNRMNCZDTcYepuUCdVZZsxQCdijt7uPljyVCzWFJPST0zaYDyEM7ygS2SN4rGxIcA30UwbJlDquOkcLAomfYfTyUZCOk2haU1OTNgmxFLHKBm1+tHt886dYXktTVnRPCHdnVM4E3fgl897S1AfHzROng5Nvy0HLTjthj0gq8jQR/TwEth8nOmk08HFQ12loojvdMidqWn5O4YFHPBVxgqIKFTZLqohwWCTBIIENIqF0XEuKOTVF/VJm5NXHGHB0Siu4hFYPJYqvdARIsHaF+MwvBCA62wF48PHlavNyKyzLvH2yV2b9WAyvftD6ekF+LX+uVca/x7GLSWmc+y05GPLVtknQryZK1qopIROtbYZa/wlFEkeWQULL8FT36ZNtkF9mQT1u5FUBTONphCWamSkjNR6iJeYgn3SbsdAuwUE1OGfs9uopizQfa76k4I6rDMkwLsXVW0m3tSpYfkF2UmnXNHZYkpbWJHJZt9W2oUdyVfXIhvtsdiu9i1JzIKgbb9gPb5gHbF7DzQXYxMPaXyotZFyxNSst2l0NAtks59hpjHTmv26l2wt1nZdVmHopd8z6w/mNg/mPWBnTAJGwcD2+x0qIfWrjZDjy8rc8F4oJl/SfABzdZm5ypgiVJzg0nTqt7LYeFPRLrsDCXs6JAESxRDkuiPimN+pCQzmGpLmT7ag2E0exP8N0VHAjbCQnpEoXVyU43gQRLR/jx/9ht/5MSz04FQbtgJGt5LYWA75RZlyyxPiRWXZH6TcwSzSrQOlYCbC0dbp1umw+8fyPw/KnWZ8Jq/kpUeZtJh0b2t4WT7r41rJGeOzfxOhV2w05q/ooFweK0IVhajEtPNElGG1YQA7HruaSDdISEAG2VZ30Z6eY5xnCE3QqvSETLQSgfrjlWnSVYVr3LbmsmppYY2MGQkCzL2H6gHf0FVn23Ta5Cky8Uv8zU4dL6AK16Tzt/DDuHVWMAtkRjk3IhK9Avuqnmr/Q1bFvGm8dZSbwd9lPgJ49of7ftszYgHhKK7n0UDx56srumkL9JS4DXC9Wq0axxIAAsf9VaziAX3Hx9tGTwQoNoh0XNYYlyWHSOCKC16zes6yTGCgq+v0hENoaEdAnVXrdTddZqo9v9G8YsImIn6ba9nvWxghDTrLKrIcHSEda8z25HnJ9829xydtua5Mu/4TMmapzZAATmbvAWycnQJ9xG25v9J7LbBY8BK/7DlhKwGi+34bAAFhNvtyutsPtMSJwsaeKwJKxE4svDJ0u4BdjJR51l2xMsgegxZCyHZRu7NXFY3FYdFkCXeKvMnA5sZM3z9Fhxxgxj28qSMx0eZh13psMSbGMLfALAkVemtg+LjeP0x55evNS3BdESCKOvuB8A0JTNGnmt2t2EuIxSKmJWvwv8oHSfHnG+ZfGkhzss+TwcBGhhS94ATqHCTmmzIADHXAdcp+SY8ZB2MrgYthISAjSxYXdRSC4y8nvFhn1P+oN6XrKU/K22DLB4YVZzWIxoOSyKw+I2d1h4u/4WvSMiiAhFna/5Oa49JIG3bMnPdmmtFZT8pCrFsdnTlCCPRbCZdMtd+ILebLLbjSDBkir1m9lsXnAAR5ydfHtVsCRpj84bLx1zHTD6Ivb7shnWxqQm3JrMcHhSor55mNULVFyHxbyJkqU8Fp4s2S9xh2RbeTJSSDuZWXFYAOt5F61GwRKJeu+EVHJYGnewNZTiVTWE/FrvHDPBYsdh4ReR3ctYou2LpzMxVNBHu4jaDQnVrmC3FSMM+UaIhNOz2q8Z8x8F/nUM8NZlrLt0UU3ikGIiUujDoj/Rb69neUz9PSwHw1HAWgYkFCx9j2PjDftZTlvNRLZQoyO5YNnT6MOtby7HD7saAWiCpdAgWJQk6qgSeFvt+Tk8X82KiAoHWKgLUC+mSeH5Jxs/t5dbZ9bEUo/V5G8prAkAkxwxU9Q+LEkcFo+TLf3Bl2NR9s8FC0+WBpAwJMRzYhyiwHLWVMHCxHF1IXPmYrrnRo05ev8JBQuvJizuXu4KQIIldZb/h90OPCV+R0c9VgRLJKKVaY44j61jAQAr34qZ4ZtiVtLM6Xs8s54Nr2fhRORv1mZt0UJInW3YFCyyrDksyZIlRSdkGPsexHVYDmxQMv7zk5dVcngYw2ZIKLoPA4QUcljevwH4+m/Ae3HW12raCUBmXUFNZrkuK2sJcQYrXaM3fQm8cxU7kVaOAq6drYUr7YaEePyftzPXdxXOhMuy6l22Ts2B9Ur/HgGY9P9S7xORQlmzPllx6wGWx9TXxQRLbhkLw6za3Rh/Z4IAnPcMExQ55cD5z7LxWxjLH95difdX7MFP/8XEfrNPCwmpRF3QOLxSKOkCiHos5viwwShCyZltPXl70GlM5DZsZS6LVZG7V5fobYbVVbhb9rCwu+jS8mmSwc95UQJgZ0MLTn10LhZvYwLF63YAjcraa1mFqvjjbpjRYRFiQkIROQIpImlVR24HhLBfSylQPt9KxWGpbUzssETstObnDgsPI3cjSLCkghRijbYA4MgrrD2H55QkCgntX8fis64coHIM0PdYoM+xzNpc+FTy14jnhADspHjhq8AFLxr/j2TwzP/cytgTUZKVS+NycAuLizvcrB1/IgQxZqXRuCEnnnBbMdJ68y1e2mwzJBSRox2WFHJYuDjlHTujadDi1Wb/j1olZCUkVDEcKBvGRMnORexCccGLrG29emFKUbDwhEV9TlAmerHMvp/d5lYAoy4EfvUZMOai1PeXimAxcVgqBXaRKq9mInltbUvi182rAG5cBNy8VAvdiMldgfV1xt4/TWaChU8uohwWW71YOGrIjL3OlqYt+GTLJ+ZJxaqzU239u+fJ0xaKfOYEYOZ11p6nrhofJ+/EYfF4VvN9+lgXvTxvL+rupTsOYMt+rXIw1+PUFost1BynfDUkZHRYQiZvWSgSUkNMuR6n9h67vOq5uFoNCSVwWARRFVgORXAldli6Z8ItQIIlNTZ+zpySnDJgyFRrz1EFSwKHha9p0edo9qUTBOCE37H7Vr2T2DaVwloM2SwkBLD9jfq5ZqVamVEnqsfn+SXRPQmSnSh4SWLV2OQxUtEZEy8Oy2HzRMg6pXLASv4Kx2rzuBjBwl4/15ULIMUqIf2sLmBykeONu+L0h7AVEgKAkRdov5/9mPaZqhdu9k4f9B9MXukly7GCRdQ7LGnuxeJv1hIOb1wEXPA80NdCK/VEWFxLSD8b1R/bWw+wC1RRhIX0KnrVAGCdSXmiZFw8eUCWbpV5C/k0LofxqhYjWEI+rQoxKoelzE63W06UU3Hft/fhj/P/iNUHTBZw1AsWOwz/qfY7b3OQCFlOHhISjUIrLgkS2uMiCAAERKJEmSAYvy9et1MTRHxRUAB5WWxsrYGwJvwEh5rDks2Tr6EIlqDmsKgCqKC3Kgq10uYEDosoqgLL62S9WxI6LAfJYTm8WPoyux37S10vjySoIaH98bcxW+J8wCRmQ7bUGtayiaFhG7PhndmGL4gpdhp8mbXk56htqm06LLsVwcI7fyZCdMb0PADihIXsZvwDmisQTnIi5zksivDkrpLXqQgWR0B1PCzj0B07OxfFPh5n0UOOpdWa9Rx9Dcu3Ov9ZYJxu1XTdTHpL0xac+vapuPvbuxPvq2EbCyuJLu3CIYraxSLdvVgSOX2pEiXU4uHXHRv6kNC+5gBEROANMpGQXdxb7bOxWTfbtjYWrSdMRI7glq9uwV8X/dWwiTOZYFFn4DksDKEjJYeFvz9yBIhEcMDHwhH81oDq7NgULGN+CRx/s/Y6yWipY8ed4IhfjWT1/BanoiopoiPGYYlOw83xOEz3z3NYpIisdsWFIKohoRjBol/c0iTcV1XIQ0KJHBaHKrD4/oORoLlTJstAvTFRuDtBgsUuTbuBTV+w38dZDAcBLF4NJHFYuGA5VrvP7dUSSHl3RzPUWccRye1NC/azCj94zTL/44SEkq4nxDt9Jipn1r2G2WnMVBSpZZU2ujNywWI1JKRY7bxyhAsWpyOklZZaQZaNxwJfQFOPPiRkgkttzS8jEkngvnG8xcDFr7GVivXojofNjZshyRLWH0zSG4MnTUevcKu+n2nOYclE500LIaFQJGQo09db6QfbgyhBM0RZYv05csowoCwHALBlf2vMvhKPRXMzattqMWfnHLy1/i3DRcUV9b2OqRJSL2i9YsIyttYT4uir9yIhVbj5wiaz+VQdFlEEJvyW/R5K0rEV0M5zJQPju7MWq7+iV7W2jOCIKWuGmcNiEhLKdjngFNlz1d4puqRbp+iEUzkuQ1IIrWoOi1NbGkQX7qtWHJY9Tb74/X9ErdNttssoiGJo288q/yBY6/zbyZBgscvK19lMoN+JQKmNLoDJcliadrGuj4KDNXrTw7Pp9WuQRMPdhbI4iWh6HBYtUyCmj4ABpYlSJE6balNCfi3XhPeGSYRocnKASdgp2K6dIKz2gQB0VUIWQ0LK7IaLtCxHjjJMmxfoQLNRJJktTKiWNJtn67t1jo6lPJZ4ODSngV+MTC9KerbxKq+opGl1dpshwRIv0TIVLAiW6PfBsMZLWxDlSv4KcsoBh1MVLDxcZHssUgjtIZbMG5EjBkeHC1QACIQlE4fFPH8FgLrQXltQUi+CycdkDPH5lN5DfslE9CR47aS4vMprBJMn+O5LknALWJ+QmTTZs4QY2+o+OiTEHBYewumj207QlTYr/6sgqi6yS3TBpYw/FAlpaxPpc2J0++NJt/5QRD0eYhAc6v55SAiIExbi+SsFfbpdSTNAgsUesswqdgCtM6VVeEgo2MJ6SETD3ZWq0YAn1/gYX/bcLGzAsfJF5lhNspRl7aJpVuKmJqAxwaLODBIJltqVTCjllFmzYkWnwX4V+bob0a9xcDMAmXUNtVK1xbHisIT8bIFLQBUsEVWwaCEhW0QL1+gOyPr3Pl4OiyNNgkWXy5FwFq2HO0LRa/hkqj3/vsw7LIvrFmNzo7ETtD8qVMgdlkhERqMvhAouWPJYPtKAUnY8bLEbEnLEfgYA4IvjOjS2h9AYLVj4DLwgVjTkepzIUXKsLLssot5hCWfGYQE0wQIo6yAlQO2snCDsa3VCFqeiKik6h8XDj3edYBEEIMvpMHVYAC2PpUXnsIRgLljUVv8eh9FBU8hyOVCcw0LLe+KFhXQCK8upiRDTxFu1JX/3CwcBJFjssWc5UL+R5YlElwgnw5OndbM0c1nM8lc43Imo+yH+hUC/CF0y1AZfSb7QrXvZCUQQzXsrqI3jmGDJdrD/L6Fg4ZUxfY+1Vk2gOzk4BAfcotv8NeysY6LHaeECy/tLiC4miKA5LG4hR3nM5rpPMYIlqiunr0HpNom4lrVBsFhNvDVDNyO15LA07mBuoOjUxDTH6rFll0QVcKmiy9Gob9uPaz+/FjfOvtGwSbRg4cddiz8MKSLrBEsVAKA/DwkdsBsSinW5AOPnoHdGDrYFY8uaeffXOC5Hud08Fl2ZejgcUP/3tAsWpwfgZbfJBAtvMpfQYbFQji3L2veaTyatIoqxAkDQXivL6YAoBbSQb1ROYUwvFtEYEuKCZdrbS/HsPOZ45Hic2v6i3mPePC5u4m2cc6ipYFETbkmwHPosf5XdHvETY4a/FQQhcS8Ws/wVTmFflmgYCZt3hQwHtAPNisNidQbCZ/gFvc2Ti6OqhDzKxT9hlRBvBd//5OTjVF6DnxwcgsMw+zCg5q/YFCxWHAHufuSUqjNhLliyHay/gixYiL/r4ceAK8f4GhweisurAnRxZz2iKKjxcMuJt2aYzO6jL9QG1s9it73Gx7qBanv+NDos4YC2AredcF8ydCsKH2jfi4gcQV1bnSEXIPrizE/yfEG6Pk6lSZzisAxUHJZt9e3qwoTWxqKJRn3IRf/6+t4dDW1BLSTkjXJY4giWMrUXi0VxLQjqpCQQ1ARYjGCRQtrxnJeCYBEEwK18DxIJloikCddEifVWzm/BVu21cmwKFp0AyHIwsaAPCUmyzHq8AGyS6i02PD1fdVhiQ0JO0QmXMv6Vu+uxXxGXOW6H9h5HjbdKzWOJ57BoAsshOlRXyDQk1I17sAAkWKxTvxlY9gr7/airU9sHtx713WYBoLlWW2W4j4lgEQRWAgxo3UX1HNjAxIynwNoMx2pISLfQlvl+HJChCRb+5Y3rsIT82uq6dgQL7yEgOtQvc4woUh0Wmxc0K+vf8GZN3tKYzrtZIhMsEQQSLpIXA5/dcYHZXm8sW08SDuLYLm02Qze75xfLsByOLzz5khT6klROJtrz8/whh8d6m3gr6EIePmX1bUmWDHkj0fkaqmBpY7e9lKZxXLD0KsqG2ykiGI5gT6JmXtHoEkXbdQtr8rwRWZaNDkt7MH6VkElICNBVCqXQPM6nW508Rsy27QcgM3HDmxDahYeFEq1m37wHCPuYuEv0vbCSw8IdTldOrOhOhlmIRSdYguGILkm/KsZJVh0WnnMiaGXHTkFzWPT7zHNBc2H168QB6iKIcZvH6QSWU3DCrXxHE+awdMMeLAAJlsRIIeDVnwGvng+89BMmCgafoa3LYxd+EHA3gPPDmwBkJlbyKmKeBkDrJsp7X+jZqVQPVY+xFmaxmkWfKOEWiGnqxr+8cQXLru/ZzDu30roTIopqG2yH4IBTiJMnk+py6PyEk8hR4K3zvcU6V0kJCYnKyU6Q1WRJS/DZEhcskZCxF0unChbd7F73PrSHTf6fljqtS/GwBIIlWRKzHfjJP6/CelMyK+hCHj6dg9CW4OLMxUyDIljKReUzyylluxQF1JSwi+9mO5VCurJmsxyWtqC2pgwAPD13s+rgxIaEzHMyqq2sOxON8h75w9p7EuOw8It/TmnqXYe5i5joO6QmyfYxuGMxWEn85mO2Gw4ClCRW9iufpEVXCalLaiihQj15Jg4L78PicrjUXEC9a1MqNkMVhVGOjdaLJXkOiyiIqsNiep5WzjtyN6wQAkiwJEaWWTOjzV+xPhy5FcAZD6a+vxLlIl2vEyyyrC3iliiRlzsse1bEPsYbzvU93to4rM6CEyXcAjHZ8rzGP65g2fQlux1wsvULTzyHJfo11NmlzQQ69QJrMSSkWOQRxQ0R4YEss/taQzYuUPyEWdjPPCyUzN1S4HksgY4IFp2FHi9/QmX9JwBkFg4qNMlryoTDwnvgmJz8O4SJwwLAIDzjhYQalJBQiaA4LDpnIaXEW11Zs9ln0Oo3Ti5+3MNe9+zRVazkNdDKumQDcR0Wvu6MLedHeY/8wWQOC1K7+HOshISsNnqz0sG4rQOCRdQWE+Rh8FjBwo/Z2Jb/MQsgRoeETByWokgj+yWnLEasWcthYb86REd8h8XfpObNnfbCFnXNqu4ECZZEiA7WZOv8Z4FL3wVuXRW/i6wVuKtwYJN238YvWDjDmZ141WfusOxbEzt75fkvyRYS5Fgu++ONj+KcIHTlcoDOYYm33w2fsdvBZ1gbJ6BUCWkOi2kOSzionTTtxtCt9A1RQ0IlusooRSDIImSJ7aM1mIJgyS3Twhx6wZKkpJmj9WJJQ0hICsfNn1DZqPQgGhqnw7PVvjZ2SHDy7xCCdvrz6S6UemcpXtItFyyFsiISvKXqNgNSSbzVhWkNDovyGRjWnlE4fXgFnrx4HPuDlxV7CrRFC6PQBIudXizcYYkv4uLlVtiCOyyJQkLcYUnWN0XXOG75vuW4/svrsb15u3GbDjosXADwQgNBiBJHCRwWbT0h7rA4wD/deCGhQllJ7s6NDblpgiXO5ypoLnXCkJBShn1QzsWWZuB3b65QF3PsLpBgSYToYE22xlwMDD7d2CArFVSHZRNb6EsKA1/cxe47+prEibyF/diFTQqyaiVO405WPmfWvyUeFlaGBaB96eLlxUQ5LEmtxv3r2DgHnWZtnIDh5OAUnOal0611AGQmxOzmOFgJCXEhYchhkZVbAYiwfdhyWFTXpkyzeA2ChZ+caxLuxpPWHBZjOCJmJh0OAFuUpOl4otNOF2Wr8OPQ6gJ1VhEEzUHQXZCtOCwH29j/lycpgiVHEyz9S1PoxZLE5Wr2x35XLxzfB6KSdG1W8hpNrw44LHpBx/NqVNSLf5xwthV4DktaHBbtvXx3w7tYsHsBZm2dZdxGDWOl4rBoAkDLYYn6/jVzwRJ7zOZbdFgE3dk1P8wFS+x7zIVobZPfvHlcnJBQdJWQ1MAmqLvlUuR6nNh6oA2vL4rKt+xiSLB0JkX92Akg7GMzohX/YRfx7CLgpNsTP1cQgH5KyGe7risqD7OY9W+Jh85hicgRrDu4LrY7rSwDLTzzP86FIqrjY8KQ0IbP2W3f4+y1Vhe1lUZFUdQcFv0FkZ8c8qvsx9Ct5Fy0KQ5LTomWw6Ik2EoSICuCpSWYZNE7PaoIKol1WMJBLR/Bag5Lh6qEtBO82exeZfu3QKiNCQfefTlmX4mrrhbVLsLPPvwZVuxbYX18yY7DjmCSVKoXLPGSbhvagnAijGyJ57DoQkJlqYSEeA6LeVmzmcNy0hBNJFlp3MYFS31bEP5QkrWi1HEpDouuH0xMbxg1JJRiwi1gTbBYdlg0x5C7ns3BZuM23BVKRWTpJlFmSbcAdK6gWQ5LVFmzPodFdKlhb/0+c0P1ccdbkZ8FQWCTlvo2k/OYIGplzbqQULRg2buTOf/7hDLcdjqLJHy1LsFivV0ACZbOxOHSLP7alcAcZa2Qk+6wdhHvpzTp4l1GZRlYMp39PuJnNsah5Rk8+8Oz+MV/f4HHlj5m3MbfxIQVEH9mG+Ww8C+CaWt+viLx4MnWxwkoawkpwxbi5LDwEsJUSiqthDD04kK5sPDuvhFZhCwpXURDNi5QPOPfTLA07WTdlF3epJZ1upNuE+aw8B46g06Ln4OUJOFx1rZZ2NiwEV9u/9L6+BLY6x2GC5awvZDQwfYgiqCIFcFhWLtnoBISqm3yW7fU43wG/PV5hVC/Ei/6FGfjjjOHwuPU5TIkaBrHyc/WmsdZdlkcsQ5UTKfbdISE3FywJBiX6rDUJN6XzmHh38mYyURH8m50OSxaWXMEOW4BeR4n/nnxWN0xa5bDoiyAqAoWQasSipPD4g3xCqHY8bqdIkpz2XnMdE0h3XnaKTjVPizRIaGDe1jhQiivN049gr3O4m0HrXdG7gRIsHQ2FUpjtw9uZF/0ov7A0ddae26N0gZ9x3fMct+1mDWTc3iMi9klQxcS+veKfwMAXl3zqnEbfhLKKojfolmMKpeL19RNCmudUa2WM+tfA7F2qeE19A6LXaw0jjMJCfEqITkiQI6wfbSELDosUggI8NwHE8HSoEu4TZKczJNuOyRYTFrzAyaChZeOVyRYDTtJTlCj0jE4ZsabiEzlsAA6waKd6K1WCZXyhFtvscHZK/S61e6jll0WXVjO3GFhF43B5bmYf8epuGFSVDVckgohgLWFt53HwkNmiXKb0hISUpJuzbqAA6wlAp+Y2Mhh4Z9lTLhWdVg6lsOi7xw7eUQpVt5zBs4dU53QYclWRKOPu1xxk251zegC3OU1H29VogowXa6hvg9LtMMSrGeCMLusBv1Lc1BT4kVIkvHNJpPFLrsIEiydzcTfsxmAv5El/Z39uPUVn8tHsJlcqA1Y/ynw8TR2/8gLYkrdEmIl6dbKrFZwGBoSmYZrANY7JtDMxE/VGOvjBIxVQrqkW4OL0xGHxUrjuLbYpFtJCRVLEQFQHBbLSbfcXRFE9p7ECJZt7NZCaSFPuk1ba/5EF6Z6Cz0aHEkES6ARgF3BEn+22mGSOCz6niyAdmw3tAdRbFIhxOF5LNvqLQoWfpGVpYRJt3x2HoO+70cCbFcKKd83fRgofpVQR0JCScqaeY6OKyd5nprueOZCJTYkxMecgsgycVgAIMfDmjki0MLO0XH2n+2KEiyiAyGTTrf6smaPXzkHxRFYXLDUmSXe6haQdQjxq4TcbcylK+vNvt+ThrLXWrCRBEvPpWoM8JN/MOHxk38AA0+x/lxR1JyUty8H6laxL+/ke+yNwUonyBYLMV5R60cgCmL8kmPe3bZmYuL+Caavoa0lZBBFaXNYknRmjUisTT6g9JlQkm6VU4AUEeznsHBhkl3E3g816VYRMjYESyb7sBgESySiayqVoNcNP7bi5ATZFiz6dZwyKli0/1WfwxIzC1X+bg2EUcJDQiYXUDXx1q7DAvOKJR4+4PkPMajf18TvERcsu+2GhBI6LB3IB+EkCwk160JeyVoiqA5L2DwkJMtaWXMqje50qyt7dIUY2fxXLh49+aZ5hVlcsARjHRb9WkL6kJDDl1hgVelWbY4dr8Mw6TMrjmj2h1AqsdfoO4Ct13VkP5am8MPuJtPX7ApIsHQF468G7thqPRSkZ+LvWeki57xn7J/IdXkGDiGOgLDssGghobht83lju5oUGu7pE8bilTV3JMchmcPiawD4atTZusZxvEoooiXdWs5h0efEANpJk5/oLPZgAdKVdGteJWS4MLXUspwmwZF40cokOUGqYAlYFCy8B4vDY8gTSRsmISGDwxItWBTHpdUfRokQWyHE0Uqb7QsWsxJinqCZ64kjWCyGOHopXVHtOix6wWJwWKSQTtB3pKyZd7qN837ZCQvqcli4w2IQLKF2rSrQ5LNLvn/NWXaJLghg59Bsl6IK+DEbR1xwhyUQ1gkWfdjbJOlW5K0V4oxX63Zr5rBo+4/Xh2X3gSaUo5ENu4zlWY7qxa4za2ubO9Y2IY2QYOkqUu0I6S0GfvYc69nym/nAEBs9TdTX1mYgTjHJCTBe512AWY36pm7xBAtfSTpeZUnCsToNdqZpa/6OLG2vljXHESw8HJRVyC7svHGc8nAkIqhJt5bLmqMFCxcm3MFQS5oT92AB0t2aP0EfFr5WVVE/Q4fYGBIk3cqybD+HpU1nhaezyy1HcfwMHX51Dgc/lvVxfykioy0ooViIrRDiDCi1KVj0XXdNkm5bVIfF5L2PSFqvoCQXdDUkZLXbrVr2rRMskl9bhoKHgwSHveq/aFxJHBZ1UmIh7Ku8l1I4qIXU9IKFH1POLONK0VbRt7oXnapgyfIoExt9o0kTslzsO2t0WNiveoeFh4RERCD4GtkGccJhWrdbc4clonNYzATLgdqdEAUZITjVcfcr9iLP40QwHMHGvTYX88wQJFgORYaeCfxiBitlTgVdSEjvsBhq+C05LKKhqZvaI0UvJgKtWgM6KwszRiM6DQljpqJIjUenMMNLtpZQ9MmH57Aorks4Iqp9WGyHhPjJh6+M6jvIwkJcuFhwWHgflg51ulXeUzlRlZDVRdFUxyr2/WwLtSEsswtvU8CizazLH6pr8mN1uu1p7rBIiR2WHCUpNBQJoU2p/CkBT7qNvTD1V7rdbt3fat4bI844ACTJYTGZYLTtZ1Vlgpg0v8N20q1yrvBFOWbqGLlgySlLfRIG6EJC6XBY2HvUrvtMW4It2ueg//6lIoKj+ppA6XTtcUVi928Cd1j84Qgbk+AwlDWLUD5jIYzeRdm4bEwBNJfXXBSqSbdxq4S087QaEtKdp1sOsKZxzc5i9T0RRQEjerHeYGn/3qUICZaeiK6rpkOXU2IMAVjJYYlqm28mJvjqqrkV9hKD9a+h/Goadgr51JPcprYsPPbFBhxotdFlVb3AxjmB67vcKuMBNMEipRQS4iXNyvvhydVyDzZ8xv4fl9fSEu/qyc9qXw0zlItSIMoZM1j/9Up35mRrNTni5wQ1BBrU39vD7fGXcNCjvP/1yMNpj87F2f+7AF+tM1ntPFVMLsiGHBYlBJTrYgIkKAXRppR5svVdwPrzRNGvxAtBYKGcg2a9MaIRHYByUTFtzR9IkMOilhXHtm2Pppcuh8WOkIoWLOoYk7gJlkm2+KGdsK/ymbbp3kdJ1lXARX//7KJzWByCA4IiMJwiFyyJ95+lVAlJERkhSY4JCcmyclkWJMy9fRLuP11xlTz5cd3NKuVz3dvsj10lXLf2UbyQUPtBVrjg8xjdQh4WWkWChegy1ItKCFJEu9AZZr2tFmY0UcrdXLCsZbdlR6Q2Vl3ptKkoUk4OsujEJa+swZOzN+KyFxapK9kmxRnfEWD715U0A7qkW4akCwml7LAAWuXN6nfZbdUYLbckAVnRFQepwG1/2bgPg4DlLlky10fNYYl9/6NdFUvvl+KwLNjDFgAEgP83czWaTRqppYRatqudvPXCM9phCUpBNQG2VFRscpOZdJbLgWrFprfc8dbE7YkuazYXLNbLipM2GYszJn+UA6mGDjt68edYDQlZSaxXzhGtUf1i1OMtiQOSfP+6viaiU3VYBNGaw5Kl65/jC0msD4uuSkiOsMddjgicDpE5r0DCkFtFngeiAIQjMuqjJ2yCqDbfdAgO0z4s4SYmWMJeo0s9opoJlnV1Nqr6MggJlp6IotIjUtBgfzcFdRcUvkJxoix6vXKP19RtnyJYyoenNlbRoVUJmeWwKF/mFiEP+1vZSXVdXQv++eXG6D2Zk6xxnH6lZiDGYYnoqoRSzmEBtAUmeefi6nGWdqU6LMEMCxarjbYSLHXQ4G8w/G0p8VZxWPZK+cjzONG7KBt1zX68+X2aWoYrjoRPd0E2K2vOdTOHJRQJoUVxO4qF+IIFSCHxlrs9dsuaebjEgmBxO0WU57Fj3lLiLV9LKBLlsISiHJZUL/4cV7KQkB2HhR3PrVEiK22CJaoQQBUsPEk2yf5dDgEOZUmFQEiK6cMSURwWl5OHsJKLQqdDRHke78US9d0TjQ6LWR8WUXHphChBOKicHfeb7XRtziAkWHoiygykParHhDoDjm5sFnc/Wtt8Q1M3/eyaJ9yWp+qwOBExqRJS+7AoJ4d9Ers4XD+JORUfrNhtLbM9WZVQ3BwW5WmS1oelMdBozWY3FSxRuSFWBUt0E6pU4BfKtAiW+O8nrxDiWEq8VRyWg3IeThxcihtPYSGptxbvtPZeJ8Mk5GFIulWOZdVhiWgOSwEUwZJtfiHhpc3Wm8e5IMPo9kSHhEyrhGyWFdvqxZLUYUmTYElU1izLKVUJtUWJLLWxYxodFlEQATXnxJpgEQQBWUrumU8RLPyM6RJdiEiKw+JUzl+qw5LYxSrJZc5JQ7RzJohavyxd0q2+x5BHKZv2FBoFCxfdB9uC1kKbGYYES0+Ez0CiBIt6QeFlihBYY7N4RNX3m4aElBVAreRjxH0NPuwEIaH6SC7cDhG3nDoYpblu1LcFMW/D/uT7T9bpVs1hMU+6lSJAJFQMl+BBS7AFGxo2qE/d0LAB1352bey6OYlCQhyLgkULCXU86dYnGAWAQbDwxOZkpavq+xnrsEQLFkuJt208hyUfR/UrwjljquF1O7B5fxuWbG9I8mQLcMESieOwSMYclpAUUnJYZOTJvA9LYsGy1eqqzaIDAUGADO1z4HlEzVZCQokq+nRovVgsJN6q748xBBeTw9JhhyXBas2+Bi0p3soCmMoFuS3KNY11WFLMu4mqEorvsMTfv2GiIWpJt07RCSnCLstOZ3SIKbFgKVBWgY4Jh4vG8UbnsATCEvLD7HuWW2rslOx1O9W8p837u75SiARLT0T9QsdxWKIbm8VDFA1N3XiVkLELLZ8ZpdCFFohdSyhGsLCxNsh5GFaVh2y3A+eMYa/135V7ku8/aUjIPOmWy4OwBEB2YUDeWADA/N3z1ac+vvRxLKpbhJdWv2Tcp9mMqXqcVm5edkTyahyF7OgmVKnAm4MJxtOBmnQbDmiOW7LkyjQ7LHK75rCMrylGrseJs0ezWeCb3+9M+vykmFyQzZJu9TksLYEw8uCDmg4eZ+bLF0G0nMPicMEXVbXSHGzDlMfnqWXrpiEhmw6LrVWb1ZBQpgWL0prfrNMtDwd5S611BVeO57aoCZl6vKmTkBTzbqLC1DznRHNYdOuExSFLTZaPxISEVMHiiAoJJXFY4goWIfFqzXVNfpQLjQCAnJLYpR0GKmGhTftIsBBdAU9KizoJaV9oiych0Wls6hadwxJoAfisxuLsL/Y1jGsJqaXT/DUUN+ignItRvZkbdMZwNgv7dnN98rCBulqz1ZAQz2FRnqY0OBhWcAwAYP4uJlh2tuzEN7vZIpXL9y03joP3VMgu1O4r7AvcuAi4bg7wm3mWS0Sz3Wy7DlUJcdtfNF4sVaeBh4NEZ/JeGwlyWKIdFSuCRWphr90sFmJENSuxvOho1rju41V7Op58KzoRAhDWhcMSOSytQT821LWgkPdgcXnjrrU1QG3P3x5buRFnLP4owSLJQazfq71viUNC1sr6q5US2N0NVkJCRsEiRFcypT0klECwWG2QqZ7fjIv2aQ5LckGREL2zLGo5LDKiHZb4AsPQ7VYQDYsfhiVR2beyP5+1xGYrDotZH5YDrUGUC+w8Kpi8x4MU4b2ZBAvRJfAZiGz8Qsc4LMm+0Ppwjc79UGOjvDTanQd48lIbq2gedlITxpSxNiJPLcEb17cQboeIfS2B5LNb/QXWTNxEn3yiBIukDG5EIRMsK/avwOoDq/HOhndUa78h0ICtzUr32ojE1lUCYi/+JQOBXkdqLoUF0lLWrIaElP4LitOiXpR4yCGnLHnfigQhoVSSbgVlNuwpKFPXTTqybyGGVOTCH4rgwxUWXLREiE74ooVaqF0VmFwY86TbzQea8MKCrShKkr8CsNCL2yEiGI5YzhfhY+GVHAAAQcmjcTvUZE0D+l4oFuhTzMTBzoY4JcR6uPumXPzzPUw0an1YrIUrksKTbsN+9h3RY6XFgh5l4tQqGy/c6lpfHc5hEQ0dviMybyYZZCEtLroS7N/wvRVEQx8WOaL1YWHjTZ/D4hSdMX1YGlratWUmzAQLd1goJER0CXwGEiVYVMveaqliVMlxtoNZzerJLB2L1olO9eQgCqK6OqpakqeM9aCcp5bgZbkcGNu3EACwaOvBxPvXz46jXRZZjo1HKxdzQ0gIQEVONU7vdzoicgS3f3073t/4Pnuak52Il+9dzjb061yGRPlBFklrWbPyWRZ6Ctk+uWDhYTErF0RVAJo3jgOAkix2Ik/qsATb4FCSO7MLtWNIEATVZXlzcQerhURnTChMhqz+79EOiyCyk3yRWiEU33FyiAL6lbDP31JYSHSqorFQtwyBILIxxF340GZORl9FsOyob0/uQKoVZOxcUeRh/2/6Q0K6jrPRibd83R+rjSF50m2UYElflZA2iRIFEXJE6awrBzU3RHQlnKTxbrd+tUqI3e8UnRDBxKosKN8hnlOYzGHxWnRYosqafQ21EAUZEkTTY2igknh7yOawPPXUU6ipqUFWVhYmTJiA77//Pu62M2bMgCAIhp+sLKOFKssy7r77blRVVSE7OxuTJ0/Gxo0Wy1IJ+/AclqgvdKzDkkSwRDksXExogsVGZn88dM3pnKJTfQ1+wpSUi2kjctWZIwAc25+N/bst9Yn378zWfo9e1C3YFrvmCHdYlDGFlV/cDhH3Hn8veuX2wu7W3WgINKDCW4FLjrgEALBs3zL2BH7ycecmbnFvkZiVX1NBFAFBVAULvyhps2gbF4wEISH+mVXmsOMhadKt8tkGZBdKiozH4vnjesHtELF6d3PHunDqRAIXl4AWFuKCpYCv36VcRAr5jDTJrFerFLJwsne4VPHkdXrh4SsBKyIp1yzhVgprIUaLF2D+PWkJhNHYniSkxkNCSsiMi1k/dyTTJVicumtCdFio1Z6DpDnIbMzclW0ONrPFvzoaEtL3nxIdkCWlchFBY85bAjfSMNGIahwnyMwBiYC7yMn7sACJHBbRkMMSk3TbxCaWrc4i01A0d1h2Nfg65uSmAduC5a233sK0adNwzz33YNmyZRgzZgymTJmCffv2xX1Ofn4+amtr1Z/t27cbHv/73/+OJ598Es888wwWLVqEnJwcTJkyBX6/xfbRhD2UL3SLbKwsUWP3Vr/QomjIPo8VLB1YlJAjGJvTZSsCg1/8wq3shNkmFiBfd0I/pj8b+9JklSQOl+qaIBR1vPHkPP2aI1FJt7w4x+UQke/Ox6MnP6qeIH8x5BcYXDQYALC3TbG11fyVDqy7oiMrHX1YAEB0qTks/OLsCyvdUO2EHBIk3fLPrDSbiT99rogpui631UXGNV+Kc9w4YwQLEby1uAPJt6JDDcN4Xd6Y44uHN/PdLBQS67AkESxlvFLIisPiMoQ/3WKW8prcYTERLP5GJGvbHk2Wy4GKfPY5bT+Y5DNQzhURxYnJcbP/xxf2sRw1nkuWRLglRRR1vViixpSyw8K+E/x4Y2NuAni+Uoc63bJfnYITUoS3c/BbFnDZcZJuXYILUPanCha7OSzRIjSqSig66TbczL7fPpf5/otz3Cj0uiDLNkr0M4RtwfLYY4/huuuuw9VXX43hw4fjmWeegdfrxfTp0+M+RxAEVFZWqj8VFVosUpZlPPHEE/jLX/6Cc889F6NHj8Yrr7yCPXv24P3330/pnyKSwL/QMPlCA5br/iFo2fKiIMac7NPjsBibHvHX4KJIVk4QYm4JBN2Mhifg7mrwxfYlMPwPguayRDssequd71t0QgbUE0BYeQOcDiWXpXQE/nHSP/DTgT/FL4f9Up21qxdnnseRppWH09KHBQAcLlUY8ouzDJnNwuzMcC04LMVZ7LhKLljYcdgg56mluHouHN8HAPDxqtrUV5PVOSzZzuyY44vH+bmIY4IlogmWJN8RW4sg6vt7iCIcgiL+hAQhIX6M8sU5LdKvmI1re32ScUU1SuShMZ/k017b5dWSZjtCvPb8ag6VRcGi5rCwd7Msmx23vrBPczhdObZyxQzoHBYBWkgoJAcsh9OjHZYQX/zQ4QJkLlgCiotlbQJpJYfFrA+LrExIQlnmYxYEQU287eo8FluCJRgMYunSpZg8ebK2A1HE5MmTsXDhwrjPa21tRb9+/dCnTx+ce+65+PHHH9XHtm7dirq6OsM+CwoKMGHChLj7DAQCaG5uNvwQNuBfaOUkZPhCAzaqhKJyWLhgkbhgSYPDosthcQgOZDmMISGHIgBcecbYa0G2S80fWL0nSciA57FEOyxmCYWiA/pLoz4kxDmt32l48MQHkefOg1c5CaulsmYVQh0gLSEhAPpVsb26fAJf2GfPYUlQdcU/s6IsJQ8iXht2jipYclFdGFuJc/zAEpTkuHGwLYhvNycJ/cUdrws+xWHzODwxx1e0wwIAEMJaSCiZw1Jqo7TZ4TI0SRRl9l4mdFhSDG/0Vb4bO5M5LCK/eCoOi1J+7Av5Oh5aiSauw8KbFloMCfFSdeWI5gLZF/ZpOWRK/pg/JGFfs00nXycAZIiqIxKKBBTHC0ndruik27AuiRfK5y4hyPJ5eL5eqiEh0ZhzEx0SEpXzvZQdPwdqYDepFLIlWA4cOABJkgwOCQBUVFSgrq7O9DlDhw7F9OnT8cEHH+A///kPIpEIjj/+eOzatQsA1OfZ2edDDz2EgoIC9adPnz52/g2C57AoX+gyryJY7Lbb1l3knIJTFSzhSJhVV6TJYdHnsBhmwOEgXGF2IfAWxJ7MRlpduCuZw6LvPRIlWEKKw+JymH+V+AledRP4DC9NgkXfzyFipXQ2HrpcIZfoUhPzmGBJMYclKqGTd0c1XEASICtOXyPy1HV5DC/lEDF1FDu2PrLSc8eMqP9b7xKGI2FElLBpnltLoBTEIIoFezksuxstxP913ycBAgTlwgUuWMxKmlPMIeGJt9vrk4WElIRSRbBwx9CvD3+kKbwZt7Q5RYeFiyxe4WUQLNmFeH7eFhz5P19gwkOzMWdd/JSGGERRPWbkiABZ+ZwCEZ8mWJIk1CdKuo2oSbw6ASQ4WN5bAhLnsMQPCbn8yZdh6S6VQhmvEjruuONwxRVXYOzYsTj55JMxc+ZMlJWV4dlnn015n3feeSeamprUn50709BAqifBl19XvtC8asO2wxK1llCWLnHOH/an0WFRftVVCfklv3rxj8gC8opiZwe8zDlpUmY8hyW6yy0fjy70FJLYe+hymCfYxYaEGtltmkNCABAId6DbrcOlLZAmOpDt0glDOxdF1WaXYxZA5ILYqmDxNykJ1XIOKgvMe52cPZo1Cfxi7V5rvU6i0QnQ6LCmfq0Vj8OjVm9ADKIQ1nJYSnPdyMtyQpaBHUndDE2wsIZk3GFJkBibomDh7mPSHJYoga46LGGfZTfBMmbdbqWw9j/azGGR5ChXSCdYZE8+npy9Ee1BCbIMPPL5eutLPejy6mTZASifU1AKWHZQ+YrNvqCkhL11nXOV/Uly0OgIJWkpUJitTDJCktpoUBsvI7oPiyzLyA6xiYEzL7lgOaQcltLSUjgcDuzda1zefe/evaistDaLdrlcGDduHDZtYsvV8+fZ2afH40F+fr7hh7BB1KzJMAMBgHZrZXTR2fJu0a02lvKH/bpVZC2eaExfQxMITiGqSkg5YTbDi8qC2Bj66I46LNFdbvl4dJvwJk/xHJZMh4T4miRAx3ux8FmjAMEYGvHxk2Zh8v3oqz10eSxSRFLDK1wgJ8thaVcES8BVqDpJ0YzvV4S8LCca20P4YVdj8vFFE9X8kAs1X9hnWGLC7XCrgkUQQpZzWARB0PJYks1OdWMRRRGSUn3Cc1jazRKrUxQsai8WCyEhvWDhOSz+sD/tx7Jpt9v2egAyS4y3+j86zMNY7aF2dcxNslddxNLtFPHjnmbMtbKUB2DIq4MsqDksAcmvExiFCXeRHZ3DAq0PSyTC84ZCkNQKocT7A1jIkGsag8siGhdr5A4LwNxwb7gRAOAuiN/nhoeEthxoS21ikCZsCRa3242jjjoKs2fPVu+LRCKYPXs2jjvuOEv7kCQJq1atQlUVm3X3798flZWVhn02Nzdj0aJFlvdJ2CQqLq0m0oV9kMNBawsfAsqqpexXh+CAIAhayCbQrK282pGmUvqFu0RjlZCsCKsmOQeV+bEzcN6XZedBX+KOqHEdFm6VRgkW3UQnFOYOi/lXiY83FAmxBM40Vwk5HaKaP9OxBRCd6go2+mqs9nC7wUZPPiBdIqPOoVAXy4MuhyWJwxJqZYJFTvC6ToeIiYOZAzZ3vcULjh6dqxHPYREFUSk31TksqmBJ/jnysFDSFW8dLoPDEgqzCxfPYTH9fK22IIiinyJY6pr9iYWuwyhYuAA3OCxp6CcEwDwkxMOR3pLEy4To4YnCSjhPf37jx/KeADtOzx5dhV8ew3r6WG5CqFtLKCKLapKsP+y3ERKKrhJi9ztFJyKS1jTQ377f0v4AQBQFNWxoECxR67FxhwUAWoM+FETYmL2F8U2HXkXZ+Nm4Xrj5lEGpJ7inAdshoWnTpuH555/Hyy+/jLVr1+L6669HW1sbrr76agDAFVdcgTvvvFPd/v7778fnn3+OLVu2YNmyZbjsssuwfft2XHvttQDYDOTWW2/FAw88gA8//BCrVq3CFVdcgerqapx33nnp+S8JI6rDwuAzEBkyAq1K3okgJv+SiA41WcyhnEy4A9Ku34+nAyc00anapfoLKQAElJBNE3JQYRIyKPC61Dbk62pb4r9GvMoWs9mroK1QDWit+ZOFhAB+8W9kf6QpJARo8fCONo/TN+hTL9yhNk3AWhmzIOhWwNbeT704sZx0y0N+caoXOCcPYVb211ZnyHqiQo4GwaI4Qjyfh8+kJw8vQrlL+d8siDjLCYtRYwkGuWBhFx8ufAykmPhanONGroeFqnYl6ngbFQI1u/in7VjmISH9cWE3fwVQz29cgJuFhLa0sm1OGlyGKSPYhXrehv3W8sB01VyyLKihO+ZGNrIHbCXdCsa1hCRNmPl4WNrie2zaPE4XctI3jgOAfa2tapdbb1F8h8UhCnjsorG4+bTBcd3OzsB6HZzCRRddhP379+Puu+9GXV0dxo4di1mzZqlJszt27ICoaz7T0NCA6667DnV1dSgqKsJRRx2Fb7/9FsOHD1e3ueOOO9DW1oZf//rXaGxsxIknnohZs2bFNJgj0gS3TJWDmH+hAcDXsgdZAPuCJJvRCA5EdA4LoDkK6swg27wZkWV0J3GHqFUJAUBb2z5kgTksA00cFgAYVpWPPU1+rK1txjH941z4zE6UgHkHUV1bboZyoonjsLgcLrhEF0KRENpD7ShQk27TFPcHm601+8MdWwBRdGmfpb58nJe4A9Zn0s4sVtmgqxTigkVfOhyWwwhJIXUNqmh4BZiQ5L06SREsK3c1otkfQn68jrBmiA6tMifKwVOTEvn3RXIDDuDEwblwr1HEh4ULydBKlrC7ti6BaAaY26NbHsEfcsAJYMrIIhQE+uKmUwfFPifFkJAgCOhT7MXa2mbsONiOQeVxurLqHCgg6uIfamR3pjskFNQ5UWpY2WKFEKDlsCiShSdM+8I+yL5GCAC2trJL33EDS1BZkIVcjxP1bUGs2t2EMX0KE+9fl8QakbUqIZ8UW4UUD2NIyKmGhJyiE+GIDDnigiCG4OfnC4vfvYJsF3bCh+Yoh0V17kTmhLtFN4KRIPa3tuFIgVXZinbe4y4ipSvJTTfdhO3btyMQCGDRokWYMGGC+tjcuXMxY8YM9e/HH39c3baurg4ff/wxxo0bZ9ifIAi4//77UVdXB7/fjy+//BJDhgxJ7T8ikiMaHRZ95ng7b3Bm5QQYtTAhoBMsPP+jww2lHIZST54rAwCNzWysTchBWZ55T4UjqpSLRW2C0vd4DotZDgsASel34RBEcMHijiNYAF0eS7g9/XF/aIm3HcphcUQ5DTyXgwsWl9faSrmA6XpCvK9JliPLtKMsAHy4+UNc/+X1agt1Z5Cd/MXcxMdiVUE2+hZ7IcvAsmSNAqMRXaYOS3uoXRUs/HgLS+xzd0MnPCx8jsOqWI7dpn0tie10hzYWASKkMHvdikIRD5w3ylyIdaDTbD8rlUIOlyEEapp0m3aHxSQkZMth4c0djTksMmQEFBHcGMmG2ymiV2E2XA4RJw6yEVbUVS5GJK1KyBgSKky4C4+hSkjLiXGJLoQkWXVt1AmDxfMFrxRq9Ol6T0WtxwZADQvVNx2AV1AmFlY7CXchtJZQT0RNSlP+1HeQtSVYnFqVkHIoqcma/tRi67GvYVzKHdDCTk0t7DV8Yl7cHBJ+sUg4u43rsPA1dIwVSBFFnIm6r0+8kBAA5Dh1SX8ZCAmlpz2/U6sSErR1oXypNLozEYB6h8XlcKkCVx8q+vOCP2PB7gV4YdUL7CVDTLC4kwgWADi6hh1ni7clWTsqGp2rof8e+CW/mnTrdrjhD0mIKEmwgqTMol05lpZX6FWYjVyPEyFJTtyPRXRC5uWysqDmRoTlOCuJAx0SLLwXS8LqJdFlCIHyi78h6TaTOSypJO6L5iFvQDuem5GD3oXZEJUuxxOHsO/4oq0W+vnoq4R0fVjM+rzEIybpVhcSCkkRLS/GTjgWUEVti1+3TpygC91HCZbGg6ySMwg34DYJOXYzSLD0RATBWJGgj93HcRXM9yPq8h7YrVp2rIY+OipYnIa20oDm4rQrsw+/K36VGBcs6+ua42e3mzksUkg7+UQtCCZxwaI0HBMEmK+iq2B0WDITEgLQ4ZCQvrmUejxYPAEb4E6MLiSkOizKex3dFfmTVbXqtstrN+Oo+z5FdoSFXTwFyRf1O7qGvZ+Lt9l1WBLksHCHxeFGQ3tQzWGRJb7adqG1lxAFLSyUyOkTXbpyWS03IiD54z/H6kKlJugXQYw/JoehKs6YdGsjGdsKZp1uba5EDSCmSsjQV0gRAM2y17D22FH92PGzcmdj8ioYvcMSETU3JOwH/NaODX3SrQxjDktIimh5MXxBWovfPy5YmqOqhHi4l59DuaPe0qxbRyjZSuzdABIsPRXRWJHAbXqfj8/YLFxQ9U3dlENJPeHzL1pHHZaoHgL612hXTphhd/wvc01JDrJcIvyhCLbFa0Nu5rDwCwGEmJNPRMnJ4YLFJYqGZQGiUXuxBJq12WM6Q0LpcFj0fVj0jlvA3sUZQFKHRX/LQ0I3vLZM3XbbwQbIfPYOIDffgmBR8pNW7mxEIGzjfdD1GYleq4on3bpEF1skkF+YUkg25YJlXSKnTzcWWRbV14tbTRWRtIToFCYGavO4RA6Lw6W6PgIEQ+M4WXUL09WHhTssJkm3ufETQmOIclgMIc4Ae/+bkYM+xVoC/+DyPOR6nGgLStiwN0muke6cFJEAWa0S8kFN9U3msOjCuPqjlYeEuGvjD/AGhYWJx6TAuyFHOyz6hHpAEyztLUrrAHf6JlCZhARLT8URb0bdyO605LDoxYQSEuIOC59pdDgkpKsSiqpE8gfZa0QSVCE5RAFDK5WwULzZrZnDoi8XjUo+Dit/8zBYonAQAPVk2c5DTBA6VjkVvX/l5BcIdaDcUFeubShPDyknTFshodgFEPlyDfyzUwVyyIewFAEEbUbY5G9Ty4abZS8K82K73EYzoDQHJTluBMIRe6s3x3MaQ0aHpckXUnMVVBFnw3XiTt+PexI4LLrvpCwL6oUwrmDx6/7PFMIyXLDsamiP3zRN5/rom0NG5AiC6c7H4iGJkG5iYbctP6DLYTER4CF+XOWgj25BTYcoYEwf9h4u25HEpdMtSSLJQqywdGYnXaeITzLag2GEdGnNTLBEtM8+yJO7LTosSg6LoY1D1HpsgJZIznNkpHSJzgxDgqWnEp2z4EpBsOjXEhKiHJagtdbl1sYJdZz61wgoJx85ycV0GJ/dxittNnVY4ofGIlEhIZcz8ddIdVi4e5VV0LHKqSjSl8PC0B8P7bxiw1ZIiAtAnWAJmTssvrAPDe0hCA5tlh+S29VOso1yDopzkif7CoKA8amEhaL/b924+MKHbtHN3lueqxC0N+sFgHFK5cnyHQ3xS2d138lIxORCGA0PL3rybS18yOGJ6v5QxLwpnTom5Vddp2kA8IdTODYSYdbpNpWyZu6w8AmZqBOiigBoglcVbJwj+7LjZ9n2xoS714dw5IhDDRWGZQkhwNJxoQ/jhqEdD07RybrUcjePizeLEwbusDQbHBbRsIQKAHhE9tmHlPO90NGJZSdBgqWnomsIZZhZqiEACwewzmFxRgkWf8ha6/KkiLEhIY+S2Mu/zKK3MOEu1MTblByW2HCEpMxSeFffeAm/HDWHJc3rCHGy0hYSYoiCqOt0m0IIy8Rh4Y3jzAVL0CBYRGeT6rA0IhfFXmvVSTzxdomdxNt4TqO+D4vDDV9Q0qpBbF5EAOCIyjxkuxxo8YexOV7HW10+TSS6v4cZHTyevG4H3IrYPhhvRXOH5rw5RAdcoi5hmodB0yZYokJCEUmbONhJulUSSk2FqPKZRuewAJpgWb4zseCN6CYbUkRQFysEAL8gWHo/cjzadzYsaw6LlsPCw0zK98Jm0m10WbO+0y2gJd1KIXZOdFpIbO8OkGDpqTjchhORVs7JhYbVKiHFTlcu3lmqmFBOOmkoa44OCTUq14uAciJ3JhFFSQWLmcPCk49zTBwW5UvP/2dXgoRbQJ/D0sjuSGOFEABku5XGcR1KujWvllEvlmmsEgJgaIF/sM0oWARnO3KFRgBAo5yLQpuCZfG2BC5GNKLDPHQQ1YfFF9QcFn8KIs7pEDG6N7uQLY1Xeq1brTkSgTbLji6356g9OqyPQ48gCChR3KuG9jiCRVclJEa7qKLAFuRzuNDsD2HaWytwyXPfoSGe+EmGKliUL3j7QUCOABBMJw5xUc4TZqG+dkVstMJrCAkBwFjFBduyvw2N8d4PABEhWrA4wBN9/KJg6fPwupjoC0ky2pWcK1GWIQoiwhFZrRLy8c++IzksukpL3iNNbc8vsfc6y0KeWHeABEtPRWc/x3Q2BSwKFl3b/KgqoXYlZyEdOSzRPQSa25VxKy3L3XmJX4P3YtnT5Dc/ESV0WGLfB4kn3cJaSEhdy0R1r9IbL85ypqEPS9xqGXsnTADmDkvY6LCoIm7r15C3LzQIFgDwuPlKzbmqC5CM4dX5yHY50OQLYaPVRdocbs1ZigodBGtXAGAhofaQFOt42BQKvBIlbo6ELvwS0a0CHHfNpTQs81CkiMH6uA6LzoHiifW85F1gF+dIRMalzy/CzOW7sXBLPf78/irrCwnqcUc5LGpb/mJ7IS9BiCkqUD9XQUCz7EWW26V2heUU5bjVdZ+W72iMu/uwLsFekgSwrjnKsWGlQziMi5a2hZgb4lLeslBYqxLyR5TvUEdyWATRsB4boDksLrBjK6ew+/dgAUiw9FwccRpm8ZOxxb4OfLbhVMSPGhLiF6t0lDVHNafjIaGQyE5JWUkES36WC70K2bhMqzRMc1iSh4REqyEhfnFOIffBCl5l/ZDWQDjJlgmIrhLiqzUrFnpqOSyxDgt34NQLyOq3cdzXl8YIFrgaAQANcq7ll3U5RIzrWwgAWLLdYljImW0QxFrjw70ILn4OAA8JhXVrxvBju9Dy2ABNsHy35aD5BV13kZX0IaFAM/DyOUBz1Fo3aSiR5/lBcV0RfQ6LItTVY0O5OP+4p9mwwOgnq+qwYNOB6D0lR+10qxwLrUpPKDv5KxyHC6ZLTQgCmuGNmxc1Vjl+lidIvJV0l81IhL+GR92/lePC7RTVZP3WMBMXfDWvoL5KyGbYLZ7Dou90CwChMK9wZMey08RJ7o6QYOmp6Fuxm8R4rTojargGRofFL4ds7ScuJmXNfBE6vyBAkgXk5Cd/jYRhITOHJUE/Gh4Ssp3DkkLugxW4rR83D8EKUX1Y1CqeiHLi62iVEA8JuaJyWHiYwdFo2IU7i71XjbAuWABgvJrHYjHx1ukxdxrlsNou3S264QvqemOos95CW2M7dkAJ3A4ROw62my+EGNVB1dCQbOs84O0rjNunISeqONmxE5WcD0SFhLILVXEyeVgFLp3AFhJ8f7nFhQT1RHe6bU2hQkgdd5zzmyigWc5RvzPRqIm3CRwWSRcCliL8/KckMIsCS4K2AE+Wbw2x75iTOyxSRMuXEgTLDQqB+Dks4agclu0HFJHEu9xS0i3RrYk7AxGtLXyoICkXHF4lpF7o+Mygo+EPMTZhLBTiSX8impGDwpzEJYQAMDxRi/5EDkuOFYclSVlztHuV5pBQSS47uR1oTdARNRkOp2EWpibdyopgsXNRTLD4Id+vepwoJ/8Ch7Eluuhhz2204bAA+gZyFh0WV7Z56ABAUDnu3A432kNhTUAoHXDtJpvmeJw4diATwLPX7o3dQOdySRGoAiksCKz6ZNdiQO/M8Iq+NDgs8ZNutQs/z2FR89SUkNA3imA5cVAJfjqmGgDw+Zo6e/1wgNhOt6m05VfHrR3PgiBAlLkDIiZ0WLhgWbmzMW4elN7HDEk81MJDQtaSbgHA62bnsfagIlgUhyUkRbRjTRSBLGsCCNAESyAc0d5/k8KFoOKwOMU0OeGdBAmWnorDbZiBGC4gWQUxvUfioYoJ3i/JqTuZObOS9iNIStTihwDgDyq3IotHF3mTzz40h8UkJGQhh6W2yYfHvtiAJ77cgLBoTDS27LBIKeSDWKA0l73H9a0dcVi0fiQCBN2FWznt2woJxV9LKKZxHF+A02l0RDxedhK/4IRRNv4JYFzfIogCsKvBh9qmJKtBK2M1VAkp4jUsAO0iT6p2wR/U5bDIyhGZwud42hHs4jt77b7YB3X5WmGz6hMA2LdG276DSbeALiQUN+nWmNsEGD+7sCcf3yvi8MTBZTi6phgV+R60+MOYt8FmWMilEyyRSGpt+dVxG3NYahvZXz5RQJOcg5Jc8/PSkIpcVs0ViF/NpSanA2pXXNVhEawLDK+HOyxKcrcsA7KMsCRrfVgE644NAORmabk+PCwkQzQs8AkAIvh6aMrnnuZzUqYgwdJTcWWbd4IUBFsztnCUw2KcfaWh3FGMtTN9AVEdazO8KMhOXkVyhCJYNuxtYY3K9KgOi3lIqC0QxnlPfYMnZ2/EE19uRGOAnaSsOixqDovE80EKk47XDqWKw7K/Qw6L29Rp8KudOwut74sLQEm7CMbrdOsTefM9JiSzUQUAaJbZZzFyUH9b/0aux4nh1eyzthQWcmYbQ0IOrUldkzI2t8ONdn1ZMy9DTeFzPG0Yu/gu2X4Q+1qiqn90FTmSBEB2QFBO0fx9wsbPte3TkMNSpAiWuGLXJCSkTkpEAQclL4LhCEpz3RhYlgNRFHDmiEoAwJz1JqIsEVywAEzsNu9mv+dV2dsPoCQLa59ru/6cIXvjhoT01VzxEm9VZxqCupilU9SHhOKsfB2FV0m8bQ/zkJAMWY4gKOn6sAiCLYfFIQrI9RjzWCRdkrDmUrNbWVCOZQoJEd0al9e8nNNiWR4nEpXDojYcsxHLTYiJw9IWUISLwOLRfIXSRPQr9sLrdiAQNmnRrzosPvjDfvhC7YaQ0Nz1+7G3WRMD+9pYSECQbTosPK8nzSEh7rC0+MP2bXiOM8tYLaMXsECKVULxy5rVNWn4/h3s8eP6DAMANEZSf6/G97PRjyXKYXE5XHAqJ/Umh9azwtA4jou4FGalvYu8GNe3EBEZ+PiHWuODOus+HAEAAW5RCc3xRmUHt2JN/Ro0BZrSIliSljVH9akBjPlH9RL7fUBZrro8xUlDWM7J/I0WVj7WoxcsoXagcSf7vbCPvf0AhuPZITjQ0q4Jv2YkbkaoJt7G6ceirvsDJUEWgEufdGvxvMdLm9t0OSxhiR0Bsj7p1uZ5NJ83j1PyWCRdYzo1JKQcaCEBLAUgjZ23MwkJlp6KK9u8E6Qg2joBSrovL5AJh8WpLdwFESEpgna/sjS7KKAFXktlr/oF6FbvjspjUS7Oj2QLOPq1o3HimxOxnv9D3hLM+rEOAHDV8TXoXZQNv8xDJ8rTkwgW/p4EOhBKSER+lgtOJXyRcljIlW2+arEoss6++otJMpxZkAG83b4dl3x0CR747oH4ix8qrxlysHHXFNQAABp47kwKMz99PxYrY43ppKx8Xs3cYRGVxnF81suTLlN0yniex4croxJTdev2hCUt4RfQcn2WNm3CRR9dhDPePQMfhRQXsAPHU9Ky5qhOt4CuElAQsDfI3quaEu34mDCgBE5RwM6DPmyPt36X6WuJrK09wJYdaFIES0Ff6/tQkF1Z6vEsCiKalFYI3GFJJFjG9WHnv7gOi26Sxh0Wg2CxmsOihIR4WbMTMkKK26JWpIn2z6N5USs2GxwWkS/jwe4LK3lI6ey8nUkOjVES6cfljdunwM4JUF22XPlbO5nZSxaLiyDqXkNgyYGyNvsIu6zZrwAwpnchAJOSReUi+pUyMwlGgljp8QCuHPjhxldKguS5Y6tx5XE1CMu8Dwsvt04cEnIprcJDHQglJEIUBTXxtiOCRR8i5CILAPxZhfZWcnV6sNHlwv8EtmJ1/Wq8tf4tNATYex4bEmL79Ssl6jX5NQCAg/zMlIrDoiTerqtrNvajMMOVFdsYTelR0aSGq1ysdb3uuIMzC3BlmewwOWeNroIosAvipn26nCqHW3NYlF+y9MmcANb42LHYHm7Hv9w8YbLjSbfxy5r15e7G9cJ8ooDdfvb8fiU56lNyPU41eXX+Rpt5LCUD2e3e1UALmyik4rBEdAJbhIgG5W3mYWT+fTGDl8Zv2NuCNpNWAZpggRpedjnsVwlFh4RcMhAKcYdF39fF3nlUa8/PHRbtu8v7sASUr0UYOGTCQQAJlp6LK8sQ4+UX1bDNHBZ1H8rfvFeKJCB9ISEeNZBlHGgNQJaVTpYQcPqRQyzv6ki1cVej8QHFYQnorsltogDklGD17ia0BSWU5nowpnchfnZkL7WsMaD4qnxNlnjwhcbURc7SHBICtLBQypVCUU4DPx4AQMq26ZQ5s9AaNWOrbWPhj0JPIQCdiOMOi/LeV3jZqryNogMyUnPpKvKz0LfYi4icuAEYH6vWh0URKMotT3R1iS4WElKEalgQkq5flYjyvCxMHsb+z5e/3W4YCxcHvAcgHwsPQ+wOaQJHzS9Kg2Bp9IXUBFIDTo9WJcQbJaqrIQvY3s6eX6MTLAAwcTCrrltgV7BUjGS362cBkJkwzLFf1hxxarlILf4IfDpHoUnOQXGCysKK/CxUF2QhIgM/7GqKeZyHWBwy61QLAE5Be0+sCoxsJSTkUwWLjJDSk4UfaxJgPySUzR0Wtq+wbnFFUWAudSisc1gOkQohgARLzyWqnJPb4ZIAWw6AFhLiybdsP+EULzYx6BrHOQSBOQjqhQPw5Fo/WR+pzJzW1jYb29grM8agzkVoFUTAW6J2TB1ena84GR5keZTQQIDto3+p8WQdDT/BB/lMJwMZ+SUdFSwur0HAOnRVYpJdp8yZpa4Oy4ko7hIXLHz//LPlr12qNOoLigLas61Xq0XDXZalyfJY9Lk7svE2qAuR+YISZH3DMLsiLoqrjq8BALy3bJfmArm8WpWQcng6lb8lpVptl6hdfNS5fwfEU6FSYSfLMO8CrXfe+K2gff82t7CLbr8SY8jwREWwfLP5QGySeyIqlaqw9Z+w24I+9tw9BcmlCZbdjQHDOaMZ8fuwcBLlsegdlqDyv6nnPRsTNe6w+HUhIZ7DYpj4peqw+NgRwo8ThyzDITrQ7Aupkz67E9SuhgRLT8XlNfRh4ReQMOw6LOyWX1bUC1EKXzRT9EujQ0Z9WwD8sJVsiqJehdkoz/MgHJENnTlNBYsoAt5SbFIEy+ByrR+I28NO8nzrAWXWBEtYACA42PoraaZU7cWSakjI6LCIgqj+f2G7TllOqaF9uZ5C5eKqCmTlfn6b48pBlvJ+HfSmfiK1nMfizNK+B4qo4sdyQFcKyhwWTTxFOijGjxtYgiEVuWgPSnhnyS52pys71mFRtpe8JUBWAXY7tTGEeWjKnfj4S4TLIapJ66aJtw6Xujq5I6paSO+w9I0SLKN7FyI/y4kWfxg/6L9ryeCChfeYMQkH7W8JYOfBOMsVKER04brdjX5VsESQPIcF0PJYVpg4dIqpAgdYG30AcAnsTjsOi5rDImlJtzwkZBD0NhNieS+WJiXpNqgc17z1f7M/rAk4gAQLcQjgyjb0YeGxzYgAWw6ApMsv4fti9yM9Dovg0F5DNjosTBRZfw1BENTYuqGxmCgC7twowSIA3hJVsAzSCxal4ZOoZEj2L00sQPi6HUFBYPHiFGaMydB6sXTEYWG/8hm0gwtDu8IzrwqxkX9W3s0XXdPPIA/KuYbS9SInuwA3ZFvPT4qGN5BbvrNBTYw0RbfgoENpyuZUblWHJRJRcli002W4g1UVgiDgSsVleXXhNtakTPcZKIUjcCnhB8mdAzm/F3Y7tT4bYYA1Vevg8VScpLRZUgS9GvbVubG8ayy/SHIcooATBqUQFuKChVOgCRZZlvGX91fh2IdmY9Ijc/F/y3fF3Y2kEyy1jQHVHZPAHBavO7FzpzksjTHLKGgTKLCFCgHwpgCSIFiekPAqIb8hJKSIF1Hn2Nj8/vG+VFywhJTpAD+W2P16h6XQ1v67EhIsPRVd0q3eYWFCo9DybvgJlndp1EJL9mcGpoiirkpIUEI5fHZgP+x07AA28/4maq0TKafE4Aq0iSKQY+6wOBWHhX95ehdp9rMZasxfECBlaDZT2tFut87Y5FO+oKVksa+ESl6lqcNSlKX971v3szJmCQI2y9Wqw+IUnShSEn4bPTYqk6IYWJaLIq8L/lAEP+6Js0o3AAiC1rlYqeJyqIKFbeIIB5WFJXWr9GZ33D08f1wv5Gc5sa2+HV9v2G8I03KNxb9Xkisb9fmV8Otyg0KCkFpTtSiSNY+LONnjqouqLNcgAWhCDvoUm39OJ6aSx+ItBvJ7a3/rHJb5Gw/gP9/tgBSRIUVk3PbWSny/1TzkF3FqgqWxLayupsxzWIQkIm9kdQGcooD9LQHsbjQ2IOTfE6eshYRUweL0WBaQakhIXUsIJiEh60m8nAKvlpcEaMn+qsPiC6luYRhIexFAJiHB0lNxZetyQxy6GKy9kFBYtdPZ30bhk4aQkOE1Iobkx1QSeycqPSKWbGsw5LEEo9p/t4oigp5i9WSld1gcLnZC4DPxZGXN3GEBgFCGMvIr8tkJemeDhe6uZkQJWEC7QEke44zxYFsQM77ZitcX7TDvJptVgLAj1nIvdGn7+XAZmx2HBWBTpAqy3mFR3L6DKVbhAMzBOMpiP5aIcsxyoeJQTvABRRy0tbWy9umydiGS0pBQ7nU7cdHR7IL80rfbDIKFn5pdMndYsrHLWwgAyFa+qxFBQCSFhNRoeGnzwTbziipJ6avDj3KHpCRzig4E4EZFvnkC68RBbGzLdjTYW5hz0h+1iUi/E9W7n5u3BQBw5XH9cO5YVhr+91nrTBeS1OewtPgi4H1vJQD3/OK4pEPIdjswohcbQ7QoCgu8caQWEvIokltyJE7A18NDQn41JCQjzN0WIfXzaKES4uM5SSEYncMmXwiyLoE8LU54J0GCpafi8hrWCDEIDTshITWsxG55aEkWBETszsyTvIYTgD8UUb9skRQclgGlOaguyEJQiqgtxQEgGLVaaasooE5mwq00141Cr3YB1mL65muNRKOvuAllaDbDlx5YV9scdw2UhLiyDCHC/9/ed4fHUZ3rvzOzXW0lq8uy3G2MG7bB2NSAcaEnJAFCEiAJ/CBwEy4lAW4CpDwXyM0llcBNIUAaLeBQHRyDTZMNNjZu2MZGttwkWZLVtW32/P6YOWdmdmfL7M5KK+W8z+PH0u5o5pyZOed85/3e7/sArdyCnmH5YH8nznjwDdz30k7c/cI2nPfQW3hrT0yCMEFAxOQd8us8M4Jat0kWBOwj1exzSZRQqj7f4470Cr4lQrp1hWSRuvjU3S0xupB2HzgG5ZbqXEI2GeNfOXU8BAF4a88x7O8hzD0FIqDE62RtiTi9OORRc54ImiEXMal1ZRVlBapmqN+cnSPUYKEuM9VgCaqRMYmi5MaN8aFhjA+RKMH6fR3pN2jeV4HbdgO37gIaFOOiqb0f7+xthyQKuO7Mibj7/BPgdojYeOC4aeg0ZVgEKJoNH1EWb1kQsHze5LSaQdnY9Z8a284SWULnElLfHdnCO0sZlqB6Px16l5CkMiywzrBQIXXXQCzDonMJEZ3LibuEOPIeDo8hgyzTK1hkWOjU7iCaQJFCtklcqlflByI6l5BFDQug7LwpVa1faEMxzEe/IOJgRDn3xApjP2RJM1hoVs9k0BssIRtcCWaYWF4Al0NEf0hGcwpBoiliRNiAlgxQVkWdfcEI/vPpLegPyZheXYQTaorRF4zgG09ujKu7YmawlOqmm1CfEp4bgYCj0O69Q3CgNKq8VcelzCKEKPSVm8124RSMYVGvS/+nCPTTvgk61skeY3zcGB+rL/TMRx2a+Ngh4rdfmQ8xqi6ETi+Oqa6ZOp1Bao/BohgcCRkWlS0TqdtXrcIdogZLYWIm7HSqY9lrwS0EKKkGirWU/BtUo2F+QynGlvpQVezBlacoCeX+9n5zfJudSp8kCOgeDKMQqsEiSmm7bE6dqGxi1n9qNHiZ+5IQpo9yq4kOzZjFRKBhzSHVJeSE3iWUefACM1gGVYYlxmDpCehdQgJ3CY0WdA2E8NXH3sfyn7+V2a41j0EcHkbDi4LIJiGrGpbYxHF0dw4AEbdNBgs9N4BASGbUphVFvh6fmaYsEKt3trKFLBgTkdIrijgUVgyWOr9Ro0I1DxVeB376+dkprycIAhw0+iNH9KtDEjG9OklF6pQniM/4Sl0kEdVgeeydJhw6Pog6vxfP3bgYK29ajNMnlyMUieL7K7cbjALZpJ/+iDqBylH09SiRIxGIOAZt8RcFEZ6w8i4GHelP/maYWVcMt0NER38ITe2JM67SiuPUOKBMC0VoQPlbpyQwcbld7CEAXH6ysvD+fWsH00ecOdGvZIylehGHB2G38hx8Ia3kQTiGGcwEqRgWpmFRH297p/Ls+qLKfUuWh4jmY3nLapr+GGw8oER7UdYMAHOn/evj1rjEd7TNAhRGoUBlWGjts3SwoKEUkiiguXPAoGPRz0ch1SXkUg0WWUqfYSlw0zT5OpeQ+rObhrNnwLDQ2moawyKrbSRANKqKbnUuIc6wjA4UuB1455Nj2NXSi/YEg3mkQtaJ0iRBgiOk7CJlQdCKAaZzHupGoP5/A8OSebil4Rq0nYQgEJHZ5JNpcrozp1bA5RDR3DmA3a3KTj8Us8D2iwL2BZVzV5cYd5DUJTTG60BlcXo6CxczWOxb6GIxQ3UL7czEYNFHCakfUReArC6Uq7YrmUe/vWQKCt0OuB0S/vuzs+B2iHhvX4dhFx1WF3RJZ8SUBpR37NNj/fBFlQUgIghoh04fJEpwhBWGSLawWzWD2yFhTr0fQPJCiJqGRS1kJxv1FnJAMVg8Tokt2hGb3m0AOHtaBcYUuNDaLyOsvieVPpXFowyLw8PGkzukGV92aKIYwzKQgmFR78/RY10AgEF1m5LMYFk0qRyioDzzI10Z6qsAbFINFlonClDcoCfWFiMsk7gyB9QlJEFhFAoFxciLWkhBX+RxYqaqY3lX53bSEsfFMyxWDBbqEgpFNZdQRE3AUyxSAwuW5zgaJdQbiCAiR1nCSicIEI2gZzCiy8MCrmEZLXBKIqrVBelQpmLGPEXUqU0yoiBCCqoGC2ApTFK/2wAASTfZy1bqzyRAlEQ1QSYhGAzJbPKJCEJGicUK3A6cqe78/rldSXUeUpkal7rABkQRTb3KQK+JMVhkgUaVpJ8Qy0kNFlcODRa1SvHOZFExiaBLUU+jQKh+Qnb6cLhrEDuP9kAUwFwYgOLSuELd6f6p8QD7PKIaZmNkja3w9yvU+q6WHhQRZQMQAdCuY1gkOQKHqm+JZMmwAOnpWGTRyLCQiHHhltQq3j6XpEXt2GiwOCURl55UBwAIq+9WuU8VPquLmex0I6KOJ4ccYSxjxFMaezrLSMmwqIsw1WzJAcWgDKlOw2QGS4nXyYxGy1lvVbT3BRlDRtMSUFw2T4koijNYJKq7URiWQsawWAsBP1t1+b6xS6s8baZhcUbVTZTkQLqgLqGwrEUJyer8WSyoz10QAAvnBGAoBtsTiIC+zU4CQA6qLiF9pKXf0vmHE9xgSYE6NWT18CgzWGIZFimgMA2yICT198eCZVFUrXgpqO3+ZFf2Bosc1RY8iRAEwlEUqoudbHHy0WPpiYrQ859qYcOgygiU6hbYoz1dAICaEiPjFLsjTwfUEAp77E8aR0EZlq2Huy09QwCAQ4tQEdVJk2o5ZKcX/9qpGHbzG0pZVl2KL5/aAECh5ukummo8ynX3s7S3DYjKOHR8EEUCFd0CvaqIVCQEYn87JJVBiIjZiW4BTceyvimx6JNQF1hUBiGE9Z/Cq075XqekY53sfY40821YnZKL1DWKsj2y5NZllSZMjxBRI4eyAWVYjqfQsAjq+0CCqsGiulcqU5SmOGNydm6hjw52AVBSC5T4jO/EBbNrIAgKA6NncGhkkwSFaSiCYnTq6+qkg3NPUIzztz85xiqh6zPHMpcQNSzF9I0L6hKKRLU8LIxhEXQueotwSCKK3Eo7jg+EdAYLASIhDAQjcKtuIi66HWUYW6osuqOOYdHR7aIgQgppokmZpD9MWGQJrWAc7GFuADnNKJpkiBBt8XAQRXRbCGUwRy1OPnqcO70SoqC4Tw52DiCkLkAFUQKvOjG39Cm++liGJSLS3a8FhkU1bkI2sE6JMLMuce6IlBBFLTW/HAIiQWaQyS4f3tun7I7PmV4V96dTqopwyoQyRAnw8lZlpxtRjdVyXdI2fyQEdB9ER18IxYQuIBokAOg+CIfKaFjZrSbCKePLWOXg5g5zMbKmYYmgvTfI6H0Kr7pEeZ0SuycRm59jfZkPJ9QUM4OFuoJYCLHDxRY2B1H+AUDEBjq/jIU1J8jDQkXmhKAvGIFTrbwdUnnVZIUEAS2VwHv7OjLSAtJcSNNr4l0jVcUeltX41W1HtTY7jEJhZrBYnDJm1pagvNCN/pCMD5oUt5RMN2c6l5CLMiwWDBav6hIKE+oS0kS3zGCxuIGkKNFFCoWJZhBBDqqbPvW9EkRrldiHGdxgSQEquDzclUHkRR6D7kAARUwnBbT02VYMFmqUUKocwW4tHNbCeRKeX8+wABgMySiC5k7IFGMK3Wyie31nK0LqAusiBAXqpNo5qLhW4jQsgnWGxakaN2EbXQmx8Dgl5haKK/CYBqJ04ZYjQKBbc384PNjTqiwas8eaL5AXzFIiOlarTExEzWtTJssQ1AnXL0eB4wdwfCCEEgyq1wQmVSpjzEEI0LJNu26GdYT0KHA7WPXdd/eZuyRov6WojAMt7SwjKIVHnfBLHSFN8G0DexiLP1y9AESNjBKjESAahSRTV4OLjScJhN2jsAXNRCKUqQbHYFg21thSQV1CIoniQEc/CtSIm5C6fLgdyZ/T3Ho/Ct0OdPaHMtJX0Qi0iQlqdl04W3n3XtEZLJruRvm9VNWEWJ2RRFHAOdONbiEWGQmt+KFLVg0MC+9sgYsaN6p2CgSyyrAUEc14jFqYZyj8LNttSGNwACASVHSA6hwaFsScZN7OFbjBkgI0i+moY1h0BosYCTKXEGA0ElJBo0fVHwLdzNdNB0o20Bs9EpERjERRnOFuKRbMLbS9BUF1Z+QiBIWqcSGIAbgkke1AWZtiNA8pEZXhVO9FKItkaOmA+vg/PJCiho4JWPh4NAQMdrFnOhiJYH+H4qaZWmWuwVkyQ2FeNh44jva+IAIq++UiBKcNBlAbjmJcJAwEutDRH0KxarAQAXj4qjkA1MmoZasmbLXB4AWAxZPUQnwJQmu15xnBkdajBqEwAPhUUr3COaiFNdtgKMSi1u+FWy2sKckRINSnsZWS08CwMJeQDfeowCXBpSY/7DTJdhtVXXMSieJAx4BusUtvADolkeU0ycQt9Okx5d2bVGnuhls+sxqCoFTmPnRc2VhSBpnevzGSqnuzfHXgHFWz9ebuNsM5RL1LSDUsIxYMFp9LgiQKgKCmzicEYZVhKYLOvZXBM6bJALsGwgir7iqFYQmpDAtt78gyAUZWa4cBo1bDoqMuxUgQjqC284mQ9Ic1E6DRxTvQo03qdjAseoNFjmAwJKOYqIsdMtt9UCyfqRgs7+/vRGufsotzEYJCek4piIoiN0TRODFTDYuYrkso0M3SYocduTVYKJuwudm6wRJlLqGwwfA8eLwPhCgp3MsT0P91fi9m1hWDEOCNj9uw75jyPkkE+E3rMdx1wA83ARDoxvH+EPy6CVkSNYodLdtsNXgBsJo27+41rxysiY1ltLa1xU2K1GCZXyno3J2Zv3fJoHdPKc+Afi6wcSmBaC4hG+6RIAgoVYW3ZrWoqGtOjEbR1N6vYzjTXz7OmKKwFJkIbz9VBbeJGJbKIg8WTjC6hWQdKwQApQJ1I1t3r5w+pQJOSUBTez8+PdanixKKsgy+rih14aR/TwRBUCorM4MFiKqaJb3BkskzLvHqXEJ6gyUSRDAso4gFLowsE2BktXYYQDUsh7sGM/Il5itYlltCIEQGIQ12ad9Z0GawwUsHlV7DYoGpSXh+lhuDQJAVOpMKNrO9Rp3fyya6H768FQAgERE+leYVxICpFoSJH9M17AY6meg2JORmoaOgDMuOIz1KOnkLYEUAVSaEMh3NnYoxN7WqMGkNlvNOUAzA13e24lCXssh8KM5B4/yfoRN+AAAZ7EJnfwglRHOxBtXJ3gEAR7eyxdgOgxcA5o3zo8TrxPGBMAuP1YNpd6IRdHa2s+tTeNXd6FkNLq1tNrzbZmCCbtUtx8YSibJrOojmgrWyuUgGKiw3Y5I1hkXGgY5+FBEtSm/pjHhNkxlossbYkhipcLw/xLQ1yaqiXzhbSdVPo4UYwwICgKCUirwzmMML3Q4snKDku3ljV5shrJkaLI4IZX2t0b5FHgcE0OdKIFMNC9Fy7WQyDrTkcWGEVPZHY1hkFFOjc+R4gwBwgyUlqOByICTjvhd34KHXd2P1zlamGB+poINABIBIAGKgm2kNMmJY1EFh2BXayLBIABAeRCAso4Todh9ZTtifm1ennkdp/7vyHOxxLwQACGIQp4yPz3MRm2gsJQY7GYVPdzu5wthSL+r8XkSiJGnuETNoUUKqS0j9nRof0xK4gyjOUxevd/Yew8HjiouxcuJ8zFt+NQYEZbFpbz+Gzv4Q/IIWTUYnVGVx1vQZdjEsDklk0R6vqxobPfTMUs/x9riSCz5VszHOG2ITpl3GVCzogicwlku7HhsLk5fA4R8PwL57NEFlL6jrz9AmxrDIONodYKL36lIfHrp8blrn15fE2JAkYouiuacZf9r5J3zcqjAyNSUe+FyJBa3nz6qBUxKw/XAPdhzp1tpMABciTDMVQTSjjSd1C63e2arbsGjncVGDxaKLpdjjBASqYdFEt4U6gz4jDQtLHhfSGBYAiAQxGJZRTLLXAQ4HuMGSAh6nhPoyZffxROMB/PKNvbjuyY1Y+rO3WLrokQg6CCRCgPAAMHhcmxwt7B7ZbiNCDZYeTZgYM6n3ByP41ZpPcPn/NeI//rY5oaZAD81vT0DCgwiEoyjRMSzZuIQAYMWsGowr86FIjVz2e304ZYKSV2TxlAI8aJLJVi/STAu9R7WwZjm3BosgCLqU4tbeT1YMUw6pDIvS5sOqwTK1OrnBckJNEer8XgTCUXQNKhP42NJCeJwSvMWK4Xe8ow2DYRl+ndEZVAWLLJdPDliMpTMo+9MSt2Bp0VERDPZ2anosFT6E8aNLToRgsz7LDOzdkkOK8Fnn+mFjYdI5cKjibbvep/FjVIPFJCMwTZQoRmV09YeYhsztdqDQnV5UjCAIltxCF7xwAX7ywU/wwicrASjVt5OhrMDFNGnPfHDQwLB4EERRlgYANcY/2N+J3rCeVSZKBmSa7DADhgWCPtOt8s4X6NqbybtGGZbOfs1gceiihIqZATeywA2WNPDrK+fhW+dMxg1nTcLlC+pRXujGgY4BfOWx97Hm4/gd20iAgWEJDxoWqHR3j1GieYQdamp/w65Qt+C09wVxxW/X439X78GGpk689NERfPkPG/Dn9QeQDMywAhAJKoPMwLBkuXAUe5z4161n4eZzxgMAzplWhzKvMjmePLGQ7Tz10LsQ0kL3IVCJZq4ZFkAr2tZo0WBhbkLVYKFL0bE+5X6b3Qs9BEHA0hNVF4G6a/R7FYbSU6S0qbdbaVOpoE3IGsOi/O7IgOlLhTOnlsPrlHCwczAugooyLNFwEL5ovxbxpmJSsYivLBqv3BOb3VWxiMZpWLQxSd91SZBYfSq77tH4csX1vb89PhpSZpotGQMDffCoy5zVK1O3UKq6Ql2BLvbzoV7FxTNuTOqoLJrA8PkPD+Nor/JOiQTwIoRCObO0DRT1ZT7MqClGlAB71HskqexNqYuwgpBW87wUeZwQBK3WD3UJFUQHEm780gFN5tfeF2RGrZMQkHAAgYjGUkdsSD0xlOAGSxqYU+/HrUun4c4V0/Hg52dj7R1nY+mMKoQiUdz8183Y3dKb+iR5Br0hkCnDoj9OpDs9nYZFP5ne/fw2bDvcjbICF3586Ux89qQ6EAJ8b+V2NCap5MqEhoQgrCasKtEtdnYsHC6HiJCaR8ElueBQd5SJjCEWTSOnb7AMFcMCaEXbth7qRn/QuntPjATVKCGlzccHlB11bE0lM1x/5kSsmFkNmmyT3suiEqVNob7jUDQFuvTy6j2hizN9D+1kMXwuB85XQ6+f3XjQ8B0V3ZJwCMUYiGNYaN4RxU1mnz7LDIxhiYRUDQvY9ei77hAd7L7aZQBTY7TJxCVEaHXyqAwy2KW5xSwudqdNLocgALtaetHWE0h43FuH32I/h0MKq5fOu3fapHJMqSxEbzCCh9fuUdoMAp8QRIHOYMn0vaIsy26VhVLYmxCqPSHtnbV4Tr3oVsl0q/zsifZnpQWkBsux3qBOdAtEwgEQAiZ6l0FGlDaTGywZoNDtwG+umoczppRjMCzjxr9sQiA8sjQtjGEhRGFYBrt14aTpDTtDUjc6qeujhNSB9ubuNry+sxWSKODPX1+IL5/agIe+OAdfXKCk1b7juY8SCkTpOSQAkZBiqJRiQMs4atPCQXf5LtGl7V4TGSy6qJK00H2I7ZaoYZRL1Jf5MLbUCzlKkqakjwXTsESCCuOm/h5W70NsPhoz1JR48ciX5+OCOYrPny6sJWWKO8AR7oEXQTihFbFkLqEYhsVuo+AL6vv28tajhveNXoWEwygWBuI0LJJaKkAvRM61hiU2Uksmsia61Rksdhl141WD5VhvkAlJWZsYwxKBFOrJ+PmUFbgws1bJ45OMZVl7cC37WXMtpjZYRFHAzedMBgDsalHySokA5paF4dI9r0yfHdVB7e/UGBY3Qqh0BjNmQwwaFkIQiSj33hftZ4tzJixaRSFlWEKGKKFwULmffmTnchouZGSwPPzwwxg/fjw8Hg8WLlyI999/P+Gxv/vd73DGGWegtLQUpaWlWLJkSdzx11xzDQRBMPxbvnx5Jk0bMjgkEb+44iRUFrnx6bF+PLpu33A3yRJoJJAEAME+IKglCkvXx6s/TtOwxCeOe3Stcm+uXTyeJTYTBAH3XHQi6vxeHDo+iD++u9/0GkxoSAhk1SVULAzaKuwFNIPFLblT7l6ZSDMaBtLZnXQfGjLRLcUilWWx4hYy6JF0ESqCEEV5oTtlgjDDuehzU5PsVVQok30xBlACdYdKcw0yDYt6/boFhnPYhYUTyjCuzIe+YASvbWthn1NXGCIhFKM/jmFxhAaU56xnWHLmEtLriIxjiWZElQTJdoOl2OPEmAJF9xGrY2Fh/HIEJejLauwxt1ASHcunXZ+yn7tVg6U2DYYFUBIYTq8uAgTlxokE+NmKKujf3Ex1bzNrS1BW4EJIpowIgVsIo8IZzPieFMdoWIJh5WdPtC+riDTKsHQPhhFQ52YnCCJqpe8yncEyVHOSHbBssDz99NO49dZbce+99+LDDz/EnDlzsGzZMrS1tZkev3btWlx55ZV488030djYiPr6eixduhSHDx82HLd8+XIcPXqU/fvb3/6WWY+GEGUFLtxz0QwAwG/e3Gc9HfowQmNYAPQquQsYw5LmJKg/TqIalqBxV3i0exDvq7v8a0+fYPj7QrcDdyybBgD4v3X70G1SLVbPsERVhqVY0Py7dk3YlPlwSs6UDAtbVAgAOQ3GROcSCqVzvA3QhLcZMCxyEFFdlBAQRZ3fWv4YJhBVF9aKCoVOLxYGUKy69Oj56T1xFI8FpiyFY/G3ANg/kQqCgC/MV1iWZzdpbiG6HAiRoCnDIoIAkUCciyYXoOydIAeNDEtUY1gkUbLdJQRoLAvNLMvaJGgMS4nQb1nrpscZqsHy9t72hK4IfZ96g8q8ko5LCFA2kr/+0kmAet9EAOhtMSx0mc4ZoigoRVMFGrAAeBDCGGdAY3wt3pMijxMCq6YMhFSDxR3pZ88+EwOrxOuEU1LepT71HjoJQSSk/FwG+yIthxKWDZaHHnoI1113Ha699lrMmDEDjz76KHw+Hx577DHT4//yl7/gm9/8JubOnYvp06fj97//PaLRKNasWWM4zu12o7q6mv0rLc2+CulQ4IJZNTh1YhlCchS/fuOT4W5O2tA0LAToOaz+rCDdQWdI6hamLqFuw87gla1HQYhSNdds0rloTi2mVRWhJxDBnzfEC3A1DQsQDQ1CRBSFGGAvbrZRQhRmDEuigawVfFQXsmQIB4D+Ni1x3BDtZk6dpBgs2w93ozeQ3jWphFoKBxHu69Qyvgok7R0uBUsHrhp/TrVIXwn6NYZFNfwYw1JQAVz1LCSfItDNBYtx2fyxEATFkDug6jXoGyREwqYMi0QIEBpQ3WT2C4L1YLW51Fw4epEv07AIjpRGdSaYM9YPIN7IjepcQiXoZ2LsTIy2+Q2l8DolHOsNYnerufZPP0aikCGJQsoCi3pMrizCPRdNB6CO0d6jEABbBNNnTasAfWNEVcNSKgUzvifFXp2GhRCEVZeQS+6z7KLXQxAElKtuof4QNVjAGJYxOg3ZqHUJhUIhbNq0CUuWLNFOIIpYsmQJGhsb0zrHwMAAwuEwysqM+S3Wrl2LyspKTJs2DTfeeCM6OhJT2cFgED09PYZ/wwVBEHD7UoUleGbjIRzsHBk1h+hCLwJAuyJQc6iCP6uiW4kQCLJew6LtNl7brlDvF8+pNT2HJAq44eyJAIDH39sfl9+GttMBgmg4gEJ1Z2Am7M0GdNE0GCyJGBaWOAoAZZb0GOgEmt5WflaNQZc66Q+F6BZQdqQNY3yQowQb0mBZCCGMVxAjAcgDeoZFjqtYnQqxDAvUIn0+IYgxgpoFV2UTKLslqfeI/k0uWIxavxenq5lvn914SLmO+p0zolSRjo0ScgBAuN9QriB3DIsCMYZhMYQ1i7kxWE6brBi578XUXKJ5hyQio0zozUrH43ZILIpt9Q7zCEtjn2RUF3vgkKztrevLaAVwsDHIxMJZPLtzpldBkqjmRGFYSsXBjO9JkcepM1iAcCQCByJwyINZC7ypW0gzWAhkdWOpGOa5DdHPBSy9Be3t7ZBlGVVVxuyGVVVVaGlpSfBXRnz3u99FbW2twehZvnw5nnzySaxZswYPPvgg1q1bhxUrVjDFdCzuv/9+lJSUsH/19fVWumE7Fowvw+mTyyFHSUItRr5B04YAOKYYLKJK/VplWJTQ6IDi5w/2aDVowiFsO6SI32gOBjNcMKsW1cUeHOsN4sUtRwzfsVBOApDwIHMnONTFzm7RrVN0pqTbZb2xF8uwEAI8fgHwxIXAvjfZZOl0FSU9Zy5A6fd06rcY2LJIEFJQY8ogRFFr1SVEmTH1nYKuqvB3T/Wq3ynTD3MJCQ7D/7nSiVxx8jgAilsoIkdZZI430puSYWE76Ry1jbBsw8E4DQvbIAgSu0d2LjanTCiDJAo40DFg2HhFaXVyAFXCcVYBOdNr02itl7YeMf1eP0YEQU7bHaSHgUFWN2SU0ctmk1PidaJhjJed2yOEUSwOItP8PIbU/FAYFropy5YRosLbgXCQnV8OBeBCGB6EbHerDwWGNErogQcewFNPPYUXXngBHo82AV5xxRW4+OKLMWvWLFx66aV4+eWX8cEHH2Dt2rWm57nrrrvQ3d3N/h08eND0uKHEN85Q9BnPbDyYNgU/nNAYFgL0KcYmXUDSfYEZRU1U10ioDyBRNnibO/sQkqMo9TnRkCSPgssh4urF4wEAf3inyeDb1owi5RrF1J1ADZYcim4TMiz6yTCWYdn1CtC2U/l55z+A4/sBAC51wR4qDQsAnKkaiW/tSW2w6F1rYn873HIfe46CEM3YJcQYFlEC3IrgeoKktCfWYBHpTp6yUTky7pbMqERZgQutPUGs23OMReYUyH0KgxAbJQToGJbcim610PJQXE4jZgSK9otuAWW3P0etxq1P6shywxCgWujMeiFdemI1XJKIPa192NUSz44HI7rnLkRZPTcrMGj01A2ZA9YY5ESYVKHMZTRKqAgDGd+T4pg8LOFwBEXqpkykBlaGz5i6hAJhNQKSAHIkyFyy1PgetQZLeXk5JElCa6uRymttbUV1dXXSv/3pT3+KBx54AK+//jpmz47PHqrHxIkTUV5ejr1795p+73a7UVxcbPg33DhragUmVxaiLxjBys2HU//BMMPAsKigk2C6uhC9IFYRJRqpfloAb269P2kNGgD40inj4HNJ2NXSawh51NdPQXiQFQWjuyW7GBbqEtLnYUnMsOgmQz3DQgiw7kHt95atQMt2AICzoCrpOXOBRZPGwCEK2N8xgOaO5K5K/UQrdjYBgEF0WxpTsToV4gwWQGNZWnco36ksAdOw0Do6lOnLkdvF7ZDwuZOUkgxPfXBQExsDKBX64qOECAEGjgNy0GBA5AK0LVKoP6aWkC6sWXDAqRb3s/t9OnuaEs31ilpEEDAa6LVCR1ZiUEBhKc6ephjTz38YP1cORnRGvSBjUpIaQolgyDNF3y/q8s7S2KwoUplAEHgQRhEGMnbfGPKwECASibAstMzAypRhUV1CAV0toWg4iGLh38RgcblcmD9/vkEwSwW0ixYtSvh3P/nJT/CjH/0Iq1atwoIFC1Je59ChQ+jo6EBNTY2V5g0rBEFgmRafMxmE+QaDhkWF5FBecKt5WCSayyWguH8kdSHa36GI6ubWpxZQl/ic+OIC5f797u0m9rlWS4hAiATYYKOLml0aFn3iuFT6ACYojWVYDm1UjBSKox8Bze8pxxbXGa4zFCjyODG/Qbn3a3Ylz8hsYFh6FG0HIcrbMXdcESsSmS6SGiwt2wAAkpo+PdYlRO9/rlgMALhcHatv7GpDJGo03mODtyUgY2G6VbA8LAMdintVdz39Pc2FSwgALpmraM3e3duOVjW5m95AnyIcthxNaAY61p/ZeNCQw6ovGAGB9vu8hmLGvlqBgZlVIYk2uRoFbe70IAQfGchOw0KLH4KARIKMYaEGVqaGITVYKGNFM91qDIty/lEd1nzrrbfid7/7HZ544gl8/PHHuPHGG9Hf349rr70WAPDVr34Vd911Fzv+wQcfxPe//3089thjGD9+PFpaWtDS0oK+PiV0rq+vD3fccQfWr1+P/fv3Y82aNbjkkkswefJkLFu2zKZuDg0umVsHSRTw0cEu7G3rS/0HwwjTAS0pbjrLoltAWbiDKsOi7pQPqFV+547zp3W+r502AaKguDBo9mBZt5iIcgDFsGcwx8KKS4iFQMcyLJseV/6fcyVQUg9EI2xxdvoV3cRQiW4paH0VKn5OBIOGheaMIYpBcebUcoiitZTjejaAgRosIeW9oAZLHMOi/p/Lnd+UqiLMbyiFHCXoCaguKRoK6zC6IJTQWDX0PwdiVz1o1l1RDgMkCoeObWLGe47CmgGgYUwB5jeUIkrAmGI9W1EsDDBRcjYL/2emV6LO70XXQBgvfaRpWXYc6WIuEgCYUO5RF3Vr0GqlaZ/RZ5ctO6Znpz1CCN5oPzLNz/Nh+9sQJE2zIsmDKGJzXHbjgBoshmrNkaBu05e9pmeoYdlgufzyy/HTn/4U99xzD+bOnYstW7Zg1apVTIjb3NyMo0c1OvGRRx5BKBTC5z//edTU1LB/P/3pTwEAkiRh69atuPjiizF16lR8/etfx/z58/H222/D7U4/lC0fUFHkxllTKdV5aJhbkxwscZzeJeRUJmqroluJECAyyFxCDnViaO9XBuKMmvRcduPG+LBMXWD/8M6nhms4QBSDJZZhsSsPiy7TbSqDJaKm5HdS7Q4A9HcA2/+u/Dz/WqDhNO0PHB64ihSGZah3M8tnKvfzg/2dONZrEtGkgr4PgDYphATFV5/JwkQnQQPDUlBuOIYyeqyWkBDjEsohwwJoLMtAWHkmojoWRK/GJkmAYkJ0Kzo5amTlTsOi05YBkLwKQxYhWpSQIXFcDhYbmqvmD+80YTCkuaIEfXQcFKMg0w2DJAq46lTFiP/5vz5hLMvWw8aItkzHN22zgUGW7GHuWOQiUcKa3boQZCvG0I6OHbjjrVshiBGUhkXURiKQIjqDRcxuHNDM1CFdtWYiaxoWp81z6FAgI9HtzTffjAMHDiAYDGLDhg1YuHAh+27t2rV4/PHH2e/79+9XQiZj/t13330AAK/Xi3/+859oa2tDKBTC/v378dvf/jYuEmmk4LJ5ymB/YfNhyFHzxEj5AMawiBoBLlKDJV2GhegYlnAAUIuW0YkBiKLI40B5Yfr6BypeXrn5CNp6A2xCFokS6llCDZYsB3Ms9BoWp5B8F02NDhchSr8BYMMjitFWMxeoPwVY9E3tD+QwnHRxHkKXEKCEN88ZWwJCgNe2H014nIFhUf+PSEpkUyY7UlOXUM0cwzGSg06oIcOxuRCUmuHC2TVqtWF1IVY/d+oMK6rHgqrrcTisjRGrMGgvAIi+Mex6dCwYItlywNh9bt5Y1Pm9aOsN4snG/egaNJZO0IuSsxl/1ywej5oSDw53DeLn/1JyWG2PNVgyNMgM1ehVSJLq8s7yvWKGIwA3wnBFei0zLFESxX+v/28QEIiDs/Ct5ir4CIGLBFGkVqN3ZKnlotFVEV1qfkS0OdTx72KwcCTGuSdUotjjwNHuANZbrJY7lDAd0A5lR53uJKF310AOAgNKf3uC6iQvRDGxvCCl4FaP+Q1lOGmcHyE5ij83HjC4nSRZ53+1id6lsJKaP2yYAAJKaYMNv1W+POM2QBCUxXnCWcpnJ39D08WkWzDRRlwyV2F3/tR4IGF2UZqFRSBg9WZlp8KMZbJo6NkAhrr52s/eMkbRx0YJDZXB4nM5cPHcWuaCoKyGw8xg6VACACSXIgDNWWp+qi1TH5PDV86up890m4s8LBQuh4hblkwBAPxyzSdoalfcs3SxED1+dmw248/ncuCeC5VM4Y+u24fnNh3CtiNGgyVTRtKQckGFwyaGRe9OdwshOEM9LEoo3eexs2MntrZvhdfhRXXoS4hEFePCi5CWWFHKriJ3RaFbyXZLw6YJAeQQc6tzg4UDHqeEC9Ukaf/Ykr/iW01Ip1G6lqOEdO4aAECvopPoD9ElL8qqwFrBdWcoieSeaDyAvqC6+yYEjmgQpYIyeUo2CzOtiG6ZTxhQtDtN64BgN+AfB0y/UDvwyr8BF/4MOPtOuKjAdIgZFgD4/IKxKHBJ+KStL2HROS3Hh/YZcZcYvrMCU4al9iTtZ1cB+y6RS4iA2KZRSoRvnj0JNCcZYxB8Ws4gmkwRfYpoeagMFlZXqUCJ2olEI4b6TLl0CQEKU7ygoRT9IZmFHtM2OYrHxrU3U6yYVYPrz1TG++3PfoSmdmOYc6aLaSxTBWjBAFlrWHSRix6EIAW7LDMsuzt3AwDmVsxFVWElBqGwP15BY0DELBMoiqKAqmIPq1XkJIAQCWkMyxBtDOwEN1hygBWqbmDdnmN5W7pbY1h0BQwtih31Sd0AMGFihKguISGKiRWFltu27MRqTK4sRPdgGGv3qAsFAEc0CH/s7sOmwWYW1pzKJcQYln1vKl9MPg8QdUPKVQAs+BrgK2NGkJ0U/qfdn+K5Pc+lXDSKPU58QY3KeHDVLkTk+OO1qDHNYpE8mafI17svGHTJ49DfzgwTeu/pfZd0bspcuV4oxpb64FabyHQjhZXseylmipRchTltVywzIBUoxlOURLXxlqM8LHqIooAHLpsNj1PUomKoQVcyjh1nh8F05/LpuEaNBBJE433NWMOir0avgs1vWbaZRUeC4KwJhRCD3QZdTzpz/p7jSm6YqaVTUV7oQgDKhsaLIMqoCFcdO9kYhbV+ryH1vxDV5WGxeQ4dCnCDJQc4eXwZPE4RrT2J62UMN9iA9qghx1WzLIsd42jXHkXtHyaahiUThkUSBdx63lQAwNufqAYLIXCREPwqw+JQGQu7o4QMBkuCiS0c4xPGp6rBMumchOeneTPsYlgIIfjPN/8TP2j8AV7c92LK47/5mUko8Tqx/XAPfrkmvuaV9iy1KcFVWG74zgpMGRYAUF0cqJvHFhAWJaS+f/rIoqEQKcfuxqVCLacUdVNRUIMlZ7WEYqJbHIWKlk8f1uwUUhfotAOTKwvxyJfnQxCMGh+pRMssbofhJooC7rv4RDx+7cn45ZXGHF3ZMizs6XlK2PuV7Zyhf0bTCwfVZJka0hkvn3QpY3BK6RRUFLoxSFSGBSH4RVV0q85x2bxrdX4vBF0mXUEO6xgW9fzcYPn3hscpYZFaLXfd7tRZRocDbNBVTAPOvAP40lOakDXNSYhGltA0+dQlFFF3C4KQmcECAMtPrMaMmmIE1WJgdAmrEroAAKKY/WCmIIRYC2vWhwl27FX+CRIw4YyE12AMi00L8IdtH+LTbiWSauXelSmPryzy4F61svgv39iLX/zrE8NOkE3wOpdQQUHmLiF9GnkDrnkZmH0FcPGv2HfMJRRTSwjIfaSQ/hpMN6JjWKhhTCGp2XpzLbplETmqwWJwCeUwrDkWn5lWiTOnKnOZQKs2++uZIWfn8zl7WiVm1Bnni6wNlroFgMMLfOEJ22pUMZcQiOYqlLTM7anuCSGEMSxTSqegvNCNAZ1LyE8DC2hEWhbtrSnxGDQsUjQEv6CkFaDvdpiM4jwsHOmBhje/uy8/hbdsknZ4gHO+B5SMtcywaPVilFWOqC6hsMEllJnBIooCbls6lQ02Su3WCIooj4bE2rFwRKIRJjo1ZLpN4L7RGBYAB5TEcKiZbXR5xMAVkyQtW/x9z9/Zz5taN+FgT+ryFJ+bNxa3L1WYq5/9aw8eWLWLGS16fQRFsVo+w1aGpfIE4HP/B4yZpBksUXMNC5B7lxCgW9z8DcD0C1n0EqC9ZxQOarDkKqxZn9tIcjOXUGwtoaFgWCh8LrVkgkdNT+Cvtz2tAEXsmMvUIGMbsvIpwF2HgEmfYUaWXS4hpbCimp/HghD52OAxdAe7IQoiJvknobzI6BJiolg1qimbd03vEnISQIyGUAqVpVbfc86wcODEOmXxamrPzwRybEDrFgerk5A2uSqvkaAmBAuru4XL5tfC53KY/3EaOGd6JSZVKpFLIjFGGtHBZsfCoXfTGPKwpHAJuQgBjn2sfFgxPek17GZY3jn8jnJZr1ov6PBbaf3dzedMwffVyIz/W/cpfvjyThCiiVujohtPRs7DV0PfRYk38zBQ0zwsMaCMSpzoVpQgYGiSWun7Ln7tdeCKvxjHhGQ0WOjClLPEcbQtZ34XuOTXmlsgGjHc06EUTLLNzbhFQPVsYPwZOcuVE/u8s9awCCIgqdoom0o+GIxKdZPm8GqblVTv7N7jSsRZQ3ED3JIb5TEuoSKoiRVtMChqSzyaS0hlWGjgAjdYOBjqS5WF9khXwFTkONxgiZV0Pnq6gFiOEorx87vdCqtSU2Kt/kwsBEHAZ+fV0t8M39GFxI4dONVQAMYooYRhzTJNxKQT142ZlPQaLtWFZYfodjAyiOPB4wCABVVKqYueUHwRuUT4+ukT8ONLZwIA/vjufnz/H9tZuHVvIIp7ItdivXgSPM7MU5nTe5fMYKFalViXkP7nXE+m+nddkuJFvw7RoeluoDEuuYpeYkzXgq8Bs78YZ9TRNg2lwcI2N1OWATe8DfjKLLuP00Xs+Mg6SkiIeZawN3Ec1PfcCsPSGVRY4kqf4nqMdQkVEjVKyJE9w1Ll10TvThA4SIgFLjhHoMGS+faXIykqi9xwOUSEIlEc7Q6gvixxteLhgOmAFqwNaEaNxhgsTlfmGVJjIYnqwkD00TeFtmWtBHS1bEQHREG0ECWk+7AsucFiZ7G6ln5FK+Rz+FClFlUcCCcvbhiLL5/aAJck4rvPb8Wf1zejW6adUSsoR6LsfchkcWZ+/jQYFhYlpBPbOgQHIojkXMNiqKFE88Do2iEJkpKhd6Bd+x25cQkRQphrklWujnGb0c9yVUvIDJq+Sbe5yRXDEtOfTBk2A8Oiwi43lhYlpEH0lkEIHQEBSXlP6FgtcCgbu4oiNwZVl1AhBuEjqktINSiyixLSGSwEcEe74aRRQ051nh4Ct6td4AxLjiCKAqoqWgAxgIOd1haToYDpgLa4q2Xp/WMMFodTzVVhw0DQzqG7hrfUNgEdYEwaByCpPkBf08WpD18cMznpNSjDYoeGhRos1QXV8KmTTn+43/J5vnhyPf73C3MgCMAr29R6Lqrr7epFDRmzHHJUZguvoZZQDBKJbgHY+nyTwZDhl4pKY8fErM8rvxRW55T5MbA9NGJKNFa0pm0aKtGtvl1D8Xxi+5O16NZkfss6cRxLmKkb/15/2qwTNVjo2C31uRBUGZZK4bjWXhsYEFHU3iknIXBDGWuy5GUamZFUS4gzLDnClrYt6PI/hAJfGZo7T8bi4W5QDMwmoUzDmh06liZAnHC5vEDAnt0XPQchRoPFLgEdoC0G1GDRMyyEEEOmXv31XE6fkuUWAMomJr2GPnFc7DmtQm+w0F1aXzgzrdTn5o2FHCW48xVFtOt2OPDhj5fD7ZDwwidK6KXV56i/R+kwLJp4e3hdQrGZdlmbTrsFcJcAk8+F1KJoh3LBsOjbQt+PWKOOtm8oRbfJ2IpcMywZZ7o1iVLLhjE0nFtfkoTCWwqpT0qLFRyIqAyLurGTRAEubyEgAxWC6tp1FdqSHJPdP2Jsb1S36RtJLiHOsOQIjUcbAQCiqxN72o+kOHroYTYJWd01maVf70IhfE77JlN2DqIbbt5S2wR0gC5MWZ0g6MRmRu/qFw6nvqqvO3mCPI8u8kS/W84ELQM6g0Wd9Ky6hPT4woJ6/Mc5ikur2OOC22Hc3Vu9x/rj9QZxLGJDns2M51zv/gwMC60WHStEl5zAwuuBMZNyyvyYsT2xbjP63XAwLPocPXYlYYsF7Y/XQevg2MewsE2OXbWE9AyLx5/2nETZUJ9Dkwl4CoqMB3lKbHnXmCaISAYVoOgbM6TvkF3gBkuOUObWKr5u6XxnGFtijqQDOt1aQrq8EBRdpBBel336EtpOt1Mn4NW7hGyMEmIuIUnz+ybb8TlKxiJduHXRJtkaLK39Su6Hap9msGTiEtLjrGmKsNTn0vqeqdFguEfJGJZYg8VMIJljl5AZw2Im/mW/51DDYtqWmGRnoiAadVZDQOdrhVJNGBabnw8db3YZLGasnV2iWyPD4k/biKMMi9epbXgm1hgrmesNoGyescawGN9jsaCMMywcGgJygP18KLh+GFtijmRhzWlHCZnQrt0oQIGNBgs9R6lPYygMDIsN19Cn5QeMi2ycwSJr0S/iRb8ACquBC3+e8hoO0cGYm0AkkOLo5LBLw6KH2bOkC5TVRUl/z5JpWGKNGTP6fkijhEzywCRigXLOsJiwPYB2X4YlSsjkvthtuMUyLFkXP9QZWQ67aglRV7hBw1Ka9vljRbcAcNKkWuNBnhItOZ/F9gYiAbzR/AZ6Qj2MESbEONYE35ghFW7bBa5hyRGoFQ0AgziatW7BbtjhEtIYFu016iKFKHRln6GRgiUgc+qirArKIak1R+x0CTGDRUhssFA2xik6lYrMt+9O+zpuhxuRcCR7l5BqsFQVVDHmRv++ZQIzxi1Tnz97ZoIj6TsftxjrtSM27YZTQX9+Mw1LIqNqyBiWWIZH/T0XtakSIZlAP1cMi0fKTnCaS4aFtsmw2/f40z5/rOgWABZMiWFrvX7LxWgpHvzgQTy35zkUuYowp2IOAIDEMCzwcYaFQwf9LpoIIRztzm5XbTeSJo6z6hLSpS/fGJ2KAnf2+QPirjHpM8Bp3wZmfRE46Su2LhyxUULJEpexkGZ9Ub80Qc+vZ98ygZmGJWuGJVkYqEVK2sxVaIZE7hbDtYeIYUnEqiRyW+XCFWMaJRTDUNHfmeh2CFxCNBvyUDAsdrmEchnWrDEsug8LxqR9T2JFtwBQVhKTJVtX+8jKM+4OduOlfS8BAHpDvSzBpDs8HbI++aa3bEiF23aBMyw5wmBkUPtFDOPjoz1KmuQ8QbLEcWkzLDTXRvlUkJNn4ivvVeEdeQa+4z5m6TzpXEPylAKn3sg+t3N3wFxComZ4OUQHwtFwfKpwOXuDJRjJnGEZjAwy46TSW4njASUMMluDJemONEOXUDL9Suy19NfT/22uF+RkOUZi26T/PdcuoVQMy7Bkus2CjU0XdENAReoEBHJUTmn8xiKnieNoOgeaOLJiOlA9O+17Yia6hShBFl2QaL4dPWNj4R6/uO9FBOUgJvsn4/YFt+PDtg9x4pgT8dxbJQi1vASvGtasMCzKvR5JYc2cYckR9AyLIMjYcfR4kqOHHnYmjpM8fvSeez/ekZWU70Vu+woTJtqt21l8LdYlBCReEOjvLsl6Fl87GBZ9NJDP6WO08mBkMKtwzWQuIcthzZkaLMMgujWroWQWrcTaleE9SQepjCdAuy/5omGxe7GLZVgyvQZ9PnqXpF1zBpv36uYDFScAX30REKW0z08ZFr1LCAAkl+53/7iMWKx1h9YBAD4/9fM4re40/MdJ/4Fzxp2Dk8aVYi/R6WS83CXEoUOssHLH0fZhaok5zHZNZmF/O45044/vNmHV9qMYDBkHjp6l6epXd0ZOER41rNkWhsVkQQHsE9AB8S4hQKcRiKlkatCwWATdNWajYaHMndfhhSiIBlo5m9DmZAyL1QmN7pLjKjXHIB2XUM4z3UZTMCxDKLpNx2CJTSg3lAyLfvHPVZRQrOgWyKyPSd1YNolupUseAW58DyiqMpw/VXsZwxJjsMClKxRbPjWjZ3y0T6ltNLV0quHzueP8uCN8g/ZBce2INFi4SyhHMLiEAOxq7RimlpjDNHGcTjRGCMGdf9+GpzceZN9XFrnxw0tOxPKZNYZzOEQHjg8oC3mpz2XrYpMoxbudokxqQOjDmRMN5nxwCQHahO6W3JAECTKR0R/uR6EreT6YRDCLqsh0R8p8/Da4hHKdIyIlw5JDZs9qW4B4hsWO+0OIkm8o0fPSMlrbL2CNhSnDksGCmtSNZVemW1ECROvnHwwrY1gfJaScUDenVEyFOLDXUnsJIUyQX1NQY/huZm0JdpFxuCT4Qzx8RghjG06DY6eSGJLnYeHAoGw0WA52dWHLwa7haYwJTAe0LirkZ//6BE9vPAhJFHDW1ArU+b1o6w3ihj9/iEfW7gNgzFDamSODxSwLqv73XORhAZIYLLRScwYuIRr5kJVLiOZwUCd0QRC00OZI5joWs+RgmUYp0HuWyqhLFtacqx18LFi/TcJfY3/W/54ThiUF2wNo98wuwSQhBFevuhqf/cdnE0YcDWWmWzq+9GMxkwU1aSi2XQxLBnMSIYSN0ziGpa9N+7l4rOXx1xnoRCgaggABVb4qw3del4TvXXACZpz8GdQuvx0QRR7WzKEhlmGBEMZ3n9uKv39zMQrdxts+EIrgaHcAYTmK8kKl3HiukcwF0BMI4uk3Fev+/s/NwhcX1CMYkfHga7vx2LtNeHDVLrgcImSvttPoogZLgdNW2txMHKxva65dQnFhzXLmLiG3Wn3VLpcQRYGzAL2h3qxcQnZGVWSqYTELJx6qsOZ0GZZchlubtSWRUae/P9mkTGgdaMXmts0AgObeZkzyT4o7xk5BdiowY1dywiE6EIlGbGNY7MrOm5L1TXJPgnKQ3U+9OxcAoB+/omh5/FF2pcJbYWCLKb5xhrF8yEjMdMsNlhwhVsNS4iPY3dqLK3+7HjecNQkhWcbm5i5s3H8cu1p6ENWFyE0oL8AXFozFV05tQJHH+sKYDpItULtbuhCJEpwxpRxfXFAPAHA7JNxz0Qz4fU48tHoPfvzKTlx4tlL3wiE40NGnMSx2ChMTuRfsvAZzCYnxLqHYwUx/T7UYm4GJbrNIHEfpZH2EAaWWs4kUSuUitAKzkg1mSKZhGSr/esoooaEMa0YaGhb1nlG2DlCM2LjdeprY1bmL/dwV7DJvl42C7FRg40tQ6iVFopHMGBYzN1aOGZZ07ol+jOo3HWawymId7Vf0K9UF1WkdT9+ZbHM4DSW4wZIjxDIs31kxEQ+ulLHtcDdu+uuHcccXuR1wOUR0DoTQ1N6Pn6zajd+/3YRvnTMZX1rYAJcjsfeuoy+Ij4/2oicQRlmBC3PG+uF1JV8szHZNx3qUieFQlzKoblkyJe7v/uOcyWjrDeDP65vx5q4WCH5lIvv4aC8AYHJlISRR0evYsdgkmhzsqgsCWGNYWB4Wkx1MKtBFJhcMC5CdwZLMRWg5rJmkx7DEultMawnl2GBJthOP/RnIbfSS2SIbyyzSe0ZF11ESRX+43xaDpWPQXGdnpyA7FQwMSxYui1xpWKjeB0iib0rybuhdurHPlqFyhuH86b5r+gzY6aDQqejd+kPZpUQYSnCDJUegu2in6EQ4GkZNqYSXbl6EP7zThI0HOuFzOnBiXTEWNJRhfkMpqkuUxaw3EMY/d7TiN2v34tNj/bjvpZ3443v7cdPZk3H+7BoUuh0ghGDfsT78c0crXt/Zio9itDGFbge+sqgB3zpnSkLDJdbVsnpnK3795qfw1ABRyJhZV4z5DWVxfycIAu696ETsbevD5n4ZLgCDIYIdR7oBKOIuMQei24QLxxCHNbNjxQzCmh02hDXHaFgA2JKe38706+m6hOLcfEMg6oxFponjcukS0rt3BEFgompAu6eCIDBXYG+4FxWoyOiaeoOlfdA8kjFZRGHOGBbRkRXLZvZc7WizWYFK9nsaLieW5dZhYmB+7vfAWz8BPv9HANZZLMqwxApuE4EK9DOt9D4c4AZLjkANllJPKdoG2jAYGUR9mQ/3XXxi0r8r8jjx+fljcencWjy98SB+tvoTHOgYwHf+vhV3vbANtX4P+gIRHB8w0qQTywtQXujGgc5+tPYE8cjafXjj4zY8fNVJmFxZFHcd/YDuCYTxvZXbQNQBLQhRXDqnLmEbnZKI31w1H+c9+QRCAP664RB6W5Qwupl1JdjdY6OGJZXAzQ4NS9TEYEmwu8sm0y1jWOyIEnLGMyxZaVhMtEJUiJqxhiVJHSEguUuI3t+hysOSrkvITmYvFmaLLP3dbBwUOgvRG+rNaodsYFgCyRkWO9i3VNALtrMRFpvWErKBHTPLRszOn8Y9SZSDBQAw+wvKPxVWxx8zWArTNFic3GDhUEEXljJPGdoG2izrFhySiKsWNuDSuXV4svEAntl4EE3t/TjYqZzXJYlYPHkMzptRhfNOqEJlsbIYRqMEr+9sxfdWbsfu1l5c9Kt38eNLZ+Ky+cZaFfqJ+tmNh9DaE4S3lA5AgovmxBTjikFZgQvnnFCOVQeAoGo7lRe6UFXsxt6+HDAsifJh2KhhsRIllIlLiIU12+ASMmhYqEsoiyghgvi8FZnWEko3rDktl9AwZLrVsxpx2qkMI6cybQug3peo7mcVha5CoB/oDfdmdL3eUC8O9x1mvydyCSWtJTSCGBY72DF9WzIRZLPCh7GCWxNYHX/MJeRLzyXE5g3uEvr3RjgaZhNtqbsUQObCpgK3AzeePQk3nj0JR7oGcbR7EG6HhMmVhfA44909oihg+cxqzGvw4z+f3oJ393bgtmc/wvpPO/DDS2YyF5FeZPn6DuVFv3D2WKxqAyZWelFV7Ik7dyw8TkpdKxOZUxLZZA/YHNacYDduq0tIjHcJxQr+WKbb4XIJhU1cQo7sXUJ2Lkr6itbJEOfm0xkwudJIxCKhQawaLLlk9uLakkLMCRjvaZFTYU4zfe6t/a2G31MxLENZrdkpOrMqz5CrWkL6/sYZ3GncE9O0/AlgNarp2KBSEqXCl557sMilvD994b68K86bCDwPSw6gF9z6PX4A2UWGUNT6vZjfUIaZdSWmxooelUUePPm1hbj1vKkQBeDZTYew5KF1+Nv7zegJhNmgeuPjY9jQ1AkAOKl+jPq36bEHdNKuL1WoxStPGQfAXmEiS04Xmw/Dxmsk07DEGiwsrDkb0a2NieMAe0S3yXKAWJ3ge0JK9FixqzjpcckSxw1ZpttkrAYS76JzWfwwUVsA4zigz70vlBmlHxsV1DnYaXpcrtwrZtDrn2xnWGxghfT9zSTVQlKXUAysGsfdQUVHWOopTet4+v4QkPg0HHkKzrDkANQ4EQWRTdrZVujNBJIo4FvnTsGC8aW47ZmPcLhrEHc9vw33vbgD5RNbAQn4YH8XAGBaVRGqipTFOd0BTY/70inj4T9pDlbMUqjIXGS6TcSw2LFwmBksKaOEhqlaM3MJ6SY8OkElCktNB3ZGVRwPKnWzqLGeCMkSxw1VJVmzfgOaYTActYSSliyIdQkhcw0CXeAoEjEsydLc2224mTEsiRLaJYOdUW966Pub6J2xm2FJ510LRAJsbqCsfip4JA9jEntDvRlHmg0lOMOSA1CDxevwsheT5s8YDiyeVI43bjsbd58/HZMrCxGMRNHRp7TRJSmD7PKT69MKy9ODDiSv04nL5o+Fz6VO8jbS+Yky3VptazIk1bAQ+wwWO2oJmUUJlXmUaK5EO+R0kIz2j5KoJc0GrSCdauKMm/B1BsxQZbo1W4wBjU0YjmrNAozUfKJijEw0mSHDQg3LSSVKsriOwQ52P8zalU1l93RhqmHJwCgyjRKiItYsjCw94xvrQklHkN0TVNlHd3L2kV4DSO8e082KQ3CkpY8BtEgzIPtq70MFbrDkANTS9UgetkgNB8Oih9cl4fozJ2H1f56Jl24+HdOqlRf11iXT0XjXObj2tPGW6e6EGR9HWlizWZRQirDmrES3NriE9Ds0ZrAEMjdYkoWu6r9PB12BLgCpqelEeSz03+VadJuIYaHvcEJDOZcMSxpVrIHsGRa6yE30KxlQA3LAVGuXLLlermoJGRiWDBLH0XlDb1RkKiI3O2/su6v/LNk9YToTb2qdCTOA0hgD9Fn6PX5LWhS9jmUkgBssOYBeZ0B3wvniIxQEAbPGlmBSpWKwFLidqCnxQhAEywN6KOr8ZFO3I11YycNiR1izHS4hU4YlC4PFbLHUL45WJvnOoNIOv9uf9LhEokX9tYcq020i10/CDMs5ZFj0WpHYtunvWbZhqdQlVFtQy94ns0gh0/IFuRLd6gTb2bgFzaLe7GCFEs15QHoGEc11U+4tT3ktFpEWTT32KKuZaszFIlsd1FCDGyw5AGNYHBrDki8GC4VZ3g2rrpyhqPOT0GAZolpCiVLzD1stoXC8wUKZjOOB4xnvHlPlI7Fyn9NmWJLVEsqhYaBHQiNBNGdYcpnQLqHxpHeV6TUsWbqE9LvyMR5FcE8ZALN2DYVLiBoEhighu2oJ2aC7SRRVBqQ3f1KDZYx3TMprWTEKqfFp1WAZablYuMGSA+g1LHRhsSNKyE7YEarI/Lk5rPOTyO2Ui1pCaYlu5cyrNdtRS8gsyoAyLBESQW8os5wcyWoJ0XOnC6qNsOoSypdMt/rfkzF7ZnoPO9qSNAOwXsOSrUtINSxL3CWoK1ISRerzsgCKxmdIawnJNuVhMaslZIORlUgYrb9WsntCDZZ0XEJW3KJM6G7VYFHfIa5h+TcGpfy9Dm/+MizJokLSHNAJXUJDyLDYWUvILA9LnIYlmnm15lzVEnJJLpaTI1O3UKoigOk+S0JI2qLbZInjhsollDBKSDQKyGM/1/+tbW1JkSQx9vp2MSyl7lKMLVQSSx7sPWg4JlFm15zVEtIxLE7Bhky3NhtZSV1CKeZPQogll5AV4bmeLbMC6hLKdKMz1OAGSw6gdwl5pTxnWLLIfTEUIces8m8uE8dF411CiRZMvSjQKmxxCZkYLABQ5s1Ox8IMFhhFt1ZFpgORAeY2S7XbS5o4bogz3SYS1yYTwNptsJhVa469pqnBkqXotsRdgvqiegDAod5Dpm2KbddQaFhyluk2i41UMtFtKpFsT6iHjQ0rGpZ07jFzw6YZ0kzBCiByhuXfF/ksuqUwjQqxWLuCpWBPlPFxhNQSMnMJJawlJNsgus3GJZSgeFq2wttETIPV2jn0+h7JkzKvQ6JrAbmtiqxHwiihBInjDJFTNrctY5dQthoWtx9ji1IzLKYGSw5rCWUVJWSiTbIj8izRnAekvieUXSl2FaflUrYy9qhLqMRdkvJYPf4tNCwPP/wwxo8fD4/Hg4ULF+L9999Pevyzzz6L6dOnw+PxYNasWXj11VcN3xNCcM8996CmpgZerxdLlizBJ598kknT8gKtA0rK60JnYd6ENcfCNCrEYpRQKtGtHfVWcl1LKEqiWrr9dDLdmoRAp4tsawnJUZldP45hyTIXSyLfvNV3gu700qGm48LhTTK6DpeGhUUJJciwnIu2pTKeYq9P3YCZLDZREmUZiUs9pcxgiWVY9IvvUGiMTFPz28ywZDMv0bbEPiMgdZ0pKmhOh10BrI09q1luKUZaxWbLBsvTTz+NW2+9Fffeey8+/PBDzJkzB8uWLUNbW5vp8e+99x6uvPJKfP3rX8fmzZtx6aWX4tJLL8X27dvZMT/5yU/wy1/+Eo8++ig2bNiAgoICLFu2DIFAfi3y6YAQgjUH1gAATq05dUQxLJZdQsScHtXT+dkKE1NdI9sJk+pXAHOXkJ1RQtR4lYmc0a5R/w7pqzUDuWNYrOqRmOA2DWo6Wc0cet1M7pMVJDS6BXOGJdPIqXRgJhSN/V3fngKXWqU7MmC5Lb2hXrYQlrhKmIalI9BhqPqdkmHJUR4WQ1hzFonjsomCTHZeszpZqdyYVgS3gLWx9+8S1mw5Nf9DDz2E6667Dtdeey0A4NFHH8Urr7yCxx57DHfeeWfc8b/4xS+wfPly3HHHHQCAH/3oR1i9ejV+/etf49FHHwUhBD//+c/xve99D5dccgkA4Mknn0RVVRVWrlyJK664Ipv+ZQVCCCvZnS4O9BxAc28z3JIbZ4w9gy0gg5FBHOk7kotmZgTqljCbDENyKK220nMk24Ue6jtkKlBLFyzzZYJrBOVgVvdVLzbTi27pZNkT6jGcn/p6s0nNDwAHug9YToVN3yVJkOKKL1KD5WDvwYzuB83AmWixPNJ/xNRvH4um7iYA6e30EmWR1V+3L9SX03Gjv6dmbUmkbQGUiJpMi5oma0uyDMBmeVgAYF/3PsPvqUCjgQqcBXBKTpRIJSh2FaMn1IMtx7ZgfPF4AMbxYaal6Q312vp8WGJGHcPSGei0fA16HjOGJZs5o22gLe687PzqO9Md7DY9Px0b6YQ0668Riqaej+m7k2lYc0egI+17UltYa+kadsKSwRIKhbBp0ybcdddd7DNRFLFkyRI0Njaa/k1jYyNuvfVWw2fLli3DypUrAQBNTU1oaWnBkiVL2PclJSVYuHAhGhsbTQ2WYDCIYFCj1Xt6eqx0I21EohEs+/uyjP72tNrTUOAsYLviwchgxufKJcxU9H3hPkttTZbo6vznz8+yhcmv0TbQZst9FSAYFwb159eaXsNrTa/FHZ9NplsA+OyLn82glQq8Dm9cNktqsLz06Ut46dOXMj53osXyG69/w9J50pk400kc9/bht4dk3KSb6ZYmWIyQCK54JTebqXQZFpfkgkt0IRQN4bIXL8voWvrnNLZoLHZ27MT/W/3/TI81Y1jWNK/BmuY1GV07GfSi2z/t/BP+tPNPGZ3HTBd1sPdg1u9U7HwEaO/zi/texIv7Xkz4t1YZlq5gV9rtzdRg2dS6Ka1ruEQXNn1lk6Vr2AlLBkt7eztkWUZVVZXh86qqKuzatcv0b1paWkyPb2lpYd/TzxIdE4v7778fP/jBD6w0PWPoF5l04XP48OUZXwYAjPGMweLaxdjUOnwPORGqfFWYXTGb/V5TWIN5lfOwo2NH2ueoK6zDjDEzDJ8VOAtw1tizsP7oelvaObN8Jqp91YbPJvon4oSyE/Bp96e2XGNpw1KDEbCodhH++vFf0R3qjju2pqAGs8pnWb6GIAi4cOKFWH1gdVZtvWDiBXGfLa5djOqCakYNZ4ICZwFOrzvd8NmKCSvw3J7nLJ3HLblxXsN5KY+bUDIBJ445EXu79mJx7WKDLufk6pNRU1CTVfbedOEUnTi34VzDZ0vHL0VnoBNzK+fGHX/+xPPxz/3/zElbHKIjri1LGpZga/tWeCQPTqs9zfDdRZMuwsufvpzRtURBNLxLl0y6BPu795u6eT5T/xmDsXRKzSmo8lVlVXAzEWaMmYHawlqcNfYsvNb0Wsbu9IbiBkwpncJ+n1Y6DVNKp6C5pzmr9omCiOXjl8d9vqh2EZ7Z80zSEOECZwE+M+4zaV2nvqgesytmY3fn7rSOn1U+C3WFdWkdSzG3ci4aihvQ0m++1sYiltkdagjEgsjgyJEjqKurw3vvvYdFixaxz7/zne9g3bp12LBhQ9zfuFwuPPHEE7jyyivZZ7/5zW/wgx/8AK2trXjvvfdw2mmn4ciRI6ipqWHHfPGLX4QgCHj66afjzmnGsNTX16O7uxvFxamLSnFwcHBwcHAMP3p6elBSUpLW+m1JdFteXg5JktDa2mr4vLW1FdXV1aZ/U11dnfR4+r+Vc7rdbhQXFxv+cXBwcHBwcIxeWDJYXC4X5s+fjzVrNJ9lNBrFmjVrDIyLHosWLTIcDwCrV69mx0+YMAHV1dWGY3p6erBhw4aE5+Tg4ODg4OD494LlKKFbb70VV199NRYsWIBTTjkFP//5z9Hf38+ihr761a+irq4O999/PwDg29/+Ns466yz87//+Ly644AI89dRT2LhxI377298CUPz6t9xyC3784x9jypQpmDBhAr7//e+jtrYWl156qX095eDg4ODg4BixsGywXH755Th27BjuuecetLS0YO7cuVi1ahUTzTY3NxsU1IsXL8Zf//pXfO9738Pdd9+NKVOmYOXKlZg5cyY75jvf+Q76+/tx/fXXo6urC6effjpWrVoFj8djQxc5ODg4ODg4RjosiW7zFVZEOxwcHBwcHBz5gZyJbjk4ODg4ODg4hgPcYOHg4ODg4ODIe3CDhYODg4ODgyPvwQ0WDg4ODg4OjrwHN1g4ODg4ODg48h7cYOHg4ODg4ODIe3CDhYODg4ODgyPvwQ0WDg4ODg4OjrwHN1g4ODg4ODg48h6WU/PnI2iy3p6enmFuCQcHBwcHB0e6oOt2Okn3R4XB0tvbCwCor68fYV7x1gAADMJJREFU5pZwcHBwcHBwWEVvby9KSkqSHjMqaglFo1EcOXIERUVFEATB1nP39PSgvr4eBw8eHLV1ikZ7H0d7/4DR38fR3j9g9PdxtPcPGP19zEX/CCHo7e1FbW2toXCyGUYFwyKKIsaOHZvTaxQXF4/KF1CP0d7H0d4/YPT3cbT3Dxj9fRzt/QNGfx/t7l8qZoWCi245ODg4ODg48h7cYOHg4ODg4ODIe3CDJQXcbjfuvfdeuN3u4W5KzjDa+zja+weM/j6O9v4Bo7+Po71/wOjv43D3b1SIbjk4ODg4ODhGNzjDwsHBwcHBwZH34AYLBwcHBwcHR96DGywcHBwcHBwceQ9usHBwcHBwcHDkPbjBkgIPP/wwxo8fD4/Hg4ULF+L9998f7iZlhPvuuw+CIBj+TZ8+nX0fCARw0003YcyYMSgsLMRll12G1tbWYWxxcrz11lu46KKLUFtbC0EQsHLlSsP3hBDcc889qKmpgdfrxZIlS/DJJ58Yjuns7MRVV12F4uJi+P1+fP3rX0dfX98Q9iI5UvXxmmuuiXumy5cvNxyTz328//77cfLJJ6OoqAiVlZW49NJLsXv3bsMx6byXzc3NuOCCC+Dz+VBZWYk77rgDkUhkKLtiinT6d/bZZ8c9wxtuuMFwTL72DwAeeeQRzJ49myUSW7RoEV577TX2/Uh+fkDq/o3052eGBx54AIIg4JZbbmGf5c1zJBwJ8dRTTxGXy0Uee+wxsmPHDnLdddcRv99PWltbh7tplnHvvfeSE088kRw9epT9O3bsGPv+hhtuIPX19WTNmjVk48aN5NRTTyWLFy8exhYnx6uvvkr+67/+izz//PMEAHnhhRcM3z/wwAOkpKSErFy5knz00Ufk4osvJhMmTCCDg4PsmOXLl5M5c+aQ9evXk7fffptMnjyZXHnllUPck8RI1cerr76aLF++3PBMOzs7Dcfkcx+XLVtG/vjHP5Lt27eTLVu2kPPPP5+MGzeO9PX1sWNSvZeRSITMnDmTLFmyhGzevJm8+uqrpLy8nNx1113D0SUD0unfWWedRa677jrDM+zu7mbf53P/CCHkxRdfJK+88grZs2cP2b17N7n77ruJ0+kk27dvJ4SM7OdHSOr+jfTnF4v333+fjB8/nsyePZt8+9vfZp/ny3PkBksSnHLKKeSmm25iv8uyTGpra8n9998/jK3KDPfeey+ZM2eO6XddXV3E6XSSZ599ln328ccfEwCksbFxiFqYOWIX82g0Sqqrq8n//M//sM+6urqI2+0mf/vb3wghhOzcuZMAIB988AE75rXXXiOCIJDDhw8PWdvTRSKD5ZJLLkn4NyOtj21tbQQAWbduHSEkvffy1VdfJaIokpaWFnbMI488QoqLi0kwGBzaDqRAbP8IURY8/cIQi5HUP4rS0lLy+9//ftQ9PwraP0JG1/Pr7e0lU6ZMIatXrzb0K5+eI3cJJUAoFMKmTZuwZMkS9pkoiliyZAkaGxuHsWWZ45NPPkFtbS0mTpyIq666Cs3NzQCATZs2IRwOG/o6ffp0jBs3bkT2tampCS0tLYb+lJSUYOHChaw/jY2N8Pv9WLBgATtmyZIlEEURGzZsGPI2Z4q1a9eisrIS06ZNw4033oiOjg723UjrY3d3NwCgrKwMQHrvZWNjI2bNmoWqqip2zLJly9DT04MdO3YMYetTI7Z/FH/5y19QXl6OmTNn4q677sLAwAD7biT1T5ZlPPXUU+jv78eiRYtG3fOL7R/FaHl+N910Ey644ALD8wLyaxyOiuKHuUB7eztkWTY8AACoqqrCrl27hqlVmWPhwoV4/PHHMW3aNBw9ehQ/+MEPcMYZZ2D79u1oaWmBy+WC3+83/E1VVRVaWlqGp8FZgLbZ7NnR71paWlBZWWn43uFwoKysbMT0efny5fjc5z6HCRMmYN++fbj77ruxYsUKNDY2QpKkEdXHaDSKW265BaeddhpmzpwJAGm9ly0tLabPmX6XLzDrHwB86UtfQkNDA2pra7F161Z897vfxe7du/H8888DGBn927ZtGxYtWoRAIIDCwkK88MILmDFjBrZs2TIqnl+i/gGj4/kBwFNPPYUPP/wQH3zwQdx3+TQOucHyb4IVK1awn2fPno2FCxeioaEBzzzzDLxe7zC2jCNTXHHFFeznWbNmYfbs2Zg0aRLWrl2Lc889dxhbZh033XQTtm/fjnfeeWe4m5ITJOrf9ddfz36eNWsWampqcO6552Lfvn2YNGnSUDczI0ybNg1btmxBd3c3nnvuOVx99dVYt27dcDfLNiTq34wZM0bF8zt48CC+/e1vY/Xq1fB4PMPdnKTgLqEEKC8vhyRJcUro1tZWVFdXD1Or7IPf78fUqVOxd+9eVFdXIxQKoaury3DMSO0rbXOyZ1ddXY22tjbD95FIBJ2dnSOyzwAwceJElJeXY+/evQBGTh9vvvlmvPzyy3jzzTcxduxY9nk672V1dbXpc6bf5QMS9c8MCxcuBADDM8z3/rlcLkyePBnz58/H/fffjzlz5uAXv/jFqHl+ifpnhpH4/DZt2oS2tjbMmzcPDocDDocD69atwy9/+Us4HA5UVVXlzXPkBksCuFwuzJ8/H2vWrGGfRaNRrFmzxuC/HKno6+vDvn37UFNTg/nz58PpdBr6unv3bjQ3N4/Ivk6YMAHV1dWG/vT09GDDhg2sP4sWLUJXVxc2bdrEjnnjjTcQjUbZpDPScOjQIXR0dKCmpgZA/veREIKbb74ZL7zwAt544w1MmDDB8H067+WiRYuwbds2g2G2evVqFBcXM9p+uJCqf2bYsmULABieYb72LxGi0SiCweCIf36JQPtnhpH4/M4991xs27YNW7ZsYf8WLFiAq666iv2cN8/RNvnuKMRTTz1F3G43efzxx8nOnTvJ9ddfT/x+v0EJPVJw2223kbVr15Kmpiby7rvvkiVLlpDy8nLS1tZGCFHC1saNG0feeOMNsnHjRrJo0SKyaNGiYW51YvT29pLNmzeTzZs3EwDkoYceIps3byYHDhwghChhzX6/n/zjH/8gW7duJZdccolpWPNJJ51ENmzYQN555x0yZcqUvAn5JSR5H3t7e8ntt99OGhsbSVNTE/nXv/5F5s2bR6ZMmUICgQA7Rz738cYbbyQlJSVk7dq1hrDQgYEBdkyq95KGUy5dupRs2bKFrFq1ilRUVORF2Giq/u3du5f88Ic/JBs3biRNTU3kH//4B5k4cSI588wz2TnyuX+EEHLnnXeSdevWkaamJrJ161Zy5513EkEQyOuvv04IGdnPj5Dk/RsNzy8RYqOf8uU5coMlBX71q1+RcePGEZfLRU455RSyfv364W5SRrj88stJTU0NcblcpK6ujlx++eVk79697PvBwUHyzW9+k5SWlhKfz0c++9nPkqNHjw5ji5PjzTffJADi/l199dWEECW0+fvf/z6pqqoibrebnHvuuWT37t2Gc3R0dJArr7ySFBYWkuLiYnLttdeS3t7eYeiNOZL1cWBggCxdupRUVFQQp9NJGhoayHXXXRdnTOdzH836BoD88Y9/ZMek817u37+frFixgni9XlJeXk5uu+02Eg6Hh7g38UjVv+bmZnLmmWeSsrIy4na7yeTJk8kdd9xhyONBSP72jxBCvva1r5GGhgbicrlIRUUFOffcc5mxQsjIfn6EJO/faHh+iRBrsOTLcxQIIcQ+voaDg4ODg4ODw35wDQsHBwcHBwdH3oMbLBwcHBwcHBx5D26wcHBwcHBwcOQ9uMHCwcHBwcHBkffgBgsHBwcHBwdH3oMbLBwcHBwcHBx5D26wcHBwcHBwcOQ9uMHCwcHBwcHBkffgBgsHB0de4+yzz8Ytt9wy3M3g4OAYZnCDhYODg4ODgyPvwVPzc3Bw5C2uueYaPPHEE4bPmpqaMH78+OFpEAcHx7CBGywcHBx5i+7ubqxYsQIzZ87ED3/4QwBARUUFJEka5pZxcHAMNRzD3QAODg6ORCgpKYHL5YLP50N1dfVwN4eDg2MYwTUsHBwcHBwcHHkPbrBwcHBwcHBw5D24wcLBwZHXcLlckGV5uJvBwcExzOAGCwcHR15j/Pjx2LBhA/bv34/29nZEo9HhbhIHB8cwgBssHBwceY3bb78dkiRhxowZqKioQHNz83A3iYODYxjAw5o5ODg4ODg48h6cYeHg4ODg4ODIe3CDhYODg4ODgyPvwQ0WDg4ODg4OjrwHN1g4ODg4ODg48h7cYOHg4ODg4ODIe3CDhYODg4ODgyPvwQ0WDg4ODg4OjrwHN1g4ODg4ODg48h7cYOHg4ODg4ODIe3CDhYODg4ODgyPvwQ0WDg4ODg4OjrwHN1g4ODg4ODg48h7/H0fWxPlguUp2AAAAAElFTkSuQmCC", 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", 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", 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eL/1/3rx58Pl8mDBhAgBg/PjxyMnJwQMPPKDYjxDLaqmXXnopVq1ahc8++yzosaamJvh8PtPHjNf3pcemTZswceJEVFVV4eOPP9Z17Zx11lkoKCjAvHnzFNvnzZuHjIwMxb1y+PBhbN68GR0dHXQbiQd64YUXFM9//vnnYbPZaPZPe3u74nmE9957D42NjUFZSgwGwBQWRhelT58+eP3113HZZZfhuOOOU1S6XblyJd555x1MnToVADB06FBcffXVePbZZ9HU1IQxY8Zg9erVePnll3HhhRcqVvJGGThwIMaOHYsRI0agoKAAa9euxbvvvosZM2bQfUaMGAEAuPXWWzF+/HhYrVZcfvnlmDhxIubOnYtzzz0Xv/3tb3Hw4EE89dRT6Nu3LzZs2BDR50Fe629/+xsuv/xy2O12TJo0KWS1UJ/Ph//85z+aj1100UXIzMw09D6feOIJnHHGGTjhhBNw/fXXo1evXti9ezetWAoIitirr76K3NxcDBw4EKtWrcIXX3yBwsJCzdf3eDw4++yzcemll2LLli14+umnccYZZ+D8888HILgF582bh6uuugonnHACLr/8chQXF6OmpgaffPIJTj/9dPz73/+O5KMM4k9/+hP+97//4bzzzqPp7e3t7fjpp5/w7rvvYvfu3YrUYCPoXRuAUKfl5Zdfxq5duxSp2Vr8+9//RlNTE1UwPvroI1pR9pZbbkFubi5aW1sxfvx4NDY24k9/+lNQkHmfPn2oSpmeno5//OMfmD59OiZPnozx48fjq6++wn/+8x/cf//9KCgoULz2Pffcg6VLl1JDZPjw4fj973+PF198ET6fD2PGjMGyZcvwzjvvYPbs2dSltG3bNowbNw6XXXYZBgwYAIvFgrVr1+I///kPqqqqFDWUGAxKEjOUGIyo2bp1K3/dddfxVVVVvMPh4LOzs/nTTz+df/LJJ3mXy0X383q9/D333MP36tWLt9vtfGVlJT979mzFPjwvpDVrpfGOGTOGHzNmDP3/vvvu408++WQ+Ly+PT09P5wcMGMDff//9ilRcn8/H33LLLXxxcTHPcZwijfWFF17g+/XrxzudTn7AgAH8Sy+9xN91111Bqa4A+OnTpwedT8+ePfmrr75ase0f//gH361bN95isYRNcQ6V1ix/rpH3yfM8//PPP/MXXXQRn5eXx6elpfHV1dX83//+d/p4Y2MjP23aNL6oqIjPysrix48fz2/evDnofZC05uXLl/PXX389n5+fz2dlZfFXXnkl39DQEPQ+li5dyo8fP57Pzc3l09LS+D59+vBTp07l165dq3ivWlV9x4wZww8aNEjzs1VfA62trfzs2bP5vn378g6Hgy8qKuJPO+00/uGHH6afBUlr/te//hV0TKhSpUNdG7/5zW/49PR0RbqxHiQNP9R3SM5L70d9HfE8zz/77LN8dXU173A4+D59+vCPPvqoIk2d53l6vS5dulSx3ePx8HfffTffs2dP3m6383379uUfffRRxT6HDh3ir7/+en7AgAF8ZmYm73A4+H79+vEzZ87kDx06FPZ9M45NOJ5PgUgwBoPBgFDpdtq0aVizZs0x6xYoLS3FlClT8K9//SvZp8JgpBQshoXBYDBShF9++QWdnZ2GmgwyGMcaLIaFwWAwUoRBgwbRwogMBkMJU1gYDAaDwWCkPCyGhcFgMBgMRsrDFBYGg8FgMBgpDzNYGAwGg8FgpDxHRdBtIBDAgQMHkJ2dnZSS1wwGg8FgMMzD8zxaW1tRUVEBiyW0hnJUGCwHDhxAZWVlsk+DwWAwGAxGBOzduxfdu3cPuc9RYbBkZ2cDEN6wuq08g8FgMBiM1KSlpQWVlZV0Hg/FUWGwEDdQTk4OM1gYDAaDwehiGAnnYEG3DAaDwWAwUh5msDAYDAaDwUh5mMHCYDAYDAYj5TkqYlgYDAaDoY/f74fX6032aTCOUex2O6xWa9THMWWwzJkzB++//z42b96M9PR0nHbaaXjwwQdRXV0d8nnvvPMO/v73v2P37t3o168fHnzwQfz617+mj/M8j7vuugvPPfccmpqacPrpp2PevHno169fZO+KwWAwGOB5HnV1dWhqakr2qTCOcfLy8lBWVhZVrTRTBsvy5csxffp0nHTSSfD5fPjrX/+KX/3qV9i4cSMyMzM1n7Ny5UpcccUVmDNnDs477zy8/vrruPDCC7Fu3ToMHjwYAPDQQw/hiSeewMsvv4xevXrh73//O8aPH4+NGzciLS0t4jfHYDAYxzLEWCkpKUFGRgYrrMlIODzPo6OjAwcPHgQAlJeXR3ysqJofHjp0CCUlJVi+fDlGjx6tuc9ll12G9vZ2fPzxx3TbqaeeimHDhmH+/PngeR4VFRW47bbbcPvttwMAmpubUVpaigULFuDyyy8Pex4tLS3Izc1Fc3MzS2tmMBgMCG6grVu3oqSkBIWFhck+HcYxTkNDAw4ePIj+/fsr3ENm5u+ogm6bm5sBAAUFBbr7rFq1CuPGjVNsGz9+PFatWgUA2LVrF+rq6hT75Obm4pRTTqH7qHG73WhpaVH8MBgMBkOCxKxkZGQk+UwYDOk6jCaWKmKDJRAIYObMmTj99NOpa0eLuro6lJaWKraVlpairq6OPk626e2jZs6cOcjNzaU/rCw/g8FgaMPcQIxUIBbXYcQGy/Tp0/Hzzz/jzTffjPokzDJ79mw0NzfTn7179yb8HBgMBoPBYCSOiAyWGTNm4OOPP8bSpUvDNisqKytDfX29Ylt9fT3Kysro42Sb3j5qnE4nLcPPyvEzGAzG0cXYsWMxc+ZM3cerqqrw2GOPJex8GKmBKYOF53nMmDED//3vf/Hll1+iV69eYZ8zcuRILFmyRLFt8eLFGDlyJACgV69eKCsrU+zT0tKC7777ju7DYDAYDAZhzZo1uP7665N9GowEYyqtefr06Xj99dfx4YcfIjs7m8aY5ObmIj09HQAwZcoUdOvWDXPmzAEA/OEPf8CYMWPwyCOPYOLEiXjzzTexdu1aPPvsswAEv9bMmTNx3333oV+/fjStuaKiAhdeeGEM3yqDkRh8/gBsVlZEmsGIF8XFxck+BUYSMDWqzps3D83NzRg7dizKy8vpz1tvvUX3qampQW1tLf3/tNNOw+uvv45nn30WQ4cOxbvvvosPPvhAEah7xx134JZbbsH111+Pk046CW1tbVi0aBGrwcLoctz0n+9x2j+/xKFWd7JPhcHo0vh8PsyYMQO5ubkoKirC3//+d5AqHGqXUE1NDS644AJkZWUhJycHl156qSLM4O6778awYcPw4osvokePHsjKysLNN98Mv9+Phx56CGVlZSgpKcH999+vOIe5c+fi+OOPR2ZmJiorK3HzzTejra2NPr5nzx5MmjQJ+fn5yMzMxKBBg7Bw4UIAQGNjI6688koUFxcjPT0d/fr1w0svvRTHT+zox5TCYqRky7Jly4K2TZ48GZMnT9Z9DsdxuPfee3HvvfeaOR0GI+X49GdBdXxm+Q7833kDk3w2DIYSnufR6fUn/HXT7VbTWSIvv/wyrrnmGqxevRpr167F9ddfjx49euC6665T7BcIBKixsnz5cvh8PkyfPh2XXXaZYj7asWMHPv30UyxatAg7duzAJZdcgp07d6J///5Yvnw5Vq5cid///vcYN24cTjnlFACAxWLBE088gV69emHnzp24+eabcccdd+Dpp58GIHgdPB4PVqxYgczMTGzcuBFZWVkAgL///e/YuHEjPv30UxQVFWH79u3o7OyM4lNksF5CDEaMCAQkg35dTWMSz4TB0KbT68fAOz9L+OtuvHc8MhzmppvKyko8+uij4DgO1dXV+Omnn/Doo48GGSxLlizBTz/9hF27dtESF6+88goGDRqENWvW4KSTTgIgGDYvvvgisrOzMXDgQJx55pnYsmULFi5cCIvFgurqajz44INYunQpNVjkgb9VVVW47777cOONN1KDpaamBr/5zW9w/PHHAwB69+5N96+pqcHw4cNx4okn0uczooM52hmMGNHm8dG/f9rfDI8vkMSzYTC6NqeeeqpClRk5ciS2bdsGv1+pEG3atAmVlZWKelwDBw5EXl4eNm3aRLdVVVUhOzub/l9aWoqBAwfCYrEotpES8gDwxRdf4Oyzz0a3bt2QnZ2Nq666Cg0NDejo6AAA3Hrrrbjvvvtw+umn46677sKGDRvoc2+66Sa8+eabGDZsGO644w6sXLkyBp/KsQ1TWBiMGNHSKVVw9Pp5/FDTiFN6s5LojNQh3W7FxnvHJ+V1k43dblf8z3Gc5rZAQFho7N69G+eddx5uuukm3H///SgoKMDXX3+Na665Bh6PBxkZGbj22msxfvx4fPLJJ/j8888xZ84cPPLII7jlllswYcIE7NmzBwsXLsTixYtx9tlnY/r06Xj44YcT9p6PNpjCwmDEiJZOn+L/ehZ4y0gxOI5DhsOW8J9Iqpx+9913iv+//fZb9OvXT9GHBgCOO+447N27V1FAdOPGjWhqasLAgZHHkX3//fcIBAJ45JFHcOqpp6J///44cOBA0H6VlZW48cYb8f777+O2227Dc889Rx8rLi7G1Vdfjf/85z947LHHaHYsIzKYwsJgxIgWl7JHhisJwY0MxtFCTU0NZs2ahRtuuAHr1q3Dk08+iUceeSRov3HjxuH444/HlVdeicceeww+nw8333wzxowZQ+NHIqFv377wer148sknMWnSJHzzzTeYP3++Yp+ZM2diwoQJ6N+/PxobG7F06VIcd9xxAIA777wTI0aMwKBBg+B2u/Hxxx/TxxiRwRQWBiNGyF1CAOBmBguDETFTpkxBZ2cnTj75ZEyfPh1/+MMfNIvFcRyHDz/8EPn5+Rg9ejTGjRuH3r17K8ptRMLQoUMxd+5cPPjggxg8eDBee+01Wl+M4Pf7MX36dBx33HE499xz0b9/fxqQ63A4MHv2bAwZMgSjR4+G1WpNSiubowmON5KrnOKYaU/NYMSLd7/fh9vf+ZH+/7dfH4frRvcO8QwGI364XC7s2rULvXr1YjWtGElH73o0M38zhYXBiBFqhcXl9aPF5cWdH/6M7/ccSdJZMRgMxtEBM1gYjBjRrDZYfH489eV2vLJqD34zb1WSzorBYDCODljQLYMRI4KDbgPYe6QjSWfDYDAYRxdMYWEwYgRJa3bahNvK5fUjJ12q8+D1s0JyDAaDESnMYGEwYgRRWEpzhIAylzcAu6xr84Em1keEwWAwIoUZLAxGjCBBtyXZTgBCDIvcTbT3CDNYGAwGI1JYDAuDESNaXIJLqCRHMFjcXj/csn5CNSyehcFgMCKGGSwMRoyQFBbJJSTPHGIGC4PBYEQOcwkxGDGCuH+IwuLy+hUGC8sYYjAYjMhhBguDEQP8AR5tbtElRBQWnx9NHR66D1NYGAwGI3KYwcJgxIAdh9rA80CGw4qKXMFg6fD40eqWOjirC8sxGIxjF47j8MEHHyT7NLoUzGBhMGLAhn3NAIDBFblId1gBAIda3ZB36upkzRAZDAYjYpjBwmDEgJ/2NQEAhnTPRZpdMFhaXT7FPi4PM1gYDCOMHTsWt9xyC2bOnIn8/HyUlpbiueeeQ3t7O6ZNm4bs7Gz07dsXn376KX3Ozz//jAkTJiArKwulpaW46qqrcPjwYfr4okWLcMYZZyAvLw+FhYU477zzsGPHDvr47t27wXEc3n//fZx55pnIyMjA0KFDsWpV+LYaPM+juLgY7777Lt02bNgwlJeX0/+//vprOJ1OdHR0oKqqCgBw0UUXgeM4+j8jNMxgYTBiwI+iwnK8zGAhWC0cAKDD68dR0Byd0ZXhecDTnvifCK77l19+GUVFRVi9ejVuueUW3HTTTZg8eTJOO+00rFu3Dr/61a9w1VVXoaOjA01NTTjrrLMwfPhwrF27FosWLUJ9fT0uvfRSerz29nbMmjULa9euxZIlS2CxWHDRRRchEFBWoP7b3/6G22+/HevXr0f//v1xxRVXwOfzqU9PAcdxGD16NJYtWwYAaGxsxKZNm9DZ2YnNmzcDAJYvX46TTjoJGRkZWLNmDQDgpZdeQm1tLf2fERqW1sxgRInXH8DG2hYAwJDueUizK9cBZTlp2N/UCX+Ah9fPw2HjknGaDAbg7QAeqEj86/71AODINPWUoUOH4v/+7/8AALNnz8Y///lPFBUV4brrrgMA3HnnnZg3bx42bNiAL774AsOHD8cDDzxAn//iiy+isrISW7duRf/+/fGb3/xGcfwXX3wRxcXF2LhxIwYPHky333777Zg4cSIA4J577sGgQYOwfft2DBgwIOT5jh07Fs888wwAYMWKFRg+fDjKysqwbNkyDBgwAMuWLcOYMWMAAMXFxQCAvLw8lJWVmfpcjmWYwsJgRMneIx3w+AJIt1vRsyADaTalwlImBuECLI6FwTDKkCFD6N9WqxWFhYU4/vjj6bbS0lIAwMGDB/Hjjz9i6dKlyMrKoj/EwCBun23btuGKK65A7969kZOTQ90wNTU1uq9LXDoHDx4Me75jxozBxo0bcejQISxfvhxjx47F2LFjsWzZMni9XqxcuRJjx441/0EwKExhYTCixOUVJOVMpw0WCxfkEirKcsBm4eAL8HB5/ciVNURkMBKKPUNQO5LxumafYlfeJxzHKbZxnKBUBgIBtLW1YdKkSXjwwQeDjkOMjkmTJqFnz5547rnnUFFRgUAggMGDB8Pj8Sj213uNcBx//PEoKCjA8uXLsXz5ctx///0oKyvDgw8+iDVr1sDr9eK0004z+O4ZWjCDhcGIEo/YhZl0aSa/CbnpdqTbrWh1+9DJAm8ZyYTjTLtmugInnHAC3nvvPVRVVcFmC57WGhoasGXLFjz33HMYNWoUACEINpZwHIdRo0bhww8/xC+//IIzzjgDGRkZcLvdeOaZZ3DiiSciM1P67O12O/x+Nh6YgbmEGIwo8YoGi0M0VCwWjv4NAMXZTqSJqc4dzGBhMGLO9OnTceTIEVxxxRVYs2YNduzYgc8++wzTpk2D3+9Hfn4+CgsL8eyzz2L79u348ssvMWvWrJifx9ixY/HGG29g2LBhyMrKgsViwejRo/Haa6/R+BVCVVUVlixZgrq6OjQ2Nsb8XI5GmMHCYESJR2xw6LBKt1OazGApz01HuugmYjEsDEbsqaiowDfffAO/349f/epXOP744zFz5kzk5eXBYrHAYrHgzTffxPfff4/Bgwfjj3/8I/71r3/F/DzGjBkDv9+viFUZO3Zs0DYAeOSRR7B48WJUVlZi+PDhMT+XoxHmEmIwooQYLHZZ9k+a3Uq7N1fkpVGDxcUMFgYjLCQ9WM7u3buDtsnLBPTr1w/vv/++7jHHjRuHjRs36j6/qqoqqOxAXl6eqVIEw4YNC9p/5syZmDlzZtC+kyZNwqRJkwwfm8EUFgYjakgMi0JhkQXeluemU5cQi2FhMBiMyGAGC4MRJdQlJHMDcbJSKxW56chgLiEGo0tDquhq/cjrvzDiB3MJMRhRQl1CMoWlsV1KlcxJt9H+QkxhYTC6Js8//zw6Ozs1HysoKEjw2RybMIOFwYgSdVozABq/AgjpjizolsHo2nTr1i3Zp3DMY9oltGLFCkyaNAkVFRWG2mNPnToVHMcF/QwaNIjuc/fddwc9Hq4MMoORKqjTmrVIYwYLg8FgRIVpg6W9vR1Dhw7FU089ZWj/xx9/HLW1tfRn7969KCgowOTJkxX7DRo0SLFfrIv6MBjxQsslpCbdITzGXEIMBoMRGaZdQhMmTMCECRMM75+bm4vc3Fz6/wcffIDGxkZMmzZNeSI2G2sCxeiSuDXqsBAqC9IBABkO4VZjac0MBoMRGQnPEnrhhRcwbtw49OzZU7F927ZtqKioQO/evXHllVcGNaSS43a70dLSovhhMJKFlkto/u9GoF9JFub/bgQA5hJiMBiMaEmowXLgwAF8+umnuPbaaxXbTznlFCxYsACLFi3CvHnzsGvXLowaNQqtra2ax5kzZw5VbnJzc1FZWZmI02cwNNFyCZ07uAyLZ43BoApBXSRBt6w0P4PBYERGQg2Wl19+GXl5ebjwwgsV2ydMmIDJkydjyJAhGD9+PBYuXIimpia8/fbbmseZPXs2mpub6c/evXsTcPYMhjbEYFE3PZSTbhdjWJjCwmCEhed5XH/99SgoKADHccjLy9OsFqvF2LFjw+5rJGEkltx9990YNmxYwl4vGhL92ZghYWnNPM/jxRdfxFVXXQWHwxFy37y8PPTv3x/bt2/XfNzpdMLpdMbjNBkM0xjJEiJ1WFxMYWEwwrJo0SIsWLAAy5YtQ+/evWGxWJCenh6z49fW1iI/Pz9mxwvH7bffjltuucXUc6qqqnTL+scT+Weze/du9OrVCz/88ENKGFwJM1iWL1+O7du345prrgm7b1tbG3bs2IGrrroqAWfGYESHVml+NSyGhcEwzo4dO1BeXo7TTjstLsdPdIIHqYjbFUjl5BfTLqG2tjasX78e69evBwDs2rUL69evp0Gys2fPxpQpU4Ke98ILL+CUU07B4MGDgx67/fbbsXz5cuzevRsrV67ERRddBKvViiuuuMLs6TEYCcdNmx/q304kS4gZLAxGaKZOnYpbbrkFNTU14DgOVVVVQW6ep59+Gv369UNaWhpKS0txySWXKI4RCARwxx13oKCgAGVlZbj77rsVj8vdHrt37wbHcXj//fdx5plnIiMjA0OHDsWqVasUz3nuuedQWVmJjIwMXHTRRZg7dy7y8vIMvSe1S2jq1Km48MIL8fDDD6O8vByFhYWYPn06vF4vAMGttWfPHvzxj3+ktckIX3/9NUaNGoX09HRUVlbi1ltvRXt7O328qqoKDzzwAH7/+98jOzsbPXr0wLPPPksf93g8mDFjBsrLy5GWloaePXtizpw5mp9Nr169AADDhw8Hx3EYO3YsVqxYAbvdjrq6OsV7nDlzJkaNGmXo84gU0wbL2rVrMXz4cNoOe9asWRg+fDjuvPNOAIKcpM7waW5uxnvvvaerruzbtw9XXHEFqqurcemll6KwsBDffvstiouLzZ4eg5FwvH6hO2sohYVWumUuIUYS4XkeHd6OhP+Y6Xj8+OOP495770X37t1RW1uLNWvWKB5fu3Ytbr31Vtx7773YsmULFi1ahNGjRyv2efnll5GZmYnvvvsODz30EO69914sXrw45Ov+7W9/w+23347169ejf//+uOKKK+DzCRWrv/nmG9x44434wx/+gPXr1+Occ87B/fffb/g9abF06VLs2LEDS5cuxcsvv4wFCxZgwYIFAIDX33oHpeUV+ONf/o/WJgME5encc8/Fb37zG2zYsAFvvfUWvv76a8yYMUNx7EceeQQnnngifvjhB9x888246aabsGXLFgDAE088gf/97394++23sWXLFrz22muoqqrSPMfVq1cDAL744gvU1tbi/fffx+jRo9G7d2+8+uqrdD+v14vXXnsNv//976P6TMJh2iU0duzYkBcf+cDl5ObmoqOjQ/c5b775ptnTYDBSBo9PMEJCx7CwoFtG8un0deKU109J+Ot+99vvkGHPMLRvbm4usrOzYbVaNd0TNTU1yMzMxHnnnYfs7Gz07NmTLqAJQ4YMwV133QUA6NevH/79739jyZIlOOecc3Rf9/bbb8fEiRMBAPfccw8GDRqE7du3Y8CAAXjyyScxYcIE3H777QCA/v37Y+XKlfj4448NvSct8vPz8e9//xtWqxUDBgzAxIkTsWTJElx33XXgnFmwWq2wOTMUn8GcOXNw5ZVXUrWpX79+eOKJJzBmzBjMmzcPaWlpAIBf//rXuPnmmwEAf/7zn/Hoo49i6dKlqK6uRk1NDfr164czzjgDHMcFlRiRQ0SDwsJCxXlcc801eOmll/CnP/0JAPDRRx/B5XLh0ksvjfjzMALr1sxgRIknROE4QhpTWBiMmHDOOeegZ8+e6N27N6666iq89tprQQviIUOGKP4vLy/HwYMHQx5X/pzy8nIAoM/ZsmULTj75ZMX+6v/NMmjQIFitVu1z5LSf8+OPP2LBggWKTtHjx49HIBDArl27NN8Lx3EoKyujx546dSrWr1+P6upq3Hrrrfj8889Nn/vUqVOxfft2fPvttwAEoeLSSy9FZmam6WOZgTU/ZDCihLqEQqY1s6BbRvJJt6Xju99+l5TXjRXZ2dlYt24dli1bhs8//xx33nkn7r77bqxZs4bGlNjtdsVzOI5DIBAIeVz5c0jMSLjnREOoc5THrMhpa2vDDTfcgFtvvTXosR49ehg69gknnIBdu3bh008/xRdffIFLL70U48aNw7vvvmv43EtKSjBp0iS89NJL6NWrFz799FMsW7bM8PMjhRksDEaUUIXFQPNDVpqfkUw4jjPsmkllbDYbxo0bh3HjxuGuu+5CXl4evvzyS1x88cVxeb3q6uqgWBr1/7HEAsBmd8DvV44XJ5xwAjZu3Ii+fftGdfycnBxcdtlluOyyy3DJJZfg3HPPxZEjR1BQUKDYj5QgUZ8HAFx77bW44oor0L17d/Tp0wenn356VOdkBGawMBhR4vaHb35IjBmvnwfP87orKAaDEZqPP/4YO3fuxOjRo5Gfn4+FCxciEAiguro6bq95yy23YPTo0Zg7dy4mTZqEL7/8Ep9++mnc7mOOAyq698C671Zi//79cDqdKCoqwp///GeceuqpmDFjBq699lpkZmZi48aNWLx4Mf79738bOvbcuXNRXl6O4cOHw2Kx4J133kFZWZlmxlNJSQnS09OxaNEidO/eHWlpabQ34Pjx45GTk4P77rsP9957byzfvi4shoXBiBKvAYVF/hhxITEYDPPk5eXh/fffx1lnnYXjjjsO8+fPxxtvvIFBgwbF7TVPP/10zJ8/H3PnzsXQoUOxaNEi/PGPf6RBrrGHw/TbZ+PAvhr06dOHBr8OGTIEy5cvx9atWzFq1CiaoVtRUWH4yNnZ2XjooYdw4okn4qSTTsLu3buxcOFCWCzB45fNZsMTTzyBZ555BhUVFbjgggvoYxaLBVOnToXf79csZRIPON5MvlmK0tLSgtzcXDQ3NyMnJyfZp8M4xhg3dzm2H2zDG9edipF9CjX3cXn9GPD3RQCAn+8ZjywnEzcZ8cXlcmHXrl3o1atXHCfWY5frrrsOmzdvxldffRXzYze0ubG/qRMAMKgiF1ZLaiqy11xzDQ4dOoT//e9/YffVux7NzN9s1GQwosRIDIvcXeT1BQDWWYLB6FI8/PDDOOecc5CZmYlPP/0UL7/8Mp5++um4v26A52HVSxtKEs3Nzfjpp5/w+uuvGzJWYgUzWBiMKPEaKM1vtXCwWjj4Azzdn8FgdB1Wr16Nhx56CK2trejduzeeeOIJXHvttQCEFOU9e/ZoPu+ZZ57BlVdeGfHrpqIT5IILLsDq1atx4403hqxtE2uYwcJgRIkRhQUA7FbBYCGl/BkMRtfh7bff1n1s4cKFtKy+mtLSUtOvJTdRAqlnryQkhVkLZrAwGFFi3GCxwOUNMIWFwTjKCFUtNhLkokogBRWWZMGyhBiMKPHQtObQfmbiMmJZQgwGIzTSGMHsFQlmsDAYUcDzPDVYwiksUi0WprAwEkc8q7Uy4oPSJXR0WCyxuA6ZS4jBiAJfgKcrIKesL4gWJFOIxbAwEoHD4YDFYsGBAwdQXFwMh8PBChbGCbfXj6YOLwqyHCELSBrF43aD93kAAC6XFXZ03QrZPM/D4/Hg0KFDsFgstHpuJDCDhcGIAo/M+LDbQk8GxGXEFJauic8fwO9fXovSbCf+NXlosk8nLBaLBb169UJtbS0OHDiQ7NM5qjnQ1IkADzhtFhRnR1+zoKXTixaXDwDga7Yjw9H1p+qMjAz06NFDs0CdUbr+p8BgJBG58REqrRkAHDZr0HMYXYdvdx7Biq2HAAAPXTKkS6gVDocDPXr0gM/n0+wHw4gN1z6yDIBQvuDzP46J+ngvfr0Lr30nGJm3/ao/fl1tvJJtKmK1WmGz2aK+Z5jBwmBEAVFYLBxgC2ewiAqLh7mEuiQ7DrXRv92+AG1omepwHAe73R7UwZcRO/a3SsZgLKoKt3g5esxWr4VVKhZhQbcMRhS4DaY0A1IMC1NYuiZ7Gjro324v+w4Z8UMeaNvJOrxTmMHCYESB10CnZgIxajwsrblLIldY2CTCiCc+2RjhYtcahRksDEYUkJRmpwmFhbmEuiZb6lrp32wSYcQTvywFmBnHEsxgYTCigFa5NaCwMJdQ16W5w4u6Fhf93+VjkwhDwsiCxQw+WT1+5n6UYAYLgxEF1CVkYMByssJxXZYdh9sU/7vYJMKQkemMbf6KX2awdHqYcUxgBguDEQVuUwoLyxLqqrS7fYr/mUuIISfDEduMMbnCwlxCEsxgYTCigPQFMhJ0S2NYmMLS5VCvctkkwpCTKSvs5ovB/R0IsKBbLZjBwmBEgc9g40NAcht5fSxLqKuhNlDcbBJhyEiXKSxtKjUuEpjCog0zWBiMKCADi9US3mBxsKDbLot6lctiWBhy5Ld/S2f0BoufBd1qwgwWBiMKyMBiM9AfQ6rDwgagrobaJcRkeoYcuYHR4vJGfTwfS2vWhBksDEYU+E0oLCzotuvSqVrlskmEIccvq0zb6oqtwsKMYwlmsDAYUUAVFgMxLA4ra37YVen0qLOE2HfIkJBXpo2NwsJiWLRgBguDEQVmYljsNqawdFXUkwZb9TLkBOKqsLDxgsAMFgYjCkgJbRsLuj2qCTJYWKVbhgy5ItIaA4WFuYS0YQYLgxEFprKEaKVbltbc1ej0KNPXWeYGQ468bkossoQUpfmZcUxhBguDEQVmsoRI4Tg3cwl1OcgqNz/DAYCVS2coiafC4vXziv9jSVczhkwbLCtWrMCkSZNQUVEBjuPwwQcfhNx/2bJl4Dgu6Keurk6x31NPPYWqqiqkpaXhlFNOwerVq82eGoORcEiwnbEsIeYS6qp0qgwW5hJiyJErLLEuHAfEx7BYu/sIqv9vEf795baYHztemDZY2tvbMXToUDz11FOmnrdlyxbU1tbSn5KSEvrYW2+9hVmzZuGuu+7CunXrMHToUIwfPx4HDx40e3oMRkIxk9bsYM0PuyxEUcnLsANgcQUMJb4Yx5z4A8oxIh6Bt//3wc8AgIc/3xrzY8cL0y0mJ0yYgAkTJph+oZKSEuTl5Wk+NnfuXFx33XWYNm0aAGD+/Pn45JNP8OKLL+Ivf/mL6ddiMBKFuUq3LEuoqxKksLAYFoYMeZZQLK4NnyrOLR4GspH+Z6lGws542LBhKC8vxznnnINvvvmGbvd4PPj+++8xbtw46aQsFowbNw6rVq3SPJbb7UZLS4vih8FIBmSgMpIlxFxCXRcaw5IpxrAwhYUhQ5HVEwP3jdwAAuIT92ak/1mqEXeDpby8HPPnz8d7772H9957D5WVlRg7dizWrVsHADh8+DD8fj9KS0sVzystLQ2KcyHMmTMHubm59KeysjLeb4PB0CSSGBYPyxLqckgKi+ASYs0PGXJi7RJSx7AwhUXAtEvILNXV1aiurqb/n3baadixYwceffRRvPrqqxEdc/bs2Zg1axb9v6WlhRktjKRgqg4L6SXEAja7HCSGhbmEGFoEYlzoTZ0VFA+FhYxHXYm4GyxanHzyyfj6668BAEVFRbBaraivr1fsU19fj7KyMs3nO51OOJ3OuJ8ngxEOKYbFeFozq8PS9SAKCw26ZUYnQ0bMFRYWw6JJUs54/fr1KC8vBwA4HA6MGDECS5YsoY8HAgEsWbIEI0eOTMbpMRiGMddLiMWwdFXIhFGQ6VD8z2AA6qDbWGQJJcJgkcYsnu8aiyjTCktbWxu2b99O/9+1axfWr1+PgoIC9OjRA7Nnz8b+/fvxyiuvAAAee+wx9OrVC4MGDYLL5cLzzz+PL7/8Ep9//jk9xqxZs3D11VfjxBNPxMknn4zHHnsM7e3tNGuIwUhVIqt0ywyWroTXH6CqWB4rHMfQwBdjlxA5XqbDinaPP04uISv92+UNIN1hDbF3amDaYFm7di3OPPNM+j+JJbn66quxYMEC1NbWoqamhj7u8Xhw2223Yf/+/cjIyMCQIUPwxRdfKI5x2WWX4dChQ7jzzjtRV1eHYcOGYdGiRUGBuAyGnLfX7kWvokycVFWQtHOQKt0aCboVy7qztOYuhXx1m09dQuw7ZAgEAjzkAkUs3IUkNi7DaUO7xx8XhUU+ZrV7fEenwTJ27NiQ8tGCBQsU/99xxx244447wh53xowZmDFjhtnTYRyjrN51BHe8uwEAsPufE5N2Hj5xYLFwLK35aIXEr3AckJsuGCweXwCBAA+LAUOVcXTj52PvviELoSynDYda3XHpXSVXhdrdPhRlpX5caNeLumEwAGw80JzsUwBgTmFxsuaHXRKX2Pgw3W5VrEKTqZT5Azz++t+f8K/PNiftHBgCwfEmgahjQsgxM8TrLR6l+b2y67fd3TVcnMxgYXRJOmSrmECcGoMZgZbmNxB0SxQWfyB+zcyOBgIBHtvqW5P6vcohCku63Yo0md8/mcXj/vPtHrz+XQ2eWrqDBQAnGa17OVpjlsawOAUnSDzS6OVKb7sn+v5HiYAZLIwuSYdsRZDMicNnJoZFVveAuYX0+ffS7Tjn0RV48ZtdyT4VANL1lWa3wmLhaPB0sq67To8fT34pJT60xKA7MCNy1C4hIHq3kF8WdAvER2HxyA2WGDRsTATMYGF0SeQdUZN5s/lN1GFxyOoeeJjBosvcxUIztvs+2ZTkMxEgGUHEHUQmkY4kXXeb6lpwuM1N/291dY3J5mhFSwmMRhHheT4hCou8p1lHF8l6YwYLo0tySDZgtyfxZjOlsMjcRsd6A8TNdS246T/fY+FPtYrt8pVp/9KsRJ+WJi6ZSwiQJpFkXXeN7R7F/8xgSS7y4FVizEajsMjtn0wHMVjiEMMiWzS1dRGFJSmVbhmMaDnUKjNYkqmwmOglxHGCO8HjCxzTcQeb61pw7mNfAQD2N3Xi18eX08fW7WmkfxdmpkbWQqfaYBEnkURed/4AT6+xxg6lC6ilk7mEkglRWCycoMK1e/xRpTbLY2IynMQlFI8YFul1kqUWmoUpLIwuyeEUMVjMKCyAtAI7lguPfbn5IP275kiH4rFVOxvo380pMhGT78ppF4bLTHESSdSq9Kml2zH0ns+xpa4VANDUwRSWVEIaAyxw2ojCErmBITdYspzxU1jkKm8yVWozMIOF0SVRKCxJjHAnBZ6MKCwAkOFIrjshFQhliGytbzW0XyIhq9s0lUuoI0HX3b8+24I2tw93fvgzAKBJpbC0sqDbpEIMDIsFSBON2mgWJKS2EyBda/FRWFjQLYMRd1xeP1oVQbfJj2ExarCQ1XlXkWDjQUunT/a3VxG0KDdSUsdgkbKEAMkl1Jbg6464phpVCgvLEkoufpnCQq6RWLmEYhETowfLEmIwEoBcXQFSJUuIKSxGkU+wAR5okykVzTJjps3tgy8FsqmIvE8K/9Gg2wRfd2TVHqywdI3J5miFpDVbOMmodUdhYMiDeMl4EY9WEMwlxGAkAHmGEJAqWULGbiWqsHSRQk3xQB0kKv+/OUg9SP7nRBQWyWBJjkqmVli656cDYAZLspE6tluoSygWMSxWCxcTA0gP5hJiMBJAQ5tyUkvmzRaIVGHpIqWw44HaYAnlBlIHmCYDEj9AAiqJwpJol5CLGizCZ9SjIAMAyxJKNjSGheNoJlk0Lhy5m5kYyfFQWORZQkxhYTDihLqGSTKDbiPNEjqmFRaVIkCMFK8/QAdO8jmlQhyLi1a6FRWWJH2HpLgXUaGowcIUlqQi7yfmFA2WaKogB2THi6fCwmJYGIwEII+iB1IkhsVALyFAaBcPHNsKCzFCSMomCcKVKwWV4mScCgaLvsKSLJeQqLAUCp8RyxJKLgoXTgzSmn0Kl5AwRcc6S4jnecXCr62LGL3MYGF0OXyqbscdKZAlZFRhyUpwSmyqwfM8NUxIDAb5nxgn2U4b8jMcim3JxE2Cbu3JDbrleUHtIYZLZT5TWFIBn0ZaczQuIVIqwWbhZHVdYjvGyQN7ga6TacYMFkaXQ90dNZllpc3XYREGoK7SHTXWdHr9dLBUqyjkd066HbnpdsW2ZEJSVNNI0G0SM71IhpDVwqEiLw0AU1iSTYCPbVqzpLBY4qawqJuvdpU4KGawMLocXrVLKCViWAxmCR3jQbfEALFZOJTnpim2kd+56XbkZYgGS0fyB1JJYSEuIdHoTIKhfETsI5QnM+pYllBy8Qfkac2igRGNS8gvi4mJk8Li9SkXfe0ef0qUEAgHM1gYXQ4yQJDux8mc/CX/tbH9M5I42aUCJF5FrqIQOVpusKSSwqJOa85KkksIEHovAUBehh3ZacRg8YLngzsGMxKDvHBcLLKE/BoxLC6vP6bfsdsffH5dwfBlBgujy0HS8XLESS2pvYT8knxrBKKwdJV27rGGGCe56XbkpCmNkhaZwUK+26ZUMFi8ytL8iSz+p3Z/7mloBwDkZziQnSacR4DvOmmpRyNSaX4pqyeaLCFSiM4qyzoK8MFxJ9FAxlCHzULd1F0hjoUZLIwuB4kbyU1P/uTvNxl0e6zHsBAXT06aLUhF0XQJpYLBkkSFRZ3Cv62+DQBQnO1Eut1KY6dYHEvy0EprjoXCYpPVYQGiM4LUeMXrymG10IWDvGVGqsIMFkaXg6w0yISX1KBb2WrICLRx3jEaw0JWcTkyFUWdJZSbYadZQqlYOC6DViv2K/ogxQOPKq5g60GhOWRpTho4jksp19mxikJhEQ2MzhjEsJDCccT1HcvUY3Jd2a0ccsSFH1NYGIw4QG5oMlgnM0WYKSzmCJUJpKWwkCDTZKIuHEcUFgDoiENBLzl6CktpjhCwTD6nxvbUn2yOVuSlDUhcUVsUk788hoXjOMk9GsMAdHJdOWxyhSX1ryFmsDC6HGSAyBNX4V4/H5dupobOxW8urZkqLMdozAENuk3TN1hy0uUKS/IHUbXC4rRZ6Pcdb7eQOv2UqImlOU4ASCkl6liFpDVbOY4akNHEXpHCmDaxGGU83KNeqrBYJKWTKSwMRuwhRkJuuh3ETkiWJO43mdZMFZZjNUvIJcWwFGQKk21jhxeBAK9QWMhjTZ3euLtdwkENFlFh4TiOfo/xdkeqDRYCVVjEyaYxBQy7YxV5ZVpqhEfxfVCFhRMGt3i4/WjQrdWCnDRlxelUhhksjC4HTWu2WegKM1muAzpYGSzNT7KE3L5Al6h7EGtI4GCGw4b8TGEg9gd4tLi8VE3Jk7mE/AE+6emW1CUkKiyArGJxnGOR1C4hAlFYiMrY1MkUlmQhb4AqV0MiTUOWG0CA3GCJ3XdMriumsDAYccbrDx4gGpMkiZuOYXFKk1684x9SEXmZe6fNimxx4m9o9+Cw2IW7KMsJp81Kmwwm67slqBUWQDJY4p2dow66JRCFJT8j9vENDHPIDYy8dAfdFmmqeUCl2ubFRWFhMSwMRkIgac12Cye5FZIQdMjzfNBqKBwOq4UaN8dippA6RbgwS/j+DrW6caTdDQAoErcR9SCZBovPH6BGqTzFlFx3DXFW9rQUFofVQg2mfHr9M4UlWcgVljS7lNUTaVyRekyJS9CtLEtIKuDIXEKMY5h/fbYZV7+4WlfWjhR5r41kTmry0Aribw6HPP7hWMwUcqmKsJGJf8ehNvp5kkmYuIySabC4ZNcuOWdAUIEAoKHNHdfXJ2pi76JMus3jD4DjlAGZLIbFGC6vH1c+/y3++Nb6mB3Tp8rqyY0ySJaqttZ4xrDIXUIkhiX1ryFmsDDixqur9mD51kP4+UBzTI9Le21YORRkJG+F6ZP1NDIawwIkLv4hFVErLAWZwsRP0nXzMuywiyvU/IzkqWcEt8xt57AmT2Fx2LSHapYlZI7/fLsH32xvwH9/2B+zzEI/rwySzYsy8FatsMQjS0gzrZnFsDCOZchq+oDY/yRWyOse5GUmb4Up78FoNIYFALLEqPxjsdiXOkW4UJz4t9YLBdGIcgHIDJYkTsZuWUVQi+w7Jq4sEncTL+Qr4VN6FQAASrKlzyjZMVxdCZ8/gFdW7aH/x8rYDKgC73OjbCtBXN62oKDbOMSwyIJuu8J4xAwWRlzwB3jqJ429wSLVPilI4gpTobCYMFgKRVWhoT2+7oRURDJYlDEsxGAhBgwAWdpzEl1C4ipcHnALAIWiYXUkzt+hW7YSfvzy4Zg8ojtenHoSfZwYdV1hskk2G2tbUHOkg/5/uDU2351PlYYcrSJCjmeJY1qzR1Sp7Ud7af4VK1Zg0qRJqKioAMdx+OCDD0Lu//777+Occ85BcXExcnJyMHLkSHz22WeKfe6++25wHKf4GTBggNlTY6QQcrl1f2N8FBa7VZbWnIRJTd6YzmgdFgAoElfI8V6dpyJulQFAjBJ5hhAhFeIz1IoQgRhWDQlTWDiU5abhX5OHYnC3XPp4nixLiHVsDo26Zk6sFgyBoDTk6IoeBlQxLPF0CdltFkVV6VS/hkwbLO3t7Rg6dCieeuopQ/uvWLEC55xzDhYuXIjvv/8eZ555JiZNmoQffvhBsd+gQYNQW1tLf77++muzp8ZIIeSNuvY3uWJ6bL8srTlfVnws0ci7p5oQWGST3bGrsJAAVqKwEOT/5ycxPomgVoQIhQmPYbFqPk4+I1+AR+sxWozQKOrg/1gtGPTqpkRaG0eeVKA4XgzHOLkhXCLW9PH4AymfHm8Lv4uSCRMmYMKECYb3f+yxxxT/P/DAA/jwww/x0UcfYfjw4dKJ2GwoKyszezqMFEWhsMTJJWS3crQORTImNXkNFs5glhAgpe3Ge3WeilCFRRV0SyiU/Z+fAi4ht6qPEKEwYVlCJNZA+/pKs1uRZrfA5Q2gqd1L5X1GMGqDJVb3X0AddJsRXV0TdW0neWG3QIBXxFJFildmiDttVhRkOnCk3YO6Fhe971KRhMewBAIBtLa2oqCgQLF927ZtqKioQO/evXHllVeipqZG9xhutxstLS2KH0ZqITdY4hV0a7VYkjqpma3BQqCT3TEdw6IMuiXIFRYSn5RMw84VxiXU4vLFPG1fjrzAlx6pEJzcFVAX4TscI2OTdldWuXAiVSv0FBueR8xUNHkwNyAFcte3xFYNjzUJN1gefvhhtLW14dJLL6XbTjnlFCxYsACLFi3CvHnzsGvXLowaNQqtra2ax5gzZw5yc3PpT2VlZaJOn2EQl6y9enOnN6Y9V3w0YIyjg3Wry6fbdyVeENeUmQwhQJrs9CTpb7Yfxn9/2BfdyaUoekG3BHkMS1mu8HddEgdRdcwNITfdTieUeLaFcPuUE4sWyW5P0VUIVlhiY7Co05qjdeGoFRanzYp00YUaTY8iOW6VwVKWK1ROZgaLjNdffx333HMP3n77bZSUlNDtEyZMwOTJkzFkyBCMHz8eCxcuRFNTE95++23N48yePRvNzc30Z+/evYl6CwyDdKpqHMRSZZFnCeWm20G8MYn2v5LzMCvREoVFa4XnD/C48vnv8Me3fsSa3UeiP8kUg9ZhEQ2AoiynIk23SGbAlOWmAxCM0Xg3GdRDL4bFIquyHE+lTN6kTo9ycbI50BxbJfNoI8hgiZGB55eNR0D0WT1kQSYfV2Kdvi6vZQUApdnEYElt1TdhBsubb76Ja6+9Fm+//TbGjRsXct+8vDz0798f27dv13zc6XQiJydH8cNILdRFmWKZKeSTKRtWi6SyJNrFYraPEKGYxj8EDz67DrfTv7/YWB/F2aUe/gBPJ2DSSNButeDFqSchL8MOh82CXrKKrllOG7LFmjW1MXYrGoU2PrQHB70mIlNIns2hR0WeYNjVxji4/WiDuIRIj6pYBd0SYZcYLFLmW2TjkboOCxB7lw1pvGoXA3tLRaM3mWqmERJisLzxxhuYNm0a3njjDUycODHs/m1tbdixYwfKy8sTcHaMeNCpavwVy8BbqXCceLOJjeDqmhN7s1Ep2ERKMyC5QTq9fnSoyvP/IqsK/PnG+pRPMzQDUVcApYtlcLdcfP3ns7D8T2Op+kSoEFWW2gR/twQ9hQWQF4+Lp8IiFfjSgxgssY4VO9ogxl+5+HnFzCWkMjCIe+VQmzsiN7U0rkgGCxnj6mNdO0Z8DdL9++DRZrC0tbVh/fr1WL9+PQBg165dWL9+PQ2SnT17NqZMmUL3f/311zFlyhQ88sgjOOWUU1BXV4e6ujo0N0sD8+23347ly5dj9+7dWLlyJS666CJYrVZcccUVUb49RrJwqeTXWBosflVlSSKJJ9pg8UUYw5LhsNKsE/XqfGOtFEC+63A7th9si/IsUwe3LK5JPQFnOW0oF40TOeV5wndbmyR3h14dFgAoy4m/MeUxEHRbIX5Gsc7GO9og3yUZLxraPbTmSTQQm4S4cIoynbBZOPC80NTTLD4N5ZYaLDG61vwBKQ4QAMpyjlKFZe3atRg+fDhNSZ41axaGDx+OO++8EwBQW1uryPB59tln4fP5MH36dJSXl9OfP/zhD3Sfffv24YorrkB1dTUuvfRSFBYW4ttvv0VxcXG074+RJFye+MWweFVyZhn14SdYYYkwS4jjOJq+q16dbzygzHj7oaYp8hNMMciEYbNwsIVQDOSQySVZCotLJ60ZALolwFCgLqEQvaqoSyhJn1FXwaMyWPwBPuLy+XLUCovFwkmqbwQGgFRnSrrmYh0U61W9BjWIUjyGxXQdlrFjx4aUqRcsWKD4f9myZWGP+eabb5o9DUaK4xLlf6uFgz/AxzSGRW0olFOXUGJXmD5VRUozFGU5sL+pU+FH53meGiwnVxVg9e4jCsWlq6NufGgEorokKz5DqhsTrLAkwhVDFRarduE4+XnUNnfGrE7H0QiNYXHakJ9hR2OHF/UtLhpzEinEhWPh5IqIE/ubOiNSfbUUFhLDEisFxB9QGsLEYDksurFCZaUlk9Q8K0aXh8Sw9CzMABDrLCGloVCWpFV4pAoLABRnB6+YGju8NHPhwuHdAAQrLl0Z6l7RCGDVoyzJGTAk2y3DEXzO3fLjb7B4adCt/jVWmu2EhRNWzfGMp+nqyDsUk+8uFgsp4hKSGxjE0I7EYNEaV8h9cDBGCog6hqUw0wGnzQKeT+1YKGawMOICqcPSpzgLgLAyiFWdFJ9Kgo1mcIjleZihOxkwZYMDmWzyM+w4oWceAGBTbctRE3hL3SsmFJaKJH23hA7R8E7XMFiIsrG/sTNu35HHQNCtzWqhK+REu0W7EsRgcVot6CZ+d/saO0I9xRB+jfIGZVFk3WgVpJSCbmOVJaRUcSwWji4u5ZmKqQYzWBhxgaxMu+enw2G1IMDHzv8qFWxTxrAkPEsoEFmWECAZLPsagw2WgkwH+hRnwWG1oNXtU+zTlYlEYSFBtwea4mcUhIIoheka50wmvXaPP26dbo1UugWSmynkD/A0TTaVkSss3fOFyTkW8UdaCgsJYo1E9VU3UwQkg6WpwxtUMiISJJVauq6qCoWSAruZwcI41nDJpHSaxRCjider4xJqdfvQ6kpc8ThpJWT+uZLBIq3wSMZQYZYTdqsF/UoFdeqXo8QtRLKEzMSwdM9Ph4UTjIJDSXB3hHIJpdmttBZLvAJvPb7wheMA6Xra3ZDYyabV5cWpc5bg6pdWp7wSKM+4IsZmbAwWZeE4QBYkG6MYlpw0Gw38joVbSOucexWLBktD9KpTvGAGCyMuEIMl3W6VpPMYDerqgm3yAmOJLC2tFc1vFLLCk6snpLQ6qfY6sFwoiLjpKAm8jSTo1mmz0s9q16HEr/yIS0ircBwQf2XDoyqhrke/EsG43V6f2DT4LXWtONTqxjfbG7B2T2NCX9ssVGGxWjQVzkgRhwHF5E+z21rMH1/LmOA4Lqapx1pGUS9RYdnJFBbGsYa8QmisfaNEJtcaIPYnMJtE66Y3ChkwD7W66WdFClmRlOfjRIPlaMkUClXTJBSk+m0yfOuSwqKdUBnLlboWXp8xl1C/0mwAwNaD2v3X4kWLTNF87ds9CX1ts7jpZ2mNcdBtKIXFTRdYRtEbV2icUgyuNak0v8wlVMRcQoxjlE6ZwVItDqabamMzmEpFj6TLt6e4Oth1KHErzIBGRUqj5KbbkeUUJkEy2R1uJy4hUWGpEA2Wo8Ul5NNuJBiO3sXJW/nRGBaH9jkTw3NPnGR00wrLwbaYFEMzSmO7ZLAs/KkuqMJ1KiF3CXXPExZRDe2eqM9ZK6unPDcdDpsFHn/AdGCvVBhT+Z3H0nDXaivSWzz+vsaOuHYgjwZmsDDiAskSSrNbMUBUCrbUx2bipe3cZTdbX3HA3pFAt0E0CgvHcbJMBcFgoQpLllJh2d/UGbMurcnE5Y1MYSED6c4kuIQ6qWtTW2HpLWbB7TwcH0NZCroNfY31KMiAw2aByxtIaJC2vBmfxx/AjgQuGMziEQ1mh82CnHQbsumCITpjkxoYsjosVgtHr1uz1ap9GscDJIMlFoa7V0MVKs52ItNhRYAHao6kZhwLM1gYcaFTFsMyoExQWPYe6YxJUCxNJ5YVbCPp04ksZa8lBZuhu0qWpkG3YiBnbrqdGjWb6rq+ykKLsJlUWHoVCd/trjgZBaEgq2+toFsA6COqP/GaqKW4i9BGns1qoRPk1vrEuYXUHdJT22CRYlg4jkP3AkFliVYdIwaLumBf35LIxiS9pqqSwhL9Z6wuzQ8Ii6j+4lgt72mWSjCDhREX5CXN8zIcNGAs2sE0EOBBFG+bLNg13hOHFpH2EiJUFpDYHuGcSdG4QlnlTeIWOhoyhUI1EgwFcQnVHOlIePosaU6pVYcFAPqIk9K+xs6YpJuqkVxC4a+x/kmIY5ErLACwLcFBv2YgnyW5/siYEe0iR09pjdZgUS+EiJq361B71BlZPp2EgeO75QIAft7PDJYuRyDAY9fhdmw80JJQv/DRgDxLCACqRct9c110g6lP9j3Ib2gycRxsdSsCAeNJNHVYAFDliXwmh1UuIQAYJBosqTqAmCHSoNuynDRkOqzw+vmEB952evXrsACCcZmbbgfPxyelmPbNMmDkEeP2p32Ju1aIwtJDNL5TuVmnRxXAHKlBoUYvlo0e3+Qiyq8q20DoUZAhpfhH2bVZr+glMVg2JPAaMgMzWELg8vlx5sPL8OsnvqK9cRjG6KTyvzDQk3iMDXujuxHkEffyVWdOmp3229iRoEEzmjosgNKIc/v8aHUJq3mS1gwAw3vkAwB+qEntlFEjkKBbrUaCobBYODoZ/5xAqToQ4GncjZ7CwnEcVYB2HIy9wUJWwuHqsADA8Mo8AIltmEkUlhOrhOt0W4KzlMygNlj6lQj337ZoFRZ/cC8hQGaw1LeZUkR8Oq5mh81CVdlo41j0VKEh3fMACIpuKi7SmcESgjTZSjCVo99TETrQiwbLKb0KAAArdx6O6rgkWAzQX9FEOwAZPheDGRx69C/NBscJqc1ESrdZOOSk2ek+w8QBZHdDBxrbPVqH6TJEGnQLAIMqiFSdONeYfJGiF8MCSPFT8XBHkmvMSIPN47vnwmrhUNfiQm2Cei81igrLyVXC/b2nIXUzTOQxLIAsUP+gOYNCDVFY1G67XkWZsHBCQUsztVP0YljIMYHoA9D1VJw+xZlIs1vQ5vZhV4KLEBqBGSwhsFg46u/sYAaLKVyqHiwn9yqAzcJh75FO1EQR5EaKtQGAXeWKoSrOvqaIj28G9YrNLJlOG3qKK6blWw8BEMryy4P3cjPsdAW/fm9TFGebfCIpHEcYnATfuvyeTwthZBGDJR6GMrnGjBjFGQ4bjisXVIN1e5pifi5aNIkKy3HlOch0WOEL8NiTghMdoExrBoCqogxYLRxa3T7UR1E91qfjGnbarDSu6EcT967e8QApTinaYpI+VXsTgs1qoYuDRLoWjcIMljCQlVU8AuqOZlwq+T/TacPwHnkAgG92RK6ykJuZ44Kj8kf0FGTpRA3WngiDSOUMKBOMrDfX1Aj/i0aXnOGVR4dbiJbmN+kSAoDB3aSaNImSqjs90jWsvtbkkFikLXHI5CLXu9o414NcK+sSdK0Ql1BBpiNmMSHxwq1aYDhtVrpgiOacQykixKW7zoSbzh/C1TwoRq5RPbcTIMWx/JSCcXPMYAkDcWl0MoPFMD5/AF7RgpcHK57WpwgAsGpHQ+THDtEh+QRxcNhc14I2d3ya0clxqyTmSBhQLqV8A8BJotElZ1ilqC508UyhSINuAaBvcRacNqEZZKJqRISrcksg3+HOQ+1URYoVUtCtsUy0Id2FayURxQZdXj918+Vl2NE3RjEh8ULtEgLkbuTIY2+06kIRThAXaWYWG6GC+YnSuKm2JaqMOT2XECAzWJjC0vUgLg3mEjKOS+bDlk9ORGGJJsdfT8oEhHLY3fLSEeCBDQlwn9A0SRPdh9WMO65U8f+JYiyAHDIR7EzhGhdGiMYlZJM1g9ySoDojHSE6Ncspy0lDbrodvgAf08Bbnuep4a91vWtBFLtEBL8SdcVm4ZDltKW0wsLzfFBaMxCbTCEjCsuGfc3U+IzmeL0KM5HltMHlDURVJDPUdXW8aPT+cqDZdFuBeMMMljAQg4UpLMbxKAwW6RIjzfx2HW6P2MUWrrosMYoSIYlrrdjMMrhbLnLTZUG2YqaHnD4lUh2Sruya7JRVP46EvnEMbtWiUxWHpQfHcbIU9dgpG/IUfqPXWN+SLHAccLjNQ9Pk4wVp1pmX4QDHcbQ9QCoqLL4ADxJXK485I0ZwNOccyr3SuygTuel2uH0BbDFY0sGnU4cFUGbMReOyCWUU9SnOQrrdinaPPynFGkPBDJYwUJcQU1gMQyZym4VT+P6Ls50ozHQgwMPwzavGr1HlVg65mRNRol/tE4+U35/eC4CwUteaHIuznMhOsyHAx69nTSLoEN10Wc4IDZYEr+A7vWLROAMGFgn4jrbOkByfLMDcSJYQIBhXpCZKvCvekhos+RmCwU2+n52H2lJuZS5fRMnv177FgqEZTSmEUO4Vi4VD/1LSvsHYmBTKmACAwRWSAhIpoYwsq4WjsTKpVo+FGSxhSBf918xgMY5e9gzHcXRgjzTK3atToZHQs0BQIxKRqRBtlhBh+pl9cNekgXjlmpM1H+c4Lq6ps4mi3WMsJkQP+hkkyGDpMKiwALErjCjHI3MhmEmdp/VF4lx1lrTZyBEVwkqxn5HbZ77hX7xRGCyyz5Kolw3tHqoYmSVUVg8AVOYLBuReg7FXoYwJAOglZg2SuLdIIMaw3nUlj8tKJZjBEoZ0MaOBuYSM4/FLTcbUEOk8UoNFqweGnJ6FsekPYgQSkxGNSwgQ4jOmnd6LpixqkejJOh6QMveZUSosO2JQmtwI4foIyakSu4Xvi2FAsE9hsBhv/1BdlphYH2LQZYpNBOUN/1LNsCbGn4UT7jdChsNG+3VFqtyFU0RIzyKjRpw/RBAvAHTLE9qcHGiKzGDheT6k2wmQKhenWhNEZrCEgbmEzBMqe4YqLBGuRMPdaMRgaWj3xD1TiKY1R5CmaxayEky1icAM7eL3EanC0rMwE1YLhzaThbgiJVxZfjlk0jvQ3BkzY8or61XFccYNFmL4bouzwUIVM9nn011UE/Y3xf/7MUMoNVSKY4nPmFQpNjk1qoiEO163PPIZR2awyN11ekYWVYVSTCljBksYqEuIKSyGMTI4RNoThqw69W607DQ7CsTmgfF2C9FCVFEqLEboXWTOD56KtLvFFXmEBovDZqEGaSLiWIwG3QJAaa4THCdU823siE0vq0grKfegK/r4VrslMUkZMsWsQlz91yWo0q5RQi2iyL21O8J7K5zCQsrpG538SeVcvcww8hk3d3ojWpTJg7n1YqPoOTOFpWvB6rCYJ5TBQmJMDrW6I1KtaJZQiEGcyplxdgvFKobFCN3FVVptc2qtXI3iD/D0HorUJQSAuhwS4fIzmtYMCOn7RWLTykilejVmyvLLIWpPfYsrrt2ticIiN0DLcoXJtDZlFZbg75IYAJHeW+Qz1lVYxPHoQFOnoWDkcApLdpodOWnCZ74/AqNUqbDoxN2I53y4zUNduakAM1jCQPzXzCVknFDKQ26GdLNF4h/1+UOvZgBZHEucVwexqHRrlNIcYVA93OY2XM8hlZAb/CTmIRKIyyHe6gEgVbc2EsMCABWioRCpVK/Ga6LxoZyiLCfsVg4BHqiPsqtvKDQVltzUNKy1arAQysVzrovwnCWFRft7KstJg93KwevnDbky/QbGuG75khFkFnn2mZ5RlJsujdPRBPfGGmawhCGdGSymCTeR9yyMPJPHFyatGQAttx1vl1Cs0pqNUJjpgN3KgeeBg3GchOIFmdwsXHQGHlGaEuFbN6OwAFIwZG2SFRaLhaNKR6zUHi06vCEUlhRzCYVSQ6Vzjsxg8RJFROd7slo4aswacbGEU1gASUXbF4nBImsgG8ooSkW3EDNYwkCKXHUwl5BhwrlKoolAD1W2mtA9QT58TxSl5s1isXBUZUm1+AAjyN0HZgJI1SRSYZHSmo0pQmSlfiBG6kI03cCJ0hFXg4UGUWsrLInI5DJKqCKPxCVU3+KKqH5MuBgWQApiNXLdhqrrQiDGcTQuIYtGPzY5PUzG3iQCZrCEgbmEzKPuiqqmR2HkBovXgFxanksm9vjK0uHeZ6wpowZL11NY2jXcB5FQWSCuLBOw6jObhh1rlxBtfBiJwUKyluIYS6JVV6ckR4jjcfsCtLBcKhCq1EJxlhMWTvi8zVYH5nletojSH5PIYqPegEuI1mEJYdh3y4/8WvMaiAMEJIUllVKbmcESBiIHd+WS6IkmXFPAnjFQWAwZLHFOfY1FaX4zpKrcboQOjQDNSCAKS0N7/IMBzRa6q8iNsUvIRxQW84qUFEgaR4VFw6BLs1tRKGbpHUih6zSU6muzWqhBYdYtZCRFGABKRUPuYJgxied5kEOGMoCImlcfwaLMSIyM8BrGjaxEwQyWMFCXUApFSqc6hl1CEWR6GIlhKRNv5laXL661WBIZwwJICksqDSBGaffERmHJTbcjO4oMCTOYbSUQa1XDQ1P4zV9f5QlwCZE0dbVBV56XGIXTDOEWUWURGpvyFGEjCku4+DMjGTwAaEZaJP2iwlXSJUiqUOoousxgCQN1CXm7XmZGsgiVQghIUuO+RvNFtkJ1ayZkOW3IEjNR4jlo0kq3iTJYogwOTCYdOpNbJCSqqJVZhYW4Qw63uRGIQS8dWj49guurG3VPxe9a6aSqmfI+L8uJbSxPLAi3iIo0u8mogUEUlnCLDYUBFGJRVpwtHO9QBAH4Rl2NUsxc6nyPzGAJA8kSYi4h44QrqFaWmwaOE/ZrMNm/gyosYVYHZQmQMxOZ1gzIZOAurLCoJ7dIIJlCcS+MZjKGpShLKB7nC/Bo7IisL40cGnQb5lrXojwBLiHynaoL65HJ+VAKXafh4s3KInQjGynCBgDF2cbUCqMupmJRYWl1+0zPTb4wpf8J1I3VmjoB1KZH2hUrVmDSpEmoqKgAx3H44IMPwj5n2bJlOOGEE+B0OtG3b18sWLAgaJ+nnnoKVVVVSEtLwymnnILVq1ebPbW4kM5cQqYJt5qxWy30hjNbYMpIyh8g+V/jpUbwPJ/4oNtcUpgsdSYCo0g1O6JXWBKVKaTn8tDDbrWgIEOI34hF6rk3iqDbEnGCbOrwKhr/xRJ1LyH1a6dS+n24MSnS8UJuYIQKkqVGXKs75ORv1MWUk26jC0KzKouROEBA+h69fj7ixpCxxvSd0N7ejqFDh+Kpp54ytP+uXbswceJEnHnmmVi/fj1mzpyJa6+9Fp999hnd56233sKsWbNw1113Yd26dRg6dCjGjx+PgwcPmj29mMPqsJjHiPJQLuu9Yga/aTkzPpOaL8CDjDtOa/zTmgFpADncFnrQS0XaddwHkUAyheJdH4JkNpkJFI5GqldDg24jMIjz0u10Qmpoj4/h0K6R1gzE9jOIFXRM0hk3pHM2u4CSmiqGShEmx/f4Q2dPGTWAOI5DUZZgHJuNY/EaiAMEBOOOBFCnShyL6TthwoQJuO+++3DRRRcZ2n/+/Pno1asXHnnkERx33HGYMWMGLrnkEjz66KN0n7lz5+K6667DtGnTMHDgQMyfPx8ZGRl48cUXzZ5ezGGl+c1jRHmINKPCa1DOjHemkKJdfYIUlkJxgHL7AtQA6CoQhTIWMSyJUFgibSVAJqZYqAtkMozEJWSxcPR6iYfh4A/wNJBVbdCVkMk/goDQeBFOYYnUyApX5ZbgtFlpj7P6EEYR+c65MAYQEP9zBsylYyeCuI+0q1atwrhx4xTbxo8fj1WrVgEAPB4Pvv/+e8U+FosF48aNo/uocbvdaGlpUfzEC7J68Pr5LlkSPRkYSfctjzDIzWew+mdZnGuxJMNgyXDYqAHdkEKTgRFo48Mos4QAeQxL/BSWSFsJSO6Q6K87jz9ylxAgTWiRZJKEQ+4iV8ewUKMtRVblQPhFFHFRm538jcaDAJIhF0qtIEVow7lrAPn3azIO0MQ5Gw0WThRxH2nr6upQWlqq2FZaWoqWlhZ0dnbi8OHD8Pv9mvvU1dVpHnPOnDnIzc2lP5WVlXE7/zRZWW4WeGsMI+m+pE6E2UwCGuEeZnVQFmFdBaOQ92izcIZu/FhRSGXg1PApGyW2CotgsDR2RNat1giRthKIpTvEqHGuR1GEk7ARSPyK1cIFfT6xzpaKBeEWUeR7a3H5aPafEYzGgwBACUltDjH5G005BiJPbTaauABEHowcL7pkltDs2bPR3NxMf/bu3Ru313LaLCCuRBbHYgwjXYypwmLaJWRsECcr3VgM1p0eP859bAUufOobOkAlslOznEJxkEqVIDijUIUlBjEs2Wl25GXYAcRPZYm0lUBJDF1C3jDZduEozopsBW4EefyK+vMpzBReN1bZUrEg3CIqN91OC/SZ+bxoEoABo7I0O7xaYcZdE6lxLHW8N6KwpFYtlriPtmVlZaivr1dsq6+vR05ODtLT01FUVASr1aq5T1lZmeYxnU4ncnJyFD/xguM4ZIgqy9ItB+NaiOxoIVxaMyBPuzTrEjImk8tXeZH0B5Hz2nd7sLmuFev3NmHljsMAQpf6jidFoh+8y7mEPLHLEgJkTRDj1Ek20lYCdBKJwQBP21BEqLDEM/g1VOVih81C4zVSJY4lnEuI47iI3EJmFBYjLhyjWZBA5AqLn7qEWAxLECNHjsSSJUsU2xYvXoyRI0cCABwOB0aMGKHYJxAIYMmSJXSfZEMG2T+/9xNG/GMx/vfjgSSfUWrjMVBQjRRqqjPZcMxrUM4szHSA44AAH50a4fL6MX/5Dvr/f3/YDyB85cx4QVxCZuvXJJsOd2xK8xOkZnJxUlgiyBACYhtwGk3zQyC+LqFwBh2Z/FMljsWIIhqJgWfGhUOMuFD3biQGkHmFxXgwd3EUFXXjgek7oa2tDevXr8f69esBCGnL69evR01NDQDBXTNlyhS6/4033oidO3fijjvuwObNm/H000/j7bffxh//+Ee6z6xZs/Dcc8/h5ZdfxqZNm3DTTTehvb0d06ZNi/LtxYZbzuqLod1z0S0vHW5fALe9vR7f7mxI9mmlLEYHB6uFg99kwzFa6TbMIG6zSil50QRAbtjXrFgRLfq5Dp0ef9JcQgWZqTWAGCVWpfkJ8S4ep1djJBxG4hSMEq3BUhzHbJ0OWgVY+/ssyYmfsRQJRhIBIjEAzLhwiAEZSh0l41u4DCH58czHsJhQcYgqlCLfo+k7Ye3atRg+fDiGDx8OQDA2hg8fjjvvvBMAUFtbS40XAOjVqxc++eQTLF68GEOHDsUjjzyC559/HuPHj6f7XHbZZXj44Ydx5513YtiwYVi/fj0WLVoUFIibLKaMrMKHM87AV3eciYlDyuH183j8i23JPq2UhcivoYIVrRapjoCZVZjk1zeyAom+gBVp0Hh630IUZzvR4fFjU10LVVgSVeWWQD6zhi4WdBupYqEHSW2OVy0WamCZjLkhk167x0/fc6RI7s/ogm7jMdl0hGlbQBWWFJnojNSGikxhMT75Fxq4dxOhsBitZQVAVuvFkxK1n0yPHmPHjg154lpVbMeOHYsffvgh5HFnzJiBGTNmmD2dhGKxcPjrr4/Dwp9qsWpnA/Y0tKNnYWayTyvlMNrFuDQnDfUtbtS3uHA8cg0d22tQYQGEG3pTbXSrPGKw9CgQvudDrW7sONhGfbt6/ZLiBRn0ulrQLYn9Io0Lo4UUj4ubwuKOTGHJctqQ4bCiw+PHoVa36efLoc0PU1BhCddqoTjVFBYDtaEiUSzMGBgkGDlUIT8/byaGRRgL2j1+dHh8hjPwjNayEl5DKnjX4vIhN91u6DXiRZfMEkom3fLSMbpfMQDg7bXxy07qyhh1l0SSUWEm1bMkBkGHe6nBkoE+xVkAgJ2H25OXJdRFXUKtLtL5OLYKS/yyhCJTWIDYFY8zGmAe7jxaXeb7zYSDtloIq7CkRrBm3GJYTE3+0mJDL93bbyLlOMtpQ5pdeD+HW40vYMy8Rprdimzxnk2FMYcZLBFw8QndAABfbj6U5DNJTYzUYQEkf7+ZCHSjdViA2BgsNTKDpXeRoLLsONgmub2OoaDb2uZO3PHuj7ji2W+xZFN9+CeIeHwBek3kpMVmhUa6Ebe4fGju1C91HinRuLBicd0B0TU/BICcNKnfTKwnG5f4fcrrVMlJtfL8kuqrb4DSLKEIFBYjBku+GFMX4IEmnWvWjAEklOc3f85m0pqB1IpjYQZLBIzsUwgA2FzXEpfBsqtjJK0ZiExhMVqHBZCvdCNf5ckNlj4lgsKy41Bb0hWWUKu0ePHcil14e+0+rNrZgH98vNGwT1seyxGLSrfCcWw0qDoeKkt7hEG3QOyq3RLpPpJeQoCYqhsnw4EoNk679rnFsg5SLHAbcAlFkyVkZDyyWy20fpBe4K2ZIF4gOlXI6GsUpVCxSmawREBJdhqqCjPA88C6msZkn07KYXQyL40go8JolhAQ/aDZKcYhAECPQskltKehg7oMEh10S1Ij/QE+4cay/Frf3dBh+Non8SvpdmvE8RhaxLMWC3F5RGJgxcolFG2WEBC/yYYoZmk6MVwpq7AYNFiMGuOSwmLsOyJGtt73QdQPI1lCQGRxN2YChSN9jXjBDJYIObGqAACwZteRJJ9J6kEGh7DF3UjlRxMrUXNZQtFNHHvFlXtuuh256XaU5aQh3W6FL8Bj+8E24TwSbLA4bBbkiIGriXQLuX1+bDwg9Ow6qSofAPDu9/sNPZfGr8Qo4JYQzziW9jBZMKGI1WQtGSyRt35ImsIiBt22un0pUSGc1oYKMSaRibnT6zfcXNRnIugWkCpV6wXemgniBSJNxTbX8oEZLEcBZNBeu5spLGqMpDUDcoXFhEvIhGRKXU4txldMckjALclIsVg49BLjWLbUtQJIvMECGKvnEGt+OdACjz+AwkwHbj27HwDgy83G4lhaXYISlB2jgFtC9zhmCpHeR8lVWKILupWfS6wNlnAKS7bTRu//VFBZjGQJZTptNOvJ6DmbiWEBdMoS+DyA3xvh8cwbEzTTkiksxw7DKgWDZWNtS0rkp6cSZrOEzJTPN5MlRAZrMysmOeQGJa4lQIhlAYCdh9oBJL7SLZCcwNsfapoAAMN75GFEz3xYLRzqW9yobQ5vLBCXUFdSWNrckSsssQ66NTqxaBGvyYYoLGk6CgvHcVRlSYVMISN1WADzHa7NKiwF6tYaAT/w4nhg7nGAu8308aIpdmfUjVWULbZZMJGJFC+YwRIhvYoyYbdyaHP7sN9kA7+jHaMGS2GWExaxfL5RtcBMqqd8xRRJ5dEj7cKqJz/DQbeRuAnSvTQZCgut55DAFc/P+5sBAMMq85DhsGFAWTYAyZAJBTVYYq2wiJlC+5tiPyF2RpHWLMVORXdeJKAzmmssbgqL10Ahtji2BjCL0THJbDsDv4nS/ICsLAFZbGz8EDiwDmg/BDTvNa2wFNMYJfMxLEZdjUxhOQpw2CzoXSQEYW6tb03y2aQOgQBPb4hw6oNQ7ZZ0MDV2MxjtJUQgqdORDJpNYqfZ/AwpFZcYLARnggvHAUBBEqL268QmlZWiwjS8Rx4A4AcDgbexrsFC6CZ+FwfisGBwiRNyuk7abiiIkdDQ7qGKYCR4feayObSI12Tj9hGFRf/zKYlBpelYYbSYpVkDz2favSJTWHge+Gqu9CAfMJV1pDhfU+1NzBlZzGA5SqgWV5mb65jBQvDIBmgjK0Max2JwNWq2mFY0JcJJNVlSPwGQ3BCEZFR+JB2bE1ntlnw/ZIAcLrpETSksMXYJlecK105zpzfmXdQ7wwSVhqIg0wGrhQPPR2dUEuM8JkG3MXcJiQpLiM8nlTKFjMSwAObP2XSWEI0/8wD7vwfqf5IeDPjNu2ui6DBtdgw93BZZLGAsYQZLFBCDZSszWCgkGA8wZrDQTCGjCovJVM/inMgNlsYOwSVUIDdYCpQKy5BKYy0FYkm4TIN4QAZE8n0NExWWn/Y3h40/ahMVllgVjSNkp9lpxlSsVRYpRsO8wmK1cDR9NZrJOjZpzfEp+kUVlhAKY6xieaIlEOBpoGlYg8WkAWA6S0jesXnDW6oT9UkpxwZtVPL9urwBw72rTKc1izEsLm8goljAWMIMliioLhUMli31bdo77P4G+OBm4Me3tB8/CvHIDRYjtVJMKixmCscB0fnRGzVcQqTCKmFY9zzTx42WwgS7hFxeP1pEo4M0lKwqzITTZoHbFwjbgDBeMSwAUEHjWGJtsITOggkH7VbcFnkcS7Sl+QFlM0aS+RQL6OcTwqCLReHGWGBG9TWrSFFFxOB4RBYbTW3twM/vKR/kA6YVlkynjbotNV02Xhew4l/AtsV0k89kMHeGw0ZjuZJd7ZYZLFFAFJYdB9uCV5l7VgILfg2sfw1YeDsQiNyX3ZWQV7nlOOP9fowqLGYDxqLJVGgkLiFZ0G22SiWQu4sSRaKDbomxJ68BY7VwtJBeuBiueNVhASQDMtYKi1tUWNIjCLoFYhNw6jFpnGuR6bDSCS2WSgetwxLCAJCMtuROcgqDJdYxLCYVFhLDMtDzE9DRAGQUAbmVwoMyl5CZzDDdBYyrGXj6VODL+4CFf9I4Z+PTf6rEsTCDJQoq8tLhsFrg8QeCB8wf35T+drcADdsSe3JJwmzJ+tIccxkVZstKR1PtligsBTpGSaw6D5sl0WnNB2XuILkR2r9UMFi2HdRRGEXa3IJrLR4KS7wCb12+0Gm74aABpyZqDKmJhUuI4zgq6cdysiGuX2cohSUr+s8gFphRfc3HsJgLYM1Js8Nm4TDW8qOwof94wCa8Jni/acUG0DEmvJ3AG1cAjbuE/8lvyKuFm3mN2F9DkcAMliiwWjhaVGxPg0wWDwSArYuUO+9bm8AzSx5mDZZIY1hMR9GbNFj8AZ42KMvLUBosJENm2mlVpo4ZK4gfvKnDG1UWilHIZ0c+S0I/0SW6LYzCQlxC8TDwqEsohsXjfP4AjXmI1CUUi2BXySUUucICxCe9OFwdFkBSWBraPYbrLMUDqfI2F7bkvZTh5TbUq8tsETaLhUNBpgNnWtYLG/qdA3DiNSaLYTGjsBTJA3kBwO8D3v09sOcbaaeMQvqn2RgW+WskOx6JGSxRUlUoVD7d3dAubTzwA9BWDziygZNvELbt/z4JZ5d4jKYPEkxnCZmMcI808K+50wsSEJ+XoXQDzf/dCDx0yRDMOKufqWPGirwMB8hY09jUCNT9DMQxep+oXyVqg6WEuIRCKyzxSmsGJIPlQAxrsbhkK/JIgm6B2GTIxEJhAWSTTQxjnqjCEsKgK8x0gOME4z+RGW1qzIxJxN3q9Rvr1WU25gQABqY3oq/lAHjOCvQ+E7AQg8VvWrEBVOoHzwMf/QHYshCwOoFJj4vHluKX/CZLQwBSx+ZYXkORwAyWKKkSS7XvkRssWxYKv/ueDfQcKfy9/xhRWPxizw6jCkuONLAbWYV5feZuNnlNDK8JNYK4g7LTbEETRmlOGi49sTIpReMAYTAryHRgsnUZCucNBuafDiz7Z9xeT09h6S8qLDsOacRwyWiLo8HSLU8weGMZdEvUAyDy5paxyJCJRWl+QJpsYhkwaURhsVktMcmWihajKc1kHxJkb0Qdi0QROcPyMwCgIX8IkJ4nKSy8X5YlFInC4gZWPAys/w/AWYDJLwG9xgg7BaRr2huFisNcQl2cqkKhLseuwzKX0JZPhd/Vvwa6jRD+rv9F6BlxlOM26RIqzHRI1W4NpOlKtSmMHb8gw0FvTDM3Gwm41YtfSTaVGR7cZXsFFp943S3/J7D1s7i8FolhITEJ9BwKMuAQM4VCxZC0xqkOCyApLHUtrpi5HeQBpUa75qqJRT+hWDQ/BGQuoRhNNjzPG1JYAGmiS2amkFk3tRn3RySKyPCAUHtlT85JwgaqsATgjyC+hMS0+Rr3A189LGw87zFgwETAIt5zcoXFT+JkjE//tKIucwl1bYIUlsbdwMFfBKu53zlCBLgjS7hgGncn7TwThVmXkM1qoal+RoLzzKZ6WmTVdM2s8o5oZAilEpP5JcjiXGjJ7gucfL2w8ZPbAE/s++rQGiw5SoXFauFobyVFDJeKeNVhAYTgVpuFgz/Ax2xSNJKyGw65SyjSYltScGQcFRZXC/D2FODlScChLYaO51a4zML0CxNdvoeb24E3rwRemgi0GmuaGSvMLqLMuPNMKyw8j/6dQsDt5rShwjaLFMPi5yOPLzmz/iXA5wJ6jAROmCIeO9hgoS0fog3sTQLMYIkSEsOy50iHEKS1RQy27XkakFEAcBxQ2EfY1rA9SWcZB3weIRJdhdnVDACU5pDA29ATDs9LZf/NrEDoatdEtkJTB+kjlPhKtmEJBHBu50cAgPWVVwHj7hEM4+a9wLIHBD/29wuArx4B3KHjS4xA+p4UaqhNPUWDRRHDJcPnD9CqsfFwCVktHMrEirexCrw14u4IR7SNN3meV5QIiAZdhcXrAl65QOhns2sF8NzZQEtt2OORPkJAeKOOvHbZ5peBzR8De74GXr1Ic+yIF2YXUWYMFkmtMDgeNexAtvcw3LwdP3H9hW0yl5A/gpTjwiwHenMHcGanqLCOu1uYdwClwSIaQx6TmZaAYPRebFkBe8tew8+JB8xgiZKKvHTYrRw8voDQEG+7WKCn/3hpp8K+wu+jxWDpOAI8Mwp4bAjQdkjxkBl/McFozxGfTPK3m7jZSiLI2JCKxqWgwlKzEgW+g2jhM/B99lmAIwM4d47w2MongXmnC4F3S+4VvidXc1Qv1yoGH2q1IehZKFMYG3YAX9yjuCba3dJknRkHgwWIffG4aKrcEjIcNmqgRdJ4k8SvADEwWPTSmr95XGi8l14A5FcBnlbBcAkDqXJr4cIrC8XZThShGSfvni9tPPhLcBZlHJHGJGPfZ0gX2uaFwPPnAN/OAxCBwrL7KwDAD3xf1BNRUhZ0G0kGT3GWE7fZ3oYVAaD/BKDHqdKDFtl75oXPgWQW2s0sKvnDeMj+LF7vvBFoqjH8vFjDDJYoka/wahuahOq2ANDnLGmno8lg4Xng3WnAoc1A+0Hgm8cUDxtt4y6nxKAC4pMN4vFWWEhmS7JqrYTkp3cAAAv9J+MgmaOPmwSc/gfh74O/AOCAtFzgyE5FlctIaKGfhZbBInMJLb0f+Hou8OMb9PFWsQaL02aJW5BytxhnCkVb5ZYQTaaQ12RPrpDnkSXVIqLuqUNbBQUOACY+DPQ/V/i7dn3Y48ldZuGKQ5ZkO3G97WM4Ap1AxQnAyBnCA1s/N/0+IsWs6qv7vf3yAfDmFcC+1cC6VwDAvCKydzUAYHWgWir0RlQQ3m+6MSEAlLZuxETragR4Dt6xf1M+aJGNX6JbiMZGmXiNsi2vwsYFsNk5BN7s7oafF2uYwRIDyIDZufNbwNcJZJUCJQOlHY4mg+XgJmDnMun/NS8A7Yfpv2blV0AY1H5nXYzrV40Vih3VbtDcT16x0ozBMrH5DTxpfwJ9dr5qOP1Xqh2SYi4hv08YOAF8GDhdWd3y7LuBi58Hxs4Gpn4MDPudsF1ejyECWlyC0aFlvFGD5XC7ZKzLFJ141mAhVIiZQrEqHkcVlgir3BKiqcUiL3YWbdBtUC8Ybyfw3u8BvxvoczYw6GKgfJiw84H1YY9HiuoZWZR0c7ThKqtoMJ/5V0l53vZ5wqp/00VUNC4hngeWPyQ7qOBqNa2w7P0OALAu0E9K9ebE8wr4pZ5HJsbP7G8eAAD8N3AGGjJVpRY0DBaP2ewzTzsc6wUDbdDFf4k6ay0aUnD52PXolpcB4AjS9opyau+xkg8ROLpiWGpWCr97jQGa9giBxPW/AL2F9LlIXELV/A78yvYK7H6/kBK+fQlQPgQYeIGwIhM/S3mRNMMuoa2fYVTN04AVwIFvgc0nCWpEGMgkHY/Mlqg48APgaoLHkYvvXMdhuLy+hcUCDJks/d/ZCHz7FLBnVcQv5/b56YCvFTRLXEJ8407AWidslMUnxDOlmSDcfzE0WGhjv2hdMeaVPQJZBVu46INuM3Z8ihedj8Ea8MD/6XLg0PdA3U9CMbELnxbur4phws51GwRDIsT95TYRlHz8nleQznmwydIPx/UdJ0yazhyg47Dgjup+YlTvzQhmSy30b1mJ9xwPwVKbATS8JIzf2xaLyqWIVfhuaZaQEaOyvQE4sgMA8EOgH9ztguLFyVxCZgOEUfMduF3L4IUNj/ouQXWbmyr+ADQNFtMuoe1fAK4mIK+HMtQhCTCFJQaQWhBlh8SJofdY5Q5EYWmrF6LyuzJk8ut5GuAU6nDII9AjCbo9bdvDsHN+1Fh7CNK03w3sWwN8/n9CXQERuX/XULqpzwN8+mfltq8fNaSytKWqS2jXMgBAW/lIBGAJ3U+oh1gD6NAmIe4oAohrDNA23rrlpcNq4TA0sFHa6JMMh3imNBMqYlyLpdMTfQwLAJzlWYbn7I9g6E/3C8ajCdy0OmuUQ/SOpcBbV+Esbi3GWDcgd/0zQk2otFzgsv8A2WXCfoX9AFu6oByIk6oeUtuCMJ9P+2GUbXkVAPCE72LBMLLapfFx1/Jo3plhTI1JO5dj8LLrMMKyDcP9PwLzRwFrXwL+d4vwePeThd9k8jejsOxbIzy1oC+akQWXN4AOj18RdGu6WODKJwAASxxnYR9fHBynpDBYhO/NtEtop/g99Z+gjIlJAsxgiQHd8tORizZUdG4WNqgNlrRcILNY+PvIzoSeW0zheaBGNFh6jJRFoEuBlW6zLqHG3cg//D0CPIcZ1r8Dl78BTP0EOPEa4fFlc6jLyWuyyyh2rQAad8GbVojR7kfhhkOoOGzARRLP6qxRIQZF+nuOAhCmn1BmEVA8QPi75tuIXk7+OWj51R02Cyry0nCKZbO0MeEKi07Qbd3PQkG9I7s0ngXB9fjKBUDtj4rNpNJtNFlC2P4FLtr9D5xj/R4j6t9RGN5G8EagVAbh8wD/vQEAj58cQ/FX7zXY1fdq4PSZwHVLhUUHwWoDyo4X/lZ9HmqIwhLWJbTySVh8nfgx0BufeoagXTReUXWG8Ht3dK5Koxh2U/u9wKd3AAA+8Z+MbwPHAd524OOZQFudcC+dJcaI8MKYZ6rSrWiwcD1Opp9dQ5tHMY6aMq4adwObPwEALC24FIBGA0SLBYB431KFRXQJGb22SAiAqKInE2awxIBueRkYadkIC3igqBrIqQjeKb9K+N20J6HnFlOa9wIt+4UbrPtJmjn+phUWMYB0ZWAgNrVngec4YUA7by5QPlQYGDYJKbxma7Bgi3Azu/tNRA1fiv/6hUkea18M+1QSexGP2iER43UBNYIP3NnvTACCQUGyNjQpGyL8PrRZf58QtIaIXyF0y0vHydwm2XnKFBZqsMTvcywXDZZWl09w5Xk7gUV/FSsAzwHevkphVFOeGSUMxov+qthMOzVHqrC4WoD3r4cFshiN7182la0Vk5Tm3V8Jqm5mCZ7t9k+87j8bX/WZBZxzj+SmllNcLfwO47qmhfVCfT7tDcDq5wAA8/lLAHBSTAgxlPZ+J8RkxRnDbpZN/wMObQafUYj/81+H33lmo33EzUBBH6Dfr4Ar3hAWnwC9nkwpLGJAM1dxglSdtt2tqMNiylDd+hkAHqgaBU++ELuiqbiqxmmPmYVf8z5BceMskqGZRJjBEgMq8tIwyiJUL+TV6gqBGCx6q72ugLhCQNkQIZVWy2Axc8PxPLBBMFg+DJwOr59HY4esf8egi4Tfv/wXgFTwyFDAbSBAKw47Bp0HAHjVd7bw2Mb/KQKFtWhNxRiWug2CuyyzBFkVx9EBJ2SfFhrwHVrm18NIttTAzFb0sMjS2+UKi5gllBPHzzHLaUNuuh1nW76H/cVxwP1lQuwOoe4nYP3ryie1HJD+tqcrHoo6rXnVU0BHAzqye6PatQB7LD2ElOEfXjN8CK9PDL6MRmEhLUKqJyAvNwdAmIwlg8kBhoJuv5snqBPlw7AxW3BN0rIFJQOFid/TJlzTccbwmLTxfwAAbvhVcGQVwAcbdp3wF+DWdcCV7wAFvYNUZVqHxZDBIr7X8mFSx/U2jxR0ywdkapCB4+34Uvjd75zQ3ZRV47QptxNJc684QTLWkggzWGJARV46Thf7Q7R3H6W9U34v4XdXrna7T2zgSALlZF1GCaYUlroNwOEtgNWJbx3CqktRrXTghcLv3V8BrmZZZ1Qjx/4RaK0FHFlw9B2L3HQ7fuGr4CoZBgS8gszb2aT79ERkt5imTjCKUT4EFqsF+ZmyQU8PspIOE5egh6Sw6CskI7BJucGn4RKK8+d4XuYmPGufi/SD64UNGYXA5AXAr+4T/l/5hDJ2acNb0t+5yjTNqCrddjYBq/4NAGg45Q644cB7EEsc7Fxq+DAkUDTiGBael1qEDJhorFKpQeM2bNCtp0PIHgSAUbNQnC2lVQMQFIUeosqyZ2Xo9xEDDI1J3k4p/X/g+fqpzaoxz7DC0lonlIEAB5QOpC0/BIVF5hIyalz5PMAuoaYL+pwV3LFZjspgIUq1oTGafD8poK4AzGCJCWnt+1FlqYePt6Ame7j2TkRh6coGC+k4TfojyaLbCaZSCEV3EPqPR0aO0P5ckVFR0AuwZwgFjzobJbnUyOqD+MerRgE2Jx2Atg+5HbA6BDfTgz2BRwYA3z0T9PQWvdiL718G/vOb5ARP1wtGMUoHA5Aqz4aMY4kypb6lM7zh1t8lGFL1NtEV6tUIuo1nLFBnI2Z3/AtWjsfusnOBWZuBP+0QFLoTpgjf9+GtklvM7wVWPy89P6DsyttJXR4RDI/rXxeUg+LjkDZEUAi/dImppjXfabumNPBEq7Ac3CS4b+0ZQK8xNLXZmMKyI2Rgetgsqh/fADqPAHk9gQHnyRqcyhYjZNFz4Adj7ycKiEsoZF2dHUsFRSinG1BxglQ8Tv15yWqmACZ6CRF1pagf4MikXaEb2j3SOMpLMSxhDdV9q4XzzSwBSgbR9iaaKfSqcdqUS0ges5gCMIMlFohR1D/yfbCvQ2dg7uoGi98rBeNRgyWKGJZAAPjpPeHvIZfSQS2o2q1FXNnLahQYSvPcKwaZ9jgFgFScbnvmCcDlr0vfR2st8N18xVPlqbxBysJHtwppfmoXQyKoEw0WMTiSyMpHQjWNJApL+6GIKt62GFBYKprXAQC+s4jGuleamBKisKx9CVmBVmwNdMO7Pf4G5JRLZQXScqUijmL9Gvz0LtCyT3q+Ko6CuoTMFo4LBIA1QtwGTrkeBVlOWDhgU6AHAvZMwN0MHNwY+hgiHrPZImoOCN8Juo0A7Gmy6q0hjNv8KgCccJ4hXKY06FZPYfn5feH3ydcDFit9bcW9TdKoDRSqC0vbQcE94m7VfJguokIZoCRjqf+5AMfp19BRTf6GW4XUiWOnGFNWpHAJSaqN4dgl4p6vOh2wWGQuIeMKS9hrq+2QtNARx9FkwwyWWCBe7CsDg/RTK8kE2bw3IYFmAICmvUJQYSxe7+AmQep35gpBaEDQagMw4S+u+xFoPSA0huz3K1l5flW1UllAGqkfEHZw4HkanIpKoUy11D3XJTSl/MOPwDWiBKzqa9ImT+WVKwPybtvWBAfjBgJCvRtAprCEkIEJzmyhkCEQURxLK21cqGNwtB1CZotw3C88YrFEr9QIkbrW4qWw+DzA6mcBAM/4JmFvi4aCQVyLP70tGG3L/yn8nyWm9KoUFuISSjdbOG7vd0IWoDMHOP5SWMXGm35Y0V4iGvkGs7W8EZQHUECUC9EwCNkAkWBPA/Iqhb9DKHIhFRZ3Ky2OhgG/BiA1QFSoFeXDpdeJpnXExg+BuccJ/YnevUZzF7eRmBvq+jgdQIhqtxalS8hwlpDMnQtIXeCPyBWWgCytOez4KR6PGkBkLIhhDAtRV0oGAun5ofdNEBHdDU899RSqqqqQlpaGU045BatXr9bdd+zYseA4Luhn4sSJdJ+pU6cGPX7uuedGcmqJh+dpYNLKwCD9BmzZ5YI0HfApV3fxYtVTwGODhbTNL/8R/fHoADhUKioVSmEJdzMQf3HvsYDNKSks6iJbxDDwe+lqJmzRuMbdgr/YYqcDdonWAJSWJ/yWTbCANMlmOqxKqVeujmUUhD6HWNO4S5CArU4q3dPAvVAuISCqwNvWEGX5AdBBbVOgErvcYlCeT6awxLsOy9ZFQGstXGnF+F/gNO3icQMmCv1yjuwE/tlD+B5zugGn3ig87lcZLJEWjtsmlpvv9yvAmQVANvEViBO0warDHjPuTy3o/Sq8rrw/Tsju0QZciC5vCMVi9zeCAZhfJQSpyl5bobBkFgK5PYS/dSpbh8XvFWo1kfFn22eaqdJSGraOAepqkdytYmxNWJeQ2Swh8h5FA6NQHlOk4RIK61LXM1jaPUITXs1z9ikayIatoLxPnNflvYmSjGmD5a233sKsWbNw1113Yd26dRg6dCjGjx+PgwcPau7//vvvo7a2lv78/PPPsFqtmDx5smK/c889V7HfG2+8oXm8lOPQFqCtHj6LE+sC/XCgWcdgsVgEny4Q/0whdyuwdI70/3fzDXVhDQldIQyVtqlWG4A8hTDM6lQ+uEPHoAAUN5vXqMIi9utAxTCaAaLZYJFkh3iVqk6rnhtDPognSiUjEFdCyQChZgZkMSzhSr+LE0ckcSxh05rFlemPloHohNgoMpFpzWIcVFO/i+GFTbufUFoOMO4u5bbzHpVWjQGVSyjSwnGk8Wm/c+gmYrDszhIVll0rDJWkj6oOi88juQ+JwSKeh8cXoPFZmhSJqc3kftfA7QvhMiOZK7JeasU5Ovd2hTiWROoW+vk9oRFfRhEw9Aph29IHNM43zGe5b7UQJ5dfJbgTgeBAYQKnp7CEGJNczcKCA6DjZ6GmSyhgzKXuaQcObxP+Ft3DRLHxB3g0dyoNcKWCI2sgG+7aIm0aKk4IvV8CMX03zJ07F9dddx2mTZuGgQMHYv78+cjIyMCLL2rXtigoKEBZWRn9Wbx4MTIyMoIMFqfTqdgvPz81JKiwiO6g5qIRcMMRusV9onoKbXhLSKMs7AtUniKseFc+Gd0xVRY9AM3CcYZcQh1HgH1rhb/Fwd2YS8hgDAtZXZJYG+iUSScGi9+tmER0VQV5po0/jKoRaw5vFX6TQnCQVmkhXUKAdN1FkCkU1iUkKga7MofBpWGwtMUz6NbVLNaiAOzDLgMA1LW4FC0cKMOnACf+HhhwHnDFm0KJcYuk3ikOa7SSq5zWOuke6XM23VwqXtebLP0AeybQ0aAs8a5DVJVuD20Srum0XJqdmGa3UrdcyEyhypOE33v1XVchs4TkrTtENBUWQJoII80U+vFN4fepNwJn/V2Y+Pd8LRlr5HzDuYSIm45kLiFEHyi5G1ymVoRUWMj55HSnymyhpkvIRw2KkN/7wU0AeCHgNltw9zpsFtpNXbfarWzRB4RRqnleUoVIvFEKYOpu8Hg8+P777zFu3DjpABYLxo0bh1WrjPUreeGFF3D55ZcjMzNTsX3ZsmUoKSlBdXU1brrpJjQ0NOgew+12o6WlRfGTNER3kK+nkPYVsjx4kZgtQKzjeEECQk+6Fhg5Xfh7x5LIjxcISJIpqYYJ6LiEDPTt2P01AB4oPo4W2QsfdOszXlKaBAeThm6QKTjym9km67khLydParCoJ1mFwpJog0V87UKpuVmBkSwhICpDOWTQrauZTtINhSPg4oXPGL5OmmUS1xYHP7wmTMzFxyG/ajjsVg7+AI96rTgNi0VQVS5/DaieIGwj7kadGBZTlW53fy38Lh8KZBXTzaXidX2gzU/jIxTNQ3XwRlM4jsQ6lQ1R9DQrMtI9Woz5Qt1PukGsugZAwC90gQZorAYg3dtH2t1UkQAA9BXnkZ3LglTOsPjckqEx4Dwgt5vUIywoiD5MZd79YoCyrK9R2BgWAOADxrKESK0Z2WdSKCscx9M6LAZ7CdHF42DFZhJ4G0qllne8D+kSOrJTCL62OhWLpGRj6m44fPgw/H4/SktLFdtLS0tRV1cX9vmrV6/Gzz//jGuvvVax/dxzz8Urr7yCJUuW4MEHH8Ty5csxYcIE+P3aKYBz5sxBbm4u/amsrDTzNmJHwC/UCAGQOUC4+Q63eWiWQRDUYNkav3PyuSXLeMBEQDSkcGhz2GJpujTuElI1rU7FhBlxDAsZ3GW5/SUyBUThY5evDgIGVh+BgDRAyFYGksIiGxjlBcO8wXEXQZOsPAYkkGCXELlmiqTPn2YahMoSAgynq2oRsnBczXcAeKCgD7KKusMFmVEjxrEYqZQbEe5W4KtHhL9PuQEWq4U2fTPcBJFcW3pZQmYUFmIkqOTzUvGc6lvckuqwI3w9FpreGolLiKRvlxyn2FxspBZLbjehyR0fkFRQFbp1ahp3CwakLV1yf0MIDrdwQIBXuS/LjhdUB2+HVKDMKPu/FwzjzGJpQj35euH3D68Cn9xGdw2Z1cTz0gJHY7xoc/tobykASoMl4JdU31BqhSp+BZAUFq+fhydgocczFBB7UKx7VDpIsTmsKiTLQgLCGFnETVc2OPEJBiFIaJbQCy+8gOOPPx4nn3yyYvvll1+O888/H8cffzwuvPBCfPzxx1izZg2WLVumeZzZs2ejubmZ/uzduzcBZ69B7XphlenMRWbVCcgUswp0B8yi/sLveLqE6n8RVozp+UBupRDcViwOXDXGVLAgiEVfOpDGTwDQjGEhN0ToiHxSI+V0uom4hDq9flq7A4Ay6NZIDMuRHYJxZUtXGFfk+C0un2RQWqxCIDSgUlgMGCyJVFh4HmgQVbkiucIirlzDuYRoumqLaaM1ZOE48j32PA0VeWmSSwgAvJ3wB3i0i4N9TF1CPjfwwU1Cx9+C3sDw3wGQ9RQK5ZaVo6uwRGGwqCaRshxisLikTrc7lwmpuIDgjvryfuDxYcCnf6FNKsnEZaiekRqicpDxRoTUYgnbPZqoLFsXaT7s0qtTQybSon6Kid1q4aiioFBQOU76TNY8J8RmGIUYOFWjJBWp52nA6DvE4z1PP8uQY1LLfuE64qxAifTdZTqstDWDQrHg5AaLz1gMiypDCBCuLTJfdBJ7SB50G2r8pIuXasVm6lZXf79apf+tFnBciHMm8SsylToVMHU3FBUVwWq1or6+XrG9vr4eZWVlIZ/b3t6ON998E9dco516Jqd3794oKirC9u3aE7vT6UROTo7iJymQLpZVp4Oz2tEtX6cJG4FMoM17Q9+c25cAz58DPHeW+QZhxDIuHybdyMQwiNRXTCXI45XbtWJYwkmaHUck91JPSWFJd0g+dsUNJwsYM1Q/gKyWygYrjKucdBs9J8UAZCOBt8FxF9nyQFGvS0jDJiTSYKE1VDgppRxS4F67x69cBaoJl656eJsQpO0Nvm5DVvwl11PP09EtLwM+2OCD+H15O9HuCd3pOSL2rQXmnSYU/rM6gIlzqeHRLS8DgImuzXoxLJFUuqVB0QMVm0tFg6WuxSVM5N1OFOIfNrwt7PDhdGDFQ4KK+d084JvHAMB4ATEtiMKikvLJudSr48TUiOnI+G4+cF8ZsESZZahbiO2QaLColB0gRNbNECH2CNs+B96eEvq85BCVtpessjjHCc0JyfcqXs8hY1jIeFFynHCf0ENx1JWl+LwU3Y8lg0V3ERXwSwaG6togRhyNkZVVug35vR/WNkg13d7yc1aMoWHc6sQAlxlZqYCpu8HhcGDEiBFYskSKhwgEAliyZAlGjgxdCe+dd96B2+3G7373u7Cvs2/fPjQ0NKC8vNzM6SUeYuWLUm+FuMLTVVgyC4X0SkA/xdTbKbQy37dakD0/+oO5jBQNeZM2GyMGllm0Am6ByArHEZWnqFrh6wekbIKDWgNEwAsv6SUUajVDAm5VKwOO4xSpnRR7sMHSotVHqFml4iUyS4jEPOX1UAyq2U4bHXiMu4VUBgvPA/8+UahNsu7VoKe1u4XBPtOhMjg8HVJxMlFhAQAXSByLCy3iSOywWfRTSs3g8wDvTBXeQ0YR8Nu3gT5n0oe7iedg2GCxSteWHElhMTg8upql66NU22A53OYWFMJhvxUeWPeKEDux4S0AnFQTRmwX4TFTPl2Ot1NKv1cZLFTtaQ5jsAy8EBjzZ+FvX6cU3Cqir7BoG0pAiJiQHqcAF4tVh8kkGY6AX7rPKzUKmhHVVFxUhExrDqEkkIDpumYdg4X306BbXYWFusnShPtXBllwdIhDSUBmAOl+7+5WQRUCFGoroOP2lp+zzCUUNnGBGr3BxmcyMW2+z5o1C8899xxefvllbNq0CTfddBPa29sxbdo0AMCUKVMwe/bsoOe98MILuPDCC1FYWKjY3tbWhj/96U/49ttvsXv3bixZsgQXXHAB+vbti/Hjx0f4thKAPOhLbLtdnitMfrWhBgRykR3aov346uekCxIQXAE/BE8kumjdgL3PFBpsHfxFSAM0S1iFxUQMCzFYegYbuJqpzbKgW1MKizz9mhxfq9YLMQDktUO0XEKNqi7biVRYNOJXAMEII8XjQjZABPQNFhJwCACuJsVDgQBPy9QHFVGrWSV87zndgbwe1B3TyZPVbQeaxEaW+Rkx8oGv/49gGGSVCg3pZMYKAEnhNOoSogpLlJVuiSskp1tQga3CTAdsFg48LxrKg38jZO8c3gI8J57/8ZdINWFIR91IFZbD2wDwwsIos0jxEInxCTk+AYJSceZfgckvi+ekbdAFGQA6sTOALEZNS93pJsb9GHUJNWwX3L72jCC3CACFGxmQBd1qGaAa7hqCFH8kN1jUMSxhFlHye9ei/LxIHAs1WGQxm7oGC7l/M4uDakHpJy7Igm4DBq4rV7M0BxVrfL5JxLTBctlll+Hhhx/GnXfeiWHDhmH9+vVYtGgRDcStqalBba2y5seWLVvw9ddfa7qDrFYrNmzYgPPPPx/9+/fHNddcgxEjRuCrr76C0+mM8G0lgL2rxaCvErqiKM/VsMjViHURSLCugkBAinC/4CngXLEi55f3UX9sSHweSZqWKywZBZJfessiYOvnwHfPhj8eIMQ8EFeIyj8fKoZF94bbIxosGr0pNH2wZuqwyFPxNAwWSZaWfT/UJSQVj2vV6iPUtFt5MNUgHleO7BR+E6NDRoGRBoiA9N2pC5d9N0/625GleIik9wJAhtpgIZkuvccCnFDR1W7l0MmT1GYXNVjy0h2ICd+K98YZf9TsHGvaJaQXw+IzWelWxx0EABYLRyfrumYXkJ4HnC2rCWNLB8b8RaYKCOcScR0WshAqHqDIEAKkBVWdegWuBzE8VMY5dQnJDQCel1RjlasCCKGwANJ152kzFhRO1JWyIcqYOoJaYSGZi1qTNIkN05iYy3Jk3xuB46TuykZcOMSI0zCsyGKj3cOLh5PGUV2XDVFbNT7jEr3aMfIYFp8BlxC5hrIrhOs1hYjIsTxjxgzMmDFD8zGtQNnq6mrd6orp6en47LPPIjmN5ELdQaPpwGBoBdPvHMEo2bZYuDnlg8qerwXLNi0XGHyJcKF9v0C46JfeD0x8JPQ5Hdwo3KRpeYoofQBA9blCjYQv7xPS1QCg79lSrxk9yAqkoLdQ5l2ORvPDkGl5ng4pxkajeqLmKoy8ht9AjYLGXWIqnkN7ladVwEqjeByJ28iRB5qqlSl/Ag0WUnSKdPyWYbjabT9Rrdy3RqgZ4m4D1i2QGlACQRNThywuJl0dz0F6r4jqosXCoTw3Ha42YrB0oLFDOF5eLBQWV7OgSgBS3IMK4pY60NQJnudDBxUCmjEsXn+AyvKGFRY6UffTfLg0Nw0Hml1CphAAjJgqKFudR4Cz7wSK+koF18TvwFSjTznkM9I4l3LZ+GTs8wmdRaVQWNoPiYHrXFD3a0B+b2sZLIKhCT4gKJ3y7D0tVFV8gwgyWHTS1P0+yX1WEDwOKuKP5HBW4VwDvvBpyHIDUgWNQfMGGyy6CvUh/e9X9zPW6AZtKAupJHXSmQmsl1CkqAZsAKigLqEQK7yeZwirqtYDUvApgbS8H3ih4Kqw2oFzxYq1G94OP0nK3SHqwWjAecKNRowVQMgaCYeeOwgw7xLa/72wb3Z5sEEFyeCrkyssVrlLiNxsOgMtef+lgzRT8YqzQlS71arDouUSIqvBRLqESGVkUrFWRpGRVFVAqODZXSwK9uQI4KmTg4sJqpSGDjF+Jd1uhUUuebc3SEqWrEBYRV4aOmUxLE1iDEtMDBZyHeb20G2LQGLIOjx+qu6EREMh7JSVJDDcrblJvDY0rmlAioWgrgWLFbjwKeCKNyTD2qq8lww3EVVDXAZaE1qOVO220cjnQyZ+1XWhaQCQ+yOnArAFK+O6lWMBwbVDCOMW2lbfis49Yrq1rsGicgnpxbA01wifty1NcOepKNNyCQGK4nFhXeDUYAlWRIg6qjZY7FZO35gk329h8PdLVKzmTq+ytIaiDkuYMRRI2fgVgBkskeFuFSZfQFBYRAwpLPY0yciRr25dLVI3WfkKstcYwS/ubtGti0Ah6oVWZcLCPsAlLyoHByOBozRdM7zBwvN86BRCWlFyZLBBBZnBIjf4FEG3YWoehIhfAXQUFlI8TqOcvCKGhUxKxC2TKIWF52UGS7DCQru0hioGRhgg9u/ytAmZKr1GAxc8LRQYBILeU4dX+ByC3EG7V4AW/suWajJV5KXLqt12oElUffIzYuASot+tftZCmt1KDThDbiFrsMJCBnqOC5NaKodM1vnaBotkiIcYF1QuoYi7NWsUGCQ4bVYaNxHSbU3PiXw+SuNcM4sqjNGmG18BCAYcGZc8bbqns3LHYUx8fJmsAqsxhUV3TGoQXa35vaT+aDLK9BQW0dDl/b7Q4x3P66YgA9Jio5W6hEK4rgiN+ouX3HS7diakwq1utJIumMJy1LBnpTBJ5/WUujBDGphaXT7qVtBk+FXC71VPA/Wi/3vDW8LNWthPyuoBhJujtxicF65abbjc+UEXArM2CRkWgDGVgPp4g1cIQW3LAzx1QWuuDEnArUb8CiD52BX9YDRWB7oxLKQEtjqbSURTMtXIEtKMYSGTElm5xsJg8bqEtPVQx2o7KDQ9BBeUZQCEKBalxYipwMALhMDPS18Brv4IGH5l0GRJIC6hoFgOkm3We6xic0VuOlzyGBZRYcmNhcKiUb1YC1OZQrKAboK0Gg9Tp0IOcRfqTNbUFRPqnCxK4yAihSUQCKmwAHLjycTnwwcUrSvc1CUkO7em0EabPK1ZMzzAIVY+11FYmju9mP7aOvTi9yGd86Ad6XDlBhvwABQGi0/m4gtSWEirCh23OE0DDypmKRzH5/OGHu/a6oUxnbNoGhjEJUQNFvE61P3OeR44slv4W2PxopsJKY9hMRJ0q5MWnwowgyUSSKVKmTsIECY4sioPuYIZMBGo/rUgtb56IfDz+0J3ZUCo1qgeKPuKvUmIn1sLv1eWO6+tMAAQgqiyxRTKcAYLz8skyOCAT7WkTgZZQOOmC/ilpoQ63T9JDEJ9i0sq4S2vIRCu0i2RXzWCHwFZ2p88Roa6hLQq3YoDtrtNiDcAJF93LFxCi/4MLPg18NVc/X3Iiiq3UkdqN+gSAgSl7tJXBKVt4AXSdhqroHxPpLaLfsCt8vovlxePk8WwJEphAUxmClmDDRaisATF7OjhapayqzQMSkBe7iCUwqI0/g1VPFXTsl9wbVps4Y0nQwqLvOaIZMxKLiHZZ9QYWmEh12mn16+9mAtjsKza0YDGDi/GZAmd7jf4e+Gr7TqJCDLlzC0bk4JcfHRs0zZY5C40hYtRvF+8PmmbppFBYpvyegC24HuAuISIwcJTl5DOd97ZKLn0ZQtlOZo902RjqNcXZtHX2QS0ikkzKZYhBDCDJTJ2igaLrMkZwVAcC8cB5z0mVFZsqwfenSZMTBlFwNDLg/cnnU8P/CC4jrSo/0VqeKZhzSvQkXqDaD8sK1imcUx6Iwg3gcJgUd909b8IDRkd2cHZRiIl2WmwWjj4Arw0AdPJ1EuPr5lC6G4TfNKA7o1GougPt8lasFOXkJAlxPN8cLG0FjFLypkrxU/EIkvo+wXC72XBHWYpJEOooErzYRKXE7I/TDjCKiwqpalxlxAP1fN0xf4VuelSx2afC800SyhKhcXnlqR1HfVMfg6AwfL8smuLYLpoHJmoM4oAZ5bmLsRgCan6qF1CkSgsRA3N76WdPQO529WIwSKbZMWxwh/QcftSlUnbaMt02mhl19CZQtoGy/d7BOPkzBwh3XYD3wtfbKzX3FeusLhDjUnEoNAIuAUERYYYFQq3kFjt1ueRGSyaGUjbQx6fuITa3MI5BgJh+rAR13B2uW5gslQaQlulDusSIupKTjfNTLxkwwwWszTvF75UzqKIXyEYrnWQXQpc8zlw6nQhq6fiBOD3i4A0jaq9ORXCyoUPCFkeWpDt3U7UjA9RoPLx6kIGwLxK7RtE5RIiA5mF0yhMROJXKk8OqkdAT0uWAkonHNkqOGSqJ5nQMkt0gzILsxzgOGHQPSKu/qnvXMwS6vT6qbojGSxiTYKccs24h7gSIuAWkMqtR2ewaKf3doiVajPlCgtJx+82IuhaLc9Lk7mEOmVZQlEqLE01wrVvz5TUQR3CVpuWo/G+O82W5aexG9oTNSC1DNDtJA0EuYTIxGKq+eHh0O4gwGCtKPU5AUGGFKATw6LjEgKAkpwQxnUYheX7PY0AgGq/8B5/CvTGks0HpYWHHNmCTJ7SbFEvdELEgxBoppBG8TivqIhojndAWJcTUR69IDExYWJYaLZgle75asbpadZh0ZkjSPxKCrqDAGawmIeoKxUnaE6MhmqxEJxZwLkPAH/eDVz3ZciBhrpR9n6n/TgJApZ1HNXFsMESwh0EBBssoVaF9PxOCvmSQZ+fzO0UcvVLo/H1ZUy71YKCDNUEryocR4rGWS2c5BYgEmlOha4aETeIwqKR0gxIsQGNHV5F63hT6ChuHVouIeLW0yj8V56bTrOEfO6O2GUJ0aDWqrDGeLdw1ablyGNYxGAEl1Z8hqFzCzFRZztpJ2nNoFMgqOpuZApLmPsV8rgMIwaLsm8OAEX2Cf2MAgGgSaz0q+MSAqRrVTu1Wd9gcXn9+Hl/C2zwIb9VWJjssPfD4TY3NuxvDtpffo/KY5IU8LyknGqkYRPI9bRPfj2RGBavVMlZkzAKjsNmQU6aDX5xGubDKSwhyhsQNDMh5ZVuwxUkpG711MsQApjBYh4SR0LcNCokhcVg8SpALEYURhUhJaiJUqGGZBCFMQgAGFcJSJEijYwDAEExLO5QKX60xXqI+BoA5WTCoQaLdLO5QvUEOWRsZVCsDrxVFY5rkQXc0qBLMrBlVwSthCPG06H6XyedM8wqMD/DQcuChy0ep4dOxVdNl1AIwzMnzQa/VSyG1d4mq3QbpcJiYGVJMOR+IShiNJQTsnGFJXTALSDUqAnbSVr1HUSUJaTRIFONqRgWjgta3JB70GbhJFWh/aBgaHFWwV2hQ7HW6p9ADZbgLKGf9zfD4w9gaGYjOL8bsGeie28hTm3tbo04Fg2XUJAR0NEgxa3lVOiec3etmChx3PMQg0XvO6IFH/VrXRVlORGAcP/yorGq+52HCLglaGZjycbp8HGATGE5eggEpIBbVVlwQoUZydUMRGHZtzY4HbmzURqsuo0IfyxxUgmvsBBJM5zCIgxi0qpQNdh7OyXLPUzQZHmOKqNCtgp2h5pMDCgsgEbFTVXhOBK/osgQIgZLLF1C5JgE4vpRQ2NYtAcpi4Wjqc0Ru4V0FLdO0SWUQT5vd6tU1bVbsJLHcRxsTmHi6WhvRRMNuo1WYdkt/A6hYhDIBHO4zaOsRaGFhsuDVrk1arAQd2GIVTogjQu6hpQ6FTcShSVESjPBVAwLEFRcz62lcpLPILtMN3YGCKOw2PUVlh2HBCNmVL7gFkJRPwzrIbRAWL+3KfhYMsVQt/txsxC8i8wSzWB2QjctA5jEsPiIwqJxrQQCsntX3+VUmOWAn5cpVQilsOwWfodyCWkW35QF3YarwxKi0F0qwAwWM9T9KGSLOLJ0lQzTA4JRio8TYl287VKlR8IuMa6gsK9u/IYCo0G3xC+tZ9HrxLAEDQ4HNwp1P9ILNAs0ySEKS61aYfF7ZS6hEBH5odxq0JDEVYXjSNE4RQ0WLZdQtEG3LfuU/5PBTU5no/ADhJaBaWpzhNecThPAoLTmAz8IsSS5lYLxpkFaujDxtLW1goQXRJ3WbGCgJuSm22nMTVi3kLy4oPjeTTc+pPFNoa/rbuEyhVTxNGEnFjXeTqkBY4h7gNQWaXP76LUeElX2ElFYFJ8PNej1lQpAJ76CEMIlVHNEUCMH2cX7sKg/hlXmAdAzWGQuIaLKqg1QamiG/t6IAbyvUaaIimOSzyd8JpqKb2utoOBw1pDqW0Gmg3Y450las576QcaM3Erd42m2QDDqEvK0S2Ndkb5bMZkwg8UMxB3Ua7RmJVXApORqBossyJeklRI2fyL87n+usWMZjcMgA6De6tFoDAvt7zMkrOurQu1Skw2Yuk3peF5aMYUIfgRkPmkyAKkKx2k2PpS7hIwae+Fo3q/8nwToKbaJqktmiW4GCiCrdtsa4TmFyRKiMSzU7agfJ5WWQRSWNvrcqDs1y2NYwsBxnHG3kEJhidAlZHCyDtvJXVUGP2RBMi0adgDghcyOjELd3TKdNuQYKb1AMNL5mN4f+u4gQK6waLxuCJdQzRHhM+vJk4Z8/TGkey44DtjX2Bmc0q/hEgpWWAwamiFcQn5fiBgW4irM7R5SdSrMciKgimGx6xWhozE3+ucsz4QMLg0huYQ0i2+SRVN6flATz1SBGSxG4XngR7F0ft9xursRhaW500uzLGIGKdRFAn8BYYDbJvZiqv61seMYCbp1tYgpzdC/qTntOixBKwQSvxImJRUIobAE/LLVnWoyaT8s9THJCS3NkxXTXnEQlLKEiMKiqsECxMklpDZYNFxCBrIYAGgXizKDRk8dQJYlRNxjJBNLJy0dADIyhX5TnR3CxBN1SjPPm1JYAGmS2ReuFovFImtkp1ZYDBgsfq9Q2A8Ia7CQc9rb2KG9g+qe9IYLjlRDXMKF/cIuCgxV3iWorg0alKypsISe/ENnCemnNe8VFZYSt2gEFPVHdpodfYuF5/yoVlkUdVh04t7CLcZEyALnYKubHiso6FbrOyLHD7OAKsp00KBb4lrXPF5Hg3htcECWfqacIhOS9BdTND8ki0qNa4S6sML0l0sizGAxys5lQmMxRxZw/GTd3bLT7DT+IeYqC4mb2btaqDsCALuWCW6D9AIpMDccRlQCMqGm5WqnWgNBzQ89JC1PPTgcCj/REcpl/Tt8/oCiND9xCQUVgCL1V7LLNAs0yaksEAwUqrCosoRa1TEsfq/Q2A1QBd1GabCQAS2zRPjd0RC8T5j4FYJULCpSl1DoLCEazxEm6wEASgvyhEO5hc+3b2m27r6G6GwU6vcAYQd/Qg/xOyYTXUiCJuQQbkc1rXUAeOEYpHq0Dj0LhXPa06BnsChdQmG7nqsJU+FWTpmZOLsgl1AIhSWM0SavdhtECJeQ8D3yyG4T7wexU/GQ7nkAgJ/3q2pTyRUWvT5CBl15BZkOev1Td544Jvn9RhQWffcNOX6QwaJlTBAFOask5BinmQkpj2EJFXRL7+8wdbySCDNYwrH6OeD7l4FP/yz8P+y3+hO4iKnUZjPk9xJWmQEv8Mv7grqyWGxVf/zkkNKjAiMuoebw/lLDLqEj4Sc6QlGWEzYLhwAvBufJgm51V78kpTLM4ABIBsv+pk5BMlVlCQU1PiSTktUhSO1GU8LDQQb5ssHC786m4H1IVkCI+BVAWUI8IjQqvgIalW7D1JUAgMoSwR2Rxgmfz7DuURafIgN/Zkn4Lr4ixGCpMWKwqAwFUwqLXHnT628lUlUoTMh7j3Ro12JRu4TMKiw04DZ87EG5Vm0RPYJcQtHHsBzp8ASn4OsYLG1uHxraPShBE6zeNkHVFSfUAWWCMby1vlX3nKlLKGiRYyyGheO4YLcQDboNUUo/TCE9QmGWUzJY+BAKi8HPGNCo6K0oHEeKb4ZwCYW4v5MNM1hC4fMAC28HPrpVUFcyioCRM8I+zXDxOLNwnNSo7n+3AO9fK3R8Ts8Hxv7F+HGMTLpGJFOVwaLpL5YHchm4EawWjk7Atc0uScWRB90GdV0l8mt4g6UsJw02CwevnxduaHWWkDqGhZx7dpkwKelM7qZprRN+kzYCJLhWjkGFpVScCOq1YgOMoHM9KIJuO5skFSjECiw/TzBQ0iEca6gYHBkxNOA5dHyEnEpTCovSUDBV6dbgKh0QrjunzQJfgNcOvNVp2Ge4cJxB9yFgcnxSK1A+jXuQfg6hJ1OSgs/zGin4xCXkVRos5DscnH5Y2JAntajoLxosW4IMFgMuIXrOoV1CgEbgLVFYiMES0iUUekwqzNJSWLQMFuPXGnG9HQxSWCSXkD2kS4gpLF2TgA8YdBHQ71dCw8KbvjGUWmmo2VmkjJgmBUT98l/B2p/wL2PZQQRyQ/tCGSxEYTFhsGgVaSKxGWl5hs+R9BSqbe5UyJmaqzvAlMJitUhBmXuPdAa7hIjBQlxCNGVTHIxjFXRLDBaSPkj60cihk1BoQ48qLJEayDpxOR1eorDYJHUlqxRw6rt5ONEAdMbKYJEHPBuEuoRM9RMS3nunXmB3qHMzsOq1WDjqFtrdoFFzR34ePC9VujVdwK4q7K7lZmpFqTLI3OoYFnkwaJjPwWrhaLfooMBbHYWFGCzHZ4rxdLKMm2rR3bjrcLsUXwIojD9N1TcQUGb+hSEotdlQ0K2xMakwUwq65fgQvYRMXGsl6kwhrTosoRQWFsPSRXFkAJMXAFe+A1zw77BlwQnURxxpTEEonFnAxLlA5alA/wnAtE+BIfoxNZoYUlgM1JdQxbBIqxnZYG/AjaCGfn5NLoWioRt0a0JhAVQrJpVLKKjxYYtqYIuFS8jvBTrEFSOpKKlWWOTKVBiFhayYD7a6tUuVh0Mv6NYtK83fYHAwE7Ou0jk3uuen0wymiDExsRCIwnKk3RM+dTeozoiJtGYTkwgA9BTdQnu0DBaL5M71+300w8OQwuLtBNpEA9iAwWI4KBkIch8HKSydjUIPMyBslhAQIotSx2Ah59jPIRaIk7lYSnOcQrHCAI+dh2TP08wSko0ZHQ2SQmpgTA9yCRGDxa/jEuJ5w0G3hVnytOYQcUsm1TxAXi1cWvTpFiT0dBgeb5IJM1jiQEW8YlgIgy8GrvkM+O2bQA+DgbZyDBks5mNYNP3FBgI11ZDP74BMYQn4vXTVqWuw5BoLyqzMJy6DziCXUAuJYSEKS6tqUqJqRBQuIZJZYrFJ8qu3g54DACkzxoAyVZTlBMcBvgCPhvYIDCmd2jIKlxAt+x5GLhazrtI5Ly4ZEV5uD0uLeZdQltNGV/I0G0wP1TWsaxRrnpvxSQQAqqjCouGqkjUa9Hqk60AzxVUNiZdw5hhKRyXX/77GDvB8GANXx6Cj9zgx2jIKQxZgI9BeRmr1WSetmbg1unFi4LtM4eY4DgPKhHjCLXUyt5BGt2aF6kuMu4wi3fIUcrrTz0sZw6JrsLQfEhVbLuy1kZ/hoApLwB/CxWQwEwvQqLYuT2v267iEyHjvyE7ZlGaAGSxxIWwZ7mRjJDWXGAGhbhAjMSwRBHJJLjWXwmAhBK1+jbivZPQgGRtH2pWF43gezer+N+oaE7EozU8GzMwSwSAhqbVyt5AJf7LdaqFKhqEeMWp03FydcpeQQfcUcbHl23yYOa6/+XNR02reJQQA3Y0G3hKXhypLyFClW+LWM6i8EoVl9+EQLiEAbo/0PRhSWIhxm9czfIsPCE0qOU54r4fDtXNQuczcaoWFZNBllYY/T/G1AeMKC6mxUuwXOzOrirD1LxNiXxRxLIosIY0YllbxWAa/t2CXkDgmiS4hp/o7ImNndnnYrEWrhUNWurBPQM8AApQNWMMQpGJpdWtWu4RIpmVepaFrKFkwgyUOkFWEoToHySCcwsLzkgqQHWIg0jVY5C4hgxOdDFqLpUVmsPgkRUMRX+D3Su4UgwNQlXziIIXj+ADg91CDJTc9ji4h+WdrsQhGC6B0C5kMgKOBt1EZLOpeQmJpfodVVrQqjNuN1LURDcCoiUBhAUykNluUE7JmnRE9iOEZoi6GnN5FwnVHSs1rngcAn0fK9jJU6dZAA0Y5TpuVug326dWFIagWN0GVgNtF12Zm6LRuAmlRcMCgwULiMPLc4nWgcrGQOJatmgqLPEtINmbQ782YkUVcyHWqUgu6BgYxZA1es7kZ6YrjacawUCPLiMEinq9GA1mPXgVlE3GAyYQZLHGAKCxNHV6aGppS2MJMuu5WWqqe1gnRQtVLSDMi32R8CSDru9IodwkJ5xrUJp5krnBWaeIPQy9x4th1uF2aYAHA2xlssOi5hMDT922aVtVERyRYeWqzwQwhAvVbR2KwaKhGgQAvqQ0OqzJbKhTEAASk5nLREKHC0qNAuIbCKyzKrK9Oo2nNRo16GSSrZc+RjuCikhYLdTV4RYPFYbVIDThDYbKwHiAroBi2uJ7KJaQ2AIjCklls6HWpwhLkEhKzhHwuheF8uM0NK/zIcIn3jMpg6V+qkSmkKM2vofqaVMaKs5xwWC3wB3hF5qKuwdImGhcGDaK8LFHlJWnN6uN52qXsKQOfM1FYGtrFflqycZq4hGx6qpCJcToZMIMlDuSk2Wg/k5RUWcLVYSGDkCMrZEl4armLNxrJEqI3HM/LBgfjK+RutIGdGx4oB4eglS8dMIvC1sIgVBUJRkpjhxdNbp66ZAIemcGSYRczIMhELZ6/3OcdqcpCBjQy0VGDRa6wGE9TBaKsxaIRw9IpaxyYYbcEK016yGuleKN0iXraZdWWI1NYwhoskaY1u1tpoLbRiakoy4miLAd4HthWr6GyiNeWy+0Wz8Hg8NxkPEOIII9jCYlenRpyj7eLRptRg0WvaB1RWABFavOhVjfKcAQW3i8YTyo1ixgs+xo7acC8MuhWo7ZJmzmXkMXC0czF/U2dwQaLevJvNWmwZArHtkAnlZ0Yxrb0kBl69HgZdnrt1MtUarlLKOg1mMJy7MJxUjv5uKQ2R0s4twa5ocMNQuFcQh1HTGUQEPIz7LRYWWOnMODwor84aCJpMzdgAkJMBlEkdjVImULt7a3Ui5Gbbtc+f1lwZMTVboMUljzhdywMlkgCvVVxHADQLioAHAekBTqkSSTcIGy1S9dFtAoLMZLsmUJAqQkM12JRx2ioJ2Q9yD3iyFZOtmEgQaKb61qCHxTVDLdLuOYyHAYLQRKDxWAlYECjRYUeOi6hYIXFoEsoT1IC/fKMNqtDum5Et1BADCLvzslqsKgWJfmZDprGSwvIyVxCQQ08AUktNOjKA1SZVVxsFZYCUWGxigZLplPdeoTECRUbii/hOI4ahgea1AaLXtAtU1iOaXRXEqlAuFoixAgId8MFGSwq/z+R8zOKwgafyeE4jga6NXQKg1pAfI2gVadJHzpB6RYiBksbfQ2nzSqdf2axdP6KhnkRGizhFBafWxpADBosxACLKJVew4DtlJXlt5DzdeaEVtwIqv5MEUPdceWmAwF70BYMncqJUY1OrxzFBKeF+js0SLXoFtosj7kgiPel2y18bhnhzoFA1S9j2UqAFJQcVmHRcwlRhYXcf8YWDCXZabBaOPgDvLJEP8cFxbE0dggN/LqTDCGdrsfkM6VxLDIFWbOZaav57657nlghW+6m1iv0RsfPEO50GYViw0JisPQpVt1jdAFp7HiArNp6S6emwRJU6ZYoLCE6S6cCzGCJE6YajCWacC4hesOFU1i0mx/Swcxk8JkcsgI83CG6JsTVTFBBL5M+dEKv4mCDpa2NNOwTPx+1OwhQxBpE7BLSi2EhWUKNewDwgkvO4PsixfAiUvRk7Q+IxKTo1EzjSAx+j6oO2BGj9fkbpDw3HTYLB48/EDoQWadXTliXEP0O/7+98w6To7jz/rd74s7mHKTV7ipnCSQki2CCdEgCA7LxHWBMMhYHhjt4hcFgY3HGvhP2YQzYHDgcBs4+kkk+gggCyRgWCQkJRZSlVdggbY4T6/2jurqre3p2J/SEXdXnefbRame2t3q6u+pbvxifYNk9iGAZUGJYhhRNAC3+yGr6xPA5jY62FksEl1C4hSW6xdQmSyhXLCLHjYXrDA0QWQbTRJcSpxbBgjTJGMfCCfAetTcYt9GIMVga0D6vhrY+dd4jQ1lYonQ5FeVSMcQEywRj/60YBRDAZ6py1cJDQS1LiHcJBf3aMy5cQqcmVbFUk0w10bqEhrSwGAvHGVxCUbadN4OZYE/0Ki4hRVxFjmGJTbCwjI0DnGDp66UTnpYhFKHkeIS6JVFjnICMFhY+4DZKywLvYx+ytoYRW7jVSGdKjzFIUattY5WFJXrLAcMmS/pFJhIGCwKzLA1Z6TZGsz9jiuIS2tXYFX6dlLGwoNuoLCxs8ZUdMVW7ZjEsx9r7By82GOYSMqR9x/H8MXEdVvbBYGFhFpg6++CCZaJRBHJjZoJFdbMQEpeFhZVCaGjrHTqGJcZ7ozhPEywVeW5t/mHE8xnzmUJmdVj4LKGu4zRL0uaKeR5NNUKwJAldtdZMY6g6LL3xuoSMFpb4d8isWFOzIljY3wi3sCToEjqhpTb391ELi5YhFCHQNJo6NpEgRNsRs8khomCJvqcHWwT6fEE1cDhqeMES0i/cHoc95oquuto2iRBnSjOjOprAW86CQAjhCscNMTXGKuIUJpTnwC5LaO/zh6f2KmPxeWOIYeGD2mNwm1XmU9eMLxjSes6YYRR0fs1VCCCu5y+idYe5ElULCx2XFsNi7q6YosYFdVMRaGJhUV1CAx1aXFoMYpPV0Glo61MtrESZk3QZSIRwgiU6i0hpLv08ZITU9g06ErCwNBoEi9esqSbv3owycSFdZPbohjERS1BnAuoDHWGiijaQNayXUIQqmDGUVWewGJaWHiXyPxQh6DZel5AiWA619oIoC+xAP50o88OKxkUSLHG4hHw9WjAqm+SZYOlTyo/H0MiO4XbYUJJDr2tUJdd5dIHE9JzUGiyuDLCwxJjSzIiqFousBRz7giE16No1lEsojkUEoNeJZbZsO9qhf5EJllgsLHE0hwRoWiubo44MFscSwSWU5ZSVdFvld2N4/iJmcKkuIbpxYBaW8hArGmduYZlQngNZoq0YTvR4dYKlV7WwKNeZCSxXftTdvwGgRhlzc5dXLaUPM5fQQIc2L0QpiHI91EVmRzDcugJwmVixx7Do+7EFVMGpC+ztif346UIIliQxPGJYLAy6JURV76qJNCELi2LSVAVLhJ1vnIKlusgDmyyhzxeET6IThm/AYGFRBZdh/BF670QFG68jWzOBMyHAKvYyC0thbD09RkUytQ8F18eGTcL6GBZ2HaMUDnaLBEuCFha2MB42K4XP4Oqw8DWThhQLccRBMGaMoh2ttx3r1L+guoTocxlVDEuclh4gytTmSIXj7DZ9um0MmVIRM7gMLiFWg6UwoIiMCIXx3A4bapUNyJeN3boxs2amaqsNdb4ojnq8AE0VZlaabj9VtcQs6JZ9Ju6CqFoVAICkXHcZIZTlmfxOD8sSikWw8C4hLdaw18ssZNwz3xv78dOFECxJgvkQ21jxnkxiKJdGtLtHfqEjofCiUtHW7jAhkksobOcbY5YCw2GTUa2Iot6QslD00wl0aJfQEEHLg2FmQmdVgNsPUcEQZ5v3iLEBQyFJYcXj1BgWh51bFKM0oVtmYYlRKBlQS+GbNRtkcOKT7T4dNsm82qhubPFlCQHAjNFUsGw9ahAstjhiWBKIE4sqtTmCS8jttOmfvRjcUREtXyYxLJVSK2QElfiKyPPRFD5dXHk+CVfpNpcF3cY5X0iS1m27a4AJFhbDwqdMxxGMrQgKm0TwvfPGh78eo4sJ0BeP8xHlXg4F0e8zxPQAMaempxMhWJJEXpZd9fMmrQlivAxmYSGEi2EZSrBwN30oAJ+x0m201VFNKMlxwuO0IUDo35DMYlgISehhY26h7gAVXgEvnUALjBaWSC6heIJuzcabN4rG0YT8wIldWuXSkth68VQZe57EguGcdGX5Y8wEiSmGpbs5rBw7HUcwoSwzQJ+6HjEQmTtvJtKianyoLiLxW1i2H+vUj0sZS8AfTwxLHBaWaFKbDfdFv48Luo3z2auOlHJuaIB4oseLajWlObwGC89kli7e2K0TLAx1gWZj9sQ+X9QU0fF1eulnMKiFJRZrhRITY0NITdbQEevzB33xuLZ+Nt4A+szS9ke6S+jxxx9HbW0t3G435s+fjw0bNkR879NPPw1JknRfbrf+ohBCsHLlSlRWViIrKwuLFi3C3r174xlaxkCL92RoHMtggoX3wQ51A/MWFi6gy2WX6YLT3xbdcUyQJAljijyqv1gyq8Pi6+VaCMQe3V5XQn3mHYpgCfoUC4vHQdutszRj44KZSAyLmQtLljX3z9YXaMR+wZiYd++aSyiRfkKGoFunTWt/EO3CFK2FpecE8MgM4PcXhL/We4JWUJbkuCdStiPuHgigLVIXa67Sre6cByPg0+7tGLOEAGByZS6cNhntfX6aVq+ORbGw+BWXUFQNGOO3QkVlYTHc616+dUGcroTyPDecNhmBENFnURrSmk90e7kaLIMXxdPVtzGM2e2QtVL0sd7LHCxTqHOAznPM6qsTLPEcX7fxM1jj/f1aB+sYjskXj2OlIUgwoMZoZfNiONoNagYQs2B54YUXsGLFCtx///34/PPPMWvWLCxevBgtLS0RfycvLw+NjY3q1+HDh3Wv/+IXv8Bjjz2GJ598EuvXr0d2djYWL16MgYEMW+hjpIIv3pNJDObSYGrbla923o1IRMFio31xiPJgx5BuyVNbnK0KFpkwwWJiynR4YvKhM1gtljYvfQyCSsGu/CyHthCYVVlNSLBEyKpg3ay3PEf/rZ4f86GZheVoIrVYWFqzsjDl2IOAV6nK6onS7x9tHZajn9HA7xNfavcdg6WU55RrtVJixO2wqSIuoluIsyDoulMPBrOuxJhKzHDZbZg9pgAA8OmBtrCxBBXBElPQbSIWlo5o0r71vZYSsbBETDk3iWHRMoQGFyxTKukzuq+lB36JXj9JuZfV+BUgIYssC7xtVwWLSdl/JliifVYAvWAhBsHC5gvZAbjzYxmuumE+2RdQDq31aNKJ4R6TTVSGErNgefjhh7F8+XLccMMNmDp1Kp588kl4PB489dRTEX9HkiRUVFSoX+Xl2q6EEIJHHnkE9913Hy677DLMnDkTzz77LI4fP47XXnstrpPKFHTlkTOJwSwssZg0dYIlqM8SYqm77nx92mwM1BR7EFRuUYmYBN3GmdLMYLVYTgzQYxI/J1j4DCejf179/AwN7KIhkg+dNTlkn1scgkVNFx2qHL0ZhnuiT8muKJGU3V0MzSWjrnTLu4KOrNe/lkDROB7WN+rgyQifCSfUonYJ8UHpMVbgZSwYSxe0+gOt2g/jEiyx9+pisKDb4x0DagXUMDhB5w+GEFBcOFSwxBcPAkQIvOUESzBE0NbrG7LKLWNUQRZyXHb4giE0dChtJUJ+AMQgWOIfM7OwsHYhIINYWGIRLNIgFhb+eDHea2zD3MJqWXFWal0D2ZEadOvz+bBp0yYsWrRIO4AsY9GiRaivr4/4ez09PaipqUF1dTUuu+wy7NixQ33t4MGDaGpq0h0zPz8f8+fPH/SYwwG1PHKmuoRCASBkmKhiKXokcbeP0SXEJoY4fMWMmuJs+I0WFruJhSXOncGEMmqCbu6nDy9zCZXkuAZPFzXpbhw1kcbMAm8Z1fNiPjRzgbT2avUnosbQtZgt3oUSZ12JtkYDs8wN1UuIfcZAuGCJFPAcI7Us8PZkBAuLmkHhj94lpGYIxT/BLxinCJb9rVoci3JfBYMsS2gIS4+3R7N+xWFhKct1wWWnXYgjBmpzad988oDLISf0/LHA20N8BhdzCfl70drrRYiAi2EZ3MIiy5LmFjqh3XcOBJHjNrGwxBPDotxLzMIihUy601ttYYnneAos8aOlR5+4kG28r2JsYJlOYhIsJ0+eRDAY1FlIAKC8vBxNTU2mvzNp0iQ89dRTeP311/GnP/0JoVAIZ555Jo4epSmc7PdiOabX60VXV5fuKxOpyNgYlvBCYSp8o62hkCR1QiNcK3ennbOwJBB5XlPsQZBE4RKK80ErzXWhwONAP1EEnGIRqC3J1lwSZrEBVsSwGCfMYi47oLAOKJsW86Fz3Q4UZdNzOTxYZowZhnNiLqEC0kF/Hst1VC0sQ1h6mDgGgCOGOLgEavjw6HpGmWHTXB79fnqPDRk7kkCgK2N2dQFcdhkne7zYf0KxYimur1CAXoPsaPsZOXMAd2zNIQG6yA+Z+s25j5k7SJLYpiT+50+tg8RfF87CcrKbfgZj5MGLxvGobQ9OaPWlHAjoF+gEYlgqlNgbX0jLugEssLAYXOs61PHGLljY+tOslIZgFhZdwG3Aq3VEH2mCJR4WLFiAa6+9FrNnz8a5556LV155BaWlpfjtb38b9zFXrVqF/Px89au6OjP7H1RmegwLEL7oxlpyXHnY/H5N+LjsNossLB4uhsXMJZRYOp4kSZhUngsv6OfhlnwoyXFRE/JgKdkGa0RMRHJjVc8Hpn8TmH8zcMPbccdtqEW5Bqs9YoYhrolZG/JDymQWywSsxrDEYGE5vlkfU5VADR+eOr4Fgxmy5vJQM2CiFQpxBNwy3A4bTh9DCwbWszgW5RowwTLkONQstviFE7PKHY7kRuRcQgNchpAkSYll6JWaCEmnVun2RI8XDgRQCuWziaIT9RRFsOxs4S0sAX3jwwTGbJMljC7KCnNT62NYlPHGEtukcwkZLN6JWFhYZ+xu5iIzsbCwz0N2aAUsM5iYBEtJSQlsNhuam5t1P29ubkZFRXQPjcPhwGmnnYZ9+/YBgPp7sRzz3nvvRWdnp/p15MiRWE4jZWRuDEt47xiVaKvcMpSHzRfgBYusPbhx7AwYlflZkJSx0sZgRB8QmYA/mjGpIhf9oMWasuBDnRLzoPWxMRMsQxTeGwxjWX6G3Ql887+BpT+PO40X4IqlxRrHwpn+AS2tOScYx+6LWViGSmvu5p75oE+7noBlFpbxitvvwIke867NnPhk5zykhSXG5naRYG6hT/cri5IinkLKszRk8G8C8SsM5uY4PJSg4yws7gT6CDHGcpYvtZcRV+n2ZLcXFVIrfe7t7qjcb5OVwNsdjT0AqJvXiYBW5TYU4iwW8c0ZNUUeBNiySayysPCl/SME3cax8VPrMnUrc3PIJKWZv4ZxxmOlkpgEi9PpxJw5c7BmzRr1Z6FQCGvWrMGCBQuiOkYwGMS2bdtQWUkfsrq6OlRUVOiO2dXVhfXr10c8psvlQl5enu4rE2EN/Np6fepkmBHINk3VBwzl+aOtcqsei04GPp9RsCRuYbHJEmpKtGtrR1BdgABY4nudVJGLAUInZTd8aszDoAW54nUJhUKWiKzBqFGbtMVpYTH0EsoOdNCfx+QSijJLiLewANo9w7+WoIVldKEHTrsMbyBkXm+ES2se8EcZw8KEVoJBiqpgOaDEsdg092p044g/Q4gRtYWFi2HJctjo4qcu/rF/DqMKsuCwSfAGQmhk1cA5l9AJY4ZQFIvp5IpcSBLQ2OUFUe5nBwJa0G1/O5e5GN9GqqY4GyFl2ZSNgoWQ+C0ibD4eLOg2RliGXHs/i7nhaisxehKzUqeamF1CK1aswO9//3s888wz2LVrF2655Rb09vbihhtuAABce+21uPfee9X3P/DAA3j33Xdx4MABfP755/j2t7+Nw4cP47vf/S4Aapa/44478LOf/Qx//etfsW3bNlx77bWoqqrCsmXLrDnLNJGfpZVzPhZrf5dkE8lKELNLiN78rHaE0y4r5mImWOK3sADAuMoC9XuHFFL7sABIOIYFoK3pBziXECvxPWhZ+GhdHkYGOrQdVIKfSyTidwnpRVgvq3TrVxoyxiI8DU3sIsLuNfZ5susJJFQlmccmSxhXSkXuvpYekzfEUTgugbL8PLNGFyDLYUNrrw97mnvCCp4N6RKywMIy5P1ikvbtdsgJL/52m6z+7QMshkcXw+JFtaRsSKJwBwE0hmtiGZ0fgkpqs0MKaEG3auZiQdyZi3xtKBkh2GRJq4zt7dZiArNiTHc39GVTSSAWMNdN1x+1lhUxSdsfRjVYgDgEyxVXXIGHHnoIK1euxOzZs7FlyxasXr1aDZptaGhAY6O2c2pvb8fy5csxZcoUXHTRRejq6sInn3yCqVOnqu+5++678S//8i+46aabcMYZZ6CnpwerV68OKzA3HBmVSG2MZBKpFkssQbeAFsOi9D9RI+YtCLoFgIkVBer344pdBnNm4taKKZV5IErvGzd8NOYhGNAW07xR4b/EFthYuxGzz9ZdQF1ASUA18bfFG3Srt7C4/R3057G49tj1MNZW4fF2awWxypUAY3Y9vd2Ar5t+n6CFBdDcQnvNBIuJy8PjtNHicK37zQ/IziuOsvw8TruMubU0buCT/SfDauEMbWGJvyw/g+9CbFoNOJJLiN3LWUVxx1uxwo1qHAtXOI5aWKLLEOI5Talv44MiWBBADlugLShBX1PsUS0sdoRQVeDW2jiwYoIOjxaPEy0sUygsSyiOmBiOUQVazA1NXCAGC8vwqXILxBl0e9ttt+Hw4cPwer1Yv3495s/XakasXbsWTz/9tPr/X/3qV+p7m5qa8Oabb+K0007THU+SJDzwwANoamrCwMAA3n//fUycGFtZ8kyF1cbIPAuLiVsjFIrbJcSCbl0s7biXmTITFCxVWiDYlDLDJGCBhSXbZcclc2lKseoS6m1RqqzazI+tVnKN0cKSgp4dtYqJ/1h7P7yBGHpYGQvHKS5Ml5dNmDGMmbkomCXCDOZWceYChbX0eyZYmHXFlQe4csJ+NVbGD2phYS4hnyrSshw24KXrgV+fDhz8m/79oZAlQbeMM8fRz/Xjfa3qM2ljO2HWoO6z/wZ+MRZ48mygabv2yxZkK40qyIJNltDvD6rdkXVwQtZrWjQu/mdvrBJ4e+AEEyxaaf6WzgGMUS0sQ2cIMZhgGQjRecgJzsJiwQZnfFmOarGwIahaiQAk5L6J6BJKMHlhVEGW1l0aNBbQtI9QtBvUNCN6CSWZ0WpH1EwTLCYuof42TeFH+1AzwRJggsVoYUnM9TGFEyyTy7h28DofemIP24Wz6ISY7whgQnkOV7SsQl8jgaFaWOIVLMmbHEpzaZZTiMToFjIWjlMWb/sAC56OYcJk5uWBThrH0t8Rbm3h4y/YZMw+H5ZSnqA7iDGhfBALi3otvVoVV6cN2P0m/fnHj+rf39+mme0t2JWeNZ4+H+sPtCIkaVYBdRwAsO0leq83baPfMyyoVeO0y2o2ySGz+8XEJZTltEawsDpIuxqVshRMsJAQ2ru6UCspwjCGJqCnKZlXfUFNsGQbOzUn4I6tLvTAZtN6/4wp4ipsJ2INYYG3xLosIYAG3jJrEwA44Tfv1DySLSyC6BmVSEO6ZGLWsZktKllF0ft4lQU94OcEiy74LDFrQlGOS90hTCzhXIQWBNAx7C466VRkEWreHSxDCIi/G3GClXmjQZIkjFN2rmp9j2hgloaQH8EQUWvq2AbiuI7uAtpdF6DWiD9eBPx6rj4LqJPWYUJelbboscnTooBbBlsY9zZ3axkpDE58qh2qeZO5t1v/fmZd8RRb4tabVpWPPLcd3d4AmvvoZ25HAHZZ0oI5ddlTipgjxBILC6A19TOt3cO7hJS0ZrfDZkmw5rQqWmp+Z2MXdUc5NGtFd3cnxqiCpS7qY44vzUF+lgN9RItLK89TrrEFGxxZllCcR8dpt9LCYhbDEgpx/djitLAUZsEHbS6nAs7MJSQsLALwLqE4yqUnE7uyoPAWlnhM3apLSAu6hbeba6CY+OLMUpsX1HG9NCzwoavYDS6eocrCq92IY7WwJDdDiMGCTPefMFmAIsHFNDF3kB0ByKwBZCzXUZK0+I6m7UDLDsDbCex9V3tP+0H6b1Gddmw24VuU0syoK8mGyy6jzxcM7ynEiU81S4iv9TNgKErJRIIF7iCABgWzbKGGDvrMOBDUxxnw2VOdimDpb9fuvwSDf8cMlllmkiXktsglNL4sB06bjO6BALVAyzY1jqXY34Qi1haiMHrBIssSzplQopYqyLX5Ma9WsXhY5JIty6MCT0bIXLDEGnALmLuEBjq0TVk8xwS1sARhU+NYXPCbpzULl5AA0FKbM8/CYuISiufmVQSLamFx2LQJ1pGtLQgJYFMmTTu4h9lK94rDEEQ7lEvCHq+FJTVNxsYpFoX9Zi6QSOh20qwsP/t9KfaiUmwRPbhO+xlfzbZNESyFtdoCwj6fDqU5av7o2P5mBOw2Wa3RsbPRIEBMLCw5EidEI1lYLBIsAHDWeHr+B9qYYAlomRzBABUnDHZvMsGXUzF0k9IhYHFPptVuzVxCfFn+BLJLnHZZddftOK7U+1ECbM+RtynHL485junciaVq5t/Mcoe2QFu0YSgvoILFLoXUtHAACVpYTIJu2fFceXFb80Yp7j5mZXFKfngcZhYW4RISQIthae7y6npxpB1Tl5B+Mv7Ve3swdeVqLHv8Y+xtNkzcDCZY+BiW3sT8ruF/w2T3YalgUSadoI/+jU6lEKFZhhAQfa8cIwn0MYmF+FxCWhA2W7hHORRrhKfIPJZnMNhCdmCt9rNDH2nfswW3sC7cJdR6gP7LtytIkGlVSlGx4wbBwllY2Hnnseq+AH0m+PvOoqJxPCzw9lA7fYbsUlAz2zOXAKPrOHUVtHEWqgRhcRimtVjkcAuLvvFhYvcyuy472XVR4lXOs22h/4/BusI4d2Ip+gm1sMwq4xZ6i0otFObQe0ZGSG3iCMD6oFsLxsuuLas15YIfHrWQHhcHOFLTmgWxUehxIFe5QY7E00U3WbAYAz41l03G2WVo7hrAE2v3o88XxJYjHbj75a0R0h6VGBZesFgUcKuN1aQUvpXxIHZuh+rvB9oP0e8jLQaDWFgIIfAGTbItgJTEsADA2FJW3bXX/JqZwX3GvYpLqNKuCJ54BBZb0E/u0X7Wuk9zt/ELripYWrX3AeENIRNgamUEwcJZWNiCrFb3BWhdDRZvA3BF46yzsIwrzUZ5ngsDSo8aB18gUU2Fzwcg0fH0ndQLvgRRi8eZxbDYwi1vVrmEAC2OZTu7LopIPUNW7psYAm4ZZXluZOfQeiwzyznBEqnKdIzUldF7yY6gVoMF4ARLPEG3JoIlwYBbACjJcdIu1krgrQt+zd3Y1wqAgFpQ43M5pRohWJKMJElqMbKIDdjSAasTwC+6PZqZ9w8fHYAvGILLLsNpk7G5oQNvbTNJU1UsLEFVsFjTR8jsb+gaNVppYeEFS2CAc1dEWAwGsbDc9sFtuODFC7ClZUv471k0YQ5FTbEHsgR0ewPmqapmMBdhwKtaGiodimCJR2BFiqs4vpm6WdhnUVinTci+bnrvsHTo4tgXq0hoO/lOvYjTWViUdgSsui+DiQOAKxpnnWCRJAlnjS+Bn6sdMl1ZyNVnKadCE4GdRzVRzVLCE4DFYXT0+dHZb6jLxPcSClgvWGZXFwAANh1upwHRxQaRGqcF6fRx1J1b4OA3OdbEsJQoMSzTKgyuKjVLyGKXUALjlSQJNcUeeDkLi9pLiLmDPMWJxwGmCCFYUgATLBE7oqYDs2qkioWF5JTh1c3UV/5fV5+Om8+lC8f/fHoo/DjKg6YKFodsyYOm/xsmEfRWChZZpn5igC4EzAxfGKH+QwQLS5+/D387+jd0+bpwzdvXoKnXIPBSFMPistvURWhftG4hLr23x0s/5zIbs7DEMQEbi6ox907rPk0Qeoppl2F3vuZ6OLJee83CZmyTK/JgkyWc7PHp48k4C4tqQTAKljZOsDALS4JF44ycN6kMfiUbzo4gpo9WBAtfgJHFVHUdB9oO0e8tcAllu+wozaUW1zAri0mWEE1rtkZ8T6vKg8dpQ2e/H3tausOtaqyoYIzYXIYNWSjI9TdL8PlT3Dcu2cIUZDOXUJ81LqzakmwthgUBLqZneFW5BYRgSQksqO2gmck1XTDB4udElLKgnkQ+Tvb4YJfpzu8f59Ju2OsPtqGly2BVMBSOc9ttlj1oxr9h6t+1ShQxcXLgQ+W4pYAr1/y9EXrlfNn2pe7/6xvp4nu46zD8vj4teDIFKYQxZwqxGhj+XvQqgqVEVuKW4rKwcAu6zQlMWkq/b90X7s6QJC3Advdb9F8L41cAushOV6wsmw5zQaychaXfT89bre7LYFlLABfnZV0MCwBcMLkMPsLM9j7OwsKJfxZT1XXMUpcQwHW1Nt4vzPJGgvAq1ayzJZ9WiTjB589ukzGnhgrTDQfbdNc9ILuBcQvjO7BxfutrA3V/IHH3h5n7BkhC0G1iVW4ZtcUeeBXB4pJ8mkuoJzUbKCsRgiUFsIZ6hzLeJUQn411d9LXJlblwO2yoLvLgtDEFIAR4c5uhYZ3yoPmUySzXbddPslagNqgzyWiy6mFjpvX9a/X/N4NZWAyl+Xe27tT9v6WvBRsaN+Brr34N93/8I/pDSU5JG/dxXJfiqOAWbiZYiiUlriAe117ZVLprdOYAlzwGlM+gP2/dr1Vr5c3/1fPov1v+V3nNWsECAHOV9NbPDnGBrKo7kEBSAtBd3nb9L7KdKJCULCEAyHHZISv1gLIkn2rx0DURZYKl7YAmoiywsABa+4KwasBcll/IR+/3AqLE+NicmmUyAVja8fqDbbrdfnfR9PgzoByG+Y19jlaUQWDzES8uQqEEXUImVmSLalnVFustLGGF9IRgEfDUlgySNpguHFqjMQA0fVKxWmxupzf3rNEF6tu/NpOao9/ebnBzGCwsOS679RYWs5iRZAmWw3/X/3+w8RhK8+9o3aH7f3NfM/6y5y8AgP9reB9NNhtNH5ST/9iNLWGZQlGKZFWw9KHHSyfiAqIIlniEZ0E1cPsXwIqdwOyrgBLOJbRf6cxee472/jFfof+yuhNxBFsOxRlK356Nh0wsLKCtGQDAztoRMIHAdqLeHq3/kcUuIQC4fD5tR1KRxbkaeEsiEydfvgWA0LYGFj1jEdsXcPFdIWWuyAt1KGMqi6qL8lDMq6OC5dP9rfAGQ1gXmg0A6DvnR/EflLufAVjbFkO1sHDiwtvJNTaNpw6LMieETK69BS4hZmGpzpO1jvTCJSQwg90gxzv7Mye12fhAs4hxSUa9YkThBcvCyfSm3tzQru7AAaiChVlYsl1264NujbslwHpzptG0PpipXbWwmAuW80afB4BaWFr6td35X3JzLE2HHYyYa7GoArYPfcr1zWc76Xgn+YJqJbsFWmxCTxNwbBP9fjxn7q/+iv53Jy6O728OwpwaupDsbu7WgkttTgB00XXBB0kCbP3KzrZ0sjJmxarCrBrO3MjuwgQ4eyqtQaIXLFwq/PhF9PvOBvpv9RmWCAaAs7AYLXKyzD1/VLDkBDvo/y2yoJ42phC5Ljtae3148bMj+BffrbgUj6Bq5vnxH1SN0WOCxcI5ycxFzawrzlytKGcsqIU8uSB5C7KEALp5Ye7Gb82pgE1W7hnhEhKYUZTtRK7bDkIyKFPIafDxsoBbTwm2HaeT1sxqrbJsTbEH1UVZ8AcJ1h9s1Y6jPGhBRUzkuO2wqlOzirEUvr/fMh+6itGiMtgO3ySGZfvJ7TjYSeMKzh9DJ9qm3iadm+i9bI9l5eaHgsWwHOvoV4NJB4X7jHuUbJlclt5rxSSfVaA/Tvl0fWE+Jg7YaxUzEv+bBkpzXagryQYhwOcNipVFktRzd0s+eBw2SGzxKZtC/2U7UVbQLlIwdqIoi6yNdzWqAezF1IVWpnW5x+yrLfvTTLAcOtkLf9AQTKqMiyguoRy/tbFYTruMr06kx/rle3vQhWwUjJkGKRExZpwzrKzoahogm2C8id0kLs6i5IXiHBfGV9FjTCji+wgJC4vABEmSMLmC7sh2N0UowJZquB01APXmDWSVoNcXhE2W1EUPoOdw9nj6sH+0lysVbrB+5LrsiflyBx2rIvbYbkl2aDv4ROEFiyRru1kzmIUl5AdCQYRICD/99KcAgIvHXoxJRZMAALvadqGfW3wa7TaQFE0ORdlOFHqoGTiqAnImQbfZLFvGKlFYMkH7ngXhMmQZWHAbjTG4/A/W/D0TWIDnRpM4Fjf8tK4GE9xMHPScoL17WCqxUo3VctRrwAfCGywDk79G/3XlA5MvtuxPV+a74XHaEAiRcNe18oyHvMzCYn3w+MIp9Lno6KOWL5buHDfGoFsrY48GS0GOd84z609mkYUFAKqKlXkyYBYHKASLwMDkChqctqupa4h3pgijS0jJye9z0oejqsBNGwFyfHUCnTT/PphgsQc1P3+yLCx8/IpFJnHdIlQ+ffCdGB8I6O/H4a7D2Nm6Ey6bC9+f+32Ue/ST4owSai3ol2V0WVVMLwomlFGRvLclCpGsC7oNQkYIWQELLSwAMP9moOp04Jw7ga/eFf764n8H7j6gWTaSAItj+cwkjsUNHwqznZpIYOMI9NN7mllYCpJlYVGuga+XCiQgvHbPnOuAipnA+T+0pO0FgzbNZHEshvvFqRcs2aqFxboCiOdNKqMVdBVOS1iwGOYMK0vQm8WwWCVYmJvZP6DNowlmCQEw7zBvQQPLVCMES4qYXEkXjy8bM8TC4jRYLZQdSIdMJ3RdUy+Fr4ylD+Pelh609ii+VkWwyAFDBoHssCSDgP4NYwBdEirG8t2pZ39r8PfauYUiMIAObwcAoNxTjpKsEhS5i2CXNNPrvIp5KFBqbDS7wz/XZBHTPce7hLwBFKIbEksDtWLCBIBpy4CbPgQWrozs57dKgEaAZQp9caQDXqUQmmZh8aEsC4CXlYmv0wR5TwvQnhqXEEiQtszQ1Q5R7vX80cDNHwFfudnyPz9JsQLvNN4vzCWkPH9uv0X1TDiKsp344w1noCzXhQKPA6fXJJhJZ7SwWND7SGXQjJ54XUIGgcVqQUk22v08UVgvIhYjQ4i1n0mKEIIlRTALS+a4hAyBrIrabiHUdGgmWAqznZhUTic1NTVUWeiYYFH7sGSXWLf4GMearHS8a/8KLLwfmHfT4O+TZa21gb8fXcoCl+ek11iWZOS7NFfV+WPOR7kSFtBsdyBVsAXoy2juOc7t1ucLaCnNWUV6MTfMGVuSjaJsJ7yBELYfU+5VLoZltFPZ1coOulDwfY6SbWFhmwiABrj2t8Oy2iFRwFcD1qE8fx7Qxc7JgpItfv6+MrYYH/3gfHx09/n6kvfxEGZhYS4hCxZn0xiWRC0sBgsInyFkxTzKFYYEQO8tVjlcBN0KjLDFo6lrAO29viHenQIiBN0e89NxVpsIFkBLQVx/UC9YbEH6oGmBmha6Pow1Y5IlWMaeC5yzIrpGf9wE0+VTBAtnUWod0AKTZ5TMQIWfXvPmFD5xk1XBEoUbUmdhCaJEUq7jMNp9RYMkSWrdj08PKPcwZ2GpUtsRKO5Gdv6psLDYHNru3den3edZhSkpnc76+uw09ltSnr8syYsshw0yc1NZEcBqwGW3IddtgUAOEywWxmuYNY61zMLCZ23CunmUa70BQN+jKp6spjQhBEuKyHHZVatFWIv7dGAsza8E3R4aoLu8mqJss9/C/LH0gdygChZ6HEeITgyegOLftlKwGNIqLa2pEC+cCZcJllynlupa5KafU21eLeRQCOVe+vk0haLs7WMBExVrWHOXFx19Q4hktrsP9KNvwIcSsBosw2f3FS1njqf35if7lYWXi2GpsBmyz9gC17oPGOig3yfLwgJoli5/v/XlAYZgiuJCPN5p2FQpz18WvNTyMRwKjvEBzIRYmxHDu5vUWKMEEw1UgaVYWKxub2K0sAyHa2iCECwpZJYSSKYrXJUuwlxC9IHe00t/buYSArSqlDsbu9A14FcftCyl6JZa1txKMREWdMt2eGnc/XOpzUaXEAA8ev6jOL/6fPz2H34L9LagPED93c3+1LkEc90OjC6kn92uoeJYuADOgLdPs7AMswktGs4cRxeVjYfaaV0kZmGRfCg1WpaYFeHIBvqvpxhwGZreWYmTE+dWlwcYgly3Q+3crOtqzbmECty28EDgTISfMwY6tCrZVoyZXSMQzYVjWdAtq8yboMXGiLHOi5VByClECJYUMk/NUGgb4p0pIIJLaG8f3ZlEEixleW61lsWmQ+3qZOaGFzZZgmOA7TSSIViMVSvTOGFy5flVlxAnWGaXzcZjFzyGqpwqoLsR5UHq727uawk7VDKZUknHtMMYl2CECyQO+XpRPIIFy7jSHJTmuuANhLC5oUMVny74UagWy1MmclY3Z8/b9N+q05I7ODVTqC85weVDwOJYth3j7hfOJVTp9mrBpimy/MQF25AF+rWGla78+Ev9mx0b0MpCJCpY1DosVAD5e0/gNwX52OiIwj0d1fEVwWK0sCTBrZdMhGBJIfPq6M286XB7eHGmVMO7hAI+tTHfSZKHXJcd+Z7IfmQ1BuBgq2ZhkXzIcdkhJWNXyJvJgcwQLFx5frMYFh1tBzULS19zKkanMkvp+vvF0SEEiyyrooX4+jWX0DCb0KJBkiTVyvLJ/pPqebvhQ17IkLI76SL9L0+/PLmDc3CuDIt6ycTCadUmmyrVJeTDKBbj487XMk8yET7lmwVLW2WRlW1c0L1FgsWwKXujfTt+W5iPG7o2JjBQDptBsAgLi2AoJpTlID/LgX5/UG9yTQcOzqzZeQQAEJLs6EAOyvMH34WwwNsNB9u03Re8Sh8hi4PFgMguoUyIYQmYu4R0nNzDWVhSLFgUN+TWox1Dv1n5nJ1kYERbWABwgqVVFZ9u+JATUBZqtrhVzgRyuYq8rHBbsuAXrjTc5yxG7bODbQiGlPgM1SU0gAo7F5ScyfClB9otFiyA3kIdCmqd2BO1sCgupkYuaN8SwiwsTLBk+HU0IARLCpFlCWco1om/7TmR3sHwZk2lgqfXVQQCGWW5g0eNM8Gy7WgnBkDf6wa1sCRlkuWtQXz9gEyzsAwiWAoUi1qvvxcBvn5Dkpk5qgAAbbw5ZHaaEqjogZeLYRleO7BoOXMcvT+/ONIBn6Tcw5IPWT6TKq6XPgZAAmZ/G3BbVFsoEmwh9PXpOzWniKmV1MLa7Q1gF0sOUF1CPpTJwyQYW5Y1EcAsLFaOmZ+T+jugpZ/HWT/GsCnL9mvB+SFigTXeGMPSm7xMr2QiBEuKuXAarYL61rbG9A7EZtdS3dppD5weOxUi5XmDW1iqizwYVZCFQIjgy1a6+GZJXmS7bMm3sAx0avUD0ulDN4thieQSOrkX2VwX1r5A6rp253scqFM6N289NoRbiAugLpVYtszwmtCipbqI9sYKhAiOdtPFxg0fHAMmAaUT/oF2nv7aw8kfGO8SSoOFxW6TMVeJtfv0gPIsc1lCwyoYm80bJ/fQf/neVQkfm0taYHOeOz/+mkWGSrcenzZHMAtuQhgtLMIlJIiGxVMr4LBJ+LKpO7wEdqphD10bFSysyu1QFhZAs7JsaaK79iz4kON2JGdXyNdhYZO4K8+aALp44S0sg7mEQkHg5F44ATiUGhu9LJU8RbA4lk2Hh8hOYwuTxLmEhtkOLBbOHEvv0V0nqQDOkvxcjRHDRF5Yk5p6FWYuISvFfxQsUNxl65gVmM8SIsNJsCjzRtN2+u9gDU1jhXcJWbFJMwTdElaWH0DbgAVJGsYYlmHY+BAQgiXl5HscOGcCfdhf3XwsvYNhtQpOfAkAaJTouMqGsLAAmmD57Cg1YWbBi3ynpPlyk+ES8vdxvtc0ZygMliXk6wNO7qPfdzRQM6zNhWwHTYft9adWsMxXWip8vO/k4G9UPudSqRNuWJgGmqGcM5HeQ9ua6SReaPdB6hu8iuu2E9uwt31v8gZl5hJK8TVYNIVagev3t6Kzz6/LEsoPDUPB0n2c/mulYNG5hNqw3enE3bk2NPbEaTnnhSoh8HINMFutiGdRLSwD1K3ekwFu9TgQgiUN/OOc0QCAP33aoHbGTQvsIWneAQA4FKITVSwWlo2NdLJ3S36U2ZjpUorflzvYOP19mRG/AqgWFp+vFwNKld88Vx6dDJ67EvjNXGD/h5o5ung8shVzf48/iu7JFnL2eLowbznSQWvnREL5nEdLbGedrS8XP8I4Z3wpbLKEAVDX6Di5ESAhuhs1MZXva9+Hb731LVz5xpUgrGCY1TCXkLeLKx6W2nt9bGkOJpXnIhAieG9Xs84lpAYlp3vDEA3G5pDF4yw8tt7C8p3KMrwte3H7h7fHeTzOJeTtghfa/WWJhUWNYfEpmaFKAkO659EYEYIlDVw4rQJ1Jdno7Pfj+c+OpG8g6g6E7gr2+OhOfKgYFoD2ZCnJcaIroJUMrwJX7Cia8vaxjtPfx/le0/yguambpauLXj8JEnIcOcCXbwAH1wEgwMePAIf+Tt9fOVMVLH3+1MWwADReo64kG8EQQf3+QXZryk56vKRY/qz0+Wcg+R4HJlfkqoJlLGmgLxTW0KBNAy/ueREA4Av5kmclYwtX6z5OPKX+Xl8yvQIA8ObW4zqXUPaAYkHIH53yMcUMn1hgcwL51dYd2+AS6lful11tu+I7Ht/8sPckfFz/oNZ+CywsNs7CwqzUDk9yiyAmASFY0oBNlnDTV6l58jcf7KVm13Rg2D1v74s+hkWSJMyrK1InewAYLScpq4HfKSkZTWn3vdacCQDoavgYAC3LLwcDwHsrtfccWAt88hj9fsKFqmDpDaTWJQRoVpa1uwcpXKdM8JOko/T/hbVJHlX6WTKtAgOE3sMO1jahsC7sff6gH+8cekf9f7s3SdWq2ULYoix8BdWm4inZXDqbitV1e06g1U83JW7JB3evImatXPyTBW9RKaxNzibKx8WwJHQ8Lq25rw1ert+hpRaWgHfYuoMAIVjSxj/OGY2J5Tlo7/Pjl+/tTs8g+B0IgH1+amEpy4suuHB+XTEIZPQrE/4Mj0lKqBXw42QulnRPmDVnAXY3uvrow5/nzAM++wPQdoC6EyYs1r9//ELNJeRLrUsIABZPozvmN7Y20nL0Ziif83hZ8fmfAoLlxnPqcO40w71kEuuwo3WHbuHoYH2FrIa5hJTMPRSMSc7fGYJxpTmYW1OIEAH+tImK3BJ0wj6gPOMFw0CwzLpS+95qa6HOJdSG4kCEZypa+OaHfXoLi+WCZZgG3AJCsKQNu03G/ZdMAwA8W384PXVZOMtF0F2EHniQ67LD44yuMyyLY+lXrCwVAWVnbvXkwFeWzBTB4sgCas9Gt7L7zQ0FgXU/p69d8CPg4l9q7y2bBrjzNZdQCtOaGWeOK8aogix0DwTw7s4IxesMAvZUECwepx1fnzdB/8OicAuL0SyfNAuLMe4iTYIFAP7pDPqMvbSVnqtbUizB7gLVJZrR1JytfW91zBHfXLGvFeVBLRbRx/oWxQJ/3buOw5tMwZIpbvU4iEuwPP7446itrYXb7cb8+fOxYcOGiO/9/e9/j3POOQeFhYUoLCzEokWLwt5//fXXQ5Ik3deSJUviGdqw4qzxJbjmK7Tz650vfYHWntR18gUAlGgTdb+HioxorSsAMKk8F3luO/qV4nFy2376Qv4o68bIYA80cwllwg5v4hJ1J+RsO0SbrFXOogXGCqqBa14DyqYC//AAANAYF6THwiLLEi4/nV6XP3162Dxo1LhYngKCBQC9ZhI3FZq4hIwCpcPbkZyxGIOck9kZeggumVmFkhwn+ohhTsiEZy8aZBn4+u+ArCLggvusPTbf86mnBTkh7Xk63nM8/uMBQPtB6wUL2/AFvVx9n1NAsLzwwgtYsWIF7r//fnz++eeYNWsWFi9ejJYWc9/42rVrcdVVV+HDDz9EfX09qqurceGFF+LYMX1K75IlS9DY2Kh+Pffcc/Gd0TDjRxdPwfiyHJzo9uIHL29NXvaBGQtuU78NKpUVowm4ZciyhHMnlakxADippHvmJUOwGHb/mRD0d/q18M+5DgDgIIROCl//LS3KBwDjzge+Vw9MWAQA8CjnkI4YFgC4ct4YOG0yNhxsoyXpjThPPQsLAGoarztX+7+JS8goUNoHkmVhMVyDNFpYspw23HzuONWCqpJGERUzs64AfnAQqJ5n7XF5l1B3EwJczMnRnqOxH8/mACQlxqb1QBJcQsq8HgqoSRanhEvo4YcfxvLly3HDDTdg6tSpePLJJ+HxePDUU0+Zvv/Pf/4zvve972H27NmYPHky/vCHPyAUCmHNmjW697lcLlRUVKhfhYUWpsVmMG6HDY9deRqcNhnv72rB/3x6OHV/PLsE+NojACRsHvUtANEF3PL89LJpKC9WrlW/8mAlQ7Dwi6lkA3IqrP8bsWJ3wV9Lzc6OsmnA9W8CZVMivp1ZWFJdOI5RVZCFb82nC+DPV3+p9YphGCv1Fg6jhSlRJnIWXRORYBQoSbOwhLmE0nsNvv2VGkwfU67/YRpFVMbALGHebqCnGX5oAuNYd5z1tbgMMZ2Fpd8KwcKJTqV33HCrcgvEKFh8Ph82bdqERYsWaQeQZSxatAj19fVRHaOvrw9+vx9FRUW6n69duxZlZWWYNGkSbrnlFrS2Ro689nq96Orq0n0NZ6ZW5eGepZMBAD97c5fWwyMVzL0BuPcoPsqhE3YsFhYAKPA4kZNjWOiSkQ7LT+R5VZoVI82wvkCO/FFA9RmDvjedWUKMW88fj1yXHVuPduLP6/XimEy5RP9mV24KR5ZmTvs2MPoM6s4z6ULMBEqWEhyZNAuLsVZImsWB22HDS987G3By90K648cyATYfdRwGSBABTmDEZWEBNCtI6z6dhaXH35N4PyE7N6+foEkeJ7MLcc9H92Bzy+bEjp1CYhIsJ0+eRDAYRHm5XnGXl5ejqakpqmP84Ac/QFVVlU70LFmyBM8++yzWrFmDn//851i3bh2WLl2KYNA88nrVqlXIz89Xv6qrh/8DdMNZtbhgchl8gRD+9bnN6PclGHUeC64ctHRTl1BpjBYWAOG7wmS4a3hTeSa4gxT8Sl8jhzx0DxHVJZQmCwtAr+9dSyYBAH6xejeaOgfU17odxfiV/3IAQLDmq2kZX9pw5QDffR9Y9rjpy0yg1OXT+JakWVgKa4HFq+j3WUWZE2dwxo3a98MlhiWZsPmo9QAAwM/1EIrbhcOOSYI6wUJAEq/7I9sBZgVSLCzvDzTizQNv4untTyd27BSS0iyhBx98EM8//zxeffVVuN2a4rvyyitx6aWXYsaMGVi2bBneeOMNfPbZZ1i7dq3pce699150dnaqX0eOpLH4mkVIkoT//OZMlOa6sLelB0+s25/Sv9/cRReuWC0sAPSBgjZXcnqf8KIoAwWLUw7flRtRXUJptLAAwNXzazC7ugA93gB+8n871J+39vjwaPAbuD20ArZlv07jCDMPJlCSLlgAYMH3gGteBb79clpqsJiy6N+Ac38A1H0VGHteukeTftic56P94PxcjRfWqiNmuN5ovEsIALp9CfadkyS9lQUSehx0c3qiPw0ZqnES09NQUlICm82G5mZ9WmRzczMqKgaPKXjooYfw4IMP4t1338XMmTMHfe/YsWNRUlKCffv2mb7ucrmQl5en+xoJFOe48JNLaarzb9ftx9H21KW/nlAsLLHGsAAId9cYHjZLGDVX+z6Dgv5YCqMjii6tqksoxb2EjNhkCau+MQN2WcLb25vwvpLmfLLHC0DCltyvnjoBt1GiCpY8RbAkqw4LY9wFwKjTk/s3YkGSgPN/CFz3f6eWqzAShuDoAC9Y4u2uzAkKn0GoJixYAP1GMr8aA8pmy5JKuikiJsHidDoxZ84cXcAsC6BdsGBBxN/7xS9+gZ/+9KdYvXo15s6dG/F9jKNHj6K1tRWVlZWxDG9EsHR6Bb4ytgjeQAir3voyJX+TEJKYhUUnWJIQcAvQtMRvvQjM+2cad5MhxOISyhTBAgBTKvPw3XNoNszK17ejxxtQ0+qLs4e2Fp1qMIHCLCxJq8MiGB4YBIufExjd/jjFBTePeg0bIEsESw23RhfVYSBA5/yT/SdTm52aADHbG1esWIHf//73eOaZZ7Br1y7ccsst6O3txQ030EXk2muvxb333qu+/+c//zl+/OMf46mnnkJtbS2amprQ1NSEnh5ai6Knpwd33XUXPv30Uxw6dAhr1qzBZZddhvHjx2Px4sWmYxjJSJKE+y+ZBlkC3tzWOHjvF4vo8QbQp8TMxFKHRSWXE5alkywalQFJAiYuBi76BZA/Gv6gHyvWrsAft/8xOX8vSphgsctDBwFnkmABgNsXTkB1URaOdw7goXd241gHncCKc+K4B0Yw/pBfXYSYYOn0diYeCCkYvhhKAPDNVeK2sHCCxWdIKrBEsNRyhfSKxqJfaYDoC/niF1kpJmbBcsUVV+Chhx7CypUrMXv2bGzZsgWrV69WA3EbGhrQ2Ki12H7iiSfg8/nwzW9+E5WVlerXQw89BACw2WzYunUrLr30UkycOBE33ngj5syZg48++ggu16k5cU6pzFPTT3/yfzsQCCZ3YmQBt7FUudWx4FbgkkeBS38DLFw59PstYPWh1Xjv8Ht4eNPDKfl7kfAHh6eFBaB1NlZ9nbpnn6k/hJ++sRMAMLcm/SUFMmnH1+ntBADIkowxefS5DJKgNYtInHQMdOCW92/Bj/7+o7SN4ZTG6BLivo/7vrBzFhbFrV7spm4cSzq8156jfZ9XpXaZB6iVZTgQV27obbfdhttuu830NWOg7KFDhwY9VlZWFt55551B33Mqcuc/TMIbWxvxZVM3/vTpYVx/Vnj1Tatg7qDSeKwrAC3TPed66wYUBUe6tUDrQCgQlYUjGaguoRhiWPoD/QiGgrBZ2YwtTs6eUIJ/nDMaL23SUjEvn5PeoOb3D7+P+z6+D/9+1r9jYc3CtI4F0DKE8p35cNlcyHZko9ffiw5vB/JdqS9R7w/6cf3q67G/kwbm3zPvHuQ6RVxJSjG6hKBtKvsCffHNSeXTgD1vAwC8kgwQoDirGK0DrfEH8vLwBRGzS9Hfo2X2tva3Ymx+eMHETCNDQtAFRgqznfj+hdS98sv39igBkcmBBdyW58YRv5Im+B1BUjM2hiCeGBYg/ZlCPPdfOg3ZTiqelk6vQEmSXUKEEHxy7BP8x/r/wMamjbrXgqEg/t/a/4defy9+s+U3SR1HtLD7q8BdQP910X+TVotlCL448YUqVgCgpW+QDtyC5GB0CRF9GYq4rCwX3Afc/Hdg+YfwKXkLJVkl8R/PiCQBV/4vMPc7wOyrVZcQMHwsLEKwZDBXzRuDaVV56B4IJDUAt7GTBdwOHxfcgc4D6veWlK6OE5YlFE1as1N2qsImHf2EIpHjsuOv/3I2vjV/DH50ceRKvVbx7uF38c/v/zOe+/K5MJfeB0c+UL/3GMvUpwkmTApdhbp/UyWUP2v6DCs/XqkuWsd79b1qmvsiNLMUJA+HB1Csa6Gv/w5BQzxTXAJDkoCKGSBVp8EbpJtIJlgsmy8mXwx87VeA3akG3QJCsAgswCZLeOCyaZAk4OXPj+KNrXE01YoCVjyssiBriHdmDgc6NMGSrp0uEJtLSJIkdXeeTquQGeNKc/AfX5+B0YXJFwm723ar3x/r0Zcxf+eQ5h6OO3jRYtjiw9wuzNKSqvvuO+98B6/uexW/3Eg7gBs/M2FhSQOyDbjmFeD6NxGY/nX1x6zWUiIWETanAFoMSzKCYnkLy3BJbRaCJcOZU1OE751Hy3Xf/Zet+LzB+knyeAe9cavyh4dLqLW/VZdWmk4LSywuIUBb7JJexyOD4S0CbQNtauAyADT2agH7Tb1NGRF8y4KkmcUn1RYWxraT2wCEdwMWgiVNjJ4L1J6tExhFbtpyptPXGfdhmXUFoDEsgEUuIQPCwiJICv9v0UScM6EEfb4grvnDejz194M40taH4x39aGjtw76Wbpzo9sY9uTOXUGX+8LCw8O4gIL2CRe0lFK1gyVALSyoxLrAt/dr/m3s1MTMQHFAzdNJJX4AWcGQxSKqFJcW1WNhnwQTLqBxa80gIlvTC5gBAEyyJCAxesFhxvEjoYlgGhodgyYwOcoJBsdtk/PaaOfjuMxvxyf5WPPDGTjygpKDyVOW7ccUZY3DzeWPhskefgcIES8UwsrDwpNUlFENaMyAECxC+wDb3NmNUzigEQoGwnV5jb6MqENJFn58KFo/dYGFJsZWMZYowl9Dsstk41nNMCJY0wywsEjSXbyICg8XFuWwu5DnzEj5eJPi0ZuESEliKx2nH/9w4Hw9cNg1TK/NgkyU4bTI8Thvy3HZIEnC8cwC/en8PLvvNx2jpHhj6oAC8gaCagVQ1TGJY+AcNyBCXUBQxLIAQLABwoo/2LmELP1twW/tbESRB2CU7phTR4N+m3uiaqiaTTLGw9Af6EQgFVCvU7NLZAISFJd2wTYtdtiPPRQVGImnIzMLitDnVuKmkW1iGiUtIWFiGETZZwrULanHtgtqw1wb8Qaze3oSfvbkTXzZ149t/WI+Xbj4T+VmDL6TNnfThcNllFHqiW3TTDe97BdJrYfGFos8SAoRg6fP3qQGEM0pn4G9H/6bGtLB/Sz2lqMyuxK62XWjqS79gYTEsTLCky8ICULEXILTGx/SS6QCEYEk3vFvYCosIb2HJcdIgXksKx3EQQnTzaNtAW8bUhhoMYWEZIbgdNiw7bRRevuVMlOe5sKe5Bytf3z7k7zV2UpVdme+GlIymhUmA7UCYGyatFpZ4XUKnaNAtW1w9dg/G5dNgcmZFYYKlzFOGiuwK3WvphAmWLKUSaTpFJ4vfqsyuVD+j1oFWXRyFILXwVlYrLCJmLqEuX5elAejeoBcE2vFCJDQs+mMJwTLCqCnOxhPfngObLOH1Lcfx+pZjg75/uMWvAJqFpSqnCsAwcwmxLKFT1MLCBEuZpwzl2bSdh2phUVwd5Z7yjBIsRpdQoZtaWFI1wdskbde7qXkTABpwW+Qugl2yI0RCw8akPxLhMwVVgZFASr6ZSygQCoS5whOBt64wAT4c4liEYBmBnD6mELedPx4AcN9r23G0vS/ie493spTm4RG/AmgxLJXZtOliOncGsTQ/BIRLiImTck85yjxlADQRo76WnWGCxRB0y65hl7cr6ZYNf8iPIFdFdX3jegC0CaMsySjx0MJiwi2UPtg9YJftqsBIJK2ZL0bpsXtU662Vrm8Wv+KUnSj1lAIQgkWQRv7lgvE4bUwBugcCWPHCFwiGzM2J+1uoubu6KDOqikYD2x0wwdLp7dTVQkglMddhOcUFi87C4qEWFtUlZGJhyYQqrkywMAsL6x9EQKzp8TII3oC+JcfWk1sBaF2jjaJPkHr4OYBVpk1k8WcWFpfNBUmSUJpFBcWJ/hMJjlSjP0gFi9vuRombjnk4pDYLwTJCsdtkPHLFbGQ7bdhwqA3/9eE+0/ftOE53AtNHpb6JW7ywB7oiuwJ2iVo20rU7iDWGJV1FxzIF5roo8ZSogvNE/wn4Q36d9aXCowmWEElut/KhYH2fWOE4u2xXTf/JjkWK5AZggoWJvkwQdqcqZoIlEXHhDWkuIQCqFY1l11kBs7Bk2bPUMQ8Ht6IQLCOYmuJsPHAZzSR4ZM3esCq5A/4g9rbQ6PNpVXkpH1+8MAtLlj1L3WGmy3WgZgnZossSyndTYdgf6NcViDpVYNkOec48FGcVwyE7ECIhtPS1qD1yKnMqUeophSzJCIQCaTdVqy4hrrcRi2NpHUju2IwZcYy6PGFhyRT4tGZ2PYwVnGOBD7oFgLIsekwrLSz8HCoEiyBj+Mbpo3DprCoEQwQ3/88mHGnT4ln2NHcjGCIo9DhQmYSg208bP8XLe162/Lhs1+myudLuOoi10m2uI1cNojwVM4X4eBBZktXrd6T7iLrojsoZBbtsVyfSdMaxEEI0l5Bd67ZtdGcli0iili2MQrDEBiEEL+5+Ee8eeteyYwaINgcUuArUeLZ4BYCaBakE8qtWGwstLLxgYeX/hWARpB1JkvCzr0/HpPJctHR7ceXvPsXuJppyt+M49b9Pq8pPSkrz8neX49/q/w2fN39u6XHZA51lz0rZwhGJWF1CkiSpMRCnoluIZdwwa0VVNs302tyyGSESgsvmUhu+qYG3aazF4gv51AWJt7Awdxbf+ygZMHHO7nMGe16FYImNl/e+jJ9++lPcue5Oy+Le+DnAipgTY5A3C4q1NIYlwMWwWBB3kyqEYDkFyHM78OyN81BXko1jHf34+n99jBc/O4J1u+kDMG2U9e4gvmbAlhNbLD022x24bK6w1NhUE2taM4BhtaOxGuNkXJlDF/5NTTRdtzK7Ul2MWRxLOi0sbLyANmZAG3fSBYtyr7vtbiytWwoAmF8xX32dCRkhWIam09uJhzY+pP6f71uVCMZMQVVgxGkRYXV/WOdnVQAlIYbFbXMPK5eQqHR7ilCe58Yrt5yJ7/35c9QfaMXdL9NsA0kCLpxaPsRvxw6L7QCAxh5rJ3XVJWR3aUGHFk0+sRJrlhBAF+W97XuTvthlIsaaJszCsrF5I/2/UlsHQEakNrPFw21z66qAsnFbfW8bYVlCbpsbD5z5AGaUzMCFNReqr7PFrLmvGYSQYVP8MR3sad+jXk+Ais3RuaMTPq5xDmAxJ3xTz1hQKys76TOSTAsLH8NipSBKFsLCcgpRmO3En747H/csnYwsB518f7h0CubUFFn+t3p8WilpqxdmNoln2bLSamEJhoJqjYxYBQuQ/N15JsImY+ZeYZYK9jnygoV9Tmm1sATCA24BbdwsUDhZ8OLcbXfjmqnXqPc8oLmE+gP9usVYEI4xBd2q50+NY7Mo5iSShcVKCwhvuWPPXLe/OyO6ow+GsLCcYthkCTefOw6Xnz4aR9v7cNqYwqT8HX7yZOXErYKfxFmvjXQsarwPPNosIUCzHCR7d56JhLmEFFHCGJUzSv0+EywsxhosDF5MJdOyweK13DbzoHiPw4NcRy66/d1o6WtRnwdBOPwmCgCO91gjNlWXkFJigYnIeC0iLJOO3XPMwsIyj2JxP0eCzaFZ9iw127KlrwUNXQ2YUToj4eMnC2FhOUUpzXUlTawAUBvcAcDR7qO6zqCJou4ObG7VJXSy/2TK+6nwgiUWC4vqToiww3vzwJv4/dbfp73+SDKIFHTL4P/PxMvRnqMpGl04qkXIrrewMDHVH+hPavA0H68VCWZxyYSqwJmMsYGgVRYWYxxbojEsRsFS4CrQ6k1ZlEbPu4QAYEzuGABAQ3eDJcdPFkKwCJJCr0+zsBAQHOw8aNmx1V2nEuFuk2wIkmDKg8Z4wRJtaX5g8IDN/kA/7vnoHjy2+TF80PBB4oPMIEIkpE6UTABU5FTorCq8S6gmrwYA3Vmmy1RtjLlhuGwu1fSfTLcQ2wm77ZHLDrA4jMPdh5M2jpEAcwmxzYVVFhZjaQM+rigemFWPuYRkSVZFkFWilFmb2MZhTJ4QLIJTGONuxkq3EF+62ibbVCuLVRNQtKgFoyQ7ZCn6R4m5E5p7mxEMBXWvfXHiC/X7F3e/aMEoMwfeysYEgEN24L8X/zfOG30eZpbMxOSiyep7PA6POvk3dKVnIlU7NTvCe22psUhJdO3xQbeRYEXkDnUeSto4RgJskZ5UOAmAdYu/MUtIjW/qOR5Xh2WjhQXQRKlV1kZmFWSVt6tzqwEAR7qOWHL8ZCEEiyApGAMArZpMCSG6GgIAUJ2nPGzdqX3Y4klpBugOzC7ZESCBMKvQZ02fqd/XN9aPqEWI3ROyJOtcHKNyRuHXC3+NP1/85zBLArOypMt6YFY0jjE6hy4iybzvWM8Xlz2yS6g2vxYAcKjrUNLGMRLo9lE39YTCCQCohTMeQWHEmCU0Omc0JEjoC/TF1UmeWaeZhYUdE6DudStggoV1jxcuIcEpjdHCYtVkyqdLs11nuh42NpZY3EEAqFVIiTswuoU2Nm3U/b++sT6BEWYWfMBttEGqqmDpSpNgiZAlBAA1+ckfWzQWltq8WgDCwjIUbE4aXzAeEiR4g15LYkKMxSOdNqeugnO84zS1sFgtWJRmrMwllOpNX6wIwSJICsz8WuSmKdNWxbDwvVXYeBxocQAAGXVJREFUrpMJllSbM2OtcsvDJrRjPcfUn3mDXrUb7yVjLwFAK8COFAZb/CPBFuPDnekRLGyHzCZ2HjY2K+OzjPDxWpFgoq6xtzFi7yGBZmEpdBeqz58VrkYWw8JvXFQXS4wCgBCi1WHhBYvF1rxILqF0xotFgxAsgqTAdgkzSmiKXENXgyVZL2xCtkt2VSgwl1CqLSxsooolpZmhWoW4CbOxpxGBUAAeuweXjr8UALClZUviA80QImXcDAbb+aXLJcQyPViqKo8qppJoYeH7ZkWiyF2EXGcuCEjaLFHDASZYcp25mlXKAsuvWfFIJgBinZO8Qa9ak4hPUbc8hkXpY8bahGQ7stUMvb3tey35G8lACBZBUmCL08TCibDLdgwEBywJclMDbjmfPr/4W+GTjpZ4qtwyWNzBwS5td8565lRkV2BmyUzYJBsaextHTLqqmiEUh4XlUOehtKR5s5L3LEuDh1k2Wgda1cXQavgU/khIkqQF3qYhjmVLy5a0BUXHAttE5TpztbgfC9xoZrFs8VpY2BglSGrKMX+8lr6WhLu89wf6VSHMuo4DdK4GaEXgTEUIFkFSYA9evitffdismBzMdpxs95HqSo2JCBazzA4mTMo95fA4POoEMlKsLGam7qGozquGQ3agL9CX8iwwQBMsxuaDAN0Bs9TmZFk2onEJAcC4gnEAgN1tu5Myjkgc7zmOa96+Bhe/enHGV9plojLHkaO587oSd+eZdWyPNyaErwTNZx4WuArU54Z3I8cDmyPtsl1n7WTByEKwCE45+Eh3tjjv79yf8HH5tugMVqkRSK1bKJEYFj6zg1mFmGBh/vXTyk4DMHLiWIxVbqPBITswvmA8AGB3e2oXY0KIZmHJCrewAMmPY4mmcBwATC2eCgDY2bYzKeOIxK7WXer3z335XEr/dqwwwZLnzEuKhcU0hiXGuDqzgFuAWtHUOJYEY/XaB9oB0PgVPvh9YpGwsAhOUdQHz5mNKcVTAAA7WnckfFy+BguPKoo6EhdF0cKyhOIRLKNzR8Mu2dEf6FcLTI14wRJH0C2Qvp1fl69LvcZmLiFAE55Wt59gRGthmVY8DQCw8+TOlLpFeQvFszueVUV8puENelVhkePUNlFHu4/qCkDGg5mldUzuGEiQ0O5tj6mgpbFoHM/Y/LEAgL0dicWYGFOaGaw+zb6OfWH1oTIFIVgESYEJlhxHjhp4u/3k9oSPG2nHyUTRztbU7TDjrcMC0MmNubJY3AETLkywzC6bDYBaFjLd3B4N8QTdApxvvS21goVZVwpcBREtHFOKFDF+MnExbka0FpaJRRNhl+xo97anNOaJtyy1e9tTbgWLFmZdkSAh25GN8uxyuG1uBEgAx7oTc7GYuYQ8Do8qZr9s+zLqY7HsSjPBolpAEnwOjCnNjDG5Y+CyudAf6M/YqslxCZbHH38ctbW1cLvdmD9/PjZs2DDo+1966SVMnjwZbrcbM2bMwFtvvaV7nRCClStXorKyEllZWVi0aBH27s3cSGXB0PAP3vSS6QConz/RGBO+aRcPq5C6q21X2O8kC7abdMqxZwkBmjvhQAfdnasWFg8VLBXZFajKrkKIhLD1xNYER5t+4rWwTCqiO79UW1gGC7hlqGK8dXtSgoKjKc0PUEEzvpC6zqywZEaL0aWSqfFWfPyKLMmQJVl1NW45sSWhY5u5hABuTmqNfk6K5BLij/dle/QCyIxIgsUm29T7eUPj4Gt6uohZsLzwwgtYsWIF7r//fnz++eeYNWsWFi9ejJaWFtP3f/LJJ7jqqqtw4403YvPmzVi2bBmWLVuG7du13fYvfvELPPbYY3jyySexfv16ZGdnY/HixRgYSH9NgVQ31Bsp8AGW+a58NaMiUSvLUBaWPe17UmbOVCcqW3xNz5mQYz2Dmnv1FhZAs7J8fOzjeIeZMUTqfDwUzMJypPtI3A3l4oEJFrOUZsb4wvFw2Vzo9nVbninT5+9Ty/7nOnKHfD9zC31y/BNLxxEJQrQeYUtqlwDQt5bIJFTBwqUKnzP6HADAhw0fJnTsSMH3zPoWyyZqsMB05rI53HU4oWayLKXZrLbQmVVnAkjdPRQrMc+0Dz/8MJYvX44bbrgBAPDkk0/izTffxFNPPYV77rkn7P2PPvoolixZgrvuugsA8NOf/hTvvfcefvOb3+DJJ58EIQSPPPII7rvvPlx22WUAgGeffRbl5eV47bXXcOWVVyZyfglBCMGta25FaVYprpt2XcwT7akMn0II0MX5cNdhvLrvVdTm10JCdJVOjbBFJKyEe24NsuxZ6A/0Y1PzJtXdkkxY1ko8MSwAcOm4S/H4lsexvmk96o/Xqx2uecGypHYJ3jr4Fl7c8yIuGXeJ+nkOR1r7aVXRWF1CRe4izCqdhS9OfIHfbPkN/nnmPydjeGGwxbgsK7JgccgOTC6ajC9OfIGPj38cV02eSLx18C10+7tRnVutBtUOxkV1F+HlvS/jtX2v4ZsTv2m6IFlJh7cD3f5uSJBw6bhLsfrQamxu2ZyWbK6hYFlcvGA5v/p8PPHFE6hvrEdDV0PMFasB2ti1rZ8WFzTOA8wisrN1Z9SfCbOymq01JVklKHIXoW2gDRsaN6ixXbHCsoxMBcuoM/HY5sewoWkDjnQfgU2yhb2Hb1CaamK6Qj6fD5s2bcK9996r/kyWZSxatAj19eYlxOvr67FixQrdzxYvXozXXnsNAHDw4EE0NTVh0aJF6uv5+fmYP38+6uvrTQWL1+uF16vlond1dcVyGlGzu323qjRf3/96Uv7GSIeZ/y8ZewneOvAW3jn0Dt459E7CxzXWpbDJNkwqnIQtJ7bgxndvTPj4sRDvwlCZU4mzR52Nj459hJveuwkAFXi8y+S8atoUcOvJrfjm/33TiuGmnVgFCwDcfvrt+M4738Ere1/BK3tfScKoIjOYSwigYvyLE1/gwQ0P4sEND1r+96+fdj1scvjCYeSMijMwp3wONjVvwhVvXGH5OCJRlVOFOeVzYJNsaO5rxuKXF6fsb8cKb6maXDQZFdkVaOptwsWvXpzwsYuzinX/ZxaWYz3HYv5MzASLJEmYVDgJ9Y31uO2D2+IfqILZvDWlaAoKXYVo97bjolcuCnvdKTux6ZpNCf/teIlJsJw8eRLBYBDl5fqaBOXl5fjyS3O/WlNTk+n7m5qa1NfZzyK9x8iqVavwk5/8JJahx8Xkosn480V/xmOfP5awn/NUZEHVAnWCOGvUWfjV+b/CqvWrVB9qvDhtTlxQc0HYz78x4RvY17Ev4aj/qMchO7G0biluPe3WuI+xfOZy7GjdgV5/LyRIWDZ+me51SZJw97y78a8f/OuICLwtchdhXuW8mH/vjIozcPmEy/HmgTdBkLosmFxnLs6vPn/Q91xcdzFWH1wd1j/LCiYVTcKl4y6N6r2SJOHOOXfitg9uS9m9IksyvjHhG/A4PLh8wuUZvbGzSTYsqVui/l+SJNww7QY8+vmjanXZeCjzlOHmWTdjXoX+vi5wF+CiuouwpmFNTMfz2D04r/o809eWjV+G7a3b4Qv6TF+PlgJXger+4ZElGddOuxa/2/o705iseOP1rEIiMeTAHT9+HKNGjcInn3yCBQsWqD+/++67sW7dOqxfvz7sd5xOJ5555hlcddVV6s/+67/+Cz/5yU/Q3NyMTz75BGeddRaOHz+OyspK9T3/9E//BEmS8MILL4Qd08zCUl1djc7OTuTl5UV7OgKBQCAQCNJIV1cX8vPzo1q/Ywq6LSkpgc1mQ3Nzs+7nzc3NqKioMP2dioqKQd/P/o3lmC6XC3l5ebovgUAgEAgEI5eYBIvT6cScOXOwZo1m4gqFQlizZo3O4sKzYMEC3fsB4L333lPfX1dXh4qKCt17urq6sH79+ojHFAgEAoFAcGoRc1j0ihUrcN1112Hu3LmYN28eHnnkEfT29qpZQ9deey1GjRqFVatWAQBuv/12nHvuufjlL3+Jiy++GM8//zw2btyI3/3udwCoH/GOO+7Az372M0yYMAF1dXX48Y9/jKqqKixbtsy6MxUIBAKBQDBsiVmwXHHFFThx4gRWrlyJpqYmzJ49G6tXr1aDZhsaGiDLmuHmzDPPxP/+7//ivvvuww9/+ENMmDABr732GqZPn66+5+6770Zvby9uuukmdHR04Oyzz8bq1avhdg9eLEkgEAgEAsGpQUxBt5lKLEE7AoFAIBAIMoOkBd0KBAKBQCAQpAMhWAQCgUAgEGQ8QrAIBAKBQCDIeIRgEQgEAoFAkPEIwSIQCAQCgSDjEYJFIBAIBAJBxiMEi0AgEAgEgoxHCBaBQCAQCAQZjxAsAoFAIBAIMp6YS/NnIqxYb1dXV5pHIhAIBAKBIFrYuh1N0f0RIVi6u7sBANXV1WkeiUAgEAgEgljp7u5Gfn7+oO8ZEb2EQqEQjh8/jtzcXEiSZOmxu7q6UF1djSNHjozYPkUj/RxH+vkBI/8cR/r5ASP/HEf6+QEj/xyTcX6EEHR3d6OqqkrXONmMEWFhkWUZo0ePTurfyMvLG5E3IM9IP8eRfn7AyD/HkX5+wMg/x5F+fsDIP0erz28oywpDBN0KBAKBQCDIeIRgEQgEAoFAkPEIwTIELpcL999/P1wuV7qHkjRG+jmO9PMDRv45jvTzA0b+OY708wNG/jmm+/xGRNCtQCAQCASCkY2wsAgEAoFAIMh4hGARCAQCgUCQ8QjBIhAIBAKBIOMRgkUgEAgEAkHGIwTLEDz++OOora2F2+3G/PnzsWHDhnQPKS7+7d/+DZIk6b4mT56svj4wMIBbb70VxcXFyMnJweWXX47m5uY0jnhw/va3v+GSSy5BVVUVJEnCa6+9pnudEIKVK1eisrISWVlZWLRoEfbu3at7T1tbG66++mrk5eWhoKAAN954I3p6elJ4FoMz1Dlef/31Ydd0yZIluvdk8jmuWrUKZ5xxBnJzc1FWVoZly5Zh9+7duvdEc182NDTg4osvhsfjQVlZGe666y4EAoFUnoop0ZzfeeedF3YNb775Zt17MvX8AOCJJ57AzJkz1UJiCxYswNtvv62+PpyvHzD0+Q3362fGgw8+CEmScMcdd6g/y5jrSAQRef7554nT6SRPPfUU2bFjB1m+fDkpKCggzc3N6R5azNx///1k2rRppLGxUf06ceKE+vrNN99MqquryZo1a8jGjRvJV77yFXLmmWemccSD89Zbb5Ef/ehH5JVXXiEAyKuvvqp7/cEHHyT5+fnktddeI1988QW59NJLSV1dHenv71ffs2TJEjJr1izy6aefko8++oiMHz+eXHXVVSk+k8gMdY7XXXcdWbJkie6atrW16d6Tyee4ePFi8sc//pFs376dbNmyhVx00UVkzJgxpKenR33PUPdlIBAg06dPJ4sWLSKbN28mb731FikpKSH33ntvOk5JRzTnd+6555Lly5frrmFnZ6f6eiafHyGE/PWvfyVvvvkm2bNnD9m9ezf54Q9/SBwOB9m+fTshZHhfP0KGPr/hfv2MbNiwgdTW1pKZM2eS22+/Xf15plxHIVgGYd68eeTWW29V/x8MBklVVRVZtWpVGkcVH/fffz+ZNWuW6WsdHR3E4XCQl156Sf3Zrl27CABSX1+fohHGj3ExD4VCpKKigvznf/6n+rOOjg7icrnIc889RwghZOfOnQQA+eyzz9T3vP3220SSJHLs2LGUjT1aIgmWyy67LOLvDLdzbGlpIQDIunXrCCHR3ZdvvfUWkWWZNDU1qe954oknSF5eHvF6vak9gSEwnh8hdMHjFwYjw+n8GIWFheQPf/jDiLt+DHZ+hIys69fd3U0mTJhA3nvvPd15ZdJ1FC6hCPh8PmzatAmLFi1SfybLMhYtWoT6+vo0jix+9u7di6qqKowdOxZXX301GhoaAACbNm2C3+/XnevkyZMxZsyYYXmuBw8eRFNTk+588vPzMX/+fPV86uvrUVBQgLlz56rvWbRoEWRZxvr161M+5nhZu3YtysrKMGnSJNxyyy1obW1VXxtu59jZ2QkAKCoqAhDdfVlfX48ZM2agvLxcfc/ixYvR1dWFHTt2pHD0Q2M8P8af//xnlJSUYPr06bj33nvR19envjaczi8YDOL5559Hb28vFixYMOKun/H8GCPl+t166624+OKLddcLyKzncEQ0P0wGJ0+eRDAY1F0AACgvL8eXX36ZplHFz/z58/H0009j0qRJaGxsxE9+8hOcc8452L59O5qamuB0OlFQUKD7nfLycjQ1NaVnwAnAxmx27dhrTU1NKCsr071ut9tRVFQ0bM55yZIl+MY3voG6ujrs378fP/zhD7F06VLU19fDZrMNq3MMhUK44447cNZZZ2H69OkAENV92dTUZHqd2WuZgtn5AcC3vvUt1NTUoKqqClu3bsUPfvAD7N69G6+88gqA4XF+27Ztw4IFCzAwMICcnBy8+uqrmDp1KrZs2TIirl+k8wNGxvUDgOeffx6ff/45Pvvss7DXMuk5FILlFGHp0qXq9zNnzsT8+fNRU1ODF198EVlZWWkcmSBerrzySvX7GTNmYObMmRg3bhzWrl2LhQsXpnFksXPrrbdi+/bt+Pvf/57uoSSFSOd30003qd/PmDEDlZWVWLhwIfbv349x48alephxMWnSJGzZsgWdnZ34y1/+guuuuw7r1q1L97AsI9L5TZ06dURcvyNHjuD222/He++9B7fbne7hDIpwCUWgpKQENpstLBK6ubkZFRUVaRqVdRQUFGDixInYt28fKioq4PP50NHRoXvPcD1XNubBrl1FRQVaWlp0rwcCAbS1tQ3LcwaAsWPHoqSkBPv27QMwfM7xtttuwxtvvIEPP/wQo0ePVn8ezX1ZUVFhep3Za5lApPMzY/78+QCgu4aZfn5OpxPjx4/HnDlzsGrVKsyaNQuPPvroiLl+kc7PjOF4/TZt2oSWlhacfvrpsNvtsNvtWLduHR577DHY7XaUl5dnzHUUgiUCTqcTc+bMwZo1a9SfhUIhrFmzRue/HK709PRg//79qKysxJw5c+BwOHTnunv3bjQ0NAzLc62rq0NFRYXufLq6urB+/Xr1fBYsWICOjg5s2rRJfc8HH3yAUCikTjrDjaNHj6K1tRWVlZUAMv8cCSG47bbb8Oqrr+KDDz5AXV2d7vVo7ssFCxZg27ZtOmH23nvvIS8vTzXbp4uhzs+MLVu2AIDuGmbq+UUiFArB6/UO++sXCXZ+ZgzH67dw4UJs27YNW7ZsUb/mzp2Lq6++Wv0+Y66jZeG7I5Dnn3+euFwu8vTTT5OdO3eSm266iRQUFOgioYcLd955J1m7di05ePAg+fjjj8miRYtISUkJaWlpIYTQtLUxY8aQDz74gGzcuJEsWLCALFiwIM2jjkx3dzfZvHkz2bx5MwFAHn74YbJ582Zy+PBhQghNay4oKCCvv/462bp1K7nssstM05pPO+00sn79evL3v/+dTJgwIWNSfgkZ/By7u7vJ97//fVJfX08OHjxI3n//fXL66aeTCRMmkIGBAfUYmXyOt9xyC8nPzydr167VpYX29fWp7xnqvmTplBdeeCHZsmULWb16NSktLc2ItNGhzm/fvn3kgQceIBs3biQHDx4kr7/+Ohk7diz56le/qh4jk8+PEELuuecesm7dOnLw4EGydetWcs899xBJksi7775LCBne14+Qwc9vJFy/SBiznzLlOgrBMgS//vWvyZgxY4jT6STz5s0jn376abqHFBdXXHEFqaysJE6nk4waNYpcccUVZN++ferr/f395Hvf+x4pLCwkHo+HfP3rXyeNjY1pHPHgfPjhhwRA2Nd1111HCKGpzT/+8Y9JeXk5cblcZOHChWT37t26Y7S2tpKrrrqK5OTkkLy8PHLDDTeQ7u7uNJyNOYOdY19fH7nwwgtJaWkpcTgcpKamhixfvjxMTGfyOZqdGwDyxz/+UX1PNPfloUOHyNKlS0lWVhYpKSkhd955J/H7/Sk+m3CGOr+Ghgby1a9+lRQVFRGXy0XGjx9P7rrrLl0dD0Iy9/wIIeQ73/kOqampIU6nk5SWlpKFCxeqYoWQ4X39CBn8/EbC9YuEUbBkynWUCCHEOnuNQCAQCAQCgfWIGBaBQCAQCAQZjxAsAoFAIBAIMh4hWAQCgUAgEGQ8QrAIBAKBQCDIeIRgEQgEAoFAkPEIwSIQCAQCgSDjEYJFIBAIBAJBxiMEi0AgEAgEgoxHCBaBQJDRnHfeebjjjjvSPQyBQJBmhGARCAQCgUCQ8YjS/AKBIGO5/vrr8cwzz+h+dvDgQdTW1qZnQAKBIG0IwSIQCDKWzs5OLF26FNOnT8cDDzwAACgtLYXNZkvzyAQCQaqxp3sAAoFAEIn8/Hw4nU54PB5UVFSkezgCgSCNiBgWgUAgEAgEGY8QLAKBQCAQCDIeIVgEAkFG43Q6EQwG0z0MgUCQZoRgEQgEGU1tbS3Wr1+PQ4cO4eTJkwiFQukekkAgSANCsAgEgozm+9//Pmw2G6ZOnYrS0lI0NDSke0gCgSANiLRmgUAgEAgEGY+wsAgEAoFAIMh4hGARCAQCgUCQ8QjBIhAIBAKBIOMRgkUgEAgEAkHGIwSLQCAQCASCjEcIFoFAIBAIBBmPECwCgUAgEAgyHiFYBAKBQCAQZDxCsAgEAoFAIMh4hGARCAQCgUCQ8QjBIhAIBAKBIOMRgkUgEAgEAkHG8/8BUdbOyMERX3sAAAAASUVORK5CYII=", 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", 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", 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9i/Wt6wEAteW16FnZM48zjw6Rl/bOmzcPU6dOFR6bNm2aK0Xc2dmJzs5O9ndzc3NUp6cQc9z78b3408I/CY99Z/R38OGmD7F021LP1w/qMQj/+eZ/ChIUbGjdwAZEit7VvTGgdkDkx84F6XQaM2bMwD//+U+Ul5fjggsuwKxZs6BpGpqamnDppZey63TVqlW4+OKLMWfOHCQSCRx77LH485//jP79+wMArrvuOjz11FO45JJLcN1112Hr1q04/fTT8ec//xk333wzbrnlFmSzWfz4xz/GL3/5S3YOt9xyC/7+979jxYoVaGxsxPTp0/G73/0OPXqQSeDLL7/EjBkz8Oabb6KrqwtNTU34/e9/j+OPPx7btm3DjBkz8NJLL6GlpQWDBw/GL37xC5x11lmhfk66rmP59uXoynQBIAHxyIaRJRto5oOPNn2EM2afwQKzAwYcgL9N+5vn66566yo8s/wZx+dH9RqFf0//t02I255uxwlPnIBN7ebCozJZiUdPfBQjGkYAIAuA6U9Ox9rWtQDIhPvst54VJmQvtKfbcfwTxwvXb2WyEo9NfwzDew73vR8/0HUd33v2e2z8qkpW4bHpj6GpZ1NO+7tu3nV44vMnhMd+su9PcOb4MwEAl/z3Erz21WsAgDKtDHcfczf2H7B/zucfFSIPRtavX88GLIr+/fujubkZ7e3tqK6utr3mxhtvxPXXXx/1qSmUAD7Z/AkAchFBA9LZND7Y+AGWbV8GAKhIVDhWEnRmOrGmZQ22dmxF/9r+0m3CRHu6Hbquo8twhdehY5vehvrydOTHri5PBq6oeOCBB/DDH/4Q8+fPx/vvv4/zzjsPQ4cOxbnnnitsl81m8Y1vfAM9evTAa6+9hnQ6jYsuuginnHIK5s6dy7Zbvnw5XnjhBcyePRvLly/HySefjBUrVmD06NF47bXX8Pbbb+Pss8/G1KlTceCBBwIgzqG33XYbhg8fjhUrVuDCCy/EFVdcgTvuuAMAcNFFF6Grqwuvv/46amtrsXjxYhaoXH311Vi8eDFeeOEF9OnTB8uWLUN7e3sen6IcGT3DAhGArDQ7M53dMhhZsm0JC0QA4OPNH/t6HbuOE2VIaiaTous6urJd+Hzb5+jMdKKqrEp43YbWDSwQqUxWoivThc5MJ5ZuX8qCka0dW1kgAgCtqVZ8seOLQMHI+tb1LBDhj/P5ts9DD0a6sl3CQqoj04Fl25flHIzQ76AsUQboQFpP45Mtn9ieB8hzn275tHsGI7ngyiuvxMyZM9nfzc3NGDJkSBHPSKFY0HWS8rjywCsxqMcgnP/K+cjoppfC69973ZHi3PufeyOdTbO0SSHQmdJx0m2rLI9+GvlxF8+ahpqKYJfzkCFD8Mc//hGapmHMmDH4+OOP8cc//tEWjMyZMwcff/wxvvjiC3Yd/uMf/8Cee+6J9957D/vvTwa2bDaL++67D3V1dRg3bhyOPPJILFmyBM8//zwSiQTGjBmDm266Ca+++ioLRniGtKmpCb/+9a9x/vnns2Bk1apVOOmkkzBhwgQAwIgRI9j2q1atwt5774399tuPvT5qVJVVoSPdUdDfVJxAr8c9GvfAZ1s/8/864/O65+h7sN+A/djjbak2HPjQgcI2stfVVdTh7VPfxtkvno331r8HflO6TXmiHEPqhmDFjhXB3hS3j56VPfHm997EmbPPxIINCyL5nulnCJifYz7Hofu7c+qdWL59OW6cf6NwDHp/bONYfLr109j+diMv7R0wYAA2bNggPLZhwwbU19dLWREAqKysRH19vfBPoXuCv3A0kJU/n3emj8ng9pwCcNBBBwlsysEHH4zPP//cZpz16aefYsiQIcKCYNy4cWhoaMCnn5qBVlNTE+rq6tjf/fv3x7hx44QGbv3798fGjRvZ36+88gqOOuooDBo0CHV1dTjttNOwZcsWtLW1AQAuueQS/PrXv8ahhx6Ka6+9Fh999BF77QUXXICHH34YkyZNwhVXXIG33347hE/FjrgO3sWE7Fp0Az85BtnG+tnT4zp9J+x5H8ezHCic/fg6lPuYlg/o9cwfg2nYYu5FEzkzcvDBB+P5558XHnv55Zdx8MEHR31ohV0A/IVELyYhGHG5wBJawrZ91Kgs1zDvlwdDg4Y1O79CdXkNmnoOi/y41eXFF1Rabcg1TZM+ls2S72PlypU48cQTccEFF+A3v/kNGhsb8eabb+KHP/whurq6UFNTg3POOQfTpk3Dc889h5deegk33ngjbr75Zlx88cU47rjj8OWXX+L555/Hyy+/jKOOOgoXXXQR/vCHPxTsPXc30MmZXltBJ2vr9Ur3AzgEGMZDdNKWjQH0HDRwYwSCXfO86Jw/r6iZkTCOw7//BOzfC/2saHqskONhEARmRlpaWrBo0SIsWrQIACndXbRoEVatItT0lVdeidNPP51tf/7552PFihW44oor8Nlnn+GOO+7Ao48+issuuyycd6Cwa4MbjKTBiA9mpFArWx06NE1DTUUSNRVJVFUkUF2RQE1FWeT/cln1vPvuu8Lf77zzDkaNGoVkUgxsxo4di9WrV2P16tXsscWLF2P79u0YN25cbh8WgAULFiCbzeLmm2/GQQcdhNGjR2Pt2rW27YYMGYLzzz8fTzzxBH7yk5/gnnvuYc/17dsXZ5xxBv7v//4Pt956K+6+++6cz8cR3M+nu7Nt9FqiE5vfa8s62VPwv1s3ZoRuJ7umZQuWoEESP6ELx4mAGeHB9DN5HEb6/iWfT5QBVhgIzIy8//77OPLII9nfVNtxxhln4P7778e6detYYAIAw4cPx3PPPYfLLrsMf/rTnzB48GDce++9qqxXwRf4QYxG/bxmhF9ZWSELXgqNuF74ANFczJw5Ez/60Y+wcOFCVvlixdSpUzFhwgT84Ac/wK233op0Oo0LL7wQRxxxBNNr5IKRI0cilUrhz3/+M6ZPn4633noLd955p7DNpZdeiuOOOw6jR4/Gtm3b8Oqrr2Ls2LEAgGuuuQb77rsv9txzT3R2duLZZ59lz0UBfiKNepKKK6zBgd/PgU32VmaEWw/L2AxrkCBjZGRjROBgxBr05MiwBDmWcJw8xiiv/dHPIu7MSOBgZMqUKa5ftMxddcqUKfjggw+CHkpBQZ6myQbUjHTPecMTp59+Otrb23HAAQcgmUzixz/+sdToTNM0PP3007j44otx+OGHC6W9+WDixIm45ZZbcNNNN+HKK6/E4YcfjhtvvFFgVjOZDC666CJ89dVXqK+vx7HHHos//vGPAEhzuCuvvBIrV65EdXU1Jk+ejIcffjivc3KFZvzrxrBObPkyI/yfrsyIlbHgV/66OzMQ5PzM04pQM8LtM+jn6LY/zfjPuj8rMxJXxLKaRkHBCv5C45kRt/RErgNTvhAG3JgGQnxJ7l//+lfb8ytXrhT+Hjp0KJ5++mnH/V133XW47rrrhMdkCxP+uABw2WWX2VK2p512GrvvFvBcddVVuOqqqxyfDwtxZreKhbBYR54ZcZv42XVu3DgdN19BaCE0I8LxQmRvNU2TM0cWnU9cmZF4h0oK3R78RRVUM0IHumJcfHFXrivkBqUZyU1/4JSmETQjLqW9FLI0DM+e5MyMWM9PEx8PE/y5hclW+GVG4ppiVMGIQqwhK4Pzy4yYWZriXXxqVb3rQNCMdPPv1S+jwbbxKMUF5IsG676l13sEAuMoFzJCMBLCcaRBnIQZCSMlFCVUMKIQa/CaERnN6MqMFHglENeLXEEhLFgpfyDY7961msZlPyx9Ipm8vcYIP7BpUyJkNiMr7eXfPye8pZ+FYkYUFPKBxWcACKAZKXBpr8KuCRk7110hE0P6mfitVTE83CZJm2GXhO0U0jQ5Ck9tVTsFSvGGESDI0lT8kJdrOXahoYIRhVhDtuqRrc5kKJRXgNuxFRR2JeTKjLi5gLotGvwECWGanrHLNsIUb1TMCCAX8Fo/eyVgVVDIAbKyNcqMeE34UXoFSCEZT+K6ClEIAPW9MsiYkSCaEdk16zZJ+kmf8IFEruX8fkqIw4JMwBqGZsTR9ExpRhQUwoV10PLK6xaLGVGVNLsmFNtlIjAzoluYBw6+PleWpXG+pvOppmHxjOZsrhYWZMFIGAGCU5pKVdMoKIQAWdTvlxmJu/2xQmlAWHlLcvLdEUE1IxRumpEgzAjPdgpjREg+I4VayIR5HA2adMyz9qaJ63ioghGFWMNNPOiZpomDZiSe172CQk6QakbyKO0FPFIiusO2/DH50t6wHFijtIOXaUbyEbBKNCOy90+7ZytmREEhF3DVNFbBqqdhUIF9RoTjKEZ/l0ZcV5dRQ6b98PVZSKriKHxpRqzpE4dqmlwn90I2ypP1kslLwCphj+lnKQQ+VPxbKA1dQKhgRCHWkJXtUXhpM+KQI+2uk1YcoGkannrqqfD2pyJMW5koEFDA6lJNIyVGfAQJXr1Z/MBP0BM2+PMNRcAq0Yzw+2WLt5gOSSoYUYg1ZFE/he80TVyvPoWSgPIZMSGzdQ9U2uumGZF17bW+TtKbxo0Z8ItiNMrLp7GfbH/Q7EEUv99kIt5de1UwohBryFY9FH6ZkaL0pon5pDVlyhRcfPHFuPTSS9GrVy/0798f99xzD1pbW3HWWWehrq4OI0eOxAsvvMBe88knn+C4445Djx490L9/f5x22mnYvHkze3727Nk47LDD0NDQgN69e+PEE0/E8uXL2fMrV66Epml44okncOSRR6KmpgYTJ07EvHnzPM9X13X07dsXjz/+OHts0qRJGDhwIPv7zTffRGVlJdra2tDU1AQA+Na3vgVN09jfCvkhX9MzGdwm/iBpGmFfQZkRKwMToSeHkFaS9NrJZ3/WzzJsT5MooYIRhdKAZp/gEz5/vgW9+HQdWlc70NUGLdUOLdUOdLVG/y+HweyBBx5Anz59MH/+fFx88cW44IIL8J3vfAeHHHIIFi5ciGOOOQannXYa2trasH37dnzta1/D3nvvjffffx+zZ8/Ghg0b8N3vfpftr7W1FTNnzsT777+POXPmIJFI4Fvf+hayWXFA/+Uvf4nLL78cixYtwujRo3HqqacinU67nqumaTj88MNZ199t27bh008/RXt7Oz777DMAwGuvvYb9998fNTU1eO+99wAAf//737Fu3Tr2d1iI64BeKARt8OaWpgmi7XIL8vNxYGX70MRgJErTM40MaqEdh98fZZkEZkSLNzNSVuwTUFBwg0ycxuBBPhSjmkZLd6DHH0YBAMYV7KgAfrEWqKgN9JKJEyfiqquuAgBceeWV+O1vf4s+ffrg3HPPBQBcc801+Otf/4qPPvoIr7zyCvbee2/ccMMN7PX33XcfhgwZgqVLl2L06NE46aSThP3fd9996Nu3LxYvXozx48ezxy+//HKccMIJAIDrr78ee+65J5YtW4Y99tjD9XynTJmCu+66CwDw+uuvY++998aAAQMwd+5c7LHHHpg7dy6OOOIIAEDfvn0BAA0NDRgwYECgz8UGF/Fld0UUpb1SZsTqwCphO2W9WXKd3K1Or5GOHVpI7C3nkcIWaDq9sTMjcUW8z06h20O2iqBQPiP5Ya+99mL3k8kkevfujQkTJrDH+vfvDwDYuHEjPvzwQ7z66qvo0aMH+0eDB5qK+fzzz3HqqadixIgRqK+vZ6mRVatWOR6Xplk2btzoeb5HHHEEFi9ejE2bNuG1117DlClTMGXKFMydOxepVApvv/02pkyZEvyD8ID6/ZjIt1GeDLmkVhy3pUxD0Goah9LeqB1Ywwhw3apzZALWuP6eFTOiUDKwpmU8e9NohWVGdOjQy6rQcvnnSGgJrGxeifJEOUb1Ghn9wctrgr+kvFz4W9M04TGWN89m0dLSgunTp+Omm26y7YcGFNOnT8ewYcNwzz33YLfddkM2m8X48ePR1dXleFz+GF6YMGECGhsb8dprr+G1117Db37zGwwYMAA33XQT3nvvPaRSKRxyyCE+330OUKZnUiFqWI3ygpT2SgWsnAYjsIBVIszl9x0FeLY3rGoa6/5kmhGVplFQyAFhVNMU9OLTNKCiBpqWhF5eDT1RHjh9Ekfss88++Pe//42mpiaUldmHjS1btmDJkiW45557MHnyZABEUBomNE3D5MmT8fTTT+N///sfDjvsMNTU1KCzsxN33XUX9ttvP9TWmp91eXk5MpmMyx5zR1xXl1HDarDl93Nw1YxYtpEdz1ra67RNrq0YrEFWlBO3LDALq1GedX8yzYgyPVNQyAH8hWtlRjx700RItXqiwIZrUeOiiy7C1q1bceqpp+K9997D8uXL8eKLL+Kss85CJpNBr1690Lt3b9x9991YtmwZ/vvf/2LmzJmhn8eUKVPwr3/9C5MmTUKPHj2QSCRw+OGH48EHH2R6EYqmpibMmTMH69evx7Zt2/I+ttKMiEFFkAnbT2mvn2oaGdvJ2/Xny4xQRPld5/oZBtmfqqZRUAgZwiAWVDNSCBFaN8Fuu+2Gt956C5lMBscccwwmTJiASy+9FA0NDUgkEkgkEnj44YexYMECjB8/Hpdddhl+//vfh34eRxxxBDKZjKANmTJliu0xALj55pvx8ssvY8iQIdh7771zPmZcB+9iwK2M1PV1PhrlBWFGnNI0uS4C/KSDwoKbkWM+kJm+lRIzotI0CrGGtD24Ad+akUJNJiVUdUFLZHmsXLnS9hg/cI0aNQpPPPGE4z6nTp2KxYsXO76+qanJNhA2NDQEGhwnTZpk2/7SSy/FpZdeatt2+vTpmD59uu99+0EpfLeRgvuNa5oG6Pmbnvmxg7duKzzOVZPka3RoPb+CmZ6F0JtG5ugqE7AqO3gFhTwgK+31OzEUfGUrCZwUdi10d7ZEmPgDTKTSYMRHAMEYCxe2M5/eNNZzKdTEHaauzcvRNe7MiApGFOINfiVmz9O4Ig7q8e4+aQUBdXeV/eP9TYoFFWDKfSt8Tdgul0GQAEI22UodWHNslGfdTxSXb1SN8oT9SXrT5CruLRRUmkYh1pBdaBSeaZoIBxQZVOCRH+699160t7dLn2tsbCzw2Zhw0zt0N7hNfH5e59Yoz4/pmVQzIqmmCcpoOAllI2FGuAVW2Hbw1v0pB1YFhZAg5Fcts4Ff07O45kgVRAwaNKjYp+CJ7s6OSDvkBglG3DQjPhrluTEjuaaOrPvjjxeJZkRiVxBWozw307OiVhf6gErTKMQabnbwfu2Ni5Ej7e6T1q6OuObdo0auE6mb6VmQRnmybcNIe1hNzwrhwCoTnEa1v7AM1qKECkYUYg030zMvxGIl0D3nrF0SsvLy7gYpMxKgmkb2+bn5X1gDFGnXXokXUa7MiFXAGmk1DcJhRmwVTrJjSZjluEEFIwqxhttg4MWMFMtnJCxnRQWFuIJfHOTbKM9Ne+KkNZFW02i5+4xYy/LzLRF2P5QZmIUR9MjSVNbS3gQSihlRUAgDuZT2xsGBVaH0EXZjs10BQZkR9jo3Aatbaa+PktswUhE2AWuEE3eun6Hb/qzMkYyRiusCSQUjCiUBqYDVpx18MVYCatLatRHXAT1qyEp7AzmwSuB6nVpeJquQCyNYdBSwRsmMIJwxyi29xbosc8xIXPVOKhhRiDVkgx+FJzMS4YAiQylNULqu47zzzkNjYyM0TUNDQ4PUxVSGKVOmeG6raRqeeuqpvM/TL6677jpMmjQp0mOEFWAW+rMJE9ZGedbHHF/nVk3j8rn6qqbhdBG5MiOF1IwwsiIEx1jAoplxYEbyqTQqFFRpr0Ks4arC92JGJKsoBYLZs2fj/vvvx9y5czFixAgkEglUV1eHtv9169ahV69eoe3PC5dffjkuvvjiQK9pampytJKPEvxns3LlSgwfPhwffPBB5MFUGJAJyv2Uzrtdx24BhKP/h1NvGstjfuFkehZpaS/yd4zl9wfNft5CpU0cBP0uUMGIQqzhWtrrQezFwWckrhf+8uXLMXDgQBxyyCGR7H/AgAGR7NcJ1Kk1Cgg+DiGwI4X+bMJEzo3yHISosm2ExxxMz2TMiPB8rtU0BTA9y9WrxQuCZgaigFUmbo0bVJpGIdZwa5Tnt9S3YLRkPOMOG84880xcfPHFWLVqFTRNQ1NTky31cscdd2DUqFGoqqpC//79cfLJJwv7yGazuOKKK9DY2IgBAwbguuuuE57nUxErV66Epml44okncOSRR6KmpgYTJ07EvHnzhNfcc889GDJkCGpqavCtb30Lt9xyCxoaGny9J2ua5swzz8Q3v/lN/OEPf8DAgQPRu3dvXHTRRUilUgBIqunLL7/EZZddZisbf/PNNzF58mRUV1djyJAhuGLmFWhrbWPPH7PPMbj197fi7LPPRl1dHYYOHYq7776bPd/V1YUZM2Zg4MCBqKqqwrBhw3DjjTdKP5vhw4cDAPbee29omoYpU6bg9ddfR3l5OdavXy+8x0svvRSTJ0/29XlEBq7qJEhLerdt/DAj1m1lPiN8mibfRnmFMj3LufqH358u2R89b0nZb1wXSCoYUYg1ZDX5FF7BSDGYEV3X0ZHuEP61pdoi/xdk0PzTn/6EWbNmYfDgwVi3bh3ee+894fn3338fl1xyCWbNmoUlS5Zg9uzZOPzww4VtHnjgAdTW1uLdd9/F7373O8yaNQsvv/yy63F/+ctf4vLLL8eiRYswevRonHrqqUin0wCAt956C+effz5+/OMfY9GiRTj66KPxm9/8xvd7kuHVV1/F8uXL8eqrr+KBBx7A/fffj/vvvx8A8MQTT2Dw4MGYNWsW1q1bh3Xr1gEgjNGxxx6Lk046CR999BEeeeQRzHt7Hm74+Q1CMHznbXdiv/32wwcffIALL7wQF1xwAZYsWQIAuO222/DMM8/g0UcfxZIlS/Dggw+iqalJeo7z588HALzyyitYt24dnnjiCRx++OEYMWIE/vnPf7LtUqkUHnzwQZx99tl5fSb5ImcNgqV0loefdKrN9EyysTDh5tibxqYZiVjAStndsE3PWG8aY+xLaImiWR34hUrTKJQEcrGDZ8FKAa+9zkwnjnj0iMId0MC7338XNeU1vrbt2bMn6urqkEwmpSmDVatWoba2FieeeCLq6uowbNgw7L333sI2e+21F6699loAwKhRo/CXv/wFc+bMwdFHH+143MsvvxwnnHACAOD666/HnnvuiWXLlmGPPfbAn//8Zxx33HG4/PLLAQCjR4/G22+/jWeffdbXe5KhV69e+Mtf/oJkMok99tgDJ5xwAubMmYNzzz0XjY2NSCaTqKurEz6DG2+8ET/4wQ8YSzRq1Cj87ubf4fijj8eNt96Iqh5VAICjjjkKF154IQDgZz/7Gf74xz/i1VdfxZgxY7Bq1SqMGjUKhx12GDRNw7BhwxzPsW/fvgCA3r17C+fxwx/+EH//+9/x05/+FADwn//8Bx0dHfjud7+b8+cRJviJ35dmxCVN42fRYBWwyibvfBxNg/iZ5Au3BVY+kApYwzZYixCKGVEoCUiZkZhV0+wqOProozFs2DCMGDECp512Gh588EG0tbUJ2+y1117C3wMHDsTGjRtd98u/ZuDAgQDAXrNkyRIccMABwvbWv4Nizz33RDKZDHSOH374Ie6//36hY/C3p38b2WwWq79czbYbO34su69pGgYMGMD2feaZZ2LRokUYM2YMLrnkErz00kuBz/3MM8/EsmXL8M477wAA7r//fnz3u99FbW1t4H2FCVkflCCXl2vlTIBGeUKahncZzXPCdavaCRth6ThkLqsyn5FiWh34gWJGFGINftAJ2pum0BefDh2VyUq8dsprKNPK8Pm2zwEAY3uP9Xhl/qguC68Spq6uDgsXLsTcuXPx0ksv4ZprrsF1112H9957j2k4ysvLhddomoZs1v1z5l/DvhuP1+SDXM6xpaUFP/rRj3DJJZewx3Z27cT6lvUYOnwoG+zLysWhk9/3Pvvsgy+++AIvvPACXnnlFXz3u9/F1KlT8fjjj/s+9379+mH69On4+9//juHDh+OFF17A3Llzfb8+KuSaYvCjGZEKWK3+Hy6N8vhzyreaplBupaE0ynPxLWE+I1oi9oszFYwoxBqyfKhfFOPi0zQN1WXVKEuUoaqMUPp+0ydxQllZGaZOnYqpU6fi2muvRUNDA/773//i29/+diTHGzNmjE27Yv07bFRUVCCTyQiP7bPPPli8eDFGjhzJHtvRuQMVOytQWV7pe9/19fU45ZRTcMopp+Dkk0/Gsccei61bt6KxsdF2DgBs5wEA55xzDk499VQMHjwYu+++Ow499NAgby8S5Foqam1Ex8NNe2J9nUz3IG2Ul2vXXk08pyggqxAMy/TMet7S8TOesYgKRhTiDZlgjsKzN00RHQcFzwNdDzU3HDWeffZZrFixAocffjh69eqF559/HtlsFmPGjInsmBdffDEOP/xw3HLLLZg+fTr++9//4oUXXoj0c2tqasLrr7+O733ve6isrESfPn3ws5/9DAcddBBmzJiBc845B7W1tXjvw/fw7AvP4oZbbvC131tuuQUDBw7E3nvvjUQigcceewwDBgyQVgb169cP1dXVmD17NgYPHoyqqir07NkTADBt2jTU19fj17/+NWbNmhXmW88ZsrLUsJgRV58RM0qw7U8W6ARmRizHiZJVlX2G+e0QbH/Wz5L1ptESsbA6cIPSjCgER6oD2L6qIIcSPASUZqQgaGhowBNPPIGvfe1rGDt2LO68807861//wp577hnZMQ899FDceeeduOWWWzBx4kTMnj0bl112GaqqqiI75qxZs7By5UrsvvvuTEi611574bXXXsPSpUsxefJk7L333rhh1g3oO6Cv7/3W1dXhd7/7Hfbbbz/sv//+WLlyJZ5//nkkEvbhtqysDLfddhvuuusu7LbbbvjGN77BnkskEjjzzDORyWRw+umn5/+GQ0QuXbQBh2vWpbzVyljIUkOhMA2Wap+C2MGHpOOQVjhZNSP89qqaRmGXwRPnAJ/+B7hgHtB/XEEOKVtFeDEjtpr7AiFKijcsWJ1HeT3CYYcd5qpPkD1ntTfnP/Ompibbd9DQ0GB77Nxzz8W5554r/M2nS9xw3XXXCV4ntISXx6233ir8fdBBB+HDDz+0bbf//vsLotPtHduxpmUNAPLdvrTwJTRWi+mWRYsWOb4PK6zv+5xzzsE555wj3XbNmjU4/vjjmeC32JC6h3pM2G4LCsCju7Y1SJAFQLyXhkvKx/UcLdU0UbKq0lLcEDQjGkyfEatmRGaIFjeoYEQhONYsJLfrFhUuGNHsDqxec34YNfxhQIdeEgFKsfGHP/wBRx99NGpra/HCCy/ggQcewB133FHs02IoZKptx44d+Pjjj/HQQw/hmWeeKdhxg8BvmsarkZ0f7YkfxiIf0zNbmiZKVpUGT1o4dvAUmqaZrtTM84wTsBbB6iAIVDCiEAyZNLCTGERhx5rIDycTzFH49hkpAlTwERzz58/H7373O+zcuRMjRozAbbfdxhiDPffcE19++aX0dXfddRd+8IMfFPJUIx/Qv/GNb2D+/Pk4//zzXb1bCg2pPiPAROpmehZqb5o8J/dCVOKFxoxImCepz0gIZcRRQgUjCsGwcx1Af8zNX0V+OOvgp0ETon03FJoZUdqU/PDoo486Pvf8888zK3cr+vfvH9UpAbB8rwWKMeNQxiuDrIt2kDSNDG7MiK20V5KGkVbT5FnaWwg7eCBczQhgH/NoSiYMD5aooYIRhWBo5tiQAjIjFJqmuXYAFTeW70Oh9ODmYlpIdHdRdC5N3mSTLw9XnxEfNu2CF1GOlueOmpEoBKwRNsqzjXlcSijuv11VTaMQDDs4NqS5AMGIgwMj4J2GydUASUFBBpV6s1Ru+LSD97r+XH1GAjAj+az+HTUjETfKy5etsKZorOctFRzHtJqmWwcjP3n0Qxz/pzfw7ootxT6VwqFzJ7D+k9xfzwcjRWJG2H2fmpGoLz6Zq2euOXWF+KEUgtliVIz5vr74LFdQ0zMnzYgkABL65eRa2ms5TqEa5eX6/VnFwVZGh/cZiTsz0q3TNCu3tGLxumZsa5PnondJPH0RsPhp4Pg/AAc4lx86gg9GOneQ4KayLrzzc4C1ayfgww4+wtUNQNwzE4kE1q5di759+yLblUVWz6KrowvZZBbZFBkIOjo6kEwkPfamEFd0dXYhm8oijTRSmRS5r6XRUdZR7FMDQH7fmzZtgqZpNgv8KI4FGBOfz4nUbzWNlGFx8v+Q9abJQxDqxIxEbnoWJjMiEamGrU+JEt06GKlIkoupKxPPLyd0ZNIkEAGA5y8HhhwADJwYbB/W1EzzWqBvdM6cFNacMf+Y42sCdBXNBYlEAsOHD8e6deuwdu1arG9dTwaHGiCpJbGxlTROS2xLeHuiKMQWralW7OjcgaqyKpQnyrGzaydaylvQWtla7FNj0DQNgwcPFhoD5oVsBmjdDLRsAGp6Az0HWQ7onz3wDEZ8LBr8MBb5lMra0sEl1ChP2J9DNY3AjMSUqe3ewUiZEYyku0kwst5i8PT8T4GzXwSClMDuWG35+6tIgxE3zYi3fjX6i6+iogJDhw5FOp3GlU9fibZUG+6Yegf61/THpc9cCgB46ISH0KOiR2TnoBAtnlvxHO763104ZNAhGNFzBP5v2f/h6KajcfEeFxf71BjKy8vDC0TatwN3TgZ2GC7LWgI4/KfAkb8QS+1zmEgDC1gtjIUs2AjVRIw6vRZAXxEKM+KgqTH1qxLNiErTxA+VRjDSmbY3qdol8eU8cjtwErB5KbD6XWDxU8Ce3/K/D6oTqR9EWJKIRaxOOWPAzLc6oVAXH6XHN6Y2YmfXTiQrkqiqrsK6LuLHUl5ZjqrK6GzNFaJFV6IL67rWoTnbzO7vzO4Mx6p+yWzgxSuBqdcD476e//7CwNIXjUBEA2oagbYtwGs3AbsflVMZreeErjlv5/Rap2oa38d02Z+fx/OBtDw6BM0Ivz/KBvPWCHFnRro1d9ztmJEv3ya3478NHHQBuf/Jv/2/vqsNaN9K7g+YQG47doR3fhI4Rv7wrqYp+MXH5bf5QCmuF7+CP8hEgKHk3dd9BPzrFGDrCuCdv+a/v7DwuWGFP/knwBUrgGGHkb+3rYxEM+LmB+TEjMhMz6C5N93zc45uxwkLYTT2417IIKRpdFHAKi37jRm6dTBSWUZozc7uEoys/YDcDjkQ2P1r5D61dvcDyoJU1AF1Rq+Mrrbwzk8Cp1yu9b4UBb74ZCV7hTy+QrQIg1YX8N695v3O5vz3FwYyaWDZK+T+qGPIbW1vctuxnW0WpCzVr+mZ9LVcoEFu7NvKXJpzNT2TpoNDRiiN/Sz7ovuzPs6PSflW7kSNbp2m6VbMSDZDxGgA0DCMVMBoCSPVsg6o99GIi+pFeg4GKmrJ/a6WaM7XgFPXTvKQh89IhKsbGWS560IeXyEasNVl2AM6basAiFVqxcSaBSToqO4FDN6PPFbVQG47dkAvt0/8eWtG3JgRhyBB+PwljGSu34/V9CxKZgTIP+hxKu2lx2ECViQKIsrNBzkxI7fffjuamppQVVWFAw88EPPnz3fd/tZbb8WYMWNQXV2NIUOG4LLLLkNHR/HL4iq7UzDStgXQMwA0oLYvUNkD6DuWPLfWJztC9SI9BwFUkNkVcUWBpbSPv3b9lvYWCrKSPSC+F7+CP4RZiimgZaN5v2N75ClPX1j/EbkdciBAy9GrG8ht+3a5BiHPaho/DKaVGZX2ptFyT0XI+tsA0bAIAluRLzPiYHpG9xnmsaJG4GDkkUcewcyZM3Httddi4cKFmDhxIqZNm4aNGzdKt3/ooYfw85//HNdeey0+/fRT/O1vf8MjjzyCX/ziF3mffL7oVgLWnevJbW1fIGkQYoP2Ibdfve9vH3T11nMwUFFD7kcdjBjIpbS3WMyIVZGvUNoQOp+GqRlpsYyZ21flv898sfFTctt3D/Oxqp7k1hIssd+3x3wta+Qm7MdHDylfpb08M5JjmsZWTRNkPy2bgHSX782FtEpIdvACM2L8Z0VcF0eBR8tbbrkF5557Ls466yyMGzcOd955J2pqanDfffdJt3/77bdx6KGH4vvf/z6amppwzDHH4NRTT/VkUwqBbpWmoSmaOq6pGA1G6GrIC7QxXj2XpklFG4zYqml4AatP5qPQF18hjJMUCodImJFsFmjdRO73GEBut32Z3z7DwKYl5LbfWPMxlqbZLk1FBrGDdzM9c3stW4xI0jDSCp9ce9O4pYPcsGYBcPNoYPbPvI/Fi4DzrPhze50OXRBf71J28F1dXViwYAGmTp1q7iCRwNSpUzFv3jzpaw455BAsWLCABR8rVqzA888/j+OPP97xOJ2dnWhubhb+RQFqetYtBKyUGaEDHwA0DDWe2+BvHwIzUpg0jZPKHYhhNU3Mjq8QDmRUd97facd2IGs4Pw/al9xuj0Mw8hm55b2DOGYkjDJaK9wYTFs3XUkwKNNg5BssBg46X7oG0LPA+/JFueNx8hwjrK+zakb4NPcuZQe/efNmZDIZW8vu/v3747PPPpO+5vvf/z42b96Mww47DLquI51O4/zzz3dN09x44424/vrrg5xaTqgs707MiBGM8MxIbT9y2ypPsdnAa0YoZRt1MOLmyugzTVOwahpLyZ6maYAe34tfwR+E8kgDeX+nNEVT1QD0GQksQfHTNK2bgbbN5H6f0ebjvGZEpkHIkxmRbWd7zFJNIwQjkiq2wKW9DkJZ3/uhLBdAigVc2j9Ig9sQxghN06Dp4m+Ufjel4MAaeVJ77ty5uOGGG3DHHXdg4cKFeOKJJ/Dcc8/hV7/6leNrrrzySuzYsYP9W716teO2+YAxI93BDp6yHzwz0oMGI5vIBeQGXReZkfLCaEbcfEY8BawFapRHkRPVm0kBr1wPfPx45OenkBt4zUhoOiSaNu3Rn1S3Ae5pmuZ1wP+ejLY5JU3RNAwz07CAkKahEETaATQjsljEjW1yKu2XClj51X+e1TSBmBFdN5lnQKySkm0u2WdYpb08W5zVs1K9TlTtMfJFIGakT58+SCaT2LBBpPU3bNiAAQMGSF9z9dVX47TTTsM555wDAJgwYQJaW1tx3nnn4Ze//CUSCfuEUllZicrKyiCnlhMqyw2fkZSPL6d1C/DmLaQx3N6nAUP2j/jsQgZjRrjvqaYPAI3Qi21bgR59nV/fvg1It5P79YOIWAsonIDVUnLHP+b4mgJrNqwDp69Vz8vXAu/cTu5PODnS81PIDbIKkrxBmZEe/UhwDwA718q3XTEX+Mc3yP3hRwBnPBPOOVixSSJeBcTSXonpWaDSXplmxEf6wBbg89tS8iQPpsGP7bwjtq4gTUMptn1pfqeyY/G/pzAb5VmZEd0UsMoM0eKGQMxIRUUF9t13X8yZM4c9ls1mMWfOHBx88MHS17S1tdkCDtpDodgfSqBGea/+Bpj3F2DhA8CT5xEBWilhJ7cSo0iWkSZYgLlScwL1GKntB5RVcj4jhUnTyMyIvCaGQtfVO7Y7dxqst68yAxEgcgM5hdwQpkkVQysXjFCG0lpdQ/HZc+b9r96LbuyhzIi11xTVjHQ2Q+c8V/yW0Xr5arhNktZryndvmnwb5QXRV1iNIz20P9J+MSHYwcssBXifkbibngVO08ycORP33HMPHnjgAXz66ae44IIL0NrairPOOgsAcPrpp+PKK69k20+fPh1//etf8fDDD+OLL77Ayy+/jKuvvhrTp08Pr7FTjjCraTxSFB07gA8fNv/eugJY8WqEZxYBZMwIwKVqPHQjvF4EKFppbxAH1kILtgL3t1j1rvi3B72rUBzwpmcUeQ/oNPiv7WcuEFo3yQMNvvQ+1QZs+yK/YzuBiVetzEhP837GLF31y4zIql14+GEw/fh/5OXAatWmBNGeUEaJYttKr4MZhwpXVCo1PZMxIzHVsAV2YD3llFOwadMmXHPNNVi/fj0mTZqE2bNnM1HrqlWrBCbkqquugqZpuOqqq7BmzRr07dsX06dPx29+85vw3kWOMH1GPH5wHz5MSlj77kFo0vl3ESvnkUcV4CxDgK7LmRGABCMbF5tpFyfwehHArKZJtZIBVJJuCwNujfJ8C1iL0JvG1/GtwcfO9UDv3aM6O4UcIWVG8s270+utRz/i/QMA2TRJh1L7dQBIdQDrPyb3qxtJb6gNn0TzO2FlvZZgpKyCaMRSbdCNYMS6CneD39JeqYDVIfXJf/68R0iuqVlHvZefiZsGH/T78SjRDkNwa90X2SHsAlYukI671UBOdvAzZszAjBkzpM/NnTtXPEBZGa699lpce+21uRwqUvj2Gfn0P+R23zNJT5f5d5HOli0bTWYhzujcCWQ6yX3r+dKKGq80De8xAogCt3S7+HeIcBokAG9mxLqPQsNzQONFb4BiRmIKRnVzFQl5/6SYgLUfkCw3J7KWDWIwsv4jUgJc0wcYcyzwwf8B6z8Bxn0jzxOwoG2reU58JQ1FVYMQjAAB2QMXuKUPHAXsunybsFb/fg3dAJjByIgjiMg4QIl2vsyIU+kzYHFgDRA8Fgvd2iLSV6O8rlZg1Tvk/qhjSD510H6AngE+erQAZxkCaLleeS1QXi0+5ztNY2FGyqrBOM0IUzVOzojkIX/MSMF701gV+Y7MiEWwqIKRWELW8j1vZqRtC7mlmi3KWFoXBTRFM3h/oL/RKXvD//I7tgyUFek5hPStssJI1TBmJIgdvIcDqyszAvn1Ly3tzUOD4Vja6+d7psHI8MPJ7Xb36s8wNSM8+LQPdzAAltLemKZpunUw4osZ+fJtsjLpORRoHEEem/R9cvvB/5WGkLVtK7mt6W1/zks8R2HVjCQSXHlvdM3y3C4cv71pil3a6zigUWak51Dxb4VYgXexpMj7N9VuXJPVjeTW6TrcaAQeu00C+u9J7m/4JL9jyyAzO+NBvUa4NI3fidRr8nNLH1iDBHojlPZat/FxTMdz0cTjeH7PHc1mYDlwIrnt2un6kjBN2qz7svamoWNPqOLriNCtgxFfjfKWG0LV3acA9Ic6/ttEM7HpU2BWL+Cf3zYn/DiCrcIa7c/V+g1GKDMyxHyMVdREWAXioMPgH3NCoWlJqekZ4Ez1NhvMyKC9xb8VYoUw7bsZ2raRWy9mZMsKctt7JNBrGLm/cx3RgYUJJ/EqRR7MCIXT9eonteJHy5GPQ65Nm+K3bJmmZGp6A3VG5/POFtfvJyrNCP/+6XNROOZGBRWMwKNR3irD5n74EeZj1b2AaZwAd/kc4J077K9t2xqPIKXVSNPU9rE/xxufOSGTNlMI9YPMxwtQ3puPZqTgPiOWAdJ1QOONknYzegQpZiSWEBrlheHVkO4yV881VmbEEoxsNYKRxhGGLxAIO9HpvvoOjHVGf6r+4+XPGyyonk2zh/x+FtYg3QpfpmdBS3tzrKaRCeVdQVM0vZpMUb+eAdKdni8Nw6TNy/SMd2AttCN1UHTrYMQzTZNJk0oTANhtb/G5fc4ADrrI/Pu9e8VJ+cOHgT+OB+44qPj+Edb8NA+nQZBHy3pygSXKxWoc1p8mujQNhdT0zCczUpCLT0K9uh6/fZspKt5tErl1Mr1SKCpC733Svo3tjZXNMmaEYyg7W8yS/MbhpJy+3FgAuC0egiKbNSt2Bu4l38YSBPATqV87eEdmxMdn6qvKhaumybVRHoVvZkQIRjgRv8uYKGPawoCsmShjlrX8A5+o0a2DEU8B65bPgXQHUFEH9BouPqdpwLE3ANdsJc+1bwM+eYI8t3o+8OSPSNlrywZg2csRvgsfcAtGaJqmbYuzJTzVi9QPFEt4C+A14jaQea1eCmnyoz/0PXbfOihIBzTKNNX0JgMZQJiRmA4U3RlCf48wKkiYXqTB7GEiS9NQP5HqRsLGAmalDb2mw8D2lYSpSVbKK2kAW6+VICkRmabDui/AQTPiQxQu66qcb28as2jH43qkZbwNw8hnRHV0LsyVkKbJk72V+q1wnxFj9ZAIT3wdEbp1MEKZkXRWRzYr+dFR6nLAeGcfjUTSFLQunU1u594obvO/J0M42zxAq2mkwUgfsurRs2Y6xwrqvsrrRQBzJZCKjvlx6k0BBOhNEzUzsu1L4PPZjseXotkIRuoGmv2C0h1mA0KF+IDTLbEAN5/fFE3dUvEqIBew0hQN7ylCPUmcrtVcQMe5fmNJmbEMksAjrJW2G9vhVNor+IxEUdrrdyHD0te7kduAqeu87eAlr+NZHRbkaPAvyi0SVDBiQGoJv54GIxPcdzR6Grld/iqw8i1g+X+BRBnwnfvJ40tfLJhTqRRu1TSJpPm4U3lvM2VGBomPswuvANU0tLQPAdI0haIl//ekMCT4opR3csFIeZVJv7fHQGOkIICvpglFM0K/Y15QTgP9bStNhnLLcnJLq/gAUzcSZprGK0UDsGAEsLMQnqW9lmvYCj+aEXYaJmVh20YIFnNM0wRulEd1XlS86iN1LUt1hRXQGX+QfYJzYA0rkI4Q3ToYqeSCEWmzPL/ByIC9yI8x1Qo88v/IYxO+A4z7JpnAU232/gWFRKsLMwLI89U8rB4jFOWF6U/DI5AdfKG6VH7yb3kw4kYZ871JAPO7iYPgWUEAP5mGohmRMSONw4l3T7od2GqkZ5h4lWdGjGCkLURmZI3hZTLALRgRJ01BM+IzxeC1eHBjRmwOrJJjhmF57uc4AnZa2mxU+ghG+N9TSI3yZM7Uus71pgkrkI4Q3ToYKUtorFq3MyPRS1AjIFrf7wRNA0YfS+7TVc+BPyKPU+Hrug/zP+FcQfPLsmoawKR+HYMRi8cIRSGqaVzSNLFgRtq3A+s/EoMRi2bEUcAKmFoAukoOUwugEAoYM4KQNSM8M5JImjbs1FuEmpv1GWVuR6/h1pB+J12txEsJECsGrbBUYgSZ+L00I360J26MRSjVNA7n6LqfbNbU+NBghDIjnd7BSBjeHzJNHV81E8ZnUyh062BE0zTWudfGjKQ6zB+aVbwqw5Sfm7n/QfuZQcjASeSWsizFgJuAFfB2YfXSjBRCwCpRintpRgpSyrbxU+MYLseXDbLMZ8KYkGoiECYqhIrQKhJkzAjAmZr9j5T/UnMzvpIv7DTNF6+TUuGGYWLQY4Xkt+w3JWK9hm27dmFYHJ1RHUzPchawWtPBfsS57VuJISZgFgKwNI3LmMhpkGzHDwhZEMV/RjxzEpZ9f1TIqTfNroTKsgQ601m7ZoSmJsprzdWrG+oGAOfNJX4jE081H6eufMViRjIpoGM7uV/jwIx4ubA6aUYq68ltZ3Nep+gGp0ZZuewjEmy0W3PbmBHZ8a0OnCoYiS1YszGEZHrGmBHLuNKPC0Y2/o8ECdW9zGorIPw0zdIXye2oY1gqRgoJM+K34sSrtNftmrb5DEnOMYw0mlPQ47ofmqKp6UOaCQK+dHT8Z5ivHbxMj8OzR/xv14tJLja6fTBSUZYEkLZ7jexYRW4bhrpfpDzqBwLH/Ep8jIrCNi8l0XJEDeUcwXsaUEtnK9xcWLvazAnSqhmhPSzCNmCSQGp65nFxFYQZ2bDYOIYJXz4jbRaqXgUjsYWsFDMUZsTKVPJ272s/IPd321scf8KqplkyG/jiNWDhP8jfNM3sBI2W9gZPMXiZnlG47sciYJc6sCIPB1YHBtZ1P1a9CBBIMxJm6kQ6LnK75AMfxYzEFKYLq+UL2k6DEUtqIijqBhCBaMsGsuIZckB++wsKOrlV97J5BTBQAassTUMtyit6mAZNFAUIRtwoXr+lvZFefNQUT3Z8N4GfYkZKBrJqmrxE0U5pmgETAGikoobaAVjNFlnlWx7ByPbVwMOnknJ+AJj0A2DkUe6vcSntzRduiwZbMGAcUkjT+HldQPj6nllFHBeM+NCMSI8T4hjF+4kIeielGYk3HPvTbOeYkXxBBxTagbOQcLOCp+jhImBlepHBdoaogMEIheDA6tMOPjLousmMSIS1rudnY0YaxccVYgeB6s5nPJcJWOnfIwwR6Revk1vaKoCCT9PkOuF+/qIZiEy/Dfj6X7zZX0lpr29mxOPDcmMhnNpBCAJWiaNprsGijdV0+4xbJMyID81IFI3yZMwIb3oGzed7KiK6fTDiaAm/3UG0mQsoG7L63fz3FRRe4lXAPU1D7Y5ln0Mh0jS2hVGAapqomZHtXwKdOwAtCZ1zrrRa19uOr+tcNY0KRuIOlncPi+p2YkYAYO/TzPsNQ4HdvyY+H0Z/GqoTmXodsO8ZzoaOPKx28Fzw4jmRSgSbwq79NMpz6U3Db5NrsOjUKM9XmqZHjmmaEDUjwsKHskfIsucFZkQFI/GEY7O8MJmRIQeS29Xv5r6ayRV+ghFastu22T4ZylwgKaqogLUAaRqJgNUvMxIKLblzPbDgfvKPNsFa9gq5Hbwf9LJK23Edj9+xA9CN35vSjMQeQo4/X4dPPhCVddHe40RDF6IB37zTbLlAEaQ/zcJ/AA9+F3jrNlKdAxANGGVdRk3zf96W950LM+JYTeNmB+8kLHWwg89VJ5aT6ZlMM+LH9EymGck3GOECPTZG6mLwWNBeXTmg22tGHJkRmp5oGJb/QXbbhwjAdq4jVTr56lCCwE8wUt0L6DMG2LyEeA6MPdF8Tma8RFGIahrrQMaNZwmPWDrfVYeAf58DrHyD3N/8Oena/LnRc2jUMdA/+4/jS23HpzR9eS1Ag5ggwUhXG/kd9XXoI6IQKgTjKDcdkB/wgaiMGSmvAs5+kVxTVr0IRW1vYHsr+a3IFgnkpIGXriaVdJ+/SOzKJ5xMDM7SHaQyrt9Y/+ctmeT9pkHzaZTnVE0j9RnhKnxyLu21nJPrfmgwSKsRAX+aEcoUhRAguJmeCaW90OC7+V+RoJgRWbO8TNoUblorSHJBRY1ZVfPlW/nvLwj8BCMA0HQoubWeH9/C3Ao+TRMF4/PqDdCzZmkaYLGDLxQz0r5N/FzevQtY/wmw4jXy9+hp4KMkG6VsPT71GOFLxun3076VmCm54anzgdv3N5kZhUghY0ZyBgtEa0jgIUPv3Z0DEYDzGnERse74yizpB0wHaMMXBwMn+a8SBKRpmrAa5bnawTtUuTgJWEMr7fXz2dBgpJYPRgKU9nLMSL6mZzz4cYdqZ4KUYhcL3T4YkTIjrRsB6ITNoKV0+WLkVHL73r3BJu6uViDVnvtx/QhYAWCYEYysfNN8LJvl0jQuwYiejcb47LWbAOtgFMSBNSzB1orXyHvsMxoYeTQxOvr7ccS6u34w0H+8XMDqRMHKfCboKlnPipOIFc1rgU8NFmb+vfm8KwWfECbgfPt7sEBUwor4BSvvdUnTbLD431CfI1r9FYQVAexde7lrz7eA1eFyDRJAuAUJYZb2+kr3sLGVmyMq/QtY+fPNF7KxUIcuT2EpzUg8QR1Yr/j3R3h4/iq0d2U4YVJ/f+IuP9j/XNKi+6v3/LMjnTuBv+wP3D2FmJflAt/MyGHkdv3Hpm5k51pC6SbKgJ4S7Ux5jamyD1s3YrADumXwEQSsPpmRvGnJ5XPI7cipwAk3k8GHpqaOmQVomu08+fOzKftlAsayCjPt5Zaq+fBhsxLi85eAnRuct93VsHkZ8PHjpmanQOCNo3JNAzA4GZ4FgR/jsw1G8ztqpLb+I3JNUWYkaDAic2D1qc/wrKbxoRmxHlPmwAqEx4Z6jh2pDnMM4Bd6LE3jPB7Kugzn/HuSvE1ZNQ2fYlTMSEzRr94UHv78iY9x2t/eRZq1d+8f3oHq+gOTDGfWDx/295rPXybup5s+Az57Nrfj+g1G6gYA/cYB0E0tBGVFGoYBSYm8SNOiq6ixrPpy6k0TlmCLpmN2PwroNQz4/qPA4AOA4/8AjD/JOJg9feTIzDiVdnr1CEp3EgEtQAJbPQMsfiqHN1SCePNW4C/7Av/+IfDOXwt6aH5Az9tIz62Sxi+Y14hL0EqZkfHfBsqqyMS57QsuGBkX7JjW0t4cDOA8NSO5lvby55QnG+q7tJcGgoly0X/Jjx28eTD/AcJnzwF/3hf44EHhYZk4WOhNo5iR0sFlU0fjV9/YEzOOHIm6yjK8/+U2vDzf6CPDl2yFgTHHk1vamMoLS543779/X27H9BuMAMAeJ5BbGvjQFuZOIjmAE7GGHIzs+Ep6eQbqTRPGz7urjZTwAmYef9A+wDkvAwecyzbTYQ+SHCl9pwmpfjdyS82UeKx6F/jnt8m59OgPHHQ+eZw6dXq9h2cvA5a+5L1tXPHJv837q94p6KFDbfnOAlEf16MT/KRp1tO+NpNMZ9fPniNBSaIM6D0y2DGtdvBBKos4waYMfgI8a4Av7drLazAC+oxYhaCeQQLTi/QRtTdBHVj9MiPv3gVsWQY8fSGw4AHpvigEAaskRRZ5F/Mc0e2DkV61FTjt4CZcPm0MbjqZiExXrDAm4TCZEcAo8dWArcu96fVMitDwFF+8bvbL8Qtdzy0YWfYK0amsWUD+dqN0GTMSckVNsxiMWHO5fhCKz8i2L8htVU95KaYBnWdGvFZXVBNi7XlESwStwcj6T4C/Hwt8aeh5jrrGLBenk44bPvg/Esw+e1nhS8vDQDZLKpgoCtznKUxfCPN6zEcz4pGm6WgmYwwA9B9PGncCwOu/J7e9R5m9VPzCxYHVd2lvLsyIQ2mv0zY5+4w4MTBO37OTFo8yI+kOx9S69HzdkM0CaxeZf1N2FID+4SPC+QIiIyy4B+f42RQK3T4Y4XHsngPQt64SvTLGgBE2M1LdQAYHAFjlwY6sWUjKAGt6m51/VwasxEm1kYsC8BeMDJxEBJmpNmDFXHMFOvQQ59dElaaxMCOywchvYJJXmoayQ427u1YfCJoRjd44rK46jMCN+rRQ0GCk2RKMvP57Uyey/znAxO+bv6NNn5keEk6gZcfNXxWvYWM+2LGKiIUpdq4VU1lv3Qb851Igm7G9NAwImhH6WK6ry1DSNB7VNF/NJ7+XhqHkN7XXd8njdMEw/PDgx2QTHP3TPzPiVU3jZr3uKCzlfUa41X+upnSO2hSn75kxI5YCBz5l07HD9Zi+TfS2fE7MFSnWLiS//1QH9NdvMt6A+XrZIigMd9qooYIRDomEhqlj+6Gvtp08EDYzAgDDjIndK1Wz3kgVDdoXGD7ZeE3AYIQOVmVV/hr0aZrJjiy4n1wEADD0QOfXROU1smONPBjR7CsAJ4TilrnVR6qKnIx513KutuPTwK3SGoxI0jRblgOLnyb3L3ibCGgTCTLRVPYklT2blzqfV9tWMYjlU3+lgk1LyG2/PUlFE2AGVZ0twCvXAQv+DqyeH8nhpZqRvNM0YTAjDpqRL+eRW7qIGLQvGQMoDr0k+DElaRrfpb0SXYOw6xyYEX5CFZiGHHViTn5GzsyIQzCSSJLrEgDat7sfi0/7uZ0v/V0PO9TsAr9sDrDhf0JwyE6Bc48VPHKUHXxpYerY/uhHg5GwmRHAnNhpCsQJGwz6vf94s+w2aDDCp2j8egrQYGTpbHLbb5w9ncAjMmZktfCnNZdrvS9DKLQk082459jdSnttoIEb/ewoWJpmvfnYyjcA6MCww8zcP0C+T77LqxOWvUKErpRFKslg5DNy23eMORivW0Ruv5oPZiL2VUTBCO9imW9FQhjMCA1GWjfJ026rjGBk2MHkVtOA435H7h88IzfvJObqGXAiBaB7tMEIVN7qEiTw30+upme+7eBlZb0U1TQY2SY/Ft2n5jOVTD+/IQcAo44h9z9/CVhn6sX4kUZI03BBm6qmKTEcNKI3C0Z2lOUhMnMCTbls+B8xV3MCVcMPGA8MPQiARgRM1IzND6zN2Pxg2KFAVYP59xAXVgSILhhpXiO9ZIIwI6FU0/BpGhcIAlavPho0GLF2Qa4bSG53ct8xFagO3s9+0AFGquar95xPjLImY79Obtd/7FytE1dsMt5D3zHAAMM8cJ3BHPJi1oiZEWHlXUxmxK0/TbrTXOjw6dV9Tgcueg84+le5HVOz+IxwaRrXiTSbgf6fS8lrHD4z19Jea5pGEiSEYkrH4gOL3stRwOri30QXb07BiIQZcR2iqF5qwF5mMLJ8DvCVuaCVLXysDqxCP6EYsiMqGLGgtjyBvhrJzy3r6BH+AXoNByrqiJbDiV7PZlk3WPQfT37cg/Ylfz9xHhGyLnmBWJQvme18LCpwq5FcME5IlgH7nmkce4JQMSJFVAJWi1g3J9OzHFdJAliaRmL6JsB+KTkev8OBGamnwch6c8VLnTMH7WM/5Mijye0HD9p1JhQ71pDbgXuZEzktVS4V8MwIZYOoeRef7vzqvUgEunyjvLx/U2GYnvH9aawi1pVvkLGlth/QZ5T5uKaR9gG5+ia52MG7BvvCdewQjLjsx2bT7hEk5G1KZzknx+/ZKU0DmIs5mXnh2g9IdZsBX6XiLUaxQ/1uZB6o7kX0KB8+JH0VzzQJKUbYH48TVDBiRdsWlCGDrK5h8Y5K7+2DIpEABkwg96kuBCDR77t3kRz4ti+AVCvJ89IV+fQ/EaX2yjeAP+4J/Ot7wMePkXy5y3sBELyMcOp1wC/WARe8KaYGZIiitLezBWjZkLeANW9mpKPZHAi8mBFZkMQWPVZmxEEzQtOC6Q6yqkp1mJOuzB581NHAkIOIuJNWSljRbAQj9YOAEVPI/RVzXd9L7EBLqxtHmMLdLcvJgPzV++Z2LRts6b0wkY8mgSEM0zOA9KcB7CLWxc+Q2z1O8J+a9QOrHbxfzciWZTZBt23XbgyLlbGQBC6CrsQ4RM5pGr+N8tyCESdmZNkc4O4p0N+4WXgvruer6+YY1KMf0aRQN2+YjKyQpuECKVmjPNfjFREqGLHCGLy3oB5LNuVhw+6GgRaquW0rcP+JwAtXkBJOamTVdw/TbGzAeOAHj9knpU2fOldT+LWCt0LT7N1CnUBX9x0hMiOG2ZouGbsSkhJaJ/hqA+4GahBVtxuphHKBLkkfOR7fSTNSXmUOZDvXEy1INk2YrZ6S5oqaBhx5Jbnv5ExK03pCMPJqcUp8MykScG8PEDCkO82Bv34wGZBregPQgY8eJYFYdSNh8QCTUQwRfHlkXr+pVAepVAPyY0YAeUVNNkO8RABg3Nfz278V1hW85qP8FQC2rjBFlg6buPkBOTXKk/WmyUfTY93e06PINU3TQG6tAlbqFWUI1IVScafz7WoxfzM9jIIKmqqBWN3Ezp3vTSOpBHM9XhGhghErjGBkrd4bSze4dF7MB5QuX/Yyye8+fhbQYogW138MzJlF7lsHlGGHAOfNBa5cA1y73VRt06oXK3JlRoLAIz+aE4zUiMxILJAdfL6r2I2GbseHdbYuGWqlx093klw/YC/tBcyKmu1fmiLiQfs4r3KbDidak84dZOUlnJTOMSO7AUMPJpNK8xpztVVIvHkrCbjvClBaSiuLkpVEZ6Fppnvoe0ZvnqEHmZVvfroeB4RQIpnPb4peI1rSrhcKCpnXyKp3yN9VDUDT5Pz2bwWb4Iw/OZbItVR0yzLhNdJdB9CMOPVgoci5N41Dozw5W6PnxowY16LwGXoFdFTfVVFnVkSOOY5o+Sb9AHqFs5SAt4PnAx/X4xURKhixwsixr9N7Y+mGndF8aSOPIhT95qXAPV8jtHmyAvj2PdxGGnDAj+Svr+xhDMrGJOm0GgzDYMkLzA3SpU9GUGxZBkDMMOdUTZOv2JAyI/19WGcbF7qMLhUmLp5Bkg0kQ/Yntwv/Ccw3fg+TfuB83EQC2PPb5D7vUgqQnDVdVdUPImxXwzDyt1s5cFSg6SE/nYkpGLOzmxmQ8R4rAAmyaiSTc0igky1fHpkTzU1TNNUN+adQZC6sNHgdPQ1Ilue3fyss15JvN9oty81fv8dblmpGAvSmycchN1CapnMnkDFYSJkez0kzssMejHgyI6xPGtcZuLIO+OFLwDfvgG4EKLL0tQ4uGOHFsrLjdbb4vyYjggpGrGgmgqt1eiO2t6WwpdXDUCoX1A0AzvgPEZklKwh9fs4cYk70g8dJU7qT7jWthZ1AJ8mNXsFIwDRNEPBlhmFhywrbQ7n4jORqDc1Ag7x+HroZmCklGXMjTFw0RVNRZ+uECoBUPQDAkufIYNY4Ahg73f3ge36L3H7+klihRcWrNb3NdvV9x5Bbr2Dko0eBF38Z7gDFswFGwOkJPs1EYQ0Ohx5ssn8RMCO8biGv8ki6Us43RQPI+9PQnlIcjR8aLPos60rbET6YET9+QG6aEf6ccvYZcfIzkZ0THevKa+XpbCdmpJWwHCz9rMFb48L0Ig6eV26LIIvPCP992Y5371HAr3oHN9YMESoYscIYwHdWki9/7faIdCO7TQJmLgZ+sRY4/WlTRzLqaOCyj4EJJ3vvo5/fYCTCNA1dobVtDm/ikjAjFMIKwOPnm5fPiK4HS9P4ZUac9CIUu+1j6h8AIiaWBS08Bu1DBsDOZtG/hmcVKGiFxSaXYKR9O/DEucC8vxg+JyGBpowA/54gfJqJYux0McAeONFk/yIIRnhmJC/TM+Yxkqd4FbCnabavIvoxLQHs/rX8928F+w2KkzbgMpGmu8h5SUSWPNyuUyfGQqoZ4YLFXAWaNgZW9jV7afGcNCMQd+kruKVpGp4ZEU7Y3Bd7iEufOe3X3rxzG6Bn5anjAkEFI1YYg19XLSmzjCwYAQiVmg+dGotgxLggs2l5KVsuoOW0nGhT1pvGtwNrLszIzvXkAtUSJpvgCvu5SCcuWknjdNFrGvD124CJpxK2bNw3vA+dSALDjyD3V7xqPs4mcs7kqo8PZoRP9/AGbPli+yrzvocRFoMsoKruBVw4jzBC024kfVYYQxexZiQMZiSMtKk1TbPc+N4HHxBNWlaSTvBMMTR/BWZI57ZrNzt4y6TptcAIZKDmAtexw00vAsiZEV5cXlZtO46zZsRgRqghogVmTyyJrkkXe9M4fja6zrF2IQTKOUIFI1bsEAfwNds7ingyHmgYSm6b19mrI7IZcyUWtJomCMoqTSFtGLqR9m0siNIbTW8PaZrGKwltIKdV7BqjZLTPGKC82n1bmNU0Mk2LNBhxYkYAwnR860650ZkTdj+S3C6XBSM8M2LYqbsFI4u4NuVhlcp27jQ1E4DY+MsNfGkyjx79gO/cDxx8Ifk7wjRNIM3IZ88Dr/9BXq3ENCNhpGks1TTUkdatdUM+YJOm8ScvYHX6LAyPEU8Bqw+dB3NGlQRAsvLVfB1YXc/JKxiRaUY4vxW9vIYdw5sZ4cp6pedNGVn5uONkeiZ8Pl2tpqheBSMxQTbD3C8rGsmqfF2UzEi+oHnEbMoMPCjat4MNA1H/wMLUjVC9SN1A6BLNTJBqmryYEersSS21PSArQ5bmr5nhWch06AgjGPnqPSJGA1iJNAtaATNN07xG7g3TuVNM9QTtFO0Eazmv38BVxozIUAjNCFc6KkU2Azx8KvDfX8nbPYS5+qy1vF8a3FGH57AhKe31LH+1BSNyuDEsTtU0XmmaXDUjFK7aE880DceM0P1SrxwA4E30vIInD82ILhkDZZ+n9bcrvC/6u0xWAOU+LR0igApGeLRsJOkGLYG6PoQZWbsjxsFIWYU5CFvbztNcclVD+Mp6K2TK/lxBhY2Nu0NmsS6rp3cC2zYXzQjt7zHUXzBCLyWxea9MwOqDGckFvYaRoEPPmHqMjUa1Ca95qWk0v6/NkpLwbV+Kf4fFjNDBmLICbZv9eZ0EDkYiqKbhvBpcaXW+R5BML8DaM4QRjHDXXCZlto+gvXvChqRRnqf4kgYjEl2DsGsXFsLW8Zdd0nZmBPAoyXWBYzVNLswI1YxkusxqNu66cqpwkcIzGKHjjoQZsfiMODIjfJAcplFeQKhghAelhOsGYmAjmSxinaYBTNfOFktuvxB6EYpQmREjGOm9e7DmcxLknN/vajW7wg49yNdLdMn5SZkb2go8CqEYa6j4Nqmqof4zVs0LS9XIgpGV4t9BDMrcQPUi1NZe1lfFilSHORh7NXejaYuOHWRyDhEyUy0p20a75QJy/VSYzAjfn+ar90mpaWVPUn0VBazVNH5YCAsz4nTp+vEZoZAFg7LvJygcG+XJ3hsNeJ2CkYoeQMIwq6TfOVc9pnPMiGclkaeA1S4O5j9PX59NDPQigApGRGz9gtw2DMOgBqITiHWaBjDNnnZaTKwKGoyE6DXCesHsLgyAuWhGcvaEWD2fMGT1g+TOpxLoHoMCg5MVfBigLM6Xb5OWApkuQrv2HCpu56YbocEIXWHv+Mofg+EFyrD0GW1SwV4sxtYVhNKu7Ok88FNUN4B9+jIDvvZtZtoqIFh5JDzasK/i+uRY06b8eYWhGamoMT/HZa+Q24F7RbeytQglBfdQp9+HzzSNn3Jca5pGWtrrxVy5gdPC8MdzLe11+k1qmslkUAE4d63p3D5dtSnZLJcScgpGnKv4+P0m4FLaq4KRGIKuJPuMxMAG4suwqaUTXen4+fgzODEj9Edc0GAkTGZkJKcUh7SEzTNNkyszQs2jRkzxPbi7ClgLoRkBTGbkq/dNDUHfMfbmaCwYWWLfxzYjIB92GLlNtYbjrsuLqWt8Vr7QAbzPSO/vIZE0B1NZUPzPbwO37QMs+pf/czYgtRu3Th66LjIj7W7BSEiDPmUkl7xAbnebFM5+ZZAJWH0yI2wXDuGIGwthYyzcmBF4MFcucNKm5KQZAYBeTeSWBveSYIRPnUiP077VrEZyOJbbuOPGjEg1I2EEyXlABSM8KG3dexR611agoiwBXQc2NMc4VePEjNALpofHijIM8F4j+UDXTQFr4+7CBGQdjPjHnJDTKknXzf4ee5zo/2VuQrKg1TS5ovfuxE4+0wnMv5s81ncP+3Z9faRp+u1hfq9h6EaYXqK3XXzpBLY4GO3vGMx7w7LfrjZg7UIAOvDU+f4reQxkJbS6tPmhYWolPQeA+wxCGvTpapn64dAAMgo4iCIBF8t0a5rGaddubJPDi4Vgg9+GakpytIP3dU5ezAjABSNfAKl2i2aEP12X49AUZXWjo+7P1NWZr+fHHadGecLxFDMSQ3Crck3TMLAnYUci9RrJF47MiDEwetHbYYBOAi15MiMtG4GunQA0oHE4K1sD5JoRvw6sgZiRdYvI5FteY5bL+oIkTSM7fpTBiKaRbq2AKWKVBSN0ct+yXHRsBcxgpFeTmaIKQzfCl7X6FZuyxcFIf8dwqqixpqMWP+1vfwZ8mWpZ9S/WNE0UXg608SFAggWflV85wdqbxo0lAoyu063kvsGEOaZpXK5TJ2aE31Tov5Jnc0xPp9ds1l8KnAYjW1eS60w4YR/BLeCtFwEnYOU/XSosNv7zfF/sd9ng/H4KABWMUOi68aMBK3/sV1cJANjcEoElfFigZjg2ZoRG784/5NBAJy2/OfkXfgY8dqZ9IqR6kYYhQFmlmKYxEMgOPpfeNB8YHhsjp/ryF6GQnqtssO4yym69rP5zhbW54qij7dvUDybBVjYlClazGVNo2quJNOAD7JVauYDvkyTrOCvD5oDMCLNItwTFmyzpqOX/9bc/A7yltiOtbgtGLAFRqs3sZxIWHT7hO+b9hqH5N99zg4Tlc51IaYqmti/0MjKOemlGpAJWbmVP9mFPw8jYmpy79tJ0sNM5de5gwYQrw8WnaWg6lOpIJN4frtoU12BEwsjCDNicGgCKzEiIzsB5QAUjFM1rSSSvJdkPqU8PchFt2hnnNA0NRiwTBmUpojQ8o+g/DoBG2JmWje7btm8D3r0T+N+TwIaPxec4ZgqA4N0ha5Tn1w7et4C1batp+LX/D/29xjyY7fykzpI0GHHptpkXhh5insx+PwT6S/rqJBKm38j6D83Hm9cS0WuijIh3aQowjA6/QprGR1M7XeeCkVH+jkGvBev50oZ6NO227sNAYmuBGXEKcKnNP4VVM0JXn4lys/tqvujHsV4DJjhvFwZkXXvdmBHOrE6ma+Dhy2fEZTKVNcpzvOZ1nfwWLcyVk+mZ7f3R77G8lhg+OoEPRmgwbJTY6xxb4cre0rHUZUEpbUPBBWR0v/QzpmOmKGDdTm5VMBIT0ImwVxPLz/UtBWakBzdh8BeNj6g6NFTUmhPGuo/ct6WdcGXbUmaqcXcAItsgrabxyYz4xnv3khVs/wmmvbpPmE6I3PFlg3VnxMFIsgz4/iPAoT8Gpv3GeTvaYn7ZHPMx+t30HkUEoT0cJvegyGbMUlc+TeMmYN22kqTstIT/clWnwJwGI8OPMPr+6MCn/yGPpTqAv00Dfrc78OjpIlvX2QI8czF0Y7AWUhM2ZsQSjFjTNLxeJMyKl9OfJr1opt0Q3j5lkFTTuNm4M2ak52DBL0i6a5egxsZYSD5/XXJOjszII/8P+N1w4OYxgnbIyiDw2jRhX20+U229hpPb5jXAkufJ/cEHGMfKsvfkqOMAzFS72xjuJWC17pNqaqRpGhWMxAPrjVU658nQlzEjnbJXxAN0AE53EI8FikJqRgBggNHoj9pSO4GaMwGmlweFhRkRSntlvWm8BKyyVYATWjcDb91G7h92aeAJw/QZ4Y4vq/bpMvLoYa2OZRg9DTh6lnuaiXZ2/fwls8EhFULSrrhO4uig6OCo7epe/txSqa5j2KHuK1AeLK1k0U/RYKTvGGDCSeT+y9eSgGfJc8DqdwhLs/hp8jfFS1cBC/+BrPF6vnTUUTNSZ5iz2RyRIxrwR0wBTntSdNmNAkGZESp67jlEWvYu7NpHOlW2GJH1rXFlS3esAT57ltzPdAGv/97xXDyZES/juto+hD2BbswtGuu+LWNyAEkA1eJDKCtbBPlgRpSANc6gDcZoeSRMZmRTS4yDkfJqszcMXcFmUuYPrBCaEcDsOrzeixnhmvpZt6Wak96UGbEPX0EErNJVgBPeupWsxAdOBPb8tvf2FjCXSUlqSewDEbFmxC+GHkzYmdZNZgC5wfhuaANGJ3F0UNCJubJebGrnlqb53xPkdnyA74IG5s0cM5LqMHUxffcADp4BDN6f5P7/+W3gtd+J+3j3bvP+5y8LTzmulgGzZLvXMOO4reTYFGH2pSkGJKZnvjQjPQcDMpGlZV+Ae6M8qxkZf1zfvWmWGyxgRQ8AGglMDJdip3SQ7bz86is0zaxaA0ifKcNFmBcBO3p/AL6YEam/ERck8pVg/K2UGYmiwWIAqGAEIIPGyrfIfa6CgmpGNsc5GAG4FawxadAVp5YsXLRLmZGv3hc7VFqxgQ9GPiEUPkBW55ZgxM1dkDzujxnxFYwsfYncTv6J3ZfDB2QCVvYcPX42yzEjRQ5GyirM3zrt0ktZq/7jyW1YzIh1AHcSsOo6afT31EWENdOSwNhv+D8OZSX4NM22LwgrU1lPBvVkOWmw13MoEUxT1uT0Z8jxvnzTzPE3kwk1y6UIHMvFKTNSP4jsh3/fgBmQFXn1mTMSzqW9cmaET9NQyK9DzVw1eMLR0tyyL+k1T83hDrnYrDp761ayvUNpr+28gnhyHMOlScd9wxbQWWFnRozrzlUzIhGwysqwLeknlaaJK1a/C6Tbif6CrgrBMSNxTtMAom4E4IRPfXKaWHPC4P3JBdq8Bnjpavk2ui5qRtLtpkixeQ1JNSXKmGOo1GKdF7D67E3jWU3TttVUvOfq1aDZ7tgp/VQb2MgWZZrGL/Y+jdx+8E+SSqElsDRNQ39XrZvMoDEX8JU0gNg+gP9uFvwd+Oc3gUX/R/7e/xzTk8QPKDPSvtUMiJkOaYRJW/UcDJz5H/O7Hnk0MOIIMzj7/CXhvHRuteysGTGCkaqe8jSUX3o/rrCYnkHzmPhp9/OeQ0xmxIHJdGtoaTUjkz0nExjbApVsBlg+l9wfORU4bCa5//FjZgUZf04SBgZAsKCy6VDgwneBqdeT37ILuwRIximapnHxinJjRrJ61saMULDPJ91Jxl0gGiPGAOjewcjaRWRF/NIvyd8Wx01TwNqZc916QWDNlfsx5QkblT2Ab91F7s+/C1j8jH2bnesIPZ4oM1fflA1hAuLhRIQJuVLcKwDh4ZrT5rHa8OToPSrY5MdBqmq3MjeUFYFW1O6YDCOnAg3DSCDy8jWk1Ley3izVru0HQAP0TH7dcPlKGsD8vabaRJ3T58bKtVcTcPZLwPGWFIoXqnsBSUNfQq8Fvr0Aj15NwFnPAT9dDnzPqKDa/Shyu/y/QlVYlpWmukx2VMBaWWcGXbxuJCYulzlD0ijP8bPIpFn3c/Qc5KkZYcSIj0Z5sslbaJTnxLJs/5KMPWVVwG57A4P3BYYfTto+vP1nW9Djq6mcH/Tbg2jQyquJKJw7NVfNSDbry55BmsqWaEZsVUL0UFRQD0TjfRQA3TsYef6nwEPfIQKjqp5mtGygd48KAEAqo2NHe7jNt0KFNU1TjGAEAEYfAxxyCbn/9Ay7iI+uQOoHAY2G2pzSuZJJQ3ah8fDLjHhaQ7MOvQe6b+cGUfQvHJ8NlnxZbxG7YzIkksBBF5D7C+4nt0MPNs8tWWayGFZRaBBY9RIVNeZgTrvy6joRkgLAt+/N7bvQNHtFjVUUbUVtH1Mgu/vXyO2XbwNrFnD7NcR/WsJZ2MgHI/R9tsuCkRJnRuifmotYdOc6khpLlAO1/TyzL25CcyvrIpu8BdMzJx0L7TvWq4kFBWy8n3839C9eF/bvbJ2eh4uukb4z9WUuzEj7NphW8C7MiEcVH++Rw9+yMZH+bstrzc+lSOjewUjDUKDPGOLNcNqTYt0+gMqyJHpWkzLfWKdqrELDYgUjAHDUNYTd6NxB0l88aODRMNRcfVPVPaXTuUnDi23w0oz4Zka+eo/cDvHXoVcGt3Nlg2xcxKs89j8XGLQfuV/RAzjut+LzYZT3WtM0AAlIATMY2bKMbFdWZTbpywVWoza+vYAX+o4h55XuAN7+M3s4y60uHUWsfJqGOllS/wYgfCv4QkPWtdeJGWF6kUFAIiF3CeX35RKYW03PpMwIz9ZYrzkKysDyZeIjphCWBIBOK6YkzEholScWZsQK4ZypeLW6F9F3OUHmv8QFZE7MCHtPzBG6+GNS9w5GTv4bMGM+cPYLwKB9pZuUhG7E6sJKV7GF8BixIlkODCH19Fj/ifgcZUZ6DjZbwtOBi8/tU7iIs8jT+TEnDHT1LDMI8wm22nEYFAAUpqw3KJJl5DoYcwJw0r12Tw8r65YLrGkagAtGDG0BZacG7es++Hqh3pKyZMyIj2BE04AxxxvnY3bgZc3hrM3G+Emqg2NGqhqMx7abz+8yzIg9TWML9pnh2WDjNe5pGj8l+LJAxrq9cE7WKZ+1ORjOvUADjrpWehxnZiSPdJtmT9M4jlE+DM/ITuyLID7tZXOwtbLFbIFU3BQN0N2DER/oY6RqNreWgvGZMQCzSX9Icc6H6kGsDqt8uZ8tGJHQ6TJDnyCmZ06rJB6pDnPVT10Tc4AbM2KuQiI2PMsVvZqAUx8Cxhxnf87JSCwIKDPCT8RGmSNjRhg7lUeqDDArarYsJ583vSb8Gqfte4btoSyXBhBWzDJmpLJOzozsaqW9XGBmS4PSQJD+dvxqRiScgVXLIZ28+WDRKUBizMhw8fHdjwR+8LgQIFiPI4wf+VRFMWaEE0Q7aVN8mlbKAj2pgBViMGJqRozfbQzGpJyCkdtvvx1NTU2oqqrCgQceiPnz57tuv337dlx00UUYOHAgKisrMXr0aDz//PM5nXChUVtBxJTtXWmPLYsIKzPC+osMK875DDCCESszwhkhCcFIJkUEZoCoGXHJh1rvS+EyyJnnZARD5bV5rVplR7Ct0qK2go8CDU3klus6GhiygdXKjNCqqjzYKQDAsEPI7ecvmc0Ca/v6T48MmEAqwwAzsDGQQMKZvueDkV2SGbGnGBzFoi1iMOKp/XJqbrdzPbDoIfE0JJO3rITVUTMiC0qT5ba34MmM5KQZ0WANyRyrdlhZr3uq3a20l98nC+asdgdRNu4MiMDByCOPPIKZM2fi2muvxcKFCzFx4kRMmzYNGzfKe5J0dXXh6KOPxsqVK/H4449jyZIluOeeezBo0KC8T74QqKogF2FHymd/k2KABiNdO0kqgAYjUbsyOqG/0Sdj6wquggRm99eeg03WZuc6sorNpoGyamECkJatcRefVxrG0S2TBw2CGobmKSq1n4ttYIyjZsQLfI+NXCGjnBkzYgQjlBnz24fGCbsfSSpqtn8JvGpYpFNPCb849iZg1DTga6TKjmdGHCcPNqjX25kRvmNvyWpG7IyDY0kuXRRRxlaWShB27RBArJ4PPdVmvNY5fcJX3Eiv+WyW+M0AdmaEOz/+JKVBZzZjVn/lGlRyIlENmvChCOfso2MvIPc3kjHC9Hdr0/mUcjByyy234Nxzz8VZZ52FcePG4c4770RNTQ3uu+8+6fb33Xcftm7diqeeegqHHnoompqacMQRR2DixDxEagVEVRn58bSn8vBZiBqVdYb1MIhXBKWEixWM9OhrCB910+RM101mpGEoMb5KVpJtVr5BHm8cIfiihCVgdUVIgZupGeGOb73w46gZ8UIYwYiUGeHSNO3bzW38CE3dUFFLSjYBM/Uz/uRg+xi8L/CDR1m3YKEU04lW56tpaPdcyox07iTBNlDCzIilmsZJOwOYq3ojGPHUjDgZybVtsR3PlRnhDiCyDOttHkbW92Y7juz9dewA+wQo+xUU/LHcKpJ8FiG4jTs6JA6sjgukEgtGurq6sGDBAkydOtXcQSKBqVOnYt68edLXPPPMMzj44INx0UUXoX///hg/fjxuuOEGZDLOk3tnZyeam5uFf8VCdQX5iNq7YhyMACb9SBufVTcW9wdGjbOow2XHdvOHX09U9uhpsGPUdru3SKF6UZB+Bayu1TQsQMpTXyNhcWzMDdOMlGAw0rzG3VnXCV1t5vfOD6x8NQ0VL9cNDIc1MnqAsH3S1E1QWAWHVgEruBUzG9TrzYmKMiN0cVBW7d4vKM6QaEYcmREajNTRYIS9yvUQtv20bTZfKxGIU/CiWnbN8Zc8TcXW78Y8jARoCVgNFqVVUzS4LK/NXWStJf0Ft36ZEbfSXq6ahj1nZbhKlRnZvHkzMpkM+vfvLzzev39/rF8vV9uvWLECjz/+ODKZDJ5//nlcffXVuPnmm/HrX//a8Tg33ngjevbsyf4NGVIkISaA6nIjTZOOeTBCy5I/N2zNi8WKUNAVLvUPoQNCTR/iMwGY5/j5i+SW6wsEuIuzrPfd4OozEhYzws7JhGNpb0XxL3zf4Bt+0TRbENASxbIqccCjzEhns8lgOHmBBMWkHwDfupuULX/rrtz9Eyzpg4TmoBmh3ysAVHFpGkrpl7peBHCtprFrRizMiEeaxpkZ2eoeJFhMz4TSXv6a9zIP0xK29Iw0SGDl23k4lSaSjM2g50whBA6sL40419rgszdNgn0HFmak1AWsQZDNZtGvXz/cfffd2HfffXHKKafgl7/8Je68807H11x55ZXYsWMH+7d6dQ6DYEhgwUjcmZG+RjBCvT2KHYxQISrVAlAbeF5ANtpSvbHHiZadaJZbSzWNzzSNKzOynUsd5QE3LwW76VkJMSOall+qpoWbCHgmq7KHGXwsfIDc+im/9YNkGTDxFOCEPxCb91xhBDF0WnP0GaFlvckKYqBmFbC2Up+V3Nx9YwGJ6Zm0Wi3daQZfTDMi3Nh37SQ6bd1sY0T468u6yHCspvFKeUjSNNLz4su3cwXPjLhV0/jq2CvX1QnBHctgiUFWyWtG+vTpg2QyiQ0bRAOkDRs2YMCAAdLXDBw4EKNHj0Yyaa5Oxo4di/Xr16OrS14uW1lZifr6euFfsVBZXgKaEQDoN1b8u1iVNBSUGaGmU2sXkVvDZAgAMOlU8TXWVImHZsSvgNW1moaVQYfDjMiOb9b0G5qRUhKwAlww8kXw17IVnmRQHXEkuaWdnMNiRsICS9PYqzUAyYBOV5c8M5LNmmXRdfIxsiTgYnomrQJJVjAmyMsO3rEcl2tB4GlGRs9JFtiwib2PwwmIOg7H8wpj4k6461MAiFbwnl5RziL/LLK2ahpHZqTUgpGKigrsu+++mDNnDnssm81izpw5OPjgg6WvOfTQQ7Fs2TJks2bUt3TpUgwcOBAVFXmYGxUI1SwYiXE1DWAPRvIVAuYLusrduoJcXLRN/W6TzG2qegIHXUTuH2tx/oRcnBVEM+LZKC+TNssQe+ZX3eWmarfX9JcQMwKYwQj1aggCN/MmrkM2ALPzc1xgYQNsaRqrmR0NMikzomdJhRsrdfWg3OMMiXuotCt2C5deYMGKPwbTVTMi2d5qBw84BCteE7umyRcTUZTBavaUoa0CqGM76RMF+GBGXKr4uDSNLc1F33CpClgBYObMmbjnnnvwwAMP4NNPP8UFF1yA1tZWnHXWWQCA008/HVdeeSXb/oILLsDWrVvx4x//GEuXLsVzzz2HG264ARdddFF47yJCVLPS3pgzI9QPgmL8SUU5DYaGoeTCS7cT8eO6D8njAyeJ2x09izRFO+BHtl14rqj8pmmcmJHWTWTC0JKhWec7qdoBcNU0xb/wA4GyWUtnA24pLxnYRCD5fJsmi/dpFUxc4NXYTNZzCADKq4hGBiAiVmYCNjDa840Ssrb0smCfuT9zgVdemhFjF5JUraxRnrT02keaRv44uTEZsBDSNNbSXojBAwCTEaqsN/smOcB3ozwLM+LI6hUREmmxO0455RRs2rQJ11xzDdavX49JkyZh9uzZTNS6atUqJLjyzCFDhuDFF1/EZZddhr322guDBg3Cj3/8Y/zsZz8L711EiKpy8l5iH4wkEqTHyJr3gSOvyk9kFQaS5SRVtHUFEdV2tZBqAqNc0tyuzLEpmlQpHsSB1al3BgXtLNqjf/5NooL0pik1ZmTMceS727qCMFx8qo0imxXKshncmJGqeuCgC4kV/En3ipqSOICtWMmfjo3yZCXbVQ2EEenYbnckLUWwCY7+6ZGm4YIRmbhb2LWTtqt1M/SGanY8igQSQgqCn3CtGoyElshbM8LAe8nkCr5yh0896bw2xRA++ygflon8eRM51ijP4jMSxzRN4GAEAGbMmIEZM2ZIn5s7d67tsYMPPhjvvPNOLocqOliaJu4CVgD41p3AmoXAhO8U+0wIGncnExgVKA6YIC+tc4BXaa9jjb4Bz2qbECcJaTWNIzNSYsFIZQ9gzLHA/54kjpjWYOSjx4D/XALsfRow9TqzWgrgNCMOFPmxN0ZyyqHAkqaBZrEJt2qB+O+1uoEEI+3bOc1I6TMj7E++csXDxlw3JlvHXcuCmq42IN0OHZJSaA2AzvmM8NU0sjRa62ZyG1AzYkufhJSmsX4UtmCMloRX9/SxPwl7zLLDfpiREk7TdDdUlUppL0DcKyeeIl+hFgPDDB0RTdGM+3qgl0spSP6y84g1PB1YQ5wkPFXtQOkGIwAplwWA+XcDfzkAePOP5nMfPwqk2oD5dwGzfy6+jjEjReggnS9omkYzV5eupb081c1X1DBH0lJmRuymZ9L0Ck0xcBO/jOEUdi0Lato2245HYV2ECMyIjLlq9fgN8jo0t2qaiASsNqE9rcLyw4y4lPZm9axjozyGMFJPISEms1Z8UVVKzEjcsP+5ZmOwynpgnzMC7sAjTZOvZiRUZsR5UGDHN6ytUc4xB6WCUUcD+51N7m9eArxynVnqu+4jc7sPHzZLWQGxBUCpgU22xp+OLpYOzAhAGqu17AppGufSXuH6Yk0ROdt7iRBd2LUsPcdV0li3cUq/2jQ90IlInTa3c03T2CtbIimDtZT2So9DS6OrvJkRaZpGwt5ZA5+sniU/7FIWsHY3MJ+RuFfTxBFV9cCRvyD3D7k4uI7FJeoHvEt7PatpKDNSHwIzIhlqbcfvMoKRihIMRgDguN8BX7va/Pt/TwLN68hkqyWAPmOATCfwwT/I811tQLNhdlfs6q5cYFQ+ZNlkKk4eroxXjcEMbPzUsILXfJRpxhjsWrOnRKTMCOep4iVElzKYrZZgxI2x4B63ddtt32qcs+bs86IlzMo92WLHWg2Xp4BVt/6erO+HMiM0oHUD/Wy5j0Jgmqw+I/yx0h1mm4IYCFhVMOIBWk0Te5+RuOKAc4FLPwEO/2ngl7qlPsjjPpkRx2AkvCoHXXIqQsmirnPMSAmmaQAiSj78cuDEW8nfn/wbWPsBud93D+DQS8j9BfeT90t9Sap6lmaDOAkbAJhpAldhMi1tp32XavuQz69U4dK1VyjJlQUjPrVdMobFLci3akas0HXd1LDU9HYWqXOaER629AlLaeQjYLWfgy2oo5qRAGka/psRetPA4sDKH6uTcw5WwUj8YTIjKhjJGQ1DcqqU0C20uO2+3940BUjTuLI4OoBUO9iAUarMCMW4b5CmY+s/Bv73BHlst72BPb9FBrVtK4kTMO0507h7/Cpl/MBS2su0CpxAEIC8ZLvvGHJLDd1KOUUDSMW8NuYAANqMFENNL/YQYwIcLkNp2oVqRiwsgnBfpzds+W9nS301nJP7jDiWweYTjCTsaRqbn0kAZkQW6Mk0I9bndOjEAwcgi6MY6AyLfwYxR6VR2tueyrjbiiuEDrcKFfK4vwnOUcDabJT2hlHl4MLiZPWsyYoApakZ4VHTCAw1xMkfP0ZuB04izMC4b5C/Fz1k9iUKy+a90JA0ygPE0kkA8jRNnzHivurzM9UrOlwErGIQIbO+98dgCmDMiLGNpMrFVtrLpY7YeUnPx3oC7oudcE3PJMyuxp0vkBMz4sQe832V+Ftd12PnCK2CEQ9QZkTXgc600o0UErolTw3kqBmRrXvSnWY31TDSNLokL86voOmFX1aVv6dJHDB6mnlfSxAvEgCYaFj8L34K2Gh0bC5FvQjAJiknwaGrgLVXE7FEp7A0gSw5WJgtqR28UY4LICfNiNhPRqymsR4bkJf22kzP/AQQhbSDl6SE7JqRHeTWT2NFGSPLnbe1moYii2zsqvtUMOIBWk0DqFRNoeHmLmi9L4OrDwntSVNeE0o3VekKhadfS7mSRoZRXDAy9BCzr9CwQ4jBWccO4KOHyWNx6znjF6xRnpgutKX/ZKW9yTIxyB11TLTnGjX8NMqjLESyQvgsZBUfwq5dtCey0l5bmow7J36zrJ7156PhoEOLxA5elqaxBmNBmBHJZyukaTjWiD+mzlfSxETDpoIRD5QnEyhLkC9QVdQUGnbNCB9geApY3RxYaTfh3uHoGWR5cfHCp5U08bjw80afUUC9Ua570AXm44kksMfx4ra9R6AkYWHerEycKWB1WGG2cA1F+1rSNqUGFoyY16RtMUCZxupG8ZoSsxH2XbtV5Vi2AeyTt5CmsR6FBRAuqQgPZiSrZ4FMymR98i7tFcc1m9CeMSMNnruT9e8SBKy0N40sxaiYkdJDdal07t3VwCzW7Upx633py93SNCwYCWfVLlX98/RryrjwdxVmRNOA058GvvcvYOyJ4nNjp5v3B04EBkws7LmFBYfSXnuzMYdB/dBLye2e3y5NAS8PSUrUxhw46DP8mp65BiMSAauMGbGV9vrx0XCopjHPn0v3eO3LC7LeNFyXXQCBTM9knyr/eToyI4jfAiknO/juhqqKJHZ2ppXxWYHh5i5ovS+D1NmRYvPn5Lb3qLzOkUJKl/Irq1L3GJGhz0jyz4qmw4F+4wA9C3z/sUAtAGIFa6M8q6W2zQ7esvqe/BNgwHhg5NFRn2n0kJU5W4WX1FzMUsbtWzPChwQWzYgrM8IFMTbTMz8Oow69aYTj0P2UVedXoi0zPeODsWzGPJYf0zO6YOM+OuHz1MXHxGqaePXKKtFRorBgzfJKwRJ+F4LbBA/4ELBaSgAF0LLTsPQMLtb1us4zI/G48CNFWQVwwdskGCllsa6kggSQpBWcBvWyCpElKmUwa3zuIWsQwYIRKzPiDyyoyWaYCyl7raSSkQaDsk7C5CUco+HWKVtLuLae8C2E9QPO9Iw9xI9jNEUD+EzT0J1JPh89a3NgFRdIDkF0kaDSND7AvEYUM1JQePWm8WJGWOkh3DQj4YorBQErP1injHzzrsSMuEHTSjsQAWAt7bWuLl0b5e1qcGmUx4IylqaxGNwF9QNq3wb6qbuakVmYEanLaB4CVtEgzIf2xA8kZcQCg0ut4MtrfTEwbnbwOuzVNIKon/1u4zEmqWDEB5RmpDiQpmmCaEZkuWgA6Gg2+4WE5IHhllISBKy7imakO4Dl8uXVNNBBhI2ZTvJ3NwhGZD4j9mDEyoz4q6ax7YdjLATdmEUzYutMGzSIEIIR+3mJZbD5BiNc116qReJ1HEGs4MmL+V0Z9833zwSsMmYkFS/NiApGfKBKBSPFgW65RUDNiJOAdfNSclvb1/9F7wGZQZuZJdoFBazdAZoGWd8SYSVLJykgNnR3JHCwxge8hZeyig8eNmbE0Iuw/j4ANIkuxMldVLDr9+UzonHXr7lPIegMi/3iS3tlab8O/3oRempkX/ZUlSx9JS6QJCXpRYQKRnygSjXLKwo8e9P4raaxMiOr5pHbQfvlfY4UsmoaYVDcFQWs3QEScaNYkWBMUolyohHZVWE1gJMxI3TitzXEtLMbkqftfiW1faVBvrX6xJqmERYB1PLczcKd/44lCx+BRch3MaHZgxGhKilggMDGSMl589U09BjCZxez9KIKRnxApWmKhJCqaWzMyJdvk9thh+R9ihRu9f4Adj3Ts+4CbvKwaUb0+A3okYLXjWiS68tBn2FOmPLr1V4ibDAjXJdjmX+P9bKW6iKYgNWfz4hsf0LQme9igi/ttaSVRJM2v2yFpDcNF3CwAI+NT9xn1xUvtlYFIz5AO/cqAWth4VVN47dRnlDam81ywUh4Ft1uLI44mHWDSWtXQiLJ5M9Wx0wAsaO6I4WFJbIzI/IyWhlrKOzWymBSZqRHP3n6xBK8SJ1YAWSzGd8CVmm6Q8qM5Hn9agk4mp7lUG4rWwSxYEyHjRkRx6R4/XZVMOIDVVyzPIXCwUvA6mr3zu+HH6w2fUpy2+W1wMC9QjhLehC64pCX2ClmpEQhiChdNCPdIcjk3EN52LraVjgFI/I0jY1hYSXCfaSlvVZnZWswwibcdCeQTZEH/ZqecccRg86Q0qycZoQdXmbR7laKzEH22fKfj2NvGiF1HI/frgpGfKCyjDAjncpnpKCQXmiS0jsn2JwyAWDNQnI7aJ/8zIus8KymiVcZnYI/6JqdVhc1Cd0pGBFLYG3CUyexqIfpma1tA/XaqGl09ShhzIhVM2Igy7umeqRpLKdqP69USN+zxBtJXoocUDPC749LL1k/mziztSoY8YFKanqmBKwFRd4CVr40j4L6i/TdI5RzpJDSpYLPSEg0r0JBoUuYOLENe7xcLCOFpbLIVtXiEIx4VdPYtF+0URwXjGgSxsLWm8bCYCHFpSESLlMdP6bIhKD8xJ13msa5UZ5gX+87deIiYIVu/2wEFkaZnpUcqhQzUhzkaXomraahwUifcGzgKdy6Z4qN8hQzUkrIygSHskkqJgN6pLBoRgSBZ7rT9FuxpUTcmRGbtksoEbZX4tjSOrr4ONtfp8+JXdPkfiZRtHPgHFit45cQ3AZmRuSlzzafEak+JR5jkgpGfECV9hYHbIKXKemRYzUN3603REgb5fGDdXeyg9+FIEvTiCvZeFHdkcIhGBGqQADnahovzQhdNFBmpKqnO+PowYzofprk2d6X/bwAhOcT5MKMCGkav6W9ksdkvX5YJViMTc9UbxofqCwjX2RnWgUjBYVHaa9nbxpLnwpNzwJbV5AHQmqQx/bvcq7KZ6R0oVt0EsJzMcy7RwpBUGHVOhiVNOW1tjYAskWFuFvLooFqRqobYKYhHIThbvuj302AYISHmI4LaeJO2H9PeRmRsXJzO7J61pkZyWaAdEewY0UMxYz4gMmMqDRNIeFmeEQe9xCwcj9vHTqwYzWQ6QKSlUDPwSGeKXd+/PGlmhEVjJQSdG5ipd+nXDMSjwE9UjiU9kKHq9OpmwiV7gvgmBEuTSNjVawrf8aM0AmXBSM+Ux68A6tTQ74ITc+EYCyogFUSrPG/TxbgaZbnaCACxCaQVsGID1BmRAUjhYVbPhTwIWDlLav1LLDZSNE0jgi9iZuse6YoFosXJargD1kJMyLXjHSD79VyzQgCcbdgJEijvEzKDPCqe7lW1Fkb5bH9UR8Sxoy4uK+yvduPIwad4dvBU+TTSVfmIydU01CfEYthn542GncmyoBkPJyDVTDiA5QZUWmawsJNh2G9770vPTK9CMCVF0qWgSIzUh36sRWigy75vUUySZUCeGZE08Rg2wcz4qgZ4Sdj2psFACrrzclW4jPi1SgvG+S7odoUWVVKmN+zpFGeaAfvwzFW3KHxf4kpnG4v7WWfXdoQG5fXSgsFigEVjPgA04woZqSgkPVd4FMvXqZnvKZE13WgZQP5I4oUjSR3a05aWdN8qUwFI6UEPk1j87HQs9zk0c2CEWgiQ+TWkM7LZ4TfD03RVNQByTJXEbtVM2LT9NBUhK/Uikc6KLQ0jYRpE4K6oNU0dF/8MYznOJ8RWyuDFNWLxOd3q4IRH1DMSLHgnPqw3pe/mhOwQgfaDWfH6sbQzpDtXzIosEE2kzYfVMxISUEQsMqqH7pdaa+ZqhIYIgcreOOF3P8lz/JC87Zt5A7rpu1d2uto7EVTET4CCJk+jSJUt9JEEv7s4INqRszHeOG84LEE7rNm4tX4aNhUMOIDVeVKM1IMeNnBe8HGjNCeFzURBCOuOWcuGCmrCv3YCtEhy5X2ss6nUdD3pQAH0zPSAZau6O36DBnDyUMQmncYC4aqBuO1xvH47S3Oyo6lvSwV4b0AYOk4p3RQaKW9CTMlZE0rZVJmkOBVAWQ9b8m4A0gCNdpJPNNFNoiRoF4FIz5A7eCVz0iBIUl9BCnt5ZHVs1zPi95hnJ0AWeDEjk2ZkWSluxOkQuzAMyPWSaTbCVg1UfXhWzMiFnRIdssJzWmaxsqM6HZmxLrqt51XijIjPoIRN+1FugvIGtdwiL1prAEC6PkCOWhG+EfsaSw2VtKYK+M/UCsU1MjoA5QZUQ6shYWXEZFfB1YGFoyEz4ywCjpJbpsxIzG68BX8QeeCR8aMCNUP3au0l93lNSNewYhk9S7slk/TcIZnTq+1Oitbm8GxyZgxIz7SNLI0Kz1OhiuDjcAOnv2eqC4lUQ6U+atwMVknOaPDfEY0MfDRM4aGLUZjkgpGfEAxI8WBSZ2ajwXpTcNvS5gRmqaJjhkRjk8v/KwRxMbowlfwB6lmRKh+6E7MiFjaKzqHulXT2K9jYbe8tkuwgudewq3ybZoRy47Zdc9W/35Soy5pGir2DBAkOEJW2svSSjRF4z+wlX2kPDPi6MFCP5sYCepVMOIDPDNirWlXiA6yksBAzAg/yOlZU8AaRTDCjikZzCjFq/QiJQeZA6u82Vh3CEYspb18OsBFwGrqTOS7FTQOlBkx0jSePZ8A+4TLmBH/1TRuLGyWpk/CEHtqLj4jzJ7dn17EeDG5cRD525gRJu6lzEh8xiQVjPhApVFNk9WBVEYFI4WCl4A1kB18Z7OZ942gmsbNut5kRuIjFlPwB9dGedmMWfLpU3BY0nBrlOdW2ktf47CQ4xcNWWoFbzAjkKQh2ITauhG44xBg+2phP3YvDR+rf5mNAGNYaFATQsDpYqLHNCM5MCOCwJfzGbEeiyKbjR8zonrT+AD1GQGAjnQGFWUqhisImPAtBGaEpmjKayNZDUjpUqYtoJqR+KxCFHyCpWa43x39XtO84LAbMiN+HYY9fEZ46CwYMTQjdBd8IGPsKLvgAWDj/6BrG4Gaakk1TS7MiEQomwqxDDYhfoYAF1wxBiZIMGIPotjvE1mbzwg7ltKMlCb4YKRT6UYKhjA1I3q74V8QQYoG8KCTKTMSo1WIgj/Q0l6hiotVPxiTlJboHik4LSE60vLaDZfKFTcPD8BynVqCGteVvyEetlan5MKMSG3nbfsJJ03D7lrZinRwIzKpwJdLY9GKI5uniQpGShOapqn+NEWBe5omiOlZllXS9Art7HjoGrWDl9T7KwFryYJW08h+d9k0nTh7OAsidiVYUgz09y20o5dM2J4CVj6dmrJocFw0ESzIt8Bc/RteGj4WASYDw50X055QxiIE9ktiemYzaQt0HGdmRLCDt7JG7LOJTxCtghGfUC6shYesUR6PIKW9eoQeI/RszP+LyOo0GInPha/gD1TAKmW8UiFOUqUAh4WAJzPicR0LpmcpOTMCif5BN64rW6msTcDq3/RMZgcPyoyE8T1rScE4jr/VcziOWZIst7F37E2jmJHShXJhLTxkjfJ4SteP6RkbuCKspAHkiz42KKg0TcmCBiNSzUgM+3tECWv5uuCE6ocZcQL3tLW5nXlMrrSXfv5ZMRixHTeIgJW9SKIZCdTjxgOS0l7TXC14OkiWXqIQSnutniZZFYyULKjXiGJGCgepoU8AASvArQQiD0bcShBVmqZUkXX5XhEmfV8CsDYNFJxQfbid+mFGzP2QCdktfWJjRqxpj0wA0zP2PduFsrkwFo6QlPYyQW5YaRpOy8NKe+lnQz9ryoyoNE3pgXmNKGak4MhVMwJwqw6q0q+ORjMiK0E0c7cqGClV0AlYVlLOqjW6g/sq7J4rQjWN28Tv0ZtG8MVIcToc40jktRJrc4tmxKaLoNO+r9Je2M7R7OMSIjMiEQALtvNAaGkaAIoZ2RXBXFiVJXzBIPUZCciMsFVHh2HKZJQMhg230l49awykMVqFKPiDTDNCke1mmhGrG61t0gdyqqYRSvAdNCOyMSDrwIyY/ifO5+R8jhLzMMaMhJumcdSM5JmmkfamsTZ5VJqR0oXJjKg0TaGgS+4FKe0FuIGui5oy2buKhgFXnwLFjJQsaEDMa0ZMZiRE+r4EoFs0WuIK3IAk4JamQDgIzIilIZ1r7xVjstUtw4DpswEgUQYky+VvSHKOUjt4xvqEk6Zhd22i0hxKe+m+HKpprA6sNmYkRjo2FYz4BK2mUcxIAUFXpZJ8KGDJNTuATRxUGBeRU6ZMM8KOTVcoKhgpOch8RsyVbPdiRuDAjADGxF9eI6QhKFiw4NJKw9pV1jrxS4N8hzSN2TtI880yuC4mckifOELGjFiPEyQd5OJSnYWkNw3dkjEj8WFrlQOrT1CfEcWMFA6u1Cl5whPsQqd21VXRMCOynLNNwBqjVYiCP8i6uZo5/u6lGbF17RXKe+EYbJuTr8uumRhWA5KVQLLMeK0zYwGvNI0G/9ec7Hu2aYMi6k3DUifB00GyMZIt0nSX3jSUgYpRiwrFjPgE7U+jSnsLB7eOlIA/ZoQNTLTVe2RpGufcLdOMxGgVouAPpmbEHgTn4phZyrCW9tqDEfnEptvu2CHoPLjP00zBOAvDraXDppYFvtlIM+iRdAemBmFhpGlkpb1Wk7Ygx9Gcg7Ussuxjs/emiV81jWJGfII5sKrS3oLBLV9sve8ENqDQNE3EAlYnuhRArFYhCv5Aq2kS3BdrZ0a6STACCzMCazDiMPF7mJ7R/bH9CJ+nZAxgaRpxLJYKWIOmaWSakTAFrJylvt2iPRxmhLeDp2kae28ayozEh61VwYhPMAdWlaYpIJx1GORxH8GIZglGItOMSI7NltCqmqZUIfUZsU1S3SNNo2sJc6VtWQhkNc0lTUMDCud9m66hEJkR41ZW2ktTDU4aDB3wfc2xcxQIMCPoCZMZkQjwzd9TcM2IW6M8mc+IydbGjxlRaRqfqFKlvQWHUENvsTUG/DEjppjNuFojStOYmhGJLbOu0jSlClmaJh/77lKGzWfExoy4T6J+mJGsJu5HylhYtFiOpmc+zonbqe04NvO0kEp7zUNaBKyZ4L8nWcWhjBlh789SiRQntlYFIz5RqUp7Cw4hF2wtUfOjXiUbAjAGuWRFZAGB1IFVpWlKHm5eN9luHIwAMs2IBzPism8vzYjs86fTr24+ITzvxtbYz1FyTix9QitPwhWwWoMnZHJgRiSpbFlvmoQlqGazWIwWSCoY8QnFjBQegg7Damvsoy8Nv50ORJai4SFb/bFVSIwoUQV/kPWmMVfM3a2aRmSH/DIjfkp7zQBDs6Rp6GQr6U1DtZuWfYiakWDBiFwzQkt7Q/ieXUzPWKlyLj4jkueE3jSyzwaIVYWfCkZ8gjXK61LBSMHAp2Eccp+eu+BXUVGlaCDP3SqfkdJHVhL0st9UN2NGrKW9/IKA+Ix4lPa67dqBGbHvxRK48Puw6iKAACyDMwMWaprGrbSXPpCTz4g/ZoQ9p4GUUCfiEwLE50xijpoKwoy0qWCkYBAmeGNCZ3SjD70IYBm4ovIYgUMJIpe7BaCCkRKENE3TbTUj8smfPAfPNI1bba+p7YJUMwJJGkI4Nn9eAjPiU8DKTlHCwISZZk0k7MEIz/RoSaCsMvh+pZoa3Tx363NArFI0gApGfKO6ghQetSmfkYJByBfTi82SF/aCMDBFyowYx5Mdm6VpVDBSaqBpmiQvYLVWWXSTNI3QtVeTmZ45TNa8EN0JvLZL+DztK3/B7p3fUlZNk0dpr83HKOSuvVbHWHYMnwstwF2rpne1sXHTuogjlUbxGo9UMOITtQYz0t6VLvKZdCdwFxplRiDSjd574AauAqRpZCsUmtuO20pEwRtZCTNir7LoLsyIWzWNs1iUrSN8l/ZyzAgNZDhPEScBq1UX4ZY6sp0j24dgoWzsRwMS5b563HhCZk3AHycg++KqdVm7gOlQbJU7Lt9XsZBTMHL77bejqakJVVVVOPDAAzF//nxfr3v44YehaRq++c1v5nLYoqJapWkKDoEMcWj45AWh50WEaRoK6aRFH1DVNCWHLBOwmjC1QMY3222CEZEdsmtGnJgR72oaIU0j8xmRMSNMwCpOtKYuQguw+rcvJpwCpLwgKe2lx8nmcBy39DCRrxoCVosdPIDSD0YeeeQRzJw5E9deey0WLlyIiRMnYtq0adi4caPr61auXInLL78ckydPzvlki4kaI03TroKRgkHIBVsErH5RMGZEIiQTVnBaMpyVlUJBYXbtNWEvj+weQaZQ2quJCwI/AlbXahqNX7HLTM/s15Vt/5YUbiDNCNuFw/UbVipOS5pjhSxNE9BYzdTVyTU1Tm6vWQ2xq+4LHIzccsstOPfcc3HWWWdh3LhxuPPOO1FTU4P77rvP8TWZTAY/+MEPcP3112PEiBF5nXCxoASshYeQD3Vo+OQJtnpCgUp7ufssPxs/SlTBH7KWwRzgVrIaSCDCrXZ3aViYEcBSneEUjPhhRgR2wF7aCwkzovPBAuwTbiAHVhrISKrhrEZseSFh9xkRmJ6gzAjbl4wZ4b4v+t3x42HMxqRAwUhXVxcWLFiAqVOnmjtIJDB16lTMmzfP8XWzZs1Cv3798MMf/jD3My0yzDSN0owUDEJpr6Ve3idDYlKtWrTVNMattGsvELsLX8Ef6IAuMCP8ZNhNUjQApHoHM4hw1jtI9RgWsDSNw4Qs7U1j3UamGQm4+ndmRkIKRiSlvUIgFjTocenfxX8+TGsnVC3Fa0wK1Jtm8+bNyGQy6N+/v/B4//798dlnn0lf8+abb+Jvf/sbFi1a5Ps4nZ2d6OzsZH83NzcHOc1IQJmRdlVNUzAIg1jepb2IWMBq84OMtXJdwR9kaRqnVfyuDl2ydvUzuQVL00BM02jGDpy0HLJ95bAIkAnQxUArpO9ZUtorLJhC+D3R95/hhkhbHxyg9NM0QbBz506cdtppuOeee9CnTx/fr7vxxhvRs2dP9m/IkCERnqU/1JSTuC2V0dGlOvcWBKZ7IFgwUlNWI9x6oVAOrLISO5HCjteFr+APVMAqfK+C2LJ7lPUCFgGrJV3qnsoIkqaRpzQdGQvu1pbCDaCLkLE3kQhYJaW9AtMTRjWNJE0jfa6UmZE+ffogmUxiw4YNwuMbNmzAgAEDbNsvX74cK1euxPTp09ljtO1zWVkZlixZgt133932uiuvvBIzZ85kfzc3Nxc9IKFpGoCIWCvKVFV0ocCbng3sMRDXH3I9duuxW6B9hJr3lUBmeS0OMvG68BX8wUzT2CdikuPvRsyIJE3jp4xWNmFa4RTUsCCfL+2lq3tKZliEq2KpbMBgRJLuyISsGWH7t6a6ctKM2DU1dH88h291YM26aHyKhUDBSEVFBfbdd1/MmTOHledms1nMmTMHM2bMsG2/xx574OOPPxYeu+qqq7Bz50786U9/cgwwKisrUVmZgwtdhKgoS6AsoSGd1dGWSqMnVGVE1JAxIwDw7VHf9r0PsYNnlBefvZqGQqVpShduaZpMN9OMCMGIhYXQXTQjMstyK0TdhBlAuAs0LdsYx0lqSfP5oKkILhih+wm3msbtM0SoPiNZM35mn5nwnmI2JgUKRgBg5syZOOOMM7DffvvhgAMOwK233orW1lacddZZAIDTTz8dgwYNwo033oiqqiqMHz9eeH1DQwMA2B4vBVRXJLGzI60qagoEnV9J6bmlxkQRWnQTh0zAKg7UKk1TishKJlJxkupOwYid9qcpK1+lvS4QJmRukpRNtskE/fw1uSAU8n25wbMqJTSfkXLH6p+8TM8kv8+0hM0Tmax4jUmBg5FTTjkFmzZtwjXXXIP169dj0qRJmD17NhO1rlq1CokYNd8JEzVGMKK8RgoDXRhm/AxpdogBQfQrAcecc8xWIQr+QFMAzmma6MvFYwOJfkb4LByDEcpwughYhQnZzozITb0AVPW0mZ6J5+RzwjWEsjK/jpyqXJyQLLf10nFihfzALEl2SC9ZjiFoc2I2JgUORgBgxowZ0rQMAMydO9f1tffff38uh4wFiPFZp2JGCgxrmibQa6PI+0rg6RQZs/ysgj9kWUmkCYEN6EbMiBmMmLOcnxSDrKO1FV5CWI27/oVtqxsAtJFtrKJaaOEIWMPUBiU5ZiSQCNgJduZOSCNaHvPjC1Ms7JoURkSoLldeI4WEzrxFkHMwkswjHxsEjMLm0zQ+KGyFeIOlaXj/mG7qMyKtGPNTncF0pW4+I/QYEAMIycpfCICqenKbSjQYvoMR+j07+HWExoxU2IIzgRkJXG5rP2867qR5ZgRiIBnHMUkFIwHAvEYUM1JQkGAktzSNcPGFlfeVwNS3OPgUxKymX8EfaAickH6v6Galvfbpws+EbV4abmkamPsp85emyUAz0jSWfRkPZIDAjfIgmdRD1YzwLSGMJna+RMAOEN47XbwZ30narRQbiN2YpIKRAFDN8goLp2qaIEgYV2su4rAgcPMZUWma0oVb195uV9qbkDEj9Dnn3ktm6a0zEsZEmk1WAJzmkKU0uNJeKmDNahCCEVYxwh83LJ+RsEzPkhWcKNfoqJtHOlfWv4sKWN1Le6MdD3OBCkYCgPWnUS6sBQFL0+h67sGIcelnE2XRNqrjB1zjvAtXVqwQFaR28AWq0IobpMwIZSlcf98+SnvpMZIV4jHpHiT+PSRN02DulaV0yFiREyPpJAQNTTNivj+NMiN5pHPNIAqwulTzzIhdwIrYVdOoYCQAalnnXqUZKQSEapqcS3sJsmVR+9Zwq0YLXRpHSlTBH8xqGhPd1Q7e/I2bk1ySBgYu15csBSLfs/06NSdbiYAVAKobbKZnCRqMJJICy+IGWdATiQMr3yhPt6ZpEEowwoIoekgnwXHMqmlUMBIAKk1TWIQRjCSNXbgNlmGApZQ4t1gh5xwzSlTBHxgz4uQf0500IwmyGJOladyCfV8OrMZzTsyIvDeNqBlhugi6r0RwJlSWpgm1Nw04hilrSdPkMU4IzAhEZkTG6ikBa4lDCViLg7xKe2mapqzCY8v8IOacyV/MCTKI34FCrJBlA7pDyXZ3YkaMNKfgM2LcZpMuwYgfB1aP61SWpsloAKoabI/TNE0mQFrWjRnJxabd9Vj087AIWLMBNC4muMochzSNrBSbaEbiNSapYCQAqo00jWJGCoMwSnuZMC7iNImoahfpUpKmidcqRMEfdJmAtZv6jLgxI36YRzefEVYBYwsg7IEMFahS0zNzS0PAylgW/zZaZjDCpYOEjsThMyOahcnIKU0jaNXEYIQiyd1XaZpdBDUqTVMU5BeMGPnjZMTMiETVrgSspQ9W2itN06B7pWkkTIMZ7LswIz6q8s00jVUzQvOsXKM8Q2tB0jQNNr6FCVgTwYMRyBgwIFxbACoszabtx8lRM0L+kAcjApPF60kUM1K6YGmalBKwFgKhMCPGbfRpGruAlTkhai6GUAqxBv1epWma7mZ6JmFG/AjEZZblVphpGjHgkZX2JrK0WgZAVb157THNSO7BiJCm4atyQvyedWpAZgQjLKDLYZxwY2Qp+Ek+KbAw8dKxqWAkAEwHVsWMFAKiz0hu+6ADinXFFTokgVMuTpAK8QKdAoXUhPFdh1ryWQKQpT2chKfC6yT3nPaTTTgEI7yw1JjEs8kyoKzK3ijP0GIEEbBKhbIZchxinR5mmkbUttDzzcXpVfh86CLIMq0LAlY+8InZmKSCkQCorTQ0I50qGCkEQintpaubiJkRCNoCkRkJ1U5aoaCgbdgTskkK6FbBCBJUwMqLSf1rslwFrGzR4OQzwqVpshzzUV5jMz0zBay8WsLz5Pgb4zhG0KMlgAD6E+9jUQErZUY4BiZgOtnNZ4RCKEvPpoxjIXZsrQpGAoAGIy2dKk1TCOh6/sEIpXSDKOtzgbTen5bRxVC5ruAPZprGBFuZa86uo7si9IS9msbUjHgzI25pGrZid0jT8Nd/0tCMkGDEvK5YmibLPR8Qgp8J/Z5z2I8b6G+K2cEbx9ETSVNPEhAynxEKQe9Ej6UFD3yihgpGAqBHJYm0W5XpWUGRlwOrw4orbIjBiMiMAO6ljwrxBWVGBC0BHdC7USACALrBNPBVMb7SNJKKJCtMnYf8MxUCIJaGSQqMI/2O2DWf8M+MSDUjGS4dFCKspb1aJv+ghw9GkpagT2CyMhzbk2PgExVUMBIAPSrJhdLSoYKRQiCc3jQFqqbh70jo0qhLixWigWkHzw/oBtXdzYIRSJgRXz4+fFsHB2gsqHEIRoQ0DZ28k0QzQgPGdCc5TT04MyINRmhKI2RmBFafEZ17PwEhS2XT3yeFwIxkOFYvZlDBSADUGsyIStMUFmEEI1GvYmXDbIKrANDLFTNSiqDfqzigRzRJxRymgJWvODGCkbwFrDSAcEjTCNU0dNukKGBNdwnP58KMgE/TUG1Q2GkaS2mveZwcghFJKjthDUaE74sGPvGb+uN3RjFGD0Mz0pnOIpXJbXJU8I8wSnvp6qOgDqxsUOhkz0fNzChEg6zEPZSumMOepOIOWXVK0gfzyEpvXe3g5YsGqRlZhmMSEglz/9lO4zYXZoT6mXAMGGNGwmURzPPNCLe5sBXSNhTpTmEbUXxtvCdJ08NiI35nFGNQASsAtCp2JHKEUU1DB7lMgSYOoVGesVIDVDBSqjBNz2RpmvhR3VGC+YxwlyUTnrowjzp7gVuahgY14nUqK+3VdDHVwHq9WJiRTA4TrpCmMfYXdkpDt1bT5BH0yBZsWqZL2EZgRli5cvym/vidUYxRnkygsox8ZCpVEz3CYEaSlLItUDAglNjxzEi8tGIKPpGlZdrcY901TUPLW8VqGj8CcR/MCF+uy0HmwJrMiGkYNrnnkaaRnSP9nnNJn/g6VhhpGomuLpkV0zSajO1RwUjpg6ZqWpXXSOQQL7TcXM9yoWxzgXCutFEeR5dmcwymFIqLrHSSIpNe90vT0GCEZykoo+HCjNBtXfZNNSP+BKyWCZUGI0bwn8gGF4Sa1y8/cXcF3o+vY1HNCGUyeD+THOHEyAJGwEgrjVggHb+pP35nFHP0qKJeIymPLRVCRc4+I0YwEnJ5nhVSVXtKBSOlDvq9CmmadDRagrhD7jPiv1rNtZqG+gE5fKZCOXHWWhFCg5Euh+e9IdWmRPQ96zZmJP/jCFo1i2YkqQOgnw3TjMSPqlXBSEDUVtBgRDEjhQLPNiCTAu47Fnj+Cn+vzaHMLxeIKSW6Cum0Pa9QWqCDtph37zSe617BCBLUZ4QX83pXq/kxPXMyKpMLWMXVvZmmEQWseoDVv9xnJKKUhk0zkjszIq2msTAjGgCkO8hz9D3FcOqP3xnFHGaaRmlGogab4DmlOLYsA1bNAxY95GsfpnFR1KW9Mmakgz2U0VXwWopgvWlUmkb6flmw78I8BinttR5D5sBqTWswR9O0mKYJImCVHYd+z6ELWJkDq4UZySUYkfqMWKppoJviXvrbVcxI6YN5jSjjs8gh5HHpIJFqI7fpDodXiUhmo/EKsEIInOh5ZzpNM6dcO/0pFBXMZ4TXEtAqixjm3aOEeQ3pJvvHhKdupb12PYYVXgJWTRCwGsJSTc6M5FIxIguYzKAz3O/ZVk2Tx3FkAlZrmkYDWJpGU2maXQc9qgwXVsWMRA5paS9lG7Ip1tvBDRrf4bMAECp/Uu2gayqlGSlNmMyI+ZiZpulew6dQ2svcQ6nw1Acz4pqmkVeUyNInmoVJYKt8q2YkiAZDtwc9GmNGwp242Xuy2sHnkaYRqmlsAlYAVNzLfrsqGCl5sP40KhiJHNLS3nS7uYEXO5JJcz0vCu8zgnQHE/upYKQ0Qb+1JJdmM2n17qYZ4Up7sylA181qNdc0qHdpr8a7qnKQpk+YLwdVk1mZkRxW/6wHkfkQE7BGpBlhAV0IQQ+fyramaZIA0drBfE+6a21TcaCCkYAwBawqGIka0t40nA4DFjrShlQb+4FHPXHIU0rtZiMxJWAtSVCqn7f2j3NFQpQQSnszXUC6w7y+XIJ91jvGNU3j1CyOXlf2KhedHV1e2hsoTWOcmiYJesKeuO3VNFTHEVKaJiUu0jTobKykbE8mhr9dFYwEhFnaq4KRgoIxI9yFlmqXb8s9z3pnRJzflwYb6U52gSkBa2mC2cFLqjniKAKMEjSFQjQIKcv15RLs04neKRjJpJgmx8n4S5amYROqrZomeNrDTAdxx2QOrNFqRljaKY+gx8lsETAm+YxFwJrzkaKDCkYCQlXTFB5C6iMVIE2TamU/8KiZCSmLk24v2PEVooFpB89rCeLrYhkp+OAr0wWk2sw0pMs8Kkz0susg1caCAKc0jSBgzYpMAtsmjzSNacwmSQdFFHRSrYiZpsm3tNcYgyzMSILzGaFGjHF0hO5mV1P+oP1pFDMSPeSaET5N4xWMtJuDJaLVbIhiWxo4dbBur1EfXyEa0FVsgteMpOMrAowSwm880yUItN2Cbc8eU6kOxoxYJ2S2Wy5NZjIWxjb0e7AGIwGYBlmjPPY9+96L32PJS3tzYdpkn23S2igPsKVp8mFhooIKRgKihwpGCga5ZiQIM9LOgoGMj8qbvMCoaAjMCKWmlYC1NMHs4LOcpXa2m6Zp+OsxkxKZEZfft2AHL9vOhUGUlfZajbvYK9KdQDaTl4kYpAxY8N24HoKJZY1qGiNQyORwHHPBZmrVNMu4mKAaH5iGaHHkaVUwEhCqN03hwAYm3vRM0Ix4BCNdrWYuOuLLT9abhqz4CFQwUpoQHFhpKWY6vqvLSMEH3AYzwjQjPoIR8oecGXFiMOUOrDRNQ7ehmpEOQacVJFiUlRAnDe1FZAJWWuHCdBy5MyNW9lhoX8ClaRLG+BnH0UgFIwGh0jSFg1OFCoMfZsS4G3UwIHWLTRfu+ArRwKwEASlnRTilmKUIkRnpEqrV3IJ9kRmRa0ZYOtN2ndjTJ4xJAP/lGI+nO0w2MlAwIvEZSUejGWHvhKZp0iGU9gJiFR/3nCxNk4khN6KCkYCoM6ppdioH1sgh7dqbDlLa28oGuUIJSK1lyM6DrEIpgLIfRASYIt41tHS0mzEjQsBtVNME8dFxTtNwmhHdgRmByUQnbcyIsQ1ja+g5Bb/mWTCi66ZBWOC9eB3EUtqbhzZFvgjqEH6ZpJqG+oxQtid+UMFIQNRXE3Of5g7VtTdy8FeMlBnxLu0tlOmYVMDKDbLKDr40wappALKSTXO/qe4Vi0iYkWDMn2Mw4nKd2tIn2axNoGpW07SL3icBpncz6OGvXfG5sGHzGck3TUN1cVz6DKCaEUPcG5EoNwyoYCQgKDPSlc6iI6V0I4WAczUNx4x07gQ+eBBo32Y+1tXGgoGofT6kKSXlwFryECapTEpgu7p1eEnTND5M/cSJXubH00Ha3LvshwUjfDBoPkv+n7IYsQW45mzalFQ7O2ZU1TRaJg3oOhOc5h3c8poR7uGEDrNRnnGsOC6OulfbyRDQo6IMmkYWvzs70qgq72aW0AWEmKYxo34G/v7c3wLz/gK8MwHoORgYeZTvnHYo5yoMokrAuquABrGmcZTOpRTiN6BHCbG0N+W7dN5bwOrCjDBGhF7/HGNhSdMg3S6UCQdJzdpKewWGJdzvWdCMCMfJZV/cufGfETct8Y3yEqlOAHWKGdkVkEhoqDNErCpVEy3EC82DGfn0GXK74WNg6QvA85d7COOigc30TGlGShr0N5jQQQSsBfSuiRuEMlKjtNdPsO0nGGEBnlc1TbqdGaRljMfY/jNdwvOBrjm6E85cMSrDQvaesmnxOLnsi/diMtI+/LgD0EC6E8hmoRmGcXEMpFUwkgOYbqRdBSNRQnqhOWlG+k+w78DnYBkGRBaHHt9ZmKdQGqDfG1ldpgPrJHZFyDQjfkzPHB1YeX2Go88IzzaK1xSreEp1iGxkIM2IpZqGCzrDTvGy87WxS8EDBFEzQsdIs6IIAEmlZVLi4iiGgbQKRnJAXRUJRlRFTbQQBzFjQHBiRsqr7Tto28ouysjt4B06DBcqTaQQDeiER3xGUkQH1E3ZLqnpme5fk+Vc2uuDzWBBQpvd9dW4IT4j+WpGuDQN233EaZp8Kv7oe6f7A4RxB+BKe4W0cfzGIxWM5ID6KpWmKQQ8mRH+flerfQfbVxWpUZ25imOUctQOsAqRgP4GWWlvqg3Jbsp2CddjAGaEwr20l8BeTUMXJOZixJoms6U9fBixOZ8jn6aJ6nvmSntT+Yns5cL5TnswYqSw4lzdp4KRHGCmaRQzUgiIUb8DM9LVYn/hjtWmSj9qAavA4ihmZFcBnfDYbzDlnFLY1SH8xq2lvT4ErGIhLgduQrZeJ6aPBhckWJgEgbHp3JHT9yNL00SdjtOMtF8+FXeirs5csPGaEdExN/djRQ0VjOQA0/hMMSMFA6cUZ+A1IzQYOfACoH4wub99VcF6w4hpGuf8tkJpwUzTwN6pNoZ594KBClh9TG5Sy3IeKe8SeCEYsTEJmvn/juacJnc2d0vE55ELWEM4jqaDBCOZFKBn2GcEGJqRdGdBfZdygQpGckB9lTI+KwQECpLLhzIIzIiRphl7ItBnpLGDbOSrG+u50uNC11U1zS4AlqahFST55vhLGML7ZcyItyZLbHPv0CjP4Tox9RUZtq11QhWuvc7mnASstiNyItCwg07zPaVcK4l87Yv/bI3gBmAO+QA4B1YXoXAcoIKRHKDSNIWB7UIDLMwId7/TYEYqaoGaPuzhopT2Qjfr+o3H43jxK3iDVdPosE8e3SzAlPWm8de1lw9GZGmaDsd0pj19YjdIM1+jAx3NpmYk6+/74a9N3lwtqoWMyYxkSMuKPI5jq6YxxkS7ZqQz78AnaqhgJAfUqzRNQSAtW+OZET4wocxIRQ+g1gxGCmYHb62msaxQCiugVQgL9DeYBFhpb5yp7kLArKbxqxmRiCx5pNq806lcNY0TY0E0I82B02h8ACTTjESWpgFI8BTCcZgdvDHuJDhuhDiwdtqqluK2QFLBSA4w0zSKGYkStr4LmbQZlAAmM6LrpmakoofAjNDKh8hLe4UBV2fnlrQ8r1BaEHxGsqlISz7jDtH0rMu/3sF4Kmg1jchYZBy3FRYCHc320l8PiMfh7eDJ3dB9Rvh7HTvyKhUXKw4zHDNiBiPMpC7dDt4vPG6/XxWM5ID6aqO0V5meRQt+EDOalAmgwUi60/QhqagFanuzTdiFXkhakmNG6KDQXVfRpQ7BZ4T2Y7E8110gT9P4T1mRa1GWppFrRkTGghewituK1TTNeU3ugs8IPY+wFzIad9OxwzFF5Qc29piOO5oZjBBWr9Nmhha3368KRnKAMj0rDIRSQqOsUgANRviyXqtmxLgtqAMrTGZE0xIFOb5CNBB9RtKisLGbfaey3jT+7OA9qml8MSN2xsLGjOgw0h7BdBHOaZqI9BX8Iqtje14aJJuujo47fJoGsFU/2V4bA6hgJAeoapoiIJuxMyMpSzBSXgMkkoJmJGF0jCqWZiShgpGShugzkhK9Y2I2mBcK7LPgBKxuq3oxGHESsLqnU/k0jVPq1co0+BawWivhgEg9OYTPo317KBokUnGYkTIjGi3ttXTzjZuIVQUjOUClaQoDWz7UkRmh4tVacsszI6OmAShwMKBDMSO7CESfkZS4Mo/ZYB41pKW9PiZssbRXFoy0ST9TJ0MvuwMrt10OAlYhjpIZFoYuYOX217E9r1Jx22fENCPm1M5X0/Alv3Ebk1QwkgMoM9LalUFXOl5f6K4E+4XmoBnhy3oBoHEEMOwwYMwJSIw6huyrUAJWHQIzkqTBSDebuHYVCD4jli6rcRvMo4bwG0+1A5muQGka8keANA2fPskYCz9JAGQNRqylv16Qp2miS8cJi6z27Xm1rHDWjJhTO6t+sjIjMfv9lhX7BEoRPavLkUxoyGR1bGvrQv/6qmKf0i4Jm+mZl2akoge5TZYBZz1HXvv5kwCiDwaEAYbTjJBBIdNtKf1Sh+Azwgb07qkZEbUOzcZ978/C24G1HQljJhJZFH4nGdNIEJZt+fMCAn8/UqFs2tn7JF+w/ekAOrabzTxzOQ597zrIZySMOwRJHay0N8F9vnH7/SpmJAckEhoaaysAAJtbOj22VsgVtkZ5lBmprCe3KWuapodtH/SijNrnwzbgsjRNYTQrCtHAbgfffX1GhN94x3YAYCyE62chBAuSCTctZyGEIAFgCxK6Lb2mRfF4cG8hqelZAfq4UGbE12foACdmRNP4NI1uExznerwooYKRHNHbCEa2tHQV+Ux2ffADEQCgqoHcZjoNjxGLZoQDDUYKykzoOjtXJWAtbVBGLQGYDqx55PhLGcLE17YVAJBIlgvPuUHKjOi62OPGQTNiMlPtNh8RgUEF8vKBEap2jMciDUY6doTSKM/mM2JL09gFrHH7/apgJEf06VEJANjSqpiRqGC/0AxmpLrB3CjdyaVpnIORwlXT6AYzYuRuC1TNoxANzDSNzhxY6WTY3XRAwuTVToIRLUGCEX9pGt0ejBj9pWRiUYGxAGzBoNT0jNuXXzZUnqaJ0A5eqLzL5CWUdepNkxCYEQBp0b4fiN/vN6dg5Pbbb0dTUxOqqqpw4IEHYv78+Y7b3nPPPZg8eTJ69eqFXr16YerUqa7blwp691DMSEHBMyNCMNJu14xwKBQzYkvTMGZEBSOlDFPAClba2919RjToQPt2AEAiScZBX9U0VNzNI9Vm7BOu+yGr+7S0moY7QfP8PM5Jen7gzi/Cjts2JicEPxMzlU2COyFNo8NIMZLuyHFNMwYORh555BHMnDkT1157LRYuXIiJEydi2rRp2Lhxo3T7uXPn4tRTT8Wrr76KefPmYciQITjmmGOwZs2avE++mOhdS5iRzSoYiQx2Qx+DGamoMx/PpM00TaU9GNGMevtCrQJMAStdoSSNR+JFiSr4g720N96dTwsBXvuRMJSnrl173XxGjIVEgjIsTmkagJWuWj1JrJqRoHbwPFiahuskrEMP9bu2aVxC04yY7HFSM43fiWak0xyTYuoKHTgYueWWW3DuuefirLPOwrhx43DnnXeipqYG9913n3T7Bx98EBdeeCEmTZqEPfbYA/feey+y2SzmzJmT98kXEyYzotI0UcHRgbW8Gkx+n03ZS3s50Hr7TDZiAat1dWWcq2akaVSjvNKEYHpmcbGM22BeDGiUGfHRKI/8YdnOuHa1MrK4c0rTkIOIPi9O11TQyd3R9MxpmzxhfV/56DhE+4OMbdxh+9ez5mcdUx1boGCkq6sLCxYswNSpU80dJBKYOnUq5s2b52sfbW1tSKVSaGxsDHamMUMfGoy0KmYkKtibQBnMSHkVYAyCyKRcNSPJAjETos8IX9prHL+brqJLHYIdvNEoL7Cp1i4CqzYDMAWsvqtpbMxIq7EfEoy4Bu0eFSFWzYjfa15uOx9dHxfreeVV4cJ/thx7LAhY6eE6STl20mCL4zYmBfIZ2bx5MzKZDPr37y883r9/f3z22We+9vGzn/0Mu+22mxDQWNHZ2YnOTpNxaG5uDnKaBQFN0yhmJDqI9C7nwFpWDRi0Ll2tApBqRliappC9aXg7eIPBidsqRMEfbI3y0h1IJItQoRUDCAG3AS1ZAegB0jTWAKFrJwAgUV4NoF1kRhzSNHznWT54sfqM5CZgtadpgJC/az6AAMSgB1kkhXfotStOf5I1u5onNAszAgAdO4y/42nEWNBqmt/+9rd4+OGH8eSTT6Kqytko7MYbb0TPnj3ZvyFDhhTwLP2BpmmUZiR62HxGyiqJsRlAVqtdRjBSXmN7bcEErFbLa8qMqGqakgarpgFMmrubpmlyZUZcTc+MzzRRVmXbj62aJkP74cgZi5x9RqwlxNmM4C4LhDtxW4M6PugJ+psSxMF8o7yERTMCsGBkl0jT9OnTB8lkEhs2bBAe37BhAwYMGOD62j/84Q/47W9/i5deegl77bWX67ZXXnklduzYwf6tXr06yGkWBHxpb3dbIRUKQrmsVTPC0jRdQMoQsLoEI4XSbDAWhwUjhsBPCVhLEvR7SwCM5ubTAN3p2pf9hmk1TWCfEV0Hvngd2PYF2Y+hGXE2PTNE4XpWmLx5LRgTsCbt+hO/0DhWM+o+Lta0Ui7HcTI9S2pm0iNB77PUcTzTNIGCkYqKCuy7776C+JSKUQ8++GDH1/3ud7/Dr371K8yePRv77bef53EqKytRX18v/IsbKDPSkcqirUuJEyMHrxkpq+LSNOYFiAp7MEJbaRc0TWOU0QGAZgQjUQtoFaKBYAdvWKDTABPoXkGmtQoEMAWsbr9vaaO8124CHpgOvHwNAJqmcf48hc+fe1y8ro3zk7AsbrCJz1mzOYdt8oSTY2w+x7E5P/PMiCamfbQCL9D8InCaZubMmbjnnnvwwAMP4NNPP8UFF1yA1tZWnHXWWQCA008/HVdeeSXb/qabbsLVV1+N++67D01NTVi/fj3Wr1+PlpaW8N5FEVBTUYaaCvIlb9ypdCNRwNYoT2BGaDDSxaVpqm37KJSAVcgDZ7o40zPFjJQyBM1IJ9E3aGXVtue7E8Q0jcFo+Kim0XSdTJjbVgJzbxT3aXymrnbw9PPnzkCqGSlzD2zcoAl6rwrpcfKFNd2VzKNfjGOjPC5g5gMTwNSMxI0ZCdwo75RTTsGmTZtwzTXXYP369Zg0aRJmz57NRK2rVq1CImHGOH/961/R1dWFk08+WdjPtddei+uuuy6/sy8yBveqxtINLVi9tQ3D+9grORTyg+1Co43xyqrMYCTLCVjL7d9BoQWsAJgfBaAErKUOOmAnATNNU15le75bgL5VvgkbTdO4CVgF5iEDfPqsbRuqGXEt7TWCkWSZ+fnLriuS8knlzYxo5e7HyRXWIEkIboNqU/hdcWMkz4bQ74j9HVMdW05de2fMmIEZM2ZIn5s7d67w98qVK3M5RElgaGMNlm5owZdb24p9KrskbI3yaDrGyoywahpnzUjh0jS6hRnxUfqoEFsIPiPGZEjZAICsmMtRXoQzKzzYb5wvG03atR5OYCJUo8kej4Sh93LdD2VGOAZUYEYoO1lWBSCVezWNMZ4kuSAhmqDT0CPlEdw6NspLcpoR7vcKcALW7lxNs6thaCNZia/a0lrkM9m1wRTuPDPCa0Z8VNMUqjcNOacuxYzsIhB8RgxmRON+Z93pezWDEU6PUBYgTQOQa6PTnqKnAYbgwGqtpqHBoEOajKVpqP7E58RuD0YoM2JO4qFW01h76eTxe3JulMelacp4ZkSLrfeRCkbywLDe5Ee0SjEjkcAp6rdX08QgGOHL9YzuogB8NRJTiC8EzYgBYSXbjbRAbPLSTM2GFiBNYwYjO23bMJ2Hm88IS5NxQYIsGMlDwKpxTS618tpIBPA2AatH2sl1X0LLjIxZTZM02ToaMAIAyqsLlroOChWM5IGhjWTy+3KLCkaigC1NI9OMpNpIHhpwTdMUatKwVtPQQSFulKiCPwg+IwaS3Z0Z4Ss1Akz8LE3TaTex1CrsaRpHASv3+acNky+2DUQBa9DVv8YL5cuqIvUpYr+p8pqcxylBHCz4jPDMCOfpxb2nuP12VTCSB4ZyzEjcKK9dDlzUL/SmMYx8yOPFK+01jweDGaGDAglG1O+jNMGYEe7r05LRCBvjDplmJFHmgxnhJ9h0p5wZoZoRh6CdD0ZQVm1WyUmOm+A0JX4md9v5pczqvChYBLbIooctrzZdUXM8DlmwpWz+RoAo+EV5Td7HigoqGMkDg3tVQ9OAtq6M6lETAWxNoARmxEjT0GAkUW6yJRwKrRmxBiOJpNKMlDLo5MgPlMJk1w2DTFHAajAjgTQjPtM0DpoRlFexIEFW2stXwQQpySXsQspc9JRVmWWwITKrNr8W7v3kmqbRAFM7B3MRBIgaG5RzzEjM2FoVjOSByrIkBtaTH75K1YQPuwOrpJqmfbvxmJ0VAQqvGQFgtOumK5SKghxfIRqYaRpuYizPoxSzlMFKeyUCVh+N8gCIwUhNb/awZjS55IMHWwDAghH31X0iYBWMvYTYSCOVV0fi4Gx7X1yaJq9xossUBgs+I7xmpKy6YC0ygkIFI3nCTNWoipqw4ctnhDIjEr0IUCRmhFv5aX66mirEFqyahntMK68uePovDpCnaez+II6vA8RgpGGYuR9jMeE6QbI0TZU0SGAmYgFN6WxMBVvgRCT2tL5FLujJq5rG6IAMLWkRsDowIzH77apgJE8MM8p7FTMSHaz5UKIZMS62TiMY8WBGIm+Ux48wHaZAjxoOdasV9C4EwQ6eghccxmx1GSVYwM0JWP1YrwsaCSEYGcq2SRrMiKxRHgsSOMZCnqYxtg8oMLYdhy5wIhKw2oKfPNgK6SKIC5YBMa2oqml2YQxV5b2RQRjE+AtHphlxCEbYCjbiYEAwPaODppY07eC70aS1K0FolEeRR46/lMECboEZ8U7TCNdGuhPoMibNnoPZNposGLFO2hwzQgWsMtOzXAWstmAkD8Yi0PF4AWvAcUp8f8Z9LogCLMFIWXUkOpgwoIKRPEHLe1cpZiR0yBpzATA0I5ZqmiKnaSg0wGRGHFZwCqUDmc9InAf0KCE3PQtY2tu+zXygptHcj9HKgf887cyIqRlhwWBW4jPCjQU5XXcSZiSKxQzTIeXBVkjHSGswYknTxHVMUsFInqDGZ8oSvkDQkkQvkoiXgJUtGjmnzqh9ChSih8xnJKoVc9zhmqbxUU0DAGjdTG4TZUCl2Y3djWFhKYdsitx6VITwaZog153JjGw3jlMTSVM5W5BVnr+oVPx9mgEHIAquQxPLRgAVjOQJyoxs2tmJ9q54RZqlDumqk15YPtM0he9NA4EZieuFr+APgh08RYzz7oUAz4wkfVivC5Nv2xbyYGWd0GVb9nk6sk5lcl8OJmDlGmbmpRmJKB3H3hfvM5LrOMEvgii4zwewpmmqXD1aigkVjOSJhpoK1FeRlIHSjYQL2yABEL0IEDhNU1ABa5dd9d8dJ61dATKfkW7PeNGu7Imy4NVifDAy7htA/WBgwneCfZ5cMMg7sFIIpdcBqmnYSMPSNAVaTJRV56xtky/YrJoRbmyMcSCtgpEQMKw3rahR5b1hQpoPtTIjXN5VBrpCiDo/Kg2cyqMxTVIoHGQ+I4LPRTeqkrJpRnjK36/pGQtG6klAcunHwEn3Sidj85qyqMYcylOlaY+8BKzhX782IzcgrzSN4MVEYROw1nLPVcZ2TFLBSAgY3b8OAPD28i1FPpNdDJSC5B+jzEjC4rbKX3Ac6Cog6gtPuv8yJWAtdbA0TRm/uoyvCDBKmI3yaDBS7UtTIU3TVPQgtwbLIgsuHAXsZXIzMrZdsjyQ5blzCXFN6N+zrd8OEL6AlQtuAFHQCz0bW7ZWBSM+kMlmsK5lHft7c/tmtKXMlMwJew0AADz70VqkM/H6ginaUm1o6bK37o4zZCZLoFbPVut3hzQNzY8WVDNCUd7N6fxdAKyapv+e5oMhCA51XRfGkFKArVGez0nUZnoGEFaEg+zzdKumc2VGtGSgyd056An/+vViRnINRgSUWQSsSc6BNZuJbSCtghEf+L9P/w/H/PsYPLb0MXzZ/CWOf+J4XPrqpez5yaP6orG2AptbuvBWDNkRXdfx3We/i68/9XWkMqlin45vyHwNQMvUrMGIQ5qmYPlRBxYnrqsQBX+gaQNtwHjzwRC0BH9c+Ecc+vCh+GzrZ3mfY6FgVtMY115lna/PwSbYNF7Lg12nsjSNZk3TuAtYkUgG+37YeUmOE/B7/rL5SzR32bsSm4figpEEl+7KsXmdPD0sCliTXPUTMqnYLpBUMOIDf3j/DwCAWfNm4R//+wfa0+2Yt24em9jLkwmcMGEgAODR91cX7TydkMqm8GXzl9jUvgk7unZ4vyBm4NX7jBnxmaYp9IWngpFdCyxNM2Av88EQLLU/3vQx0tk0lmxdkvc5FhpadS9g/3OAI38ZSJsh6BqszIjLZCxjLNjqPitZ3SfKcvp+rDFPkOs3q2excsdKnPjkiZj2+DR/x0tUsuPIgrEgsI07CS5Nwy/msunYjkkqGPGBIXVD2P156+ax+yubV7L7px5ArI1f/GQ9NjZ3FOzc/KArY3YULilmhOWouUvNiRnxqKaJXMDKu0xSeLQG39i2ESc8cQL++uFfIz03hdzB0jQDJpoPaom8RYApwzOD3jphVfMqzJo3C2ta1uR0nCigJZLACTcDY47z1aNHunp3SNPIS3utjIXdK0ODBjRNBno1AQMnBlqEmNeu83HcvucFGxbg0H8dip++/lMAQEvKOR0u7Kesgh0n33JbN2ZEeF98MBIz8bUKRnygllt1r95pMh/Lty9n98ftVo/9hvVCOqvjX/PjxY7wA57X4BcnBNKMeNjB69AjZUek++Zz6pILf/YXs7Fq5yrcseiO2K1SFMh3yuzgG8wFCRqG5Z3+owsEfqEgw18W/QWPLX0Mx/772JyOEyZkE3LOq2wqYDUg/TydLtdyuR08zvgPMGOBUDHiZ8J1DDTKq3wFWz9/4+doSbX4S7nxh2ocThjehiGha0YEAauWAKp7kT9GT4vEyC0MqGDEB7Z3bpc+/vn2z4W/Tzt4GADgoflfIhUjISs/4HkNfnGEEIxUGCsqVtprwCEYSXIpnigraqR58YoergLaXlW92P2l25ZGdm4KuYH/vSS0JHD558DFC4GaxrzTf36ZkR2dZlr1400fY8nWJdjUtimnY3phe8d2/Hb+bx1/i7JSW1+aESkzIgYjMmbAkbGo6GELXjRNIwyq4T8URKTpWEJc0cPX+0sEmEYFzch3/wlcvADo0S/3ahrZZ8t9PoDxWVz0HnD6M8CY42PrM1JW7BMoBdAB4bRxp6FHeQ9sad+CR5c+KjAjAHDs+AHo06MCG5o78fLiDTje0JEUG13ZLun9uMMUsHGaEaOhFhKWn65lcKPgL8osV9YWNqSK/Ipas7RYMmnxg8G7697FHo17RHJuCrlBKBvVNKBHP/IP+Tv7+g1G+lb3ZffPfvFsdGQ6MKrXKDzx9SdyOq4brnj9CsxbNw9zV8/F7JNm2543BeXmY4GraSgqRI2Xa2mvVctR0cPmH2QNJHJL01jACXTd9lNF7QZ8QAhGqurZ4irXtJ98EVSLBGfJmtSSQI++QI8jyLGUZqQ00ZnpRHu6HQBw/sTzceGkC3F009EAgGXblwnbVpYl8b39iXbk/rdXFvQ83bBLpWmoNsTKjFSIOWgKPviI9OKTVdNU1Lpe+Hxg+O66d6M7N4WcwE9A1iA2327QftM0/G+kI0O0aJ9v+9xp87xA9XBO+hQZU+HLZ0QajFjSNEFMz7ggX9CMcAgy4ZpBlstxXL7nSr501oDTccXSXgt74fN8hf3JtGrcuANIfrsxZUZUMOIByooktSTqysmEN6LnCABEP2K1I/5/Bw1DeVLD/C+2YuGqbYU9WQfwotV80jTvrHsH761/L4xT8gV24Sb4YMRYUVk1Iw7MSKGCEbnPiHvJHv9dLN6yOLJzU8gN/HdmHdDDTNNk9SzeXvM2tnZstW9nXLs/3ufH+PruXwcgn/zyBT+O9a7qLd3GNU3j5sAq+4wcmBFfaRpOWMrO27JJLqW9wnESZUCywrx+s877kTEjTuOswIxoks8x5zQNd+4Vtc4CVhTOeykoVDDiAaoX6VnZk/14GqsaoUFDVs/aasoH9KzCNycNAgDcOVdM4xQLYTAj7el2XPTKRbhozkUFY1fkzAh1brRW0xQ3GKFwyt3Kjs0HiXTVqxAfiB4Wua+8ZeCZkfnr5+NHr/wIN7x7g307gxnpXdUbl+17GQDC1oYtPuTZFr56UIZcJ1G3NI1rozyesSivBRIJ24Rq+35ySHtYJ3Romq9gq8LK0sLfOCsL6nKupuG9RDitC79v9reygy9NUGakZ2VP9lhZogz1Rvvr7bTdNIcfHTECmga8tHgDlm3cWZDzdEMYpb2tqVZ0ZbvQnm5HZ7ozrFPzBalmJAdmpBACVuuAywZNyWDGU/CdmcJ+pgreEAWs4VLdPDOyoXUDALBbHvTaLU+WC5OerEFcPvhg4wfmMT10ZblOokJn2XIHZkRS9SYLYqzpE2swkpMDK78LY3HjJ9iqSgZgRhw+p3zTftYxUhYwmtuqNE1JgjEjFT2Fx3tVkkoIGbU6sl8djhnXHwBw12sroj1BHwiDGeEvrkJNnFIHVqdgxIkZQYHSNA5UtNtgzX8X6Ww6doNDd4drmiZfnxFjUdCV6WKTv+y6otddRaICFQkzGAlbiM57JjktNmS/YT+aCulnZE3TQLJokDmjGosOr/RJIM0Ie18WZgT+gq1cmREe+aZpYAlGXJkRJWAtTdBgpKGyQXic/u1U9nv+EbsDAJ5atAabW4q76g2jtJcfKAtWHsxYWkmahh8AymsAnqbkYK2miQpOgZNbiaH1cyzFsutdGUKaRst95S3bb1onzEYqm3IVs9JJrSJZIUx6YS8I+P05pQxNBsEuYA1c2uuQpuH3JTueNUhg1TSW7ycXAavsOH6+Z1ng4cRAh64ZoeeeEMdIPrhTwcguAlmaBgAaqhoAANs65SLVvYf2wsQhDUhldDy5sLjuiWGU9haTGfEs7a2UV9IABRSwsr4d3Hl5MCPWyUelauIFoZoG8gE9F2dfganMpNj37saMlCfKkdASKDN+X2EHrh1pMwCRnUdbqg0LNyy0Pe6HOZBXfIhMppBONfYlF2eS11mD/DCqaWTH8WOeJgs8nMZZp2qavE3PXJgRWyDtw8itGFDBiAdoMGJlRmiaZnXzaqzYLk/FnLIfEYI98v7qorrdhZGm4QeowgcjvAOrpLTXIUUDFEHAmpAPClIBq+W7UMxIvMBPQGFW0whMZbaLXU+y759OapQVoamasNs68MfmAxOKP3/wZ7yw8gUAwUtS/TAjwnUKCzMieZ1NwOrAjPhJo+WbppEFHrlW0wT9PbHPlv/8LcEIb/zI/60ErCUGlqYxmBAK6p75/9s78/Aoqnzvf6vXbCQBsgMBAggiiwoS44YOeVnEBZ0ZHWTeQZ0HropzYVBm1JkRde69+M7c8dVxXN55VPCZUZnRK+CCjgiCIsgeNiVASAhLduyks3d3nfePTlWqqmvrpLurE36f58mT7qrqU+fUqTr1O7/trD66GrdvuF11watbJ+ci0WnHydpmfFFaG+2qahKJ0F4rzDTd9lA1M43EZ0TDeVUgnIGpp6hrcVJ0Z1YhZpo+lJDuYkDXTNOL2aVyciDcBx28vmYE6A7rjbWZ5mzzWfGz6ktU59lST1kuD0+WCjjC4ndmzCdamqme9E9PzTR6QqQSmTAiFep668AqrYPCgbU3zr2xhIQRA6ShvVIEzYiAWtKqAQlO/KwrRfx/bTwGv0Up4pWOkj3BUjONWp4RmTlE20wDdKtaVVf4jDBaMxSjpGcAmWniDXHFXpWsvb2ZXSp9uPQ0I8JEQtCMOLuE8EgLrtJ7z8/7Q54VqVOrWtKzsEN7NTQZQPc1VddYqEe5RCL0WtVMY6IcvX4ze75e+4xI62B3kgNrf6S5M7gC4wDFC0+pKclMyoQaD900GgOTnDhZ24w3vi6PSh2N6LMOrF1wUtWlGE0jMdMYaEbElOzR1IwI6tKAZBB3JOrOQsiBNb4RV+xVGSZ7M6BrakZU8oeIZhqb3EwT6XtFKQjrfVcz05jxneFUPgnomVNVHVgVE4zIO7AqfEbCdGA14zMiy7HW2zwjivqZcWClhfL6GIL9NMkhX4hNqRnR0jikJTrx2JzgmiN/+uw4TtVpLy8dLfp8aG9Acm3VQnt1fEaA2GQc7A5HlNTVZtMP7VXMnkgzEl+ovqS66I2qW9rvUgdWaZSNgBja2yV8C2aaSAsjyvKUphqtCBtTDqzKfcqwfOgLI2q+HEbXP1KhvWZCl8OJptGitwvlKbFJtMlaJsaeOF9HExJGDBAeQmViG6VmRFi/Ro27pg7DdaMz0OHn8dBb+9HWGdubINKaETXbdlQQXEakD7swkEkHNKf+QlWxsJGKwohCKA3HTEOakfhC1IyomGl6M7tUTg70tI4hDqxd/yNtplEKG8pcIzKnVpUZvamF8oRLpcyeDIWZRoim0fEZESYYEV0oT+c8ug6sOiHZIefSiqYxEbWjWp7GIn9SzYjSgTUWPnQ9gYQRAwQhQ7n+gFIzouaBLsBxHP5012RkpLhxrNqLZf84gAAfuxshEqG9ljiwivZQlQdbOqAZrJoZE7WkuL6F4tzhOLCSMBJX6AkjvXE4VE4OtLSOPONFjavgwCoII5HWoinvvbaAfHKlZabRy5wqEPLCVNGMSMsUo2lUQ3uD5nKjhfLC6R/VtPO9dWA1E00TgXTwmpoRqc+IRlg6+Yz0MQQhI0QYSZALI0aDQ3ZqAl5ecCVcdhv+dbQGK947GDOHVqVauCdYYqYRHjS1WYbUZ8Rg4TDlcuPRQHOGIjz4KpkiyYE1vtFcNRaR8xmRhvYC8udMavpVakYiHdqrnEzpaUbUkp4B2jPtkNBelYylHMeFRMCEk/QsMgvlhUbtmXJgVQvtNRNNI414CcP3Rq085R2qVrYACSN9FEF9mWhPlG1Pccr9FPTMNALTRg7Cn+dfDruNw/v7z2Hx3/bFJDurls9IgA9g0+lNqG01Dju2VjOi4o8jnV059IURM3bf3tId72/+3MoXCoX2xhdCn0XaTCPtZ6kDK6D9nCnzjERbMxKuAyug/XLrfgF3/VfRjACh17T7d9oOrJGIptEVekyk/VdNemZibZqILpSn+GQmmoYcWPsQjDFNzQjHcfi3Sf8mfjc7OMyekIuX7glqSLYcq8Xs57/EZ0erI1dpFbSEkQ9PfYjlW5fjrg/vMizD0tBeNc2IdOAwEEbM2H0jBacYtPTOLfSFoIInM018IcxSVc00vfBD0grtBRTCiERoUZppohXaO8AZNIOEOLBKNSMqL1HA+PnSM9MAKteUybcDCMnAKmiPIpGuX77sRBhmmq6++OP0P6IotwiAyVV7w0yrr0bIJKjrPaXVR9J90Zyc9QQSRnTw835xQFIKIwDw8BUP46HJDwHQ9xlRMntCDtYvuRZjswegvrkTi/+2D/ev2YPy+pbIVFyBlgPrN1XfAAAa2hsMy7AiA6uAqs+IFLOakRg4sGqpS/VCewUtG5lp4gu9PCM9dTgEtEN7AfVn1WFziHUQhZEICq4848UXqrAaudRM4+f9sigfrRVhNa+F0p9KxYEV0NZCyM0nSbLzqqZyR3gTEL2080YaFukCl0W5RchIzABgbm0aKeJ5epr0TPjQ5cwvdVrV0ozEIu9SOJAwooPUiUtNGAEAd9eLUCv0TYvxeanY8PC1eGD6KDjtHLYcq8XM/7sNqz75Ds0dkV0eXEszkpWYJX42EqasXChP1WdEikkH1phE02icW3WhvK4XQErXwEeakfgiatE0GqG9gPw5ExOeSVbrjUaeEWlZqa6gMCIdz/SEZJnjqYGZxkgzonxOVc0nXf5hyhdqJBxY1TQjRmOH9No5bU7TSel6E/0jJeTaOhJl5Sk/y85F0TR9B+EF7eAcoppUiRDyG45mRPyt047H5ozDp8tuwPRLMuELMPy/badw039vxf/sOws+QhE3WjMv6Sqgp5tO65Yhc7qLtc+I0QNqoBnpqQo0HDS92qE9yCg1IySMxBda/ghAL/OM6IT2qplppM9pNDQj0nMKmhHpeKbnD2fGTBPy0pNmT5agvKaq+T8ccmEkInlG1KJpus5jlFZe2pcuu0t8T5gJ7ZXS4zwjymsr1JvSwfcvtPxFpAj7eqNiH5WZgjX3XYXXF07FiMFJqPN24JF3D+LOV3Zgf+X3PS5XQOm9L9Di6zYLlTfpZ4e1dKE8owOzLtPdHQsHVvFc4geb4bmFma+Q3ZfMNPGFcP/paUZ66zMSYAHZy15t4iDTjETBZ0S47+ycXdVkqLwvtfwRNDUjJqJppGXp5hkRhBFFhFyvMrCqCT1dGg4jLYLQRxw42Dm7obColUivx+ngxbp3/e96H+lpRmLpQxcO6iIqAUA7x4iU3mhGpHAchxmXZuO6MRlY/XUFXtx8AiVnPLjz5R2444oh+N0t4zEoWf0hNkIrtLfV3yp+rmis0C3D0oXynEkAWgGnfKVPLNoCNJwC8gt1y4nFwxciOGVcYnhu4YWS3NUu0ozEF1orwgK907YpZ83CkhNA6Iq+QPd6NEB0MrAKz7bL7hLLl45nyjBfrbBRLWG/Oztx14ahV6kepxQwZC/upMFAhxcYOEJ2Xq3r32MH1nG3AL42ID24ppihmUaiveI4ztAZXStc3EzUjmp5ynEn61JZedI2CMSrZoSEER1EYcRurBlRJgnqKW6HHQ9MH4U7rxiC//6sFO/uO4t1B87hy+N1WHnbZbh1Uq7q4KiHMpRQQKYZadTXjFgaTTP9V8CRT4Hip+QHDJkS/DMgJg6swiAzaxXw7b+Amf8JQHswY4yRmSbO0XNg7Y22TW+1ZjWhX2qmiUbklVCW2+5W1fQq/eHUMocC6rl0ZL+7603gzAHg2mXq+xXXVKax+OW3AONDzDRaGVjDWQJCJvT85C3ZPrM+I+LaQUIeGC0zjYbDbY/HKMHCdNtLwMltwP/6vazeys9A75yvowkJIzqIqeBNaEaUs4fekpWagD/8aDLuKRyOX793CKU1Xvz7Owfw+lensHzmWNwwJsO0UKLlwCoVRiqaKnTLsFIzwg0cCfzvdT0uJ5YOrFzmOOCe+8XtWsmM/Mwv/kZwYCUzTXyht1Beb7RtemGf0mdL1YE1ChlYhXHObXd3a0YkAoie1tdMNI34HGdcAoyZa1iW8ppy4EKWfAgRRjRCe81oGswkt9PqZ6G/BO2V0FeGob29SdImQRx38iYDE+4OKU/5Wfo93sw05DOig/AQJjoSNY8RBJVwo2nMcvmwdHz4i+vwy+JLkOSy4+DZRix8Yzdu/vN2/GNPJdp9xuFZWg6srb5uM01da53pMmIe2humJkhJTDMOKgcZDQdWqblM1IxQ0rO4Qni5RnqhPL1+NnJgFYSFni54qVofqWZEZXKlHNuk9TeT9Ew81sD7S+s5VTWTKY7VMnuEZ6ZR6WeDqBwhz4nQR2Y1V71J0mamPDMOrPG2UB5pRnQw48Aqhvb20mdED5fDhqXFY7Dg6ny8urUMf991Gt9VNeHX/3MYqz45hh9eORTFl2Yjf3ASWjv8KKtrwan6Zpy50IYUtx31Ld1Ch5ZmxNPhAWNM88VvSWhvhIipZkQ5yNjUVaLSfqDQ3vhEN89Ib9LB6+TNUZs4SCP5ohlN47K7VCdXSq2v8rudsyPAAsZr0xhMKjRDe02k449IBtYepP0XBcYujYgY2humz4hR1I5R3ZVI71m7TX2hPPIZ6UOY8RkR0sRHSzMiJSPFjd/eMh6/+MEY/HPvGby5swJnv2/D69vL8fp2bZ+PpJFNEJogfUikwoiP96HV3yo6Uyqx1GfEOJ5Gl546h4WDUWiv8sEXrqeNs4maNzLTxBe6eUZ6cU/paTWMNCOCYBLJe0UQLhLsCeoOrDqp4YEuIYOZSQevj/Ka6pkRjF7e4Wiu9M5j1kwTsnaQgc+I5nnCdWA1GHeUn2XnijMzDQkjOpjyGXFEx2dEj7QkJxbdUID7rxuJL47V4oOD57Hv9Peo9bYjwWHHiIxkFGQmY/igJDS1+7Gurnte3urrrqc0mgYIake0hBFLQnt1bLnhEEu1pNmQPemMKhoREkTviVaeEb1+Vkt6JtWMiPdKFEJ7pZoRaT2UeUaU9TcSzMw+xyF5RnQ0KsJzJS4mqGEeDSvPiE6dtMYOpfZKTEpnsFBexEJ7NcrTXSiPHFj7HmZ8RqQOXzzjVWdR0cJu41A8PhvF47N1j9vxnhNVXUqQls4O0Rwj1YwAQWFkSMoQ1TKsXCivl7JIbMw0WupXjZeW1PEtGqp3ovdEK8+IWQdWtWiaaJpptBxYlZMPpRbY6FqYfY5D8oyEsWpySDSNLXwHY70Qbk3NiEJ7JSY900oHrxXaG2GfETPp4ONNM0IOrDqIPiN6ZhqJoBKvanafREoPMB8WvLYL5XVNYn2zk4LCjKfdo1lGPJtpeJ6hqtE4S2Rs8oxo5A9QnFsaEii8AOL1/rlYiVY6eLOaEaU/AhBlYcTRLYxINb3K+1J5bkMtkSiL9MxnRO9YzWiacNLBmxF6NMoRI54UZpqeJj0LOx28wSRIb1+8+YyQMKKDkDtE14HV3p2KXGmqCfCBuFiMSDYT4wLYUdaAOX/ZJG4StCGeDo9mGVauTWM0iD236TiKVm3BE+sOwxcIfcBi6sCqHGQMHFhddldU1hsheo9e0rPerHyqqxnhQzUj0qRn0bhXpJoRYXKlF9qrFE6MXqRmJxVa17RH0TQWObAa+YxoyVc9vZ+MhBsbZ9PcF2/RNCSM6GAmmsZus4uqOekDHOAD+PFHP8aPP/qx5QKJdODiOIbCgjR0CHVlDri5dAD6wohMM8LHT2gvYwxr95wBALy9qxKvbi0LOSYWDqxaGDmwuuyu7twRMb6uhD5iNI3KMBktM40Va9NIQ3sHJw4GANS01Ij7lWaZEGHEpA+C2Wga1TwjyrIg9+WIxOxfT+gxm2fE0bXuTk8XyouUmUYURtTuXQPTk1WQMKKDGZ8RQD0l/Nnmszjx/Qmc+P4EzjWfi14lTaAc/FbfdyV+OSsfAMAHXPiqNOjI2tCmvg4OY8xSnxG9GdWp+hbUN3fXbfOx2pBjYrFkdri2YDHVt83ZnTtCJ+STiD3CyzWWZhqjpGfRcGCVJj0bNmAYAKCqpUqsi1Izovxu9OI3qxkJMdOE4zPSm7VpTDiwGmVgVTqwavqMRNpMo+GPI1wzXa1SnDmwkjCig2lhRCU2v8xTpvo51vCM7/Y478LH+zB9XHB1zkRHEgL+JADA6zuO4KG39uG1r07hy+N1qGpsA2MMft4ve2A7Ah0xkaqV5wjwDO/srsTeigvitq2lwWRtBRnBKKDD5xrR0iFvbywXylNi6MBqc0YlqybRe3TNNBFatVeJYTp4gzwWPUGmGUkYjCRHEhgYzjafDamT2rkNzTQmxwqtaBo1BAdNrQlGOBlydUN7DbQ+UnOr9H+4ob09XrVXo+5C+yPtfB1NKJpGB9FnRMeBFZAII5IZw6nGU7LPN+GmKNTQGLWHwsf7xEia/PSBGJM3BhvPb0EH34yNh6ux8XC1eGyK24GCLDuQ0v17nvHwMz+cnFNZdERRziL+/s1prPzgKADgjiuG4GdFw7H5u6A6+Z7CfKz+ugLnPG3Yd/p73HBJplhOTBfKU7y4tM4tdXwjYSQ+0UsH35uF8kyH9vKhob3R9BkRFnvLT83HsQvHcKbpDArSCkz7jGj5IJjWjCiuqV5or+FCeeE4sJoIITbMM2KTR9P0dKG8HvuMaJlpdNZV6hdmmpdeegkjRoxAQkICCgsLsXv3bt3j3333XYwbNw4JCQmYOHEiNm7c2KPKxhozq/YCUA2HO+WRCyNWoaYu9AV8Yir4ZGcyrisIrlA5ebgDK2aNxezLcjAqMxl2G4fmDj8On28IKePpjw7in3vO4NBZD9o6e2f+YIzBH+DR4Q/AF+DB812hfZJZRGunHy9uOSl+X3fgHO54eQd2lAXrNuuyHBSOHAQA+OaUvL4xXSgvTDONdKVUMtPEF3rRNL3RtpkO7dVJBx/RPCOSpGcARFNNpbcSgH46eCCM7KEGob3aC+WFEkkHVj1HecM8I4o+En16jPKMaNXXYLFBlQJVyxPqHY5mhDFmqYAStmbkH//4B5YvX45XX30VhYWFeP755zFr1iyUlpYiKysr5PgdO3Zg/vz5WLVqFW655Ra8/fbbmDdvHvbv348JEyZEpBHRwowDK9BtxtHUjHisE0akD0WSIwmt/lZ08p2iZiTZmYx0dzoAgNlaseSm0d2/9fOoaGjBnjOn8OxRgIMdDMGH8q1dZfh7IKiV4DhggNuB1EQnXHabKEKI+QIA+AMMvgAPX4APfuaD/wOMQev+Tx7ZCFsC8OT6o8hyOFHf3IH8QUn4w48m4Q+fHsP+Sg8A4JpRgzFsUBKuHZ2B9w+cwxtfl+P6MZkoGhV0xrMymkZroBbVu7buaBrSjMQXooBpIpojHASBI9mZLD6HDpsDft5vaKaJhhZNqhkBgPwBQX+yyqZKU+cyyh5qNumZZjp4nWgmrdDe3kbT1Dd34LuqJjS2BU2+ntYObP6uBhdaOuFt98PP83DZbTh4ITjxqfL4cLzGC7srqAk1Cu0N8fHooXCrvEYnarx4a1clmDPop+gPAGu+Lsfl+QOx7/T32Hi4Cq6BVQCAw+c8mPfS16jzdsDb7kNzhx8f/uI6XJaXFlYdIkXYwshzzz2HRYsW4b777gMAvPrqq/j444/xxhtv4LHHHgs5/oUXXsDs2bOxYsUKAMDvf/97bNq0CX/5y1/w6quv9rL6vaO+rV5X3dnc2QygO+W7FsJspaqlCuebz4OByYSRssYynGs+1+tMoj2hvq0eAODgHHDb3Wj1t+Jc8zlUtQRvyCRnkiiMNLQ14HzzednvU5KBS4Z2AkeBFGcS2gPt8PE+3DbVjfMNwMnaZnhaffD6Aa83zMp1Ce1aV4UhOBCc+b4NFS1BP5Hfzr0UVxcMxn/dORGzn/8KAPCjKUMBALddnoePD1dhy7FaLHxjN+69dgRGDE7GhZbgi39b2SlU1+6Hn2cI8Aw8AwI8j0DX9wBjsIEDxwE2joONAzgbB67rs40L9qB0v43jYLNx8HYEB+wjZxtRW1eNL47V4uuyetgcXmAw4OcDmP7c+2ju8IMxhkDSAWAgsLu8EYtPlADJQcFx6Xtb4LBxsHEcHDYOdluwfEfXeew2wG6zwd713cZBrF/wf/AzVOoJybE2yd3IFP+Dn4XEU4pj1CRHpvEbjd+ykN+pFieDU37murdxHCf53PUnbOG6jxG+cuKurv6U/BaS35V2PcNNbQF8/m0NOA5obPPhQksnjn8fFCL2Vp7H855d6Azw6PAFwDN5HWwcYLMJs9TgvVXlbQyeg3cDCJbj4lLghwfVXg9W79oHm82Gk/VBf6iKug5sLa2F025Diz84Jvl5Pzaf+A52m013XNELYBH2nW0KjhGeVoZj1U1wsqCJ83DtcWwvP46a5lDH9uM13Q+7EE1/4FwF6ptsIbUJdAkEp+tb0dbq1ayTzx/s+aM1ZwHfCXx74by4/WRtM/w8j5aOAFo7/aioD2p261qC9WjuCODDg+fhdtjgbffjdENw//6z57CmfT/AgvcnzwM867pTWTBx5Jm2oMbV2+7Hv45WY2dZA9buqUS7j4cr8wzcGcD7JSfxTt0mKHFlVMA1ENh0tAEfb/0SdqcHSaOBNl8Hbn3lAzhsNtg44TkG2lEL2IGWjgAeemsf7DYbTtR40TGgCnAAHx05hc93rkdjuw+d/lDBxGHn4LDZ4LTb4LBzaEnzARzwm3WHMSrdi3d2n0FngIfNXYXkAqDdx+OpD7+VleFs9CAhFzjj+R7tVeXdO+zA962tAKwRRjgWhl6ms7MTSUlJeO+99zBv3jxx+8KFC+HxeLBhw4aQ3+Tn52P58uVYtmyZuG3lypVYv349Dh48qHqejo4OdHR0S+NNTU0YNmwYGhsbkZqaara6hvx0409xsE69DlLWzF6DKdlTNPc/+PmD2H5ue8h2h80BsOBy8VaT6EjEAOcA1LbJo03mjZ6HxZMW4+b3bzYsY1DCIHQGOtHsa45WNVUZ3rkUR8pyceeVQ/DcXZeL29/YXo7Sai+emXcZ3I7gjKTdF8DStQfwr6PdoYmJw16DI+Wkstio0FLxIPi24eJ3zu5FyiX/qXm8r2ki2qt+iAFjn4pB7Yie4G8dgbbTD8i2ubM+gmtw6DMfDoGOTNjdQYGD78iAzV2velx71Tz4PFcHv9jao3avtFfdAZ+nEPakU0ga/lfdY73fPSt+Th79LGxOj2H5zSd+DeYfqLk/acSLsCeGRh4G2nPRWr5Uts2VsQnuzM3id74jAy2nHhW/u3PWwTVwl2Gd5OfJQ2v5v4vfh6QnwuP+ELZBnxv+Nq3jZjSe+wGa/R6kXPIfhsczfxKaTzwpfndlfgZ3xpaw6iul+eQKMF9QE3z9mAw4E2qxx/8E7CwFV7AXUHLGAz/PsPj6ApR4PsXuZvX+XTPrb5iSc3mP66FGU1MT0tLSDN/fYWlG6uvrEQgEkJ0tTz+enZ2NY8eOqf6murpa9fjq6mrV4wFg1apVePrpp8OpWo+QhlVqkZ+aj0sHXap7zMzhM1FSWxJiC543eh4YY9hQFiqkxZqbR96MVFcq3jn2jjiDTXAk4AfDfoC85DxclXMVDtUd0vw9Bw5zC+aiM9CJ9SfXx6jWQG5yLl6feSfKaximjhgk23f/dSNDjk9w2vHKgil4b/9ZlJzxoLapHRWdhahjZ0UTkwiHsHRVyhm9EgefiYLU0bCnJqCwYBB+MC4LCQ4b/s/BT1DRfEQyI+863ubCTwvnYXTiNXjt+NUoa9mvepJwrLhGdYx7tNVkFmFDtn0a0oalAwCSXXZkDnCjprMIpfxBBLj2Huk7E7lsDE++Bcf9fwMAFCTcibPsE7Qx+bhoZwMwesBk2JJSEeAZfHwyPB0T0elSH29No7yefAoGYBxsKW4wbhR8nUPBHN114QLpsDfeDH/6x3Bc+BEGJ3ebjvxtV4C3b1cptBuuMx/p7kzApX21Au2Xg7nrAJmpwgZH2+VIT3LCYeOQ5HIgyWUHEqagmu0BjzYAHIa4rkbq8IHwBXikJjrRxBXiNDsKHubMWRxsyLRPQ1p+OvLSEnH3VcNw/ZgMHKhNxy+/OCBqpNRIcabg+TnzMTlzMmqb2rFs22co9ZTo3rJTc2bgilFj0e7jMXloGo40OPB2xX508q0hmj8pIWUyYEjyGNx4/VU43dCOeVfk4aaxWfDzfiz89B1MzJiIxwundfmDBLV0FY1OLN70IS60Xwgp32m3LsA2LM3I+fPnMWTIEOzYsQNFRUXi9l/96lfYtm0bdu0KlURdLhfefPNNzJ8/X9z28ssv4+mnn0ZNTU3I8UDsNCMEQRAEQUSPqGhGMjIyYLfbQ4SImpoa5OTkqP4mJycnrOMBwO12w+3W11gQBEEQBNE/CEsn43K5MGXKFGzeLLHV8Tw2b94s05RIKSoqkh0PAJs2bdI8niAIgiCIi4uwo2mWL1+OhQsXYurUqZg2bRqef/55tLS0iNE1P/vZzzBkyBCsWrUKALB06VJMnz4df/rTnzB37lysXbsWe/fuxV//qu8gRRAEQRDExUHYwsjdd9+Nuro6PPnkk6iursbll1+OTz/9VHRSraysFFcqBYBrrrkGb7/9Nn7729/iiSeewJgxY7B+/fq4zzFCEARBEERsCMuB1SrMOsAQBEEQBBE/mH1/00J5BEEQBEFYCgkjBEEQBEFYCgkjBEEQBEFYCgkjBEEQBEFYCgkjBEEQBEFYCgkjBEEQBEFYCgkjBEEQBEFYCgkjBEEQBEFYCgkjBEEQBEFYStjp4K1ASBLb1NRkcU0IgiAIgjCL8N42SvbeJ4QRr9cLABg2bJjFNSEIgiAIIly8Xi/S0tI09/eJtWl4nsf58+cxYMAAcBwXsXKbmpowbNgwnDlzpt+uedPf29jf2wf0/zb29/YB/b+N/b19QP9vY7TaxxiD1+tFXl6ebBFdJX1CM2Kz2TB06NColZ+amtovby4p/b2N/b19QP9vY39vH9D/29jf2wf0/zZGo316GhEBcmAlCIIgCMJSSBghCIIgCMJSLmphxO12Y+XKlXC73VZXJWr09zb29/YB/b+N/b19QP9vY39vH9D/22h1+/qEAytBEARBEP2Xi1ozQhAEQRCE9ZAwQhAEQRCEpZAwQhAEQRCEpZAwQhAEQRCEpVzUwshLL72EESNGICEhAYWFhdi9e7fVVeoRTz31FDiOk/2NGzdO3N/e3o4lS5Zg8ODBSElJwQ9/+EPU1NRYWGNjvvzyS9x6663Iy8sDx3FYv369bD9jDE8++SRyc3ORmJiI4uJinDhxQnbMhQsXsGDBAqSmpiI9PR0///nP0dzcHMNWaGPUvnvvvTekT2fPni07Jp7bt2rVKlx11VUYMGAAsrKyMG/ePJSWlsqOMXNfVlZWYu7cuUhKSkJWVhZWrFgBv98fy6ZoYqaNN954Y0g/PvDAA7Jj4rWNr7zyCiZNmiQmwSoqKsInn3wi7u/r/QcYt7Ev958azz77LDiOw7Jly8RtcdOP7CJl7dq1zOVysTfeeIMdPXqULVq0iKWnp7OamhqrqxY2K1euZJdddhmrqqoS/+rq6sT9DzzwABs2bBjbvHkz27t3L7v66qvZNddcY2GNjdm4cSP7zW9+w95//30GgK1bt062/9lnn2VpaWls/fr17ODBg+y2225jI0eOZG1tbeIxs2fPZpMnT2bffPMN++qrr9jo0aPZ/PnzY9wSdYzat3DhQjZ79mxZn164cEF2TDy3b9asWWz16tXsyJEjrKSkhN18880sPz+fNTc3i8cY3Zd+v59NmDCBFRcXswMHDrCNGzeyjIwM9vjjj1vRpBDMtHH69Ols0aJFsn5sbGwU98dzGz/44AP28ccfs+PHj7PS0lL2xBNPMKfTyY4cOcIY6/v9x5hxG/ty/ynZvXs3GzFiBJs0aRJbunSpuD1e+vGiFUamTZvGlixZIn4PBAIsLy+PrVq1ysJa9YyVK1eyyZMnq+7zeDzM6XSyd999V9z23XffMQBs586dMaph71C+rHmeZzk5OeyPf/yjuM3j8TC3283eeecdxhhj3377LQPA9uzZIx7zySefMI7j2Llz52JWdzNoCSO333675m/6UvsYY6y2tpYBYNu2bWOMmbsvN27cyGw2G6uurhaPeeWVV1hqairr6OiIbQNMoGwjY8GXmXTgV9LX2jhw4ED22muv9cv+ExDayFj/6T+v18vGjBnDNm3aJGtTPPXjRWmm6ezsxL59+1BcXCxus9lsKC4uxs6dOy2sWc85ceIE8vLyUFBQgAULFqCyshIAsG/fPvh8Pllbx40bh/z8/D7b1vLyclRXV8valJaWhsLCQrFNO3fuRHp6OqZOnSoeU1xcDJvNhl27dsW8zj1h69atyMrKwtixY/Hggw+ioaFB3NfX2tfY2AgAGDRoEABz9+XOnTsxceJEZGdni8fMmjULTU1NOHr0aAxrbw5lGwXeeustZGRkYMKECXj88cfR2toq7usrbQwEAli7di1aWlpQVFTUL/tP2UaB/tB/S5Yswdy5c2X9BcTXc9gnFsqLNPX19QgEArKLCwDZ2dk4duyYRbXqOYWFhVizZg3Gjh2LqqoqPP3007j++utx5MgRVFdXw+VyIT09Xfab7OxsVFdXW1PhXiLUW63/hH3V1dXIysqS7Xc4HBg0aFCfaPfs2bNx5513YuTIkSgrK8MTTzyBOXPmYOfOnbDb7X2qfTzPY9myZbj22msxYcIEADB1X1ZXV6v2sbAvnlBrIwDcc889GD58OPLy8nDo0CH8+te/RmlpKd5//30A8d/Gw4cPo6ioCO3t7UhJScG6deswfvx4lJSU9Jv+02oj0Pf7DwDWrl2L/fv3Y8+ePSH74uk5vCiFkf7GnDlzxM+TJk1CYWEhhg8fjn/+859ITEy0sGZET/nJT34ifp44cSImTZqEUaNGYevWrZgxY4aFNQufJUuW4MiRI9i+fbvVVYkaWm1cvHix+HnixInIzc3FjBkzUFZWhlGjRsW6mmEzduxYlJSUoLGxEe+99x4WLlyIbdu2WV2tiKLVxvHjx/f5/jtz5gyWLl2KTZs2ISEhwerq6HJRmmkyMjJgt9tDPIZramqQk5NjUa0iR3p6Oi655BKcPHkSOTk56OzshMfjkR3Tl9sq1Fuv/3JyclBbWyvb7/f7ceHChT7Z7oKCAmRkZODkyZMA+k77Hn74YXz00Uf44osvMHToUHG7mfsyJydHtY+FffGCVhvVKCwsBABZP8ZzG10uF0aPHo0pU6Zg1apVmDx5Ml544YV+1X9abVSjr/Xfvn37UFtbiyuvvBIOhwMOhwPbtm3Dn//8ZzgcDmRnZ8dNP16UwojL5cKUKVOwefNmcRvP89i8ebPMVthXaW5uRllZGXJzczFlyhQ4nU5ZW0tLS1FZWdln2zpy5Ejk5OTI2tTU1IRdu3aJbSoqKoLH48G+ffvEY7Zs2QKe58UBpS9x9uxZNDQ0IDc3F0D8t48xhocffhjr1q3Dli1bMHLkSNl+M/dlUVERDh8+LBO6Nm3ahNTUVFGNbiVGbVSjpKQEAGT9GM9tVMLzPDo6OvpF/2khtFGNvtZ/M2bMwOHDh1FSUiL+TZ06FQsWLBA/x00/RswVto+xdu1a5na72Zo1a9i3337LFi9ezNLT02Uew32FRx55hG3dupWVl5ezr7/+mhUXF7OMjAxWW1vLGAuGbuXn57MtW7awvXv3sqKiIlZUVGRxrfXxer3swIED7MCBAwwAe+6559iBAwfY6dOnGWPB0N709HS2YcMGdujQIXb77berhvZeccUVbNeuXWz79u1szJgxcRP6qtc+r9fLHn30UbZz505WXl7OPv/8c3bllVeyMWPGsPb2drGMeG7fgw8+yNLS0tjWrVtlYZGtra3iMUb3pRBSOHPmTFZSUsI+/fRTlpmZGTdhk0ZtPHnyJHvmmWfY3r17WXl5OduwYQMrKChgN9xwg1hGPLfxscceY9u2bWPl5eXs0KFD7LHHHmMcx7HPPvuMMdb3+48x/Tb29f7TQhkhFC/9eNEKI4wx9uKLL7L8/HzmcrnYtGnT2DfffGN1lXrE3XffzXJzc5nL5WJDhgxhd999Nzt58qS4v62tjT300ENs4MCBLCkpid1xxx2sqqrKwhob88UXXzAAIX8LFy5kjAXDe3/3u9+x7Oxs5na72YwZM1hpaamsjIaGBjZ//nyWkpLCUlNT2X333ce8Xq8FrQlFr32tra1s5syZLDMzkzmdTjZ8+HC2aNGiEEE5ntun1jYAbPXq1eIxZu7LiooKNmfOHJaYmMgyMjLYI488wnw+X4xbo45RGysrK9kNN9zABg0axNxuNxs9ejRbsWKFLE8FY/Hbxvvvv58NHz6cuVwulpmZyWbMmCEKIoz1/f5jTL+Nfb3/tFAKI/HSjxxjjEVOz0IQBEEQBBEeF6XPCEEQBEEQ8QMJIwRBEARBWAoJIwRBEARBWAoJIwRBEARBWAoJIwRBEARBWAoJIwRBEARBWAoJIwRBEARBWAoJIwRBEARBWAoJIwRBWMaNN96IZcuWWV0NgiAshoQRgiAIgiAshdLBEwRhCffeey/efPNN2bby8nKMGDHCmgoRBGEZJIwQBGEJjY2NmDNnDiZMmIBnnnkGAJCZmQm73W5xzQiCiDUOqytAEMTFSVpaGlwuF5KSkpCTk2N1dQiCsBDyGSEIgiAIwlJIGCEIgiAIwlJIGCEIwjJcLhcCgYDV1SAIwmJIGCEIwjJGjBiBXbt2oaKiAvX19eB53uoqEQRhASSMEARhGY8++ijsdjvGjx+PzMxMVFZWWl0lgiAsgEJ7CYIgCIKwFNKMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKSSMEARBEARhKf8fT4SlRz8vR84AAAAASUVORK5CYII=", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "max_t = 400\n", + "\n", + "ppo_2o_UM2_ep[ppo_2o_UM2_ep.t" + ] + }, + "execution_count": 120, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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QQaPVPRYE0d6x2+2wWq1tvRlEiGIwGLyW8hFEe4eEBUEI8DyPoqIiVFVVtfWmECGMRqNBdnY2DAZDW28KQTQJEhYEISCKipSUFERERFADN6LVERsIFhYWIjMzk76DRIeEhAVBgKU/RFGRmJjY1ptDhDDJyckoKCiAzWaDXq9v680hiIChRB5BAJKnIiIioo23hAh1xBSI3W5v4y0hiKZBwoIgFFDomWhr6DtIdHRIWBAEQRAEETRIWBBEB2fChAm4//77PT6elZWF1157rdW2hyCI0IbMmwTRydmyZQsiIyPbejMIgggRSFgQRCcnOTm5rTeBIDo8PM/DZHUg3KBt601p91AqhCA6ATabDffccw9iY2ORlJSE//u//wPP8wDcUyF5eXmYMWMGoqKiEBMTgyuvvBLFxcXS408++SSGDBmCjz/+GJmZmYiKisLdd98Nu92OF198EWlpaUhJScGzzz7rtA2vvvoqBg4ciMjISGRkZODuu+9GXV2d9PipU6cwffp0xMfHIzIyEv3798eSJUsAAJWVlbj22muRnJyM8PBw9OrVC5988kkLfmIEERj//G4PBj31G/LKG9p6U9o9FLEgCBV4nkejtW3K/cL12oArAz799FPccsst2Lx5M7Zu3Yrbb78dmZmZuO2225yWczgckqhYs2YNbDYb5syZg6uuugqrV6+Wljt27BiWLl2KZcuW4dixY5g1axaOHz+O3NxcrFmzBhs3bsTNN9+MyZMnY9SoUQBYx8g33ngD2dnZOH78OO6++2489NBD+O9//wsAmDNnDiwWC9auXYvIyEjs378fUVFRAID/+7//w/79+7F06VIkJSXh6NGjaGxsbManSBDB5eutpwEAH284gScv6d/GW9O+IWFBECo0Wu3o9/hvbfLa+5+eighDYLtmRkYG/vOf/4DjOPTu3Rt79uzBf/7zHzdhsXLlSuzZswcnTpxARkYGAOCzzz5D//79sWXLFowYMQIAEyAff/wxoqOj0a9fP0ycOBGHDh3CkiVLoNFo0Lt3b7zwwgtYtWqVJCyUBtKsrCw888wzuPPOOyVhkZeXh5kzZ2LgwIEAgJycHGn5vLw8DB06FMOHD5eeTxDtEYvd0dab0O6hVAhBdAJGjx7tFOUYM2YMjhw54tZk6cCBA8jIyJBEBQD069cPcXFxOHDggHRfVlYWoqOjpdupqano16+f03Cs1NRUlJSUSLdXrFiBSZMmoWvXroiOjsZ1112H8vJyNDSw0PHcuXPxzDPP4JxzzsETTzyB3bt3S8+966678NVXX2HIkCF46KGHsHHjxiB8KgQRfGwkLHxCEQuCUCFcr8X+p6e22Wu3Na6tpDmOU73P4WAH2ZMnT+Liiy/GXXfdhWeffRYJCQlYv349brnlFlgsFkRERODWW2/F1KlT8euvv+L333/H/Pnz8corr+Dee+/FtGnTcOrUKSxZsgTLly/HpEmTMGfOHLz88sut9p4JwhOiXwkArHbey5IEQBELglCF4zhEGHRt8q8pnRc3bdrkdPuvv/5Cr169oNU6i5S+ffvi9OnTOH36tHTf/v37UVVVhX79+jXtwwKwbds2OBwOvPLKKxg9ejRyc3NRUFDgtlxGRgbuvPNOfP/993jggQfwwQcfSI8lJyfjhhtuwOeff47XXnsN77//fpO3hyCCSYNFjvxZKWLhE4pYEEQnIC8vD/PmzcMdd9yB7du3480338Qrr7zittzkyZMxcOBAXHvttXjttddgs9lw991349xzz5X8DU2hZ8+esFqtePPNNzF9+nRs2LAB7777rtMy999/P6ZNm4bc3FxUVlZi1apV6Nu3LwDg8ccfx1lnnYX+/fvDbDZj8eLF0mME0dbUmW3S76Y2MnV3JChiQRCdgOuvvx6NjY0YOXIk5syZg/vuuw+3336723Icx+Gnn35CfHw8xo8fj8mTJyMnJwdff/11s15/8ODBePXVV/HCCy9gwIABWLhwIebPn++0jN1ux5w5c9C3b19ccMEFyM3NlYydBoMBjzzyCAYNGoTx48dDq9Xiq6++atY2EUSwUAqLygZrG25Jx4DjlcmjVqCmpgaxsbGorq5GTExMa740QXjEZDLhxIkTyM7ORlhYWFtvDhHC0Hex/bHrdBVmvL0BAJCTHIk/HpjQthvURvh7/qaIBUEQBEF4oV4RsaiiiIVPSFgQBEEQhBdqnYSFBQ4HVYZ4g4QFQRAEQXhBGbFw8ECtyeZlaYKEBUEQBEF4QWneBIDKBksbbUnHgIQFQRAEQXiBhEVgkLAgCIIgCC/UuaQ+yMDpHRIWBEEQBOGFeopYBAQJC4IgCILwQq2LsHBNjRDONEtYPP/88+A4zmlcMkEQBEF0JlwjFjYaROaVJguLLVu24L333sOgQYOCuT0EQRAE0a4QIxQaYT6gnfpYeKVJwqKurg7XXnstPvjgA8THxwd7mwiCIJzgOA4//vhjW28GEaLUmdngsbgIAwDA6qAJp95okrCYM2cOLrroIkyePNnnsmazGTU1NU7/CIIgCKKjUGdiVSBx4XoAlArxRcDC4quvvsL27dvdJhd6Yv78+YiNjZX+ZWRkBLyRBEF4ZsKECbj33ntx//33Iz4+Hqmpqfjggw9QX1+Pm266CdHR0ejZsyeWLl0qPWfv3r2YNm0aoqKikJqaiuuuuw5lZWXS48uWLcPYsWMRFxeHxMREXHzxxTh27Jj0+MmTJ8FxHL7//ntMnDgRERERGDx4MP7880+f28vzPJKTk/Htt99K9w0ZMgTp6enS7fXr18NoNKKhoQFZWVkAgMsuuwwcx0m3CaK1EFMhsRGCsKBUiFcCEhanT5/Gfffdh4ULF/o9de+RRx5BdXW19O/06dNN2lCCaFV4HrDUt82/Jgwc/vTTT5GUlITNmzfj3nvvxV133YUrrrgCZ599NrZv347zzz8f1113HRoaGlBVVYXzzjsPQ4cOxdatW7Fs2TIUFxfjyiuvlNZXX1+PefPmYevWrVi5ciU0Gg0uu+wyOFxCwI899hgefPBB7Ny5E7m5ubj66qths3l3zHMch/Hjx2P16tUAgMrKShw4cACNjY04ePAgAGDNmjUYMWIEIiIisGXLFgDAJ598gsLCQuk2QbQWDUIqJFaKWFAqxBu6QBbetm0bSkpKMGzYMOk+u92OtWvX4q233oLZbIZWq3V6jtFohNFoDM7WEkRrYW0AnuvSNq/9aAFgiAzoKYMHD8a//vUvAEzMP//880hKSsJtt90GAHj88cfxzjvvYPfu3VixYgWGDh2K5557Tnr+xx9/jIyMDBw+fBi5ubmYOXOm0/o//vhjJCcnY//+/RgwYIB0/4MPPoiLLroIAPDUU0+hf//+OHr0KPr06eN1eydMmID33nsPALB27VoMHToUaWlpWL16Nfr06YPVq1fj3HPPBQAkJycDAOLi4pCWlhbQ50IQwcBsY0Ii0shOmWTe9E5AEYtJkyZhz5492Llzp/Rv+PDhuPbaa7Fz5043UUEQROugrM7SarVITEzEwIEDpftSU1MBACUlJdi1axdWrVqFqKgo6Z8oBMR0x5EjR3D11VcjJycHMTExUvohLy/P4+uKqYySkhKf23vuuedi//79KC0txZo1azBhwgRMmDABq1evhtVqxcaNGzFhwoTAPwiCCDI8z8MiRCgiDewcZyWPhVcCilhER0c7Xa0AQGRkJBITE93uJ4gOjT6CRQ7a6rUDfYpe73Sb4zin+ziO1ck5HA7U1dVh+vTpeOGFF9zWI4qD6dOno3v37vjggw/QpUsXOBwODBgwABaLc8dBT6/hi4EDByIhIQFr1qzBmjVr8OyzzyItLQ0vvPACtmzZAqvVirPPPtvPd08QLYcYrQCACIMYsaBUiDcCEhYEETJwXMDpiI7CsGHD8N133yErKws6nfshoLy8HIcOHcIHH3yAcePGAWBmymDCcRzGjRuHn376Cfv27cPYsWMREREBs9mM9957D8OHD0dkpPz56/V62O32oG4DQfiDUlhECakQK6VCvNLslt6rV6/Ga6+9FoRNIQiiNZgzZw4qKipw9dVXY8uWLTh27Bh+++033HTTTbDb7YiPj0diYiLef/99HD16FH/88QfmzZsX9O2YMGECvvzySwwZMgRRUVHQaDQYP348Fi5cKPkrRLKysrBy5UoUFRWhsrIy6NtCEJ6wKIRFuJAKsVMqxCs0K4QgQowuXbpgw4YNsNvtOP/88zFw4EDcf//9iIuLg0ajgUajwVdffYVt27ZhwIAB+Pvf/46XXnop6Ntx7rnnwm63O3kpJkyY4HYfALzyyitYvnw5MjIyMHTo0KBvC0F4wmxjkTKjTgOd0HqTGmR5h+P5JtS2NYOamhrExsaiuroaMTExrfnSBOERk8mEEydOIDs72+9SaoJoCei72L44VlqHSa+sQUyYDnMn9cIzvx7AjCFd8Prs0BO4/p6/KWJBEARBEB4QUyEGnRZ6LTtlUudN75CwIAgi6IhdPdX+KftnEER7RzRvGnUaaIVUiI1SIV6hqhCCIILOhx9+iMbGRtXHEhISWnlrCKLpmK2Cx0KvgV4rCAuKWHiFhAVBEEGna9eubb0JBBEUxOZYRp0WWo2QCqFyU69QKoQgCIIgPGC2ih4LRcSCUiFeIWFBEARBEB5Q9VhQKsQrJCwIgiAIwgMWu7KPBaVC/IGEBUEQBEF4QEyFKBtkkbDwTsgLi+pGK857eTUe/2lvW28KQRAE0c6QUyFa6KSqEPJYeCPkhcVH647jeFk9PvvzVFtvCkE0CZ7ncfvttyMhIQEcxyEuLg7333+/X8+dMGGCz2U5jsOPP/7Y7O30lyeffBJDhgxptddrDq392RCtj3NLb2qQ5Q8hX266J7+6rTeBIJrFsmXLsGDBAqxevRo5OTnQaDQIDw8P2voLCwsRHx8ftPX54sEHH8S9994b0HOysrJw//33+y2ogoXyszl58iSys7OxY8eODiOMCN/InTc1csSCqkK8EvLC4mBRbVtvAkE0i2PHjiE9PR1nn312i6w/LS2tRdbrCbFDZ0egtT8bovVRVoWQx8I/QjoVwvM8CqtNbb0ZBNFkbrzxRtx7773Iy8sDx3HIyspyS2/897//Ra9evRAWFobU1FTMmjXLaR0OhwMPPfQQEhISkJaWhieffNLpcWW4/+TJk+A4Dt9//z0mTpyIiIgIDB48GH/++afTcz744ANkZGQgIiICl112GV599VXExcX59Z5cUyE33ngjLr30Urz88stIT09HYmIi5syZA6vVCoClc06dOoW///3v4DgOHMdJz12/fj3GjRuH8PBwZGRkYO7cuaivr5cez8rKwnPPPYebb74Z0dHRyMzMxPvvvy89brFYcM899yA9PR1hYWHo3r075s+fr/rZZGdnAwCGDh0KjuMwYcIErF27Fnq9HkVFRU7v8f7778e4ceP8+jyItkUSFnotdDQrxC9CWlicrpBbDiuORQQBnufRYG1ok3+BDBx+/fXX8fTTT6Nbt24oLCzEli1bnB7funUr5s6di6effhqHDh3CsmXLMH78eKdlPv30U0RGRmLTpk148cUX8fTTT2P58uVeX/exxx7Dgw8+iJ07dyI3NxdXX301bDYbAGDDhg248847cd9992Hnzp2YMmUKnn32Wb/fkxqrVq3CsWPHsGrVKnz66adYsGABFixYAAD4/vvv0a1bNzz99NMoLCxEYWEhABbJueCCCzBz5kzs3r0bX3/9NdavX4977rnHad2vvPIKhg8fjh07duDuu+/GXXfdhUOHDgEA3njjDfz888/45ptvcOjQISxcuBBZWVmq27h582YAwIoVK1BYWIjvv/8e48ePR05ODv73v/9Jy1mtVixcuBA333xzsz4TonWQUiFaZcSCUiHeCOlUyP5C8lcQ6jTaGjHqi1Ft8tqbrtmECH2EX8vGxsYiOjoaWq1WNSyfl5eHyMhIXHzxxYiOjkb37t0xdKjzuOdBgwbhiSeeAAD06tULb731FlauXIkpU6Z4fN0HH3wQF110EQDgqaeeQv/+/XH06FH06dMHb775JqZNm4YHH3wQAJCbm4uNGzdi8eLFfr0nNeLj4/HWW29Bq9WiT58+uOiii7By5UrcdtttSEhIgFarRXR0tNNnMH/+fFx77bVS9KZXr1544403cO655+Kdd96RRpJfeOGFuPvuuwEADz/8MP7zn/9g1apV6N27N/Ly8tCrVy+MHTsWHMehe/fuHrcxOTkZAJCYmOi0Hbfccgs++eQT/OMf/wAA/PLLLzCZTLjyyiub/HkQrYeTeVPwWNgpFeKVkI5YVNRbpd95nr4sROdjypQp6N69O3JycnDddddh4cKFaGhocFpm0KBBTrfT09NRUlLidb3K56SnpwOA9JxDhw5h5MiRTsu73g6U/v37Q6vVBrSNu3btwoIFC5wmq06dOhUOhwMnTpxQfS8cxyEtLU1a94033oidO3eid+/emDt3Ln7//feAt/3GG2/E0aNH8ddffwEAFixYgCuvvBKRkZEBr4tofaQ+Fnq5KsRKqRCvhHTEosZkdbpttTug1Wg9LE2EEuG6cGy6ZlObvXawiI6Oxvbt27F69Wr8/vvvePzxx/Hkk09iy5YtkudBr9c7PYfjODh8hHqVzxE9Db6e0xyaso11dXW44447MHfuXLfHMjMz/Vr3sGHDcOLECSxduhQrVqzAlVdeicmTJ+Pbb7/1e9tTUlIwffp0fPLJJ8jOzsbSpUuxevVqv59PtC1mu3sqhC5CvRPSwqK60V1YhOlJWBDs5OJvOqK9o9PpMHnyZEyePBlPPPEE4uLi8Mcff+Dyyy9vkdfr3bu3m9fD9XawMRgMsAutl0WGDRuG/fv3o2fPns1ad0xMDK666ipcddVVmDVrFi644AJUVFS4jX83GAwA4LYdAHDrrbfi6quvRrdu3dCjRw+cc845zdomovWQIxZygywrNcjySkgLixo3YUEqlOhcLF68GMePH8f48eMRHx+PJUuWwOFwoHfv3i32mvfeey/Gjx+PV199FdOnT8cff/yBpUuXOlVrBJusrCysXbsWs2fPhtFoRFJSEh5++GGMHj0a99xzD2699VZERkZi//79WL58Od566y2/1vvqq68iPT0dQ4cOhUajwaJFi5CWlqZa4ZKSkoLw8HAsW7YM3bp1Q1hYGGJjYwEAU6dORUxMDJ555hk8/fTTwXzrRAuj1iCLIhbeCWmPRY3J5nSb2rQSnY24uDh8//33OO+889C3b1+8++67+PLLL9G/f/8We81zzjkH7777Ll599VUMHjwYy5Ytw9///nfJLNkSPP300zh58iR69OghmSgHDRqENWvW4PDhwxg3bhyGDh2Kxx9/HF26dPF7vdHR0XjxxRcxfPhwjBgxAidPnsSSJUug0bgfOnU6Hd544w2899576NKlC2bMmCE9ptFocOONN8Jut+P6669v/hsmWg2LWktvBx9Q9VaowfGt/OnU1NQgNjYW1dXViImJac2XduP6jzdj7eFS6fb6hyeiW3znCH8TgWEymXDixAlkZ2e36AkwVLnttttw8OBBrFu3rq03pc245ZZbUFpaip9//tnrcvRdbF9c+vYG7DxdhQ+uH44RWfEY8jQrxT767DSpr0Wo4O/5m1IhCqjpCUEEh5dffhlTpkxBZGQkli5dik8//RT//e9/23qz2oTq6mrs2bMHX3zxhU9RQbQ/nDpvKoSEzcFDR5Y8VUJbWKhUhRAE0Xw2b96MF198EbW1tcjJycEbb7yBW2+9FQArHT11Sn3o33vvvYdrr722NTe1xZkxYwY2b96MO++802tvEKJ9YnHyWMg+IWrr7ZnQFhaNzh4LMm8SRHD45ptvPD62ZMkSqR23K6mpqS21SW0GlZZ2bMzKIWRKYUEXoh4JWWHB87yUCuE41iCLIhYE0fJ4615JEO0Ns8K8qaWIhV+ElvNEgdnmgEUQEomRRgDU/50gCIJwRqoK0WvAcZw8L4Qi3B4JWWEhRis0HBAbzgI3Fht9UUKdluweSRD+QGWM7Quxj4VBMG5qaRCZT0I2FSJ23YwJ10MvjsKlL0rIYjAYoNFoUFBQgOTkZBgMhhZt6EQQavA8j9LSUnAc59ZqnGh9eJ5XjE1n5wm9VgOzzUERCy+ErLAQK0Jiw/Uw6MTBMiQsQhWNRoPs7GwUFhaioKCgrTeHCGE4jkO3bt2chq4RbQNrhMV+Nwq1pRSx8E3oCguhIiQmTC/lzKgqJLQxGAzIzMyEzWZTnfdAEK2BXq8nUdFOEKMVACs3BQC9ovsmoU7oCguTmArRSSEtilgQYgiawtAEQVgUwkLv6rGgC1GPhKx5U/RYxCo9FvRFIQiCIATEXhVaDScJCnEQGUUsPBOywqJWGEAWZdRJoS0LRSwIgiAIAfGcoGyMJQ0io/OFR0JWWJisLIceYdBJ/d8pYkEQBEGIiL47g2JGiNTHgiIWHglZYdFoEfq/6zXSl4Y8FgRBEISIGJXQ65TCgi5EfRGywsIkND0J12ul0BYJC4IgCELEayqEyk09ErLCotHCvhRheq1k3qRyU4IgCEJEPCfo1VIhdL7wSMgKC2XEQk9mHIIgCMIFMYptUKZCtFQV4ovQFRaCxyJMr1FELEhYEARBEAyrWiqEOm/6JHSFhU0UFlrJjGMlBUoQBEEIqKZChAi3nc4XHglZYdFokYWFXieYN22kQAmCIAiGeE5QqwohT55nQlZYmKwK8yZ1UiMIgiBcENMdepVUiJ1SIR4JYWGhNG+yj4E6bxIEQRAiFi+pEIpYeCbkhUWYXkMtWgmCIAg3vKVCyGPhmZAVFo2KiIWB+lgQBEEQLqimQqihok9CVlgoPRb0RSEIgiBcUUuFaDVUFeKLkBQWPM9LEQvnzpskLAiCIAiGWiqEzP6+CUlhYVaUlbIGWdSilSAIgnBGLRWipQi3T0JSWIjGTcA5YkFVIQRBEISIWoMsPaVCfBKiwkJu06rXauTe7xSxIAiCIAQsUipEEbGgBlk+CUlhoawIAQADhbYIgiAIF8RUiFhiCkBKnVODLM+EpLAQUyFGQVjQrBCCIAjCFTEqoZxuKlaFUMTCMyEpLKSIhYG9fdHxS7NCCIIgCBEpFaJV9rGgBlm+CElhIXXd1LGIhZ7G4BIEQRAuqKVCaGy6b0JaWIQbBGGhIzMOQRAE4YzV5p4K0VF7Ap+EqLAQum7qRI8FmTcJgiAIZ8RzglMqRIpYkLDwREgKi0aLkAoRIxbUeZMgCIJwQTT0O6dCqPOmL0JSWJhsosdCMG9SHwuCIAjCBdXppjQN2ychKSzEiIXksRC+KNR5kyAIghARo9gGp1QIRSx8EZLCQpwVIlWFUMSCIAiCcEG82FStCqELUY+EpLCQPBZ651QIeSwIgiAIEfFiUzUVQhELj4SksJD6WAipEOUXhefpy0IQBEGop0K0Gio39UVICotG1wZZisl11MuCIAiCAGRh4TwrhDpv+iIkhYXYptUopUJkNUrd1AiCIAhAMTZd5+6xsNK5wiOhKSyk8JazxwKQO60RBEEQoY1qgyxpuimdKzwRmsJCjFgIKlRUoACpUIIgCIIhCwv3BlmUNvdMQMLinXfewaBBgxATE4OYmBiMGTMGS5cubaltazFcvywcx0mKlCpDCIIgCECRCtFSuWkgBCQsunXrhueffx7btm3D1q1bcd5552HGjBnYt29fS21fiyD2sXAaLKOhXhYEQRCEjHoqhMybvtAFsvD06dOdbj/77LN455138Ndff6F///5B3bCWxKIiLPRaDo1W6r5JEARBMNRSIVoyb/okIGGhxG63Y9GiRaivr8eYMWM8Lmc2m2E2m6XbNTU1TX3JoGFR+bJQ902CIAhCiU0lFSJGL+x0rvBIwObNPXv2ICoqCkajEXfeeSd++OEH9OvXz+Py8+fPR2xsrPQvIyOjWRscDKSmJzp3YUEeC4IgCAJQXoS6N8iyUirEIwELi969e2Pnzp3YtGkT7rrrLtxwww3Yv3+/x+UfeeQRVFdXS/9Onz7drA0OBlJViNKQQ+ZNgiAIQoFaKoQaZPkm4FSIwWBAz549AQBnnXUWtmzZgtdffx3vvfee6vJGoxFGo7F5WxlkLCqjcA1aKiEiCIIgGHYHD1E7qHos6CLUI83uY+FwOJw8FB0BUTwYVCIWVEJEEARBKIWDMhWi11DEwhcBRSweeeQRTJs2DZmZmaitrcUXX3yB1atX47fffmup7WsR1MpNRUVKVSEEQRCEs7BQRCy0NITMFwEJi5KSElx//fUoLCxEbGwsBg0ahN9++w1Tpkxpqe1rESw2NoTMqekJVYUQBEEQAspzgZPHQmyQReWmHglIWHz00UcttR2tipgKMTp5LChvRhAEQTDEc4GGk30VgPy7gwccDh4axWMEIzRnhaiUm0r93ylvRhAEEfKI5wmd1vk0qbxto/OFKiEnLOwOXjLdKM2bYoWI1UYRC4IgiFBHzeQPOA+tpHSIOiEnLCwK4aAsN6W8GUEQBCFiU2mOBcgVhABFLDwResJC4aEwqDQ9sZB5kyAIIuTxmArRKFIhdL5QJfSEhU29Npn6WBAEQRAi0sh0F3OmVsOBE+6iCLc6oScsROOmVgOOk78wBpoVQhAEQQhIqRCd+2lS9FlQxEKdkBMWVpXmWIByVgh9UQiCIEId8VygUykn1VH3Ta+EnLBQKzUFaLopQRAEISOmOfRazxELOl+oE3rCwqbu9NVT502CIAhCQDwX6LQqEQvRk0cRC1VCTliozQkBSIESBEEQMuK5QFkFIqLV0IWoN0JOWFgV5k0lUoMs+qIQBEGEPGI0wjW6rbyPqkLUCTlhYZEiFlqn+/UUsSAIgiAEvEUsKBXindAVFp48FqRACYIgQh6vHgtKhXgl5ISF1UNViNhdzWKjLwpBEESo409VCF2IqhNywsJzuSl9UQiCIAiG1HlTJWKhpQZZXgk5YWG2qatQ6mNBEARBiFg9zAoB5PMFNchSJ+SEhceqEC1VhRAEQRAMm4dZIYAcsaALUXVCTlhYfLb0pi8KQRBEqGN1eItYsPMFRSzUCV1h4fJlMVDnTYIgCELA5ofHwkrCQpXQFRYeIhYWilgQBEGEPDYvfSxkjwWdL9QIOWHhqdyUzJsEQRCEiBiNUOtjIXssKGKhRsgJC7PdU1UIlQ8RBEEQDJuHcwVAY9N9EXLCwlMqhCIWBEEQhIgYjdCpVIVIDbLofKFKyAkLT+WmogIlYUEQBEF47bxJs0K8EnLCwlPEwqCjnBlBEATB8FYVoqPOm14JXWHhIWJBoS2CIAjC4qXzpk4aWknCQo3QExY+qkIspEAJgiBCHht5LJpM6AkLYXopDSEjCIIgPOGPx4IaZKkTesLCY7mpYN60kbAgCIIIdaSqEFWPBTXI8kboCQubHYCXWSGkQAmCIEIeqY+FSudNMm96J+SEhahCPc0KoXJTgiAIwuat8yaVm3ol5ISFXG7q/GURXb48T93UCIIgQh2rl6oQPVUReiV0hYVW63S/slaZohYEQRChjU2KbnueFUIRC3VCT1j4KDcFSFgQBEGEOtIQMtXppuSx8EboCQsfs0IA6r5JEAQR6khj01UjFtQgyxuhJyykclPnL4tWw4ET7qK8GUEQRGgjt/T2ErGgclNVQk9YCBELo07tyyJ236QvC0EQRCgjmTe9dd6kiIUqIScs5OmmWrfH9BoaREYQBEEAVofnqhCtlqpCvBFywkKMWOh17ipUr6MvC0EQBOF9uqmeGmR5JaSEhcPBS6Er1wZZgKKtN31ZCIIgQhqppbda503xXEGpEFVCSlgovROuVSGAMhVCEQuCIIhQRh5C5tljQbNC1AlZYaHq9NVRW2+CIAjCe1WINFuKotuqhJawUEwupVQIQRAE4Qmrlz4WOmrp7ZWQFBZ6LQeNSgmRngaREQRBEJBLSb33saCLUDVCSljIpabqb1uvJY8FQRBEqMPzvDSMUrWPBUW3vRJSwkIuNfUkLOjLQhAEEeoozwHq002Da95stNg7VVolpISF2UYRC4IgCMI7ylbdalUh2iD2scgrb8Do+Stx04ItzV5XeyGkhIXVw2RTEfJYEARBEFabImLhtY9F888Vb/xxBNWNVqw7UobDxbXNXl97IKSEhcVnxEJ0+lIqhCAIIlSx+ohYBGtsekmNCT/vLJBuf789v1nray+ElrDwGbHgnJYjCIIgQg9RMLCp157LTZvrx1t3pMzpfPPTznzwfMe/sA0tYWHzLix0lAohCIIIecRzgFq0Qnl/c82beRUNAICLBqYDAAqrTZIXsCMTUsJC/rKov20DpUIIgiBCHqmHhYq/AgieefN0JRMWvdOipfsaLPZmrbM9EFLCwt+qEEqFEARBhC42L103AYXRv5kRizMVjQCA7okRUiS9wWJr1jrbAyElLCgVQhAEQfhCmmzq4SJUFyTzppgKyUyIQIRBC4D1tOjohJSwsHoZKgNQKoQgCIJQTDZV6boJKGaFOPgmmy3NNjuKa00AgIyECETombCgVEgHw2JjfzCjj6oQilgQBEGELr4iFkpTp72J80LyKxvB80C4XovESAMijDoAJCw6HL7KTcUvEXksCIIgQhdfHgutIpLR1EFkpyuZvyIjIRwcx8mpECt5LDoUogqlBlkEQRCEJ6S0uYeqEGU6vakR7tOCvyIjPgIAi1wAFLHocJilIWTqKtRAqRCCIIiQR6z28BSxUE48beqFaEmtGQCQFhsGAFLEgoRFB0Nu6a1VfVxPqRCCIIiQx+bD6B+MVEhlvQUAkBBpAABEGJjHgqpCOhj+lptSKoQgCCJ0sfnovMlxnDwvpIm9LCoamLCIj2DCIpwiFh0Tabqphy8LpUIIgiAIq8N7xAJofvdN94iFKCzIvNmh8BWxoLHpBEEQhNUmeiw8nyL1muadLyobrACA+EiKWHRo/C03be7EOoIgCKLjIqY3PEW3AUX3zeZ6LIRUSISe+lh0SCw+hpBRgyyCIAjC4sO8CTTPk8fzvOyxiNQDgKKlN6VCOhS+UiEGSoUQBEGEPP6lQppu3myw2KXzUQKlQjo2Fh/TTSkVQhAEQVh9VIUAzTtfVAhpEINOIzXGkjtvkrDoUPg2b1IqhCAIItQRfROeLkIBuUmWrQnniyrBuJkQYQDHsfWEbIOs+fPnY8SIEYiOjkZKSgouvfRSHDp0qKW2LejI5aaUCiEIgiDUES9CvXssmm7elP0VBum+cEOImjfXrFmDOXPm4K+//sLy5cthtVpx/vnno76+vqW2L6j4WxVCDbIIgiBCF6uPIWSA8+j0QJF7WOil+zqTeVMXyMLLli1zur1gwQKkpKRg27ZtGD9+fFA3rCXwNxVCLb0JgiBCF1/RbUA+XzQlFSJ6LMSum0DnGkIWkLBwpbq6GgCQkJDgcRmz2Qyz2Szdrqmpac5LNgvf5aaUCiEIggh1rAGUmzbFvFnZ4Nx1E1BGLDq+sGiyedPhcOD+++/HOeecgwEDBnhcbv78+YiNjZX+ZWRkNPUlm43PclMdpUIIgiBCHX9SIdpmlJuKEYu4CKWwEDwWVjt4vmOfg5osLObMmYO9e/fiq6++8rrcI488gurqaunf6dOnm/qSzUYcm2705LHQUCqEIAgi1LH6iG6zx5o+K6TGxHwUseGyx0LsY2F38B3+HNSkVMg999yDxYsXY+3atejWrZvXZY1GI4xGY5M2LthYfAgLSoUQBEEQoljwXm7adPNmTSMrN40Jk0/BYioEYOkQo07r9ryOQkARC57ncc899+CHH37AH3/8gezs7JbarhbBbGO5K09/MEqFEARBEBY/GmQ1x7xZYxKEhSJioddqJCHT0Q2cAUUs5syZgy+++AI//fQToqOjUVRUBACIjY1FeHh4i2xgMPHlsZAanjh4OBw8NBrPXyqCIAiicyJ7LHxHLKzNiljone436jWw2B0wdfDumwFFLN555x1UV1djwoQJSE9Pl/59/fXXLbV9QcNmd0D8+3sKb+kVgsPaBEMOQRAE0fGx+pEK0TYrYuHusQDki1tHBzdvBhSx6MhOVdG4CTBVqIbyS2Sz8zA2qxiXIAiC6IhI5k2dl1SIphnmTTFiEe58ktE2w7fRngiZWSEWhbDwOIRMkfogAydBEERoIqVCNH6MTQ9QBJisdulCN8ZDxKKj+/xCRliIf0ithvOYN9NqOAjzYDp8uQ9BEATRNPxpkNVU82atkAbhOCDK4BqxaPr8kfZEyAgLXyPTAYDjOOmL1NEVI0EQBNE0bNJcKd+zQgI1b4oVIdFGnVuBgNiQy97BPX6hIyzsQqmpB3+FiJg3o1QIQRBEaGLxI2KhbeLYdNlfoXd7jFIhHQyT1XfEApArQ0hYEARBhCb+eCz0UnQh0IgFS4W4lpoqXy/QdbY3QkZYiJ4JnxGLZgyWIQiCIDo+Vn9SIU08V3iqCAHIY9HhMPsbsaBUCEEQREhj88e82cQhZFLXTbWIRROjIO2NkBEWFkmBeu+/TqkQgiCI0MYSQLlp4BELIRWi4rHQdpIL25ARFmarOCeEUiEEQRCEZ/xLhTTNvFntoZ03IJs3KWLRQZAjFt7fsq6TKEaCIAiiafiTCmmqCJAHkJHHosPja2S6iLaTKEaCIAiiacjTTYM/hMzTADLlOjv6+SdkhIU5QGHR0YfAEARBEIHD87xiumnwx6ZL5aZqfSy0FLHoUMgRC+/mTQ0nRixafJMIgiCIdobdwYP3MQkbCEK5aZh7KkROr3TsE1DICAuzjZk3/fVYdPRQFEEQBBE4ymiBPx6LJpebeqkKoYhFB8Ffj4WGhAVBEETIohxA6S0V0tSeE1K5qRePBbX07iBIQ8h8eSzEVAh5LAiCIEIOq00WFnpvfSw0Tet5RFUhnQizH9NNAYV5s4P/YQmCIIjAEU/qOg3nNn1UiWze9P9cYbLapYvcWC9DyMhj0UGQqkJ8zAqhVAhBEEToIp74vfkrgKaVm4rRCg0HRBooYtHhkSMW3qtCyLxJEAQRuvhTagoA2iaUm4r+iugwvWo0RPJtkMeiY2DxN2JBHguCIIiQRSwf9ZU2b8pFqDd/BVunYN7s4Be2ISMspHJTnx4L9pMiFgRBEKGH1Y+um4Bs9A+kmaK3rptA5+n8HDLCwt+IBXXeJAiCCF38TYU0xY8ndd30ICx05LHoWEhDyHyoULnzZsf+wxIEQRCBE2gqJJBThRSx8JAKaYpvoz2i/u46IWZrYNNNSVgQBEG0L8rrzLjr8+2oaLBg9ogM3DouJ+ivYfMzFaJpQudNyWNBEYvOgRix8DkrhIQFQRBEu+TXPYXYfLICR0vq8P7a4y3yGtJkU52PqhDRYxFAcEHquqnSwwIAtDTdtGMhmjd9TjelqhCCIIh2ydaTldLvZlvLpAvEVIjOS9dNoGlGS4pYdDL8nRVCnTcJgiDaJ9tOycIi0Fba/mL1048nCYsALkKrfXksgtB502S1N/m5wSJkhIXZz1khciqkxTeJ6ADUm21Ye7hUEqYEQbQNhdWNyK9qlG63tLDwmQppSsTCR7mp1Ca8GRe213+8GTd9shnHS+uavI7mEjLmTTli4W/nTTqRhDqF1Y2Y/uZ6lNVZ8OxlA3DtqO5tvUkEEbKI0Yr02DAUVptgtfPgeR4c510ABIq/qZCmVBBK5aYt5LHYdqoSm09UQK/lEGlsu9N7yEQs/J1uSp03CZGnft6PsjoLAOBUeUMbbw1BhDZHitkV+NDMOOk+awu0vva7QVYT0uZyxMJT583AB5speW/NMQDAZUO7IjUmrEnrCAYhIyzMAXosKBUS2vA8jy0nK6TbjZa2z1sSRChTXGMCAGQmREr3tUQ6RCw3NfhIheia4LGoqGcXKgmRBtXHtU0oYRUprTVj+YFiAMDt43sE/PxgEjLCwt+IBXXeJACgsNqEcuEgAAB1Zlsbbg1BEIXVTFhkJIRL97WEsLAI0QL/+1j4d66w2h2SedOTsGhOH6UjJbXgeSA7KRI9U6ICfn4wCQlhYXfwUm1ymN5HHwvqvEkA2JNf7XSbhAVBtC1ixKJrXDhEW4WlJYSFcBHqs9yUCywVUtnALlQ4DoiL8BWxCPz8c6KsHgATFm1NSAiLeot8Uog00th0wjf7BGERJsyWqTORsCCItkSMWKTHhkvRhJao1hJ7HoX5OVfK31SImAaJjzBIz3VFGpveFGFRyoRFViIJi1ahXrja1Gk437NCSFgQkCMWo3MSATiLU4IgWpdGi11KI6TFhsEoHMdbwrxpsvoX3RbFAc/7F7WoqPPur2DrFMamN+F9nSwXIhbJJCxahXozU6CRRp3P0iTqvEkAwGHBgT4iKwEARSwIoi0pEtIg4XotYsJ00OtEYRH8iIXYYMpnxEJxLvHnfFHuw7gJAPpmXNgeF1IhOZQKaR3EiEWkwbsCBQAxoEGdN0MXnudRUssOZLmp0QDIY0EQbUmRkAZJiw0Dx3FSI6mWSYX4O1dK/t0fISCmQhK9RizY+7IGWBViszuQJ5TEZ5GwaB0kYeFHwxBKhRCVDVYpxJqdFAGAhAVBtCWicTNN6M2g17ZcxMLsZ8RCae70p4pQjFjEexEWTfVY5Fc1wubgYdRpkN6G/StEOpWw4HnWic2VeqEHQYQfwoLMm4R4EEuINCBecG83WOz0nSCINqJQEbEA5DkeLeKxkMyb/kcs/KniqKg3A/AVsWiax+J0BWt1npkQIV0ctyWdRlhMfHk1ev9rmWqHRDFiEeWjIgSgzpuELCxSoo1OUS4ycBJE2yDuk6mtErHws5miwmPhl3nTD49FUy9sywXRkhxtDOh5LUWnERYWmwMWu0OqFVYinhAiDb4jFk0ZLEN0Lkpq2E6aGhMGo04j5XPrKR1CEG2CeFwXr/bFAWEt4bHwN2KhLBn153xR7ldVSNM6b5b5se7WpNMIi7gINtSlqsHq9lggHgvqvEnIV0dGcJw8zIcqQwiibRCP67HCcV5MhbREgyyT1T/zJsdxELWFPxFuWRx5jio0NWIhplmSoihiEVTEXHhVo0rEQio3DSAVQhGLkKW41jnsGiUKC4pYEESbUCX0sIgTpoK2aCpEiFgYfZg3gcAi3P6kQpraeVOMhnjzb7QmnUZYiBGLynovEQs/UiFk3iTEVEgKCQuCaBdUC1f7YitsQ4v2sRAaZPmIWAD+X4ja7A5JWCRFefNYNM28KaVCvKy7Nel0wqLKm8eCyk0JPyiuFYSFYIQShQV5LAiibZAiFhEuEQtbS3Te9K/cFFCOTve+XEmtGQ6eXbgmeklXiOWmgUYs5IoTSoUEFTkVohaxEMpN/WmQJVWFBHHjiA5FiYsDXRSkteSxIIhWx+HgpXbesrAQzJstkgrxz2MB+D8vpLCalYOmxoR5nBMCKCPmgb2vcj+iIa1JpxEWYois0ot5MyoQ8yZFLEISnudR6hqxCKOIBUG0FbUmG8TzdmwreCyaErHwJQTEPhxd4rw3r2qux4KqQoKMaOqhVAjRHOrMNmmnFnfSKAN5LAiirRAN+REGrRRFMLRCHwtf5aaAIsLtYzMKq+TJrN4QPRaBnH9MVrt0bPKWZmlNOo2wiI/0Vm7qf1UImTdDG/H7Y9BppAOLGLGoE75HBEG0HuI+KV48ArJ5M9h9LBwOXkqv+GqQBfhfFVIgpELSfUUsmuCxEE2hei2HmDDfF8+tQacRFnIqpHkNsqjzZmhT3eh+EJP6WJjdRStBEC2L6JuLjZDD/Hqpj0Vwj9NmhVDxK2Lhp7AQIxZdfEYsAr+wVaZBfE3vbi06j7AID26DLIpYhCY14kFMISxE02+DhSIWBNHaiOltpdhvKY+F2MMC8C9i4e+FqGjeFGedeEJ5/lGbe6VGeTurCAE6kbAQq0LqzDa3L5ucCvFHWLCf1HkzNKlSERZiPjfQ2nKCIJpPjUtFCCC39LYGORUi9rDQaTjotMFMhQQWsQD8T4dIzbHaSUUI0ImERUy4HmIUSBm14HlekQqhzpuEd1zL2gBA30L5XIIgfCN5LCLcxX6wIxZyRYjvcwUgCwFvF6IWmwNldSyq4MtjoRQz/p6DqlUuhtqaTiMstBoOMWHulSGNVrtUquRPxKIprlyi8yDupDFOEQvh6qgFHOgEQXhHjiK2nsfCn1JTQK4i9BbNLK4xgeeZ4dRXy+2mRCzE/jrRYSQsWoR4QdG+s+YYtp2qhMPBS2kQjgPC/VChgq4gYRGiSMOOVPK5LdGMhyAI76hGLFqopbcYsfCnORYgl5t6i1gUVAkVIbFhPs2VThNT/RRNtSbhYqidVIQAQPvZkiCQHG3EyfIGfL89H99vz8eo7ATcMjYbABvOovHS8UxES1UhIY1cFeJ+dUQRC4JofaqFPhZqYr/FhEWAEQtvF6Jic6x0H8ZNQD7/AP6PTpcjFu3ndN5+tiQI/GNqH3z+1ynUmKzYdLwCm06wfwDQv0usX+ugzpuhjVwVIu8a8tURfScIorWpEU6cMWHu6clg+56kVIifEQudHy29xR4WvoybABMqGg5w8P5HzWtM7unbtqZTCYuR2QkYmZ0AANhysgJXvPun9NiArjF+rUPjZ+93onMidvmLU9TMi0YxMm8SROtTJwiLKMUVebuLWHi56JC6bvowboroNBpY7I4meCzaz+m8U3kslJyVGS95LgD/IxY6P74oROdFzWFNqRCCaDvqVGY9tZR50xRgxEIInHi9EBV7WPhq5y2t0w9DqBLRYxFtbD8Ri04rLDQaDsOzEqTbA/wUFtR5M7RRqwppyUmKBEF4RxQWyitysQQ82H0szAEMIAP8S50XVPk3gExEJw0i8++9SamidpQK6bTCAgByU6Ok3zMSAlOLdA4JTVrTgU4QhG+kVIgiYtFSJeCmAEamA/6NTS+q8W8AmYhOG1gvJSli0Y5SIe1nS1qAW8fmYO3hMkzsk+J3D3WtHw1PiM6J3cFL+UrVclPyWBBEq2K22aVIofLE2VJiv6kRC08iwGS1S0PC/DFvsnUKnX79Nm+2P49F+9mSFiA+0oBf7h0b0HOo82boIlaEAC4tvakqhCDaBFHoA85DJFu+QZZ/EQtf5wux1DTCoEVMuH+n20AGkZmsdumChxpktWNobHroIh7EIgxa6cAFKMybFLEgiFZFmQZR9iGSo4jBHQwoN8jy79To63xRJAiLND+aY4lI5k0/zkHiMYvjgGg/Oku3FiQsXKDppqFLjYdcpRixIPMmQbQuahUhgLJSK8hVIQHOCvGVOhfTIEkBTB6VPRa+jzeivyLKoPOrAWRrQcLCBepjEbp4PojJVSH+jjImCKL51Kr0sABacgiZYN4MMBXiKbpQIYw0j4/0P00hihV/RFN77GEBkLBwQ+r9ThGLkENuxON8EBAPYnwA3fAIgmg+HsW+rmWqQmoCnLvhq9y0XIhYJAQSsQggal7bDktNARIWbkhDyOjKNOSQ6uU9hF0BMnASRGtSZ1ZPT7ZUpValVG7ufQqpiK/UeaUkLPw/8YsTtv0RTZ7St21NwMJi7dq1mD59Orp06QKO4/Djjz+2wGa1HeIflecpahFq1PrI5wLksyCI1kSthwWgTIUE9xhd1cCEgLJrszd8GS2bErGQPF1+iCa5h0UHj1jU19dj8ODBePvtt1tie9oc5XQ5ilqEFmozCQDZYwFQkyyCaE08if2W6mNR2eA+K8gbvsami+tLjPRvfUBgZvH26rEIeGumTZuGadOmtcS2tAs0Cqlld/Dw08NDdALEsKvrQYzjOBi0bDAQNckiiNbDs9iXm0g5HHzQKiKq6tkxwN+IhcZHp+byOiECEoCwMAYQsRB778S0s4hFi8scs9kMs9ks3a6pqWnpl2wWWsUXlLpvhhZ10nhm991Cr+VgsVPEgiBaE8++J/k4bbE7EKZp/hWg1e6QIiT+Rix0fpabBhSxCMA/0h67bgKtYN6cP38+YmNjpX8ZGRkt/ZLNQqNMhZDHIqTwVNoGKIYekbAgiFajTjpxOl+RK2d5mIMURRTnBHGcc+ddb2i8TCLleV5KhQQSsWhaKqR9RSxaXFg88sgjqK6ulv6dPn26pV+yWeg0JCxCFTmf676TylcRwftObDpejt/3FVFvDILwQI0X35N4qDYHqftmdSMTATFheqfItTe0XqZh15ptkrk0wc8ICNA086a/7cJbixbfGqPRCKPRf0dsW6MlYRGyeMrnAsrZBMG5OtqbX41rPtwEu4PH5cO64pUrBvvd8pcgQgVvviejTotGqx1ma3D2SbHU1F9/BeC9j4VYahqu1yLc4H+qRryI8ScSU9NZqkI6OxzHQTy+U1VIaOEpnwsE14Vud/B4cNEuSbh+vz0f+wrat/eIINoCqUGWitg36sUTcHAiFqIQ8NdfAXgfmy6Xmvq/PiDQiEX79FgEvDV1dXU4evSodPvEiRPYuXMnEhISkJmZGdSNayu0HAcbz8OPVu1EJ8LbQUw0iwVjENme/GocLKpFtFGHqDAdCqtNKK0z+34iQYQYksdCReyL1ROmIEUsqpoRsVCLbotCJTGqicIiAI+Fv51CW4uAt2br1q2YOHGidHvevHkAgBtuuAELFiwI2oa1JRoNBzh4iliEGLUemvEAwU2FbD9VCQAYmZ2AOrMNhdUmp/HQBEEwvEYsBANnsMybgfawALyPTRcjFvEBrA8ILGIhtyBvX6mQgIXFhAkTOr3ZTKfhYAFgp/bNIYWnfC6gTIU0/zuxPY8Ji2Hd47Ejr4q9NgkLgnDDm9gXIxZBS4VI7bwDab/tWVg0pdQUAIx+lpvyPB+6VSEdEW9OX6JzYrU7pJCqmvoP5mwCMWIxNDNOCmGK7m6CIBgWm0OKRkSrVGqJo82DV24aeIRB46WPhZgKCaTUFPA/YtFotUuCpr15LEhYqKAJYLoc0TlQRgwije4O7mCNaS6sbkRBtQkaDhjcLU46IFAqhCCcqTd73yeliEVbeiy8jE1vtnnTx7FGPGZoNRwiAqg6aQ1IWKig9dFNrd3D80DBTuD7O4Cf5gB2uhr2hZjLDddrodO67xaiebO5HosDhaz6Izc1GpGCeROgiAXRypzZBiyeB9SXtfWWeMTXPhnsqpCSWhMAICnK//YI4mZ5KzcNVFiI3hFfEQuxnXd0mK7dlaq3r/hJO0E05Kh1U2vX8Dyw/0dg7StA8R75/swxwNC/tdlmdQS8dd0EgldumlfeAADonhgBQM6NUsSCaDUqTgAfnsd+T+4NjLqjbbfHA75KKSXzZpAiFmcqGwEAXePD/X6OVhgu5c282dSIha8UT3tt5w1QxEIVX/3f2y3rXgEW3chEhVbxZV77MmCnE5c3vPWwAILnsTgtHLwyE0RhIUQszPT3IVoBm4UdI0Qaq9pqS3zirSIECK5502S1o6SWlXx3i4/w+3lixELNj1fRVGHhZwWaNDJdxX/S1pCwUEG1NtlSD/z2GPDzXODMVhYdaE8cWQH88W/2+zn3AQ8cAh4tAMITgMoTwKn1bbt97RypIsRTxCJIHovTFSxikZHgGrGgVAihoK4U2PQ+UHkquOtd+yJQuDO462wh5BOnL2HR/IhFYTVLg4TrtQF5LLyVmzY1FSKbN70LJqmHRTtr5w1QKkQVjasKNdUAH18AlOxjt7d/CiT3AbqNACY+BsSkt82GijgcwPL/Y78PvwWY8rT8WM65wL4fgPztQM6ENtm8joC3sjZAjlg0t9w0TxQW8S4RCzEVUrgLWPYI0G04MP4fgDG6Wa9HBAGrCTj2B2CqBvpe3LJ/E3MdsOE14M//AtZ6YNM7wJ0bAIP/V9EeKTkArP8P+z0qFagrBuzttzGbr4hFMKtCzlSy/bJrfHhAfgVPDbLMNrsUhQy03NT/VEj7bOcNUMRCFdHpKxlyVj7FREVkCjDwCkBrBEoPAjv+B3xxBTsYtCUHfgJK9gPGGGDS/zk/lj6E/WwvVymFu4GV/waqz7T1ljghHcQ8CQudYN5sxkGM53kpjytGLGKUwqJgJ/DJRcCpDcCG14EFF5Pxtq1pqAA+mgJ8dTXw453sAqOmoGVey24FvpwNrH2JiQpOA1QcB1Y92/x18zyw5B+Awwb0vggYdKXwmpbmr9sfGirYvwAivb7EvlwV0vxUSL6wX3YLwF8BAHGmfITD5JY2FytMtBou4OZV/pabttd23gAJC3fqStCfPwxAKCE6vgbY8iF7bNZHwMwPgQcOAld+BkQmA0V7gNXz2257eV6+Chl9NxAe7/x4lyHsZ8HO1twqdfK3AwsuAta9DLxzNnB6S1tvkYSvRjMGLbs6ak4qpKrBKgkY8QAmvl5doxn45T7AUssiYWFxTAz+9d8mvx7RTHge+PJqoGg3YBCiFMV7gW9vBhwBnswOLQWWPgyUHva8zPIngJPr2Gtd+Rlw1efs/l1fNj/1emoDW7fWCFwwn/0EmOeipdnwBvBiNvv3QhYTz+teZellL9R5mTYMAMagRiwE42ZcAMJiz7e4dN3FeEP/lpvRv7xO7Imhl9oX+Iu/DbJq22nXTYCEhTM2C7DgIrzd8BCu1q6EvvoUO4gAwLAbgOzx7PeIBKDfDOCSN9ntHf8DrI1ts82nNrDwuS4MGHm7++Ppg9nPqlPsiqGtKNoL/O8ywFwD6CNYWHn5//l+XitR50P9O0UsSg8D2z4Ftn8GFOwAbP6Fk8U0SEq0UQrjildjk6yrmJAwRAOzvwDOf4Y9aeW/gT3fNu1NVZ5iabCyo76XbUks9cCKJ1kUpr68bbclEPb/BJz+CzBEAbeuAO7dzn7P+xPY9J7/6zm2CvjqWmDTu8B/RwMHFrsvU7yPpT0A4PL32fGl5xQmABrKWeSiOWx8i/0ccg0Q3x3QCcKipVMhx1YBK56Qb5uqmN9r5VPs4qK2yONTfe2T8qyQIEQsqsSIhZ8pp9JDwHe3gAOPKdrt0Lh8jhVNbOcN+N/Hoqaxfc4JAUhYOPPXf4EydkXxjO5jDF5yCdBQBqQOBKa94L58r/OBuEx2ktz3QytvrMCfwhXt4KuByET3x8Pjgfhs9ntbpEN4np0YP5nGDirdRgJ3rAM0enaAPrOt9bdJBV+pENG8mVOxBnhnDPDLXODne4H3JwDPdQHeOQf44U5g/Wss5Kxy8jgt5HHFihBAqEGHA3dpfmR3jH8AiEph5cEDrwAcVuC7W4Cv/wZYGvx/Q8dWAW8NZxUA74xpujjxB29X0+Y64H+Xs6ja8seBDyYE9j7aCoddNkOPuQdI6QMk9gCmPMXu2/KBf1EEuw344Q6AF05+vB348S5noeBwAEseAngHExR9LmT36wxAl6Hs99Obmv5eSg8Dh5cC4IAxc9h9WuEqtyUjFjwP/PYoe19DrwMeK2b7/sX/AWK6ApUnga+u8Ri58LVPBmzeLDvKvocqlTBKj4VfuAjLTNMhp9sVDU0zbgKBpELIY9H+sdSzck0BLcdDZ61lHoVrvwH0Kl84jRY460b2+6Z3W79SpPwYcGgJ+3303Z6XEw9O+a18ErfUs5zxd7ewSEXmGODaRUBST2DgLLbMn2+17jZ5wFcfC71Wg77cKVx54v9YnrrrWUD2uUy4OWwsRL7rS3Z1tvl94NcH3NZRJDjP0xXh1kiDDlO025CjKYLDGAuMuJU9wHHAZe+xCh9OCxz4xf+UW2Ml8OPdcv7cbmGiJ9jegKI9zHPwbBrw2aXq6//zLXbVL1KVB2z9OLjb0RIcWgqUH2UpqbPvke8fNJtFESqOM1+TL06uZSbJiETgkXwgYzTbF765gZlCAeCvt9lVvC7c2XgNABkj2c/Tm5v+XsR9rPeFQFIv9ru2FSIWR1ewz8gQxSJw+jAgfRAw/Gbghl/YvpO/jYkLlaifr30yXONAf+4kulVvA44sZ+mVjW+pN/06tRF46ywWOdv9tdvDBVXsb9E1Lsz3+7JZgH3fAwAsOpYi62na47RIhTCtOGBhseIp9P5uCj7Rv4Awa7XXRauFBlmx4SQs2i/7fmQ7fHwWZiT+gunmZ7Dz3I+Am38DYrp4ft6wG9kBoXAXcGKtfL+phoVSDy1ruR4Sf70DgGeRk+Rcz8sF4+AUKA4HuzI7vIz11JjwCHDDYiA8jj0uCqH9P7GTjS8sDcDns1iEoOxI0DfX2wAyADBqeczXfwAdbwV6TQVu/h244WfgoRPA/XuBqxYCEx5lERmARbpcEEejJys6+2k0HO7UM3FY3f8654oDjZadaGYvZLf/fJudzH2x5B9AbQGQ0IOdzLoOZ5GPYEbV8rcDH09jUSebCTi+ikWlxJMlAJhrhe8ogFkfy6nDDa85L9ceEbd7+M3OfxNjFNBzEvv9wC++1yN+5n0vYc+d9TETGUW7mfF75dMskgMw70N8lvPzm7vv1pUAu75iv599r3y/TjjhtaR5c+Mb7OdZN8r7vUhiD+CaRUx0HF/Neu244HWftJpwxeZZ+NX4KO7Jux9YOIulV35/jInd2mK2nMPBohQLLlasuNhpVTzPo1ToYZEa44ewOLqcifeoNBzucxcAINfsIiyaUmpauAtY/yqMlYcxUbsLD9g/Yhco744Dfv8Xe00ForCIIWHRjtn+Kfs57HpwGi328DkoSRnLVLY3IhOBYdex31c+xa7Sa4uA988Fvrke+PIqdiANNnWlwA7B3OUtWgHIB6czW9iO1hrs/ZaJBo0euP4nYMI/Aa3iAJE+iHlWeLvvfDXPA9/fxnbogh3MpR/kqhKpQZba1ZHDgQmHn8MQzXE0aiKB6a/L74XjgLgMVoY44WHgGuFqyGFzE5TiwSs5WtEy+PRmDMMhmHkd8ntfr75xvaexEDlvZycib+z8EtiziEU5Ln+fncwGz2aP7Vnk/bmBsOJJZjTtfg5w01IgOp2Ftjcr/pab3mPpr8SeQL9LWboupitQX8quZv2l7Chw8Fev+XgJuxVY+k/gjaHAM6nAq/3YZxIIpYdYBEGjkyNISvoIJykxWuhtW8SUWP/L2M/YrsDMj5gn6sRaFiXlHcBZN8nRTyWiUC3Zzy5WAmXLhywq0XU4kDlavr+FzJvfbTuD8/+zBnPe+Jq9P04DjLpTfeGMEcCMt9nv6//j5gXyuk8e+AUxDeyCpFCXwUR0v0uZR6n8CPDpxUz8LpzFvqu8wofhkoqrarBKfganfdMToqAcMBPlyaMAAINMW4HNH0iLlArmzUDag2PD6043L+bWs79f0W5g45vAy72B1XJKniIW7Z2KEyyHyWmBIdcG3nnz7HtZqWf+NuDt0cBbI5xzqH+9E/wrtD/fBGyNQJdhvvtTpA1iUZXGShbebWkcdlYyB7CTbfez1ZcbLeR7d33lPaqzcyFwcDGLfCT2Yu9jwxtN377i/Sx0qqDOW2nbto/Ru+AH2HkOnyc/4L1viSFS/t3qnDtWFRYb2VX8j/axqNQkeF7vpCfY9/PI78CpP9WXObKC+T4AYPyDrBcGwA64nJaJsvJjnl/DX4r2AifWsJPGZe+yv+95ghF37StATSFQnS+nFs99mEVftHq2LQBrPS/icAB/vcsiIMufkFOKPA8se5SFsL+6BnhtkHcRyvPAkgeZCbLiOIuk1OSzMtFd7uFvj+z/if3scR4TAq6IJu7ifd736xNrgcYKICKJCTCRHhNZb4rBVzORcsmbzHeg1j8hOlWIYvBA/lb/3wPATqDiye7se53X3wLmzY1Hy/DAol04XFyHwSXsM7RkT2LC2xP9ZrDP02Fl+7gCr+bNbZ8AAF61zsI/0j4C5m4HrvwUuHMdE69lh4EPJgLHVrJj3yVvyt9RS63TqoqFGSFxEXqpTbhHeJ75lwAg93w0xPfDp7Yp0IBn/WeE1gNlQnQyyR+hAjDRLES3Kq5biZ2OHPZyKf2Ai19jfUfsZpY2E6gWzJskLNorh5ayn93PBqLTFNNN/Xx+XCbwt+8AYyxQncdSKkm9gXu2AbEZLCy++6umbduJdaw866OpLGQICFeGwgHj3IfVD0hKtPrgmMD85eBitmOHxQEjvcwh6DmJ5VkbyoC8jerLVJ1mYUAAOO9fwIWCYNn+WdMGKNnMwKfTgYVXsM9RoNaTUYzngS0fAQBetM3Gpojx3tevNbCTOOB2ZeQmLEw1LFUE4BP7Bd7nhST2kCNjv8x1r0La9wPzszisQP/LgXP/KT8WlSyLu8O/OT+vsQpYdBPwSl/gzeHAH8/4Tt1tEb57fS9h332ARUW6DAXM1SxK9+nFgLWBeQoGXiE/V7xyP7RUfg9bPwKWPcy+AxteY7d54UAtHkgTctiB9bdHWURBjcO/AdsWAOCAS94C5u6Ur5b/eMbv6h3s/1l+f2rEdmPpDIeNiQtPiGmQfpc4R+sA5jO67F2W5hp2vfd9uFsT0yHbP2PCJq470He682MtYN58Zw0TrRf3T8SVunUAgEWY7P1JHMeaDQIsdaag1lO5acVx4NQG8NDgG/u5zlUhCdnAjYvZ947TAmkDgdv+YJ+xmNJyeZ2SGiENEu1HGqTkAFBXxMRKxmhotBo8YbsRJhjZviekQMtU0p5eOfALi1x1HQ5t+mDcavkHHrLeBusNy4DhNwG3r5G3nefB87w0hCw2gE6hrQUJC0AOafZmbmyxQZZa/3ePZIwE7t/FBMZNy4C7/2IHj9EsB4c/3/achqg+w8pav5jNDgbi61blsTK1U+uZAe7La9iV9o93s4N293OA3Kn+bV/2OPZz5xf+v6emsv1/7OeIW4CwGM/LafVyWHnfj+6Plx8D/ncpi1CkDWIpn5wJLEpja3Qy2/rNwcXCzs87hdY99rHI3w6U7IddY8CX9omw+Oq8yXFy1MLF7V4mhEelg83RFYDdgiJ9NxzkM6WmOh6Z9AS7cik77JwSOb0F+P52dmAbMJOZPjUuu7b4PTnyu3yfpZ6JrH3fM09G+REWaRLTgmrYLPLfavjN8v0aLXDpuyzEXriLHfzDE1jaSHnS7DaciW1LHUvNWBvl/LpGOPku+QfLk4vll9PfYKWevS9kJ/Nlj7hvl8MhV3GcfQ8TYQnZwmeWxgT/7m88vy+RihNs1g6nBfpcpL4Mx/luPGdXXIGLYqqpNMVnYa5j/WIAZgDWuFyJB9m8eaioFuuOlEHDAU/0LUQcalDCx+Gpg12lNvYeEfcXq/NyHqOIx/4AAFQlD0cREt2rQhJygFt+A/5VAty5Hkjtx+6XhIVzQ8PiGhaxSInxQwQcF6IVWecA+jDhXMGhTiOsW/BByBcRfnosxH2q/6Uw6DQoQyy+sU+ERSd8NsYo9pN3ANZGmKwOKX1DEYvWxp8mNo2VzDEMAL0vAKAYm67S/90r4fFAz8lA9zHygX3odSxNUnbY+aAuwvPM5Lj3O1YS9vO97KC67VNWpmeuZleFyX1ZaH3hLNa7Qh8BzHjLd7RC5KwbhRLPjS1r4qwrkXZ8DLnW9/L9L2U/9//kfEW58wtW515+FIjNBK7+igkRjgMmCWa3ze97vnr1xPbP5N8VBxiPYdddLD9f2HUqahCFRosfRlzpQCkLC7uDR0W9S8RCELQHY5noK6/zcZCPSGBX4gArjT6+hlVifH0tM+H1uRi4/EPZmKeklyAsTm2Q3/fGN1n+NiIJ+Nv3wLgH2f3rX/Pc8fP4auabiEoFssY6P5bSh1X99J0OZI1j3ouUPs7LcJwcRVj7EmsKVlfExMajBex7yjuEShKOCZOzbmDPm/ocS78cW+ne12Hvd6wyxxgLjJ0n32+IYBEDgM3M8YX43c0cwz5vT4iN5zwJi+Nr2LElMtk5DdIUmuKRWvcK87LEZ7OrdVeCbN5cd6QUAHBubjKSj7NIzcaIibA4NNh5usr7k/WiEHc+4XvsvClEbmu7sM/V4xAy1yiRIUr1dcThYyn+RCyOC5GDnInsJYRzRS0nCwue5xURCz/WWVfC9ksA6DdDKjcFFCWn4mckbL/or9BqOEQafKRv2oDOKyxObgCe785KkLxxYh0z9iTlMqULSKkQW6DCQo2wGNmU9ftj7g2CdnwuV5MMu4GF2E7/xcLd5UeYKe76n4Fbfme9DTgtMypd+620vX4R0wUYfBX7/Y9/t1xp7N7v2OfZdTgL3/si+1z2HhvK5BD0hteZ2LKZWITipiXOue4eE9mJ0mED3h4JvDfevz4NlafkdBIg5VptdgcahXCq00GM56VUhan3pQDk1r9e0Qt9KhQRi/J6Mxw8oOEEp7jdJgnN/NSJwjJ+HORzz5e/T59dArw9irnck/uy0LprpEIkqRfL1dstTMTVFMo+lQtfYmmp8Q+ytvXVebLPwBWhzA79ZrhfBQNsNs1Vn7NwtKuoEBl+M3udqjy59G/qcyzvf/FrwOUfAOMfAu7a6GxoTMiW/US7FUZUmxn4Q4jgnHOvuyAQ/x7++JzEA7wY4fOEGLHw1NHW1+cUCCn9mWAy18gpw9LDwMIrgRd7sNLVmkJ5+UPL5G68U56W0x5KAjFvVpxgfVq2LfC4yLZT7Ep9bDe9lFo+kMIiwOLVu0fEOSiK1KFVsU86Ddly2NkxG0BDNyZs/e5jIV71u0QsxO3zGbFwOIAzwkWZkFqUhYVw4m+sRL3FDpMwyj3Jn4jF0ZUAeNbMMC4TWg0nrVcSFhqNLIzMtU7GzUBmm7QWnVNYOOzAggvZiWPlU96XFQ8kWfKBRNfUiIUnzp4LxHRjV98fny8LCVM1cywDwJR/A5e8Ady7DRh1FzuADruehfISsplAmfE28NAx4J4tLBQXKOP/IbvR934XnPfmiuiCV+bVvaHVyyH1P99i3hGx/G7cA8DfflA3f13yJmtcBrDQu8KR7ZGdC51vCyf+erN8xROpFBYlB4Dq04AuDHH9WYlhYY3J95hmKRUiHyjFg1dCpJEdNAp3sb9/WCxMqcMA+CksAOD8Z2UDobmG5fuv/sL7cCyOY8IVAH66mxnbrPUsrSSG6vXh8t9CLFFUYjWx6gyA+TiaiiGCVawk5bIIxLQX5agCx7E5Fuc9JoewlQwSxPHur2RxvPVjJlKi0tQrpMQeNC6hdjd4nl2QAL6jDGLEomS/u9/FZlFUgzTjcxLR6uTPZ9dXzDz7yQXAkd8EQf4jK8MW24Z/ORsAz/7e4vNcCcS8+flMFg365T7Vh3mex1ZBWJzn2MDEa0p/WJL6A5AjAh6RhJ/891H6jZzEftFuFjEzRMOWxnxjZqufwkJsy+5q3hRSIam+jJblR1gUShfOvBsA7LwFAO8UsRD39QiDFhEGP7piiumVHufJm6rW1lsRcWnPFSFAZxUW4mwPgJ3QvSEeSBQnalFY+Gqp6jdRycB137PwcflR4NNLgFXzgcV/ZweGxJ5yeDi2KzDteVaiecmbQGSS87rC45t+BRSfxU7WADOzBTrvwBeNlayvAcBKJP1l2A1Cbn4nc/UDrGJk0uOer8CjU4Gbl8onGh9zB+CwAzsEYSEeYIQrl1qhXt6o0ziFIXFEMDpmjUNiXBwiDVrwPHC6wkfUwuAe2nUzbp5YLa07IZqd+MRUiU+MUSx1cf6zwIUvA3M2+xe9Gn233CehtpCZay//wDmdJg6nOvYHK2lWcmwlEzLRXYCMUf5tqyd6TGQC+V8lwCgvBl9X+lzMwsIVx5nfyFQNrHmRPTbxEeeqHBFRWNh8RCwqjrO0jNYgV9R4IjaDCRmHzT1qcewPlsKMSnMu8WwOg69mP3f8D3j3HNbmO30Ii1wm92Xb/eVs1qgPPItuTnvR8/r8NW867ECF90qiM5WNKK01Q6fh0P20EHUcPFv6rvuOWLh7kkRjYpRRB51WsU/mCc3Wuo9BmJFFA3wKfREPEQspFeKrh4VofO96FqDVI68mD3P/ugBh6YtQDWHdjZVyGsSfihCel6OoQnoFULb1Vrw3xfa35x4WQGcSFic3sDKg9f9RN3ep0VjJlDgAdJfzxXGCy1b84wWF5N7sBDDkbwB4YM3zQtSAY+3C1fLiLcGYOeyEUnlCCvMHjaMrWRokpR+bR+Av0anANV8xL4kujAmK8//t+3nGaFb/D/i+Gs37E6g5A4TFyi2ThSsXj/XyR1eyn7lTwXEcMhPZATCvwoeIUTGjuQsLIWqVfS4SI9l94uAiv9DqmUlx5G3u4tMT+jAmJHqdz07Qf/ueGYyVJPZgUQze7t6hcK8Q3u9/mWfBFyhqYXpvGKOYSx5g+9BP97DKh6RcYd9SQednxOLkevaz63D1TrtKOE5hqnSptBLTIP0vbX4aRCRzDLsAEUnowS4+ek1hqcJ+l7L7ciayv+uMt7334PHXvClGdAFW6abC9jwWrZiY2gjNmU0sCjXwCsmzUFLrQ9CpRCzkkeAu++QZYXBhxkipNNTkd8RC3WMhRSx8pULyhL9zJhPV/9vPTOr6uO2okYRFFcqEfd2vHhYl+1kqUxfuJEJV25X7E7HY94PsE2pD2t/0kqby7c1MtYtkns3ykS7dypzI+wsAz3bY6FQAwHeHv8Mu608Ad5mkPINGeBwzXGaNZcbDhjJmTlOEwFocQyQ7MK//D5sz4sn5rqRgB6ug8BWFEIWKv5UqSnqcB9y7g1V7eAvpu+JvmFsMTfe+SO4CKFy5qLrPbRb5ICakHbISI3CgsAanyn28lorHwqnrps0sX3llj0eClYlKv1MhzSFjJDNYemPY9UDBdmbuHHEL+4zry+U0yIAghPebw9n3sv0nfxv7x2mYR8PVrCcifUd8nOBOuUcvvZIxCjjws7MZ2moCDgpVZs2tBlGi0bCKs9UvsJD8JW/J3+OIBNbDIRCkVIiPiyfxbw4wU60Kh4qYQL84Yh9QCVbqGZOO5GgW8WqKx0JMhbhN7hT3yW4jFCdfO3ie9+01EI8rdgvbB3VG8Dzvv3lT7CMilP/aFU23lBELtQ67HhHFbPcx8t8EHuaFKMplVYVF5Sk2GwgALnqV7bttROeJWCT3BlIHsNzo9NeBq4SSR2u953CfpH5lpfj5gc9RYNkBbcRJqS1rUOE4YMjVwO2rgPv3tK6oEBlxGyvtO7We5fo9cWYr8N2tLH/75WzvUzIddvkKv9f5TdsurS4wUQGo+hnc4Hn5ANn3YoXyZyd+qV5eeXVUuJOFziMS2dUwgMxEdgD0KSxc1g+4RCwKdwvrTgKSe0tXNpX1luD5eprDkGtZqL+uSPaubP2Iib70wSwU3JZEp7GS2vhsdqU362N25e4Jf8WnWB3mbxWHmA46vUn2exz5nUXCYrrK/SeCRXwWcNk7bNKqJ2Osv2iFCKmv3h7iPg14TCWdLGff88HmbewOoeV5ir+pELHiweqeCnEybtYWC+3/OaDLMCli4eD9NNqL+yUgXVTUNNqkk7fX1IW1URpQKfprlMKiileJWPhj3JS+c85NBFWFhWrEQvH5KGdB/TpPbuTVBnSeiMUNPzvfdtgBcAB4oTwuxf054h+im3ygbLSx/DnHWVtGWLQHYruy0Oneb1lX0MveZQeY6jPsgMhxrLfAWpccbW2he+hcpGAnC0kbY4N/QPWGFEb1kp4o2sMqHXThLFQsdh8VQqJSDwtlIx5xh88cI3kQuiewA+Cpcl+pEPfQrtTDItoIFAgla12HARyH+Ej2ujYHjxqTFXFNGLUcVHQG1njt53uAVc+yBkab3mWPnT3X/xLnlmTA5SwiYLf6TiP647GoPMWMuhqdnOLwRbrQ0bahjF2kZIyUP6cBM4OXLmoJlOZNnlf/m1blseiIiIfP70RZA/SwoVuVcKEmCAvxRF3RYIHV7oBe6+HzUIlYiKkQp4iFGDFI6QuExcCoaIxltnlZv4hWx/5etkYm/iITpa6bseF6hOm9pK1K9rOITWQy88oBsDlkg2kN5KoQv9t587wcucx0ERaieVPp81N4LGrUIhbK0udBs1nFXRvReYSFKxoty6ebqoSBMS7CwuFgzY8AllMVMIs5R401sJx3R2P03UxY7PqSdSy01Av5VqHBk5iHHDCLuc4dNmbc84Q4+yHnXM8h6ZZAPCg5bCwypXaSEUVC9ji2vBjlEDrwieOHnSIWogk1c4x0V3cxYuFvwx+niAU7gCVFGYATO9idXVg1iFGnRXSYDrUmG8rrLW0vLAAWtdj3AzNsfiFU+CT3ZeWT7QWO88+bpBNC3K7VG0rENEiXYeoGUNX1GpnA2bmQGcZ5nq1Ho/c8H6O9oPS2eBJnYq4+IomJJ5XoBs/zOFVej6HcEehs9WzZtMEAgIQIA7QaTujhYvE84EvFk1QjtKt2MidKx2txv5GFhNlq9zhA0AljFBMWQsRC6rrpy18hDv9LGyiJMOeIhSwsTtnZft9VMcVYlcoTLCqo0UvvSdpMvyMWSmEhRJ8vfo0Z4ttQ2LZjSR0EwuPZTzWfRfkRdqLURzCzoYBJUOWdOmIBsCiNOGCpsYKJCo0eAM9ERXQ6a7Y06yNFaWOtx9Xh6HL2s6ePFr7BRtk4xlOoW6w9FyMpUtkZOwCIHS/jxda4PC+nyRSGqswEJizOVDTC7i30qlcTFopUiMsBEgAShSmI7eY7pxHngAim5thM4G/fBm62bA9IUS0vwkJRbRAQ4j60+2tWSg6wfjFqM0baE1rFidSTgVM0GAuNA9UiFiW1ZjRY7DhLK0Q2up8tndA0Go4JacgncFWU+4uQUlI1b4ond6GHCMdxUsrA714WLgZOqeumL3+F+NqpA6S77IqquipFxOJwMVt3bqqPtK4486frMDezsLrHQr2PBQD2uYnVSV2GtHm0rPNGLABmbqoEm4fgipgGSR/idIVtsgs7j8aK8hqzf6agjsqFL7O8bflRVl2RPpjN36gtYA5w0VXuoce+REOF/Hm2trDQ6lnTMN7OhIXreGZA4aUZwX4anQ8ubjtpTT4r59PonA4kXeLCoddysNgdKKoxeb4ikUK77sIi1WhV5GqHSo8nRhlxsrzBd/fN1iQqBbjpVxYSD4vz3p69PaP3I2JRIESRFNFLv+g6DOgxiUV2AObHmfRE4NvY2uiUwsKDgVPcb3ImskZ+dgtLMSsqXU6Use/4aONJwA63Mt3kaCOKa8worTMBiFV/HXF/Ac/Eiz5c9lgoUyFFu9lPoYcEwK7sLTYH6s1+dMQF3EpOZeOmvxGLQdJdyohFsTUC0AB8YyXK6k0AOPRIiYJXVKKiInK5qTJiIV4Q1aGqgV2ASMesqjwWndfonS6U24pOLiy8RCxEdae4arQ5bHLejLPCaudRa7a5O5M7CxzHHPZKopLZPyWSsPCQCjm+iuUfU/q1/pWaOJvDXKNu4HQxfAFQpELYwUXcSaUUhPjdSO7rVLKn1XDIiI/A8bJ6nCqr9yIsnEO7JqsdNYKPI7X+MACe9VdRpOcSIluxMiRQxEFjHRUxYmHzICysJpZDB5zEnt/M/gLY9QVrqDb+H+p+rvaGRisLcjUDp3K/UZpZbWaFEABOCsJiAIReFy7GXhYJqPERsZDXB0s9ExZiVYhoTqwrZR4vcEBqf2nxnOQo7Dpdhb0F1ejlK0IAsPEKgFRqLpbCeu1h4XCwpmSAk6hReiwKLeFAGMDZzQiDBYlxcb5TM6KwUJn+LHoszKoRizoUVbtstyh8Uvo4i8Y2InRTIWI+SqFAzYqQoEHP1GhFZ/ZZ+Iu4M3qKWIjOccG01ep4M3CKV12C4QuAWyrELWIhfje6DHZbXaY/PguX2Qdi2bJBq0Fk1UH2mOIABchGL68HYKJp+PJYFO9jHp2IJDa5NFD0Yaxj6YUvdQxRIeKt+6a03/RjhkURl3TIyfIGJKMSifZSAByLeipIi2WffUG1F+OsRiv/jcRKLVfzphitSMhxqhwbmcWO8ZtPeGkroMTgErGo8SNiUXmCHVt0YU69RJQRi3qEwQYWyYlDHXr6ilbUlQgmck7VLJwg9LbZdLzCbdt5cy2KhUiLdHEjTtlNdT6utBWdW1iExbGfrsLC4ZAbY6XLwsKk2GnCDUwptssryNZGFBYmlYgFzyuERSunQUQMXnLo4gGpyzDF8uKJnwkl0WMhNkaT3NXiPAgF3RP8KDl1KYFV+iu4kgPssZS+Tk/pFs8OEAVVfswiIQJDiliY1GfkFAiely5D20fFS2vhrfum5EsazlLF4uRZF2FRUNWIwRphIFxyH7dycfF7fabSz94vQpTPzbwp7seK4zUAjMxOBABsOVkBv1D4FAA5YuHRWKp87ZR+Tmlzu1PnYl4ycMZx9ejlMw3yl7xO8QJYwfVjWIPBH3acwZHiWqdttzTWwO7godNwcuVJiSgs2j4NAnR2YSH+wUxVzvdXHGdXk7owILGXdLcyYmE0CBELEhbePRais1lrcOoH0qqomCUlxBO5codzybOKEYu4cCEVIkYsVISFX903XcpNy6TyM4MccleEcwHlAZiERdBRdqBUK5mUTG9NSIN0ZLx13xQNxt0EX5IYUXD5/IqqTejHnWI3xPkpCrrFC4ZnX99rFzHuVm6q4nEAgOHd2TH+aEmdf8dqN/OmHwPIlBUhCmy8nAo5v38Synl2AZbIVaNXqg9hIfWvUDcLD86IwwX90+DggZd/PyRsOzsO2xrZcTg1JkwaViZHLPq7rqpNCA1h4RqxKBJOHKn91Y2bUKRC/J3f0JnxJizEroPpQ7y3EG5JvDVAEoVFsqKhkHhwcVgBm9k5YlFXylrsglNV/1n+NMlyOXhJEYsog7w9LgYrUVic9nVlRwSOTuGFUYtqicbNUBMWYirENWLB8/KJSjyZSss6Hw8LaxrRS3OG3VDuYwLi99rnVGCXdKZo3pSqQgpF46azsIiPNKC34K34dU8hfKI4lrGum+IAMm8RC3VhoYxY3Dc5BxVgwiI3shFT+6cJ78fEmgyufZlNNBYRS3kVwy9deXBqLjQc8Nu+YuzIq5QuiHgTOw5LaRBLA7tYBtgk3HZAaAoLD19SZSpEr2NfmjLyWHgXFmJIz9+mQi2BSoMdAGynFgcoKU/kyg58lnpUNSoc1mJEISFbtZ9Bd4Ww4D2Nntc7b48oLHqGVTOTqUbnPPcB8pVdYbUJtmANvyMYWp1QSg13YWGpB0oFsRdqwkLsvml3OcbVl7ISdE7DOhoDqhELnudRXG1GT66A3aEmLISTX2F1I6zevtcu+7Bs3tSzv5HY1M4lFQIAV49k04/fWXXU90AyxbGs1myT5oz4F7Fwfm2leTM9Xo/umVkAgIfGJshG8KMrgD2LgD/+DSwSpgtXnwHKDrHPN8e9iVWlqRL7yvehZ0o0Zg5jnp+XfjskHbc4QXylxwl/k9KDzDwfkdRuPD6dXFjEsZ9uEQv1fJ2aefNYqfPAmpBEND2qVYWIEYtgTXFsCiotgQGwsk7ewbw20Wny/VqddKA011dLB5e4CL3HiIJIRkIEdBoOdWYb8j35IVwaZLFSO6A38tj9SbluDYmSo4wwaDWwO3gU1fiYaUEEjqdeFkV72HckKg2ISW/97WpLPJk3JXGdI0cDJQOs/N2sqLfAZrchhxMiBcm5bi+RFGWEQaeBg4dUyaCKKPat9bA7eGkwYEyYToie8KzjpcqJc/bITKREG1FQbcKirWe8vmVEME8GGsql7YkN1yNs05vAgovd06n1ZUI1CtwimMrzhc1hQ5euzBcRbimXF1K22T64GCg/Jkcrup6l6q+Y9v00zF48G8eqjuH+KbkwaDXYeKwcWwtZFEdvE4RFrPC3kdKr/dqNR6iTC4sE9rNB8YfmeUXEwtnBrIxYRIaxk43fpqDOjNGDsDDVyF/q1mzj7Yon86ZSJLjucMLJv66GiU6thmPlYeL7UZgrrQ4rNhZsRIO1AUadVmp8szffQ/mtstzU4ZDyuN3tp+TtcUGj4dCVfBYth5imcy05DdU0CODZvKlmMFaJWBRWm5DBlcDIWdnjce4TjTUaTopaeE3zKaJ84lBAAIgO0yv6V7hHKwAgTK/F3RN6AAD+6ytqESGeEyqkC4P0GCOw4gng5Dph4rQC0eQfn+1mTFWmzq0Oq1ymX18mLyQag0UO/gocEoY19nCvojtRfQL1wgXSvvJ96BoXjmtHs3Lv19czgWNwNIKDA13FiIXkrxjgtr62onMLC1Hd1pXIbvDaQtaeltN6VaBhBgc0HHC6opGc+p5SIeKVRExXaTpsm6D3kAoRQ9xqA5uEK6S6WiYOYsP1rBGairBYfGwx7lh+B97b/R4AYGBX1uhnb361+vZIKRQesDagRIhApJnFPGhf1aeRgbMFkXw4JCwkPJk3pX1AcXxU8VgUVZvQk8tnNxJ7eRwR39Ufn4XC8Fwu+NoiDVrWKEq6EPRcSqmMWnyz5bTn14lIYj8bylBYxfbLQdGK45rrBFzJa+J+0jYrPgur3QpEKs43gNANU/h+Df0b+7nhdeCQOP32Urd1Lju5TPo9TMuEw5yJPRFh0GJzgdzILBqNcsSinRk3gc4uLMTwt7VBPimKX9KkXLc2qsqIhc1hwQDhBBLyUQuPwkJQ822tlD31sfCW1hDeU2NdFQAgLlzPDgTSc+Sd9EwdC68W1LFc8oCuLIKzt8CDsNBHyPnrxgoptRFfJ/g9PBwA/C7NIwJH50FYSD1LhrTq5rQLPBgyUewuruWIhfz5FdaYFP4K9zSIiOgfOu1NWCgqu6QqKrG3hAfzZJWpCtVmtg+G6bW45zzmW3ptxRGpqsQNRSpEvGAcrDslP15f4ry8l2iAMmJhc9jkC1lxHRXHAVM1E3DjHhRetwwAD+ROU73A+P3k79Lv4oVuUpQRt47LgRkGNID9HRK4GmQkRAhGW+E43A46bop0bmFhiJSbIdUVs58e/BWA8xfFZDdhZBYLm/11vNxt2ZBCFBZ2i/NBSBIWbayUPZk3VaIP8nNYxMJcXwUAiI3Qs+mWljpm9EvsIS3aIHbQFITnAEXEQtXAyXHSlZGtthSltWboYENYtWBA83AAEA/APseyE4GjFrGwmYEyYcZFW3+H2wLJvKk4CTsczAwIOH9PpVSSvP8XV5vQSyNELFSMmyI5SUw0HC3xMmtI0QZfbCiXFGVklRTifqxovtVgbcC4r8fh0p8ulaozrh6ZiZzkSJTXW/D2qqPqryMJiwoUVrELkVz+hPx4tYtHQ5oR4v79aFSILKvDKjcSqytlP88I01jTBzEz+Ln/ZMZtTguMf1B18/Jq8pzXKXDbuGykxYShxMGOPWPTeeSmRrHoSEO5YLT1/DdobTq3sAAU6RBBWKh03BRRhrbMdjPO7sm+hGsPl3muAAgFDIrcojJq0V5CcGoRC3Od0JIYrDW3K8IBxlrHRGNcuMK4mZTrNGxLzHmKB5K+6THQajiU1Vk8py0i2fpryovg4IEemmJwdgsTNLEZqk8Rm+ocKvJyACaahjQ6XfH3KjvCWlobY1k6L9RQM2+K4lprYOZNaVl1j4WUCknyHLHo14VF+PYXeJmOrGiQJQsLAxsWaTOx/SY+W1p8dxm7QCxrLEODjQlxvVaDxy5k+/on608iT02gi8KCt6O6knkhupkVIkQpLOw2WWS5HON4nndKnTOPhRixKBVGogstu0X/2cRHgL/vA+ZsdpupArCoh8Uh+12U648O0+PlKwajXChpvXVolJC6FY7BCTlOrdbbms4vLMR0SG0R+ynlVIe4LaqMWDTaGjEmJwkGnQb5VY04WhLC1SEajSwuTEL43+GQQ6Zecp+tgmSWVJw0SoWmMlGp0kneiQjmxubrBWERYZCFkkuEw1VYhOm1OCuTPf/3/cXq2yRELGor2PduRESRvG4Pkwf7pLGDxtGSOio5DTZqEQulSbGduOlbFTXzpgdxre6xaEAPL6WmIn3T2ff6ZHmDVO3hhtS0rgZltYqIhXKqqGK/OVh+UPpdeQI+r08KxvZMgsXuwNOL97lfEOoMkhndVM1SFgk18rqchEX5URalNUQBcVlOq7E6rHDwDqfbkn/DYWVNGdUm5kanAUnOpeYijS7GYotLGfDYXknI6MaMnFlhgmhqLxd3LnR+YRElmArrSoCaQja5ktOodlVUeizMdjPCDVqMymbpkNWHSltja9svrj6LqpMsQqA1Agk9PD6tVVAzb4rhU08HPOHKRRYWenU3PIB6obxLvDICgAsHMsG61FNTHiEs2ljJBMUgQ77qupV0iw9HpEELi90hTY0kgoTavBBvqbJQQM286ekzUfn8rFX5iOYawXNa5+iGCwmRBqQLM0MOFnqIWkjGx1KUSp1qjYouuM4RZjFiATifkDmOw/9d3A96LYcVB0rw6caT7q8l7Pu22jIkowrGBsU+XFPALpoAZ++Cy8WAqwiwOWwsXWQUJriWHpbN4yrTS9VocGnwZ1bpiJqSLkQ764Xzkco49/ZACAmLIrn0J7mPrJAVKP+QYlpkYm/2hV99uMRt+ZDCVVhIV/d9nLqXtglqqRAf/SgkYdHAwqEZ8RGK9t/O6r9ROJgqDyYXDGA9D7aeqlSvGopkVy/WWva96YOT7H4PJXMAK83LTWOf80FKhwQXtT4WatUPoYTYS0Xpm/IgruVUCFuW53lE17IqJ2tslltfFlf6CVGL/Z6EhXScLpZSIcnRRo/Gzd2lsrAwubQZ750WjUeFlMhzSw5i95kq59cS9v0YRxWGaAVDdWJPABwTWcIxwVs0wPU1JT+EWHJ64Gf2MylXOhb4wlfEAoDs4xCFhZfxA21J5xcWYhlkbbHc/14xKl2Jq3mT53lM6M3+kJtPVKDeUxgvFHAdnd6eaqfVzJu+rkaFg4vWxPpYZMXrWTc8lee4pkIANrVRjGa9vuKIx/XzQk17llU4gPlIG/WRhIWXfDQROGp9LJSNhUIRKWKhMG96EuQuHotasw2ZduZh0voR8RF9Fh5LtBWtASSPRaRB0cNC3m9KGkpQ3CCnIF1P8gBw49lZmNo/FRa7A/d8sUOaBwRAOtHHc3U42ygYNzNHy2lzMR3iRVi4RhOs4mcoTsfd8T/2U2UkuieUEVHAk7BQlLRa6lkTQMBtqmxb0/mFRZTwZakrlrugdT1LdVGzS9mV2W5GdlIkMhMiYLXz2HC0TPV5IYHkeBYiN17c0q2Oy2REAH5HLIzWKgBAjraE5VP1kUBsptOiasICAB66gLU7/mbbaew543LAFA5e2sZyJKAGMVZhrLSPz0uce3CgkCIWQcW13NRc693cGwq4mjftNoW4dhUWoseCncRZDwvmr9Cm9vb5UkMz4wAA6454MMKLEYv6EpTXsr9RF00565qs0Tn9jUoanKPHygtCEY7j8OLMwegWH468igb8Y9Eu+XWFfT8RNRihF3rLdB0uiwI3YeF+8eSWChEHkg26Stgo4Xgw5Fr39+oB13WqpUKk6Ed9Gds+sWtsW/YRUiEEhIWg8CqOyWYaD10iXb+gZrsZHMdhohC1WH04hH0WAex0rY5LC200VLDUFyDPOnBFOLjEOlhkoEujWArqbq4UryRMNpPTQfGs7gm4dEgX8Dzw5C8uRjHByGUwV6K/5iS7LyHHrXufK4Mz4gAA205VwuEI4UqkYCOZN4V93Je5NxSQzJvCCaziuGxWdK1ckqpq2OdXWG1CTz9KTUXO7pGEcL0WhdUm9Y614oWLwwZrHesblNYoRAKTejsNOHQ9AbveFomN0OO/1w6DQavB7/uL8dF6ITohCguuBj1twmt0PQuIz2K/Vxxjx5Aa4VinEtFyPVdIEYv+l8smzm4jA5qh5I/HwqlXhpQGaV/RCiAUhIUY3qrKY2HQhByPV42uITXx9gTBZ7HmUGnolp0qhYW5jo1LB9pHxELst99Qzsq8xBKx2Ax5zokrwsElnqtDSrQRhjLBqKXS30SMWPDg3Q4o/5zWFxEGLbadqsQPO/LlB4Qri3BrpTxWWmXdrgzoGotIgxbVjVbyWQQT1wm4HiqAQgrXIY1Kw7Nr5ZJLVUhRdaNfpaYiYXotzs1l4mH5/iL3BXQGaQRDtI0Ji7hqYT92SR+6Cgm1VIjIoG5x+L+L2d/4+aUHse1UhbTvT9TsQJi9ngmplH5MwADMeCl+FnGZQFis23pdo9uSx0IfBkz4J4t8nvcvj9ulRsAeCzG178dxpbXp/MIioYf8xwCAATM9lpa5KkTx9uicRCo7VQoLMc0Qlea3MalFEXsQWOpYCNIft78wMyCaa0ROvM6j+rc5bE7fC9edPy02TOr498TP++TBZMJVSyxfgyEa//wVAKvFH06N2YKPFNUS9l+VDqshh5h+EEvxPRk3ATePRXVZERI5Qfgm9fLr5ab0Y6/3064C2NWiccL2JHNVCNdrYShVF/tuwkIlFaLkb6O7Y/rgLrA5eMxZuAOVmjgAQI5GeN99LmIGdLF7aNkhuQeFB1Ok62sqJ51i5G3AYwWqk0u94eaxcHgRFqZquTV493MCep3WoPMLC30YcOk78u3+l3tc1PXLIt4ON2gxOoep3FWHQrQ6RAyNVp+We4Go9M9vEwwR8tVXTb73A6SIMRYOsNkGfWOsinkEzgcx151dLex6+7gcDMmIQ63Jhge/2cVSGEJ4PZprxCSt8Hll+3egEb9rJCyCSEwX9rNauMoO9VJTwLkUH/BeJSNGLIRUEi9EBauNXRSzcbxzwYA0xEXocaq8AYt3F7gvIPgEklEtVISozwhxjVA0urZpd4HjOMy/fCBykiNRVGPCeT8bUcfLqRUMvIL9VEYsjq9hv2ePV12n63FA2SWzqfjlsQiLY54TgPXKMMaQsGgzek0BrlgAXPquVwe4p1QIANlnEar9LMSIRU0BmwIIABltOCrdlRgxopLv0bh5sKgGP+8qwMZjZbCDQ52WpUkG6c8AjRWs1a7Lc1zznmoHMZ1Wg/9cNQThei3+PF6OD9cfB8Li4ODYAcAAKwu/+jno6uweTFisO1LmeeYBERiSMBby5r7MvaGAshQf8C62dM4eC2MV8yQ1xPjfwybSqMMt57Duma+vPAKT1WUKqSJiMSy+UTDXcm5i3+047SNiAQBRRh3eufYshOk1qEQM3rJdyh7QGoGcCez3hBx2DLDUysc4DxcDblUhQRAW4rFGw7HTsmoqRKNx7hnS4zyfpb5tQWgICwDofxkw5Gqvi3hKhQCyz2LLyQpUN4TgwT46je10Dqtcox1AKVWLIwqfqlNAwU72u3ClY7E58OgPe3DBa+sw98sduOaDTejx6BIUWVk1yViNcGWU3MfJJAbI/goRT0ax7KRIPD6dnaReXHYI209XoVTfRV6gxySP0x9dGdQtFr1SotBoteMnpW+DaDqSMM5njfLqSwBwns29oYDoP2soB0w1zLwJeI9YCN6C2DrmsbIl+vZXKLnhnCwkRRlwvLQeLy475PygYExM5qoxySj4K7oMAcLjnBbz17zpSu+0aLw0azDiIvSoHHw7Gic8BfztO9nEqnNpYx6V5jHNU2dxTokHM2IRZ4wD4CFiAQAXvyb/3vvCZr9uSxA6wsIPvEUsspMi0SctGlY7j189dVvszGi0zvMUtAaPZbttQqywbUd+Z42yjDGSW/21FYfxxSZWWji8ezzrsgmgEqxCI/nET+y5Kg5uf4UFAMwekYGLBqbD5uBx9+fb8RR/m/xg7wv8fiscx+GaUazk9bM/T1F772AQlcpCyLwdOLiY3eehUV7IEJ7ALhYA4MQaVroYkShXHihRTDfleR6p5pMAAENaYKmkmDA9XprFfEwfbziBNcpKOyFikcJVYrDVc/qw0e6/edOV6YO7YOfj5+OFK89C+IT7gexxzgsohWavyR79ePvK9znddvJYNBEx7RordO+02j2IlaxzgNtWAVP+zTyD7RASFgpEhajX6J1ui1w2lJ28ftjhMgEvVIhVCIuuw92u7tuUGIWwANiQH40Wu89U4d01zDz5+uwh+Paus7Hp0Un496UDEJsghIIbBC+DivoPRFhwHIf5MweiZ0oUimpMWFLbA1dyL6Fx8vNAv0tVn7OjZAe+Pvi109wBALh8WDdEG3U4UlKHN/7wMKmR8B+NVvZZ7PuB/VQZBBVSaDSyiDj4K/vZ9Sz1k6kiYlHTaENPMKEelxm4z2pinxTcMKY7AODBRbtQVC34NoR9eDB3DOnlm9jCKgbIpqRC/KbvJUxEDZrNTtwq8DyPLUVbAADdY9j7CGbEIt7I/GIeIxYAa/J4zty273rsARIWCsQvrBiKcj2JXDq0KzQcsOVkJY4Uh2ApoFjnDQBDrmmzzVBFDHWLZIwCALy75hgcPLtSmTGEHbiMOi2uG90dfUZMdn6OilHLzWPhI+waE6bHpzePRPfECHSJDcNTt89G+Ni7PKZBbv7tZjyz6RksPLDQ+e2E6/HMZeyg/eYfR7DC07Azwn9En8WpDexnAD0GOi2iz0ISFh7ElmKIW1HBSaRwVXCAg7Fb00odH7mwL3JTo1Baa8aNn2xGdaMVxanjUMOHI1tTDH1DMTvBq/i4xH2QAxNAgUQsfDL4KuCxIuDy96TKMVfO1J1BYX0hdBodhqeyz8tjdCEAxGONGLHwKizaOSQsBArqClBtYd3SUiKYinc9iaTGhEklU6+tVGnj3Nk5535g5B3AjUuAYde19dY44zr2utsIFFQ14rd97IQ8Z6KKyWzUnfLQoB6TVCMw/lSFuNI1Lhwr5p2LtQ9NlCY7ekIMob654023HikzhnTFNaMywfPA3K92YEdepc/XJrzgKj67jWib7WhPiMJCbNXfzUN6Uxw3XluE+pOsf0K+tqvfFSGuhOm1+OiGEUiONuJgUS1u/2wrNp42Y5F9grzQuQ+pjgIXhUR8GLuy99dj4Tc+Jt1uLtwMABiYNBAxwqTUYKRCXD0WqubNDgIJC4FP9n4CB+/A6PTRyI1nhqRKk/uB/O9TcsFxwK+7C7HzdFUrb2Ubk9IHuPBFluNrbyjTNHHdgcwx+HrLadgdPEbnJEgjyZ3QGYA7VgNDrwMumK+6WtdUiKvQ8IReq4FO6333UqY/Gm2N2Fq81W2Zpy7pj3G9ktBgseP6jzdTCWpzUAoLY4xcXhjKuLaC9uSbSsgBNHrAWo+IE78BAIrCAzNuupKREIEFN41AlFGHTScqMO+bXfjYdgEatDFAz8nsQkYF18hyUCMWPmiwNuDDPR8CAMZ0GSOlzYNSFSIcWyRhodbHooNAwgJMQPxwlOVdbxt4G5LCWXOjskb32SB90mJwmRBSf+CbnWi02N2WIdqA2EwgaxyQeTZw8zLAEIFle1kZ3ZXDMzw/LyEHmPGWx+qAQDwWgeKaZll2YpnbMnqtBu9ddxZGZiWg1mTD3z7chE83ngzdDrDNIUZRpTNmjnt3yVBE2TwwqbfcD8YVrV6YAArkFLLGTDVxze8B0r9LLD68YTgSIlnJZFRqDvCPo8A1izymDyUvghCxCKrHwgcf7/0YZ+rOIC0yDdf1vQ46oadEUKtCwuIAUCqkw/PD0R9gtpvRL7EfRqSNQGI4C/uVm9SvDh+f3g8p0UYcK63HQ9/tppkO7QGNBrhxMXDzUiCmC06W1eNQcS10Gg6T+jR9QE9LCotai7NPZ2XeStgd7kI1wqDDpzePxCVC98Anft6H2z7bij1nqklgBEL2BDawbuAVwPiH2npr2gfKFOIFz3lfVhDfBgfbB2wp3jvJfrz3Y1z202U4XHnY63KjcxKx9L5x+NdFffHZLSMREWb0KvrEqhDR5NiaEYsdJaxa5c5BdyLKEBXciIXVJWJBqZCOi91hxzeHvgEAzO49GxzHycKiUV1YxEUY8PrsodBrOfyyqwBPuQ6gItqc34V5BKNzEhErlJc2haZ4LPylxsLy2tGGaEQbolFuKpcOXK6EG7R4ffYQPHphH2g1HFYcKMH0t9Zjyn/W4o2VR3CgsIa+g75I6gn8Mw+Y+SFFK0T6XwYM/Rvr59BzsvdlFY2zLLwWxkzv5eb/2fYfHK06ipk/z0S12cO4dIHUmDDcOi4HqTG+K81a3GPhhaJ6dlzJjGHl4KKwaAmPhdlu7rD7dMjvXQcrDyK/Lh9R+ihckM16DSSFsVSIp4gFAIzpkYgXZw0CxwGf/nkKD327G2YbpUXaC78Lps3z+zdvnLAYVQgXOg8G8yBWZ2VNdhLCEjAxYyIA4OdjP3tcnuM43D6+B367fxymD+4Cg06DoyV1eHX5YUx7fR0mvLwa7645hqqGjnul0+Jomy4yOyURCcCMt32LCsApXbjEMQqpqWleF9dycirjq4NfNXkTXXE9AbdWKoTneRQ3sONKWiR77y2SChHeFxAcwdIWhLywKKlnffKzYrKkk4cYsVDzWCi5bGg3vDBzEDQcsGjbGVz69kZsOVnRshvcjjlT2YCvNufhjZVH8MWmPBwprm0TxV1aa8Y2oYJCrOJpKmLUqls0M/5Vmarcek40FVG0ROujcUUum1ew5MQSVJmqvD6vZ0o03rx6KLb+azJenDkIk/umwKjT4FR5A55fehCj56/E07/sR2ltx83REu0QxXj0hfYpyEr0XBHiuo+szFsZtM0QIxYJYQlOt1uaSnOl5HtIjWDHFSkVEoRyUzVh0VF9Fu2zu0YrIkYlRDEBQDJv1lvr0WhrlASHGlcOz0BaTBjmfrUDBwprcMW7f2JEVjxuH98D5/VJgVbjvXSpM1DdaMVTv+zDDzvy4aojBnSNwW3jcnDRwHSfVRLBYsWBYvA8MLhbLNJjPf/t/EH8fnSN6oojlUewIm8F7lpxF96b8l6zt1MSFoZoDE4ejL4JfXGg4gC+O/Idbhl4i8/nx4TpceWIDFw5IgMNFhsW7y7Egg0nsb+wBh9vOIEvN+fhpnOycOeEHogJoyt1opkk9UZRxkVYfaIetclnIdzguUV9jbkGdl6O4B6oOIDCukKkR6U3ezNczZutlQoR0yCJYYkwaJnZVEqF8M2LLDh4h/Q+xBJWgAmLKHS87rAhH7EQoxKimACAKH0UDBr2xfHks1AyPjcZK+edi6tHZsKg1WDLyUrc9tlWjHvhD7y24jAKqlovB9jaFNeYMOOt9fh+OxMVI7LiceXwbhjbMwkGrQZ782tw31c7MeHl1fhycx4stpZvT/3bPnYAOL+/91CtP1Q0sghUtyi5VHFjwUbsK9vn6Sl+IwqLKEMUa+PdlzUd+/rQ1wGHQCMMOlw5PAO/zh2Lz24eicEZcWi02vHf1ccw4aXVWLDhRKt89kQnRqPBFxlP4J+22zGwW5zXRSvMbL+J1kdjWMowAMAfp/8IymZIHotWNm+KwkJMgwCAXhuciIXyPUTqI6XzT0c1cIa8sBCFgxhWA1gu21vJqRqJUUbMv3wg1j08EXee2wPxEXoUVJvw2oojGPvCH7hlwRYs3HQKu89UocHSMfNmrtSbbbjuo004Wd6ArnHh+O6us7HozrPx4qzB+PzWUfjr0UmYNyUXiZEGnKlsxCPf78GEl1bhf3+edJ9sGCQq6y1Yf4T9zaY2U1g4eAcqTOwAOb7beKfI1ZcHv2zWugFZWMQY2BXKtOxpiDfGo7C+EGtOr2nSOjmOw/jcZPx499l477qzkJMciYp6C578ZT8mvboab686ir351S32+XdUHA4eG4+V4eXfDuGxH/bgld8P4Y+DxSTGXNidz0yYg7rFel1O7AEUHxaPCRkTADBBHgzEqhCxLNNkNwUtPekNNWERLI+FeJzRa/QI04bBqGUt1DtqLwtKhaikQgAWwSioL5Aer7XUwqg1SiEwT6TGhOGf0/rg/sm98Nu+InyxKQ+bTlRg5cESrDxYIi0XadAiKdqIuAgD4iP0SIg0ICsxErmpUeiZEo2sxIhWSx00lWd+PYDDxXVIiTbiq9tHIyPBuUteQqQBcyf1wm3jcvDl5jy8u+YYCqpN+L+f9uGtVUdxx/geuGpEBiKNwfsaLtlbCJuDR/8uMeiZ0rwQYo25RgpxDk8djg2zN2Bf+T5ct/Q6LDu5DI+OehQRevfOgP6iTIUAgFFrxMzcmfhwz4dYdHgRJnWf1OR1cxyHqf3TMKlPCr7achqvrTiM0xWNeOm3Q3jpt0PgONYhNCc5CjlJkeiRHIleqdEY0DUWUUH8e3QE9uZX49Ef9mD3GffKhegwHS7on4arR2ViaEYcOB9dGTszPM9jryAsBnT1X1iM6TIG2AZsKdoCq90qXeU3BavDKkXzlBeDZrvZa8o6GBQ1qEQsglRuml/Hphh3jeoKjuPYZ2Qlj0WHRYxYuAqLhHD2pc2rycMzfz2D7458hy6RXfDulHeREe2l4ZJAmF6LGUO6YsaQrjhWWocfd+Rj5+kq7MmvRlWDFfUWO+rLG3CqXL2To0GrQU5yJHqmRCE3NbrdCY6VB4rx5WY2iOi12UPcRIWScIMWN4/NxjWjMvHN1tN4Z/UxFFab8PTi/Xjxt4OY3DcVE3qnIDc1CllJkYg26pp8AP9pRwEA4JLBXXws6RtRVMYYYqSD4eDkwegS2QUF9QXYWrwV47u5zxfxF7EqRBQWADCjxwx8uOdDbCrchBpLjRTNaCo6rQZ/G90dlw/ril92FWDZ3iJsO1WJGpMNZyobcaayEWsVEyY5DuiVEoUBXWIRE66HQadBvdmGygYLKuotqGqwotFqR0KkAf3SYzA4Iw6jsxORmdh0gdWWLN9fjHu/3A6T1YEoow7n909Ft/gIFFebsOpQCUpqzVi07QwWbTuD/l1i8LfR3TFjSBdEGELv0LnyQAnK6iwwaDU+W9WLV+DxYfHIjc9FvDEeleZK7C7bjbNSmz4VWZkyUJocTTZTywsLMWIR4S4smlu9oRQWAOSIRQdNhYTe3uGCePIQS0xFxFTI69tfl0xIebV5uPm3m/HTjJ8CulLtkRyFB85npVo8z6PeYkdprRnldWZUNlhRWW9BaZ0Zx0vrcaSkFkeK69BoteNgUS0OFtUCkMe0uwqOXilR6J0WjeykyFa7miqrM+Ph73YDAG4dm42zeyT5eAYjTK/F9WOycNWIDHy3LR8frjuO42X1WLy7EIt3y+/RqNMgKcqIpGgjkqOM6J4YgR7JUeiZEoVeKVGIj1SPGq0/UobNJyug1XCYHgRhIR4cXdNk53Q9B4sOL8KG/A3NEhZiH4sovRxZyYrNQo/YHjhWfQzrzqzDRTkXNXn9SiIMOlw1IhNXjcgEz/Mor7fgeGk9jpfW4XhZPY6V1OFAYQ0Kqk04XFyHw8V1Xtd3qrwBO/KqsFAYR5+ZEIGxvZIwOicR/dKjkZ0U1e6NyxuPlWHOwu2w2B0Yn5uMV64YjORoo/S4w8Fjy8kKfLP1DBbvLsC+gho88v0ePPfrAUzqm4JzeydjWGY8kqON4HlmYq5qsKK60YrqRgtqGm2ICtMhIz4CWUkRiO5ABlqe57HtVCX+OFiCIyV1qG604kAh+77edE4WwvSejZuAHLFICEuAhtNgVPooLDu5DH8W/BkUYaHltCyCrDHA4rC0is+iuN651BQIXirkTC2bmO0qLChi0UHxFLGYmjUVS44vQYOtAUnhSZh31jy8vfNt5Nfl44uDX+DWgbc26fU4jkOUUYcoow7ZSerlWg4Hj/yqRhwpqcXh4jocKa7zKTiSo40Yk5OIMT0SMSYnEd0TI1pEaNgdPO7/aifK6izonRqNB6cGPm/BqNPimlGZuHpkBvbkV2Px7kLsPlOFI8V1KK+3wGxzIL+qEfkeTK8p0Ub0SY9B79QopMaEITnaCI7j8MrvhwAA143uji5xzb968fTdkIRFwYZmrd81FSJyXuZ5OLbnGP7I+yNowkIJx3FMuEUZMTLbeYJjSa0Ju09X41BxLRotdphtdkQYdEiINCA+kqXtwvRaFFWbsCe/GjvyKrEjrwp5FQ34YlMevhCEhlGnQXZSJHokR6FHciR6pEShV0o0eqZEwaBr+4jb/oIa3PHZNljsDkwbkIY3rx7qFgnUaDiMyknEqJxE/Ouivvh22xks3HQKJ8sb8OPOAvy4s8Dv1+M4doExJCMOgzPiMDQjDr3ToqFvB9FHV/48Vo5nl+zH3vwat8dykiPx9ym+Z4RUmasAyAbLs7ucjWUnl2HFqRWYM2ROk49NYuVEmC4MHMchUh8Ji9mCClNFUCpOPGF32HGokh1fsmOzpfuDngqJZsJCTLmHVMTi7bffxksvvYSioiIMHjwYb775JkaObF8jiMsay/Dcpudwac9LPV5VmmwmKRztevIYnT4av8/6HWvPrMWYLmOkCMaj6x/FJ3s/wRW5V0jjbYONRsMhIyECGQkROE/RjlopOI4IV5VHSpjIKK014+ddBfh5FzvYpceGYUxOIkZmJ2Bgt1jkpjb/IFZZb8FTv+zD+qNlCNdr8dY1Q31euXiD4zgM6haHQQqHeYPFhrJaFsEpqzOjpNaMk2X1OFZah6MldThT2YiSWjNKakudQvgiydFG/H1y84YjiUj+mzDn78aotFHQcTqcqjmFE9UnnA40gVBnYd8913THeZnn4YM9H2B9/nqY7Wbp6qU1SIkOw+R+YZjsR/8PMSpUZ7Zh0/FyrDtShl1nqnCwsNZFAMvoNBx6pkShR0oUkqOMSIw0ICHKgJgwPaLDdIiWfrLfIw3aoAvkY6V1uOGTzag12zAyOwH/uWqIz/RifKQBt43PwS1js7H1VCVWHyrBuiNlOFxcC7Ng8NRrOcSG66V/MeF61DRakVfRiLI6M46WsO/wt9vY1akovronRqB7ovAzgf1Mjw1r9ZRng8WGF5cdwoKNJwEAEQYtzu+XiqGZ8UiMMiDSqMPQjDi/9nllKgQAJnefjGc3PYtj1cewt2wvBiZ7bwfuCUlYaFmHzgFJA7Aufx22Fm9F/6T+TVqnPxytOop6az0i9ZHoGddTur+lUiEdvSokYGHx9ddfY968eXj33XcxatQovPbaa5g6dSoOHTqElJSUltjGJvH+7vex/NRy7Cnbg6WXL5VCVkrEE4dBY0C0Ptrt8VhjLKb3mC7dvjD7Qny892McrTqKd3e9i4dHPtxyb0AFT4LDZLVjR14V/jxejr+OlWPH6UoUVpvw/Y58fL+DfWF1Gg5psWFIjw1DpFEHo04Do04LHoDFZofZ5oBF+GeWftoVvztQb7GB5wGthsOLswahV6r7Z9ZcIgw6ZCbqPObs6802HCquxcHCWhwpYYKqrM4Mk9WBwd1icdeEns1q4a3EU8QiyhCFMV3GYF3+Oiw+vhj3Dr23Seuvtcrlpkr6JfZDSkQKShpKsKlwU7PSLa1BlFGHSX1TMakv+07aHTxOVzTgeFkdjpfKovBgUS1qTTZVweEJjmPrF4VHlFEWHVGiADHqYNBpoNdqpJ/hei0ijVpEGNhzIgxa6LUabDlZgeeWHEBZnQV90qLxwfXDAxLHGg2HkdkJGJmdgIcuYGK/UaiwifAigsrqzNh1ugo7hX+7TlehxstnodNw6BYfjszESGQlRiA1JgxxEXpEh+lh0Gpg1GtgFN6vUaeFQSf+rpF+N2jZbX+E2abj5Xjou92S5+uaUZl4YEouEqOaJmqV5k2AReUmd5+MX4//iu+Pft9kYSF22RT9FCPTRmJd/jpsKdqCG/rf0KR1+sPOkp0AgEFJg6BVDEcLdsRCLGsXIxYhkwp59dVXcdttt+Gmm24CALz77rv49ddf8fHHH+Of//xn0DfQX4rqi6SSI7PdjJ+O/iTd/8uxXzAqfZTbcw5XsOE4ieGJfu18Wo0WD414CLcvvx1fHvwSg5IHYXDy4CC+i6bTPRXonhqF2WOiYLJ2w54z1dh+uhL78mtwqLgGdSY78muBfP+O5+pogZ4pkbhvUi+c1R0oqPM/FBxM0hKAtAQdJvR3n8ToQAUKvNsD/OZMHbuydI1YAMD0HtOxLn8dFuxdgBk9ZqgKV1+I8xNcUyEaToOJGRPx9aGvsfTEUqcrpI6CIQzo0w3o0y0MQBiAJNYSudaMo8V1OFPZgKpGK6rqLahstKLOZEO92YZ6i/DTbIdNGO5XZwPq6gAE6e8KAL26ROGVqzJRby9FfZDWW+3j3NI3A+ibEY2rEQ2HoxvyqxpxurIB+YKJtqC6EfmVjSioMsFqd+BUNXCqGlh3vHnbxQQXB4NWA70gvIw6DSKNOoTptCitY1FBAEhLMOLhaX0wKjsRZpQ3eV8qbWTRRDEVAgAze83Er8d/xQ9HfsCU7lOQFZMV8Hrza9kJOEzHIhYj01mkfGvxVpypPQMN1zJRnk1FmwAAQ1KGON0v7vdF9UVNfn2rwyq1NXD1WBQ3FDf5OJsakeokglqTgI6GFosF27ZtwyOPPCLdp9FoMHnyZPz555+qzzGbzTCbZdVVU+OetwsG1/x6jfRlduXxjY97fa7aicMTY7qMwbTsaVh6YikeWtsBJiQaAGQgaL3bigE8uhXA1iCtsAMgVggpmZgxEZH6SNRb63HRD83zQahFyyZlTsLXh77G4uOLsfj44matv0Mg6g/FzZakCMBs9yn1bQsHIAEwJgAtkfyyCv/ciAeihPN/PYDHtwPYHpzXVBqfR6SNwLSsaVh6cinuWH5Hs9YrRix6x/dGjCEGNZYaTPt+WrPW6Q9Dkoc43Y7Uyz655r5+pD5SSq+LwuLFLS/ixS0vNml9q65c5dT4sTUJSFiUlZXBbrcjNdU5/5qamoqDBw+qPmf+/Pl46qmnmr6FfmLQGpxy0QatAfcOvRdfHPgChfWFHp+n5bQBG+SeHfss0iLTsOjQoqAMnyHaL4lhiRidPtrt/jBdGB4c/iA+3fcpiuqLwKNpM1GGpAxBaqS7n2F42nCclXoW9pbtbdJ6CYKX/pPvUd4U2+9zYH6nYHu9e8b1RK/4Xk73PTb6MZyoOYET1SeavF4Np8EFWWxgpFajxd/6/g2f7PukxZtk9YzriWGpw5zu6xrVFX8/6+/44cgPXs8zvuDA4bKel0mR88ndJ2Nr8dYOe37h+ACmRBUUFKBr167YuHEjxowZI93/0EMPYc2aNdi0aZPbc9QiFhkZGaiurkZMTPNq9AmCIAiCaB1qamoQGxvr8/wdUMQiKSkJWq0WxcXFTvcXFxcjLU29fbLRaITR2HqudoIgCIIg2o6AnCYGgwFnnXUWVq6UR+A6HA6sXLnSKYJBEARBEERoErCVfd68ebjhhhswfPhwjBw5Eq+99hrq6+ulKhGCIAiCIEKXgIXFVVddhdLSUjz++OMoKirCkCFDsGzZMjdDJ0EQBEEQoUdA5s1g4K/5gyAIgiCI9oO/5+/216ieIAiCIIgOCwkLgiAIgiCCBgkLgiAIgiCCBgkLgiAIgiCCBgkLgiAIgiCCBgkLgiAIgiCCBgkLgiAIgiCCBgkLgiAIgiCCBgkLgiAIgiCCRsAtvZuL2OizpqamtV+aIAiCIIgmIp63fTXsbnVhUVtbCwDIyMho7ZcmCIIgCKKZ1NbWIjY21uPjrT4rxOFwoKCgANHR0eA4LmjrrampQUZGBk6fPt1pZ5B09vfY2d8f0PnfY2d/f0Dnf4+d/f0Bnf89ttT743ketbW16NKlCzQaz06KVo9YaDQadOvWrcXWHxMT0ym/KEo6+3vs7O8P6PzvsbO/P6Dzv8fO/v7+v737jamq/uMA/ubfvcIIrnSBCxX/hHDEnyUm3Vrmxp1CruzPAzMeYDWchpts6lJbUT7Bra2tWvNJS3vQYtVEW2GLQCjbFYW4AVo3YdeoxoWEgRCiwv38HjjOfof/4Ylzz937td3ter5f7j5vPwf47HIOAIGf8b/IN987FVN48SYRERFphoMFERERaSZgBguz2YzKykqYzWa9S/nPBHrGQM8HBH7GQM8HBH7GQM8HBH5GvfMt+8WbREREFLgC5h0LIiIi0h8HCyIiItIMBwsiIiLSDAcLIiIi0kzADBYffPABUlJSsGLFChQUFOD8+fN6l7Qkb775JoKCglSP1atXK+vj4+MoLy/H3XffjcjISDz33HPo6+vTseKFff/993jyySeRmJiIoKAgnDx5UrUuInjjjTeQkJCA8PBwOBwOXL58WbVncHAQJSUliIqKgsViwcsvv4zR0dFlTDG3hfJt3759Rk+LiopUe/w5X1VVFR566CHcddddiIuLw9NPPw23263as5jzsqenB5s3b0ZERATi4uKwf/9+TExMLGeUOS0m44YNG2b0cefOnao9/prx6NGjyM3NVX5hkt1ux+nTp5V1o/cPWDijkfs3myNHjiAoKAgVFRXKMb/powSA6upqMZlM8tFHH8nFixelrKxMLBaL9PX16V3av1ZZWSkPPPCA9Pb2Ko+///5bWd+5c6fcd999Ul9fLy0tLfLwww/LI488omPFC6utrZXXXntNTpw4IQCkpqZGtX7kyBGJjo6WkydPys8//yxPPfWUpKamyvXr15U9RUVFkpeXJ+fOnZMffvhB0tPTZdu2bcucZHYL5SstLZWioiJVTwcHB1V7/Dnfpk2b5NixY9LZ2Skul0ueeOIJSUpKktHRUWXPQuflxMSEZGdni8PhkLa2NqmtrRWr1SoHDx7UI9IMi8n4+OOPS1lZmaqPw8PDyro/Z/zyyy/l66+/lt9++03cbrccOnRIwsLCpLOzU0SM3z+RhTMauX/TnT9/XlJSUiQ3N1f27NmjHPeXPgbEYLFu3TopLy9X/j05OSmJiYlSVVWlY1VLU1lZKXl5ebOuDQ0NSVhYmHz++efKsV9++UUAiNPpXKYK78z0b7w+n09sNpu8/fbbyrGhoSExm83y6aefiojIpUuXBIBcuHBB2XP69GkJCgqSv/76a9lqX4y5BostW7bM+TFGyici0t/fLwCkqalJRBZ3XtbW1kpwcLB4vV5lz9GjRyUqKkpu3LixvAEWYXpGkdvfmP7/i/h0Rsu4cuVK+fDDDwOyf1OmMooETv9GRkYkIyND6urqVJn8qY+G/1HIzZs30draCofDoRwLDg6Gw+GA0+nUsbKlu3z5MhITE5GWloaSkhL09PQAAFpbW3Hr1i1V1tWrVyMpKcmwWT0eD7xerypTdHQ0CgoKlExOpxMWiwVr165V9jgcDgQHB6O5uXnZa16KxsZGxMXFITMzE7t27cLAwICyZrR8w8PDAICYmBgAizsvnU4ncnJyEB8fr+zZtGkTrl27hosXLy5j9YszPeOUTz75BFarFdnZ2Th48CDGxsaUNaNknJycRHV1Nf755x/Y7faA7N/0jFMCoX/l5eXYvHmzql+Af30eLvsfIdPa1atXMTk5qfqPAoD4+Hj8+uuvOlW1dAUFBTh+/DgyMzPR29uLt956C4899hg6Ozvh9XphMplgsVhUHxMfHw+v16tPwXdoqu7Z+je15vV6ERcXp1oPDQ1FTEyMIXIXFRXh2WefRWpqKrq7u3Ho0CEUFxfD6XQiJCTEUPl8Ph8qKirw6KOPIjs7GwAWdV56vd5Zezy15k9mywgAL7zwApKTk5GYmIj29na8+uqrcLvdOHHiBAD/z9jR0QG73Y7x8XFERkaipqYGWVlZcLlcAdO/uTICxu8fAFRXV+Onn37ChQsXZqz50+eh4QeLQFNcXKw8z83NRUFBAZKTk/HZZ58hPDxcx8poqZ5//nnleU5ODnJzc7Fq1So0NjaisLBQx8r+vfLycnR2duLs2bN6l/KfmSvjjh07lOc5OTlISEhAYWEhuru7sWrVquUu81/LzMyEy+XC8PAwvvjiC5SWlqKpqUnvsjQ1V8asrCzD9++PP/7Anj17UFdXhxUrVuhdzrwM/6MQq9WKkJCQGVe+9vX1wWaz6VSVdiwWC+6//350dXXBZrPh5s2bGBoaUu0xctapuufrn81mQ39/v2p9YmICg4ODhsydlpYGq9WKrq4uAMbJt3v3bnz11Vc4c+YM7r33XuX4Ys5Lm802a4+n1vzFXBlnU1BQAACqPvpzRpPJhPT0dOTn56Oqqgp5eXl49913A6p/c2WcjdH619raiv7+fqxZswahoaEIDQ1FU1MT3nvvPYSGhiI+Pt5v+mj4wcJkMiE/Px/19fXKMZ/Ph/r6etXP1oxqdHQU3d3dSEhIQH5+PsLCwlRZ3W43enp6DJs1NTUVNptNlenatWtobm5WMtntdgwNDaG1tVXZ09DQAJ/Pp3xxMJI///wTAwMDSEhIAOD/+UQEu3fvRk1NDRoaGpCamqpaX8x5abfb0dHRoRqg6urqEBUVpbxVraeFMs7G5XIBgKqP/pxxOp/Phxs3bgRE/+YylXE2RutfYWEhOjo64HK5lMfatWtRUlKiPPebPmp2GaiOqqurxWw2y/Hjx+XSpUuyY8cOsVgsqitfjWLv3r3S2NgoHo9HfvzxR3E4HGK1WqW/v19Ebt9OlJSUJA0NDdLS0iJ2u13sdrvOVc9vZGRE2trapK2tTQDIO++8I21tbfL777+LyO3bTS0Wi5w6dUra29tly5Yts95u+uCDD0pzc7OcPXtWMjIy/OZ2zPnyjYyMyL59+8TpdIrH45HvvvtO1qxZIxkZGTI+Pq68hj/n27Vrl0RHR0tjY6PqVr2xsTFlz0Ln5dRtbhs3bhSXyyXffPONxMbG+s2tfAtl7OrqksOHD0tLS4t4PB45deqUpKWlyfr165XX8OeMBw4ckKamJvF4PNLe3i4HDhyQoKAg+fbbb0XE+P0TmT+j0fs3l+l3uvhLHwNisBARef/99yUpKUlMJpOsW7dOzp07p3dJS7J161ZJSEgQk8kk99xzj2zdulW6urqU9evXr8srr7wiK1eulIiICHnmmWekt7dXx4oXdubMGQEw41FaWioit285ff311yU+Pl7MZrMUFhaK2+1WvcbAwIBs27ZNIiMjJSoqSl588UUZGRnRIc1M8+UbGxuTjRs3SmxsrISFhUlycrKUlZXNGHr9Od9s2QDIsWPHlD2LOS+vXLkixcXFEh4eLlarVfbu3Su3bt1a5jSzWyhjT0+PrF+/XmJiYsRsNkt6errs379f9XsQRPw340svvSTJycliMpkkNjZWCgsLlaFCxPj9E5k/o9H7N5fpg4W/9JF/Np2IiIg0Y/hrLIiIiMh/cLAgIiIizXCwICIiIs1wsCAiIiLNcLAgIiIizXCwICIiIs1wsCAiIiLNcLAgIiIizXCwICJNbNiwARUVFXqXQUQ642BBREREmuGv9CaiO7Z9+3Z8/PHHqmMejwcpKSn6FEREuuFgQUR3bHh4GMXFxcjOzsbhw4cBALGxsQgJCdG5MiJabqF6F0BExhcdHQ2TyYSIiAjYbDa9yyEiHfEaCyIiItIMBwsiIiLSDAcLItKEyWTC5OSk3mUQkc44WBCRJlJSUtDc3IwrV67g6tWr8Pl8epdERDrgYEFEmti3bx9CQkKQlZWF2NhY9PT06F0SEemAt5sSERGRZviOBREREWmGgwURERFphoMFERERaYaDBREREWmGgwURERFphoMFERERaYaDBREREWmGgwURERFphoMFERERaYaDBREREWmGgwURERFphoMFERERaeZ/NUMGHusWVYAAAAAASUVORK5CYII=", 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "max_t = 400\n", + "\n", + "ppo_2o_UM3_ep[ppo_2o_UM3_ep.t Date: Thu, 6 Jun 2024 18:46:03 +0000 Subject: [PATCH 63/64] updated results notebooks --- notebooks/for_results/2_reward_distr.ipynb | 333 +++++------ notebooks/for_results/3_policy_plots.ipynb | 4 +- notebooks/for_results/4_episode_plots.ipynb | 593 ++++++++++++++++++-- 3 files changed, 674 insertions(+), 256 deletions(-) diff --git a/notebooks/for_results/2_reward_distr.ipynb b/notebooks/for_results/2_reward_distr.ipynb index b71230d..8af97b4 100644 --- a/notebooks/for_results/2_reward_distr.ipynb +++ b/notebooks/for_results/2_reward_distr.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 1, "id": "0e5ee484-d06a-44ef-b263-6488207bc9b0", "metadata": {}, "outputs": [], @@ -45,13 +45,9 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 2, "id": "7fc4fa4a-95d8-452c-beb9-d01b9578e764", - "metadata": { - "jupyter": { - "source_hidden": true - } - }, + "metadata": {}, "outputs": [], "source": [ "## UM1\n", @@ -133,16 +129,14 @@ { "cell_type": "markdown", "id": "e47f7d71-7186-45fd-a019-8ab3019fbae2", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## Load" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "b2ad8d67-5113-4747-bd0f-28111e1ee572", "metadata": {}, "outputs": [], @@ -162,7 +156,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "89f24e34-7302-4d8f-afca-4671d55355b7", "metadata": {}, "outputs": [], @@ -182,143 +176,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "2146eba9-ad8e-4e4b-90fc-84bc650f3477", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true - }, "scrolled": true }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2017439f0195413e8026e831d4b9b334", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "(…)PPO-AsmEnv-2obs-UM1-64-32-16-chkpnt3.zip: 0%| | 0.00/106k [00:00,
)" + "(
,\n", + "
,\n", + "
)" ] }, - "execution_count": 38, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -578,6 +466,7 @@ "(\n", " ggplot(fixed_pol_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", " ggplot(ppo_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + " ggplot(results_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", ")" ] }, @@ -591,7 +480,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 14, "id": "17233ba3-9669-4f49-8fdc-66ce612e75c1", "metadata": { "scrolled": true @@ -601,9 +490,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-05 20:47:42,007\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:47:57,485\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:48:13,228\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-06-06 18:09:31,889\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:09:48,756\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:10:05,022\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], @@ -629,7 +518,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 15, "id": "28b79920-2de2-4a7b-ac9f-a4dcf5c86b09", "metadata": {}, "outputs": [ @@ -637,9 +526,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-05 20:48:34,047\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:48:41,952\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:48:49,682\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-06-06 18:10:21,063\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:10:28,771\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:10:36,460\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], @@ -674,7 +563,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 16, "id": "d66f1288-cb48-4a4f-971e-3b47226cbf32", "metadata": {}, "outputs": [], @@ -692,12 +581,16 @@ " pd.DataFrame(PPO_mw_rews),\n", " pd.DataFrame(PPO_bm_rews),\n", " ]\n", + ")\n", + "\n", + "results_df = pd.concat(\n", + " [pd.DataFrame(CR_rews), pd.DataFrame(Msy_rews), pd.DataFrame(PPO_2o_rews), pd.DataFrame(PPO_bm_rews)]\n", ")" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 17, "id": "467b094f-1948-4a0e-af8b-dd437adc8fe4", "metadata": {}, "outputs": [ @@ -710,7 +603,26 @@ }, { "data": { - "image/png": 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" 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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2Pl8SHYAAAAAAAO9CAAjAY/3555+SJD/fANWOq1ft4zVtUhoA7tixQ3v37q328QAAAAAAcAcEgAA81qZNmyRJdRIby8fHWu3jNW3KPoAAAAAAAO9DAAjAYxkBYFKdxg45XnLd5goMDJVEAAgAAAAA8B4EgAA8Uk5Ojnbu3Cmp+gNADFarrxo3OlcSASAAAAAAwHsQAALwSFu2bJHNZpMkJSU6JgCUpGZNSpcBb9y4UZmZmQ47LgAAAAAAZiEABOCRjOW/UvUnAJdl7ANos9m0YsUKhx0XAAAAAACzEAAC8EibN2+WJAX4Byk6OtFhx23YoI2sVj9JIgAEAAAAAHgFAkAAHmnbtm2SpPj4hvLxcdxLmb9/oBrUbyWJABAAAAAA4B0IAAF4JCMArF27vsOP3aTxeZKk33//XYWFhQ4/PgAAAAAArkQACMDjlJSU2APAhPiGDj9+4xMBYF5env744w+HHx8AAAAAAFciAATgcXbt2qWCggJJTuoAbHSu/TbLgAEAAAAAno4AEIDHMbr/JOd0AIaHxyourp4kAkAAAAAAgOcjAATgcbZu3Wq/HV+7gVPOYewDuGLFCtlsNqecAwAAAAAAVyAABOBxjA7AkJBwhYZGOuUcRgC4b98+paWlOeUcAAAAAAC4AgEgAI9jdADG124gi8XilHMYAaDEMmAAAAAAgGcjAATgcYwOwNpOWv4rSXUSGis4OEwSASAAAAAAwLMRAALwKIWFhdq5c6ckKSHeeQGgj4+PGjf6ex9AAAAAAAA8FQEgAI+Snp6u4uJiSc7tAJSkJo3OlST9+eefyszMdOq5AAAAAABwFgJAAB7F6P6TpLjYZKeeq/GJfQBtNptWrVrl1HMBAAAAAOAsBIAAPErZibyxsXWdeq6Uhm1ltfpKYhkwAAAAAMBzEQAC8ChGB2CAf5DCakU79VwBAUGql9xCEgEgAAAAAMBzEQAC8ChGB2BsXLIsFovTz9fkxDLgVatWqaioyOnnAwAAAADA0QgAAXgUowMwNsa5y38NRgCYm5urtWvXuuScAAAAAAA4EgEgAI9i7wB08v5/hsYnJgFL0q+//uqScwIAAAAA4EgEgAA8RnZ2tg4fPixJinNRB2BkZLy925AAEAAAAADgiQgAAXgMY/mvJMXGJrvsvI1PLANeunSpy84JAAAAAICjEAAC8BjG8l/JdUuApb/3AczIyChXAwAAAAAAnoAAEIDHKNcB6KIlwNLfAaAkLVmyxGXnBQAAAADAEQgAAXgMo/suNDRSQUGhLjtvUmITBQXVkkQACAAAAADwPASAADyGEQDGuXD/P0ny8bGqUUo7SQSAAAAAAADPQwAIwGOkp6dLkmJiklx+bmMZ8Lp163Ts2DGXnx8AAAAAgKoiAATgMXbt2iVJiolOdPm5jUnAJSUlWrZsmcvPDwAAAABAVREAAvAI2dnZyszMlCRFRSW4/PyNGraTj49VkrR06VKXnx8AAAAAgKoiAATgEYzuP0mKNqEDMDAwRPXrtZAk/frrry4/PwAAAAAAVUUACMAjlAsATegAlKRmTTtIkpYvX67i4mJTagAAAAAA4GwRAALwCOUDwDqm1NC0SWkAeOzYMW3cuNGUGgAAAAAAOFsEgAA8ghEA+vr6q1ataFNqMDoAJWnFihWm1AAAAAAAwNkiAATgEYwAMCoqQT4+5rx0xcQk2icQEwACAAAAADwFASAAj7B7925J5i3/NZxzTkdJ0pIlS2Sz2UytBQAAAACAyiAABOARjA5AswaAGFq17CZJ2rdvn7Zs2WJqLQAAAAAAVAYBIAC3Z7PZ/g4ATyzBNUvrlt3ttxctWmRiJQAAAAAAVA4BIAC3d/jwYeXn50sq3QPQTHFxyYqvXV+S9PPPP5taCwAAAAAAlUEACMDtGd1/kvl7AEpSqxNdgEuWLFFRUZHJ1QAAAAAAcHoEgADcnjEARDJ/CbAktW5VGgBmZWVp7dq1JlcDAAAAAMDpEQACcHsZGRn222YPAZGkli26ymKxSJJ++uknk6sBAAAAAOD0CAABuD2jAzAwMFTBwWEmVyOFhUWrYYM2kqQffvjB5GoAAAAAADg9AkAAbs/YAzAm2vz9/wxt2/SWJP3+++86cOCAydUAAAAAAFAxAkAAbs9YAhzlBgNADEYAaLPZNH/+fJOrAQAAAACgYgSAANyesQTYHfb/M9RLbqnw8FhJLAMGAAAAALg3AkAAbq24uFh79uyR5F4dgD4+PmrburQL8KefftLx48dNrggAAAAAgFMjAATg1vbv36/i4mJJUrQb7QEoSe3a9pUkHTt2TD///LPJ1QAAAAAAcGoEgADcmrH/nyRFu1EHoCS1btVDgYEhkqQ5c+aYXA0AAAAAAKdGAAjArRnLfyUpyo32AJQkf/9AtW/bT5L07bffsgwYAAAAAOCWCAABuLW9e/fab0dG1DaxklO7oMNgSVJmZqYWLVpkcjUAAAAAAJyMABCAWzMCwKCgWvbltu6kVcvuCgqqJUn64osvzC0GAAAAAIBTIAAE4Nb27dsnyT27/6TSZcDntR8gSfrqq6+UmZlpckUAAAAAAJRHAAjArRl7AEZExJlcScV69RwmScrLy9Mnn3xicjUAAAAAAJRHAAjArRlLgKMi402upGKNG52npMQmkqT3339fNpvN5IoAAAAAAPgbASAAt2YEgBFuugRYkiwWi3r3vE6StGnTJi1btsyhxz9y5Ij27t2rkpIShx4XAAAAAFAzEAACcFvZ2dk6duyYJCky0n0DQEnq0vkyBfgHSZJefPHFah9v3759+u9//6v27durSZMmatWqlZo0aaJHHnlEBw4cqPbxAQAAAAA1BwEgALdlDACR3HcIiCEkJFz9+t4gSVq4cKFWrFhRpeMUFxdrypQpuuCCC/Tcc88pPT3dfl9mZqamTZumrl27OrzLEAAAAADgvQgAAbgtY/mvJEW68R6AhoEX3q6AgGBJ0vPPP3/WewEeOnRI11xzjUaPHq2cnBxJUpMm5+v6657SLTc9r3NPTBs+fPiwrr76aq1evdqxnwAAAAAAwCsRAAJwW+UCQDfvAJSksLBo9etT2gW4aNEiff7555V+7u+//66+fftq4cKFkqQ6CY00bvSnenzMZ+rf7yb17HGN7r93su6+63VZrb7Kzc3VjTfeqMOHDzvjUwEAAAAAeBECQABuq2wAGB4ea2IllTd08EhFRSVIkv7973+X+xxOxWaz6d1339XgwYOVkZEhSerZ/Ro9/dS3atb0gpMe37HDEI248TlJ0p49ezR69GgHfwYAAAAAAG9DAAjAbe3Zs0eSVKtWlPz8AkyupnKCg8N0y03PS5KOHj2qESNGKC8v75SPzc7O1siRI/Xwww/r+PHj8vMN0IibntMtNz8vf//ACs/RvduV6tzpUknS559/riVLljj+EwEAAAAAeA0CQABuy+iei4xw//3/ymrdqof69r5ekrRixQpdfvnlSktLs99fWFio2bNnq0uXLvr0008lSbExdfX4uM/Uq8ewSp3jumvGKTgoTJI0ceLEs95vEAAAAABQc/iaXQAAVMQeAEa6//5//zT82id0+Mgerf79B61cuVIdO3ZUly5dFBoaqmXLlungwYP2x7Zr21d33PqiQkIiKn388PBYDbzoNs36/L9auXKlFi9erB49ejjhMwEAAAAAeDo6AAG4rX379kmSIjxgAMg/+fr6adTdb+nCAbfIYrGosLBQCxcu1Ndff20P/yIi4jTyjtf0wKipZxX+GQb0u1lBQbUkSVOnTnVk+QAAAAAAL0IHIAC3ZLPZ7HsAesIE4FOxWn01fNjj6t71Sv20cKa2bV+roqLjql27vjp2GKy2bfqcdq+/MwkKClW3rldo3g/T9P333ysjI0NJSUkO/AwAAAAAAN6AABCAWzp69KgKCgokeeYS4LKS656jG/413inH7tv7es37YZpKSkr0/vvva8yYMU45DwAAAADAc7EEGIBbMvb/kzy3A9AV6iSkqEXzLpKk6dOnq6ioyOSKAAAAAADuhgAQgFsylv9Knt8B6GzG5OADBw5o6dKlJlcDAAAAAHA3BIAA3FLZDkBPHALiSmX3Evzyyy9NrgYAAAAA4G4IAAG4JSMA9PGxKjwsxuRq3FtgYIjatOolSfrmm29UXFxsckUAAAAAAHdCAAjALRkBYHh4rHx8rCZX4/46nD9IUuky4GXLlplcDQAAAADAnRAAAnBLRgDIAJDKade2j/z8AiSxDBgAAAAAUB4BIAC3tG/fPklSREScyZV4hsDAELVs3lWS9NNPP5lcDQAAAADAnfiaXQA8g9XqvCWYzjx2TWR8PT3963rgwAFJpQGgj4/7vVfhjjW1bt1Tv6+dr+3btys9PV3169c3u6RK85br1hPwNXYsrl3X4OvrWFy3rsHX17G4bl2Dry/gvQgAUSmRkZFOOa7VanXasWu6sLAws0uoMpvNZg8Ao6PiFRgYaHJF5VksFrerSZLOP6+/3vvgMUnS8uXL1a5dO5MrOnuefN16Al5znYdr13m4bp2H69Z5uG6dh+vWebhuAe9GAIhKOXLkiEOPFxYWJqvVquLiYmVlZTn02DWd1WpVWFiYsrKyPHYabFZWlvLz8yVJISGR9ttmCwgIkMVikc1mU0FBgdnlnCQyoo5iY+rqwMF0ffPNN7r66qvNLqnSvOG6dWe85joP167zcN06D9et83DdOg/XrfO483VLIAk4DgEgKsWZ32T5Bu4cxcXFHvu1NQaASFJYrWiVlJSYWM2puWNNktSyZTf9tPBDLVq0SPn5+fLz8zO7pLPiydetp+Dr6xxcu87F19Y5uG6di6+tc3DdOhdfW8B7ud8mVgBqvP3799tvh4fHmliJ52ndsock6dixY1q9erXJ1QAAAAAA3AEBIAC3Y+z/J0nhYQSAZ6P5OZ3st5ctW2ZiJQAAAAAAd0EACMDtlA0Aw8JjTKzE84SERCgpqamk0kEgAAAAAAAQAAJwO0YA6OcXoKDAUJOr8TxNG58vSVqxYoXb7lUIAAAAAHAdAkAAbsfYAzA8LFYWi8XkajxP0yYdJEmZmZnatGmTydUAAAAAAMxGAAjA7RgdgAwAqZomTc6332YZMAAAAACAABCA2/k7AGT/v6qIiU5UdFQdSQSAAAAAAAACQABuyB4AhhEAVpXRBUgACAAAAAAgAATgVmw2m30PwLAwlgBXVeOU9pKkjIwM7du3z+RqAAAAAABmIgAE4Fays7OVn58viSXA1dGwQRv77bVr15pYCQAAAADAbASAANyK0f0nSREMAamy5OTmslp9JUm///67ydUAAAAAAMxEAAjArRj7/0lSGHsAVpm/f6CSkppJIgAEAAAAgJqOABCAWykbAIbTAVgtDRu0liStWbNGNpvN5GoAAAAAAGYhAATgVsouAWYKcPUY+wAeOnRI6enpJlcDAAAAADALASAAt2J0APr5BigoqJbJ1Xi2soNAWAYMAAAAADUXASAAt2IEgOHhsbJYLCZX49mSEpvIzy9AUukyYAAAAABAzUQACMCt/B0Asvy3uqxWX9VLbiFJWr9+vcnVAAAAAADMQgAIwK0YASATgB0jue45kqQNGzaYXAkAAAAAwCwEgADcijEEhAEgjpGc3FxSabC6b98+k6sBAAAAAJiBABCA27DZbOX2AET1GR2AEsuAAQAAAKCmIgAE4DZycnKUl5cniQDQUeomNbMPU2EZMAAAAADUTASAANyGsfxXYgmwowQFhSourp4kOgABAAAAoKYiAATgNsoFgHQAOgyDQAAAAACgZiMABOA2jP3/JKYAO1K95BaSpNTUVPsSawAAAABAzUEACMBtlA0AWQLsOEYHYElJiTZt2mRyNQAAAAAAVyMABOA2jADQzzdAwcFhJlfjPeomNbPfJgAEAAAAgJqHABCA2zACwLDwGPvkWlRfdHSiAgKCJUmbN282uRoAAAAAgKsRAAJwG8YQEJb/OpaPj4/q1GkkSfrrr79MrgYAAAAA4GoEgADchtEBSADoeIl1GkuiAxAAAAAAaiICQABuwx4AhseaXIn3SUpsIknauXOncnJyTK4GAAAAAOBKBIAA3AYBoPMYHYCSlJqaamIlAAAAAABXIwAE4Bays7OVm5sriSXAzlA2AGQfQAAAAACoWQgAAbgFYwCIVDoFGI4VE1NX/v6BkqRNmzaZXA0AAAAAwJUIAAG4BWP5rySFh7EE2NF8fHxUJ6F0EjCDQAAAAACgZiEABOAWygWA7AHoFMYyYJYAAwAAAEDNQgAIwC2U7wBkCbAzJJaZBJyXl2dyNQAAAAAAVyEABOAWjADQ19dfwcFhJlfjnRITSzsAbTabtmzZYnI1AAAAAABXIQAE4BaMISDhYTGyWCwmV+OdEus0sd9mH0AAAAAAqDkIAAG4BaMDkAnAzhMXW1d+fgGS2AcQAAAAAGoSAkAAbsEIACOYAOw0Pj5W+yRgAkAAAAAAqDkIAAG4hb87AAkAnalOndIAcOvWrSZXAgAAAABwFQJAAG6h7B6AcJ742g0kSdu3b1dRUZHJ1QAAAAAAXIEAEIDpsrOzlZubK0kKZw9Ap0qIbyhJKiwsVHp6usnVAAAAAABcgQAQgOmM5b8SHYDOFh/fwH6bZcAAAAAAUDMQAAIwXbkAMDzOxEq8n7EEWCIABAAAAICaggAQgOnoAHSd4OAwhZ+YtEwACAAAAAA1AwEgANMZA0Ak9gB0BWMZ8LZt20yuBAAAAADgCgSAAExndAD6+vorODjc5Gq8X/yJQSB0AAIAAABAzUAACMB0RgAYFhYti8VicjXeL+FEB2BGRoby8vJMrgYAAAAA4GwEgABMZwSA4eGxJldSM8TXbmi/vX37dhMrAQAAAAC4AgEgANMZewAyAMQ1jA5AiWXAAAAAAFATEAACMJ29AzCMDkBXiIurZ19qTQAIAAAAAN6PABCA6YwOwDAmALuEn1+AYmKSJBEAAgAAAEBNQAAIwFQ5OTnKzc2VxBJgVzL2ASQABAAAAADvRwAIwFTG8l9JimAIiMsY+wASAAIAAACA9yMABGAqY/mvJIWxB6DLxMeXdgAePnxYhw8fNrkaAAAAAIAzEQACMFXZDsBw9gB0mYQTAaAkbdu2zcRKAAAAAADORgAIwFTlAkA6AF2mdlw9++0dO3aYVwgAAAAAwOkIAAGYyggArVY/hYSEm1xNzREdnSir1VcSASAAAAAAeDsCQACmMgLA8PAYWSwWk6upOaxWX0VHJ0qStm/fbnI1AAAAAABnIgAEYCpjCEh4GPv/uZqxDHjnzp0mVwIAAAAAcCYCQACmMgJAJgC7XtyJAJAlwAAAAADg3QgAAZiq7BJguFZcbLIkad++fcrNzTW5GgAAAACAsxAAAjDV3wEgHYCuFldmEjDLgAEAAADAexEAAjBNTk6OcnJyJLEHoBlqlwkAWQYMAAAAAN6LABCAaYzuP0kKZw9AlzOWAEsEgAAAAADgzQgAAZimXADIHoAuFxgYYg9et2/fbnI1AAAAAABnIQAEYJryHYAEgGaIiyvtAqQDEAAAAAC8FwEgANOU7wCMM7GSmsvYB5AAEAAAAAC8FwEgANMYAaDV6qeQkHCTq6mZjEnA6enpKi4uNrkaAAAAAIAzEAACMM3+/fslSWFh0bJYLCZXUzMZAWBRUZF27dplcjUAAAAAAGcgAARgGiMAZP8/8xhLgCWWAQMAAACAtyIABGAaYwlweHisyZXUXHEEgAAAAADg9QgAAZiGANB8YbWiFRgYIokAEAAAAAC8FQEgANOwBNh8FotFcbHJkqTt27ebXA0AAAAAwBkIAAGYIjc3Vzk5OZIIAM1mLAOmAxAAAAAAvBMBIABTGMt/JSmMJcCmiov9OwC02WwmVwMAAAAAcDQCQACmKBsA0gFortpxpUuAs7OzdejQIZOrAQAAAAA4GgEgAFOUDQAj6AA0VdlJwDt37jSxEgAAAACAMxAAAjCFMQBEYgmw2WqXCQDZBxAAAAAAvA8BIABTGB2AVquvQoLDTa6mZouOTpTV6iuJABAAAAAAvBEBIABTGB2AYbWi5ePDS5GZrFZfRUfVkcQSYAAAAADwRvzWDcAURgcgy3/dQ2xsXUlSWlqayZUAAAAAAByNABCAKYwAkAEg7iEmhgAQAAAAALyVr9kFuFJmZqZmzZqlFStW6NChQwoICFBKSooGDhyojh07Vvm4RUVF+vrrr7Vo0SLt3r1bkpSYmKgePXpo0KBB8vU99Zd537592rhxo1JTU7V161Zt27ZN+fn5kqQvv/zytOfct2+fbr311jPW9uijj6pLly5n+RkBzmdfAhwWY3IlkKS4EwHg7t27VVRUVOHrFgAAAADA89SY3/DS0tI0duxYZWZmSpKCgoKUk5OjNWvWaM2aNRoyZEilArV/ysvL02OPPabNmzdLkvz9/SVJqampSk1N1ZIlSzR+/HgFBgae9NyZM2dqwYIF1fisSoWFhVW4h5pRD+BujA7AcAJAt2AsAS4uLtauXbtUr169MzwDAAAAAOApakQAWFhYqKefflqZmZmqV6+eHnjgATVo0EAFBQWaM2eOZsyYoa+++koNGjRQ3759z+rYb7zxhjZv3qyQkBDde++99k7CZcuW6ZVXXtGmTZv0v//9T/fff/9Jz7VYLEpISFCjRo2UkpKivLw8ffzxx2f9+b3wwguqXbv2WT8PMEteXp6ys7MlSeEsAXYLMTFJ9ttpaWkEgAAAAADgRWpEAPj9999r7969CggI0OOPP67Y2NLAISAgQFdddZUOHz6sb7/9VtOnT1fPnj0rvfRt+/btWrx4sSTpnnvuUadOnez3derUSSUlJXruuee0cOFCXXbZZSf9Qn333XfLarXa/3/ZsmXV/VQBj2B0/0l0ALoLowNQKp0E3K1bNxOrAQAAAAA4Uo0YArJw4UJJUvfu3e3hX1mXX365LBaLDh8+rD/++KPSx120aJFsNpsSEhLKhX+Gzp07KyEhQTabTYsWLTrp/rLhH1CTGPv/SXQAuouI8Dj5+QVIktLT002uBgAAAADgSF4fAObl5WnLli2SpPbt25/yMbGxsUpKKl3+tnbt2kofe926dZKkdu3ayWKxnHS/xWJRu3btyj0WwD86AMPpAHQHFotFMdGlr4NMAgYAAAAA7+L1S4AzMjJks9kk6bR7WtWrV0/p6emV7nyx2WzKyMg443GTk5MlObej5vnnn9fu3btVUFCg8PBwNWnSRH379tX555/vtHMC1VF+CTAdgO4iNrau9uzdqp07d5pdCgAAAADAgby+A/Dw4cP221FRURU+zrjvyJEjlTpuXl6e8vPzK33cvLw85eXlVerYZ2vLli2y2Wzy8fHRoUOHtHTpUk2YMEHPPfecCgsLnXJOoDqMANDHx6qQkAhzi4GdsQ8gS4ABAAAAwLt4fQegEdJJpUM/KmLcV9mQruzjKnNc4zlBQUGVOv6Z+Pv7a+DAgerWrZsaNGig4OBgSaVL9z777DP99NNPWrJkiUJCQnT33Xef8XjTp0/Xhx9+WOH9w4YN07XXXuuQ2iXJx8fH/t/IyEiHHReyL0cPDw+3d7+6m6ysLEmly39DQkJMrqbyjK+txWJx2L9ld1InoaEkae/evQoKClJgYKDLzu0J160n4zXXebh2nYfr1nm4bp2H69Z5uG6dh+sWqBm8PgD0VpGRkbrjjjtO+nhycrLuv/9+hYWFac6cOfrhhx90ySWX2Pc4rEhOTk65wQz/lJub65ShJRaLhWEoTmJ8I3dH+/btkyRFRMSdcv9MT+CpdZ9O7bhk++2MjAw1bdrU5TW483XrDXjNdR6uXefhunUerlvn4bp1Hq5b5+G6Bbyb1weAZTtYCgoK7J1y/1RQUCBJle7qKfs447mnO+7ZHNsRrrvuOn333Xc6fvy4Vq5cecYAMCQkRHFxcRXeHxwcrOLiYofV5+PjI4vFIpvNppKSEocdF6XfuH18fFRSUuK2747u3btXkhQRHuu2NZ5K2dDPk+qurNjYvwPArVu3qlGjRi47tydct56M11zn4dp1Hq5b5+G6dR6uW+fhunUed75uCSQBx/H6ALDs/nyHDx+uMAA09gqsbMtzUFCQgoKClJeXV26fwYqOazzeVQIDA5WcnKzU1FR7t9XpDB8+XMOHD6/w/oMHD1Z6f8TKiIyMlNVqVUlJiUOPi9JvkpGRkcrMzHRoaOtIe/bskSSFhkQ5bW9MZwgKCrL/cORJdVdWWNjfbwJs3LhRHTp0cNm5PeG69WS85joP167zcN06D9et83DdOg/XrfO483UbExNjdgmA1/D6/umkpCR7105aWlqFjzPuq1u3bqWOa7FY7F11jjwuUBMYQ0DCw/mG7k5CQyIUGFi6J+PpXtcAAAAAAJ7F6wPAoKAgNW7cWJK0evXqUz7m4MGD9qmXbdq0qfSxW7duLUn6/fffK3zMmjVryj3WVfLz8+2/wNeuXdul5wZOJy8vT8eOHZMkhYXFmlwNyrJYLIqNKX2zYufOnSZXAwAAAABwFK8PACWpZ8+ekqTFixfbO4/K+vzzz2Wz2RQVFaVWrVpV+rjdu3eXxWLR7t27tXTp0pPu//XXX7V7925ZLBZ7DY5ypn0vZs6cqePHj8tisej888936LmB6ij7bzAinADQ3cTGlgaAxpsiAAAAAADPVyMCwAEDBig+Pl75+fmaMGGCtm/fLql0QMesWbP0zTffSCrdB8/Xt/y2iLfccouGDh2ql1566aTjNmjQQN27d5ckvfrqq1q2bJlsNptsNpuWLVum1157TVJpAJmcnHzS84uKipSVlWX/U3ZPsbIfz8rKOum5Y8aM0SeffKLt27eX2wMjLS1NL7/8smbPni1J6tev3xkHgACuVDYADGMJsNuJiTnz1gYAAAAAAM/i9UNAJMnPz0/jxo3T2LFjtWPHDo0aNUrBwcHKz8+3TzkaPHiw+vbte9bHvuuuu7Rnzx5t3rxZzzzzjPz9/SVJx48flyQ1a9ZMd9555ymf++eff2rs2LGnvO+fAzm+/PLLcv9/4MABTZ8+XdOnT5fValVwcLCOHz9ebupwjx49dPvtt5/15wQ4U9kAMJwlwG4n7sQS4EOHDik7O1uhoaEmVwQAAAAAqK4aEQBKUnJysl599VV99tlnWrFihQ4ePKiQkBA1bNhQgwYNUseOHat03KCgIE2aNElff/21Fi1apN27d0uSUlJS1LNnTw0aNOikrkJHuPHGG7V27Vpt2bJFR44c0bFjx2S1WpWQkKBmzZqpT58+Lt93EKiM8gEgHYDuJjb2727l9PR0nXPOOSZWAwAAAABwhBoTAEpSRESERowYoREjRlT6OVOmTDnjY3x9fXXJJZfokksuOat6WrVqdVJnX2V17dpVXbt2rdJzATPt379fkuTjY1VoaKTJ1eCfjCXAUukyYAJAAAAAAPB8NWIPQADuwwgAw8Ki5ePDS5C7MYaASEwCBgAAAABvwW/fAFzKWALM/n/uKTiolkJDIiQxCAQAAAAAvAUBIACXMgLAMPb/c1vGMuD09HSTKwEAAAAAOAIBIACXsncAhhMAuitjGTBLgAEAAADAOxAAAnApYw/AiHCWALur2JjSScBpaWmy2WwmVwMAAAAAqC4CQAAuk5+fr2PHjkmSwtgD0G0ZHYDHjh1TZmamydUAAAAAAKqLABCAyxjLfyUpnD0A3VbsiT0AJZYBAwAAAIA3IAAE4DLlAkD2AHRbRgegxCRgAAAAAPAGBIAAXKZ8ByBLgN1VbMzfASCTgAEAAADA8xEAAnAZYwCIJIUzBMRt+fsH2gNalgADAAAAgOcjAATgMkYAaLH4KDQ00uRqcDrGMmCWAAMAAACA5yMABOAyxhLg8PAY+fjw8uPOYk4MAmEJMAAAAAB4Pn4DB+AyRgcg+/+5P6MDMD09XTabzeRqAAAAAADVQQAIwGXsASD7/7m92BMdgLm5uTp48KDJ1QAAAAAAqoMAEIDLEAB6DiYBAwAAAID3IAAE4DLGHoARBIBur2wAyCAQAAAAAPBsBIAAXCInJ0fZ2dmS6AD0BNHRdey3CQABAAAAwLMRAAJwCaP7T6ID0BP4+QUoMqK2JJYAAwAAAICnIwAE4BLG/n+SFMYUYI9gTAKmAxAAAAAAPBsBIACXKBsA0gHoGWJiCAABAAAAwBsQAAJwibJLgNkD0DPExiRJkjIyMmSz2UyuBgAAAABQVQSAAFzC6AD08w1QcHCYydWgMoxJwPn5+eU6OAEAAAAAnoUAEIBLGAFSeHisLBaLydWgMmJik+y3WQYMAAAAAJ6LABCAS5QNAOEZjCXAEpOAAQAAAMCTEQACcIm/A8AYkytBZUVH1ZHFUvptgg5AAAAAAPBcBIAAXMIYAkIHoOfw9fVXVGS8JAJAAAAAAPBkBIAAnM5ms9k7ACMIAD1KzIllwCwBBgAAAADPRQAIwOmysrJUUFAgSQoPjzO5GpyN2NjSScB0AAIAAACA5yIABOB0RvefxBJgT2MMAsnIyFBJSYnJ1QAAAAAAqoIAEIDTlQsAwxgC4kliYko7AI8fP659+/aZXA0AAAAAoCoIAAE4XdkAkD0APUvsiQBQYhkwAAAAAHgqAkAATlc2AAwjAPQoxhJgiQAQAAAAADwVASAApzMCwMDAUAUGBJtcDc5GVFSCfHyskggAAQAAAMBTEQACcDojAGT5r+exWn0VHVVHkpSenm5yNQAAAACAqiAABOB0RgDIBGDPFHNiGTAdgAAAAADgmQgAATjdgQMHJDEB2FMZASAdgAAAAADgmQgAATjd3x2AcSZXgqqIiy2dBJyRkaHi4mKTqwEAAAAAnC0CQABOVVxcrIMHD0piD0BPZXQAFhUVac+ePSZXA1ROYWGhbDab2WUAAAAAbsHX7AIAeLfDhw/bu8bYA9AzxcbUtd9OS0tTUlKSidUAJysuLtaCBQv03Xffafny5UpPT1deXp6Cg4NVp04dderUSQMGDFDfvn1ltVrNLhcAAABwOQJAAE5lLP+VCAA9VdkAkH0A4U6Ki4v10Ucf6YUXXjjltZmbm6vU1FSlpqbqgw8+UHJysu6//35de+218vFhEQQAAABqDgJAAE5lDACRpPBwhoB4osjI2rJafVVcXMQkYLiNzZs366677tLatWvtH6sVFKQLmjXVOcl1VSsoSMfy8rQ5Y5eW/vmnsnLzlJaWpvvvv1/Tp0/X66+/rpSUFBM/AwAAAMB1CAABOFX5DkCGgHgiHx+roqPqaP+BNAJAuIWPP/5YDz/8sPLy8iRJyXGxGnXJUA3peIEC/f1Penz+8eP6atkKvTrnK+3Yt0+rVq1S37599corr2jIkCGuLh8AAABwOda/AHCqcgFgWLSJlaA6Yk9MAmYJMMxks9n03HPP6e6771ZeXp6sPj566IrLNP+5Z3Rl926nDP8kKdDfX1d276p5z07QfZdeLB+LRdnZ2br55ps1efJkF38WAAAAgOvRAQjAqYwAMDQ0Ur6+p/7lHO4v5sQ+gHQAwiw2m01jxozRlClTJEmx4eGafP89at+oUaWPEejvrwcuv1Qdz2mmO195XUeyszVmzBjl5eXp3nvvdVbpAAAAgOnoAATgVEYAGMEAEI8WG1M6+Xf37t0qKioyuRrUNDabTePHj7eHf43q1NGcpx47q/CvrM7Nz9Gsx8YoPjJSkjRhwgR98MEHDqsXAAAAcDcEgACcyhgCwgRgz2ZMAi4uLtbu3btNrgY1zTvvvKPXXntNUmn498nYfysppnpDhRon1tGnj41WbHi4JOmhhx7Sjz/+WO1aAQAAAHdEAAjAqfbt2ydJCg8jAPRksbFJ9tssA4YrLV68WGPHjpUk1Y2N0czRjygmPMwhx64XF6cPHnlQtYKCVFJSojvuuEPbt293yLEBAAAAd0IACMCpjAAwIqK2yZWgOow9ACUCQLjO1q1bNWLECBUXFyskMFBTHxil2pERDj1H83rJeuWu2yVJmZmZuummm5Sfn+/QcwAAAABmIwAE4DR5eXk6evSoJCkiIs7cYlAtEeFx9iEuTAKGKxQUFOiWW27R0aNHZbFY9PKdt6tZ3bpnfmIV9GnXVvdfdokkacOGDZo4caJTzgMAAACYhQAQgNMYA0AkAkBP5+Pjo5joREl0AMI1Jk2apPXr10uS7r/sEvU/t51TzzfqkqHqdE4zSdKbb76pxYsXO/V8AAAAgCsRAAJwGmP5ryRFsgTY48WcmARMAAhn++WXX/T6669Lks5v0kT3XDzE6ef08fHRi7ffqrDgIEnSAw88oNzcXKefFwAAAHAFAkAATrN37177bToAPV9sbOnyS5YAw5mysrI0cuRI2Ww21QoK0st33Sarj2t+XEmMidYTw6+VJO3cuVP/93//55LzAgAAAM5GAAjAacp2AEaEEwB6utgTHYC7d+/W8ePHTa4G3uqZZ57R7t27JUlP3/gvJcXEuPT8V3TrqguaNZUkvf7669q8ebNLzw8AAAA4AwEgAKcxOgADA0MUFBRqcjWoLmMSsM1m065du0yuBt5o9erVeueddyRJfdq10SWdO7m8BovFoqdvvF6+VqsKCwv1yCOPyGazubwOAAAAwJEIAAE4jdEBGMH+f14hLubvCawsA4ajFRUV6YEHHpDNZlNQgL8m3PAvWSwWU2ppmpSoWy8aIElasmSJvvnmG1PqAAAAAByFABCA09gDQJb/egVjCIhUuj8a4EiTJ0/Whg0bJEkPXHapy5f+/tOoSy5WXESEJGnixIkqKioytR4AAACgOggAATjN3x2ABIDeIDw8Vn5+AZLoAIRjHTx4UP/5z38kSeck19XNA/qZXJEUHBig+y69WJKUmpqqmTNnmlwRAAAAUHUEgACcxtgDMJIlwF7BYrEoNoZJwHC8559/XseOHZMkPTn8Wvn5+ppcUamre3RTw/h4SaU15ubmmlwRAAAAUDUEgACcoqCgQEeOHJFEB6A3MZYBswQYjvLXX3/p/ffflyQNOLe9OjU/x+SK/ubn66uHr7pcUukbGlOmTDG5IgAAAKBqCAABOMX+/fvtt+kA9B6xJwJAOgDhKI8//riKi4vlZ7Vq7LCrzS7nJAPPP09tGjaQJL3xxht0AQIAAMAjEQACcApj+a9EB6A3iY0tXQK8d+9eFRQUmFwNPN0vv/yiBQsWSJJu7N9X9ePd780Ci8WiUSf2Ajx06JA++OADkysCAAAAzh4BIACnMAaASEwB9iZlJwFnZGSYWAk8nc1m07PPPitJqhUUpHsuHmJyRRXr07aNzkkuDb9ff/11HT9+3OSKAAAAgLNDAAjAKcp1AEa6X1cPqsYYAiJJaWlpJlYCT7dgwQKtWLFCknTbwAsVERpqckUVs1gsGjl0sCRpz549+uSTT0yuCAAAADg7BIAAnMLoAAzwD1JQoPv+Yo+zUzYAZB9AVJXNZtOkSZMkSRGhIbp5QH+TKzqzQR3OV/3apW9mvPLKKyouLja5IgAAAKDyCAABOIXRARgRWVsWi8XkauAotWpFKcA/SBKTgFF1c+fO1Zo1ayRJdw4epFrBQeYWVAlWHx/dNWSgJGn79u2aO3euyRUBAAAAlUcACMApjA5A9v/zLhaLxb4PIB2AqIqSkhJ7919seJhu6NvH5Ioq79IunRUTFiZJmjx5ssnVAAAAAJVHAAjAKfbv3y9Jioxg/z9vY0wCJgBEVXz11VfauHGjJGnk0CEKDgwwuaLKC/Dz03V9ekmSlixZog0bNphcEQAAAFA5BIAAnMK+BDiCDkBvY+wDyBJgnC2bzaaXXnpJklQ7MkLX9uphbkFVMLx3L/lZrZLoAgQAAIDnIAAE4HDHjx/XoUOHJBEAeiNjCfCBAweUl5dncjXwJPPnz9f69eslSbcPvEiB/v4mV3T2akdGaPAFHSRJn332mf21DgAAAHBnBIAAHM5Y/itJESwB9jplJwFnZGSYWAk8jdH9FxkaqmEe2P1nuGlAP0lSfn6+3nvvPZOrAQAAAM6MABCAwxkDQCQ6AL1RbGyS/TbLgFFZS5cu1fLlyyVJNw/op5DAQJMrqrq2KQ3VLqWhJOn9999XSUmJyRUBAAAAp0cACMDhjP3/JCmSKcBeJ6ZMByCDQFBZL7/8siQpJDBQN/Tva3I11Xdd79JhIGlpafrxxx9NrgYAAAA4PQJAAA63e/du++3IqAQTK4EzhIZEKDAwVBIBICpn3bp1mj9/viRpeJ9eiggJMbmi6ht8QQfVCgqSxDAQAAAAuD8CQAAOt2fPHklSYGCogoNqmVwNHM1isSj2xCAQlgCjMl599VVJUoCfr265cIDJ1ThGcGCALu7cUZI0Z84cHThwwOSKAAAAgIoRAAJwOCMAjIqMN7kSOIsxCZgOQJzJrl279NVXX0mSLu/aVbUjI8wtyIGG9SwdZFJYWKiZM2eaXA0AAABQMQJAAA5nDwCjCAC9VWxs6T6AaWlpJlcCdzd16lQVFxdLkkZc2N/kahyrVYP6alW/viRp+vTpstls5hYEAAAAVIAAEIDDGXsARkay/5+3ijsxCOTQoUPKzs42uRq4q5ycHH3wwQeSpJ6tW6lxYh2TK3K86/r0lCSlpqZqxYoV5hYDAAAAVIAAEIBD2Ww2+xRglgB7r7i4evbbO3bsMK8QuLVPP/1UR48elSTdPKCfucU4yZCOFyjAz09S6ecLAAAAuCMCQAAOdfToUeXl5UkiAPRmcXHJ9tsEgDiVkpISvf3225KkRnUS1L1VS5Mrco7wkBBdeP55kqQvvvhC+fn5JlcEAAAAnIwAEIBDGct/JSmSANBrxcXSAYjT++mnn7RlyxZJ0k0D+snHx3t/5LiqZ3dJUmZmpubNm2dyNQAAAMDJvPencQCmMAaASFJUFHsAeit//0BFRtSWJO3cudPkauCOjO6/8JAQXd6li8nVOFfvtm0UHVZLEsuAAQAA4J4IAAE4VNkAkA5A7xZ7YhkwHYD4p82bN2vBggWSpGG9eig4MMDkipzLz9dXF3fqJEn68ccfdfDgQZMrAgAAAMojAATgUEYA6Ovrr1qhUSZXA2eqfWIZMAEg/mny5MmSJKuPj27o28fkalzjim6lXY5FRUWaPXu2ydUAAAAA5REAAnAoYw/AyIjaXr3nF/4eBJKRkaGioiKTq4G7OHLkiD7++GNJ0kXnn6fEmGiTK3KNVg3qq1GdOpJEAAgAAAC3w2/nABzK6ACMjGL5r7czBoEUFRVp165dJlcDdzF9+nT7JPARF/Y3uRrXsVgsGtrpAknSypUr+TcBAAAAt+JrdgHwDFar1SOPXRMZX0+zvq5GABgdVcerOwC9+XOrrNq169tvp6WlqWHDhlU+ltnXbU3izK9xYWGhpkyZIklq07ChzmvSWBaLxWnncwfG52exWDSkYwe9+Flp99/XX3+tu+66y8zSvAqvDY7Fa65r8PV1LK5b1+DrC3gvAkBUSmRkpFOOa7VanXbsmi4sLMyU8+7du1eSFBuTqMDAQFNqcDaLxeK1n9vZSE5uYr+9f/9+h/xbNuu6rSmc/Zr7ySef2LcBuHPoYAUFBTntXO4mICBArVJS1LxesjbuTNPXX3+tsWPHml2WV+BnBefhNdd5uG6dh+vWebhuAe9GAIhKOXLkiEOPFxYWJqvVquLiYmVlZTn02DWd1WpVWFiYsrKyVFxc7NJz5+bm2q+V8LA45efnu/T8zhYQECCLxSKbzaaCggKzyzFdgH+oAgNDlJ+fo40bN1brdcLM67YmcNVr7n//+19JUu3ISPVv39brXgNOxWKxKCAgQAUFBbLZbBrU4Xxt3JmmZcuWad26dapbt67ZJXosflZwHl5znYfr1nm4bp3Hna9bAknAcQgAUSnO/CbLN3DnKC4udvnXNiMjw347IiJOJSUlLj2/K3nz53Y24mKTlZb+p7Zt2+aQ682M67amcdbXd/Xq1Vq5cqUk6Ya+veXr41Mj/p0Y2wHYbDaVlJRo4Pnn6T+ffiapdBjIyJEjzSzPa/C64By85joXX1vn4Lp1Lr62gPdiEysADmPs/ydJUVEJJlYCV4mLKx0EsnPnTpMrgdnefvttSVKAn5+u7d3T3GJMlFInQc2TS7v+5syZY3I1AAAAQCk6AAE4jLH3lyRFRjIFuCaIi02WJO3YsUM2m83rBz7g1Pbs2WMPuy7t0klRtWqZXJG5Bl/QQRvT0vX7779r586dqlevntklAQAAuJ0nn3xSklS/fn3deOONptZSE9ABCMBhjA5Ai8WiiPA4k6uBKxgdgMeOHXP4XqHwHO+8846KiookSSMG9De5GvMNvqCD/faXX35pYiUAAADu66mnntJTTz2ld9991+xSagQCQAAOY3QAhofHytfXz+Rq4ApGB6BU2gWImicvL0/vv/++JKlryxZqWjfJ5IrMVz++tlrWLw3HWQYMAAAAd0AACMBh9u7dK4nlvzWJ0QEoEQDWVLNmzdLhw4clSSMG9DO5GvcxqMP5kqS1a9eWG5AEAAAAmIEAEIDDGB2AUREEgDVFTHSiLJbSbyUEgDWPzWazD/9oEF9bvdq0Nrki9zHgvPb22999952JlQAAAAAEgAAcyOhyiY5JNLkSuIqvr59iokv/vgkAa57Fixdr06ZNkqSb+veTjw8/Vhga1amjlITSN0Pmzp1rcjUAAMBV8vPzNWfOHN17773q3LmzYmNj5efnp1q1aqlx48b617/+pR9++KFSxyosLNRrr72mLl26KCoqSsHBwWrSpInuvvtu/fXXX5JKB2lYLBZZLBYtXLjwjLW99dZbGjx4sOrWravAwECFh4erZcuWuvfee7V58+bTPv9U51q1apVuuukmNWzYUIGBgYqOjlavXr307rvvqqSk5JTHMY5hWLRokf1jZf+wN6BjMQUYgEPk5eXp4MGDkqSYKALAmiQuLlkHDqZr586dZpcCF3vrrbckSWHBQbqye1eTq3E//c5tr61ff6slS5bo6NGjioiIMLskSaW/TGzevFnp6ek6ePCgioqKFBISotjYWCUkJCglJUW+vvyICABAVTRv3lzbt28/6ePZ2dlKTU1Vamqqpk+frosvvljTp09XaGjoKY+zd+9eXXjhhVq7dm25j2/ZskVbtmzRtGnTNG3atErXtWjRIl133XXatWtXuY8XFBRow4YN2rBhg9544w1NmDBBo0ePrtQxn3vuOY0dO1bFxcXljrdw4UItXLhQc+bM0aeffsrPFW6CvwUADlH2G0kMHYA1SlxssjZoCR2ANczWrVvt715f07OHQgIDTa7I/Qw4t73e/PpbFRcX68cff9QVV1xhWi379u3TnDlz9O2332rVqlXKz8+v8LHBwcFq3bq1unTpokGDBqlly5bl3qUHAAAVy83NVUREhHr37q127dqpXr16Cg4OVlZWltatW6ePP/5Ye/bs0Zw5c3TzzTfrk08+OekY+fn56tevn9avXy9JiomJ0YgRI9S6dWsdP35cP//8sz744ANdf/31uvDCC89Y03fffaeLL75YhYWF8vHx0YUXXqi+ffsqMTFR+fn5+u233/T+++8rMzNTY8aMkaQzhoCTJ0/Whx9+qNjYWN14441q3bq1fHx89Ouvv2rKlCkqKCjQF198oeeff95+TMPs2bMlSZdeeqkkqUWLFnr66adPOkf79u1P+hiqjgAQgEOU3eQ+OpoAsCYxBoHs2bNH+fn5CiQIqhEmT54sSfKxWHRDvz4mV+Oe2qU0VGx4mA5kZunbb781JQDcunWrXnzxRc2ePVuFhYWVek5ubq6WLVumZcuW6YUXXlD9+vU1bNgwXXfddapdu7aTKwYAwLNNmzZNffv2lZ+f3ynvnzhxoq677jp98cUX+vTTT/XLL7+oa9fyKymeffZZe/jXsmVLzZ8/X3Fxcfb7b7zxRt15553q27ev5syZc9p69uzZo+HDh6uwsFBxcXGaM2eOOnbsWO4x119/vR599FFdeOGFWr9+vR577DFdeumlatasWYXH/fDDD9WjRw/NmTNH4eHh9o9fe+21uvLKK9WnTx8VFxfr//7v//TQQw/J39/f/phLLrmk3LFiYmJO+hgcj816ADhEenq6/XYMAWCNUvtEAGiz2cpdB/BemZmZmjlzpqTSYRd1Y2NNrsg9+fj4qG/7dpKk+fPnn7brztGys7M1ZswYde3aVZ988ok9/KvTqI4uvH2gRr55rybMe1avrH5db6x/Wy8uf1lPfDVed752ty68baAandvY3vW3Y8cOPfvss2rbtq3uvPNObdmyxWWfBwAAnuaiiy6qMPyTSjvt33vvPYWEhEiS3nvvvXL3Hz9+XG+88YYkydfXVx9//HG58M9w3nnn6YUXXjhjPf/5z390+PBhSdKsWbNOCv8MiYmJ+vTTT2W1WlVcXKyXX375tMeNiorSZ599Vi78M/To0cP+xufBgwe1cuXKM9YJ5yMABOAQxhJgP98A1aoVbXI1cKXY2GT7bZYB1wwzZsxQbm6uJOnmAf1Nrsa99T8RAObm5urnn392yTmXLl2qHj16aPLkySoqKpKP1Uddruimp759Ws8seF7XjL1W5w/soLrN6iosJlzBYcGKSohWgzYNdcHQjrpm3LUaN/sJvfTba7rhmZvU6NzGkqSioiLNmjVLXbp00R133EEQCABAFYWFhalVq1aSpGXLlpW775dffrHvrd6/f381b968wuNcf/31io6u+Hcvm82m999/X5LUqVMndevW7bR1NWvWTB06dJAkff/996d97JnO3a9fP/tto5sR5mIJMACHMDq/oqITmARawxgdgBIBYE1QVFSkKVOmSJJa1q+nDk2bmFyRe+vSormCAwKUW1Cg7777rtwPw45ms9n09ttv64knnrBvxt26Vxtd89h1qtOozlkfLzw2XL2G91Gv4X2UtnGnfnjne/36+RIVFxXrs88+0+zZs3XDDTfo3//+t6Kiohz96QAA4LGOHDmiGTNmaO7cuVq/fr0OHTqknJwc2Wy2kx5bdislSeW65Xr16nXa8/j5+alLly768ssvT3n/xo0bdejQIUlSZGSkvvjiizPWbrVaJUnbt28/7fY+nTp1Ou1xkpKS7LePHDlyxvPC+QgAATiE0QHI8t+aJzg4TKEhEcrOOUoAWAPMnTvXHvjfPKA/wyHOINDfXz1at9J3K3/T3Llz9d///tcpb5KUlJRo9OjReueddyRJAcEBGj7+enW9srtD/o6Sm9fTiP/epiH3XKKvX5+jJbN+UXFRsaZNm6bZs2fr0Ucf1Y033siUPwBAjTdnzhyNGDHCHrydSVZWVrn/3717t/12SkrKGZ/fsGHDCu8r+7P5t99+q2+//bZSNRkOHz6sOnVO/SZiTEzMaZ8bEBBgv+3KbVBQMX5KA+AQxjtXDACpmeLi6il7+1Ht3LnT7FLgZG+99ZYkKTY8TEM6djC5Gs8w4Nz2+m7lbzpw4IBWr16t8847z6HHLy4u1n333aePPvpIkhRXL073TrlfSU3rOvQ8xrFvfv5WDbpriD56eqZ+n7dKR48e1ejRozVz5ky99NJL9iVNAADUNEuXLtUVV1yhoqIiSVLr1q3Vt29fNWrUSJGRkQoICLC/MTdu3Dht2LBBJSUl5Y6Rk5Njvx0cHHzGcxp7CZ7K0aNHq/BZ/O348eMV3seqL89DAAig2oqLi+3vVNEBWDPFxSZr2/a1dAB6uTVr1tj3qRnep7cCTrPBNf7Wu21r+VgsKrHZ9MMPPzg0ACwuLtadd96p2bNnS5KSW9TTQ9MfVVh0mMPOcSq168dr1JT7tX7xH/rwqenavWWX1q1bp379+umee+7Rgw8+yERwAECN8/jjj9vDv9dff1133XVXhY+dOHHiKT9eNtAz9lw+nbKB4T+Fhobabz/wwAOVGhoC70VkC6DaDhw4YJ8wSQdgzRR3Yh/AnTt3nnJvE3iHN998U5IU4Oerf/XpbXI1niMiNFTtGzeSJP34448OPfYTTzxhD/9S2jfSox+NcXr4V1bL7q00fu5EXfHoVfIN8FNxcbFeeukl9erVSytWrHBZHQAAmK2wsFALFy6UJJ177rmnDf+kivfOLrvkduvWrWc877Zt2yq8r+w+fMYWLqi5CAABVFvZbybR0We/0Tw8nzEIJD8/X3v37jW5GjjDrl27NGfOHEnSpV06KybcdSGTN+jdprUkad26dQ77N/LWW2/Zl2TXb9VAD01/VCHhFS8DchZfP18NHjlUE+ZOVJPzS4fCpKamasiQIZo0aZL9DSIAALzZwYMH7d1/jRo1Ou1jV65caZ/0+0/nn3++/fZPP/102uMUFhZqyZIlFd7ftm1bhYeH249VUFBw2uO5mrEcmgYC1yAABFBtZSdXxUQnneaR8Fa1a9e33z7du5DwXFOnTrX/UDviwgEmV+N5erVtbb89f/78ah9v3rx5euyxxyRJ0Ukxum/agwoKDar2casjIaWO/v3pOP3r6RvkHxSgkpISvfDCCxo8eHClOhgAAPBkZZfupqamnvaxTzzxRIX3denSRdHR0ZJKv99v3Lixwse+//77px02YrVadd1110kqDShffPHF09blasYS5dMtY4bjEAACqLayAWBUZLyJlcAs8bUb2G8TAHqf7Oxsvffee5Kknq1bqWkSS/3PVvPkZNWOjJBU/WXA6enpGjlypGw2m4LDgvXAuw8rIi6i+kU6gI+Pj/pc30/j505Uw7alkwtXr16t3r1764MPPuAdfgCA1woLC1OTJqWd8KtWrdKsWbNOekxxcbHuv/9+fffddxUeJyAgQCNHjpQkFRUV6eqrr9b+/ftPetxvv/2mBx988Ix1jRkzRhEREZJKB4+89NJLJw0eKSsnJ0dTpkzRzJkzz3js6mrQoPR3iE2bNikvL8/p56vpGAICoNqMADA8PFb+/mz6XhOFh8cqMDBE+fk5BIBeaObMmcrKypIk3XIR3X9VYbFY1KtNa320cLEWLlyowsJC+VVhiEphYaFuu+02+1S/21+5S4lN3C+QjW8QrzGfPaYvX/lCX706R7m5uXrggQe0YMECvfzyywoLYwk5AMD73Hffffa9/6666ipdffXV6tGjhyIjI5WamqoZM2bozz//VMuWLRUQEKBVq1ad8jijR4/W559/rvXr12v9+vVq0aKFRowYoTZt2uj48eNavHixPvjgA/n4+Gjo0KH68ssvJZ16Mm9iYqI++eQTDRkyRAUFBbr//vv1xhtv6NJLL1Xz5s0VGhqqY8eOafv27frtt9+0YMEC5efna8KECc77Qp3Qt29frVu3Tjk5ORoyZIiuv/56xcbG2pcGt2rVSomJ7vdzjqciAARQbUYAyATgmstisah27QbauXM9S/28THFxsd5++21JUtOkJHVr2cLkijxXn7Zt9NHCxcrOztby5cvVtWvXsz7GxIkT9dtvv0mSBt4xWG16t3VwlY7j6+eryx68Qq16tNbbo/6nA+kH9PXXX2vDhg2aOnWqWrVqZXaJAAA41B133KHffvtN77zzjmw2mz766CN99NFH5R7TqlUrzZkzRzfddFOFxwkMDNS8efN04YUXat26dTp48KCee+65co8JDg7WtGnTtG7dOnsAWKtWrVMer1+/fvrll180fPhw/fXXX9qyZYuef/75Cs9vtVoVH+/8lV0PPvigZsyYoX379mn+/PknbZMybdo03XjjjU6vo6ZgCTCAatu1a5ckJgDXdPEn9gGkA9C7zJ071z6l7taLBtjfkcXZ69KiufysVklVWwb866+/6vXXX5ckNTq3sS57+AqH1ucsjc9rovFzJ+r8QR0kSdu3b9dFF13EkmAAgNexWCyaOnWqPvvsMw0YMEDR0dHy8/NTfHy8evTooddee00rVqywL309nYSEBP3222969dVX1alTJ0VERCgoKEiNGjXSXXfdpdWrV+uqq64qtwdgVFRUhcc777zztHHjRn366acaPny4GjdurLCwMFmtVoWHh6tly5YaNmyY3nrrLWVkZOiWW25xyNfkdOrUqaPVq1frgQceUOvWrVWrVi1+1nQii42fvFAJFU0oqqrIyEhZrVYVFxfryJEjDj12TWe1WhUZGakjR46ouLjYJedMSUlRVlaWBl54m669ZpxLzmmGoKAgWSwW2Ww29qg4hU8/+4/mfPWqAgIClJaWdsolCBUx47qtSarzmjt48GAtX75cseFh+vWlFxRQhWWr3szHx0eBgYHKz88/7X46hmHPPq8lGzaqadOm+uWXXyp9ntzcXPXs2VPbt29XYGigJv4wSdGJMdUp3eVsNpvmv/eDZk6YoeLC0n/nV155pZ5//nn7JuBl8bOC8/Ca6zxct87Ddes87nzdxsR41vc6M5x77rlavXq1IiIidPjwYQI0VIgOQADVkpWVZd8bLDq6jsnVwEzx8aXvZBYUFNi7QuHZVq9ereXLl0uSru/bh/DPAfq0bSNJ+uuvv5SWllbp502aNEnbt2+XJF0z9lqPC/+k0q6Ivjf219jPH1d0Umn9n376qQYMGKAtW7aYXB0AAJ5n6dKlWr16tSSpZ8+ehH84LQJAANVSdgJwTHSSiZXAbEwC9j5vvvmmJCnAz0/D+/QyuRrv0KtNa/vtH374oVLPWbVqlf3v4pzOzdXjWs/+u2jYJkXjv52otn3bSZI2b96sAQMGVPrrAQBATbB69WodO3aswvs3btyoYcOG2f//zjvvdEVZ8GAEgACqpWwASAdgzUYA6F127txp31D6sq6dFc3UVodomBCv5LhYSdLChQvP+Pji4mI98sgjstls8g8K0M3P3+IV7+6HRIRo1NQHdNXoa2TxsejYsWO67rrr9Morr7AvIAAAkt555x0lJCTosssu03PPPaeZM2fq008/1auvvqorr7xSbdq00c6dOyVJ11xzjfr3729yxXB3TAEGUC3GkjRJiotNNrESmC00NFLBwWHKzc1iErAXeP3111VcXCyLxaLbB15kdjlew2KxqHurlpo+/yf98ssvKiwslN9pllbPmDFD69atkyRdct+lik2Oc1WpTmexWDTwzsFKOqeu/nf368rLytWECRO0YcMG/d///Z8iIyPNLhEAAFPl5ORo9uzZmj17doWPue666zR16lQXVgVPRQcggGox3nUywh/UXBaLxd4FSAegZ9u3b58+/PBDSdLA889Tw4R4kyvyLt1btpQkZWdna9WqVRU+7siRI5o4caIkKb5hvPqPuNAl9bla655t9MSXTyk+JUGS9Pnnn2vw4MHlOswBAKhpHnnkET333HMaOHCgmjZtqpiYGPn6+io8PFzNmzfXrbfeqiVLlmj69OkKCAgwu1x4AAJAANViBIB0/0GS4uMbSiIA9HRvvfWWCgoKJEkjhw42uRrv06l5M/mcWMZ7umXAkyZN0uHDhyVJ1z75L/n6e+/CjfiGCXp8zlNq3bt0SMoff/yhLl26aO3atSZXBgCAOZKTk/XII4/om2++0aZNm3TgwAEVFhbq6NGj2rBhg95++2117tzZ7DLhQQgAAVTLjh07JElxcfXMLQRuIb52fUmlwXBRUZG5xaBKMjMzNW3aNElSj1Yt1bI+/7YdLTwkRO0apUiqOABMTU3Ve++9J0lq16+9Wvds46ryTBMcFqz7pj6ogXeUhs67du1St27dNG/ePJMrAwAA8HwEgACqrKSkRGlpaZLoAEQpYwlwUVGR0tPTTa4GVTF16lRlZ2dLovvPmbq1bCFJ+v3333X06NGT7p84caKKi4tl9bXq6nHXurg68/hYfXTVmGt0wzM3yeLjo2PHjmno0KH2JekAAACoGgJAAFW2f/9+5efnSyIARKnaZSYBMwjE8+Tm5urtt9+WJJ3buJEuaNbU5Iq8V7dWpfsAlpSU6Oeffy5336pVq/T1119LknoM66n4BjVvD8Zew/vokQ/+rYCQQBUVFWnUqFF68cUXmRAMAABQRQSAAKrMWP4rsQQYpYwlwBL7AHqiGTNm6NChQ5Kku4YMkuXEPnVwvLYNG6hWUJCk8suAbTabJkyYIEnyDwrQ0FGXmlGeW2jf/1w9NWeCIuIiJEnPPvusJkyYQAgIAABQBQSAAKqsfABIByCkkJBwhdWKlkQA6GmOHz+uN954Q5LUNClJfdp6/55zZvLz9VXn5udIKg0AjVDrp59+0pIlSyRJA2690B5+1VQN26ZowrfPKDY5TpL06quv6pFHHlFJSYnJlQEAAHgWAkAAVWZMALZa/RQVWfOWqOHUap/oAiQA9CwzZ85URkaGJOmuIQPl48OPCM5m7AOYlpam7du3y2az6T//+Y8kKSQiVBfdNsjM8txGXL3aGjPrMdVpnChJevfdd3X33XczaAgAAOAs8NM9gCozAsDY2Lry8bGaXA3chTEIZPv27SZXgsoqKCjQiy++KElKSYjX0E4dTa6oZuh+Yh9AqbQLcPHixfrtt98kSRfedpGCw4LNKs3tRMZHavSn41SvZX1J0qeffqrbbruNEBAA4BYsFovH/Pnhhx/M/nLBJA4NAK+99lotXrzYkYcE4MaMJcAMAEFZRgCYlpam48ePm1wNKmP69OnavXu3JOn+yy6Rle4/l6hXO051Y2MllQaAL7zwgiQpOCxYfW/oZ2ZpbqlWVC09+tEYNTm/iSTpq6++0l133aXi4mKTKwMAAHB/vo482EcffaSPP/5YTZo00e23367rr79eUVFRjjwFADdCAIhTqR1fX1LpdNOdO3eqcePG5haE08rPz9dLL70kSWqSlKhBF3Qwt6AaxGKxqFvLFvrwp4VauHCh8vLyJEn9R1yooFp0/51KcFiwHnj/Eb14/fPavHKzZs+eLT8/P7366qssWwcAmO7Zm2/UOfXc73ejP3emafQ775pdBkzm0ABQKp1et3nzZj344IMaM2aMrrjiCt12223q2rWro08FwEQ5OTk6cOCAJCYAozyjA1Aq3QeQANC9vf/++9q7d68kuv/M0L1VaQBohH+BoYHqd9MAk6tyb4Ehgbr/3Yf0n+HPadvvW/XJJ5/I399fL774IpOrAQCmOqdesjo0bWJ2GcApOfSn/IULF+qaa66Rv7+/bDab8vPzNWPGDPXo0UMtWrTQq6++qqNHjzrylABMYuz/J9EBiPLKBoBbt241sRKcSW5url5++WVJ0jnJdXXReeeaXFHN07lFc5WNrPrdNEAhESGm1eMpgmoF68H3H1H9VqWvN9OnT9fEiRNNrgoAAMB9OTQA7N69uz788ENlZGToP//5j5o0aSKbzSabzaZNmzbpvvvuU2Jiom666SYtXbrUkacG4GJlA8DadACijMDAEEVFJUiStmzZYnI1OJ0pU6Zo//79kqQHLruEJZQmiAgJUa3gIEmS1d+q/iMuNLkizxESHqKHZjyqxCZJkqSXX35ZkydPNrkqAAAA9+SUn/Sjo6P14IMPatOmTfrpp5909dVX27sC8/Ly9P7776tr165q3bq13njjDWVlZTmjDABOVDYAjI2ta2IlcEd1ElIkEQC6s0OHDtn3/mvdoIH6n9ve3IJqqL8ydikrt3T5b2TLaAWEBphckWcJjQjVgx88rKg60ZKksWPH6osvvjC3KAAAADfk9Lf6e/TooZkzZyojI0PPP/98ua7ADRs26J577lGdOnV0yy23aMWKFc4uB4CDGANAwsJiFBjIcjWUlxDfSJKUmppqciWoyAsvvKBjx45JksZdezV7p5lkyndzS2/4SFFtorVr1y5zC/JAUQnReuiDRxQSHiKbzaaRI0fq119/NbssAAAAt+KytT7R0dF66KGHtGnTJs2fP19XX321/Pz8ZLPZlJubq2nTpqlTp05q166dJk+ebN8MG4B7YgIwTsfoADx06JAOHTpkcjX4p23btmnatGmSpL7t2qrjOc1Mrqhm2n/0qGYvKd0SJaJJpPxC/ZWWlmZyVZ6pTuNE3TftQfkH+uv48eO66aab7N+nAAAA4MIAsKxevXpp0qRJuvHGGyXJ3nVgs9m0bt063XHHHUpOTtb//d//qaSkxIwSAZyBMdwhvnZ9cwuBW0qok2K/TReg+5k4caKKiorkY7Ho39dcaXY5NdZ7P8zX8aIiSVLzXqXTsgkAq67xeU106//dIUk6fPiwhg8fzjYzAAAAJ7g0ACwpKdEXX3yhiy66SCkpKfaNmm02m0JDQ9WvXz97V+ChQ4f00EMPqXfv3nQDAm7m+PHj9l9SE+JTzvBo1ER1EhrZb7MPoHv57bff9OWXX0qSrunZQ00SE02uqGbKzS/Q+z8ukCSd076BmrduKEnat2+f8gvyzSzNo50/qIMuffBySdJff/2lW2+9VUUnQlYAAFA5N954oywWy0l/QkND1axZM916661au3btSc+rX7/+Sc/x8fFRRESEzjvvPI0bN0579+494/l/+ukn3XLLLWratKnCwsIUHBysBg0aaNiwYZo9e7bDP9/Vq1friSeeUK9evVS7dm35+fkpIiJCnTp10qRJk7zmDUWXBIA7d+7UuHHjVLduXV1++eWaN2+eSkpKZLPZ1KpVK73xxhvatWuXvv/+e6Wnp2vixImKjY2VzWbTzz//rBdffNEVZQKopB07dti7c+PjG5hcDdxRZERt+96QdAC6j5KSEo0bN06SFBwQoAcuv8TcgmqwT3/+WZk5OZKk/ld1Ut3YGEmlb4qmp6ebWZrHG3rvJbpgaEdJ0oIFCzRhwgSTKwIAwDP5+fmpdu3a9j/5+fn666+/NGXKFJ133nl68803T/m8kJAQ+3Oio6OVmZmpVatWaeLEiWrZsqWWLVt2yucdPXpUQ4cOVe/evTV16lRt3rxZRUVFslqt2rFjhz766CNddtll6tSpkzIyMhzyOc6YMUPnnnuuxo8fr4ULF+rAgQMKDQ1VVlaWli1bptGjR6tVq1bauHGjQ85nJqcFgMXFxZo9e7YuvPBCpaSk6Nlnn9WePXtks9nk5+ena6+9Vj///LPWrl2rO+64Q6GhoZKk2NhYjR49Wn/++adatGghm82mmTNnOqtMAFVgLP+VpIQEOgBxMovFYr826AB0H9OmTdOqVaskSXcNGaS4iAhzC6qhiktKNOW7eZKkOvVi1bJDI8VHRsrP1yqJZcDVZbFYNOK/t6lh29LXoDfeeMPe9QoAACqvc+fO2rt3r/1Pbm6u5s2bp0aNGqmoqEgjR448ZSfgQw89ZH/OgQMHlJWVpTfffFO1atXSoUOHdMUVVyg/v/yKh8zMTHXr1k1fffWV/P399eijjyo1NVW5ubk6duyYdu/ereeff161atXSsmXL1KlTJ4f8zFRYWKigoCDdfPPN+uGHH5STk6MjR47o2LFjeu+99xQTE6O0tDQNHjzY41enOjwA3LFjh8aOHavk5GRdccUV+uGHH+zdfvXr19ezzz6rjIwMTZ8+XV26dKnwOFFRURo1apQkafv27Y4uE0A1lO3oqh1X37xC4NbqxBMAupNDhw5pzJgxkqT6tWvrtoEXmlxRzfXT2nXauX+/pNLuP4vFIquPjxKjoyVJ6Wl0AFaXf6C/7n7rXtWKDpMkjRo1im5kAACqyd/fX/369dOcOXPk5+enkpKSCrsAy6pVq5Zuv/12++rOXbt2ac6cOeUec/vtt2v9+vUKDAzUd999p0mTJikl5e9mk4SEBD388MNasmSJoqOjlZGRoWHDhlV7bkSnTp20bds2TZ06VX379lVQUJCk0i7G66+/Xp988omk0lzq008/rda5zObQAHDAgAFq1KiRJk2aZO/2s1gsGjRokL755htt3bpVjz76qGJiYip1vKSkJEk6KRkGYC6jAzA6OlEBAUEmVwN3ZewDuHPnThUUFJhcDcaMGWOfyDz++usU6O9vckU113vzfpQkhYYFqUOflvaPJ8XGSpIOHDignNwcU2rzJlEJ0brz1btk8bEoOztbN910k3Jy+LoCAFBdzZs313nnnSepdH/pyho+fLh8fHxOet6qVav08ccfS5Keeuop9e7du8JjtGrVSq+//rok6ddff9UXX3xxtuWX07RpU8XHx1d4f69evVSvXj17nRXZuHGjbr75ZtWvX1+BgYGKjIxU165d9eabb7rNfsQODQDLdvvFxcVp9OjR2rp1q7766itddNFF9mm/lRUcHKzk5GT7FxuAezC6KBLY/w+nYSwBLikpoZPbZCtWrLAP3rro/HPVs01rkyuqubbt2atFf6yXJHUd1F7+AX72+4x9ACW6AB2ledeWuvyh0knXmzZt0kMPPSSbzWZyVQAAeD6jYSszM7PSzwkMDFT0iRUPZZ/31ltvSZLCw8N19913n/E4V199tRo3blzuuc5kNLFVFOS9//77atOmjaZNm6adO3cqMDBQOTk5WrJkie6880716NFDR48edXqdZ+LwJcDdunXThx9+aB/mUZ3wrnv37tqxY4e2bdvmwAoBVJfxb5IJwDidOnX+vj5YBmyeoqIi3XPPPbLZbAry99fj111rdkk12vs/zpckWXws6jn0vHL3xUVEKMCvNBBkH0DHGXjXYLXr116SNGvWLHuHAQAAqLqdO3dKkiIjIyv9nJycHB08ePCk5/3000+SpP79+ys4OLhSx7r44oslSUuWLHFqh93hw4e1fn3pm7ctW7Y86f4VK1ZoxIgRKioq0kUXXaTU1FQdPXpU2dnZeueddxQcHKxff/1VN998s9NqrCyHBoB//PGHFi1apGuuuUZ+fn5nfgIAj5OZmakDBw5IYgIwTq92XH1ZLKXfZggAzfPGG2/Ylys8cOVlSoyJNrmimisnP1+fLv5FktSmUxPFxEeUu9/HYlHSiXeYCQAdx8fHR7e8cLuiE0uv/UcffbTcMCsAAHB2Vq5caV/C27Fjx0o/780337R34hvPKywstK8wa9u2baWP1aZNG0mloaIRRjrD+PHjVVBQoFq1aumKK6446f5x48apqKhI7du315w5c+z7Fvr7++umm27SlClTJEmzZ8/W8uXLnVZnZTg0AGzRooUjDwfADZWbAEwHIE7Dzy9AcXHJksTm+ybZvHmznn/+eUlSqwb1NXLoEJMrqtk+X/Krjp2YHtf70g6nfEzSiWXAxvQ5OEZIRIhue+lOWXwsys3N1R133KHjx4+bXRYAAB5l9+7d+uCDDzR06FCVlJTI399fI0eOPO1ziouLlZqaqqeeekpjx46VJDVq1EiDBw+WVNphZzCWB1dG2dkSxj7XjvbNN9/o1VdflVQaBMae2K/ZcOTIEf34Y+nezqNHjz5lI9ywYcPUtGlTSTJ9FYJDA0AfHx/5+vrqyy+/PKvnff/997JarfL19XVkOQCcoGyQQwcgzoRJwOYpLi7WqFGjVFBQIF+rVa/cfZf8+D5rGpvNpvd+KF3+G183Wue0P/XrZ3Lc3z/M0gXoWE0vaKah91wiSVqzZo0mTZpkbkEAALi5RYsWyWKx2P8kJibq+uuv1969exUcHKzp06erSZMmJz3vqaeesj/H19dXjRs31pNPPqmCggLVq1fPPkXYna1Zs0bXXnutSkpKdMkll2jUqFEnPWb16tX2jsbTDS7p27evpNMPEXEFh/8mUNWNldmQGfAMf/31lyTJ3z9QMdFJJlcDd5eQ0Ei/r52vLVu22CfDwzVee+01+9KM+y67RK0a1Od7rYmW/blJmzN2SSrt/qvo30J0rTAFBwQot6BAaWlprK5wsKGjLtGGX9YrddUWvfbaa+rTp4+6dOlidlkAALglPz8/RUVFSZIsFouCg4OVlJSkbt266bbbblNycvIpnxcSEqLQ0FBJpY1itWrVUqNGjXThhRfqxhtvVK1ateyPNY4vnV0nn7GX4D+P4Qh//vmn+vfvr6ysLPXs2VMzZ8485c9uxtZYgYGBp63BGJiyf/9+h9Z5tmgFAHBWjACwTkIj+wh3oCJ1TkwCzsnJ0d69e5WQkGByRTXD6tWr7d1N5yTX1f2XX2ZyRXj3RPdfQJC/OvVvU+HjLBaLkmJjtDljFx2ATmD1ter2V+7S4xeOUd6xPI0aNUoLFy60/5ICAAD+1rlzZy1cuPCsn/fQQw/pySefrNRj/fz8lJKSoq1bt2rNmjWVPsfatWslScHBwdUaPvtPW7ZsUZ8+fXTgwAF17NhRX331lQIDAx12fDO5xW/vubm5kuQ1X1TAmxkBYGKdxiZXAk/AJGDXO3bsmG6//XYVFRUp0N9fr468Q/5+vN9npj2HDmveqtWSpM4D2igoJOC0jzcGgWRlZSkzK9Pp9dU0sXVjNezx4ZJKJxiOHz/e5IoAAKjZjOWz8+bNs+dDZzJnzhxJUpcuXRy2nHjbtm3q3bu39uzZo3bt2um777477ZuExp6A+fn55fYy/KeMjAxJUlxcnEPqrCq3CACXLVsmyfwvBoDTy83NtU9YSkw8ea8H4J8SEhrZbxMAOp/NZtMjjzyiHTt2SJIev26YmiQmmlsU9PHin1VcUiJJ6nXx+Wd8fNlJzenp6U6rqybrdlV3te5V2ok5bdo0/fzzzyZXBABAzXXbbbdJkjIzM/Xaa6+d8fEff/yx/XeL22+/3SE17Ny5U7169VJGRoZatmypefPmKSIi4rTPad++vX1p8Pz58yt8nHHfueee65Baq6rKLQHr1q2rsD1zwYIFOnr06Gmfb7PZlJOTo9WrV2v69OmyWCw6//wz/1AMwDypqan2PcQSE+kAxJnVCo1UrVpROnbsMAGgC0yZMkWzZs2SJA04t72u693T3IKg4pISfbRwkSSpcatk1akfe4ZnSNFhtRQUEKC8ggKlp2eoZYuWzi6zxrFYLLpx0s0a22+08rJyNWrUKC1evJilwAAAmOC8887TFVdcoVmzZumJJ57QeeedV+FQjT/++MM+ebhTp0669NJLq33+Xbt2qXfv3kpLS1PTpk31448/lpsyXJHIyEj169dP8+bN06RJk3TJJZec1I04c+ZMbdq0SZJ0zTXXVLvW6qhyADh79uxTLpmw2Wz2McmVZWwMf8cdd1S1HAAuYCz/laQkOgBRSQkJKQSALrB06VI9/vjjkqTkuFj959abGbriBhb/sV67D5UuCek+uH2lnmORRUkx0dqya7cy6AB0mqiEaF33xHBNefBtpaen68knn9R///tfs8sCAKBGmjx5sjZu3KiNGzfqoosu0gMPPKBbb71VDRs2lCTt3btXH3zwgZ5++mllZWUpISFBM2fOrPa+9Pv371efPn20bds2paSkaP78+apdu3alnz9hwgQtWLBAq1ev1iWXXKJXXnlFKSkpOn78uGbMmKG7775bknTZZZepQ4cO1aq1uqr1lbLZbOX+VPTxM/2pXbu2Jk+efNqxyQDMZ7xz4ecXoNiYuiZXA09h7BdpXD9wvN27d2vEiBEqKipSUIC/Jt93ryLoZHILHy5YKEkKDg3UuT2aV/p5daJLlwEfPXpU2dnZzigNkrpc0U1t+rSTJL333ntavHixyRUBAFAzRURE6JdfftHAgQN1/PhxTZo0SSkpKQoJCVFYWJgSEhL0yCOPKCsrSx06dNCyZcscMvzjzTfftDe67N+/X+eee67i4+NP+eeyy04erNehQwdNnTpVvr6++vbbb9WoUSNFRkYqNDRUN998s3Jzc9W5c2dNnTq12rVWV5U7AC+55BLVr1+/3MduuukmWSwW3X333Wrf/vTvcvv4+Cg0NFQNGjRQq1atZLVaq1oKABfZvHmzJKlOncby8eHfLCrH6Bbdv3+/Dh8+rKioKJMr8i5ZWVkaNmyYDhw4IEn6zy0365xkAnp3sO/IUf34+xpJUsd+reUfUPkNqpNiy+8DeM455zi6POjEUuBnb9a4fv9WTmaOHnzwQS1evFhBQUFmlwYAQI0TGRmpb775RvPnz9eMGTP0888/a8+ePSoqKlK9evV0wQUX6KqrrtJll13msJUuJSf2aZZKh+kdO3aswsdWNOjj+uuv17nnnqv//ve/WrBggfbu3avg4GC1aNFCw4cP1y233OKwQSXVUeUAsE2bNmrTpk25j910002SpD59+mjo0KHVqwyA2zE6uJgAjLORlNjUfnvTpk3q3LmzidV4l8LCQt18883auHGjJOmuIYM0tFNHk6uC4dMywz8qu/zXEBMWrgA/PxUUFhIAOllkfKSuGjtM0x6Zoh07dujFF1/U2LFjzS4LAADTvPvuu3r33XfP+nnGILrq6tOnj/r06eOQY53Jk08+qSeffLLax2nRooWmTZtW/YKcyKFTgKdNm6Z33nnnjN1/ADxPXl7e3xOACQBxFsruF1l2H0lUT0lJie677z4tWlQ6YOLiTh31yJWXm1wVDCUlJZp5YvhHSoskJTWs/F4ykuRjsdinATMJ2Pm6XdVdTTqUvlnx2muv6c8//zS5IgAAAMdyaAB4ww036IYbblBSUpIjDwvADWzatMm+12dy3WYmVwNPEhYWo9DQSEnsA+goNptNjzzyiD755BNJUsdmTfXf20ZUexNkOM4vGzYq/cBBSVK3QVV7YzTpxPS5w4cPKycnx2G14WQ+Pj668dmbZfWzqqioSA8++GC5JUEAAACejt8UAFTK+vXr7beT61Z+I3vAYrHYuwDpAKw+m82mMWPG6L333pMktaxfT5Pvv1cBbrCvCP4248Twj6CQAJ3fs0WVjmF0AEpSegZdgM5Wp3GiBt01RJK0cuVKffDBByZXBAAA4DgEgAAqxQgAQ0MiFBWVYHI18DSJBIAOUVxcrIcfflhTpkyRJJ2TXFczHn1Y4SEhJleGsg5kZuqH1b9Lkjr2baWAIP8qHScuIlz+vqXbNbMM2DUGjxyq+IbxkqTx48dr7969JlcEAAAqY9SoURVO763oT01TpSEgDRs2lFTa1bF169aTPl5V/zweAPexYcMGSVJycnOHTVxCzZFUpzQAPHjwoA4ePKiYE0sbUXnHjx/XyJEj9cUXX0iSGifW0YxHH1ZkrVBzC8NJPl38i4qKiyVJ3QafW+Xj+Fh8lBgTre179ykjPcNR5eE0/AP9dcMzN+u5a55RVlaWnnjiCb311ltmlwUAAM4gMzNT+/btM7sMt1alANCY7PLPEGDHjh2yWCz2fcLOFqEC4J5KSkr+DgDrMokSZy/xH4NACADPzpEjR3TLLbdo8eLFkqQ2DRvovYcfUFStWiZXhn8qKSnRzJ9Kh3/Ub1ZHyY2q9+5yYkyMtu/dp4MHDyovL09BQUGOKBOncU7n5upyeVct+ewXff7557rhhhuYXg4AgJur6uTimqRKAWBycvIpw7qKPg7As6WlpSk7O1tSaQcgcLbKTgLetGmTunTpYmI1nmXTpk3617/+ZX/zrUuL5pp83z0KJQhyS0v/3KSd+/dLkrpXo/vP8M99AJs0bnKaR8NRrhx9jVbPW6W8Y3kaPXq05s+fL1/fKv3YDAAA4Baq1QFY2Y8D8GxG958k1WMACKogLCxaYbWilXXsEPsAnoXvv/9ed9xxhz2Av7JbVz1z8w0M/HBjH/60UJIUEOSvDr1bVvt4tSMi5OdrVWFRsTLSMwgAXSQiLkKX3H+5Zo6fro0bN+qdd97RbbfdZnZZAAAAVcYQEABnZAwAsVp9VadOI5OrgacylgFv2rTJ5ErcX0FBgR5//HENHz5c2dnZ8rFY9PjwYfrvbSMI/9zYoawszV25SpJ0QZ+WCqzi8I+yrD4+Sogq7QJkEIhr9bmhrxKbJEmSJk2apP0nOjsBAAA8EQEggDMyAsA6CY3k5xdgcjXwVEllJgFXda/YmiA1NVUXXXSR/ve//0mSwoKD9f4jD+qWCwewzYab++yXJSo8MfzDEct/DUknlgEfOHBA+QX5DjsuTs/Xz1fDJ1wvSTp27JiefvppkysCAACoOgJAAGe0Zs0aSVL9+q3MLQQezegAPHz4sA4cOGByNe6nqKhIb775pvr06aM//vhDktShaRN9/8wEdW9V/aWkcC6bzaYPF5QO/0huHK/6Tes47NjGPoA2m027MnY57Lg4s3M6NdcFQztKkmbOnKmVK1eaXBEAAEDVuHw347y8PL355pv6+eefVVRUpLZt2+rOO+9UQkKCq0sBUAl79+7V3r17JUkNG7QxuRp4sqR/TAKOi4szsRr3smbNGj344INat26dpNJln/dderHuvniIrD68V+cJlm36S9tOvFY6svtPkuKjIuVrtaqouFjp6elKSUlx6PFxelePHaY1P/6ugtwC/fvf/9a8efNktVrNLgsA4Ib+3Jlmdgmn5K51wbUcGgD+/vvvuuGGG2SxWPTmm2+qU6dO5e7PyspSt27d7MsJJembb77R//73P82bN0/t2rVzZDkAHOD333+33yYARHUk/mMScLdu3Uysxj1kZ2frmWee0dSpU1VSUiJJapqUpOduuVHtG7Hfpif5cMFCSZJ/oJ8u6OPYbmlfH6sSoiKVfuAg+wCaICohWhePulSfPPuR1q1bp+nTp+uGG24wuywAgBsa/c67ZpcAVMihbQWzZs3S+vXrtX//fnXs2PGk+8eOHas//vhDNput3J9Dhw7p8ssvV0FBgSPLAeAARgBotfopuW4zk6uBJ6sVGqnwsFhJDAKRpG+//VadO3fW5MmTVVJSokB/f/376iv17dNPEv55mMPHjunbFaVLQzv0aqGgEMfvlVonunQZ8P79+3X8+HGHHx+n13/EhYpvGC9JevbZZ5WZmWlyRQAAAGfHoR2Ay5cvl8ViUb9+/U7aqPzYsWOaOnWqLBaL6tatq5dfflkNGjTQG2+8obfffls7d+7U9OnTNWLECEeWBKCajAAwuW4zBoCg2pKSmihz44EaHQBmZGRo9OjRmjt3rv1jPVu30oQb/6V6LIv2SJ8sXKyCwkJJjl/+azD2ASwpKdGePXtUr149p5wHp+br76thjw/X/934Xx06dEgvvviinnrqKbPLAgC4iXnz5pldQqU1b97c7BJgEocGgLt2lW5MfaqlvN99953y8/NlsVg0depU9enTR5L05ptvatmyZfrjjz/0xRdfEAACbsRms2nt2rWSWP4Lx0hMbKING5fYJwHXpKm2RUVFmjJlip599lnl5uZKkmLDw/Xkv67T4AvOr1FfC29is9n0/g8/SpKSGtZWg3MSnXKehKgo+VgsKrHZlJGRQQBogta92qhlj1Zav+gPTZ48Wddffz37MQIAJEn9+vUzuwTgjBy6BPjgwYOSdMqBHosWLbLfZ4R/hiuvvFI2m82++TkA97Bjxw4dOXJEEgEgHKNuYlNJUmZmpn24TE2wbt069e/fX4899phyc3NlsVj0rz69teD5ZzSkYwfCPw/22+Yt2nxiMm/3we2d9nfp7+ur2IgISX+/4QrXslgsGvbYcPlYfVRYWKgnn3zS7JIAAAAqzaEBoLEfis8pJhYuXbpUFovlpPBPkpKTkyVJBw4ccGQ5AKppzZo19tsEgHCEunXPsd/esGGDiZW4Rn5+vp5++mn1799ff/zxhySpWd0kff74WE286XqFh4SYXCGqa8aCnyRJfv6+6tivtVPPVSc6SpK0e/du+9AYuFZik0T1+lfpz7Jz5861v8ENAADg7hwaAAYHB0s6OcjLzMy0d/d17tz5pOcFBgZKkoqLix1ZDoBqWr58uSQpMDBUiYmNTa4G3iApsYm9Q2rjxo0mV+Ncy5cvV69evfTyyy+ruLhYAX5++vfVV+qbCU/q3MYM+fAGR3Ny9NWyFZKk83u1UHBooFPPZ+wDWFhYqH379jn1XKjYpfdfppDw0vD+scceU1FRkckVAQAAnJlDA8D69etLkn755ZdyH//666/t71R36dLlpOcdOnRIkhQeHu7IcgBUkxEANm7UXj4+VpOrgTcIDAxRXFzp3mXeGgAWFhZqwoQJGjJkiFJTUyVJHZo20ffPTNBdQwbJz9eh2+/CRLOX/Gof/tFjiHOGf5SVeGISsFQ6TAbmCI2spUvuv0yS9Oeff2r69OkmVwQAAHBmDv0tpFu3blq3bp2+/PJLrV27Vm3atFFWVpaef/55SVKdOnXUsmXLk563fv16SVKDBg0cWc5JMjMzNWvWLK1YsUKHDh1SQECAUlJSNHDgQHXs2LHKxy0qKtLXX3+tRYsWaffu3ZKkxMRE9ejRQ4MGDZJvBb/s7du3Txs3blRqaqq2bt2qbdu2KT8/X5L05ZdfOvXcwJkcO3bMHtA0aXy+ydXAm9RNaqZ9+3Z4ZQCYnp6u22+/XStXrpQkhQQGavTVV2p4n16n3B4Dnstms2nmT6XLPxMbxCmlRV2nnzM4IECRoaE6kp2tXbt26fzzeW02S69/9dGC6fO1J3W3Jk2apEsvvZQ3sgGgBvOk/ZznzZvH0JIayqHp0K233qr//e9/ys/PV4cOHdSuXTtt3bpVhw8flsVi0a233nrK5y1YsEAWi0WtWztv75y0tDSNHTvWvk9hUFCQcnJytGbNGq1Zs0ZDhgypsL7TycvL02OPPabNmzdLkvz9/SVJqampSk1N1ZIlSzR+/Hj7MueyZs6cqQULFlT5c6rOuYEz+e233+ydu00an2dyNfAmdZOa6bdVc7VlyxYVFBQoICDA7JIc4vvvv9fIkSPt32faN0rRqyPvUN3YWJMrgzP8vnWrNqWXduH1HHKeLBaLbDab08+bGBOtI9nZysjIqHGTtN2Jr5+vhj12nV684T86dOiQXnjhBY0fP97ssgAAACrk0ACwdevWeuKJJ/TEE0+osLBQK1eutP8w3Lp1az388MMnPeePP/7Qpk2bZLFY1LVrV0eWY1dYWKinn35amZmZqlevnh544AE1aNBABQUFmjNnjmbMmKGvvvpKDRo0UN++fc/q2G+88YY2b96skJAQ3XvvvfZOwmXLlumVV17Rpk2b9L///U/333//Sc+1WCxKSEhQo0aNlJKSory8PH388ccuOTdwJitWlO5r5eNjVUpKO5OrgTdJPjEIpKioSFu2bDllZ7gnsdlseu211zRhwgT797w7Bg/Uw1dcxnJfL/bhgtLuP18/qzpf2NZl560THa31O3YqLy9Phw8fVnSZZcFwrda92qhVz9b6Y+E6TZ48WTfccINSUlLMLgsAYKIbn71ZyefUM7uMk6T9uVPvjn7H7DJgMof/ZvLYY4+pTZs2mjx5slJTUxUSEqL+/fvr3//+t4KCgk56/Kuvviqp9BeoAQMGOLocSaVdGXv37lVAQIAef/xxxZ7oxggICNBVV12lw4cP69tvv9X06dPVs2fPSi+b3b59uxYvXixJuueee9SpUyf7fZ06dVJJSYmee+45LVy4UJdddpnq1ft/9u47vs3y3P/4R5L33nvGzt57kEkIe5fRFE4PFFq6KS2nC0qhtJS257S00Jb+6KAts4RAIAGy9957OrEdO3GmYyfeQ78/ZAmHLDuRfGt836+XX4hIz6OvHcV+fOm+r+vsbwTf/OY3sdk+7au2atWqDn9OV/rcIpfi7P+Xm9uXsNAIw2nEn7SfBLxjxw6fLgA2NTXxve99jzfffBOAmIgIXvzGV5k00LPTYMWs6tpaPljl+B45bGJfomIiumwQhHMQCEBZeZkKgIZN/cl9bF+6jebmZn7605+qH6CISIDL6Z1LjxE9TccQOS+PNCS69dZb+fDDD9m5cyfr1q3jueeeIyYm5ryP/X//7//R2tpKa2sraWlpnojDokWLABg/fryr+Nfe5z73OSwWCydPnmTr1q0dPu/ixYux2+2kp6efVYBzGjNmDOnp6djtdhYvXnzO/e2Lf511pc8tcjFNTU2sX78egJ7q/ydulpKcQ2iI4w0hX+4DWF9fz4MPPugq/uWnpfLBM0+p+BcA3l++kvrGRqBrhn+0FxsZQWRba4/ysvIufW45V0b3TK7+L8fukdmzZ7uuOUVERES8jd93JK+rq2Pv3r0ADBky5LyPSU5OJisrC4DNmzd3+NxbtmwBYPDgweftwWOxWBg8ePBZj3UXk88t/m/Dhg3U1tYC0LPHCMNpxN9YrVaysnoBsH37dsNpLk9NTQ33338/s2fPBhxTfmc8/RO6pXvmjSzxHna7nTcWLgIgLSeJ7v1zuvT5LVhcqwA1Cdg73P7YHUTGRgKOnTBdtRpUREREpDP8vgDobJINXHQbrPO+gwcPdui8drvddeF9sfPm5OR06rze/twSGJYtWwY4Csm9e527wlTkSuVkOwqAO3fuNJyk8+rq6rjvvvtcq6snDujPv7//PeKiogwnk66wZf8BdpQ6fq6Ov2mIkSEcmW3bfquqqjh9+nSXP7+cLSo+mtu/+zkAdu3axb/+9S/DiURERETO5ffdyU+ePOm6nZCQcMHHOe+rrKzs0Hnr6uqor6/v8Hnr6uqoq6s7bx/EzvLEc7/22mu88cYbF7x/6tSpfOELX7jMxOeyWq2u/8bHx7vtvPLpCPrY2NjLnki5YsUKALrlDyA5Od1t2Xyd82trsVjc8m85kHXrNoCFi9/kyJEjNDc3u75fXcnrtis0NzfzpS99ieXLlwNw08gR/OWxbxMaHGw42cXptes+by91vEESFGxj3E1DsAU52nk4/9sVclJTXLePHj1KSkrKRR7tu3zpdXvjl29i0esLKN9Txq9//Wu+9KUvefX1jTuuFeT8dI3rOXrdeo5etyKBwWMFwE2bNvHxxx+zbds2KisrXQWri7FYLMyfP9+tOdo/b2ho6AUf57yvrq6uQ+dt/7iOnNd5jLsKgO5+7pqaGo4ePXrB+2tra6+oZ+GFWCwWj5xXPv1B3lm1tbWugTT9+40zsrrFF+jrcmXycvu6bu/YscPVA/ZyX7ddobW1lUceeYQPP/wQgClDh/DX733H5yb96rV7+U7X1vLeMkfxd9iEvsTEfbrq00LXfV2T4+IIDQ6moamJ0oOl9O/fv8ue2xRvf90GhwTz388+wHP3/pwTJ07w85//nBdeeMF0rEvy5u+5vk7XuJ6j163n6HUr4t/c/lvL4cOHefDBB5k7d26njrPb7V5/cefPIiMjL7qCICIigpaWFrc9n9VqxWKxYLfbaW1tddt5xfGD22q10traelnvji5ZsoTGtub2/fqO0zus7bT/HqWvy5XJaTcJeNOmTUycOPGKXrdd4ec//zn//Oc/ARjZuxd//d53CLLZvDZve3rtuse7S5dRU98AwIRbh2HH8bW0YHHd7goWi2Ma8P7DFZSWlPrt36mvvW4HXj2YIVOGsmHuel566SUefvhhevfufekDDbjSawW5MF3jeo5et57jza9bFSRF3MetBcAzZ84wadIk9u7d6zXflMPaJuUBNDQ0EBERcd7HNTQ4Lug7ukKv/eOcx17svJ05t4nnvv/++7n//vsveP/x48c7vD26I+Lj47HZbLS2trr1vOL4IRkfH09VVdVlFW0/+uijtvMEk5c3sMOrYgNBeHi46+JIX5crY7OFkpCQzsmTh1m3bh1VVVVX9Lr1tI8++oinn34agB5Zmfz1O9/C0trqM68DvXbd49XZjjc3U7MSKOyXRXNTMxaLhaCgIFqaW7r02ic9IYH9hys4evQolZWVZ13v+AtffN3e/eN72bxwEy3NLXz729/m7bff9so3uK/0WkEuTNe4nqPXred48+s2KSnJdAQJAM6f1QsXLmTixIlmw3iQW9dP/+53v2PPnj0AZGVl8ec//5l9+/ZRX19Pa2vrJT888Y28fY+89v0AP8t5X0d7HoSHh7uKah05b/vHXymTzy3+b+HChQB0LxxCWOj5C+Yi7pCd5VgZs2PHDsNJLm7nzp18/etfByAuKpK/ffdRYiMjDaeSrrblQDHbiksAGH/zUONFnYzET69vyg+VG0wi7aUXZHDNg9cCjp+nnd0RIyIi4g0eeOABLBbLOR9RUVH06tWLL3/5y2zevPmc4/Ly8s45xmq1EhcXx7Bhw3jyySepqKi45PMvXLiQhx9+mJ49exITE0NERAT5+flMnTqV9957zxOfckBwawHQ+ReRlpbG2rVreeSRR+jWrRshISHufJpOycrKcl2kl5aWXvBxzvuys7M7dF6LxUJWVpbbz+vtzy3+7fDhw2zbtg2AgQMmGU4j/s45CXj37t00NzcbTnN+NTU1PPjgg9TU1GCzWvnTN79Brp8OXJCLe3PhIgBsQVbGXDfQbBggLT4eW1sfrLKyMsNppL1bv3070QnRADz11FOuthoiIiK+Jjg4mNTUVNdHfX09u3fv5q9//SvDhg3j5ZdfPu9xkZGRrmMSExOpqqpi/fr1/OIXv6Bfv36unvOfderUKW699Vauvvpq/va3v7Fnzx6am5ux2WwUFxfz1ltvceeddzJ69Ghd/1wGtxYAi4qKsFgsfP3rXyc1NdWdp75s4eHhdO/eHYANGzac9zHHjx/n4MGDAAwc2PGL+gEDBgCwcePGCz5m06ZNZz3WXUw+t/ivefPmuW4PGjjZYBIJBNltfQDr6+vZv3+/4TTn9+STT1JUVATAjz9/D2P79TGcSEw4XVvH+yscF6qDx/YmOs78CtAgm420tl0L5WVaAehNImMj+dz/3A04ro3/9re/GU4kIiJyecaMGUNFRYXro7a2ljlz5lBYWEhzczPf+MY3zrsS8PHHH3cdc+zYMaqrq3n55ZeJjo7mxIkT3HXXXecMiq2qqmLcuHF8+OGHhISE8IMf/IB9+/ZRW1vL6dOnOXToEL/+9a+Jjo5m1apVjB49+qILouRcbi0AOhuG9uzZ052nvWLOPdxLlizh2LFj59w/ffp07HY7CQkJnZqkN378eCwWC4cOHWLlypXn3L9ixQoOHTqExWJx+z5yk88t/stZAExMyCArs4fhNOLvnCsAAdfKU2/ywQcf8NprrwEwaeAAHr7hOsOJxJT3lq+gpu0idcItQw2n+VRGUiIAFRUVXruKNlCN//xEsvvkAPC///u/573+FBER8TUhISFMmTKFGTNmEBwcTGtr6wVXAbYXHR3NI488wm9/+1sAysvLmTFjxlmPeeSRR9i2bRthYWF8/PHHPP/88xQUFLjuT09P53/+539Yvnw5iYmJlJWVMXXqVK8bXOPN3FoAzM3NBeD06dPuPO0Vu+6660hLS6O+vp5nn32WAwcOAI4hGdOmTWPWrFmAYxBGUNDZc1Eefvhhbr31Vl544YVzzpufn8/48eMBePHFF1m1ahV2ux273c6qVat46aWXAEcBMicn55zjm5ubqa6udn20b3Dd/s+rq6vd/twin9XQ0MCiRYsAGDTwauP9rcT/pacVEBwUCnhfAfDw4cN897vfBSA5Nob/+8rD+jcRoOx2O/+cNx+A9Nwkeg3OMxuoncy2PoAtLS0cPnzYcBppz2qz8oWfOoarVVdX8/zzzxtOJCIi4j59+vRh2LBhAKxbt67Dx91///1Y21qYtD9u/fr1vP322wA888wzXH311Rc8R//+/fnjH/8IOBY+vf/++52Nf1FlZWV85StfITs7m9DQUPLy8vjOd75zwfkLTz/99FkLr9555x3GjRtHXFwcCQkJ3HDDDWd9rtXV1Tz11FP07NmT8PBw0tPT+cY3vsGpU6fc+nmcj1unAN96663s2LGD5cuX8+CDD7rz1FckODiYJ598kieeeILi4mIeffRRIiIiXMNJAG6++WauueaaTp/761//OocPH2bPnj0899xzrn6Hzn4vvXr14mtf+9p5j925cydPPPHEee/77ETeDz74wK3PLfJZK1eupLa2FnAUAEU8zWYLIiu7JwcObGHr1q2m45zlhz/8IVVVVQD831ceJik2xnAiMWX1rt3sLT8EwKTbhntVITg9McE1JbesrEw9f71M79F9GHbDcNZ9vJZ///vfPPDAA53aaSIiIuLNnHMJnNfMHREWFkZiYiLHjh0767i//OUvAMTGxvLNb37zkue59957+clPfsLevXv5y1/+wp133tnJ9OdXVFTEPffcw7Fjx4iKisJms1FSUsLvf/973n//fZYsWXLRBVZPPPEEzz33HEFBQYSHh1NVVcUnn3zCkiVLmD9/PgUFBUyePJmtW7cSGRlJa2srFRUV/OlPf2LNmjWsWLGC4OBgt3wu5+PWFYDf+ta3iI+P5/XXX2fXrl3uPPUVy8nJ4cUXX+S2224jPT2dpqYmIiMjGThwID/+8Y/5yle+clnnDQ8P5/nnn+dLX/oSBQUF2Gw2bDYbBQUFPPTQQzz33HOEhYW5+bMx/9zif5wrYUNCwujT+yrDaSRQ5OX0BfCqAuDMmTP56KOPAPj8xPFMHKg+qoHsn3Mdq/9Cw4IZfa354R/thQWHkBTjKE6rEbZ3uveJqQSFBmO323nyySex2+2mI4mIiLhFSUkJAPFtPYk7oqamhuPHj59z3MKFCwG49tpriYiI6NC5brvtNgCWL1/utlYo3/ve94iNjWXp0qWcPn2aM2fO8MEHH5CcnExJSQlTp0694M/yTZs28Zvf/IYXXniBqqoqqqur2bJlCz179qS2tpbHHnuML3/5yzQ2NrrOf/r0af76178SFBTEunXrPN432K0rANPT011TWaZMmcLrr7/u2qbqDeLi4njooYd46KGHOnzMX//610s+JigoiNtvv53bb7+9U3n69+9/3pV9nXG5zy3SXktLi6sAOLD/JEJDww0nkkCR01YAPHr0KBUVFYSGhhrNU1VVxQ9/+EMAkmNj+fHUe43mEbMqKiuZvd4xQGzUtQMIjzT7+jyfjKREjlVVcejQIVpbW13basQ7JOekcP2Xb2DmSx+wYsUKZs6cyS233GI6loiIyBVZu3ata1vrqFGjOnzcyy+/7CqgOY9rampi3759AAwaNKjD53IOcK2pqaGkpOSsfoGXq6GhgY8//pjCwkIArFYrt9xyC++++y7jx49nxYoVfPzxx9x4443nHFtVVcXTTz/No48+6vqz/v3788orrzB+/HhWrVpFcHAwO3bscJ0/JCSEhx56iBUrVvD3v/+dd955h69+9atX/HlciFsLgD/72c8AuOaaa5gxYwaTJk1i0KBBjB49mqSkpA5dlD711FPujCQiHbBmzRpXg/Lhw24wnEYCSW7Op1N1N23axMiRIw2mgV/84hccOXIEgJ/99/3ERZqf9irmvLlwMc0tLYBj+683ykxMYHPRfhobGzl27BipqammI8ln3PyNW1n2nyWcOnqKp59+milTpmiHhoiI+KRDhw4xf/58vv/979Pa2kpISAjf+MY3LnpMS0sLBw4c4PXXX+eXv/wlAIWFhdx8880AZ/XWS0xM7HCWpKQk1+0TJ064pQB4zz33uIpz7Y0bN47x48ezZMkS3nnnnfMWAENCQlw9xNu76qqrCAsLo76+nrvvvvu85588eTJ///vfPb4ryq0FQGfzQ8DVk2bTpk1s2rSpw+dQAVCk6zlX/9lswer/J10qJ7u36+fFxo0bjRYAd+zYwT//+U8Arhk8iBuHDzOWRcxram7m9QWLAOg+IIesbt5ZWMtsd6FcVlamAqAXCosM4+4f3ssr3/0LpaWl/PnPf+axxx4zHUtEROSSFi9efMH+xxEREbz66qv06NHjnPueeeYZnnnmmfMel5ub65oi7G2cgzzOZ8KECSxZsoQNGzac9/68vDyio6PP+XOr1UpSUhJlZWX069fvvMc6r98qKys7H7oT3FoABM7ZD92ZXife1FhbJFC0trYyc+ZMAPr1HUdEhIYdSNcJC4skNTWfior9nXqzyN3sdjs/+clPHO9kBgXx0//6gn4mBbg5GzZytG0am7eu/gOICg8nNjKSqpoaysvLGTp0qOlIch6j77yK+f+ax/5NRbzwwgtMnTqVtLQ007FEREQuKjg4mISEBMBRr4mIiCArK4tx48bxla985YIDMSIjI4mKigIcBbDo6GgKCwu5/vrreeCBB84qlDnPD46VfB3l7CX42XNciczMzEved/To0fPen56efsFjbTbbRR/jvN9dvQwvxK0FQGfjRhHxHatXr6a8vByAEcPPXcos4ml5OX2pqNjPxo0bjWWYM2cOS5YsAeCh668lNyXFWBbxDv9qG/4RmxDFkHG9Dae5uMzERKpqajQIxItZrVa+8NP7+fkdz1BbW8uzzz7LH//4R9OxRERELmrMmDEsWrSo08c9/vjjPP300x16bHBwMAUFBRQVFXVqQcDmzZsBx0rE3NzcTmcMRG4tAE6YMMGdpxORLjBt2jQAgoNDGT70esNpJBDl5PRh1ZoP2bdvH6dPn+7w5C93aWxsdLWfSIqJ4Zu3qkF/oNtTXs7KnbsAGHfTEIKCbYYTXVxGUgI7SkupqamhsrKyU9P4pOsUDu3O6DvGsPK9FfznP//hi1/8ovG+pyIiIt7g6quvpqioiDlz5lBbW9uh3wdmzJgBOHrsuWs78aFDhy55X4oPLxTQqDiRANbQ0OD6xjlk8BRt/xUjctsmAdvtdnbs2NHlz//GG2+wf/9+AP7n7s8RHaEp2IHu3/MWAGC1Whh/i/dvqf1sH0DxXvf8aCphkY4BID/4wQ88vtVHRETEF3zlK18BHJN0X3rppUs+/u2332bv3r0APPLII27LsXjx4kveN2TIELc9X1dTAVAkgM2bN4+qqioArhp9h+E0Eqjycvu6bnt68tVn1dfX89vf/haAwowM7pkwrkufX7xPdW0t05YuB2DQVb1ISPb+N0bio6OICA0FVAD0dvFp8dz22J0AbN++nX/84x+GE4mIiJg3bNgw7rrrLgB++tOfsmDBggs+duvWra7Jw6NHj+aOO9z3e+zbb7/tWhjQ3ooVK1ztgu6++263PV9X83gBsKysjDlz5vDWW2/xr3/9y9NPJyKd8M477wAQFRXPgP7awi9mxMYmExfrWErf1QXAf/7znxw+fBiAx+68HZtV74sFurcXLaGmvh6AyXeOMJymYyxYyGhbBejs6Srea8qD15LR3dFI/Je//OUFm4mLiIgEkldeeYU+ffpQX1/PDTfcwI9+9KOzinEVFRX85je/YezYsZw4cYL09HTefPNNrG68fg8JCeH6669n+XLHm8Gtra3MmjWLO++8E7vdzpgxY7jhhhvc9nxdzWO/6fz973+nb9++5ObmcsMNN3Dffffx4IMPnvO4X/ziF1x77bU89NBDnooiIudx6tQp5s6dC8CoEbcQFBRiOJEEsty2VYBdWQCsqanh97//PQC9c7K5acSwLntu8U7NLS38Y47j+2JO9zR6DPSdhtKZSY4CYGVlJTU1NYbTyMUEBQfxXz//bwBOnz7NM888YziRiIiIeXFxcSxbtowbb7yRxsZGnn/+eQoKCoiMjCQmJob09HS+//3vU11dzYgRI1i1apXbh3/87//+L6dOnWLs2LFER0cTFRXFzTffzJEjR8jNzeXNN9/EYrG49Tm7ktsLgHV1ddx00018+ctfZteuXdjtdtfH+QwbNox58+bx6quvsnPnTnfHEZELmDFjBo2NjQCMHXOn4TQS6JwFwJ07d9LU1NQlz/n3v/+dY8eOAfC9z93h1ncPxTfNWb+BsuMnALjmc6N86gIvIzHBdVvbgL1f79F9GHX7GAD+85//sHLlSsOJREREzIuPj2fWrFnMmzePBx98kMLCQiwWC83NzeTm5nLPPfcwbdo0Vq1aRU5Ojtufv7CwkA0bNvDwww8TFxdHS0sLOTk5PProo2zYsMEjz9mV3DoFGOCLX/wiH3/8MQB5eXlMnTqVyspKXn755fM+fsqUKSQnJ3P8+HFmzpxJ79693R1JRM7jtddeAyAtNZ+CgsGG00igy2sbBNLQ0MC+ffs8/rOgrq6OP//5zwAMyM9nyhD9GxD46ydzAIhNiGL4pL6XeLR3SYmLJSQoiMbmZsrKyujZs6fpSHIJ9/54KpvmbaD+TD0//OEPmT9/PkFBbr80FxER6bRXX32VV199tdPHFRcXu+X5J0+ezOTJk91yro747IK1V155pcPHPv300zz99NMXfcylvi4TJ0684KI5d3Lrcof58+fz7rvvYrFYmDp1Krt37+YXv/gF11133YUDWK1MmTIFu93OsmXL3BlHRC5gy5YtbNq0CYCJE6b61CoX8U+5XTwI5O2333at/vvWbTfr34CwuWg/6/Y4pslNvG0YwSG+VYixWqykJzhWAWoFoG+IT4vnju9+DoAdO3bwt7/9zXAiERER8WduLQA6K8TdunXj1VdfJTg4uEPHDRw4EEBbgEW6iHP1n80WzLixdxlOIwKpKXmEhUUCsG3bNo8+V3NzM3/84x8BKMxI1+o/AeBvsx2r/4KCbUy81Tf7QWa09QE8duwYDQ0NhtNIR0z+7ylk9cwC4Fe/+hUVFRWGE4mIiIi/cmsBcPny5VgsFr74xS92uPgHkJGRAaCLHpEuUFNT45r+O3TItcTGJBlOJOJYDZ6X2w/w/ArADz/80LUM/6s33ajef0LFyUpmrl4LwKgpA4iOizSc6PJktvUBtNvtlB/SNGBf4BgI8gDgGAjys5/9zGwgERER8Vtu/a3nyJEjAJ3uOxMWFgZAfX29O+OIyHnMmDGDM2fOADBpwlTDaUQ+lZ/nKABu27bNYz0w7HY7L774IgBp8fHcftVojzyP+JZ/zp1Pc0sLAFPuGmU4zeVLS4jH1lbQLi9TAdBX9BzZi9F3XAXAO++8w/Llyw0nEhER8T2PPvooaWlpnfoING5tcGOz2QBobW3t1HEnT54EHGOfRcSz/v3vfwOQnJxN3z5jDacR+VReWwHw1KlTlJeXk5WV5fbnWLZsmWuF4ZdvuI4QNdwPeLX1Dby+cCEAfYZ1IzM/xXCiyxdsCyIlLo7DJ0+qD6CPufcJx0CQutN1fP/732fhwoWEhISYjiUiIuIzqqqqXIvS5PzcugIwNTUVgH379nXquPXr1wOQnZ3tzjgi8hk7duxg3bp1AEwcP1VbH8WrdMvv77rtqW3Af/3rXwGICgtj6qQJHnkO8S1vLV7CqTM1gG+v/nNy9gGsqKigpW1Vo3i/uJQ4Pvc/dwOwZ88eXnrpJcOJREREfMurr76K3W7v1Eegcetv/2PGjMFut/P+++93+BhnPzKLxcLYsVqNJOJJztV/VquN8ePuNpxG5GzZWb2w2Rwr8rZs2eL285eWlvLJJ58AcPf4cUSFh7v9OcS3NDU388pHjtdEVrdU+o0oNJzoyjn7ADY3N3O44rDhNNIZV//XNeQP7AbAb3/7W/bv3284kYiIiPgTtxYA777bUVDYuHEjf//73zt0zNe+9jUqKysBuO+++9wZR0Taqa2t5T//+Q8AgwddQ3xcquFEImcLCQkjM6M74JkVgP/4xz9cLSr+e8pkt59ffM8Hq1ZTfuIEANd/fgwWi8VwoiuXmZjouq1twL7FarPywPMPYbVZaWho4Pvf/35Ark4QERERz3BrAfDmm29m1KhR2O12vvrVr/LLX/7SNWzgszZu3MhNN93E66+/jsVi4YYbbmDEiBHujCMi7cyYMYPq6moArp6oYrt4p/y8AYD7VwDW1tby2muvATBp4AC6pQde0185m91u5+WZHwOQmBrL8Kv7GU7kHmEhISTFxAAaBOKLcvvmcu1D1wOwePFi3n33XcOJRERExF+4vQHY22+/TVpaGs3NzTz55JOkpKTwne98x3X/8OHDSU9PZ9iwYXzyySfY7Xays7N59dVX3R1FRNr517/+BUByUjb9+403nEbk/JyDQA4fPszRo0fddt53332XU6dOAfDAtde47bziuxZs2szuthVy194zGpvNf3qiOvsAlpeXawWZD7r9sTtJzHT8Hf7kJz9x7ZQRERERuRJuv9rNzs5m9erVrpWA9fX1lJaWurbVbNiwgSNHjriaLo4cOZIVK1aQlJTk7igi0mb79u2fDv+YoOEf4r3y8zwzCMT5JlNeaioT+vvHSi+5Mn+e+REAUbERjL1xiOE07uXsA9jQ0MCx48cMp5HOCosM47+efQCA48eP87Of/cxsIBEREfELQZ44aXZ2NitWrODDDz/kn//8J0uWLOH48eOu+6OiopgwYQL//d//zV133eWJCCLSzj//+U8AbLYgJoy7x3AakQvLyemDxWLBbrezZcsWJk++8l59mzdvdm0pvu/qiSqAC+v27GXN7j0ATL5jBKFhwYYTuVdm0tl9AFOSUwymkcsx6JrBDLthOOs+Xstrr73GPffcw+jRo03HEhGRSyjdWWI6wnl5ay7pWh4pADrdcsst3HLLLYCj/9KpU6eIiooipq03jYh4Xk1NDdOmTQNgyOApxMXpF0HxXmGhEaSnF3Do0D639QF8/fXXAQiy2fjc2Kvcck7xbc7VfyFhwUy6fbjhNO4XHR5BTEQE1bW1lJeVM2Swf61wDBT3PfNfbFu6lfoz9Tz++OMsXLiQkJAQ07FEROQiXv1Rx4ahipjQZcsgIiIiyMjIUPFPpIu99957nD59GoDJk+43nEbk0vJyHduA3bEFuK6uztVEf8qQQSTF6mdQoNtdVs7cDRsBGH/TEKJiIwwn8gznKkBNAvZd8WkJ3PV9x6r9PXv28NJLLxlOJCIiIr5M+6BE/Jxz+EdKSi59emv1k3i/vFxHj76SkhLX4I7LNXPmTNf0689PnHCl0cQPvPj+BwDYgqxMudt/t1RmJDoKgGfOnLnif0diztX/dQ35A7sB8Nvf/pb9+/cbTiQiIufjnHHgCx9Tpkwx/eUSQy5rC7AnmxE/9dRTHju3SKDZvHkzGzc6VrpcPfEL6n0mPsFZAATYsmUL48df/tTq1157DYD0hATGa/hHwNt36BAfrl4DwFXXDyIxNdZwIs/5bB/AuLg4c2HkslltVh54/iGeufknNDQ08P3vf5933nnHNVxPREREpKMuqwD49NNPe+zCQwVAEfdxrv6z2YIZN/Zuw2lEOiY3p4/r9pUUAIuKilixYgUA90wYh00F8ID34owPsdvt2GxWbrxvnOk4HpUQHUV4aCh1DQ2UlZXRr58K4L4qt28u1z50PZ/8v49YvHgx06ZN4+679TNdREREOueyfxvqyNLSSz3us/eLiPvU1NQwffp0AIYPvZ7YmCTDiUQ6JjIylpSUXIArGgTyxhtvAGCxWLhn/Fi3ZBPfdaCighkrVgEw+toBJKXFmQ3kYRYsZCYmAFBeXm44jVyp2x+7k8RMx6rOp556Stu6RUREpNMuawXgwoULL3r/iy++yPTp07FarVx77bVMnjyZwsJCIiMjqampYd++fcyfP585c+bQ2trKnXfeyTe/+c3L+gRE5PxmzZrFmTNnAJgw/l7DaUQ6Jz+vP0ePllx2AbC5uZm33noLgLF9+5CdnOzOeOKDXpzxIa12O1arxe9X/zllJCay79BhTp48SU1tDZERkaYjyWUKiwzj/p/9N79/6LccP36cZ599lv/7v/8zHUtERER8yGUVACdMuHAj9ccee4z33nuP3r1789Zbb9G/f//zPu673/0u27Zt495772X69Onk5OToQkbEjd58800AEhLS6dtHwz/Et+Tl9mP1mpkUFRVx+vRpoqOjO3X80qVLOXr0KAD3jA+MYo9cWPGRo7y3fCUAI68ZQEpmguFEXaN9H8DysnJ69OhhMI1cqcFThjD0+mGs/2Qd//rXv7j33nsZMWKE6VgiIiLiI9zaEGnu3Ln8/ve/JyEhgQULFlyw+OfUr18/FixYQHx8PC+88ALz5s1zZxyRgFVSUsKSJUsAGDvmc1itNsOJRDqn/SCQbdu2dfr4adOmARAZFsa1Qwe7LZf4pj99MJOW1lYsVgs33Rc428GTY2MJDnJ8/y8rKzOcRtzhC0//F2GRYQA8/vjjNDU1GU4kIiLgaDnjKx9z5841/eUSQ9xaAHz55ZexWCw89NBDpKamduiY1NRUHnroIex2O3/5y1/cGUckYP373/929dUcN/Yuw2lEOu+zk4A7o7a2llmzZgFw/bChhIeGujWb+JaDx44xbdlyAEZM6kdaTuD0Q7VZraQnOFY7qgDoHxIzErnje58DYOfOnbp2FhERkQ67rC3AF7Ju3ToABg0a1KnjBg92rM5Ys2aNO+OIBCS73c6rr74KQPfCoaSndTMbSOQyREcnkJiYyYkT5Z0uAM6ePZuamhoA7rhqtCfiiQ/53fT3aW5pwWKBm+4PvO3gGYmJlB49xtGjR2lsbCQkJMR0JLlC1zxwLcvfXUbp9hJ+85vfcNttt5GdnW06loiIAF964Jfk5vQ2HeMcJaU7+furPzIdQwxzawHQ2W+poaGhU8c5H+88XkQu3+rVqykqKgJg/Ni7DacRuXx5uf04caKcrVu3duo45/bf5NgYxvTxvgsw6Tq7D5bx7rIVAIyaMpCMvMAbBuPsA2i32yk/VE5+Xr7hRHKlbEE2Hvjll3j2tqepra3lhz/8Ia+99hoWi8V0NBGRgJeb05uePdSfVbyTW7cAx8fHA7B48eJOHed8fFxcnDvjiASkd999F4Dg4FBGjrjZcBqRy+fcBrx7925qa2s7dMyJEydYsGABALeMGkmQTf0vA9lvpr2L3W7HFmTltgcnmo5jRHpCPFar43KvvKzccBpxl26DCpj0X5MBmDNnDh999JHhRCIiIuLt3FoAHDVqFHa7nddee42VK1d26JhVq1a53rUcNWqUO+OIBJzm5mZmzJgBwKCBVxMREWM4kcjlcxYAW1tb2bFjR4eO+eCDD2hubgbgjjHa/hvI1u/dx5z1GwGYeOswktLizAYyJNgWRGpcLKA+gP7mru/fQ2yy4+/2Rz/6EWfOnDGcSERERLyZWwuAjzzyCAAtLS1cd911vPzyyxecTtbU1MRf/vIXrr/+etcva1/72tfcGUck4Cxbtozjx48DMHrUbYbTiFyZvLzODwJxbv/NT0tlQDdtdQxUdrud599+B4DQsGBuun+84URmZSQ6tgEfPnyYlpYWw2nEXSJiIvjCT/8LcPzdPv/884YTiYiIiDdzawHwuuuuc030ramp4Rvf+AapqanccsstPPbYYzzxxBM89thj3HLLLaSmpvL1r3+d6upqAB566CGuvfZad8YRCTjvvfceAGGhkQweONlwGpErEx+XSlxcCtCxAmBpaalrmNTtY0arH1YAW7xlK6t37Qbg2ntGExMfaTiRWc4+gM3NzVQcqTCcRtxpxC0j6TehPwCvvPIKmzdvNpxIREREvJVbh4AA/L//9/+IiIjgpZdewm63c+rUqfP2JbHb7QBYLBa+9a1v8bvf/c7dUUQCSmNjI7NmzQJg+LDrCA0Np7W11XAqkSuTl9uPTacWdKgA+MEHH7hu3z5GLSUCVWtrK7/6j2MlaFRMONfeM8ZwIvOcKwDBsQ04MyPTYBpxJ4vFwheffYAnpvyQpoYmHn/8cT755BNs6n8qIiIin+HWFYDguBD5/e9/z5IlS7j99tsJCQnBbref8xEaGsodd9zB0qVLeeGFF7RSQ+QKLVq0iKqqKgCuuuoOw2lE3CMv17GyZdeuXZecMO8sAPbLzSU/Lc3j2cQ7zVy9hu0lpQDceP84wiNDDScyLzwkhMSYaECDQPxRSl4qt3z7dgA2bdrEa6+9ZjaQiIiIeCW3FwCdrrrqKqZPn051dTWrV6/mvffe49///jfvvfcea9asoaqqinfffZcxY/TOvIg7OLf/RkTEMHjg1YbTiLiHcxBIU1MTu3btuuDjDh48yMaNjoEPN44Y1iXZxPs0Njfzm3emA5CQEsOk24YbTuQ9nKsAy8vLXbswxH/c+MhNpBWkA/Dcc89RWVlpOJGIiPiyBx54AIvFcs5HVFQUvXr14stf/vJ5207k5eWdc4zVaiUuLo5hw4bx5JNPUlFx6XYkCxcu5OGHH6Znz57ExMQQERFBfn4+U6dOdf3eK53nsQKgU0hICMOHD+e2227jvvvu47bbbmPYsGGEhIR4+qlFAkZDQwOffPIJAMOGXk9wsFa8iH/o6CCQmTNnum7fOEJFn0D19qIllBw9CsCtD0wkOMTtnU58lrMPYH19vWtYlPiPoJAgvvDT+wE4efKkBoKIiIhbBAcHk5qa6vqor69n9+7d/PWvf2XYsGG8/PLL5z0uMjLSdUxiYiJVVVWsX7+eX/ziF/Tr149Vq1ad97hTp05x6623cvXVV/O3v/2NPXv20NzcjM1mo7i4mLfeeos777yT0aNHU1ZW5slP3S95vAAoIp63fPlyzpw5A8DwYTcYTiPiPokJGURFxQOwdevWCz7Ouf23d0423dK1/TcQ1dY38MJ7MwBIz01i9LUDDSfyLpmf6QMo/mfAxIEMnjIEgFdffZVt27YZTiQiIr5uzJgxVFRUuD5qa2uZM2cOhYWFNDc3841vfOO8KwEff/xx1zHHjh2jurqal19+mejoaE6cOMFdd91FfX39WcdUVVUxbtw4PvzwQ0JCQvjBD37Avn37qK2t5fTp0xw6dIhf//rXREdHs2rVKkaPHk1paWlXfSn8ggqAIn7AufovNCSc/n3HGk4j4j4Wi8W1DfhCKwDLy8tZt24dADcO1/bfQPX3OXM51tYH9Y6HrsZm0yVOezEREcRGOqYhHzx40HAa8ZSpT91PUGgwra2t/PjHP9Z2bxERcauQkBCmTJnCjBkzCA52/Ly50CrA9qKjo3nkkUf47W9/Cziu32fMmHHWYx555BG2bdtGWFgYH3/8Mc8//zwFBQWu+9PT0/mf//kfli9fTmJiImVlZUydOlWDLztBV8ciPq61tdVVAOzXbzwhIeGGE4m4l7MAuH37dpqbm8+5v/3235tGavtvIDp15gwvz3RMQc/vlcngsb0MJ/JOWUlJgAqA/iwlN4UbvnIjACtXruT99983G0hERPxSnz59GDbM8ca78434jrj//vuxWq3nHLd+/XrefvttAJ555hmuvvrCPe379+/PH//4RwBWrFjhlp91zn6FixYt4ujRo3zzm98kLy+P8PBwunfvzrPPPktjY6Pr8QsXLuSGG24gOTmZiIgIRo0addbvJE6rVq3CYrEQHR193t9j+vXrh8ViITQ0lNra2nPuHzVqFBaLpUNF1o5QAVDEx23evJnDhw8DMHTItYbTiLifsw9gfX09e/bsOed+5/bfHlmZFGZkdGk28Q5/mvkR1bV1AHzuK5OxWCyGE3mnrGTHNuDa2lqOn1AfQH918zduISE9AYCf/vSn1NTUGE4kIiL+KCsrC3Bs3e2osLAwEtvakrQ/7i9/+QsAsbGxfPOb37zkee699166d+9+1rHuUFJSwuDBg/njH/9IZWUlTU1N7Nu3j6eeeoqpU6cC8Oc//5lrrrmGOXPm0NjYSF1dHatXr+bWW29l+vTpZ51v2LBhREZGcubMmXMKpceOHWPHjh0ANDY2smLFirPuP3PmDOvXrwdg4sSJbvn8VAAU8XEff/wxABaLlcEDJxtOI+J++Xn9Xbc/uw348OHDrFmzBtD230BVcbKSf8yeC0DfYQX0GpxvOJH3cq4ABDhYqlWA/io0Iox7n/gC4Pge+dJLLxlOJCIi/qikpASA+Pj4Dh9TU1PjGkbW/riFCxcCcO211xIREdGhc912222Aox/++VbXXY7vfOc75ObmsnnzZqqqqqiurubZZ58FYPr06fz85z/n0Ucf5Qc/+AEnTpygqqqK4uJiRo8ejd1u59vf/jYtLS2u8wUFBXHVVVcBsGjRorOea/HixdjtdmJiYs57/7Jly2hubiYtLY1evdyzu0UFQBEf59z+27PHcKKjEwynEXG/lORcIsIdPxg/WwCcNWuW6/ZNI0d0aS7xDi+8N4OGpiYA7nj4wttFxNkH0HFRrW3A/m3ELSPpMbwHAH/605+oqKgwnEhERPzJ2rVrXSvaRo0a1eHjXn75ZVd/WudxzlV2AIMGDerwuQYOdAx8q6mpcRUjr5TFYuGjjz5iwIABAERERPDkk0+6tiT/5Cc/4f777+e5554jLi4OgNzcXN58800sFgvl5eXnrORzrt47XwEQ4Nvf/vZF758wYYJbPjdQAVDEpx04cICdO3cCMHTIdYbTiHiGxWIhN7cvcOECYEF6Gj0ytf030Ow/XMHbi5cAMGxiX/J66jVwKeoDGBgsFgv3PulYBVhbW8uvfvUrw4lERMQfHDp0iH//+9/ceuuttLa2EhISwje+8Y2LHtPS0sK+fft45plneOKJJwAoLCzk5ptvBuDkyZOuxzq3B3dEUrudDSdOnOjMp3FBX/3qV12FvfauueYa1+0f/ehH59yfm5tLYWEhAFu3bj3rPmcB77MrFZ0Fv6997WukpKSwdu3as/oAOu9XAVBEAJg7d67r9pDB11zkkSK+zTkIZOvWra5JX6dOnWLlypUAXDdsqPq+BaD/nTadltZWrFYLt39pkuk4PiGz7WK5trbWbRfL4p0KBhcy4uaRALzxxhvs2rXLcCIREfE1ixcvdg3IsFgsZGZm8sUvfpGKigoiIiJ47bXX6NGjxznHPfPMM65jgoKC6N69O08//TQNDQ3k5ua6pgh7m/79+5/3z1NSUgBHD0Nnoe+zUlNTAaisrDzrz4cPH35OH8Djx4+zfft2evToQUZGBhMmTDirD2BNTY3rse7q/wcqAIr4tAULFgCQltaN1JQ8s2FEPMhZAKytrWX//v0AzJs3z9VjY8qQwcayiRlbDhQzc7Wj/+PYGweTlt3xd4wDmXMQCEDpwVKDSaQr3PWDe7EF22htbeWZZ54xHUdERHxMcHAwqamppKamkpaWRrdu3Rg/fjxPPPEEO3fu5O677z7vcZGRka7j0tPT6dGjBzfeeCN/+MMf2Lp1K3369HE9NiHh0zZWnXlz0tlL8LPnuBLp6enn/XObzQY4inwXWnTgfExTW2sap+DgYMaMGQN8uqrP2f/PWdz77DZhZ/+/1NRUevfufbmfzjlUABTxUfX19a53CAb0d9+yYBFv5JwEDJ9uA3YOwEmOjWFwQTcjucScX/9nGgDBIUHc8kV9D+yo2IhIYtqaa2sQiP9LyU3hmv+eAjjeNFm6dKnhRCIi4kvGjBlDRUUFFRUVHD58mKKiIhYvXszPf/5zcnJyLnjc448/7jru0KFD7N69m1mzZvGtb32L6Ojosx4bHBxMQUEBAJs2bepwts2bNwOOPn25ubmd/+S60GcLfM7+fhcqADrvHz9+vFtzqAAo4qNWrVpFXV0dAAP7TzQbRsTD0tO6ERoSDjgKgA0NDa4VsJMHD8Jq1Y+zQLJ8+w6WbN0GwOQ7RxCfHGM4kW/JSnZsAy4rKzOcRLrCLd++nYgYR9H3pz/9qauNgoiIiLdwDtmYM2fOWX3wLmbGjBkAXHXVVV65nbi9z/YBdBb6nIW/Pn36kJqa6uoD+Nn73UW/MYn4KGfxIzgolF49Oz55ScQXWa02cnIcWwW2bNnC8uXLOXPmDKDtv4HGbrfzq7bVf+GRoVw/dazhRL4nK8mxDbimpoYTJ9UH0N9FxUVxy7duAxx9VKdPn244kYiIyNm+8pWvAFBVVcVLL710yce//fbb7N27F4BHHnnEo9ncYcSIEURERHDmzBlmz57Ntm3b6Nmz51lbjp19AOfOneuR/n+gAqCIz1q4cCEAPXuOIDQ03HAaEc/Ly3U05d2yZYtr+294aAjj+vU1GUu62Ox1G9hU5OgDecPUq4iK0fe/znKuAARtAw4Uk/97ColZjr/3X/3qV+f0JxIRETFp2LBh3HXXXYBjtbpzscv5bN261TV5ePTo0dxxxx1dkvFKtO8D+LOf/eys/n9Ozv9/7rnnaGpqIiUl5axeie6gAqCIDyovL3dN8xvQT72vJDA4+wBWVVUxa9YsAMb360dYSIjJWNKFmlta+PU77wIQmxDF5DtHGk7km87qA3hQBcBAEBIWwu3fcfyCVFxczFtvvWU4kYiIyNleeeUV+vTpQ319PTfccAM/+tGPXMP/ACoqKvjNb37D2LFjOXHiBOnp6bz55ps+0wrIuQ14zRrHELsLFQCd97u7/x+oACjik9q/IzJggAqAEhjy8/q7bh87dgzQ9t9AM33ZCvYdOgTAzV8cT2i4ir+Xy7kKUAXAwDHmzrGk5qcB8Jvf/IaGhgbDiURERD4VFxfHsmXLuPHGG2lsbOT555+noKCAyMhIYmJiSE9P5/vf/z7V1dWMGDGCVatWef3wj/YuVPBz6t27N6mpqRe83x1UABTxQc7tvwkJ6WRm9DCcRqRrZKQXEhwU6vp/i8XC5MEDDSaSrlTf2Mhvp78HQHJGPONuGmI4kW9TH8DAYwuycftjdwKOATB/+9vfDCcSERE5W3x8PLNmzWLevHk8+OCDFBYWYrFYaG5uJjc3l3vuuYdp06axatWqi04h9kbOPoAAPXv2JC0t7ZzHtC/6eaIAGOT2M4qIR7W2trJs2TIA+vcdj8ViMZxIpGsEBQWTnd2L/Qc2AzC0eyGJMZr+Gihem7+QQydOAnDHQ1cTFGQznMi3ZSW16wN48CCJCYkG00hXGXnLKD58cQaH9pbz85//nNtvv50QtVEQEZHPePXVV3n11Vc7fVxxcbFbnn/y5MlMnjzZLefqCLvdftH7H3jgAR544IGLPsY5ufdCQkJCqKmpuehj3nrrLY+26dAKQBEfs337diorKwHo03uM4TQiXSsj/dMVr1MGDzIXRLrU6do6XpzxIQDZhWkMm6jBL1cqJjLi0z6AGgQSMKw2K3d873MAHD58mH/84x+GE4mIiEhXUQFQxMcsX77cdbtP79EGk4h0vdDQT1ctDS4sNJhEutJfP5lN5ZkzANz58NVYrVr5fKUsWFyrANUHMLAMvX4YOX0dPZP+8Ic/UFdXZziRiIiIdAUVAEV8jHP7b1paN+Ljz+0bIOLPmho+3apWXVtrMIl0lZOnT/PKR58A0H1ADv1GqPDrLlnJ6gMYiKxWK3e09QI8evQob7zxhuFEIiIi0hVUABTxIS0tLaxcuRKAPr20+k8CS2NjI9XVLTh/dG11U48R8W5//nAWZ+rrAUfvP/U9dZ/2fQBLS0sNJpGuNvjaoWT3ygbgpZdeoqmpyXAiERGRK/Poo4+SlpbWqY9AowKgiA/ZunUr1dXVgLb/SuApKSnFbrcQFpYAwDYVAP1exclKXp07H4B+IwvpMSDXcCL/EhsZSWxkJAClJSoABhKr1crtj346EXjatGmGE4mIiFyZqqoqjhw50qmPQKMCoIgPcW7/BeitFYASYA7s3w9AVEQqAFsPlJiMI13gDzM+oKFtZdIdX7racBr/lJ3sWAVYWlp6yQl44l/G3DGWlNwUwNELsKWlxXAiERGRy/fqq69it9s79RFoVAAU8SHOAmBmRndiY5MNpxHpWvsPOAqA2SkFABw9dYojlacMJhJPKj5ylLcWLQFg2IQ+5PZIN5zIP+WkOH6W1NfXB+Q74YHMFmTjpq/dAsC+ffuYNWuW4UQiIiLiSSoAiviIpqYmVq1aBUCf3mMMpxHpWkePHuP06dMA9Mnr7/pz9QH0X7+b/h7NLS1YrBZu+9Ik03H8Vnbyp28mlZRoVW2gGXv3eOJS4wH43e9+F5CrIURERAKFCoAiPmLz5s3U1NQA2v4rgWd/2/ZfgKE9h2K1tA0COVBsKJF40u6DZby/wvGGx5hrB5Kek3SJI+RyRYSGkhwbC6gAGIiCQ4O54ZEbAdi2bRuLFy82nEhEREQ8RQVAER/hXP0H0KvnSINJRLregbbtvylxcSTExJKR7BgGsa1YBQt/9L/TpmO327EFWbnlvyeYjuP3stu2AZeXl9Pc3Gw4jXS1CVMnERETAcCf//xnw2lERETEU1QAFPERa9asASA9rYCYmETDaUS6Tn19A+Xl5QDkpzkGgOSl9wC0AtAfbTlQzOz1GwCYcMtQktLizAYKADltg0Cam5s5dOiQ4TTS1cIiw5j4BceQnQULFrB7927DiURERMQTVAAU8QF2u91VAOzRY7jhNCJdq7j4gKsvVV7q2QXAispKjlVVGcsm7vfC9PcBCA4J4sb7xpkNEyAyk5KwWh2XhMUlxWbDiBHXPDgFW5ANgL/85S+G04iIiIgnBJkOICKXVlRUxIkTJwDo0X2Y4TQiXcvZ/y8sJIS0BEez+rz07q77tx4o5upBA41kE/facqCYeRs3ATDh1qHEJUabDRQgQoKCSI+Pp/zECUpLSkF114CTkJ7I8JtGsGrGSv7zn//w4x//mKQk9d4UEemsktKdpiOcl7fmkq6lAqCID1i9erXrds/uWgEogcNut3PgwAEA8lJTsFosAGSnFmCxWLHbW1UA9CO/f28G4Fj9d/3nrzKcJrBkpyRTfuIEFRUVNDQ0EBoaajqSdLHrHr6BVTNW0tDQwKuvvsrjjz9uOpKIiM/5+6s/Mh1B5IK0BVjEBzgLgDHRiaSm5pkNI9KFKiqOUFtbC3y6/RcgNDiMzCTHIJCtxcUmoombbT1QzNwNGwFH7z+t/utaOW2DQOx2O6UHSw2nERPyB3ajx4ieAPz973+nvr7ecCIRERFxJxUARXxA+/5/lrYVUCKBwLn912KxnFUABMhNLwQ0Cdhf/P59x+q/oGCbVv8ZkBYfT3CQY2NIif5NBazrvnwDAMeOHWP69OmG04iI+A673e4zH1OmTDH95RJDVAAU8XLHjh2jqKgIgB6F6v8ngeXAAUcBMD0hnvDQkLPucw4COXTiJCeqq7s8m7jPtuIS5qxvt/ovSav/uprNaiUryTFhvrRUKwAD1eBrhpCc7VgN+o9//MNwGhEREXEnFQBFvNzatWtdtzUBWAJJXV0dFRUVAOR+ZvUffFoABMf2UfFdzt5/QcE2bpg61nCawJWd7Cj8nDhxgjNnzhhOIyZYbVYm/ddkADZt2sTGjRsNJxIRERF3UQFQxMs5+/8FB4eSl9vXcBqRrlNSUoLdbgcgNyXlnPtz2gaBgPoA+rIdJaXMXr8BgPE3a/WfSc4+gADFJcXmgohR4+6ZQFBoMODoBSgiIiL+QQVAES/nXAFY0G0QQUEhl3i0iP8obivqhQYHkxofd879oSHhpCdmA7D1gHqW+ao/z/wIcK7+U+8/k5JiYohom/5brFW1ASs6IZqRN48E4P333+fkyZOGE4mIiIg7qAAo4sUaGxvZsmULAIUFQwynEelazgJgTkoy1gsMv3FuA96mFYA+qfjIUT5c5VjlPObagcQnxxhOFNgsFgu5qY7VtsXFxa4VuBJ4rv7iNQDU19fz1ltvGU4jIiIi7qACoIgX2759Ow0NDQAUFAw2nEak65w4cZLTp08D59/+65Sb3h2AsuMnqDytnmW+5v999DGtdjsWq4XrtPrPKzgLgHV1dRw5csRwGjGl26ACcvvlAvDqq6/S2tpqOJGIiIhcKRUARbzY+vXrXbcLuw0yF0SkixW3W9GXc5ECYF5bARDUB9DXHD11ineWLAVg6Pg+pGYmGE4k4Ci4W9pW3B44cMBwGjHFYrFw9X85VgEeOHCAxYsXG04kIiIiV0oFQBEvtmGDozF+YkIG8fFphtOIdJ2StgEE8VFRxEZGXPBxuWndseAoVmxRzzKf8rdP5tDQ1AzAjV/Q6j9vEREaSkpcHKACYKAbddtowmMc33//8Y9/GE4jIiIiV0oFQBEv5lwBWKDVfxJAWlpaKC0tBT7djnghYSHhpLkGgRR7Opq4SXVtLa/NXwhA3+EF5HRPN5xI2nP+uzt8+LCrDYUEntCIMMZ+biwAc+bM0ZZwERERHxdkOoD4BpvN5pPn9mWVlZXs378fgMLCIVitHavXO7duWSyWDh8jnaevrXu1f90ePnyYpqYmAHJTUl33XUheRg8OnyhlW3Gx/l46wBu+Rq/NX8jpujoAbvzC2Ev+HXs1y6f/teDDn0c7+akprNm1m9bWVkpLS+nZs6fpSF7xuvUnHb1WmDD1aub+Yw4tLS1MmzaNb3/7210V0S/oGte9nF9PfV09S19fEf+lAqB0SHx8vEfOa7PZPHZuX7d69WrX7T69RxIWFtap40NDQ90dSdpYLJZO/31Ix4SGhnLwYBng+IU/Lz2NoKCL/6jqltGTlVvncfDYceqamomPjuqKqD7JG167dQ2N/O2TOQAU9M2m77BC3y4Atgmy+c8lVXZqCqHBwTQ0NVFaWsrAgQON5vGG162/utS1Qo8hPSgYVEDRpiLeeOMNnnrqKb/499oVdI3rOTExmhjvKXrdivg3/7laFY+qrKx06/liYmKw2Wy0tLRQXV3t1nP7i0WLFgFgtdrIzOhFfX19h46zWCyEhobS0NCA3W73YMLAExoaisViwW63a1ucm7V/3e7btxeAjIQEbBZobm6+6LE5qYWu2+t27WJc/34ezeqLvOm1+9q8BRyrqgLghqlX0dLSYjTPFbM4in/NLc3gR99yc1JS2Ftezr59+6irqzNS9PGm162/6cy1wrh7J1C0qYg9e/bwySefMGrUqC5K6Zt0jes5NpuNmJgYqqurff9nh5fx5tetCpIi7qMCoHSIJ3/I6gf4+a1duxaA7KxeBAeH0tra2qHjnFt57HZ7h4+RztPX1r2cr9uamhpXn6mclOQOFbFz0gpctzfvP8BVfft4JqSfMPnabW1t5ZWPPgEgLSeJAaN7+PwbFa5tv3Z8/nNpLzc1mb3l5VRXV3P8+HESExON5tH3XPfqzLXCiFtG8frT/6apoYl//etfDB8+vCsi+gVd43pGS0uLvrYepK+tiP9SQxURL2S329m4cSOgASASWIqLS1xFlNyUiw8AcQoPjSQtIQvQIBBvt3DzFvZXVAAw5XMjsVq1ldBbtf/3p2nAgS0iJoJhN44A4IMPPuD06dOGE4mIiMjlUAFQxAvt37/fte26oGCw4TQiXae42FFoCAsJISU+rsPH5aX3AGBrcbEHUom7/LWt919kTDijrjXbV04uLiYigsSYaEAFQIHxn58AQG1tLe+//77ZMCIiInJZVAAU8UKbNm1y3S7opl+SJXAUtxXwcpKTsXai51huencASo8e41RNjSeiyRXaWXqQ5dt3ADDhlqGEhgUbTiSXkpeaCsDBgwdpbGw0nEZM6jWqNym5jlWhb7zxhuE0IiIicjlUABTxQlu2bAEgNDSCjPTCSzxaxD8cP37ctbUsp4Pbf53y2gqAANuLS9yaS9zDOfnXFmTl6ttHGE4jHdEtPQ1w9IMq1uragGaxWBh3r2MV4Lp169i7d6/hRCIiItJZKgCKeKHNmzcDkJvTB6vVZjiNSNcoKipy3c5NTe7UsblpnxYA1QfQ+xyrquL9FSsBGDGpH3FJ0YYTSUekJyQQGuxYqdn+36cEpjF3jnVNg37nnXcMpxEREZHOUgFQxMu0tra6VgDm5fU3nEak6zgLDAnRUcRERHTq2IiwKFITMgH1AfRG/563gMbmZgCm3D3KcBrpKJvVSn6aYxvw/v37/WrKsXReYkYivUb3BmDatGmazCwiIuJjVAAU8TIHDhxwbYPMVwFQAkRzc/On/f86uf3XybkKcOsBbQH2JvWNjfx7/gIAegzMJad7uuFE0hnOAmBtbS2HKw4bTiOmjbnzKsDRF3L16tWG04iIiEhnqAAo4mWcq/9ABUAJHOXlh2hqagIg9zILgM5JwMVHjlBdW+u2bHJlZqxcxYlqx5saU+7S6j9fk5ea6hrIU7RP24AD3bAbhhMc6tgWrm3AIiIivkUFQBEv4+z/FxISRnpageE0Il2juPgAAFarlaykpMs6h7MACBoE4i3sdjuvzpkHQHJGPANH97jEEeJtwkJCyEhMBBzbgCWwhUdHMPjaoQDMmDGD+vp6w4lERESko1QAFPEynw4A6YvNFmQ4jUjXcG7/zUhIICT48l73uWmfTsxWH0DvsLGoiO0lpQBMum04VpsuO3xRfts04KNHj1JdXW04jZjm3AZcXV3N3LlzDacRERGRjtKVuIgXsdvtnw4AydX2XwkMtbV1VFRUAJCbennbfwEiw6NJjnf0l1MfQO/wz7nzAQgOCWLM9YPMhpHL1q2tDyBA0X5tAw50/cb3JzoxBtA2YBEREV+iAqCIFykuLnatrlD/PwkUJSWfFusut/+fU16aY4vp1gPFV3QeuXInqquZtXotACMn9yMqJtxwIrlc8dFRxEVFAeoDKBAUHMTIWxz9POfNm8fJkycNJxIREZGOUAFQxIs4t/+CCoASOJz9/8JDQkiJj7uic+WlOyYB76+o4HRt3ZVGkyvw9uKlNDY3AzDxtuGG08iVsGBxTQMuLS2lsbHRcCIxbcznHNuAm5qa+OCDDwynERERkY5QAVDEizi3/wYHh5KRUXiJR4v4B2f/v9x200Yv11mDQEq0DdiUltZWXpu/AID8Xpnk9cwwnEiuVEFbH8CWlhb2H9AwkECXP6AbqXmOovD7779vNoyIiIh0iAqAIl7EuQIwJ7uPBoBIQDhx4gRnzpwBIK9dn7HLldu2AhBgmyYBG7Nw8xbKjp8AYNLtWv3nDzKTEgkPDQVg7569htOIaRaLhRFt24BXrFjh6uMqIiIi3ksFQBEv0X4AiLb/SqA40K5XX17qlRcAo8JjSIpzrFRSH0Bz/tU2/CMyJpzhk/oaTiPuYLVYXasA9+/fT3Pb9m4JXM4CoN1uZ+bMmYbTiIiIyKWoACjiJUpLSzl16hSgAqAEjpKSYgASoqOJiYxwyznz0hyrALccOOCW80nnFB85yqItWwEYe8NggkO0mtlfFGY6tnI3NjaeNbxHAlNWzywyCh2vCW0DFhER8X4qAIp4ifYDQPJUAJQA0NLSwsGDBwHITb2y6b/t5Wf0BKDocAXVtbVuO690zOttvf8sFph46zDDacSdspOTCA0OBmDPnj2G04hpFouF4TePBGD16tUcOnTIcCIRERG5GBUARbyEswAYHBRKZkb3SzxaxPeVl5fT1NQEQG6K+wqA3TJ7uW5v2V/stvPKpTU0NfHO0uUA9B1RSHJGvOFE4k5BVhvd0hzbgPft20dra6vhRGLayLZtwICmAYuIiHg5FQBFvMS2bdsAyMruSVBQsOE0Ip7n7P9ns1rJSk5y23nz0ntgwTFNePN+TSvtSnM3bOTk6dMATLh5qOE04gkFmekA1NfXu1bwSuDK6J5JVq9sQNuARUREvJ0KgCJeYvv27QDkZvcxnESkazj7/6UnJBAS5L4+ceGhkaQnOX4h3bxffQC70psLFwMQmxBF/1FayeyP8lJSCLLZAG0DFgfnMJD169dTWlpqOI2IiIhciAqAIl7g+PHjHDlyBICcHBUAxf/V1ta6XvPu7P/nlJ/h2Aa8qUgrALtK6dFjLN3meCNjzPUDCQqyGU4knhAcFER+mmNi9969e7Hb7YYTiWkj2voAAsyYMcNgEhEREbkYFQBFvIBz9R9ATnZvg0lEukb7CaI5buz/5+QcBFJRWUlFZaXbzy/n+s/iJa7b424cYjCJeFpBhmMbcE1NDeWHyg2nEdPS8tPI7ZcLaBuwiIiIN1MBUMQLOPv/gQqAEhiKi4sBCA8JISUu1u3nP3sQiLYBe1pzSwtvL1kKQK/B+aRkJhhOJJ7ULS0Nm9VxCblr5y7DacQbjLjZsQ14y5Yt7FfvVREREa+kAqCIF3CuAExOyiYiIsZwGhHPcxYAc1KSsVosbj9/dko3bFZHX0H1AfS8RVu2cqTyFADjbhpsNox4XGhwMPlt04B3796tacCibcAiIiI+QAVAES/gLACq/58EguPHT3DmzBnAM9t/AYKDQshJKwDUB7ArOId/RMaEM2ScVjEHgp7ZmYCjn2dJacklHi3+LjknhfyB3QCYNWuW4TQiIiJyPioAihjW0NDgmqSo7b8SCJyr/wByPVQAhE/7AG7ef0CDCjyoorKSBZs2AzB6ygCCQ9w30Vm8V7e0NNf07p07dhpOI95g6PXDANi8eTMHDx40nEZEREQ+SwVAEcP27NlDc3MzoBWAEhiKix1bchOio4mOCPfY83RrmwRcXVtLcdvEYXG/aUuW0dK2BXTcTRr+ESiCbDYKMzIAxzRg588xCVzDbhjuuq1VgCIiIt5HBUARw9oPAMnVCkDxc83NzZSVlQGe2/7r5CwAgrYBe4rdbuftxY7hH936ZJGZ79m/U/Euzm3AjY2NFO0vMpxGTEvrlk5Gd8dr4qOPPjKcRkRERD5LBUARw5z9/8LCokhKyjacRsSzyssP0dTUBEBuSrJHnystKZuwkAhAg0A8Zc3uPZQcPQrA2Bs1/CPQZCcnExEaCmgasDgMvcGxDXjVqlUcbfveICIiIt5BBUARwz4dANIbq1X/JMW/Ofv/2axWspKTPPpcVouV/IwegAqAnvLu0uUABIcEMWyCWhgEGpvVSvcsx4qv/fv309DQYDiRmDbsesc2YLvdzuzZsw2nERERkfZUbRAxyG63uwqAudn65Vn8n7P/X0ZigmuAgCflpzsGgWwrLqFJPcrcqq6hgZmr1wAwZFxvIqLCDCcSE3q2FQCbm5vZs3eP4TRiWk7fXJKyHau7Z86caTiNiIiItKcCoIhBhw8fprKyEtAEYPF/NTW1ri1hnu7/55Sf6egD2NDUxO6y8i55zkDxybr1nKmvB2DMdQMNpxFTMhISiIlwbLXfsX2H4TRimsVicU0DXrp0KdXV1YYTiYiIiJMKgCIGtR8AognA4u9KSkpct3O7qADYLaOn67YGgbjXO23bf+OTouk9JN9wGjHFYrHQO8fRv7a0tJRTp06ZDSTGObcBNzU1MXfuXMNpRERExEkFQBGDnAVAi8VKVmbPSzxaxLc5t/+Gh4SQEhfbJc+ZEJNCTGQ8AFvUB9BtDp04wfK21V6jrh2A1abLiUDWJzfHdbv9G1sSmAqGFhKb7Pger23AIiIi3kNX7CIGOfv/pad1IzQ03HAaEc9yrgDMSUnBYrF0yXNaLBa6ZTi2AW/arxWA7jJ92QrsdjsAY64bZDaMGBcXGUl2sqPv27Zt21yvDQlMVquVIdc5tgEvWLCA2tpaw4lEREQEVAAUMco1AVj9/8TPHT9+nDNnzgBdt/3XqVtbH8A9ZeWcqavr0uf2R3a7nWlt23+79c4kPcez05zFN/TNc6wCPH36tGvatwQuZx/A2tpaFi1aZDaMiIiIACoAihhTV1fHgQOOLYnZWb0MpxHxrPYFgZyU5C597oJMR4G91W5nU5G2AV+pDfuK2F9RAcCY6weZDSNeo3tGBqHBwQBs3brVcBoxrdeo3kTEOIbDzJo1y3AaERERARUARYzZs2cPra2tAGRlq/+f+DdnATAhOproiK7d7t4tsxcWHFuON+zb16XP7Y+mLV0GQFCwjeGT+hpOI94iyGajZ3YWAPv27aNOq20DWlBIEAMnDwZg3rx5NDc3G04kIiIiKgCKGLJr1y7X7WwNABE/1tzczMGDBwHITe3a7b8A4aGRZKbkAbBhrwqAV6K+sZEPV60GYNCYnkRGq3epfKpv2zCQlpYWduzYYTiNmDb4GkcB8OTJk6xdu9ZwGhEREVEBUMQQZwEwNDSCpKRsw2lEPKe8vNy1+qOr+/85FWY5VqptKCrSgIIrMGf9BqprHSu7tP1XPis1Po6k2BhA24AF+k0YgC3YBsDs2bMNpxEREREVAEUMca6OyMrsgdWqf4riv5zbf21WK1lJZgZGFGb1AeDUmRr2H64wksEfvLtsBQCxCVH0HV5gOI14GwsW+uXlAXDs2DHKysvMBhKjImIi6DXK0YNVBUARERHzVHUQMcS5AjBL23/FzzkLgBmJCQQH2YxkcBYAQX0AL9fxqmqWbN0GwIjJ/bDZdAkh5+qdk+X6d75p4yazYcS4wVOGAI6+kPv0vVdERMQoXb2LGFBVVcWhQ4cAyM5SAVD8V01NDUePHgUgx9D2X4DUhCyiwh1bE9epD+BlmbVmDS1tg4tGXTPAcBrxVmHBIfTKdrS12L17N2dqzhhOJCYNumaI67ZWAYqIiJilAqCIATt37nTdzlIBUPxYcXGJ63ZeaqqxHBaLhYIsx1a0DXuLjOXwZe+vWAVAWnYiOd3TDKcRbzawWz4Ara2tbNmyxXAaMSkpK4ns3o7hMJ988onhNCIiIoFNBUARA9pPANYWYPFnxcUHAIgIDSW5bTiAKQWZjkEge8rLqa6tNZrF15QePcb6tpWTIyf3x2KxGE4k3iw5NpbMxEQANm/aTGvbylEJTIOmOKYBr1mzhpMnTxpOIyIiErhUABQxwLkCMCoqntjYZMNpRDzDbrdTUuJYAZibkmK8aNQ929EH0G63s6lov9EsvuaDVatdt0dM7mcwifiKgQWOVYBnzpxhz549htOISc4+gK2trcybN89wGhERkcClAqCIAc4CYHZWL+NFERFPOXr0GDU1NYDZ/n9O+Rm9sFgcP/Y27NM24M74YKVj+29erwxSsxINpxFfUJiRQWRYGADr1q0znEZMyuufT2xyLKBtwCIiIiapACjSxex2uyYAS0BwTv8FyEkxv9I1LCSc7JRuAGzQIJAO23XwILsOlgGO7b8iHWGzWhlU4Pj3dvjwYcrKygwnElOsVqtrGMiCBQtoaGgwnEhERCQwqQAo0sWOHDlCZWUlAFlZPQynEfEcZ/+/5NhYosLDDKdxKMxybAPesG+f+pJ10IwVju2/FgsMn9TXcBrxJQO65REcFATA2rVrDacRk5zbgGtqali+fLnhNCIiIoFJBUCRLtZ+AnB2Vi+DSUQ8p6mpifLycgByUs1v/3UqaCsAVtfWse/wYcNpvJ/dbmfGypUA9BqcT1xitOFE4kvCgkPol5cLwL59+zhZqQEQgarP2L6EhIUAMHv2bMNpREREApMKgCJd7OwJwFoBKP6ptPQgLS0tgGMAiLfonvXpCra1u/caTOIb1u/dR9nxE4C2/8rlGVzYDWtbr9u1a9ULMFCFhIXQd5xjgNDs2bOx2+2GE4mIiAQeFQBFuphzBWBiQgYRETGG04h4hrP/X5DNRmZigtkw7STHpxMX7RhisWb3bsNpvN+MtuEfQcE2hozvbTiN+KLYiEi6Z2YCsH3bNs6cOWM4kZgyqG0bcHl5Odu2bTOcRkREJPCoACjSxZwFwKwsDQAR/+Xs/5eVlESQzWY4zacsFgs9sh0r2dbs2mM4jXdram5m5uo1APQf2Z2IKO/o4yi+Z1jPQgBaWlpYs2aN4TRiyqDJg7G0rQbVNmAREZGupwKgSBdqbW1ld9uqo2wVAMVPVVdXc/Kko9dXrhf1/3PqmTsAgPITJyg7ftxwGu+1fPsOTlSfBmDk5H6G04gvS4mNoyA9HYDNmzdTU1NjOJGYEJscS/4gx2TouXPnGk4jIiISeFQAFOlCJSUl1NXVAZCVqQKg+Cfn9l/wrv5/Ts4VgKBVgBfzftv239DwEAaMVr9SuTIjejleQ83Nzaxdp4nAgWrg1YMA2LhxI8eOHTMbRkREJMCoACjShdpPANYWYPFXzgJgdHg4CdHeNzU2MyWPyDBHrjW7VQA8n7qGBmav2wDAkHG9CQkNNpxIfF1afDz5aakAbNq4idq6WsOJxISBkwYBjgnj8+fPNxtGREQkwKgAKNKFnAVAi8VKRnqh4TQi7tfa2kpJSQng2P7b1u7Jq1gtVrpnO7a0ahDI+c3buJma+npA23/FfUb2crzx1dTUxJrV6gUYiHL65RKbHAvAvHnzDKcREREJLCoAinShXbt2AZCWmk9IiBrqi/+pqDhCfVvhKMcLt/86OfsA7jt0mONV1YbTeJ8P2rb/RsdF0HtoN8NpxF+kJyS4VgFu3LiR6tP6txdorFYrA9q2AS9cuJCmpiazgURERAKICoAiXchZAMzKUj8t8U/O6b8Wi4XclGTDaS6sR86nfQDX7tE24PZO1dSwcPMWAIZP6ovNpksFcZ+r+vYBHL0AVyxfYTiNmDBg0kDAMTBKU6FFRES6jq7qRbpIY2Mj+/btAzQARPyXs/9fanwcYSEhZsNcRG5ad0KCHatw1QfwbJ+sXUdjczMAIyf3v8SjRTonOTaWXtlZAGzbto0TJ08YTiRdrd+4ftiCbQDqAygiItKFVAAU6SL79++nue2X6qxMrQAU/9PQ0MDhw4cB75z+216QLYjCLMdKpNW71AewvfdXOLb/JqXF0a1PluE04o9G9+mN1WrFbrezdMlS03Gki4VHR9BjuOON0Llz5xpOIyIiEjhUABTpInvabTPMzOxuMImIZ5SUlNLa2gp4fwEQoGfbNuAdJaWcrq0znMY7VFRWsnKno1XBiMn9sHjjFBfxeXGRkfTPywVg7969lJaWGk4kXc3ZB3DXrl0cPHjQbBgREZEAoQKgSBdxFgCtVhtpqfmG04i4n7P/X2hwMGkJ8YbTXFqPHMcgkFa7nfV79xpO4x1mrlqD3W4HtP1XPGtU716EBgcDsGDBAtebBxIYBrYVAEHTgEVERLqKCoAiXcRZAExNySMoyHt7o4lcLmf/v+zkJGxW7//xUpDZG5s1CIDVu9QHED7d/pvZLYXMfO9fxSm+KyI0lNF9egNw7NgxNm3eZDaQdKn0gnSSsx2DorQNWEREpGt4/29oIn7CWQDU9l/xR5WVlVRVVQGQ4wPbfwFCgkMpyOwFwMqdOw2nMW//4Qq2HHCs4tTqP+kKA/LzSIyJBmD5suXU1WkrfqCwWCwMmDwIgGXLlunvXkREpAuoACjSBVpaWlwTgDPSCw2nEXG/A22FI4DcVN8oAAL0zhsMwOb9BwK+D+CMlatct0dc3c9gEgkUNquVCQMcxeb6+nqWLVtmOJF0Jec24Lq6OpYvX242jIiISABQAVCkC5SUlNDQ0ABAZoZWAIr/cRYA46OiiIuMNJym43rnOwqALa2trN4duNOA7XY7M9q2/xb2yyYpLc5sIAkYuSkpFGZkALB582YqKioMJ5Ku0mtUb0LCHC1RtA1YRETE81QAFOkCmgAs/qy5udk1xTMvLdVwms4pyOxNSFAoAMu37zCcxpxtxSXsbyu8aPuvdLXx/fsSZLNht9uZPXu2BoIEiJCwEHpf1RdwDAJxDiASERERz1ABUKQL7G5bWWSxWEhPKzCcRsS9SksP0tzcDEBeqm8VAIODQuie49juGsgFQOf2X6vVwrCJfQynkUATGxnpGghy9OhRVq9ZbTiRdJWBVw8EoLS0lL2axi4iIuJRKgCKdAHnCsCkpCxCQ8MNpxFxrwMH9gMQZLORlZRoOE3n9WnrA7jrYBnHq6oNp+l6La2trgJgn+EFRMf5zhZu8R9DCruRGh8HwMoVKzl58qTZQNIlnH0AQduARUREPE0FQJEu4JoArP5/4oec/f+yk5MJstkMp+k8Zx9AgBUBOA14za7dHKk8BWj7r5hjtViZMmQwVquVlpYWZs+erS2hASAxM4msnlmAYxuwiIiIeI4KgCIe1tra6ioAZqSrACj+pbKyksrKSgDyfGj6b3t5ad0JD3WseluxPfAKgO+3rf4LCQ1i8FU9DaeRQJYcG8uw7oUAlJWVsWbtGsOJpCsMmDQIgFWrVlFdHXirsEVERLqKCoAiHnbo0CFqa2sBDQAR/7N//wHXbV8bAOJktdrolevoQxVofQAbmpr4aM06AAaO6UlYRKjhRBLoRvbqSUJ0NADz583n2LFjhhOJpw2cPAhwDJRatGiR0SwiIiL+TAVAEQ9zDgABbQEW/+Ps/xcfFUVcpO/2juvTtg245OhRyo4fN5ym6yzeso2qmhoARlzdz3AaEUcv0euHD8VqtdLc3Mz06dNdQ4bEPxUMKSQ8JgLQNmARERFPUgFQxMOc238BMtI1AVj8R1NTEwcPHgR8d/WfU5+8Ia7bgbQNeMbKlQBERIXRb0Sh4TQiDqlxcYzu3QuAiooKFi5caDiReFJQcBD9xzv6j86bN4/W1lbDiURERPyTCoAiHuYsAMbHpxEREWM4jYj7HDx40LUyJz/VtwuAGcm5xETGA7B8R2BsAz5TV8fcDZsAGDqhN8EhQWYDibQzrEd3spKTAEdvuNLSUsOJxJOc04CPHTvGli1bzIYRERHxUyoAiniYcwuwtv+Kv3H2/wsOspGZlGg4zZWxWCz0yXNsA162bUdATB+ds34j9Y2NgKb/ivexWizcNHIEocHB2O12Zs2aRU1tjelY4iH9Jw7AYrEAMH/+fMNpRERE/JMKgCIeZLfbP50AnKHtdeJfnP3/spKSCbLZDKe5cn27DQXgWFUVuw6WGU7jeTPapv/GJUXTY0Cu4TQi54qJjODaYY7t+WfOnGHmhzMDojgfiGKSYskf2A2AuXPnGk4jIiLin1QAFPGgo0ePUlVVBWgFoPiXyspKTp06Bfj+9l+nfgXDXLcXbdlqMInnnaiuZsnWbQAMn9QXq02XA+KdeufkMKjQ0T+3tLSUZcuXGU4knjJgkmMa+4YNGzgeQMOYREREuoqu+EU8qP0AEBUAxZ/s37/fddvXB4A4xUcnkZWSD8BiPy8AfrRmHS1tjfa1/Ve83dWDBpIa7+jRuWrlKor2FxlOJJ4w4GpHAdBut2vwi4iIiAeoACjiQc7+f6ACoPiXAwcc/f8SoqOIjYwwnMZ9+hcMB2Dt7j3U1NcbTuM5769wbP9NzU4kt0e64TQiF2ezWblp5DDCQkIA+GjWR1RVVxlOJe6W1z+f6ETHsLR58+YZTiMiIuJ/VAAU8SDnCsCY6ESioxMMpxFxj6amJg4ePAhArp9s/3VyFgCbWlpYuXOX4TSeUXb8OGvbvjeNnNzP1XhfxJvFRkRyXVs/wPr6ej6Y8YFrCrn4B6vVyoCJAwBYsGABLS0thhOJiIj4FxUARTzo0wEgWv0n/qO09KDrF29/6f/n1D27HyHBYYD/bgP+YOVq1+0RV2v7r/iObmlpjOjZA4CKigpmz55tOJG424BJgwA4deoU69evNxtGRETEzwSZDtCVqqqqmDZtGmvWrOHEiROEhoZSUFDAjTfeyKhRoy77vM3NzcycOZPFixdz6NAhADIzM5kwYQI33XQTQUEX/zLv37+f9957j61bt1JdXU1sbCz9+vXjzjvvJD8//7zHHDlyhC9/+cuXzPaDH/yAq666qvOflLiFswCYqQnA4kec03+Dg2xkJiUZTuNewUEh9M4bxOa9q1i8ZZvpOB7hnP6b2yOdtOxEw2lEOmd0n94cq6riQMURduzYQVJSEiNHjjQdS9yk3/j+WG1WWltamTt3LiNGjDAdSURExG8EzArA0tJSvvnNbzJjxgwOHz6MzWajpqaGTZs28dxzz/HKK69c1nnr6ur44Q9/yN///neKiopoaWmhpaWFffv28be//Y0f//jH1F+kj9TixYt5/PHHWbx4MSdPniQ0NJQTJ06wePFivve977F06dJLZoiJiSEuLu68HyFt/XKk6508eZJjx44B6v8n/sXZ/y87OZkgP5we69wGXHzkCMVHjhpO4147S0vZWerYvq3hH+KLrBYLNwwfRkJ0NABLly6lqEhDQfxFZFwkhUMd10zqAygiIuJeAbECsKmpiZ///OdUVVWRm5vLd7/7XfLz82loaGDGjBm8/vrrfPjhh+Tn53PNNdd06tx/+tOf2LNnD5GRkXz72992rSRctWoVf/jDH9i1axd//vOfeeyxx845trS0lN///vc0NzczduxYHn74YRISEjh58iSvvPIKy5cv54UXXiA/P5+srKwLZvi///s/Uv1sG54/aD8BOCNTBUDxDydPVnLq1CkA8lL88/uOswAIsGTLVvKmTDaYxr2mL10BgMUCwyf1NZxG5PKEBgdz6+iRvLlwMQ1NTcycOZP77r+PpET/WpEcqAZMGsieNbvZtm0bhw8fJj1dg4pERETcwf+WbpzH7NmzqaioIDQ0lKeeesq1rTY0NJR77rmHG264AYDXXnutUw2lDxw4wJIlSwD41re+xejRo7FYLFgsFkaPHs03v/lNABYtWkRJSck5x7/++us0NzeTn5/P9773PRISHEMiEhISePzxx8nPz6epqYnXX3/9ij5/MaN9ATAzXVuAxT8UFe1z3c5L888CYGpCJsnxjl84F/lRH0C73c70ZcsA6Dkoj/jkGMOJRC5ffFQUN40cjtViobGxkfemv0ddfZ3pWOIGA68e5Lo9f/58c0FERET8TEAUABctWgTA+PHjSU5OPuf+z33uc1gsFk6ePMnWrR3/ZW/x4sXY7XbS09MZPXr0OfePGTOG9PR07HY7ixcvPuu+mpoa1q5dC8Dtt9+OzWY7636bzcbtt98OwJo1a6itre1wLvEOzgJgRHgMcXH+WSiRwOPcapcUG0NsZIThNJ7jXAW4YsdOGv1k0uiaXbspPepoS6Dtv+IPclNSGD/A8Vo+deoUH8z4gNbWVsOp5Epl9comPi0e0DZgERERd/L7AmBdXR179+4FYMiQIed9THJysmuL7ebNmzt87i1btgAwePBgLBbLOfdbLBYGDx581mOdduzY4VpteKFczj9vampi586dHc4l3mH37t0AZGZ2P+/rQ8TX1Nc3UF5eDkB+WprhNJ7lLADWNjSwZteeSzzaN0xb4lj9FxRsY+iEPobTiLjHoIJ8+uXlAo7WKioY+T6LxeKaBrx48WIaGxvNBhIREfETfl8ALCsrw263A5Cbm3vBxznvO3jwYIfOa7fbKSsru+R5c3Jyznte5//HxcURGxt73mNjY2Nd95WWll7wOX79618zdepU7rzzTh588EF++ctfulYXijnOFYAZ2v4rfuLAgQOu1TXd/LwA2CdvMEG2YADmb9pkNowbNDU3M2PFSgAGjOpBRFSY4UQi7mHBwtWDBpKZ5JhovXnzZtZvWG84lVypgZMHAXDmzBnWrFljNoyIiIif8PsC4MmTJ123nT32zsd5X2VlZYfOW1dX55ru25Hz1tXVUVf3aW8a5/Nc7NiO5tq7dy92ux2r1cqJEydYuXIlzz77LL/61a9oamrq0Ocj7nX69GkOHToEaAKw+A9n/7/w0FDSEuINp/Gs0JBw+uQ7VnDP27DJ9UaSr1q4aTMnT58GYOQ12v4r/sVmtXLLqBHERkYCsHDBQte0cvFNfa7qiy3Y0R5n7ty5htOIiIj4B7+fAuws0oFj6MeFOO9rX6S7mPaP68h5nceEh4efdfzFjr1YrpCQEG688UbGjRtHfn4+ERGOXlylpaW8++67LFy4kOXLlxMZGekaRnIxr732Gm+88cYF7586dSpf+MIXLnmejrJara7/xsf7XyHBue0cID+/r+vvvStd6rUlnefcym2xWIz8nZrU2trq+oW6ID2dkOAQjzyPzeY9P5YG97yKLfvWUHL0KIcqT1GYmWE60mWbttSx/TciKozBY3sRFOw9X2d/YQuyXfpB0ikWLK7/Xuo1Gx0cxOfGXcXr8xfS0NTEhx9+yJe+9KXz9n6WT3nrtUJ4eDh9xvRl6+ItLFy4kD/84Q+mI3WYv1/jmuS8DouNjfX5N+a8jV63IoFBvwH4qPj4eL761a+e8+c5OTk89thjxMTEMGPGDObOncvtt9/u6nF4ITU1NRw9evSC99fW1p4zqMQdLBaLR85rWvsJwNlZPY30AFTfQc8KtK9vWVmZ6w2Vgox0PPXpe9OXdXDP0fxz1u8AmLN+A92zMg0nujyn6+r4ZM06AIZN7EtoqGeKt4HOWawSz+jI1zcpNpZbRo/k3aXLaWho4K233uLhhx92vUkq5/Lmn2WDrxnK1sVb2LlzJ6WlpeTn55uO1Cn+eo3rDZzFKnE/vW5F/JvfFwDDwj7tc9TQ0HDBi8CGhgaADq/qaf8457EXO+9nj3Hevtixl5PL6b777uPjjz+msbGRtWvXXrIAGBkZSUpKygXvj4iIoKWlpVMZLsZqtWKxWLDb7X45sW/btm0AhIZGkJiY2eXvUjq/tuJe7X9RCrSvr3Oojc1qJS81FU98+hYLHjnv5UqKTSM7tRsHj+xnzrr1fP3Wm01HuiwfrVpDXVsT/THXDsSOF32R/YQFi76uHtC+6NfRr29+ehqTBg1kwcZNVFZW8p///If7779fv9Ceh7dfKwy+ZjD/+sk/AJg1axZf+9rXDCfqGH+/xjXJYrFgtVppbW316teuL/Lm162+f4u4j98XANv32Dt58uQFC4DOXoEdXfIcHh5OeHg4dXV1Z/UZvNB5nY//bK6LHXs5uZzCwsLIyclh3759HDly5JKPv//++7n//vsveP/x48c73B+xI+Lj47HZbLS2trr1vN7COfU5I73gkkVed7NarYSFhdHQ0OB1P8B9XXh4uOviqKPtAvyFa6p1UhJWCzQ3u7e/qMViISgoiJaWZq+6qB9YOJKDR/azaucuDh8/TlxbjzFf8p9FiwGIT46hx6BcmpuaDSfyL67XbnOLV712/UFQcJCruNqZ1+2A/FyOnTrF1gPFlJSUMOODD7jh+us9mNT3+MK1QlxGPMk5KRwrPcoHH3zA5z//edOROsTfr3FNstlsxMfHU1VV5daFCeLdr9ukpCTTEUT8ht+vn87KynKt2rnYJF3nfdnZ2R06r8Vica2qu5zzOv//1KlTVFdXn/fYqqoqqqqqgE+nCYtv0ARg8SeVlZWuNyP8ffrvZw3sPhqAltZWlmzZajhN5x2rqmLptu0AjLpmgLZNSUCwYGHSwAFkt/X/27Z1K2vXrTWcSjrLYrEw8OpBACxbtizg3ngTERFxN7//TSA8PJzu3R1TWDds2HDexxw/fpyDBw8CMHDgwA6fe8CAAQBs3Ljxgo/ZtGnTWY916tOnD0FBQRfN5TxvcHAwvXv37nAucAw/cRYfU1NTO3WsXJm6ujpKSkoAyMzUBGDxfUVF+12389MD6/tJQWYvosJjAJi/cbPhNJ334ao1tLatSht9bcd/von4OpvVys0jhxMXFQXA4kWLKdpfZDiVdNaAqx3ft+rq6li+fLnhNCIiIr7N7wuAABMnTgRgyZIlHDt27Jz7p0+fjt1uJyEhgf79+3f4vOPHj8disXDo0CFWrlx5zv0rVqzg0KFDWCwWVwaniIgIhg8fDsCMGTPOWcbe0tLCjBkzABgxYsQ5W5cvtc3ozTffpLGxEYvF4noe6Rr79u1z/f1kZvQwnEbkyhUV7QMgMSbaJ7fAXgmr1caAwpEALNyyhWYf23I0Y4XjZ1NGXjI5hYG1elMkLCSE20aPJDQ4GLvdzswPZ3Ls+LnXgeK9eo3qTUiYY3DRvHnzDKcRERHxbQFRALzuuutIS0ujvr6eZ599lgMHDgCOARvTpk1j1qxZgKMPnnNVntPDDz/MrbfeygsvvHDOefPz8xk/fjwAL774IqtWrcJut2O321m1ahUvvfQS4ChAnm8L73333UdQUBBFRUX89re/dfVbqKys5Le//S1FRUUEBwdz3333nXPsj3/8Y/7zn/9w4MCBs4qHpaWl/P73v+e9994DYMqUKZccACLutXfvXtftjAxtARbf1tDQQFlZGQD5Abb912lQD8c24FNnatiwz3dWEBVXHGFj2+rN0dcO9OppnyKekhAdzU0jh2O1WGhsbOS96e9RW1trOpZ0UEhYCL3H9AFg/vz56rMpIiJyBfx+CAg4ttA++eSTPPHEExQXF/Poo48SERFBfX29q/HxzTffzDXXXNPpc3/961/n8OHD7Nmzh+eee46QEMe7lI1tExd79ep1wallOTk5PProo/z+979n6dKlLFu2jIiICGpqagAICgri0UcfPW8B79ixY7z22mu89tpr2Gw2IiIiaGxsPGvgxIQJE3jkkUc6/TnJlXEOSwgKCiElWb0bxbcdOHDA9X0y0Pr/OfXrNhSb1UZLawvzN25iRE/fWNn7/spVrtujpgy4yCNF/FtuSgoTBw5gwabNVFVV8f7773PPPfec86aveKcBVw9k84JNFBcXU1RURGGh3lwVERG5HAFz5ZOTk8OLL77Iu+++y5o1azh+/DiRkZF069aNm266iVGjRl3WecPDw3n++eeZOXMmixcv5tChQwAUFBQwceJEbrrppoteYE6YMIHs7GymT5/Otm3bqK6udm1FvvPOO8nPzz/vcQ888ACbN29m7969VFZWcvr0aWw2G+np6fTq1YvJkyef03dQuoazAJie1g2bLWD+iYmf2r/fsYIsLCSE9MSESzzaP0WERdEjZwA7izcyb+MmfvT5e0xHuiS73c77yx3bfwv7ZZOc3rlJ8iL+ZmC3fE6ePs2mov2Ul5czZ84cbrzxRtOxpAMGTBoE/BNwbANWAVBEROTyBFR1Ii4ujoceeoiHHnqow8f89a9/veRjgoKCuP3227n99tsvK1e3bt14/PHHO3XM2LFjGTt27GU9n3iWcwuwtv+Kr2ttbXUVAPPTUrEG8BbSQd1HsbN4I3vLD1Fy9Ci5KSmmI13UlgPF7K+oAGDkNR3vbSvizyYM6EflmTOUHDnK9u3bSUxMZOTIkaZjySUkZyeT0T2TQ3vLmTdvHl/96ldNRxIREfFJAdEDUKSrNDY2ugommRmaACy+rbz8EHV1dUDg9v9zGtj901Xi8zZsMhekg95dugwAW5CVYRP7Gk4j4h2sFis3jhhGQnQ04BgO175vr3gv5zTgFStWcObMGcNpREREfJMKgCJudODAAZqbmwEVAMX37dvn+MXYZrWSl5pqOI1ZaYlZZCQ5enrO3bDRcJqLa2xuZsbK1QAMGNWD6NiISxwhEjjCgh2TgcPaejbPmjWL48ePG04llzJw0iAAmpqaWLJkidkwIiIiPkoFQBE32rNnj+t2hgqA4uP27dsHQHZyMqHBAdUx4rwG97gKgNW7dnPKi1egLNi4mcq2fGOuG2g4jYj3iYuK4uaRw7FarTQ1NTFjxgzX8DbxTt2H9SAsKgxw9AEUERGRzlMBUMSNnAVAq9VGWmqe2TAiV+DYsWOcOnUKgIKMdLNhvMTgnmMAaGltZf6mzYbTXNi0ZY7tv1Ex4fQfqTciRM4nOzmZcf0c2+NPnjzJxx9/bDiRXExQSBB9xzn6mc6bNw+73W44kYiIiO9RAVDEjZwTgFNT8ggODjWcRuTyOftiWSwWCtIDu/+fU7fMXsRGOSYhz1nvnduAT1RXs2DTFgBGTO5PULDNcCIR7zW4sBs9sjIBxxt4a9euNZxILmbg1YMAOHz4MDt27DAbRkRExAepACjiRs4VgJoALL7OWQBMT4gnMizMcBrvYLVYGdxjNACLt2yl3gu3DL6/YhXNLS2Atv+KXIoFC1OGDDprKMjBgwcNp5IL6T9hgOu2tgGLiIh0ngqAIm7S0tLi6pmmASDiy6qqqjl69CgA3dK1/bc9Zx/A2oYGlm/3vhUo7y5dDkBmfgq5PfR3J3IpIUHB3DxqBMFBQbS2tvLhhx9ypsZ7e3wGsvi0eHL75QIqAIqIiFwOFQBF3KSkpISGhgZABUDxbc7pvwCFKgCepXf+YMJCwgGYvX6D4TRn23XwINtKSgDH6j+LxWI4kYhvSIyOZsqQQQDU1NTw8Ucfq8eclxrQNg147dq1rj61IiIi0jEqAIq4iXPLJGgLsPg250rWhOho4qOjDKfxLiFBIfQrGA7A/I2baG1tNZzoU9PaVv9ZrBZGXtPfcBoR39IzK4uB3fIBKC4uZs3aNYYTyfkMmORobdDS0sLChQsNpxEREfEtKgCKuIlzAIjFYiEjXQVA8U11dfWuHliFmv57XkN6OrYBH6uqZmPRfsNpHJpbWnhv+QoA+g4vIC4x2nAiEd8zvn8/kmJjAFi2dBmHDx82nEg+q2BwIZFxjjemtA1YRESkc1QAFHETZwEwKSmL0NBww2lELk9RUZFr61uBtv+e18DCkVgtjh+f3rINeMnWbRyrqgZgzLUa/iFyOYJsNm4cMYwgm83VD9DZ2kO8g9Vmpf9ExzCQBQsWeNUqbBEREW+nAqCImzi3AGekq/+f+C5n/7+o8HBS4+PMhvFSkeHR9Mx1FNnmekkB0Ln9NzwylMFjexlOI+K7EqNjmDjQsYW+qqqKOXPmGE4kn+XcBnz8+HE2b95sOI2IiIjvUAFQxA3sdrtrBaAGgIivampqori4GICC9DQNkbgI5zbgosMV7Dt0yGiWUzU1zN3gKEQOn9SX4JAgo3lEfF2/vFx6ZGYCsGvXLrZt32Y4kbTXf8IA188nbQMWERHpOBUARdygvLyc2tpaADIzVQAU31RcXEJTUxOg7b+XMrjHGNftOes3GkwCM1aspKGpGYAx1w0ymkXEH1iwMHnIQGIiIgBYMH8Bp0+fNpxKnKITouk2uABQAVBERKQzVAAUcYM9e/a4bmdqAIj4KOf239DgYLKSkwyn8W5JcankpDr+rc/dYK4AaLfbeXPhYgDSc5Mo6JtlLIuIPwkLDuHaoYMBaGho4JNPPnH1RxXznNuAN27cyLFjxwynERER8Q0qAIq4QfsCYEaGCoDie1pbWykqKgKgW1oaNqt+PFyKcxvwhn1FHD11ykiGLQeK2VHqmNo87sYh2rYt4kbZyckMKnCsNCsuLmbT5k1mA4nLwEmDAMebIAsWLDAbRkRExEfoNzwRN3D2/4uPTyMiIsZwGpHOO3iwjLq6OgC6ZWj7b0cM7unYBmy325m3cZORDM7Vf7YgK6Ov0/RfEXcb26838VFRACxetJjKU5WGEwlATr9cYpNjATSoRUREpINUABRxA+cKwEyt/hMftWePo4gdZLORn5pqOI1vyEktIDHW8bUy0Qewpr6eGStXATB4bG+iYyO6PIOIvwu2BXHdMMfq2qamJj7+6GNtBfYCVquVgZMHAbBgwQIaGxvNBhIREfEBKgCKXCG73e4qAGao/5/4ILvdzt69jv5/+WmpBAfZDCfyDRaLhSFtqwCXb99OTX19lz7/zNVrXM85/uYhXfrcIoEkPSGB4T0cA77Ky8tZt26d4UQCMPgax/e9M2fOsGLFCsNpREREvJ8KgCJX6OjRo5xq6/+VmdnDbBiRy1BWVkZNTQ0A3TMyDKfxLYN7OPoANjQ1s3jL1i59buf236T0OHoNzu/S5xYJNCN79yQ51rHldPny5ZyqOmU2kNBnXD+CQ4MB+OSTTwynERER8X4qAIpcobMmAGd0N5hE5PLs3u14DQfZrOSnpRlO41t65PQnMiwagDldOA1498EyNuxzDG0Zd+MQrFYN/xDxpCCrjWuGDHJtBZ47Z67pSAEvNDyUvuP6ATB79mxtzRYREbkEFQBFrpBzAAhoBaD4Hsf2X0cBMDc1lZDgIMOJfEuQLYgB3UcCMH/jZpqam7vked9c5Fj9Z7VauOr6QV3ynCKBLi0+nkEF3QDHVODtO7YbTiSDpzi2AZeVlbF9u/4+RERELkYFQJEr5CwAxsYkEx0VbziNSOccOnSIM2fOANr+e7mG9HD0AayqqWHtnr0ef776xkamL3f0uxowqgdxSdEef04RcRjTpzcxEY6BOwsXLKS2rtZwosA2cPJg1+3Zs2cbTCIiIuL9VAAUuULOAmBmprb/iu9xbv+1Wa10S9f238vRr2A4QTZHH6rZ6zZ4/Pk+XruOU2ccPRvHafiHSJcKCQri6sEDAairq2PRwkVmAwW4uJQ4ug0uANQHUERE5FJUABS5Qs4egOr/J77GMcHaUcDOSUkhNDjYcCLfFB4aQZ98RyFu7oYNHu9D9a95CwCIT46h3whNHhfpavmpqfTKzgJg+/btHCg+YDhRYHNuA960aROHDx82nEZERMR7qQAocgWOHz/OiRMnAMhQAVB8TEVFBadPnwage6a2/16JIT0d04DLjp9ge0mpx55nW3EJ6/fuA2DCrUOx2fRjXMSECQP6ExYSAsC8ufNo7qL+n3IuZwEQYM6cOQaTiIiIeDf95iByBc4aAKICoPgY5/Zfq9VKgbb/XpHBPUZjwTGJd/Z6z20D/tfc+QDYgqyMu1Hbf0VMiQgNZVy/PgCcOnWKtevWGk4UuDJ7ZJGcnQxoG7CIiMjFqAAocgXaFwCzNAFYfIxr+29ykmsli1ye2KgECrP7AjB73XqPPMepmhreX7kKgGET+hKbEOWR5xGRjumbm0t6gmP41+pVq6murjacKDBZLBYGta0CXLp0qWuwlYiIiJxNBUCRK+AsAEZHJxATk2g4jUjHVVQcoaqqCoDumZmG0/gH5zbgXQfLKD5y1O3nf2fxUuobGwGYdPtwt59fRDrHYrEwceAALBYLTU1NLFy40HSkgOXcBtzQ0MDixYsNpxEREfFOKgCKXAENABFf5SxeWy0WCtLTDafxD0N7jnXdnrPevasAW1tbXcM/sgvTKOib5dbzi8jlSYuPp19eLuC4JiguLjYbKED1GNGT8JgIQNuARURELkQFQJEr4CyiqAAovsa5/TcrOZnwUG3/dYeUhAyyUvIBmL1uo1vPvWTrNkqOOlYVTrp9OBaLxa3nF5HLd1XfPq42CvPnz6elpcVwosATFBzEwEkDAZg7d67+DkRERM5DBUCRy3Ty5EmOHTsGQKb6/4kPOXLkCKdOnQKgMEOr/9zJuQ143d69HGvbYu0Or7YN/4iICmPk5P5uO6+IXLnwkBCu6usYCHLy5EnWrV9nOFFgGjxlKAAnTpxg3Tr9HYiIiHyWCoAil0kTgMVX7dq1C3Bs/+2emWE4jX9xbgO22+3M3eCeVYD7Dh1iwabNAIy9cTChYcFuOa+IuE+/vFxS4uIAWLVyFTU1NWYDBaD+EwdgC7IB2gYsIiJyPioAilwmZ/8/UAFQfIfdbncVAHNSkokIDTWcyL/kpBWSGJsKwJx1G9xyzr99MgcAq9XC5DtHuuWcIuJeVouFSQMdq3MbGxtZtny54USBJyImgl6jewMwa9Ys7Ha74UQiIiLeRQVAkcvkXAEYGRlLbGyy4TQiHXPo0CGqq6sB6JGlQRLuZrFYXNuAl23fwenauis638nTp5m21FFIGDaxL4mpsVecUUQ8IyMxkR5ZjqnqW7dscbUJka4z9HrHhPQDBw6wY8cOw2lERES8iwqAIpep/QRgNeQXX7Fzp2P1n81qVf8/D3EWABubm1m0ZesVnevf8xbQ0NQEwDV3jbribCLivbtBUwAAcetJREFUWWP79sFmtWK321m0aJHpOAFnyLVDXNdks2bNMpxGRETEu6gAKHKZnNsoNQBEfEVra6tr+m9+Wiqhweol5wk9cvoTFR4DwOx16y/7PPWNjfyzbfhH9/45dOud6ZZ8IuI5sZGRDC4sAKC4uJj9+/cbThRY4lLjKRzqaMsyc+ZMw2lERES8iwqAIpfh1KlTHDlyBFD/P/EdBw+WuRrTa/uv59isNgb1GA3Agk2bXSv4OuuDlas53rZde8rdWv0n4itG9OxBeFt/1UWLFtHa2mo4UWAZdqNjG/DOnTspKioynEZERMR7qAAochk0AER80a5dOwEIDrLRLS3NcBr/5pwGfKa+npU7dnb6eLvdzisfzwYgOSOeQWN6ujWfiHhOaHAwo3v3AuDEiRNs3rzZcKLAMuS6Ya7bWgUoIiLyKRUARS6DcwAIaAuw+IaWlhZX4bpbWjrBQTbDifxb325DCQkOA2D2+s5PA563cRO7y8oAuOZzI7Ha9ONaxJf0z88lIToagOXLl9PY2Gg4UeBIzk4mt18eoD6AIiIi7ek3CpHL4CykRITHEB+XajiNyKUVF5dQX18PQE9t//W4kOBQ+hc4tqHNWb+xU1sA7XY7L834EICo2AjG3jjEIxlFxHOsFivj+/cFoK6ujrVr1xpOFFic24A3btxIWdubKSIiIoFOBUCRy/DpABBNABbf4Nz+GxocTG5qiuE0gcE5DfhYVRUbizo+CGD59p2ux0+5axShYRrWIuKL8tJSyUpKAmDt2rXU1NYYThQ4hl4/3HVbqwBFREQcVAAUuQzOFYAZ6v8nPqCpqYl9+/YBUJiRQZC2k3aJQd1HYbM6tlp/0olpwC994Fj9Fx4ZyqTbh1/i0SLirSxYuKpfH8DxfXjVylWGEwWOjMIMMgozABUARUREnPRboEgnnT59mkOHDgEaACK+Yf/+A67+Uz2zMg2nCRyR4dH0yh0IwOx1G7Db7Zc8ZsO+faxoGxpy9R0jiIgK82hGEfGsjIQECjLSAdi8eTOnqk6ZDRRAhrZtA161ahVHjx41nEZERMQ8FQBFOkkTgMXXOLf/RoSGkp2cbDhNYBnctg24+MgR9pQfuuTjX2zr/RcSFsw1d43yaDYR6Rpj+vTGYrHQ0tLCiuUrTMcJGMPatgHb7XY++eQTw2lERETMUwFQpJPaTwDO0gRg8XINDQ3s3+/oJ9c9MwOrVT0ru5KzDyDAnPUX3wa8vaSE+Rs3AzDh5qFEx0Z4NJuIdI2kmBj65GQDsGPHDo4dO2Y4UWDI6ZtLUrbjTa8PP/zQcBoRERHzVAAU6SRnATAsLJKEhHTDaUQubs+ePTQ3NwOa/mtCQkwy+Rk9Afhk3YaLPvZ/p00HICjYxrX3jPZ4NhHpOqN698JmtWK321m6dKnpOAHBYrEw/MYRACxdulSFVxERCXgqAIp0krMAmJmhCcDi/Xbs2AFAbGQEGYmJhtMEpqE9xwKw9UAxh06cOO9j1u/d51r9N/G2YcQnx3RZPhHxvJiICAZ26wZAUVERZWVlhhMFhpG3OloptLS0MHPmTMNpREREzFIBUKSTNAFYfEV19WlKS0sB6JWdjerVZrTfBjx7/flXAf7mnXcBCA0L5sYvjOuSXCLStUb06k5ocDAAS5YsMZwmMOT2yyM1LxWA9957z3AaERERs1QAFOmE06dPc/DgQUD9/8T77dy5w3W7V3a2wSSBLSM5l7REx9d/9nm2AS/btsM1+feau0YREx/ZpflEpGuEh4QypHshAOXl5Rw4cMBwIv9nsVgY0bYKcNWqVRw+fNhwIhEREXNUABTphF27drluZ2f1MphE5NKc23/T4uNJiI4ynCawOVcBrt61m8rTZ1x/brfb+fU70wCIiArjunvHGMknIl1jSGE3wkNCAFi2bJnhNIFh1C2Onqp2u50ZM2YYTiMiImKOCoAinbBz507X7eysngaTiFzckSNHOX78OAC9crT6z7ShvRx9AFtaW5m/abPrz+du2MSmIseU5us/P4aIqDAj+USka4QEBTO0h6OFSEVFBUVFRYYT+b/Mnllk9XQMwXr//ffNhhERETFIBUCRTnCuqIqMjCUuLtVwGpELc75WrRYLPTMzDaeR/IyexEU5hrDMXrcegKbmZn751tsARMdHMvnOkcbyiUjXGdQtn4jQUMCxCtButxtO5P9G3OpYBbh+/XpKSkoMpxERETFDBUCRTnBuAc7O6qUJwOK1WltbXf3/clNTiQgLNZxIrBaraxvw4q3bqGto4N/zF1J0uAKA2x6YSGh4iMmIItJFgoOCGN7T0Uf46NGj7N2713Ai/zfylk/fYNEqQBERCVQqAIp0kN1ud20BzsrU9l/xXiUlpdTU1ADQOzvLcBpxchYA6xsb+WjNOn43/X0AMrulMO6mIQaTiUhXG5CfR2SYY8v/8uXLtQrQw1Lz0sgfkA9oGrCIiAQuFQBFOujIkSOcPHkSUP8/8W7O1X8hQUF0S083nEaceuUNJDzUMeH3pQ9mUtVWpP3816/DZtOPY5FAEmSzMaJtFeDx48fZvXu34UT+z7kNePv27ezZs8dwGhERka6n3zhEOuisCcDZmgAs3qmxsdH1i033zAyCg2yGE4lTkC2YQd1HAVB0+DAAg8b0pPfQbiZjiYgh/fJziQ4PB7QKsCuMuFnbgEVEJLCpACjSQe0nAGdm9DCYROTC9u3bR1NTEwC9sjX919sM7zPRddtqtXD316aYCyMiRgVZbYzo5dhRcPLkSXa0rd4Wz0jMSKTHcMf12/Tp01VwFRGRgKMCoEgHOaeqJiZkEBkZaziNyPlt374dgKjwcLKSkwynkc8KDU3Hag0GIDU7kdSsRMOJRMSkvrk5xEZGALBi+QpaW1sNJ/JvI29zbAMuKipiw4YNhtOIiIh0LRUARTrIuQU4K0vbf8U7nTlzhpKSEgB6Zmdh1aRqr1Lf2MTyHbuIiXZs+T11/DRNjc2GU4mISTar1bUK8NSpU2zbvs1wIv828pZR2IIdrTHefvttw2lERES6lgqAIh3Q0tLiatCdnaXtv+Kdtm3b7trS1Dcnx3Aa+axl27dTU99AXEwhAHU1Dexcv99wKhExrU9ONnGRjgFBq1auoqWlxXAi/xUVH82gaxxT19977z0aGhoMJxIREek6KgCKdEBxcTF1dXWAVgCK99q2bSsAaQnxJMZEG04j7ZUdP8HWA8UAdO89mJBQR+P/dYvV80sk0FktVkb2dqwCrKqqcrVyEM+46nNjAceKy7lz5xpOIyIi0nVUABTpgLMmAGf2NJhE5PzKy8uprKwE4P+3d9/hcZT32se/s7vqvXfJsmRbli13GzfcqYZQEpIATshJIL3n5CRvSAglBNJIAjkpHJLQE8B0sDEE94Z777ZsFTd1ySorbXn/WGtt4yZbWs1q9/5cl6L1zuzsT8rDaPaepxSr959fcThdfLhxEwC2ECvDJxYzsHgsABuX79IwYBGhKCebhOhoAFatWqVegD40bNpwYhI9N8k0DFhERIKJAkCRLuhcAdhisZKZWWhyNSJn27bVM2+UzWplUHa2ydXI6Vbt3EltUxMAg0f1JyIyjOJhEwENAxYRj9N7ATY2NrL1ZI9u6Xm2UBtXfMKzGMh//vMfqqurTa5IRESkdygAFOmCzhWA09PzCQkJM7kakTN1dHSwa7enl2phZgbhoSEmVySdKqtrWL93HwBJaXH0G5QJQMHA4RoGLCJnGJSdTWKMp2ea5gL0rcmfuhIAh8PBa6+9ZnI1IiIivUMBoEgXeFcA1vBf8UO7d++hvb0dgOK8PJOrkU7tHQ4WrN+A2+3GFmJlxKQijJMrM9tCQjUMWETOYDEMrji5InBTUxNbtm4xuaLAlVfSj8wBWQC8/PLLJlcjIiLSOxQAilxEW1sbBw54hujlaAEQ8UOdi3/ERkaSm5JscjXSafGWrTQ0NwMwZGwhUTERZ2zXMGAR+biB2VneXoAfrf4Ih0M3B3zBMAxvL8DNmzd7R3qIiIgEMgWAIhexZ88e7zCc7Gz1ABT/Ul/fQHl5OQCDc3O8PczEXNsPlbH90CEA0nOSyB2QftY+pw8DXrtYHz5FxNMLcPxgz81G9QL0rQm3TMJi9XwUev75502uRkRExPcUAIpcxPbt272Pc3PUA1D8y7Zt27yPi/O0+q8/qG5oZOGmzQBERIUxfFIRBmcHs7aQUAYN8QwD3rRiF+32jl6tU0T808CsTJJjYwH1AvSlhPQEhs8cCXiGAbe2tppckYiIiG8pABS5iM6AJSIihpRkBSziP9xuN9u3e9pnTkoy8VFRJlck7R0O3l2zBofTicViMHpqMWFh51+UZegIzxC01mY7W1bt6a0yRcSPGYbhXRH4xIkTbN682eSKAte0O6YD0NDQwNtvv21yNSIiIr6lAFDkIjoDwNycwVgs+k9G/MehQ2U0NjYCUJyrxT/M5nbDfzZuorbpBACDR/cnMSXugq/pP2A4kVGenj6rP9jq8xpFpG8YkJlJSpzn/PHRR+oF6CslU4eRmJkEwLPPPmtyNSIiIr6lNEPkAtxutzcAzMstNrkakTN1Lv4RarMxICvT5GpkzZ7d7K6oACAjL5n+xdkXfY3FamXIiMkAbF2zlxMNLT6tUUT6htN7ATY3N7Np8yZzCwpQFquFqZ+dBniC1j171BNbREQClwJAkQsoLy/39rDKyx1icjUip7S1tbF3717As2pkiM1qckXBbXdFJSu37wQgJj6SERPPPe/fuZSMnAKA0+Fi3RItBiIiHoUZGd5egGs+WkNHh+YJ9YUrPzMFw+I5Xz/33HMmVyMiIuI7CgBFLuD0BRZy1QNQ/Mj27du9Q8KG5Gn4r5mO1Nbx/voNAISGhzBuRgkhobYuvz4zp5DE5AwAVn+gFT9FxMMwDMarF6DPJWYkMWz6CABeeukl2trazC1IRETERxQAilxAZwBotdrIyhxgcjUip2zZ4gmKkuNiyUhMNLma4NXQ3MLbq1d7Fv2wWhg7fShRMRGXdAzDMLy9APdtK6fqSJ0vShWRPqggM4PU+HhAvQB9qXMxkLq6Ot59912TqxEREfENBYAiF9AZAGZmFBIaGm5yNSIeFRWVVFdXA1DSrx9G10aaSg870drGq8tX0NxmB2DExEEkpV540Y/zGTpqivfxRx9qMRAR8TA41QuwpaWFjRs3mlxRYBo2fTiJGZ6baU899ZTJ1YiIiPiGAkCRC9ACIOKPtmzZDIDNaqUoJ8fkaoJTq72dV5evoKG5GYDBI/PJ7p922cdLTEonK3cg4FkN2O1290idItL39c9IJy0hAYC1a9fS3t5uckWBx2qzMv1zMwFYt24dGzZsMLkiERGRnqcAUOQ86uvrKS8vByBXC4CIn2hra2P37t0ADMrOIjw0xOSKgo+9o4PXV66ktqkJgMKhuRQOy+32cUtO9gI8WlZN6a7D3T6eiAQG9QLsHdPumEFImOdv6pNPPmlyNSIiIj1PAaDIeWzfvt37WD0AxV+cvvhHSX4/c4sJQm3t7by2YiXH6uoB6Dcok8Gj87u84u+FDBk+GavVs3jI8nnqfSIip+Snp5GeqF6AvhSTGMOEWyYC8Oabb3L06FGTKxIREelZCgBFzkMrAIs/On3xj/QELf7Rm1ra7MxdtoKjtZ5FOnIK0ii5YkCPhH8AkVExDBp6BQBrFm7D3qoP+CLi4ekFWARAa2urhqj6yFVfvBYAh8PBP//5T5OrERER6VkKAEXOozMATErMJCY6weRqRKCyUot/mOVEaxuvLFtOVUMDALkDMhgxqQijh/9PGDnWMwdVW0s765bs6NFji0jf1i8t1bvq+9q1a7Hb7SZXFHhyinIYPNFz0/fZZ5+lra3N5IpERER6jgJAkfPoDADV+0/8xebNWvzDDDWNTby0ZKl3zr/8wVkMnzCwx8M/gPzCEuISUgBYPl/zfInIKQYGE4o9vQDb2trUC9BHrvriNQBUV1fz2muvmVyNiIhIz1EAKHIO7e3t3oUW8rQAiPgBLf5hjrLjVby0ZCmNLS2AZ8GPoeMKfRL+ARgWC8PHzABg75YyjpbX+OR9RKRvyk1NITPJ0wtw3bp16gXoAyNmjiQlx3Mj5m9/+5tWZRcRkYChAFDkHPbs2UNHRwegBUDEP2zfvsO7+MfQfv3MLSZI7DhUzhsrV2Hv6MAwYOjYQopH9++xOf/OZ8SY6XSO79ZiICJyutPnAmxra2P9+vUmVxR4LFYLV3/JMxfgjh07+OCDD0yuSEREpGcoABQ5h9MXAFEAKP5gyxbP8N/k2FjvHFDiG263m5U7d7Fg/XqcLhdWm4Ux04bSvzi7V94/LiGFgoEjAFg+byMd7Y5eeV8R6RtyU1PISkoC1AvQV6Z8dirRCdEAPP744yZXIyIi0jNsZhcgfYPVau2Tx75cW7duBSAiPJrU1Dwslr6TlXcOTTQMo0/V3df05u+2rKzs1OIf+flYLIG4+ofh/W7m4iat9nbmr13HwWPHAAiLCOWKmSXEJ8f0ah1jJl7D/t0bOdHYytpF25l07YgeO7avhi8HrVNN1+e9Q4OZ2u0pBgYThgxm7tLl2O121q1fx5WTr7y0Y+ha4YIioiO5+kvX8tpv5/LRRx+xdu1axo8ff8nH8cdr3L6s8/ep36tv6fcrErgUAEqXJCT4ZhVcq9Xqs2N3x/bt2wEoKBhOZGSkydVcnrCwMLNLCFiGYRAeHt5r79e5+EeozcawgnxstsA9ddts5l10VlbX8NbKVTS1tgIQmxjN+JnDiIzpvf+vOw0sHkN8Yir1tcdZ9OZapt4wpkeOa2AEdPsxk82q36uvqN2eLT8jnZyUFMqrqli/bj2TJ00mIiLiko+ja4Xzu+Grn2DeX96hrbmNP/3pT1x33XWX9Hp/vcYNBLGxsWaXELDUbkUCm66mpEvq6up69HixsbFYrVacTieNjY09euzucjgc3pX18nKH0tbWZnJFl8YwDMLCwrDb7Zq4uoeFhYVhGAZut7vXhlw1Njaya9cuAIrzcrEahncuwMBiYLNZcTicQO+2W7cb1u/dx/Lt23G5XADkDchg6BUDsNos3ud6l8Ho8dfw4bznKN1ZyZ6tB+k/+PKHIFttVgwM3LhxOpw9WKdgeMI/h9PR20034KndXtj44iLKl1Rht9tZtnwZU66c0uXX6lrh4mzhNqbPmcn8v73LvHnzWLp0KSUlJRd9nT9f4/Z1VquV2NhYGhsbcTp1TuhJ/txuFUiK9BwFgNIlvvwj629/wHfu3EnryR5A+f1KTPrwf/k6h/K43e4+V3tf0lu/240bN3nfa1h+fsB+UDs1us/dqz9jW3sH72/YwP7DRwCw2iyUXDGQ3ML0znJMM2LsDBa//2+cjg4Wvr6W/KKsHjluoLYhs3iH/br1u/Ul/W7Plp2UdEYvwNGjRxMR3rVegLpW6Jqrv3QtHzz9Pg57B4888gjPPffcJb3e365xA4XT6dTv1of0uxUJXJr0Q+RjNm3a5H2cnz/MvEIk6DmdTu/iH7mpKSTF9u48dIHuaF09Ly5a7A3/ouMiuXL26FPhn8kio2IZMnwSAGsXbaOh9oTJFYmIvxk/eBAA7e3trFmzxuRqAk9CegLT75wBwHvvvcfGjRtNrkhEROTyKQAU+ZjOADAyMpbUlDxzi5Ggtnv3blpaWgAY3r+/ydUEDrcbNu8v5eUlS2lobgYgu38aU24YTWx8lMnVnWncpNkAODqcLHpDH+5F5EzZycnkpqYCsGH9Bk6c0I2Cnjb76zcSGh4KwK9+9SuTqxEREbl8CgBFPqZzwYX++cO06qCYqrOnQWxkJP3T/aNXWl/X3uFg/tq1LNy8GafLhcVqYfj4gYy8ssjUBUjOJyO7P/0KhgKw8I21tLW2m1yRiPibSUMGA545jFesWGFyNYEnPjWeGXfNAuDDDz9k7dq1JlckIiJyeRQAipymvb3duwJwfj8N/xXzHD16lMOHDwNQkt8Pi0VhdHdVNTTy4qLF7K6oBCAqJoLJ140kb1DmqXnc/NCEaTcD0NLUxvJ5Gn4mImdKT0hgULZnjtCtW7dSU1tjckWB5/qv3kBYpGfF5IcfflhzUoqISJ+kAFDkNLt27fKu7qoAUMzU2fvPZrUwtJ+GonfX9oNl/HvxEupODo/LyEtmyg2jiU/y/3kVCwaOIDU9F4D/zF2N06kJ+0XkTBOHFGOxWHC73SxbuszscgJObFIsV3/pWgBWrFjB+++/b3JFIiIil04BoMhpOof/gmcIsIgZWlpa2LVrFwADs7KJDAszuaK+q8Ph5P31G3h/wwYcTicWi8HQsYWMmTaEkFCb2eV1iWEYjJ96EwDVR+tZt3i7yRWJiL+Jj4piWH4/APbu3UtlZaW5BQWg6786m9jkWADuv/9+Ojo6TK5IRETk0igAFDlN5wIgMTGJJCVlmVuMBK2NGzfhcDgAGF6gxT8uV21TE/9evITth8oAiIgKY+K1I+lfnO3XQ37PZejwScTGJQHw7nPLcKkXoIh8zBVFgwi1eW5sLFmyxORqAk9ETCQ3f++TAOzbt4/nn3/e5IpEREQujQJAkdN0BoD5/bQAiJjD4XCwaZNn+G92cjLpCfHmFtRH7S6v4MVFS6hubAQgLTuJqTeOITEl1uTKLo/VFsLE6bcAcPhQFeuW7DC5IhHxN5FhYYwaUAhAZWUl+/bvM7miwDP19mlkFmYC8Otf/5rGk39jRERE+gIFgCIntbW1sXPnTkDz/4l5duzYSUtLCwCjCgtMrqbvcbpcLNq8hXlr19HhcGAYBoNH5TNuxlBCw0LMLq9bRo6b5e0F+NYzS9QLUETOMnpAgXfaiGVLl+Fy6TzRk6w2K5++93YAqqurefTRR02uSEREpOsUAIqctHnzZu98LoUFI8wtRoLW+vXrAIiPjiY/I93kavqWppZW5i5bzqb9BwAIjwhlwtXDGVCSFxA9em22ECbP8Aw/O1pWzdpFmgtQRM4Uagth/OAiwBNQbdu2zeSKAs/wGSMYNmM4AH//+9/PmD9aRETEnykAFDlp3bp13seFBaNMrESCVWnpQaqrqwEYWdAfSwCEVr2l7HgVLy5azOGaWgCS0uKYcuNoktPjzS2sh40YO4O4+GQA3np2iVYEFpGzDO2XR3x0NADLly+nvb3d5IoCi2EYzHngLkLCQnC5XPzP//yPelqKiEifoABQ5KTOADA9LZ+YmESTq5FgtG7dWgDCQ0MZkpdncjV9g9vtZs3uPby2YiUtdjsABUNymHD1cMIjAm/1ZKsthMkzPwXAsfIalr6z3uSKRMTfWC0WrhxaDEBzczOrVq8yuaLAk5qXyo3f8qzOvmHDBp599lmTKxIREbk4BYAieEKEzgCwsGCkydVIMKqurubgwYMAlOT3I8RmNbegPqDD4eTdNWtZsX0HbrcbW4iVMdOGMGRMARZL4P55GzFmBsmp2QC89fRiWpvtJlckIv6mIDOD3NQUANavW099fb25BQWg674ym/T+nqk6HnjgAcrLy02uSERE5MIC9xOSyCWorKzk6NGjABQWjja5GglGnQG0xWJhRP/+Jlfj/xpbWnl56VL2Vh4GICY+iimzR5OZl2JyZb5nsVqZNfvzADTVtzDvxWUmVyQi/sbAYOqwoRiGgdPpZPHixWaXFHBCwkL4r1/djWEYnDhxgu985zsaCiwiIn5NAaAIsHbtWu/jAZr/T3pZc3MzO3bsAGBQdhbREeEmV+TfKmtq+deixRyvbwAgPTeZK2ePIjou0uTKek9h0SjyC0sA+OCV1VQfrTe3IBHxO8mxcZTk9wNg7969HCo7ZG5BAWjQFUVc9cVrAFi2bBn//Oc/Ta5IRETk/BQAigDr13vm0QoLiyQ7e5DJ1UiwWbduPU6nE4BRhYUmV+Pfth8s49Vly73z/Q0clsfYaUOwBdmQacMwmHXDF8AwcHQ4eenPC8wuSUT80MTiIsJCQgBYtHCReqj5wKd+9GnSCzIAePDBB9m5c6fJFYmIiJybAkARTg2/LOg/AqvVZnI1EkzsdjubNm0EoF9aKqnxcSZX5J/cbjfLtm3n/Q0bcLpcWK0WRk0ZTNHIfIwgXS05PbMfo8bNAmDjsl1sWrnb5IpExN9EhIYxfnARAFVVVWzevNnkigJPaHgo9zz2FSxWCy0tLdx+++20tLSYXZaIiMhZFABK0Gtra2PLli0AFGgBEOllGzZspL29HYCxAweaXI1/cjhdvLduPev27AUgPDKMideOIDs/zeTKzDfjujuJjIoF4MXH52NvbTe5IhHxN8P755MYEwPA8uXLaW5pNrmiwFMwspBb/9uzQvu2bdv45je/aXJFIiIiZ1MAKEFvy5YtdHR0AJr/T3pXR0cHGzZ4hp9nJiWSlZxsckX+p629gzdWrmJXeQUAsQnRXDl7FAnJsSZX5h8iImO46sYvAFB7rIG3nllsaj0i4n+sFgvThw8DPDc9lyxeYnJFgen6r93AsBnDAfjnP/+p+QBFRMTvKACUoNc5/BegUAGg9KItW7Z6hwmNHTiQIB3Jel5NLa28snQZ5VVVAKRkJDDp2hFERIaZXJl/KRk5xbsgyPuvrGb/jgqTKxIRf5ObmkJRTjYA27dv14IgPmCxWPjy779KUpbnZt7Xv/51Vq5caXJVIiIipygAlKC3atUqANLT+xMbm2RyNRIsnE4na9euASA5Lpb89HSTK/IvVQ2N/HvJUqobGwHIKUjjilklhIRqjs6PMwyD62/9CiEhYbhdbv7+y9c1FFhEzjKlZKh3QZAP3v/Au/iU9JzohBh+8PQPCY0IpaOjgy984Qvs37/f7LJEREQABYAS5FwuF6tXrwZg8KArTK5GgsmOHTtpamoC1Pvv4yqqqnll6TJOtLYCnpV+R0wuwmLRn6zzSUzOYNYNnwfgeGUtc//2gckViYi/iQoPZ9KQYgBqampYsXKFyRUFpoIRhXzzz98BoK6ujjvuuIOqkz3ZRUREzKRPUxLUdu7cSX19PQCDFABKL3G73axZ8xEAcVFRDMzKMrki/3HgyFFeX7kKe0cHhmEwfMJAz0q/KCG9mNHjr6FgkGcho0VvrmPL6r0mVyQi/qYkvx/pCQkALFu6jJraGpMrCkzjb5zA7T+9E4ADBw5w2223UVdXZ3JVIiIS7BQASlA7fW6WwYPGm1iJBJPdu/dQW1sLwJiBA7BYFG4B7DhUxlurP8LhdGKxWhgzbQh5AzPNLqvPMAyDGz/1dSIiowH4+yOvU3OsweSqRMSfWAyDmSOHYzEMHA4H8+fNx+12m11WQLrp27cw6wtXA555F2+77TYaT05rISIiYgYFgBLUOuf/S0nJISlJQYP4ntvtZuXJYVfREREU5+aYXJF/2HyglHc/WoPL5cJms3LFzBIycrUq8qWKiUvkE5/+JgDNja389f5XcHRoni8ROSU1Pp6xgwYCUFlZyfqTq9FLzzIMgzvun8OUz04DYPPmzdx8880cO3bM3MJERCRoKQCUoOV2u73z/xUN1PBf6R27du2mpsYz5GrcwIHYrFaTKzLfmt17+HDjJtxuNyFhNiZcPZyUjASzy+qzBhaPZeK0mwEo3VXJS39eYG5BIuJ3rhg8iOS4OACWL1tOXb2Gp/qCxWLhC498kUmfnAzA1q1bueGGGzhw4IDJlYmISDBSAChBa9++fd5JmYuKNPxXfM/lcnl7/8VERjCkX57JFZnL7Ybl23ewYvsOAMIjw5h07UgSUmJNrqzvm37NHeTmeyb7X/TGWha9sdbkikTEn9gsVq4bNwbDMOjo6GDBews0FNhHLFYLX/rdl7nqi9cAcPDgQa6//nqWLVtmcmUiIhJsFABK0Dpz/j/1ABTf27lzl3fuv3GDBmGzBu8p2O2GpVu3sXb3HgAiY8K58vpRxCZEmVxZYLBYrXxyzveJjUsC4Lnfv8P2tftMrkpE/ElGYiKjBxQCUF5erqHAPmSxWLjj53O47cefATyrMH/qU5/iT3/6k4JXERHpNcH76VOCXmcAmJCQTkpKrsnVSKBzuVysWuVpc3FRkQzJC94253bD4i1b2LDPE0hFx0Uy+dqRRMVGmFxZYImOSeAz//UTQkLDcTld/Oln/6ay9LjZZYmIH5lQPJjEmBgAli5ZyvHjOkf4imEYzP76jXzjL98mPCocl8vFAw88wKc//WkqKirMLk9ERIKAAkAJSp6FGDxhzOBB4zEMrcIqvrVjxw7q6jxzLI0bNAirJThPv263m0WbN7Npv2f+o5j4KCZeM4LwqDCTKwtM6Zn9uPWO74Jh0HKijd9872mqjmiuLxHxCLFauW7caKwWC06nk3feeYeOjg6zywpoY2eP4763HiCj0LP43OLFi7nyyit5+umncTq1aJOIiPhOcH4ClaC3d+9ejh49CsBgzf8nPuZwOFixwjP3X1xUFIODdOVft9vNh5s2s/lAKQCxCVFMvGY44RGhJlcW2AYWj+W6m+8GoL66icf++znqa5pMrkpE/EVqXDyThnjmDK2pqWHxksXmFhQEMgdkcf87DzLrC1cDcOLECX74wx8yY8YMFi9ebG5xIiISsBQASlBatGiR93HJ0CkmViLBYOPGTTQ2NgIwsXhwUPb+c7vd/GfjJraWHgQgLjGaCdeMICxc4V9vGDf5eqZfdwcAVYfr+P0Pn+dEY6vJVYmIvxhVWEBeaioAmzZuYt9+zRnqa2GR4cx58PP8+OV7SctPBzyjBW677TZmz57NggULcLlcJlcpIiKBJPg+hYqA9+5qRnoBycnZ5hYjAa2tzc7q1asASI2PZ1B2lskV9T6X280HGzay7eAhAOKSoplw9XDCwkJMriy4XDnzU0yYehMAlaXHeey/n+NEQ4vJVYmIPzAMg6vHjCQi1HNTZv68+dQ31JtbVJAoGj+Yhz94lDt+PoeoOM9CWGvWrGHOnDlMmDCBP/zhDxw5csTkKkVEJBAoAJSgY7fbvfP/lQy90uRqJNB99NFHtLW1ATB5SHHQzTfpcrt5f/0Gth8qAyA+KYYJVw8nVOFfrzMMg6tuvIuR42YBULb3CL/53jM01J4wuTIR8QfR4RFcM3Y0hmHQ1tbGm2+8icPhMLusoGALtXH1l67l18se45YffJKYRM/CLAcOHODhhx9m+PDhXHvttfzud79j8+bN6hkoIiKXRQGgBJ21a9fS0uLp9aLhv+JLTU1NbNiwHoDc1FTy0lJNrqh3uVxuFqxbz86ycgASkmM94V+owj+zGIbB7Fu/wujxnnmnKkuP8+vvPk1tVaPJlYmIP8hPS+OKokEAHD9+nA8++MDkioJLVHwUN33nFn676g98/uH/ov+IAsAzjcb69et59NFHmTVrFoWFhdx66608+OCDvP7662zevJmmJs3tKiIiF2YzuwCR3tY5/5/VGsLgogkmVyOBbMXyFd7eE5NPTrAeLJwuF++tW8+eikoAElJiGT9rGCGh+rNjNsNi4bpbvowtJJSPlr3DsfIafvWtf/CdX91JZl6K2eWJiMnGFw3iaG0dB48dY9u2bWRmZTJ82HCzywoqYRFhzPjcTGZ8biaVuytYO28NmxduonTzAcBzg3HZsmUsW7bsjNclJSWRlpZGamoqKSkppKSkEBsbS3R0NNHR0cTExJzxFRsbS3x8PBEREWb8mCIi0sv0SUyCTuf8fwMKRxMeHmVuMRKwjh07xrbt2wAoyskmLSHe3IJ6kdPlYv7adeytPAxAYmocV8wqISREf3L8hWEYXHXDFwgJCWP5wlepOdbAo9/6B9986LMMHJ5ndnkiYiLDMLh27GheXLiYxpYWPvzPhyQmJJKTE5wr2Jsta1A2WYOyufl7t9JQ1cD25ds4sHE/pVsOcGj7IRz2Du++NTU11NTUsGPHjkt6j7CwMOLi4khISCAuLo7ExEQyMjLIzs4mOzubrKwsBgwYQGJiYk//eCIi0ov0aUyCSnV1NVu2bAE0/Fd868MPP8TtdmOzWplYHDy9/5wuF/PWrGPfYU/4l5QWxxUzS7Ap/PM7hmEw/do7iIyO5f23n6alqY3HfvgcX/zxzYybMdTs8kTERBGhodwwfhyvLF1Gh8PJG2+8wZ1z7iQxQQGQmeJS4ph4yyQm3jIJAEeHg+ryKo6WHuVY6TGqK6porG6gsbqRhuP1NNY00nqiFWeH84LHtdvtHD9+nOPHj19wv7S0NAYPHkxxcTEjRoxg/PjxZGRk9NjPJyIivqVPZBJUlixZ4n2sBUDEV3bu3EVlpWfo6+iBA4iLijS5ot7hcLp4d80aDhw5CkBSerwn/LNZTa5MLuSKyTcQG5fMG//6I46Odp586FVqjtVz7WcnBd2iNSJySlp8PNeOGc07H62lra2NV+e+ypw5czRc1I/YQmyk988gvf+FQ7gOewetJ1ppa2ql9cTJr8YWWhpbaG5o9nzVe763NDTTVNtE7eEaGqoacLvd3uMcO3aMY8eOeUfTAOTm5jJhwgSuvvpqpk+fTkxMjK9+XBER6SYFgBJUFixYAEBMTCL98tTDRXpeR0cHS5YsBiAmMoKxAwaYW1AvcThdvPPRGkqPesK/5IwExs0YqvCvjxhcMp6Y2AT+/c9HaG1p4tUnP+RwaRWf+8ENWrFZJIgVZmYyeegQlm3dRn19PW+88Qa33XYbNps+QvQlIWEhhISFEJsUe0mvc7Q7qDtaS1XZcSr3VFKxu4KK3eVU7q6grbkNgLKyMsrKynjppZew2WxMnDiRm2++mRtvvJH4+Hgf/DQiInK5DPfpt3VEzqO6urpHj5eQkIDVasXpdFJXV9ejxz6f9vZ2ioqKaGpq4srJt/GVu3/XK+/b2ywWC+Hh4bS1teFyucwuJ6BERERgGAZut5vW1tZz7rN8+XJWrVoFwPXjxjIoO6s3SzSFw+nk7dVrOHjsGAApmQmMnX6J4Z/habsulwv0V6nHWawW72OX8/znhZqqw/z7n7+ktvoIAP2KMvnGg58hIeXSPjQGE8MwsNlsOBwOdEnVs2whNgwM3LhxdDjMLiegXEq7dePmPxs3s630IACFhYXcdNNNWCyWC74uWHXlWqGvczldlO8qZ8+a3ez+aBc7lm+jpbHljH1CQ0O56qqruOOOO5g5cyZWa/dvCFqtVhISEqirq8PpvPCwZrk0Znw266rk5GSzSxAJGPrLLUFj5cqVNDU1ATB65NUmVyOBqL6+gbVr1wKQnZzMwKzgCP/eWvWRN/xLzUpUz78+LCklky9+81EKBo4A4OCuw/ziq//H/u3l5hYmIqYxMJgxfBj56WkA7Nu3j/nz5yvwDmIWq4W8IXlc9V9X882/fpsnNv2F//fKT7n+qzeQkpsKeG68v/vuu9x5552MGzeOJ554gtraWpMrFxEJbgoAJWjMnz8fgJCQMIZq/j/xgQ8+eB+Hw4FhGEwdVkKgT5/W4XDyxsrVHDo5aXhadhJjpw/tkbv8Yp6IyGg++8WfMGHqTQA01J7gN997hmXvbjC5MhExi9ViYfYVY8lKTgJgx44d/Oc//zG5KvEXVpuVQVcU8emffJZfL/sdP33958y86yqi4qMBzzDhBx98kJEjR3Lfffdx9OR0ISIi0rsUAEpQcLvd3vn/hg65kvCw4FiUQXrPjh07OHjwIAAjCwtIjY8ztyAfa3c4eHPVKsqrqgBIz0lizLQhWK36sxIILBYrs2Z/nps/+x1stlAcHU6e+e3bvPj4PBwODbsSCUYhVhs3TRhPWkI8AJs2beLDhR+aW5T4HcMwKBw9gM89dBe/X/M4X/rdl+lXkg9AS0sLf/nLXxgzZgw/+tGPqKioMLlaEZHgok9qEhS2bNlyalVWDf+VHtba2sqiRYsAiI2MZMLgIpMr8q32DgdvrFxFeZVnbtCM3GSFfwGqZNQUvvD1XxAb5+n1s/D1tTz238/RVN9scmUiYoawkBBumTSBpFjPSq8b1m9gwfvvaziwnFNoeChX3jaFn7/zIPe+dh/DZ4wAwG63849//INx48bxs5/9zO/mnBMRCVT6tCZB4b333gM8dyVHjphpcjUSaBYvXkxLi2fy6xkjhhMawKsj2jscvL5yJZXVNQBk5qUwemqxJoMPYBnZBXzp278mp58n2N6z+RAPffX/KNt7xOTKRMQMEaFhfPLKSSTHeRYH2rJ5M/Pnz9fCY3JehmEwYMxAvvf0f/PAvF8w5rqxAHR0dPDXv/6VsWPH8uc//xm73W5ypSIigU2f2CQodM7/V1gwiri4FJOrkUBy6NAhtm3bBsCg7CzvJOmByN7RwesrVnC4xjOJd1Z+KqOmDFb4FwSiY+L53JfvZ9QVnh7UtccaePRb/+CjD7eaXJmImCEqLJzbrpxMWkICANu3b+ett96io6PD5MrE3+UN7cc3//YdHnr/EYZNHw5AQ0MDP//5z5k4caL3pr2IiPQ8fWqTgLdnzx62b98OwJjR15pcjQQSu93uvVANCwlh6rASkyvynbb2Dl5bvpIjtZ5hOtn90xh5pcK/YGK1hTD7k1/h+lu/gsVqo93u4P9+8Rqv/PUDXE71/BEJNuGhoXxy8kQykzxTBOzdu5eXXnqJ5hZNESAXl1OUw/ef+SH/8+KPyR2SB3gWC/nc5z7H5z//ec0PKCLiA/rkJgHvtddeAzzDD8Zf8QmTq5FA8uGHH9LY2AjAtGHDiAoPN7ki32hrb+fV5Ss4enKOnpyCNEZOLsIS6MscyzmNHn81n/vy/URFxwOw4KWV/PHHL9Lc1GpuYSLS68JCQrh10gQKMjIAOHLkCC88/wI1tTUmVyZ9RfHkodz/7kPc/bsvE5vsGVY+f/58Jk2axBNPPKFepSIiPUgBoAQ0t9vNq6++CsCggVeQlJhhckUSKE7vWTogK5PBuTkmV+QbzW1tvLJ0Ocfr6wHIKUxnxKQiDIV/QS03fzB3f/vXZOYUArB93X5+8dX/o7L0uMmViUhvC7HZuGH8OEYUFACe4ZwvPP8C+/fvN7ky6SssFguTb5vCIwt/w4zPzcQwDFpaWnjwwQeZMWMG69evN7tEEZGAoABQAtqGDRs4ePAgABMn3GRuMRIwmpqaeP/99wGICg9j5ogRBGIe1tjSyitLl1N9spdj3sAMRkwcpPBPAIiNT+Kurz7EsNHTAKg6XMcvv/F3Ni7fZW5hItLrLIbB9OElTB1WgmEY2O12XnvtNZYtX6YVgqXLouKj+PzD/8XP3ryfvKGeYcG7du3i+uuv58EHH6Strc3kCkVE+jYFgBLQOnv/Wa0hjBsz2+RqJBC43W7efvttWls9wx1njRxJRFioyVX1vLoTJ3h56VLqTpwAoKA4m2ETBir8kzPYQkL5xKe/ydWf+C8MiwV7azv/+7OXeOuZxfrQLxKERhUWcPPE8YSHev4url61mrlz59LS0mJyZdKX9B9RwH1vPcjt980hNDwUl8vFE088wbRp0/joo4/MLk9EpM9SACgBy+Fw8MYbbwAwfNg0ok/OVyXSHStWrGDfvn0AlOT3o39GuskV9bzqhkZeWbqMphZPyDloeD+KxxZgoPBPzmYYBldMvoE7v/QzIiKjAXjr6SX8/ZE36Gh3mFydiPS2fmlp3DFjKqnx8QAcPHiQp59+mv0HNCRYus5qs3LN3dfy0Pu/ZOC4QYBn+pWJEydy//33qzegiMhlUAAoAWvZsmVUVVUBMHG8hv9K9x08eJCFCxcCkBwby9SSwFv192htHa8sW05zmx2AIWMKGDSin8I/uaj8AcP40rd/TUqaZz7M1R9s4fc/fJ4TjVocRCTYxEVG8ZmpVzI0vx8Azc3NvPbqa3zwnw+0qINckrR+6fz45Xu58/7PeXsDPv7448ycOZMtW7aYXZ6ISJ+iAFAC1gsvvABAeHg0I0dcZXI10tc1Nzfz2muv4Xa7CbXZmH3FOEJsVrPL6lEVVdW8unwFbe3tGAYMnzCQgiGBubiJ+EZCYhpf+PrD5Bd6wvE9Ww7x6Df/TtXhOpMrE5HeZrNauWrkCG4cP46Ik0OCN23cxNNPP+2dn1mkKywWC1d98Roe/uBRBo8vBjy9Aa+99loef/xxnE6nyRWKiPQNCgAlIFVXVzNv3jwAJk24mbCwCJMrkr7M5XLxzjvvcOLkfHjXjB1DYky0yVX1rP2Hj/D6ylW0OxwYhsHIyYPJG5hpdlnSB4VHRHH7F+9l+JgZABwtr+GX33iK/TsqTK5MRMxQmJnJnFkz6JeWCkB9fT2vvPIK7777ruYGlEuSlp/Oz996kDt+PgdbWAgdHR089NBD3HrrrVRU6G+MiMjFKACUgPTSSy95h5hMm3q7ydVIX/fhhx9SVlYGwMgBhRTlBFavuK2lB3n7ozU4nE4sVgtjpg0hu3+a2WVJH2a1hXDjbV9n2jWe829TfQu//d4zrFuyw+TKRMQM0eHh3DxpAleNHuldIGTHjh384x//YMuWLVo0SLrMYrFw7T3X8/O3HyS7yHM9tnLlSqZOncprr71mcnUiIv5NAaAEHLfbzXPPPQdAfr8S8vsF3jxt0nvWr9/Apk2bAMhKTmL68OHmFtSD3G5YvWs3/9m4CbfbTUiojfGzhpGRm2x2aRIADMPgypmf4pbbv4vVaqOj3cHfHniF919ZpQ/7IkHIwGBoXh53XTWTopxsAFpbW1mwYAHPPvus90abSFfkFOVw31sPcM3d1wLQ2NjIV77yFb72ta/R0NBgcnUiIv5JAaAEnMWLF7N/v2elOfX+k+44cKCURYs8i37ERUVy86SJ2KyBcdp0ud0s2ryZVTt2AhAeEcrEa0aQnB5vbmEScIaOvJI5X/454RHRuN3w8p/f599/eg+X02V2aSJigsiwMK4bO4ZbJk0gPioKgOPHj/PSSy/x+uuvU1tXa3KF0leEhody+31z+OELPyY+LQGAuXPnMm3aNFasWGFydSIi/icwPsmKnObJJ58EIDIylkkTbzW5GumrqqqqePvtt3C73YSFhPCJCROIDAs3u6we4XA6mbdmLZsPlAIQHRvBpOtHEpcYWPMaiv/IzS/mv77xMPGJnjnAPnxtDX954BXsbVoNVCRY9UtL4/NXzWRKyVDCQkIA2LdvH//4+z+YP38+9fX15hYofcaQK4fyiw8eYcz14wCoqKjglltu4aGHHqK9vd3k6kRE/IcCQAko+/bt4z//+Q8A06feTnhYpMkVSV9UV1fHK6+8Qnt7O4ZhcP24sSTHxphdVo9otbfz+opV7K08DEB8cgyTrhtJVLQWyhHfSk7N5r++8QgZ2QUAbFy2i9/94Fma6ptNrkxEzGK1WBg9oJD/umYWIwr6YzEM3G4327Zt4+9//zvvvfeehnNKl0THR/ONv3yLu3/3ZcKjwnG73Tz++ONce+217N692+zyRET8ggJACSidvf8sFitXzfqCucVIn9TY2MTLL79Mc7MnlJg5Yrh35cK+rq7pBP9espSK6moAUrMSmXjNCMLCQ02uTIJFdEw8n//qgwwYPBqAAzsq+OU3/s6xihqTKxMRM0WEhjF9+DDuumomxbm5GIaBy+Vi69atPPXUU7y3YAG1tRoaLBdmGAaTb5vCg+/9ksLRAwDYunUrs2bN4sknn8Tl0tQTIhLcDLdm4pYuqD4ZGPSUhIQErFYrTqeTurq6HjnmsWPHGD16NHa7nXFjZ/Ptb/ylR47b11gsFsLDw2lra9OFziVqbm7h3//+l/dDxpSSoYweUOjdbrOFYBiexTMcjr41dLGiqpq3P1pD28mhMLkDMhg2fgAWi5/cBzI8bdflcoH+KvU4y2lzV/rD3Hsup5P33vo761ctADzD0L/1y9spGNL3Vtg2DAObzYbD4dDiJj3MFmLDwMCNG0eHw+xyAoq/t9vapiY+2rWb3RWVZ9RXWFjI2HFjyc7KNrG6C4uIiMA42ZOxtbXV7HICyqVc4zodTt79yzu8+fvXcDqcAEybNo3HH3+cjIyM3ii3T/HFZ7OekpysxelEeoqffPIT6b6//OUv2O12AD5xwzdMrkb6mhMnmnn55Ze84d8VRYPOCP/6su2HynhtxUra2tsxDCge3Z/hEwf6T/gnQcditXLdzfcw8/rPAXCisZXffv9Z1i/daXJlIuIPEmNiuG7sGD43azpFOdlYDAPwTPXyrxf/xQsvvMCevXv8MrwU/2C1WfnEt27iZ2/cT0ZhJuBZKHDKlCm88cYb5hYnImIS9QCULvH3HoC1tbWMHDmSlpYWhg+bwQ+//3T3i+yj1APw0jU2NvLSSy95JxwfUVDAtGElnPy84dXXegC63W5W7tzFml2euW+sNgsjJw8mMy/F5MrOQT0AfcrfegCebtum5bz10hM4nQ4MAz799Wu46lPjzS6ry/y9J1Vfph6AvtPX2m1jSwsb9u1n28FDdDhOtYW4uDhGjBhBSUkJERH+MZetegD6zuVe49pb7bz8yL/58OkPvM/ddtttPPLII8TFxfmi1D5HPQBFgoMCQOkSfw8AHQ4Hr776Jo8++nu+eNcjDBwwpgeq7JsUAF6auro6Xn75ZRobGwEYPaCQK4cOPSv8g74VALZ3OHh/wwbvYh/hEaGMnTGUhORYkys7DwWAPuXPASDAoQPbefmZX9HW6pl7c9Ynr+DTX7v6jLr9VV8LUvoSBYC+01fbbVtHO1sOHGTT/gM0t7V5n7fZbBQVFTFi5Agy0s0d3qkA0He6e427dckW/v6DJ6k/Xg9AVlYW//u//8ukSZN6uNK+RwGgSHBQAChd4u8BIEDzCRfLFrdhnCu5CSIKALvuyJEjvP76694FP8YPLmJ8UdE5wz/oOwFg3YkTvL36I2oamwCITYhi3MwSIqPCTa7sAhQA+pS/B4AAVccq+Nc/fkFDXRUAQ8YWcM+9txId59+ruffVIKUvUADoO3293TpcTnaXV7LlQClHP3YdmZ6ezsiRIxk0aBAhISG9XpsCQN/piWvcE3VNPP3//sm6eWsAz38LX/va1/jxj3/sN71IzaAAUCQ4KACULukrAeDyJfYeOVZfpgCwa3bt2s38+fNwnBxKdOXQoYwZeOE5//pCAHjgyFHeW7cee4envsy8FEZMGoQtxGZyZRehANCn+kIACHCiqY5///MRjlTsByApLY6vPfBp+g3KNLmy8+vrQYo/UwDoO4HUbo/W1bH5QCl7KipwnHZ+CwsLo2jwYIaVlJCent5r9SgA9J2eusZ1u92sfHU5z933DG0nPD1JCwoK+MMf/sD48X1nCoqepABQJDgoAJQuUQDYdygAvLjVq1ezbNkyAKwWC1eNGsng3IuvPurPAaDb7eaj3XtYvXMXbrcbw4CikfkUluRi0Ad6xSoA9Km+EgACdHTYmf/6U2xetxAAW4iVT3/taqbfPNYve3gHUpDibxQA+k4gttvWdjvbD5axpfQgDSd79ndKSUmhpKSE4iHFRIT7tpeXAkDf6elr3KryKp76wd/YvXoX4Pnv4otf/CI//elPiY6O7vbx+xIFgCLBQQGgdIkCwL5DAeD52e123nvvPfbs2QNARGgoN46/gqzkpC693l8DwFZ7OwvWr6f06DEAQkJtjJ5STGpWosmVXQIFgD7VlwJA8ATaG9f8h/feeAqn0xP8FI/pzxd++AkSU/1rwvZADFL8hQJA3wnkdutyuymvqmLbwUPsP3wE52nXQlarlQEDBlAyrIS83Dyf3FRQAOg7vrjGdblcLH5hES//8l+0NXt6A+bm5vLYY48xderUHnmPvkABoEhwUAAoXaIAsO9QAHhux44d56233vSu9JsYE8NNE8YTHx3V5WP4YwBYUVXN/HXrONHquWiNTYhi7PShRMX0sXlsFAD6VF8LADsdLt/H6//6I7XVnsVsIqLC+MzXr2HitSOwWPyjN2AgBylmUwDoO8HSblvb7ewsq2D7wUNUn1zsq1NMTAzFxcUMGTKEpKSu3QjsCgWAvuPLa9yaymqe/n//YOviLd7nbr/9du67776gCKAUAIoEBwWA0iUKAPsOBYBncrvdbNy4iSVLFnvn+xuUncWskSMJvcR58fwpAHS53aw5bcgvQO6AdIaOG4DNZjW1tsuiANCn+moACNDRbmfh/OdZs2Ke97n8oiw++61rKSjONrEyj2AJUsygANB3gq3dunFzrK6ebQcPsbu8gnbHme0pPT2d4iHFDB48mMiI7i08pADQd3x9jet2u1kxdxkvPvA8LY0tAMTHx/PTn/6UOXPmYLX2weurLlIAKBIcFABKlygA7DsUAJ7S2NjEe+/N59ChQ4Bnvr8pJUMZ3r//eVf6vRB/CQBPtLbx3rr1lFd5Vku1hVgZNn4g2f3TTKup2xQA+lRfDgA7Hdy3lbfn/pn62uPe54ZPHMjsO6+kv4lBYLAFKb1JAaDvBHO77XA42Hv4MDvLKiivqjrj57dYLPTv35/i4mIKCgqw2S59AS0FgL7TW9e49cfrefH+51jzzkfe50aOHMlvfvMbhg8f7rP3NZMCQJHgoABQukQBYN+hANBzB3fr1m0sXrwIu93TJhKio7l27BjSE+Iv+7hmB4BuN+wqL2fR5i3eVX7jkqIZPaWY6Nju9VgwnQJAnwqEABDA0dHO6mXvsHzhq3S0t3mfHzAslyuvH8XoKYMJiwjt1ZqCOUjxNQWAvqN269HU2squ8gp2lpVT87EhwmFhYRQVFVE8pJjsrK7fZFAA6Du9fY27belWnr/vGY4eOAp4/rv53Oc+x//8z/+QltaHb7qegwJAkeCgAFC6RAFg3xHsAWB1dTUffPABFRUV3udGFhYwqbiYkG4OjTUzAGyx21m4aTN7Kw97n8sfnEXx6AKsp4U7fZYCQJ8KlACwU1NjHasWv8H6j97H0dHufT4sIpSh4woZNn4Ag0flk5AS6/OVgxWk+I4CQN9Ruz2TGzdV9Q3sKCtnd3kFLfYzryfj4+MpKipi8ODBFw0jFAD6jhnXuB32Dt77v3m8/fibtLd5/t5ERkbyrW99i6997WtERXV9Lml/pgBQJDgoAJQuUQDYdwRrAGi321m9ejXr1q3z/txxUVFcNWokOSk9c+FgRgDodsPew4dZtGmz9wNJRFQYwycOIjWzD63yezEKAH0q0ALATs0nGli3agGb135IQ/3Zf6fiEqPJL8oiZ0A6aVmJpGQlkpqVSHRsRI8FgwpSfEcBoO+o3Z6f0+Wi7PhxdpaVs//IERwfO2empKRQVFRE0eAi4uPiz3q9AkDfMfMat6q8ipd+8SLr5q/1PpeWlsaPfvQjbr/99ssaLu5PFACKBAcFgNIlCgD7jmALAJ1OJ5s3b2HVqpW0tHgmbLZaLIwZOIBxgwZi68EJm3s7AGxsaWHR5i0cOHLU+1xOQTpDxxUSEtq3LzTPogDQpwI1AOzkcjkp3beVnVtWsXfnek40XfjvSkRUGElp8SSlx5GUFk9yejxJ6ae+R8WEdzkgVJDiOwoAfUfttmvsHR3sraxkV3klFdXVZ/2uMjMzKSoqYlDRIKKjogEFgL7kD9e4e9ft4aWH/8W+9Xu9zxUWFvL973+fW265pc8GgQoARYKDAkDpEgWAfYc/XBz1lj179rB06dIz2lBuairThw8jMSa6x9+vtwJAl8vNxv37WbVzJx0OJwDhkaGUXDGQjNwAvQhSAOhTgR4Ans7tdnPsyCEqy/ZwuHwvleX7qDleicvl7PIxwiNDyeyXSk5BGtkFaeQUpJM7IJ3QsJCz9lWQ4jsKAH1H7fbSnWhrY09FJbsrKjhae+a1q2EY5ObmUjS4iGElw4iMjFQA6AP+co3rdrtZN38tcx99iWMHj3mfz8/P53vf+x6f+tSnCAk5+++FP1MAKBIcFABKlygA7Dv85eLIV9xuN3v27GX16lUcP35qNdDk2FgmDx1Cv7S0y1rhtyt6IwA8dOw4S7duo/rkZOSGAf0GZVI0sn/g9fo7nQJAnwqmAPBcXE4nDQ3V1FUfpa7G81VfX0VDXRX1tcdpaW686DGsNgt5AzMZUJJD4dBcCofmEBMfpSDFhxQA+o7abffUNzezu6KC3eWVZy0eYrVaKSwsZMjQIeTm5Pa5IMif+ds1rqPDwbKXlvDOn9+mpuLUZ6Xs7Gzuvvtu5syZQ1xcnIkVdp0CQJHgoABQukQBYN/hbxdHPcXlcrF79x5Wr151RnuMCg9nYvFgivNysfh4sn9fBoA1jU0s27aN0qOn7iTHJkQzfMJAElJie/S9/JICQJ8K9gDwYtrb22ioq6ah7jj1dcepqznG8SOHOHbkIM0nGs77uvTcZAYNz2PwqP4UluQQnxTTi1UHPgWAvqMAsOdUNzawq7ySPRUVNDS3nLEtJCSE/v37M3DgQPr3709oaO+uUh5o/PUa19HuYMVry3nniTepKq/yPh8ZGclnP/tZ7rnnHgoLC02s8OIUAIoEBwWA0iUKAPsOf704ulxtbXa2bNnCxo0baDztLntUeDhjBg6gpF+/bq/u21W+CACbWlpZu2cPW0sP4jp5Og4JszFoeD/6DcrEYgmAFX67QgGgTykAvHwnmuo4UnGAikO7KT+4i8qyvTgc7efcNzUrkYHD8xg0PI+Bw/uRlNY3en74KwWAvqMAsOe5cXO0to49lYfZXV5Bc1vbGdttNhv5+fkMHDSQgv4FhIWFmVRp3+Xv17iODgdr3l7Ngqfe49C2g2dsGzduHLfffjs333wz0dE9P01NdykAFAkOCgClSxQA9h3+fnHUVbW1taxfv4Ht27fR0XEqbIuJjGDMgAEM7ZfXowt8dEVPBoAnWtu8wZ/z5P9PFotBv6IsBg7LO+dcYwFNAaBPKQDsOU5HB0cqSykr3UHZgR2UHdyJva3lnPsmp8czcHgeA4fnMWBYHqmZCT22+nAwUADoOwoAfccWYsPtdlN27ORKwoeP0GI/8/rUarXSr18/Bg4aSGFhIeFh4SZV27f0lWtct9vN3rV7eP/v77F+wTrcrlP/jUVGRjJ79mw+8YlPMHXqVCIiIkys9BQFgCLBQQGgdIkCwL6jr1wcnUtHRwd79uxh69atlJeXn7EtLSGeEQUFDMrOwmpSr7ieCADrm5vZuG8/2w4exHFaEJORl8LgUflEx0b2VLl9iwJAn1IA6Dsut5Oqo2WU7tvGoQPbKTuwk7bWE+fcNzI6nNwB6eQOyCBvYAZ5AzJIzU7CYlEoeC4KAH1HAaDvfLzdutwuKqtr2Hv4CPsqD5/VM9BisZCbm0tBYQGFBYXExgbBtB+XqS9e49ZUVrN87jKWv7KMqrLjZ2yLjIxk1qxZ3HDDDUydOpXExESTqlQAKBIsFABKlygA7Dv64sXR4cNH2LZ1Kzt37aS9/dTQOothUJiZyYjCAjITE322uEdXXW4A6HbD4ZoaNuzbz/4jR874sJWRm8zA4f2IS/S/4SC9SgGgTykA9KGPtV23y8XxY2UcOrDjZCC444KLjIRFhJJTkOYJBgszyB2QTma/VGwhvdvD2R8pAPQdBYC+c6F263K7OVJby97Kw+yrPEzTOVYJTklJoX9BfwoLCsnIyFCv4dP0xWvcTi6Xiz1rdrPs5aVseH89rY1n9hw3DIOSkhKmTp3KlClTGDNmTK8OFVYAKBIcFABKlygA7Dv6ysXRsWPH2LVrN3v27Ka+vv6MbTGRERTn5TE0L4/YSP8YGgGXHgDaOzrYXV7JtkMHOVZX733eMCAtJ5mBw/K0aEAnBYA+pQDQhy7Sdt1uN9XHK6gs28vRygMcqTzAscMH6eg4/98rq81CZr9UcgvTvT0GcwrSCI8MrjnDFAD6jgJA3+lqu3W73Rytq2Nv5WEOHDlK3Ymzew5HRkbSv39/CgoKyM3LDfqhwn3lGvdiHO0Odqzczrp5a9n4/nqaapvO2scwDAYPHszo0aMZNWoUJSUlDBgwgMhI34wUUQAoEhyCKgBsaGhg7ty5rFmzhpqaGsLCwigoKOD6669n/Pjxl31ch8PBO++8w5IlSzh8+DAAWVlZTJ06ldmzZ2Oz2S74+gMHDvD666+zdetWGhsbiYuLY+jQodx6663k5+f79L27SgFg3+GvF0dut5vDh4+wf/8+du8+O/SzWiwUZmYwJC+PnNQUn6/oezm6EgC63G4qqqrZUVbG3srDOJxO7zarzUrugHTyB2cTHeM/waZfUADoUwoAfegy2q7L5aSm6sjJQHA/RytLOXbkIG2tzed/G8OzyEj/4hwGlORQWJJLRm5yQPcOUgDoOwoAfedy221tUxMHjh6j9MhRDtfUeBcG62QYBunp6eTl5ZHXL4+szCysvTwXstn89Rq3O1xOF6VbDrB92Ta2L9/GvvV7cXY4z7mvYRj069eP4uJiBg0aRL9+/cjNzSUvL4+MjIxutQcFgCLBIWgCwLKyMu69914aGhoAiIiIwG63e/943Hjjjdxzzz2XfNzW1lZ+9rOfsWfPHgBCQ0MBvMMYi4qKePDBBwkPP/cduyVLlvDHP/4Rh8NzgRAVFUVzs+cDgM1m43vf+x5XXnmlT977UigA7Dv86eKora2N0tJSDhw4QGlpKa0fG+piGAY5KSkMzMqkMDOTiLBQkyrtmvMFgE6Xi4qqavYdPsy+c0z2HR0bQe6ADHIHZhAaGmSLe3SVAkCfUgDoQz3Udt1uNw11VRw9XMrRygOe74dLaWqoPe9romMjKCzJZUBJLoUlueQNzMDWS6ui9wYFgL6jANB3eqLdtrW3c/DYMQ4cOcbBY8ewd5x90zEkJITs7GxycnLIysoiPT29x278+yt/usb1lbbmNvat38uBTfvZv2EfBzbtP2cPwY/rbA+5ubmkpaWRlpZGamqq93Hn1/mGFSsAFAkOQREAdnR08I1vfIOjR4+Sl5fH97//ffLz87Hb7bz55pu88MILuN1uvv3tbzNr1qxLOvbvfvc7lixZQlRUFN/+9re9PQlXr17N448/TnNzM9OnT+d73/veWa8tKyvju9/9Lg6Hg8mTJ3P33XeTmJhIbW0t//d//8eKFSsICQnhj3/8I9nZ2T363pdKAWDfYebFUVtbG+XlFZSXl1NeXkZVVdVZHywMwyA7OYkBWVkMyMwkMrzvDGk7PQCsbWyk7PhxDh0/TtnxKtpOm7vQs6+VzH4p5AzIIDE1FoPA7aXTIxQA+pQCQB/ycdttPtFwMhQs5UjFfsoP7uREU/059w0Ns3l6CA7LZeCwPPoXZxMW3ndvOigA9B0FgL7T0+3W6XJxtK6OsuNVlB2v4mht7Vm9A8GzsnBaWhqZWZlkZWWRlZlFVFRUt9/fnwRDAPhxbreb6vIqKnZXULm7goo9nu9H9h/G0X7p7SsyMpKkpCSSk5N58cUXveGaAkCR4BAUAeA777zDk08+SVhYGH/+859JSUk5Y/tf//pX5s2bR2JiIk899VSX756Vlpby3e9+F7fbzY9//GMmTpx4xvYVK1bwq1/9CsMwePzxx8nLyztj+yOPPMKqVavIz8/nscceO6PbttPp5Pvf/z6lpaVMmjSJH/3oRz363pdKAWDf0VsXR06nk6qqao4ePcrRo0c4evQo1dXV5/wgEREWRr+0VPLT0shLSyO8j/WCc7nd1DY2cbyhgSO1tVRUVVPbdPbdWKvNQlpWEhl5KaRlJ2ILCew78T1KAaBPKQD0oV5uu263m/raY5SV7qT84C7KDu6k5njlOfe1Wi3kDcpkQEkuA4fnUTg0h6g+NP2AAkDfUQDoO75ut/aODipraryBYE3j+RcZiomJITU11fOV5vkeHxff4zX1lmAMAM/H5XRRd6yO6vIqqsqOU1VeRXV5FdWV1TQcr6f+eD1tJ9oueIyDhw4SFekJiRUAigSHoPh0unjxYgCmTJlyVvgH8MlPfpL58+dTW1vL1q1bGTlyZJeOu2TJEtxuNxkZGUyYMOGs7RMnTiQjI4MjR46wZMkSPv/5z3u3NTc3s3btWgBuvvnms+ZssFqt3Hzzzfz+979nzZo1tLS0nDHpa3feW+RSuFwu6usbqKmpoaamhtraGqqrq6mursbpPPccJTarlcykJLKTk8hNTSEtIcEv5/Q7F3tHBzWNTdQ0NlLT1ER1QyPH6upod5z7Ij4iMozkzATSspNIzUoMqOF3IuJ/DMMgISmdhKR0ho+ZDnh6CZYf3EVZ6Q7KSndytLIUt9uF0+niwI4KDuyoYMFLKzEMyMpPY8CwXPoPziK7IJ2MvGSdt0T6kLCQEPqnp9M/PR3wDBc+XFvLkZpaDtfUcrSuzjv/cFNTE01NTezfv//U68PCSExMJDExkYTEhFOP4xMCfghxILFYLSRlJpGUmcSgK4rOuY+9pY2G4w3UnwwEG47X01jTSFNNIy1NrYRHBPeiMiLBKODP8q2trezduxeAUaNGnXOflJQUsrOzKS8vZ/PmzV0OALds2QLAyJEjzzkJt2EYjBw5kiNHjnj37bRjxw7vvH/nq6vz+Y6ODnbu3Mno0aN75L1FOrndbtra7LS2ttDc3ExjY+NZXw0NDecN+jpFhYeRlpBARmIi2cnJpCXEY7VYLvgaM7jcbtra22m1t9PU2kpjSwuNLS00tbTQ2NJKY0szJ1ovfLc0LCKUxJRYktLiSclMIDo+UsN7RcRUUdFxFA29gqKhVwBgb2ulomw3ZQc8gWBl+V6cjg7cbqg4cIyKA8dY9IbnJqQtxEpGXgo5helk5CaRkpFASmYiKZkJREbrw6GIvwsPDT0jEHS6XFQ1NHCkto6q+gaqGhqoaWzEebLHnN1u58iRIxw5cuSsY0VGRhIbG0tMTAwxsTHex1FRUURGRhIZEUl4eHhALz4USMIiw0ntF05qvzSzSxERPxHwAWBFRYV3aMOFhsHm5eWdnLesvEvHdbvdVFRUXPS4ubm5AGcdt/Pf8fHxxMXFnfO1cXFxxMXF0dDQQFlZmTcA7O57i//6+DAct9uNy+XC5fL05HC5nGd8dzqdJ7c5Tz7npKPDAbhpbm7GbrfT3t5Be3s7HR3ttLe309raSktLC62trbS2tl7SEArDMIiLjCQxNobk2FjSEhJIi48nOiLCOzfeqdrh4+Phzhpk5P74P924XG6cJ39ml/vkY7cLp+u038XJ34vD6aTD4aDD4aTd6aDD4aDd4fA+Z+/ooLXdTqu9nVa7nbaOjksa6hQSaiMmPor45BgSkmNJTIsjKjoCDA2jFBH/FRYeQcHAERQMHAF4Fi06XL6PstKdlJXuoOLQbuxtLZ5tHU7K9x2lfN/Rs44TFRtBfHIMsQnRxCZEnfyKJjIqjPCoMMIjwwiPCCU8MoywiFBCQqxYbVasNsvJ7ycfWy0KDER6idViIT0hgfSEBO9zTpeL2qYmjtfXU93YRF3TCepOnKChufmM66KWlhZaWlo4evTs80EnwzCIiIjwfoWFhREaGur5Cgs99Tg0lJCQEKxWK1arFZvV5vlu83y32qzebRaLBYvhOU98/Mti0flDRKSnBHwAWFt7avW8xMTE8+7Xua2rcx60trbS1tbW5eN2hi0RERFnvM+FXtu5vaGh4Yy6uvve5/L888/z4osvnnf77bffzh133HHBWi+F5WTvMIvFQsJpFyjd8dHqJfz2t292+ziaC+dsBoBheOaeam6mvrmZA0fOf3HYl1htViKjw4iICicyOpyYuChiEqKIiY8iPDL0vBedp8+pJj3H4oc9RwON2q5v+HPbDbWG0a9wCP0KhwDgdrmoqz3G0cMHOVpZyrHDBzl25CAN9dVn3MlpbmylubGVSo53uwarzYph8fSX9p5XDc/jzr8xhnHye+c+xql9Pd9O7iMiPcbldntuOJ/8fuZjs6s7k+H9n8t+9VkPL+PVAePQgTKSEz2fw3zx2UxE/E/AB4CdQRl45rw4n85tra2tXTru6ft15bidr+kM4Tpff6HXnq+u7r73uTQ3N3P8+Pkv8FtaWs6ap7AnGIbRY8c1LB2Uls3rkWNJ32QxDMIjw4kIDyciIpzIyEji4mKIi4slLj7W8z0uhrj4WBKTEklPTyUuLkZ3lkUkCPUHzpxD2DM08DAVFRVUVpRTWVlJTU01tbW11NbWUFtbS2NDw2W9m9Nx4akkRESkd4VaQ876HNaTn81ExP8EfAAoXRMVFUVqaup5t0dGRl50HrhL0dmdv3OIa0/Izc2ioDD2jOc+Huyc6klgdGv75R7vcl5jsVi8QyQ+/nWubeHh4d7hGDab7axeKV39mcz4t2EYhISEEBIS4h06cqGvyMhIoqOjvV8RERE+DfN80W7Fo3OYj8vlUi9cH1Db9Z1ga7sOh4OmpiYaGxu9Cww0NTXR3Nx8crqJjrO+dz7ubHvu03oanf718W2dOtttMPx+e0vn8MqP/66l+/S7BafTSXt7Ow6HA6fTM0XN6Y8//tX537e3B+LH/n2ur4//LTvf7/pc0+t0xYX2C5T/X0NDQ72f7/z5OkGBpEjPCfgAMDz81ATWdrv9jJV0T2e32wEu2EvudKfv1/naCx3346/pfHyh156vru6+97nMmTOHOXPmnHd7dXV1jy4J37nUvMvl6rHjpqens2DBgh45Vl9mtVpJSEigrq6uR0Nbf2e32y/631N3+aLdikdnu+3KojNy6dR2fSdY225sbCyxsbEX37EbOtut0+lUu+1hwXqt0BvUbn1H7bZnnX7t7M/XCcnJyWaXIBIw/HfCmh5y+hx5p88H+HGd27o650HnxLddPe7p+59e14Vee766uvveIiIiIiIiIiISPAI+AMzOzvYOCSwrKzvvfp3bcnJyunRcwzDIzs6+7ON2/ru+vp7GxsZzvrahoYGGk3PtdK7o2xPvLSIiIiIiIiIiwSPgA8CIiAgGDBgAwIYNG865T3V1NeXl5QAMHz68y8ceNmwYABs3bjzvPps2bTpj307FxcXYbLYL1tV53JCQEAYPHtxj7y0iIiIiIiIiIsEj4ANAgGnTpgGwdOlSqqqqztr+2muv4Xa7SUxMpKSkpMvHnTJlCoZhcPjwYVatWnXW9pUrV3L48GEMw/DW0CkyMpKxY8cC8Oabb541j4XT6eTNN98EYNy4cWfNXdid9xYRERERERERkeARFAHgNddcQ3p6Om1tbTz00EOUlpYCnolP586dy7vvvgt4FsLo7JXX6e677+YTn/gEf/jDH846bn5+PlOmTAHgiSeeYPXq1d6VqVavXs2f/vQnwBNAnj6Et9Odd96JzWZj//79PPbYY94JV+vq6njsscfYv38/ISEh3HnnnT3+3iIiIiIiIiIiEhwCfhVg8Ayh/elPf8q9997LwYMH+c53vkNkZCRtbW3eZc5vuOEGZs2adcnH/vrXv86RI0fYs2cPv/zlLwkNDQWgvb0dgKKiIr72ta+d87W5ubl85zvf4Y9//CPLli1j+fLlREZG0tzcDIDNZuM73/mOd76/nnxvEREREREREREJDkERAIInbHviiSd49dVXWbNmDdXV1URFRdG/f39mz57N+PHjL+u4ERERPProo7zzzjssWbKEw4cPA1BQUMC0adOYPXv2Wb0KTzd16lRycnJ47bXX2LZtG42Njd6hyLfeeiv5+fk+e28REREREREREQl8htvtdptdhPi/6urqHj1eQkICVqsVp9PpHfosPcNqtZKQkEBdXd1Zc0tK96jd+o7arW+p7fqO2q7vqN36jtqt76jd+o7are/4c7tNTk42uwSRgBEUcwCKiIiIiIiIiIgEKwWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISABTACgiIiIiIiIiIhLAFACKiIiIiIiIiIgEMAWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISABTACgiIiIiIiIiIhLAFACKiIiIiIiIiIgEMAWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISABTACgiIiIiIiIiIhLAFACKiIiIiIiIiIgEMAWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISABTACgiIiIiIiIiIhLAFACKiIiIiIiIiIgEMAWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISABTACgiIiIiIiIiIhLAFACKiIiIiIiIiIgEMAWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISABTACgiIiIiIiIiIhLAFACKiIiIiIiIiIgEMAWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISABTACgiIiIiIiIiIhLADLfb7Ta7CAk+zz//PM3NzURFRTFnzhyzyxHpErVb6avUdqUvUruVvkjtVvoitVuR4KAAUExx/fXXc/z4cVJTU5k3b57Z5Yh0idqt9FVqu9IXqd1KX6R2K32R2q1IcNAQYBERERERERERkQCmAFBERERERERERCSAKQAUEREREREREREJYAoARUREREREREREApgCQBERERERERERkQCmAFBERERERERERCSA2cwuQILTHXfcQXNzM1FRUWaXItJlarfSV6ntSl+kdit9kdqt9EVqtyLBwXC73W6zixARERERERERERHf0BBgERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmFYBll7V0NDA3LlzWbNmDTU1NYSFhVFQUMD111/P+PHjzS5PgtCHH37IH//4x4vu9/zzzxMbG3vObatWrWL+/Pns378fu91OcnIyY8eO5bbbbjvva0Qu5MSJE2zbto19+/axf/9+9u3bR0NDAwAPP/wwJSUlFz1Gd9qlztVyObrTbu+++26OHz9+weNff/31fPWrXz3vdrVbuVxVVVWsWrWKLVu2cPDgQWpra7HZbKSkpDBixAhuvPFG0tPTL3gMnXOlt3Wn3eqcKxKcFABKrykrK+Pee+/1fhiIiIigubmZTZs2sWnTJm688Ubuuecek6uUYGWxWC54gW4Yxjmf/+tf/8q8efO8xwgLC+Pw4cO8+eabLFmyhIcffpicnByf1CyB66OPPupSMH0+3WmXOlfL5epuuwWIjIwkNDT0vNvOR+1WLldVVRV33303brfb+1xkZCTt7e2Ul5dTXl7OggUL+O53v8vkyZPPeQydc6W39US77XyNzrkiwUMBoPSKjo4OfvGLX9DQ0EBeXh7f//73yc/Px2638+abb/LCCy/w9ttvk5+fz6xZs8wuV4JQcnIyTz311CW9ZsGCBcybNw/DMLjzzju56aabCAsLo7S0lMcee4xDhw7xi1/8gj/96U+EhIT4qHIJVAkJCRQUFFBYWEhmZiaPPfZYl17XnXapc7V01+W220733HMPM2fOvKTXqN1Kd7hcLgBGjRrFjBkzGDFiBLGxsTidTnbu3MmTTz7JwYMHeeyxx8jOzqZfv35nvF7nXDFDd9ttJ51zRYKL5gCUXrFgwQKOHj1KWFgY9913H/n5+QCEhYXx6U9/muuuuw7wDLN0OBxmlirSJR0dHbz44ouAZ4jEpz/9acLCwgDIz8/nZz/7GWFhYRw5coQPPvjAzFKlD5o2bRrPPPMM9913H3fccQdjxozp0uu62y51rpbuuNx2211qt9Id0dHR/P73v+f+++9nypQp3tEAVquVoUOH8sADDxAXF4fD4eDNN98847U654pZutNuu0vtVqTvUgAovWLx4sUATJkyhZSUlLO2f/KTn8QwDGpra9m6dWsvVydy6bZs2UJdXR2GYXDrrbeetT01NZUpU6YAp9q/SFdZrdbLel1326XO1dIdl9tuu0vtVrojKiqK/v37n3d7QkICo0ePBmD//v1nbNM5V8zSnXbbXWq3In2XAkDxudbWVvbu3Qt4uqmfS0pKCtnZ2QBs3ry512oTuVxbtmwBICcn55wXPwAjR44EYPfu3bS1tfVabRK8utMuda6WvkjtVnpDZ+8qp9N5xvM654o/O1+77Q61W5G+TXMAis9VVFR4J6jNy8s77355eXneSWtFeltDQwPf/e53qaysBCApKYmhQ4dyww03nHPelM52erE2DeB2u6moqKCwsLDnCxc5TXfapc7V4g9ef/11nnvuORobG4mMjKRfv35MnDiRWbNmnXOierVb6Q3btm0Dzm5jOueKPztfuz2dzrkiwUU9AMXnamtrvY8TExPPu1/ntrq6Op/XJPJxdrud0tJSQkJCcDqdHD58mPfff5/vfve7vP7662ft39muu9KmQe1aekd32qXO1eIPysrKOHHiBGFhYTQ2NrJlyxb++te/8oMf/ICqqqqz9le7FV9bvXo1+/btAzhrsQSdc8VfXajdnk7nXJHgoh6A4nOnD3fonBj5XDq3tba2+rwmkU6JiYncfvvtTJw4kczMTEJCQnA4HOzYsYNnn32WPXv28M9//pPExESmTp3qfV1nu+5KmwZoaWnx3Q8hclJ32qXO1WKmK664giFDhjB06FDvsLXa2lo++OADXnrpJQ4dOsQDDzzA73//+zNWUlW7FV+qqqrif//3fwFPG+2cU62Tzrnijy7Wbjuf1zlXJPioB6CIBLWRI0dy++23k5eX573AsdlsDBs2jEceeYRBgwYB8Mwzz+ByucwsVUQkYN1zzz1MnDjR+0EUPDdoPvOZz/CjH/0I8PRU+fDDD80qUYLMiRMneOihh2hoaCA9PZ1vf/vbZpckclFdbbc654oEJwWA4nPh4eHex3a7/bz7dW6LiIjweU0iXRESEsKcOXMAqK6u5sCBA95tne26K20aIDIy0kdVipzSnXapc7X4qyuuuILi4mIA1q5de8Y2tVvxhdbWVh544AEOHjxIYmIiDz74IDExMWftp3Ou+JOuttuL0TlXJHApABSfO31+iNPnjfi4zm0JCQk+r0mkqzp7AAIcPXrU+7izXXelTYPatfSO7rRLnavFn3Wei08/D4ParfQ8u93Ogw8+yO7du4mLi+Ohhx4iPT39nPvqnCv+4lLabVfonCsSmBQAis9lZ2djGAbg6Up+Pp3bcnJyeqUuke7obKddadOGYZCdnd0rdUlw60671Lla+iK1W+lJdrudhx56iO3btxMdHc2DDz54wTajc674g0ttt92hdivStykAFJ+LiIhgwIABAGzYsOGc+1RXV3uXiR8+fHiv1SZyMbt37/Y+TktL8z4eNmwY4LnAqa6uPudrN27cCHjuop4+ZELEV7rTLnWuFn/WeS4+/TwMarfSczo6OvjlL3/Jli1biIyM5P777yc/P/+Cr9E5V8x2Oe22K3TOFQlMCgClV0ybNg2ApUuXnnNJ+ddeew23201iYiIlJSW9XJ0EK7fbfcHtDoeDF154AYCkpCQKCgq824YNG0ZCQgJut5vXX3/9rNdWVVWxdOlS4FT7F/G17rZLnavFDBc7F69du5YdO3YAMG7cuLO2q91KdzkcDh599FE2btxIeHg49913HwMHDrzo63TOFTNdbrvVOVckeCkAlF5xzTXXkJ6eTltbGw899BClpaWAp8v63LlzeffddwGYM2cONpvNzFIliBw/fpz//u//ZsGCBRw7dsz7vNPpZNu2bfzkJz9h165dANx1111YLKdOmSEhIdxxxx0AvPPOO8ydO9c74XFpaSkPPfQQbW1tZGRkcNVVV/XiTyWBorGx0ft14sQJ7/PNzc1nbHM4HN5t3W2XOldLd11Ou33yySd58skn2bZt2xmTytfV1fHKK6/wq1/9CoDc3Fxmzpx51nuq3Up3OJ1Ofvvb37J27VpCQ0P56U9/6l0A4WJ0zhWzdKfd6pwrErwM98VuAYj0kLKyMu69914aGhoAz0pobW1tuFwuAG644Qa+/OUvm1miBJljx45xzz33eP8dGhpKeHg4LS0t3g+nNpuNu+66i5tuuumcx/jrX//KvHnzALBarYSFhdHS0gJAfHw8Dz/8sOY/kcvyiU98okv7Pfzww2fdYe9Ou9S5WrrjctrtH/7wBxYuXAh45knrXCm1ubnZu3///v259957SUlJOefx1G7lcnXe8ANPoBcVFXXB/Z999tmzntM5V3pbd9qtzrkiwUsBoPSq+vp6Xn31VdasWUN1dTXh4eH079+f2bNnM378eLPLkyBjt9v54IMP2LlzJ6WlpTQ0NNDS0kJYWBhpaWmUlJRw3XXXkZWVdcHjrFq1innz5nHgwAHa2tpITk5m3LhxfOpTnyIuLq6XfhoJNN0JAKF77VLnarlcl9Nud+3axapVq9i9ezfHjx+nqakJl8tFTEwMBQUFTJo0iSlTply0J4narVyOrVu3cu+993Z5/7feeuucz+ucK72pO+1W51yR4KUAUEREREREREREJIBpDkAREREREREREZEApgBQREREREREREQkgCkAFBERERERERERCWAKAEVERERERERERAKYAkAREREREREREZEApgBQREREREREREQkgCkAFBERERERERERCWAKAEVERERERERERAKYAkAREREREREREZEApgBQREREREREREQkgCkAFBERERERERERCWAKAEVERERERERERAKYAkAREREREREREZEApgBQREREREREREQkgCkAFBERERERERERCWAKAEVERERERERERAKYAkAREREREREREZEApgBQREREREREREQkgCkAFBERERERERERCWAKAEVERERERERERAKYAkAREREREREREZEApgBQREREREREREQkgCkAFBERERERERERCWAKAEVERCRoLV68GMMwMAyD+++/H4C9e/fygx/8gCFDhhAfH3/Gtk5tbW387W9/44YbbiAnJ4fw8HDi4uIYOnQo3/72t9mzZ89533Pw4MEYhkF2dvZ597n33nu9dcXExNDR0XHO/X7zm99493v33Xcv+ecXERERkeCgAFBERETkpOeff57hw4fz2GOPsWPHDhoaGs7aZ8mSJRQWFvLVr36Vd999l4qKCux2O42NjWzfvp0nnniC4uJiHnnkkXO+x/Tp0wGorKxk9+7d59xn4cKF3scnTpxgzZo1F9zPZrMxZcqUS/pZRURERCR42MwuQERERMQfrFy5kocffhjDMLjrrru48soriYqKYt++feTm5gIwf/58brrpJjo6OrBYLFx77bXMmjWLrKws2traWLduHc8++ywNDQ385Cc/AeD//b//d8b7zJgxg7/85S+AJ8AbNGjQGdubmppYt27dGc8tXLiQSZMmnfFcR0cHy5cvB2DMmDHExMT03C9DRERERAKK4Xa73WYXISIiImKGxYsXe3vkAaSmpvLBBx8wbNiws/Y9cuQIQ4cOpba2ltTUVN58803Gjx9/1n6VlZVce+21bNu2DavVyrZt2ygqKvJur66uJjU1FbfbzSc/+Unmzp17xuvnzZvH7NmzAZg4cSIrV65k2rRpLFq06Iz9Vq5c6Q0Ff/KTn/Dwww9f/i9CRERERAKahgCLiIiInPS3v/3tnOEfeObbq62tBWDu3LnnDP8AsrKyeOWVV7BarTidTv74xz+esT05OZmSkhLAE0B+/F5s57DegoIC7rrrLgBWrVpFW1vbOfcDT69CEREREZHzUQAoIiIiAuTl5XHTTTedc5vb7ebZZ58FYMKECVx55ZUXPFZRURHjxo0DYMGCBWdt7wzsampq2Lx58xnbOoO9GTNmePez2+2sWLHinPuFhYWdNTxYREREROR0mgNQREREBJg0aRKGYZxz244dO6ipqQEgISGBN95446LHs1qtAJS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" + "image/png": 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,\n", + "
,\n", + "
)" ] }, - "execution_count": 42, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -754,6 +668,7 @@ "(\n", " ggplot(fixed_pol_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", " ggplot(ppo_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + " ggplot(results_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", ")" ] }, @@ -767,7 +682,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 18, "id": "d0fd387d-f999-48bd-a79c-142c9f3c0d51", "metadata": {}, "outputs": [ @@ -775,9 +690,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-05 20:50:03,511\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:50:19,287\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:50:35,191\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-06-06 18:11:41,693\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:11:58,052\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:12:14,206\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], @@ -803,7 +718,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 19, "id": "495838f3-cb9e-448f-9a04-c5241cb935c9", "metadata": {}, "outputs": [ @@ -811,9 +726,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-06-05 20:51:32,538\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:51:40,525\tINFO worker.py:1749 -- Started a local Ray instance.\n", - "2024-06-05 20:51:48,198\tINFO worker.py:1749 -- Started a local Ray instance.\n" + "2024-06-06 18:12:30,533\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:12:38,570\tINFO worker.py:1749 -- Started a local Ray instance.\n", + "2024-06-06 18:12:46,479\tINFO worker.py:1749 -- Started a local Ray instance.\n" ] } ], @@ -848,7 +763,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 20, "id": "1b6d4958-6956-41ca-8368-32942f1e2226", "metadata": {}, "outputs": [], @@ -866,12 +781,16 @@ " pd.DataFrame(PPO_mw_rews),\n", " pd.DataFrame(PPO_bm_rews),\n", " ]\n", + ")\n", + "\n", + "results_df = pd.concat(\n", + " [pd.DataFrame(CR_rews), pd.DataFrame(Msy_rews), pd.DataFrame(PPO_2o_rews), pd.DataFrame(PPO_bm_rews)]\n", ")" ] }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 21, "id": "c6673202-3c37-4779-b648-2c2636b6c7fa", "metadata": {}, "outputs": [ @@ -884,7 +803,26 @@ }, { "data": { - "image/png": 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zsBIAAAAAgKcgAATg9VavXi1JSmqVrICgAIOraZrQyFAlZCZIklasWGFsMQAAAAAAj0AACMDr2ZcAp3Xw7OW/dvZ9AAkAAQAAAAD1QQAIwKsdO3ZMubm5kqR0D9//zy6zS9Uy4G3btunQoUMGVwMAAAAAcHcEgAC82rp16xzHXjMDsFojkJUrVxpYCQAAAADAExAAAvBq9gYgkpTWLs3ASpwno1OmTGaTJBqBAAAAAADqRgAIwKutX79ekhQaGaaI+Ehji3GSoNAgJbeu6mbMDEAAAAAAQF0IAAF4tQ0bNkiSUtqmyGQyGVyN89j3AWQGIAAAAACgLgSAALyafQZgSttUgytxLnsn4D179mjv3r0GVwMAAAAAcGcEgAC81qFDh3TgwAFJUnKbFIOrca6s4zMAJSk7O9vASgAAAAAA7o4AEIDXsi//laqWAHuTtPbpsvhZJLEMGAAAAABwagSAALxWzQDQu5YABwQFKLVd1de0YsUKY4sBAAAAALg1AkAAXsu+/19YVJjCY8MNrsb5MjtX7QO4YsUK2Ww2g6sBAAAAALgrAkAAXuv3DsCpXtUB2M7eCOTgwYPatWuXwdUAAAAAANwVASAAr/V7AOhd+//ZVW8Ewj6AAAAAAIDaEAAC8Ep5eXle2wHYLuW0VPkF+EmiEzAAAAAAoHYEgAC8kn3/P8n7GoDY+fn7Ka1dmiQCQAAAAABA7QgAAXilmh2AvXMGoCRldK5aBpydnU0jEAAAAADASREAAvBK9gCwRXQLhcdGGFyN62R2ypRU1Qhkz549xhYDAAAAAHBLBIAAvJI9AEz24tl/kpRxPACUWAYMAAAAADg5AkAAXun3DsDeuf+fXcppqbL4WSQRAAIAAAAATo4AEIDXycvL08GDByVJya2TDa7GtQKCApRyWlXIuXLlSoOrAQAAAAC4IwJAAF4nJyfHceztAaD0+zJgZgACAAAAAE6GABCA16keACb5UAC4d+9e7du3z9hiAAAAAABuhwAQgNexB4BBoUGKTIgyuBrXy+yc5ThmFiAAAAAA4I8IAAF4nU2bNkmSElsmyWQyGVyN66W1T5PJXPV1EgACAAAAAP6IABCA17EHgEmtkwyupHkEBgcquXWKJAJAAAAAAMCJCAABeJWysjJt27ZNUtUMQF+R2TlTEgEgAAAAAOBEBIAAvEpubq4qKyslSUmtvL8BiJ29EcjOnTuVl5dnbDEAAAAAALdCAAjAq9iX/0q+0QHYzh4ASswCBAAAAADURAAIwKvYA0CTyaSEzASDq2k+6R0zHA1PCAABAAAAANX5GV1AcyooKNCnn36qn3/+WXl5eQoMDFSrVq107rnnqnfv3o0et6KiQl9//bXmz5+v3bt3S5JSUlI0aNAgjRo1Sn5+J/41r1q1Sg888EC9r/Hf//5X8fHxjj/v27dP1113XZ3Pu/fee9WvX796XwfwdDk5OZKk2NRYBQQFGFxN8wkOC1ZCy0Tt3byHABAAAAAAUIPPBIDbt2/XAw88oIKCAklScHCwCgsLtWLFCq1YsUKjR4+uV6D2R8XFxXrooYe0ceNGSVJAQFXgkJOTo5ycHC1atEiPPfaYgoKCajzPz89PkZGRpxz72LFjqqioUFRUlGJiYmo9Lzw8XGbzySdz2usBfIU9APSl5b92mZ0yCQABAAAAACfwiQCwvLxcTzzxhAoKCpSRkaE777xTWVlZKi0t1bRp0/Tee+/pq6++UlZWloYNG9agsV955RVt3LhRoaGhuvXWWx0zCZcuXaqXXnpJ69ev13/+8x/dcccdNZ7Xvn17vfPOO7WOW1paqokTJ6qiokKDBw+WxWKp9dznn39eCQm+s9QRqI3NZnMsAfalDsB2GZ2ztHTaEuXm5urw4cN1vskAAAAAAPANPrEH4OzZs7V3714FBgbq4YcfVlZWliQpMDBQF198sUaOHClJmjp1qioqKuo97tatW7VgwQJJ0i233KI+ffrIZDLJZDKpT58+uvnmmyVJ8+bN07Zt2xpU89KlS1VYWChJGjp0aIOeC/iqAwcO6MiRI5KkpFa+FwBmVmsEsnr1auMKAQAAAAC4FZ8IAOfNmydJGjhwoOLi4k54fOzYsTKZTDp06JBWrVpV73Hnz58vm82mpKQk9enT54TH+/btq6SkJNlsNs2fP79BNf/www+SpDZt2ig9Pb1BzwV8la92ALZL75jhOF65cqWBlQAAAAAA3InXB4DFxcWOUOD0008/6TlxcXFKTU2V1LBfmu37bHXv3t3RfbM6k8mk7t271zi3Pg4ePOg4n9l/QP3Z9/+TfHMJcGhEqOLSq5oFsQ8gAAAAAMDO6/cA3Llzp2w2myQpIyOj1vMyMjK0Y8cO7dixo17j2mw27dy5s85x7bP36juuJM2ZM0dWq1X+/v4aOHBgnec/++yz2r17t0pLSxUREaG2bdtq2LBh6tmzZ72vCXgDe9gfHB6iiLgIg6sxRmbnTB3Yvp8ZgAAAAAAAB68PAA8dOuQ4jo6OrvU8+2P5+fn1Gre4uFglJSX1Hre4uFjFxcUKDg6uc+y5c+dKks4880yFhYXVef6mTZsUEhIis9msvLw8LVmyREuWLFG/fv105513yt/fv84xpk6dqvfff7/Wx8eNG6fLLrvslGPYOxGbzWZFRUXVeU2gLvaZtREREY4g/1Tse22mtElRSEiIS2tzV627t9GyGT9r8+bNslgsCg8PN7okt8J9Cs7W0PsUUBfuU3A27lNwJu5RgOfy+gDQHtJJVU0/amN/rLi4uF7jVj+vPuPan1NXALh27Vrt2rVL0qmX/wYEBOjcc8/VgAEDlJWV5Qg7tm/frs8++0xz587VokWLFBoa6mhGciqFhYXav39/rY8XFRWdshNxdSaTqd7nAvVhf6FRlw0bNkiSklunnHRZvi9o2bWV43j16tUaMGCAgdW4L+5TcLb63qeA+uI+BWfjPgVn4h4FeB6vDwA9zZw5cyRVzRzs1q1bredFRUVp0qRJJ3w+PT1dd9xxh8LDwzVt2jR99913uuCCCxx7HNYmNDRU8fHxtT4eEhKiysrKU45hNptlMplks9lktVpPeS5QHyaTSWazWVartc53rIuLi5WbmyupKgD01Xe4MztnOY6XLVumvn37GliN++E+BWdryH0KqA/uU3A27lNwJu5RzkeQiubi9QFgUFCQ47i0tLTWZYGlpaWSVK8lun88z/7cU41bn7FLS0v1448/SpKGDBnSpBvB5ZdfrlmzZqmsrEzLli2rMwAcP368xo8fX+vjBw8erHN5dFRUlCwWi6xWa72XUgOnYrFYFBUVpYKCgjoD6LVr1zpe1MZlxNZ7Nq+38Q/xV0xKjPJ25emnn37i3+IfcJ+CszXkPgXUB/cpOBv3KTgT9yjni42NNboE+AivnwdefX++6vsB/pH9sfruYxAcHOwI9OozbvXza7NkyRIVFRVJanr336CgIEcDkn379jVpLMAT2BuASFJSq2QDKzFeRqdMSXQCBgAAAABU8foAMDU11bEX2Pbt22s9z/5YWlpavcY1mUyOWXXOGveHH36QJLVr167OGXsAasrJyZEkmS1mxWckGFyNsezLgDdu3KjCwkKDqwEAAAAAGM3rA8Dg4GC1adNGkvTrr7+e9JyDBw9qx44dkqSuXbvWe+wuXbpIkn777bdaz1mxYkWNc2tz4MABrVq1SpJ01lln1buG2pSUlDjCx4QE3w5D4Bs2b94sSYpNjZVfgNfvbnBK9hmAVqtVa9euNbYYAAAAAIDhvD4AlKTBgwdLkhYsWKADBw6c8Pjnn38um82m6Ohode7cud7jDhw4UCaTSbt379aSJUtOeHzx4sXavXu3TCaTo4bazJkzR1arVQEBAfXq2lnXBr4ffPCBysrKZDKZ1LNnzzrHAzzdli1bJEkJWYkGV2I8ewAosQwYAAAAAOAjAeCIESOUmJiokpISPf7449q6daukqqYbn376qWbMmCGpqhGGn1/NmUPXXnutxowZo3/9618njJuVlaWBAwdKkiZPnqylS5fKZrPJZrNp6dKlevnllyVVBZD2/fhqY+/+26dPH4WGhtb5Nd1///36+OOPtXXr1hqb+W7fvl0vvviivvjiC0nS8OHDWU4Mn2APABMJABUZH6nIhKr9TFeuXGlwNQAAAAAAo/nEOjl/f389+OCDeuCBB5Sbm6vbbrtNISEhKikpcbQuP++88zRs2LAGj33jjTdqz5492rhxo5566ikFBARIksrKyiRV7ef3l7/85ZRjrF27Vnv27JFU/+YfBw4c0NSpUzV16lRZLBaFhISorKysRtfhQYMG6YYbbmjw1wR4mvz8fEcXMmYAVsnolKnD+/KZAQgAAAAA8I0AUJLS09M1efJkffbZZ/r555918OBBhYaGqmXLlho1apR69+7dqHGDg4P1zDPP6Ouvv9b8+fO1e/duSVKrVq00ePBgjRo16oRZhX9kb/4RGxtb516BdhMnTtTKlSu1adMm5efn6+jRo7JYLEpKSlK7du00dOjQeo8FeDr77D+JANAus1OmVv7wmzZs2KCSkhIFBQUZXRIAAAAAwCAmW12byQGqapRSl6ioKFksFlVWVjpmYwFNYbFYFBUVpfz8/BpL3f/ok08+0Y033ihJenbhC4rPiG+uEt3Wb9/+ohev/ack6dtvv1X37t0Nrsg9cJ+Cs9X3PgXUF/cpOBv3KTgT9yjni42NNboE+Aif2AMQgHezdwC2+FsUkxJjcDXuIaNzpuOYZcAAAAAA4NsIAAF4PPsS4Lj0eFn8LAZX4x6iEqPVIiZcEo1AAAAAAMDXEQAC8Hh0AD6RyWRSRqcMScwABAAAAABfRwAIwKPZbDZHAEgDkJoyO2dJktatW+foTA4AAAAA8D0EgAA82sGDB3X06FFJUkImAWB1GZ0yJUllZWVav369scUAAAAAAAxDAAjAo9ln/0lSYlaCgZW4H/sMQIl9AAEAAADAlxEAAvBo1QNAlgDXFJsaq9DIMEnsAwgAAAAAvowAEIBH27x5syTJP9BfUUnRBlfjXkwmkzI7Z0piBiAAAAAA+DICQAAezT4DMD4jQWYzt7Q/si8DXrNmDY1AAAAAAMBH8dsyAI9mDwATW7L892Qyu1QFgDQCAQAAAADfRQAIwGPZbDZt3bpVEh2Aa0MjEAAAAAAAASAAj7Vv3z4VFRVJkhLoAHxSNAIBAAAAABAAAvBY9gYgEh2Aa1O9EciKFSsMrQUAAAAAYAwCQAAey77/n8QS4FPJOr4P4Nq1a2kEAgAAAAA+iAAQgMeyB4CBIYGKTIg0thg3ltGZRiAAAAAA4MsIAAF4LHsAmJCVKJPJZHA17otGIAAAAADg2wgAAXgsRwCYSQOQU6ERCAAAAAD4NgJAAB7JarUqNzdXEg1A6kIjEAAAAADwbQSAADzS7t27VVJSIokAsD5oBAIAAAAAvosAEIBHqt4BOJEOwHWiEQgAAAAA+C4CQAAeafPmzY7jhCz2AKwLjUAAAAAAwHcRAALwSPYZgMEtgtUiJtzgatxf9UYgBIAAAAAA4FsIAAF4JHsAmJiVKJPJZHA17s9kMjn2ASQABAAAAADfQgAIwCPZA0AagNSfvRMwjUAAAAAAwLcQAALwOBUVFdq2bZskKYEGIPVGIxAAAAAA8E0EgAA8zs6dO1VeXi6JBiANQSMQAAAAAPBNBIAAPI59+a/EEuCGiE2NVVgUjUAAAAAAwNcQAALwOJs3b3YcEwDWn8lkcswCJAAEAAAAAN9BAAjA49hnAIZFhSksMszgajwLjUAAAAAAwPcQAALwOHQAbjwagQAAAACA7yEABOBxHAEgHYAbLKtLS8cxy4ABAAAAwDcQAALwKOXl5dqxY4ckOgA3RkxKDI1AAAAAAMDHEAAC8Cjbt29XZWWlJJYANwaNQAAAAADA9xAAAvAo1TsAJ7IEuFFoBAIAAAAAvoUAEIBHse//J7EEuLEyj+8DWFZWpnXr1hlcDQAAAADA1QgAAXgUewAYHheh4BYhBlfjmexLgCUpOzvbwEoAAAAAAM2BABCAR7EHgImZzP5rLBqBAAAAAIBvIQAE4FHsASANQBqPRiAAAAAA4FsIAAF4jJKSEu3cuVOSlEADkCbJ7FIVANIIBAAAAAC8HwEgAI+xbds22Ww2ScwAbCr7DEAagQAAAACA9yMABOAxNm/e7DimA3DTZHWhEQgAAAAA+AoCQAAew77/nyQl0ASkSaKTY9QiuoUkacWKFcYWAwAAAABwKQJAAB7DHgBGJUYpMCTI4Go8m8lkcuwDSCMQAAAAAPBuBIAAPAYdgJ2reiOQ0tJSg6sBAAAAALgKASAAj+EIAOkA7BT2RiDl5eU0AgEAAAAAL0YACMAjFBUVac+ePZJoAOIs1RuBsA8gAAAAAHgvAkAAHmHr1q2OY5YAO0dUYrTC4yIksQ8gAAAAAHgzAkAAHmHz5s2O48SsJAMr8R4mk0lZx5cBMwMQAAAAALwXASAAj2Df/89kMikuPc7garyHfR/A9evXq6SkxOBqAAAAAACuQAAIwCPYA8DolBgFBAUYXI33sHcCrqio0Nq1aw2uBgAAAADgCgSAADyCfQlwIvv/OZV9BqDEMmAAAAAA8FYEgAA8gr0JCA1AnCsqMUqR8ZGSCAABAAAAwFsRAAJwe0eOHNGBAwckMQPQFezLgLOzsw2uBAAAAADgCgSAANxe9Q7AzAB0vqwuLSVVNQIpKioyuBoAAAAAgLMRAAJwe/YGIBIBoCvYZwBWVlZqzZo1BlcDAAAAAHA2AkAAbi8nJ0eSZPGzKDY11uBqvA+NQAAAAADAuxEAAnB79hmAsWlx8vP3M7ga7xMRF6HopGhJ0sqVKw2uBgAAAADgbASAANyefQ9AGoC4jn0ZMAEgAAAAAHgfAkAAbs1mszkCQPb/cx37MuCNGzeqsLDQ4GoAAAAAAM5EAAjAreXl5amgoECSlJCVYHA13ss+A9BqtWr16tUGVwMAAAAAcCYCQABubePGjY7jxKwkAyvxbjQCAQAAAADvRQAIwK1t2rTJccwSYNcJjwlXzPEOy+wDCAAAAADehQAQgFuzB4B+gf6KTo42uBrvZp8FSAAIAAAAAN6FABCAW7MvAU7ISJDZzC3LlbKOB4CbNm3SsWPHDK4GAAAAAOAs/DYNwK3ZZwAmtmT5r6vZG4HYbDZlZ2cbXA0AAAAAwFkIAAG4LZvN5ggAEzIJAF0ts3Om45hlwAAAAADgPQgAAbitvXv3qrCwUJKUkJVgcDXeLyyqheLS4iQRAAIAAACANyEABOC2tmzZ4jhObJlkYCW+w74MeMWKFcYWAgAAAABwGgJAAG4rJyfHcZyQyQzA5pDVpaUkafPmzTpy5IjB1QAAAAAAnIEAEIDbss8ADAoNUkR8pLHF+Ijq+wCuWrXKuEIAAAAAAE5DAAjAbW3evFmSlJCVKJPJZHA1viGjU5bjmGXAAAAAAOAdCAABuK3qASCaR2hkqGO5NQEgAAAAAHgHAkAAbqmyslK5ubmSpMSWBIDNKaMzjUAAAAAAwJsQAAJwS7t27VJpaakkKZEZgM0q63gn4NzcXB0+fNjYYgAAAAAATUYACMAt2RuASFJiVpKBlfiezC6/7wOYnZ1tYCUAAAAAAGcgAATgluz7/0lSAkuAm1Vmp0zHMcuAAQAAAMDzEQACcEv2GYBhUWFqEdXC4Gp8S3CLEMe+iytXrjS4GgAAAABAUxEAAnBL9gAwqSXLf42Q2aWlJAJAAAAAAPAGBIAA3JJ9CXBiy2SDK/FN9kYg27Zt06FDhwyuBgAAAADQFASAANxOeXm5tm/fLklKasUMQCNkdqYRCAAAAAB4CwJAAG5n+/btqqyslCQlMQPQEOkdM2QymSTRCAQAAAAAPB0BIAC3U70DMDMAjREcFuz4uycABAAAAADPRgAIwO3YG4BIzAA0Eo1AAAAAAMA7EAACcDv2ADAiLkLBLYINrsZ3ZXbOlCTt3LlTBw8eNLYYAAAAAECjEQACcDu/dwBm+a+Rso7PAJSYBQgAAAAAnowAEIDb2bRpkyQCQKOld0yXyUwjEAAAAADwdASAANzKsWPHtGfPHklScmv2/zNSYEiQklunSJKys7MNrgYAAAAA0FgEgADcSvUOwIl0ADZcZpcsScwABAAAAABPRgAIwK3k5OQ4jpNYAmy4zE6ZkqTdu3crLy/P2GIAAAAAAI1CAAjArdgDQIu/RXHp8QZXg/SOGY7jVatWGVgJAAAAAKCxCAABuBV7AJiQkSCLn8XgapDeId1xvHr1agMrAQAAAAA0FgEgALfi6ADM/n9uIbhFiOIzqmZiMgMQAAAAADwTASAAt2G1WrVlyxZJUlIrOgC7i/SOmZKYAQgAAAAAnooAEIDb2L17t4qLiyUxA9Cd2PcBzMnJUVFRkcHVAAAAAAAaigAQgNuo0QGYGYBuI+N4AGi1WrV27VqDqwEAAAAANBQBIAC3Yd//T5KSWjID0F2kd/i9EzDLgAEAAADA8xAAAnAb9hmALWLCFRoZanA1sItMiFR4bLgkGoEAAAAAgCciAATgNjZv3ixJSmL/P7diMpkc+wASAAIAAACA5yEABOA27EuAE1n+63bsy4DXrVuniooKg6sBAAAAADQEASAAt1BYWKjdu3dLYgagO8romClJKikpqdGsBQAAAADg/vyMLgCewWKxuPR8IDc313Gc3CZFZrNZJpNJUtUSVLOZ9yuMlNkly3G8Zs0adezY0cBqnIP7FJzB/n3E9xNcge8rOAP3KbgK31OAZyEARL1ERUXV+1yLxdKg8wFJjtl/kpTZPlNBQUGOPwcGBhpREqrJaJehwNAglRaWaNOmTR7/b5z7FJwtPDzc6BLgZbhPwdm4T8GZuEcBnocAEPWSn59f5znh4eGyWCyqrKzUkSNHmqEqeJMVK1ZIkiz+FoUnRKikpEQmk0mBgYEqLS2VzWYztkAovX26Ni3fqGXLltXrnuCOuE/B2SwWi8LDw3XkyBFVVlYaXQ68APcpOBv3KTgT9yjnI0hFcyEARL009MUCLy7QUPYGIAkZCTKZTbJarY5lvzabTVar1cjyICmtQ1UAmJ2drYqKCscSbU/FfQrOVFlZyfcUnI7vKTgT9yk4G99PgGdhUy0AbsHRAZgGIG4ro2NVJ+DDhw9r165dBlcDAAAAAKgvAkAAhrNardqyZYskKbElAaC7sncClqRVq1YZVwgAAAAAoEEIAAEYbs+ePSoqKpIkJbVONrga1Ca5bYrMlqofG2vWrDG4GgAAAABAfREAAjCcffmvJCUxA9BtBQQFOGZoEgACAAAAgOcgAARguJycHMcxewC6t9R2aZKkdevWGVwJAAAAAKC+CAABGM4eALaICVdYZJjB1eBU0tpXBYBbtmxxLNsGAAAAALg3AkAAhrMHgEktEw2uBHVJa5cuSbLZbNq4caPB1QAAAAAA6oMAEIDh7AEgy3/dn30JsMQ+gAAAAADgKQgAARiqsLBQu3btkiRHgwm4r5iUGAW3CJYkrV271uBqAAAAAAD1QQAIwFDVG4Akt0kxsBLUh8lkUhqNQAAAAADAoxAAAjDUhg0bHMfJrQkAPYF9GfDatWtls9kMrgYAAAAAUBcCQACGsjeSCAgKUGxqrMHVoD5SjzcCycvL0/79+w2uBgAAAABQFwJAAIayB4CJrZJktnBL8gRp7X9vBMI+gAAAAADg/vhtG4Ch7EuA2f/Pc6Seluo4JgAEAAAAAPdHAAjAMKWlpcrNzZVEAOhJgluEKDYtThIBIAAAAAB4AgJAAIbZvHmzrFarJCm5dbLB1aAh7LMACQABAAAAwP0RAAIwTI0OwMwA9Chp7asagWzcuFHl5eUGVwMAAAAAOBUCQACG2bRpkyTJ4m9RfEa8wdWgIdLaVTUCKSsr05YtWwyuBgAAAABwKgSAAAxjnwGYkJkoP38/g6tBQ6S2oxMwAAAAAHgKAkAAhtm4caMklv96ooSsRPkF+ksiAAQAAAAAd0cACMAQFRUV2rx5syQpuQ0NQDyNxc+ilOPBLQEgAAAAALg3AkAAhsjNzXU0j2AGoGeyLwMmAAQAAAAA90YACMAQ1TsApxAAeqTU01IlSTt37tSxY8cMrgYAAAAAUBsCQACGsO//ZzKblJCVaHA1aIyUtqmOY/v/TwAAAACA+yEABGAIe2AUnx6vgKAAg6tBY1Rful19RicAAAAAwL0QAAIwhD0wYv8/zxWdHK3AkEBJzAAEAAAAAHdGAAig2VmtVuXk5EiSklrTAdhTmc1mR4C7fv16g6sBAAAAANSGABBAs9uxY4eKi4sl0QDE09kDQGYAAgAAAID7IgAE0Oyq7xeX1IYZgJ7MHuBu375dhYWFBlcDAAAAADgZAkAAzW7Tpk2O46RWBICeLLnt7zM4q/9/BQAAAAC4DwJAAM3Ovl9cdHKMgsOCDa4GTZFCJ2AAAAAAcHsEgACanT0ATG2XanAlaKqY1FgFBAVIIgAEAAAAAHdFAAigWVmtVkdQlNo2zeBq0FRms9nRyZkAEAAAAADcEwEggGa1bdu23zsAn8YMQG+Q0rbq/yOdgAEAAADAPREAAmhW9uW/kpRKAOgVko93ct62bZuKiooMrgYAAAAA8EcEgACa1bp16yRJJrPJsXQUns3eCMRms9EJGAAAAADcEAEggGZlnwGYkJngaB4Bz5bc9vdOwCwDBgAAAAD3QwAIoFnZA8CU02gA4i3i0uLlH+gviUYgAAAAAOCOCAABNJuysjLHEtHUtuz/5y3MFjoBAwAAAIA7IwAE0Gy2bNmiiooKSXQA9jbJx/cBJAAEAAAAAPdDAAig2dgbgEh0APY2Kcf3Ady2bZuKi4sNrgYAAAAAUB0BIIBmY9//zy/AT/GZCQZXA2eyzwC0Wq3avHmzwdUAAAAAAKojAATQbOwBYFKrZPn5+xlcDZwppc3vnYBZBgwAAAAA7oUAEECzsS8BZv8/7xOXHi+/gKpQd+PGjQZXAwAAAACojgAQQLMoKipSbm6uJDoAeyOLn0XxGVXLunNycgyuBgAAAABQHQEggGaxadMm2Ww2ScwA9FZJrZIkiT0AAQAAAMDNEAACaBZ0APZ+iS2rAsAtW7bIarUaXA0AAAAAwI4AEECzsDcACQwJVExqrMHVwBUSj88ALC4u1q5duwyuBgAAAABgRwAIoFk4GoC0TZXZzK3HGyW1SnYcsw8gAAAAALgPfgsH0CzsMwDZ/897JR1fAiwRAAIAAACAOyEABOByBQUF2r17tyQppW2KwdXAVUIjQ9UiJlxSVdMXAAAAAIB7IAAE4HJr1qxxHKe3TzewErhaUstESXQCBgAAAAB3QgAIwOWqB4CpBIBezd4IhCXAAAAAAOA+CAABuNzatWslSZHxkQo/vkQU3sneCGT37t0qLCw0uBoAAAAAgEQACKAZ2GcAprZPM7gSuFpitUYgLAMGAAAAAPdAAAjApSorKx0dgNPbZxhcDVwtqRUBIAAAAAC4GwJAAC61detWFRcXS5LSOrD/n7eLTYuTxc8iiU7AAAAAAOAuCAABuNTq1asdx2ksAfZ6fv5+isuIl0QjEAAAAABwFwSAAFzKvv+fX4Bfjf3h4L3sjUAIAAEAAADAPRAAAnApewfglLYp8vP3M7gaNIek40Hv5s2bZbPZDK4GAAAAAEAACMClHB2A27H/n69IPN4IpKioSHv27DG4GgAAAAAAASAAlzl8+LB27dolSUqnAYjPSKq21JtlwAAAAABgPAJAAC5jn/0nSWntaADiK+wzACU6AQMAAACAOyAABOAyNQLADhkGVoLm1CK6hcKiwiQxAxAAAAAA3AEBIACXsTcAiUyIUovoFgZXg+Zk7/hMAAgAAAAAxiMABOAy9hmAae1Z/utrklr93gkYAAAAAGAsAkAALlFRUaH169dLktLa0wDE19hnAO7cuVMlJSUGVwMAAAAAvo0AEIBLbN261RH80AHY98RnJkiSbDabtm3bZnA1AAAAAODbCAABuMTq1asdx2ntCAB9TWJWouN4y5YtBlYCAAAAACAABOAS9gYgfgF+Sjy+Hxx8R3xGvON469atBlYCAAAAACAABOAS9gYgKW1TZPGzGFwNmltgSJAiE6IkMQMQAAAAAIxGAAjAJX7vAMzyX1+VkFW1DyAzAAEAAADAWASAAJwuPz9fu3fvliSltc8wuBoYJeF4IxBmAAIAAACAsQgAATidff8/SUprn2ZgJTBSQmZVI5Bdu3Y5OkIDAAAAAJofASAAp6vRAZglwD4r/vgMQJvNpm3bthlcDQAAAAD4LgJAAE63atUqSVJ0UrRaRLcwuBoYJTEr0XHMMmAAAAAAMA4BIACns88ATO/I/n++LD4j3nFMIxAAAAAAMA4BIACnKikp0YYNGyRJGR0zjS0GhgoMCVJkQpQkZgACAAAAgJEIAAE41fr161VRUSFJyuicaWwxMFxCVtU+gMwABAAAAADj+BldAADvYt//T5IyWALs8xIyE7Rh6XpmAAIAAADwOX//+98lSZmZmZo4caKhtRAAAnAqewAYGhmm6OQYg6uB0RIyqxqB7Nq1SyUlJQoKCjK4IgAAAABoHo8++qgkadCgQYYHgCwBBuBU9gAwo2OGTCaTwdXAaPGZVUuAbTabtm3bZnA1AAAAAOCbCAABOE1lZaXWrFkjScrolGlsMXALiVmJjmOWAQMAAACAMQgAAThNTk6OiouLJUkZndj/D1J8RrzjmEYgAAAAAGAMAkAATlO9AUh6x0zjCoHbCAwJUmRClCRmAAIAAADeoKSkRNOmTdOtt96qvn37Ki4uTv7+/mrRooXatGmjK664Qt999129xiovL9fLL7+sfv36KTo6WiEhIWrbtq1uvvlmbdiwQVJVIw2TySSTyaR58+bVWdtrr72m8847T2lpaQoKClJERIQ6deqkW2+9VRs3bjzl8092rV9++UVXXXWVWrZsqaCgIMXExGjIkCGaMmWKrFbrScexj2E3f/58x+eqf0yZMqVef0/OQBMQAE5jDwADggNrLP2Eb0vIStDhffkEgAAAAIAX6NChw0lX9xw7dkw5OTnKycnR1KlTdf7552vq1KkKCws76Th79+7VOeeco5UrV9b4/KZNm7Rp0ya9/fbbevvtt+td1/z583X55Zdr165dNT5fWlqqNWvWaM2aNXrllVf0+OOP67777qvXmP/4xz/0wAMPqLKyssZ48+bN07x58zRt2jR98skn8vNz/3jN/SsE4DGys7MlSekd0mW2MMEYVRIyE7Rh6XqWAAMAAABeoKioSJGRkTrrrLPUvXt3ZWRkKCQkREeOHFF2drY++ugj7dmzR9OmTdPVV1+tjz/++IQxSkpKNHz4cK1evVqSFBsbq2uuuUZdunRRWVmZFi5cqHfffVcTJkzQOeecU2dNs2bN0vnnn6/y8nKZzWadc845GjZsmFJSUlRSUqLly5frnXfeUUFBge6//35JqjMEfOONN/T+++8rLi5OEydOVJcuXWQ2m7V48WL997//VWlpqb788ks9++yzjjHtvvjiC0nSn/70J0lSx44d9cQTT5xwjdNPP73Or81ZTDabzdZsV4PHOnjwYJ3nREVFyWKxqLKyUvn5+c1QFdyJzWZTmzZtVFBQoKFXDtcVj1/Z5DHNZrOCgoJUUlJS69RquL8Zr3ylT575SCaTSdu3b1dQUJBhtXCfgrNZLBZFRUUpPz+/xjvDQGNxn4KzcZ+CM3GPcr7Y2FijS2iwWbNmadiwYfL39z/p40VFRbr88sv15ZdfSpIWLlyo/v371zjnkUce0WOPPSZJ6tSpk3744QfFx8fXOGf58uUaNmyYCgoKHJ+bO3euBg8eXOO8PXv2qFOnTjp06JDi4+M1bdo09e7d+4S6du3apXPOOUerV6+WxWLR6tWr1a5duxrn/P3vf9ejjz7q+POgQYM0bdo0RURE1Dhv/vz5Gjp0qCorKxUbG6tdu3YpICDghGvalwEPGjSozuXLrsYUHQBOsWPHDseNOb0jDUDwu/jMBElVIfG2bdsMrgYAAABAU4wcObLW8E+SQkJC9L///U+hoaGSpP/97381Hi8rK9Mrr7wiSfLz89NHH310QvgnST169NDzzz9fZz3PPfecDh06JEn69NNPTxr+SVJKSoo++eQTR4j94osvnnLc6OhoffbZZyeEf1JVoHfhhRdKqpowtWzZsjrrNBoBIACnqN4AJIMAENVU3w+SfQABAAAA7xceHq7OnTtLkpYuXVrjsR9//NGxyvDss89Whw4dah1nwoQJiomJqfVxm82md955R5LUp08fDRgw4JR1tWvXTr169ZIkzZ49+5Tn1nXt4cOHO47tS5ndGXsAAnAK+/5/Fn+LUtqmGlwN3Il9BqBEAAgAAAB4g/z8fL333nv65ptvtHr1auXl5amwsFAn22Vu586dNf5cfbbckCFDTnkdf39/9evXT9OnTz/p42vXrlVeXp6kqiXq9mXHp2KxWCRJW7duVUlJSa1bFPXp0+eU46Sm/v57rycsiScABOAU9hmAKW1T5R9Y+3Rw+J7A4EBFxkfq8P7DLAEGAAAAPNy0adN0zTXXOIK3uhw5cqTGn3fv3u04btWqVZ3Pb9myZa2P5ebmOo5nzpypmTNn1qsmu0OHDik5Ofmkj9W1P2NgYKDjuKSkpEHXNQIBIACnsAeALP/FycSlx+vw/sM1fkADAAAA8CxLlizRhRdeqIqKCklSly5dNGzYMLVu3VpRUVEKDAx0NL548MEHtWbNmhMaOhYWFjqOQ0JC6rymfS/Bkzl8+HAjvorflZWV1fqY2exdu+YRAAJosv3792vv3r2SpPSOmcYWA7cUnxGvTcs3EgACAAAAHuzhhx92hH///ve/deONN9Z67pNPPnnSz1cP9IqKiuq8ZvXA8I/CwsIcx3feeWe9mob4Ku+KMwEYonoDkMxOmcYVArcVl17V1WvHjh2qrKw0uBoAAAAADVVeXq558+ZJks4444xThn+San3zv/qS282bN9d53VPtI159H74dO3bUOZYvIwAE0GT2ANBkMimtQ7rB1cAd2QPAioqKGnt+AAAAAPAMBw8edMz+a9269SnPXbZsmaPT7x/17NnTcTx37txTjlNeXq5FixbV+ni3bt0UERHhGKu0tPSU4zU3+3LokzVHaW4EgACazB4AJmQlKCj05B2U4NviM+IdxywDBgAAADxP9aW7OTk5pzz3kUceqfWxfv36KSYmRpL07bffau3atbWe+84775yy2YjFYtHll18uqSqgfOGFF05ZV3OzL1E+1TLm5kIACKDJHA1AWP6LWthnAEoEgAAAAIAnCg8PV9u2bSVJv/zyiz799NMTzqmsrNQdd9yhWbNm1TpOYGCgbrrpJklVK4QuueQS7d+//4Tzli9frrvuuqvOuu6//35FRkZKqmo88q9//euExiPVFRYW6r///a8++OCDOsduqqysLEnS+vXrVVxc7PLrnQpNQAA0yZEjR7R161ZJUgYNQFCLiLgIBQQHqqy4lAAQAAAA8FC33367Y++/iy++WJdccokGDRqkqKgo5eTk6L333tO6devUqVMnBQYG6pdffjnpOPfdd58+//xzrV69WqtXr1bHjh11zTXXqGvXriorK9OCBQv07rvvymw2a8yYMZo+fbqkk3fmTUlJ0ccff6zRo0ertLRUd9xxh1555RX96U9/UocOHRQWFqajR49q69atWr58uebMmaOSkhI9/vjjrvuLOm7YsGHKzs5WYWGhRo8erQkTJiguLs6xNLhz585KSUlxeR0SASCAJlq9erXjOL1jhoGVwJ2ZTCbFp8dp54ad2rZtm9HlAAAAAGiESZMmafny5Xrrrbdks9n04Ycf6sMPP6xxTufOnTVt2jRdddVVtY4TFBSkb7/9Vuecc46ys7N18OBB/eMf/6hxTkhIiN5++21lZ2c7AsAWLVqcdLzhw4frxx9/1Pjx47VhwwZt2rRJzz77bK3Xt1gsSkxMrO+X3Wh33XWX3nvvPe3bt08//PCDfvjhhxqPv/3225o4caLL65BYAgygiap3AGYJME7FvgyYABAAAADwTCaTSW+++aY+++wzjRgxQjExMfL391diYqIGDRqkl19+WT///LNj6eupJCUlafny5Zo8ebL69OmjyMhIBQcHq3Xr1rrxxhv166+/6uKLL66xB2B0dHSt4/Xo0UNr167VJ598ovHjx6tNmzYKDw+XxWJRRESEOnXqpHHjxum1117Tzp07de211zrl7+RUkpOT9euvv+rOO+9Uly5d1KJFC8fsv+ZmsrlDK5JmUlBQoE8//VQ///yz8vLyFBgYqFatWuncc89V7969Gz1uRUWFvv76a82fP9/R3TIlJUWDBg3SqFGj5Od38omW//rXvzRnzpxTjp2enq6XX37Z6dduqNq691QXFRUli8WiyspK5efnO+W6cH8333yzPvroI0Unx+iFpS86dWyz2aygoCCVlJSccg8HeIYPHpuq2f/9RpGRkdq0aZMhNXCfgrNZLBZFRUUpPz9flZWVRpcDL8B9Cs7GfQrOxD3K+WJjY40uwe2dccYZ+vXXXxUZGalDhw4ZFqB5Op9ZArx9+3Y98MADKigokCQFBwersLBQK1as0IoVKzR69Ghdd911DR63uLhYDz30kDZu3ChJCggIkFTVEScnJ0eLFi3SY489pqCg2jujBgQEKCQk5KSPhYeHu/TaQFM5GoCw/Bd1sM8APHz4sA4fPuzYqBcAAAAATmbJkiX69ddfJUmDBw8m/GsCnwgAy8vL9cQTT6igoEAZGRm68847lZWVpdLSUk2bNk3vvfeevvrqK2VlZWnYsGENGvuVV17Rxo0bFRoaqltvvdUxk3Dp0qV66aWXtH79ev3nP//RHXfcUesY/fv31+23397gr8sZ1waaori4WBs2bJAkZXaue4o3fFt8RoLjeNu2bQSAAAAAgA/79ddf1aZNm1r39Vu7dq3GjRvn+PNf/vKX5irNK/nEHoCzZ8/W3r17FRgYqIcfftixFj0wMFAXX3yxRo4cKUmaOnWqKioq6j3u1q1btWDBAknSLbfcoj59+shkMslkMqlPnz66+eabJUnz5s1z+p5XRl4bsFu7dq1jKQn7/6EucelxjmM6AQMAAAC+7a233lJSUpL+/Oc/6x//+Ic++OADffLJJ5o8ebIuuugide3a1ZFnXHrppTr77LMNrtiz+cQMwHnz5kmSBg4cqLi4uBMeHzt2rGbNmqVDhw5p1apV6t69e73GnT9/vmw2m5KSktSnT58THu/bt6+SkpK0Z88ezZ8/XxMmTGjS1+Eu1wbssrOzHccEgKhLbGpVu3ubzUYACAAAAECFhYX64osv9MUXX9R6zuWXX64333yzGavyTl4fABYXFzs2mz/99NNPek5cXJxSU1O1Y8cOrVy5st4BoD386N69+0nXoZtMJnXv3l179uypEZQ4g5HXBuxWrlwpSYqIi1BUYpTB1cDd+Qf6KyopWod25zEzGQAAAPBx99xzj9LT0zV//nxt3rxZeXl5Onz4sEJDQ5WSkqJ+/fpp4sSJ6tu3r9GlegWvDwB37twpe6PjjIzamxRkZGRox44d2rFjR73Gtdls2rlzZ53jpqenS9Ipx83OztYNN9ygAwcOKCAgQElJSTrjjDM0atQoRUWdGKo489pAU9jD5YzOmcYWAo8Rlx5HAAgAAABA6enpuueee3TPPfcYXYpP8PoA8NChQ47j6OjoWs+zP1bfVubFxcUqKSmp97jFxcUqLi5WcHDwCeccPHhQFotFwcHBKioq0ubNm7V582bNmjVL99xzj7p27eqya9tNnTpV77//fq2Pjxs3Tpdddlmtj0uS2Wx2/PdkwSW8S2lpqdavXy9JatO9zSm/v5oqMDDQZWOjeSW3TNaGpeu1fft2Q+4TzXGfOnbsmIqKimQ2m2WxWBQREeG4LryPfRZ+RESE4w1HoCl4PQVn4z4FZ+IeBXgurw8A7UGZdOoQwf5YcXFxvcatfl59xrU/p3pI0qpVK7Vt21Y9e/ZUTEyMzGazioqK9PPPP2vKlCk6dOiQnnrqKb3wwgtKSUlx6rX/qLCwUPv376/18aKiIlksllofr85kMtX7XHiudevWqby8XJKU1bWVS9ux0+rdeyRkJkqStm/fLqvVKn9/f0PqcMZ9qrKyUj///LMWL16spUuXKjs7W7t379axY8dqnOfn56eEhASlpaWpU6dO6tKli3r27KkzzjjDsK8fzkfIC2fj9RScjfsUnIl7FOB5vD4AdGejR48+4XMhISEaPHiwOnTooNtvv13Hjh3TBx98oLvvvtultYSGhio+Pr7Wx0NCQhzdXmtjNpsdG/xbrVZnlwg3s3z5csdxVucsl72jbP+egneIz6i6z1itVm3ZskWtW7du1us74z61du1avfbaa/r000+1b9++Os+vqKjQrl27tGvXLi1dutTx+bCwMPXv319DhgzR6NGj1bZt20bVA2OZTCaZzWZZrVbuVXAKXk/B2bhPwZm4RzkfQSqai9cHgEFBQY7j0tJShYSEnPS80tJSSar3Msbq59mfe6pxGzK2JMXHx2vUqFH66KOPtHz5clmtVse7dq649vjx4zV+/PhaHz948GCdy6OjoqJksVhktVrrvZQanmvJkiWSpBbRLRQSHVrv2bMNYTabFRQUpNLSUl5geInIpN+XimRnZysmJqZZr9+U+9SKFSv09NNPa86cOSc8lpjYUi0zuygmJlmRkfEKCgqTbDZVVJbryJE8HS7Yr/37t2vnzvXKP1wVGh47dkzffPONvvnmG917771q3769zjvvPF1wwQWEgR7EYrEoKipKBQUFdb5RBtQHr6fgbNyn4Ezco5wvNjbW6BLgI7w+AKy+R96hQ4dqDQDtewXWdx+D4OBgBQcHq7i4uMY+g7WNaz+/Iey/ABYVFeno0aOKiIhotmsDdXE0AOmUyRJd1Ftc+u8zjT2lEciBAwf0yCOP6JNPPnF8zmy2qHvXoTrzzNHq3GmgWoTVfw+cI0fytGHjz1q7bonWrV+snbs2SqpaVr9u3To999xz6tGjhy677DJdcMEFatGihdO/JgAAAAC+xesDwNTUVMcU5e3btys1NfWk523fvl2SlJaWVq9xTSaTUlNTtWnTJsdznTGuu18bkKTy8nKtXbtWkpRJB2A0QFhUmIJbBKv4aLFyc3ONLqdO06ZN0913363Dhw9Lkvz9AzV86JUaMfxqxcQkN2rM8PAY9ewxUj17jJQkHTy4U8t++UbLls/UppxfZLPZtHz5ci1fvlwPPvigxowZo2uvvfaEhlAAAAAAUF9evxNscHCw2rRpI0n69ddfT3rOwYMHtWPHDklq0C9YXbp0kST99ttvtZ6zYsWKGuc2xMaNVbNCgoODT5gB4uprA6eyYcMGxxLzjE5ZBlcDT2IymRyzAN05ACwrK9Pdd9+ta6+91hH+9e3zJ73w7EJddumDjQ7/TiY2NlUjR1yrhx/4XC++8JMuGnuP4uMzJFXNAP/www81bNgwnX/++Zo1axbLtwAAANCsTCaTR33g5JwaAF522WVasGCBM4d0isGDB0uSFixYoAMHDpzw+Oeffy6bzabo6Gh17ty53uMOHDhQJpNJu3fvduyHVt3ixYu1e/dumUwmRw12dW3Ae+DAAc2cOVOS1KNHjxO6djXl2kBT2Zf/SlVLgIGGcPcA8PDhw7r44ov1v//9T5IUER6nv975jm684UVFRSW69NrRUYk6f/TN+r9n5uv+ez9Svz5/kp9fgKSq+/qECRPUu3dvTZky5ZR7wAIAAABAdU5dAvzhhx/qo48+Utu2bXXDDTdowoQJNfbgM8qIESM0ffp07d27V48//rjuuOMOZWVlqbS0VF999ZVmzJghqaoRhp9fzb+Sa6+9Vvv379dZZ52l22+/vcZjWVlZGjhwoObPn6/JkyfLZDLpzDPPlCT99NNPevnllyVVBZDp6ek1njtv3jwtXbpUQ4YMUYcOHRQeHi5JKi4u1s8//6z//e9/Onr0qIKDgzVu3LgTvqamXBtoqpUrV0qSQsJDFJceZ3A18DTxxwPAbdu2yWazudW7dDt27NCll17qmIHdoX1f3TRpsiIimvf73Gw2q0P7PurQvo8uu/RBfT/nXf0w510dOZqn3Nxc/fWvf9U///lP3XbbbbrssstqNLwCAAAAXOHpqyeqfYZ75gvrtm3XfW9NMboMt+b0PQBtNps2btyou+66S/fff78uvPBCXX/99erfv7+zL1Vv/v7+evDBB/XAAw8oNzdXt912m0JCQlRSUuLoLHreeedp2LBhDR77xhtv1J49e7Rx40Y99dRTCgiomqlRVlYmSWrXrp3+8pe/nPA8q9WqJUuWOGbvBQcHy8/PT4WFhY6aIiIi9Ne//rXWfQsbe22gqVatWiWJBiBoHPsMwGPHjikvL89tOp9t375dY8aM0a5duyRJA/pdqGuuesYxA88oERFxGvunOzV61I1asnSaZsx6Tbv35Gj37t2699579a9//Uu33nqrJkyY4Pg5AAAAADhb+4x09TqtrdFloJGcugR43rx5uvTSSxUQECCbzaaSkhK99957GjRokDp27KjJkyc79lJqbunp6Zo8ebLOP/98JSUlqby8XKGhoeratavuv/9+XX/99Y0aNzg4WM8884yuvvpqtWrVShaLRRaLRa1atdI111yjp5566qQzMzp37qzx48frjDPOUGJiokwmk4qKihQaGqoOHTpowoQJeuWVV065f19jrw00RUVFhVavXi1JyuzM/n9ouPgM9+sEvGfPHo0dO9YR/v3p/Nt0/bXPGx7+VRcQEKRBAy/RM09+p5v/8rJSkqv2t92zZ4/uu+8+DRgwQDNnzqxziwkAAAAAvsdkc8FvCnl5eZoyZYreeOMNxzIq+yyhoKAgXXzxxbr++uvVp08fZ18aLnLw4ME6z4mKipLFYlFlZaXy8/OboSoYYf369RowYIAkadLLN6n3GNf9OzabzQoKCqoxWxeeb3/uPt0z8C5J0muvvaY///nPzXbtk92nDh48qDFjxmjTpk2SpLF/ulN/Ov/2ZqupsaxWq35ePkNffPkv7dq9yfH5Pn366LHHHlO3bt2MK86HWCwWRUVFKT8/nwYtcApeT8HZuE/BmbhHOZ+7rIY5FXue8+WjD7vtDMCfN2zUBY88Jqnungu+yiVdgGNiYnTXXXdp/fr1mjt3ri655BLHrMDi4mK988476t+/v7p06aJXXnlFR44ccUUZAFygegOQTBqAoBGiU2JktlT9+Nm6dauhtZSVlWnixImO8O+8cyfpgjG3GVpTfZnNZvXuNVpPP/Gtrpn4jCLCq/YpXLJkiYYPH6477rjDsFn3AAAAANyLSwLA6gYNGqQPPvhAO3fu1LPPPqu2bdvKZrPJZrNpzZo1uuWWW5ScnKxrr71WP//8s6vLAdBE9gYgQWFBis9MMLgaeCI/fz/FJMdIMnYJsM1m07333quffvpJkjRk8GW65KL7PG5fS7PZoiGDL9P//WO+zh99qwICqrZ+mDp1qvr27asvvviCd0EBAAAAH+fyANAuJiZGd999t9avX68ffvhBl1xyifz9/WWz2VRUVKS3335bffr0Uffu3fXGG2+ouLi4uUoD0AD2GYAZHTNlNjfbLQRext4IJDc317Aa3nzzTU2dOlWS1L5dH105/nGPC/+qCw4O00Vj79ZzT89TzzNGSpIOHDig66+/Xpdddpn27t1rcIUAAAAAjGLIb+9DhgzRM888o4kTJ0r6fT25zWZTdna2Jk2apPT0dP3zn/9k3y/AjVitVkcH4MzOmcYWA49mDwCNmgG4dOlSPfjgg1W1xKXp1pv+Iz8/f0NqcbaYmGTddstruv2WNxQVlShJ+v777zV48GDNnj3b4OoAAAAAGKFZA0Cr1aovv/xSI0eOVKtWrfTGG29Iqgr+wsLCNHz4cMeswLy8PN19990666yzmA0IuIktW7aosLBQkpTB/n9ogri0qv3q9uzZo9LS0ma99pEjR3TFFVeosrJSgQHBuvPWN9WiRXSz1tAcepwxQv946gedNfhySVUNusaPH6977rlHRUVFBlcHAAAAoDk1SwC4bds2Pfjgg0pLS9PYsWP17bffymq1ymazqXPnznrllVe0a9cuzZ49Wzt27NCTTz6puLg42Ww2LVy4UC+88EJzlAmgDtUbgGR0yjKwEni62PSqANBms2nXrl3Neu2bbrrJ0Xxk/GWPKC2tXbNevzmFBLfQ1ROf1h23/dcRcr799tsaNWqUduzYYXB1AAAAgPFKS0v11ltvaezYscrKylJYWJiCg4OVmpqqUaNG6eWXX9ahQ4dqPGfixIkymUwnfISGhqpVq1a6/PLLNX/+fIO+opNzWQBYWVmpL774Quecc45atWqlp59+Wnv27JHNZpO/v78uu+wyLVy4UCtXrtSkSZMUFhYmSYqLi9N9992ndevWqWPHjrLZbPrggw9cVSaABrA3AAkIDlRSqySDq4Ens88AlKTt27c323Xff/99x75/Pc8YqcGDxjXbtY10Rvez9dTjs9W500BJ0urVqzV8+HAtWrTI4MoAAAAA43z33Xdq06aNrrnmGn3++efKzc2V1WpVYGCgdu3apZkzZ+qWW25RZmam3nzzzROe7+/vr4SEBMdHWVmZtmzZovfff1+DBw/W3/72NwO+qpNzegCYm5urBx54QOnp6brwwgv13XffOWb7ZWZm6umnn9bOnTs1depU9evXr9ZxoqOjddttt0mSY6YGAGPZZwCmd0iX2UIDEDSeEQHg/v37HT9XoqOTdM1V//Doph8NFRWZoL/e+Y7OH32rpKolwWPHjj3pCxkAAADA233wwQc699xztWPHDrVq1Upvvvmm9u7dq6KiIh0+fFiFhYWaOXOmLrroIh07dkxfffXVCWP07dtXe/fudXyUlJRo+fLlGjBggCTpH//4h9vsw+3nzMFGjBihH374QTabTTabTZJkNpt17rnn6sYbb9Q555zToF+2UlNTJUklJSXOLBNAI9ib9EhSBg1A0EQtYsIVEByosuLSZmsE8sADDyg/P1+SdNOkFxUWFtks13UnZrNZF429Wxnp7fXaG3eqtKxYf/vb37Rz5049/PDDPhWIAgAAwHetWbNG11xzjSoqKjRixAh99tlnCg0NrXFOSEiIRo4cqZEjR2rJkiX1Wp1qsVh0xhlnaNq0aWrbtq0OHjyoKVOmaMSIEa76UurNqVN4qs/2i4+P13333afNmzfrq6++0siRIxv8i0VISIjS09OVkZHhzDIBNEJubq6OHDkiScrszP5/aBqTyeSYBdgcMwC//fZbffnll5KkwQMvUbeuQ1x+TXfWq+coPfLQl4qNqXqj7eWXX9Ytt9yi8vJygysDAAAAXO/BBx9UcXGxkpOT9eGHH54Q/v1Rnz599K9//ave40dFRalXr16SqsJGd+D0NXwDBgzQ+++/72jm0ZTwbuDAgcrNzdWWLVucWCGAxqjeACSTDsBwgthmCgCPHTume+65R5IU3iJGEyc85tLreYr0tPZ65MHPlZp6miTpo48+0tVXX62ysjKDKwMAAABcZ/fu3Zo2bZok6dZbb1VkZGS9nmc2NyxCs6+MtVqtDXqeqzg1AFy1apXmz5+vSy+9VP7+/s4cGoDB7A1A/AP9ldwmxeBq4A1i02IluT4AfP755x2dhq+68gmFh8e49HqeJCoqUQ/d94natu0pSfrmm290zTXXEAICAADAa82bN88Rzo0ZM8Yl1zh06JB+/vlnSVLLli1dco2GcmoA2LFjR2cOB8CNrFq1SpKU1j5dFj+LwdXAG9iXAB88eFDHjh1zyTW2bNmi1157TZLUsUM/Deg/1iXX8WShoZG6966p6tC+r6SqEPDaa68lBAQAAIBXWrt2rSQpMDBQ7dq1c+rYlZWV+uWXX3TBBRcoLy9PkjRhwgSnXqOxnBoAms1m+fn5afr06Q163uzZs2WxWOTn59SeJACcpEYDEJb/wkmqdwLesWOHS67x97//XeXl5TKbLRp/2d9pclGLwMBg3XX7244QcNasWbrtttvcZrkCAAAA4Cz2YC4qKqrJvx8sXrxYiYmJjo+goCD16NFDCxculCTdcMMNGjvWPSYhOH0PQPs0ysY8r7HPBeBaO3fu1KFDhyRJmXQAhpPEpsU7jl2xDHj+/PmaNWuWJGnokPFKO77XHU4uMDBYd97+ltqd1luS9Omnn+qxx9gvEQAAAKhNeXm59u3b5/ioqKiQVNUN+N1339Wrr77qNpMQnB4AAvA+1RuAMAMQzlJ9BuC2bducOnZlZaUeeughSVJoaIT+/Kc7nTq+twoKDNGdt/1X6WntJUn//ve/9Z///MfgqgAAAADniYmp2hM8Pz+/yRPRBg0a5JjQVlZWpvXr1+umm25SZWWlbrvtthq/SxvNLQLAoqIiSVJQUJDBlQA4GXsDEIu/RamnpRlcDbxFSHiIQiNCJTl/CfDHH3+sdevWSZL+fMEdahEW5dTxvVlISLj+euf/FBuTKkl6+OGH9c033xhcFQAAAOAcHTp0kCSVlpZq/fr1ThvX399fp512ml5++WXdeuutOnTokC688EJH5mU0twgAly5dKkmKj4+v40wARrC/a5F6Wpr8AtirE84Te3wWoDOXAJeWluq5556TJMXFpWnokPFOG9tXREUl6p6731VoaIQkadKkSU59cQQAAAAYZfDgwY5luQ3tYVFfTz31lOLj47Vp0yY9//zzLrlGQzX6N/ns7GytWLHipI/NmTNHhw8fPuXzbTabCgsL9euvv2rq1KkymUzq2bNnY8sB4CI0AIErxaXFadvqXKcuAX7nnXccMwrH/uku+fkFOG1sX5Kc1Eq33PiKnn1+ggoLC3XFFVdo9uzZio6ONro0AAAAoNGSk5M1ZswYTZs2TZMnT9YNN9ygyMjIOp9ntVplNtdvHl1oaKjuvvtu3XPPPXruued00003Gf46utEB4BdffHHSzcFtNpsmT57coLFsNptMJpMmTZrU2HIAuMjevXt14MABSVJm5yyDq4G3iU3/fQag/WdBUxw7dkz//Oc/JUmpqaepb+/zm1yjL+vUcYAuu/RBTX3/UeXm5mrSpEn68MMP6/3CBwAAAHBHTzzxhGbPnq1du3bp0ksv1eeff66QkJBaz1+yZIk++OADvfTSS/W+xqRJk/TUU0/p8OHD+uc//6nHH3/cGaU3WpNewds3OvxjB98/fr6uj4SEBL3xxhs666yzmvwFAXCu6puW0gEYzmZvBHL06NE6Z47XxxtvvOEIrC8a+1eZzZYmj+nrRgy/WgMHXCxJmjt3boNe9AAAAADuqFOnTnrjjTdksVg0e/Zsde3aVW+//bb279/vOKeoqEjffPONLrnkEvXr16/B2xa1aNFCN998syTppZdeUn5+vlO/hoZq9AzACy64QJmZmTU+d9VVV8lkMunmm2/W6aeffsrnm81mhYWFKSsrS507d5bFwi9pgDuyNwAxW8xKbUcDEDhXXNrve79u375dUVGNb9Zx7NgxR8fa1q1O1+ndhje5Pkgmk0kTr3hCW7dma8fO9XrmmWd05plnqk+fPkaXBgAAADTa+PHjFRsbq2uvvVY5OTm6+uqrJUkhISHy9/dXQUGB49zIyEj9+c9/bvA1brvtNr3wwgs6cuSI/vWvf+nRRx91Wv0N1egAsGvXruratWuNz1111VWSpKFDh2rMmDFNqwyAW7DPAExpm6qAIPZSg3PFpsY6jrdt23bCz5WGePvttx3vqv35gjuavJwYvwsICNItN76ihx49T6WlRbrhhhs0d+5cxcTEGF1ag1RUVOjQoUM6dOiQ8vLyVFhYKJvNJqvVKqlqr5bIyEhFRkYqNjb2lMtAAAAA4PnOOeccbd68We+++65mzJihX3/9VQcOHFBJSYlSU1PVtWtXnXfeeRo3bpwiIiIaPL49YHzppZf04osv6o477qjXfoOu4NR2nm+//bYk1Tn7D4Dn+L0BSIbBlcAb2bsAS03rBFxUVOSY/ZeV1UWdOw1scm2oKTm5ta6a8KRefeMO7dmzR3/961/15ptvumXQWllZqY0bN2r58uVat26dNm/erC1btmj79u2OsK8+EhMTlZWVpVatWqlz587q2bOn2rdvLz8/uqEDAAB4i8DAQF177bW69tpr6/2cKVOmaMqUKfU698UXX9SLL77YyOqcx6mvYK+88kpnDgfAYPv379eePXsk0QAErhEQFKCIuAgVHChoUgD4zjvvOPb+u2DMrW4ZSnmD/v3GatXqBVq05At99dVX+vzzzzV27Fijy5LNZtO6dev0/fffa/78+frll19UWFjY5HH37t2rvXv3asmSJY7PhYSEqGfPnho2bJhGjBih1q1bN/k6AAAAgKvxFjaAWlVvAJLRKdO4QuDV4tLjVXCgQNu2bWvU80tKSvTyyy9LktLTOrD3n4tNGP+Y1q5fovz8vbr33nvVt29fJSUlNXsdNptNy5cv1yeffKLZs2dr9+7dJz0vIjRUrZOTlJWYoKzEBMVHRioqrIWiW4QpLDhIZrNZJlUFxoUlJSooLFRBYaH25udr69592rp3nzbv2aN9+YclVc02nT9/vubPn6+HHnpInTp10lVXXaVzzz1XsbGxJ60BAAAAMBoBIIBa2QNAk9mk9A7pBlcDbxWbFqecXzY1egbgxx9/rH379kmSzh99M7P/XCw0NELXX/N/+sf/jVdBQYFuu+02ffTRR832975r1y699957+uSTT5Sbm3vC4+3T09S7XTud3rqVurdupbS4WKfUtjsvT79s2qzlGzdp4eo1yjkeOK5evVp33XWX7rnnHo0aNUqTJk1Sz549m3w9AAAAwJkaFQC2bNlSUlVnwM2bN5/w+cb643gAjLVq1SpJUlLLJAWGBBlcDbxV3PF9AHfu3CmbzdagsMZqtTr2/ktMyFLPHiNdUiNq6txpoIYPvVLf/fA/zZ07V59++qkuuugil13PZrNp2bJlev311/X111+rsrLS8ViAn58Gd+2sod26aUjXLkqMbnwn6VNJjolRckyMRvfuJUnK3bdf3/7yiz5ftERrt21XZWWlpk+frunTp6tHjx665557NHjwYAJpAAAAuIVGBYD2d9z/+KI2NzdXJpNJNputUcXwIhlwL6tXr5YkpXekAQhcx94IpKSkRPv27VNiYmK9n/vdd98pJydHkjRyxLUymy0uqREnuuSiv+m3FT/oYN5OPfTQQzrrrLOc3hXYZrNp7ty5evbZZ/XLL7/UeKzXaW315/59dW6vnooMDXXqdesjMyFe1587UpPOG6WcPXv15sxv9MnCH1VSVqbly5fr4osvVu/evfXQQw+pV69ezV4fAAAAUF2jAsD09PSThnW1fR6A5zly5Igj7CcAhCvF/aETcEMCwFdeeUWS1KJFtPr3u9DptaF2QUGhmjjhCf3fPycqLy9PDz/8sP797387ZWybzaaFCxfqmWee0bJlyxyfDw4M0Nj+/TTx7GFqm5LilGs5Q6esTD19zUTdfeGfNXXOHL0+c7YKCgu1dOlSjRo1SpdccokefvhhxcfHG10qAAAAfFSTZgDW9/MAPI999p8kZXTMNK4QeL0/BoD1nS21YsUKLV68WJI07KwJCgwMdkl9qF23rmep95ljtPSn6fr444910UUXafDgwU0ac/Pmzbr//vs1Z84cx+ciw0J1/bkjNf6swYoMC2ti1a4T1SJMt5w/RlcOH6Y3v/lWr8/8RoUlJfroo480c+ZMPfbYY7r88st5sxQAAADNzmx0AQDcU/UAkBmAcKXo5BiZLVU/jhrSCdg++8/fL1DDhk5wSW2o2xWXPaLQ0AhJ0n333aeysrJGjXPs2DE99thjGjBggCP8Cw8J0d0X/lmLXvg/3TzmPLcO/6oLDwnRHX++QHOfe1oX9O0tSTp69KjuuOMOXXbZZdq7d6/BFQIAAMDXEAACOCl7A5DopGi1iG5hcDXwZhY/i6KTq/aOq28n4B07dmj69OmSpP79xyoiPNZl9eHUIiLidPHYeyRJOTk5evPNNxs8xnfffae+fftq8uTJKi8vl8Vs1rXnjNCP/3xOt14wRi1CPHN2Z2JUlF66cZI+uv9epcdXzXT9/vvvNXDgQH3//fcGVwcAAABfQgAI4KTsASCz/9Ac7MuA6xsAvv76645OsCPPvtZldaF+hgy+TOlpHSRJzz33nPbv31+v5xUUFOjWW2/VZZddpj179kiS+nXsoNlPP66Hx48zpLmHK/Tp0F6zn3pcVww9S5KUn5+vcePG6emnn67R0RgAAABwlUbtAdgUxcXFevXVV7Vw4UJVVFSoW7du+stf/qKkpKTmLgVALcrKyrRx40ZJBIBoHrGpVTP46hMAHjt2TO+9954kqXvXoUpObu3S2lA3s9miCeMf1RNPX6SjR4/qySef1IsvvnjK5yxcuFA33XSTI/iLCgvT41eO1+jeZ3rlHnmhQUF68qoJGtKti27/z+s6UlSkF154Qb/99pvefPNNtWjBTGsAAODe1m2r35v1RnDn2tyFUwPA3377TVdeeaVMJpNeffVV9enTp8bjR44c0YABA2rsLTZjxgz95z//0bfffqvu3bs7sxwAjbR+/XqVl5dLkjIIANEMYo/PANy1a5cqKirk51f7j6dPP/1UR48elSSNGHFNs9SHurU77Uz17jVaS3/+Su+//74mTpx40p/rlZWVeuGFF/Tcc8/JZrNJks7pcYaevGqC4iIimrvsZjesezfNfOJR/WXyv7Vqa67mzp2rUaNG6b333lNaWprR5QEAANTqvremGF0CmsCpS4A//fRTrV69Wvv371fv3r1PePyBBx7QqlWrZLPZanzk5eVp7NixKi0tdWY5ABqpRgOQDgSAcD37EuDKykrt2rWr1vNsNpveeustSVJyUmt1bN+vWepD/Yy75AEFBARJku6//35ZrdYaj+/fv18XX3yxnn32WdlsNoUFBemlG2/Qa7fd7BPhn116fJw+e+h+nd+n6rXSunXrNGLECMfWCwAAAICzOXUG4E8//SSTyaThw4efsHzn6NGjevPNN2UymZSWlqYXX3xRWVlZeuWVV/T6669r27Ztmjp1qq65htkcgNHsv4SGhIc4ZmYBrhSXFu843r59uzIyTh48L168WOvWrZMkDTvrCq9cKurJYmKSNXrUTfrsi+e1fPlyTZ8+XRdccIGkqlUCV1xxhfbt2ydJ6piRrv/ccpMyExMMrNg4QQEBeunGG5SZEK8Xv5yuAwcO6IILLtCHH36onj17Gl0eAACAw7fffmt0CXACpwaA9lkbJ1vyM2vWLJWUlMhkMunNN9/U0KFDJUmvvvqqli5dqlWrVunLL78kAATcgH0GYHrHDAIWNIvqQfOp9gG0z/4LCgpV//4XurwuNNyokTdozrz3lJ+/V0899ZRGjRqlmTNn6uabb1ZJSYkkafzQIXr48nEKCggwuFpjmUwm3XXhn5USG6O/vTlFR44c0YUXXqh3331XAwcONLo8AAAASdLw4cONLgFO4NQlwAcPHpSkkzb0mD9/vuMxe/hnd9FFF8lmsyk7O9uZ5QBoBKvV+nsAyPJfNJOI+Aj5BfpLqj0A3LNnj2bMmCFJ6tf3zwoJpmmCOwoICNLYC+6UJG3dulUTJ07Utddeq5KSEvlbLHr++mv01FVX+nz4V92lgwdp8k1/kZ/FoqKiIl1++eX68ccfjS4LAAAAXsSpAWBBQUHVoOYTh12yZIlMJtMJ4Z8kpaenS5IOHDjgzHIANEJubq6OHTsmiQYgaD5ms7nOTsDvvPOOKisrJUnDh05ottrQcAP6X6jkpKruzPYlI1FhYXr/vnt00cABRpbmtkb37qU3br9Fgf5+Kikp0eWXX66ff/7Z6LIAAADgJZwaAIaEhEg6McgrKChwzO7r27fvCc8LCqraMNz+ix0A49RoANIp07hC4HPsjUC2bdt2wmNlZWX63//+J0lq366PUlNOa9ba0FAmZaYPcfwpukULTXv0YZ3Zjv9vpzK0ezf959abHTMBL730Uq1cudLosgAAAOAFnBoAZmZmStIJy1a+/vprRyfAfv1O7NiYl5cnSYrwoQ6AgLuyNwDxC/RXUqsTl/MDrmIPAE82A3DGjBmON5eY/efeysrK9Pnnn+vY0UCFBFfdQ0rKytQiOMjgyjzDsO7dNPmmSTKbTDp69KjGjRt3yn0xAQAAgPpwagA4YMAA2Ww2TZ8+3fGO9ZEjR/Tss89KkpKTk9WpU6cTnmefcZSVleXMcgA0gv3fY2rbVPn5O7VPEHBK9kYg+/btU3FxcY3Hpk6dKkmKjIzX6d3PbvbaUD+lpaX65JNPlJubK5PJpO7tR0mSikpLNXnaVwZX5zlG9eqp566raop24MABjRs3TocPHza2KAAA4LNMJpNHfeDknBoAXnfddTKbzSopKVGvXr3Uu3dvtWrVSqtXr5bJZNJ111130ufNmTNHJpNJXbp0cWY5ABrBPgMwvWO6wZXA18SlxTuOd+7c6TjOzc3VggULJEkD+18sPz//Zq8NdSsrK9Nnn32m3bt3S5LapCTrqnMuUdc2vSVJ782Zq735+UaW6FEuGthfd479kyRp48aNuvLKK1VaWmpwVQAAAPBUTp3e06VLFz3yyCN65JFHVF5ermXLlslmszke++tf/3rCc1atWqX169fLZDKpf//+ziwHQAPt379f+/btkySld8w0thj4HHsTEKlqH8A2bdpIkt577z3H5wcNvLjZ60LdysvL9dlnn2nXrl2SpPZpaTq7x+kym0z686CJWrlpqUrLK/TKVzP02ITxBlfrOW67YIx27D+gTxb+qMWLF+v222/XK6+8wjvbAADAEBOfvlrp7d2zUeT2dds05b63jC7DrTl9fd9DDz2krl276o033lBOTo5CQ0N19tln629/+5uCg4NPOH/y5MmSJJvNphEjRji7HAANUL0BCB2A0dzi0uMcx/Y9zyoqKvTBBx9Ikjp26KeE+EwjSsMpVFRU6IsvvnDM2mybmqKzz6gK/yQpI6mNTj+tn37dsEgfzJ2nG88bpcToKCNL9hgmk0nPXDNRe/Lz9ePqNfr000/VsWNH3XzzzUaXBgAAfFB6+wy17UVTN0/l1CXAdmPGjNFXX32ldevWafny5XrqqacUHh5+0nNff/11Wa1WWa1WJSYmuqIcAPVkX/5rMpmU1p4lwGheoZFhCgqrahRhDwC///57x6zUwQPHGVYbTs5qtWr69OmOzs2tk5N1To8zZDbXnKF2wcArJUml5RX691dfN3udnszfz0+v3nqTWicnS5Ief/xxx5J4AAAAoL5cEgAC8Ez2GYAJWQkKCqVjJ5qXyWRy7ANoD5TeffddSVJYWJR6nMEscXfz3XffafPmzZKkrMREndurhyzmE19apCe20hntBkiSPpg7X7vz8pq1Tk8XHhKi12+/WWFBQbJarbruuuu0Y8cOo8sCAACAByEABOBgDwDZ/w9GsXcC3rFjh3bv3q3vv/9ektS/31j5+wcaWRr+YPHixcrOzpYkJcdE67wze540/LO7YOAVkqSyigq9PJ1ZgA3VOjlZL9xQ1Uzt0KFDuuqqq1RSUmJwVQAAAPAUBIAAJElFRUWOmTxp7dMMrga+Ku54ALh9+3Z98MEHslqtkqQhAy81siz8QXZ2thYtWiRJim7RQmN695afxXLK56QltFKP9gMlSR/NW8AswEY4p+cZumn0eZKklStX6v777ze4IgAAAHgKpzcBsVuxYoVmzZql1atXKz8/v17vUptMJv3www+uKgnAKWzYsMHRtZv9/2AUewCYn5+vqVOnSpLatD5DKSltjSwL1eTmbtN3330nSQoNCtKf+vVRcGBAvZ57/oArtHzdApVXVur1md/o71dc7spSvdLdF/1Z2Vu3auHqNXr33Xc1ePBgjRkzxuiyAAAA4OacHgDu2bNHV111leOXg/qy2WwymUx1nwjAJdasWeM4JgCEUexLgCU5usoOGXSZUeXgD/Lz8/XVV9NltVoV4OenC/r2UXhISL2fn5bQUt3b9tVvGxfr/bnzdcv5oxVTS5MwnJzFbNaLf7lBI+5/UAcKjujOO+/U6aefrtTUVKNLAwAAgBtz6hLgY8eOaciQIfruu+9ks9ka9AHAWGvXrpUkhYSHKDop2uBq4Kvi0uNq/Dk4uIV69RplUDWorrS0VF988YVKSkpkMpl0Ts8eio+MaPA45/WvCnRLysr01uyGvVmIKrER4frnpOslSQUFBZo0aZIqKioMrgoAAADuzKkB4D//+U9t3LhRkpSamqr//Oc/ysnJUUlJiaxWa50flZWVziwHQAPYA8C0DunMxoVhYlNrBoC9zxytoMD6zzCDa9hsNn399dfKO75vX98O7dUqKbFRY7VKaa/2md0lSf/77nsdKSpyWp2+ZGDnTrrh3HMkST/99JNeeOEFgysCAADwHBMnTpTJZKrXx8SJE40u1ymcugT4iy++kCQlJiZq2bJlSkhIcObwAFzEZrM5lgCntWP5L4wTFBqkwNAglRZW7Rs7sP9FBlcESVqwYKG2bNkiSWqXlqqebZu2J+Po/pdpXe5vOlJUrHe/n6ObxpznjDJ9zl8vvlCL163Xqq25ev755zVkyBD17NnT6LIAAAA8hr+/v6KjT70CLiKi4ate3JFTZwBu3rxZJpNJN954I+Ef4EH27Nmjw4cPS6IDMNzA8W0hwkLj1LrV6QYXg5yczfr5558kSQlRURp+enc1dZJw+8zuapncTpL05jffqqSsrKll+qQAPz+9fNMkhQQGymq16pZbblERMyoBAADqrW/fvtq7d+8pP1588UWjy3QKpwaAVqtVknTaaac5c1gALkYDELiLPZt3q7SoVJIUH9eZ5egGKygo0KxZMyVJQQEBOu/MXvKzWJo8rslkcuwFePDIEX00f0GTx/RVWYmJuv/SiyVVvRH79NNPG1wRAAAA3JFTA8CMjAxJ0tGjR505LAAXs+//ZzKZlNI2xeBq4MsWffaj4zg0pKWBlaCiokLTp093NP0Y2eMMhYcEO238bm37KCUuU5L06tezVE4Ti0YbP3SI+nXsIEl67bXXtGTJEoMrAgAA8F6rVq3SVVddpZYtWyooKEihoaHKysrS0KFD9Y9//MOxb/YfFRQU6KmnnlLv3r0VHR2toKAgtWzZUuedd57+97//qaSkxKV1OzUAHDNmjGw2mxYtWuTMYQG4mD0AjM9MUGBIkMHVwFdZrVYt/rzq50dYaKrMpmCWMxpo7tx52rt3rySp12ltlZno3K09zCazRvUbJ0nalZenLxcvder4vsRsNuu5665WWFCQbDabbr31VhUWFhpdFgAAgNf55ptv1KNHD02ZMkVbt26VVLWPYG5urubMmaO//e1v+u2330543k8//aTTTjtNDzzwgH766ScdPXpUoaGh2rFjh2bMmKGJEydq/fr1Lq3dqQHgLbfcoqioKL333nsuLxyA8zg6ALdj/z8YZ/2SdTq0u+rdsqjIqv3hDh8uMLIkn7Vx40atWFH1wiUtLk6927dzyXXO7DhEcZFJkqTXZs6S7fj+j2i41NhYPXR5VaCam5urxx9/3OCKAAAAvM9NN92ksrIynXvuuVq3bp1KSkp0+PBhHT16VD/99JNuvfVWhYeH13hObm6uRo4cqX379qldu3aaMWOGioqKlJeXp6KiIi1atEg33HCDAgICXFq7UwPApKQkffjhh/Lz89Pw4cO1YAF7+gDurrS0VJs2bZLE/n8w1qJPF0qS/AOCFNGilaSqafJoXseOHdPs2bMlSaFBgRrZs4fMLtqL0WK2aETvCyVJG3fu0rzsVS65jq+4dPBADercSZL01ltvafny5QZXBAAA4N4WL16sxMTEU34sXrxYkrR//35t2bJFkvTmm2+qXbvf3yQPCwtTr1699OKLL6pXr141rnHfffcpPz9fGRkZWrRokc4991z5+/tLqpo92LdvX7366qvq0KGDS79WP2cO9thjj0mShg0bpmnTpmnIkCHq1q2b+vTpo9jYWJnNdeeNDz/8sDNLAlCHDRs2qLKyUpKUSgdgGKSksETLZy2TJLU/fYDMxwJls9lUUHDY2MJ8jM1m08yZMx37j5x9+ukKDQp06TUHdB2hL+ZPUWHxUb02Y5aGdO3i0ut5M5PJpKevmaih996v4tIy3Xnnnfrhhx8cLzABAABQU3l5ufbt23fKc8rKyiRVhXxms1lWq1V79+5VYmJineMXFhbq008/lSQ98sgjio6ObnrRjeTUAPDvf/+7o2OjyWSSzWbTihUrtGLFinqPQQAINC/78l9JSmcGIAyyfObPju6/3fqdo02L96voSJEKWALcrH755Rdt27ZNktStVUun7/t3MoEBwTrrjPP11Y9TtXjtOmVvzVWXrEyXX9dbpcbG6q8XjtVj732gdevW6d///rduv/12o8sCAABwS4MGDdK8efPqdW5ISIgGDRqkuXPnasSIEbrppps0atQodevWTRaL5aTPWbZsmSqON7sbNWqUs8puFKcuAZaqZg/YP/7457o+ADQ/ewAYFBakmNRYg6uBr7J3/w2Pjlfmad0UEhEqSSo4QgDYXPbvP+DYuiMmvIUGdOrYbNce1vN8+VmqZqm9PmNWs13XW008e5g6Hw9Rn3/+ecdSFQAAADTNf//7X3Xo0EH79+/XI488oh49eig8PFwjRozQG2+8odLS0hrn22cXBgUFKT4+3oiSHZw6A3Du3LnOHA5AM7AHgKmnpdVrmT7gbAd3HtS6xVXfh116D5fJbFZoeIgOij0Am0tFRYVmzPhalZWVspjNOqdHD/nV8i6mK0SERatfl7M1/7cZmvHzMt174EKlxcU12/W9jZ/FomeunqjRDz+qkpIS/fWvf9Wnn37qWKUBAACAxmnZsqWys7M1c+ZMzZo1Sz/++KNWr16tb7/9Vt9++62effZZzZ8/X8nJyUaXegKnBoCDBg1y5nAAmoGjAzDLf2GQxV8schx37Xu2JDlmAB45ckRWq5Vw2sUWLlyogwcPSpL6duig+MiIZq9hRO8LNf+3Gaq0WvXmN9/q71dc3uw1eJPOWZm6duQIvT7zGy1YsEAff/yxLrnkEqPLAgAA8HgWi0WjR4/W6NGjJUkHDx7URx99pPvvv185OTm6/fbb9fHHH0uSY5/AkpIS7d+/39BZgPxGBfiw/fv368CBA5KkNBqAwAA2m02LP6vq/pvasoNiE6uC6JDwqgDQarXq6NGjhtXnC3bv3q1ffvlFkpQWF6cz2rQypI7k2HR1b9tXkvThvAU6XFhoSB3e5M4//0mpsTGSqvZYPnTokMEVAQAAeJ/Y2FjddNNNjp4W1fcU7NGjh6Mh24wZM4woz4EAEPBha9ascRyntWMGIJrf1uwt2rtlrySpS5+zHZ8PiQhxHB+mEYjLVFRU6JtvvpHNZpO/n5+Gn97d0GWiI/tcLEkqKi3V1B/YVqSpQoIC9eRVV0qSDh06pKeeesrgigAAADyXvRtwbYKDgyWpxj6AoaGhuvDCCyVJjz76qPLz811XYB1cHgDu3LlT3377rT788EO98847rr4cgAao3gE45bRUAyuBr1ryxWJJktliUceegx2fDz2+BFiSCgoON3NVvmPx4sXKy8uTJPXv2EERoSF1PMO12qR1UsuU9pKkt2d/p9LyckPr8QZDunbROT3OkCS98847WrFihbEFAQAAeKjFixerW7dumjx5sjZt2uRoZltRUaGZM2fqsccekySNHDmyxvOefPJJRUZGatu2berXr59mzZql8uOvc8vLy7Vw4UJdccUVNX4/dwWn7gFY3VtvvaXnn39e69evr/H5CRMm1Pjzk08+qfnz5ystLU1vvvmmq8oBcBL2G0xsWpxCwo39xR++p7KiUj99tVSS1LpjL4WE/b7vXGBIkCx+FlVWVNIIxEX27t2nZcuWSZJSYmPUtWWWwRVJJpNJI/tcrH9/+qgOFBToy8VLdMmggUaX5fEeHj9O87JXqaSsTPfee69mzZrFvpoAAACqCvXs+/TVplOnTvr+++8lSStXrtStt94qSQoICFBYWJgOHz4sq9UqSWrbtq1eeOGFGs/PysrS119/rQsuuEDr1q3TueeeK39/f4WHh+vIkSOOMPCuu+5y9pdXg9Nf/RUXF2vUqFG67rrrtH79etlsNsfHyfTo0UPff/+9pkyZonXr1jm7HACnYF8CnNaO/f/Q/NYtXqsjB6rCvc69h9V4zGT6vREIAaDzVVZW6ptvZslqtcrPYjF86W91Z5zWT/FRVV3TXpvxjePFFBovNTZWN485T5L066+/6r333jO4IgAAAPdQXl6uffv2nfLD3iyvZ8+e+uijj3T99dere/fuioqK0pEjRxQeHq4+ffro2Wef1W+//XbSDsD9+vXThg0b9PDDD6t79+4KCgpSYWGh0tLSNHr0aL3zzjtq3769S79Wp88AnDBhgmbNmiVJyszM1Lhx45Sfn69XX331pOcPHz5ccXFxOnjwoL7++muXf8EAqpSXl2vjxo2SpFQagMAAS76sWv7rHxiktl37nPB4aHiIjuYdIQB0gZ9++snRAKhvh/aKCgszuKLfmc0Wjeh9od6d9ZJydu/W3JXZGtq9m9Flebzrzz1Hny5cpNx9+/TEE0/ovPPOU1RUlNFlAQAAGGLKlCmaMmVKg54TGhqqiy++WBdffHGjrhkdHa1HH31Ujz76aKOe31ROnQH4ww8/6LPPPpPJZNK4ceO0YcMGPfnkkxoxYkTtBZjNGj58uGw2m3788UdnlgPgFHJychxTjdPbZxhcDXxNWUmZfvmmavlp++4DFBAYfMI5zAB0jby8Q1q6tGrpdVJ0lLq3Nqbr76n07zpCYcHhkqTXZswyuBrvEBQQoEcnXC6pqiHI008/bXBFAAAAaE5ODQDt6WnLli01ZcoUR6vjunTt2lWSWAIMNKPq/95oAILmtuL731RyrETSict/7eyNQAoLC+vsuIX6++67b1VZWSmL2axhp58us5ss/a0u0D9IQ3ucL0laun6DVm7ZanBF3mFI1y46+4zukqpes61cudLgigAAANBcnBoALlq0SCaTSRMmTKh3+CfJsT567969ziwHwCnYA0C/QH8lZCYYXA18zdJpVct/Q1pEqmX7M056TnC1xjRHjhxplrq83erVa7Rjxw5J0hltWis2vIXBFdVuaM/z5Wepei3x+kxmATrLI+MvU6C/v2w2m/72t7+xxyIAAICPcGoAuG/fPknSaaed1qDnBQUFSZJKSkqcWQ6AU9iwYYMkKalVkix+FoOrgS8pPFyo7LlVM4869hwis+Xk33/2GYASy4Cdobi4RPPnz5MkRYSGqlcDf1Y3t/DQKPXverYkacZPy7Tj+J6FaJq0uDjddLwhyPLly/XRRx8ZXBEAAACag1MDQMvxX+Ia+m7yoUOHJEmRkZHOLAfAKaxfv16SlNKW5b9oXstm/qyKsgpJUuczh9Z6Xki1APDw4cOuLsvrLVgwX0VFRZKqloL6e0DwP+LMi2SSSVabTW9+863R5XiNSaNGKj0+TpL0+OOPM8MWAADABzg1AExIqFpGmJOT06Dn/fLLL5KktDQ6kQLNoaioSLm5uZKkVAJANDP78t+ouGSltuxQ63n+AX4KCA6QxAzAptq5c5eys7MlSW1SkpWV6BnL/pNi09StbVWH6A/nLdDhwkKDK/IOQQEBevjyyyRJBw4c0PPPP29wRQAAAHA1pwaAffv2lc1m05dfflnv5xQWFuqTTz6RyWRS//79nVkOgFps2rRJNptNkpTSNsXgauBLDu3J04alVbNPO505VKY6GlCE0gm4yaxWq777rmr2XICfnwZ36WJwRQ0zss/FkqSi0lK998Ncg6vxHsNP76ZBnTtJkl5//XVt3LjR4IoAAADgSk4NAC+66CJJ0m+//aa33nqrXs/5y1/+ovz8fEnS5Zdf7sxyANTCvvxXklJOY+Ytms9P05c6wufOvWpf/msXEk4A2FS//PKrDh48KEnq06G9woKDDK6oYdqkdVLLlPaSpLdmf6fS8nKDK/IOJpNJj1xxmfwsFlVUVOiBBx5w/NsEAACA93FqAHjeeeepd+/estlsmjRpkp5++mkdO3bspOf+9ttvGjVqlN577z2ZTCaNHDlSvXr1cmY5AGphbwASEByo2LRYg6uBL1nyZdXy38T0NopLzqjz/JDjnYDZA7BxCgsLtXjxIkn/z959hzldZm0c//6STKb3Tu+9iIA0BVQEsWDvDcTeFcWGrmvddZd97b333rErvYOKgPQOwwzTe03y/hEygoq0zDxJ5v5cl9c7yyS/3PBOSU7OeQ6kxsdzSLt2hhPtP8uyGD3Q+wZjbnExn86ZZzhR6OjQrBnjRx0DwLRp0/j6668NJxIRERGRhuLXAiDAu+++S0ZGBnV1dUyaNIm0tDRuuOGG+s/379+fzMxM+vXrx9dff43H46Fly5a88sor/o4iInuwYsUKAJp3bIbN5vcfAyJ/advqbWxevgn4++Ufu/KNANfW1tYvsJB9N2PGDGpqagAY3rsXNtvfj1wHqr5dDic1MROAZ7/8Sp1qfnTdySeRGh8HwF133UVlZaXhRCIiIiLSEPz+yr9ly5bMnz+/vhOwqqqKzZs315/z9NNPP5GTk4PH48Hj8TBgwADmzJlDSoq6kEQai68DsJkWgEgj8i3/wLLocdhR+3SfXTcBawx4/2zfvp1ly5YB0KVlC1qkJBtOdOBsNjujBpwOwJptWUz7danhRKEjNiqS287ynrO4adMmnnrqKcOJRERERKQhOBrioi1btmTOnDl8/vnnvPrqq8yYMaP+/CGAmJgYhg0bxkUXXcTpp5/eEBFEZA/KysrYsmULAC06qwAojcPj8TBv5/hvm86HEJeYuk/3i/5DATAzM7NB8oUaj8fDDz/8AECYw87h3bsbTnTwjug9io+nv0J5ZSnPTvmKI3sH1zKTQHba4YN588ep/LR2HY8++ihnn302zZtrQZSIiIjsbvOKTaYj7FEgZwsUDVIA9DnxxBM58cQTAaioqKCoqIiYmBji4uIa8mFF5G/4uv8AmqsDUBrJup/XkbslF9i35R8+kbGRWJaFx+PROYD7Ydmy5Wzfvh2Awzp3JjYq0nCigxfujOSovifx+aw3mPPbCpZu2EjPtm1MxwoJNpuNf15wHmPuuY/Kykruuecenn/+edOxREREJMC8cvu+LXuVwNRoh39FRUXRrFkzFf9EDPOd/wfQXB2A0kgWfO5d3GCzO+h66BH7fD+b3UZkrLd4pRHgfVNdXc3MmTMAiI+O5tAO7Q0n8p8R/U/CYQ8D4LkvtbDCn3q3b8dZQ73fm5988gmzZ882nEhERERE/Emn/4s0Mb4OwMjYSJIykwynkabA7Xaz4Iv5ALTv3o/ImP17I8h3DqAKgPtm7ty5lJeXAzCsZ08cdrvhRP4TH5PEkF4jAfhi/gK27nK8iBy8iWeeTtzObtE77riDuro6w4lEREQkEPh2OATLf/LXDmgE+N577/V3jnp33313g11bRGDlypWAd/zXt5xHpCGtWbiaopxCAHr037flH7uKjosiDxUA90VBQQGLFy8GoE16Gu0yMwwn8r9RA09n+s9TcLndvPT1d9x9/jmmI4WMlPg4bjz1FP75xlv89ttvvPrqq4wfP950LBERERHxgwMqAN5zzz0NVjhQAVCkYfkKgM066oB3aRzzP5sLgN0RRudDBu/3/aPivB2AJSUluN1ubDY1r+/J1KlT6/+NhvXqSSjW+JultOKQjoP4Zc1c3p42netPGUN8dPTe7yj75MIRR/HW1Gms2ZbFv/71L04++WSSk4N3g7SIiIiIeB3wq6h9bbvcn8+LSMMqKioiOzsb0AZgaRyuOhcLv1wIQKdeAwmP3P9CjW8E2O12U1pa6td8oWTjxk2sX78egEPatSMpNtZwooYzetCZAJRXVfHW1OmG04SWMIeDf15wPuD9nfHQQw8ZTiQiIiIi/nBAHYBTp079288//vjjfPTRR9hsNkaOHMnRRx9Nhw4diI6Opry8nLVr1/LDDz/w7bff4na7OfXUU7nmmmsO6C8gIvvO1/0H2gAsjWPFnN8ozS8BoHv/Iw/oGlHxUfUfFxcXEx8f75dsocTj8TB9+jQAIpxOBnTpZDZQA+vUqiftmnVhfdZKXvrmW8YfOxKn44Ce0shfOLxHN0b378dXCxfx2muvceGFF9KrVy/TsURERETkIBzQs+Vhw4bt8XM33ngjH3/8MV27duWdd96hZ8+ef3m7m266iWXLlnHWWWfx0Ucf0apVKyZPnnwgcURkH+1WAFQHoDSCBV94t/+GhUfQsdfAA7pGdPzvXYNFRcW0auWXaCFl2bJl7NixA4ABXToT4XQaTtSwLMvi2EFn8tSH95JTWMSnc+ZxxtDDTccKKZPOPYsff1lCdW0tt99+O1988YXOjRUREREJYn49SOm7777j0UcfJSkpiR9//HGPxT+fHj168OOPP5KYmMgjjzzC999/7884IvIHvgJgdEIM8anqopKGVVdTx6Kd47+dew/GGR55QNcJj4rA7vBusi0uLvJXvJBRU1PDrFmzAEiIjqZ3u7aGEzWOvl0OJzUhE4DnvvxaR4n4WcvUVK484TgAFixYwIcffmg4kYiIiJhiWVZQ/Sd/za8FwGeeeQbLshg/fjzp6en7dJ/09HTGjx+Px+Ph2Wef9WccEfkDXwGwRWdtAJaGt2zmUipKKoADH/8FsCyIivOOAWsT8J8tWrSIsrIyAA7v0R17E1mSYrfZGTngNABWbd3KtF+XGk4Ueq468XhapHgXgNxzzz31X2ciIiIiEnz8emDOokWLADjkkEP26359+vQBvO8wi0jDWbVqFQDNO2kDsDS8+Z95x3/DI6Pp0OOwg7pWdHw0pQWlKgD+QVlZef3vzubJyXRo1sxwosY19JBj+WTGq5RXlvLkZ19wZG+dU+dPEU4nk849mysee5KcnBz+97//cffdd5uOJSIiIoZcPPYhWrfqajrGX9q0eQUvvXK76RgBza8FQN/5Q9XV1ft1P9/tffcXEf/Lzc0lLy8PgGZaACINrKaqhp+/WwxAlz6H4wg7uDPpfJuAVQDc3axZM6mtrQVgaM8eNLXG3nBnJCMPO5WPp7/KglWrmb9yFQO6dDYdK6SM7t+Pwd26Mue3FTzzzDOcd955tG/f3nQsERERMaB1q6507nRwb+yLOX6dE0pMTARg+vTp+3U/3+0TEhL8GUdEduHr/gPvCLBIQ/p16hKqyqqAgxv/9fGNAJeXl9cXvJq6HTtyWbZsGQBdWrYgIynRcCIzRvQ/hQin93zJJz/7wnCa0GNZFv+88HzsNhu1tbXcddddpiOJiIiIyAHwawFw4MCBeDwe3njjDebOnbtP95k3bx5vvPEGlmUxcOCBbYgUkb3bbQOwOgClgS343Dv+GxkdR7uufQ/6elG7bAIuLi456OuFgunTp+HxeHDYbQzu1s10HGOiI2M5qu8YAKb9upSlGzaaDRSCOrdozkXHHA14F759++23hhOJiIiIyP7yawHw8ssvB8DlcjFq1CieeeaZPXZq1NbW8uyzz3LsscdSV1cHwJVXXunPOCKyC18BMC41ntikWMNpJJRVlVfxy/c/A9C17xHYHQd/2kT0bgXAooO+XrBbv34DGzduBOCQ9u2Jj44yG8iwkQNPx2EPA+AJdQE2iBtPPZmkWO/vjkmTJu33cS8iIiIiYpZfzwAcNWoU48eP58UXX6S8vJyrr76aO+64gyFDhtChQweioqKoqKhg7dq1zJ49m+LiYjweDwDjx49n5MiR/owjfmS32xv09tLwVq9eDUDzjs2xBcmWUN+mYsuygiazwK8//kJNVQ0APQ472i8bp6P/0AHoj6+HYP2acrvdTJ8+DYDI8HAGdOnc5Ld6J8YmM6zPcfyw6FO+XrSYddu307F54yw7aio/pxJjY7nt7DOY+PxLbNiwgeeff57rr7/edKyQp+dT4g++ryN9PYm/6WtKJLj4tQAI8NxzzxEVFcUTTzyBx+OhqKiIL7/88k+38xX+LMvi2muv5f/+7//8HUX8yHe+476w2+37dXtpHGvWrAGgVdfWREREGE6zf8LDw01HkP2w4AvvVtqY+CQ6dO+LzXbwTw4dDgfhkeFUV1ZTVlZ20F/DlmUF3feBz+LFP9Uv9BnSvRvRkZGGEwWGE484l6k/fYHb7eLZL7/miWuvbtTHbwo/p8aOGslbP07nl3Xr+O9//8tll11Gsya2ebox6fmU+FtcXJzpCBJC9DNKJPj4vQBoWRaPPvooZ555JpMnT+bLL7+kpqbmT7cLDw/nuOOOY8KECQwePNjfMcTPCgsL93qbuLg47HY7LpeLkhKd0RVI8vPz6wsG6W3TqaqqMpxo31iWRXh4ONXV1fVvGkhgqyip4JcffgKgW99huN0e3O46v1w7Kj6K6spqCgryD/hrODw8HMuy8Hg8QTnCWFNTw7RpUwFIio2le+tW9cdoNHWJsakM7jmCWUu+4f3pM7n+5DG0TE1t8Mdtaj+n/nnBuZx0z32Ul5dzww038Oyzz5qOFHL0fEr8zW63ExcXR0lJCS6Xy3QcCXL6GeV/KqRKY/F7AdBnyJAhDBkyhJqaGpYsWUJWVhZlZWXExMTQvHlzevXqhdPpbKiHFz/b3ycLenIRWFasWFH/cUb7TNxut8E0+843TufxeIImc1O36KsF1NV4C1Ld+x/p14JIVFw0hdmFFBUV+eXrIRi/phYtWkRZWRkAQ7p1w7azmClexw06i9lLvsXldvPUZ1N4YNyFDf6YTe3nVJ8O7Tnt8CF8OGs277//PhdddBEDBgwwHStk6fmU+JPL5dLXlPiVvp5EgkuDH1bjdDrp378/J510Eueddx4nnXQS/fr1U/FPpBH5zv8DaNZB41rScBZ8MR+AuMRUWrbv7tdrR8V5F10UFRX59brBorKyigULvOPVmUlJtG+WaThR4GmW2pq+XQ4H4N3pM9iWl284UWi67awziNk5Qn/77bfrBaCIiIgEnbFjx2JZVv05zr4Fe3uyZcsW7HZ7/X3Gjh3bKDn9KXRPqxaRer4CYFRcFPFpCWbDSMgqKyxl+cxlAHTrNxzLzwsRfItAamtrqaio8Ou1g8G8efPqx5YP796NJr73Y49OGurt+qupq+OJzz43nCY0pScmcP0pJwGwdOlS3njjDcOJRERERA6cx+Phtdde+9vbvPrqq0E/7aECoEgT4CsANuvYvMlvC5WGs+irRbjqvJ1APQ47yu/Xj074fRNwYWGR368fyEpKSvj5Z+/Zim0z0mmRmmI4UeBqmd6Ow7oNB+Dd6TPZkptrNlCIGjfqGNpnZgDw4IMP7tNZwSIiIiKBpnXr1gC89tprf3u0zquvvrrb7YORCoAiTYBvA3Cmxn+lAc3/bC4AianNaNams9+vH50QU/9xUxsDnj17Ni6XC8uyGNLdv6PVoeikoRdgYVHncvH4p+oCbAhOh4N/nH8uAAUFBfz73/82nEhERERk/x1yyCH06NGDdevWMWvWrL+8zezZs1m7di09e/bkkEMOadyAfqQCoEiIKysrY9u2bYDO/5OGU7SjiJXzvMtmuvcf3iCdppExkdjs3l9bTakAmJeXx/LlywHo0rIFqfFxhhMFvuapbRjQ/UgA3p8xi007dhhOFJqG9+7FMYf2AeDll1/mt99+M5xIREREZP9ddNFFwO9dfn/0yiuv7Ha7v+LxeHj99dcZMWIEqamphIWFkZycTJcuXTj//PN5//336287depULMvC6XSy42+ep5aXlxMXF4dlWXz00UcH8DfbnQqAIiHO1/0H3hFgkYaw6MsFeNzelvnu/Y9skMewbFb9IpDi4qIGeYxANHPmTDweD3abjUFdu5qOEzTGDL0Ay7Lhcrt5/BN1ATaUu847h/AwB263m9tvv11bqUVERCTonHfeedjtdt5///0/nTVeWVnJe++9h91u57zzztvjNS666CIuvPBCfvjhB/Ly8oiKiqK8vJxVq1bx5ptvcuONN9bfdvjw4XTs2JHa2lpef/31PV7zvffeo7S0lPT0dE488cSD/nuqACgS4rQBWBrDgs/nAZCS0Yr0Fu0b7HF8Y8BN5byxrVu3sXbtWgB6tWtLfHSU4UTBo1lKKwb28J5F+eGs2WzIzjacKDS1SU/jsuNGAzBnzhw++eQTs4FERERE9lNmZiYjR46kpKSEjz/+eLfPffzxx5SUlDBq1CgyMjL+8v4zZ87k9ddfx2azMXnyZIqKiiguLqayspKcnBzeffddRo8eXX97y7K45JJLAHjxxRf3mMv3uQsvvJCwsLCD/WuqACgS6nwFQGeEk+QWWhwg/peflc/qhd6vs+79j2zQRTO+TcBNZQR4xozpgPe8tcM6dzKcJvicdMQF2HZ2AT76yWem44Ssq088gcykJADuvPPOJlOgFxERkdCxpzHgfRn/nTvXexb6Mcccw0033UR8fDzgLfSlpaVx5pln8vzzz+92n7FjxxIWFsaKFSvq77+rVatWMXv2bADGjx9/YH+pP1ABUCTE+UaAM9pnYrPpW178b+GU+fUfN9T4r4+vAFhRUUFNTU2DPpZpa9euqz+/s2+njkSFhxtOFHwyklswuNcxAHwyey6rtm4znCg0RUWEc99F5wOQm5vLPffcYzaQiIiIyH466aSTSEhI4IcffmDr1q0AbN26lR9++IHExEROOumkPd43Ls57Rndubi5ut3ufHi8tLY2TTz4ZgJdeeulPn/d1/x1++OF07uyfBYuqBoiEuFWrVgE6/08azvzPvOO/6S3akdqsdYM+VlPZBOzxeJg5cwYA0RHhHNqh4caqQ92YI87HbnPg9nh4+L0PTMcJWSP7Hspxh/UD4K233mLGjBmGE4mIiIjsu4iICM466yzcbnf9uXyvv/46brebs846i/C/eTP+6KOPxul08tNPPzFs2DBee+21+iLi37n00ksBePfddykvL6//87q6Ol577TXAf91/oAKgSEirrq5m48aNgM7/k4axY9MONixZD0D3w45q8MfzdQACFBYWNfjjmbJs2XLy8vIAGNC5C06Hw3Ci4JWW2Iyj+nkPTf7up59ZsGr1Xu4hB+reC88nLsp7TuWECRP+dIi2iIiISCD74xiw7//+3fgvQMeOHXnmmWeIiopi1qxZXHTRRbRs2ZKWLVsyfvx4Zs2a9Zf3GzFiBO3ataO0tJT33nuv/s+/+OILcnJyiIuL48wzz/THXw1QAVAkpK1fv76+BTlTBUBpAL7lHwA9Gnj8FyAqPqr+jMFQ7QCsq6tj9mzvk4SE6Gh6tG3Yrsqm4MTDzyfC6S1MPfTOe9pU20DSEhK485yzANi4cSP//e9/DScSERER2XeDBg2iU6dOrFq1iv/7v/9j1apVdOrUiYEDB+71vuPGjWPDhg08/vjjnHrqqaSnp7N161ZeeukljjjiCK666qo/3WfXZSC7jgH7xn/PPvtsoqL8twRQBUCRELb7BmCNAIv/zf/CWwBs1qYLiakNX2S2O+xExEQCUByiBcCff/6Z0tJSAAZ364pdZ3cetLjoBI4b7C1MLV6zlm8W/WQ4Ueg6e/hQBnXtAsBTTz3FkiVLDCcSERER2XcXXnghALfeeiuw9+6/XaWlpXHNNdfw4Ycfkp2dzS+//MIFF1wAwNNPP82XX375p/uMGzcOh8PBrFmzWLVqFVlZWXz11VcA9cVBf9GrCpEQ5lsAYnfYSW+TbjiNhJqstVls+W0z0PDLP3YVnbBzE3BxUaM9ZmOprq5m3jxvUTUtIYFOLVS495dRA04jPsa7qfbf771PnctlOFFosiyLf40fS3iYA5fLxQ033EBtba3pWCIiIiL75IILLsCyLGpra7HZbPUFvAPRu3dvXnvtNXr27AnAtGnT/nSbjIwMTjzRe1zNSy+9xKuvvorL5aJnz57079//gB/7r6gAKBLCfAtA0tqk43DqDDHxr13Hf7v3H95oj+s7B7CwsLDRHrOxzJ+/gKqqKgAO796tftxZDl64M5KTh3rf0V23PZt3pmlJRUNpm5HBDaecDMCyZct45JFHjOYRERER2VetWrXiP//5DxMmTOA///kPLVu23Ot9ampq/vbzERERgPfN/r9y2WWXAfDaa6/VjwL7u/sPQBUBkRDm6wDUAhDxN4/Hw/ydBcCWHXoQn5TWaI/tKwCWlpbicrmw2+2N9tgNqaysnJ9+WgxAq7RUWqc33r9pU3HEIaP5Zv6HZOdvYfKHH3HiwMOIj47e+x1lv11+/Gi+XrSYJes38L///Y+RI0fSu3dv07FERERE9mrChAn7dfurr76asrIyzj77bI444giSkrxTJ/n5+TzyyCMsXLgQgNGjR//l/UeOHEmbNm3qF3iGh4dz/vnnH/hfYA/UASgSolwuF2vXrgW0AET8b+vKLWxfmwVAj0bY/rsrXwHQ4/FQXFzSqI/dkObMmV0/Kjmke3fDaUKTw+7g7GOuACC/pJTHPvnMcKLQ5bDb+d/llxIe5qCuro5rr712j+96i4iIiASz2tpa3nnnHU4++WSSk5OJi4sjPj6elJQU7r//fsBbJDz22GP/8v42m43x48fX/+9TTjmlvojoTyoAioSozZs317/YatZR54iJf83/bK73A8uiW99hjfrY0Qkx9R8XFYXGGHBBQSFLly4FoFOL5mQkJpgNFMJ6dxhAz/be81Re/vZ71mVtN5wodHVs3oybTz8NgBUrVvCf//zHcCIRERER/7vrrrt45JFHGDNmDJ06dQKgsrKS5s2bc+qpp/Lll1/yxBNP/O01TjvttPqPdy0G+pMKgCIhyjf+CxoBFv/yjv/OB6Bt50OIiff/u1N/x7cEBKCwsKhRH7uhzJw5A7fbjc1mY3C3rqbjhDTLsjhn5FXYbXbqXC7ue/Nt05FC2iWjR9GvU0cAHn/8cRYvXmw4kYiIiAi88soreDwePvnkk/263yeffILH4+GVV16p/7P27dtz/fXX8+mnn7Jq1SpKSkqoqalh69atfPjhh3sc/d3Vjz/+CEDbtm05+uij9yvTvlIBUCRE+RaAAGS2zzSYRELNxl83kLt5B9C42399wsLDcEY6ASgqKmr0x/e37du3s3r1agB6tmlNYkzMXu4hB6tZSitG9D8ZgB+X/MqPvywxGyiE2W02Jl82nginE7fbzTXXXENlZaXpWCIiIiIBw+Px8PTTTwPe5R8NtQhQBUCREOUrKCS3SCE8KsJwGgkl87/wLv+wbDa6HjrUSIboeG+RrLi4yMjj+9OMGd5ttGEOOwO6dDacpukYM/RCYqPiAbj3jbep3nn+ovhf24wMbj/7DADWrl3LPffcYzaQiIiISIDweDw8/PDDLF++nOjo6PqNwA1BBUCREKUNwNIQ3G43C3aO/7bv1o+o2HgjOXxjwMHeAbhx40Y2b94MQJ8OHYiOULG+sURHxHDakRcDsD47m2enfGU4UWi7aMTRDOneDYCXXnqJb7/91nAiEREREXPmzZtHmzZtSExM5LbbbgO8ZwmmpKQ02GOqACgSgjweT30HoBaAiD+t+2ktBVn5gJnxXx/fJuCioiI8Ho+xHAfD4/Ewc+ZMACKcTvp17GA4UdMz9JDRtGvWBYDHP/2MDdnZhhOFLpvNxv9dfikJMd7v3euuu46cnBzDqURERETMqKqqYtOmTZSXl9OxY0f+97//MXHixAZ9TBUARUJQTk4OpaWlAGS2Vweg+M+Cz73jv3ZHGF36HG4sh68A6HK5KC0tM5bjYKxevZrsnQWn/p06Eh4WZjhR02Oz2bno+BuxWTaqa+u485XXg7agHAwykhL5zyXersv8/HyuvfZa3G634VQiIiIijW/48OF4PB5qa2tZvXo1N954Y4Od/eejAqBICFq7dm39x1oAIv7idrlZ8IV3/LdDj/5ERJlbVhGd8PtjB+MYsNvtZtasWQDEREZwSPt2hhM1Xa0zOjBywGkAzFq2nE/nzjOcKLSN6teXc48cDsDUqVN57rnnjOYRERERaSpUABQJQSoASkNYtWAlxbnFgNnxX/i9AxCgqKjQYJIDs2zZcgoKCgAY0KULDrvdcKKm7eRhF5EUlwZ4F4IUlZcbThTa7j7vHNpnZgBw3333sWzZMsOJREREREKfCoAiIci3ACQ6PprY5DjDaSRU+JZ/OMKcdOo92GiW8OgI7GEOAAoLi4xm2V91dXXMmTMbgISYGLq3bmU4kUQ4I7lg9LUA5JWU8MBb7xhOFNqiIsJ5/OorCbPbqamp4bLLLqOsLDhH+UVERESChQqAIiHI1wGY0T6zwc8RkKbBVedi0ZcLAOjUaxDhEVFG81gWxNRvAg6uDsBffvml/ozOwV27YLfpV3Eg6NNpMP26HAHAu9NnMnXJr4YThbYebVpz21lnAN43rW6++WadvygiIiLSgPSqQyQErVu3DoCMdhr/Ff9YMec3Sgu8RSvT478+MYnecwALC4OnAFhTU8O8ed4z5tIS4unUQlu6A8kFo68jJtLbNT3xhZco1ihwg7pk9ChG9u0DwIcffsjrr79uOJGIiIhI6FIBUCTEVFZWsnnzZkDn/4n/zN+5/TcsPIKOPQcYTuPlWwRSWFgYNJ1DCxcuorKyEoDB3bqpQzfAxMckcf6x3lHgnMIi7n3jbcOJQptlWfz3sktomZoCwB133MHSpUsNpxIREREJTQ7TAUTEvzZs2FBfDFEBUPyhrqaOxV8tBKDLIUMIC48wnMgrZmcBsK6ujtLSMuLiYg0n+nsVFZUsWuT9d2yekkyb9HTDieSvDOh+JItWzGDRypm8P3MWxx3Wj6P7HGI6VshKiI7mqWuu4tR7H6C6uprx48fzww8/EBsb2N/PIiIiTdGmzStMR9ijQM4WKFQAFAkxu28AbmYwiYSKZTOWUlFSAQTO+C9A9M4RYIDCwoKALwDOmzePmpoaAIZ0746a/wKTZVlceNz1rNr8K6UVxdz64it899D9JMbG7P3OckB6t2/HXeedw92vvcGGDRu44YYbeOGFF9QhKyIiEmBeeuV20xHkIGgEWCTE+DYA2+w20lqrw0gOnm/8Nzwymvbd+xtO87uYxN8LfoF+DmBJSSm//PIzAG0zMmienGQ4kfyduOhELhh9PQA7ioqY+MJLQTNmHqwuOuZojj/M+/Pls88+48UXXzScSERERCS0qAAoEmJ8C0BSW6bicKrJVw5OTVUNP3+3GIAufQ7HEeY0nOh3zggnYeFhABQUBHYBcM6c2bhcLizLYkj3bqbjyD44rNswhvQ6BoBvFv/Emz9OMxsoxFmWxb8vGVc/Gn/33XezcOFCw6lEREQEwOPxBNV/8tdUABQJMb4R4AyN/4of/Dp1CVVlVQD0OOwow2l2Z1m/dwEWFQVuAbCgoIBly5YB0LlFc1Lj4wwnkn11/rHXkZroPUv13jffZvW2bYYThba4qCievu4qwsPCqK2tZdy4cWRnZ5uOJSIiIhISVAAUCSEej6d+BFgLQMQfFuwc/42MiaNtl0MNp/mzmJ3nABYUFBhOsmezZs3C4/Fgs9kY1LWr6TiyHyLDo7jylEnYbXaqamq47slnqNp5jqM0jO6tW/Pv8eMAyMnJ4eKLL64/O1NEREREDpwKgCIhJCcnh7KyMgAy2qkAKAenuqKKX374BYCuhx6B3RF4I+W+TcDFxcW43W7Daf4sOzuHVatWAdCjTWsSYqINJ5L91a55F04ZNhaA3zZv4cG33zUbqAk49fDBXDzKO369cOFCJk2aZDiRiIiISPBTAVAkhPjO/wN1AMrB+/n7n6mprAagR//AGv/18W0CdrvdFBcXG07zZzNnzgDAYbczoHNnw2nkQB03+Cy6tO4NwCvf/cBnc+cZThT67jznLAZ28X7PvPzyy7z11luGE4mIiIgENxUARUKIb/wXVACUg+cb/42OS6R1596G0/w1XwcgBN4ikM2bt7Bx40YADmnfjpjICLOB5IDZbHauOOVO4mO825snvvCyzgNsYGEOB09eexWZSTv/zSdO5JdffjEbSkRERCSIqQAoEkJ8C0Ci4qKITdaiATlwFSUV/DrtVwC69R2GzWY3nOivRSf8PlJbWBhYBUBf9194WBj9O3UynEYOVkJsMledehc2y0ZFdTVXPPok5VVVpmOFtNT4eJ69/hqcDgfV1dWMHTuW3Nxc07FEREREgpIKgCIhpH4BSIdmWJZlOI0Es5+/XUxddS0QeNt/dxUWHkZ4tLezLpAKgGvWrCUrKwuAfp06EuEMM5xI/KFz616cftQlAKzNyuLWF17G4/EYThXaDmnfjvvHXgDAtm3buPTSS6mrqzOcSkRERCT4qAAoEkJ8ZwBqAYgcrPlfeMd/YxNTaNm+u+E0f883BlxUFBgFQI/Hw6xZMwGIjginT/v2hhOJP40edCaHdh4CwGfz5vPyt98ZThT6zh4+jPOPPhKA2bNnc88995gNJCIiIhKEVAAUCRFVVVVs3rwZgEwVAOUglBWVsXzGMgC69xuOZQvsXxUxOxeBFBQUGE7i9dtvv5GXlwfAYZ07E+YIzPFpOTCWZXHJmImkJzUH4N433mbWsuWGU4W+ey44j74dOwDw7LPP8u672sYsIiIisj8C+1WdiOyz9evX14+iZXZQAVAO3OKvFuKqcwGBu/13V74OwJKSEuOjgS6Xi9mzZwMQHx1Fz7ZtjOaRhhEVEcM1p/8DZ1gEdS4XF//nf2zeobPpGpLT4eCZ664hPTEBgAkTJmgpiIiIiMh+UAFQJET4FoAAZLRrZjCJBLsFn88HICElk2ZtuxhOs3fRib9vAi4qKjIXBFiyZAnFxcUADOzaFXuAd0/KgWuZ3p5LT7oVgILSUsZN/j/KKisNpwpt6YkJuy0Fueiii9ixY4fpWCIiIiJBQa9MREKErwBo2SzSWqcZTiPBqiSvmN/meMcZu/cbHhTLZHwdgAAFBebOAaypqWHePO/ZiclxcXRp2cJYFmkc/bsO5eRhFwGwastWbnjmOdxut+FUoe3QDh14YNyFAGRlZTF+/Hhqa2sNpxIREREJfCoAioQIXwEwrVUaYeHaOCoHZtFXC/G4vaPkgbz9d1fRCdH1hUqTm4AXL/6J8vJyAIZ064otCIqncvBOGnoB/bsNA+DbxT/zvw8/Npwo9J01bCgXjvD+fJo3bx6TJk0ynEhEREQk8KkAKBIifAVAbQCWgzH/s50dbOktSW8ZHNtr7Q47kbGRABQWmlkEUllZxcKFCwDITEqiXaa+D5sKm2XjilPvoFW69/vlsU8/57N58w2nCn13n38uh3XuBMBLL73Em2++aTiRiIiISGBTAVAkBHg8nt8LgO1VeJADU5hdyOoFqwDo3j84xn99fGPApjoAFyyYT3V1NQBDuncjiP7pxA8inJFcf9Z9xEYlAHDzcy+yZP0Gs6FCnNPh4OnrriYzKQmAiRMnsnjxYsOpRERERAKXCoAiISAnJ4fS0lIAMttrAYgcmIVT5tdvkg6W8V8f3yIQEwXAsrIyfvrpJwBap6fRMjWl0TOIeSkJGVx7xj3YbQ6qamq45P8eJdvgmZRNQWp8PM9dfw3hYQ5qamoYO3YsOTk5pmOJiIiIBCQVAEVCwLp16+o/zlQHoByg+Z97x3/TmrcltVkbs2H2k68DsLy8vL4Tr7HMnTOXuro6AIZ069aojy2BpVOrnow94UYAcgqLuPh/j1DZyF+PTU3v9u146OJxAGRnZzNu3DhqamoMpxIREREJPCoAioQA3/gv6AxAOTA7Nu1g3U/er6Pu/YOr+w8gJim2/uOCgsY7B7CoqJhfl/4KQMfmzUhPTGi0x5bAdETvYxk96EwAlm3cxA3PPK/NwA3s9COGMG7kMQAsXLiQO+64w3AiERERkcCjAqBICFizZg0AUXFRxKXEGU4jwWj+53PrP+5x2JEGkxyY2F0KgPn5jVcAnDNnNm63G8uyGNS1a6M9rgS2M466hD6dBgPw1cJFTNZm4AY36dyzGNS1CwCvvvoqr732muFEIiIiIoFFBUCRELDrApBgWtwggWP+p94CYPN2XUlKa244zf6LjI3E7rADUFCQ3yiPmZ9fwG+//QZA15YtSY6L3cs9pKmw2excfsodtNy5GfjxTz/no1lzDKcKbWEOB09dexXNk5MBuO2221iwYIHhVCIiIiKBQwVAkRDgOwMwU+O/cgC2rNzC1lVbgeBb/uFjWVb9GHBjjQDPnj0Lj8eDzWZjQNfOjfKYEjwinJHccNZ9xEUnAjDxhZdYvGbtXu4lByM5Lo7nbriW8LAwamtrGTduHNnZ2aZjiYiIiAQEFQBFglxVVRWbNm0CtAFYDsz8T72dSZZlo3u/4Bv/9fGNAefnN3wH4I4dO1i1ahUAPVq3IiE6usEfU4JPcnw61515Lw57GDV1dVz6f4+xNS/PdKyQ1rNtGx6+xLsUZMeOHYwdO7bRFwOJiIiIBCIVAEWC3IYNG/B4PIB3BFhkf3g8HuZ95t3+26bLIcQmJBtOdOBiE70FwKKiogZfujBr1iwAHHYbh3VW95/sWYcW3bhkzEQA8kpKGPffRyirrDScKrSdMmQwl44eBcDixYuZOHFi/e9JERERkaZKBUCRIOdbAAIaAZb9t+6nteRtyQWCd/zXJyYxBgC3201RUVGDPU5W1vb6sfuebdsSGxXZYI8loWFgj6M46YgLAFi1dSvXPPkMLm0GblC3n30mQ7p3A+Ctt97i5ZdfNpxIRERExCwVAEWCnG8BiGWzSGuTbjiNBJt5O5d/2B1hdD10qOE0Bydmt03ADTcGPGvWTADCHHb6d+rUYI8joeWkYRfSv+swAH78ZQkPvfOe4UShzWG389Q1V9EyNQWAO++8k7lz5+7lXiIiIiKhSwVAkSDn60RKbZlKWHiY4TQSTFx1LhZ84R3/7dDjMCKjg3uLbUxiTP0W7Pz8hlkEsnnzlvozNw9p357oiPAGeRwJPTbLxiUnTaRtpndk/Lkvv+adadMNpwptibExPH/DdUQ4ndTV1TF+/HgtBREREZEmSwVAkSDnGwHW+X+yv1bM+Y2SvBIAeg442nCag2d32ImKiwKgoKBhOgB93X/hYWH069ihQR5DQld4WATXnXUvibHerrQ7Xn6Nub+tMJwqtHVr3Yr/XjYegNzcXC6//HLq6uoMpxIRERFpfCoAigQxj8dTPwKsDcCyv+bt3P7rDI+kU69BhtP4h28MuKDA/x2A69dvYNu2bQAc2rEDEU6n3x9DQl9ibArXn3UfzrAI6lwuLn/sCTZm55iOFdLGDBzA2JEjAJgzZw7//ve/DScSERERaXwqAIoEsR07dlBaWgpoAYjsn5qqGhZ/vQiAzocMISw8wnAi//BtAm6IMwB93X+RTid92rf3+/Wl6WiT2YnLTroNgKKyci7+3yMUl5cbThXa7jznLHq3awvAI488wvfff284kYiIiEjjUgFQJIj5uv9AI8Cyf36duoTK0kogNMZ/fXwdgDU1NZSV+a+gsnr1GnJyvF1a/Tp1IjzM4bdrS9PUr+sRnH6kdzR1bdZ2rnr8KepcLsOpQld4WBhPXXsV8dHRAFx11VX1Hb0iIiIiTYEKgCJBbNcCoEaAZX/4tv9GxsTRrls/w2n8J3aXTcD+OgfQ4/Ewe/YsAKIjIuq7iEQO1vFDzmFwz2MAmLlsOfe8/qbhRKGtZWoq/3fFpQAUFhZyySWXUFNTYziViIiISONQAVAkiPkKgJFxUcSlxBlOI8GisrSCX374GYBufYdjd4RON1vMLgVAf40Br1ixkry8PAAO69yJMIfdL9cVsSyLcSfcRIcW3QF47fsfefU7jaY2pBF9DuGKE44DYNGiRdx///2GE4mIiIg0DhUARYKYbwNwZvtMLMsynEaCxU/fLKauuhaAngOOMpzGv8IjnTgjvcs5/FEAdLvd9d1/cVFR9GjT5qCvKbKrMIeT6878JykJGQDc8/pbzFi6zHCq0HbL6afSv1MnAJ5++mmmTJliOJGIiIhIw1MBUCSIrVu3DtACENk/8z7zjv/GJabSqkNPw2n8L9aPm4CXLVtGUVERAAO6dMZh169N8b+46ERuOOt+IpxRuNxurnzsSdZsyzIdK2SFORw8ec2VJMV6f1Zcd911bN682XAqERERkYalVzIiQaqqqqr+BYsWgMi+KskvYflMb3dR98OOwrKF3q+B2CTvOLxvbPdAuVwu5s2bB0BCTAzdWrU66Gwie9IirS1XnjoJy7JRWlnJuMn/R8HOLe/ifxlJiTx21eVYlkVJSQlXXHEFdXV1pmOJiIiINJjQe+Un0kRs2LABt9sNaAGI7LuFU+bjdnm/bnoeFlrjvz6+8zDLy8uprKw84OssX76c4uJiwNv9Z7NpzF4aVu+OAzh7xOUAbN6Ry+WPPkGNilINZmjPHlxx/GgAFi5cyOTJkw0nEhEREWk4KgCKBKndNgBrBFj20bxPvOO/yRktyWjV0XCahhGb/PtCnAPtAty1+y8xJoYuLVr4JZvI3owccBrD+hwPwPyVq7jz5VfxeDyGU4WuCaefSq+23s3e//vf/5g7d67hRCIiIiINQwVAkSDlKwBaNou0NumG00gwyNuax5pFqwHocdjRIbs4Jm63AuCBLQLZtfvvMHX/SSOyLIsLRl9Hl9a9AXh3+kxe/Ppbw6lCl9Ph4PGrLycqPBy3282VV15Zf+6niIiISChRAVAkSPkKgKktUwkLDzOcRoLB/M9+72wJ1fFfgPCocMIjw4ED6wBU95+Y5rA7uOaMe0hPag7AA2+/y/yVqwynCl1tMzK476ILANi2bRsTJkxQ16WIiIiEHBUARYKUrwCoBSCyr+Z+MgeAzFYdSc5oaThNw4pN9m73zM/f/wKgzv6TQBATGcd1Z9yLMywCl9vN1U88zQ51pjWY048YwpiBAwD47LPPeOuttwwnEhEREfEvFQBFgpDH46kvAOr8P9kXW1ZsZuvKLQD0HHiM4TQNz3cO4P52AP6x+6+zuv/EoOZpbRh3/E0A7Cgq4uonnqbO5TKcKjRZlsUD4y6kRUoyAHfcccduZ+2KiIiIBDsVAEWC0I4dOygpKQG0AVj2zZyPZgNgWTZ6DjjacJqG5zsHsLKykvLyin2+n7r/JNAM6nk0R/c/GfAuBfn3u++bDRTC4qOjefSqK7BZFhUVFVx22WVUV1ebjiUiIiLiFyoAigShXbsSNAIse+N2uevHf9t160tMfJLhRA1v103A+zoGrO4/CVTnHHMF7Zt3BeDZL7/mq4WLDCcKXf07deSGU08GYOnSpfznP/8xG0hERETET1QAFAlCuxUANQIse7Fy7m8U5RQC0GtQ6I//wh83Ae9bAVDdfxKoHPYwrj79H8RGJQAw4dkXWJe13WyoEHbNmBPo27EDAI8//jgLFiwwnEhERETk4KkAKBKEfAXAyLgo4lPjDaeRQDd75/hvWHgEXfocbjhN43BGOgmPjgAgPy9/r7f/U/dfS3X/SWBJikvlylPvxLJslFVVcfljT1BRpfHUhuCw2/m/yy8lMtyJ2+3m6quvpqyszHQsERERkYOiAqBIENp1AYhlqUtJ9qy6sprFXy0EoGufI3CGRxpO1HjikrybgHPzcvd62z91/+n7SgJQt7aHctrwcQCs3rqN219+BY/HYzhVaGqTkc6kc88GYOPGjdx7772GE4mIiIgcHBUARYKQrwCo8V/Zm5+/+4mq8iqg6Yz/+vjGgPPz/74DUN1/EkyOG3I2fToNBuDj2XN5f8Ysw4lC1/lHHcnwXj0BePnll/nxxx8NJxIRERE5cCoAigSZ6upqNm/eDEBmBxUA5e/N+chbHIiJT6Jtl0MNp2lcvkUgVVVVlJWV7/F26v6TYGKzbIwfcwvJ8WkATHr1dVZv22Y4VWiyLIuHL72Y+OhoAK6//noKCwsNpxIRERE5MCoAigSZDRs24Ha7AXUAyt8ryStm2fSlAPQ47ChsdrvhRI0rdrdFIH89Bux2u5k/fz6g7j8JHjGRcVx56iRslo2qmhquevwpKqt1HmBDyEhM5IFxFwKQnZ3NbbfdZjiRiIiIyIFRAVAkyKxZs6b+48z2KgDKns3/bB5ul7dY3GvQSMNpGl9cyu8FwNzcvy4ArlixkqKiIgD6d+6k7j8JGh1adOf0o8YD3vMA//Ham4YTha4xAwcwZuAAAD766CM+/vhjw4lERERE9p8KgCJBxnf+n2WzSGudbjiNBLI5H3u3/6Y2a01Gyw6G0zS+sPAwouK9o3t/VQD0eDzMn+89+y8+Ooou6v6TIHPsoDPp1eEwAN6ZPoOPZ88xnCh03T/2AtISEgC49dZbyc7ONhtIREREZD+pACgSZHwFwJQWqTgjnIbTSKDavi6LDUvWA9Br4Mgmuy06PiUe+OsC4Jo1a+oXhPTt2BG7Tb8SJbjYLBuXjLmVhNhkAO54+TXWb1dhqiEkxMTw30svBqCwsJCbb75ZG5hFREQkqOjVjkiQ8RUANf4rf8fX/QfQc8DRBpOY5SsA5ufn43K56v/c4/HUb/6Njoige+tWRvKJHKy46ASuOOVOLMtGeVUVVz/xFFU1NaZjhaThvXtx7pHDAfjmm2/48MMPjeYRERER2R8qAIoEEY/HowKg7JXH42Hux95RwNadehOf3HRHxWNTvecAulwu8vML6v987dq15OTkANC3YwccTWxBioSWLq17c/JQ76KK5Zs288Db7xpOFLruPOcsmiUnAXD77bfX/xwRERERCXQqAIoEkdzcXEpKSgBtAJY9W7NwNXlbvCOvvQYdYziNWfGp8fUf5+buqP941qxZAEQ6nfRq27bRc4n424mHn0vXNn0AePW7H/hywULDiUJTbFQk/x4/DoCioiJuvfVWjQKLiIhIUFABUCSI7LoBOEMdgLIHvvFfuyOMbn2HGU5jVnR8NA6nA/j9HMCNGzexZcsWAPp0aE+YQ91/EvxsNjuXn3IHcdEJAEx84SW27GH7tRycYb16ctawIwCYMmUKn3zyidlAIiIiIvtABUCRILJu3br6jzPbNzOYRAJVTVUNCz73nm3XufdgIqJiDCcyy7Is4v6wCGTmzBkAhIeF0btdO2PZRPwtISaJy06+HYCSikquffIZauvqDKcKTZPOPZuMxEQAbrvttr9cNCQiIiISSFQAFAkivvP/ImMjdxttFPH55bufqCipAKD34FGG0wSGuGTvOYA7duxg69atrF/v3Y7cu11bIpxhJqOJ+F2Pdv04fvA5APy0dh2TP/zYcKLQFB8dzb/GjwWgoKCA2267zWwgERERkb1QAVAkiPhGgDPaZWJZluE0EohmfTATgOi4RNp37284TWDwFcsrKiqYNm0aAGEOB306tDeYSqThnDJ8LO2bdwXgqc+nMGPpMsOJQtNRh/TmtMOHAPDZZ5/x2WefGU4kIiIismcqAIoEkd83AGv8V/6sMLuQpdN/BaDXwGOwOxyGEwWGuF26ZX3df73atSUqPNxUJJEG5bA7uOLUSUSGRwNww9PPsaOoyGyoEPWPC84lLSEBgFtvvZX8/HyzgURERET2QAVAkSBRXV3N5s2bAS0Akb829+PZeNzebZQa//2d7wxAH7vNxmGdOxtKI9I4UhMyuPiECQDklZRw4zPP43a7DacKPQnR0Tw47iIA8vLyuP322w0nEhEREflrKgCKBIkNGzbUv3jLbKcCoOzO4/HUj/9mtu5Eegstt/AJczqIiouq/9892rYhJjLSYCKRxtG/2zCO7HsiADOXLeeZKV8ZThSaRvbtwymDBwHw8ccfM2XKFMOJRERERP5MBUCRIOEb/wXI7KACoOxuw6/ryVqzDYBDhhxrOE3gCYv+fdlHf3X/SRNyzjFX0iK1LQD/ef9DFq9Zu5d7yIG454LzSI33Lhy65ZZbKCgoMJxIREREZHcqAIoECV8B0LIs0lqnG04jgWbW+97uP5vdQY/DjjKcJrDU1tbicni7Zy0gVt1/0oQ4w8K58rRJOB3huNxurn3yaYrLy03HCjmJsTE8MNY7Cpybm8tdd91lOJGIiIjI7lQAFAkSvg3AKS1ScEY4DaeRQFJTVcP8T+cC0Ln3IKJi4vdyj6Zl+/bt2CO9C1E8QK6WIUgT0zy1Decdew0AW/PymfjCy3g8HsOpQs+x/ftywoDDAHjvvff44YcfDCcSERER+Z0KgCJBYt26dQBkdtAGYNndL9//THmxt6On92CN/+7K5XKRvT0bR/TvG5FzCovMBRIxZOghoxnQ/UgAvlq4iDd/nGY2UIj654XnkRDj3b588803U1ZWZjiRiIiIiJdj7zcJHcXFxXzwwQcsWLCA/Px8wsPDad++PccddxwDBw484OvW1dXxxRdfMH36dLKysgBo3rw5w4YN4/jjj8fh+Ot/5nXr1jF//nyWL1/O5s2bKSsrIyIighYtWjBgwACOO+44oqKi/vK+OTk5XHrppXvNduuttzJkyJAD/rtJYPB4PPUdgBlaACJ/MOuDGQBExybSocdhhtMElpycHdTV1WEPs+OMDKOmspacokLTsUQanWVZXHTcDazPWklu4Xb++cZb9OvUgS4tW5qOFlJS4+O55/zzuOGZ59i6dSv33Xcf//73v03HEhEREWk6HYCbN2/mmmuu4dNPP/WOg9ntlJeX88svv/Dggw/y/PPPH9B1Kysrue2223jppZdYt24dLpcLl8vF2rVrefHFF7njjjuoqqr60/2mTZvGjTfeyDvvvMPSpUspKSkhIiKCiooKVq1axWuvvca1117L5s2b95ohLi6OhISEv/zP6dSoaCjIzc2lpKQEUAFQdleUU8iy6UsB6DlwBPY9vOHQFHk8HrbvfFMmKiKcxBTvAf3ZBSoAStMUFRHDladOwm5zUF1by1WPP01FVbXpWCHnlCGDOLJ3LwBeeukl5s6daziRiIiISBPpAKytreX++++nuLiY1q1bc9NNN9G2bVuqq6v59NNPefPNN/n8889p27YtI0aM2K9rP/XUU6xevZro6Giuu+66+k7CefPm8dhjj7Fy5Uqefvppbrzxxt3u53K5cDqdDB06lKFDh9K1a1fCw8Opqqpizpw5vPTSS+Tm5nLffffxxBNPEB4evscMkydPJj1dSyFCmTYAy57M/WQObpd3wcUhg0cZThNYcvPyqK72Fjcyk5MoKLbI2ZJPXkkJdS6X4XQiZrRr1oUzjr6Ed757hrVZWdzz+ps8fOnFpmOFFMuyeHDcRYy47U7Kq6q48cYbmTp1KpFaQCQiIiIGNYkOwG+++Ybs7GzCw8O5++67adu2LQDh4eGceeaZjB49GoA33niDurq6fb7uhg0bmDHDO3p37bXXMmjQICzLwrIsBg0axDXXeA/cnjZtGps2bdrtvp07d+b555/nuuuu45BDDqkv8EVERHDUUUcxceJEwDvqO3v27IP7B5Cgt1sBUB2AspPH46nf/pvZqiPpLdsbThRYsrZtAyA8LIzk2Djik2MAcLvd5BYXm4wmYtTIAafRq8MAAN6ZPoNP58wznCj0NE9J5o6zzwS8R77897//NZxIREREmromUQCcNm0aAEOHDiU1NfVPnz/ttNOwLIuCggKWLl26z9edPn06Ho+HzMxMBg0a9KfPDx48mMzMTDweD9OnT9/tcy1atCAxMXGP1+7VqxdpaWnA78sfpOnyFQAjYiKIT0swG0YCxoYl69m2eisAvdX9t5vCwkIqyisAyEhOwmZZxCfH1n8+p1BjwNJ02Swbl4yZSEJMMgC3v/QKG3N2GE4Ves47ajgDunQG4Mknn2TJkiWGE4mIiEhTFvIFwMrKyvrlCYceeuhf3iY1NZUWLVoA7NeTs19//RWAPn36YFnWnz5vWRZ9+vTZ7bb7Iy7Oe16VS6NqTZ6vAJjZvtlffq1J0zT97WkA2B1h9By4f8cXhLptO7v/HHY7afHxAEREOQmP9J6LqgKgNHVx0QlcfsrtWFiUVVVxzRNPU7MfUxCydzabjX+PH0d4WBgul4sbbriB2tpa07FERESkiQr5AuDWrVvxeDwAtG7deo+3831uy5Yt+3Rdj8fD1q1b93rdVq1a7dd1fUpLS+vHhn3X2JOHH36Yc845h1NPPZVx48bx0EMPsXDhwv16PAls2gAsf1RVXsX8z7wHy3c99AiiYuINJwocpaVllBR7l+akJyVit3l/1VlYJKR4uwBVABSBrm36cOIR5wHw64YNPPzeB4YThZ52mRncdNopACxbtownnnjCcCIRERFpqkK+AFhQUFD/cVJS0h5v5/tc4T6+KKysrKzf7rsv162srKSysnKfrg3wzjvvUFtbS2RkJEOGDPnb265ZswaPx4PNZiM/P5+5c+dy33338e9//1vvNIeA6urq+m3Qme1VABSvBV/Mp6rc+zOozxHHGU4TWHxn/9lsFhmJCbt9LmHnGHBecQl1O5eniDRlJw29kE4tewDw3Jdf8+MvGlP1t0tHj6Jn2zYA/Pe//61/U09ERESkMYX8FmBfkQ742026vs/ta5Fu19vty3V999mXDXALFy5kypQpAJx77rnEx/+5s8fpdHLcccdxxBFH0LZtW6KiogDYvHkzH374IVOnTmX27NlER0fXLyP5O2+88QZvvfXWHj9/zjnncO655/7tNWw7u2xsNtvfnm8o++e3337D7fYWKlp3bdMktwj+3fdYUzXrPe8CosTUTDp0P6z++6+pq6yqJL8gH4C0hETCnc7dPu8rALrcborKy8n4mzdwRPaH3R6cT6kchHH1Gf/gjqcvpryylAnPvcC0yQ/re8PPHrvmSo6ZeAc1NTVMmDCBadOmYbfb//K2ej4l/uY7PiY+Pr5+MkrkQOlnlEjwCs5nqyFs/fr1TJ48GbfbzcCBAxkzZsxf3i4xMZErrrjiT3/eqlUrbrzxRuLi4vj000/57rvvOPnkk+vPONyT8vJyduzY8wHgFRUVe3yi+keWZe3zbWXvdu0UaN6xeZM8A7Ap/p3/ztZVW1i9cBUAfYeegN2u4p9P1rZt4AEsaJby5wJGwm6LQIrITFaRQ/wjmH9MpSSkc9nJt/F/b99JfkkpVz76BB/+4y79bPGjnm3bcv0pJzH5g4+YO3cuzz77LNdee+3f3kfPp8Tf9Gah+JN+RokEn5AvAEZERNR/XF1dXd8p90fV1dUA+9xdtevtfPf9u+vuy7W3bNnCP/7xDyoqKujZsyc333zzARc+zjvvPL766itqampYuHDhXguA0dHR9VuH/0pUVNRel5HYbDYsy8Lj8dR3rMnBW7FiBeD9JZveJr3JvXPr+5qS3/3wxvcAWJaNPocfh/55vOrq6sjeng1AUmwsEX/o/gOIjI4gPNJJdWUN2YUFeDztGjumhCDLIui/D/t2OYKRA07j2/kfMmvZcv7vo4+YcPpppmOFlBtPP5XP581n9dZt3H777Rx33HG0adPmT7fT8ynxN8uysNlsuN1uPaeSg6afUf6nQqo0lpAvAO56Pl9BQcEeC4C+swL3tY05MjKSyMhIKisrdztncE/X9d1+T7KysrjrrrsoLi6mc+fOTJo0CedfvHjdVxEREbRq1Yq1a9eSk5Oz19uff/75nH/++Xv8fF5e3l7PR0xMTMRut+N2u/f5LEXZu6VLlwKQ0iIFF+79Oksy2NlsNiIiIqiurtYTjJ1qq2uZ8e40ADr2HEBUbAJ1dTrrE7ybf31vVGQkJuL+izP+bHYbialxZG/OIysvX/92ctAsy8LhcOBy1QX9C+vTj7qElRuXsDlnLQ+/8z5927dnQJfOpmOFlH+PH8ep9z5AeXk5l1xyCe+9996f3uzV8ynxN7vdTmJiIsXFxXt9Q19kb/Qzyv9SUlJMR5AmIuT7wFu0aFH/xMq3SOGv+D7XsmXLfbquZVn1XXUHe93s7GwmTZpEQUEB7dq14x//+EeTPOdN/tratWsByNACEAF+/u4nSgtKAS3/2JXH42H79u0AREdGEBu155+hSSlxAOSXllJdW9co+USCgdPh5MpTJxEeFoHb4+G6p56lqKzMdKyQ0rdjB8aNHAHAtGnTeOeddwwnEhERkaYi5AuAkZGRdOzYEYCffvrpL2+Tl5fHli1bAOjdu/c+X7tXr14A/Pzzz3u8zS+//LLbbf9ox44d3HnnneTl5dG6dWvuvfdeYmJi9jnDnlRVVdUXH9PT0w/6emKGx+P5vQDYTgVAgRnvTAMgJj6Jjj0Hmg0TQPLy86mprgEgMykJiz0fn5CY5l2s5PF4yNE71yK7yUxpyYWjrwdge0EBNz//YtB3NgaaW844jZap3m6Pu+66a58mNUREREQOVsgXAAGGDx8OwIwZM8jNzf3T5z/66CM8Hg9JSUn07Nlzn687dOhQLMsiKyuLuXPn/unzc+bMISsrC8uy6jPsKj8/n0mTJpGbm0vz5s259957iYuL26fH3tuT8bfffpuamhosy6J///77dE0JPLm5uRQXFwOQqQ7AJi93Sy7LZy4DoPegUdgdIX+Kwz7bvi0LAGeYg6TY2L+9bWJKbH1neLYKgCJ/MqT3SAb3PAaAbxf/zKvf/WA4UWiJjojgX+PHAVBcXMytt95qOJGIiIg0BU2iADhq1CgyMjKoqqrivvvuY8OGDYB3QccHH3zAlClTAO85eI4/vKC+5JJLGDNmDI888sifrtu2bVuGDh0KwOOPP868efPweDx4PB7mzZvHE088AXgLkK1atdrtvkVFRUyaNIns7GwyMjK4//7792uN+h133MF7773Hhg0bdjvLY/PmzTz66KN8/PHHABxzzDF7XQAigWvXDcCZHZoZTCKBYNZ7M+qL/xr//V1JSQllO8cUMxITse1leZLD6SA2wXse7Pa/OcNVpCm7YPR1pCc1B+D+t95h+aZNhhOFliN6dOesYUcAMGXKFD7//HPDiURERCTUNYn2kbCwMCZNmsSdd97Jxo0buf7664mKiqKqqqp+scAJJ5zAiBEj9vvaV111Fdu3b2f16tU8+OCD9Ys7amq8o2hdunThyiuv/NP9vv76a7Zt2wZ43/298cYb9/gYXbp04Y477tjtz3Jzc3njjTd44403sNvtREVFUVNTs9vW4WHDhnH55Zfv999JAsfq1avrP27WobnBJGKa2+Vm5nvTAWjdqTfJ6Srs+2Rlebv/bDYbaYkJ+3SfxNR4SgrLyS4oxOPxbnEVkd9Fhkdx5amTuP/l66ipq+Wqx5/i83v/QdwelqnJ/pt07tlMXbKUHUVF3HrrrRx++OH79WawiIiIyP5oEh2AAK1ateLxxx/npJNOIjMzk9raWqKjo+nduzd33HEHl1122QFdNzIykn/9619cfPHFtG/fHrvdjt1up3379owfP54HH3yQiIiIP91v142mlZWVFBUV7fG/sr84gHvs2LGMGjWKdu3aERcXV78ZNjMzkyOPPJL777+fCRMmEBYWdkB/LwkMvgJgdEIMcSn7Nh4uoWnp9F8p2O7tVjv0iOMNpwkclVVV9dvW0xLicdjs+3S/xFTv91NFdTXFFeUNlk8kmLXJ7MRZI7xvJG7IzuHm53QeoD/FR0fzwNgLAO8bu3fddZfhRCIiIhLKLI+eyck+yMvL2+ttfCvhXS6XVsL7yemnn8706dPp2K8Td350t+k4jc5msxEREbFbt25T9cjFk/nl+5+JiIrhpv9+QJgz3HSkgLB+/Xqyt2eDBYe0b0dEmPNvb2+ze9/3Kiks48ePFwAwun8/urRUR6UcGMuycDgc1NXVhWRxzOPx8PRH97Pgt2kA3HH2mVxxgo4g8KcrH3uSKQsWAvDuu+9y2mmn6fmU+JXdbicxMZHCwsLdjg4SORB6zed/KSkppiNIE9FkOgBFgpGvA1Dn/zVt+dvyWPLjLwD0Hnysin871dXVsWPHDgCSYmP3WvzbVWx8NI4wb7fg9gI9eRXZE8uyGHfCBDKTvWcZ/+vd95n72wrDqULLvRedT0JMNAATJkygtLTUcCIREREJRSoAigSokpIStm/fDkCzjioANmXT3pqKx+3tLOo3/ETDaQJHdk4Obpe3MzQzaf/OzbJsFgk7x+qzC7UIROTvRIZHce0Z9xAeFoHb4+GaJ5/WBm0/So2P5x/nnwvA1q1bmTRpkuFEIiIiEopUABQJULtuANYCkKarrqaO6W9PBaBtlz6kZLTayz2aBrfbQ3aWt0AeExlBTGTkfl8jMSUWgNyiYuo0EiXyt5qltubiE28GILe4hKsef4raujrDqULHqUMGM7xXTwCeeuopZs2aZTiRiIiIhBoVAEUC1K4bgDUC3HQt/noRJXklAPQ78iTDaQJHfn5e/bb1jKQkLPZ/ja9vEYjL7SanqNiv+URC0YDuR3LMYacCsGj1Gh56533DiUKHZVk8dPFYoiMi8Hg8XHLJJVRVVZmOJSIiIiFEBUCRAOXrAHRGhpPcPNlwGjHlxze+ByAmPpnOvYcYThM4srKyAAgPCyM5LvaArpGUFl//8bZ9WHQkInDWiMvo0KI7AC98/Q2fz1tgOFHoaJ6SzO1nnQHAqlWruO+++wwnEhERkVCiAqBIgKpfANI+E5tN36pN0bbV21g1byUAhw49HrvDYThRYCgpKaW8rByA9KTEA+r+A3CGhxGb4D14Pys/32/5REKZwx7G1afdRVx0AgATX3iJNduyzIYKIecffSQDu3YB4L///S+//vqr4UQiIiISKlRVEAlQvgKgFoA0XVPf+AEAy2aj7xEnGE4TOLJ3Lsex2SzSEuL3cuu/l5zuvX9WfgFuj+egs4k0BYlxqVx56iQsy0Z5VRWXP/o4pRWVpmOFBJvNxiNXXU54WBgul4vrr7+e2tpa07FEREQkBKgAKBKAqqqq2LRpEwCZWgDSJFVXVDH7w5kAdO49mLikVMOJAkN1TQ35O7v1UuPjcdjsB3W9pJ0FwOraWvKKSw46n0hT0bVNH844ajwAa7O2c9Ozz+N2uw2nCg3tmzXj1p2jwMuWLePJJ580nEhERERCgQqAIgFo/fr19S+kmmkBSJM079O5VJZ6O2r6DR9jOE3gyN6ejWdnp156UuJBXy85PaH+4215GgMW2R+jB51Fv65DAfhm8U88/unnhhOFjqtOOpFe7doC3lFg37nAIiIiIgdKBUCRALRq1ar6j1UAbHo8Hg8/vu5d/pGY2ox2XfsaThQY3G43OTnZAMRHRxPlDD/oa0ZGhRMVGwHAtnwtAhHZH5ZlccmYibRI9Raq/vfRJ3z/8y9mQ4UIh93Oo1dfgcNup7q6mhtuuEEdliIiInJQVAAUCUC+d/rtDjtpbdINp5HGtv6XdWxa5h0B7zd8DJaWwACQm5dHXW0dAOlJCX67rq8LMCs/Hx0DKLJ/IpyRXHfmvURFxODxeLj+qWdZvz3bdKyQ0KNNG6484TgAFixYwEsvvWQ4kYiIiAQzvaoUCUC+BSBpbdJxhGnza1Pz42ve7j+7I4xDhhxrOE3gyM7yLv8Id4aRGBPjt+smp3nPASyvqqaorMxv1xVpKtKSmnHFKXdiYVFaWckl//eYloL4yXUnj6FDs0wA7rvvPjZv3mw4kYiIiAQrFQBFApCvA1Djv01PcW4x8z+fB0CP/kcSFXNwW25DRUlJCeXl5QBkJCZiYfnt2r5FIADb8nUOoMiB6NXhME478mIA1mZlaSmIn4SHhfHwJRdjWRYVFRVMmDCh/hxUERERkf2hAqBIgHG5XKxbtw6AZh21AbipmfbWj9TVeMdcB4w4zXCawLF9u7f7z2azkZrg36JodFwk4ZFOQItARA7G8UPO2W0pyBOffWE4UWjo16kjY48ZAcC0adN49913DScSERGRYKQCoEiA2bRpE9XV1QBkqgOwSamrqasf/23VsSeZrTsZThQYqqurKcgvACA1Pg6Hze7X61tYJO/sAtyal6dzAEUO0B+Xgkz+8GN+0FIQv5h45mm0TE0B4K677iInJ8dwIhEREQk2KgCKBBjf+C9oBLipWfjlAopziwE47OhTDacJHNnZ2fUjb+lJiQ3yGCkZ3uuWVFRQvHPUWET2X4QzkmvP/Gf9UpDrtBTEL6IjInjo4rEAFBUVcdttt5kNJCIiIkFHBUCRAONbAAKQ2T7TYBJpbN+9/A0AcYmpdO1zhOE0gcHtdtd3usTHRBPlDG+Qx0lp9nthcdOOHQ3yGCJNRXpScy0FaQBDe/bgzKHe3w1ffPEFn3/+ueFEIiIiEkxUABQJMKtWrQIguUUK4VERhtNIY1n381rW/+w9+7H/kSdjs/t3zDVY5ebmUlfrPRMxI7Fhuv8AomMjiIrxfr9tyc1tsMcRaSq0FKRhTDrvbFLjvUcW3HrrrRQWFhpOJCIiIsFCBUCRAKMNwE3Tdy9/C4AjzMmhQ483nCZwZO8cHYxwhpEQE91gj2NhkZLpLTBuyc3DrYMARQ6aloL4X0J0NA+MvRDwvkFy9913G04kIiIiwUIFQJEA4vF46keAVQBsOgqzC1n4xXwAeg48hqgY/265DVbFxSWU7zyPLz0xEQurQR8vdWcBsKqmhh1FxQ36WCJNgW8pSPPUNoCWgvjLsf37cvxh/QF45513mDp1quFEIiIiEgxUABQJINnZ2ZSVlQHQrGNzw2mksUx98wdcdS4ABmj5R73s7dsBsNtspCY0fFE0JTOh/uPNOgdQxC8inJFcd+a99UtBrn/6WTZma4Ptwbr3ovOJj/Z2RU+YMKH+uYOIiIjInqgAKBJAdl0A0qyDCoBNQU1VDVPf+BGANl36kN6ineFEgaG6upr8gnwAUhPicdga/kzE8Agn8UkxgM4BFPEn71KQO7CwKKmo5NJHHqeiqtp0rKCWGh/PP84/F4AtW7bwwAMPGE4kIiIigU4FQJEAstsG4I4aAW4K5n48m9L8EkDdf7vanp0NO4/hS09MaLTH9XUBZuXnU+dyNdrjioS6Xh0GcPKwiwBYtXUrt7zwIh6dtXlQTjt8MMN79QTgxRdfZP78+YYTiYiISCBTAVAkgPg2AMenxhOTEGM4jTQ0t9vN189/BUBSegs69x5sOFFgcLnc7Ng5IpgQE02kM7zRHtu3CKTO5WZbfkGjPa5IU3DiEefRp5P359zn8xbwwlffGE4U3CzL4sGLLyI6IgKPx8MNN9xAVVWV6VgiIiISoFQAFAkgK1asAKB5pxaGk0hj+PXHJWxfmwXAoJFnYNn0IxkgLy+Xuro6ANKTEhv1sZPTE7DZvMtGNuXonDIRf7JZNi496VYykry/4x585z3m/LbCcKrg1iIlhdvOOh2AtWvXMnnyZMOJREREJFDp1aZIgPB4PKxcuRKA5p1VAGwKvnpuCgBRMfH0HjTKcJrAsX3n8o8Ip5OEnYfcNxaHw05yRgIAG7SoQMTvoiJiuPbMfxLhjMTldnPV40+RlZ9vOlZQu+Doo+jfqRMAjz/+OEuXLjWcSERERAKRCoAiAWL79u2UlHjPgmuhAmDIW79kHavmeQu+/Y86hbBGHHMNZMXFxVSUVwDe7j8Lq9EzpDdPBqCgtJSisvJGf3yRUNc8tQ3jx0wEvN9nlz3yBFU1NYZTBS+bzcbDl4wjPMyBy+Xi+uuvp7a21nQsERERCTAqAIoECF/3H2gEuCn4+jnv2X+OMCf9jzzJcJrAkb09GwC7zUZqfJyRDOktk+s/VhegSMPo33Uoxw0+G4BfN2zgrldf11KQg9C+WSY3nnoKAEuXLuWpp54ynEhEREQCjQqAIgFi9wJgc4NJpKHlbsll4RTvtsbeg48lOjbBbKAAUV1dTX6BdxQwNSEeh81uJEd0bCQx8VEAbMjONpJBpCk4/ciL6d72UADenT6TN3+cZjZQkLvsuGPp0aY1AP/5z39Yu3at4UQiIiISSFQAFAkQvgUgyc2TiYyNMpxGGtK3L36Nx+0By2LQMaebjhMwtmdnw84GoPTEBKNZ0lt4uwC35uVRU1tnNItIqLLZ7Fx56iSS49MB+Mdrb/CTilYHzGG3859LL8Zht1NdXc3111+P2+02HUtEREQChAqAIgFi1apVgMZ/Q115UTkz3pkGQOfeg0nOaGk2UIBwu93s2Ll1Nz4mmkjDZyL6CoAut5vNO3KNZhEJZTFR8Vx7xj2EOZzUulxc/ugT5BYXm44VtLq3bs2VJxwHwIIFC3j55ZcNJxIREZFAoQKgSABwu90qADYRP77xPdUV1QAMHnWW4TSBIzcvj7qdnXYZiYmG00BSWhxhTgcAG3I0BizSkNpkdmLscTcCkFNYxPVPP4dLnWsH7NqTTqRDs0wA7rvvPrZs2WI4kYiIiAQCFQBFAsDmzZupqPBuPtUG4NBVXVnNty98DUCL9t1p2aGH4USBI3v7dgDCnWEkxEQbTuPdqpnaLAnwLgLRcgKRhjWk90iGH3oCALOWLefxTz83nCh4RTidPHzJxViWRXl5ORMmTNDPMBEREVEBUCQQ7LYARAXAkDXjnemUFpQCcMRx52FZluFEgaGkpJTysnIA0hMTsQiMfxffNuDyqiq2FxQaTiMS+s4ddTUt09sD8H8ffcLs5b8ZThS8+nXqyNhjRgAwdepU3nvvPcOJRERExDQVAEUCgK8AaFkWmR2aGU4jDaGupo6vnp0CQFrzdnTsNdBwosDh6/6z2SzSEuINp/ldRotkbDZvMXLNtizDaURCn9Ph5OrT7ibCGYXH4+G6p55hR1GR6VhBa+KZp9EixftGxl133UVurs4zFRERacpUABQJAL4CYFrrNMIjzS4/kIYx95PZFGTlA3D4ceeq+2+nmpoa8vO9/y4p8fE4bHbDiX4X5nTUjwGvydqmETqRRpCR3IKLT5gAQG5xCdc99azOAzxA0RERPDjuIgAKCwu56667DCcSERERk1QAFAkAvgKgxn9Dk9vlZspT3vOsElOb0b3fcLOBAkj2LufrZSQmmA3zFzJbpwJQWlFJdmGR2TAiTcRh3YdzVL8xAMz5bQWPfPyp4UTBa3jvXpwyZBAAH374Id9//73hRCIiImKKCoAihtXV1bFmzRpAG4BD1eKvF5G93rtJdsixZ2OzB06Xm0lut4ecnRt246KjiAqPMJzozzJa7joGvM1wGpGm45xjrqR1RkcAHvvkM2YsXWY4UfC6+7xzSIyJAeCWW26hrKzMcCIRERExQQVAEcM2bNhATU0NoA7AUOTxePjiSW/3Skx8Mr0HjzKcKHDk5+dRW1MLQHoAdv8BOMPDSMlMBLznAGoKWKRxhO08DzAyPBqPx8P1Tz9LjrpwD0hyXBz/OP9cALZu3cpDDz1kOJGIiIiYoAKgiGErVqyo/7iFCoAhZ+n0X9m0bBMAg0aeiSPMaThR4Mje7u3+c4Y5SIqNNZxmz5rtHAMuqaggp1DbgEUaS1pSMy4+8WYA8ktKuenZ53HrPMADcsqQQQzr2QOA559/nsWLFxtOJCIiIo1NBUARw3zn/9kddjLaZhpOI/7k8Xj44nFv919EVCz9hp1oOFHgKCsro7S0FID0xEQsAncpSkarlPqlLauztA1YpDH17zq0/jzAmcuW8+LX3xpOFJwsy+LBiy8iMtyJx+PhxhtvrJ8+EBERkaZBBUARw3wFwPS2GTicDsNpxJ9WzF7O6oWrARgw4jScEZGGEwWO7du3A2CzWaQlxBtO8/ec4WGk7hwDXrVlK27NAYs0qrNHXEGzlNYA/Pu9D1i+aZPhRMGpZWoqt5xxGuCdPnjiiScMJxIREZHGpAKgiGG+AqDGf0OLx+Phk//7CICIqBgGjjjNcKLAUVtbS15eHuA9myrMHviF7+bt0wEoq6xky45cw2lEmhZnWDhXnnonDnsYNXV1XPvkM1RWV5uOFZTGjTyG3u3aAjB58uT6JWQiIiIS+lQAFDGoqqqK9evXA9oAHGp27f4beMzpRETFGE4UOLJzcvC4vV106YmJhtPsm8xWKTjCvNubV2zeYjiNSNPTMr09Zxx9KQBrs7Zz31vvGE4UnOw2G/8ePw6H3U5NTQ033XSTzlUUERFpIlQAFDFo1apVuFwuAFp2a2U4jfjLH7v/Bhyt7j8fj8dDTrZ3+UdsVCQxERGGE+0bh8NOszbeZSBrsrKorq0znEik6TnmsFPo0b4/AG/8MJVvF/9kOFFw6ta6FVccPxqAefPm8frrrxtOJCIiIo1BBUARg5YtW1b/ccuuKgCGCnX/7Vl+QQE11d6D54Ol+8+nZfsMAOpcLtZs22Y4jUjTY7NsXDJmIrFRCQDc8vxLZGsz9wG57uQxtMvw/kz75z//WX8uq4iIiIQuFQBFDFq+fDkAkXFRpLRIMZxG/EHdf38ve+eLzDCHg6TYWMNp9k9SWjxRsd6Oxd82bzacRqRpSohJYvyJNwNQWFbGxOdfwqPFPPstwunkX+PHAlBaWsrtt99uNpCIiIg0OBUARQzyFQBbdmmJZVmG04g/qPtvz8rLKygpLgEgLTEBW5B9zVuWRct23o6ZbXn5FJWVG04k0jQd0mkQR/UdA8C0X5fy9rTphhMFp4Fdu3DOkcMAmDJlCl988YXhRCIiItKQVAAUMcTj8fxeANT5fyFB3X9/Lzvb2/1nWRbpCQlmwxygFju3AQMs3bjRXBCRJu7MEZeRltgMgPvefIctudrOfSDuOPtMUuPjAbj11lspLi42nEhEREQaigqAIoZs27at/ol2K53/FxLU/bdndXV15O58gZ4cF4vT4TCc6MBEx0aS1jwJgGUbN1G3c4mPiDSuCGckl4yZiIVFeVUVNz/3orbZHoD46GjuH3sBADt27OCf//yn4UQiIiLSUFQAFDHE1/0H6gAMBer++3s5OTtwu7wvzoNt+ccftenSHICqmhpWbdEyEBFTOrXqyciB3p+1c1es5NXvfzCcKDiN7t+PY/v1BeD1119n3rx5hhOJiIhIQ1ABUMQQ3wZgy2bRonNLw2nkYC2d/mt999+AEer+25XH8/v4b3REBDGREYYTHZz05kn1y0B+Wb8e7R8QMee04ReTmex9E+2hd95nQ3a24UTB6d4Lzycmwvtz7ZZbbqGmpsZwIhEREfE3FQBFDPF1AGa0y8QZ4TScRg6G2+3mw4ffAyAyOo6BI9T9t6vCwgKqq6oBSE9KwCK4ln/8kWVZtO3s7QLcUVREdmGB4UQiTZczLJxLT7oVy7JRVVPDTc++gEujwPstIymRm8/w/u5auXIlTz31lOFEIiIi4m8qAIoYUr8AROf/Bb1FXy5k07JNABx+3Lnq/vuD7O3ejhyHw05KXJzhNP7RskMGdrv3V+gv69YbTiPStLVr3oXjB58NwOI1a3n+y68NJwpOFx1zND3btgFg8uTJbNSiIxERkZCiAqCIAeXl5WzYsAHQApBg56pz8dHkDwCITUih/5Enmw0UYCorKykqKgIgLSEBmxUav3ac4WE0b+fdCLx6WxYlFZWGE4k0bScNvYAWaW0BmPzhR6zfrlHg/WW32Xjo4rHYLIuqqiomTpyIR2cciIiIhIzQeCUmEmRWrlxZ/6RaC0CC2+wPZ5G9znu+3dATLyDMGW44UWDZvt37b4MF6QkJRrP4W7tuLQDvCPjiNWsMpxFp2sIcTi4dcys2y0Z1bR23vviytgIfgF5t2zB25AgApk6dyieffGI2kIiIiPiNCoAiBuy6AbiVCoBBq6aqpn7zb1Jac/oMOc5wosBSV+dix44dACTFxhIeFmY4kX/FJUST2ToVgGUbN1JWWWU4kUjT1jqzI8cOOhOA+StX8fa0GYYTBaebTz+VjJ3b2idNmkRxcbHhRCIiIuIPKgCKGODbAByTGENCeqLhNHKgpr7xIwVZ+QAMP2kcdofDcKLAsmNHDm6XtwPH92Iy1HTs6S3g17nc/LR2reE0InLy0AtJT/Iu6Xnw7XfJLig0nCj4xERGcu+F5wOwY8cOHnjgAcOJRERExB9UABQxYNcFIJYV3BtRm6rKskq+ePIzANJbtKNH/yMNJwosHo+nfvw3OiKC2KhIw4kaRkJyLOktkgH4dcNGKqtrDCcSadqcYeGMPf4mAEorK5n06ms6x+4AjOp3KCP6HALAK6+8wqJFi8wGEhERkYOmAqBII3O73fz222+ANgAHs29f/JrS/BIAjjrlEiybfpzuqqCggOqqagAykhKxCN1Cd8de3u/j2ro6FqsLUMS4rm0OYVif4wH4dvHPTFmw0HCi4GNZFvdddAFR4eF4PB5uvvlmamtrTccSERGRg6BXrCKNbPPmzZSVlQFaABKsygpL+fq5LwFo2b47HXsNNJwo8Pi6/8IcdpLjYg2naVhJqfGkNvOOOP+8dh2l2ggsYtyZIy4jIcbbnXv3q29QtPP3ruy75inJ3HTayYB3cuG5554zG0hEREQOigqAIo1stwUg6gAMSp899imVpd4iz1GnXqIx7j8oKyunpNjbHZmWmIjNCv1fNV0PbQdAncvF3BUrDacRkeiIGC4YfR0AeSUl3P/Wu4YTBaeLR42kW6uWADz88MNs2bLFcCIRERE5UKH/qkwkwPgWgNgddpp1bG44jeyvHRtz+OG17wDo2HMAbTofYjZQANq+PQvwjpClJyaYDdNIEpJjadEuHYDfNm9mR5G2ZoqY1rfL4fTrOhSA92bMZM5vKwwnCj4Ou52HLh6LZVlUVFRw22236UxFERGRIKUCoEgj+/XXXwFo1qk5YeFhhtPI/vrg4fdw1bqwLBsjTr/cdJyAU1NTS15eHgAp8XE47U1nM3KXPm2x2W14PB6mLlmiF8kiAeD8Y68lMjwagDtffpVqnWO33/p0aM8FR3sXXX377bdMmTLFcCIRERE5ECoAijSyJUuWANCmZ1vDSWR/rf1pLQu+mA9AnyNGk9Zc/z/8o+ycbDxub+ErIzHRcJrGFRUTQcce3rH+rPwClm3cbDiRiCTEJHHGUZcAsG57Ns99+ZXhRMFp4pmnkxofD8Dtt99OaWmp4UQiIiKyv1QAFGlE2dnZ5OTkANCmZxuzYWS/eDwe3r3/LQDCwiMYPmac4USBx+32kJOdDUBcVBTRERGGEzW+Dj1bER0XCcCs5cspr6oynEhEhh96PG2bdQbgsU8+Z9OOHYYTBZ+4qCjuueA8wPtc5qGHHjKcSERERPaXCoAijcg3/gvQuoe6x4LJT98sYs2i1QAMHnkWsQnJhhMFnry8XGprvON1GUlNq/vPx2630XNARwCqamr4/udf0CSwiFk2m52LjrsBy7JRXVvLXa+8rhH9A3DCgP4M79UTgBdffLF+okFERESCgwqAIo3IVwC02W206qYNwMGirraO9x7ybpCMiU9i8KizDCcKTNuztgMQ7gwjMTbGcBpz0pol0bpTJgDrt2ezbOMmw4lEpE1mJ0b0PxmAab8u5cuFi8wGCkKWZXHf2AsIDwvD7XZz880343K5TMcSERGRfaQCoEgj8r1b3qxjc5wRTsNpZF9Ne2sqORu8o63Dx4zFGRFpOFHgKS4uoby8HPCe/WdhGU5kVvd+7YmK9Y5AT/v1V3KLSwwnEpFTh48lIdbbvX3P629SWlFpOFHwaZ2WxvUnjwHgl19+4ZVXXjEbSERERPaZCoAijej3BSBtzAaRfVZZWsGnj3wMQEpma/ocfpzhRIEpe7u3+89us5GaEG84jXmOMAeHHtEVm82izuXii/kLtH1UxLDI8GjOHXk1ADmFRUz+8CPDiYLTZcePpkOzZgA88MADZO88+1VEREQCmwqAIo1kx44dbN9ZJNH5f8FjytNfUJrv7d465ozLsdnthhMFnqqqKvIL8gFITYjHYdO/EUBSajzd+rUHoKisjCkLFuJyuw2nEmna+ncdSs/2/QF45dvvNaJ/AJwOBw+OuxCA0tJS7r77bsOJREREZF+oACjSSHZdAKIOwOBQsD2fb57/CoA2XfrQsedAw4kCU/b2bPAAFqQnNs3lH3vStmtzWrRLB2BTzg4tBRExzLIsLjj2OsIcTtweD7e/9IoK8wdgYNcunH7EEAA+/vhjpk6dajiRiIiI7I0KgCKNxDf+a9ksLQAJEu//6z1qq71jm8ecfjmW1bTPtfsrdXUucnJyAEiMiSHSqbMtd2Vh0XtwZ5IzEgD4bdNmpv36q4qAIgalJTXjxMPPB2DJ+g28PXW64UTB6c5zziI+OhqAiRMnUlmpMxVFREQCmQqAIo1k6dKlAGS2b0Z4VIThNLI3a39ay9yPZwPQa9AxNGvT2XCiwJSTk1O/BTIjSd1/f8Vut9H/yO7EJXpfKP+ybj0/LlmCW1VAEWNGDzqDjKQWADz8/gcUlpYZThR8kuPiuOPsMwHYuHEjjz32mOFEIiIi8ndUABRpJL8vANH5f4HO7Xbz1j2vAxAWHsHRp15qOFFgcrs9bN+eBUB0ZARxUVGGEwUupzOMQSN71xcBf12/gc/nzaemts5wMpGmKczh5PxjrwWgqKych9//wHCi4HTWsCPo27EDAI899hhr1641nEhERET2RAVAkUaQl5fH1q1bAZ3/FwzmfjyH9b+sA+Dw0ecRl5hqOFFgysvPo6a6BoDMpCQsNCL9d8IjnAwadQgJKbEArN+ezbszZlBcXmE4mUjT1KN9P/p2OQKAt6ZOZ8n6DYYTBR+bzcZDF1+E3WajpqaGiRMn4lF3s4iISEBSAVCkEfz888/1H7ft1c5gEtmbqvIq3v/XuwDEJ6czaOQZhhMFru3bvN1/4WFhJMfFGk4THMLDwxhy7CE0a5MGQF5xCW/+OJWVW7YaTibSNJ1zzJU4HeF4PB7ufvV13FoIst+6tGzJJaNHATBz5kw++EDdlCIiIoFIBUCRRvDTTz8BYHfYaa0OwIA25anPKcopBGDkGVcS5gw3nCgwFRUVUV5eDnjP/lP3376z2+30HdqVzr1bA1BdW8tXCxfx9cLFVNXUGk4n0rSkJKRzwuHnAvDzuvW8N2Om4UTB6cZTTqZ5cjIAd999N0VFRWYDiYiIyJ+oACjSCHwFwBZdWuKM0JbUQJW7JZevnvsSgNadetG171DDiQJX1s7uP7vdRlpCvOE0wceyLDof0pZBI3sTGeUtMq/YsoXXvv+BdVnZhtOJNC3HDjqTtMRmAPzr3Q8o2vnmhuy7qIhw7r3Iu1k5Ly+P+++/33AiERER+SMVAEUamMfjqR8BbndIe8Np5O+89+Db1FXXgmUx6uxrsCx1tf2V8vKK+u6O9MRE7Da72UBBLDUzkWFj+tGsjfecyfKqKj6bN4+vFi6icuf5iiLSsJwOJ+eNugaAgtJSJn/wkeFEwemYQ/swqu+hALz66qssXLjQcCIRERHZlQqAIg1s/fr1FBZ6R0rb9VEBMFCtnLeChVMWAHDoEceR2aqj4USBKytrG+DtYstITDAbJgQ4w8PoN6w7/YZ3JzwiDICVW7by2vc/sGZnp6WINKzeHQdwSMdBALz+/Y8s37TJcKLgdM8F5xEV7u1qvuWWW6ir06ZzERGRQKECoEgD23UBSLveKgAGIrfLzVv/fAOA8Mhojjp5vOFEgau6poa83DwAUuLjcDrCDCcKHc1apzL85MNo3ta7IKSiupov5i9gyvyFVFRVG04nEvrOHXUVDnsYbo+HSa9oIciBaJ6SzE2nnQzA8uXLef75580GEhERkXoqAIo0sMWLFwMQERNBZodMw2nkr8x8bzqbl3u7PYaecAHRcYmGEwWu7du34/F4AMhMSjKcJvSEh4fRd2g3+h/Zg4hI73mhq7dt47UffmTVlq3s/KcXkQaQltiM44ecA8DiNWv5aPZcw4mC07iRx9C1VUsA/vWvf7Ft2zbDiURERARUABRpcL4FIG17tcNm07dcoKkoqeCDh98HICm9BQOOPtVwosDlcrnIyfYuqEiIia4f8xL/y2yVwvCT+tOyfQYAldXVfLlwEVMWLKCmViN1Ig3l+MFnk5Lg/b576J13KamoMJwo+IQ5HDw47iIAKioquPPOOw0nEhEREVABUKRBVVdXs2zZMgDa6/y/gPTpIx9Rml8CwMgzrsSukdY9ysnJwVXnAtT91xic4WH0ObwLA47uScTOTcFrtmXx7owZlFRUGk4nEpqcYeGcO/IqAHKLS/jfhx8bThSc+nbswLlHDgdgypQpfPPNN0bziIiIiAqAIg1q+fLl1NR4N3m21QbggLN11Ra+e/lbANp370en3oMMJwpcHo+H7VnbAYiOiCAuOspwoqYjvUUyR57Uv35TcF5xCe9Mm0Z2QaHhZCKhqU+nwfTqcBgAr373Ayu3bDGcKDjddtbpJMfFAnD77bdTXl5uOJGIiEjTpgKgSAPyjf8CtFcBMKB4PB5ev+tV3C43NruD0edch2VZpmMFrNzcXKqrvYsoMpMTsdC/VWMKczroO7QbnXq1BqC8qpoPZ80mK7/AcDKR0GNZFueNugaHPQyX282kV16vP/tU9l1CTAyTzj0bgC1btjB58mTDiURERJo2FQBFGpCvAJiUmURCuhZLBJL5n81l1byVAAwaeSbJGS0NJwpcHg9s2+o9xD3cGUZyXJzhRE2TZVl06dOWPod3wbIsaurq+Hj2HBUBRRpAelJzRg86E4AFq1bz6dx5hhMFp1OHDGZQ1y4APP300/z222+GE4mIiDRdKgCKNKCFCxcC0K5PB8NJZFeVZZW8c//bAMQlpjL0hPMNJwpsBQX5VFZ6z5xrlpys7j/DWrbPoO/Qrths3iLgp3PnkV9SajqWSMg5Ycg5JMWlAXD/W+9SqrM395tlWTww7kLC7Hbq6uq45ZZbcLvdpmOJiIg0SSoAijSQnJwcNm7cCEDHfp3MhpHdfProxxTleM9PG3XW1TjDIw0nCmy+7r8wh4PUeHX/BYJmbdLoc3hXLAuqamr4ZM5cyquqTMcSCSnhzkjOGXklADuKinj0k08NJwpOHZo148oTjgNgwYIFvPXWW4YTiYiINE0qAIo0kAULFtR/3LF/R4NJZFfbVm/juxe92wjbde1L175DDScKbEVFRZSVlQGQmZyEzdKvjUDRvG0a3ft7u4tLKiqYMn8hLnXWiPhVvy5H0L1dXwBe+uY7Vu18Q0T2zzUnnUjrNG835b333kteXp7hRCIiIk2PXsmJNBBfAdAZGU6rbq0NpxHwLv544+5XcdW5vIs/ztXij73xdf857HbSE+INp5E/ate1BW27NgdgW34+039dajiRSGixLIvzR12L3eagzuVi0iuvaSHIAYhwOrl/7AUAFBYW8s9//tNwIhERkaZHBUCRBjJ//nwA2h3SDkeYw3AaAVjw+XxWzPEeQD7wmNNJyWxlOFFgKy0tpbi4GID0pETsNrvhRPJXuvdrT3J6AgBL1m9gbdZ2s4FEQkxmSsv6hSDzV67i49lzDScKTsN69eTEgYcB8M477zB79mzDiURERJoWFQBFGkBFRQVLl3o7cTr21/l/gaCqvIp37n8TgNjEFIadcKHhRIHP1/1ns1lkJGqLdaCy2Wz0HdaN8EgnAN///IvOAxTxsxMPP5fkeO8I6wNvv0NJRYXhRMHprvPOITbSe+7uxIkTqampMZxIRESk6VABUKQB/Pzzz9TV1QFaABIoPnv0EwqzvYs/Rp5xJc4ILf74O+UVFRQUFACQnpBImF3df4EsItJJ78GdAaisrua7n35GU4oi/hPujOTckVcDkFtcwuQPPjacKDhlJCZyyxmnAbB69Wqeeuopw4lERESaDhUARRqAb/zXsiw6HKoFIKZlrdnGNy98BUDbLn3o3v9Iw4kCX9bO7j/LsshIVvdfMMhokUzrTpkAbMjO4dcNGwwnEgkth3YeQq8OAwB49bvvWb5pk+FEwemCEUfRs20bACZPnszGjRuN5hEREWkqVAAUaQC+BSDNO7cgKi7KcJqmzePx8OqdL+9c/GFn9LnXa/HHXlRWVZGblwtAanwc4Y4ww4lkX3Xv34HoOG936+zlv1FWqVFgEX/xLgS5Boc9DLfHw6RXXsetzdv7zW6z8dDFY7FZFlVVVdx2221arCIiItIIVAAU8TO3283ChQsBjf8GgtkfzGTVvJUADDzmDFKbaSPz3mzbshU8gAWZycmm48h+cDjs9B7kHQWurq1l5rJlhhOJhJa0pGYcP+QcABavWcsHM7XI4kD0atuGC485GoAffviBzz//3HAiERGR0KcCoIifrVy5kpKSEkALQEwrKyzl3QfeBiA+OZ1hJ2rxx95UVlWRm+vt/kuJiyPS6TScSPZXSkYCLdunA7Byy1Y278g1nEgktBw/+GxSE73j9g++8x5FZWWGEwWnm08/lbSEBADuvPNOSktLzQYSEREJcSoAivjZvHnz6j9WB6BZ7z30DqUF3hcUx513Pc5wLf7Ym21btnpHsSxonpJiOo4coK592xPmdADw4y9LqHNpTFHEX5xh4Zw36hoACkpLefj9Dw0nCk5xUVH84/xzAcjOzuZf//qX4UQiIiKhzWE6gAQH+35uAN3f24eSOXPmAJDcPIW0Vmk6b+4g+P7tLMvCZtu/9ytWzV/JjHemA9C171A69x7s93yhprLy9+6/1Lh4IsNDvPsvhL81I6KcdD20Hb/OW01hWRlL1m+gX6cOpmOFKKv+/+rHfdPRp9MgDu08hJ9WzebNH6dxzpHD6N2und8fZ39/9wWbMYMG8N6MmUz/dSkvvPAC55xzDr179zYdK+T4npc35efn0jD0NSUSXCyPTt0V8RuPx0N6ejq5ubkMO/tIrn7iWtORmqS6mlomHnkzW1dtITwiiusfepO4pFTTsQLeqpWryM7OBgv6dOgQ+gXAEOdxe5j2+SKK80uJcDq59LjR+v+piB/lFmUz8fELqKmtpk+H9nz90APY7aFdsGsIG7KzOeKGCVTV1NKvXz/mzZunooKIiEgDUAeg7JPCwsK93iYuLg673Y7L5ao/A6+pWbFiRX0HVafDOlFVpQ2cB8OyLMLDw6murt6vDYGfP/EpW1dtAeDIU8YTFZdIXV1dQ8UMCZWVVeTk5ADe7r/wMEdIbrfctZsmFP9+f9StbzvmfruEqpoa5ixfzrBePU1HCkEWDoedujoX3u050lQkxqQw5vDz+WDqi/y8dh0vf/015x991EFfNzw8HMuy8Hg8VFdX+yFpYMtMSOC6k0/i4fc+YNGiRTz88MNcccUVpmOFFLvdTlxcHCUlJbhcLtNxJMjpNZ//JSYmmo4gTYQKgLJP9vfJQlN9cjFjxoz6jzsP7NokCgwNyVes8Xg8+/xvuWPTDj75v48AyGzVkf5HnrRfxcOmauuWLfVn/zVLSW4adYwm8HdMzUwkrXkSO7YV8Mu69fRu14746CjTsULK72O/Hv2saYJGDTydWUu+IbtgKw++/S4j+hxSv9jCH5rK84hLR4/i49lzWLMti/vuu48RI0bQtm1b07FCjsvlarLP0aVh6OtJJLhoTkHEj2bNmgVAastUUlpogUJj83g8vH7XK9RW12JZNk64cAI2m8aI9qZKm39DWre+7bAsC5fbzezlv5mOIxJSwhxOLjzuBgBKKir55xtvmQ0UpMLDwvjvpeOxWRaVlZXcdNNNTab4KSIi0lhUABTxE7fbzdy5cwHoMqir4TRN08Iv5rN02q8A9D/yJJq16Ww4UXDYulWbf0NZXGIMLTukA7Bq61byijWuI+JP3dr2YUivkQB8Pm8BP/z8i9lAQapPh/ZcOnoU4H1D9fXXXzecSEREJLSoACjiJytWrKCgoACALoO6GU7T9JQVlfHGP14DIDYhhaNOGW84UXCoqqoid4e6/0Jdp95tsNm8s6rzVq40nEYk9Jx9zBXERsUDMOmV1ynXGcAHZMLpp9I2w/uGxT333MPWrVsNJxIREQkdKgCK+Ilv/Beg62B1ADa2t+99k5I8b2fT6HOvIzwy2nCi4LBll7P/1P0XuqKiI2jVMROANduyyC0qNpxIJLTERsVzzjFXArAtP5//ffix4UTBKcLp5OFLLgagrKyMCRMm6GxNERERP1EBUMRP5syZA0B6m3SSMpMNp2lals1YyuwPZgLQrd8wuh56hOFEwaGioqL+7L/U+Hh1/4W4jr1aY7N7f+3PX7XKcBqR0DOo5wi6t+sLwItff8uvGzaaDRSkBnTpzNhjjgbgxx9/5N133zWcSEREJDSoACjiBy6Xq74A2Hmguv8aU1V5FS/f9iIAEVGxjD7nOsOJgsfmzZvBA5Zl0TxFRetQFxkVTutdugB3qAtQxK8sy+Ki0TcQ5nDi9ni47YWXqdOGzANy61ln0DLV25U+adIksrOzDScSEREJfioAivjBkiVLKCoqAqDbEJ3/15g+fPg98rfmATDqrKuIiU8ynCg4lJaWUZDvPbMyPTGBiDB1/zUFHXq2+r0LUGcBivhdWlIzTh56IQDLNm3i5W++M5woOEVHRPDv8d5R4OLiYiZOnKhRYBERkYOkAqCIH0ydOhXwvvvf/YiehtM0HWsXr+H7V7wvrtp370fvwaMMJwoemzdvAsBms2im7r8mIzIqnNadvF2Aa7O2qwtQpAGMGngGLdPaAfCfDz5iY3aO4UTB6fAe3TjnyGEAfPXVV3z00UeGE4mIiAQ3FQBF/ODHH38EoE3PNsQmxRpO0zTUVtfy0i3P4/F4CAuP4IQLJmBZlulYQaGouJjinYWfjKQknHaH4UTSmDr2+L0LcOGq1YbTiIQeh93BuBMmYFk2qmpquOWFl3C73aZjBaU7zzmLzCRvZ/+tt97Ktm3bDCcSEREJXioAihykkpISFi9eDECPYb0Mp2k6Pn/iU7LWZgFw9KmXkpCSYThR8Ni8ydv9Z7fbaJaskemmJiIqnFYdvN8va7KyKCwrM5xIJPS0a96F0QPPAGD+ylW89v2PhhMFp7ioKP572XjAOwp83XXXqZgqIiJygFQAFDlIM2fOxLXzkO8eQzX+2xi2rNjMlCc/B6BF++70P/Ikw4mCR35+AWWl3oJPs+RkHDa74URiQvvuLbEsC4/Hw+I1a03HEQlJJw8fS2ZyKwAeevc9Nu3YYThRcDqiR3fGjTwGgBkzZvD8888bTiQiIhKcVAAUOUi+8/8iYiJof2gHw2lCX11tHS/e/DyuOhd2RxhjLroZm4pY+8Tj8dSf/RfmcJCRmGg4kZgSHRtJszapAPy2aTNllVWGE4mEHqfDyfgxt2BZNiqra5j4vEaBD9TtZ59Bh2be80vvu+8+Vq1aZTiRiIhI8FEBUOQgeDye+gJg18HdcYTpLLWGNuXJz9m4dAMAQ0+4gNRmbcwGCiI5OTuorKgEoHlKMnabfgU0ZR16eDuTXG43P61bZziNSGjq0KIbowaeDsDcFSt544ephhMFpwink0euvByH3U51dTVXXnklNTU1pmOJiIgEFb36EzkI69evZ/PmzQD0GNrDcJrQt/HXDXz22CcANGvThcNHn2s2UBBxuVxs2eL9Wo0Md5KWkGA2kBgXnxRDWgvvGZBL12+gqqbWcCKR0HTqsLFkJLUA4MF3NAp8oHq1bcMNp3iP/Fi6dCn/+c9/DCcSEREJLioAihwEX/cfQM+hWgDSkGqqanj+pmdx1blwhDk5Zfzt2Owa/d1X27Zto3ZngadlWio2bUwWvBuBAWrq6vh1wwbDaURCkzMsnPFjJmJhUVFdzY3PPE/dzrODZf9cdeLxHNqhPQCPPfYY8+fPN5xIREQkeKgAKHIQvv/+ewDSWqeR1ibdcJrQ9vHkD9m2eisAR51yCSmZrQwnCh41NTVkZXk3JsdFRZEYE2M4kQSKpPR4ktLiAPh57ToVJUQaSMeW3Rk9+CwAFq1ew9NfTDGcKDg57HYeueIyIsOduN1urrzySoqKikzHEhERCQoqAIocoLKyMmbNmgVA76P7GE4T2lYvXMXXz30JQOtOvRg44jTDiYLL5s2bcbu8B8+3Sk/FQt1/4mVh1Z8FWFFdzfKNmw0nEgldpw4fS6t077Kw//voU5asW284UXBqk5HOPeefB8CWLVu44YYb8Hg8hlOJiIgEPhUARQ7Q9OnTqa6uBqDPCBUAG0pVWSXP3fAMHo+HsPAIThp3G5aWV+yz8vIKduw8byolPo6YiEjDiSTQpLdIJjYhGoDFa9fgduuFtEhDcNjDuPyU2wlzOKlzubj+6eeoqKo2HSsonT18KGMGDgBgypQpvPzyy4YTiYiIBD69ihY5QF9//TUAkXFRdBrQxXCa0PXGva+zY1MOAKPOvIrE1EzDiYLLpo0bwQM2m0WL1BTTcSQAWZZF++4tASgur2DNznFxEfG/5qltOGvE5QCsz87m/rffMZwoOFmWxUMXj6V1WhoAd999N0uXLjWcSkREJLCpAChyAFwuV/35f72G98IR5jCcKDT98sPPfPuSt9DaocdhHDr0BMOJgkthYWH92UgZiYlEhDnNBpKA1aJdGpFR4YD3fDJN04k0nKP7nUTP9v0BeOOHqXz308+GEwWn2KhInrz2KsLsdqqrq7n00kspKyszHUtERCRgqQAocgAWL15MXl4eAIeMONRwmtBUlFPI8zc+A0BkdBwnXnQzljbX7jO328OGnVtdHQ47zVKSDSeSQGaz2WjXrQUAO4qK2JKbaziRSOiyLIvxJ95CTKR3Ac/Nz71IVn6+4VTBqVfbNtxxjne5yrp167j11lt1HqCIiMgeqAAocgB84782u41ew3sbThN63G43L0x4jtKCUgDGjL2FuMRUw6mCy/btWVRVVgHQMjUVh81uOJEEuladMglzeruZF61ZYziNSGhLiE1m/Jhb7CTwxAAAW89JREFUACgsK+PqJ56mtq7OcKrgdPGoYzjmUO9ZzO+99x6vvPKK2UAiIiIBSgVAkQPw7bffAtB5QBeidx6eL/7z7Ytfs2yG9yyfw448ma6HHmE4UXCpqalh65atAERHRJCWEG84kQSDsDAHbTo3A2BTzg52FBUbTiQS2vp0GsyxA88AYPGatfz3g48MJwpOlmUx+bL/b+++46uu7j+Ov+5IbvYiiwxCAihLNgqIIEsRRASVOnC11trxs462tq66R4fbqtW21tFaRS2KWAcoyBZk7xFIwsre8977/f1xyTUxgAGSfO+9eT8fjzxy8x33fkA5ued9z/gR6QmeDwrvuusuVq1aZXJVIiIivkcBoMgJys7OZvv27QAM0u6/bW7fpr2889h/AIjvmsHkK35hckX+J2dfDi6XC4CM5EQsaOq0tE5mn1SsNs9bgzUaBSjS7i4dfwM9UvsA8MK8+SxYu87cgvxUTEQEf73lFziCgmhoaOCHP/whhw4dMrssERERn6IAUOQEzZs3z/t4sNb/a1N11bW88H/P42pwYbMHcelP7iHYEWJ2WX6loqKC/Px8AOKjo4gKDTO5IvEnIaEO0nskAbAjbz9lVdUmVyQS2Ow2Oz+deQ/hIZEA3PrSy+w/ssawnJh+GRk8/qPrATh8+DA/+tGPqK+vN7kqERER36EAUOQEzZ07F4CM/hkkdk8yuZrAYRgGr931Kod2HwRg4qU3kpze0+Sq/Ith4N34w2q10i1R6ybKievRNx2LBdyGwTe7dptdjkjAi49J4obpvwGgtLKKHz/xNPUNWg/wZMwcPYrrz5sEwKpVq7jnnntMrkhERMR3KAAUOQF79+5l/fr1AAyfepbJ1QSWxW99ydJ3lwDQa8AIzppwickV+Z/8/HwqKyoBSI3vQrA9yOSKxB9FRIeRnB4PwOZ9e6mp0wgakfY2+LRRTB45C4Cvt+/gzr//w+SK/NfdV/6AM08/DYC///3vvPHGGyZXJCIi4hsUAIqcgA8//ND7+EwFgG1m3+Z9vH7vawBExyVx8Q9/i8WidetOREODk3379gLgCA6ia1ysuQWJX+vRPx2ABqeL9UdGlYpI+7p03I84PWMgAK9+8hmvffq5yRX5pyC7nb/8389Iio0B4Ne//jVLliwxtygREREfoABQ5AR88MEHgKb/tqXq8mqev+lpnHUNWG12Lrvp94RFaNfaE7Vv316cR6aMZSYnYbWoeZeTF5cQTZckz7/Ddbv34DyyqYyItB+7zc7PL7mXLtGe9xe//dvf+XqHNuM5GYkxMfzttlsIdQTjdDq57rrr2LVrl9lliYiImEo9RJFW2rdvH+vWrQNg+BSN/msLhmHwt1/9lfx9nk0rzpv1U1Kz+phclf8pKy8n/7Dn77BLVCQx4REmVySBoEc/zyjAmro6Nu/LMbkakc4hKjyGW694mOAgBw1OFzc9/SwHi4rNLssvDcjszjM//QkWi4WysjKuuOIKioqKzC5LRETENAoARVqp6fTf4ReeaWIlgeOTVz5mzf9WA9Bv2LmcOX6GyRX5H7fbIHv3HgBsVisZSYkmVySBIimtC5Exnl2k1+zchdswTK5IpHPo3vU0fjz9DgAKysr58VPPUqvdbE/K+cOGcuflnrUV9+7dyzXXXENNTY3JVYmIiJhDAaBIKzXd/Tepe7LJ1fi/zV9t4u1H3gKgS1I60677tdb9OwkHDuynuroagLTEBG38IW3GYrF4RwGWVVWxa/8BkysS6TxGDZjIhWdfAcCG7Gxue+kV3G63yVX5pxunTOaKcWMBz87AN954I06ndlkWEZHORwGgSCvs2rXr2+m/2vzjlOXvPcxffvYsbpebYEcos352P46QMLPL8ju1tbXk5eYBEB4aQvKRBc9F2kpqZhIhYQ4AVu/ciQYBinScWRNvZEBPz4yDeStX8djbc0yuyD9ZLBYeuvZqxg/ybLDyv//9j9tuuw1DDZqIiHQyCgBFWuHtt98GPG8iR8442+Rq/FtNZQ1P3/AkVWVVAMy44U4SUzNNrso/Ze/J9owIsUBmcjIWNIJS2pbNZiWrTyoAh0tKySssNLkikc7DarXx05n30C2pJwAvzpvP658vNLkq/xRkt/PC//2Mob08f5f//ve/efDBB02uSkREpGMpABT5Hm63mzlzPJ+69x7Zhy4pXUyuyH+53W5evvVF9u/wjFo7d/r19B482uSq/FNBQQElJSUAJMfGEhESYnJFEqgyTkshKNgOwGrtSCrSoUIdYdx6xcPERSUAcM8/X+fztevMLcpPhToc/ONXt3J6WhoAzz77LE899ZS5RYmIiHQgBYAi32PFihXk5uYCMGqmRv+dirlPvc83n6wBoM/QMYyZOtvkivxTfX0D2XuyAXAEBZGeEG9yRRLIgoLtZJzWFYC9hw9TUFZuckUinUtsZDy3Xv4IoY5w3IbBz5/7C+uP/A6QExMTHs7rv7mdtHjPh7kPP/wwzz33nMlViYiIdAwFgCLf45133gEgyBHEsAuGm1yN/1r+32XMfep9AJLSsrj4+t9isaoJOhnZe/Z4FzDP7JqEzWozuSIJdFl90rBaPVPM1+zUKECRjpaelMUvLv09NquNmrp6rvvTE+w5eMjssvxSclws/77zDrrGxQFw//338+KLL5pclYiISPtT71vkOGpra/nggw8AGHL+UEIjtVHFydi6bAuv3P4SAGGRMfzg5w8RHBJqclX+qbCoiKKiIgASYqKJCY8wuSLpDELCHKT1SAJge24e5Ud2nhaRjtMvayjXX3g7AEXlFVz52B/YX1hkclX+KSMxkf/ceQdJRzbPuueeexQCiohIwFMAKHIcn3zyCeXlnuluo2ZqrbqTsX97Hs/c+BSuBhf2YAdX/N/DxCZ0Nbssv9TQ4CR7zx7As6B5RlKiyRVJZ9KjXzoAbsPgm127Ta5GpHMaPfB8rpj0UwAOFBVz5WN/oKCszOSq/FP35CT+c+dvSYyJATwh4J///GftDiwiIgFLAaDIcbz55psARMVH0X/MGSZX439KDpXw52v/SE15NRaLlUt+fDdpWX3NLstv7c3OpqG+AfBM/bVr6q90oMjocJLTPetNbtq7j9r6epMrEumczh9xKdPHXANA9qHDzH78T5RWVZlclX/K6prMW3f+huTYWAAee+wx7rnnHtxut8mViYiItD0FgCLHkJOTw5dffgnA6EvHYLMrbDkRNZU1PHn9nyg+4JmeNPmKX2jH31NQXFxMQUEBAPHRUcRFRJpckXRGPfp7RgE2OJ2sz9YmBCJmuXjMNZx/1iUAbM3J5do//JmK6hqTq/JPPVNSePfeO8lI9Iyqf+mll7j55pu9a+2KiIgECgWAIsfw5ptveqeBjLniXHOL8TP1tfU8c8OT5GzeB8DI83/AmeNnmFyV/6pvaGD3kSmXQXabpv6KabokRhOXGA3Aul17cLpcJlck0jlZLBYun/RTxgy6AIC1u/dwzR//rPU5T1J6QgLv3nsnfbp5PuT4z3/+w1VXXUVFRYXJlYmIiLQdBYAiR+F0OvnXv/4FQJ9RfUnOTDa5Iv/hrHfy/E3PsHXZFgD6DR/HpEtuNLkq/7Z71y4aGhqn/iYTZLObXJF0Zo1rAVbX1bFp7z6TqxHpvCwWC9dNvZUR/ScAsGbnLq5+/E+UaTrwSUmMieE/d/2Wob16ArBw4UKmTJlCTk6OyZWJiIi0DQWAIkfx+eefc+jQIQDGavRfq7ldbv56ywusX7gOgF4DRjDjR7/DYlVTc7IOHT5MSXEJAIkx0Zr6K6ZLTu9CVGw4AF/v2InTpbWyRMxitdq4cfodjDxjIuAZCXjVY1oT8GTFhIfz79/9hotGnAXAtm3bmDx5MqtXrza5MhERkVOnXrnIUbz22msARMRGMOT8YSZX4x/cbjf/uOMVVs1bCUD33oO57Kb7sNmDTK7Mf9XU1rL3yDprjuAgMpKSTK5IxDPqqNcZGQBU1tSwZZ9Gx4iYyWq18eOLfsPZA84DYEN2Nlc++gdKKytNrsw/hQQH8+zPb+KXM6YDUFBQwPTp03n11Ve1Q7CIiPg1BYAi35GXl8eCBQsAOPuS0QSHBJtcke8zDIM373udr95eDEBqVh8u/8VDBAU7TK7MfxmGwa4dO3G73GDxLFJu00hK8REp3ROIiA4D4OsdO3Bpx0wRU1mtNn407VecM3Ay4Nmp+7KHHuNQSYnJlfkni8XC7ZfM4Omf3ogjyE59fT2//vWv+fnPf06VRleKiIifUm9S5Dv+8Y9/4D7SmR175XiTq/F9breb1+9+lQWvfgZAUloWV/3ycRwhYSZX5t/y8vK8i4+ndulCZGioyRWJfMtisdBrgGcUYHl1NVtzck2uSESsVhvXT7udsYOnArA9L49LHniYvYcOm1yZ/5px9ijeu/du0hPiAXjnnXe44IIL2L59u8mViYiInDgFgCJN1NTU8PrrrwPQf8wZpPRMMbki3+Z2u3n1t39j4eueEZMJKd2ZfesfCQ3XOnWnoqysnNxcT6ASHhpCany8yRWJtJSamUh4pCeY/nr7DtxuTY0TMZvVYuW6qbcyZeQPAMgtKGTmAw+zeZ827DlZZ2R256OH7mfC4IEAbN26lQkTJvDSSy95PzAWERHxBwoARZp49913KTkyXWbi9eeZXI1vc7vc/O32v7L4rUUAJKX34NpfP0lEdJzJlfm3hoYGdu7YAQbYrFZ6pqRgtVjMLkukBavFQq8zugFQWlXF9rw8kysSEfCM0J018UZmTbgRgMLycmY99Bgrt2nU2smKCQ/nb7f+kjtmXYrdZqOuro67776byy67jAMHDphdnoiISKsoABQ5wjAMXnnlFQASMxIZMG6gyRX5LmeDk7/e8gJL310CQEr307n29icIj4wxtzA/Zxiwa+cu6uvrAcjsmkRosNagFN+V1iOJsIgQAFZt345bC+SL+Iwpo37AD6f9CovFSkVNDbMf/yMfrFhpdll+y2q18vOLLuS/991Dz5SuACxevJjRo0fz97//HZfLZXKFIiIix6cAUOSIZcuWsXnzZgAmXnceVm24cFR11bU8c8OTrJi7HIC0rL5cfdufCI2IMrky/3fgwH7vCNTEmGjio6JNrkjk+KxWK736e0YBFldUsjNvv8kViUhTYwZdwC8u/T12WxB1DU5+8dwLPP/BPO1mewoGZHZn/kP3c/15kwCoqKjgjjvuYOrUqWzatMnk6kRERI5NCYfIES+//DIAIeEhjL5sjMnV+KaK4goev/xRNnyxHoCM0wYw+7Y/EhIWYXJl/q+iooKcfTkAhDqCyUhOMrkikdZJ65lMaLhnx+8V2zQKUMTXDO09mjuu/jMRoZ4P6h5/ew53/O0fNDidJlfmv0KCg7n/mqt4+67fekcDrlmzhokTJ/Lb3/6W4uJikysUERFpSQGgCLBr1y7mz58PwNmXnUNYlHaw/a6C3AIennk/e9btBqDPkHOYfesftdtvG2hwOtmxfQeGYWC1WuiVmorNouZZ/IPNZqXXGZ4dgYsrKtiWo7UARXxNr/R+3PPD50iOSwPgrS8Xc92fnqS8utrkyvzbiD69+fjhB7jtkhkE2+24XC7+9re/ceaZZ/LCCy9QV1dndokiIiJe6mGKAM8//7wnfLFZmXzDBWaX43P2bd7HQxffx6E9hwAYOvYiLr3p99iDtD7dqTIM2Ll9h7eT0D0piTCHw+SqRE5Mt17JhEV61gJcsW0bLu2MKeJzkuJSufv6Zzit2xkAfLVpM5c88Ag5+QUmV+bfHEFB3DJjOp8++hCThgwGoKysjHvvvZdRo0bx+uuv09DQYHKVIiIiCgBFOHToEG+//TYAZ04bQUK3RJMr8i1rPlnNI5c8QFlBGQDnTr+eqbNvwWq1mVxZYNiXs4/S0lLAs+5fQozW/RP/Y7VaOW1AdwDKqqrYvDfH3IJE5KgiwqL59VV/YET/CQBsz8tj2r33s3TzFpMr839ZXZP5222/5N+/+w39Mjxro+bk5HDbbbcxYsQIBYEiImI6BYDS6b300kveXVen3DTV5Gp8h2EYzHv+A5678WnqquuwWK1ceM3tjJ12DRaLxezyAkJhUREHjmyaEBEaQvfkJCzo71b8U3qPJCKiPUsCrNy+Had2xBTxSUH2YH5y8e+4eMy1AJRUVjL78T/xt/99qs1B2sDZ/foy78H7ePKmH5N5ZD3fxiDwrLPO4sUXX6S8vNzkKkVEpDOyGPpNL61QWFj4vdfExsZis9lwuVzenUx9XVlZGYMGDaKyspIB4wZy2z9/bXZJPqG+tp5Xf/t3lr23BICQsEhm/fQ+MvsM6dA6LBYLdrsdp9MZcJ2S6upqNmzYgNvlJshuo39mdxz2ILPLCnhW27efe7ldmqba1g7szWf1Is9IorFnnMGQXj1Mrqj9BXI7Jeaw24OwWDxLRDid7TtibM22Jbw89zFq62sAuPScs3nk+msJCdYSH23B6XIxd/kKnvnvB2QfOuw9Hh4ezpVXXskNN9xAVlZWu9dhs9mIjY2lpKQElz6ckVPkj30+XxcfH292CdJJaASgdGr/+Mc/qKysBGDKTy80uRrfUFZQxh+ueNQb/nVJTueGu/7S4eFfIHM6XWzbtg23y43FAj1TUxT+SUDompFAdJxnV/Cvd+ygXruMivi0ob1Hc8/1z5EYmwLAnK+WMuvhxzhUrE59W7DbbFwy+mwWPP4IT910o3dqcFVVFS+//DIjRoxg1qxZzJ07VxuGiIhIu9MIQGmVQBwBWFNTw9ChQykoKCBrcA/u+e99nX5q6+61u3j+p89SfKAIgB79hnHpT35PSFiEKfUE4sgawzDYunUrpSWlAHRLSiQlLs7cojoRjQBsf4fyili1YCPgmQp35umnmVxR+wrEdkrM1ZEjABtV1pTz4nsPs2nPagASoqP5y//9jLN6n94hr99ZGIbBym3b+dv/PuXTb9Y2azNiY2O59NJLufLKK+nfv3+bvq5GAEpb8rc+nz/QCEDpKBoBKJ3WG2+8QUGBZ+e7qT+b1qnDP8MwWPDaZzxy6YPe8O/M8TO48ubHTAv/AlV2drY3/IuPjqJrXKy5BYm0saS0OGITogBYvWMnNXX1JlckIt8nIjSKW694hMkjZwFQUFbG5Y88zgvz5uPWrt5txmKxMKJPb16+9WYW//lxfjL1AhKiPe1lSUkJL7/8MuPGjePcc8/lySefZPfu3SZXLCIigUQjAKVVAm0EYHV1NcOHDyc/P5+009N44JNHsFo7Zx5eV13Lq7/7O8vfXwaAPSiYqbNvZdDZk02uLPBG1hw8eJDsPdkARIaF0qdbOlZL5/z/ziwaAdgxCg6WsPzT9QAM6dmTsQPadjSLLwm0dkrMZ8YIwKZWbFrIP+b9mbqGWgAmDB7Ikz/5MTER+kCwPTQ4nXy5YSNvL/qKBevWt9hAqX///kyfPp2LLrropNcL1AhAaUv+1OfzFxoBKB1FAaC0SqAFgC+88AL33nsvAL946ZcMu2C4yRWZ49Cegzz3k6fJ254HQGxCCrN+ej/J3XqaXJlHIHWsS0pK2Lp1KxjgCA6if/cMgmx2s8vqdBQAdpyVCzZyOK8Im9XKNZMmEBMebnZJ7SKQ2inxDWYHgAAHCvbx3Jz7OVC4D4C0+C688H8/Z2CP9t+wojMrKCvjv0uX8+HKVazbvafF+f79+3P++edz/vnnM3DgwFZ/eK0AUNqSP/X5/IUCQOkoCgClVQIpAKyqqmLYsGEUFhbSrV8G9330YKcc/bdi7jJe/d3fqa30fMJ/2sBRXPzD3xIaHmlyZd8KlI51dXU1GzdsxOVyYbNa6dc9gzCHw+yyOiUFgB2nvLSKRR+sxjAMTk9LZcqZgflBS6C0U+I7fCEABKirr+HV+U+xfOPnAATb7dxz1eVcM3FCp142paPkFhQwf9Vq5q1cxfojsweaSkxM5LzzzuO8885jzJgxhB/nQxYFgNKW/KXP508UAEpHUQAorRJIAeCzzz7LAw88AMAv/3Ybgyd1rt1ta6tqeePef7Lkna8AsFisjLv4ekZfcCUWHwtCA6FjXVdfz6YNGz27+1mgd3oaMeGaRmUWBYAda/3y7ezbcRCAy88dG5BrXgZCOyW+xVcCQPCsEbxo7Xze+N+zOF2eWi4YPozHf3SdpgR3oJz8Aj5a9TWffbOWb3buwv2dtiYkJITRo0dz/vnnM2nSJFJTU5udVwAobclf+nz+RAGgdBQFgNIqgRIAVlZWMnToUIqLi8kckMm9Hz7QqT7F3rdpLy/84jkO7TkEQGRMPDNuuJPM3oNNruzo/L1j7XQ62bRxE9XV1QB0T04iOTbwAhB/ogCwY9XW1LHgvVW4nC5Su3ThsjHnEGhNrr+3U+J7fCkAbLTv4E6ef/cB8ksOANA1Lo6nbvoxI/v2Mbmyzqe4ooKF6zbw+dq1LN6wicra2hbX9O3bl4kTJ3LeeecxbNgwgoODFQBKm/GHPp+/UQAoHUUBoLRKoASATzzxBI8++igAt/3z1wwYN9DkijqGYRh8+rdPeOext3DWOwHPlN/p1/2GsMhok6s7Nn/uWLtcbrZs2UxFeQUAKfFd6JaQYHJVogCw421ft5ft6/cCMG3EWfRM6WpuQW3Mn9sp8U2+GAACVNdW8vrHz7B80wLA8//+z6dN5daZFxNk15q2Zqh3Olm5bTuff7OOz9euI7egoMU1sbGxTJgwgZkzZ3LWWWcRFRVlQqUSSPyhz+dvFABKR1EAKK0SCAFgUVERw4cPp6Kigh5DenL3+7/vFKP/yovKeeX2l9iw0LMjp80exKTLbuLM8TN8/s/vrx1rwzDYtm0bJcWefweJMdFkdk3Ggm//fXcGCgA7ntPpYuF7K6mtqSc2IoKrJ47H5mPLDZwKf22nxHf5agDYaNmGz3jt42eorfeMbh/UI4tnfnYT3ZMSTa6sczMMg10HDrJg7ToWrlvP1zt24nI3/z1ntVoZPnw4kyZN4rzzzqN3794+/15QfI+v9/n8kQJA6SgKAKVVAiEA/N3vfscrr7wCwB3/uZM+I/uaXFH72/Dlev7+q5cpzS8FoEtyOpfeeK/P7PL7ffy1Y71r1y7yD+cDEBsZwWlpqQr/fIQCQHPs23GA9ct3AHDugAEM7hk4O4n6azslvsvXA0CA/JIDvPj+I+zZvxWA8JAQ7rv6SmaNOUeBko8oq6pi8cbNLFi3ji/Xb6S4oqLFNWlpaUyaNIlJkyYxevRoQkNDTahU/I2v9/n8kQJA6SgKAKVV/D0A3L17N6NHj8bpdDJo4mBu+fvtZpfUruqqa/nPw/9m4esLvMcGjb6AC674P4Id/vPmzh871tl7sjl40LPpQWRYKH26pWO1BM5oJ3+nANAcbsNg8YerKS+pwhEUxHWTJhIWEhg7YftjOyW+zR8CQACny8ncxa8zb8mbGHj+3x8/aCCP/eg6rXfrYwxga24e81euYsHadWzel9PimtDQUEaPHu0NBNPS0jq+UPELvtzn81cKAKWjKACUVvH3APC6667jo48+wmqz8tCnj5LSK/X7b/JTu77Zxcu3vsjhbM9GHyFhkVx49a30Gz7O5MpOnL91rPfu3cuB/Z4F0sNCHPTN6IbdajO5KmlKAaB5Cg+VsuyTdQD0757BpCG+ufnQifK3dkp8n78EgI2279vAyx88TmGp531HVFgYD1wzmxlnj9RoQB9htVoJCQmhtrYWt9vNwaJiFq7fwMJ161myeTM1dfUt7hk8eDDTpk1j2rRpdO/eveOLFp/ly30+f6UAUDqKAkBpFX8OAFeuXMmFF14IwLjZE7j2ketNrqh9OBuczH36feY99wGG2/PPumf/M7noul8TGeOfv1T8qWO9b98+9uftByDUEUzfjG4E2bQouq9RAGiu1Yu2cGBvPhaLhcvHjiE5zv9HCflTOyX+wd8CQICaumreXvBXvljzoffY+UOH8MgPryUh2nc3G+ssvhsANlVbX8/KbdtZsHYdC9ZtOOpGIgMGDOCiiy5i2rRpZGUFzhIOcnJ8tc/nzxQASkdRACit4q8BoGEYTJkyhdWrVxMSHsLji/9MdELgvRHdv2M/f73lBfZt2gtAUHAI5836KUPHTvPrT9/9pWOdk5tLXk4uACHBnvAvWDsi+iQFgOaqrqrli/+uwuV0kxwXy+Vjx/h1GwX+006J//DHALDRpj2r+fuHf6a4/Mg6uBER3H/NVUwfOcLv/637s+MFgE0ZhsHOAwf4dPU3zF+1mk379rW4pn///lx00UVccskldOvWrT3LFh/li30+f6cAUDqKAkBpFX8NAN977z1+8pOfADDzV5dy0c0Xm1tQG3O73Xz290955/H/4KzzdBJSs/ow40d30iXJ/9du8YeOdW5uLrlHwj9HcBB9M7rhsAeZXJUciwJA8+3YsI9ta7MBOG/IEPp19+8OpD+0U+Jf/DkABKiureStz15k8bqPvcfGntGfh66/hoxE7RRshtYGgN+193A+81d9zfxVq9mQnd3i/FlnncWsWbO46KKLiImJacOKxZf5Yp/P3ykAlI6iAFBaxR8DwMrKSkaOHMmhQ4eI6xrHo1/+EUdoYCw6D1C0v5BXbv8rW5dtAcBqszF22rWMvuBKrLbAWHfO1zvWe/fu48B+z7RfR9CR8C9I4Z8vUwBoPpfLzZdzv6aqooZQh4NrJ04g1BFsdlknzdfbKfE//h4ANlq/cyX/nP8kxeWeKaWOoCBumTGdG6dMJkij5DvUyQaATeUWFDB/1Wo+WvU163bvaXYuODiYSZMmcdlllzFx4kQcjsB5vy0t+VqfLxAoAJSOogBQWsUfA8D77ruP559/HoCfv3Azw6eeaXJFbcMwDJa9u4Q3fv8aNRU1AMR3zWDGj35HSvfTTa6ubflqx9owIHvPHg4d8ix47ggOok+3dEKC/DfE6CwUAPqGQ3lFrFqwEYB+GRmcN9R/NwTx1XZK/FegBIDgWRvw/UWv8tmq9zEMT5t7eloaj/7wWoad1svk6jqPtggAm9p7OJ/3ly7j/aXL2Xv4cLNzMTExTJ8+nauuuopBgwZp6ncA8rU+XyBQACgdRQGgtIq/BYDbt2/n3HPPxel00u+c/vzqjTsC4g1IyaESXv3d31m/YK332FkTL2XCzBsICg68T1t9sWNtGAa7du2iIN8zoiHUEUyfbukEa9qvX1AA6DtWL9rMgb2ef0eXjD6bbokJJld0cnyxnRL/FkgBYKO9B3fwj3lPsO/QTu+xGWeP5Hc/mBUQmwH5urYOABsZhsHa3bt5f+lyPli+kpLKymbn+/Xrx1VXXcWll15KbKz+OwcKX+rzBQoFgNJRFABKq/hTAGgYBjNnzmTJkiXYgmw89OmjdO2RYlo9bcEwDJa9t5Q3f/8a1eXVAETHJTH9+t+Q2WeIydW1H1/rWLvdbnbu2ElRUREA4SEh9O6Wpt1+/YgCQN9RW1PHF//9moZ6JzEREVw9YRx2P1y+wNfaKfF/gRgAArjcLj7/+r+898XfqWuoBTwfov3iogv58QWTCQnWKPr20l4BYFP1TieLNmzkvSXL+OybtdQ7nd5zDoeDqVOnMnv2bM4++2ysVutxnkl8na/0+QKJAkDpKAoApVX8KQB8//33ufHGGwGY8tMLmfW7y02rpS0cbdTf0LHTmHTZTThCwkysrP35Use6ocHJtm1bqSivACAyLJTT09OwW/0vsOjMFAD6ln07DrB++Q4Azux9Omf37WNyRSfOl9opCQyBGgA2KqkoZM7CV1i64TPvsfSEeO684gdMGT4sIGZs+JqOCACbKq6o4L2ly3jry8XsyNvf7Fz37t254ooruOKKK+jatWu71yJtz1f6fIFEAaB0FAWA0ir+FADu3buXW+68la2btvDIwj8QEh5iWi2n4lij/i667tdk9R1qcnUdw1c61rW1tWzZsoXaGs+IhZiIcHqlpmLTJ9h+RwGgbzEMg2WfrKPocBlWq5Wrxp1LfHSU2WWdEF9ppyRwBHoA2Gj3/q28+cnz7Nm/1XtsYFYmv77sEs7p309BYBvq6ACwkWEYrNu9h39/uYgPV6yiqrbWe85mszF58mSuu+46xowZo1GBfsRX+nyBRAGgdBQFgNIq/hQAAmxs2MLGg5uITog2tY6TVXq4hH/e+Q/WfvaN99iQMRdy3mU34QgNN7GyjuULHeuKikq2bd1KQ4OnE5YYG0NmchIW1DHxRwoAfU9FWRWLPliN222QGBPN5eeO9atw3RfaKQksnSUABHAbblZsXMDbC1+mtKLIe3xkn978+rJLtFFIGzErAGyqqraWeStX8daXi1mzc1ezc1lZWVx77bVcfvnlxMXFmVKftJ4v9fkChQJA6SgKAKVV/DEAzHHmmlrDyTAMg+XvL+XN379OVVkVAFFxiVx07a/p0W+YydV1PLM71oWFhezatcsbFKUnJpDSJU7hnx9TAOibdm7cx9ZvsgH/mwpsdjslgaczBYCN6upr+Pzr/zJ/2X+oqq3wHp8weCC3XDydgT2yTKzO//lCANjU9rz9vLlgIe8uWUZFTY33uMPhYPr06Vx//fUMHTpUo0B9lC/1+QKFAkDpKAoApVUUALa/kkMlvHb3q6z9dI332JAxUznvsp92qlF/TZnVsTYMyMnZx/4j69ZYLBayUpJJiPLPEaXyLQWAvsltGCz731qK88uxWCz8YOw5dPWTUSAKAKWtdcYAsFFVbSWfrHiHT1bM8W4UAnB2v778bNpURvfrq1DoJPhaANioqraWuctX8MbnX7Bp375m5/r378/111/PzJkziYiIMKlCORpf6vMFCgWA0lEUAEqrKABsP263m0X/+oK3H32LmgrPp6BRsQlMu/ZX9Ox/psnVmcuMjrXT6WTHjh2UlpQCEGS30Ss1laiwwN5wpbNQAOi7KsurWfThGlxOF7EREVw1fhxBdt/fZEcBoLS1zhwANiqvKmHe0n/zxZoPaXDWe48PyMzkJ1MvYPKwIQTZ7SZW6F98NQBs1LhW4OsLFvLhilXUNXz7/31ERASzZs3iuuuuo08f/xkdHsh8qc8XKBQASkdRACitogCwfRzcfYB/3PE3dqza7j02+JypnHfZTYSE6dPOju5YV1dXs23bNu9mH+GhIZyWlorDHtTury0dQwGgb9u7fT8bVuwEPJsBjB800OSKvp8CQGlrCgC/VV5Vwmer3mfB6rlU11Z6jyfFxnDV+HFcce5YkmJjzCvQT/h6ANhUaWUl7yxewhsLvyD70OFm58466yyuv/56LrzwQhwOh0kVii/1+QKFAkDpKAoApVUUALYtZ72T+S99xAdPv4+z3glAXFIa066+ne69B5lbnA/pyI714cOHyc7O9oZC8dFRZHVNxmrxn80I5PspAPRtBgYrP99I/v5iAC4860x6paaYXNXxKQCUtqYAsKWauiq+/OYjPlk5p9lmIXabjQuGD+UHY8dwdr++frWBUEfypwCwkdvtZumWrbyxYCGfrlmLq0ndXbp04fLLL+fqq6+mR48eJlbZOflSny9QKACUjqIAUFpFAWDb2b12F//4zSvkbc8DwGK1cvbkyxlz4TUEBevTzKY6omPtcrnYvXs3hQWFR14TuiUmkhwXq80+ApACQN9XW1PHog/XUFdTjyMoiCvHn0tMuO+ug6oAUNqaAsBjc7qcfLNtCZ+v/i87cjY2O9c1Lo6ZZ4/i0nPOpkdKV5Mq9E3+GAA2dai4hLcWLeZfC7/k0Hf6GOeccw5XX301U6dOJTg42KQKOxdf6vMFCgWA0lEUAEqrKAA8dTUV1bz353f5/B+fejuJKd1PZ9q1vyI5vafJ1fmm9u5YV1ZWsmP7DmprPVN+HUFB9ExNITI0tM1fS3yDAkD/kH+gmJWfb8AwPFP9Zo0Zg93mmyN7FABKW1MA2Dq5h3fz+ddzWbl5IbX1Nc3O9e+ewZThw7hg+DCFgfh/ANjI6XKxYO06/vXFIr7csLFZmxsfH+8dFZiVpV2j25Mv9fkChQJA6SgKAKVVFACePMMwWDF3OW89+CZlBWUABAWHMO7i6zlrwiVYbb6/yL1Z2qtj7XYb7N+fR15unvd546IiyeqajN2q/x6BTAGg/9i2NpsdGzy7Qp6R2Z2JgweZW9AxKACUtqYA8MTU1dewZtsSlmz4lK3ZazFo/u/wtLRULhg+jPOGDKZfRjesnXCacKAEgE3lFhTw1peLeevLxRSUlTU7N2bMGK6++mqmTJmiUYHtwJf6fIFCAaB0FAWA0ioKAE/O/h37ef2eV9m2fKv3WI9+w5k6+1ZiE/SJ9Pdpj451VVUVu3buoqqqCgCr1UK3pESSYmI05bcTUADoPwzDYPln6yk8WArA+EEDGZiVaW5RR6EAUNqaAsCTV1R2mBWbFrJ621dkH9je4nx8VBTn9O/HmAH9Oad/PxJjYjq+SBMEYgDYqMHpZMHa9fzriy9ZtHFTi1GBV1xxBZdffjmnnXaaiVUGFl/q8wUKBYDSURQASqsoADwxNZU1zH36fT772ye4nC4AouISmfyDn9N7yDlYLAqaWqMtO9ZHG/UXERpCVkpXwrT2YqehANC/1NXW89VH31BdWYvVamXm2aNIT/CtN8kKAKWtKQBsG0Vlh1m9bQlrti5mZ+7mFiMDAXqnp3Hm6acx/LTTGH56L1K6dDGh0vYXyAFgUzn5Bfxn0dFHBQ4dOpQf/OAHzJgxg5hOEvy2F1/q8wUKBYDSURQASqsoAGwdt9vN8veWMucPb1NyyPN3YLXZGXneLMZcOJtgh9aWOxFt1bEuKytjz5491FTXeJ83LSGelC5xGvXXySgA9D9lxZUs+XgtLqeL0OBgfjB2DLGREWaX5aUAUNqaAsC2V1ZZzKY9a9i0ZzWb96ymvKr0qNeldunCsNN6MSCzO2dkdqdvRjeiwsI6tth20FkCwEYNTiefr13HvxZ+yeJNm5u1zQ6Hg8mTJ/ODH/yAcePGYbfbTazUP/lSny9QKACUjqIAUFpFAeD327ZiK/9+4E32bdrrPZbZZwhTrvwl8V27dWgtgeJUO9b19fXs3bvXu8MvaNRfZ6cA0D8d2FfA6i83AxAdHsasMWOICA0xuSoPBYDS1hQAti+34Sb38B427f6a7Tkb2Jm7mZq6qmNe3z0piTMyM+jfvTunpabQKzWVtPgufrWWYGcLAJs6UFTEe0uXM2fxEvYcOtTsXGJiIpdddhkzZsxgwIABmqHTSr7U5wsUCgCloygAlFZRAHhsh/Yc5D+PvMXaT9d4j8XEJzPxkhvpO+xcvZk4BSfbsXa73Rw8eIi83FxcLs8UbJvNSnpCAkmxWuuvM1MA6L92b85l8+rdACRER3PZmNE4goJMrkoBoLQ9BYAdy+12sb9gLztyN7EzZxO79m+hsPTQce8JCQ6mZ9eu9EpNoWdqV3qmpJCZnER6QgLhIb7x4URTnTkAbGQYBmt37+adxUv4cMVKyqub7xydmZnJjBkzmDFjBr179zapSv/gS32+QKEAUDqKAkBpFQWALRUfLOLDZz9g8Vtfetf5c4SGc87U2Zw1YSb2IO06dqpOtGNtGFBQUEBuTg51dXXe4wkx0XRLTCDIpmkenZ0CQP+2efVudm/2tO2pXbpw8aiRBAeZ++9aAaC0NQWA5qusKSfn0C72HtzJ3oM72HdoJ4eL97fq3oToKLolJtItMYFuiYlkHHmc0iWOpJgYgkyYcqoAsLna+no+/WYtcxYv4atNm3F95++kd+/eXHzxxVx88cX06NHDpCp9ly/1+QKFAkDpKAoApVUUAH6rNL+Uj/7yIV+8uRBnneeNucVqZdjYixh70bWER8a0y+t2RifSsS4pKSFnX453d1+A8BAHGclJRIX6//o90jYUAPo3wzBYu3QbebsPA5ByJAR0mBgCKgCUtqYA0DfV1tdwsDCHAwX72F+4z/O4cB/5JQcxjNb9PrFYLCRER5PSJY6ucXF0jYs98riL93FiTAx2m61Na1cAeGxF5eXM/3o181asYsW27S3a8f79+zNlyhQmT55M//79NbMH3+rzBQoFgNJRFABKqygAhIriCj5+8SM+/+dn1Nd8O7qsz9AxjJv+QxJSMtr09eT7O9aGASUlxeTl5VFZUek97ggOIj0hni5RUZruK80oAPR/bsNg7Vdb2Z+dD0BKlzimjxxJSLA504EVAEpbUwDoX+qd9RwuyiO/5AAFpQc930s83wtLD+NyO0/o+awWC/HR0STHxpIcF+P5HhtLclxcs2MRoa3fWE4BYOscKinho5VfM2/lKtbs3NXifHp6OpMnT+aCCy5gxIgRBPnAMhRm8KU+X6BQACgdRQGgtEpnDgALcvL53ysf89Vbi6ivrfceP23gKMZNv57kbj3b5HWkpWN1rA0DiooKycvLo7qq2nvcbrORGt+FpNgYrBb/WZxbOo4CwMDw3RCwS1QUF48aSVRYx++0rgBQ2poCwMDhdrsoqSgkv+QgJeUFFJcXUFxRQHFZASUVnp8rqstO6rkjQkJIjoslqTEgjI2la1xss2Px0VHYrFYFgCcht6CAeSu/5tM13/DNrt0t2vfo6GgmTJjAuHHjOPfcc0lOTjap0o7nS32+QKEAUDqKAkBplc4YAO7btJePX/qIVfNWNgsKevQbzrjp15Oa1edUy5Tv8d2OdYPTSf7hwxw6dIi62m9HYQbZbSTHxZEUG4Pd2rbTZiSwKAAMHG7DYP3S7eTu9izWHx4SwsWjRpIYE92hdSgAlLamALBzqW+oo6SikOLy/CPBYGGLr7LKklZPM27KZrWSGBNDclwsqfFdSGgcWRh7ZGRhnCcoDHU42uFPFjjyS0tZsHY9n6z5hqWbN1PX0HJUZ79+/bxh4FlnnUWID24G01Z8qc8XKBQASkdRACit0lkCwIa6Br6ev4qFr33OrjU7vz1hsdBn8GhGTb6ctKy+bVipHE9jx7q0tJSDBw9SWFDY7JPr4CA7Xbt0ITEmGptG/EkrKAAMLAYG29fuZceGfYDnw4DxAwfRNyO9w2pQAChtTQGgfJfL7aKsstgTCJY3DwdLjxwrriikvqH2pJ4/KiyM9IR4MpIS6Z6UREZiIt2TEslISiQ5NharVe+xGlXV1rJ44yY+XbOWxRs3UlBW3uKa0NBQRowYwahRoxg5ciSDBg3CEUAhqy/1+QKFAkDpKAoApVUCPQA8vPcQX/1nEYveWkRF0be/yG32IAaMPI9R588iPrlbe5Qqx1Df0EBhQQEFBQVUVVY1OxceGkJybCxdoqKwajFmOQEKAANTzs6DrF++wxvA9e+ewbkDBhBkb/8RwQoApa0pAJSTYRgG1XVVlJa3HEHoCQqLKC4voLzqxN6jO4Ls3t2Muycl0SOlK71SU+iVkkJsZEQ7/Wn8g9vtZmtuLos2bGLxxk18vX0HDS5Xi+tCQkIYNmwYI0eOZOTIkQwdOpSwMP/doM6X+nyBQgGgdBQFgNIqgRgAVpZWsurDFSx7b2nz0X5AVGwCQ8dOY8g5U4mIjmvPUqUJp9NJcXEJRUWFlJaUNutMWywWukRFkhQbS0RoiDb3kJOiADBwFeWX8c2iLdRUe5YHiI2IYOLgQaQltO+bagWA0tYUAEpba9pONTjrKa0obh4QlhdQUHqI/OL9HC450OqRhF2iIumZkkKv1BR6pqTQM6Urp6WmkhQb0yl3y62urWP51q0s2riJldu2szXn6H0Rm81Gnz59GDJkCIMHD2bIkCGcfvrp2Np49+f24kt9vkChAFA6SqcKAMvKypgzZw6rVq2iqKgIh8NBjx49mDJlCiNGjDjp53U6ncybN49FixZx4MABAFJTUxk7dixTp07Fbrcf9/49e/bw/vvvs3HjRsrLy4mOjqZ///7MnDmTzMzMdn3t1gqUALCiuIJ1n3/Dmv+tZuOiDbgamn9Kl9VnKMPHX8xpA0Zi9ZNfwv6uvr6e4pISiguLKCsra9GBDg8JIT46ii7RUQTb2ub/Z+m8FAAGtrq6BtZ+tZX8/cXeY2dkdmdU3z6EtdP0KwWA0tYUAEpbO5F2yjAMyqpKjoSB+8kvPkh+yX7yiw9wqDiPmrqq494Png1Keh4ZJdgz1RMQ9kpNIT0+vlNNJy6trGTV9p2s3LaNldt2sGnvXtzH+PsPCwtjwIABDBo0iD59+tCvXz9OO+00Qk9gt+eO4kt9vkChAFA6SqcJAHNycrjrrrsoK/PstBUaGkpdXZ13PbFp06bx4x//+ISft6amhnvuuYcdO3YAEBwcDHhCDYDevXvzwAMPHHMh2EWLFvH000/jdHoWkw0PD6eqyvOL1W63c+utt3LOOee0y2ufCH8NAA3D4OCuA2xctJFvPl3NjlXbMdzN/5fvkpTOgJHnMWDERGLiO88OXmZxudyUl5dTVlpKaWkp1dXVLa4JDrLTJTKKhJhoIsJCPf9OO0VLJe1NAWDgMwyDnJ0H2bJmDw31nt+twXY7w07vxZAePdt8WnBHB4D1DU4Ky8spLCunpKqSmro6aurqqK6rx+ly4Xa7cRsGhmEQZLcRZLcTZLMT6ggmPCSUyNAQIkNDiYmIIC4yskOmScuJUQAoba2t2inDMCirLOZAYQ4HCvdxoHAfBwtz2F+wr1VTix1BQfRsnEJ8ZNRgr9QUMhITCWqjQQu+rKK6hjU7d7J29x7W797Duj3ZFFdUHPN6q9VKVlZWs0AwKyuLzMxMU6cQ+1KfL1AoAJSO0ikCwIaGBn7+859z6NAhMjIyuO2228jMzKSuro65c+fy5ptvYhgGN998MxMnTjyh5/7zn//MokWLCA8P5+abb/aOJFyxYgXPPPMMVVVVjBs3jltvvbXFvTk5Odxyyy04nU5Gjx7NDTfcQFxcHMXFxbz88sssXbqUoKAgnn76adLS0tr0tU+UvwWAz773PAs+W8CWJZsoOdSylqjYBHoPHs2AEZNIyezdKacpdJSGhgYqKiqafX03hAVwBAcRFxlJXGTkt1N8LZ43PwoApa0oAOw8aqrr2LRqJwf3ffv7KzQ4mAFZmQzMyiS8jXZobK8A0DAMSquqKCwrp6C8nKKyMgrKyimr+v7RNyciKiyMuMhI4qOjSIyJISk2huiwcPRr0TwKAKWtdcQHFVU1FS2CwQOFORSWHvree4NsNronJx0JBlPpldKVXqmpZCYnEXJkgEMgMgyD3IJC1u05EgjuzmZrTg6Vtd8/Bbtr165kZWV5vzIyMkhJSSE1NZWEhIR2nU7sS32+QKEAUDpKpwgA582bx1//+lccDgd/+ctfSEhIaHb+xRdfZP78+cTFxfHKK6+0etpsdnY2t9xyC4Zh8Nvf/pZRo0Y1O7906VIef/xxLBYLzzzzDBkZGc3OP/rooyxfvpzMzEyeeOKJZg21y+XitttuIzs7m7PPPps77rijTV/7RPlbAHjBpReyetHKZsfiu2bQe/Bo+gw5h64Zpyn0awf19fVUVVVTXV1FdVU1FRUV1B7jTYzVaiEyLIzo8HCiw8MIczharuunAFDamALAzqfocClb1uyhpKDJBk9WK1ldk+mdlk735CTstpOfktYWHeva+oYjo/rKmn1vcLZcTL6poGA7IWHBBDuCcYQEYQuyYbVasFgsWCzgdLpxOV04G1zU1dZTW11PXU3999YTEhxMYkw0iTExnlAwJobocIWCHUUBoLQ1M5cqqKuv4WBRLgcKPMHg/gJPOHi45ACGcfzfw1aLhW6JifRKTaFHSlcyEhPplphAt8QEUuLiAnLUoGEY5BUWsjUnj+15uWzNyWNbbh57Dh485vTh77LZbCQnJ5OSkkLXrl1JSkqiS5cuxMbGEhcX1+wrOjqa0NDQE5qa3d59PsMwaGhooKGhAZfL5X3sdDq935s+bvxuGAYxMTH079+/zWtqbwoApaMEXqt5FF9++SUAY8aMaRH+AVxyySV8/PHHFBcXs3HjRgYPHtyq5120aBGGYdC1a1dGjhzZ4vyoUaPo2rUrBw8eZNGiRVxzzTXec1VVVXz99dcAXHzxxS0+pbHZbFx88cU8+eSTrFq1iurq6mZDvU/ltTuDXr3PYvOarWT1GUpWX89XTBdN720LLpeL2tra5l81tVRVV+FscB7zPovFQkRoCBGhoUSHhxMVForV0nnWgRERc3RJimH0lMHk5xWze0suhQdLcbnd7Nx/gJ37DxBst9MtMYGMpCRSu3QhNjKi3XYXr3c6Ka6opLiiguKKCgrLyiksL6Oiuua491mtFiKiw4iKjSAqNtz73REWfMIbIrlcbmqq66gsraKyrJqKsmoqSqsoL6nyhuK19fXk5BeQk1/gvc8RFER8lGdphvioKBKio+kSFaUpxCJyXI7gULp3PY3uXU9rdrzBWc+hojzPFOLCfd6A8FBRHi635/2k2zDYe/gwew8f5rNv1ja732a1ktKlizcQ7JaQQFp8PMlxsSTFxpIcG+OXowctFgvpCQmkJyRw3tBv+6S19fXsO5zP3sOHyT50mOzDh9l3OJ/sQ4c5WFzc7DlcLhf79+9n//79rX7dsLAw71d4eDhhYWE4HA7sdjtWqxW73Y7NZsNutxMSEuIdMFNTU4PryPITTqfT+9jlcjX7ak2A1/jYdZSdlFtrzJgxvPvuuyd9v0igC/gAsKamhp07PTu8Dhky5KjXJCQkkJaWRm5uLuvXr291ALhhwwYABg8efNTRZBaLhcGDB3Pw4EHvtY22bNniXffvWHU1Hm9oaGDr1q0MHTq0TV67Mxh/0SX0GjodSydaaPhUuVyuI7vDOamvr6ehvp76+nrq6xu8j+vq62iob91oBEdwEBEhnsAvIjSU8BCHAj8RMYUFC0lpXUhK60JZcQU5Ow+yP7uA+roG6p1Odh04yK4DBwEIsttJjIkmITqaqLAw71eoI5hgexCOIHuL37tut0FtfQN1DQ3UNzRQXVdHRU0NlTU1VNTUUFFdTXFFJeVHWfP0u0LCgr0BX2Tj9+iwNls432azEhEZSkRkKKQ3/TO4qSitpqyogrLiCkqLKikvrsR1JBSsa2hgf1ER+4uKvPdYLBZiI8KJi4w8Mpo7nJiICGLCw4kMDcVq1ZBBETm6IHsw6UlZpCdlNTvucrvILz7gnUrcGAweLt5PbX1Nk+vc5BYUkFtQwNLNR3+NmIhwkmNjvV/x0VHERUYSG+lZAzUuIoLYyEjiIiMIDwnx6dlBIcHBnJ6exunpLZeFqqmr40BRMQeLSzhYXHTke7H3e2FZGSWVVTiPE6xVV1cfdV1uv3OcNRVFpBMEgHl5ed6h7sebBpuRkUFubi65uUffrv27DMMgLy/ve5+3W7duAC2et/HnmJgYoqOjj3pvdHQ00dHRlJWVkZOT4w0AT/W1O4PgYAcWq+9P72s5kt84ctz43i+3YcCR795jbjdulxu3+8inb9/52e1y43J7gj6X0+X9tO1UpoQEB9kJCQom1BFMWEgIYQ4HYY5gbFaNChER3xMdF8kZZ0XSb3hP8vcXcziviPwDJdRUepYraHA62V9YxP7CoqPeb7FYsFmt3umwhsFxO1XHYrNZiYwJ947oi4z1PHaEmDNixWq1Eh0XQXRcBNAV8Iy+qSitoqyokvISTyBYVlJJQ53nA0zDMI6MaKxs8XwWi4XQ4GDCQ0KOfDkIdThwBAURbLcTHBSEwx5EcJCdYLsdm9WKzWb1fPd+eaY0Wy1WTT8W6SRsVhtd49PpGp/OUEZ7jxuGQUV1GQWlB8kvPkBB6UEKSg6Sf+R7SXkBxnfWiymtrKK0soptuXnf+7rBdjuRYaGEh3g2Sgpv/BDb+2G2py0LCQ7GERTkbcscwUGEHPnZezzITpDdjs1i/U7bZvu2fWvR3llP+oOeUIeDHild6ZHS9ZjXGIZBRU0NJZWVlFRUUlLpGY1eUV1DdV0d1bW1VNfVU+3dWKqO2vp6XEf6F06XC9eRvoWBZ+CAYRje34mN9Td7fOSc3W7DbrMRZLNjs1kJsjX+bMP+3WN2zzF7s/ts2KyN52zea5t+BdltWC1Worse++9ARDpBAFjcZEh0XFzcMa9rPNfadQxqamq8a5u15nlramqoqanxbuXe+DrHu7fxfFlZWbO6TvW1j+aNN97gX//61zHPX3HFFVx55ZXHrbXxl5bVaiU2Nva417a3pUuWknfoSIfsO7lWszcHxjGOn+y5Vr6Wv7BYLATb7QQd6aAF24MICQ4iJDjY8wYoOAhbB4yybKuRLyJNWU9h3Tfxf1ablZTuiaR0T8QwDKrKaygpLKesqIKSwgoqS6upq225Xp5hGK0O/CxWCyGhDkIjHERGhRERE05kTBiR0eGERYRg8fERclYgNj6K2Pgo7zHDMKipqvOEgcWeYLCqvIaqihrvrsuN11Uf6UQWlJWdci0Wy5HJzke+f/fnYx73c748IknEXPFgj6dL/Bl0iQe320l9QyX19ZWe7w0V1DV5XF9fSYOzGrf76DNZ6p1OisorKCr3vxFkx2wlLMc9G5C6xseT88Mfm12GiM8K+ACw6QYEDofjmNc1nqupOf46PI2aXtea5228pzGEa7z/ePceq65Tfe2jqaqqIj8//5jnq6urW72blMViadedp1rDXZLH+qVfmFqDr7DZbDiCHTgcwQQHeYK78LBwwiPCiAgLIyI8nPCwMMLDI4gI9/wcFxNDbHQMUZERCt9EpNOqqakl/3AB+fmFVFRWUVVZRVVlNXX1zYPB0BCHZ+2kiDDCwkKJjookIbELMTHRrd5YzN8ZhkFZWQUHDxxif95BCguLKS4uoaS4lKLiEkqKyygrK6O6qqbVC9mLiLQFqzWUkJBQQgDDcB/5cmEYLtxHvn97zADDjYG7ybVuwH1ktozvtV/HrMg47tmAVOt0mt4PFfFlneNdqXyv8PBwEhMTj3k+LCzsexdktVqtWCwW71RUM006ewQRVs8vPM9uiBbv4xM91hbPcaLPa7PZCAoKwm63H/X70c7b7XZCQ0ObLeIbGhpKUFBQm/29djSLxeLdBbgTbFguHcCX2ikJDGqnToxhGFRVVVFWVkZ5eTllZWVUVFRQV1dHQ0MDdXV1njVnv/Pd+M5yF0f7frRj/qjxvYE//xn8te5A1fj/VOO/Ezl5hmF4N7Zo3PSi6ePGpXWO1U4dr7062r/5xp+bHj/WNce6/vvuP1FNRyb72v9Pp59++iltImIWhZbSUQI+AAwJCfE+rqura7aTblN1dXUAxx0l11TT6xrvPd7zfveexsfHu/dYdZ3qax/N7NmzmT179jHPFxYWfu/06MYt4d1ud7tsCX8ixo8fz/jx402twWwul4vKypbrMvkTm81GbGwsZWVlfvnLXHyPL7VTEhjUTp2cxg+qkpOTzS7F5zS2Uy6XS+2UtInGdqqkpETtlJwyX2+jfLGm7xMfH292CdJJBPzcvqZr5BV/Z4v0phrPtXbtutDQUG+o1prnbXp907qOd++x6jrV1xYRERERERERkc4j4APAtLQ07zDlnJycY17XeC49Pb1Vz2uxWEhLSzvp5238ubS0lPLy8qPeW1bmWS8Hvt3Rty1eW0REREREREREOo+ADwBDQ0Pp1asXAN98881RryksLCQ3NxeAgQMHtvq5BwwYAMDatWuPec26deuaXduob9++3oXBj1VX4/MGBQXRp0+fNnttERERERERERHpPAI+AAQ499xzAVi8eDEFBQUtzr/33nsYhkFcXBxnnHFGq593zJgxWCwWDhw4wPLly1ucX7ZsGQcOHMBisXhraBQWFsbw4cMBmDt3bov1OFwuF3PnzgXgzDPPbLF24am8toiIiIiIiIiIdB6dIgA8//zzSU5Opra2lgcffJDs7GzAs0nGnDlz+OijjwDPRhiNo/Ia3XDDDVx00UU89dRTLZ43MzOTMWPGAPDss8+yYsUK765OK1as4LnnngM8AWTTKbyNrrrqKux2O7t37+aJJ57wLlhaUlLCE088we7duwkKCuKqq65q89cWEREREREREZHOIeB3AQbPFNq7776bu+66i7179/LLX/6SsLAwamtrcbvdAFx44YVMnDjxhJ/7Zz/7GQcPHmTHjh088sgjBAcHA1BfXw9A7969+elPf3rUe7t168Yvf/lLnn76ab766iuWLFlCWFgYVVVVANjtdn75y1961/try9cWEREREREREZHOoVMEgOAJ25599lneffddVq1aRWFhIeHh4WRlZTF16lRGjBhxUs8bGhrKY489xrx581i0aBEHDhwAoEePHpx77rlMnTq1xajCpsaOHUt6ejrvvfcemzZtory83DsVeebMmWRmZrbba4uIiIiIiIiISOCzGIZhmF2E+L7CwsLvvSY2NhabzYbL5fJOZxY5FTabjdjYWEpKSlqskylyMtROSVtTOyVtTe2UtDW1U9KW1Ea1vfj4eLNLkE6iU6wBKCIiIiIiIiIi0lkpABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAGYxDMMwuwgJDG+88QZVVVWEh4cze/Zss8sREWlB7ZSI+Dq1UyLiy9RGifgvBYDSZqZMmUJ+fj6JiYnMnz/f7HJERFpQOyUivk7tlIj4MrVRIv5LU4BFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAGY3uwAJHFdeeSVVVVWEh4ebXYqIyFGpnRIRX6d2SkR8mdooEf9lMQzDMLsIERERERERERERaR+aAiwiIiIiIiIiIhLAFACKiIiIiIiIiIgEMAWAIiIiIiIiIiIiAUwBoIiIiIiIiIiISADTLsByysrKypgzZw6rVq2iqKgIh8NBjx49mDJlCiNGjDC7PBEJYAUFBSxfvpwNGzawd+9eiouLsdvtJCQkMGjQIKZNm0ZycvJxn2P58uV8/PHH7N69m7q6OuLj4xk+fDiXXXYZUVFRHfQnEZHO5KGHHmLVqlUAjB8/nltuueWY16qNEpGOVFpayrx58/j666/Jz8+noaGB2NhYMjMzOeuss5gwYcJR71NbJeL7tAuwnJKcnBzuuusuysrKAAgNDaWurg632w3AtGnT+PGPf2xmiSISoAoKCrjhhhto+mssLCyM+vp6nE4nAMHBwdxyyy2MHj36qM/x4osvMn/+fACsVisOh4OamhoAYmJiePjhh0lPT2/nP4mIdCZLly7l8ccf9/58vABQbZSIdKSVK1fy1FNPUVVVBXjeR9lsNm+7k5yczF//+tcW96mtEvEPGgEoJ62hoYGHHnqIsrIyMjIyuO2228jMzKSuro65c+fy5ptv8uGHH5KZmcnEiRPNLldEAkzjBw1Dhgxh/PjxDBo0iKioKFwuF1u3buWvf/0re/fu5YknniAtLY3u3bs3u/+TTz5h/vz5WCwWrrrqKqZPn47D4SA7O5snnniCffv28dBDD/Hcc88RFBRkwp9QRAJNVVUVL7/8MuHh4cTGxpKXl3fMa9VGiUhHWrduHY8//jhOp5Nx48ZxySWX0K1bNwAqKyvZvn0727Zta3Gf2ioR/6E1AOWkffLJJxw6dAiHw8G9995LZmYmAA6Hg1mzZnHBBRcA8MYbb3hH44iItJWIiAiefPJJ7rvvPsaMGeOdXmKz2ejfvz/3338/0dHROJ1O5s6d2+zehoYG/vWvfwEwZcoUZs2ahcPhACAzM5N77rkHh8PBwYMH+eyzzzr2DyYiAevVV1+luLiY2bNnExMTc8zr1EaJSEeqqanhmWeewel0MnPmTG699VZv+Aee91xDhw7lqquuanaf2ioR/6IAUE7al19+CcCYMWNISEhocf6SSy7BYrFQXFzMxo0bO7g6EQl04eHhZGVlHfN8bGwsQ4cOBWD37t3Nzm3YsIGSkhIsFgszZ85scW9iYiJjxowBvm3rREROxZYtW/j000/p1auX90PSY1EbJSIdacGCBRQWFtKlS5cWId/xqK0S8S8KAOWk1NTUsHPnTsAz/e5oEhISSEtLA2D9+vUdVpuISKPGUYEul6vZ8Q0bNgCQnp5+1A8wAAYPHgzA9u3bqa2tbccqRSTQNTQ08Nxzz2GxWPjZz36G1Xr8t+Bqo0SkIzWGc6NGjTqhabpqq0T8i9YAlJOSl5fnXXg/IyPjmNdlZGSQm5tLbm5uR5UmIuK1adMmoGU71dgmfV/7BWAYBnl5efTs2bOdqhSRQPfOO++Ql5fHtGnT6NGjx/derzZKRDpKfX09e/bsAaBHjx7k5eXxn//8h/Xr11NZWUlsbCxnnHEGM2fObDYtGNRWifgbBYByUoqLi72P4+Lijnld47mSkpJ2r0lEpKkVK1awa9cuACZMmNDsXGMb1pr2C9SGicjJy83NZc6cOcTFxbV6ap3aKBHpKPn5+d712g8cOMALL7xAXV0dwcHBBAcHU1BQwMKFC/nqq6+49dZbGT16tPdetVUi/kUBoJyUpsO3Gxd6PZrGc43bwIuIdISCggKef/55AM466yzvWoCNGtuw1rRfANXV1e1QpYgEOsMweP7553E6ndxwww2EhYW16j61USLSUSorK72P58yZQ3R0NHfccQdDhgzBarWyZ88ennvuOXbt2sVTTz1FVlYWKSkpgNoqEX+jNQBFRCSgVFZW8uCDD1JWVkZycjI333yz2SWJSCf1ySefsGXLFoYOHdps1IyIiK9oXNYJwO12c8sttzBs2DDvWqVZWVncfffdhISEUF9fzwcffGBWqSJyihQAykkJCQnxPq6rqzvmdY3nQkND270mEZGamhruv/9+9u7dS1xcHA888ACRkZEtrmtsw1rTfgGtHrUjItKouLiYf/7znwQHB/OTn/zkhO5VGyUiHaVpPy09Pd27aUdTcXFx3t18m27uqLZKxL8oAJST0nQth6brAX5X47nY2Nh2r0lEOre6ujoeeOABtm/fTnR0NA8++CDJyclHvbaxDWtN+wVqw0TkxL322mtUVVUxffp0oqOjqampafbldrsBzy7l3z2mNkpEOkrTfl1aWtoxr2s8V1BQ0OJetVUi/kFrAMpJSUtLw2KxYBgGOTk5x/xlkZOTA3g+TRIRaS91dXU8+OCDbN68mYiICB544IHjtjvp6emsXr3a20YdTeM5i8Vy3DfEIiJHk5+fD3h2AH7nnXeOed2iRYtYtGgRgHd9LbVRItJRoqKiiI2NbfUGHRaLxftYbZWIf9EIQDkpoaGh9OrVC4BvvvnmqNcUFhZ6t4YfOHBgh9UmIp1LQ0MDjzzyCBs2bCAsLIz77ruPzMzM494zYMAAwPOmtLCw8KjXrF27FoDTTz+92bIHIiLtTW2UiHSkQYMGAZCXl3fMaxrPJSYmeo+prRLxLwoA5aSde+65ACxevLjZUPBG7733HoZhEBcXxxlnnNHB1YlIZ+B0OnnsscdYu3YtISEh3HvvvZx22mnfe9+AAQOIjY3FMAzef//9FucLCgpYvHgx8G1bJyJyIh555BE++OCDY371798fgPHjx3uPZWVlAWqjRKRjjR8/HoDc3NyjDu4oLi72tjnDhg3zHldbJeJfFADKSTv//PNJTk6mtraWBx98kOzsbMAzFW/OnDl89NFHAMyePRu7XbPNRaRtuVwu/vSnP/H1118THBzM3XffTd++fVt1b1BQEFdeeSUA8+bNY86cOd5FqrOzs3nwwQepra2la9euTJo0qd3+DCIiR6M2SkQ60sCBAxk6dCgATz/9NGvWrPGuSZqdnc3DDz9MbW0tkZGRTJ8+3Xuf2ioR/2Ixmu77LXKCcnJyuOuuuygrKwM8OzvV1tZ6f2FceOGF3HjjjWaWKCIBatOmTdx5552A5w1oeHj4ca9/7bXXWhx78cUXmT9/PgA2mw2Hw0F1dTUAMTExPPzww1rDVETaxZ133smmTZsYP348t9xyy1GvURslIh2lsrKSu+++mz179gAQHByM3W73tjkRERHceeed3tHLTamtEvEPGpYlp6Rbt248++yzvPvuu6xatYrCwkLCw8PJyspi6tSpjBgxwuwSRSRANf38qqGhgdLS0hN+jptuuomBAwcyf/589uzZ4/2U+swzz+TSSy8lOjq6DSsWETkxaqNEpKNERETwxz/+kY8++ojFixezf/9+nE4nqampDB06lBkzZtClS5ej3qu2SsQ/aASgiIiIiIiIiIhIANMagCIiIiIiIiIiIgFMAaCIiIiIiIiIiEgAUwAoIiIiIiIiIiISwBQAioiIiIiIiIiIBDAFgCIiIiIiIiIiIgFMAaCIiIiIiIiIiEgAUwAoIiIiIiIiIiISwBQAioiIiIiIiIiIBDAFgCIiIiIiIiIiIgFMAaCIiIiIiIiIiEgAUwAoIiIiIiIiIiISwBQAioiIiIiIiIiIBDAFgCIiIiIiIiIiIgFMAaCIiIiIiIiIiEgAUwAoIiIiIiIiIiISwBQAioiIiIiIiIiIBDAFgCIiIiIiIiIiIgFMAaCIiIiIiIiIiEgAUwAoIiIiIiIiIiISwBQAioiIiIiIiIiIBDAFgCIiIiIiIiIiIgFMAaCIiIiIiIiIiEgAUwAoIiIiIiIiIiISwBQAioiIiHSQL7/8EovFgsVi4b777gNg586d3H777fTr14+YmJhm5xrV1tby0ksvceGFF5Kenk5ISAjR0dH079+fm2++mR07dhzzNfv06YPFYiEtLe2Y19x1113euiIjI2loaDjqdX/84x+913300Ucn/OcXEREREXMoABQRERExyRtvvMHAgQN54okn2LJlC2VlZS2uWbRoET179uSmm27io48+Ii8vj7q6OsrLy9m8eTPPPvssffv25dFHHz3qa4wbNw6A/fv3s3379qNes3DhQu/jyspKVq1addzr7HY7Y8aMOaE/q4iIiIiYx252ASIiIiKd0bJly3j44YexWCxce+21nHPOOYSHh7Nr1y66desGwMcff8z06dNpaGjAarUyefJkJk6cSGpqKrW1taxevZrXXnuNsrIy7rzzTgB+97vfNXud8ePH88ILLwCeAO/0009vdr6iooLVq1c3O7Zw4ULOPvvsZscaGhpYsmQJAMOGDSMyMrLt/jJEREREpF1ZDMMwzC5CREREpDP48ssvvSPyABITE/nss88YMGBAi2sPHjxI//79KS4uJjExkblz5zJixIgW1+3fv5/JkyezadMmbDYbmzZtonfv3t7zhYWFJCYmYhgGl1xyCXPmzGl2//z585k6dSoAo0aNYtmyZZx77rl88cUXza5btmyZNxS88847efjhh0/+L0JEREREOpSmAIuIiIiY5KWXXjpq+Aee9faKi4sBmDNnzlHDP4DU1FTeeecdbDYbLpeLp59+utn5+Ph4zjjjDMATQH73s9/Gab09evTg2muvBWD58uXU1tYe9TrwjCoUEREREf+hAFBERETEBBkZGUyfPv2o5wzD4LXXXgNg5MiRnHPOOcd9rt69e3PmmWcC8Mknn7Q43xjYFRUVsX79+mbnGoO98ePHe6+rq6tj6dKlR73O4XC0mB4sIiIiIr5NawCKiIiImODss8/GYrEc9dyWLVsoKioCIDY2lv/+97/f+3w2mw2A7OxsamtrCQkJ8Z4bN24cTz31FAALFixg0KBBABQXF3sDwQkTJtCzZ0/S09PJzc1l4cKFTJgwAfDsQrx8+XLAE0g2fW4RERER8X0KAEVERERMkJaWdsxze/fu9T6eP38+8+fPP6HnLi4uJiUlxfvz2LFjvVOEFy5cyO233w54dhh2u91YLBbv2oTjxo3jtddeazblt+mUYE3/FREREfE/mgIsIiIiYoLQ0NBjnistLT2l566vr2/2c3R0NEOGDAHgq6++wul0At9O6+3Xrx+JiYnAtwHf6tWrqaioaHZd0/MiIiIi4j8UAIqIiIj4mIiICO/j2267DcMwTuire/fuLZ6zcYRfRUUFq1atApqv/9eo8bHT6WTx4sXNrgsPD/euNSgiIiIi/kMBoIiIiIiPaTo9ODc3t02es2nIt3DhQg4fPsyWLVsAvGv9AaSnp9OjRw/vdZWVlXz99dcAjB49mqCgoDapR0REREQ6jgJAERERER8zaNAgoqOjAfjiiy+oq6s75edsGt4tXLiQL774AvBsHjJ27Nhm1zaGhQsXLmTJkiU0NDQ0Oy4iIiIi/kUBoIiIiIiPsdlsXHXVVQAUFhbyxBNPnPJzNp2+u2zZMu/GIkOGDPGGjY0ag77169czZ86cFsdFRERExL8oABQRERHxQXfeeScxMTEA3H333Tz11FO43e5jXl9VVcUrr7zCv//972Ne0xjg1dXVea9rOv23UeN6gYZh8M9//hOAmJgY70YiIiIiIuJf7GYXICIiIiItpaam8vbbbzNt2jTq6uq49dZb+ctf/sKMGTPo27cvERERVFRUkJ2dzerVq1m4cCG1tbU8+OCDx3zO8ePHe8837gR8tFF9SUlJ9O3bly1btnivGzt2LFarPjsWERER8UcKAEVERER81KRJk1iyZAmzZ89m+/bt7Ny5kz/84Q/HvN5ms5GcnHzM8yNHjiQkJITa2loAgoODGT169FGvHT9+vHeTkMafRURERMQ/6WNcERERER82bNgwtmzZwjvvvMPs2bPp1asXUVFR2Gw2oqOj6d+/P1dccQUvvfQSeXl53HDDDcd8LofDwahRo7w/jxgxgtDQ0KNe+93ATwGgiIiIiP+yGIZhmF2EiIiIiIiIiIiItA+NABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQCmAJAERERERERERGRAKYAUEREREREREREJIApABQREREREREREQlgCgBFREREREREREQC2P8DFUfcEwt8j1EAAAAASUVORK5CYII=" 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" 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}, "metadata": { "image/png": { @@ -916,10 +854,12 @@ { "data": { "text/plain": [ - "(
,
)" + "(
,\n", + "
,\n", + "
)" ] }, - "execution_count": 46, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -928,13 +868,14 @@ "(\n", " ggplot(fixed_pol_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", " ggplot(ppo_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", + " ggplot(results_df, aes(x='rew', fill='agent')) + geom_density(alpha=0.5),\n", ")" ] }, { "cell_type": "code", "execution_count": null, - "id": "1ac02e72-2b26-4277-8fe0-631b49c3b763", + "id": "cc61027f-a482-4d8c-bdd4-9351060a384b", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/for_results/3_policy_plots.ipynb b/notebooks/for_results/3_policy_plots.ipynb index 99d1b48..f359d86 100644 --- a/notebooks/for_results/3_policy_plots.ipynb +++ b/notebooks/for_results/3_policy_plots.ipynb @@ -772,9 +772,7 @@ { "cell_type": "markdown", "id": "2fbd46bf-f639-4fe2-bfb4-8e6ddd95bf6a", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## UM3" ] diff --git a/notebooks/for_results/4_episode_plots.ipynb b/notebooks/for_results/4_episode_plots.ipynb index a97a078..ba27a9b 100644 --- a/notebooks/for_results/4_episode_plots.ipynb +++ b/notebooks/for_results/4_episode_plots.ipynb @@ -10,13 +10,13 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 19, "id": "2e5a5d9f-2dca-4e84-85e0-f638ebcd1713", "metadata": {}, "outputs": [], "source": [ "from huggingface_hub import hf_hub_download, HfApi\n", - "from plotnine import ggplot, aes, geom_point, geom_line\n", + "from plotnine import ggplot, aes, geom_point, geom_line, ggtitle\n", "from skopt import load\n", "from stable_baselines3 import PPO\n", "\n", @@ -119,16 +119,14 @@ { "cell_type": "markdown", "id": "22e758ef-6f8d-4356-9d17-05ea02212a1b", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## Load" ] }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 3, "id": "3f3c8ad5-d4c9-41db-8361-f74f77ecb18b", "metadata": {}, "outputs": [], @@ -148,7 +146,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": 4, "id": "6013cb2d-7b22-44ee-a8b2-c70bb60bc444", "metadata": {}, "outputs": [], @@ -168,7 +166,7 @@ }, { "cell_type": "code", - "execution_count": 100, + "execution_count": 5, "id": "2c340620-3d64-421c-b7eb-5da488d4eebf", "metadata": {}, "outputs": [], @@ -191,7 +189,7 @@ }, { "cell_type": "code", - "execution_count": 109, + "execution_count": 6, "id": "c875e183-dec5-48c3-b901-b9e01b3f99fb", "metadata": {}, "outputs": [], @@ -212,9 +210,7 @@ { "cell_type": "markdown", "id": "f77e3ec2-dcbc-4a10-b4d4-b1d4c2ae1b9c", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## Utilities\n", "\n", @@ -223,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 7, "id": "57161153-9490-4588-bf1c-473bdcd6d28f", "metadata": {}, "outputs": [], @@ -292,16 +288,14 @@ { "cell_type": "markdown", "id": "5d1ddd08-656b-4676-b819-979ff99219b6", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## Reproducible noise env" ] }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 8, "id": "381c0204-ff17-425a-a222-ce385f24d23d", "metadata": {}, "outputs": [], @@ -322,9 +316,7 @@ { "cell_type": "markdown", "id": "ff7b86b8-cf75-4889-ab7d-a8dc3f4abbaf", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## UM1\n", "\n", @@ -333,7 +325,7 @@ }, { "cell_type": "code", - "execution_count": 115, + "execution_count": 9, "id": "f7d75696-1bea-4bf0-b6a0-58a14f5561e4", "metadata": { "scrolled": true @@ -374,23 +366,23 @@ }, { "cell_type": "code", - "execution_count": 116, + "execution_count": 10, "id": "22240bd9-936c-46f8-9f11-ac8063f0642a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 116, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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", 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", 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", 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", 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+nw/33XcfKisr8X//938xx//ll1/iiy++wA033JCUSicgkDH0Wx6PgMAAwPr167VLLrlEq62t1fx+v5afn68de+yx2h/+8Aetu7ubbffSSy9pBx98sBYMBrXa2lrtrrvu0h5//HENgLZlyxa2naIo2i9+8QutrKxMy83N1ebMmaNt3LgxJrVX00glzlGjRmkej8eUHmqXyrp3717tggsu0MrKyjS/369NmTIlJn2Wpvb+7ne/i/mesKS87tixQ/ve976nFRUVaYWFhdqZZ56p7dq1K2Y7mtpbX1/veA53796teTwebdy4cY7bWOFUgVXTyDkcPXq0Nnr0aC0ajWqapml///vftVGjRml+v1+bNm2a9vrrr7tK7dU0cu7mz5+v1dTUaD6fT6uqqtJOOukk7bHHHjNtd+ihh8ak2zoBXPqt9Z8V//vf/7RjjjlGCwaDWnl5uTZ//nyWjs3jww8/1E499VStqqpK8/l82rhx47Tbb79di0Qipu1mzJhhu5/t27drZ5xxhlZQUKDl5eVp3/72t7UNGzbYHv8NN9ygAdC++OILV99XQCDTkDTNxTJAQEBAwAENDQ2orq7GzTffjJtuuqm/DycltLW1oaSkBA888EDSRewEBAR6D+EZERAQ6BUWLVoERVFw3nnn9fehpIxly5Zh6NChuOSSS/r7UAQEshJCGREQEEgJb7/9NtasWYObbroJs2bNwosvvtjfhyQgIDBIIciIgIBASpg5cyaWL1+OY489Fn//+99T6kUjICAgAAgyIiAgICAgINDPEJ4RAQEBAQEBgX6FICMCAgICAgIC/YpBUfRMVVXs2rUL+fn5okCPgICAgIDAIIGmaWhra8OQIUNimn3yGBRkZNeuXaipqenvwxAQEBAQEBBIAdu3b49pBMljUJARWu56+/btrP27gICAgICAwMBGa2srampqEratSJqMLFu2DL/73e/w6aefYvfu3fjXv/6F7373u67e+/7772PGjBmYPHkyVq1a5XqfNDRTUFAgyIiAgICAgMAgQyKLRdIG1o6ODkydOhUPPfRQUu9rbm7GvHnzcNJJJyW7SwEBAQEBAYEDGEkrI6eeeipOPfXUpHd02WWX4dxzz4XH48G///3vpN8vICAgICAgcGCiT1J7n3jiCWzevBkLFixwtX1PTw9aW1tN/wQEBAQEBAQOTGTcwLphwwbccMMN+N///gev193u7rzzTtx6660ZPjIBAQGBwQ9FURCJRPr7MASyFD6fDx6Pp9efk1EyoigKzj33XNx6660YN26c6/fdeOONuPbaa9n/qRtXQEBAQIBA0zTs2bMHzc3N/X0oAlmOoqIiVFVV9aoOWEbJSFtbGz755BN89tlnuPLKKwGQAmaapsHr9eKNN97AiSeeGPO+QCCAQCCQyUMTEBAQGNSgRKSiogK5ubmiIKRAn0PTNHR2dmLfvn0AgOrq6pQ/K6NkpKCgAKtXrzY99/DDD+Ptt9/GCy+8gJEjR2Zy9wICAgIHJBRFYUSktLS0vw9HIIuRk5MDANi3bx8qKipSDtkkTUba29uxceNG9v8tW7Zg1apVKCkpwfDhw3HjjTdi586d+Otf/wpZljF58mTT+ysqKhAMBmOeFxAQEBBwB+oRyc3N7ecjERAwrsNIJNJ3ZOSTTz7BrFmz2P+pt+PHP/4xFi1ahN27d6Ouri6lgxEQEBAQcA8RmhEYCEjHdShpmqal4VgyitbWVhQWFqKlpUVUYBUQEMh6dHd3Y8uWLRg5ciSCwWB/H45AliPe9eh2/u6TOiMCAgICAgIAMHPmTFx99dWOr9fW1uKBBx7os+MRGBgYFI3yBAQEBASyAx9//DFCoVB/H4ZAHyOryci+tm70RFSU5QWQ4+990RYBAQEBgd6hvLy8vw9BoB+Q1WGaS//6KY6/+x38b0N9fx+KgICAQNYgGo3iyiuvRGFhIcrKynDTTTeB2hetYZq6ujqcdtppyMvLQ0FBAc466yzs3buXvX7LLbdg2rRpePzxxzF8+HDk5eXhiiuugKIouPvuu1FVVYWKigrcfvvtpmO47777MGXKFIRCIdTU1OCKK65Ae3s7e33btm2YO3cuiouLEQqFMGnSJLz66qsAgKamJvzwhz9EeXk5cnJyMHbsWDzxxBMZPGMHPrJaGaEG4AHv4BUQEBBIAE3T0BVR+mXfOT5PUhkVTz75JC666CJ89NFH+OSTT3DppZdi+PDhuOSSS0zbqarKiMi7776LaDSK+fPn4+yzz8bSpUvZdps2bcLixYvx2muvYdOmTTjjjDOwefNmjBs3Du+++y6WL1+OCy+8ELNnz8aRRx4JAJBlGQ8++CBGjhyJzZs344orrsD111+Phx9+GAAwf/58hMNhLFu2DKFQCGvWrEFeXh4A4KabbsKaNWuwePFilJWVYePGjejq6urlWcxuZDUZkfWbZ+DnEwkICAjER1dEwUE3v94v+15z2xzk+t1PJzU1Nbj//vshSRLGjx+P1atX4/77748hI0uWLMHq1auxZcsW1hLkr3/9KyZNmoSPP/4Yhx9+OABCWh5//HHk5+fjoIMOwqxZs7Bu3Tq8+uqrkGUZ48ePx1133YV33nmHkRHeRFtbW4vf/va3uOyyyxgZqaurw+mnn44pU6YAAEaNGsW2r6urw/Tp03HYYYex9wv0DlkdpqE8fhBkNwsICAgcMDjqqKNMSsrRRx+NDRs2QFHMys7atWtRU1Nj6k120EEHoaioCGvXrmXP1dbWIj8/n/2/srISBx10EGRZNj1Hy5YDwFtvvYWTTjoJQ4cORX5+Ps477zzs378fnZ2dAICrrroKv/3tb3HsscdiwYIF+OKLL9h7L7/8cjz77LOYNm0arr/+eixfvjwNZyW7kdXKiAjTCAgIHCjI8Xmw5rY5/bbv/oTP5zP9X5Ik2+dUVQUAbN26Fd/+9rdx+eWX4/bbb0dJSQnee+89XHTRRQiHw8jNzcXFF1+MOXPm4L///S/eeOMN3Hnnnbj33nvx05/+FKeeeiq2bduGV199FW+++SZOOukkzJ8/H/fcc0+ffecDDdmtjIgwjYCAwAECSZKQ6/f2y79kK3B++OGHpv9/8MEHGDt2bEwp8YkTJ2L79u3Yvn07e27NmjVobm7GQQcdlPK5+vTTT6GqKu69914cddRRGDduHHbt2hWzXU1NDS677DK8+OKL+L//+z8sXLiQvVZeXo4f//jH+Pvf/44HHngAjz32WMrHI5Dtyoj+qAo2IiAgINBnqKurw7XXXouf/OQnWLlyJf7whz/g3nvvjdlu9uzZmDJlCn74wx/igQceQDQaxRVXXIEZM2Ywv0YqGDNmDCKRCP7whz9g7ty5eP/99/Hoo4+atrn66qtx6qmnYty4cWhqasI777yDiRMnAgBuvvlmHHrooZg0aRJ6enrwyiuvsNcEUkOWKyPkUVARAQEBgb7DvHnz0NXVhSOOOALz58/Hz372M1x66aUx20mShP/85z8oLi7GCSecgNmzZ2PUqFF47rnnerX/qVOn4r777sNdd92FyZMn46mnnsKdd95p2kZRFMyfPx8TJ07EKaecgnHjxjFzq9/vx4033oiDDz4YJ5xwAjweD5599tleHVO2I6t705y78AMs37Qfv//BNJw2bWjaPldAQEAgkxC9aQQGEkRvml6CKSMDno4JCAgICAgcuMhuMqK7RjQRqBEQEBAQEOg3ZDcZEcqIgICAgIBAvyPLyQhhI6ogIwICAgICAv2G7CYj+uMg8PAKCAgICAgcsMhqMiKL1F4BAQEBAYF+R1aTEaMCq6AjAgICAgIC/YWsJiOyMLAKCAgICAj0O7KajICl9goICAgICAj0F7KajNDUXtGbRkBAQEBAoP+Q1WREhGkEBAQEBNINSZLw73//u78PY1Ahq8mIJMI0AgICAgIC/Y7sJiNMGRF0REBAQKAvMHPmTPz0pz/F1VdfjeLiYlRWVmLhwoXo6OjABRdcgPz8fIwZMwaLFy9m7/nyyy9x6qmnIi8vD5WVlTjvvPPQ0NDAXn/ttddw3HHHoaioCKWlpfj2t7+NTZs2sde3bt0KSZLw4osvYtasWcjNzcXUqVOxYsWKhMeraRrKy8vxwgsvsOemTZuG6upq9v/33nsPgUAAnZ2dqK2tBQB873vfgyRJ7P8C8ZHVZERmqb39fCACAgICvYWmAeGO/vmX5CD65JNPoqysDB999BF++tOf4vLLL8eZZ56JY445BitXrsQ3vvENnHfeeejs7ERzczNOPPFETJ8+HZ988glee+017N27F2eddRb7vI6ODlx77bX45JNPsGTJEsiyjO9973tQVdW031/96le47rrrsGrVKowbNw7nnHMOotFo3GOVJAknnHACli5dCgBoamrC2rVr0dXVha+//hoA8O677+Lwww9Hbm4uPv74YwDAE088gd27d7P/C8SHt78PoF8hDKwCAgIHCiKdwB1D+mffv9wF+EOuN586dSp+/etfAwBuvPFG/L//9/9QVlaGSy65BABw880345FHHsEXX3yBt956C9OnT8cdd9zB3v/444+jpqYG69evx7hx43D66aebPv/xxx9HeXk51qxZg8mTJ7Pnr7vuOnzrW98CANx6662YNGkSNm7ciAkTJsQ93pkzZ+JPf/oTAGDZsmWYPn06qqqqsHTpUkyYMAFLly7FjBkzAADl5eUAgKKiIlRVVbk+J9mOrFZGjHLw/XoYAgICAlmFgw8+mP3t8XhQWlqKKVOmsOcqKysBAPv27cPnn3+Od955B3l5eewfJQ80FLNhwwacc845GDVqFAoKClhopK6uznG/NMyyb9++hMc7Y8YMrFmzBvX19Xj33Xcxc+ZMzJw5E0uXLkUkEsHy5csxc+bM5E+EAENWKyMsTNPPxyEgICDQa/hyiULRX/tOZnOfz/R/SZJMz7EmpqqK9vZ2zJ07F3fddVfM51BCMXfuXIwYMQILFy7EkCFDoKoqJk+ejHA47Lhffh+JMGXKFJSUlODdd9/Fu+++i9tvvx1VVVW466678PHHHyMSieCYY45x+e0F7JDVZEQYWAUEBA4YSFJSoZLBgkMOOQT//Oc/UVtbC683dsrav38/1q1bh4ULF+L4448HQAyl6YQkSTj++OPxn//8B1999RWOO+445ObmoqenB3/6059w2GGHIRQyzr3P54OiKGk9hgMdIkwDEaYREBAQGKiYP38+Ghsbcc455+Djjz/Gpk2b8Prrr+OCCy6AoigoLi5GaWkpHnvsMWzcuBFvv/02rr322rQfx8yZM/HMM89g2rRpyMvLgyzLOOGEE/DUU08xvwhFbW0tlixZgj179qCpqSntx3IgIqvJiBGmEWxEQEBAYCBiyJAheP/996EoCr7xjW9gypQpuPrqq1FUVARZliHLMp599ll8+umnmDx5Mq655hr87ne/S/txzJgxA4qimLwhM2fOjHkOAO699168+eabqKmpwfTp09N+LAciJG0QxChaW1tRWFiIlpYWFBQUpO1zr31+FV5cuRM3nDoBl80YnbbPFRAQEMgkuru7sWXLFowcORLBYLC/D0cgyxHvenQ7f2e1MsIqsA54OiYgICAgIHDgIqvJCOtNI8I0AgICAlkLWt3V7h9f30QgcxDZNBDKiICAgEA2489//jO6urpsXyspKenjo8lOZDcZYWEawUYEBAQEshVDhw7t70PIemR3mEb/9oKLCAgICAgI9B+SJiPLli3D3LlzMWTIEEiShH//+99xt3/xxRdx8skno7y8HAUFBTj66KPx+uuvp3q8aYZegU+QEQEBAQEBgX5D0mSko6MDU6dOxUMPPeRq+2XLluHkk0/Gq6++ik8//RSzZs3C3Llz8dlnnyV9sOmGJAysAgICAgIC/Y6kPSOnnnoqTj31VNfbP/DAA6b/33HHHfjPf/6Dl19+ud+LwcjCwCogICAgINDv6HPPiKqqaGtrGxAOZWFgFRAQEBAQ6H/0ORm555570N7ejrPOOstxm56eHrS2tpr+ZQJGmEZAQEBAoC+gaRouvfRSlJSUQJIkFBUV4eqrr3b13pkzZybc1o2XMZ245ZZbMG3atD7bX2/Q1+cmGfQpGXn66adx66234vnnn0dFRYXjdnfeeScKCwvZv5qamowcD+tNI9iIgICAQJ/gtddew6JFi/DKK69g9+7dWL9+PX7zm9+k7fN3796dlJWgt7juuuuwZMmSpN5TW1sbY2HoC/DnZuvWrZAkCatWrerz47BDn5GRZ599FhdffDGef/55zJ49O+62N954I1paWti/7du3Z/TYVMFGBAQEBPoEmzZtQnV1NY455hhUVVWhoqIC+fn5afv8qqoqBAKBtH1eIuTl5aG0tLTP9tcb9PW5SQZ9QkaeeeYZXHDBBXjmmWfwrW99K+H2gUAABQUFpn+ZgNG1V0BAQEAg0zj//PPx05/+FHV1dZAkCbW1tTGhl4cffhhjx45FMBhEZWUlzjjjDNNnqKqK66+/HiUlJaiqqsItt9xiep0PRdDV/4svvohZs2YhNzcXU6dOxYoVK0zvWbhwIWpqapCbm4vvfe97uO+++1BUVOTqO1nDNOeffz6++93v4p577kF1dTVKS0sxf/58RCIRACTUtG3bNlxzzTWQJAkS9QsAeO+993D88ccjJycHNTU1uOqqq9DR0cFer62txR133IELL7wQ+fn5GD58OB577DH2ejgcxpVXXonq6moEg0GMGDECd955p+25GTlyJABg+vTpkCQJM2fOxLJly+Dz+bBnzx7Td7z66qtx/PHHuzofqSJpMtLe3o5Vq1YxaWfLli1YtWoV6urqABBVY968eWz7p59+GvPmzcO9996LI488Env27MGePXvQ0tKSnm/QC4hy8AICAgcKNE1DZ6SzX/65TQL4/e9/j9tuuw3Dhg3D7t278fHHH5te/+STT3DVVVfhtttuw7p16/Daa6/hhBNOMG3z5JNPIhQK4cMPP8Tdd9+N2267DW+++Wbc/f7qV7/Cddddh1WrVmHcuHE455xzEI1GAQDvv/8+LrvsMvzsZz/DqlWrcPLJJ+P2229P4szH4p133sGmTZvwzjvv4Mknn8SiRYuwaNEiAKT21rBhw3Dbbbdh9+7d2L17NwCiGJ1yyik4/fTT8cUXX+C5557De++9hyuvvNL02ffeey8OO+wwfPbZZ7jiiitw+eWXY926dQCABx98EC+99BKef/55rFu3Dk899RRqa2ttj/Gjjz4CALz11lvYvXs3XnzxRZxwwgkYNWoU/va3v7HtIpEInnrqKVx44YW9OieJkHRq7yeffIJZs2ax/1977bUAgB//+MdYtGgRdu/ezYgJADz22GOIRqOYP38+5s+fz56n2/cnKB8V2TQCAgKDHV3RLhz59JH9su8Pz/0Qub7chNsVFhYiPz8fHo8HVVVVMa/X1dUhFArh29/+NvLz8zFixIiYEhAHH3wwFixYAAAYO3Ys/vjHP2LJkiU4+eSTHfd73XXXMVX+1ltvxaRJk7Bx40ZMmDABf/jDH3DqqafiuuuuAwCMGzcOy5cvxyuvvOL6+1tRXFyMP/7xj/B4PJgwYQK+9a1vYcmSJbjkkktQUlICj8eD/Px80zm488478cMf/pCpRGPHjsWDDz6IGTNm4JFHHkEwGAQAfPOb38QVV1wBAPjFL36B+++/H++88w7Gjx+Puro6jB07FscddxwkScKIESMcj7G8vBwAUFpaajqOiy66CE888QR+/vOfAwBefvlldHd3x006SQeSVkZmzpwJTdNi/lFisWjRIixdupRtv3Tp0rjb9ydkWYRpBAQEBAYKTj75ZIwYMQKjRo3Ceeedh6eeegqdnZ2mbQ4++GDT/6urq7Fv3764n8u/p7q6GgDYe9atW4cjjjjCtL31/8li0qRJ8Hg8SR3j559/jkWLFpk6Bs+ZMweqqmLLli2230WSJFRVVbHPPv/887Fq1SqMHz8eV111Fd54442kj/3888/Hxo0b8cEHHwAgc/pZZ52FUCiU9GclgyxvlEcglBEBAYHBjhxvDj4898N+23c6kJ+fj5UrV2Lp0qV44403cPPNN+OWW27Bxx9/zDwcPp/P9B5JkqCqatzP5d9DPRqJ3tMbpHKM7e3t+MlPfoKrrroq5rXhw4e7+uxDDjkEW7ZsweLFi/HWW2/hrLPOwuzZs/HCCy+4PvaKigrMnTsXTzzxBEaOHInFixebBIZMIavJCGUjojeNgIDAYIckSa5CJQMdXq8Xs2fPxuzZs7FgwQIUFRXh7bffxve///2M7G/8+PEx3hXr/9MNv98PRVFMzx1yyCFYs2YNxowZ06vPLigowNlnn42zzz4bZ5xxBk455RQ0NjbGFBr1+/0AEHMcAHDxxRfjnHPOwbBhwzB69Ggce+yxvTomN8hqMiLqjAgICAgMHLzyyivYvHkzTjjhBBQXF+PVV1+FqqoYP358xvb505/+FCeccALuu+8+zJ07F2+//TYWL15synJJN2pra7Fs2TL84Ac/QCAQQFlZGX7xi1/gqKOOwpVXXomLL74YoVAIa9aswZtvvok//vGPrj73vvvuQ3V1NaZPnw5ZlvGPf/wDVVVVtplBFRUVyMnJwWuvvYZhw4YhGAyisLAQADBnzhwUFBTgt7/9LW677bZ0fnVH9HkF1oEEFqYRrhEBAQGBfkdRURFefPFFnHjiiZg4cSIeffRRPPPMM5g0aVLG9nnsscfi0UcfxX333YepU6fitddewzXXXMMMo5nAbbfdhq1bt2L06NHMSHrwwQfj3Xffxfr163H88cdj+vTpuPnmmzFkyBDXn5ufn4+7774bhx12GA4//HBs3boVr776KmQ5dqr3er148MEH8ac//QlDhgzBaaedxl6TZRnnn38+FEUxZcdmEpI2CAwTra2tKCwsREtLS1prjvzu9a/x0DubcP4xtbjlO5m72AUEBATSie7ubmzZsgUjR47M6KSZrbjkkkvw9ddf43//+19/H0q/4aKLLkJ9fT1eeumlhNvGux7dzt8iTANhYBUQEBDIZtxzzz04+eSTEQqFsHjxYjz55JN4+OGH+/uw+gUtLS1YvXo1nn76aVdEJF3IajJihGkEBAQEBLIVH330Ee6++260tbVh1KhRePDBB3HxxRcDIGm627Zts33fn/70J/zwhz/sy0PNOE477TR89NFHuOyyy+LWbkk3spqM0BKsojeNgICAQPbi+eefd3zt1VdfZaXcraisrMzUIfUb+iKN1w5ZTUZkUQ5eQEBAQCAO4lUxFUgfsjybRlRgFRAQEBAQ6G9kNxlhyoigIwICAoMPmawiKiDgFum4DkWYBiJMIyAgMLjg9/shyzJ27dqF8vJy+P3+jBbpEhCwg6ZpCIfDqK+vhyzLrKprKshqMiKJCqwCAgKDELIsY+TIkdi9ezd27drV34cjkOXIzc3F8OHDbYuruUVWkxEKkU0jICCQbmiahrrGTtQU57IO4emE3+/H8OHDEY1GbfuLCAj0BTweD7xeb6+VuawmI6zoWT8fh4CAwIGHv32wDTf/5yv8ZMYo3HjqxIzsQ5Ik+Hy+mE6uAgKDDcLAChGmERAQSD/ueHUtAOBP727u5yMREBj4yG4yoj+KbBoBAYF0ozw/0N+HICAwaJDVZESEaQQEBDKF8jxBRgQE3CKryYioMyIgIJAp8MqIoooxRkAgHrKajFCIcUJAQCDdKAkZZKShvacfj0RAYOAjq8mICNMICAhkDsbIsqu5qx+PQ0Bg4COryQgN04g6IwICAulGVDHGld0t3f14JAICAx/ZTUboH4KLCAgIpBm8T0SQEQGB+MhqMkKrImqCjQgICKQZUZ6MiDCNgEBcZDUZocqIaHwpICCQbghlREDAPbKbjEhCGREQEMgMotwqpzMc7ccjERAY+MhyMkIehX9VQEAg3eCVEUWMMQICcZHdZEQP1Ig6IwICAukG7xlRxSAjIBAXWU1GZJFOIyAgkCGYlBFBRgQE4iKryYgI0wgICGQKfJ0RUctIQCA+spuMsDCNGCgEBATSC14NEWOMgEB8ZDcZocpI/x6GgIDAAQg+myabwzT/9/znOOvRFYgqooaCgDOynIzoqb3ZO04ICAhkCGZlpB8PpJ/xz5U78NHWRnywubG/D0VgACO7yYj+KCRUAQGBdCMiPCMm7O8QnYsFnJHVZETO6m8vICCQSYhsGnNKc2NHuB+PRGCgI6unY2pgFYsWAQGBdIP3jGQpF4HCDa5NgowIxEF2kxE9TiMkVAEBgXRDEUXPTOegsVOQEQFnZDkZEcqIgIBAZhA1lYPPzkEmKsI0Ai6R3WREfxSN8gQEBNINoYxYlBFBRgTiIGkysmzZMsydOxdDhgyBJEn497//nfA9S5cuxSGHHIJAIIAxY8Zg0aJFKRxq+mGEafr3OAQEBA48REXRMxMZaeqI9OORCAx0JE1GOjo6MHXqVDz00EOutt+yZQu+9a1vYdasWVi1ahWuvvpqXHzxxXj99deTPth0QxZVzwQEBDIERYRpTCZekdorEA/eZN9w6qmn4tRTT3W9/aOPPoqRI0fi3nvvBQBMnDgR7733Hu6//37MmTMn2d2nFSJMIyAgkCnwFUfVLC0+yhOy/R1hRBUVXk9WuwMEHJDxq2LFihWYPXu26bk5c+ZgxYoVju/p6elBa2ur6V8mIMI0AgICmYLoTWNuFqhpwjci4IyMk5E9e/agsrLS9FxlZSVaW1vR1dVl+54777wThYWF7F9NTU1Gjs3IpsnOgUJAQCBziIqiZzHfe1+bCNUI2GNA6mU33ngjWlpa2L/t27dnZD9GmEZAQEAgvRDKiJmQAUBrtzCxCtgjac9IsqiqqsLevXtNz+3duxcFBQXIycmxfU8gEEAgEMj0oTFlJEsXLQICAhmCpmlCGUHs985W74xAYmRcGTn66KOxZMkS03Nvvvkmjj766EzvOiFkJo1k50AhICCQGVi5R5ZykRgyEhVsRMABSZOR9vZ2rFq1CqtWrQJAUndXrVqFuro6ACTEMm/ePLb9ZZddhs2bN+P666/H119/jYcffhjPP/88rrnmmvR8g15AZPYKCAhkAtZJVxQ9I8jWcJVAYiRNRj755BNMnz4d06dPBwBce+21mD59Om6++WYAwO7duxkxAYCRI0fiv//9L958801MnToV9957L/785z/3e1ovYDTKEzeIgIBAOmGdhEWdEQJFCCMCDkjaMzJz5sy42Sd21VVnzpyJzz77LNldZRxMGcnOcUJAQCBDiChCEQBsSJkI0wg4YEBm0/QVRKM8AQGBTEAYNwms2TRCGRFwQlaTEZkVPRNsREBAIH2ICU9k6RgjwlUCbpHVZERilUYEBAQE0gdh3CSIVUaENCJgj+wmI8IzIiAgkAFELZ4RTRv8lZ6/2NGMa59bhY372ly/x5pFJMI0Ak7IeNGzgQxJhGkEBAQyALsiZ4qqwesZnGrs59ubcdpD7wMASvP8+NW3DnL1Pqsykq0pzgKJkd3KiB6mEbeHgIBAOkEnYZnjHoPZL/Hk8q3s75Yu9yXdrWGZwXwOBDKL7CYjLEwjbhABAYH0gSojPo8xxA7mYaYzrLC/+e+UCFZlxPp/AQGKrCYjskjtFRAQyABoNo3fawyxg7k/Tap9dmJTnAfvORDILLKajIhy8AICApkAnYQDPBkZxKsePtySjLphNfIOZkImkFlkNxnRH0WYRkBAIJ2I2oVpBnEmSbqUEUFGBJyQ3WREor1p+vlABAQEDijQSdd/wCgjxrEnpYyIomcCLpHlZIQ8aiJQIyAgkEbQ8ASvjAxmVYAPtyRTuMxKPgbzORDILLKbjOiPgqwLCAikE3TS9coSPDI1yg/egYYvb2/1gcSDoli79g7ecyCQWWQ1GRHZNAICWYq2vcA/LgDeXAA0b0/7x9PJ2+uRWK2RwRyiUFL0jMSWgx+850AgsxAVWDG4VywCAgIp4I1fA1+9SP7e+j/gkrfT+vF00vXIsr7o0Qb1RBxN0TMievQIuEVWKyO0AusgHiMEBASSxa5VwOrnjf/vXQOkuYFbRIkN0wzmHnHpUkZE0TMBJ2Q3GREGVgGB7MOHfyKPB30XkL1AtAto35PWXRjKiMTCwYNZFTArI0kYWEXRMwGXEGQEwjMiIJA1iHQBa18mfx95GVBYQ/5u3JzW3TDPiCw8I06fIyDAI7vJiAjTCAhkF9a/BoTbgMLhQM2RQMko8nyayQivjBhhmsE70ERTrMBq/c4iTCPghKwmIzL79uIGERDIClBVZMrpZABgZGRLWncT5VJ75QOguKKipEcZGcyhKoHMIqvJCFVGxP0hIJAlqPuQPI4+kTyWjCSPGVNGZMi6MjKYQxQmz0gydUZUUWdEwB2ym4zosVzB1gUEsgAtO4DWHYDkAYYeSp7LUJiGV0Y8B4CBNV2ekcF8DgQyi6wmI7Lo2isgkD2o+4A8Vk0B/CHyNyUjTVvTuitaedTjMTwjg1kV6G02jc9DzkEyqopAdiGryQhEmEbADZrrgJ0r+/soBHqL7XqIZvhRxnP51eSxpxUId6ZtV7wyciAosFGurHsqyohf79EzmDOKBDKLrCYjB8IgIZBhqCrw5HeAP88mxbEEBi92fkoea44wngvkAx4/+buzIW27ss2mGcTjTMoVWBVz9+LBnFEkkFlkNRmRJRGnEUiA3auApi2ApgCr/9HfRyOQKlQV2Pc1+btysvG8JAGhcvJ3R/rIiJ1nRMniCqyUjIjUXgEnZDUZYV17+/UoBAY01i02/v7ynyKmx6NhA7D2lf4+Cndo2Q5EOgDZZ/hEKHJLyWMayQifTTPYFVhN01JWRuh3Dng9pv8LCFiR1WTkQCjTLJBh8GSkeRtRSgSAaA8JXT33Q2Djkv4+msSo11WRsrGAx2d+jSkj9WnbnUkZGeRFz6yH3RtlZDCbeAUyi6wmI6IcvEBcNNcBe1cDkgxUTyXP7f2qf49poGDVU0B3M/l75V/79VBcYd9a8lg+Ifa1UBl5TKtnRM+m4YqeDVbzpjV7JppEvImeB2ZgzSAZeeajOjy4ZEPGPl8gs8hqMkIhGuUJ2GL96+Sx5iiDjLTs6L/jGSjoagKW3Wv8f8MbQE97/x2PG1BlpGJi7GsZVkYGewVWK4FIShlR+kYZUVQNN764Gve9uR5bGzoysg+BzCKryYgsD+5BQiDDWPcqeRx/qtFQLdvJiKYB/55PiocVDSepsZFOYONb/X1k8UGVEVsyoisjHfvTtjs6CfN1RgZrmMbqEUkqm8YapsnQKWjqDLO/hUl2cCKryQg1sAphRCAG3a3Alv+Rv8d/EygcRv7OdjKy4o/Auv+SdNiz/gqMPZk8P5DDV5pGzLYAUDY+9vVcSkbSp4wovDLSF0XPGjYAjxwHrHo67R+tWBhEMh47SgwCTBnJTEpRQ3sP+1sbpOGwbEd2kxGW2Ssu3gEPJQJ8+iTQtqdv9rdpCaBGgNKxQNkYoGAoeT6byUjdB8CbC8jfp9wJDJluTO4N6/rvuBKhbQ/JpJFkoLg29vWMhGmoZ0SGXnw0s56Rf11G/E3/vjztH50OZSSQ4TDN/nZDGemJDuIc6ixGVpORwR7LzSosuwd4+SrgqTMIMck0aBbN+FPII6+MZOPKq2kb8I8LSL2VyacDh11Eni/XyUj9+v47tkRo3EQei4YDXn/s68zAmr4wDSuDznlGMrZi72kHdn5i/L9lZ1o/3kogNM19yMkapsmQMGJSRsKDuaBLFiOryQirM5KNk8tgQncr8OEj5O89q4HlD5K/6z4EVj2T/v0pUWLKBEiIBjCUkWgX0NmY/n0ORKgqIYH3TwYePgpo20WUorm/N2TFsnHkcf9Gct4GIvbrZKRktP3rIS5Mk6axgPeMGGGatHx0LNb8x/z/ze+k9ePtetG4VUcYGclwOfj6No6MCGVkUCKryQhEAdbBgc/+DnS3AP588v+ldxHl4vFvAP++LO0dV7H9Q5IxklMCDNNLh/uCQKiC/N2aJaGat28D3v6NXjCsExh6GHDev0gJdYrCGsCbQ0JaaW42lzZQZaTUgYxQz0i0GwinJxOD94x4Mp3au/FN8/83pZeM0O8iS7HPJQIlMrToWabMpQ1cmCYilJFBiawmI4Z82s8HIhAf294njzOuB8acDCg9wDM/MF7vbknv/jboKb1jTwY8XuP5bDOxfvlP8njSAuDSpcCFrwNFNeZtZJl4agCgYYCGaqgyUjrG/nV/CPDpXXzT5EmKsAlcgqyPshlRYDUN2KrfHydcTx7TXJgvopirqALuO/fGhmkyRUaEMjLYkdVkhCP6fReqyVTQdKChpz19PoLdX5DHIdOBb98PFAwzv57u3269HqIZ+w3z85SMNG9P7/4GIjobSdE3ADjsQnLueWLGY6CbWKly5hSmkSSgUA/DpUn1ooXB/F7ZKHqWiYl4/0agYx/gCQAHfYc8174vrbtgJlSfHPNcIvRVBVZBRgY/UiIjDz30EGpraxEMBnHkkUfio48+irv9Aw88gPHjxyMnJwc1NTW45ppr0N3dndIBpxOSZNCRjHOR7hbg1Z8Ddw4DPnwswzsbAHjpp8BDhwNrX+7d53Q2Ai36pFg1hazMf/oJcOm7gERXamn88ZrrgPq1JPNi9Inm12gmRrrDQgMRuz4jjyWjgZyi+NsOZBOrqhq/V+ko5+1YtlR6zJ9UTfDKMqszkpGJmKqGww4jBl0A6GkFwp1p2wVVQXwemXsuOc+IL8kKrOv3tuH4u9/G85+4I/7CwDr4kTQZee6553DttddiwYIFWLlyJaZOnYo5c+Zg3z57Nv7000/jhhtuwIIFC7B27Vr85S9/wXPPPYdf/vKXvT743oKPgWa0P80nTwD3jAc+eoykGC6+3qhhcSBCVYCvXiR/P/cj0sckVezRVZHiWmNS9OUAQ6YZSkU6fztqXK05EsgtMb9GPQfUg3Agg5KRIdMTb0tNrL1RRr76F/DgdGDXqtQ/ww7te4kXRPIAhcOdt6PXUmt6yAidwL0eKbM9sLa+Rx5HHAsECoh/ByDfO03gM4O8SRKrmDojLs/Bz55dhe2NXbj+hS9cbd/QZnhGhDIyOJE0GbnvvvtwySWX4IILLsBBBx2ERx99FLm5uXj88cdtt1++fDmOPfZYnHvuuaitrcU3vvENnHPOOQnVlL6AxAVqMkZFupqA139JsjDKxgN5VWRv7/8+U3vsf9BqlxRfPJf6Z9EQTdXBsa9JNBifxsFng24GpMW8eFDPwX5BRkzglZFUJlxVBf5xPlEwFv8i+ffHAw01FQ51DjMBnB8oPSE4mk3j82SwHLyqApveJn+PmknCTXm6yTqNoRpKKPhqskln0yTpGdm2372RWNM07O8QyshgR1JkJBwO49NPP8Xs2bOND5BlzJ49GytWrLB9zzHHHINPP/2UkY/Nmzfj1VdfxTe/+c1eHHaawCkjGRNGPl1EMhEqJgHzPyRVK4GBXbGyt9j+gfn/dGJLBbs/J4+0NwyPdJORSBew+V3y99g5sa9Tz0FzXd/UOulP7FlNHu3OuxUlo8hvEW5LzQC6+W3j7/q16b0Zm7eRx6IR8bdLe5hGV0ZkGTS6kfYwze5VpDaKPx+o0bO+8irJY3v6igMamUGyoYy4rOtuLXrmlsR0hhXXx9fSFWFhMQCICGVkUCLOUiEWDQ0NUBQFlZWVpucrKyvx9ddf277n3HPPRUNDA4477jhomoZoNIrLLrssbpimp6cHPT0G021tbU3mMF2jT8I0n+iK0dHzycqF9sZo26WnjxZnZr/9ie266lU8EmjaAtT3Qr6nYZq+ICNb3ycKVsFQoHJS7Ov5VSTrItJBioCVOWRnDHaoihGuKInjs6DwBshv3biJhGoKqpPb32d/N/7ubiFEvWpycp/hBLdkJM2ZUlHVUEZYb5p0jzEbl5DHUTMAj4/8nU/JSBqVEVozReaVkeSyaTJZgbXDQlyEMjI4kfFsmqVLl+KOO+7Aww8/jJUrV+LFF1/Ef//7X/zmN79xfM+dd96JwsJC9q+mpsZx296AN7BmBC07yCpa8gAHnUaeCxYYTdes4YwDBTs+Jo+HnEceUyUj4Q6jp0hfkBE+pdfu2pAkY3LevzE9+xyI6KgH1Cg5v3mVibcHemdipaE46new1s3oDZooGYnjFwHMnpE0kIYop4zQcSbtaa20OeGYk4znmDKSfs+IV5bgTdKISkkLC9O4OLf8ecrxeeJsSWD1iAjPyOBEUmSkrKwMHo8He/eaL/S9e/eiqqrK9j033XQTzjvvPFx88cWYMmUKvve97+GOO+7AnXfeCdWBXd94441oaWlh/7Zvz0wqpTm1NwM72P4heayaAgTyjOepOrJvTQZ22s9QosYEMFEnYJ0NQEdD8p+150sAGvHZ0Fg4j3SSEU0zzKvWlF4efWliTdRFVtPINum+eGmoIr86vs+CR6omViVqqBeH6yXm6z5w3j5ZUM9IscswTbg9LXVrWDaNhy961uuPNdBeb4wvfEiRkpE09nDizbi99Yy4eR+fGVMSsinfb4G1yFk4U62BBTKKpMiI3+/HoYceiiVLlrDnVFXFkiVLcPTRR9u+p7OzE7Js3o3HQ9iuU22PQCCAgoIC079MQOZWvxkJ09Tpg0XNkebnGRk5AJWRtl2kf4nHT1QEuiJNRR1hIRob8yqQXjLSsIFUEPX4gZEznLcrG0seM+n5ifYA/74C+N0o5zTwjUuAeyeQbVY8lN790xBNwRD376HN5rqTDKm27iAqjCcATJxLntv5afoIVrNLZcSfSyruAmkxsfLpsCxMk05lZP1rADSgeppRIwXglJH0hWkoofDwnpFk64zoY76bc7C9qYt7f+J7WygjBwaSDtNce+21WLhwIZ588kmsXbsWl19+OTo6OnDBBRcAAObNm4cbb7yRbT937lw88sgjePbZZ7Flyxa8+eabuOmmmzB37lxGSvoLvBKf6jARt1gaXblQcxlFhe5H2HsAKiMse6GGVOcsn0D+X2/vKYoLWknSyUSZTjJCQzQjjjWrWFYMP4o8bn43c67nd24HVj1F/nbKRPr4z4ZJ8Ytn07v/1l3kMRkyIuv3crK/ReMW8lg8gvzOspeEidLh3VAV43MSeUYAI9TUG8O1jiirMyKxcSatC56v/0seJ3zL/HwGwjRRLkyTtDKiWIqeuTgHO5qMGiluOvDGKCOCjLjDACs9npSBFQDOPvts1NfX4+abb8aePXswbdo0vPbaa8zUWldXZ1JCfv3rX0OSJPz617/Gzp07UV5ejrlz5+L2229P37dIA1KpwPqTv32CLQ0deOWnx7ObjSHcYWQkWJWRkpHk8UDscWKN0ZeNI+GPVEqF05oTdmm9gMEmE0yAmqYl9gete408xgvRAMDwY4h60rqD+EaoUpJO0GMBSDZRuIOULOfB1+PYs5rI9nnl6dk/vS6tlW7jgRFD91kQAIjBGSAGWF8OMQ7v/pyoI9bS88mibTdRXWQfMR8nQu3xQN0KYMsy4JB5vdp1hIU25PT3pon2AFv0rK/xp5pfY6m96feMeEx1RtxN+KlUYN3BKSPdkcTXU8QSlhG9aVygZQfw+CnApO8C3/htfx8NgBQNrFdeeSW2bduGnp4efPjhhzjySGOyXbp0KRYtWsT+7/V6sWDBAmzcuBFdXV2oq6vDQw89hKKiot4ee69hDtMk996IouL1r/Zi/d52fLnLJsa8cyUZmAuGxg6quaXkMZEnYDCCKiOUjFDDJyUpbtHZaIRCrGSOgk2Azj/eLS99hRN+9w6aOsKO26B9n1HJcuK34x+XP5dTR5bG3zYVdDYavgtfLmlAZ/VQtO8j4TBIZBIHjMkpHUhFGUlVpWKl2vXrZOih5HHnp8l9jh1o2f7CoYZyEw8jTyCPW5b1etXI1xlJe5hmx8ekXECoHKi0ZB1R0tW+L6b1RGc4it++sgafbmtKandGmjKnjLhN7dVomMY9GWnuNO7VnqiacKEowjQp4F+XkXDk8j/095EwZHdvGpODNbn38i2r/R6b0+gUogGM+HqkI61lmwcErIZBKo/T592ibgUAjSgr+Q4ZHS4mwEXLt2J7Yxee/TiOD2Dty2RfQw9N7C0ASIEpgIRQ0t1riGYilY4BJn2P/L1lmXkbWnulbKxBnmjxq3SAkhHei5AIKZMRXRmhaiEjIyuT+xw7MO+Ly+8x7HDAGySqQi+b/vHl4GWmJrh777vr6+OXQae1cEaeEJv1RccWTQG6Gk0vLV1Xjz+/twUPvJXcdzMrI8ll01j72rh5Hx+a0bTEqbqxBlZBRuJC04CtA68CeHaTEe5vLUk2sqfV6K1jKyVudzCvAqQFu0d3iXemkGUykMGUEUpGhhvPJ7PapJ1IRxzrvE2CCbCl0yhM1shVaIzB2pfII02/ToSDf0Dqjez4GPjsb+7e4xZUBak5yvjuOz4xb8N7aWhYae0rQCRN/Z5akpzEAVcqlS2atpLHYgsZ2fUZ8Xz0BsmSEV/QUL029C692DCwSqyekVvPyI8f/wjXv/AFNtW3229AVTBKinl4fIbyasmoae+JAgAa46mENkjVM6JpmpFN43Gf2tsTMd/PiXwjVvIhlBEbrHoa+Ot3yXXNq465Zf12SFZkNRnpTZhmb4sx8MdUC1RVo/CXnTIiScYKpqM+uR0PdFizF2iIKtxGiry5BWXutcc5b5OAjNQ1GqrTtv0OClS4E9i2nPw93mVV4MKhwIm/In+nu6w/VUZqjgAqDyJ/W82/1C9SPRUYcRzxdvS0EIWnt74EVdVDQEgtTJMMgdC0WGWkbBzgzyOqYW+K5QEGqUpG4aHXwNev9GrXzMDKeUbcTMQdOmEAzOEKhkiXMZnQsJIVeTRUY/aN0Em6rTtqfUdcmLJpPO6zafhtkqnA2hM1X0Mxi72GDcCbN7NyARlXRrqa0/t5fY1IN/DaDcDmd4CnzgD+zNWl8eX233FZkNVkxJRNk+QgzisjXdabpXET0N1Mijg5mS8PRN+IEjVWo5SM+HIMh7/bUE3DBpLWK8nOAy6QkIxsazT6W6zb22b/Gds/AJQwWT2XJlFRddq55LFxU3p/QzoBV00hvYwgxdZpoUXCqqeRjKVp55D/v3gxSfd993epk5LO/cT0Ccl9wTMgtWya9n2EdEiycb3IHqMfTm99I8kqI4CRnVL3AdCWugmU91nISaTD7m9PoFrUryO/T26pc4aQQ38aekyt3S5aGbTsZGnaSSkj4Q6yCu9sNG0T8NJyDonHWqsSYlVK8MixZBGw+HrT92KHkE5l5P0HgbtGGPfUZ08B699I/nN6q/L1ButfM2rnyJaclWQN5xlElpOR1Bvl7W01ZP8uqzJC64dUTDDKNFtxICojbbvJZCT7gBBXpIwP1bjBp4vI49g59sXOKBKREU4NqWvsNK06GagJlTYac4ucYqPQF1UzeovuFqBDn0BKxxCzLKvToqsjnY1Ai34eaf2V6ecRNQEg6b7v/BZY8cfUjoGupnNLna9dO6TiGaGZNAXDSEl5iqGHkMfekhGa1psMGSkcpoeKNGDdf1PetVEOXk6qUV49V/DLtj8LG1sOcr5eHfrT0Em7rTsanxDs3wTcfxDwN+JZUvT3efgCbk5eqZevBv59OfDipSbyxWcbJiJlMWTEopRA0c+Rnq2YMQPrhreIAgMAS+8EXv4Z8J8rgKfPTO5zVr8A3DEEePX69IVSk8Hneur/cdcAP/sC+M4fgB+/TJ5Tk1PJMomsJiMAUq4BsDeeMkLNb2XjnT8gpMfqDiTPCF8siy9054aMaBqRoHd9ZvQqOfT8+PtLFKbhyIimAevt1BFmBoxT6MwJww4nj+kiIw16ifm8KtI2AIgtkEf9IiWjgGAh+bt4BPB/64DrNgAnLSDPvbnAKKWfDOgE5iYVlkcqqb0sRFNrfp76RqxemWTRmkKYBjCKr619OaXd8l4Jb5K9afYnJCN6bSJ6XdjBoT8NnaQVVYvfiI4S2Z3k/DNi5UYZWf08edz4pmkbn8cgTolCNbFhGgdyoavL1oqrSaX27t9ExoD9m2LVxBV/BKCR+0xTgJVPuv9cHh89BkS7gY/+BDw/r29VEk0Dtr5H/p70fXIvHDLP8Ir0p2JjgSAj9I8kpZE9nGckRhlhZCRODYoDURlhg7+lPkUiMrL5XeDOYcDtVcBjM0mIq2ISMGa2/fYUCeqM8GEaANjSYGlLrkSAvV+Sv0ccE39fdhh2GHlMFxmh/W7464b1fNHDN7xfhEcgj6hIx10DjJpFBs8vnk/+GOgEFk+RskNvlBFqXqWo0U2ke1en1kYAILU46L2VTL0UAJigk5Ety5LzOeng617wyoibME0DF6bpDNusWpkyEoeMOBQ+4yftuL4RS2ZWSp4Rj9/sGeF6zCQiZVZlI0YZodDJCO3SmxcgIQjXnpH3HwT+cAjw1++Qx3/9xCAkkW49ow/AOc8BY042v9ft4rW93vAPAqS44jt3uHtvOtDRQPx6kIyxBDDCNSJMM3BAB4rkwzRxlBE6cZTHUUYORM9IC6eM8IhHRlQFWPwL0hOEYszJwPmvJO6LkiCDY3sjKZ5UkU9CADFhmpbtRKb0BpOT8imoMrJzZXqqGe7XlQza/wYAyq3KiJ7WWz3N/jMkCZj2Q/L3Vy8mf1w0AyMvVWUkCTJirTFCkV9p1M9ItZYLTU/2BoHckuTeWzaGhEHUqLkAnUvwJcz5bBp3nhGXYZpyN2TEXhkBgDYn30ik28hw0mH2jOhG1ER1RoqGm76vl2uRnnSYhldGFO64KRnRyUcoQAiPqzDN/k3A2781PkfykFT9L/9JnqtbQdSM/GqSYfWjF4CLuAwrt4rC+sVgZfu/p7d2+N89xn4yDUr4Cy2hUOrxEsrIwEFawjT8oKGqhjweN0xzACsj1ok9HhlZ/QJQvxYIFgHXfg3ctJ/c+G4mkDgTYERRsauFkJGJ1STk0d5jNRrTlXmtOazkFmXjySAWbjMmv96AXjelnDJCFZBdK8lqn/oonErkA8D4U8gkvH+jUQXYLXqrjCRTd8WaScNj9CzyuOmd5I6Dgg8ZptKde9wp5JEWw0sCvDLilY3eNG5M8nyTuE7r9drdYlTHrZjg/CEOzfL48IWjiZUnf7oPiSkjHil+b5oolz5fWGNKb/YkQ0YsYZluXhnhx0s9lGmQkSSUkbd/S7wno08Efr4JmPEL8vzrvySEbLN+3Y2aZVw//OLSraKwUe/jNuHbwNSzgaPmk/+/cCHwj/NTUt6SAiX8xbXm51PJfsswBBkBHSjcv6e9J4oOjoCYVjCtO0mGgOy1H2QpDkTPCDUMxoRpuMJn1hO95t/k8agrgIIkusQCccnInpZuaBoxzo0oJelrMcqI08rcLbx+473Jdqu1w369EzAfpqmYSIhrpJMYe1u2kywtp6q0AKljQ0Nc619P7hh67RlJQ5gGIJMAQEIGcW7OrQ0d2N5ok7bdups85ieRnsyDKpdKcjU5APOkT5QR9+XgzWEay0RBw3h5lcRA7QQXykirU5iGr5ujT1Sus2n4fkI5xVx/HiO9GXCjjJD9Uv5iIid86Ek/n2FrmCaRMtLRYPiBZt9KyMZx15BwXvte4g358kXy+ugTjffxmShujZ+0uzc1m598G3D4xeR++epfwMKTgB6HTL90wInw0+8iDKwDB6koI1aJ0xSmoVJ7yaj42QhMGTmAyIhTGXFKTqy1RlTVKPKVyB9ihzgT4K5moooMKQyyFVOHNQZvLbiVCmhGTSpmUR6axpEjLkwjSUZxKz2VEaNPJJk28UAH0WTDHDSdNZm0XsAxtVfTNPuYf08bSSMGYldtADD8aDJgtu0yatdY0BVWMPOepTj+7ndiTYuMVCX5PSjoYK04KAhxQCdhjyxBkowJ3M2C3aSMRKxhRZdN/6iq1dNCTOE6TMpIl833at0NrFts/F9f/dPMmYS9aSi5BABNNdKbPSS9mY61iUgZDdMU5pDx06SM8ARLn0ipFybkd0lGPn+GtFkYcohBErx+4GhdtVh8PSH9+dWGmRkgKijbtwtFQdO4Xl36b+bxAt+6F7jkbXKPNW4Cvn418WelCvqbWBdc7H4VysiAAfNAJqGMWGXELn6SoxNyorLizDPSMHC6J360EHjjptRL1DuFaZxqjezfQEpWe3OMQSEZxCMjeohmSFEOWzHFKiNxwgRuUa6Tkd4W6OpoIIoapNheRtZKm9ZOrXag79n+Ian94BbtKZIRh2yam/7zJabf9mZsNVHqLwoWGplDPPy5RiiKNwBy4BcFMfU5UvW+UHhSXznyNUYAY4Xf6zAN67WTwJBLs6wA06rb7Bmx+V5fPEd+PzpxJquM8F4TTTGlNwMwir8l4AqUjBToZMRRGdF/G6tnJGE2DU11PeQ88/OHzDOPXcf/H6nKS5GsMtLVBPSQWi0x88GQ6UYzRloBOhNgoWgnZUSQkQEDyVQU3h2sBiuTMuJ2EKTKSLQruckiU2jdBbx6HbD8QWDRt5LPh4+GjVWL3WBp5xuhbvVhhyVX04IirjJCjn9IUQ5CfjJIdcR4RqgSkQ5lpHe9TNjqv2CI2WgGEJWDtg/w5Rp+hngoGQUU1uiN9la4Pw462KcpTPP3D+rQGVZw/QtfmLdnIb04nXlpVo21UaCOCDch7muzXK+pfg+KXgzW1kk4btEzy+fv74gTpmnRyUiibsaSZKziuc/nvRS2ZGTNf8gjLeinE0tD6ZHje0b4ZpiqGkvKGJGJTxZ69PG0IKgrI/z4GoeMuArTNG0lGXSSBzjou+bXAnnApUuB468j3o5Dfmx+nW+26CYcSe/pvEp7JZOqLhuXmBeA9etjQmwpo8lhwcVUHi39/bVSRNaTkWT7RgCxqWamQYMNgglWlv4QMRkCfecb+efFwO+nGvF0HjRGChCz5PokswjadgPQAE/AUH14MDLCDVh0kqH9QJJFHDKyM1GYRlXTFKbRTW00TLPmJeD304zcfregx2InwRcMAS5eApzxBHDJO0DI5vxawYd3Vr/g7hh62o2spjSn9sZ0im1xscqnrRQclBF+0uGLEAIwFgW9JiPJKyNRLjwBGIpATHjis6eAO2uYSTeiqGjm+inFpPYyZSQBGQFsZXizZ8QSpmmuI/c9JHOPJlU1aqbw2TR2ZIRfaGiK6X38Y6K5j5ImGqYxLf5MYRry3ZIysNIw1Ihj7E3yeRXASTcBp9xBQjc8JIkzfrq4LqwhGiuqDibjYrTLMMzu+gx4+Cjg/snAh3+yf5/i8poMdxiGX2solDfsD5BQTdaTEVqFNZlIibUIT7etMpKAjEiSUXjGrW9k56fAew+kpqTsXAms/geZ9N67L/b11f/Qj0u/JJLNIkiUvRBPGUmZjDjXGWGekaIcg4zwYZrOBjIIQHLXqdcJZXoJ+fY9JE37nxeT1ciibyXnN2DEqNb+9eqDgcnfj59FYcVhF5DHL5435Np4oNVffbnEBJsMJHvPCFWlAHOna1dkhF4X+75ipcl5mMmIgzKSbLiJgpGR5D0jfMdegCsfYB1jNrxOQnN6U80Wi4/DWRlxcb3aKCMRkzJi+V7U0DniWDOB0xSmZJg9IzYDJp9RpirGebCEaeJ5RhRVY+8ryCG/QbdjmIZ8N0pW6H0eUTSoTibZdbo/Y/ypjscQFzbn1RGJ7mlJIlWmASPrZtUzhBwoPcBrN8aaW/d9Dfy/4UZacjzQc+ULmUN3QGpm3AxDkBH9MRnXhitlxM0gGEqCjHz2d+Av3wDeWgC8/iuXR8phxUPG358uMg8cDRtIZU/JA3zzHvLc1iTJCGtK5jC5WMlI625ys0oyMMymmaAbuDGwcmTElNpLf6dQWWohIopgoVETY/nvjVLVgFHW3g2oYlScwJyYDIYeCow+iQxuH/858fb0OqQhxGTAnODm36I4ZKwu39/IXedOmVc88qtIhoOmGsXpOPBkZJ+VjLSlK0yTgjLCpbQCccI09BzopNVaPDGmmKIbAkdho4zwKcetXZbvRbuMjz05xqhpUkbiFT2jCxJ9v1aFSI5nftXB/6aGMsLft1xqLwvTmA2sABCx20dXkzGupUpGkrku3NzT1Gi+aQkhODS7ECC/nVUV/PflhMAu+13i/cdL00/WjNsHEGQklTCN1cBqp4y4GQTdpvfWfQC8dJVxA3y6KLlS2V3NxkVeXEvSFfnqnFTGH3MSMPE75O99X5E+KG6RqCkZJSN0hb5dD9FUTrI3MLpBnKJnuznPSJ5ubDPJ3vRGDSUZjrADjf1aO/gmE+pKJOmmirF65cg2m9CcFVTSTYmM2BNDvjiWSb1w4xkBSMNAwGgOyCGsGPfdPl51iXSRTBIgDcpI8gO1oQjQMA15PkYRoAReV1+sXjRTWLGn3chEcxOmYSt44zPjFj3bq5eZr5pi/JaATioMhcPrZGBVouZrTOUMrLpC5HWRVcQTD8Mzwr2BHyspGWHKiDHB2vpGNrxFJvjyiamn8ydTuTRe6JVi5PHkM5u2knG9fS+puTTp++R1q99r71fujzXewphXRkSYZmAgpTCNfsPk6hJ0N13BaBrHRt0oIy4Kn3XsJwVyNAWYfDow9RwAGvDK1e5jh1veJTdu2Tjg6CvJc1Su1DQjRDPlTCCv3PBBOBgH23uiWLfHIh/yYRo7UPVg/wYSZqrTV2LDj3b3HezgMAG2dkfQpodkhhQFkeu3CdOw3ymFideKCd82///Yn5HHXavcX1iZUEaA5FJUGRkpS2E/9mEaPjTQzp9/t6t8mmVlU7ytxylMQxcE3mCsPO0WvUrt1ZURGqZhXgnuWoiGjclCv4+7I3GUEUrenLKPrKCeAN4z4mRgDXca9TAqJ5mNmlZlxEndaN9r/u0tqb3kkBKXkqe/qUeW2H1rUkZoOjjgaGAFHMgIbXyYqioCGOfVDUllqdhxyGMg3zBq//da8jjlDMPvtc1CRhSLNyoe4ikjslBGBhwMe0PyykhxLpGgO+kg0tOq+xDgjozw6b120DTg35eRib50DDD398A3fkuY857VwMcL3R3wxrfI45jZwPhvkr+3f0Sk7A8eIQORN8d4jU6I/I3P4epnV2HOA8uwdjcXx2dhGgdlJL+KqCaaSkqaU09KvOJdieBARpo7yAQS9MnI9XvZIGWaDDuSII2JUDkJKNe9HMddA8y8kUxmnQ3mQlBOUKLGdk7x5VRBQ1BuBhwWpkmBjDik9tqSEVUxwoSJyEgVJSOfx7zU42Rg5VeEqVRfBbjzlkqYxqyMGF17uTGGGr4BVljNGv41KSMtSZhXAftsGicDa/3X5B7KLdXPGZ81YigcvGckRhnhQzQAoKkmRQXgPCPxyIg+tga8MgI+8j6mjKiKpU4R+W6UZAV8hnITsZarVyJEGQHcpcY7IRnFjIUKq+Nvd8xPjb8lGZhxg9Era8fHRmVb3ivopt9SPGWEV78EGRkYcNXeO9JNXNj6RUEHwaJcMmCxFQy9+AIFiYtSAYkLn+1cCWx4g2SonPkkYdGhMmD2LeT1d+8iJaLjQdOMm3DMbEIWhhwCQCNN6V6/kbx2/P+R1DYgoRS5dT+5KUxdcJkyEucmoa3h1/wH2PMFAAkYeUL8448HBzJC5fuAlwyq1DPSHTEyA4wwTRqUEUkCfvQicOHr5Lfx5Ri9Q2iX3Xho30smPdmbel0MJyQT4+6VZ8QhTMPdWO10NU6/r+RJ/H1pmGbf10RN4GDyjPCpvTRckGgSiAfWu6M3dUb0SdguPMFP3jRMEzF7TUxeNPqdnJRHK2w9Iw7KCO0EXDmJXMumFFZrB2LynRTrZG8l3VyYhhIEdh7iqIWUkAW8MoJe2fQculvM1xctehal502GX39PjDKyfyMpuujP18e/FCG5vC6SCRWOPwU47SGyWPv+QqLWlo4h16/SA2z5H9mOhtIAd+0y4pIRyf136SNkPRlhBtZ4ZOTxOcAzPyCV+2DcHJSM9ET1SY5WfXS72k7kGdH3h4O+A1RNNp6ffh4JpXQ1Acv/EH8fe78kVSy9OQbbPuHnpG5F2y4yWZ14E3DCdcZ7EvQt6NRXuE1cTYSEYRrAaA3/4aPkcfhRyaeQ8nCYAClZpANTLpfRwVabyYTT3KBwqDkraIhesIt22Y0HqhLkD0mtR048JEVG9DBNbirKiH2YhveMsHNPU8vzKhOX/y8aTpRANUJ8TBz4CaehPWxMtmxF2ovftjd1RhRaZ8Sc2mtSRlo4MkLDNPq4whTXsGIUSks2VTlBnRFTBVbqQ6iYpL/XvGq2y6aJVUb0a9inL8K4LJwYMuIiTBPwelinX6aMWJVazZza6/PIrLYL7ycCYBCuigm9u8fcekYoEfAE3IUKp/8IuOYrEqIBCFmg9YRoeIlf2Li5LhP1mRpgVVgFGaHZoU5hmo4G4yLQy/bSm6Mo18gU6I4oyTv443lGomGjs+PBPzC/5vECM28gf3/+bHwmtUav7jfmJLJiB4AJ3wSuXg2c/hfgpysJEeHlbIf4PwXty9NIayLw7drjye6UjFD0Ri4FnJURNqDJ7JEOiMw30pHgRu0taFddN43q3BC5VJFMimo6DKyWQZLPamjjlRHAHVmQJCOUt3mp6SXr6pelDrNFQS9Upl6k9rJJWJ8YbU3yrZySoO+DjislegaSomoGgUhW7bFTRrjz1RE2vCCsYB9NG+fraWhOnhGHMA01qqsKR8qsCpELMuKTEfRZlBErGbFk0/hNyohlH/u+1r9jnG7HbuBWMeMJsdtQoXU7Oj6uW0yMyNTnBzgSCJMvKVFm5wCrwirISKISxXzjKF2doDcHTT0DdEm1I0npn9UZsfFm7PiIlEoPlceWAweAcXMA2UdiybSSqB1oqWGaJUORX0VYuJ1hMkEuPc1KaezQB3/Wrj0nfgOvoYcaN4Ykxxo/k4VLZUSSJK7WiP6d2nsx8boB9QO5qQnj1NMnHUimVTgd7N0UVbPCJrNJUTUTT2ZEMFmyQDOCNrxpetpa3KqpU1fq0qKMpO4ZMeqMxFEETMqI2TNSzC1yjBBwsspIbBdl6/liYTOqVPELCW4MMDwjcbJprNlRmhJrYKVZRXHJiBGmoWHWHidlxFL0zO+V4WfKiGVAp8pIebrISILKbYwI9IIQ1x5PaoS07Sal+je/a7xmc13+94vdOPjWN7Bkrb7vRMqICNMMLBh1RhxuEFoiGWDOejrZBb0e5DApkTNX2VUgtQOrM1Ifq27s+ow8Dj/KXsr2h4wKlVvejX0dAPatJeY02UfIi1vEke/CUZUNtk26UdR1u3Z/CLjyY1JJ9Lx/9a4MO+BY9IyumOnABIArCW9VRtIUprEiGQk0o8pIEpNqr5SR2N/C2iOEGViTJQuUjNR9QNLUdViVEVY0LK3KiPN56+iJ4k/vbsK2/WbCadQZMSsC5jANp4woZmUkFPAwIs26g6dBGbGeL2ZibePChDbvt68zYpmMrT25VJXzjMimx3hlFPiFRIwyYvXW2XhGqBraY8lMQn2alBG3E3gy6p8TfEHg0PPJ3/++zDyW2Cwu5j+9Eu09UdJ6QVUTh6Jl+8Vcf0GQkXiN8sKdZpldNafgBXwy8yN0hjkyEk8d4EHJiNITW2mPkpEh053fTxUTi3zNsPyP5HHcHCCnyN0xAXGVEb5WRyP1jNBVm5vJNFhIKonaqT3JwmWYBoC5CqsSNQa2TIVpkll1MGXEIROpN3DrGVHV3hlYbUJ71tWzoUolSRaKa0lauqaYyuzHTK5dKZIdO9DvEyd9/oG31uPOxV/jWw+aS/9b64xIdlkkpjCNdVzxsHGFNeFMg2fEmmHS2h0hRks6bvGfzb2fkkpX2TSUjHBFzxIWf+NgZNN4WGovTdNnykiwSD82nYxw+8kPevXvxv1ukW5DPe51mMalZ8RtJe5EmHWjeVyY9D3yGEfpDHhloLvZCDE63c+9KOyXCWQ9GXEs1QwQQsD/UDbKSFBXRroiKZARf4hk3gCxRakoGaHeAzvQCX3TUnNju44GYPENwKq/k/8fd42746GIs6rnHf6GLE5vvAxN7E5wKHrGUv28hnHV6E+j6IOaRt7vVsVKFsmER/rEM5JgwOluNn7vVM6JTWpvxEIWWKGtVMgC7R/U3cyeskrxbKWfDmXERWrvR1vJ/d5u6QYd45Wwy9gzhWlix5WQnwsrqgq30u6FMqKfr3z9XmjtipprsvDjFkcu7XrTmAiFEjE+h9bU4MrBe1i4CrHvBYD9m1gxRD5MQ70zrF8PJSN0grfUGfF5ZObja+7kzPUN6wlJzinuPTlw6xlJR5gGIBmU5z4PnHA9cNbfjDpRlrGZ/75Di3OM/QeLYnvsUCRT2r4PkPVkJG6YhpZIpqCxXcreeWWkJ5o8GQGMOC2tIwAQKZoy+XjKyNDDSCptT4vhuO5oIH1RPnyE/H/0iaQrbjKIk03DKyOsw2i6brxk4egZIcftNykjXJiGhmhyS81pjGk9tmTCNJlURhKv8AEYqkigMLZrsBvY/BbWktztPVGSHZJK3xgbUmWV4lu7IsT4TSetVEvBO+zPiiLOM8bDWg7ew+wb+hgT7iR+MAp9XKHKSNAnI4eGFcNRPYyrknPsVrWyTDSKaqToluaRyamtO2IO//AhVm4MSFhnpG0PAI2EBOlvyoV3jHCVDZGJdAMLZwELTwRUhcumkVm2YnNnmLyHVoSmix6rgdUro5i9hzMe71tLHssnpl53hiJZMtIbdY6iajJw4q9IViW9Ny1j81e7jJpPqgZ3loFkqsn2AQQZiaeM0L4AIfPF382xd2pibe2OpEhG9JUEH0PerRd4KhoRP59cloFp55C/P3uKPL78MxIfzR8CnHo38P0/uz8W9rnO2TQdXH+Xpo6weXJJx42XDBKEaUxkxM8VPutNOMIt3BrdVCX5GhJJHYdLZYT5RVJUimxSe6OWsICq6b6IVMirzSTQY1VGuiIG0ZR9QI6LWgyO+3NBRnINMsJXT7U2ymNhGjrI8H2huH10cyGKgiCvXujXR6jCPXm2VArl/TuleWRCa+uOcmnlFsWFU1aiXNiJmXH535ZX9rgMjYg1tdeuLH7LdlI/pKsRiHRxIVYPM/Kqmv7bxigjZNsI5xGjykgTr4zU62SktyEawLbMvi3SFaZx3L/5uvxyp1FvqqXL5VzUi1o6mYAgI/F60+xaSR5H6CXLqZyqDxpBn4cNSE2dqZIRXRlp5pQR6lOhpbDjYapORjYtAf59BfD1KwAk4If/AI78SYqZEc7yHV8VMqpqJJ7blgZZPBUk4RmhVVg7w1FjUMtUiAZwb2DtqNcLgMmZMdO6rSTKzkkKNUYAWzWNTmJBn8zus7buntTIq00aoq2BtY1TXXpVTyLxQO3jDNK7W4wwqbVBXEyYhveLAJyB1VBG6KTa0hVO3i8CxChzfEirVA9/tHZz4ZUCCxmx8Yz4PDK7j0yTPd+XiiOlMRVY7TwjreasIj611+eRWUipqTPsGKahpNTHqSlNdspIOsiIW3Kf7jpG1v1bxpU1XDXsZrdzkU3GVX9CkBFWZ8SCjv3GoFmtF7BiDa0MZcSIUfaSjPDKCC1CVDkl8ftLRxuekFW6OjLlDHORtGQRzzPSY36usT2cOIUsU3CZ2gsAefxKk8q9bqoYpnxsLuOx/Ko3UQGwVOB28Ozq5Tmx8e9EuKySPF2Z6mppMI4lmSaFNuSAkhGaKdXaHTX8Ir1V6VxkIfG9jnY2dbG/rQ3iWDYNnYSpX4RNBhbPCLfIae6MpEZGLJ4lnrgZYZqoc5YOr4xwWTG1ZSEAwJYGLoOIbwXBZWhYDaz2ZIRTidSoEWLVCQzt+mwmI+Vse03TOLIkMTWlpYsjS2klIy4WGapqKI3pHhMdvGh8EbuWrjA0NhcVxfksYWAdUJDgEKah0l7RCMO9bTGaBbweFjdu6egySrMnQ0ao+9xERvR26ZWT3H3GSQtIVdXCGvJv1i/d798OLpURAGjsDHMTwMBQRnpsUntLQ0Sa3t8RHmDKCK3tkaGQkVsjLSNoKZ4TmzRB3shJDcQ9TbuN/TgZ62w/P3bgpBNseT75bYkyQqu79vJadJPay5m5dzUbZCRhgzhWk0NfiDDFlVvk5NBJOJKax8aijPATNu2G28qfL2uI0EYZ8XsljNTJyL62HsOQbKeMqAoiltRe+xRnizLC+fEAMA9IU0fEIMycMsLXsiFhGm57gHQ7pk0oe1tjBHA3gffWDB4PTsUFubBZRNEQadfPlZswjfCMDAzQQjyalY0wNn1QjNTdw8mplLn3tDUZ700mjZYpI3XkUYkaOfFuyYgkASf+GrjmS/Iv1fbYFC6zaQCguZVrbZ6pmh1OSFRnhFNGSvTV4P72nr4hI26Vkd50ynUDt5VE6TlJhkjzsMumYT1aJKZMRVu4UvDJwE4Z0T+/TPdAtPJhml4rI1QOVx1lbF4Z2cGREWs2jWwNBdMwDW2KSMM0UTqueNgk3NKVovLooIz4PTIK9AUU8YxQZcRC3kwKh0EqCnN8KNPvpa0Nnfr34ciIyWtiLXqmm1/t/CYAoERMCz2AU0b4xR4l7lzGDkANrBbPSMM6/T0VqfuheCRolQHAuJcCBamZwePBgQxZQ5aRdhf3s6jAOrDADKzWF1gvg4mkjwvAVUo0bhhqYI3QFa4/3yAvbkDJSOsuclHs30j2488jqkx/IM4N12FJY+xs1GVWjz/1iSxVODbKi03tpXHyxoGmjNC+RBknI4nCNNR939swTWydEV4ZUdpT/L5xPCNUGWntjnDkrpfyuKnFuv254+8FkzISY9yknWT1c0PVAEpGLI3yiGeEW+GnUqDPSRnxyqwWR1tPxNlM7OAZAYBRZXkAgM0N7ebvU2hWRqyN8qhS2cZ3DI4hI4Y6BBjVaDtauOqr9BpVoyYvjM8jm8NbALeonIC0wM0ETg3ymRhfHMYVa5p71I0yIiqwDiw4Fj3jlRF6AVrDND6DiasdKfhFAD2lzkMuiPa9RoimYmL6m6a5RZxsGqsyEmnmVrq9TZtLFg51RuigzisjlIz0WZjGrTmMDVyZIiNuDax08EojGeGLUelkREt1oI4TpqHKSEtXJH1KE7+gcCIjXMjS5BmxGDeHl5LmcVv3d5LmktQnwZQRa5aeB4XUi9YVTq11gWy+/vjQpRGm4czc1vPFTXoRi/djVDkJ1Wyq130jfDsD2ywcciyHjCBj42tf7TH2w3tGlLApmwYwyEhPG7fY8+awffCKgFeWYpURfhxPB9wsMtgCIwOhVwcyZK12rNJKxdRiYPtZogLrgAKdPk1xTE2zKCPmAZ253r2G0UzqdmEYsoPsMQoF7Vtj1DahrdP7A3ErsJqfUzKVwuYGTmEaJbbOSKkpTNMHBlbXnpFMKyMuw0XMwNrL1F6bLrFeLgsj5f3Y1RmxkJG4k2uyoPsDHENcfJr73jYjm8Y6eQ8rzsWEqnwoqoal6/cZHqtC3S/G6owYyoipXkYqTR1jlBFDpaLKSEdXN+dzs9wLfJ0RC6mgZGRzfTv5venx0YUVAFIOXj8PujLy3emkjs4HmxuxkypJvFdOjZgWeoDhGYlSMpJTbLoWmJ/FI0OSJFMn9e6IwtUYSbcyYiao+1q7cdof38NTH27LbOiVnl9opoWOlYzI3S4Wx8LAOrBgW2ekc79+k0pA6RhjdWmjjNCLX+5pJtukEqqoPZ48bngTWPsy+Zu2j+4PxPWMkAuXDrRSplLY3CCJ1F5qYG3tjkLrU89IIkVigIRp2DlJpzJiyPQ0TOPpSjGF2IWBtSuiGMpLb1elJjJiT+T4ME0D7RiM2DojADB7Irk/3v5qlxESo6ZRa5aez8MMrM2dEcMzklL2kTlM4/fKyNeVEa27GSxAbR23ODITtpCrkXqYZuv+jtiCbGyBoHBl8cl5GFqUg6NGketr8erdpIkkV1GX94xYs2kUtoAoNn03K/HLC3hZWKipM8z1pEmTMuKwUPvL+1vw+Y4W/OpfXxqm9EyGaQDbvkN0PvK4mY9EBdYBhLoPcXx0OcrRbK7ASqufFgwlzYqYMmLjetdlQX84hUwairHfII8fPkrc7YGC9PRuSRXxsmn01eDQIiKVssklU5NpPCRBRgpzfLqbX+tbz4hrA2umsmnMIUZHpCtMA40xe75hHF2Ne7tTVUZizyetL0FVLwDQ6PnsbdhL9oDppjZELqqobOIECMmliqnVuAkAJ00kRGLtxk3kCcljEHgapqHKCKe4dne1AWHdm5GXxDVirTNiMrBafotgUWxaOXe+o5ZKqkOKggCAPS09RtoxLcjGv89CFADgiFpyfW1p6Igt/qZEWJdi2maDdTDmyybYKSNch25Wo6WxwfCklI93OFFJwqH+jATjO6qZVEYcvEyU+FGV0OdmPhIVWAcOlr9+LQ6THsQE/2qzMqL3SWBdZT1mZaTbVCWQvJantpFtUiEjo2Zy8htIY7t0u7CTAYslOisjw4pJHNzb00t5vzdIos6IrMeTc9EDSdFXsX2hjLgN02TMM8INOE7dUlXVWKGmnNrLr9jIfviGcbSiqC+colE2jjKS4/MgP+CFF1HI9HukYyKIQ+Q6wrG/a0M7ua7o5C3LCpbtWIY3tr6BISVksgrQ+yVUZqQ2q+aiZ7zimhfVz5cnYPSxcnXslmwaZmCVmDLio6tnu99Cv7dUxdy1FwAqCwgZ2d/Rg2gLreCqG2C5656m9rYr+7C+aT15byF5797WHrN5FQCUMDsHtM1GcUhXnrvtyUg4aiZKgKEORPboofaCocmHz53g4Kfjq/F2Numm4Ezc0/w8YRMSLc8LQIYKf1QnsIOoAmsGqiwNHjzk68YXFWWYHK63kBFdGaFkhAvTRBWjcVTQJyPH54HfI6NQ0s1cqVz0wQJgzEnAhjfIKuXYn6XyddKHOCWP6SA8rJgoI8FIM3lhAJGRsE2dEYCYWIMdOmn0BgFfbuaOzW05+HR5HJzgsYQb7AqrdTcb5zDl1F7OvKwpAGQjxVWWUaaHUgLhZrJNWgyshjeoIMeHYI9O7CQ5PZldspcQBZvBmoZo/B4ZZXl+7GrpRn1bD4YV57LV+tftb+HhJY8CAL4/5vsI+o5CmULTUyu4ccWcpRf0eli4oVzTt0/WIG5JtebviRJdOchX9c+2+y3061fhvrtPJ/cluX74PBIiiob2hh0oAoyiaXyDPf33/8u2S/CXbcBbZ7yFynxKRrrNNUYAQI2ShqOIVUZMK31uEg1bMn3Ie/Tzmm6/COAY9uzkQnbdLfuQB2RIGeHvZ14ZMUKW+eiExMJvRc6fdSBUYH3ooYdQW1uLYDCII488Eh999FHc7ZubmzF//nxUV1cjEAhg3LhxePXVV1M64HRC1iddvxS2D9PQeh1cmIaXZgNeDzNNFUh6zn2wMLWD+e6jwA9fAK5d07/mVSBBBVZyA9SUkIk8JxpnQMs0EqX2+ixkJM+PYuhkJLc0s9k/bgyskS5Dgs+0ZwRwXgHREI0/P7lCZDwk7lzrvwcL03gl5tnJjTaTbdJBRjiJvjDHh1JJL4mdU+K+h0uS+6SgCmFuwGMUXWvYDbTvYySsQ2lg2+/r2oeyvADKQMlImTGu6LVM+HLwdFwpkygZSTKMZyHDfHpujp8oScWSfu3Z/Rb62KhEOTKiK6ayLKFCJxVdjTqhoHVdTKm95vtydcNqVBVyZCQmTBNmYRraKJCGHQIR+ttyyoimImLTFJN2+5WadIW7dEzs90sVDiHsdr4ydbpChXYwKZDG+aVksyI/gCL6u/rz4peZGOwG1ueeew7XXnstFixYgJUrV2Lq1KmYM2cO9u3bZ7t9OBzGySefjK1bt+KFF17AunXrsHDhQgwdmoEOpUlClikZiZjbe9OLmLYtZ3Jt1EJGyOkryvUhHzoZSUZK5REqBcaeDPhDqb0/nYhbgdWsjBSq3ODa13DIpjFMcOYJqSTkR4lEyUgGM2kAd+YwGqKRfalfN4nghoywDJdeqAlS7CDJGzlJoSwN+ao+qSRdZ8QmW4db7ZflB1AipfjZTqAqks1vSCefkN+L8vwAvIhi5ktHA/eMhUbDgJLxPlVTUZYXQCkjFxWW9OEIV32UfNfCHB/KJU5JSQZOnhF9zCovCKCEEnM7nxBVRrhuz7z3o6KAkIQoTe23KiPQWAM7ivqueva+hvYeqHwmDUA8I5YwTWnID48soVDiwg7chNwTJiEu3h9GyaGvjRaXS2O9JocJnDcz+/hQXLrBk37uuqRkc0hRDorgIkQDDLgKrEmHae677z5ccskluOCCCwAAjz76KP773//i8ccfxw033BCz/eOPP47GxkYsX74cPh+5+Wpra3t31GmCRJURRMwVWOMoI3T14vfIrMxzUa4f+Y29VEYGElxk01QX5kCSgOK+mtztkIRnBNAHtngDcDqRbD2CTKk0LlJUe10KHrAdJHkDY1l+AAXohBf6+Uj2/McpehbwyijPCyACSkbSZAaOU72WTj6hgAdleQFUoJm95o2QkK2GWDJSJnHHKBtkRImGmdITZIscP8oae6uMWLJp9HBGRX4ARU1x7l19bIxGje9Ay7kDYOEWtFsquHLXgapGARj3Zn1nPcpCAXhkCYqqIdy0HUF+n5yBNUcnZLIsoTwvgOIunowY13Q4TEJclMABQHke+dTcTl21SWfxSAc/XTsjIxpyoxlcoEkS+W00hREi0p+HzF9DinIMy0C8GiPA4K7AGg6H8emnn2L27NnGB8gyZs+ejRUrVti+56WXXsLRRx+N+fPno7KyEpMnT8Ydd9wBRXE+AT09PWhtbTX9ywSoMuKTIkaQprvFiOMzA6tRgbXHJlOjJNePfKmXyshAgotsmvygF0U5PmN11a9hGrMx0y6bBiCt04t64+1J6tiSUEbSUabaCS5SVJky0huCZhOmMcrByyjLCzDiqvnzSJZaMohTZ8TvlVFRwCkj6boW48jYBhkhyggL0wJQ6HmWjIlY1VSU5/u5sItZGQn3GKnBhl/CZygpyRKsRMpIfjD+vauPjapqpPJLHGGu1BUOXydN7a8yvQ+gqopxDvZ379dDPOS9GjW/MuU5HOMZofsqkhzISEQnIzbKSGGPTpRo/690wGECp2SkAJ3wQb9eMjUmWrJg+JL4Q4tyUACXC2PmGRmEYZqGhgYoioLKSnNNicrKSuzZs8f2PZs3b8YLL7wARVHw6quv4qabbsK9996L3/72t477ufPOO1FYWMj+1dTUJHOYrkE9Iz5eGWnWe8TklgKBfH1DPkxjON4piGlIL+ITPADISJxsGj6tuTpXQ46kVzocSJ4RmzgyQFaDhXC5augtOLnaMYuFVknMZBl9upIC4oRpUqwebNqPHRkxZ9NUeMi5V4Ip7CdONo3fK6MiE2GaONVrafVVGqZhkyUATQ9tqDDep2iKxTNSbppUe3qMomkBjjDE9XXEPXZrNo0566QiP8CpmnaeEbKdot9LPosZvELPqMnp0f0R1mwaAKoSBSTj2m/oIuSbZuN42nQyUqiP76qhjNAwDUDOQyHsyUjEhoxU5AeQg24UqM3kiXSSEYdFBiWnNJyk+XIBX0769svDkgXDFzwbUhREnkTmoqg/z93nZEsFVlVVUVFRgcceewyHHnoozj77bPzqV7/Co48+6vieG2+8ES0tLezf9u3bM3JsEucZYfMF67MwzNjQFKYxlysGyMV/YCojsRcpbxockUO+syL7iVmqr5HAwGolI5WFwd5lPaVybICtIrG/vQcvf6S7/TMd2ktkVKNVOHtzHDbGOr7OiCRJqA2S6yXsT4WMmAdgVdVYCm3A60FFfhBlaQ/T6PtU7JQR3TMS8JAwAlUZAKh6KjAfptE0zRKmqSBEUSc8PWGijHhliRUJqywImA3XycCSTWOtx0HICCU6cTwj+vn2yuYwYmVBEDJU5NPUY+oZ4a97RTGpQ/Wd9ex75aAb/oh+3ell8ZVID7t3c2KUEXrfFpsIT1j3jPBKSnl+AEMlXXUMFKb3Xne4l6gyQhc7ij+D97SFEPEl8Yty/Sj1EGLbLSciIwPLwJqUZ6SsrAwejwd79+41Pb93715UVdm37K6urobP54OHMxNOnDgRe/bsQTgcht8f694PBAIIBDJfZ0PWfwyijOhPtujEp5BTY7jUXqvbGwAq9XQqAAeIMuLsd+Bjz0P9hIF3+4oQ6uu+NICzZyRiHCOP6sIg9ruNp/YWMZUSzbfa7a+uRfWW7Zjr64tj8QJKTxxlpJk89mbQjqeM6BPZ0EAXEAU6vYVIOqnaIo/zjcFomEaOt9JPBW7CNH6vbp41yEhXdw8AP2TZuH+YMmLNjvH4ADWCiO59MIcnOGUkaY+NeUFBJyxqQq1IRHT0CU91UEYqCwIoRQtk0OqrZeb9Anoo3vidqDJSVRBEtcRlcOn7j0YMbw4/vlbk+Q1FM6dYV25JAUM7ZaQ8P4BhEiE+WvFwpHVkchgbqVJGSVOPryBzdTMc/ECyRHw9FYEeIAJ0SjmIS0cGcwVWv9+PQw89FEuWLGHPqaqKJUuW4Oijj7Z9z7HHHouNGzdC5VbZ69evR3V1tS0R6UtQA6tPihi9aajD204Z0RR060zcxNxDGvzUOX8gGFgdLlJF1VjWkc8jY4if3Hid3qI+PDgOCZSRoCW1t6ogyAa1SCZXLoClOFHsZLaqrhkFjBj1kTJis8IHkB5lxFRnRFdGaGhAnyiq/ISwt8spEHZLqInPavN7SJiGxsq1dJE7l56RyvygSRkhZASQLZ6RspAPJVb1Rl/ohMNkNctfs6Y0zWQN4hbPSNRSj6MiP2gQqDjZNKoSNb2PorIgiEpJV0XyKo0Jkg/TqFFI3DnY370fqqaioiCIKkpGCoYwT15EPweSZCYXw3IjkGm4h/62+m9jp4yU5vkxTFdGIvlpDvE7VFamStmwAPkOXZ4MLkothMhaa6XMSwhaq5aA8g/2CqzXXnstFi5ciCeffBJr167F5Zdfjo6ODpZdM2/ePNx4441s+8svvxyNjY342c9+hvXr1+O///0v7rjjDsyfPz993yJFSEwZiRoGVjsyYortkoGGJyNVAfKcArl/whXphgP752OTPq/MPACtUj+pQQmLnplTewtzfCiSyTG3aBlOoTaVbY692f1emU2eSiDTZCSBZ4RWLe3tJM4mQEuYRldGynT5uBUpnHsLMeClaZ9H0k2k5Lft8qTpt2WpvbHZNLRhZG7Ag6rCoI0yAsiyxcAajMBLJ2fqz9H3Ee6hK3yzMmKYTFNVRuw9I+V5PsPoGCebhqb28qXtAZK1USE1k234tGPuutcsyoiqqWjsbkRNSS6GSHqSQOFQdg6iusqR4/OYzLLV+vgahs8wPuvXQyQam9ob8Howxkc+vyNnSOx36w0c/Fft3eT/o/LJ8bRJGZwHLCohVSCpElziJfdZi5rAJM46Ow/CMA0AnH322aivr8fNN9+MPXv2YNq0aXjttdeYqbWurg4y1yCqpqYGr7/+Oq655hocfPDBGDp0KH72s5/hF7/4Rfq+RYpgYRqTZ8ROGTEUnG7daBbkDVY6E23XggipWsyNO+jgoIyYpHGPjEovGfz3a3kY3WcHxyERGbF4RiRJQoncBWhAfTSIjFZGMdXdiCUjiqqxybNJzc3ssXicjZgA0qOMAOT30JSYQZJ6IIo9ZPJrUlOofGslI5wHQpIk5Pq9KNKNe41KTvJhoLj7tDFycy0h/F4ZQ/0dbN7V6Hm2KiP6JNGj+aDBT9Ja9bGlR1cFeONmRa6GXEkvMR8oTm6wdlBG6NhU6e9hakO3Jw8x05ZslIMHYkOeeQEvRgXaAA3o8JeDLUckCTSEomhmzwgA7OnYgxElw1CFWGUkGold6AFAhZ8834qQcZ/ov02UkRHze4b5WoEI0OIpRVrt4Q4p5vR6HJHbA7QCzZlc7FgIkXW8K5TpfZCAjMTxBvYHUgprXXnllbjyyittX1u6dGnMc0cffTQ++OCDVHaVUci8MhITpuHkPS4Fr0eP7eZyN0yR/uO3IRdd7WFWZXDQQraf5COW1WiZvhqsV/pJDbIpeqZwxkYrGQFADKwasC+Sg4mZPDZTSq35PGqahl3NXSxktKcnkFkyksiolg7PCBBDDq0TIDUP71dSyDKwrvQpGeAmSZpe2xDJwTCkAXHOG8uq06+xSm8HoCeWeaHoNTnMnpF8vX9VK3LR1dqD4aW5hoFVV1N4MlKqn6+oJmN/NIik+mInqDNSoF97XZofDV1AjfUnoZ4R1V4ZAYAxOW1AJ9DsKYVJG5U9gBqNUUYAoCPSgQmlIaaMREJD4NP7qDBlxG8mFqVeMr42q7koUlRCbvXvRz0j1pBsuUzOdSMKUBtz5L2AjcrIFzyr9hFS2aBkstWENbXXHKahmZ0NkUTKyMAysGY8m2Ygg4ZpvDRMo0RJ11yANFei4PPaaZiGu2HkMIkDt2m52NdmpOgNWiRQRmjNATr47wn3E/myqTMStqmQyyNfIwPfrp4MG6Q5ddCqjLR0RdARVtj5294Zp2RzWo4lgVEtncoIEFNnhJYRz9cM8pU0LANnjzV9W9OQp0+wexMNwq736awoWWvZlHKpvV4oKAh6EdWM96maCqmHjBOtWi52teilAGiYRp9Uc/3GWOPRu+o2IQ9724w6JK5g/S1YszvyvKSH5loQwu4WmzGLeUYU0/t41PjJhL9PK7LsmxKZWGVE0RQU5vowzEv8Jg1yGfttlai9MkLDSa3INc5DAmWEhrf2pnuhZBPCppk0Aa/M1L+9kQyl9QJceCW2CSIAhPT7bF9PgnFlgFVgzWoyIuuKh1eKkvmsfQ/5YWSf0d4b0FPwqGGK3Ay8YQp0kEEu9rUmOWgMRDh5RiwdMtngH/abSECfwSZMwx9HjDKiRBDQyMBb19UHXZEdSN2OJjIR0UF2S3uG+1XGqSQKIH2eEct1wyZADx0kyYS9PZVzbyEj9Fpkv3G4Ax59Fb6jM03nk6X2xp43a/p4gWYUZvRAQWGOD1HVTEaoAtWCEPZQAqCHKMJ6+DcU4MYVvTJus5ZPutymcuxUGYmaJyx2LFoIO5s7re82CAU1sNoQ+yrdwLo9aiGx+r41JRpDRlT9Xq3xkP3vVEvYOVB1YmFVRjyMxIWwu1kncZSMRHQiYFFGCvQGgzvCaQ6X2NzTNJMmL+Bl3dt392RwgSY5/Lb6uBxUye+5szsRGRnEFVgPNPBhGlXTgGY9rbeg2ryyBTjXuw1776bKSA72JbuCGYhIqIyQc0PbVLf2lyJkQ0boilmSYmsjsHAEgLoO84CXETiQOkpGaNhifWuGjyWeHBsNA5E0tTKwKFXWDI5glAzUdZ0+1vnaNWI8IxZlRFd3IpoH21qT/OyE+7Qr/mcOe4RoN14APsmBjOjH2KqFDGXEOq5wygitBN2EPNJYLhlYPSOq0UEZACOgLQhhV3McZUT/7j7rvQSgWCVkaVN3vu2+NVWFBHsyUqGRbJfN4UIWBlccPCPsvCEXOxkZIdtEo3qYxkKWQnpJ9k3taSYFNtcENa/mBb3IVchcsL07ADXZazzpY7D4p+i4rJBxOeEYN5grsB5okPSBwCPpYZqmreQFvQiPCdRkFY6N7VJlpA25yQ8aAxEJsmno5CL1kMmlTcs1Vnp9CVsyYsjnkrX2iT4At2q52NnioBKk9fjsSR0ZUDUWptmQcTISx8Daw7Va6DUZMXt4WGqvrox49HBmk5qL+mRJe4xnxKzS8RPWDrvJNRXEIXGmztDhTniVLvaaByoKLGRE0RR2jC0IYTc9Rj1MQ+uMhPhxRS/T36TlJz+uxGTTmOuMmJWRLuu72b1FwzTW1F4AyAsTQrGu3eKP0AmPpporsAJ6qfxwB0K6grC2s4CRES1q7xkxSFwsGVGYMsK9J9wBr0rO19etaQ6B2nhG2rmaM/4wOdb9agj17RlamFoVSItK5wmTc7u9w8cWZ/E/Z2AYWLOajNAwjSSppCiUtVsvD8ugYbphmDKSi90tNjf2YIPDJGqY4PQBjX5v5NjHnTMNuzCNZZVgQqIBON1wIHW7m7sQQjcLK2xq87IGjBk9DjsyQtWiQIE5HTkVWOVjq0+BO/+7kr1PrGEa6+/MT1hNafptucrLVpg6Q9PePjq8epgmwr2PKCPN7Bh3W5SRiJ15s5OEQZq0PKamuYbF5GiYic3KSCtC9udL4ggFbAysShS+bkJGVrfmss83vVdRwJt4Af08tJIy8G1aDtY1gZ0DWrnWWRkJYZclTKMosam9tOdTj+bD+mbN3AS1t7CpzUFrjOQFvJAo4dRC2NFkE/5KyzHEIebRHkh61+g2JFgkCgPrwAFVRjRI8ES6gEadjJTYkBE2aDh7RtqQ0zeTXKZhMUhRMGWE3vg95MYbSMqIkeZmM7Fy0nR9W09mCQDgmDrXEVaM4muaB93wG4NsJhAvNpwu8yrgmE3j80hApIsQflgmFbewTAKsoii7Fqlvi0wCaZmA4pA4U2foTnsy4himQa5B3nXFlYYoQjZhmmbkY3tjkhObZL6HrbUoeGJu+1tQ34fqoIx01EPSVCiahH1qvnnco2Eam9ReRVOAVtJyY7dWgg372tk5cKWMNFnISJScY9N4rHfD3o98dIZV7O8Ix36/VGET2uA7ONM+T83Iw/bGDN3TVtLP32c9Rr2bduTYh+AcPqe/kdVkhHpGVACy0gk0biYvlIyK3VhfJUWZ6z1WGWnVHOKvgw2S/Yo+Vho3jLsDRRmx66rMoA/A7XpBoqRXm8nCoeFgT8TIpGmX8wFI2J7JY2EVWG1CU916Fc10VC2Nyabh6ozoE4oKGe0IGmEKt3BURqhKZ0xYHWEFzZ1pCMPFIXGmbBraaFCHx0YZUTTFRAAMMkIVVz38yxtYdcWlUctDXbJkxCLBRyxp1oyY62QkhrxZDaxWZaSDlFtvkQuhQsbGfUY2Ed03Uf7Mn6tqKuv/tUcrQX1bDzqi5LM1V8qIft4YGbFTRgiJa5MJwU6ayMUDuyaMMYf1pfGpQJTcxy1aXgaVEfvUXr/Xw0h5l5QDFXJ8pX6wV2A9kCBTORGAHOmKH6Zh7m2jSiCDfrO06QarjBmX+goOqaAmaVzTGAtv03Izu7J3QlxlxObS1gfgiJ9URcjYYEHhUK2xK6KwOg89XkKM0jpgWhFPjk2nMmIJS9EKrF5ZYhNxjzcPGuReh2limiHq3yPsJWbKtBDNOCTO1BnaQka8UGOUEU3TTJNqY0eYKHO64konVb5+Eb/K3peskue4erYoIwihI6ygtctybViUEa+NMgIAXT5SvXUDT0b0fctQTeXgAZ2M6OUT2vykJP6edv17KTZjK2AKb+2yekbsUnt1ZaTLR8qdJU3k4sHmXurSf5dSvSK1Cg/akJO5xY5FsTMqTktsgRjWqxDHXSQOsAqsWU1GqMFRlYBgdz2TRZftt8lNp3JqNLahFWWj7chBOKqioWOQZ9Q4KiOcNB7pZK+3Iye9N7xbMMOkQf7ooBtPGdH08uuZV0bsSV13RGGZNFEfJUYZPBZPHDKSroJngHOdEY/MJhT6fZMP09gXPfNZPBBagJKRNFyPcYy/pjBNDBmJxpAR3sDaJZNj3N3SHau4BrgwDc0Q8qbwnazE0GImpueLdpfdYU3vlcxkJCabRh8r1ZxSAHBWRuzCNDqRkfTyCbsYGSHnK9cpTINctPVE0dIV4ZQb2psm1jOiBglRSuu9ZeMD69HJCG2SF/ERtTNj93Q8oqnPRVEfuWbi3mcDrAJrdpMRvZ+jCiDY9DUAoEErwE+eW499Vvc6Sz+zM7CSm8WjD+iDPlSTUBkxGLgmedCJALbt70ivUcwN4igjdu5/OgB7cjMwSNnBgdR1R9SYpm7bM6nS9JNnxAjTSEaYRt9P0vdITJjG4oHQP1/S78H0KCPOnpF4YRqmjGhWz0gzeU8+WbFvb+xk44oatcnS0++xnHxyvSZF+F0qI379s2P8DTaekY92f4RL37gUXzV8xSZ8Tz5RN0xkRL8OZGiwVmBVNRVo3wcACBYTMrKjlZwnSdUXeg5khN4rO5u62PVAw0h2yoiUR+oab9vfgbTBRhmhxJSqnZp+jWfsnrYqI3zfIV2tpqQ8vjIiDKwDBkaYRkLzls8AANu0SnRFFDz49gbLxjRGaeMZ0dlorj7IpM3N31+wNDyjCNswcATyIUkSOsIKGtrTaBRzgzjZNDExboAbgMnvlPEwjU18GQC6owrrS+PN1Vem/RamaSaPafGMmJUqU50R/dx7dSKYNHmNaZSnT5KWMI0/RH7bbY1pmIDieUYUZzLikRTk+D2OBtb8IjKBb93fYWSS6OEGk4FVv8fyCvVww/7UlRFrnyD6u+cVOkzYLJuGvL8Nm3HRGxdhxe4V+NfGf7EJP6eINMnbtK/d+D1lLkwj25ARXRkpLCNF++ua9TCYfr6cPCN5hUSFqWvs5LJpbIqe6Z6RnCJCdtbt5YhSb2ExBgMGGcnXFxhyDiXcXcnX03EDBz+Q3yszAisHXSiQogLrwAHvGZnS/QkAoKVgPADg+Y93mHoOMGUkamOy0i+AUCEZaPvFP5FOOGbTcAxc/85SsABDCknp47SuQNzAhozErAB56ANwbgEZgPvLwNoVVpCn948I5mUgrh1zHHEqsKZVGTGvxlmhLY/Ezn1QJ4Kt3VE0JWMyTaiM0HuQTFib69NwLcZL7WVFzzwxZMQHBflBr2MF1tKycuMYqTKiOBvji0vI9VqXTHZGTDaNfZ2R4lJKjCzXn0UZ2R55k71EQi2EjOSXVMMjS2jriRpVYiUjTOORLXVGNIUpIxXVpP8XJSOyfp5N50BVGCkrKiHHum1/B7seNJ2MBE3KCCEjJRWkY++6Pa3pIwU2BJXW8ghp5Bz6covglSVEFC0zdacsx2BSg/Vz5QsVASA1jRxJv6jAOnDAe0aGSMS5PvrIuRhalIOwomLFpv3GxmwFY/GMaJpxsxSTgXDQp/c6hBfMsUl9EgsUoraMFD2KGdAyjThkxNbAqg/ABWxw7ysDqyWbJqoiJJFBKq+gCADQ1BlBc2eGlCUXdUYWb+rE6h0tsa8nA6cwjWxk03hyi1GtN5Lc0pAEYXAo4mUN05SUchN9b+G26JmFjHxjQikOGV4c6xmJkGOqrCAr9i0N3KRKDax+boLQi1eVlRH1YWsyZN+yejaIoUyUOv18lZdXkc+2/haWa1eRDB+cDJlN+N78MtSWkvt/3d420749kgqPpegZUUYIGakeUoOgT0abnk1DyYidHw8AKst1MtLYyZElG2VE/26lZZUI+mR0R9T0LZRsPSPkHOfqPWGkYAGGl5BzktQ17hYWY7wpfN5DQ3uE9Ld1R50zy0QF1oEDWf/6dCpTIKHm0DmYOZ5c9O+urzc2plUCFYtnJNLFfky64ukXM2c6kcgz4jU8IwgWYEQpcW73nzIS2yjPtuiZvjovLyMDcGNHGC3pSAF1goMM2h1RWGdNX24hm5w3pWMCtT0OusJ39oy8sakHc//4HrrCvVglxevayxSYAtTq10vMBBgPDhkErNcKnVz1e3BPa7dZ2UwFDiQuqqhspe3nQlD0+88YQxRShfvdNY4wD63iyAitsUGVEZray9WLqKkm16vJl5EIFjIRu3omx19dRT475t61KCN8WXdeGUFuGSZWk5DA2t36mMA8Iyo8HosyooQZefMWVOKg6gJE9Obxkl2Yhl433hwMLSsCoIerZPoecnwmw7p+7jzBfIyvzNePzTifvUIczwglIwgWYlQ5SYLYXJ/GEJH1GDQzMecVa29OISoLSA+obU7zkajAOnBAlRFNN7JuD4yDnFuMmePJSmTp+n2GxEWrtVLHN71heowbcFgFFwsezEiUTWPyjBSwldG2AaCMmMxcVuiTRrCgBFUFOgFoyMBgwY7PntR1RRTkSbp6FsjHqHIyOWdk4AJceUZaQX7Dhf/b3Iv9WFN7eWMdd72U6WQkqZW+U50RfZ/6pBUqLEVpiEzwvV6VstRe83mjgz9gyaYJlevHGDGpIgBHTPx5GFVBs7k6EaVZK9ZMEnq+PAGMGUIU1+1Nne7JYrw0a+6zR1TqoeWWbnPqsPXalSxkRPeMIFSGg4YQMrJmV6vpvXZhGrWH2yanBJOHFiKike0lnZCV5XONFLkwIl30bOXCNF6JHJ9ZTaGqbQEjSl/vMRSWXsHmnqZhmhylg+13tH5PZ2SBYUnJNTWNpCQ24GKRKAysAwfUM7JRqwYA7B4+FwBwzOhS+D0ytjd2YTMd0GTa4Ve/8OigQRWCQD5qy42aEabyyIMNbEVo/g4RG9c2r4xkRJKMB7swjYs6IwgWcQQgg8ccRxkJ6coI/HkYVaavojJ1/lzUGWnRyPl4/pPtqe/HIbWXTIA60QrkY2RZChI2/x00zVEZIatSOhH0ktw5pPbynaFNBtZQBds+YvGZ0AZx8OehPD+AvIAXqga0hfUQhUbJiP49OeWxNORHca4PmpbEd4rJpuEmLO6zS0J+5OvpxKZaN7S/DLt2OTKiGum5CJXjIH3CX0OVEdlQRmSrZ4SSkVAZIMuYPLQQUYsyMrqMK61gIiPkutnV3AVVv9ZoSwWTEspNyJSMMKLUW9ioxlQZCar6bxMswGh9Luj1NWh7DGZjfJjvH8QlFowoSbBIFBVYBw4oGXlFPRKHdz+MyGE/AQCEAl4cPpLE3Jau0286j9HhV5I4WZD9+IWoLggi4JURUbTBnd7LJhV7ZcQ0oAXyMaaC3Hgb9rVlxj3uBEtjNiC2szCDEgHC+sCQU8wmrC0ZVUboCsY4Pk3T0B1Rkd+nyog+6NhVYNXVolaQY9jR1IX9qTb4ildnhJ57f54RpklFGdE/P7YAH51gCw1y11ui6UDi6H0gS3p2CiMjZfr2ig0Z0e+LQB4kScJIXR1q6tEJvt7DhSkj3cbqXpIkjK0g4QbXoRqHZmomZUTPhBthRw65zrvk/8Z9rahR4/hyyxgZ2VzfTpQbXhmxhGnUbp0o6MRt8pBCFqbxSVGUhvwozOWa23FkpCI/gKBPhqoBXbrPxAsFfo8MmdZB0TTT2DRlGFGhVtY1pacYZRzPSJBXRioyuNixekai9kRzRCLFWlRgHTigdUYADfUowgT9pgKAmeP0UM06YrZiyggU5Pg8RkdYttouhCxL7ALYMphDNW4qsJrCNCEEvMQo1qd+GRvPiKGMWDv2cubMYCFGpmvCige7gUs/PppNg0ABF1/OtDJiGXS4qqBUGQGAL3amaGS1kK+onZLGka8t9R3uJwi+iZ8aNRtYo92semd6lRF6H5iJhangWaSLlQBHnq6MKLFhGg0acWn4yW89Vifw9R2UjETh98gGie4xJhUAGFNpEH5XsPwWERtfAQLksyl528ifL/27S/q1q3EN75RIp7GPnGKU5wdQlueHqukmVtk5TKPonZuRR0JaYyvz4PGRsJoXCvvtGDgyIkkSRpSQ19v10ytDNZtXI13G/RYswJShhcjxedDUGTFXiU0Vtp4RvRqvYigj9JzubO5CZzjNYRAHomnqTeMqTBPH2N4PyGoyQpURauYq52KV1MT64ZZGwvZ1z4gPUdu0XjpojEjFnDfQkDCbxmxg9cgSxuqD5bp0xWbdIF42jVUZsXSn7ZMwjY0MSuPyIejKWSAPo8rooJGh8J7HPtyAcDv7jVuRi1MmETPjF9t7SUbs+qGwME0eRpSG4PfI6Agr7jPPeGVEjRp9krxGpg4kGfDnYVwVURG+3tNL0yI7b7HZUIBeaIuZVz1ATjE7PisZAfT+tXoxKuqz2K3Pql5EzX1pLISBkpcNbmtmOFZglWOIzoRq/XzxJk9LBVY+TKNS8pVTAsgyJEnCQUOIArF6ZwtXDl5DkBM5AEDtMSsjPo+MicOIJ8aPKJvEGSyp5/S+bdMVJS9Uc8EzZvyVAF8IPo+MQ0eQ3+XDLVx2ZKqwafFArwdfhF7jBSgO+Zl3Ke1jjFNrBGuYhiojTgtEG+W2PyHICABJlyCZ2gFgTEUeSfGNqlixuYEjI4p96pk+aFD5tc/9E+mEgzJiX/SMfO/xldQolibXuhvYNcpzCtNYinvRuPSW/R2ZCy3ZrDy6dUmXD9MMLcpByO9BWFEz4xtx8ozQfi6aB6FQPo4cRcyMn+9oTm0/1mwaPuOEu158HpmF9pjPwO13AIgngx+AuZAGJMkUNuhVZ+YEYRqTeTWnyLQ9X32VHTbAlJFJ+uS9s01fVUuKuS+NhTDQrBDX54sjwpqmWWq+cOcLwMQqG5OnhcxoHBmJRnUiTcNSAKbq4ZDPtzebip7l+M33oULDddx7p40gxCSuMqJX1qWkrEUnIx4olkwaYzKm3pUjR5Lr+sPNjeg1bFRGeo35ooaPDgC7xtele0y01JAxtemw8fLVt/WwZn4mCAPrwIFBPmInI0mSMENXR5auqzeHaWwKE9ELMKV4+ECDmzojlhXLBH01mvYbLx5sDazcipkH68FCjndocQ6CPhnhaBprEMQcX+x5pAOXEabJhyxLzGj31a5e1vqwg5Mcy/lFhpWEcPCwIgDAFzuaUyvtH08Z4TwjgMNqPO534MmIYh6ALddiRX4AJSESNli/txfXoxMZ4YkQIyPFJgWKKiNGKBhQJQkIkO9PlZGGLp2wIWLblwZ6H6VJQ41+Sk0dLurRcGSCmlcB3ePCJiz93tV/i031HSzkQK9dyVYZ6TG+s45pNUUAdDLCmUtz/OZwqRrRr/vcUvbcIaPIOOtDlK3mGeh9qx/rGJ2UNXfr1xZUc18ayyIJAI4cRfb1web9vfeN2BSEpMqIlykj5Fjpb/xVusyz7Bio1yN+CK4wx8fU/g1294GowDpwwHtGHjxneszrM8YZZERjqWRR21LwLP6qM/ukagIMNJgG/tiJnqSQWZSRgUJGXCojHlnCuMoMH7ONwtQVUeBDFAFJ9yGwlbI+cO3MQJgrgTLSooUwrDgHk4YUwCtLaGgPY1e8nhaO+zEGN03T7LOv9DCF7Wo8HiTu91QV2z5JdMKSJImRY9dkxw4Oxl/aGM1U8Cyn2KyM0GJcHiP0yysjhTk+1JTkIAxCYPyIImQ3rujfqTDHx1TX1W48PZwyEuFTkW1UzaqCIApzfFBUzQgDyeZ7S+U8I1Glx3RsABiR3VjfjiiMbBorGVGoqsK9d2wVUS58koJJnG8PQAzRpMpIUzc5HqKM2IRp9OsMAKYPL0J+wIv9HeHUVT8KG9MnJSOesFkZoepX2hcYlsUFy5SSEfPb0vvAlpSLCqwDBzRM84MjavCdqUNiXj92TBl8Hgl1jZ1o0RcjPijm0sMWZYTKqTuauuylscEAmbssuJvOyTMCGKuALfs70NadwUJiPOI0yovp2svL6Trojbo202SEOz5TWi/ABk1j4Op7MtKGXAwpykHQ52EE7Yvtzcnvh/s9otwK1IeoYTANWJQRt+dekkzfg6kTXtlkIqeYaE03TQUOxeIclREbMuLzGKYJ4hkxPBGTqgsR1jNJ/IggL8grI+b7CwCmDOV8GQmP3ciIi5qUEe7e1a89SZIw0fp7xGTUcam9zCxcxJ4rzw9gaFEONA1o69EnZ6gIWD0jNmRE9hob1RRa3mAhIyPLQpAlLptGUizVV2PPm88j4wR9Yfn21/vQK9h5RiIKJKiQKRkJUDJiXINpbSJqLQevX4856AZT+fXvT+9n2/vM5rv0J7KajFBlxBrXpMgLeHGEHm/c3EhuQB+iqNQrZgKIYaLFIT8qdGmsT1WCdELiyBY3EJs9I+YbryzPGIx6XVbc9XHGU0as2TTN5JEbQCfQ1XlvJqy4x2dnYFWNgmfeHCbtG5JuS/q7HzvUy2AFz7RcFOcSs93UGj32n8pvyP0eptV4lDPQ+cngSM/91v0d7iul8mSEL8Bn018nPWQkvmckwBMhnoxw2TQmZUQC+/4AcOiIYvRoVBmJYMrQImMnFl8HABys+zK+cLO659rD80XaTKm93IRNz9dq+tk0TGPjGVGpUmTpZzRtODn+VkpGJDXGwMqUEW5RQKvQkg0sISjLbxv0eTCiNIQojIydYAJlBABOnEB8KUvW9pKM2PamURFCNyQLERhTkQe/R0ZbdzS2K3Jv4FAOPkftNI7RS+ao8XGVkdjxsz+R1WSEKiNqnB+DKiZf7SUXkxcKW1EDsGXicS+AwQA+jZJTRuwrsBrngg5Gq3orhbpF3K69Tp6RIvYU87lk6neyicl2RxXkcZk0FOMq8+HzSGjtjqa/gZ+TZ4SGaRBCsV7bYSrnG0kanLGOhvQAwBvVpX9vDqvXU54fQFVBkJBXt6nEHDmI518CDBXhq50tqRuUHRoMmrNp7JQRo86IOUwjAX7DoHnc2DIjTCNFcfRow0dhRxiYMuKGKHLXHq2+6vNIxCdnydQBgMNGkEXXR1ubLO+3CdPQ88ETCgCH6VkrjZ1kWxkaAj6LZyQaq6qAU49imhLa/LZjKvKgwPClFIe499uMSwDJjpQkQk73pBKCpLCEXqMKUQFpewfIPkYEfB4Z46rIPZ7WUI2lAWfYWnRNN3IDhlK/bo+NbUAYWAcO3JCRb06pRtAno75Dv6GhMOkLgK1hql/MnOmEgzJCJ4CgFOHqOhjfe5o+ka2qa870ERJYWtYDlkwHHjbKCCWN2/Z39r6Pie3x2SgjYQV5eqtxfsD0e2VW2CpjhjdrbJgaWLUQinRlhMb+V+9oSd7sx9V9Ma3GKRnhyBdAYvkAsMptSIibCMxhGvsJK9fvQUdYSb3eCPOMuMmmcQjTyM5hmglV+QgGScfrAKJsMgdgSxgmDS2EJJHS7fVtCQrT8Z4RaupmNUzM3gYArMjj13taSb8mi4GV762j0smLJxQADq8lhKaxi7zugQrekwsAio3fxORRsxbms/ltJw0p4JQRhWVPmb4bd94AoDQvgOm6ybZXoRrLAoNehwUS7UtjEAGAhOKAXip0Mcdg37XXKLpmjCtjK/MgSUBDe09sMUNRgXXggPWmiSOL5wd9mDOpyqgSiChjmwBsb5bxyZrzBhoclBFqlAqpNPtEMsnOVBnptUnMLZIxsNooI6V5AeY2z4iK5aSMcGm9PCYP1UMLaTe8GeEDE2yUkXGVefB7ZbT1RJMvYGfyjBi+CokrBc+DZmB8Vmfuepvwe6hRw0xtqpth3IMeWWJKgmuyYwUNH1hW645khGXTRFhqr1f2skWPJoEZWAEy/owbStSQQr+KED9z2ygjeQEvKzP+ZSI1ic+m4fvS8J/NTdgV+UGMKgtB04BPtjVyRc9ilRFFtQ/TTKwuQH7Ai7Cql7iHGlN8ULXxm0CSjHPtSEaM7acOK2LKiBcqC3Gav5v5WgOAkyaSBoVvf7035jXXsIRIaPXVfLbAMJOgSUMzkFFjbYLIwjQcIdKR6/eyDsIxCrCowDpwYHTtjR8zO/2QYcxoliNHMaw4x3jR5sYez2VppD3+3xcwKSOxIRB20XO5/AAp7SxLwN7WHuxr7YNy+LZkhJukeNgMaoChYmWkPoqlHgCge0ZomMZvHjAzZmJ1NLA2A9A9I3qBJq9Hxji9gF3S54SfAHWyYJfWSzF9OFmNf1bnMpXYJkzjpIwAlnTTVODVQyxR84qSpr8GYpQRY6KK6JOqT/YxMqJAipkkZ00aBgAoDcKM7liCBQAHD6W+kQRkhJuwonxfmjifTf1xH21pZNeuhFhlRKHXsyVM45ElHFZbbAqh+L2WCqyUmwTNkzbzNfGeESUKsAwVPnOn0KKMcN/D4bsBhm/kvY0NqdefsagSNGRXJOsLDMv3msR5wdIGa9deGjZkyoj5uztmDYoKrAMHbMWSYCA8dkwZAkHCLkuDmtEHAbAdCMdW5kGWgKbOCOpT7fPRn0iQTWOKTXLI8XtY+mHGMlR4xMmmiQnT2CgjQIZDajbZNF1hZ2VkUqbqEnjsyYjG1Rkp4vqB0AJ2SZ8T7veIVyCPYsrQQnhkCfvaerDbTRyfIyM9dgZWy+dPpWQkVaWOrdbNpsqehGEahYVpvLIXHp0YqBZlBAAmDiNZHvley+TodM6G0Yya5vjHzpkTjb40NExDz5f5+jtMD7OsrGuKr4ywcuuxE/7hI0ugcmTEawnTqADxDnkD5heoqsQrIz3cfcCdh9K8APJyyPvzfBoqC7jPcjCwAuReryoIojuiYuU2l2qcFZYJnBLTYm9PzHGSfRZA0hdoDemaCyzHwMa8qL0C6ZjeKyqwDhzQME08zwhAGP/BtUTiK+FXMHxTJo4RB30eVvxs0PtG7DwjNnIgBc2S6JOy8MkYWJlnpNj0ND3etZnIqLHzjEQVruCZZWKqJgPXntbu1JvV2cHBMxLtbAZA6owU5RgZDYZalOQ5sQnTEDJi7xnJ8XtY3QhX55/zjJjTzO2VERqmWbenLbUy+w7KiG1qb7CIW93bh2lUIOYcMMIT5QiPqhhqklUZGZa8MsLOlVfSmwra+yqokrR6Zwuiml4rRCce/BhpkJGimN0eObLEUEYkDV5LbxpVkmIWBACMc61w55r+rr5cwOs3bV5WSK7RshzJVDk7HhmRJIlVGf5gS2PsMbgB87dogKoyYlrMlBHz7xUKeNkCLW2LDIuJtsdKRizjsrMyYpD70x9ZjmP/39upq4hpQFaTETcGVoqTptQAAEYVcSGMSKehHFhu7H4pApZO2PgdqPTOd6e0Ii3FptwimdReB2VkPBemSX9KrX05eCdlJBTwYmRpmgcuwDFMo+rnJOzNMylJKV+7Ntk0fj5MYzNBjK2kqzYXJlMuXk8JQSBOmGZoEamyG1G01Bo40kwYqzKi+wRI0bNm8qSDgdVMRqQYZcR2EnZQBADgoGpiYt3X1hPfxGpTgdUny3o/Iv1+sUxao8pCyA960R1RsauVfGemjGi8MkLfH6uMTBlaxH6nkE8yiAt9r8P7DOLHnWuH0CoAjKkmpGJYgUV6cVCUKI4cSTw6H6Xap4Yvvqcp7FpgYRqbazztxc+snhGqEir2irWR3dluHuO4a2R3cxd2Nnfx3ts+R3aTEf3razbl4K3w+YlPxK9xMiJVRSSPKWUPME9ygxI2q3q2IozGurYpaOfjPgnT0Aq6dmEaXhkxxZ6LTJ8wpiIPHllCS1cEe1vTHFKzq9YYUUyl4K3ISAlphxRVev1qlsmBFiTbur8judi6TZjGVH7cOhEDGMcawLm4XkwGVj5MY+8TkGXJ6EibSkVkuhp3UEaCsmZMfhbPCCMjkkFGFAmxv7mdMkInYW8wRhHI8XuYITHudzJ5RniVqs143WcuvS7LEkvt3ryfXKO0UR5fZ0Sh46WNwuH3yigOEWIR8hkqil8m30MF7MkIJX5RLlznQDIBYFINCW+NLrYUMomjjACGL+azumaj9H0ysLQloJ9RKNN0/VgSlPbwq6XSMbvXIvakf2RZCD6PhPaeqLkxJaeYdun3uam6eB8jq8mI2zANAJY7brpZeOe2hVKOZyu+QUpGbJQRNtErsamBFFQZ2bSv3VT4KiOI17WX94x0cysSy8AW9HlY19y16Q4t2RhYuyKK0bHX3werKMBRGfGEyT7k3CLT8+V5Rm+XpCZxm6Jn5rbmsWSEKSP7kiQjvCkzzqRFm5VtSqVzqsdGtYBxH+SD+8xgoW1vGq/shYcteuBOGbFJ6+VBQ1sb450z7v41iKGlcrLNMpgWvdvUQCYtWSchvMKhQNIXYLG/JwCU5hOSE/JJbGyllWgVSbJVOmzH1zi/Kz3XkpVg26Qt8xhdHkJZnh89UTVxqMsOfKahGo1tfGmzX5p6vCZtZCTWOwVwZMRyDD6PzLKwTPMRR1gpGTE1ge1jZDUZSSZMw1YovGRr4xeh4AufZawrbCbBVXCkYBNMxF4OBIg0nhfwIqyome9czNW1MI7RUlMBMPwi/nzDzMkhYyE1h3Lw+Q5hGoArIZ0RZYRbCaoKG7x8FjIiSRKLcyfV8JH7PaK2fWlirxeaubNxX3viuib699C4MI1PiwBR54lgTEU6lBGrgZWcxwKNfq9Ccl3xZEmfJL2ylw2yiiQDvhzTZzHCo0aNe80mVZnHaDffibt/zb9FfKIzrYZ4qjbWk3PqgYq8gBcK14VYkfRjc9D0h+tq1JjynJh6K47KiJ0/x6bMP4PH3s+TiMhJkoRD9XouKdVD4pURzVBG8iX71F7AuKe37u9IT4sQjkTw9XyMcvSx44qtUq8bmjWOVOUIMtI/oOXgXXkFbJURc2dNHiNKQ/B7ZRJ/5aWxwQJLlT+AUx0cjFLkbRIbLDdlulmgFBumMWVZUDj4RShoKey0l4V3KgcfJ0wzievxk7ZCbHZ1RnqMQckfKop5ywg9FLBtfxJeC5NPgfsdHFJ7AfN9sr0pwb70z49Gje/BrkXAdiJgZCSVwmeJlBFN/0x6Xcn2yohMFVhfKHYC58MwdD9xFjkAWHG8DfHuL+7+te0p5TBZU2WkrpkciwwVpXl+04JNBRzvJQAozCVj5REjitj7aJjG2TOij692BtY4yohpcahpiFdnhIJmWaVUKdpSELKHqWSxhQwpSvOMasNpGWN41SvKkxH63WPPFzWxrjeRkdg2Ebn+2MVaXyG7yQgdJBLUGQHgwNydBw2PLDH5P6WBsL9hm02j146IOK90AbDvvbnPlJFEYRou48EGNKSWdn+PTairK6IgJNln0wDmgSttGT5xMhW6NR/y82KPY7jeyr0uGTJim9orxY3je2SJk5AT3Cc6qeLJSCDKXYty7KqOfvamfe3JG5TpedNUUxVWg4zo+87RM7S4iq0mMqIvelS/2aMBwCA8gDG2JFAvaJgmLhnhs2lUXhmhE7z9Z1fkBzG0KMdUK6Qk5DWRkagkOao2AEzZHjS8Q8M0ztk0Nv6ceGTEa2MuDreDNYpzOHeAUSk6pcwR2UpGyPdjzS8dzmtafSPc+e3hPHJSnBCV7Rinn0NJ6QE9bzENRvsQWU1G3NYZAWAvCyYYNPiBcNDBzjPCjFKxhYh4MDKSSpw+GcQjI0koI9Swuam+3bTS6P3x2Skj8Q2sgLnbZ1oQxyRJaoz4Y94yQicjqYVpVLMy4pDaS0HViy0N7siIEjGIgREnt78Wa8tyIUtAe080+Zo/HhvVAob6FlI58yp3fFCjLLXXJ/vYIKtaQzSAuS8LnVgTKCNUeaxv6yGl2+1gKkBnYyaON1nXFEGhqb1QURoym0SJulHk+H523WtKTJgmoTLi2jNiNx7z5lybc61j8jCSkbSjqSv52h+SxHnBIiybJqTZFxyjSGvxMy7sam7a6KwK0TDN5voOw8vHXd8+KAj6ZHMNrT5GdpORJLJpklVGAGKWAlI0z/U3LBOppmnsIvaEEygjOgnbnGhy6fUxOhc98/FlqOPFnkF8LvkBLyKKlt5jtiF0PRGV84w4rHz1VUxKPgc7xBnoW7VcFOb4Yt4yQk8xTiolljPsmqp+xollA2D+lIQeI0pG9HCTR5aYCdfptw14PaguJBPT9mTTe702qgUMMpJLjdyU5DoaWAkUuwlSkmInVhb+tb8+8gJeDNE7h2+sd1Dz+GwaVppfSjhmASRUY1JG8szXhwop7vv5lTsL0+gTn+qkqtiOr27CNAYZ+8WHv8G86gooDuZcioKgjy0UU2oIyZWuZ9eC6hymAYCD0lldmU9x5wvwxSGaQ4tyEPJ7EFZUbKMLDO769iPSryEaIMvJSK+zaeLdLDBWMCk36upPWCZSRdWYT5QZpRwGpFHlhjKS0XL4FjKiqhqiqk05+ATKiCRJmTGx2pWDj/LZNPGVgrRdN7bma6qM5KIgGDsIUc/IntZu9+m9bEXMpfbKXJjGJnsIMJS0hKSdekYieql1vuBZnJU+TYVNutaI7AVLH+fOHT0fBhkp4bYHoEaYgdUn+0Drfql+h9W6NeSQYFwBjLFlg1Noy5RNo4dX5cQGVoCYWFkVVUlFScgc/opK8d/P35csTMMrI3YTdrLjqyX0GFEjeHXXe/gsGMTGXGe/CAVNYV61PQWlgqs/Q8M0QU2/thKEadbvbeu9+mrjGSFkxFkZkWWJLXJYqMakjET71bwKpEhGHnroIdTW1iIYDOLII4/ERx995Op9zz77LCRJwne/+91Udpt2JJdNQ13vkVjXe4IwzebBSEYspYLdurYBstKVJKClK4LGjrDtNmk9Rv33i3CZPz6TZ6SZPMaRlumN6ji4pwK7cvA90YRhGqao7UuTohZXGSGFrqwoCfmRF/BC04AdiYylFJyh2D5Mk15lxFQKPs7EzcjI/iSN5JJku2KnZCTHqozIvBrBe0YIGVC9Np4RgAujWQ2szt8poYmVM1pGo3qoJIGUTzF5aAEzwErQUJRrnqRUID4Z4a572seGKSNO+45b9MxOGTET7JYeg1T4faHY7S2Ypht1U/KNcP4WEqbRkONQcIxiWHEOCoJEfd3gJo09HkyeEd2z4lGM+9uBELGy8JSMyB52nfgRRdDXv9pE0nt/7rnncO2112LBggVYuXIlpk6dijlz5mDfvvhtmbdu3YrrrrsOxx9/fMoHm24k5RnhJVuXrnc6yDa0h9HcmcFJOROwKCO0oiYASAnCNEGfB0N0aTyjJlYLGeFXHMkoIwBvCkynMhLrGVGjXfBJtGqvg1Kgk9g9rd3pSQWM6xnJRX4wNkwjSRKbxF1n1PDl4Gk6qUk+tleCavX7pL6tB23dDh4IwCAjuoE1XvVVHsyMm6YqrDQNMhjV9808IzZhGsnLlBHFZ+2Gp8NqMHahXozlUqJtwfWXooZfnyzZdgO2ItfvxbAS8vkeqCi2ekakBGEa7rq3Fj1TJMn+e8UremZ331qu6cbuRvaS6qA48uD7FiWt3nJZVj1RFUGE4aG9exzOiyRJ6StoyKf20kZ9Hi685XDdsLLwfK0R/drzS4MwTHPffffhkksuwQUXXICDDjoIjz76KHJzc/H44487vkdRFPzwhz/ErbfeilGjRvXqgNMJmtrrLpuGG0joDZNg0Ahxsd1B5xuxTKQ9CifVu4g701DNlkx+b1aaWQM0jWX7AA51RuIoI72qR+EEm3Lwngg3IToMmoU5PpTnk0EiLebnOGmTrVou8gL2gxA1sbomI9yKmPUxkqLGfuN837I8MrlsbYizL0ZG9JV+nOqrPGpYmCaFa9Emy6NbX436I3TfRabjgxKxeEZ0ZcTJVGkliy7ur4TXK6eMKArNaHFnYAWAsVXkfHqgojDXPE04hlrYvo20YtajR6/vowL214E3DhlxoYw003scQMQua8mCCVUF8HtkNHdGkiepXP2ZnqhipPVCAuKoMrSgYa9rCHGVnXsUSkZ01c8Xss0qAxyagureG/9gC9OEw2F8+umnmD17tvEBsozZs2djxYoVju+77bbbUFFRgYsuusjVfnp6etDa2mr6lwkkFabh48dJDBqD1jdiUUaYa9yrQorGN2ACnA8gkyZWU58IzmArS/DwrnC+f4gD6OC+bX9n+irH2pSD9+p1MVRfyNwd2QLD/JwOMsKt7mkoi8umybMJ0wApKAo2qb154CaXOBPYSJYOHq92BrkmUw7TpKKM2BA5ei/4w1ZlxL7oGevvkkZlZIyunu1s7rJXz+TYMI03TlNBK8ZXk9dlqCjMNV8fmiTFVx94Ays1zzJlBAk8I25Te81kpLHHUEbckBG/V2ZKxapkQzUWZcRkSI9zT6etoCG3yGG9ceJUgKUYp5ORbY2d6ArrY5L+XfyIIqcfS8EDSZKRhoYGKIqCyspK0/OVlZXYs2eP7Xvee+89/OUvf8HChQtd7+fOO+9EYWEh+1dTU5PMYbpGUmEaSYqNvccpekbB0nsHGxmxNmPSJ5cSLz+5xFNGqF8mk8oIRzg01ciksTbJ66gnj6Fyx4+qLgwi5PcgqmqG27zXxxdrYKXVazUHMydFWq8bU4iRDN6avpJs1XKR76SMlBCC4Pp88Km9elgvRHt2eIPmNFYLaA+ZuL4RfbJX9cnVXAre+VqkZty9rT3J9doBbENc9DN8VjJCq/taPCMejXpGHMhICspIcciPsrw46hmnjKi8kuSC6ADA+GrynTxQUZgTO0kp8SZ8LrWXGVj151RI8T0jlJApUa5zcVHs9hZlpInWEgIQiZPWy4N2KU6ajHDKSHeEU0biha7AKSO7WxNXG44HPrVXH5cLWG8c53GlLC+A0pAfmsaFo2mYBpHBpYwki7a2Npx33nlYuHAhysrKXL/vxhtvREtLC/u3ffv2jBxfUtk0QKyZzY0ykm4zYl/BUoGVTvQlHv2i94VsS6tTGBk1faWM8IW2LJd1RwN5DDlfg5IkMXUkbSZWi4FVUTUEVeeCZzyMGjVpuG5MhbXI76d0NgOIr4zUJhumsUknZcpIPFkfwMhyFyZWSkaSVEaKcn2McLk241LYFIyjZISlFTMDq5FNYzKw0t/fiYykoIwAwJgKvaiiHRmR+TANJSPuUnsBYHgZ+b38sob8YOw0ocRVRgzzOz0PfhYSR4IwjeUcAPE9JkoY0DRzmMZJgbLg4GHkmlmdbI8aThnpMqXqJ1pghBDwymjviaam0lFwixw6LhckKBdAEZM1qC8QfINNGSkrK4PH48HevXtNz+/duxdVVVUx22/atAlbt27F3Llz4fV64fV68de//hUvvfQSvF4vNm3aZLufQCCAgoIC079MgNYZceUZAVIaNAZtRo2lN02PlYwkGMyoMlLX2Mm6hqb/GM1khIZXTFUEVQXo1NuFx1FGAJc9P5I6PrO61B1RkKf3sJASTjRpVEY8PlhTVNUuMgC3SyHHFREN02xv6nTXX8kmTJOr6uQigalwpJtCeXGVEWcyIkkS5xtJchKwU0aiJINCphNgoqJn+j2k8QqVaR/WRY67UEpc9YzPpjF5RhJn0wCAx0Pen+OVYtJzAUDxx8lY4ZQRVmdEf0mVZftFjFV1Zv2k8uy3NxWLi5gMrBEn0mfBwXp671e7WpMbozjiZC5iGP+e9npk5tvolYmVC6EbvXESh2kAriw8NbHSMI00yMiI3+/HoYceiiVLlrDnVFXFkiVLcPTRR8dsP2HCBKxevRqrVq1i/77zne9g1qxZWLVqVcbCL26RVJgGMLN3VY3v9tZBJ7htjZ3pre6ZaVg8I/TY47XK5lFdEETQJyOiaNjelKHePFYyErVpktfVBFYimtaDcECv+pjYwXIOu7iBSwomWEXpx7J1f0fvyZwpRZX8fpruo4l485lCaEV1YQ58HgkRRcPuFhe/IZ/aq/8WuZI7ZWQUl97reD/q55MqI34Pnx0Sf+I20nt7p4xEFBWKqiGEbkjUC2SXTaPYKSMOZIT3P0S6AGpyznV3vdqSEc67QA2/XjlxbxoGnVBIHKEIcApbXDJiVw5e/00VyWHCsyoj1Ofl9Ltashube5rZfyNO59mCUWUhhPwedEWU5O55LkREGl+6C9MAfPGzXlRi5Uhv2EVvHB4TrA3z9GsvMBjDNNdeey0WLlyIJ598EmvXrsXll1+Ojo4OXHDBBQCAefPm4cYbbwQABINBTJ482fSvqKgI+fn5mDx5Mvz+2DLUfQp97HQfpuHYe3ezUT8iziRXkR8gXS9VLTU3f3/B6hmhKWSyO0lSliXUltIJJkOqUEyYhlsBUlC/SE5J3LASYJgCM6uMkMlZSnD+qguCyPF5EFG03km6FJY6DpI+iUf9zgOoR5ZQU5zEJM6n9upqQK7mbpAcXpoLKVHZdmpg1VNVgz6PaxWBqjzbUlZGyDHREE0R9GvEEzBKj/OhEd3A6pE88Oi/v7NnhJuIO/UVvuxNSBgMZcRhXKE+DT1UEpQipE4SkHji5Gum6CqPn1MjbKvJWvZr8oxQ34yTwTNGGWlBqyxBczpOvlR/NGzxjLgjI7IsYfJQct18kUyoxqKMFDAi4IaMpCG91ya1N8/lMYyrclBGBiMZOfvss3HPPffg5ptvxrRp07Bq1Sq89tprzNRaV1eH3bt3p/1AM4GkysED5kGjS7/4/fnmzpsWSJLEfCMbB5NvxKqM6BN9gexODgT4EFWGvreVjES5EuQUzLya2LNEC59tqnfRzt4NLOcwUcde01tliflu0pIWbqnjIOvmay3B4JXUJG6T2puToEw2RcDrwbBiMsE5poPTKp46ocrhyUiC70HDNCmXhNfDW7TGSJGsHyOfocW1l4+asmkoGXGhjNCQYk5J3JLmAKe67u+wzwDTf4+I3suHreAhOVbDZeAJhU6mvJIXElU4Ai6VEVr0TCenjsqIJRy2fO+nOHZEDf6Y4zBFcQW7oITN2TQe94tcWm8kqbLwnDLS5aLXFI+0NMz7/+29d5gc1Zk1fip0nJxnNMoBZQmQQEgmGWSCccDYGANrMOvFBsNn82F7bby2cfh2wbs2P6+NjXdtE/ZxAOMleE1YMCCikFBCCIRy1oxGYXLoeH9/VN1bt6qruqu6q7tnNPc8Dw+jmQ51K9x77nnP+75clh4lIxXMRJudlNMwzZG+mFb7Sh9LAKmxFaahuPXWW7Fv3z7EYjGsWbMGy5YtY39btWoVHnzwQcf3Pvjgg3jiiSfy+VrfUVCYhu5gos7pohRjMqPGWmdEn4RrJPe7AF8XUzs4eEbMygg1r2b3iwDApLoIgorWzv5Qjw+hJUs2jaaMuJ+4/M2o4VJU02koNKsnSyYYAKZuuWqYx3tGdGIYocqIi0JU03Jl1OjGRJLQVIrKAMmeccEh7/Rei5+DKiONiv45fIiWUw5M2TRUGXHKJjJtcui80pDz0Hj1zJZk6c9wXC+fb5Lys6SgAjARy7R+/IokGX12si34XJ0RpozQcyC5U0Z+sPcJAMB/ylmKEDJSEDMbWHMooDwWtudhYjUpI2lPYZq5rdWQJeDYQAxdfSM5X28LOj5TbxzaqC/7vFIZUhnp39bZz4jwmFRGTiZ4z6bhHhh+B5MDY7LWiGwsLICR2luVo1U2j6Jn1GQoI7pZjk/tpWTExeSuKjIzUvoSqrFk05jMbi4W5xl+ho344l3xfki6GihHs5MRVvgsWzEyCo58MTOxy+whwOwbsYVKyYj2mXV81ckc9+MUjox4qrhpqWdBDYNNKiUj2ZURRVIg6wux4wKuGosqm1dc3K851TOmjGjHUuEhnGAywOpjkSEZacpZ30vnDmJUYGVkxEHtsXhGupMuyK9+3kgyju4YF6bJkkJuBe1Rs7XDQ88YjgQNx1PGnOjivEaCCjP3v5tvV26OvDKjOHF/DLN5E+tYNbCebPCeTcNN6GwH44KMjMXuvVZlhBqlvCgjjbR7bymUEWKvjAy5V0YAYGaLj2XhMzwj7sM0gFHye8cRH46FLyqlhzZGSAChcPYCUbRUuztlxCBf1DMSdhmmAfjCZ05kxGwmraEhw0BF1homADChNgJZ0q6BoyfFDhnKiDauBjk7GUnpykgAMuRcYRr2HXFPiivgLqMmoRtYK1z6dwCYDbA6EVNhLBjUR2L/3swwTUA/HylHMmJWRoayfT6Fft76R7qZEgUACdm9MjKpPoLaaADxVNp9k0zOfxVLpjzNiYAPxc844kYJVMSlMgIY6b3vd/abUnujgoyUD97DNJzUTScNN8oI9U50DRS3i62fcMimqSTuYpOAoYzk7DmSL6xFz3Qykq9nBPDZxGopB+81TDObmc188LDwRkyu+qpdXxoeNEyz77gLRcEmTBNK0dRe92TEWRnR5GVJV0ZqJff3YlCV0ab3S/LkG+FVCxhhmnpKRvjwkCQxApDUM36UdMLo2utEmHiS5UEZAXKoZzqhoMoIa3PvQtU0lZPX71+FSFBpnx2ukJ/je7kwTVA/H87KSGbZ/ZzQ7+mhuHlR9xKmkSSJhWo2H+px+b1cnZE4p3a6Oa/gfSN5ZtRwxI11DU7TcKULZUSfV7Z29LF7L4SEZggvI8Y1GSmo6JmH2O7khigUWUJ/LImj/R4etnLCQRnxIvVWhY0eKzk7suZ1jBJYSpSpAmt+nhHA5x41lnLww4kUKlwWAQM0IhBSZQwnUoVn1PBEWicj/SRi27GXx8S6CBRZwnAiha5c9y7nFaAqVdCDMkLJ6z6ndGaLMlIt6feUy0XAc+M/wKxawFBG6uwMrIDRP4f2ZEklmc/C0S/BmzeH3M8rADCjOUvbAIsyYuyeXZwvLqSUSummZxCjz062OdMutVfPgMqpjKTM95iabYnSCUyCtqfQ4UUZAYziZ5sPuCQHLDwUw0gyjWrPyghN781XGdHPVTqBuG5OZqTfxTFQMrS1ox9phXpGxlhvmpMNnnrTAOaMBLaDya2MhFSFTYS+1bAoNhyUEbfZERSuilkVAptCW2ZlxL1nBDCTkYJVLBsDq9tqjYCWWktDNe+7lZCdoNorI05N8igCimxkueQilJzPiIZpgjT278IzMqEmgqCq1aaxNRDr6aSyvmBVucwgoJhUT5URD+ZkCwGiykiN5EBGdPUjQdWEVAIy81k43E92yogLxRXgao3Y3a8sFdpCRtyQNy6klNINwypxG6Yx6mCwMI1O5hxnWi6MOMQ1k6zL0niOEqZE0mwETSCLamMDWvzsbbcZNfo6kE7EkEoT1zU+KOa1aed/3/Eh9A7loRhz1yatXxsvZGRaYyUiAa2+Sn9cI4dBJESYppzwnNqr2sR2XU4aY843YllIKRmJEm+70RmlMrGSNMv4MVVgHezS/u8yTDOtsQKyBPSN+KBiWQ2sybQnAysAzG7RzrPreLYTbDwj2Tr28pjSYCgWWcEZF1kBupT7WLYsS5jWkMU3oo9B0YlBJbsXXZKROqOirGtYUk5px94aWmfEWvCQEgCaTZOMs0k2RRwWST6E5jFMM7WhApJ+vx4biJv/yJQRbcELpfRjdmVgldiiS5URBQQqcaGMcKmvLEyjh19SyGVgHUHnoNHnLCBnydqhZCRhISMpbwv86ZM1QrntSD96h128Vyf2lKRVuqx+SlFXEWRm7XX7TuR4td33G/VqiD72YNJ9mEaRJcxp057HY7S7h5QUYZpyoqBsGlpnxIUyAvC9RsaaMkKzabRJxZPUC8PEuqvYJlY7ZSSVBLr3aT/XTXX1ceEAp2IVeq0y0qNTqPCgjADA3DZqNiuw0ydb8EY4ZSTq2JeGB+1RszdXeMPmWgSS7j0jAOcbsSPt+oKlpLVFIOqRjHjuQsx9p6GMaOOqJpSM2IdpWGpvKmaEaZzmGb6WiQdjPKDdr5RkZYRq9GeYdu31smBpx6XNdyldeVBI2iBW2Twj3DxpeEa08+esDtEwTRydA4fZr2NOBA5g93TSGqZJeyMjTVUhTGmIghBg4/7u3G9gyoh2Xrxk01Asm65d3zV78iAjimoUtEuOACAI0Gvrcl6hoZqjQ3ptprHWm+Zkg+cwjcpN6EMnMCxJ6HVZ7W/M1RpxqDMSTnmb0Iz03hKQkSRVRvRj79mnVZxUI0D1RNcf6VtZeGs5+Lj7PhYUc1p1532+aYAU3GRvKCMVjh17ebBaI7kIpU1qLyMjbsN62Rrm6QZWRkaYac8dGZmoL9oHvZARqzKih2kqKRmx1jfRX08XYTUZZ4XCHOcZU/jXm2cE4FVXKxmhvXy0Y/d6LShJ4smIQg2s2UgCpyCzMI2+cDu+i/OodPTtZz/HSRZioX9PImVRRjySEQBYMkUjlev3uSAjqhGmUZFEVNIVVJf3IQCcOa0AMgIYz3MiprUmoCTP5byyQPetdAxSMiLCNGVF/tk0WqXEiydNwNlrvoWBeO5FixrNirYo+42MCqyUjHhURppoISufqppawYdpdAmdhWmO7QABkGyYkbvIEwffGuZlpPYmuS627sI01Om/7/gQugfjOV6dBWoBykijW2WES+1Nadda8eAZAZC9zou+CKhp7TyEvYQdYBhYO/pG3NeUcPCMVKb1sJlVGdFfT5URJelGGeENrO69aBSOHZ51j42kH7ua1I85R6E747goGdHer6TTzMCanYzYKCM6GcmpjAA40rOb/RxPZ/GmUH+OJQPHa5gGAJZO0c73W3tdkAOdOKWTMcOQDrgneQDOnKaRzS2HejEQc5HGbAXL8hoxNjiyarQmyAFaBn9fjx7Ck1Koi5a3Pcu4JiMSa2vtcWJKDCM+fALdemfLnT07c76VhisO9QxjKJ7HzVdq2PSmkZE2siNcx+kjUGUJI4k0OvOtOJj1OO2UEf13x3fg2431uCA6hGPDx1x/5KxmbVLZccRfZSQVG4Qs0R2Mu4mrJhpg8eVNXkpWW8EWCIsykiO1FzB7RrISd+5aUGVE1Su9uvXIzNWVoK2dfZnfpU+0AaKTEbq4urwXGyuDiAQUEAIcdlth16E3TUVaV6qsnhFdvWFhmsSIC8+IPq/E+owmeS69aECWoopc2iYAxOK9+Jf6OqxP9rj7YEpGUpSMpJgyksxGErisQ6aMxLVxpZzICNdZemCoi/06loo533P6eUtaMnDyUUbOmKqRyk0HeuxL6/PQx0cSMaPGiBrJWeuGR3ttBBPrIkilCTa4UWMyjsEgfEadk6qcLQQo5rRWaSbWtLYZaY5CeEbKCeoZca2M0EljuBvHOcEx6KIXQl1FEA0V2uvGhDpiWUhjybTRjAlwvRtVFZnF6osybs40SdOPg5wy8peqSnQjicd3PO76I30L07CwhXZcJKYtnmnIQCB7sTEep+r9Mzbu78n/WPhQAK+MuAjTTKqLQpaAoXgqu6mXS+2Np9JQkWSZL27J16yWSiiyhJ6hRCZ51ReBINE+M+iRjEiSxDKDXPtGbHrTqEgalWWtyohesj5JwzTxQVa11HGeoR1wj74PAHg3UolXjm12d3zIUmtEJ0ZhaMe+OnkCf6ypwn90venug6lnhJGRpLvUXm6hpK8LxAb09zmcA0li74uPmFNsHckFU0YKD9PMaKpETSSAkUQ6dzEyfb4nqZjRJM+tD4cDDdWszSdUo9+XUjLmqVEfe7siY9HEGsShk5GIOxJTTIxrMsLCNK6zafSH7MRuHFMMFhlPuZPPx5RvxCabppqaL9Vw1uaAVhiVWIswbq5tvVEOXjv2gePb2cv64+6zUWZwxdpcueudYCF00MlIQo263sEAwKmTawFou7a8wS2qRO/j0UeiOeuMABq5a9cX8ayhGj61N0XykrDDAYWd/61Wn4z+/AV0HwFTXTzE6mmoxnVGjU1vmhpwpNr63VZlJD7I8kcclZHGWdr/9RDNZ1rrccuLt+Bg/0FXh0jJ86GeYQzHue/QiVEYcSiyhJGkNubetMssMRam0eY3JZU0PCNZDay6cpCMGR1/9VB2KiuJ0bNjYuZn1XF+pSExS1gmHzIiyxLzjazLpVRwyo+XispWLGO+keOe30ufBSkV4wopeiNEp0+pQ0InIw2CjJQXLEzjtehZ13s4phpkZDjpTvI1ChSNJWVEOzexpLdS5jxmFNPEavKM6GGagAwQgsPdu9jLOoc67d5ti6pwAG012sNekG/EEuqS9Qk5oboLWVBQZWTT/m6k8vXdcKmTZNh9nREKVyZWPrU3xd0vatiThD23zaFctmosrgCgJvS/eyAjRvdel2EaS2+akWTKqDESrjGeEwqdANBFV00M5faM1M9g90qMWxO6uHBFNtRXBFEX1c6vifDr5yskJRBWZVYcbDDt0nuURRlx4xlJc4pFgFahzRYSp8pIwvzMxVIO5Imm9lrDNHl4RgDDxLoul29EMYi911LwPJbpvpG3D/Sy8J9rcMqIl35hPE6fXIcYtPumLlT+yuDjmox4z6YxMmeOcVU+HR8WC8aUMsIVLgI0A2tVHnIgYIx7ux89Vqyw8YwEFRk4sBYdCWMx29u719PHGsXPCjhmSzl4RVdnUh7JyLy2alSGVPSNJH3oZxEHGe4BoIVp3DroXXXv5dS0eCpt7Nhc+kUoaFGorR2Wc88trgCBEqNkpNb1Z9MwjeuS8Da9aWrhkEkDGMqIvlgrsUFW9MxxAVeDQMMMAEAPR25UD5VEjbmFuz4ceQsHFGb0HEi59G5ZPSOphMtsGp2McApFkMsocgxX6d8XT5jvMUdlhJER89/zUUYAYCmnjGQN3XMFBPMlAoDWhLK5KoR4Ko0NblKKTcegnWM5Hc9bGTlzaj1CIf0ekcvvYxRkBB48I1Vt7MfjXJhmxOXDPaZqjfAeA2g1Mry0yuaxUC+3/PaBnvx39k6wy6YJKMCG/8Jh1ZjM9/TucU864VPHXEs5eFmfZFPZqkraQFVknDVd20W9uvNofsfC9dOAHqZJBmuYbyoXprBaI9nIiKGmJVJpT6XveVBlZIu1dwe3GQghASmm/93D/eg5TGPTm8ax+irAeUZ0ZSQ+wCbZrPNM02wAQHcemxzAYW6h5A0JVKiELdKDLpVcQxmhYZoEU3ncpPYmuXsryI3dOatIV0bi5msTd1JyWOaSP2Rk8aRaBBUZR/tj2cOR+rMkpwtTRiRJwgdmasUYX9nu3mAPgI1dTsU8V4ClqIkG8K2PLdaOJVlApp5PGNdkhBU9c5tN076ETbi8Z2Qk6Y2M7Dk26P+i7DdoipiekleIMnJKSxUqQyoG4yn/1RGbME2EDAPvPoYOjoyMpEbQMdjh+mN96VFDd7kpmlmhm/hcFgDjcfZMjYy8vtPjpEVBF/LhHqbQxELuqtICWdJHeUhmz4ixY/OmjNC27vuOD+E432GXS1usVuKQqLcgrzCNV2XEMLAyz4g1kwYA1IiWTq7PKWpsIHc2DQA0zQEAdHMp6G7Dv4BDjxrOM1IfGEFCn+9GUjF3CzatmUKb/pE0ZBqmcVH0jJ9VA3BBRvRznbD4u3KHafwhI+GAwkKib+7O4uPQCaqUiudV8IzH+bO1nlkvve8uJGccg+EZyXeTCABR2rXbpe+xmBjXZISWg3e9Yw5VAq0LAJiVkZjLTpPtdVrvjVgy7T61sFwIUEe8dpzxZNroq+LxpldkiT3krooKeYENGWnvXgskhnA4aj7O3Vz9glyY5UdGDc2Y0c+hqldJJB7DFgBw9ixt0nprb7fZpOgWlIz0aAWlRkgAkocJlPbI2X1swDn1kSmNaSTTxHOBN4qaaICRwQ18BpGsgujf0RYYBDwWegIMMtI9lHDXSdpSZySWTKFWcqi+CgCBsGkRVmMDLLSRdZ7RyUgPR6A9kZEsYZqQlECDEkOSE8H4/i+OsCojAFSifUhWYqVXCOW/L8ApI47vrWoBAMQtap2jB4RWYNWPj5aqz5eMAMBZemXUrGTEThnJgwgAwHmnNEGWtFL0tv2YnKDflwFSICGyKH/lxPgmI17DNADQdioAizLiMkyjyBKrGTHqG+bRhTRhkBEjhcz9TpTidD0jxHNsNBdsPCOtXa8CADqi5uP0UmuELoYHu4fzW/yBDHUpkMpPTgU0E3B7bQTxZBpv7MpDHaGZYDoZ6SK1qIx4q4tQEVSQSBHnHjX0edI9MhWS/lzkQb6WTLapiClJSCvaOCaqeohGDRvE2QUqQyrq9RR7VyZWWgm1rwNIxjCSyEFG1LBpEVZi/aw6ZlYy0r4EkGR0101hv3KruAIGGdl9lCsuyHlG6pRhJLi+MIMJF2Zy6hlJU2WEQKa9d7KREf29fB+aADfFOp6HNi1kYCUjOZUR3Rge1VPo8zWwAsBZM7Tr/ebu4zm9LXI6kbdaTFEbDbLeOC9sPeL+jYpRQybfMA3/ORBhmvLCc28aAGiYCcBsYM1n0hj1vhFWblibsGPJdEG7gNN1c9ia3ScK74bLg8vg0MgIQVPnKwCAQ5J2XSdVTQIADCXdlwFvqAyhLhoAIQUYjlVKRoYAQlhnTSmPSUOSJFwwpxkA8IJXSRfgindp1/Moal1n0tDvn9miHfd2p2Jw+kJF9EXB2LHlQUb0+8VKXtP65DlB0c2reSwCk6iJ1Y1vpH46EG3Udo6HN5nDNHYG1kDEtAirsb7c2TQAUD8NuPkN9Cz6FPuVl3llUn0UQUVTXdkOmyMjNYoRpgGAgYSLe9qijKgAFN0HlTVMAwBqCGn96ySAZeEAWYiMvtFzTUZoKrDeJyyqqzaFKCOnT65DUJFxpC9m36wRYM+Sko6jQdLvQ5eNOO1w8fxWAMBfNh3O8UoOnB+oRtHvk3zUGa6pYbkxrsmI5669ALDkcyCTl+N40NiNeTOaOfSRGG2gu3p9QoybUnvzS2MLB2Qc6hnOzJIoBFydkVgyhZnSIYSHOpBQwzie0L5nes10AN5kb4Brz57vtWIeBwIkY4yMyJE8djAALpirkZEXt3Z5J3SqWT04SmpdlYLnQUNXjr4fSu51MlJRQA0GSl7fPtBjSntM611c22RvDeV4TPTiG5EkYPJZ2s8H3sRQPJndwKqGkeDWUjU2ANlNBgoANM/FiZRxj7pVXAFNdZ1mVV0DRpimRho2HZcXZSSpL+4yIVBlTU3LuYFTw0jqpEyFzM5B1vfqykjCzEWyFD3TwzTDWkglYmlSmA/CAQVnTNOu68vbHMzitC0BSaBR0hW6iqa8v/Njp06AJGlZPK69TLS6rhRHjexHmEaQkbLCc2ovAISrMfTZ/8YwN7F4WeTo7rLglvDFBgsx6GGaVNpcdtgjIkEF5+i+h+fec1/zIycsnWJnSJpJtatFi8EH5SDaKrQsKO9kRBtn3iZWvk9EchghvZS+kmd8efn0BkSDCjr7RvCu1xRfS5G6LlLrqkkej1N034hjmXz6POm7ZrZjyyNMM6OpAk1VIcSSaVOoJqmHadqgLUCD0XrP15Vm1Liuwjppmfb//W9iMJZCI/QFyK6ZnUUZUQBm+nQzz/TEetjPXpQ8gDOx0vtVV+ZCiOtkhFNGXPTTYkZU3YCtAJD1ejG0mJnze0MsXKVCgsL9yZGU1U4GAMT046R1oJzDNLrhVZ+jojRsU4AyAgDnn6KR/lXbHcgIV3G7TdJJcQFkpKU6jBV6eOjJTYfcvYlXRvJM7QWQkbpeToxrMpJXmAaZD7IXZYTWUHi/s390Z9SoFjKSTBeUUw8AF83TDGr/+66H2Ggu8AbWRBrNkrZwdVVou5umaBMq9FRaV6Y9DlQZybtHjRJg6b2p2BCiRPt+NeLdcwNou7az9VTAF7bm576nOEpqPIVpAGAWC9M4KSN6W3N98aqRaSn4/NIez5mlpz3uMBaFpKQtBM3kGBIAzpcP4dyHz80dNuAwlaUpu7wfqDKy/00MxBJol3TPTu2kzNeqYZbSKuvaq0zPixsyoqddA97CNICNiZXrTVMlDTGlAsjPM6Lyykg6tzKSYsqIeaFxPA/6eaNhmkqdxDqTEZ0Y6cOKqNp1LcQzAgAfnKMRizd3H7fvI8almFNSjMrmgr7z46e2AwAe33jInepJWyMgiWoWNsxjXhFhmtEByry9St7WvHcvk8a0xgqEAzKG4ilnI+BoQMDqGUkVlFMPABfObYEqS9ja0Ycth3pzv8ENLMpIq75TORLWJrLmaDMiOrHKN0zjR0ZNbHiAhbkC0fzICACsnKsRuhfe90joLP2TulDnqkkej1N0MrLn2KB911vVvMuqkkfwZGUFbj32qqdy/BTnnaItCq9yNRiSsvYdTelj6FYUjIBgJDViUhRyYVqj0UnaFdoWa6Ry+ARq450GGamZmPnaQIR1rVJ1D41CvRe5wjQAumOGCpQ3GaHKSMDoTVOFIVP4w51nxBKmASDT0IgHZYSqIoo+32Yljjc8i4R+vqoC2v3mSC7011HFJxrQxl+oMjKjqZKZxVfvssmqUQwyotDGlwV4RgDgkgWtCKkydh0ddKd6MmUkjhpSgG9FhGlGB1iYxm2dER3WioBeY7tz9M6knqX2UoJLS02nCRIpYri281RG6iuCuGSBZtb6/Zp9fhxlhjLSSpWRgDZh8GTEq+xNPRJ7jw3m7uTpBH1BiI0MsuwSNU/PCAB8UDexbj7Yiy4vXZAtIYWjpMazZ2RCTRiVIRXJNLEvfmbxGVVLw/h2UwNeHtyHn6z7iafvAsAKQr3X0Ycj+ljjkkag6lNHTU6vEyPum41Rb8XB7mFWKC8r1BDQqBUlWyFvQVhKgEACqm3ICKeMqPq9KeuLl5tNT/cIR0Y8zCuAQZ63d/Vr38V8BQlUkgFTmMadMqKHaWg1WQIotPZITgOr4Rmh5lVXYfEpyxHXN0I5lZHmuQDAvieqKwOFkhFJkpg6ssrONyLLRkFDAGlJ9VQF2A7V4QDbaDy+0UWoRr+2FdIIKoh+Le3ChrnAh2n8TCzIA+OajHju2qvDSka8hGkAYP4EvfeGtRHYaALLphlBXF+IWZ2RPFJ7KT57lpa6+MTGw+ge9IGNW5SRFmiL0lE926k52oyoTqy8KiNtNWFUBBUk0wT73Er6VtCqkkODTE6V8wzTAEBTVQiL9ZotjjFtO9RNASaczv55NA/PiCRJxoJnF6rRSZ+kq2mVXKO8F/a/4Om7AKCxMsRSwp9+R/MCDaU0MlKV6kGc2+kfH3HfbKyxMoiqkApCgP1ur2vrQgDAh+QN2r+rWu2bRQYinCKgkxEa7sihjBBCTMrIcMK7kkc7Hh/pi4Hv2luV7jNVRPUWptGL9oFA0X+X28AaQop6RvT5VdGf1Vzngc6vlYEcZKR1IRCuYYpPJKKZmQslI4DhG3lpm4NZnFNH4uEGT40vnfCJ07RQzRMbD9krjzz0eYV5ViQ5P0LEekYR1raiXBjXZMRz114dhYRpAGDehDGkjCSGWTGxQtplU5w5rR7z2qoxnEjht6/tKfQoGRlJpVJIpQlTRo5Am5Baoi15h2kkScKMQnvU6OcxPjLINVirze+zdJyreynetJOQs+G0v2M/duWRTQPkMLHqyoikn+cKyTjfPbEez94sAPjIogkAgL9u1shIX9KwQvI7fS81ZCRJwlRdHXFM37RCL3b4IWW99hk1Nn4RwKQIBPTjc7uADyYGTZkgwylv92tGx2P9e8OII5rqA79Ee0ntpcckE0BRaLn7XGEaTiFKu1dGCCFsfq3SKxU7kgtZAdqXGGGaaGP213vAipkNCCoyDnYP2zc25YhoKlJYiIbi/NlNaK4K4fhgHH/LVXNE//5WffOFSL3RNdsLOP9LuUM145uMeK3AqqOQMA0ALJig7YzfOdjjb80NP8FVYI0n05BQWGovhSRJ+MpKrWX6A6/vKVwd0Se4RErbbTEDqz6RmzwjHneaADCz0B41+gKdHBngyojbpIR6wHK9T80bu7IUZrLDwk8B4VockZtxDN4NrIDhG9lhR870scr68xAlw2hLGovW9u7tnr/vskVtkCSt+NmhnmF0x40piycjx4e9ETMaqsnahZhHywLzv+38IoBm3GTKiJ4VwsId2ecZaxjR6yYHAAsBb+3sY9cjhIRGRvJURmh2lAICRf9MV8qI/qOiv1aRchdM48kYNZ5nVZ5rpzDSEwnVsmPzYmi2QzSoYplejXXVNhuzOKeMFJJJw0NVZFy5VLuvHn7rQI4XW5SRfEI0gHkcZc6oGddkJN9smgwy4nHSmNtWjZAqo3sogT1uJ8NSg2bTpOKIJxKowAhkatbKp9Ifh4vmtWBuWzUG4yn8Ye3+wo5Tv4aJZBJRjKBa3413xTWDLB+m8eoZAYCZLf6QkfRAl2F2s+tp4gGnT6lDUJXR2Tfi7f4J1wBf3ojPhe5BCkpeysisbIXP9LEqqREAhGUPUWw+utnz97VUh7FsmrYoPLx2P3p4MsJlh3gJ0wAGGXF9/vQwDYNdJg0ABLj6GvrlVlySEeuimxcZadOuz/sd/UbRMymOSNIcpvGS2pvSVRCVAIpOEFx5RpgyojeKdJFVxKvOVBnJSkY+8GUkdP9GlGtA6UuoZrae4mvjGyGcMiIXmEnD49NLtfvq1R1HcTBbUT7ODwSgADKiApWaVwUH1uT3GT5hXJORvMrBI/Ph8OoZCaoyFrZr6oip98ZoAlcjIzEyhFoaYlDD5voZeUCSJNx4zjQAwENv7M0dH836Ydo1TCZTLJOGBKvQpcv2zZH8s2kAQxnZUSAZkfu1MEMMwYLPXzigsHLpb3gN1UTr0RHTJjKvnhEAmM1l1PDFyAAYYyUpBJBClAyCf0U+GTUAcNUZ2gT98xd3YpgYiwCfHeJVGZne5DFMU9GIgeqZxr8dwzS8Z0QPT9AF3KVXgiKf+3UuKx3QZ6pFEUr0FlD0TCcTIFCC7sYCNQSqcWjnQTKqt2Z5L38OqDKSNVW3fjqSs1YCAHvOAb/IiKZ4rN1zAoMxc1gqXW1cf7WmpeDvopjSUIEVMxpACPDouoPOL7Sk6udT/I9h4ZXa/zf+Lv/P8AGCjCCPbBqdvdOHJZ8dzOkO5a5HDbibPREbRC30hSRSj1g6joP9WR4UF/jIoglorgqhqz+GZ7a476abAaaMpNCih2j6qlsZQWyKNiGq5mdgBcxVWNP51IWhasGANsZB2XsBMDvQIkm2qYdZQAhB37A2Udd46E1D0VIdQkNFEKk0ySzcR31GAGowiABJmHbj+ShTAHDpgjZU6ypODMYx82XDvSojUxs8KiMA1i7+f8Y/6qbZvyjAKwLavCLrHqtcm55Cw7+AUcdoZ9cAhoh2riKII5joNSlJrjwjCg3T0DojgKJnuOQmI2GkJE4hijawvjZZlRFael5SEdbnoFybPRp+8puMTG+swOT6KOKpdAbp71l8I/tZtTMyFwBKvh9dd8C5FhXv9QDyV0YA4NRrtP9vfxYYzLMruA8Y12SE1hnJN0xTHdQe/HwmjdP0jIgNfnex9QuyzCaj+PAg6mhzsGg97nj1Dlz62KXY0b0j748PqjKuWaZVXPxjIaEaqoykkmiBdi77qzRDWVgJI6yGC1JGJus9P0YSaW9dNSn07w4MaYa0ISV/vw2PFTN1MrL7uCeSNBhPgb68Og8yIkkS5uuq3pbDlloxShDQn6kWXaXiC215LTpHEQ4o+Ds9C2sEnDLC9bzxqoxQA+vR/hgGYu6yCA5E5uK6+DfwbN01wIwP2r9IjTBFQKXGTz37LNcCbl1087lfW6rDaK+NIE2Ad49onxeSEpBJKm/PSFK/boqsMM+IKzJCfyQEqGxhm7+syoi+0QsoAQT10v9WkmYF9ZkElSBUSSOthRY+A/QUX10decniG+lqM66/1Lao4O/icfH8VtRGAzjcO2Iq+GdChjJSABlpma/1BUqngL2v5f85BWJckxH6cADeQjX04WAxzTyMP0umasrItiP9ONpf/lK8ttAnnvjIIOpgdCrd3bMbALCrZ1dBH//ppZMgS8Cbu09gd76FxRgZSbFslbg++Qf0tDWejHglnqois4ya9/Mp4U9NhMMaGRlW/FFGFk2sRTSo4MRgHNucKqLagKoiQUVGSM3v8V+gZ4NtOWTJBpMkpo5QlcoPZQQAvrJyFuorgogRThnhjNReyUhNJIDGSm2xc2tiHYgl8Up6MV5sv4k1BcxAgFME9AVR0T1Cue49Oq9Qo2c+ZAQwVNeX95qfqSSXbeGpUZ7+TzlYaXTtddEoj157BQAqm9m4slVvpSQiqAQRopuhHGSEqiABOcCeeT+UEcDwjby87ahpjegdSWH5yM/xk9AtwNyP+vJdFOGAwtJ8H1nrYGT1k4wAwEfuAW7bDMy/vLDPKQCCjOjwskjRHQyvjHj1nTRXhbGwvQaEAC/l04W1FGBkZAh1kr7gcb1AemOFVVGdUBthD/ufssVHs0Gf4JKJBKvjkdDj2nRnFeXCB/mE1Kj0/V4+qdj6d0dGNDISU/1RRgKKjDN1Y6cX30jfiDZJV0dUZuD2igW6MvKuVRkB2D1jS0byVEYAIKQq+Nvt5+HchVPZ7xJcVtKJkROeiSYN1bj1jVAFpSKb14ZTRhR9EZX0VG63ykiNTqbzuVcBYIlem+XPm8zzSoIjUJ6yaSi5ClYy5SGnMqJwnhFCgMpmV2FxqowE5SCCeoG1nGGalEFGVN2X4hcZOWt6A0Kq1uCT9431DSfQgQa8Wn2ZMzEtADRU87etR+w3q9YwTYEVYNG+hPUGKhfGNRnhJ2MvvhF681MyAng3sQJGae/nc+WUlwv6wpIYGTTISKSehaV644WXdL9yiZbK9uSmQwV5MtLxYVaULRHUfkcns7ASZiG5fHbnc/UMhfc68hivfnyRRA8AIBbIv+CZFTTFd/Uu93He/hFtiaj2WAqeB01Nf7+jP7MyrUUZ4ZesQpQRQKvgu+TDN2qGu0VXIbHwCva3FEl5Jscso8aujoQNqIkxq/FXCTAFgmXT6MqIW88InVcS6UReHWiXTNFIaudgGilizHEJbvM1mBjMvYGidUb0fyqhaiPU4kIZYQoRYFZGXHhGgopBRqx1nayg50iVVQRkf5WRSFDBWfpzxqf49hbgu3KDOa3VOHVSLZJpgsc22GzUFB89I6ME45qMyMgvTMOUkVBhZORCvSX8qzuOZri1RwX08EYyNoRaGJ4Rqox46QfihA/OaUZVWEVH7wje3OMxMwQAdBUkHR/glBFtQaQTkyRJBdUamVdIxVxL5kwi4I8yAgArZmi7oTW7TyDpslw9DdNUFTCJTqqPoCqsIp5KZ1Zi1evTNKMbBGA1N4DClBGG6jbgk78BrvhPJCy1PvhS6m4wrYmaWN2FCAdGXCgjkoSkvlAoIECoGrLqzmdBF90arsJxPvPK3LYqnTBJZo+NRQnOGQaiYRra+C9UDYWGaVx4RpiR1+oZyUJkKBkJyIH8wjQ+kxEAzDfyt62ZZCQf35VbXH2mpo488taBzPUpw8Baj+6Rbvx+6+8LVqzLhXFNRkzKiAeJl04aETXCZMF84rvzJ1RjWmMFRhJp/GldjiI35YC+sCRjQ8zAmg7X+RamAbT46EcWtQHQyiB7hk5GEBtijfzi+iQa5JrD5dufBjDCNAdODLNJyDUsZCRZQCl9K+ZNqEZ1WEV/LOm6mi8L0+RRY4RCkiSmjrxr9Y2wME0PrPTaVWjAA6wLTn/Cm6dnusdaIzRMk6s+S0rVFqgAAVDZwhZwt3VGKoOVTMnLZ15RFRkX6z2g+OyjhCUql/N60DAN/We4moVpvBQ905SRFnfKSDpTGclFyKgyElA4MuKDgZVipd5tfN3eEzg+oB1Ln05MayL5P0e58JFFE1ARVLD72GCGgTbDM1Ldjtteug13r70bd6+9u2jHVEyMbzKCPMlIyohrRhS9EVoeOxhJkvD3H5gKALj/9T35N2MrFnTJPR0fQp2e2huLGDv7vpg/5ewv19tnP/NOZ2btilygZCQ+wMrV00ZbdGICUFBGTW00iPZa7f3ve1VHLGQkFfSPjCiyxCRkt76RvuHCwzQAsKBdN7FafSNcmCZp8aTka8h0gnXH7KqQF4cZXHVdNyFCRkZ0ZWR/33589unP4qX9L5lel9S9SiohQFWr66w9Oh6aBQbkf87oM8UrI1ZymNPESsM01IgaqmXqRs7wkRo26q0QAlQ0QZZzZ9MwA6scdJ1NQ0mpKqtMTcknw9EJE+uiWNhegzQBK9NeSHq8W1SEVFyrZ5Hd9fT7JvUzHWnA1vQk7Es3o++jvwGqWrGhS+ublE8fqNGAcU1GeAOrF/BxzZC+e8jXbPapJZNQFw3gwIlhfPmPG7Gza8BdJ9FSgFaOjA+jVldGhrl0Sj88IwBwxtR6tNdG0B9L5u7JYAXroWMoIwn9mgQUY6IopAorYBST2uqVjKhmMkIK7EtjBa038oZL30jfsGFgLQTUxLrlkOUe0O+ZFqkb1rvYlzANh0KVkamNFQgoEgbjKVdp24MWMnL32rux6egmfPmlL5teR5URBQCq2lwpAoCxoQkqQUae851Xluv3BZ99lNCLsFFylFMZUVRAko1smkgtU4LdKCNG117kpYzQbMVcxfL4MI3b93jFxfM1deTZLZ0AuOeoQFKfC7ecPxO10QB2dA3g/teNXl7DKeDS+N04L/5TBBddYQrjtET9K8JWSuS1Gv/iF7/A1KlTEQ6HsWzZMqxdu9bxtb/+9a9xzjnnoK6uDnV1dVi5cmXW15cS+WbT8A9MoUw8ElTwk08vRkCR8MyWTqy852XM+c6zuPwXr+OZdwooBuYHApSMDLHU3mEuM8Wv2KQsS7j8NK0hmudQjV6ESUoMGsqIXoTIL2UEKMA3YlFGSIF9aaxYMVPzjby194SrSrZGmKZQZUQjI+919JkLM+n3R5PUm6GMFGpgtcJKRgbj3sJAAUVm6khGATcb9FuyaZwWvIROgjVlpMWVIgAYZCSkhAomI4os4YWvnoemOkOJo2SEet1cpfeSNNK0+27dNEMZcdEoL+XkGXFRgTWgBJiRN9emhzew0rH5pdpSXKKHvV7feRx9I4miG1gpaqIBfPOSOQCAH//vdnafauRZQkVQQUiVTY0im6L+9MopNTyTkUceeQS333477rzzTmzYsAGLFy/GxRdfjK4u+/TUVatW4eqrr8ZLL72E1atXY9KkSbjoootw6FAe/gCfkW82DX1g/Jg0AOCCOS146IYzsWJGA4KqDEKATQd6cPPvN+CuZ7bm/bkFQ19YSMJQRkaCxuLqh4GVgubVr9p2lMVlXUE3q8q8MqIvBlTmBcCqsOa7O2fpvZ7JSNT0T6nAvjRWzGquRGNlECOJNDYd6Mn5ehamKXASndZQgYqggpFEGrv4GjEc+UpaPApDySFfG0NmhGncLK4WzG7VdtJuarVYlRG6C7cipYcOFQCom+a6IScNUYSUEMJKYWEaQAtDVfZqzQlTANI6GakLaYTYrYeHKRw1k4xmd27qjNAfJRWI1HnLppGDBmmKD2T9Pl4ZoQTGb2VkZnMVZjRVIJ5K46X3u7gU+eKSEUBL871gTjPiqTRu/9MmxJNpVmZgbls1JEkyFaDMFdYarfBMRu655x7ceOONuOGGGzBv3jz86le/QjQaxf3332/7+t///vf40pe+hFNPPRVz5szBb37zG6TTabzwQvnjWvlm0/BhmsqAtrMq9OZfMbMRf7jxLGz74SVYfccFuPn8GQCA/3h5Nx55q8BmcvlCl9zVeD9Lmx1WjYevL9bn2+Iys7kKC9trkEwTPOVFEdIXezk5hGq9qzAlI3yYpmBlRCcj2zsHvHl7AmajmRKtzev7nSBJvG8kd6jGDwMroKlZ83UT6+aD3M6VGy9ffRXQFqF8vFVOyAjT5PEMUjKSkRVkA5oWXaWfOz6bjl8AkrMvBQCorYuBxVd7DtME5AAqdcXPa+jJCYmoUYeiVu9u64qMXPqvSFZo95ciK67HYip61jIfkGVPykhQCaJG91cRkKxE06SM6GSkL+6vMgIY6sj/vtuJ7qHSKCOA9ozf/cmFqIsG8O7hPvzshR2sxs98XbHd0WOQEb+JWKngiYzE43GsX78eK1euND5AlrFy5UqsXr3a1WcMDQ0hkUigvt65sU8sFkNfX5/pv2Kg0KJnQcVg737dAJIkoa0mgm9cMgdf/dApAIDvPvku9h/3V+J2BX2XWxnTVK80ZAzLxiKWJElfpffLdXXksQ0eVDN90g7Ge1gHy4SiHSOvjEQChZGRiXURVIW0dNZdXqrFcsrIEAmB1E7N6/uzgab4vrEzt4nVzx3doomUjPQYv+TGS5WREFcTwc+MGl+UEb3xX64wzUgihaG4tojWVWSGAbuGDGU4pXdBVZvmAMGoUezLJRkJKSGmuhQcbrj0X7Vmcp99jP2qVvctuTL8LvsiktVaCFWVjX4xOc918zymEKltiwHAm2dEDiKgBNgmIltI2KSMhIpIRuZrWX9Pv9PJunjThovFRnNVGP/yCa1z9C9X7cTv3tQ2qDR8zCsj44KMHDt2DKlUCi0tZoNMS0sLOjs7XX3GN77xDUyYMMFEaKy46667UFNTw/6bNMmhQ2aBKDS1NygHi8rEb/ngTKyY0YBYMo07/7LFV4nbFfQFvCahmUoTwWoMp807Wz9z2j+2eAIUWcKmAz3uG5jpYZpoTOvhkIaEuD7584sFDdPkuxjKssRMrBnprNnAhS3WpU9BOFxYx147nDNLIyPr93fnDHH5lU0DAIv0/kpvm5QRY3wpXRkJyIGCUqudQBchSjq9ZtMAhjKy6+hAVs/N8UHqZZBY0TOe2PJkhPopqNnTLRnhw7++hRuWfRH48kYk6ozqmp6UEZgX+wmVGjHJ2SgzWo/k8lsAgHXr9eoZAYyaK9nmV5bay4Vp/PaMAFoGGW2cCQCnTa5FW43/z7MTLl3Yhk+c1o40AYb1rEOqTnbHjBo744KMFIq7774bDz/8MB5//HGEw2HH191xxx3o7e1l/x04ULwaHPQBIfAepuF3MMUoNCPLEn54+QIEFAkvbTuK/33XHeHzDfoCMjmu9aAZrpiUoSz46RtpqgrhbN2Q6drIqu++qHoTVyqQIEbdAQo6ARdynRbqSsDGAx6Ka3HZNKvT8xEJ+F86elJ9FAvaq5FKEzz/XvZsJL4cfKFYrJ+PrYf7jIXcRhlRZbVgz44d6CJUF9Y8EPkoI+21EdREAkikSNZQzYkB7ZmvrwiyTQz/LBwZMs47PS5aX8TNIgyYFVemjPi0yaGEQpEU9tluzxe/2E+q0jaGHYMdOdN7U/qcSkmZm940fHIAYFSjdXpuU+kUO6/FDtNIkoRrzjRI3aV62KaU+N7H5iMaNOaQWS0aOeLrqoykRsakb8QTGWlsbISiKDhyxDzhHTlyBK2t2S/Mj3/8Y9x999147rnnsGhR9i6HoVAI1dXVpv+KBbfmMh52ju9isdEZTZX44rmaf+T7//NeaSu16qpDNdEe7JG6UzLIiN8k7IrTtVDNE5sOuVOCAhoZCRBtIo+rlaYqjhR0h1UIeTpDb264bq8XMmKEKFan5yESLA7/v3SBLiFvyU5Y/UxJnFwfRW00gHgqzcIcKS4kwzwDksJSq/2sNUKvc31YC/nmo4xIksTi7ra9dnQcH9Tur/oKY3yOygj1MEiWRbgcyogOXt2o0J+ZfJSR5mgzgnIQKZJCx2B2bxdTiCT3yghfZwTIrYzwWT0mZaQIZAQAPnm6UfWXPnOlRE0kgD99cTmqwyounNOMkKr35rJkN41FdcTTzBgMBrFkyRKT+ZSaUZcvX+74vn/913/FD3/4Qzz77LNYunRp/kdbBNBdTr5Fz4p98wPArRfMxKT6CDp6R/DLVTuL9j0ZaJ5n+meifnYmGfGp1gjFh+a1IBpUsO/4EDbs78n9hqA5ZpsMVBvyPVeB1Q9lZOlUbdHbdqQfvUMuKzxWNIHoO9F3yDREg8Wp2Eh3aW/sPIZjDqEaQgirHOmHZ0SSJCyaWAvAUIviMm9g1VAsZYReZ0pG8jV7Go3/nJ/hE3qYpqHCuKf4sdgpI1QRYHNMjow9XhXwe17hm8lR071XZUSVVciSjIlV2oJ8oD+7Yp2hEMm5N368gRUAM7E6Pbe8OmNK7S3SfFwTDeCv/+dsPPKFszCpPpr7DUXAgvYarPnWSvz6OmMttVacPenJCADcfvvt+PWvf42HHnoIW7duxc0334zBwUHccMMNAIDrrrsOd9xxB3v9j370I3znO9/B/fffj6lTp6KzsxOdnZ0YGMizZbzPYGGaPLJpTEazIpKRcEDBty/TiMGvX91TOjPrpDMBzuSbapqbkcLsd2w2GlSZa/3xjS46+VrISCpYlbG7AgwywsdWvaKxMoTpjRUgBFi//4S7NwXCGLppLU4d+Q+koBTNfT+9qRKLJ2rZSE4hroFYktUE8atY09IpZrUoIRnKQaJK2zmqsmrsxpP+G1ipITNfPxBVRjIKuHGgZKSeIyOmMM2gQUb4sAFgLKy5lJtiGuP5kumFKCMAWKgml2+EpuNSZaha78uUjcRQQka/i54HJzLCL8LFTO3lsaC9Bsuml7cxXSSoQJa5Jog+ZJaVG57JyFVXXYUf//jH+O53v4tTTz0VmzZtwrPPPstMrfv370dHhyHf3XfffYjH4/jUpz6FtrY29t+Pf/xj/0ZRANy0tbaimJOGEy6a14KzZzYinkzj/z31XlG/iyFUBTTOZv+UW+YVPUwDGDVH/rq5I3chLwsZSQcNZcTkGdEXrEKP9wxdHVmz2yUZAdAr16EHVVBlyRTv9RtXLtUWiUfXHbQl10f6tPu2Kqwi4tNxLNVDV2/tPQFCCOIcGUk3aOFFVVZZNlNRlZE8n0FqAtza0W8u4MbheA4yYhum0cnI7LrZUCUVHYMdWRfwYm5yWMl0SWXKiGsykrInI7mUEUrK6PvOmXgOgOzlyvlzABjKSK4wjSzJUGTFlIVUasN/yRMMOIxLMgIAt956K/bt24dYLIY1a9Zg2bJl7G+rVq3Cgw8+yP69d+9eEEIy/vve975X6LH7inwrsJYiTANoUu+dH50HRZbw3HtH8NoO923jCwGpMHYAobr2ohpYKVbMaERLdQg9Qwm8kKs8vKWoGAlXm8JoFFQZKfR4V8yk7cSPun4PX61RslQl9RMfXTwBIVXGtiP9eMdml3+kT1O1WqudzeNeceqkWqiyhI7eERzqGUaMIyPJuqkAtAWQhWl8zKahz2EhnhEAmNaoFXAbTqTwfqf9c0yzlExhGm4sJ0YMcsrCE7oiUBmsxKImzSe3usO5BIJpk1MszwinjLg9X1ZylW+Y5rxJ50GVVezs2YndPbuzHiczsLpURqgvhZ63JEn63gspGw72H8SFj16I/3j7P0r2nTwKbY0wGjCue9MAXK0RD6SWDwMUM5XMilktVbhuudY46fv/825JGuslFl0LANiXbkYkpLIHnO52iqGMKLLEjGIPv5Ujk8qijEiRWntlhEtnLKSj5/mnNEORJWw70o8DJ9wtrCUrHR0JsBCXXRfojl6djNT4R0aiQRXzdc/FW3tP4ETcUFySejpp0Twj+nWkFUXj6XheWQSKLDE/kJPixcI0lZwykjAWOxMZsaT2AsDyCZqnbvVhZzJiq4z4NK/woRZaUM1zmEbxFqaxkrLqYDXOajsLAPDywZdt32P1jOTa7PHhJ8DcSb3YG0Qe//Xef+Ho8FHcu+nekn0nD5ZZpj8L40YZOZnAsmnyCNMUw/WeC7etPAX1FUHs6BrAQ2/sLfr3DZ7ySXwh/n9xdfzbiAYURkZoMya/DawUn9ZDDq/sOIrD2ZqYyYqpnTapmZIRdwa00t2UeBaijtREA8wn8eL79i0QrOhlzemKX63xyiXaefvLpsMZHZCpMtLiozICAMumaQv5GzuPo6PfMBQma7RjUWSl4EaFdqATcC3XfDCf9F4ArIrtm7vtC8cdtxhYk+kku8/o99KFlHol7MjI2k7nvly22TQ+7XB5dYMpIy7OVSqdYmUP6PPUHG0GAFM/FNv3kszzMK9B874dGrD3NfHqEGBk0zgqI1zHXkBTkHOlAxcDlGwDLkrlFwF+hSzLiXFPRvLKpqGLnWJU/Iun4wX1p3GLmkgAX79Y83H8+LltrBJgsTCUTOO59Bk4pjRDVWRGRlortB14sRShqY0VWD69AYRoHois4EI1csPUjBg3oClgdJIqNFRz4VxtMnZb96UU7cYpVsxoQHttBH0jSfx1szn1slNXRtp8VEYA4NxZWmOul7cfxaFerix6VJsYVVn1rW0CD/ochpUwWwzyDdWcNV1XRvacQNrGN2IYWLUwlF0IoHtEM/FaU3sBYFrNNADaAulUEp8vB0/nleHkcEFKHoVJGfHgGeHlf7rgN4Q14tYd68668FrDOwDQGNHqCB0ftid9dA6lvXlyKSNWc62b9xQDlDQBQOdQietBwVAJ6yOCjIxZeM2mSZM0e8hCSghRNcpkyFLd/FctnYRzZjViJJHGl/+4EcPx4jHx4bg2Vmp4pJNFW4WWKVHM3cdVZ2g76z+tO+BoLAQAwoVq1IbpGYWTKPzyjdD6Aqt3H0dHb+64dKnCNIBWKO/as7TwyAOv7zHd151FUkaWTq1DJKCgqz+G3+xtxm+Tl+L1hf+MlK42qpLKCpP1jPT49r2mdNUCe7ksaK9BRVBB73DCthkiX/QMMMiIIilscaahGhqmoV4JAKgKVDFyQkmLFbwyUhmohKRXsPVjXuHPFQ0BxVKxnBsonozQBb8uXAcJEtIknTU7jSojdH4EDDLipKrwqjPA1Rlx2PTYEZ5ip/fage/avq9vX8m+l8KqjJRy7H5BkBGXpZop+Jh0UNGqMdKHu1RsVJYl/NunFqOhIoj3Ovrwj/+9OetiXQhoPw6aBWJVRophYKW4ZEErqsMqDvUM4/WdzpIw4a5JpHmGrTIC+EdGJtVHcebUehCihUNyoZTKCABcfcZkhAMy3j3chzV7DC8DVUb8NLACWur58hnagnyoL44fJj8LLP6MaaHwI7XaCp50VgX0qqJ5KiMBRcYKvfrvcxbFK5ZMoV8vNthgISMRNcJ2oxnKCLdASpLEwklOZCSWNhZiWZIZwfKFjHDhjMpAJXs2eK+LHax1POj/Kbl0Ujj499opI05khC7qtAcOf9/YbRj5LCEKloFTAh8fBe8f2t9X+sam9FwLMjKGQXcfbj0jvMRKd96lqDViRWtNGPdeczoUWcL/vH0YX/3TpgyPgB8YjGmfGbGQEd4zUqyUtnBAYWm+j9gYMimkQWNiC1dU2RY9A/wjI4DR1O/P6+3TaHkYnpHiFDyzoq4iyAzA975oFMmjyoifBlaKC+Y0m/49tbHCtBjRSdJpIc4HvETvR4XdDy/UCLa1iu2RXupjkBmhNJGRkDa2EzFtYbfW16CgC3guZcRq3vRjk8ObUCVJYtcjFxnhy8jzjUXp+4+P5CYjJmUk3Jj1fbGkdq5pmIZ+TyKdsFW9rKnAgHGec43NT/BeqHIqI00RLWTqpwJZKox7MuI1TEMvugQpI52s1HG65TMa8LPPnAZFlvDEpsP4+L2vY+N+/yZ7ABhOaBNK1BKmocpIMl3cFLpP66Ga597tZHF7KySuvLQkSbbl4IHcZjgv+MjiNkSDCnZ0DWC1g+mRopRhGoqbzpsBVZbw2s5jWLf3BBKpNKvMWgwy8vFTJ5j+3VYdNi1GuVSBfMAUMCWAhog5VJIPLpzbgoAiYWfXAHZwfWp2H9PUlqmNUVZoimYFRdSIsbAPm8M01vvPSlqssC6sfnof+P4yAFyfL+v7KHJ5PwB7Ayv93uHksG1mFVVGQnobhbAaZoZbu++yC8kWg/jmAj+WUpMRQghbl6i5uJREzC+MezLi1cDKxzTpe8vh3qa4bFEbHrzhDDRWBrHtSD+uuO8NfPfJLawhWqHo18uHV1o6ldaF64qa3ksxf0INFrbXIJEieGyDi4qsyKxVQMEkXx8mqepwgKk2ubKaykFGJtVHceVSTR354VNb0dk7AkK0rrP10WCOd3tHVTjAugcDWiiRT3GlKYdOcns+4LOm2E49y+KYC9XhADPj/nm9ca/RDtLTGg1vEn0OooGooXjoISimjMhmZYQSMrtdazKdZIu3VXH1VRnRn1m358uarUJBSUVWMmKTVRQNRJnZ2C5UYzWwAoZh1u67rNk3AFyrPn6CV0b295c2TMP3paFkpJREzC+MezLitQKrtcU14K/8nw/OmdWEZ287F1ec1g5CgP9avQ8rf/IyntrcUfDEf1w37jVUmrMIImrEF2ncDag6kiskslfWXkcXKesEyhYDn473uuVTAQDPv3cka1ZTOcgIAPzflaegIqjg7QM9uP5+LaV0RlOlqYy0n/jJpxfj3FOa8JMrFwMwL0Z0wU6kE3mXbbeC37X7tQBdrXdl/dO6AyzsaZARo308/xxYwy922TSAUQPC7hitXjTAn+aOFI5kJEuYBcisvkpBwy3Z0nv5EA8PSmTs3kvJRZhL12fEx+ZY7cI0ZSEjnDLCV+MtBfhsKxo+PxE7UdaKsPlAkBF4C9PY3fxudgnFRmNlCPdcdSr+8A/LML2xAl39Mdzyhw340u83FKSS0G6ljbpxjzeYseZzRao1QvGxRRMQVGW832lfWXTTeb/F2vRs/Kj62wAyO39S5DLPecXs1iqsnNuCNAHufXGH4+tKWWeER3N1GP/3Q6cAAHbrC+rnVkwt3vdVhfFff38mPrlEU2T4RTmiRthu1y8TK++xsGa05IsPzmlGe20E3UMJlhpNych0ThmhO2E+TEMXS7tsGoALH9iM3+RF0+9bP9QeClap1JKemzNMY1PADchOEChYNo3lPGR7DlmYhp9fsygjdpvDcntGnEJQxYKdMpJMJ8dcFdZxT0a8hmnsSo273WWUAitmNuLpr5yD21bOQkCR8MyWTnz0569lbQKWDVZlxK4wU7HDUzXRAC6er3lU7GqO7K9fgU/H70R3VKtOa1eBFTDMXUeH3Zdyz4XbVs4CADz59mG8faDH9jW9w9pkwSsjvbFe3LPuHuzsLm4X5r//wDScP1sbd3NVCJ84vb2o38fDmk2Ry8DpBal0ytT7hGa0FLpwK7KEvztLu4/uW7UTqTQxlJEmLkyjZ09E1WiGR8Gu9gWArOnNlIyossoW72wKglc4KSM5DaxOyogLz0guv4l1XMl0kr3HFKbJQnxY2FzOJC+lJCNW35yfc0wu8MpIRaCChcHGWqhm3JMRr6m9VoMV4N4MViqEAwpuW3kK/nzTCrTXRrDv+BCu/NVqvLLd+wNyjJGRIBLpBFsAQkrIV0NoLlyp77af3HQoI2toKGb2teRSRvxUsBa01+DyUyeAEOAb/705o7EfIcQ2tfcn636CB959AFc/dbVvx2IHWZbwi2tOx/+5YCbuveZ0hNTiNeqzwqoQ+BnO5HeDQSXoqzT/d2dNRk0kgF1HB/HYhoM4pFcAtvOM2IVpaHoxLS5GQcOE2cI0toqAD5scvlAjwM1Zw+6UESuxp8d2bMSZKNnVGTG910JGeHXIFKbJoozY+cN4ZaRUoQqrEuKX+uoGvK+Hz5QSZGSMgab2EpfNaVhMk2PufsqpfmLxpFo89eWzcc6sRgwnUviHh9bhjV3eHhIapmmoCJni2jwZNloOrQAAK35JREFUKUVK8wdmNmJCTRh9I0k8/565ed5AjGb8aGTEqegZJSMnRk5kNJYqBN/5yDzURQN4v7Mf33r8HdMEGEumEdd7CPFkZEPXBgDmYknFQkVIxVcvmo0z9bLtpYJVGfGTMPD3YkAO+LobrgoH8PmztYqpX//zZhACVIVU2yZ5ETWSsbgyMhI0kxGaTWMXprEjI+x+zUEY3MApZdatZ8Tqf3ETmrY2yqNwUkb4Amy2YfAsyogdGfHTn5QL9H6g9W7KQUa8+oFGG8Y9GfGa2ksfGLsdzGhRRnjURoP47fVn4KJ5LYin0vjif63He4fdkwcapmmsDGZMFn5mp+SCIkvMi2BtAkcLs1VQZSSLTE53aX5M8BQNlSH89DOnQZY0k+2vXjY6ktJmeuGAzJQb67GNNaOZW7DUTn0hy5ZN4hXWMuU0TDOQGHAst+4FN54zHZPrjTYDn1wy0dRxmVdGaJx+KDmE/ng/i9XThYkia5gmbZSCp3Djy3ALqzHUa50RqzLCp5A6nW8nI29LhWayPDJk3lTYZSoC3Pxq88xaK7YC2jWJqBF2fKUAvR8mVWsm+lKSEWs4zM9waCkx7smIV8+ItUIgAFO8ejQuLEFVxs+uPg1nTqtHfyyJzz2w1nXHWdY6vTJk8stIksQmiVLFR69cMgmSBLy64xiL4wPAoK6MVOi1UKzFoyhkSXaUiAvFeac04Xsfmw8A+NGz7+PpdzTz4wa97sviibWmCZY3BI61HYxbZHhGaDaJQ50NL6DXWJVVyJKMqkCVUVXUB6IZCSr40ScXoTKk4tIFrfiny+aa/s7ISCCCaCDK/FOHBw6zv1mVEUZGYj0ZPV0o0aeLKGAOZxQ6r1iNobyUn23ucyIUtaFadqxHBo9kvA+wrzMCAO2Vmm/p8IC5ejFL61XNdXCykTIWkrU866XMqEmlU+yaT6nS/EalVMnz9QONNox7MsKyadyGaZLOYZp4Op5319BiIxxQ8OvrlmJOaxW6+mO4/oG1jGg4YTiewqCuOjRWBjP8Mo1Rf7NTcmFyQxTnn6KZMX/3plFYaFDvn1MRUk0FgKyTIGAcczEI1HXLp7Jsldse2YS1e05g/T6NjCzRO/1S8BPFgX7n6rJjGcU0sFonYC9VRd1i+YwGrPv2Stz3d0sQUMxTpbUeBt3t7+wxDMlWMkKVRAKS4ZuxW4jpIhxLxQoONziFaVIklbVsupMyIkkSK3x4eNC+JYJdnREAmFCpFcg7PHDYRITsMmkAs2fESsrswjT8e0qxIPOhVqqMlNTAapnvhDIyRpGvMsIbWCNqhDmYRzMbrYkE8OANZ2JCTRi7jw7iU79anVUhoX6RoKqFGKxx7eaIJtUeHSrdg0dre/xp3QGWstw9pP2/KqyaemlYJyjA//ReK77zkXlaSCyZxj889Bb+pGf/8GQkmU6avv9kJyM0NOYnWbAzLhYjVh4O2Bt+rQopre+wq2cXAG1OsIYJ+bL41vuPD/tQRNSIUX20wDFZ562AYpTQz7Zw2vWXoZhQoZGKjoGOjL/x77UaWJujzZAlGfF03KQg2PnxAIOUjaRGTCm0gH12I1Da9F5qXpUlmak+JfWMpIQyclLAczaNjWcEGB21RtygtSaM3/3DMrTXRrDn2CA+8cs38M5B+2wY5hep0MIy1p1LqZURQAuHzGquRP9IEg++vhcAsL1Ti9FPb6qw7TLKoxjpvTwUWcLPrj4NS6bUoW/EIEanTTbIyLHhY6b7rRyNtUoB60LGzr0P5NUu5dSv9F43sIZVqEpAlRFrJg2F0/1HyUjGQuxTWNGusin1fWQr0uXkvwKAtkqte7WTMuJUbyUgBxh5OzRwiP2engN+owdoVVspKbMeKzWrW+fjUiYVsGq8arQoGXu5YFWvBBkZo/BqYHVk7z6m4RUb05sq8diXVmBuWzWODcRw5X+8gb9uzpxQWCaNTY0RwJhYBxIDRe1Pw0OWJdx6wUwAwG9f24NjAzFW0GteW425kqWcqYyUgjSGAwp+c91S1jxu6ZQ61noeADoHzY3YTlZlxOoZcLP4uYWdpE+VulJUwMwI01iUEVrK3YqmqD0hY2TEyS9R4P1qZ/Sk18NqJOWRjYzkUkacPCOAOVTDjlEPJUWUSMbrne4dpzCNn/daLlC1JqpG2ZxYTgNrsXxxxca4JyNeu/baGVgBjo36mKVRTLRUh/GnL56F82c3YSSRxq1/2IifPLcN6bRByvgaI0CmKlQZqGST8bGh0t34H1k0AdMbK9A7nMB3ntiCVJqgLhpAS3WI7ZRkSc7YkQH+7s6zoa4iiPs/dwZe+tr5+M31S01/s07+B/vd9dwZa8hQRvSF2I/Uar5RHYVTlkYxMJwykwdKRmhfEqtfhILef9ZF0s7ACvi3ybELL7dGNTUn2/nKFqahalDHYPYwjdX8CnAmVk5VYYTJoowAzsTJyazeVtGW9dj8BL0XowFOGRk5nmFSLhashJE+Z4KMjDF4DdNQ9u4YphkDyghFVTiA315/Br547nQAwM9f3Imbfrcew7pplYY/Wqu1CdeqjEiSxB6+ruHS9WNQOHXkGb3d+9y2akiSZHgJbFQRgNuZlshgNq2xArWWxnQ0+2BSlWZ2syolJwusi1F9uB6KpICAFLzT5xvVUdDFtRTnkxlCKRnRiRCFNa2Xwun+s/OMAP5VYbUz3hcaprFTN3g4NQzk38uHaZwMrIBB9jLCNDb1WYASkxFLawBVUpEm6ZKRAauBlV7XnliPSSke7RBkJN8wjUUZcdrxjHYosoQ7PjwX93x6MYKqjOfeO4LP/nYNeocSeH6rtmiep2ew2O2uSr24U3xs8QRTr5A5rVpqJetVYTN5AqVdsJxA75HFTVpDuaPDR00lnU8WWPuayJLMyGuhyhQvjVNQQtA5VPxrS58Fq2eEwkkZcTJ9Wz+Pgn5uofer3bzlhoy4MbB2DnXabubY9bdRRuh7D/VzZMRBHQIMMmJNI6bjsj7vrZWle855lU6RFTYnluI+BDIJY3Wwmm3GSj0vF4JxT0a8ZtMwk5WFiZdSIi4Grjh9Iv7wD8tQHVaxbl83Fv/gOew7PoSgKuNcnYxkqxJZyjANAKiKjJ9+5lT273kTNDLilIpIQa/TseFjZSMAtCjW1OqpCMpBEJCSKkulgl0FTrbDLXC8dmEaFnZwqHvhJ6zzAP1uipyeEcsi4VRjwy8ywsLLPiojTdEmqJKWwWb9DEKIYwVWwFAFaVgLsPe1UDAy4hCmsb6HXo+BxAD648VtGMeIsa7S+XXN3MJq5pYkydGbNJox7skIrTPi1jNCHxgre3d6WMYSlk6tx6M3rUBLtfFgnzOzkVU2tTUN6hNaORj4oom1+M11S3HV0km4bKEmyzo19qKoD9cjIAdAQMq2a+DLhbO4u4MJcCzDrs4EnSQLVRDtwjSUaPbF+4reNdVKHqKBKFM9AOcwjRMBcArT+BVusAsvO6kNPLI9T6qssnCLNSOM39zZKSPTarRy+3yROKdMRcD5vDmRkWggyuq6FDtUwzwjukpXavWVGVi5DVgpDbx+QZARr+XgHeKaY/Hi22F2axWevOVsfOK0djRVhfD5c6axv2VTRsrFwFfOa8GPPrUIEb36ql39CR6yJLNrVa5QzWBSy/6pDBhkpFSSbilhJ9P7ZSC2C9NUBatYCmixNwUspMBlfkyvnc5+zmVgtaZ3O6X2slDIoH0oxPXx2oRY6XPQHet29BZkKyAIAJOrJwMA9vXvM/2eZtI4vbc+XI/qYDUICCMyTiFwAGiucCAjlgaAPCiRK/ZzXnZlxEa9Gou2gXFPRijog55MJ7MSE7bDUO3DNL2xXlMPl7GI1pow/r+rTsVb/7QSK2Y0st/b7VxGmyLkFEbjUerJworBuEZGKgIVZT+WYsLOb+AXaXdSEkqxK02lU2wR5BfOGbUz2M9OYZqGSAMkSEiRlKkOhFNqb1O0CbIkI5FO5G36JYTY1hmpDdUyb4HT9bCmjVoxpVorf25VRvjig3ZhGkmSmDqyp3cPAGdCBhjzzLHhY6ZMLCdlBEDJVEcaBqLXvNQhezvCyJ6zMRT+HfdkhCkjINhwZAPOfeRcfOOVbzi+3u6hBjRZlk6MY4mNeoFdTJem6PGu+HKCTgy0V4gdyq1GUGXkZCcjdmEav8J6fDolj1IsBE6t7qfXcMqIQ9EzVVZZhgw/TziZN1VZZecs33BDIp1g7S74TZQkSTlrjeRSRigZ2ddnVkaoKgbYh2kA43xRMpIttbc+XA9VVjMysVidEZvsuVJl1NCwKw3NlfqZtiOM7DkTnpGxA0pGDvQfwE1/uwn98X48s/cZbDm2xfb1TnVGJEkadSqB37CbLGjMuHOw07QbKhesuxQ7lNLoaAeqjFQGKkuaglhq0IWMLwfuV4jMURkpwULAF/jjibkbZQTgFklux+40HoArLpbnPcL3TrFuolgVVYf03FyGcNoYzqqM8DU27JQRABnKiFNBSUAPr0Yy7x2nOiOAMTcdHChuHR/rnJOr/orfsA3TCAPr2APNpvmfXf9jmmR+vfnXtq/P9sBQMnIy7nIB5yqOqqwiRVKjQhHqi2tNv1wpI2W6TrSZ4kmvjNhU4OQ7thbSiZYvwc2DLvROi6sf4DNT6GYGAGbUGGTE2o+Fx8TKiQDMi6RTai9QeLiBhpYlSBnhllzKZq4wDfWM7O/fbyIg9H2yJJvOEQ9KRnb37gbgHKqisCNO2cI01s8vFvoS2pxDfUJ0s3N8+HhJMvbsyAirRizCNGMHNJuG3rBXzb4KALDq4Comv/FwKnoGnDwmVifYkRFZko2aAaMgVONKGSljmIYQwkIMFYEK0+JZaJv40QY7z0hbRRtkScZIaqSgAoFOYRq7lFG/4ZSGWxuuZT/TucAOE6s0MsK3AXD6TKDwcAOv5tLNFwVPDu2QK0zTVtGGgBxAIp0wPU+UiGYjZTRMs7dvL5LpZNaNnulYuaqt1Ltjp4xQpWpv796iqrYsTKPPOfXhepayX4o5hhIeu3Bo52DnmJlXBBmxsPYrT7kSk6smI03S2NC1IeP1dq50irFeayQXnOoAjCbfCFNGQs7KiJ1MXirEUjEWT68IVLBzN5AYQG/MvmFhsTGSHMF9b9/H5HK/YFcOPKAYTdIKKYPvFNagZKSY/X6yEYc/fPgPuPucuzG7frbj+ykZ4cfPV/G0otBwg131VYpcz262OiOAFoKZXKWpI/z9k4vEANp5iKgRxFIx7O/fn3WjB2RWbSWEOPamAbTnPKJGkEgnitpywepTkyQJ7VXaeS1Fqwc79YqqSMPJ4bLNK14x7skIv1OoClRhZu1MnNF6BgBgTceajNfbpfRRUHnuZIz/A86qUK6y0KUEJSNOdR4AYzHojnXbql/FBA3RANquPqyGmaRaroZ5j+98HL/c9Et87ImP+dpPw6lRGl0AC4nl26X2AgYZ6RrqKlpWW7asj4VNC3HZ9Muyvt82TJOF4DhlrLhFNmOo2zBNNlJBU5ppk0CAMy87mFcBbSM4s1Zr67Cje0fWjR6Q2ZiPz6qxIyOyJGNq9VTt2Hp3ZfzdL1AywpuWKUErxTNt5+sJKSFWduHQYPk3iW4w7skIr4yc2nwqFFnBsrZlAIC1nWtNr02TtNGy2uaBseu3cDIhlh79yoibME1FoII1Niy2uc0KPkRD7z072b6U4BeRp/c87dvnOlXgpOPlS4F7hVOYpjZUyxaFYt2P2fwdbsDGP3CILdpM6bHZ5FAycrD/YF7hBrvqqxT02XUyoOdSRgAwQrGzZyf7HQvTOJhXKWbVzQKgkRGaJVMTrLF9rXV+5WujOKkpNFSzu6d4vhG6weDnnFIodBRO12g0bRLdQJAR7hQsbFwIAEwZ2XZiG3pGetjfTSl9dg+2Ls0d6j80ZuJ0XuBUY2U0kRE3YRrA2J2WmgAw86pq9NUp5cRlB75c9u+2/s63z3XaVftxvziFaSRJMnwjeSoJuWBtkucVLdEWqLJRRj2ZTrIFxY7gNEebEVbCSJJkXgtLtsqmTdEmBOQAUiRlG152Q0bogs+TWjeKCgCcUncKAGDria1MUabXzwq6uHYMdphCNIBzY0x2bEVSRhLpBLsX7chIse5BHk4m4/aK7H6g0YZxT0b4MM20Ws193RhpxIyaGSAgWHdkHfs7nYQA+webTrJDySH0xHqKdMTlA3Ouy+axl/LBywU3dUaA8qkRgwm9xkhw9JARPpNn+4ntvnX6tDbKo/CDjDiFaYDiX9vhlHOYxg0UWTGFqvhwkh3BkSWZZa3s7dvr+fuyhT9kSc66g3ZDKqgysqtnF9uE0WufzcAKALNqNWXklYOvIEVSCCkhlpZqRWu0FRIkxFIxHB85bmqKaTXmWo9t24ltWY8jX/BhXlr9FzCyjA4MlE4ZsV4joYyMMUgwbmK+aBFVR/hQDX2oVVm1lR9DSoiV4R0NKoHfcJrUptZMBaAVsip2U6pccEtGykUAGBkZRcoIT0aSJGmS2wuBk2+Ajjdfcx+fkWSnJBT7fDKlwcHb4AaUMO3t28ueKwmSY7jBqbiYG2QzsAKch8fmeuTq9QRoC68qqxhKDjF1w67gnR2oMkIxsXKiYypwQAmwLJHDA4eNkHmWassLGhcA0IhSMeYm+pkVgQrTWNk92Heg6Cq50zUSZGSMoTvWzX6mDzwAwzfSwZGRLOZVCj/MeaMVTjn9VcEqZsL0OyPDK/piuoE1i2cEKB8BYGEaG2WkFM57K1Jpoz4MNfu9f+J9Xz7baVdNx9sx2JGXyTSWirGKolbPCGA8x/moCG7gZh7IhZk1hprA19dw2uHTa5MXGcnSDZf/bLtn140yEpAD7DMokaWl7p0q0VLUhmtN865TiIaCzq8H+g9kzaShaIw0or2yHQQE7xx7J+tn5wM78yqgmW0VScFIaqToDTlzeUaEgXWMYG/vXvYz/7AubVkKCRJ29e7CseFjALK70il438jJhmxGuFIVGMqGWCrGdktuyUipCQDd0Zuc97qk2zXcxZSTUuHY8DEkSRKKpODs9rMBAFuPby34cwcTg4zoU7MwRX24HrWhWhCQvAgDDdEA9veinYfBTzhVYfaCmXW66bN7Z9bqqxQsTMPNV26R63iz+SrceEYAI9yyvXs7AIOU8M0DnXBa82nsZ6oYOYF+3s6enUwRyEZGAGBR0yIAwOajm3Mei1f0J+wN8wElwEoI5EMgvcCuay/AeWwGOsaEh3HckxFeGeFRG65ltQLe6nwLgHPHXh6jyczpN7KVXraWdi4H6C5FlmRT/NYOdHLvGOwoert5Hnz1VYqaUA0rxPbe8fdKdiyAUfitKdrEJG0/lBEao2+JtqAuXGf6myRJLCSaD2HgU2vtwqW0EurR4aNFqbGQq1KoG9DFe0fPDse+NDxoOOO94+957t6bq34H20jYZJy4qRcCAHMa5gAwiCz9LOrZyIbTm09nP+dSRuh52NG9I2tfGh6LmxYDKBIZyZK9x1+zYsJRGamYAFmSMZAYGBO1r/IiI7/4xS8wdepUhMNhLFu2DGvXrs36+kcffRRz5sxBOBzGwoUL8fTT/qUP+gU75n9m65kADN9IrtgrYGRpFLMCZLng1CQQGB3KCA3RVAYqHePOFA3hBrRVtDkWtysWmGfEQpZoJlcxpORsoDH+too2zG2YC0DLbCiUoG09oS1Kc+rn2P69EPXCKa2XojJYycidX/4XHtlqgrjFtJppkCDhxMgJFtPPRUYiagT9iX7PaapulZFDA4cywma5ysFT0OtMiSw973y/HifwyggtHOkERuJ4MpJDGTm1+VQAwMaujb6ZsymykZHFzRoJevvo275+pxVOhDGshjG3Xnum+USM0QrPZOSRRx7B7bffjjvvvBMbNmzA4sWLcfHFF6Ory74E+htvvIGrr74an//857Fx40ZcfvnluPzyy7Fli30julLja0u/BgD46Qd/mvE3RkZ034gbeXZewzwAwIYjG0xpwScDsikjTD7t3lk2SdBNXxoKSZKYL8iuuF2xQMmINcbMyMjR0pKRzgFNGWmNtmJa9TS0V7Yjlorh1UOvFvS5dFHKRUbyIa/ZqpVS8BkefsMPz0g0EGUhCUpAs21yVFll98imo5s8fVeuMuvZwma5GuVR0Ou8v38/+uJ9TCHl+/U4gfeMzKufl/W1tC7J4cHD6B7RVO1sSjUAzK2fi+ZIMwYSA3iz482cx+MF2cjIokYtPPR219tFnROzhdJoIsa6ztFPRrJrbza45557cOONN+KGG24AAPzqV7/CU089hfvvvx/f/OY3M17/7//+77jkkkvw9a9/HQDwwx/+EM8//zzuvfde/OpXvyrw8AvH9fOvx5WnXGm7y1rSsgSKpGB//368cvAVJrdlu/ln18/G3Pq52HpiKx7Z9gg+OuOjRTv2UiJFUixdz46Mzambg6AcxMGBg3h0+6PMf1BK0NhsLr8IxbK2ZXhi5xN44/AbuHrg6mIeGgPtomm93+hCs/no5pK53xPpBB7Z9ggAjUxKkoSLpl6EB7Y8gKd2P8WOKR+8e/xdAGA7MytomGZ793bP46U+n1xk5LVDr2Hz0c2+34s0tFuIMgJou/wD/Qfw7N5nAZhNzXZY3LQYazvXYk3HGqyYsML191AzabZ5a3rNdGzo2oCndj9lIvOUyOQK09SH69EcbUbXUBf+e/t/YyQ1gqAczBl2AbSNwf9+8n/RH+9nZcydUBOqYd9Dd/u5lBFZknHB5Avw8LaH8dTup1yFjtyCZqLZGXXnN86HIinoGu7ClmNb0BBp8O17eVCl0ImMPPjug1jbudbVc9YYacx5PosFT2QkHo9j/fr1uOOOO9jvZFnGypUrsXr1atv3rF69GrfffrvpdxdffDGeeOIJx++JxWKIxYyaHn19fV4O0zOyyb3zG+dj89HNuOWFW9jvl7Yuzfp5V8y6Av+85p9x76Z7ce+me3091tEAu5u1NlyLLy7+In6+8ef44Zs/LMNRGXCjjADAslZNGdnevR0X//fFxTykDFjDNPMa5rGJq9TH0lbRhmvnXgsAuGiKRkZeOvASXjrwUsGfTb0EVtAF4UD/gbzHa1djhIIqL0/uehJP7noyr8/PhVw78lz48PQP48UDL7JspqtnZyfENNzw7N5nGYHxgmzG+5m1M7GhawMefPdBPPjugxl/z1bWnWJu/Vx0DXXhnvX3ANBCUbkqsFJQs6UbzKqbha6hLjy6/VEAuT0jAPChKR/Cw9sextN7nva1yjCF3QYookZwSt0p2HpiK655+hrfv9MKO8J4WvNpkCXZ9XP2uw//jnlsSg1PZOTYsWNIpVJoaTHH9VpaWvD++/amt87OTtvXd3Y6dzO866678P3vf9/LoRUNd5x5B36x6RfYcGQDFFnBNXOuwc2Lb876no9M/wj+vP3PRUstLCfOaT/HUe69Yf4NeKvzLWzs2ljiozKgyiounuZucWuKNuGj0z+K5/Y9V+SjMqMuXIez2s4y/S4aiOKKWVfgL7v+UtJjqQhU4F/O/hc2mc5vmI/zJ56P1R32mwsvOKvtLNZPxIrGSCMumHQBXj/8el6frUgKLpl2iePfz24/G5OrJhfNuGd3Db3i4qkXI56K476378N1867DhVMuzPr6pS1LMbd+bl6hrapgFT4w4QOOf79+/vU4OnwU646sy/BVzKqdZarB5IRr5lyDA/0H0BvrRTwdxydmfcLzcbrB5TMux+ajmxFPxaHKKi6aelHO95zecjqWtS7zHOJyg8pAJc6deK7t366afRX+bd2/FbVrMKBtKKgBnUdVsAqfnPVJ1/MKX3er1JCIh2DW4cOH0d7ejjfeeAPLly9nv//Hf/xHvPzyy1izJjP2HgwG8dBDD+Hqqw3W/8tf/hLf//73ceSI/URhp4xMmjQJvb29qK52t+sVEBAQEBAQKC/6+vpQU1OTc/32pIw0NjZCUZQMEnHkyBG0trbavqe1tdXT6wEgFAohFCpMAhUQEBAQEBAYG/CUTRMMBrFkyRK88MIL7HfpdBovvPCCSSnhsXz5ctPrAeD55593fL2AgICAgIDA+ILnbJrbb78d119/PZYuXYozzzwTP/3pTzE4OMiya6677jq0t7fjrrvuAgB85StfwXnnnYef/OQnuOyyy/Dwww9j3bp1+M///E9/RyIgICAgICAwJuGZjFx11VU4evQovvvd76KzsxOnnnoqnn32WWZS3b9/P2TZEFxWrFiBP/zhD/j2t7+Nb33rW5g1axaeeOIJLFiQabYREBAQEBAQGH/wZGAtF9waYAQEBAQEBARGD9yu3+O+N42AgICAgIBAeSHIiICAgICAgEBZIciIgICAgICAQFkhyIiAgICAgIBAWSHIiICAgICAgEBZIciIgICAgICAQFkhyIiAgICAgIBAWSHIiICAgICAgEBZIciIgICAgICAQFnhuRx8OUCLxPb19ZX5SAQEBAQEBATcgq7buYq9jwky0t/fDwCYNGlSmY9EQEBAQEBAwCv6+/tRU1Pj+Pcx0ZsmnU7j8OHDqKqqgiRJvn1uX18fJk2ahAMHDpy0PW9O9jGe7OMDTv4xnuzjA07+MZ7s4wNO/jEWa3yEEPT392PChAmmJrpWjAllRJZlTJw4sWifX11dfVLeXDxO9jGe7OMDTv4xnuzjA07+MZ7s4wNO/jEWY3zZFBEKYWAVEBAQEBAQKCsEGREQEBAQEBAoK8Y1GQmFQrjzzjsRCoXKfShFw8k+xpN9fMDJP8aTfXzAyT/Gk318wMk/xnKPb0wYWAUEBAQEBAROXoxrZURAQEBAQECg/BBkREBAQEBAQKCsEGREQEBAQEBAoKwQZERAQEBAQECgrBjXZOQXv/gFpk6dinA4jGXLlmHt2rXlPqS88L3vfQ+SJJn+mzNnDvv7yMgIbrnlFjQ0NKCyshKf/OQnceTIkTIecW688sor+OhHP4oJEyZAkiQ88cQTpr8TQvDd734XbW1tiEQiWLlyJXbs2GF6zYkTJ3DttdeiuroatbW1+PznP4+BgYESjsIZucb3uc99LuOaXnLJJabXjObx3XXXXTjjjDNQVVWF5uZmXH755di2bZvpNW7uy/379+Oyyy5DNBpFc3Mzvv71ryOZTJZyKI5wM8bzzz8/4zredNNNpteM1jHed999WLRoESuCtXz5cjzzzDPs72P9+gG5xziWr58d7r77bkiShNtuu439btRcRzJO8fDDD5NgMEjuv/9+8u6775Ibb7yR1NbWkiNHjpT70DzjzjvvJPPnzycdHR3sv6NHj7K/33TTTWTSpEnkhRdeIOvWrSNnnXUWWbFiRRmPODeefvpp8k//9E/kscceIwDI448/bvr73XffTWpqasgTTzxB3n77bfKxj32MTJs2jQwPD7PXXHLJJWTx4sXkzTffJK+++iqZOXMmufrqq0s8EnvkGt/1119PLrnkEtM1PXHihOk1o3l8F198MXnggQfIli1byKZNm8iHP/xhMnnyZDIwMMBek+u+TCaTZMGCBWTlypVk48aN5OmnnyaNjY3kjjvuKMeQMuBmjOeddx658cYbTdext7eX/X00j/Evf/kLeeqpp8j27dvJtm3byLe+9S0SCATIli1bCCFj//oRknuMY/n6WbF27VoydepUsmjRIvKVr3yF/X60XMdxS0bOPPNMcsstt7B/p1IpMmHCBHLXXXeV8ajyw5133kkWL15s+7eenh4SCATIo48+yn63detWAoCsXr26REdYGKyLdTqdJq2treTf/u3f2O96enpIKBQif/zjHwkhhLz33nsEAHnrrbfYa5555hkiSRI5dOhQyY7dDZzIyMc//nHH94yl8RFCSFdXFwFAXn75ZUKIu/vy6aefJrIsk87OTvaa++67j1RXV5NYLFbaAbiAdYyEaIsZP/FbMdbGWFdXR37zm9+clNePgo6RkJPn+vX395NZs2aR559/3jSm0XQdx2WYJh6PY/369Vi5ciX7nSzLWLlyJVavXl3GI8sfO3bswIQJEzB9+nRce+212L9/PwBg/fr1SCQSprHOmTMHkydPHrNj3bNnDzo7O01jqqmpwbJly9iYVq9ejdraWixdupS9ZuXKlZBlGWvWrCn5MeeDVatWobm5GbNnz8bNN9+M48ePs7+NtfH19vYCAOrr6wG4uy9Xr16NhQsXoqWlhb3m4osvRl9fH959990SHr07WMdI8fvf/x6NjY1YsGAB7rjjDgwNDbG/jZUxplIpPPzwwxgcHMTy5ctPyutnHSPFyXD9brnlFlx22WWm6wWMrudwTDTK8xvHjh1DKpUynVwAaGlpwfvvv1+mo8ofy5Ytw4MPPojZs2ejo6MD3//+93HOOedgy5Yt6OzsRDAYRG1trek9LS0t6OzsLM8BFwh63HbXj/6ts7MTzc3Npr+rqor6+voxMe5LLrkEV1xxBaZNm4Zdu3bhW9/6Fi699FKsXr0aiqKMqfGl02ncdttt+MAHPoAFCxYAgKv7srOz0/Ya07+NJtiNEQCuueYaTJkyBRMmTMDmzZvxjW98A9u2bcNjjz0GYPSP8Z133sHy5csxMjKCyspKPP7445g3bx42bdp00lw/pzECY//6AcDDDz+MDRs24K233sr422h6DsclGTnZcOmll7KfFy1ahGXLlmHKlCn405/+hEgkUsYjE8gXn/nMZ9jPCxcuxKJFizBjxgysWrUKF154YRmPzDtuueUWbNmyBa+99lq5D6VocBrjF77wBfbzwoUL0dbWhgsvvBC7du3CjBkzSn2YnjF79mxs2rQJvb29+POf/4zrr78eL7/8crkPy1c4jXHevHlj/vodOHAAX/nKV/D8888jHA6X+3CyYlyGaRobG6EoSoZj+MiRI2htbS3TUfmH2tpanHLKKdi5cydaW1sRj8fR09Njes1YHis97mzXr7W1FV1dXaa/J5NJnDhxYkyOe/r06WhsbMTOnTsBjJ3x3XrrrfjrX/+Kl156CRMnTmS/d3Nftra22l5j+rfRAqcx2mHZsmUAYLqOo3mMwWAQM2fOxJIlS3DXXXdh8eLF+Pd///eT6vo5jdEOY+36rV+/Hl1dXTj99NOhqipUVcXLL7+Mn/3sZ1BVFS0tLaPmOo5LMhIMBrFkyRK88MIL7HfpdBovvPCCKVY4VjEwMIBdu3ahra0NS5YsQSAQMI1127Zt2L9//5gd67Rp09Da2moaU19fH9asWcPGtHz5cvT09GD9+vXsNS+++CLS6TSbUMYSDh48iOPHj6OtrQ3A6B8fIQS33norHn/8cbz44ouYNm2a6e9u7svly5fjnXfeMZGu559/HtXV1UxGLydyjdEOmzZtAgDTdRzNY7QinU4jFoudFNfPCXSMdhhr1+/CCy/EO++8g02bNrH/li5dimuvvZb9PGquo29W2DGGhx9+mIRCIfLggw+S9957j3zhC18gtbW1JsfwWMFXv/pVsmrVKrJnzx7y+uuvk5UrV5LGxkbS1dVFCNFStyZPnkxefPFFsm7dOrJ8+XKyfPnyMh91dvT395ONGzeSjRs3EgDknnvuIRs3biT79u0jhGipvbW1teTJJ58kmzdvJh//+MdtU3tPO+00smbNGvLaa6+RWbNmjZrU12zj6+/vJ1/72tfI6tWryZ49e8jf/vY3cvrpp5NZs2aRkZER9hmjeXw333wzqampIatWrTKlRQ4NDbHX5LovaUrhRRddRDZt2kSeffZZ0tTUNGrSJnONcefOneQHP/gBWbduHdmzZw958sknyfTp08m5557LPmM0j/Gb3/wmefnll8mePXvI5s2byTe/+U0iSRJ57rnnCCFj//oRkn2MY/36OcGaITRaruO4JSOEEPLzn/+cTJ48mQSDQXLmmWeSN998s9yHlBeuuuoq0tbWRoLBIGlvbydXXXUV2blzJ/v78PAw+dKXvkTq6upINBoln/jEJ0hHR0cZjzg3XnrpJQIg47/rr7+eEKKl937nO98hLS0tJBQKkQsvvJBs27bN9BnHjx8nV199NamsrCTV1dXkhhtuIP39/WUYTSayjW9oaIhcdNFFpKmpiQQCATJlyhRy4403ZhDl0Tw+u7EBIA888AB7jZv7cu/eveTSSy8lkUiENDY2kq9+9askkUiUeDT2yDXG/fv3k3PPPZfU19eTUChEZs6cSb7+9a+b6lQQMnrH+Pd///dkypQpJBgMkqamJnLhhRcyIkLI2L9+hGQf41i/fk6wkpHRch0lQgjxT2cREBAQEBAQEPCGcekZERAQEBAQEBg9EGREQEBAQEBAoKwQZERAQEBAQECgrBBkREBAQEBAQKCsEGREQEBAQEBAoKwQZERAQEBAQECgrBBkREBAQEBAQKCsEGREQEBAQEBAoKwQZERAQKBsOP/883HbbbeV+zAEBATKDEFGBAQEBAQEBMoKUQ5eQECgLPjc5z6Hhx56yPS7PXv2YOrUqeU5IAEBgbJBkBEBAYGyoLe3F5deeikWLFiAH/zgBwCApqYmKIpS5iMTEBAoNdRyH4CAgMD4RE1NDYLBIKLRKFpbW8t9OAICAmWE8IwICAgICAgIlBWCjAgICAgICAiUFYKMCAgIlA3BYBCpVKrchyEgIFBmCDIiICBQNkydOhVr1qzB3r17cezYMaTT6XIfkoCAQBkgyIiAgEDZ8LWvfQ2KomDevHloamrC/v37y31IAgICZYBI7RUQEBAQEBAoK4QyIiAgICAgIFBWCDIiICAgICAgUFYIMiIgICAgICBQVggyIiAgICAgIFBWCDIiICAgICAgUFYIMiIgICAgICBQVggyIiAgICAgIFBWCDIiICAgICAgUFYIMiIgICAgICBQVggyIiAgICAgIFBWCDIiICAgICAgUFYIMiIgICAgICBQVvz/bnObg+VhxBoAAAAASUVORK5CYII=", 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", 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", 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", 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z5qBv375obGzEZ599hlWrVmH27NmYPn26vO0HH3yAa665Bq+99pp8HOfn5+Pee+/Ffffdh7PPPhtz5szBjz/+iJdffhlz587F+PHj5ecvXLgQ77zzDi688ELceeedSEtLwwsvvACn04mHHnrI0PshiA4RzVIeguhsfvnlF/GGG24QS0pKxPj4eDElJUWcNGmS+PTTT3s1NHM6neJf/vIXsbS0VLRYLGJRUZHfpme+TJ061av0869//at48skni+np6WJCQoI4ePBg8cEHHxQdDoe8jcvlEm+55RYxJydHFATBq8z3n//8pzhgwADRarWKgwcPFl977TW5eZkaSE3PfCkuLhavuuoqr/seeOABsVevXqLJZOpQ07NA710URfHll18W+/btK5rN5nZltWvWrBFnzpwppqWliTabTezXr5949dVXi5s2bfK7f1EU230G7733nnjWWWeJubm5Ynx8vNinTx/xt7/9rVhZWem1P98xNDU1iZdffrmYnp4uNz3z5ZxzzhEBiOvWrdP8jLKzs8VTTz1V8zFf6uvrRZvNJv7617/W3Wbjxo3ixRdfLPbp00e0Wq1iUlKSOHbsWPGxxx5r12OEN5d77bXXvO73eDzi008/LQ4cOFA+jv/4xz96HXecsrIy8YILLhBTU1PFhIQEcfr06eKGDRsMvR+C6CiCKEYgq40gCKKbccEFF2Dbtm3Yu3dvu8d27tyJYcOG4eOPPw4pjEcQPR0KBBIEQQSgsrISn3zyCa688krNx9esWYMJEyaQECGIECFnhCAIQof9+/fj22+/xSuvvIKNGzeirKzM7+J0BEGEBjkjBEEQOnz55Ze48sorsX//frz++uskRAgiQpAzQhAEQRBEVCFnhCAIgiCIqEJihCAIgiCIqNIlmp55PB4cOXIEKSkpndrGmiAIgiCI0BFFEY2NjSgsLPTbybdLiJEjR46gqKgo2sMgCIIgCCIEDh48iN69e+s+3iXECF+k6eDBg/Jy8ARBEARBxDYNDQ0oKioKuNhilxAjPDSTmppKYoQgCIIguhiBUiwogZUgCIIgiKhCYoQgCIIgiKhCYoQgCIIgiKjSJXJGjODxeOBwOKI9DKKHYrFYYDaboz0MgiCILkm3ECMOhwP79++Hx+OJ9lCIHkx6ejry8/OpFw5BEESQdHkxIooiKisrYTabUVRU5LepCkFEAlEU0dLSgqNHjwIACgoKojwigiCIrkWXFyMulwstLS0oLCxEYmJitIdD9FASEhIAAEePHkVubi6FbAiCIIKgy9sIbrcbABAfHx/lkRA9HS6GnU5nlEdCEATRtejyYoRDcXoi2tAxSBAEERrdRowQBEEQBNE1ITESJaZNm4bbb79d9/GSkhI88cQTnTYegiAIgogWXT6BtbuyceNGJCUlRXsYBEEQBBFxSIzEKDk5OdEeAkEQRERwe0SYTZRjRShQmCaKuFwuLFiwAGlpacjOzsaf/vQniKIIoH2YpqKiAueffz6Sk5ORmpqKSy65BNXV1fLj999/P0aPHo1XX30Vffr0QXJyMm6++Wa43W488sgjyM/PR25uLh588EGvMTz22GMYMWIEkpKSUFRUhJtvvhlNTU3y4+Xl5Zg9ezYyMjKQlJSEYcOGYfny5QCAEydO4IorrkBOTg4SEhIwYMAAvPbaaxH8xAiC6OqsL6vFwD9+itfXHYj2UIgYots5I6IootXpjsq+EyzmoCoqXn/9dVx33XXYsGEDNm3ahN/85jfo06cPbrjhBq/tPB6PLES+/PJLuFwuzJ8/H5deeinWrl0rb1dWVoZPP/0UK1asQFlZGS666CLs27cPAwcOxJdffol169bh2muvxYwZM3DKKacAAEwmE5566imUlpZi3759uPnmm3HPPffgueeeAwDMnz8fDocDX331FZKSkrBz504kJycDAP70pz9h586d+PTTT5GdnY29e/eitbW1g58iQRDdmate2wC3R8Sf/7sDV00sifZwiBih24mRVqcbQ+/7LCr73rloJhLjjX+kRUVFePzxxyEIAgYNGoRt27bh8ccfbydGVq9ejW3btmH//v0oKioCAPzrX//CsGHDsHHjRowfPx4AEy2vvvoqUlJSMHToUJx++unYvXs3li9fDpPJhEGDBuHhhx/GmjVrZDGiTqItKSnBX//6V9x4442yGKmoqMCFF16IESNGAAD69u0rb19RUYExY8bgpJNOkp9PEAThD4eLlu0g2kNhmihy6qmnejkpEyZMwJ49e+RGbpxdu3ahqKhIFiIAMHToUKSnp2PXrl3yfSUlJUhJSZH/zsvLw9ChQ71a5Ofl5cltywHg888/xxlnnIFevXohJSUFV155JWpra9HS0gIAuPXWW/HXv/4VkyZNwp///Gf89NNP8nNvuukmvPXWWxg9ejTuuecerFu3LgyfCkEQ3ZUTzbSYKaFNt3NGEixm7Fw0M2r7jiYWi8Xrb0EQNO/jCwoeOHAA5513Hm666SY8+OCDyMzMxDfffIPrrrsODocDiYmJuP766zFz5kx88sknWLlyJRYvXoxHH30Ut9xyC2bNmoXy8nIsX74cq1atwhlnnIH58+fjH//4R6e9Z4Igug6by094/d3Q5kSqzaKzNdGT6HbOiCAISIyPi8pPsB04v//+e6+/v/vuOwwYMKDduiZDhgzBwYMHcfDgQfm+nTt3oq6uDkOHDg35s9q8eTM8Hg8effRRnHrqqRg4cCCOHDnSbruioiLceOONeP/993HXXXfh5Zdflh/LycnBVVddhTfffBNPPPEEXnrppZDHQxBE9+aHg95ipLKuLUojIWKNbidGuhIVFRW48847sXv3bvz73//G008/jdtuu63ddjNmzMCIESNwxRVXYMuWLdiwYQPmzZuHqVOnyvkaodC/f384nU48/fTT2LdvH9544w288MILXtvcfvvt+Oyzz7B//35s2bIFa9aswZAhQwAA9913Hz766CPs3bsXO3bswMcffyw/RhAE4UtNo3eY5kgdJbwTDBIjUWTevHlobW3FySefjPnz5+O2227Db37zm3bbCYKAjz76CBkZGZgyZQpmzJiBvn374u233+7Q/keNGoXHHnsMDz/8MIYPH46lS5di8eLFXtu43W7Mnz8fQ4YMwdlnn42BAwfKya3x8fFYuHAhRo4ciSlTpsBsNuOtt97q0JgIgui+NDtcXn8fqScxQjAEkTe2iGEaGhqQlpaG+vp6pKamej3W1taG/fv3o7S0FDabLUojJAg6FgkiENe8tgFrdh+DzWJCm9OD+af3w+9mDo72sIgI4m/+VkPOCEEQBNEpNDtYpWD/XNariHJGCA6JEYIgCKJTaJHCNP1zmBihMA3BITFCEARBdAotduaM9M5IBADUt7r8bU70IEiMEARBEJ0CT2DNS2M5VU12ZzSHQ8QQJEYIgiCIToE7I/mpTIw0tpEzQjBIjBAEQRARRxRFxRlJtQIAmtpc6AIFnUQnQGKEIAiCiDh2lwceSXfkSc6IyyOizUkL5xEkRgiCIIhOoNmuhGSyk63gq2c0Ut4IARIjBEEQRCfQIvUYSbCYYTYJSLaydVqbKG+EAIkRgiAIohPg+SJJVrYQaIokRiiJlQBIjBARRBAEfPjhh9EeBkEQMUCzVEmTGM9ESIrNAgBospMYIUiMEARBEJ0A776aGM+ckWQbOSOEAomRKDFt2jTccsstuP3225GRkYG8vDy8/PLLaG5uxjXXXIOUlBT0798fn376qfyc7du3Y9asWUhOTkZeXh6uvPJK1NTUyI+vWLECp512GtLT05GVlYXzzjsPZWVl8uMHDhyAIAh4//33cfrppyMxMRGjRo3C+vXrA45XFEXk5OTgvffek+8bPXo0CgoK5L+/+eYbWK1WtLS0oKSkBABwwQUXQBAE+W+CIHomPIE1SQrPJMthGkpgJbqjGBFFwNEcnZ8g6+Vff/11ZGdnY8OGDbjllltw00034eKLL8bEiROxZcsWnHXWWbjyyivR0tKCuro6TJ8+HWPGjMGmTZuwYsUKVFdX45JLLpFfr7m5GXfeeSc2bdqE1atXw2Qy4YILLoDH4106d++99+Luu+/G1q1bMXDgQMydOxcul/+rE0EQMGXKFKxduxYAcOLECezatQutra34+eefAQBffvklxo8fj8TERGzcuBEA8Nprr6GyslL+myCIngkP03AxkiI5IxSmIQAgLtoDCDvOFuChwujs+w9HgPgkw5uPGjUKf/zjHwEACxcuxN/+9jdkZ2fjhhtuAADcd999eP755/HTTz/h888/x5gxY/DQQw/Jz3/11VdRVFSEX375BQMHDsSFF17o9fqvvvoqcnJysHPnTgwfPly+/+6778a5554LAPjLX/6CYcOGYe/evRg82P9S3tOmTcOLL74IAPjqq68wZswY5OfnY+3atRg8eDDWrl2LqVOnAgBycnIAAOnp6cjPzzf8mRAE0T3hYZokKUyTQmEaQkX3c0a6ECNHjpRvm81mZGVlYcSIEfJ9eXl5AICjR4/ixx9/xJo1a5CcnCz/cPHAQzF79uzB3Llz0bdvX6SmpsqhkYqKCt398jDL0aNHA4536tSp2LlzJ44dO4Yvv/wS06ZNw7Rp07B27Vo4nU6sW7cO06ZNC/6DIAii29Ps8E5glUt7yRkh0B2dEUsicyiite9gNrdYvP4WBMHrPkHqCuTxeNDU1ITZs2fj4Ycfbvc6XFDMnj0bxcXFePnll1FYWAiPx4Phw4fD4XDo7le9j0CMGDECmZmZ+PLLL/Hll1/iwQcfRH5+Ph5++GFs3LgRTqcTEydONPjuCYLoSbTYfUp7pWoackYIoDuKEUEIKlTSVRg7diz+85//oKSkBHFx7f9ttbW12L17N15++WVMnjwZAEsoDSeCIGDy5Mn46KOPsGPHDpx22mlITEyE3W7Hiy++iJNOOglJScpnb7FY4Ha7wzoGgiC6JnrOCCWwEgCFaboM8+fPx/HjxzF37lxs3LgRZWVl+Oyzz3DNNdfA7XYjIyMDWVlZeOmll7B371588cUXuPPOO8M+jmnTpuHf//43Ro8ejeTkZJhMJkyZMgVLly6V80U4JSUlWL16NaqqqnDixImwj4UgiK6Db85IMiWwEipIjHQRCgsL8e2338LtduOss87CiBEjcPvttyM9PR0mkwkmkwlvvfUWNm/ejOHDh+OOO+7A3//+97CPY+rUqXC73V65IdOmTWt3HwA8+uijWLVqFYqKijBmzJiwj4UgiK6D3PRMckRSbdQOnlAQxC6wfnNDQwPS0tJQX1+P1NRUr8fa2tqwf/9+lJaWwmazRWmEBEHHIkH44/rXN+LzXUex+NcjMPfkPvhmTw3+75/fY1BeCj67Y0q0h0dECH/zt5qgnJHnn38eI0eORGpqKlJTUzFhwgSvplxavPvuuxg8eDBsNhtGjBiB5cuXB7NLgiAIohtgd7EkeZuFTTtKB1bKGSGCFCO9e/fG3/72N2zevBmbNm3C9OnTcf7552PHjh2a269btw5z587Fddddhx9++AFz5szBnDlzsH379rAMnggvvLur1o+6vwlBEESwcDESb2Y5Izx3pMVJSe5EkNU0s2fP9vr7wQcfxPPPP4/vvvsOw4YNa7f9k08+ibPPPhu/+93vAAAPPPAAVq1ahWeeeQYvvPBCB4ZNRIJXXnkFra2tmo9lZmZ28mgIguhOOCQxYjGzdgIJXIw4SIwQHSjtdbvdePfdd9Hc3IwJEyZobrN+/fp2FR0zZ84MuJKr3W6H3W6X/25oaAh1mEQQ9OrVK9pDIAiim+J0S85IHDPkeYmvw+WB2yPCbBKiNjYi+gRdTbNt2zYkJyfDarXixhtvxAcffIChQ4dqbltVVSV3EeXk5eWhqqrK7z4WL16MtLQ0+aeoqCjYYRIEQRAxBHdGFDFilh/jZb9EzyVoMTJo0CBs3boV33//PW666SZcddVV2LlzZ1gHtXDhQtTX18s/Bw8eDOvrEwRBEJ2LQ3JGrJIYscaZIDWARiuFano8QYdp4uPj0b9/fwDAuHHjsHHjRjz55JPyAmpq8vPzUV1d7XVfdXV1wIXTrFYrrFZrsEMjCIIgYhQlZ4SJEUEQkGgxo9nhprwRouNNzzwej1d+h5oJEyZg9erVXvetWrVKN8eEIAiC6J745owAQIKUN0JihAjKGVm4cCFmzZqFPn36oLGxEcuWLcPatWvx2WefAQDmzZuHXr16YfHixQCA2267DVOnTsWjjz6Kc889F2+99RY2bdqEl156KfzvhCAIgohZlNJeRYzwvJFWJ+WM9HSCckaOHj2KefPmYdCgQTjjjDOwceNGfPbZZzjzzDMBsKXqKysr5e0nTpyIZcuW4aWXXsKoUaPw3nvv4cMPP8Tw4cPD+y66IKIo4je/+Q0yMzMhCALS09Nx++23G3rutGnTAm4rCELAqqVwcv/992P06NGdtr+O0NmfDUEQ7cM0gCJGyBkhgnJG/vnPf/p9fO3ate3uu/jii3HxxRcHNaiewIoVK7BkyRKsXbsWffv2hclkQkJCQthev7KyEhkZGWF7vUDcfffduOWWW4J6TklJCW6//XbDIixcqD+bAwcOoLS0FD/88EOXEVME0RVx+iSwAtRrhFAIuc8I0THKyspQUFCAiRMnRuT1AyUJhxveqbUr0NmfDUH0dFxuDzzSKmjqnBHujLRRF9YeD63aGwWuvvpq3HLLLaioqIAgCCgpKWkXennuuecwYMAA2Gw25OXl4aKLLvJ6DY/Hg3vuuQeZmZnIz8/H/fff7/W4OhRx4MABCIKA999/H6effjoSExMxatQorF+/3us5L7/8MoqKipCYmIgLLrgAjz32GNLT0w29J98wzdVXX405c+bgH//4BwoKCpCVlYX58+fD6WTrUEybNg3l5eW44447IAgCBEFpePTNN99g8uTJSEhIQFFREW699VY0NzfLj5eUlOChhx7Ctddei5SUFPTp08crD8nhcGDBggUoKCiAzWZDcXGxnMfk+9mUlpYCAMaMGQNBEDBt2jR89dVXsFgs7frh3H777Zg8ebKhz4MgCAVe1gv4JLBaKIGVYHQ7MSKKIlqcLVH5MboA8pNPPolFixahd+/eqKysxMaNG70e37RpE2699VYsWrQIu3fvxooVKzBliveqlq+//jqSkpLw/fff45FHHsGiRYuwatUqv/u99957cffdd2Pr1q0YOHAg5s6dC5eLJY59++23uPHGG3Hbbbdh69atOPPMM/Hggw8G8cm3Z82aNSgrK8OaNWvw+uuvY8mSJViyZAkA4P3330fv3r2xaNEiVFZWyrlGZWVlOPvss3HhhRfip59+wttvv41vvvkGCxYs8HrtRx99FCeddBJ++OEH3Hzzzbjpppuwe/duAMBTTz2F//73v3jnnXewe/duLF26FCUlJZpj3LBhAwDg888/R2VlJd5//31MmTIFffv2xRtvvCFv53Q6sXTpUlx77bUd+kwIoifidCnnRsoZIbTodmGaVlcrTll2SlT2/f3l3yPRkhhwu7S0NKSkpMBsNmuGDCoqKpCUlITzzjsPKSkpKC4uxpgxY7y2GTlyJP785z8DAAYMGIBnnnkGq1evlpOJtbj77rtx7rnnAgD+8pe/YNiwYdi7dy8GDx6Mp59+GrNmzcLdd98NABg4cCDWrVuHjz/+2PD79yUjIwPPPPMMzGYzBg8ejHPPPRerV6/GDTfcgMzMTJjNZqSkpHh9BosXL8YVV1whu0QDBgzAU089halTp+L555+HzWYDAJxzzjm4+eabAQC///3v8fjjj2PNmjUYNGgQKioqMGDAAJx22mkQBAHFxcW6Y8zJyQEAZGVleY3juuuuw2uvvSavq/S///0PbW1tuOSSS0L+PAiip2J3M7EhCECcqu27XE1DHVh7PN3OGekOnHnmmSguLkbfvn1x5ZVXYunSpWhpafHaZuTIkV5/FxQU4OjRo35fV/2cgoICAJCfs3v3bpx88sle2/v+HSzDhg2D2ay0fDYyxh9//BFLlizxWjF45syZ8Hg82L9/v+Z7EQQB+fn58mtfffXV2Lp1KwYNGoRbb70VK1euDHrsV199Nfbu3YvvvvsOALBkyRJccsklSEpKCvq1CKKn41CV9apDspTASnC6nTOSEJeA7y//Pmr7DgcpKSnYsmUL1q5di5UrV+K+++7D/fffj40bN8o5HBaLxes5giDA4/FovJqC+jn8hBDoOR0hlDE2NTXht7/9LW699dZ2j/Xp08fQa48dOxb79+/Hp59+is8//xyXXHIJZsyYgffee8/w2HNzczF79my89tprKC0txaeffqpZLUYQRGAcGj1GAArTEArdToywFsOBQyWxTlxcHGbMmIEZM2bgz3/+M9LT0/HFF1/g17/+dUT2N2jQoHa5K75/h5v4+Hi43d4nobFjx2Lnzp3ykgOhkpqaiksvvRSXXnopLrroIpx99tk4fvw4MjMz240BQLtxAMD111+PuXPnonfv3ujXrx8mTZrUoTERRE/F6WY5I+rkVQBIsPAwDYmRnk63EyPdgY8//hj79u3DlClTkJGRgeXLl8Pj8WDQoEER2+ctt9yCKVOm4LHHHsPs2bPxxRdf4NNPP/WyVMNNSUkJvvrqK1x22WWwWq3Izs7G73//e5x66qlYsGABrr/+eiQlJWHnzp1YtWoVnnnmGUOv+9hjj6GgoABjxoyByWTCu+++i/z8fM3KoNzcXCQkJGDFihXo3bs3bDYb0tLSAAAzZ85Eamoq/vrXv2LRokXhfOsE0aPwXbGXI7eDp9LeHg/ljMQg6enpeP/99zF9+nQMGTIEL7zwAv79739j2LBhEdvnpEmT8MILL+Cxxx7DqFGjsGLFCtxxxx1ywmgkWLRoEQ4cOIB+/frJiaQjR47El19+iV9++QWTJ0/GmDFjcN9996GwsNDw66akpOCRRx7BSSedhPHjx+PAgQNYvnw5TKb2h3tcXByeeuopvPjiiygsLMT5558vP2YymXD11VfD7XZj3rx5HX/DBNFDcUjOo68YoQRWgiOIRutRo0hDQwPS0tJQX1+P1NRUr8fa2tqwf/9+lJaWRnTi7InccMMN+Pnnn/H1119HeyhR47rrrsOxY8fw3//+N+C2dCwShDbry2ox9+Xv0D83GZ/fOVW+/6Oth3HbW1sxqX8Wll5/ahRHSEQKf/O3GgrTEDL/+Mc/cOaZZyIpKQmffvopXn/9dTz33HPRHlZUqK+vx7Zt27Bs2TJDQoQgCH140zPfBFaeM0IJrASJEUJmw4YNeOSRR9DY2Ii+ffviqaeewvXXXw+AlemWl5drPu/FF1/EFVdc0ZlDjTjnn38+NmzYgBtvvNFv7xaCIAKjlzOSKOWMUAIrQWKEkHnnnXd0H1u+fLncyt2XvLy8SA0palAZL0GED73SXuozQnBIjBCG8NfFlCAIwh98xV69BFYSIwRV0xAEQRARRT9MQ9U0BKPbiJEuUBREdHMi2c2WILoydr0EVu6MON10Du/hdPkwjcVigSAIOHbsGHJyciLapIsgtBBFEQ6HA8eOHYPJZJK7uhIEwXBKzohFJ4FVFAG7ywObxdzuuUTPoMuLEbPZjN69e+PQoUM4cOBAtIdD9GASExPRp08fzeZqBNGT0SvttanESZvTTWKkB9PlxQgAJCcnY8CAAbrVHgQRacxmM+Li4siZIwgN9HJG4swmxJtNcLg9aHW6kR6FsRGxQbcQIwCbDNTL1RMEQRCxgVxNY24v1m0WSYxQRU2PhvxkgiAIIqLoOSOAksTaSovl9WhIjBAEQRARxe5PjEh5Im0kRno0JEYIgiCIiMITWC3m9lMOT1ptdVBpfE+GxAhBEAQRUZx+nBFZjJAz0qMhMUIQBEFEFL3SXkAJ05AY6dmQGCEIgiAiCk9gtfpJYG2japoeDYkRgiAIIqI4/eSMyAmsLhIjPRkSIwRBEERE8VdNoySwkhjpyZAYIQiCICKK/z4j7D7KGenZkBghCIIgIoq/0l5KYCUAEiMEQRBEhJHbwftrekZhmh4NiRGCIAgioshhGq2mZ9QOngCJEYIgCCLCON0iAP/OSKuTOrD2ZEiMEARBEBGFh2niTFqr9lI1DUFihCAIgogwLskZ8dtnhMI0PRoSIwRBEEREcXkkZ8TsxxkhMdKjITFCEARBRBSeMxJn0m8HT2Gang2JEYIgCCKiOA0slEdhmp4NiRGCIAgiovCcEa0wDTU9IwASIwRBEESEcfrJGfHXDl4URfxn8yF8t682sgMkok5QYmTx4sUYP348UlJSkJubizlz5mD37t1+n7NkyRIIguD1Y7PZOjRogiAIomvg9ogQmTECi0bOiF5pryiKuOe9n3DXuz/ipjc3Q+QvQnRLghIjX375JebPn4/vvvsOq1atgtPpxFlnnYXm5ma/z0tNTUVlZaX8U15e3qFBEwRBEF0Dni8CABY/Tc/sLg88HkVwbKmow7ubDwEATrQ4cazJHuGREtEkLpiNV6xY4fX3kiVLkJubi82bN2PKlCm6zxMEAfn5+aGNkCAIguiyqMWIv6ZnABMkvLqm7GiT13YHalqQm0KuenelQzkj9fX1AIDMzEy/2zU1NaG4uBhFRUU4//zzsWPHDr/b2+12NDQ0eP0QBEEQscN3+2qxqzLwuZknrwLaTc/UYkSdN3K4rtVruwM1/h14omsTshjxeDy4/fbbMWnSJAwfPlx3u0GDBuHVV1/FRx99hDfffBMejwcTJ07EoUOHdJ+zePFipKWlyT9FRUWhDpMgCIIIMwePt+Cyl77DrCe/htvjP5eDJ68KAmDWcEbMJkFes0YtRirrvcXI/loSI92ZkMXI/PnzsX37drz11lt+t5swYQLmzZuH0aNHY+rUqXj//feRk5ODF198Ufc5CxcuRH19vfxz8ODBUIdJEARBhJmdKkdkr084xRe5FbxG8ipHLu91uOT7jtS1AQCGFqQCIGekuxOSGFmwYAE+/vhjrFmzBr179w7quRaLBWPGjMHevXt1t7FarUhNTfX6IQiCIGKDfccUYbD14Am/2/KcEYtGWS8nScoTabYrzsgRyRmZ2C8LALCfxEi3JigxIooiFixYgA8++ABffPEFSktLg96h2+3Gtm3bUFBQEPRzCYIgiOiz52ijfPuHijq/28qt4DXyRThJVlZL0Sw5I6IoolJyRib1zwYAlNe2UHlvNyaoapr58+dj2bJl+Oijj5CSkoKqqioAQFpaGhISEgAA8+bNQ69evbB48WIAwKJFi3Dqqaeif//+qKurw9///neUl5fj+uuvD/NbIQiCIDoDdWhm68E6v9vyRfL8OSOJXIxIzkhdi1POHxlfygokWp1u1DY7kJ1sDXncROwSlBh5/vnnAQDTpk3zuv+1117D1VdfDQCoqKiASRUbPHHiBG644QZUVVUhIyMD48aNw7p16zB06NCOjZwgCILodDwe0UuM7K5uRIvDhcR47enE5WeRPE6ylYdpmDPCQzTZyfFItsYh1RaHhjYX6lpIjHRXghIjRiyytWvXev39+OOP4/HHHw9qUARBEERscqS+FS0ON+LNJggC6w1ytMGOkmzt6cTBc0bi/Dgj8d5hGp68WpDGHPeMpHg0tLlwosUZtvdBxBa0Ng1BEARhmPLaFgBAn6xE5KQwl+J4i0N3eyPVNMlymIaJkaoGJkby01iTs/TEeADAiWb9/RBdGxIjBEEQhGEa25g7kZFoQWYSEwnHm/yJEf1F8jiJPtU0XHRkJ8fL+wJYLgnRPQkqTEMQBEH0bBrbmHuRZI1DkpS+cdyPY+H0GMkZ8XZG+OtxRySDOyN+HBiia0NihCAIgjAMFwxJ1jhYpc6ptX7EiMtInxG5tJdX07DXy5RESLrkjFDOSPeFxAhBEARhmCZJjCTHxyE1gU0hx5v1V9RVmp7pOyNKmEZyRiTRwUUId0bqyBnptlDOCEEQBGGYJimvI9kWh0wpTuPPGVGanuk7IzxM0yJV08jOSJJ3zgiFabovJEYIgiAIw6jDNFk8gdVfmMZjwBmRxEiTTs6IXE1DYZpuC4kRgiAIwjBymMZqVqppjDgjGiv2cnjTsxaH0oEVUDsjFKbp7pAYIQiCIAyjiBELMqXS21o/pb3GckYUZ8Tucsv7oATWngOJEYIgCMIwSpjGbCxMw5ue+REj6tJe7oqYBCDFxu7PSFKcEVosr3tCYoQgCIIwjOKMxMlhlFanG61SiMUXZxBNz1rsbjlJNSMxHiYptMMTWJ1uUS7/JboXJEYIgiAIw6jFSLI1Tu4fotcS3hVM0zOHS+7mykMzAJBgMSNe6mkSqCV8XYsD68tqyUHpYpAYIQiC6CSO1LWivLY52sPoEOpqGkEQAraEd7qMNz3ziEBlPVuXhr8uAAiCILsj9a3+80YW/W8n5r78HR5f9YuRt0PECCRGCIIgOgG3R8SFz6/DeU9/g/ounIjZ1KY4IwCQlsBEQkOb9nvi7eD95YwkWMzy7UMnWgEo5bycFBvbD29Hr8f7PxwGADz1xV4cPN7id1sidiAxQhAE0QkcqG1GZX0bGttc2Ha4PtrDCQmPR8nZ4G6GIhK0xYiRhfJMJgFJUt7IoRNMQGT6iJFkn14kWoiiKL8OALy3+ZD+myFiChIjBEEQncDPlY3y7a4qRlqcSvIor3Thvxt0HAuXAWcEUBqfHZDCWFnJvs4IFyP6rlJ9q9MrwfVwXavffRKxA4kRgiCITmBXZYN8e/uRrilGeIjGbBLkRfIChU/kaho/Tc8AxfnYXcVEW++MRM3Hm/yEaXiIh1Ml5Z8QsQ+JEYIgiE7g5ypFjOzoos4ID5EkxZshCExccMdCL0xjpOkZoIgN7rD0ykjQfLzRT5jG1wmprCdnpKtAYoQgCKIT2KUK0xyobdFN+IxleCUNd0MAIIWLBL0wjdz0zL8z0ifL2wnp7StGbMadkSEFqQBYZQ6V+HYNSIwQBEFEmIY2p3zVzvtn7Klu9PeUmKRJ1X2VkxJAJCir9vqfbgblpXj93SvdW4ykGEhgPSyJkZOKMwCwtW78OSlE7EBihCAIIsIca7QDYBN3SVYSAKDGz3ousUqTqscIR84Z0Uks5av2BsoZGZiXLN/OSbHCpir3BYw6I6wSp39uslxyTHkjXQMSIwRBEBGGT6CpNouhlW5jlWa7d48RQJ0z4j+BNVDOyACVM1Lo44qwfTJx4dcZkdynXukJKEizAWCN5ojYh8QIQRBEhFEvLteVxUiLVDabGK8O0/CmZ/7DNIHESHGmkjOi5aHIzogfMcIX2ctJsSJfEiPkjHQNSIwQBEFEmEaVo2BkpdtYxS61drfGtc8Z6UjTM/a4Mh21ONoLDiM5I3wMybY42RmpJDHSJSAxQhAEEWHkFupdPExjdzFnhPcYAQKHaZSmZ/7FCABMH5wLALh6Ymm7x5IC9BkRRVEWKinWOOSnslAPOSNdg7jAmxAEQRAdodnBnRElTFPbFcWIU3JGLIoYSQ3QDl5pehb42vepuWOw7VA9Ti7NbPdYoD4jLQ43JN2DZFuc3MFVbzVhIrYgZ4QgCCLCNKoWl5MnyWZ7NIcUEg63fpimzemRhYcaozkjAPt8JvTLglmj8iZQCTF3RUwCW3iPl1B35UUJexIkRgiCICJMs6okNkNaAO54Fyzt5c5IvCpMo66s0QrVuORqmsBhGn/w/bQ63fJrqlELPkEQkJ7APue61q73OfdESIwQBEFEGHUuQ1aSFUDXDB9o5YzEmU1ydY1WqMZo07NAqHubNNvd7R5v8ukOy52ROnJGugQkRgiCICKMksAah0wpTNPm9GhWjcQyWtU0gP8kVt70zBKg6Vkg4uNMsgjSarDGP2M+FlmMtDqpJXwXgMQIQRBEhFF3Lk2KN8thjtouFqpxuNqHaQB1r5HIOSNsP/rlvU2SQOHhnHQpHOZwedDmbB/WIWILEiMEQRARpsnunc/QVXuNaIVpAP/OiDNMOSOAIjS0klgbVe4TwFYW5i3oKW8k9iExQhAEEWGUfAY2UcpJrF0sb0QJ03hPHf5EgiuIappAcKGhVd7b5NOqXhAEOVRzopnyRmIdEiMEQRARRg7TxLOJkpf3nuhqzojcZ8RnETtJADRr5MDIC+WFwRnhn58/Z4QLPgDyYnnkjMQ+JEYIgiAiTJNPCIE3Cmto7VpX7LzPSLyPy5Hkp1W7nDNioOlZILjo0Ur89a2mAZS8Eeo1EvuQGCEIgogwviGE1AT2W29xuVhFzhmxaIdpmjXFiLaACYVEeT/tS3vVfUY46QlKRQ0R25AYIQiCiCBujyivdiuLkS7qjMhhGp2cES2R4JKracKRwGqW9hM4ZwRQnBHqNRL7kBghCIKIIOo8CjlMk6BfChvL6PUZ0QvTiKIoh3bCkcCaGM9zUzSanqlW7OUovUYoZyTWITFCEAQRQXi+iMUsyJN4qjRhNrR2rTCNQ7eaRtux4Cv2AuEJ0yT5CQepu9xyeJiGckZin6COjsWLF2P8+PFISUlBbm4u5syZg927dwd83rvvvovBgwfDZrNhxIgRWL58ecgDJgiC6Eo0a4QPuq4zot1nRM8ZUS+cZ4kLRzWNJHo0Elh9+4wA1BK+KxGUGPnyyy8xf/58fPfdd1i1ahWcTifOOussNDc36z5n3bp1mDt3Lq677jr88MMPmDNnDubMmYPt27d3ePAEQRCxTqOq+yon1U/H0lgmUJjG17FwuhRnJBxhGkPOiKqaJk3KGTnRxfq59ETiAm+isGLFCq+/lyxZgtzcXGzevBlTpkzRfM6TTz6Js88+G7/73e8AAA888ABWrVqFZ555Bi+88EKIwyYIgugatEr5DXwxOUBVTdNVwzQ61TS+zohD5YzEdXBtGgBIksJBLVo5IxoOFO850tWqlnoiHZKq9fX1AIDMzEzdbdavX48ZM2Z43Tdz5kysX7++I7smCILoEjg03ISu6Iy43B45B0Svz4hvNY26rFcQwtj0TMsZ0Sjt5Z9zk8bCekRsEZQzosbj8eD222/HpEmTMHz4cN3tqqqqkJeX53VfXl4eqqqqdJ9jt9tht9vlvxsaGkIdJkEQRFSxaywuJ+eMSCvKhmOijjRql6O9M8KEll7OSDjWpQEU0dPiI3ocLkUoJagdKD9r5hCxRcjOyPz587F9+3a89dZb4RwPAJYom5aWJv8UFRWFfR8EQRCdgUNjQuZX7B5Ru0w1FrGrVr7Vd0ZcEEUlT0QWI3HhKdzUS5RtVX2G6nAYzx9pbPMeFxF7hHSELFiwAB9//DHWrFmD3r17+902Pz8f1dXVXvdVV1cjPz9f9zkLFy5EfX29/HPw4MFQhkkQBBF1HLIzokySNotJFiddpfEZF1VxJgFxOmLE5RFlJwgAHK7wLZIHKNU0vu3gW51ueWzqffGcEbdHlLchYpOgjhBRFLFgwQJ88MEH+OKLL1BaWhrwORMmTMDq1au97lu1ahUmTJig+xyr1YrU1FSvH4IgiK6ILEZUk6QgCF0ub4Q7I/EaLgfP5QC8K13C2Qoe0M9N4eJEHaIBmEtilhJnKVQT2wR1hMyfPx9vvvkmli1bhpSUFFRVVaGqqgqtra3yNvPmzcPChQvlv2+77TasWLECjz76KH7++Wfcf//92LRpExYsWBC+d0EQBBGj8AnZtzeHkjfSNSZJvR4jAGA2CUiw8MZnilAIe86IJHocbo8s8gCluibRR4wIgiAntDZ2EdHXUwlKjDz//POor6/HtGnTUFBQIP+8/fbb8jYVFRWorKyU/544cSKWLVuGl156CaNGjcJ7772HDz/80G/SK0EQRHfBoZHACqi7sGpPkhsPHMfv3v0R9TESxtHrMcLRyucIZyt4AEi0KvtWh2rapBAMF0RqqLy3axBUNY2RBKC1a9e2u+/iiy/GxRdfHMyuCIIgugUOnVCFvy6sHo+Ii19g7Q8ykuLxh3OGRHiUgbHr9BjhpNjiUNNk9+qO6nSHN2fEYjYhPs4Eh8uDZocb6Ynsfu6MJMS3n9JYEmsrhWliHFqbhiAIIoLwSdy3Hbq/lXu/2Vsj395xpD6CozMOD9Po5X8kaZT3Ol3hraYB1CsEK/vRC9MAijNCYZrYhsQIQRBEBFESWL0nSrkLq8YV+7LvK+Tbu6saY6IsNZAzwvM5tBNYw9dHhQsO9X5anVICq0aYhnqNdA1IjBAEQUQQ/ZwRfWdk22HFDalpcuDg8dZ223Q2vJpGL2dEy7EId86I936URNlWB9uPbzUNoO41Qs5ILENihCAIIoLI7oBeNY3PJOnxiKhuaAMA5KVaAQBbKk5EepgBcehUBXGUBFZ1NU14c0YAlTPiUIdpXF6PqUkhZ6RLQGKEIAgigihr0+hV03hPkrXNDrg8IgQBmDGELaWxszL6S2LYpYoVrT4jgEqMtLUP04RTjGit3Ms7sPqrpiExEtuQGCEIgoggwVbTcFckO9mK4qxEr/uiiV1HVHH4+jTe1TTcFQpfzoicm6JqAc+7q/oL03SV5nI9FRIjBEEQEYQ7I76Nv/Q6sFbVM+GRn2pDXqoNQKyJkSD6jLg6xxkxVk1DzkgsQ2KEIAgigtg11qYBVNU0PmGaKjlfRBEjRxvsiDZ64SaOVgJrJHJGeAlxi0aYJlG3zwglsMY6JEYIgiAiiG4Cq44zwl2Q/DSrLEaqGtqiXt4r9xkJkDOiVdobCWdEnSjbIoVpbJQz0mUhMUIQBBFBdEt7E5TSXrXQUIdpclNYNU2Lw+0V/ogGdp33wdEK00Siz4jWyr2tfsI01Geka0BihCAIIoLoJrBKzohH9E7GVIdpkqxxSJEm+eooh2qcAcSInMCqciwi0WdES/TwpmfaOSMUpukKkBghCIKIIHq5FjaLSU5qVTc+U8I0LESTl8bzRqKbxOrUEVUczQ6sLilnJIzt4Pl+WlQCjt8OFKaJdqiL0IfECEEQRATRqygRBEEzb4Q7IPlSvghvfFYVZTHiCJCMmmzTD9NE3BnxW03DPmOXR0Sb1EWWiD1IjBAEQUQQh04CK6DOG2ETq8vtQb3kkmQlMxGSl8LLe6McpvHzPgC9apoIrE1j1cgZceqLkaR4M0zS7ilUE7uQGCEIgoggegmsgLoLK5sk61ThmjRJqOTGSK+RQC6HXE3jcMPjYS5KZ61N4y9MIwiC/BytRQmJ2IDECEEQRATRS2AF2ndhrWthv1NtcTBLl/O8ouZYY4w4IzouB5/wAaXUNqJr0xjsMwJQEmtXgMQIQRBEBPHvjHiv3FvX4gAAZCTFy9tkSrdPSI9FC4fLv7CwxplkAcXXp+EVOOFMYPUNB4mi6DdMA1Cvka4AiRGCIIgI4q9zqdyFVZokT0jOSHqiIkbSEy1ej0WLQGEaQRDkHiA8uTQiOSO8msbJwkEOtwduKSykFaYBFNFHYiR2ITFCEAQRQfzlTeg5I+lS+AYAMiRhUhdlZ0QWI35cDl/XIpI5I6LIEldbVSW+gZ0RCtPEKtoBNoIgCKLDuD2ifNXut5rGJ2ckI7G9GIl+mCawy+HbEj4Spb02iwkmgTeLc8El56UIuvuhME3sQ84IQRBEhOCTMRComoaHaSRnRB2mSWLCpM3pQZvTjWhhRFj49gCJRAIrCwcpFTVc+KgTaH2hBNbYh8QIQRBEhODruQAGq2laec6I4oykWOMQJyWGRtMdCdT0DFCFaRw+OSNx4csZAZReI812FxolMZLkV4xQaW+sQ2KEIAgiQjhUYsSiEd7w7cAqV9OonBFBEJQk1uboXdkbc0Z4AitzcPS6z3YUdTgoOGeExEisQmKEIAgiQqi7rwqChhhJ8AnTNLd3Rtjf0U9iDdSBFeicnBHAe30aXkbsX4xQAmusQwmsBEEQEUJJ+tSejNs5I63tS3sBJaE1muW9zgDvBWhfTROJnBFA7cC45B4jfG0cLSiBNfYhMUIQBBEh/DU8A9Rr0zghiqIqTKPtjMREzoif/I/2CayBBUwoKM6IS24F7y9nRO4zYidnJFYhMUIQBBEhAk3GfJJkZapuWWxk6DgjsRCmMZTA6humCXMCqyJ63GiR9pViKExDzkisQjkjBEEQEcIewBmxWUxyYuvRhjZ5ifs0H2dE6TUS/QRWY2GaSCewSiv32l1oclACa3eAxAhBEESECBSmEQRBdkfKa1sAsKob36v8WAjTdKTPSKTCNE0Ol5zAaqS0t7GNhcOI2IPECEEQRITwt2Ivh+eN7DnaCADITbG1q7xRwjTRcUZEUVQlo+qHXJKt2mvTdEZpb4qBBFanW/Tq/ULEDiRGCIIgIoTDwKq1vAvrnuomAEBuqrXdNtF2RhyqTrL+3otaJHg8IlyewAImFNISFHHWZKDpWVJ8HLi+a6Dy3piExAhBEESEkFfsNeSMMDGSl2Jrtw3vO1LfGp2JlLsigH+XRx2mcXqMCZhQyExSxFmjgT4jJpMgP055I7EJiRGCIIgIYaRRGM8Z2cvFiIYzkpbgvbpvZ+P06iRrrJrGqIAJBXVH2mYDCayAqryXxEhMQqW9BEEQESJQAiugdGHl4Ybc1PbOCBcj9VI/Eq1urpGEiyqTAJhNRlbtdRsWMKGgdkas0mfrr+kZQF1YYx1yRgiCICKE3UgCq827jDfPjxhxukW5yVdn4jDg8ABAslTl4nB7ZMcikIAJhQxVDg1fByeQM0K9RmIbEiMEQRARwpgz4i1GclPah2kS483yyr3RyBsx2tad9/8AgOoGu3Rf+A34DMkZaXN6UNPE9hNYjPAwDTkjsQiJEYIgiAhhpOlXqk94QcsZUa/cGx0xYqyte5zZJIdNjja0AQgsEkIhKd7crkKHnJGuDYkRgiCICGHEGfFdFE8rgRVQHJRoiJFgOqlyUVAVQTEiCEK7lvmBHBguRhpIjMQkJEYIgiAiBHcUrH7EyJSBOV5/p/mEbXzvj6YzYmSNGS4KIhmmAbzX74mPMwXMZ6EwTWxDYoQgCCJCGEn8TEuw4JELRwIAhhak6lbKyGIkCl1YjeaMAGoxEjlnBAAykhTR5m+RPHkb7oy0kjMSiwQtRr766ivMnj0bhYWFEAQBH374od/t165dC0EQ2v1UVVWFOmaCIIgugRymCTCJXzK+CMuuPwXPXTFWd5tYcEaM9AvhwqCqPsJiROWMBCrrBcgZiXWCPkqam5sxatQoXHvttfj1r39t+Hm7d+9Gamqq/Hdubm6wuyYIguhSBFq1V83E/tl+H4+mGAkmZ4RX1FQ3tkl/R8oZUcTIyN7pAbdPpQTWmCboo2TWrFmYNWtW0DvKzc1Fenp60M8jCILoqgQziQciPZpiRF7wLoicEckZ8beAXUfgiwcCwBmDA1/cyh1Y7eSMxCKdljMyevRoFBQU4Mwzz8S3337bWbslCIKIGkabhRkhmtU0way+K7eEl5qzqXuPhJNmu9L8bdqgHD9bMqi0N7aJeDv4goICvPDCCzjppJNgt9vxyiuvYNq0afj+++8xdqx2fNRut8Nut8t/NzQ0RHqYBEEQYccZRJgmEDGRM2LgffiGZSIVphneKw0AIAjty6O1SKG1aWKaiIuRQYMGYdCgQfLfEydORFlZGR5//HG88cYbms9ZvHgx/vKXv0R6aARBEBGFOyP+Vu01ChcjddEQIy5WTWMkgdVXfBipdAmFX4/pBY9HxGkD/OfayONQrU0TjfV9CP9EpbT35JNPxt69e3UfX7hwIerr6+WfgwcPduLoCIIgwoORpmdGiebKvY6gwjTeYZlIOSMmk4BLxhehMD3B0PZcjDjdopxYTMQOUVm1d+vWrSgoKNB93Gq1wmrV7kJIEATRVQirGImBdvCWEMI0kSrtDZak+DgIAiCKQEObEzZLZHJZiNAI+ihpamrycjX279+PrVu3IjMzE3369MHChQtx+PBh/Otf/wIAPPHEEygtLcWwYcPQ1taGV155BV988QVWrlwZvndBEAQRg9iDcBQCkZ7A8iLqWzs/zOAMoprGt4NsrIgRk0lAsjUOjW0uNLa5kJsS7RERaoI+SjZt2oTTTz9d/vvOO+8EAFx11VVYsmQJKisrUVFRIT/ucDhw11134fDhw0hMTMTIkSPx+eefe70GQRBEdyQSYRq3R0Szw92pkzzvwGokZ6RPZqLX35EK04RCqs0iixEitgj6KJk2bRpEUdR9fMmSJV5/33PPPbjnnnuCHhhBEERXJ5jOpYGwWUyIN5vgcHtQ3+rsVDESTL+Ukuwkr7+NdEftLJSW8NRrJNagtWkIgiAiRDidEUEQ5F4jdS2ODr9eMATTZyTVZkGWqjtqrIRpAOo1EsuQGCEIgogQXIz4W7U3GNIS2GTa2UmssjNiYNVeAMhPs8m3Y0uM0Po0sQqJEYIgiAgRzg6sgNLcKxxhhnVlNfj4pyOGtg023JSbolRDJsbHTtUKOSOxS+xIVoIgiG5GONemAcLXhbXN6cblL38PAChIS8C44gy/2zukBFaj7yNHJUZiqbmYuvEZEVuQM0IQBBEhwpkzAoRPjGypOCHffm/zoYDbB5MzAniLkViCL5bXQM5IzEFihCAIIgKIoqiEaWLMGVm3t1a+/b8fj6DF4X9yDmZtGgC4akIJUqxxOHekfnPLaEDr08QuFKYhCIKIALw3BxA+Z0SppumgGCmrkW832V3YeOAEpg7UX/lWCTcZC7nkptqw8Y8zwpa4Gy4oTBO7xNaRQhAE0U3grggQzmqajjsjLQ4XfjxUDwAYWpAKACivbfb7nFD6pdgs5pjKFwEogTWWITFCEAQRARyqxdjClcCaHgYxUlXfBrdHRLI1DpP6ZwEAymtb/D7HHubcl2jBc0Ya7eSMxBpd+8giCIKIUbgYMZsEmE3hcQjCsXJvbTNrmJadHI/iLNYtNZAzEu5E3GihdGAlZyTW6NpHFkEQRIwiT+BhckWA8KzcW9tkBwBkJVtRnMXWkTkQwBkJdyJutKCmZ7FL1z6yCIIgYpRwNzwDwpMzUtPEnJGspHiUSM5IxfEWeDz6a44pHVi79pShzhnxt8Ya0fl07SOLIAgiRolEaEMtRvyJB3/UcjGSbEVBmg0WswCHy4Oqhjbd5/AEVmuXd0aYGHF5RLQ5PQG2JjqTrn1kEQRBxCiRCG1wMeIRgaYAvUH0qG1mYZrs5HjEmU3oncFDNfp5I90lZyQpPg68wIdCNbFF1z6yCIIgYpRITOA2i1kuE64PsddIrSpMAwB9MpkYOXhcP2+ku4gRk0mQF+6jLqyxRdc+sgiCIGKUSCSwAh3PGzmmSmAFgMJ0tsJudYNd9zmRyH+JFqmUxBqTdP0jiyAIIgZxuN0Awj+Bd7S8l1fTZEtiJDeFixH9nBF7mBf8iyZyeS85IzFF1z+yCIIgYhCHiyWYRkqMhOqMqPuMAEBuKhMl/pyRUDqwxiqpYejVQoSfrn9kEQRBxCCR6s3BxUhdCJOp0+2R17XhYZo8yRk52qjvjPCQU6ytNRMK4VpskAgvXf/IIgiCiEEilfTZkcn0hOSKmASltXxeqv8wjcvtAa8i7g45IyRGYpOuf2QRBEHEII4I5Vl0pAsrb3iWmWSFSWpRnyeFaY412uHW6F2iXvCvO4kRCtPEFl3/yCIIgohBHC6WwBru0EZHruwbpAqS1IQ4+b6sZCtMAutdwpNb1URiwb9oQs5IbNL1jyyCIIgYJFLlsB2ZTFsdTCAlxStixGwSkJOin8TK34cgAHFhWvAvmpAYiU1IjBAEQUQAp1uqpolUn5EQmp41S11bE+PNXvf7yxtR90sRBBIjRGQgMUIQBBEB7DGYwNoiOSO+YkTuNaJRUdNduq9ySIzEJt3j6CIIgogxYrGapsUuOSPWOK/7eRJrdb2GGOlGPUaAjiUAE5GjexxdBEEQMUakqmnSOzCZtjglZ8Ti7YzwnJFjUrWNGmeEmrdFC3JGYpPucXQRBEHEGJFqBy93EG1zwqNRiuuPFruUwOrjjMhipFErgTUy7yNacDHS2ObSLGUmokP3OLoIgiBiDO4oRKq0VxSBRntw66vwnJEEnZyRYxo5I/YILfgXLfjnB1CvkViiexxdBEEQMUakci2scWbYLOw1g62oaZGqaZLidcI0Ws5IN0tgtZhNcgIvhWpih+5xdBEEQcQYkZzEQ817UJwRnTBNkx2i6B26iFTuSzShvJHYo/scXQRBEDFEpEp7gY6IEW1nhK/g63SL7V5T7pfSTZwRgMRILNJ9ji6CIIgYgodpIuEopCcw8RC6M+ItRqxxZnmC9g3V8ATW7rBiLyeVxEjM0X2OLoIgiBiCr00TCUch1Mm0WaMdPEcvb8TRzRJYAXJGYpHuc3RFmf9sPoST/vo5vvzlWLSHQhBEDBCpdvBA6JNpq047eADISVbyRtR0twRWAMiQerXUtbTvq0JEh+5zdEWRXZUNuOvdH1HTZMcTn/8S7eEQBBED8Ek8EuENLkbqWoObTJulPiO+HVgBfWfE3g0TWDMSWZjrRAjr+xCRofscXVHk6S/2yLd3HGmQV8YkCKLn0hnVNMH2yWh1aq9NA+iLke6YwJouixFyRmKF7nN0RZE91U3ybYfLg2/31kRxNARBxAJyn5GIiBHmbASdM2L3E6YJlDPSjcSIEqYhZyRW6D5HV5TweESUH28BAEwblAMAWLP7aDSHRBBEDBDJ/hz8yj4YMeL2iHLIJVErgVUvZ4S3g+9GYRpyRmKP7nN0RYnqxjY4XB7EmQScP7oQALC7qjHKoyIIItpEso16KAmsvMcIQM4IOSOxR9BH11dffYXZs2ejsLAQgiDgww8/DPictWvXYuzYsbBarejfvz+WLFkSwlBjkwM1zBXpnZGAAbkpAIB9Nc3RHBJBEDGAM4JhmlBKe3kum0nQTqrtSaW9GUnkjMQaQR9dzc3NGDVqFJ599llD2+/fvx/nnnsuTj/9dGzduhW33347rr/+enz22WdBDzYWqTjOhEefrCSUZicBAI43O6hkjCB6OJ1STRPElT3vMZIYHwdBENo9zsXI8RaHLKQAwNEtE1gVMUcr98YG7QOHAZg1axZmzZplePsXXngBpaWlePTRRwEAQ4YMwTfffIPHH38cM2fODHb3MceBWuaMlGQlIskah/xUG6oa2rCvphlj+8RHeXQEQUSLyCawssm0sc0Ft0eE2dReXPjS4qfHCABkJsbDbBLg9oiobXIgP42t5NsdwzS8g60osook7pQQ0SPiR9f69esxY8YMr/tmzpyJ9evXR3rXnUJ5LXNGirOYK8LdkX3HKFRDED0Vt0eUr7gjmTMCAI1txtyRFod+WS8AmEyCvEaNOlQTqdWHo0l8nAkpUq8VCtXEBhE/uqqqqpCXl+d1X15eHhoaGtDa2qr5HLvdjoaGBq+fWKVCqqQpzkwEAPTN4WKkSfc5BEF0b7ibAACWCDgK8XEmWVQYzRtpUYVp9FBW722T7+Nt7SPxPqJJehITdCRGYoOYPLoWL16MtLQ0+aeoqCjaQ9LlRDM7EWRLX+K+OckAyBkhiJ6MWoxEylEItqKmxU+PEY5c3qt2RnjuSzdyRgBVF9ZmqqiJBSJ+dOXn56O6utrrvurqaqSmpiIhIUHzOQsXLkR9fb38c/DgwUgPM2R4B8RUG7vaKM1mDsmBWhIjBNFTcagSQC3mwPkcoRBsEqvsjGi0gudoVdR0xw6sAPUaiTWCTmANlgkTJmD58uVe961atQoTJkzQfY7VaoXVao300DqM2yOiUbra4CeGXulMjFTWt+k+jyCI7o06eVWrciUc8IqQOsNhGskZsfhxRjTESHdMYAWo10isEfTR1dTUhK1bt2Lr1q0AWOnu1q1bUVFRAYC5GvPmzZO3v/HGG7Fv3z7cc889+Pnnn/Hcc8/hnXfewR133BGedxBF1OtC8Lr/gnSWgV7f6pRbLxME0bPojNBGplQBctynY6oeijNiIEyjek17N0xgBdSL5ZEzEgsEfXRt2rQJY8aMwZgxYwAAd955J8aMGYP77rsPAFBZWSkLEwAoLS3FJ598glWrVmHUqFF49NFH8corr3SLst4GKYs9Md4st3xOtVnkLO3Keu0EXYIgujed4SbIYsTglX1zgGoaAMhJYRdTamfESK5JV0T+/JpJjMQCQYdppk2bBlHUbxKj1V112rRp+OGHH4LdVczDE8fUZXYAUJiegN3VjThS14b+UldWgiB6DpFcl4aTmcgnU2POSKsUpkkyUk2jEiPc4U3yk2vSFcmSyphrSYzEBN3Ld+tk6uXkVW8xwkM1R+rIGSGInoi8uFwnOCNGq0G4M5Lg1xnRECPS87qdGJE+v1qDYS4ispAY6QANrd7Jq5zCdFYldISSWAkiNmmuATYvAWr2RuTlHa7IV6DwrqG1hp0RSVQYcEaaHW40210QRVHljHSvME2WlB9Dzkhs0L2kbicjOyO+YiSNnBGCiFl+eBP45C7A1QaY44FfPQ2Muiysu+iMrqVZSWwyNeyMSKLCnzOSFG9GgsWMVqcbNU125KXa4JI6yXZfZ4TESCzQo52RD384jKdW75FbugcLT2BNTfD+knJnhBJYCSLG2LoM+Gg+EyIphYDbAXz2B7ZISRjpjATWDKmDqNEr+1YnD7foixFBELxCNeqKQH+OSleEOyNNdhfapM+GiB49Woy8tu4AHlv1C3ZXNYb0fL0E1oI0KUxTR2EagogZmo4Bn/4/dnvCAuC2rUBcAtBSCxz7Oay76gwxIjsjLQ6IdRXAZ/cChzfrbi87Ixb/osJbjEh5JhazocX4uhKptji5IR1V1ESfHi1Ggm2n7IueGOnFc0bqWv1WHhEE0YmseRCw1wP5I4EzFwFxVqBoPHvswDdh3ZWcwBrBMA13RoaJeyG+OA1Y/wzw5oVA/SHN7VscgZ0RQOk1crTRjmZH96ykAZgLlEmhmpihR4uR9A6KkQadapq8NPZltrs8pLgJIhZoOQ78+G92++y/ASZpQi4+jf0u/zasu+sMZ8QaZ0aJtREvxz8KU2stu7P1BMuH0SDQqr0crTBNd0te5XB3yWgSMBE5erQYiZQzYo0zy19oCtV0cdwu4N+XA0+fBDRWB96eiE1+eIPliRSMAoonKveXSGLkQJjFCF/PJZJdS112PGN+FHlCHVrTBwLXrmT3l30BONufd4ys2gt4i5Eme+DeJF0ZudcIOSNRh8QIOu6M+IoRQF3eS0msXZrP/wzs/gSo3QOs+lO0R0OEgigCm15jt8ffAKjXiilknaTRfBRorg3bLiPujIgi8MldGO75BfViIjZNeAYoOhlIymVJuUe2tHuKvDZNAGckN0VpCc9zRpK7YZgGUFXUkDMSdXq0GEnv4EJJDW3sy+1b2gv4lPe21QMb/wm8cxXw2jnAj2+FPXufiADb/8Pi8AAAAfjpbeBI9+sk3O05uAE4sR+ITwaG/9r7sfhEIK0Pu13zS9h2GXExsumfwA9vwAMTbnHegiOmAiayuOvjE3byeES5miYYZ6Tbh2l4rxFyRqJOjxYjqREK0wCKM1JfUwm8PB345E5g54fsJPHBb4FvHgtt0ETncHgL8NECdnvS7cDgc9ntsjVRGxIRIj+9zX4PmQ3EJ7V/PHsA+91VxMiJclY5A2B57m/wlWcUavhkWjyJ/S5f5/WUNpdbvv4xmjNytLFNDtMkGnVGWuuALx5kY4xljvwAvH0l7tg2By9bHkVG9fpoj6jH06PFSEcSWEVR9CtGCtJsEODB7F2/A2r3sp4G0//ISgoBYN0zgIuswZiktgxYehHgbAH6TQem/wnoM4E9dmhTdMdGBIfbCex4n90eeYn2NtkD2e9wipFIVtOs/CPLfymZjG0lVwEAanhLc+6MVHwPeJTeGTxfBGBluv7IT1UWy+O9lJKN5oy8Ngv46hHdJNqYYOsy4JUzgV3/RbK9GmeaN+PG8juAT39PjnUU6dFipCM5Iy0ON9xSZ0LfpmcAK+89x7QB/dq2M3v4qv8CU37HSgpTCoHW48DuTzv2BmKZpqPALyvD9+V2OYCd/2WvG0kaq4E3LmC9JwpGAZf8CzDHAb2lEtBDG3rOCWvfWnaCbq2L9khCp/xbVmGSmA2UTNHeRnZG9oRttxFzRo7+DOz6LyCYgFkPy6vsys5I7hB2vnE2e/VOaVH1CzEF6BeSnRSP8+I2YCj2YX8NawhpqLTX7QSO7mS3NXJWwkbVduD934aWUF62hjmeHicw+Dz8OO01vO46Ex4IwPcvsB8iKvRoMZIurXoZihjhz7GYBc0rjYJUC+6Ok+zhibcqJzyTGRg9l93euiz4QXcFHM3sCmnZxUo5ZUfweIAPbwTeuRJ4fhJwSL+xU4doqweWXgjUlQMZpcAV7wFWadXlglGAyQI0H2OPd3eO7wPeuoKdnD+8SVuA1R9mgiWWxdnPn7Dfg2YxUalFBJwRZ6SqaTa9yn4POgfIG6bK75CqZ0xmJSlX5eK1OI3nfpi2voFn4p7AU5ZnsKe6CQCQbCRnZN9a5XbvkwNvHyovTAJ+egv4/P7gntdyHPjP9YDoBkZeBlz6JiwDZ+DPrmvwhGke22bln4Cju8I+ZCIwPVqMqJ2RYJuTya3gbRYIQvsrjdKaNSg1VeO4mAznKTd5Pzj0fPb74PexfSIPlVV/ZqEpAFizmF0xdYSNr7BkUoBVPbxxAVC9k8V9f1nZsdfmNBwBlpwHVG0DknKAK98HknOVxy02oGAku31wY3j2Gcv873bAwSYi7F6uTIKc+kPAi1OAf50PfPHXju2rsQr4+lHg4zvZAnbhQhQVMTL4PP3tuBipK9csiQ0FeyScEUcLS34HgJOuAQBkSwmYNeoEzN4nsd+HFTEid1INkC+Cmr3ACtalNktowN6j7Bgw5Izs+EC57Y5QQqhTVZ3YEuSxsnoRe07OYGD2k4AgIDeVfX5PtZwFz4CzmWPy31uUc1Zrnfc+iYhBYgSA2yPKiVpGqW/RzxcBgNQfXgYAvOmegapWny9yzmDAFAe01bFJsDthbwS2/Ev5u74C2PFh6K8nisBG9lni9D8CRaeyLpovTWM/yy4GThwI/fUBNr7nTgWqfmJC5P/+A2T2bb9d0ansd3l4u3XGHC3Hgf1fsdunzme/v/grC3cALFS27DJlMvj6H8Avn4W+v/euZRPFpn8CX4cxsbvqJ6DhMGBJAvpO098uORdIyABED3AsPFfFEQnTlK1mx356H6DvdABqMaLKP+sliRGVg2hkxV64HMB/rmO5UgCscMoL/gVMYPV4vI8B6TXCjrofTFKu/na+HN/HVmkGgHMfYxcXADIT4xFnEgAIODb1QSA+BTi0kTkob10BPFwM/K0P8N3zYXsLhDY9WozYLCb5ZBFsqEZvxV4AQNV2CIe+hwNxeMN1VvvVe+OsytVY9fagxx3T7F0NuO1sMj/tDnbfvg5UoBzewuzzuATglN8Cc/8N9JnI9sFpOR766+/6GHjvGhaiKRgNXLeKhWS0KJVyDvhE3V058A0AEcgexHKccoawHKf3rmVC86VpQPU2locxdA57Dr9iD5baMu8y1F3/C59buHc1+913qjz5aCIISmjjcHhyHewuAwmsdRUsGdXo8fvzcvZ78GzAxF6Xh2nqWpxwSsJBdkaO7WIhU0Bu6+7XGfn+BaByK2BJBADYBCcA9r8IGKY5ssXbqQhGjATz/y5brdxuqzP+vI3/BCAC/WcAJZPku00mQRZ0VWI2cOErLB9n54fAzx+zjdwOYMXC0HP8HC3AtveAhsrQnh8ODm4AvvqHckEBxJwr36PFiCAIsrMRbK8Rfz1GsOu/AICfbONxDOk47CtGACBvGPvd3cSIbIufy0QDwMJRobJ1Kfs9ZDZgSwUSM4FrlgM3fKFs4wnO1ZJxtAAf3cyuiEf/H3D9aiCzVH/74omAYGZXWXUHQ9unEY7vYw5BXUXk9uGP/V+y332nsjyL8x5nYrDsC2ZhNxxmYvO6lcCkW9m2v3wWmp3Nc4pKJrNJsL6CTYjhgIuRftMDb1s4lv0OU+Jlq5F1YF6YDKx7Wg6L+MXtAn5ZwW4PPke+Oz3BIi9gJ/fKSMlnzqvoYSIbBpwRRzPw7ZPs9nSluV88DHZg5a5IUg77bfRYcDuBFycDL5/B3JVA7PtSuW00sdrZCvzwJrs9/oZ2D+elKmvxYNDZwNy3WSh9yGzgt18DY64EIALvzGMh6IMbjO0XYBP+e9cwx+mJ4eF1/ozyy2fAknOBLx4AnpvIvscHvgEeGyKXiMcCPVqMAEp5b0OIzohmmGbX/wAAv2Sxk2A7ZwRQiZEdQe03pnE7gT3SSWnwecoiZLV7Q8sFcLYB299jt0dfrtwvCECvcUDWAGW/ofDzx+xknd6HxZD1Ehw5tlSgcDS7feDr0PYZiOZa4PVfAav/Ajwznp04Oht+wi+dyn4XTwCu+YQJht4nA6ffC9z4LZDVj03i6X1Y9caeVcHtx+NR5UBcCww4k92Wvj8dwt4IHPyO3e5/RuDte0li5HB4mtrxUtoEvUlcFJUreyNuzKENzJ1KyFDChWBX9ryL6LFGlVtoZhMsbx8Q0BnZ/DpzNjJKgHFXy3dbIZX2BgrTcMeC58MZFSMHN7A8rcObgMYAIeuW48BR1flSfZXvj18+Y591WpFyjKngFUlHeRLwwLNYFd2lb7I8sfMeZ8LE7QC+fQL492XG9gswJ5GLSI+Lfa/X/s348zuK28kS0N0OJvYbj7CcuyXnAo2VMRV+6vFiJNTyXkWM+HxJa8tYeZspDnW9mRg5rLU+Td5w9rs7iZGDG9jknpjFSmETMlh+DH8sWHYvZ6+X2lsJkagxS0LQE6IY4a7L6CsCCxEOzz3gCbXh5n+3AvWS6+Jq838lVbWNWa/htH+bjrLW9xC87Gz0Ggdc/TFw/Spg6j2scynAhCGfgHZ+GNy+DnzN3qstjVWHDJKu+Peu9v88Q6/9DTv5Z5Rq5//4wp0RVWijI8it1/V6eqjKbpGSH/gFeaVKv+ntjlXNvJE4JlB4IqnijOiMh4v+CQsASwJEMLeFixG/CaxtDcCRrez2oFnst9EwjTrkeXy//20rvvP+26gY4eJ22BxlgUQVPIn1aINO3yezBbjoNWDq79nfLbXGXBwA2CDlu834Cwt5AsDaxaxqxx2ioxsMB75m403MBu7cBYy/noWhOIlZkR+DQXq8GJFbwgcpRvRW7JVPGn0mIDs7DwD8h2lq9oQtgz/q7JEqW/rPUL70Raew3we/036OP354g/0edZnmSQQm6QQZype66ZjiAIyaa/x5Y/6PfZn3fh7+EsBjv0hxagG4TApflH/LxurLD28CL5zGrNf/XB+++C8/4ecOZWLSCDxvZPeK4EI1PEQz7Ncsp4MLvcofO15Vc0BKMu471dj2qQWs/4/o8Q4FhEjAFXL3q5w1I+/V161SkaNaS0YmTsqRcbFzi1JNoyEqGo4AhzcDEIAhv2ICU3q+FQ6YBNbEUZeD37Ny2YwSxa00ehzsV33WJwKJEamrLD9OjIgRl10JIQ35leYmuaqOs7qYLcDEW5S/3TrCRU1dBcutEkzA2HnApNuAs6TKs3VPAa+exaqXIgkvHhgyG0hIB859FPh/B4ErP4zsfkOgx4uRgjTWtn3Hkfqgnqe7SB6v7e8zAb0ypMXytMRISoGUwe/2vkrqynCbvr/KCuXJdMGu6XJ4MwtRCGYmALToiDNy8DsAIkvOzCg2/rzMvkqZ6P9uY2Wp4eK759jvQbNYXkDhGDY58kQ6jigq8X2AVfeEK5zD83v6nGL8Ob3GMQvc2cxEmhEcLcDOj9jt0Vew3yn5kmMoevesCAUeRiuZbPw5Iy5iv+X1iEJHCdPoiBF1mC9QRZ29SSnT1RBXms6IWXJGXMwZkfuMaI2H53kVnQyksAsoIY695iVjcvDR/NOQm+pHjHDhV3KanPwKZ0tg98DexCpXOIGcEd7ifpC0NIOrNfCF3L4vAUcjO9/yKiMfcnmYRs8Z4cQlKLeNiK3dUnim6BSW6wYwQXPhP5kbeHgz8NJUliMWCTxu5dzB3UsAsCaz7ysQU13Ae7wYmT6YlYet3FENj8fn6rK1jsVS1/6NhV9U6OaMHJLCEb3Hy+vTHD7R2r6PiSB0r1BN/WEpnit4x+gLRrPfR340fvXu8QCrH2C3R16qn1Rqkj77UHJGuANQPCH45079PSsXPfg98MavO95HBWAnZr6Gyqk3s9/8BMInC87RnazCyGxVhNrKP4VnHPxzUeUlBEQQlKtOo3kjZavZhJXeRxGsANDvdOnxDoir1jqg8id2u3iS3029OPUmdkyVf9thcccXpdMNb6gnYXs9y3HRo2I9CzmlFzP3wYfsFI2cEUlM8Ct43oFV06nhzgFffwmQnZHbpvbBiN5p+mMDFDFSfBpgUU3YrgBC4dBG7+Rzf86Iy8HCkgA7v/BQQ6CKGu7WDjxbrkDyhSewVvtzRgAWHhOkz8/PJF7X4mDzA88V4aErzoiLgJvWs9Cgo4l9dyPBsZ9ZiCY+mQlFNfz4CPQ/6kR6vBiZ2D8LydY4HG20Y+uhOuWBqu3A8xNZDH/tYpZMqIply03P1GKk5bjS7Kv3SbK12ep0a1frdCcxsleahHqfpFwFAKw9tdnKTrh6VwC1ZcCHNwPvXcdyID68kZUDmyzAlLv199kRZ6RCWhirTwhiJH848Ju1QEImE2AbXgr+NXzZ9T82OWf2U04c/Wew3+XrvIXGdmmtlQFnAjMWKeP4+A5WQuizLolhnK0sRAIE54wATFQA/idVNbukK7bBs5mY4fD3/Mtnob0HQPrfikBWfxZ+MUpqITD2Snb73Ws6FIbjOSOa68DUH2bJg4JZmdz85f1wR0DH5cnTurL3SWCVw0a+4sjjUYSROi8rzvv5ujjblGOmeIK3GAnkHvD9cjfFnzNydCfLf7GlM3fSls7u9xeqEUXlvDTgLN3N8qXzdFW9gYmZvz+X9nurbmjD6f9Yi7Me/QIeLuy1qrnSegFznmf//58/9u6fEi54nl6vscq5ksPDeG57zJT49ngxYo0z43TJHflsh2S5N1QCr89mJYwZJSwJU3R7lahqOiM8RJPVH0jMhM1ili3UDpf3OlpY19H6Q0G9v3b4O/CO7WZXtkYnFDV7dL70ZovyPrVKNusPseqRrUtZEt0XDygOwfnPsIoNPULNGXE0qybdIBwANTkDgRn3s9trH2b/n47wk1RVMuoyZXLOHcaEhrNZCXOJotLpctgFQFIWcJbkIv3wBishfPUs4KnRwa+1UvkTE3bJeewqPBiCEYZuJ/CL1LNhiE9n1OJJgDWNVXaEuighnwRCEZozH2LJ1211bEmD6p1Bv4TbI6LNKTUL03IieMglb6iyTETDYf0X5JOKjkDMk0Io1Q2qyTTOV4y4tMdTu5e91zibcnEEtMs50aVKOmYSs9kxYzIrQihQEit/X3wBQ3/OCD93FIxi3w+ez+SvvLe2jDVENMdrJ8BL9JIc7JomB9qcAQRwAJH20PJdONHiRGZzGUzOZojxKSz/SovcwcA4ttAh1i5mv+2NwH9vZSHgjva84WJPqzU/fx9A5LrlBkmPFyMAcPYwls3+2fYqiB4P66XQehzIH8GugHk5mCrLvqFV6jOiTmDlX5he4+S7eqWzL3VAMaIlEkQR+O4F4J9nsS6Az08AHh/GWqwHq2btTcCbFwGPD9c+yGv2Ai+dzlarfWpMu7CUX1wOJcbPr2zV8HJYnnGvZtWfgYZDLKY79f+xCXbUXOCyZWxi9keozsiRH5g9nNpLuaIPhTFXshOwvV7JfxBFdgI0mm0PeCfTqleWNZkUl4Qn+lX9BBwvY5PFwJnsvtFXABe8BAy/kF0929JY8tzSi4JrCMd7bBSO9XYrjMBzFIyEig5vVqquinwmWLNF+b7t/qT9c43AT8K+r20ESwJw+TvsM2g9EdLCaa2qCS1RK2GUi6xeJzE3BmBOiRZul/J/0VnvJT9NI8zgG6aRE2p9xsM/q8Ix3lfPRm18/l56n6QcM7zSyp8zIorKvkdczH631esfr/zcwc8lCenstz9nhJcb95nA8iR0SEuwyCKtMpA7wvNGND6XsmNN+GjrEQgCcFIcO382ZY/UTr7nnHYnc4APfM0uMt7/DbDlddYt9rVztBcDPLJV7h/jl4NKykD796HKAYqRUA2JEQDTBuUgPs6EA7UtOPTDSmbtma3Ar19hCtySxDZUKX1NZ4SvWMlFBuA/iTV3CIt9ttRqJ7Gt/COw4vfMkfE4FWvyy7+xRklGJzyPG3jrcva+Gg4Bb8zxzuJ22YH/XMuuwAG2GNyq+4y9NsDG52hiDY94jogave6WzbVygzjM/Tdw+kLg4iXABS94x6/1kJ2RYMXIVu9xhYrJpNj6vAX+ioXAk6OAp8cav7LfuwqACOSPbJ8TwK/oytay39wVGXCWsoifIACjLgUuepWV3y7YzETSiQPBxaO5+8J7bgSDLEYMXGXJOQaTtE/UPMa+44PgXS+3SznOtE7CRkjMVPraBNPlU4K7EILAujy347DUpr23SozoOSPV29l5x5amdG32gSdgVjfYldw03wRWPWfkkM6EJTsjAcI0h1XCiqNOYtVD7cj0Pllplqbn/MrOyGj2W3ZG/IgRHor144oArPklD6lXap2n1XCRppE4++PBOgDA+OJMzEpnDQt3mQf7f730InmdIbx7NWtnwHG1Auuf9t5+y79Y0uvye/y/bstxqUQf2t8DswWQyrdjJYmVxAhYktmUAdkAANe30j9/7DxmowFAvCRGJCve4fLIVz/eYkSqilHZcoVpShJrOywJijXqW/patkbJ6p/+R+C2H4HfHwBm/Z3d9/0LLJ/FiCDZ8DK7srYksQmvrR5YfrfirqxexMIWCRnAlR8wgfTzx8ZtQt7Ou3SqdpIYv0I9vFk+OQJgoQm3g1mvoQgDLkaC7cDKT2z8KqsjjL6CfV4V69iy5t9LTYRO7GcOm5H/D090G3h2+8cGnAlAYBUzVduBH6UQ1rAL9F8vOYe1tQaArW8aT8bk/+9Q/hfmIIQhP158k+o4g85hrkldRfD9XKq3s5O4n8nbEDw3IITwG+/pkWAxt19EUxSV5NrCscydA/QramSrfbxuAibvk+FweZTcNF1nxFeMqISRmqCdEcUNlj87f2KEC7KC0awnSiI7/2oufudyKHl1sjMiiRE9sSiKLHcKMBSKlYsNAokRi74z8nMVC28PKUjBcA9bAXpVQ1HAfeOsB1l5O8Ac4suWAZe/y/7e+E9vd+S/UnkxD+vqwT+v9GIWyvVFVb5NzkiMcdawfPQTDqP0+DcABJZZz5FtR+Yc8ORVAEi2SSdhl0NRorlD5Mf5QX6kXucg53Ft/sXhfCM1uzr5N8CU37ErZkEATvkNcMGLbAL84Q3W0c8fx35hYgMAzloEXPI6u2rat4blF7x5kSJ6zn+WJVvxOn6evR4IPrkUT9R+PHsgy31wtbIwA8BOFptfZ7dVHR+DQg7TBClGuDNS0EFnBGBXthN9ThBD57AFt47uVISGHi4HE56AEnZRk1Gi5OG8MIl1UEzt3T5D35eik6U21gCWXqLsQ4+2euX4LYygM+J2Kse6XqVLfCIwQVqg7+tHg0tk5ZN3r5N0J29DWAyEGnTQDYkATGA5GtnnlT1AmYT1eo1wgahTlgqwvLcMqV9SFc8bkZ0RP2Eat1NpK+C7HpMRZ6TlOFvpGPA+ZoyIEZ6zxYVvEv8cattve+xnKXk1jTWxAwI7I/UH2XfFFGfoeOYXjYHDNPoibVdlAwBgeI4Zqc0HAAAfHM1HXUuA70RcPHM1b/4OuH0bc4UHnMn+584WYO1DbDt+sQsoTpIe/P+qmov03ws5IzHFjCF5uCXuQwBAS9+Z3omTPEwj5YzwEE2KLU5eFwK1e9mkaE1VrnaghGk0u7ACSlKa2hk5vJl1JjTFsUY5voy6DDhf6kmx7mnvg1RNcy3w9v8xEVUyGRh3LctEP/0P7PHt/2EhAsEETPuDEhrh9r8Ry93lAA5KE4De5CIIytUJt04rvgNqdrOT/vCLAu9Hi1BKe+2NSsVTOJwRgK3lUTqVhfZOuhaY8xww/jr2mHoFYy2O/ADYG5gToHfSPPk33n+f8SfvqgU9Zj3ChIzHqazNoQe/Wk/ro30lFQijOSOVP7LjMSFDP7EPYGuI2NLZMbLtPePjkENN4/xvFwjuhvLQZRD4bXjGr1izBzExzSvP9CZVfkGgt3ijRLskVh8xoRmmqS1jx0Z8Mvu/qzHijPDE+/RiJYcDMCbkuBjh74t3AtVyRnyTV4HA1TRc8OaPVC4m/SBfNAYM0+i7CbsqmTMyKo51UD4mZKFGTMV3+wzkbQmCVHloUf7mDdK2/Av4ZSXw6e+U7RMy27+GGi5GeAdsLcgZiSGO75ebVmU2/oJfmdlE+VnWPO/t+MEsWbZ+80VyBnsl//VS9RrRhPdzqNqmVLF88wT7PeISIK239vNGz2XNf0Q3yytRhwMqvgM+uAl4cQo7macUMOXNrxRPu4OtTnvqfOD0PzJFPu33yvPNQSjmyq3M8UjMAnIG6W8nixFJdG2RXJHhv2ZrvoQCDw0Ek8Ba+RMAkbkL/Gqso5gtrKPhHw6zdSzikxTbO1CXSDl/4GT9K/l+04HJd7HY9/gb2HFhhPhEpUFboBbn8qQ30thr+2I2KAy5WPATdgDAjgkuxNc+5B3e8wcXVQEm74CEIUzjV4zwvDJ/V/guhzKp5I/wu08uRuTyXrkdvJ8+I3ydl5zB7f8XRpyRqu3aYwskRjye9v8n/l1s0XBGZCdztHIfP2e0NWjvg+fCGExiLvBXaKCGfy4+OSPHGu2oabJDEIASF0terUlmYcKf1C0jgqF4AkvmFz3Asou9W+cHEhDHdrPffsVIbDkjBhfk6Kasuo8tCz3obODgBpjgwUr3OCw7mAGviLzF+ypJsxU870ngY4spZWN2tDndsPn2HUjrxaz4EweYU1E8SVlLQcsVUXPmItbxct9alux6xn2sNFbdQTKjhFUHJOd6P7foZPajRTANceSOnRP8V2AUS/kBe1ezCYlf7Y67JvA+9JCdkSDCNHwyCHByD34sJnhpe7PBz1BOAPRzJW8ysf9tKBhJJgQUMRLq5yL/LwKIBvVVbiBO+S1byOvEARaS5G6THi47W1sGCF1UceTvfPBhGr+L0nE3wYgYOfazkriud1EiwRt3KWEafvw5IIoiWpwaYRp+zsrTcKiMXDXrHTOBjrkT+1moKs6m5PX4C1dp5XhZJTFi1xEjXOwYTMbm5+nAYRrtz2W3lC9SkpWE+GPsHOPOHQEcA346FFx3by9mP8UE/vb32Od68g2s+3IgAcH/t/4uEMkZiRHcLnYC8DjZ5N9UDWf2EPzeeQM2lZ/w7mZoxBmpYQlLvv/89ESL3PhI90DnNvz/bgOWnAdAZEl8uX5ULQBk9wd+9RS7/d2zwIN5ihAZ83+sGui3X/k/ILWQk98MXI3Ksd/R/rfrNZZZpq5W4KVp7HMvndo+cS4YQintlWOpAT7bjmL0qkN2RjoYVtAj3qAYqe6gGDGaM8IniXwDYiE+ieVLAcCXj+hfBXOO7mKhUlu60u46VHzyxAIiiqzp3EcLgnNGeJhGq6SV51fljwhYap3fLkyjJLDaXR64pe7SiVbVmHgPlVyl+k/GyPHLjxl1fxJAlTOiI+T4OSNvuOJuJukksLqdigNj1BnxeBTRZ/B49tstW41FewKvOM6+X6XZSbJISy1lQujHQ3Xtu3sbJS4euOifrHjhd2VKHphO0zUATNDxz9GvGImtLqw9V4yY41gZ5A1fsGqVWX+H5bpP0ad3EUQRWLVTlcHso/Qb2tiVj5cY4X05+EJREoIgKHkjeqGacdcASZJz0VTFkpPOXmzsfYy6jCWeJrNeKTBZWGe/858FRl7Mkr6CJRjFLMd+R/vfThBYeEgNz10JlSBzRjYeOI5Nm1gobnlVCJ9LMKg7HOrRXMuu+oHQkkaNEGhiAFg4gOcd+U4sRjESpnHZlSs2o2GUcVexXjBNVWzpdr9hA279jwy+T4ovRj43NY1VwKZXgR/egLOZuRwJFh/j2eVgPWIAJV+GOyOu1vb7kp2HwMKNrx0jdxFViQkujgCfVYR5aFkryTFQmEZ9zLRzRniIS0fIyUJBdazxnBHfBNZjP7PvkDVVSV4FVM6IRoPGE/tZq4E4W7vzsR690hNgEliPGK8FB33ROTdyR6ogJU4+xgsGnQxrnAmNbS4cqO3gStAJGUwgGxGJPEST3kfJfdIixsI0PVeMcHqNY1dfp/wGSMjAzOFSAzTejRVoV9orh2kSeM6CRznJZPdvt4vekhg5eELn6jQ+kfXW6H8mC2dc8a7mGhS6jPk/4I7twK1bgbt/UXokhIpPjwJdHM1Kl08jk8vQ85nwGnQOcPHroXc/lccZXGnvS1/tQ4nI+hi8vCseRxsieEXAY/b+vug8fyKrv3cCYDgxEqap+YW5S9a00JvA8WPGn0t1dJcSdjC6nzgrcMm/2ORT/q3/6qQgJu+AqHsLGSnP5vkXAJxtTQCAJKuPM1J/kMX/LYlsUUCAvS/eEt43VBNE6KyXXLXnG6axy2Gj+DgT4swm+X5ZCGvlFQQ6fo9Lya/W1Pb/y0A5I3JIW+XI6Dkjcr7IKO+8FlmMaIRA+OeWO1Q5RwQgPs4kL5paUevnu6Ij0qqlz32QpYaJJ0siLFmlGFrIxtmhUI3m/tt0G182VjKX/rC5l+bjmq8VA5AY8eGsoewksb6sVrmisHhbtu3CNPUH2T/UZGmflQ6gOJM9n1t5mvQ/A/i/94BrPgmxz4OFLSinXhcmVAy3gt4OQGQJsr45KVqYzMDsJ1iDs2FzOjhIBOWMnGh24Kfde5EtNMAjCtjlLsCSdQc6PgY9jHyGNdIVTJ6GTR4ujFQ2qPMYQnUUjIRp1JNrMPspHKM0rtIrgQWUsEM48oHUFRj+LHGOah0bVxv7nrcL0/B257xMH/Bpba4SI6IYlBhpVw2iSmDVDBudKAcgskoare9uoONXdoL7tf9fBurAKosRlQiSnRGf/69v1Q3HX5gmxPynkmw27nIjYsTnvXFnpK8gNW3LHgCYTBjRizmwOysDhBiNou6cqvNd+24zC/1+UZ2EtzdW+HktckZimn45SShMs8Hh9mBzuXRy4F8ujwtwOWRnRBYjvFQ0s6+mEi/iYsTfQR5LxBmN/0sninBciYZCEDkjH2+rRLGHnSjaknuhDVa8s+lg6LHcgGMz4C7xPCODVnJIcDHiryqEj6MjeTRGmp7xfJ1QxBd/H0bEXUeanXGCXS5eLUbs7KKlXZiGOxG+rqdW3khdOUvONMcbyvkqlKpB6ludaLK7vBJYmyUxkqROXpWFUam2MAw0UXEnOFNj7Sh/bpyjRfkc1KXdPIG19YR3Xxk5edXnAk0dpvF1CEIUI30ymRtW7u+i0aLjjEhipJdLmvyz2f9saAEb584jERAjGsfl9sP1aKlm/5sKMRcPfLxLf70dckZiG0EQMKEf+2KsK5NUukUVd3M2y85Iqq8YydaeVIqz+EHewbhhZ2G0tJdb0/kh5hl0lCDawa8vq8EAE2u5bSsYisR4M2qaHNhVFaaThC+GnBF+3IRh8tTDSAMqfvxmtQ8xGsaIM8JDejrfE78Eeh8tx9kyBkB4Pk+TSREkgcqiASX/AoBbEiPtnJHjKmdEjZYzIocaVL0n/JBisyBVasB4pK7VKzmxRau6h48l02csnGCcEV/85dvU7AYgMvGhLq2XHV1R+RzcLu3kVUBxRkR3+2NCTlL308dGg+Is7oz4+X/Ln4u2M5LZKjWBy2HHIA/T7Kxs8J8Ya5QAbdw/21GFPsJRAEBDQi802V3KPOYLOSOxz4R+zDJcVyYlU8XFKyEBR3P7MA0/yeqsMNunyzkjBrOs5cklyGqdcBFEO/ifKxsxQLJQTbmDcWpf9j/+eo8f278j8JOWx6mfc8AdCY08o7DBJwaPU1+06SRfB4W66ZneSVd+vyEcL4ESSvlrp/b2uyhaUBitRPJ4vBoPeuxs+3alvbIzUup9P29g1apyRkK4uvdqaa6qiOM9RpK8xMg+9juzr/aLBToHyM/3J0Y0JnWdFggwW5RGZjxUU7ObTfrxKe3HaUlUcm3UoRpHM+tyC/jvsaEBD6cbCtOoJvA2p1tuw5/UwHMH2TE+MC8FJgE43uxAdUMYJv0Abdx3HGlAkSRGivsxMfbZdo3F9gByRroCXIxsO1yPRt76XVXey9vBy31GuGWpc2XJxUhDmytwa+BYwGhpryxGIjiZ+sNgo602pxsHapsxQJAWI8sZjMnSWkTfREyMxCu3tSpqWuuAZnbSiGiYRp1NrzWRezz+r3KNIl+9i9rt251tSuvwUJyLQGJEqiBwh/OzNNqjpe6A15Wyx6mXMyK9/2CckSBCoL3VVXsqd5P3GPESR+owjRaBqmn4MaMlZvyFBvXECNA+iZW3wvdNXgXYpMw7Rat7jdTsgeK8BNdJuE+Wgdw+jZwRHqKxWQSYj0suoxRas1nM6JfDxPGusOWN6Dsa+w5VIVtg+xk3ioW2Vu6skku7jb5ONAhJjDz77LMoKSmBzWbDKaecgg0bNuhuu2TJEgiC4PVjs9l0t48FeqUnoCQrEW6PiI0HpKsVVeOzdmEa2fLUvspIiDcjN4X94/2q7ljBiGLurMnUH9ytCuCM7KlugkcEBpnVYoSt7bDhwHH9mGpHCLRENw+NJOeH3oHWCOZ41u4f0J5UGw6zidRkYW29Q8WkCiVoidjjZaySxJZmLNnZl0DCQHJGXt9jxQMf74TTbXBFayP7DNSFtXqn99/SGL1yNEQxuJyRDjgjLEyjhM1a7K7245GdDT0x4scZcbSwdV8AbQErt9LX+Nxq/YQmUwrYb+5s8IaAej14bKq8EY6RzqM68HD68WaH1/pjXmhM4LycekRyEwRHE3NsVCJPHaoJC/Jifd7C/GhjG2zNzP0VEzIxblAxkq1xONHixC/VGiXQXd0Zefvtt3HnnXfiz3/+M7Zs2YJRo0Zh5syZOHr0qO5zUlNTUVlZKf+Ul5d3aNCdgRyq2SuFalTOSH2LKkzjdrFqGkD/KgOqUI0/1R0rGEm+7KzJ1B8GS3t3VTUgDU3IRh27I2cg+uUkISspHg6XBzvClVymxhSniACtz1EOWURYyAmC/4lcTr4uNVwGqYlZ7QT5e78DQ6vYCeCM1FWw3IK9Yi/885v9eOaLvcHvwxejYRpV8irbno3Ry4loOc66jgLtS2F5WTd3RlqOK+eUIJJ9e6nFiKoDMF8rRx6Px624NLphGj/OCBcytnTt6j3ZsdCYAP05KjxRlwsKvqKw3iKBVqlXUJuqbFZekyX4UGCyNU6+aNx3TCdvRGPVXp4vMjJBcnQySryc0fAnsWo7GjuONKCPwEIyQkYJ4swmjC5KBwClGMPA60SLoMXIY489hhtuuAHXXHMNhg4dihdeeAGJiYl49dVXdZ8jCALy8/Pln7y8vA4NujNQklglMSKd0D32ZjRKVxqpCXHspOGRste5steAq+4DNV0gidVIzkhHkhHDhcHS3t1VjejPQzRpRYA1BYIgYEwfZo//UBFg/ZhQEAT/LeEDuGlhxV95bziSVwHvJEut/4d8vISYXBoggbWtik1g+0T2HVz6fTnsrg46XkbDNEe9nRFHC+szkpmkEmjcFUkpVCoyOHLOiHQcclckoySopoWaOSMuh5zAKjsjDYdZDpHJ4rWopxf+zgHHA4T14nXEiMethIe0jjeeS1TzC8v94J+rXpdmrTBNB5wRAOify0Iqe482aW+g8bnwMM2AeEmM+HwuQyQxEr4wjbajseNwvZwvwt23sX3SAQBbtM5xXdkZcTgc2Lx5M2bMmKG8gMmEGTNmYP369brPa2pqQnFxMYqKinD++edjx44dutsCgN1uR0NDg9dPZzNBSnDcVdWAE80O2XpsbWmU8/PSEizevQP8LPzVN4c9f19XEiP+ckZqY0CMGCzt/aW6Ua6kUV8xjS1OB6Bz1RAO/F15cCs6owOhEaP4W/RNFiMdyBcBmPgy+fl/8MlYLywQCD+Cyu6wI8vFTsJ/u+5XyEu1oqbJgRXbq9ptG9I+A4VpuDMilae2tLBJeECuKpH2hE4lDaDkSkiLdoZamio3VzyuTmC1t3dGuLORUcx6/2jhzxmR3Q2dY0bPGak/yM4p5njttXakChQc283aBohudoGXWqi9H61eI7IzEpro5fkdZcf0xEh7Z6S2iZ0n+0BKFPVxyLkY2V/bjGZ7EOto6aFzXimvbZEraWQxUswuuLZ0N2ekpqYGbre7nbORl5eHqirtL/6gQYPw6quv4qOPPsKbb74Jj8eDiRMn4tChQ7r7Wbx4MdLS0uSfoqIOrjMRAjkpVgzITYYoAt/vr5VPTG3SicZmMcEaZ1Zd4fo/yfbjYkTvII8ljCzyJlcQRdMZMVbae/hEq5K8qqrkGCc5I1sqToSn7M4X1YTQDp7M2ZE8DaMYCdOE4//or7yXi69Q36/sjLQ/Jvfs2Q2L4IYDcSgu7Y+5J7MwyPtbDoe2L46RMI3LoQhz6QreJjqQlmBBjmT5A9DPFwEUl6Bmj0+zs+D695RI7mtVQxvaROm74VLEiNwR1ogr5++qOZAzwquZHD7nOi5iMkq1RRD/bp7YD+xZxW77W7vKtyW8s00RfSE6I/w8HdAZUR2Htc3seM9zSXk0PnNBTooVuSlWiCLwc5VG6CpY4rRDltWN9nZihLu/B2pbUOPb5r4rOyOhMGHCBMybNw+jR4/G1KlT8f777yMnJwcvvvii7nMWLlyI+vp6+efgwYORHqYmE9UlvtKJyS6JEbmSJlBWukRfWXE3R2biCycqi1cX+Uq3E8IMepgDJ7CKoojDda1yWa+6sdfI3umIMwmobrArbbTDiRFnpFPEiL++D1xUhqEiyl/jM/n9hthu3o+gqihjzkStpQCCyYxzRrBQzXf7ar3WZQnnPmVq97Ljz5oqf4YJggMD85IhqHNj/DkjWf1ZfpG9HmiqDlmMZCTFy+0GKpulBF6XnTVBg2rFXiPnLH/Hbq2fsl5AcUbcDu/nc0dGT8Sk5LPPUfQA3zzG7ht8nv4Y5QRWyRmp3atKkg4tFaB/Lhu7rjOikTNyXBIjmQ5J/GqcE3kSa1hCNTr/m6MNbe3ESFqCRXbofqioM/Q60SIoMZKdnQ2z2Yzqau+65erqauTn5xt6DYvFgjFjxmDvXv0EM6vVitTUVK+faMCTWNeX1crVNC1NLFlKvuox6IwUZyXCJABNdpf3isCxiL8resB/ZUBnYiBnpKbJAbvLg34m6apF5YwkxJtlC1XTxuwoela3ywE0SOPpjDCNXnWDy66IhLCIER1nxO1ieQpAB8SIvqA6cZglxzpS2GsPyE1Gr/QE2F0efLevtt32xvdpIExzTArR5AySt7fBLk9qyiB5wqjGeSLOqnyPDm1UXrMg+M7GJVJ56qEG6YLHbZfbCWQkSv+fQD1GAIPOiM7z41XhKbtqUg8UEhQE75wiczwwaJb+GLno4WEaOUQzOORlDfrlSg0qa1vgcGlUZGnkjNQ22QGISGmRLng0RB4/z4QlWV7nf3O0vgW9Banxn+q8PE4K1bQLR3dlZyQ+Ph7jxo3D6tWr5fs8Hg9Wr16NCRMmGHoNt9uNbdu2oaBAP9kzVjilNAuCAOw52oQWgf3jWprYwcQXVdJtZOSDNc4st4Uv08vUjhUC9RhoPaFcjYQ6uYQDAzkjh+takYRW9BKkScknlswTvCKSN6IX7qo/CEBkdmtSTvj364te8ufxfWwc1tTQym19UTc+U9NYydwDk0VZXTpY4nTeAwCPdKUen80mR0EQMHUQ+1zX7tav8guIke61Uhfd4wkl+M82VpqbAOaMeBFIvHORvOFldnWfNUA/V8IPPFH+YIPkFrocypV7Em9FII3F3wWU3lWzvZG5N4C+M2Iyq4ScKiwRKNcEAAbOVG73O8N/Aq9vmEZOXg29CWN+qg1J8Wa4PaL2SrtaOSPNDmSjAXGuZgCC5gXG8EL2PrYfDsOCeRqCqM3pRnzrUVgFF0RTnFdispw34pvE2pWdEQC488478fLLL+P111/Hrl27cNNNN6G5uRnXXHMNAGDevHlYuHChvP2iRYuwcuVK7Nu3D1u2bMH//d//oby8HNdff3343kWEyEiKl8uyDjczpc1zRgrTbcwhMOiMAEDfbJ7EGuN5I3Jpr85Bym3e5HzvBcU6GzlnRD9Mc/hEK/oJkguRnKc0mJLgX9SIVNTofdnVIYuOLnVvBD1XQX2lGo5x6DWh42Wqab39Jnn7Rec9OFweZNjZ/zelUHF3pg1kYqRDHXb99cvgSPkir/4ch21H2aSfKLRhYJ7KGXE5gHp+1Vyi/TpcJO//kv3uNz2kIZdI55jyeik85bbjhNSKICMxXnI1jYRpdFaH5a5KYpb/laa1klgD5ZoAwGl3Auc9AQyYCUz/o/52gCpMI03wamckRARBwMB8NnbNkIrGd/p4s0MuqUVab2UbFSN7p8mv2eG+RhqhomPqfJG0Iq8y/bFS3siPB+u8++90ZWcEAC699FL84x//wH333YfRo0dj69atWLFihZzUWlFRgcrKSnn7EydO4IYbbsCQIUNwzjnnoKGhAevWrcPQocGtGxAteFVNuXRcOluZkChMT2BrYTglNWzAIeCZ2rrJUbGCOkyjld/S0cqIcCG3g/fnjLQoZb0aZaX8i7rjSBhOEr7ohbvk5NVOcpUsOpNquMp6OXLYzCdMI4uvDiSi64iR6oY2uZwxKU+Z5Lirua+mOfSwqKFFBpkY2ePOR3ZGOgAgL0GUjysAihNmSdR3wnyPzX6nhzRkHqbZf1z6TnhcqGtin1lmUjw7ZzmaoHcFLyNPqKL3/9OIuwEooRoepnE7lVCVv+PNHAecdA1wxTuB17ziK/02SZNwGJwRABjGm5RphVTUx6EootXhRovDjWIuRnTEZu+MBGQlxcPlETueN6JTXtzHxD4HwWcMfbOTkJ5ogd3l8X5PRpf96CRCukxZsGABysvLYbfb8f333+OUU06RH1u7di2WLFki//3444/L21ZVVeGTTz7BmDFjNF41NpnYnx3wu+vY32IbU/oFaTbFFdFRw77wqyXNbnixhPq9aHbT9JOM15kYaAd/+ESrZlkvp3dGAnJSrHB5RGwLh4WqJpAz0hn5IoC+M1ITxkoaQD9npKPJq4B3MqlKIB+pa5WvCAVVDkRaogWDpO/bJt5FuSP71EIUIUqCbq9YiMlD2fs7uZdNp/V6ib4DpU5WjbMBJaeFNGQepik7oXwnWtvY/z0jKd74OcuicjzVCwUacTeA9s7IiXJWqmtJ9NuPKSjUVUjOVmVsHXBGAGCYFFLRzO/wEmlO1Daz73ZfsySIdC7QBEGQ3ZGfDnXwPKMRRq9SiXLf87LJJGCM1PzMK1QTKBzfydDaNAEYX5IJs0nA/mZ2oo1z1AGQnBF/GfIaDC5gX9CfK2NcjJhVJykt1RwLyauAoXbwh+ta0Z+HaTROUoIgKI2Bwp03omeDnuhsZ0Rn9dlw9Rjh6InDcFQO8fcgur1e/1hNNTKEJs3XP7mUNRP7fn+IYiRQaW9jFQRHE1yiCc2JvTGsWMqH8RV9Rr4vBSOBX78CTFsIXPGuMpkHCS9NLW9QXL54sM8r3bcvkj/MFkWQqDucBqqk4fDx85wRLhQy+4YvNJnZD4DAFhjcu5qdB5Lz9Bu5GYQ7IzuO1LevfPRa5qFVzsfpb1F1X9VhlCQIfjxY16HxaTsj7ct61WgmsXb1ME1PI8VmwYheaagX2Zc8wcXUcmF6QtAOwYDcFAgCS3iK6Yoa9RWTVnlvrIgRA+3gD51oRT8/YRrAT7Z5R9Frq9+ZZb2AfsOwcIdp+Pv1DZvx95vWkTCN6kpdJQ6aq9jk2GjOaLda7/gSJkY2dtQZ8RVxHClf5KCYg1MHFCDOqvM5G/2+jLwYmPb/gNIpIQ0XANIT45GfaoMLZojSUvNWuJCWYEGc2WSskoYjJ4iqHIJAlTQcOUwjiRF/beBDJT5RCf1tXcp+9x7fYbEzMC8FZpOAEy1OVPqW/JvjAelzhbNNbnhWbOJCQD90PUrLnQgFOZlbGZtWWa+asXK36TrV63TxBNaeyOQB2agT2ZcrBc0wCUBeilW5yjCYO5EQb0apZKP+XNX5XWUNIwgqy13jQI0VMWKktLeuXonn6sSSx8rNz+rC2wNG78ojHGGLYIjXmCRbTyiro4ZbjEQiTGO2KEvGqz5Pt3RB0JjQ/mqYOyO7KhuU1beDQV4zpk77cWm9nX1iIUb2TtdPeO3ksCZzYAW4Tez/YRWcSmv6IBLuNTucGs0ZkcM0kmsVYGXzkOEXGLuXs9+9x3f4JW0Ws9ybo131i3q1YEeT3PCs0CM1/fTzuY7tkwFBYA3IjjZ0wI3QyxnxI0ZGFaXDJDCnmC/sR85IF2TmsHzUgR2c6UITclNs0lWGsYZnagZJmdq7w9GJL5L465FRr19P36kEKO1tbHMiy34IZkGE6KcR0vBeabCYBdQ02XHohM4S9aEQp1GV5GwFmqQTV6c7I6orfD6ppBS0cxRCRqvpmcejHC8dESM6C/7F1bOQF+8xoiYv1YbirER4xBBdL981Y3wQpeTVfWIBu+rVy83hYblO+r4Mzmciwgn2/YiHExmJvKyXt4I3MBZfZ6StXiVgA4kRny6s4Q4JcnzdzjCIEQAY1TsdAPCDVkjFxh5Dax2ON9uRiDake6RjxI/gTEuwYIj0v9kQqlsHaJ6bT9TVIUeo1x1DkjVOPi5kZ4a/jqNFu1ChkyExYoBhhalISmeJrGloRq80aZIJ0hkBlBPFrpjPG9Ep762rgFwZEI7eFB0hQGmvOl9EyB6ka9/aLGYMlZLWOmyhquFfdrW7xCfm+GTtFU8jgdYkGe4QDaDtjDRVMbEomDueuKjxPpKapbLhzBLNp/BQzYZQ8kZ4GbiOGLFLi/MdQCHLM9BKeI1Cg8AhUm5amyxGXIozIp+zDIRLfJ0RLmCTcgPntPgmsNZGyhlRJV+bLEDh6LC8LF+3SjOPjPc+aatDbZNDSRy1pbdrHeALd+tCOh45Gs6IuZ65j674NN2Sax6OlvfN34fHqbsadmdCYsQAgiBgwjD2JTILIm6amMeuEpqlbndBxEF5W+CwNL+JJHplX+oTa2f0yPBHAGeEVdJIk3+AhbP4OjVhzRvR+gzVyaud9flpTZLhbAPP0RIjcr5IL6/eByHBV7tVnTgzHExs2nK138fJHckb4ROLq1XzZO2RPkNnej/YLGZt0ddyXEni7KSwHL/gaXWzsJYVDtZjpK0eaJGa/xm5gPJ1RgK1c1ejXrnX3qj0mgl11WY98lSLCZ69WAmVdRAeuv3pUL13bw5Amezb6lDT5FDCwAY+01N4UvW+cDgjynkloZmd59xp+sfYqVKbCrkrsTVFCX221YU+njBBYsQgN5w+FE4Tm1xmlMQrV5bJeUEt8z1KKu/ac7QxPCs4Rgq9lXsNrsXTKQTIGQlUSaNGvhIKpzMid2BVT86duEAeh5+gNVtzh1OM8P+H6riu4w3PwjAR+4iqZrsLhR42EaQW6IgR6eT/48H64PvIWFMU983XHXG2IaGZJUYnFQ72Hp/bDnikfXHxnlKoiKkI0zcnCfFxJjSITBwlC63MGeFh5cRsY9U6es5IoHwRQAnT2Bvl3Bok54XfDex9EjD7KeDaz4CTbwjby/bLSUaqLQ6tTnf76kfZGalHTZP/KhZfTi7NhCAAu6sbQ88b8Wl61mR3IdfNenuZs/TPy6f0ZZ/9z1WNrApIEOT3srfiEPbXNGu3wO8kSIwYJDMpHpYkqclO64mQbcfcVBvyU23wiDHujui1Mg8mAS7S8MkPonLyV3H4RKuq4Zn/Rkj8SmhXZSNaHGESiVoJYp3d8AxQmkPxq2IgMra5VtOzcL5fH+eh8kQjegkshyExT/t9FGclIifFCofbE3xJpSDoh2qO74MAEQ1iArLzi7zHpxpjsOX/4cBiNmF0UTrqwURoOpqRnhgfXIgGUDkj0nnKaCUN4JXkKTcjC7crArD/0birgD6nhvVlTSZBXvF2c7mPi8HFSGudd+dTAxdoWclWjOjFnr/2l2OhDc6nCqaqXklejfMjRrKTrfIyBRv2S+cCyeV5ZvlmnP6PtWyF+ihBYiQY1Nn1HbC5RxWFqflNJNFbuVcVplmxvRKjF63EhMWr8c7GKKysbFLZ/hruyNHjxxUxEqCbY2F6AvJTbXB7xPD9X7QSWDu74RmgEiPSSdXjUZyR7DA1PAO0wzTcng+LGPF2RmqOHIBFcMOBON18FEEQZHekQ6GaFp/n1vLk1UKUZEsugLoHBQ+JRany7NTSTLkCMF1oYuvSBHshITsAITgj6tLeMLRpjwa6fWp4AmtbPY412YMK0wDKUgVfhixGvC9yjvppeOYLD9V8u1cSHdL/2NnE3mNheoLm8zoDEiPBoL5K6oDNPVLK1P7xUF14xhUJdHNG2AmtKbE3/vDBdtRJtfj/7/2f8FWoX65QUYsRjbwRW80OxAketNlyDC06FvZ+I1oJrJ3d8AxQrHFHIxNGjUdYHoQpLrzj0Gp6Fo5W8BwfZ6Slin0Ha+MK/K55c0pHmp/pOSPSxUiZWIBiqQW7ZsVPlMTIKX2zZDGShiZ2zgmmkgbQyBkx2H0V8C7tDVOb9s7m1L7KcePxqKpNpAnc01rnvS6Nwc+VL+L49S/H4PLNRzECPzdLfUaqG/2X9aqZPIDte83uo6yNgSSs4l3SmmtpJEa6Bl5iRHJGQriyHM2b35SfCG9fi3CidZWrqgx4/WcBx5sdyE+1YcaQPHhE4Pf/+Ql2V5jXd/E7RotyW8MZyWnYAQBw5I429HI8pvpNRxZXU6PVVKizG54B7ITDE9VaahUhnVHi/Rl2FK2mZ+HsqeIjRly1TBg3aPQYUcMrajaXnwj+5K9T3uuo2gkAKPMUyovTeY3REV0xMrZPBuqkMM2oLJEtYS+vKWUwTKPOGWk5rnwGRp7PBXDDIeDoLna7izkjI3qlI8FixvFmB/ao1xOTHHJn8wmIHjd6C4G7r6oZXZSBjEQLGtpcoQlkeeVg9j2oqjMuRib1z0K82YRDJ1pRdqxJfi9pQjMyEi3eyxh0MiRGgkEO06hzRoIXI2P6pMNiFnCkvg0Vx/0swhVNtPqMNB0FnC0QBRPe2cMqQf5y/jA8c/kY5KfaUFnfhrc7M1zj5Yx453m0Od3o52SJc3F9xhl6uSnSVcOm8uNoCkdysW/ejaNZ6dPQmc6IIHjnjcghxjCGaACVMyIJWFEMT48Rjk8nWXP9AQCAPcW/6zIoLwWptji0ONza6434Q74A8Z403JVM6FZa+yLZqjoO5R4U0sQdpUUlE+LN6N+nNwBgSpE0vmDDNGpnhLsqKQXGKlZyh7EFGltPSHlDApDbNRZH5cTHmXBSCfv/ry9TXaDw0EbzcRQKtbAIbibEDbivAGA2CThrKFs64NPtlQG21kDOWWHh5Objh2ETnPDAFLDLcWJ8nHzRtebnY/LxmoZmFETRFQFIjAQHP9FUbmU2rMkSUuw/MT5Obqqzvix6CUN+0SxLZSczV3IhyutdiDebMHlANmwWM+ZPZ+Gq59aUhWY9hoIgqHqNeDsjB4+3YKTABGNCsbFGSCXZSSjOSoTTLYbn/+Kbd8NdApvSC+BATXNo3UGDJSmb/W6uUQnpMDeg8g3TNB1lx49gktcLKa9tRqsjRPdMdkaYgJd7jASwx00mIfT+DlphGrcT1jr2GbZl+lzt8947zcd8GgSWBLffMHDGGBYWSXA3Mku/QcqfMhqmUTsjweSLACxfqniC8nefUwFeANCFmNCPjfmbvWoxkg4AEFvrlRBNejFgMu4qzBrBxMiK7dVwe4J0x/l32V7PLhYlwdtsyzfkdJ4+iB2jq3ZVy8ImTWiOar4IQGIkOPiJafen7HfhmJBtbn6Qr98X42JEHaaRDvqaOJYseFJJBhLjmRi45KTeyEqKR1VDG1b/fLTzxqmzWN7RAztRaqqGGyYIvcYafrmpcnJZGN6Dr6BThSxEUcQzX+zBtH+sxcTFX+D1dQc6vj9/qJ2R2gj0GAHah/b4+00pBMwWPLtmL6b+fS3GPLASz63dG/zr85BJM5sY0u2sbDs+J/AEGfKieVpipGYPTKITjWICknJ9JnZZ9B2TknelBoFJOcHtNxyox15XzsYSn6KMMRBezkgQlTSc0qnK7SG/Mv68GIK7pevKapUQtDSBC211QZX1qpnYLxuptjjUNNnxfbBzgE/YNb6Bfc/sGl2ItThrGOtEvfHAcTSZWF5RqtCCwvTOKT3Xg8RIMPAvN5/41Mo/SCZIWc3rymq9k6NiBa3SXsnm3eNkJzOeDAUA1jgzLjqJ2cL/3lDROWMEVI3PvMWIbfcHAICfE8cF1duAi5G1u491PJ9HFnRSqEtOXi3G/36qxD9WsjBSo92FP/93B9ZEUsTxz0CdMxLOShqgfZimXkle/XRbJf7+GUtkbHN68MiK3fjfj0eCe33ezr+pCqIoIs/N2uqnFQR+HzxvZFP58eC+b4ka1TRHWb7IL2Jv73wRgHUnBZgYUZf1RqNBoFqMyCGaIMaidkZ4aM+oMwIApZOV20POM/68GGJYYSpyUqxocbixcb8kSCVX0+xoCLqShhMfZ8K5I1lY570th4IblMmkfJ+ba5DYwp4vGhREvTMSMaooHaIIbD/OJEAayBnpWvguTd1nYsgvNbY4A8nWOBxrtOOHg2FeLTYcaCVfSs7Ijy3si8Bjj5y545ky//KXYzjYWbkwWmGahiMoOfw/AMC+/FlBvdypfZUEr/01Oqu1GsU370bV8OzN79jt608rxZWnslDf3e/+iIZIhWwSpavh4/uVPIZwJxTKzogkDFVO0GuS83PtpFL8diq7uv7D+9vkJdgNkSKJkcZq1B2vQYbAkgoziwI7PMN7pSHBYkZdixO/HA1iKQZ5Qq9T7pPEyG5PkYYYkQR609HoLyjpJUaCrKQBAKuUm+BsBg5tZLcLRhl/fsFoYOKtwBn3dW6OVBgRBEF1gcLbvrPPxepsxFBB+k6H0EPlonHs4u3TbVXB56hJ32exuQaZDhZ+i882/r89ZzgLE313hO03VWhGQRo5I12H/jO8v1R9Tgn5pWwWM84cyk6uH/8UQhJTpJGTpFRCSbrS+7ktC4IADM737uJYkp2ESf2zIIrAO5s6KZHVtyX88f3Ac6ciy34IzaIVrf3OCerlkqxxGF/KTuIh9wHgxPlUVkhi5Hh8PjbsPw5BAK6bXIp7zx2CfjlJqG124IW1ZR3bpx48TFP2BfudVmTcrjeKb9MzSYw02grl93vDlFLcM3MwhhakotHuwrNrggjXJLMTKJqqUHuQ9a6oRRqsiYE7IFvM6mTEIGxxuc+I6jlHfgAA/CwWoSTLR4wkS2Kk+RhQw6uWotQgUN0X6ShLuA2qvFbdpbX+IAABCCLkCUEAznoAmHyX8efEINMHM7dr5c5qr3JYE9w41cSEaVCfi8TYPunom52EVqcbH/5wOLgnS9/d5hPV6A0mkpJ0Gv9pcd6oQggCsKmauYRpaEYvcka6EOY44JJ/sRhw6dSAiyIF4ryRLPdi+bbK4JOYIg1vItWoEkqS1Vsu5qI0K0nOF1Fz+cnsKv/tjQfbr+kQCXxbwm/5F9BWjwpTL1zt+D165QUfq1eHajqEnD9wVCqLZmLk2xo2gZ3WPxsFaQmwWcz4/dnMpXj12/0dW1480FhqpJ4PYVpQzAvfMI3UCn5LA4tLjy/JREFaAswmAQvPYe/3jfXlypLmgVA5I22HtwMAjliMX3FP6s8+g6BKt3kJ9rFdwHcvAI5miAe+BQB86xmu9BjhJKnECBcAeVGqIlGvrXNoE7udP9L48+PivRu55QwKaumL7sK0QTmwWUyoON7CqrEsCfJ5xyq44DZZgDz/TRW1EAQB/ye5oq9+uz/I8CG7uGg6USU3dozLMS5GeqUnYPKAHNSL7FyUKjSjVwaJka5F4Rjgjh3AFe92+KVOG5CN9EQLqhvsWLmjKgyDCyMp0lVooxQTtTexSRVAhZjL+hZocObQPGQnx+Nooz2yORAcvviax8U6i/70NgDg746LsVEcjD6ZiX6erA2/ElpfVtuxsAkXdG6HVxXLt3XpACA7Y/z2uOIMtDk9eOHLfaHvU49En0qGwjHh34ccppE+M8kZWV/LTnjnjlC6pE4ekIOTSzPhcHvw6rf7jb0+d0ZcrbAc2QAAOJZo/AQ8eQATI+v31RpfgyOrHzDlHnb7s4XA149CcNtR4clBfWIJUmw+CezqnJFq6ao5WiWt1lQl0ZF3Qc0fob+9Fuockd4nhWdcXYzE+Dj5nPDxT5XSMgHp8uP2rGFKWDtILhlfhBRrHPYda8YXwZwvpYsLT9UOZApNcMMUdFO5y8YXyUsGZJlaqLS3S5KYGfLBp8YaZ8Y8SRk//2VZbDVAk8WI5IxIJ7N6cyYakCwvU+5LfJwJvx7LYqHvbAoyMSsU1M5I+bdAw2F4rGlY6RoNi1kIKSmrf24K+uUkweH2dExQxcUruRqHNwPOZoimOKypZgJpeC/lKlMQBNx2BkvEXPp9OY42htkd8U3iLRgd3tcHvJueeTztxMgoqdkf56apbKJb9n0F6lsNiL74RLnCI+/YegBAc5rxWP2Q/FRkJcWjxeHGD8EsiHj6H4ARlwCiB/j6UQDAGs9oFPM28Gq4M3J8n9RTRohesy+fSRPxKcE32zv7IeV2YfChiO7CuSNYsun/fjwCj0eEM1Vx5OL7hC7Skq1xuPxU9lr/WLnbuEMunVdSK9cBAI7G9fJeG8kAZw7Nw4RhLH/LKra1X/qjkyExEmWumlgCm8WEnw7V4z9bgowbRhJZjFSxEEM1s5z3CuyLo+eMAMDFUmLWmt1Hwz+p+sITWD1O4MgWAMCx3ImwIx79cpJhNoVWxXC2lOD16bYOOlbcHdn/FQDAnV6K6mYPTAKbHNVMHpCNMX3SYXd58PJXYXZH1MnXgilCzogqTNNYCbhaIZrisKMlDSaBNR9TM21QDgblpaDJ7sLS78uN7UOqqEl3MJHsCcJ1MJkEnCa5I0EtUiYIwKyHgdTe8l0rPSe1D9EASs4IJ7MvE1HRQh1Kzh/ut22+Jn2nAWc+ABSdCgy7IKxD60qcMSQXqbY4HK5rxdd7a7BzzJ9gF9m5J6409EIGgInyVFscfq5qxH82G7yAk5yR5FY2ZxxLDL5nkMVswsOXT1bcszcuULrlRgESI1EmK9mKBaczq/m+j7YHd8UWSbgl7rYDbXWyGPnBzia1QfnazggADMhLwZg+6XB7RHwQaYHFwzRul1wxUCGwMfom2AbDrOFMRKzZfbRjTclSuRj5EgBwPIFdmfbPTW7XelkQBNwquSNvfFeOmiY7wkbOIGDWI8DYecD5z4V/KXdAcUacbXJfitak3nAhDn1ztN8vr6x59ZsDaHMaaIaWnOf1p7VgWFBD5Hb76l3VQT0PiZnATd8AF/4TS4oewLeeESj1TV4FmHPDPwcAyAtufGGHN2oEgg/RcCbdClz3WWSOmS6CzWKWHd+3NlRgq6sUp9sfw0s5fwCGzunQa6cnxuOW6ex7/9Cnu4x9733Crk1BOIRemMzAWX9luUHl38g9fKIBiZEY4KZp/TGxXxZaHG7Mffk7rNgeA/kjFptyImuskssZd7mLkBhvDph5felJrC3x25sORjb8ZFJV00hiZJeDXTUMytd3bwIxrDAVfXOSYHd58NmOICcuNdwZqWYJl+UCO6ENL9ROBJw2MAejeqehzRkBd+SU3wK/ehoYPTe8r8tRu2lSfsxRCxOGQ3WctNmjClGYZkNNkx0fGKkoSFHEyEFPDvJygqsImjYwF3EmAb9UN6G8NsjS7YQMYMRF+MjOlhcozdEQI4LAwjmcaIuRftPZb2taj3Y2wsFlJ7Nz2sqd1fh8VzWOIBt1/c4PqvOqHldPKsHQglTUtTjx5//uCPwEn0o4Z/aQ0Hc+4WZgwUZg5mLv3jCdDImRGMBsEvDSvJNw+qActDk9uGnpZrzy9b7o55CoK2qkyfRnsQ/65SRDCNA46dyRBUiwmLHvWHP4VsHVQl6YrFmu9tncwKzpwTp5LUYQBAEXjGYTadBld2p8lrbfZmdX5sN6aYsRQRBw2wx2lfSv9eWoDac7Emn4uhgNh4Ea1tBtn4cJlKGF2mLEYjbhusnMHXnpq32BY+ZW5XW+8owMOicoLdEid2NdtTN4kSmKIvZWs/4mA/N0jq8c1cQw+vKg9xFWpt8L/KES+H/lQHHHwgk9ncH5qZg6MAduj4ivpYos3WMgSCxmEx65aCTMJgGf/FSJzwIVNCR6ixFzYRD9X7RI78NESRQhMRIjJFvj8PK8k3DFKX0gisBfP9mFv/xvZ3QFCb/SPbIVaD0BD8zYKxain9YVoe9TbRacK5UuL4lkq/M0KY5fWyavA7JOqlbxzckIljljmBj5tqwGh06E2MQt1VuMrKtjE+FwnckZYGtHjOiVhlanG698Y7DSJBZIzmMhCtENHPgaALCthdnJes4IwLL60xIs2F/TjFU7A5yE81kJpVM04xHPFchODj6RnFcxLd8WfH+fyvo2NNpdiDMJ7XuMcKb9nrkQt/0YG82+4hOj0wG2G8IvFAAgKd7crvFjRxjeKw2/ncKE+b0fbPcfruHnZgBPuH6N9MIwL+0QBUiMxBBxZhP+Omc4/njuEAgCm8QfWr4reoKEH/CblwAADtv6wY549M/VqCLQ4NpJrNnT8m2VqKiNUEdWXh2wby0AEW5LCo55kpGWYEFeascqnooyEzGxH2vi9taGEJu4qZwRjzUN3zSyiVDPKQC8c0f+te4ATgTTpTQEaprsePWb/Xh308GOOTEm1aqhVdsAAJub2MnaX8JzkjUO8ybwqrIAjuCoy3Fg0sM41f4MUtIyQkpQPndEAUwCsKWiLujjki8lX5KdhPg4ndPnkNnAxUui13mViBhj+2TgdzMH4ZKTeuPD+ZPCXg576xkDMCgvBTVNdvzu3R/1vwuJmWg77znc6piPJ1wXRb1hWTggMRJjCIKA6yf3xUMXsGSzl7/ej8dX/RKdwXAxInUOXWU6DQAMi5GhhamYMjAHHhF4Zs2eiAxRPuFXsBK3hsQiAAIG56cEDCUZgTclemvjQeO9KdSoxMihfpeiDVaUZie170/hw4whuRhakIpmhxsvfBWhrqwAvt5zDNP+vhaLPv7/7d15XNR1/gfw1xzMAHIMOMAAcgpqyKUoiOaxCypopdWuZrZ5tJqmpZu6qVtZPvpFrdVaabq7bam1Sdl6ZR4pHmkiCoIcKomheDAoEDCAXDOf3x/DfHOQYwYGvjPD+/l48HjAfL8Mn/d8vsP3PZ/zIlZ8m43x//jRuEXBWmrREvALU8DNUQo3x/YTw1kj/SEVC3HhRgXO/NLOZnYSe2TKH0EZnDu9l4a7ky23UeV32cbtj3OlRLuUfLCB7wFifRb9Lgh//0MEgk3URXM/WxsRPpoxBBKxEMfy77a7geZF90nYqxkFd0cpXPpI2jzPUlAyYqZmRPvijUe10xY/OlrQ/bu6tqbF6PsvqrXz6Q1NRgBwa2d8k36ze2YKueivm1As1N782/skbozxIR5wc5SitLoe3+cYubEboHdzPuasHUA4uJ1WER2BQIC/jNeOkP/PyULk3a40/m93oKy6Hn/5OgvV9U0I8XRCf7c+KK9pwNwt53Cms7tJy3y4bxvEDrjN5O120ejIHaT4Y/NGi+sOXW53NcpLxdqEoCuzpaZEaLvgdqTfMGrlyyvN40W640ZECKCdqfjqZO24o7f3X27zvfizUsWdbw0oGTFjs0cFYFnzDemN7/I61cfdJSGPAyO0g5rq/MahsEEGG5EAfm31lbciys8FTzZPiXv5mwuoqDVxl0OLpvA8jfZmaKo3qI1IiFnNXQj/7KgLoTV2MmDWd8Bzh3G2VLu0dmgbg1dbin/IHYmhCjRpGF7anmny127doXyUVjdgoIcjdr4wEt+/NBoTQjzQoNZg/rb0zm12eF/yddkhBhoI2+2Sut/i3wXDXiLC+aIK7Gxn0PDF21UAupZwTg73hINUjGtltfjpquEtQfnNLSMDPKhlhHSfP43ww6QwBRrUGszblo6zhQ+2Fl7WJSNWkhhTMmLmFv8+CM+M0A5qXZqchWP5PbDEuo5QCEx8G5h3DGeGvAcA6O/mABuRcZfN6kmD4C2zQ2FpDZ797CxuVdwzXRkdPQH81h3zXbX2E0VXPjW39MwIP9hLRLisVHVuv5qAMYBPNHKbWzfamtbbkkAgwNopofB0tsXVu9rX7raJXrua+ibsvaBt6Vk7ZTBsbURcE3GkjwxVdU1YvD3T+K6p+1b4PKzWToE1pGUEABTOtlj8e+1AvDf35uFaK7smM8ZwqbjKqOdtTR+pGE8O1baObEs1bMG1ukY110IVZmBCSUhnCAQCfDAtEtEBrlDVNeGZT9Pw2Sn9/Wt+1iXG1DJCeoJAIMCbj4UiMVSbJT+/LaNTUxK7UADAeyjyftXe8Dtzk+/rIMVns4dDZm+D7JuVmPDBCWw8VmDYIlcdEYoA/PYGPVnjDYHAdFPuAO2iRLqxI+/9kG/chlbNKu814nrzYElDuml03Byl2Do3mnvtJn90suu7CUM7qLi2QY0AeR9uqiug7bPe8PQQONvZ4MKNCrx78LJxT9zntxVIkyu0e2UY2jICAPNGB2K4vwtU9U2Yu+Uciiv1k6+7qnqU1TRoV3Tt4j/hPzW3eB25VML9Y29PZlEFGtUMCifbTu15RIgxbG1E2DonGgmDtf/71+67iGf+k8Z9mNNds9QyQnqMSCjARzOGYHKYJxrUGiz8MgPfpHdydkcn6T6NDurkp9GBCkd8t/hhDPWVoaZBjXWH8hH3/gnsvXDbpLOFGITwdbVHH+mDOwp3xYKx/dFHIkLe7SrsuWD8uiO6rgVvmZ3Rg80GeDhi76KHEerthF9rGzH787N475AR+1i04tvmZaf/ENXvgYG+/Vzs8d4ftesW/OdUoXHJr/9oIGwaSmNfxd1GO9jZiNqeAtsKG5EQG54eCi9nW/xSWoMnPzmNjOu/NVHnNV+HgW4OsLXp2mJTQe6OSAxVgDHgo5SOB1jrmsqHB7iaZHA0IR2xk4iw6ZmheGtqKOxsRDh9tQwJ//gRf96ajtLqBoiEAgRbSZchJSMWwkYkxIdPRWJKpBeaNAx//TYbq3bmmKZ1wQC6/smudH/4uNrj2wUjsX56JDydbXGr4h5e2p6JJzadRr6y40+mbUr8OyAQ4fvIzV0uY1tc+0iwcJx2/4c3v7uIO1XG7bmja94P9e5cMufbV/vaPd28Ds2GYwV4/osM1DY0Gf1cRWW1SCssh0AAPDHUu9Vzxod44LmHtVOzl++4YPg6KyIx8OS/cVoxE4A2CTV2+q2Hky2+WRCLQHkf3K6swx82p2JpciZulNdyC9AZ07rUHt0y3PuyizscYH32mnYg4f0tSYR0N4FAgGdG+OHAktEY6iuDqr4JR5q3M5g90h/2EtN+8OILJSMWRCwS4h/TIvHy+AEQCIDtZ4sw6cOT+CFP2a1rkdQ1qlHY3H/f1VkqQqEAU4d44+iycVg2fgDsJSJkFlVgysZT+PpcUefiiHkeePUODtRquwXC+8m6VMa2PD+2PwZ7aZdsXvBlBu41GJ4I5t4ybrxIa2xtRHj78TB8+FQkJGIhjlwqwbR/phqdGH17Xtsq8nCQvN11El5JGIQIHxkq7zXixe2ZaFQbPn6EG9fRyaShn4s99iwehSeH9gNjwO6s2xj992PYk3UbQsFva9h0VYiXEzfA+vU9eW3GWF3fxK0kHO1PyQjpef7yPtixYCRenfwQHKViPBwkxysJPO0I3Q0oGbEwQqF2Qawtc6LRt48Ev5TWYP4XGXj8k9PYftbArdiNdFmpglrDILO3gXsH60UYyk4iwotxwTi+fBzGDNAug//K/3K4qaZGE4mR03zDD+/XPYMLta1T2vEU54sqMGfLWVTWGvZ65zZ30xg6k6Y9UyK9sX3eCLj2kSD3VhWmbvwJl5VVBv2uRsO4nUH/ENWv3XMlYiE2zBgCJ1sxMosq8LddOQaPl9F1S3VlkKmjrQ3enxaBfS8+jNHBvy1/PW90ICJ8ZJ1+3pZWJg6Co1R7/by172Kr5xzKVaKuUYNAeR+aSUN4IxJq16HKWjMB2+ZGt73wngWynkh6mbED3HBsxTi8MK4/pGIhsm5UYNXOHAz/vyOYvy0dey/cRk1nbuqtON089XG4v+n7yt2dbLFl9nD8NWEgREIBdmfdRsL6H3H0snGDdCtqG7gBouHeMpOW8X5B7g74z6xhcJCKceaXcjyy4STSOliTo6SqDgXNK3eGmShRivJzwa4XRiLQrbkrY1MqjhgwtuPML2W4VXEPjrZiTBys6PB8H1d7vD8tEkKBdq2Yl5IzDeoautjFlpH7hXo744vnYnBmVRy+eT7W5J8G3RyleG+adozM1tTreGvfRTS1aCHZnaXtHpo6xJvGixDeiYQCCDux+rA5o2TEgjnZ2uCvCYNw8q+/w8rEQQh2d0BDkwY/XCzBS9szEfXWYbzw3wx8n11sVJdCS6cLtDfbUf37dnBm5wiFArwwLghfzx8Bb5kdbv56D3O3pGPetnT8crfaoOfQtYr49bWHs337q5t21TB/V+xYEAtvmR1ulN/DU/8+g9f35LY5ZVk3ADTSR9apvVTa4te3D3YuHImYAFdU1zfhz9vS8eet57gutdboBq4+GuFl8ADQ8SEe+Mf0SIiEAuzLLsbjG0+3+zdulNfirqoeIqHApON3FM62iA5w7ZZ/whMHK7iFpj49VYipn/yEnJvaayrnZiV+KtAm5FMjWx9jQwjpGgHjfWvYjlVVVcHZ2RmVlZVwcjLNwDXGGO41mXC9CzPAGEN+STUO5hbjYK4SReW/xWcvESH+IXdMCvPEyKC+EAsNy0PrmzQY8XYK6ps0+G7xKPTv5mWwaxvU2HS8AFtPX0eThkEkFGDasH5YOC4Icoe2Z6F8cuwqNhwrQGKoAu9P6+IOlgaqrm/Cuwcu43/ntZ+aRUIB4h9yx9QhXhgVJOde4/lfZODUlVL8ZXww5jXvUGtKDWoN1h/+GV+eKeJes0mhCvx5dKDeSHtlVR0mfXgSdY0aJM+PMXpsTcb1X7H06yyUVTfAzkaEl+KC8KcRfg8kB1+euY6391/GcH8XbJ0bbYoQe8z+HCXe/C4Xqjo1hAIgIdQTl25XorCsFpPCPPHeH8P5LiIh3cZObGfylj9D79+9NhmpbaxFzFcxJnkuQgghxNKlPZ0GexvTrqFj6P2bumkIIYQQwqtOTVDeuHEj1q1bB6VSiYiICHz88ceIjm67OXbHjh147bXXcO3aNQQHB+Pdd9/FpEmTOl1oU7AT2yHt6TRey8AHtUaDM7+U4/ucYqRcKoGqTn8siVCg3QQs0scZTWqG/52/BVsbIQ4tHdPhzqvdhTGGQ3klWH/kZ67rSSoWIu4hDzwcLMfpglLsyy7GuIFu+GTmUF7KeD/da3woT4nLShWG+bngL+MHGL2MfleVVjfgUJ4SP+QpcfF2FXz72mPh2EDEh3Q8cNUQd6vrsfn4VexIv4mmFrNswryd8PXzsSb5O4SQnmEn7txO2KZgdDfN119/jWeffRabN29GTEwM1q9fjx07diA/Px/u7u4PnH/69GmMGTMGSUlJeOSRR/DVV1/h3Xffxfnz5xEaGmrQ3+yObhqineb58x0V0q/9iozrv+LctXLc/PXBcTTLxg/Ai8277/KpoUmD/52/iW2p17l1LO732exh+P0gDx5K1rtdL6vBpycLsSfrFqrqmvCQpxO2zBkODydbvotGCOFZt40ZiYmJwfDhw7FhwwYAgEajgY+PD1588UWsXLnygfOnT5+Ompoa7Nu3j3tsxIgRiIyMxObNm00aDOm6kqo6pF/7Fdm3KlBR04hHI7wwKqivWU1nZIwh60YFUi7dwckrd3GvUY0VEwdhfAglInxSaxiuldWgn4sdpOKuLdVOCLEOht6/jeqmaWhoQEZGBlatWsU9JhQKER8fj9TU1FZ/JzU1FS+//LLeYxMnTsTu3bvb/Dv19fWor6/nfq6qMmxBJ9J1Hk62mBzuicnhnnwXpU0CgQBDfF0wxNcFyycO5Ls4pJlIKEB/N1oQjBBiPKM6sUtLS6FWq+Hhof8J1MPDA0qlstXfUSqVRp0PAElJSXB2dua+fHx8jCkmIYQQQiyIWc6mWbVqFSorK7mvGzd6dodaQgghhPQco7pp5HI5RCIRSkr0l50uKSmBQtH6CH2FQmHU+QAglUohlfIzc4MQQgghPcuolhGJRIKoqCikpKRwj2k0GqSkpCA2tvVpfLGxsXrnA8Dhw4fbPJ8QQgghvYvR64y8/PLLmDVrFoYNG4bo6GisX78eNTU1mDNnDgDg2Wefhbe3N5KSkgAAS5YswdixY/H+++9j8uTJSE5ORnp6Ov71r3+ZNhJCCCGEWCSjk5Hp06fj7t27eP3116FUKhEZGYmDBw9yg1SLioogvG/fk5EjR+Krr77Cq6++itWrVyM4OBi7d+82eI0RQgghhFi3Xrs3DSGEEEK6F+1NQwghhBCLQMkIIYQQQnhFyQghhBBCeEXJCCGEEEJ4RckIIYQQQnhFyQghhBBCeEXJCCGEEEJ4ZfSiZ3zQLYVSVVXFc0kIIYQQYijdfbujJc0sIhlRqVQAAB8fH55LQgghhBBjqVQqODs7t3ncIlZg1Wg0uH37NhwdHSEQCEz2vFVVVfDx8cGNGzesdmVXa4/R2uMDrD9Ga48PsP4YrT0+wPpj7K74GGNQqVTw8vLS2yqmJYtoGREKhejXr1+3Pb+Tk5NVXlz3s/YYrT0+wPpjtPb4AOuP0drjA6w/xu6Ir70WER0awEoIIYQQXlEyQgghhBBe9epkRCqVYs2aNZBKpXwXpdtYe4zWHh9g/TFae3yA9cdo7fEB1h8j3/FZxABWQgghhFivXt0yQgghhBD+UTJCCCGEEF5RMkIIIYQQXlEyQgghhBBe9epkZOPGjfD394etrS1iYmJw9uxZvovUKW+88QYEAoHe16BBg7jjdXV1WLRoEfr27QsHBwc8+eSTKCkp4bHEHfvxxx/x6KOPwsvLCwKBALt379Y7zhjD66+/Dk9PT9jZ2SE+Ph5XrlzRO6e8vBwzZ86Ek5MTZDIZnnvuOVRXV/dgFG3rKL7Zs2c/UKcJCQl655hzfElJSRg+fDgcHR3h7u6OqVOnIj8/X+8cQ67LoqIiTJ48Gfb29nB3d8eKFSvQ1NTUk6G0yZAYx40b90A9LliwQO8cc41x06ZNCA8P5xbBio2NxYEDB7jjll5/QMcxWnL9teadd96BQCDA0qVLucfMph5ZL5WcnMwkEgn77LPPWF5eHps3bx6TyWSspKSE76IZbc2aNWzw4MGsuLiY+7p79y53fMGCBczHx4elpKSw9PR0NmLECDZy5EgeS9yx/fv3s7/97W9s586dDADbtWuX3vF33nmHOTs7s927d7MLFy6wxx57jAUEBLB79+5x5yQkJLCIiAh25swZdvLkSRYUFMRmzJjRw5G0rqP4Zs2axRISEvTqtLy8XO8cc45v4sSJ7PPPP2e5ubksKyuLTZo0ifn6+rLq6mrunI6uy6amJhYaGsri4+NZZmYm279/P5PL5WzVqlV8hPQAQ2IcO3Ysmzdvnl49VlZWcsfNOca9e/ey77//nv38888sPz+frV69mtnY2LDc3FzGmOXXH2Mdx2jJ9dfS2bNnmb+/PwsPD2dLlizhHjeXeuy1yUh0dDRbtGgR97NarWZeXl4sKSmJx1J1zpo1a1hERESrxyoqKpiNjQ3bsWMH99ilS5cYAJaamtpDJeyaljdrjUbDFAoFW7duHfdYRUUFk0qlbPv27Ywxxi5evMgAsHPnznHnHDhwgAkEAnbr1q0eK7sh2kpGpkyZ0ubvWFJ8jDF2584dBoCdOHGCMWbYdbl//34mFAqZUqnkztm0aRNzcnJi9fX1PRuAAVrGyJj2Znb/P/6WLC1GFxcX9umnn1pl/enoYmTMeupPpVKx4OBgdvjwYb2YzKkee2U3TUNDAzIyMhAfH889JhQKER8fj9TUVB5L1nlXrlyBl5cXAgMDMXPmTBQVFQEAMjIy0NjYqBfroEGD4Ovra7GxFhYWQqlU6sXk7OyMmJgYLqbU1FTIZDIMGzaMOyc+Ph5CoRBpaWk9XubOOH78ONzd3TFw4EAsXLgQZWVl3DFLi6+yshIA4OrqCsCw6zI1NRVhYWHw8PDgzpk4cSKqqqqQl5fXg6U3TMsYdf773/9CLpcjNDQUq1atQm1tLXfMUmJUq9VITk5GTU0NYmNjrbL+WsaoYw31t2jRIkyePFmvvgDzeh9axEZ5plZaWgq1Wq334gKAh4cHLl++zFOpOi8mJgZbtmzBwIEDUVxcjDfffBOjR49Gbm4ulEolJBIJZDKZ3u94eHhAqVTyU+Au0pW7tfrTHVMqlXB3d9c7LhaL4erqahFxJyQk4IknnkBAQACuXr2K1atXIzExEampqRCJRBYVn0ajwdKlSzFq1CiEhoYCgEHXpVKpbLWOdcfMSWsxAsDTTz8NPz8/eHl5ITs7G6+88gry8/Oxc+dOAOYfY05ODmJjY1FXVwcHBwfs2rULISEhyMrKspr6aytGwPLrDwCSk5Nx/vx5nDt37oFj5vQ+7JXJiLVJTEzkvg8PD0dMTAz8/PzwzTffwM7OjseSkc566qmnuO/DwsIQHh6O/v374/jx44iLi+OxZMZbtGgRcnNzcerUKb6L0m3ainH+/Pnc92FhYfD09ERcXByuXr2K/v3793QxjTZw4EBkZWWhsrIS3377LWbNmoUTJ07wXSyTaivGkJAQi6+/GzduYMmSJTh8+DBsbW35Lk67emU3jVwuh0gkemDEcElJCRQKBU+lMh2ZTIYBAwagoKAACoUCDQ0NqKio0DvHkmPVlbu9+lMoFLhz547e8aamJpSXl1tk3IGBgZDL5SgoKABgOfEtXrwY+/btw7Fjx9CvXz/ucUOuS4VC0Wod646Zi7ZibE1MTAwA6NWjOccokUgQFBSEqKgoJCUlISIiAh9++KFV1V9bMbbG0uovIyMDd+7cwdChQyEWiyEWi3HixAl89NFHEIvF8PDwMJt67JXJiEQiQVRUFFJSUrjHNBoNUlJS9PoKLVV1dTWuXr0KT09PREVFwcbGRi/W/Px8FBUVWWysAQEBUCgUejFVVVUhLS2Niyk2NhYVFRXIyMjgzjl69Cg0Gg33D8WS3Lx5E2VlZfD09ARg/vExxrB48WLs2rULR48eRUBAgN5xQ67L2NhY5OTk6CVdhw8fhpOTE9eMzqeOYmxNVlYWAOjVoznH2JJGo0F9fb1V1F9bdDG2xtLqLy4uDjk5OcjKyuK+hg0bhpkzZ3Lfm009mmworIVJTk5mUqmUbdmyhV28eJHNnz+fyWQyvRHDlmLZsmXs+PHjrLCwkP30008sPj6eyeVydufOHcaYduqWr68vO3r0KEtPT2exsbEsNjaW51K3T6VSsczMTJaZmckAsA8++IBlZmay69evM8a0U3tlMhnbs2cPy87OZlOmTGl1au+QIUNYWloaO3XqFAsODjabqa/txadSqdjy5ctZamoqKywsZEeOHGFDhw5lwcHBrK6ujnsOc45v4cKFzNnZmR0/flxvWmRtbS13TkfXpW5K4YQJE1hWVhY7ePAgc3NzM5tpkx3FWFBQwNauXcvS09NZYWEh27NnDwsMDGRjxozhnsOcY1y5ciU7ceIEKywsZNnZ2WzlypVMIBCwH374gTFm+fXHWPsxWnr9taXlDCFzqcdem4wwxtjHH3/MfH19mUQiYdHR0ezMmTN8F6lTpk+fzjw9PZlEImHe3t5s+vTprKCggDt+79499sILLzAXFxdmb2/PHn/8cVZcXMxjiTt27NgxBuCBr1mzZjHGtNN7X3vtNebh4cGkUimLi4tj+fn5es9RVlbGZsyYwRwcHJiTkxObM2cOU6lUPETzoPbiq62tZRMmTGBubm7MxsaG+fn5sXnz5j2QKJtzfK3FBoB9/vnn3DmGXJfXrl1jiYmJzM7OjsnlcrZs2TLW2NjYw9G0rqMYi4qK2JgxY5irqyuTSqUsKCiIrVixQm+dCsbMN8a5c+cyPz8/JpFImJubG4uLi+MSEcYsv/4Yaz9GS6+/trRMRsylHgWMMWa6dhZCCCGEEOP0yjEjhBBCCDEflIwQQgghhFeUjBBCCCGEV5SMEEIIIYRXlIwQQgghhFeUjBBCCCGEV5SMEEIIIYRXlIwQQgghhFeUjBBCeDNu3DgsXbqU72IQQnhGyQghhBBCeEXLwRNCeDF79mxs3bpV77HCwkL4+/vzUyBCCG8oGSGE8KKyshKJiYkIDQ3F2rVrAQBubm4QiUQ8l4wQ0tPEfBeAENI7OTs7QyKRwN7eHgqFgu/iEEJ4RGNGCCGEEMIrSkYIIYQQwitKRgghvJFIJFCr1XwXgxDCM0pGCCG88ff3R1paGq5du4bS0lJoNBq+i0QI4QElI4QQ3ixfvhwikQghISFwc3NDUVER30UihPCApvYSQgghhFfUMkIIIYQQXlEyQgghhBBeUTJCCCGEEF5RMkIIIYQQXlEyQgghhBBeUTJCCCGEEF5RMkIIIYQQXlEyQgghhBBeUTJCCCGEEF5RMkIIIYQQXlEyQgghhBBeUTJCCCGEEF79P8PxSC8wsJ1LAAAAAElFTkSuQmCC", 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" ] @@ -488,16 +480,14 @@ { "cell_type": "markdown", "id": "70e7b061-4bea-4503-878d-964fdedc1241", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## UM2" ] }, { "cell_type": "code", - "execution_count": 117, + "execution_count": 11, "id": "d657634c-3365-4760-8200-ba97c604a704", "metadata": {}, "outputs": [], @@ -536,23 +526,23 @@ }, { "cell_type": "code", - "execution_count": 118, + "execution_count": 12, "id": "0b70e10a-4e20-408c-a7b5-a8ca314fac9b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 118, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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ii3H8xhgMRrwY1OEAh5U40L3+QJJHwjhc4Hke/d7El1dm2K2GKyqWLl2Ka6+9FuvWrcOGDRtwww03YNiwYbj++uuDHhcIBEQh8uWXX8Ln8+GWW27BJZdcgpUrV4qP2717Nz766CMsX74cu3fvxkUXXYQ9e/Zg7Nix+PLLL7FmzRpcc801mD17No499lgApHPoE088gREjRmDPnj24+eab8atf/QpPP/00AOCWW26Bx+PBqlWrkJWVha1btyI7OxsA8Ic//AFbt27FRx99hOLiYtTU1KC/vz+Gb5HBYCSLQS1G7FYSGPIwMcIwiX6vHxPv/jjh77v1/jmGU41VVVV47LHHwHEcxo0bhx9++AGPPfZYmBhZsWIFfvjhB9TW1qKqqgoA8NJLL2HSpElYv349jj76aABEtLzwwgvIycnBxIkTceqpp2LHjh1YtmwZLBYLxo0bhz/96U/44osvRDEiN9FWV1fjgQcewI033iiKkX379uHCCy/ElClTAAAjR44UH79v3z7MmDEDRx11lPh8BoORngzqNA0VI14/n+SRMBiJ57jjjguKpsycORO7du0Ka5y1bds2VFVViUIEACZOnIj8/Hxs27ZNvK26uho5OTni/2VlZZg4cWLQAm5lZWVobm4W///ss89w+umnY8iQIcjJycGVV16JtrY29PX1AQBuu+02PPDAAzjhhBNwzz334Pvvvxefe9NNN+H111/H9OnT8atf/Qpr1qwx4VthMBjJYFBHRhw2KkZYZIRhDhl2K7bePycp75tsQtuQcxyneFsgQPa3uro6/OQnP8FNN92EBx98EIWFhVi9ejWuvfZaeDweZGZm4rrrrsOcOXPw4Ycf4pNPPsFDDz2ERx55BLfeeivOPvts7N27F8uWLcOnn36K008/Hbfccgv+8pe/JOwzMxgMczAcGVm1ahXmzp2LyspKcByHd999V/dzv/rqK9hsNkyfPt3o28YFh5WJEYa5cByHTIct4X/RdOBcu3Zt0P/ffPMNxowZA6s1WNhMmDAB+/fvx/79+8Xbtm7dio6ODkycODG6LwrAxo0bEQgE8Mgjj+C4447D2LFjUV9fH/a4qqoq3HjjjXjnnXfwy1/+EosXLxbvKykpwVVXXYV//vOfePzxx/H8889HPR4Gg5E8DIuR3t5eTJs2DU899ZSh53V0dGDevHk4/fTTjb5l3LALBlaPj4kRxuBj3759WLBgAXbs2IHXXnsNf/vb33D77beHPW727NmYMmUKrrjiCmzatAnr1q3DvHnzcMopp4h+jWgYPXo0vF4v/va3v2HPnj14+eWX8eyzzwY95o477sDHH3+M2tpabNq0CV988QUmTJgAALj77rvx3nvvoaamBj/++CM++OAD8T4Gg5FeGE7TnH322Tj77LMNv9GNN96Iyy+/HFar1VA0JZ4wzwhjMDNv3jz09/fjmGOOgdVqxe23344bbrgh7HEcx+G9997DrbfeipNPPhkWiwVnnXUW/va3v8X0/tOmTcOjjz6KP/3pT1i4cCFOPvlkPPTQQ5g3b574GL/fj1tuuQUHDhxAbm4uzjrrLDz22GMAyOJwCxcuRF1dHTIyMnDSSSfh9ddfj2lMDAYjOXA8bSwQzZM5Dv/+97/x05/+VPNxL774Ip555hmsWbMGDzzwAN59911s3rxZ9fFutxtut1v8v6urC1VVVejs7ERubm60ww3jt//+Aa+u3Yc7Z4/F7bPHmPa6jMHBwMAAamtrMWLECLhcrmQPhzGIYdsiI1Xp6upCXl5exON33Ktpdu3ahd/85jf45z//CZtNXyDmoYceQl5envgnd/GbCfOMMBgMBoORfOIqRvx+Py6//HLcd999GDt2rO7nLVy4EJ2dneKf3DhnJnbW9IzBYDAYjKQT19Le7u5ubNiwAd9++y3mz58PgDRG4nkeNpsNn3zyCU477bSw5zmdTjidzngODYBU2suanjEYDAaDkTziKkZyc3Pxww8/BN329NNP4/PPP8dbb72FESNGxPPtI2JnaRoGg8FgMJKOYTHS09ODmpoa8f/a2lps3rwZhYWFGDZsGBYuXIiDBw/ipZdegsViweTJk4OeX1paCpfLFXZ7MhDFiI9V0zAYDAaDkSwMi5ENGzbg1FNPFf9fsGABAOCqq67CkiVL0NDQgH379pk3wjjCDKwMBoPBYCQfw2Jk1qxZ0KoGXrJkiebz7733Xtx7771G3zYuUAOrm4kRBoPBYDCSxuBeKI+uTcM6sDIYDAaDkTQGtxhhaRoGg8FgMJLOoBYjThtrB89gMBgMRrIZ1GKERkZYnxEG4/DD6KriDAYjeTAxApamYTAYDAYjmQxyMcLawTMGJ7NmzcKtt96KO+64AwUFBSgrK8PixYvR29uLq6++Gjk5ORg9ejQ++ugj8TlbtmzB2WefjezsbJSVleHKK69Ea2ureP/y5ctx4oknIj8/H0VFRfjJT36C3bt3i/fX1dWB4zi88847OPXUU5GZmYlp06bh66+/jjhenudRUlKCt956S7xt+vTpqKioEP9fvXo1nE4n+vr6UF1dDQC44IILwHGc+D+DwUhNBrUYcbCmZwyz4XnA05v4vygW3166dCmKi4uxbt063Hrrrbjpppvw85//HMcffzw2bdqEM888E1deeSX6+vrQ0dGB0047DTNmzMCGDRuwfPlyNDU14eKLLxZfr7e3FwsWLMCGDRuwYsUKWCwWXHDBBQgEgsX+7373O9x1113YvHkzxo4di8suuww+n09zrBzH4eSTT8bKlSsBAO3t7di2bRv6+/uxfft2AMCXX36Jo48+GpmZmVi/fj0AsmJ4Q0OD+D+DwUhN4toOPtWxs7VpGGbj7QMWVSb+fX9bDziyDD1l2rRp+P3vfw+ALE75xz/+EcXFxbj++usBAHfffTeeeeYZfP/99/jss88wY8YMLFq0SHz+Cy+8gKqqKuzcuRNjx47FhRdeGPT6L7zwAkpKSrB169agjst33XUXzj33XADAfffdh0mTJqGmpgbjx4/XHO+sWbPw3HPPAQBWrVqFGTNmoLy8HCtXrsT48eOxcuVKnHLKKQCAkpISAEB+fj7Ky8sNfS8MBiPxDOrIiGhgZX1GGIOQqVOnitetViuKioowZcoU8baysjIAQHNzM7777jt88cUXyM7OFv+oeKCpmF27duGyyy7DyJEjkZubK6ZGQjsyy9+Xplmam5sjjveUU07B1q1b0dLSgi+//BKzZs3CrFmzsHLlSni9XqxZswazZs0y/kUwGIykM7gjI8wzwjAbeyaJUiTjfY0+xW4P+p/juKDbOI7sH4FAAD09PZg7dy7+9Kc/hb0OFRRz587F8OHDsXjxYlRWViIQCGDy5MnweDyq7yt/j0hMmTIFhYWF+PLLL/Hll1/iwQcfRHl5Of70pz9h/fr18Hq9OP7443V+egaDkUoMajEi9RlhYoRhEhxnOF2SDhxxxBF4++23UV1dDZstfNpoa2vDjh07sHjxYpx00kkAiKHUTDiOw0knnYT33nsPP/74I0488URkZmbC7Xbjueeew1FHHYWsLOm7t9vt8Pv9po6BwWDEB5amAWt6xmBE4pZbbsGhQ4dw2WWXYf369di9ezc+/vhjXH311fD7/SgoKEBRURGef/551NTU4PPPPxcX0TSTWbNm4bXXXsP06dORnZ0Ni8WCk08+Ga+88oroF6FUV1djxYoVaGxsRHt7u+ljYTAY5sHECJiBlcGIRGVlJb766iv4/X6ceeaZmDJlCu644w7k5+fDYrHAYrHg9ddfx8aNGzF58mTceeed+POf/2z6OE455RT4/f4gb8isWbPCbgOARx55BJ9++imqqqowY8YM08fCYDDMg+O1luBNEbq6upCXl4fOzk7k5uaa9rot3W4c/eBn4Dhgz6JzxPw1g6GHgYEB1NbWYsSIEXC5XMkeDmMQw7ZFRqqi9/g9qCMjtM8IzwO+QMprMgaDwWAwDksGtRix26RICDOxMhjJhXZ3VfqT9zdhMBiHH4O6moZ6RgChC6sjiYNhMAY5f//739Hf3694X2FhYYJHw2AwEsmgFiM2CweOEzp4s8gIg5FUhgwZkuwhMBiMJDGo0zQcx7GVexkMBoPBSDKDWowAssXymBhhMBgMBiMpDHoxwlrCMxgMBoORXJgYESIjbrZYHoPBYDAYSYGJEdYSnsFgMBiMpDLoxYiDLZbHGITwPI8bbrgBhYWF4DgO+fn5uOOOO3Q9d9asWREfy3Ec3n333ZjHqZd7770X06dPT9j7xUKivxsGIx0Y1KW9gMwzwtI0jEHE8uXLsWTJEqxcuRIjR46ExWJBRkaGaa/f0NCAgoIC014vEnfddRduvfVWQ8+prq7GHXfcoVuEmYX8u6mrq8OIESPw7bffpo2YYjDiwaAXIzQywvqMMAYTu3fvRkVFBY4//vi4vH55eXlcXlcN2qk1HUj0d8NgpAODPk3DPCOMwcYvfvEL3Hrrrdi3bx84jkN1dXVY6uXpp5/GmDFj4HK5UFZWhosuuijoNQKBAH71q1+hsLAQ5eXluPfee4Pul6ci6urqwHEc3nnnHZx66qnIzMzEtGnT8PXXXwc9Z/HixaiqqkJmZiYuuOACPProo8jPz9f1mULTNL/4xS/w05/+FH/5y19QUVGBoqIi3HLLLfB6vQBIqmnv3r248847wXFc0CKZq1evxkknnYSMjAxUVVXhtttuQ29vr3h/dXU1Fi1ahGuuuQY5OTkYNmwYnn/+efF+j8eD+fPno6KiAi6XC8OHD8dDDz2k+N2MGDECADBjxgxwHIdZs2Zh1apVsNvtaGxsDPqMd9xxB0466SRd3weDkW4wMcL6jDBMhOd59Hn7Ev5nZPHtv/71r7j//vsxdOhQNDQ0YP369UH3b9iwAbfddhvuv/9+7NixA8uXL8fJJ58c9JilS5ciKysLa9euxcMPP4z7778fn376qeb7/u53v8Ndd92FzZs3Y+zYsbjsssvg8/kAAF999RVuvPFG3H777di8eTPOOOMMPPjgg7o/kxJffPEFdu/ejS+++AJLly7FkiVLsGTJEgDAO++8g6FDh+L+++9HQ0MDGhoaAJCI0VlnnYULL7wQ33//Pd544w2sXr0a8+fPD3rtRx55BEcddRS+/fZb3HzzzbjpppuwY8cOAMATTzyB999/H//617+wY8cOvPLKK6iurlYc47p16wAAn332GRoaGvDOO+/g5JNPxsiRI/Hyyy+Lj/N6vXjllVdwzTXXxPSdMBipCkvTMDHCMJF+Xz+OffXYhL/v2svXItOeqeuxeXl5yMnJgdVqVUwZ7Nu3D1lZWfjJT36CnJwcDB8+HDNmzAh6zNSpU3HPPfcAAMaMGYMnn3wSK1aswBlnnKH6vnfddRfOPfdcAMB9992HSZMmoaamBuPHj8ff/vY3nH322bjrrrsAAGPHjsWaNWvwwQcf6PpMShQUFODJJ5+E1WrF+PHjce6552LFihW4/vrrUVhYCKvVipycnKDv4KGHHsIVV1whRonGjBmDJ554AqeccgqeeeYZuFwuAMA555yDm2++GQDw61//Go899hi++OILjBs3Dvv27cOYMWNw4oknguM4DB8+XHWMJSUlAICioqKgcVx77bV48cUX8b//+78AgP/85z8YGBjAxRdfHPX3wWCkMiwyIhhYWZ8RBoNwxhlnYPjw4Rg5ciSuvPJKvPLKK+jr6wt6zNSpU4P+r6ioQHNzs+bryp9TUVEBAOJzduzYgWOOOSbo8aH/G2XSpEmwWq2Gxvjdd99hyZIlQSsGz5kzB4FAALW1tYqfheM4lJeXi6/9i1/8Aps3b8a4ceNw22234ZNPPjE89l/84heoqanBN998AwBYsmQJLr74YmRlZRl+LQYjHRj0kRGapul1+5I8EsbhQIYtA2svX5uU9zWLnJwcbNq0CStXrsQnn3yCu+++G/feey/Wr18vejjsdnvQcziOQyCgLejlz6EejUjPiYVoxtjT04P/9//+H2677baw+4YNG6brtY844gjU1tbio48+wmeffYaLL74Ys2fPxltvvaV77KWlpZg7dy5efPFFjBgxAh999BFWrlyp+/kMRrrBxIhQTXPff7ZiV3MPfnfOBGQ5B/3XwogSjuN0p0tSGZvNhtmzZ2P27Nm45557kJ+fj88//xw/+9nP4vJ+48aNC/OuhP5vNg6HA36/P+i2I444Alu3bsXo0aNjeu3c3FxccskluOSSS3DRRRfhrLPOwqFDh1BYWBg2BgBh4wCA6667DpdddhmGDh2KUaNG4YQTTohpTAxGKjPo0zSnjSsVUzWvrt2H3/37hySPiMFILh988AGeeOIJbN68GXv37sVLL72EQCCAcePGxe09b731VixbtgyPPvoodu3aheeeew4fffRRUJWL2VRXV2PVqlU4ePAgWltbARD/x5o1azB//nxs3rwZu3btwnvvvRdmYNXi0UcfxWuvvYbt27dj586dePPNN1FeXq5YGVRaWoqMjAwsX74cTU1N6OzsFO+bM2cOcnNz8cADD+Dqq6+O+fMyGKnMoBcjFx45FNv/72z846qjAAAf/tCA1h53kkfFYCSP/Px8vPPOOzjttNMwYcIEPPvss3jttdcwadKkuL3nCSecgGeffRaPPvoopk2bhuXLl+POO+8UDaPx4P7770ddXR1GjRolGkmnTp2KL7/8Ejt37sRJJ52EGTNm4O6770ZlZaXu183JycHDDz+Mo446CkcffTTq6uqwbNkyWCzh063NZsMTTzyB5557DpWVlTj//PPF+ywWC37xi1/A7/dj3rx5sX9gBiOF4XgjNYFJoqurC3l5eejs7ERubm7c3uf8J1fjuwOd+N05E3D9ySPj9j6Mw4OBgQHU1tZixIgRcT1oDlauv/56bN++Hf/973+TPZSkce2116KlpQXvv/++5uPYtijR3D2ADXXtOHNiGWzWQX++nXT0Hr/ZLyXj0mOIQe297w4meSQMxuDjL3/5C7777jvU1NTgb3/7G5YuXYqrrroq2cNKCp2dnVi9ejVeffVVw23uBzs/eWI1bn5lE17+Zm+yh8IwgGExsmrVKsydOxeVlZW6Fnx65513cMYZZ6CkpAS5ubmYOXMmPv7442jHG1dOGlMMANjR2A0PK/VlMBLKunXrcMYZZ2DKlCl49tln8cQTT+C6664DQMp05eW28r9XXnklySM3n/PPPx9nnnkmbrzxRs3eLYxwmrtJmv2zbU1JHgnDCIbLRnp7ezFt2jRcc801upz1q1atwhlnnIFFixYhPz8fL774IubOnYu1a9eGNVJKNkPyM5DjtKHb7cOe1h6ML49fSojBYATzr3/9S/W+ZcuWia3cQykrK4vXkJIGK+ONHQ7xMz8zzMewGDn77LNx9tln6378448/HvT/okWL8N577+E///lPyokRjuMwviIH6+vasaOxm4kRBiNF0OpiymAoEcdCLEYcSLhnJBAIoLu7O6zeXo7b7UZXV1fQX6KgAmRbQ3fC3pPBYDAY5mJhaiStSLgY+ctf/oKenh7NNRYeeugh5OXliX9VVVUJG9/4ihwAwPbGxAkgRnoTzy6iDIYe0qAoMuFYmBZJKxLaavTVV1/Ffffdh/feew+lpaWqj1u4cCEWLFgg/t/V1ZUwQTK+nIiRbQ1MjDC0cTgcsFgsqK+vR0lJCRwOR1ybdDEYSvA8j5aWFnAcF9amfjDDIiPpRcLEyOuvv47rrrsOb775JmbPnq35WKfTCafTmaCRBTOyOBsA0NTlxoDXD5fdGuEZjMGKxWLBiBEj0NDQgPr6+mQPhzGI4TgOQ4cODVoYcDASCEgRIqZF0ouEiJHXXnsN11xzDV5//XVxCfFUJT/TDpfdggFvAM1dbgwrSv91Rhjxw+FwYNiwYfD5fIrrizAYicButw96IQIAAz5pH2RRyvTCsBjp6elBTU2N+H9tbS02b96MwsJCDBs2DAsXLsTBgwfx0ksvASCpmauuugp//etfceyxx6KxsREAkJGRgby8PJM+hnlwHIeKvAzUtvaiobOfiRFGRGh4nIXIGYzk0u+RiZEkjoNhHMMG1g0bNmDGjBliWe6CBQvE9RsAoKGhAfv27RMf//zzz8Pn8+GWW25BRUWF+Hf77beb9BHMpzyXtFNu6BxI8kgYDAaDoZc+mRjx+JmxPJ0wHBmZNWuWpnN7yZIlQf+nY/OeijwmRhgMBiPdGPD6Fa8zUh+2No0C5YIYaezsT/JIGAwGg6EXeWRkwMsiI+kEEyMKVORnAGCREQaDwUgn5GLEzdYXSyuYGFGgQvCMNHYxMcJgMBjpgjw142ZpmrSCiREFaJqmvoOJEQaDwUgXgtM0TIykE0yMKEANrK09bnhYqI/BYDDSgn65gZXN3WkFEyMKFGY5YLeSKvWWHneSR8NgMBgMPfR7fOJ1lqZJL5gYUYDjOBRmOQAAh3o8SR4Ng8FgMPQQlKZhkZG0gokRFQqzyNo4bb0sMsJgMBjpgDxN4w/w8LLGZ2kDEyMqFGaR1t6HellkhMFgMNIBeTt4gJlY0wkmRlSgkREmRhgMBiM96A8RH6zXSPrAxIgKRdQzwsQIg8FgpAV9KpGRpq4B9Lp9Sk9hpAhMjKhQyMQIg8FgpBWhkZEBbwDfH+jAyQ9/gateWJekUTH0wMSIClSMtDExwmAwGGlBqGek1+3DTf/cBLcvgA1729E14E3SyBiRYGJEBZamYTAYjPSizxOcivlsWxMOdkgLnm452JnoITF0wsSICixNw2AwGOlFf8hKvTXNPUH//3CAiZFUhYkRFYqyhTQN68DKYDAYaUF/SGRkf3tf0P8/sMhIysLEiAq0tLdrwMca5zAYDEYaQEt5LWQ1D+xrI2LkmBGFAJgYSWWYGFEhP8MubtDtLFXDYDAYKY9XECM5LtK0smuAREpOHVcKANjb1hdmcmWkBkyMqGCxcCjIZBU1DAaDkS54/DwAIDfDFnT72LJsZDqsAIDGroGEj4sRGSZGNMjPJOq6vY+JEQaDwUh1aEo9x2kPur00x4XyPBcAoKGzP+x5jOTDxIgGeRlCqK+f1aYzGAxGquMR0jTZruDISEmOExWCGGnsZJGRVISJEQ0kMcLaCDMYDEaqQyMj+RlSZITjSHVkWa4gRliaJiVhYkQDKkY6WWSEwWAwUppAgIcvQDwjx40sEm8vzHTAbrWwyEiKw8SIBkyMMBgMRnrgkbVgOGNiWdjt5XkZAIAGJkZSEiZGNGBihMFgMNIDeT+okhyneL1bKO8tF9I0TSxNk5IwMaJBLhMjDAaDkRZ4hbJeAHBYLbhp1igAwKVHVwGAmKZhkZHUxBb5IYMXJkYYDAYjPaCVNDYLB4uFw/+eOQ7HjCjEkcMLAEAs7W3tccPrD8BuZefiqQT7NTRgaRoGg8FID2iahooMi4XDqeNKkSt0Yy3MdMBhtYDnWaomFWFiRAPWZ4TBYDDSA48oRjjF+y0WDsXCAqitPayRZarBxIgGLDLCYDAY6QGNjDhs6oe1QkGMHOplq7GnGkyMaCBGRga84Hk+wqMZDAaDkSyoZ8Sh4QUpElZjZ5GR1IOJEQ2oGPH6efR72UqPDAaDkaqInhGNyEiRGBlhYiTVYGJEg0yHFTYLyT+yVA2DwWCkLh4fiV5rVckUZQkrsfewNE2qwcSIBhzHMd8Ig8FgpAHUwKqZpskmaZo2FhlJOZgYiYAoRvqYGGEwGIxUxeuLnKYpFCMjTIykGkyMRIA1PmMwGIzUR6ymUSntBSCW9jLPSOphWIysWrUKc+fORWVlJTiOw7vvvhvxOStXrsQRRxwBp9OJ0aNHY8mSJVEMNTkwMcJgMBipjyek6ZkStJqGeUZSD8NipLe3F9OmTcNTTz2l6/G1tbU499xzceqpp2Lz5s244447cN111+Hjjz82PNhkwDwjDAaDkfqIpb160jS9HtauIcUwvDbN2WefjbPPPlv345999lmMGDECjzzyCABgwoQJWL16NR577DHMmTPH6NsnnLwM8hV1CSs/MhgMBiP1oAvlaUZGhDSN2xdAr8ePbCdbni1ViLtn5Ouvv8bs2bODbpszZw6+/vpr1ee43W50dXUF/SUL1hKewWAwUh+vjmqaTIcNGXYrAJaqSTXiLkYaGxtRVlYWdFtZWRm6urrQ39+v+JyHHnoIeXl54l9VVVW8h6kKS9MwGAxG6qMnTQNI0RFW3ptapGQ1zcKFC9HZ2Sn+7d+/P2ljYWKEwWAwUp9IC+VRaOOzQ6y8N6WIe8KsvLwcTU1NQbc1NTUhNzcXGRkZis9xOp1wOp3xHpoumBhhMBiM1Mero5oGAPIziRhp72NiJJWIe2Rk5syZWLFiRdBtn376KWbOnBnvtzYFVtrLYDAYqQ9N00QSIwWZZE7vYI0sUwrDYqSnpwebN2/G5s2bAZDS3c2bN2Pfvn0ASIpl3rx54uNvvPFG7NmzB7/61a+wfft2PP300/jXv/6FO++805xPEGdYZITBYDBSHxoZcUbwjLDISGpiWIxs2LABM2bMwIwZMwAACxYswIwZM3D33XcDABoaGkRhAgAjRozAhx9+iE8//RTTpk3DI488gr///e9pUdYLALkuJkYYDAYj1dFT2gsA+TQywub0lMKwZ2TWrFmazWKUuqvOmjUL3377rdG3SgnyhA3X4wtgwOuHSygLYzAYDEbq4NadpiGRkQ4WGUkpUrKaJpXIdthgEczZrNcIg8FgpCZin5GIaRpygtney+bzVIKJkQhYLBwzsTIYDEaK49VZ2lvAPCMpCRMjOmAmVgaDwUht9DY9k9I0bD5PJZgY0QETIwwGg5Ha6O8zIqRpWGQkpWBiRAdMjDAYDEZq4xGqabTWpgGAgixpsbx+jz/u42Log4kRHTDPCIPBYKQ2XlpNEyFNk+Wwir6Sjn4WHUkVmBjRAYuMMBgMRmrjEVft1TawchyHvAzBxMoqalIGJkZ0QBufdQ/4kjwSBoPBYCiht7QXkLeEZ5GRVIGJER3kuEhvONZnhMFgMFITvWvTAPLyXh1zessO4PlTgXduANp2xzRGhjpMjOiAeka6BpgYYTAYjFTEo7OaBjBQUeP3Af/+f0D9JuD7N4ClcwFvf8xjZYTDxIgOcoXICEvTMBgMRmqit7QXMNASfuOLQL2wlInFDnQdBL55JqZxMpRhYkQHLDLCYDCU0Fqni5FYvD7yW0RatRcA8rNoZERjTg8EJOFx9sPA+U+R61/9ldzHMBUmRnRADaxd/SwywmAwCF9sb8YR//cpXv66LtlDYcBYmkZXS/g9nwOHdgPOXGD6FcDkCwGrExjoADrqTBgxQw4TIzrIyxAMrCwywmAwAOxr68PVS9ajvc+Lv67YlezhMCDrMxKhtBcA8mm7Bq3IyIYXyeX0KwBnNmC1AaXjyW2NW2IaKyMcJkZ0IEVGvCwsy2AMUv7vg6246oV18PkDeGXtXvH29j6v6FdgJA9jBtYIkZGeFmDncnL9yKuk28umkMumH6MeJ0MZW7IHkA7kCGIkwAO9Hj+ynexrYzAGG/9YXQsA+G9NK/a394m3+wM8djX1YGJlbrKGxgDgCwjt4A31GVGJjPzwJhDwAZVHAKUTpNvLJpHLJhYZMRsWGdGBy24RQ3/dLFXDYAw6AgEpInqox4PGzoGg+3842JHgETHk8DwPv/AbWS2R0zR0fRrVyMjmV8nl9MuDb2diJG4wMaIDjuOYiZXBGMQM+KQF1boHvKIYOXZEIQDgh4OdSRkXg+CTiUWbDjFC+4x09nuDhCYAoOF7oOkHwOogplU5ZZPJZXsd4O6OZciMEJgY0Qkr72UwBi/y1V3b+7xo6nYDAM6YWAYA+LG+KynjYhD8MkGhJzKSL6xNE+AV5vTNr5DLcecAmYXB92UVARnCbe110Q6XoQATIzrJZS3hGYxBS59MjGxv7II/wMPCAUcOLwAANHQMqD2VkQDkkRE9BlaHzSJ6/4J6jQQCwJZ3yPXpVyg/Ob+KXHYeiGqsDGWYGNEJi4wwGIOXAa8kRr4/QFIyJTlODCnIAAA0dw/AxypqkobfbywyAkipmqAurM0/Ar3NgD0LGDlL+Yl5ghjp2B/NUBkqMDGiE2mxPOYZYTAGG/0yMdIg+EXK8zJQnOWEzcIhwAMtPe5kDW/Q45N1RLVyRsWI7ARz9xfksvoEwOZQeeIwctm5z/A4GeowMaITea8RBkOT/euAZ04EdnyU7JEwTEKepqGU5zphsXAoy3UBkEQKI/HQNI2FAyw6IyOKXVj3CGJELSoCAHlDySWLjJgKEyM6oWmabjeLjDA08HmAf5xB3Pjv35bs0TBMQh4ZoVTkkRRNeR4RI6HlvozEQcWIzaL/kCY1PhNOML0DwN415PrIU9WfmMc8I/GAiRGdMAMrQxcbXpCu9zYDvW3JGwvDNPoVIiM0IsLEiERz9wB+9+8fUNPck9D3pZ4Rm45W8JSCUM/I/m8A3wCQXR7c6CwU0cDKIiNmwsSITpiBlaGLXZ8E/1/zaXLGwTAVJTFyzAhSSVMhiJLGLiZG/vTRDryydh/OeeK/CV06g3pG9JpXAYWW8HtWksuRswAt30me4BnpaSLRFIYpMDGik4Q1PQsEgL1fA7s/B/o74vteDHPheaBhM7k+6nRyufPjpA2HYR59IWmaK44dhiOHk34TNDLCPCPAf3e1AAA8vgC+2NGcsPf1i2ka45ERMU1DzaujNFI0AOk9Ys8k17sOGhqnJj3NwKuXAlveNu810wgmRnQiVtPEOzKy7jngxbOAly8AHp8irRzJSH06DwB9bYDFBhz5C3JbW01Sh8QwhwEhMjJ1aB7+eul03H/+ZPE+KU3Tn5SxpQqHej1o7pYqil7+eq/Go83F66et4PUf0qiBtbPPS9KpDd+RO7TMqwCJmlATq5mpmu//Bez8CHjrmkFpfmdiRCdimiaenpFAAFj7nPS/uwv48Jdsuep0gUZFSicABdXkendjskbDMBFqYJ1UmYfzpw8JSgdUCGKkfpA3PvtmT7A/antj4tql08iI3YBnJE+MjHiAms8A8KTde065jifHoddIy3bp+ucPmPe6aQITIzqhaZrugTimaWq/BNprAWcusPAgMGEuwPuJIElg/pURJfWbyWXFdCCnglzvbQH8zGeU7tDS3kyHNey+0hwiRlp63An1SaQa62oPAQB+NmMIAJK2StTCotF4RmhkpKPPC+xcTm4ce5a+J8fDxCoXI4dqB92cz8SITnIzpDRN3CacLW+Ryyk/B5zZwFl/Amwu4vI+uDE+78kwDxoZqZwOZBYBFjsAnhjdGGkN7cCaYQ8XI8XZTgDEJ9EziEv/D3aQNNURwwtQmkO+k0RV1cTiGenu6wNqVpAb9YoRsyMjPA80y8SIt5dExgcRTIzohEZGvH4eA944tX3ev45cjp1DLvOGABN/Sq4z70j8+Ph3wJPHAB0xdFTkeVlkZAZgsUjhXpaqSXv6PERkZChERjIcVmQJt7f2qCxJPwhoEzrQFmc7MaYsGwCwK0FihPYZiaaaZqJvG+DuBDKLgSFH6Hwy7cJqkhjpPAB4uonfzEG+O3TVm/PaaQITIzrJbPgGK5x34TzLmviYWPvbgdad5PqQo6TbqRFyy9tEhe/4CPjgThLGiyddDaSqx3eYt7je+THw9ZNA6w7g03uif52ug0BfK5lMyiaR20Qx0hD7OBlJpV84AVGKjABAkRAdaRvELeGpECvOdmBMaQ4AYHeixIjfeNOzXJcNVguH0y2byA1jzgQsyr9vGHkmp2loiqZotOQ3M7NSJw1gYkQP7h5w/74Jo7h6/Mn+PPrrt0d+jlEOCjtE4UiyTDVl2HHA0KMBXz/w+GTgtUtJY61/XUm6fcaDNX8DHh1Pqnr+fjqw8o9Ay874vJccnge2fZA4w67PA3x4l/T/j+8A9d9G91o0KlIyAbATDwGLjBw+0D4jSpERgByAAaB1UIsRKTIyujTRkREiFo00PeM4DvkZdpxmEfb5cTpTNICsmuYgKTyIleat5LJ0ApBbSa6zyAgjjK+fFBdFyuA8KP58gTkboJwDG8jl0KODb+c44MJ/AK784NsbfwDWPmPuGABy4KROblsGeZ+VDwHv3mj+e4Xy1ePAG1cAS84F+g7F//22vEV+1+wyYNRp5DbaDtoool9kmnQbNbGyyEja0+8laRolAysgRUYGW5qmvqMfe9t60efxiSbf4hxJjOxuSV3PCABMdjVjlKUBAYtduwV8KDkVAGcFAl6gx4STDeoXKWFihKGF0AznlYzL0cs7kd28EfjuNXPf48B6cilP0VAKhgPXLAfOfxr4dR1w2h/I7Q3fmzsGAPjqr6Ql8tBjgNu+BY6YR24/uDG+Z/h1XwGf3UuuD3QAXyyK33sBREyufpxcP+5mMgkA0X9GeSUNhUVGDhtoZMSlkqYpFsXI4ImMBAI8jv/j5zjlzyuxu7kXAOC0WZDlsGJoAVm3p6FjAAFBKKB9L7D9w7hUiUTjGQGA0zgSkT5UfBTgytX/RKsNyCVVQ6asUdOyjVyWTpBel6VpIvPUU0+huroaLpcLxx57LNatW6f5+Mcffxzjxo1DRkYGqqqqcOedd2JgIE1q8v1e8ax3U85peNx3Ibn98wcAv0nOeZ6XxMhQBTECkI10xhVARoFkcILJO7V3APj2n+T6Kb8GciuA8/4GVAqmrtBW52by5R/JZf5wcrnxRcAdx7OqncuJT8SZCxx1NZBTRm6PRjjIO69WzpBuZ5GRwwat0l5AStO0mRUZ2f05sOJ+wNNnzuvFgV6PNP99uo1UjBVnO8FxZCVjCwd4/AG09rqB798EnjoWeP1yYN1i08fij2KhPAA4wfs1AKCu2EBUhELLe2MxvgPkxKhlB7nO0jT6eeONN7BgwQLcc8892LRpE6ZNm4Y5c+aguVm59e+rr76K3/zmN7jnnnuwbds2/OMf/8Abb7yB3/72tzEPPiE0bSGRAlc++rKrsdQ/BwOOAqC73tjBub8D+PFdIBC+xgXadpNogM1Fmu5EghN+Nt7kVNGuT0g5We5QKW0BSNU98WptfmADULuKmD9/8SE5Mwj4pI6IZsPzwOrHyPWjrwVceWRxLCC6kGtXPeknwlkl8yogRUa6mBhJd7RKewGTIyOBAPD29cB/HwHevi5l+03Iey6tqWkFIIkyu9Ui9l9pbOsClt1FfG8ASXsrzYMx4PUb94yguxGj3T8CAH7MO8n4m5plYu3YC3j7AKsDKBjBxIheHn30UVx//fW4+uqrMXHiRDz77LPIzMzECy+8oPj4NWvW4IQTTsDll1+O6upqnHnmmbjssssiRlNSBtHLcRRyMh3wwI6tpXPJbRuX6HuNQAB45SLgzauCV3UV30OIilRMB2yOyK9HF3EyW4z88Ca5nHIhKU2ljD6DXO79KuqJsbPfi2uXrMfiVXvC79wolC1PuZicbdDyunj0VulvBz76NXBgHWB1AsfeRG4XIyNR9ASRd161Z0i3Z5WSy77WqIfLSA36EpmmObBe2mZ2fJiy6xvJxciGve0ApO8BACryiRjx7PycnGw5c4nw7xDSNSbijyZNs/0DAMCmwGgc9BcYf1PRxBpjmoZW0hSPC07/sDSNOh6PBxs3bsTs2bOlF7BYMHv2bHz99deKzzn++OOxceNGUXzs2bMHy5YtwznnnKP6Pm63G11dXUF/SUPm5aC9RtYV/YTcVvOpvrD+ty9Lr6PULyRSiiaUeERGOg9KXQgnXxR8X9lEABw5kPdGd2B9emUNVmxvxoPLtqFT3lLfOwBs/Q+5PuMKcjnkSHIZKkZ6W4HFpwPfRGncrVsNPDqRrP8DAGfcL4mQWCIjSn4RgDQ+A4gZ12zDMyOh0Hbw6gZWB47mtmN4hwknWdv/E/z/gdQ8cVPqrioXI5X5RJjn1QqfZ9qlwFHXkOvfvW7qWHzRGFi3kXEt9x+N9t4o0mtUjMTa+EyspBlPLmlkZKAzvqnqFMOQGGltbYXf70dZWVnQ7WVlZWhsVJ7EL7/8ctx///048cQTYbfbMWrUKMyaNUszTfPQQw8hLy9P/KuqqjIyTHOhJtHKGcgRxMhevpIYPPkAsOWdyK8hX2+mZVv4AZ1ONqGVNGqIYsTE8O3qxwC/Bxh+IlAxNfg+e4bU5Efeslgn/R4/3twgnT0s+0GWtqj5lDQcyh0CDDue3CaKkU3BL/TRr4CDG4DlvzE8BvA8sHwhCYcWjwMu+SdwnKxCiIqSgU7Aa3DBM3nnVTmZhcJ7+8lnZKQtYppGRYyUWbrwT8ci/GXgHuDTu6N/I1reDgBVx5FL6idIMZSWxijKliK7lXkuWBDA0OYvyQ2TLiDdpQGyFsyAeSeZUmRE5yGt7xBQ+18AwMeBo6WVe40gtoSPMTIiVtIIYsSZQ6JIwKDym8W9mmblypVYtGgRnn76aWzatAnvvPMOPvzwQ/zf//2f6nMWLlyIzs5O8W//fhP7/xvB5wHadpHrZZOCWsKLOxVNbajh7paUb3YZETA7lkn39x2S+moMO07fuMyOjLTvBTYtJddn/Vr5MXRHaTU+Ma7Y3oRDsjOPdzbJdt7v/0UuJ8tSQxXTAXCk7LZH5kXasdzwe4vsXA40fg/Ys0hl0oS5wfe78knaBjDWvj2o8+r04PtsTsBBmj8lpFSZERe8/oC4Kmym3ab4mPK978PJCQfnr/4KHIgyxdi8laxPZXUCM28mt9FmiCmGUvPHopDIyCiuHhn+brLfVR0LlE4EisYAfrcUiTUBw5GRncsB3o+uvHHYy5ejoy+ayIhJnhGxkmaidJvoGxk8qRpDYqS4uBhWqxVNTcGTdVNTE8rLlVc6/MMf/oArr7wS1113HaZMmYILLrgAixYtwkMPPYSASuja6XQiNzc36C8ptO4kRkpnHpA3VEzTdPV7icrnrED9JqC9Tv016jcD4IkplIYod38u3b9nJbm/dKK+1SIB88XIZ/eQqMiIk4FqFSNXyVhyGUXzs71tpCJg5kiSttiwt52USg50SvnwqRdLT3DlAiXjyHWaqvH7yHoN0UJFz1FXSxELORwnK8U1IEa6G4DeZrItlCuYj+l79bWF38dIC2iKBgCcdoUpk+fh+jEk7VDzWXRvRqMio06VqtgO7UnJxRa7hMjIkHzJJ0VLegGgIi8DMyzCydyQI0h3U44jcycA/Phv08biM2pgFTwrncOJOb89KjEipGncXWQui4aAX5pTaZoGGJQmVkNixOFw4Mgjj8SKFSvE2wKBAFasWIGZM2cqPqevrw+WkNCZ1UpCnSm/wqW8Kx7HIS9DJkayS6S0yp4v1V+DHkyHHEEO9gDxLtDPToWJkYY7ZoqRxi3CpMABcxZJ5thQigVxEEVkpF5YQOuo6gLkZ9rB88Ce1h4y8frdJOoSWkVE+63Q70/eGbVwpOExhK37o0ROFL4RsfPq+GDzKkX0jTAxkq4MyMWITWHKPLQHXPNWeGDDH72XktvkJxxGoH6R8T8hBzt7FjkhOqRg/E4y1DNy3MgifHT7Sfj9uRNw2vhS8f7KfBemczXkH5p6BSQxUvNZ9AfxEAw1PQv4xRRNYBQx53dEk6ZxZAEZwslGtL6RQ7VkDrRlAPnV0u1MjERmwYIFWLx4MZYuXYpt27bhpptuQm9vL66++moAwLx587Bw4ULx8XPnzsUzzzyD119/HbW1tfj000/xhz/8AXPnzhVFScrSJKRPykj4LE9Y5VE0YI48hVzWaokRqRoHQ44k5bu9LSTqwvNCZATBpbSRMFOM/Ch4XsafC5RPUX8cjVREERlp6CQ9ZSrzMzC6hPRIqWnuATa/Sh4w5aJwERRaURPtmSZAcrpdB0j0gp5tKpEdRUWNml+EwsRI2uPxkf3MYbOAUxLrgo9qr7UaHwSEVOuB9cY9Ed2NpOMxOGDc2WSfKB4jvEfq+UaoZyTHZcOEilxcd9JI2K3SIYVERnYDAHyVMjFSOoGc3Pg9ZK2taJFF1n1GPCP1m4mHy5mHjOFkXO19Hqk5mxFi9Y3QFE3JuOAKRrGihokRVS655BL85S9/wd13343p06dj8+bNWL58uWhq3bdvHxoaJNPN73//e/zyl7/E73//e0ycOBHXXnst5syZg+eee07tLVKHJiEyIvSOyBciIx1UjIygYmSVspmU56XS4CFHEg9B1THk/7r/klLZzv2kidnw4/WPyywxwvPA1vfIdXq2okaxkKbpridVNQagkZGKPJfYJrqzdjOwdzURCNMuD3+SvKKG54GdskkrYLDZHI2KlE8GnNnqj4slMhLqF6EwMZIedNWTvjYKqWMqRpxWlemyjZz9tzqrcIAvRXfWcGJaNrq0ABXepROArGJynZ4EpKBvhEZGcl3KPppCuxdjORIxaC+QmeLlqZpt/1F4pg42vwr8cRjww1sADEZG9pCO2hhxEvKzSTQzwCsbciMSq2+kWdZ5VU4skRF3N/DuLaaXT8ebqAys8+fPx969e+F2u7F27Voce+yx4n0rV67EkiVLxP9tNhvuuece1NTUoL+/H/v27cNTTz2F/Pz8WMcef8Q0DREj8jRNIMCTNI09k0Q66GPltO0mngKrQzojp56Mre8D6/9Brk/5OeDI1D8us8RI8zYykVqdZMVKLTLype6oBpuRUTFSmZ8hipERtUJUZMJPgLwh4U8qm0TGNdBJhJv8PY2WyVIxMvQY7cdFIxxYZCT98fQCz50CPHcy8ORRYWLb45ciI4oIYqQrk+wf9dlChJFuG3qh1WPy6F3BCHJp5GDXsR/ojf/2JkVG7Ir3W1u2wcrxaObz0cSH9PGgFXtGzOKU+m+Bd28CPN3A928AkFbtterxjNBI9shZcAjt64EYfSOxipGS8cG3x9Jr5L35wOZ/km63aQRbm0aN/nZpQxBUa64gRgI80O32kQZlwwSvjJJvpHYluaw6VhIbky8ELHayQ9AUyVFXGxubWU3Paj4llyNn6VuXgbY6p9EAHfS6faLRjUZGbPBhRpdwdnL0dcpPtNqlKNLS88ilTVgN12hkhB4UIpVO0/yv3sqXrnoymXIW9c65mQXGXvNwxNNH1gF67TJD207C+P5fxIQMAId2S9FMAXmaRpFWIkb6c4lw2OsYRW43unYU9UUNkS0pYPQMufMgWd3776cbe+8okKdpFGkm3U23BYahJbQZnEUQMEaNuX4fOeunZBOPCl211x4pMuLtB/atJddHzgIA5GeScuSoxIj4+0RZgktbJcgraYJe12BkhOeBre9GN5Ykw8SIGlSx5g4lUQGQ7osuwU3fpcc3Qv0gNJ0DAEWjpJI9AJj4U6BiGgxhVp+R2lXkUtgpI0LP/uVmUhX2tfXh7Y0HxKhIjtOGHJcdo0uzcZRlJ7LRCz6zCBh+gvqLnHC7cEX4nLTihjfYSpqGuGnIWw1a+aI3DUUjLqWT1CNb8sZng5X/3EYqtnYsA/41L3GNnNw9pEne61eQ6IcS3v7gPkBA2FojEcWIEBkJFBIRsoMTohmNBsQIz5PKPCA4MmLUO0AX8Gyv1f/eUULTNGqRETQRMbKdr0JLd6gYEfyCRtvCb/iHKHLI88lvo9szsu8bYhjNqQSKRgMACrOIGInKxJojiIZo+oH4vUCrUG1UGhoZEV63r5U0htSLPBpHe0PpwZf81aaZGFFD2JGoeZWSnxGy4VKhUfdV8MJ5fp/o2BYFC+WUXwPH3gic+whwkUJH1kiYkabxe4G9QtdcWuUTCeqL0BF+vvKFtfjlm9/hgQ+JqKOtoSvzMnCmjYiZ3mGnSZOSEqNnS5GnCedJrduNREb6DkkpEmHyUSXTYGSEds6t0oi4DPY0TVd9cGPAjr3Af/+SmPfe+i4xkG//AHj1kuD9c99aYOlc4K/TiYnQkQ1MvYTcFxJyF8WIkmdkoFOMqlgFs+kP/uHS6+jdltrriAi2OoKjbEb7TdSt1vc4E4gYGaFiJDBMQYwIzzEa5dwo9EMqqCaXwomJ6BmJlKahJ4gjZ4kR5nyhMOFQNF1YY+kH0rYbCHjJtke9JxRXPqmwAfQLHZ4niytSaI8jPSw+FVg0lBzHkgQTI2qIfpFgMUJ9I2JFTflUspKup1s6swGAXR+T9Rgyi4JXcgVISdjZfyIpCoOrTAIwR4wc3ET6dmQUhocI1aARHDpxakB7i3y5s4U8NY/sWBYLh9NtxP9xsDSCCOI44OdLgQueBy78O5moAWOeEXrmkTtE27wKSGmafp0HED1elMEuRjYuJQeM4ScAFwgRCBqRize0WgsgvqM1fyXXf/w38OJZZBw9jWQNoUtfkURASGWEW8sz0kaqRZBdhvxC8lvv67VJB0u90RFauVcyPnh9Knqw62+PvIIvz5PPSYnzEgSaYoTnZZERk8TIQKc0L1MDrPB80TMSKU0jFyMCBTGlaYSVubsajEeqW2R+kdAqLY4j7SMA4knUw4//Di4pN3J86G4kxzA96fo4wcSIGiGVNJQ8saJG2HAtFmnDpo21AGlBvBn/Q/wPZmKGGKErDlefqF8QZRZGbWIdQpshDXRheIBM9ttcGmW2lJwyYNolpBJJDO0amMBoB11aIqmFPDISaWLxuaUIURUTI4r4vdJikkdfK4nylh3xX6unvY5Uq3EW4HShPfsXDwEf/w74941k35l8ITDvfeDWjWQfVllrxKuVpqENDwtGoEgI97f1eshJCiCU6uqApoVD5hu48kivESDyGXLL9uB9w2jUwSBdWmmarnpgoAMBzordfGX4AoJ0TgwYSI0c2ACAJ0KPpkcCNDKiwzPiHZB+j2opPVwgREaiS9MIYsTXb7jKUKqkGa98P201oMfk63OTVChAlvQA9B8f/F5pfqJrdCUBJkaU4HnZhhISGQntNQIAR/6CXH73GuktsOdLoGZF8H1mEqsYCfil3PLE8409VzSxavtGQpda/8kUYacV/BtNfD729jlDn6YNFSNGPCPUL1KkQ4zQyIjfTdaw0aLhe9InIbNIuwkbFSP97aYvm57ybP9AijyMn0u+J4sd8PTE3kI7EjRdUXUccOICIjwCXrJ8vW+AmMoveJ6kUOnZIM2xh6Zp/BppGrpQZm4lSnLI9nyo1wO+RCjV1LuWk0okFhynPxUQWspp5EBvkECAR4+biB3F0l7hc/dmV8MDuzmekf2C8bTq2LATE68ez0jLdjJ3ZBRIXhzEaGC1Z0jzhlHfiFhJM0H5fiNiZMMLxOuUXQ6ceCe5Te882dsKgCdtFpS6UycIJkaU6GkWFjbjws6ow9I0APGNlIwnk+w/fyaUVPHA1Euj6xYaiVjFyO4vyMTmyiedHo0gmlg3az7MHpK7nTlKOCgLzZtqAkNwsCPCAT+UaEK7QqWD2CdFC0eWlAqKlOs/IEvRqHWtBcjEBwDggf6OyGM4nKCl60f+gqQerHbpd4hiwUVD0MjdkCPI7/OzvwNn/ZGU1k//H5L+s4YcRGnevrshqMpD08DaLRhLcypEI6Q/wKM3T/An6W1WpnLyA0B/ZcW294P/j2NkpNfjE4OHipERIX3lzSem3vBqGv378t62Xjz6yQ40bBGKBORiRJgD/X4dnhHRBzg5aJ+NycAKRF9RI1bSqIkRoZttj440zY/vksuTfimlo/UeH6jYySrR9vDFGSZGlDgk5IHzq0h6QAZtfNYp33A5joSCLTZiavT0EFPo3L/GZ3yxiBGfB/jiAXJ96iWA3WXs+TpNrH0eSZX/46qjpM6VQjv5Gr4S9R0GXOIAUe6AsbMpMU0TwbwKkN9RLO+NkFahfhEt8ypADsCuPH2veTgx0EXSJABwxJXS7TQkTQ++8YKKEbq9WizAcTcBv/gA+OlTUq5fTlYJEaN8IOjALzY9UxIj9ACUWwG71SKaIVszhZOQlh36Un5CRY7igUlPz4n2veGpU3/8xAj1i9gsnFhhGITweThhv4vWM9Le68Gcx1fhic9r4GgVxMSQI8OeL1XT6BQjMmIysALRmVg9fdJvHpqao+iNjAT8kjdpxMnS8UHvPElfn4qfJKFigx7k0HUgFKIaipERgLRTv3ktMRGVTgDGnhV+5mUW0YiRT+8moWt3DxEEGQWy0lkDhJpYxTN/CY8vIE4OG38/O2glT9pOvoYfIpb96oZOQOCJ5yCS14Xnpfw/9bpEIrOQpBYimVhpJU2kRmoASdUMdA4uMXJgHdk+C6qDSwzpwTaeYiTgl1bCps219GCxEN/IoT0kVVNAthnNpmc0NC94B4qznejo86LBWolqzkoWUeuqV27sR2mrkRbkpAc2OXoiI7STafVJQoqKj2uaRm5eVWyRLxxonWVjxccPeP1w0fStzj4jW+o7MeANIBMDKOK6yY2FI6TtJ8QzotmBtUnwi4Qc/GMysAKSb8RImqZ5K9k/skrVF0gVIyPNyvdTWneRtLI9i0TyadRar6FWFCNl+h4fJ1hkRAnqkBf6BsjJ1zI7FY8GTvlf0lU0XkIEMN70rLuRLGt+cCMRIhY7cP7T2hOkGnITq0qqpl8WFaGN4kTEyMgQHOzoN7ZYolx86MmH9rcTYxkQlCPWRE/js84D5CyIs0pr6Oh6zTQVI/XfAi+cDewysD4QLRunpdkUo16KaGjbTSrF7JmRy7lDEaMQ0oFFs7SXCgRBMFATa0s/SE8hIPJnpcJJWJAzfEyCGNFa/4SKkQlzZebQeEZGIvQYEaLLGeVjxe8tyMSq0zNS00x60gzlSKqi15JDIo0qkRFVMcLz0vccsro2FSPRp2mEbcbI+jQ0iqW1HpjeyAiNUpdPkVZGBvR7Rujr5zAxknrQNE1RuBjJVYuMJBKjTc9oSgEALn0VuP07YPw50b+/fN0YBXo9ZIJwWC1BC2fBOyBWH+zmK+H2BUjlgV4sMoGnZ6Klk0NWif50lJ7GZ/T7LJtEfCYRXzMOFTWdB4E1fzO37bfPDfzrKmDZ/0oHCU8f8Na1wL41wJu/kIR6JPZ9Qy5DxQiNNtIqlHggn+iN5sBpWlYWVXCreUZ4PjwyIphY23rcssUlI/hG6H4U2gKAIkRo0L5X+f7uRsncOf4n0n5itLupATTLen1usXEcVzRaNPYGpWp0pml2CWLklFLiL9vPF5MTGEtwdFhqB69ySOttFaKdXFjrdXqCGXVkRGwJb0CM0LSKVuQuS2dkhJ4UUj9fiJ8mIvT1WWQkBWmjaRqlyIigolNCjOjc2GhK4cirSTopmoiIHFGMbFK8m/pFMhwhB4KOfWTMjmxwwoZ/sN1AqiZIjOhQ/XRy0BsVAfQ1PhObnelI0QCyihoTu7B++gfgk98Dz54QbJwL+IHPHySt13tbjb3mxiWkUdi650kJLAB89bgkzj3dpINqpH4Xfq+0WnWoGKEpm4EO05aPD4OeKRrtbAwo5ttVDaz97aQyB5DEiBAZae1xSwe9SJER+creStCl5Tv2Kp+AbP8QAA8MOYrs2zQFEsfqrS5xkTyFyEh7nbCf5wDZpaJACxIjOqM3NDIyZwgRCnW+YtLDyGhkhHakzR1CKmBkUAOr2xcIiurqhorFDhWxqARdKqBcQ4yIaZom7RPPUH+UUc8IrQhjYiTF4HnJM6IQGRE9I9GqaDOIVoxEWptFL3TSPLhBcSehO3RmqBihJZN5VajIJ+3TGzoNmFg52evpiYxQQxk9c9GDnsZnehfeo2SanKbxuYEtb5Pr3Q3BXRf/fSOw6mHSen35b/S/pqcPWCXrjLr2GSI2N71E/j/zARJhatoCvHeL9ll3Ww05SDtywvu7OLOBTGFFWrUz/VgRIyMG/CIUhX1LKu0N2Z5pVCSjUIy8FWfTyIhHJkY0IiM+t9T7gor8UPKrAHDEF6AkMGkZ89izyKWYAklSZIQaM4tGARyHEuE7CaqoEcWEV/NAu1sQI8OtZN85wBdjZ1N3mJmdekZUDaxiP5jqsLsyHVYxlXQomnmdCuyO/fr65/i9Uim3lmCmYsTv1hbuovlZ2N64aCMjyTWwMjESSncjyTdzFkXTY6FodkqTyIjPI/UE0XsmH4nyqWSD72lSdJDTNE2YGJGJg/JcMnk3dRkQI/LIiJ7PTiMjRsRIJOHgHZAOdpEqacTXNHl9mtCW39s/JL9zx37gB1njvR/eJKtD62H9YtLWPH84WS8JIO3SuxtIjv6YG4AL/0F+9x/fAd64Un3iFfsnjFP2QIhphzp9YzMCz8tC4NFERsInctXIiFhJI5lOqVk7ODKyTf2A2/iD1K9G4UAJgKSO6HsofWehkTqrPnNoLGiu2EtN48LvXJIjRIu6ZQd6HfvyoV6PmMYt8JDv+gBfgrq23igiI3XksrA67C6O46RUTTQVNTmVZLsJeIn5PRL13xKxnlEgrcqshD2DmJoB9VSNp09a5JFuP0ZPVpmBNUURy3qHBbdlFijIIhttv9cfXUjPDIxsbO210lmqUTOfGo5Mac0eBd+IFBkJOWsSxcEQlOcRMWIoMiI3sBrxjBgRI5FMYw3fkUknq0R7IpFjtmdkxzJyOeNKMl53J1mokd4+7Hjg+NvI9X/fKHUTVoLnyeS4+nHy/6zfSE2TPMKCdpMvJAfEkacQz5EtA9j5EfDNU8qvKfZPUOksmR9FWFsvHXvJWaTVEb4sux4UzH+qYiTELwIAxdk0TeMh+xtnIeNR256ot2bIUdr9atS+s64GEnHkLJKZ2pJIA6tCZEQWAQUgi4zI9nVL5Cjn7hay/Q3Jz4Cti7zmAb4Eta29YQ0QfWKfEZVD2iEhTaMi+GIysVpt0hyjJ9pHW/YPPyFyRSCNVqhV6tDtwZknVTaKxwe9BlbmGUlNNCppACDbaRMbekVteIoVI2KEToK5FdqTnVHo99MdfiZAIyNhnhGZOKBixFBkBJCdEenY0WgkxohnhJbZKXwuAMElvXq/T7PFCB3DmDOkpnVb3pY6cI4/Bzj9HtKMz9sLfHAnER08D3z4S+Cp44A3/ocIq3/+DHh+FklLFY0BplxMjHBTfk5ey5EDHH299N7jzgLOWkSuf/J74MVzw82+kTpLRjJkxgKNWpVOVDyZiIh4kJMiGap9RnrDw9tBkRG7SxKsar4R2qgs0srZatEkui2UTgScOcGfIa5iRKP7ashJgLKBVRZRUYng7BPWtxpRnCUaYsPEiJim0RkZUTmBiNnEKqZq9mk/DpAWUNWzQCnth6MmRug+VCArn1fYhlXx9JI5AiAnWEmEiZFQNPwiAA3pxViXHiuGxEicVK+GKKAG1ixVMVKFCjEyYrDXCGdgopW9n27EngEqYoQ2TjKSAjBTjPA8cKiOXC8eC0y7lFz/7jUSHQGAceeQs7WfPkPKW/d/I6Rs3gXW/52kDbb9B3juZLKwltVJnnPJP6WS9Av/Dvy+Bfh1XdjK1TjyarLII2cF9q4GVj8WfH+kyAg9O41HZIT6L4z0F5GjZGBVawdPK5no7wspCtDWI8wNWr6RzgNCFQwHTPqp9rjUvjOxE7AsZWi0tPfrp4E/j5EWldSBZmmvLjESuTLugGBur87lRA9XPV+Euta+MM+IT7dnRFmMSF1YoxUjNHIVQYz4PFLlU/VJkV9XLDVX6TFDtwd5xIeeJOk5YaMeJKtDErNJgomRUGiaRqONu+gb6U2SbyQqMWKyOUljnZjIaZqhKBM9IyGdGSO+r031fYMIBKSzCaVGUmrQyIi7izSICyXSgVYJM8VI3yFhqQKQCajqGGkFU4D0maBCOm8IcNICcv2d60lpLgCUTpKWF688ArhpDXDZa+GfyeZQ7pfDccC5j5CUDQCsfV4Sbz63FF1Ui4zkxzEyQs18xeOie74Rzwj9PbOKxZuKhDRNv9ePXrdPVt6rEBmh60MNPz7yNpqvEhmhZZ3yShydDcUAkBTSxwtJlOeHNyM/XkDTwKoiRlp7ZAd6HZVxB9pJZGRMJjlz520Z6EImGrsGMBCgB1wyDs3IiLdfatuvkqahJ5iHop3TxchIhG16y9vEiJxdpt4GXk6khmp0H5L7G40YWPsEMZJZbG7kPAqYGAlFo6yXQn0jUTmvzUDMa+sIw8XLnKTRml3RwMrzQWkTeWTEWOMznS3h+1qFiYoz9tmdOdKBOjQ6EghIZ7hqB1olqBgZ6IzdVEgjd/ISxTMfBMqmkNTKz/4e/PgT7ggur80uB679BLh+BXDek8A1y/W1yldi7BxyRu7rB354i9zWuosIRWeu+gFWfpZv9uq91BtQqNPPE4pCvl21z4g4kUuRkSynTVwksq3HI3X7DPVWHdwEfPkwuT798sjjokKx4TvpO+N5qURUHqmTV6pE4ttXpOsGTlhUDaw+jyw1TMQIrTBq6XZL+7rFAiBYUIRCIyMjXF0AAC67VPR2NHQJn416RgIanhEarXDkqC4EVxBrmiaSKbt1F2k8+e6N5P/jbtJ38I/UfVepSsiIZ4RG97KKtB+XAJgYkRMIREzTAHKzUxqlaczOB2rkpRVLe/vahJ4MZBVSGhkZ8AbQ1W8gt61XjFAhkVVsvBuu6BsJORvpOkDyqxa7sYNdRj7EiTfWihqlpQryhgA3rSapldDmblY7WRRu4k+BY28Crv2YlNeWjCNrxoSsvWQIjgMmnEeu0wof6mGonK4+2eZVke/QN0C+UzOh/ST0motD0SztDU3TyM4qZdDoSEuPm5gUASIa6G/fsY/0gfF7iOdn+hWRx1U2hbT7HuiUoiztdSRKFmrWtaqnUMOg0RnAkDDsUjOwdtcD4EnqT4gYUTHS7/WjV276F9NJyqLpoLBcRKVNaAOfU47qYtJksL5beA6tpvFrREbkJf4q22TMczrd3pSifVveBp48iizJARDxKvdhaUEjI5HSNPLIiJGmZ33K23AyYGJETncDOcvjrMHraYRQkEVDeukgRuIUGdHY4HvdtOmZbKKiDvvsMsDmhMtuFU1jjUZMrHo9I+LnVln3QQs1EyuNihSNliZSPVisgiBB7I3PRDFi4GCbUwZcvBQ4+4/q5aPRUn0iudy7hhz89KzZY7VJYsqATyEifYekfgzRfk6F7drjI9tzeGRE+C0zg88qi+Um1twKYaViniwc6B0AXr2UlICWTAB++rS+M2SrTUrF7BNa7cvNuvLtUW8HVp6X0lqALo9JXWsvfvP299jeSARCmBiRp2iEz5XltIn+Mb1dWDv7veLaVSUQDNLZZRhaQPoTtfRQMSJ0YNXyjND9WG0NGMgNrFFGLun23LmfpCrlfPUEuRw2E5jxP8DPl0gr60aCRkaU0jQ8LzOwytM0Bo4PVFBnMTGSWtAds2C45sFG8oykgxiJk4FVI03T7yWTS5CBVba6KYX2GjFkYtXrGREnoCg+t1qeNhq/CIWeecTqG9FYxDEplE8lKRl3JzGPiqsZR+hpQ8vM5QfDWKFRkexyUn4eDQrmP3XPCJ3IQ8UImR9EE+uIU8jlzuXAR/8LNP9IIpX/85a0orMehh1HLqkBUq2fikU74iDS00T8C5QIYmRHYzdm/WUlXl+/X7wtLE0jK9+Xo90SPnhffm/zQUy77xP4AjzsVg45PkmMDMknqcnGbl/QmDU9Izq8YzEbWLOKhfQuHxwdadtNOgJzVuCSV4Dzn9JXRUOhY+5pCl+FuaeJdEXmLCFpGpmgjpQCZ5GRFIUebCL0J6CRkaQ1PosqMhInA6vCBKbYDp42A5L1ZIiqvFdv2SJ9v2giI2I5XUhkpFnf9qEIPXs22qI9lFQTI1ab5EnZ8hbQJkQ6InX7LY6DGInVLwLIJnJZaa/Sqr2ePulAHjKRB0VGAOng8+0/pY625z9trP8NAFQdSy7rVpOIAG1mGFo5pDdNQ78vSoR96tW14SmIsNJecQmG4M8W9p0Aqvvya+ukihSbxQKLbCG3IQWCGOlR9oxEHxkRot3RihGOk7Y7uo8CpEEgQHr0ROPLyCoh2yQfCO9VQ/ed/OHB6VZOtp1GEiPMM5Ki0P4IEVzOMZudYkWvGAn4JeVruhhRj1DQNE1QNU13eLqoIqrGZ3QCi/DZu6UJzDBiZCQkTyuK1SgqNbJMioxQM55Cd+CkMf5ccrnmb+SyaLSqUVCkSGgTb2aaJla/CKBo/hP7jMg9I/R3tNjDSiKLxMiIcOAdO4eE520uIo5/9ndg7JnGxzZsJmlu1XWQHORovwrqS6HoTdPID5pARPFCF62TExYZoZHYkP1OWYwoV/3kZ0j9YWxWLijVPCSfzBlqkRG7koFVoTldKHRO74ilQpKeIMi/191fkMuJ50f3mhareqSW7juhzSzlab9IEWQWGUlRRDEyUfNhaeMZ6WsTHsOZv7FpLMYkpmmcssiIOCFIZydl0bSE1+0ZiSEyQscoN43xfHSVNBQz1qfxe4FespS6oUZu8WbqJYBDlgM/6prIz4lHmob2X4klMqLoGVGIjPTJcu0hng/pwCvMDzYnCc8vPAj8cjsw9efRjc2RCUy9mFx/+1qShqmYFn7ypLcDa7uxyEiNghhx2VUawWUFn/wUiy3hI3tG5PPq/edPCtqXhwhrWtV3CY8RTkq8fo3ISFf43BMKNbB2u33w+qOs8AoVI36fbCmO46J7TUCK1HbuD75dLGMPWf9J3t1WzzECYJ6RlILndUdGCmNpHWwGesUIPaOIpqIkEnoMrHZ5moZGKqQJIbrIiL6lx2OKjIjmyp1SmLOrnuRnLbboUiRmeEZ6mgDw5GCTmfywqojdBcxaSK6PPJVU7USCTqCd+0kXSDOgkaxYhJreVXvp76gg8hWjAADZB2Pt5XDkVcH/T1MoC45QpSJiIE3TNeBFsyAkRpZkibdzoZ+nVzkSW6y5WF7wCU1rL3nMa9cfhwtmDA3qlVQpREbaBwJBY6YL5Sl7RsJTxKHkZtjFnybqeT1UjLTuIKk8pQUjjUDLw6kfiyJfkFCOPE0TKVWnUhGWDJgYoXTVExOexSaFkFWgKrqt12DDLrPQ22ekR/ksxRQ0RIFi0zMaGckOj4w0RpOmiRR+jCUyUjyORGD626WJrEUQqoWjomszbkbjM3nuO9KaFolm5i3AVf8BLntd39gyiyRfATVkxgqNGsWSklRqeqbkGRG7r4ano4rE9WniMD+UTyF9ZbLLSaqORkrk0H0k1PAYCo2M0MpBDTFCV88tzXFiUqWG6Vacc4IPbpKBVRZNtmpHRoqzHeRgSn/XnHLkuOzIddkQ4IPTaaqekUBA0a8WitXCIV9YkT1qEysVI1Qk0N4yldODoxVGoUsF0JQPRRQjIccrjkVG0hsaFSkaHfFgUyhMNgPeAPo88Vv/QRW9kRG6Zkik/H1UY1CvpukT0jSZQWma8EhFRZ5gRotm5V6tyAjPxxYZsbukNEKz0P5dTNFE2dnTDAMrTRtphJuTBscRo2Zon5NIjweA2lXmjKFHOGjFMrEq7Fti0zOrSpomBLElfLzSuMfPJ+meO75X3rd1p2nqyCXd1jUeT1M0o0uzcfUJ1QCAo6sLwh+olqZR9IyEN2fz+gNiZKIwy0H2Fz5AfhehV1JlfgZ8CE7XqnpG+tpkzQ+1RWpBZozpdxpRp4s1UjEy5MjoXo8y4hQAHDkhoickfm/470cJMrBqHCN8btJpGkiJSCsTI5SDG8glDYlpkOWwiotmtfUkwTdiVIzQHhdmohGh6BMNrDLBQicpeTWNEBnp6PNiwKtzhUkxjK7x2Qc6AL8w6UUTGQGk9VjoWjRiWW8UfhHAHAOrjqqAtMJMMRIIyARCLJERnav2imma8EmcLpbX0eeN3n+gd5xK6OnA6vdKn4FGRjTmk5oWSYwcMawAny04BUuuDinf9nulOUclTaMsRiQRRIsCLJxQ4ULnjYxCcc4ZWpCBAILTaaqRERqRzSqJ2Bso5l4jmYVAnvBdNv4A7Bd67tDVlKMls1Aq36bRkeat5Htz5oWXLAd5RjTmVfr7c1bAlR/bGE2AiREKdabTJk4acBynnhdOBIbFSBwiIxoltj1u2mdEmGx6W8LObgAgN0Nqna07VaMnMkLPkJ15+s/UQykVRGnTVnLZuIVcRh0ZMcHAKpqADay1k8qMEBYKO7gRePZEKfURDQMd0jYRS2QkZMVTnueV0zS04ZnCvpWfYRcPikkxuaukP4Kg4+cskqDSeHxtC/H1jCohRuXRpdnIcob40GjUj7OEfS8lii3hw+cQenJXkOkg36FCGmFIfgZ84qGLBwIB+PwqnhED/YZM6axNy6xrPpOiqqHVTtEw5gxyueVtckn9I0OPChemekt7xaZ9hSmR9k3+CFIBb7+0+iVtUBSBsMZGicSwGFEIp8Y8BuUSW58/IIa1s+lkJbZmLwlS7RzHib1GdKdq9HhGxAkshtAjjYw0/0hCrg2byf+014NR5AZWI2vxyDncIiN5Q4GK6eR64w9A3X+jfy16IHTmxdjiPvyMm/5cTqvsjFMjBWqxcGITraAmX4lCLJnVEiPCPpJRQFq3A5pihK4TM6xQo5kcjWJkFocd3Gg1jdsXEE9WpHSStC9T8UZ9N0pG4cr8DPhlh66A3wchMBIeGRF9RJHFiLQaewyFCXR7XvMkuSybbI4fY6qwOvfuFSRdS31WSvORXgNrPI8PUcDECEB+WL+HnHHqrJQoSqvISBw2NhVRIF97QvSMaBxEy42aWPVERhQWMDMMDYs2/Qj8+C75rgtHGm9URaFj8Q0Ed700Aq0W0TDipR3z3tPvcdCi1wS/CBBmYKUpGiAkMhJh3yqOt29ECz1pGnl/CR2NBPcLK+gOFZqOKdKjbiDOdEgt4cWSZ4V+KHQ+pWJOySg8pCADfkjC0C97vi30DN/AXFCYFaOBFZDmDfrd6zy5jUjxaFIezAfIekKiGFHodMxxENfC0jpG9KtH95IBEyMAsOllcjniZN2ld2JkJBmTje4+I3Rji4cYURYFvcJZj93KwWkTJgx6xqRwdmI4MqJhnJUGYUK5Wt5QYMhR5Dv+cAG5zUgb51AcWaTplXx8RqGiLvcwEiMZ+dL3aoYYibW5X0jTM1UxMtBBLlVy7XR+aE1GZMSqQ9zJPS8qJbaUzn6vuErvEC0xIgpC5UU5i3NCTuAU5hAaaaYne0renNDIiF8WAbJZQ+ZvjRLsUPJjNbACpHIGsjGMNEmMAGRhSwBYcT9pfshZ1M2xelbuZZGRFOLj3wHPnEDaWHMW4JgbdD+1SJYDTTipEBlREQW0uiiorFdjQhDFiO7IiA4xorJmiGGmCM2p6GQZixjhuNjLe3V0kkxL9PaO0cKsyEhI/xzqF7FauOAUQIR9i3okmpOSptHRgbVPFnGI8P0fEKIiRVmO4P06FPGkQ1kQFofOmQoRGTFNkxWSppH9rkPzgyMjPp/0/LA0TV94ZEWNAjPSNNmlZPHD8qmkY24sc0YoU34ebMgfdjzgylV+rJ6Ve+N5shoFg1uM7F8HNAnGxONvBYbqL8GiO0tSIyOAtv8gnqW9KmmaHqGSJtupJEbCx2E8TaPHM0KNWTEemCZdIKUQCkcBo2fH9npieW+L8ed6B6QVac1u7Z9sTBUjymflugkR+h6lsl4A6O8glyoTeYXQnIuuPJtQ9HyfvbKDfITH7z9EPsNQLb8IIOsxovwblISmtq3hnhHau6koi0ZGwtMsxdlOWGVNHP0+eZomVIwor6yshNgSPtZlPqZfDtz4X+Ca5YBdI5JkFJsTOOE2cj2jkIgeNTQ6ZIvE8/gQBVGJkaeeegrV1dVwuVw49thjsW7dOs3Hd3R04JZbbkFFRQWcTifGjh2LZcuWRTVgUzn5LrJg1c+XAqfdbeiptIlPW1I8I/K1B7RygvGMjChv7H20kkbeY0RjQhAbn+k2sOqZaE3wjADEgT/vXeDCfwA3rja2wqoSNE1FJ20j0EnZYk+JMjxT0bv4oRamiZHgVXvdSmW9fq/Un0Fl3xLblidDjBhO02h//wf0+EXkr6kSnQprCa/gbWnvpT1G7OHjFLBYOJTlSWPxycSIemQk8lwgGViTtMyHHo75f8DZDwNXf0RWl1dDoXlfGKJnJN+04cWC4R7hb7zxBhYsWIBnn30Wxx57LB5//HHMmTMHO3bsQGlp+Bmbx+PBGWecgdLSUrz11lsYMmQI9u7di/z8fDPGHxtj50T9VKrck2pgBYSNTaG7H8/H2cCqnGemTnnlNE34hFBhNE2jxzOi0ZDKMDpKvXVDywtpR0gjyAVWrC3FU40IngVdmCZGgkt7FXuM0AgVoCpQadvyg0mJjCgvQBeEPHWqkfr8sb4TL6wmnVojihGdpt6WUAOrTAR1DZAx52ZQMaJ8IjOkIBO+XgtsXAB+Hxm31cKpt6fXZWBN8mrserDagGP/X+TH6Unli9G91IiMGBYjjz76KK6//npcffXVAIBnn30WH374IV544QX85je/CXv8Cy+8gEOHDmHNmjWw28kGVl1dHduoUwCq8pNa2guob2zuLimVkcBqmj6PVpomfEKgnpGWHjd8/gBsSqtuKr2vrshI8lscBxFTZCR12jabjilpGipAzUrTkO2YNi0LStPQg64zV3XNJ3rgTo4YMSDYM4ukBoEK3/+N/9yIeuFEoaogQpqGHtxUTb2RDayiGKGrAauIicr8DPgPWGFDAP1u8npik0U5BvYbeZomEOBhUVrnJl2w6BAj6ewZ8Xg82LhxI2bPlnLnFosFs2fPxtdff634nPfffx8zZ87ELbfcgrKyMkyePBmLFi2C3x/DWVAKQCMjh/o8YsOdhKEnTUMnTJvL3LylOAblCU+KjMjTNOpipDjbCauFgz/ASyV/WhgxZsVqYDUbUYw0GX+uASNe2mGGGDHr+wnZvmhnz6AqDR2djSvzyT7XPeATD7AJQ89CeYrVNMHffyDAi34RABhfnqP9vrTCSOV7CTewUqOtTIz0k+u5GTYSnVKZO4bIKmr6BDGSE9qEze+TxmQgTRPgkfjfzGx0RUbS2DPS2toKv9+PsrLgEs2ysjI0NiqHnvfs2YO33noLfr8fy5Ytwx/+8Ac88sgjeOCBB1Tfx+12o6urK+gv1SjIJKs88jwRJAlFT2Qknt1XAdUJjFbT6I2MWC0cSgX/jS7fSKQDF8+b02ckHlAx0h2FGEnVaI8ZmOEZiXBWrpvQpmeyapqw99I4o8x02MQz7YPtCY6O6KqmkQl2lTSZ/ID80jXH4MjhEc6gI3wvJTpKe4MiI+5uSVApiBHahbW/n7xetitEjNA5EJyu7cJhs4iCJimdc81ETzq7P40jI9EQCARQWlqK559/HkceeSQuueQS/O53v8Ozzz6r+pyHHnoIeXl54l9VVVW8h2kYm9UiVtQkvLzXkBiJ04amEgak1TRiwzO/V8qxq4gDqbxXx6QdaSfz9JLGYkDqHbiVIiMBP/DefOAb9f0BgLk+mFQjVs8Iz0c8K9dNiPFPXIDNopCmibBv0Z4cCTex6hHs8vSHihik3olspw0njy0J92OEEqH3iryahuf5sHHyPC/2M8nNsEsnMfZMwBGcIhoiW5+mz+0RxxkE3Wcy8lXTaaHQRVDTX4xEiIwEeQrTMDJSXFwMq9WKpqbgM7umpiaUlyu3qK6oqMDYsWNhlbVSnjBhAhobG+HxKP/gCxcuRGdnp/i3f/9+I8NMGKU55CCa8F4CesRIvPOBKqKgV6ymEXZ++dmJyoHCUHlvpImWTkA2F2k0lkrQktyeJqkk+4c3gW9fBpb/Wvu5h3VkJMY0jbefdFAGzIuMCPuVV2kBNr1iJD9JvpFI1TSeXsknotH0jB6QC7LsZG2m5b+V5pVQvP3SSYBamiZHWu281+MPW0Onz+MXxV+Oy6YZUR0iW7m3b0AQI9RnQjHQ8IxSmMyWDWYSqemZt0/aZ9IxMuJwOHDkkUdixYoV4m2BQAArVqzAzJkzFZ9zwgknoKamBgHZGiY7d+5ERUUFHA6H4nOcTidyc3OD/lKRslyhsZHeslSz0CNGzDpTVCNCmkZcJE++BoZFwWAGKTLSoCtNE2EnE96PzyzCurp2bNyrMnkmAxoZ8fYBHrIKKupW63uuGevtpCqxihG6rXNWwBnB1xBxLMHbl1+Yt+xKnpEIwof6RpKWplH7Pml43uokgl3l8e1UjGQ6gK8eB755SlqoLew1O8glZwEcyr9BpsMmeslaut1h70tTNDYLRxbQlC/kFkJ5nkuMjDR3kkX8wjwjBsp6KTTanfaRkUjeOvrdWh0pc9JmOE2zYMECLF68GEuXLsW2bdtw0003obe3V6yumTdvHhYuXCg+/qabbsKhQ4dw++23Y+fOnfjwww+xaNEi3HLLLeZ9iiRBe2Q0dSUzMqLS9IymRmLtjaFGhKZnYmREx4RAIyNNhiIjamKEHCgOul24+Lmvcclz32BfW5RrwZiNMxtwkFVPxYqahu/0PTeKiTVtiNUzIvpF8mIvexbPKMl+5fVHHxkZLjQJq23tjW1MRolU2htqXFQTI30yMUK3P7XuwfIUjcYKsEG+kVAx0i+laDiO0xR9LrsVvBCd3d/aDUApTWN8nyk8XMRIpDSNfBtOkVYBhkt7L7nkErS0tODuu+9GY2Mjpk+fjuXLl4um1n379sEi2xirqqrw8ccf484778TUqVMxZMgQ3H777fj1ryOEpdOAUlGMpGJkRDD9xkuMqLWDd1MDq3C/HjFCIyN6xEgkz4gwKe7vI5OeL8DjP9/X45ZTR0d+7USQXQoc6iHrzBSNAhq/1/e8QZGmidIzYmYUMMTA6heraYx7RkaVEuG5u6Un9nEZwRopMhIyflXPCDkgF2Y5AFpEIO+xEvSaHcJr5msOrTjbib1tfaTxWYgY6RYiIznUiBrpd7VYgQCwv60bQG64gVWMrOhPQxRm0WaWh4kYCaiJkdQyrwJRiBEAmD9/PubPn69438qVK8NumzlzJr755pto3iqloWmaxEdGdJT20knDGacUl0ovg7CmZ0YiI2ZU0wgTbSek0OO73x7EzbNGRTbgJYLsMuDQHtL4zMiCeYPCwBprZCQ/9rGEGFhpn5GgNuM6xc/IEiJG9h3qg9cfgD1SDx2z0LmPSGJEWQxSA2t+ph1oIdEHVTESwbxKERcQVIqMhPYYifC7Wqw2ICClacIiI1GY+KU0TRKaWZpJpMiIGDnPT8hw9DC416aJkTLRwJrgyAgQeWNzxzkyorfpmY6zkwqhtXND5wBx2UfxviLCpNjJZ+GSo6rgsFqwq7kHNc0JPjtVo6CaXDZvI2sjUThlPw0A0i9BDK0zMRJGPCIjfHBkJChNozPqWJHrQobdCq+fx/5DCUwV6k3ThIkRZc9IYaZDmk9UIyORe68AUq+RZnlkxB+aptEXGbEIESBOmANzQiMjOgWSnMPGwBpxnhR+xxRpBQ8wMRITZclK0wAGlG+cIiMRqmnEpmc6zk5KhQiT2xdAZ3+EZkOR/AXC2VQnsnD86CIcMTwfALB5f4f26yaK4ceTy7rVwM6PpNt5v7r/h4ZUwaVMgyJTSaXISGjTM8EzEhTV0Bl1tFg4jCgmEbo9LQn0jSis+RJEqHDglPcp6pvIz3JIAixSmibCb0DnzOYu9TSNocgIABun0PVZ/nwDkRFa2nvYpGlUPSMd5DJeJ6tRwMRIDNA0TUu3WzyDShgRxUhyIiO9tJqGTgw6jLQuu1VsEBXRNyJOnMqfOyC8XyefhUmVeZhUSd73x/oUaZw3/ARyuX8dsOWd4PsiOd9deaoVSWlNrAbWuERGgjuwBkVGxKhjZKGfFN+IVTntIqIzMtIhpGkKM6yAVxBT9LsORfwNtA/8Ykq2e0AhTUMu9XpGbDYyZ1hAfqvwpmfaz1fisKmmieiti3OBQxQwMRIDRdlOWDjSPjjhq/fqTdPEzTOiPIH1hlbT6MxNlgupmohdWCOcRfd1EG9FvzUbI4qzMLGCfP6tqSJGCkcCOZVExHl6AMgOchFMualkNjOVWA2spnpGQjqwKpX2ikI/8vuNFCIjCRUjhtM0ymWgtLN0sV02t8VoYKVR0MbOgTCjbVe/scgIFSM2QYxkhUZGYkjTHOr1RE4ZpzLMMzK4sFq44BxoItG9scW7mkZ6f57nZZERa8g48jVfrpyagSNFRiLkQt09JIqQmVcEq4XDpCGCGGnoQiDR0SslOC54JeCpl0jX1fK7UZzhpRUp6Rkh24pPLO2ViRSPYObUIfTHlpGeG9saumMfm14iNgbUGxkhYqTIJtsnYzSwimkajT4j4oq9EX5Xu508n0ZGwvqMRGVgJfOQxx8QzfhpScTjQwe5ZJGRwwdalprwls+60zTxioyENx9z+wKi7cFlp2KkQ7hBe6Mvl5lYtd9Xe6LlhQN3Zh4xeo4qyYbDZkGP24f97SnSb+SUXwFTLgbO+iNwzsPS7WoHjyjO8NKKlPSMhERGaJrGLYuw6di3pg4l2/22hi4MeBO0OGikhfJ0pGkCAV6spimwysVIl3KKVKdgpmmaQ70ecW2Z0DRNLk23RPhdrWJkRPCMmJCmyXBYScM1pHmqJtKqvSxNc/hBWz4nT4wonO37vVKON14HMIUJzCtbvVhccl3nRq+7vDckjB6K1U3eLzefiBG71YJxwtlpyqRqiscAFy4GjruJrLtBiZjjz4/70JJCOnlG6PZscwE2Z8SXG1qQgeJsB3wBPnG+JYXVcIPQIUZ6PD7RB5cN+dzGS5EhpdeMMN/kZ9rhsJHvuNvDBb0vTdPkuPRFRjghOit6RuSREZ9HmgMNpjcPi4oavZHzFJpTmBiJEdryuV5Pwy4zoT0zlDY2t2yyiLU9tur7hxukaLdKwLgYqdDb+CyCv8DpIxN+QWGpeNuYMmIi3JPoTph6kJf0qoqRDnLJPCPKxNMz4g9pembQGM5xHKZXkXElrKLLcJ+R8H25R4hS2K0cnL4Qv4tSqkanr4njONH43+Xhg8YZZGD1eciyCYD67yp8TpuYppGtTSMabTnAaezsv4gulpfOFTWRDKysmubwI2nrT2gpXzpZ2LOkkK3ZKHg3PD6pQZTFwgmrqeoTI2V5OiMjWp6RgB+ZPJnASkslMTIyGeWVepG3zo7QO4WlaVQwNTISUtpLO7CGpmkMGMMTLka00jRBq7WqR0Z6xU7KtuCTG0BZjBhIidD+TJ1uQYwIEZx+j+w95VU7anOHsO9YQU3zMmEvHmxzNdvTK3FYtIRnBtbBR9JW5tQjRuLlFwEUz2ZpmkbsyeDpkcYXYZIyHhkJP3AF+qVJsrysQrw+ophERmpbU6TxWSiRIgPMwKqNmRNraJqGdmC1hqRpDOxb06vIQX/tnrbEmKi1tidvv7Rir4YY6Zavvu0OER+hYoTnDQlmamLtGAgEvW+/4KlxOazSNu/UKGcXxm1FABl2a1Qt+5U4LNI0epuescjI4UPyPSNKaZo49xiRv79swvOIYkSYuOmEYnWQHLsGdILq7Pei36MRrtcIP7a2NgEAenknKgql9BRtPJXwBcv0otJ0SkRnPj5ticUz4h2IuHS9sbEod2AVIyNR9O85qroAWQ4rmrvd+O5AR+xjjIToGVGIjNBtyWKTFm2MFBkZCPG6hIoRb79sOfr8iMMTxYg7OE3T7yHzR4bdKot2aXzPwn5j4/zh5tUYoomHRUt4reODzw34hOMVEyOHD5X5Uqma25cgtzygLzISrx4jgKLyppERhy20rDfyaqq5Lml5cc1eIxoHrsamRgBAryU76CypupiYRNv7vGKL65SCHgwipWmYZyQc+t1oLF1vCJVVe22hHigD+5bLbsWs8SRt+MnWptjHGAmtNI0YMSiU9kl5nxGhUqZH7t+IlKZREjgaUM/Iof7gyAitNsqwW/X5gCy0tJcXDfBhY4oqMiIslpeKc4VetIz+4u/HxfcYYRAmRmKkMMsBl518jY2JNLFqipEEREaU0jQ+MnE7wkLakcfBcZw4oWh+jyoL9G3c244nl20gb2sL3sEyHTYxDVTbloLREZXPJCJL0/gDfOJKRBNFLGkauRHPoDdAkZDImz8QslBelFHHMyeSVc0//rEx9jFGQv59hlbbKZXay9MggiDuCUrTRIiMyKMQOhajpD67tj5JjPA8L6ZpMhxW5XGGIox73jFD8Ngl04PviyG1eVh0YdWqtpSnGs3YZ0widUaSpnAcJ5lYE5mqSbZnRCG14PGTycRuM1ZJQ6E9Wxq7NL5HlSjCJz82wu6hlTQlYU8TUzWpaGKNUK5MJ2belYerXliHYx78DFsOqjSfSkdiESNmm3tD9iuvmKYJ3aaN7Vunji+F3cphT0svaprj3ADNIktZhG5TSiWdQY8nv0GPkTSNwQM/nS+be33ie3r9vJgSc9mt+kpPBTEyqSIbo0tDIjIxRBMPewNrClbSAEyMmAL1jRxIZEVNsj0j4tkUL6pvjy9kUTGDBwopMqKRq1XxV7T0uJHLEaGRkx++sm11KvtGtA7GsuqHz+q8WF3Tiq4BH254aQM6+yIsKpgumBEZMcvcG7pqr5imMR7tk5PrsuP4UWS7/PjHOKdq5BV0oakapTSTgnihaZqgahp6YNeKjOhgaAGZL1tlkZF+WbQvw26VVS1F9owobjcx+KwOi8XytAysKVhJAzAxYgpVhcSTkNBlwsU+IwphODp5xKvHCCBN2oA4gYmeEYM9RihiZKRTR2Qk5IyvrccjNWdSyIMOF36jfYn8jfSiNXHIzIF/WdUs3lzfOYC3Nx1IxOjiT6Q0lRZmR0ZC1mnxqqVpDPauAIA5k8oBJCBVoxDpEFFK4SpFRuRltvQz5wgVat6QfcigICzJdsJu5eDhpQ6sNPVotXDEAE/HqTWHaXmNYkhVH15pGqXIeQe5ZJGRw48RReSsu64tkWJER2TEDEOfGgoTmFjaG3OaRsszopzSaOt1I4cTvn+FCWx4EREje1NSjGhNqh0AAJ6zYkd7AFYLhwVnjAUArNieADNkIkjJyAjZlv1qHVijSIGeMbEMHAd8f6AzvtV3FllkJLSiRmmfVGi8RyMjWfI0TQ4RU/CEihFjZlGLhUN5ngs+CO/r94kVdBl2KziOk06otL5nrSostw4xo0KRsN5Yv9evXdmXymg1PUvBsl6AiRFTEA90iTRHaooRoZ9GPCMjCqY32vQsGgMrIJX8NXZppGlUPCNtPR7k0MiIwgQ2rJAIxn2paGDVmjiEg63XkQuAw8jiLMydVgkAWLvnkLi4WFqTUp6R4AUgxQ6sMZT2UkpynDhyGDlgfxrPqhr5vhkWGVHYJy0WmW+JPJ6W9pJqGuEzZwtiJDQyEsVvMCQ/Az5eEhNijxG6ppWe6K5WRFF8vnHRmOWwii3r29K1vFfPyWoKVdIATIyYgtyPkLBlp7U2Ng8VI5HL7KJ///CzKU9o0zODYqRCT5pGIU/M8zwRIxxN04RPYMOKpPLelDuAa02qwllnn4V8prHlORhRnIVRJVnwBXis2tmSqFHGj5SKjAQvs0AXyhNLe2OcyM+clICqGo4jvX0Aqf8HRW2fDPkNFKtpcsjYY03TAMTE6pctlCdV0hj4nrVEvOibM/47cRyX/qkahYVMReK9iGqUMDFiAsMEP0L3gA8diTIV6omMOLLh8QVwsKNfjFqYhmKaRijtDUvT6NvoqYG1pdstdr5UfV/ZBNQ14IPHH9D0jGQ7beIEsy+R6TQ9aIWbhe+wkyeCly76N2sc6Vvx9e62+I8v3kTyjPjcQLdKJMHs/Hfoqr1hkZHYQtzUN7K29lB8e95YhUX8fCFn9uL3FbKPqIiRbIdVijKIkZGQk4VoIyOQtvsBWZoGgM7IiEZ6M0bfXNp3YdUq7Y0hahRPmBgxAZfdKp7V1yUqDaApRsjG1up14JhFn+GEP36OC57+ytyoTVCaRjD7hUZGDJ5FFmU7YbNwCPCkOkbzfWUH7jbhsfkWdTECSNGRlDOx6jjDO+Qn29dYYdG/o6tJuH/j3vb4jy/eRIqMvHgO8MhYoG13+H1mLpIHqK7aG75QXnQT+fCiLIwvz4E/wGPF9ubIT4gWm0pkRIwY5AffriJGcm0+6XehkRFPyBwXRWRkSH4G/KJnxCtFRkQxomPu0BTx0XtGAFl5b7pW1OhK08QxjR8FTIyYBPWNpIQYEZb4Xl/vESM1P9Z3mbtQF8cBoEuAh3pGqBgxpsCtFg6lOeSMTrXxWUi1AwC0ChNGvlV4jsqBImUrarQ6sAqTaqObfC9jhcjIEcOJGNnR1J16aSejRBIjB0kzO/zwVvh9Zi6SByg0PZNFRrwD0rouMURiElJVYzhNE/y5e93kMo8KfM4CZAn9e8LSNMa7nVYVZsID+rt7MeAl+7PoGdEj+rT2mxjP/tM+TaNpYGVpmsOa6iLqG0nQgU5HmmZzc/CG+P539eaOIeQg4g1dmyaKUKlU3qsiRhQ8IzQykqvhGQGkdNrelEvTBJsHgxAOHh2BDDhtFgwXtrPSHBeGFWaC54Fv93UkaKBxQq9nRLGfRAe5jFfTM/lCeWInUi6mSjUqRlbtbEGfJ8rFASNBxYhPpxgJ2a+6aZ8RyPYpO9l/zEjTjCjOEsUI7/cEd18F9M0dnMp+4/dKa69EHRlJ85bwOiLnLE1zmDKqhITPdzcnaGXYEKNdEIKBdX092ZGuOWEEAODD7xvEMz1TCMmve8S1aaIPaUcs71XIE7cKE0YWaGmvWppGqKg5lGIVNeJnUpo4yMGjG5k4cniBVGIK4Mjhh0mqRsszIj/wKYq1DnIZr6Zn8siIPPQfQxvtCRU5qCrMgNsXwJc74mRAtgmeEX+oZ0SvgZVE23Lk+5SD7D9mpGnKc12wCmPkfZ7gNA3P6ztgqu038rV0ohQjRWLjszStptGsNErA2mVRwMSISYwWcvm74t3qmaJmUPJ7xVVMd3dZYLVwuP30McgUVg01dXwhoUBvaAfWaCIjuaQ7Y8Q0jUJkJDPQq/l+Ugl2ikVGtDpJCgfALj4Tx48qCrpLEiOH4jq8uKMVGaEHOiDcjCm/3/SmZ8JCefJ28Cb1Z+A4DmfFO1WjlKbheZmgUjew+vwBMW2SwfdKj7eTfTNIIPJ8VJERi4VDWSEZA+f3YEDwqGTYrWT+op1j9ZT2hm43NIJlzwzuRmuAtG8Jr2vtMiZGDkvGCGsj1Lb2iqHduKK2scnOCnrhwuTKXORl2jFtaD4AYNPeDvPGEOLfENemsVpCQqVGIiOCZyRSZESm+Ft73LDDBzsvTBwR0jT1Hf2J+Y30onEWww9IkZGZo4Lb3FMxsnlfh3r1UTqgKUZkUZ++1uD75Euhx6m0ly6UZ7Vypp5R0lTNiu3N5le6AcppGk+vtI2peUb4gOgXAYAMKvBduYBdiIz43VIUy9Mr/W4Gf4MhxWQMHHi4PWScLnn1DjjtVYDVPCMmdKA+bKpp4lBpFC+YGDGJIfkZyHJY4fXziWl+piZGhBSNj3PABxsmDSE7/BHD8wEAm/aZGNIPOTMJKu2NMlRankfOvhpUPSPhO1l7nxfZkEU7VA4WpTlOuOwWBHjgYCLXEYqExsG4oYlUXHhsOZg2NPgAMrYsBzlOG3o9fmxvTFBELh7oFSO9IWJEjJpwUbVnVyQk2kdLe+0Wi6mrYR8xrADF2U50D/jw9Z44lGcrpWloZMdil6IcFNlvQFvBO2wW2L2yBory51ATK/19rA7JU6KTquJ88brHQ/Z3l82qPx2mFlGMsZIGOBwMrCqRc55nTc8OdziOE1eO3NWUAN+IamSEvHe/hUwM1MtyhND58VszxUjIxE3P8Oxys58tw1ColPYaaTLgGenq9yKbmlftmYDVpvBE8huJJtZUqqhROYtZu6cNTS1EjEwfM0wqLxWwWjhMH5YPwGSRmWjEM9xAeP4/SIyE+CvkPTPMWgpdpbTXauFMXQ3bYuFwxkRSKrtiWxy6sdJ9Tt4OXp5m4rjgx8vESK98xV75gcueAbGCjraEl6doQl8zAsNLJVHndZP9PcNh0V96quY1MsGgmfZpGoWqQwAkxUbFG0vTHL6MLiU7z65EmFgjREa6eXJQH1lCQqszBDGyu6UXHX0m7WAh6QVpoTxZqNXgBk/7tTR0Dij3RVHIE3cN+JCr0fBMjtgWPpXEiPxgLOP7A53IBYmyXXzCRMWn0lTNhrp0FiPhSwuI0IMdoB4ZMXP10bCmZwoC26QGa6eOI6WyX8aji65S0zMtz4tMjMjXiQnajzlOVlFDIyMd5DKKNNmI0nz4eSJgPFSMyN8zZjESS2SEfH89bh/cvjRcnybEiC0iT4HRtFuKwMSIiYwRTKw7EhEyV42MkAmz0092ptFCZKQwy4FqwcD5rVn9RkLC62JkxKZz1U0FSnOd4DjyWopnJQoh/e5+b3AJogY0MpJSa9SoGPHaeqUW95zKZH9MdSEA4Js9bYlbisBstFaZDfWMyD+j2ZU0gL7IiEnh7eNHF8Nu5bC3rQ91rSZvj0ppGq0W6bJt0C3sx06bJXw/Fk2sCpERg4yvyIFXKO+taSAmbJfdqj+NoOoZiT2ClZthE7vupmV0JMLxAU4To4kmkVqjSXMmVJCNf1tDV4RHmkCENE0374LDZkFlvpTnlVI1HSaNIXhRMSkyYon67MRps4qNzw4o+ToUxEhnv1dasTfCBJSSFTUqDYraez1iZERtYj5ieAEcNguau93Y3ZJCAssIesWI3yPr9YH4REbk+xXPS54Rq8X0KoRspw1HDSdi0vToiFaaRmlbkqU/aSSAeL9CnuMI6TUiRkb0NzyjOG1W+C0kHbK3hfzOGQ4DkRE1z4gJaRqO41BATazp2IVVremZCX6aeMHEiIlMFMRIbVuvmHeNGxHSND18BkYWZwX1pZgx3GTfSMhiTF75xB3DhDC0gEx4imJEPOMjEwTP8+gaMBAZScWW8CoGzo6eXrg44WCicgB02a04Svhd1+xuVXxMyqNXjADBqZq4REbkKSM+ODJicpoGAE6JV6pGKU2jGRmRtkG3UNbrDErTCJ+Zpmlor5EYfwNOaFvvgKy0V2+KV21tGpMOuGltYo0UGUkxvwjAxIiplOQ4UZrjBM8D2xvjHB0RSxBDQvNCZKQXLtEvQplRlQ+AlIIGzGh+FpqmkTc9E8+ojE8IQwtINOdAu4JgkPdP4HkMeAPw+nkpMhLRMyKJkZRJa6issOnplR2INT7XCaNJye+amjRdNC9oyfuQA4u8zwgQLEbiEhmRmTD5gLRqbxzSNABwylgiRtbsbsWA10Rvgrg2jVyMaJwgyNI0A0JkxKWYpgmNjAjbaJS/gc1BPGJ2uRjRKybUOheb1GE0rU2saqv2pmglDcDEiOlMqiQ/8o/18RYjysq3vplUX/TwGWIImDK+PAeZDiu63T7UtJhgslWtpok1MkLFiEJkRF6ZE/CJ67JIreC1329oQQY4Dujz+MU1bZKOSidJb28HAMBvzw4+YIdAm6F9VdMan54V8Ybj1EPuYZERWQQhHpGREDOtn67aG5SmMS8yMr48B2W5Tgx4A1hfZ2LzOlG0y9M0Ggci1chIyHNEMSJERmIwsAKA3UEiOE6QcZI+I0Y9Iyq9lmKMjFAx0pqOXVjVSntZmmbwMFEQI1uTJEZ+rD0IACgqLMS8mcOD7rNZLZgq9KrYZEYLcZVqGruViym/TtM0BzuUxIhDuu73oKufTGJFNmHCiLCTOW1WVAq9TFKmLbzKgdjfR87EAxEm5WlD80nPCrcPa2vTNTqi0mskVIz0yw7YYnVIvnnj4GRTIh+AVykyYmKIm+M4MTpiamt4xTSNxkFaVpkSZGANTZmEekZiMLACACeM0w55BY9OMaLqGTHngFsieNdUVxBPZdQ8I1FWOSYCJkZMZlIlOdgnKzISGCAbW3VlWVhfCkAq8TWlL0VIaZ0ZBlaANJADIqRpAMDnFiMjBVSM6NjJqgqpGEkR34hCVYDXHwDnIdsQF+FM3GLhMHtCKQDg061x6FmRCCKJkbxh5NIti+jFeFauCBecMhLXppF3YDVT/AA4WRAjq2tM9PzYZOlMiqYYkfwXNF2kWU3jCS3tNW5gBSDuzw7BG2WstFdlmzHpgFsm9Dxq6UpHMaKjmibFiEqMPPXUU6iurobL5cKxxx6LdevW6Xre66+/Do7j8NOf/jSat00LaJpmR1N3fFuOq2xsnBA+dWblKz7tCFGMdJgwhpA0jVIH1hjTNGG+DrnZ0e9FVz+ZiPItQpM0HeJnuNBrJGUqahRKezv6vMgVuspaMyKnBWgDrc+2NqWOF8YIamZEerDLryKXHpkYifGsXBFZZITn/aIp2xq0UJ65E/kxI0g6dUdTNzr7vREerROltWl0iRGptFexzJb2pggt7Y1WEAqiiXpGnHaFaIwaShVDgGkHXFrV19ydhmJEremZuA1otNlPEobFyBtvvIEFCxbgnnvuwaZNmzBt2jTMmTMHzYJXQY26ujrcddddOOmkk6IebDpQVZCJbKcNHl8Au83wZaihIkZsPvKeGdnKB7AZQsfOmuae2Ce+0FV7gzwj0YdKaTlyn8eP9r6QMXJc0EQrekYs+pcMFytqUkWMKHRgPdTrEU25nI4zvBNGFyPDbkV950D8o3LxQKnXSiAgbUd5Q8mlfJmBeERGZJ6RgOxkws5xcVvTozTHheqiTPC8iZ10xbVpFKppIooRIWViDUiiQ6ymCekzEqOBlY7z2uOG4P+dPBLjynL0+xqUfDGAab6IskjdoFOZSE3PHIeBZ+TRRx/F9ddfj6uvvhoTJ07Es88+i8zMTLzwwguqz/H7/bjiiitw3333YeTIkTENONWxWDixxDeuvhEFMTLg9cPlJ5NEVk6+4tOKs51ir43NsTY/C1211y8XI9FP3C67FWW55KxEMZVilcp7qWckR2dpLyDrNZJqaZpQMaKzqyxAvrOTx5Kqmk/SMVWjFHL39AAQojy5leRSLkbiHBnx+qSxWPkBaWKPw1nl0ULzuvW1JplYFSMjWgbW8KZnOZzsIEz3K0dIaW+sglAY5wkjcrHwnAngjIg+q0LFEGBaNU1aR0YitH5I+8iIx+PBxo0bMXv2bOkFLBbMnj0bX3/9terz7r//fpSWluLaa6/V9T5utxtdXV1Bf+nExERU1Ci4pQ/1epAlTCCZOeqhfVriG7OJNeQAInpGbLH3ZBheRFMpCiZTWXi2a4C8dxb0lfYC8jRNihhYFVbtPdTr0d07hXLGRLISbFr6RpTECN2GLHYgU1ix2BNvz4g0Jfpl4tBOIwFxaqMtihGzKmpC+vEA0E5/KHhGxAo1+fpS8tJeno/dRKwYwaFiIsLcYVOJjJgUwSoVIiOd/V5zy64TgdqqvdRzpbUacpIwJEZaW1vh9/tRVlYWdHtZWRkaGxsVn7N69Wr84x//wOLFi3W/z0MPPYS8vDzxr6qqysgwk05CKmpCljoHSAkaPYBxGjviEbT5WayRkdBqGp9sbZoYQ6UjBDFSq9QmW56mESIjGTwVI5Hfr7qYTKitPR7zcvSxoBgZcSNLLFfWN3GcNr4UFo50AN6fKlEfvSiKEdlBhX4HdDL1e6XyUtP7jHDCW8giIz7hvRzZcWmjTffJHw52iqbZmBAP8tF7RsTInFy8yNem6W+XBHRmUXTjVBRNOnsUKUV/fG4pUhKjGMl12YiJF0BLukVH1Ep7xcjIYZCmMUJ3dzeuvPJKLF68GMXFxbqft3DhQnR2dop/+/fvj+MozUfqNdIZPzOhQhiurUeKjGhtbPIVfGNqfiaqbzIG2vTMbos9vz68WKNtuyxXTD0jroB+MZLjsosh2D3x9PXoRaFE8VCv11CaBiB9EY4SzrA/i8dKsPFEadEzuaClZ3J0MpU3QzOx7wcAcbv2ycZi88bHL0IZWZyFLIcVA96AOdukUgpDrxgR+oxkc73hj5d3YKUN6Fx5UpTC8DhplFMQFDxvwMCqEVUJHXcUcByHUiFdnHa+EYVoK4C4+Z7MwJAYKS4uhtVqRVNT8ETX1NSE8vLysMfv3r0bdXV1mDt3Lmw2G2w2G1566SW8//77sNls2L17t+L7OJ1O5ObmBv2lE2NKc+CwWdA14Itf+aiC8m2RRUa0wnDjynPgslvQPeCLzWSrtlBejE3PgEiREWkCo9U0Tr/CxKkB7U67JxXWc1Holtg14EU2ZyxNAwBnClU1n/yYbmJEIzLiypW2I3ob9Ys48zQbwkU3FvJ6fj8Zi4UDLDQKE6dcu8XCiRHVHw52xv6CoREHnwfwaZyoBHlGyHaYxSukPqlAcHdJDeiySqIfpzVknN4+6QQrGgMrTRs5tBsF6qUsh6Rq0s43Eskzku5pGofDgSOPPBIrVqwQbwsEAlixYgVmzpwZ9vjx48fjhx9+wObNm8W/8847D6eeeio2b96cdukXvThsFnHRvO8PmDCxKKEUGekeQLaOyIjdasHUofkAYlw0L6zpmVDay3tjDpVqe0aks76uAS8c8MIa8Bh6v5HCasZ7WlMgMqKQpuke8CILwm9pYOKgJb7r6g6hoy9FOszqQVGMyNqvi2kaQYzQKg4dZc+GEfYtv5/8Hja5uI7jJE57FG05aEJ6V5amCfABNLbLTvyUKilkZvQBITKSSaON8ggFTcf0tZkkRoQTCxrdoNEwzipFYVSfq1W+bM4JbNpGRjgr3snOwjpviC/QfZgYWAFgwYIFWLx4MZYuXYpt27bhpptuQm9vL66++moAwLx587Bw4UIAgMvlwuTJk4P+8vPzkZOTg8mTJ8PhiDK0lwZMHUImFlPOcpRQECNdXR3S/REmzSPMaH6mUk3jDMgERJRihPo62vu86Awt75UZWLsHfMii0SBAd8naKCpGUiEyotAtscftiyoyMrwoC+PKcuAP8Phih3a5fUqh6RnJDU/T9AmdZjP1p391I/wefqGaxmbhZJN4/MLbk4U5Y0u9CXOGcKBu8vfhig+vwBnLLsbyrExygLfawh8vfv9eMTKSyStEGzOFJSb6DsnESAy/gRjBEfZxeRpBvk6QEkZ7qURBaZpGRn50t+KekiJcO7A9+I4UjowobJXaXHLJJWhpacHdd9+NxsZGTJ8+HcuXLxdNrfv27YMlDgavdGMKFSMJjIz0CmIkwFlhof0AVKD9RmIq75WFdgMBaYVTh0+2wUcZKs102FCa40Rztxu1bb2Ynpkv3SkLQfd7nNJBW22iVSC10jThHVi7B3yGypXlnDGxDDuauvHp1iZcMGOoWaOML5E8I6EGVlGMRGmc1IJ6RmhkxMIBnvjn2icPkYzvgQAPiyXCwVgLwcPxmLUXW9q2AABq7TaAU5kXZCkPsekZPamQV7WYHhkJ8bYYaVim2GXW3LVX0jUy0uRXsAcE/FJ/mBT0jBgWIwAwf/58zJ8/X/G+lStXaj53yZIl0bxl2jFlKA25dsY+sSihIEb6e4jw8dmy4IhwVkHLe3c0dZOzcGcUm4Ksy59H3iDKZ85Z5MiSLDR3u7G7uQfThfECAKwO0n3C50a/NzOqg/aoYnJwq23rhT/Akw6bycJiJStz+L2g0i0o4hOFGHnyixp8uaMFbp8fTpvJnop4IDdQ+t341Ze/wvE9nbgEIGkCGvHy9hLDtIIY6ezz4qvdrTh+VBHyM2OIulpomkZYlybGvjl6GV2SDafNgh63D3sP9WFEcQwlxIIXowFSpMnLceoHedmBXVybRsmHRb9v3wDQsY9cj0GM8BY75peVwNb6FR7neXBGlrjXioyYtPYK9YykWzWNQ9apmud50r9FXhafgpERFsKIE2NKycTS7fahLh79LBTEiIcurKajD0JprgtD8jPA88D3BzqiHIN0NusNEiN0EottQhhTSibBnc3dQbfzFhuuKy/FldsXo9fbDZvzABEnBg4UQwoy4LBZ4PEFcFBpdeAEEuAsuKSyHBd1rkVA+D27ozSwAiQqV5brRK/HjzW702ThPJkYeWP7G/h8/+d4oH0juU0eGQHIpKogRu7812bc/MomHPfQCqzaGcOic6JnhKQOgtI0cZzEbVYLxgtesy2xpneFA7UXksHdB059W5ItrOcWemq4qBiRH9gd2ZIIaBFSADGIkS4Lh1WZGfjc3Yith7ais1cwXuvZ5uk4+AAgmI1NT9OkaWTEzklixO13Y13DOjy84RG4OZB9jUaXUwgmRuKEzWoRS3zj4htR6DPCCcqX1zlh0mhD1CZWWXqBmlcB88ogx5aRz1HTFGwyHbDasS7Dhe96D8Az9HeoHfEBNrichsSP1cKhWujEujvJJtZu3o8dTgdqAn1o6ycH2R63z3DTMwpZOI+kTdOmAZpMjOzr3hd8nzMXsLmkx3h6gF4qRoiHYVdTNz7fTjwyA94AHvhwa/Rl61xIZMQiL1WP7xnlZGHOiNk3YgsXIx5OQ4zYpDJZty8Ae8FX2OyrJ7fJ9yuOkwRgMxUj0XtG/LK06qUfXIpTvn0I+202Y2IEkKIjtJrGJDFCW8Knm2fEbrGL191+N6795Fq8vPvfeC1HKJOP5MdJAkyMxBFasRKXipqQyMiPrT+ixSZMDjrFSMy+EZlnhJb12iw8eCOhVg3GlClHRvxWe9hjV2VkGJ6ARhanhomVk/lq3H43NjdvRl/ui+iwCQeSKM7G5QvnxdRLJlHIPCOHBkK6kFIzo0NWUUMjI8KB8IWv6gAAJ4wuQo7Thp1NPVixPToD73d2G24qK8G+XtLfyGpNjGcEkEysP8ZaUSNEOryykxUvBw0xQg668LvRy22Fq/w/+BWECpzQ51DTsE8QyzFERvyW4PSwH7z+EwslMaK3e6tOaD+ijj7J2JsOcLJOwv0+KfLboFfoJQEmRuJIXE2sIX1GLv3wUnxfuho1druuhdWA4MhIVM3ZwtI0PFzDn8ZF258nHoiYIyPk+fsP9aPPI+W+fQom1aE+n3ExIppYkxsZCcjEiMfvwZUfXQnkfI8Hi4Rl2aP4HmeOKkK204bmbje+j1dFl5nIIiPtAyEVXrSpGf0e3OFpGpqWufGUUbj8uGEAgJe/2RvVUP6n0InVmRn4U+2TAAC7xSJL08RZjFRKFTUxNUwUBLtXdgKs6RmRNRDz2OqC7wudT2hFDcVEMQIAmYGAzsiI7KQkTIyY8zvlZdjJKuQAmrvSJzril0U+BnxSiimDD6SkXwRgYiSuUBPrj/UmtXiWI4uMyCetepsVVpe+HXHykDzYLBxae9w42BGFb0LWrMvtC4Cz9oJz7UeNuw2HrJaYJ4TCLAeKs8kkWdMsCQafJTwyYuN5wx6VkSlS3uuDNHG4ZR0zG2w28PasqCqSnDYrThlLDhKfblVeqiGl0BIj4iJttLy3O0iMdPZ7xe136tB8/PxI0r/o692tYofeaGj2kg6j1qA0TXzFyNjybNitHDr6vDgQi5dJ8ATIP72X49S71QqPD/jc8HGhkalQMRJSwRSDGPEqbNsejtMXVQ1ZwRuA6dU0HMel5YJ58hiOPDKSwfMp2WMEYGIkrowqyUaG3Ypejx+1JvsSmgMenDu0Ai92bgna2Fw8D1uGvh3RZbeKzdmi8o3ImnV5fAFwNim0HABnSqh0dCnZcXY0SqkanzV8AvNq5cNVGEUjI0n2jARkZzHy3zKTD4CLYeI4I526scrESHiaRjgwyct7ZWKEbhtD8jOQl2HH6NJsjC7NhtfP44soUzVyvM6t2OPpCB5DnHDarBgtGLe3NcSQqrEqiBFAfVFBmwvfOh2Y6dsOLm9tyKA0xAhnjWltIL9ClNPIvsxbHfgoKxM723eSG0yupgFkvpE0MrHKxUjbgGRidwV4FhkZjFgtnNg7wGzfyOL+Ouyz2/Fox2Z0eaRJywLtRfJCick3IkvTePwBcDZJMGjmpw0wsUIqkRZfWyG0q2nOU4FGRpq63OiO4Qw6VvwqYiQjwMf0HZ46rhQ2C4ddzT2oU2qrn0rI/EftbikyElQlRSfRgQ6pHXxmkXjQnlAhfVdnTSLLUyzfEltUyOLah7bsp3G+rSV4DHGEfo5tDd0RHqmBQpqGRBzyVR7vwN/z89CH4AiuH1BI08jESOnEmBYO9AtzSD4sOGP4GdI4dUY5v3W58KvSYlz45e1YsHIBLvfsIsXMJkaw0jEyIm8C39wnCXIrwDwjg5UpQ/IBmC9GeNkkIxcjXsDQhCn5RqLoxCprB+/2+mGRRUaiEQdKTKsiYkTue/ApiJFoxE9ehh3F2WSi2Z3EVI2aGMnkYxMjeZl2HDuS5PdTvqpG+E09vuAW9j5AOhjS74L2twAHZBRgeyPZ7saXSwew2UJUaHVNa0wpUmtmXfANJrUZ12KiEK3c2hDDnEHTNLJty8uR70vt8RU+X9jNisJALkYmzI1+jAB8gpCx8oCNbgNa6aQQDtolE+unez/FD5wX++02U38nGhlJp/LegOz40NQn7fsek04S4wETI3Fm6tD4tIV3cFKqotsjj0gYEwFUjPxY3xXUK0QXstC6xx8AZ5dFL6Az7xsBWpG0VTY+n1qeOYqdjJYP72yK4Sw0RgIy53uHu0O8nhGI3Wx2RrqU+Fps2OR04sidzwTdHGS6pL9vu2BMzSgALFYxgjBeFhmZXJmLHKcN3QM+bK2PPt3BWULW90lAvp2KkdgiI0Jpb5gYyVd+vM2JfIX9X1Hky1fojVmMkH3ZBsBhoWOGbjGSx4WfmAAwVYyUpGFkRC4r5ZERr7wqLcVgYiTOiKV69Z3wGT3Ya2CWGKkuykKOywa3LxDky9CFrBzT7Q1N05gTGakuykRuyPjkYoQP2GTvZ3wCohU7u5IoRnyyA4b8LMYZhSk3FBoh2LD3EA71pvDCeVY73s8Ob9YXJDJpP4vG78llZhEOdvTjR6EnBz2IA6TPzzEjSFTo6z2tUQ8rXIzE/6yS+rj2HeqLPn1osYLnrCFiBBppGif5rkPwcDbAEfK7FI+VrpdOiG58An4qRnjAIQgoI5ERr4LnxKyoLCUtIyOydFtLn9QA0AOOGVgHKyOLs5DlsGLAGzA1FeDUEiMGlK/FwmFatP1QZE52jz8QlKYhZ1Sxn51wHBfWr4WKkVI44W0nq0V7tbpLajBGjIwkz8QqN7A29koeB58Jk+rQgkxMrMhFgAdWbEvh6IjNiZyAwpm5LUMq4SwRDnzNW8llVjGe/LwGXj+PmSOLRA8QZeYokk742mAXWqs8q2MJORtOwFllQZYDlXnkALjd6AmCDF9Il00ftCMj3nAtAq9ToUHW8OOBny8F5m+MuXkWFeJW8KIY0az6CcGtECV1663G0Qn9LeqjqThMEn5ZhR6LjDAAkIM9jY5E3XZdAYcsPCkP7ZOzAmMbG00lfWfUxCpvIe3zB1XTmHl2QsdHvz8qRqw8wPPyyIjx9xtHG6slMTIinzgaehvE69H8lkrQqpqPf0zhEl+bK+gsnuJ1ys7KyyYG3dddMBFvbiCNyRacORahHDeSiJH1de2GopLyVW3kkREfkLCJnEZHYkkxeW3B6/NoGlhtTnIQD30NtX1q0k+B4tFRj41CDaw2nodDKNk3EhnxKFTWuU2OjFTmk8UF6zsGYuv9kkDkW7s82mpWYUE8YGIkAcTDN+KUnREEKV/A8IRJIw/fGRVLssW1PL4AOLs8MqIx8RlEGh+NjJDN1sYD4Mn3EK0xi3Z5begciKknRSzIDaxNvbKJAzBl4vjJ1AoAwBc7WtDQmaJndzYXWTcDwC3Tb0GOlRwAvPKeOcVjpf46AP7TNgS+AI+TxhTj6OqQRlwgaZu8DDt63D5D+55dJg7lkRGPMzumyhEjTKw0QYxYg8WIl4N6ZESWpnE3nwW7n5xoeJwxLNanAx9HDaw8bML37oEBMaJYWWcBdKzPpZdyITLS7/Wjoy95VXdG8HGSaJKXyrPIyCBnShzawltlaRr5AcxIWRyFmlh3NfcEdTqNPAgpMtLv9YKzSqkOI6HWSNCKmp1N3ej3+OHlaGSEB2KMjORl2FEmLIa1K0mpGrU0jVnRpTFlOTh2RCH8AR6vrt0X+QnJwOYSD4YOqwN24SDlcWRKj7FnALlDxX+f20MiH3eeER4VAUhU8ljRN6I/VaMWGfEmcBKnkZFtjbFERoLTNF7Oqr5Ams0hfv98wAYr6PcfXzHiF08seDiENJ3Hov+A6eUUIiOOTFNFo8tuFavuomoOmQQCUI7geE2KtsYDJkYSwFQhTbO1IYqKFRXUw3DGN7byPBdKc5zwB3j8aORMTBYZaXe3gZOpcQ9gmhgpz3WhRBjf1oZO+Cw0zwxwQo1zNCKMMjbJqRp5mmbAL5nkyFmMOSHVeTOrAQCvrdsvriOUUtglMeK0OmETxIg39GAoWy5+b6AYo0uzccQwlXJVROcbcch+D84i/R6eBE7i1Iy7vbE7auO7LyN4//NqHaCtTilNxttgE/Yrr1wMxgHRM8LzcARIqy6vzanbi+KxKJhu7RnmDVBgSH56+UbUqtm9YJGRQc3wokzkuGzw+AKmHfDUSrc8UYbhxFSIEd+ILDLS7g5est1rcwB2l+FxKMFxHKaJvpbOoNCuQ8jhxlK9k3QxojLvmlWRBABnTipDWa4TrT1ufLSlIfITEo0sMmK32MVUiTf0wDLiJACAx5YDgMOQfO0DDxUjG+radYuwIDFilUzn8T4wyxlWmIkshxUeXwC1UTas84a0afdwGtO9TUrTcDwnfv8eh/kHdjk0RWnjA3AEyKzmVVgIUw1qYL2wYCpOKCAGZ49J844c6htp6EyPihq1Jf1Yn5FBDsdx4qJ5W0zyjah12CMGJeNiZDptLmYklURDvn432j0hYsTkiVvua6FixMbzcPHC2ZTFGtz/wAC010iy0jRqE4eZZjO71YLLjhEWkPt6rymvaSohaRoqCMIiI+f8GTjuZrw65QUAQGW+9oFnbGkOirIc6Pf6dXcZlntGgkzZCRQjFguH8WLzs+hSNd6s4DVklKplRGxOcqACYOM5MVXltcVXjEgnFgE4/ESMeAyIETGaxnFwCr+bOw6REcnEmiaREa00DYuMDG6mDI3iYK+BX7axeQKyvHaskREjJlarHR0WCx4KtKC275ugu7x2cydu6mvZvL8DPmHStPKQiRGV5kc6GJP0yIjyUcKsahrK5ccMg83CYcPe9piMkXHBnhGUprELm7fHHuJxyCgAznoIW72kQqgiT/vAY7FwOH406U+yukZfv5EgMWKRpKLHRFOkHibGKkYyQ8WIhhqRGVhtPAcq8byh37/J+EQBxMPuI2Zhj0LvEDVo6snBc3AKuQlPlCclWlQIJtZ08YyoOf+YZ4SBqUJbeLMqatTOpt0We1SrvNKKn71tfejo09kcy+rEc/m5eNXSi73ur4LuMjtUOn1YPjiOjK9b2NNsfEAUI0YmsFDGCIvxNXe79X92E1FLHkTbO0WN0lwXzppM1mx5+Zs6017XFGRpAofFAbsgtn0qZ+Y0XE4PElqcOJoclL/SKUbUije9DvPD/1rEWt7rzSReGgtNZap+MgBWm5jGsfOAE/TAHl8x4pdFOe3CInceA/OXmNoDYBc+pzsOYmTIYRIZiTaNnwiYGEkQ9GC/raELbp+alNCPX21js0a3I+ZnOlBdRKIZuqM3NgfqbcoiwGuyGMl12TFaaGpVL7RltvE8MkEjI9FvyjkuuzjZJKP5mXZkxNy1UKiR9d1v69GZSmWKtgyxz4XD6oBdOMsN7ZVBoQeFygieEQA4QYiMbN7foaujqZo4jIcXQQta3httW3ivUMabJXyXPvCafTI8ojAAXAkTI0JlHABHLzEZe7W8LSF4hCiWgwecQjWO20CaRy9DCsh2tr89PcSIZuqXiZHBzdCCDORn2uH189jZGPsBT830aCTfGophE6vViaEhi2vlQuhPEIdJjFZNUDFiD/DI5MnBxaNQ4mcE2ol1RxJSNWrCMh753aOrCzC+PAf9Xj/e2JBCZb6yDqAOqwMOnhxYlNIEPM8biowMLchEdVEm/AEea/ccivh41X0rzgfmUMaV5cDCAa09bjR3GzdOeoVqtgxeklfegLoYo5UpDp6HS5Bkob1KzMbLk/nDyvNw9BDfmZETC+pzcfA8nAHjnhO9DCskJ2ot3W70e2I/mYw3qp4RixWIIYocT5gYSRByE+v3Bztifj2/WulWDDviNMGX8Z3uyIgzuHU2gDIIzariMInNGJYPQB4ZCSBLyI56FUr8jEBXfN0RQ1+HaEmEgZXCcRyuOWEEAGDpmr2mrpcUE3YpMuK0OmEP0PRb+Pbc1e9Dn3BAiOQZoZxgwDeiWomQYDGS4bBiRDHxqUSTqvEKLdEzZXWeWmKERiQcPA+XIGA8NvMP7HL8QprVBsDRQ1oUeKB/X6ZixMnzYjWOOw4H27wMO3Jc5HUPtPeZ/vpmo36CE9tJWzxhYiSBmFlRo7qxxbAjiuWzBzr0tT22OtAfIgIqA0JL5zicnRwldNls6BEiIwiIkRGvgQlMiQnCiq/bY1kpNUoCKmMnkRHzTZPnTa9EYZYDBzv68UmqrOYr84zYrXbYxTLPcAFQL3SRLci0I8Ohb3KlYkSPb0Q1TZNgMQIAEyulHkVGoSbyTHlkxC+JkdYeNz75sRH/3dUCnuclzw4PWZltfM+i/YLotPE87N2k4Z/HwK5MHV52noeTVuPEoUsux3FidGTfofQTI6XOfACxpbPjTeqO7DBkqokVNapn0wprNehlUmUerBYOLd1uNOpZodLmxECI36GEp+MwX4yMKslCcbYTbuE97HwAOTyZjjTLFnVAIyPbG7sTvv5EaFrA6iVj8XKWmBciU8Jlt+J/jiVlvi+srjX99aPCliFWezgsDtj96gdD2tJeb1QEAGaOLALHkS7DkVZfVa1EiMM2HYkpQ8i28O2+DsPP9QqzhIvnSbdiSJGRAa8f5z/5FW54eSOu/Mc6vPzNXvHA7uADcFExEkOVmh58wvtYIRlQPVpG2xDoYx18AA4f+QRuA54TI6STGAmEzGEjXKTnjGavmSSTuiM7DKFt4Xc0dmPAG1veUTUyEkUlDSXDYRUbgH23X4dgsjrQH3KwzBAmu3icUXEcae/tFzq92vkAsoUpNNYamJElWbBbOfS4fTiQYJNaaMrN7iXRECNniEb5n+OGw24lZb5mLuAYNbKF2pxWJ2xUjChsz3vbyMFgaIF+MVKQ5cBkIcrw5Y4WzceqVjclQYwcOZxEAzftbTcskmkUxM4DdmGqp2Lk398eDCpTvf8/W8W1gZzgYRc63cYjyiDHJ3hGbPIGhgbEiFcmRpyCGNnUV4+H1z+MHo+5ZvQqQYzsP5T6JtbQo0u1Ix9AhPLuJMPESAKpzHOhKMsBX4CPaWlwIHxjswTIRuaLUflOC1khVxObEwOyyaq//kK4hEksFlGkxbEjC8XeBI6ALDJiYAJTwm61YHSpkKqJ8bcxip8LHrvTR9IBXnBxi9KU5rrwk6mVAIBnv9wdl/cwhKzPiMNih0M8GIZvR3VCR9KRJcbMvbMn6Fu9WL1SLfHGv8lDcuGwWdDW6zHciZUKD5s9A3YhZePxexAI8Fi8ag8A4PfnTsDcaZXwBXhR0BdaZd1Q47QfU2iaxsqT9BAAeHn9PiY3FSP+AJxCn5J97ja8vPVlPPPdM6aOtSqNIiOh23C1jcxtsUaQ4wkTIwmE4zix+dkPMZ6Nhm5seT5iGFVaq8EIhpqfWZ1iZKS072r4Oo+Gy08mhHhNYseNLBKFmAMBVDiESVP1fFY/E8rJDpvohmChwjLLS8QIz0lnjvHgxlNGAQA+2tKImubkNHyjBKwOKU3jc4sGVqXtaA8VI8XG/DRzJhMx8t+aVvS41b/XsLNKn5A+iPOBWQmnzSqubbVhb7uh51IxYh9xCuyC38Ub8GJXcw/2tPYiw27FZccMw58unIJx5VkQzmcw1OEWoxSeOJ9JSwZWKTLi4fVHjT3Cfu/g/XB4g9Nvezr3mDRKwjAxMpIGYiTkpHQoJ1Q5JmMwOmFiJMFQE6vuihUV/CEH3wIvmSiN1OgrMU3WFj6gttoSxeaQPCNCuMIpLPQWr0lsTGk2sjPIGaoDAVQ6hNJeA2dTalChuHm/sUk/VkJHnueRjJJyw6HZjCvPwZkTy8DzwNMrkxsdkYsOR3+X2IFVKaxMIwQjSoyJkXFlOaguyoTHF8DKHc2qjws7q/RSY2RyKhGOrCYl7etrI5clyxHFiMUOm+D98Aa8+HYf2b6nV+Ujy2lDpsOG+386Xnxevq9L8m8E4ieGAckzYuMhiRGNip9Q6H7vCPjh8AanT5wK5udYkHtGEu0rM4p8JfAx+WMwkiMnq74YI8jxhImRBEPLU9fXGZtYQgk9dygR4m9GzF9KjC3LgdNmQfeAD3VtEcLCVqdUTSO4MF0+IkbilZvkOA5VxWRSsPE8ykHywl7eH/MEceRwMulv2tcRWYiZiPzgd2zZSRjdI61Cq1WKaQa3nDoaAPDe5vqknvG5ZZLMOdAhdmD1hkSGBrx+0etQXWRMjHAc9//bO/PwKKp0/3+res3W3dn3kAQQRHaQGFRAyQiI+4ao43IdvK6j13HDUXGZe2FmHO8sLjg6qL9xwR29igsiIAqCLGEHWcISIAkhZE86vZzfH1Wnuqq7et/j+TxPHkJXpfucrqpz3vO+3/c9mCZWoP1qh/csIvdnyyIahPHKRDh7oJAJtGLPiaDuS0kzwuug54XJSDBGWgG4xiIAGFro0t9Y7G2ukEmU7z/q+dOAQCsT2Qb6LNOQjt5ug6FPef/SPkeKkswUaHkOPTZHYAL/OEI9I7e0tuP96f+GQfQahRvOjibMGIkxZ5ZnQcNzOHSyO6x8dYfbw1pgp+Kv8NBpeJwhVn70u7GYRieFaTg7gQ52GGisP4o3fUm2MHBqCZBpda1w7WGu4k4vNMGo49HWY8OB5thVYqWT36+6uvHgqAUwkT5wbtkP0WJUqQXnDs6Bw0nw8nfx847IV8ParpMuMaObZ+hISzcIATIMWuSkBz/ZTDtDMEZW7G7yWgnZ3TNioDVP4iT+O6syG+kGLZo7ragNIrwr94zoRPFtn6MPm0XP35gyT6OXIwTnF9hc33+U7z+FZkT2vQf6uZJnpLtFKpRH0Ue41pFOw0vekQMnQttJOVbQDD0dIdA4+ySvkR0Ezgh4kaMBM0ZiTIZRJ6X4rt1/MuT3ca+wV2Sn2onwjQBa6dRvOiHHSQJWzg5Y0Cm5d6M5hKWlCAOrFgSGPpe+I9yBU6fhJc3MxiDj8+FAr6WGEPT22ZDB9XidjKMB9Y68t6EeTXFa8dF+GpxOcJ2NrjCN2zU9IAvRcCEYB6NLLMg3GdBptWPNPvXnz32odqWcxscY0Wt5TB4ipGZ+E0RdGMkY0eig44Vnpr23F3ubBEObbj4JAFZR66UnBEVci6vPjuiqDKQwDYjkjZG33R9W0bOi62yCwW2BFukwDSBk3QHAgRPx2eE7UGhqrwYA7FboZF6jaBuYocKMkTgwcaCwcVc4xoh77K9ITGuLhHaChisCEcz1iu5AzgaYuc6YrKhc6YCuODMQmYGT9n1dkPH5cLCL10wDwNrXh3T0gCaRyndkjhZVFVkYPyATfXYnXlkdWdFfoLgmQwDt9S6j1u0+2tPQAXB9UmXSYOF5TvKOLN12XPUc+mxZrKlIP3S1awdhEr9B/IJhgvj20y3H4AgwVKPwjIjGyFc7j4IQoDw7FbkZrsmaPjvC93/MFSaLtmeEClhDfJZt4t8betsVfw9A0slEEprBtT/RPSOiSc2DAPZe6OXGSAwWOKHAjJE4QGPA3+1tDlmbIPeMpGhMMEspruEbI2PFCXlPQ7vPjcUIIegRF4ucnYieEeH/UTVGnK7aBBrIdiWNwGeeO1i4Nst3NaHPHht3Jv0UDSGw2mxI53pj6hnhOA53nS94R95adxinumKvuadGlw5EmAy99P+rA6uQPuRJwLw65M+6cEQhAODLHQ2qoRr6bJ1fPwyWnhyXsDLKXgJfTDujAJmpOtSf6sHXflKTKWrGyKdbjgAAfjt1sOJclzFCgK4TMeuzq+gZAQ9AK05JgX4uzbzRg3h4RqIxBtEMrv0J7xkRFzgEgK0XWlnNlVgscEKBGSNxYHx5FjKMQgx4c6Cb0rlBNSO3Iwu3V74KE8Qslgio3/NNRpRkpsBJfBc/szvt0o6zGrsTFq5LivtGcxBzuXYF9KL7PBIPWVVFNnLSDWjrseGH/YFtOR8uVGymAWCzdiMD3ZKYL1YDx5TTcnFGkQndfQ689kPsq7LS+8VACNB2VHVl3mW140DHdnCcEz383pA/a0J5FgpMRnT02rHSrQAaIcRlHALIQLc0MYerSQoHo06DG84aAECoCxPIIkYhYBX1E3anDRMqsnD5mGLlueL3TJ9fyRsU5ftPvrAQ2qoN+HMJIdJ4pyeexgj1tkUS6hlJeM2IqMWhnhHe2ukSCDPPCIOi1/I4b0geAODrnYGtctyhruRiaECcRliIqJYOIkffFzRc4Us70W13uf4MTsDCdXp1r0cSjwFMNIgi8ZBpeA4XjhDc+J/WHgv7/QKBCiZ5Ath6OmHmumImIKRwHCdpR15fc9CnRywaKFbm7cdck6H4+okOKx78YAucvLDCszpDrwXD8xwuGil4Rz7dorzGDtnzwxMgg3MZI6vqV+HjvR+H/Lnh8uvqAUjVa7Clvg1vrjvk93w1zQh4Oy4fU+yht1F8/7J/7Q7fBhgh4QkipTDN8KuBSQ9CpxV2YQ7kWbY77SCS8UQ8wjTRWBBRzcixtp6wq2hHE3n4C/ZewCpP12aeEYaMC84QYsBf72gMKSXVJVAi6LP2IF2UjEZq8pKMkcPejZFeMY1XSwiMnBNmxMgYIS7RGwDoxJ0oI/WQXSauGj+pPYodx8LfR8gfkksVBE5rF0zo9piMY8H0MwowMDcN7b12vPnj4Zh9LqAUUKppRu55ZxOWbmsApxGMkVZra1ifd8loofrs8l2N6JIVQJNPrHrOgQz0SF6a5p5mPLHmCexvjU/WUV6GEY/MEOqB/M/SXdjix6tKjXYdrwMhoraLc0gLITlSmIwQxb++nilCCG7+8mZc83/XhOw1krJpiscB5z8meXACGT/kbdMTxMQzkp2mR2aqDoQA+5oSN1RDjREeEIyR3raYjM3hEJIx8sILL6C8vBxGoxFVVVVYv36913NfeeUVnHvuucjMzERmZiZqamp8nv9LYfJpudBreNQ1d4UUf6QCJQ0BSK/L6rUTR0RSt6SMmkOnvLqEe8UCZ0ZCoIcdFq4rJip8eaEkANBxroJOkWBsWSZmjiyEkwD/9W6tVH48Wki1Fgjg6OtGBtcdl4GD5zncOUXwjvzr+wMxXflJYQJCAOJU9H9bfRt+PCAIik1pwgRzqje8bKcRxWaUZ6ei1+bEMlmGinxSTSE2ZPLdHivucA2hcLihagAmn5aLXpsTt7z+E/Y2eq+cK9eMnOoSxoRCiw4FZqPHud48I76e46buJmxq2oQ9p/agqdt7ETlfSPe+WFCO1gYJZPyQn6MnymycQN8jWDiOkzbVDGUn5VhB5wAeBLBRY0Q41m/CNO+++y7uv/9+zJs3D5s2bcKoUaMwbdo0NDWp34wrV67E7NmzsWLFCqxduxalpaW44IILcPTo0bAbn8xkGHWYOEjIqgllG3eqGdEQAL1tigEzEhPY0IIMpOo16LDapVRAd3rsQu660Umghw3ZXKc0IDR2N2J1/eqo5LS7h2mk1VQEH7LHZw5DdpoePzd2YsqzKzHlzytw6+s/YcnmowFnMwSK0jPSCRNc2ptYDxyXjC5CSWYKmjv7sHh97LwjCs0IoDBGFor1Ty4dXYT8TOHat/W1SavqUOA4DpeMErwj/ycL1cjv1zRYYeF7PCY5DRefSqyAYDC+cP1YjCg2o6WrD7Nf+dGrQSLXjDR3CN/V4Hz1zQUV2TSAVyG63WnHqiOrcKr3lKLcOvWSBov0LItaEfosB+LlpG3WQtD3uBuN0fCMAEI9IgDYfTy+Wyj4QiFg7TkFOO2uMaW/eEaee+45zJkzB7fccguGDRuGhQsXIjU1FYsWLVI9/6233sKdd96J0aNHY+jQoXj11VfhdDqxfPnysBuf7FwwTNAmfO2jGqQ3XJ4RAs7aIbmSgchMYFoNL9Uh8KYboQNQCnFCDzuyeJdnBADuXH4nlh+O/HV2F7Dq+MBdu4FSYDbi03vOkdKwD57sxvLdTbjv3Vr85783oKcvcl4DhUvV2gkT1xM3l6pOw0t71rz83YGYZRTRiYNOgrRc1fG2Tny+9Tg4DvjNOZVo6RU8JE7iREdfeJPBxaIx8t3eE2jtFiY2uWYkHX0w8z0ekxz1CMaLdIMW/751AoYVmtDc2YfZr6xT9d7Re4fntDjRLjwzFTmeXhHA0zOi8yJE//DnD3H3t3fjxi9uVBgjXbbQvIeStkH0blKjJCDPCA0ticZhLDQjADC0UNjDalcCe0bkWUroFOaXWGQ6hkNQxkhfXx82btyImpoa1xvwPGpqarB27dqA3qO7uxs2mw1ZWVlez7FarWhvb1f89EdqhuWB44RKp8fbgtuWWvKMgICzuvbyACKnnaC6EW+l6yXPCBE8IxauS2EUAcCaY2si0hY5UixcvH314iZgkR58ii0peHvOWdj4WA3enlOF+2oGw6Dl8c2uJjz84daIfY68CqWuR/Aw0hVqPNJJrxpXgrwMA4639WLJ5th4MD0mQ/Hfo22CV+6BC4ZgaFEq2mVF7lqs4dWCGZyfgaEFGbA5CL7YLgjJ5cZIKnph5jzDNKF6ASKJJVWPt35ThdMLTWjutOK3izfD5lAajnTSqW+xos8uPCvZGepeHTpmuIdp3CeuFUdWAAAOth9UaGe67CEaI/Tep2GaYDQj9J4RxbnuPYuWZ2SY6BnZ1dCesHvUKDwj1BhB5IT+0SAoY6S5uRkOhwP5+fmK1/Pz89HQEFhWyMMPP4yioiKFQePO/PnzYTabpZ/S0tJgmpk05GUYMV6c8L/YFlxWDc3A0Djt0Ng6wUO88RC5m626UvAKrN7brPrQUWMkxUmg5+ywyIqeUcx6c0TaIkfyjJiKAXDQ6QSFe7Qs/ux0AyYOzMF9Nafhjf+YAA3P4dMtxzwyMUJFHqZJ6WkUfxcHjjisYow6DeacWwkAeGnV/oiHpdTwFqZxEjsyDFrcMXkgWntbFX/j/v9QoEJWmjklpUQSgjT0wcT3KLx9QGIYIwCQmabHopvHw5yiw9b6Nry4QimspffO3sZegAhTtd1L4TbXxC6GS7ykgealusSvCmOkLzRjRHqWRc+ItIdOAGOYq83qZd+jZYwMykuHhufQ2m1DY3t0PiNcFN5W0RjRR1joH2limk2zYMECLF68GB9//DGMRnV3IQDMnTsXbW1t0s+RI0di2MrYQgsweasG6Q26ftPYrdDahNWiLoL1NgBht9AUnQbNnVbsbvB0ibvCNIJnxCwrekZJ16dHpC1ypGya834P/OYb6MTPiIUX4azKbNwtpsD+4bOd6O4Lv/aENHAQIFXca0crrvPi5VK9rqoMllQd6pq78NGm+qh/nkc2hzjBcJwDw4vN4HlOCtFQwhWxAsDFIwVj5Me6kzja2qMYxFM5K0zo8jBGqBGeCBSaU/D0pWcAEOqPNMrK+dN758hJq2SMeLufJAGxUVgceaszkpOSI/2+qWmT9HuonhEPAWswmhHqzdGL1XjTlFlC0TJGjDoNBon1RrYGsVdQLJEvcNApjCk68TvuF56RnJwcaDQaNDYqNQ6NjY0oKCjw+bfPPvssFixYgK+//hojR470ea7BYIDJZFL89FdmDC8Exwml14MJ1dCNkHhbL7Q2wZVNwxaRmsAMWg3OqhTCaav3nvA47h6mMRFPz0g0bnxpNZVRAJSMlzYBi9XEfed5A1GalYKmDiteXR1+gTC6GteCIK1PKLSm4Vwbm8WDNIMWd04RtCN/+mpP1OuO0ImDekb0BvGZ5+3SXk4ne5XbJ5yyhm+MlGaloqoiC4QAH22sl9VnIEiBFRnwFLAmkjECAJeMKsK4AZnosTnwv8t+ll6nz97Rlj4QolW85o7kZSg5EzCYoB/za8Xr/ujsCy3NVbr3Rc+IfEM/f0ht1hqB3/0M3K3M0oyWMQK4djze5G//rjghD/1SzwjV48jHybrmLry6+gA+2Fgf95BTUMaIXq/HuHHjFOJTKkatrq72+nd/+tOf8Mwzz+DLL7/E+PHjQ29tP6TA7ArVLA0iVEM9I1p7D3R2YSCgpZQjaQCcO1jYoGv1Xs9qpFTIl+J0IhVWpKE7JqtIDwV+EOmAkcCg1eDBaUK9h1dXH1DUqQgF+WrcZBOMPmqMxFNsdvPEClTkpOFEhxXPf7svqp9F71lJM9IjGhqcAyNEY8TdE7K9ebtCQxIqV48XwsAfbKqXVa6EdE8nmoDVHY7j8OiFwv34wcZ6HG0Vnjl673TbOGj8pL9LAuKULODhg9BPflj1fG8TvLwAYjB4fZYD8IxI9wyvBzLygZRMxfFojge09MGmGG6oGQyqYRpRW0O/231NnZjxt+/wh8934YH3t+AvX/8cV4Mk6DDN/fffj1deeQVvvPEGdu3ahTvuuANdXV245ZZbAAA33ngj5s6dK53/xz/+EY8//jgWLVqE8vJyNDQ0oKGhAZ2diVswJtbMFEM1n28NXIMg7fRq64FBNEaoqjySE9ik0wS37Lq6Fo8MErlnJJcTioO5b00V6iDlC9o/OoDR6pKxnLgvGlGIihyhQNh7G8ILI8rFZmab6BmJQ5/c0Wt5PH7R6QCART/URXWnUsnlrhHCt5qCUQAADg6MLLYAgEeY5sO9H+Ke5feE/dkXjihAml6DQye7UXtE+AwNAVI4K9JJp2JreyBxNCNyxg3IwsSB2bA7CV5eJWg5pHuHaJCXLoQVvLVd8jJo9ACvUayi5ROUN2Mk3GwaGqaxGCwAgH2n/Bu/UqE8jUsz8vCZD6PCXOGzrZGA7t+1pb7VQzicCLjGFAL0CmOzzk2Ps+CLXei1OUGL8T6/Yh/e3xj9kKw3gjZGZs2ahWeffRZPPPEERo8ejdraWnz55ZeSqPXw4cM4ftylf3jppZfQ19eHq666CoWFhdLPs88+G7leJDkzRgihmk2HW3GsNTBPgl0cIHiHDWkO0RAIIi0uUAbmpqPQbESf3Yn1blk1cgFrAScc4wxm1XMiibfaBLEuEPabc4VB71/f18EexoAkDcggMDlbAQBaXsgQioRIMxzOH5qPKUNyYXMQ/OHzXVH7HGliGXsTMPEeNA+bAwDgeAdKs4TaGNQY4eAqZS7XLYRKql4rabe+2C4sCDQgSEMvUomnty8RjREAuFvc7HDxT0fQ1NGrMEaKTYIYvc2qXlGYnmvQCPedfIKXLyjcx5aRuULIPdQwjaQZERdSvxrwKwDA0rqlfj28ks6IlroHcMOwG/D69NcBCH2KRp0jQNgwz5Kqg9XuxM5jiZftqfCMiOhk4+TW+lZ8s6sJGp7Dsv+ajMdmno6zKrOkbRLiQUgC1rvvvhuHDh2C1WrFunXrUFVVJR1buXIlXn/9den/Bw8eBCHE4+fJJ58Mt+39hnyTEWcOELQZgQpZaZ0RLQEyHUIsPdKVSAHBBUx3sl39s1I3YrULE4iREJRyYtE7k/JmjqoxIvbXpBf0BQfbDkb8s3xx5dgSZKXpUX+qB18GuJOqGnIBK0UrTgpv7HwDz29+Pqx2hsvjFw2DTsPh291NWLE7tEqb/pBW5kYTcMEfcEh7mnCAs0kT1olu4f7LNCrd8ZGYcGioZtVe4TpqCGBCNwzE6hGmSTTNCKW6Mhtjyyzoszvx6uo6aTInRIOB2cJi0Vv1WPr904k9XZeO4nRhW4S3d70tnefubTi3+FwAkQvTVBdVIyclB63WVnxX/53Pv5UysMRnhSL/f7RCNTzPYZwYqll74KSfs2OPQjMiote4SiB8tlWYZ2YML8CgvHT85txKvHlrFVL17r7t2MH2pkkQZooW6eeBGiOycr85TsG1Tx/CY52R3eBt0mmCbmSVmzEiz4AYIBkjRYpzomKMENeeGwAwuXQyAODrQ1/HdGdVo06DX4s7qf7zuwMhx1vlAlaKU+tamS47tCyMVobPwNx03HK24AV65rOdUSmE5j6xNLcZQBxGgHNKKaRHO4WaJ9cMuUbxt+EWPwOAM8szxfLwsi3tOZpmrDw30TQjFI7jJO/Imz8eQrdNbKdTi7MGCMaWV2PEKQvTAOA5HnePuRsA8K/t/5I8H/LJfc6IOcg0CBNyyGEaeu/zrqJnNWVC2YeNTRt9/q2UAaRRpvbK/x/NUA1dpK3cEx0DPRzk3lZKjui1Pt51XFr0UokAIBS6jCfMGEkQZgwvAMcBmw+3SgI0X8gt3xwiuK+rTEMAAH/f/Hev7thQOHdQLrQ8h71NnYp9dKTVLAhSOfGhdzNGum2R14yoraYsBgtaeluwviG2+x7dWD0Aei2PrfVt2FIf2neu5hkZk1Im/Z6hzwirjZHgnvMHISfdgAPNXXh9TfgZRO64u9wPNvfA0VMCANjWvA2Ayxg5u+hs/HT9T5LhEgljhOM4zJ5QBogGiHxgNOhSFecmqmcEAM4bkodhhSZ09zlwslswEAbnZWFIrpDt6C0DSaEZEbmw4kJYDBZ02bpQ3yloCagh9szZz+C3Y3+LNDGtttMWYjYNnTRlJfazjIKX2F84TK3NgOAx5TlecU40mCJuOLjh4KmY73LtD1dqr4uKNGFsrm3Yg/pTPTDqeEwekhuH1qnDjJEEIc9kxJnlwkP4RQDeEfnNlsEJg+MNpTMxwDQAzT3NEV1Nm1N1OHuQsApYutXVNveqmQAAUzEeP+txZBuFGHU0wzRU9KbjdagZIKymvj/6fcQ/zxfZ6QZpdfHuT6EJWdUGjvOyRuH584XwTDREwMGSYdThoemisbt8H5o6IusdcPeMHGjugqNXWM1vb94Om9OGxm4hK6AkowRGrVEqqBeJjBpAqDyr08j2fBKx6DLw3+f8N84uPhtA4mpGAKV3BJwwQU4dWgyL0QIAaLe2q+7po1ZAjOd4pIkFBWmf3a9TmlY4Huqiw31hAQBGrVHxmd6QMoBkmhFA+A5o+6LpGSnPSUN5dirsToIf9iVWqMa1wHHdyJUZghd3+4m9AICa0/PjGpZxhxkjCQQVD3221b8xIgm/ZG649PRcjMoVshAiNUBTLhwhrKzkYST3EtIAAFMRrhlyDZ6dLAiUY6EZASDFt0MV0oXDNaLe4NPaoyGl+bq8XK7vUZ+eKWkjouFdCoWrxpZgVIkZnVY7/vjFnoi+t/sqt665C06ZZ6ShswFO4oRRY5QMXeoxioRnBBAMy0mnCe/NyQ8Yzbhk4CW4pPISAIltjADA9DMKcM7gbHC8cC9eNKIMZtFFT0BUxwZvXoYUrSAeph4R9wwWWtQwVM+ItLCQeUaoIeEvHOYtTCN/Ldrp/ucNFbwjwRatjDZqC5xKi2CkOvhTKMnSYN7FZ8ShZd5hxkgCMV0M1dQeaUX9Kd8TkBRrlQuU0jJhFFMjqbg0UlwwrABansPuhg5JPS6J3uQxdZNgFKTohEEs0sYIIcRVmEq+mtIEtpqKBmdVZqE8OxVdfY6ANT9y1JTvxswCpGqF8ECiGCM8z+HJS4QB7MNN9fgqDNGuO/LJsLW7Dy1dfZJnZH/rfvzcKhTzKkovAifmIprEwmiRNLxvnCh8Jk9k5ohR+By6Yu9xJG6YBhCu06s3jZb+X2YxQ8frkKETjDe1UI1aZgrgMgzoeOLuGUkVQ1hhb5Qne5YlAyjAMI27gBUADHz0PSMAcMUYwWD+akcD2noSJ1Qjhb9kY3OWqQQ8SQPHEVw70YjcDM/vLZ4wYySByMswYoIUqvE90DtlAlaKIc0ctQEzM02PaWcI3pG31x8C4BrADG5hGsA1oETaGJELVOUDmEEb2GoqGnAch2vOFCax90II1aitYvQ5lWEP9NFgTFkm5ogpzQ99sDUgfVMgSCtuXo+DJwXjKzclF6naVDiJE1uatgBwecCAyHtGAECvFYwQLS8bGtOFTJRAwweJgHwSps8GDdWo6clo5o37xC712c0zEqkwjbuAVf7e/gwJ9wwgOdQzEm1jZHixCUPyM2C1O/FZEHWioo2reJ9rbO5MLYKtR9CIWCyt8WiWT5gxkmBIoRo/K2wpTCOzA7gUS1QHzOuqBFHlks3H0Gm1SwNYpzPNdZIoYKWr+ogbI8RljMgHoXh6RgAhhKHhOWw4dAr7moKbHF3XUty2HVogo1CK1/c5+xJq2+8Hpw3FqFIL2nps+O07nrvFhoK8zgXdX6XIkiIZHLtahBonJRkl0t/QlO5IGiN0EKf7eAAAzMJnRuuejgb0OdBwGuk5oZkvanv6uGfTUNyfK29hmi5bV0jZZO51RgBPA8gb3toMuAyaaIdpOI7D1eOF++PV1eHVG4okil17ASAtFxuO2+GwCsZIqy1+xc28wYyRBGPa8ALwHLDlSCuOtHhfbSg2QgLQAjOg0UkeiWisCKors1GZk4ZOqx3/b+1B6UFvJ7K9g4xCbJq2w+a0RXQi9eYZoQNYtFdC3sgzGXGeqK4PVsjq7hlp4PIAXiNNfkDihGoAoTLrP64dgwyDFhsPncJDH2yFM8ydfSUxokaHEx3C77kZBskY2dMiaFTUPCORzByTQmacbGgUjZFk9IzIPR2+PCPeNCPuz5VHmEa8RwlISEaaqoA1wIWFtzbLX4vFeDB7Qhmy0vTippJHo/55geAK/YrPZVYl1tW1gNiF8dlbinc8YcZIgpGXYcSECjFUs13dO0II8bB8WzRCtgsdJKKxeuN5l1L/n98dQK8YRz7kkKXzivF8aoxEui1ejRFxAIvnqvVaMVTz4aajQdXikG9bDwDNWiEcptPopFVtoq3Gy7JT8ffrxkDDc/h481Es+HJ3WO8nz+agxkhOugHpOmHlTXUO+an50t9EI0wjaRhkK3Uaeoy39y0YqFeBGhOAq9R6KJoRev+5e0ZStCmS4RZKOFFNM0LDSoGGaVQ1IzHyjADCppJ3TBY2lfyfL3ZFLHQZDtL3Sl/IGojtR9tAnIk5ngDMGElIZorbmi/ZrB6DpDca4FpNt2kFYyTaq7dLRhWhMicNrd02HGsXFPT/Zz8X32knApe/LJ2n43WS67XHFnljhOd4xeo13p4RAJgyJBd5GQa0dPXhm12N/v9AxFWgSKBDly0dS0TdCOW8IXn405VCOfB/fncA//35TjhC9JDIJ5bmTk/PCMUs226AhmkiKWB1eUbkYRrByEwWASugPlFTY0Rti4FQPSMcx0m6kWAzapzE6VpUqYRp/E2Y3gwoIHCDJlLcOHEARpaY0dptw82L1ivqMcUDSVNIH8fsSuxr6gSIcH0T0aBmxkgCctGIQug1PHYeb8f2o54uVYUxIq6mO/WiMaKJ7qSs1fCYJ2ZUtPYIg0UvScPzOU8Ao66VzuM4LioiVrW0XiAxVq1aDS/FjxcHEapx93L16l3lzsMVCEabK8eV4LGZwmZ6r6yuw7X/XIu65uANJ3n8Xx6moZoEipoxEg3NiEYRplGKsu1Oe0JpeNSgz4HcGKGp4mouerU6I4DyuSKEqIZ/qMEc7D0qr3eikWl0Ah3DfIVpYlFnRPF5Wg1euG4scjMM2NvUiZrnVuGql9bgD5/txPd7m8MOYwaLewXWnowBON7WK3lGErGKMDNGEpDMND2mDRdc9Yt/OuxxXPEQi/92GwS9Qizi2pNPy8UVY4oBTjAMCNEgJ8NzQIiG4E8txgzEN5tGzqzxgsh39d4TPjU/cqRaC+LAYTXkSMckz4g98TwjlN+cW4l/zB6DVL0GPx08hel//Q6vrj4QlJdEPrGcoJ6RdL2Ujkqhq3sgOp4RyTCUFwZLUz5bQGKuLOXQSVjeZmrIqYZpvEzs8ufK7rSDiPeo/LxQFx1yMbp8cRHoGObNgAJiG6ahlGal4vN7zsGUIbkgBNhw6BRe/b4ON/xrHS5+/nvUHmmNWVucTqVn5AgR7mGTQRhPEvH+ZcZIgjJLLKT1Se0x9PQpKyaqeUasYiw9VtqJ+VeOgEEn3PAV2WbcOWWQxznRqDVCV6TuxkiKJrDaBNGmLDsV5wzKASHAexsC8464C1hPmYZKx0Jddcaai0cV4av7JuGcQTmw2p34w+e7cN0rP6I9wDLZ8skw0DBNNDQjdILk5XsciWm+el4vhQbjfZ/5gxrlcqPBlyfJW2YKfa6sdqvCy0DHGcCzMFqgeE3Tl3k1fGXoJIqAVU6eyYjXb5mA1Q+dh2evHoVZ40uRbtBix7F2XL1wDRZ9XxfyHlbB4CqKKbDLKixwCk3CPZCI9y8zRhKUiQOzUZKZgo5eu4eQVc0zYksVPCmBpsWFi0GrgVGsdvbKr8/C8GKzxzl0kIpkOXMar5ev+IT2BDaAxYJrJ4g1RzYcCSjVjxqX3xbchqdtv8bJ3LOkY9S7lIiaEXdKs1Lx71snYP4VI5Bu0GJdXQtuWrTew5h2hxDimgxlAtbcdKMiTKPltIoMI2qMRMMzonV4VtLlOC4hwoGBIO2orWY0qLSdpun78ozIxxRFWn2I3ljFOCbTjMjF776MiYBSe52x84zIKc1KxVXjSvDHq0biu4fOw4zhBbA5CJ7+bCfueHNT1AukSQucS18Erv8AO1uF77fUIozTiah7YsZIgsLznFRm3F1/IPeM0AvoTBfqk0ipvRGuwKoGfdCNWvVKftHQjNABTz4pCW0QBkQHccR05141fjUsH1lpejS2W7Fizwm/59PruU8/DIscM5BhdA30tNZIIqrf1aAbzi2+7SyYU3TYfLgVD36wxaeBaCd2afC0OTTotQm/52QowzRmg1mqvgq4KrBGQzPCiynqENNhKckiYlXTdngzRtyNQTly40suXpVfh1C9sfIwjVyMLm+zLwNHMqBUwjT0tUR4brLS9Hjx+rF48uJh0Gk4fLmjAZc+/31URa6SELtyMjD4V9jfJHzWgCzhvk5EY5oZIwnM1eNLwHPA+roW7DjmErK6xEm8tIcGZxKMkUD3dQgXQohPNykQHWOEvpd89QQoV4Dx1o0YtBpcNU4Qsr754yG/59OJuKdP+DfD6HJZJ5NnRM7wYjP++etx0PIcPtt6HC+t2u/1XDqpAEB7t2C0pOk1SNVrFWEaeYgGgJT2a3VYI6YNkJ6t/DOASQ8Bt61QHA+0VHm8UUvt9WY0yI1Bb9k0vY5ej7ReSqiZK/Lqq3LjRstrJQ2Jr2fZl2ckWttRhArHcbj57Ap8cPtEFFtScPBkNy5/4Qes2d8clc9zz1I60iJ8D2WZFgCJef8yYySBKTSnSGm+L686IL2upvg3ZAjpoIGmxYWLnbjEbGqpdYDMGIlgai99iNzDNDpel1Dx/OsmlIHjgFU/n8CeBt8rd3o9u6zC95kuN0aoZiQBdu4NlqrKbGkvmz9/tQcrdjepniefxFq7qFdEmODkYRp3Y4R+N0Dk7ndpENcagfN/D2RVKo4nQj2bQKCeUbmXwVsIV24M+tqbxltdj1D1WtQz4p4Zp2irj/f0ZhwBiVstd1SpBZ/cfTbGllnQ3mvHTYvWe30uQkVeh4qOiY3iLtvFZqYZYYTIf04SBsPPth7DAdGtJ63eeC1OcRYsc4yDKcVVhAiIvnZCPoB584xIG71FUjPixTMi3zY83p4RQNhefIaYEfXyd969AoDrevb0CddLHqZJ5DojgXDDWQNwfVUZCAHue7dWNcOITnJaTouTncIElZsuXEuFZ0SvNEZ0vE5yx0dK4Ku2i6wcej0SbZJzhz4DamEa97bLvUrePCM9jh7V0I/8nGCfO2lRxXt+14Gk5vramyZae2NFgpx0A96ec5akI7n9zY3YfNgzwylU5GF8La9Fr82B1m5hvC42Mc0II0SGF5tx/tA8OAnwl2XCzqVyY+TqlFcwx3a/5NqnD7GTOKNaC0ExgKnEbIHorOrp4CIPy1ASzYX+n5OEqoxLNh/F7gbvIkt6Peuahb7JwzSJXmckEJ64eBhGi3vZ3P7mRvTalIJWubv950bBi1SWJdw77poRd6g7PlL3mFoRLjnJEjajz6ciTCPzNsgXKvT713Aajyw1+S7g3jwRoXpjJc8I78Mz4sPA8ba5HyATzyfoc2PUafD32WMwdWgerHYn7nxrE052RkbnR+9hQPCMUEG4QcsjN13wNCZirRxmjCQBD04bAo4DPt96HBsPnVLsn3HKygHgJNe+fPCJ5qpAPoCprWyA6KzqJc+ILsXjWKwLHfljVKkFM4YXwEmAZz7bqVr4iBCCLqto2BEOPAcUW1x9S5bUXl8YtBq8eP1YZKXpseNYOx79aJtyMpRpj7bWtwIARpYIhoc8TEMFq3Ik71uEvh+Xoe/7nk70sJmaZ0S+j4z8GfGl/ZJXYPUWpgk1m8aXFyqQrCVfmpFk8GDpNDz+eu1oVOam4XhbL+55Z3NENtpTlH7gNNLGk/kmo2LcjEWSQzAwYyQJOL3QhKvGCoLIuR9tRa/NVWujo1d4oKlrX8frpBhsNCdlf+JVIDqrel+ekVjpZYJh7ozTodfy+GHfSQ8R57b6Nly9cC06rML1HD8gBx/eMRH5JlffohHqigdFlhT8Y7awl81Hm4/iL1//LBkk8ntpm1hxeGSpBYAyTKN2zSOtDVDdKE/+eUliHKppRuS/y78vX2XV5RoZb56RUDUj1LOh+rkBbO/gq+hZIodp5GQYdXj5hnFI1WuwZv9J/G353rDf090z0tgufIf5JgP0vB6cmPaQCOFsOcwYSRIevfB0ZKfp8XNjJ977ScjQ4MCjz+GZgSHVBohiuCIgY0RMS42kZ4T2yV0zAkS/FH4olGWn4imZiPPJT3dgxZ4mPPzBVlzywvfYcOgUOE64hguuGIUxZZmKv4/Gdxgvzh6Ug2cuHQ4AeH7FPjz92U5Y7Q7pemmgQ3NnH7Q8h2GFghdEnsKtZiBE2lMhz/BQI1nCZmqeEQ2vkSZu+dgQaFl1v56RICe3DpsQknMvbCf/DF/GhKQZ0XjXjCSDET84PwMLxD2eXlixDz8dbAnr/eSlDTS8yzOSZzIKtXISdPdpZowkCZlpejxx8TAAwDuiMUI38+I4IF0f2x1svdUlkBONidSbgBVI3C3eZ08ow51TBP3I62sO4pbXfsK7G46AEOCy0UVIMwiPodoEmCxhgUC5rqoMj18k3Mev/XAQM/66Gktqhfu5o0fwlJyWnwGjjt7brpRPNWMk0tqAQD0jiW4cqpWDB2QprzIBoy8Pg/yZirRmpLNPEOTTFG219/S2sHASp6Q58ZlNE8FMvmhyyagiXDm2BE4C/Ne7tegIsHKxGnLPiIbTSJk0+RnCd5po2joKM0aSiEtGFWHKkFzYqOVLhMuXrteC52VFiGJQhTUQz0g0Bm7aJzVjJJDVVLx4aPpQLLp5PKYOzUNlbhpmjijEB7dX46/XjgGBMg1PDjXo6MDdH7j1nAosvEHQkBxo7sK/1wnhqzbxso0dYFH9OzUBa6TDWJJmxE82TSLvFQSoh2kA9YVKIJoReZ0RA6/+nsFObnSX3zR9mufn+nlPuYDel4A1EccCbzx5yTCUZqWg/lQP5n26I+T3URTF5Hg0ycI0gOy7TbAwjbovkpGQcByHBVeMxPSFtXAAaGwXHsjKPOXKIhZVWH2l1VHoRBrRbBqbD89IAoZp5Jw/NB/nD833eN1VN8ZzAqTprJEseZ4ITB9eiLMH5eDDjfX4aE896iBU8p11djnuEL1IlIfPfBirj67GFYOv8HifSBe38nUtgOQO0wDqq2JfQlC5TodWuvX2nsE+d9TAdt8MEfAfapaXeVfz6CRqnRFfZBh1+N9rRuOal9fio01Hcf7QPFwk1pkKBveMMLmAFUhMbR3APCNJR4HZiHumCrVHiOgZmSeGbyixqLfhawCjRCVM42VvGvlrieZ+9IevDA6aQdLe165wv/YHMow63Hx2Be48fwAAYHRJDuZdfAbyMpTX9oZhN+DlX72saoBGOpvGvViUx+cli4DVW5hGxWPgq6y6QbbVQ1ufIC72qMCqCU2jRjUj8owp93Z6M3DknhG18KbcSI33XlXBML48C3edJ2w6OvfDbT5LAnhD2tKAFjyTNCOiZyRBx0lmjCQhI4qFCSpFp8XTl56BsW6ix1hYvr4GMEo0ajL40owkUtGzYPClU6A7rTqJM+F1CqHiS7Pgj4gLWIkfAWsUvH3RgE40gaTh+lpYyLPz2q3tPt8z2EJaXX3C/aymGfEXcpXfM3JdEUWexpxs48Fvpw7GhIosdFiFCq27jgdnkMjvYYeT4Gir8B0WmYUxM1HDNMwYSUKocKs8OwM3Vpd7HA8kLS5cgvGMRCW1t594RtzFZu4YtUZpku5voRpKIPojb8RcwJokRc8kz4jGv2fEV1YK4PKOnOoVqoR687aEqhkJRcDq756JVb2laKDT8Hjl1+MxJD8Dje1WXPnSGixctR+t3YHtvyT37h1p6UavzQmDlkepWEgwUQWsTDOShPiLa8dim3N/AxjgWrX2Onphd9q9rjaDIdlSe/2h2EbdS6Etk8GE5p5mtFvbUZxeHKumxQxfe4z4I+ICVj/PVrJkN3nNfPElYPXimTJoDOiydeFY1zEAQJYxS/meIS4CqAZFLUzjV8DqZzHEczyMGiN6Hb3otnV7tDnRMafq8N5/VuOOtzZizf6TWPDFbvzpy90ozkxBeXYastL0yDBqkWHUocBkxISKLJwupsPLDeo9YkXjwfnp0IhJDomqGWHGSBLir2R1LG42bzUH5FDPCCAM3jTkEA60T/L6E5REfch84V4tUQ2z3iwYI/3UM+KrrLc/Il1pM9AKrEnjGfGS2htonRHAZfgf7TgKAMhOyVYcD3XxQ79DX2Eab6EEKUzsJ5uv19GbVOOBHHOqDm/eWoUPN9Vj0Q8Hset4O4609Eg78LozotiM66vKMKLCVR37Z3GTztPyZcUDE9SDzIyRJISGabwNmLHwENB9DXzF+fW8HlpOCzuxo9sWGWPE26698teSyjPiloanhlzE2h+h18tXZpY3Yp3amyzZNEGl9vqpGUTfgwpOs41uxkiImhFfAlZ/E2YgdY6SMb3XHZ7ncPX4Ulw9vhRNHb042NyNQye70NZjQ3uvHR29NtQ1d2HNvpPYdrQNj3y0DdlZJ4F8oQ7Vz01CKExhjCSoZoQZI0lIoJ6RaFq+0gTiI0zDcRxSdalo72uP2ODts+hZDMJTkUaxw6bKVuqAS8RKBYT9jUD0R96QPCMRKm7l79mSC1gJIariyUSATjTeNCPyiSgY/QXg6Rmh70k3XwvUqPSV2ktryrT0qlcjDSS0l0xVWAMhL8OIvAwhJONOS1cfPth4BG+sOYTjXb1IA3Cy04b/2yuE1oYkgWeECViTEF9bbwOuAbPN2ha1NgSaARHp9F7JM6KyT0ksyuBHGqdTuY+EGtQYoamV/Y1wwjSRnnCkzdv8hGmcxJlwK0tKj71H8lzS9lKCrTMCAHmpeYr/56TkKP4vN1aCqW3kq+hZSbqwF9exzmOqfxtInaNkq8IaDllpetw2aSBWPDAF90wV6vQQ4jKUTyvw9IwkmseIGSNJiD/Ff2lGKQDgUMehqLUh0NWsZIxEoGKlzWGTQlRqu/bmGIVBsqG7IezPihW0P0AAYZp+6hmJRJgmUgOrP8+I3COXqKGaw+2HAQjeBfeqtWq6Kn/6CzqeUDKNylICoW6+5sszUpQuFPtq6G5Q3eo+EAO2P4RpgkWv5TH19FwAQF5GCqYOzcPlY4pRZHYZjIkazmZhmiREyiP34tYvN5UDAA61R88YCURABkRW8Cdf/dKdQuUMtAgrgrq2OjicDq+r20RCPvl5c/n31yqsFGrYhiNgjVhqr9O3oc9zPFK0Keix96Db1u0RskgEDrYfBAAMMA3wOKa2KpZCHl68nHJjxGKweBiNdPO1HntPwF5Jh9MhPc9qmpGclBzoeT36nH1o7GpESUaJ4nggi6FfojECuOaHVJ0e/5p1psfxRE3tZZ6RJMTfgEkHoYauhqg9iAGHaSIo+KMPj5bTqmpVitOLoef1sDqsUhpiouOv4ifQ/wWs4dQZibWAFUj8wmd0EUIXJXLUyuf7S9MvyyiTfncXr1KC1WvJPaVq2TQ8x0vekaOdRz2OB6JZo31N1OsULfzND/0qTPPCCy+gvLwcRqMRVVVVWL9+vc/z33//fQwdOhRGoxEjRozA0qVLQ2osQ8Bf+mGmMVNyz1KXbaShKxNfgwEQWc2IL/EqIHwf5eZyAMCB1gNhf14soBoFXzVY+r2ANRxjROYZiUTZ72CMkURN7z3YdhCAujGiZjT4y4yTe0ayUtTrdQS7OScN0eh5vdfrTmvqqOlGAlkMJeP+NJHAX6gxP03YH2t3y+6EKpUftDHy7rvv4v7778e8efOwadMmjBo1CtOmTUNTU5Pq+WvWrMHs2bNx6623YvPmzbjssstw2WWXYfv27WE3/pcKtXy9hWkAl3eEumwjTSB1RoDIhmmkDAGVtF7KQLMQqjnQlhzGSECeEX3/9oyEU/SMGqYEJCIxcH+GPhB5b0ykoZ4RtTANbbtaNo23Z7kwvVD63dvkFWyNH18FzyjUM1LfWe9xTDKgWJjGA0lTyKuPKRMKJkDH61DfWY+69rpYNs0nQWtGnnvuOcyZMwe33HILAGDhwoX4/PPPsWjRIjzyyCMe5//tb3/D9OnT8eCDDwIAnnnmGSxbtgzPP/88Fi5cGGbzw6O5p1mx4VKy0GIV0t18TWDlpnJsPbEVO5p3YETOiIi3gU6MgWbTNHY3elXGB0p9hzAoefOMAECFpQIAsOPkjrA/LxYc7zoOILAwzaneU0nRp2ChWRWh7E0jz6o60HYAFoMlrLbQzAtfnhFqYB/tOJqQ18OnZkQ0Gtqt7VLb6bPszcsp14h4M8DodTjWeSyg7+Rwh+CxVQvRUKhn5EDrAY/3PNlzEkBgAtYT3ScS8jpFixM9JwD4riJ8ZsGZWHNsDb6o+wKXD7pcOpaTkhPSoiASBGWM9PX1YePGjZg7d670Gs/zqKmpwdq1a1X/Zu3atbj//vsVr02bNg1Llizx+jlWqxVWq2uV094enRXhfSvuw5YTW6Ly3rHA14BJXbSv7XgNr+14LWptCDRM887ud/DO7nci8pmBeEa+OvgVvjr4VUQ+Lxb4upZUwHqs6ximfTgtVk2KOaEMghpeIwlKZ302K2Jt8WUcUu/CH9b9AVgXsY+MOGWmMo/X6LOzv22/x70UyPfvbSFAX3/sh8eCaqMvzwg1Rr45/A2+OfyN6jk+U3tFo/GT/Z/gk/2fBNWu/oCve3hSySSsObYGC7csxMItLqfAmxe+iVG5o2LRPA+CMkaam5vhcDiQn5+veD0/Px+7d+9W/ZuGhgbV8xsavKdfzp8/H0899VQwTQsJHa8LScGfCOg1epxfdr7X4+eVnofFexZHtdaIxWBBVUGVz3MmlUzCx3s/lla/4cJzPGZUzPB6vKqwChXmiqRbCV1YcaHXY6WmUozOHY1dLbti2KLYkpuSizF5Y0L624sqL8Kn+z+NWFtyUnIwLn+c1+PTyqdhc9Nm1ZTTRGFa+TRVw+H0rNNxWuZpHpl2WcYsnJnvmXlB+Z9z/gcv1r6IuRPmqh6/oPwC7G7ZrSji5w+e433e9xMKJ6DcVC55D90xao2YUjrF699PLJqIt3e93W/Dm77gOR7Ty6d7PT69fDoW717s8d3SFO14wJEgFCzHjh1DcXEx1qxZg+rqaun1hx56CKtWrcK6dZ7LBL1ejzfeeAOzZ8+WXnvxxRfx1FNPobGxUfVz1DwjpaWlaGtrg8kUfklxBoPBYDAY0ae9vR1ms9nv/B2UZyQnJwcajcbDiGhsbERBQYHq3xQUFAR1PgAYDAYYDMnpsWAwGAwGgxEcQWXT6PV6jBs3DsuXL5deczqdWL58ucJTIqe6ulpxPgAsW7bM6/kMBoPBYDB+WQSdTXP//ffjpptuwvjx4zFhwgT89a9/RVdXl5Rdc+ONN6K4uBjz588HANx7772YPHky/vKXv2DmzJlYvHgxNmzYgH/+85+R7QmDwWAwGIykJGhjZNasWThx4gSeeOIJNDQ0YPTo0fjyyy8lkerhw4cV+c0TJ07E22+/jcceewyPPvooBg8ejCVLlmD48OGR6wWDwWAwGIykJSgBa7wIVADDYDAYDAYjcQh0/mZ70zAYDAaDwYgrzBhhMBgMBoMRV5gxwmAwGAwGI64wY4TBYDAYDEZcYcYIg8FgMBiMuMKMEQaDwWAwGHGFGSMMBoPBYDDiCjNGGAwGg8FgxBVmjDAYDAaDwYgrQZeDjwe0SGx7e3ucW8JgMBgMBiNQ6Lztr9h7UhgjHR0dAIDS0tI4t4TBYDAYDEawdHR0wGw2ez2eFHvTOJ1OHDt2DBkZGeA4LmLv297ejtLSUhw5cqTf7nnT3/vY3/sH9P8+9vf+Af2/j/29f0D/72O0+kcIQUdHB4qKihSb6LqTFJ4RnudRUlIStfc3mUz98uaS09/72N/7B/T/Pvb3/gH9v4/9vX9A/+9jNPrnyyNCYQJWBoPBYDAYcYUZIwwGg8FgMOLKL9oYMRgMmDdvHgwGQ7ybEjX6ex/7e/+A/t/H/t4/oP/3sb/3D+j/fYx3/5JCwMpgMBgMBqP/8ov2jDAYDAaDwYg/zBhhMBgMBoMRV5gxwmAwGAwGI64wY4TBYDAYDEZc+UUbIy+88ALKy8thNBpRVVWF9evXx7tJIfHkk0+C4zjFz9ChQ6Xjvb29uOuuu5CdnY309HRceeWVaGxsjGOL/fPdd9/h4osvRlFRETiOw5IlSxTHCSF44oknUFhYiJSUFNTU1GDv3r2Kc1paWnD99dfDZDLBYrHg1ltvRWdnZwx74R1//bv55ps9run06dMV5yRy/+bPn48zzzwTGRkZyMvLw2WXXYY9e/Yozgnkvjx8+DBmzpyJ1NRU5OXl4cEHH4Tdbo9lV7wSSB+nTJnicR1vv/12xTmJ2seXXnoJI0eOlIpgVVdX44svvpCOJ/v1A/z3MZmvnxoLFiwAx3G47777pNcS5jqSXyiLFy8mer2eLFq0iOzYsYPMmTOHWCwW0tjYGO+mBc28efPIGWecQY4fPy79nDhxQjp+++23k9LSUrJ8+XKyYcMGctZZZ5GJEyfGscX+Wbp0Kfn9739PPvroIwKAfPzxx4rjCxYsIGazmSxZsoRs2bKFXHLJJaSiooL09PRI50yfPp2MGjWK/Pjjj2T16tVk0KBBZPbs2THuiTr++nfTTTeR6dOnK65pS0uL4pxE7t+0adPIa6+9RrZv305qa2vJhRdeSMrKykhnZ6d0jr/70m63k+HDh5OamhqyefNmsnTpUpKTk0Pmzp0bjy55EEgfJ0+eTObMmaO4jm1tbdLxRO7jp59+Sj7//HPy888/kz179pBHH32U6HQ6sn37dkJI8l8/Qvz3MZmvnzvr168n5eXlZOTIkeTee++VXk+U6/iLNUYmTJhA7rrrLun/DoeDFBUVkfnz58exVaExb948MmrUKNVjra2tRKfTkffff196bdeuXQQAWbt2bYxaGB7uk7XT6SQFBQXkz3/+s/Raa2srMRgM5J133iGEELJz504CgPz000/SOV988QXhOI4cPXo0Zm0PBG/GyKWXXur1b5Kpf4QQ0tTURACQVatWEUICuy+XLl1KeJ4nDQ0N0jkvvfQSMZlMxGq1xrYDAeDeR0KEyUw+8LuTbH3MzMwkr776ar+8fhTaR0L6z/Xr6OgggwcPJsuWLVP0KZGu4y8yTNPX14eNGzeipqZGeo3nedTU1GDt2rVxbFno7N27F0VFRaisrMT111+Pw4cPAwA2btwIm82m6OvQoUNRVlaWtH2tq6tDQ0ODok9msxlVVVVSn9auXQuLxYLx48dL59TU1IDneaxbty7mbQ6FlStXIi8vD0OGDMEdd9yBkydPSseSrX9tbW0AgKysLACB3Zdr167FiBEjkJ+fL50zbdo0tLe3Y8eOHTFsfWC495Hy1ltvIScnB8OHD8fcuXPR3d0tHUuWPjocDixevBhdXV2orq7ul9fPvY+U/nD97rrrLsycOVNxvYDEeg6TYqO8SNPc3AyHw6H4cgEgPz8fu3fvjlOrQqeqqgqvv/46hgwZguPHj+Opp57Cueeei+3bt6OhoQF6vR4Wi0XxN/n5+WhoaIhPg8OEtlvt+tFjDQ0NyMvLUxzXarXIyspKin5Pnz4dV1xxBSoqKrB//348+uijmDFjBtauXQuNRpNU/XM6nbjvvvtw9tlnY/jw4QAQ0H3Z0NCgeo3psURCrY8AcN1112HAgAEoKirC1q1b8fDDD2PPnj346KOPACR+H7dt24bq6mr09vYiPT0dH3/8MYYNG4ba2tp+c/289RFI/usHAIsXL8amTZvw008/eRxLpOfwF2mM9DdmzJgh/T5y5EhUVVVhwIABeO+995CSkhLHljFC5dprr5V+HzFiBEaOHImBAwdi5cqVmDp1ahxbFjx33XUXtm/fju+//z7eTYka3vp42223Sb+PGDEChYWFmDp1Kvbv34+BAwfGuplBM2TIENTW1qKtrQ0ffPABbrrpJqxatSrezYoo3vo4bNiwpL9+R44cwb333otly5bBaDTGuzk++UWGaXJycqDRaDwUw42NjSgoKIhTqyKHxWLBaaedhn379qGgoAB9fX1obW1VnJPMfaXt9nX9CgoK0NTUpDhut9vR0tKSlP2urKxETk4O9u3bByB5+nf33Xfjs88+w4oVK1BSUiK9Hsh9WVBQoHqN6bFEwVsf1aiqqgIAxXVM5D7q9XoMGjQI48aNw/z58zFq1Cj87W9/61fXz1sf1Ui267dx40Y0NTVh7Nix0Gq10Gq1WLVqFf7+979Dq9UiPz8/Ya7jL9IY0ev1GDduHJYvXy695nQ6sXz5ckWsMFnp7OzE/v37UVhYiHHjxkGn0yn6umfPHhw+fDhp+1pRUYGCggJFn9rb27Fu3TqpT9XV1WhtbcXGjRulc7799ls4nU5pQEkm6uvrcfLkSRQWFgJI/P4RQnD33Xfj448/xrfffouKigrF8UDuy+rqamzbtk1hdC1btgwmk0lyo8cTf31Uo7a2FgAU1zGR++iO0+mE1WrtF9fPG7SPaiTb9Zs6dSq2bduG2tpa6Wf8+PG4/vrrpd8T5jpGTAqbZCxevJgYDAby+uuvk507d5LbbruNWCwWhWI4Wfjd735HVq5cSerq6sgPP/xAampqSE5ODmlqaiKECKlbZWVl5NtvvyUbNmwg1dXVpLq6Os6t9k1HRwfZvHkz2bx5MwFAnnvuObJ582Zy6NAhQoiQ2muxWMgnn3xCtm7dSi699FLV1N4xY8aQdevWke+//54MHjw4YVJfffWvo6ODPPDAA2Tt2rWkrq6OfPPNN2Ts2LFk8ODBpLe3V3qPRO7fHXfcQcxmM1m5cqUiLbK7u1s6x999SVMKL7jgAlJbW0u+/PJLkpubmzBpk/76uG/fPvL000+TDRs2kLq6OvLJJ5+QyspKMmnSJOk9ErmPjzzyCFm1ahWpq6sjW7duJY888gjhOI58/fXXhJDkv36E+O5jsl8/b7hnCCXKdfzFGiOEEPKPf/yDlJWVEb1eTyZMmEB+/PHHeDcpJGbNmkUKCwuJXq8nxcXFZNasWWTfvn3S8Z6eHnLnnXeSzMxMkpqaSi6//HJy/PjxOLbYPytWrCAAPH5uuukmQoiQ3vv444+T/Px8YjAYyNSpU8mePXsU73Hy5Ekye/Zskp6eTkwmE7nllltIR0dHHHrjia/+dXd3kwsuuIDk5uYSnU5HBgwYQObMmeNhKCdy/9T6BoC89tpr0jmB3JcHDx4kM2bMICkpKSQnJ4f87ne/IzabLca9UcdfHw8fPkwmTZpEsrKyiMFgIIMGDSIPPvigok4FIYnbx//4j/8gAwYMIHq9nuTm5pKpU6dKhgghyX/9CPHdx2S/ft5wN0YS5TpyhBASOT8Lg8FgMBgMRnD8IjUjDAaDwWAwEgdmjDAYDAaDwYgrzBhhMBgMBoMRV5gxwmAwGAwGI64wY4TBYDAYDEZcYcYIg8FgMBiMuMKMEQaDwWAwGHGFGSMMBoPBYDDiCjNGGAxG3JgyZQruu+++eDeDwWDEGWaMMBgMBoPBiCusHDyDwYgLN998M9544w3Fa3V1dSgvL49PgxgMRtxgxgiDwYgLbW1tmDFjBoYPH46nn34aAJCbmwuNRhPnljEYjFijjXcDGAzGLxOz2Qy9Xo/U1FQUFBTEuzkMBiOOMM0Ig8FgMBiMuMKMEQaDwWAwGHGFGSMMBiNu6PV6OByOeDeDwWDEGWaMMBiMuFFeXo5169bh4MGDaG5uhtPpjHeTGAxGHGDGCIPBiBsPPPAANBoNhg0bhtzcXBw+fDjeTWIwGHGApfYyGAwGg8GIK8wzwmAwGAwGI64wY4TBYDAYDEZcYcYIg8FgMBiMuMKMEQaDwWAwGHGFGSMMBoPBYDDiCjNGGAwGg8FgxBVmjDAYDAaDwYgrzBhhMBgMBoMRV5gxwmAwGAwGI64wY4TBYDAYDEZcYcYIg8FgMBiMuMKMEQaDwWAwGHHl/wNwqu0JbYWDdQAAAABJRU5ErkJggg==", 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", 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YiPLycvk4HoqjQrDwNFBWVhYJFoIgCIJIMvTYOch0SxAEQRBEwkOChSAIgiCIhIcEC0EQBEEQCc9R4WEhiGTA4/HA5XLFezOILojVaoXZbI73ZhBEhyDBQhAxRhRF1NTUoL6+Pt6bQnRhcnJyUFJSQr2qiKSFBAtBxBguVoqKipCWlkYHDKJTEUURra2tOHjwIACgtLQ0zltEEJFBgoUgYojH45HFSn5+frw3h+iipKamAgAOHjyIoqIiSg8RSQmZbgkihnDPSlpaWpy3hOjq8O8g+aiIZIUEC0F0ApQGIuINfQeJZIcEC0EQBEEQCQ8JFoIgApgwYQJuvPHGoI/36tULjzzySKdtD0EQBJluCYIwzJo1a5Cenh7vzSAIogtBgoUgCMMUFhbGexMIIiEQRRHtLi9SbVR5FWsoJUQQhCZutxuzZ89GdnY2CgoK8J///AeiKAIITAlVVVXh7LPPRkZGBrKysnDBBRfgwIED8uO33347RowYgQULFqBHjx7IyMjAtddeC4/Hg/vuuw8lJSUoKirCXXfd5bMNDz30EIYOHYr09HSUl5fj2muvRXNzs/z47t27MW3aNOTm5iI9PR2DBw/GJ598AgCoq6vDxRdfjMLCQqSmpqJfv3546aWXYviJEV2Ruz7+DUNu/wy/VTfGe1OOeijCQhCdiCiKaHN54vLaqVazoUqRRYsW4YorrsDq1auxdu1a/OlPf0KPHj1w1VVX+Szn9XplsbJixQq43W5cd911mDFjBpYvXy4vt2PHDnz66adYsmQJduzYgfPOOw87d+5E//79sWLFCnz//fe4/PLLMWnSJIwZMwYAYDKZ8Nhjj6F3797YuXMnrr32Wtxyyy146qmnAADXXXcdnE4nvv76a6Snp2PTpk3IyMgAAPznP//Bpk2b8Omnn6KgoADbt29HW1tbBz9FgvDlhW93AQDuXbIZC2cdH+etObohwUIQnUiby4NBt34Wl9feNG8y0mz6f/Ll5eV4+OGHIQgCKioq8Msvv+Dhhx8OECzLli3DL7/8gl27dqG8vBwA8PLLL2Pw4MFYs2YNjjvuOABM2CxYsACZmZkYNGgQJk6ciC1btuCTTz6ByWRCRUUF7r33Xnz11VeyYFEbf3v16oU777wTV199tSxYqqqqcO6552Lo0KEAgD59+sjLV1VVYeTIkRg9erT8fIKIFQ1t1N8m1lBKiCAITU444QSfiMzYsWOxbds2eDy+EaLffvsN5eXlslgBgEGDBiEnJwe//fabfF+vXr2QmZkp/11cXIxBgwbBZDL53MdbyAPAF198gVNPPRXdunVDZmYmLrnkEtTW1qK1tRUAcMMNN+DOO+/ESSedhNtuuw0bNmyQn3vNNdfg9ddfx4gRI3DLLbfg+++/j8KnQhDaNLSSYIk1FGEhiE4k1WrGpnmT4/ba8cRqtfr8LQiC5n1erxcAUFlZiTPPPBPXXHMN7rrrLuTl5eHbb7/FFVdcAafTibS0NFx55ZWYPHkyPv74YyxduhTz58/Hgw8+iOuvvx5Tp07F7t278cknn+Dzzz/Hqaeeiuuuuw4PPPBAp71noutQTxGWmEMRFoLoRARBQJrNEpeL0U6nq1at8vn7hx9+QL9+/QLm0AwcOBB79uzBnj175Ps2bdqE+vp6DBo0KOLP6scff4TX68WDDz6IE044Af3798f+/fsDlisvL8fVV1+Nd999F3/961/x/PPPy48VFhbi0ksvxX//+1888sgjeO655yLeHoIIBaWEYg9FWAiC0KSqqgpz5szBn//8Z6xbtw6PP/44HnzwwYDlJk2ahKFDh+Liiy/GI488ArfbjWuvvRannHKK7B+JhL59+8LlcuHxxx/HtGnT8N133+GZZ57xWebGG2/E1KlT0b9/f9TV1eGrr77CwIEDAQC33norRo0ahcGDB8PhcOCjjz6SHyOIaOPxivHehKMeirAQBKHJzJkz0dbWhuOPPx7XXXcd/vKXv+BPf/pTwHKCIOCDDz5Abm4uxo8fj0mTJqFPnz544403OvT6w4cPx0MPPYR7770XQ4YMweLFizF//nyfZTweD6677joMHDgQU6ZMQf/+/WVDrs1mw9y5czFs2DCMHz8eZrMZr7/+eoe2iSDU8DJ/TnucKgC7CoLo/4knIY2NjcjOzkZDQwOysrLivTkEIdPe3o5du3ahd+/eSElJiffmEF0Y+i5GH6fbi/7//lT++5tbJqI8jyazG8HI8ZsiLARBEAQRAe1u34hKTWN7nLaka0CChSAIgiAiwD8FVNNAgiWWGBYsX3/9NaZNm4aysjIIgoD3338/5PKXXXYZBEEIuAwePFhe5vbbbw94fMCAAYbfDEEQBEF0Fg6X1+fvAxRhiSmGBUtLSwuGDx+OJ598Utfyjz76KKqrq+XLnj17kJeXh/PPP99nucGDB/ss9+233xrdNIIgCILoNPwjLC0OMt3GEsNlzVOnTsXUqVN1L5+dnY3s7Gz57/fffx91dXWYNWuW74ZYLCgpKTG6OQRBEAQRF9r9Iiz+nhYiunS6h+XFF1/EpEmT0LNnT5/7t23bhrKyMvTp0wcXX3wxqqqqOnvTCIIgCEI3/gKFyppjS6c2jtu/fz8+/fRTvPrqqz73jxkzBgsXLkRFRQWqq6txxx13YNy4cdi4caPP7BGOw+GAw+GQ/25spLHeBEEQROfiL1D8Iy5EdOlUwbJo0SLk5ORg+vTpPverU0zDhg3DmDFj0LNnT7z55pu44oorAtYzf/583HHHHbHeXIIgCIIIir9AcVCEJaZ0WkpIFEUsWLAAl1xyCWw2W8hlc3Jy0L9/f2zfvl3z8blz56KhoUG+qGeYEARBEERnEBBhIQ9LTOk0wbJixQps375dM2LiT3NzM3bs2IHS0lLNx+12O7KysnwuBEEQBNGZ+AuWNicJllhiWLA0Nzdj/fr1WL9+PQBg165dWL9+vWySnTt3LmbOnBnwvBdffBFjxozBkCFDAh67+eabsWLFClRWVuL777/HOeecA7PZjIsuusjo5hEEQehCTx8pgghFu9uvSog8LDHFsIdl7dq1mDhxovz3nDlzAACXXnopFi5ciOrq6oAKn4aGBrzzzjt49NFHNde5d+9eXHTRRaitrUVhYSFOPvlk/PDDDygsLDS6eQRBEATRKXDPSobdgmaHm1JCMcZwhGXChAkQRTHgsnDhQgDAwoULsXz5cp/nZGdno7W1FVdddZXmOl9//XXs378fDocDe/fuxeuvv45jjjnG8JshCCI6TJgwAddffz1uvPFG5Obmori4GM8//zxaWlowa9YsZGZmom/fvvj0U2Xw28aNGzF16lRkZGSguLgYl1xyCQ4fPiw/vmTJEpx88snIyclBfn4+zjzzTOzYsUN+vLKyEoIg4N1338XEiRORlpaG4cOHY+XKlWG3VxRFFBYW4u2335bvGzFihE9a+dtvv4Xdbkdrayt69eoFADjnnHMgCIL8N0EYgaeEslOt0t8UYYklNEuIIDoTUQScLfG5GBzMvmjRIhQUFGD16tW4/vrrcc011+D888/HiSeeiHXr1uH000/HJZdcgtbWVtTX1+N3v/sdRo4cibVr12LJkiU4cOAALrjgAnl9LS0tmDNnDtauXYtly5bBZDLhnHPOgdfru5P/17/+hZtvvhnr169H//79cdFFF8HtdofcVkEQMH78ePlkqa6uDr/99hva2tqwefNmAMxHd9xxxyEtLQ1r1qwBALz00kuorq6W/yYII3CBkpPGBAtVCcWWTi1rJoguj6sVuLssPq/9z/2ALV334sOHD8e///1vAMybds8996CgoECOlN566614+umnsWHDBnzxxRcYOXIk7r77bvn5CxYsQHl5ObZu3Yr+/fvj3HPP9Vn/ggULUFhYiE2bNvl4226++WacccYZAIA77rgDgwcPxvbt28POF5swYQKeffZZAGzm2ciRI1FSUoLly5djwIABWL58OU455RQAkNPNOTk51GGbiBgeYeGChRrHxRaKsBAEocmwYcPk22azGfn5+Rg6dKh8X3FxMQDg4MGD+Pnnn/HVV18hIyNDvnCBwdM+27Ztw0UXXYQ+ffogKytLTsP4e97Ur8tTOgcPHgy7vaeccgo2bdqEQ4cOYcWKFZgwYQImTJiA5cuXw+Vy4fvvv8eECROMfxAEEQTuWclJZa062kiwxBSKsBBEZ2JNY5GOeL22kcWtVp+/BUHwuU8QBACA1+tFc3Mzpk2bhnvvvTdgPVx0TJs2DT179sTzzz+PsrIyeL1eDBkyBE6nM+jrql8jHEOHDkVeXh5WrFiBFStW4K677kJJSQnuvfderFmzBi6XCyeeeKLOd08Q4eEpoWw5wkIellhCgoUgOhNBMJSWSRaOPfZYvPPOO+jVqxcslsDdSm1tLbZs2YLnn38e48aNA4CoT2QXBAHjxo3DBx98gF9//RUnn3wy0tLS4HA48Oyzz2L06NFIT1c+e6vVCo+HzoiJyJFTQtx06/ZAFEVZaBPRhVJCBEF0mOuuuw5HjhzBRRddhDVr1mDHjh347LPPMGvWLHg8HuTm5iI/Px/PPfcctm/fji+//FJuiRBNJkyYgNdeew0jRoxARkYGTCYTxo8fj8WLF8v+FU6vXr2wbNky1NTUoK6uLurbQhz98IhKbhpLCYki4PRQlCVWkGAhCKLDlJWV4bvvvoPH48Hpp5+OoUOH4sYbb0ROTg5MJhNMJhNef/11/PjjjxgyZAhuuukm3H///VHfjlNOOQUej8fHqzJhwoSA+wDgwQcfxOeff47y8nKMHDky6ttCHP04JA8LTwkBlBaKJYIoGqx1TEAaGxuRnZ2NhoYGatNPJBTt7e3YtWsXevfujZSUlHhvDtGFoe9i9Dnv6e+xdncdnr74WFz36jp4RWD1P09FURZ9vnoxcvymCAtBEARBRACvEkqxmpFiNQOgSqFYQoKFIIikgHfR1bqo+78QRGfB0z92q0kWLJQSih1UJUQQRFLwwgsvoK2tTfOxvLy8Tt4aglCqhFKsZqTKgoUiLLGCBAtBEElBt27d4r0JBOGD28MsoDazCXYrS1iQYIkdlBIiCIIgiAjwSDUrZpOAFIsUYXFTSihWkGAhCIIgiAjweFWChSIsMYcEC0EQBEFEABcsJkFQmW5JsMQKEiwEQRAEEQFcsFhMJFg6AxIsBEEQBBEB6pRQKpU1xxwSLARBaCKKIv70pz8hLy8PgiAgJycHN954o67nTpgwIeyygiDg/fff7/B26uX222/HiBEjOu31OkJnfzZEZKhNt1QlFHuorJkgCE2WLFmChQsXYvny5ejTpw9MJhNSU1Ojtv7q6mrk5uZGbX3huPnmm3H99dcbek6vXr1w44036hZq0UL92VRWVqJ379746aefkkZwdRV8TbcUYYk1JFgIgtBkx44dKC0txYknnhiT9ZeUlMRkvcHgXXGTgc7+bAjjiKLoK1jksmaKsMQKSgkRBBHAZZddhuuvvx5VVVUQBAG9evUKSPM89dRT6NevH1JSUlBcXIzzzjvPZx1erxe33HIL8vLyUFJSgttvv93ncXXao7KyEoIg4N1338XEiRORlpaG4cOHY+XKlT7Pef7551FeXo60tDScc845eOihh5CTk6PrPfmnhC677DJMnz4dDzzwAEpLS5Gfn4/rrrsOLpcLAEtr7d69GzfddBMEQYAgCPJzv/32W4wbNw6pqakoLy/HDTfcgJaWFvnxXr164e6778bll1+OzMxM9OjRA88995z8uNPpxOzZs1FaWoqUlBT07NkT8+fP1/xsevfuDQAYOXIkBEHAhAkT8PXXX8NqtaKmpsbnPd54440YN26crs+D6Bhe1dhgs6CUNbc5SbDEChIsBNGJiKKIVldrXC5GBrM/+uijmDdvHrp3747q6mqsWbPG5/G1a9fihhtuwLx587BlyxYsWbIE48eP91lm0aJFSE9Px6pVq3Dfffdh3rx5+Pzzz0O+7r/+9S/cfPPNWL9+Pfr374+LLroIbrcbAPDdd9/h6quvxl/+8hesX78ep512Gu666y7d70mLr776Cjt27MBXX32FRYsWYeHChVi4cCEA4N1330X37t0xb948VFdXo7q6GgCLPE2ZMgXnnnsuNmzYgDfeeAPffvstZs+e7bPuBx98EKNHj8ZPP/2Ea6+9Ftdccw22bNkCAHjsscfw4Ycf4s0338SWLVuwePFi9OrVS3MbV69eDQD44osvUF1djXfffRfjx49Hnz598Morr8jLuVwuLF68GJdffnmHPhNCHx6VYjGpUkIOirDEDEoJEUQn0uZuw5hXx8TltVf9v1VIs6bpWjY7OxuZmZkwm82a6Ymqqiqkp6fjzDPPRGZmJnr27ImRI0f6LDNs2DDcdtttAIB+/frhiSeewLJly3DaaacFfd2bb74ZZ5xxBgDgjjvuwODBg7F9+3YMGDAAjz/+OKZOnYqbb74ZANC/f398//33+Oijj3S9Jy1yc3PxxBNPwGw2Y8CAATjjjDOwbNkyXHXVVcjLy4PZbEZmZqbPZzB//nxcfPHFcrSpX79+eOyxx3DKKafg6aefRkpKCgDg97//Pa699loAwN///nc8/PDD+Oqrr1BRUYGqqir069cPJ598MgRBQM+ePYNuY2FhIQAgPz/fZzuuuOIKvPTSS/jb3/4GAPjf//6H9vZ2XHDBBRF/HoR+1ILFYhJgt7Dzfwd1uo0ZFGEhCMIwp512Gnr27Ik+ffrgkksuweLFi9Ha2uqzzLBhw3z+Li0txcGDB0OuV/2c0tJSAJCfs2XLFhx//PE+y/v/bZTBgwfDbDYb2saff/4ZCxcu9JkWPXnyZHi9XuzatUvzvQiCgJKSEnndl112GdavX4+KigrccMMNWLp0qeFtv+yyy7B9+3b88MMPAICFCxfiggsuQHp6uuF1EcbxqCKWZhIsnQJFWAiiE0m1pGLV/1sVt9eOFpmZmVi3bh2WL1+OpUuX4tZbb8Xtt9+ONWvWyJ4Sq9Xq8xxBEOD1ht6Zq5/DPSPhntMRItnG5uZm/PnPf8YNN9wQ8FiPHj10rfvYY4/Frl278Omnn+KLL77ABRdcgEmTJuHtt9/Wve1FRUWYNm0aXnrpJfTu3Ruffvopli9frvv5RMdQR1jMJgE2yXTrJMESM0iwEEQnIgiC7rRMomOxWDBp0iRMmjQJt912G3JycvDll1/iD3/4Q0xer6KiIsBL4/93tLHZbPB4fD0Jxx57LDZt2oS+fft2aN1ZWVmYMWMGZsyYgfPOOw9TpkzBkSNHkJeXF7ANAAK2AwCuvPJKXHTRRejevTuOOeYYnHTSSR3aJkI/PoJFoAhLZ0CChSAIw3z00UfYuXMnxo8fj9zcXHzyySfwer2oqKiI2Wtef/31GD9+PB566CFMmzYNX375JT799FOf6p1o06tXL3z99de48MILYbfbUVBQgL///e844YQTMHv2bFx55ZVIT0/Hpk2b8Pnnn+OJJ57Qtd6HHnoIpaWlGDlyJEwmE9566y2UlJRoVjwVFRUhNTUVS5YsQffu3ZGSkoLs7GwAwOTJk5GVlYU777wT8+bNi+ZbJ8LABYsgMNMtbxznoMZxMYM8LARBGCYnJwfvvvsufve732HgwIF45pln8Nprr2Hw4MExe82TTjoJzzzzDB566CEMHz4cS5YswU033SSbXGPBvHnzUFlZiWOOOUY2vw4bNgwrVqzA1q1bMW7cOIwcORK33norysrKdK83MzMT9913H0aPHo3jjjsOlZWV+OSTT2AyBe6SLRYLHnvsMTz77LMoKyvD2WefLT9mMplw2WWXwePxYObMmR1/w4Ru5B4skmC285SQhyIssUIQjdQ6JiiNjY3Izs5GQ0MDsrKy4r05BCHT3t6OXbt2oXfv3jE9sHZVrrrqKmzevBnffPNNvDclblxxxRU4dOgQPvzww5DL0Xcxuuyrb8NJ93wJm8WErXdOxYqth3DpgtUYVJqFT/5CvXD0YuT4TSmhEIiiCJdHhFcUYbeYYhp6JggiPA888ABOO+00pKen49NPP8WiRYvw1FNPxXuz4kJDQwN++eUXvPrqq2HFChF9PB5lUjMAlYeFUkKxggRLCBxuLwb8ZwkAYOMdk5Fhp4+LIOLJ6tWrcd9996GpqQl9+vTBY489hiuvvBIAK1HevXu35vOeffZZXHzxxZ25qTHn7LPPxurVq3H11VeH7G1DxAZ58KHgK1goJRQ76AgcArNJiaioHeEEQcSHN998M+hjn3zyidxW35/i4uJYbVLcoBLm+CJ7WMzsOGHjERYafhgzSLCEwCyQYCGIZCFUt1iCiDbBTLdU1hw7qEooBCaTAB5kcceweRVBEASRXKgnNQOqlBAJlphBgiUM/MtIERaiI8SyWytB6IG+g9ElmGBxuD2GBo0S+jGcEvr6669x//3348cff0R1dTXee+89TJ8+Pejyy5cvx8SJEwPur66u9hnk9eSTT+L+++9HTU0Nhg8fjscff7zDc0KigdkkwOURSbAQEWGz2WAymbB//34UFhbCZrNRtRnRqYiiCKfTiUOHDsFkMsmdc4mOwU23Jr+UkFcE3F4RVjP9zqONYcHS0tKC4cOH4/LLLzfUgnvLli0+NdZFRUXy7TfeeANz5szBM888gzFjxuCRRx7B5MmTsWXLFp/l4oHFZALgJcFCRITJZELv3r1RXV2N/fv3x3tziC5MWloaevToodmcjjCOR4pYWSRhwjvdAszHYjXT5xxtDAuWqVOnYurUqYZfqKioSLPtNMDaVF911VWYNWsWAOCZZ57Bxx9/jAULFuAf//iH4deKJjzc5ybBQkSIzWZDjx494Ha7NefBEESsMZvNsFgsFN2LIrx6mZtubSqB4nR7AXs8turoptOqhEaMGAGHw4EhQ4bg9ttvl4d0OZ1O/Pjjj5g7d668rMlkwqRJk7By5crO2rygkIeFiAaCIMBqtQZM8CUIIjnx97CYTAKsZmYhoOZxsSHmMavS0lI888wzeOedd/DOO++gvLwcEyZMwLp16wAAhw8fhsfjCeiTUFxcjJqaGs11OhwONDY2+lxihRxh8ZBgIQiCIBj+ggVQlTZTL5aYEPMIS0VFhc8E1xNPPBE7duzAww8/jFdeeSWidc6fPx933HFHtDYxJLztspdc3wRBEISE3OnWR7CY0OygbrexIi6uoOOPPx7bt28HABQUFMBsNuPAgQM+yxw4cMCnikjN3Llz0dDQIF/27NkTs20lDwtBEAThDzfdqgULdbuNLXERLOvXr0dpaSkAZkgcNWoUli1bJj/u9XqxbNkyjB07VvP5drsdWVlZPpdYYZE9LPQFJAiCIBg8iGISfCMsAA1AjBWGU0LNzc1ydAQAdu3ahfXr1yMvLw89evTA3LlzsW/fPrz88ssAgEceeQS9e/fG4MGD0d7ejhdeeAFffvklli5dKq9jzpw5uPTSSzF69Ggcf/zxeOSRR9DS0iJXDcUTE3lYCIIgCD/ksmYNDwt1u40NhgXL2rVrfRrBzZkzBwBw6aWXYuHChaiurkZVVZX8uNPpxF//+lfs27cPaWlpGDZsGL744gufdcyYMQOHDh3CrbfeipqaGowYMQJLlixJiIFlcoSFPCwEQRCEhBxh0UoJkWCJCYYFy4QJE0K2HV64cKHP37fccgtuueWWsOudPXs2Zs+ebXRzYo5ZarJEZc0EQRAEh5/EWkyUEuosqBVfGCxkuiUIgiD80DLd8m63FGGJDSRYwsDDfR7ysBAEQSQNOw41478/7I5ZdFzudKtOCZlJsMSSTut0m6yQh4UgCCL5uHzhGuyubcWeI62Y+/uBUV+/HGERNBrHkWCJCRRhCQO15icIgkg+dte2AgCe/XpnTNavZbqVU0Iu8rDEAhIsYSAPC0EQRPKhTtU0tLmivn6tsmaeEqJOt7GBBEsYzNQ4jiAIIukoyUqRb3+1+WDU18+j7toRFjpexAISLGGg4YcEQRDJR4vTLd/edbgl6uvnhwStxnHkYYkNJFjCQMMPCYIgko9Wp+IjaWyPXUrIrNGanzrdxgYSLGGg4YcEQRDJhccr+oiGpnZ3iKUjfQ12rTn8kBrHxQQSLGGgKiGCIIjkotXpK1CaYhlhoZRQp0GCJQy8NT95WAiCIJIDdToIABrbYhdhMWm05qeUUGwgwRIG8rAQBEEkF/6CpcnRSWXNlBKKKSRYwkAeFoIgiOQiMCUUgwiLdBJr0jDdUkooNpBgCYOFPCwEQRBJRZt/hCWGplufsmYr87BQSig2kGAJg4n6sBAEQSQVLZJgyUu3AQAa21wQo5zW1zLd0vDD2EKCJQw0/JAgCCK5aJNSQkWZdgAspd8e5e6zWmXNcqdb8rDEBBIsYaDW/ARBEMkFN90WZNjB9US0S5u1y5qpNX8sIcESBhp+SBAEkVxwwZJuNyMzxQog+t1uQ5luafhhbCDBEgbuYfGQh4UgCCIp4FVCaTYLMlMsAIDGKBtveSGG5iwhirDEBBIsYaAIC0EQRHLBIyypNjOypAhLtCuFNKc1Ux+WmEKCJQy80y01jiMIgkgOeFlzus2sRFjaou1hYddaERYqa44NJFjCQBEWgiCI5EKJsFhkD0v0IywaZc3UOC6mkGAJg5k8LARBEElFi+xhMSNLirBEvUpIOiRoVQm5vWJSNxsVRTGgW3AiQIIlDNSanyAIIrngKaE0mxlZqZ0XYeF9WIDkTgs9+dV2DLr1M3y3/XC8N8UHEixhoOGHBEEQyUWrLFjUVULR9rAEljXzTrdA8hpvWxxuPLB0KwDgvz/sjvPW+EKCJQwUYSEIgkgu1BGWTDklFPuyZovZJB8zktXH8v76ffLtbCk6lSiQYAmDhTrdEgRBJBXcw+Jb1hyjCItKsACq5nFJKlg+3lAt365tccZxSwIhwRIGGn5IEASRXMgRFquq021blCMs0iHB4idYbEnei+WISqQcbnbEcUsCIcESBvKwEARBJBftLiYWUqzmGHpYAk23gBJhifawxc6i2aEIOxIsSQZvHEceFoIgiOTAJe2vrWZTzD0satMtoGrPn6QpoRaVYKltppRQUqF4WEiwEARBJANuqQ2t1SzIZc2xqhIKlhJKVg+LOsLS6vQkVD8WEixhIA8LQRBEcsH31xZVhKXZ4YY3iiee4Uy3yehhcbg9cPkd6w43JU6UhQRLGCjCQhAEkVy4JH+JxSTIVUKiqFQPOdwdjxwEi7DYk7g9f4tDEVml2SkAgEMJ5GMhwRIGuTU/mW4JgiCSAh4lsJpNsFtMckM37mO54NkfMPGB5R1KE/Fjgn+EJZlTQs3S55NiNaEoiwmWRDLekmAJAw0/JAiCSB5EUZnjYzULEATBp1KorsWJn/fU40CjA99sjbz1vNa0ZiC5Tbfcv5Jht6IwwwYgyQXL119/jWnTpqGsrAyCIOD9998Pufy7776L0047DYWFhcjKysLYsWPx2Wef+Sxz++23QxAEn8uAAQOMblpMMFHjOIIgiKRB7cGwSJEVdaXQzsMt8uO/VTdG/DpyWXNAlVDyelh4yizDbkZBhh1AkntYWlpaMHz4cDz55JO6lv/6669x2mmn4ZNPPsGPP/6IiRMnYtq0afjpp598lhs8eDCqq6vly7fffmt002KChUy3BEEQSYNbdXJpNbP9tzIA0YWdh5rlx9dV1UX8OkFNt1YWYUnmlFBGigX5UoSltiVxIiwWo0+YOnUqpk6dqnv5Rx55xOfvu+++Gx988AH+97//YeTIkcqGWCwoKSkxujkxx0yN4wiCIJIGnwiLyTfC0tjmG2FZv6cebo9XjsQYIWhZszl5Tbc8JZRus8hm5eYo96/pCJ3uYfF6vWhqakJeXp7P/du2bUNZWRn69OmDiy++GFVVVZ29aZpYqHEcQRBE0sB7sABKhCXTrkRYdh1SBEur04OtB5oRCcFMt3arJFiSsNOt4mGxIIOn0RxdWLA88MADaG5uxgUXXCDfN2bMGCxcuBBLlizB008/jV27dmHcuHFoamrSXIfD4UBjY6PPJVaYqayZIAgiaeAnl2YT80MCqghLuxs7D/sKlP31bRG9jjeo6VaqEvIkoYfFoaSEMuxS/5quGmF59dVXcccdd+DNN99EUVGRfP/UqVNx/vnnY9iwYZg8eTI++eQT1NfX480339Rcz/z585GdnS1fysvLY7bNZvKwEARBJA3cO6IWEtzDUt/qRGVtKwCgT0E6AKCuNTJTKffK+Lfml4cfJnGEJd2uSgl1xQjL66+/jiuvvBJvvvkmJk2aFHLZnJwc9O/fH9u3b9d8fO7cuWhoaJAve/bsicUmA6DhhwRBEMkEj7DYVL4UHmHZXNMEp9sLm8WEwd2yAQD1rZH1YpHLms1HUVlze2BKqMsJltdeew2zZs3Ca6+9hjPOOCPs8s3NzdixYwdKS0s1H7fb7cjKyvK5xAoz9WEhCIJIGriHRS0kMqVowYa9DQCAXvlpyE9nVTCRRliO7rJmJSUU7aGRHcFwlVBzc7NP5GPXrl1Yv3498vLy0KNHD8ydOxf79u3Dyy+/DIClgS699FI8+uijGDNmDGpqagAAqampyM5mCvfmm2/GtGnT0LNnT+zfvx+33XYbzGYzLrroomi8xw5BrfkJgiCSB5dqjhAnS4oWNLSxaErvgnTkpDERUxdxhCX0LKGkLGuWWvOnqwRLsyO6QyM7guEIy9q1azFy5Ei5JHnOnDkYOXIkbr31VgBAdXW1T4XPc889B7fbjeuuuw6lpaXy5S9/+Yu8zN69e3HRRRehoqICF1xwAfLz8/HDDz+gsLCwo++vwyjDD5Pvy0cQBNHV4N4Sq0pI9ClM91mmT2EGctNYhKU+4gjL0TdLqFkaVZBpt8hptHaXF64EOf4ZjrBMmDABYgg/x8KFC33+Xr58edh1vv7660Y3o9OgCAtBEETyoBVhGVyWDZvZBKd04O1TkC6bYyNOCfGy5oCUUPJ6WFpUEZZ0u0V1vxs5ksCLJzRLKAw0/JAgCCJ50PKwpFjNGNJN8Tr2KUxHXjqPsESW8vAGMd0m9fBDuUrIDKvZhBSr79DIeEOCJQy8cRxFWAiCIBIfeVKzyffwNrBUJVgKlJTQkZaOlTUfTaZbLlh4OijDnlilzSRYwsC/81QlRBAEkfi4uIfF4iskjinMkG/npttk0219qyukzUELURTBDwnmYJ1ukzDC0ipVCaXZmGDJTLDSZsMelq4Gj7CIIuD1igGOcIIgCCJx4E0+LX4RlouO74FVu2oxpnc+AMgRFqfHi1anx8ezEQ51xD1AsFiSd/hhq1PysNh4hCWxut2SYAmD+svoEUWYQIKFIAgiUeEeFquftyTVZsazl4yW/06zmWUjbl2r05hgUUVk/E9iuYel3ZVcKSGvV5QFS6qNiS4uWBrbE6O0mVJCYVCXrJGPhSAIIrFxebUjLP4IguCTFjKC+ljgX9ackqRVQu0qz00aFywJlhIiwRIGdYSFfCwEQRCJjVaVUDB4WshoabNasPiXNfPKmmSLsPDoCgCkWplgyUywlBAJljD4pIRoACJBEERCwz0sVnP4w1uk3W69quBJQIRFOti3J9nwwzZJsKRYTXKaiyIsSYa6ZI16sRAEQSQ2vDmcv5DQgguWxjZjgsWtUizBqoTa3R7D1UfxhEdYeIUQgISbJ0SCJQwmkwD+fVR/SQmCIIjEQzbdWsIf3nifEaMHZKXLLfPCqOERFlFUxFMywEuaeToIoAhLUkLN4wiCIJID7jW06oiw8D4jTQarYPixwD+6AiimWyC50kJtcoRF2X7ysCQhcvM48rAQBEEkNFqzhIKRFWEEQZ7ULAQKFqtZico7ksh426ohWCjCkoRQhIUgCCI5CNaHRYuMlMg8GsEmNQMsRcSbxyVThKXV5duDBVD8LC1OEixJAw1AJAiCSA709mEBgMyUCD0sPMISJO2UojLeJgttfm35AcV020IRluSBq2iKsBAEQSQ2RvqwKFUwBsuaxeARFkBd2pw8gsW/yy2gpIdaHInxPkiw6IBHWFxJ5PgmCILoirjklJCeCEtkHg13CNMtkJy9WJQ5QioPi51SQkkHV5ltzsRQmQRBEIQ2sunWUJVQZCmhYILFnoTzhNo0+rCkSYKllSIsyYNszEqQPB5BEAShDe+XpS/CwjwskVYJmTWqhICjJyWUIYkXp8ebENOnSbDoINFGbBMEQRDaKK35jXlYjHSl1W+6jf9BXi9tLsl0q2ocl2ZXbrcmQFqIBIsOeDfERKlFJwiCILQx0oeFp4RcHtHQdOVQZc3A0RNhsZpNsEnprUQ4/pFg0YFszKIIC0EQRELDU0J6PCzpNgt4VseIjyVshEXqw5KcjeMsPvdzE25rAng4SbDoQA4bJoDCJAiCIIJjZFqzySTIPg0jEQRP2LJmbrpNopSQRqdbAEi3J063WxIsOsigCAtBEERS4DTQhwVQd7vV34slVGt+IFlTQtLwQ3/BYkucSiESLDqQTbcOY82FCIIgiM5Fbs2vo9MtEFnKX/awBBFFXLAY8cXEG61ZQgCQLhlvKcKSJETaXIggCILoXORpzRadERbphLQxAsESrKzZbk2+PizBBYsUYaEqoeRAKX2L/z+MIAiCCA7vdKtnlhAQWS8WvabbZJolJFcJWf1Nt4kzT4gEiw4yEsh0RBAEQQTHSB8WoGMelvBlzcmTElKGH/pGWHgvlhaqEkoOIp3oSRAEQXQuRqY1A0BWJB4WMZzpNrlSQqIoolXaVnWzOCCxJjaTYNEB9WEhCIJIDoxMawYia1uh13SbLBGWdpcXvNGvfx+WNDklFH/xRYJFB5QSIgiCSA6MTGsGIoughy9rZq/tSBIPS0MbS4dZTILPtGYAyOApoQQ4/pFg0UGGqkrI69U/b4IgCILoXNwGpjUDvvOE9BLOw2K3JFcflvo2JwAgO9UKwU+EyREWqhJKDvgXGkiMfxpBEAShjYtPa7YY7MMSQUrIfJR0um1oZWItO80a8Bh5WJIMu8UkO84pLUQQBJG4yFVCBhvHGUoJhTPdJl2ERRIsqYGChaqEkgxBEBQfCxlvCYIgEhZlWrO+lJDiYYkgJRTkNezW5OrDwj0sORqCJZ0iLMmHXKufAP80giAIQhs+rVlvH5aOtOYPX9acZCkhDcGSIXe6jb/4MixYvv76a0ybNg1lZWUQBAHvv/9+2OcsX74cxx57LOx2O/r27YuFCxcGLPPkk0+iV69eSElJwZgxY7B69WqjmxZTMuxSN0SKsBAEQSQsiulW3+Etkk7m+hvHxf8grwc5wpJmC3iMN5JLBDuEYcHS0tKC4cOH48knn9S1/K5du3DGGWdg4sSJWL9+PW688UZceeWV+Oyzz+Rl3njjDcyZMwe33XYb1q1bh+HDh2Py5Mk4ePCg0c2LGVyFNxoIGxIEQRCdi9FpzXJrfqf+KtCwrfn58MMkibDwKqGsUBGWBBAslvCL+DJ16lRMnTpV9/LPPPMMevfujQcffBAAMHDgQHz77bd4+OGHMXnyZADAQw89hKuuugqzZs2Sn/Pxxx9jwYIF+Mc//mF0E2NCruSermslwUIQBJGouA33YWGHQVFkVaBcwISCm26DRVhSJcHi9Hjh8YpBq4kShYY2Jka0PCxKWbMHXq8YVKR1BjH3sKxcuRKTJk3yuW/y5MlYuXIlAMDpdOLHH3/0WcZkMmHSpEnyMolArhQqq29xxnlLCIIgCC28XhE8SKJXsERSBerxhC5rVs/jaUuCtFB9q9KHxR91W494v5eYC5aamhoUFxf73FdcXIzGxka0tbXh8OHD8Hg8msvU1NRortPhcKCxsdHnEmt4bo8iLARBEIkJ78EC6E8JqatA9fpYwpU12y0m8Idak6B3V6PsYQkULClWE7gui3elUFJWCc2fPx/Z2dnypby8POavqaSEKMJCEASRiHDDLaC/DwtgvD1/ONOtIAhyWqjdmfg+llB9WARBQLoqLRRPYi5YSkpKcODAAZ/7Dhw4gKysLKSmpqKgoABms1lzmZKSEs11zp07Fw0NDfJlz549Mdt+Tm46j7CQYCEIgkhE1IJFb4QFMN6eP5zpFlB8LK2uxI+wNISIsACq5nFHe4Rl7NixWLZsmc99n3/+OcaOHQsAsNlsGDVqlM8yXq8Xy5Ytk5fxx263Iysry+cSa3IpJUQQBJHQ+KSEDJhDjbbnD2e6BYBUycfSlgD9S0Lh9YqyYNGqEgISp3mcYcHS3NyM9evXY/369QBY2fL69etRVVUFgEU/Zs6cKS9/9dVXY+fOnbjllluwefNmPPXUU3jzzTdx0003ycvMmTMHzz//PBYtWoTffvsN11xzDVpaWuSqoUSAp4TqKcJCEASRkPBJzRaTEDDELxRG2/Nz062eCEuiC5YmhxuS/tJMCQFQpYTiK1gMlzWvXbsWEydOlP+eM2cOAODSSy/FwoULUV1dLYsXAOjduzc+/vhj3HTTTXj00UfRvXt3vPDCC3JJMwDMmDEDhw4dwq233oqamhqMGDECS5YsCTDixhNuuj1CVUIEQRAJidtgW36O3IvFoOk2VISFVwrFu7ImHPwkPNVqlqdM+5Nu583j4vteDAuWCRMmQBSDN9fR6mI7YcIE/PTTTyHXO3v2bMyePdvo5nQaeZKHpandDbfHC4vOkjmCIAiic3AZ7MHCidTDYg4RxeEpoURoaR+KPUfaAAClOSlBl+ERlng3j6Ojrk6yU61ymRp3VBMEQRCJg1sSEkYFS6bBWXFGTLeJnhLacagZANC3MCPoMtzDEu/2/CRYdGI2CchKIR8LQRBEoqL2sBghw6iHJUxZM6B0iE30lND2g0ywHFMUSrAkRrSIBIsBuPH2SAtFWAiCIBIN7mExHmEx6GHREWHh84TifZAPB4+wHBMqwmJL0iqhrgz1YiEIgkhc3F5jgw85mdzD4tDpYTmKTLeKYEkPukyaPTGqhEiwGECeJ0SChSAIIuFwusMLCS3kPixGIyw6TLdtCdyav6ndhQONDgChU0IZcuM4SgklDVyw1FJpM0EQRMLBIyyRVwlFz8Mim24TOMKy41ALAKAo0y57NLVIo5RQ8lGYaQcAHG4iwUIQBJFodNTDYrRKKNi0ZiA5ypr31bGS5p75aSGXy6CUUPLBBcuhZkect4QgCILwR64SMtw4LvqzhLiHpT2BIyyHmtoBKMe2YPD3QimhJEIWLNI/mSAIgkgc5D4sBiY1A4pgaXd5ZdETCq8O020yVAnxk+/CjNCCJSNZZwl1Zfg/9VATRVgIgiASjUgjLLwxGqDPeOvWYbpNS4Lhh/xYFjbCIn0+8RZfJFgMoERYSLAQBEEkGsosIWOHNqvZJJtk9RhvZdNtCGGUDGXNegVLhjxLiCIsSQP/pza2uxM6L0kQBNEVkauEDJY1A+r2/OF9LHrKmpMhJXS4mRWQhPew8AhLkk1r7spkpVhgs5jgdHtxuNmB7rmhndUEQRBE5+GMcFozwNrzH2xyGIqwhKoSklvzJ7BgkSMsGcEHHwJs+O+8swcj3WaBKIoQQgi1WEKCxQCCIKAww4599W041ESChSAIIpFwRzitGTDWnv9o6MPi9Yo43KwvJZRiNWPm2F6dsFWhoZSQQcjHQhAEkZhE2ocFMNaen7fmT2bTbX2bSzYP52fY4rw1+iDBYhDqxUIQBJGYuLyRTWsGjLXn9+ow3aaoIix8+USCn3TnpdsiEnjxgFJCBqEIC0EQRGISaZUQoPQaaYxyWTMAONxepDZXASufBLLKgGNnAukFhrcxmij+ldDpoESCBItBqBcLQRBEYqJ4WCKJsEgeFh2lu4qHJbgw4hEWgFXXpC67A/j1PXbHoS3AH541vI3R5FCzvi63iURyxIESCIqwEARBJCYuHUIiGBkG2vMrrfmDL2M2CbBb2AKtra3Ats+VB7d9Bnjj622pa2HvMyct+NDDRIMEi0HIw0IQBJGYuNyRR1iyDHhYuOnWHKa8l6eZhMqvAWczkF4E2LOAtjpg3zrD2xhNePVSui15Ei0kWAxCERYdiCLw8c3AJ7ew2wRBEJ2APEuoAx6WaHW6BYA0qUOsffun7I6B04Bjfsdub/88yLM6B94ELlXltUl0SLAYRO1hEelgrM2RncCa54HVzwL1VfHemqMDjxv45W3gyK54bwlBJCyRzhICFA9LkwEPSyjTLaBELzKqv2d39J8M9DuN3d7xpeFtjCZtTvZZkWA5iuERFofbq+uL3SXZu0a5vT++Yc+jAlEEPp4DvHMFsGAyCycTBBFAR/qwKB4WA2XNYbwy6XYLilCH1KbdgGACepwA9BjLHqzeALidhrczWrS52PtMs5JgOWpJsZrlev2jNi3kbAGcrZE/f+9a5Xac87TJhCiKeOWH3Xjvp72+D2z6AFi3iN1uPgB8fmvnbxwRH0QRWHE/8MTxLHJJhCQqfVh0NI5z6zDdAkywHG/azP4oHgKkZAN5fYDUXMDjAA5sNLyd0YLPOKIIy1HOUe1jcTuAZ08B7j+G9QyIJO3lE2H5KXrbdpTz1ZaD+M/7G3HTGz/7llZu/Yxdlx3Lrn/6L9CwN3AFxNHHD08DX90JHN4CrH0p3luj0FgNvDULWDAFeOpE4J0rgYO/xXurOtSHJdOAh8Ur6oyw2MyKYOl5ErsWBKDbKHZ734+GtzNakGDpIhzVvVg2fQDUbgNcrcBn/wQ+/bsx0eJq8z1r2L8ekM56iOB4vCLu/XSL/Pe2A03Kg5Xfsuvf/RvoNQ4QvYl18CJix3ePKLe3fBq3zQjgi9uBX98FqlYCB38FfnkLeOE0dsITR+RpzR3pw9LuDutPdMvDD0OvM91uwXEm6Xfdc6zyQAIIlnapSiiNBMvRzVEdYVnzArtOLwQgMOPspvf1P7/6Z8DrZs+3pALOJqCOjKLh2LS/EVtUImXbgWZ2o2430FAFmCxA+RjguCvZ/T8uBFqPdP6GEp1H80GWAuTUbgMObdVe1uNiqaPHRwNblsR2uw5vB355k90+4yHgojeU33qcI39Od8f7sLi9ItpdoU+y9Jpuc6we9BOkz6T7ccoD3Uaza3U0upORIyxWKms+quGC5aBewXJ4G1C7I4ZbFCXqdgN7VrGD49XfASf9hd2/7mX96+D+le7HA1ml7HZTTXS38yjksF9fH1m88OhK2bGAPQMYcAaQdwzQepiZcONo2iNiTM0v7Dq/L9B3Eru9+SPtZZf8g6WOarcB7/2ZpWxixZrnWZSv32TguCuAiilATjl7LM6CpSMRlnSbGVx/hBuAqKfTLQD0cFfCInjRYskBMkuVB7qPBiAAtduZMI0DXLBQhOUox1CE5df3gadOAB4fxdIriZwe4TvIokFAZjEw6jL2946vgIZ9+tbBzxi6j5aiNGAHVyIktS2+wmMrFyz88+ThZLMVuOBldka740tg8XlAS23cdnpEDOGp1ZKhTKgCwOaPA5drrAZ+XKT83V4PLL87dtvFPVXHzlTuy+7OruMtWDpQJSQIgu5eLHo63QJAD8c2AMDelH6AOhqTlgcUD2a3d39veFujQRv1YekayB6WcN1uN7wJvD2LpUggAqueATa9F/sNjJSDm9g1/yHl9QZ6ngxAVGZghIPnZLuPBtKk4V4th6K6mUmLozloRKROEiw989MAAFtqJMFyWEoBFA1WFi4ZAly4GLBlALtWAA/2Bx7oR436jjb4CUTxEKDi9+z2vrWB0ZPVzwJeFyuXvfhtdt/OFbHZptodLMVrsgJ9TlHuTxDB0pE+LACQpfKxhEKv6ba0lf1+K639Ah/seSK73v2dwa2MDkpKiATLUU3YCMvhbcD//gK8+ycWOh3xR2D8LeyxL+9i+WYg8aItB35l10WDlPv6nsqu9ZjDmmqAhj0ABKBsJJCez+5vqY3qZiYlVT8ADw0CXjxN8+EjrUywHN8rDwBLN9a1OIFDUoVBYYXvE/qeClz+GZDfTxLEYAeulU/EZPOJOFCjirBkligeiC2fKMt4PcBPi9ntsbOZz0kwAfW7gcb90d8mPg+nxwmAPVO5P5unhPZE/zUN4O7ALCFAf7dbvWXNhc3s97vd3CfwQV41FK8IC5luuwYhBcvKp4AnRjNTJERgzNXAWY8DJ93AIg5HdgB3lQLPjAPm5QHP/w7Ys7pTtz8ocoRFJVjKRrDr6p/DP5/7V4oGsp0ZpYQYDXtZwzdHA1C9XnMRHmEpz0uTv181NfuAVknsFWicoZUMAa7+FvjzN8Ck29l9X90dW/8C0Tm4nUp0jUc8B5zJrn95W1muaiXQchBIyWFdVFOyWEQGYCI52vB28v38hHdWN3Yd95RQ5B4WQF8vFq9XlAOZIYWR14PsJpYS2oxegY/3PAmAwFJ/dbsj2t4AanewUvi6Sva32wF8fhuzJvjRJntYyHR7VMMPKEdaHHIuEwBwYJPS1KvvJGDWp8DUe5kMt2cCZz/Bzn68LqBmAwCRRS7e+GPcywHhaleMwT7ph+Hs+sgOoL0h9DrU6SBAlRLq4oJl5ZNhFzkiCZbcdBuKs9j3q3WfFPHK7gHY0rWfaE0BSocBJ93Izq5drawrrqstGltOxIv63YDoAazpihgYej7bf1R9r/xW+YFowJnM3wQonVSrVkZ3m1xtigm8r59gSZiUUOR9WAClUqgxRITFo0q7hhx+WFcJs9eBNtGGXe5CjRcrBPpMYLd/eiWSzfWlsRp46ffMgP3oCHby/L+/sNL4ty71WdTp9spRIkoJHeXkp9thEgCvCNS2qITG57cyMVLxe5ZL5jlKTsVU4A/PA73HA2c8CFy3mu2Mmg8AP7/euW/Cn8Nb2A4yNZeFnznp+Uq4l+fUg8EFC+8xkN7FPCy/vA28PJ0JUD7zp60+sMpKw2dSJ6WE8tJsKMpMAQB4D0r9Gwr7h39tQQAm3w0IZpYymF8OLDwz/kKYiAwuSPL7KGbN7G7K4Lyf/su6UfOWA4POVp7b4wR2re44HQ0qvwXc7WyfVTTQ9zG1YImjj4p7WKwRdLoFfHuxBEN9khoyJXSI/X53iqVocgX5TLhx+af/MqtA80Hgu0eB5gj2mR9cBzTzikwR+Gwu8PNrmovy6ApAptujHrNJQF66X1qo5bAyzOq0//N1hKsZeh5w6f9YP43CCmDsdez+lU/E1zB5mIUuUTggcNtLpShLqLSQ16t0tfUXLK1dwMOyZzUrM975FfDb/4DnTgE2vgu8fw0bK5+hEoFioHdJibBYUSRF8CxHVP8TPXQfDfzxHfZaXhdQ+U38hTARGbXb2XV+X9/7+QFu9XPA5/9hJwM5PZQzdUARE7U7ortP4f6VvpMC9xE8CuRui2t/IHlasyWyQ1umjnlCasESMiUk+c+2id3Q4vBoLzPgTJY6b6oGvrqLmec/v1Xph6WX5kPK8ee6NcD4v/k+nprn8yf3r1hMAmwRflbxIKItffLJJ9GrVy+kpKRgzJgxWL06uAdjwoQJEAQh4HLGGWfIy1x22WUBj0+ZMiWSTes0Anwsv33IIhSlw4GCviGe6cfIS5jj/vBWZScVD/gZXd4xgY+VjmDX+9eHeP52wNHIym0LpR1mV0kJiSLw2b/Y7YozWA+a9gZWIbblE8CSwnxMHG/gzquuleXM89PtsmBJa5KiNP4HrVAcMxG4aaPSQ+fbh9mkZyK5CCZYBkxj3y9ns3JQm/hvwGJTlsntxa4dDdEblCmKwFap066/fwVgqUl+UGyOX98luUoo0giLbLoN7mFRp4T0RFi2ebujJdigXIsNOP1Odvvbh5X7jR4Lti0FILLjT2F/1hV7zmbgEqm6U/Td57QmYUkzEIFgeeONNzBnzhzcdtttWLduHYYPH47Jkyfj4EHtPhDvvvsuqqur5cvGjRthNptx/vnn+yw3ZcoUn+Vee007lJUoBAiWje+y68F/MLailCygl+QW5/0N4sERVQjaHz0RFp4OKhsBmCUTlzrCkmgVUdFkzypg72rAmsZSfZd9DJxwLRt0VjgAmPFf37bcfjsPj1dEfasqwpLFUkJZ7VKVBz8A6cVsBU75OzuA1O0Cdi2P8I0RcSOYYDGZgGmPsO8aAAw+h3lb1FhTlYhHtAYm7lkF1FexUvpjTtVexsK+t3IVZBzoSB8WQG26dQP1e1jlpF+Uyqs3wnKYCZbtYje0uTy+fkc1w2YAg6b73peSbWzDeeVY/6nKfVmlyr7D6y9Ykq+kGYhAsDz00EO46qqrMGvWLAwaNAjPPPMM0tLSsGDBAs3l8/LyUFJSIl8+//xzpKWlBQgWu93us1xubm5k76iT8OnF0lSjmNEGn2N8Zf2laNK2OAqWkBEWSbAc3somOWvh718BlAiL6GHNrI5WNr7DrgedzXYSFhswZT7wjyrgulXsjFRQ7Rj8UkKNbS7wfVlumk2KsIjIc0lnqrk9jW+TLR0YdBa7nUgzaAh9cKGh9XssHgzc9Cvw90rg/IXap/l5fXzX01E2SK34B04DbGnay5ikExWNCGJnwTvdRtqHhZU1i5i053Hg0eHA0yeyVgQqM7Fb7WEJ9jJerzxGYZvIxCOPagQgCOz/OHcfi4wAgMdAB2uvB9i5nN2u8MtMyP8T39dOxpJmwKBgcTqd+PHHHzFp0iRlBSYTJk2ahJUr9TnSX3zxRVx44YVIT/eteli+fDmKiopQUVGBa665BrW1ie178ImwbPoAgMj6JERycOl3Orve/X30QrhGkXeQGhGWzGLJgyEGN97ukwx+3Y5V7rPYALt0pnC0poW8HqVSI1R0TVD91Px26LwHS2aKBVazCUVZKShEA+xwsudx07NReLOxLUuooVwy4WwBGqXO0vkaggVgnVJTQ5zU8TPraAiWtnpFlPtHc9SYpIOfN34pSLlKKMI+LJkpVpxm+hGT6t9kJ1omK+s2vegsNkMJSoTFbGL2BU0a9wGuFogmK/YKzL/W6gwh5ASBjd4wS6k9I5/hkV0sRWhJBUqG+T4WRES2yZOak6ekGTAoWA4fPgyPx4Pi4mKf+4uLi1FTEz5vuXr1amzcuBFXXnmlz/1TpkzByy+/jGXLluHee+/FihUrMHXqVHg82v9gh8OBxsZGn0tn4yNYIk0HcfKPYc3avG5g8yfhl482bXVAm2SU0xIsQOh+LK52pckVH+rF4c3jjtZeLLtWsD4Yqbm+xkd/TOoIi+/3mvdgyUtnO6viLDvKBZZiFbPKlHJVo/Qez3ZijXv19dEhEgMuMlLzmDCJhGhGWL59iEVICyrCfMe1z+Y7kw73YbGJmGt5lf1x8k3ADeuYqfnIDhZt2f6FMqk5ZEkz858JuT2RYmO/6+ZgPhY1XLAYibDwEQ5FA333M0DQ/0kyzhECOrlK6MUXX8TQoUNx/PHH+9x/4YUX4qyzzsLQoUMxffp0fPTRR1izZg2WL1+uuZ758+cjOztbvpSXR3gG2gG4YGmvP8DyuwAweHrkK+SpJL0t8KNJrbRTyyhhKl8LnhbilUBqDmxkVSlpBezHrYY3jztaZ938uJBdDznX1/jojzol5Ofn4RVCOWns+QUZdpSbWFmjO7MD321rKtBfit4tvyfy9RCdSzD/ihFkwRLhpPS2euD9a4EXT2dltgBw2rzAA6KaBBAsHe3D0r3uB/Qx1aBeyALG/ZXtz2Z9yoaPehzA9mX65ghxoZjbG+mSkbc1WKWQGv4ZGvEB+Y9U0VofRJ/9TptLMt3q9bB4vcCXd7Ly6zi2SjD0Xy0oKIDZbMaBAwd87j9w4ABKSkqCPIvR0tKC119/HVdccUXY1+nTpw8KCgqwfbu2U3ru3LloaGiQL3v2dH47aO5h6dm4BoDIuktmlUW+Qm662vlV5x/cZcNtkPAzoPR2+O2jwLSV2r/if9bBe7o0+35njgqaDijD6EbNCr2seu/mF2FpkXLbWZLhz2o2ob+NRbxa0rp1bBsn/pvttLZ+Cmz7omPrIjoHWbCE+D2Go6MRluX3AOsXSydjAnD8n1gn3VAkgmDpwLRmACjZy34jnwsnKaMHsrsr/W+8blmwhIywcKGYpwiWcBOg2Up5hMWAYOEjVXiHYzVqgan6v8imW70RlsZ9wNf3s0Z0QvyiMoYEi81mw6hRo7Bs2TL5Pq/Xi2XLlmHs2LEhngm89dZbcDgc+OMf/xj2dfbu3Yva2lqUlpZqPm6325GVleVz6Wx4hGVIu3SwPmZiB1fYn6VTvG7gy//r4NYZRDbcBkkHAUDvCawDrrMJWPWc72N8eFf30f7PUvqPNMWv1DFmrHqa/b+6H8fa5IeD/9D9TLdajv0+VubhqrN1QAQD7Hs15mp2e8U9wb0smz9m3TF5rw0ifvCIZ4cES2923Xo4eIdqtxN4/WLg2VOA5fcq34263cDaF9nt0VcA1/8I/P7+4L2lOLKHJT6mW4+qZb41Eg+L14PsqqUAgE9co3wfU3lBdPV6UUVY+HyicAMVASjpX68RwSKlhNQjVTgmlUdFJVjajKaEpBQXcnooVaBxwPB/dc6cOXj++eexaNEi/Pbbb7jmmmvQ0tKCWbPYGebMmTMxd+7cgOe9+OKLmD59OvLz833ub25uxt/+9jf88MMPqKysxLJly3D22Wejb9++mDw5jKKPI4VSJccYcQO7o08HBQsATL6LXa97JXxX2WiiJ8JiMgHj/8pu//AU4JCmCXvcwI7l7DY/C1GTKfmdjjbB0rifzewAgJPn6HsON94GNcApO49ygaWEaq2hI5e6OPEGwGxn5kFezaam9Qjw4fVsp/T+NXFt/NUhmg+xs8DPbws6FTspiEZKyJ4JpBex28HSQluXAJs/YvOtlt+tRErXLmAeit7jgTMf0i+c5IN6fMqaeQ8WIMIqoT2rYG4/gjoxA9+4+qPdpfqdqgzFSq+XEIfPOiXCoqcZnYxRD4ujSZkbVKSREhK0IyyGBQv/DuX21rd8jDAsWGbMmIEHHngAt956K0aMGIH169djyZIlshG3qqoK1dW+w9e2bNmCb7/9VjMdZDabsWHDBpx11lno378/rrjiCowaNQrffPMN7HZ7hG8r9mSlWHCM5RDKhCMQTbbANvyR0OMEYOBZAETFG6GHqlXh5/yEIlRJs5pB09lOtL0eWCOdge1byxpUpeayCc3+ZEpRslg0k/J6gTdnAu9cGX7ZaLN8PmtTXn4CG7mgB77T80sJtWuUGBZ5mWA5IGjMIDFKZjEwUopsak1zXnGf0o245RDwxW0df83OxusBFp7B8uzfPQJseCPeWxQ50RAsQPi0kH/b9p9fZ1GWTR+wv8OlOf2Jc0pIXW4cUR8WafbS997BcMOChjaV8FL9dnmvF1swUSSKwJFKdjuvD7J4u389plvZw6LzMzwoTXPPLFUKHLTWB/imhKR9TopeD4tKgMWTiJxJs2fPxu7du+FwOLBq1SqMGTNGfmz58uVYuHChz/IVFRUQRRGnnRbYITE1NRWfffYZDh48CKfTicrKSjz33HMBlUiJhiAIOCGVNfZqza1gBsdoMFraSfzyNqu+Ccf614AFp7OhV85W468nivoiLAD70Y6Toiwrn2Cvt13yRRzzO21DXgaPsMTAw1LzM9u5/vKWvs8qWhzawsxnAHDaHeFD5RxBO2TOU0LyzkMUkeNhVVV7vVHqR3TCNex662esAZiarUvYNe+O+9Pi6PXv6Cz2/Sg36gLgO79JFFnUsvK7zt8ufzxuYMlcRfD703okfMWeXvjBRet/2XRA6o4KYPJ8dr3xbWDfOnZwsqQo7Rb0Em/Boo6wRNLpVpq9tMXCRmHw+V4AfH67Th5hCSaKWg6z1DkEIKenKsJixMOiM8Iip4M0oiuAX3Wi8vnwkyTdpttkjbAQCsOszOxbl1URvZX2PgXI6s6iGLwVdjAczWyeCMC+uEv+Yfz12uqU6IyeL+PQ84GcnuxMfNUzyoE72M6Nm26bqrUf7wj71im3O2snKYrAZ/9kP/6KMxQzsh7kszRfD0ub/87D0QiblwmwKmeU/FkF/dh3yz9611QjnT0JLLXV9zQWAfr6wei8bmfBm+P1GscOnHtXs+np/LEPZwOvzgDaO78Fgg8b32Yp1Y/naJ9Fc3GRWRZ8QrdeQlUKffOA5L86HhjzZ3aG3lYHvCCldY85NXjFYDDMis8jHvAKIYD1SDGEKMqCZVcKGy1S36qOsKg8LOFKp3mKJqsMsKbIHhZ9KSGDHhZuuC3S8K8A7GRKUNJZHIebvQe7pQtEWAhGBSoBAPtT+kVvpSYzMExqzsRDs8H48SXfScg/vcIMc0bg6aCsbsE7WKoxW1l/AgBYdgcTItnlwTv88pRQ25Ho+wqq1yu3xU7aSf7yNosqmW0sumIE7mHxFyz++eRGJu4axDQcaIviT/Q4KSW77mXlfyGFwVE8BEjNAcZJfpzfPoxri3XD8CjRsZcqnaN/eYsdiL59iP3tbIp/qkjdtoAf2NREo0KIEywldOBX5lMBWGdVk5kNbFXDvytGiHOExaUSEkEbugWjYQ/rp2Sy4HAmi7DUqyMsPh6WMO3/G6SqVanhI58A3WhEsOj97YWqEOJo/F8cLkmwWHXsX/xSXPGEBEsH6OViB/tdlij/EwdKLdW3Lg2d6vjlLXZ9xkOsoZPoZVNcjcDTQUa+iCP+H1DQX/n7lFsASxC/UWquEuaMdmmzuhlaZ5zVOZqBpdKQw/G3sKiFEYKZbv3zyU0s1Vgj5qG2JYoir+L3TEC2HGKCBAB2S4KFzzoqHwOk5bNBllU/RO+19eJxM0OzERqrWS8KwQT0PRUYIjVw/PU9VsG2d42y7Orn49f1t/mQbxXWod8Cl4mWfwXQTgkd3g68cg47ePWfAvQ5hd0/7HzmWbGmAdOfYZ+jUSIVLK524K1Z7H/TAdwd6XIrRVdQPBhpaSyypBlhET2q0ukgr8O7FGezlgQ+84nCYTIgWEQROMgFS5CUEKAtWNxsn2PXM6m59QjzKQLG55pFGRIskdJ6BDku1i9ls9gjzMIGKRvJ0kKuFmCHUkKOPatZLw2vl+14qn9mX8ZB04ETrmPLrH4eWPkkcPA3JnhWPatU9Gihp6TZH4sduPILYPrTwJmPACNClKoLQmxKm90OJeQPdI5gWfkEE125vRS/hxGCmG6VrpPSjkX6nA6IuahtjqJgMVuBUZex22teZDs8PoOEp7ZMZpYWAhSPQzBqd8jRoKix/G7goYHMAKoXPhaiaDDrDNtvMuvwW7cLeOsy9tiQ8wAIzOcSryaGe37w/d8f2hy4TFQFi/Sbbq5h6Z66SmDRNPYdLh7Cfr9qpj3C5hONuCiy14tUsHz3KPDru8AnN0f2uhJOqTO6rqiBPzxSUTYS2WlMNNSpBYvqZMPlDjOvqEESLFm+giXqHpbGfSydb7L4nkD6o1FubiglxCOBmaXR82pGCAmWSJG+4FXeQuxtjXJduiAog+s+vJ5Vcbx3NRvCtfhclmf+ShpJ3mcic4f3nQQMOJN1Y/zsn8BTJwCvng98ekvoLqd6Dbf+pGSzSMvoWWFaPkIpbY5mpVD1z7553o6GoeurlJ4UWsLK2QJ8L1XYTLo9dFfbYAQx3coGOJv0OTYqEZYj0YywAMCxM9l2VH0PrFvEDuCWVN8JvP10CJa9a4EnxzDDdzQncX8jeWfe+3Nooa2Ge5m6SVVq9gylwy9Pmf7uX0CO1DWYf+c7G//I0UEtwRLh71GL1FygkPkxsGUJ8M5VLHpXOACY+YF22/9gkVI9RNqHJVzqOxQ1G4H/ngfsX492Kc2RoteXoeYwG1SIgv7IlTpO17epU0IafViCRlikQYnZ3QHAYFmzAdHHvz/5/ULvjzRmPDllwaJDAjRIJn3/LuZxgARLpEhnR1vF7myeULQZ91fWDr+1FvjqLqUE0ZLK2uPzXPhxUkmvyQRc8Aow9X42AMuuMmtu+iB4GFxvSXNH4MZbo6H+UPDIAKcjHhZRBF75g6onxfzAZX77iHkgcnsFjoLXS5AIi9yHxcojLCxqcQC5aHa4fftBdJSsMmDAGez2/6Qo0eBzmH+F0/dUdkZ5aLO2J8rVBrx9OROM9VW+1Tkdwb+D8poX9D1Pa1L4qbexAzMADLuQRRt41IJHMTobnirg5vZDfp+bKKoESxQiLACbrgwA71/NjMi2DOCP7wDpBdFZv5pIIizqtEYkrHkB2P45sOEN+XeSEkmEhX8nCvojJ5VFWBp8UkKBfViCmm4DIixsfVGPsMjbHOa7ojEAkaeEbLoEi+/7iSckWCJFUuTbxW6xESzpBWyGxel3ASMuBsbOBi79H/CX9ayhk9kGnPW47zhxkwkY8yfg6m+AuXuAf9WwnHTDHl+DKkcUlfx2NM7ogsF30LVRPLP1FywdibA0VQO125S/170SuK3rpWqoERfrL2P2J1ynW266lSI8hwV2Bhz1KAsXuZxRl/r+nZrLvCyAdpRl6xKgXiVkeKfjjrL3R7+/14Z/jtcL7F/PbqsFS/4xwNXfst/QWY9J93HBEucIC/eHHN7qWynUVMPSwIKZVeJFg4Fn+v49Ya585h91IhEs6gaZfLK7Efjz3Q7jlS8cr0d18O+HHGkIqU9Zs9rDEs50G8zDYqhxnA5xozd9qOlhMRBh8Xs/8YQES6RIZ0c7xDIcanZAjIWRz5YOnDgbmP4U64LbezyLVlz6P+AfVSy8HwprKksVAcBv/wt8vOUwM1dCiG19PTenqkVBR3A0Mz+Pmo54WA6pQqt9JrIIyMZ3lMebaoBdX7Pbwy+M/HW40PFLoQT0RJAObM021qk06oKl93gmgCt+D0y5VxEnaniZularfn+xuPv76GwXHyLKPU/+EQgtarczQ6AlVUl/cMxW1tCRpzl4FDFuERZJsPQYyw5MHodssPbZrtyekaUctSgZpkSaTrxe6ccTCyIRLOrvUqjBilp4PYr3xOuKPMJSv5tFNMx2ILtcjrD4mG6FwAiLprnX7VQ8UllMGBoqazYy/LAjgkWuEtLxmTdIKa6sGAldA5BgiRQeYfF2g9Pt1VeyFk30mp/4gcf/AA8o0ZXs7oA1JTrbpUW+JFgOR0mwVK1k6YicHsxLA3RQsEj568IKYNDZ7Lb6QL31M3bdbXTH8rhhTbe+ERZXGvP+RLVSCGDCafJdwEWvASdcrR0x4oPudq1gk3vV8IPMidez690ro1N5s1f6jh57Cbs+sjP8ZFjeuLD76PAzTuIeYeFnqt3lklefJn5c0EczPSsIwGUfA9euAk6/07goMIKGVyIsld8ot42mdWu3A+42dtvjkj0sug7Cag6rDvwmM3LSNASL/N68smCxWTR+N037AYhM/EhpN54Sana64fWG+Z3wCIuePix604eaplsDVUIUYUly2hsUn4GdHcBikhaKBiVD2fWBXwMPKpGUNEcCd7A37ImsG68//IDZZ4JPqDZieISlsEKJSO1bq8zU4T0++k8JfK4RgphufcqavV65/NsrRRpqm+Pw3SoaxC7udmCNqtz0yC5WNWCyACfdyMowm/YrZ2EdgQvHfpOZB0v0hBcXvLminvEIPO15ZGegwPV6gWXzgCX/DD57pyN4vUqEJatMMQCrBYtaOEeT9AKgaEB016mFhlciJB63UlZv5HkcdTrJ4zJ2EFYjG27ZgV/bdBvYh0UzwiL7PcrkEwGeEhJFJlpCIvdhcYY+CXC1Kf1eYp0SIg9LksMjBRnFSMlkPoOEFSyFFcxA2XYksA9KNCsSQpGez3wRQHQqNLQES0c8LHyHVTiAHUgKBzCfyc6v2I6Bv15FBwVLGNNtms3MjKfS45ZMNkco6ikhPQiCMtRxpWrYJY9odBvNDoT84MpbhEeKs1VJj+Qfo6xXq/SX096gpKP0CJacHkoqhu/sObu/YxVKPzwJPBekUqwjtNZKRkqpzJ9H6tSChZuXQ5WoJjJG0hkA89U5VZVgRgWLug+Tx6lUCRmNsBzxjVRkpyplzXKq38fDEqIPCxelKp9QitUMm7RsWB8LFyxA6M/jyC4AIoswp2nMEFKj0enWqdfv43Yqx41YeZ8MQIIlEvhOtKA/CjNYfvxQPM6C9WBNVRS4/0GF50BjWSHEkdNCWzu2nuaDyvvofUrQqIUhVP9PAEoabdOHzHTqamX521DdJPWgYbp1e7zybJJUq5l12wSA1FzkZrLOw1FPCell8Dnsu9F2BPhSmiTOq9V46ox/JjUdFCy89XdKDiu3lQVLCB/LulfYTrigQl+U0GRWvocH/Zq2qc3F7Q1s6nM04WH1jCLmT9ESLLGKsHQWvOmZ3pMHng4qHc6ujUZJ1REWr1vlYTEoWHh0UPqf5EqmW6fbK0c/1Qf9kK35eesGXhkpkaG3tNmkEiyhKoXU/pVwRQChIizh/D5N1WApLhuQFoPKMoOQYImE6g3sumQYCjMlwZKoERZAmTPBDWocVe+BmMONt4d0CBavF1hxP2uS5w83v5YMZWf4RsPQ/rQeUSYV820cci673roEWCV1Dh56XuTVQRyNTrftbkW8pNrMimEvvQj50o4zLikhgHlCfi8duFc9A3z/OCshNlnYTCkAKOGCZUPHXsu/gSE3ih7c5Lucs4UJyS/vBL6U2smfcLX+1ykJIrC4YBl9Obv+cSEbwwAwcfPkGODR4cA3D/k+r72BtbkP1zNGnQ4ClCogLlgcTUr/jqSNsBj0sPDoWO/x0vMM/IZF0S8l5DSW5lDToPIWAUi3meVyX7lxo2o/4wxVJcSjEXzoq4Tu5nFmldk6lI+FV+npqSbTiOzKZc3hplo3qlJckXQQjjLx34JkhIciS4cnh2DhZ8HqzrAet6LSCzthB9ntWHa97bPwy275hDXGe/vywNEE6nQQoPyIIvWw8B9keqEybK50ODtouNuB3d+y+0b8v8jWr0beVkWktEo5bUGQdrS80VlGEfLS2XcrLikhTt9TgZF/BCACS//N7ut3OpDB0lXKd6uDERb/BoYlw9g1L1nmvH058OYlLALibmcN70bN0v868vaqDnZ1u1mUTTADp94KDP4DO+i+cwVrY//UCVJPmko2P2vdK8pznz0F+Ogm4NtHQr8uT3dlcsHCIyzSgYefPKQXaTd0SwaMnDx4Pcroh16SYDHyG26qBloPK397OlAlxCMskhFaEAT5ZEH+7ZmUkw23PK1ZK8IinXBkFPncrbt5nDolFCq1JkeFykOvDwj4v4iiqD/CIvtX4p8OAkiwGMfrUZR90ggWac6EOsLCS/ksKUB2J3QwHHg2OyDs/ym8kZKXYDsafEP16lbyvSew645GWJo0zogEARiuak/e/bjohOk10lftTiUdJAiCKsJSiPwMKcIST8ECAGc8DPSXPCIlQ1m1CYebuo/s0t+ZVgtescbTk2Uj2HVDFSu/B9j3d+sSFqka8Ufg9w8AM/5rLPKlFWHh37HyMcxrde4LwPi/sf/Xji/ZY7ZM1kkaYN2jmw8yMc1TWVUq86gW/P/Kuz5zwdKwj508JHs6CDDmJzuwkbVUsGUqKSFAf9dkdXQFYIJFihoY6nTb3qjMyVGZSvMCBEugh0UzOhEswmLnAxDDRFgEQZ8XyE9khcTv/+LyiLKfN6yHRSouQVZp+NfpBKLcU/4oxe1QejnU7mDNnaxpQEE/FGawM6eE9bAAQLGUEjq8hf0IzFbljC6/X+eE+jIK2aC1HV8CPzwNTL1P+3XdTqXyAwB+eVMZU3BkJzNLmqzKsD4NQ5khguxgMPY6FnVxtekzdOpBIzTb6mLbLZc0tyhnaEpKKM6CxWIDLnyVidzcXr4CIb2AzRhpqmYHkZ4nRvYatVywSCmhlGz23azdxkRuv9PYjCyADQed/mRkr1PMBdZOll6ypStl67ydv8nMphgPOY+lhg5tZgKmx1jgxUksLfbdo0DPk5T1lo0M/bqqVB8AZrw1WVnYv3GfEqHqKoKFVwf1GOMbVRA90HUezVOQ9iwmfLwuYxOIOTzCmpLDRjpIcMFymO/XffqwSFVCsYiwANL3wh3aw+I3ETr0+nz/LzwdBOhInzVpe3LiBUVYQlFfBSw+H3j6JKXEjKeDSoYCJnNyRFiye7AzGY9TSQNxM2NnpIM4I6UhiWueB/57jhJuVLP7O+YLsEh9ZrYuVXpx8OhK+RglfdPRsuYgJjlY7KwfyJg/6Qu76kEITAnxCiHZKNgspYTSCwPP8uKJycSm/2pFM7ofx67DRRlCoTXTiqcR961j0Qw+jmLsdZG/TkahJE5F9lt2tirmz36TfZctGgBMvQeY+T7Q6yT2GUz4J3tszQvAd48oy4phIgPygUxKpZlMyns98Kvy2XU/PsI3lgAY8bDw7sg9T1R+w4D+SCn3EXKhqCprNhRhCRKpCEwJKZHckFVCQU6AeG+XhjYD7flDfY7ydutI1fj9X5wq31xYwcL3jxkkWBKf1DxmDKvdphjE+A+tdAQAJIdgMZmUKAtPC8mG2048oxv8BxbGt6Qy8fHyWYEhYL7jHnQ2K9fzOJTwvb9/BVDlliOMsMgpoaLQy0UDjZSQMkdII8IiVaBFfZ5QtOGRhkg73rbVKaFnbnwGgDIuWH5kZmtXKwvbc4EUKb1PYdern2eeKnc7O2AVDQz9PIB5enqfwp7DO/MC4Ut5W/wiLABQLomTHcuUEyEeOUxG9KZnRVH5rvQ8ybeZnd7fMT/h4qlDVeM4Q1VC8oHft8cI/+0pgkX57bqDmW49LsXA7ydYeKm0PsHCU0JBTlScrcrrGBIs7P/C/Ss2i4mloUNBEZYkwp7BSjsB4Kf/soPrlk/Y31L4mAuWIy0OeMJ1MYwn/pVCvPqiMyMsggAcfxWb8WLPZtEe/7PyvWvYdflxymyYfT+yHxuvEPIRLHwnGeHEYPmMqBN+kBopIV42qaSEeISlCFkpFrl0MiGiLMHgB9mqVZF5ifjU2azuSudi9Xp3fsVSMwDrwNvRaq2TpKGPv74LvHUZu623CkwQgOlPsxQCoOq0HOZApJUq6CGlz9a8wA7UWd30hfgTFb0pocPbmGHWksIiJIJKYOiJlHo9ineIj2PwqhrHGUkJBYlU8Ohmrb9g8enD4vd94b9dwcxOdlVkaw1UDEa4eUJ8m22Zvr+XYASkhKTUWbgKIUAlWBLDw0KCJRwjpTbhm95nTbOaD7C8qeRsz0+3wyQAXhGobUngKIvaeOtsUUxr6oFxnUVBX2Uo26/vKvd7varJu6PZBWBdZ6t/Btrr2Wev9gtEy8OSWRx6uWgglzWrUkL+vSN4SiijEIIgyF03E1qwFA9h/xdnU2TlzVw88yggp3Q4UH4CO9Pc8jG7r38U/EQlQ5Q+MgDzyoy/Rf/zs7uxdvfnvgiceAO7zxPm+9eipPpk/KMpPcZ2XIzFE72ChUepu41mqVefCIsOwdK4j30nTFbmqQJ8G8dFlBLyFSwBLQXUHhZvkE63zapord9j2Vrdc4PBe7EEFSySfyWnXN/3xS/ypVvYiSJFWJKO8uNZdMLVCrwq9Z7od7o8nMxsEuTy04ROC3HBUrNBili4WYllvM7ohvyBXW/6QNlJ1W5X/CvFg30jLDwd1Guc78yYjnpY+A/S33QbC7RMt+out6KoSh2wAxsPTce9UigUJjP7vwDAD88Yfz5v4qaVkjnpBuV2fl+lZ0dHOedZNvhx+P8DLlwM2NKMPb9kCIvK6PEbOJrZ/gPw/Z7l9PQ9Ex/we2PbkGjo9bDwqCo3aPtEWHRESnlFWW4vZQaaR0mbGoqw8HJzv7bzQauEvB64pAiF1d//EcRwCxhNCfEGfGEiLHo7z/pHWLg5OZywczSxAhOgc/aPOiDBEg5BAKY96nsfby4lkRQ+ltIRLATbVA2seZHd1+OE+J3R9T6FhTNbDim9Nng6qGwE+9Fy02XtdiUloE4HAZENXFMj72Q6McKi2inLk5ptZibWeN5a8jrEvXmcXsbfzK43vA7s+ib0sv7IgmVQ4GP9p7KKnd/9G7jqy+gN6bSmsoZz5zzdscoc+WAQ4kDEz7ytaT6VKBAENo09uxyY9hjzeCUzej0s+39i19zDo45G6ImwyCXwfVTRCHXjOAMRliARhICWAqr9jFuKkFpNfvvOYBWHUAsWHfsp9TwhLeRmbjpn+/jtI3U32OPvx57l+72NIyRY9FB+PHDGQ+ws8vKlrGJARVIIFluacrDf9D677nFCvLaG/Sj52fLOr9g19wf1kELlaXmsMRjASmrTC4FhF/iuR2MSqW46+wxCw3Tbqq4S4kY6W6Z8YE6oSqFQdDsWGHYhu/3fc4EXJgEbVem+T24B7ioDXjxd8awALKrEU0JaERaTiZUUj/+bvnx9Z2MOE74HtNNBnHF/BW7aCIy6NLnTQUD4yADADKO8UpE3BwRUYysMChbVdOOIGsc1aXvY8v2bNsqRXG/wTrfqlJAfObKHRcfvOJxgMeorCZISsoUtaZaM8AkSXQFIsOjnuCuAyz5ifQP8SPh5Qhz/acM9T9JerrPgAmrnctYin/fDGHqesszZTyhh89PmAak5vuvoyCwhHl2xZXTOGYRWi2x1ZQOfDq3qdJowzeP0cMaDQMXvWWXX3jXAB7OB+j2sLf2a55k43LMK+O8flJL2IzvZrCKTNTlb0uvxbYRIFRxV6PksDv7GIozphb6+MSMnHnyadl4fVUWNy/gsIWer0jTOz8OWJ/3uWp0eVskn+8/cwTvdtkgnHBrC1FBKSI4aBfkcjfru/P4v8uDDcJ9TgvlXABIsUSEpIiwAEyz8h3fiDUrXz3jRZyK73rMKWLeInZkVD1X8NgCbYXH5EuCCl327z3I64mEJcUYUEzRmCckGOItJibCopq8mTUoIYKJvxmIWhczuwQTKkn8A619lB6m0AiZKGvexFvseN7Dtc/bcnmNZmibZ0BVh0ShpPhrRI1j4SAT/QaJGfsfylPk+PhU1hmcJ8R4j1jSW9lCRaVcq9GpbHJp9WAI63fJRARpDArlgaXEqzw+K/J6CnKSESD1pIgRJCYWrEkqwCiGAOt1GhaQRLFmlwPkLWRMu/9RKPMjrw4xzdZXAF7ez+7Rm9hRWBPcZdMTDEipUHwvkCIuyw/LJu2sIloSYJ2QEk4lFIS9+kzVc3PwRuwDA6f/H0n3Pjgf2/AB88wCwdy17rO+k+G1zR9AzoViu/DraBYuOKAmvTuQjHThGIqVylUxPHw+L4T4s6rEcfuk4QRBQkGFHdUM7apud6J6t1enW74DPR0iofr+crFSlm29DmwsFUlRek3CpNaO9owI8LDrNyZ19QqcDirBEgaQRLAAr5xw+IzHy5YIAnPUEYJZ+vH0msj4tRujILKGW4GdEMUHDdBs2wpJMKSE1RQOBkRcrf2f3AAZNZ91yz3yY3bd8PrBdirD0Pa3TNzEq6BHMLZQSkuFNIP0Fiykw+qiJowlwNgMAxIxiVVt/ES4XO8DrFizBulxL8P36wSaHTwTIJf1mA/qw8AhLeuD+xGwS5Pb8YdNCoaJ2Xq/q+6QzVaPy3wDqKqFwgqUTCxJ0QoIlCiSNhyUR6T2OtT4f/zcW/VHPFdGDKrdsGC4Q0gPPiGKCxlmkr4clVEooyQQLAJzyD6m5VQ5w8VtK6fCQc30jKgUV+rrMJiJ6UkKqgZZHNXoES+02dl04wPd+naZbUUpTNIsp+MOCX9Co+ti9bvYb0Z0SCuPRKFKfiKrGB3g9XLD4R1gCf79qdPtYQvVhaTuifL56v0/BGseFq6ZKQKFNKaEoIEdYGkmwRETPEyMfmud39mAIHmHp9JSQ2sOiOttp4Ds8xXSbNFVCWmR3A65bxQ7q6p2eIDCD7tuXs+nMp/4nMSJ+kWAKE74HyHTLcbYoopxPq5afqy8lVLNvN0oBHBRz8FNVPd79+RAukx4TPU4AFgMpodBzcpQISzsgKB4Xj2SG9REsohgywgIwwbK3ri18t9tQVUI8TZOWL/cCC0uQ4YfhIyydnDLXAQmWKMC/2E0ON9qcHtZTg+gcouFh6bSUkEaERZ1PlquE1Ckh33lChuakJAJ+M1pkcnuxvirJDpluFcKJDt7wzJ4VvNovTIRl164dTLAgFwDw2W+HZcFiBdsH6C5rDlNtU5jJWgsERFi8XLCoRLajSREYQfYnugcgmkP4oiJpdBlk+CF5WLooWSkWuab9MKWFOpeOeFjCnBFFHZ6nV+2U212hTbdJM0+oq6Ln+9dlTLdhIiz1kllWq7u2zgjLwf2VAABbDqtcWVVZD1FKC1vAIwd6IyxSn5EgVTC+HhZlnV63RkqI/3ataUG7JutOCYWqEookWhfQh0VHSsjjVqXME+d7S4IlCgiCIPtYDja1x3lruhgdmSUUJuccdSIw3SbNPKGuSrhOt45mVXPCxNnxx4RwgqWhil3naAgWOcISPLUriiJaaln/nuKyXhhYmgWvCHgFJgSs8MBqFmD270AbjKbQ5cHBPSzsf60pWELsS7JTpXlC4VJCoTwsklF4yW7g/Z/2hV6PvD7tsuaQjeNaawGIbJ/VWSd0OiDBEiVKs1n4sKaBIiydioYvRDedHWGRxZVWWbNJ1cfBd6eXFPOEuirhUkI8HWRJZQ0Kj2bClXh3MMJS3+pCmpP9RgrLemBcP/a7dYE91yq4tQcfiqL2CnVWCR1qcvjMO+IpIZ/GcSFKmjm5UkqoLly321DfKSnCUunIwI1vrMeGvfWh1wVozBLS4WHh39u0fN/hlHGGBEuUKJEES3VDW5y3pIsRaWt+UVSdFXVWSih4p1u7WQTa6qXt8RMsydQ8rqsR7iCtmr6dtMZivej1sGhFWHSceBxoakcR6gEAtpxuGFGeAwBwiOyAbIEn0Jex/lXgziI2EoKXVAOsF1VbHbuto0pIFAQAgrSJUmt7nwhL+JMf3Qb6EH1Y2urYsMZDIhtTcf9nW0KvCwiREgpx+Of+lQRKBwEkWKJGWQ7r0lndQCmhTiVSD0t7vao8MP6m23RvEwDpTDA11+dpSV0pdLSjag2vSVcx3AI6UkIhIiw6Urs1De0oEurZHxnFimDxssOYDe5AX8a2pcwLsmcVsEo1SZwfkM12VnavAW/u5vR4me9EElViyAhLeMESPsIS3MNSe4Clgdps7KRmTeUR2UQblKDDD0NETtRCO4GISLA8+eST6NWrF1JSUjBmzBisXr066LILFy6EIAg+l5QU34mroiji1ltvRWlpKVJTUzFp0iRs27Ytkk2LGyVZFGGJC5F6WLh/xZYJWEJ0nYwmIcqa09zSTJOUHOUgKJG0zeO6AmEjLF2kpBlQBEsw8cZTQv4lzYCuSOnBRgeKBSUqUpqdgsJMO5xQIiwBFUK88g5QTLaAb4VQkMhXitUsG2XVPhZRq6xZR4QlV29PJflz1PhOScJo3IiByEu3od3lDZ8W8jupc+rxsMg9WBKnaRwQgWB54403MGfOHNx2221Yt24dhg8fjsmTJ+PgwYNBn5OVlYXq6mr5snv3bp/H77vvPjz22GN45plnsGrVKqSnp2Py5Mlob0+eaEVZDhcsybPNRwWReljktvydZLgFgphu2e1ULlj8oisApYQSmnBt1Dt7/EM8CRVh8XqAJpbOQHb3wMd1lDUfrqtHltDK/sgohiAIGFGeA7coeVjglqMYMmrBwkUKELZCiFOkrhSSttEksN+s1aQWLIGDS/3Jj0KEJc3NBFtBcTec0Ie91g87a0Ovz+//omuqdYI2OzQsWB566CFcddVVmDVrFgYNGoRnnnkGaWlpWLBgQdDnCIKAkpIS+VJcrKg2URTxyCOP4N///jfOPvtsDBs2DC+//DL279+P999/P6I3FQ9KsqWUUD0Jlk4lUg9LiEFlMUNr+CHfebgb2R1agkUKTR9Oxm63Rzv8+xdusm6CnanGhFC/xbY6Rahr/ebk1vzB0xvNdeyz9AgWIIV5OEaU58AlRVis8KCiJNP3Sa2qg3mz6qQ6TIUQR/EmtssHfgskwWJRRWa4YEkNLlh4tV9tixNiMCMwEFQEi14Psr3sxKaopDtO6MNOtlaGEyx+Ueh2uTIxVEooMSODhgSL0+nEjz/+iEmTlLbaJpMJkyZNwsqVK4M+r7m5GT179kR5eTnOPvts/Prrr/Jju3btQk1Njc86s7OzMWbMmJDrTDTKpC/2waZ2efw40QlE6mHp7C63QOjhh+4mdod/Qy0oox+ox08CEq7TLUVYGFw4aKQ8AeiKsLQ3sIOow5Ynp3FGlOfAraoSGlCimrqsNtYD7H/B9xNhKoQ4vPqzur5NFlUmSbBY1BEWbuANFWGRUrtOtxetzhD7qyBVQnWHD8AsMKFTUtoNo3uy19qwtyG0APL3sMjjQHSkhBLMe2VIsBw+fBgej8cnQgIAxcXFqKmp0XxORUUFFixYgA8++AD//e9/4fV6ceKJJ2LvXuYY588zsk6Hw4HGxkafS7zJz7DDYhLgFaXwIdE5ROphkXPOnZkS8j0DFUVR6YngUnlY/CjKSqLhml2NsGXNvPlW4vSyiBmhBEtLGI+HjhMPdzNbhydFiUIO7Z6t8rC4MUAdYXG1Ah7Vb0b0KgImzBwhTqkUOd/vE2HRGH7IBYtGhJSTajXLlTkhDfRB+rAcqGbHzEZkwG5PQd+iDFhMApra3Wz7gq7P97OVIyyhumYfTaZbI4wdOxYzZ87EiBEjcMopp+Ddd99FYWEhnn322YjXOX/+fGRnZ8uX8nIN13knYzYJKM4iH0uno5qiagi5aVwnHkj8/DZOVSTO6gzuYeH9IA43O+D1hjiTIjoffnCBqJ3O0NFQ7KhBT4Ql2O9NjxdNEj2C6iQjK8UKi5VFLmxwo79asPDXNNuUCBdP0YWZI8RRvIlt8gmHGV5YTKyAREaHYBEEQfaxhBQsQTwstQdZhVCTOQcAM832LWK9fX7bH+Kk3W8fybtra/as4RwNptuCggKYzWYcOHDA5/4DBw6gpETfqGur1YqRI0di+/btACA/z8g6586di4aGBvmyZ88eI28jZpRSL5bOR859RxphiYOHRUoJ8R0HAFic3MOSE/C0/HQmWFweMXxbb6JzUac3tNJCXVGwaIm3IE0RZTRK/tW4PV5YHMwnYsn0PetPsbP9blG6GVkpqmnv6s+eCxPuXQkzR4gjR1jq2+T3Z4Y3cPBhW3gPC6BUCh0JZby1aAuWliPMKNxuV16DR5Q21+gQLH6m26CzhLyehGzLDxgULDabDaNGjcKyZcvk+7xeL5YtW4axY8fqWofH48Evv/yC0lLmzu7duzdKSkp81tnY2IhVq1YFXafdbkdWVpbPJREolXqx1FCEpfOQf4wGfUM6+iZEHb+dMu/BIgiAqb2ePaaRErJZTHKXTEo3Jhiqlu0BaSGvVzmQdYmUkOqM3f8EQk6NBREspkBDupraFidywHxetizfg2hGGtvv9s0PUiGUlq+YR+UIi74qIbm/Vn27vI1meH17sDiblfcbIsICqHoqhTLQW6S2H27f40hbPdt2b6ryXRpYyo59v9U0BV9fwLTmMBGWlsPSSZWQcELbcEpozpw5eP7557Fo0SL89ttvuOaaa9DS0oJZs2YBAGbOnIm5c+fKy8+bNw9Lly7Fzp07sW7dOvzxj3/E7t27ceWVVwJgYbIbb7wRd955Jz788EP88ssvmDlzJsrKyjB9+vTovMtOgkdY9lOlUOfRYQ9LZ6aEfIcfyl1uLSYIXLAE2eH5tAknEgeT6ozeP8LSXq8YrMOceR8VmNWfhd/vMVykKYzp9lCTA/mSYDH5raMoh6VF/jDcL1qiLjXmqY3mA4CzRdmerDLt7ZHgKaEmhxteOSXk8e1yy9NBZjtgTQ25Pl3N47hgcfkeR7xS5Y5ZFWEawAVLdagIi++JUtiyZnVbfi2DdBwxvDUzZszAoUOHcOutt6KmpgYjRozAkiVLZNNsVVUVTCr3dF1dHa666irU1NQgNzcXo0aNwvfff49BgwbJy9xyyy1oaWnBn/70J9TX1+Pkk0/GkiVLAhrMJTryPKFGSgl1GhF7WJQQ9cHGdqTY/MLJscBvlpBPx0nell8jJQQwwbL1QDMONZMYTijUB2n/0mZ+ULRnKWH+oxl1tClAsISJaIZpT9DY7kKuIEUR/E4yBMnzkWX183fxzz81TxVhOQgc2ancHyYikmazIDvVioY2F9yiCTZoRFjkkubcsOMX1KXNQQkSYbHJKTFFmA2UUkKVh1vQ7vIgRctIG6RKKKjptjkx/StABIIFAGbPno3Zs2drPrZ8+XKfvx9++GE8/PDDIdcnCALmzZuHefPmRbI5CQNFWOKAKYIIiyjKguXGj/bi/V3V6JWfhs/nnOKbm442fsZCn0nN/CwtSJtwXtpMEZYEQxCYEBU9IaIKXSC6AoQWLOGqhMJEWBrbXMjjgsX/8zQHMfu2qVNCqggLFyz5x2hvix+l2SloaHPByQWL4Odh0VHSzMnXkxKycsHi+1tPc7HXsapSYoWZdmSmWNDU7kZlbYtvWTdHlRLyekXZ7J8SrNNtS2JWCAE0SyiqcIMWmW47kUgaxzka5fD9kl1sJ1dZ24qvNgfv1hwV/Ey3coTFamLpAyBkhAUgwZKQBOt2Gw+fVDwRVIcT/99juJRQuAhLmxt5aNReR7DOsOrX5Kmf+ipFsOT10d4WP7pJPhaXl0VPAky3OiqEOMrk9RC/YznCohxHvF4RmZ566WWUyIcgCHKl0PaDzdrrU5U1O1RzhzSjMUDCDj4ESLBElVK5eZwDLmoe1zmEqS7QRDqQOE2paIcyR+jNtXujuWWB+Jtu5UnNJlVKiDwsSUewGTpdqUIIkNzjQaIdegVLkAhLQ5sqJeQvAIP0LfGJcBUOYLcP/gbUsgpVvYKley4TLA4PEywWeAz3YOH4tPoPBp9tpoqwNLa7ZMGWlutrFO5bGE6wKFFo7l8BQkxrTtAutwAJlqhSIDWPE6l5XOcRiYdF2pHVgYVPZ0/sCwD4astB1MVywGCQlFCWxaWcnQdLCXHBQt1uE49ID9JHI/JnoRIP6o6zYcuatU/0GtscyEWz9jqCRbjUVUL5fVkkxtUC7FjO7s/TlxLqkZ8OAGiXBIsJXt/oRJvKwxIGXSceFsm461IiLLUtThQIrFeTLcvXWxJJhMViElgDvF/fVyKBnATuzkyCJYqYVM3jaigt1DlE4mGRfqA1bvZDn3FcOfoWZcDjFbG68kioZ3YMv1lCfOdRYJYGupksgC1d86lFmfx7Rf6ohCNYt1u5l0VXFCyq36OzRTGQBu10GzrC4myug0Xgs4j8PSzBPn9VlZDZAhRWsL8bpUiqzghLz7w0AECbtGkWeGQvCnugnl3ribCoulYHbQKpEWGpa2xGNh/86PcZ6hcsblWFkJmJlbcuBR7orzTSAxLadEuCJcrwMjgy3nYSkcwSkioWasVMFGXa0T03Fcf3ZjvBNbtiKFj8ZglxwZJramH3h6gy4EPYDjRShCXhkOcJUYRF04vCK4QsqUEFebjUrpencc0ZygGdI3tYgghGXlJeNNj38bze2tviR498JlhapX+vCSIKMlTbYMTDIjWBdHtF1AdrAslLo91tLDoFZfCjG+aAKCwXLDsPt8CjJYLUgkVt9OepMdEDfDRHWV7uUUOC5aiHjLedjBy1MB5hOYIsDOueDUEQcHwvSbB0RoSFCxbpbCdXkARLkHQQAJRIkbtmhxtN7dTtNqEIVqXSJQWLxmeh53MIFymVGs857TnBX1NtulV3n+WvW6y00kDxUN3VWz2kCIvTw36/FnhQkKkSLK36U0I2i0nuxXKwKchJLRdkolf+PHjTuGZzttLPSaJ7bhpsFhOcbi/21rUGrk9Qe1j44EMzKz7g1Pyi3G5gIwCQ1T3s++lsSLBEGd4ZcV8dCZZOQWMCclhalAhL91y2M+IRlo37G9HiMNiETi9+Z5HtUoQlBzzCkhP0qel2CzJT2I75QCNF7xKKsKbPLi5YwnW5BcKWNZvbmShw2zVEBo+wqF/T1aqkoWTBooqwTHsk+Lb4kWI1ozjLDg8UD4tmhEWnAArbosCiaj4n+VhcDUywtFoCRZHZJKBPAYtcaaaFVFEvh7otf6vq5KypmvmH2hsAp2Ruzu6m6/10JiRYokx5Hvuy7SHB0jmEGrgWDClEfUTMkiu7ynJS0S0nFR6viHVVddHeSoa/6VbaeWQJqpRQCJRZVSRYEgotoynQ9cqaAe30WLg5QoCqNb/2iQefI+TVWofsYVFFWNSDD3kaqvcEYPQVwNlPAt1HB98WDXrmpcMD9vu1wIOCDLWHRX9KCNAxfV2d8pJ8LF5perJDS7AhjI9FVZjQ7tOsUrWf87pYRKpB8vek5gZP38UREixRhocPq45ohOaI6NOBsuYjyJTnPwFKlGV1rHwsAbOE2M4ji1c/hEgJAUCJnG4kwZJQhDV9dqUIi5aHRcdk9DARlhQnO7gKWlEarbJy9WfPfWFmC3DmQ8DIP4Z6B5qU56XBIx0uzUKQCItOwcIjLEErSQUhsBeLVLnjTtX+DI8JVdqsabo1KSkzTuP+hE4HASRYok65lGLYW9cKUQziAieiRwciLLViFrrlKOMfYi5YTH4eFkmwZIrSTiZESggASqQzswMkWBILLeO326GE1rtKp1sgSEpIx9yuMOb5VHc9AMCstQ4t022U03F9CpUIi1mdEvKZ1KxTsOgqbfatFLK0s/cjBhF9PMKy41BoweIz+LDNL5LcVK1UUCVgOgggwRJ1ynJSIQhAu8tLPTM6A7+BgnoQpZx6rZglm6QB4DjJeLt+T73cIyWqBHS6Za+R7uWCJfQOT46wkIclsdDqA8IPmEJgVcdRTUjTbQjhFqKsud3lQbYoTWrO1mhmpvn5GxMR4RhclqVEWOBVUkI+k5p1elh0NY/jlULst26XUmKmjNCCZfvB5sATZVXUyyfCwj+jnB7suqlaFWEhwdIlsFlMKJMOLHuOkI8l5hgta1bNEaoXsuXOkwBwTGE68tNtcLi9+GVvQ7S3NGin23SvdCYe5sAmD9ekCEtioWW6VR+kTV1oNxtSsOhICWn8jtVdXm2ZWhEWDQ+Lf4VQBxlclg23LFg88hBDI5OaObJgCXXiwSMs0sTmVGmOkH/TOE7vgnSYBKCx3R14oqyOsHDBYhaUcSC83LuxGmiUBEs2pYS6DLyVs2aJGRFdjHpYnC0QPGwnYMkogEU1E0QQBDnKEpMGckE63aZ5JMESNiVEgiUh0SrJ7YoVQoD2Z9FiwHSrEWFpbHPLgw9NoVJCbg3TbZQ+/8JMO7yqCIvJJPliDExq5vBK0pBeNL+JzVnSHCF7jrZgSbGaUS75JwN8LKr/CU8J5ZjblMpKXu7dVK2YbkmwdB34F2cPGW9jj1EPi+RfaRetyMkJDBcfF8sGcv5lzVKEJdWjL8LCm8ftpx4/iYWW6bbLChaNiKfc8TeyCEtDmwu5CDJHCACsbH+rHhYYi8/fKygeFhmDJc2AWrC0Be92a1UEi8vjRa7IIr4pOSVB18tnCu0IECyBplu595M1HcjtxW43VQMNe9htSgl1HXil0O5aEiwxJ0xL7wC4fwVZKJMM0mrGSIJlbWWddtfIjuDXM0bOJ8sRltD59m5S5K6+1YXmWPWKIYyjVcrb0kUFCxdvqrbySllzKNNtmJSQPPhQ4/PkgsWlJViiZ3hOT2FpGk3BYsArU5xph0kAXB4Rh4P5HFURlsY2F/IFlhJLzw0hWIKVNstlzV60O9nnmwPVPidTGqZ4YBNQV8luF/TX/X46ExIsMaBnPgmWTiPMWPoApPLAI1Jbfn8GlmYhw25Bk8ONzTWNAY93CB4yFnmERWri5JJeJ0xKKCvFiuxUdkCgdGMCEcp029UEi9XXLAqPizUjA0J/FiHKmpubW5ApSGJES4Dw13SqfhMxKCk/rg8bBvj7waqhgBEIFovZJKd399YHiZZyweJqR2NjA9IEqVooM/hAwmO4YPGvFOKCBYDTydaTLQ+SzAWyythtXiFU0B/ISLzBhwAJlpjQp0CZ7UDEGKMeFlXTuDz1ADMJs0nAqJ5s57NqZ5TTQn4TadtdXgjwwsYFi45qErkxIRm6Ewe5Dwh5WGCVmo25JPHAhYNgCi3IQ5x4OBrZSYYHJu3fiBxh0RIs0Yuw5KQzETG8W6Zyp1zSrLFdIeDR0v3hBIu7Ha11bDChAzbAlhF0nUEjLCozsFeKQmWKqghLQQWQoYrc9Bir9210OiRYYkCvAvYDOtzsQCPNfYktRj0svC0/snwnrqoY14+Frj/7tUbz8YjxS1+1uz3IQDsEHmLWsdPjfX7IH5VAaHW6bdXRe+RoxD/awT+H1Fzl+69FiNSuu5mto1Vjjo7Pa2qlhHSWGutCa18jT2o29jrcxxJUsKg8LO1SW/4GU3ZIYy8XLAca/Y47ZpvcUsHrYCfRGbJgkSZZD5+hLN/zREPvpTMhwRIDMlOsculaJUVZYotRD4uqaZxWhAUApgxhZxurK4+ELj00iobpNpub3ywpusoiZUM3pYQSBzLdKsjigQsWHSXNQED0UY1XEizt1pwgr+nnYdEafBgNtAzFEaSEAB0z51QRFlfjQQBAkzn0a2SlWOU0t4/xVhDkvi5eqUw6w8PT0NI6R1ysLE8Rlq5Hb2kY1S4SLLHFcISF7UCDpYQANv10ZI8ciCLwyS/V0dhKhsa05mydbfk55bmUEko4NHuPRD8lkRT4iwc9XW6BkCcegnSS4bQHOWD7iyStwYfRQDX1WCbCBnWyYKkPNrFZ8bB4m5hgabWGfw2l463fccfvM0rjvZ/497OwAph6PzDlHiC3p8530fmQYIkRvfOZYNnp/8UhogsXAUGGpgXAIyzIDCpYAODMYcyI9vqaPdEbseCfEnJ5lAiLzh1e9zxl9AORIJi1Bv519QiLJFj0VuuE8KKZ29hv1hVkjg5skkjyuliUS2vwYTTQElURlDUDQPdwKSF1HxZJ9Dls4V8jnI9F5I3o3H4RFgAY8yfghGv0bH7cIMESI3oXsh9KZS0JlpiidXbbfBB450pg9/cBi3tbFNNtfnpglRDnvGO7I9VqxuaaJny/ozY62+pvunV7kQ0uWHJ0rULtYaFZVQmCf6dbVTflLjWpGQg0wOpNCWk1nJOwO9hn6Q0mWKyq9gSuVu3Bh9FAyxgcYUqomxwpDfI7VnlYZMGW0nHBwv8vqW6pciuaHp9OgARLjOgjpYQ0p2cS0UPrrGfTB8AvbwHfPxGwOB/TXi9kISvVEvA4JzvNivNHs26Pz329M0rb6tvNs93lQY5gLCXUPZfNqmpxelDb4gz/BCL2+JtuHU3K7a4WYbH5CRY9XW6BkGXNqU5JgGRozBECfEylcLXFLroVRQ9Lj7w0CALQ5HDjcLPG71gVYbFKgw+9OsQvn9ocMARRWh/v8m13ccESnVlLnQUJlhjRr5iVvm0/2Bz9BmSEQij/AK9QUCFIOzN3Sj6EMGdfV5zcG2aTgBVbD+GnqrqQy+pCFfYWRZGlhGAsJZRiNaObFE6mdGOCYPY7kPEDpiVVOYB3FQJMt3o9LDy1GyhY0qU5OuZM7bb0EATfyE6UBx8qr+MXBYpgUjNH/TvW9DnK05rbYXdK+5708L1ReIRld22L7wBX6fMRpOotm7Oe3Z9kHisSLDGiR14a7BYTHG4vlaDGEvnMzMt2IIBy1tPq10fF2Qqzm/0vBB3lpj3z03HOSNai+tFl26KwrYrp1uUR4RWh8rDk6F5N0LMoIj74p4T0tKI/WvE33epOCSndWP3J9kqD/7QmNcuvq/LOxKJCCFBtoyQEIpjUrEYpzND4HfNpza52pEmCzZQZ4v1LFGXakWm3wCsClYdVxx0pxeR1sv+LlSIshBqzSZAPLFsPNMV5a45i1L0d+NkZFyxtfoKFVxuIZqSk5+ha/fW/6wuzScDyLYewrqNRFlX6ql06+zFaJQSoKgEo3ZgY+He6jUFb+KTB33Tb0jHTrdcrynN07CHm6Pi8bsxSQjwKJImUCCY1q+HHB80Go6oIS6aHT2oOL1gEQVA63qr3DyohaYIXZgc33SbXd5QESwzpX8y+ONvowBI71IJF9Bcsdb7VQ3LTuGzkZQQ33KrpmZ+Oc49lUZZHvuhglEW1U+Zt+XMowpL8yJ1u/QVLF/OvAMFNtxGWNTc7XMgHEyzpeWUhXleqBnK2xE4wyulnaZ8SwaRmNTzCopnaVQmwbJGJi5TsICkxP/oVaZwoqzwsWWiBACkabbBDb7whwRJDuI+FIiwxRDUnI+DMR/QC7fXK4628B0vokmZ/Zk/sB7NJwNdbD2H7wQ78L1XDDx3SpOYck7RjNxCaPUaqQAvotUDEB/+yZhIsLNIhivo/iyARlqaGOqQITAjaQx2wfSIsMUoJ+XtYIixp5oTs1cUjLHW7YIUbbtGEtLxSXesdUJoFANhUrZqFJv1fUuFELjf627OU726SQIIlhlRIgmVLDQmWmCGESAn53+YRlhBN47TokZ+GiRUsHPvm2r0Rb6rSM0YjwmIgJcRDvnvqWuX1EHGEH6Sd0v+yq5Y0A6rPopUNPZSrpSKLsLTWscaNrUgJ3VPFx3Qb4yoh/0huhD6QPtKJx+7aFrg9ft4d7mE5wioUq8QiZGfo6ykzpEwSLPvVgoVFWFIEJ4os/CQpJ6LtjickWGJIRQkTLDsONcPp1tnYjDCGOsLivyMBfI23fPAhMpGbZuzM4sLjygEA7/y4N/L/pcp0284jLAb7sABAfroN2alWiCJVCiUEfCCdUzpz7dIRFlWVEP8cbBlKX5FgCNpVQo56NkenXsjR+brqCEu0U0JBIiwRCpay7FSk28xwecRAH4vfOneJpfKk9nAMkgTLvvo21PHWB9LnkwIHSm2SvyjJ/CsACZaY0j03FVkpFrg8IrZ1JJVABMffdCuKfhEWlWBRNY3LNRBhAYAJFYUoyrSjtsWJZb8d6Ni2qky3WQbLmgFmrONieHNNY5iliZhjlwSLgwuWLtqWHwhiftXxOQSZ1uxqZL+1xjBzdHyEklxqHCvBwk+MIpvULK/OJGBgqUY0BABKhykiDsBec3eYTfp8MpkpVvTMZxGnX/l6pYhNKpwothpPQycKJFhiiCAIstr91f8LSUQHQfA9O3M0+YaVNSIstWIWctKMCRaL2YTzRrFGcq+v2RPhtvqabk3wIgPGU0IAMCjYjo7ofAIiLF10UjPgm5oxkhoL0jjO28QES9g5Op2RElIbe4GIJzWrGVym4TcBWPqraLD85yF7D0PrHVKWDQD4db9UvixHWJwoMkuCJQkFNQmWGDNY+uLQgSWGqM1wbX6lxz4RFsl0i0zk6AyvqrlgNEsLfb3tEPYFmwESCnWExeVVoiuA4bO0QVrGOiI+2Fm0S4mwUEoIEIHGfeymns9Bq4ssAFNzDQCg1R6maRpv0NdUoww+1NFozRA2f8HSsZQQANUJbUPgg91Hyzfr03oZWu/gbmy9G/b5CpZUwYE8s/GobqJAgiXG0JlwJ6A2w/kLFnWEpZmdrdWKWcg1GGEBgF4F6TihTx5EEXj/p33Gt1NlEG53upSmcbYMw279QaozM5opFGfkCIuU9u3SgkXV2bd2O7vOClGOzAliurW17AcAtKaGqZDhr3t4K7tOy49+l2F/wRKFjrqDSpUT2oDfcckQ+WZLZm9D6x1RngMA+Gm3tD+UIywu5PEqIfKwEP5wpbupuhFeatEfG0z6IixiI6s42C/mI9ug6Zbzh5EsLfTeT/uMCwVVrwaH06W05TeYDgJY8ziLSUB9qwvVDUFG1BOdg9rD4lF9B7tilZDZwmb7AIp4yOoW/nlBpq6ntbEIiys9jOjhkR0jr2kUHknjwrSDZc0A0K+Y/Y7rtH7HPU+Sb1ozjUWLhnfPgUkA9je0o6ahXRZ0KXAgB9L2d5UIy5NPPolevXohJSUFY8aMwerVq4Mu+/zzz2PcuHHIzc1Fbm4uJk2aFLD8ZZddBkEQfC5TpkyJZNMSjr6FGUixmtDscGMXTW6ODWozXLAIi8cFSOHlg0I+slKCDz4MxZShJbBZTNh+sNm4L0llEHa43crgwwhMeylWs9zxlvxRcYZHWLwuoKlaulNIygNCVJDFgxRhydYhHoJEWDIcLCrqyQwXYZFes75Kes1yPVtqjBikhFKsZvSX2l/8vKfe98GigXi54kmc7rgXuSEmy2uRbregooSdLK+rqpMbx6UITuRIow6CDpNMYAwLljfeeANz5szBbbfdhnXr1mH48OGYPHkyDh48qLn88uXLcdFFF+Grr77CypUrUV5ejtNPPx379vmG1KdMmYLq6mr58tprr0X2jhIMi9kkG6DWV9XHd2OOVizqOSJBIizNByBAhFM0w6Nj8GEwslKsmDSQ/dA/WG8wLaRKCTmdTsODD/0Z2k36Xu2JwmBGInK4YAGAIzvYdXqBMhSxq8HTMw2SeNAVYdGoEvJ6keNixxUhJ4wAsfqlf/SIJKPEQLAAwMgeOQCA9f6CBcB68xBsFcsNVzUCwLHSetftrvNpHJftkszQ4URgAmJYsDz00EO46qqrMGvWLAwaNAjPPPMM0tLSsGDBAs3lFy9ejGuvvRYjRozAgAED8MILL8Dr9WLZsmU+y9ntdpSUlMiX3Nyj5+xkuJRP/HlvfVy346hFNj02KTuRTCmEzGeZNLJc+EHkItvg2Yo/00ewneEH6/cbm8RtUgsWlYclJTui7RjZg/1GtHZ0RCditiiiuVYSLBn62qgflfjP1cnuHv45WhGW1sOwwgWvKMCaE0aARPKaRuHC1N3OIrZREiyy30TjhJb3UcmLwHM3qifbrrW76+Q+OKlwIMN5iC2QdZQLFqfTiR9//BGTJk1SVmAyYdKkSVi5cqWudbS2tsLlciEvzzfvt3z5chQVFaGiogLXXHMNamtrjWxaQiMLFjqwxAYtwcINa41SZ1qpYqFazIuoQkjNhIoi5KRZcbDJgZU7DHxP1REWl1sVYcmJaDv4mdnPexqMCSci+nAfCwkWpfyXo8d069/2HgAa2G/3IHKQmR7GQOv/mrEULAA7AZK7+HbMXM1/x7/sawjoeFvXyl4jkgjLcb3y5PW2iez5hUI9LF7JK3O0R1gOHz4Mj8eD4mLfH2NxcTFqamp0rePvf/87ysrKfETPlClT8PLLL2PZsmW49957sWLFCkydOhUej3bbcYfDgcbGRp9LIjOiew4AZrx1uKmVetRJYblaOBqBFunsoWwku25vYEJGirDUiHkRVQipsVlMOGMo+7G/Z6RaSNUIyuFSR1hyItqO/sWZSLOZ0exw+05mJToffjA7QoLFJ9qRkhO6pT5H9qGpDtiSYKkW88N3efWPsGTFQLBYbIBJ2o66XezanhXRpGY1fQoykJliQZvLg81+Y1zqWlmExWhnbgAoz0tD99xUeLwiNh5k68kSpHYMKTkd3u540KlVQvfccw9ef/11vPfee0hJUVo1X3jhhTjrrLMwdOhQTJ8+HR999BHWrFmD5cuXa65n/vz5yM7Oli/l5TEwWEWR8rxU5KXb4PKI2LhPo96e6BhyhEUlWHJ7KUKgYZ8sWKo7UCGk5pyRLES9ZGM12pw6Rag6JeR2IQfcdBtZSNlsEjBcEsPrqsjHElcCIizJZ2iMGuoDod5Ih1ZKSIqK7hfzkJUS5jdrz/D9OxYRFkARX0ckwRKFXi8mk4BjpfTuql1HfB47IqWEIomwAMDYPiz6s3a/XwWSnqhXAmJIsBQUFMBsNuPAAd/W5AcOHEBJSUnI5z7wwAO45557sHTpUgwbNizksn369EFBQQG2b9+u+fjcuXPR0NAgX/bsibDzaCchCAJGS/nE1bvowBJ17DzC0qQIlvRCpVKgYa+884tGhAVg+eHuualocXrwhd5W/YIAgJl9XU438gQpMtiBjqjH9WZh3x92Hj0p1KTEJolm3nskM/T+8KhGbYDVW16sYbr11LH9uq4IS4+xQLaqG2ysPn9+ciQNJYyWMD3xGCYsVu44LN/n8njR1M5SZJF4WABgrLTeVXtafR9IwnQQYFCw2Gw2jBo1yscwyw20Y8eODfq8++67D//3f/+HJUuWYPTo0UGX4+zduxe1tbUoLdX+UO12O7Kysnwuic7x0oFlTeWRMEsShlF7WHg78PQC5SyrYY8qwtJxDwvARCg33xpqIieNjfe42pEvSOHfDvTr4Du673fUUgO5eCKf4Uv/g64cYUlR7Y/DVfdwNCIsngObAAA7xDJkhGtDYLEDf1oOVJwBjPur74yxaMIjLHXRi7AAwInHsH3Aqp1HZB9LveRfEQQgK8J91kl92XrXVTt8H+gKggUA5syZg+effx6LFi3Cb7/9hmuuuQYtLS2YNWsWAGDmzJmYO3euvPy9996L//znP1iwYAF69eqFmpoa1NTUoLmZhcObm5vxt7/9DT/88AMqKyuxbNkynH322ejbty8mT54cpbcZf9SChQySUYYLlvZGlWApVEobG/YCdbsBsAhLToThVX+mj2Rh1RVbD6G22RFmab6tbGducjQhlzdw6oBpb2SPHNgtJhxqcpCPJZ7Y/FISGV04wnLCNcDAs4Ah5wJjrtb3HI0Ii+nQbwCAPdbe+gb/pecDF70KnHqr0S3Wj39KKErCdFBZFrJTrWhyuPGLZBs40MjSOPnpNt2DD/0pzkrB8PIc2XQrk4QVQkAEgmXGjBl44IEHcOutt2LEiBFYv349lixZIhtxq6qqUF1dLS//9NNPw+l04rzzzkNpaal8eeCBBwAAZrMZGzZswFlnnYX+/fvjiiuuwKhRo/DNN9/Abu9Y+WkiMag0C+k2M5ra3djiZ6wiOggXLI37VM59VYSlaiXQXAM3zNgslkclwgIAfYsyMbRbNtxeER//Uh3+CYBcwmx2NUYlJWS3mOVqgO+NVCwR0cXfQ9GVTbdlI4EZrwDnLQAK+ul7jn+EpfUILC2skOOAvU8MNjJCAjws0REsZpMgR0u/3spOuiqlRqM983WYlkNw+qBiuGCGW1Qd7rtKhAUAZs+ejd27d8PhcGDVqlUYM2aM/Njy5cuxcOFC+e/KykqIohhwuf322wEAqamp+Oyzz3Dw4EE4nU5UVlbiueeeC6hESnYsZhNGSweW77YfDrM0YQj/vLItk/Ud4B6W3d8BALaZjkEbUpAfpQgLAEyXzLe6q4UkwWJzHFEc+x0sizyxL08L0fcqbnAPC6crp4Qiwb81/0GWDtrjLYQ1LYFS/vz/7JIq/KL4f55Ywda1bDPzxFUeZq/Rq4OCZfLgEgACmqEyQ8didEEnQLOEOpHx/Vm+8+tth+K8JUcZ3HTLBQuPWPhVCqwVKwBE7rjXYtrwUpgE1vRpt57RC5JgyWtnhkJRMEdc1szh+e+VO2op3Rgv1BEWa5oiogl9qOeBAYDkX9ksliMrNYE6BvuXaEdRsEwYwI4PG/Y24GBjO3YdZkbZ3gUdG+LYtygDd50zBFtH/BPodzpw7EzgmIkd3t54QIKlEzmlv2Ss2nVEfyksER5+cPCwEkDZCFc4wKdi4WtnfwCIaoSlKDMFJ/djr/f+T/vDP0ESLEUuFpHxpOQCpo79DIeUZSHTbkFju5umgscLtUDJP8Zn0CWhA8EvJXTwVwDAFrE8fIVQZ+IvWKKUEgLYvoQ3GV22+aCcEupV0LEICwBcPKYnjj9nNnDxW8BZj8vm/2SDBEsnckxhBrrlpMLp9uKHXeQ3iBr+Z7NcsKTmsDw6ANGSgtUeFmHJiUJZs5rpI5j59r2f9oav1JEqKMq8zPMiRmHEu8Vswhip38J3lBaKD2rT7Yg/xm87khWTFEXhpttDWwAAW73l4XuwdCYBXqXoVAlxTpPmlH3ySzV2RSkldDRBgqUTEQQBp1SwL/jnm3T27iDCY/fLcatNrBVTgT8tx96z30YDWEdJmyW6X/vJg0uQZjOjsrYVP+4O02dHirCUgxkKhQ4YbtVww943lG6MDzy6BwDDZ8RvO5IVtelWFOV+NjvE0ohLemOCfzVYFCMsAHDmMHby8822w3LTuN5RiLAcLZBg6WSmDGbljkt/PUB+g2gREGHxEwFlI1GTORhAdNNB8svZLfi91Kr/rbV7Qy8sCZYSgQkbc5TO0CYOYDvOVTuPoKHNFZV1EgYYNB3I7wdMur3Dw/C6JGoh0LBXbgBZKZZE1JY+ZqhTQvZswJYGl9eFg60Ho7L6XgXp8jBEACjKtCPdnkAenjhDgqWTGXtMPrJSLDjc7Ah/Nk7oI1hKSEVtc8daXIfj/FHM4PvRhv1odbqDL+g3mVlI71iFEKd3QTr6FWXA7RWxfEt0dp6EATKLgevXAiffFO8tSU5saYpoqfoBAFBnzkcLUpHXwenqUUUtWHqPAwD869t/4dS3TsWdP9wJl6fjJwvnjlKKBU7uG50I7NECCZZOxmo2YdIgVrL90QYdJk0iPP6CpSRw9AMPr8YiwgKwxoA989PQ4vTg019CDAL1rwjqQJdbf06TvldLf6V0I5GE8PL+qpUAgL0mVnqbF6PfbESoy9cHnIHKhkp8uutTAMAbW97Aok2LOvwSFx/fA09ffCzeueZE3H/+8A6v72iCBEsc4C3dP1i/H+0uqhbqMGa/kHG3YwMWUaaexmbnJwgCzjuWnRm99WOI2Vah/DYdZLKUbvxy80G0OEJEeQgiEeGRUSnCslNkadb8jAQSLC7VTJ7+U/Da5td8Hn5jyxtwezv22zOZBEwdWopRPXMj7nB7tEKCJQ6c1LcApdkpaGhz6R+cR+jDmq45Np2nhPJiuPM7d1R3CALww84jctOnAPxSQtHsiDqsezZ6F6SjzeXBZ7+GiPIQRCLCBYvUNG6ri/02EirCcszvALOdjR5Iy8MXu78AADwy8RHk2nNR01KDFXtXxHkjj15IsISgwdGAm766CRd/fHFUB8uZTQLO5Wfj4UyahDGKB2vezSMssUoJAUBZTipOkZoDLvy+Unshf8ESZHsjQT2QUXfnXYJIFGQ/F9vXbpIESyx/s4bJKQf+XgmctwDt7nYcbGN+sVFFozC933QAwMc7P47f9h3lkGAJQZolDcuqlmHD4Q2obY9u3xRurPpm2yHUNLRHdd1dEp5bHnmx5sO1LbFNCXEuP6k3AOCttXvQ2K5hwFMJFqdgA/KiOyflHGlUwLfbD2PPkdYwSxNEAuFnlt8llsBsEhKrDwvADMJmK/Y3Mw9ihjUD2fZsnNrjVADAD9U/dDgtRGhDgiUEVrMVJenMF7C3KbqRkN4F6TiuVy68IvDOOoqydJgrvwDOegI49lLNh4+0sGnKsc6Hj+tXgP7FGWhxevDmGg0vi0qw1NtKlf4TUaJHfhrG9SuAKAL/XbU7qusmiJiiEiyiYMFesRC5aTaYIvRxvPjLizj1zVPxr2//hfr2+ihtpMLeZrbf7pbRDYIgYEj+EGTZstDkbMLGwxuj/noECZawlGeyAXp7mkIYKSPk/FFs3a+vqaKeLB2laABw7CVBW6If4R6WGJdICoIgR1le+q4Sbo/XdwGVv6Y5JTYTUy85oScA4M01e8jUTSQPKsHSltkDblgiTgc1O5vx7IZncbDtID7c8SHmr54fra2U4Sex3TNZtNxsMmNs2VgAwHf7v4v66xEkWMLCv4xcTUeTM4eXIifNij1H2qjzbQzxeEUcaGIRluKs2Pd0mD6yG/LSbdhX34ZPN/qZX1WCqi01NoLl1IHF6J6birpWF95cG32hTURGY7uLBGQoVFPLG9KY6I7UcPvxzo/R5m6T//5k1yfYfGRzx7bPD3WEhXNS2UkAgO/2Ja9gaXQ2YsHGBZi3ch5qWhLLvE+CJQzdMyTBEuWUEACk2Sy4eEwPAMDz3+yMqrGXUDjU5IDHK8JsElCUmRLz10uxmnHp2F4AgAeXboHLP8oicbD45Ji8vtkk4M/jmTfm2RU7g74+0Tk43B7c8b9fMfyOpRh06xLMeWN96OaCXRVVhOWwnUWfI63qe3/7+wCAvx/3d0ztNRUA8Mi6R+THv6r6Cm9uedNH1BhlXxMztvOTWgA4sexEAMDGwxtR1558jUFFUcTsZf+/vfuOj6rKGz/+mZ5Mem8kJECI9AhIiDQVpIht190fKrsguLIqKKxtEQsr+iy6ioLuKrrWZ1dF2YeiLiAYpClEqpRAICGQEFJI75lyz++PIUOGJKSQZCbxvHnNa2buPblzDmfK9557yjze2P8Gq0+u5tGtj1JjcZ0+ljJgaYa9haUDAhaAmYnR6LVq9p8tZleaXLiuI5wvtX0phXgZOm1eg/vHxBDoqedMYRWfJWc67PtL8AqeNc+iOGpSh73+b4dHEuhpILukWrayONnLG0/w0Q9nEAIUAWsOZnP3e3uokHPlOKoXsJzX2L5323JJyGw121tTxkeNZ96189CqtPyQ/QM7zu1gye4lPPr9o7y450VuX3c7ORU5bcpuYy0sIR4hxPrFIhDsydnTpuM604H8AxzMP2h/frzoOCt/XunEHDmSAUsz7C0sHXBJCCDY283eyvLa5pOylaUD1I3CCvNtOD9LR/E0aFkwoS8AK5JOUV5vxNBBEcu/rTfj5d5xHYDddBrm3dgbgOXfnZJn9E5yKq+c/91t6/z893uv5Ys5I/Ez6jh8rpQ5/7tP1kt99S4JncF2ubQtl4TOlJ3BIix46jwJ9QglyjuKu/reBcDcpLmsPrkaFSoC3ALIrczlpeSXWv29K4Qgu6JhCwvA6HBby+mu7F2tzruzfXLMNlPvb/r+huU3LgdgVeoqykxlTszVJTJgaUbdmzG/Kp9aa22HvMbDN/TBXafh56wS/rNfjhhqb+dLbC0soT4dfzmovmnXRdIryIOiShNvb0u3by+9OCeMl1vHLmp2b0JPovyNXCivZcV3pzr0taTGLU86hVURTOwfwq2Dw0noFcAns0fgodfwY3oh97y3h12nCsgvr0H5pXe81+ohqB/ovUix2k7i2tLCklZiW+m5t29vVBf7jD1y7SMkhtk6xPoYfHhnwjt8OOlDdGodO87tYFvWtla9RpmpjEqzbXLIMA/HvmijIi71Y1FE17kcW1BdYJ/07vf9fs9NkTfRx7cPleZKvkz90sm5s5EBSzN8Db546GwLXtV9ENpbkJeB+RNiAfjrhuNcKO+YwOiXKudiC0t4JwcsOo2ap6f0A+CfO06TmltOWY2ZsxfnR+kT7HmlP79qeq2axbf1t73+ztP8nFXSoa8nOSqtNts70z86Pta+fXAPX/73/gR83HX8fK6U332QzIj/SaLvsxsZ/cpWlnyd8sv9Drh/Mzx6gDOVtmA+xLv1n9m67+k+vn3s23wMPrw38T1W37aar+78ilERo+jl24sZ/WcA8O7hd1vVypJXZatXX4Mv7lrHlttrg6/FqDVSWFPI8aLjrc6/s2zK2IQiFAYHDaaXby9UKhWzBs4CbEsOWBXndxiXAUszVCqVPTLvyCjz/tExXBPqRXGVmT99cUgOc25HORf7sIT5dN4loToT+gVzc/8QLIrg6TWHOZRZghAQ6e9OoGfHj1ga3y+E24eEowiY+9kBSquufjVZqWU2HMnBZFGIC/FiQLjjGlLDevrxzSOjuWdEJKHebqhVYFEE54qr+fCHDKas2PnLXM3dzRs8gzlfdxm3DZ/ZtOKGAUuda/yvwd/N3/58xoAZuGncOFZ4jN05u1v8GnmVtoAlxNhwaQ29Rs/IsJEA7Dy3s1V5d6avT38NwK29brVvmxQ9CV+DL7mVuS5xiUsGLC0wc4BtMrKv07/mQtWFDnkNnUbNW/dci7tOw660Al76b4rsz9JO7C0svp3bwgK2gHfJHQPwNGg5kFnCE6t/BuDaSL9Oy8OLdw4kyt/IueJqHvp0P7UW558p/RKsP2Tr4/CroRH2SxP1RfobWfrrwexZNJ6TL01h99M38f6M4fQN8aSgopbfvZ/MgcxfXtBisigUVNhamMLa8JlNL7Vdfu3t27vZtP5u/vym728AeP/I+y1+jboWlhCPxtcCG9NjDAA7s7tGwLIrexcphSlo1VomRV8aDGDQGLij9x0ArD652lnZs5MBSwvEB8cTHxSPWTHzxv43Oux1YkO8+NtvBgO2Scfe2CI74baHnBJbwBLqhBYWsJ0lPjU5DoD8i03910b5dtrr+7jrWPm7YfZ+E3M/PSjnA+lglbUW9p2xBRtTBoY2m16rURPm486E/iGsfXgUY2IDqTZbmf3x3l/cEgt5ZTUIYbuk2do+LDWWGjLLbKPyYv1im0ltM3PATLRqLXtz93Io/1DL8ljVdAsLwJgIW8By5MIR8qvyW3RMZykzlfHa3tcAmH7NdIcWKMAe0O3M3tnmEVXtRQYsLfTUdU+hQsXXp7/u0Kax24aE8+xUW7+HN7em8cTqw3L441UwWRTyy53Th6W+6Qk9uTHu0rDNa6M6r4UFoH+4N+/NGI5eq+a743n87v1k8spcZ36F7iY5oxCLIoj0d6dngEer/tbDoOXd3w9jcA8fSqrMPPzpgV9UgJljvxzk1mjL1JVklGYgEPgYfAhwC2j+D4BQj1Bu73070PJWlitdEgJby0t8UDwCweYzm1t0TGfIrczl7m/uJr00HV+DLw8MfqBBmmifaBJCE1CEwv+d+j8n5PISGbC00KCgQdx9zd0ALNy5sMPmZQH4w5he/OW2/qhVtnWGblmxk71nijrs9bqzU/nlKAK83bQEeXV8n5GmaNQq3p4+jMkDQhnXN4iBl/Vp6Ayj+gTyyawReBm07DtbzKTlO/j8p0w5OqUD7DplWyx1dJ+gZlI2zqjX8s7vhuFn1HEku5Ql36S0Z/ZcWl2fs9Cr7HDbmmBn9sDZqFVqtp/bTmpRarPpm7skBDA5ZjIAG89sbHE+OpPJauLxbY+TVZ5FuEc4K29eiY/Bp9G0v437LQBrTq3BrDivH5wMWFrh8eGPMzBgIKW1pcz/fj5V5o5rqr1vVAyr5iQS4etOZlEVv125m0c/P0h2SdtnZvwlOnbeNn9A/3DvVp+ttTd3vYaVvx/GJ7NHoNU0/OjtOLeDl/a8xCfHPsFkNXVIHhJ7B/DVI6MZEO5NSZWZp9cc4dfv/MjR7NIOeb1fqh8uTgI5uk9gm48R4evO8ruvRaWCz5IzWfMLWST1Up+zNnS4bWSEUEv09O7JxJ4TAduiic1proUFYGLPiahQcfjCYc6Wud5CpKtPruZwwWG89d68P+l9BgQMaDLtTZE3EegeSKxfbIcsJNlSMmBpBYPGwBs3voG/mz8ni0/y3A/Pdeg4+xEx/myYP4a7r4tEpYKvfj7P+GXbeH1zKqXVcrRHS6RcDFgGhDd+5uAqNpzewNykuXyR+gWv7XuNe/97b4d9McQEerB+7iiev7U/ngYth7JKuP3vu3h+/VH5vmoH+WU1pOaVo1LZAsSrMa5vEPMvDoletPYIJ3JdYwKvjpRTUjeqr32GNLfUHwb9AYBvz37bbIBR18IS6tF0/6QgYxCjI2yTyK06sarV+eloX6V/BcDD8Q/bF/ltik6j4+s7v+bdm98lyNi2VsP2IAOWVgr1COWNG95Aq9ay+exm3j70doe+no+7jpfvGszX80YzIsafGrPCm1vTGP3yVl77NpWiyo45E+8uUnIutrCEdf4lmJYqqC7gpeSXANuZjL+bP6nFqTz6/aMd1tKi1aiZPTqGpMfH2Yc9/+/us4xfto01B87Jzt5X4Yd0W+vKgHDvNi/eV9+jN8Uytm8QNWaFh/59gLKa7h1Unq/Xh6W1rjSkuTlx/nGM7TEWRSh8ePTDJtNVmCqoMFcAV25hAbi3372AbW2juonmXEFacZptVJBKyy0xt7Tobzz1HTtvVEvIgKUNhoYM5fmRzwO2CYe+Of1Nh7/mwAgfvpgzknemD6VviCfltRb+/n0ao1/ZylI52VyjFEVwvN4lIVe1OnU15aZy+vn347UbXuODiR/gpfPiYP5BXv7p5Q597RBvN96851o++0MCvYM8KKgw8diXPzPtvT2k5pZ36Gt3V1fbf+VyarWK5dPiCfdxI6Ogkgf/tb9bT+l/vqRt8yZVmis5X3keaFvAAvDAIFun03Vp6zh84XCjaTLLbaOQfAw+GHXGKx7v+vDrifaOpsJcwWfHP2tTnjrChowNgG34tZ9b5w4AuBoyYGmjX8X+yj4L4OIfFrd4ONzVUKlUTBkUxqb5Y1n5u2EMCPemymTl3R2nGfO3rbzw9TH7ujkSpF2ooLzWgl6j7vBZZdtKEYp9ZdmZA2aiU+vo49eHV8e9igoVq0+uZn3a+g7Px/V9Atk4fyxPTY7DXafhp4wipr65k0Vrj/BjWoFc8bmFhBDt0n/lcv4eelb+/tLQ9Lvf29MthztbrApp+bbWi15BrRtdVbfYYLhHOL5uvm16/fjgeG7tdSuKUHj2h2cb7ad4tOAoAP39+zd7PLVKzYNDHgTgw6MfOrX/R33bzm0DYGL0ROdmpJVkwHIVFgxdwE2RN2FSTDy69dEW9S5vD2q1iskDQ/nmkdF8eN9w4iN9qTErfPTDGcb+7XueXnOYvWeKfvGjP9YcsE3cNbZvILpGOrm6gr25ezlfeR4vnRfjo8bbt4+KGMVD8Q8B8OKeFzle2PFTfOu1ah6+oQ9bHhvLxIuz836WnMm97yczdMkWfvd+Mss2p5J0PI/Ciqtr0asxWzlTUMmWlDz+vvUU8z47wN3v7eb+j/fyt00n+CGtAJOl6wVJqXnl5JbVYNCqGR7dvmeug3v48q8/JOB7cfHEW9/axeZjue36Gs52prCSWouCUa9pcjh4VlkWO87t4FjBMYfp4uuGD4/vOb7Rv2uphSMWEuQeREZpBs/+8GyDfop1LS+Dgga16HhTYqYQ5xdHhbmCV/e9elV5aw/nK85zqvgUapXaPl9MV9Gxq691c2qVmqVjljLr21mkFKYw+9vZvHfzewwIbLq3dXtSqVTcdE0IN8YFsyutgLeS0vjpTBGf/5TF5z9lEe7jxm1Dwrm5fwjxkb6NjkzprixWxT6q4jfDrtyhzJn+e/q/AEyKmYSb1vGa/R8H/5HDFw6zK3sX85Lm8enUT6/Yya+99PAz8t6M4fyQVsC6g9kkncinqNLErrQCdl1sPQCI8jcSH+nL8Gg/rov2J9LfiEalQiAorjJTVGGisLKW8yU1nC2s5GxhFVnFVeSW1lB4hb5XSSfyeXtbOka9hut7B9I72AMPvRY3nRqtWo1RryHCz51IPyPhvu7ota7zvt56wjZJ2PW9A3DTadr9+EOjbFP6z/3sID9nlTDnX/uZPCCU52/r36ZRNa6mblTfNaFeaNSOo/rKTeUs2rXIYaHCALcA7up7F7f1us2+cF/daJ+28jH48PoNrzPr21lsObuFJbuX8NzI59CobfVZ18IyKLBlAYtapebZkc8yY+MMvkr/ihsjb2RCzwltyltKYQqfHPuElMIU/Nz8GBk2krti77ri8OrL1f0/xQfFNzmM2VWpRDfoXVdWVoaPjw+lpaV4e3d+X4XS2lIe/u5hDhccxlPnyUujXrrqKL+tkk8Xsnr/OTYdzXWYcM7HXcfgHj6EershsM3EWVFrwWxVCPZyY3APHyYNCCXS/8rXZLuK9Yeymb/qEH5GHcmLJjT6o5ZVnsXGjI1cqLpAgHsACWEJDAkaglrVOT+AZquZcV+Oo9xUzoeTPuS60OsapCkzlTFjwwzSS9OJ8orig0kfdErQUp9VEZzILeNQVgmHMks4mFVib7a/Ggatml5BnsSFeBIX6k24rxtlNRYOZhaz42SBfXr2K1GrbH0d+oV5MTzan5G9Ahgc4YNa7Zwh7P9v5W5+OlPEkjsGMCMxusNex2RReG1zKh/sysCqCNx1Gh4dH8v9o2NcKoBrraUbj/Pu9tP8bmQUL915KSCoNFcya9MsjhcdR61S08e3DzkVOZSbHftZhRhD2Pybze3yGd6YsZGFOxeiCIWxPcbyP6P+B61ay/WfX49AsO3/bSPAveWjwF7f9zofHfsId607H036qNUntqtPruave/6KRTj2XzJoDEzvN537B92Pt77537/Z385mb+5e/jTsT8weOLtVeegIrfn9lgFLO6k0VzIvaR778vYBtumMnxz+ZLOdsjpKjdnK9yfy2XA0lx0nL7R4uOqoPgFMT+jJpAGhDc5wuooqk4Xxy7aTU1rD4zf35ZHxjlN0WxUr7x5+l3cPv9uguTfcI5xbet3C1JipDsvTd4TtWduZt3UeQe5BbPnNFvsZ3OVyKnKY9e0ssiuyCXYPZtkNy4gPju+wfLVEabWZw+dKOJhZQnJGIYfPlVJec+mLVKtWEeCpx9/DQKi3gZ4BHkQHGIkKMBLm406Yjxs+7rom/38VRZCSU8autAIulNdSZbJQY1YwWxUqai2cK64mq6iK2kYuGwV6Ghh/TTDj+wUzOjYQo75zGpKLK00M/5/vsCqCnU/d2CnB/4ncMp5bd5S9F5cBiA4wsnBKPyYNCHH6vENt8fsPktl5qoC//moQ9yZEAbZ+QU/ueJJvz3yLv5s/b094mwEBAzArZrZmbuVfKf/i5ws/E+UVxZJRSxgWMqzd8rPpzCae3fUstdZa/N38UavUFFQXEOEZwaa7NrXqWGbFzLykefx4/kc8dZ68ceMb9kUSm5N0Nok/bfsTAsGEqAnc1fcuLlRdYM2pNRy6cAiwtQw9MOgBpsVNa9BaWyerLItb1t6CChXf3vUtYZ5hrSpDR5ABi5OYrWbeOvQWHx/9GIHAz+DH7IGzmXbNtAZLkHcmi1XhSHYpqbnlFFWZUKHC06DBw6BFo1aRXVLND2kF/JheSN27ITrAyANje3HX0B4d0rTdkV7fcpI3k07Rw8+d7x4b55B/i2LhmV3P2HvJjwwbyeCgwWSWZbIre5d9uCLYFkYbGDiQOL84+vr3pa9vX6K8o9Cq2+cH8E/f/4nvMr9jer/pLByx8IppcypyeOi7h0gvTUetUjMtbhqzB87u9NaWpgghqDErKBffQEa9psN/MIUQXKio5WxhFYcyS/jpTBG70wsdWhb1WjWDInwYFOHDwAgfBvfwoXeQZ4cE428lnWLZlpP0D/Nmw/zO6xsghOD/DmTzyqYT9tGCgyJ8+MOYGG4ZFOay/bcuV1lr4fqXt1JabWbtw9fbl6/49PinvPzTy2hVWj6a/FGjwXpJTQmees92+2zWl1KYwqKdi+yLKgK8OOpF7uxzZ6uPVWGqYN7WeezP248KFff2u5c5g+c0WL+nvsMXDnP/t/dTY61hWtw0nkl4xv7ZEkKw/dx2lu9fbs9foHsgswfO5s4+d+Kl93I41ooDK3j/yPuMCh/FyptXtjr/HUEGLE6WnJPMkt1L7MPfPHWeTIqexNReU4kPjken1jk5h43LKqrii71Z/GvPWXuLTKCnnjvjI/j10B70C/Ny+bO2c8VVjF+2nVqLwjvThzJl0KUziPrBilal5YVRL9jXEAHbwmnbz23nm9PfsCt7Fxal4dBRvVpPb9/e9AvoR3///vQL6Edfv75NntE0JbMsk1vX3opAsPb2tfTxa34YZqW5khf3vGjv96JRaZjYcyKToieRGJ7otNY8V2KyKCRnFJJ0PJ/vjudxrrjhzNDuOg19gj3xMGgw6rXoNWq0GhV6jRqjQYOfUY+vUY+fUYevUXfxsd6e3qjTNLjkVFRpYvyybRRXmVlxdzx3xEd0VpHtKmotvLs9nX/uPE2N2dby5O2mJbF3ACNiAugV5EGvQA8ifN2d0p/NqgiOZJeScr6MvLIaiqtM6DRq3HRqvNx0HM0u5ZvDOfTwc2fr4zeg16o5mH+Q2d/OxqJYeOq6p/h9/993er7BNo39urR1bD67mTt638FtvW9r87FqLDX8NfmvrE1bC4BOreOGyBuY2msqCaEJDvOdnCg6wZzNcyiuLWZMxBjevOnNRoMyi2Lhq/SvePfnd+1Duw0aAzdG3shNUTdxXeh15FflM3PjTGqsNSwbt8xlRgh1eMDyj3/8g1dffZXc3FyGDBnCW2+9xYgRI5pMv3r1ap577jnOnDlDbGwsr7zyCrfccmmyGiEEixcv5p///CclJSWMGjWKd955h9jYlq226WoBC9jeQF+nf80/j/yTrPIs+3aj1sjw0OEMCBhAnF8ccf5xhHuGd1q/iZaorLXwxd4s3t952j6JE9gmchrZK4BBET70Dva0f/k5q7/A5YQQ/OGTfSSdyGdkL38+f2CkPcCqtlTzzK5n2HJ2C1qVltdueM1hVM7laq21pBalcqTgCKeKT3Gy+CRpJWlUWxr+AGpUGnr59qK/f3/i/OOI8YkhxieGMI+wRutVCMGfd/6ZjRkbGRMxhrcntG7ywd3nd/PBkQ9Izk22b9Or9QwKGsTQ4KEMCBhAjE8Mkd6RLhscdwYhBKcLKjl8roQj58o4ml3K0fOlVJmufiFBN50ao16Lu06DWg3FlWYqai1EBxhJevwGp15OLayo5d97MvnXnjMUVDTs3KzTqIj0MxIT6EF0oAcx9W6h3m7t/nmutVj5955MPtyV0aKlRT68bzg3XRPC8cLj3L/5fspN5dzc82aWjVvm8idMrfHj+R9568BbHC08at+mVqnp79+f/gH9sQorGzI2UG2pZkDAAD6c9GGzJyVmq5l16ev4d8q/OV16utE0oyJG8fb4t13mN6dDA5YvvviCGTNmsHLlShISEli+fDmrV68mNTWV4ODgBul//PFHxo4dy9KlS7n11lv57LPPeOWVVzhw4AADBw4E4JVXXmHp0qV88sknxMTE8Nxzz3HkyBFSUlJwc2v+zNUVA5Y6ilDYn7ef9Wnr2XFuB8W1xQ3S6NQ6Qj1CCfcIJ9gYjLfBGy+9F956272b1g2D2oBeo0ev0WPQGDBoDPbH9bfp1E33C2gts1VhW+oF1hw4R9LxfEyNzMWh16qJ9HMnyt9IlL+RyIu3ngG2553VfwBg1U+ZLFxzBL1GzX8fHU1siBeV5kp2Zu/knUPvcLr0NFq1llfHvtqmXvqKUMguz+ZE8QmOFx4npSiF44XHKappfGFKvVpPsDGYYGMwIcYQgo3B+Lv7c6LoBBszNqJWqflk8idt7o+SUpjC1+lf833W92RXZDfYr1VpCfMMI8g9iED3QIKMQXjqPDHqjBi1Rjx0Hhi1Rty17ug0OvQaPTq1Dr1ab3+v6dQ6h8eu8iXXVlZFkFFQwZmCKqrMVqpNFsxWgdmqYLIoVNZaKK4yU1JtpqTKREmVmeKL95UmC1f6tuwb4snyadcSF+rB6dLTHCs8xtGCo6SXpFNcU0ypqRS1So1BY8Bd6277/79YF1q1Fp1ah06tsz9207rhqfPES+9lv6977Km3PTdqjU1+3utaNHadusCR7FLOFFSRUVh5xeHiBq2a6AAPwnzdCPV2I8TbjTAfN0J8bPeh3lfue3S5rSfyWPJ1CmcKbfOZeBm0DIv2I9zXnQAPPWaroNpkobzWQlm1mWuj/JgztidfnvyS5fuXU2OtYUjQEN67+b1u24KYWpTK+vT1bM/abm+Vr++60OtYceOKBpd3rkQIQUpRChtObyA5J5nUYtuUG8NChrHixhUuNTqoQwOWhIQErrvuOv7+978DoCgKkZGRPPLIIyxc2PA6/LRp06isrOSbby7NBjty5Eji4+NZuXIlQgjCw8N5/PHHeeKJJwAoLS0lJCSEjz/+mLvvvrtdC+xMilA4UXSC/Xn7SS1KtZ+1t/fql1q1Fo1Kg1qltt+ael6XVqPWoFVpbfsuPq5/r0JDebVCSZWFihpBRa1CZY2CVVEB9b+8VA737joN3m46PAxadBrbsFStWu2QRsDFHwKV7YnDcRo+VqsEKpVApQKVSqBWQVlNLafyy0FlpleogsGtnLyqPMpNl0YR+Lv5s2zcMoaHDm+f/2hsXwx5VXn2ACa9JJ2M0gzOlp1ttl6fTXiWaddMa5c8nCk7w/68/RzMP2jPQ5Wl/ScW06q0qFQqVBfrpO5x/R+w+s8v7rVXYWNp66v/vKkfxbpj1L9Xq9QNtl++rS7YUqlUqFE7pr3sef30atWlfUKoUISw3SsgLr5n1Wo1HgYNuZU5ZJZlYlI6Z8kMtUqNh84DD50HerXeIeDRaXT2IEin1tk7ddeaBVUmK5UmK1W1VirrbibrZZ9Dx8+yuHivValxv9i65KHX4m7Q4qHX4aHX4mHQotdoqKi1cDynnHNF1aBScNfDgAhPIvz0CKxYFIvtJixYFStWYdtmFVZOl5y2j/4ZFTGKv439W4tGv3QHuZW5HMg7QFpJGopQGB46nFHho676JLS01ra4qSsFKnU6LGAxmUwYjUb+85//cOedd9q3z5w5k5KSEtavbzgjZ1RUFI899hgLFiywb1u8eDHr1q3j559/5vTp0/Tu3ZuDBw8SHx9vTzNu3Dji4+NZsWJFs/nqKgFLYyyKhQtVF8iuyCanMocL1ReoMFVQZiqjzFRGuamcWmsttdZazFaz/bHJanK4F3T5rkgdJsIzgltibuG+gfd12hefRbGQW5lLflU++VX55FXlkV+VT3FNMV562yRxI8Kavox6tYQQ5Fflc67iHBeqL1BQVUBBdQGV5kqqLFVUmavs99WWakyKCZPVhNlqtj82KaZG+/FIzTNqjfQL6MfAgIHE+ccRZAzCR++DQFBrraXaXE2lpdJWH+Yq+4933Q+5WTFTbamm3FROhamCcvPFe1M5FeYKKkwVDYa3difB7sH8ccgfuSv2riZHz0ndQ2t+v1vVXl9QUIDVaiUkxHGSmpCQEE6cONHo3+Tm5jaaPjc3176/bltTaS5XW1tLbe2lORrKyrruCqZata3Z/mqGlwkhsCiWS4GNYkYRClZhRQiBVVibfK4IxX5mc/mZjlWxNnoGZFWs9i9YRSj2hfLExX91sVO12WJrVq82U15jxmxVsCgKFquCwNY6ArbzN9sJxMU/rP+Y+o8vhmVChSJU9rNcRYBBqyU6wJPYYB+C3IMI8Qgh1BhKsDHYKYt2adVaenj1oIdXj05/bbC1IoR4hLRqQqnGKELBrJhtAYzVhFkxN6xvbO9Be9AsuLQd4bDPIbC+LMauv6/+edTlwXjdUPS6YysoIGzbBcK+//LndWmFuJSnujRNPW/J8eunDTYG2/svdeQPrRCCGmuNPZipC3rMihmz1Wy7r3+zmrEoFnudOdSJuMK2y/7/zFYr5bVmymsslNeYqag1X7y3UFFruzdZrLjrNET62+Z3CvB0t7f6aFVatGrHm0alcWjpDXIPYkDAABmoSA10yZluly5dygsvvODsbLgMlUpla/7V6PDENdfMkbqmuj4XBo3B2VmR6lGpVLhr3XHXuhNE+yyyKEmurlU96AIDA9FoNOTl5Tlsz8vLIzS08fkgQkNDr5i+7r41x3z66acpLS2137KyshpNJ0mSJElS99CqgEWv1zNs2DCSkpLs2xRFISkpicTExEb/JjEx0SE9wJYtW+zpY2JiCA0NdUhTVlZGcnJyk8c0GAx4e3s73CRJkiRJ6r5afUnoscceY+bMmQwfPpwRI0awfPlyKisrmTVrFgAzZswgIiKCpUuXAjB//nzGjRvHsmXLmDp1KqtWrWLfvn289957gK1pc8GCBbz00kvExsbahzWHh4c7dOyVJEmSJOmXq9UBy7Rp07hw4QLPP/88ubm5xMfHs2nTJnun2czMTNTqSw03119/PZ999hnPPvssixYtIjY2lnXr1tnnYAF46qmnqKysZM6cOZSUlDB69Gg2bdrUojlYJEmSJEnq/uTU/JIkSZIkOUVrfr+79rSVkiRJkiT9IsiARZIkSZIklycDFkmSJEmSXJ4MWCRJkiRJcnkyYJEkSZIkyeXJgEWSJEmSJJcnAxZJkiRJklyeDFgkSZIkSXJ5MmCRJEmSJMnltXpqfldUN1lvWVmZk3MiSZIkSVJL1f1ut2TS/W4RsJSXlwMQGRnp5JxIkiRJktRa5eXl+Pj4XDFNt1hLSFEUzp8/j5eXFyqVql2PXVZWRmRkJFlZWd12naLuXsbuXj7o/mXs7uWD7l/G7l4+6P5l7IjyCSEoLy8nPDzcYeHkxnSLFha1Wk2PHj069DW8vb275Ruwvu5exu5ePuj+Zezu5YPuX8buXj7o/mVs7/I117JSR3a6lSRJkiTJ5cmARZIkSZIklycDlmYYDAYWL16MwWBwdlY6THcvY3cvH3T/Mnb38kH3L2N3Lx90/zI6u3zdotOtJEmSJEndm2xhkSRJkiTJ5cmARZIkSZIklycDFkmSJEmSXJ4MWCRJkiRJcnkyYGnGP/7xD6Kjo3FzcyMhIYGffvrJ2Vlqk7/85S+oVCqH2zXXXGPfX1NTw9y5cwkICMDT05O77rqLvLw8J+b4ynbs2MFtt91GeHg4KpWKdevWOewXQvD8888TFhaGu7s7EyZM4NSpUw5pioqKmD59Ot7e3vj6+nL//fdTUVHRiaW4subKeN999zWo08mTJzukceUyLl26lOuuuw4vLy+Cg4O58847SU1NdUjTkvdlZmYmU6dOxWg0EhwczJNPPonFYunMojSqJeW74YYbGtThgw8+6JDGVcsH8M477zB48GD7RGKJiYls3LjRvr8r1x80X76uXn+Nefnll1GpVCxYsMC+zWXqUUhNWrVqldDr9eLDDz8Ux44dEw888IDw9fUVeXl5zs5aqy1evFgMGDBA5OTk2G8XLlyw73/wwQdFZGSkSEpKEvv27RMjR44U119/vRNzfGUbNmwQzzzzjFizZo0AxNq1ax32v/zyy8LHx0esW7dO/Pzzz+L2228XMTExorq62p5m8uTJYsiQIWLPnj1i586dok+fPuKee+7p5JI0rbkyzpw5U0yePNmhTouKihzSuHIZJ02aJD766CNx9OhRcejQIXHLLbeIqKgoUVFRYU/T3PvSYrGIgQMHigkTJoiDBw+KDRs2iMDAQPH00087o0gOWlK+cePGiQceeMChDktLS+37Xbl8Qgjx1Vdfif/+97/i5MmTIjU1VSxatEjodDpx9OhRIUTXrj8hmi9fV6+/y/30008iOjpaDB48WMyfP9++3VXqUQYsVzBixAgxd+5c+3Or1SrCw8PF0qVLnZirtlm8eLEYMmRIo/tKSkqETqcTq1evtm87fvy4AMTu3bs7KYdtd/mPuaIoIjQ0VLz66qv2bSUlJcJgMIjPP/9cCCFESkqKAMTevXvtaTZu3ChUKpXIzs7utLy3VFMByx133NHk33S1Mubn5wtAbN++XQjRsvflhg0bhFqtFrm5ufY077zzjvD29ha1tbWdW4BmXF4+IWw/ePV/GC7XlcpXx8/PT7z//vvdrv7q1JVPiO5Vf+Xl5SI2NlZs2bLFoVyuVI/yklATTCYT+/fvZ8KECfZtarWaCRMmsHv3bifmrO1OnTpFeHg4vXr1Yvr06WRmZgKwf/9+zGazQ1mvueYaoqKiumRZMzIyyM3NdSiPj48PCQkJ9vLs3r0bX19fhg8fbk8zYcIE1Go1ycnJnZ7nttq2bRvBwcHExcXx0EMPUVhYaN/X1cpYWloKgL+/P9Cy9+Xu3bsZNGgQISEh9jSTJk2irKyMY8eOdWLum3d5+ep8+umnBAYGMnDgQJ5++mmqqqrs+7pS+axWK6tWraKyspLExMRuV3+Xl69Od6m/uXPnMnXqVIf6Atf6HHaLxQ87QkFBAVar1aECAEJCQjhx4oSTctV2CQkJfPzxx8TFxZGTk8MLL7zAmDFjOHr0KLm5uej1enx9fR3+JiQkhNzcXOdk+CrU5bmxuqvbl5ubS3BwsMN+rVaLv79/lynz5MmT+fWvf01MTAzp6eksWrSIKVOmsHv3bjQaTZcqo6IoLFiwgFGjRjFw4ECAFr0vc3NzG63nun2uorHyAdx777307NmT8PBwDh8+zJ///GdSU1NZs2YN0DXKd+TIERITE6mpqcHT05O1a9fSv39/Dh061C3qr6nyQfeoP4BVq1Zx4MAB9u7d22CfK30OZcDyCzFlyhT748GDB5OQkEDPnj358ssvcXd3d2LOpLa6++677Y8HDRrE4MGD6d27N9u2bWP8+PFOzFnrzZ07l6NHj7Jr1y5nZ6VDNFW+OXPm2B8PGjSIsLAwxo8fT3p6Or179+7sbLZJXFwchw4dorS0lP/85z/MnDmT7du3Oztb7aap8vXv379b1F9WVhbz589ny5YtuLm5OTs7VyQvCTUhMDAQjUbToCd0Xl4eoaGhTspV+/H19aVv376kpaURGhqKyWSipKTEIU1XLWtdnq9Ud6GhoeTn5zvst1gsFBUVdckyA/Tq1YvAwEDS0tKArlPGefPm8c033/D999/To0cP+/aWvC9DQ0Mbree6fa6gqfI1JiEhAcChDl29fHq9nj59+jBs2DCWLl3KkCFDWLFiRbepv6bK15iuWH/79+8nPz+foUOHotVq0Wq1bN++nTfffBOtVktISIjL1KMMWJqg1+sZNmwYSUlJ9m2KopCUlORw/bKrqqioID09nbCwMIYNG4ZOp3Moa2pqKpmZmV2yrDExMYSGhjqUp6ysjOTkZHt5EhMTKSkpYf/+/fY0W7duRVEU+5dOV3Pu3DkKCwsJCwsDXL+MQgjmzZvH2rVr2bp1KzExMQ77W/K+TExM5MiRIw6B2ZYtW/D29rY32ztLc+VrzKFDhwAc6tBVy9cURVGora3t8vXXlLryNaYr1t/48eM5cuQIhw4dst+GDx/O9OnT7Y9dph7brftuN7Rq1SphMBjExx9/LFJSUsScOXOEr6+vQ0/oruLxxx8X27ZtExkZGeKHH34QEyZMEIGBgSI/P18IYRu2FhUVJbZu3Sr27dsnEhMTRWJiopNz3bTy8nJx8OBBcfDgQQGI119/XRw8eFCcPXtWCGEb1uzr6yvWr18vDh8+LO64445GhzVfe+21Ijk5WezatUvExsa6zJBfIa5cxvLycvHEE0+I3bt3i4yMDPHdd9+JoUOHitjYWFFTU2M/hiuX8aGHHhI+Pj5i27ZtDsNCq6qq7Gmae1/WDaecOHGiOHTokNi0aZMICgpyiWGjzZUvLS1NLFmyROzbt09kZGSI9evXi169eomxY8faj+HK5RNCiIULF4rt27eLjIwMcfjwYbFw4UKhUqnE5s2bhRBdu/6EuHL5ukP9NeXy0U+uUo8yYGnGW2+9JaKiooRerxcjRowQe/bscXaW2mTatGkiLCxM6PV6ERERIaZNmybS0tLs+6urq8XDDz8s/Pz8hNFoFL/61a9ETk6OE3N8Zd9//70AGtxmzpwphLANbX7uuedESEiIMBgMYvz48SI1NdXhGIWFheKee+4Rnp6ewtvbW8yaNUuUl5c7oTSNu1IZq6qqxMSJE0VQUJDQ6XSiZ8+e4oEHHmgQTLtyGRsrGyA++ugje5qWvC/PnDkjpkyZItzd3UVgYKB4/PHHhdls7uTSNNRc+TIzM8XYsWOFv7+/MBgMok+fPuLJJ590mMdDCNctnxBCzJ49W/Ts2VPo9XoRFBQkxo8fbw9WhOja9SfElcvXHeqvKZcHLK5SjyohhGi/9hpJkiRJkqT2J/uwSJIkSZLk8mTAIkmSJEmSy5MBiyRJkiRJLk8GLJIkSZIkuTwZsEiSJEmS5PJkwCJJkiRJksuTAYskSZIkSS5PBiySJEmSJLk8GbBIkuTSbrjhBhYsWODsbEiS5GQyYJEkSZIkyeXJqfklSXJZ9913H5988onDtoyMDKKjo52TIUmSnEYGLJIkuazS0lKmTJnCwIEDWbJkCQBBQUFoNBon50ySpM6mdXYGJEmSmuLj44Ner8doNBIaGurs7EiS5ESyD4skSZIkSS5PBiySJEmSJLk8GbBIkuTS9Ho9VqvV2dmQJMnJZMAiSZJLi46OJjk5mTNnzlBQUICiKM7OkiRJTiADFkmSXNoTTzyBRqOhf//+BAUFkZmZ6ewsSZLkBHJYsyRJkiRJLk+2sEiSJEmS5PJkwCJJkiRJksuTAYskSZIkSS5PBiySJEmSJLk8GbBIkiRJkuTyZMAiSZIkSZLLkwGLJEmSJEkuTwYskiRJkiS5PBmwSJIkSZLk8mTAIkmSJEmSy5MBiyRJkiRJLk8GLJIkSZIkubz/D2lWma7tEUJeAAAAAElFTkSuQmCC", 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", 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", 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4PHxNTQ3/8MMPi50wd+7cKW4XCoX4P/7xj3xpaSmfnZ3NT548md+2bVtEaS/P8/y8efP4fv368Xa7XVHmq1XKWldXx0+dOpUvLS3lXS4XP3LkyIjyWVra+9e//jXieUJV8rpv3z7+wgsv5AsLC/mCggL+kksu4Q8cOBCxHS3tPXTokO5rWFtby9vtdn7QoEG626jR68DK8+Q17N+/P9+/f38+GAzyPM/zr776Kt+vXz/e5XLxY8aM4T/++GNTpb08T1676dOn89XV1bzT6eQrKyv5M844g3/hhRcU2x177LF8ZWWlqf0PhUJ8z549+WOOOUZ3m23btvHXXHMN369fPz4rK4v3eDz88OHD+dmzZ0d0sf388881933fvn389ddfz/ft25d3uVx8VVUVf+ONN0a8Hx988AF/wgkn8Hl5eXx2djZ/4okn8m+99Zap58JgdCUcz5sM9xkMBsMCDQ0NqKqqwqxZs3DPPfekendiorW1FcXFxXj88cctN7FjMBjmYZ4RBoORFObPn49QKISrr7461bsSM8uXL0fPnj1x4403pnpXGIxuDVNGGAxGQvnss8+wYcMG3HPPPZg4cSIWLlyY6l1iMBhpDgtGGAxGQpkwYQJWrlyJk08+Ga+++mpMs2gYDMbRBQtGGAwGg8FgpBTmGWEwGAwGg5FSWDDCYDAYDAYjpWRE07NwOIwDBw4gLy/PUrtsBoPBYDAYqYPnebS2tqJHjx4RQz3lZEQwcuDAAVRXV6d6NxgMBoPBYMTA3r170atXL93/Z0QwQtta7927VxzzzmAwGAwGI71paWlBdXW14XiKjAhGaGomPz+fBSMMBoPBYGQYRhYLZmBlMBgMBoORUlgwwmAwGAwGI6WwYITBYDAYDEZKyQjPiFlCoRACgUCqd4NxFOJ0OmG321O9GwwGg5GRdItghOd5HDx4EE1NTaneFcZRTGFhISorK1kvHAaDwbBItwhGaCBSXl6O7OxsdjJgdCk8z6OjowP19fUAgKqqqhTvEYPBYGQWGR+MhEIhMRApKSlJ9e4wjlKysrIAAPX19SgvL2cpGwaDwbBAxhtYqUckOzs7xXvCONqhn0HmW2IwGAxrZHwwQmGpGUaqYZ9BBoPBiI1uE4wwGAwGg8HITFgwkiImTJiAO+64Q/f/NTU1ePzxx7tsfxgMBoPBSBUZb2DtrqxevRo5OTmp3g0Gg8FgMJIOC0bSlLKyslTvAoPBYGQsgVAYTjsT/zMF9k6lkGAwiFtvvRUFBQUoLS3FPffcA57nAUSmafbs2YPzzz8fubm5yM/Px6WXXoq6ujrx//feey/GjBmDF198Eb1790Zubi5uueUWhEIhPPLII6isrER5eTkefPBBxT7MnTsXI0eORE5ODqqrq3HLLbegra1N/P/u3bsxZcoUFBUVIScnB8OHD8eiRYsAAI2NjbjyyitRVlaGrKwsDBw4EC+99FISXzEGg8Ew5vPN9Rh6z2L86+vdqd4Vhkm6nTLC8zw6A6GUPHaW026pouLll1/GtGnT8O2332LNmjX47W9/i969e+PGG29UbBcOh8VA5IsvvkAwGMT06dNx2WWXYdmyZeJ227dvx0cffYTFixdj+/btuPjii7Fjxw4MGjQIX3zxBVauXInrr78ekyZNwrhx4wAANpsNTz75JPr27YsdO3bglltuwd13341nnnkGADB9+nT4/X4sX74cOTk52LBhA3JzcwEA99xzDzZs2ICPPvoIpaWl2LZtGzo7O+N8FRkMBiM+pr60GgBw73s/4+oT+6R4bxhmsByMLF++HH/961+xdu1a1NbW4r///S8uuOCCqLfx+Xy4//778eqrr+LgwYOoqqrCrFmzcP3118e637p0BkIYNuvjhN+vGTbcPxnZLvMvaXV1Nf72t7+B4zgMHjwYP/74I/72t79FBCNLly7Fjz/+iJ07d6K6uhoA8Morr2D48OFYvXo1jj/+eAAkaHnxxReRl5eHYcOGYeLEidi8eTMWLVoEm82GwYMH4+GHH8bnn38uBiNyE21NTQ0eeOAB3HTTTWIwsmfPHlx00UUYOXIkAKBfv37i9nv27MHYsWNx3HHHibdnMBiMVLL3SIf4e/8y5rvLFCynadrb2zF69Gg8/fTTpm9z6aWXYunSpfjnP/+JzZs34/XXX8fgwYOtPnS348QTT1QoKePHj8fWrVsRCimVnY0bN6K6uloMRABg2LBhKCwsxMaNG8XrampqkJeXJ/5dUVGBYcOGwWazKa6jbcsB4NNPP8UZZ5yBnj17Ii8vD1dffTUOHz6Mjg7yhb799tvxwAMP4OSTT8bs2bPxww8/iLe9+eab8cYbb2DMmDG4++67sXLlygS8KgwGgxE7767fL/6e6+524n+3xfI7dc455+Ccc84xvf3ixYvxxRdfYMeOHSguLgaQ3BV0ltOODfdPTtr9Gz12KnE6nYq/OY7TvC4cDgMAdu3ahfPOOw8333wzHnzwQRQXF2PFihWYNm0a/H4/srOzccMNN2Dy5Mn48MMP8cknn2DOnDl47LHHcNttt+Gcc87B7t27sWjRIixZsgRnnHEGpk+fjkcffbTLnjODwWDI2dcopYrbfMEU7gnDCkk3sL733ns47rjj8Mgjj6Bnz54YNGgQ7rrrrqjeAp/Ph5aWFsWPWTiOQ7bLkZIfqx04v/nmG8XfX3/9NQYOHBgx12To0KHYu3cv9u7dK163YcMGNDU1YdiwYZYeU87atWsRDofx2GOP4cQTT8SgQYNw4MCBiO2qq6tx0003YeHChfh//+//Yd68eeL/ysrKcO211+LVV1/F448/jhdeeCHm/WEwGIx48QfD4u9tXhaMZApJ17B27NiBFStWwOPx4L///S8aGhpwyy234PDhw7qVF3PmzMF9992X7F1LOXv27MGMGTPwu9/9DuvWrcNTTz2Fxx57LGK7SZMmYeTIkbjyyivx+OOPIxgM4pZbbsHpp58u+jViYcCAAQgEAnjqqacwZcoUfPXVV3juuecU29xxxx0455xzMGjQIDQ2NuLzzz/H0KFDAQCzZs3Csccei+HDh8Pn8+GDDz4Q/8dgMBipwCcLRlpZMJIxJF0ZCYfD4DgOCxYswAknnIBf/vKXmDt3Ll5++WVddWTmzJlobm4Wf+SKQHfimmuuQWdnJ0444QRMnz4dv//97/Hb3/42YjuO4/Duu++iqKgIp512GiZNmoR+/frhzTffjOvxR48ejblz5+Lhhx/GiBEjsGDBAsyZM0exTSgUwvTp0zF06FCcffbZGDRokGhudblcmDlzJkaNGoXTTjsNdrsdb7zxRlz7xGAwGPEgD0ba/EGEw3wK94ZhFo6njS1iuTHHGVbTXHvttfjqq6+wbds28bqNGzdi2LBh2LJlCwYOHGj4OC0tLSgoKEBzczPy8/MV//N6vdi5cyf69u0Lj8cT61NhMOKGfRYZjNRzzYvfYvmWQ+LfP903mRlZU0i087ecpCsjJ598Mg4cOKBopLVlyxbYbDb06tUr2Q/PYDAYjKMIf1BZjdjqDaRoTxhWsByMtLW1Yf369Vi/fj0AYOfOnVi/fj327NkDgKRYrrnmGnH7K664AiUlJZg6dSo2bNiA5cuX4w9/+AOuv/56ZGVlJeZZMBgMBoMBpYEVYCbWTMFyMLJmzRqMHTsWY8eOBQDMmDEDY8eOxaxZswAAtbW1YmACALm5uViyZAmamppw3HHH4corr8SUKVPw5JNPJugpMBgMBoNB8KmCkVZW3psRWE6kTZgwAdFsJvPnz4+4bsiQIViyZInVh2IwGAwGwxJqZYRV1GQGbFAeg8FgMLoN/hAJRhw20veJpWkyAxaMMBgMBqPbQJWR4hwXAGZgzRRYMMJgMBiMbgMNRkpy3QBYS/hMgQUjDAaDweg2UANriaiMsGAkE2DBCIPBYDC6DZFpGhaMZAIsGGEwGAxGt4DnedHAWpJLgpE2H/OMZAIsGGEkDY7j8M4776R6NxgMxlECDUQAoJR5RjIKFowwGAwGo1sg7zHC0jSZBQtGUsSECRNw22234Y477kBRUREqKiowb948tLe3Y+rUqcjLy8OAAQPw0Ucfibf56aefcM455yA3NxcVFRW4+uqr0dDQIP5/8eLFOOWUU1BYWIiSkhKcd9552L59u/j/Xbt2geM4LFy4EBMnTkR2djZGjx6NVatWGe4vz/MoKyvD22+/LV43ZswYVFVViX+vWLECbrcbHR0dqKmpAQBceOGF4DhO/JvBYDCShbz7alG2EwDQzpSRjKD7BSM8D/jbU/NjcQDyyy+/jNLSUnz77be47bbbcPPNN+OSSy7BSSedhHXr1uGss87C1VdfjY6ODjQ1NeEXv/gFxo4dizVr1mDx4sWoq6vDpZdeKt5fe3s7ZsyYgTVr1mDp0qWw2Wy48MILEQ4rOxL++c9/xl133YX169dj0KBBuPzyyxEMRv/CchyH0047DcuWLQMANDY2YuPGjejs7MSmTZsAAF988QWOP/54ZGdnY/Xq1QCAl156CbW1teLfDAaDkSyoMuK0c/A47QAAbyAc7SaMNKH7zVUOdAAP9UjNY//PAcCVY3rz0aNH4y9/+QsAMmDw//7v/1BaWoobb7wRADBr1iw8++yz+OGHH/Dpp59i7NixeOihh8Tbv/jii6iursaWLVswaNAgXHTRRYr7f/HFF1FWVoYNGzZgxIgR4vV33XUXzj33XADAfffdh+HDh2Pbtm0YMmRI1P2dMGECnn/+eQDA8uXLMXbsWFRWVmLZsmUYMmQIli1bhtNPPx0AUFZWBgAoLCxEZWWl6deEwWAwYoUGI26HXQpGVFN8GelJ91NGMohRo0aJv9vtdpSUlGDkyJHidRUVFQCA+vp6fP/99/j888+Rm5sr/tDggaZitm7dissvvxz9+vVDfn6+mBqRDy5UPy5Ns9TX1xvu7+mnn44NGzbg0KFD+OKLLzBhwgRMmDABy5YtQyAQwMqVKzFhwgTrLwSDwWAkAGpgdTlsYjDiY8pIRtD9lBFnNlEoUvXYVjZ3OhV/cxynuI7jyGyFcDiMtrY2TJkyBQ8//HDE/dCAYsqUKejTpw/mzZuHHj16IBwOY8SIEfD7/bqPK38MI0aOHIni4mJ88cUX+OKLL/Dggw+isrISDz/8MFavXo1AIICTTjrJ5LNnMBiMxEKVEZfdBo+TrLW9AaaMZALdLxjhOEupkkzhmGOOwX/+8x/U1NTA4Yh82w4fPozNmzdj3rx5OPXUUwEQQ2ki4TgOp556Kt599138/PPPOOWUU5CdnQ2fz4fnn38exx13HHJypNfe6XQiFGIHAgaD0TX4hJSMy2GDx0E9I+wYlAmwNE2GMH36dBw5cgSXX345Vq9eje3bt+Pjjz/G1KlTEQqFUFRUhJKSErzwwgvYtm0bPvvsM8yYMSPh+zFhwgS8/vrrGDNmDHJzc2Gz2XDaaadhwYIFol+EUlNTg6VLl+LgwYNobGxM+L4wGAyGHFpNI0/TeIMsTZMJsGAkQ+jRowe++uorhEIhnHXWWRg5ciTuuOMOFBYWwmazwWaz4Y033sDatWsxYsQI3HnnnfjrX/+a8P04/fTTEQqFFN6QCRMmRFwHAI899hiWLFmC6upqjB07NuH7wmAwGHIkA6uUpgmFeQRCLCBJdziet1iPmgJaWlpQUFCA5uZm5OfnK/7n9Xqxc+dO9O3bFx6PJ0V7yGCwzyKDkWo++fkgfvuvtRjbuxCv33gihtyzGADw471nIc/jNLg1IxlEO3/LYcoIg8FgMLoFYjWN3Qa3wwbBn896jWQALBhhiNDurlo/8v4mDAaDkY7QMl6XwwaO4+B2sIqaTKH7VdMwYuYf//gHOjs7Nf9XXFzcxXvDYDAY1qDKiFuopPE47fAGwmKVDSN9YcEIQ6Rnz56p3gUGg8GIGbmBFYBQ3htAp5+ladIdlqZhMBgMRrfALyvtBSA1PmPKSNrDghEGg8FgdAvkBlYAsmF5LBhJd1gwwmAwGIxugS8gdWAFADeb3JsxsGCEwWAwGN0CX0jtGWHVNJkCC0YYDAaD0S2I9IywNE2mwIKRFMLzPH7729+iuLgYHMehsLAQd9xxh6nbTpgwwXBbjuPwzjvvxL2fZrn33nsxZsyYLnu8eOjq14bBYCQffQMrS9OkO6y0N4UsXrwY8+fPx7Jly9CvXz/YbDZkZWUl7P5ra2tRVFSUsPsz4q677sJtt91m6TY1NTW44447TAdhiUL+2uzatQt9+/bFd999lzHBFIPBiERPGfExZSTtYcFICtm+fTuqqqpw0kknJeX+Kysrk3K/etBurZlAV782DAYj+YhTe+3yPiMsTZMJsDRNirjuuutw2223Yc+ePeA4DjU1NRGpl2eeeQYDBw6Ex+NBRUUFLr74YsV9hMNh3H333SguLkZlZSXuvfdexf/lqYhdu3aB4zgsXLgQEydORHZ2NkaPHo1Vq1YpbjNv3jxUV1cjOzsbF154IebOnYvCwkJTz0mdprnuuutwwQUX4NFHH0VVVRVKSkowffp0BAIBACTVtHv3btx5553gOA4cHSQBYMWKFTj11FORlZWF6upq3H777Whvbxf/X1NTg4ceegjXX3898vLy0Lt3b7zwwgvi//1+P2699VZUVVXB4/GgT58+mDNnjuZr07dvXwDA2LFjwXEcJkyYgOXLl8PpdOLgwYOK53jHHXfg1FNPNfV6MBiMrkVseuakHVipgZWladIdy8HI8uXLMWXKFPTo0cNy3v2rr76Cw+FIqhTO8zw6Ah0p+bEyAPmJJ57A/fffj169eqG2tharV69W/H/NmjW4/fbbcf/992Pz5s1YvHgxTjvtNMU2L7/8MnJycvDNN9/gkUcewf33348lS5ZEfdw///nPuOuuu7B+/XoMGjQIl19+OYLBIADy/tx00034/e9/j/Xr1+PMM8/Egw8+aPo5afH5559j+/bt+Pzzz/Hyyy9j/vz5mD9/PgBg4cKF6NWrF+6//37U1taitrYWAFGMzj77bFx00UX44Ycf8Oabb2LFihW49dZbFff92GOP4bjjjsN3332HW265BTfffDM2b94MAHjyySfx3nvv4a233sLmzZuxYMEC1NTUaO7jt99+CwD49NNPUVtbi4ULF+K0005Dv3798K9//UvcLhAIYMGCBbj++uvjek0YDEZyENvBsz4jGYflNE17eztGjx6N66+/Hr/+9a9N366pqQnXXHMNzjjjDNTV1Vl9WNN0Bjsx7rVxSbv/aHxzxTfIdmab2ragoAB5eXmw2+2aKYM9e/YgJycH5513HvLy8tCnTx+MHTtWsc2oUaMwe/ZsAMDAgQPx97//HUuXLsWZZ56p+7h33XUXzj33XADAfffdh+HDh2Pbtm0YMmQInnrqKZxzzjm46667AACDBg3CypUr8cEHH5h6TloUFRXh73//O+x2O4YMGYJzzz0XS5cuxY033oji4mLY7Xbk5eUpXoM5c+bgyiuvFFWigQMH4sknn8Tpp5+OZ599Fh6PBwDwy1/+ErfccgsA4I9//CP+9re/4fPPP8fgwYOxZ88eDBw4EKeccgo4jkOfPn1097GsrAwAUFJSotiPadOm4aWXXsIf/vAHAMD7778Pr9eLSy+9NObXg8FgJI+AEIw47ERlFfuMsA6saY9lZeScc87BAw88gAsvvNDS7W666SZcccUVGD9+vNWHPCo588wz0adPH/Tr1w9XX301FixYgI6ODsU2o0aNUvxdVVWF+vr6qPcrv01VVRUAiLfZvHkzTjjhBMX26r+tMnz4cNjtdkv7+P3332P+/PmKqcGTJ09GOBzGzp07NZ8Lx3GorKwU7/u6667D+vXrMXjwYNx+++345JNPLO/7ddddh23btuHrr78GAMyfPx+XXnopcnJyLN8Xg8FIPqEwUacddlU1DUvTpD1dYmB96aWXsGPHDrz66qt44IEHDLf3+Xzw+Xzi3y0tLaYfK8uRhW+u+Cam/YyXLEfiKmHy8vKwbt06LFu2DJ988glmzZqFe++9F6tXrxY9HE6nU3EbjuMQDkf/0slvQz0aRreJh1j2sa2tDb/73e9w++23R/yvd+/epu77mGOOwc6dO/HRRx/h008/xaWXXopJkybh7bffNr3v5eXlmDJlCl566SX07dsXH330EZYtW2b69gwGo2sJ0mDERo5tzMCaOSQ9GNm6dSv+9Kc/4csvv4TDYe7h5syZg/vuuy+mx+M4znSqJN1xOByYNGkSJk2ahNmzZ6OwsBCfffaZpfSYFQYPHhzhXVH/nWhcLhdCIeWB4phjjsGGDRswYMCAuO47Pz8fl112GS677DJcfPHFOPvss3HkyBEUFxdH7AOAiP0AgBtuuAGXX345evXqhf79++Pkk0+Oa58YDEbyoMqInQYjrB18xpDUappQKIQrrrgC9913HwYNGmT6djNnzkRzc7P4s3fv3iTuZXrywQcf4Mknn8T69euxe/duvPLKKwiHwxg8eHDSHvO2227DokWLMHfuXGzduhXPP/88PvroI0WVS6KpqanB8uXLsX//fjQ0NAAg/o+VK1fi1ltvxfr167F161a8++67EQbWaMydOxevv/46Nm3ahC1btuDf//43KisrNSuDysvLkZWVhcWLF6Ourg7Nzc3i/yZPnoz8/Hw88MADmDp1atzPl8FgJI8IZURI0/iYZyTtSWow0traijVr1uDWW2+Fw+GAw+HA/fffj++//x4OhwOfffaZ5u3cbjfy8/MVP0cbhYWFWLhwIX7xi19g6NCheO655/D6669j+PDhSXvMk08+Gc899xzmzp2L0aNHY/HixbjzzjtFw2gyuP/++7Fr1y70799fNJKOGjUKX3zxBbZs2YJTTz0VY8eOxaxZs9CjRw/T95uXl4dHHnkExx13HI4//njs2rULixYtgs0W+ZF3OBx48skn8fzzz6NHjx44//zzxf/ZbDZcd911CIVCuOaaa+J/wgwGI2mEhDRtpDLCgpF0h+Ot1KOqb8xx+O9//4sLLrhA8//hcBgbNmxQXPfMM8/gs88+w9tvv42+ffuaMgO2tLSgoKAAzc3NEYGJ1+vFzp070bdv36SeNI9WbrzxRmzatAlffvllqnclZUybNg2HDh3Ce++9F3U79llkMFLL2Y8vx6aDrXh12jicMrAUn2+qx9T5qzGyZwHev+2UVO/eUUm087ccy56RtrY2bNu2Tfx7586dWL9+PYqLi9G7d2/MnDkT+/fvxyuvvAKbzYYRI0Yobl9eXg6PxxNxPSM9ePTRR3HmmWciJycHH330EV5++WU888wzqd6tlNDc3Iwff/wRr732mmEgwmAwUo/aM+J2sqm9mYLlYGTNmjWYOHGi+PeMGTMAANdeey3mz5+P2tpa7NmzJ3F7yOhSvv32WzzyyCNobW1Fv3798OSTT+KGG24AQMp0d+/erXm7559/HldeeWVX7mrSOf/88/Htt9/ipptuitq7hcFgpAdSaa8qTcM8I2mP5WBkwoQJUTuN0u6aetx7770RbcsZ6cNbb72l+79FixaJrdzVVFRUJGuXUgYr42UwMouguprGwappMgU2KI9hmmhdTBkMBiPVhHSqaViaJv1hg/IYDAaD0S0I6lTT+JgykvZ0m2AkmV1EGQwzsM8gg5FaJGVEOSjPHwqL/2OkJxmfpnG5XLDZbDhw4ADKysrgcrmS2qSLwVDD8zz8fj8OHToEm80mdnRlMBhdS4RnxCmtt72BEHLcGX/K67Zk/Dtjs9nQt29f1NbW4sCBA6neHcZRTHZ2Nnr37q3ZWI3BYCSfUEh7Ng3AgpF0p1u8My6XC71790YwGNScL8JgJBu73Q6Hw8FUOQYjhaiVEZuNg8tugz8UhjfI0qjpTLcIRgDSDdbpdEZMcmUwGAzG0YG6zwhAGp/5Q2FWUZPmMD2ZwWAwGN0CdTUNwObTZAosGGEwGAxGxhMO86AFMw6Zb0vqNcLSNOkMC0YYDAbDJN5ACN/taYzahZqRGkKy90ShjDhorxGmjKQzLBhhMBgMk/zPwh9x4TMr8daavaneFYYKeR8Rh1aahs2nSWtYMMJgMBgmWfjdfgDAAx9sTPGeMNQEwzrKCEvTZAQsGGEwGAyLtPqCqd4FhgraYwRgBtZMhAUjDAaDYRJ5R8/mTu0J1ozUEJSNY7DL+v242eTejIAFIwwGg2ESp6xKY/3eptTtCCMC6hmxcaTZGYVN7s0MWDDCYDAYJgiFeUV6Zv2eptTtDCOCoGpIHoUZWDMDFowwGAyGCVq9yrTM4XZfivaEoUVI1QqekuVkaZpMgAUjDAaDYQK1R6SFeUbSCkkZUQYjNE3D+oykNywYYTAYDBOog5FWL6uooQRDqVcdRGXErg5GWDVNJsCCEQaDwTBBhDLiZcoIADy8eBNG3vsJtta1pnQ/QrrKCEvTZAIsGGEwGAwTMGVEm2eXbUdnIIT7P9iQ0v3QGpIHAG6HUE3DDKxpDQtGGAwGwwQ0GKnIdwNgnhE1+xs7U/r4IaNqGpamSWtYMMJgMBgmoMFIr6JsAEwZAZQn+LoWbwr3RDKwqpURlqbJDFgwwmAwGCaQgpEsAKQlvHw429GIPABp94dQ35q6gETfM8KanmUCLBhhMBgME7R0EiWEBiMA0HaUz6ipbVYGHz/sbU7RngDBkI4y4mBpmkyABSMMBoNhAuoRKct1i6bIo903ok7NbKlPXUWNXtMzlqbJDFgwwmAwGCagaZqCbCfyPE4AzDeiVkaaO1IXnNFqGkdEnxFWTZMJsGCEwWAwTCAGI1lO5Gc5ALBeIwdVwUhTCoMRSRlh1TSZCAtGGAwGwwSdwsksy+lgyogADUYGlOcCiOzF0pUYtYNnaZr0hgUjDAaDYYKA0PLc5eCQ7xGUkaPcM3JQ8IwMrswDADR1+lO2L3qeETczsGYEloOR5cuXY8qUKejRowc4jsM777wTdfuFCxfizDPPRFlZGfLz8zF+/Hh8/PHHse4vg8FgpAR/UAhG7Hbki8rI0R2MHGolk4sHlZNgpLkzdUqRvjJCghFfMAyeP7pLsdMZy8FIe3s7Ro8ejaefftrU9suXL8eZZ56JRYsWYe3atZg4cSKmTJmC7777zvLOMhgMRqqgyojTwck8I0d3moaWNtNy51QqRSGddvA0TQOQgISRnjis3uCcc87BOeecY3r7xx9/XPH3Qw89hHfffRfvv/8+xo4da/XhGQwGIyVQZcRpt8k8I0e3MtLhJ8FIVaEHANDUkbo0De0zoqeMACRVI/+bkT50uWckHA6jtbUVxcXFXf3QDAaDETN+6hmx22SekaNXGfEHwwgIAUDPQqKMtPtDooLU1ehV0zjtNjFAYSbW9MWyMhIvjz76KNra2nDppZfqbuPz+eDz+cS/W1paumLXGAwGQxd64nU5bMh1k0Nnq+/oVUaoKgIAFfke8ffmzgBKc91dvj96nhGAqCNtviAzsaYxXaqMvPbaa7jvvvvw1ltvoby8XHe7OXPmoKCgQPyprq7uwr1kMBgMJaEwL668nXYbsoVgpMN/9J7c2oXn7nLY4HHakSeoRakq7xWVEbtWMMIan6U7XRaMvPHGG7jhhhvw1ltvYdKkSVG3nTlzJpqbm8WfvXv3dtFeMhgMRiTy1IPLYUOOiwUjHYJ5NcdFPBgFWcRHk6rGZ9GUEVre23kUv1/pTpekaV5//XVcf/31eOONN3Duuecabu92u+F2d73Mx2AwGFr4ZcGI084hWzgBy1MVRxtUGckWArOCLCf2NXamrKJGr5oGYI3PMgHLwUhbWxu2bdsm/r1z506sX78excXF6N27N2bOnIn9+/fjlVdeAUBSM9deey2eeOIJjBs3DgcPHgQAZGVloaCgIEFPg8FgMJJHQFYS6rLbZMHI0bvSFpURN3ktCrMFZSRFjc+MPCMAS9OkM5bTNGvWrMHYsWPFstwZM2Zg7NixmDVrFgCgtrYWe/bsEbd/4YUXEAwGMX36dFRVVYk/v//97xP0FBgMBiO5UGXEaefAcZyoBnT4jt6Tm5YyAqRuWF4opF1NA8ganzEDa9piWRmZMGFC1C528+fPV/y9bNkyqw/BYDAYaUUgKJlXASDbzdI09LlTZaQgywUgdV1YoykjWeKwPJamSVfYbBoGg8EwwB+SKkcAKNI0R2uL8XaftjKSqjSN3mwaQO4ZYcpIusKCEQaDwTDAr1ZGhBNwMMwrzK1HE6IyIgRmtLQ3VZOMo1bTONmwvHSHBSMMBoNhQEDWfRWQlBHg6C0XFZURoecKbQTX7ktNMCJW02j1GaGlvSxNk7awYITBYDAMEFvBC2kap90mBibtR2kwolZGcoRgpC1FwUj0ahqWpkl3WDDCYDAYBgSCUjUNhZpYO49SE2u78LxpyirXndpyZ73ZNAAr7c0EWDDCYDAYBqiVEQDIFk5w7UdpeS8NOmg1TU6K0zRUGbFz+sqIj6Vp0hYWjDAYDIYBflEZkQUjR/l8GtpjJUtQRlKdpqF9RhwanpEsZmBNe1gwwmAwGAbQib2KYOQobwnfrvKMpNrAGoxa2suCkXSHBSMMBoNhAK2mcTu0gpGj8wTXoerASl+PVKWtaDVN9NJelqZJV1gwwmAwGAZopmnEyb1HqTKimk1DlRF/KCy+Xl1JVGVECCI7mTKStrBghMFgMAyQz6ahMGVEqYxQzwiQmlRNyMygPBaMpC0sGGEwGAwD6Erf5ZCanbFgRKmMOO02sdqoPQVqUdBUaS9L06QrLBhhMBgMAwKaysjRnqYRSntdkiIimVi7PkALm2h6xqb2pi8sGGEwGAwDohlYj8Y+I6EwL/ov5K3xqUqSivLeaJ4RVtqb/rBghMFgMAzQMrBSj8TROJtGbgSVe0WoSpJSz4jWbBpWTZP2sGCEwWAwDPBr9Bmhq+1U+CNSTYcQbNg4pVqUyi6sQTooL9psGtYOPm1hwQiDwWAYENBoB5+T4lksqYQOB8xxOcDJ2q+nsgtrtGoaN53aexS+V5kCC0YYDAbDgKO5z0hzRwCfb6oHz/PidVT5oMMCKXRYXmqUEeNqGl8wrHgejPSBBSMMBoNhgKiMHIV9Rma99xOmzl+Nxz/dKl7X4Y+spJH/3Z6C1yR6nxHpVOdj5b1pCQtGGAwGwwDNqb2uo2NQ3rvrDwAAnlgqBSPUJ6NWRlLqGQkZz6YBWEVNusKCEQaDwTBAO00jKCMpGgzXVcjP7S3eAABpYm+2ShlJ5bC8aMqI024Tr2cVNekJC0YYDAbDAKnpmYaBtZuvtOWlu19sPgQgcmKvetu2FPReiVZNA0jqCJtPk56wYITBYDAMkNrBy0p7aZqmGzc98wZCaPVKKsfa3Y0ApKqUbLfKM5JCA2u0PiMAm0+T7rBghMFgMAwICH4El1wZEVQBfygsKifdjUOtPsXfDW3kb9Ez4lQpI6KBNb2qaQAgy8Um96YzLBhhMBgMA7QMrFmyFEV3NbEealMGI4fb/AAkNSgnQhlJT88IIGsJ303fq0yHBSMMBoNhgJaB1SUzRXbXZlpqZeRwu0oZcan7jKRuUF602TSALK3WTd+rTIcFIwwGg2GA1tRejuNEdaS7toSnwUh1cRYAM8pI6gblGSsjLE2TzrBghMFgMAzQagcPSB6J7q6MDKnMBwAc6fAjFOaNlZFUeEZC0atpslg1TVrDghEGg8EwQKymsSsPmdkprB7pCqhnZHBFHjgO4HmgscOv34E1LTwjegZWVk2TzrBghMFgMAwIaEztBWSNz7rpCY4qI5UFHhRluwCQVI3ebBoanARCPHxdPCFX9IwYlPZ2VxUr02HBCIPBYBigVU0DyFrCd9NeI7SUtzTXjZIcGoz4oigjUnDS1SZWs9U0LE2TnlgORpYvX44pU6agR48e4DgO77zzjuFtli1bhmOOOQZutxsDBgzA/PnzY9hVBoPBSA1a1TSAfFhe90zT0CAr1+1ASS4JRhra/bqeEYfdBrcQsHVlqobnecNqGrqvTBlJTywHI+3t7Rg9ejSefvppU9vv3LkT5557LiZOnIj169fjjjvuwA033ICPP/7Y8s4yGAxGKpCm9mobWLtruahXSLV4nDaU5LoBCMqITjUNkBoTqxCHAGDKSKYS+Uky4JxzzsE555xjevvnnnsOffv2xWOPPQYAGDp0KFasWIG//e1vmDx5stWHZzAYjC4nqNNqvLuX9lIVweO0ozRH5hnRUUYAEqAcbvd3qTJC59IAUWbTMGUkrUm6Z2TVqlWYNGmS4rrJkydj1apVurfx+XxoaWlR/DAYDEaqoGWj6lV3Tjc/wdHKE4/TLiojDXLPiIYykopheSGZNKJbTcOUkbQm6cHIwYMHUVFRobiuoqICLS0t6Ozs1LzNnDlzUFBQIP5UV1cnezcZDAZDk3CYF9MADlWahnb1TEXH0a7AK3hlSJqGKCP7GjvFk7+mMuLq+nLnoCwYMeozwkp705O0rKaZOXMmmpubxZ+9e/emepcYDMZRSrQTnaiMBLpfmiYc5kXjrsdpR48C0oV1+6E2cZtsVzRlpOtek1BIrozotYOnZmMWjKQjlj0jVqmsrERdXZ3iurq6OuTn5yMrK0vzNm63G263O9m7xmAwGIYoUwA6npFuqIx4ZX1Cspx29Cgkx+vaZi8AwO2waaoQuQlofBYK83hi6VaM71eC8f1LDLenASPHATZmYM1Ikq6MjB8/HkuXLlVct2TJEowfPz7ZD81gMBhxE5CZI9UGVqoCdMfVtjcgPW+P046qQo/i/+X52gtG2mskntfkiy31eHLpVlw+72s0dfgNtzfqMQJIgWN39fdkOpaDkba2Nqxfvx7r168HQEp3169fjz179gAgKZZrrrlG3P6mm27Cjh07cPfdd2PTpk145pln8NZbb+HOO+9MzDNgMBiMJKJMARw9fUaot8Jp52C3ccj3OJEnM6z2L8vVvF0i0jRUfQGApz/fZrg9rabR84sAzDOS7lgORtasWYOxY8di7NixAIAZM2Zg7NixmDVrFgCgtrZWDEwAoG/fvvjwww+xZMkSjB49Go899hj+8Y9/sLJeBoOREVBlhOMiT3bZ3bjPCE1neBySSZWmagD9YCQRaZqGVkkNeWvNPsPtqTJi5/SDEQ9L06Q1lj0jEyZMAM/zuv/X6q46YcIEfPfdd1YfisFgMFJOtBRAzlGgjHhc8mDEg811rQCSq4zUt0rKSHNnAB3+oKZZlmLUfRVgBtZ0Jy2raRgMBiNdCIb0p8F25xMc9Yx4nNLzrpIpI/3KcjRvl4jS3nphQJ/4d4tPZ0uCGDDa9U9p2Wxqb1rDghEGg8GIQjCaMtKNDaw+jTQN7cIKGCsj8VQYqYORuhavzpYEGjCa8YwEQrzY3p+RPrBghMFgMKIgdl/VGE1PT3DdMU3TKeu+SvHJTuKlua6I2wCJSdM0CMEIHbpX12pSGYkSjMifB1NH0g8WjDCSzoYDLV3ajZHBSCSSHyHycElPvN5AWNGPpDtA0zRZspP4r8f2AgAcX1METscsmiuqRbF953mexyEh+BjZswAAUG+kjJiopnE7bKC7zEys6QcLRhhJ5b/f7cMvn/wS//vBhlTvCoMREzTIcGooI/J26N3tBEfVA7fMMzK4Mg9f3j0Rr1w/Tvd28aZpmjoC8AsKzPAe+QAi0zZqzCgjHMdJ5b1+lqZJN1gwwkgqd775PQDgjdWspT8jM6H+Aq1Vt9thA726o5upf7QDqzy9AQDVxdmicVeLXKHpWaxpGhp4FGU70bOIGGaNPCMhE9U0gKwvTDds35/psGCEkTS21bcp/u5uMjbj6EBSRiIPlxzHddteI7RTqToYMSJH1mckWhsIPWhZb1meGxX5pOur2WBEb2IvRew10s3eq+4AC0YYSePjnw8q/j7QpD2lmcFIZwIGlRp0td3ezUysviD1jFg7TdDgLBjmxfuwAi3jLc/zoDzPo7hODzN9RgA2nyadYcEII2k0tCkPILsOt6doTxiM2DHyI2R3014jXo1qGjPkyFI4sRjXmzsDAIDCbKc4/8a0Z0TD1yNHfK+s+llaDgC+NuPtGDHDghFG0mjpVB6IdjWwYISRedB28Honuu6apok1GHHYbWKjtFheE6paZLvsYpqmzReMGtiYVUbE98qKMrLnG+CJ0cDcYcCal8zfjmEJFowwkgZd4dBSv50NHancHQYjJkIh/dJeQDaltpsZWKXZNNZPE7lx9Bqhfo5slwM5LjtcwuM3RpneG6IBo1kDq9n9CoeARXcBIT/gawY+nAEc3m7utgxLsGCEkTRavCQYGdWL9ApgaRpGJkJ7WDh1TnRZ3VYZEdrBR6mc0SMnjmF58mZrHMehMMsJgJT86mFaGbHaMXfDO8DBHwBXHlA1BuDDwMqnzN2WYQkWjDCSRksnDUYKAQC7WTDCyECMTnTddVieV6MdvFlyXLErIx1+KU0DEO8IICmtWpitprH8Xq1/nVyeeDNw9hzhugWAt8Xc7RmmYcEII2m0eskXvr8wUOtwu77MymCkK3TuiVZpL9B9h+VJg/KsByO5cTQ+o0EQrXwpzCJt56OlaczMpgEkz0i7mfeqrR7Y/hn5ffRvgN7jgfyeJGVTv9H49gxLsGCEkTSoMtK3lAQjTR0Bcc4Hg5EpGCsjFk5wGYRkYLV+msh2xz65l6oWNMgryDZO05jpwApY9Pf8tBDgQ0DPY4GS/gDHAWVDyP8ObTK+PcMSLBhhJIVQmEer8IXvXZItzoRojHJAYTDSERpAa7WDB6R0Qmc3TdNkxaCMxDMsr1M1E4d6RqKlaUz3GRF7wpgIHH94k1yOuky6jgUjSYMFI4yk0OqVDhyFWS4UZROp9QhL1TAyDKMTnSXpP4PQawdvhlxX7MPyaFBHg7yiHHLsaDJTTWPQZ4SqWIYdWBu2AgfWAZwdGP5r6fqyweSSBSMJhwUjjKRAe4xkOUlpXrFwQDncFr15EYORblBlxKHjGZGUke4VjNDn444hTSMpI7H3GaFVPAWWqmmi76vpbrk/vEUuB5wB5JZJ15cPJZeHNke/PcMyLBhhJAVa1ksPJGIwwpQRRoYRNOrAGoc/Ip2Jz8Aaj2dEqKZxKqtpmkxV0xh5RgTFxihI2ryIXI64SHl96SBy2bIf8DZHvw+GJVgwwkgK1Lyan0W+/CU5LE3DyEyCBmWjojLSzead+IJxlPbG0WfEKwQj1N9Bq2mipWnMd2A1oYw07wfqfgLAAQPOVP4vqxDIqyK/N2yN+lgMa7BghJEUqDKS7zkKlZHGXcArF0hSLyOjMZ5NE/uJN53xicpIPGmaGJSRgHafkURU05hq3b/1E3LZ63ggpyTy/0U15LJpd9THYliDBSOMpEA9I/lCmkZSRrq5ZyQcBv51IbDjc2DhjUAMI9QZ6UUgZDSbpnv2GfGLVUSxBCOxTzKmXhWaHhI9I9GqaUz3GTGRPtq6hFwOPEv7/wXV5LJ5X9THYliDBSOMpEDL8NSekW6fpvl5IXBkh/T3wR9Tty+MhGBWGelOwQjP82Iw4o5hNo3UgdXaaxIK8/AFyePS11XswNoRAK8T3JudTUMVG12zcdAH7FhGfh94pvY2Bb3IZdPeqI/FsAYLRhhJQUrTkC9/cS4ZBd7Q1s2DkW1LlX9TIxwjYxE9IzoKgdhIqxv1GQmFeVHUi0UZyRWNotZeE6/MdyP2GRHaAvhDYV1fjtlqmhyZZ0QzsNn9FRBoB3IrgarR2ndSSJWRJAQjbfVAsJsfI3VgwQgjKUgGVnWappt/0favIZfDzieXWxanbl8YCUEs7dVTRpzdTxnxyzolu2JRRmI0sMpfQ+pVyXHZxYZzer4RUb0y6DNCB+WFeYgKjAIxRTMJYqdGNQW9yWWi0zSHtwNzhwLzfgF0NiX2vjMAFowwkgKdS5MnKCMluUdBMNLZBDRsIb+Pu5lcsnHjGY9h0zO35BkJh7uHRygQlJ5HPMGIVQOrvOsrJwQDHMehwGA+jekOrLIyZc1AacvH5HLgZP07SVaaZtcKIBwE6n4EFv42sfedAbBghJEU6KqDmtCKs6WDSXc5YEdwYB25LKoBKkeQ330tbMJnhkPNkUZNzwCpa2mm4wtJz8PIh6GFOCjPH9L1eWihnthLKRBaBFBjvBqz1TR2GycqLhFK1uHtwJHtgM0B9Jugfyc0TeNrTmyvkbqfpd+3fnLUpWtYMMJICjQYcQkHcDrsiucl1aTbsW8tuex5HODOA9z55O/W2tTtEyNujJqeeRx2UdGPZUptOuKn31+HTVQorEDVIrkh1Qxi91VVo7V8g/k0QcHAaqSMAJK5NiIYoSma3uMBT77+HbhygKxi8nsiUzXyYAQ80HogcfedAbBgJN3geeLm/nIu6VPha0v1HsUEbZhEW0m7HXZxtdPU2U0jfuoX6XUcuczvQS5bjq6DSncjaFDaa7NxovzfXVrCBwQ1yBWDeRWQTviAtVRNh2ouDYVW5bXoBCNmlRFA1jFXbTjeKqRoBkVJ0Yg7lOBUDc+T9Iyco6x0mAUj6camD4BXzgeW3kf6VDx/aka2HRZXVnbpoFJoYsZEygibX71pwvPAPiEY6cmCke6EmROdNCyve6h+cmUkFuyyAM2KibVT1X2VQpsntnh1lJGQuWoaQKaMyFUsXyvxbAD6/UXkFFITa4KCEdpe3uYgygzAghEzPP3006ipqYHH48G4cePw7bffRt3+8ccfx+DBg5GVlYXq6mrceeed8Hq9Me1wt+f7N8iluwDIrSA9KxbPTO0+xQCVZuU9Cgqyo5vQUsYnfwEeqgJ2fRX7fTTtBjoaAJsTqBxJrssTgpGjTG7tbgQM2sED3a/xWUBseGY9RUORKmrMvyadMgOrnAKDNI0VZSRLqyX81iVAyA8U95Pmz0SjIMHlvTRFUzqY7EMi7ztDsByMvPnmm5gxYwZmz56NdevWYfTo0Zg8eTLq6+s1t3/ttdfwpz/9CbNnz8bGjRvxz3/+E2+++Sb+53/+J+6d73Z4m6W85dRFwKWvAOCA9QuAA+tTuWeW0VpZFWVHP6CkhB/fBlY+BQS9wIczYldIqCpSOQJwesjvTBnpFpgZTy8FI91DGfHFqYwAsmF5Fl6TDj1lRDSw6nlGzFXTAHLPiGy/Nr5PLof+Sr+kV06i0zS0OWLFcOm+m/cn5r4zBMuftLlz5+LGG2/E1KlTMWzYMDz33HPIzs7Giy++qLn9ypUrcfLJJ+OKK65ATU0NzjrrLFx++eWGaspRyeaPgJCPROYVw4HeJ0pTI79+lly2HAA+ewCo25C6/TSB6BmRHczMzJjoUjqbgEV/kP4+tAnY8E5s97VfZl6liMEIM7BmMtQ/cTQqI7F6RoDYynu9Ab1qGpPKiAklR2oJL7xXAa80j2bor8ztaKIbn1FlRBGMsDSNLn6/H2vXrsWkSZOkO7DZMGnSJKxatUrzNieddBLWrl0rBh87duzAokWL8Mtf/jKO3e6m7PmaXA46W4rOx99CLn/6D/n5xyRg+V+Bl84Gar9P3r6EQ8De1YC/I6ab06ZJ8pVVgTh9M02Cka8eBzqPEGn0hN+R6+h7YJV9KvMqIAtGjq4VTnfDTApAHE3fTZQRqmzG0n2Vomh8tnY+8MxJwBd/BUL6r1GHX7uaRjSw6lTi0WoamwlVI9ejasi26QPA30ZSLz2PMbw92aEEz6cRg5ERR20w4jDeRKKhoQGhUAgVFRWK6ysqKrBp0ybN21xxxRVoaGjAKaecAp7nEQwGcdNNN0VN0/h8Pvh80kC1lpajpE/DwR/IZY8x0nU9jwX6ng7s/AJ4+3pync1BUjqfPQhcmYTJsEd2AG9dS/Ynt4KMzB46BTjtLtN3QSd+umXjx6kyousZObIT+Ox/yWNOfsicXGqFcBjYuQwo7k9ev1VPk+vPvE+SW2Mpww36pcBQUxlhaZpMxmhQHkBW26fbvkfPrT8BY+5O/Ge3i/FreL6sQluvh5v2Acv/BAQ7gfqfyWujcyzp1OkzQg2sifCM5KkVm7XzyeWYK82/bzQYaT1Ivv8Ol7nbaRHoBA5vJb9XjiBmWoCoLjyf8Z8lsyS9mmbZsmV46KGH8Mwzz2DdunVYuHAhPvzwQ/zv//6v7m3mzJmDgoIC8ae6ujrZu5l6QkEpOq5UzUS4ZL5kihxyHjDlCfJ755Hk7Muiu6XAqK0OqF0PLJtjqUWxljIS1TNyaAvw3KlE/fn6GWD3ylj3Xp8l95CJuk+OJVVKIT8w+FyiROVXkW1iCUbqfiLpNU8hUNJfuj5PuM+OBiCUJmoQwzIhE36EwaFteNn1ME7Y8JAk+WcwgTgm9lKoMjJk45MkEKFseFf3Nl4DA2siPCNUGWn1BoGGrcCuLwFwwNirDG8rklMKOLIA8EBLnArGoU0AHwayS8hCLL8nud7flpGVlLFi6ZNWWloKu92Ouro6xfV1dXWorKzUvM0999yDq6++GjfccANGjhyJCy+8EA899BDmzJmDsI5ZcObMmWhubhZ/9u49ClzFR7YTE6UzByjuq/xfdjEw7VPgd18Cl71KPrQA+QAnmoZtwLYlADjg5pXAZQvI9eGg1CrZBJIyIvOMiGkalTISCgLv3AT4W6XrqGqRKDa8C6z6O/mdF3LFRTXAr54iKw8aOLQetH7fol/kWOUqJqsIgPB3R5ICR0bSoWWjuifmcBhX1T4k/U39XfGw8ingrwOA3drp72SjtZiwSq7bgWx40a9OCM5+8zoAjix0dNRCqQrPWtMzK56RXDe5rzZfEPjyMXLloMmSD8QMHJe4dIrcL8JxgCtbaqp2FKV4LX3SXC4Xjj32WCxdKk0mDYfDWLp0KcaPH695m46ODthUxi+70HtCr02w2+1Gfn6+4qfbI3dT2+yR/3d6gKpR5MPKCa9nMoKR1fPI5aCzyb4MPQ84TTB5bnzP9N1ojR+nXVib1AeU714hJ3R3AXD1O+S6zYsSa/z8QUhnnXgLcOsa4MbPgFu+BnKEwC5PCKZbD1qvqNHyiwDkfcwWDiodh2Pbb0bKMezu2bgT5b7d0t87PidKX6yEAqTcvP0Q8PJ5RMbvYuLtMwIQZeR02/dwhH0k8B98DtDrePJPnQGSWsZ3QO4Zib/PCFVGslt2Aj+8Sa487W7D20VAg5d4K2rEYGSkdN1R6Bux/EmbMWMG5s2bh5dffhkbN27EzTffjPb2dkydOhUAcM0112DmTKkvxpQpU/Dss8/ijTfewM6dO7FkyRLcc889mDJlihiUMCB5DipHRt8OkIKRcIKd+6Eg8OO/ye/H3yBdP3QKudy21FS6IRgKiysVl0IZ0aimCXiJqQ0AJs4E+k8EyocB4El6KBEEfcD2z8nvoy4FSgcSFcOZJW2TK/igwgHr6S+tShoKVbE6GqzdJyMxHNoC1Gv72cxCUwC6PTeEhcT34X7Ylit8BnYtj/0B6WcVIIok9TR0If4EpWkm21eTP4ZOIQupQUJDsW1LNW8jKqpO5eNSz4g3EBYDFjlWPCO05Pisw6+QBd2gs4Fexxo/ITViwBBnMCJfiIr3neBqnQzAkoEVAC677DIcOnQIs2bNwsGDBzFmzBgsXrxYNLXu2bNHoYT85S9/Acdx+Mtf/oL9+/ejrKwMU6ZMwYMPPpi4Z9EdoB/IqlHG24rKSIIHzu38gqzgs0uUg6IqRwGuPJJGObwNKB8a9W7k48flcmtRjkaaZtVTpClYfi/gOMGgWzECqN8AHPyJrKbktB0iMqYrx/zz2rUCCLQDuZWRfhyK3QnklJHVaGstyQmbobNRMp/11DigZZcC2MKUkVTQvB94YQLxBl3zDlBzSkx3Y7jqrvsJALAx3Bslnl4Y0LYmvko3ulqnHPgu9vuKkUAClJE8J49f2IR9HyIsaPqeDuAB4gnTMGfqpWnyPA5wHLlJS2cQZXnK/1uZTZPrdqIfdwDjO4Sgb8KfLD4zgYIEdGHleWWaRrxvpoyY4tZbb8Xu3bvh8/nwzTffYNy4ceL/li1bhvnz54t/OxwOzJ49G9u2bUNnZyf27NmDp59+GoWFhfHue/eB56VgxIoykug0zc8LyeWw8wG7LE7lOCkAqTfub0JXN4C2MtLcGSCTe2u/B5Y9TP55xizA4Sa/09dAa1bDowOAl6eYf06AtAobdBYQTcaVp2rMsp9O6u0rpXzk0DRNO1NGupxlc0gQGg4Ab14V/X39/k3gvzcDmxdHBPn0RKe76j4oBCN8H+ywDyDX1f4Q2z4HvKTfEACc/Hty2RBHyidG/AnoM1Lt3Yx8rhPttjwphVk1hhg/O48AhzZH3Eav2ZrNxolVMM2dAZK6kqm0QrxoUhlxYLrjHdgRBgb/EugxNoZnh8SkaVoPkteCswNlQ6Tr4wlGQgHg4z8D61+Lfb9SAJtNYwaeJ5F80Ge8bSy0HiQyPmcTUhQGJCMYaT8M/CQEI7TRmhwajJhotkYPZA4bp1ipUBNamAfad68BXrmAnCgGn0vSJ5TKEeRSOMiLrH2ZXNK0iFkOCAFDn5Ojb5cXQ0UN3Re1X4RCFRZmYO1amveRzsWUzkYSnGjRuBt471bg+9eA1y+LSCEYTe2VKyNb7EIr7/oNsVVQ7ficBFD5PYFRvyHXNWxLvApqgD8YfzDSu5l4qX52jZJ8cA4XUC34RnZHjl/Q84wA5PjRi6tH+X8vAR6sBB6oAL5+DoDUJdeMMlLs34/zbUK1HvXDxUIi0jTCZwelA6XOzYr7jiEYWfkUMeu/c7P523z8ZzITTSd91hWwYMQMK/4GvHQOsGR2cu6fltGWDlL6GPQQg5EEeka+eRYIdJCVi9ZJmwZJ9RsN74oqI+rVjcdpR5bTDjtC8Lz7W7Ii6HkscP7flXItNXId2QH426Xr98XQtTcclqXAdFI0lFiUEfVwPDXMM5Iatn1KgvVeJwBTBbPkuleksQreZhJ8b/mEzH4KyVKHB5WqBk3TaFZqdDaKJ6ONfB/sDpYSI3bIT0o2rbLxA3I55FxSJs7ZSHq0rS767RKMn1YQOWLvcVFx+BsAwHd2VeqZHl80gxHtNA1ATKz3O+Yjv1YIJPiQOGk3aKJLLqXHT8/DwYXxJT/GfJMzLURfx/7Yx0jQYESeogHiawn/1ePWb7NvNZkW70/dlHgWjBjh7yATdAHhhB2js732e+Bfv9aeMUMPfpUm/CKAtMpIlDLScQT45nny+6n/T7vJTgUNRswoI/qrm6JsJy6xfwFn0w5yor76v1Iqg5JbJhhKeaUSs3e1mWejpHEn+YI5PEDJwOjbWlVGeB7Yr1NJQ8mmyshR7Blp2gO8ehHwUC9g+aNd85h0hTdgEtBnPEk98mHgrWvIavqxIcDbU4HXLgE2fyhseya5bNyluKtQtEF5h7cDALzZlWhFNjoCYcn3ZdU3wvNSlcmQ80jasrAP+bthq7X7inMKtdbUbUsEvChqIIrk11Clnql3Z+fyiP3UGrBJqXT5cIpNWFicKHSmFkz8ZnrBAACa9yN3E6mse8L/K5IujpX8HiRYDPmI1ywWtPwigBSMtOy3Vqiwe1VsvUloqTXtcZICWDBihFzqBYBNH1q/D54Hnj8N2L6UDGNTY8UvAiQ+TbP8r4CvhSgSQ87T3oYqI427lGqFBl4dZQQgk3tvsC8if5z2B8BToH0nVMWg5r32w0S+tgqtyKkYrvTBaEEralpNrkIPbyNBht2t/95RZeRo9ox8+P+IUuFvJXOVdn6Z3McLBYkZGwAGnEEuz3uclJc27QYW/5GogCUDgZIBRD257FUpPakKRqKaI5tISW8gl5w8OvxB6cRiVRlp3EkUNLtLGiNfKgTQZn0jPA+8eDbw3ClxVdsF4u0zcvBH2MJ+NPD52BRQduxGrxMAVy45gatUqGglxaeEV8PFhdCU2x+oPoFcqQpGDPuMrPo7uJAf34SHYA0/xNIQvwjsTmkBE2uqRt4GXk5uBem0zYfMK7XeZuC/v5X+duWau104JC3AaNfoFMCCESPWCT4Ft3DSpL4KK8ibhe1fG7lqoSZIozQCJZHBSHsDsPof5Pez7tc3eOaUSmqF2suhQuoxErmqqnZ1YIBNiMJH/0b/TnoI8in1e+yRd2S1IB1TI6GZ15YGDmZLe3etIJe9jpfMt3r3ebR6Ruo3Ch1JOaB8OABeUhqTxYHvyIHZUyCZE7OLgasWEn+SzQmcdDsw/VvgtrXADUtI6WlRDdlWHYxEa3ommBdD+USy7/CHSIADEK+HFehxoHKk1F6cqnmHTd7XwR+APatI2/VYV+uQKyMxpmmE7+0P4X5oUw8PdLiAmlPJ79uVHoVonpHjvCSts6X4F8TwCZDSZ5jswBoOi60L5oXJQDwrQ/w0iacEN+iTgkx1MGKzS4GBWd/IJ38hKiTF7Pmh/RB5HTm7tCBLASwYicbBn4hqYXcBFwgdQet/tn4/619V/i2/j5Za8kHmbObzl2KfkQQEI5s+JPntqtFA/19E31YdIOig5xkBgNE2Ijc35fQVOpTqQMtkqUFU3nsBvPnnTnOyZlQnMXAwmVKhLetrohhjc45yz8jKp8jl0CnAb4TvQe0PUYelxc0uQXmpOVXZQLCkP3D5a8Bf6oGz/jcy8KbBSPM+hfk06omOnoQKSZlnhz8kqRmHLaZWaDDSQ3YcKBEMsaoASZetS6Tfw7G/xnErI4Ki+QPfD+2+YGSDS6pYbftMcbXUZ0RjIeMlAdnm7GOIagCIvjlTfUZogObMwffOMQCANp3Be6aJp6Lm0GbyHnkKtRWJPOE6M2nj3SuJJwoALnyBXJpVxmiX17xK7YabXQQLRqLx/evkctDZRFoEiPM+4LV2P9T0aSPVJNjxhfS/fYIPonwY4M4zd3+JVEY2vk8uzYzOpgECNW3qoNV9lTIsRKTr/TkjIv6nfCzhgNywhaxydyxT/t+seZeuKEsHG29LK1/MpFR4XjLg9TlJfzt5mqaLKyJSTkut1Pn25N8DhTWkX03IZ/1EbQWqWNHVtxo99S+3gniL+JBiNRoUG4BppWnIStRWRJWRIHiqZhzZSYaomYUG+fJFSb7MO2AGeTASxzykuKf27peUkTAvpW5FqMdKpfjoHjv8HSjwk3TFTvSUghFRGTFRTUMXNDUnw5NFCgVa41ZG4qiokadotHx6Vgz1NBAZe5XkyTF7jBT9IqlL0QAsGNEnFJQOpGOuAHLLhVQNT6o8zBL0SduPE8bU75LlzGkwomeA1CJRwYi3Wcqt0y6r0aAHSYPSWp8w7EprVdXPSwypOzwGJcw5peJqExveI7N75JhZ9QX9kmwpH2Cnh5imaTReVTTtJicIm0Nqca15n0KAEw5I0ziPFr55jjzv3uPJ59tmk/wU1CeVaEJBYC+p4oiqWGlhs2mmaqIqI8KK2FlMbhfmAV9WBcnX8yHzikY4JBle5cqIlcnPHUeUFWdxKCO+eJQRX6uYfvgxTJSdiHSIQyhjDSsDJt1jx+Ft4MCjkc9FbSBHWsELzzGqyZiyQwhG+k2U5tPEq4yIaZoYSnD1KmkoVgz1e4X3fdiFsteGBSPdg+1LgfZ6cjIZMIlErqU0F2yhCdHhbSRocBcAwy8k1+1bLa2SxbkmUU5oahIVjOz4gqRoSgYAZSaUA5p/b9wZ1QOhu7oJh9GjnQQjG+1D1DeLpPpEcvnereRS7vuIcqBtbPeTg1/zXvIaObPN5ULFtBFvPKGYpmh6HBO9G6wrmzw+EFcOP4KdXwKPDSXNutIRnicTmAGp8gGQ0mXJCkZqvyfVU55CwaNikSjBSIRKwPPiithVWiNe3REIS8GvWQXo8HZiqnXmSGkeQKpuaD9k3Odo8yLlMSEOZSQQjzJy8CcAPJDXA51uEoxHBCNU2VCl63SraYRj7ja+B5q9wYgTrqFnJBwC9nxNfu93uthALW7PCF0wxZKmEQsXdFRiURkxCEY6jkiLtV7HSn4a8ObUWKq6pbCSBmDBiD60e93IS4hrGiB9QABrEjNN0ZQPIaW7djfxJBzZAXhbJGWEuufNEEufkc8eIKXF8tU5VUWMvCKU7GKgWDjIRknVSJ4RVf6xZT+coU4EeDs2h6qMH+/k25V/nyBziusEIw1tPvzisWX49TNfgacScHE/bRlUjd0pVfcY+UbMpGgoVtI/Znn3FtJG/7+/BdrqE3e/iaJpNzlR2xySPwCQNbRLUjBCVZHe46N329WDngCE15Tnef2y0c5GsS+DvbAaHmGeSrsvKB0rzC5cqI+sfIgyb59dTI4ZgPFJ6ed3lH+H40jTxKOM0OdcPgR5wlC6VvWAO1WaBSCvtW6fEeE+t4d7kGF5qtuHQgaekcZdJNhzeICyIeKwvPiVkRjTNDxvPI8s36RnhJ5DSgeRBRUne8/MLFiZMpLGhENSn4JRl0jXiy55C8EIbXlcNpi4yHuMIX/v/ZaoL+EAuV8zaQSK1T4j9ZtI+e72pVLqCZC8K31PN//YfYSgafcK3U10lREhONjDl+OI18S+V44ExlxJfh/6K2D0FdL/dCTI/67bj8aOALbUtaF+txAIFvc1fiyKWRPrLhqMmEgFUFWmPUFBw95vla55vc6iqYT6Nnoeq1SOaEM7KlEnmkPCe262TF6NaIwkn8+grA+FUx3c0PcgpxxwepDjIrclFTW0JNdkFYy4aFHNfeI4c6mazkYpDUGJwyQciOL7MoQuAkoGigPuWjp1lBFZwBQISa+1elAePY5u43uSdvDi7U0qI9SfUTYYsNmRmyhlhKZpvE3W0rCNu8ht7C59Bc+sZ4SmaKi6Lv+cmknVsGAkjanfSHoiuHJJR1KK1dUOIPUaoHMH6Adm37dkDgYQOQzOCKtpGlrRAEh9U1oOEIWHs1kbIEZNgbv0g5FoeV8A2MH3QHOHyVXbuY8Bl8wHfv0C+ZIZTCx+73vpgH14j/DaF/cz91iAuWCk5QBJVXE2oPc4/e0oOeXkMlFdNOl7SGXVjR8k1xwbDhNjpBVlR89EWiZ8h9oPxdacyQg6oddM2lELleoYkgUjdrWBlcrbwupYXG37AlJK16yKSk+WWicm+j5H68a56UOiEpQPI3OSAGvKiOq9jcvAKgYjA/SVEao2y5QR+TTeiDb0wgJwOz12qJURo2CENmsUXl/pvYozGHHnSuldK6ka2j+pYoRUxq2GekZaDJQRqrDQAgNOpiqZUc/FahoWjKQfVOrtdZxSMhWHxW00n4+lXwIajFQLJ6/NHwFbhIFYg39pbf+sBCNBP/AjVUM4Yj6t+1mqoqkaDWQVmn9sqgQcWE/STBoYKSM7+Eo0dZp8/ZxZxGtD2+RryLuUnQ3t+HG/dIILNQh5VEvBCO2YGuXES/0ilSP1m7bJyS0jl20J8ozQFMeke8nQsfZ6U236TdHZFPm+fvkosOBi4IWJ5hswUeVIHei686TgzIoR3Aw8LymRBpOldeGUXoSAbAJ1RAqABpfCSYOeeFu8saRpdJQRACgQgpFoFTU0RTP8QulEb/YY9em9wF/7Az++LV5F28HHNJtGrGAbIM6jaolI0wj7yIfFMn2aogFUxw6eFz08u/kKtPqCCENalPA8Lx5zdIMnVadT6hlpMXscikYsc2RoMBJtSB9VRvyt0VUX6hehnzn5OcvoHMHzUpqXPl6KYMGIFlT2qlateov7EyNq0Gvu4O9rE9tFi7LxwDOJSa61lqwMy4ZIZcNmsdJnpLWWmFTtbmCo0F310/uAr54gv8tTH2YorCb7z4ekoE2F2CtAJxjZyVehqcMfWyvmKMHItnrlXIW8TmGlUpTgNM1uCykaQDr5JiJNEw5Lq/+qMZJnhZY+dzYB70wHnhhjffR8ZxPw7EmkVToNJg5tBr54hPzevIcEJTpBqEjHEbItIK3W5NDgkH43EkVrLeBrJgEFTalaRUyBRiojkcGI8H7mkveXSv+t3qDkrepsJN2Do+HvkAIzrcoKozSNPEUz7ALpRG9GGTm0mczeAqRpwZApI1bTNKEgKWkGgJKBMmVEnaaRnTCF/ZRP7OXkHq/ORrH78n6+FDwPtNO7CwfFQITeVhO6KBTGWtAgKWK/YqFAMLHSz7wZzAQj7jxSCg/od4UOBUi7CUBK9XMW0jT+NuKlAcTPcapgwYgWtDyuWhUk2GyS58PM5Nj6DQB4ILdSeqOdWcCUJ4Xfs4FLXjZuU67GijIiOqV7AL+4hxyot35Mrs+tAI652tpjA9JqV16iLEO3AytVRsJVCPMx1vhHCUaOtJNqg9MGlSHLCVTxgrpR1Mf8/dM5OdE6plJlxIx5FZDe+0QYTZv3kAOz3UVO6v0mkOtpMPLmVaTJXuNO4L3brPkGvnqcfC4C7cCCS4gnYsXj5GTR52QSVB38EXj9N9FPsPTAX9gb8ORH/p8eNOlJK1EckqXl9DriGqFKA8p9DBEpAKqMCO9vnoee4AKkior6CYxSNYc2AuBJIJxTFvn/fANlZMsnUoqmbJB0PDHz3i//q+xxJJneL6RMLCsjTbvJ58WRBeT3lHlGdNI0gPhd9utV0lDFIbtULAlup3fHh5ReE61gJOCVgj0hTZMvqlgJUEasNj4L+qUGd0aNLo0qapr2kMDZkUXOM4C1NA0Nclx50asCuwAWjKjpbJQ+uFqrOnqdQRdSALIBeCozXb/Tges+BKYtIe55q1gJRmieuaAXyaPTihTODvziL+amBKvpQ4MRbd+IT2u+RNAnGv5qHUTWNO0bkROlhr6hjTSYqshzY3hBAG4uAB6ctVyokTLS3iCd9HpbDEYSUdpLFbnSweSkQytVdnxO3g95gHjwRzLc0QwtB4CvZdsG2oGl9wMb3iF/nzEbuPLfxEe1+ytg3gT91RodbqhucU2hhuJEp2ni9YsAsu8WOcHJO3ty6ooslTISoQKIhneDVI3YeXWsdtWXUVvwvULJKq2Ks0X6MXSRD+6UbU9P8JaraUS/SH/AZlOmruTYZAuwEFVGdFrB0+dd0AsFNO3j58V99svSO5rBU9Mecqx05YnvFVVGmlORptn3Lfl+5ZQBZQbpRBqM6Kli9DtU3E8yripUJ4NzhCqgTiUsGFFDD6QFvbXblYttys0EI1EG4NWcol9fboQlZUT4gtAD2uQHgemrgT/tAY65JrbHp82kDqzXzGVqrnDEA0IuglnEl9HUaaE7JUU1k0LOYSEYKc51YWQu2a9OT5m+QUwLo2BkzypyWTZUavVuRCINrKIRTziIVQwn6ZqQH5h/LrluyHnAFCENt/R/zaUUl80h6cfe44HrhEGGP/6bSLilg4hK2GMMCaCLasj7+fpviPdIbZ6llTJ0uKIamsJQN7KLF3XuPBZUaRrqGdE0RooHclItlS9XRuT7YVR9JzY+1Ok1JPY+0VGS6DRrquTaTaZp5A0ZAcV3SppNY1UZEVIVwj4bekYAcWEhpXdViio9yRdWi/fX5g+Lt6X76rBxsEUZZoiiPmKwp7tfsUB7jZhtcEc7wfabaFx+LjZV00kBicGILBVtpbRX9RlOJSwYUaM30plCg5H6DcalXFan8ZpFdcCMClVGqNRrsxMp121yoqMWhb3JaHM+BOyJ9I34tCReekAo7I2CbBIcNMakjOinaQ4LaZrSHDcGeZrIYzgsfsloTxC9lAp9T3tpqGZ6iGmaBCojcqPjsdcptxl7NXDMtcCAM0nr9Q/vkgIGbzMZ9rjtU7JqOrCepGS+E+bGTLqPBJvycu/jpkkr9ophwJX/Adz5RB188ypltRZg/B2inpFEKyO06oAaPmNBZWAN6TU8A2TKCPmMRSgj4owag/Jeoy7MNBjxNkemD31tUo8S6j0TG4oZfL8Ob1MeQxTKSIx9RlQVRvqeEXllnNIzEqmMCOmPgmpRGWml6xiZMqK7r7JjD0W35DgWqAJ2eJu5qrbtwjweM/2djFJA1Hclbw3BcRCHiRqdI0TzKgtG0g+jFr35VcKJOKx5IhYJ+qTptman8ZolFs9IPAdoLahvRMPEKh5U5L0C6JepsDeKhGCkqSMGZUQ1IEsOVUZKcl3oYycH7Tqu1Nr9G7VgVpUImoL6AALtgL/d2v6ooats+ep/5MXkM+nwkGoK2jH4vL8R4/LuFST48LUBz58GvD0VePUi4MXJwLyJZKouHyZBDS1VvuxV4Ip/A1e/A5xwo3IfSgcA1y8GRl9O/l42R1oRh8NSwKSbphGCkUSX97YKUnY8JYqqQF935om8CkGVpmmzkqZpPxw9LQyQXD5duarVkQPryHuX34scmwDNsllNaLqRIgtepNJei1N7xcUPeQ90PSNARNCkG1TI0jSi18NH0zQh+EP64ycASJ9NWTBSkJVAz0hxPwAc6Rti1J/o4E+SeZX6vaJhNBVYnqaRY7YlPFNG0hijVR0gnYijNP7C/nVkVZpTZq201AyWPCM0TdMrsftAT7AaJ1dNiZceEAqqUZgdR742qmeEKCMluW5UgZhX94RMplIoVEFqq9ceclanSpOYwZ0nzeKI18SqmhIr3v/t64GZ+0hPFmpgLKwGxgkeoQ//HxkxLpeS931LPkMjLgJu+Ro473Hpf558YNBZQP+J2pM8K4YD5z9D0jqBDuBbYVJow2YSdDmz9T/3nnwpYKCluIlAbN5koruvHqrvltQKXnVS9rUCwU7ye47SwCr6I2jA2LhLX6Wgfo/SwdGnWNOKMLXpl6oq1bIUD02BGCkj9apgRPadirkDq/gekO9R1KoVlbfFimekyRcWb+szSimJwYhkZJcHSTFV9clxZklBg1ZKjudJn57FM4HnTgbAk6onM59To3bzYpdpVdNMqvCZTtMwz0h6EQ7LSsCi+DloFQWtqtBC3i7cTCtyKyhKtww+bPTgkGhlJEq6RDKwyk5i4klUCkaaEp6mEZSRHBeKg+RLttVrog+InJxSUqkCPlIdCXTKXPkGg/7kcFxiTKz+dmnlJQ9GACJ7yysUKKfeRbZt2g2sfYlcd+m/gItfJDnrK/5Nfi8fav1zarMBx99Aft/6Kbmk34lex0WvEqPGbfp9i5dQQAr04pmxoaqmCYZ0mmnRx3LlkcoZILLBV34PMmsmHNT3E2x4l1warZJpYKdWRsTherISUbOeEaqM0BOpsL28b4dlz0iLUhnJi1a1ovou67aClwUjhYKq2kKDET4Ef5TBnACk0ld5mkYIasI80O5PQKomWpO79a+RkvivnyF/213AmfeZu1+apmneF5kCCnRKn6syVSGE2VQ+U0bSlCPbpfkF0dQM2l9i/zp92Z0aHc1WXFjBrEEp4JWadyV6CFKUdIm2gVVa0RdkUc9IHGkaVTASDvM4IgQjpblu5HhJc65N3kJ4AxZm+Cjab6tKKQ9tBsADWcXWVxKJMLHSg7I733yjuqxCEny48ohacdJtZELziIuAa94h6kc89P8F+Twe2kj2jw4jM/rc02BOvTqPlbY6ADxZbdPGdbGgGrUQ1JsGq7GiVPQZAchniebytVI1/g7SORUgqbZoiBVIu5TXi760UbLnYLK0l66q6XshfKeCYV4871lSRng+orW4ZOrV2Be7OhgRlBF5ejcUlBYF+ZIy0tgpnZj9gUD0fdVI03icdnH7iEqfWIg2KoTOORs4GRh/K3DpK5IPyIj8XgA4osKpOyA3bIV4PMpRfeYNOlWLiJ/j1DY8A1gwooQeSHuMjb6qK6ohkl84QOQ3NaGg5Ccx24vCCmaDEZpDd2RFl4BjQTXCW45oYFVX0wBAQW8U0TRNXKW9ysdt7gyIZsPiHBfsreTEfYAvxf6mTmuPQVNa6nI60Tw6zLqKkIheIzSgoytZs/QYA8zYANy9AzjrgcQqddnFQE/BeLntU1kQfmL025UlWBmh5tW8ytgG5FEiDKxCpYY6TUMb2MlWlGKfEZ/scx2tombj+6TpVGFv46ndNE0jV0a8LZJSJw9GzCoj9PNNT4xCWidgpomYFh1HSGoaEL1X+TK1iFev7FXpJM1FTPshADx5X3LKRFW1UTbbKhAUghEtFcffLi3IVGoiDZRiOg6pobOI1Gbl5v2SSn7uY6Sa0cr4D4dLKu9VV9SIc8+GRH6nTadplL6nVMKCETniqs7gQMpxwPALyO8/L4z8/67lpIVvdkl070msmA1GaCSdW5b4VFGUYCTioBL0S6ubwt5SmiYuz4jycWmKJt/jgIv3gxPSGbV8MWqbvNYeQ6+vg7qs1grUYxNPmoYejAotBiMA8WnE0lPGDAMFdWXx/5B0HGc3PrnS1bjaRBkr4nyNOPwiQIRnJKA3DVY8iEtNyvK1KkfEihpVMNJyAFj8J/L7mKuMv59UGWnYIsn11N+W31NZZm7GMxL0EcMlIKVwhQBM3rfD0mwa+h7klItN55TpENUqXSdNowiA2oTxA7nlgM0mmt8bO2XBiKCMaDY8owG8hpqYn0gTa6mOMrLhHQA88VbF8r0FpMWH2jcizj3T6KtjU36ONQmHpOMRC0bSDGom6z3eeNvhvyaXWz4hVQpy6JyIoVO0zX/xopg9EEWGo8FIPLK17j4op2bKiTiotOwDwBOFJqdUTNPEVU2j8socFsyrpbluUXoMwIkm5KK+1WIwIs4C0VNGYghG4lRGtta14tA+YdVlVRlJNsdcQ1KbQstuDDzTuHScHkDb6qJ3uzWLKOXHOexLpx18RJqGfrdkHVPzZCkJUQWg8v0hWZomHAL+cyPQeYRU2p1yh/F+VQwnr3H7IekkJDZVHKXcVkx/RDnJ0s+h3SUdH2gnVEEZ4TiNICwaGtNf3Q6baP6N7MKqCka0+oyoVu4FwkLmcKd03AlGS9OIn4vINLXYQC0Rjc+o0ndkB0mPU6iHasi5sd83DWLUfiH1EFY5KoVPk85GKVjJLtHfrotgwQil7ZAksanbwGtRNZr4SoKdwJbF0vWhgDSEbviFid9PwLwyQuVJdT4xEUQJRvxqI5rYBbYnwHFJMbCK5tVcl3gAa3UUA+BQ3+qz9hh67bflaRqrUDk/hvk0/mAYFz+3Cl+tFUoCY11hJYu8CuCUGeR3dz4pKTbCnSv5sqgiGSMf/HAAn327nvwRbzCiMygvIk1DjcSygzg1a4bCPDqpT4mW9deuJx4RgMyC2b2CdLO9+CVzreudWZJXjfapoCWi6j5GojISxQshNy6q0jryib0RXWejITZYlE78HMfp+0ZUpb2a1TR0MKPgaSgUAogjHdJxR0zTaAUjUdIQYpomEcFIXhXgKSRBbIOsQoyODaGpzFigJd/UJE4R0zQaTf5U06c1oapIVpG2+b2LYcEIZftSclk+zJy/guMkdeQnWapm+2dkxZNdKrVNTzRW0zTJUEaidEKNUEZU003FPiMxpWm0gxEa2BRkuURpt9NNnnd9SwKCEW+zdLCNpYU/XUHH0PhsR0MbmjsD6MmR97PelnpJNYJT7gDOmEVMsWYDggGTyCWdXh0jD364ES2HSAqr1aUx28UKNuVBXN4OXkFH5Hcr22UXq24ULeHze5IOuXu/JurB8kfJ/375qLJZlRG0Sdb2z0igsfUT8jftiEwx4xmRG3BVCwuamnJbraShgYNq+isN0iJO+qrSXk3PiCqYoNU0jV5ZMBIgCxFNz0iUahGpC2sCDKwcJ1Vg0vL/lgNEmeHsQNUo/dsaMXQKudz9lfR6eJuljsNaiyMzfUaSeX6IARaMUH54i1wOO9/8bUYIwci2JVLzpu/+RS5HXWp9AJ5ZTCsjwuotKcqIBc9IxAGFKiMxTO7VCUY6hPK8XLddPCgGssiJKeY0TdMeKT9Pqz7ye8ZmBhbTNNaraTbVkk6/VRxJZ/zUnm/98ZONww2c+v/0G3dpMehscrn+NfL6muleqeJQqw+1zV6Ugnz/vj0U5wpPNZtG9IyoT3R0UCAdrAiiAkgVNQF6pVS2u/1zYMksoqZWnwiM/o21faPByK4VwMb3yPc7qzhy0WOmA6tccdBpPmZ5Yq/oUVMGy7Tjsn6aRtmBVekZUQYTVBlp84XAC/sdDAQjbxdx+8gAXmx8lghlBBAnAosdcenIkPKh8Q2hK+wtlG7zkuq+V+gRVNQ3IvgDYM7AmkzlPAZYMAKQkyUdwT3yEvO3Kx9GmhWF/MQn0t4gjeEee1XCd1NEPpUxWp+R9tSkaSLkVnpAEMpbC2SmtjarNf46JWttwgTgbLcjosWx5TRNyUDyGncclvLg8ZhXAam0NwYD68baFgA8ytAEAPi+2RPbPqQbNaeQVEU4CDwzDti8yPJd/LCvCQBQwrUAADa3xjitl6LTDj6iz4hOoK/Z/rzfRHK58kky7wcAzvpf66by8qEk7RP0ki66ADDkl5GLHjMdWOULBLu2QmG5xwj9bKv8B2KjsghlRHkM0ewzIhpYhfk/WU7pZRPeq6CYptHw56la9ssRG58lwsAKSAoFVUbEFM0x8d83Tfmv/ic55ot9rE7W3t6MgVVURlLvFwGO9mBk9T+Al84Fnh5H3rSex1qTTTkOGHsl+f2b54GvniBf6B7HJKeKRv64FDORbzINrFH7jAgHB5Uy4nHa4RF6CTS1WzwQ6CojZD9y3Q7xAGYXOhweshqMuLKlAwudzhyPeRWQqi78bZJ3wCQbD7aiAO1wc+Q5rz6UJMWtq3G4yRwditF0Ww2+39sEACizEfXo+8Y4lRGddvBm0jSARq8RgHSxdWZLf5/3uDlfmhqOA85+WHndyEsjtzNTTdMmS6nYlApFzN1XxQBNmSqjakaEYV21n5qeEdXCwm6TPCi8KhjRbF1vIk2TEM8IIB3zaZUT7Y5rRS3UY+zVpFdQ/c/Eo0iNsX10ii3M9BnRMGGnkqM7GPnxbWIk6zxCDhaTH7J+H8dcS7os1v9MVj4AcPofE7ufahSDkFKljFjwjGj0ZJB8IxYranSCoHaqjLjs4mh7TxHxLtS3WEzTAKQ3ByCZBOkMnsoY5wy586WW8BZNrBtrW1DGNQEAmvgc/FjrjezZkKmc83/A6CvI70ZNujT4fl8zOIRRDBKM/HDEgU51CakVVMpIUCtNEw5LFUA6KoDiBJdTCkz/Brjon8C17wPHTY19//qMBybdSyYzX/4G0O/0yG1MeUZkCwSVvyDmuTRUGVEdb3SrVmzaaRpF0zONYIKmecPCexWKVtobxcAqvleJ6DMCCP2H7CTQO7xdCkYS0fgyuxg4Qeh2/OlsKQWk18eKUwbVmnSHNM3TTz+NmpoaeDwejBs3Dt9++23U7ZuamjB9+nRUVVXB7XZj0KBBWLTIuiSbcC54BjhjNsldX/Uf4/4iWmQVKqem9jkZGDQ5UXuoj5n5NKLjP5lpGuUJJBTmxa6VEWka2QFFlG6tHggMlJEcl0N8vNxS4v1o94fEYMU0tL32/nVAZ5NURknnElmF42RdWM2nao60+3Go1YdyjngiDqEIrb4g9h6x2MgtnaH9T4wGu2nw0/5m5KMDNpD3v4HPx6aDLbHvS8RsGg1lxNskHeRVwYhuD53C3qTLat/TYt83yil3Ar9ZoN88y0wHVnnnTZWRVJrYa7EtgY4hUvc1sWunacT0EM+LCwt5MEGVlrCojASVt5MTRRkpiqffkRbuXEkFWTGXpNNyyqReM/Fy0u3k89awhQRwPcZKzfDU2Ex4RjLdwPrmm29ixowZmD17NtatW4fRo0dj8uTJqK/XXu35/X6ceeaZ2LVrF95++21s3rwZ8+bNQ8+eCW5PHgvF/YBTZwBXvBlfp9RJs0nL7bMfJnM+Et1gTAszswdEZSQJOUEdt7a8YZIrwsAqyYFiJ0WrvUZ0FBnqGclxS8FIVlEPopQgBt8IzfMe+I4YBvmwUBkRR1Mt+vwtmFhrm0nQ0ddDenh0OIlhckNtHCfcdMNsx1AVvmAIh9v9KBUCtXYuBwE44nttItI0GtU0VBVx55MOmTKo4tccSw+dRGHm9WyVnaT1pufKlRF/O/Dzf8mAQC1CAamJmkr21114qNM0tM+IU3gP5MMI5QsZ4TUOQ1BGQjqlvUE/Ub1Vt6eIlTmJfK+oUvXdq+QykbPJsouBsx4kv7tyidKmd99m+owks8AhBiwnn+fOnYsbb7wRU6cSqfG5557Dhx9+iBdffBF/+tOfIrZ/8cUXceTIEaxcuRJOJ/nw1dTUxLfX6YbDDQz7Vdc+ppEy4m+XvshdqIzIgxG3wyZ0+aMue+mAUJwjHAjaY0zTqL5ktJomxwVZnrkS5XnN2HW4A/UtXvQtteBoLx8OuAvIAXbxTHJdzanW9lUNff40X28CegCvdrYAPiCQVQ60AXuO6MxEykSiDD+MRkMb+eyU20nTQZ+rGOgEtta1RbtZdMRcu6CMiGkaeTCib/wrEIPsBK22Y8HIM8LzstRpmfR9iVBGZCf3RX8A1i8g7QwueSnyPumJjbNFVJtppq4AjQ6sauM7HUaYq6hGoYpGSHivQsEAAHdkMELTRjaHZgWcmCpO5HvVbwKw/K/S34lu7zD6N+R8U9wvur/RSp+RNAlGLCkjfr8fa9euxaRJk6Q7sNkwadIkrFq1SvM27733HsaPH4/p06ejoqICI0aMwEMPPYRQSP9F8vl8aGlpUfwwVBgFIzQAcHjiKyvTQycooAcUGyfk2TuOCF8IThEU0WDkiOVgRFsZafeRxy3g26THyylDeR7xaVhWRhwu4IQbye+0DbtWft4K4gC+2ujbyaCrth52svrnBbl6zxFrJti0xuxgNxXUmNzXQ16LYBYJDvY1xpHC0lVG5PNS9HPthVlJOMFZxagDq7+NVAAC5Dup+k5pGljXLyCXWuMvAGUljapbbaFeXyGdZmui8V3H00DTNCFeUEbENI0qrSSv4tOYV1QUT4sBPXodTxQzgARAQ89LzP1SOI60lKCeNj1syqBak0xO0zQ0NCAUCqGiQil5VVRU4OBB7dXejh078PbbbyMUCmHRokW455578Nhjj+GBBx7QfZw5c+agoKBA/KmuTrOOk+mAUTAid/snI22k0/QsojxPPCCUKkoQi3NICebhmJUR7T4jBWGh34unALA7UZZPHsdyMAIAJ94sVUEM/iUwZIr1+5CjNw04CnSFXW4jz8tZQHoKdCvPiJlSVA1oMFLtJsGITThp7WuMI1BTe0ZCGp4Rje6rFPkJLmUYdWClaSaHh1SOqTwjPlkHVtNEObEVioMx1dU0dsV+RhjfdV5nmqYJCKcv0TOiVkY00sPK/RLSPbzOVOFYcLiBK94iFVO3rYu/I3CsGPUZCYekFFaaKCNJrxEMh8MoLy/HCy+8ALvdjmOPPRb79+/HX//6V8yePVvzNjNnzsSMGTPEv1taWlhAokYMBvSCEer2L9b+f7zoBAW63VdVOduSuJURdTUN+TuPFyR64XmX59FgJIaKmpxS4KqFZMjZ6Cvib2InTgNWBSOhADloaLQFb6Jt7vkmskvF5OC2tzsqIxY9I/Q9rXKS99xZQD5j+xs7wfO8tVbmFHU1TThamkb/xJswU2QsGHlG6EkoSzg2qDwjYpomlmBE48Smn6bRDoLcBsFIsfAaB3myXVjPM6JTakxxOWzIcdnR7g+hscMvptjips94/ZLbrsLIU5hmc2kAi8FIaWkp7HY76uqUBry6ujpUVmp0gQNQVVUFp9MJu0xCGzp0KA4ePAi/3w+XyxVxG7fbDbc7zuZF3R3OoLS3s5FcJi0YiW5gFQ8oOnnJopiDEe30ULugjGSHhZSepxAAxDTNIast4SmJPLCIyohsAF/QD/z9WDJE8JavI+RkqowUhMn7WVBeDSCEfY2dCId52KwMMktXYvSMUGWEekZyCkkw0uoLoqUzGNvJRZ2mCdGmZ7L3JUqgL6Yk0kIZ0QlG1Cd51Xcqpg6sUcpEC2XBiOIzqwqaIjwjOtWAxbnk3BAwCkboMVA4FmhRmO1Cu78TjR1+1CAJ6exUYdRnhL62goKcDlhK07hcLhx77LFYunSpeF04HMbSpUsxfrz2Afvkk0/Gtm3bEJat4Lds2YKqqirNQIRhEqM0Df0ixtK63Aw6/T7oAUU8MIj7oTxwx66M6KRpBGUkKyS4/YXnLSkjMQYjiYS2mW/eL7U+37+GtJ1v2CxNvZVBT2p5QXLwKK7oBbuNgz8UTo/nlAji9IyUCK3gHfnlZGozgL2xpmoiOrBq9NyIGozEMQQyUdgNgrsOulAp0tyeKiO6s2m03idx0RGpQuTLOi63ykvs1V4V3TSN8nUuFY4d/jAn3Dyovb+0uifKMbAoJw3er2RglKbpUKljaYDl0t4ZM2Zg3rx5ePnll7Fx40bcfPPNaG9vF6trrrnmGsycOVPc/uabb8aRI0fw+9//Hlu2bMGHH36Ihx56CNOnT0/cszgaMaoj72wil1FWBQl5fJ1qGnF1Q/dDdUCI3cAaeaD1B8Oi6c4TaFE8Xnl+HGmaRJMnKCPBTilI27dG+r/GKqaxww87QsgKNAEAHPmV6FlI+nJ0GxNrnJ6RAl7wCWWXolcReW1iNrGKiqMwm0arHbxOgA3IDKydgdQ1pjOrjKjTNBpTewFEzgyiKoicKJ4RecdlReMzlbclwm+m01iuOJe8xr6woIyEDZSRKMEIfb8SWt6bDhimaZKcxo8By0nwyy67DIcOHcKsWbNw8OBBjBkzBosXLxZNrXv27IFNJmlWV1fj448/xp133olRo0ahZ8+e+P3vf48//jHJXUq7O0alW12ljOh6RoQvg7g6KVRsR5WRRsHJbjrdoPG4HbL5Nq6AcGISlZEYq2mSgdNDDtYdDcQ3kl0sza8AdIKRAApBS1U5IKsI1cVZ2HOkA3uPdOCEvulzMImZGD0jh9rIe5oTbCJX5JBgZP3epthNrKqDOJ1NozBzRvluUWUkFObR5gsiz5MCCdysZ0RM06hm0wipKfHkToeAUtrqI4ezGfSsKMxy4WDAi6aOAKrpR1Zd2hsQ0jS0A6vO7JRiuTJiA8JqNVZ8nvR9KtTcJ0De76i7KSMGaZooAXWqiMmRd+utt+LWW2/V/N+yZcsirhs/fjy+/vrrWB6KoYfpNE1hch7frGdEJ29LPSNhnqwi6QHGEPFLJgUg7X7pYGT3NZErhedN0zRNHQH4giHlEK5UkN9DCEYOAJUjlcGIRmDZ1OFHEUdTT4WAzY7qomwAh2NPRaQbZqbMakCVEY9f+IzllKJXETm5xK6MaLeDVyojVOKODEaoCuANhNHUEUhNMGKU9lKnmcSUaxgIh/XTJRRapSLHoGdFYbYTB1u8yvEPEZ4RHQOr2m8m+HJCUHlG1GkaHVVW675S6vFJBobVlvqf4VRxdM+myWSMPmwm8qVxodtnRHUgEw8IhYrtnHYb8oUJp0faLagWGo/bQbuvuuwRB6DCbKd4kLI8MC8ZFAgVNc37iHekea/0P400RWNHQJy7QleINE1zoKmblPdGmQCtB8/zqG/1gUMYDh8tUSyLP02jMyjPqZmm0f5uJaWZlhWMlBG1gVVeJRYORqZp6ImLojVbyWDoWr5WF1ZZEMrzfGR/E51qGqfdhoIsJ4JCB9ZwSKe014Q6XBRrJ+h0xzCNn35pGhaMZCpGpb3JTtPo9Bnxh1SOeBoUaXhXSgSz4RErk3s1jLNt4pA8R8Tz5jgOZWllYhWCkYatwGbVfCaNOT8t3gCKOCFNI0iqPcRgJA18MIkghnbwrT5y0ixEGzhZiWKPQpKWo230LRMxm0ZVTcPzhpVqtJQ1ZSc4I8+IXmkvAIQDkR1YO1XBiNY4A4MGWpr9V2RBaCDEi9YUI88IQNK8tOkZH449GClMdeCYLIzawXcHAysjTTBb2ps0A6uOZySgTtM0kUuNdJFkYo1FGZF7RsgXLtft0HzeYjASa3lvIqGD9rYsBja+p/yf6rVs7gyA5yGlaagyIqz+93c7ZcS8gbVJCGB7OoUKJE8hYHfKArVEpWmEpme0msbfJu2nzkku5b1GDJURnTQNoFBGxNk0EWka1aDHoB/wCb4SnTQNbXKoWHjI9pNW4QHCsSMUkO5TIxgpznEhJEwu50MGnpEox8DuW01j5ClMP2Uk6U3PGEnC0DPSRC67OE0TIbVGUUaonG2pC6tGFQ+dyJvttmump2gwcigdKmoGTCKdLxt3kh85qteSrqwrnYI3RDhw0DTN/qY4mnulEzGU9lLvQbW7AwhCPAlWFZDXprEjgE5/CFkuix4hm7YyInZglXcvpdOGVaTch2DZMyLztYRDkcpIRDCiUkZodQ1n1z3xFwsnfcXCQxaE+tQzrdrofdo075MEIyplRO4ZCYcl460Jz4jlqr50R8fTJ5Ls80MMMGUkU4kWjMil5KQFI9qlY5IyIvw/ijJSKpToHWmzEoxEBkHt4pC8yDQNAFTE0xI+0bhygH4Tpb+rxkgrP5UyQIcIVjqE1b9w8qjI94DjiFm4wcprl67EUNpLu3n2cgkpLMGrkO9xEIUMwIFYUjVGBlYTVQhU8UvZe2O5A6sNEFQGhALwqTuwyqcUA5HVNfKqF40ZMIDspK/pGZGrMTYSXNMAJ6tY8z5Lcl2iZ4R+btxyZcTXDEDI+0Qx8ZeIik03+B7JMWtgTSNlhAUjmUq0OnJ/u3QgSlo1jc7UXvmBLNAJhIQAQGN1QxtUNbRZSdNoKSNCmsbFaUb8YnlvOqRpAODYa8ll5Ujg1y/oqkx0XkaJXQhGhJOHy2FDhfCcuoWJNYbSXiqrVzpo+38S0HEch6oCwTcSi6dGdRCPKO01EeRTJc7S5zqRRPOMBDqBgFJpA6AICAPqDqxUGSnsTS79quZ8URqeUUpyNaZ0K9I05lrBU4gyImyrZWCl75MzR3PMgnq/Drf7UtcXJhmYNbAyZYQRN9EiX5qqsLukQW+JRqfpmaJXAA0MODvgzou4CzF9YikY0e8zUuLwQWs1FNd8mmQw+Bzgrm3Ab78AygbrBnZU8VFX0wAQjZrdIxixroxQP0a5XXhtZCfCKuobiUUZUQX5NGUhKSPGB3EaZKeseitaB1a6IrY5JKWD/g0A4YByQQFIz5mar/1tUCCW4OrPONFMySrSNKoeIwYm4eIctxiM8LyGZ8RkawOqYgVCPFoSNSwvHYjWZ4TnmYGVkUCiBSPy1Vuy/AR6Blb5gUze8ExjPyQvR3ylvVQZKbIJKzZntmI1VJGfRo3PKLll0olPJ79LW9wXiMGIdODoUdiNTKyq6a1moBNgSzih467MONkznkAtoh08VUbUaZpC3buI6XOdSKIpI/IUjfw7KQaEGp4RuqgQg5EYlBEhHdKoFYyEAhrp3ejm09JcyTNC3yuFZ8SkJ8LjtItpvW6VquGiKOeBDkmxZmkaRtyYCUaSVUkDqBz40j6IBxWnzXA/YgtGIhWZTkGNKbYJ8rPqAEQfpy5d0jRqDJSRfDr8T6aMdKuKmjg8I0U8DUZkyohgYo0pTaNWRtSlvSYGUKY8TRPNM6Iz70UKCAMK/wYAE8FI9LJeQKpaOdLul9IhsoVFhPHdIJiozPcgKJy+HIimjBinIcRUTarer2QQLU1DXxubE3Dldt0+GcCCkUxFlOEMlJFkQT/sgHJOjKiM2KOaVwGgLBY5W0MZ8QZUCoIq+KHzaQ63+8RSzbRCb/gfLVkO06oA6QTSrRqfxeEZyaevjSKFFUeaRgzyyQkzYlBehwnPiOxznRIfAlU5hI6qCvR6d8g+gxFNz6jCWVBNLtXBiDix11gZ8YfCYsdkhWckoiVAdAWqssAjKiN2IRjRbtmvfXvlvqXYcJwMovUZkZtX06gSjwUjmUpUZaSJXCbLvApIH3ZAcRJVKCNRynoBoFRYQbb7Q2J5riEaJ+5O4eCWx9PmYMoTRUmOGzaOnF8slRF3FToN5Np8QTIkL6Q0aQJAj4JupIzE4RnJDdJW8NKJsEdBPGkaZa49oFtNY+wZ8QXDYkO+LkXRUVUV4Ol5XmSBQcRsGvqc5Z4ReZAldl/V94xkuaRheWKqRpZOEj0j6pYAOq9zRb4HIZ4qIyolB7A0KJT2QDlspd9RuhOtz0gamlcBFoxkLlENrMJq0VOQvMdXNUqiKMxvBkFRjsuOLCc5EZuWtDVO3DRNkysGI8rHs9s4WaomTUyscvSUEV8QBWgHJ5pypYMHTdN0iy6sRp6RbZ8C/75O0Zacpmk8AWkuDUXeodayMqEzKM+hTtNEOZBnuezIE3wIKfGNyPuGqH0jeiWdMt+SXz54LhSQDKv5PYWNeakiBzBsBU8pEU/6NBiRvssRE3sNUrwepx12B3mNbQgjy2lXDtu0MA4jphYD6Y4tinIunh8Ku2x3zMCCkUwlWk7QJ+TRUxGMyF3xBsqIvFW76YO2hmeEpmlyw3SgXOQBKO3Ke+XovJft/hAKaSt4d4FixUtPuEfa/aIylLEY9cV49SLg5/8Cn84Wr2ruCMCGMFz+JnKF7ERYKSgjnYGQGLSYRq8DKz3RmQz0S1NpYrXLghH1a6qbppGV9oZk5cx0QQEAeVUQ+5HIUzXUwBrFMwJIvhFRGZF5hSKG85kwoLrd5DV2cCH0L89R/jMWz0g6qqaxwkU5P3i74PwQAywYyVSiyXD0gCkv3Us0cs+I7APvC5pXRoAYTKzyCaMCXiE1lB1q0X288nSaT6NG1zNClBEAQJbywCFv7pXxqRqz7eDrN4m/NnX6UYRWmWokrfQ9TrvoA7CsHOnMphHbwZsMRsrEHjopOMHJFwpqtUnd8Ex9G5mB1e2QLShoMOwSTvry8l6d6bpqIsp7tUp7TXpGAMDtIvdnRxiDK1THOgueEZqmSZnhOBlE60PVFcp5DLBgJFOJmqahkW8SgxGOk+XX5coI9YzYDZURQGb2M3sg0PKMCMqIJxRFGRHLe9MwraFXTeMLIZ8T5HDVgYPjuO5jYjXbDj4ovXfNnQEU05k9WcVKnwQQ+4wa9dTekCpNY1oZISfKlIwg4Dh9U7BeMzF507OQzMAqLiiE50urL6gyEvRJSqxBMEIDRG3PiMxrBphKs2S5ye0dCGFIpaqPkYV252KaplspI1H6jLBghJFQogUj9OCQTGUE0DyJdpkyomFg9QSpMqKVpknj8l4zyohGQNdtGp9FU0bkno8gee+8gRC8gTBKOf3hbGIXVqsVNQpjdhjBsGpQnpgCLYx6N5aD7ESj12vE0DOiSpmo0x2iMiJ8LqlfxOYwfE0iFAhZczbdMRJR7jPLTd5jG8IYHBGMWEjTUC9Ld/KMRE3TsGCEkUhMKSNJ/rBpnET88hWOGWXE6kRdjceknhGXX38wFi3vTYtheWps2quYNl8I+RwNRiLfy27T+CyaZ4Se/AFRGaE+kFJbZPdVivTaWHy/5XNQ+JByUF44ZNqPRZW4g82p7jWiCvCoMqKXpgkHxcaFTjsX+R2mwYhPSNPI/SIGZaIRHZfl5cRy43soKL3OUYIJl4sqI2ENZcS6Z4SlaVILC0YylWh9RsQPW1cpI9IHXsz9KpQR/QMCHWJXZzZI0Dhxi8FIQN8lTme5ZJpnJF/0jBRG3KzbND6TP3919Yt8Yqywqqc9Rno56QDByJJSqhpZV0bkwUhYStPYbcrAyEB17CW8N/saO6JulzRkHhAFYtM2bQMrH/IrO7CqvRdimkYIRsQeI9FTNICGCipP08jHSMgH8UU5YdoEZcWOkHjfIhYaP9JS7CMd/vTsQxQLLE3D6DKipmmogTXZykhkYx2FMmLCRFYhriDNBiP6nhGHCWUkvUt7lQcOpWekMOJm1DOyr7GbBCNA5MGzXRaM+FsBb4uojIhD8jSUkZi7sCrSNCEpTWPjpIO4MxtwuKLejRSMpOi90VKbQgEpoIpI05D3IBQMivGgW9G40CBNYyIYKY8IRuQGVg3TrCsvwgskZ1BlIQBgXJ8CMumXIh/QaUIZKc5xwW7j0rcPUSykuvVDDLBgJFNJtYEV0Oz5IXpGbObSNPSkcdBskKBx4qbBiM0bJRgRlJGGNr/YOyJtiNEz0ruYDEHcczhFq+9EoShF1UkrUFoOoEmYSyMNyYs8EcacwlJUiYXEz4pdHoyYOIj3KiLvzcEWb2pW21qeEbFPCxf5HISTfki2vdOhkaZxqwysJlrBUyLa5Nu1ghGNAEgHp5MEhEMrVMNA6SJIZ0CnGruNE821aVn6HwvRWj+wYISRUPRygjzfNX1GgKieEQ/nB0LCKiOKMlIpKCNNHQEx3WLlMXmehzcQhht+2EJe3ccrzXWB40gTq7RzzWv0TgmHeXT4o3tG+pSQVerBFq+51y5dUSgjOtUflJb9YvfV6J4R8rmqa/FaCz4jlBHZoDwLB/GyXDdcdhtCYd58oJ1IqHIjD0bknTflQRcgvgfBgPTdICZ0PQOryjNi0PAMkIKRw+1COkTW28SnaZo1eJ11BkzGMihU9JS1paFyGgvR2sF3VRrfIiwYyVT0lBF/m3RdV1XT8HLPiBCM0MoWzh51GFN+lkPswmoqVaM6ANHHK0Sb9Hgaz9tht4mu+bQr742i9uSDDv8rjLhZUbZT7PS590gGqyO2aMpIg/LvlgNoEYKRYj5yLg2lPM8Du41DMMxbazym4xmx22yW+vfYbJwYEO1PRarGQR5bXg6tW0kDiO9BKEheW44T1CB1RZy6tFf0jOi3gqcUZUvpkCPtfuXUXnmfEbPdU/WqsCz0GKGkdVPEWDBlYC3sst0xAwtGMhW9YISmaGwOwJmV3H2I4hnxyBuQRVmdcBwndsw0tYJUHYBoWW8BJzN66jxeudXKna5CI91FZ/UURlFGOI5D7xIiUe/O5FSNfJWu7jWimaZRDcnTWJXbbZyoulkamKdq5qfpGTGpOPZMpW/EIRg6g7LPul4lDSA+75CgjLjsNuLDMFRGaMMzY2VEkQ5p9SkqfhSeEbPmU91gpEm5zyZI66aIsaBnYA0FifcKYGkaRoLQC0bkPUaSPZFRlV4Ih3mpRC+gPUFXiwor5lLViZsqCKV2qiAYV+6krzIiC0bEIEvfwApIvpHdmayMKJp0GQQjnY1o6iQnzNxQE7lOxzwp9hqxYmLlOIgtz8MhWTWN9WCkVyF5b1ITjGgoIzRNo6EkyQ2sgKwtu15przpNY8IzAqgqauSzacQBm+Y9I1rpTQAxTS233O8o3TE6PwDJV84twoKRTEUv8u3KuQOqE4hfZtRz0jJbE1KpWPlgKk2jUkaEYKTMoW/0pKStFKuR7qLKSEEUZQSAqIzsOdyu+f+MQa9jKF15F/Ull52NaOoIkGnGQX1lBIi/CysfDsr6jNhiVkb2N6UgUNRURqKkaQSVIiykacQJuBFpGsEQKhpYqWcklmBEMtkqB2yaTLPopSIslPVSJGUkzRYqsaJnYKXBiImKsK6GBSOZihj5qsx5XWlOUnkdqNQKAC6/FWXEQnmv6jG9ojIinHCirIbKrfY06So0Vngd/hAAHrnQbgdP6VNMVqp7MlkZAaJ0DBWCkZIB5LKzkbSCB/Uk2XTf86rCGNI09D4BhELSSY6kaawF+lS12tmQgkBR0zNC0zQar5fwvQoEierkEXxc+spIOzn2tB4kf+dVmdotRWdaeZpG0WekSX8/NfY5ckFm8vby/UrnPkSxoGdgTdNKGoAFI5mLmTRNslGdRP2yYMROp6maUkasBCPK1RANRkrs1DMSJRhJV8+IxkG13R9ELjphh/Ca6ryONYIysiuTPSOAfmWETjBSyQmr39yKyMoQgZhn9wgHckUwEkOaZmAFMXtuqWsDr140JBtRGZGnaXQangGyahoSDGa77EDAK91eVEZkwUh7g9DPgzMdjEidkH2yKioeAeFxSWlvvJ6R2NM0aXdsiBW9QaosGGEkHD0Zris/bKroW+6I5yyYyCqtzBGJMLCS51/EGQcjVIFJu8ZnGgfVDl9IqqSxu6SVror+5eSEt/twe2aX9+q1hKcnluJ+4t9NHQFU0GAkyknQUvpPjvDdCsrMtLGkafqX5cLGkfb1Xe5FEJURDQOrZjWNsrQ32yUbdMnZpPQMrabxtQAt+8nvueWmJX+aKj3Y7FX0lwkFyHvkcZrr3Ez2K3GekXJZq/ouDxyTQTqcHyzCgpFMJR0iX7VnRN4rwETDM0pPK3NEdDwjhfJqGh1ED4HVk1Oy0TSwBmV+kcKoFUIFWU6EeWDHoQz2jWitcnle+jzTYMTbJCgjgv8hajAS4yBB4SQXDsqCkRiUEY/TjppSoiRsrmu1tg/xoqWMdEQxsAqBQTBIlRGHTKEokMYw5FWQy9aDUjCS39P0bikGGDqkaj+fl7xHeR6nBc+ITpomhtJeqoz4g2Gxw29Gw9I0jC4jLdI0yhOIdhfFQsO7ocFIQ5vPeHWvmmNCtxc7lUZZDdFg5FCrT1Rx0gJx3o5yEnG+gV8EIOW9g4R0wNb6Lj7hJRLRMyILRnytUrBdTAysfGcjWrx+lIvKSKXuXUqfK7811UgI/IIRnhHrB/JB5URR2Hywq4MRDWVEbHqmr4yE5MqI1uTcgl7ksv0QcHg7+T2/h+ndUiwI7A7xpBn0kWAk1+0wv5DRbXom3N6CMuJx2lEslB2npEldorGlwWLVIjEFI08//TRqamrg8Xgwbtw4fPvtt6Zu98Ybb4DjOFxwwQWxPCxDjlGfka40sAofeL/WfAkTykhhtlNsfGYoqav6QEjNwYRSwygHoKJsJ9k3AHWpmqaqhU7TswKOPqfCqDcfWJGiE14i0SrTpCtcu1tUQLhwENm8FxVoIv/L11dGCrOd5KQKi+oI7bkhBEZ2G0d6bsTQLGqQME12S1ooI9HSNPQ5C8qIPCiQf6c8hVKqZp9w3KcBigkiFgRC0BT0U2XEYT7NkkDPCCClcS2n9dIRvUGq3SkYefPNNzFjxgzMnj0b69atw+jRozF58mTU19dHvd2uXbtw11134dRTT415ZxkyjJSRLknTKMuLlY2Lmsj/TCgjHMdJZZBGPRnkwUg4KK5483jj6h2O42QrszQaLqcRjJBW8MbKCAAMrqAnvLak7F6XoOUZkZ8MnVkkKAHpttvTbuwZ4TgO1cKMmL1Wen1QA2tQCkbI/livVKPvzaZUKyPhkPSd1DSwKjuwZjt11E2Ok9Iye74hlxbSNBELAifZTycv9I6xBSJNs3ro9hmh+20tGKEppLpuEYwcBZ6RuXPn4sYbb8TUqVMxbNgwPPfcc8jOzsaLL76oe5tQKIQrr7wS9913H/r16xfXDjMEjCLfFKRpYvWMABZ6QqgmvNIOrDlhY2WEPE6MPoJkorHC8wZCUYfkyRnYLdI0Gqtc+cmQ48T3tpBrR6VN+J9BFYc0PddCtRFVCYR9cdo48j2LIdAf1Ytsu+FAi9g7pktQKyPeZgCCMTNKaS/tM5Lttut/h8VUjbAAtZCm4ThO5hHrFIMmN/ywcUB2WPgM64x10NpnRSoiHJKmlltsdy4Z6btBMKLXg6Urzw8WsRSM+P1+rF27FpMmTZLuwGbDpEmTsGrVKt3b3X///SgvL8e0adNMPY7P50NLS4vih6EindI0omdENl/CgjICSPn9fYbBiGyOScgPr9C5MSdM289HD0ZirrBIJhorvM4YlJE9RzrQ6s1Q8504p0QjTUNPKsJ7W8C1oQzGyggAVAu9PvYesaKMCH1GhODabuOEQEQ4mVs4kFcXZ6NnYRaCYR5rdjea34d4USsjNEXjzldOSabQpmfC65/jcuh/h9VpGQtpGkDq/0JMrOR3D/zIdTvAyVfuRh2ktZQRenut/TbaLyv9jtKd7m5gbWhoQCgUQkVFheL6iooKHDx4UPM2K1aswD//+U/MmzfP9OPMmTMHBQUF4k91dbWV3Tw6SCsDq9Iz4rJrjB43gK5gDRULuxNiu+6QH52BEGwIIytkVhmJcbR8MtHxjOTDuEIIAEpy3ehZmAWeB37c3xx127RF1gBLRO1ZEC4r0IgCXvicRzGwAtLnaq8VZYRW0wgnZofdJn2vHB4xtWCW8f1JWuTrHYcNtkwg6qZn0bqvAuKJPSw0PctyRVNGVMdjC8oIAPQokH3XqTLCBVSVNCZSLFrVNPT2rjztoCsKFVZmZKU76VBtaZGkVtO0trbi6quvxrx581Baaq5dMADMnDkTzc3N4s/evXuTuJcZim4deVd6RpQrE+oZybMHgZAwitzk6sT0hFOOUxxovfKTtonH6yHOK0mjYESjX0JnIIR8g1bwcsZUFwIAvt+bocGIVjt4dYmmcIIaZNtH/nZ4DE9aVBmxNB9G8ELRPiOxVtJQTuyXimBE1Q4+2pA8QFQcw2GqjESpiCuQeUQKewP5VpURWUWNU6mMWFJUtfqMxFDWK+6XleaL6U4G9hlxGG8iUVpaCrvdjrq6OsX1dXV1qKyMXKFs374du3btwpQpU8TrwnQKpsOBzZs3o3///hG3c7vdcLvdVnbt6CMdIl+VFEiVkSJbu/R/6rw3oKcwVMyUYuFwA8FOIOBFpz8k9eNw5RquhsQDoZXhaclGyzNisrSXMrq6AB/+WIvv9zYlYQe7AJuGMqI2IgqXozmhpLSgl6GUL3pGrLTLFz7XvFDaG28wcpKgjHy/twm1zZ1iqjCpqJWRTgNlxE7KWrkgLe2NUmIrN6yOu0kyspukp9y3JXpGAsi1Ukkj22dx4QMkJBgx1Xwx3dH1FNLFamGX7o4ZLH2KXC4Xjj32WCxdulS8LhwOY+nSpRg/fnzE9kOGDMGPP/6I9evXiz+/+tWvMHHiRKxfv56lX+JBK00TDknjoVPSZ0TdgKzI9OTg6mJJug2GwtE3lh1oOwMhFJoo66X0KpLSNGnTaVHDiEdKe80ZWAFgdC+yzff7mhK7b10FXcmFNNI0omeEXJ5k30D+rhxpeLdUGTnc7jdvIBW+W4GQbIJtHMFIj8IsnNC3GGEeeHvNPsu3j4kIZSRKwzNAVChsIRK8ZLvt+oFB6SDp97FXW961XkKF054jHQrPSJ7HQo8R2T4re6k0ae+zCSqFILHFG0SHvwvNxsnAyMCahsqI5TTNjBkzMG/ePLz88svYuHEjbr75ZrS3t2Pq1KkAgGuuuQYzZ84EAHg8HowYMULxU1hYiLy8PIwYMQIuV3pNDcwotIIRn6yaIgV9RmiapsBEN1Q1FXkeuBw2BMO8sblUdhDq8Iek4Mdkt1eOA9p8QTR2pInZU8vAGrCmjIzoWQAbR4y5GSkza5X26qRpRKpGG95tvseJgixy36Z9I7QdfIC8H26HPe6D+GXHkYXXW2v3IhzugiA4wjNikKYRuqE6wuTEnh0tTZNfBUz9CLjl65iOM31KqKm4A2GhXNvNBYQ0jQVlgz7HgEzJiLHHCEAaruW6yTEtrQzusaC5WI2tIqyrsByMXHbZZXj00Ucxa9YsjBkzBuvXr8fixYtFU+uePXtQW1ub8B1lqNAMRmQmO0cXpLl0OrCKDcgsSIE2G4dqQbUwnECrUEaCKBCVEePH8zjtqBRc82kz6VbLwCpPP5l4XjluB4b1ICeGb3Z2oTchUUQt7RVOLNXjlLepHGXqrsVhgg0m32/aFVRoABavMgIAvxxZhTy3A3uPdHaNd0StjBilaYQA3xEWlJFoaRoA6HMSUD40pl3rUZAFl8OGQIhHJ08WpKIyYiWY0Owya3LInt6+pWPpfyxoVdPIK8K6YrFqkZgMrLfeeit2794Nn8+Hb775BuPGSQeJZcuWYf78+bq3nT9/Pt55551YHpYhRysn2NU15Ko25tQzksdbV0YAaeS6cTAi9VDoUJy0za2Gqs0+TlehcSJWVNOYPAGe2JcaJY8kdPe6BLG0V6PpmXBiCVePRwcvC7JNKCMAxPkwuw6bnN1DDayiMmKL+7uV5bJjyhhSdfLmmi4w5FutpnGS74TTjDISJzYbhz7Cd7A1RE6abgjKiFE6SY74HDvJHCNAu2usBWgKyZLhOR3RStPQz7Ajq2sWqxZhs2kyFS1lpCt7jAARK3qxmoa3rowAVoIRmTLit+YZASB15UybYCQyTeP3+ZDDCSs+k6/jOKFqI7OVEY0yTeFkeMQbwka+t/T/HHMVejUlJBjZaXaQoPDdCgr7kghlBJBSNR/9dBDNyU4R6nlGdNM0tBMq2T7HFgBC1j5/VqABYnOAvNYezi+U9hrspxx5iTU1scaRpgFkQzszPRjRUkbS2C8CsGAkc9Eq3erKHiOAbp+RHN582kSOacVCdqBVeEZMPp4Y9BxOl2AkUhlxBuX+H3MHjxNqisFxZHpvfWuG5bw1PSPCwVM4sRxs9uLPgWnohBsYf6vpu+5XJgQjZpURTu0ZSUwwMqpXAYZU5sEfDOPtdUk2supW0+gZWMlJ2CW0ZRc7GnN2wJ2X8N3rKwQjR3zkFBSpjJgIRhyyYIT6RuIMRmLq2JuO0MIBuUmfBSOMpKBV2tuVPUYA3Woa8UAWozJiqFjQ0eMxpml6l5j0pnQVGtNH3QHyXoZdecp5PFEoyHZiaKXgG8m0VI06INNo613X4sUmvjcuK3oTmPyg6bsWlZEGs2ka6hlJrDLCcRyuHt8HAPDq17uTa2TVraaJrox4oApGzHRCjQFqYj3s5cTHVZb2mghG7C6IDRBFb0zspb3AUZKmYcEII6FopmmsD/JKyD6oPCPZIWFVb9UzIhygdhspFvRAG+hEp19uYDUZjKStZ4QcOAKhMLLlJwMLjOtHDuIZl6pRe0Y02nrXtZATTlmBud41FJoSONTqQ5uZ8l5xUB7Zl0RU01AuGNMTuW4Hdja046vtDXHdV1TkygjPR6Q/Xl65C9NfW4cXV+wkQZGgjNBgxBOk4xUKk7J7fYUAsa6TBBNuBJCnUEZMfJcVDRCpMtJELmNN08hK/zOaqGma9DOvAiwYyVw0q2m62sCq7RnJCsXWWIcGCc2dATR1+PU3FA5AfNCLjkAIhZxFz4jwOLXNnaKak1JUqoA3IJ9LU2jprsYJJtbMVUaE90Ns6y01stt+iLzPVEo3S0GWEyU5pGpjlxl1hHpGNJWRQkuPrSbH7cBFx5CmYa+s2h3XfUWFnqTDAfJaUsUpuxj7mzpx7/s/48MfanH/Bxvw4Y+1imDEaefg9CtTZIlmoDBPqV4457s5P/KcISBAVU4TyggQ2WskQWmagy1ecXGVkTBlhNFlRDWwdnGahld6RjzB2JSRbJdD7IK4PZrZUFBGgn4veB4oNDndllKW60au24Ewb0KF6QpUwUinX5rYy2VZVEb6koP41vo2NLT5DLZOI9SeEY2y0h+Ehm6jeknXmYV6FGhAExU6tTeYWM8IhaZqlm6sS94KXF4t0Sq0WnBmA84s/GftPoWV4J8rdkoGVi6EXCcsz5aySlmeG5X5HrG0140AiiDzqZh9neW9Rng+7mCkJMcFj9MGns/wTqxRlXMWjDASiVZpb1c3tFGdRP1C51S3GIxYPyDQk0bU/L6wigv6yMHCqmeE4zjR1LjDzMkp2YjvJQnqOmXKCGfxNSzKcWFIJVl1frszg9QRdTt4Ve4/GAqLQwBHV1v/fNOV+Ja6VoMtIU3tTXA1DWVAeR7G9ytBmAfe/HZP3PeniV0WjLQIwUhWMXiex9triXn2f345BC67Dev3NmH9QSlwLXaFk1bWK2dEzwL4IAUj4vBDC52bFb1G/O1SMBtjEMVxXPeoqGHVNIwuI1rk2+VpGqWB1RWMLU0DwFyQQJURXwcA3nJpLwD0E1fKJk2NyUStjAQkZSSWAwdVR77pysFs8SK2gxdOJqrc/9b6NngDYeS6HehXas0zAgCDK8htNh+MQRmxcwkP9C8fR0qU3167D6FkGFntDulz1XqAXGYXY9fhDuw50gGXw4arTuyDc0dVAQA++FkKXAucwaQrIwAwomc+vDwJQgudIfRwdYr7aRq5Z4Tus80JuHJi3q9uYWK1MWWE0VWY6DOy+3A7bnxlDf7vo03J2QfNpmc8XP7YzW/0RBNVGREOQCF/J7Lgg4sLWn68/mXkcXakYzDitzaxV82JYr+RDFJGxDSNyjMiPH+aohnZswA2m/XqjkGV1pWRsLAvuZxX+p4lyPx31rAK5HscONDsxcpkGVnpibpFCkbo8x9YnotslwOTh5PO2Us21SNkJ9sXOUNdooyMlCkjPXI52LwWKmkocs+IPEUTRwVQtyjv1e3AChaMMBKMQZ+Rg81eTHlqBZZsqMNzX2zH55vqk7APkQbWLPhg42OXSvuKyoixZyTk90p+EZvD9IRgAOhHg5GGNEjTqLw3SmWk0PLdnSAoI5sOtuJIexQjcDpB0zS0eZXYSbMQALB+L1nVjYohRQMAg4U0zZ4jHcYD8zilMpJH3wu7S9nbIg48TjsuGEuMrG8la3genWpLg5GsYmyrJ5/3QcLrcerAMrjsNuw+3CEGBhXZ4S5RRkb2KoAX5H0v9YSNW9ZrIfeMxFnWS+kWygjzjDC6DIM+Ix//fBAtXumg+78fbEi8HKzR9KxAERxYl0r7U2XkcLt+Hwahz0go4FX6RSyshvrJgp6UT++NWk1j/cBRkuvGwHLyOmaMb8RFTgAICM9blaZZs4s8j+P6WDhRySjJdaM0lwSxW+sNAlAh0KfKiDjeIME9Ny45lnRk/fjnJHVkpSfqJqFqJ6dMVEYGCJ+PHLcDJw0gSlpLkHwOh5e5u0QZKc/zYNqEIQAANx8w7hKrhdwzEmdZL4WW9+7L5PJezWqaJnLJghFGQjHoM0KHcd10en/keRzY0dCOtbsbE7sPGoPyFGPvYzhw9yzKgstugz8Y1q80kPUZsVrWS+lbmgOOI2XEh1OtHqiannX6w9JcmhhPBjRVs2LboXj3rmsQZqPAL7yf9MTiKURju18MII7tE/uJZnAl9Y20RN+QGlgFZSSHjz1lFo0RPfPFjqzvfb8/ofcNQPqeNGwjl4W9sbVOqYwAwKShJFXTKfg3hpQaDMlLIKcOIQEZgjJlw0yPEYrcMxJnJQ2Fpmm6r4G1sMt3xwwsGMlUokzt5d35ol9g0tBy8WDzyc8HE7sP4kmUrOoUykiMJ1G7Tap00c3v0z4jAa/U8MziF8zjtIszarYcNOEjSCYaBtZ4PCMAMHFIGQDgs431qVd+zEBTbH5BGZGlaWgQ3b8sB8VCv5BYoN1pfz5gLhihykh2koIRjuNwqTCvJimpGtEzQu47VNBLLG0eVCGlNM8YWg4A8AppmgHFjoSpDIbIPR+xKCN6npE4oMFIbXMnAqEM7TXC+owwugx1MBIKiBL39lY7jrT74XHaMKpXIc4aJpjUNtYl9sRE27IHyPwLX1DWgCyO6HuwYDbcpBckyKRZq2W9coZWkcfZmPJgRDkoj3SVjd0zAgAn9S+Fx2nDgWYvNtam+PmZgab0/MLzlp0MV+8mJ6nja2JL0VBG9qJm2OboG6rSNNnh5AQjAHDB2J5w2jn8uL8ZG2sNgiSrqCaz1qEcvmAYHqdN9EUAQFVBFqlsAdm+wB5MmP/CeB9lno92wdeWUxbb7UXTc2Fcu1Sa44bLYUOYJ/OQMhLx/CAc78Phru9DZREWjGQq6j4jPumEs7aWnNTGVhfB5bDhtEFlcDmISW1LXQINm+KqhAYjsjRNHAexwUaVD/QgG/LGVNZLGSKslDcl+iRgFU1lJHbPCECUn1MGkIP60o11ce9i0qGeETEYkU4sPwjm1WPiSNEAUrO0DbUt0Ve8gsQdDpH3w0PHGyThIF6c4xKVy38nWh1RmW13h0gw16c4B3ZVRdJZwyrhFRqQKcpkky3pyz0fzUKqqqBnbLcX1bT4Pic2G4dehbSiJkNTNareRfC3AhACk65q/WARFoxkKmplhH4RnTnY2Ug8EFSKzXE7cHJ/4iH4fHMCq2qcStOhLyjzOsSjjAj57M16ioXQ9IwLemUTe+NRRlIdjFBlhLyXnb5Q3OkuQJLflyajkirR0DQNbQcuO7HQMm9quoyVPsXZyPM44A+Go5f4Cu8HL7SD94RimxNkFpqqeXf9/sSazPMqpd8dWdjrJd/XqsLIiqDfntYPPcuF71DHEamqqauUkWAn0CwEY/m9Yrt9gtI0gMzEmqnlveo0DU3R2N3SIjLNYMFIpqIu7ZX1GNkrfIHoDBYAmDiEnJgSWuIrSqRe8DxPPCNxBAcUaq7bfqhNewUrKCO2kE+mjBRafpyhVWSFsKWuDcFU5oZVykjA1woHR/taxH4CPEN4z7/f14RDrWneGl4nTeN15ONgC1He6HC1WLHZOIwSUjU/RkvViJ4ROt4gucHIKQNLUZDlxOF2f2Krn2pOkX4vrEatMGiQjlyQ43Ha0btcSIM1CV1hHR5L5fIxIT8x+oUA0YoykgTPCCAdOw0niKcrEYvV9PaLACwYyVzUHzZZj5F9RyKDkQmDyIlpze5GtHgTVEYoU0ZoK/hErOh7FmYhx2VHIMRrDzYTgiBb2I8ijraet+4nqC7KRo7LDn8wbH68fDJQBSPoJAeOEOeQXuMYKM/3YFSvAvB8goPQZOCUpWmCflEh2dNJKjzyPQ4UZjvjfpiRPQsBAOv3NulvRNM0wvvhCiYvTQMATrtN9HV99FNt4u647+nS7znlONhCUg6V+TqDBqkHrHEnucyrTGgps/ZjqgIjT6G1lgBJ6DMCADXCBPGd6TC7KhbU1TQsGGEkDXWfEZk5aa+Q56yWmdR6l2Sjf1kOQmEeK7YmqOOjzDPS6Sf7oSjtjRGbjRN9Iz8d0FjBCsqIPeRDBSccgOSSdAyPk1ITqzoYEVIUfkde3CeDXwjqyJJ0942I1TTt0kkFwI5W8tqQUuz4T4zH15BVc1QFQugszAsHcmdQCvSTxS9HkrbsH/10UL+/jlVKB0q/t9aiVjBjaikjAMT0J47sIpe51r9TlrG7AMje1wILKRpA6RlpF8YfWGmapkONoMKZmvKcjuilaVgwwkg4OjJc0JUndt2sLlaugCYOTnCqRqaMdAbIh76QGi/jXJ2Mria3/36vVjBCnpcj7EM510SuiyEYAYAhVWlgYqWrGPBAOAzOR56z3xn/ye/sEeR1Wba5Pr27sYqrYV7yDmQVY9cRcgKtKY0vRUM5rqYYHAfsaGhHfatOpYTwfojBCE0fJNHMedKAEuS47DjU6sOGRH0WOQ7oeRz5feTFYmVIpVEw0riLXMb4nbIExynVkXwLKRpApoy0S9U4CQii5AM7M6I0Xo14TIFQScOCEUay0EnTtHMkQCjMdiLPo5S1qW9k2ZZDiVl9yTwjHYIyUmSLXxkBgDFCMKIppwvKiJP3oQzC/2M8cA6lykgqgxGb/MARhN1HA8v4g5EhlfkY0TMfgRCPd9cnobFWopCno2iaIKcMuw+Tz1OfOP0ilIIsp9hvRFcdUfUZcQSSXxLpdtgxXjCZf7ElgY3qrvoPcP4zwKn/z1gZod9nGnx1RTACANkl0u9W/CKApM62HBCURQ7ILY97l6qLs8FxQJsviIa2NA7i9ZCriHz6l/UCLBjJXNR15MKHrYUnB3V5ioZyXE1RYldf9AQS8qHTS76wifCMAFIwsuFAizgNWEQ4aLp4P9x0SF5uRUyPQ02suj1NugKapgGAcBAO4WQQTkAwAkhtx99cvTd9V3k2m/R5oivz3HLRy9O3NHbvjBo6u0c3GLEplRG7P7meEcrpg0gpdkKDkaxCYOyV6Ajb0dxJvGIVRsoIJcbvlGVG/Fr6PVZlpFFoeZ9dIg1djAOP044eBeT12HU4A1M18gUOH2LKCCOJqOvIBWWkMUS+QOoUDUBWXycPKAUALP4pAd1YZU54n5ekZxLhGQGA3sXZKMp2wh8KY5O6aZeqmZPfVRBxnVnoNNfaZi+aOlK0ApIHI3wIrgA5cIQTlBY4f0wPZDnt2HSwFV9tO5yQ+0wKNFUjU0b2HiH+p97FiVFGAGCcUTCiMv/Zumja6WlCMLJudyNaE2UyF6ApmhyXHXluh/ZGajNpXlVC90GXY6+Tfrfqy6H7TFM0CVRz5KmajEORpmHBCCOZ6PQZaQiSk3IvDWUEAKaM7gEAWLhuX/w9DRxSwOPrbAOHMPJ5IXDIKY3rrjmOE30jETN1VCu4YHbsK7h8j1Ns/5yyTqUqZcQllpImRhkpzHbhsuOJOvL88u0Juc+kICojZJXL55SKvg5dn0MMyKcaN2r5aIRVpR08AF708CT7QN6nJAc1JdkIhnms2p7YoFHuF9E1Aqsrt/K6SBkp6Q8Mu4BMbh5whrXbqgOoBKo5NYIal5EmVvnrEvSyYISRRHT6jBwOkg9hWa62UnDmsAoUZDlxoNmLr7bFWVVjs5EmOgD83g7kowN2CPsTQ6mtGjrsbeV21X7alfNJ+DgPQMOq6MwSgzbhycKmXMVkhch7ySXgNaRMO6Uv7DYOX25twE/7U/Q8jaAVNUIw0ukqQSBEAubyvNiULy1Kct1iA7XVuzTUEeFkzSGMbPjA0YqELjiQJyVVA4i9WqIGdepmWF1RTUO56B/A3dtJYGIF9T4nUBnpJ0wQp/N8Mgq7QwpIfK2yjsYsGElLnvh0K87/+wp8uiHNyx61UJf2ClJyvV8IRnQO3h6nHReMIerIW2v2xr8fwsEg4G1DMe354c4HHLEPNKOcIqSUvt5xRNn8jOPAyyJ/W36PuB6HKjDf7WmK635ihuNkabcgckIkWLDlJC4YqS7OxnmjiOz+wvIdCbvfhELTNM2k6VYTVwgAKM11wWlP7KGKpmq+0UrVcFQZkQ1+tDkjPRVJ4DRZMJJIfw9teleeFyUYcaieX1cZWAHi84jlRJlEZWSg0MGaTozOOMRy+TagU/icJ6DsOVkc1cHI7iPt+H5fMzZHaw2druiU9h70kSCgVEcZAYBLhPbTn/xcF79PQpB2A94OFEF4HRP0gR9WlY+ibCfafEF8r6qq4e3S83MVxpfbPqY36T3x3Z5Ggy2TiKzXSF6YvI6O3JIoN7DOb0/rBwD44IcD2JOOzZxcyjRBA8jJKeoJNEZoqubrHRrpEJsUjJTZhdcpuzj5DcBA1ECX3YZ9jZ0J9SrQYERvkQIgMi2Y7Im9iSDC55K4AGpgOfGT7T7cAX8wA6f3uoVgxNcW20TkLuaoDkZoe+mMNijRYERon73fKwQjefrKxIieBRhalQ9/KIz3vj8Q334IB4OQr0PqhpqdmJOozcbhJEEdUcvWIY/0GPb8+IKRUb0KYOOAA83e1E3pFIIRvz+AAiGo+//tnXd8FGX+x9/bk2x6TyAhlNBCCTUEpShIkVNUVMSG2AUERO9O8BT17sTeEMHDE/R+KjZABUTpRZHeIdSEUFIIIX2TbHl+f2whgYS03ewGnvfrta8kO7Mzz5OZnfnMt2p8GxZ3cykJ0QEMaBuGRcDstcecum2ncEnp8SyT9e8If+e5aOz0bW393x44W3B5vRHbd0uJhVB1w9sb1AW9Tk1PW2G2jc4qTgicK7KKkVDfK1gsWw6A7mOtDzoxSY0ivhqMCy0jEf46/HRqzBbRNDNqtFYxRXmhtIx4Oi1Cm3CVPfuF4pIA1nSD9cJdXcyInbt7Wisdfr21gemeNsuIuazkopvGSWIEYLCt2duyfRmVxnmyx/MXV6prbYJL0OvUtLPVnth9yk3WEZsYKSsvJ8jWb0fr51wxAjBpkLUq5w87T3te341LyoCfNlovps4MXrUT5qdz9KlZf/iS+Ayb1VGJIFTVuGIEoF+81VWz8ajz4kZyimphGdF4wa0fwrNH4IElTtu3S3FhzIhCoaCN3VXjzG7njYXDMlIhZkRaRjwTu2WkSapeR4yBpVKFvXxhbQ8e5HPlmI3buzVDq1ZyKKOAPVdqGlYTtouBpbyim8aZYiQCnVrJiXPFlWqjnAwbyAPlz7PIexTED2nwfrrHBgKw011xIzbXgKG8jCCF9cKncYEY6dEiiH7xoZgsgo/XeZh15JJsjjRbl1lXuGkABra7WASwEhXcNMFKd4gR63HffPy809wDDjeNby3+l75hl7nMPBbfiMo3WCfHucSH2+NGmqAr325pLMy82GpCWkY8E3vqVk5RudPz+l1OxZiR8kKHhaQAPcF6LUrllU2sgT5aRtj6YXy15WT9x2G3jJQbCLbdRJ0pRvy8NI7+Kj/vudhE7EKJkY2WLiwJe7LeNUYq0s3dcSM2c3N5UR7+jpL6rrkBTrZZR77bftqzWqRXtIxo9Jwptp7DEf6uESM3tLNaIDYcOVe5a7PDMmIh2NGFuvEu4h2j/An11VJcbmank85Huxi5kvu2SaLxhqf+gD7joc8ECGzh1M3b40aatGXE0YXZu1GCsOtLvcTI7NmziYuLw8vLi6SkJLZu3VrtuvPmzaNfv34EBQURFBTE4MGDr7h+Y+LnpXH4UNNyPOiiXBsqpvba4kXMKh1laGt00di5NykWsN7k693J11ES3vkBrHbstVF+3nPW4aqx14cIckInV4BuNsvI3tP5lTN3Ggub8LDYm5SBy3qh9IwL5vo2VuvI278edsk+6kXFmBHfMEc6qitiRgC6NA8kWK+lsNRU2SJmSx3XKkwE2gW2EzrB1halUuHIJHOGq8ZotnChxPr9ru21oUnhHwXDZsKw15we59LW0UjTje0i6otd3NvFiAdbRaAeYuSbb75h6tSpzJgxg507d9K1a1eGDh1KdnbVzdfWrVvHmDFjWLt2LZs3byYmJoYhQ4Zw5oxn9Mmwd2dMbWqumoqWEUeXV2vcQ2gtazL0bBFEfLgvBqOZH3fV83jYlLYwll6MGXHyU+QN7cLRa1WcyTOwy5ZVc6HELkac86TXKlRPgLeGMpPFPX1qbMJDmWstSlaI3lorwEX8fVh7FApYsvus056+G0xF10CrG8gqsD7Nu8oyolIqHHU91h6ucP2ypZj6U0ygovHdNFAxbqThQaznbb1VauO+lVSmQ5RVjKTmFFNSbnLzaOqIPYDVLkYuuS5bLIJ5G07w7m+HPcIzUGcx8u677/LYY48xbtw4OnbsyNy5c/Hx8eGzzz6rcv0vv/yS8ePHk5iYSPv27fn000+xWCysXr26wYN3BvZuoL8eyMRQbq5hbQ+iYp0RW3CSQWU9+a4YMV9xEwqFwzry5Zb0+gWy2s1+JoPTs2nseGtV3NTRGiX/025r9o/9Sc9ZF1eFQuGwjril3ojtZqfOTwOgUOm6dvUAnZsHcGd3axDzqz8fdF7b+oZQelEEmns9znlb0GW4iywjAANtrppKnaxtVpAARbEjs6nxxYjVMrLvTH6Duy3bXTQhtXDfSioT7udFqK8OIeCwO/tX1YdL3TQ+F89hIQTPfb+Hfy8/xIdrjjH8g42O88Rd1EmMlJeXs2PHDgYPHnxxA0olgwcPZvPmzbXaRklJCUajkeDg6p+ey8rKKCgoqPRyFfaL0bK9GQx+dz3rDldt4fE4KlpGbG6aIoX15LtixPwl3NGtOTq1kpTMQvbWJ5DVJkaUJoNLAljt2F01S/dmYDJbHG6aYL1z3DQA3WKsX9atVVXldDW2m52uwNqXpVjlWjEC8Neh7dBrVew+lcePezzAUtmir/VnYAvO61thEVare7ALn+b7x4ehVFhLwzuyixyWkRICsLtpGleMhPt70T7SDyEa7qqpVSaNpFrs1hGnNBdtTOxuT5vlvKJlZFvaBRbtPINaqSDCX8fpCwbeXelel22dxEhOTg5ms5mIiMq53BEREWRm1q7x2t///neio6MrCZpLmTlzJgEBAY5XTExMXYZZJ0Z0juKTB3rQLNCbM3kGxi3Yxn88uX+HnYp1RmwnWwFWK09d/MIBPhqGd7JGoC/cVo+KrLaqjQpTqUtSe+30bxtGsF5LTlEZG4/lONw0gU68UV0fbx33hiPnGj9uxPY07lNoDSYuaQQxEu7vxfgb2gDw72Upjq6ubqP1jTD2Z3jqd3IKrcc3RK9F7eTqqxUJ0msdbQeW7bMFSNtcZlbLiD0ou/H97XYX0rpLU4/rSK0KnkmqpWO09bvoFvdtQ9BVrttT8Rxestv68HFbt2Z8dG93wNrV251zbNRsmtdff52FCxeyePFivLyq9wNPmzaN/Px8x+vUKSeULa8GhULB0IRIVk0dwH1JsQgBry1P4Ztt6S7bp1Nw1BkRDsvIBWEVIyG1dNPYudvWRO3nPWfr7he1WUY05pKLpbNdcOHWqJTcarOOLN55hjwnu2kAEmOCHAGNVfYscSU2MaIz5gFQpglslN0+2q8lrcL05BSV8davKY2yz2pRKKBlf9D5OZ7mr1RJ2FnYrW52F2BFy4ivxT2WEYDBNtfk6kNZDRLH5xrxf3k1crF3VRMTI/aYETs2y0i5ycKyvVbhfVtiM3rFBTsyK6usSNxI1EmMhIaGolKpyMqq3MslKyuLyMgr53e//fbbvP766/z222906dLliuvqdDr8/f0rvVyNt1bFv2/vzETbk+ILi/d7thJ21BkxOywj583WAMC63qD7tAyhRYgPRWUmlu+rnYXLgU2MRJpOo1QILEot+Di/PgZYa6OANb7HnpJaV+F1JVRKBTfYak+sPtTI7rpLbnalmsZpaKVTq/jXbZ0Aa9yQW0viV6AxxciwhEjUSgUHMwo4ll100UqlKENvtF2c3SBGuscGEaLXUlBqYltVPXRqiaNjr4sCga92EqKt38WDZwvck2lXX6qxjGxNzSXfYCTMT0dya6tVcPqIDiyb1I9x17Vs7FE6qJMY0Wq19OjRo1LwqT0YNTk5udrPvfnmm/zzn/9kxYoV9OzZs/6jbQSeHdKWwR0iMFkEf/9hb+X6A56EyhYrYS53BLCeM1mFQYi+bhdwpVLB3bZ+NXW2CNnESJzZ+jmjX4y1m68L6NLcWsa+zGShuNxMixAf2kX41fzBOnBTR6sY+WnPWUqNjRjQfEkar1EXWOVqrqBv61Du6N4MIWD64v0ecc476mI4UWxWR5Be6wgYXbr3rLXRow2lowt144sRlVLB4A5W68iKA3V8SKiAI0XaBZVsrwVaherx81JTZrI0rSDWSyoa2y0je07nAdY+SCpbQHOzQG86RLn+of9K1PmuMXXqVObNm8fnn3/OoUOHeOqppyguLmbcuHEAPPjgg0ybNs2x/htvvMGLL77IZ599RlxcHJmZmWRmZlJU5JlFZBQKBa/d3gl/LzV7T+ezqL4pr67GfnE0XHCIkUxbx96gegR13tmjOUqFNbCpTi2zbXVGwrE+uZkDnFt0qCIKhYL7+8Q6/n6gTwunZwfc2D6CqAAvzhWW8cPO007d9hW55GZX7uUa61J1vHBzBwJ9NBzKKGD+72mNuu+qaEzLCFxSy0ahpJAKacZK9WV9cxqL4Z2tFuef9pylzFQ/cSwtIw1DqVTQtXkgALsvadjp0VzqpvG1xiDttYmRrs0bx/paW+osRkaPHs3bb7/NSy+9RGJiIrt372bFihWOoNb09HQyMi5WypwzZw7l5eXceeedREVFOV5vv/2282bhZML9vZh4o9Vd88Gqo/W+CLgUe5CoMDtSt3Jtbpq6WkbAWsvB7qL4ti6BrJeU8BZBcXXed10YmdiMMD8dob5aR/dhZ6JVKx3dbT9YdZQzeQan76NKLimqVeLbuObSEF8d04a3B+DdlUcab97VkGOrjVHbmjkN5aaOEWjVSo6fK+bA2QLyRYXz2rtxOvZWRb/4MCL9vcgrMbLqYP1ch3bLSJS0jNSbxJhAgMu6h3s0l7ppIqzuWHvWZOdmTVyMAEycOJGTJ09SVlbGli1bSEpKcixbt24dCxYscPydlpaGEOKy18svv9zQsbuUB5PjiPDXcSbPwMKtrgugrTdq3UXle/4EAPno8dIo8daq6rXJ0bZA1h92nq69b/SSRlXKINdZRgB8dWpWTO7Hr1P6E+DtvLTeitzTK5Y24b5kF5Yx6uM/eOvXFP7vz5OsOphV/0q1NXFpzEhAa9fs5wrc1SOGXnFBGIxmZvx4oNH3XxFHOmojWUb8vDQMsrUd+GxTKvmigonbyf1O6oJKqWBUD2us1P/9Wfe2DUazxfG/dFXxuGuBrnYxYrMqNAkqWvP0YeAbQXZhKRn5pSgUkHA1iJFrAS+NiqdvtPbwmLXmmGdW37NnrZRdbJJXH6uInRvahxPqqyOnqLz2AZyXWEbUoa3qvf/aEuKrI8SFNylvrYovHu5NTLA3mQWlzF57nH8s2c+jX2ynxz9X8uaKFOcHslUQIwahRePvvFbotUWpVPDv2zujVipYdSiLFfszav6Qi7jYS6XxMkDsWWWLdp2hoKIYCWl8YViRe3rFolEp2HziPBsubepXA+cKyxACNCoFIXpZfbW+2C0jR7OLyC9xf7XSWlHRMhLaFhQK9p+x3ivahPniq3Ndhef6IMXIFbi7ZwyxwT7kFJXxxeYGNJNzFZfU88jDt17xInY0KqXjKezb7bW0BoV3QHDRhK0Oiav3/j2J6EBvVj4zgDfv7MKY3jEM6RhBqzA9RrPg43XHefJ/O5wb6Km7+JSSIwIIcNONo22EH08OsN58X/zxAHklDav+WV8cbppGCGC10z8+jGibKyOfCmIk2L1iJCbYhwf6xAHwys8H6mSdy7DFi4T7ecnqqw0gzE9HqzA9QripKGJ9qGgZCbK6fQ9nWuMB7bVTPAkpRq6AVq10dDj9z4YTFJd5mHXkEjGSIUIIboBlBGC0LQ5j3eFsR+DbFQmKwxA7wPGnwsUxI42Jl0bF3T1jmHlHF/7zYE/WPDuQj+/rjk6tZHVKNv9cetB5O6uQgXQef7f2EJl4Yxtah+k5V1jG1G/3NHqpeLNFkFvcuG4asLpEHkiOA6CgYsyImy0jAE/f2IZwPx3HzxXz8PxtZOTXLqYnyxYvEinjRRqMvTieO2tx1AllBXd9cBwAqTlWMdIq1D0B2VdCipEaGJkYTVyID7nF5fyvHj5bl1JBjJRqAinBi+AGdrFtFeZL77hgLMJaka82pHd6GoCzigjw8jzF7Uxu7hzFh2O6oVDA55tP8msDUi6rI0f4E+ikbsT1wUuj4oN7uqFTK1mTks1Ha4816v5zi8svloJvZAvRY/1aEu6n8yjLCFjTj+eP64WvTs32kxcY9M56/rX0YI2iRGbSOI+klla3+JbUJiJGAOxW63Y3A3DinLUwZaswfXUfcBtSjNSAWqV0xI54nHVEfzH9M09jjTFoqGUEcDTP+2rryVrFRqTrOzGy7FVeDfp3g/fdFBiaEMnj/ayxMdMW7XP0yXEWmyydCXRRcG5t6dQswFEM7b1VRyo3knMx2YXWG2iIXufSUvBVoVYpWfnMAHq2rhC06gGWEbAW31oyoS+JMYGUlJv5dFMq/d9cy3Pf7XFYQC7F/v61FLwqhGDPuT38cOQH8ux9WZyA3TJy4GxB04kbmbQLHlkJEQmAtfswQMtQKUaaJCMTo2kZqie3uNyzYkcqlF0/p7ZePJ3ROO7mzlGE+urIKihjxf6an/xzisrZI9pgCohr8L6bCs8OaUfbCF9yi8t581fnNJgqenAlbxjv4QvzEALcaBmxc1fPGEeLhKe/3sWRrMYp+HTxBuqe8uUBPhq6hVZwTbmg11J9aRPux+LxfZk/rhdJLYMxmgXf7zjNX2ZtqjLtNO289ebTLMi7kUfqPj7d9yn3L7+flze/zOS1k7EI58R2Rfh7ER/uixCwoYHNCxuN4JYQ0xuA/BIj520PTlKMNFGs1hFr3ZE56445/Um43lS4SGZgtZI4wzKiVSu5z2Yd+fyPtBrXP38N9r7QqpX867bOAHy9NZ2dTiijfj4ggTnmW/HSatCp65ee7Wxm3JJA75bBFJWZeOTzbY5j7UqyCjwgFbWiAHFTjZHqUCisbQu+eSKZH57qS7sIP84VlvHAf7dcViHU3k/F3nn2akcIweJjix1/78zeyTeHv3Ha9m+wpX+vaURLobNItQnTCH8deg/LpAEpRmrNyMRmtI/0o6DUxPurjrh7OFYqXDBPC7sYcc4T9X1JsaiVCrafvOBIB6sOu9p2Zp+YpkDvlsHc2aM5YO1l1NDsGnvzP3e7aCqiVSuZe38PYoN9OJVr4In/7XB5EUCPcC30nQgJd8CYhe4bQy3o0SKIReP70j02kIJSEw8v2Eau7fuYX2Lk9AVrTElClGfVlHAVhy8c5lThKXQqHVO6TwFg3t55GC3OcavYC0OuO5yNuZEDuxuKPXjVE60iIMVIrVEpFfxjREcAvvjzJJuPe0AQUwUxcqzc6rJxVv2NcH8vbrZ1cvzs99QrrmsvqtSQGidNlWnD2xPgbS2j/k1t06GrIc9gvWAGuDGTpiqC9Vo+e6gnfl7W4Mlpi/YhhOsuxO520wDWui93zYd2w903hlqi16n57KFexIX4cCbPwOSFuzBbBAdtjT6bBXp7hNuvMfgt7TcArm92PQ92fJAQrxDOGc6xNn2tU7bfMy4IPy81F0qM7DjpGU0la0vqOc+NFwEpRurE9fGhjO4ZgxAw5ZtdpJ8vce+AKnTHTTEEAs5NhXz4emtu+o+7z3LiCv1qzhddm5YRsIq/qTe1BeDd345Q2IAKrfaaHkEeeONoE+7H7Hu7o1IqWLTzDB+vO+6yfXmEm6aJEeijZe4DPfDSKNl4NIf3Vh7hwFmrRTPBA2tKuIotmVsAuDH2RjQqDaPajgJg4WHnWLg0KiVDOlrj837c7aF9y6rhZK71fhUXIsXIVcFLt3QkPtyXrIIy7vnPZve2XK8QwHq83FrB05kVKxNjAhnUPhyzRfDeqqPVrne++NqLGanIvUmxtArTc764nDkNuEk73DQeKEYA+rcNY8YtVuvgW78eZs664y6xkDhqY3igGJmzZw7XfX0dz298nnMlnhXE2D7SnzdGdQHgo7XH+NeyQ4A1C8eVGM1G0gvSXWotqw0WYeHoBet1qlOINRPsrrZ3oVQo2Za5jeN5zhHQt3ezFoZcujeDcpP7O1zXlnSbGIkN9qlhTfcgxUgd0evUfPloEq1C9ZzNL2XUnD949ts9/HnifOO2nAdram/fp8nvOZl8fPHWqNDXsy9NdUwdYn3q/3nPWQ7aguEu5WK1zGtTjGhUSqYP7wDAp5tSOX2hfhazCzbLSIC351qYHkyOY/xAa6rrGytS+NeyQ04vimYXI+HudNNUweqTq/l498cUlBew7MQynln3DCaLB6X6Y41te6hvXKX3ro93XTZQekE6dy+9mxGLR3DPsns4kX/CZfuqidOFpzGYDGiVWmL9rQH4kfpIboi5AcBpgazJrUOstWgMRlYdynLKNhuDUzYxEiPFyNVDuL8XSyZex8jEaCzC2ljunv/8ScKMXxn2/gae/XYPn21K5VBG1TdvpzLkXxzrPAWAUD8tCidH/idEBzCiizV25J3fLk9hNZktjpvoteimsTOoQzjJrUIoN1l4q56pvnbLiCe6aSryt2HteeFmq/j676ZUxs7f6qgN0lCsjd2s55MnuWmEELy7410AuoZ1xU/jx55ze/hs/2duHtnlTL+5AwPahhHko+HDMd3o0SK45g/VgzJzGY+vfJxjedaieAfPH2Ti6onkl1054N1VHLlgTSxoE9QGtfJitsjodqMB+On4TxSVV+9uri0qpYK7bZWq/7PhhNstQrWhqMzk+F7FhkgxclXh76Xhg3u6sWTCdYzq3pwQvRazRZCSWcgPO0/z6tKDDP9gI2P+82eN2SgNxdFUzEWWiak3tUWpgNUp2axJqfwkcKHEiLBVy3RnCXN3o1AoeGFEBxQKa4zN7nq0Gs83eLabpiKP9W/FB/ckOmIUbv5gIz/tOdtgK0m27VzWqBQEe9D5lFaQRnphOmqlmk9u+oRpSdMA+O++/5Jb6lm9SrRqJQvG9WL7P27i1q7RLtvPwpSFnCk6Q7h3ON/+5Vui9dGcKjzF61tfd9k+r8ThC9aHgLZBbSu93yeqDy0DWlJsLK6U9tsQxvaNQ6tWsvtUHn+e8KzjXxV2q0iQjwZ/L8+8vkgx0kASYwJ55+6ubP/HYDZPu5F5D/ZkyuB4bmwfjlpp7bR560ebXOZfBzhnU7yu6uPROsyXR2zBrP9YvL9S9UF7vEiwjxbVNd6Iq1OzAEZ1t6b6/mvpwTofb7uFKdCD3TQVGZnYjJ8nXk/7SD9yisqZ9PUubnpvPf/782S9KxVnemhjtw2nNwDQM6Ineo2eEa1G0DGkIyWmEubtnefm0V2OQqFw2vdx8dHF3L/8ft7a9hY5hhwA8svy+WTvJwBM7DaRDiEdeHvA2yhQsPTEUnZl73LKvuvCkVyrZaRdULtK7ysUCu7vcD8AXx76ErOl4e70MD8dd9nS+v+17KDHp/l6erwISDHiNBQKBVEB3tzUMYIpg9vy2UO9WP+3GxjROQqLsPrXpy/e55KmY43Rbv2Zm9oSG+zD2fxSpnyzy/Hly8izle6+hl00FXluSDu8NSq2n7zAL7WoXlsRe4p0U7CM2ImP8GPJhOuYelNb/HRqjp8r5sUl++kzczVvrEihpLxuouS4LWurhYeZkjee3ghA/+b9AVAqlEzuNhmwxiJkFGW4bWyu5MtDX/LSHy+x59wevjj4BWN/GUtmcSaf7vuUwvJC2gS24dbWtwLQOawzd8TfAcDMLTMbfNM3mAyUGGsff1WdZQTglta3EKAL4EzRGdadWtegcdmZMrgt/l5qDpwt4L+b3BcrUxs8PV4EpBhxKc0Cvfno3m7887ZOKBXw9dZTPPfdHue2nufiTcyVHU59tGpHx9q1h8/x1++t87A3iusWE1Tl5w7nHuan4z9xqrBhNTiaCpEBXjze39q35vVfUmpdIKzMZOaIrb13+8imlYrppVExaVA8f0y7kRm3dCQuxIfCUhNz1h3nLx9u4lh27cvIH7WVnG8b4TkVQ41mIzuzdwLW+hV2kqOT6RXZC6PFyJw9c9w1PJdRbCxm1q5ZgNXV0cy3GemF6Yz6aRT/O/g/AKb2mIqqQnfYSd0n4afx41DuIX44+kO997346GL6LexH0ldJPLnqyRp7zBSVF3GmyJpqW5UY8VZ7c3fbuwH44uAX9R5XRcL8dPx9eHvA+l1fddBzg1lPnpeWkWsehULBA31a8ME93aw1GnadYdLCXU5NCWsMywhY3RDvjU501JoY/Z8/WWjr7Duy2+W+6Xl753Hnz3fywqYXGLlkJAv2L3Dp+DyFJwa0ItxPR3puCV/8UbteRgfPFlButhCs1xIT3DT7iPh5aRh3XUvWPDuQTx7oQaS/Fydyirn94z/4/VhOrbZxJMsqyDxJjBy5cASjxYi/1p84/zjH+wqFgsndrdaRH4//yIk8z346ris/Hf+JYmMxcf5xfHLTJ8wfOp92Qe0oKC/ALMzc2vrWSuIMINgrmAndJgAwa9esegWzrk5fzUt/vESZ2Xpd+/3M7zzwywNX3NbRPGtKb7hPOIFegVWuc0/7e1Ar1OzM3snec3vrPK6quLd3LHf1aI5FwBP/t4MPVh1tUK0hV2HvUeRpFseKSDHSSNzSNZo593VHq1KyfF8m4xY4LwOhMSwjdm7uHMWc+7rjo1U5KhBG+OtIalk5fXB75nY+2v0RAG0C22C0GHlnxzt8uu9Tl4/R3fho1Tw31Oq3fn/VEYeJ9ErsSs8DoFtMoNMzohobpVLB0IRIlk/uR88WQRSWmhj72Va+3VazdeyIwzLi6+ph1poD5w8AkBCScNmx6RrWlYExA7EIi+N8v1r49vC3AIxpPwalQkmUbxRfjviS6UnT+XTIp/z7+n9Xea6ObjeaNoFtyCvL46NddfufCCH4ePfHju18f8v3ROojSStI4/mNz1fb9O5wrtVFc2m8SEXCfcL5S+u/APD+zvedEsOnUCj49+2dGdW9ua0e0xESX13JgLfWMuS99fxl1kbumvsHL/90gD+O5bjETV8bTtiqr7YO85zv1aVIMdKIDEmIZN7YnnhrVPx+7DxD3tvAwq3pDT5B7ZaRML/GidsYkhDJz09fz4jOUQT5aJhwQ5vLguXm7p2LRVgY2Xoki25d5HiC/GDnB/yS+kujjNOd3Nm9Ob3jgikuN/Pst3sw1uCas2ffJMYEun5wjUSwXsv/PZrEyMRoTBbB337Yy8xfDlUb7FdQaiTDFsAa70GWEbsY6RTaqcrlk7pNQoGClSdXciDnQGMOzWWk5adxLO8YaqWaW1rf4nhfp9Ixpv0YkqKSqv2sWqlmetJ0AL498q1DKNSGDac3cOTCEfQaPU93e5p2we2YdeMsdCodm85scgiVS7Gn9bYLrl6MAIzvOh6tUsu2zG1Oix3RqpW8fVcX3h+dSJtwX8wWwcnzJRzJKmL/mQK2pV1gwR9p3PvpFvq9uZZ3fjvMSZulojEoKTdxJs/ao0iKEYmDAW3D+GnidXSI8ievxMjzi/Zx1yeb612TxGS2uKWxWOswX2bf151dLw3hweS4SstyDDlsy9wGwJNdn0ShUPBo50cZ23EsAC/+/iL7zu1zybhO5J/g65SvWXpiKYXljdPyviqUSgVv39UVvVbF1rRcXqgmePmCrWqrvXhSt9iqY2+aKl4aFe+PTmTSoHgAPll/gkc/30ZBFabsozYXTaS/FwEe1Cxwf85+wGoZqYr4oHj+0sr6xP3Bzg8abVyuZP3p9YA1e8hPW3dh2CuyF0PjhmIRFl7b8lqtrRDfH/kesFZODdBZK8e2D27PjOQZAHyy9xPWpK+57HNXCl6tSJRvFA90fACA17a+RrHROaJAoVBwW7dmrJo6gN+fv5Hvnkzmq0eTWDCuFx/ck8iY3jH4eak5k2dg1ppjDHx7HePmb2XDkXMur1Nit4oE67UE6T030UCKETcQH+HHzxOv4x8jOjjcHX+ZtYl/LzuIobxuEeinLxgwmgU6tZLoAM+INfgt7TcswkKX0C4092vueP+ZHs8woPkAysxlTFo7icziumWb1MTio4u5bcltvLblNaZtnMbQ74fy0/GfnLqPuhAb4sOHY7qhVMC320/z6BfbOZJVSLnJwva0XKZ+u5skR9aJmR4tgujVsmoxYjAZyCjKwGj2PH90TSgUCqbe1JYP7kl0BECP+HAja1KyKl2IfztoPR/a17HdvUVYyC/Ld0rK5qUYTAZHGfGE0KrFCMD4xPGolWo2Z2xm5cmVTh9HY2O3GgyMGVjvbTzb41m81d7szN7JVylf1bh+Xmkem85sAuD2NrdXWnZL61u4t/29AEzfNL1SpVej2egoA1+TGAF4vMvjNPNtRmZxJm9te6vW86ktzQK96RUXTN82oQxsF87IxGbMvKML214YzKwx3ejfNgwhYO3hczz42VbGzt9Gao7rLCUnbNtu5aEN8uxIMeIm1Colj/ZrxepnBzC8UyRmi2DexlRu//j3Op2Y9nVbhuo9pi7Dr2m/AjCs5bBK76uUKt7o/wZtAtuQY8hh0ppJdUrduxK/n/mdGX/MQCDoEdGDOP84Co2FvLDpBV7b8prbynYP6hDBe6MT0aqVrEnJZsh7G2j7j1+4c+5mFu08Q7nJQkK0P2/f1ZVvn0hGp65czt8iLMzePZsbvr2BIT8M4fqF1/PmtjcpKG+E6r5OZmRiM75/si/NAr05lWvg4QXbufGd9UxfvI9/Lj3IJ+utN5gHk1vUantCCL478h3DfxjO9Quvp89XfXhl8ytO7RlzOPcwZmEmxCuECJ+Iatdr7teccQnjAPjn5n96XN+aupBflu+oEzKg+YB6byfKN4pnejwDwLvb3+XQ+UNXXP+3k79hEiY6BHegVWCry5Y/1+s5uod3p9hYzOQ1kx3VVLdkbsFgMhDqHUrLgJY1jstH48MrfV9BgYIfjv7Az8d/rsfs6o6XRsUtXaP54uHerH1uIA/1jUOrUrLhyDmGvreBTze6pprr8Wzr/8mTXTQgxYjbiQrwZs79PZj/UC9CfXWkZBZy66xNrKhljQp7XYZWYZ6hejOLM9mZvRMFCoa0GHLZcr1Gz0eDPiLYK5hDuYd4atVTDTaVGi1G3tj2BgLBHfF3MH/ofBaPXMz4xPEAfJ3yNRNXT3Sb22ZkYjMWj+/L4A4RjtgaP52aO7pb31/69PXc2aN5lUWq3t3+LnP3zKXYWIxKoaLEVML/Dv6PUT+N4s+MPxt7Kg2mc/MAfn2mP4/3b4VeqyI1p5ivtqTz302pACS1DOaGduE1bsdenv3Vza9ytvgsAKXmUr4/8j2jfhrF+lPrnTLeivEiNQUWP9n1SdoGteVC2QUmrZmEwWRwyhgam41nNmIWZtoEtqlk2awP97S7hwHNB1BuKWfy2smOomlVsezEMgBGtBpR5XKNUsM7A98h3CectII0pqydQqmplFUnVwFwY8yNKBW1u6UlRSXxRNcnAHjpj5f4/czvdZlWg2kZquflWxP49Zn+9IsPpdxs4V/LDjHhq51Oz8ax3yNah3vGPaI6pBjxEG5oH86ySdfTKy6IwjITT/7fDv619GCNdSoumuA8Q/XarSLdI7oToa/6SbKZbzNmD5qNn8aPndk7eXzl4w0SCkuOLSE1P5UgXRDP9nwWhUKBWqnmqa5P8d7A9/BSefH72d95YPkDnC48Xe/9NISE6AA+HduTlH8OY9sLg9kzYwjv3p1It9igam9yG05v4PODnwPwUvJL7HxgJ3MGzyHWL5bM4kwe++0xXtvymtOsS42Fr07N9Js78Of0Qcy9vzvjB7bmzh7NeahvHG/f1bVW2URfpXzFggMLAHi629P8ee+fLBi2gPbB7blQdoGJayby2pbXKDU1LGPNHpBaXbxIRbQqLe8NfI8AXQD7z+/nqVVPNUkLll3INcQqYkehUPBav9eI848joziDJ1Y+UWWK7tmis46HmGFxw6rYkpVQ71A+vOFDfNQ+bMncwhMrn3DEkAxqMahOY3uq61MMjxuOyWLimXXPsDt7d50+7wxahur54uHevHJrAhqVguX7Mhn50e+kZDrvvDloi0dsE+4Z94jqkGLEg4jw9+Krx/rwWD+rqfHTTancPvuPKxaNOuFhlhF7pszwuOFXXK9TaCfmDZ2Hv9afvef2cu+ye+sUdW/HIix8fsB6w36sy2P4aysXDBvcYjALhi8g3Duc4/nHuXfZvW4pVW1Ho1IS5qer0aVmsph4e/vbADzY8UFHK/Trm13Pd7d85yjg9HXK14z6aRQbT29sEg27KuLnpWFYpyj+Nqw9b9/VlZdvTahVhcgtGVscvv7nej7H410eR6/R0yOiB1/e/CUPdnwQsP5vxiwbU6/zys7+87bg1SvEi1Qk1j+Wj278CF+NLzuydnDnT3eyJn1Nkzk2RovRYSVoSLxIRfy1/sweNJsQrxCOXDjCQyseuixebHnqcsAa+FrdQ4ydhNAEZg+ajV6jZ2f2Ti6UXSBSH0mvyF51GpdSoeTf1/+b65pdh8Fk4PGVj7M2fW3dJucEFAoFY/vG8e0TyUQHWGvz3Db7d77emt7g8yaroJQT54pRKKBHrGsaJjoLKUY8DI1KyQsjOvKfB3oQ5KPhYEYBN3+wiZm/HKoyA8EeM9LKA/yBpwpOceD8AVQKFYNbDK5x/YSQBP479L+OOgL3Lb+Pr1O+rlMg4vpT6zlZcBI/rR+j4kdVu5+vRnxFh+AOXCi7wCO/PsJ3R76rtmaBJ/Dz8Z8d1p4nuz5ZaZmPxocXk1/kk8GfEKmP5HTRacavHs+on0ex6OiiJvk0XltSclN4dv2zmIWZW1rd4hAedrQqLX/t9VfmDp5LqHcox/KOMWbZGD4/8DlGS93M30XlRaTlpwG1s4zYSQxPZP6w+TT3bU5GcQaT105mxOIRvLntTVadXHVFV4W7+SX1FwqNhQR7BdM5tLPTthvrH8u8IfMcx+Tun+9m9cnVCCEoKi9iYcpCoHoXzaX0jOzJVyO+ok9UH25rcxufDf0MjbLuGVgalYb3Br5Hn6g+GEwGJq+dzH/3/dct14ZusUEsndSP/m3DKDVamLZoH3d/spm1h7NrLA1QHX8ct55rnaIDCPDwNhMK0QQke0FBAQEBAeTn5+Pv37RKZTeErIJS/vb9XtYfsQbDBeu1jE2O4/4+sYT46jh5vpgBb60DYM+MIZXSIQvLC9l0ZhNZxVnotXriA+NJCE2o1xe2tszbO48Pd31I3+i+fHLTJ7X+XF5pHtM3TWfjGWv/j4SQBKYnTadLWJcrfk4Iwf3L72dvzl4e7vSwI1iuOkqMJbyw6QVWpVt9zIlhiUxPmk6HkA61HmtjYLaYue3H20grSOO5ns8xNmFstesWlhcyZ88cvj/yvSNGQa1UkxyVzJC4IdwQc4MjRbIpc+TCERYfXcwPR3/AYDLQKaQT84fNx0tdfTp7bmkuM/6Y4cgMaeHfgondJnJT7E2VSphXx7pT63h6zdNE66P59c5f6zzmEmMJ8/bN46tDX1FiquxKi/GLoVt4NxLDE+kW1o1Wga1qHe/QEC6UXuD/Dv0fm89uJrskG3+dP4lhifSM6En74PaMXz2eM0VnmNJ9Co90fsTp+z9TdIYpa6eQkpsCQI+IHuhUOv44+wfNfZuzaOQivNWNnxVotBh5Y+sbfHP4GwCSo5J59bpXidRHNvpYLBbBp5tO8N7KoxiM1gczX52aFiE+RAd6E+CtwVujwkerwsv2M8BbQ5fmgbSL9KsUe/bX7/bw3Y7TPDGgFdOGu+c6V9v79zUtRgwmA1nFWcQFxDltm85GCMGalGz+vfyQI19cq1YyonMUqw5lUVhqYkDbMD5/uDdgNe8vOLCAuXvmOsop29Fr9PSM6ElSVBJJUUnEB8Y7rdqnEIJRP4/i6IWjvNr3VW6Pv73mD1XAIix8nfI1H+36iCKj1fWUFJnE/R3v57ro69CoLhdRG09vZPzq8XipvPhl1C+EeofWaj9fHPiCj/d87Lh5D4wZyCOdHqFrWO3iFVzNqpOreGbdM/hp/Vh550r0mppdcPll+Y7MgGN5xxzvqxVquoR1oWdkT7qEdiE+KJ4ofZRHzLM2lBhLePmPl/kl7WKhvL7RfXmz/5u1EllCCH44+gOzds0it9Ta6j1KH8XtbW7n5lY308K/+syd5zc+z7ITy7i/w/38vfffGzSHDWc2sC1jG7vO7eLYhWMIKl92/bX+dA3rSveI7vSM6Enn0M61Ekx1YcPpDTy/4XkKjVeOzwrzDmPZHctcJgrKzGXM3TOXBQcWVMpy+3TIp1cspuZq7NlZb217i1JzKX5aPyYkTuDudne79CGuOs7mGZi38QRLdp3hQkntrHq+OjXdWwSR1DKY+HBf/vbDXvJKjHz+cG8GtA1z8YirRoqRWjBr1yw+2/8ZD3R4gJ6RPQnQBeCv9cdf60+ALgC1Uu20fTUUo9nCL/sz+e+mVPbYqnXa+Xni9XRuHkCZuYzn1j3HutPrAGgV0IqOIR3JK8tjX86+ywLHgr2CSQxLJCE0gYSQBDqGdCTIq35Ft7ZlbuPhXx9Gq9Sy5u419X4azzHk8N6O91h2YhlmYX0q0Gv0JEcl0zOyJ4nhibQNaktheSEPLH+A9MJ0xnYcy3O9nqvTfjKLM3l3x7usSF3huDG0C2rH7fG3M6TFEMJ83PPFtQgLd/58J0cvHOWxzo8xqfukOm/jRN4Jfj35K7+l/VZJmNjRa/S0CWxDm8A2xAfFE+sXS3O/5jTzbYZW5TlFkU4VnGLS2knWSqAKNTfE3sDtbW7numbX1dmKUGws5vMDn/PloS8rubFaBbTihpgb6N+8P51COznmbzAZGPjNQEpMJfzfzf9H17CuTptXQXkBe8/tZVf2LnZn72Zfzr7LMm+CdEH0a96PgTED6Rvdt1aCtDqEEPzv4P94Z8c7WISFdkHtGJswllYBrcgsyWRn1k62ZW4jJTeFzmGd+Vuvvzl1vtWRWZzJ4qOLKTYWM6jFILqFd3P5PmtDan4q0zdOd8QLtfBvwRNdnmBo3FC3fD/MFsGx7CJOXyjhbH4pRaUmDOUmDEYzJeVmDEYz2QVl7D6VR1HZ5SUMOkb5s2TCdWjVF78zJcYS9ufs52zxWRQoCPMJI9w7nGjfaHw0zu1f41IxMnv2bN566y0yMzPp2rUrs2bNonfv3tWu/9133/Hiiy+SlpZGfHw8b7zxBjfffHOt9+cKMSKEYOq6qQ6T/aWolWpi/WKJ84+jZUBL4gLiHL+70+wthGDP6XwW7zzN3jP59IsPY+pNbTGYDExaM4k/M/5Ep9LxYp8XubX1rY4nYIuwkJKbwpaMLWzJ2MLO7J1Vph42821Gx5COJIQkkBCaQIfgDrWa76O/PcqWjC3c0+4eXujzQoPnmVGUwZeHvuTnEz87nmjteKu9USqUFBuLidZHs/AvC+stok7kn2D+/vksO7GsUkxBuE84MX4xhHmH4aX2wkvlhbfa2/q77W/7OjF+MU77Ai89sZRpG6fhq/FlxagVDT7X0gvS2Za5je1Z20nJTSEtPw2TqLrmigIFEfoIYvxiaO7bnBi/GJr5NiPMJ4wQrxBCvEPw1/o3ilVl05lN/G3D3ygsLyTUO5R3B77rlJtVqamU1emr+fHYj2zL3Fbpf6FVaukU2olu4d1IL0xn5cmVROujWTFqhUvnbLQYOZJ7hF3Zu9iZvZMtGVsqCSaNUkO7oHa0C25Hc7/m+Gn88NP64av1Ra/RO14hXiGXnYfl5nJe2/Kao4PuHfF38I+kf1RpabQIS6O4ipoCJouJRUcXMXv3bMf1J9grmNva3MZNLW6qsk+RuzFbBCmZBWxLzWVrWi5bUy8QGaBjwbjehNr6lhUbi5m/fz5fHPyiyuv/K31f4Y74O5w6LpeJkW+++YYHH3yQuXPnkpSUxPvvv893333H4cOHCQ+/vD7AH3/8Qf/+/Zk5cyZ/+ctf+Oqrr3jjjTfYuXMnnTpV3euhvpOpK0II1p9ez8LDC8k15FJQXkBBWUGNZsxgr2AifCLw11mtKH5aP3QqneMmVel3tQ5vlTc6tQ4vlRf+On8CtAEE6AKu6O+uCwaTgafXPM2WjC34qH34aNBHNUaWG81G9uXsY3/Ofg6cP8DB8wdJK0irct0YvxgSQhJoHdiaCJ8IIvQRhHmH4avxRa1U83XK18zbNw+1Qs3yO5YT5RvllHmB9QJ56Pwhfj/7O7uyd7Hn3B5HGnCkPpJPbvqEVgGXF0iqK/ll+Sw9sZRlJ5axP2f/ZWb0mgjxCiHGL4YW/i0qveoiVFJyUxi3YhxFxiImJE64LHDVGRjNRk4WnORo3lGOXjjK8bzjnC46zanCU7Wqi6FRagj2CibEO4RQ71BCvEII9grGV+uLr+bizdFX44teq0ev1jtuml4qrxov4EaLkQX7FzBr1ywEgi5hXXhv4HuE+9Rce6SuFJQXsOn0JtaeWsvWzK2XiV6VQsXr/V+/YqqpKzBZTOzK3sW6U+tYd2od6YXptf6sn8aPcJ9wwnzC0Gv07Du3j2xDNkqFkmd7PMsDHR/wuJuoJ1NUXsTXKV+z8PBCskuyHe+HeofSJbQLCaEJxPjFEKWPwl/nj4/aB2+1NzqVDpVShUqh8giBZ7QY+f7I98zdM9dxnof7hBMfGI9FWDhnOMc5wzle7/f6ZZ2YG4rLxEhSUhK9evXio4+s3RgtFgsxMTE8/fTTPP/885etP3r0aIqLi1m6dKnjvT59+pCYmMjcuXOdOhlnYbKYyC7JJi0/jdSCVFLzU0krSCMtP42skiyn7Uen0lW6gPtofPBR+1T6W6/RO97z0figV1de92zxWT7e/TH7cvbho/Zh7k1z6/0EWVheSEpuCgdyDnDgvPV1qrDmTqt2agq2dAYWYSE1PxWLsNAyoKVLXGn5ZfmcLDjJqcJT5JXlYTAZKDWVWl/mUgwmAyXGErJKskgvTK+xTXqgLpAAXQAB2gB8ND4IITALMxZhodRs3a7BZCCjOAOA7uHdmTdkXqOahIUQ5JbmcqrwlEOcnC48zdmis+QYcjhfer7BReOUCmVlsWL73VvtjQIFJouJQ7mHHN+xUfGjmJ40vVH+D0IIThacZGf2Tvbn7KfIWMRdbe+qc7qoK8Z1uvA0B3MPcjj3MDmGHArKCygsL6SwvJASUwnFxmKKyosoNVddUyXMO4yX+75M/+b9G3n0Vw9Gi5G16Wv57eRvbDi9oU4F7RQoUClVqBVqVEoVOpUOb7U33mpvq3jRXPy9oqXL/j2xX+sriptKP5XKqt9XKDGYDOzK3sUXB7/gZMFJwOp2mtRtEje1uOkyYSqEcLpYdYkYKS8vx8fHh++//57bbrvN8f7YsWPJy8vjxx9/vOwzsbGxTJ06lSlTpjjemzFjBkuWLGHPnj1V7qesrIyysovBlwUFBcTExHhENk2JsYS0gjRyDDkUlhdSUF7guBCUmkopM5c5blplpjIMZgNlpjLHTaywvNDaR0M4t4+GXqNnzuA5Tve75pflc/D8QYcwySrOIqskixxDDiXGEsot5cT5xzE2YSx3tr3TqftuKhSUF3Cq8BSnCk5xsuCk9VV4krT8tDql2SpQ0K95P/553T8J9vK8mgBl5jJyDbmcLz3PecN5h0jJLc2lqLyIElMJReVFFBuLrTdI48Xf62JpCvYKZkr3KXUOgr7WKSovIrskm6ySLLJLsik1lRLmE8b1za73qFigpk6ZuYwDOQfYl7OPlNwUzhadJbM4k0JjIQaTwW2tJ2oi2CuYp7o+xai2oxo1ILe2YqROj5U5OTmYzWYiIioXpYmIiCAlJaXKz2RmZla5fmZm9eXOZ86cySuvvFKXoTUaPhofOoZ0bNA2hBAUG4vJL893XMTtF+0SY4Xfbe873jNZfy8xllBssq4TqAukd2Rvnuz6pEvS0AJ0ASRHJ5McnVzlcrPF7PSo/6aGv9bfGmNTRS2KvNI8cgw55JfnU1BWQJGxqNLTjP0pyUvlRYQ+wiXuCGehU+mI8o2qsxtOCIHBZLhMoBQZiygxlmAwGRxPZM18m9E9ortb0jubOr5aX3y1vlX2dZE4D51KR/eI7nSP6F7lcqPFSLm5HLMwY7aYMQszJosJi7BgspgoM5dRYipxWFgNJgMlppKL1/YK341ik9XqZTAZHNZUx0/LJX9XsVyn1tHCrwWDWwzm7nZ3NygQ2tV4TrpIBaZNm8bUqVMdf9stI1cLCoXCceFo6lzrQqQmAr0CCfQKdPcw3IpCobCamjU+hOGeLCWJpLHQKDVuSQVu6tRJjISGhqJSqcjKqhw3kZWVRWRk1U/lkZGRdVofQKfTodPp6jI0iUQikUgkTZQ6hflqtVp69OjB6tWrHe9ZLBZWr15NcnLVZvzk5ORK6wOsXLmy2vUlEolEIpFcW9TZTTN16lTGjh1Lz5496d27N++//z7FxcWMGzcOgAcffJBmzZoxc+ZMACZPnsyAAQN45513GDFiBAsXLmT79u385z//ce5MJBKJRCKRNEnqLEZGjx7NuXPneOmll8jMzCQxMZEVK1Y4glTT09NRKi8aXPr27ctXX33FP/7xD6ZPn058fDxLliypdY0RiUQikUgkVzfXdDl4iUQikUgkrqO292/3l4aTSCQSiURyTSPFiEQikUgkErcixYhEIpFIJBK3IsWIRCKRSCQStyLFiEQikUgkErcixYhEIpFIJBK3IsWIRCKRSCQStyLFiEQikUgkErcixYhEIpFIJBK3Uudy8O7AXiS2oKDAzSORSCQSiURSW+z37ZqKvTcJMVJYWAhATEyMm0cikUgkEomkrhQWFhIQEFDt8ibRm8ZisXD27Fn8/PxQKBRO225BQQExMTGcOnXqqu15c7XP8WqfH1z9c7za5wdX/xyv9vnB1T9HV81PCEFhYSHR0dGVmuheSpOwjCiVSpo3b+6y7fv7+1+VJ1dFrvY5Xu3zg6t/jlf7/ODqn+PVPj+4+ufoivldySJiRwawSiQSiUQicStSjEgkEolEInEr17QY0el0zJgxA51O5+6huIyrfY5X+/zg6p/j1T4/uPrneLXPD67+Obp7fk0igFUikUgkEsnVyzVtGZFIJBKJROJ+pBiRSCQSiUTiVqQYkUgkEolE4lakGJFIJBKJROJWrmkxMnv2bOLi4vDy8iIpKYmtW7e6e0j14uWXX0ahUFR6tW/f3rG8tLSUCRMmEBISgq+vL6NGjSIrK8uNI66ZDRs2cMsttxAdHY1CoWDJkiWVlgsheOmll4iKisLb25vBgwdz9OjRSuvk5uZy33334e/vT2BgII888ghFRUWNOIvqqWl+Dz300GXHdNiwYZXW8eT5zZw5k169euHn50d4eDi33XYbhw8frrRObc7L9PR0RowYgY+PD+Hh4fz1r3/FZDI15lSqpTZzHDhw4GXH8cknn6y0jqfOcc6cOXTp0sVRBCs5OZlffvnFsbypHz+oeY5N+fhVxeuvv45CoWDKlCmO9zzmOIprlIULFwqtVis+++wzceDAAfHYY4+JwMBAkZWV5e6h1ZkZM2aIhIQEkZGR4XidO3fOsfzJJ58UMTExYvXq1WL79u2iT58+om/fvm4ccc0sX75cvPDCC2LRokUCEIsXL660/PXXXxcBAQFiyZIlYs+ePeLWW28VLVu2FAaDwbHOsGHDRNeuXcWff/4pNm7cKNq0aSPGjBnTyDOpmprmN3bsWDFs2LBKxzQ3N7fSOp48v6FDh4r58+eL/fv3i927d4ubb75ZxMbGiqKiIsc6NZ2XJpNJdOrUSQwePFjs2rVLLF++XISGhopp06a5Y0qXUZs5DhgwQDz22GOVjmN+fr5juSfP8aeffhLLli0TR44cEYcPHxbTp08XGo1G7N+/XwjR9I+fEDXPsSkfv0vZunWriIuLE126dBGTJ092vO8px/GaFSO9e/cWEyZMcPxtNptFdHS0mDlzphtHVT9mzJghunbtWuWyvLw8odFoxHfffed479ChQwIQmzdvbqQRNoxLb9YWi0VERkaKt956y/FeXl6e0Ol04uuvvxZCCHHw4EEBiG3btjnW+eWXX4RCoRBnzpxptLHXhurEyMiRI6v9TFOanxBCZGdnC0CsX79eCFG783L58uVCqVSKzMxMxzpz5swR/v7+oqysrHEnUAsunaMQ1ptZxQv/pTS1OQYFBYlPP/30qjx+duxzFOLqOX6FhYUiPj5erFy5stKcPOk4XpNumvLycnbs2MHgwYMd7ymVSgYPHszmzZvdOLL6c/ToUaKjo2nVqhX33Xcf6enpAOzYsQOj0Vhpru3btyc2NrbJzjU1NZXMzMxKcwoICCApKckxp82bNxMYGEjPnj0d6wwePBilUsmWLVsafcz1Yd26dYSHh9OuXTueeuopzp8/71jW1OaXn58PQHBwMFC783Lz5s107tyZiIgIxzpDhw6loKCAAwcONOLoa8elc7Tz5ZdfEhoaSqdOnZg2bRolJSWOZU1ljmazmYULF1JcXExycvJVefwunaOdq+H4TZgwgREjRlQ6XuBZ38Mm0SjP2eTk5GA2myv9cwEiIiJISUlx06jqT1JSEgsWLKBdu3ZkZGTwyiuv0K9fP/bv309mZiZarZbAwMBKn4mIiCAzM9M9A24g9nFXdfzsyzIzMwkPD6+0XK1WExwc3CTmPWzYMO644w5atmzJ8ePHmT59OsOHD2fz5s2oVKomNT+LxcKUKVO47rrr6NSpE0CtzsvMzMwqj7F9mSdR1RwB7r33Xlq0aEF0dDR79+7l73//O4cPH2bRokWA589x3759JCcnU1paiq+vL4sXL6Zjx47s3r37qjl+1c0Rmv7xA1i4cCE7d+5k27Ztly3zpO/hNSlGrjaGDx/u+L1Lly4kJSXRokULvv32W7y9vd04Mkl9ueeeexy/d+7cmS5dutC6dWvWrVvHoEGD3DiyujNhwgT279/Ppk2b3D0Ul1HdHB9//HHH7507dyYqKopBgwZx/PhxWrdu3djDrDPt2rVj9+7d5Ofn8/333zN27FjWr1/v7mE5lerm2LFjxyZ//E6dOsXkyZNZuXIlXl5e7h7OFbkm3TShoaGoVKrLIoazsrKIjIx006icR2BgIG3btuXYsWNERkZSXl5OXl5epXWa8lzt477S8YuMjCQ7O7vScpPJRG5ubpOcd6tWrQgNDeXYsWNA05nfxIkTWbp0KWvXrqV58+aO92tzXkZGRlZ5jO3LPIXq5lgVSUlJAJWOoyfPUavV0qZNG3r06MHMmTPp2rUrH3zwwVV1/KqbY1U0teO3Y8cOsrOz6d69O2q1GrVazfr16/nwww9Rq9VERER4zHG8JsWIVqulR48erF692vGexWJh9erVlXyFTZWioiKOHz9OVFQUPXr0QKPRVJrr4cOHSU9Pb7JzbdmyJZGRkZXmVFBQwJYtWxxzSk5OJi8vjx07djjWWbNmDRaLxXFBaUqcPn2a8+fPExUVBXj+/IQQTJw4kcWLF7NmzRpatmxZaXltzsvk5GT27dtXSXStXLkSf39/hxndndQ0x6rYvXs3QKXj6MlzvBSLxUJZWdlVcfyqwz7Hqmhqx2/QoEHs27eP3bt3O149e/bkvvvuc/zuMcfRaaGwTYyFCxcKnU4nFixYIA4ePCgef/xxERgYWCliuKnw7LPPinXr1onU1FTx+++/i8GDB4vQ0FCRnZ0thLCmbsXGxoo1a9aI7du3i+TkZJGcnOzmUV+ZwsJCsWvXLrFr1y4BiHfffVfs2rVLnDx5UghhTe0NDAwUP/74o9i7d68YOXJklam93bp1E1u2bBGbNm0S8fHxHpP6eqX5FRYWiueee05s3rxZpKamilWrVonu3buL+Ph4UVpa6tiGJ8/vqaeeEgEBAWLdunWV0iJLSkoc69R0XtpTCocMGSJ2794tVqxYIcLCwjwmbbKmOR47dky8+uqrYvv27SI1NVX8+OOPolWrVqJ///6ObXjyHJ9//nmxfv16kZqaKvbu3Suef/55oVAoxG+//SaEaPrHT4grz7GpH7/quDRDyFOO4zUrRoQQYtasWSI2NlZotVrRu3dv8eeff7p7SPVi9OjRIioqSmi1WtGsWTMxevRocezYMcdyg8Egxo8fL4KCgoSPj4+4/fbbRUZGhhtHXDNr164VwGWvsWPHCiGs6b0vvviiiIiIEDqdTgwaNEgcPny40jbOnz8vxowZI3x9fYW/v78YN26cKCwsdMNsLudK8yspKRFDhgwRYWFhQqPRiBYtWojHHnvsMqHsyfOram6AmD9/vmOd2pyXaWlpYvjw4cLb21uEhoaKZ599VhiNxkaeTdXUNMf09HTRv39/ERwcLHQ6nWjTpo3461//WqlOhRCeO8eHH35YtGjRQmi1WhEWFiYGDRrkECJCNP3jJ8SV59jUj191XCpGPOU4KoQQwnl2FolEIpFIJJK6cU3GjEgkEolEIvEcpBiRSCQSiUTiVqQYkUgkEolE4lakGJFIJBKJROJWpBiRSCQSiUTiVqQYkUgkEolE4lakGJFIJBKJROJWpBiRSCQSiUTiVqQYkUgkbmPgwIFMmTLF3cOQSCRuRooRiUQikUgkbkWWg5dIJG7hoYce4vPPP6/0XmpqKnFxce4ZkEQicRtSjEgkEreQn5/P8OHD6dSpE6+++ioAYWFhqFQqN49MIpE0Nmp3D0AikVybBAQEoNVq8fHxITIy0t3DkUgkbkTGjEgkEolEInErUoxIJBKJRCJxK1KMSCQSt6HVajGbze4ehkQicTNSjEgkErcRFxfHli1bSEtLIycnB4vF4u4hSSQSNyDFiEQicRvPPfccKpWKjh07EhYWRnp6uruHJJFI3IBM7ZVIJBKJROJWpGVEIpFIJBKJW5FiRCKRSCQSiVuRYkQikUgkEolbkWJEIpFIJBKJW5FiRCKRSCQSiVuRYkQikUgkEolbkWJEIpFIJBKJW5FiRCKRSCQSiVuRYkQikUgkEolbkWJEIpFIJBKJW5FiRCKRSCQSiVuRYkQikUgkEolb+X8MM3IPvBtUrAAAAABJRU5ErkJggg==", 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", 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WyXrvvfeQlpaG/v37Y926dfjhhx9cunw6Y7FYcP755+Oqq67C3r178dprr+Gcc87BH/7wBwAsVTd//nxcf/31GD58OK655hrk5OSgpKQE3377Lc4++2y88sor/ryUbbj//vvx9ddf4+KLL8aMGTMwYsQINDY2Yvv27fjss89w5MgRZGdna7pPT58NgHVVXbRoEQ4fPoxu3bp5vI9Ro0bhyiuvxOzZs1FRUYHi4mIsWrQIR44cwTvvvOOy7fTp07F69WoXQXj77bfjrbfewtSpU3HffffBaDTi+eefR15enmzuBphn5LHHHsOsWbNw5ZVXYtKkSfjpp5/w/vvv4/HHH0dmZqam504QLkSukIcggse+ffvEmTNnit26dRPj4uLElJQU8eyzzxZffvlll4ZmVqtVfPTRR8Xu3buLRqNRLCoq8tr0rDXjx48Xx48fL///73//WzzzzDPF9PR0MSEhQezbt6/4+OOPu5Sj2mw28c477xRzcnJEQRBcSjnfeecdsVevXqLJZBL79u0rLliwQG5e5gykpmet6dq1q3jDDTe4XPbYY4+JnTp1EnU6naqmZ/BQ2ut8WzXPUxRFcceOHeJll10mpqeni/Hx8WKfPn3Ef/3rX/L11dXV4o033ihmZ2eLycnJ4qRJk8Q9e/a0eR6tm55lZGSIycnJ4nXXXSdWVla2eR4rV64UJ02aJKalpYnx8fFiz549xRkzZoibNm1yea7uGryNHz9eHDBggNvXtvVnoL6+Xpw9e7ZYXFwsxsXFidnZ2eKYMWPEZ599Vn4tnJuetQatyoW9fTYuv/xyMSEhQayurm5zP61pbm4W77vvPjE/P180mUziyJEjxaVLl7p9ru4O+8eOHROvuOIKMTU1VUxOThYvvvhicf/+/W4f68033xT79OkjN32bN2+eS/k2QfiDIIphcL8RBEFoYOHChbjxxhuxceNGnHHGGZHenYiQl5eH6dOn45lnnon0rhBEyCHPCEEQRJSxc+dONDc30/A5osNAnhGCIIgoY8CAAXJTP4LoCFBkhCAIgiCIiEKeEYIgCIIgIgpFRgiCIAiCiCgkRgiCIAiCiCgxYWB1OBw4efIkUlJSQtrumiAIgiCI4CGKIurr61FYWAidznP8IybEyMmTJ11aGhMEQRAEETscO3YMnTt39nh9TIgRPqjp2LFjbUaCEwRBEAQRndTV1aGoqEg+j3siJsQIT82kpqaSGCEIgiCIGMOXxYIMrARBEARBRBQSIwRBEARBRBQSIwRBEARBRJSY8IyoweFwwGKxRHo3iA6K0WiEXq+P9G4QBEHEJO1CjFgsFhw+fBgOhyPSu0J0YNLT05Gfn0+9cAiCIDQS82JEFEWUlpZCr9ejqKjIa1MVgggFoiiiqakJFRUVAICCgoII7xFBEERsEfNixGazoampCYWFhUhMTIz07hAdlISEBABARUUFcnNzKWVDEAShgZgPI9jtdgBAXFxchPeE6OhwMWy1WiO8JwRBELFFzIsRDuXpiUhDn0GCIAj/aDdihCAIgiCI2ITESISYMGEC7rnnHo/Xd+vWDS+88ELY9ocgCIIgIkXMG1jbKxs3bkRSUlKkd4MgCIIgQg6JkSglJycn0rtAEAQR89gdInQCebqiHUrTRBCbzYY77rgDaWlpyM7Oxr/+9S+IogigbZqmpKQE06ZNQ3JyMlJTU3HVVVehvLxcvv6RRx7B0KFD8e6776JLly5ITk7G7bffDrvdjqeffhr5+fnIzc3F448/7rIPzz//PAYNGoSkpCQUFRXh9ttvR0NDg3z90aNHcckllyAjIwNJSUkYMGAAlixZAgCorq7Gddddh5ycHCQkJKBXr15YsGBBCF8xgiAI9RyoaMCAh5fi8W93R3pXCB+0u8iIKIpottoj8tgJRr0m9b1o0SLcdNNN2LBhAzZt2oRbbrkFXbp0wcyZM122czgcshBZvXo1bDYbZs2ahauvvhqrVq2Stzt48CC+++47LF26FAcPHsQVV1yBQ4cOoXfv3li9ejXWrl2LP//5z5g4cSJGjRoFANDpdHjppZfQvXt3HDp0CLfffjseeOABvPbaawCAWbNmwWKxYM2aNUhKSsKuXbuQnJwMAPjXv/6FXbt24bvvvkN2djYOHDiA5ubmAF9FgiCI4LBsZxlarA5883sp/nlx/0jvDuGFdidGmq129H9oWUQee9ecSUiMU/+SFhUVYd68eRAEAX369MH27dsxb968NmJkxYoV2L59Ow4fPoyioiIAwH/+8x8MGDAAGzduxMiRIwEw0fLuu+8iJSUF/fv3x7nnnou9e/diyZIl0Ol06NOnD5566imsXLlSFiPOJtpu3brh3//+N2699VZZjJSUlODyyy/HoEGDAAA9evSQty8pKcGwYcNwxhlnyLcnCIKIFrYeqwEAlNW14HSDGdnJpsjuEOERTWma+fPnY/DgwUhNTUVqaipGjx6N7777zuP2CxcuhCAILj/x8fEB73R74ayzznKJpIwePRr79++XG7lxdu/ejaKiIlmIAED//v2Rnp6O3buV8GO3bt2QkpIi/5+Xl4f+/fu7tMjPy8uT25YDwA8//IDzzz8fnTp1QkpKCq6//npUVlaiqakJAHDXXXfh3//+N84++2w8/PDD+P333+Xb3nbbbfjoo48wdOhQPPDAA1i7dm0QXhWCIIjAEUVRFiMAsPNkXeR2hvCJpshI586d8eSTT6JXr14QRRGLFi3CtGnTsGXLFgwYMMDtbVJTU7F37175/1CbiBKMeuyaMymkj+HtsSOJ0Wh0+V8QBLeX8YGCR44cwcUXX4zbbrsNjz/+ODIzM/Hzzz/jpptugsViQWJiIm6++WZMmjQJ3377Lb7//nvMnTsXzz33HO68805MmTIFR48exZIlS7B8+XKcf/75mDVrFp599tmwPWeCIAh3nKhpxql6s/z/zpO1GN+bCgOiFU1i5JJLLnH5//HHH8f8+fPx66+/ehQjgiAgPz/f/z3UiCAImlIlkWT9+vUu///666/o1atXm7km/fr1w7Fjx3Ds2DE5OrJr1y7U1NSgf3//86C//fYbHA4HnnvuOTl68sknn7TZrqioCLfeeituvfVWzJ49G2+99RbuvPNOAKzq54YbbsANN9yAsWPH4v777ycxQhBExHGOigAUGYl2/K6msdvt+Oijj9DY2IjRo0d73K6hoQFdu3ZFUVERpk2bhp07d/q8b7PZjLq6Opef9khJSQnuvfde7N27F//973/x8ssv4+67726z3cSJEzFo0CBcd9112Lx5MzZs2IDp06dj/Pjxsl/DH4qLi2G1WvHyyy/j0KFDeO+99/D666+7bHPPPfdg2bJlOHz4MDZv3oyVK1eiX79+AICHHnoIixcvxoEDB7Bz505888038nUEQRCR5GglSzUXpDFrwG4SI1GNZjGyfft2JCcnw2Qy4dZbb8WXX37pcXXep08fvPvuu1i8eDHef/99OBwOjBkzBsePH/f6GHPnzkVaWpr84+yVaE9Mnz4dzc3NOPPMMzFr1izcfffduOWWW9psJwgCFi9ejIyMDIwbNw4TJ05Ejx498PHHHwf0+EOGDMHzzz+Pp556CgMHDsQHH3yAuXPnumxjt9sxa9Ys9OvXD5MnT0bv3r1lc2tcXBxmz56NwYMHY9y4cdDr9fjoo48C2ieCIIhgUNfCBlYOKEwDwEysRPQiiLyxhUosFgtKSkpQW1uLzz77DG+//TZWr16tKl1gtVrRr18/XHvttXjsscc8bmc2m2E2K7m+uro6FBUVoba2FqmpqS7btrS04PDhw+jevTuZY4mIQp9FgogeZn+xHf/dUIKbz+mOt38+DADY89hkxEfY29fRqKurQ1pamtvztzOazRVxcXEoLi4GAIwYMQIbN27Eiy++iDfeeMPnbY1GI4YNG4YDBw543c5kMsFkohIsgiAIwj94ZKQwPQFGvQCrXURVowWF6QkR3jPCHQF3YHU4HC5RDG/Y7XZs374dBQUFgT4sQRAEQXikvsUGAEhNMCIjMQ4AUNVoieQuEV7QFBmZPXs2pkyZgi5duqC+vh4ffvghVq1ahWXLWJOx6dOno1OnTrLvYM6cOTjrrLNQXFyMmpoaPPPMMzh69Chuvvnm4D8TgiAIgpCoa2aRkdR4AzKT4lBRbyYxEsVoEiMVFRWYPn06SktLkZaWhsGDB2PZsmW44IILALDqEOcGW9XV1Zg5cybKysqQkZGBESNGYO3atQGVoxIEQRCEL+qlNE1KvBGZSRQZiXY0iZF33nnH6/XOc1IAYN68eZg3b57mnSIIgiCIQKiT0zQGWYxUkhiJWmhqL0EQBNHu4JGRVKfISDWJkaiFxAhBEATRrrDYHGixsrEXzmKEIiPRC4kRgiAIol3BoyIAkBxvQBZFRqIeEiMEQRBEu4L7RZJNBuh1AjLIwBr1kBghCIIg2hXOZb0AnNI06npiEeGHxAgRMgRBwFdffRXp3SAIooPBG56lxBsBAFlJrKN3dZPV422IyEJihCAIgmhX8FbwqQksMpKRxERJdZMFdoemcWxEmCAxEiEmTJiAO++8E/fccw8yMjKQl5eHt956C42NjbjxxhuRkpKC4uJifPfdd/JtduzYgSlTpiA5ORl5eXm4/vrrcfr0afn6pUuX4pxzzkF6ejqysrJw8cUX4+DBg/L1R44cgSAI+OKLL3DuueciMTERQ4YMwbp163zuryiKyMnJwWeffSZfNnToUJfW/j///DNMJhOamprQrVs3AMBll10GQRDk/wmCIEKNc8MzAEhLYL9FEWgw2yK2X4Rn2p8YEUXA0hiZH20DkLFo0SJkZ2djw4YNuPPOO3HbbbfhyiuvxJgxY7B582ZceOGFuP7669HU1ISamhqcd955GDZsGDZt2oSlS5eivLwcV111lXx/jY2NuPfee7Fp0yasWLECOp0Ol112GRwOh8vj/uMf/8B9992HrVu3onfv3rj22mths3n/ggqCgHHjxsmN7aqrq7F79240Nzdjz549AIDVq1dj5MiRSExMxMaNGwEACxYsQGlpqfw/QRBEqKlrlhqeSZ4Rk0GPOAM73TlX2hDRg+apvVGPtQl4ojAyj/3gSSAuSfXmQ4YMwT//+U8AbO7Pk08+iezsbMycORMA8NBDD2H+/Pn4/fff8cMPP2DYsGF44okn5Nu/++67KCoqwr59+9C7d29cfvnlLvf/7rvvIicnB7t27cLAgQPly++77z5MnToVAPDoo49iwIABOHDgAPr27et1fydMmCBPZ16zZg2GDRuG/Px8rFq1Cn379sWqVaswfvx4AEBOTg4AID09Hfn5+apfE4IgiEBpHRkBmDA53WBhQiUjUntGeKL9RUZiiMGDB8t/6/V6ZGVlYdCgQfJleXl5ANhMoG3btmHlypVITk6Wf7h44KmY/fv349prr0WPHj2Qmpoqp0ZKSko8Pi5Ps1RUVPjc3/Hjx2PXrl04deoUVq9ejQkTJmDChAlYtWoVrFYr1q5diwkTJmh/IQiCIIJInWxgVdbbXJhQZCQ6aX+REWMii1BE6rG1bG40uvwvCILLZYIgAAAcDgcaGhpwySWX4KmnnmpzP1xQXHLJJejatSveeustFBYWwuFwYODAgbBYXGvrPT2GLwYNGoTMzEysXr0aq1evxuOPP478/Hw89dRT2LhxI6xWK8aMGaPy2RMEQYSGJgsTI0kmZzHC/uaVNkR00f7EiCBoSpXECsOHD8fnn3+Obt26wWBo+7ZVVlZi7969eOuttzB27FgAzFAaTARBwNixY7F48WLs3LkT55xzDhITE2E2m/HGG2/gjDPOQFKS8tobjUbY7fag7gNBEIQvzDa2uDIZlOC/LEbMFBmJRihNEyPMmjULVVVVuPbaa7Fx40YcPHgQy5Ytw4033gi73Y6MjAxkZWXhzTffxIEDB/Djjz/i3nvvDfp+TJgwAf/9738xdOhQJCcnQ6fTYdy4cfjggw9kvwinW7duWLFiBcrKylBdXR30fSEIgnBHi5UtguKNevmyFBNP01BkJBohMRIjFBYW4pdffoHdbseFF16IQYMG4Z577kF6ejp0Oh10Oh0++ugj/Pbbbxg4cCD++te/4plnngn6fowfPx52u93FGzJhwoQ2lwHAc889h+XLl6OoqAjDhg0L+r4QBEG4gw/JcxEjlKaJagRR1FiPGgHq6uqQlpaG2tpapKamulzX0tKCw4cPo3v37oiPj4/QHhIEfRYJIlq4+o11WH+4Ci9fOwyXDGHVlXP+twvv/nIYfxnfA7On9IvwHnYcvJ2/naHICEEQBNGuaLFRZCTWIDFCyPDuru5+nPubEARBRDNm2TPixsBKYiQqaX/VNITfvP3222hubnZ7XWZmZpj3hiAIwj/cGVhTqc9IVENihJDp1KlTpHeBIAgiYGQDq4HSNLECpWkIgiCIdkWLzV2ahiIj0QyJEYIgCKJdYXZT2puaQJGRaIbECEEQBNFuEEVRjoyY3EZGSIxEIyRGCIIgiHaDxe4A757lrrS3wWyD3RH17bU6HCRGCIIgiHYDN68C7g2sABMkRHRBYiRCiKKIW265BZmZmRAEAenp6bjnnntU3XbChAk+txUEAV999VXA+6mWRx55BEOHDg3b4wVCuF8bgiDCB+8xIgiAUS/Il5sMesRJg/PIxBp9UGlvhFi6dCkWLlyIVatWoUePHtDpdEhISAja/ZeWliIjIyNo9+eL++67D3feeaem23Tr1g333HOPahEWLJxfmyNHjqB79+7YsmVLzIgpgiA841zWKwiCy3UpJgMqbRaKjEQhJEYixMGDB1FQUIAxY8aE5P7z8/NDcr+e4J1aY4FwvzYEQYQPd2W9nCSTAZWNFjSSGIk6KE0TAWbMmIE777wTJSUlEAQB3bp1a5N6ee2119CrVy/Ex8cjLy8PV1xxhct9OBwOPPDAA8jMzER+fj4eeeQRl+udUxFHjhyBIAj44osvcO655yIxMRFDhgzBunXrXG7z1ltvoaioCImJibjsssvw/PPPIz09XdVzap2mmTFjBi699FI8++yzKCgoQFZWFmbNmgWrlYVHJ0yYgKNHj+Kvf/0rBEFwWcH8/PPPGDt2LBISElBUVIS77roLjY2N8vXdunXDE088gT//+c9ISUlBly5d8Oabb8rXWywW3HHHHSgoKEB8fDy6du2KuXPnun1tunfvDgAYNmwYBEHAhAkTsGbNGhiNRpSVlbk8x3vuuQdjx45V9XoQBBEZ3HVf5STGscsazfaw7hPhm3YnRkRRRJO1KSI/agcgv/jii5gzZw46d+6M0tJSbNy40eX6TZs24a677sKcOXOwd+9eLF26FOPGjXPZZtGiRUhKSsL69evx9NNPY86cOVi+fLnXx/3HP/6B++67D1u3bkXv3r1x7bXXwmZjK4RffvkFt956K+6++25s3boVF1xwAR5//HENr3xbVq5ciYMHD2LlypVYtGgRFi5ciIULFwIAvvjiC3Tu3Blz5sxBaWkpSktLAbCI0eTJk3H55Zfj999/x8cff4yff/4Zd9xxh8t9P/fcczjjjDOwZcsW3H777bjtttuwd+9eAMBLL72Er7/+Gp988gn27t2LDz74AN26dXO7jxs2bAAA/PDDDygtLcUXX3yBcePGoUePHnjvvffk7axWKz744AP8+c9/Dug1IQgitLS46THCSTaxZABFRqKPdpemabY1Y9SHoyLy2Ov/tB6JxkSf26WlpSElJQV6vd5tyqCkpARJSUm4+OKLkZKSgq5du2LYsGEu2wwePBgPP/wwAKBXr1545ZVXsGLFClxwwQUeH/e+++7D1KlTAQCPPvooBgwYgAMHDqBv3754+eWXMWXKFNx3330AgN69e2Pt2rX45ptvVD//1mRkZOCVV16BXq9H3759MXXqVKxYsQIzZ85EZmYm9Ho9UlJSXF6DuXPn4rrrrpOjRL169cJLL72E8ePHY/78+YiPjwcAXHTRRbj99tsBAH//+98xb948rFy5En369EFJSQl69eqFc845B4IgoGvXrh73MScnBwCQlZXlsh833XQTFixYgPvvvx8A8L///Q8tLS246qqr/H49CIIIPWbeY8TgPk0DUDVNNNLuIiPtgQsuuABdu3ZFjx49cP311+ODDz5AU1OTyzaDBw92+b+goAAVFRVe79f5NgUFBQAg32bv3r0488wzXbZv/b9WBgwYAL1eWZ2o2cdt27Zh4cKFLhODJ02aBIfDgcOHD7t9LoIgID8/X77vGTNmYOvWrejTpw/uuusufP/995r3fcaMGThw4AB+/fVXAMDChQtx1VVXISkpSfN9EQQRPigyEpu0u8hIgiEB6/+0PmKPHQxSUlKwefNmrFq1Ct9//z0eeughPPLII9i4caPs4TAajS63EQQBDofDzb0pON+GezR83SYQ/NnHhoYG/OUvf8Fdd93V5rouXbqouu/hw4fj8OHD+O677/DDDz/gqquuwsSJE/HZZ5+p3vfc3FxccsklWLBgAbp3747vvvsOq1atUn17giAig+IZabvWlj0jFvKMRBvtTowIgqAqVRLtGAwGTJw4ERMnTsTDDz+M9PR0/Pjjj/jjH/8Yksfr06dPG+9K6/+DTVxcHOx214PC8OHDsWvXLhQXFwd036mpqbj66qtx9dVX44orrsDkyZNRVVWFzMzMNvsAoM1+AMDNN9+Ma6+9Fp07d0bPnj1x9tlnB7RPBEGEHm8G1iSKjEQt7U6MtAe++eYbHDp0COPGjUNGRgaWLFkCh8OBPn36hOwx77zzTowbNw7PP/88LrnkEvz444/47rvv2tTpB5Nu3bphzZo1uOaaa2AymZCdnY2///3vOOuss3DHHXfg5ptvRlJSEnbt2oXly5fjlVdeUXW/zz//PAoKCjBs2DDodDp8+umnyM/Pd1sZlJubi4SEBCxduhSdO3dGfHw80tLSAACTJk1Camoq/v3vf2POnDnBfOoEQYSIFhuLkLrzjFCaJnohz0gUkp6eji+++ALnnXce+vXrh9dffx3//e9/MWDAgJA95tlnn43XX38dzz//PIYMGYKlS5fir3/9q2wYDQVz5szBkSNH0LNnT9lIOnjwYKxevRr79u3D2LFjMWzYMDz00EMoLCxUfb8pKSl4+umnccYZZ2DkyJE4cuQIlixZAp2u7cfdYDDgpZdewhtvvIHCwkJMmzZNvk6n02HGjBmw2+2YPn164E+YIIiQY/ZW2muiNE20Iohq61EBzJ8/H/Pnz8eRI0cAMIPiQw89hClTpni8zaeffop//etfOHLkCHr16oWnnnoKF110kaadrKurQ1paGmpra5GamupyXUtLCw4fPozu3buH9MTZEZk5cyb27NmDn376KdK7EjFuuukmnDp1Cl9//bXPbemzSBCR55Uf9+PZ7/fh6jOK8NQVrkb//6w7gocW78SUgfmY/38jIrSHHQtv529nNEVGOnfujCeffBK//fYbNm3ahPPOOw/Tpk3Dzp073W6/du1aXHvttbjpppuwZcsWXHrppbj00kuxY8cObc+GCAvPPvsstm3bhgMHDuDll1/GokWLcMMNN0R6tyJCbW0tfv75Z3z44Yea29wTBBE5lGoaN6W9cVTaG61oEiOXXHIJLrroIvTq1Qu9e/fG448/juTkZLn8sTUvvvgiJk+ejPvvvx/9+vXDY489huHDh6vO/RPhZcOGDbjgggswaNAgvP7663jppZdw8803A2BRMOdyW+efDz74IMJ7HnymTZuGCy+8ELfeeqvX3i0EQUQXagysTZSmiTr8NrDa7XZ8+umnaGxsxOjRo91us27dOtx7770ul02aNMnnxFSz2Qyz2Sz/X1dX5+9uEhr45JNPPF63ZMkSuZV7a/Ly8kK1SxGDyngJIjYxcwOrWzHC28FTZCTa0CxGtm/fjtGjR6OlpQXJycn48ssv0b9/f7fblpWVtTlR5eXltZn50Zq5c+fi0Ucf1bprRAjx1sWUIAgiWvDWZ4Q6sEYvmqtp+vTpg61bt2L9+vW47bbbcMMNN2DXrl1B3anZs2ejtrZW/jl27FhQ758gCIJon/DS3ngDdWCNJTRHRuLi4uSGVCNGjMDGjRvx4osv4o033mizbX5+PsrLy10uKy8v9znC3WQywWQyadovDUVBBBESQtnNliAIdahqekaekagj4KZnDofDxd/hzOjRo7FixQp56BkALF++3KPHxB+MRiMEQcCpU6eQk5MT0iZdBOEOURRhsVhw6tQp6HQ6uasrQRDhx+yl6VmS1A7eYnPAanfAqKdWW9GCJjEye/ZsTJkyBV26dEF9fT0+/PBDrFq1CsuWLQMATJ8+HZ06dcLcuXMBAHfffTfGjx+P5557DlOnTsVHH32ETZs24c033wzaE9Dr9ejcuTOOHz8u9z8hiEiQmJiILl26uG2uRhBEeLBKYiTOy9RegKVq0hNp4RAtaBIjFRUVmD59OkpLS5GWlobBgwdj2bJlculjSUmJy4F4zJgx+PDDD/HPf/4TDz74IHr16oWvvvoKAwcODOqTSE5ORq9evTxWexBEqNHr9TAYDBSZI4gIY7EzMeIu6mHU6xBn0MFic6DRYkd67I8xazdoEiPvvPOO1+vdlUNeeeWVuPLKKzXtlD/o9XqXcfUEQRBEx8Nq55ER9wuDpDg9EyNkYo0qKJ5MEARBtBssPE3jYXFK5b3RCYkRgiAIot2gpGncR0aovDc6ITFCEARBtBt4msboxsAKOJX3mqm8N5ogMUIQBEG0G6w21nMqzkPZbmIctYSPRkiMEARBEO0Gi91zaS/glKaxkBiJJkiMEARBEO0G3mfEU0MzStNEJyRGCIIgiHaD6sgIpWmiChIjBEEQRLtAFEWf1TTcM0KlvdEFiRGCIAiiXWB3iOAzUz0ZWHmapok8I1EFiRGCIAiiXWC1K9PbfadpyDMSTZAYIQiCINoFvPsq4NnASmma6ITECEEQhEZW7q3A6Lkr8OH6kkjvCuEE94sAgEFHHVhjCRIjBEEQGvly8wmU1rbgwS+345vfT0Z6dwgJq1MljacJ2nJpr4XSNNEEiRGCIAiNVDVa5L8/++14BPeEcEYZkuf51JZEkZGohMQIQRCERk7WNst/n6hu9rIlEU6sPsp6ASDJRO3goxESIwRBEBoQRREna5zESE0zRFH0cgsiXCg9RrxERuKoHXw0QmKEIAhCA9VNVrRYFaNkk8WOmiZrBPeI4MhpGg9lvYBiYG2xOmBzMrwSkYXECEEQhAZ4VCQnxYTsZBMAFh0hIg/vM6LGMwKQiTWaIDFCEAShAS48CtMT0CkjAQBwnHwjUYFVRZomzqCTPSXUhTV6IDFCEAShAR4Z6ZQej86yGGmK5C4REr6G5HGooib6MPjehCAIguCU1rYAAArTEqCXGmtRmiY64J4Rb9U0ADOx1jRZ0UAt4aMGEiMEQRAa4JGRgvQE+aRH5b3RgZo0DUBdWKMREiMEQRAaqG1mlTMZiUakxhsBKNESIrJYVaZpEqnXSNRBnhGCIAgN8BNYksmArOQ4AK4dWYnIoaYDK+AUGSEDa9RAYoQgCEIDfPR8ssmAjEQmRqqbSIxEAxaptNdXmoY3PiPPSPRAYoQgCEIDfPR8YpweGUlMjDRZ7Gix0okt0lhVND0DlDRNE6VpogYSIwRBEBrgof1kkwGp8Qa5ooa6sEYeNe3gATKwRiMkRgiCIDTg7BkRBAEZiczESqmayKNERnyU9pooTRNtkBghCIJQidlml1uO8xOa7BshE2vEkatpfHpGpDQNGVijBhIjBEEQKmlyWknzExoXI1UUGYk4ZpVpGiUyQmIkWiAxQhAEoRJ+8oo36mCQTngZSTxNQ56RSGO1SdU0vtrBS9U0TTQoL2ogMUIQBKESZ/MqJzOJ0jTRguo0DUVGog4SIwRBECpxNq9y0qnXSNRgUVnam0QdWKMOEiMEQRAq4dUXPMwPAJlkYI0alNk06qppKE0TPZAYIQiCUIkSGdHLl6VLpb1VHdgzYneIOFHTDLtDjOh+WFRX01CaJtqgQXkEQRAqaXCTpuGekZoOnKb51+Id+HB9CVLiDVh440iM6JoZkf3gaRqfBlZK00QdmiIjc+fOxciRI5GSkoLc3Fxceuml2Lt3r9fbLFy4EIIguPzEx8cHtNMEQRCRwJ1nhLeE78jD8lbvPQUAqG+x4dvfyyK2H1aNpb1NFjscEY7mEAxNYmT16tWYNWsWfv31VyxfvhxWqxUXXnghGhsbvd4uNTUVpaWl8s/Ro0cD2mmCIIhIwMVIspNnJD2BpWk6ajv4+hYrTtQ0y//vLa+L2L7whnQmH5ER52qoJpopFBVoStMsXbrU5f+FCxciNzcXv/32G8aNG+fxdoIgID8/3789JAiCiBJkA6vTySxVEiMNZhvsDlGeVdNR2F/R4PL/ntL6CO2JU5rGR2TEZNBBJwAOkQ3LcxYnRGQIyMBaW1sLAMjM9J4fbGhoQNeuXVFUVIRp06Zh586dXrc3m82oq6tz+SEIgog0cmTEycCaEq+cyBpaOp4HYV8ZEx8ju2VAEIDKRgtO1Zsjsi9qB+UJgkC9RqIMv8WIw+HAPffcg7PPPhsDBw70uF2fPn3w7rvvYvHixXj//ffhcDgwZswYHD9+3ONt5s6di7S0NPmnqKjI390kCIIIGu48IyaDHvFGdiita+l4qZq95UyMDOmcjm5ZSeyysshER9SW9gJKRU0jDcuLCvwWI7NmzcKOHTvw0Ucfed1u9OjRmD59OoYOHYrx48fjiy++QE5ODt544w2Pt5k9ezZqa2vln2PHjvm7mwRBEEGDd2BNahXWT4lnqZqOKEb2SWKkd34K+uSlAAD2lEUmmi13YPXhGQGcKmpoWF5U4JcYueOOO/DNN99g5cqV6Ny5s6bbGo1GDBs2DAcOHPC4jclkQmpqqssPQRBEpGmUPSN6l8tTpVRNXXPHO7EdOsUKGIpzk9E7n4mRA618JOFC7sDqI00DKCZWKu+NDjSJEVEUcccdd+DLL7/Ejz/+iO7du2t+QLvdju3bt6OgoEDzbQmCICKJ3GckzjUywk2s9R0sMuJwiLI/pCAtHp3SWduG8rqWiOwPr6bx5RkBgERqfBZVaLIQz5o1Cx9++CEWL16MlJQUlJWxevK0tDQkJCQAAKZPn45OnTph7ty5AIA5c+bgrLPOQnFxMWpqavDMM8/g6NGjuPnmm4P8VAiCIEJLs9Q+PDHOU5qmY53YaputsEl9OrKSTMhN5WIksgZWdWkaagkfTWgSI/PnzwcATJgwweXyBQsWYMaMGQCAkpIS6HTKB6G6uhozZ85EWVkZMjIyMGLECKxduxb9+/cPbM8JgiDCjNnGTlzcsMpR0jQdKzJyuoGJjvREI+IMOuSlMDFSUR+ZyIja0l6AurBGG5rEiCj67lS3atUql//nzZuHefPmadopgiCIaMQsnexMhlaeETlN07FObDxFk51sAgDkpbLfpxsssNodqkRBMLGqnE0DKJERqqaJDmhQHkEQhEparJ4iIx2zmuaUFBnJkcRIRmKcXFZbEYFeI1qqaWQDK1XTRAUkRgiCIFTiKTKS0kHTNHJkJIWJEZ1OQG5KZEysDofoZGD13WckMY69h2RgjQ5IjBAEQahEFiOtIyMdNE1zuoENB+SREQDIlVI1FWEWI1aHQ/7b19ReQImMNJEYiQpIjBAEQajAZnfA7nA/iE02sHa0NI0cGYmTL8tLiUxFDY+KAOo8I0ppL3lGogESIwRBECrgURHAjYG1g3pGTrfyjACKiTXcaRqL0/tD1TSxB4kRgiAIFbiKkdZpmo7ZgbW1ZwRAxHqNcPOqXieompwsp2nIwBoVkBghCIJQAa+kidProGt1suORkY7WgdVdZCRXEibh7jWipRU8QB1Yow0SIwRBECpQKmnaHja5gbWuxaaqH1N7wOEQUdkoGVidIiO850iVdF24sGiY2As4R0bIMxINkBghCIJQAe++2rqSBlBKe+0OscOc3OparLKhNyNRMbBmJrG/wy1GtPQYAYBEE5X2RhMkRgiCIFRgtrrvMQIACUY9DFLqpqOU91Y3sZRUssngIgCcxUg4o0RWG3sstWka56m9HSWaFc2QGCEIglCBpx4jACAIglOqpmP4RnjkIyPJ6HJ5hiRGzDYHmq3hixJZ7Oyx1PQYAZR28A7R1ZxMRAYSIwRBECrgBlZ3kRGg43VhrWmSxIhTigYAkuL0cqSksiF8qRqLjXdfVZmmMSrvI6VqIg+JEYIgCBV4M7ACzhU1HePExiMj6a3EiCAIyJQuq24KnxjRMiQPYK3reUt46jUSeUiMEARBqEA2sHoSIwkdqwtrjeQZyUw0trkuIwImVl7aqzZNAyjlvTS5N/KQGCEIglCBbGA1ekjTmCTPSAdJ01Q1uY+MAEBWBMSIEhlRV9oLAMm8Cys1Pos4JEYIgiBUwNM08T4jIx3jxMY9I7x6xpmIREY0lvYCiomV0jSRh8QIQRCECmQDq4fISEebTyNX07hJ0/DUTTg9I3KaRqVnBACSKE0TNZAYIQiCUIFPAysv7e0g82l4n5EMN5GRzCTehTV8woxP7dUkRmhYXtRAYoQgCEIFvgyscmlvB4mMVDe6L+0FgEyp90hVY/iG5WmtpgGARJ6mIc9IxCExQhAEoQIlMuI9TdNRSnt5ZCTdXZpGioxUhzUyot0zkhxHnpFogcQIQRCECng1TbybDqyAc5qm/UdGRFH0YWBlr0VlGCMjZpu2QXmAYmBtIM9IxCExQhAEoYIWm8oOrB0gTVNvtsHmZkgeJz2BXVYbRmFmtfthYJU8I02Upok4JEYIgiBUoPQZoQ6s3C8Sb9Qh3k11EU/d1DZbwzaEzp80jRIZaf/vWbRDYoQgCEIFqjuwdoA0zWlp5kx2ssnt9VyMWO0imizhSYHw0l4tBlbqMxI9kBghCIJQgS8Da4oUGTHbHHJPkvbK6QbmBfEkRhKMetm7Ea5UjT+lvSkm6jMSLZAYIQiCUIHcgdVDmibFZIAgeSfbe6pGESNt/SIAG5aXJvlG+AybUONPB9ZkSYzUU2Qk4pAYIQiCUIHcgdVDZESnE+STW3s3sZ6u956mAYA0KW1V0xyeLqz+dGBNlkzHDe38/YoFSIwQBEGowFcHVqDjmFh5ya43McIH6IXLQ6NU02gZlEcG1miBxAhBEIQKzPJsGi9ipIP0GvGVpgGAdOm1CFeahosRb2KxNSlyZITESKQhMUIQBKECi+wZcZ+mAYDUDtJrRE7TpHhL0yjlveHArzSN3A7eDrsjPCXIhHtIjBAEQahAVZqmgwzL81VNAwBpUnlvTbjEiB/VNNwzAtB8mkhDYoQgCEIFvgysgOIZae+RkVMq0jThjoxYbdqraUwGvdyXhFI1kYXECEEQhArMKk52HaHxmdlmlw26Xg2sXIwE4Blpsdpxx4eb8fz3e31ua/GjHTzgVFFDJtaIQmKEIAhCBWr6WHSEyEil1H3VqBfk6Ic7lDSN/6W9b605hG9+L8VLPx6QW9B7QmkHr76aBnDqNUKRkYhCYoQgCMIHoiiqKh3tCJ4R7hfJSjJBEDy/FoEOy6tpsuDNNYfk/38+cNrr9ko7eM9pNHdQeW90QGKEIAjCB3aHCD7vzeTlZNcRqmlO1jQDAPJSPadoAKfIiJ9pmvWHq1w6o67Zd8rr9hY/+owAzo3PSIxEEk1iZO7cuRg5ciRSUlKQm5uLSy+9FHv3+s7lffrpp+jbty/i4+MxaNAgLFmyxO8dJgiCCDd87gkAGL2kATpCn5F95Q0AgOLcFK/bBWpg5aKHz4/5af9prxOA5ciVBgOr8/03mNvvexYLaHrXVq9ejVmzZuHXX3/F8uXLYbVaceGFF6KxsdHjbdauXYtrr70WN910E7Zs2YJLL70Ul156KXbs2BHwzhMEQYQDvuoGvBskFc9I+11l7y2vBwD0yU/2uh03sNa32Pzq4cHFyLRhhdDrBJTVtaCsrsXj9lYbewwtU3sBJTJCnpHIYvC9icLSpUtd/l+4cCFyc3Px22+/Ydy4cW5v8+KLL2Ly5Mm4//77AQCPPfYYli9fjldeeQWvv/66n7tNEAQRPqxOYsSg8xYZaf/VNPvKmBjpnec9MpLqZG6ta7YiI8lzGbA7TkhipEd2MgrT43GsqhnHqppRkJbgdnt/BuUB5BmJFgLyjNTW1gIAMjMzPW6zbt06TJw40eWySZMmYd26dR5vYzabUVdX5/JDEAQRKeRKDb3Oq2mzvVfTWGwOHD7NIuG+xIhRr5NP9P40PjtRw6IghekJ6JKZCAA4VtXkcXurHx1YAfKMRAt+ixGHw4F77rkHZ599NgYOHOhxu7KyMuTl5blclpeXh7KyMo+3mTt3LtLS0uSfoqIif3eTiAIOn27EmY//gMte+wW/+HDEE0Q0wlMAvsyRPBrQYnXAbLOHfL/CzeHTjbA5RKSYDChIi/e5fZo8n0Z7eS9P03TOSEBRBhMjJV7EiL8G1hSKjEQFfouRWbNmYceOHfjoo4+CuT8AgNmzZ6O2tlb+OXbsWNAfgwgfy3aWoaLejC0lNZj9xfZI7w5BaMZiZ8LClzkyxWQAD5y0Rw/ChiNVAIDe+SleI0Qcf02sZpsdp+pZCXFhegKKfERGRFEMOE1TT2IkomjyjHDuuOMOfPPNN1izZg06d+7sddv8/HyUl5e7XFZeXo78/HyPtzGZTDCZvJeNEbHDfsl9D7CVTU2TRR4vThCxgMWmbu6JTicg2WRAfYsNdc1Wrx1KY43S2mY8s3QPAGBivzwfWzPSE/0TI2W1LEUTb9QhI9GoiJFq92LEancqvfbSrt8dyVJqjdI0kUWThBRFEXfccQe+/PJL/Pjjj+jevbvP24wePRorVqxwuWz58uUYPXq0tj0lYpb9FfUu/+86SR4gIrZw9oz4or1W1Ly15jDqWmwYUpSOm8f6PvYD/kdGuHm1MD0BgiDInhFPaRrnaidvgwzdQQbW6EDTuzZr1iy8//77+PDDD5GSkoKysjKUlZWhublZ3mb69OmYPXu2/P/dd9+NpUuX4rnnnsOePXvwyCOPYNOmTbjjjjuC9yyIqMXhEHGggkVG+kiGtx0nayO5SwShGTXdVznttdfIqr0VAIDbxvdQbRJN97Px2UnJvNopnVXOcDFSXmeWBxY6Y3a6TGtpbwoZWKMCTe/a/PnzUVtbiwkTJqCgoED++fjjj+VtSkpKUFpaKv8/ZswYfPjhh3jzzTcxZMgQfPbZZ/jqq6+8ml6J9sPJ2mY0Weww6gVcNKgAALDjBEVGiNhCix+Bd2EN17TacHC0shGHTjfCoBNwdnG26tul+hkZqWrkU4FZmisj0YikOJZ+OV7d3GZ7Z/OqzkvptTsoMhIdaPKMeOt+x1m1alWby6688kpceeWVWh6KaCfsl6IiPbKTMaQoDQCwkyIjRIzBO7CqiQjIkZF2VN67ai9rxT6iawZS4j0Px2sNn0+jNTLCZ/twYScIAgrTE7C/ogFltS0oznVtuGa2MjGi1S8CODc9az/vVyxCs2mIkHJAbh2djP4FqQCAQ6cbXZpIEUS0o6WHhewZaUfD8jZKVTTjeudoup1iYNVW2ssjKc5TgXOlWTgV9W27sPpbSQO4lvaqWXAToYHECBFS+IGjU0YCspNNiDPoIIqKW54gYgFNBtaE9jcsr1xqw941K1HT7fw1sPLXzrmLa24K62tSIZX8OqNERrSf0nhkxCECzW78KER4IDFChBQenk1LMEKnE2RDGnfLE0QsIHsSvAzJ4yiRkfYjRrgA4IJALekJ/hlYuXhxFSNSZKSurRjhfWD8iYwkGPXgNhMysUYOEiNESKmWDkIZUl+RwnR2MDtJYoSIIfzzjLSPE5soirIA4IJALf4aWN2laXJSPKdpzDb1kavWCIJAjc+iABIjREjhuWKeO5YjI24c8QQRrVg0eUba17C8BrNNTl9w34Za5NLeZqsmPwZ/7VLjnT0jXtI00vtjMvp3SkuhxmcRh8QIEVJ4ZIQflAolMXKylsQIETto8YyktbNqGn7yTzEZkBinrWk377RssTnQYlVvWq+VzL/OkZE8KTJyyo0YsQQQGQGovDcaIDFChBSeK+Ylfjwy4q5XAEFEKx256RlP0eRojIoAQFKcHgbJkFGjoaJGMbAq4keOjNR5TtP4U9oLOJf3khiJFCRGiJAhiqI8rTMjyTVNQ54RIpZQmmp1vHbw3KOh1S8CMD+G1oqaFqtdjnSkuTGwNlrsbSIYcmTEDwMrQJGRaIDECBEyGi122BwsTyxHRjKUahqq6SdiBas0KE9VB9aE9uUZOeVnJQ0njfcaUVlRw0WLTgCSnNJCSSaD3IW1dXTEbGOeFn9KewElMtLQTlJrsQiJESJkVDeyqIjJoEOCdBDJT2MHtBarQ/aTEES0Y9USGZFW82abw+0clVhDKev1bwIxj27UqBRndU5lva1bu3sysQYaGUmhyEjEITFChIyaVuZVgOV0s5JYlMRdiR5BRCNWDR0+k+MMEKRzaHvwIPCGZ1oraTi814jWyIhzioajlPe6ipGAPSNU2htxSIwQIYMb1niKhsOHX7lzxRNENGLRYGDV6QR5pd0eKmqUHiP+pWl4RY1az0itm7JeTo507KhsCG5kJJkm90YcEiNEyGhd1svJ8VKiRxDRiJY0DdC+KmqqZRN6nI8t3aOkadRV03AB5y4ykpXM9qGywfW+AvaMUJom4pAYIUJGbZNrwzMOFyOnG0iMELEBN7CqFiPtqKKGn6BT4rX1GOGkaWwJz9M5zmW9HB5VbX3ssNj8n00DKM+NIiORg8QIETJat4LnUGSEiDUsGpqeAe2roob7XlL9FCPK5F6VBtaWtg3PODwycrpNZCTQ0l72WOQZiRwkRoiQIQ/JaxUZyZYOKCRGiFhBi2cEcI6MxLYYEUXRKTLSVhyoQWufkXrpNXP3eKGKjJBnJPKQGCFChicDqxwZoTQNESNY+WwalSe7VD+n1UYbzVY77FKvIO6r0Io8n0bla9FoYf6PJDet5/lCprIxyAZW8oxEHBIjRMhoMrODSrLJtdwuJ5m58ikyQsQKWg2sGRpTE9EKT9HoBCAxzr+y2bQEbdU0TZIgSDK1fTw5MlLvPk3jb2lvitwOPrbfr1iGxAgRMhot7KDSeriWYmBVP6uCICKJ1S51YFUpRng5Kx+HEKtwMZJsMkAQ1KWoWqMYWNW9FjwykuBG/GRJYqTZakeTRYliBOoZ4Wm1+hYbdYaOECRGiJDRzMOtrSMjkhiparTIK06CiGYsGpqeAUpqIta7DHvzb6iFvxZ1LTY55eMNLjLcpWmS4vSIN7L3wDk6EmhpLzcc2xwimttB19xYhMQIETL4Cqd1ZCQ9wQi91Oa5db8AgohGtKZpuE9KbdfRaIVHRvwt6wVcq2LUpEEazfy40TYyIggCspKkyKqTbyRQz0iCUZkuHOuptViFxAgRMprkNI3rQUWnE6iihogprBqraWTTpspGX9FKoD1GACbg+IA7NSZWOTLiwTCbzdO8TseOQD0jztOF65rJxBoJSIwQIUNZ4bQ9qCgVNTSfhoh+5Km9qj0jlKZxRvbQqIg6eIuMAEB2Eq+oUYReoJERwKlrLplYIwKJESJkNFs8u+JzPLjiCSIakSMjqj0jSpomlg2RzgbWQNDSa4R7NjxGRpLdRUbYbdSKRXfwpm6xnlqLVUiMECHB4RDRZPUcGZGH5VGvESIG4GkAraW9FrsDTZbYNUQGwzMCaKuoaTS7T+9y5Pk0zpERSSyajBQZiVVIjBAhocVmB18Quo2MUEt4IobQ6hlJMOrlVbqa1ES0ooiRQNM06iIjNrtDFn7uqmkA9wsZs1Vbu353pGrsFEsEFxIjREhwXg3GuzGVkRghYgmrxtk0giDIYxCqG2M3Fdlg5p6RwCIjshjxkQJpciqrTXSziAGcJ/c6VdNI7098AJERMrBGFhIjREhocjKh6XRtV5MkRohYgjc9U5umAdpHF9bgpWnUGVj5ccOgEzwKP9lv5tQWQImM+FdNA7SfeUKxCokRIiR46r7KyfEw8IogohGLRgMroPQaqY7hLqy8tDdcBlZ+3EiI03vs+Mq7sLqLjATmGTGo2kciNAT2CSMIDzR5qaQBlF4BFBkhoh1RFDWnaQDtA+Kikboge0Z8vRY8MuLJLwIow/Kqm6yw2h0QALmzayCeESVNE7vvVyxDkREiJHDPSILRvRjhaZp6s01uG08Q0YjdIcpmbH/ESCyvtJU+IwF6RuTIiPcokRxR9bCIAVjZNM/8Vjda5KgIEGBkJD72369YhsQIERJ44yJPvQJSTAZ5jgSlaohohvtFAMBoUD8sLkPqNRLTBtYw9xnxNpeGo9cJyExSKmp4wzMgONU0PBpEhBcSI0RI8NQKniMIglMXVhIjRPTivPLWYmDljc+qYliMNFm8LyrUkqY2TWPx3n2Vky1X1FjkUmCdABgoTROzkBghQgIfkuc990u+ESL6cZ4sbXBTGeaJLDdty2MJUVQm2PoSB75Q2w6+yUdElZPtZIAPVpdY3oGVxEhkIDFChIRmFblfKu8lYgF57ole57HCwx28H0asRkYsdodsDI334P1SC486WGwOtFg9e8QafURUOVlOkRFeipuaEJjJlu9jvdkmP28ifJAYIUKCr2FXgOvqhiCiFa3dVzmZSbEtRlosSkQo0MhIUpxejip5S9U0qYioAu4jI4FW/DjfvoF8I2FHsxhZs2YNLrnkEhQWFkIQBHz11Vdet1+1ahUEQWjzU1ZW5u8+EzGAGiMaRUaIWEDrkDxOlmSyrGyMzc93k5V9hw06QZNXxh2CICjlvV4qauS5NF4iqoASGTndYAlaxU+cQSdX/1FFTfjR/AlrbGzEkCFD8Oqrr2q63d69e1FaWir/5Obman1oIoZQjGhexIh8QInNgzXRMbDYtHdfBYBM6fPdYnXI4jyW4CX3CQFGRTjy7BcVkRHfBlYlMsLbt6cGGBkBnEys1IU17GiWklOmTMGUKVM0P1Bubi7S09M1346ITRQXfvg9I6Io4tWVB5CWGIfrz+oa1PsmOh7+NDwDWGoizqCDxeZAZYMFiZmx1WOSm1c99QrSCu814s3Eqkzs9ZWm4eZgsxwZSQ0wMgKwLqxldRQZiQRh84wMHToUBQUFuOCCC/DLL7+E62GJCKHmoJLtZsZEMNhcUo1nv9+Hf321Az/uKQ/qfRMdD1mMaEzTCIIgV9TEom8k2JERuaLGS3t8xTPiI00jpcBO11uCNj8HcJpPQ2Ik7IRcjBQUFOD111/H559/js8//xxFRUWYMGECNm/e7PE2ZrMZdXV1Lj9EbKEm3Bqq0t7/bSuV//5/n2/36t4nCF9Y/DSwArFtYg16ZIRPMfaSplE6sPqIjKQofhwexQi0mgagNE0kCXncsE+fPujTp4/8/5gxY3Dw4EHMmzcP7733ntvbzJ07F48++miod40IIfKBzIsY4WmaZqsdjWZbwI2VANa6+9vtihipqDdj58lajOiaGfB9Ex0Tfyb2cjJjuNdIU5AjI5mJvgcHqq2m4REnq13EyZpmAEGKjKjsFEsEn4iU9p555pk4cOCAx+tnz56N2tpa+efYsWNh3DsiGPBohLf+BEkmg7zqCpaJ9ffjNThVb0ZqvAHje+cAALYeqw3KfRMdE6uNR0a0Hy6VNE3smbRbgtTwjJOR5Ls9fpOK/kQAO66kSIuXw6cbAQTZwNoce4bjWCciYmTr1q0oKCjweL3JZEJqaqrLDxFb8AOZyUeePdgm1qOVTQCA/oWpGNktAwCw7VhNUO6b6Jj4a2AFnMfdx3BkJEhpGnlWj7dqGhVTezm8vPeQJEYC7TMCKCZYioyEH81xrYaGBpeoxuHDh7F161ZkZmaiS5cumD17Nk6cOIH//Oc/AIAXXngB3bt3x4ABA9DS0oK3334bP/74I77//vvgPQsi6mixsgO4r86N2clxKKlqClpk5IQUsi1MT8CQonQAwFYSI0QAyJ4RDUPyOLGcplEMrMHJ5mdwz4iX10JtB1aAec6OSIsPILhpGvKMhB/N796mTZtw7rnnyv/fe++9AIAbbrgBCxcuRGlpKUpKSuTrLRYL/va3v+HEiRNITEzE4MGD8cMPP7jcB9H+MNt4msb7ajLYJtbj1UyMdE5PwOBO6QCAkqomVDVa5BMDQWjBEoQ0TWUM9tJRDKzBCaDLaRpvnhGVs2kAJTLCCYaBNZWG5UUMzWJkwoQJEEXPffsXLlzo8v8DDzyABx54QPOOEbGNHBkxeF/hKJN7g7Ny5JGRThkJSEs0oltWIo5UNmHXyTqc0ys7KI9BdCwCMbDyz3ewy9fDQXOY0zSiKGqOjDgTzNJeStOEH5pNQ4QEJTKivpNiMODO+k7piQCAHjnJAIDDlY1BuX+i4xGIZyQ3JR4AUFHfEtR9CgdKRVyQ0jRJUtOzJgscbgbRmW0O8IvViJGsUIiRBGlyL82mCTskRoigY3eI8moynAZWURRxolqJjABAt6wkAMDR0yRGCP/wd1AeAOSmKpGRWJsEG2wDa3oCi4w4RPeeDN4oEfDdgRVQxklwgllNQ5GR8ENihAg6zk3GwhkZqW6yyqu5gjS2Iu2ezSIkRygyQviJxc8OrADzjAgCE+ix1vgs2KW9cQadXI7r7rXg4ifeqINe51v49S9Mc/nf17FGDdSBNXKQGCGCjrMYCWdkhEdFclJM8oGpWzaLjBymyAjhJ1Y/B+UBgEGvk02ssTadmvf8iA+SGAGA9CTPXVjVNjzjDO+S7pdA9EaaVPFjtjmoc3OYITFCBJ0Wm7KS1PlY4eQ4RUa8GaPV4FzWy+FpmmNVzTEXJieiAyVN49/hMidGfSPNkgk9MUhpGsCpC6ubyEijyoZnHEEQ8MAk1t07GH4RAEiOM0CQDllU3hteYmuMJBETmHn3VRWrluwUZcx6g9kWUOOiU1KqJz9VMbYVpicgTq+Dxe7AyZpmFGUm+n3/RMfE30F5nNwUE3aXstEEsURLkNvBA8qwvCo35b1aGp5xbjqnO1LiDeiTH5zGmDqdgBSTAXUtNtQ125CbEpS7JVRAkREi6KhteAYwoxqf0Blo+WONtNriJYQAoNcJ6JLFBAilagh/CGRQHhD8LsPhosnKIhXBMrACShM4d5N7tZT1cgRBwNUju2Co1OAwGPBUTW1zbHl8Yh0SI0TQaZHKek0qmyVlpwTHxFojmc74wYTTTRIjR6ua2tyGIHwRaJomN0bFSHMIIiN8oeCuIy33qARjYGYg8KofqqgJLyRGiKAjD8nz0fCMkxOkLqw1kimOH0w4nSQPSankKSEILQTSgRVQxEjMeUaCXNoLKF1Tq9xEQRvNwX88f0hP5P1QSIyEExIjRNAxa0jTAMEr7+Wh34xWkRFuaD1JYoTwA94zx5+mZ4CTgbUuxiIjQS7tBZza40dxZCSVeo1EBBIjRNBRO5eGw02sAUdGpINHukcxElsrUyI6CNQzkicZqsvqYuvzp/T9CGZkhE8xbvtd55GRYIoff0hPoMhIJCAxQgQdLQZWAMhJZivHQCMjfABXWqs0DRcjJygyQviBladp/Kym4Z+/8rqWmCkvdzhEmKXnHUxx4G2KcbRERtITKTISCUiMEEGHe0Z8NTzjKJGRwNzrtdJKhs/A4HDPSFldC2zSKpcg1BLIbBqAeUb0OgFWuxi0GUyhhpvQgeAaWLOT+RRjzx1YIx8ZIQNrJCAxQgQdWYyojozwyb3+H6hFUVTSNK0iIzkpJhh0AuwOMeZ6PTjz29Fq/POr7Xjk653yCZIIPbJnxM/IiEGvQ34qi/7FSnSOCwNAvRFdDTxN02y1y5GQ1o+ppc9IKEhLUAb6EeGDmp4RQYd3YFV7EJNLewMQCvVmmxwCb+0Z0esEFKTH41hVM07WNLt0aI0VWqx2TH9nPRqlA/bwrhn4w5DCCO9Vx8ASYGkvABSmx+NETTNKa1qALsHas9DR7DQnxlcXZS0kxelhMuhgtjlQ2WBBYqZyCuKD8tR2YA0VvDVADUVGwgpFRoigI5f2qjSwOkdG/G0Jz1M0JoPOrVelMC22fSM7TtTKQgQAFm85EcG96VgE2mcEiL2KLl5JE+wyW0EQPFbUREtkhBtYa8nAGlZIjBBBhxvftJb2WmwO1JttPrZ2D3e+O3dfdaZTjFfU/Ha0GgDQM4fN2lm971TMTYGNVawBVtMAsWeibpb9G8EXBp4qangH1mB6VPyBt6wnz0h4ITFCBB2tBtaEOD2SJQe9v+W9vJKmdYqGE2sr09ZwMXL1yCL0L0iFzSFi5Z6KCO9Vx4BP7fXXwAoAhWnMMxIrn78mi7bophZ447PWkRGepkmJcDWN7BlptgY8vJNQD4kRIuhoLe0FlPkd/vpG5FbwCd7FSKysTJ0RRRGbS5gYGdE1A2f1yAIAbD9RG8nd6jDInpEAxtXLYrg2Nj5/LdYQRkaSeGTEVYzUtzAxkhykCbz+whc0doeIBj8jtYR2SIwQQces0TMCKCV//g7Lq21qOyTPmcL02FqZOnOiphmnGyww6gUM7JSGIUVpAIBtx2siu2MdhEDbwQOx13gvVJ4RwCky0ipN08DFSIQjI/FGvRzVpcZn4YPECBF0WmzaOzcqk039O1hXN3mPjHTOiN3ICD+BFaYnwGTQY1AnJkZ2nayjEt8wEEzPSFWjRfZjRDNymiYE/g1uYHXuueJwiGiQPCMp8e6/w+EkjVrChx0SI0TQkWfTaOhPoMyn8S8yUt/CDhqpCe5XVQVSNU19iw11LbF1gCmVQvt5Uq+KbllJSIk3wGxzYF95fSR3rUMQaNMzAEiNN8gr/lhI1chzaUIQGZFTsk7f9UaLDdyekRLhNA1AXVgjAYkRIujwyIhJU5omsMm9DdJci2ST+1VVkskgH2BKYyRUzimXZpoUSCZInU7A4M4sOvL7cfKNhJpAm54BrKQ1llKFzSGsbMnlgwOdoqDcm2HQCaqN76GEN06spsZnYSPy7zrR7uAGVpOGyIiyWvJPjHAnfpKXhklKr5Emvx4jUpTVsteEd/EEgAGFTIzsLaPISKgJRtMzILYqupot7DmHQozw77pzN2TuF0mJN0AQgtdkzV/4SIlq8oyEDRIjRNDR2vQMUBqf+duuna+svIV4lYqa2IqMlNWxk1d+miJGeuUmAwClaUKMKIpBaXoGxNbnL5QG1lxJjNQ0WeUJ33VRUknD4QP9qqmXT9ggMUIEHUWMqD+Q8ROtv2PWG8y+J352iqEwuTNltew1cY6M9M5LAQDsK2+IyD51FOwOUfYyBOIZAZTGe6Ux8PnjaZpQDK1LTzTKZmDuG5EXEx7SrOGGV+VRY8HwQWKECDr+9Bnh5szTDWa/KkR4mNerGOEVNdXRfzJwRhYjTpGRYikycrrBTKu3EML9IgBgNASWPpA9IzFkYNXyHVaLIAhKJFRafDREaWSExEj4IDFCBB3eDl6LES0rKQ4GnQBR9M/EyltJe+veyMPkpTFwMuA4Txp2FiNJJoNcrkypmtBhcRLGgaZpeEVXLPQa4aW9oUjTAECOtPjg33VeDRfp7qscOU1DBtawQWKECDpmP1ZVOp0g55L9SdU0qkjTxFrjKYA1hrI5ROgExVfDkVM1FZSqCRW84RnAKj0CoZNTF+BobzOudGANkRhp5RFT4/kKJxkUGQk7JEaIoKM0PdP28cqTVv7ltdrFQr2K7o38ZFBW1wJbjDQL48IsJ8UEQ6uVea88lqrZT5GRkOHcYyTQKo+81HgIAhM4p/ysGgsXcmQkRGIkN9VVjERLK3hOZiIZWMMNiREiqNgdopxn19L0DFAMmuUaIyNWu0NODXkTIznJJhj1gkvqI9rh8zt4OaQzvXO5iZXESKgIRvdVTpxBJ5eXH6uK7vLyUFbTAEpk5FRrMRIlBlbZM0JpmrBBYoQIKjy8C2g3v3ETa1mdNqHQ6DTMyluaRqcTZN9FrFTU1DR7nrnD0zT7qaImZFiDMCTPmS6ZiQCAo5VRLkbCFBnh4x8azJJnJEoiIzxN02J1xET7/vYAiREiqJidcuxaOylyoaA1MsLzzXEGnc8umUrjsxgRI15m7hTnJkMQ2Cj21kPHiOBgsbEoX6DmVU637BgRIyH2jOSl8O96dHpGkuL0cik3RUfCA4kRIqjwyEicXgedRsMfT9OUafSMNEqt4NU48TvFmImVixHeyt6ZhDg9ijLYyY36jYQGSxDm0jjTJTMJAHC0sjEo9xcqeDQgFKW9gLLw4JVtajxf4UQQBKULK/lGwgKJESKocDGiZS4NJ89PzwgP8XpL0XBiqSU3oAzq4rMyWtObm1gryDcSCmQDa5DSNF2zpMhItHtGQlzay7+HpxssaLHaZTESDRN7OdT4LLyQGCGCij8NzzjOXVi1lD7yIXntUYzUSCFid5ERAOiVRyZWAHht1QFMfmEN3v7pEByO4JXN8tLeYEVGuBgpiZk0TWgiFRmJRrnarqy2RU7TREtkBACykqnXSDjR/A1bs2YNLrnkEhQWFkIQBHz11Vc+b7Nq1SoMHz4cJpMJxcXFWLhwoR+7SsQC/pb1AkCeZGprsthR72RK9YU8ZEuVGGGCJ2Y8I82ePSOAEhnpyGma6kYLXli+H3vK6vHvb3fjww0lQbtvWYwELTLC0jSVjRa50Ve0YbE5YJMEXagiI4IgyP6tk7XNStOzKPGMAEpkhFe0EaFF8zessbERQ4YMwauvvqpq+8OHD2Pq1Kk499xzsXXrVtxzzz24+eabsWzZMs07S0Q/cppGY1kvwFZh/GCkpdeImom9nE4xFxnhnhH3aZpeubyipj7qG2mFis83H3fplPrpb8eDdt/mIIuRZJMBWVKlRrSaWJudKuJCVU0DAAXSwuB4dbOcCuEltdEAf58qG8kcHg40y9ApU6ZgypQpqrd//fXX0b17dzz33HMAgH79+uHnn3/GvHnzMGnSJK0PT0Q5/ODtT2QEYCbW+pYGlNW1yCkIX/AoSrKKfHOBJEbqWmyob7FGVY7aHbJnxEOapjg3GTqBjTo/3WBx24+kvfPxxmMAgL9d0BsvrNiPbcdqcOhUA3rkJAd838E2sAJAj5wkVDZacPBUAwZ2Sgva/QYLvqDQ64Sg9FfxBI+MbCmpgdUuIk6vk31j0UC21AuFIiPhIeSekXXr1mHixIkul02aNAnr1q0L9UMTEUBuBe9HZARw8o34ERlJVhEZSTYZ5JRHLFTUcM+IpzRNvFEv967oiJ1Ya5ut2C+1w58+uhvG9soGAHzze2lQ7p+naYLVZwQAiqVo1oEobePPu68mGvUBd531Bl8YrD9UCYANstQH2HI/mGRJYuQ0lc2HhZCLkbKyMuTl5blclpeXh7q6OjQ3uw+Vm81m1NXVufwQsUEgBlZAqajR0iG1UaP5LVZSNQ6H6FRN4zmC05FNrHvL2HPulJ6AtEQjLujPjjXrD1cG5f6DbWAFgF65vI1/tIoR9n2KD2GKBgAKpYXHodOszLlIEtXRQrZkYD1FkZGwEJXVNHPnzkVaWpr8U1RUFOldIlTSYvXfwAr412ukXsWQPGcK02Oj8Vm92QZeGJLqRYzIJtYoXWmHkj1lbKHSN58JspHdMgHw0H/g84f4fWht4OeN4tzoLsfmZb1JIRYjPDLCKcpI8LBlZMiWUp6nY2R0RKwTcjGSn5+P8vJyl8vKy8uRmpqKhAT3H77Zs2ejtrZW/jl27Fiod5MIEoEYWAFlWJ6Wyb3aIyOx0RK+VjKvJhj1XiNNSlv46Dy5hZLdpew59ytIBQAU5yQjNd6AJosdu0sDj6gGu5oGUAYcHq1scpkKHC00yq3gQ1vZ0iM7yeX/LtEWGUmSPCON5g5rDg8nIRcjo0ePxooVK1wuW758OUaPHu3xNiaTCampqS4/RGzADaz+ND0D/BuW16Cxe2Os9Brhc2k8mVc5veSBeQ0d7qApR0YK2Gug0wk4Q4qObDxSHfD9h8LAmp8aj2STATaHGJWdWJt4pDHEkZGizEQ5qgdEoRhJUebTNNJ8mpCj+RvW0NCArVu3YuvWrQBY6e7WrVtRUsJq+2fPno3p06fL29966604dOgQHnjgAezZswevvfYaPvnkE/z1r38NzjMgoopAPSP+pGka/EzTRLuBtdZHjxFOj5wk6AS2/akOFFJ2OETZM9I3X1mwjOiaAQDYfDRwMRLs0l6A9djoKadqoi+1JhtYw9CAbPLAAvnvaPOMJMYZkBNnxp/0K4DPZwLf/R04tAroYII/XGj+hm3atAnDhg3DsGHDAAD33nsvhg0bhoceeggAUFpaKgsTAOjevTu+/fZbLF++HEOGDMFzzz2Ht99+m8p62yly0zO/0zSKg92mMuffaOGlve3LM+JtLo0z8UY9uknNtDpS87Py+hY0Weww6AR0y1JOZEM6pwMAdkVpmgaIbhMrN7CGOjICAJMH5Mt/R5UYaakFVj+NFbo78YTxHSTv+wJY/zrwn2nAJ9MBR/Sl12IdzdJ3woQJXkPB7rqrTpgwAVu2bNH6UEQMEqiBNTvJhDi9Dha7A2V1Leic4fsApTVNU5TJxEhpbTMsNkfQTzTBgkdGUlX0QumVl4xDpxuxr7we50jlre0dHtnKS42HwSmN0k9K2RypbESD2RZQi3G5tDeIaRpAESMHTkWfGFE8I6EXI/0KUvDA5D6I0+t8RgDDxoa3gBWPAeZapAI46CiAY+AV6BVfB2z7L7D7a2DjW8Cov0R6T9sV0XkUJmIWnqbx18Cq0wlyZ0a1aRQ+m0btSScn2YQEox4OMbqjI/K8DhURH9nEGqUVGqGAT3zt1KoqIyvZhPzUeIgisCfA6EiwB+VxuIk1Gk3HTXI1TejTNIIg4PYJxbh5bI+QP5YqfnoeWHIfYK4Fcvrizdx/4ALLM1jfZSbwh5eASU+w7X54BGg4FdFdbW+QGCGCijmA2TQc3pnxRI26dtl8aq9aMSIIgmyWK4ni6am8SkjNzB2l10j0rbRDBTcgc/HqTP9C5iEJNFXDIyPBLO0FgOIc9n4dOt0IexAH+wUDbmBNVNFEsF3xy0vAikfZ3+f+A7htHQ7nT4YDOqXx2Rk3AYXDAGsTsOndyO1rO4TECBFUzAEaWAHWiRFQFxmx2R1yNEZLOL4oBsQIH6uuxpirDMzrODNq+OejIK1ti4D+UqnvrpMBipEQVNMA7DMeb9TBYnPgWJR9BhvlDqzRM7Qu5Kx7DVj+L/b3uf8Axj8A6HRyS3hZjOh0wOg72N8b3wZsHccwHmpIjBBBJVDPCKDNYNpoVkru1FbTAEoZ4bGqJqDuJHPJB8uUJopA5cGAXfeNGtI0PbKTYdQLqG+x4Xh19KaegomSpgl9ZCTYaRq9TkDPnOisqJENrB0lMrLlfWDZbPb3+L8zISKRyztC1zmJjv7TgJRCoLEC2PNNOPe0XUNihAgqcjWNP5GRqsPA8odwwamFyEclTqg4qTZIB844vU7TCaNLZgIAEZ0Ofw68MpK55N8YC9SX+7ytV2qPAwsvBl4eDnz254AEToOGNE2cQYc+UhfSnSdr/X7MWEJNZGRPWb3qqix3hKK0l8M7sUZbG3+5tDfYnhG7lX0/oilyd+AH4Ou72N9n3w1MmO1ydZ7UhbXcuWRebwSG/on9ve3jcOxlh4DECBFUFAOrxo/W5v8wUfDLixi071UsMc2Gucr3KHgt0QNnipPNeN34Am449QxgaQAEPVC+A9jwhrb9dkYUgS9vBY7+zP7f+QWw9iW/705r/5SBhWwC7I4THWOWE4+MuPOMdMlMRFKcHhabQ5594g88TRPsahpA6RobaCop2IQkMrLra+DFocC8AcCLg4EdXwTvvv2lbDvwyQ2AaAcGXw1MfBRoNRhQiYy0ShkPuYb9PvAD0FARnP1xONjrcnJLdAm2MEFihAgqcjt4LZGR9W8AX98JOKxA9/GwZBQjU2jArfUvQ/QRWVB8FRoeb9/3OGvpxZis3wirqId4/sPAtFfZdXu/U38/be53KXDkJ0BvAkbdxi7b+I7fB5YGjW3uB0ipiY4QGWmx2nFaGmDWupoGYFVZwTjZW6RIn6bIiCiqiohx8Rht7xdPfSYE4PtyYc8S4NMbgDppcVFTAnx2I7B4FmCOUIrK0gh8eiNbiHQfB/zhlTZCBADyUllk5FS9GQ5no3F2L6DTGUzIbP80OPu04U32urw5AVj2j+DcZwxBYiQaOb0fOPJzUHwHfsE9D6f2ak4z8LC26qZn+38Alv4/9vfYvwHTF0O8chHMogEThM1o2vSBsm1dKfDV7cDu/8kXKXNpVPQosLYA39wLfHglDM2nsM/RCZdaHkP18DuAPpNZdKRiF0sXacVuBb6XDHCjbwfO/xegjwNqS9hr6Qda+6cM6CRFRqJspR0KeIfeBKPeY3+KYPhGrHb2/VNlYHXYge/+H/BUV+DJLsCKOewz5wEuHo9UNqGuxep65YEVwMongNoTfu+7vyiRkSCkaWqPA1/MBEQHMORPwAOHgXH3AxAkr8aDgT+GP/zwKFC5H0gpAK5cBBji3G6WnWyCIAA2h4iqplbTe4dey35v+2/g+2O3AmtfVv7f+FbkhFqEIDESbayYA7xyBrBwKvMdvD4WOLk1fI9/ah/w9vnssV89E5jXH1j0B2Df96pursnAWlcKfHkLO1ANux4471+AIMBUOBBv6a9m9/PDg0wUle8Enu8LbP0AWPWUfBdK9MCH+BFF4Jt7gE3vsP/Puh0zTc9ip9iNzQdJyAC6jmHX+RMd+W0hO7glZgHn/BWISwK6nMWuO7jC6009oTUF1S8/FTqBreLahJXbGSedUjSCmxUtEJyKGk2lvd89AKyfz7p3WuqBn54DPp0B2G1uN89IipOjOi77uOEt4P3LgdVPse/h8U1+778/KJ6RIERGvr2PRR+KRgF/eBlIzATO+yfr2QGwlIQ/lO8EvriFpVq0UradnewBFhFNzPS4qVGvQ5Y0MK/NvKwBfwR0RnZ/ZTu074czO79kkaOkXGaOtVuAw6sDu88Yg8RINLHtY3YAA9gHUm8CyrcD704GDq9hl5sbgIrdbBUWbMq2A+9cAJz4ja3qDQlAfSn7Unz8f6q++Kpn0zjsTIg0VQL5g4Cpz7mESVdlXYOtjp7QW+qAN8az0CWncr/8p+pUxu8fsxWMoAOu/RiYPBd52WyGiVzeW3w++12yzufzdKGlFlg1l/09YTYQzyIU6Cnd3wH/xEi9Rs9IQpxertDYEWWh/2DDzavuUjSc/oWpEODA6ZOHIdaeUKKMosgqqCoPKqWZlQeB0m1tIpGqq2mOb2KlnhCAS+cDVy4EDPHAvu+Alf/2eLOBnZhg2nFCer9+fJw13YIIJOcDthblsxUmgmZgPfIze/46I3DJS4De6f6yerHfFj9W/5UHgflj2Hd6w1vab7/sQbYAGnCZ8p33Ak/VuFTUAEzE9JnM/t7xmfb94Igi8MuL7O9RfwH6XcL+3rfM//uMQUiMRAs2C4uKACyM+bfdwL272AnN1gz851J2Un6qK/DaWcDr5/i3KnCHKLKV/buTgZYaoNMI4O5twN+PANO/BgqGAHYz8OVtPtNGZu4Z8XXw/uVFJrCMicAVCwCDyeXqouxU3Gi5H2Wpg9nzt1tY1AEAknLk7RrVnLDtVnaQB4AJD8oHEJfyXgDofCb7fXyjtvTYz/OYqMrqBYyYoVze81z2u+RXzek2URQ1NT3jDOSpmnZuYi3lDc/S2ppXOb3i6/BD3P1Y6vgLhHn9gbmdgddGAy8MAp7vx6IOc4uAl4axv98YB7w9EWhRXjuL2g6sq6Vo3dDrWKXFgMuAy15nl619mS0g3DBA9o3UscXImqfZFRMeBP78HRPPB34Aynf5ekmCBv/cBRwZ4a/JiBuA3L6u15mkab1aUxHWFuDj65X/68u03f7Iz+y4ozMCFzym6ia5KR4iIwDQ/1L2OxCv2cEVzDxvTAJG3gT0vpBdvn95hzKykhhRg8MBnD7gMdwaFLZ/qoTpxt7HLkvKBq75kH3gRTtQuhVw2ACdgXkb1r0a+OOa64EPrwL+dzdbpXQ9G7j+SyC1EDDGAz3GA//3JRMN5dt9Rg1UlfbWlwGrpYPuRc8wM1grumQmohqpeKnrS8Atq4Hb1wM3SDX9VqXkV5WvYvunzLuRlAOMucPlMQCnyEjhUOYbqS8F6lTm6quPsIZJAHDBHFb2x8ntz6Jb5lqg6pC6+5NottrB/XJacvfchyCvtNspcprGTVkvAMBuRcLim9FTV8pMyoKefb4rdgG1x9j7bExkIrvqEDvpGxKAE5tYFZSEHBnx5hk5tQ/Y/z27z3F/Uy4fcBnQ5yL2nV18BxPFreCRkcrje4FvpEnm4x4AJvwdyOwB9L2YXbZ5kcpXJjDsDlH2fQXkGTm+STnpn31P2+vjJDGiNTKy6gmgYqfyv06jYOLHneHXA+lFqm6Sxytq3E3ELj6fve+n9mj+jsv8IqWsRtwgpYvPYZ/N+pPBW3DGACRG1LDkPuCVEcAzPYG9S4N//w47W10DwOhZTARwjPHAVYuAmSuBy94E7tqizEdwOin7hd3Gctr7v2cnzQv/DdzwPyXNwEnKAgZdwf720gLZ7hBlw59XMbLmWRbt6HwmW0m6gQuFI1VmJhJy+wJG6cTjLEYsKsTIeqlc96zblftweoyjlZIYiUsC8gawv49v9Hx/ziz7BzuhdR8H9Jniep3eCOQPZH9rzI3z9JMgaFuhDk9vxOW6Ncg99l1oxXOE8Zmm2fohcGw9mnRJON/yLN4ZvxaYtZEJ7elfA7OPAQ+eBO7czD7zd20Fxt/PbutkkDarGZS3azH7XXw+ExDOTHkaMKUxkfPNX1kVhxOsokbEzbUvA9ZGoMsYYML/UzYYzLxT2PtdWFbJ3LwKBBgZ2fg2+z3oCvcnfRPriQNrk/qUc1MVsP5N9veAP7LfWsTM6QMs5SzomK9LJby8121kxMVr5se54eRWaZ/07PgESIvACezv/R0nVUNixBf7limmx5YaVoLqj8u5+ghLhVjctH7e8w3zQcSnAWf82f3tOw0HhlzNDnY66cTrCPBks+ZpFgI2JAAzvgXG3Ol5pcH3a9dilm93AzevAl7KApurlVXe+f9yW04HAF2z3LRr50LC1iwfmBt8tUw/tZdFlHQGYPh0l6uKWqdpAKBIStUcUyFGDv7I3jtBD0x+yv1zKRjKfpdu9X1/TsgRnziDR4MmANakjX8eD6zAsP9NwnNxr+Pf1mdhe2ey/6u1KMdbjxE4HHJlwm9dZ6JEzMOuihYgpzfQ8zwW7YtLYu9XVk8mJDO6Av3+wG5/aDXQXANAZWnvbkmM8Ns7k14E/EHyA2x5D3h1FLD1v0DjaQDsRPe3xO8wTrcdDn0cMO0V1+9gz3PZQqHmKPss+8JhZwZvP5txcb+ITghgHk9TldJHZOTN7rfhkRFAvaDY9C777ucPAgZdKd1WQw+Zre+z38UXAOldVN+Me0bcihFAWYTs8yNVw/sQDbzcVbT1klI1KgsHXHDYWV+X6qPabxtBSIx4w9oCfCuFXc+8BcjozloAc7ORWo6uZfno/90N/O8u1+scDmDNM9Jj/AWIT/V9fzwV4Cbsq5qSX1mEAmAHwKKR3rcvHMZSOHaLx+fvLEY8Hsh2fc3uI7c/Owl4oIskRk7WNMuhclmMiA52H3AaJuep4uT3T9jv4oks7eUEFzyldS3ygD8UjWK/eeMyT9itrIwTAM6cCeT1d79d4VD2W2NFFO/14LGSxtwAfD4TeK43MLcT8HRP4P0/QrA04qDQFXViAgwnNwLzz2F9HiLJic1sX9+7jJ2Ig9B231v3Vez7jol7UxrMQ5i/YE+pii6n2b2A7D6s341kGOeRPo+f56rDLJQu6FlKxh0DLgOu+S+Q1oWliL66lUVZ558NfHAV7nSwk+SmXn9l4siZuCTle6LmZPf9P1kq48tbfG/rBtmD5UsEe2P7ZyxamD+Y+c/cYTApiyo1iztRBDYtYH+PvkPxnKgVIw47++wBwLD/U3cbCe5LKq31IUaOrpVFrCqqj7AqGgA4u9V5gYuR4xuZuFOLKLJig0+uV9J+avjpOZbCqj6i/jZBhsSINza8wQ4eKYWsO9/ER9jlv7wAVOxRdx8OO+vK2SLl8Ld/yr6snG0fsoOZKRUYdau6+9RJYsThpxg5ug744CrmQxnwRyUF4ws+s+G3hW6NY81O5lWdzsOBjDcI4isbD+Qkm5Bg1MMhKtNZYXA68UipmgbppO0xMsLz/24eLyspDklxeogicKxKegx+4C/9HWis9LyDa54FTu9lplrnsHprCocp96chzF7vaxLx0r8D2z9R/m86LUd/Xi1+C1PMT+J42ggW+v9kukvqIawc+AFYcBHb14M/shMxn4zqJ3UtVjmNVeguMsLF8sg/o3dRIduNigZY1bSFz+jKfkvfV58GVl623WU0S2d6ou9FwKz1zJiaK6UCy3fIYfiXbZfic8PF7m/LKzZ2+5iDsmcJ8Otryv9+VNzJlTSBdF/l37kh13iMfEIQtPlGSrcyT50xiXnojEnSbVUOGTy2AWgoA+LTgd6T1d1Gggtej2Iks4ckYm3s866Wda+yhVXP81i0x5m0TkBOXwAiEzlqaKpiImSvtPhQ21JAFFn6a+XjQM0x1bsfbEiMeKKpClgjldme908gLpENSOo1ia3KF89S92Xfv5yFWOPTgTGS+l32D7YaqCsFfniEXTb+Ae8HM2f8iYw4HMDhn1ht/oIpzFTZZTSr/VdL9/EscmBrcW3QI8EjIwmecs0NFczNDvgUQIIgKL6RSmn1ozeyFSjgJEbYa+BWjFQeZGkKnRHoPcntY3TPYQe1Q6ekA2JKPovaQASOrHG/c8d/U6JZU55meWNP5PT1y8TqNf1UfVRZ5f3f56zqaeaPwL17gD+8jEHdcnECOXgk/QkmNh1WVoHw9V2sImrxHe6d+jXHgCX3AyvnKuIZYKu9nV9qW6EBLKX34TUstN7zPCVPv+FNlq7zk1IpKpKeaGxbflryK3BsPStNH3UrOmcksLbwdgeOqGkLr5eaX9ktsDtE2B0+mp4d/on97jHe933HJTJj6u1rgfsOsCqy8/6JnycuxnO2q/C7J9Nx30sACMx3UlPieT8+neF6mZYUhkTAZb11JxWTe/9p3rflvhE1kREe3Ss+j3kq4rgYUZni4Sfo3pM8NjjzBB/cWdVoQbPFwzGfR0fUVtXUnWQjMADlvNCabuew30d+8n1/JzazSJvzoiOnn7p9qT7MhJrOCHQ+Q91tQgCJEU+seYadQPIGKXMIBAG4eB6LYpzYBKx/3ff98Fknw69noiajO3vjv/wLq2JpPMVOfmdqCKtq9Yw47MB704BFF7PafIisG+J1nyrhTjUIghId2fhOm5kMco8RT91XD65kj10wRFXOtocsFBqVx3f2jUBpB+82TcP7e3Q5SznwtaJY6stx4JTTQY2bxw6tansDS5PUqE1lVMnZxKrBN9Jo8fK81r3KHr/HBJZ+Sshg4fBkVvI8tCgdAPDbsTqIf3xTKjcWmVdn24fMu/DBFSxtsvgOJlIW3wG8PIIJhdVPAq+cycpJf1vI5ol8OoOVwG54S50xtuowE74OK3udrv0YOP9hIG8gMy1ueV/1a9Gak3JZr5sUzW8L2e/BVwEp+dDpBPSWBgjuLlORqnES+nJ6EB4iI6KoiOtuY9XuPiM5Bxj4R2Dc/SgexJrj7SuvdzGQyqTksRQpoJhlnSnbDvz3WpYa6TNVuVytGLE0sdW3KMqfO7/Nq7u+Zr+LzgLSOnvfVo6MqHhfuJjg1UWyGFH5HLlIaG0yV0FqvAFJ0uvBvUpt4Cm6/d+zNg2+WP0UW9R1Ga0cb1ojixEfKWOHnZ1P6k8CmT2Zfw2QU9k+4ZGXTiNcDP7hhsSIOxpOKW7wC+e4GsrSOrESTgBY8Zj31W7pNhaaFnTAGTexPOlFzwAQmPGx7HcWMbnmgzZ9NryiNTKy+2uWAzfEA8NvAG5eAVw23+MJ2is9z2cfWlsz8PMLLlc1+4qMHPxRuo/z1D2UJBQOOguFVhU1XIykxrtpCc5DpsUTfT9GhdNBrYfUH2TPkrav8ZpngMoDrI301OdUPQ/ZxKrBNyJHRlqvUB0OJQw++k63t+1fmIo4vQ7VTVaU1FiAi19gEZRRtwLn3AuMnMkE7aGVTJhsXsR+282srDCzJxPM80crJd+mVGbgXnIf8OpIdtL35v347gF2sO02Frj8bbYaFQTW1Algt/ezOoSX9XZqnaKxmYE937K/hyq+gL75zIe1t0xF7xWnyIizGHFbTXNqD0uPGRKYwdxP8tPikZdqgt0heu4PM+BS9nvLB64RWbsN+Oo2dkLvNha44l1WvQOoO1E7HMBro1i09MAPqGv2kR70xYHl7Hffqd63AxRB4SsyUlfKUloQFC8Fv63d7Ps4WHmQeYh0RqURoQYEQZCjI9yr1IbOI4HkPMBcpzSo9MTRdUpU5PyHPaeyukpipHyH96jkji+A0/vYuWTmCsX/p1qMSJGsrqPVbR8iSIy4Y8t77I0sHO7+xDliBvvi25rZqtLTQZUbRAdeDmR2Z3/3ugD48zKW8hh+A3DLyrblgL7Q4hkRRUU0nH0Pa8McSChOEIBzpXkSm95hBwoJHsJ0W9YritrFSC474LiIEe4bkWZ+8JkeaQmtDp42ixLe9NJlsWeuG8HT81zWk6SxwjUHXHtCyclf9KzXNtIucBOrhshIgycD64nfWDTNlOrRAGwy6OW5LFtKath7VjwRmPIUMPFhYOqzwF/WMA/U+Q8xH8NZtwPXfQ7M+IYd0PhKHADG/x144BB7zgkZTID/725myl71ZNsS82Mb2QpRZwSmPu8q5gdcxtJWlQc8NgLzhcfIyMEf2ckgpVAxIgPoK0VGVJlYZaFvgdmunPSNejcnjKO/sN9FZ2pbTLiBR7O2HvOQvhp0Bau2O7Xb1XO24U0WGYlPZ2kfrSmMre8rqZ/SbahqZCewrGRtqQwA7Dt5RHpNVHQ2VW1C5a9zwWDlO+dSjePj9lwcFI1SVyDghgIuRjxFRnQ6RYDtaeXPsltZhda+ZWyB8/lNzCsy+BrvAiA5R0m18NfAHWslj9SYO9n300lQq6JEiow4f+cjAImR1jjsimv7zJnutxEEdlI3JLATHg8NO3N4DYtIAGwAnDNdRgE3fM3uQ6sQAZS2ymrC5RW72UnQEK8tFeQNOTrSwibVSsieEXdzaSp2sZO7MdHlROH1YeTIiNPBRo6MNEEURXkl1yYyUrqVpQMSs1hqwOdjNEDkolJvVPo7bH5P2XjVE0poVc3KjyNHRtq2G/dEgycDK6+oKD7fa+57WJd0AMDWYzXuN8gbwDwcY//GfAyT5wK9JrLPdkIGK/W+Zztw724mPvVG9n24Zwdw4ePMQFi+nbUqXzjVdeXGBdugK1k5rTOmFEWM8u+HRrhnpE1ZL08RDLiUnRwkZDGiKk3DD+RWl1bwbitLTki9Y1R+nr0xtIj5jrYd8+AbSchQmof98AgzV9eeYKZDALjgUTlNpzqFIYqK9wkABB2qJTGSmeSHGClZyxZoKQWS78oHatM0fFHhnAozxCmLMrVippv/J1sehZPN9O7gbdx3fa2MGWisBBZdAvznDywt/9G1rKFiVjFbFPiCp2q4N6k1p/czMaozKO0XtIiRxtNSdF9Q2hpECBIjrTm8mnXrjE9nqzhPZPZgfTIANq3VebpmYyXrRwIAI24EclUaidSiJTLCzWRFo9QbZH0hCOzLBLisvpqtXiIjPC9ZNEr1KrKHJBRO1ZtRK4kOuSGcrQWNFqVLaUprMcIfr8toz2FQsPJencDSPacanDosDpNaTu9dwsxhFbtZIy2Apem0lD3m9tNsYpVLe9uIEanvQG/vue9hXdjJbUuJn0ZRQWC+ntRC18tNyayL7V1bgEteZCfJE78By6XvQtUhxdcw+nb3991f6sfhzv+gAiVN0yoycmw9+90q8sbTNCdqmttOx22N04FcLuv1ZF7ljex4xVQADCliqRWP4hFgabbMnswb8N9rWJWUpYE1Dxzm1ENHrRgp2+5qiLU0olIWI35Eepwjn2q+H2oNrLIv5xzXy/nztHqpqHHx9ZzjeTsfyBU1ntI0ANBtHBNizVUsXWi3AR/9iR2D41Ikr1xXdmy5abm6NLkv38jOr9jvHucqUSMtaXz+Gc7u1bbZZZghMdKabR+x3wMv923mGXUryxVa6llNtyiySodFl7B67dTOir8kmGj5sB3bwH7zCbLBggsKm/LlVCIjbsRIya/SfqjPSyabDMiXuh/K1S5GVmEDaxPqpROLUS+0nRLMRZiPx4s36uXmZy6+kdy+UnREZCmJr25jodV+l2hfQfhhYq13V03TXM2iEYAy98YDw6Sw/67SOpf+L0EjJY+lK6+VmmtteZ+djL77f8xc2/P8tuWKnD5T2Em/YhcredaI2x4jzdVA1UH2d6veFmmJRhRKvSJ8TvB1StN4HZJnaWIpEyAoYmRw53QIAhNMFfUeTnhxicDV77Oo1PENzEQflwJc8oJLJEh1ySz313AsjXKaJjPRjQfLF/yE6cmQ2Ro1+1lfxlJ6ENp+l9Wko6oOsfEO+jh2rPYT3mvEY5oGYBFr3sNk49vAikeAY7+ylOrNy1lq9J7fWV8ntSleLkYqdrZtNSCKin/MeeGsl47NaiIjJzaz34X+e56CBYkRZ8wNSmnUkGt9b6/TsxHU+jjWL2DBFFZeVbGTTdy8/ku/c5TeH5dHRlSkaY5JIiDYITgDj1Ao0QS5msadgZWvWrtoC2lz38j+igbXx7W2oK5ZMa+6hNEdDkWM8FbN3h7DnVEWYL1lTKnMaHxyC4uWTfSzR4ZGE6ucpnH2jHBhmVUMJOd6vX3njARkJ8fBahfZELZQ0WUU8z4BrDpn/zL2+ZzylOfbJGQo1Qfb/qvp4RwOEWW1XIw4pWn4Ci+jm9sD/aDObNX3+/Ea7w/gIU3ThrLtTJwm5wOpBVqegluSTQb0kvxLHlM1AGuu95fVzKDbZypw6xplhAFHbWSEi5FMqdGapUERI8kaIyPmBkVYqvjOAVA3LI+PZcjtDySku16n5nnyRVDh8IAqRXgU7oS3NA3Aoh6CnqWGePuDi+f5Hx1PylZSXq3Tmie3MEGvN7E+NhznNI2vtPBJLkYCF9SBQmLEmW3/ZSG/rGL1Js+cPizfLujZCdBSz8KmN33fNl8eLGTPiI/ISH251FFPCGhV4BaDki7hyGma1qW9tSeU4WSdtJlne+WyUOZenu/nkRGbEnJPTWi1iju9l/XJMCaxLpA+KHZnYgXYSeam71k5YZfRrAqpdYdMtWg0sSppGqfXUo72+I5yCYIgmyL9TtWoZcpTStpIb2LfBzfDD10Y+if2+/ePNfXDqGy0wGJ3QBBYFYoMX+F56Pg5RHotvJ7oAddqGruXVvBBTNFwfJpYOdm9gEtfBa790L3nTM1JurlGibLxVbW1STGwavWMHN/AImJpXXyX9Mr7qcIzcnwT+93Zzfuq5nny9ynA/hk8enq8uhkOh5cTfEZX4I9vSscpAZjyjPqmkp7g87t+fMzVm8XHavT/g2uvI+dhnd4WrKLo9L2JfGQkgLGM7QyHXZmCO+pWbZ6AkTczc9W+ZSwc33289mmSWlDpGana/ysyARzWFeHHTVW46Zwg5gSdIhQcXk2TENfq4M2jIvkDtfU1AdC/gEWWdpdKq3vuGbE2O5lXW32M+QGoYIgi3LzQU+pncqDCzQottx8rvQ4UeUaNZGL18fmqN/MBgE4HFo2prmFdMvDD7gr8drQaN2tsg6EJYwJLHxxezV7zVm333dLzfOZJqSlhKc4pT7dd+bqBGwhzU0yu5bY+ws1DO7P73uYzMqKkQL0OySuTogAFQ3zus1qGFKXjk03HfQsmX6hJXzhHknjXWUsjqpuYGMlI1ChGuEdLbVQEUOcZOfEb++1uEaMmzROklX9BWjz0OgEWmwMV9WZXIdyaQVew16GljqV7A2XUX1ga9NRu4Kvb2ST35mqlqopHJjl6p/fObnEVJ87UnWRFBYLec0o1jFBkhLP9U9aJLiFDWbVpIacPmy/Q87zQChHA6YDpPU2zeQPL4W6xdsFj3+zCpiMaO2h6w51nxObBM1K6jf32NKfCC/2cxIgoii59RpSGZ62+bBpXrTxNc+iU+hW6ZriJtaWWfc58IM8I4ZERm0U54Rap8/+c2Z2lKzYeqVIqhUKF3sAqfNQIEb79FKmS4/ePgWd7qxqxIA/Ia13We9J7ZGRg5zQIAlvZnnY2KrfZr7Z9Rtx2Xy2Xxti3TpEEwFA5elPjffXtC/kk7eXzzE/yhcNl8SKaG1DdxAS+5tJef3pV+BITDrvyXXb3vvqKjNgsQNkO9neAYsSg18mpGpfhnZ5ILQyOEAHY8f7SV9nxY993wLIH2QwiSwNrytnamNtajHiiXHptcvpEtNkZh8QIwNpgL5Xmi4y5U/mQRytyB1bPkZGK+hZYTrLV20GwbqePfbMreCcld54RiwcxUiaFg/1Q373ykqHXCahusqK8zuzUZ8Q5TeMhMqJRjJyoaXbfATMYOJtYj//mc3Pe9CyFR0ZO7WENnkxpqlNFgzunIc6gw+kGCw6raYUebvpMBkbdxv62m5XPiRdOSOZVl5k0dSeZSVHQsV4UbkiNN6JHNvtee/WNOJn/eDVNmzSNw87eDyCoYqRPXgrijTrUm204FMj7pSV90WmEPOfFbm6U299riozYzMxMCwBdtERGfHhGTu1lJ1xjknvPhfw8PYiDil3scxWf5l8LhVZ0cTflO1x0GqGM7lg/n3VSBlh5cOsoq04PQLrMWzdYLkaC+BkOhI4tRr6aBbwxHnhtNAt7FQzxPCcgmlBRTfPNtlL0Aht6NPPKi5Fg1GPb8VpsLqkJzj64iYzIg/KcxYgoKiHtfO0h7XijXj6J7C6tc2kH77bHiN2qnNRUipGMpDi5r0JIoyO8H8XxDT435ZER2cAqpwUGq04hmgx6DJGMm5uOhNg34i9TnlT8Jt5KNCV4VVW3LKcFA48Y5fb3upBQ5Rtx0w6+jRipOsw+94YEluYIEga9DoM6qSjx9YUaMSK9Zl9V5MGiZ98phyQKUkyGts/5yM9sGuzpA23v6+RW9nokZvv2Crnsp4/IiPNn3l202Vc6ynlR4u8EYieKMjVERkLBkKtZ40FIQwYvmOPePyYI6nqNhCC6FwgdW4yc3scMhZZ6pjyvXOg5vxZNOHtGPEQ6dpaUo7vAuqOmdxuGKQPzAQBfbD4enH2QRYESGWmWqmlcIiMN5axjqKDz21HOUzW7nMWItRl1vBW8s4H11B52YDRpWw1x30gbE2sw4RVN3EPjAVEU0WBplaYp9c+jMLIbS9X8etjLBOJI06rFvze4r4ebjgE4pRy8i085DeI1MqIcxJs8zWmpkA7iOX2CnpJVbWL1hq+TfH05UH8SdlHA7F91+OuX+wEAoiReMt2laJY/xCoNXxnRVuQ4G6u1nPT5fpo9GFjlk6WHpoW+0lF8URIkX09RJCMjnDNnskaE9x8Ezr7b83aaxIjnppDhpEOLkTnWP2Gm/e/YM+Vj1oQmCKG8sODilnbfQ6Lu2C4YBAescWlASgH+OJw53L/5vRRmWxD6TshpGuUE4nZqLz+JZvdmfRL8YGAnJkZ+P17jdOJqkSMjKc69OPgXLH+ga+8FHxRLVTv7y0MoRjpLYqRshxKatjQCn9zgMuenyWKXNaacpuG+GxXVQc6M6ck8HD/vPx1634i/OPWO8QUXizy1BsCnX4QzmJtYj9V4fi1cxAifYNtKcJTvYr9DsKJUXfXjDR+RkVP7WbnsIbEQBlMy9lSxRYSOixF3lTTO/WDWveZ6nYYyehdkA6svMeKhmyv/3HgSI/Ltg2PO5GmaiEVGOKkFipHfE76i59YW1r0VoMhINLDP2B/LrUOwXT8g9KbTYKJzOvm68Y3UNlmRUruX/ZPbHxAEjO6ZhfzUeNQ2W7FyT0Wb22hGTtM49xnhHVidPlbl/vtFOEo30RqIchVPkzIkzzkyUiGdKNS0o3aiTx47ualqGe4vaZ1YIzzRrqzmlzwA7PoK+OFhebMGKUWjE6TX0uFQ8rsePBGeOKNbBuKNOlTUm7G3PITPLRDkKJuX7pYAaposON3AVnp8phAcDqUtu4/yxH4FKTDqmf/oeLWHKIzTQbxJ9kC18iT5+RlTA4+M7A6kWZ0PMXJ4B6vKqkgsxvz/G4EmkX2nBBs7yWa29os017geZ5wjew6HU5WXxsaKvOOnuc59hNdnZMTL83Q4gp6G4GLkaKTFiBp8RUZO72XHoYQM1jU2CujQYqRrlvThqoyBD5cz+lYeiVb8fqIGPXUnAQDGfJYa0esETBvGWnt/vvlEm9toxl2fEXcGVp5jzunj90MNLEyDXiegot6MWptRfly3BlY+fE1jSqiP1DJ8X6hP2N2lGtuNb7FuvVvfb7MJF1nJJgNr5lZ9mIXcDfFAloacPJjnZlR3Ngbgp32nA9v3UOE0b8gbPCpSkBavtMmvOsTa7BvifYoDk0Evl4pv8eTJcDqIN7dOlXH4ijKAz7QnOqUnIDvZBJtDxM6TfkZHfKRpzCdYlCO+aCjO6ZWNwT3ZccEgWmGEzTUFBrQdaMhP8gArN22pkXr6aEyH8IaQDlvbFF1jJZscDXj+Lnt7nrUlLP2uj9PmY/FC10wmfk7Vm2VPV9Ti1LzPLbxyTVqsRgMdWoxwE9yRyiisNPCGzjlN0/ZL8fvxWnQXpC+y08nrj8NYqmblngq5uZHfuIuM2NzMpuEtunmXRz9IiNPLw84O10hj3a1N7g2s5f6tWntLkZGSqqbQVdQAbNiZoGP59xedoxyCvDqUzav8hHtKinJl91bVN6U1Y3uxVM3qfaf83evQIqdpvHtGvPpF8ger8nvxyMNvnsrcncRIo8VN2tFhVz7TQTrJOcOa1XETq79ixHP6oqy2BQXNTEz1GMTKcP9yvhJ5SBJacN2orq434pEgXlJef1JpviXPnBqp/bMZl8y+CwAreXd5TEnwpHf1PMPFW2SEl/Tm9AmaDzAt0Sg3g4vK6jRnDCoiIwA7pkQJHVuMZMeqGHE+OLY9cR4+3YgeknlVHmgHoE9+CgZ2SoXNIeJ/204Gtg+GtqZDHhlxESOVUmTE386lEnwK7cEa6flaW2QDq9xnpKUWqJMMuhojI1nJJmRLLbBD6hvJ7evax8bEG9GJ8iqmoXUlDS8j9XMlfl5f1jr+10OVqG1SMc8o3Kg0sPL3xR+/COesHixK9OshT2KkbZom0TlNU3NUaiRlAtKKVD2mVhQTa41/d+DlJL3l4EnZ2J7RnaW1hvfIh03qfzm5dxq6ZLXydvHISNGZTBwAStpQNq9q9IsAbEVukqIj5lYjC9T4crx5TkJkzuwRDqN7MPCZptnHfpMYiQ668TTN6aboNfe5QxAU34ibMNyxygYlMpJd7HLdZVJ05MstAaZq3HpGWlXTNNcATVIVR4DmYD5ifc9pLkaU1tXpfKgXDz2mdlLVzbM1ffLZSS7k3orJT7GZRpOfZLNFOJIZuEFueCa9x/zA4acY6ZGTjN55ybA5RPy4t9zv3Q4ZKg2sG6VoBi9/BeDUoVNdO+tRkhjZW16PSnfNz3ylaXiKJqs4ZD6zIU7Nz/zCS5XJ6UNboBdE1Bsy2LBDCUHq+fHX8YVtbuOS+uQn9/KdLJJ31KmSxh94qqZ1ZERNDwxPtwVC5uvpkc1HR0T5AtaXgfUUP6bEuBh59dVX0a1bN8THx2PUqFHYsMFz34SFCxdCEASXn/h4H07gMFGUmQhBYK23KwNNW4QbLy3hLVUlMAlWOHRGZSUjccmQAugEtuo6FIi6d+MZaVNNw8PZyXnqxmV7gUdGdktixGFtRq2Upinko+T5FNUc/zof9smTSohDOVgOYM2ehv0fcNZt0vsj5Wyl1voNLa3TNJLIyvbfozBpACvtXrYjGsWI0uLfE3UtVmw/wU46Y4qZoIDdqlR5qIyMZCbFySm/9YfdREeccu1u0zRcjIQgRcPhVT8lVU3uBZMvnPtvtFpkmUvZSbohzfUkpJfESJ7JTYpSFsN9naZP/87aItSfZFFSf2dfcRNrS6vvXIWayIiHqAqgfGf8HVDnAT64M6BjZziQP8duPj92q1OqMfi+J3/RLEY+/vhj3HvvvXj44YexefNmDBkyBJMmTUJFhecKjdTUVJSWlso/R48eDWing0W8UY9Cqa300VhL1XhoCW+22ZHScAQA4Ejv3mb1lpsSj7G9cgAAX20NIFXjJjLCm57JkZHKQ+x3lmt0xh+6ZyUhNd6Aejs7QdvNbBWdlmBUTtoBGgsHdXYqIQ4XgtBG2DVanMSIKAbFMMnFyMq9FahvibJUjYrIyIZDVXCIQPfsJKUVfPlOvzps8lTNuoNueq/I3yuLnHZMinNK08jh7dCJkbQEo9z3Zos/TQrlxm9iG4EXV80+S/rWJ2lPqZ3mGja/BGDfY964b/8yYNtH7O8+k/0u25fTlGan6IbD7hSN8RYZ8SBk7FYlPeznwsQTPDIS0uaIwcBbmqb6CEvvGxNZFDlK0CxGnn/+ecycORM33ngj+vfvj9dffx2JiYl49913Pd5GEATk5+fLP3l5eR63DTe8ouby+esw/pmVeHjxjsg2tVGLh5bwJ6qb5ZywPtf9AfOPw9kH8KstJ/xPTzmXY4oiRFF06sAqfaz4ASEI/Vt0OgFDu2SgGUwEidKJS46KAMqJwk/xM0Rake48WQer3eH3vmqmVTdb52oa1J1gK1ydIaDXcUBhKopzk2G2OfDd9rKAdzmo+PKMVOxGzaZPAYgY3TNLuVwegjZcU0WA4htxJ0baNj1ziYzwz3SIc+28Wd16f5rVGZ260DpVmlTUt6CTtQQAkN61lZcizoMg5M83pYClRbqPZ5HOpkpg/evsuoGXa99HjiwonMRI9RG2H4Z47595fltLvWu/pcqD7GQbl6x+grBKuGfk0OmGwOYHhRpvaRrZEN9LUy+mUKNpTywWC3777TdMnDhRuQOdDhMnTsS6des83q6hoQFdu3ZFUVERpk2bhp07d3rcNtyc2ydX/vtoZRMWrTuKS175Gb8djdL22RwPH7aSqiZ0k/wigoeT8gX985AYp0dJVZP/z5OfQCFK49YdckRYjozwUGCA5lXO0KJ0NInscXXSQbOTixjhIXT/ThTdpOiL2ebA3lD2G2lNqz4bLgZWfuDI7BFQVYAgCLII/TxYXXiDhS8x8v7luOLQP3CZ7meM7uEkRjT6RTijpAGC+ysa2g7Nc2dgdREjgVeHqdrHHlyM+DHcUqdTUhhOUYNdJ+vQS2DvfVx+Ky+FpzLZ1gJfbwAGXalcn5AJFF+gfR858W33Uzaf5vTxXqHDnyPgmqpxNnwHuWy1KDMRRr2AFqsDJ2p8dwyOGN4iI3JRQeiie/6gSYycPn0adru9TWQjLy8PZWXuV1t9+vTBu+++i8WLF+P999+Hw+HAmDFjcPy45wOi2WxGXV2dy0+omDmuBzb9cyLW3H8u3p1xBgZ3TkNNkxUzFmyQJ4RGJR48I8eqm1EkSGFVD3MzEuMMmCy1h/fbyGpw8v3YWtBiUSIJcjVNkA/cw7qkox5sBWdwmGGEDZ0znNrS10jpPz9D6DqdoJgHw5mq4cJO8oy4lPZWBS/VddmwThAEdoKLquiftzSNtZlFhwDcZvhajmoAcGp2pm0adIaTb6RNdMRtB1bphGhpUnpfZHbX9Jha4b1hdpyo9S+tFp/OfrfUyBeVlJ1GZ0HqNdM6feEpTeNO4J/xZxaVyOkLXPep726gXvfTTWREbSWMIU45DrW4EyPBTdEAgFGvk6u5QtogMVC8pmmkqeEh/gxrJeQxmtGjR2P69OkYOnQoxo8fjy+++AI5OTl44403PN5m7ty5SEtLk3+KikJTQsfJTjahS1Yizuubh49uOQtDOqehvsWGv3++PXqrbPiKoZVn5FhVE7r4ECOA0nPE7/bwzmOqbWY5RWPQCTDqdczrIEdGAj+RAix03axTctMpaFKmt1YdAkQHEJfCwsh+MlgaLOdXrt5fDK0iIy1O1TTVR9h1QUh1FaQl4GypPXzA1VTBxFtkhK/MAfTWnUBOk/SZsjQqhuVCbZERAHK6p41vxFmMmFvNpuHvhSmNda4MIYXpCSjKTIBDBDb5E73kJ/nmGvmi5tI90AkiGg0ZQFKW6/aeJuC688hk9QTuOwDMWg90PkP7vjnjzoTKe4yoqYRxd/sQihFAmZW1pzTERvdA8JamqZLESEZ31DZZcayqKbxpaQ9oEiPZ2dnQ6/UoL3d15JeXlyM/P1/VfRiNRgwbNgwHDriZ/igxe/Zs1NbWyj/Hjh3TspsBkRhnwHNXDUWcQYc1+05hVbQ2ivIQGTle1YgiQdrnVpU0zozumYW8VJPUHt6P59jKeNkst4KXDtxNlcpqJ0gKPNlkwKDOGagX2ckrRWhCp3RJnDhXOQQQmuW5+l8OhHGWi9HVwFpv5v1TnCIjQXoNearmi83Ho0doe4uM8HJtzsEV7PeJ35j4TClkszo0wmf2/NR6Zo+cChNhtrJVpSJG+IqyW1i6VvLoyHpPPVG8wUvbnSIjgnSSbkh1E6mU57y0StPIHplW0UZDHIKCtzSNmjbu7m5fEWoxwqJqu8uiWYz4joyU6QtwztM/YuzTK3HhvDUor/M+jiHUaBIjcXFxGDFiBFasWCFf5nA4sGLFCowePVrVfdjtdmzfvh0FBZ4PICaTCampqS4/4aQ4Nxk3jGYn8nnL90XPQdsZD8rXXFOGBMECETqvTZn0OgHThipGVr+Q58S0tO0aylM0qZ2VlW8QOLs4G/WQxIhzZCRIVQ6jumchzqBDaW1L+BobtaqmkQcAxhudxEhwhjhOGpCPxDg9jlQ2eW78FW68RUZ49IPDBwYe+YX91jqcTWJMzyzE6XUoqWpy7RnhFPGzWZmfRE7TOK0owwH3tvhlYpXTHzXyRUn17DvpcFfO6a6BmN2mfI9D5S9onaaxNCqvs5qGZc7zbQDXSprcUEdGYjBNY7cCtcwi8cjPynyvw6cbced/t8AWwQiJ5jTNvffei7feeguLFi3C7t27cdttt6GxsRE33ngjAGD69OmYPXu2vP2cOXPw/fff49ChQ9i8eTP+7//+D0ePHsXNN98cvGcRAm4d3xOJcXr8frwWP+2PwpkecjWNa5rGWM/c8pakfJ+rl8uGMTHy454K/zpzOp1E61ucVvOAU4omuJOQR/fMQoMcGWlGJ+4ZCZIpKyFOL58EVodrlouTqAOUapoUk045MAdJjCSZDPL7vuCXw0G5z4Dhq3K7pU3a0V7G+k2ssA9jF8hi5Gf2u9s5fj1kkskgm0RdBkc6iRGj2DpNE95cO/fHbD9eq31EgewZYSd5u0NEXssRdlWBm/QHTzs5iRfUHGWRV0N8yLrNtkmzVOwBIAJJOUByjvrbczFTdYjtszGJLYRCQF9pjtXhysbQjo4IBE+zaWpKANEBuz4eS0tYscGiP5+JZJMBGw5X4ZNNkTO3axYjV199NZ599lk89NBDGDp0KLZu3YqlS5fKptaSkhKUlpbK21dXV2PmzJno168fLrroItTV1WHt2rXo3z/4Ey+DSVayCVedwb6A/1kXHX1RXHATGRFFEclNLMoheknRcPoVpKJvfgosdge+2e5HzxGnXiPcZCe3MK8Mrl+EM6p7FuKS0gEAl/dPRm4Kj4wErxnVOKkPy6q9QZhurAZD6zQNey2z7KdZHw2dMagH1hvP7gYAWL67PDqMrM6RM5trdMQutQVfZhjPLji9n81FOb6R/d9trN8PyyvpVjq/z04VS0ZIpb1ydVh4IyOdMxJQmBYPm0PUXvXG0zSSZ6S8rgU9wE40qV3cRBy4GGlyipa5dJsNkb2wdWRETedVl9u3StM4V9KEaJ9zUtjoCFGMYhOrp8iIJKhPGwsACLh0WCHG987B01cMxl3nFePqkaH1Z3rDr3frjjvuwNGjR2E2m7F+/XqMGjVKvm7VqlVYuHCh/P+8efPkbcvKyvDtt99i2LBhAe94OLheStWs2BMlB21n3HhG6lpsyHcwP48hS90Bk6+S/UrVOJ1EG1qnaYIwIM8dep2Abp1Yiu+KAdKBzLkxWBDEyMT+TFj/cuA0ymrDkEdt7RmRIiOZZmmVktHVrwF5nijOTcHYXtkQRWDR2iNBu1+/ca7Mck7VWJthrGevQU3uWZIxWQQ2vMVEWnJ+QGXjfGbPhsNVSsWKIMjfLSNsSDDqodNJ/pDq4EapfCEIgty+fq27Bm3eaHWSL6moRleBHRvaNDwDFDHS7CR6KkPfbbaNmJDbuKsUI3JkRRIz8jTa4HZebQ03uvvdsj/UcFFta1W6LgnqfVbmmTqvLzvWXTSoAPde2Ad6Xei9UJ6Ino4nUUjPnGT5oP3++iiLjriJjJyqb5EradSKkWlDWbnnxiPV2gWXU2SkwdwqTROkAXluaR3abTwlHYyEoJwoumcn4cxumXCIwGe/hcE8LadpmiGKopKmaZIeOwQnvz+fzT4fH286Fvlx6ILg3sRadQgCRNSKiSgsLAIKpBH1q55gv/tMCchI2i07Cd2zk2BziPjlgFNKTlpVGgWbkqKx21iIGwhrSeT43ixK9+NujVG6VqW9Ncd2Qi+IaNClAMm5bbeXxUiNclk4hqnx/eTf5ZNSuXb+IJW3b9WFNcChkmoZJrUACGvVnRY8pWmkirC95mzEGXQ4u7hVVVUEITHig+mjuwEAPtl4TJ69EhW48YxU1JmVShovZb3O5KfF+1/uKTfranbyORhZpIK3gg9Fc6jWqyl+0EzvEjSz7FVSuPK/G47BYguxqUuOMJnRZLHDLnV2TGiQBHAIxMj43jnokZ2E+hYb/ruhJOj3rxl3JlZJ0B4WC9C3IBXoPdn1NmPuDPhhearmxz1tUzVxsCGRD8mrO86+a3oTq+AJExP65ECvE7C3vF7bYkGupmERA0spMwJXJnR3L+BkMeKcpglDcyznhYW1GTi5lf2vdtZN6zQPbyMfokoazrAu7PXacixKm2N6StNIkZGjYh5Gdc9UzNlRAIkRH5zXNxed0hNQ3WTF/7YFMMsl2LiJjFTUm1Gkkw6qKjwjnEudUjWaKodcPCNOXUMbygFrIyDoVIsiTbSOjIRgeNnUQQXITjbhRE0zPgx1VEwWI4qo0+sEGGuPsMtDIEZ0OgEzx7H7fX31wchHR+TIiJMYkd7Xg2IB+uSnsGZbg69m1w28IihRN56qWbn3lCwC5cgI7Eg0tq6k6RrWFtrpiXE4oys78f2wW8OQw1Z9RoxVTLA3p3l4zSKVpknMVNrX7/iCpd8SMtS/t87HAksTcFrqWKw2suIng4vSIAjAsapmnKr3Y5hhqPHUZ0RKNZaIeRgqRXeiBRIjPtDrBFx3VhcAwIfRsILkuPGMnK6tRwGk3LIGETB5YD7ijTocOt2IbcfdjOP2hItnRDKwmgyKeTW9S/D6ETgT30qMhGBeSEKcHvdMZAfhl348gIr6EHpHjEpkRDYCmwwQQmyYvGJEZ3TNSsTpBgsWrTsSksdQjZvIiLWCnQwPOwpQnJvMVvTTXgOu+xy45IWgPOyZ3TORGm/AqXozNvDW67IYsSlzaapD+1544wLJw/TN76U+tnSiVZomo56JEdGTF4OLEWsTq+pqqmLpTyDoJnQXdHqgUPIQ/jqf/e48Un36zTlKWrGL9Z5JymGzdEJIarwRvXJZJ9bNJVEYHXEXGRFFOU1zVMxF/4LwtszwBYkRFVw5oggGnYAtJTXYHS1d99x0YDWfPgq9IMKqM7nPC3sg2WSQp7p+qWVuidOAN5fSXnlAXojmd7Seu8HzxEFewV09sgh981NQ1WjBvR9vU1bOwcbJM1InvY6p8fqg9xhpjVGvkwXXG6sPobY5gtN83YmRU0yMnI4rYj1XAPa57zVR6YsRIHEGnTwa4Wse+dQrBtYkU6tKmgi00L5kSCF0AvDb0Wr1vW9apS+KrOyzlNhlsOftBem5Nlcr36m0LoAp2d9dVwfv4lq+XfpfZYoGcI2MlG5lfxcMDUtTOt4g0e3050jjTow0lAPWJthFASfEHPQvJDESc+SkmHDhALY6+XB9lERH3HVglQx2DQmdNH8Zearmf7+Xqm8N7NQfo8FZjAR5QF4b2vQm4OPGg1subtTr8PK1w5Bg1OPnA6fxyNc7Q9MAz9A2MtIlroGtUgUdizCFiD8M6YTi3GTUNlvx9k+HQvY4PnFjYDVUs89RS3poq1f+MIR99r/bUcr8QdKBPE6wIYGnaSIYGclLjccEydvyqdo+EE6ekdqq0+gEFuXI6emhdb4gOJUDVztVtYS2KgVA25byWhrZcdHVVKn4TbjROcScU8y7+EZhl253aRpJUJciCyZTPIoyEt3cMHKQGFHJn85kHoyvtpyIjkY3bj5scfXM22BO1l4rPrY4GzkpJlQ1WrBCrXPfuemZXNprDP1kU+fQbHO1PEgtFAfOXnkpeP6qIRAE4L1fj+KNNSE4YbvxjBQbpPcgrSg0qS4JvU7A3y5g6a031xyKXAl768hIUxXiLDXsqpzQTsgd3TML2ckm1DRZ8fOBUy5pGrmapuoI+x2h4WK859F/N5SoG5zH0zSiA1V7fwIAlCMLiWleGok5+0ZkgR9aIygAoJOTGOk0Auh6tvrb8u981SHggNQZPExiZEzPbOgE4OCpxugbqsqj1s6REUlQH3XkoX9BqlKyHiWQGFHJmJ5Z6JqViHqzDd9s05C7DRVuqmmSm9U3PGuNQa/D5cNZY62PN6qM/ris6J0MrEGcNOsW58gI7yuQ2llZJQWZKYMK8K+pLOry5Hd7sHhrkIfMOXlG6qQTTTepJ0Q4elpMHpiPs3pkwmxz4PFvd/u+QShoHRmRUn0nxUzkZ4e2/FCvE3DxYOYx+HrrSZc0TVZynJRrj1xkBGC+kZ45SahttmLBL0d838AYzyp/ANgOsW61x+N8fJZcxAjv1xGG5pSpBSy1YkwCpr2qLaqblK20ja+X0myFQ4O9h25JSzRiUOd0AIi+Lt3u0jRyJU0u+hYEJ80ZTEiMqESnE3DtmSxcvnDtkcjPq+GREScxkmFmIsmQ7d8Bk3ffW73vFE7WqFD6smekWTawshbmXIyE6ETa2rQGhDyc/OdzuuPmc9jret+n27C+9ej5QDAoUQEu6jqLfFR96MWIIAh45A8DoNcJWLqzDD9H4sAqR0ZcxchhRwG6ZIY+nHzJEFau+/2uctidmp71yk0BGk9LA+QEVk0TAfQ6AfdMZBGsN1YfxPFqFREsKe2SXsoiIzUpPjxVCcwDgeYq5XsV4hJZmRnfAHdt8e973H2c8neXMSFNa7aG94H5fqeGSqdwIEfO20ZGSsQ8dM9OisBOeYfEiAauPqMIiXF67Cqtw+pIT/PVuaZpmi12FIjsC5GU519Yu3t2Es7qwZt9qchNO82/4J6RDOsp1klUZ2Dmt1DgEhnh4eTQ57YfvKgfpg4ugNUu4t5PtsmN3gLGxQjM3s8Ch7TKC1O3z775qbj+LHaifeR/O8M/Urz1yHuprPeQWICuWaE/cA7vko6izAQ0WeyobGELjTjY0CsvWYmKpHZS3qsIMHVQAc7omoFGix33f/q7b0O1VF2W08DKXWvzfQwz5ZGRU3ulfiNCyJuHyZhSgJQ8/27rLEZG3RKc/VHJ1EEsorZm3yk5qhkVeI2M5KFbGL5TWiExooGMpDg5OvLKjwciGx3RuxpYK+pbUCR1X03I9f8Eds1I9vw+3ngMDl8HO2nlJTZVySv61GYpxZPRLagtzF3gJy5rExslD4QlnKzTCXj68sEoykzAiZpmzF0SpJSG3DxOqUrKtkipoDCJEQD468TeyEyKw4GKhvC3iU+WTkQNTFA7TisNz8IRGREEAVeNYJHBkhr2HhhhQ3FOckQraZzR6QQ8c+UQxBt1WHeoEk/4+vwNulL+s1pMhrF4vPftuRjZ8y37ndMnqBO3Q0a3c5hQzBsI9L04rA/dOy8ZxbnJsNgd+GFXFEVH3ERGRKfISNes6DKvAiRGNDNzbA+YDDpsOlqNZZEMzelcS3tPV55GpsDK/oQAGo1NHpiP1HgDTtQ04+cDPsL1iSysKzZVwSYJlyS5a2gITYemVMVjcHIz++3n9FatJJkMeOpyVh75wfoS1zbi/sJX21YuRkRk8Lk0YRQjaYlGPDCJrYRf+GG/ulRdsOCl6JIYsUllvcd0hchNCU804qqRRdDrBFRLPawy4gVkJMU5+UW6hWU/vNE9OwnPXskMmu/8fBjzVx30vHH/afIKeZn9DPTIS/d+51yM8Ofb87wA9zZMmFKAOzcDN69wGXQYDgRBkKMjqqLJ4aJ1O/iWOghNLLV8DLnoHGWVNACJEc3kp8XjFqlz5RNLdkeusqZVZKSxjPk0aoXUgHowxBv18vC8jzf6mMsi5ZgdTazpjyAAppoQm1cBFnHpc5Hyf94gID180ybH9MyWUxqzv9ge+JgAgxIZqWu2IgP1MNm4R6FbYPetkavOKMKwLuloMNvwwGe/hy/65xwZcTiglz5H5rTuYXP956XGY9KAPFjBhH5hsnR4jJLICOfiwYX4+2Tm5Xhq6R68+/Nh9xsmpKNlwNWwiTp8Yp/g2yfQuhS/5/lB2NswYYxXjOBh5sozOkMnsGGG+8qjZIpv6zSNJDArxRSkpmchzhB9p/7o26MY4NbxPVGQFo+SqiY89d2eyOxEK8+IVZoFUxUX+NyMq6VUzfe7ylDZ4KXVcaux48lxBgjVITavcoZco/zdZ0poH8sNf5/SF3mpJpRUNeEdTycDtbRqHidX0qR2CvsBVqcT8JyUCvj5wGm8/2uYBkTKYqQCqDsOvd0Mi6iHSeXAx2Axe0o/WYykxklCLMKVNO64bUJP3HU+M6TO+WaXx/5HO4b+CyPNr6E8bYjvOST9p7lOUNbS76MD0zkjUe6S61EYhpvWrR+qlBRNNPpFABIjfuEcql+07ii++T0CM2u4H0OKjAg17KTRmNgp4LvuX5iKIZ3TYLWL+NRb6FFK0+haqgGIrKw31D1GOD3OlQaWCUC/S0L7WG5INhkwewozzb7y44HA+gw4eUaqmizyqPdIrcR75CTLK+8nluzBgQqVXT8DwTkyIpWVHhXz0Tk7vCWIRZmJGNKVVUiM6iI9dpRFRjh/ndgLf5GitP/4arvSQdaJg5VmVCMVPXJUnID0RuCaD1kn1gF/BOKiL5Qfrdx0DnsfPv3tOA5UREF0xENk5KiYiy5R6BcBSIz4zbjeOZg5lh2c/vbJtuB4B7TQyjMSV8dWRubk4FSwXCelId79+TDMNg9pCClNo3NYkAAzUuMEefZByLqvcvQG4Iav2U+BhxbXIWba0EKM6JqBZqsdTwYSIXPyjFTUtaCbLnxlvZ64YXQ3jOmZhWarHTP/swm1TSGuFEiSmnE5bMDBH/H/27vzuKjLfQ/gn9+sgMAMCMwAsgpCsrigjmipBbmeND3dg6alVnpdMj0u96iVltXB6lZmudTtpt1zMspySVNTUTAVRREU1BAVw4VFIfZlgHnuHwODg6w6M7+Z4ft+vXiF8/vNzPPtGWa+8/ye5/sAwEXmY5LJq835uskBAN4yEVBTDlQ0FKAzo5ERQDtfYfmYYEyP9AFjwH/9eB6X7uhvV3HtbgUAoKdrB0u6B0QBi9KBZzcZurlWbZCfM6IfU6Bew/D2nkvtT/43NklDf1eXaOvk6K2koWTE6iwf8xiiH3NDTZ0GM7eeMe0Epmbl4B+l4FlLnu3rCXeZDQrKarDjXCtFviTddO1wQjlCbe5p2yPupi1CZmwugfrL+kyM4zi8PT4EHAfsTruDMzeK2r9TSxrmjLC6apRW18KXa0xG+PvwEwg4rJ/SD55yW2Tfq8Cr351DnTGX+4okTXUusn4FAKRr/PiZ9a+7/FjYlFzbOjWVSzcjHMdh1TMhGNbLFdW1Gsz5d4pe4pjVMIehZ0dGRhrJTH950Bq8Pu4xSEQC/JZ1D58ducpvYxy0+y2hrlq7WWLjShqNwiRL5R8GJSOPQCjgsGFqf4zsrYC6ToOl28/jP/911jSlgZtdE3RWa4doxa6G+TYtEQnwyhPax/oi8VrLNQ04TnepxokrRx9pwzCxW7BJt1nnU6inDJMbisW99fPFh9tMr2FkhAODBHXoJWj4/+hiohoPrXCxl+LLFyNgKxbit6x7eM9QS5lb0/gG2lA0L0Pjz8vICBwb5l2V3m7akt6AO0IbmlDAYf3kvvBytkVOUSUWfZ8KjYahpq5etxNxXy8nnltp/fxcuuHdCdpqsJ8cvoKPD13hb4REbNtUB6osT1e3J5spzXJZL0DJyCOTioTYNC0CS57uBZGAw68X8xH9USK2nMg23i6vgH45eE09FJpHK3jWkskDvSC3E+NGYSX2Z7RSAr/h26yMK0cg17D6xhSba5mRpSOD4GAjwsU7pfjhbDsrkFoiddD1pxv3J3pyDcmIqQpOtSHEQ4ZPYrRLSbecuGHcjSKb7TR9CT78LEHUJSO52gJggFn0RVvkdhJsnhYBqUiAo5l3seHoVZzJ/hMV6nq4OkgRYmY7tFqrvw30wmtPaVcSro/PwuT/OcXffk+Nr+O7vwNl2vfvLNaDnwS/AygZMQChgMOCqEDsfe1x9PeWo0Jdj7f3XMLEjSeQcbvESE/aNDJSU5gDKWpRw0Rw8TRcMtJNKsKMIb4AtH9YLQ7TNwxpO6EcPWpvaG8zxX4WZqS7vRR/byjV/d+/ZqKkqpPzKwRCXQnrxwUZkEKtXdVgBnUtAGB0qLsuvjd2pWNfupH2ZrJvqsB5XaNENwdn2IiFxnmutuiSkTvaN3LAdGXRH0GIhwzvPqv9Zv7RoSuYviUZADCil6vZbYpmzRaPDMIHz4XDTiJEcnYRRq07hm2nc0xfJLNxpPHaUQDafZ7sHJ3aX1XFE0pGDChY6Ygf5wzBexND4WAjwoVbJZi08SR+MsZckvvmjBTf0u4jkQMlZN0Me6135hA/yGzFuJJf3vKcGN1lmjJ0r2hYSdPFkhEAeCHSBz1du6GwQo3P4rM6/wANkyOjBA1F3Fx6aZMUM/FaVABiBnhBw4CFcanG2Q6hcRIrgIOagfztn+HYsCKtPA/Iv6j93cxHRhr9xwAv3WXDxpHZp4Ld2roLMYK/DfDCgYXDMMjPGZXqeqzcmY75286hwlBbSHSEg7YYG65rk5EsTQ/4OJvnfBGAkhGDEwg4TFX5IH7JcDzdWwF1vQZLtp/Hh7/+btjMWNi0mqYy9woAIE/kCa4zO152gMxOrKtn8OGvmSiuVOsdZw0jIwruT9g2Vl/tgsmIWCjAqmdCAGg3Urx2t5PLYRsmqz4tbEhGzOybOMdx+OekMIwL0+7NM+v/zmJPC0tJH0nQWMDBAyc9Z+KDupiOLUc1hm6u2uWtTKPbsM/c+qMtb40PwROBLnBzkGJ8Hw889RglI3zw7m6HuFmD8ca4xyAWctiXnodJG0/ixr0K0zSgcWSkWHtpNYt5mu18EYCSEaNxc7DBF9MiMP9J7WWTDUev4a2fLxouIRE07T2gaSid/aetcTame2GwDwLd7FFYoca7zbaYrxFr94l5UpAGjmm0b+T2XfPNb3gvV0QFu6FOw/Du3kudu3PzSzJu5vfhJxRw+CSmr27C9oLvUrExwYB7NPkOBZZcxr9sX4AGAv5GRgTCpm+VACBxaBotsQA2YiH+9bIKya9HY/2UfpCKzGeErasRCDi88oQ/4mZHws1Bisz8Moz//DgSMguM/+T3v4YBXGE94GuGu/U2omTEiAQCDstGBeP9v4aB47QF0t795bJh3rwbs96SmxA3lM6ucjDOUlCJSIC1DTH8mHILu9OalvqWQLuePVRwQ3tDwNPaVTZd1OsN34KOZt7F0d878YbTvIaFW4hhG2YgEpEAm6ZF4KWh2vZ+cCATM7eeQUFptcGeI/teJ2tjGIPjfZWMXYO69GuaPLoIHyfsWaCdU1haXYeZW89gw1Ejb7baLBm5qvE028mrACUjJhEz0BtrJ4UB0G5utfaAAS7ZNC41LMuFS6n2una9k/GKZEX4OGPeCO0oz/Kf0nEuR7sfTa6w2TfG4LHN79ql+LvaY2bDB/WqnzNQpe7gvjX31RSpFTsC/u3ssMojoYDDqmd6491nQyEVCZCQeRej1h3D/x7PfuS9mjQapktGeLtMAwCO972RB4/jrx3EaigcbfDd7MGYMsgbjGkve8/71ojzSO5LRnLRHReYP79/U+2gZMREYgZ662a6f5F4HW/vuQR13SMUkbKVA/ba0RG7em3VRbFb4KM2s02Lnw7CsF6uqKqtx/Svk3HqeiF2VvVBjqZp4iH8nzRqGyzBa1GB8JDZ4GZRFT46mNmh+9xfrK7C+0mL2Lp92mAf7F3wOEI8HPFnZS3e2XsJj79/FJ8cuvLQIyW3i6tQU6eBRCjgd2fRyvsK2PWfzl87iFWRioSInRSGf04Mg1jIYX9GHiZuPGGceSSNo+cAvqodjXpOBH8XHkcb20HJiAlNG+yDt57RTu7cevIGYr5Mwu1H2abdtakQ023WHXJX41Y9FQo4bJ7WHwN9nVBWXYfJX57CN6du4ZXapVDbugKD/hOQmu+L3VTspSK8O1GbeH51PBvHs9rfKuByoQa5TLsyyfbxOUZtnyEFKhywc95QvDcxFN7OdiiqUOPT+CwMff8Ilm4/j4KyziUl1xvelH2620HI53LUftO0/31sPNCtO3/tIFbpeZW3bh7JlfxyjP/8OE5dLzTskzgoAZdeqHbwxXf1UfCU28JWYr7zhygZMbEZQ/3w5QsRcLQRITWnGKPXHcNPKbce7rLNfRU6j9WHw11u/G/TdhIR/vWyCuP7NF1Td+vZD5L/ygLGfmD057cUTwUr8LxKO6F4YVwq/ihs+5vP0cwCTFG/jljlOkj9LGu3VIlIgKkqHxxZMhzrp/RDhI8TausZfky5haj/7lwBwPRbxQCAXkrTbpD3gLC/AS8dBJ77mt92EKvVfB7JjC3Jht3jTCAE5ibh5yHbUQkbfudgdQAlIzwYGaLEL689gT5ecpRV12HJ9vOY9X8pnf4WeX/tg2OacChlptlPwkYsxKeT++LbV1R4+XE/vP9cOE3wa8Gb43ojxMMRhRVqvPC/ybjeynLf6tp6HLyYhxvMHV59nzJxKw1HJBRgfB8P/DR3CHbMG4I+PWQoq6nD23su4bnNJzu0m+mp69rLI4P9nI3d3LYJBIC3qqm4ICFGoHC0wbZZgzEiSLu30Etbzxi2ho9QhCuF2jkplIyQFnk52+GnOZFYNioIYiGHw5fzMfKTYzjQWtn1lsiblvKeF/dF924SI7S0ZRzHYWiAC978S294mmBExhLZSoTYMmOgbs+Q8Z+fwLrDV3Au50+cul6IDUevYvrXyej/ziGcv6Wt1PuklRSo6u/thB3zhuLdZ0NhL9WOAo5dfxwbE662uuGeuk6Ds380JCP+dGmEdA02YiG+eCFCt+nqrG/OIv5yvsEev7HmUU838528ClAywiuRUID5TwZgT8MkwOLKWsz59zms2HGhY6sS/EcgTzEMn9dNgKe70uAFz8ijc3O0wY65QzHAxwnlNXVYdzgLkzaexOQvT+HDXzOReOUuKtX18JDZ4IPnwq0qsRMKOEwb7IODfx+GEUGuUNdp8MGBTEzadLLFbRLO3ypGda0G3btJEOBm3t/iCDEkqUiIjVMjMDpECXW9dvflAxl5BnnsrAJtMhJg5iMjHDN5wfzOKy0thUwmQ0lJCRwdrXPDJ3WdBh8fuoIvjl0DY9pljesn90Oop6zN+8Xuv4wvEq/jhcE+eKdhtQ4xPxoNw54Ld7Dj3G1k5pVBLOIQ5inDQF9nDPbvjiCFg1XvH8IYw0/nbmPNnosordYm2iOCXDE2zB2hHjIEuNnj79+n4Zf0XIwNU2Lj1AieW0yI6dXWa7Do+zT8ciEXHAcseCoQrz4ZAIno4cYNbhdXYejaIxBwQNrqkXC0Mf1lx45+fpvnjjldkEQkwPIxwRjWywWLvz+P63crMHHjCSwbFYRXHvdv9YPqcq72OnywO88T/kibBAIOE/p6YkJfy6nkaUgcx+G5iB4YFuiC9/Zdxs/n7yAh8y4SMvWvj4sEHF5+3DjF+wgxd2KhAJ/G9IWTnRj/PpWD9fFZ2HvhDl4a6oeRvRVwc+zcvMDGCbF9vOS8JCKdQSMjZujPCjWW77iAXy9qrxsO8nPGyrGPoa+X/IFzB713GAVlNdgxbwj6ezuZuKWEPJzsexXYce4WkrOLcCm3FGXVdZCKBHhnQij+1rDRGyFd2e6021iz5xIKK5r2A5PbieHTvRtc7aWQ24nhZCeGUmaLME8ZQjwc0U2qP76wKC4Vu9LuYMFTAVgykp/NHjv6+U3JiJlijOG75JtYs/ciqmu1E/5G9lbg5cf9MMjPGRzHoaCsGoPeiwfHARlvjXrghUiIJWCMobiyFhKRgF7DhNyntLoWP5y5id1pd5BxpwRtfVoLBRz6e8sxvJcrhvdyg3d3O0R9lIB75WrEzR7M26RwSkasxM2iSqw7nIUdqbd0L8QghQP+Y0APHLyYj+QbRQjxcMQvrz3Bb0MJIYQYTaW6Dn8UVuKPwkoUVajxZ6UaxZVq3CisRMbtEuSW6JeGEAk41GkY3Byk+O0fT/K2YSIlI1bmSn4ZtpzIxq7UO6iq1d/vhM+slxBCCP9uF1chMfMuEq8U4MTVQpTX1EFuJ8a3r6gQ4tH2Qghj6ujn90NN0d2wYQN8fX1hY2MDlUqF5OTkNs/fvn07goODYWNjg7CwMOzbt+9hnrZL66VwQOykcJxaGYV3JoRgSM/u6N5NgjnDe1IiQgghXZyn3BbPq7zxxQsDkLrqafw0dwgOLBzGayLSGZ0eGfn+++/x4osvYvPmzVCpVFi3bh22b9+OzMxMuLk9WLDp5MmTGDZsGGJjY/GXv/wF27Ztw/vvv49z584hNLRjS1FpZIQQQgixPEa7TKNSqTBw4EB8/vnnAACNRgMvLy8sWLAAy5cvf+D8mJgYVFRUYO/evbrbBg8ejL59+2Lz5s0GDaYzGGOoqnuETeoIIYQQK2IrsjV48Uyj1BlRq9VISUnBihUrdLcJBAJER0cjKSmpxfskJSVh8eLFereNGjUKu3btavV5ampqUFNTo/t3aWlpZ5rZIVV1VVBtUxn8cQkhhBBLdPr507AT2/Hy3J2aM3Lv3j3U19dDoVDo3a5QKJCX13Lp2ry8vE6dDwCxsbGQyWS6Hy8vqjtACCGEWCuzXNS/YsUKvdGU0tJSgycktiJbnH7+tEEfkxBCCLFUtiL+9sbqVDLi4uICoVCI/Hz9HQXz8/OhVCpbvI9SqezU+QAglUohlUo707RO4ziOt+EoQgghhDTp1GUaiUSCiIgIxMfH627TaDSIj49HZGRki/eJjIzUOx8ADh061Or5hBBCCOlaOn2ZZvHixZg+fToGDBiAQYMGYd26daioqMDMmTMBAC+++CI8PT0RGxsLAFi4cCGGDx+Ojz76COPGjUNcXBzOnj2LL7/80rCREEIIIcQidToZiYmJwd27d7Fq1Srk5eWhb9++OHDggG6Sak5ODgSCpgGXIUOGYNu2bXjjjTewcuVKBAYGYteuXR2uMUIIIYQQ60bl4AkhhBBiFEYtB08IIYQQYiiUjBBCCCGEV5SMEEIIIYRXlIwQQgghhFeUjBBCCCGEV5SMEEIIIYRXlIwQQgghhFeUjBBCCCGEV5SMEEIIIYRXnS4Hz4fGIrGlpaU8t4QQQgghHdX4ud1esXeLSEbKysoAAF5eXjy3hBBCCCGdVVZWBplM1upxi9ibRqPR4M6dO3BwcADHcQZ73NLSUnh5eeHmzZtWu+eNtcdo7fEB1h+jtccHWH+M1h4fYP0xGis+xhjKysrg4eGht4lucxYxMiIQCNCjRw+jPb6jo6NVvrjuZ+0xWnt8gPXHaO3xAdYfo7XHB1h/jMaIr60RkUY0gZUQQgghvKJkhBBCCCG86tLJiFQqxerVqyGVSvluitFYe4zWHh9g/TFae3yA9cdo7fEB1h8j3/FZxARWQgghhFivLj0yQgghhBD+UTJCCCGEEF5RMkIIIYQQXlEyQgghhBBedelkZMOGDfD19YWNjQ1UKhWSk5P5btJDeeutt8BxnN5PcHCw7nh1dTXmz5+P7t27w97eHn/961+Rn5/PY4vbd+zYMTzzzDPw8PAAx3HYtWuX3nHGGFatWgV3d3fY2toiOjoaWVlZeucUFRVh6tSpcHR0hFwux8svv4zy8nITRtG69uKbMWPGA306evRovXPMOb7Y2FgMHDgQDg4OcHNzw7PPPovMzEy9czryuszJycG4ceNgZ2cHNzc3LFu2DHV1daYMpVUdiXHEiBEP9OOcOXP0zjHXGDdt2oTw8HBdEazIyEjs379fd9zS+w9oP0ZL7r+WrF27FhzHYdGiRbrbzKYfWRcVFxfHJBIJ+/rrr9nFixfZrFmzmFwuZ/n5+Xw3rdNWr17NQkJCWG5uru7n7t27uuNz5sxhXl5eLD4+np09e5YNHjyYDRkyhMcWt2/fvn3s9ddfZzt27GAA2M6dO/WOr127lslkMrZr1y52/vx5Nn78eObn58eqqqp054wePZr16dOHnTp1iv32228sICCATZkyxcSRtKy9+KZPn85Gjx6t16dFRUV655hzfKNGjWJbtmxhGRkZLC0tjY0dO5Z5e3uz8vJy3TntvS7r6upYaGgoi46OZqmpqWzfvn3MxcWFrVixgo+QHtCRGIcPH85mzZql148lJSW64+Yc488//8x++eUXduXKFZaZmclWrlzJxGIxy8jIYIxZfv8x1n6Mltx/zSUnJzNfX18WHh7OFi5cqLvdXPqxyyYjgwYNYvPnz9f9u76+nnl4eLDY2FgeW/VwVq9ezfr06dPiseLiYiYWi9n27dt1t12+fJkBYElJSSZq4aNp/mGt0WiYUqlkH374oe624uJiJpVK2XfffccYY+zSpUsMADtz5ozunP379zOO49jt27dN1vaOaC0ZmTBhQqv3saT4GGOsoKCAAWCJiYmMsY69Lvft28cEAgHLy8vTnbNp0ybm6OjIampqTBtABzSPkTHth9n9b/zNWVqMTk5O7KuvvrLK/mvUGCNj1tN/ZWVlLDAwkB06dEgvJnPqxy55mUatViMlJQXR0dG62wQCAaKjo5GUlMRjyx5eVlYWPDw84O/vj6lTpyInJwcAkJKSgtraWr1Yg4OD4e3tbbGxZmdnIy8vTy8mmUwGlUqliykpKQlyuRwDBgzQnRMdHQ2BQIDTp0+bvM0PIyEhAW5ubggKCsLcuXNRWFioO2Zp8ZWUlAAAnJ2dAXTsdZmUlISwsDAoFArdOaNGjUJpaSkuXrxowtZ3TPMYG3377bdwcXFBaGgoVqxYgcrKSt0xS4mxvr4ecXFxqKioQGRkpFX2X/MYG1lD/82fPx/jxo3T6y/AvP4OLWKjPEO7d+8e6uvr9f7nAoBCocDvv//OU6senkqlwtatWxEUFITc3Fy8/fbbeOKJJ5CRkYG8vDxIJBLI5XK9+ygUCuTl5fHT4EfU2O6W+q/xWF5eHtzc3PSOi0QiODs7W0Tco0ePxqRJk+Dn54dr165h5cqVGDNmDJKSkiAUCi0qPo1Gg0WLFmHo0KEIDQ0FgA69LvPy8lrs48Zj5qSlGAHg+eefh4+PDzw8PHDhwgX84x//QGZmJnbs2AHA/GNMT09HZGQkqqurYW9vj507d6J3795IS0uzmv5rLUbA8vsPAOLi4nDu3DmcOXPmgWPm9HfYJZMRazNmzBjd7+Hh4VCpVPDx8cEPP/wAW1tbHltGHtbkyZN1v4eFhSE8PBw9e/ZEQkICoqKieGxZ582fPx8ZGRk4fvw4300xmtZinD17tu73sLAwuLu7IyoqCteuXUPPnj1N3cxOCwoKQlpaGkpKSvDjjz9i+vTpSExM5LtZBtVajL1797b4/rt58yYWLlyIQ4cOwcbGhu/mtKlLXqZxcXGBUCh8YMZwfn4+lEolT60yHLlcjl69euHq1atQKpVQq9UoLi7WO8eSY21sd1v9p1QqUVBQoHe8rq4ORUVFFhm3v78/XFxccPXqVQCWE9+rr76KvXv34ujRo+jRo4fu9o68LpVKZYt93HjMXLQWY0tUKhUA6PWjOccokUgQEBCAiIgIxMbGok+fPvj000+tqv9ai7ElltZ/KSkpKCgoQP/+/SESiSASiZCYmIj169dDJBJBoVCYTT92yWREIpEgIiIC8fHxuts0Gg3i4+P1rhVaqvLycly7dg3u7u6IiIiAWCzWizUzMxM5OTkWG6ufnx+USqVeTKWlpTh9+rQupsjISBQXFyMlJUV3zpEjR6DRaHRvKJbk1q1bKCwshLu7OwDzj48xhldffRU7d+7EkSNH4Ofnp3e8I6/LyMhIpKen6yVdhw4dgqOjo24YnU/txdiStLQ0ANDrR3OOsTmNRoOamhqr6L/WNMbYEkvrv6ioKKSnpyMtLU33M2DAAEydOlX3u9n0o8GmwlqYuLg4JpVK2datW9mlS5fY7NmzmVwu15sxbCmWLFnCEhISWHZ2Njtx4gSLjo5mLi4urKCggDGmXbrl7e3Njhw5ws6ePcsiIyNZZGQkz61uW1lZGUtNTWWpqakMAPv4449Zamoq++OPPxhj2qW9crmc7d69m124cIFNmDChxaW9/fr1Y6dPn2bHjx9ngYGBZrP0ta34ysrK2NKlS1lSUhLLzs5mhw8fZv3792eBgYGsurpa9xjmHN/cuXOZTCZjCQkJessiKysrdee097psXFI4cuRIlpaWxg4cOMBcXV3NZtlkezFevXqVrVmzhp09e5ZlZ2ez3bt3M39/fzZs2DDdY5hzjMuXL2eJiYksOzubXbhwgS1fvpxxHMcOHjzIGLP8/mOs7Rgtvf9a03yFkLn0Y5dNRhhj7LPPPmPe3t5MIpGwQYMGsVOnTvHdpIcSExPD3N3dmUQiYZ6eniwmJoZdvXpVd7yqqorNmzePOTk5MTs7OzZx4kSWm5vLY4vbd/ToUQbggZ/p06czxrTLe998802mUCiYVCplUVFRLDMzU+8xCgsL2ZQpU5i9vT1zdHRkM2fOZGVlZTxE86C24qusrGQjR45krq6uTCwWMx8fHzZr1qwHEmVzjq+l2ACwLVu26M7pyOvyxo0bbMyYMczW1pa5uLiwJUuWsNraWhNH07L2YszJyWHDhg1jzs7OTCqVsoCAALZs2TK9OhWMmW+ML730EvPx8WESiYS5urqyqKgoXSLCmOX3H2Ntx2jp/dea5smIufQjxxhjhhtnIYQQQgjpnC45Z4QQQggh5oOSEUIIIYTwipIRQgghhPCKkhFCCCGE8IqSEUIIIYTwipIRQgghhPCKkhFCCCGE8IqSEUIIIYTwipIRQghvRowYgUWLFvHdDEIIzygZIYQQQgivqBw8IYQXM2bMwDfffKN3W3Z2Nnx9fflpECGEN5SMEEJ4UVJSgjFjxiA0NBRr1qwBALi6ukIoFPLcMkKIqYn4bgAhpGuSyWSQSCSws7ODUqnkuzmEEB7RnBFCCCGE8IqSEUIIIYTwipIRQghvJBIJ6uvr+W4GIYRnlIwQQnjj6+uL06dP48aNG7h37x40Gg3fTSKE8ICSEUIIb5YuXQqhUIjevXvD1dUVOTk5fDeJEMIDWtpLCCGEEF7RyAghhBBCeEXJCCGEEEJ4RckIIYQQQnhFyQghhBBCeEXJCCGEEEJ4RckIIYQQQnhFyQghhBBCeEXJCCGEEEJ4RckIIYQQQnhFyQghhBBCeEXJCCGEEEJ4RckIIYQQQnj1/yMIsM86k8YlAAAAAElFTkSuQmCC", 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", 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", 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" ] @@ -650,16 +640,14 @@ { "cell_type": "markdown", "id": "adef1b12-54ca-4326-add1-b6bc7faae812", - "metadata": { - "jp-MarkdownHeadingCollapsed": true - }, + "metadata": {}, "source": [ "## UM3" ] }, { "cell_type": "code", - "execution_count": 119, + "execution_count": 13, "id": "3dc5578c-add3-4633-a9de-698c7de93f5d", "metadata": {}, "outputs": [], @@ -698,23 +686,23 @@ }, { "cell_type": "code", - "execution_count": 120, + "execution_count": 14, "id": "b78b6332-0234-4c77-bae6-e5cd9ebd37ef", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 120, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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", + "image/png": 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AWLRoEXQ6HXbv3o2goCBkZmYiODgYAPD3v/8dmZmZ2Lx5M6Kjo3HhwgU0NjY281skCILomlyuUuP2Tw8CADZmFOJftw1r4xa1Hu1aWDTqjRjw0q9t8tmZr81AoML7rycpKQn//Oc/wXEc0tLScPLkSfzzn/90EBbbt2/HyZMnkZOTg6SkJADA//73PwwcOBCHDx/GqFGjADAB8tlnnyEkJAQDBgzAVVddhaysLGzatAkSiQRpaWl46623sGPHDlFYWAeQJicn4/XXX8fDDz8sCou8vDzMnTsXgwcPBgD06tVL3D8vLw/Dhg3DyJEjxfcTBEEQTWPXuTKb5xq9ESp51yi2R64QPzF27FgbC8e4ceNw/vx5seiXwJkzZ5CUlCSKCgAYMGAAwsPDcebMGXFbcnIyQkJCxOdxcXEYMGCATZnzuLg4sfQ0AGzbtg1Tp05Ft27dEBISgjvvvBMVFRVQq9UAgCeeeAKvv/46JkyYgJdffhknTpwQ3/vII49g3bp1GDp0KJ577jns27fPD98KQRBE16SqwXYhzcLqrmMBbtcWiwC5FJmvzWizz25L5HK5zXOO45xuExZry83NxXXXXYdHHnkEb7zxBiIjI7F3717cf//90Ol0CAwMxAMPPIAZM2bgl19+wW+//YYlS5bgvffew+OPP45Zs2bh0qVL2LRpE7Zu3YqpU6di0aJFePfdd1vtnAmCIDoLlQ22VXsLqhvRKya4jVrTurRriwXHcQhUyNrkz9cI3oMHD9o8P3DgAPr27euwzkT//v2Rn5+P/Px8cVtmZiaqq6sxYMCAJn9XR48ehclkwnvvvYexY8ciNTUVhYWFDvslJSXh4YcfxoYNG/CXv/wFn376qfhaTEwM7r77bnz55Zd4//338cknnzS5PQRBEF2ZKjVZLIhmkpeXh6effhoPPfQQjh07hg8++ADvvfeew37Tpk3D4MGDsWDBArz//vswGAx49NFHceWVV4rxDU2hT58+0Ov1+OCDDzB79mz88ccf+Pjjj232Wbx4MWbNmoXU1FRUVVVhx44d6N+/PwDgpZdewogRIzBw4EBotVr8/PPP4msEQRCEb1SaXSEKqQQ6owkF1Zo2blHr0a4tFh2Ju+66C42NjRg9ejQWLVqEJ598Eg8++KDDfhzHYePGjYiIiMCkSZMwbdo09OrVC+vXr2/W5w8ZMgTLli3DW2+9hUGDBmHNmjVYsmSJzT5GoxGLFi1C//79MXPmTKSmpoqBnQqFAi+88ALS09MxadIkSKVSrFu3rlltIgiC6KpUmy0WA7uFAgAKqrqOxYLjhWILrURtbS3CwsJQU1OD0NBQm9c0Gg1ycnKQkpIClUrVms0iCBvoWiQIojlMfPt35Fc24s6xPfHFgUsY1ysKXz04tq2b1Szcjd/WkMWCIAiCIPxMlTl4c3C3MABAYU3XsViQsCAIgiAIP6IzmFCvNQAA+iewmX1xDcVYEARBEATRBIT4CgkHRAUrAABGU6tGHbQpJCwIgiAIwo9UmoVFRKACMgkrXWBq3XDGNoWEBUEQBEH4ESHVNCJIIdZEMvFAK+dKtBkkLAiCIAjCjwiBm5GBCkisai12EV1BwoIgCIIg/IlQdTMiSA6plbLoKu4QEhYEQRAE4UeEBcgiAhU2y0MYSVg48sorr4DjOJu/fv36tVTbCIIgCKLD0aBjq1oHK2Vd0hXi81ohAwcOxLZt2ywHkNFyIwRBEAQhoNEzYaGSS8kV4g0ymQzx8fHiX3R0dEu0i2hncByHH374oa2bQRAE0e4RhEWAQgqJtSuki9Sy8FlYnD9/HomJiejVqxcWLFiAvLy8lmgXQRAEQXRIGs3CQimTwEpXoIvoCt+ExZgxY7Bq1Sps2bIFK1asQE5ODiZOnIi6ujqX79FqtaitrbX562xMnjwZjz/+OBYvXoyIiAjExcXh008/RUNDA+69916EhISgT58+2Lx5s/ieU6dOYdasWQgODkZcXBzuvPNOlJeXi69v2bIFV1xxBcLDwxEVFYXrrrsO2dnZ4uu5ubngOA4bNmzAVVddhcDAQAwZMgT79+/32F6e5xETE4Nvv/1W3DZ06FAkJCSIz/fu3QulUgm1Wo3k5GQAwI033giO48TnBEEQhCONOovFQmqlLKiOhRNmzZqFW265Benp6ZgxYwY2bdqE6upqfP311y7fs2TJEoSFhYl/SUlJ3n8gzwO6hrb58/ECWL16NaKjo3Ho0CE8/vjjeOSRR3DLLbdg/PjxOHbsGK6++mrceeedUKvVqK6uxpQpUzBs2DAcOXIEW7ZsQUlJCebNmycer6GhAU8//TSOHDmC7du3QyKR4MYbb4TJZLL53BdffBHPPPMMMjIykJqaivnz58NgMLhtK8dxmDRpEnbu3AkAqKqqwpkzZ9DY2IizZ88CAHbt2oVRo0YhMDAQhw8fBgB8/vnnKCoqEp8TBEEQjmgMrJ8OkNu6QrqKxaJZkZfh4eFITU3FhQsXXO7zwgsv4Omnnxaf19bWei8u9GrgzcTmNLHp/K0QUAR5vfuQIUPwf//3fwDYOS9duhTR0dFYuHAhAOCll17CihUrcOLECWzbtg3Dhg3Dm2++Kb7/s88+Q1JSEs6dO4fU1FTMnTvX5vifffYZYmJikJmZiUGDBonbn3nmGVx77bUAgFdffRUDBw7EhQsXPGbrTJ48GStXrgQA7N69G8OGDUN8fDx27tyJfv36YefOnbjyyisBADExMQDY7x0fH+/1d0IQBNEV0egswZvWrhCKsfCC+vp6ZGdn25jQ7VEqlQgNDbX564ykp6eLj6VSKaKiojB48GBxW1xcHACgtLQUf/75J3bs2IHg4GDxTxACgrvj/PnzmD9/Pnr16oXQ0FDR/WAf02L9ucLvUFpa6rG9V155JTIzM1FWVoZdu3Zh8uTJmDx5Mnbu3Am9Xo99+/Zh8uTJvn8RBEEQXRwhxiJALgXHcWLKaVdxhfhksXjmmWcwe/Zs9OzZE4WFhXj55ZchlUoxf/78lmmdPJBZDtoCeaBvu8vlNs85jrPZJtaLN5lQX1+P2bNn46233nI4jiAOhO/5008/RWJiIkwmEwYNGgSdTufyc60/wxODBw9GZGQkdu3ahV27duGNN95AfHw83nrrLRw+fBh6vR7jx4/38uwJgiAIASErRClnc3cJx8HE8+QKccbly5cxf/58VFRUICYmBldccQUOHDggmsr9Dsf55I7oKAwfPhzfffcdkpOTndYBqaioQFZWFj799FNMnDgRAAum9Cccx2HixInYuHEjTp8+jSuuuAKBgYHQarVYuXIlRo4ciaAgy3cvl8thNBr92gaCIIjOiLXFAoA5zoKnypvOWLduHQoLC6HVanH58mWsW7cOvXv3bqm2dVoWLVqEyspKzJ8/H4cPH0Z2djZ+/fVX3HvvvTAajYiIiEBUVBQ++eQTXLhwAb///rtNnIq/mDx5Mr766isMHToUwcHBkEgkmDRpEtasWSPGVwgkJydj+/btKC4uRlVVld/bQhAE0VnQ6M3BmwqzsDCPtKYuYrKgtULagMTERPzxxx8wGo24+uqrMXjwYCxevBjh4eGQSCSQSCRYt24djh49ikGDBuGpp57CO++84/d2XHnllTAajTaxFJMnT3bYBgDvvfcetm7diqSkJAwbNszvbSEIgugsiJU3ZdYWi65T0pvjWzmapLa2FmFhYaipqXEI5NRoNMjJyUFKSgpUKlVrNosgbKBrkSCIptL7b5tgNPE4+LepiAtVYdDLv6Jea8COZyYjJbrjuvfdjd/WkMWCIAiCIPyE3mgS00pVYowFe43WCiE6NEJVT2d/1vUzCIIgCP8hBG4CgErICpEIrpCuISxoadJOyn/+8x80NjY6fS0yMrKVW0MQBNE1EIpjSThAIbWkmwKA0XMlgE4BCYtOSrdu3dq6CQRBEF0OISNEZS6OBViEBblCCIIgCILwCfsaFgDFWBAEQRAE0UTEVFMbYSFURW6TJrU6JCwIgiAIwk80isLCMrxKJeQKIQiCIAiiCYiuEIXFYsGRK4QgCIIgiKagtau6CVgHb7ZJk1odEhZ+gOd5PPjgg4iMjATHcQgPD8fixYu9eu/kyZM97stxHH744Ydmt9NbXnnlFQwdOrTVPq85tPZ3QxAE4Q5nFouu5gqhdFM/sGXLFqxatQo7d+5Er169IJFIEBAQ4LfjFxUVISIiwm/H88QzzzyDxx9/3Kf3JCcnY/HixV4LKn9h/d3k5uYiJSUFx48f7zDCiCCIzkWjzpJuKiC6QrqIyYKEhR/Izs5GQkICxo8f3yLHj4+Pb5HjukKo0NkRaO3vhiAIwh1us0K6hq4gV0hzueeee/D4448jLy8PHMchOTnZwb3x0UcfoW/fvlCpVIiLi8PNN99scwyTyYTnnnsOkZGRiI+PxyuvvGLzurW5Pzc3FxzHYcOGDbjqqqsQGBiIIUOGYP/+/Tbv+fTTT5GUlITAwEDceOONWLZsGcLDw706J3tXyD333IMbbrgB7777LhISEhAVFYVFixZBr9cDYO6cS5cu4amnngLHcWJRGADYu3cvJk6ciICAACQlJeGJJ55AQ0OD+HpycjLefPNN3HfffQgJCUGPHj3wySefiK/rdDo89thjSEhIgEqlQs+ePbFkyRKn301KSgoAYNiwYeA4DpMnT8bu3bshl8tRXFxsc46LFy/GxIkTvfo+CIIgvMVSx8IqK4QKZLUfeJ6HWq9ukz9va7r/61//wmuvvYbu3bujqKgIhw8ftnn9yJEjeOKJJ/Daa68hKysLW7ZswaRJk2z2Wb16NYKCgnDw4EG8/fbbeO2117B161a3n/viiy/imWeeQUZGBlJTUzF//nwYDAYAwB9//IGHH34YTz75JDIyMjB9+nS88cYbPnzzjuzYsQPZ2dnYsWMHVq9ejVWrVmHVqlUAgA0bNqB79+547bXXUFRUhKKiIgDMkjNz5kzMnTsXJ06cwPr167F371489thjNsd+7733MHLkSBw/fhyPPvooHnnkEWRlZQEAli9fjh9//BFff/01srKysGbNGiQnJztt46FDhwAA27ZtQ1FRETZs2IBJkyahV69e+OKLL8T99Ho91qxZg/vuu69Z3wlBEIQ9GicFsrpaVki7doU0GhoxZu2YNvnsg7cfRKA80ON+YWFhCAkJgVQqdWqWz8vLQ1BQEK677jqEhISgZ8+eGDZsmM0+6enpePnllwEAffv2xb///W9s374d06dPd/m5zzzzDK699loAwKuvvoqBAwfiwoUL6NevHz744APMmjULzzzzDAAgNTUV+/btw88//+z1+dsTERGBf//735BKpejXrx+uvfZabN++HQsXLkRkZCSkUilCQkJsvoMlS5ZgwYIFovWmb9++WL58Oa688kqsWLFCXI78mmuuwaOPPgoAeP755/HPf/4TO3bsQFpaGvLy8tC3b19cccUV4DgOPXv2dNnGmJgYAEBUVJRNO+6//358/vnnePbZZwEAP/30EzQaDebNm9fk74MgCMIZ5App5xaLzsD06dPRs2dP9OrVC3feeSfWrFkDtVpts096errN84SEBJSWlro9rvV7EhISAEB8T1ZWFkaPHm2zv/1zXxk4cCCkUsuN4k0b//zzT6xatcpmZdUZM2bAZDIhJyfH6blwHIf4+Hjx2Pfccw8yMjKQlpaGJ554Ar/99pvPbb/nnntw4cIFHDhwAACwatUqzJs3D0FBQT4fiyAIwh2NzoSFeaSl4M12QIAsAAdvP9hmn+0PQkJCcOzYMezcuRO//fYbXnrpJbzyyis4fPiwGPMgl8tt3sNxHEwear9av4cTy8W2XL3YprSxvr4eDz30EJ544gmH13r06OHVsYcPH46cnBxs3rwZ27Ztw7x58zBt2jR8++23Xrc9NjYWs2fPxueff46UlBRs3rwZO3fu9Pr9BEEQ3mK9CJlAV4uxaNfCguM4r9wR7R2ZTIZp06Zh2rRpePnllxEeHo7ff/8dN910U4t8XlpamkOsh/1zf6NQKGA0Gm22DR8+HJmZmejTp0+zjh0aGopbb70Vt956K26++WbMnDkTlZWVDsu/KxQKAHBoBwA88MADmD9/Prp3747evXtjwoQJzWoTQRCEM7QGJiyUMotDgOtirpB2LSw6Az///DMuXryISZMmISIiAps2bYLJZEJaWlqLfebjjz+OSZMmYdmyZZg9ezZ+//13bN682SZbw98kJydj9+7duO2226BUKhEdHY3nn38eY8eOxWOPPYYHHngAQUFByMzMxNatW/Hvf//bq+MuW7YMCQkJGDZsGCQSCb755hvEx8c7zXCJjY1FQEAAtmzZgu7du0OlUiEsLAwAMGPGDISGhuL111/Ha6+95s9TJwiCENGbhYXCSlgIq5sau4iyoBiLFiY8PBwbNmzAlClT0L9/f3z88cf46quvMHDgwBb7zAkTJuDjjz/GsmXLMGTIEGzZsgVPPfWUGCzZErz22mvIzc1F7969xSDK9PR07Nq1C+fOncPEiRMxbNgwvPTSS0hMTPT6uCEhIXj77bcxcuRIjBo1Crm5udi0aRMkEsdLVyaTYfny5Vi5ciUSExMxZ84c8TWJRIJ77rkHRqMRd911V/NPmCAIwgk6o1lYSB0XIfM227Cjw/GtfKa1tbUICwtDTU0NQkNDbV7TaDTIyclBSkpKiw6CXZGFCxfi7Nmz2LNnT1s3pc24//77UVZWhh9//NHjvnQtEgTRFO7870HsOV+Of946BDcO6w4AmLdyPw7lVOLD24fj2vSENm5h03E3fltDrpBOyrvvvovp06cjKCgImzdvxurVq/HRRx+1dbPahJqaGpw8eRJr1671SlQQBEE0FSHGQiG1Tjdl/41dxGJBwqKTcujQIbz99tuoq6tDr169sHz5cjzwwAMAWOropUuXnL5v5cqVWLBgQWs2tcWZM2cODh06hIcffthtbRCCIIjmoje7QuRSS0xbV3OFkLDopHz99dcuX9u0aZNYjtueuLi4lmpSm0GppQRBtBY6p8GblG5KdHLcVa8kCIIgmo7eSfCmpdZQmzSp1aGsEIIgCILwE84sFtIuFmPRLoVFV/FDEe2XlqxiShBE50VvZOOXXOroCukqY1u7coXI5XJwHIeysjLExMS0aEEngnAGz/PQ6XQoKyuDRCIRq3kSBEF4g9aJxYIqb7YhUqkU3bt3x+XLl5Gbm9vWzSG6MIGBgejRo4fTQlwEQRCusGSFWBfIYv+7SuXNdiUsACA4OBh9+/Z1mbVAEC2NVCqFTCYjixlBED4jCAulk6wQcoW0IVKp1GaJboIgCILoCAjBm85iLLqIwaJ9Bm8SBEEQREfDZOJhMKsHmzoW5gJZXcUVQsKCIAiCIPyAsAAZYFt5Uyjp3VUKZJGwIAiCIAg/oLcRFs5iLFq9SW0CCQuCIAiC8ANCfAVgW3lTEBZUIIsgCIIgCK8RimPJJJwYVwGQK4QgCIIgiCbgrJw3QK4QgiAIgiCagM5JcSyAskIIgiAIgmgCri0W7D+5QgiCIAiC8BpnS6YDVCCLIAiCIIgmILhC7C0WUknXKulNwoIgCIIg/IBeLOdtu86QsOwQxVgQBEEQBOE1riwW5AohCIIgCMJnnC1ABliCN8kVQhAEQRCE1wgFshyCNyndlCAIgiAIX9EZjQDIFULCgiAIgiD8gN7AlIMrVwjVsSAIgiAIwmu0LupYSEWLBQkLgiAIgiC8REw3tXOFcCQsCIIgCILwFR1V3gTQTGGxdOlScByHxYsX+6k5BEEQBNEx0YtrhdgWyBJ0hqmLKIsmC4vDhw9j5cqVSE9P92d7CIIgCKJD4spiQa4QL6ivr8eCBQvw6aefIiIiwt9tIgiCIIgOh8tl08kV4plFixbh2muvxbRp0/zdHoIgCILokAjppo6LkLH/XcUVIvP1DevWrcOxY8dw+PBhr/bXarXQarXi89raWl8/kiAIgiDaPUKBLNcWi64hLHyyWOTn5+PJJ5/EmjVroFKpvHrPkiVLEBYWJv4lJSU1qaEEQRAE0Z5xZbHgyBXimqNHj6K0tBTDhw+HTCaDTCbDrl27sHz5cshkMhjNas2aF154ATU1NeJffn6+3xpPEARBEO0FV8Gb0i5WedMnV8jUqVNx8uRJm2333nsv+vXrh+effx5SqdThPUqlEkqlsnmtJAiCIIh2jiV40zbdVFiEjISFE0JCQjBo0CCbbUFBQYiKinLYThAEQRBdCZ1Yx8J2ki26Qkyt3qQ2gSpvEgRBEIQf0LuwWHS1tUJ8zgqxZ+fOnX5oBkEQBEF0bCwWC1rdlCAIgiCIZqKntUIAkLAgCIIgCL+gMzLl4FDHoosFb5KwIAiCIAg/YDBbLGT2WSHmp8YuYrIgYUEQBEEQfsDgymJhdoV0EYMFCQuCIAiC8Ad6V4uQkSuEIAiCIAhf0ZvIFQKQsCAIgiAIvyC6QiTkCiEIgiAIopmIrhCZvcWCXCEEQRAEQfiI3myxkDlYLNh/IwkLgiAIgiC8xeBqETIqkEUQBEEQhK/oXaSbSiVCjEXXUBYkLAiCIAjCD7jKCuForRCCIAiCIHzBaOLFrA9XWSFGWjadIAiCIAhv0FupBrnD6qbkCiEIgiAIwgeshYVMYhe8aR5pyRVCEARBEIRXCMWxANdrhVDlTYIgCIIgvEKwWEg4SxaIAFXeJAiCIAjCJ/Rma4RM6jisSskVQhAEQRCEL4jFseysFQDACa4QEhYEQRAEQXiDZZ0Qx2FVrLxJ6aYEQRAEQXiDq3VCAEBK6aYEQRAEQfiCuGS61JkrhP0nVwhBEARBEF6hExcgc+MK6Rq6goQFQRAEQTQXIXjTfp0QgBYhIwiCIAjCRwxmc4T9OiEAq20BUIEsgiAIgiC8RHSFyFynm3YRXUHCgiAIgiCai8FdVohEEBZdQ1mQsCAIgiCIZiIWyHISYyG4QkxdxGRBwoIgCIIgmgllhVggYUEQBEEQzUR0hTgTFuQKIQiCIAjCFwwm12uFCJu6iK4gYUEQBEEQzUUnVt507QqhypsEQRAEQXiFuwJZlhgLEhYEQRAEQXiBwa3Fgv3n+a5RfZOEBUEQBEE0E53bdFPLtq6QGULCgiAIgiCaiTdZIUDXcIeQsCAIgiCIZuJNVghAwoIgCIIgCC/wpkAWAJj1R6eGhAVBEARBNBN3rhApuUIIgiAIgvAFd2uFcOQKIQiCIAjCF7wpkAWQK4QgCIIgCC/wpkAWQBYLgiAIgiC8wGAuUCGXuC6QBZCwIAiCIAjCC9wVyOI4Toyz6ArrhZCwIAiCIIhmYnGFOB9WpcJ6IRRjQRAEQRCEJyxrhThaLABLyqmhCygLEhYEQRAE0UzcFcgCAJlZWBi7wGIhJCwIgiAIopm4K5Blvd1AwoIgCIIgCE+4WysEsFgsBAHSmSFhQRAEQRDNxF2BLMBS34JiLAiCIAiC8Ii7AlkAIDPXtyCLBUEQBEEQHjF4bbEgYUEQBEEQhAf0HrJCxHRTI7lCbFixYgXS09MRGhqK0NBQjBs3Dps3b26pthEEQRBEh0Bv8uQKoXRTp3Tv3h1Lly7F0aNHceTIEUyZMgVz5szB6dOnW6p9BEEQBNHuEV0hTtYKASwxFvouICxkvuw8e/Zsm+dvvPEGVqxYgQMHDmDgwIF+bRhBEARBdBREV4jMhcVCKlgsOr8rxCdhYY3RaMQ333yDhoYGjBs3zuV+Wq0WWq1WfF5bW9vUjyQIgiCIdoleKJDl0mJBdSxccvLkSQQHB0OpVOLhhx/G999/jwEDBrjcf8mSJQgLCxP/kpKSmtVggiAIgmhvGNysbgpYpZt2AVeIz8IiLS0NGRkZOHjwIB555BHcfffdyMzMdLn/Cy+8gJqaGvEvPz+/WQ0mCIIgiPaGntJNRXx2hSgUCvTp0wcAMGLECBw+fBj/+te/sHLlSqf7K5VKKJXK5rWSIAiCINoxnrJCKN3UB0wmk00MBUEQBEF0JYwmHrzZEOEqK0TehRYh88li8cILL2DWrFno0aMH6urqsHbtWuzcuRO//vprS7WPIAiCINo1eisrhFzmqUAWCQsbSktLcdddd6GoqAhhYWFIT0/Hr7/+iunTp7dU+wiCIAiiXWMtLGQeVjeldFM7/vvf/7ZUOwiCIAiiQ2JthXAdvGkukNUFLBa0VghBEARBNAPBYiHhLC4Pe6ikN0EQBEEQXiGU6Za5sFYAVgWySFgQBEEQBOEOsTiWC2sFYFXHgtJNCYIgCIJwh2WdEHcWi66TbkrCgiAIgiCagad1QgCrdNMukBVCwoIgCIIgmoG4ZLqLqpvWr5HFgiAIgiAIt+jEBcjcWSzMrhBKNyUIgiAIwh1CQKardUIAi8WC0k0JgiAIgnCL4N5wtU4IYImx0FNWCEEQBEEQ7hBdITI36aZUIIsgCIIgCG8weJEVIutCq5uSsCAIgiCIZiAWyHITYyFW3iRXCEEQBEEQ7vAmK4RKehMEQRAE4RWiK8RduqmU0k0JgiAIgvACoZqmu7VC5GSxIAiCIAjCG3Ri5U0q6Q2QsCAIgiCIZuFdgSw23FK6KUEQBEEQbjH4YLGgAlkEQRAEQbhF50O6KVksCIIgCIJwizdZIVQgiyAIgiAIr/AmK8RSIIuEBUEQBEEQbvCqQJaU0k0JgiAIgvACrwpkUUlvgiAIgiC8wZu1QijdlCAIgiAIr/ClQJaeCmQRBEEQBOEOrwpkmZdUN1LwJkEQBEEQ7hACMgXx4AyLxYKEBUEQBEEQbvCqQJaUCmQRBEEQBOEFFleIm3RTygohCIIgCMIbLGuFuCuQRZU3CYIgCILwAiqQZQsJC4IgCIJoBl6tFUKuEIIgCIIgvMGrtULMosPEA6ZObrUgYUEQBEEQzcCXAllA53eHkLAgCIIgiGbgVYEsq9c6e8opCQuCIAiCaAYGHy0Wnb2sNwkLgiAIgmgGem+yQqyqcnb2st4kLAiCIAiiGQgWCHeuEKmEA8fZ7t9ZIWFBEARBEM1AdIW4WSsEsKScUowFQRAEQRAuEV0hMtcWC8Cq+ia5QgiCIAiCcIVeKJDlpcWC0k0JgiAIgnCJwYvVTQHrFU4pxoIgCIIgCBfovUg3BQCp2aKhJ1cIQRAEQRCu8CYrBLBYNCh4kyAIgiAIpxhNPHizTvCUFSIUydJ38oXISFgQBEEQRBOxFglymfshVXCVkCuEIAiCIAinaA0WYaHwEGOhNAsPnYEsFgRBEARBOMHGYuEhxkIplwIANHpji7aprSFhQRAEQRBNRLA+KKQScJwHYWG2WGjJYkEQBEEQhDNEYeEhvgIAVGSxIAiCIAjCHXovi2MBgMosPjQGEhYEQRAEQThB64PFQoix0OrJFSKyZMkSjBo1CiEhIYiNjcUNN9yArKyslmobQRAEQbRrdEYfXCFksXBk165dWLRoEQ4cOICtW7dCr9fj6quvRkNDQ0u1jyAIgiDaLXqD4ArxxmJhFhad3GIh82XnLVu22DxftWoVYmNjcfToUUyaNMmvDSMIgiCI9o5osfBCWKhkZldIJ7dY+CQs7KmpqQEAREZGutxHq9VCq9WKz2tra5vzkQRBEATRbhCyQpQ+ZIVQjIULTCYTFi9ejAkTJmDQoEEu91uyZAnCwsLEv6SkpKZ+JEEQBEG0KyxZIV64QsQ6Fp3bYtFkYbFo0SKcOnUK69atc7vfCy+8gJqaGvEvPz+/qR9JEARBEO0KX7JCLHUsOrfFokmukMceeww///wzdu/eje7du7vdV6lUQqlUNqlxBEEQBNGe8a1AlhC82bktFj4JC57n8fjjj+P777/Hzp07kZKS0lLtIgiCIIh2j7BSqXeuECF4kywWIosWLcLatWuxceNGhISEoLi4GAAQFhaGgICAFmkgQRAEQbRXdOZ4Ce8KZHUNi4VPMRYrVqxATU0NJk+ejISEBPFv/fr1LdU+giAIgmi3CBYLb9JNBYtFZxcWPrtCCIIgCIJg+FTHQk6rmxIEQRAE4YamZYV0bosFCQuCIAiCaCJNqWPR2dNNSVgQBEEQRBPxLd20a2SFkLAgCIIgiCbii7AQK2+SK4QgCIIgCGfoxeBNzuO+ZLEgCIIgCMItTXGF6IwmGE2dN8uShAVBEEQn4nRhDf7xcya2ZpZQiYBWQOtDuqn1CqideSEyEhYEQRCdiFd/zMR/9+Zg4f+O4MsDl9q6OZ0evdliIffBYgF07qXTSVgQBEF0Euo0ehzNqxKfX6pQt2Fruga+FMiSSjjIzbEYGrJYEARBEO2dAxcrbXz3DbrOO3i1F3yJsQCsy3qTxYIgCIJo5+w5X2bzvFFnaKOWdB30PlgsAOuy3p1X9JGwIAiC6CQcyqkEAFyZGgOALBatAVksHCFhQRAE0UkoqGoEAKR3DwMANJKwaHF8WSsEsCyd3pmLZJGw8ANagxFfHcrDmaLatm4KQRBdlFqNHnVa5vroExsMAGggV0iL48taIQCgEiwWnbhIlk/LphOO1Kj1mPPhXuRWqNEvPgRbFk9q6yYRBNEFEawVkUEKRAUpAZDFojUQs0J8tFh05hVOyWLRTL45mo9cc0rX2eI6qGmGQBBEG1BYzYRFYrgKAQo2K1aTsGhxxBgLXy0WJCwIVxzPr7Z5fqaorm0aQhBEl0YUFmEBCFIKwoImOi2N3sjSe721WASaRV9ntiaRsGgmGXnVACylWk8X1rRhawiC6KoUVGsAAInhAQiUMy83WSxaHl8tFsEq9tvUazuv6CNh0QzK6rQoqG4ExwHzR/cAAJwuoABOgiBanwKzxaJbeAAClRZXiKkTL3bVHtD5UNIbAIKVJCwIN/xpdoP0jQ3G2F6RAIBTZLEgCKINEFwh3SICRHM70LlLR7c1PM/7VNIbsLJYaEhYEE44WcBERHr3cKTGhQAAcsob2rJJBEF0USzBmwFigCBA7pCWRIivALyPsQghiwXhjsvm9K6U6CDRvKXRG2mpYoIgWhWe51FWpwUAxIUqIZFwotVCrSVh0VII1grAB4uFeayoI2FBOKO4lgmLhDCVWKbVxAMG8mkSBNGK1GkNYr8TEagAYMk+UOs77wDW1uitilx5a7EIUpIrhHBDUQ2Lwo4PU9lcVNpOXFGNIIj2R3WDHgAQIJdCJWeCQqhl0UAWixZDsFhIJRykEs6r94SYYywayGJB2MPzPIrNwiIhLMBWWHTiwicEQbQ/KtU6AEBEoFzcFqRgA1hnrpfQ1ogZIVLvRAUABCvZb0QxFoQDtY0GMSgqPlQFqYQTLy5rvxtBEERLU2UWFuFmNwhgZbHwokjWzycKMW3ZLjz8xVFKT/UBXzNCAEtWSB25Qgh7iszxFRGBcvEGFuIstJ14OVyCINof1YLFIsh3i0VGfjUeW3scF0rrseV0MX4+WdRyDe1kCN9tgFV6ryeojgXhEkt8RYC4TXCHUIwFQRCtSZU5xsKZxcJTuun2MyU2z9/59SxZLbyk0ez2DpA3TVh01gxCEhZNxBJfoRK3CWW9dSQsCIJoRaqdxFiIWSEeXCH7sisAAK9ePxASDsivbERZvbaFWtq5sFgsvF8oXHCFGE18p52EkrBoIkXmYjTxToSFlirdEQTRilSpmcUi0spiEajwvF5IvdYgVhCe2j9WfE9nXnnTnwjfbaAPrpBAuRScOdazs8ZZkLBoIoIrJCHUIizIFUIQRFvgLHgz0IvgzcM5lTCYePSIDET3iEAxVbWRhIVXaJrgCpFIOAQrOnecBQmLJiLcyNEhSnGbELxJrhCCIFqTarPFwjp405vluc8W1wEAhvcIBwAEKCQe30NYUDcheBPo/OuFkLBoIsKNHB5guZHJFUIQRFvg3GLh2RVyqYKtbdQzKgiAZeZNFgvvaErwJmBd1lvv9za1B0hYNJHqRnZBhFkLCzm5QgiCaH2qGoTgTUdXiLvgzUsVagBAz6hAAJYBkmIsvKPR/N36EmMBWMp6d9aqqCQsmohgsQizisIWiqRQHQuCIFoTIXjTOitEZZ7oaNz0R3mVtsJCjLHQUR/mDYI1SOWjxUIo611PFgtCgOd51DY65o2LBbKo8iZBEK2ERm8UTfLW/ZHKg/VBazCisIZlt4muEAW5QnxB+J58tVgEd/KFyEhYNIFGvVEs5RruzBVCNyVBEK2EMMmRcECoylJPwZOwuFzVCJ4HghRSRAUxQUIxFr7R2IR0U8AiLGpJWBACghtEJuFsLijRFUIxFgRBtBJ15pTFYKUMHGdZDMsiEpz3R3nm+IoeUUHi+8QYC8oK8QpBgPnqCgk1T0gFUdjZIGHRBMSMkEC5zY0sWCwo3ZQgiNZCMKeHqOQ224XBzpUFNVfICIkMtLzHyzLgBMNSIMv7ypsAEGm2EAnZPJ0NEhZNoMZJRghgFWNBwoIgiFai3spiYY0QvOnKrVFQxeIrkiIt6x2RK8Q3xAJZCt+G0nBzkK0QdNvZIGHRBGoaHXPGAapjQRBE61OnYYNTiMpWWHhKHRXWA4mzqh5M6aa+IRbIkvtosTCPHUKacGeDhEUTcFYcC6CS3gRBtD7CehPBKnuLhXvrQ1kdExYxVtWDA7yo1klYaMqy6YBlUkquEELEWXEsgEp6EwTR+rh2hQjWB5PT5blFYRFsJSzIFeITTU03FUqvkyuEEBFjLALthQVZLAiCaF0swZvOYywA531SqVlYxIY6sViQsPAK0WLhY1aI4AqpVutgMjmKvo4OCYsmYHGF2MZYiK4QuikJgmglPFksAMeYCa3BKE6QYoIpxqKpCOXSm+oKMfGdc+l0EhZNwBK86dxioaPKmwRBtBKWOha2/ZFcKoFMwtLh7S0Q5fWsD1NIJQgNcCyqRTEW3iGUS/fVFaKQSUQhWNkJ4yxIWDQBcZ0Q+xgLMW+chAVBEK1DnQtXCGBtgbDtk0prNQBY4KZNUS1yhXiNwWgSJ5G+ukIA65RTEhYEvImxoJuSIIjWod6cbmqfFQJYJjv2FghnGSEABW/6gtrqO/LVFQJYVqLtjCmnJCyagKd0U3KFEATRWggxFiFKR2EhrnBqN9kRali4EhZU0tszwnck4SzLOfhChFh9s/NlhpCwaAI1TlY2BawsFuQKIQiilXBVxwJwHYxZWutCWCjcV+skLFiX87Z2J3mLsMR9NblCCL3RJM4QqKQ3QRBtjausEMD1CqeCxSLWTlh4KqpFWGjqAmQCgiukklwhhPVqdKF2MwSKsSAIorURXSE+BG96irHQ6E2dsr6CP1E3ccl0gYhOXH3TZ2Gxe/duzJ49G4mJieA4Dj/88EMLNKv9IlTdDFHJILPzq4nppmSxIAiiFeB53iorRO7wurDisn3wZqmTqpuAbRAiWV7dIy5A1kSLRXQIExZldSQs0NDQgCFDhuDDDz9sifa0e6yXTLeHXCEEQbQmGr0JRrNlwZkrRLRA2FlRy11YLFQyyyBJ7hD3CIIuSNk0YREbwgqTldVp/Nam9oJvS7IBmDVrFmbNmtUSbekQCMWx7OMrAFqEjCCI1qVOyyY6HOfcJO+s4BXP86IrJNZqZVMAkEg4KGUSaA0mqHUGRAbZBqgTFoSxICKwad+REN9SYg6k7Uz4LCx8RavVQqu1fHG1tbUt/ZEtipgREuB4MQmuEKOJh8FocnCVEARB+BNhnZBgpfPMBMFiYT3ZqW00iCnx0cGO/VigQgqtwURlvT0gpIna1zPyFmGNlvJ6LUwmHhKJ75kl7ZUWH/mWLFmCsLAw8S8pKamlP7JFqXZzMSmtFv2hWhYEQbQ07mpYAJY6FtYWi1Kz6T0sQC66b60RxIiaalm4xdWaUd4SHawExwEGE9/pynq3uLB44YUXUFNTI/7l5+e39Ee2KK6KYwG2RVLso7AJgiD8Tb2bGhYAoFI4ppuKbhC7+AoBsaw3CQu3WFwhTbNYyKUSRJldTaWdzB3S4q4QpVIJpdL5BdwREct5OxEWMqkEKrkEGr0JDVryTxIE0bLUaV1nhACWYEzrQExXVTcFgszWjwZd51t105+4C+T3lpgQFcrrdSit02AAQv3VtDaHggB8xFJ10/nFJJjFqjthmVaCINoXdRrXxbEA6wJZFguqq6qbAkEKs7DQksXCHRa3eNMnkILVSEj/7Sz4LCzq6+uRkZGBjIwMAEBOTg4yMjKQl5fn77a1S4Tyq678aoLgqG6085mVnwdWXQfsea9F20cQRNfB3QJkABAgrBXizGIR7MpiIcRYkMXCHdWNrt3i3iIKi9rOlXLqsyvkyJEjuOqqq8TnTz/9NADg7rvvxqpVq/zWsPZKtYuVTQUEF4mNxaLwOPDJZPY4/yAw8S8t2USCILoInoM33cRYhDoXFoFmi0U9WSzcIk4ym+EKEX6Dzmax8FlYTJ48GTzfdUu91qhdx1gAlpxmQYCgLAv44ibLDsbOFf1LEETbUedmnRDAEohpXSBLyApxHWNhtlhoyWLhjuZmhQCWIlmdLXiTYix8xGOMhXl7jVoHVOcDX9wINFYCESmWnQwkLgiCaD4es0KcpI4KBZmEQc0eMcaCskJcotEbxYDYptaxAIA4c4GyuuoyoPgU0Fjll/a1NSQsfIDneSu/mnOVKlxk9XU1wFe3AbUFQHQacP9vlp00NS3eVoIgOj/1HrJCQs3ba6wWTyyuYRaLhDDnwiJQyAohi4VLhMUopRLOYTFKX+hlysP/5Evwv4r5wMcTgGUDgP0f+auZbQYJCx+o1xrEuvzus0J4zLrwGlByCgiKBe7cAATHAkpzOhEJC4Ig/IC4AJkLV0hUsO3S3HUavShG4l0IiyCz+4TSTV1TbVV2wFnFU48YDcCe99D3h2swSXoSUpjAK0MBvRr49QXgwjY/t7h1IWHhA4JPTSGTiCZGe8ID5XhUuhFD6nYBEjlw65dAWHf2oiqM/ddUt0JrCYLo7HhyhQgxXzWNehiMJtFaERYgF4M07REsFmoK3nRJVYOQHdgEN0hjFbBmLrD9NXAmPX7nR2CS9p/IfeAMMPI+ts+2VwFTxy2ySMLCB2q8SC9K1pzB07Jv2ZNr3wV6jLG8qApn/0lYEETnpOgE8PXdwOWjrfJxnoI3IwLlkMIInmf9V6EHNwg7FlksPOEpO9Al5eeBT6cCF3cC8iDghhV4M/Ql5PFxKKjWAFf9H6AIAYpPANnb/d/wVoKEhQ94CtyE0YAhR/8GGWfC77JJwIh7bF8XLBaN1S3WRoIg2oiS08DKiUDmD8ChT1rlI+u17utYyAqP4LjqYbwo+xKVDToU1zQCcO0GASzppsbGOuDMT8Cx/wG1hX5uecemxs3SDi6pugSsuhaozAbCkljc3dDb0S0iEABQUK0GgqKAobez/U+s93ezWw0SFj7gMb3oxDoE1lxABR+C1/n7HF8PCGf/vY2x0NYDJZlAe0vvrc4HTH4ykxr1wK8vAoc+9c/xiLYlewf7Lf11fXQkfv2b5bG6vFU+st5djIWmFvjvdISiAQtlm1DZoEORFxaLIIUMMySH8UHFQmD9HcCPjwPLhwP7/t3++qI2osRc0CraRZExB/QaYO2tQH0JEDcIWLgDiB8EAOgWEQAAKKhiog/p89j/s7+wMaADQsLCB4RqmqHOVKrRAOx+BwCw0nAd8jVKx3ofvsRY8DzLKlkxDvhgBFB2rhkt9yP7PgDeHwR8fAWboTWX3e8A+/8NbHoGyNrc/OO1FOe3Av+ZBnw5F8jd29ataZ8cWAF8cQP7LTcu8uwjPvkt+04LWsdt0KKUnmXmbQFJ01MQvYXnefdZIQc/Fh9qebnZYsEGxPjQAJfH7XXmQ6xU/BNRfCWbWcenA4ZG4LcXgW/uAbR1fj2PjkhBNRMBgijwyN5lQNkZFsy/4BsgOEZ8qbv5GJfNx0S3Eaw8gV4NnNvi13a3FiQsfMCtKyT7d6AqF3xAJL4wTofeyDvmgYsxFl5YLLK3A7l72OPKbCBjjet9nc0OTSbgxNfArrf95++tyAa2/4M9Ls0EfnnG83uMetbhZm0GGuxmcRd3ArvftTz/8fH2WePj5LfAmpuBy4dZtPaaeUDN5bZuVfsi7wCw5a+W539+5b5TPLoK+O5+9p3+9lKLN6/FsXd9GBpb/CO1BhP0RjZ5cXCFmIzA0dXiUxkMqGpo9GyxOPcbEo8tAwD8j7seePwo8NBu4Jp3mVjK/IGZ8/1xn9aXsqrEHRBRWIR7ISxqC4E97DvFNe8AoYk2LwvHEC0WHAf0u5Y9ztntl/a2NiQsfMCtX+3k1wAAbvAtMMmYz0wo+SoiuEK8ibHY+Rb7L4iRvAOO++gagPV3Akt7APs/tAiMwgzgv9OBDQuBHW8A/5niH2vAjjcBoxYI78meXz7kfvZSdo6ZUP83h1lf/jkQOPgJs8bkHWRt543A4FtYwFJDGVB5sfnt9Cf1pcAv5hLsw+4Auo8C9A1sW9k54PiXQO4fLWciLj0LXNrn+vh1xUBdSct8trcYtMCPT7DHQxdYIttzdjnfv/wCsPl5y/NLe4Hiky3bRm9oqGBieWlPYMOD3rtzjAY24ALAyPvZf70f137QNwK1RQ7tEVJNOQ4ItM9Su7ANqL0sprhLOR7q6nIUuYux0DcCPz4GAPjcMANv6G8HZEr2AaMXAvduAgIigaI/gUMrm3dOlReBFePZUgff3sc+uwNx2SwCupvjI9xyfA1g0gNJY4EBcxxeFi0WVVbfQcok9t/eOmrUs/utnUPCwgdcLpOrrWf+MABIn2dZiMx+hVPRFeLBYlF+ng3aEhlwuzmAp/CYbWdlMjKf3ZkfAV098+9+MIL9fXIlUHCEDdY9xrP9f366efUz1JXsswBg3mogIhkwGdig54zqPOB/1wM1eUBgFBDVFzBogM3PAh9PZLMebS3QcwIw50Mgqhd7X2V209vYEvz2f8x1FZ8OXPc+MHs5+13ObQE+HMVM/quuAc796vuxq3KZcHAGzzM30YrxwOezgC9vYr+BgE7NBsF/DgT+NQQ48rnltYZy4PfX/eOqqsgGVl8PfDSOfRfOZqp7lgHlWczMe/XrQPIVbLuza8NkYoOXQQP0ugoYeCPbfnRV89vaHIpPscDLw5+y3/vEeuCXp70TjPkHAHUFEBAB9J3OtvnLYnHqO+DdVGBZP+D9wTYzWMENEqyQQSKxq6Vwgk10MOwONMqYuGisLkFepRqACxP+yW+A+hIYQ7tjqWE+tAYTDEYrd1bSaGD6a+zxzqVMiDUFbR2w5hY2kRDOcd8HTTtWG2Ay8aLForsnV4jJxIJfASa4ndS86BkVBAAorGm0rOnSYyzASVh/WFvIhNevLwJvpTDh+9ks4Kv5wLnfHI7XHiBhoW9kQU45u9nKo1teAA6udOofFmIsHNYJubCV+cMiUoBuI8QyrYXVdp2Lt+mmJ83pqr2nAEljgOA4tsaItS/60KfMVaIIBiY+w0RLVQ5QcYENfINuBh47DNzxHWtXXSGw7RXvvhNnnPiatSF+MJA4DOg1mW239isLaOvZRV9XBMT0BxYdZm2Z9Q4gUwElJ5mCHzAHuP1rNiuK7M3eW9FCwqKuBFgxAdj4mPfvuXzUHJnNAbP/BUjlQNwAYO5/HH3o1Zd8a8/FXcCHY4GPxjJLkP0AtuttJg54I8BJmavtf3OAjLWsE/50ChsETQY2iP28mFkBSjKBd3ozUbLrLe/bU1/KxIo1ZedYDETOLub62vcBa0P5ecs+BccsK/bOegsIjLSI2ZJT7N6y5vCnQN5+dt1evxzofz3b3pYm8bpiYO08ViU3qo/Z6sAxsbNzief3n/mZ/U+dxc4LaL7FoiwL+PJmNpvXmr/D2gK2ra4YgJsaFkY9iwkCgAE3QKuIBADk5l2CRm9CqEqGFPNgJsLzwAEWk8GPehBasAB1B3fu0AVMZOvqPWe+1JUwy4n1d8HzwKbnWD8V2o0JUYBdW9bCWeDyUeDru9j1fvATZtlq4wDS8gYtdAYTJJz77BoAQO5uNrlShQEDrne6S1SQAiFKGXgeyDcLP6jCgIQh7PGON4H/Xs1i0XR17H7P2wdkbQLW3tIuA9+bXou0o2PQATteZ+VTTXrH1+MHAz3H22yqEXOX7bJCBNXY71qA45AUGYgTl2uQX2UvLLywWPA8mzkAzEXAcUCPcczUenEnkDyBmRG3v8r2mf4qMOoBYMKTbPBRBrPgn4AIyzGvXw6sng0c+YwJjuQJrj/fVZsE1T3sLvY/5UrW8Z7fCsx401aJ73jTUnX0jm9ZChUAjHmQiaWLO5g46TbC8r4os7BoCYsFz7Ogy5JT7G/Ov717z68vsMdDbwe6Dbe8NvBGILIXUF8GnPqWxRP4YsqtyGauIWFWu+stICiGmZsB4PB/gZ1vssczlgC9rmRWg+ITwA+PWI4TFAPcuBIoygC2v8aC9awC9lCS6bktOjWbPV7aC8gDmVVmyK3sfL65h61zEzcYGDof2LGEdWgfjWXXXM8JwKZn2f3T7zqL9SE0gVm0qnLZar7CLL4yxyJup78KhPewDDqlZ5mYl7TyXIfnge8fNpfeTwXu38pclvGDmVjb8x67txRBrt+ftYk97nctIDfPYH21WNQVM7FZV8Ssk2d+ZqJSIgeuWAyMf4JZjWovM2EXEo86IdXUPiPk0h+AtgYIjAa6j4RBFQmoc9FYXQIgBUN7RDhaOC4fBkpPA/JAyEbeBfmW/dAbeah1BtuJlEQCXPEU8O29zB0y4Qnn383lI8yiqi5nE6o5/2bCa/srwJ9r2Wx87n+Ye+DP9WyysXMJi0EQKD3LrJ46c2aEMLFKnQncshqQexjUranOZ21JHOb9e1wguCziQ1WQSz1cr6e/Z/8H3GC5NuzgOA4pMUE4cbkGF8sb0DcuhL3QewoT3Me/YM8DIpl1NzSRCbPcvcDRz4GtLwOpM9j91E7ousJi+6tMAQoExQDJE4HTG9hzJ8F51c5iLEwmZrEAgL5XAwCSzH43UX0KeBNjUXKaDa4yFZB2DdvW71omLA5/Cox9hPmz9WrW3hFmf7YqFBh4g/NjpkwCht/FxMFPTwAP/8FuSpOJdfwGDbNAuCpNe/kI63RkKiD9Fratz1T2vOI8m7V2H8G2V2RbZjI3rLBUHRWI7sP+7GlJi8X5razjEuB51+cqcHoD+27kQcCUvzu+LswmzppnqwYvZ6gmk+X36zmBdR6//4O5GXT1bPAVRNykZ4Fxj7LH9//GLGmlmUw0Jo0G0m9lpeL7TGUz7e2vsQ5HQLje3HFwBRMVAGvT9w8yAVt9if3mQTHM6hUSxzr0X//G3EDWIiamP/utrb/T5IlMWOxZxs6RN7HgXPvrNrIXIFWyuJXqXPbcF3ieWQCthbQvnPyWCV2pErhtreU7G3kvswAZtWwm7UpYVF5k35VEzu6hqly23ReLRcFRtgKyvSUz7Ro2oxdEd2AkExbma01MNbW3WAjxVGkzAYkUpsBooBKI4pjlY3iPcMc2CK6T/tcDAREIVMhQ06hHg7Pqm/2vtwjHY18AYx+2fV1dycRqo9kCoalm8VSBUZY03JlvWSZuM95gAuLQp0D6bawvKT3DgqR19cwC1u8a4NQGNjE4twX4+SngxhWuvlELJiPw3QOWfv2qF4Ern/P8PjcIQZYeM0KMBlYHBLCIbhckRzFhkVPeYNk46VkmDnN2sRTVUfdbAj8ThwIDbwLKzjIL4C/PMLd5U8qLtwCdU1hoapglIns7U6iTnmUdsEBJJkuNA9iMr/9sQBbA1DgnYbNQwf9nhdOskKIMtq8ihFkWAPSIdCEsvLFYCLOf3lOY9QEABs1lpu3yc8Db5lVS5YHMEuHtDG/6P5hlpeIC6+AnPMlmasKAO2AO+y6cqepjq8z73GDpwFVh7D0n1jNFLQiL7a+yGWzvqUDfad61DWADI9AywmLfctvn+kZA4SboymhgJXUBNjsLTXC9r/B9eWuxOLbaYh2Y8yELhM0/CJz/zdZVNfoh1gkKRPUGrnnb9XEHzGEdvkHDOpovbvTcJnUlsPd99vj6D5iY3vU2m1EC7Jqe9z8mKoQ23L4euLCdDQKlp5mYvvKvTNhaM+kZNhDk7QO+uZtd87l72H1mfd1KZUBMGrPGlJz2TVhkbmTuovJzwPjHgWmvAhLnpfad0lhlsUpNehaI7mv7ujIEUGstrghnXNzB/ieNYferaLHwUlg0VjP3hqaaxSF1G87E+MAbmdXEGrn5mtWzfqVOdIXYu2bNFRtTZwIAJObURouwsBNhRj2LcwDEiUOQQoqaRj3UzqpvSmXs+/7lL2xyNup+5iYU2P4qExWxA4D7trB76ch/magIjGJWuCG3WvbvdSUTySfWs+t20E3ssV7NrodbvwCCotlnXtjO4o1OfQvMfNNWUBp0TCif2sB+y/TbgPO/WkQFwILZI3sBg292PC8v8Toj5NJeFnsTGMXEtBtSoplwzbUWFvIANrEQJhf2SCTMRfvxFew8T35rmfi1MZ1HWGT+yG7mxirgwEeWmcPlw8yseNdGICbV7ON7hpkZ+10HDLnN9jhB5vzi+lKHjxAsFjamQSHyvdeVgIy5SJIi2QWX5yAswtl/TY3rWbMwAxbSjQDWWU7/B7BuPpv5SRXAzZ/51gkHhLOLcN18lsFizmKBIph9b5kbmSl4yv/Zvk9Ty25UABhxt+1rw+5gHcDJb4Cr/sZm25kbmTgTfKfeIszK6gqZed7dwO8LRX+yAY2TsO8OYNk07o5/+ns2Cw2MBsYtcn98mdkc602kdm0RsNWcWjnl70CkWSTeuoYJjnO/sniaobf77q4C2PUkD7AMQLoG9/tnbWKDZkw/YOgdrKPqOZ7FcUhk7NzjBjq+r89U9ueOiGRW0v6HRyyzNlkAGyTsr9u4gWZhkclEvit4nrkB6oqY++nPryyv7fuAXTfXLXPfLmu2v8YmBdGpzKRvjyqUDYbuMp+yzcKi92T2X7gevBWaBz5ig3B0GrBwOxMzrhBM/2ZrSK2G9Uc2q2vWFDArIicRB7OwKCaMo1ALlVyCofYWi5xdrA1BsUAKO48gs3ul3tUKp0MXsADOmnzWPwhCoeycJc312vfYBOS6ZWwiU1vAxJKzc5z1FoufKM1k5n2AuVtvWcUsNQJ9pgKxA5mozdxoW93456eAjC/Z46IMi0sZAOb+lwnXvcuY0Ok/m8V2NYECbzNCBBd56iwmxtwgCIuL5R7uWXti0oCJf2FupI2LgMAIoI8PE7oWovMIi03PAvXFlufhPYBxjzP3Qfk5Fll/5wZ28V76g3VyM50EZgVFs/92NRe0BiMazRG7NsIi7yD7b7ZWAFYWiyo1eJ63rH4nqGveyMSFvam6poANhJxEnG2IpM0EHj3ABp8eY5kp3FfSZrLiLD8+yUyqPcYzgZJ/gPnT//gXMGS+ZZAH2MxAr2adr9U5AgB6XgEkDGU38Tf3su8ZYIIjboBvbQuMZN9PYxU7TuJQ38/PGZnmTJb+1zOrgF7NzO6Icb4/zwN/vM8ej33Ys8Dxxae+5102kHcbCYx5yLJdpmDxFUKMRXMRZ7Ye2nTWbB0beJPFgtBrsiUwt7kMvZ3NWo+uYoNJ+jzHWThgES+ldlksl/axao9GHRDbn5n4K6wCR8Exi1JkCnMvHfkvEwE1+Sx+Z8YbrttWU2AZAK/7p/NBRlyN2IXFwmQEcsy1ZnpNYf+F68GkZ5YvdwOKpsZiOZ3yontRAThYLGob2aAf6myikzhM7F/kocxae3WyDAOvHisupS4iBHqmzRTb63EhMnkAu4Z/f531G+nzmLDduwwAD6RdaxujFtGT/bkiIAK4YwOwaykL/k6dYYkxsyd9HrDtZRabIQiLs5vMooJjMV+V2Ux4BESwgXfwzcy1lLGWBVMe/q9rS4AHLle5yayxRljrw5MIh0VY5PgqLAB2fsUn2aT0y5uBtFnMSjLtVUt8WyvTeYRFz/FsUJIHsptq9APsoho0l5nOijKAT66yzFon/cV5sIvgMrFzhQjLDssknOXG5HlmxgbYYG8mMTwAEg7Q6E0oq9ciNsQ805CrmIVAV29OTwu3/WzBrNpthEXgWBOTxv6aQ59pwNOnmflTMF8OuIGl/l3cwbJiFnxtOT8hDXD43Y43uUQCzHob+Oxqi58+vCcwpYkFjxKHs5sx/6CtsDAagM3PMRPxxKd9O6aQB95nGhOUerX7mXzBUebHlQWwAEVPyGxnkS6pK2b+aIAFLvpisvcVb4SFvpEF+wKsI2opEocCie+73yc+nf3PP2Sx5DVWMbFbb67RIcQxSZXsvo3uyzrU7iPZ9roSFowtWOLy9gNTXxatiA4c/ZwJ/J5XWNJj7RHcO65cIaVnWJCkItgScyNcDwATm1I3YuHUd+zY0WlAPzeWGgHROmZrsbCJsbgoWFAnW7YFssElTlqHOHs3CGARFn2mi5uEEuFCgKhTRj3AXGmlp5n1K6y7JVZj0l88n489oQnMquqJ9HnM2pS3j/0Gkb0txdnGP24RDNe+Z/s+RSAw+a8sKPf311ncRkSyz830yhVSc5nFP3ASr4R6SgwTFmV1WtQ06h0zD90hlbMJ4i9Ps7o6gjt9atsVnus86aa3fA7c9QMwfy1w5bMW60BQFHD3j+ym4Y0AeJZONmGx8+MIrpAGW1dIeR0TFpFBCktEdfl5ZkKUqSydIwC5VIKEMHbROQZwms16zlKrhNRNf80Y3WHtE+U4Fo0tkTNfnVCT4/xvzIIiVTJLhjN6jGG1HRKGsr+7frApV+sTwgzHvijM8f+x2ej2V31bSlintkSSJ0/wzkWQYY4v6D/bu4BAby0Whz5lgYBJY1nQZksiWFn0bs4zZzdrc1iScytCa5I0ht1DdUUszRJgA0d9CaAMY261wbewgL/nsoHHjwDzv7KICoDFdCz4DhhnlU7sJE4KABPVgmB2ZyUSLRYuYqKESUX3kRbLhLWw8CQ2j5ur6Q6/y7tYKYcYC8EVYnUvC/eOUGAJsOrTnKxfUnmRze4lMpt+JzKICbKKejcVNgMiLMXQ1t3OMs94I7t3uo3wfD5NJTTR4io+9CnLdqu+xNyIk//q/r3D72b3n76BuXJcUV8KfDaTDdRW8DzvXfCm4CJLHG7rynFBqEouVkM9X9KEkukyJYvZuucXltY/5e+WmL42oPNYLNyhCmNpjxXZrJOwTh20x8VNWN7AfOg2i84IHUu3EQ4zox6RgSiobkROuRojelpdWIGRzBTXaCcseN75bKO1iO7LfOp/vM/MyrEDLAGMYx50b1Ibcbdj/EVTsC6sJMxceZ7lrwvo6h0DBV1x+TAzSYcksloeQo0BV8LCoLUEsQkrDHpCMKG7G0R43jKTHvNgy0dui+Z4g61lyhqh4+szre0jyeUq5ma7uIOJa5nS4qaYv9a1RcEajmPBwn2nMZ9/XSETJmHdHPfNP8hER0CkbSyTPULH7MpikX+I/U8aY9kmkTAhbtS6F5tl51gRO05qWXTKE2KgsNliYe8Kqc5nLk5OyirECriYLAGwWK2SxtrcV6KwaPBQuvuqv7H7teAI61vDkthEo6UZ/SAr2GddWO3K51xn7whIJMzScukPttqoK7b8lVm98vYz166Zmka9WNvDrcXi0h/sf68rPZyIhbT4EBTVaHC2uA4jkz2LEacku7HAtSKdx2LhDVG93YsKwOomLLMpxFJex4RFVLCVgMg3l9l2Eu+QFs9MoGeL7Dols1kSaruqdaVn2I0vC7DtFFqTyS+wtCZ1OfDBcGbiVIYBV/jofmgqicPZjE9dbpm5XtjOFu8R8KV6qDB7S76CDTxCp+NKWFz6g0XnB8fbzvjcIfPCYpF/iFUiVQSzQK6WRpjZAq7PtTWtY94gtOPCNlbXgzcy0dOUTlJwZzoJwAZgZfqf5lx0CQgxD65iLISJhf39L/fCPXbWHNDae4ptxpo7xOOaYyzsgzeF9iSk2w6wweasnsYqxyBj4R6xuw6izf1cpTuLBcDEzu3rWXDm1JdZHRAvZujNJvkKFkDKG9nfkPnAiHu9e6/o4nJjGXCxRodQwyI6WAmVfRl1a0QX+TjX+9iRZq5fca4pFot2RtcSFt4gxDYYNDYXnqDcY6wtFkLgZpIlvkKgfwK7SM4UeykshKCrnuNRa5CIMR2tilzFCs9E9WGxKAERwO3rWqejAJjVR3CHHP4Pi634zS5LxV3qnz3CrEHIsFB4cIUIUdx9p3sfA+HNICJEp/e7zn/ZLu6QKtisFXAeZ1FXYhZrnPcCqqURimhd2GrJ9rjSg1nbFcJAKsRn2CMIC3PdGZco3cRY1JeySrfgHCcC3ohN4VpLm+l6H3sEwWgXYyG6QvL2s//2/VFgpKVSrPV3wvO24tuKKHM/V9HgRbZTUDQr9T3xafep2f6E44AbPmLZfnP/y+qoeHvPKsyCUediAOd5l260y964QerLLGseWbvrPCBORos7vrDoGq4QX1AEsaJI+gZ2cZnVrYPFoqHCEqHuxGLRP4G970xRnW1miCthYZ5B7jIMwMJ/bIPBZMLsIYlYNm8opPZV8lqS6D7AokNMscf2B0LiW++zAWYdyf6d+U3zDrABMCCCDZTqcu8tFnoNK+wFsAA9wMoVUu/8PeeF9LAZ3rdXHERcCAuTyZJCPOgm74/bHDiODUK6OnF2a4MwG0tIbz3R6Im4gSzV+XdzmvL0fwBJTbTcubNY1BSYs084Zi1whzCzdWaxEGaksQMcfdmexKa6kq0FBAB9fbnWbFNZhToWoQHmblzMULMTFhzHxFbtZSYqhaD1sizWx8kCHCy5giuk3JPFoq1pisVNqA+kddEPCNltAiajKFq8WiNEuDZi+vtUuE0QFudK7MaMDghZLJzhJOVUsFiIMRZCxxCd5rRzTo0LgYRj2SSldVaq35mwMOrFmcPb5xKgM5pg4oGNGYXILPRhhu4vJFKg91WtLyoAIGUim0nyRla8SyJn6YBCqpq3wqLgCPNzB8dZ0mcF87CzwbYi2xzEJmf5894iDCKuhEXhMRaUqAhpXbeDGMDp5FyFjq9n2/tibZj0LDB/PQvCdFZXwlvcWSwubGP/u43wnIrnzmLhyg0CeLZYZP/OLIKxA4HwJPdtsMYu26e20cpioWuwpOs6a5NQ5Mw6JT93j2V/u3Rb0RXSFpbTlsbTBEOwdApY9TlCqml3d/EV7q4NN/SOCYZUwqFarUdJrReWonYMCQtniCmnlhlPeb1gsTDfgMIy5j3GwBkquRS9YtgFnGkdZxFoVrDWWSEFxwBdPaoRgky+B56enoqhSeHsJfuFzLoCN3/GopqH38WinAfe6DlC3x77+ArAfVaI0Jl0H+V9cChgGURczU6F4lB9pze5IE+TcFcRtPAY++8p3qgtSJvpW8VWZwiC2HoQFRDL7093fM0ed754Z4GbAp4sFkLf4UNgn+1xG8HzPGrFkt5y8+JcJhYfJJR9tibE7KKosxYWwj3iWBUyKsjsCqnv2AOcU4TYGYOGTersyT9s+7yxSnzoVUaIu2vDDSq5FL3NaaenCnyIJWuHkLBwRpBgSrXMeASToKDkLarU9cUjuENOW18kziwWZjfIXuMAJEeH4OEre4sRxw4rpHYFlCEsffD6DyzCzdsl5wWETtM6tVMM3nQyUxGDrXzrDCwWCxe/07kt7L+77IOWwJWIMujYEuFA+xQW/sCVK8SoB7J3ssfeCAtXBbIMWstqrE2xWBSYXXQ++N8BWMVYNEKtM8JoYsHloQEyoDCDveaqsJy9FcdNfAUARJr7uQadEY32K5x2dKwLkTkTjcLvI2AtLDzVsLC+NuxdUl4wuFs4AOAkCYtOiJCiZrUQmaDco4OV7OIpMM/6nARuCgzpzgbDY3nVlo2isLCyWJgDN/8wDcKCMT2gkEmQGM4GrC5psXCGKCy8cA0ZtCzVFLDtNEUTqDP3gHl/H2cZbgtk1RayIjne+PP9jasiWWVnmItIFcZScDsjrlwheQdY3ElgNJAwzPNxxHRTu06+6E9WDTQoxnlZfXcWC30jsy4ArAKrL1jFWAjxFTIJhwC5lBUABFgtGWcIVhzBYlGWxWKWZAFOa06EKGVQmFfu9CqAsyMhlbOUYMBxktFYbYmxCDUvoGjVV1tiLFwEYRf9ye6vwCjfF9QDkG4eM0hYdEaEFTnNwsJk4m1jLIpOmC+eaNvy13YIucjH8qpgMs8uHCwW2nrwZtPZPtMgzB7CzJhd2mLhDFFYVHvet+AYM3MGxbBS5AKuskLUlUC5Ob21u4+l0mVuLBZCSmfisNYPkhRdIXYiShDEicPavn5FS2FtsbBKGRdrNvSe4l1BKlfppoJo7T7K+XfozmJRdILVFwmK9X2Za6sCWdZVNzmO891iIcRX9BjjtDopx3FioHqnjLNwFcApuAkjki2rMJstFvVag7helEtXiLUluwn312CzsDhxuQa89bXbwSBh4Ywwc0CVWVjUNOpFs2NkkMKqfoX7i2dgYihUcgmq1XpcLDdfwIKwaKxkGQN5+8GZ9Mg3xSAhuR/iQtlAlUjCwhaVDzEW1m4Q69/HlStEyB6J6uN7bX2bYlR2CzaJC1Rd5dsx/YGrQFXBTJvYSd0ggMWVqVfb/taCsPBi7QYAVsGbdbYCRRQWLiwO7iwW1m4QXwceqwJZYuBmgDlwUxDG3losBNHrJoDXq+qbHRVBNNq7QoS+oNtIS5VkczFDIb4iLECOYKWLhMo8q7GhCQxICIVUwqG8XoviWi9XyG2HkLBwhiAsqvMBQMzqCAuQQyGTWF087me3cqkE6d3DAQBHcs1+OuFi5U1s9m3u7P4wDcTU/pYsDEFYFFR33IvLr1ivDOuJSy58x4IrxH6w9SJexiU2a0NY/VY8b0nr7NUGwsJV8GahlcWis6IMZoXdAPEeRkM5M1MD3mfnCGKWN9pauYTBx1UhO3dl3sWBqwklr62CN21qWBSfMgduxrmuI2FtsdBrLCLLTayJEKhe3hkDOF3VsrD+bYVUUbPFoqDanBHiylrB800O3BRQyaXoG8v6qZOXO647hISFMwRXSF0hYDQgt4J1Kj0iA10uPOaKkT3ZxXko1+ynkyks1T3LzoI3Zw3sMA3D+D6W2bLgCimv10Kj72TBU03B2+BNo95yc9uvyeEqoFFc86EJdRNcCYvaQpaVwElbdt0EV8idVBnVN7IKr0DnFhaAZUn6qhz2/+JOADyrLOttGrU80FJoTEg5rStmq6eCc/0dussUamrgptAeADA0WpXzlnmOrwAs59xQxlJu9WpW6l5YPM0J0R2llkVTcOYK4Xnb30dwXwrCospD4GZVLssklMibdX91hjgLEhbOCI5jFwdvAuoKkWteyjYlOoh1VA1lrLqhuxvZzPjerCbG3vPlFp+ZUO1wz3vgavLRwCtxQjUS/eMtaY7hgXIEKlinVlRDVguvhUXhcdZpBkYBMf1sX3NW0ttosArEbcIsQ1gbArC1DgiWgdgBrVNt0x5nFoviU2b/foxFPHdWhMA5oQJiU9xSHOdYJEuY0cYOcL3MuatMofoyVtodXNNcUTbBm+YYC6Xcc3wFwNxDwXGsT/vpSbYtbZZbd4wQR5Bnv5BiZ0CwXlq7QqpyWeybVMEW5hMsFubgTY9VN4UJSuJQyzXQBAZ3s8RZdFRIWDhDIrHJDMkxC4vk6CBLdbvEYQ4Xj9FkdAi4GZkcAaVMgtI6Lc6XmtVxH3OevrlYzw7TUAzvnWhZNRUseEp0h1S1rzgLE2/CkeIjqNU1v3jXhaoLqNXVIq82D7k1ua53dFasqDoPWHubxTUFWILSeo53DNBztghZ6WlWZVUZ6ihEzPA8j6zKLNRoa7C/cD8u11223cFZkSxBrHRrI8uAs+BNMb6iZQI3c2tykV2djVJ1Kbbkbmnb4DMhqLryIpuJZm9nz33NzhHiNeqK2H8X8RVGkxGlanN6qyuLhTAbjknzrVaKgFWmT7U5oNLGYuFuliyRWFYoVpsL//W/zuXuJt6E5CgmxIWJFQCUqkuhdlZ0raMhiELrGBxBNMYPZjVn7Fwhl6sbcYt0Jxafuc35WiJuXKr7CvbhdPlpr5o22Ow+P1nQcQM4SVi4wiqAUxAWvaKDXC48pjPqMGfjHDyy/RGb7Sq5FKNTmElt9zlz/fnetsFjPxivsHGDCHSLUEERswXPHpqLzIrM5p6RX+B5HksPLcW9v96LpQfdLDvsBVmVWbjxxxux4JcFuPb7a3HTjzdBa3Thz3Vmsdj6EnBuM/DZDEtwXa650JWzoDRnWSGC26T7KJeZAr9e+hU3/3Qzrlh3BR7c+iCe3PGk7Q52pZYBtH0sg7PgTWth4Wf0Jj3u2nwXbth4A6Z+MxXP7noW+wv3u9x/9+XdmPvjXEz/djqOlx73e3tEi0VFNkv5rStiv5MPi0IBsGRuVOex/5eduzLePPgmpn4zFQeKDri2WAiixNc0UwFxIsOjspbNtLsF8uaUZni2oA670/I4dZbL2J9ndj2DKV9PQWgwu09yKxpQr6vHPVvuwdRvpuL2X27vsAOeiDNXSIFd7EyArSvkclUjnpF9jTB1Hlsivvy87THznAuLisYKPLTtIdz2y23QOyvIZUe/+BDIJBwqGzQo7KDWahIWrhCERWmmKCxSrC0WdvUrzlaexaXaS/ij4A9o7Mo7T+rLYip2CcIiJE58//vGW7DNNAITzC4TaxoCfoYyeifqDZWsw/KRz099jtcPvO7VxewtH2Z8iK/OskWiLtdf9rC3e/YUMOtCbm0uADY4VbtKJ7UWFkKnVnrW8nrBUTZDFKwXyXbxFYBzV4gXgZv2ou5c1TkYTVZxLzI7iwXPt332hTNXiCh2/N+m/Np8VGmrbLadrz7vYm/gi8wvcK7qHIobivF73u9+b4/FFZLDVsgFmBVL7sKM7QqhlHz1JeY2E35Xu3icr899DQBYdmSZa4uFC1HiNVar1lbVMMtdGnLdBm6WqkstIiC6DzDyfpZSPeffTq1W5Y3l+C33N1RoKnC06hcAzBX7TdYGHC05CgDIrslGo7sF1joCzoI3rTNCACtXCCsNUFJegTiu2rL/tlcsjxvKLSXV7WLvqjSW++J0hWerhUouRUKPQwhOfRWbsw553L89QsLCFSmszC1/YAVC67PZJlW9ZVVIu5kPD4uCL6wvtHltSn9mTj1wsQI15jQx3LYGR2d8j/f1N6JbeAB6Rtn64Y0mIy7pt4vPfb2RG/QNWHZ0GdZnrce/jv3Lp/e6YtPFTVh5YqXNZ3jDmjNrsObMGoft1jeceEyDi2MKwsJkYLNwo4H5RAWOfAZc3MHcGqHdWZCePWJWSANL9QW8qutfaU43u6mvZREx0ewNOA7ilReZAJIq2eJabYF9oKq23rIUvTtffBPJrsl22CYVAh+dYP3bV2oqXe7XZARhUZMPHF3FHntazdQZ1haLsjMWt1l0mtPdS9Qlzl1jJpOVKGmisJDKxWDSmjomLHrqzOLNibVi9+XdmPrNVHxw/APLxuuWAQ9stayH5OQ9Ql+26dIPCFEBAI9vzn1ns1+NfdGwJlCpqcS5qnOed2wJ7NNNDVqg+AR73N0cbC24w2sLUFXbgBTtWdtjnP0FKL/AHgurU8cNstRRMaM2WKyGgjjzRHXAd+CkWqy/+KFX+7c3SFi4Ysh8oM80cAYNnpF9g6ggBUILzWb2hHSHegcNVrNg+5l875hg9I0Nht7IY8dZ84AUFI3fqtgMY0KfKIeV7DIrMqExWdS0t4O4gLU/73+Z/8Ol2ks+vd8ZOy/vBAAMiRnidZvOV53H0kNLsfTQUmzJ2WLzWl5tnsP+Lv23iiBAYs4dV1ew2YG12Dr9A/DnOva4/3XOYwgEiwXABoi6YjZgcBK3mRvCTHxIzBAkhTBLVkF9gWUHe4uFMIDED2aDQVtgX3mz6E8APMsEaIHF5S5WX3TY5u76aHFhERRjFpI8W4VYHggMuc3344SbLRZVlyyujMRhLt1mlZpKK4uF1fVZfo7FB8kD2aqXTcX8u9bXs74hrsE82DkRi4eK2Gz3cPFhh9dcsTN/p/i4SlOF2PgsSFSXkV9/EUqpEkpzoHKNrvnC4uYfb8bcH+fiQtWFZh/LZ+xdIcUnWTXVwChLRdqQRPZ9mwwovHQWwzmziBt4E5A6EwAPHFzBtgl1QZykMlvfB94KCwGN3uTT/u0FEhau4Dhg2isAgKskGRgYJWEzYsCpb7JObxEBNoOOmZmDWGe++RQLAuN5HlvPsCp4E/o4zh7+EESMGXcBUybe8eI7WX5SfMyD94uwqDcHOgnCwpsgrs05m8XH/zjwD5v3XKpjbUoOTRa3uRyMOM5yw5eft3Tyva5i2/UNQOYPbFv/2c6PIQ+0rW8gxFfEDnAbTCdYLCJVkUgMZpVRCxusrFJi3QKzsBADN9uwCJW9FUUQOy3UJsFi8ciQRzC7F/v+XVmfeJ63cZs4s1w1G46zLYQ1ZL5PS1iLWLtCBJeKhzgNk/DdWwcaC/77xGGA1EVxJW8wH1vdwPqbkErzui9OLBaCi/FizUWvYiJ4nhddrtN6sABzbeBeyMPZvTat5zRRWFdrq5t6BiJljcw1vCN/R7OP5TP2K5xau0GESYlEIgYB1+RlYqTEbPFLGgOMeYg9PvUdW39HEBZOVka27vOOlx63daN6QKd3bfVrz5CwcEfcIJTJu0HJ6TEv9KTblDXrAbGgzrWw2JFVhhq1HlkldbhY1gCFTIIp/WId9t9XuA8AYNSwwjZVLtbI+CjjI1zx1RXIqcmx2W4tLAD4JYOjXs9uwthA1l5PFgue522ERa2uVvS7G01GMbti5fSVSI9O93zMGLP5ufwccMkcGJg02nYmGtnL9fotHGeVLZDt9fLGwow6QhWBbsHMPGrzG9uvF9KCsQxeIwZvmr9PsU1DW+TjBIvFgKgB6BbCviNXwlNtUENvssT9tIjFAgBuWAFc+TybXU561qu36I16vH34bfH+Ey0W9SXM9A0A/a5xeJ+126dEZf7uheJcQPMKY1ljdrPITToEcFrIKs2uBCe/qyAsanW1Xn3HaoNadLn+ZeRfIONkqOHPQxHBBPhNfW5CqIIJ8Oa6Qqzj0PzRN/mMvSvEVX2RqL4AAFPxSYyVmGvA9BzPBERwPAvs3PYys3zKAthrdlgL7Hp9PS7WOFr3rDGYLBV8G3Udc4jumK22w2A04esj+Vj4vyOWNTn8AA9gs4kF9V134WVW8EgV5nTgqrdKW3JmsRiQEIr+CaHQGUz48c8CbDrBLBdXpsawZY/tOF/FBmCFbgAAoFLtZBU+ACv+XIE6fZ2tHxUWYRGpYpHNtVr/CYu4ICZ2dCadzQBhz8Wai7hcfxkqqQr9I5n5t6ienXdRQxH0Jj0UEgXig+IRaDbxeiUsSs9YrEcpVwJDb2cFoaL6AHdtdD8jFIRFxQVLypiHGagwu45URVqEhfVvbF1p0WiwVHhsyyJUQkR7nXltiAKzCbYF2mQ0GcVBrHdYbwTJ2MDq6re0t1C0iMUCYOLqqr8Bt693XZHSjtWZq/FF5hd4aKt5RhoQYQn0A8+CuuPTbd6jN+lh5C2z0BzObEGsL7aITU9lwL3FfJ8EcFqMDSwCJwRuhtien96ot0mL9jSYAUCdOZBRLpGjW3A3TE+2VOWUGqMxMn4kwswWv+YKC+vfvLyxvFnHahL2wkKwXtoLP/NaQ+mFXyOA06FOFc9cnBIpMPhmts+Bj9j/YQssLhYr7O+Ds5VnHfaxxtoapDNIUK3ueAXKOoWwqNMY8I+fMrE1swSbzK4Gf5BXqcZq9TjoeCtz1PjHnRY/EQZdwLmw4DgOt4xgRYmWbj6Lf+9gfsVrBzt2eAaTQTxelJK9Xq1xstS39edbCZvyxnKUqkvBgcOYBCaM6uxL1zYB4TPiAuPEbe7cISUNbFBLCk1Cr3AWTFfUwH4fIb4iKSQJEk6CIHOlSLfuFSFg7uQ3LM5CEcKsDeE9gKdOAY/s97ywU5R5YaH8Q5ZgLTclntV6yywuShXl3BUiEwpkadiaDXo1M7VG93XflpYkxrz4Wl0hy56pyjXHkjRzYHNCsboYWqMWcokcicGJokh09VsKg4owSGmMmnZTG+GPAlsXJDjO9prqd61D/I5927MbSyym9prLQEMFUGJ2WfSwndGqdQYcuFiBbZklyCys9TwxMlvHlNBhnNJspXRSlyS/Lt9W7NhZNJ0hWA5CFCHgOA4vjnkR1ybfAJMhEA0lU1GvNSJcGc5Oq5nCwtqC4rZ+TUshBIOrK5m1ofoSC4y1t16a7+FQI7tmq5OmWb7rEfdY4mnAAWMfdfpR9sLCU+mAisYK8THH6cSsxI5EM5x97YeIIAXun5iC97edx3u/nYNaZ4RSJoFSJkVMiBLdIwIQHiiH1mBCSY0GxbUaVDbooJBK0DcuGL1jgh2CJwFgZ1YZsvluWBm+GI/XvMcCwsY87LQNnoQFANwwrBv+ufUc6rTM1DUgIVR0kVhjLQISgxNQqgdqnQgDa2uBgbeYz4RBOyEoQRQBfhEW5nMMU4ZBIVFAZ9KhQd8gDhD2VGjYDRKlikJikHlANmfM5NWZhUUo89kKwsJlVghgGSyFjjxlkiU40tvVQwVhkbWJ/Y8d6BDFbY3QASqlSgTIAtA9uLvNeQCwXc1SSHftNoLNatoKVRgLPqsrBI78l22LTwcCwv3+UUIMSlRAFKQSqcffUrAAJQYlQmvQQmPUoFJTKQqStsT63uV5nvUL4xYB+//Ngl6d3P/2A8eJ8pNMjJRmAtW5FlEROxAIjhGPvXpfLt77zdIfAKzi7rheUZg+IA5T+8chLMDOmilYLKDDcJhnvk5SpXNqbYWEN8JC6CMEd0eYMgxLr/wH9h64CpdrGnEiv8ZvFgtrYXGp9pLlu24thGJ4NXmAeVkFdBvuWE1V6C/MyPtfa3kS3Rd45A9g33KWDeJipWtBeAbLg1Gvr8eZyjNum2YtLCDRIreiAcN6NCE+qA3pFMICAO6/IgWr9+Uip7wBz317wqf3JoapMHNQAq4ZHI/hPSIgkXAwmXis2pcLAAgadSeQNJ0NQC7K+FpbDGp1tajR1jgMuJFBCnz14Fg8++0JNGgN+OSuEVDJHQcfYeYQJA9CamwcMgqABiczOusL0HrWlF/HfLtJIUkIMZtxrYNLmwLP82IHGiIPQZA8CDqtzq3rQug8IlWRiA9iAkqwWBQ3sFUWBcERKPPCFWK9BDoA9J3m+4kIaYgCHko8C7PrSFUkq4ZqtlgUNxTDaDJCKpHarmYprMXhxToyLU5sPyYsDn3KntsvyuYnBNOtMJv1ZH0S9o9QRaBaW42ihiJUaarQPaRty4zrTXrx+gTYPROqCGUm7mELXL7P/po9VnIMfFgPcKWZbDZcbBYWQil/AG//moUVO1nAa1yoEvGhKmSXNaBarcfmU8XYfKoYcimHCX2iMWdoImYNSmB9hTlNtDtXhlSd87oJgMUKIJPIYDAZfHKFhChs+7hhPSJwuaoRGflVCIthfVpzgzethUWdvg4VmgpEBzhPgW0RAsKByN4s1uqP5Wybs/sjOhVGeTCk+nr8xF2J64bYpSxH9QZmu0/nF66PkXEjsfPyTmRVZsHEmyDhnDsMhAkZAHBSDd799RzqtUbcOKyb61VV2xkdo5VeEKKS4/3bhmH94Txo9CZoDUaodUaU1mpRVNMIwcIYqpIhPkyFqCAl1HojsoprUVijwWd/5OCzP3IQF6rEzIHxCFLKkFPegFCVDLeOSgKUKW4/39piATA/muCGsGZQtzBsfnIiTCbepoS3NcJsIFQRikEJMfi6ANAaHTtp61oK1h2iKCxCrYRFMy0WaoNazD4JVgQjUB6IKm2VWyEgCJ+oAIsLQRQWaiYsBMHhlStEEQREJDOzfvxgS4liX7CfVaTOcLu7tTgCmPVFwklg5I2o1FQiJjDGYlatL272ssl+Jaa/eRVL88WfPLFFPkYYZAQhLVosPMRYhCvDEamKRFFDUcsFcPqAfU2FysZKcfbuDuE8YwJiUKWtQmljKS5H9kMSwNJUxYwB9v1vzCgQRcWL1/THfVekQCrhYDCacKKgBjvPlmLzqWKcL63Hzqwy7Mwqw8pdF/H9oxMQ0G04cOZHXC/dh1BDJVvXwkmQsGB5GRw9GMdLj4tuSXcIfUSw3DZOYGhSOH76sxDH8qoxy7xAVnPTTe3janJrcltXWADMQlGZze5bwPn9oQjEumFf4j97spE6YChmNyGjR7g+BkUPwv6i/ajX1yOvNg/JYclO97eOOZHJdCiobsTffziFpZvO4M5xyXhqel8oZe07W6TTCAuABUJemRrjsN1gNKFBZ4RcyiFQYXvKGr0Ru8+VYfOpYmzLLEFJrRar91tSM++ZkIIgL1SitcUCAE6Vn3IqLARciQrAYrEIVYQiPYG5MnhOi9JaDWJDLfEdZeoy8XGlphKNhkYEyAJsLBZCx9jcyGvh/KScFCqpyishICjvSFWkaJkQgjeFjk5w1XgajESu/4DFR4x7rGkL/ajCgLAezAQ6aqHNLNIZ1hkhACCVSBGtikZpYylKG0uZsBDiFk7/AGiqWSxDU1ZK9TexVmufyAKAnj6Ws/YSQQgLFgtPgbjCoBKhihCvy/YgLOzXcqjUVLrs/K0R7oEIVQS6h3TH8dLjOCqXMGFx4mtmNZIFAMlXoKZRj3/8zKxaj0/pg4WTLBY0mVSC4T0iMLxHBJ6+Og0XSuvxy4kirNqXg7PFdXhry1n838DhkAEYLMllb0oY6vQ+EER9akQqjpce9+r7tY6xsGaMeUmCgxcrcPMkc3/SzGBw+/YU1BdgJPwf/+OWxOEsXgsAVOEurYzbSoKQwyfgjhTHZRe8QSiQFaoMxaDoQThachS7L+92eW1ZW6LDgoxYfN0ArDl4CdllDfh4Vzb2X6zAuoVjEaBov+KiUwRvekImlSAsQO4gKgBWPvXqgfH4561DceTv0/DZPSNx84juGJUcgX/MGYgnp3oXgCd0osNj2ezBm9KtrhBu2jBlGKKD2I3MSQw4lmcbPV3aWGrzXBi0hWhwa1dIczsCwSITrGDxKN7ERFjHWAiWiTp9Hep0daIrRNjuVVYIwITApGeatXog5q0GbvoPcM07Hne1t1gAQHQgm1m9eeBN3PLTLciJMFfoE8qRxw1s2iJTTrhYcxEZpRlNe7P1ompTXrRYVqzgeR4avbFZ2VQOrhCZl64QZYT4vbYHYWFf2M7bbBXhHgiWB4v3/58m83VcZ47FSb8FUIVhxc5slNdr0SsmCI9Pcd+39IkNxpPT+uKftw4FAKzal4v/OyiHibealLhYVE249/qGs8+o1lbbpDE6w5UrZEBCKKKCFGjQGVFaLRWP1xyszf1AG2WGWGeATPk/2wJ6ZjR6I45cYtfB6GQv47jsEPq0IHkQpvdkmTa/5v7qcn/r70atV+O+K1Kw7ekr8fEdIxAeKMef+dV4aeOpdr1eS6eyWDQXpUyKKf3iMKVfnOed7RBiGMYmjMWx0mMOdSR8wdpiIQzgAPDwV/sws19vJEUGoEdUEE405Nq8r7ChEL3Ce9lYLIR88ea6QkRhYTaTeiMErIP6AuWBCFeGo1pbjcL6Qlb6GJbUVa+CN/1Ft+FeF4oSBrwolWW2EhsQi0xk4kQ5i+W5/te7sC86FSHlZlP6kNv90kye5zHnhzkAgN/m/oaEYO9SJkUShrBU2qAYh4j1vAo13tuahd/PlKJOa0CgQor+CaHonxCCtLgQpMaFIDk6CLEhSo9BdfauEPHaMDQ4DcqztlgI11WLpZz6gH0pfvvBzxXCPRAoDxRnoUWwG8RHP4RajR5rDjBr6Auz+kMh825eNzktFgsnpuDTPTlYd6IKS1VWA8rohU7fI1y3vcJ7gQMHHjyqtdVu3Q2CVdLe/SORcLiibzQ2ZhQiq5Cdl7/STSOUEajSVrWNsEgcysSFMhQYca/DyzzPY+nms6jTGBAXqkT/BOfxdZ4QhYUsCOMSxuGtQ2/hRPkJFNQXiOnr1lhbLHQmHXRGHRRSBWYOikeISoY7/nsQ3xy9jOJaDZbOTUe3cB/Xv2kFSFj4CaGk96j4UeD+5FDcUIzyxvIm+Q3FGAtlKGQSGeQSBfQmHTiJFltOF4v7qRLOQh5ueV9BXQHqdfVi1H1SSJJoGWhu8KbQ6QjCwlOtAsDWYgGwLJVqbTVOlp+E3qQHBw6xAbE2x20vaYcCQhxLVIBFWAgWC2s2h4ZgntA3DrvDL59tPbCdrjjtICx4nsd7R96DhJPg6ZFPOx5ApgTu2+Kw+bfTxXhyXQYa9ZZ0RLXOiKOXqnD0ku0Ar5JLkBYfitnpCbh3AosFsEewhtkHb5p4EzRGDQJkth2fcH2GK8PF66dc0wYDix1C0TNhsPPWimI9IxVceyX6OuDO74FTG1jQcfwgrN2VjTqtAX1jgzHVSVE8d/x1Vn/UaQz4+kg+vjRdjTskvwFDF7hc80MYnGIDYxGhikClphIVje4DJIU+wt5iAQAT+8ZgY0Yhjl7UAWGsj2pOJofw3aZGpOJg8UGxCmerIlMCC50vgLfvQjle/SkTWSXsO1l6Uzpk0qYZ+K2FZ0xgDEbHj8bB4oNYkbECr1/xus2+PO9YJblB3wCFVAGAVWlecuNgvPzjaew5X46rl+3ClWkxGJMSheToIEQFKaCUSWDkefSJCW5ym5sLCQs/IdyUcYFx6B/VH5kVmViftR6Lhi7y+VjWFgsACFEEo1JTiTdu6gudOg75VY3ILW/AMV0DDAB4QzA4WT3OV58XCxVFqiIRJA8Sj1Gnq2tWRyCcnzBoeIqx4HnewY2QHJaMM5VnxLLBUQFRkJvTRb12hbQyQhCckGYKQBRD1uR1GwrkHAeuetFvbhDrtVSE9Fz7tq3OXA0AuGPAHWJFVHfsPV+ORWuPQW/kMSYlEs/NTENqXAhKajU4XViLM0V1OFdSh/OldSioaoRGb8Kf+dX4M78aP/5ZiIcm9cawHuFICFOJ15K9K8RaSDToGxyEhTDoRagixAWvnFWrbW2E2iSDogdhT8Eer60owj0QJA8SLXAlDSXMTWF2VWgNRny2l6V8Pjipl9sYK2sE8RgoD8Q/bliI128YBKN6LJDzOzBgjtP3NBoaRb9+lCoKkapIJiw8WGBcuUIA4Kq0GMgkHM4VGRESxtLb1Qa1jUXVF4TvNjWSCYs2sVi44KOdF/D2Fla+O0AuxRNT++IqH4WgNdbXBwA8NuwxHNp8CBuzN2J6z+m4MslSBvxE+QkUNhQiQBYg1s+p19eLMV5Hio+gdw8em56ciGe++RPH86qx6WQxNp0shj2HX5yGmBBlk9vdHEhY+AGjySheBEGKIDww+AE8vfNprD69GnN6z/E5jU4QFtZR9pWaSvTvpsSwWEt2ypwf9LhYA+jrBkARcQinyk+J1oH0GFYdUOgkTLypWR2BYJERjucp2LJOXyf6dCPNVSB7hbFANaFccnygpYaH18GbrYwgLIQy1YBzi8VliQn4v1K/LjpmLSacLdRkXcHvUu0lj8KivF6LxeuPQ2/kcc3geCy/bZg4owlRydEnNgRzhlr21xtNyK9UY8/5crz7axZOXK7BorWsNHhYgBz94kPQKyYYF7TMrSUD+w0lnASBskCoDWrWqQZYH1Mvfqc9QnqIglJw37UVar1aFMKCsPDWYiG4cwJlgZa6Mfo6NOgbxOv6+2MFKK3TIj5UhTlDHc3frsiuzhbF49GSo/j06k8hC4liMRsuEISbQqJAkDwIUaooXMAFj+fjKngTAKKClZicFottZ4ohhQJG6FDeWN7k/sTaYgG0UYyFEz7dfVEUFQvG9MBzM/s51hLxEcG9K3xXQ2OHYl7aPKzPWo+ndj6FJ4c/iRv73ogQeQg2XtgIAJjaYyoOFB1AeWO5KExqtDV4aOtDMMGErTdvxXcPj8exvCocuFiBI5eqUFzD6jPpjSZIJZzNitutDQkLP2CdahosD8a0HtMwOHowTpafxIJNC3DPwHuQHpOOHiE9EB0Q7dFqIJiWBWuDs0FXb9KLnbGscSgQcQhnKs6izuyyEIKElFIl5BI59CY96nR1Te4IhHMU3u/JwiB0bsHyYHFFREFYCDMjYXYHeA74awusBxtrX6i1xSJEEYI6XR0LmPXzSqbWFosL1Y7CwrqC36XaSxgV7zoThed5PPftCZTX69AvPgTL5g31aCaVSyXoFRMMNZeLr3qn4cejjdiVVYbssnrUNOpxMKcSB3MqEdS7EhIF8PcNFzH8ofGIC2VZQ2qD2uH6yK9nFSEDZYGIDYxFgLkceoWmAmq9us2KZAlp0CHyEPQMZeuDNMUVEiQPQog8BHX6OpQ0lKBXeC/ojSZ8vIull95/RYrXsRUAxLV1AOBQ8SFcqL4gDsauEOOCAtiqyWKAbKP783FnsQCAm0d0x7YzJTDpYgBFAS5UXxC/K18oU5dBY9RAwknEUv/WGW5txe5zZViymWXsPDsjDYuu6uPhHZ7heV6clFn3vc+Peh5Vmir8duk3vHvkXbx75F0EyYPEa+m6XtfhVPkplDeWi33vkZIj0JlYee/dl3fjpr43YWRyJEY2Mai0JekSWSEtjXAxKCQKKKQKcByHZZOXoV9kP1RqKrHs6DLcs+UeTPlmCv66568ejyfkiAvCwlnxqIvVF6E36REiD8HiCbNgMgTBBCPy6i6BgxS62jQYTcz1IXQUzQm4Ei5ue4uFYHK1x7pzExCEhUBCkCVmoD1aLISZdagi1KazjQm0pDRPSJwAgGUU+DtK29rXml2d7bAqonUFP0+r13554BJ+P1sKhUyC928b6rQwmzNya3Jxx6Y78NDvC3DvpHD8+tQknH5tBn554gosmzcET0ztC7mCBQhX1Mrx6Jpj0BlMLn9PoXBTz9Ce4DgOoYpQ8Tq3z8poTawtU75mqtibugXBLNRq+e7oZeRWqBEZpMD8MR5KztshrBkkcKbCfdVGwKp+jNl6KdyDns7Hk7CY0i8W3cIDoFPHOW2btwjXba+wXqI1V7RutRGXKhrw+FfHYeKBW0cm4dHJzqto+orOpBOrIluLZrlUjrcnvY1Xxr0iru7coG+AQqLAgv4LMC5xnMM9dKjokPj+Hfk7fFoltbVpksXiww8/xDvvvIPi4mIMGTIEH3zwAUaPdr9CZGdGLCyjsBSWiQ+KxxezvsBPF3/C9kvbkVubi4L6AmzJ3YK/jfmbyzLYgFWMhdLWYmF94wlm8LTINCyc1Ae/lPVFdn0GAEBf3wfPrL+AT3YW491bhiBUEYpKTWWzMkN8Dd4UBhDrYLEeobad6vhEy7oJwk0nLGwml/h39u8rGr0R5yvZYC0U9xKICbAIi9EJo7Eldwsa9A2o1laLvlCB0loNNmYUYvf5MlyuakRhdSMM5tROlYylQYcGyG3+C3/HSy0dt86kQ15dHlLCmCuM53kbi4UQW+OMjPxqsXbCX2f2Q79472NA9hTsgZE3olZXi2d2P4MvZn0BpUyKgYlhGJgYBr1Rj8+/ZMIiWB6Ko5eq8OpPpy3rhdgJT6Gd1jn8SSFJOF1xGpfrLnucjbcUgrBIDEoUhUWJusRSXdUJtRo98ivVyKtiA3ZFHQee5xEXGIcL1RdQ0lCCinotlm1l2UKPTu7tc+XE7Gpm6ZByUhh5IzIrMjGnj/PYCgExaNosKITz8TrGQu5cWChkErw0ewAe+yUecgCfHdqHP44MQ5BCBr3RBK3BBI3eCL3RBIOJh1TCIVgpY38qGUJVcgQrZTij2QsAiJClwGRUiPEE5Y3l6CH3TXj5gxq1Hg+sPoKaRj2GJoXjtRsG+q28uHX/KEwQBaQSKeamzsXc1Lmo0dagUlOJ6IBoh8mb0PceKrYIi535OzHyy5H4ZvY36BPRfMuKv/FZWKxfvx5PP/00Pv74Y4wZMwbvv/8+ZsyYgaysLMTGNj3ApSMjRLnbV6xTyVS4JfUW3JLK/KE3brwRF6ovYF/hPsxKmeXyeGIdC4VtJUNrl4sgLPpFsloF1/SdiA+OZ0AuUeDG5CfxY0UjzpXU48aP9qHHIDZIN6dIlr148uQK2Za3DYCteBAimwWsX7M2E6r1arfCy5/wPI/cCjUO5VTgUE4VjlyqRFG1BjqjCfKIP6CKB05fkuHWlftxx9ieuHZwgk1Ni/jAeMQGxqJUXYr8unxEqCKg1hnw2+kSbDhegL3ny+CqRESDzogGnRGFNRonr/IITisAJwFMhiBIZA24e91n6K2YjdAAOTh5hc0MNKviIk4V1EAll6JMk4d/nXgDN/W5BVH8ODz/3QnojCZMHxCHe8Yn+/T9CIG2AHCi7AQOFR/C2ARLISEhcFPCSfDeLWPxwOpjWHMwD936syqt9oXjBMGZEmqJFRKERWvFWfA8D72Rh8ZghEZvhNHE40hRBgAgISgRvcJ6IVQRilpdLQ6XHBbPl+d5nCmqw46sUuzMKsXRS1Uw8UBAjxLIgoCPdxTgwoVjUCWw6yOnqhDrfj+G0jpWt+KOsb67DQQX2Ozes/HDhR88rjMB2Fa8BeCVBYbneY8WCwC4ekAcpp0dgr31m1DPX8ae877HRqi6/wl5CLDnlBJjDm5HRGoYGtGIzNJ8KPhYyKQc5BIJpFIOMgkHCcdBwgESjgPHwa9riuSWN+DJdcdxvrQecaFKfHzHCL9WtRT6R5VUBZnE9XAbpgxz6POs+/3ihmLxWkgMSkRhQyEMvAFrz67FS+Ne8lt7/YXPwmLZsmVYuHAh7r2X5f1+/PHH+OWXX/DZZ5/hr3/1bOZvKYobisWS063N56c+BwD0j+rvdr+J3SbiQvUFbLu0DUNihrjczz4rRLjAShpKxFx7oU6GICwW9F+AEEUIpvaYitjAWCyerMPffziFX04WobhKAlkw8Oj3a8BVl0AuZTeqMN4JFnyHYB+e7cPzAKLPQhIEvP9bHn77Yz9i4piYyqsux5dHMsABYIHuHHS8BvsL2YAUbBiO38+WgAPrFJKDByC3PhOjY6bhwMUqmN8CDpyYVrvp7J+IUEaLnQgH9joH83Nzv8JZdTYGIw+TiYeBN8Fg5Nkfz8No5GE0maA3sf8GIw8jD1SrdThfUo8/L1ejot5uWWIO4GSARMlM2UZdBA5eZvEESzadwcS+MegXNAU1xgJcLuyGQC4WQCk+P7IbjTWl2HOuDGqd2UwpBdK7h2Fa/zj0jglCXKgKCpkEPM+sInUaA+q0evZfY0CdRo96rQHZ9UdwSqsDx8vAVc0EYr5DhWQn8i+mAjwHZdxmyEMBky4KEkUFChsKcP0n34I3yRCQtBpSZRlOlZ2B+tJC8IYQpCYG49lrY1Cs9n71XyNvxOFittz3kJgh+LPsT6w5swY9QiyzSsEFE6oIxbT+CfjHDYPw2k+nUVnHQRYCLP5uB55qqIZCxkEhlcIQfQxQAF/90Yjt+/ehb1wIKmVMrG7LzgDU6eAgXHfOrkdevGYt1y3bl7e+Zs37aPVGVKp1qKjXobROg9JaLUrqNNDqLX0FJ6tHYPIWcBzwyeZQ/LRjD5TxwwBuF17dsQoDVI0or9fiTFEdyuq0lvZIgaggOXilBnoAUiix5XQxFCVqKGOATw8egKYkDAEBUrw2ty8qtSWA1ds9oTPqRLF1fe/r8cOFH3C28iwK6gvMd4NzhPfYu0Ks+w97NAaNuBqqO2HBcRxemzUdU75ZApmyAi/OiYZWz0EulUApk0AhlUAuk0Am5WA08ajXGqDWGdl/rRENWgN21BVDywNR8hQU64zg61SQBQKPf7sFhnrPi6VxHCDlOLEvsAgPwPprEfocTnwfJ/ZRHGfOXGtgCzmGBEvx7vwRMEkrUeh+IWmfEMrENyV2SJioFjcUY9nRZQDYeiNvT3ob357/Fh9lfITNOZtxz8B7nIqWuMA4l9a2lobjfXAM63Q6BAYG4ttvv8UNN9wgbr/77rtRXV2NjRs3OrxHq9VCq7XcTbW1tUhKSkJNTQ1CQ/2TlgcAU76e0ja50GbkEjl+mPODg7nfmsPFh3Hfr/d5fcy9t+1FmDIM7xx+B//L/J/Tfb6d/S3SItNcHuOXE0V4Z++3qAj6xOvPdUdjwa0w1A6DNPACAnv+x+2+Rk0c1DlP2Wzj5BWQhZyCvmo8wNu6O4L6/gMSWfuJsRB4aOAzMFSPw3/35NisRCmgSvga8vBjLfLZi4Yuwm2pd2LWhqtRb7C3OHEYp3wVBzT/AM/pnb7fH0QoI/Dp1Z/i5p9udrlPcmgyfrqRrRJ5urAGj/z6F1RJDrrcv+Hi4zBpWUCsPOwwVInf+bfRTcBQ3weN+Q8AAKQBFxGY7Ns98/fhy/HbsRDsLf4Z8nj/nU+EMgI75u3A2LVjoTE6s2455/lRz+OOAXfgRNkJLNjkehE1a6ScFMfvPO7WKsDzPCatn9Ts6pv7btuH7Zm1eOf431ArbZn7p73QI6QHfrnpF5/e88aBN7Aua53NtnXXrsPA6IEw8SZcs+EalytpA8COeTv8vv5KbW0twsLCPI7fPlksysvLYTQaERdnW5kyLi4OZ8+edfqeJUuW4NVXX/XlY5qEQqoQsw9aGyknxSNDHnErKgCWZjQibgROlZ/yeMxxieNEi8XkpMn4+eLPDm6HITFD0DvcfZDRtekJuDb9cXxxKhYrT/7bnBbrjZZ07FgiVVF49fbbcLlciaP50fi9ZhO0cC7mOMgQg1kI6R4Gk3mmyWaZoeCRAj7O/FzYDqBWPxqN0r1etM0OngecdIQuu0bzLIazMrG6IlIViTmpU5AUmoSHr+yNPy6U41heFUprtVDrjGjQGVBmnIAC/hxM0LLjmc23zYEDh+t7X48H0x+EhJPgseGPYvmx5eKsUsJJsKD/Ajw5/EasyCjGxuyNaNA3oNHQCIVEgfsG3Y9vz3+L8maKbQknwR0D7kBaZBqu732901LEEk6Ca3tZlpMemBiGv0+5FS/vOwOtQZhUWOxhycFpePL261GjMeFsUS1Ol8hxit8FPZpXzVGEc3woWr7M1jHA9pIJlgfjnzNfQ1JQKi6WNeBs8QCsyzuMQs1p8UDurpWkkCRc22805g0OwqWaeNz36z5UayudXZY+IeEkuDn1ZkglUtyadivWZ633Ko0wQhWB8d2YqzEtMg0DogaI8RruuCblGo+uBo7jcEvqLfjyzJdNthLPSJ6BEGUIbhgWgsCIBXh1/wVojY7mHN7hgSfc72j/qmDVaCk4sKycOwb4XjTvqqSr8Gvur1Ab1JBwEszvNx8DowcCYNfFQ+kP4e3Db0NvarlJRVPxyWJRWFiIbt26Yd++fRg3zrKg0XPPPYddu3bh4EHHGUprWSwIgiAIgmg5WsRiER0dDalUipIS2yV4S0pKEB8f7/Q9SqUSSmXbWBIIgiAIgmhdfKpjoVAoMGLECGzfvl3cZjKZsH37dhsLBkEQBEEQXROfs0Kefvpp3H333Rg5ciRGjx6N999/Hw0NDWKWCEEQBEEQXRefhcWtt96KsrIyvPTSSyguLsbQoUOxZcsWh4BOgiAIgiC6Hj4Fb/oDb4M/CIIgCIJoP3g7ftNaIQRBEARB+A0SFgRBEARB+A0SFgRBEARB+A0SFgRBEARB+A0SFgRBEARB+A0SFgRBEARB+A0SFgRBEARB+A0SFgRBEARB+A0SFgRBEARB+A2fS3o3F6HQZ21tbWt/NEEQBEEQTUQYtz0V7G51YVFXVwcASEpKau2PJgiCIAiimdTV1SEsLMzl662+VojJZEJhYSFCQkLAcZzfjltbW4ukpCTk5+d32jVIOvs5dvbzAzr/OXb28wM6/zl29vMDOv85ttT58TyPuro6JCYmQiJxHUnR6hYLiUSC7t27t9jxQ0NDO+WFYk1nP8fOfn5A5z/Hzn5+QOc/x85+fkDnP8eWOD93lgoBCt4kCIIgCMJvkLAgCIIgCMJvdBphoVQq8fLLL0OpVLZ1U1qMzn6Onf38gM5/jp39/IDOf46d/fyAzn+ObX1+rR68SRAEQRBE56XTWCwIgiAIgmh7SFgQBEEQBOE3SFgQBEEQBOE3SFgQBEEQBOE3Oo2w+PDDD5GcnAyVSoUxY8bg0KFDbd2kJvHKK6+A4zibv379+omvazQaLFq0CFFRUQgODsbcuXNRUlLShi32zO7duzF79mwkJiaC4zj88MMPNq/zPI+XXnoJCQkJCAgIwLRp03D+/HmbfSorK7FgwQKEhoYiPDwc999/P+rr61vxLFzj6fzuueceh9905syZNvu05/NbsmQJRo0ahZCQEMTGxuKGG25AVlaWzT7eXJd5eXm49tprERgYiNjYWDz77LMwGAyteSou8eYcJ0+e7PA7Pvzwwzb7tNdzXLFiBdLT08WCSePGjcPmzZvF1zv67wd4PseO/Ps5Y+nSpeA4DosXLxa3tZvfke8ErFu3jlcoFPxnn33Gnz59ml+4cCEfHh7Ol5SUtHXTfObll1/mBw4cyBcVFYl/ZWVl4usPP/wwn5SUxG/fvp0/cuQIP3bsWH78+PFt2GLPbNq0iX/xxRf5DRs28AD477//3ub1pUuX8mFhYfwPP/zA//nnn/z111/Pp6Sk8I2NjeI+M2fO5IcMGcIfOHCA37NnD9+nTx9+/vz5rXwmzvF0fnfffTc/c+ZMm9+0srLSZp/2fH4zZszgP//8c/7UqVN8RkYGf8011/A9evTg6+vrxX08XZcGg4EfNGgQP23aNP748eP8pk2b+OjoaP6FF15oi1NywJtzvPLKK/mFCxfa/I41NTXi6+35HH/88Uf+l19+4c+dO8dnZWXxf/vb33i5XM6fOnWK5/mO//vxvOdz7Mi/nz2HDh3ik5OT+fT0dP7JJ58Ut7eX37FTCIvRo0fzixYtEp8bjUY+MTGRX7JkSRu2qmm8/PLL/JAhQ5y+Vl1dzcvlcv6bb74Rt505c4YHwO/fv7+VWtg87Adek8nEx8fH8++88464rbq6mlcqlfxXX33F8zzPZ2Zm8gD4w4cPi/ts3ryZ5ziOLygoaLW2e4MrYTFnzhyX7+lI58fzPF9aWsoD4Hft2sXzvHfX5aZNm3iJRMIXFxeL+6xYsYIPDQ3ltVpt656AF9ifI8+zgcm6E7eno51jREQE/5///KdT/n4CwjnyfOf5/erq6vi+ffvyW7dutTmn9vQ7dnhXiE6nw9GjRzFt2jRxm0QiwbRp07B///42bFnTOX/+PBITE9GrVy8sWLAAeXl5AICjR49Cr9fbnGu/fv3Qo0ePDnuuOTk5KC4utjmnsLAwjBkzRjyn/fv3Izw8HCNHjhT3mTZtGiQSCQ4ePNjqbW4KO3fuRGxsLNLS0vDII4+goqJCfK2jnV9NTQ0AIDIyEoB31+X+/fsxePBgxMXFifvMmDEDtbW1OH36dCu23jvsz1FgzZo1iI6OxqBBg/DCCy9ArVaLr3WUczQajVi3bh0aGhowbty4Tvn72Z+jQGf4/RYtWoRrr73W5vcC2td92OqLkPmb8vJyGI1Gmy8KAOLi4nD27Nk2alXTGTNmDFatWoW0tDQUFRXh1VdfxcSJE3Hq1CkUFxdDoVAgPDzc5j1xcXEoLi5umwY3E6Hdzn4/4bXi4mLExsbavC6TyRAZGdkhznvmzJm46aabkJKSguzsbPztb3/DrFmzsH//fkil0g51fiaTCYsXL8aECRMwaNAgAPDquiwuLnb6GwuvtSecnSMA3H777ejZsycSExNx4sQJPP/888jKysKGDRsAtP9zPHnyJMaNGweNRoPg4GB8//33GDBgADIyMjrN7+fqHIGO//sBwLp163Ds2DEcPnzY4bX2dB92eGHR2Zg1a5b4OD09HWPGjEHPnj3x9ddfIyAgoA1bRjSV2267TXw8ePBgpKeno3fv3ti5cyemTp3ahi3znUWLFuHUqVPYu3dvWzelxXB1jg8++KD4ePDgwUhISMDUqVORnZ2N3r17t3YzfSYtLQ0ZGRmoqanBt99+i7vvvhu7du1q62b5FVfnOGDAgA7/++Xn5+PJJ5/E1q1boVKp2ro5bunwrpDo6GhIpVKHyNeSkhLEx8e3Uav8R3h4OFJTU3HhwgXEx8dDp9OhurraZp+OfK5Cu939fvHx8SgtLbV53WAwoLKyskOed69evRAdHY0LFy4A6Djn99hjj+Hnn3/Gjh070L17d3G7N9dlfHy8099YeK294OocnTFmzBgAsPkd2/M5KhQK9OnTByNGjMCSJUswZMgQ/Otf/+pUv5+rc3RGR/v9jh49itLSUgwfPhwymQwymQy7du3C8uXLIZPJEBcX125+xw4vLBQKBUaMGIHt27eL20wmE7Zv327jW+uo1NfXIzs7GwkJCRgxYgTkcrnNuWZlZSEvL6/DnmtKSgri4+Ntzqm2thYHDx4Uz2ncuHGorq7G0aNHxX1+//13mEwmsXPoSFy+fBkVFRVISEgA0P7Pj+d5PPbYY/j+++/x+++/IyUlxeZ1b67LcePG4eTJkzYCauvWrQgNDRVN1W2Jp3N0RkZGBgDY/I7t+RztMZlM0Gq1neL3c4Vwjs7oaL/f1KlTcfLkSWRkZIh/I0eOxIIFC8TH7eZ39FsYaBuybt06XqlU8qtWreIzMzP5Bx98kA8PD7eJfO0o/OUvf+F37tzJ5+Tk8H/88Qc/bdo0Pjo6mi8tLeV5nqUT9ejRg//999/5I0eO8OPGjePHjRvXxq12T11dHX/8+HH++PHjPAB+2bJl/PHjx/lLly7xPM/STcPDw/mNGzfyJ06c4OfMmeM03XTYsGH8wYMH+b179/5/e3fP0kgUhXH8StYJBjEoXlQEE8Q0YmVhGYRAIKVVsPIFLLQSjJDGJl/BDyB+BDsRQa1UsBA7ITAhjY0WEoiC6LPFsgHf4rJe9k6W/w/SJMNwDmeKhzBnRplMJjLrmO36azQaKpVKOj09VRiGOjw81PT0tDKZjB4fH1vniHJ/q6urSiaTOj4+frWq12w2W8d8dV3+XnPL5/O6vLzU/v6+rLWRWeX7qsdqtapKpaKLiwuFYai9vT2Nj48rm822zhHlHsvlsk5OThSGoa6urlQul9XV1aWDgwNJnT8/qX2PnT6/z7zddInKHP+LYCFJ29vbGhsbUxAEmpmZ0dnZme+S/kqxWNTIyIiCINDo6KiKxaKq1Wrr94eHB62tram/v1+JREJzc3O6ubnxWPHXjo6OZIx591lYWJD0a+V0a2tLQ0NDisfjyuVyur6+fnWOu7s7zc/Pq7e3V319fVpaWlKj0fDQzXvt+ms2m8rn87LWqru7W6lUSisrK+9Cb5T7+6g3Y4x2dnZax/zJdVmr1VQoFNTT06PBwUFtbGzo6enpH3fzsa96rNfrymazGhgYUDwe18TEhDY3N189B0GKbo/Ly8tKpVIKgkDWWuVyuVaokDp/flL7Hjt9fp95GyyiMkdemw4AAJzp+HssAABAdBAsAACAMwQLAADgDMECAAA4Q7AAAADOECwAAIAzBAsAAOAMwQIAADhDsADgxOzsrFlfX/ddBgDPCBYAAMAZHukN4NsWFxfN7u7uq+/CMDTpdNpPQQC8IVgA+Lb7+3tTKBTM1NSUqVQqxhhjrLUmFot5rgzAv/bDdwEAOl8ymTRBEJhEImGGh4d9lwPAI+6xAAAAzhAsAACAMwQLAE4EQWCen599lwHAM4IFACfS6bQ5Pz83tVrN3N7empeXF98lAfCAYAHAiVKpZGKxmJmcnDTWWlOv132XBMAD1k0BAIAz/GMBAACcIVgAAABnCBYAAMAZggUAAHCGYAEAAJwhWAAAAGcIFgAAwBmCBQAAcIZgAQAAnCFYAAAAZwgWAADAGYIFAABw5icb84u+AO4ytwAAAABJRU5ErkJggg==", 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", 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", 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" ] @@ -744,7 +732,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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+e/fuLpdxxFXnTZ5n72HXrl35rl278mazmed5nv/yyy/59PR0XqPR8AMHDuR///13r8pNeZ69d3PnzuVTU1N5tVrNJyQk8BMnTuQXLlxot9yQIUP4hIQEj9veuXNnHoDTH8ft4XmeX716NQ+Af++991yuc/369S5LlRcuXMj36NGD12g0fNeuXfm3336bt1qtDZbLzc3lr7vuOj4sLIwPCQnhr7jiCv7UqVMeXw9BNDccz3uQ7wRBdGiKi4uRmJiI559/Hs8991xLb45fVFVVISoqCu+8847PDc8IgvAN8lgQBOGWJUuWwGKx4LbbbmvpTfGbTZs2ITk52euJowRB+A9FLAiCcMqff/6Jo0eP4rnnnsP48ePxww8/tPQmEQTRBiBhQRCEUzIzM7F161aMGjUKX375pV+zQQiC6HiQsCAIgiAIImCQx4IgCIIgiIBBwoIgCIIgiIDR7A2yrFYr8vPzERoa6lPbY4IgCIIgWg6e51FVVYWkpCS3E3ybXVjk5+cjNTW1uZ+WIAiCIIgAkJubi5SUFJf3N7uwENsT5+bmSuOtCYIgCIJo3VRWViI1NdXjmIFmFxZi+iMsLIyEBUEQBEG0MTzZGMi8SRAEQRBEwCBhQRAEQRBEwCBhQRAEQRBEwGh2j4U3WK1WGI3Glt4MooOiVquhVCpbejMIgiDaJK1OWBiNRpw9exZWq7WlN4XowERERCAhIYF6rRAEQfhIqxIWPM+joKAASqUSqampbhtwEERTwPM8amtrUVhYCABITExs4S0iCIJoW7QqYWE2m1FbW4ukpCQEBwe39OYQHZSgoCAAQGFhIeLi4igtQhAE4QOtKiRgsVgAABqNpoW3hOjoiMLWZDK18JYQBEG0LVqVsBChvDbR0tA+SBAE4R+tUlgQBEEQBNE2IWERADIzM/Hoo4+6vD8tLQ3vvPNOs20PQRAEQbQUrcq82V7ZtWsX9Hp9S28GQRAEQTQ5JCyagdjY2JbeBIIgCKKZqDdZoFN33GoySoUECLPZjAcffBDh4eGIiYnBc889B57nATRMheTk5ODKK69ESEgIwsLCcMMNN+DixYvS/S+++CIGDhyIzz77DJ06dUJISAjmzJkDi8WCN954AwkJCYiLi8Mrr7xitw3z589Hv379oNfrkZqaijlz5qC6ulq6/9y5c5gxYwYiIyOh1+vRp08frFy5EgBQVlaGW265BbGxsQgKCkJGRgYWL17chO8YQRBE+2PJlrPo9+Lv+Hn/+ZbelBajVUcseJ5HncnSIs8dpFb6VBnw+eef4+6778bOnTuxe/du3HvvvejUqRNmz55tt5zVapVExcaNG2E2mzF37lzceOON2LBhg7TcmTNnsGrVKqxevRpnzpzBddddh6ysLHTv3h0bN27E1q1bcdddd2HSpEm45JJLAAAKhQLvvfceunTpgqysLMyZMwf/+Mc/8NFHHwEA5s6dC6PRiE2bNkGv1+Po0aMICQkBADz33HM4evQoVq1ahZiYGJw+fRp1dXWNfBcJgiA6Fl9sOweThccjy/ZjRHo04sN0Lb1JzU6rFhZ1Jgt6P/97izz30ZenIFjj/duTmpqKt99+GxzHoUePHjh06BDefvvtBsJi3bp1OHToEM6ePYvU1FQAwBdffIE+ffpg165dGDZsGAAmQD777DOEhoaid+/eGD9+PE6cOIGVK1dCoVCgR48eeP3117F+/XpJWNgaSNPS0vB///d/uP/++yVhkZOTg2uvvRb9+vUDAKSnp0vL5+TkYNCgQRg6dKj0eIIgCMI3kiKCkFVcAwBYsjUbT03t2cJb1PxQKiRAjBgxwi7Ccemll+LUqVNS0y+RY8eOITU1VRIVANC7d29ERETg2LFj0m1paWkIDQ2V/o+Pj0fv3r3t2pzHx8dLracBYO3atZg4cSKSk5MRGhqK2267DSUlJaitrQUAPPzww/i///s/jBo1Ci+88AIOHjwoPfaBBx7AsmXLMHDgQPzjH//A1q1bA/CuEARBdCzqbaLsFyvrW3BLWo5WHbEIUitx9OUpLfbcLYlarbb7n+M4p7eJw9qys7NxxRVX4IEHHsArr7yCqKgobN68GXfffTeMRiOCg4Nxzz33YMqUKfjtt9/wxx9/YN68eXjrrbfw0EMPYdq0aTh37hxWrlyJNWvWYOLEiZg7dy7efPPNZnvNBEEQbZ1qg1n6u6re7GbJ9kurjlhwHIdgjapFfnztvLhjxw67/7dv346MjIwGcyZ69eqF3Nxc5ObmSrcdPXoU5eXl6N27t9/v1Z49e2C1WvHWW29hxIgR6N69O/Lz8xssl5qaivvvvx8//PAD/v73v2PRokXSfbGxsbjjjjvw5Zdf4p133sHChQv93h6CIIiOSK1RjlhU1XfMkQCtOmLRlsjJycHjjz+O++67D3v37sX777+Pt956q8FykyZNQr9+/XDLLbfgnXfegdlsxpw5czBu3DjJ3+AP3bp1g8lkwvvvv48ZM2Zgy5Yt+Pjjj+2WefTRRzFt2jR0794dZWVlWL9+PXr16gUAeP755zFkyBD06dMHBoMBv/76q3QfQRAE4R01NhEL2+hFR6JVRyzaErfffjvq6uowfPhwzJ07F4888gjuvffeBstxHIeff/4ZkZGRGDt2LCZNmoT09HQsX768Uc8/YMAAzJ8/H6+//jr69u2LpUuXYt68eXbLWCwWzJ07F7169cLUqVPRvXt3ydip0Wjw9NNPo3///hg7diyUSiWWLVvWqG0iCILoaFAqBOB4sdlCM1FZWYnw8HBUVFQgLCzM7r76+nqcPXsWXbp0gU7X8Up0iNYD7YsEQfiK2WJFt2dXSf9H6TXY+9zkFtyiwOLu/G0LRSwIgiAIIgDUGO2rAKs7aMSChAVBEARBBIAaB0+F0WK1Kz/tKJCwIAiCIIgAUGtkwiJMp4JYWNgRfRYkLAiCIAgiAFQbWHQiVKdGiNC5uSNWhpCwIAiCIIgAIKZC9FolQnRMWHTEXhYkLAiCIAgiAMjCQoVQSVh0vIgFNcgiCIIgiABQI3gs9BoVxN7NJCwIgiAIgvAL0WOh1yqhVDBp0RFTISQsCIIgCCIA1NqkQtRKNiCSIhYEQRAEQfiF5LHQqKBVMWFBVSE+8tprr4HjODz66KMB2hyitcJxHH766aeW3gyCIIhWi5wKUSFUpwZAqRCf2LVrFz755BP0798/kNtDEARBEG0SsUFWiFYJcQpXR0yF+BWxqK6uxi233IJFixYhMjIy0NvU5sjMzMRDDz2ERx99FJGRkYiPj8eiRYtQU1ODO++8E6GhoejWrRtWrZKH0xw+fBjTpk1DSEgI4uPjcdttt6G4uFi6f/Xq1Rg9ejQiIiIQHR2NK664AmfOnJHuz87OBsdx+OGHHzB+/HgEBwdjwIAB2LZtm8ft5XkesbGx+O6776TbBg4ciMTEROn/zZs3Q6vVora2FmlpaQCAq6++GhzHSf8TBEEQMmLaI1ijkvtYUCrEO+bOnYvp06dj0qRJHpc1GAyorKy0+/EangeMNS3z4+PQ188//xwxMTHYuXMnHnroITzwwAO4/vrrMXLkSOzduxeXXXYZbrvtNtTW1qK8vBwTJkzAoEGDsHv3bqxevRoXL17EDTfcIK2vpqYGjz/+OHbv3o1169ZBoVDg6quvhtVqtXveZ599Fk888QT279+P7t27Y+bMmTCb3e/IHMdh7Nix2LBhAwCgrKwMx44dQ11dHY4fPw4A2LhxI4YNG4bg4GDs2rULALB48WIUFBRI/xMEQRAyosciRKtCiFbovNkBIxY+p0KWLVuGvXv3en1ymTdvHl566SWfNwwAYKoFXk3y77GN5Zl8QKP3evEBAwbgX//6FwDg6aefxmuvvYaYmBjMnj0bAPD8889jwYIFOHjwINauXYtBgwbh1VdflR7/2WefITU1FSdPnkT37t1x7bXX2q3/s88+Q2xsLI4ePYq+fftKtz/xxBOYPn06AOCll15Cnz59cPr0afTs2dPt9mZmZuKTTz4BAGzatAmDBg1CQkICNmzYgJ49e2LDhg0YN24cACA2NhYAEBERgYSEBK/fE4IgiI6EON00WKuUbqujIWTuyc3NxSOPPIKlS5dCp9N59Zinn34aFRUV0k9ubq5fG9rasfWaKJVKREdHo1+/ftJt8fHxAIDCwkIcOHAA69evR0hIiPQjCgEx3XHq1CnMnDkT6enpCAsLk9IPOTk5Lp9XTGUUFhZ63N5x48bh6NGjKCoqwsaNG5GZmYnMzExs2LABJpMJW7duRWZmpu9vBEEQRAfFaGYRZZ1KiSA1ExeGDigsfIpY7NmzB4WFhRg8eLB0m8ViwaZNm/DBBx/AYDBAqVTaPUar1UKr1fq3depgFjloCdTBvi2uVtv9z3Gc3W2cMOrOarWiuroaM2bMwOuvv95gPaI4mDFjBjp37oxFixYhKSkJVqsVffv2hdFodPm8ts/hiX79+iEqKgobN27Exo0b8corryAhIQGvv/46du3aBZPJhJEjR3r56gmCIAiThR171SoFVEKDrI4YsfBJWEycOBGHDh2yu+3OO+9Ez5498dRTTzUQFY2G43xKR7QVBg8ejO+//x5paWlQqRp+BCUlJThx4gQWLVqEMWPGAGBmykDCcRzGjBmDn3/+GUeOHMHo0aMRHBwMg8GATz75BEOHDoVeL7/3arUaFkvH+4IQBEF4iyQslBy0KnY+rDd5vtBrb/iUCgkNDUXfvn3tfvR6PaKjo+3y/oR75s6di9LSUsycORO7du3CmTNn8Pvvv+POO++ExWJBZGQkoqOjsXDhQpw+fRp//vknHn/88YBvR2ZmJr7++msMHDgQISEhUCgUGDt2LJYuXSr5K0TS0tKwbt06XLhwAWVlZQHfFoIgiLaOycJM/xqlAjo1O712xIgFTTdtAZKSkrBlyxZYLBZcdtll6NevHx599FFERERAoVBAoVBg2bJl2LNnD/r27YvHHnsM//nPfwK+HePGjYPFYrHzUmRmZja4DQDeeustrFmzBqmpqRg0aFDAt4UgCKKtI3os1EqF5LGo74DCguN5H+sqG0llZSXCw8NRUVGBsLAwu/vq6+tx9uxZdOnSxWtzKEE0BbQvEgThK8NfWYvCKgNWPjwGEcFqjHztT6iVHE69cnlLb1pAcHf+toUiFgRBEAQRAESPhUbFSRELk4WH2dKxfBYkLNopYldPZz+2/TMIgiCIwCB6LNRKBXRquZih3tyxhAVNN22nfPrpp6irq3N6X1RUVDNvDUEQRPvHKEQmVEoFtCr5ur3eZJE6cXYEOs4r7WAkJye39CYQBEF0GHietys3VSg4aFUKGMxW1Bk7loGTUiEEQRAE0UgsVl4aMaVRslNrkEbovmkmYUEQBEEQhA+I/gqAeSwA1tobAOqMHctjQcKCIAiCIBqJ0abyQ+0QsainiAVBEARBEL5gshMWbE6IaOAkjwVBEARBED5ha9wUB0JKEYsO1n2ThEUA4Hke9957L6KiosBxHCIiIvDoo4969djMzEyPy3Ich59++qnR2+ktL774IgYOHNhsz9cYmvu9IQiCcIbJLPewEJE8Fh1MWFC5aQBYvXo1lixZgg0bNiA9PR0KhQJBQUEBW39BQQEiIyMDtj5PPPHEE3jooYd8ekxaWhoeffRRrwVVoLB9b7Kzs9GlSxfs27evzQgjgiDaB0aLPCdERKoK6WATTklYBIAzZ84gMTERI0eObJL1JyQkNMl6XSF26GwLNPd7QxAE4QyTE2HRUSecUiqkkcyaNQsPPfQQcnJywHEc0tLSGqQ3PvroI2RkZECn0yE+Ph7XXXed3TqsViv+8Y9/ICoqCgkJCXjxxRft7rcN92dnZ4PjOPzwww8YP348goODMWDAAGzbts3uMYsWLUJqaiqCg4Nx9dVXY/78+YiIiPDqNTmmQmbNmoWrrroKb775JhITExEdHY25c+fCZDIBYOmcc+fO4bHHHgPHyflFANi8eTPGjBmDoKAgpKam4uGHH0ZNTY10f1paGl599VXcddddCA0NRadOnbBw4ULpfqPRiAcffBCJiYnQ6XTo3Lkz5s2b5/S96dKlCwBg0KBB4DgOmZmZ2LRpE9RqNS5cuGD3Gh999FGMGTPGq/eDIAjCE9KcEKV8/NN10AmnrVpY8DyPWlNti/x4O/T13Xffxcsvv4yUlBQUFBRg165ddvfv3r0bDz/8MF5++WWcOHECq1evxtixY+2W+fzzz6HX67Fjxw688cYbePnll7FmzRq3z/vss8/iiSeewP79+9G9e3fMnDkTZrMZALBlyxbcf//9eOSRR7B//35MnjwZr7zyig/vfEPWr1+PM2fOYP369fj888+xZMkSLFmyBADwww8/ICUlBS+//DIKCgpQUFAAgEVypk6dimuvvRYHDx7E8uXLsXnzZjz44IN2637rrbcwdOhQ7Nu3D3PmzMEDDzyAEydOAADee+89rFixAt988w1OnDiBpUuXIi0tzek27ty5EwCwdu1aFBQU4IcffsDYsWORnp6O//3vf9JyJpMJS5cuxV133dWo94QgCEJEiliobCMW5LFoddSZ63DJV5e0yHPvuHkHgtXBHpcLDw9HaGgolEql07B8Tk4O9Ho9rrjiCoSGhqJz584YNGiQ3TL9+/fHCy+8AADIyMjABx98gHXr1mHy5Mkun/eJJ57A9OnTAQAvvfQS+vTpg9OnT6Nnz554//33MW3aNDzxxBMAgO7du2Pr1q349ddfvX79jkRGRuKDDz6AUqlEz549MX36dKxbtw6zZ89GVFQUlEolQkND7d6DefPm4ZZbbpGiNxkZGXjvvfcwbtw4LFiwQBpHfvnll2POnDkAgKeeegpvv/021q9fjx49eiAnJwcZGRkYPXo0OI5D586dXW5jbGwsACA6OtpuO+6++24sXrwYTz75JADgl19+QX19PW644Qa/3w+CIAhbjE7Mm0FSxKJjeSxadcSiPTB58mR07twZ6enpuO2227B06VLU1tbaLdO/f3+7/xMTE1FYWOh2vbaPSUxMBADpMSdOnMDw4cPtlnf831f69OkDpVKe1ufNNh44cABLliyxm6w6ZcoUWK1WnD171ulr4TgOCQkJ0rpnzZqF/fv3o0ePHnj44Yfxxx9/+Lzts2bNwunTp7F9+3YAwJIlS3DDDTdAr9f7vC6CIAhnuPNYdLRUSKuOWASpgrDj5h0t9tyBIDQ0FHv37sWGDRvwxx9/4Pnnn8eLL76IXbt2SZ4HtVpt9xiO42C1ule4to8RPQ2eHtMY/NnG6upq3HfffXj44Ycb3NepUyev1j148GCcPXsWq1atwtq1a3HDDTdg0qRJ+O6777ze9ri4OMyYMQOLFy9Gly5dsGrVKmzYsMHrxxMEQXjCmcciqIN6LFq1sOA4zqt0RGtHpVJh0qRJmDRpEl544QVERETgzz//xDXXXNMkz9ejR48GXg/H/wONRqOBxWL/5Rk8eDCOHj2Kbt26NWrdYWFhuPHGG3HjjTfiuuuuw9SpU1FaWtpg/LtGowGABtsBAPfccw9mzpyJlJQUdO3aFaNGjWrUNhEEQdjiPGJBHguiCfj111+RlZWFsWPHIjIyEitXroTVakWPHj2a7DkfeughjB07FvPnz8eMGTPw559/YtWqVXbVGoEmLS0NmzZtwk033QStVouYmBg89dRTGDFiBB588EHcc8890Ov1OHr0KNasWYMPPvjAq/XOnz8fiYmJGDRoEBQKBb799lskJCQ4rXCJi4tDUFAQVq9ejZSUFOh0OoSHhwMApkyZgrCwMPzf//0fXn755UC+dIIgCBgtThpkddCIBXksmpiIiAj88MMPmDBhAnr16oWPP/4YX3/9Nfr06dNkzzlq1Ch8/PHHmD9/PgYMGIDVq1fjsccek8ySTcHLL7+M7OxsdO3aVTJR9u/fHxs3bsTJkycxZswYDBo0CM8//zySkpK8Xm9oaCjeeOMNDB06FMOGDUN2djZWrlwJhaLhrqtSqfDee+/hk08+QVJSEq688krpPoVCgVmzZsFiseD2229v/AsmCIKwwWR2VxXSscybHO9tXWWAqKysRHh4OCoqKhAWFmZ3X319Pc6ePYsuXbo06UmwIzJ79mwcP34cf/31V0tvSotx9913o6ioCCtWrPC4LO2LBEH4wrKdOfjnD4cwqVccPr1jGADgt4MFmPvVXgzvEoVv7ru0hbew8bg7f9tCqZB2yptvvonJkydDr9dj1apV+Pzzz/HRRx+19Ga1CBUVFTh06BC++uorr0QFQRCEr1BViAwJi3bKzp078cYbb6Cqqgrp6el47733cM899wBgpaPnzp1z+rhPPvkEt9xyS3NuapNz5ZVXYufOnbj//vvd9gYhCILwF2ceC7EqpKONTSdh0U755ptvXN63cuVKqR23I/Hx8U21SS0GlZYSBNHUOItYaAVhYTB3LI8FCYsOiLvulQRBEITviOZNjUquvtMKRk6DuWNFLKgqhCAIgiAaibs+FtTSuxXQzIUqBNGApuxiShBE+8OZx6KjRixaVSpErVaD4zgUFRUhNja2SRs6EYQzeJ6H0WhEUVERFAqF1M2TIAjCHZ4iFjzPd5hzWqsSFkqlEikpKcjLy0N2dnZLbw7RgQkODkanTp2cNuIiCIJwxNmsEK1aPn4YLVZoVcoGj2uPtCphAQAhISHIyMhwWbVAEE2NUqmESqXqMFcXBEE0HqdVITZdOA1mEhYtilKptBvRTRAEQRCtGaNZ8FjYiAmNUgGOA3ieNckK06ldPbxdQXFegiAIgmgkziIWHMfJBs4OVBlCwoIgCIIgGoksLOxTqDqpSVbHqQwhYUEQBEEQjcRZxAKQfRYdqZcFCQuCIAiCaCTO+lgAkAybFLEgCIIgCMJrxJbeDVMh5LEgCIIgCMJH5D4WriIWJCwIgiAIgvASVx4LMWJRb6JUCEEQBEEQXiJ5LFQUsSBhQRAEQRCNxOyy3JQiFgRBEARB+Ah5LGRIWBAEQRBEIzG5LDeliAVBEARBED5iFCIWKodUiFZNEQuCIAiCIHzE7KHzJjXIIgiCIAjCa8xCKkSlcD4rhFp6EwRBEAThNSYrRSxESFgQBEEQRCORIhYupptSxIIgCIIgCK/geR5mq5gKcRWxIGFBEARBEIQXiKICaNggSysNIaNUCEEQBEEQXiCmQQBA5TgrRGiQVU8RC4IgCIIgvEE0bgINq0IoYkEQBEEQhE/YRiwaTDeliAVBEARBEL4gNsfiOEBJEQsSFgRBEATRGETzplrR8JSqo5beBEEQBEH4gpgKcYxWADblphSxIAiCIAjCG0TzpmNzLIDGphMEQRAE4SNmFyPTAUCnprHpBEEQBEH4gEkcme40FUIRC4IgCIIgfEAyb7qJWJitvFQ90t4hYUEQBEEQjUAUDO48FkDHiVqQsCAIgiCIRmASJ5u6qQoBOo7PgoQFQRAEQTQCs1AV4iwVolBw0Cg71oRTEhYEQRAE0QjEqhBnqRCg441OJ2FBEARBEI1ArgpxfkrVCt03KRVCEARBEIRHLFJVCEUsABIWBEEQBNEoTFbRvOn8lNrRmmSRsCAIgiCIRuCu3BToeE2yfBIWCxYsQP/+/REWFoawsDBceumlWLVqVVNtG0EQBEG0esxuyk0Bili4JSUlBa+99hr27NmD3bt3Y8KECbjyyitx5MiRpto+giAIgmjVyEPIXJg3O1jEQuXLwjNmzLD7/5VXXsGCBQuwfft29OnTJ6AbRhAEQRBtAXkImYtUiLpjjU73SVjYYrFY8O2336KmpgaXXnppILeJIAiCINoMnspNdULEop4iFs45dOgQLr30UtTX1yMkJAQ//vgjevfu7XJ5g8EAg8Eg/V9ZWenflhIEQRBEK0QcQubSvNnBIhY+V4X06NED+/fvx44dO/DAAw/gjjvuwNGjR10uP2/ePISHh0s/qampjdpggiAIgmhNiFUhag8Ri47isfBZWGg0GnTr1g1DhgzBvHnzMGDAALz77rsul3/66adRUVEh/eTm5jZqgwmCIAiiNWHy1NK7g0Us/PZYiFitVrtUhyNarRZarbaxT0MQBEEQrRJ3Q8gAQKcmj4VLnn76aUybNg2dOnVCVVUVvvrqK2zYsAG///57U20fQRAEQbRqJI+Fiz4WUktvilg0pLCwELfffjsKCgoQHh6O/v374/fff8fkyZObavsIgiAIolUjTzd11ceiY80K8UlY/Pe//22q7SAIgiCINolk3nThsdDRdFOCIAiCILzF0xCyjhaxIGFBEARBEI3A4xAyilgQBEEQBOEtnoaQUcSCIAiCIAivkVIhnspNKWJBEARBEIQnPJk3KWJBEARBEITXSJ03XZo3qaU3QRAEQRBeInbedGXe1AktvSkVQhAEQRCERyyCx8J1KoQiFgRBEARBeIlJLDd1Nd2UIhYEQRAEQXiLWG7qMmKhpogFQRAEQRBe4m3nTaPZCquwbHuGhAVBEARBNAJPnTfFPhYAYLS0/6gFCQuCIAiCaARyKsR9xAIADCYSFgRBEARBuMEklpu6aOmtViqgFO6rN7d/AycJC4IgCIJoBNKsEBcRC8Cm+yZFLAiCIAiCcIfksXARsQBs5oVQxIIgCIIgCHfIQ8hcCwuKWBAEQRAE4RXyEDLPqRCKWBAEQRAE4Raz1MfCcyqEIhYEQRAEQbjFU7kpYDs6nSIWBEEQBEG4wdN0U0Bu611PEQuCIAiCIFzB8zxMFvctvQGKWBAEQRAE4QUWm9kfroaQATblphSxIAiCIAjCFWYbYeFVgyyKWBAEQRAE4QrboWLuIhZaVccZnU7CgiAIgiD8RKwIAQC1G4+FTi30sTBRxIIgCIIgCBeYhIiFUsFB4aaPBUUsCIIgCILwiNEsdt10LSoAilgQBEEQBOEFonnTXXMsgCIWBEEQBEF4gcmLOSEARSwIgiAIgvACb1MhcrkpRSwIgiAIgnCB16kQGkJGEARBEIQnfE2FUIMsgiAIgiBcIgsLT6kQilgQBEEQBOEBbwaQATbmTYpYEARBEAThCpNo3lR5WW5KEQuCIAiCIFxhtjKhoPG2QRZFLAiCIAiCcIXRy1QIRSwIgiAIgvCI96kQqgohCIIgCMID3qdCWMSiniIWBEEQBEG4wvtUiByx4Hne7bJtHRIWBEEQBOEnXqdChIiFlZdLVNsrJCwIgiAIwk/EVIi3s0KA9u+zIGFBEARBEH4iRh/UXqZCgPbvsyBhQRAEQRB+Ik03VbmPWHAc12EqQ0hYEARBEISfyKkQz6fTjjI6nYQFQRAEQfiJlArxQljIJacUsSAIgiAIwglSKsSDeRMAtGJbb/JYEARBEAThDF9SITqprTdFLAiCIAiCcILJ7H0qJEgjpELIvEkQBEEQhDNMFu9TIaLHos5IqRCCIAiilVNSbUBeWW1Lb0aHw2T13bxZR6kQgiAIorUzc9F2jH59PXJLSVw0J2JLb5U3qRDJvEnCgiAIgmjF1BjMOHmxGgDwxbbslt2YDoa3000BIIjKTQmCIIi2QEFFnfT3qsMXYLW27yFXrQlvp5sC1MeCIAiCaCPkl9dLf+eV1eFAXnnLbUwHw9vppgB5LAiCIIg2gm3EAgByy+pcLEkEGp9SIRqqCiEIgiDaALYRCwAoqjK00JZ0PHxKhaiojwVBEATRBnCMWJCwaD58SYUEaYSqECMJC4IgCKIVU1DBIhZdY/UASFg0J3JLb++rQshjQRAEQbRqzpeziMWAlAgAQGFVvZuliUDiy3RTLVWFEARBEK0dnudRIHgsBqRGAKCIRXMiTzf1pkEWRSwIgiCIVk5lvVk6UfVLCQcAFFeTsGgu/EuFUFUIQRAE0UqpqjcBADQqBVIjgwEAJTVGmC3t++TVWvAlFSL2saCx6QRBEESrpU6oMNBrlIjSa6DgAJ5n4oJoeky+pEKEqhBKhRAEQRCtllpBWARrVFAqOMSEaAGQz6K5MPmQCpHHppOwIAiCIFopNUYzALmrY2woCYvmxJ9UCFWFEARBEK2WOiliQcKiubFaeVis3gsLebpp+/a/+CQs5s2bh2HDhiE0NBRxcXG46qqrcOLEiabaNoIgCMIDtQ7CIiJIDQAoryOPRVMjpkEA36pCjBarJEjaIz4Ji40bN2Lu3LnYvn071qxZA5PJhMsuuww1NTVNtX0EQRCEG2qFVEiwRgUACBeERUWdqcW2qaMgpkEA31IhQPtOh6h8WXj16tV2/y9ZsgRxcXHYs2cPxo4dG9ANIwiCIDwjRixEjwUJi+bDtqTXq86bNvNE6kwW6LU+nYLbDI16VRUVFQCAqKgol8sYDAYYDHKur7KysjFPSRAEQdhQa1NuCgBhgrCorDO32DZ1FIyCsOA4QKnwnApRKDhoVQoYzNZ2XRnit3nTarXi0UcfxahRo9C3b1+Xy82bNw/h4eHST2pqqr9PSRAEQThQZ1NuClDEojnxpSJERIwsGdrx6HS/hcXcuXNx+PBhLFu2zO1yTz/9NCoqKqSf3Nxcf5+SIAiCcMCx3JSERfMhpkI0vggLqZdF+60M8SsV8uCDD+LXX3/Fpk2bkJKS4nZZrVYLrVbr18YRBEEQ7pEiFmrHVAgJi6ZGHkDmOQ0iousAg8h8EhY8z+Ohhx7Cjz/+iA0bNqBLly5NtV0EQRCEF0jlplpKhTQ3Yj8K22oPT3SEJlk+CYu5c+fiq6++ws8//4zQ0FBcuHABABAeHo6goKAm2UCCIAjCNXK5qX0qpLLeBJ7nwXHeX00TvlEv+CR8ERZB6vY/L8Qnj8WCBQtQUVGBzMxMJCYmSj/Lly9vqu0jCIIg3ODYIEsUFiYL365PXq0BMepgW0bqCYpYOMDz7bdTGEEQRFuk1qEqJFijhErBwWzlUVFnkm4nAo8/qRBRANZSuSlBEATRGnGcFcJxHPksmgkxIqRT+1JuyoQeCQuCIAiiVeJYbgrYGDhrSVg0JfUm3z0WwVK5afttYEbCgiAIog1TJ3XelFMeoRSxaBYMorBQ+WDepFQIQRAE0ZpxNG8CtpUh7fequDUgeyy8P5WSx4IgCIJotVitcuWH01QIRSyaFL9SIRoxFULCgiAIgmhl2JaT2kcsWFqEhEXT4lcfC9G82Y7LTUlYEARBtFHEcDrH2ef5w3TU1rs5EFMhWj9SIWTeJAiCIFodYtfNILUSCpux3aGCsKgij0WTUu+HeZM8FgRBEESrxZlxEwBCdSzcXlVPEYumxJ8GWeJ0UxIWBEEQRKujzoV5UBYWFLFoSmSPhS+pEPbZkHmTIAiCaHUYxBy/w6wK0WNRZaCIRVMi9rEI8sm8KUQsTO1X9JGwIAiCaKMYLaKwoIhFS9CYWSEUsSAIgiBaHUYzO7FpHCIWZN5sHur9mBVC5k2CIAii1eJaWMjmTZpK3XSIHgutTxELeQiZ1do+PxsSFgRBEG0Ug3hicyEsTBYeBkF8EIFHSoX4UW4KyMKkvUHCgiAIoo0iRiwchYVeowIntLWopJLTJkP0Sfg0Nt0mutFe0yEkLAiCINooonnTMRWiUHAI0ZKBs6kx+NHSW6HgJCHSXg2cJCwIgiDaKJLHQtnwUB5GBs4mx5+qEMDeZ9EeIWFBEATRRjG4MG8C1H2zOfCnKgSw7b7ZPkUfCQuCIIg2isHsvI8FQL0smhqzxQqzUNXhi3kTaP+9LEhYEARBNCM1BjPeW3cKpwurG70uV+WmgG0vC4pYNAX1NtU2vqdC2ncvCxIWBEEQzch3e/Iwf81JTJq/ERcq6hu1LtE86D4VQhGLpkBMgwANq3I8Ibf1JmFBEARBNJKj+ZXS3y+sONyodbkqNwVkYVFJwqJJEIWFRqWwG1nvDfIgsvb52ZCwIAiCaEbyK+qkv/fllDdqXZQKaTnk5li+n0aDKBVCEARBBIrskhrp78IqA2oM/l+1Sn0snJSbUiqkaal3MbLeG4LVJCwIgiCIAGA0W3G+rM7utnMltX6vz9XYdIAiFk2NP82xRPRasY9F+xR9JCwawdniGnyy8QwKqxpnwCIIomOQV1YLK8/6GAxIjQBgH8HwFVdj0wEgjCIWTYrcHMv306heyz6vGkP7jFioWnoD2io/7z+PR5btBwBcqKzHCzP6tOwGEQTR6hGjE52jg5Eeo8eB3HKcLW6EsPCqQRYJi6ZATGGJRkxfECMW1Y1Ig7Vm2lXEguf5ZhsRvGJ/vvT3kfOVbpYkCIJgiNGJtGg90qL17LYmExaUCmlKyuvY+xoRrPb5seIcl8b4a1oz7UZYjH79T3R7dhXOFDW+6Yw35NvUn5+4WNVsgoYgiLZLnuCvSI0KQlpMMIBGeizEPhZk3mx2KmoFYRHku7DQayhi0SawWHlYrHyzuWzzy2UDVkWdCRcrDc3yvARBtF0qpKtcjRyxaITHQmrp7STPH0pDyJqU8jojAPZZ+oqeIhZtg+asC641mqUDRHyYFgCLWhAEQbhDTEuE6VRIjNABAIqqDTBbrO4e5hJvyk2NFqtdl0giMJQLEYtwPyIWciqkfX4u7UZYNOdQl/xylgYJ0aowtHMUAODEBfJZEAThHjF6EKpTI1qvhYIDeB4oqTH6tT6x3NSZxyJEowLH2T8vETga47EIFqpCKBXSyglWN998+wKhc15iuA7d40MBAMcvUMSCIAj3yMJCBaWCQ0wIi3gW+plKdVduqlBwCNHQ6PSmQvJYNMa8SX0sWjdiKqSuGUJ+BULEIjEiCF1iWZ40z6HpDUEQhCPiCV70P8QJqVR/e+G4qwphz0MGzqZC8lgE+e+xqKVUSOsmSC2mQpr+CyT2+k8K1yEhjOVJCyupSRZBEO6xjVgAQFyocPyo8jNi4WYIGXseMnA2FaLHIswfj4VG9r8Yzf75a1oz7UZYNOd8eyliER4kmTcvVNZTySlBEG5pKCwalwpxNzbd9nkoFRJ4GpMKETtvAu2zMqTdCIvmrAoRIxaJETrECxGLepOVxhMTBOGSepNF8kRIqZBQ/1MhZosVVuFaxnXEglIhTYHJYkWVIAj86WOhUiqkz6w9GjjbjbAIbkaPRang4I4N1UKnVkrlRhcpHUIQhAtsT+6ieS82zP9UiNGmRNV1xIIdmyopYhFQKuvk99OfclOgfRs4242wCNI037Q4UWGKQ37EdAgJC4IgXCGmI0K0rCIEsI1Y+CEsbHLzzvpYABSxaCrEPkahWhVULt57T7TnJlntR1hI5s2mN8JUC1/SEC1TqmI6hLpvEgThCvHkLl6QALKwKPLjokTsuqng4PLkRubNpkHsYRHuh79CRB5E1v4qQ9qNsJBTIU3/BRJzayFSxEIUFhSxIAjCObbNsUTiwuTum76av+WKkIY9LETIvNk0NMa4KaLXiKPT25/oazfCornMmwazRfpCizkySoUQriiqMmDTySJYrVQx1NGRe1jIEYtYoUGWycKjrNa3k7/BQw8LQI6OUMQisDSmh4VIex6d3m6ERXOVm1Y7MWAlUMSCcMET3x7A7Z/txFUfbSEDXQfHsdQUYKJANP8VV/uWSvVUagrIPRaqDLTvBZKSanEAmf8Ri/Y8Or3dCYumnhUiqstgjVI2YAnC4gJ5LAgHtmWVAAAO5lXgy+3nWnhriJak0qHrpkis4LMo9tHA6ak5FnsudvKqrGt/J6+W5EIFu4gULyr9QexlQcKiFaNTN0+5aZVk3GxowPL1wEC0b8pqjHbO/UN5FS24NURL4yxiAQAxISycXuRjxMJTO29ALoWsqKOIRSApEKLTCeGNERZiuSmZN1stwUK5aXNFLEJsDg7iICF/DFhE+yWruNru/8P5JCw6Ms7Mm4B8/Ciu9m3CqbuR6SJhOhIWTcHFCrn7sr9QKqQNIHssmvZDEj0WoTYRCzGUaTRT901C5kxRDQBgQEo4ACC3tA7ltf6NxybaPs7Mm4DNhYmPEU9xZLq7VIgYsaiqN5GBOIAUVAQuYlHdDs8Z7UZYiH0smty86SRioVMrJfXpqwGLaL+cKWIRi4GpEegUFQwAOJJf2ZKbRLQgzvpYADYeC19TIW5GpouI5k0rD1Q7ueiykNjwGauVl4z6iY0QFmFSV1QSFq0WMWJhMFub9Msi9bDQOs+Tks+CEMkSIhZd40LQL5lFLQ6dp3RIR0Vs3SymbUViQ/wUFl54LHRqpRTRqHAoZ119+AJ6P78ab6w+TilcHyiuMcBs5aHgZFHoD2FBgrG2HVaLtRthIfaxAJrWwFkd4Dwp0X4RIxbpMSHomRAKADh1sdrdQ4h2jOj/CtbYRxhiQoWLkiYQFoBrA+d3e3JhMFvx0YYz+GjDGZ+euyMjVoTEhmqh9rOdN2ATsWiH/pd2Iyx0NuHApjRwVhvkfv+2+BvOJNovRUL5cVKEDp1j9ACA3NLaltwkogURL3iCHIWFeFFS5dtFidTHwsPJTRQWticwnuexP7dc+v+XA/k+PXdHRvZX+G/cBNr3HJd2IywUCs5mXkhzRCycG7BIWBAAy12LabPwILXksThXWtOSm0W0IOJxSTxOidhelPhisBQ7b2rV7g/jYU4iFtkltXbR1VOF1c0ywLE9IEYsEhvRwwKQPxdKhbRypMqQJpwX4tpjQcKCkLGdzRAWpEZnQVhcrDSgvol7rRCtk1opFWJ/7IjWs2OH2cr7VBbqTbkp4DwVsiu7FAAwLC0ScaFaWKw8GYu95EIAelgAciqk2mBudxU77UpY6JqhMkSabOoYsRDypEU+hjOJ9ol4ENdrlFArFYgIVktRrhxKh3RIxIiAYyrE37beYrmpPx6LvefKAABD06LQPyUCAHDAJjVCuEYsC26McROQo948L1+wthfalbBojrbezjpvAvZNsghCPIiL4U6O46R0SE4JCYuOSL0gBBzNm4B/3Te9KTcFnAuL7BKWkuuZEIqBqaxi6SB1hvWKEuEzEj8zf9GplZIobG/TZ9ulsGjKTmZiHwuXHgsqNyUgz2YQD+oA0Dla9FmQsOhomC1WSQg4eiwA+erXlyZZ3laFOMvl55ezcH5SRBD6CRGLI9QZ1itEb4p4zG8McmUIRSxaLWLO63x5XZM9h9QgS+swSMjGY0E14YRjxAIAOkWxypCcEjJwdjRqbXw1jqkQwL9ydd/LTdmxy2rlUVDBjpFJEUFIFyuWyuraXa6/KRAjFtGBEBbttJdFuxIWXWNDAACnC5uuV4CYChEn04mIHguD2SqJD6LjIgkLna2wEFIhFLHocIjpWQXnvAW3P+ZvsdzUXUtvQO70Ke6TRdUGmCw8lAoO8aFaJIbroFJwMJqtkjGRcA7P8zYRi8alQgD5+NDeSk7bpbAQGxM1BaIBK9QhYhGsUUmpGGqSRYhXILapkNQoVveeV9Z0ETWidVJnUxHCcVyD+/0Zne7N2HSgocdCjOgmhOmgUiqgUiqQEsn2zXPk/3FLlcEspbTEap7GII+1p4hFq6VrnCgsmibUbLXycsmY1nWelEpOCfEgbissUiJZxOJ8eR2lyzoY4nHDWRoEkFOp/pg3vU2FiCev/HIxDSKXS6ZK0TRK07mjRLho1GuULj9LX2ivvSzalbBIj2W5wqIqQ5OMCbZtFa53qEUHyMBJyMgeC3k/EQcW1RotKKttXwcSwj11Qm8dZ8ZNwL+23pLHwkMfi4hgtu4yYbKuKCySI+TOkaKxmNJ07hE/n5hGlpqKkHmzDRCmUyNO+MCzmiAdIg4R4jhA56TbnTSIjCIWHZ5KJxELnVop7Z95ZXQA70jUupgTIuJPW2+Dl+bNBKFDZHmtCfUmC86XycZNkc6CsZhSIe6RjJv6xvsrAPnCg8pNWzlNaeCsMbCDg95FnlTqZUERiw6PM/MmACmXTT6LjkWdp1SIIDhLarxv6y219PbQxyIsSCVFSi5U1OO8TampSCeKWHhFUQBLTQHb0ekkLFo13eOZsDhxoSrg6xb7Y3i66igi82aHx1nEApB9FhSx6FiIaVRXxw7RCGiyeN/W29tyU47jpDRcQUW9tO8lRzZMhVDEwj2BLDUF5IodSoW0cvoksy5yh5ug2YsYztRrG/orADnvRqkQolIoHwsPthcW4sH8PEUsOhS1LgaQifjT1tvbVAgg9/jJL6+Tum52idZL94ul0BV1JlSQ/8cl4mcTG4BSU8D5gLj2QLsTFn2TmLA4cr4y4M1eRI+FYw8LkVjyWBAClAohbJGrQpxflAC+t/U2etnHApCFxYG8ctSbrFApOGlfBFgZrBhxpXSIa0prWDQ6KkAeC9FYW97RhcWmTZswY8YMJCUlgeM4/PTTT02wWf6TER8CjVKBKoMZuQEON9canE8nFKEJpwTAmug4KzcFbFMhJCw6EuJE22AXEQsAiAtlJ//CSi+FhZflpoBckbTtTAkAVl6qcqgmkVvOU8mpK8TvdWSAhEWUICxKa9rXOcNnYVFTU4MBAwbgww8/bIrtaTRqpQI9E0MBAIfPB3YMsBSx8GDA8sXZTbQ/6kwWWIRomW25KWAbsailXhYdCFeTTW0RT/7edr/0ttwUABLC2X53SjC1pwkiwpbOUeSz8ITohXCMRPpLlBClKqsxtavjgeu4nAumTZuGadOmNcW2BIw+SWE4mFeBQ+crML1/YsDWWyuaN115LISIRZ3JghqD2aUXg2jfiC3dOa5hTl3sHVBjtKCiziSFQon2jacGWYCcrrhQ4Z2wMHjZeRMAEsN0dv+nxegbLCNVhpCwcImz/jSNQYxYGC1sFERogARLS9PuPBYA0F+Y1rc/tyyg660RzZsuDg56rdzWu5BKTjsstW7KknVqpSRAKR3ScZBaertJhSRIlRve7RdGL8tNbdct0sWJsKBUiGfEstBARSyCNErp4qOspv34LJpcWBgMBlRWVtr9NDWDO0UCAA7kVsAs5CEDgVxu6lqtis1ovL3qINofnky+tukQomPgVcTCx2OHt+WmgH3PCgBIi3YSsRCaZOWWkuB1Bs/zUhl5WFDgIguiEbSkHfksmlxYzJs3D+Hh4dJPampqUz8lMuJCEKpVoc5kwfEA9rOQy03dGLDC2NVoYRUJi46KbSM1Z1BlSMdD7mPh+qIkUfBBeOOxsFh5mAUfjzfCIkqvwc2XdIJGqUBEsBr9U8IbLCOWnOZX1EmTUwmZGqMFYqFhoCIWgCwsxJbr7YEmFxZPP/00KioqpJ/c3NymfkooFBwGdooAAOzLCVw6xJeIxUUaP9xhESMWzgbVAVQZ0hGp89DSG5DTFYVVBpg8RFrFaAXgnbAAgFev7of9L0zG9qcnOvX2xIRooNcowfO0bzpDjFZolAqnIx38RawwKWlHjRWbXFhotVqEhYXZ/TQHg4R0yN6c8oCtU4xYhLgxZcZL4cz2E9YifEMUoK4iFskUsehwiFUhOjcei2i9BmolB573PBbAVlh4Y94UCdaoXG4Dx3HoHC3ODCGfhSOSvyLI+UgHf4kSmuh16IhFdXU19u/fj/379wMAzp49i/379yMnJyfQ29YoBgsRi72BjFgY3bf0BmRhcZFSIW0Si5VvdNmXZN50IUDJY9Hx8DSEDGCRVrGXRYEHn4XBwtbHcYBKEbiTXFoMi6ZlF9O+6UigS01FovTinJgOLCx2796NQYMGYdCgQQCAxx9/HIMGDcLzzz8f8I1rDINSWcTiXEltwBpWeTphADbCwvHAYLUCB5YB+fsDsi1E4DmaX4kxr/+J6z7e1qiurbJ50/l+kmrT1rs91a4Trqn3MCtEJNHLklODSe5hEcir505RFLFwhVhqGhpA4yYAROnZ+krbUSrE52LczMzMNnEwDA9Wo1tcCE4XVmNfTjkm945v9Dq9i1gw9WkXseB54Ns7gGMrgLjewJxtjd4WIrAUVRkwc9F2VNSZkF9Rjz+OXsTUvgl+rUtOhTjfT5Ij2FVhlcGMyjpzg3kiRPvDm6oQwH6mhzvErpu+pEG8QWyclU29LBogVYToAtufSIxYdOhUSFsi0OkQ6YThTcSi0iALsI1vMFEBAIVHA7ItRGDZfLrIbhDQgg2nPQvoujLg/B7Aau+grzG6rwAI0igRLRi28srpAN4RqPMwhEzE2+m3cqmp5x4WviB6LGheSENkj0XTRCw6dCqkLSH2s9h7LkDCwos8qVhuajRbUV5rAk6sBja8Ki/AKVgEg2hVHMpj/VVmDEiCRqXAgbwKnClyEw7O3Ql8OAJYNAF4uw9QfEq6SxSgIW7KkqnktOPA8zxqvSg3BbzfL4w+dN30BdFjkVtaG9AeQO0B0WPhOP+nsYgRi1ISFm2DwZ2ZsDiYF5hGWbUe3P4A64In1iUXXcgFfp7L7hh4K/vNWwFjdaO3hQgsh89XAADGdY+VIl07zpY4XzhnO/D534DqC+z/qgLg7CbpbrGPhavW7wCVnHYkTBZemh3jKRWSKvSS8DRA0ZeR6b4QH6qDVqWA2cojv5wM6LYEuuumSEyIBgpYEVF1CqgsCOi6W4p2LSy6xYYgVBeYRllWq81Vh5srUUDuZRGx4VmgthiI6wNMfwtQCDtkfUWjtoUILFYrjyP57DPplxyOEenRAIDtWaUNFy44CCy9ATDXAV0nAN0msdst8tVGrQfzJkCVIR0JMQ0CeDZvisbe3FL3xt6milgoFJzUKCvbmYHTVA+UnQPMHa+cvjLAc0IAAFYLkk/+Dzu0c/Cz4knwb/cBVv2Tmf3bMO1aWCgUHAamRgBovM+izmSRMhjuIhYAa587SnEIcbmrWOrj6o8BtQ7QCd3uSFjI8Dyw93/AmT9bbBPOltSgxmiBTq1A11g9LunChMWOrBL7g3t5LvDlNYChAuh0KXDjUkAfx+6zOdBWezBvApQK6UjUmtj+oFZyUHuYRJocGQSOY8cbdzl3o1BuGuiIBQDXvSzObQPe7g282x94bzBQejbgz92akQaQBSpiYaoHvrsT2jX/RCxXiVpeC463ADsWAIe/C8xztBDtWlgAgfNZVNWzg4NSwXm86ugUpsRLqs/ZP8NmA4n92d86oTkYCQuZnYuAFQ8CX90IlGW3yCYcyWf+il6JYVApFRjUKQIapQKFVQacLRYOrhYz8P09QE0RkNAPuHk5oAkGlMJBxiIbP2s9mDcBuUnWeRIW7R5xf3DXHEtEq1IiXuhlkevGQOnLyHRfEStD7ManH10BfHElUCukByvzgG9nAeb24wvwREDNm1Yr8ON9wNGfAYUa72nvRX/DIuQMeIzd/+e/23RUqP0Li86B6cBZJexUIVrPXdcmV/+Ebop8VCkjgfHPyHdIEYumH8TWJsjdBfzxLPvbYgT+eK5FNkM8uXcRrtR0aiX6CbMUDuSVs4V2LQJytwPaMOCG/8mfpYoZr2CRDwKyedMbjwWlQtoVVReAXx8DLsrVX96087ZFjGbluhGdTeWxAIDOwuRTqeR05yLgm9vZPt7jcuDB3UBQJFCwHzjyY8Cfv7USUPPm2heAoz+x9Pgt32B7zLUwQ4UDKbcCoYlAeQ5w+PvGP08L0e6FhZgKySltXKOsSiFiEeqphrm+AkNz/gsA+EJ/JxAUId/XnKkQqxXY8i7w3iDgtc7Ar48DhlZkGi0+DXx9ExMUUV0BcKwktwXMSxeEMdW2o6X7JbPP6lBeJVBXDmx8nd0x+SUgqov8YKUwc8Hm6sLTrBAASBamTVbWm+3KXO0wVAFZG1kIuq3kXOvKgDXPA0uuAE6tdb9syRlg/atARV7zbFtzsDAT2P0Z8NvfpZu8GUBmi2jgdCc6DU3ksQBsIxY1wLaPgJVPAOCBIbOYqI7JAC55gC28/8uAP39rRTZvNtJjsXsxsPU99vdVHwFdJ0htCs7XcsDw2fJybZR2LyzCg9TIiAsBAOxrRNRCjFiEesqv7fov1KYqnLIm42vDKPv7Ai0sjq8EFk8H3uoFLLuFHQQO/wAc+wX4+kZ2gC/NAurLgd3/Zf8HAqsVOPYre/46H1NMPA8c/w347DJmbE3oB9y3CUjoy+7P3R6YbfQBcZqkrbDoKwiLw+crgB0fs9cZ2xMYdLv9g0VhYZsK8TDdFGDGzpgQDQZzJ1G57XPm3xAxG4Et77HP9Yu/AYunAh9dAhQea8zLbHpM9cBn05igzf4LWHot8PVMoDK/4bLlOcCS6UywfT4DqC5q/u0NNNWFrEIIYKkCgVove1iIiMIip6SWfV9ydgD7vgSyNkil6l6PTK8uBP53DXu8l4gj1buUbQb/uxBxHfcUcMU7gFLYpwfOBMCxaqgWSmE2NwEZmX7xCLDqKfb3hH8B/W8AILcpuFhZzyoIFSogbydw4VCjtrmlCGwLsVbK4E6ROFVYjb05ZX534KzyJmJhNgLbPwIAfGT+GwqqjDBbrFCJeVCt4LEw+CAsqi4yY2PP6bJHA2BXRb8+Jv9/PB84/qv9Y5UaYMqrLGz5/d3sMYNuBZIHe//8zlj/f8Bfb7G/E/oD924EFB4OcOf3AvuXAid/ByqEk2jSIODmbwFtCDNDXjjESjn7XN247fORC5Us2iBeNQByxOJkfjH4qv+CA4CxT8oHVhEnqRDJvOmueojn8Zr6U0zSrgY2Adj0dyC+LxCewg4+4nsUlsKEaPFJ4LMpwJgngD5XARGdWASq5DQQmsB+Wpq/3gKKjgH6WKDnFcC+/wEnVrI29rd8K4vHopPMBCuehEuzgPWvADPeaaktDwx7P5f/ju0l/VknRLA8lZqKpAupCO357cCSfwLntsh3pl4C3PajTSrEwzq/vwc4uxE4s459970gMVyHOEUVXlV8DA48MOROIPNpNphEJKIT0GUsW/fRFcCoh71ad1vFauVRZWjkrBCrhfkqLAYgQ/guC4i+msJKAxAaz74/R39i6eHbfrR/79sAHUNYdI7A8t25jTJwisLCbRjs5Gqgpgh8SAJWl42ExcKjsMqAJCHs7XPEouQM65dQmQeEJABXLwDSxwPbPgD++BdbZsgsoO91QN4uIG83W7ephpW4jnhAPpif/B049A2w6T/AzK99fwNEsjbIogIALhxkr7vn5a4fs3MRU+m8UHanDgYuuR8Y+wSgYQdRdBoB7FwI5DR/u3NxrkuCjbDoGquHTq1ApnkzuJpClvfsfWXDB4vmTcHEZrZYpYO+2+qhk79jUt1qWHgOJSHdEVdzErh4mP0ArNpk0ovAgJks4vT1TUDuDmDNc+wnLAWovghYTUxAZv4TGP144A9AhioWgai+CHQeza6wnD1H4TFg89vs78vfZOLnkvtZK/ui48BnU4HL/8N6uKx9kf2O7saWWfmE/cmzJeF54MgPwK7/svd1+Gwm6r3hyE/y3yY5jVHn5ZwQkW6hJryl/gjXlm4GSsG2o/Mo9h7l7gAuHILRHAvAg3mzrpyd+H1EpVTgleCvEGOuRG1EdwRPe935Z959Klt/1gb/hUVFHvOjpAwFgqP8W0czUGUwS1WBHtPhrtj7Bbt40oUDV35g957KHZuF3iETnwdOrAKy1rNIc88rgPy9TJx0uhRIGdKYl9PkdAxh0UlulGWyWD2WfDnDq1TI/qUAAG7ATYjZF4Lc0jrkl9fZCIsI9ttbYfHjfUxUcArWjOnLa4H4PnJ4bPRjwMQX2A7aZYz7dY37BxMWJ1YxwRLd1bttcGSD4DUYMotFQja/zYSGK2Gx/yshRwugx3Rg8O3sSkcTbL9c6gj2+8IhdjLThvq3fT5isfIoErw3tqkQlVKBPolhuPPCanbDsLtlEWGLUoxYMGFRY9OzwGUfC6uFmbcALLRcgVOdn8D8y5OZqKotYSImbZT8HgRHAXf8Chxczg5O5/fIoXZdONuf1r3M1jvuHyxVlbuDVSOJws0fKs6zVEzJafb/3i9Y9GzGO4A6yP71rHiIiZwel8sCLK4ncNdqYNmtwLnNwE/3y4/pNBK48UsAPNs/ik+y1yGK75Zi50Jg1T/k/7P/Av6Z23B/daTkjCwKATth4VMqJGsjev94D/oqC2HhOVgG3Q7N+KeA8GTW6bXoGGCul8RKkMbNsezgcvv/zQY5wuaOnB2YbN4IK89hY++XMM3VY9Iz2e9zW71fty2b3wb+fEUWx9csbPZopbeIaRCtSuFVdU8DTHUsKgew6E9InN3dDWZMRXcFxj/NRPjW92RPhkifq4E+1zDB4Sla3AK0vi1qArrGhiAiWI06kwUH82xO6mYjC+OdWstOaKVn7XLltnhMhVQXAafWsL8H3SqZ8+z6FPgSsSg8xqIQChXw0B6Wd+OtbDsVauCyV2RR4Q0xGSz8Bh7YvsC7xzhyfg+Qs5U9/7h/AiPmsL/P73aeC9z7BTvhAMCoR4CblgI9pjo/SIcnA+Gd2GvM3+ff9vlBcbUBFisPpYJDTIj9gXFaZB4GKLJg5jQsHOwMh1SI2BxLreRc579P/g4UHYdRHY4F5r8hu7gGCIkFev8NGHone48chZVKAwy+DbhnDfDPc8AdvwAP7QWeOgdMfY0ts/4Vlh77dALzZYj5cX8w1gLLZjJREZbMzHqcEji4DFh8ub0nYtd/2b6qCWXRCtt9MigSuO0HlqOPzmDpninz2PbrowF9DBDRmS17fq//2xsIcncBvwtVSiPmsN9Ws3ffV8c0pEn+3ntdFXLkR+DLa6CoKUQ2knC98QUcH/oy+24A8r5mNspdgN1UHuHoCvv/qy96fBngeWm/WW7JxC5Dmutl43oBIfGsWVzuDs/rtuXUWnbStJqYkLYYgZ/mAIXHfVtPMyEaN/2uCDm4nJWqh3cCht3T4G6nM6ZGPQrc8AWQPIRFKNMz2cUZOLavfHMb89IZGtf8sSnoEMJCoeAwsitrevTXKeGAWJYNfDKWfThLrwU+Hg28N5BVUHx/j92BAbCNWLj4Ip9ew0L9Cf2BmAykCuWEdsN8pD4WXpSb7v+K/c6YAkSls9DZ7D+Bqz4G5mwHRj7oe9j7UuFguX+p76ZLANj1Gfvd91ogLJGp7h7ThHXapFfqK4Bv7xSuYs1A/5uAiS963l6x30czGpYKhDRIXKgWSoX99k2uZgfmv3SZ7AToDIc+FlI7b3dpkF2fAgAqet2ESujt+wV4gzaURX2iu7L3dMQDQKYgInZ/JguzohPer9NiYqbazW8De5YwYVJwAAiOBu5cBUx7jeV6g6JYSPaLv7HSyotHgXUvsXVMekE+Cdqi0rKy64d2Aw9sYfuhrVclZSj7fX63b+9DIKkpYX0ZrCYWcZnyquyJMnoxQvyEENnqf2ODx8iTTd3sE0UngR8fYN+XPtfg2YQF2Mt3R5btvBpJWNRLkTGX6baaYnYRYEvVBc+v4/Ra4PxumJVBeMt8A04Xuakk4zg5anF6ned1i9SWyqMOht8HPHaE7c+mWsGDYLZf3lDV4vOVxFJTv4ybViuw7UP294j7nUY+48N04DhmypUao3Ec2xdn/wk8fgS4/Wdg5lfA7HVM6Kt0wKk/gE1v+vuymowOISwAYEwGy0luPlXMdtKfH2RhxeBodiUVEs8+KFMNcOhbFt6zQY5YuNixTv3BfnefAgDo7KzJjLcRC54HDgmd1wbOZL85jinXgTOBmG5evGIndBnHrhhNtezk4QtmI3D8F/b34Nvk2wfewn4fXM6qAkx1wFc3sTw1pwTGP8s6j3oTrktoQmFhqmeCUfQBCFwQhIWtcRMAUF+J1AssAvVJzThYrS4ObGIqRCg39djDovQsM9KBQ/BIVlZWUmOUroj8JvMpYOYydiAKZiIanJchW7OBeSCW3cyuIn95RBYVM5cBkUJEIX0ccPca5vcpPAp8NIIZSo3VLO879G7/tj1ZyBfn7fHv8YHg96dZeim6G/A3If8tppFMHoSFsZZFbACg1wzhMTYRC5OHVAjPAz/PYVf+XcYB1/4XneKY3yCr2JmwMEiRMZdRkBOrWPQvoR+QMpzdJpplXcHzUll1Uc9bUYxwnCn0UKKecRn7ffw3+9sN1cxXtTAT2PO5PAGY51lUrfoCENOdlW8rlMA1i9jxsWA/S0VVnGfHgUUTgHkpwPxewJn17relCWlUqWnudpbq04QAg25zuohGpZA8Xu4aowFg35dpr7H3DGDHcm/EbzPSYYTF6G7sinNfbjnq9i1nuVOVDrhnHbuSeuIk8OwFIDKNPUDsMCfgto+FxQScFlpSZzBh0UkaP2zzgXsrLC4cBKrymcmx22TvX6QnOE4O8W56i10leUv2Jrbd+lh2EhHpNomFymuLWbOrb+5gV0raMOCu31nO39vISkI/9rsphMX2j5hgXPui3c2iWSrBUVgcWwGFxYAsPgnbjWn2B3hbVGK5qeix8HDAF/Pe6ZnQJ2RI6Zez7iapekuPaSx0+rcP2P9mL4dIbX6bRQu0YSxv220yuyK6dwOQOtx+2ZhuwJ0rmTm4rgwwVAIpw5gh2N9cb7JNxKIlrkxzdwqfCyec4IRIhVpI2Xk6aOduZ5GO8FQgrje7zZdUSO5OJkxUOkmEdxEqQ7JsIwYqYR+1GCQB6zIVckaIIPSYzqoMAFZh5vZ1yNsRNO5RAMD58jpJxDgl4zKWDi05JR9PjLUs4rXjYxY9++VhluYwVAErnxQaQ6mAqz+RvTqhCXJKb/d/Wevwj0ez9CvARNHXN7Hvb62TGT5NTKNKTcXvfO+r7Cv7HPC5zX/P6ex8VV/e0E/TwnQYYZEaFYy06GAEW2ugECsqxjxh3+yI41gJJNBg53Vr3szbzUpIg6KkUs7OUW4iFgYPqZCTQvQjPZPNGAkk/W9kwsBYBXw4DPhoJHDAi53y6M/sd88r2BWGiFIFTBMMnbs+BU79zq7iZy4DUof5tm1iKqToeODb2e79Qv7b5uRVWCVGLByMZ8IXdVvIJACcNP20AUoHYSH2sHB2wOd54OA37O8BNwEAusWxE8hpT1eGviDuM94Ii+oiucpnxjvA9YuBW79jV0QRnZw/JrorC8/e/C0zld65mnkp/CWxPzvR1BSx/hbNzZ//Zr8H3WJfii1GLIweriDFybZdxspixFQj7We1nspNdy5kv/tdB4QlAQAy4pjH5tRFm/1CasZW73k/y97M/k4fxzwMgOeIxY6Phe24HhFxKdKU5ix3olcXxp4DAI4Jx4iVT7CLg+AYoVJJ8ObMS2EdbMEB0+c3LHsfeDMz9Mb1YY9RBQFdJwJzdzFTsLmeieAvr2ERyGakUqoK9FFYmA1ytVD/690u6vPEY4WSVVUBwPaPWzxdZEuHERYAMKZbFF5Ufw5tfRHr9uisRCpIKHlyiFi4NW+KucwuY6STrpgKKawyyNMNxZxtfYX7nUBMq4hhxkCiVLGrspju7P/CI8CP98qpF2dYTKwhFuC85LLXDODSB1n1SlAkOzmljWq4nCfCktnjrebANoMqOgmU2QxMsrmaLKlmgiDa1rhZWwpks/LH4jQW2j7kUljYp0LkyaZOTiL5e4HSM+yAKZQwSieQQAoLlWdhUW+yYNGmLGRtXs5EUeIAFq3wFrUO6H4Z2+cde3v4ijqIpegA+Qq1ubhwmAkDTskMybZIwsLDZ3P2L/Y7bYxsTOatktisdRexqCuXRfuw2dLN3RPYfnGmqFpqhiV/rkZ5P3O2zuKTTKSpdCxsLvY4ceexqC6Ut+OS+wCw6dCAF6K391Xs9+Z3gbUvMQ8Xp2DHgUkvANcvYSIDYFGd6xcDQ+5wvq5eM4A5W4HnioBn8pnxN7Y7ExzXf86OD/n7WBWUt1QWAH/+H4ua+NmIrcLfyaZnN7GIQmgi2z/cIE229aXN/8BbmGm6+ESLDnJ0pGMIi9pSYO8XeOz833Gt8i9YwbEx5s7Ko8Ra6jqHiIXBTY4tR+gWaZMiiAjWSMtKO4oYsbAYXR/0a0vlfG1TCAsAiEgF5u4E/n5Szov/9rjrUGn2X+z9CI52/eWY8grwXDHwxGnv6/4d4TjZZ5EfwAqBYw7ueJvQtmiUEq/OADADG28B4nojOZ2Ftl0LC9G8aR+xcGreFMWZTdVHRrx48A6gs1s8Abm5qvvgz9N4ZeUx5G1Zxm7ofVXLNuGRDJw+Cgur1TtToivEq/ReM9j3whYp+uDmQG+qY74AAOg8Un6MzePq3XkszqxjaZSYHkDSQOnmpHAdQrUqmK28PAjPiXnT6X4mRitShrHHeBOxOPYL2+eTBkspya5Cx+JTnvbNATPZY4xVwOb57Lbxz7AIDsCqnZ44BTx6CHh4n3clpQqlfWpNoWS9Ua4UTJAHvmpo8nRGXRnw6UTWv2f/UmD5LX5FO8RUiM9VIZL3bqp9pNcJPkcsABYxEhufbXqz1UQt2r+wOPYL8E5/YMVDiCreBROvxKPGuciLusT58lLEwjEV4sK8abWylrsAa/JkQydHA6cmhCl5wLXP4twWADw70Dhz2AcKjmO512mvs5N5fYUQpnSCOGio19/cX50qlI2/ek0VPhfxPQ0EJ3+3/9/mCrRUEBbRtsLixCr2u/tUqQPnkfMVzg2cUrmpKCzcmDfF7egh9/zoJh28my9iUVhZj/9uPotwVGOk4ggAoLjT1MA9vz+IPgtRVAPMrPfLo67Hc5/fAywcC7zVA1j1T9/nqdQUy6kp0XtkixSxcJMKKDjAImwh8Sx1pFSztA4gpVDkqhAnJxaxmkQwfYtwHCdFLY5fEFKntuZNd91dxWZj4kVAiOCxcFduKkYr+lwl3dRDEL0nLngQFkoV8Lf3heObkhkUR//dfhmFQn5/GkPGFBa1qCuz31cAdlLd+wUzfH53F/u+rXgIqDwvH3dzd7AGgz4imzd92H6et4k+e/bKpUQJHgtP5k1HRj7IoqA5W5lpvhXQvoXFwW+B5bcyJR3bE5jwHB6JWYgV1pHYeNJFSEx01NtELHied50KKTrG/BVqPRDfz+6uzlHswHSuRDgwKRQ26RAXPgvbfG1zoFQDY4SDwO7FDdW8xcTEGWB30GkyRHEWqA6cNcUND0BOhIUUsbCY5dK5HtOkDpw1RotzA6eUCvFg3izPZWknTsEMrwLd49nJI6e0VrqybTQ2V7bO+GZ3LupMFtwclw0VZ8UJawq+OOFH059A0lmI9uXuZM2m9n7Bcul7FgOfTmJtwW05sZrNyRGNvjsWsI6kvrBnMes/kjSooUkV8E5YiPtWyjA54qMWq0nYlWetq+iCxczK1AG5bNuGHoKwkE7sNuZNsW2804iFuE2dBJHuKRVSUyJHOXr9zeb52bHquCdhAbD38KlsFrW88oOma9qkVMmG9pOr7O/b9CYTEuf3sMmgX93Ajl2cghnJrxKiUzsX+Tzu3a9y05IzrK2BQu3V8VxsUZBXXue6Cs0Z4SmsWSIArBQqalqY9iMsakvtDwDZW1gJF8CaG92/GRj7BPr0HQgAWHes0Pl6ght6LOpMFliED7pBxCJ3J/udMqTB1brk7LY9IUm9LFxELJpbWADMkClWdjgq3rOb2NVBcAxr6dzUpAxjB4Lyc40LcYucXguAZ1GZqHR2m81+IkUsQgRhUXCACUVdOJA8BCqlAr0T2Wfm1MDZIBXiImIhXrmkDLNrXRyt1yAyWA2eD6CBU3TauxAW+3PZ65gewYySO6y98NXOHJgtLThBNTJNbuD2/hBgxcPMpxAczfbLL68BVj8NfD+bNej6+kZWntltEktrAuxKdNenLM/vaeiW1SpPjxwxx3kayBthIX3/bYzK4vsvpEJcVoUU7GffLV24XBJqQ09BWJy8KJzYBfMmb6qXxEqD/axaNMByLK0ByP6GujK57NOWsxuF1F8fOzO7+Px5ZXWSkHGLUt08XSDF6M4JG2FRngP8JfRzGP04MPxe1hY/vi9w8zdMOPa9lpVKV1/weSS5XxGLLKE8ttMIrzoJJ4broFRwMJqtUjdgrxn1MLuwrS1mw/22L2D+nRaifQgLnmcNVz4ezfwOBQdYTb7FyHKn0+dLJ4BJvVhYcPPpYudlVFIqRG4gJUYrFJwTs1TBAfZb/BLb0FVw/NvVgrsrOa26yCoiwAFpzXASF1GqWMtqANjxiX2eTkyD9PaQBgkUujB2gAMCE7UQ15Ge2cCMZ7JYJVNWlF64ys8WhF3n0VJOtH9KBAAXPguHzpsuc9/izAabaAXAQt6igVM6gTQW8crWanaahz6Sz15HWs1BAMAxdS8UVxuxM7v5y/jsGCl0aQXPfvpeBzy8n10N15YIJcPfCKF+jjVXuulr1slQ7Iz6299Znv/Xx93nm/P3shC5JtS5IRnwzmORJzT1ciosWMRC7GPRoBW02Cun8yin360eQjTraL6YCmGfq9VsgFm40Al2TIWITcZie8gXMZKQ5Z2fbMQIR+eRdjdH6jVStZTHdEhzkjGZiazik6xBG8DMmeZ6lv6Z+DybS/PkKdaQTUxDqDTAJfeyvze+7rLLsjMq/TFviqLTy2O5SqmQSk7dVuI4Qx0E3Pg/1g6g7Cyw+p9s/24h2oewqLrAQqWlWaxhzyfjmBM3eShw9UI7Fd09PgSpUUEwmq3461Rxw3UFC2VzNqkQsdQ0RKsC53hlc4EdnKVSSRu6xcrObglpXkh5w+cW2+LG92n+gTyDZ7GwfsF++QthqrNJgzRjD39x7oloduR5YMdC+yFP3iK+ltThLAcMSFegZbUsysBxNqYsMSRsM3tFHKHuVFhIJYBCBYCz3DfPyycRJweZ3kliRMSLjqzeIAoLoEHUorjagIKKegRz9dCXsYNySDf2Wv844kXL56YkbTQL6SYPZRcEM95lJ8dbf2AVG6MeAS77P9b/YM524PI35D4iU+ex8vHoDPa/xeC+X4zY0CljsusZF9L+4iKSVHWB9ZvhFHbGS7uSU7ipChH3Cdu+MDb0TgoDxwH5FfUorjZIr9VskM19wY5iRRQ6omcFYBdVWuGCxqHaDYD9d8QBMR3SqoSFLlwW6Ed+YOkGsartsn+7NyEPv08++frQJNAv86Z4PHeWZnNBV7ESx13HU1dEdQEe3M3a6g+8lZ1HWoj2ISzCEoE521jpDacEwLPGMLd822AuBcdxUtRi7VEnB1LRY2Gqla44ioWSRMdZErCY2YhrAEgY0GBV6bF66fHlwknMbS+LPNdf8CZHHy3XWW96g/3e9yUTQOGd2FVVc9FP2I7jv7KTw8FvgFVPskmZvrie6yvkstWU4XLEwsC+tGIaJDJYw9p5W0zAOSHCYVP9Iho4j+ZXNsx9OvSxqHbWX6D4lH35nwOicDmc7+VwOk/Ynigd+oGI6ZypEefBWc1AWDKGD2L77h9HLshzCloCjmMTXWevY+WFWuHEHhzFBjJNfplFNQbcxAac2aIOAiY+x5rdaYSws7OTqIgoLNxVMInHDld9LAqEi4roDPthb+LjJI+FE9+N1SpH01x8t0J1aimdeuh8hSQYzUYmFrUqBVSOAxXFiIXj9EsnKV62jfVy1NU26iLQ09FA2loQS6MPfgOs+zdL5XSdIPchcoU2BBgptBmwTaU4o64M4HnwPI+yWh+FRdUFls4FZy/yPNA11kmU2xeCIthE3qs+9O/xAaJ9CAuAvaFXfcQGND1ygA28cnHVP1kQFn8eL5S8ExLaMNnVLVSGFFWxg3NMqIOwKDnFrgg1IXL+3ga9VoVEYWLmGTG0pXXjsci1MYK1BKMfZ0aj02uZS3zr++z2kQ95LJUKKEmDmNnWXM/y4Guel++z+GC6ytsNgGdDrkLjG0QsSqsdjJuFR9lVpi5c7qAIeYR6tcGMsyUOIUrxJG41AVar85PIOYfyPwf6JrN9wqlw8QeFkn2OAPMh2CAKi8yQXGmbxmTEIFijRH5Fveuy2raEdBJ1kdopz2V1/5yyQWrKDk8eiwvCCTnR4aLCJhVisliliIXdSanoOBPt6mCn0U6R/qLozKuQ9h2rYLB22hzrwmH22/EEK14wOQqLgv1s39XHyl2HbRD9RUfyW5mw6DGVRX/LzwGHhWjFmCe8e6z4Ot31Jyk4ALyRDvz2OCrrzVI6q0Hrf1eIUaD4Pm67bToiVomd8Sdi0YpoP8JCRBvKdhw34bBhXaIQqlOhpMaI/bkOw7g4Tu4iWGcvLGIdhYV4xRLf16VpSdpRRAXqymNhNoIXhked0vRyue1NSnRX2Wvxze3sS6uPleukmwuOAwYLDXTWvsDMViIGH75wYu5YjAA5hLYb9LAQr9wSB9p9nm4NnLblcxaj3GrZ1mMhRkEcctgi3WJDoFUx4ZLtKFz8RTJw2kcsTgqdHPtAKOFMGgidWolx3dksnd+PBMAw29K4OomKiCmIpIHsgsQVUnWHi89E2l8chIFNK3DRnwU4GC3FfTN5iNsSzH6Cv+fg+QqpAkkWFg5iv7qImffAsXJ1W1y9J5L5dLjTY2Zfm2hdg4uwlkQbyppnBccwgXjlR9435fPGO/P7s8w8vPszqe1/RLDa+5HpUuTIt4tEMRXid8SildD+hIUXqJUKjO8RBwBYc9RJdYhDLwvRoRvrmApx468QaZAzk4SF/RVAdc4+cBYDSvkQTF9agD9a6gA/4V9yY66gKNaa29mY86bmkvuYeU/cDhGjD7lesURRTD84mDcb9LAocHEFCjkdcjDPUVjY7BMWozx10vYkIh5kXKS4VEoFegnCJWARAzEy4jCl93w5+z+h9ji7IXEgAGBKH1aS2OI+i0DgSVjkuPc2SHiKWLjaX9RyKkTMzYdoVfZpC7GplmNbawfk/a5cSoXwglhsMNm0SEj7RXVp+J119Z5I6VfnJ8D0GD30GiXqTJbWdxWdPAR4eC/w6EHWjt1bPKW4ADvjozgBucE8IXeIZdBOjiXuEM8X+RX10kVKW6RDCgsAmNRb8Fkcc+OzEL6EYsQiznGehHhgSXAtLMSIhWR+chGx2LeFNU/ab82A0cLjwa/3SZM3mxVtKCvPun0F8MBWuSNic6NQMpPezGVsO/TsitqnKX6S8BO+3Fr7VIjriIUTYeGqMkT0WACAxdjQvFlbykzFgNPKIZH+KWy/2J9b7uYF+YDKecQir6wWYaiGvkZIhQivdXzPOKgUHE4VVtsPvmqLuPITiHiIIEm4OwHVlclzTRy//zZXxFIraMf+N6LoFYSdK/omh0Gp4HCx0oAS4aPkhYhFAzOo6CeKdRLx1DsRFjxvk351LnoVCk4yFx9yFNWtAV046+PgC95ELCrzpT8vlLPlxLS2V4gpKTfnBmdE6jXShU6rE3I+0GGFxbjusVApOJwurJZb5oo4HJikVIhtxILnvYpYiFeixwqECIWTPhZWKw9jNnMQx/QajSGdI2E0W/HJpjP+vLTGw3FssFBYYss8v4hSxRoHhSXKaQxvUyE1xfJVhziHokHEgn2u0XoNM+KKBwMnB3uXBk6FQvbkmOXGRVLE4rzQmjyqq9tKnyGdWfptV6BKPp00yTKarSisMqCvIpvdENFZ2qbwIDUu7cpOPr+39aiFu4hFTTHzVwBeRCzcVIWIpu3wTg3TKTZ9LKT+B7b+CrMRuOjCC+FAsEaFPsKJ/VSJUB4pRiwcPRaisHA0tgI274nN/lWRy9KMCpXb7XBbFdUW8SQs6ivtvjelpWw/SvBWWFRdBGoKWbVQnO9pbbHN//GCVlSJ4yMdVliEB6lxSTo7qK5zjFrohYYyNawctdCZx6I8h4kDhdr5FYJAz4RQcBxbR0m1wWnEYsuZYvQws9B0j6ET8egkVjL31Y4cKVzf4ZEO8l5+2cToQ1S6LOYcxIld182SU8zo6MKI69bAKaRDeItRMupJYWop1+o+8jO8C9sXj+ZXSuXNjUJq6y2nQgoq6sDzwEDVOXaDbYkk5HRIm/dZuItYiN6GmO6eS7rdnYDE/gnxvRveZ2PedNqxsegYMyHrIpwaJh0Z2plt5/Fi4Vgg9ExxGbGIc7JNzsSW6K9I6Oc23WmXjmkPeEqFiKJPoKaMzVhJCAvybv1iGiS6m19p5L5JwhiBQFWJtQAdVlgAcrOsNY5lp3rmv0ANa/vt1LwpRiviesm19E7Qa1XSCPXjF6qclpvuOnQMKVwxrFBA23koRneLQd/kMBjMVqzY3/LtWVsFDmkMjzimQYAGVSHFVUIZcajWPq3lxIjr1sApfP5GQ13DxkXiUC0nZaa2JIYHISUyCFYe2JdT7unVeUYanS6nQsThRgM1QphXjOQITBbSg/tzy1smDRconF2di+T5UHnlzmNRKEQsnJ3ExcfZRixsOzZKaZABXg1+G5rGolmHL7LPRGFxErHgedljEesuYmEjLPLcp0FEBncSnv98JQzmALWdb0lEwWg1OW+SJZryBerL2fkhIdxFvxNHLgrCIqGf++VcIJeft7JKHB8gYQFg97kylNlGBsR8fk0RLFZeCpnbCQtXjnAn9EywSYc4iVjUZ7Gcb1VYBqANBcdxuG4wyxt+v5eEBQDfUyHO/C8OJwo7U64bf4WIeOXWINcs+Czq6+WTsRSxkNIrnk1cw9PYlenOswFIh0gTTuWIxXlBWHRTCPuUwwkoPkyHQZ0iAABrjrbhqIW7VEiedxEkAHYCocGAMyli4aQJkU3Ewum4bfGK2MsTz1AhTXZSSIVwQsm1nXmzqoAdUzglEJPRcCXuIhYe+uZ0jg5GtF4Do8UauCZuLYmTCbR2iKJRwFLFLjATwn2MWDgId2+xLT9vVZU4PtChhUVqVDB6JoTCYuWx4aRNdYiUCilCSY0BVp61847W20YsRFXqWViIPoujBZUN+lhUG8yIKWcnNVVneeLqjAFJUCk4HDpfgVOBavXclnHwR3ikwF3Egq2j2LY/ie1VpAtcGzjZflFfx07cOrWCNdyqK2OdGQGvcq0j0tnBf/NpJx1hfUXlLGJRCw5WpJgF06GTK1s5HdKGfRauhIXVCggl3V41LbJtemV7AuJ5Oe3gVFjI5aZOOza6EyVOiAvTIT1Gj3qerUNpZcLCrp23uD3RXZ13EnWM4pjq5Kieh+gNx3EYJEQt9p4rc7tsm0CllaedOkuHiJ+PAFfH9iOvzZs+nBuc0SUmBEFqVolztrhtGjg7tLAAYNOF00ZYhMipEDENEqXXspOFiNRx0/NVh+iqPnLeJmJhqgUsJuw9V4ZBilMAAH1X2UwWHaKVegv8crDA59fV7tC6MdI5Ul8JlArGV1uhYLOOepMFVYLRMkavdp46cWBAilxyarId2CX0Iag3sIOU1K+gUCjpDE+VP3c3jOkeI6y/XO7U6i+SeVOOWOSV1yGZK4HGWs+iLE68JKKw2J5VgoraAHg9WgJXwqL4JEtBqoOdpzAcUdlcodoKi/Ic5vVRqFke3RHbclPHVAjPy1fEPrRcHp0RAyPYfqW0smNSiG3EQvJXuBCw4ntiqGBiM3+//bh3D4jm4j3tQVhwnE2PEgdhYbUK85ogCa4gI3vNXjXHMtYCJafZ336mQpS2lTht1DBLwkLIK68/USgPJbNJhRRWOkmD1JUxRzXg1QFqQCo7qZwsrEI1ZxOGq6/E3qyL6M8JzYoccp1XDGBVGb8dzG/ZVsutAbFNszepEPGKISxFjj4BdqmQYiENolEqEFabwwSLSsdMfS7oGhuCyGA16kwWe5+FcBI31IumOlFYCFc+XjrDE8OD0D0+BFY+AFELJw2y8svrkMHlsX+iM5wOvuoSo0f3+BCYrTzWHW+jUQvxJOo4zVM00iYO9G6gnkIhn4BsBa34ucb2cN7cSnzvjTWocDRvVl1g28UpGzaxcsPobjEw8CzlJkYsxFJ2ADb+Chf7WlCkLG6LTsj9K2zHvbtBFBa7z5W2j2ORwwRaiYpc9lkr1EAqiyBHc5VIj9F718678BhrrKWPZd1+/WRQagSAAKVFW4AOLywGpISjU1Qwao0W2cQpCov6CmQXMrUqGjAByKEyZ6VmTogL1SE5Igg8DxzKr5E7e1aeR/nZvdByJtSrI1gY04aJveKhUSpwpqgGJzp6OsSXVIirMmA7YSHOf9GAE/0V8X3dnnAUCg7DnPkglLJ5E7Bx6/soLABgbAbb9zaeKPL6MU5xUm56sdKA7qKwiHV9UpvWlwnab3fnNW4bWgrx++U4zVPyV7g30tqhkdMaEhfdGDcBOx9VpWMfCzFaEd1VNth6wYiu0bAIbdrVMIODFf2Fkw9br4eIBcfJ0biC/fKwvdRLnC/vwIDUcOjUChRXG3GqjXeFBOC6MsRWNIay6F0UV4mrByV7t17x2ONntEJkZDcmjreecTPvphXT4YUFx3G4amASAOCnfYKpTRch9Sa4kM8OrnZXB6L5yodQphi1OJBXLh2Q+IuHEVzIqgaMCYMbXDmE6dQYK6RDVnb0dIgvVSGujJhi1MNYjeJKJgJibStCHMovnSGWhe5wIizq6thBSro6dVf+54LxPVkazukcG1+QzJtMWPA8j4uV9cgQjZtuxM4Nw1Kh4IBtWSU43RZPIkq1HLWwbQcvRix8GArl2IUXgHzycVZqCsgXG/XlUipEutoVL0p82CcAdizonRor/Z+oVyBJzPlbrSwKAbgXseL34dw2IGsj+9vdrBQbtCqlVPa6rY2e7OxwlQoRPls+rhc2C4fcaFTiKm+FhXRu8M+4KTIsLQpKBYdzJbVSt9y2RIcXFgBwpbDTbDpVzPrCKxSsBz2AsiJ2IBablgCwcXV7v/MMEIx/B3LLpZ2u+tx+DDIzhRvczXmf++n9mWr+9VBB+whB+otUFeJF5MalsJDNeGUV5QCEibVeVISIXNKFnbB2ZZfKJ34hOlBTK4iVEK2QS/f9JDK8SxTCg9QoqTFid2OaZUnmTSYsqg1m1BotcirETcQiOSIIEwSB89WOHP+3oSUJYxcLUgdFY618UvdlfoOYSqu1SU1J4sDFhYUugv2uK7epChGFhe/+CpHLB3WR/h6YFAROvBARw/cufDMSYuO3A1+xXhgRnX2KpokN1LaeCYC5uKVxlQoRLgaOWZKxaA871qQH1yHVNmLtjkYaN0VCdWqpCm1rIMzczQwJC7Dc+dDOkbBYeXyzS/BOCOmQ2tICaRmJC76r0oFC2HJvThl44aBiOrcToxVsXaoeU5w+blKveGhUCmQV1bA+GB0Vd10QbTHVyVdvDVotB0mGvNoylvaK0Wt8Eha9EkMRqlOhqt4sNwwS8uy1QsQiOkQDVF8UcukKt74NR9RKhWQoXt2YRlUOwuJipQEcrHLEwk1TNwC4ZURnAMB3e3JRZ2yDvQvChCtMsftqwX42Wjs0EQj38uoTkCMfQrM8mI2smRrgJmIhpGJMNaipZe+/ZN6UhIXvV7RTB6RKfyfYVj6KZsPoDLcDzRp0lO1xuVf+CpGRgrDYnlXaZssgJVylQgTR+L8zehTzzECZpPYyame12rTyblwqBABGCemQ9SeczLNq5ZCwELhlBHNGf70zB2aLFQhhwkJrKAXH2QgLq8Wm1MyHiEVqBDRKBS5WGlCgY3XmUaX7EMQZUa6Oc7muUJ1ayrv/ciDf6TIdAm9TIRePshNIcIx81SrCcZJgNFawk3a6poSNr/bQQVVEpVRgVFd2FfvXKeFkI5Sb1gnlpjEhWjlaEeVbLh0ApvVlUapVhy74fwBX2wuLwsp6JHMlCIaBvdaoLm4eDIzLiEVqVBAq68345WAb3O8cIxa200R9QTJyC5918UlWTaENl8WLI2JJOcCqMACEB6tZMyZRBPgRsQgL0sDEsbTbjYNtjIHuWnnbEpVuX53U52qfnr9fcjjCg9SoqDM1nArd1nCWCrGY2OcL4K/KONTrWNSOqy60b6RlqGIRSUfKzrJJuEqt82ohH5nah3md1h8vkgsL2ggkLASm9U1EZLAa+RX1rIZfOKBEcxVIiQxCkGjIK81iJXzqYI8HZ1t0aiUGCs2HtlTG2N1XnDTB7ZXDVYPYQfKHvefb/pWCv4hpDE9VIeLUSFddDYXQttj0JsMiDAiL7+22g6otYlnoX6cEg6VKbJDFhEV0iMYmXO77rIAx3WMQHqTGhcp6//PZDn0sLlTWo5uYBonxcGULZlS9eTiLWnyxLbvtpeFEYVEhRCxytrPfnUb4th6bnjYAbCIOvaX9q8F7o1RJfp5gC4syhulUgigxMeHhRYmnM1Qa9rn2iLHZVz0ZN0UUCuDaz4CxTwL3bgA6eWfclJ5bqZA8X38eb3tX0XY4S4WUnAGsJtRzQcjjYzBleF8mwsGzah4A2PQmMC8FeK0TcPIP+3VKjbF6e1d15IG+yWFIjQpCncmCDY01czczJCwEdGolbrs0DQCwcNMZ8GGs82VfRTa62aVBhJ0nrhebwOkDYgOkLedqYImXQ2Uho2a7fdzk3vGICGYnGulk1tGQjJc26SCzETj4rf0Iek/9KKQeJezAmGI46X55J4gRpH055Wyuh0NVCItYuGmg5AGtSokZQqnx93v9rMxw6LxpXxHi4cpW4MZhqdCpFTh8vhLbstqYYc82FWK1AjnCRFNPg8ccCXbwWNi4/qvqTbjmoy3o8dxqXLtgK3JLbU5SgoEzHDXQKBWsS6atv8KHFIQtnEOKC4DnUlNbMiYBE/7lcfiZKyb0FIVFGz8OOav2ESp2TvKpADhk9kyQBzFWCU7OIz+y34ZKYMs79utsZMdNRziOw+X92PP/3MZGO5CwsOGOSztDq1LgQF4F9uvZSOVJir0Ym2bTga8ROdIRQkXBtqwSbB3wGp403Yurgz9HQnf3LnWtSomrBrIDZZs10zUWZ3Mb9iwBfrgH+OJK+TZPrdaFK1BrtdCmt0bwY/ggLFKjgpEeq4fZymPjySIpFWIwsIN9TIjGr1JTW64VWrqvPnxBmpjqEw4Ri4uV9ejuopW3K6L0Glw/hOX1F23K8n0bWhLbVEjxCeZ3UQf79DkDsIlYCMJK2L+sCf0x96t92JtTDqPZij3nynDLpzuk/iiigTOMq0Hn6GAoFJxf1WQNkD5XoYGa1eJdRUiAGJsRC45j4wnaYrWChJQKsXkNwsXAEXMy9Bola29vK1CNtfIFAwCc2wKUZcv/S6b+xhk3bRGPA2uPFbLCgjYCCQsbokO0uPkSFqK8/08e2dZ4BHMG/C1ov7xQI8qJBneORKhOhYuVBjy10YBvLZno18O7XNwtwnatOXax4Zj3joDosbBNhRz4iv3O38vCmMYat6PPAUgD5oKMpQB4hJQecb+8CybbDrATUiFmUVjo1XIu3ceyQpGBqRFIj9GjzmTBqkN+lBo7TDctrLJJhXjKxdtw9+gu4Dhg/YkinGxLvVSEiCMq8+VoRcpQjymgBtimQnheilgcNHfGppNF0KkVmH/DAHSKCkZOaS1e+U048dhELNJihJPYhUAICyEFIkYsyrLZ3yqdV5NSG0t0iBbDhLJTv/bL1oKzVIggGk7wqRiRHg21UsHMvgDbjy4cYv6tkHigyzh2+8Fv2G+et5lPFJiIBQB0jw/FsDSHwoI2AAkLBx6akIFQrQoXq4z4xcrCptE5Nrk0qZzI951Hp1bi5uFMIOQL0yPFsLonMuJDMaFnHHgeWPRXG7t6DARiVYjFIBupLDZX8js+BrK3sBx2eCfXB1nBOxPLVaBvaB0UtUWsC6KPB3txEuj644WwKNjBXiF0RIwxX2QHLKUWiPTeh2MLx3G4dog4iM6PdIjDdNPCijpkcL5FLAAgLUaPqUKb7zYVtRBD2MYq4NB37O9OI31fj2jerC0Gys+xGT9KDT4/zd7f64ak4JrBKfjg5kHgOODHfeexPatEMkmGczVIF4WFFO1sRMWAKBiFCafSFXRsD59Ts/4yvb/QEbgtCwuNE/Om8Pmc4FOl0lq7yFf+XvZ30mCg3/Xs71PCuaH8HEuXKFQ+X6R44pZLmNfpf9vPtZnpsiQsHIjSa/DqNf0QplPhL4twAMjZzhRpeQ4LiSlUvodUBWaNSoNKmDkytU+C1BDJG+4dy2rUv92di3MlHSxqobHxuRirBQf3Cfm2wz8Ap9eyv7uOd53DFjwW0ahEZph4ou0hX8F4yaBOkYjWa1BZb0ZuHUuFRKAKOrUCwWXH5fU2wsR19aBkcBwr78v2NUrl4LGwVuRBzxlgVajd9zpwwmxhv/tp/3nklTkZ2tQa0ejlfhLntrDffa/1fT2ix6KuDDjPmtmZY3rit6MsNXLjUHah0D8lQrpomLfqOHhBWISJEYuaYrlZV2NSFkoxYiEIC1/8FQFiWt8EcBzzGNn5StoSaodyU2ONlNY4aU2RRpfbpULOC8IieTDQZQz7O38fW8e5rez/pMGyfyNAXN4vEQlhOhRWGfBjG5l2TcLCCTMGJGHf85fh46dmg1eo2QGhLFveeRIH2k8+9IHE8CC8N3MQnr28Fz68ZbD9YDMPjEiPxtjusTBZeLzx+wnPD2hPqDTywaC2lKU+LEYWFdCFsyvKnZ+w+7uOd70eIbQdw1VgsFrwq/ghEpUKDlOFstBdxSy8HstVIFqvBSce7P1Mg4gkRQRJg+i+2HbOtweLJY915bBYeURWs6FslsiuPqcDBneKxMiu0TBZeHzw52nftqMlsf1ck4cCsd73E5EIjgIgfEeFKoA8XXcYzVZ0jw+RRlwDwKOTuiNIrcSB3HLk1DIBEM7VoEuMXk6hRnaR03r+4Gje9LYiJIDEhekwQmgU9+2eNtr23TEVUnQcAI8iPgwlCJeGgMnVRXmyQE0azJqLhSWz0uO8XfJ9nf2IinlAo1LgnjEs8rlg4xkYzVYPj2h5SFi4QKngEBURDk5s85y7QxYWjdx5Lu+XiNlj030SFSJPT+sJjgN+O1iAfTltvJbcV8KFBkHlOfLMhYR+rNGPCKeU859gXQLv+XwXHlm2D5tPFUsei2iuAj1N/vkrRK4UDLUb89nXKJYrZyPYA3iwnzUyDQDwze5cVoHiLeIBsaoARZV16AqWn1XG+7dNf7+MnZS/3ZOHU23Fa3HlB/IV55A7/FuHQimICwAHlwEAtlpZ2mxc91i5+yVYe/hZo9IAAH+eY2mxMNQKwkLcXxuZf5fKroXPQJyg24zCAgBmCp6v5buEvj9tDcdUiPCdPWlNRVp0sNzQTNx/8naxqIUmBEgbzSKiYoVRzraAnRtcMXN4J8SEaHCupBZLd/h4kdECkLDwhDikJ2d7k+883tArMUxyCr+68ljb6y/QGMTa//Jzcp+I+N5ArxnyMhOfk04E3+zKxc2LdmDtsUL8vD8ft/53B97bUQ4AiOKqkVgqTHh0F+Fww9DOkUgK1yHXyK5AY7kK1snTjxkhrhibEYuusXpUG8z4crsPFUGhCQA4wGpC4cU8yV+h8PMENKRzFCb3jofFyuOZHw/B2hb6qUR0Au5ZB1z3GTDwVv/XI6ZDAIBT4sti1uBuZLeYBoveNzYdoVoVsqrZiSlKWYu4UG2jqsnsEL0jlQV2DZ2aW1hM6ROPKL0GFysNWHusDU7BdUyFiMKCT0GfJJsmYo5N9rpPlf1L4nlgwzzW30ih8nqom6/otSo8NpmJ+3fXnUJFrQ8XGS0ACQtPdBZmeBz+nrXy5RRNtvN4y98v6w6dWoFd2WX4qY3VNzeKSGZiQnmObKRK6A9kTAGG3wdc/iYw+jEArAri378x8XHdkBTcNIxFO97ZWgILz64yOd7KjJ4+tNy2RaHgcN2QFBTxEQCAWJRjQFKwfLB31fLZx+eYk8kqhxZuOoMab0tPlWrJT1J+4RwyFJ5nhHjixb/1QbBGiV3ZZfhmdxtxqIclMm+FohGHOpv3zBA/CEfLFFDZTLq1JSJYg9lj01HJsxNXF72JRTUKhP4XjakIAWyqXfLYycxqYlfRYjSvmdCqlJg5nD3nRxvOtL0LHFFYmATvkiD8jvOd0McmvYWwJLsIKPpcJf/dY5o0IgAAMOAmr6Zd+8uNQ1OREReC8loTPlh/qsmeJxCQsPBExmRWYWAQmjD1v1EOjbYQieFBeGgCu2r6v1+PobzW2KLb02yIEYvSs/II7NRLmEHy8jeA4XKjsbfXnEJVvRn9U8Lx+rX98dq1/fGf6/qDUyhRgGh5nd0m+t2sCABuH5mGShWbDaHhLJiVWii0fA5z3fLZR64cmIS06GCU1Zqw0JfKDOFqy1B0Fj05QQg04oo5OSIIjwtXTa+uPIaiKoPf62pTTH1NOqEfi2LRrf4p4QjROjfm3j+uK6YNZZU3GWFmVkkieix8GYDmDNsqBTEKEtujUfuwv9w1qgt0agUO5lWwfi5tCa3QcK++QigjZtV+J6yp6JVoIyw4Dpi5DBhwM5sE222yfF9YEjD+afn/0Y836SarlAo8M51Fpj7feq5VTx4mYeEJpRoY90/2t0IFjPtHy26PwOwx6ciIC0FJjRGvrTre0pvTPEQIEYtTfzChpwlxmm6oNpilTnXPXN5L8rJcPzQVqx8ZA276W7K5secVjdqkmBAtrhveFeU8y9mGnVvD7kgaGLCDvUqpwBNT2FXzxxvPeF+ZEcpOQtEFm6DjTKhThgHRXRu1LbNGpqFvchgq6814ZNm+tplf95XwZOC+jcDVC/GdYhoAYFgX1xcXGpUCU4ex/ZKrKRLaifNsbkxoQuO2xVn5Y4DLG70lOkSLW4VSyOd/PtK25lmI5egVecwIXlsME6/EMb4TeiaE2i+rCQauXgDc+n3DuT8j5gKjHgVmvNvo75Y3ZHaPxfgesTBarPj7twda7fePhIU39L8ByHwGuOpjn0v1mgqNSoFXr2HlsMt25fo/U6ItIUYsxAmnyUOclnP+eiAftUYL0mP1uMThBJARH4rk4VcBD+4Cbv+ZRSwayTOX94I6XBgKdfxX9ruxV6YOTO+XiEu6RMFgtuKZHw97F3oWTkI9ytYDAEoj+zVa7KiUCsy/YSCCNUpsPVPSdvwWjUUfAwy4ETtz2b43pFOk++XjerELkaoCYP9SdlsgvFl25Y/72N/Jgxu/Xj95eFIGksJ1yCmtxT+/P9R2ZhmFxLGLC94KHGZ9To7zqdDogpEQ5sPQQKUKmPwSMGRW02ynAxzHYd41/RGmU+FAbjne/ONkszyvr5Cw8AaFEsh8Cuh/fUtviR3D0qIwU6id//s3+1u9oafRODa9cuF1+U4ogbthaKqda9+O0AQgPTMgUQWNSgF9lHDALxcc2wEWFhzH4ZWr+0GrUmDTySJ8vjXb84MEo5/eyk6Ghjj/5kM40j0+FPNvGAgFB3yzO6/DiIuKOhNOCeHnwZ09CAttCJAynP199Gf2W/RrNQYxYlFfAZzbzP72dWJrAAnTqfGf6wdApeCw4kA+7vvfHhRWtYHW0xwnTyA9uJz9snZFj/hQ18eMVkJCuA7zrmFtwz/eeAYrWuHUaxIWbZx/Te+FtOhg5FfU45mfDrU9E5UvBDkczHtOb7DIhYp67D7HynDF+SrNgjjcTCTZ/fwXf+gWF4KnprLc/f/9dgxbzxS7f4CDx0PZeXjAtmVq3wS8fSMTF8t25eKfPxxsO1erfrI/txw8D3SODmaD5jyRnmnzD8fKFBuLLkweyAewdKCf5uNAMapbDN6bOQgqBYe1xy5i8vxN+HZ3bus/FsUwnxpKmW/pAJ+O7o5pkFbK9P6JmC30tvj7N/uxvpVNmyVh0cbRa1V49yb2pf7tYAGWtaF+8j7DcYJDmwOuWsB8DA78cZR1NxzcKQIJ4T6ENBuL3kZYRHQCQrxr1e4rd45Kw98GJMFs5TFn6V73HTltSuUMvBoR3QNbJn3lwGRJXHyzOw+PLNvXJpr3+Mue7FIArGGYV9gKi5EPAhEBqtywLYFMHNhsrbzdcXm/RPz84Cj0TQ5DRZ0JT353EHcs3tW6B5VFZ9j9K0Ys2gr/nNYL0/slwmThcc8Xu/HpX1mtxnNBwqIdMCA1Qqpxfu6nw23Poe0LN30FPHIAGHiz07tXHWLCYlrfxObcKnshMfLhJnsajuPwxnX9MSAlHOW1Jty5ZBcuVLgIPYueFABvae5DeGTgxc6VA5Pxwc2DoVZy+PVgAe77327Um9rGPANfEUfHO/p2XJI8hAnhrhOBCc8FbkOsNibJjMmul2tm+iSF46c5o/DU1J7QCCm7y+ZvxPJdOa0zehEjD4A8y6XiBJ+CjPhGdEVtZpQKDm/fOBDXDEqGxcrj/347honzN+KdtSexK7u0RUU+CYt2wgPjuuKqgexK9oEv9+BQXkVLb1LToA2R+1k4UFpjxI6z7OAvtttuNnpdydIf0+fblb02BTq1EotuH4rkiCCcLa7BjQu3Ob8yjEzDlh5PY47xYeR0uqbJtufyfolYdPtQ6NQKrD9RhDs+2+lbl9AWxNsTXq3RjH055QCAkV0bNsZyilIF3LECuO0HQOVF6sRbxJSKWg9cOjdw6w0AKqUCD2R2xapHxmBo50jUGC146vtDmP3FHtcCuKWwiVjMM1wHHgr75lhtAI1KgbduGIBXr+6H8CA1zpXU4p21p3D9x9tatByVhEU7QaHg8MZ1AzCqWzRqjRbc9tkO7DnXsVp+rzl6AVYe6JMUhtSowA4C8khMN2D2OmDY3c3ydHFhOiy/bwRSo4JwrqQWN3y8DYfPNxST33JTsNI6An2SwpysJXBk9ojDF3ddghCtCjvOluLWT3egtKZ19lepMZgxb+UxjJy3Dl2eXolBL/+BB77cg62ni10KjV3ZZTBbeSRHBCE1yreBdQFnzOPA2CeBh/f5Pga+megaG4Ll912Kp6f1hEapwNpjFzHuP+sxb+UxlLWW/SKuF9Drb7jY9Xr8YR2KTlHBCA9qne+nOziOw82XdMK2pyfgjev6Y3r/RHSLC2lYNtuMkLBoR2hUCnx86xAM6hSB8loTbvl0O9a1xXa7frL6sJgGaeZoRQuREhmMb+67FF1i9DhfXodrFmxtEHY+nM8au0nTGpuQ4V2i8PXsEYgMVuNAXgWuXbC11U3hzS+vwxXvb8Ynm7KQL1xBl9WasOrwBdz86Q5c+eEWrD9e2EBgbDnNjLIju0a3fNVAZBow4V9AaHzLbocHlAoO943rip8fHIXhaaxU+pNNWRj9+p94Y/XxlheeCiVw4//wY6enAXB2A+XaIsEaFW4YmooPbx6MtY+Pg8KPWVSBgoRFOyNUp8bSey7B+B6xqDdZMfuL3fhow+nWmeMMIKU1Rmw53UJpkBYkMTwIP84ZiQk942A0W/HU94dw+2c7cfJiFcpqjDhTxMKhfZrpoNkvJRzf3n+plKa55qOt2JHVOnqsVNabcMdnO3G2uAaJ4Tp8fOtg7Hx2In6YMxK3X9pZ6iJ555JduP2znTh+gYmyepNFKmGe0DPO3VMQTuiVGIbl943A4juHoXdiGGqMFny04QxGv/4nXlt1vMXL5MVIX3OI744CxzfzGaeyshLh4eGoqKhAWFjgDnYXay7iVPkpjE4OQEmXB6y8FVnlWbDwskmtc1hn6FTNWIXgAZPFin/9eBjLhZkOk3vH4/Vr+yNKr2nhLWsaPvjzFN784yT6JYfjl4eafh9obVitPBZsPIN3156C0WKFggPE6s+MuBCseXyc+xUEmMLKetz1+S4cPl8JjmOdYh+f3B06dctVMPz9mwP4fm8eEsJ0+H7OSCRH2Kc0SqoN+GRTFpZsyZbewxuHpSI2VIf31p1CckQQNj6ZCZXS/+sxK2/FucpzsFgtUCqUUClUUCvUiA6KhlrhXxi+uK4YJXXOxRvHcUgNTUWQqoXTNwI8z2PN0Yt4d90pHBGiaWE6FeaO74Y7Rqa1yP4x/s0NOFtcgy/uGo6x3b03OBstRpyvPg+jxb/Ii0apQVpYWstHwHzA2/N3uxAWRbVFuG3VbSisLcSHEz/EpUmXBmS9zjBYDHhg7QPYdWGX3e1qhRrXdb8OTw570u8DRKDheR7LduXihZ+PwGixIiJYjWem9cJ1Q1JaNEwWaOpNFox9Yz0Kqwx458aBuGpQM/avcMPRkqN4e8/b2HNxD8K14ZjYaSLu7HsnkkOabvvOldRg3srjWH2EpYU0KgV+eGBki1yN1RjMeOmXI/hmN7vaT41iM26uGZTcqJOzP6w9ehH3fLEbHAd8d/+lGNLZdWVHTkktXl99HL8dKrC7/bkreuPu0V383oYTpSfw3JbncKz0WIP7EvQJeCfzHfSJ8X5Imclqwus7X8e3J7+FlXddAaDklLi99+14bMhj0kmM53kcKDqA3Rd3Q6vUYnjCcPSI8n9Ana/wPI+1xwrx5u8ncOIiGwGfFK7D3WPSce3gZEQEN88F0PnyOox67U9wHLD3X5MR6cWFl5W3YsmRJViwfwHqLY0zpHaL6IYXLn0BA+MGNmo9zUWHEhZmqxn/2PQPrDm3BkGqIMzsORMze85Egj7wIfF/bf4Xfj7zM9QKNSK0EQCY2Kg0MvV9ScIlmD9+PsI0rSdfdyivAk9+dwDHL7AvcFp0MG4c1gkzBiQiJbKZTY5NwNM/HMTXO3MRH6bFX/+YAI2q5TN8J0pP4LZVt6HObF+toVPqcG//e3FHnzugUTbdwfNQXgV+OZiPS7tGY3yPlg3frz16Ec/8eAiFwtCyTlHBuG1EZ1w/NKVZTiDltUZMfnsTiqoMuHdsOp653LsR47uzS/HG6hPIK6vFjIFJeOKyHlD7KYhMVhOu+fkaZFdmQ6PQQK/Ww2w1w8ybYbKYYObN0Cl1eG3Ma5jY2bs288uOL8MrO14BAMQExYBDw4sFo9WICgML9T848EHc2/9enK08i39v+zd2X9xtt+yguEF4ZPAjGBLffJ08LVYeP+zNw/w1J1EgeF60KgUm9IxDZo9YjOse16T9aBZvOYuXfjmKYWmR+PZ+z31e6s31+Odf/8S6nHUAgGBVMPRqvV/PXWmshMFiQIQ2AsuvWI6kkCTPD2phOpSwAFhY6pH1j2DzedbmVsWpcGnSpZjaZSrGp45HqKbxDtmt57fivrX3QcEp8PGkj6XICM/z2Ji3EU9tegq15lqkhaXh9bGvo3d048dmBwqTxYolW7Lx7rpTqLYZvZ0cEYRhaZHomRiGbrEhCNWpEKRRosZgQWW9CRV1JlTWsd9Wnkf3+FD0TgxD19iQVhH1+HpnDp7+4RA4Dlhy53CM8yGUaYvZasbOCzuRX52PEHUI+sT0QWqofw2Nakw1uObna5Bfk4+h8UPx7CXPorCuEAsPLsSei3sAAGlhafjXiH/hkkTnbcnbG3VGC/63PRsfb8ySTHtalQJ/G5CE2y9NQ7+Upomo8DyPuV/txcpDF9A1Vo/fHh7TIuH2b058g39v/zeidFH44W8/IDpInrBbbazGE5uewJbzWwAAN/W4CY8NeQzBavei/+bfbsah4kN4ZPAjuKffPU6X4Xke/zv6P/xn938AsJRtXlUeLLwFOqUOY1PGwmAxYGv+VpiszOswOnk0Hhn8CHpG9QzES/eKepMF3+/Nw5fbc3CsoNLuvh7xoRiRHoXhXaIxvEsUYkMDV7p708Jt2J5Vin9N74V7xrifA2WxWvDQnw/hr/N/Qa1Q49lLnsU1Gdf4ncqoNFZi9h+zcbTkKNLC0vDpZZ8iXt+6DbkdTlgALES1MXcjvjj6hZ0aVyvUGJU8ClPSpmB86ni/FGaNqQbX/3I9cqtycWuvW/HU8KcaLHOi9ATmrpuLi7UXoeJUmDtoLu7oc0erSY0ALDz928ECfLM7F/tyy/1uwxyt12BktxiM7haN0RmxDfLVzcG+nDLc+Ml2GC1WPDmlB+aO7+b5QU7YUbADz2x+BoW19m1xe0f3xuVdLscV6VfYnQg88drO17D02FIkhyRj+RXLEa5lJ02e5/Hb2d/w5q43UVLPcuLT0qZhzsA5SAtP82vb2xq1RjNW7M/HF9vO4ajNCaRbXAgu6x2PgakRiAvTISpYA61aAa1KAZ1aCY1S4bOQ5XkeH204g//8fgJqJYfv7h+JAakRAX5Fnqk11eLyHy5HSX0Jnh7+NG7u1bC5m9lqxpu738TSY2xgWZI+CY8MfgRT0qZA6aSzZlZFFq786UqoOBXWXr/W7f7J8zyWHluKt/e8DaOVibrM1Ez8c/g/pbTcxZqL+OTgJ/jh1A+Sd2xq2lQ8OOhBdA5z3jemKeB5HofPV2Ld8YvYcKIIB/JYG3VbEsN16JEQivhQHXRqBTiOQ7XBjBqDGXUmC/QaFcKC1AgLUiFMp0aYToVQnRohWhVCdSqE6FQI1aqRVVyNu5bsgpUH/vrHeI8l6vP3zMfiw4uhVWqxYNICDEto/DygguoC3LH6DhTUFCAuOA5vjnsTgwI006cp6JDCwpas8iz8nv07VmevRlZFlnS7SqFC/5j+GJ44HMMThmNA7ACPIWkrb8VTm57C6uzViA+Ox89X/exSnJTXl+OlbS9hbc5aAEBKSAoeHPQgpqZNdXqAEOF5HgU1BSg3lCNYFYwEfUKTm0GrDWbsOVeGQ3nlOH6hCtklNag1WFBnsiBIo0R4kNrux2LlceJCFY7kV6LOobtilxg2SbRLjB6do4PROVqPTlHB0GsbTh8NBEVVBsx4fzMuVNZjSp94fHzrEL+uHL49+S1e3f4qzLwZUboo9IvphzJDGY4UH5EOsCpOhXGp43BNxjUYmTQSKoXr13S4+DBu/u1m8ODxyeRPMDKpYXi1yliF9/e9j2XHl4EHDwWnwOVdLse1GddicPxgKLimS+XUmmrx0+mfsDZnLXIqc6DgFEgNTUW/mH4YEDsAg+MHS0KoKeF5HntzyvDFtnNYeagAJovnw5BGyYSGVq0UfiugUykb/NapFdCqlDhbXIOdQhtub65Im4oF+xfgowMfoVNoJ/x05U9Qu+k9sS1/G17a9hLOV58HAHQK7YSbe92MqWlT7cTDs5ufxYozK5CZkon3J77v1XZcrLmIM+VnEBMcg+6RzueL5FTm4IP9H2DV2VUAmD/j6oyrcVvv25Ae3vzvX2mNETuySrA9qwQ7zpZK6dxAcnm/BHx0i/v0z4ozK/Ds5mcBAG+MfQPTukwL2PPnV+fjvjX3IbsyGxw4XJNxDe7qexc6hXXy/OBmpkmFxYcffoj//Oc/uHDhAgYMGID3338fw4d7N+CouYSFCM/zOF1+Gr9n/47fs39HdmW23f1apRYD4wZiUNwg9IzqiV5RvZCoT5ROUvnV+Xht52tYn7seKk6FxVMXezTa8DyPFWdW4O09b0tXpon6RFzd7Wpc0fUKKcRusBiw5fwWrDm3Bn+d/0vKhYrEBcWhV3Qv9I7ujV5R7HdccFyLu4iNZiv255Zj86kibD5djAN5FS4jHzEhWqRFB6NTdDA6R+mRFhOMTlFMeEQGq/16LRV1rEfH4fOV6Bqrx09zRyFU51tUyGK14M3db+LLY18CAKanT8dLI1+CVsnCrCV1JVhzbg1WnFmBQ8WHpMfFBcVhWpdpGJc6DoPiBtmJDJPVhFt+uwXHSo9hevp0vDbmNbfbcKzkGD7c/yE25m2UbkvSJ2FU8igMiR+CIfFDAuoT2le4D89ufha5Va7nyXDgkBGZgcFxg9E7uje6R3ZHekR6k1YVVNabsOFEEdYdu4js4hoUVhlQXmuCwWxBY+eaKTjg6Wm9cM+YLk32vREPoc7Wf7DoIO5cfSeMViPeHPcmpqRN8bi+WlMtvjj6Bb489qV0TFBySgxNGIpLEi6BRqnBm7vfBAcOX17+JfrH9g/sCwKLvr637z1sytsk3dYnug+mpE3B6OTR6BbRrUWOQ5X1Jpy8UIUTF6tQXmtCndECHjz0WhVCtCroVErUGs2orDdLKdyqejOqDWZU1ZtQZTCjqp79XW+yYpowTM82PcbzPM6Un0FWRRbKDeU4UHQAK86sAADM7jcbDw8OfMv+GlMNXt3xqvQ8HDiMSxmHCZ0mYETiCCSGNPOIAhc0mbBYvnw5br/9dnz88ce45JJL8M477+Dbb7/FiRMnEBfn2STW3MLCFp7nkVedh50FO7Hjwg7sLNgpnfhtCVWHIikkCWarGVkVWeDBQ61Q49+j/o3p6Q0narqi1lSLL499ic+PfC6ZOwEWxYjSReFMxRnUmOQGQmqFGpHaSFSZqhqY/kSiddHoHd0bXSO6IlGfiKSQJCTqE5EYkohQdcuM/K2sN2HbmRIcPl+BcyW1OFdai3MlNSj3UJ8eqlOx6EYUi3IkRgQhWq9BlF6D8CA1/r+9ew2K6jzjAP7fO7tyWXBhAeUionjBS9VItrnUFhKxaY1NZ2qtmcG0Y8bUdGJzaTRtNfGLmelMpk2b8UuT2A+d0iajMTEmqUGlGhEFoQIa5KYosotc9gJ73/P0A9kjy11c2Eufn+6cs+ecXZ+H9+Xs4znnPSuRAESAQASvj+D2CbjePYB3TjXjeo8ds2cp8cEOA3KSA+/vL5CAFnMLrvVdQ4+jB2aXGVKJFDHyGMQqYuEVvPi09VPU99QDuHtR21g/u6a+JhxuOoxjrcdgdpnF5bMUs7AyeSVWpKxARlwGPmn5BOdun0O8Mh4fb/p40qdPGrobUNpYihM3TgT0BwDQa/RYmLgQeUl5YpunaFKQokkRi6CJuH1uvFP7Dg41HIJAAvQaPbYt3YYVySsgQEBTXxPquutQ01WDNkvbiNdLJVJkxmUiJyEHc+PmYm7cXMyJnYOkmCRoVVokxiRCI9dMS9/z+AS4vAJcHt/g1CvA5fXB6RHg9C/z+OAcNnV5BcTHyPHIgmRk66Z2cd1o3D43qkxVONtxFuc6zsFoN8LpdUICCXQaHfQaPTLjMpEZnwm3z41/Nv4TVrcV6zLW4e3vvn1PPyP/0aVjrccCilu/zXmb8bsHfxe03EZzyXQJ79W/h686voKX7l6bpVPrkK/Lx9LZS5Edn425cXOhVWkRq4jFLOWssDr9OxafQJANOb12x34Hn7R+giNNR0b8BxQAtizagt1rd0/rEcVqUzXerXsXZzrOBCxPiklCTkIO5mvnIzs+W9wHpM5Kva+hyvdq2gqLgoICPPDAA/jLX/4CABAEARkZGfjVr36F3bt3By2wmUBEaLW04oLxAhq6G/B179doMbcE/AIBQEFaAX696tf3NBRsKJfPhS9vfIkjzUdQZawKuP+FXqPHY1mP4bGsx7AseRkUUgWICBaXBW3WNlzpuSI+Wi2t4w4rm6WYhURVIhJjEpGgSoBWpYVWpUW8Kh4auQZquTrgoZAOHjGQSWSQSqTivDj95ipziUQC/x+pRApIID6XSCSQYsiyITtOm8OLDrMdt/ocuG1x4FavHR0WJ2732XGn3zWJn9zYXVMXq8SBp5YhJ0WDXkcvuuxdaOxrREN3Axp6GtDvmfg++Wq5Gvsf2o/i7OJJxDL4oVJ+qxyn2k/hTMeZgCJj6Hu+te6tKd1Pxel1ouJ2BapMVag2VeNq79Vx29vf1nHKOMQr4xGnjBPnY+QxUMlU6HP24YvrX+BW/+CQz43zN+LVta+OOWqp29GNS6ZLqL1Ti2t913Ct9xr6XBPfGl4pVUIboxU/XPzxxCpjA+Lz9zulTAmFVCHO+58rpUpIpYM77qG7JhraFwJmR99m6Gvdghs9jh7xfg/djm50O7vh9N4dKiiBBAqZAiqZCiqZCkqZMmDq8rrQ0NOAC8YLYxb9Y1k6eyneXf/ulEcPAMAN6w2cu30OF40X0e3oxnczvounFz897mmVYOpx9OCL61/gTMcZXDRehMs3/u9vjCwGsxSzoJaroVHc3fdo5BqoFUPmh+yP/P1AKVVCIVMETqUKSKVScR/kn/r3W1IMTv3tTt/88XcJAoGIxD4y9HmzuRlftA3m5t83x8hisDBpIZJikjA3di6+l/m9oFxTMVmtllYcbz2O853nUd9dH/CZMRq1XI1ZilnQyDVQyVWQS+Q4WHTwnq4Nm4xpKSzcbjc0Gg0+/PBDbNq0SVxeUlICs9mMo0ePjniNy+WCy3W3E1qtVmRkZIRFYTEat8+NG9YbMNlNICIsSlqEZE3wvhXS4rKgsbcRNo8NqbNSsThp8aQrYIfXgcbeRlztvYp2azs6BzoHH/2dk9r5/z9Ry9VYnLQYeo0e2hgtiAgunws2tw0SiQS52lz8JO8n0Kkn+YVSw/gEH5rMTbhkuoT67nrcHriNObFz8PTip7F49uSGM05kwDMgfrhf67uGVksrTHYTuuxdE+7Yh0uKScJew14UZk5uKKMfEaHH2YNrvddww3YDt2y3cMt2C50Dg32uz9l3z7FEumR1Mh6e8zAenvMw8pLyoJar4RN8uOO4g86BTty03US7tR0AsEq/Cj/I+cG41+VEGqfXiau9V1F3pw6NfY24abuJDlvHuEdaI8XK5JXYlLsJ67PXI1YZHt906vA60GppRau5Fc3mZnT0d8A0MLgf6LJ3jfiPsN+pn5ya8v5tLNNSWNy+fRtz5szBuXPnYDDcvQnVb37zG5SXl6OysnLEa15//XW88cYbI5aHa2ERqeweO0x2E8wuM8xO8+D0m4fVbYXD64DD44DD64DT54TD64BX8MJHPhARBBLEeR/5IJAwssr/Zt6/bvAvjdh2+Hj6iQ7/TrT9iPVDn0sGPzR1ah2y47ORr8tHvi4fudrcqNqZD+U/omWym2BxWWBz22B1W2F1W2Fz22Bz2+DyueDwOhCnjBPPjU80fHGqsTi8DphdZvQ5+2BxW8QY+t39d2PyDC5zep1w+9zwCB64BTc8Pk/Ac7fPHXC0Yay+M7QPDN0mYPk38zKpDDq1DrPVs6FT66CL0SFZkxxw3YhAAtw+txiDy+cSpy6fCzKJDPO181GQVoC8xLyQX+cUrjyCBwPuAfR7+jHgGYDD64Dda4fD883U67i7zOuA3XN3mcd3tw94BM+IqUDC4L4KQsC+aOhy/5FUfzfwH0UVl+Nuf/GvS9GkwJBmwMbcjSG5QPV+CCTA7DJjwD0Au9eOAc8AXD4XPIIHhjRD0I9oTbawmPY97549e/Diiy8GBJaRMbX7A7CxaRQazEuY+l0BWeSQSCSDpx1itKEOBRKJBBqFBhqFJiJu8MOml0KqCJu++f9AKpEiKSYJSTFj30k2FO6psNDpdJDJZDCZAr8x02QyITV19KvXVSoVVKrg3dCEMcYYY+Hrni5vVSqVWL16NcrKysRlgiCgrKws4NQIY4wxxv4/3fOpkBdffBElJSVYs2YN1q5diz/+8Y8YGBjAM888Mx3xMcYYYyyC3HNhsXnzZty5cwd79+6F0WjEypUr8fnnn0OvD+97nDPGGGNs+kXtLb0ZY4wxFjyT/fwO/fdLM8YYYyxqcGHBGGOMsaDhwoIxxhhjQcOFBWOMMcaChgsLxhhjjAUNFxaMMcYYCxouLBhjjDEWNFxYMMYYYyxouLBgjDHGWNBM+9emD+e/0afVap3pf5oxxhhjU+T/3J7oht0zXljYbDYAQEZGxkz/04wxxhi7TzabDQkJCWOun/HvChEEAbdv30ZcXBwkEknQ3tdqtSIjIwM3b96M2u8gifYcoz0/IPpzjPb8gOjPMdrzA6I/x+nKj4hgs9mQnp4OqXTsKylm/IiFVCrF3Llzp+394+Pjo7KjDBXtOUZ7fkD05xjt+QHRn2O05wdEf47Tkd94Ryr8+OJNxhhjjAUNFxaMMcYYC5qoKSxUKhX27dsHlUoV6lCmTbTnGO35AdGfY7TnB0R/jtGeHxD9OYY6vxm/eJMxxhhj0StqjlgwxhhjLPS4sGCMMcZY0HBhwRhjjLGg4cKCMcYYY0ETNYXFO++8g+zsbMTExKCgoAAXLlwIdUhT8vrrr0MikQQ8Fi1aJK53Op3YuXMnZs+ejdjYWPz4xz+GyWQKYcQT+89//oMf/vCHSE9Ph0QiwUcffRSwnoiwd+9epKWlQa1Wo6ioCE1NTQHb9Pb2YuvWrYiPj4dWq8UvfvEL9Pf3z2AWY5sov23bto1o0+Li4oBtwjm/AwcO4IEHHkBcXBxSUlKwadMmNDY2BmwzmX7Z3t6OJ554AhqNBikpKXjllVfg9XpnMpUxTSbHdevWjWjHHTt2BGwTrjkePHgQy5cvF2+YZDAY8Nlnn4nrI739gIlzjOT2G82bb74JiUSCXbt2icvCph0pCpSWlpJSqaT33nuPGhoaaPv27aTVaslkMoU6tHu2b98+Wrp0KXV2doqPO3fuiOt37NhBGRkZVFZWRlVVVfTggw/St7/97RBGPLHjx4/Tb3/7Wzp8+DABoCNHjgSsf/PNNykhIYE++ugj+u9//0sbN26kefPmkcPhELcpLi6mFStW0Pnz5+nMmTOUm5tLW7ZsmeFMRjdRfiUlJVRcXBzQpr29vQHbhHN+69evp/fff5/q6+uptraWvv/971NmZib19/eL20zUL71eL+Xn51NRURHV1NTQ8ePHSafT0Z49e0KR0giTyfE73/kObd++PaAdLRaLuD6cc/z444/p008/pWvXrlFjYyO99tprpFAoqL6+nogiv/2IJs4xkttvuAsXLlB2djYtX76cXnjhBXF5uLRjVBQWa9eupZ07d4rPfT4fpaen04EDB0IY1dTs27ePVqxYMeo6s9lMCoWCPvjgA3HZ1atXCQBVVFTMUIT3Z/gHryAIlJqaSn/4wx/EZWazmVQqFf3jH/8gIqIrV64QALp48aK4zWeffUYSiYQ6OjpmLPbJGKuwePLJJ8d8TSTlR0TU1dVFAKi8vJyIJtcvjx8/TlKplIxGo7jNwYMHKT4+nlwu18wmMAnDcyQa/GAauhMfLtJyTExMpL/+9a9R2X5+/hyJoqf9bDYbLViwgE6cOBGQUzi1Y8SfCnG73aiurkZRUZG4TCqVoqioCBUVFSGMbOqampqQnp6OnJwcbN26Fe3t7QCA6upqeDyegFwXLVqEzMzMiM21ra0NRqMxIKeEhAQUFBSIOVVUVECr1WLNmjXiNkVFRZBKpaisrJzxmKfi9OnTSElJQV5eHp577jn09PSI6yItP4vFAgBISkoCMLl+WVFRgWXLlkGv14vbrF+/HlarFQ0NDTMY/eQMz9Hv73//O3Q6HfLz87Fnzx7Y7XZxXaTk6PP5UFpaioGBARgMhqhsv+E5+kVD++3cuRNPPPFEQHsB4fV7OONfQhZs3d3d8Pl8AT8oANDr9fj6669DFNXUFRQU4NChQ8jLy0NnZyfeeOMNPPLII6ivr4fRaIRSqYRWqw14jV6vh9FoDE3A98kf92jt519nNBqRkpISsF4ulyMpKSki8i4uLsZTTz2FefPmoaWlBa+99ho2bNiAiooKyGSyiMpPEATs2rULDz30EPLz8wFgUv3SaDSO2sb+deFktBwB4Gc/+xmysrKQnp6Oy5cv49VXX0VjYyMOHz4MIPxzrKurg8FggNPpRGxsLI4cOYIlS5agtrY2atpvrByByG8/ACgtLcWlS5dw8eLFEevC6fcw4guLaLNhwwZxfvny5SgoKEBWVhb+9a9/Qa1WhzAyNlU//elPxflly5Zh+fLlmD9/Pk6fPo3CwsIQRnbvdu7cifr6epw9ezbUoUybsXJ89tlnxflly5YhLS0NhYWFaGlpwfz582c6zHuWl5eH2tpaWCwWfPjhhygpKUF5eXmowwqqsXJcsmRJxLffzZs38cILL+DEiROIiYkJdTjjivhTITqdDjKZbMSVryaTCampqSGKKni0Wi0WLlyI5uZmpKamwu12w2w2B2wTybn64x6v/VJTU9HV1RWw3uv1ore3NyLzzsnJgU6nQ3NzM4DIye/555/HsWPHcOrUKcydO1dcPpl+mZqaOmob+9eFi7FyHE1BQQEABLRjOOeoVCqRm5uL1atX48CBA1ixYgX+9Kc/RVX7jZXjaCKt/aqrq9HV1YVVq1ZBLpdDLpejvLwcb7/9NuRyOfR6fdi0Y8QXFkqlEqtXr0ZZWZm4TBAElJWVBZxbi1T9/f1oaWlBWloaVq9eDYVCEZBrY2Mj2tvbIzbXefPmITU1NSAnq9WKyspKMSeDwQCz2Yzq6mpxm5MnT0IQBHHnEElu3bqFnp4epKWlAQj//IgIzz//PI4cOYKTJ09i3rx5Aesn0y8NBgPq6uoCCqgTJ04gPj5ePFQdShPlOJra2loACGjHcM5xOEEQ4HK5oqL9xuLPcTSR1n6FhYWoq6tDbW2t+FizZg22bt0qzodNOwbtMtAQKi0tJZVKRYcOHaIrV67Qs88+S1qtNuDK10jx0ksv0enTp6mtrY2++uorKioqIp1OR11dXUQ0OJwoMzOTTp48SVVVVWQwGMhgMIQ46vHZbDaqqamhmpoaAkBvvfUW1dTU0I0bN4hocLipVqulo0eP0uXLl+nJJ58cdbjpt771LaqsrKSzZ8/SggULwmY45nj52Ww2evnll6miooLa2troyy+/pFWrVtGCBQvI6XSK7xHO+T333HOUkJBAp0+fDhiqZ7fbxW0m6pf+YW6PP/441dbW0ueff07JyclhM5Rvohybm5tp//79VFVVRW1tbXT06FHKycmhRx99VHyPcM5x9+7dVF5eTm1tbXT58mXavXs3SSQS+ve//01Ekd9+ROPnGOntN5bhI13CpR2jorAgIvrzn/9MmZmZpFQqae3atXT+/PlQhzQlmzdvprS0NFIqlTRnzhzavHkzNTc3i+sdDgf98pe/pMTERNJoNPSjH/2IOjs7QxjxxE6dOkUARjxKSkqIaHDI6e9//3vS6/WkUqmosLCQGhsbA96jp6eHtmzZQrGxsRQfH0/PPPMM2Wy2EGQz0nj52e12evzxxyk5OZkUCgVlZWXR9u3bRxS94ZzfaLkBoPfff1/cZjL98vr167RhwwZSq9Wk0+nopZdeIo/HM8PZjG6iHNvb2+nRRx+lpKQkUqlUlJubS6+88krAfRCIwjfHn//855SVlUVKpZKSk5OpsLBQLCqIIr/9iMbPMdLbbyzDC4twaUf+2nTGGGOMBU3EX2PBGGOMsfDBhQVjjDHGgoYLC8YYY4wFDRcWjDHGGAsaLiwYY4wxFjRcWDDGGGMsaLiwYIwxxljQcGHBGGOMsaDhwoIxFhTr1q3Drl27Qh0GYyzEuLBgjDHGWNDwLb0ZY/dt27Zt+Nvf/hawrK2tDdnZ2aEJiDEWMlxYMMbum8ViwYYNG5Cfn4/9+/cDAJKTkyGTyUIcGWNspslDHQBjLPIlJCRAqVRCo9EgNTU11OEwxkKIr7FgjDHGWNBwYcEYY4yxoOHCgjEWFEqlEj6fL9RhMMZCjAsLxlhQZGdno7KyEtevX0d3dzcEQQh1SIyxEODCgjEWFC+//DJkMhmWLFmC5ORktLe3hzokxlgI8HBTxhhjjAUNH7FgjDHGWNBwYcEYY4yxoOHCgjHGGGNBw4UFY4wxxoKGCwvGGGOMBQ0XFowxxhgLGi4sGGOMMRY0XFgwxhhjLGi4sGCMMcZY0HBhwRhjjLGg4cKCMcYYY0HDhQVjjDHGguZ/Dp3fRxUCuDkAAAAASUVORK5CYII=", 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", + "image/png": 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", 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", 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", 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" ] @@ -809,10 +797,501 @@ ")" ] }, + { + "cell_type": "markdown", + "id": "697a6ff0-c059-4fe3-ab1f-f1f42c6d9f8d", + "metadata": {}, + "source": [ + "## Phase space plot type things" + ] + }, + { + "cell_type": "markdown", + "id": "9f966f2f-53ae-4077-981c-d7f2678ed7a2", + "metadata": {}, + "source": [ + "### UM1" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "8d1b60ce-2980-4e7f-a7e6-fc01da832857", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
,\n", + "
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(ppo_2o_UM1_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO 2o'),\n", + " ggplot(ppo_bm_UM1_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO bm'),\n", + " ggplot(ppo_mw_UM1_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO mw'),\n", + " ggplot(cr_UM1_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('CR'),\n", + " ggplot(esc_UM1_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('Esc'),\n", + " ggplot(msy_UM1_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('Const Act'),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "df7afd54-31a9-4cab-836c-63af6aff76c1", + "metadata": {}, + "source": [ + "### UM2" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "2fe0d7ca-e522-4df4-a494-858ee4ba1b1b", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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" + }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
,\n", + "
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(ppo_2o_UM2_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO 2o'),\n", + " ggplot(ppo_bm_UM2_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO bm'),\n", + " ggplot(ppo_mw_UM2_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO mw'),\n", + " ggplot(cr_UM2_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('CR'),\n", + " ggplot(esc_UM2_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('Esc'),\n", + " ggplot(msy_UM2_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('Const Act'),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "d9457e7a-f526-4056-8332-e85eaab254bc", + "metadata": {}, + "source": [ + "### UM3" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "20ef0164-499c-469b-a4ee-959a73aff727", + "metadata": { + "collapsed": true, + "jupyter": { + "outputs_hidden": true + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/venv/lib/python3.10/site-packages/IPython/lib/pretty.py:778: FutureWarning: Using repr(plot) to draw and show the plot figure is deprecated and will be removed in a future version. Use plot.show().\n" + ] + }, + { + "data": { + "image/png": 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+ }, + "metadata": { + "image/png": { + "height": 480, + "width": 640 + } + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(
,\n", + "
,\n", + "
,\n", + "
,\n", + "
,\n", + "
)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(\n", + " ggplot(ppo_2o_UM3_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO 2o'),\n", + " ggplot(ppo_bm_UM3_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO bm'),\n", + " ggplot(ppo_mw_UM3_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('PPO mw'),\n", + " ggplot(cr_UM3_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('CR'),\n", + " ggplot(esc_UM3_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('Esc'),\n", + " ggplot(msy_UM3_ep, aes(x='biomass', y='mean_wt', color='rew')) + geom_point() + ggtitle('Const Act'),\n", + ")" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "ceec39e9-c9c9-4f44-92c8-e0ee9490e571", + "id": "582e102a-ad57-49f8-b417-e4293cd38861", "metadata": {}, "outputs": [], "source": [] From 664965fc2dcc87e0382df5ecd6b3d1e4e53e37b3 Mon Sep 17 00:00:00 2001 From: Felipe Montealegre-Mora Date: Thu, 6 Jun 2024 18:54:22 +0000 Subject: [PATCH 64/64] updated tests --- tests/test_asm.py | 13 +++++-------- 1 file changed, 5 insertions(+), 8 deletions(-) diff --git a/tests/test_asm.py b/tests/test_asm.py index 65f6418..d3e10fb 100644 --- a/tests/test_asm.py +++ b/tests/test_asm.py @@ -1,15 +1,12 @@ # Confirm environment is correctly defined: from stable_baselines3.common.env_checker import check_env -from rl4fisheries import Asm, Asm2o, AsmEsc, AsmEnv - -def test_Asm(): - check_env(Asm(), warn=True) - -def test_Asm2o(): - check_env(Asm2o(), warn=True) +from rl4fisheries import AsmEnvEsc, AsmEnv, AsmCRLike def test_AsmEsc(): - check_env(AsmEsc(), warn=True) + check_env(AsmEnvEsc(), warn=True) def test_AsmEnv(): check_env(AsmEnv(), warn=True) + +def test_AsmCRLike(): + check_env(AsmCRLike(), warn=True)